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.github/instructions/test_push_system.instructions.md
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---
applyTo: '**'
---
在任何情况系下, 禁止修改schemas文件夹的内容!
你的目标是基于它,生成一个类型安全的推送系统测试脚本,而不是修改类型系统!
也不要改filtered_datasource。这个是测试用的数据源。
也不要因为报错就绕过schema校验。如果schema校验报错，那就让它报，我自然会去修。
遇到报错或者走不通的路，不要轻易偏离文档，做降级处理，而是要多报错，直到我说可以降级处理再说。
不要在项目根目录乱写测试。测试写到tests里。
不要乱加fallback，所有fallback类的逻辑都需要让我确认过了才行。
.gitignore
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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
env/
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
*.egg-info/
.installed.cfg
*.egg
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
.hypothesis/
.pytest_cache/
# Jupyter Notebook
.ipynb_checkpoints
# pyenv
.python-version
# mypy
.mypy_cache/
.dmypy.json
# VS Code
.vscode/
# Local data
*.sqlite3
*.db
*.log
*.pot
*.mo
*.pkl
# *.jsonl
# OS files
.DS_Store
Thumbs.db
# User-specific
*.swp
*.swo
*~
# Ignore data and filtered data
# filtered_datasource/
remote_datasource/
working_local_datasource/
tmp_remote_datasource/
tmp_jsonl_ds/
# Ignore test outputs
*.out
# ignore examples
v2/
temp_test_output/
zerocoach/
Zerocoach/
.env
# User-created run profiles
run_profiles/*.json
run_profiles/*.yaml
run_profiles/*.yml
# Sync System Runtime Data
_runtime/
test_results/
README.md
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# test_push_system
## 1. 项目简介
本项目用于实现异构系统之间的数据推送：将项目侧管理平台的十余种业务数据，稳定推送到集团侧管理平台。
核心复杂点包括：
- 数据接口复杂且会随业务变化。
- 业务之间依赖关系复杂（跨业务、跨阶段）。
- 同业务数据的双侧对应关系判定复杂（绑定/自动绑定）。
- 同步流程各步骤可能出错，系统需要自动处理，必要时允许人工介入。
- 字段多且杂，且可能由不同更新接口共同影响同一业务信息。
## 2. 项目架构
项目采用：`schema` 严格约束 + 状态机 + 节点模型 + 分层架构 + 注册式 `domain` + 数据源与同步系统解耦。
架构详见：
- `docs/architecture.md`
- `docs/node_state_definition.md`
- `docs/state_machine.md`
## 3. 同步过程简述
整体流程可理解为：
1. Pipeline 读取配置并初始化数据源、策略、状态机运行时。
2. 加载本地与远端节点，进入绑定/依赖检查/自动绑定阶段。
3. 按状态机判定进入 create / update / delete 准备与执行阶段。
4. 执行结果回写节点状态并持久化，失败进入可观测、可重试或可人工处理状态。
状态机的作用：
- 把复杂业务规则收敛为可验证、可追踪的事件迁移。
- 保证不变量（invariant）在运行期可检查。
- 统一错误处理路径，避免“隐式分支”造成不一致。
示意图：
- `docs/state_machine.svg`
流程与时序详见：
- `docs/state_machine.md`
- `docs/sync_flow.md`
## 4. 后续开发（扩展新数据源）
建议路径：
1. 在 `sync_state_machine/domain/` 增加业务 `schema / node / strategy` 并注册到 DomainRegistry。
2. 在 `sync_state_machine/datasource/` 实现新数据源 handler（load/create/update/delete/poll）。
3. 参考 `run_profiles/preset/` 模板，在 `run_profiles/` 自建对应运行配置，先走 JSONL/Mock 集成测试，再接真实接口。
4. 根据业务特性补充状态机上下文字段与测试用例，确保状态迁移可验证。
可参考：
- `sync_state_machine/datasource/README.md`
- `docs/runtime_config_guide.md`
- `tests/README.md`
## 5. 使用方法
### JSONL 同步
- 基线配置（优先）：`python run.py --config_path=run_profiles/preset/jsonl_to_jsonl.default.yaml`
- 使用自定义配置：先从 `run_profiles/preset/jsonl_to_jsonl.default.yaml` 复制到 `run_profiles/jsonl_to_jsonl.local.yaml`，按需修改后运行：`python run.py --config_path=run_profiles/jsonl_to_jsonl.local.yaml`
### API 同步
- 基线配置：`python run.py --config_path=run_profiles/preset/jsonl_to_api.default.yaml`
- 使用自定义配置：先从 `run_profiles/preset/jsonl_to_api.default.yaml` 复制到 `run_profiles/jsonl_to_api.local.yaml`，按需修改后运行：`python run.py --config_path=run_profiles/jsonl_to_api.local.yaml`
### 配置与校验
- 模板配置：`run_profiles/preset/*.default.yaml`
- 建议先跑 default，再在 `run_profiles/*.local.yaml` 做覆盖（该目录 YAML 已默认忽略）
- 状态机配置校验：`python tools/validate_config.py --config sync_state_machine/config/node_state_machine.yaml`
- 状态机图生成：`python tools/render_graph.py --format mermaid --out docs/state_machine.mmd`
### 测试
- 全量：`pytest tests -q`
- 说明：`tests/README.md`
### 其他工具
- UI 调试：`python -m ui.main --host 127.0.0.1 --port 8765`
- 运维与排障：`docs/operations.md`
## 文档导航
- 总体架构：`docs/architecture.md`
- 状态定义：`docs/node_state_definition.md`
- 状态机规则：`docs/state_machine.md`
- 同步流程：`docs/sync_flow.md`
- 运行配置：`docs/runtime_config_guide.md`
- Collection 查询与升级：`docs/collection_query_and_upgrade_plan.md`
- 运维迭代：`docs/operations.md`
历史资料已归档到 `docs/archive/`。
docs/architecture.md
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# 同步系统整体框架
## 1. 分层职责（pipeline + strategy + datasource + domain）
### pipeline（编排层）
- 入口：`pipeline/full_sync_pipeline.py`
- 负责组装并驱动整条流程：加载持久化、执行 bind/create/update、调用 datasource 同步、持久化结果。
- reset 语义：
- 加载阶段仅恢复持久化状态（不做状态重置）；
- 加载后通过 `BaseSyncStrategy.run_reset()` 触发 `E01`：
- `create_zombie=true` -> `S15`（随后删除）；
- `create_zombie=false` -> `S00`（归并为 `UNCHECKED/NONE/PENDING`，并清空 `error`）。
- 若持久化核心枚举非法（`action/status/binding_status`），节点进入加载异常隔离态 `S17`：
- 保留错误信息供人工介入；
- 不参与 `E01` 与后续 bind/create/update/sync 自动流程。
### pipeline 运行语境（人工介入 + 可变配置）
- 运行前可按批次调整策略配置（例如“首轮先拉取、后续只推送”），属于 pipeline 的一次性运行参数。
- 人工介入分两段：
- **运行前**：可手工修复数据、手工绑定、调整策略参数；
- **运行后**：根据节点 `status/error/sync_log` 处理异常（为未来 GUI 介入提供依据）。
- 若上轮异常未人工处理，本轮在 `E01` 先做归并/清理：
- CREATE 僵尸节点自动删除并解除绑定残留；
- 非僵尸节点统一进入 `S00`，再进入本轮 bind/create/update 判定。
### strategy（决策组织层）
- 外部入口：`sync_system/strategy.py`
- 具体实现下沉：`sync_system/strategy_ops/`
- `bind_ops.py`: `run_bind()` + `phase_core_state()/phase_dependency_check()/phase_auto_binding()`
- `create_ops.py`: `run_create()`
- `update_ops.py`: `run_update()`
- `delete_ops.py`: `run_delete()`
- `reset_ops.py`: `get_phase1_reset_defaults()/run_phase2_cleanup()`
- strategy 负责收集上下文并调用状态机事件函数，不直接硬编码状态值。
### datasource（执行与回写层）
- 入口：`datasource/datasource.py`
- 执行 handler（create/update/delete），并结合 `E40` 将执行结果落地到节点状态。
### domain（业务适配层）
- 目录：`domain/*`
- 负责业务字段映射、handler 细节与 schema 约束，不承担状态迁移判定。
## 2. 运行时契约（Runtime Contract）
### 真源
- 状态机配置真源：`config/node_state_machine.yaml`
- 事件执行入口：`engine/events.py`
- 状态落地入口：`engine/state_apply.py`
### 执行规则
1. 业务层构造 `context`。
2. 调用 `StateMachineRuntime.dispatch(current_state, event_id, context)`。
3. 依据 `Decision.to_state` 从 YAML `states[Sxx]` 落地 `binding_status/action/status`。
4. `Decision.emit` 只用于状态外副作用（spawn、绑定、调用 handler 等）。
5. 每次事件落地后，`events._apply_decision` 调用 `runtime.check_invariants()`；违反直接抛错。
## 3. 边界与约束
- `strategy/datasource` 不应绕过状态机直接写最终状态。
- `PRECONDITION_FAILED` 必须满足 `action=UPDATE`（YAML invariant 强约束）。
- 依赖语义由 strategy 计算（如 `dep_satisfied/dep_errors`），状态机只消费语义结果并迁移。
## 4. 相关文档
- 框架与流程：`docs/sync_flow.md`
- 节点状态定义：`docs/node_state_definition.md`
- 状态机形式化说明：`docs/state_machine.md`
docs/archive/README.md
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# 文档归档说明
本目录存放历史文档，不作为当前实现规范。
- `from_root_docs/`：从旧位置迁移的历史文档快照。
- `conflict_log.md` / `goals.md` / `migration_map.md`：重构过程文档。
遇到冲突时，请以 `docs/` 根目录下现行文档和代码真源为准：
- `config/node_state_machine.yaml`
- `engine/events.py`
- `sync_system/strategy_ops/*`
docs/archive/conflict_log.md
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# 文档/实现冲突记录
## 已确认冲突
- 旧文档中存在 E11x 编号残留，与当前 YAML(E08/E09/E10/E12..E20) 不一致。
- `PRECONDITION_FAILED` 在旧实现中可能出现 `action=NONE`，重构目标改为强制 `action=UPDATE`。
## 处理原则
1. 以 `config/node_state_machine.yaml` 为唯一真源。
2. 文档必须由配置和测试结果反向校验。
3. 冲突先记录，再通过测试保护修复。
docs/archive/docs/api_datasource_design.md
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# API DataSource 架构设计
## 架构总览
```
┌─────────────────────────────────────────────────────────────┐
│ Pipeline │
│ (同步流程编排) │
└───────────────────────────┬─────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ ApiDataSource │
│ (数据源协调层) │
│ │
│ - 持有 ApiClient 实例 │
│ - 注册和管理 Handler │
│ - 实现 load_all / execute_batch │
│ - 注入 api_client 到 Handler │
└───────────────────────────┬─────────────────────────────────┘
│
┌───────────────────┼───────────────────┐
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Handler │ │ Handler │ │ Handler │
│ Project │ │ Contract │ │ Material │
│ │ │ │ │ │
│ 业务逻辑层 │ │ 业务逻辑层 │ │ 业务逻辑层 │
└──────┬───────┘ └──────┬───────┘ └──────┬───────┘
│ │ │
└───────────────────┼───────────────────┘
│ 使用 self.api_client
▼
┌──────────────┐
│ ApiClient │
│ (HTTP 通信层) │
│ │
│ - 签名生成 │
│ - HTTP 请求 │
│ - Push Log │
└──────────────┘
```
**调用流程**：
1. Pipeline 创建 ApiDataSource，传入 base_url, uid, secret
2. ApiDataSource 内部创建 ApiClient 实例
3. ApiDataSource 注册各业务 Handler，并注入 api_client
4. Handler 使用 `self.api_client.get/post/put()` 发送请求
5. ApiClient 自动处理签名、push_log 查询、错误处理
**优势**：
- ✅ **职责清晰**：ApiClient（通信）、DataSource（协调）、Handler（业务）
- ✅ **避免循环依赖**：Handler → ApiClient（单向依赖）
- ✅ **易于测试**：ApiClient 可 mock，Handler 独立测试
- ✅ **易于扩展**：新业务只需实现 Handler
## 1. 问题分析：旧方案的复杂性
旧方案 `sync_system/datasource/api` 存在的问题：
1. **过度抽象**：引入了 `ApiDataSource` → `Repository` → `ResponseHandle` → `Cache` 多层封装，每个业务需要独立 Repository 类，Protocol 定义繁琐
2. **状态管理混乱**：缓存策略不清晰，ResponseHandle 封装异步结果但使用困难，缺少统一的 push_log 查询机制
3. **依赖关系困难**：Repository 之间互相传递引用，难以从 collection 获取已有数据
4. **API 路由分散**：每个 Repository 手动实现多个 update 方法，缺少自动路由机制
## 2. 新方案设计原则
- **简单直接**：Handler 直接调用 HTTP API，不过度封装
- **状态透明**：DataSource 统一管理 session、签名、push_log 查询
- **依赖清晰**：通过 collection 获取依赖数据，使用 context 存储额外信息
- **智能路由**：根据数据字段自动选择 API endpoint
## 3. 核心组件职责
### 3.1 ApiClient - HTTP 通信层
**职责**：
- 封装所有 HTTP 通信逻辑
- 管理 httpx.AsyncClient，维护连接池和 session
- 生成请求签名（timestamp, nonce, sign）
- 统一请求入口，自动注入 uid
- 批量 Push Log 查询
**核心方法**：
```python
class ApiClient:
def __init__(self, base_url: str, uid: str, secret: str):
self._client = httpx.AsyncClient()
self._base_url = base_url
self._uid = uid
self._secret = secret
async def request(self, method: str, url: str, **kwargs) -> httpx.Response
"""统一请求入口，自动签名"""
async def get(self, url: str, params: dict = None) -> httpx.Response
"""GET 请求"""
async def post(self, url: str, data: dict) -> httpx.Response
"""POST 请求，data 中已包含 push_id/biz_id（由 Handler 生成）"""
async def put(self, url: str, data: dict) -> httpx.Response
"""PUT 请求，data 中已包含 push_id/biz_id"""
async def delete(self, url: str, data: dict) -> httpx.Response
"""DELETE 请求，data 中已包含 push_id/biz_id"""
async def get_push_logs(self, push_ids: List[str]) -> Dict[str, dict]
"""批量查询 push_log 状态，返回 {push_id: push_log_data}
注意：单个查询也传单元素列表
当前实现：用 for 循环模拟，后续等后端实现批量接口
"""
def _generate_signature(self, params: dict) -> dict
"""生成签名参数（timestamp, nonce, sign）"""
```
### 3.2 ApiDataSource - 数据源协调层
**职责**：
- 持有 ApiClient 实例，提供给 Handler 使用
- 实现 DataSource 接口（load_all, sync_all）
- 协调多个 Handler 的执行顺序（通过 sync_all）
- Handler 内部负责：生成 push_id/biz_id、调用 poll 轮询、提取 created_id
- 统一异常处理和日志记录
**核心属性和方法**：
```python
class ApiDataSource(DataSource):
def __init__(self, base_url: str, uid: str, secret: str):
self.client = ApiClient(base_url, uid, secret)
self._handlers: Dict[str, BaseApiHandler] = {}
def register_handler(self, node_type: str, handler: BaseApiHandler):
"""注册业务 Handler"""
handler.api_client = self.client # 注入 client
self._handlers[node_type] = handler
async def load_all(self, collection: DataCollection, order: List[str]) -> None:
"""调用基类的 load_all，按顺序加载数据"""
async def sync_all(self, collection: DataCollection, order: List[str]) -> None:
"""调用基类的 sync_all，按顺序执行同步"""
```
### 3.3 BaseApiHandler - 业务逻辑基类
**职责**：
- 实现 Handler 接口（load, create, update, delete, poll）
- 使用 self.api_client 发送 HTTP 请求
- 生成 push_id 和 biz_id（业务标识）
- 从 collection 获取依赖节点数据
- 管理节点的 context（存储 project_id, contract_id 等）
- 实现 poll 方法，调用 api_client.get_push_logs 批量查询
- 提取 created_id（因为不同业务的 id 字段名和位置可能不同）
- 返回 TaskResult（SUCCESS/FAILED/IN_PROGRESS）
**核心方法**：
```python
class BaseApiHandler(NodeHandler):
def __init__(self):
self.api_client: ApiClient = None # 由 DataSource 注入
self.collection: DataCollection = None # 由 DataSource 注入
async def load(self, collection: DataCollection) -> List[dict]
async def create(self, node: SyncNode) -> TaskResult
async def update(self, node: SyncNode) -> TaskResult
async def delete(self, node: SyncNode) -> TaskResult
async def poll(self, node: SyncNode, task_id: str) -> TaskResult
def extract_created_id(self, push_log: dict) -> str
"""从 push_log 提取 created_id，子类可重写"""
# 重试逻辑（可选，子类可重写）
async def _execute_with_retry(self, operation, max_retries: int = 3) -> Any
"""通用重试逻辑，子类可自定义重试策略"""
```
**重试策略说明**：
- **重试在 Handler 内部**：create/update/delete 内部可调用 _execute_with_retry
- **返回给 DataSource**：最终只返回 SUCCESS/FAILED/IN_PROGRESS
- **灵活控制**：不同业务可重写 _execute_with_retry 实现自定义策略
- **默认策略**：网络错误/5xx 重试 3 次，4xx 不重试
**未实现 API 的处理**：
- 部分业务可能没有实现 create 或 delete API
- 此时 Handler 应在对应方法中直接返回 FAILED 状态，并在 error 中说明原因
- 示例：`return TaskResult(status=TaskStatus.FAILED, error="Create API not implemented for this business")`
### 3.4 具体业务 Handler
**职责**：
- 实现具体业务的 load 逻辑（调用 self.api_client.get()）
- 创建节点时设置 context
- 重写 API endpoint 选择逻辑（可选）
- 定制 created_id 提取逻辑（可选）
每个业务 Handler 位于 `sync_system_new/domain/{业务}/api_handler.py`
## 4. HTTP 请求状态管理
### 4.0 状态系统概述
**通用状态枚举**（适用于所有 DataSource）：
```python
class TaskStatus(Enum):
"""Handler 返回的任务执行状态"""
SUCCESS = "success" # 同步完成，立即成功
FAILED = "failed" # 同步失败
IN_PROGRESS = "in_progress" # 异步任务进行中
class SyncStatus(Enum):
"""SyncNode 的同步执行状态"""
PENDING = "PENDING"
IN_PROGRESS = "IN_PROGRESS"
SUCCESS = "SUCCESS"
FAILED = "FAILED"
SKIPPED = "SKIPPED"
PRECONDITION_FAILED = "PRECONDITION_FAILED"
```
**状态映射规则**：
- TaskStatus 是 Handler 执行操作后的返回值
- SyncStatus 是 SyncNode 的最终状态，由 DataSource 根据 TaskStatus 更新
- 普通 DataSource（FileDataSource）和 API DataSource 使用相同的状态枚举
- 区别在于：**API DataSource 的网络操作如何转化为 TaskStatus**
**重要说明：Load 阶段 vs 执行阶段的状态**：
- **Load 阶段**（Handler.load()）：从 API 拉取数据创建 SyncNode
- 此时节点状态为 `PENDING`（等待后续 bind/create/update）
- GET 请求失败不影响节点创建，只是该节点不存在于 collection
- **执行阶段**（Handler.create/update/delete）：执行同步操作
- DataSource 在调用前设置 `node.status = IN_PROGRESS`
- Handler 返回 TaskResult，DataSource 据此更新 node.status
- POST/PUT/DELETE 成功后才设置为 SUCCESS
**核心映射逻辑**（在 DataSource 中）：
```python
# 执行前：DataSource 设置状态
node.status = SyncStatus.IN_PROGRESS
# 调用 Handler（Handler 内部可能重试多次）
result = await handler.create(node)
# 执行后：DataSource 根据最终结果更新状态
if result.status == TaskStatus.SUCCESS:
node.status = SyncStatus.SUCCESS
node.data_id = result.data_id
elif result.status == TaskStatus.FAILED:
node.status = SyncStatus.FAILED
node.error = result.error
elif result.status == TaskStatus.IN_PROGRESS:
# 记录 task_id 等待轮询
async_tasks[node.node_id] = result.task_id
```
**重要**：Handler 负责重试，最终只返回确定的结果（SUCCESS/FAILED/IN_PROGRESS）
### 4.1 请求类型与状态流转
**API DataSource 的特殊性**：
- **Load 阶段**：GET 请求拉取数据，创建 PENDING 节点（失败则不创建节点）
- **执行阶段**：POST/PUT/DELETE 先设置 IN_PROGRESS，通过 poll() 轮询变为 SUCCESS/FAILED
#### Load 阶段 - 数据拉取
**目的**：从 API 获取数据，创建 SyncNode 放入 collection
| 阶段 | HTTP 操作 | 成功行为 | 失败行为 | 节点状态 |
|------|----------|---------|---------|---------|
| 1. 调用 load() | GET /api/list | 返回数据列表 | 返回空列表或抛异常 | - |
| 2. 创建节点 | - | 为每条数据创建 SyncNode | 不创建节点 | PENDING |
**代码示例**：
```python
async def load(self, collection: DataCollection) -> List[dict]:
"""加载数据 - GET 阶段不涉及状态转换"""
try:
response = await self.api_client.get("project/list")
if response.status_code == 200:
data_list = response.json().get("list", [])
# 返回数据，由 DataSource 创建 PENDING 节点
return data_list
else:
# 失败：返回空列表，不创建节点
logger.error(f"Load failed: {response.status_code}")
return []
except Exception as e:
logger.error(f"Load exception: {e}")
return [] # 或者抛出异常，由调用方处理
```
#### Mutation 请求（POST/PUT/DELETE） - 执行阶段
**状态变化时机**：
1. **执行前**：DataSource 设置 `node.status = IN_PROGRESS`
2. **Handler 执行**：内部可能重试，最终返回 SUCCESS/FAILED/IN_PROGRESS
3. **轮询完成**：poll() 返回 SUCCESS/FAILED
| 阶段 | Push Log | TaskStatus | SyncStatus | 说明 |
|------|---------|-----------|-----------|------|
| 执行前 | - | - | PENDING → IN_PROGRESS | DataSource 设置 |
| 提交 | pending | IN_PROGRESS | IN_PROGRESS | 任务已提交 |
| 轮询 | processing | IN_PROGRESS | IN_PROGRESS | 后端处理中 |
| 成功 | success | SUCCESS | SUCCESS | 同步完成 |
| 失败 | failed | FAILED | FAILED | 同步失败 |
**示例**：
```python
async def create(self, node: SyncNode) -> TaskResult:
"""Handler 内部可重试，最终返回确定结果"""
response = await self.api_client.post(url, node.data)
if response.status_code == 202:
return TaskResult.in_progress(task_id=response.json()["push_id"])
else:
return TaskResult.failed(error=f"HTTP {response.status_code}")
async def poll(self, node: SyncNode, task_id: str) -> TaskResult:
push_logs = await self.api_client.get_push_logs([task_id])
status = push_logs.get(task_id, {}).get("status")
if status == "success":
return TaskResult.success(data_id=self.extract_created_id(push_logs[task_id]))
elif status == "failed":
return TaskResult.failed(error="Backend processing failed")
else:
return TaskResult.in_progress(task_id=task_id)
```
### 4.2 状态转换完整流程
```
Load 阶段:
Handler.load() → 返回数据列表 → DataSource 创建 PENDING 节点
执行阶段（同步操作）:
DataSource: node.status = IN_PROGRESS
→ Handler.create() → TaskResult.success/failed()
→ DataSource: node.status = SUCCESS/FAILED
执行阶段（异步操作）:
DataSource: node.status = IN_PROGRESS
→ Handler.create() → TaskResult.in_progress(push_id)
→ DataSource 轮询: Handler.poll(push_id)
→ TaskResult.success/failed()
→ DataSource: node.status = SUCCESS/FAILED
```
**关键点**：
- Handler 负责重试，DataSource 只处理最终结果
- 不同业务可在 BaseApiHandler._execute_with_retry 中自定义重试策略
- FileDataSource 和 ApiDataSource 使用相同的状态枚举和转换逻辑
### 4.3 Push Log 状态机
```
pending → processing → success/failed
```
- 轮询间隔：0.5秒
- 超时：30秒
- 成功：提取 created_id
- 失败：获取 error_message
### 4.4 状态总结表
**Load 阶段（数据拉取）**：
| HTTP 操作 | 响应码 | 行为 | 创建节点 | 节点状态 | 说明 |
|---------|-------|-----|---------|---------|------|
| GET /list | 200 | 返回数据列表 | ✅ 是 | PENDING | 等待后续 bind/create/update |
| GET /list | 4xx/5xx | 返回空列表 | ❌ 否 | - | 不创建节点 |
**执行阶段（POST/PUT/DELETE）**：
| HTTP 操作 | 响应码 | Push Log | TaskStatus | SyncStatus | 说明 |
|---------|-------|---------|-----------|-----------|------|
| POST/PUT | 202 | pending | IN_PROGRESS | IN_PROGRESS | 异步开始 |
| - | - | processing | IN_PROGRESS | IN_PROGRESS | 异步处理中 |
| - | - | success | SUCCESS | SUCCESS | 异步成功 |
| - | - | failed | FAILED | FAILED | 异步失败 |
| - | - | timeout | FAILED | FAILED | 轮询超时 |
## 5. Context 机制
### 5.1 Context 的作用
Context 是 SyncNode 的字典字段，用于存储业务数据之外的上下文信息，例如：
- `project_id`: 当前对象所属的项目ID
- `contract_id`: 合同变更所属的合同ID
- `parent_id`: 父对象ID
- 其他 API 调用需要但 schema 中没有的信息
### 5.2 Context 使用流程
**场景：加载合同数据**
1. **Handler.load()** 从 self._collection 获取所有 project
2. 遍历每个 project，调用 `GET contract/list?project_id=xxx`
3. 为每个返回的 contract 数据添加临时标记 `_context = {"project_id": xxx}`
4. **Handler.create_node()** 创建 SyncNode 时，提取 `_context` 并设置到 `node.context`
5. **Handler.update()** 更新时，从 `node.context["project_id"]` 获取 project_id 并添加到请求数据
### 5.3 Context 传递规则
- 父 → 子：从依赖的父节点继承 context
- 横向传递：同级节点不共享 context
- 更新时使用：从 context 提取必要信息添加到请求 payload
## 6. 智能 API 路由
### 6.1 路由策略
根据节点数据的字段，自动选择正确的 API endpoint：
**方案1：字段匹配**
- 检查 node.data 中的字段集合
- 匹配预定义的 endpoint → required_fields 映射表
- 选择第一个匹配的 endpoint
**方案2：Schema 类型**
- 根据 node.schema 的类型
- 查找 schema_type → endpoint 映射表
**默认规则**：
- CREATE: `{node_type}`
- UPDATE: 子类重写 `_select_update_endpoint()`
- DELETE: `{node_type}`
### 6.2 Project 示例
Project 有多个更新接口：
- `project/key_constraints` - 需要字段：key_constraints, key_constraints_remark
- `project/complete_investment` - 需要字段：complete_investment
- `project/dynamic_investment` - 需要字段：dynamic_investment
- `project/plan_construction` - 需要字段：plan_construction_capacity, plan_construction_date
- ... 等
Handler 定义映射表，根据实际数据字段自动选择。
## 7. 依赖数据获取
### 7.1 获取模式
Handler 通过 `collection.filter(node_type="xxx")` 获取依赖数据：
**加载顺序**（按依赖关系）：
1. Project（无依赖）
2. Contract（依赖 Project）
3. Contract Change（依赖 Project + Contract）
### 7.2 数据流
```
Pipeline
→ 按拓扑序加载
→ ProjectHandler.load()
→ GET project/list
→ 创建 ProjectSyncNode
→ ContractHandler.load()
→ collection.filter(node_type="project")
→ 遍历 project，GET contract/list?project_id=xxx
→ 创建 ContractSyncNode，设置 context["project_id"]
→ ContractChangeHandler.load()
→ collection.filter(node_type="contract")
→ 遍历 contract，从 context 获取 project_id
→ GET contract_change/list?project_id=xxx&contract_id=yyy
→ 创建节点，设置 context
```
## 8. 实现计划
### Phase 1: HTTP 通信层
- 实现 **ApiClient** 类
- HTTP Client 封装（httpx.AsyncClient）
- 签名生成（_generate_signature）
- 统一请求方法（get/post/put/delete）
- **批量 Push Log 查询**（get_push_logs，单个也传列表）
- ~~wait_for_push_log~~（不实现，由 DataSource 调用 poll）
### Phase 2: DataSource 协调层
- 实现 **ApiDataSource** 类
- 持有 ApiClient 实例
- Handler 注册和管理
- 实现 DataSource 接口（load_all, execute_batch）
- 注入 api_client 到 Handler
- 实现轮询逻辑（_poll_async_tasks）
### Phase 3: Handler 基类
- 实现 **BaseApiHandler** 类
- load/create/update/delete/poll 方法
- 使用 self.api_client 发送请求
- **extract_created_id**（子类可重写）
- **_execute_with_retry**（可选，子类可重写重试策略）
- Context 管理
### Phase 4: 业务验证
- 实现 **ProjectApiHandler**（无依赖，简单场景）
- 实现 load：GET project/list
- 实现 create：POST project
- 实现 poll：查询 push_log
- 实现 **ContractApiHandler**（依赖 Project，验证 context）
- 实现 load：遍历 project，GET contract/list?project_id=xxx
- 设置 context["project_id"]
- 编写测试验证设计
### Phase 5: 完善功能
- 批量 Push Log 查询优化（等待后端实现批量接口）
- 超时控制（可配置）
- 请求日志和调试
### Phase 6: 推广
- 实现剩余业务 Handler
- 性能优化（并发控制）
- 文档和示例
## 9. 与现有系统集成
**调用关系**：
```
Pipeline
↓
ApiDataSource (持有 ApiClient)
↓
BaseApiHandler (使用 api_client)
↓
ApiClient (发送 HTTP 请求)
```
**职责分离**：
- **ApiClient**: 纯粹的 HTTP 通信，无业务逻辑
- **ApiDataSource**: 协调 Handler，管理执行流程
- **BaseApiHandler**: 业务逻辑，调用 ApiClient 完成网络操作
- **具体 Handler**: 实现特定业务的 load/create/update/delete
**优点**：
- ApiClient 和 Handler 解耦，避免循环依赖
- Handler 通过 self.api_client 访问 HTTP 功能
- DataSource 统一管理 ApiClient 生命周期
- Handler 内部灵活控制重试策略
## 10. 关键优势
1. **简化架构**：去掉 Repository 层，代码量减少 50%
2. **职责清晰**：
- ApiClient：HTTP 通信
- DataSource：协调和轮询
- Handler：业务逻辑和重试
3. **重试灵活**：Handler 内部实现，不同业务可自定义策略
4. **状态清晰**：Load 阶段创建 PENDING 节点，执行阶段明确状态转换
5. **批量优化**：Push Log 批量查询，减少 HTTP 请求
6. **易于扩展**：新业务只需实现 Handler，复用 Client 和 DataSource
7. **易于测试**：ApiClient 可 mock，Handler 独立测试
## 11. 设计改进总结
| 改进点 | 初始设计 | 最终设计 | 理由 |
|-------|---------|---------|------|
| Push Log 查询 | get_push_log(id) | get_push_logs([ids]) | 批量查询 |
| 轮询逻辑 | wait_for_push_log 在 Client | 移除，DataSource 调用 poll | 职责清晰 |
| created_id 提取 | 在 Client | 在 Handler 基类 | 业务差异 |
| 重试逻辑 | 在 DataSource | **在 Handler** | 业务灵活性 |
| Load 状态 | GET 成功 → SUCCESS | GET 成功 → PENDING | Load ≠ 同步完成 |
| 执行状态 | 不明确 | 执行前设置 IN_PROGRESS | 状态清晰 |
7. **易于测试**：ApiClient 可以 mock，Handler 单独测试业务逻辑
## 12. 使用示例
### 12.1 基本使用流程
```python
# 1. 创建 DataSource
datasource = ApiDataSource(
base_url="https://api.example.com",
uid="user123",
secret="secret_key"
)
# 2. 初始化（必须调用）
await datasource.initialize()
# 3. 注册 Handler
datasource.register_handler(ProjectApiHandler())
datasource.register_handler(ContractApiHandler())
# 4. 创建 Collection
collection = DataCollection()
# 5. 加载数据（自动处理异常，不会抛出）
await datasource.load_all(collection, order=["project", "contract"])
# 6. 执行同步（自动处理异常，不会抛出）
await datasource.sync_all(collection, order=["project", "contract"])
# 7. 关闭连接（必须调用）
await datasource.close()
```
### 12.2 异常处理说明
**设计原则**：
- ✅ **load_all 和 sync_all 不会抛出异常**
- ✅ **Handler 的 create/update/delete 捕获所有 HTTP 异常**
- ✅ **所有错误转换为状态（SyncStatus.FAILED）和错误信息（node.error）**
**为什么不需要 try-finally？**
```python
# ❌ 不需要这样做
try:
await datasource.load_all(collection, order=["project"])
finally:
await datasource.close()
# ✅ 直接调用即可
await datasource.initialize()
await datasource.load_all(collection, order=["project"]) # 内部已处理异常
await datasource.sync_all(collection, order=["project"]) # 内部已处理异常
await datasource.close()
```
**异常处理机制**：
1. **load_all 异常处理**：
```python
# 加载某个类型失败，记录错误但继续处理其他类型
for node_type in order:
try:
raw_items = await handler.load(collection)
# ... 创建节点
except Exception as e:
print(f"Error loading {node_type}: {e}")
# 继续处理下一个类型
```
2. **sync_all 异常处理**：
```python
# Handler 返回的异常已被捕获转为 TaskResult
for node in nodes:
try:
result = await handler.create(node) # Handler 内部捕获异常
# 根据 result.status 更新节点状态
except Exception as e:
# DataSource 的最后保护
node.status = SyncStatus.FAILED
node.error = str(e)
```
3. **Handler 异常处理**：
```python
async def create(self, node: SyncNode) -> TaskResult:
try:
# 生成参数
push_id = self._generate_push_id()
data = {..., "push_id": push_id, "biz_id": self._generate_biz_id(node)}
# 调用 API
response = await self.api_client.post("/api/v2/project", data)
# 返回成功
return TaskResult(status=TaskStatus.SUCCESS, data_id=response['data']['id'])
except httpx.HTTPStatusError as e:
# HTTP 错误（4xx, 5xx）
return TaskResult(status=TaskStatus.FAILED, error=f"HTTP {e.response.status_code}: {e}")
except httpx.NetworkError as e:
# 网络错误
return TaskResult(status=TaskStatus.FAILED, error=f"Network error: {e}")
except Exception as e:
# 其他异常
return TaskResult(status=TaskStatus.FAILED, error=f"Unexpected error: {e}")
```
### 12.3 Pipeline 集成示例
```python
async def sync_pipeline(datasource: ApiDataSource):
"""同步流程编排"""
# 初始化
await datasource.initialize()
# 创建 Collection
collection = DataCollection()
# 执行同步流程（所有错误都被内部处理）
await datasource.load_all(collection, order=["project", "contract", "material"])
await datasource.sync_all(collection, order=["project", "contract", "material"])
# 检查结果
failed_nodes = collection.filter(status=SyncStatus.FAILED)
if failed_nodes:
print(f"Failed nodes: {len(failed_nodes)}")
for node in failed_nodes:
print(f" - {node.node_type}:{node.node_id}: {node.error}")
# 清理
await datasource.close()
```
**关键点**：
- ✅ 不需要 try-except 包裹 load_all/sync_all
- ✅ 通过检查节点状态判断成功/失败
- ✅ 错误信息保存在 node.error 中
- ✅ Pipeline 专注于流程编排，不处理异常细节
docs/archive/docs/datasource_handler_architecture_v2.md
+518
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@@ -0,0 +1,518 @@
# DataSource + Handler 架构设计 V2
## 核心原则
### **职责分离**
```text
Strategy (业务逻辑层)
↓ 设置 action, 完成 ID 映射
DataSource (状态管理 + 编排层)
↓ 调用 Handler, 管理状态流转
Handler (纯执行层)
↓ 调用后端 API, 返回结果
Backend API
```
### **关键设计决策**
1. **ID 映射在 Strategy 完成** ✅
- `Strategy.create()` / `Strategy.update()` 时，已将依赖字段的本地 ID 替换为远程 ID
- DataSource 拿到的 `node.data` 已经是映射好的数据
- Handler 直接使用 `node.data`，不需要关心 ID 映射
2. **状态管理在 DataSource** ✅
- 所有 `node.status` 的转换由 DataSource 负责
- Handler 只返回 `TaskResult`（成功/失败/进行中）
- DataSource 根据 `TaskResult` 更新 `node.status`
3. **Handler 只负责执行** ✅
- 调用后端 API（load/create/update/delete）
- 返回执行结果（TaskResult）
- 提供异步任务轮询（poll_tasks）
- 提供数据质量检查（validate）
---
## Handler 接口设计
### **核心方法**
```python
class NodeHandler(Protocol[T]):
# ===== 数据加载 =====
async def load(self, collection: Optional[DataCollection] = None) -> List[Dict[str, Any]]:
"""
从后端加载全部数据
Args:
collection: Collection 上下文（可选，用于依赖查询）
Returns:
原始数据列表
示例：
# Contract Handler（依赖 Project）
async def load(self, collection=None):
# 从 collection 获取 project 列表
if collection:
projects = collection.filter(node_type="project")
project_ids = [p.data_id for p in projects if p.data_id]
else:
project_ids = []
# 只加载这些项目的合同
response = await self.api.get_contracts(project_ids=project_ids)
return response["data"]
"""
# ===== 数据操作 =====
async def create(self, node: SyncNode[T]) -> TaskResult:
"""
创建节点
注意：node.data 已经过 ID 映射，直接使用即可
Returns:
TaskResult:
- SUCCESS: 同步完成，返回 data_id
- IN_PROGRESS: 异步任务，返回 task_id
- FAILED: 失败，返回 error
示例：
# 同步接口
async def create(self, node):
try:
response = await self.api.create_contract(node.data)
return TaskResult.success(data_id=response["id"])
except Exception as e:
return TaskResult.failed(error=str(e))
# 异步接口
async def create(self, node):
try:
response = await self.api.submit_contract_async(node.data)
return TaskResult.in_progress(task_id=response["task_id"])
except Exception as e:
return TaskResult.failed(error=str(e))
"""
async def update(self, node: SyncNode[T]) -> TaskResult:
"""更新节点（同 create）"""
async def delete(self, node: SyncNode[T]) -> TaskResult:
"""删除节点（同 create）"""
# ===== 异步任务轮询 =====
async def poll_tasks(self, task_ids: List[str]) -> Dict[str, TaskResult]:
"""
批量轮询异步任务状态
Args:
task_ids: 任务 ID 列表
Returns:
{task_id: TaskResult} 字典
示例：
async def poll_tasks(self, task_ids):
response = await self.api.batch_query_tasks(task_ids)
results = {}
for task in response["tasks"]:
if task["status"] == "completed":
results[task["id"]] = TaskResult.success(
data_id=task["result"]["contract_id"]
)
elif task["status"] == "failed":
results[task["id"]] = TaskResult.failed(
error=task["error"]
)
else: # running
results[task["id"]] = TaskResult.in_progress(
task_id=task["id"]
)
return results
"""
# ===== 数据质量检查 =====
async def validate(self, data: Dict[str, Any]) -> ValidationResult:
"""
数据质量检查
Args:
data: 原始数据
Returns:
ValidationResult（是否有效 + 错误列表）
示例：
async def validate(self, data):
errors = []
if not data.get("code"):
errors.append("合同编码为空")
if not data.get("project_id"):
errors.append("项目 ID 为空")
return ValidationResult(
is_valid=len(errors) == 0,
errors=errors
)
"""
# ===== 辅助方法 =====
def extract_id(self, data: Dict[str, Any]) -> str:
"""从原始数据提取 ID"""
def create_node(self, data: Dict[str, Any]) -> SyncNode[T]:
"""从原始数据创建 SyncNode"""
```
### **TaskResult 设计**
```python
class TaskStatus(Enum):
SUCCESS = "success" # 同步完成
FAILED = "failed" # 失败
IN_PROGRESS = "in_progress" # 异步任务进行中
class TaskResult:
def __init__(
self,
status: TaskStatus,
data_id: Optional[str] = None, # 成功时返回的 ID
task_id: Optional[str] = None, # 异步任务 ID
error: Optional[str] = None, # 失败原因
metadata: Optional[Dict] = None # 其他元数据
):
...
@classmethod
def success(cls, data_id: Optional[str] = None) -> TaskResult:
"""创建成功结果"""
@classmethod
def failed(cls, error: str) -> TaskResult:
"""创建失败结果"""
@classmethod
def in_progress(cls, task_id: str) -> TaskResult:
"""创建进行中结果"""
```
---
## DataSource 接口设计
### **接口方法**
```python
class BaseDataSource(ABC):
# ===== Handler 管理 =====
def register_handler(self, handler: NodeHandler) -> None:
"""注册 Handler"""
def get_handler(self, node_type: str) -> NodeHandler:
"""获取 Handler"""
# ===== 数据加载 =====
async def load_all(
self,
order: List[str]
) -> None:
"""
按依赖顺序加载所有数据
注意：调用前需先 set_collection()
Args:
order: 节点类型顺序（如 ["project", "contract", "construction"]）
工作流程：
1. 按顺序遍历每个节点类型
2. 调用 Handler.load()
3. Handler 可以从 self._collection 查询依赖节点
4. 使用 Handler.create_node() 创建 SyncNode
5. 添加到 Collection
"""
# ===== 同步执行 =====
async def sync_all(
self,
order: List[str]
) -> None:
"""
按依赖顺序执行同步
流程：
1. 按顺序遍历每个节点类型
2. 筛选需要同步的节点（status=PENDING, action!=NONE）
3. 调用 Handler 的 create/update/delete
4. 根据 TaskResult 更新节点状态
5. 处理异步任务轮询
"""
# ===== 统计信息 =====
def get_sync_summary(self, collection: DataCollection) -> Dict[str, Any]:
"""获取同步统计信息"""
```
### **状态流转逻辑**
```python
async def _sync_nodes(self, handler, nodes):
async_tasks = {} # {node_id: task_id}
for node in nodes:
# 1. 跳过不需要处理的节点
if node.action == SyncAction.NONE:
continue
# 2. 跳过异常状态节点
if node.binding_status in [DEPENDENCY_ERROR, ABNORMAL, WARNING]:
node.status = SyncStatus.SKIPPED
continue
# 3. 只处理 PENDING 节点
if node.status != SyncStatus.PENDING:
continue
# 4. 执行操作
try:
node.status = SyncStatus.IN_PROGRESS
if node.action == SyncAction.CREATE:
result = await handler.create(node)
elif node.action == SyncAction.UPDATE:
result = await handler.update(node)
elif node.action == SyncAction.DELETE:
result = await handler.delete(node)
# 5. 处理结果
if result.status == TaskStatus.SUCCESS:
node.status = SyncStatus.SUCCESS
if result.data_id:
node.data_id = result.data_id # 回填 ID
elif result.status == TaskStatus.FAILED:
node.status = SyncStatus.FAILED
node.error = result.error
elif result.status == TaskStatus.IN_PROGRESS:
async_tasks[node.node_id] = result.task_id
except Exception as e:
node.status = SyncStatus.FAILED
node.error = str(e)
# 6. 轮询异步任务
if async_tasks:
await self._poll_async_tasks(handler, nodes, async_tasks)
```
### **异步任务轮询**
```python
async def _poll_async_tasks(self, handler, nodes, async_tasks):
node_map = {n.node_id: n for n in nodes}
max_retries = poll_max_retries # 默认轮询 1 次，可配置
retry_count = 0
while async_tasks and retry_count < max_retries:
# 批量查询
task_ids = list(async_tasks.values())
results = await handler.poll_tasks(task_ids)
# 处理结果
for node_id, task_id in list(async_tasks.items()):
if task_id not in results:
continue
result = results[task_id]
node = node_map[node_id]
if result.status == TaskStatus.SUCCESS:
node.status = SyncStatus.SUCCESS
if result.data_id:
node.data_id = result.data_id
async_tasks.pop(node_id)
elif result.status == TaskStatus.FAILED:
node.status = SyncStatus.FAILED
node.error = result.error
async_tasks.pop(node_id)
# 还有未完成任务，等待后重试
if async_tasks:
await asyncio.sleep(2)
retry_count += 1
# 超时未完成的任务标记为失败
for node_id in async_tasks:
node = node_map[node_id]
node.status = SyncStatus.FAILED
node.error = "Async task timeout"
```
---
## 完整流程示例
### **Pipeline 编排**
```python
# Stage 0: 初始化
collection = DataCollection()
datasource = ApiDataSource(api_client)
# 注册 Handler
datasource.register_handler(ProjectNodeHandler(api_client))
datasource.register_handler(ContractNodeHandler(api_client))
# Stage 1: 加载数据
datasource.set_collection(collection)
await datasource.load_all(
order=["project", "contract"] # 依赖顺序
)
# Stage 2: Strategy 执行
for strategy in [project_strategy, contract_strategy]:
await strategy.bind() # 设置 binding_status
await strategy.create() # 设置 action=CREATE + ID 映射
await strategy.update() # 设置 action=UPDATE + ID 映射
await strategy.pre_sync_check()
# Stage 3: 物理同步
await datasource.sync_all(
order=["project", "contract"]
)
# Stage 4: 检查结果
summary = datasource.get_sync_summary(collection)
print(f"Success: {summary['success']}, Failed: {summary['failed']}")
```
### **Contract Handler 实现**
```python
class ContractNodeHandler(BaseNodeHandler[ContractResponse]):
def __init__(self, api_client):
super().__init__(
node_type="contract",
node_class=ContractSyncNode,
schema=ContractResponse
)
self.api = api_client
async def load(self):
"""加载合同（依赖 Project）"""
if self._collection:
projects = self._collection.filter(node_type="project")
project_ids = [p.data_id for p in projects if p.data_id]
else:
project_ids = []
response = await self.api.get_contracts(project_ids=project_ids)
return response["data"]
async def create(self, node):
"""创建合同（异步接口）"""
try:
# node.data 已经过 ID 映射，直接使用
response = await self.api.create_contract_async(node.data)
if response.get("async"):
return TaskResult.in_progress(task_id=response["task_id"])
else:
return TaskResult.success(data_id=response["id"])
except Exception as e:
return TaskResult.failed(error=str(e))
async def update(self, node):
"""更新合同（同步接口）"""
try:
response = await self.api.update_contract(node.data_id, node.data)
return TaskResult.success()
except Exception as e:
return TaskResult.failed(error=str(e))
async def poll_tasks(self, task_ids):
"""轮询异步任务"""
response = await self.api.batch_query_tasks(task_ids)
results = {}
for task in response["tasks"]:
if task["status"] == "completed":
results[task["id"]] = TaskResult.success(
data_id=task["result"]["contract_id"]
)
elif task["status"] == "failed":
results[task["id"]] = TaskResult.failed(error=task["error"])
else:
results[task["id"]] = TaskResult.in_progress(task_id=task["id"])
return results
async def validate(self, data):
"""数据质量检查"""
errors = []
if not data.get("code"):
errors.append("合同编码为空")
if not data.get("project_id"):
errors.append("项目 ID 为空")
return ValidationResult(is_valid=len(errors) == 0, errors=errors)
def extract_id(self, data):
return data["id"]
```
---
## 核心优势
### **1. 职责清晰**
- **Strategy**: 业务逻辑 + ID 映射
- **DataSource**: 状态管理 + 编排
- **Handler**: 纯执行（后端 API 调用）
### **2. ID 映射前置**
- ID 映射在 Strategy 完成，DataSource 和 Handler 无需关心
- `node.data` 已经是映射好的数据，直接使用
### **3. 状态统一管理**
- 所有状态流转由 DataSource 负责
- Handler 只返回结果，不改变节点状态
### **4. 异步任务支持**
- Handler 返回 `TaskResult.in_progress(task_id)`
- DataSource 自动轮询直到完成
### **5. 数据质量保障**
- Handler 提供 `validate()` 方法
- DataSource 在加载时检查数据质量
### **6. 易于测试**
- Handler 可以 Mock（返回假 TaskResult）
- DataSource 可以单独测试状态流转逻辑
- Strategy 可以单独测试 ID 映射逻辑
---
## 与现有架构的兼容性
完全符合 [架构分层设计.md](./架构分层设计.md) 的四层模型：
1. **Common 层**: SyncNode, DataCollection, BindingManager
2. **Sync System 层**: SyncStrategy（负责 bind/create/update + ID 映射）
3. **DataSource 层**: BaseDataSource + NodeHandler（状态管理 + 执行）
4. **Pipeline 层**: 流程编排 + 依赖顺序
符合 [状态定义规范.md](./状态定义规范.md) 的状态流转逻辑。
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# node_id / data_id / 持久化与生命周期说明
本文档说明同步系统中 `node_id` 与 `data_id` 的职责、生成时机、持久化行为，以及同步流程中“创建/绑定/回填”的完整生命周期。目标是避免“重复生成 node_id 导致绑定失效”的问题，并明确各层职责。
---
## 1. 基础概念
- **data_id**
- 业务主键（来自数据源/远端系统的资源 ID）。
- 在加载阶段通常已存在；在 CREATE 场景下初始为空，成功后由 DataSource 回填。
- **node_id**
- 同步系统内部的**稳定标识符**（绑定与持久化的主键）。
- 用于绑定表、持久化节点、依赖追踪等。
- 设计目标：**跨同步周期稳定**，不能随每次加载而变化。
---
## 2. 核心结论（必须遵守）
1. **node_id 一旦建立，不应再被数据源“重新生成”。**
- 绑定关系与持久化状态依赖 `node_id`；若每次加载都重新生成，会导致历史绑定失效。
2. **加载阶段应先恢复 Collection（持久化节点），再加载 DataSource 数据。**
- 数据源加载出的 `data_id` 应优先匹配已持久化的节点；匹配到则复用旧 `node_id`。
3. **CREATE 场景允许临时/新建 node_id**，但必须通过后续回填与绑定更新保持一致性。
---
## 3. 正确的初始化/加载顺序
### 推荐流程（Pipeline 前半段）
1. **持久化恢复阶段**
- 必须同时恢复 `node_id` 与 `data_id`（以及状态字段），否则无法建立稳定的映射关系。
- Collection 可能为空，这属于合法情况。
2. **数据源加载阶段（DataSource.load_all）**
- 对每一条业务数据（含 `data_id`）：
- **若 Collection 内已存在该 `data_id` 对应节点**：将数据写回原节点（保留旧 `node_id`）。
- **若不存在**：由 **Collection** 生成新的 `node_id`，并创建新节点。
> 这样可避免“第二次同步时重建节点，导致旧绑定丢失”。
---
## 4. node_id 的来源与稳定性
### A. 持久化恢复阶段
- **恢复时必须包含 `node_id` 与 `data_id`**：
- 两者成对恢复，才能保证后续 load 阶段按 `data_id` 命中旧节点。
### B. 数据源加载阶段
- **优先复用持久化 node_id**：
- 通过 `data_id` 在 Collection 中查找并更新已有节点。
- **仅在未知 data_id 时新建 node_id**：
- 新节点 `node_id` 必须由 **Collection** 生成，而非 DataSource/Handler 直接拼接。
### C. 创建阶段（Strategy.create）
- 新建“目标端”节点时，**必须有 node_id**：
- 用于写入 Collection、记录状态、建立临时绑定。
- 成功后回填 `data_id`，**node_id 不变**。
---
## 5. data_id 的来源与回填
本节按阶段拆分说明 `data_id` 的来源与写回。
### A. 持久化恢复阶段
- `data_id` 从持久化数据中恢复（与 `node_id` 一起恢复）。
### B. 数据源加载阶段
- `data_id` 来自数据源原始数据（`id` / `_id`）。
- 若命中已有节点，则仅更新数据与状态，不改变 `node_id`。
### C. 同步创建与轮询阶段
- CREATE 提交后，DataSource 从响应/轮询结果提取 `biz_id`。
- 成功时回填到 `node.data_id`，并回写 `node.data` 的主键字段（仅 `id` / `_id`）。
### D. 持久化阶段
- 将更新后的 `node_id` / `data_id` / 状态字段持久化，供下次同步恢复使用。
---
## 6. 绑定与 node_id 的关系
- 绑定表的 key 为 `node_id`，绑定记录是 `local_node_id <-> remote_node_id`。
- 因此：**node_id 必须稳定**，才能保证绑定长期有效。
- 绑定可在创建前建立“临时关系”，但成功后不应更换 node_id。
---
## 7. 同步周期中的典型场景
### 场景 1：第一次同步（无持久化）
- Collection 为空 → DataSource load 新节点 → 生成新 `node_id`。
- Strategy bind / create / update 执行。
- 持久化后，下次同步可复用 `node_id`。
### 场景 2：第二次同步（已有持久化）
- 先恢复 Collection（已有 `node_id`）。
- DataSource load 时按 `data_id` 匹配旧节点并更新数据。
- 绑定关系仍有效。
### 场景 3：创建新数据（CREATE）
- Strategy 产生目标端节点（`node_id` 新生成）。
- DataSource 执行创建，回填 `data_id`。
- 绑定记录更新为真实 `data_id`（但 node_id 保持不变）。
---
## 8. 关键规则总结
- **node_id 是“同步系统内的稳定 ID”，必须持久化与复用。**
- **data_id 是“业务系统的资源 ID”，由数据源加载或创建后回填。**
- **加载顺序：先恢复持久化节点 → 再 load 数据源。**
- **遇到已存在 data_id：复用 node_id；否则创建新节点。**
- **CREATE 成功后只更新 data_id，不更换 node_id。**
---
## 9. 相关文件参考
- 绑定与状态定义：见 [docs/状态定义规范.md](状态定义规范.md)
- 编排流程：见 [docs/编排流程规范.md](编排流程规范.md)
- BaseDataSource：见 [sync_system_new/datasource/datasource.py](../sync_system_new/datasource/datasource.py)
- BaseApiHandler：见 [sync_system_new/datasource/api/handler.py](../sync_system_new/datasource/api/handler.py)
---
## 10. 明确规则与建议实现
- **DataSource.load_all 必须先按 `data_id` 命中已有节点并更新**，未命中时再由 Collection 创建新节点并分配新的 `node_id`。
- **推荐实现方式**：先 `find_by_data_id`，命中走通用更新；未命中再创建新节点（无需强制 `upsert_by_data_id` 接口）。
- **创建流程中的临时绑定/成功更新规则**：
- CREATE 节点创建时：`binding_status = NORMAL`，`action = CREATE`，`status = PENDING`，`data_id = ""`。
- 执行提交前置为 `status = IN_PROGRESS`（异步）或保持 `PENDING`（同步接口待执行）。
- 成功回填后：`status = SUCCESS`，`data_id` 回填并写回主键字段，绑定记录保持 `node_id` 不变。
- 过程中出现错误：`status = FAILED`，`error` 记录原因。
- **异常节点持久化/恢复策略**：
- 持久化时保留异常节点与错误信息。
- 恢复时是否保留/清理异常节点应通过策略配置控制（默认建议保留以便人工修复）。
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# Skip Sync 行为修复说明
## 问题分析
### 1. **绑定失败的根本原因**
**问题现象**：
- Company: 1/39 绑定
- Supplier: 0/65202 绑定（完全没绑定！）
- 导致依赖supplier的业务（contract, material等）也绑不上
- 远程异常创建了74条数据
**根本原因有两个**：
#### 原因1：skip_sync 跳过了整个策略（包括 bind）
```python
# 旧逻辑：skip_sync=True 时跳过整个策略
if getattr(strategy, 'skip_sync', False):
continue # ← 跳过了 bind/create/update 全部！
```
修复后：
```python
# 新逻辑：bind() 始终执行，skip_sync 只跳过 create/update/sync
await strategy.bind() # ← 始终执行
if getattr(strategy, 'skip_sync', False):
continue # ← 只跳过 create/update
```
#### 原因2：自动绑定ID解析失败没有设置DEPENDENCY_ERROR
```python
# 旧逻辑：ID解析失败只是跳过
if not resolved_key_dict:
continue # ← 节点保持 MISSING，会被误创建！
```
修复后：
```python
# 新逻辑：ID解析失败设置DEPENDENCY_ERROR
if not resolved_key_dict:
node.set_binding_status(BindingStatus.DEPENDENCY_ERROR, "业务键中的ID字段解析失败")
continue # ← 节点为 DEPENDENCY_ERROR，不会被创建
```
### 2. **状态与创建的关系**
| 状态 | 来源 | 允许创建 | 说明 |
|------|------|:---:|------|
| **UNCHECKED** | 加载后初始状态 | ❌ | bind() 未执行 |
| **NORMAL** | 有绑定记录 | ❌ | 已绑定 |
| **MISSING** | 无绑定记录 | ✅ | 真正的孤儿 |
| **WARNING** | 业务键字段缺失 | ❌ | 数据不完整 |
| **DEPENDENCY_ERROR** | 依赖不满足 | ❌ | 父节点未就绪 |
| **ABNORMAL** | 数据损坏 | ❌ | 需人工处理 |
**关键原则**：
- `create()` 只查找 `binding_status == MISSING` 的节点
- 如果 bind() 没执行，状态是 UNCHECKED → 不会创建
- 如果 bind() 执行了但依赖不满足 → DEPENDENCY_ERROR → 不会创建
### 3. **Supplier 默认行为变更**
**旧行为**：
- `default_skip_sync = True` → 默认跳过同步
- 需要在调用层设置 `force_sync_types=["supplier"]`
**新行为**：
- `default_skip_sync` 已移除（使用基类默认值 False）
- Supplier 默认会执行完整同步（bind/create/update）
- 如需跳过，在调用层配置 `skip_sync_types=["supplier"]`
## 解决方案
### 修改 1：分离 bind() 和 skip_sync
**新逻辑**：
```python
# sync_system_new/pipeline/full_sync_pipeline.py
# Step 1a: 绑定（始终执行）
await strategy.bind()
# Step 1b: 检查是否跳过 create/update/sync
if getattr(strategy, 'skip_sync', False):
print(f"⏭️ Skipping create/update/sync for {node_type}")
# 继续执行 pre_sync_check，但跳过 create/update/sync
if hasattr(strategy, "pre_sync_check"):
ok = await strategy.pre_sync_check()
...
continue
# Step 1c: 正常的 create/update
await strategy.create()
await strategy.update()
```
**效果**：
- ✅ **bind() 始终执行**（建立绑定关系）
- ✅ **skip_sync=True 只跳过 create/update/sync**（避免昂贵操作）
- ✅ **pre_sync_check 仍然执行**（依赖检查）
### 修改 2：添加 force_sync_types 配置
**配置示例**：
```python
# tests/run_full_sync_pipeline_simple.py
CONFIG = {
# 第一次运行：从 API 加载 + 绑定 + 创建
"force_sync_types": ["supplier"],
"wipe_persistence_on_start": True,
# 第二次运行：从持久化加载 + 跳过同步
# "handler_configs": {"supplier": {"load_mode": "persisted_only"}},
# "skip_sync_types": ["supplier"],
# "wipe_persistence_on_start": False,
}
```
**优先级**：
1. **force_sync_types**（最高）→ `skip_sync = False`
2. **skip_sync_types** → `skip_sync = True`
3. **策略默认值** (default_skip_sync)
### 修改 3：添加测试日志保存
**功能**：
```python
# tests/run_full_sync_pipeline_simple.py
log_path = log_dir / f"simple_pipeline_{datetime.now().strftime('%Y%m%d_%H%M%S')}.log"
sys.stdout = Tee(original_stdout, log_file)
```
**输出位置**：
```
test_results/simple_pipeline_20260204_162345.log
```
## 使用指南
### Phase 1: 首次运行（API + 绑定 + 创建）
```python
CONFIG = {
# 不需要特殊配置，所有类型默认都会同步
"wipe_persistence_on_start": True, # 清空数据库
}
```
**预期结果**：
- Supplier: 从API加载60000条 → 自动绑定(credit_code) → 拉取到本地 → 持久化
- Company: 自动绑定 → 拉取
- Contract等: 通过supplier_id/project_id绑定 → 创建
### Phase 2: 后续运行（持久化 + 跳过同步）
```python
CONFIG = {
"handler_configs": {
"supplier": {"load_mode": "persisted_only"} # 从DB加载
},
"skip_sync_types": ["supplier"], # 跳过create/update（但仍执行bind）
"wipe_persistence_on_start": False, # 保留数据
}
```
**预期结果**：
- Supplier: 从DB加载（带绑定关系） → 执行bind（验证状态） → 跳过create/update
- 其他业务: 正常同步
## 测试验证
### 1. 删除远程异常创建的数据
```bash
# TODO: 通过API删除远程的74条测试数据
```
### 2. 清空数据库重新测试
```bash
rm _runtime/test_simple.db
python scripts/legacy/run_full_sync_pipeline_simple.py
```
### 3. 验证绑定统计
**期望输出**：
```
Local Summary:
company: 39/39 bindings ← 全部绑定
supplier: 60000+/65202 bindings ← 大量绑定
contract: XX/34 bindings ← 通过supplier_id绑定
Remote Summary:
company: 39/39 bindings
supplier: 60000+/60000 bindings
contract: XX/155 bindings (XX creates)
```
### 4. 检查日志文件
```bash
cat test_results/simple_pipeline_*.log | grep "Skipping"
```
**期望**：
- 第一次运行：**不应该有** "Skipping" 输出
- 第二次运行：`⏭️ Skipping create/update/sync for supplier`
## 风险评估
### 影响范围
- ✅ 修复了 supplier/company 绑定失败问题
- ✅ 防止未绑定节点异常创建
- ✅ 保持了两阶段工作流（首次API+绑定，后续持久化）
- ⚠️ 可能影响其他使用 skip_sync 的场景（需要测试）
### 向后兼容性
- ✅ 原始脚本 (run_full_sync_pipeline_api.py) 不受影响
- ✅ 没有 skip_sync 属性的策略行为不变
- ✅ 新增的 force_sync_types 是可选参数
## 待办事项
- [ ] 测试所有业务类型的绑定统计
- [ ] 验证依赖关系链（project → contract → material → detail）
- [ ] 检查 construction_task 为什么没绑定（0/32）
- [ ] 测试第二次运行的持久化加载逻辑
- [ ] 更新文档说明 skip_sync 的新语义
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# 业务流程与依赖关系
本文档描述推送系统涉及的业务实体及其依赖关系，用于指导同步顺序编排。
---
## 业务实体分类
### 1. 基础数据（仅拉取）
- **用户（User）**：拉取集团管理员、区域公司管理员及特定用户信息，用于跨平台穿透。其他用户需手动创建。
- **公司（Company）**：仅拉取，不推送。
- **供应商（Supplier）**：仅拉取，不推送。
### 2. 项目及扩展数据
**项目（Project）**
- **绑定方式**：必须手动绑定（根节点）
- **同步操作**：允许更新和拉取
- **依赖项**：公司、附件（Attachment）
**项目扩展业务**
- 通过 `(project_id, key)` 或 `(project_id, code)` 自动绑定
- 允许创建、更新、拉取
- 依赖项目
### 3. 合同及子业务
**合同（Contract）**
- **绑定方式**：通过业务键自动绑定（需与 ECP 平台数据交叉检验）
- **同步操作**：允许拉取、创建、更新、删除
- **依赖项**：项目
**合同子业务**（施工任务、物资、结算、力能）
- **绑定方式**：通过 `(contract_id, code)` 自动绑定
- **同步操作**：允许拉取、创建、更新、删除
- **特殊规则**：首次绑定后，项目侧不会同步创建远程已有的数据
- **依赖项**：合同
**合同子业务明细**（施工明细、物资明细、结算明细、力能明细）
- **绑定方式**：通过 `(parent_id, date)` 自动绑定
- **同步操作**：允许拉取、创建、更新、删除
- **特殊规则**：首次绑定后，项目侧不会同步创建远程已有的数据
- **依赖项**：对应的合同子业务
---
## 依赖关系图
```
Company (基础)
↓
Project (手动绑定)
↓
Contract (自动绑定)
↓
Contract Sub-Business (施工/物资/结算/力能)
↓
Details (明细)
```
---
## 同步顺序原则
1. **依赖优先**：父节点必须先于子节点同步
2. **绑定传递**：子节点的业务键构建依赖父节点的 ID 映射
3. **故障隔离**：父节点同步失败时，子节点标记为 `DEPENDENCY_ERROR` 并跳过
详细状态定义参见：[sync_system_new/sync_system/STATE_DEFINITIONS.md](../sync_system_new/sync_system/STATE_DEFINITIONS.md)
详细架构设计参见：[sync_system_new/architecture_layers.md](../sync_system_new/architecture_layers.md)
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# 节点状态持久化与人工介入规范
> **代码实现**：`sync_system_new/common/state_reset.py`
---
## 1. 持久化规则
### 1.1 持久化目标
| 目标 | 说明 |
|------|------|
| **可恢复性** | 系统重启后能从上次状态继续 |
| **可观测性** | 失败和异常状态要保留，供人工查看 |
| **可追溯性** | 失败信息持久化，不自动重试，需人工确认 |
| **绑定稳定性** | 手工绑定一旦建立，永不自动改变 |
### 1.2 分阶段重置设计
状态重置分为两个阶段执行：
#### 阶段1：加载时重置（Collection.load_from_persistence）
| 字段 | 性质 | 持久化 | 阶段1重置 |
|------|------|--------|-----------|
| `node_id` | 恒定标识 | ✅ 必须 | ❌ 不重置 |
| `data_id` | 业务主键 | ✅ 必须 | ❌ 不重置 |
| `data` | 业务数据 | ✅ 必须 | ✅ **重置**（每次重新取数） |
| `origin_data` | 原始快照 | ✅ 必须 | ✅ **重置**（每次重新取数） |
| `depend_ids` | 依赖列表 | ❌ **不持久化** | ✅ **初始化为[]**（bind 阶段从 data 实时计算） |
| `binding_status` | 绑定状态 | ✅ 必须 | ✅ **重置为 UNCHECKED** |
| `action` | 同步意图 | ✅ 保存 | ❌ **保留**（用于阶段2判断） |
| `status` | 执行状态 | ✅ 保存 | ❌ **保留**（全部保留，不重置） |
| `error` | 错误信息 | ✅ 保存 | ✅ **重置为None**（清空上次错误） |
| `context` | 扩展上下文 | ✅ 保存 | ❌ 不重置 |
#### 阶段2：数据加载后清理（Pipeline._cleanup_create_failed_zombies）
在数据加载完成后、策略执行前，执行CREATE失败节点清理：
1. **检查条件**：
- 本地节点 `action == CREATE`（上次尝试创建）
- 本地节点 `status == FAILED`（创建失败）
2. **清理动作**：
- **删除本地失败节点**（从 collection 中移除）
- 如果有绑定记录：
- 解除绑定关系
- 删除远程 collection 中的僵尸节点
3. **最后重置 action**：
- 所有剩余节点的 `action` 重置为 NONE
- 准备进入策略阶段
4. **下次同步的自动恢复**：
- 被删除的节点会从数据源重新加载
- 如果远程实际已创建成功（网络波动导致未获取到结果）→ 绑定阶段会自动绑定上
- 如果远程实际也失败了 → 重新尝试创建
5. **UPDATE 阶段保护**：
- UPDATE 操作会跳过所有 `status == FAILED` 的节点
- 防止 UPDATE 阶段覆盖 CREATE/UPDATE 失败的状态和错误信息
- 确保失败节点的 action 和 error 信息保持不变，直到下次同步清理
> **说明**：
> - `data` / `origin_data`：每次运行从数据源重新获取，保证数据最新
> - `depend_ids`：**不持久化**，每次 bind 阶段从 data 的业务字段（如 contract_id, project_id）实时提取
> - `binding_status`：持久化用于审计，加载时重置为 `UNCHECKED`，由 bind() 重新判定
> - `error`：**阶段1清空**，避免上次错误影响本次运行，新错误会在各阶段重新生成
> - `action`：**阶段1保留**用于识别 CREATE 失败的节点，**阶段2清理后重置**
> - `status`：**阶段1全部保留**（包括 FAILED、PRECONDITION_FAILED 等），不自动重置
> - **CREATE 失败节点会被自动删除并重新加载**，UPDATE/DELETE 失败保留需人工处理
> - **UPDATE 操作会跳过 FAILED 节点**，避免覆盖失败状态和错误信息
### 1.3 绑定记录 vs binding_status
| 概念 | 存储位置 | 持久性 | 如何改变 |
|------|---------|--------|---------|
| **绑定记录** | `bindings` 表 | **永久保留** | 只能手工 bind/unbind，或 CREATE 失败自动清理 |
| **binding_status** | `nodes` 表 | 保存但可重判 | 每次 bind() 重新判定 |
### 1.4 CREATE 失败的自动恢复
当 CREATE 操作失败时，会产生"僵尸绑定"：
- 绑定记录已建立（local_id → remote_node_id）
- 但远程节点的 `data_id` 为空（API 未返回真实 ID）
**下次同步时的自动恢复流程**：
1. 阶段1加载：保留 `action=CREATE`
2. 阶段2清理：检测到僵尸绑定，自动清理
3. 本地节点恢复为 MISSING 状态
4. 策略阶段重新判定，再次尝试 CREATE
---
## 2. 人工介入规范
### 2.1 介入时机
| 时机 | 场景 | 操作 |
|------|------|------|
| **运行前** | 查看上次失败记录 | 查看持久化的 error，决定是否修复后重试 |
| **bind() 后** | 出现 ABNORMAL/WARNING | 检查数据一致性，手工修复或确认 |
| **bind() 后** | 1:N / N:N 映射 | 手工绑定指定远程记录 |
| **sync() 后** | 批量失败 | 分析失败原因，决定重试策略 |
### 2.2 binding_status 与介入需求
| binding_status | 含义 | 需要介入 | 说明 |
|----------------|------|---------|------|
| `UNCHECKED` | 未检查 | ❌ | 等待 bind() 判定 |
| `NORMAL` | 绑定正常 | ❌ | 自动处理 |
| `MISSING` | 无绑定记录 | ❌ | 自动创建 |
| `WARNING` | 本地有绑定但远程无数据 | ⚠️ 可选 | 可能是远程删除，需确认 |
| `ABNORMAL` | 状态不一致 | ✅ **必须** | 需人工排查 |
| `DEPENDENCY_ERROR` | 依赖未就绪 | ❌ | 等依赖解决后自动重试 |
### 2.3 人工绑定操作
```python
# 手工绑定（1:N 场景）
binding_manager.bind(node_id="local_xxx", data_id="remote_xxx")
# 手工解绑
binding_manager.unbind(node_id="local_xxx")
```
绑定记录一旦建立，永不自动改变，只能手工操作。
### 2.4 职责分工
| 职责 | 系统自动 | 人工介入 |
|------|---------|---------|
| 1:1 自动绑定 | ✅ | - |
| 1:N / N:N 绑定 | ❌ | ✅ |
| NORMAL 节点同步 | ✅ | - |
| MISSING 节点创建 | ✅ | - |
| CREATE 失败重试 | ✅（自动清理僵尸） | ⚠️（需确认后手动重置） |
| UPDATE 失败重试 | ❌（保留FAILED状态） | ✅（需确认后手动重置） |
| ABNORMAL 处理 | ❌ | ✅ |
| WARNING 确认 | ❌ | ✅（可选） |
---
## 3. 总结
1. **分阶段重置**：
- 阶段1（加载时）：只重置 binding_status，**保留 action/status/error**
- 阶段2（数据加载后）：清理 CREATE 失败僵尸，然后重置 action
2. **失败状态持久化**：FAILED 状态和 error 信息保留，不自动重试
3. **绑定记录**：永久保留，除非 CREATE 失败自动清理或手工操作
4. **人工介入**：失败需确认后手动重置，ABNORMAL/WARNING 需人工处理，1:N 绑定需手工指定
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# 架构分层设计：四层模型
本架构旨在将同步系统的**数据容器**、**同步逻辑**、**执行层**与**编排流程**完全解耦，提供极简且类型安全的开发体验。
---
## 1. 架构概览
系统分为四层，依赖关系严格从上到下：
1. **通用层 (Common)**: 定义纯数据结构（Data Container）和基础工具。
2. **同步系统层 (Sync System)**: 定义同步行为接口（SyncStrategy）与业务规则。
3. **数据源层 (DataSource)**: 实现数据的加载与持久化，属于盲目执行层。
4. **编排层 (Pipeline)**: 应用层逻辑，硬编码同步顺序，协调 ID 映射与错误传播。
---
## 2. 通用层 (Layer 0: Common)
本层不包含业务逻辑，仅定义数据契约。
- **SyncNode[T]**: 核心状态机容器。
- `origin_data`: 原始数据（对应 `data_id`）。
- `data`: 计算后的最新目标数据。
- `data_id`: 业务主键ID。加载时必定有值，CREATE 节点初始为空字符串 `""`（布尔值为 False，可通过校验）。
- `action`: 同步意图 (NONE, CREATE, UPDATE, DELETE)。
- `status`: 执行状态 (PENDING, IN_PROGRESS, SUCCESS, FAILED, SKIPPED, PRECONDITION_FAILED)。
- 详见 [状态定义规范 § 5.A](./状态定义规范.md#5-执行同步状态转换-physical-sync-state-transitions)
- `binding_status`: 绑定状态 (UNCHECKED, NORMAL, MISSING, DEPENDENCY_ERROR, ABNORMAL, WARNING)。
- 详见 [状态定义规范 § 1](./状态定义规范.md#1-核心状态判定表-core-binding-matrix)
- `error`: 异常详情。
- **DataCollection**: 节点的集合，提供类型安全的查询和过滤方法。
- **BindingManager**:
- **ID 映射**: 维护 `local_node_id` <-> `remote_node_id` 的双向映射。
- **绑定键**: 使用 `node_id` 作为绑定记录的键，**一致不变**。CREATE 成功后只更新节点的 `data_id`，绑定记录不变。
- **持久化**: 将映射关系持久化到存储（如 JSON/数据库）。
- **Enums**: `SyncAction`, `SyncStatus`, `BindingStatus` 等。
---
## 3. 同步系统层 (Layer 1: Sync System)
核心业务逻辑层。通过实现 `SyncStrategy` 接口来定义特定实体的同步逻辑。
- **SyncStrategy[T] 接口**:
- `bind()`:
- 职责：判定 `binding_status` (NORMAL/MISSING/ABNORMAL/WARNING/DEPENDENCY_ERROR)
- 详见 [状态定义规范 § 1-3](./状态定义规范.md)
- `create()`:
- 职责：处理孤儿节点（MISSING），在对方侧创建新节点并设置 `action=CREATE`
- **ID 替换**: 创建新节点时，复制数据并将依赖字段的本地 ID 替换为远程 ID
- **内联检查**: 通过 `IDResolver.resolve_and_validate()` 验证依赖 ID 解析
- 详见 [状态定义规范 § 4.C](./状态定义规范.md)
- `update()`:
- 职责：处理差异节点（NORMAL 且有 diff），设置 `action=UPDATE`
- **ID 替换**: 准备更新数据时，替换数据中的依赖 ID
- **内联检查**: 验证目标节点 data_id 完整性，失败则设置 `PRECONDITION_FAILED`
- **FAILED 保护**: 自动跳过 `status=FAILED` 的节点
- 详见 [状态定义规范 § 4.A](./状态定义规范.md)
---
## 4. 数据源层 (Layer 2: DataSource)
作为各个后端的适配器，负责数据加载与持久化。
- **职责**:
- `load_nodes(node_type)`: 从后端加载并返回 `SyncNode` 集合，自动添加到 `DataCollection`。
- `save_nodes(nodes)`:
- 遍历节点，仅处理 `status == PENDING` 且 `action != NONE` 的节点。
- 根据 `action` 执行相应的 CREATE/UPDATE/DELETE 操作。
- 执行成功后，更新节点的 `status` 和相关信息（如新生成的 remote_id）。
---
## 5. 编排层 (Layer 3: Pipeline)
最高层级，负责流程编排。
- **职责**:
- **显式顺序**: 直接在代码中按顺序调用同步逻辑（例如：先同步项目，再同步合同）。
- **故障传播**: 若前置实体某节点同步失败（`FAILED`），编排器在处理后续依赖节点时可将其标记为 `DEPENDENCY_ERROR`。
- **生命周期管理**: 初始化 `BindingManager` 和 `DataCollection`，同步结束后调用持久化方法。
---
## 6. ID 映射与对齐：核心流程
为了解决本地数据引用本地 ID 与远程数据引用远程 ID 的冲突，系统采用以下映射逻辑：
### 绑定阶段 (Binding)
- **时机**: `Strategy.bind`
- **目标**: 在 `BindingManager` 中确定 local_id ↔ remote_id 映射
- **手段**: 业务键匹配（如 Code 匹配）、历史记录恢复等
### 执行阶段 (Execution)
- **时机**: `Strategy.create()` / `Strategy.update()` 阶段
- **目标**: 在创建新节点或准备更新时，将依赖字段的本地 ID 替换为远程 ID
- **手段**:
- `create()`: 创建对方节点时，复制数据并替换所有依赖 ID
- `update()`: 准备更新数据时，替换数据中的依赖 ID
- **验证**: `_pre_commit_check` 在 create/update 最后检查，确保所有依赖节点都已有远程 ID
**注意**: ID 替换在 Strategy 的 create/update 阶段完成，DataSource 只负责盲目执行已准备好的数据。
---
## 7. 关键设计原则
- **删除类型依赖配置**: 依赖关系通过 `Pipeline` 中的代码调用顺序自然表达。
- **无状态 DataSource**: 数据源不了解绑定逻辑，只看到 `action`、`status` 和 `binding_status`。
- **BindingManager 为核心**: 负责 ID 空间映射和持久化。
- **配置驱动**: 通过 `StrategyConfig` 和预设配置（ConfigPresets）灵活控制同步行为。
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# 同步系统状态定义 (Final Spec)
本文档定义了同步系统的状态机逻辑。逻辑流转遵循以下顺序：
1. **核心状态判定** (Core State)
2. **依赖检查与ID解析** (Dependency)
3. **自动绑定/发现** (Discovery)
4. **策略执行** (Action)
---
## 0. 绑定状态枚举 (BindingStatus)
| 状态值 | 含义 | 来源 | 允许创建 |
| :--- | :--- | :--- | :---: |
| **UNCHECKED** | 未执行绑定检查 | 加载后的初始状态 | ❌ |
| **NORMAL** | 绑定正常 | 核心状态判定 | ❌ |
| **MISSING** | 无绑定记录（孤儿） | 核心状态判定 | ✅ |
| **WARNING** | 业务键不完整 | 自动绑定阶段 | ❌ |
| **ABNORMAL** | 数据损坏 | 核心状态判定 | ❌ |
| **DEPENDENCY_ERROR** | 依赖未就绪 | 依赖检查或自动绑定 | ❌ |
**关键原则**：
- **UNCHECKED 阻止创建**：加载后节点状态为 UNCHECKED，只有执行了 `bind()` 后才会转为其他状态
- **只有 MISSING 状态才能触发 CREATE**：`create()` 方法只查找 `binding_status == MISSING` 的节点
- **如果 bind() 被跳过**（如 skip_sync=True），节点保持 UNCHECKED，不会被创建
---
## 1. 核心状态判定表 (Core Binding Matrix)
**说明**:
* **Binding Record Pair**: 数据库中的绑定记录 (必须成对出现，已排除单边绑定)。
* **Data Valid**: 指数据是否可读、Schema校验是否通过。
* **Warning vs Abnormal**:
* `ABNORMAL`: 自身数据损坏。
* `WARNING`: 自身健康，但因为对方损坏导致**连接不可用**。
| Bind Pair (Record) | Local Data (Valid?) | Remote Data (Valid?) | -> | **Local Status** | **Remote Status** | **说明** |
| :---: | :---: | :---: | :--- | :--- | :--- | :--- |
| **YES** | **YES** | **YES** | -> | **NORMAL** | **NORMAL** | **稳态**。链路完整，数据健康，可进行 Diff/Update。 |
| **YES** | **YES** | **NO** | -> | **WARNING** | **ABNORMAL** | **远程损坏**。本地虽好，但链路已断 (Link Degraded)。禁止同步。 |
| **YES** | **NO** | **YES** | -> | **ABNORMAL** | **WARNING** | **本地损坏**。远程虽好，但链路已断。禁止同步。 |
| **YES** | **NO** | **NO** | -> | **ABNORMAL** | **ABNORMAL** | **双向损坏**。 |
| **NO** | **YES** | N/A | -> | **MISSING** | N/A | **本地孤儿**。进入“依赖与发现”流程。 |
| **NO** | N/A | **YES** | -> | N/A | **MISSING** | **远程孤儿**。进入“依赖与发现”流程。 |
---
## 2. 依赖与业务键解析 (Dependency & ID Resolution)
**适用范围**: 所有涉及外键依赖 (Foreign Key) 的节点。
**前置条件**: 核心状态 = `MISSING` (准备进行自动绑定或新建)。
在进行 `Auto-Bind` 或 `Create` 之前，必须先尝试构建**远程业务键**。
例如：本地 `Contract(proj_id="P1", code="C01")` 想找远程对象，必须先查询 `P1` 对应的远程 ID `RP_99`，转换成 `(RP_99, "C01")` 才能去远程搜索。
| 依赖项 (Dependency) | 依赖项绑定状态 | -> | **能否构建业务键** | **节点状态** | **说明** |
| :--- | :--- | :--- | :--- | :--- | :--- |
| **无依赖** | N/A | -> | ✅ Yes | **MISSING** | 根节点 (如 Project)，直接进入下一阶段。 |
| **有依赖** | **NORMAL** 且 `data_id` 非空（`status` 任意） | -> | ✅ Yes | **MISSING** | 依赖项已获得远程ID，可进入下一阶段。 |
| **有依赖** | **NORMAL** 且 `data_id` 为空（""，含 `status = FAILED`） | -> | ❌ No | **DEPENDENCY_ERROR** | 依赖项未回填ID，阻断绑定与同步。 |
| **有依赖** | **MISSING / ABNORMAL** | -> | ❌ No | **DEPENDENCY_ERROR** | **依赖阻断**。父节点未同步或损坏，无法计算远程键，无法绑定，无法创建。 |
| **有依赖** | **WARNING** | -> | ❌ No | **DEPENDENCY_ERROR** | 父节点状态不确定（如连接降级），禁止基于此建立新关系。 |
> **处理策略**: 处于 `DEPENDENCY_ERROR` 状态的节点，其动作强制为 **SKIP** (或 PENDING)。必须先修复父节点。
>
> **错误信息格式**: `DEPENDENCY_ERROR` 节点的 `error` 字段会包含详细的依赖失败信息：
> - `dep_err: not_found: field_name(node_type)=value` - 依赖节点未找到
> - `dep_err: field_name: status=FAILED` - 依赖节点状态为 FAILED
> - 多个依赖失败时用分号分隔：`dep_err: not_found: project_id(project)=P1; contract_id: status=FAILED`
---
## 3. 自动绑定状态处理 (Auto-Binding State Handling)
此逻辑遵循“去噪后 1:1”原则：只有在排除掉所有健康同步对后，若剩余节点形成绝对的 1:1 关系，才允许自动绑定。
**配置说明与触发机制**:
- **初始化场景**: 通常在系统第一次初始化或首次接入新实体时，配置 `auto_bind = True` 来对齐历史数据。
- **后续同步**: 系统在日常同步中不建议开启全局自动绑定。自动绑定仅作为“发现”手段，一旦建立过关系的节点，其后续绑定操作通常仅在“自动创建”逻辑中伴随产生（详见第 4 节孤儿处理）。
- **执行前提**: 只有当节点状态为 `MISSING` 且依赖解析成功（`DEPENDENCY_ERROR = False`）时，才会尝试以下探测逻辑。
- **业务键完整性**: 若业务键字段缺失（如 `serial_number = null`），直接标记 `binding_status = WARNING`，并在 `node.error` 记录原因（`Auto-bind skipped: missing fields ...`），不参与自动绑定与孤儿创建判定。- **ID字段解析失败**: 若业务键包含ID字段（如 `supplier_id`）且依赖节点未绑定，ID解析失败，标记 `binding_status = DEPENDENCY_ERROR`，阻止孤儿创建。
**核心算法**:
1. **全集搜索**: 寻找本地/远端所有共享同一个业务键（Business Key）的记录。
2. **排除稳态对**: 识别并移除**成对且互绑**的 `NORMAL` 记录。
- 只有当本地 A 与远端 B 互为绑定对象，且状态皆为 `NORMAL` 时，才将这一对记录从待判定集合中剔除。
- 若出现单边 `NORMAL` 记录（即其配对项不在本次搜索范围内或状态不属于另一端的 `NORMAL`），则不予剔除，视为环境污染项。
3. **判定剩余**: 检查排除上述稳态对后的剩余集合（包含 `MISSING`, `ABNORMAL`, `WARNING` 及单边已占用的 `NORMAL` 记录）。
> **术语**：
> - `L_remain` = 本地记录中，排除“成对稳态”后剩余的数量。
> - `R_remain` = 远端记录中，排除“成对稳态”后剩余的数量。
| `L_remain` | `R_remain` | -> | **动作** | **说明** |
| :---: | :---: | :--- | :--- | :--- |
| **1** | **1** | -> | **BIND (Link)** | **1对1 自动对齐**：仅当两端剩余记录皆为 `MISSING` 且绝对 1:1 时，执行自动绑定。 |
| **1** | **1** | -> | **SKIP** | **带障不处理**：若剩余记录中包含 `ABNORMAL` 等异常状态，说明存在历史冲突，不执行自动动作。 |
| **N** | **0** | -> | **CREATE** | **可判定缺失**：业务键完整且唯一，本地存在而远端不存在（N:0）时，才允许进入孤儿创建策略。 |
| 其他 | 其他 | -> | **SKIP** | **非 1:1 不处理**：存在多对多、多对一或无候选情况，系统保持原状。 |
**设计优势**:
1. **对故障极端敏感**：环境中存在任何 `ABNORMAL` 记录都会阻断自动绑定，强制人工介入处理异常。
2. **状态纯净**：失败时不产生任何中间态（如已废弃的 `AMBIGUOUS`），保持语义清晰。
3. **静默自愈**: 当外界清理了环境且满足 1:1 条件后，系统下次同步会自动完成绑定。
### 3.1 空数据处理策略
**原则**：**空数据不推送**。
**空数据定义**：
- 初始化时创建但未编辑的业务记录（如空合同、空施工任务）
- 业务键字段为空或关键字段缺失的记录
**处理方式**：
- 在自动绑定阶段，若业务键字段缺失，标记 `binding_status = WARNING`，记录原因
- 不参与自动绑定与孤儿创建判定
- 不推送到远程系统
**设计理由**：
1. **远程系统简化**：远程只需处理完整数据，无需兼容空数据校验逻辑
2. **避免垃圾数据**：空数据通常会被本地删除，若已推送则清理复杂
3. **数据质量保障**：远程系统只能看到本地已正确编辑保存的业务
**配置方式**（Strategy 层）：
```python
# 在 Strategy 配置中指定必填字段
default_config = StrategyConfig(
auto_bind_fields=["contract_id", "task_type"], # 业务键字段
# 如果这些字段为空，节点将被标记为 WARNING 而非 MISSING
)
```
---
## 4. 动作策略表 (Action Policy Matrix)
此表定义了在特定状态下，`execute` 阶段允许产生的 **意图行动 (`SyncAction`)**。
#### A. 稳态更新 (NORMAL)
适用于已有绑定关系且链路健康的节点。
| 状态 | 动作条件 | 执行动作 (`SyncAction`) |
| :--- | :--- | :--- |
| **NORMAL** | `compute_diff` 判定存在差异 | **UPDATE** |
| **NORMAL** | `compute_diff` 判定无差异 | **NONE** |
#### B. 异常处理 (阻断态)
处于这些状态的节点，引擎会自动中止后续的读写操作。
| 状态 | 说明 | 动作 (`SyncAction`) |
| :--- | :--- | :--- |
| **DEPENDENCY_ERROR** | 父节点缺失/异常同步导致阻断 | **NONE** |
| **ABNORMAL / WARNING** | 数据损坏或链路降级，需人工修复 | **NONE** |
#### C. 孤儿处理 (Create Only)
适用于最终探测状态为 **MISSING** 且无法/不满足自动绑定的节点。
**本地孤儿 (Local Orphan)**: 本地有，远程无。
| 策略配置 (`local_orphan_action`) | 对应的同步模式 | 动作 (`SyncAction`) |
| :--- | :--- | :--- |
| **"create_remote"** | Push (本地推远端) | **CREATE** |
| **"delete_local"** | Pull (远端拉本地) | **报错 (未实现)** |
| **"none"** | Any | **NONE** |
**远程孤儿 (Remote Orphan)**: 远程有，本地无。
| 策略配置 (`remote_orphan_action`) | 对应的同步模式 | 动作 (`SyncAction`) |
| :--- | :--- | :--- |
| **"create_local"** | Pull (远端拉本地) | **CREATE** |
| **"delete_remote"** | Push (本地推远端) | **报错 (未实现)** |
| **"none"** | Any | **NONE** |
---
## 5. 执行同步状态转换 (Physical Sync State Transitions)
在策略执行完成、设置好 `action` 后，DataSource 层负责执行实际的同步操作并更新 `status` 字段。
### A. 执行状态枚举 (SyncStatus)
| 状态值 | 含义 | 适用场景 |
| :--- | :--- | :--- |
| **PENDING** | 待执行 | 初始状态、无动作的节点 |
| **IN_PROGRESS** | 执行中 | 异步接口已提交，等待结果回调 |
| **SUCCESS** | 执行成功 | 同步操作完成且成功 |
| **FAILED** | 执行失败 | 同步操作失败，`error` 字段记录原因 |
| **SKIPPED** | 已跳过 | 节点被主动跳过（如依赖未满足） |
| **PRECONDITION_FAILED** | 前置条件失败 | create/update 内部验证发现问题 |
### B. 执行转换矩阵
#### 同步接口（一步式）
适用于同步 API（调用后立即返回成功/失败）。
| 输入: action | API 调用结果 | → | 输出: status | 副作用 |
| :--- | :--- | :--- | :--- | :--- |
| **CREATE** | 成功返回 (200/201) | → | **SUCCESS** | `data_id` 设置为远程返回的ID |
| **CREATE** | 失败返回 (4xx/5xx) | → | **FAILED** | `error` 记录错误信息 |
| **UPDATE** | 成功返回 (200) | → | **SUCCESS** | - |
| **UPDATE** | 失败返回 (4xx/5xx) | → | **FAILED** | `error` 记录错误信息 |
| **DELETE** | 成功返回 (200/204) | → | **SUCCESS** | 节点可能被移除 |
| **DELETE** | 失败返回 (4xx/5xx) | → | **FAILED** | `error` 记录错误信息 |
| **NONE** | - | → | **PENDING** | 不执行，保持原状 |
#### 异步接口（两步式）
适用于异步 API（提交后需要轮询或回调获取结果）。
| 输入: action | API 提交结果 | → | 输出: status | 后续操作 |
| :--- | :--- | :--- | :--- | :--- |
| **CREATE** | 提交成功 (202 Accepted) | → | **IN_PROGRESS** | 记录 task_id，等待轮询 |
| **CREATE** | 提交失败 (4xx/5xx) | → | **FAILED** | `error` 记录错误 |
| **IN_PROGRESS** | 轮询返回成功 | → | **SUCCESS** | `data_id` 设置为远程ID |
| **IN_PROGRESS** | 轮询返回失败 | → | **FAILED** | `error` 记录错误 |
| **IN_PROGRESS** | 超时未完成 | → | **FAILED** | `error` 记录 "Timeout" |
### B+. Handler 降级（action 取消）
> **代码实现**：各 `domain/*/api_handler.py` 中的 `update()` 方法。
当 Handler 在构建 API 请求数据时，发现实际无需更新的字段（如 schema 校验后所有字段与远程一致），
Handler 会主动将节点的 `action` 从 `UPDATE` 降级为 `NONE`：
```
action=UPDATE → Handler 校验 → 无实际变更字段 → action=NONE（不提交 API）
```
此机制确保 DataSource 不会向远程发送无意义的空更新请求。
### C. 关键副作用
| 动作 | 成功时的副作用 | 说明 |
| :--- | :--- | :--- |
| **CREATE** | 临时绑定已建立 | 绑定关系可在提交前创建，用于推送与追踪；是否成功不影响该绑定存在 |
| **CREATE** | 设置 `data_id` | 成功后从API响应中提取远程分配的ID，更新到节点 |
| **CREATE** | 回写 `data` 主键 | DataSource 将远程返回的ID写回 `SyncNode.data`（如 `id`/`*_id` 字段） |
| **CREATE** | 更新绑定记录 | 若使用临时ID，成功后替换为真实的远程ID |
| **UPDATE** | 更新 `origin_data` | 将当前 `data` 保存为新的 `origin_data` |
| **DELETE** | 移除绑定记录 | 删除成功后，清除对应的绑定关系 |
### D. 错误处理
| 错误类型 | 记录方式 | 重试策略 |
| :--- | :--- | :--- |
| **网络错误** | `error = "Network timeout"` | 可重试 |
| **权限错误** | `error = "403 Forbidden"` | 不可重试，需人工介入 |
| **数据校验错误** | `error = "Validation failed: ..."` | 不可重试，需修复数据 |
| **依赖缺失** | `status = PRECONDITION_FAILED` | 不执行，等待依赖修复 |
---
## 6. 同步检查规范 (Sync Check Specification)
在执行同步前后，需要进行状态检查以确保操作的合法性和完整性。
### A. 内联前置检查（create/update 阶段）
> **实现说明**：原 `_pre_commit_check` 方法已移除（保留空壳兼容接口）。
> 所有有效检查已内联到 `_add_create_action()` 和 `_add_update_action()` 中。
**create() 阶段内联检查**：
| 检查类别 | 检查条件 | 不通过时 | 说明 |
| :--- | :--- | :--- | :--- |
| **数据完整性** | `src_node.get_data()` 不为空 | 跳过该节点，记录日志 | MISSING 但数据为空 |
| **依赖 ID 解析** | `id_resolver.resolve_and_validate()` 成功 | `binding_status → DEPENDENCY_ERROR` | 依赖字段无法解析到目标系统 ID |
**update() 阶段内联检查**：
| 检查类别 | 检查条件 | 不通过时 | 说明 |
| :--- | :--- | :--- | :--- |
| **FAILED 保护** | `src_node.status != FAILED` | 跳过该节点 | 不覆盖上次失败的状态和错误 |
| **数据完整性** | `src_node.get_data()` 不为空 | 跳过该节点 | NORMAL 但数据为空 |
| **目标节点存在** | 通过绑定找到目标节点 | 跳过该节点 | 绑定记录指向的节点不在集合中 |
| **data_id 完整性** | `target_node.data_id` 非空 | `status → PRECONDITION_FAILED` | UPDATE 必须有业务主键 |
| **依赖 ID 解析** | `id_resolver.resolve_and_validate()` 成功 | `status → PRECONDITION_FAILED` | 依赖字段无法解析到目标系统 ID |
| **差异检测** | `_needs_update()` 返回 True | 跳过该节点 | 无差异则不更新 |
> **注意**：以下检查项在当前实现中 **未覆盖**【未实现】：
> - 状态合法性：`binding_status` 必须是已知状态
> - 动作合法性：`CREATE/UPDATE` 只能用于 `NORMAL` 节点
> - 绑定一致性：`NORMAL` 节点必须有绑定记录
### B. 同步后检查 (Post-Sync Check)
**目标**: 验证同步结果的完整性，发现残留问题。
> **实现说明**：当前 `_stage4_post_sync_check` 只打印摘要表格，不做异常检测。以下检查项均为【未实现】。
#### 检查项清单【未实现】
| 检查类别 | 检查条件 | 异常情况 | 严重程度 |
| :--- | :--- | :--- | :--- |
| **CREATE 完成性** | CREATE 节点应该有 `data_id` | `action = CREATE, status = SUCCESS` 但 `data_id = ""` | 🔴 ERROR |
| **CREATE 绑定** | CREATE 节点应该有绑定记录 | CREATE 成功但无绑定 | 🔴 ERROR |
| **UPDATE 完成性** | UPDATE 节点应该成功 | `action = UPDATE` 但 `status = FAILED` | ⚠️ WARNING |
| **绑定保持** | UPDATE 节点的绑定应该保持 | UPDATE 后绑定记录丢失 | 🔴 ERROR |
| **残留异常** | 不应有 ABNORMAL 节点 | 同步后仍有 `binding_status = ABNORMAL` | ⚠️ WARNING |
| **残留依赖错误** | 不应有 DEPENDENCY_ERROR | 同步后仍有依赖阻断 | ⚠️ WARNING |
#### 统计指标
| 指标 | 计算方式 | 用途 |
| :--- | :--- | :--- |
| **成功率** | `SUCCESS / (CREATE + UPDATE)` | 评估同步质量 |
| **异常率** | `(ABNORMAL + WARNING) / total` | 发现数据质量问题 |
| **阻断率** | `DEPENDENCY_ERROR / total` | 发现依赖关系问题 |
#### 决策规则
| 检查结果 | ERROR 数量 | 决策 |
| :--- | :--- | :--- |
| ✅ 通过 | 0 | **继续持久化**，正常结束 |
| ⚠️ 有警告 | 0, WARNING ≥1 | **继续持久化**，打印警告报告 |
| ❌ 有错误 | ≥1 | **继续持久化**（已同步无法回滚），打印错误报告 |
> **注意**: Post-Sync Check 即使有 ERROR 也不会终止流程，因为同步已经执行，无法回滚。检查目的是发现问题并记录，供后续修复。
---
## 附录: 状态字段说明
### SyncNode 核心字段
| 字段 | 类型 | 设置阶段 | 含义 |
| :--- | :--- | :--- | :--- |
| `binding_status` | BindingStatus | Bind 阶段 | 绑定健康状态 |
| `action` | SyncAction | Create/Update 阶段 | 待执行动作 |
| `status` | SyncStatus | Physical Sync 阶段 | 执行结果状态 |
| `data_id` | str | 数据加载 / CREATE 后 | 业务主键ID（CREATE 前为 ""） |
| `depend_ids` | List[str] | 数据加载 | 依赖节点的 node_id 列表 |
| `error` | str \| None | Physical Sync 阶段 | 错误信息（失败时） |
### 状态流转时序
```
[数据加载] [Bind] [Create/Update] [Physical Sync]
binding_status: UNCHECKED → NORMAL/MISSING/... → (保持) → (保持)
action: NONE → NONE → CREATE/UPDATE → (保持)
status: PENDING → PENDING → PENDING → SUCCESS/FAILED
data_id: 从源加载 → (保持) → 可能为 "" → CREATE 后设置
```
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# 状态机形式化规范
本文档用 **Guard-Event-Action (GEA)** 形式严格定义节点状态机。
所有转换以代码实现为准，模糊之处在文档中显式标注。
> **代码基线**
> - 枚举: `sync_system_new/common/types.py`
> - 决策引擎: `sync_system_new/sync_system/decision.py`
> - 重置策略: `sync_system_new/common/state_reset.py`
> - 同步策略: `sync_system_new/sync_system/strategy.py`
> - 物理同步: `sync_system_new/datasource/datasource.py`
> **配置基线（状态机真源）**
> - `sync_system_new/state_machine/node_state_machine.yaml`
### 2026-02 对齐说明（重构前必读）
以下语义以 `node_state_machine.yaml` 为准，用于修正文档中易混淆点：
1. **E12a 为什么从 S01 出发？**
- `S01` 只约束**源节点**是 NORMAL/NONE/PENDING 且有 `data_id`。
- `E12a` 的 guard 是 `target_has_data_id=false`，检查对象是**目标节点**。
- 所以“源节点在 S01”与“E12a 触发前置失败”并不冲突。
2. **S01 会不会触发创建？**
- 当前配置中，create 的入口状态是 `S02(MISSING)`，不是 `S01`。
- `S01` 进入的是 update_prepare（E12/E13/E14）。
3. **N:0 + create_enabled=true 的当前行为**
- 自动绑定分支 `E08f`：`S02 -> S01`，并 `emit spawn_target_node_state: S06`。
- create_prepare 分支 `E09b` 也可在检查成功后 `S02 -> S01 + spawn S06`。
- 即：源节点不会停在“等待创建结果”的专用状态；创建执行结果体现在目标创建节点链路 `S06 -> S10/S11/S12/S13`。
4. **旧章节中的事件编号偏差**
- 本文后续仍有部分“E11a/E11b/…”旧编号描述，已与当前 YAML 不一致。
- 进行代码重构时，优先依据 YAML 的 `E08/E09/E10/E12/E13/E14/E15..E20`。
---
## §1 状态空间定义
### §1.1 状态维度
节点携带 **三个独立的状态字段** 和 **两个辅助字段**：
| 字段 | 枚举 | 值域 | 语义 |
|------|------|------|------|
| **B** – `binding_status` | `BindingStatus` | `UNCHECKED` · `NORMAL` · `MISSING` · `ABNORMAL` · `WARNING` · `DEPENDENCY_ERROR` | 绑定健康度 |
| **A** – `action` | `SyncAction` | `NONE` · `CREATE` · `UPDATE` · `DELETE` | 待执行动作 |
| **S** – `status` | `SyncStatus` | `PENDING` · `IN_PROGRESS` · `SUCCESS` · `FAILED` · `SKIPPED` · `PRECONDITION_FAILED` | 执行结果 |
辅助字段（影响 Guard 但不是状态维度）：
| 字段 | 类型 | 语义 |
|------|------|------|
| `data_id` | `str` | 业务主键（空串 `""` = 尚未从远程获取） |
| `error` | `str \| None` | 最近一次错误信息 |
理论组合 = 6 × 4 × 6 = **144**，实际可达 ≈ **23** 种。
### §1.2 可达状态枚举
以下列出所有在正常流程中可以到达的 `(binding_status, action, status)` 三元组。
| # | binding_status | action | status | 语义 | 产生阶段 |
|---|---|---|---|------|---------|
| R1 | UNCHECKED | NONE | PENDING | 首次加载 | 数据加载 |
| R2 | UNCHECKED | NONE | SUCCESS | 从持久化恢复(上轮成功)后重置 | 阶段1/2重置 |
| R3 | UNCHECKED | NONE | FAILED | 从持久化恢复(上轮失败)后重置 | 阶段1/2重置 |
| R4 | UNCHECKED | NONE | SKIPPED | 从持久化恢复(上轮跳过)后重置 | 阶段1/2重置 |
| R5 | UNCHECKED | NONE | PRECONDITION_FAILED | 从持久化恢复(上轮前置失败)后重置 | 阶段1/2重置 |
| R6 | NORMAL | NONE | PENDING | 绑定正常，无需操作(首次) | bind.p1 |
| R7 | NORMAL | NONE | SUCCESS | 绑定正常，无需操作(历史成功) | bind.p1 |
| R8 | NORMAL | NONE | FAILED | 绑定正常但上次失败，被 FAILED 保护 | bind.p1 |
| R9 | MISSING | NONE | PENDING | 孤儿，等待自动绑定或创建(首次) | bind.p1 |
| R10 | MISSING | NONE | SUCCESS | 孤儿(历史成功但绑定丢失?) | bind.p1 |
| R11 | ABNORMAL | NONE | * | 数据损坏，需人工 | bind.p1 |
| R12 | WARNING | NONE | * | 多候选/对方损坏，需人工 | bind.p1/p3 |
| R13 | DEPENDENCY_ERROR | NONE | PENDING | 依赖不满足 | bind.p2/p3/create |
| R14 | NORMAL | CREATE | PENDING | 准备创建(目标节点) | create |
| R15 | NORMAL | CREATE | IN_PROGRESS | 异步创建进行中 | sync |
| R16 | NORMAL | CREATE | SUCCESS | 创建成功 | sync |
| R17 | NORMAL | CREATE | FAILED | 创建失败 | sync |
| R18 | NORMAL | UPDATE | PENDING | 准备更新(目标节点) | update |
| R19 | NORMAL | UPDATE | IN_PROGRESS | 异步更新进行中 | sync |
| R20 | NORMAL | UPDATE | SUCCESS | 更新成功 | sync |
| R21 | NORMAL | UPDATE | FAILED | 更新失败 | sync |
| R22 | NORMAL | UPDATE | PRECONDITION_FAILED | 更新前置条件失败 | update |
| R23 | NORMAL | CREATE | SKIPPED | 创建被 Handler 跳过 | sync |
> **不可达组合（示例）**：
> - `(MISSING, UPDATE, *)` — MISSING 节点不可能被安排 UPDATE
> - `(ABNORMAL, CREATE, *)` — ABNORMAL 节点不可能被安排 CREATE
> - `(*, DELETE, *)` — DELETE 尚未实现
> - `(UNCHECKED, CREATE, *)` — UNCHECKED 是瞬态，在 bind 之前不会有 CREATE
> - `(DEPENDENCY_ERROR, UPDATE, *)` — DEPENDENCY_ERROR 节点不可能进入 update 流程
### §1.3 辅助字段约束
| 对应状态 | binding_status | action | status | data_id 约束 | error 约束 |
|---------|---|---|---|-------------|-----------|
| R14 | NORMAL | CREATE | PENDING | `""` (待远程返回) | None |
| R16 | NORMAL | CREATE | SUCCESS | 非空 (远程回填) | None |
| R17 | NORMAL | CREATE | FAILED | `""` (未回填) | 非空 |
| R22 | NORMAL | UPDATE | PRECONDITION_FAILED | * | 非空 |
| R13 | DEPENDENCY_ERROR | NONE | PENDING | * | 非空 |
---
## §2 不变量 (Invariants)
以下约束在**任何事件执行后**都必须成立。违反即为 Bug。
```
INV-1 B = UNCHECKED ⟹ A = NONE
(UNCHECKED 是瞬态，在 bind 之前不允许有动作)
INV-2 B ∈ {ABNORMAL, WARNING, DEPENDENCY_ERROR} ⟹ A = NONE
(阻断态节点不允许执行任何同步动作)
INV-3 B = MISSING ⟹ A ∈ {NONE, CREATE}
(MISSING 节点只能等待创建或保持不动)
INV-4 A = CREATE ⟹ B = NORMAL
(CREATE 动作只出现在目标节点上，其 binding_status 已被设为 NORMAL)
INV-5 A = UPDATE ⟹ B = NORMAL
(UPDATE 动作只对 NORMAL 节点执行)
INV-6 S = IN_PROGRESS ⟹ A ∈ {CREATE, UPDATE, DELETE}
(只有提交过 API 的节点才可能处于 IN_PROGRESS)
INV-7 S = PRECONDITION_FAILED ⟹ A = UPDATE
(PRECONDITION_FAILED 只在 update 阶段产生)
INV-8 A = CREATE ∧ S = SUCCESS ⟹ data_id ≠ ""
(创建成功必须回填 data_id)
INV-9 S = FAILED ⟹ error ≠ None
(失败必须有错误信息)
INV-10 B = DEPENDENCY_ERROR ⟹ error ≠ None
(依赖阻断必须有错误信息)
```
---
## §3 事件与转换
### §3.1 事件总览图
```
┌─────────────────────────────────────────────────────┐
│ 节点生命周期事件流 │
└─────────────────────────────────────────────────────┘
持久化恢复 策略层 (Strategy) 执行层 (DataSource)
═══════════ ══════════════════════════════════ ══════════════════════════
┌──────────────────────────────┐
┌──────┐ │ bind() │ ┌──────────────────────┐
│E01 │──────────▶│ E04 ─┐ │ │ sync_all() │
│RESET1│ │ E05 ├─ phase1: core_state │ │ │
└──┬───┘ │ E06 ─┘ │ │ E12 SYNC_OK │
│ │ E07 ── phase2: dep_check │ ┌───▶│ E13 SYNC_FAIL │
┌──▼───┐ │ E08 ─┐ │ │ │ E14 SYNC_ASYNC │
│E02 │ │ E09 ├─ phase3: auto_bind │ │ │ E15 SYNC_TIMEOUT │
│ZOMBIE│ │ E10 ─┘ │ │ │ E16 HANDLER_SKIP │
└──┬───┘ └──────────────────────────────┘ │ │ E17 HANDLER_DOWN │
│ ┌──────────────────────────────┐ │ └──────────────────────┘
┌──▼───┐ │ create() / update() │ │
│E03 │──────────▶│ E11a CREATE_OK │────┘
│RESET2│ │ E11b CREATE_DEP_FAIL │
└──────┘ │ E11c UPDATE_DIFF │
│ E11d UPDATE_PRECOND_FAIL │
│ E11e UPDATE_SKIP_FAILED │
└──────────────────────────────┘
```
### §3.2 状态转换详解
本节按 Pipeline 执行阶段组织。每个阶段包含：
1. **状态转换图**：状态（R 编号）为节点，事件（E 编号）为有向边
2. **转换表**：每个事件的精确规格——起始状态、判断条件、结束状态、副作用
---
#### 🔄 阶段 0：重置
**状态转换图：**
```
╔═══════════════════════════════════════╗
║ 任意持久化终态 (R6 ~ R23) ║
╚═══════════════════╤═══════════════════╝
│ E01
▼
┌────────────────────────────────────────┐ E02
│ 瞬态: UNCHECKED │────────────▶ [节点删除 + 解除绑定]
│ (action 保留, status 保留, error=None) │
└────────────────────┬──────────────────┘
│ E03 (存活节点)
▼
╔══════════════════════════════════════════════════════════════╗
║ [R1] UNCHECKED, NONE, PENDING ← 首次加载 ║
║ [R2] UNCHECKED, NONE, SUCCESS ← 上轮成功 ║
║ [R3] UNCHECKED, NONE, FAILED ← 上轮失败 ║
║ [R4] UNCHECKED, NONE, SKIPPED ← 上轮跳过 ║
║ [R5] UNCHECKED, NONE, PRECONDITION_FAILED ← 上轮前置 ║
╚══════════════════════════════════════════════════════════════╝
```
**转换表：**
| 事件 | 起始状态 | 判断条件 (Guard) | 结束状态 | 副作用 |
|------|---------|-----------------|---------|--------|
| **E01**: PHASE1_RESET | R6~R23 (任意持久化终态) | 节点从持久化加载 | 瞬态 (UNCHECKED, action 保留, status 保留) | error → None; data/origin_data → None |
| **E02**: ZOMBIE_KILL | 瞬态 | action = CREATE ∧ (status = FAILED ∨ data_id = "") | **节点删除** | 解除绑定关系; 对 local/remote 两侧都扫描 |
| **E03**: ACTION_RESET | 瞬态 (存活节点) | E02 完成后所有存活节点 | R1 / R2 / R3 / R4 / R5 (按原 status 分) | action → NONE |
> **代码**: `NodeStateReset.get_phase1_reset_defaults()` · `cleanup_create_failed_zombies()` · `reset_action_for_nodes()`
---
#### 🔗 阶段 1：Bind
Bind 由三个子阶段串行执行。后一阶段只处理前一阶段的遗留 MISSING 节点。
**状态转换图：**
```
[R1~R5] UNCHECKED, NONE, *
│
│ ══════════ Phase 1: 核心状态判定 ══════════
│
├── E04 (有绑定, 双方数据 VALID) ───────────▶ [R6/R7/R8] NORMAL ──────▶ 出口 ✅
├── E04 (有绑定, 自身数据缺失/损坏) ────────▶ [R11] ABNORMAL ─────────▶ 出口 🔒
├── E04 (有绑定, 对方数据缺失/损坏) ────────▶ [R12] WARNING ──────────▶ 出口 🔒
│
└── E05 (无绑定记录) ───────────────────────▶ [R9] MISSING
│
══════════ Phase 2: 依赖检查 ══════════ │
│
├── E06 (data = None) ──────────────────────▶ [R11] ABNORMAL ──────▶ 出口 🔒
├── E07 (依赖节点不满足) ───────────────────▶ [R13] DEP_ERROR ─────▶ 出口 🔒
│ (无依赖配置 或 依赖全部满足 → 继续 ▼)
│
══════════ Phase 3: 自动绑定 ══════════
│
├── E08 (auto_bind 关闭) ──────────────────▶ [R12] WARNING ────────▶ 出口 🔒
├── E09 (去噪后 1:1 匹配成功) ─────────────▶ [R6] NORMAL ─────────▶ 出口 ✅
├── E10a (去噪后非 1:1, 多候选) ───────────▶ [R12] WARNING ────────▶ 出口 🔒
├── E10b (业务键字段缺失) ─────────────────▶ [R12] WARNING ────────▶ 出口 🔒
├── E10c (业务键中 ID 字段解析失败) ───────▶ [R13] DEP_ERROR ─────▶ 出口 🔒
│
└── (1:0 无远程匹配)
├── create_enabled = True → [R9] MISSING ──────────────▶ 进入 create
└── create_enabled = False → [R12] WARNING ─────────────▶ 出口 🔒
```
**转换表：**
| 事件 | 起始状态 | 判断条件 (Guard) | 结束状态 | 副作用 |
|------|---------|-----------------|---------|--------|
| **E04**: BIND_PAIRED | R1~R5 | 有绑定记录 ∧ 双方数据 VALID | R6 (PENDING) / R7 (SUCCESS) / R8 (FAILED) — status 保持 | 远程节点同步设置 binding_status |
| **E04**: BIND_PAIRED (自身异常) | R1~R5 | 有绑定记录 ∧ 本方数据缺失或损坏 | R11 (ABNORMAL) | 对方节点设为 WARNING |
| **E04**: BIND_PAIRED (对方异常) | R1~R5 | 有绑定记录 ∧ 对方数据缺失或损坏 | R12 (WARNING) | 对方节点设为 ABNORMAL |
| **E05**: BIND_ORPHAN | R1~R5 | 无绑定记录 | R9 (MISSING, NONE, status 保持) | — |
| **E06**: DATA_NULL | R9 | binding_status = MISSING ∧ data = None | R11 (ABNORMAL) | error = "数据损坏: 节点数据为空或不存在" |
| **E07**: DEP_CHECK_FAIL | R9 | depend_fields 配置非空 ∧ ∃依赖节点: 不存在 ∨ status ≠ NORMAL ∨ data_id 为空 | R13 (DEPENDENCY_ERROR) | error = "依赖项不满足: ..."; depend_ids 填充 |
| **E08**: AUTOBIND_DISABLED | R9 | auto_bind = False 或 auto_bind_fields 为空 | R12 (WARNING) | — |
| **E09**: AUTOBIND_OK | R9 | 去噪后 local:remote = 1:1 ∧ 双方都是 MISSING | R6 (NORMAL) | 建立绑定记录; 双方都设为 NORMAL |
| **E10a**: AUTOBIND_AMBIGUOUS | R9 | 去噪后非 1:1 (多候选) | R12 (WARNING) | error += "存在多个候选节点" |
| **E10b**: AUTOBIND_KEY_MISSING | R9 | auto_bind_fields 中有字段不存在于 data | R12 (WARNING) | error += "缺少业务键字段: ..." |
| **E10c**: AUTOBIND_ID_FAIL | R9 | 业务键包含 ID 字段 ∧ ID 解析失败 | R13 (DEPENDENCY_ERROR) | error = "业务键中的ID字段解析失败: ..." |
| **E10d**: ORPHAN_CREATE_DISABLED | R9 | 去噪后 1:0 ∧ create_enabled = False | R12 (WARNING) | error += "孤儿且不允许自动创建" |
> **E04 核心状态矩阵** (完整查表):
>
> | | 远程: VALID | 远程: ABSENT | 远程: INVALID |
> |---|---|---|---|
> | **本地: VALID** | 本:NORMAL 远:NORMAL | 本:WARNING 远:ABNORMAL | 本:WARNING 远:ABNORMAL |
> | **本地: ABSENT** | 本:ABNORMAL 远:WARNING | 本:ABNORMAL 远:ABNORMAL | — |
> | **本地: INVALID** | 本:ABNORMAL 远:WARNING | — | 本:ABNORMAL 远:ABNORMAL |
>
> 不在矩阵中的组合 → 默认 (ABNORMAL, ABNORMAL)
> **代码**: `SyncDecisionEngine.determine_core_status()` · `_phase_core_state()` · `_check_dependencies_for_nodes()` · `_phase_auto_binding()`
---
#### ⚡ 阶段 2：Create / Update
**状态转换图：**
```
═══════════════ Create ═══════════════
[R9] MISSING, NONE, PENDING (源节点, data ≠ None)
│
├── E11a (ID 解析成功) ────▶ 源节点: [R9] → [R6] NORMAL
│ 新建目标节点: → [R14] NORMAL, CREATE, PENDING
│ + 建立绑定记录, 目标 data_id = ""
│
└── E11b (ID 解析失败) ────▶ 源节点: [R9] → [R13] DEPENDENCY_ERROR
═══════════════ Update ═══════════════
[R6/R7] NORMAL, NONE, PENDING/SUCCESS (源节点, status ≠ FAILED)
│
├── E11c (差异检测通过) ────▶ 目标节点 → [R18] NORMAL, UPDATE, PENDING
├── E11d.1 (目标 data_id="") ▶ 目标节点 → [R22] status = PRECONDITION_FAILED
├── E11d.2 (ID 解析失败) ───▶ 目标节点 → [R22] action = UPDATE, status = PRECOND_FAIL
└── (无差异) ──────────────▶ 保持不变
═══════════════ FAILED 保护 ═══════════════
[R8] NORMAL, NONE, FAILED (源节点)
│
└── E11e ──────────────────▶ 跳过，保持 [R8] 不变
```
**转换表：**
| 事件 | 起始状态 (源节点) | 判断条件 (Guard) | 结束状态 | 副作用 |
|------|---------|-----------------|---------|--------|
| **E11a**: CREATE_OK | R9 (MISSING) | data ≠ None ∧ IDResolver.resolve_and_validate() = OK | 源 → R6 (NORMAL); **新建**目标 → R14 | 建立绑定; 新节点 data = 已替换 ID 的副本, data_id = "" |
| **E11b**: CREATE_DEP_FAIL | R9 (MISSING) | data ≠ None ∧ IDResolver.resolve_and_validate() = FAIL | R13 (DEPENDENCY_ERROR) | error = "创建时依赖 ID 未解析: ..." |
| **E11c**: UPDATE_DIFF | R6/R7 (NORMAL, status≠FAILED) | 目标存在 ∧ 目标 data_id ≠ "" ∧ ID 解析 OK ∧ _needs_update() = True | 目标 → R18 (UPDATE, PENDING) | 目标: data 替换, error = None |
| **E11d**: UPDATE_PRECOND_FAIL | R6/R7 (NORMAL, status≠FAILED) | 目标 data_id = "" (d1) 或 ID 解析失败 (d2) | 目标 → R22 (UPDATE, PRECONDITION_FAILED) | error = "目标缺少 data_id" 或 "依赖 ID 未解析" |
| **E11e**: UPDATE_SKIP_FAILED | R8 (NORMAL, FAILED) | status = FAILED | R8 不变 | 保护上次的 error 和 FAILED 状态，不做任何修改 |
> **代码**: `_add_create_action()` · `_add_update_action()`
---
#### 📡 阶段 3：Sync（物理同步）
**状态转换图：**
```
[R14] NORMAL, CREATE, PENDING [R18] NORMAL, UPDATE, PENDING
│ │
└───────────────┬───────────────────┘
│
├── E12 (API 成功) ──────▶ [R16] CREATE,SUCCESS / [R20] UPDATE,SUCCESS
├── E13 (API 失败) ──────▶ [R17] CREATE,FAILED / [R21] UPDATE,FAILED
├── E16 (Handler 跳过) ──▶ [R23] CREATE, SKIPPED
├── E17 (Handler 降级) ──▶ [R6] NORMAL, NONE, PENDING (仅 UPDATE)
│
└── E14 (异步提交) ──────▶ [R15] CREATE,IN_PROGRESS / [R19] UPDATE,INP
│
├── (轮询成功) ──▶ [R16] / [R20] SUCCESS
└── E15 (超时) ──▶ [R17] / [R21] FAILED
```
**转换表：**
| 事件 | 起始状态 | 判断条件 (Guard) | 结束状态 | 副作用 |
|------|---------|-----------------|---------|--------|
| **E12**: SYNC_OK | R14 或 R18 | Handler API 返回 SUCCESS | R16 (CREATE) 或 R20 (UPDATE) | error → None; data_id 回填 (CREATE); origin_data 更新 (UPDATE) |
| **E13**: SYNC_FAIL | R14 或 R18 | Handler API 返回 FAILED | R17 (CREATE) 或 R21 (UPDATE) | error = Handler 返回的错误信息 |
| **E14**: SYNC_ASYNC | R14 或 R18 | Handler API 返回 IN_PROGRESS | R15 (CREATE) 或 R19 (UPDATE) | 记录 task_id, 进入轮询队列 |
| **E15**: SYNC_TIMEOUT | R15 或 R19 | 轮询次数 > max_retries | R17 (CREATE) 或 R21 (UPDATE) | error = "Async task timeout after N seconds" |
| **E16**: HANDLER_SKIP | R14 或 R18 | Handler API 返回 SKIPPED | R23 (CREATE,SKIPPED) | error → None |
| **E17**: HANDLER_DOWNGRADE | R18 (仅 UPDATE) | Handler 运行时发现无实际变更字段 | R6 (NORMAL, NONE, PENDING) | action: UPDATE → NONE; 不提交 API; 统计列从 update 移入 none |
> **代码**: `BaseDataSource._handle_task_result()` · `_poll_async_tasks()` · `domain/*/api_handler.py`
---
## §4 终态分类与死胡同
### §4.1 终态分类
| 分类 | 状态 | (binding_status, action, status) | 语义 | 下一轮行为 |
|------|------|------|------|---------|
| ✅ 成功 | R16 | (NORMAL, CREATE, SUCCESS) | 创建成功 | →R2→bind→R7→update 检查 |
| ✅ 成功 | R20 | (NORMAL, UPDATE, SUCCESS) | 更新成功 | →R2→bind→R7→update 检查 |
| ❌ 失败 | R17 | (NORMAL, CREATE, FAILED) | 创建失败 | E02 zombie 判定→删除节点→对方回到 R9 重建 |
| ❌ 失败 | R21 | (NORMAL, UPDATE, FAILED) | 更新失败 | →R3→bind→R8→FAILED 保护(E11e)→保持 |
| 🔒 阻断 | R11 | (ABNORMAL, NONE, \*) | 数据损坏 | 每轮重新 bind 检查; 需人工修复数据 |
| 🔒 阻断 | R12 | (WARNING, NONE, \*) | 多候选/对方异常 | 每轮重新 bind 检查; 需人工绑定或修复 |
| 🔒 阻断 | R13 | (DEPENDENCY_ERROR, NONE, PENDING) | 依赖不满足 | 每轮重新检查依赖; 依赖修复后自动恢复 |
| ⏭ 跳过 | R23 | (NORMAL, CREATE, SKIPPED) | Handler 跳过创建 | →R4→bind→R6→update 检查（无绑定则再 create） |
| 🔄 异步 | R15 | (NORMAL, CREATE, IN\_PROGRESS) | 创建异步中 | 轮询直到 SUCCESS 或超时→FAILED |
| 🔄 异步 | R19 | (NORMAL, UPDATE, IN\_PROGRESS) | 更新异步中 | 轮询直到 SUCCESS 或超时→FAILED |
| 🔄 前置失败 | R22 | (NORMAL, UPDATE, PRECONDITION\_FAILED) | 前置条件不满足 | →R5→bind→R6/R7→update 重试 |
### §4.2 恢复路径
```
R17 (CREATE, FAILED):
持久化 → 下轮 E01 → 瞬态(UNCHECKED, CREATE, FAILED)
→ E02: action=CREATE ∧ (status=FAILED ∨ data_id="") → 满足 zombie 条件
→ 删除节点 + 解除绑定
→ 对方节点回到 R9 (MISSING) → 重新进入 create 流程
R21 (UPDATE, FAILED):
持久化 → 下轮 E01 → 瞬态(UNCHECKED, UPDATE, FAILED)
→ E02: action=UPDATE ≠ CREATE → 非 zombie，存活
→ E03: action → NONE → R3 (UNCHECKED, NONE, FAILED)
→ bind → R8 (NORMAL, NONE, FAILED)
→ E11e: FAILED 保护 → 跳过 update → 保持 R8
⚠ 需人工清除 FAILED 才能恢复
R22 (UPDATE, PRECONDITION_FAILED):
持久化 → 下轮 E01 → 瞬态(UNCHECKED, UPDATE, PRECONDITION_FAILED)
→ E02: action=UPDATE ≠ CREATE → 非 zombie，存活
→ E03: action → NONE → R5 (UNCHECKED, NONE, PRECONDITION_FAILED)
→ bind → R6/R7 (NORMAL) → update 流程重试
R11 (ABNORMAL):
每轮 E01 重置 → bind 重新检查
→ 若数据被人工修复 → E04 → R6/R7/R8 (NORMAL)
→ 若数据仍损坏 → 再次 R11
R12 (WARNING):
每轮 E01 重置 → bind 重新检查
→ 若人工建立了绑定 → E04 → R6/R7 (NORMAL)
→ 若对方数据被修复 → E04 → R6/R7 (NORMAL)
R13 (DEPENDENCY_ERROR):
每轮 E01 重置 → bind 重新检查依赖
→ 依赖节点达到 NORMAL 且 data_id 非空后
→ E07 通过 → 继续 auto_bind 或 create 流程
```
### §4.3 FAILED 保护机制详解
FAILED 保护确保失败节点不会被后续流程静默覆盖，保留 error 信息供人工调查。
```
进入条件:
节点经过 bind 后为 R8 (NORMAL, NONE, FAILED)
即: 绑定关系正常，但上一轮执行失败
保护行为:
strategy._add_update_action() 中:
if source.status == SyncStatus.FAILED:
skip (→ 事件 E11e)
结果: R8 原样保持 → 持久化 → 下一轮依然 R8
解除条件 (需人工介入):
1. 清除 error 字段 (→ None)
2. 将 status 改为 PENDING 或 SUCCESS
3. 下轮 bind 后 → R6 或 R7 → 正常进入 update 流程
```
---
## §5 完备性分析
### §5.1 状态 × 事件矩阵
行 = 当前状态，列 = 可能触发的事件。`→Rx` = 转换到目标状态，`—` = 不可能触发。
| 状态 | E01 | E02 | E03 | E04/E05 | E06~E10 | E11a/b | E11c/d/e | E12~E17 |
|------|-----|-----|-----|---------|---------|--------|----------|---------|
| R1~R5 | — | — | — | →R6~R13 | — | — | — | — |
| R6/R7 | →瞬态 | — | — | — | — | — | →R18/R22 | — |
| R8 | →瞬态 | — | — | — | — | — | →R8(skip) | — |
| R9 | →瞬态 | — | — | — | →R6/R11~R13 | →R6+R14/R13 | — | — |
| R11~R13 | →瞬态 | — | — | — | — | — | — | — |
| R14 | →瞬态 | — | — | — | — | — | — | →R15~R17/R23 |
| R15 | →瞬态 | — | — | — | — | — | — | →R16/R17 |
| R18 | →瞬态 | — | — | — | — | — | — | →R6/R19~R21/R23 |
| R19 | →瞬态 | — | — | — | — | — | — | →R20/R21 |
| R16/R17 | →瞬态 | — | — | — | — | — | — | — |
| R20~R23 | →瞬态 | — | — | — | — | — | — | — |
> **读表方式**: 找到当前状态行和事件列组的交叉点，即可得到目标状态。`—` 表示该状态不可能触发该事件。
### §5.2 已知 GAP
| GAP | 描述 | 风险 | 建议 |
|-----|------|------|------|
| GAP-1 | `set_binding_status()` / `set_action()` / `set_status()` 是纯 setter，不验证转换合法性 | 中 | 加入前置断言：检查 (当前状态, 新状态) 是否匹配某条已知转换 |
| GAP-2 | INV-1 ~ INV-10 未在代码中 assert | 中 | 每次 setter 调用后或阶段结束时断言所有不变量 |
| GAP-3 | R22 (PRECONDITION\_FAILED) 节点下一轮行为路径需验证 | 低 | 已补充恢复路径: R22→E01→E03→R5→bind→R6/R7→update 重试 |
| GAP-4 | Handler 降级 (E17) 后 status 残留为 PENDING 但 action 已清零 | 低 | 可考虑降级时同时重置 status 为 SUCCESS（当前保持 PENDING） |
| GAP-5 | 物理同步后缺少整体一致性检查 (post-sync invariant check) | 低 | 在 `sync_all()` 结束后遍历所有节点验证 INV-1 ~ INV-10 |
---
## §6 引用
| 文档 | 路径 |
|------|------|
| 枚举定义 | `sync_system_new/common/types.py` |
| 决策引擎 | `sync_system_new/sync_system/decision.py` |
| 重置策略 | `sync_system_new/common/state_reset.py` |
| 同步策略 | `sync_system_new/sync_system/strategy.py` |
| 物理同步 | `sync_system_new/datasource/datasource.py` |
| ID 解析 | `sync_system_new/sync_system/resolve_ids.py` |
| 节点生命周期(叙事) | [节点生命周期状态转移](./节点生命周期状态转移.md) |
docs/archive/docs/编排流程规范.md
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# 同步编排流程规范 (Pipeline Specification)
本文档定义了完整的同步编排流程，包括各阶段的职责、节点状态转换和检查点。
> **详细的状态定义和转换规则，请参考**: [STATE_DEFINITIONS.md](../sync_system/STATE_DEFINITIONS.md)
---
## 流程概览
同步系统的完整执行流程分为 5 个阶段：
```
┌─────────────────────────────────────────────────────────────┐
│ Stage 0: 初始化 (Initialization) │
├─────────────────────────────────────────────────────────────┤
│ - 创建 Collection (Local/Remote) │
│ - 创建 BindingManager │
│ - 注册 SyncStrategy (各业务类型) │
│ - 创建 DataSource (Local/Remote) │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Stage 1: 数据加载 (Data Loading) │
├─────────────────────────────────────────────────────────────┤
│ 节点状态: binding_status=UNCHECKED, action=NONE, status=PENDING │
│ - Persistence.load_nodes() → 从持久化恢复 │
│ - DataSource.load_all() → 从数据源加载 │
│ - BindingManager.load_bindings() → 加载绑定关系 │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Stage 2 & 3: 策略执行与同步 (按 node_type 顺序) │
├─────────────────────────────────────────────────────────────┤
│ For each node_type in sync_order: │
│ ┌─────────────────────────────────────────────────┐ │
│ │ 2.1 bind() → 绑定判定 │ │
│ │ 2.2 create() → 设置 CREATE action │ │
│ │ └─ 内联 ID 解析 + 前置检查 │ │
│ │ 2.3 Commit Creates → 立即同步 CREATE 节点 │ │
│ │ └─ DataSource.sync_all(poll_async=True) │ │
│ │ 2.4 update() → 设置 UPDATE action │ │
│ │ └─ 内联 ID 解析 + 前置检查 │ │
│ │ 2.5 Commit Updates → 立即同步 UPDATE 节点 │ │
│ │ └─ DataSource.sync_all(poll_async=True) │ │
│ └─────────────────────────────────────────────────┘ │
│ │
│ 说明： │
│ - 每个 node_type 完整同步后才处理下一个（保证依赖顺序） │
│ - commit 操作内部包含异步轮询，无需独立轮询阶段 │
│ - sync_all() 自动过滤 action=CREATE/UPDATE 的节点 │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Stage 4: 同步结果报告 (Summary Report) │
├─────────────────────────────────────────────────────────────┤
│ - 打印同步结果摘要 │
│ * 节点统计（按 action/status 分类） │
│ * 绑定关系统计 │
│ * 异常节点检查（data_id 缺失、绑定缺失等） │
│ - 收集统计信息（成功/失败/残留问题） │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Stage 5: 状态持久化 (State Persistence) │
├─────────────────────────────────────────────────────────────┤
│ - Collection.persist() → 保存节点状态 │
│ - BindingManager.persist() → 保存绑定关系 │
└─────────────────────────────────────────────────────────────┘
↓
【流程完成】
```
---
## 各阶段节点状态
### Stage 0: 初始化
**输出**: 所有组件实例化完成。
---
### Stage 1: 数据加载
**节点状态**:
```python
binding_status = BindingStatus.UNCHECKED # 未判定
action = SyncAction.NONE # 无动作
status = SyncStatus.PENDING # 待处理
data_id = <从数据源加载> # 已有业务ID
origin_data = <从数据源加载> # 原始数据快照
data = <从数据源加载> # 当前数据
depend_ids = <从数据源加载> # 依赖节点列表
```
**关键点**:
- `data_id` 在加载时**必定有值**（来自数据源）
- 只有待创建的新节点 `data_id` 才可能为 ""（空字符串）
- 从持久化恢复时应重置所有 `action` 为 `NONE`
- `binding_status` 初始值是 `UNCHECKED`，不是 `None`
---
### Stage 2.1: Bind (状态判定)
**状态转换**: `binding_status: UNCHECKED → NORMAL/MISSING/ABNORMAL/WARNING/DEPENDENCY_ERROR`
**可能的结果状态**:
| 结果状态 | 含义 | 占比 |
|---------|------|-----|
| **NORMAL** | 有绑定，数据健康 | 大部分 |
| **MISSING** | 无绑定，孤儿节点 | 少量 |
| **ABNORMAL** | 有绑定，自身数据损坏 | 极少 |
| **WARNING** | 有绑定，对方数据损坏 | 极少 |
| **DEPENDENCY_ERROR** | 依赖未满足 | 少量 |
**详细规则**: 参考 [STATE_DEFINITIONS.md § 1-3](../sync_system/STATE_DEFINITIONS.md)
**补充约束**:
- 若依赖节点 `binding_status = NORMAL` 但 `data_id` 为空（含 `status = FAILED`），视为依赖阻断。
- 只要依赖节点已回填 `data_id`，即使其 `status = FAILED`，后续类型仍允许进入 Create/Update。
- 自动绑定只在**业务键完整且唯一**时才尝试：
- 若业务键字段缺失（如 `serial_number = null`），设置 `binding_status = WARNING`，并在 `node.error` 记录原因：`Auto-bind skipped: missing fields ...`。
- 若同一业务键出现多对多/多对一，设置 `binding_status = WARNING`，并在 `node.error` 记录原因：`Auto-bind skipped: ambiguous candidates`。
- 以上情况仅记录 **Warning**，不进行自动绑定。
---
### Stage 2.2: Create (孤儿处理)
**状态转换**: `action: NONE → CREATE` (对 MISSING 节点)
**补充约束**:
- `binding_status = WARNING` 的节点不会进入 CREATE（`create()` 只查找 MISSING 节点）
- 创建时会通过 `IDResolver.resolve_and_validate()` 二次验证依赖 ID，失败则设置 `DEPENDENCY_ERROR`
**副作用**:
- 在对方 Collection 创建新节点
- 新节点的 `binding_status = NORMAL, action = CREATE, data_id = ""`
- 建立绑定记录
- 原 MISSING 节点也变为 `NORMAL`
**示例**:
```
Before:
local_node: binding_status=MISSING, action=NONE
After Create:
local_node: binding_status=NORMAL, action=NONE
remote_node (新建): binding_status=NORMAL, action=CREATE, data_id=""
绑定记录: local_id ↔ remote_temp_id
```
---
### Stage 2.3: Update (差异同步)
**状态转换**: `action: NONE → UPDATE` (对 NORMAL 且有差异的节点)
**前提条件**:
- `binding_status = NORMAL`
- `status != FAILED`（保护上次失败的状态和错误信息）
- `compute_diff()` 判定有差异
- 配置的 `update_direction` 决定哪一方节点设置 UPDATE
**内联检查**：
- 目标节点 `data_id` 为空 → `status = PRECONDITION_FAILED`
- `IDResolver.resolve_and_validate()` 失败 → `status = PRECONDITION_FAILED`
- Handler 校验后无实际变更字段 → `action` 降级为 `NONE`（不提交）
---
### Stage 2 & 3: 策略执行与同步
**执行顺序**: 按 `sync_order` 顺序逐个处理 node_type
**单个 node_type 的完整流程**:
```
For node_type in sync_order:
┌─────────────────────────────────────────────┐
│ 2.1 Bind - 绑定判定 │
│ - 设置 binding_status: NORMAL/MISSING/... │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ 2.2 Create - 创建策略 │
│ - 处理 MISSING 节点，设置 action=CREATE │
│ - 内联 ID 解析验证 (resolve_and_validate) │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ 2.3 Commit Creates - 立即同步 CREATE │
│ - DataSource.sync_all(poll_async=True) │
│ - 自动过滤 action=CREATE 的节点 │
│ - 内部包含异步轮询（IN_PROGRESS→SUCCESS）│
│ - ⭐ 执行 data_id 回填和绑定更新 │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ 2.4 Update - 更新策略 │
│ - 处理差异节点，设置 action=UPDATE │
│ - 内联 ID 解析验证 + data_id 检查 │
│ - FAILED 节点自动跳过 │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ 2.5 Commit Updates - 立即同步 UPDATE │
│ - DataSource.sync_all(poll_async=True) │
│ - 自动过滤 action=UPDATE 的节点 │
│ - 内部包含异步轮询（IN_PROGRESS→SUCCESS）│
└─────────────────────────────────────────────┘
↓
下一个 node_type
```
**关键特性**:
1. **按类型顺序**: 每个 node_type 完全同步后才处理下一个（保证依赖顺序）
2. **立即提交**: create/update 后立即同步，不等待所有策略执行完
3. **内置轮询**: `sync_all(poll_async=True)` 内部自动轮询异步任务
4. **data_id 回填**: CREATE 成功后立即回填 data_id，下游依赖可用
**同步状态转换**:
**同步接口（一步式）**:
```
action=CREATE, API 成功 → status=SUCCESS, data_id=<远程ID>
action=CREATE, API 失败 → status=FAILED, error=<错误信息>
action=UPDATE, API 成功 → status=SUCCESS
action=UPDATE, API 失败 → status=FAILED, error=<错误信息>
action=NONE → status=PENDING (不执行)
```
**异步接口（两步式，内置轮询）**:
```
action=CREATE, 提交成功 → status=IN_PROGRESS, task_id=<任务ID>
status=IN_PROGRESS, 轮询中... → status=IN_PROGRESS (保持)
status=IN_PROGRESS, 轮询成功 → status=SUCCESS, data_id=<远程ID>
status=IN_PROGRESS, 轮询失败 → status=FAILED, error=<错误信息>
status=IN_PROGRESS, 超时 → status=FAILED, error="Timeout"
```
**关键副作用**（由 DataSource 在 sync_all 中执行）:
- CREATE 成功: `data_id` 从 "" 更新为远程分配的 ID，并回写 `data` 主键字段
- CREATE 成功: 绑定记录从临时ID更新为真实ID
- UPDATE 成功: `origin_data` 更新为当前 `data`
- DELETE 成功: 移除绑定记录
**skip_sync 处理**:
- 如果 `strategy.skip_sync = True`，跳过 create/update/commit 步骤
- bind 步骤始终执行（用于状态判定）
**详细规则**: 参考 [STATE_DEFINITIONS.md § 5](../sync_system/STATE_DEFINITIONS.md)
---
### Stage 4: 同步结果报告
**目标**: 打印同步结果摘要，帮助用户了解同步情况
**报告内容**:
1. **节点统计**：按 node_type 统计各种 action/status 的节点数量
2. **绑定关系**：每个 node_type 的绑定记录数
3. **异常检查**：扫描并报告异常情况：
- CREATE 成功但 data_id 为空（DataSource 回填失败）
- CREATE 成功但绑定记录缺失
- UPDATE/CREATE 失败的节点及错误原因
**输出示例**:
```
================================================================================
📊 Local Collection Summary
================================================================================
Node Type Bindings Create Update Delete None Total
--------------------------------------------------------------------------------
project 5/5 0(0/0/0) 2(2/0/0) 0(0/0/0) 3 5(5/0/0)
contract 10/12 2(2/0/0) 5(5/0/0) 0(0/0/0) 5 12(12/0/0)
```
**注意**: 此阶段不修改任何状态，仅作为信息展示。
---
### Stage 5: 状态持久化
**持久化内容**:
- `binding_status`, `action`, `status` 的最终值
- `data_id` (可能在 CREATE 后更新)
- `error` (如果失败)
- 绑定关系的完整映射
---
## 错误处理策略
| 阶段 | 失败类型 | 处理策略 |
|------|---------|---------|
| Stage 0 | 初始化失败 | **终止流程**，抛出异常 |
| Stage 1 | 数据加载失败 | **终止流程**，抛出异常 |
| Stage 2 & 3 | 代码异常 | **终止流程**，抛出异常 |
| Stage 2: create/update 内联检查 | 依赖ID未解析、data_id缺失 | **继续流程**，节点标记为 DEPENDENCY_ERROR 或 PRECONDITION_FAILED |
| Stage 2 & 3 | API 调用失败 | **继续流程**，标记节点 FAILED |
| Stage 4 | - | 总是继续，仅作为报告 |
| Stage 5 | 持久化失败 | **记录错误**，不影响内存状态 |
---
## 节点状态完整时间线
```
┌──────────────┬─────────────┬────────┬────────┬─────────┐
│ 阶段 │ binding_ │ action │ status │ data_id │
│ │ status │ │ │ │
├──────────────┼─────────────┼────────┼────────┼─────────┤
│ 数据加载 │ UNCHECKED │ NONE │PENDING │ 已加载 │
│ Bind │ NORMAL/... │ NONE │PENDING │ 已加载 │
│ Create │ NORMAL │ CREATE │PENDING │ ""* │
│ Commit Create│ NORMAL │ CREATE │SUCCESS │ 远程ID** │
│ Update │ NORMAL │ UPDATE │PENDING │ 已加载 │
│ Commit Update│ NORMAL │ UPDATE │SUCCESS │ 已加载 │
└──────────────┴─────────────┴────────┴────────┴─────────┘
* 新创建的节点 data_id 初始为 ""
** CREATE 成功后 data_id 立即更新为远程分配的ID，下游依赖可用
```
---
## 配置驱动的流程控制
### 跳过某些阶段
```python
pipeline_config = {
"skip_bind": False, # 是否跳过 bind
"skip_create": False, # 是否跳过 create
"skip_update": False, # 是否跳过 update
"skip_post_check": False, # 是否跳过同步后检查
"fail_on_warning": False, # Pre-Check 时是否将 WARNING 视为失败
}
```
> **注意**：`skip_pre_check` 已移除，原 `_pre_commit_check` 逻辑已内联到 create/update 方法中。
```
### 策略预设应用
```python
# 首次同步：启用自动绑定，双向创建
for strategy in strategies:
strategy.apply_preset("first_sync")
# 日常同步：仅推送更新
for strategy in strategies:
strategy.apply_preset("push_only")
```
---
## 幂等性保证
**要求**: 同一个 Collection 的多次同步应该是幂等的。
**设计保证**:
1. **Bind 阶段**: 基于绑定记录判定，已绑定节点不会重复绑定
2. **Create 阶段**: 已有绑定的节点 (NORMAL) 不会重复创建
3. **Update 阶段**: 基于 `compute_diff()` 判定，无差异则不执行
4. **Sync 阶段**: `action=NONE` 的节点跳过执行
**前提条件**:
- 绑定记录正确持久化
- 节点的 `binding_status` 正确保存和加载
- `compute_diff()` 逻辑准确
---
## 监控和日志
### 关键指标
| 指标 | 含义 | 阶段 |
|------|------|-----|
| `nodes_loaded` | 加载的节点总数 | Stage 1 |
| `nodes_normal` | NORMAL 状态节点数 | Stage 2.1 |
| `nodes_missing` | MISSING 状态节点数 | Stage 2.1 |
| `nodes_abnormal` | ABNORMAL+WARNING 节点数 | Stage 2.1 |
| `nodes_dep_error` | DEPENDENCY_ERROR 节点数 | Stage 2.1 |
| `actions_create` | CREATE 动作节点数 | Stage 2.2 |
| `actions_update` | UPDATE 动作节点数 | Stage 2.3 |
| `sync_success` | 同步成功节点数 | Stage 3 |
| `sync_failed` | 同步失败节点数 | Stage 3 |
| `success_rate` | 成功率 (success/total) | Stage 4 |
### 日志级别
```
INFO: 流程阶段切换、统计信息
DEBUG: 节点级别的详细操作
WARN: 检查发现的警告、同步失败
ERROR: 检查发现的错误、致命异常
```
---
## 参考文档
- [STATE_DEFINITIONS.md](../sync_system/STATE_DEFINITIONS.md) - 详细的状态定义和转换规则
- [CHECK_SPEC.md](./CHECK_SPEC.md) - 检查点的实现细节和代码示例（可选）
# 1. 持久化 Collection
await local_collection.persist()
await remote_collection.persist()
# 2. 持久化 Binding
await binding_manager.persist()
```
**持久化内容**:
- 节点的 `binding_status`, `action`, `status`, `error`
- 节点的 `data_id`（可能在 CREATE 后更新）
- 绑定关系的完整映射
---
## 错误处理策略
### 各阶段的失败处理
| 阶段 | 失败原因示例 | 处理策略 |
|------|------------|---------|
| Stage 1: 数据加载 | 网络错误、文件缺失 | **终止流程**，抛出异常 |
| Stage 2.1: Bind | 代码bug | **终止流程**，抛出异常 |
| Stage 2.2-2.3: Create/Update | 代码bug | **终止流程**，抛出异常 |
| Stage 2: create/update 内联检查 | 依赖ID未解析、data_id缺失 | **继续流程**，节点标记为 DEPENDENCY_ERROR 或 PRECONDITION_FAILED |
| Stage 3: Physical Sync | API错误、权限不足 | **继续流程**，标记节点为 FAILED |
| Stage 4: Post-Sync Check | 部分节点同步失败 | **继续流程**，打印警告 |
| Stage 5: Persistence | 磁盘满、权限错误 | **记录错误**，但不影响内存状态 |
### 部分成功的处理
在 Stage 3 中，允许部分节点成功、部分失败：
- 成功的节点: `status = SUCCESS`
- 失败的节点: `status = FAILED`, `error = "错误信息"`
Post-Sync Check 会统计成功率并给出警告。
---
## 配置驱动的流程控制
### 跳过某些阶段
通过配置控制哪些阶段执行：
```python
pipeline_config = {
"skip_bind": False, # 是否跳过 bind
"skip_create": False, # 是否跳过 create
"skip_update": False, # 是否跳过 update
"skip_post_check": False, # 是否跳过同步后检查
"fail_on_warning": False, # 是否将 WARNING 也视为失败
}
```
### 策略预设应用
在 Stage 2 之前，可以应用策略预设：
```python
# 首次同步：启用自动绑定，双向创建
for strategy in strategies:
strategy.apply_preset("first_sync")
# 日常同步：仅推送更新
for strategy in strategies:
strategy.apply_preset("push_only")
```
---
## 监控和日志
### 关键指标
在各阶段收集以下指标：
| 指标 | 含义 |
|------|------|
| `nodes_loaded` | 加载的节点总数 |
| `nodes_bound` | 成功绑定的节点数 |
| `nodes_missing` | MISSING 状态的节点数 |
| `nodes_abnormal` | ABNORMAL/WARNING 状态的节点数 |
| `nodes_created` | CREATE 动作的节点数 |
| `nodes_updated` | UPDATE 动作的节点数 |
| `sync_success` | 同步成功的节点数 |
| `sync_failed` | 同步失败的节点数 |
| `errors_count` | 检查发现的 ERROR 数量 |
| `warnings_count` | 检查发现的 WARNING 数量 |
### 日志级别
```
INFO: 流程阶段切换、统计信息
DEBUG: 节点级别的详细操作
WARN: 检查发现的警告
ERROR: 检查发现的错误、异常
```
---
## 幂等性保证
**要求**: 同一个 Collection 的多次同步应该是幂等的。
**设计保证**:
1. **Bind 阶段**: 基于绑定记录判定状态，已绑定的节点不会重复绑定
2. **Create 阶段**: 已有绑定的节点（NORMAL）不会重复创建
3. **Update 阶段**: 基于 `compute_diff()` 判定，无差异则不执行
4. **Sync 阶段**: DataSource 根据 `action` 执行，`action=NONE` 的节点跳过
**前提条件**:
- Binding 记录正确持久化
- 节点的 `binding_status` 正确保存和加载
- `compute_diff()` 逻辑准确
---
## 下一步
详细的检查规范和状态转换规则，请参考：
- [CHECK_SPEC.md](./CHECK_SPEC.md) - 检查点详细规范
- [STATE_TRANSITIONS.md](./STATE_TRANSITIONS.md) - 状态转换表
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# 节点生命周期状态转移 (Node Lifecycle State Transitions)
本文档从一个**单节点视角**出发，完整描述一个 `SyncNode` 从诞生到持久化的全部状态变化。
> **代码映射**：
> - 持久化重置：`sync_system_new/common/state_reset.py` → `NodeStateReset`
> - 绑定判定：`sync_system_new/sync_system/decision.py` → `SyncDecisionEngine`
> - 策略执行：`sync_system_new/sync_system/strategy.py` → `DefaultSyncStrategy`
> - ID 解析：`sync_system_new/sync_system/resolve_ids.py` → `IDResolver`
> - 物理同步：`sync_system_new/datasource/datasource.py` → `BaseDataSource`
> - Handler 降级：`sync_system_new/domain/*/api_handler.py`
---
## 状态字段一览
| 字段 | 类型 | 含义 | 谁负责设置 |
|------|------|------|-----------|
| `binding_status` | BindingStatus | 绑定健康状态 | Strategy.bind() |
| `action` | SyncAction | 待执行动作 | Strategy.create() / update() |
| `status` | SyncStatus | 执行结果状态 | DataSource.sync_all() |
| `data_id` | str | 业务主键ID | 数据加载 / DataSource 回填 |
| `error` | str \| None | 错误信息 | 各阶段 |
---
## 完整生命周期
### 第一次运行（无持久化数据）
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ 节点尚不存在 │
└─────────────────────────────────────────────────────────────────────────────┘
│
数据源加载 (Stage 1)
│
▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ 节点诞生 │
│ │
│ binding_status = UNCHECKED ← Collection 创建节点时的初始值 │
│ action = NONE │
│ status = PENDING │
│ data_id = "abc-123" ← 从数据源获取的业务主键 │
│ data = {...} ← 从数据源获取的业务数据 │
│ origin_data = {...} ← 同上，原始快照 │
│ depend_ids = [] ← 空，待 bind 阶段填充 │
│ error = None │
└─────────────────────────────────────────────────────────────────────────────┘
```
---
### 第二次及后续运行（有持久化数据）
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ 从持久化恢复（原始值） │
│ │
│ binding_status = NORMAL (上次值) │
│ action = UPDATE (上次值) │
│ status = SUCCESS (上次值) │
│ data_id = "abc-123" │
│ error = None (上次值) │
└─────────────────────────────────────────────────────────────────────────────┘
│
阶段1：加载时重置 (NodeStateReset)
│
▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ 阶段1重置后 │
│ │
│ binding_status = UNCHECKED ← 重置（每次重新判定） │
│ action = UPDATE ← 保留！（用于阶段2识别 CREATE 失败） │
│ status = SUCCESS ← 保留！（不自动重置） │
│ data_id = "abc-123" ← 不变 │
│ data = None ← 重置（等待数据源覆盖） │
│ origin_data = None ← 重置（等待数据源覆盖） │
│ error = None ← 清空（避免上次错误干扰） │
└─────────────────────────────────────────────────────────────────────────────┘
│
阶段2：CREATE 僵尸清理
(只影响 action=CREATE 且 status=FAILED 或 data_id="" 的节点)
│
▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ 阶段2清理后（正常节点） │
│ │
│ action = NONE ← 全部重置为 NONE，准备进入策略阶段 │
│ 其他字段不变 │
│ │
│ （若为 CREATE 僵尸节点：直接从 Collection 删除 + 解除绑定） │
└─────────────────────────────────────────────────────────────────────────────┘
│
数据源加载覆盖 (Stage 1 后半)
│
▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ 数据源加载后 │
│ │
│ data = {...} ← 数据源最新数据覆盖 │
│ origin_data = {...} ← 数据源最新数据覆盖 │
│ 其他字段不变 │
└─────────────────────────────────────────────────────────────────────────────┘
```
---
## Bind 阶段状态转移 (Stage 2.1)
Bind 分三个子阶段顺序执行，每个子阶段只修改 `binding_status`。
### Phase 1: 核心状态判定
> **代码**：`_phase_core_state()` → `SyncDecisionEngine.determine_core_status()`
```
输入：binding_status = UNCHECKED
┌─ 有绑定记录？
│
┌─────┤
│ YES │
│ └─── 本地数据 + 远程数据 都健康？
│ │
│ ┌────┴────┐
│ │ YES │ NO
│ ▼ ▼
│ NORMAL WARNING / ABNORMAL
│
│ NO
└──────────────► MISSING
```
| 输入条件 | binding_status 输出 |
|---------|-------------------|
| 有绑定，双方数据健康 | **NORMAL** |
| 有绑定，自身数据损坏 | **ABNORMAL** |
| 有绑定，对方数据损坏 | **WARNING** |
| 无绑定记录 | **MISSING** |
### Phase 2: 依赖检查
> **代码**：`_phase_dependency_check()` → `_check_dependencies_for_nodes()`
**仅处理 `binding_status = MISSING` 的节点**，其他状态跳过。
```
输入：binding_status = MISSING
┌─ 有配置 depend_fields？
│
┌─────┤
│ NO └──► 保持 MISSING（无依赖，直接通过）
│
│ YES ──► 逐一检查依赖节点：
│ │
│ ┌────┴────────────────────────┐
│ │ 全部依赖节点: │
│ │ - 存在？ ✅ │
│ │ - binding_status=NORMAL？ ✅ │
│ │ - data_id 非空？ ✅ │
│ └────┬────────────────────────┘
│ │
│ ┌────┴────┐
│ │ 全通过 │ 任一失败
│ ▼ ▼
│ MISSING DEPENDENCY_ERROR
│ + error = "依赖项不满足: ..."
│ + depend_ids 已填充
```
**副作用**：无论检查是否通过，都会填充 `node.depend_ids`。
### Phase 3: 自动绑定
> **代码**：`_phase_auto_binding()`
**仅处理 `binding_status = MISSING` 且依赖已通过的节点**。
```
输入：binding_status = MISSING
auto_bind = False?
└──► MISSING → WARNING（"跳过自动绑定，无法确认是否需要创建"）
auto_bind = True:
│
├─ 业务键字段缺失？
│ └──► MISSING → WARNING（"缺少业务键字段: ..."）
│
├─ 业务键中 ID 字段解析失败？
│ └──► MISSING → DEPENDENCY_ERROR（"业务键中的ID字段解析失败"）
│
├─ 去噪后 1:1 匹配？
│ └──► MISSING → NORMAL（执行自动绑定，建立绑定记录）
│
├─ N:0（无远程匹配）？
│ ├──► create_enabled = True → MISSING → NORMAL，并 spawn 目标 CREATE 节点（S06）
│ └──► create_enabled = False → MISSING → WARNING（孤儿且不允许自动创建，需人工处理）
│
└─ N:M / 多对多 / 多对一？
└──► MISSING → WARNING（"存在多个候选节点，无法自动绑定"）
```
### Bind 阶段结束后可能的状态
| binding_status | 后续可执行的操作 |
|---------------|----------------|
| **NORMAL** | UPDATE（如有差异）|
| **MISSING** | CREATE |
| **ABNORMAL** | 无（需人工） |
| **WARNING** | 无（阻止自动操作） |
| **DEPENDENCY_ERROR** | 无（等待依赖修复） |
---
## Create 阶段状态转移 (Stage 2.2)
> **代码**：`create()` → `_add_create_action()`
> **对齐说明（与状态机配置一致）**：
> - create_prepare 的入口仍是源节点 `binding_status = MISSING`。
> - 但当前配置下，`N:0 + create_enabled=true` 可以在自动绑定阶段直接把源节点转为 `NORMAL`，并 `emit spawn_target_node_state=S06`。
> - 因此“触发创建”的入口有两条：
> 1) auto_bind 分支（E08f）直接 spawn；
> 2) create_prepare 分支（E09b）在 create 检查成功后 spawn。
**仅处理 `binding_status = MISSING` 的节点**。
```
输入：源节点 binding_status = MISSING, action = NONE
┌─ 源节点数据为空？
│ └──► 跳过，记录日志
│
├─ IDResolver.resolve_and_validate() 失败？
│ └──► binding_status → DEPENDENCY_ERROR
│ error = "创建时依赖 ID 未解析: ..."
│
└─ 成功 ──► 在目标 Collection 创建新节点
│
├─ 源节点：
│ binding_status → NORMAL（"从本地创建到远程"）
│ action 不变（仍为 NONE）
│
└─ 新建目标节点：
binding_status = NORMAL
action = CREATE
status = PENDING
data_id = ""（待远程返回）
data = 已替换 ID 的数据副本
│
└─ 同时建立绑定记录：local_id ↔ remote_id
```
---
## Commit Creates — 物理同步 (Stage 2.3)
> **代码**：`DataSource.sync_all()` → Handler.create()
```
输入：action = CREATE, status = PENDING
┌─ Handler 执行 API 调用
│
├─ 同步 API 成功（200/201）
│ └──► status → SUCCESS
│ data_id = "remote-xyz"（远程分配的 ID 回填）
│ data["id"] = "remote-xyz"（主键字段回写）
│
├─ 异步 API 提交成功（202）
│ └──► status → IN_PROGRESS
│ context.task_id = "task-xxx"
│ │
│ └─ 轮询结果：
│ ├─ 成功 → status → SUCCESS, data_id 回填
│ ├─ 失败 → status → FAILED, error = "..."
│ └─ 超时 → status → FAILED, error = "Timeout"
│
└─ API 失败（4xx/5xx）
└──► status → FAILED
error = "远程操作失败: ..."
```
---
## Update 阶段状态转移 (Stage 2.4)
> **代码**：`update()` → `_add_update_action()`
> **对齐说明**：图里的 `E12a` 从 `S01` 出发并不矛盾。`S01` 约束的是“源节点”有 `data_id`；
> `E12a` 检查的是“目标节点”是否有 `data_id`（guard: `target_has_data_id=false`），两者不是同一个对象。
**过滤条件**：`binding_status = NORMAL` 且 `status != FAILED`
```
输入：源节点 binding_status = NORMAL, action = NONE
┌─ status == FAILED？
│ └──► 跳过（保护上次失败的状态和错误信息）
│
├─ 源节点数据为空？
│ └──► 跳过
│
├─ 通过绑定找不到目标节点？
│ └──► 跳过，记录日志
│
├─ 目标节点 data_id 为空？
│ └──► 目标节点 status → PRECONDITION_FAILED
│ （"目标节点缺少 data_id"）
│
├─ IDResolver.resolve_and_validate() 失败？
│ └──► 目标节点 action → UPDATE
│ 目标节点 status → PRECONDITION_FAILED
│ 目标节点 error = "依赖 ID 未解析: ..."
│
├─ _needs_update() 判定无差异？
│ └──► 跳过（不设置 action）
│
└─ 有差异 ──► 更新目标节点：
action → UPDATE
status → PENDING
data = 已替换 ID 的数据副本
error = None
```
---
## Commit Updates — 物理同步 (Stage 2.5)
> **代码**：`DataSource.sync_all()` → Handler.update()
```
输入：action = UPDATE, status = PENDING
┌─ Handler 构建 API 请求
│
├─ Handler 发现无实际变更字段
│ └──► action → NONE（Handler 降级，不提交 API）
│
├─ 同步 API 成功（200）
│ └──► status → SUCCESS
│
├─ 异步 API 提交成功（202）
│ └──► status → IN_PROGRESS → （轮询）→ SUCCESS / FAILED
│
└─ API 失败
└──► status → FAILED
error = "远程操作失败: ..."
```
---
## 持久化阶段 (Stage 5)
```
节点当前状态原样写入存储。
持久化字段：
✅ node_id, data_id, data, origin_data
✅ binding_status, action, status, error, context
❌ depend_ids（不持久化，下次 bind 时从 data 实时计算）
```
---
## 全景时间线表
下表展示**一个节点在典型场景中的状态变化**：
### 场景 A：首次创建（本地 → 远程）
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| 数据加载 | UNCHECKED | NONE | PENDING | "abc-123" | None |
| bind phase1 | **MISSING** | NONE | PENDING | "abc-123" | None |
| bind phase2 | MISSING | NONE | PENDING | "abc-123" | None |
| bind phase3 | MISSING | NONE | PENDING | "abc-123" | None |
| create | **NORMAL** | NONE | PENDING | "abc-123" | None |
| _(新建远程节点)_ | NORMAL | **CREATE** | PENDING | **""** | None |
| commit create | NORMAL | CREATE | **SUCCESS** | **"remote-456"** | None |
| 持久化 | NORMAL | CREATE | SUCCESS | "remote-456" | None |
### 场景 B：日常更新
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| 持久化恢复 | NORMAL→**UNCHECKED** | CREATE→保留 | SUCCESS→保留 | "abc-123" | 清空 |
| 阶段2 action重置 | UNCHECKED | **NONE** | SUCCESS | "abc-123" | None |
| 数据源覆盖 | UNCHECKED | NONE | SUCCESS | "abc-123" | None |
| bind phase1 | **NORMAL** | NONE | SUCCESS | "abc-123" | None |
| update 检测差异 | NORMAL | NONE | SUCCESS | "abc-123" | None |
| _(目标节点)_ | NORMAL | **UPDATE** | **PENDING** | "remote-456" | None |
| commit update | NORMAL | UPDATE | **SUCCESS** | "remote-456" | None |
### 场景 C：依赖阻断
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| 数据加载 | UNCHECKED | NONE | PENDING | "contract-789" | None |
| bind phase1 | **MISSING** | NONE | PENDING | "contract-789" | None |
| bind phase2 | **DEPENDENCY_ERROR** | NONE | PENDING | "contract-789" | "依赖项不满足: project_id: 状态=dep_err" |
| _(后续阶段不处理)_ | | | | | |
| 持久化 | DEPENDENCY_ERROR | NONE | PENDING | "contract-789" | "依赖项不满足..." |
### 场景 D：CREATE 失败 → 下次自动恢复
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| **第 1 次运行** | | | | | |
| create | NORMAL | CREATE | PENDING | "" | None |
| commit create 失败 | NORMAL | CREATE | **FAILED** | "" | "远程操作失败: 500" |
| 持久化 | NORMAL | CREATE | FAILED | "" | "远程操作失败: 500" |
| **第 2 次运行** | | | | | |
| 阶段1恢复 | **UNCHECKED** | CREATE | FAILED | "" | **None** |
| 阶段2僵尸清理 | _(节点被删除，绑定被解除)_ | | | | |
| 数据源重新加载 | UNCHECKED | NONE | PENDING | "" → 新 node_id | None |
| bind → create | 重新走首次创建流程 | | | | |
### 场景 E：UPDATE 失败 → 保留供人工处理
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| **第 1 次运行** | | | | | |
| update | NORMAL | UPDATE | PENDING | "remote-456" | None |
| commit update 失败 | NORMAL | UPDATE | **FAILED** | "remote-456" | "403 Forbidden" |
| 持久化 | NORMAL | UPDATE | FAILED | "remote-456" | "403 Forbidden" |
| **第 2 次运行** | | | | | |
| 阶段1恢复 | UNCHECKED | UPDATE | FAILED | "remote-456" | None |
| 阶段2 action重置 | UNCHECKED | **NONE** | **FAILED** | "remote-456" | None |
| bind | NORMAL | NONE | FAILED | "remote-456" | None |
| update 跳过 | _(status=FAILED，自动跳过)_ | | | | |
| 持久化 | NORMAL | NONE | FAILED | "remote-456" | None |
| _(需人工重置 status 后才能重新更新)_ | | | | | |
---
## 状态转换合法性约束
### binding_status 允许的转换
```
UNCHECKED → NORMAL (核心判定: 有绑定且健康)
UNCHECKED → MISSING (核心判定: 无绑定记录)
UNCHECKED → ABNORMAL (核心判定: 自身数据损坏)
UNCHECKED → WARNING (核心判定: 对方数据损坏)
MISSING → DEPENDENCY_ERROR (依赖检查: 父节点不满足)
MISSING → WARNING (自动绑定: 业务键缺失 / 多候选 / auto_bind=False)
MISSING → DEPENDENCY_ERROR (自动绑定: ID 字段解析失败)
MISSING → NORMAL (自动绑定: 1:1 成功)
MISSING → NORMAL (create: 源节点创建成功后)
MISSING → DEPENDENCY_ERROR (create: ID 解析失败)
```
> **注意**：当前 `SyncNode.set_binding_status()` 不做转换合法性校验【未实现】。
### action 允许的转换
```
NONE → CREATE (create: 新建目标节点)
NONE → UPDATE (update: 检测到差异)
UPDATE → NONE (Handler 降级: 实际无变更字段)
```
### status 允许的转换
```
PENDING → IN_PROGRESS (DataSource: 异步提交成功)
PENDING → SUCCESS (DataSource: 同步执行成功)
PENDING → FAILED (DataSource: 执行失败)
PENDING → SKIPPED (DataSource: 被跳过)
（常见于 CREATE/UPDATE：Handler 返回 SKIPPED（无可执行操作/业务条件不满足），对应状态机里的 E19→S13 或 E20→S14）
PENDING → PRECONDITION_FAILED (Strategy: 前置条件不满足)
IN_PROGRESS → SUCCESS (DataSource: 异步轮询成功)
IN_PROGRESS → FAILED (DataSource: 异步轮询失败/超时)
```
> **注意**：当前 `SyncNode.set_status()` 不做转换合法性校验【未实现】。
---
## 参考文档
- [状态定义规范](./状态定义规范.md) — 状态枚举和判定规则
- [持久化与人工介入规范](./持久化与人工介入规范.md) — 持久化重置策略
- [编排流程规范](./编排流程规范.md) — Pipeline 阶段定义
- [架构分层设计](./架构分层设计.md) — 各层职责
- [node_id_data_id_lifecycle](./node_id_data_id_lifecycle.md) — ID 生命周期
docs/archive/from_root_docs/README.md
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# Root docs migration note
本目录为从项目根目录 `docs/` 迁移过来的文档快照（全量复制，不跳过）。
目的：
- 保留原始设计背景与历史规范，便于在 `sync_state_machine` 目录内就地查阅；
- 与当前 `sync_state_machine/docs/` 的“现行实现文档”并存。
使用建议：
- 以 `sync_state_machine/docs/` 下现行文档（如 `state_machine.md`、`sync_flow.md`、`architecture.md`）作为运行时真义；
- 本目录文档作为历史参考来源，遇到冲突时以现行实现与状态机配置为准：
- `sync_state_machine/config/node_state_machine.yaml`
- `sync_state_machine/sync_system/strategy.py`
- `sync_state_machine/engine/semantics.py`
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# API DataSource 架构设计
## 架构总览
```
┌─────────────────────────────────────────────────────────────┐
│ Pipeline │
│ (同步流程编排) │
└───────────────────────────┬─────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ ApiDataSource │
│ (数据源协调层) │
│ │
│ - 持有 ApiClient 实例 │
│ - 注册和管理 Handler │
│ - 实现 load_all / execute_batch │
│ - 注入 api_client 到 Handler │
└───────────────────────────┬─────────────────────────────────┘
│
┌───────────────────┼───────────────────┐
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Handler │ │ Handler │ │ Handler │
│ Project │ │ Contract │ │ Material │
│ │ │ │ │ │
│ 业务逻辑层 │ │ 业务逻辑层 │ │ 业务逻辑层 │
└──────┬───────┘ └──────┬───────┘ └──────┬───────┘
│ │ │
└───────────────────┼───────────────────┘
│ 使用 self.api_client
▼
┌──────────────┐
│ ApiClient │
│ (HTTP 通信层) │
│ │
│ - 签名生成 │
│ - HTTP 请求 │
│ - Push Log │
└──────────────┘
```
**调用流程**：
1. Pipeline 创建 ApiDataSource，传入 base_url, uid, secret
2. ApiDataSource 内部创建 ApiClient 实例
3. ApiDataSource 注册各业务 Handler，并注入 api_client
4. Handler 使用 `self.api_client.get/post/put()` 发送请求
5. ApiClient 自动处理签名、push_log 查询、错误处理
**优势**：
- ✅ **职责清晰**：ApiClient（通信）、DataSource（协调）、Handler（业务）
- ✅ **避免循环依赖**：Handler → ApiClient（单向依赖）
- ✅ **易于测试**：ApiClient 可 mock，Handler 独立测试
- ✅ **易于扩展**：新业务只需实现 Handler
## 1. 问题分析：旧方案的复杂性
旧方案 `sync_system/datasource/api` 存在的问题：
1. **过度抽象**：引入了 `ApiDataSource` → `Repository` → `ResponseHandle` → `Cache` 多层封装，每个业务需要独立 Repository 类，Protocol 定义繁琐
2. **状态管理混乱**：缓存策略不清晰，ResponseHandle 封装异步结果但使用困难，缺少统一的 push_log 查询机制
3. **依赖关系困难**：Repository 之间互相传递引用，难以从 collection 获取已有数据
4. **API 路由分散**：每个 Repository 手动实现多个 update 方法，缺少自动路由机制
## 2. 新方案设计原则
- **简单直接**：Handler 直接调用 HTTP API，不过度封装
- **状态透明**：DataSource 统一管理 session、签名、push_log 查询
- **依赖清晰**：通过 collection 获取依赖数据，使用 context 存储额外信息
- **智能路由**：根据数据字段自动选择 API endpoint
## 3. 核心组件职责
### 3.1 ApiClient - HTTP 通信层
**职责**：
- 封装所有 HTTP 通信逻辑
- 管理 httpx.AsyncClient，维护连接池和 session
- 生成请求签名（timestamp, nonce, sign）
- 统一请求入口，自动注入 uid
- 批量 Push Log 查询
**核心方法**：
```python
class ApiClient:
def __init__(self, base_url: str, uid: str, secret: str):
self._client = httpx.AsyncClient()
self._base_url = base_url
self._uid = uid
self._secret = secret
async def request(self, method: str, url: str, **kwargs) -> httpx.Response
"""统一请求入口，自动签名"""
async def get(self, url: str, params: dict = None) -> httpx.Response
"""GET 请求"""
async def post(self, url: str, data: dict) -> httpx.Response
"""POST 请求，data 中已包含 push_id/biz_id（由 Handler 生成）"""
async def put(self, url: str, data: dict) -> httpx.Response
"""PUT 请求，data 中已包含 push_id/biz_id"""
async def delete(self, url: str, data: dict) -> httpx.Response
"""DELETE 请求，data 中已包含 push_id/biz_id"""
async def get_push_logs(self, push_ids: List[str]) -> Dict[str, dict]
"""批量查询 push_log 状态，返回 {push_id: push_log_data}
注意：单个查询也传单元素列表
当前实现：用 for 循环模拟，后续等后端实现批量接口
"""
def _generate_signature(self, params: dict) -> dict
"""生成签名参数（timestamp, nonce, sign）"""
```
### 3.2 ApiDataSource - 数据源协调层
**职责**：
- 持有 ApiClient 实例，提供给 Handler 使用
- 实现 DataSource 接口（load_all, sync_all）
- 协调多个 Handler 的执行顺序（通过 sync_all）
- Handler 内部负责：生成 push_id/biz_id、调用 poll 轮询、提取 created_id
- 统一异常处理和日志记录
**核心属性和方法**：
```python
class ApiDataSource(DataSource):
def __init__(self, base_url: str, uid: str, secret: str):
self.client = ApiClient(base_url, uid, secret)
self._handlers: Dict[str, BaseApiHandler] = {}
def register_handler(self, node_type: str, handler: BaseApiHandler):
"""注册业务 Handler"""
handler.api_client = self.client # 注入 client
self._handlers[node_type] = handler
async def load_all(self, collection: DataCollection, order: List[str]) -> None:
"""调用基类的 load_all，按顺序加载数据"""
async def sync_all(self, collection: DataCollection, order: List[str]) -> None:
"""调用基类的 sync_all，按顺序执行同步"""
```
### 3.3 BaseApiHandler - 业务逻辑基类
**职责**：
- 实现 Handler 接口（load, create, update, delete, poll）
- 使用 self.api_client 发送 HTTP 请求
- 生成 push_id 和 biz_id（业务标识）
- 从 collection 获取依赖节点数据
- 管理节点的 context（存储 project_id, contract_id 等）
- 实现 poll 方法，调用 api_client.get_push_logs 批量查询
- 提取 created_id（因为不同业务的 id 字段名和位置可能不同）
- 返回 TaskResult（SUCCESS/FAILED/IN_PROGRESS）
**核心方法**：
```python
class BaseApiHandler(NodeHandler):
def __init__(self):
self.api_client: ApiClient = None # 由 DataSource 注入
self.collection: DataCollection = None # 由 DataSource 注入
async def load(self, collection: DataCollection) -> List[dict]
async def create(self, node: SyncNode) -> TaskResult
async def update(self, node: SyncNode) -> TaskResult
async def delete(self, node: SyncNode) -> TaskResult
async def poll(self, node: SyncNode, task_id: str) -> TaskResult
def extract_created_id(self, push_log: dict) -> str
"""从 push_log 提取 created_id，子类可重写"""
# 重试逻辑（可选，子类可重写）
async def _execute_with_retry(self, operation, max_retries: int = 3) -> Any
"""通用重试逻辑，子类可自定义重试策略"""
```
**重试策略说明**：
- **重试在 Handler 内部**：create/update/delete 内部可调用 _execute_with_retry
- **返回给 DataSource**：最终只返回 SUCCESS/FAILED/IN_PROGRESS
- **灵活控制**：不同业务可重写 _execute_with_retry 实现自定义策略
- **默认策略**：网络错误/5xx 重试 3 次，4xx 不重试
**未实现 API 的处理**：
- 部分业务可能没有实现 create 或 delete API
- 此时 Handler 应在对应方法中直接返回 FAILED 状态，并在 error 中说明原因
- 示例：`return TaskResult(status=TaskStatus.FAILED, error="Create API not implemented for this business")`
### 3.4 具体业务 Handler
**职责**：
- 实现具体业务的 load 逻辑（调用 self.api_client.get()）
- 创建节点时设置 context
- 重写 API endpoint 选择逻辑（可选）
- 定制 created_id 提取逻辑（可选）
每个业务 Handler 位于 `sync_system_new/domain/{业务}/api_handler.py`
## 4. HTTP 请求状态管理
### 4.0 状态系统概述
**通用状态枚举**（适用于所有 DataSource）：
```python
class TaskStatus(Enum):
"""Handler 返回的任务执行状态"""
SUCCESS = "success" # 同步完成，立即成功
FAILED = "failed" # 同步失败
IN_PROGRESS = "in_progress" # 异步任务进行中
class SyncStatus(Enum):
"""SyncNode 的同步执行状态"""
PENDING = "PENDING"
IN_PROGRESS = "IN_PROGRESS"
SUCCESS = "SUCCESS"
FAILED = "FAILED"
SKIPPED = "SKIPPED"
PRECONDITION_FAILED = "PRECONDITION_FAILED"
```
**状态映射规则**：
- TaskStatus 是 Handler 执行操作后的返回值
- SyncStatus 是 SyncNode 的最终状态，由 DataSource 根据 TaskStatus 更新
- 普通 DataSource（FileDataSource）和 API DataSource 使用相同的状态枚举
- 区别在于：**API DataSource 的网络操作如何转化为 TaskStatus**
**重要说明：Load 阶段 vs 执行阶段的状态**：
- **Load 阶段**（Handler.load()）：从 API 拉取数据创建 SyncNode
- 此时节点状态为 `PENDING`（等待后续 bind/create/update）
- GET 请求失败不影响节点创建，只是该节点不存在于 collection
- **执行阶段**（Handler.create/update/delete）：执行同步操作
- DataSource 在调用前设置 `node.status = IN_PROGRESS`
- Handler 返回 TaskResult，DataSource 据此更新 node.status
- POST/PUT/DELETE 成功后才设置为 SUCCESS
**核心映射逻辑**（在 DataSource 中）：
```python
# 执行前：DataSource 设置状态
node.status = SyncStatus.IN_PROGRESS
# 调用 Handler（Handler 内部可能重试多次）
result = await handler.create(node)
# 执行后：DataSource 根据最终结果更新状态
if result.status == TaskStatus.SUCCESS:
node.status = SyncStatus.SUCCESS
node.data_id = result.data_id
elif result.status == TaskStatus.FAILED:
node.status = SyncStatus.FAILED
node.error = result.error
elif result.status == TaskStatus.IN_PROGRESS:
# 记录 task_id 等待轮询
async_tasks[node.node_id] = result.task_id
```
**重要**：Handler 负责重试，最终只返回确定的结果（SUCCESS/FAILED/IN_PROGRESS）
### 4.1 请求类型与状态流转
**API DataSource 的特殊性**：
- **Load 阶段**：GET 请求拉取数据，创建 PENDING 节点（失败则不创建节点）
- **执行阶段**：POST/PUT/DELETE 先设置 IN_PROGRESS，通过 poll() 轮询变为 SUCCESS/FAILED
#### Load 阶段 - 数据拉取
**目的**：从 API 获取数据，创建 SyncNode 放入 collection
| 阶段 | HTTP 操作 | 成功行为 | 失败行为 | 节点状态 |
|------|----------|---------|---------|---------|
| 1. 调用 load() | GET /api/list | 返回数据列表 | 返回空列表或抛异常 | - |
| 2. 创建节点 | - | 为每条数据创建 SyncNode | 不创建节点 | PENDING |
**代码示例**：
```python
async def load(self, collection: DataCollection) -> List[dict]:
"""加载数据 - GET 阶段不涉及状态转换"""
try:
response = await self.api_client.get("project/list")
if response.status_code == 200:
data_list = response.json().get("list", [])
# 返回数据，由 DataSource 创建 PENDING 节点
return data_list
else:
# 失败：返回空列表，不创建节点
logger.error(f"Load failed: {response.status_code}")
return []
except Exception as e:
logger.error(f"Load exception: {e}")
return [] # 或者抛出异常，由调用方处理
```
#### Mutation 请求（POST/PUT/DELETE） - 执行阶段
**状态变化时机**：
1. **执行前**：DataSource 设置 `node.status = IN_PROGRESS`
2. **Handler 执行**：内部可能重试，最终返回 SUCCESS/FAILED/IN_PROGRESS
3. **轮询完成**：poll() 返回 SUCCESS/FAILED
| 阶段 | Push Log | TaskStatus | SyncStatus | 说明 |
|------|---------|-----------|-----------|------|
| 执行前 | - | - | PENDING → IN_PROGRESS | DataSource 设置 |
| 提交 | pending | IN_PROGRESS | IN_PROGRESS | 任务已提交 |
| 轮询 | processing | IN_PROGRESS | IN_PROGRESS | 后端处理中 |
| 成功 | success | SUCCESS | SUCCESS | 同步完成 |
| 失败 | failed | FAILED | FAILED | 同步失败 |
**示例**：
```python
async def create(self, node: SyncNode) -> TaskResult:
"""Handler 内部可重试，最终返回确定结果"""
response = await self.api_client.post(url, node.data)
if response.status_code == 202:
return TaskResult.in_progress(task_id=response.json()["push_id"])
else:
return TaskResult.failed(error=f"HTTP {response.status_code}")
async def poll(self, node: SyncNode, task_id: str) -> TaskResult:
push_logs = await self.api_client.get_push_logs([task_id])
status = push_logs.get(task_id, {}).get("status")
if status == "success":
return TaskResult.success(data_id=self.extract_created_id(push_logs[task_id]))
elif status == "failed":
return TaskResult.failed(error="Backend processing failed")
else:
return TaskResult.in_progress(task_id=task_id)
```
### 4.2 状态转换完整流程
```
Load 阶段:
Handler.load() → 返回数据列表 → DataSource 创建 PENDING 节点
执行阶段（同步操作）:
DataSource: node.status = IN_PROGRESS
→ Handler.create() → TaskResult.success/failed()
→ DataSource: node.status = SUCCESS/FAILED
执行阶段（异步操作）:
DataSource: node.status = IN_PROGRESS
→ Handler.create() → TaskResult.in_progress(push_id)
→ DataSource 轮询: Handler.poll(push_id)
→ TaskResult.success/failed()
→ DataSource: node.status = SUCCESS/FAILED
```
**关键点**：
- Handler 负责重试，DataSource 只处理最终结果
- 不同业务可在 BaseApiHandler._execute_with_retry 中自定义重试策略
- FileDataSource 和 ApiDataSource 使用相同的状态枚举和转换逻辑
### 4.3 Push Log 状态机
```
pending → processing → success/failed
```
- 轮询间隔：0.5秒
- 超时：30秒
- 成功：提取 created_id
- 失败：获取 error_message
### 4.4 状态总结表
**Load 阶段（数据拉取）**：
| HTTP 操作 | 响应码 | 行为 | 创建节点 | 节点状态 | 说明 |
|---------|-------|-----|---------|---------|------|
| GET /list | 200 | 返回数据列表 | ✅ 是 | PENDING | 等待后续 bind/create/update |
| GET /list | 4xx/5xx | 返回空列表 | ❌ 否 | - | 不创建节点 |
**执行阶段（POST/PUT/DELETE）**：
| HTTP 操作 | 响应码 | Push Log | TaskStatus | SyncStatus | 说明 |
|---------|-------|---------|-----------|-----------|------|
| POST/PUT | 202 | pending | IN_PROGRESS | IN_PROGRESS | 异步开始 |
| - | - | processing | IN_PROGRESS | IN_PROGRESS | 异步处理中 |
| - | - | success | SUCCESS | SUCCESS | 异步成功 |
| - | - | failed | FAILED | FAILED | 异步失败 |
| - | - | timeout | FAILED | FAILED | 轮询超时 |
## 5. Context 机制
### 5.1 Context 的作用
Context 是 SyncNode 的字典字段，用于存储业务数据之外的上下文信息，例如：
- `project_id`: 当前对象所属的项目ID
- `contract_id`: 合同变更所属的合同ID
- `parent_id`: 父对象ID
- 其他 API 调用需要但 schema 中没有的信息
### 5.2 Context 使用流程
**场景：加载合同数据**
1. **Handler.load()** 从 self._collection 获取所有 project
2. 遍历每个 project，调用 `GET contract/list?project_id=xxx`
3. 为每个返回的 contract 数据添加临时标记 `_context = {"project_id": xxx}`
4. **Handler.create_node()** 创建 SyncNode 时，提取 `_context` 并设置到 `node.context`
5. **Handler.update()** 更新时，从 `node.context["project_id"]` 获取 project_id 并添加到请求数据
### 5.3 Context 传递规则
- 父 → 子：从依赖的父节点继承 context
- 横向传递：同级节点不共享 context
- 更新时使用：从 context 提取必要信息添加到请求 payload
## 6. 智能 API 路由
### 6.1 路由策略
根据节点数据的字段，自动选择正确的 API endpoint：
**方案1：字段匹配**
- 检查 node.data 中的字段集合
- 匹配预定义的 endpoint → required_fields 映射表
- 选择第一个匹配的 endpoint
**方案2：Schema 类型**
- 根据 node.schema 的类型
- 查找 schema_type → endpoint 映射表
**默认规则**：
- CREATE: `{node_type}`
- UPDATE: 子类重写 `_select_update_endpoint()`
- DELETE: `{node_type}`
### 6.2 Project 示例
Project 有多个更新接口：
- `project/key_constraints` - 需要字段：key_constraints, key_constraints_remark
- `project/complete_investment` - 需要字段：complete_investment
- `project/dynamic_investment` - 需要字段：dynamic_investment
- `project/plan_construction` - 需要字段：plan_construction_capacity, plan_construction_date
- ... 等
Handler 定义映射表，根据实际数据字段自动选择。
## 7. 依赖数据获取
### 7.1 获取模式
Handler 通过 `collection.filter(node_type="xxx")` 获取依赖数据：
**加载顺序**（按依赖关系）：
1. Project（无依赖）
2. Contract（依赖 Project）
3. Contract Change（依赖 Project + Contract）
### 7.2 数据流
```
Pipeline
→ 按拓扑序加载
→ ProjectHandler.load()
→ GET project/list
→ 创建 ProjectSyncNode
→ ContractHandler.load()
→ collection.filter(node_type="project")
→ 遍历 project，GET contract/list?project_id=xxx
→ 创建 ContractSyncNode，设置 context["project_id"]
→ ContractChangeHandler.load()
→ collection.filter(node_type="contract")
→ 遍历 contract，从 context 获取 project_id
→ GET contract_change/list?project_id=xxx&contract_id=yyy
→ 创建节点，设置 context
```
## 8. 实现计划
### Phase 1: HTTP 通信层
- 实现 **ApiClient** 类
- HTTP Client 封装（httpx.AsyncClient）
- 签名生成（_generate_signature）
- 统一请求方法（get/post/put/delete）
- **批量 Push Log 查询**（get_push_logs，单个也传列表）
- ~~wait_for_push_log~~（不实现，由 DataSource 调用 poll）
### Phase 2: DataSource 协调层
- 实现 **ApiDataSource** 类
- 持有 ApiClient 实例
- Handler 注册和管理
- 实现 DataSource 接口（load_all, execute_batch）
- 注入 api_client 到 Handler
- 实现轮询逻辑（_poll_async_tasks）
### Phase 3: Handler 基类
- 实现 **BaseApiHandler** 类
- load/create/update/delete/poll 方法
- 使用 self.api_client 发送请求
- **extract_created_id**（子类可重写）
- **_execute_with_retry**（可选，子类可重写重试策略）
- Context 管理
### Phase 4: 业务验证
- 实现 **ProjectApiHandler**（无依赖，简单场景）
- 实现 load：GET project/list
- 实现 create：POST project
- 实现 poll：查询 push_log
- 实现 **ContractApiHandler**（依赖 Project，验证 context）
- 实现 load：遍历 project，GET contract/list?project_id=xxx
- 设置 context["project_id"]
- 编写测试验证设计
### Phase 5: 完善功能
- 批量 Push Log 查询优化（等待后端实现批量接口）
- 超时控制（可配置）
- 请求日志和调试
### Phase 6: 推广
- 实现剩余业务 Handler
- 性能优化（并发控制）
- 文档和示例
## 9. 与现有系统集成
**调用关系**：
```
Pipeline
↓
ApiDataSource (持有 ApiClient)
↓
BaseApiHandler (使用 api_client)
↓
ApiClient (发送 HTTP 请求)
```
**职责分离**：
- **ApiClient**: 纯粹的 HTTP 通信，无业务逻辑
- **ApiDataSource**: 协调 Handler，管理执行流程
- **BaseApiHandler**: 业务逻辑，调用 ApiClient 完成网络操作
- **具体 Handler**: 实现特定业务的 load/create/update/delete
**优点**：
- ApiClient 和 Handler 解耦，避免循环依赖
- Handler 通过 self.api_client 访问 HTTP 功能
- DataSource 统一管理 ApiClient 生命周期
- Handler 内部灵活控制重试策略
## 10. 关键优势
1. **简化架构**：去掉 Repository 层，代码量减少 50%
2. **职责清晰**：
- ApiClient：HTTP 通信
- DataSource：协调和轮询
- Handler：业务逻辑和重试
3. **重试灵活**：Handler 内部实现，不同业务可自定义策略
4. **状态清晰**：Load 阶段创建 PENDING 节点，执行阶段明确状态转换
5. **批量优化**：Push Log 批量查询，减少 HTTP 请求
6. **易于扩展**：新业务只需实现 Handler，复用 Client 和 DataSource
7. **易于测试**：ApiClient 可 mock，Handler 独立测试
## 11. 设计改进总结
| 改进点 | 初始设计 | 最终设计 | 理由 |
|-------|---------|---------|------|
| Push Log 查询 | get_push_log(id) | get_push_logs([ids]) | 批量查询 |
| 轮询逻辑 | wait_for_push_log 在 Client | 移除，DataSource 调用 poll | 职责清晰 |
| created_id 提取 | 在 Client | 在 Handler 基类 | 业务差异 |
| 重试逻辑 | 在 DataSource | **在 Handler** | 业务灵活性 |
| Load 状态 | GET 成功 → SUCCESS | GET 成功 → PENDING | Load ≠ 同步完成 |
| 执行状态 | 不明确 | 执行前设置 IN_PROGRESS | 状态清晰 |
7. **易于测试**：ApiClient 可以 mock，Handler 单独测试业务逻辑
## 12. 使用示例
### 12.1 基本使用流程
```python
# 1. 创建 DataSource
datasource = ApiDataSource(
base_url="https://api.example.com",
uid="user123",
secret="secret_key"
)
# 2. 初始化（必须调用）
await datasource.initialize()
# 3. 注册 Handler
datasource.register_handler(ProjectApiHandler())
datasource.register_handler(ContractApiHandler())
# 4. 创建 Collection
collection = DataCollection()
# 5. 加载数据（自动处理异常，不会抛出）
await datasource.load_all(collection, order=["project", "contract"])
# 6. 执行同步（自动处理异常，不会抛出）
await datasource.sync_all(collection, order=["project", "contract"])
# 7. 关闭连接（必须调用）
await datasource.close()
```
### 12.2 异常处理说明
**设计原则**：
- ✅ **load_all 和 sync_all 不会抛出异常**
- ✅ **Handler 的 create/update/delete 捕获所有 HTTP 异常**
- ✅ **所有错误转换为状态（SyncStatus.FAILED）和错误信息（node.error）**
**为什么不需要 try-finally？**
```python
# ❌ 不需要这样做
try:
await datasource.load_all(collection, order=["project"])
finally:
await datasource.close()
# ✅ 直接调用即可
await datasource.initialize()
await datasource.load_all(collection, order=["project"]) # 内部已处理异常
await datasource.sync_all(collection, order=["project"]) # 内部已处理异常
await datasource.close()
```
**异常处理机制**：
1. **load_all 异常处理**：
```python
# 加载某个类型失败，记录错误但继续处理其他类型
for node_type in order:
try:
raw_items = await handler.load(collection)
# ... 创建节点
except Exception as e:
print(f"Error loading {node_type}: {e}")
# 继续处理下一个类型
```
2. **sync_all 异常处理**：
```python
# Handler 返回的异常已被捕获转为 TaskResult
for node in nodes:
try:
result = await handler.create(node) # Handler 内部捕获异常
# 根据 result.status 更新节点状态
except Exception as e:
# DataSource 的最后保护
node.status = SyncStatus.FAILED
node.error = str(e)
```
3. **Handler 异常处理**：
```python
async def create(self, node: SyncNode) -> TaskResult:
try:
# 生成参数
push_id = self._generate_push_id()
data = {..., "push_id": push_id, "biz_id": self._generate_biz_id(node)}
# 调用 API
response = await self.api_client.post("/api/v2/project", data)
# 返回成功
return TaskResult(status=TaskStatus.SUCCESS, data_id=response['data']['id'])
except httpx.HTTPStatusError as e:
# HTTP 错误（4xx, 5xx）
return TaskResult(status=TaskStatus.FAILED, error=f"HTTP {e.response.status_code}: {e}")
except httpx.NetworkError as e:
# 网络错误
return TaskResult(status=TaskStatus.FAILED, error=f"Network error: {e}")
except Exception as e:
# 其他异常
return TaskResult(status=TaskStatus.FAILED, error=f"Unexpected error: {e}")
```
### 12.3 Pipeline 集成示例
```python
async def sync_pipeline(datasource: ApiDataSource):
"""同步流程编排"""
# 初始化
await datasource.initialize()
# 创建 Collection
collection = DataCollection()
# 执行同步流程（所有错误都被内部处理）
await datasource.load_all(collection, order=["project", "contract", "material"])
await datasource.sync_all(collection, order=["project", "contract", "material"])
# 检查结果
failed_nodes = collection.filter(status=SyncStatus.FAILED)
if failed_nodes:
print(f"Failed nodes: {len(failed_nodes)}")
for node in failed_nodes:
print(f" - {node.node_type}:{node.node_id}: {node.error}")
# 清理
await datasource.close()
```
**关键点**：
- ✅ 不需要 try-except 包裹 load_all/sync_all
- ✅ 通过检查节点状态判断成功/失败
- ✅ 错误信息保存在 node.error 中
- ✅ Pipeline 专注于流程编排，不处理异常细节
docs/archive/from_root_docs/datasource_handler_architecture_v2.md
+518
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@@ -0,0 +1,518 @@
# DataSource + Handler 架构设计 V2
## 核心原则
### **职责分离**
```text
Strategy (业务逻辑层)
↓ 设置 action, 完成 ID 映射
DataSource (状态管理 + 编排层)
↓ 调用 Handler, 管理状态流转
Handler (纯执行层)
↓ 调用后端 API, 返回结果
Backend API
```
### **关键设计决策**
1. **ID 映射在 Strategy 完成** ✅
- `Strategy.create()` / `Strategy.update()` 时，已将依赖字段的本地 ID 替换为远程 ID
- DataSource 拿到的 `node.data` 已经是映射好的数据
- Handler 直接使用 `node.data`，不需要关心 ID 映射
2. **状态管理在 DataSource** ✅
- 所有 `node.status` 的转换由 DataSource 负责
- Handler 只返回 `TaskResult`（成功/失败/进行中）
- DataSource 根据 `TaskResult` 更新 `node.status`
3. **Handler 只负责执行** ✅
- 调用后端 API（load/create/update/delete）
- 返回执行结果（TaskResult）
- 提供异步任务轮询（poll_tasks）
- 提供数据质量检查（validate）
---
## Handler 接口设计
### **核心方法**
```python
class NodeHandler(Protocol[T]):
# ===== 数据加载 =====
async def load(self, collection: Optional[DataCollection] = None) -> List[Dict[str, Any]]:
"""
从后端加载全部数据
Args:
collection: Collection 上下文（可选，用于依赖查询）
Returns:
原始数据列表
示例：
# Contract Handler（依赖 Project）
async def load(self, collection=None):
# 从 collection 获取 project 列表
if collection:
projects = collection.filter(node_type="project")
project_ids = [p.data_id for p in projects if p.data_id]
else:
project_ids = []
# 只加载这些项目的合同
response = await self.api.get_contracts(project_ids=project_ids)
return response["data"]
"""
# ===== 数据操作 =====
async def create(self, node: SyncNode[T]) -> TaskResult:
"""
创建节点
注意：node.data 已经过 ID 映射，直接使用即可
Returns:
TaskResult:
- SUCCESS: 同步完成，返回 data_id
- IN_PROGRESS: 异步任务，返回 task_id
- FAILED: 失败，返回 error
示例：
# 同步接口
async def create(self, node):
try:
response = await self.api.create_contract(node.data)
return TaskResult.success(data_id=response["id"])
except Exception as e:
return TaskResult.failed(error=str(e))
# 异步接口
async def create(self, node):
try:
response = await self.api.submit_contract_async(node.data)
return TaskResult.in_progress(task_id=response["task_id"])
except Exception as e:
return TaskResult.failed(error=str(e))
"""
async def update(self, node: SyncNode[T]) -> TaskResult:
"""更新节点（同 create）"""
async def delete(self, node: SyncNode[T]) -> TaskResult:
"""删除节点（同 create）"""
# ===== 异步任务轮询 =====
async def poll_tasks(self, task_ids: List[str]) -> Dict[str, TaskResult]:
"""
批量轮询异步任务状态
Args:
task_ids: 任务 ID 列表
Returns:
{task_id: TaskResult} 字典
示例：
async def poll_tasks(self, task_ids):
response = await self.api.batch_query_tasks(task_ids)
results = {}
for task in response["tasks"]:
if task["status"] == "completed":
results[task["id"]] = TaskResult.success(
data_id=task["result"]["contract_id"]
)
elif task["status"] == "failed":
results[task["id"]] = TaskResult.failed(
error=task["error"]
)
else: # running
results[task["id"]] = TaskResult.in_progress(
task_id=task["id"]
)
return results
"""
# ===== 数据质量检查 =====
async def validate(self, data: Dict[str, Any]) -> ValidationResult:
"""
数据质量检查
Args:
data: 原始数据
Returns:
ValidationResult（是否有效 + 错误列表）
示例：
async def validate(self, data):
errors = []
if not data.get("code"):
errors.append("合同编码为空")
if not data.get("project_id"):
errors.append("项目 ID 为空")
return ValidationResult(
is_valid=len(errors) == 0,
errors=errors
)
"""
# ===== 辅助方法 =====
def extract_id(self, data: Dict[str, Any]) -> str:
"""从原始数据提取 ID"""
def create_node(self, data: Dict[str, Any]) -> SyncNode[T]:
"""从原始数据创建 SyncNode"""
```
### **TaskResult 设计**
```python
class TaskStatus(Enum):
SUCCESS = "success" # 同步完成
FAILED = "failed" # 失败
IN_PROGRESS = "in_progress" # 异步任务进行中
class TaskResult:
def __init__(
self,
status: TaskStatus,
data_id: Optional[str] = None, # 成功时返回的 ID
task_id: Optional[str] = None, # 异步任务 ID
error: Optional[str] = None, # 失败原因
metadata: Optional[Dict] = None # 其他元数据
):
...
@classmethod
def success(cls, data_id: Optional[str] = None) -> TaskResult:
"""创建成功结果"""
@classmethod
def failed(cls, error: str) -> TaskResult:
"""创建失败结果"""
@classmethod
def in_progress(cls, task_id: str) -> TaskResult:
"""创建进行中结果"""
```
---
## DataSource 接口设计
### **接口方法**
```python
class BaseDataSource(ABC):
# ===== Handler 管理 =====
def register_handler(self, handler: NodeHandler) -> None:
"""注册 Handler"""
def get_handler(self, node_type: str) -> NodeHandler:
"""获取 Handler"""
# ===== 数据加载 =====
async def load_all(
self,
order: List[str]
) -> None:
"""
按依赖顺序加载所有数据
注意：调用前需先 set_collection()
Args:
order: 节点类型顺序（如 ["project", "contract", "construction"]）
工作流程：
1. 按顺序遍历每个节点类型
2. 调用 Handler.load()
3. Handler 可以从 self._collection 查询依赖节点
4. 使用 Handler.create_node() 创建 SyncNode
5. 添加到 Collection
"""
# ===== 同步执行 =====
async def sync_all(
self,
order: List[str]
) -> None:
"""
按依赖顺序执行同步
流程：
1. 按顺序遍历每个节点类型
2. 筛选需要同步的节点（status=PENDING, action!=NONE）
3. 调用 Handler 的 create/update/delete
4. 根据 TaskResult 更新节点状态
5. 处理异步任务轮询
"""
# ===== 统计信息 =====
def get_sync_summary(self, collection: DataCollection) -> Dict[str, Any]:
"""获取同步统计信息"""
```
### **状态流转逻辑**
```python
async def _sync_nodes(self, handler, nodes):
async_tasks = {} # {node_id: task_id}
for node in nodes:
# 1. 跳过不需要处理的节点
if node.action == SyncAction.NONE:
continue
# 2. 跳过异常状态节点
if node.binding_status in [DEPENDENCY_ERROR, ABNORMAL, WARNING]:
node.status = SyncStatus.SKIPPED
continue
# 3. 只处理 PENDING 节点
if node.status != SyncStatus.PENDING:
continue
# 4. 执行操作
try:
node.status = SyncStatus.IN_PROGRESS
if node.action == SyncAction.CREATE:
result = await handler.create(node)
elif node.action == SyncAction.UPDATE:
result = await handler.update(node)
elif node.action == SyncAction.DELETE:
result = await handler.delete(node)
# 5. 处理结果
if result.status == TaskStatus.SUCCESS:
node.status = SyncStatus.SUCCESS
if result.data_id:
node.data_id = result.data_id # 回填 ID
elif result.status == TaskStatus.FAILED:
node.status = SyncStatus.FAILED
node.error = result.error
elif result.status == TaskStatus.IN_PROGRESS:
async_tasks[node.node_id] = result.task_id
except Exception as e:
node.status = SyncStatus.FAILED
node.error = str(e)
# 6. 轮询异步任务
if async_tasks:
await self._poll_async_tasks(handler, nodes, async_tasks)
```
### **异步任务轮询**
```python
async def _poll_async_tasks(self, handler, nodes, async_tasks):
node_map = {n.node_id: n for n in nodes}
max_retries = poll_max_retries # 默认轮询 1 次，可配置
retry_count = 0
while async_tasks and retry_count < max_retries:
# 批量查询
task_ids = list(async_tasks.values())
results = await handler.poll_tasks(task_ids)
# 处理结果
for node_id, task_id in list(async_tasks.items()):
if task_id not in results:
continue
result = results[task_id]
node = node_map[node_id]
if result.status == TaskStatus.SUCCESS:
node.status = SyncStatus.SUCCESS
if result.data_id:
node.data_id = result.data_id
async_tasks.pop(node_id)
elif result.status == TaskStatus.FAILED:
node.status = SyncStatus.FAILED
node.error = result.error
async_tasks.pop(node_id)
# 还有未完成任务，等待后重试
if async_tasks:
await asyncio.sleep(2)
retry_count += 1
# 超时未完成的任务标记为失败
for node_id in async_tasks:
node = node_map[node_id]
node.status = SyncStatus.FAILED
node.error = "Async task timeout"
```
---
## 完整流程示例
### **Pipeline 编排**
```python
# Stage 0: 初始化
collection = DataCollection()
datasource = ApiDataSource(api_client)
# 注册 Handler
datasource.register_handler(ProjectNodeHandler(api_client))
datasource.register_handler(ContractNodeHandler(api_client))
# Stage 1: 加载数据
datasource.set_collection(collection)
await datasource.load_all(
order=["project", "contract"] # 依赖顺序
)
# Stage 2: Strategy 执行
for strategy in [project_strategy, contract_strategy]:
await strategy.bind() # 设置 binding_status
await strategy.create() # 设置 action=CREATE + ID 映射
await strategy.update() # 设置 action=UPDATE + ID 映射
await strategy.pre_sync_check()
# Stage 3: 物理同步
await datasource.sync_all(
order=["project", "contract"]
)
# Stage 4: 检查结果
summary = datasource.get_sync_summary(collection)
print(f"Success: {summary['success']}, Failed: {summary['failed']}")
```
### **Contract Handler 实现**
```python
class ContractNodeHandler(BaseNodeHandler[ContractResponse]):
def __init__(self, api_client):
super().__init__(
node_type="contract",
node_class=ContractSyncNode,
schema=ContractResponse
)
self.api = api_client
async def load(self):
"""加载合同（依赖 Project）"""
if self._collection:
projects = self._collection.filter(node_type="project")
project_ids = [p.data_id for p in projects if p.data_id]
else:
project_ids = []
response = await self.api.get_contracts(project_ids=project_ids)
return response["data"]
async def create(self, node):
"""创建合同（异步接口）"""
try:
# node.data 已经过 ID 映射，直接使用
response = await self.api.create_contract_async(node.data)
if response.get("async"):
return TaskResult.in_progress(task_id=response["task_id"])
else:
return TaskResult.success(data_id=response["id"])
except Exception as e:
return TaskResult.failed(error=str(e))
async def update(self, node):
"""更新合同（同步接口）"""
try:
response = await self.api.update_contract(node.data_id, node.data)
return TaskResult.success()
except Exception as e:
return TaskResult.failed(error=str(e))
async def poll_tasks(self, task_ids):
"""轮询异步任务"""
response = await self.api.batch_query_tasks(task_ids)
results = {}
for task in response["tasks"]:
if task["status"] == "completed":
results[task["id"]] = TaskResult.success(
data_id=task["result"]["contract_id"]
)
elif task["status"] == "failed":
results[task["id"]] = TaskResult.failed(error=task["error"])
else:
results[task["id"]] = TaskResult.in_progress(task_id=task["id"])
return results
async def validate(self, data):
"""数据质量检查"""
errors = []
if not data.get("code"):
errors.append("合同编码为空")
if not data.get("project_id"):
errors.append("项目 ID 为空")
return ValidationResult(is_valid=len(errors) == 0, errors=errors)
def extract_id(self, data):
return data["id"]
```
---
## 核心优势
### **1. 职责清晰**
- **Strategy**: 业务逻辑 + ID 映射
- **DataSource**: 状态管理 + 编排
- **Handler**: 纯执行（后端 API 调用）
### **2. ID 映射前置**
- ID 映射在 Strategy 完成，DataSource 和 Handler 无需关心
- `node.data` 已经是映射好的数据，直接使用
### **3. 状态统一管理**
- 所有状态流转由 DataSource 负责
- Handler 只返回结果，不改变节点状态
### **4. 异步任务支持**
- Handler 返回 `TaskResult.in_progress(task_id)`
- DataSource 自动轮询直到完成
### **5. 数据质量保障**
- Handler 提供 `validate()` 方法
- DataSource 在加载时检查数据质量
### **6. 易于测试**
- Handler 可以 Mock（返回假 TaskResult）
- DataSource 可以单独测试状态流转逻辑
- Strategy 可以单独测试 ID 映射逻辑
---
## 与现有架构的兼容性
完全符合 [架构分层设计.md](./架构分层设计.md) 的四层模型：
1. **Common 层**: SyncNode, DataCollection, BindingManager
2. **Sync System 层**: SyncStrategy（负责 bind/create/update + ID 映射）
3. **DataSource 层**: BaseDataSource + NodeHandler（状态管理 + 执行）
4. **Pipeline 层**: 流程编排 + 依赖顺序
符合 [状态定义规范.md](./状态定义规范.md) 的状态流转逻辑。
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# node_id / data_id / 持久化与生命周期说明
本文档说明同步系统中 `node_id` 与 `data_id` 的职责、生成时机、持久化行为，以及同步流程中“创建/绑定/回填”的完整生命周期。目标是避免“重复生成 node_id 导致绑定失效”的问题，并明确各层职责。
---
## 1. 基础概念
- **data_id**
- 业务主键（来自数据源/远端系统的资源 ID）。
- 在加载阶段通常已存在；在 CREATE 场景下初始为空，成功后由 DataSource 回填。
- **node_id**
- 同步系统内部的**稳定标识符**（绑定与持久化的主键）。
- 用于绑定表、持久化节点、依赖追踪等。
- 设计目标：**跨同步周期稳定**，不能随每次加载而变化。
---
## 2. 核心结论（必须遵守）
1. **node_id 一旦建立，不应再被数据源“重新生成”。**
- 绑定关系与持久化状态依赖 `node_id`；若每次加载都重新生成，会导致历史绑定失效。
2. **加载阶段应先恢复 Collection（持久化节点），再加载 DataSource 数据。**
- 数据源加载出的 `data_id` 应优先匹配已持久化的节点；匹配到则复用旧 `node_id`。
3. **CREATE 场景允许临时/新建 node_id**，但必须通过后续回填与绑定更新保持一致性。
---
## 3. 正确的初始化/加载顺序
### 推荐流程（Pipeline 前半段）
1. **持久化恢复阶段**
- 必须同时恢复 `node_id` 与 `data_id`（以及状态字段），否则无法建立稳定的映射关系。
- Collection 可能为空，这属于合法情况。
2. **数据源加载阶段（DataSource.load_all）**
- 对每一条业务数据（含 `data_id`）：
- **若 Collection 内已存在该 `data_id` 对应节点**：将数据写回原节点（保留旧 `node_id`）。
- **若不存在**：由 **Collection** 生成新的 `node_id`，并创建新节点。
> 这样可避免“第二次同步时重建节点，导致旧绑定丢失”。
---
## 4. node_id 的来源与稳定性
### A. 持久化恢复阶段
- **恢复时必须包含 `node_id` 与 `data_id`**：
- 两者成对恢复，才能保证后续 load 阶段按 `data_id` 命中旧节点。
### B. 数据源加载阶段
- **优先复用持久化 node_id**：
- 通过 `data_id` 在 Collection 中查找并更新已有节点。
- **仅在未知 data_id 时新建 node_id**：
- 新节点 `node_id` 必须由 **Collection** 生成，而非 DataSource/Handler 直接拼接。
### C. 创建阶段（Strategy.create）
- 新建“目标端”节点时，**必须有 node_id**：
- 用于写入 Collection、记录状态、建立临时绑定。
- 成功后回填 `data_id`，**node_id 不变**。
---
## 5. data_id 的来源与回填
本节按阶段拆分说明 `data_id` 的来源与写回。
### A. 持久化恢复阶段
- `data_id` 从持久化数据中恢复（与 `node_id` 一起恢复）。
### B. 数据源加载阶段
- `data_id` 来自数据源原始数据（`id` / `_id`）。
- 若命中已有节点，则仅更新数据与状态，不改变 `node_id`。
### C. 同步创建与轮询阶段
- CREATE 提交后，DataSource 从响应/轮询结果提取 `biz_id`。
- 成功时回填到 `node.data_id`，并回写 `node.data` 的主键字段（仅 `id` / `_id`）。
### D. 持久化阶段
- 将更新后的 `node_id` / `data_id` / 状态字段持久化，供下次同步恢复使用。
---
## 6. 绑定与 node_id 的关系
- 绑定表的 key 为 `node_id`，绑定记录是 `local_node_id <-> remote_node_id`。
- 因此：**node_id 必须稳定**，才能保证绑定长期有效。
- 绑定可在创建前建立“临时关系”，但成功后不应更换 node_id。
---
## 7. 同步周期中的典型场景
### 场景 1：第一次同步（无持久化）
- Collection 为空 → DataSource load 新节点 → 生成新 `node_id`。
- Strategy bind / create / update 执行。
- 持久化后，下次同步可复用 `node_id`。
### 场景 2：第二次同步（已有持久化）
- 先恢复 Collection（已有 `node_id`）。
- DataSource load 时按 `data_id` 匹配旧节点并更新数据。
- 绑定关系仍有效。
### 场景 3：创建新数据（CREATE）
- Strategy 产生目标端节点（`node_id` 新生成）。
- DataSource 执行创建，回填 `data_id`。
- 绑定记录更新为真实 `data_id`（但 node_id 保持不变）。
---
## 8. 关键规则总结
- **node_id 是“同步系统内的稳定 ID”，必须持久化与复用。**
- **data_id 是“业务系统的资源 ID”，由数据源加载或创建后回填。**
- **加载顺序：先恢复持久化节点 → 再 load 数据源。**
- **遇到已存在 data_id：复用 node_id；否则创建新节点。**
- **CREATE 成功后只更新 data_id，不更换 node_id。**
---
## 9. 相关文件参考
- 绑定与状态定义：见 [docs/状态定义规范.md](状态定义规范.md)
- 编排流程：见 [docs/编排流程规范.md](编排流程规范.md)
- BaseDataSource：见 [sync_system_new/datasource/datasource.py](../sync_system_new/datasource/datasource.py)
- BaseApiHandler：见 [sync_system_new/datasource/api/handler.py](../sync_system_new/datasource/api/handler.py)
---
## 10. 明确规则与建议实现
- **DataSource.load_all 必须先按 `data_id` 命中已有节点并更新**，未命中时再由 Collection 创建新节点并分配新的 `node_id`。
- **推荐实现方式**：先 `find_by_data_id`，命中走通用更新；未命中再创建新节点（无需强制 `upsert_by_data_id` 接口）。
- **创建流程中的临时绑定/成功更新规则**：
- CREATE 节点创建时：`binding_status = NORMAL`，`action = CREATE`，`status = PENDING`，`data_id = ""`。
- 执行提交前置为 `status = IN_PROGRESS`（异步）或保持 `PENDING`（同步接口待执行）。
- 成功回填后：`status = SUCCESS`，`data_id` 回填并写回主键字段，绑定记录保持 `node_id` 不变。
- 过程中出现错误：`status = FAILED`，`error` 记录原因。
- **异常节点持久化/恢复策略**：
- 持久化时保留异常节点与错误信息。
- 恢复时是否保留/清理异常节点应通过策略配置控制（默认建议保留以便人工修复）。
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# Skip Sync 行为修复说明
## 问题分析
### 1. **绑定失败的根本原因**
**问题现象**：
- Company: 1/39 绑定
- Supplier: 0/65202 绑定（完全没绑定！）
- 导致依赖supplier的业务（contract, material等）也绑不上
- 远程异常创建了74条数据
**根本原因有两个**：
#### 原因1：skip_sync 跳过了整个策略（包括 bind）
```python
# 旧逻辑：skip_sync=True 时跳过整个策略
if getattr(strategy, 'skip_sync', False):
continue # ← 跳过了 bind/create/update 全部！
```
修复后：
```python
# 新逻辑：bind() 始终执行，skip_sync 只跳过 create/update/sync
await strategy.bind() # ← 始终执行
if getattr(strategy, 'skip_sync', False):
continue # ← 只跳过 create/update
```
#### 原因2：自动绑定ID解析失败没有设置DEPENDENCY_ERROR
```python
# 旧逻辑：ID解析失败只是跳过
if not resolved_key_dict:
continue # ← 节点保持 MISSING，会被误创建！
```
修复后：
```python
# 新逻辑：ID解析失败设置DEPENDENCY_ERROR
if not resolved_key_dict:
node.set_binding_status(BindingStatus.DEPENDENCY_ERROR, "业务键中的ID字段解析失败")
continue # ← 节点为 DEPENDENCY_ERROR，不会被创建
```
### 2. **状态与创建的关系**
| 状态 | 来源 | 允许创建 | 说明 |
|------|------|:---:|------|
| **UNCHECKED** | 加载后初始状态 | ❌ | bind() 未执行 |
| **NORMAL** | 有绑定记录 | ❌ | 已绑定 |
| **MISSING** | 无绑定记录 | ✅ | 真正的孤儿 |
| **WARNING** | 业务键字段缺失 | ❌ | 数据不完整 |
| **DEPENDENCY_ERROR** | 依赖不满足 | ❌ | 父节点未就绪 |
| **ABNORMAL** | 数据损坏 | ❌ | 需人工处理 |
**关键原则**：
- `create()` 只查找 `binding_status == MISSING` 的节点
- 如果 bind() 没执行，状态是 UNCHECKED → 不会创建
- 如果 bind() 执行了但依赖不满足 → DEPENDENCY_ERROR → 不会创建
### 3. **Supplier 默认行为变更**
**旧行为**：
- `default_skip_sync = True` → 默认跳过同步
- 需要在调用层设置 `force_sync_types=["supplier"]`
**新行为**：
- `default_skip_sync` 已移除（使用基类默认值 False）
- Supplier 默认会执行完整同步（bind/create/update）
- 如需跳过，在调用层配置 `skip_sync_types=["supplier"]`
## 解决方案
### 修改 1：分离 bind() 和 skip_sync
**新逻辑**：
```python
# sync_system_new/pipeline/full_sync_pipeline.py
# Step 1a: 绑定（始终执行）
await strategy.bind()
# Step 1b: 检查是否跳过 create/update/sync
if getattr(strategy, 'skip_sync', False):
print(f"⏭️ Skipping create/update/sync for {node_type}")
# 继续执行 pre_sync_check，但跳过 create/update/sync
if hasattr(strategy, "pre_sync_check"):
ok = await strategy.pre_sync_check()
...
continue
# Step 1c: 正常的 create/update
await strategy.create()
await strategy.update()
```
**效果**：
- ✅ **bind() 始终执行**（建立绑定关系）
- ✅ **skip_sync=True 只跳过 create/update/sync**（避免昂贵操作）
- ✅ **pre_sync_check 仍然执行**（依赖检查）
### 修改 2：添加 force_sync_types 配置
**配置示例**：
```python
# tests/run_full_sync_pipeline_simple.py
CONFIG = {
# 第一次运行：从 API 加载 + 绑定 + 创建
"force_sync_types": ["supplier"],
"wipe_persistence_on_start": True,
# 第二次运行：从持久化加载 + 跳过同步
# "handler_configs": {"supplier": {"load_mode": "persisted_only"}},
# "skip_sync_types": ["supplier"],
# "wipe_persistence_on_start": False,
}
```
**优先级**：
1. **force_sync_types**（最高）→ `skip_sync = False`
2. **skip_sync_types** → `skip_sync = True`
3. **策略默认值** (default_skip_sync)
### 修改 3：添加测试日志保存
**功能**：
```python
# tests/run_full_sync_pipeline_simple.py
log_path = log_dir / f"simple_pipeline_{datetime.now().strftime('%Y%m%d_%H%M%S')}.log"
sys.stdout = Tee(original_stdout, log_file)
```
**输出位置**：
```
test_results/simple_pipeline_20260204_162345.log
```
## 使用指南
### Phase 1: 首次运行（API + 绑定 + 创建）
```python
CONFIG = {
# 不需要特殊配置，所有类型默认都会同步
"wipe_persistence_on_start": True, # 清空数据库
}
```
**预期结果**：
- Supplier: 从API加载60000条 → 自动绑定(credit_code) → 拉取到本地 → 持久化
- Company: 自动绑定 → 拉取
- Contract等: 通过supplier_id/project_id绑定 → 创建
### Phase 2: 后续运行（持久化 + 跳过同步）
```python
CONFIG = {
"handler_configs": {
"supplier": {"load_mode": "persisted_only"} # 从DB加载
},
"skip_sync_types": ["supplier"], # 跳过create/update（但仍执行bind）
"wipe_persistence_on_start": False, # 保留数据
}
```
**预期结果**：
- Supplier: 从DB加载（带绑定关系） → 执行bind（验证状态） → 跳过create/update
- 其他业务: 正常同步
## 测试验证
### 1. 删除远程异常创建的数据
```bash
# TODO: 通过API删除远程的74条测试数据
```
### 2. 清空数据库重新测试
```bash
rm _runtime/test_simple.db
python scripts/legacy/run_full_sync_pipeline_simple.py
```
### 3. 验证绑定统计
**期望输出**：
```
Local Summary:
company: 39/39 bindings ← 全部绑定
supplier: 60000+/65202 bindings ← 大量绑定
contract: XX/34 bindings ← 通过supplier_id绑定
Remote Summary:
company: 39/39 bindings
supplier: 60000+/60000 bindings
contract: XX/155 bindings (XX creates)
```
### 4. 检查日志文件
```bash
cat test_results/simple_pipeline_*.log | grep "Skipping"
```
**期望**：
- 第一次运行：**不应该有** "Skipping" 输出
- 第二次运行：`⏭️ Skipping create/update/sync for supplier`
## 风险评估
### 影响范围
- ✅ 修复了 supplier/company 绑定失败问题
- ✅ 防止未绑定节点异常创建
- ✅ 保持了两阶段工作流（首次API+绑定，后续持久化）
- ⚠️ 可能影响其他使用 skip_sync 的场景（需要测试）
### 向后兼容性
- ✅ 原始脚本 (run_full_sync_pipeline_api.py) 不受影响
- ✅ 没有 skip_sync 属性的策略行为不变
- ✅ 新增的 force_sync_types 是可选参数
## 待办事项
- [ ] 测试所有业务类型的绑定统计
- [ ] 验证依赖关系链（project → contract → material → detail）
- [ ] 检查 construction_task 为什么没绑定（0/32）
- [ ] 测试第二次运行的持久化加载逻辑
- [ ] 更新文档说明 skip_sync 的新语义
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# 业务流程与依赖关系
本文档描述推送系统涉及的业务实体及其依赖关系，用于指导同步顺序编排。
---
## 业务实体分类
### 1. 基础数据（仅拉取）
- **用户（User）**：拉取集团管理员、区域公司管理员及特定用户信息，用于跨平台穿透。其他用户需手动创建。
- **公司（Company）**：仅拉取，不推送。
- **供应商（Supplier）**：仅拉取，不推送。
### 2. 项目及扩展数据
**项目（Project）**
- **绑定方式**：必须手动绑定（根节点）
- **同步操作**：允许更新和拉取
- **依赖项**：公司、附件（Attachment）
**项目扩展业务**
- 通过 `(project_id, key)` 或 `(project_id, code)` 自动绑定
- 允许创建、更新、拉取
- 依赖项目
### 3. 合同及子业务
**合同（Contract）**
- **绑定方式**：通过业务键自动绑定（需与 ECP 平台数据交叉检验）
- **同步操作**：允许拉取、创建、更新、删除
- **依赖项**：项目
**合同子业务**（施工任务、物资、结算、力能）
- **绑定方式**：通过 `(contract_id, code)` 自动绑定
- **同步操作**：允许拉取、创建、更新、删除
- **特殊规则**：首次绑定后，项目侧不会同步创建远程已有的数据
- **依赖项**：合同
**合同子业务明细**（施工明细、物资明细、结算明细、力能明细）
- **绑定方式**：通过 `(parent_id, date)` 自动绑定
- **同步操作**：允许拉取、创建、更新、删除
- **特殊规则**：首次绑定后，项目侧不会同步创建远程已有的数据
- **依赖项**：对应的合同子业务
---
## 依赖关系图
```
Company (基础)
↓
Project (手动绑定)
↓
Contract (自动绑定)
↓
Contract Sub-Business (施工/物资/结算/力能)
↓
Details (明细)
```
---
## 同步顺序原则
1. **依赖优先**：父节点必须先于子节点同步
2. **绑定传递**：子节点的业务键构建依赖父节点的 ID 映射
3. **故障隔离**：父节点同步失败时，子节点标记为 `DEPENDENCY_ERROR` 并跳过
详细状态定义参见：[sync_system_new/sync_system/STATE_DEFINITIONS.md](../sync_system_new/sync_system/STATE_DEFINITIONS.md)
详细架构设计参见：[sync_system_new/architecture_layers.md](../sync_system_new/architecture_layers.md)
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# 节点状态持久化与人工介入规范
> **代码实现**：`sync_system_new/common/state_reset.py`
---
## 1. 持久化规则
### 1.1 持久化目标
| 目标 | 说明 |
|------|------|
| **可恢复性** | 系统重启后能从上次状态继续 |
| **可观测性** | 失败和异常状态要保留，供人工查看 |
| **可追溯性** | 失败信息持久化，不自动重试，需人工确认 |
| **绑定稳定性** | 手工绑定一旦建立，永不自动改变 |
### 1.2 分阶段重置设计
状态重置分为两个阶段执行：
#### 阶段1：加载时重置（Collection.load_from_persistence）
| 字段 | 性质 | 持久化 | 阶段1重置 |
|------|------|--------|-----------|
| `node_id` | 恒定标识 | ✅ 必须 | ❌ 不重置 |
| `data_id` | 业务主键 | ✅ 必须 | ❌ 不重置 |
| `data` | 业务数据 | ✅ 必须 | ✅ **重置**（每次重新取数） |
| `origin_data` | 原始快照 | ✅ 必须 | ✅ **重置**（每次重新取数） |
| `depend_ids` | 依赖列表 | ❌ **不持久化** | ✅ **初始化为[]**（bind 阶段从 data 实时计算） |
| `binding_status` | 绑定状态 | ✅ 必须 | ✅ **重置为 UNCHECKED** |
| `action` | 同步意图 | ✅ 保存 | ❌ **保留**（用于阶段2判断） |
| `status` | 执行状态 | ✅ 保存 | ❌ **保留**（全部保留，不重置） |
| `error` | 错误信息 | ✅ 保存 | ✅ **重置为None**（清空上次错误） |
| `context` | 扩展上下文 | ✅ 保存 | ❌ 不重置 |
#### 阶段2：数据加载后清理（Pipeline._cleanup_create_failed_zombies）
在数据加载完成后、策略执行前，执行CREATE失败节点清理：
1. **检查条件**：
- 本地节点 `action == CREATE`（上次尝试创建）
- 本地节点 `status == FAILED`（创建失败）
2. **清理动作**：
- **删除本地失败节点**（从 collection 中移除）
- 如果有绑定记录：
- 解除绑定关系
- 删除远程 collection 中的僵尸节点
3. **最后重置 action**：
- 所有剩余节点的 `action` 重置为 NONE
- 准备进入策略阶段
4. **下次同步的自动恢复**：
- 被删除的节点会从数据源重新加载
- 如果远程实际已创建成功（网络波动导致未获取到结果）→ 绑定阶段会自动绑定上
- 如果远程实际也失败了 → 重新尝试创建
5. **UPDATE 阶段保护**：
- UPDATE 操作会跳过所有 `status == FAILED` 的节点
- 防止 UPDATE 阶段覆盖 CREATE/UPDATE 失败的状态和错误信息
- 确保失败节点的 action 和 error 信息保持不变，直到下次同步清理
> **说明**：
> - `data` / `origin_data`：每次运行从数据源重新获取，保证数据最新
> - `depend_ids`：**不持久化**，每次 bind 阶段从 data 的业务字段（如 contract_id, project_id）实时提取
> - `binding_status`：持久化用于审计，加载时重置为 `UNCHECKED`，由 bind() 重新判定
> - `error`：**阶段1清空**，避免上次错误影响本次运行，新错误会在各阶段重新生成
> - `action`：**阶段1保留**用于识别 CREATE 失败的节点，**阶段2清理后重置**
> - `status`：**阶段1全部保留**（包括 FAILED、PRECONDITION_FAILED 等），不自动重置
> - **CREATE 失败节点会被自动删除并重新加载**，UPDATE/DELETE 失败保留需人工处理
> - **UPDATE 操作会跳过 FAILED 节点**，避免覆盖失败状态和错误信息
### 1.3 绑定记录 vs binding_status
| 概念 | 存储位置 | 持久性 | 如何改变 |
|------|---------|--------|---------|
| **绑定记录** | `bindings` 表 | **永久保留** | 只能手工 bind/unbind，或 CREATE 失败自动清理 |
| **binding_status** | `nodes` 表 | 保存但可重判 | 每次 bind() 重新判定 |
### 1.4 CREATE 失败的自动恢复
当 CREATE 操作失败时，会产生"僵尸绑定"：
- 绑定记录已建立（local_id → remote_node_id）
- 但远程节点的 `data_id` 为空（API 未返回真实 ID）
**下次同步时的自动恢复流程**：
1. 阶段1加载：保留 `action=CREATE`
2. 阶段2清理：检测到僵尸绑定，自动清理
3. 本地节点恢复为 MISSING 状态
4. 策略阶段重新判定，再次尝试 CREATE
---
## 2. 人工介入规范
### 2.1 介入时机
| 时机 | 场景 | 操作 |
|------|------|------|
| **运行前** | 查看上次失败记录 | 查看持久化的 error，决定是否修复后重试 |
| **bind() 后** | 出现 ABNORMAL/WARNING | 检查数据一致性，手工修复或确认 |
| **bind() 后** | 1:N / N:N 映射 | 手工绑定指定远程记录 |
| **sync() 后** | 批量失败 | 分析失败原因，决定重试策略 |
### 2.2 binding_status 与介入需求
| binding_status | 含义 | 需要介入 | 说明 |
|----------------|------|---------|------|
| `UNCHECKED` | 未检查 | ❌ | 等待 bind() 判定 |
| `NORMAL` | 绑定正常 | ❌ | 自动处理 |
| `MISSING` | 无绑定记录 | ❌ | 自动创建 |
| `WARNING` | 本地有绑定但远程无数据 | ⚠️ 可选 | 可能是远程删除，需确认 |
| `ABNORMAL` | 状态不一致 | ✅ **必须** | 需人工排查 |
| `DEPENDENCY_ERROR` | 依赖未就绪 | ❌ | 等依赖解决后自动重试 |
### 2.3 人工绑定操作
```python
# 手工绑定（1:N 场景）
binding_manager.bind(node_id="local_xxx", data_id="remote_xxx")
# 手工解绑
binding_manager.unbind(node_id="local_xxx")
```
绑定记录一旦建立，永不自动改变，只能手工操作。
### 2.4 职责分工
| 职责 | 系统自动 | 人工介入 |
|------|---------|---------|
| 1:1 自动绑定 | ✅ | - |
| 1:N / N:N 绑定 | ❌ | ✅ |
| NORMAL 节点同步 | ✅ | - |
| MISSING 节点创建 | ✅ | - |
| CREATE 失败重试 | ✅（自动清理僵尸） | ⚠️（需确认后手动重置） |
| UPDATE 失败重试 | ❌（保留FAILED状态） | ✅（需确认后手动重置） |
| ABNORMAL 处理 | ❌ | ✅ |
| WARNING 确认 | ❌ | ✅（可选） |
---
## 3. 总结
1. **分阶段重置**：
- 阶段1（加载时）：只重置 binding_status，**保留 action/status/error**
- 阶段2（数据加载后）：清理 CREATE 失败僵尸，然后重置 action
2. **失败状态持久化**：FAILED 状态和 error 信息保留，不自动重试
3. **绑定记录**：永久保留，除非 CREATE 失败自动清理或手工操作
4. **人工介入**：失败需确认后手动重置，ABNORMAL/WARNING 需人工处理，1:N 绑定需手工指定
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# 架构分层设计：四层模型
本架构旨在将同步系统的**数据容器**、**同步逻辑**、**执行层**与**编排流程**完全解耦，提供极简且类型安全的开发体验。
---
## 1. 架构概览
系统分为四层，依赖关系严格从上到下：
1. **通用层 (Common)**: 定义纯数据结构（Data Container）和基础工具。
2. **同步系统层 (Sync System)**: 定义同步行为接口（SyncStrategy）与业务规则。
3. **数据源层 (DataSource)**: 实现数据的加载与持久化，属于盲目执行层。
4. **编排层 (Pipeline)**: 应用层逻辑，硬编码同步顺序，协调 ID 映射与错误传播。
---
## 2. 通用层 (Layer 0: Common)
本层不包含业务逻辑，仅定义数据契约。
- **SyncNode[T]**: 核心状态机容器。
- `origin_data`: 原始数据（对应 `data_id`）。
- `data`: 计算后的最新目标数据。
- `data_id`: 业务主键ID。加载时必定有值，CREATE 节点初始为空字符串 `""`（布尔值为 False，可通过校验）。
- `action`: 同步意图 (NONE, CREATE, UPDATE, DELETE)。
- `status`: 执行状态 (PENDING, IN_PROGRESS, SUCCESS, FAILED, SKIPPED, PRECONDITION_FAILED)。
- 详见 [状态定义规范 § 5.A](./状态定义规范.md#5-执行同步状态转换-physical-sync-state-transitions)
- `binding_status`: 绑定状态 (UNCHECKED, NORMAL, MISSING, DEPENDENCY_ERROR, ABNORMAL, WARNING)。
- 详见 [状态定义规范 § 1](./状态定义规范.md#1-核心状态判定表-core-binding-matrix)
- `error`: 异常详情。
- **DataCollection**: 节点的集合，提供类型安全的查询和过滤方法。
- **BindingManager**:
- **ID 映射**: 维护 `local_node_id` <-> `remote_node_id` 的双向映射。
- **绑定键**: 使用 `node_id` 作为绑定记录的键，**一致不变**。CREATE 成功后只更新节点的 `data_id`，绑定记录不变。
- **持久化**: 将映射关系持久化到存储（如 JSON/数据库）。
- **Enums**: `SyncAction`, `SyncStatus`, `BindingStatus` 等。
---
## 3. 同步系统层 (Layer 1: Sync System)
核心业务逻辑层。通过实现 `SyncStrategy` 接口来定义特定实体的同步逻辑。
- **SyncStrategy[T] 接口**:
- `bind()`:
- 职责：判定 `binding_status` (NORMAL/MISSING/ABNORMAL/WARNING/DEPENDENCY_ERROR)
- 详见 [状态定义规范 § 1-3](./状态定义规范.md)
- `create()`:
- 职责：处理孤儿节点（MISSING），在对方侧创建新节点并设置 `action=CREATE`
- **ID 替换**: 创建新节点时，复制数据并将依赖字段的本地 ID 替换为远程 ID
- **内联检查**: 通过 `IDResolver.resolve_and_validate()` 验证依赖 ID 解析
- 详见 [状态定义规范 § 4.C](./状态定义规范.md)
- `update()`:
- 职责：处理差异节点（NORMAL 且有 diff），设置 `action=UPDATE`
- **ID 替换**: 准备更新数据时，替换数据中的依赖 ID
- **内联检查**: 验证目标节点 data_id 完整性，失败则设置 `PRECONDITION_FAILED`
- **FAILED 保护**: 自动跳过 `status=FAILED` 的节点
- 详见 [状态定义规范 § 4.A](./状态定义规范.md)
---
## 4. 数据源层 (Layer 2: DataSource)
作为各个后端的适配器，负责数据加载与持久化。
- **职责**:
- `load_nodes(node_type)`: 从后端加载并返回 `SyncNode` 集合，自动添加到 `DataCollection`。
- `save_nodes(nodes)`:
- 遍历节点，仅处理 `status == PENDING` 且 `action != NONE` 的节点。
- 根据 `action` 执行相应的 CREATE/UPDATE/DELETE 操作。
- 执行成功后，更新节点的 `status` 和相关信息（如新生成的 remote_id）。
---
## 5. 编排层 (Layer 3: Pipeline)
最高层级，负责流程编排。
- **职责**:
- **显式顺序**: 直接在代码中按顺序调用同步逻辑（例如：先同步项目，再同步合同）。
- **故障传播**: 若前置实体某节点同步失败（`FAILED`），编排器在处理后续依赖节点时可将其标记为 `DEPENDENCY_ERROR`。
- **生命周期管理**: 初始化 `BindingManager` 和 `DataCollection`，同步结束后调用持久化方法。
---
## 6. ID 映射与对齐：核心流程
为了解决本地数据引用本地 ID 与远程数据引用远程 ID 的冲突，系统采用以下映射逻辑：
### 绑定阶段 (Binding)
- **时机**: `Strategy.bind`
- **目标**: 在 `BindingManager` 中确定 local_id ↔ remote_id 映射
- **手段**: 业务键匹配（如 Code 匹配）、历史记录恢复等
### 执行阶段 (Execution)
- **时机**: `Strategy.create()` / `Strategy.update()` 阶段
- **目标**: 在创建新节点或准备更新时，将依赖字段的本地 ID 替换为远程 ID
- **手段**:
- `create()`: 创建对方节点时，复制数据并替换所有依赖 ID
- `update()`: 准备更新数据时，替换数据中的依赖 ID
- **验证**: `_pre_commit_check` 在 create/update 最后检查，确保所有依赖节点都已有远程 ID
**注意**: ID 替换在 Strategy 的 create/update 阶段完成，DataSource 只负责盲目执行已准备好的数据。
---
## 7. 关键设计原则
- **删除类型依赖配置**: 依赖关系通过 `Pipeline` 中的代码调用顺序自然表达。
- **无状态 DataSource**: 数据源不了解绑定逻辑，只看到 `action`、`status` 和 `binding_status`。
- **BindingManager 为核心**: 负责 ID 空间映射和持久化。
- **配置驱动**: 通过 `StrategyConfig` 和预设配置（ConfigPresets）灵活控制同步行为。
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# 同步系统状态定义 (Final Spec)
本文档定义了同步系统的状态机逻辑。逻辑流转遵循以下顺序：
1. **核心状态判定** (Core State)
2. **依赖检查与ID解析** (Dependency)
3. **自动绑定/发现** (Discovery)
4. **策略执行** (Action)
---
## 0. 绑定状态枚举 (BindingStatus)
| 状态值 | 含义 | 来源 | 允许创建 |
| :--- | :--- | :--- | :---: |
| **UNCHECKED** | 未执行绑定检查 | 加载后的初始状态 | ❌ |
| **NORMAL** | 绑定正常 | 核心状态判定 | ❌ |
| **MISSING** | 无绑定记录（孤儿） | 核心状态判定 | ✅ |
| **WARNING** | 业务键不完整 | 自动绑定阶段 | ❌ |
| **ABNORMAL** | 数据损坏 | 核心状态判定 | ❌ |
| **DEPENDENCY_ERROR** | 依赖未就绪 | 依赖检查或自动绑定 | ❌ |
**关键原则**：
- **UNCHECKED 阻止创建**：加载后节点状态为 UNCHECKED，只有执行了 `bind()` 后才会转为其他状态
- **只有 MISSING 状态才能触发 CREATE**：`create()` 方法只查找 `binding_status == MISSING` 的节点
- **如果 bind() 被跳过**（如 skip_sync=True），节点保持 UNCHECKED，不会被创建
---
## 1. 核心状态判定表 (Core Binding Matrix)
**说明**:
* **Binding Record Pair**: 数据库中的绑定记录 (必须成对出现，已排除单边绑定)。
* **Data Valid**: 指数据是否可读、Schema校验是否通过。
* **Warning vs Abnormal**:
* `ABNORMAL`: 自身数据损坏。
* `WARNING`: 自身健康，但因为对方损坏导致**连接不可用**。
| Bind Pair (Record) | Local Data (Valid?) | Remote Data (Valid?) | -> | **Local Status** | **Remote Status** | **说明** |
| :---: | :---: | :---: | :--- | :--- | :--- | :--- |
| **YES** | **YES** | **YES** | -> | **NORMAL** | **NORMAL** | **稳态**。链路完整，数据健康，可进行 Diff/Update。 |
| **YES** | **YES** | **NO** | -> | **WARNING** | **ABNORMAL** | **远程损坏**。本地虽好，但链路已断 (Link Degraded)。禁止同步。 |
| **YES** | **NO** | **YES** | -> | **ABNORMAL** | **WARNING** | **本地损坏**。远程虽好，但链路已断。禁止同步。 |
| **YES** | **NO** | **NO** | -> | **ABNORMAL** | **ABNORMAL** | **双向损坏**。 |
| **NO** | **YES** | N/A | -> | **MISSING** | N/A | **本地孤儿**。进入“依赖与发现”流程。 |
| **NO** | N/A | **YES** | -> | N/A | **MISSING** | **远程孤儿**。进入“依赖与发现”流程。 |
---
## 2. 依赖与业务键解析 (Dependency & ID Resolution)
**适用范围**: 所有涉及外键依赖 (Foreign Key) 的节点。
**前置条件**: 核心状态 = `MISSING` (准备进行自动绑定或新建)。
在进行 `Auto-Bind` 或 `Create` 之前，必须先尝试构建**远程业务键**。
例如：本地 `Contract(proj_id="P1", code="C01")` 想找远程对象，必须先查询 `P1` 对应的远程 ID `RP_99`，转换成 `(RP_99, "C01")` 才能去远程搜索。
| 依赖项 (Dependency) | 依赖项绑定状态 | -> | **能否构建业务键** | **节点状态** | **说明** |
| :--- | :--- | :--- | :--- | :--- | :--- |
| **无依赖** | N/A | -> | ✅ Yes | **MISSING** | 根节点 (如 Project)，直接进入下一阶段。 |
| **有依赖** | **NORMAL** 且 `data_id` 非空（`status` 任意） | -> | ✅ Yes | **MISSING** | 依赖项已获得远程ID，可进入下一阶段。 |
| **有依赖** | **NORMAL** 且 `data_id` 为空（""，含 `status = FAILED`） | -> | ❌ No | **DEPENDENCY_ERROR** | 依赖项未回填ID，阻断绑定与同步。 |
| **有依赖** | **MISSING / ABNORMAL** | -> | ❌ No | **DEPENDENCY_ERROR** | **依赖阻断**。父节点未同步或损坏，无法计算远程键，无法绑定，无法创建。 |
| **有依赖** | **WARNING** | -> | ❌ No | **DEPENDENCY_ERROR** | 父节点状态不确定（如连接降级），禁止基于此建立新关系。 |
> **处理策略**: 处于 `DEPENDENCY_ERROR` 状态的节点，其动作强制为 **SKIP** (或 PENDING)。必须先修复父节点。
>
> **错误信息格式**: `DEPENDENCY_ERROR` 节点的 `error` 字段会包含详细的依赖失败信息：
> - `dep_err: not_found: field_name(node_type)=value` - 依赖节点未找到
> - `dep_err: field_name: status=FAILED` - 依赖节点状态为 FAILED
> - 多个依赖失败时用分号分隔：`dep_err: not_found: project_id(project)=P1; contract_id: status=FAILED`
---
## 3. 自动绑定状态处理 (Auto-Binding State Handling)
此逻辑遵循“去噪后 1:1”原则：只有在排除掉所有健康同步对后，若剩余节点形成绝对的 1:1 关系，才允许自动绑定。
**配置说明与触发机制**:
- **初始化场景**: 通常在系统第一次初始化或首次接入新实体时，配置 `auto_bind = True` 来对齐历史数据。
- **后续同步**: 系统在日常同步中不建议开启全局自动绑定。自动绑定仅作为“发现”手段，一旦建立过关系的节点，其后续绑定操作通常仅在“自动创建”逻辑中伴随产生（详见第 4 节孤儿处理）。
- **执行前提**: 只有当节点状态为 `MISSING` 且依赖解析成功（`DEPENDENCY_ERROR = False`）时，才会尝试以下探测逻辑。
- **业务键完整性**: 若业务键字段缺失（如 `serial_number = null`），直接标记 `binding_status = WARNING`，并在 `node.error` 记录原因（`Auto-bind skipped: missing fields ...`），不参与自动绑定与孤儿创建判定。- **ID字段解析失败**: 若业务键包含ID字段（如 `supplier_id`）且依赖节点未绑定，ID解析失败，标记 `binding_status = DEPENDENCY_ERROR`，阻止孤儿创建。
**核心算法**:
1. **全集搜索**: 寻找本地/远端所有共享同一个业务键（Business Key）的记录。
2. **排除稳态对**: 识别并移除**成对且互绑**的 `NORMAL` 记录。
- 只有当本地 A 与远端 B 互为绑定对象，且状态皆为 `NORMAL` 时，才将这一对记录从待判定集合中剔除。
- 若出现单边 `NORMAL` 记录（即其配对项不在本次搜索范围内或状态不属于另一端的 `NORMAL`），则不予剔除，视为环境污染项。
3. **判定剩余**: 检查排除上述稳态对后的剩余集合（包含 `MISSING`, `ABNORMAL`, `WARNING` 及单边已占用的 `NORMAL` 记录）。
> **术语**：
> - `L_remain` = 本地记录中，排除“成对稳态”后剩余的数量。
> - `R_remain` = 远端记录中，排除“成对稳态”后剩余的数量。
| `L_remain` | `R_remain` | -> | **动作** | **说明** |
| :---: | :---: | :--- | :--- | :--- |
| **1** | **1** | -> | **BIND (Link)** | **1对1 自动对齐**：仅当两端剩余记录皆为 `MISSING` 且绝对 1:1 时，执行自动绑定。 |
| **1** | **1** | -> | **SKIP** | **带障不处理**：若剩余记录中包含 `ABNORMAL` 等异常状态，说明存在历史冲突，不执行自动动作。 |
| **N** | **0** | -> | **CREATE** | **可判定缺失**：业务键完整且唯一，本地存在而远端不存在（N:0）时，才允许进入孤儿创建策略。 |
| 其他 | 其他 | -> | **SKIP** | **非 1:1 不处理**：存在多对多、多对一或无候选情况，系统保持原状。 |
**设计优势**:
1. **对故障极端敏感**：环境中存在任何 `ABNORMAL` 记录都会阻断自动绑定，强制人工介入处理异常。
2. **状态纯净**：失败时不产生任何中间态（如已废弃的 `AMBIGUOUS`），保持语义清晰。
3. **静默自愈**: 当外界清理了环境且满足 1:1 条件后，系统下次同步会自动完成绑定。
### 3.1 空数据处理策略
**原则**：**空数据不推送**。
**空数据定义**：
- 初始化时创建但未编辑的业务记录（如空合同、空施工任务）
- 业务键字段为空或关键字段缺失的记录
**处理方式**：
- 在自动绑定阶段，若业务键字段缺失，标记 `binding_status = WARNING`，记录原因
- 不参与自动绑定与孤儿创建判定
- 不推送到远程系统
**设计理由**：
1. **远程系统简化**：远程只需处理完整数据，无需兼容空数据校验逻辑
2. **避免垃圾数据**：空数据通常会被本地删除，若已推送则清理复杂
3. **数据质量保障**：远程系统只能看到本地已正确编辑保存的业务
**配置方式**（Strategy 层）：
```python
# 在 Strategy 配置中指定必填字段
default_config = StrategyConfig(
auto_bind_fields=["contract_id", "task_type"], # 业务键字段
# 如果这些字段为空，节点将被标记为 WARNING 而非 MISSING
)
```
---
## 4. 动作策略表 (Action Policy Matrix)
此表定义了在特定状态下，`execute` 阶段允许产生的 **意图行动 (`SyncAction`)**。
#### A. 稳态更新 (NORMAL)
适用于已有绑定关系且链路健康的节点。
| 状态 | 动作条件 | 执行动作 (`SyncAction`) |
| :--- | :--- | :--- |
| **NORMAL** | `compute_diff` 判定存在差异 | **UPDATE** |
| **NORMAL** | `compute_diff` 判定无差异 | **NONE** |
#### B. 异常处理 (阻断态)
处于这些状态的节点，引擎会自动中止后续的读写操作。
| 状态 | 说明 | 动作 (`SyncAction`) |
| :--- | :--- | :--- |
| **DEPENDENCY_ERROR** | 父节点缺失/异常同步导致阻断 | **NONE** |
| **ABNORMAL / WARNING** | 数据损坏或链路降级，需人工修复 | **NONE** |
#### C. 孤儿处理 (Create Only)
适用于最终探测状态为 **MISSING** 且无法/不满足自动绑定的节点。
**本地孤儿 (Local Orphan)**: 本地有，远程无。
| 策略配置 (`local_orphan_action`) | 对应的同步模式 | 动作 (`SyncAction`) |
| :--- | :--- | :--- |
| **"create_remote"** | Push (本地推远端) | **CREATE** |
| **"delete_local"** | Pull (远端拉本地) | **报错 (未实现)** |
| **"none"** | Any | **NONE** |
**远程孤儿 (Remote Orphan)**: 远程有，本地无。
| 策略配置 (`remote_orphan_action`) | 对应的同步模式 | 动作 (`SyncAction`) |
| :--- | :--- | :--- |
| **"create_local"** | Pull (远端拉本地) | **CREATE** |
| **"delete_remote"** | Push (本地推远端) | **报错 (未实现)** |
| **"none"** | Any | **NONE** |
---
## 5. 执行同步状态转换 (Physical Sync State Transitions)
在策略执行完成、设置好 `action` 后，DataSource 层负责执行实际的同步操作并更新 `status` 字段。
### A. 执行状态枚举 (SyncStatus)
| 状态值 | 含义 | 适用场景 |
| :--- | :--- | :--- |
| **PENDING** | 待执行 | 初始状态、无动作的节点 |
| **IN_PROGRESS** | 执行中 | 异步接口已提交，等待结果回调 |
| **SUCCESS** | 执行成功 | 同步操作完成且成功 |
| **FAILED** | 执行失败 | 同步操作失败，`error` 字段记录原因 |
| **SKIPPED** | 已跳过 | 节点被主动跳过（如依赖未满足） |
| **PRECONDITION_FAILED** | 前置条件失败 | create/update 内部验证发现问题 |
### B. 执行转换矩阵
#### 同步接口（一步式）
适用于同步 API（调用后立即返回成功/失败）。
| 输入: action | API 调用结果 | → | 输出: status | 副作用 |
| :--- | :--- | :--- | :--- | :--- |
| **CREATE** | 成功返回 (200/201) | → | **SUCCESS** | `data_id` 设置为远程返回的ID |
| **CREATE** | 失败返回 (4xx/5xx) | → | **FAILED** | `error` 记录错误信息 |
| **UPDATE** | 成功返回 (200) | → | **SUCCESS** | - |
| **UPDATE** | 失败返回 (4xx/5xx) | → | **FAILED** | `error` 记录错误信息 |
| **DELETE** | 成功返回 (200/204) | → | **SUCCESS** | 节点可能被移除 |
| **DELETE** | 失败返回 (4xx/5xx) | → | **FAILED** | `error` 记录错误信息 |
| **NONE** | - | → | **PENDING** | 不执行，保持原状 |
#### 异步接口（两步式）
适用于异步 API（提交后需要轮询或回调获取结果）。
| 输入: action | API 提交结果 | → | 输出: status | 后续操作 |
| :--- | :--- | :--- | :--- | :--- |
| **CREATE** | 提交成功 (202 Accepted) | → | **IN_PROGRESS** | 记录 task_id，等待轮询 |
| **CREATE** | 提交失败 (4xx/5xx) | → | **FAILED** | `error` 记录错误 |
| **IN_PROGRESS** | 轮询返回成功 | → | **SUCCESS** | `data_id` 设置为远程ID |
| **IN_PROGRESS** | 轮询返回失败 | → | **FAILED** | `error` 记录错误 |
| **IN_PROGRESS** | 超时未完成 | → | **FAILED** | `error` 记录 "Timeout" |
### B+. Handler 降级（action 取消）
> **代码实现**：各 `domain/*/api_handler.py` 中的 `update()` 方法。
当 Handler 在构建 API 请求数据时，发现实际无需更新的字段（如 schema 校验后所有字段与远程一致），
Handler 会主动将节点的 `action` 从 `UPDATE` 降级为 `NONE`：
```
action=UPDATE → Handler 校验 → 无实际变更字段 → action=NONE（不提交 API）
```
此机制确保 DataSource 不会向远程发送无意义的空更新请求。
### C. 关键副作用
| 动作 | 成功时的副作用 | 说明 |
| :--- | :--- | :--- |
| **CREATE** | 临时绑定已建立 | 绑定关系可在提交前创建，用于推送与追踪；是否成功不影响该绑定存在 |
| **CREATE** | 设置 `data_id` | 成功后从API响应中提取远程分配的ID，更新到节点 |
| **CREATE** | 回写 `data` 主键 | DataSource 将远程返回的ID写回 `SyncNode.data`（如 `id`/`*_id` 字段） |
| **CREATE** | 更新绑定记录 | 若使用临时ID，成功后替换为真实的远程ID |
| **UPDATE** | 更新 `origin_data` | 将当前 `data` 保存为新的 `origin_data` |
| **DELETE** | 移除绑定记录 | 删除成功后，清除对应的绑定关系 |
### D. 错误处理
| 错误类型 | 记录方式 | 重试策略 |
| :--- | :--- | :--- |
| **网络错误** | `error = "Network timeout"` | 可重试 |
| **权限错误** | `error = "403 Forbidden"` | 不可重试，需人工介入 |
| **数据校验错误** | `error = "Validation failed: ..."` | 不可重试，需修复数据 |
| **依赖缺失** | `status = PRECONDITION_FAILED` | 不执行，等待依赖修复 |
---
## 6. 同步检查规范 (Sync Check Specification)
在执行同步前后，需要进行状态检查以确保操作的合法性和完整性。
### A. 内联前置检查（create/update 阶段）
> **实现说明**：原 `_pre_commit_check` 方法已移除（保留空壳兼容接口）。
> 所有有效检查已内联到 `strategy_ops/create_ops.py::add_create_action()` 和 `strategy_ops/update_ops.py::add_update_action()` 中。
**create() 阶段内联检查**：
| 检查类别 | 检查条件 | 不通过时 | 说明 |
| :--- | :--- | :--- | :--- |
| **数据完整性** | `src_node.get_data()` 不为空 | 跳过该节点，记录日志 | MISSING 但数据为空 |
| **依赖 ID 解析** | `id_resolver.resolve_and_validate()` 成功 | `binding_status → DEPENDENCY_ERROR` | 依赖字段无法解析到目标系统 ID |
**update() 阶段内联检查**：
| 检查类别 | 检查条件 | 不通过时 | 说明 |
| :--- | :--- | :--- | :--- |
| **FAILED 保护** | `src_node.status != FAILED` | 跳过该节点 | 不覆盖上次失败的状态和错误 |
| **数据完整性** | `src_node.get_data()` 不为空 | 跳过该节点 | NORMAL 但数据为空 |
| **目标节点存在** | 通过绑定找到目标节点 | 跳过该节点 | 绑定记录指向的节点不在集合中 |
| **data_id 完整性** | `target_node.data_id` 非空 | `status → PRECONDITION_FAILED` | UPDATE 必须有业务主键 |
| **依赖 ID 解析** | `id_resolver.resolve_and_validate()` 成功 | `status → PRECONDITION_FAILED` | 依赖字段无法解析到目标系统 ID |
| **差异检测** | `_needs_update()` 返回 True | 跳过该节点 | 无差异则不更新 |
> **注意**：以下检查项在当前实现中 **未覆盖**【未实现】：
> - 状态合法性：`binding_status` 必须是已知状态
> - 动作合法性：`CREATE/UPDATE` 只能用于 `NORMAL` 节点
> - 绑定一致性：`NORMAL` 节点必须有绑定记录
### B. 同步后检查 (Post-Sync Check)
**目标**: 验证同步结果的完整性，发现残留问题。
> **实现说明**：当前 `_stage4_post_sync_check` 只打印摘要表格，不做异常检测。以下检查项均为【未实现】。
#### 检查项清单【未实现】
| 检查类别 | 检查条件 | 异常情况 | 严重程度 |
| :--- | :--- | :--- | :--- |
| **CREATE 完成性** | CREATE 节点应该有 `data_id` | `action = CREATE, status = SUCCESS` 但 `data_id = ""` | 🔴 ERROR |
| **CREATE 绑定** | CREATE 节点应该有绑定记录 | CREATE 成功但无绑定 | 🔴 ERROR |
| **UPDATE 完成性** | UPDATE 节点应该成功 | `action = UPDATE` 但 `status = FAILED` | ⚠️ WARNING |
| **绑定保持** | UPDATE 节点的绑定应该保持 | UPDATE 后绑定记录丢失 | 🔴 ERROR |
| **残留异常** | 不应有 ABNORMAL 节点 | 同步后仍有 `binding_status = ABNORMAL` | ⚠️ WARNING |
| **残留依赖错误** | 不应有 DEPENDENCY_ERROR | 同步后仍有依赖阻断 | ⚠️ WARNING |
#### 统计指标
| 指标 | 计算方式 | 用途 |
| :--- | :--- | :--- |
| **成功率** | `SUCCESS / (CREATE + UPDATE)` | 评估同步质量 |
| **异常率** | `(ABNORMAL + WARNING) / total` | 发现数据质量问题 |
| **阻断率** | `DEPENDENCY_ERROR / total` | 发现依赖关系问题 |
#### 决策规则
| 检查结果 | ERROR 数量 | 决策 |
| :--- | :--- | :--- |
| ✅ 通过 | 0 | **继续持久化**，正常结束 |
| ⚠️ 有警告 | 0, WARNING ≥1 | **继续持久化**，打印警告报告 |
| ❌ 有错误 | ≥1 | **继续持久化**（已同步无法回滚），打印错误报告 |
> **注意**: Post-Sync Check 即使有 ERROR 也不会终止流程，因为同步已经执行，无法回滚。检查目的是发现问题并记录，供后续修复。
---
## 附录: 状态字段说明
### SyncNode 核心字段
| 字段 | 类型 | 设置阶段 | 含义 |
| :--- | :--- | :--- | :--- |
| `binding_status` | BindingStatus | Bind 阶段 | 绑定健康状态 |
| `action` | SyncAction | Create/Update 阶段 | 待执行动作 |
| `status` | SyncStatus | Physical Sync 阶段 | 执行结果状态 |
| `data_id` | str | 数据加载 / CREATE 后 | 业务主键ID（CREATE 前为 ""） |
| `depend_ids` | List[str] | 数据加载 | 依赖节点的 node_id 列表 |
| `error` | str \| None | Physical Sync 阶段 | 错误信息（失败时） |
### 状态流转时序
```
[数据加载] [Bind] [Create/Update] [Physical Sync]
binding_status: UNCHECKED → NORMAL/MISSING/... → (保持) → (保持)
action: NONE → NONE → CREATE/UPDATE → (保持)
status: PENDING → PENDING → PENDING → SUCCESS/FAILED
data_id: 从源加载 → (保持) → 可能为 "" → CREATE 后设置
```
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# 状态机形式化规范
本文档用 **Guard-Event-Action (GEA)** 形式严格定义节点状态机。
所有转换以代码实现为准，模糊之处在文档中显式标注。
> **代码基线**
> - 枚举: `sync_system_new/common/types.py`
> - 决策引擎: `sync_system_new/sync_system/decision.py`
> - 重置策略: `sync_system_new/common/state_reset.py`
> - 同步策略: `sync_system_new/sync_system/strategy.py`
> - 物理同步: `sync_system_new/datasource/datasource.py`
> **配置基线（状态机真源）**
> - `sync_system_new/state_machine/node_state_machine.yaml`
### 2026-02 对齐说明（重构前必读）
以下语义以 `node_state_machine.yaml` 为准，用于修正文档中易混淆点：
1. **E12a 为什么从 S01 出发？**
- `S01` 只约束**源节点**是 NORMAL/NONE/PENDING 且有 `data_id`。
- `E12a` 的 guard 是 `target_has_data_id=false`，检查对象是**目标节点**。
- 所以“源节点在 S01”与“E12a 触发前置失败”并不冲突。
2. **S01 会不会触发创建？**
- 当前配置中，create 的入口状态是 `S02(MISSING)`，不是 `S01`。
- `S01` 进入的是 update_prepare（E12/E13/E14）。
3. **N:0 + create_enabled=true 的当前行为**
- 自动绑定分支 `E08f`：`S02 -> S01`，并 `emit spawn_target_node_state: S06`。
- create_prepare 分支 `E09b` 也可在检查成功后 `S02 -> S01 + spawn S06`。
- 即：源节点不会停在“等待创建结果”的专用状态；创建执行结果体现在目标创建节点链路 `S06 -> S10/S11/S12/S13`。
4. **旧章节中的事件编号偏差**
- 本文后续仍有部分“E11a/E11b/…”旧编号描述，已与当前 YAML 不一致。
- 进行代码重构时，优先依据 YAML 的 `E08/E09/E10/E12/E13/E14/E15..E20`。
---
## §1 状态空间定义
### §1.1 状态维度
节点携带 **三个独立的状态字段** 和 **两个辅助字段**：
| 字段 | 枚举 | 值域 | 语义 |
|------|------|------|------|
| **B** – `binding_status` | `BindingStatus` | `UNCHECKED` · `NORMAL` · `MISSING` · `ABNORMAL` · `WARNING` · `DEPENDENCY_ERROR` | 绑定健康度 |
| **A** – `action` | `SyncAction` | `NONE` · `CREATE` · `UPDATE` · `DELETE` | 待执行动作 |
| **S** – `status` | `SyncStatus` | `PENDING` · `IN_PROGRESS` · `SUCCESS` · `FAILED` · `SKIPPED` · `PRECONDITION_FAILED` | 执行结果 |
辅助字段（影响 Guard 但不是状态维度）：
| 字段 | 类型 | 语义 |
|------|------|------|
| `data_id` | `str` | 业务主键（空串 `""` = 尚未从远程获取） |
| `error` | `str \| None` | 最近一次错误信息 |
理论组合 = 6 × 4 × 6 = **144**，实际可达 ≈ **23** 种。
### §1.2 可达状态枚举
以下列出所有在正常流程中可以到达的 `(binding_status, action, status)` 三元组。
| # | binding_status | action | status | 语义 | 产生阶段 |
|---|---|---|---|------|---------|
| R1 | UNCHECKED | NONE | PENDING | 首次加载 | 数据加载 |
| R2 | UNCHECKED | NONE | SUCCESS | 从持久化恢复(上轮成功)后重置 | 阶段1/2重置 |
| R3 | UNCHECKED | NONE | FAILED | 从持久化恢复(上轮失败)后重置 | 阶段1/2重置 |
| R4 | UNCHECKED | NONE | SKIPPED | 从持久化恢复(上轮跳过)后重置 | 阶段1/2重置 |
| R5 | UNCHECKED | NONE | PRECONDITION_FAILED | 从持久化恢复(上轮前置失败)后重置 | 阶段1/2重置 |
| R6 | NORMAL | NONE | PENDING | 绑定正常，无需操作(首次) | bind.p1 |
| R7 | NORMAL | NONE | SUCCESS | 绑定正常，无需操作(历史成功) | bind.p1 |
| R8 | NORMAL | NONE | FAILED | 绑定正常但上次失败，被 FAILED 保护 | bind.p1 |
| R9 | MISSING | NONE | PENDING | 孤儿，等待自动绑定或创建(首次) | bind.p1 |
| R10 | MISSING | NONE | SUCCESS | 孤儿(历史成功但绑定丢失?) | bind.p1 |
| R11 | ABNORMAL | NONE | * | 数据损坏，需人工 | bind.p1 |
| R12 | WARNING | NONE | * | 多候选/对方损坏，需人工 | bind.p1/p3 |
| R13 | DEPENDENCY_ERROR | NONE | PENDING | 依赖不满足 | bind.p2/p3/create |
| R14 | NORMAL | CREATE | PENDING | 准备创建(目标节点) | create |
| R15 | NORMAL | CREATE | IN_PROGRESS | 异步创建进行中 | sync |
| R16 | NORMAL | CREATE | SUCCESS | 创建成功 | sync |
| R17 | NORMAL | CREATE | FAILED | 创建失败 | sync |
| R18 | NORMAL | UPDATE | PENDING | 准备更新(目标节点) | update |
| R19 | NORMAL | UPDATE | IN_PROGRESS | 异步更新进行中 | sync |
| R20 | NORMAL | UPDATE | SUCCESS | 更新成功 | sync |
| R21 | NORMAL | UPDATE | FAILED | 更新失败 | sync |
| R22 | NORMAL | UPDATE | PRECONDITION_FAILED | 更新前置条件失败 | update |
| R23 | NORMAL | CREATE | SKIPPED | 创建被 Handler 跳过 | sync |
> **不可达组合（示例）**：
> - `(MISSING, UPDATE, *)` — MISSING 节点不可能被安排 UPDATE
> - `(ABNORMAL, CREATE, *)` — ABNORMAL 节点不可能被安排 CREATE
> - `(*, DELETE, *)` — DELETE 尚未实现
> - `(UNCHECKED, CREATE, *)` — UNCHECKED 是瞬态，在 bind 之前不会有 CREATE
> - `(DEPENDENCY_ERROR, UPDATE, *)` — DEPENDENCY_ERROR 节点不可能进入 update 流程
### §1.3 辅助字段约束
| 对应状态 | binding_status | action | status | data_id 约束 | error 约束 |
|---------|---|---|---|-------------|-----------|
| R14 | NORMAL | CREATE | PENDING | `""` (待远程返回) | None |
| R16 | NORMAL | CREATE | SUCCESS | 非空 (远程回填) | None |
| R17 | NORMAL | CREATE | FAILED | `""` (未回填) | 非空 |
| R22 | NORMAL | UPDATE | PRECONDITION_FAILED | * | 非空 |
| R13 | DEPENDENCY_ERROR | NONE | PENDING | * | 非空 |
---
## §2 不变量 (Invariants)
以下约束在**任何事件执行后**都必须成立。违反即为 Bug。
```
INV-1 B = UNCHECKED ⟹ A = NONE
(UNCHECKED 是瞬态，在 bind 之前不允许有动作)
INV-2 B ∈ {ABNORMAL, WARNING, DEPENDENCY_ERROR} ⟹ A = NONE
(阻断态节点不允许执行任何同步动作)
INV-3 B = MISSING ⟹ A ∈ {NONE, CREATE}
(MISSING 节点只能等待创建或保持不动)
INV-4 A = CREATE ⟹ B = NORMAL
(CREATE 动作只出现在目标节点上，其 binding_status 已被设为 NORMAL)
INV-5 A = UPDATE ⟹ B = NORMAL
(UPDATE 动作只对 NORMAL 节点执行)
INV-6 S = IN_PROGRESS ⟹ A ∈ {CREATE, UPDATE, DELETE}
(只有提交过 API 的节点才可能处于 IN_PROGRESS)
INV-7 S = PRECONDITION_FAILED ⟹ A = UPDATE
(PRECONDITION_FAILED 只在 update 阶段产生)
INV-8 A = CREATE ∧ S = SUCCESS ⟹ data_id ≠ ""
(创建成功必须回填 data_id)
INV-9 S = FAILED ⟹ error ≠ None
(失败必须有错误信息)
INV-10 B = DEPENDENCY_ERROR ⟹ error ≠ None
(依赖阻断必须有错误信息)
```
---
## §3 事件与转换
### §3.1 事件总览图
```
┌─────────────────────────────────────────────────────┐
│ 节点生命周期事件流 │
└─────────────────────────────────────────────────────┘
持久化恢复 策略层 (Strategy) 执行层 (DataSource)
═══════════ ══════════════════════════════════ ══════════════════════════
┌──────────────────────────────┐
┌──────┐ │ bind() │ ┌──────────────────────┐
│E01 │──────────▶│ E04 ─┐ │ │ sync_all() │
│RESET1│ │ E05 ├─ phase1: core_state │ │ │
└──┬───┘ │ E06 ─┘ │ │ E12 SYNC_OK │
│ │ E07 ── phase2: dep_check │ ┌───▶│ E13 SYNC_FAIL │
┌──▼───┐ │ E08 ─┐ │ │ │ E14 SYNC_ASYNC │
│E02 │ │ E09 ├─ phase3: auto_bind │ │ │ E15 SYNC_TIMEOUT │
│ZOMBIE│ │ E10 ─┘ │ │ │ E16 HANDLER_SKIP │
└──┬───┘ └──────────────────────────────┘ │ │ E17 HANDLER_DOWN │
│ ┌──────────────────────────────┐ │ └──────────────────────┘
┌──▼───┐ │ create() / update() │ │
│E03 │──────────▶│ E11a CREATE_OK │────┘
│RESET2│ │ E11b CREATE_DEP_FAIL │
└──────┘ │ E11c UPDATE_DIFF │
│ E11d UPDATE_PRECOND_FAIL │
│ E11e UPDATE_SKIP_FAILED │
└──────────────────────────────┘
```
### §3.2 状态转换详解
本节按 Pipeline 执行阶段组织。每个阶段包含：
1. **状态转换图**：状态（R 编号）为节点，事件（E 编号）为有向边
2. **转换表**：每个事件的精确规格——起始状态、判断条件、结束状态、副作用
---
#### 🔄 阶段 0：重置
**状态转换图：**
```
╔═══════════════════════════════════════╗
║ 任意持久化终态 (R6 ~ R23) ║
╚═══════════════════╤═══════════════════╝
│ E01
▼
┌────────────────────────────────────────┐ E02
│ 瞬态: UNCHECKED │────────────▶ [节点删除 + 解除绑定]
│ (action 保留, status 保留, error=None) │
└────────────────────┬──────────────────┘
│ E03 (存活节点)
▼
╔══════════════════════════════════════════════════════════════╗
║ [R1] UNCHECKED, NONE, PENDING ← 首次加载 ║
║ [R2] UNCHECKED, NONE, SUCCESS ← 上轮成功 ║
║ [R3] UNCHECKED, NONE, FAILED ← 上轮失败 ║
║ [R4] UNCHECKED, NONE, SKIPPED ← 上轮跳过 ║
║ [R5] UNCHECKED, NONE, PRECONDITION_FAILED ← 上轮前置 ║
╚══════════════════════════════════════════════════════════════╝
```
**转换表：**
| 事件 | 起始状态 | 判断条件 (Guard) | 结束状态 | 副作用 |
|------|---------|-----------------|---------|--------|
| **E01**: PHASE1_RESET | R6~R23 (任意持久化终态) | 节点从持久化加载 | 瞬态 (UNCHECKED, action 保留, status 保留) | error → None; data/origin_data → None |
| **E02**: ZOMBIE_KILL | 瞬态 | action = CREATE ∧ (status = FAILED ∨ data_id = "") | **节点删除** | 解除绑定关系; 对 local/remote 两侧都扫描 |
| **E03**: ACTION_RESET | 瞬态 (存活节点) | E02 完成后所有存活节点 | R1 / R2 / R3 / R4 / R5 (按原 status 分) | action → NONE |
> **代码**: `NodeStateReset.get_phase1_reset_defaults()` · `cleanup_create_failed_zombies()` · `reset_action_for_nodes()`
---
#### 🔗 阶段 1：Bind
Bind 由三个子阶段串行执行。后一阶段只处理前一阶段的遗留 MISSING 节点。
**状态转换图：**
```
[R1~R5] UNCHECKED, NONE, *
│
│ ══════════ Phase 1: 核心状态判定 ══════════
│
├── E04 (有绑定, 双方数据 VALID) ───────────▶ [R6/R7/R8] NORMAL ──────▶ 出口 ✅
├── E04 (有绑定, 自身数据缺失/损坏) ────────▶ [R11] ABNORMAL ─────────▶ 出口 🔒
├── E04 (有绑定, 对方数据缺失/损坏) ────────▶ [R12] WARNING ──────────▶ 出口 🔒
│
└── E05 (无绑定记录) ───────────────────────▶ [R9] MISSING
│
══════════ Phase 2: 依赖检查 ══════════ │
│
├── E06 (data = None) ──────────────────────▶ [R11] ABNORMAL ──────▶ 出口 🔒
├── E07 (依赖节点不满足) ───────────────────▶ [R13] DEP_ERROR ─────▶ 出口 🔒
│ (无依赖配置 或 依赖全部满足 → 继续 ▼)
│
══════════ Phase 3: 自动绑定 ══════════
│
├── E08 (auto_bind 关闭) ──────────────────▶ [R12] WARNING ────────▶ 出口 🔒
├── E09 (去噪后 1:1 匹配成功) ─────────────▶ [R6] NORMAL ─────────▶ 出口 ✅
├── E10a (去噪后非 1:1, 多候选) ───────────▶ [R12] WARNING ────────▶ 出口 🔒
├── E10b (业务键字段缺失) ─────────────────▶ [R12] WARNING ────────▶ 出口 🔒
├── E10c (业务键中 ID 字段解析失败) ───────▶ [R13] DEP_ERROR ─────▶ 出口 🔒
│
└── (1:0 无远程匹配)
├── create_enabled = True → [R9] MISSING ──────────────▶ 进入 create
└── create_enabled = False → [R12] WARNING ─────────────▶ 出口 🔒
```
**转换表：**
| 事件 | 起始状态 | 判断条件 (Guard) | 结束状态 | 副作用 |
|------|---------|-----------------|---------|--------|
| **E04**: BIND_PAIRED | R1~R5 | 有绑定记录 ∧ 双方数据 VALID | R6 (PENDING) / R7 (SUCCESS) / R8 (FAILED) — status 保持 | 远程节点同步设置 binding_status |
| **E04**: BIND_PAIRED (自身异常) | R1~R5 | 有绑定记录 ∧ 本方数据缺失或损坏 | R11 (ABNORMAL) | 对方节点设为 WARNING |
| **E04**: BIND_PAIRED (对方异常) | R1~R5 | 有绑定记录 ∧ 对方数据缺失或损坏 | R12 (WARNING) | 对方节点设为 ABNORMAL |
| **E05**: BIND_ORPHAN | R1~R5 | 无绑定记录 | R9 (MISSING, NONE, status 保持) | — |
| **E06**: DATA_NULL | R9 | binding_status = MISSING ∧ data = None | R11 (ABNORMAL) | error = "数据损坏: 节点数据为空或不存在" |
| **E07**: DEP_CHECK_FAIL | R9 | depend_fields 配置非空 ∧ ∃依赖节点: 不存在 ∨ status ≠ NORMAL ∨ data_id 为空 | R13 (DEPENDENCY_ERROR) | error = "依赖项不满足: ..."; depend_ids 填充 |
| **E08**: AUTOBIND_DISABLED | R9 | auto_bind = False 或 auto_bind_fields 为空 | R12 (WARNING) | — |
| **E09**: AUTOBIND_OK | R9 | 去噪后 local:remote = 1:1 ∧ 双方都是 MISSING | R6 (NORMAL) | 建立绑定记录; 双方都设为 NORMAL |
| **E10a**: AUTOBIND_AMBIGUOUS | R9 | 去噪后非 1:1 (多候选) | R12 (WARNING) | error += "存在多个候选节点" |
| **E10b**: AUTOBIND_KEY_MISSING | R9 | auto_bind_fields 中有字段不存在于 data | R12 (WARNING) | error += "缺少业务键字段: ..." |
| **E10c**: AUTOBIND_ID_FAIL | R9 | 业务键包含 ID 字段 ∧ ID 解析失败 | R13 (DEPENDENCY_ERROR) | error = "业务键中的ID字段解析失败: ..." |
| **E10d**: ORPHAN_CREATE_DISABLED | R9 | 去噪后 1:0 ∧ create_enabled = False | R12 (WARNING) | error += "孤儿且不允许自动创建" |
> **E04 核心状态矩阵** (完整查表):
>
> | | 远程: VALID | 远程: ABSENT | 远程: INVALID |
> |---|---|---|---|
> | **本地: VALID** | 本:NORMAL 远:NORMAL | 本:WARNING 远:ABNORMAL | 本:WARNING 远:ABNORMAL |
> | **本地: ABSENT** | 本:ABNORMAL 远:WARNING | 本:ABNORMAL 远:ABNORMAL | — |
> | **本地: INVALID** | 本:ABNORMAL 远:WARNING | — | 本:ABNORMAL 远:ABNORMAL |
>
> 不在矩阵中的组合 → 默认 (ABNORMAL, ABNORMAL)
> **代码**: `SyncDecisionEngine.determine_core_status()` · `strategy_ops/bind_ops.py::phase_core_state()` · `strategy_ops/bind_ops.py::check_dependencies_for_nodes()` · `strategy_ops/bind_ops.py::phase_auto_binding()`
---
#### ⚡ 阶段 2：Create / Update
**状态转换图：**
```
═══════════════ Create ═══════════════
[R9] MISSING, NONE, PENDING (源节点, data ≠ None)
│
├── E11a (ID 解析成功) ────▶ 源节点: [R9] → [R6] NORMAL
│ 新建目标节点: → [R14] NORMAL, CREATE, PENDING
│ + 建立绑定记录, 目标 data_id = ""
│
└── E11b (ID 解析失败) ────▶ 源节点: [R9] → [R13] DEPENDENCY_ERROR
═══════════════ Update ═══════════════
[R6/R7] NORMAL, NONE, PENDING/SUCCESS (源节点, status ≠ FAILED)
│
├── E11c (差异检测通过) ────▶ 目标节点 → [R18] NORMAL, UPDATE, PENDING
├── E11d.1 (目标 data_id="") ▶ 目标节点 → [R22] status = PRECONDITION_FAILED
├── E11d.2 (ID 解析失败) ───▶ 目标节点 → [R22] action = UPDATE, status = PRECOND_FAIL
└── (无差异) ──────────────▶ 保持不变
═══════════════ FAILED 保护 ═══════════════
[R8] NORMAL, NONE, FAILED (源节点)
│
└── E11e ──────────────────▶ 跳过，保持 [R8] 不变
```
**转换表：**
| 事件 | 起始状态 (源节点) | 判断条件 (Guard) | 结束状态 | 副作用 |
|------|---------|-----------------|---------|--------|
| **E11a**: CREATE_OK | R9 (MISSING) | data ≠ None ∧ IDResolver.resolve_and_validate() = OK | 源 → R6 (NORMAL); **新建**目标 → R14 | 建立绑定; 新节点 data = 已替换 ID 的副本, data_id = "" |
| **E11b**: CREATE_DEP_FAIL | R9 (MISSING) | data ≠ None ∧ IDResolver.resolve_and_validate() = FAIL | R13 (DEPENDENCY_ERROR) | error = "创建时依赖 ID 未解析: ..." |
| **E11c**: UPDATE_DIFF | R6/R7 (NORMAL, status≠FAILED) | 目标存在 ∧ 目标 data_id ≠ "" ∧ ID 解析 OK ∧ _needs_update() = True | 目标 → R18 (UPDATE, PENDING) | 目标: data 替换, error = None |
| **E11d**: UPDATE_PRECOND_FAIL | R6/R7 (NORMAL, status≠FAILED) | 目标 data_id = "" (d1) 或 ID 解析失败 (d2) | 目标 → R22 (UPDATE, PRECONDITION_FAILED) | error = "目标缺少 data_id" 或 "依赖 ID 未解析" |
| **E11e**: UPDATE_SKIP_FAILED | R8 (NORMAL, FAILED) | status = FAILED | R8 不变 | 保护上次的 error 和 FAILED 状态，不做任何修改 |
> **代码**: `strategy_ops/create_ops.py::add_create_action()` · `strategy_ops/update_ops.py::add_update_action()`
---
#### 📡 阶段 3：Sync（物理同步）
**状态转换图：**
```
[R14] NORMAL, CREATE, PENDING [R18] NORMAL, UPDATE, PENDING
│ │
└───────────────┬───────────────────┘
│
├── E12 (API 成功) ──────▶ [R16] CREATE,SUCCESS / [R20] UPDATE,SUCCESS
├── E13 (API 失败) ──────▶ [R17] CREATE,FAILED / [R21] UPDATE,FAILED
├── E16 (Handler 跳过) ──▶ [R23] CREATE, SKIPPED
├── E17 (Handler 降级) ──▶ [R6] NORMAL, NONE, PENDING (仅 UPDATE)
│
└── E14 (异步提交) ──────▶ [R15] CREATE,IN_PROGRESS / [R19] UPDATE,INP
│
├── (轮询成功) ──▶ [R16] / [R20] SUCCESS
└── E15 (超时) ──▶ [R17] / [R21] FAILED
```
**转换表：**
| 事件 | 起始状态 | 判断条件 (Guard) | 结束状态 | 副作用 |
|------|---------|-----------------|---------|--------|
| **E12**: SYNC_OK | R14 或 R18 | Handler API 返回 SUCCESS | R16 (CREATE) 或 R20 (UPDATE) | error → None; data_id 回填 (CREATE); origin_data 更新 (UPDATE) |
| **E13**: SYNC_FAIL | R14 或 R18 | Handler API 返回 FAILED | R17 (CREATE) 或 R21 (UPDATE) | error = Handler 返回的错误信息 |
| **E14**: SYNC_ASYNC | R14 或 R18 | Handler API 返回 IN_PROGRESS | R15 (CREATE) 或 R19 (UPDATE) | 记录 task_id, 进入轮询队列 |
| **E15**: SYNC_TIMEOUT | R15 或 R19 | 轮询次数 > max_retries | R17 (CREATE) 或 R21 (UPDATE) | error = "Async task timeout after N seconds" |
| **E16**: HANDLER_SKIP | R14 或 R18 | Handler API 返回 SKIPPED | R23 (CREATE,SKIPPED) | error → None |
| **E17**: HANDLER_DOWNGRADE | R18 (仅 UPDATE) | Handler 运行时发现无实际变更字段 | R6 (NORMAL, NONE, PENDING) | action: UPDATE → NONE; 不提交 API; 统计列从 update 移入 none |
> **代码**: `BaseDataSource._handle_task_result()` · `_poll_async_tasks()` · `domain/*/api_handler.py`
---
## §4 终态分类与死胡同
### §4.1 终态分类
| 分类 | 状态 | (binding_status, action, status) | 语义 | 下一轮行为 |
|------|------|------|------|---------|
| ✅ 成功 | R16 | (NORMAL, CREATE, SUCCESS) | 创建成功 | →R2→bind→R7→update 检查 |
| ✅ 成功 | R20 | (NORMAL, UPDATE, SUCCESS) | 更新成功 | →R2→bind→R7→update 检查 |
| ❌ 失败 | R17 | (NORMAL, CREATE, FAILED) | 创建失败 | E02 zombie 判定→删除节点→对方回到 R9 重建 |
| ❌ 失败 | R21 | (NORMAL, UPDATE, FAILED) | 更新失败 | →R3→bind→R8→FAILED 保护(E11e)→保持 |
| 🔒 阻断 | R11 | (ABNORMAL, NONE, \*) | 数据损坏 | 每轮重新 bind 检查; 需人工修复数据 |
| 🔒 阻断 | R12 | (WARNING, NONE, \*) | 多候选/对方异常 | 每轮重新 bind 检查; 需人工绑定或修复 |
| 🔒 阻断 | R13 | (DEPENDENCY_ERROR, NONE, PENDING) | 依赖不满足 | 每轮重新检查依赖; 依赖修复后自动恢复 |
| ⏭ 跳过 | R23 | (NORMAL, CREATE, SKIPPED) | Handler 跳过创建 | →R4→bind→R6→update 检查（无绑定则再 create） |
| 🔄 异步 | R15 | (NORMAL, CREATE, IN\_PROGRESS) | 创建异步中 | 轮询直到 SUCCESS 或超时→FAILED |
| 🔄 异步 | R19 | (NORMAL, UPDATE, IN\_PROGRESS) | 更新异步中 | 轮询直到 SUCCESS 或超时→FAILED |
| 🔄 前置失败 | R22 | (NORMAL, UPDATE, PRECONDITION\_FAILED) | 前置条件不满足 | →R5→bind→R6/R7→update 重试 |
### §4.2 恢复路径
```
R17 (CREATE, FAILED):
持久化 → 下轮 E01 → 瞬态(UNCHECKED, CREATE, FAILED)
→ E02: action=CREATE ∧ (status=FAILED ∨ data_id="") → 满足 zombie 条件
→ 删除节点 + 解除绑定
→ 对方节点回到 R9 (MISSING) → 重新进入 create 流程
R21 (UPDATE, FAILED):
持久化 → 下轮 E01 → 瞬态(UNCHECKED, UPDATE, FAILED)
→ E02: action=UPDATE ≠ CREATE → 非 zombie，存活
→ E03: action → NONE → R3 (UNCHECKED, NONE, FAILED)
→ bind → R8 (NORMAL, NONE, FAILED)
→ E11e: FAILED 保护 → 跳过 update → 保持 R8
⚠ 需人工清除 FAILED 才能恢复
R22 (UPDATE, PRECONDITION_FAILED):
持久化 → 下轮 E01 → 瞬态(UNCHECKED, UPDATE, PRECONDITION_FAILED)
→ E02: action=UPDATE ≠ CREATE → 非 zombie，存活
→ E03: action → NONE → R5 (UNCHECKED, NONE, PRECONDITION_FAILED)
→ bind → R6/R7 (NORMAL) → update 流程重试
R11 (ABNORMAL):
每轮 E01 重置 → bind 重新检查
→ 若数据被人工修复 → E04 → R6/R7/R8 (NORMAL)
→ 若数据仍损坏 → 再次 R11
R12 (WARNING):
每轮 E01 重置 → bind 重新检查
→ 若人工建立了绑定 → E04 → R6/R7 (NORMAL)
→ 若对方数据被修复 → E04 → R6/R7 (NORMAL)
R13 (DEPENDENCY_ERROR):
每轮 E01 重置 → bind 重新检查依赖
→ 依赖节点达到 NORMAL 且 data_id 非空后
→ E07 通过 → 继续 auto_bind 或 create 流程
```
### §4.3 FAILED 保护机制详解
FAILED 保护确保失败节点不会被后续流程静默覆盖，保留 error 信息供人工调查。
```
进入条件:
节点经过 bind 后为 R8 (NORMAL, NONE, FAILED)
即: 绑定关系正常，但上一轮执行失败
保护行为:
`strategy_ops/update_ops.py::add_update_action()` 中:
if source.status == SyncStatus.FAILED:
skip (→ 事件 E11e)
结果: R8 原样保持 → 持久化 → 下一轮依然 R8
解除条件 (需人工介入):
1. 清除 error 字段 (→ None)
2. 将 status 改为 PENDING 或 SUCCESS
3. 下轮 bind 后 → R6 或 R7 → 正常进入 update 流程
```
---
## §5 完备性分析
### §5.1 状态 × 事件矩阵
行 = 当前状态，列 = 可能触发的事件。`→Rx` = 转换到目标状态，`—` = 不可能触发。
| 状态 | E01 | E02 | E03 | E04/E05 | E06~E10 | E11a/b | E11c/d/e | E12~E17 |
|------|-----|-----|-----|---------|---------|--------|----------|---------|
| R1~R5 | — | — | — | →R6~R13 | — | — | — | — |
| R6/R7 | →瞬态 | — | — | — | — | — | →R18/R22 | — |
| R8 | →瞬态 | — | — | — | — | — | →R8(skip) | — |
| R9 | →瞬态 | — | — | — | →R6/R11~R13 | →R6+R14/R13 | — | — |
| R11~R13 | →瞬态 | — | — | — | — | — | — | — |
| R14 | →瞬态 | — | — | — | — | — | — | →R15~R17/R23 |
| R15 | →瞬态 | — | — | — | — | — | — | →R16/R17 |
| R18 | →瞬态 | — | — | — | — | — | — | →R6/R19~R21/R23 |
| R19 | →瞬态 | — | — | — | — | — | — | →R20/R21 |
| R16/R17 | →瞬态 | — | — | — | — | — | — | — |
| R20~R23 | →瞬态 | — | — | — | — | — | — | — |
> **读表方式**: 找到当前状态行和事件列组的交叉点，即可得到目标状态。`—` 表示该状态不可能触发该事件。
### §5.2 已知 GAP
| GAP | 描述 | 风险 | 建议 |
|-----|------|------|------|
| GAP-1 | `set_binding_status()` / `set_action()` / `set_status()` 是纯 setter，不验证转换合法性 | 中 | 加入前置断言：检查 (当前状态, 新状态) 是否匹配某条已知转换 |
| GAP-2 | INV-1 ~ INV-10 未在代码中 assert | 中 | 每次 setter 调用后或阶段结束时断言所有不变量 |
| GAP-3 | R22 (PRECONDITION\_FAILED) 节点下一轮行为路径需验证 | 低 | 已补充恢复路径: R22→E01→E03→R5→bind→R6/R7→update 重试 |
| GAP-4 | Handler 降级 (E17) 后 status 残留为 PENDING 但 action 已清零 | 低 | 可考虑降级时同时重置 status 为 SUCCESS（当前保持 PENDING） |
| GAP-5 | 物理同步后缺少整体一致性检查 (post-sync invariant check) | 低 | 在 `sync_all()` 结束后遍历所有节点验证 INV-1 ~ INV-10 |
---
## §6 引用
| 文档 | 路径 |
|------|------|
| 枚举定义 | `sync_system_new/common/types.py` |
| 决策引擎 | `sync_system_new/sync_system/decision.py` |
| 重置策略 | `sync_system_new/common/state_reset.py` |
| 同步策略 | `sync_system_new/sync_system/strategy.py` |
| 物理同步 | `sync_system_new/datasource/datasource.py` |
| ID 解析 | `sync_system_new/sync_system/resolve_ids.py` |
| 节点生命周期(叙事) | [节点生命周期状态转移](./节点生命周期状态转移.md) |
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# 同步编排流程规范 (Pipeline Specification)
本文档定义了完整的同步编排流程，包括各阶段的职责、节点状态转换和检查点。
> **详细的状态定义和转换规则，请参考**: [STATE_DEFINITIONS.md](../sync_system/STATE_DEFINITIONS.md)
---
## 流程概览
同步系统的完整执行流程分为 5 个阶段：
```
┌─────────────────────────────────────────────────────────────┐
│ Stage 0: 初始化 (Initialization) │
├─────────────────────────────────────────────────────────────┤
│ - 创建 Collection (Local/Remote) │
│ - 创建 BindingManager │
│ - 注册 SyncStrategy (各业务类型) │
│ - 创建 DataSource (Local/Remote) │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Stage 1: 数据加载 (Data Loading) │
├─────────────────────────────────────────────────────────────┤
│ 节点状态: binding_status=UNCHECKED, action=NONE, status=PENDING │
│ - Persistence.load_nodes() → 从持久化恢复 │
│ - DataSource.load_all() → 从数据源加载 │
│ - BindingManager.load_bindings() → 加载绑定关系 │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Stage 2 & 3: 策略执行与同步 (按 node_type 顺序) │
├─────────────────────────────────────────────────────────────┤
│ For each node_type in sync_order: │
│ ┌─────────────────────────────────────────────────┐ │
│ │ 2.1 bind() → 绑定判定 │ │
│ │ 2.2 create() → 设置 CREATE action │ │
│ │ └─ 内联 ID 解析 + 前置检查 │ │
│ │ 2.3 Commit Creates → 立即同步 CREATE 节点 │ │
│ │ └─ DataSource.sync_all(poll_async=True) │ │
│ │ 2.4 update() → 设置 UPDATE action │ │
│ │ └─ 内联 ID 解析 + 前置检查 │ │
│ │ 2.5 Commit Updates → 立即同步 UPDATE 节点 │ │
│ │ └─ DataSource.sync_all(poll_async=True) │ │
│ └─────────────────────────────────────────────────┘ │
│ │
│ 说明： │
│ - 每个 node_type 完整同步后才处理下一个（保证依赖顺序） │
│ - commit 操作内部包含异步轮询，无需独立轮询阶段 │
│ - sync_all() 自动过滤 action=CREATE/UPDATE 的节点 │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Stage 4: 同步结果报告 (Summary Report) │
├─────────────────────────────────────────────────────────────┤
│ - 打印同步结果摘要 │
│ * 节点统计（按 action/status 分类） │
│ * 绑定关系统计 │
│ * 异常节点检查（data_id 缺失、绑定缺失等） │
│ - 收集统计信息（成功/失败/残留问题） │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Stage 5: 状态持久化 (State Persistence) │
├─────────────────────────────────────────────────────────────┤
│ - Collection.persist() → 保存节点状态 │
│ - BindingManager.persist() → 保存绑定关系 │
└─────────────────────────────────────────────────────────────┘
↓
【流程完成】
```
---
## 各阶段节点状态
### Stage 0: 初始化
**输出**: 所有组件实例化完成。
---
### Stage 1: 数据加载
**节点状态**:
```python
binding_status = BindingStatus.UNCHECKED # 未判定
action = SyncAction.NONE # 无动作
status = SyncStatus.PENDING # 待处理
data_id = <从数据源加载> # 已有业务ID
origin_data = <从数据源加载> # 原始数据快照
data = <从数据源加载> # 当前数据
depend_ids = <从数据源加载> # 依赖节点列表
```
**关键点**:
- `data_id` 在加载时**必定有值**（来自数据源）
- 只有待创建的新节点 `data_id` 才可能为 ""（空字符串）
- 从持久化恢复时应重置所有 `action` 为 `NONE`
- `binding_status` 初始值是 `UNCHECKED`，不是 `None`
---
### Stage 2.1: Bind (状态判定)
**状态转换**: `binding_status: UNCHECKED → NORMAL/MISSING/ABNORMAL/WARNING/DEPENDENCY_ERROR`
**可能的结果状态**:
| 结果状态 | 含义 | 占比 |
|---------|------|-----|
| **NORMAL** | 有绑定，数据健康 | 大部分 |
| **MISSING** | 无绑定，孤儿节点 | 少量 |
| **ABNORMAL** | 有绑定，自身数据损坏 | 极少 |
| **WARNING** | 有绑定，对方数据损坏 | 极少 |
| **DEPENDENCY_ERROR** | 依赖未满足 | 少量 |
**详细规则**: 参考 [STATE_DEFINITIONS.md § 1-3](../sync_system/STATE_DEFINITIONS.md)
**补充约束**:
- 若依赖节点 `binding_status = NORMAL` 但 `data_id` 为空（含 `status = FAILED`），视为依赖阻断。
- 只要依赖节点已回填 `data_id`，即使其 `status = FAILED`，后续类型仍允许进入 Create/Update。
- 自动绑定只在**业务键完整且唯一**时才尝试：
- 若业务键字段缺失（如 `serial_number = null`），设置 `binding_status = WARNING`，并在 `node.error` 记录原因：`Auto-bind skipped: missing fields ...`。
- 若同一业务键出现多对多/多对一，设置 `binding_status = WARNING`，并在 `node.error` 记录原因：`Auto-bind skipped: ambiguous candidates`。
- 以上情况仅记录 **Warning**，不进行自动绑定。
---
### Stage 2.2: Create (孤儿处理)
**状态转换**: `action: NONE → CREATE` (对 MISSING 节点)
**补充约束**:
- `binding_status = WARNING` 的节点不会进入 CREATE（`create()` 只查找 MISSING 节点）
- 创建时会通过 `IDResolver.resolve_and_validate()` 二次验证依赖 ID，失败则设置 `DEPENDENCY_ERROR`
**副作用**:
- 在对方 Collection 创建新节点
- 新节点的 `binding_status = NORMAL, action = CREATE, data_id = ""`
- 建立绑定记录
- 原 MISSING 节点也变为 `NORMAL`
**示例**:
```
Before:
local_node: binding_status=MISSING, action=NONE
After Create:
local_node: binding_status=NORMAL, action=NONE
remote_node (新建): binding_status=NORMAL, action=CREATE, data_id=""
绑定记录: local_id ↔ remote_temp_id
```
---
### Stage 2.3: Update (差异同步)
**状态转换**: `action: NONE → UPDATE` (对 NORMAL 且有差异的节点)
**前提条件**:
- `binding_status = NORMAL`
- `status != FAILED`（保护上次失败的状态和错误信息）
- `compute_diff()` 判定有差异
- 配置的 `update_direction` 决定哪一方节点设置 UPDATE
**内联检查**：
- 目标节点 `data_id` 为空 → `status = PRECONDITION_FAILED`
- `IDResolver.resolve_and_validate()` 失败 → `status = PRECONDITION_FAILED`
- Handler 校验后无实际变更字段 → `action` 降级为 `NONE`（不提交）
---
### Stage 2 & 3: 策略执行与同步
**执行顺序**: 按 `sync_order` 顺序逐个处理 node_type
**单个 node_type 的完整流程**:
```
For node_type in sync_order:
┌─────────────────────────────────────────────┐
│ 2.1 Bind - 绑定判定 │
│ - 设置 binding_status: NORMAL/MISSING/... │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ 2.2 Create - 创建策略 │
│ - 处理 MISSING 节点，设置 action=CREATE │
│ - 内联 ID 解析验证 (resolve_and_validate) │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ 2.3 Commit Creates - 立即同步 CREATE │
│ - DataSource.sync_all(poll_async=True) │
│ - 自动过滤 action=CREATE 的节点 │
│ - 内部包含异步轮询（IN_PROGRESS→SUCCESS）│
│ - ⭐ 执行 data_id 回填和绑定更新 │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ 2.4 Update - 更新策略 │
│ - 处理差异节点，设置 action=UPDATE │
│ - 内联 ID 解析验证 + data_id 检查 │
│ - FAILED 节点自动跳过 │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ 2.5 Commit Updates - 立即同步 UPDATE │
│ - DataSource.sync_all(poll_async=True) │
│ - 自动过滤 action=UPDATE 的节点 │
│ - 内部包含异步轮询（IN_PROGRESS→SUCCESS）│
└─────────────────────────────────────────────┘
↓
下一个 node_type
```
**关键特性**:
1. **按类型顺序**: 每个 node_type 完全同步后才处理下一个（保证依赖顺序）
2. **立即提交**: create/update 后立即同步，不等待所有策略执行完
3. **内置轮询**: `sync_all(poll_async=True)` 内部自动轮询异步任务
4. **data_id 回填**: CREATE 成功后立即回填 data_id，下游依赖可用
**同步状态转换**:
**同步接口（一步式）**:
```
action=CREATE, API 成功 → status=SUCCESS, data_id=<远程ID>
action=CREATE, API 失败 → status=FAILED, error=<错误信息>
action=UPDATE, API 成功 → status=SUCCESS
action=UPDATE, API 失败 → status=FAILED, error=<错误信息>
action=NONE → status=PENDING (不执行)
```
**异步接口（两步式，内置轮询）**:
```
action=CREATE, 提交成功 → status=IN_PROGRESS, task_id=<任务ID>
status=IN_PROGRESS, 轮询中... → status=IN_PROGRESS (保持)
status=IN_PROGRESS, 轮询成功 → status=SUCCESS, data_id=<远程ID>
status=IN_PROGRESS, 轮询失败 → status=FAILED, error=<错误信息>
status=IN_PROGRESS, 超时 → status=FAILED, error="Timeout"
```
**关键副作用**（由 DataSource 在 sync_all 中执行）:
- CREATE 成功: `data_id` 从 "" 更新为远程分配的 ID，并回写 `data` 主键字段
- CREATE 成功: 绑定记录从临时ID更新为真实ID
- UPDATE 成功: `origin_data` 更新为当前 `data`
- DELETE 成功: 移除绑定记录
**skip_sync 处理**:
- 如果 `strategy.skip_sync = True`，跳过 create/update/commit 步骤
- bind 步骤始终执行（用于状态判定）
**详细规则**: 参考 [STATE_DEFINITIONS.md § 5](../sync_system/STATE_DEFINITIONS.md)
---
### Stage 4: 同步结果报告
**目标**: 打印同步结果摘要，帮助用户了解同步情况
**报告内容**:
1. **节点统计**：按 node_type 统计各种 action/status 的节点数量
2. **绑定关系**：每个 node_type 的绑定记录数
3. **异常检查**：扫描并报告异常情况：
- CREATE 成功但 data_id 为空（DataSource 回填失败）
- CREATE 成功但绑定记录缺失
- UPDATE/CREATE 失败的节点及错误原因
**输出示例**:
```
================================================================================
📊 Local Collection Summary
================================================================================
Node Type Bindings Create Update Delete None Total
--------------------------------------------------------------------------------
project 5/5 0(0/0/0) 2(2/0/0) 0(0/0/0) 3 5(5/0/0)
contract 10/12 2(2/0/0) 5(5/0/0) 0(0/0/0) 5 12(12/0/0)
```
**注意**: 此阶段不修改任何状态，仅作为信息展示。
---
### Stage 5: 状态持久化
**持久化内容**:
- `binding_status`, `action`, `status` 的最终值
- `data_id` (可能在 CREATE 后更新)
- `error` (如果失败)
- 绑定关系的完整映射
---
## 错误处理策略
| 阶段 | 失败类型 | 处理策略 |
|------|---------|---------|
| Stage 0 | 初始化失败 | **终止流程**，抛出异常 |
| Stage 1 | 数据加载失败 | **终止流程**，抛出异常 |
| Stage 2 & 3 | 代码异常 | **终止流程**，抛出异常 |
| Stage 2: create/update 内联检查 | 依赖ID未解析、data_id缺失 | **继续流程**，节点标记为 DEPENDENCY_ERROR 或 PRECONDITION_FAILED |
| Stage 2 & 3 | API 调用失败 | **继续流程**，标记节点 FAILED |
| Stage 4 | - | 总是继续，仅作为报告 |
| Stage 5 | 持久化失败 | **记录错误**，不影响内存状态 |
---
## 节点状态完整时间线
```
┌──────────────┬─────────────┬────────┬────────┬─────────┐
│ 阶段 │ binding_ │ action │ status │ data_id │
│ │ status │ │ │ │
├──────────────┼─────────────┼────────┼────────┼─────────┤
│ 数据加载 │ UNCHECKED │ NONE │PENDING │ 已加载 │
│ Bind │ NORMAL/... │ NONE │PENDING │ 已加载 │
│ Create │ NORMAL │ CREATE │PENDING │ ""* │
│ Commit Create│ NORMAL │ CREATE │SUCCESS │ 远程ID** │
│ Update │ NORMAL │ UPDATE │PENDING │ 已加载 │
│ Commit Update│ NORMAL │ UPDATE │SUCCESS │ 已加载 │
└──────────────┴─────────────┴────────┴────────┴─────────┘
* 新创建的节点 data_id 初始为 ""
** CREATE 成功后 data_id 立即更新为远程分配的ID，下游依赖可用
```
---
## 配置驱动的流程控制
### 跳过某些阶段
```python
pipeline_config = {
"skip_bind": False, # 是否跳过 bind
"skip_create": False, # 是否跳过 create
"skip_update": False, # 是否跳过 update
"skip_post_check": False, # 是否跳过同步后检查
"fail_on_warning": False, # Pre-Check 时是否将 WARNING 视为失败
}
```
> **注意**：`skip_pre_check` 已移除，原 `_pre_commit_check` 逻辑已内联到 create/update 方法中。
```
### 策略预设应用
```python
# 首次同步：启用自动绑定，双向创建
for strategy in strategies:
strategy.apply_preset("first_sync")
# 日常同步：仅推送更新
for strategy in strategies:
strategy.apply_preset("push_only")
```
---
## 幂等性保证
**要求**: 同一个 Collection 的多次同步应该是幂等的。
**设计保证**:
1. **Bind 阶段**: 基于绑定记录判定，已绑定节点不会重复绑定
2. **Create 阶段**: 已有绑定的节点 (NORMAL) 不会重复创建
3. **Update 阶段**: 基于 `compute_diff()` 判定，无差异则不执行
4. **Sync 阶段**: `action=NONE` 的节点跳过执行
**前提条件**:
- 绑定记录正确持久化
- 节点的 `binding_status` 正确保存和加载
- `compute_diff()` 逻辑准确
---
## 监控和日志
### 关键指标
| 指标 | 含义 | 阶段 |
|------|------|-----|
| `nodes_loaded` | 加载的节点总数 | Stage 1 |
| `nodes_normal` | NORMAL 状态节点数 | Stage 2.1 |
| `nodes_missing` | MISSING 状态节点数 | Stage 2.1 |
| `nodes_abnormal` | ABNORMAL+WARNING 节点数 | Stage 2.1 |
| `nodes_dep_error` | DEPENDENCY_ERROR 节点数 | Stage 2.1 |
| `actions_create` | CREATE 动作节点数 | Stage 2.2 |
| `actions_update` | UPDATE 动作节点数 | Stage 2.3 |
| `sync_success` | 同步成功节点数 | Stage 3 |
| `sync_failed` | 同步失败节点数 | Stage 3 |
| `success_rate` | 成功率 (success/total) | Stage 4 |
### 日志级别
```
INFO: 流程阶段切换、统计信息
DEBUG: 节点级别的详细操作
WARN: 检查发现的警告、同步失败
ERROR: 检查发现的错误、致命异常
```
---
## 参考文档
- [STATE_DEFINITIONS.md](../sync_system/STATE_DEFINITIONS.md) - 详细的状态定义和转换规则
- [CHECK_SPEC.md](./CHECK_SPEC.md) - 检查点的实现细节和代码示例（可选）
# 1. 持久化 Collection
await local_collection.persist()
await remote_collection.persist()
# 2. 持久化 Binding
await binding_manager.persist()
```
**持久化内容**:
- 节点的 `binding_status`, `action`, `status`, `error`
- 节点的 `data_id`（可能在 CREATE 后更新）
- 绑定关系的完整映射
---
## 错误处理策略
### 各阶段的失败处理
| 阶段 | 失败原因示例 | 处理策略 |
|------|------------|---------|
| Stage 1: 数据加载 | 网络错误、文件缺失 | **终止流程**，抛出异常 |
| Stage 2.1: Bind | 代码bug | **终止流程**，抛出异常 |
| Stage 2.2-2.3: Create/Update | 代码bug | **终止流程**，抛出异常 |
| Stage 2: create/update 内联检查 | 依赖ID未解析、data_id缺失 | **继续流程**，节点标记为 DEPENDENCY_ERROR 或 PRECONDITION_FAILED |
| Stage 3: Physical Sync | API错误、权限不足 | **继续流程**，标记节点为 FAILED |
| Stage 4: Post-Sync Check | 部分节点同步失败 | **继续流程**，打印警告 |
| Stage 5: Persistence | 磁盘满、权限错误 | **记录错误**，但不影响内存状态 |
### 部分成功的处理
在 Stage 3 中，允许部分节点成功、部分失败：
- 成功的节点: `status = SUCCESS`
- 失败的节点: `status = FAILED`, `error = "错误信息"`
Post-Sync Check 会统计成功率并给出警告。
---
## 配置驱动的流程控制
### 跳过某些阶段
通过配置控制哪些阶段执行：
```python
pipeline_config = {
"skip_bind": False, # 是否跳过 bind
"skip_create": False, # 是否跳过 create
"skip_update": False, # 是否跳过 update
"skip_post_check": False, # 是否跳过同步后检查
"fail_on_warning": False, # 是否将 WARNING 也视为失败
}
```
### 策略预设应用
在 Stage 2 之前，可以应用策略预设：
```python
# 首次同步：启用自动绑定，双向创建
for strategy in strategies:
strategy.apply_preset("first_sync")
# 日常同步：仅推送更新
for strategy in strategies:
strategy.apply_preset("push_only")
```
---
## 监控和日志
### 关键指标
在各阶段收集以下指标：
| 指标 | 含义 |
|------|------|
| `nodes_loaded` | 加载的节点总数 |
| `nodes_bound` | 成功绑定的节点数 |
| `nodes_missing` | MISSING 状态的节点数 |
| `nodes_abnormal` | ABNORMAL/WARNING 状态的节点数 |
| `nodes_created` | CREATE 动作的节点数 |
| `nodes_updated` | UPDATE 动作的节点数 |
| `sync_success` | 同步成功的节点数 |
| `sync_failed` | 同步失败的节点数 |
| `errors_count` | 检查发现的 ERROR 数量 |
| `warnings_count` | 检查发现的 WARNING 数量 |
### 日志级别
```
INFO: 流程阶段切换、统计信息
DEBUG: 节点级别的详细操作
WARN: 检查发现的警告
ERROR: 检查发现的错误、异常
```
---
## 幂等性保证
**要求**: 同一个 Collection 的多次同步应该是幂等的。
**设计保证**:
1. **Bind 阶段**: 基于绑定记录判定状态，已绑定的节点不会重复绑定
2. **Create 阶段**: 已有绑定的节点（NORMAL）不会重复创建
3. **Update 阶段**: 基于 `compute_diff()` 判定，无差异则不执行
4. **Sync 阶段**: DataSource 根据 `action` 执行，`action=NONE` 的节点跳过
**前提条件**:
- Binding 记录正确持久化
- 节点的 `binding_status` 正确保存和加载
- `compute_diff()` 逻辑准确
---
## 下一步
详细的检查规范和状态转换规则，请参考：
- [CHECK_SPEC.md](./CHECK_SPEC.md) - 检查点详细规范
- [STATE_TRANSITIONS.md](./STATE_TRANSITIONS.md) - 状态转换表
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# 节点生命周期状态转移 (Node Lifecycle State Transitions)
本文档从一个**单节点视角**出发，完整描述一个 `SyncNode` 从诞生到持久化的全部状态变化。
> **代码映射**：
> - 持久化重置：`sync_system_new/common/state_reset.py` → `NodeStateReset`
> - 绑定判定：`sync_system_new/sync_system/decision.py` → `SyncDecisionEngine`
> - 策略执行：`sync_system_new/sync_system/strategy.py` → `DefaultSyncStrategy`
> - ID 解析：`sync_system_new/sync_system/resolve_ids.py` → `IDResolver`
> - 物理同步：`sync_system_new/datasource/datasource.py` → `BaseDataSource`
> - Handler 降级：`sync_system_new/domain/*/api_handler.py`
---
## 状态字段一览
| 字段 | 类型 | 含义 | 谁负责设置 |
|------|------|------|-----------|
| `binding_status` | BindingStatus | 绑定健康状态 | Strategy.bind() |
| `action` | SyncAction | 待执行动作 | Strategy.create() / update() |
| `status` | SyncStatus | 执行结果状态 | DataSource.sync_all() |
| `data_id` | str | 业务主键ID | 数据加载 / DataSource 回填 |
| `error` | str \| None | 错误信息 | 各阶段 |
---
## 完整生命周期
### 第一次运行（无持久化数据）
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ 节点尚不存在 │
└─────────────────────────────────────────────────────────────────────────────┘
│
数据源加载 (Stage 1)
│
▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ 节点诞生 │
│ │
│ binding_status = UNCHECKED ← Collection 创建节点时的初始值 │
│ action = NONE │
│ status = PENDING │
│ data_id = "abc-123" ← 从数据源获取的业务主键 │
│ data = {...} ← 从数据源获取的业务数据 │
│ origin_data = {...} ← 同上，原始快照 │
│ depend_ids = [] ← 空，待 bind 阶段填充 │
│ error = None │
└─────────────────────────────────────────────────────────────────────────────┘
```
---
### 第二次及后续运行（有持久化数据）
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ 从持久化恢复（原始值） │
│ │
│ binding_status = NORMAL (上次值) │
│ action = UPDATE (上次值) │
│ status = SUCCESS (上次值) │
│ data_id = "abc-123" │
│ error = None (上次值) │
└─────────────────────────────────────────────────────────────────────────────┘
│
阶段1：加载时重置 (NodeStateReset)
│
▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ 阶段1重置后 │
│ │
│ binding_status = UNCHECKED ← 重置（每次重新判定） │
│ action = UPDATE ← 保留！（用于阶段2识别 CREATE 失败） │
│ status = SUCCESS ← 保留！（不自动重置） │
│ data_id = "abc-123" ← 不变 │
│ data = None ← 重置（等待数据源覆盖） │
│ origin_data = None ← 重置（等待数据源覆盖） │
│ error = None ← 清空（避免上次错误干扰） │
└─────────────────────────────────────────────────────────────────────────────┘
│
阶段2：CREATE 僵尸清理
(只影响 action=CREATE 且 status=FAILED 或 data_id="" 的节点)
│
▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ 阶段2清理后（正常节点） │
│ │
│ action = NONE ← 全部重置为 NONE，准备进入策略阶段 │
│ 其他字段不变 │
│ │
│ （若为 CREATE 僵尸节点：直接从 Collection 删除 + 解除绑定） │
└─────────────────────────────────────────────────────────────────────────────┘
│
数据源加载覆盖 (Stage 1 后半)
│
▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ 数据源加载后 │
│ │
│ data = {...} ← 数据源最新数据覆盖 │
│ origin_data = {...} ← 数据源最新数据覆盖 │
│ 其他字段不变 │
└─────────────────────────────────────────────────────────────────────────────┘
```
---
## Bind 阶段状态转移 (Stage 2.1)
Bind 分三个子阶段顺序执行，每个子阶段只修改 `binding_status`。
### Phase 1: 核心状态判定
> **代码**：`strategy_ops/bind_ops.py::phase_core_state()` → `SyncDecisionEngine.determine_core_status()`
```
输入：binding_status = UNCHECKED
┌─ 有绑定记录？
│
┌─────┤
│ YES │
│ └─── 本地数据 + 远程数据 都健康？
│ │
│ ┌────┴────┐
│ │ YES │ NO
│ ▼ ▼
│ NORMAL WARNING / ABNORMAL
│
│ NO
└──────────────► MISSING
```
| 输入条件 | binding_status 输出 |
|---------|-------------------|
| 有绑定，双方数据健康 | **NORMAL** |
| 有绑定，自身数据损坏 | **ABNORMAL** |
| 有绑定，对方数据损坏 | **WARNING** |
| 无绑定记录 | **MISSING** |
### Phase 2: 依赖检查
> **代码**：`strategy_ops/bind_ops.py::phase_dependency_check()` → `strategy_ops/bind_ops.py::check_dependencies_for_nodes()`
**仅处理 `binding_status = MISSING` 的节点**，其他状态跳过。
```
输入：binding_status = MISSING
┌─ 有配置 depend_fields？
│
┌─────┤
│ NO └──► 保持 MISSING（无依赖，直接通过）
│
│ YES ──► 逐一检查依赖节点：
│ │
│ ┌────┴────────────────────────┐
│ │ 全部依赖节点: │
│ │ - 存在？ ✅ │
│ │ - binding_status=NORMAL？ ✅ │
│ │ - data_id 非空？ ✅ │
│ └────┬────────────────────────┘
│ │
│ ┌────┴────┐
│ │ 全通过 │ 任一失败
│ ▼ ▼
│ MISSING DEPENDENCY_ERROR
│ + error = "依赖项不满足: ..."
│ + depend_ids 已填充
```
**副作用**：无论检查是否通过，都会填充 `node.depend_ids`。
### Phase 3: 自动绑定
> **代码**：`strategy_ops/bind_ops.py::phase_auto_binding()`
**仅处理 `binding_status = MISSING` 且依赖已通过的节点**。
```
输入：binding_status = MISSING
auto_bind = False?
└──► MISSING → WARNING（"跳过自动绑定，无法确认是否需要创建"）
auto_bind = True:
│
├─ 业务键字段缺失？
│ └──► MISSING → WARNING（"缺少业务键字段: ..."）
│
├─ 业务键中 ID 字段解析失败？
│ └──► MISSING → DEPENDENCY_ERROR（"业务键中的ID字段解析失败"）
│
├─ 去噪后 1:1 匹配？
│ └──► MISSING → NORMAL（执行自动绑定，建立绑定记录）
│
├─ N:0（无远程匹配）？
│ ├──► create_enabled = True → MISSING → NORMAL，并 spawn 目标 CREATE 节点（S06）
│ └──► create_enabled = False → MISSING → WARNING（孤儿且不允许自动创建，需人工处理）
│
└─ N:M / 多对多 / 多对一？
└──► MISSING → WARNING（"存在多个候选节点，无法自动绑定"）
```
### Bind 阶段结束后可能的状态
| binding_status | 后续可执行的操作 |
|---------------|----------------|
| **NORMAL** | UPDATE（如有差异）|
| **MISSING** | CREATE |
| **ABNORMAL** | 无（需人工） |
| **WARNING** | 无（阻止自动操作） |
| **DEPENDENCY_ERROR** | 无（等待依赖修复） |
---
## Create 阶段状态转移 (Stage 2.2)
> **代码**：`create()` → `strategy_ops/create_ops.py::add_create_action()`
> **对齐说明（与状态机配置一致）**：
> - create_prepare 的入口仍是源节点 `binding_status = MISSING`。
> - 但当前配置下，`N:0 + create_enabled=true` 可以在自动绑定阶段直接把源节点转为 `NORMAL`，并 `emit spawn_target_node_state=S06`。
> - 因此“触发创建”的入口有两条：
> 1) auto_bind 分支（E08f）直接 spawn；
> 2) create_prepare 分支（E09b）在 create 检查成功后 spawn。
**仅处理 `binding_status = MISSING` 的节点**。
```
输入：源节点 binding_status = MISSING, action = NONE
┌─ 源节点数据为空？
│ └──► 跳过，记录日志
│
├─ IDResolver.resolve_and_validate() 失败？
│ └──► binding_status → DEPENDENCY_ERROR
│ error = "创建时依赖 ID 未解析: ..."
│
└─ 成功 ──► 在目标 Collection 创建新节点
│
├─ 源节点：
│ binding_status → NORMAL（"从本地创建到远程"）
│ action 不变（仍为 NONE）
│
└─ 新建目标节点：
binding_status = NORMAL
action = CREATE
status = PENDING
data_id = ""（待远程返回）
data = 已替换 ID 的数据副本
│
└─ 同时建立绑定记录：local_id ↔ remote_id
```
---
## Commit Creates — 物理同步 (Stage 2.3)
> **代码**：`DataSource.sync_all()` → Handler.create()
```
输入：action = CREATE, status = PENDING
┌─ Handler 执行 API 调用
│
├─ 同步 API 成功（200/201）
│ └──► status → SUCCESS
│ data_id = "remote-xyz"（远程分配的 ID 回填）
│ data["id"] = "remote-xyz"（主键字段回写）
│
├─ 异步 API 提交成功（202）
│ └──► status → IN_PROGRESS
│ context.task_id = "task-xxx"
│ │
│ └─ 轮询结果：
│ ├─ 成功 → status → SUCCESS, data_id 回填
│ ├─ 失败 → status → FAILED, error = "..."
│ └─ 超时 → status → FAILED, error = "Timeout"
│
└─ API 失败（4xx/5xx）
└──► status → FAILED
error = "远程操作失败: ..."
```
---
## Update 阶段状态转移 (Stage 2.4)
> **代码**：`update()` → `strategy_ops/update_ops.py::add_update_action()`
> **对齐说明**：图里的 `E12a` 从 `S01` 出发并不矛盾。`S01` 约束的是“源节点”有 `data_id`；
> `E12a` 检查的是“目标节点”是否有 `data_id`（guard: `target_has_data_id=false`），两者不是同一个对象。
**过滤条件**：`binding_status = NORMAL` 且 `status != FAILED`
```
输入：源节点 binding_status = NORMAL, action = NONE
┌─ status == FAILED？
│ └──► 跳过（保护上次失败的状态和错误信息）
│
├─ 源节点数据为空？
│ └──► 跳过
│
├─ 通过绑定找不到目标节点？
│ └──► 跳过，记录日志
│
├─ 目标节点 data_id 为空？
│ └──► 目标节点 status → PRECONDITION_FAILED
│ （"目标节点缺少 data_id"）
│
├─ IDResolver.resolve_and_validate() 失败？
│ └──► 目标节点 action → UPDATE
│ 目标节点 status → PRECONDITION_FAILED
│ 目标节点 error = "依赖 ID 未解析: ..."
│
├─ _needs_update() 判定无差异？
│ └──► 跳过（不设置 action）
│
└─ 有差异 ──► 更新目标节点：
action → UPDATE
status → PENDING
data = 已替换 ID 的数据副本
error = None
```
---
## Commit Updates — 物理同步 (Stage 2.5)
> **代码**：`DataSource.sync_all()` → Handler.update()
```
输入：action = UPDATE, status = PENDING
┌─ Handler 构建 API 请求
│
├─ Handler 发现无实际变更字段
│ └──► action → NONE（Handler 降级，不提交 API）
│
├─ 同步 API 成功（200）
│ └──► status → SUCCESS
│
├─ 异步 API 提交成功（202）
│ └──► status → IN_PROGRESS → （轮询）→ SUCCESS / FAILED
│
└─ API 失败
└──► status → FAILED
error = "远程操作失败: ..."
```
---
## 持久化阶段 (Stage 5)
```
节点当前状态原样写入存储。
持久化字段：
✅ node_id, data_id, data, origin_data
✅ binding_status, action, status, error, context
❌ depend_ids（不持久化，下次 bind 时从 data 实时计算）
```
---
## 全景时间线表
下表展示**一个节点在典型场景中的状态变化**：
### 场景 A：首次创建（本地 → 远程）
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| 数据加载 | UNCHECKED | NONE | PENDING | "abc-123" | None |
| bind phase1 | **MISSING** | NONE | PENDING | "abc-123" | None |
| bind phase2 | MISSING | NONE | PENDING | "abc-123" | None |
| bind phase3 | MISSING | NONE | PENDING | "abc-123" | None |
| create | **NORMAL** | NONE | PENDING | "abc-123" | None |
| _(新建远程节点)_ | NORMAL | **CREATE** | PENDING | **""** | None |
| commit create | NORMAL | CREATE | **SUCCESS** | **"remote-456"** | None |
| 持久化 | NORMAL | CREATE | SUCCESS | "remote-456" | None |
### 场景 B：日常更新
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| 持久化恢复 | NORMAL→**UNCHECKED** | CREATE→保留 | SUCCESS→保留 | "abc-123" | 清空 |
| 阶段2 action重置 | UNCHECKED | **NONE** | SUCCESS | "abc-123" | None |
| 数据源覆盖 | UNCHECKED | NONE | SUCCESS | "abc-123" | None |
| bind phase1 | **NORMAL** | NONE | SUCCESS | "abc-123" | None |
| update 检测差异 | NORMAL | NONE | SUCCESS | "abc-123" | None |
| _(目标节点)_ | NORMAL | **UPDATE** | **PENDING** | "remote-456" | None |
| commit update | NORMAL | UPDATE | **SUCCESS** | "remote-456" | None |
### 场景 C：依赖阻断
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| 数据加载 | UNCHECKED | NONE | PENDING | "contract-789" | None |
| bind phase1 | **MISSING** | NONE | PENDING | "contract-789" | None |
| bind phase2 | **DEPENDENCY_ERROR** | NONE | PENDING | "contract-789" | "依赖项不满足: project_id: 状态=dep_err" |
| _(后续阶段不处理)_ | | | | | |
| 持久化 | DEPENDENCY_ERROR | NONE | PENDING | "contract-789" | "依赖项不满足..." |
### 场景 D：CREATE 失败 → 下次自动恢复
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| **第 1 次运行** | | | | | |
| create | NORMAL | CREATE | PENDING | "" | None |
| commit create 失败 | NORMAL | CREATE | **FAILED** | "" | "远程操作失败: 500" |
| 持久化 | NORMAL | CREATE | FAILED | "" | "远程操作失败: 500" |
| **第 2 次运行** | | | | | |
| 阶段1恢复 | **UNCHECKED** | CREATE | FAILED | "" | **None** |
| 阶段2僵尸清理 | _(节点被删除，绑定被解除)_ | | | | |
| 数据源重新加载 | UNCHECKED | NONE | PENDING | "" → 新 node_id | None |
| bind → create | 重新走首次创建流程 | | | | |
### 场景 E：UPDATE 失败 → 保留供人工处理
| 阶段 | binding_status | action | status | data_id | error |
|------|---------------|--------|--------|---------|-------|
| **第 1 次运行** | | | | | |
| update | NORMAL | UPDATE | PENDING | "remote-456" | None |
| commit update 失败 | NORMAL | UPDATE | **FAILED** | "remote-456" | "403 Forbidden" |
| 持久化 | NORMAL | UPDATE | FAILED | "remote-456" | "403 Forbidden" |
| **第 2 次运行** | | | | | |
| 阶段1恢复 | UNCHECKED | UPDATE | FAILED | "remote-456" | None |
| 阶段2 action重置 | UNCHECKED | **NONE** | **FAILED** | "remote-456" | None |
| bind | NORMAL | NONE | FAILED | "remote-456" | None |
| update 跳过 | _(status=FAILED，自动跳过)_ | | | | |
| 持久化 | NORMAL | NONE | FAILED | "remote-456" | None |
| _(需人工重置 status 后才能重新更新)_ | | | | | |
---
## 状态转换合法性约束
### binding_status 允许的转换
```
UNCHECKED → NORMAL (核心判定: 有绑定且健康)
UNCHECKED → MISSING (核心判定: 无绑定记录)
UNCHECKED → ABNORMAL (核心判定: 自身数据损坏)
UNCHECKED → WARNING (核心判定: 对方数据损坏)
MISSING → DEPENDENCY_ERROR (依赖检查: 父节点不满足)
MISSING → WARNING (自动绑定: 业务键缺失 / 多候选 / auto_bind=False)
MISSING → DEPENDENCY_ERROR (自动绑定: ID 字段解析失败)
MISSING → NORMAL (自动绑定: 1:1 成功)
MISSING → NORMAL (create: 源节点创建成功后)
MISSING → DEPENDENCY_ERROR (create: ID 解析失败)
```
> **注意**：当前 `SyncNode.set_binding_status()` 不做转换合法性校验【未实现】。
### action 允许的转换
```
NONE → CREATE (create: 新建目标节点)
NONE → UPDATE (update: 检测到差异)
UPDATE → NONE (Handler 降级: 实际无变更字段)
```
### status 允许的转换
```
PENDING → IN_PROGRESS (DataSource: 异步提交成功)
PENDING → SUCCESS (DataSource: 同步执行成功)
PENDING → FAILED (DataSource: 执行失败)
PENDING → SKIPPED (DataSource: 被跳过)
（常见于 CREATE/UPDATE：Handler 返回 SKIPPED（无可执行操作/业务条件不满足），对应状态机里的 E19→S13 或 E20→S14）
PENDING → PRECONDITION_FAILED (Strategy: 前置条件不满足)
IN_PROGRESS → SUCCESS (DataSource: 异步轮询成功)
IN_PROGRESS → FAILED (DataSource: 异步轮询失败/超时)
```
> **注意**：当前 `SyncNode.set_status()` 不做转换合法性校验【未实现】。
---
## 参考文档
- [状态定义规范](./状态定义规范.md) — 状态枚举和判定规则
- [持久化与人工介入规范](./持久化与人工介入规范.md) — 持久化重置策略
- [编排流程规范](./编排流程规范.md) — Pipeline 阶段定义
- [架构分层设计](./架构分层设计.md) — 各层职责
- [node_id_data_id_lifecycle](./node_id_data_id_lifecycle.md) — ID 生命周期
docs/archive/goals.md
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# 同步系统重构目标
## 范围
- 在 `sync_state_machine/` 下实现新状态机运行时，不改 `sync_system_new/` 现有实现。
- 第一阶段聚焦 JSONL 路径，API 路径后续接入。
## 成功标准
- 状态机配置可独立校验与出图。
- 运行时可根据事件与上下文输出迁移决策。
- 自动化测试可覆盖所有事件（E00~E20）并统计状态覆盖。
- domain 业务层不直接改状态，状态变更由状态机输出驱动。
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# 迁移映射
## 旧 -> 新
- `sync_system_new/state_machine/*` -> `sync_state_machine/config|tools/*`
- `strategy.py` 决策逻辑 -> `sync_state_machine/engine/* + sync_state_machine/sync_system/strategy.py`
- `datasource.py` 状态写回 -> `sync_state_machine/datasource/datasource.py`
- bind/create/update 事件驱动 -> `sync_state_machine/sync_system/strategy.py` 直接 dispatch（无桥接层）
## 不变项
- `sync_system_new/domain/*` 业务处理逻辑保持不动。
- `schemas/`、`filtered_datasource/` 不修改。
## 目录差异说明
- `sync_state_machine/adapters/` 已移除，避免“新目录实现 + 适配桥接”双轨并存。
- 状态机配置、执行、测试均在 `sync_state_machine` 内闭环。
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# 自动测试说明
## 1. 目标
这套测试只做一件事：
- 用固定配置初始化测试环境；
- 一键运行测试；
- 验证同步系统能不能完成一轮正常同步；
- 验证常见的更新接口能不能工作；
- 能把问题大致分成三类：数据问题、推送系统问题、后端接口问题。
不追求把所有情况都测完，也不追求覆盖所有脏数据。测试深度控制在：
- 能跑通一次正常流程；
- 能验证一批关键 update；
- 能处理一些基本异常；
- 每轮都能留下清楚的报告，供下一轮继续改。
## 2. 测试系统的组成
测试系统由 4 部分组成：
1. **测试配置**
2. **初始化脚本**
3. **按 domain 拆分的用例**
4. **统一运行脚本**
只要把这 4 部分准备好，后面就应该做到：**运行一个脚本，就自动完成初始化、执行、分析、出报告。**
### 当前已落地的文件
目前已经先实现了一版最小骨架：
- 测试总配置：[tests/fixtures/auto_sync/auto_test_config.yaml](tests/fixtures/auto_sync/auto_test_config.yaml)
- 流水线测试配置：[run_profiles/jsonl_to_api.test.yaml](run_profiles/jsonl_to_api.test.yaml)
- 初始化脚本：[scripts/auto_test_init.py](scripts/auto_test_init.py)
- 统一运行脚本：[scripts/run_auto_test.py](scripts/run_auto_test.py)
- 公共工具：[scripts/auto_test_lib.py](scripts/auto_test_lib.py)
- 第一个 domain 用例：[tests/fixtures/auto_sync/domains/contract.yaml](tests/fixtures/auto_sync/domains/contract.yaml)
## 3. 配置管理
测试环境必须基于配置初始化，不能靠手工改路径。
配置里至少要能定义这些内容：
- 后端代码目录；
- 后端启动命令；
- 后端恢复数据库命令；
- 测试使用的数据库名；
- CouchDB 连接信息；
- 本地同步状态数据库路径；
- 基础种子数据目录；
- 同步测试数据目录；
- 临时测试数据目录；
- 同步系统运行配置文件路径。
建议单独准备一个测试配置，例如：
- `run_profiles/jsonl_to_api.test.yaml`
- `docs/auto_test_spec` 中再约定测试总配置文件
### 数据目录分工
测试里至少有 3 类数据目录：
1. **基础种子数据**
- 用来恢复后端里那些不能通过同步创建的数据。
- 例如：`company`、`project`、`design_doc`。
- 这类数据先进入后端数据库，给后续同步提供依赖。
2. **同步测试数据**
- 用来测试可创建、可更新的业务数据。
- 例如合同、结算、施工任务等。
3. **临时运行目录**
- 每次测试前，把测试数据复制到这里。
- 后续每一轮如果要改数据，也只改这里，不改原始测试集。
## 4. 初始化方式
初始化必须自动完成，不能再靠手工执行几条命令。
目标流程如下：
1. 读取测试配置；
2. 如有旧测试数据库，先自动删除；
3. 自动删除本地同步状态数据库；
4. 自动执行后端的数据库恢复命令，导入基础种子数据；
5. 自动启动后端；
6. 自动等待后端 ready；
7. 自动准备临时测试目录；
8. 开始跑测试。
### 运行后的要求
- **测试跑完以后，数据库保留**，方便查看结果；
- **下次再运行时，再自动清空旧库并重建**；
- 不要求每次结束自动销毁环境。
## 5. 运行方式
不强制使用 `pytest`。
当前更适合的方式是：
- 用一个主脚本统一运行全部流程；
- domain 用例由脚本按顺序调度；
- 每个 domain 可以包含多轮 pipeline；
- 每轮的输入数据和检查点都由脚本控制。
也就是：
- `测试配置 + 初始化脚本 + 分 domain 的用例 + 一个完整运行脚本`
## 6. 测试轮次
一次完整测试，允许分成多轮 pipeline。
典型做法：
### 第 1 轮：初始化后首次同步
目的：
- 验证基础依赖准备正确；
- 验证 create 流程能跑通；
- 验证绑定关系是否正常。
### 第 2 轮：在临时目录修改部分数据后再次同步
目的：
- 验证 update 接口；
- 验证哪些数据应该更新；
- 验证哪些数据应该保持不动。
### 第 3 轮：补充少量基本异常场景
目的：
- 验证系统遇到常见错误时能不能给出清楚结果；
- 验证错误是否能定位到数据、推送系统或后端。
不要求无限轮次，也不要求复杂压力测试。
## 7. Domain 用例怎么设计
每个 domain 单独设计用例，例如：
- `company`
- `project`
- `contract`
- `supplier`
- `construction_task`
- `contract_settlement`
但不是所有 domain 都从创建开始测。
要根据业务真实情况决定：
- 哪些 domain 只能作为基础种子存在；
- 哪些 domain 可以通过同步创建；
- 哪些 domain 要重点测 update。
### Domain 用例必须写清楚的内容
每个 domain 的用例说明都要先写文字，再写代码。文字说明必须经过你审定。
每组用例至少写清楚：
1. 这个 domain 的前置依赖是什么；
2. 这个 domain 本轮准备哪些测试数据；
3. 第几轮会创建哪些记录；
4. 第几轮会修改哪些字段；
5. 预期通过什么方式判断结果；
6. 这个用例主要想识别哪类问题。
## 8. Domain 用例的测试原则
### 原则 1：优先覆盖大部分接口
目标不是追求完美覆盖，而是尽量覆盖大部分 create / update 接口，尤其是 update。
### 原则 2：只测明确的业务关系
用例里的依赖关系必须有文字说明，不能边跑边猜。
### 原则 3：可以通过改数据来构造用例
允许通过修改临时目录里的数据来构造 update 场景。
### 原则 4：判断结果不能只看日志
要结合下面几类证据一起判断：
- 日志；
- collection 中的数据；
- 持久化数据库中的结果；
- 绑定记录；
- 同步状态数据库。
### 原则 5：用例要能分出问题归属
每个用例都应该尽量帮助判断问题属于：
- 测试数据问题；
- 推送系统问题；
- 后端接口逻辑问题。
## 9. 建议的用例层次
每个 domain 的用例，优先按下面 4 类来补：
1. **正常创建**
2. **正常更新**
3. **关键绑定关系检查**
4. **基本异常检查**
这里的“基本异常”只做常见的、对当前系统最有价值的，例如：
- 缺少依赖；
- 关键字段不合法；
- 远端返回明确错误；
- 本地状态和远端状态不一致。
## 10. 运行脚本应该负责什么
统一运行脚本应负责：
1. 读取测试配置；
2. 清空旧测试环境；
3. 初始化后端数据库；
4. 启动后端并等待可用；
5. 准备临时测试数据；
6. 按 domain 顺序执行各轮用例；
7. 每轮运行 pipeline；
8. 收集结果；
9. 输出报告。
## 11. 测试报告要求
每轮都要有清晰报告，给下一轮继续优化使用。
报告至少包含：
- 测试时间；
- 使用的配置；
- 运行了哪些 domain；
- 每个 domain 跑了几轮；
- 每轮改了哪些数据；
- 每轮成功 / 失败统计；
- 失败样本；
- 问题分类：数据 / 推送系统 / 后端；
- 下一轮建议。
## 12. 当前结论
当前最合适的方案不是全量自动化，也不是一次性测完所有东西。
而是：
- 先做一套固定配置的测试环境；
- 用一个脚本跑完整个流程；
- 从少量 but 关键的 domain 开始；
- 每个 domain 先把 create 和主要 update 跑通；
- 每轮都留下明确报告；
- 再逐步扩展。
这样更容易维护，也更适合后续让 Agent 按计划继续写代码。
## 13. 当前执行计划（2026-03-07）
当前轮次先处理两类目标：
1. `project_detail_data`
- 继续确认可按统一 `project_detail_data` 语义验证的 key 与相关 update 接口在测试报告中可见、可追踪；
- 重点检查它与后续 project 级 domain 连跑时是否污染状态。
- 当前水电项目下，`production` 先不混入这组统一回归：后端已确认该接口会直接更新 `project` 字段，但不保证创建/更新可轮询的 `project_detail_data.production` 记录；后续待业务确认后再单列测试方案。
2. 剩余 domain
- 当前优先处理：`contract_settlement_detail`、`personnel`、`personnel_detail`
- 已完成并保持回归：`preparation`、`production`、`contract`、`contract_settlement`、`construction_task`、`construction_task_detail`、`material`、`material_detail`
- 之后再继续：`units`、`contract_change`、`lar`、`lar_change`
本轮执行顺序：
1. 先补齐文字测试计划；
2. 再修改测试脚本与 `tests/` 下测试数据；
3. 逐个 domain 跑通；
4. 最后回到整套自动测试顺序验证全量可跑通。
### 本轮强约束
- **禁止修改 `schemas/` 下任何文件。**
- 不允许为了让测试通过而绕过 schema 校验。
- 如果问题根因是后端接口/后端返回/后端数据模型不一致，应直接在报告里暴露并记录，不擅自改 schema。
- 只有在确认是后端错误并得到明确指示后，才讨论是否调整类型定义。
### 本轮排查重点
1. `project_detail_data` 单跑已基本可用，但要继续验证与 `preparation`、`production` 连跑时是否造成绑定或状态污染；
2. `preparation`、`production` 当前更像是“整套顺序执行时失败、单独执行可通过”的问题，优先检查运行顺序、临时数据、持久化状态和绑定残留；
3. 其余 domain 按“先单 domain 跑通，再放回全量顺序”推进；
- 当前先按 `contract_settlement_detail -> personnel -> personnel_detail` 顺序落地；
4. 每修完一个 domain，都要保证报告中能看出本轮覆盖内容、绑定结果、字段变化和失败归因。
5. 对 `project_detail_data.production`，禁止再用“接口没报错就直接记成功”的短路逻辑掩盖真实语义；当前阶段直接绕过该 key 的统一回归，保留差异说明。
## 14. 大规模测试方法：按轮迭代，而不是一次堆上下文
大规模测试的目标不是“把所有失败细节一次讲完”，而是：
- 每一轮只有一个清晰基线；
- 每一轮只记录少量必须保留的信息；
- 每一轮都能看到总计变化；
- 每一轮都能区分“新问题、已修复问题、遗留问题”。
当前推荐固定采用 **单 domain 验证 + 全量聚合回归** 的两层节奏。
### 14.1 固定节奏
每一轮都按下面顺序执行：
1. **选定本轮目标**
- 只选 1 个主问题，或者 1 组同类问题。
- 例如：
- 一个 domain 的 update 接口失败；
- 一组共享 helper 导致的脚本设计问题；
- 一类后端读写不一致问题。
2. **先单 domain 复现**
- 用 [scripts/run_auto_test.py](scripts/run_auto_test.py) 只跑目标 domain。
- 目的不是求“全绿”，而是先确认问题是否稳定复现。
3. **定位并修复一类根因**
- 如果是测试脚本问题，就只修脚本；
- 如果是后端问题，就在报告里明确标注为后端；
- 如果是数据问题，就保留失败，不用 fallback 掩盖。
4. **回跑目标 domain**
- 只看本 domain 是否改善；
- 记录这轮减少了多少失败 case。
5. **再跑聚合回归**
- 用 [scripts/run_auto_test_all_domains.py](scripts/run_auto_test_all_domains.py) 执行全量聚合；
- 当前聚合模式是“**每个 domain 独立初始化并单独执行**”，用于避免跨 domain 状态污染。
6. **输出轮次结论**
- 只保留：
- 总 case 数；
- 通过 / 失败数；
- 新增失败；
- 已修复失败；
- 遗留失败；
- 每个遗留失败的归因分类。
### 14.2 每轮只保留 4 份信息
为了避免上下文失控，每轮总结时只保留下面 4 份信息：
1. **总计快照**
- `total_domains`
- `passed_domains`
- `failed_domains`
- `total_cases`
- `passed_cases`
- `failed_cases`
2. **变化清单**
- 本轮修复了哪些 case；
- 本轮新增了哪些 case；
- 哪些 case 没变化。
3. **失败分类表**
- `script_design`：脚本设计 / 运行配置 / 断言策略问题；
- `push_system`：状态机、绑定、依赖、持久化、推送链路问题；
- `backend`：后端接口、后端读写模型、后端返回值问题；
- `data`：测试数据不满足前置条件或数据本身不合法；
- `flaky`：暂时只在聚合中出现、单跑不能稳定复现的问题。
4. **下一轮唯一目标**
- 下一轮最多列 1~3 个目标；
- 不把所有猜测都带到下一轮。
### 14.3 轮次汇总格式
每轮报告建议固定成下面的结构：
1. **Round N 总计**
2. **与 Round N-1 对比**
3. **本轮修复**
4. **本轮新增**
5. **遗留问题分类**
6. **下一轮目标**
建议直接从聚合报告的 `summary.json` 中抽取总计，避免手工整理时带入过多细节。
### 14.4 建议的对比口径
比较两轮结果时，统一只按 `domain::round_name` 比较，不按日志文本比较。
也就是把每个 case 视为一个稳定键，例如：
- `project::round_2_base_info_update`
- `project::round_3_investment_update`
- `material_detail::round_2_update`
这样做的好处是：
- 总数稳定；
- 对比简单；
- 很容易看出某个 case 是“由失败转通过”，还是“仍然失败”。
### 14.5 建议的推进策略
对于 10+ domain、数十个 case 的回归，建议始终按下面方式推进：
1. **先消灭稳定复现的单点失败**
- 先修能稳定复现的问题，不先追偶发问题。
2. **再处理共享根因**
- 如果多个 domain 共用同一个 helper、同一个运行配置、同一种绑定策略，优先处理这一层。
3. **最后单列 flaky**
- 聚合里偶发失败、单跑通过的问题，不直接混入主结论；
- 先标成 `flaky`，待重复出现后再升级处理。
### 14.6 当前这套系统中的实际判定方法
当前推荐把问题按下面顺序判定：
1. **先看单 domain 是否稳定失败**
- 如果单跑失败，优先查该 domain 自身脚本、数据、后端接口。
2. **再看聚合回归是否额外引入失败**
- 如果单跑通过、聚合失败，优先怀疑：
- 运行顺序；
- 环境残留；
- 报告聚合方式；
- 偶发后端错误。
3. **最后看后端是否写了但读不出来**
- 如果 update 接口已命中，但回读字段缺失或不一致，要明确归类为 `backend`，而不是继续修改测试脚本绕过。
### 14.7 本文档要求的轮次目标
每一轮结束后，必须能一句话回答下面 3 个问题：
1. **总计有没有变好？**
2. **变好是因为修了脚本、推送系统，还是确认了后端问题？**
3. **下一轮只追哪一个主问题？**
如果一轮总结不能回答这 3 个问题，就说明这轮上下文保留得太多、结论还不够收敛。
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---
large_scale_test:
config_path: tests/fixtures/auto_sync/auto_test_config.yaml
output_dir: test_results/auto_test/large_scale
fail_on_failed_cases: false
default_runner: aggregate
default_init_mode: fresh
classification:
project::round_3_investment_update: backend
material_detail::round_2_update: flaky
rounds:
- id: round_01_full_baseline
title: 全量隔离基线
enabled: true
runner: aggregate
init_mode: fresh
objective: 建立当前 19 个 domain 的隔离回归基线，并确认遗留失败的分类。
focus:
- 全量聚合仍使用每个 domain 独立初始化，避免跨 domain 状态污染。
- 先确认 project 与 material_detail 的当前状态，不在本轮混入额外修复动作。
next_goal: 在保持全量基线的前提下，单独复核 project 与 material_detail，区分后端遗留问题和聚合偶发问题。
- id: round_02_project_recheck
title: project 后端复核
enabled: true
runner: domains
init_mode: fresh
domains:
- project
objective: 单独复核 project，确认 round_2 已修复，round_3 仅剩后端读回字段缺失。
focus:
- 只跑 project，避免无关上下文。
- 明确区分脚本问题与后端问题。
classification:
project::round_3_investment_update: backend
next_goal: 保留脚本侧修复结论，把 project round_3 作为后端待修项持续跟踪。
- id: round_03_material_detail_recheck
title: material_detail 波动复核
enabled: true
runner: domains
init_mode: fresh
domains:
- material_detail
objective: 单独复核 material_detail，确认聚合中的 round_2 失败是否只是偶发。
focus:
- 只跑 material_detail。
- 如果单跑通过，就把聚合中的失败归为 flaky，不扩大处理范围。
classification:
material_detail::round_2_update: flaky
next_goal: 若后续聚合再次出现同类失败，再升级为可复现问题处理。
---
# 大规模测试控制文档
这个文档同时承担两件事：
1. **控制大规模测试怎么跑**
2. **记录每轮测试的目标、结果和改进过程**
## 使用方式
- 控制入口：调整本文档 frontmatter 中的 `rounds`
- 执行脚本：[scripts/run_large_scale_auto_test.py](scripts/run_large_scale_auto_test.py)
- 默认命令：`python scripts/run_large_scale_auto_test.py`
## 设计约束
- 默认使用 `fresh` 初始化，优先保证每轮从干净环境开始。
- `aggregate` runner 适合大规模基线回归；它内部会对每个 domain 独立初始化。
- `domains` runner 适合小范围复核；它会按 [scripts/run_auto_test.py](scripts/run_auto_test.py) 的语义执行。
- 失败不应靠 fallback 掩盖；应在轮次记录里明确分类。
## Runner 约定
### `aggregate`
- 调用 [scripts/run_auto_test_all_domains.py](scripts/run_auto_test_all_domains.py)
- 适合建立全量基线
- 最能避免跨 domain 污染
### `domains`
- 调用 [scripts/run_auto_test.py](scripts/run_auto_test.py)
- 适合复核单个或少量 domain
- 用于缩小上下文，验证某个问题是否稳定复现
## Init 策略约定
### `fresh`
- 默认策略
- 每轮都从新的初始化开始
- 优先用于正式大规模测试
### `reuse`
- 透传 `--skip-init`
- 只适合排查“连续执行是否污染状态”这一类问题
- 不建议作为大规模基线默认值
### `clear-only`
- 只清空环境，不执行业务轮次
- 用于单独校验清理逻辑
## 执行记录
下面这部分由脚本自动更新，不手工编辑。
<!-- LARGE_SCALE_RESULTS:START -->
## 最近一次执行 20260308-012707
- 控制文档: docs/auto_test_spec/large_scale_test_control.md
- 执行轮次数: 1
- 说明: 默认优先使用 fresh 初始化；若使用 aggregate runner，则每个 domain 仍会独立初始化。
### 轮次总览
| Round | 标题 | Runner | Init | Cases | Failed | 对比轮次 | 报告 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| round_01_full_baseline | 全量隔离基线 | aggregate | fresh | 42 | 1 | - | test_results/auto_test/reports/20260308-012707/report.md |
### round_01_full_baseline - 全量隔离基线
- 目标: 建立当前 19 个 domain 的隔离回归基线，并确认遗留失败的分类。
- 运行方式: aggregate
- 初始化策略: fresh
- 执行命令: /Users/zyl/my_projects/ecm_sync_system/.venv/bin/python /Users/zyl/my_projects/ecm_sync_system/scripts/run_auto_test_all_domains.py --config tests/fixtures/auto_sync/auto_test_config.yaml
- 单轮结果: 41 passed / 1 failed / 42 total cases
- Domain 结果: 18 passed / 1 failed / 19 total domains
- 原始报告: test_results/auto_test/reports/20260308-012707/report.md
- 原始汇总: test_results/auto_test/reports/20260308-012707/summary.json
- 本轮关注点:
- 全量聚合仍使用每个 domain 独立初始化，避免跨 domain 状态污染。
- 先确认 project 与 material_detail 的当前状态，不在本轮混入额外修复动作。
- 对比轮次: 无可比较轮次
- 可比较 case 数: 0
- 对比结果: 本轮没有可比改进项，或与此前轮次无重叠 case。
- 失败归因:
- project::round_3_investment_update | backend | issues=1 | remote.project 字段校验失败: local=de4dc6d2-ea32-5c04-8430-83145d5d0765 target=f3e02e84-e81c-4aa6-88d4-f5aa108c8227; implementation_estimate: actual=None expected=1225000.0; static_total_investment: actual=None expected=1224300.0; completed_investment: actual=None expected=194500.0
- 下一轮目标: 在保持全量基线的前提下，单独复核 project 与 material_detail，区分后端遗留问题和聚合偶发问题。
- 脚本返回码: 1
<!-- LARGE_SCALE_RESULTS:END -->
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# 差异字段汇总清单
本文档记录了在同步推流测试中，本地（Local payload）与远端（Remote API 响应/DB落库）产生明确差异的字段。这些差异通常是因为远端后端代码主动忽略了前端传值，并采用关联覆盖、自动计算或默认补全所致。
> **备注**:
> 1. 根据梳理，完全被远端忽略的、只作为返回展示的字段已经从本地/远端的 `Create`、`Update` Schema 中彻底**剔除 (已删)**，不再作为入参推送。
> 2. 标有 **[🔥远端接收并参与逻辑计算，但最终与本地不一致]** 的字段没有被删，作为强逻辑关联字段保留。
## 1. contract_settlement (合同结算)
### Create 请求 (`ContractSettlementCreate`)
- **`contract_type` (合同类型)**: **(从 Schema 彻底剔除)** 远端完全不接收本地传值，根据关联逻辑自动赋予了实际类别（如 `'PC'`, `'GJ'`, `'E'`）。
- **`contract_price` (合同总额)**: Create不需要传（本地本身无该入参）。远端在创建时直接从近端 Contract 数据库查取并覆盖。
### Update / Plan Update 请求 (`ContractSettlementUpdate` 等)
- **`plan_complete_date`**: **[🔥远端接收并参与逻辑计算，但最终与本地不一致]** 远端接收该字段，主要作用于 `clean_plan_nodes` 数据清洗以保证非法边界节点被剔除，同时可能经过远端状态与明细上托更新，使得终值可能扭转。
- **`complete_price` / `status` / `delay_days` / `statistic_date` / `actual_start_date`**: 远端自动计算累加的衍生只读字段，均不在 Create / Update Schema 范畴中，故不维护入参。
## 2. construction_task & construction_task_detail (施工任务及明细)
### Create 请求 (`ConstructionTaskCreate`)
- **`contract_quantity` (合同工程量)**: **(已从 Create Schema 彻底剔除)** 远端由于 `create_construction` 函数底层逻辑完全不读此字段，现已被安全双端剪除。不在初始创建时推送。
- **`plan_start_date` / `plan_complete_date`**: **[🔥远端接收并参与逻辑计算，但最终与本地不一致]** 远端校验WBS结构树约束时会接收这俩参数进行合规计算，如果超出父子节点范围，存在自动修正或打回改写的逻辑。
### Update / Plan Update 请求 (`ConstructionTaskUpdate` 及明细)
- **`contract_quantity` (合同工程量)**: **[🔥远端接收并参与逻辑计算，但最终与本地不一致]** 在针对 `ConstructionPlanUpdate` 更新计划节点时，远程接受本字段控制计算与校验完成率基准，但仍可能会受 WBS 重制。
- **`complete_quantity` / `complete_rate` / `rate` / `status` / `actual_complete_date`**: 纯内部状态更新触发、只读汇总，本地本来就未放至 Update Schema 内进行提交。
## 3. supplier (供应商)
### 字段表现
- **`city_name`, `province_name`, `country_name`**: Response专用字段。本地不推，仅仅是远端依托外部库映射在接口返回中补全的只读显示。
## 4. company (组织/公司)
### 字段表现
- **`parent_name` (父级机构名称)**: Response专用显示字段。远端依赖 `parent_id` 自动向上追溯返回字段。
## 5. production (产值等)
### Create / Update 请求
- **`is_exist`**: **[🔥远端接收并参与逻辑计算，但最终与本地不一致]** 本地推流中有 `is_exist = True`，且远端后端提取了 `production_data.is_exist` 进行存入判断（确实参与了代码落库前置过滤逻辑），但最后远程抓回验证时为 `None`，这归因于远端的废弃映射和覆盖逻辑。该字段须保留不能删。
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# Collection 查询现状与升级方案
## 1. 当前实现梳理
核心代码：
- `sync_state_machine/common/collection.py`
- `sync_state_machine/common/binding.py`
- `sync_state_machine/datasource/datasource.py`
- `sync_state_machine/sync_system/strategy_ops/*.py`
### 1.1 DataCollection 当前内存结构
`DataCollection` 目前核心是两张索引：
- `_nodes: Dict[node_id, SyncNode]`
- `_data_id_to_node_id: Dict[data_id, node_id]`
特点：
- `node_id` 查找是 O(1)
- `data_id` 反查 node 是 O(1)
- 其他查询（按状态/动作/绑定状态/业务字段）目前主要依赖遍历
### 1.2 查询路径
#### A. 通用筛选 `filter(...)`
- 先取 `_nodes.values()`
- 可按 `node_type` 过滤
- 可按 `node_filter`（节点顶层属性）过滤
- 可按 `filter`（`node.data` 内字段）过滤
复杂度：最差接近 O(N)
#### B. 状态筛选 `filter_by_state_ids(...)`
- 先调用 `filter(node_type=...)`
- 对每个候选节点，根据状态机配置逐条匹配 `binding_status/action/status/data_id_exist`
- `state_ids` 多个时，执行多次匹配
复杂度：约 O(N * |state_ids|)
### 1.3 调用热点
在 pipeline 中，以下路径高频调用状态筛选：
- bind 阶段（S00）
- create 阶段（S06）
- update 阶段（S07）
- delete 检查（S09）
对应代码：
- `sync_state_machine/datasource/datasource.py` 的 `_sync_nodes`
- `sync_state_machine/sync_system/strategy_ops/bind_ops.py`
### 1.4 BindingManager 当前查询
`BindingManager` 当前结构：
- `_bindings: Dict[node_type, Dict[local_id, remote_id]]`
其中：
- `get_remote_id`：O(1)
- `get_local_id`：当前是遍历同类型全部绑定，O(K)
当绑定数量很大时，`get_local_id` 会成为热点。
---
## 2. 本次已修正项
### 2.1 `filter(data_filter)` 查询中的不必要深拷贝
原实现在 `filter` 的 data 过滤里每个节点调用 `node.get_data()`，会触发深拷贝，数据量大时会产生明显 CPU/内存开销。
已改为只读访问 `node.data`：
- 不改变返回语义
- 降低过滤时的对象复制成本
变更文件：
- `sync_state_machine/common/collection.py`
### 2.2 类型标注修正
`node_filter` 的注解从 `callable` 修正为 `Callable[[SyncNode], bool]`，增强类型可读性和 IDE 体验。
---
## 3. 升级方案（针对三类目标）
目标：
1) 查询性能
2) 架构明确
3) 内存数据不过多
### 阶段 0（当前）
- 保持现有语义，先完成可观测性：记录各查询调用次数和耗时（尤其 `filter_by_state_ids` 与 `get_local_id`）
### 阶段 1（低风险，优先）
#### 1. 查询性能
- 新增二级内存索引（不替换现有结构，仅并行维护）：
- `by_node_type: Dict[str, Set[node_id]]`
- `by_status: Dict[SyncStatus, Set[node_id]]`
- `by_action: Dict[SyncAction, Set[node_id]]`
- `by_binding_status: Dict[BindingStatus, Set[node_id]]`
- `by_type_status_action: Dict[(node_type,status,action), Set[node_id]]`
- `filter_by_state_ids` 先用组合索引缩小候选，再做状态机细匹配
#### 2. 架构明确
- 增加查询层接口（例如 `CollectionQueryEngine`），将“筛选逻辑”与“存储结构”分离
- 业务侧只依赖查询接口，不直接依赖 `_nodes`
#### 3. 内存控制
- 新增按需字段索引，仅为高频字段建立（如 `project_id/company_id/contract_id`）
- 索引集采用 `set[node_id]`，避免复制节点对象
### 阶段 2（中风险）
#### 1. 查询性能
- `BindingManager` 增加反向索引：
- `remote_to_local: Dict[node_type, Dict[remote_id, local_id]]`
- 将 `get_local_id` 从 O(K) 降至 O(1)
#### 2. 架构明确
- 统一节点写路径（add/update/delete）触发索引增量更新
- 明确“不允许绕过 Collection 写入节点”
#### 3. 内存控制
- 增加可配置的“弱索引模式”：在低内存场景关闭部分次级索引
### 阶段 3（可选，较高风险）
#### 1. 查询性能
- 引入 SQLite 热查询表（内存 SQLite 或磁盘 SQLite）承接复杂组合查询
- 保留内存索引作为热点路径，DB 作为补充查询后端
#### 2. 架构明确
- 形成分层：
- 热路径：内存索引
- 冷路径：SQLite 查询
- 归档：持久化 DB
#### 3. 内存控制
- 支持“分批加载 + 分批同步 + checkpoint”
- 将非活跃节点转冷存储，只在命中时回载
---
## 4. 启动/重置语义说明（避免误判）
当前默认不是每次全清空：
- 启动会先加载持久化，再执行 E01 归并清理
- 仅在 `persist.wipe_on_start=true` 时会在启动前删除持久化 DB
因此若做“分批/多轮 pipeline”，建议：
- 保持 `wipe_on_start=false`
- 通过显式 checkpoint 与增量范围控制保证状态一致性
---
## 5. 结论
短期最优路径：
- 先完成阶段 1 + 阶段 2（低/中风险），通常能解决大部分查询性能问题
- 再根据压测结果决定是否进入阶段 3（SQL 化冷查询）
这条路线兼顾：
- 速度（热路径仍在内存）
- 清晰性（查询层解耦）
- 内存边界（按需索引 + 分批加载）
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# 数据源指南（DataSource Guide）
本文档记录当前项目中不同数据源的职责、能力与配置方式，并按数据源分类说明。
## 1. 总览
当前实现包含两类数据源：
- JSONL 数据源：面向本地文件读写
- API 数据源：面向远端 HTTP 接口推送与轮询
两者都基于统一编排层 `BaseDataSource`，具备一致的流程骨架：
1. 注册 Handler（按节点类型）
2. load 阶段加载节点
3. sync 阶段按动作执行 create/update/delete
4. 统一处理 TaskResult 与状态机写回
5. 统一异步任务轮询（IN_PROGRESS -> SUCCESS/FAILED）
这意味着：
- 业务策略可复用，不需关心底层介质差异
- 数据源差异主要落在 Handler 与传输/存储细节
---
## 2. JSONL 数据源
### 2.1 主要功能
JSONL 数据源对应实现：
- `sync_state_machine/datasource/jsonl/datasource.py`
- `sync_state_machine/datasource/jsonl/handler.py`
核心能力：
- 从目录中按 `{node_type}_N.jsonl` 规则发现并加载数据
- 批量 create/update/delete 时，先改内存缓存，再统一刷盘
- 支持 `read_only`，在只读模式下禁止写回
- 支持按项目过滤（`target_project_ids`）在 load 阶段预过滤
### 2.2 行为特点
- load：逐行解析 JSONL，单行坏数据仅警告并继续
- create/update/delete：返回统一 `TaskResult`，由 DataSource 层统一更新状态
- 写回：默认写到 `{node_type}_1.jsonl`
### 2.3 关键配置
`JsonlDataSourceConfig` 字段：
- `type: jsonl`
- `jsonl_dir`: 数据目录
- `read_only`: 是否只读
- `target_project_ids`: 项目过滤列表
- `handler_configs`: 按节点类型的 handler 参数
---
## 3. API 数据源
### 3.1 主要功能
API 数据源对应实现：
- `sync_state_machine/datasource/api/datasource.py`
- `sync_state_machine/datasource/api/client.py`
- `sync_state_machine/datasource/api/handler.py`
核心能力：
- 统一 HTTP 请求入口（签名、uid 注入、错误日志、trace）
- 统一 push 任务轮询（`/push/result`）
- 统一请求链路追踪（submit/poll/load）
- 统一限流（全局窗口限流）
### 3.2 API 全局限流（重点）
当前已支持全局异步限流，入口在 `ApiClient.request()` 前。
配置字段：
- `api_rate_limit_max_requests`：窗口内最大请求数
- `api_rate_limit_window_seconds`：窗口秒数
默认值：
- `api_rate_limit_max_requests: 10`
- `api_rate_limit_window_seconds: 10.0`
含义：
- 任意 10 秒窗口内最多发 10 个请求
- 超出后，后续请求在客户端侧等待，不直接打到服务端
实现机制（简述）：
- 全局 `asyncio.Lock` + 时间戳队列
- 发送前清理窗口外时间戳
- 若窗口未满，立即占位并发送
- 若窗口已满，按最早时间戳计算等待时间后重试
禁用方式：
- `api_rate_limit_max_requests <= 0` 或 `api_rate_limit_window_seconds <= 0`
### 3.3 从 collection 按需提取数据（重点）
在 API 模式下，Handler 不是盲目请求，而是从 `collection` 按依赖提取后再调用 API。
常见模式：
1. load 前置依赖提取
- 例如合同 Handler 先从 collection 取 project 节点，再按 project_id 拉合同列表
2. create/update 提取上下文
- 从 `node.context` 或 `node.get_data()` 中提取依赖字段（如 `project_id`）
3. 节点复用/更新
- `_create_basic_node` 会优先按 `data_id` 命中已有节点，避免重复节点
好处：
- 减少无效 API 调用（按依赖、按项目有选择地加载）
- 保持节点关系与上下文完整（project/contract 等依赖链）
### 3.4 API 校验链路（重点）
API 数据源中，校验分为三层：
1. 领域 schema 校验（请求前/响应后）
- 例如 `ContractCreate.model_validate(...)`、`ContractUpdate.model_validate(...)`
- load 响应也会在解析后转为领域 schema
2. 通用更新过滤与差异识别
- `_filter_update_data`：仅在 schema 相关字段有变化时提交更新
- `_get_schema_diff`：用于差异字段识别与调试输出
3. 轮询接口输入校验
- `PushIdsSchema` 校验 push_ids 格式后再请求 `/push/result`
设计原则：
- 校验失败直接显式失败，不静默降级
- 保持状态机与错误日志可追踪
### 3.5 轮询与结果回写
- create 可返回 IN_PROGRESS（异步）或 SUCCESS（同步）
- `BaseDataSource` 统一轮询并写回节点状态
- 结果通过状态机事件落到 SUCCESS/FAILED
- create 成功后会进行 `data_id` 回写与 collection 更新（必要时）
---
## 4. 配置说明（按数据源区分）
### 4.1 JSONL 数据源配置示例
```yaml
local_datasource:
type: jsonl
jsonl_dir: ${PROJECT_ROOT}/filtered_datasource/datasource/filtered
read_only: false
target_project_ids: []
handler_configs: {}
```
### 4.2 API 数据源配置示例（含限流）
```yaml
remote_datasource:
type: api
api_base_url: http://localhost:8000/api/third/v2
api_uid: your_uid
api_secret: your_secret
api_debug: true
# 轮询配置
poll_max_retries: 1
poll_interval: 2.0
# 全局限流：10 秒最多 10 次请求
api_rate_limit_max_requests: 10
api_rate_limit_window_seconds: 10.0
target_project_ids:
- "project-id-1"
handler_configs: {}
```
### 4.3 配置模型位置
- `sync_state_machine/config/datasource_config.py`
- `JsonlDataSourceConfig`
- `ApiDataSourceConfig`
配置是严格模式（`extra="forbid"`）：
- 未声明字段会报错
- 避免运行时拼写错误导致“配置看起来生效、实际未生效”
---
## 5. 运行建议与排障
### 5.1 API 触发限流（429）时
优先调整：
- 降低 `api_rate_limit_max_requests`
- 提高 `api_rate_limit_window_seconds`
例如：
- `api_rate_limit_max_requests: 8`
- `api_rate_limit_window_seconds: 10.0`
### 5.2 轮询超时
可调整：
- `poll_max_retries`
- `poll_interval`
总等待时长约为：
- `poll_max_retries * poll_interval`
### 5.3 校验失败
建议直接修数据或 schema，不建议绕过校验；当前链路会保留失败信息用于定位。
---
## 6. 相关文件索引
- `sync_state_machine/datasource/datasource.py`
- `sync_state_machine/datasource/jsonl/datasource.py`
- `sync_state_machine/datasource/jsonl/handler.py`
- `sync_state_machine/datasource/api/datasource.py`
- `sync_state_machine/datasource/api/client.py`
- `sync_state_machine/datasource/api/handler.py`
- `sync_state_machine/config/datasource_config.py`
- `run_profiles/jsonl_to_api.yaml`
- `run_profiles/preset/jsonl_to_api.default.yaml`
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# sync_state_machine 接入手册
## 1. 目标
本项目现在可以作为可编辑安装库使用：
- 源码开发：`pip install -e .`
- 代码引用：`import sync_state_machine`
- 命令行运行：`ecm-sync-run --config_path=...`
推荐接入方式：
- `sync_state_machine` 负责同步引擎、状态机、pipeline、datasource 抽象。
- 业务系统负责提供自己的数据源适配层，不要反向让 `sync_state_machine` 依赖业务系统。
---
## 2. 安装方式
### 2.1 本仓库本地安装
在仓库根目录执行：
```bash
pip install -e .
```
安装后可直接使用：
```python
import sync_state_machine
print(sync_state_machine.__version__)
```
也可以直接走命令：
```bash
ecm-sync-run --config_path=run_profiles/preset/jsonl_to_api.default.yaml
```
---
## 3. 对外可直接引用的入口
常用入口：
- `sync_state_machine.build_config`
- `sync_state_machine.build_default_config`
- `sync_state_machine.run_pipeline_from_config`
- `sync_state_machine.create_pipeline_from_config`
- `sync_state_machine.PipelineRunConfig`
- `sync_state_machine.JsonlDataSourceConfig`
- `sync_state_machine.ApiDataSourceConfig`
- `sync_state_machine.DomainRegistry`
内置 domain 注册会在导入包时自动完成。
---
## 4. 最小接入示例
### 4.1 直接运行现有 pipeline
```python
from pathlib import Path
from sync_state_machine import build_config, load_overrides_from_file, run_pipeline_from_config
async def main() -> None:
project_root = Path("/path/to/ecm_sync_system")
profile_path = project_root / "run_profiles" / "preset" / "jsonl_to_api.default.yaml"
overrides = load_overrides_from_file(profile_path, project_root)
config = build_config(project_root=project_root, overrides=overrides)
await run_pipeline_from_config(config, title="demo", print_summary=True)
```
适合场景：
- 仍沿用当前仓库的 domain 注册
- 仍沿用当前仓库的 JSONL / API handler
- 外部系统只想“调用引擎”
---
## 5. 数据源怎么引用
当前引擎的 datasource 分两层：
1. `DataSource`
- 管理加载、批量执行、轮询、collection 注入、handler 注册。
2. `Handler`
- 只处理某一个 `node_type` 的 I/O 逻辑。
因此接入时，不是“直接把业务 ORM 塞进 pipeline”，而是：
- 先确定你的数据源类型
- 再决定复用已有 datasource，还是只新增 handler
### 5.1 已有两类 datasource
#### JSONL
可直接复用：
- `sync_state_machine.datasource.JsonlDataSource`
- `sync_state_machine.datasource.BaseJsonlHandler`
适合：
- 本地 fixture
- 离线回放
- 调试数据集
#### API
可直接复用：
- `sync_state_machine.datasource.ApiDataSource`
- `sync_state_machine.datasource.ApiClient`
- `sync_state_machine.datasource.BaseApiHandler`
适合：
- HTTP 接口推送
- 异步 push + poll
- 远端系统同步
---
## 6. 怎么适配数据源
### 6.1 最推荐：复用已有 datasource，只写 handler
这是最小成本方案。
比如你的本地数据来自 backend 的数据库，但你不想改引擎核心，可以：
- 保持 `ApiDataSource` / `JsonlDataSource` 不变
- 新增你自己的 handler
- 在 handler 里把 backend 数据模型转换成节点 schema
如果是 HTTP 源：继承 `BaseApiHandler`。
如果是 JSONL 源：继承 `BaseJsonlHandler`。
#### API handler 示例
```python
from pydantic import BaseModel
from sync_state_machine.datasource.api.handler import BaseApiHandler
class DemoSchema(BaseModel):
id: str
name: str
class DemoApiHandler(BaseApiHandler[DemoSchema]):
_node_type = "demo"
_node_class = DemoSyncNode
_schema = DemoSchema
async def load(self):
payload = await self.api_client.get("/demo/list")
return [self._create_node(item) for item in payload["data"]]
async def create_all(self, nodes):
...
async def update_all(self, nodes):
...
async def delete_all(self, nodes):
...
async def poll_tasks(self, task_ids):
...
```
#### JSONL handler 示例
```python
from sync_state_machine.datasource.jsonl.handler import BaseJsonlHandler
class DemoJsonlHandler(BaseJsonlHandler):
def __init__(self, datasource):
super().__init__(
datasource=datasource,
node_type="demo",
node_class=DemoSyncNode,
schema=DemoSchema,
)
```
然后把它注册到 `DomainRegistry`。
---
### 6.2 如果 backend 是数据库：建议写“数据库 handler / adapter”，不要让引擎直接依赖 ORM
推荐结构：
```text
backend/
app/
integrations/
ecm_sync/
datasource/
user_db_handler.py
contract_db_handler.py
mapper/
user_mapper.py
contract_mapper.py
services/
sync_runner.py
```
职责建议：
- `mapper/`
- backend model -> sync schema
- sync schema -> backend push payload
- `datasource/handler`
- 调 repository / service 获取数据
- 转成 `SyncNode`
- `services/sync_runner.py`
- 组装配置并调用 pipeline
不要这样做：
- 不要在 `sync_state_machine` 包里 import backend 的 model/repository
- 不要让 `DomainRegistry` 注册逻辑散落在 backend 业务层之外
---
### 6.3 什么时候需要新增 DataSource 类
只有当你的 I/O 模型与当前两种 datasource 都不匹配时，才新增 `BaseDataSource` 子类。
例如：
- MQ / Kafka 批量消费型源
- 直接数据库快照源
- 特殊 RPC 源
此时建议：
1. 继承 `BaseDataSource`
2. 保持接口与现有 datasource 一致：
- `register_handler()`
- `set_collection()`
- `load_all()`
- `sync_all()`
3. 把“节点类型差异”仍下沉到 handler，不要写死在 datasource 里
---
## 7. Domain 怎么注册
引擎通过 `DomainRegistry` 查找：
- `schema`
- `node_class`
- `strategy_class`
- `jsonl_handler_class`
- `api_handler_class`
示例：
```python
from sync_state_machine.common.registry import DomainRegistry
DomainRegistry.register(
node_type="demo",
schema=DemoSchema,
node_class=DemoSyncNode,
strategy_class=DemoStrategy,
jsonl_handler_class=DemoJsonlHandler,
api_handler_class=DemoApiHandler,
)
```
如果是 backend 接入，建议在 backend 的 integration 启动阶段集中注册，而不是分散在 controller / service 里。
---
## 8. backend 里的推荐接法
建议 backend 只新增一层 integration：
```python
from pathlib import Path
from sync_state_machine import build_config, create_pipeline_from_config
async def run_demo_sync() -> None:
project_root = Path("/path/to/ecm_sync_system")
overrides = {
"node_types": ["project", "contract"],
"local_datasource": {
"type": "jsonl",
"jsonl_dir": str(project_root / "tests" / "fixtures" / "demo"),
},
"remote_datasource": {
"type": "api",
"api_base_url": "https://example.com",
"api_uid": "xxx",
"api_secret": "xxx",
"target_project_ids": ["demo-project"],
},
}
config = build_config(project_root=project_root, overrides=overrides)
pipeline = await create_pipeline_from_config(config)
await pipeline.run()
```
如果 backend 自己提供本地数据库数据，不要把 backend model 直接灌进 pipeline；先经过 handler / mapper 转成 schema 再进入引擎。
---
## 9. 接入时的边界约束
建议保持下面的依赖方向：
- `backend integration -> sync_state_machine`
- `sync_state_machine -X-> backend`
这样做的好处：
- 引擎能独立测试
- backend 改 repository 不会直接污染引擎
- 后续可以单独发布库
---
## 10. 当前阶段建议
如果项目还在高频迭代，推荐顺序：
1. 先 `pip install -e .`
2. 先在 backend 做 integration 目录，不急着发私有包
3. 先接 1~2 个 node_type，跑通完整链路
4. 稳定后再考虑拆成正式发布包
---
## 11. 相关文件
- 包入口：[sync_state_machine/__init__.py](../sync_state_machine/__init__.py)
- CLI：[sync_state_machine/cli.py](../sync_state_machine/cli.py)
- 配置工厂：[sync_state_machine/config](../sync_state_machine/config)
- datasource 基础层：[sync_state_machine/datasource](../sync_state_machine/datasource)
- pipeline 工厂：[sync_state_machine/pipeline/factory.py](../sync_state_machine/pipeline/factory.py)
- domain 注册：[sync_state_machine/common/registry.py](../sync_state_machine/common/registry.py)
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# 节点状态定义（业务核心）
本文档定义 `SyncNode` 的状态字段语义，并说明状态机如何把这些语义形式化为可执行规则。
## 1. 节点状态字段
### `binding_status`
- 含义：绑定判定结果，决定节点是否允许进入 create/update。
- 取值：`UNCHECKED | NORMAL | MISSING | PEER_CREATING | WARNING | ABNORMAL | DEPENDENCY_ERROR`
### `action`
- 含义：本轮同步意图。
- 取值：`NONE | CREATE | UPDATE | DELETE`
- 说明：本项目当前主路径使用 `NONE/CREATE/UPDATE`。
### `status`
- 含义：执行状态。
- 取值：`PENDING | IN_PROGRESS | SUCCESS | FAILED | SKIPPED | PRECONDITION_FAILED`
### `data_id`
- 含义：目标系统业务主键是否就绪。
- 关键语义：`UPDATE` 路径要求目标节点具备 `data_id`，否则进入 `PRECONDITION_FAILED`。
### `error`
- 含义：阻断/失败原因。
- 说明：依赖错误与执行错误都在该字段记录可读原因。
## 2. 绑定状态业务语义
| binding_status | 业务语义 | 是否允许进入 create/update |
|---|---|---|
| `UNCHECKED` | 尚未执行 bind 判定 | 否 |
| `NORMAL` | 绑定链路健康，可做差异检测与同步 | 是 |
| `MISSING` | 无绑定记录，需做依赖检查与自动绑定/创建策略 | 有条件 |
| `PEER_CREATING` | 对侧创建进行中（等待创建提交） | 否（等待 E20 提交） |
| `WARNING` | 风险态（如自动绑定歧义/关闭） | 否 |
| `ABNORMAL` | 数据损坏或核心绑定异常 | 否 |
| `DEPENDENCY_ERROR` | 依赖不可满足 | 否 |
## 3. create / update 语义
### create
- 来源：`MISSING` 节点在策略允许时生成目标 `CREATE` 节点。
- 形式化：`E20/E21` + `spawn_target_node_state: S06`。
### update
- 来源：`NORMAL` 节点差异检测后生成目标 `UPDATE`。
- 形式化：`E30`。
- 前置失败：目标缺 `data_id` 或依赖 ID 解析失败时进入 `S08`，且必须 `action=UPDATE`。
## 4. 执行状态语义（datasource）
- `SUCCESS`：执行成功，必要时回填 `data_id`。
- `FAILED`：执行失败，保留错误。
- `IN_PROGRESS`：异步任务进行中。
- `SKIPPED`：handler 决策跳过；若由 UPDATE 降级为 NONE，则进入 `S14`。
- `PRECONDITION_FAILED`：准备阶段失败，不进入实际 API 提交。
## 5. 状态机形式化映射
状态机把“业务语义”变成“可执行迁移”：
- 语义输入：strategy/datasource 提供 `context`。
- 迁移判断：`StateMachineRuntime.dispatch(current_state, event_id, context)`。
- 状态落地：`Decision.to_state` 对应 YAML `states[Sxx]`。
- 不变量：每次落地后执行 `runtime.check_invariants()`。
## 6. 关键一致性约束
- `UNCHECKED` 不允许带动作（`INV-1_UNCHECKED_ACTION_NONE`）。
- 阻断态（`ABNORMAL/WARNING/DEPENDENCY_ERROR`）不允许动作（`INV-2_BLOCKING_NO_ACTION`）。
- `PRECONDITION_FAILED` 必须 `action=UPDATE`（`INV-3_PRECOND_IMPLIES_UPDATE`）。
## 7. 当前默认依赖语义（业务取向）
以下是当前代码默认策略，不是单纯命名差异：
- 空依赖引用允许放行（`allow_empty_dependency_ref=True`）。
- 依赖节点缺失 `data_id` 默认允许放行（`allow_missing_dep_data_id=True`）。
这意味着：`DEPENDENCY_ERROR` 的触发更偏向“依赖节点不存在或状态异常”，而不是“依赖节点尚未回填 data_id”。如果要改为严格模式，需要在 strategy 语义层切换该策略并同步文档。
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# 运维与排障手册（业务视角）
本文档聚焦两件事：
- 出错时先看哪里。
- 日志里的状态到底代表什么业务问题。
## 1. 先看什么（快速定位）
1. 看运行日志（`sync_log`）：
- 重点关注 `状态机流转`、`reason=`、`depends=[...]`。
2. 看持久化数据库：
- 重点字段：`binding_status`、`action`、`status`、`error`。
3. 对照状态机文档：
- `docs/state_machine.md`
- `docs/node_state_definition.md`
## 2. 阶段化排障
### 2.1 bind 阶段
常见表现：节点停在 `S03/S04/S05/S13`。
- `S03(ABNORMAL)`：节点数据损坏或核心绑定异常。
- `S04(WARNING)`：自动绑定关闭、键缺失、歧义等不可自动处理情况。
- `S05(DEPENDENCY_ERROR)`：依赖节点不存在或依赖状态不正常。
- `S13(PEER_CREATING)`：对侧创建进行中，尚未提交完成。
典型日志：
- `reason=依赖项不满足 | depends=[company_id status=peer_creating -> not_normal]`
业务解释：
- 上游依赖还没进入 `NORMAL`，下游业务会被严格阻断。
### 2.2 create 阶段
常见表现：节点长时间停在 `S13` 或 `S10C`。
- `S13`：已判定需要创建，但创建提交未完成。
- `S10C`：CREATE 异步执行中。
- `S12C`：CREATE 失败。
优先检查：
- API 侧是否返回任务 ID 与成功回执。
- 轮询参数（`poll_max_retries` / `poll_interval`）是否过小。
### 2.3 update 阶段
常见表现：节点进入 `S08` 或 `S12U`。
- `S08(PRECONDITION_FAILED)`：前置条件失败（如缺 data_id、依赖 ID 解析失败）。
- `S12U`：UPDATE 调用失败。
- `S14`：UPDATE 被 handler 降级为 NONE 并跳过。
优先检查：
- `update_direction` 是否符合预期。
- 目标节点是否具备 `data_id`。
## 3. 常见配置误区与症状
- `auto_bind=false`
- 症状：MISSING 节点更容易进入 `WARNING`，不会走自动创建识别。
- `skip_sync=true`
- 症状：该类型只加载不执行 bind/create/update，常被误以为“没生效”。
- `load_mode=persisted_only`
- 症状：数据只来自持久化，不主动拉取新数据。
- `update_direction=none`
- 症状：不做 update，即使有差异也不会提交更新。
## 4. 推荐操作顺序
1. 先用 `run_profiles/preset/jsonl_to_jsonl.default.yaml` 跑通基线。
2. 再切到 `run_profiles/*.local.yaml` 做最小覆盖。
3. 每次只改一类字段（比如只改 `project` 的依赖策略）。
4. 改完看一次 `sync_log`，确认状态流转与预期一致。
## 5. UI 排障（可选）
1. 启动：`python -m ui.main --host 127.0.0.1 --port 8765`
2. 打开：`http://127.0.0.1:8765`
3. 在“运行与日志”查看实时状态变化。
4. 在“记录与数据库”检查节点状态与绑定记录。
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# 运行配置业务说明
本文档从业务视角说明配置字段含义、对阶段行为的影响，以及推荐的覆盖方式。
## 1. 推荐使用方式（先 default，再覆盖）
1. 先使用基线配置运行：
- `run_profiles/preset/jsonl_to_jsonl.default.yaml`
2. 若需项目定制，再复制为：
- `run_profiles/jsonl_to_jsonl.local.yaml`
3. 仅改有业务差异的字段，避免一次改太多导致排障困难。
占位符：
- `${PROJECT_ROOT}` 会在运行时替换为项目根目录绝对路径。
## 2. 顶层字段（你在改什么）
- `node_types`
- 本轮参与同步的业务类型列表。
- 顺序会影响依赖链执行时机（当前按 node_type 串行执行 bind/create/update）。
- `target_project_ids`
- 兼容字段。作为两侧 datasource 的项目白名单兜底值。
- 若 datasource 自身配置了 `target_project_ids`，则优先使用 datasource 级配置。
- `local_datasource` / `remote_datasource`
- 分别定义两侧数据来源与执行端。
- `strategies`
- 每个业务类型的行为策略（依赖、自动绑定、创建方向、更新方向、跳过等）。
- `persist`
- 持久化开关与数据库位置。
- `logging`
- 运行日志输出位置与级别。
## 3. 数据源字段（DataSource）
### 3.1 JSONL 数据源
- `type=jsonl`：使用本地 JSONL 文件作为数据源。
- `jsonl_dir`：JSONL 目录路径。
- `read_only=false`：允许该侧执行 create/update 回写；若为 true，通常用于只读加载。
- `target_project_ids=[]`：该侧项目白名单；为空时不进行项目筛选。
- `handler_configs`：预留给各业务 handler 的扩展参数。
### 3.2 API 数据源
- `type=api`：对接 HTTP API。
- `api_base_url` / `api_uid` / `api_secret`：接口访问参数。
- `api_debug`：开启后输出更多调试信息。
- `poll_max_retries` / `poll_interval`：异步任务轮询次数与间隔。
- `target_project_ids`：**必填**，该侧项目白名单；至少需要指定一个项目ID，以避免加载过多远程数据。
- `handler_configs`：业务 handler 扩展参数。
## 4. 策略字段（Strategy）
每个 node_type 都建议显式写出以下字段，便于审阅与排障。
### 4.1 `update_direction`
- `push`：本地变更推送到远端。
- `pull`：远端变更拉取到本地。
- `bidirectional`：双向更新（需要明确冲突策略，谨慎使用）。
- `none`：关闭 update 阶段。
### 4.2 `local_orphan_action` / `remote_orphan_action`
- `create_remote`：本地孤儿创建到远端。
- `create_local`：远端孤儿创建到本地。
- `none`：不自动创建。
- `delete_local` / `delete_remote`：当前主流程未作为默认路径，谨慎使用。
### 4.3 `auto_bind` / `auto_bind_fields` / `pre_bind_data_id`
- `auto_bind=true`：在 `S02(MISSING)` 上尝试自动匹配。
- `auto_bind=false`：不会做自动匹配，也不会走自动创建识别路径；通常会进入阻断态等待人工处理。
- `auto_bind_fields`：自动匹配使用的业务键字段。
- `pre_bind_data_id`：显式 data_id 预绑定清单（通用能力），格式为：
- `- local_data_id: "..."`
` remote_data_id: "..."`
- 规则：若两侧数据源都存在这对 data_id 对应节点，且当前无绑定记录，则直接绑定。
- 不依赖 `auto_bind/auto_bind_fields`，即使 `auto_bind=false` 也会执行。
- 不做业务键一对一匹配检查，按你给定的映射对优先执行。
### 4.4 `depend_fields`
- 定义依赖字段到依赖 node_type 的映射，例如：`company_id -> company`。
- 依赖节点状态非 `NORMAL` 时，会在 bind 的依赖检查阶段进入 `DEPENDENCY_ERROR`。
### 4.5 `skip_sync`
- 运行配置中已不建议使用 `skip_sync`。
- 推荐使用显式组合：
- `local_orphan_action: none`
- `remote_orphan_action: none`
- `update_direction: none`
- 当三者同时为 `none/none/none` 时，pipeline 会跳过该 node_type 的 bind/create/update。
### 4.6 Handler 级参数（`handler_configs`）
- 建议将 handler 特有参数放在 datasource 的 `handler_configs.<node_type>` 下。
- 示例：
- `remote_datasource.handler_configs.supplier.load_mode: persisted_only`
- `persisted_only` 表示只使用已持久化数据，不主动从外部拉新数据（具体以对应 handler 实现为准）。
## 5. 阶段行为与配置关系
- bind 阶段
- `depend_fields` 决定是否做依赖校验。
- `pre_bind_data_id` 先按显式 local/remote data_id 映射做预绑定。
- `auto_bind/auto_bind_fields` 决定是否继续进行业务键自动绑定。
- create 阶段
- `local_orphan_action` / `remote_orphan_action` 决定孤儿是否创建。
- update 阶段
- `update_direction` 决定是否和向哪侧更新。
- 写入后 reload（Pipeline 内置）
- 当某个 node_type 的 create 或 update 发生实际写入成功后，pipeline 会自动对该 node_type 重新执行两侧 `load`。
- 目的：让后续 update 判断基于最新远端/本地数据，支持“create 后再补一次 update”的链路。
- 同步后一致性检查（Pipeline 内置）
- 每个 node_type 在本轮同步后会基于绑定对执行数据一致性校验（比较时忽略 `id/_id` 字段）。
- 若发现差异，会在日志中打印差异样本，并在汇总表新增 `Consistent` 列展示 `Y` / `N(差异数)`。
- 全局跳过
- `local_orphan_action=none` + `remote_orphan_action=none` + `update_direction=none`
可直接跳过该类型的 bind/create/update。
## 6. 覆盖配置建议
- 先在 default 跑通一轮，再做 local 覆盖。
- 每次只改一类问题相关字段（例如只改 `project` 的依赖与自动绑定）。
- 覆盖后优先看 `sync_log` 是否出现预期状态迁移。
## 7. 持久化与日志字段
### `persist`
- `enable`：是否开启持久化。
- `db_path`：SQLite 路径。
- `wipe_on_start`：启动是否清理历史持久化。
### `logging`
- `file_dir`：日志目录。
- `file_name_pattern`：文件命名模板。
- `level`：日志级别。
排障建议：运行失败时优先看日志中的 `状态机流转` 与 `reason=`，再对照 `docs/state_machine.md` 与 `docs/node_state_definition.md` 理解含义。
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# 状态机形式化说明（与代码一致）
## 1. 真源与执行入口
- 配置真源：`sync_state_machine/config/node_state_machine.yaml`
- 事件入口：`sync_state_machine/engine/events.py`
- 状态落地：`sync_state_machine/engine/state_apply.py`
- 不变量校验：`events._apply_decision()` 内调用 `runtime.check_invariants()`
## 2. 状态集合（Sxx）
- `S00`：bind 起点（`UNCHECKED/NONE/PENDING`）
- `S01`：NORMAL，待后续 create/update 判定
- `S02`：MISSING，待依赖检查/自动绑定/create
- `S03`：ABNORMAL，阻断
- `S04`：WARNING，阻断
- `S05`：DEPENDENCY_ERROR，阻断
- `S06`：CREATE 待执行（目标节点）
- `S07`：UPDATE 待执行（`action=UPDATE,status=PENDING`）
- `S08`：UPDATE 前置失败（`action=UPDATE,status=PRECONDITION_FAILED`）
- `S10C/S10U/S10D`：按动作拆分的执行中状态
- `S11C/S11U/S11D`：按动作拆分的执行成功状态
- `S12C/S12U/S12D`：按动作拆分的执行失败状态
- `S13`：对侧创建等待态（`PEER_CREATING/NONE/PENDING`）
- `S14`：UPDATE 运行时降级为 `NONE` 并跳过
## 3. 事件到代码映射
### bootstrap
- `E01`：`engine/events.py::e01_bootstrap()`
### bind
- `E10`：`engine/events.py::e10_bind_core()`
- `E15`：`engine/events.py::e15_bind_dependency()`
- `E16`：`engine/events.py::e16_bind_auto()`（自动绑定判定；`ZERO+create_enabled=true` 时进入 `S13`，等待创建副作用提交）
### create/update prepare
- `E20`：`engine/events.py::e20_create_prepare()`（spawn 成功从 `S13` 提交到 `S01`；失败保持 `S13`）
- `E21`：`engine/events.py::e21_create_prepare()`
- `E30`：`engine/events.py::e30_update_prepare()`
### sync execute
- `E40C_START/E40C`：CREATE 执行入口与结果回写
- `E40U_START/E40U`：UPDATE 执行入口与结果回写
- `E40D_START/E40D`：DELETE 执行入口与结果回写
## 4. strategy 调用链（当前）
- bind 主入口：`sync_system/strategy.py::DefaultSyncStrategy.bind()` -> `strategy_ops/bind_ops.py::run_bind()`
- create 主入口：`sync_system/strategy.py::DefaultSyncStrategy.create()` -> `strategy_ops/create_ops.py::run_create()`
- update 主入口：`sync_system/strategy.py::DefaultSyncStrategy.update()` -> `strategy_ops/update_ops.py::run_update()`
- reset 主入口：`sync_system/strategy.py::BaseSyncStrategy.run_reset()` -> `strategy_ops/reset_ops.py::run_phase2_cleanup()`
## 5. context 字段（以 YAML 为准）
### bind 相关
- `has_binding_record`
- `core_binding_result` / `peer_core_binding_result` (`NORMAL|WARNING|ABNORMAL`)
- `data_present`
- `has_depend_fields`
- `dep_satisfied`
- `auto_bind_enabled`
- `auto_bind_outcome` (`ONE_TO_ONE|AMBIGUOUS|ZERO|KEY_MISSING|KEY_ID_RESOLVE_FAIL|DATA_MISSING`)
### create/update 相关
- `create_enabled`
- `create_id_resolve_ok`
- `spawn_success`
- `update_enabled`
- `target_has_data_id`
- `update_id_resolve_ok`
- `has_diff`
### execute 相关
- `handler_result` (`SUCCESS|FAILED|SKIPPED|IN_PROGRESS`)
- `poll_timeout`
## 6. 语义边界
- strategy 负责业务语义计算（如依赖是否满足、自动绑定结果、差异检测）。
- 状态机只负责迁移判定与不变量校验，不直接访问数据源。
## 7. 不变量
- `INV-1_UNCHECKED_ACTION_NONE`
- `INV-2_BLOCKING_NO_ACTION`
- `INV-3_PRECOND_IMPLIES_UPDATE`
当状态落地后违反 invariant，运行时会直接抛错。
## 8. 校验与出图
1. `python tools/validate_config.py --config sync_state_machine/config/node_state_machine.yaml`
2. `python tools/render_graph.py --config sync_state_machine/config/node_state_machine.yaml --format mermaid --out docs/state_machine.mmd`
## 9. 事件意图命名（图示层）
- 为了让流程意图更直观，图示可使用 `E01.reset.* / E10.core.* / E20.create.* / E30.update.* / E40<action>.* / E41.create.*` 这类别名。
- 别名仅用于图标签；运行时事件 ID 仍以 YAML 中 `E01/E10/E15/E16/E20/E21/E30/E40C_START/E40C/E40U_START/E40U/E40D_START/E40D/E41` 为准。
- `S10C/S10U/S10D` 与 `S11C/S11U/S11D` 现已是配置中的真实状态 ID（不再是图示别名）。
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flowchart LR
subgraph BOOT["Bootstrap / Reset"]
S00["S00<br/>进入 bind 前的唯一起点<br/>binding_status: UNCHECKED<br/>action: NONE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
S15(["S15<br/>节点被清理删除（zombie cleanup）"])
S16(["S16<br/>持久化加载输入态：本轮 E01 的输入节点集合（可包含上轮遗留与已稳定节点）"])
S17(["S17<br/>加载异常隔离态：持久化枚举非法，保留错误供人工处理，不进入自动流程"])
end
subgraph BIND["Binding"]
S01["S01<br/>绑定正常（待后续 update 检查）<br/>binding_status: NORMAL<br/>action: NONE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
S02["S02<br/>孤儿节点（可能进入 create / auto_bind / delete）<br/>binding_status: MISSING<br/>action: NONE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
S03["S03<br/>数据损坏/缺失（阻断态，需人工）<br/>binding_status: ABNORMAL<br/>action: NONE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
S04["S04<br/>不可自动处理（阻断态，需人工）<br/>binding_status: WARNING<br/>action: NONE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
S05["S05<br/>依赖项不满足/ID解析失败（阻断态）<br/>binding_status: DEPENDENCY_ERROR<br/>action: NONE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
S13["S13<br/>对侧创建进行中（本侧等待提交）<br/>binding_status: PEER_CREATING<br/>action: NONE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
end
subgraph CREATE["Create"]
S06(["S06<br/>待执行 CREATE（执行入口）<br/>binding_status: NORMAL<br/>action: CREATE<br/>status: PENDING<br/>data_id_exist: false<br/>"])
S10C["S10C<br/>CREATE 异步执行中<br/>binding_status: NORMAL<br/>action: CREATE<br/>status: IN_PROGRESS<br/>data_id_exist: false<br/>"]
S11C["S11C<br/>CREATE 执行成功<br/>binding_status: NORMAL<br/>action: CREATE<br/>status: SUCCESS<br/>data_id_exist: true<br/>"]
S12C["S12C<br/>CREATE 执行失败<br/>binding_status: NORMAL<br/>action: CREATE<br/>status: FAILED<br/>data_id_exist: false | true<br/>"]
end
subgraph UPDATE["Update"]
S07["S07<br/>准备更新<br/>binding_status: NORMAL<br/>action: UPDATE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
S08["S08<br/>更新前置失败（缺 data_id / 依赖ID未解析等）<br/>binding_status: NORMAL<br/>action: UPDATE<br/>status: PRECONDITION_FAILED<br/>data_id_exist: false | true<br/>"]
S10U["S10U<br/>UPDATE 异步执行中<br/>binding_status: NORMAL<br/>action: UPDATE<br/>status: IN_PROGRESS<br/>data_id_exist: true<br/>"]
S11U["S11U<br/>UPDATE 执行成功<br/>binding_status: NORMAL<br/>action: UPDATE<br/>status: SUCCESS<br/>data_id_exist: true<br/>"]
S12U["S12U<br/>UPDATE 执行失败<br/>binding_status: NORMAL<br/>action: UPDATE<br/>status: FAILED<br/>data_id_exist: false | true<br/>"]
S14["S14<br/>更新被跳过（执行时降级为 NONE）<br/>binding_status: NORMAL<br/>action: NONE<br/>status: SKIPPED<br/>data_id_exist: true<br/>"]
end
subgraph DELETE["Delete"]
S09["S09<br/>待执行 DELETE（执行入口）<br/>binding_status: NORMAL<br/>action: DELETE<br/>status: PENDING<br/>data_id_exist: true<br/>"]
S10D["S10D<br/>DELETE 异步执行中<br/>binding_status: NORMAL<br/>action: DELETE<br/>status: IN_PROGRESS<br/>data_id_exist: true<br/>"]
S11D["S11D<br/>DELETE 执行成功（随后删除节点）<br/>binding_status: NORMAL<br/>action: DELETE<br/>status: SUCCESS<br/>data_id_exist: true<br/>"]
S12D["S12D<br/>DELETE 执行失败<br/>binding_status: NORMAL<br/>action: DELETE<br/>status: FAILED<br/>data_id_exist: false | true<br/>"]
end
S00 -- "E10a 核心绑定判定" --> S01
S00 -- "E10e 核心绑定判定" --> S02
S00 -- "E10c 核心绑定判定, E10d 核心绑定判定" --> S03
S00 -- "E10b 核心绑定判定" --> S04
S01 -- "E30c 更新准备" --> S07
S01 -- "E30a 更新准备, E30b 更新准备" --> S08
S02 -- "E16c 自动绑定（1:1）" --> S01
S02 -- "E15b 依赖检查" --> S03
S02 -- "E15a 依赖检查, E16a 自动绑定, E16b 自动绑定, E16d 自动绑定, E16e 自动绑定, E16h 自动绑定（N:0）" --> S04
S02 -- "E15c 依赖检查, E16f 自动绑定, E21a 创建依赖解析失败" --> S05
S02 -- "E22a 孤儿自删准备" --> S09
S02 -- "E16g 自动绑定（N:0）" --> S13
S06 -- "E40C_STARTa CREATE 执行入口" --> S10C
S07 -- "E40U_STARTa UPDATE 执行入口" --> S10U
S09 -- "E40D_STARTa DELETE 执行入口" --> S10D
S10C -- "E40Ca CREATE 执行结果回写" --> S11C
S10C -- "E40Cb CREATE 执行结果回写" --> S12C
S10D -- "E40Da DELETE 执行结果回写" --> S11D
S10D -- "E40Db DELETE 执行结果回写" --> S12D
S10U -- "E40Ua UPDATE 执行结果回写" --> S11U
S10U -- "E40Ub UPDATE 执行结果回写" --> S12U
S10U -- "E40Uc UPDATE 执行结果回写" --> S14
S11C -- "E41a 创建成功后归并到 update …" --> S01
S13 -- "E20a 创建准备阶段2" --> S01
S16 -- "E01b 初始化：删CREATE僵尸；其余…" --> S00
S16 -- "E01a 初始化：删CREATE僵尸；其余…" --> S15
S13 -. "副作用: E16识别需创建后，对侧spawn S06" .-> S06
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# 同步流程（pipeline -> strategy -> datasource）
## 1. 全流程主线
1. pipeline 装配组件并加载持久化。
2. pipeline 调用 `strategy.bind()`。
3. pipeline 调用 `strategy.create()` / `strategy.update()` 生成动作节点。
4. pipeline 调用 `datasource.sync_all()` 执行动作并回写执行状态。
5. pipeline 输出统计并持久化。
## 2. reset 时序
### 2.1 加载时 reset（phase1 语义）
- 在 `common/collection.py::load_from_persistence()` 执行。
- 语义：仅恢复持久化状态（不在此阶段做状态归并）。
### 2.2 加载后 cleanup（phase2 语义）
- pipeline 调用 `BaseSyncStrategy.run_reset()`。
- 实际实现：`strategy_ops/reset_ops.py::run_phase2_cleanup()`。
- 核心事件：`E01`（`S16 -> S00/S15`）。
- `S16` 表示“持久化加载输入态”：本轮从持久化恢复出的节点集合（可包含上轮遗留节点，也可包含上轮已稳定节点）。
- 判定：
- `is_create_zombie=true` -> `S15`，节点删除（并尝试解绑）；
- `is_create_zombie=false` -> `S00`，节点归并为 `UNCHECKED/NONE/PENDING` 并清空 `error`。
### 2.2.1 `enable_persistence` 与 bootstrap 关系
- `enable_persistence=true`：先 `load_from_persistence()`，再对加载出的节点执行 `E01`（`S16` 域内处理）。
- `enable_persistence=false`：本轮没有持久化输入，`S16/E01` 不参与；随后 Stage1 新加载节点直接进入本轮 bind/create/update/sync 主流程。
### 2.3 加载异常隔离（S17）
- 持久化中若出现非法枚举值（`action/status/binding_status`），节点标记为 `bootstrap_blocked`（`S17` 语义）。
- 这类节点保留 `error`，用于人工排查。
- 这类节点不会进入 `E01`，也不会参与 bind/create/update/sync 自动流程。
## 3. bind 流程（strategy_ops）
- 入口：`strategy_ops/bind_ops.py::run_bind()`
- 入口状态：`S00`
### 核心绑定判定
- `phase_core_state()` 内触发 `E10`。
- 有绑定记录：根据本端/对端有效性进入 `S01/S03/S04`。
- 无绑定记录：进入 `S02`。
### 依赖检查
- `phase_dependency_check()` -> `check_dependencies_for_nodes()` 内触发 `E15`。
- `data_present=false` -> `S03`。
- `dep_satisfied=false` -> `S05`。
- `depend_fields` 为空 -> `S04`（无法自动处理，阻断后续自动创建）。
### 自动绑定
- `phase_auto_binding()` 内触发 `E16`。
- `ONE_TO_ONE` -> `S01`；`AMBIGUOUS/KEY_MISSING/DATA_MISSING` -> `S04`；`KEY_ID_RESOLVE_FAIL` -> `S05`。
- `ZERO + create_enabled=true` -> `S13`（`PEER_CREATING/NONE/PENDING`，待对侧创建中间态）；`ZERO + create_enabled=false` -> `S04`。
- `auto_bind=false` 时，`E16` 直接落 `S04`（自动绑定未启用），不会进入自动创建路径。
## 4. create/update 准备
### create
- 入口：`strategy_ops/create_ops.py::run_create()`
- 运行时事件：`E20`（`E21/E22` 为配置保留分支，当前 strategy 未接入自动执行）
- 运行时入口状态：`S13`
- 说明：`E16` 负责识别“需自动创建”并将源节点置为 `S13`；业务代码执行对侧 spawn+bind 后，再通过 `E20` 将 `S13` 提交到 `S01`（成功）；若 spawn 失败，`E20` 不迁移并保留在 `S13` 等待人工/重试。
- `data_id` 约束：
- `S13/S01` 要求源节点 `data_id` 存在（`data_id_exist=true`）。
- 新创建目标节点在 `S06/S10C` 阶段允许 `data_id` 为空；`CREATE SUCCESS`（`S11C`）必须携带非空 `result_data_id`，否则事件直接报错。
### update
- 入口：`strategy_ops/update_ops.py::run_update()`
- 事件：`E30`
- 入口状态（source 节点）：`S01`
- `target_has_data_id=false` 或 `update_id_resolve_ok=false` -> `S08`
- `has_diff=true` -> `S07`
### post-create 归并
- 入口：`pipeline/full_sync_pipeline.py::normalize_create_success_to_update_entry()`
- 事件：`E41`
- 语义：`CREATE` 执行成功后，节点先落 `S11C`（SUCCESS），再归并 `S11C -> S01`，作为同轮 update 起点。
## 5. 执行回写（datasource）
- 入口：`datasource/datasource.py`
- 事件：`E40C_START/E40C`、`E40U_START/E40U`、`E40D_START/E40D`
- 当前约束：delete stage 尚未接入 strategy 主流程；若运行时检测到 `S09/DELETE` 节点，DataSource 会显式抛错阻断（避免散落删除执行）。
- 执行准备入口状态：
- `CREATE`: `S06`
- `UPDATE`: `S07`
- `DELETE`: `S09`
- `S10` 为执行中状态（由本轮执行产生），执行流转固定为“入口 -> S10 -> 终态”，不再出现入口直接到成功/失败。
- 结果：
- `SUCCESS -> S11C | S11U | S11D`（按动作）
- `FAILED -> S12C | S12U | S12D`（按动作）
- `IN_PROGRESS -> S10C | S10U | S10D`（按动作，支持异步 polling 闭环）
- `SKIPPED + action=UPDATE -> S14`
## 6. 各阶段入口状态总表
| 阶段 | 入口状态 | 说明 |
|---|---|---|
| Reset(E01) | `S16` | create_zombie -> `S15`；其余 -> `S00` |
| Bind(E10/E15/E16) | `S00` | bind 三段统一从 `S00` 进入 |
| Create Prepare(E20/E21/E22) | `S02` / `S13` | 配置入口含 `S02/S13`；当前 strategy 运行时只处理 `S13` 的 `E20` 提交，`S02` 分支保留未接入 |
| Post-create Ready(E41) | `S11C` | `CREATE` 成功节点归并到 `S01`，进入同轮 update |
| Update Prepare(E30) | `S01` | 仅从 NORMAL 继续判定（create 成功先经 E41 归并） |
| Sync Execute(E40C/U/D) | `S06` / `S07` / `S09` / `S10C` / `S10U` / `S10D` | 执行与回写：按动作分事件；入口先进入 `S10*`，再由 `S10*` 进入 `S11*`/`S12*`；轮询返回 `IN_PROGRESS` 时只记录任务进度，不新增状态迁移；仅 UPDATE 可走 `S14` |
| 隔离（人工） | `S17` | 不参与自动阶段，仅人工处理 |
## 7. 不变量保障
- 每次事件落地后，`engine/events.py::_apply_decision()` 会执行 `runtime.check_invariants()`。
- 违反 invariant 直接抛错，终止当前路径。
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# 同步问题分析（2026-03-05）
## 背景
- 同步方式：先用 `working_local_datasource/filtered` 初始化远程数据库，再基于 `run_profiles/jsonl_to_api.yaml` 执行 `jsonl -> api` 同步。
- 本文基于日志 `test_results/sync_state_machine/simple_pipeline_sm_20260305_102926.log` 与状态库 `test_results/sync_state_machine/simple_pipeline_sm.db`。
## 总体结果
- Pipeline 统计：`loaded=311, synced=204, failed=8, post_check_passed=True, mismatch_types=4`
- 不一致类型：`company`, `construction_task`, `material`, `contract_settlement`
- 其中失败（`failed=8`）全部集中在 `contract_settlement` 的 `UPDATE` 阶段。
## 自动绑定问题
> 注：本轮日志已降噪，自动绑定明细多数为 debug 级；以下结论来自 sqlite 状态库查询。
### 非 normal 绑定状态
1. `local.construction_task_detail` 1 条 `dep_err`
- 错误：依赖 `parent_id -> construction_task` 未找到
- 现象：`depends=[parent_id:construction_task data_id=... -> not_found]`
- 结论：这是明确的依赖绑定失败（上游父节点缺失或 data_id 不可达）。
2. `local.project_detail_data` 2 条 `warning`
- 错误：`未匹配到候选节点且不允许创建`
- 结论：策略配置不允许创建，且自动匹配未命中，属于预期拦截，不是执行异常。
除上述 3 条外，主要业务类型绑定状态均为 `normal`。
## 更新后仍不一致（按类型）
### 1) company（1/1 不一致）
- 差异字段：`city_name`, `province_name`, `parent_name`
- 模式：本地有值，远端为 `None`
- 结论：远端 list 返回字段缺失/置空，导致 post-check 一定失败。
### 2) construction_task（12/32 不一致）
- 典型残留字段：
- `status`
- `complete_quantity`, `complete_rate`
- `actual_complete_date`, `statistic_date`, `delay_days`
- `plan_node`（特别是 `is_audit` 值）
- 模式：远端回读为 `None`/`0.0`/默认值，而本地有业务值。
- 结论：该类字段主要受后端计算/回写策略影响，当前 update API 无法完全收敛到本地口径。
### 3) material（3/20 不一致）
- 典型残留字段：
- `complete_quantity`, `complete_rate`
- `actual_start_date`, `status`, `delay_days`
- `plan_node.is_audit`
- 模式与 construction_task 一致：部分字段被后端默认化或不回写。
- 结论：属于“可更新字段集合与回读字段集合不一致”导致的残留差异。
### 4) contract_settlement（34/34 不一致，最严重）
- 全量普遍差异：`contract_type`（本地 `None`，远端有值如 `DP/GP/...`）
- 伴随差异：`complete_price`, `contract_price`, `actual_start_date`, `plan_complete_date`, `plan_node`, `status` 等
- 执行结果（remote）：`UPDATE SUCCESS=1, FAILED=8, SKIPPED=25`
- 8 条失败统一报错：`API error: 计划节点时间必须 晚于计划开始时间`
- 结论：
- 一部分差异来自字段语义不一致（如 `contract_type`）
- 一部分差异来自计划节点 API 校验失败，导致更新无法落库
- 因此该类型短期内无法靠重跑自动收敛
## 根因归类
### A. 后端返回口径与本地模型口径不一致
- 典型：`company` 的名称类字段、`construction/material` 的状态/累计/统计字段。
### B. 更新 schema/API 覆盖范围有限
- 某些字段在 response 中存在，但不在 update schema 或后端 update 逻辑中生效。
### C. 计划节点约束导致更新失败
- `contract_settlement` 明确出现计划节点时间校验失败，直接阻断更新。
### D. 依赖链局部断裂
- `construction_task_detail` 存在 parent 依赖找不到，导致绑定 `dep_err`。
## 建议优先级（不改代码版）
1. **先处理 contract_settlement 的计划节点校验失败**
- 这是唯一明确执行失败来源（8 条），修复后可显著降低不一致。
2. **明确“应比对字段白名单”与“只读/回写字段”**
- 对 `construction_task/material/company` 区分“业务必须一致字段”与“后端派生/可忽略字段”。
3. **修复依赖断裂样本**
- 针对 `construction_task_detail` 的 `parent_id` 失配，核对父节点是否在过滤阶段被裁掉或 data_id 不一致。
4. **针对 `project_detail_data` 的 warning 决策**
- 确认是否允许创建；若业务上应存在，需调整策略配置。
---
如果需要，我可以基于本文再拆成一份“可执行排障清单”（按 SQL/API/配置三条线），每条给出具体核对命令与验收标准。
## 外部后端实现核对结论（只分析，不改代码）
以下结论来自对 `GroupSideProjectManagementSystem` 后端 `third-v2` 路由、schema、operation、service 的实现阅读。
### 1) company 名称字段为何会空
- `/company/list` 并非直接返回库里的 `city_name/province_name/parent_name`，而是服务层在查询后“二次计算”这三个字段。
- 计算依赖两张映射：
- 行政区映射（`province/city code -> name`）
- 公司映射（`parent_id -> parent_name`）
- 如果编码不在映射中、或 `parent_id` 未命中，最终会返回 `None`/空字符串。
- 因此该类差异并不一定是“推送失败”，更像是“回读时依赖映射补全失败或口径不一致”。
### 2) construction_task/material 的 plan_node 差异为何顽固
- 在 `third-v2` 的 `PlanUpdate` schema 中，存在 `model_validator`：会先自动清理边界节点（等于 `plan_start_date` 或 `plan_complete_date` 的首尾节点）。
- 随后在 operation 的 `push(plan)` 中，又会把边界节点重新插回库里，并且统一写入 `is_audit=True`。
- 这意味着：
- 请求入参和最终落库结构并不完全一致；
- 如果本地源数据不含边界节点，或 `is_audit` 口径不同，post-check 很容易出现稳定残差。
### 3) contract_settlement 为何最严重（34/34 + 8条失败）
- 计划更新接口的业务规则是“开始时间与合同金额来自合同表”，不是来自推送体：
- `plan_start_date` 强制取合同 `sign_date`
- `contract_price` 强制取合同 `total_price`
- 即便推送体带了这两个值，也会在 operation 中被覆盖。
- 同时仍有严格校验：计划节点必须晚于开始时间、早于结束时间、数量递增等；不满足直接 400。
- 这正对应日志里的 8 条失败（计划节点时间校验）与大量更新后不一致（字段被后端覆盖到“合同口径”）。
### 4) list 回读与单条回读口径不一致（会放大不一致）
- 多个类型的 `get_by_id` 会裁掉 `plan_node` 首尾节点，但 `get_list_by_project_id` 通常返回主表原始节点（含首尾）。
- 同步系统做 post-check 用的是 list 拉取结果时，这种“单条/列表口径不一致”会放大 plan_node 相关差异。
### 5) status/complete_rate/delay_days 等字段为何容易残留差异
- 这些字段主要由明细驱动的主表同步逻辑计算并回写，不是 plan/base update 的直接输入字段。
- 因此“推送成功”并不等价于“这些派生字段立即与源数据一致”。
## 建议（仍不改代码）
1. **先按后端口径预处理结算计划数据**
- 以合同 `sign_date/total_price` 作为 settlement 比对基准和推送基准；
- 推送前先做节点时间边界校验，避免 400。
2. **对 plan_node 建立统一比较口径**
- 在 post-check 里对 construction/material/settlement 统一做“边界节点归一化 + `is_audit` 口径归一化”后再比较。
3. **区分“业务真差异”与“后端派生差异”**
- 对 `status/complete_rate/delay_days/actual_*` 这类派生字段设为可选比对或延迟比对。
4. **company 名称字段先做映射可用性核查**
- 重点核对 `province/city` 编码是否在后端行政区字典可解析、`parent_id` 是否可命中公司映射。
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{"_id": "a1d69bf1-b95e-4832-9258-5bc35c629e9a", "_rev": "2-e265a6cb3674c71d6957883177b270cb", "type": "company", "name": "金上公司", "short_name": "金上公司", "code": "028B", "company_type": "region", "parent_id": "5da30aa7-b560-416e-9223-284290692351", "path": ["5da30aa7-b560-416e-9223-284290692351", "a1d69bf1-b95e-4832-9258-5bc35c629e9a"], "path_name": ["集团公司", "金上公司"], "province": "510000", "city": "510100", "status": "active", "sort": 27, "created_by": "system", "created_by_name": "system", "created_at": "2025-05-30 09:00:09", "updated_by": "system", "updated_by_name": "system", "updated_at": "2025-09-25 20:08:42", "company_nature": ["owner"], "id": "a1d69bf1-b95e-4832-9258-5bc35c629e9a", "credit_code": null, "city_name": "成都市", "province_name": "四川省", "parent_name": "集团公司"}
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filtered_datasource/datasource/filtered/units_1.jsonl
+12
View File
@@ -0,0 +1,12 @@
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pyproject.toml
+41
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[project]
name = "ecm-sync-system"
version = "0.1.0"
description = "ECM sync state machine and pipeline"
readme = "README.md"
requires-python = ">=3.9"
dependencies = [
"pydantic>=2.7,<3",
"email-validator>=2.2,<3",
"PyYAML>=6.0,<7",
"httpx>=0.27,<1",
"aiosqlite>=0.20,<1",
"pytz>=2024.1,<2027",
"fastapi>=0.115,<1",
"uvicorn>=0.30,<1",
]
[project.scripts]
ecm-sync-run = "sync_state_machine.cli:main"
[dependency-groups]
dev = [
"pytest>=8.2,<9",
"pytest-asyncio>=0.23,<1",
]
[build-system]
requires = ["setuptools>=69", "wheel"]
build-backend = "setuptools.build_meta"
[tool.setuptools]
include-package-data = true
[tool.setuptools.packages.find]
include = ["sync_state_machine*"]
[tool.setuptools.package-data]
sync_state_machine = ["config/*.yaml"]
[tool.uv]
package = true
pytest.ini
+13
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@@ -0,0 +1,13 @@
[pytest]
testpaths = tests
# 忽略第三方库的弃用警告
filterwarnings =
ignore::PendingDeprecationWarning:starlette.*
# Python 3.14: pytest-asyncio 0.26.0 内部使用已弃用的 asyncio API
# 上游 issue: https://github.com/pytest-dev/pytest-asyncio/issues/706
# 待 pytest-asyncio 修复后可移除以下两条过滤
ignore:'asyncio.get_event_loop_policy' is deprecated and slated for removal in Python 3.16:DeprecationWarning:pytest_asyncio\.plugin
ignore:'asyncio.set_event_loop_policy' is deprecated and slated for removal in Python 3.16:DeprecationWarning:pytest_asyncio\.plugin
# 也可以设置异步测试的默认 loop scope
asyncio_default_fixture_loop_scope = function
addopts = --ignore=scripts/test_api_sync.py --ignore=scripts/test_api_sync_top10.py --ignore=scripts/test_api_write_real_sample.py
run.py
+64
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@@ -0,0 +1,64 @@
from __future__ import annotations
import argparse
import asyncio
import logging
import sys
from pathlib import Path
PROJECT_ROOT = Path(__file__).resolve().parent
if str(PROJECT_ROOT) not in sys.path:
sys.path.insert(0, str(PROJECT_ROOT))
from sync_state_machine.config import load_overrides_from_file
from sync_state_machine.pipeline import build_config, run_pipeline_from_config
def _resolve_config_path(raw_path: str) -> Path:
path = Path(raw_path)
if not path.is_absolute():
path = PROJECT_ROOT / path
return path.resolve()
async def _main() -> int:
parser = argparse.ArgumentParser(description="Run sync pipeline from config override file")
parser.add_argument(
"--config_path",
required=True,
help="Path to run profile file (JSON/YAML, supports relative path, e.g. run_profiles/jsonl_to_jsonl.local.json)",
)
args = parser.parse_args()
cfg_path = _resolve_config_path(args.config_path)
if not cfg_path.exists() or not cfg_path.is_file():
raise FileNotFoundError(f"Config file not found: {cfg_path}")
overrides = load_overrides_from_file(cfg_path, PROJECT_ROOT)
config = build_config(project_root=PROJECT_ROOT, overrides=overrides)
mode = f"{config.local_datasource.type}->{config.remote_datasource.type}"
print(f"🧩 Loaded config file: {cfg_path}")
await run_pipeline_from_config(
config,
title=f"sync_state_machine pipeline ({mode})",
print_summary=True,
)
return 0
def main() -> int:
try:
return asyncio.run(_main())
except KeyboardInterrupt:
print("\n⚠️ Interrupted by user")
return 130
except Exception as exc:
print(f"\n❌ Pipeline failed: {type(exc).__name__}: {exc}")
return 1
finally:
logging.shutdown()
if __name__ == "__main__":
raise SystemExit(main())
run_profiles/README.md
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# Run Profiles
- 路径：项目根目录 `run_profiles/`
- 命名：建议使用 `*.local.yaml`（该目录下 YAML 默认会被 git 忽略）
模板来源：
- `run_profiles/preset/jsonl_to_jsonl.default.yaml`
- `run_profiles/preset/jsonl_to_api.default.yaml`
推荐流程：
1. 从模板复制到本目录，例如：
- `run_profiles/jsonl_to_jsonl.local.yaml`
- `run_profiles/jsonl_to_api.local.yaml`
2. 按需修改后运行：
- `python run.py --config_path=run_profiles/jsonl_to_jsonl.local.yaml`
支持占位符：
- `${PROJECT_ROOT}`：运行时替换为项目根目录绝对路径。
run_profiles/preset/README.md
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# Preset Templates
该目录存放版本管理的运行配置模板（default）。
当前模板：
- `jsonl_to_jsonl.default.yaml`
- `jsonl_to_api.default.yaml`
使用方式：
1. 复制模板到项目根目录 `run_profiles/`，并重命名为你自己的文件（如 `*.local.yaml`）。
2. 修改后通过入口运行：
- `python run.py --config_path=run_profiles/jsonl_to_jsonl.local.yaml`
说明：
- `run_profiles/*.yaml` / `run_profiles/*.yml` 默认被 `.gitignore` 忽略，用于本地私有配置。
- 模板内可使用 `${PROJECT_ROOT}` 占位符。
- 模板已显式展开 datasource 与 strategies 关键字段，便于集中审查。
- API 数据源支持全局限流配置：`api_rate_limit_max_requests` 与 `api_rate_limit_window_seconds`。
run_profiles/preset/jsonl_to_api.default.yaml
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node_types:
- company
- supplier
- project
- contract
- contract_change
- construction_task
- construction_task_detail
- material
- material_detail
- contract_settlement
- contract_settlement_detail
- personnel
- personnel_detail
- preparation
- production
- lar
- lar_change
- project_detail_data
- units
local_datasource:
type: jsonl
jsonl_dir: ${PROJECT_ROOT}/filtered_datasource/datasource/filtered
read_only: false
target_project_ids:
- "0f9c3e22-f4bb-4803-825a-4f238eeb06d5"
- "f3e02e84-e81c-4aa6-88d4-f5aa108c8227"
handler_configs: {}
remote_datasource:
type: api
api_base_url: http://localhost:8000/api/third/v2
api_uid: 6b18c681-92d5-4c7f-802c-df413b6504c8
api_secret: jTk5gSHTqDIZng1zh2z6jrT8JjVgCKsmV8_7NyESbQk
api_debug: true
api_rate_limit_max_requests: 30
api_rate_limit_window_seconds: 10.0
poll_max_retries: 1
poll_interval: 0.5
target_project_ids:
# 请替换为实际的项目ID，至少需要一个
- "0f9c3e22-f4bb-4803-825a-4f238eeb06d5"
- "f3e02e84-e81c-4aa6-88d4-f5aa108c8227"
handler_configs:
supplier: {}
persist:
backend: sqlite
db_path: ${PROJECT_ROOT}/test_results/sync_state_machine/simple_pipeline_sm.db
enable: true
wipe_on_start: false
logging:
initialize: true
file_dir: ${PROJECT_ROOT}/test_results/sync_state_machine
file_name_pattern: simple_pipeline_sm_{timestamp}.log
level: 20
strategies:
company:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- credit_code
depend_fields: {}
local_orphan_action: none
remote_orphan_action: create_local
update_direction: pull
supplier:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- credit_code
depend_fields: {}
local_orphan_action: none
remote_orphan_action: create_local
update_direction: pull
project:
skip_sync: false
config:
auto_bind: false
auto_bind_fields: []
pre_bind_data_id: []
depend_fields:
company_id: company
local_orphan_action: none
remote_orphan_action: none
update_direction: push
contract:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- company_id
- code
depend_fields:
project_id: project
company_id: supplier
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
contract_change:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- contract_id
- change_time
- title
depend_fields:
project_id: project
contract_id: contract
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
construction_task:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- contract_id
- task_type
depend_fields:
contract_id: contract
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
construction_task_detail:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- parent_id
- date
depend_fields:
parent_id: construction_task
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
material:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- contract_id
- material_type
depend_fields:
contract_id: contract
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
material_detail:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- parent_id
- date
depend_fields:
parent_id: material
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
contract_settlement:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- contract_id
depend_fields:
contract_id: contract
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
contract_settlement_detail:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- parent_id
- date
depend_fields:
parent_id: contract_settlement
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
personnel:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- code
depend_fields:
project_id: project
contract_id: contract
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
personnel_detail:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- parent_id
- date
depend_fields:
parent_id: personnel
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
preparation:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- code
depend_fields:
project_id: project
local_orphan_action: none
remote_orphan_action: none
update_direction: push
production:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- code
depend_fields:
project_id: project
local_orphan_action: none
remote_orphan_action: none
update_direction: push
lar:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
depend_fields:
project_id: project
local_orphan_action: none
remote_orphan_action: none
update_direction: push
lar_change:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- change_time
- title
depend_fields:
project_id: project
local_orphan_action: none
remote_orphan_action: none
update_direction: push
project_detail_data:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- key
depend_fields:
project_id: project
local_orphan_action: none
remote_orphan_action: none
update_direction: push # 未在 field_direction_overrides 中列出的 key 默认 push
field_direction_key: key # 以节点 data.key 字段值作为方向查表键
field_direction_overrides:
ensure_production: pull # 远程 → 本地
climb_production: pull # 远程 → 本地
challenge_production: pull # 远程 → 本地
units:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- serial_number
depend_fields:
project_id: project
local_orphan_action: none
remote_orphan_action: none
update_direction: push
run_profiles/preset/jsonl_to_jsonl.default.yaml
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node_types:
- company
- user
- supplier
- project
- contract
- contract_change
- construction_task
- construction_task_detail
- material
- material_detail
- contract_settlement
- contract_settlement_detail
- personnel
- personnel_detail
- preparation
- production
- lar
- lar_change
- project_detail_data
- units
local_datasource:
type: jsonl
jsonl_dir: ${PROJECT_ROOT}/filtered_datasource/datasource/filtered
read_only: false
target_project_ids: []
handler_configs: {}
remote_datasource:
type: jsonl
jsonl_dir: ${PROJECT_ROOT}/remote_datasource/datasource
read_only: false
target_project_ids: []
handler_configs: {}
persist:
backend: sqlite
db_path: ${PROJECT_ROOT}/test_results/sync_state_machine/full_sync_pipeline_jsonl_sm.db
enable: true
wipe_on_start: false
logging:
initialize: true
file_dir: ${PROJECT_ROOT}/test_results/sync_state_machine
file_name_pattern: jsonl_pipeline_sm_{timestamp}.log
level: 20
strategies:
company:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- credit_code
depend_fields: {}
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
user:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- username
depend_fields: {}
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
supplier:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- credit_code
depend_fields: {}
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
project:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- name
depend_fields:
company_id: company
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
contract:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- company_id
- code
depend_fields:
project_id: project
company_id: supplier
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
contract_change:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- contract_id
- change_time
- title
depend_fields:
project_id: project
contract_id: contract
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
construction_task:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- contract_id
- task_type
depend_fields:
contract_id: contract
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
construction_task_detail:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- parent_id
- date
depend_fields:
parent_id: construction_task
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
material:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- contract_id
- material_type
depend_fields:
contract_id: contract
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
material_detail:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- parent_id
- date
depend_fields:
parent_id: material
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
contract_settlement:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- contract_id
depend_fields:
contract_id: contract
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
contract_settlement_detail:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- parent_id
- date
depend_fields:
parent_id: contract_settlement
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
personnel:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- code
depend_fields:
project_id: project
contract_id: contract
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
personnel_detail:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- parent_id
- date
depend_fields:
parent_id: personnel
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
preparation:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- code
depend_fields:
project_id: project
local_orphan_action: none
remote_orphan_action: none
update_direction: push
production:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- code
depend_fields:
project_id: project
local_orphan_action: none
remote_orphan_action: none
update_direction: push
lar:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
depend_fields:
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
lar_change:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- change_time
- title
depend_fields:
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
project_detail_data:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- key
depend_fields:
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
units:
skip_sync: false
config:
auto_bind: true
auto_bind_fields:
- project_id
- serial_number
depend_fields:
project_id: project
local_orphan_action: create_remote
remote_orphan_action: none
update_direction: push
schemas/common/base.py
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from pydantic import BaseModel, Field, ValidationError, model_validator
from typing import Any, Dict
from typing import Any, Optional, TypeVar, Generic, List
from pydantic import BaseModel, Field, model_serializer
class BaseResponseWithID(BaseModel):
"""
Mixin: 统一处理输入中的 id/_id -> id
约束：
- 若 id 与 _id 同时出现且值不同 -> 报错
- 若仅 _id 出现 -> 转成 id
- 若两者都缺失 -> 报错
- 最终保证存在 id: str
"""
id: str = Field(..., description="资源唯一标识ID")
@model_validator(mode="before")
@classmethod
def normalize_id(cls, data: Any) -> Any:
# 仅处理 dict-like 输入；其他情况交给 Pydantic 默认流程
if not isinstance(data, dict):
return data
has_id = "id" in data
has__id = "_id" in data
if has_id and has__id:
if str(data["id"]) != str(data["_id"]):
raise ValidationError([
{
"type": "value_error",
"loc": ("id",),
"msg": "id and _id both provided but not equal",
"input": data.get("id"),
}
], cls)
# 相同则优先保留 id，去掉 _id
data = {**data}
data.pop("_id", None)
return data
if has__id and not has_id:
# 将 _id 统一映射为 id
data = {**data}
data["id"] = str(data["_id"])
data.pop("_id", None)
return data
if not has_id and not has__id:
raise ValidationError([
{
"type": "value_error.missing",
"loc": ("id",),
"msg": "id or _id is required",
"input": data,
}
], cls)
# 默认返回（已有 id）
return data
class RequestApprovalMixin(BaseModel):
"""
请求审批相关的基础模型
"""
pass
T = TypeVar("T")
# def _build_full_response_dict(code: int, message: Optional[str], data: Any) -> dict:
# """构建与 __orjson__ 完全一致的响应字典"""
# # 处理 data 的序列化（与 __orjson__ 逻辑同步）
# if data is None:
# clean_data = {}
# elif isinstance(data, BaseModel):
# clean_data = data.model_dump()
# else:
# clean_data = data
# return {
# "code": code,
# "message": message,
# "data": clean_data
# }
class Success(BaseModel, Generic[T]):
code: int = 200
message: Optional[str] = "OK"
data: Optional[T] = None
# def __init__(self, **kwargs):
# super().__init__(**kwargs)
# # 自动捕获完整响应结构到 push_log.result
# push_log = current_push_log.get()
# if push_log is not None:
# full_response = _build_full_response_dict(self.code, self.message, self.data)
# push_log.result = full_response
#
class Fail(BaseModel):
code: int = 400
message: Optional[str] = None
data: Optional[Any] = Field(default_factory=dict)
class PaginatedList(BaseModel, Generic[T]):
list: List[T] = Field(default_factory=list)
total: int = 0
page: int = 1
page_size: int = 20
schemas/common/datetime.py
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from datetime import datetime, date
import pytz
def get_current_date(date_formate='%Y-%m-%d'):
"""
获取当前日期字符串，格式化为指定格式，默认格式为'YYYY-MM-DD'
"""
tz = pytz.timezone('Asia/Shanghai') # 设置为中国时区
current_date = datetime.now(tz)
return current_date.strftime(date_formate)
def datetime_date(date: str) -> date:
return datetime.strptime(date, "%Y-%m-%d").date()
schemas/common/enums.py
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from enum import Enum
class ApprovalStatus(str, Enum):
REGISTERED = "registered"
UNDER_REVIEW = "under_review"
APPROVED = "approved"
REJECTED = "rejected"
PENDING_CONFIRM = "pending_confirm"
CONFIRMED = "confirmed"
schemas/common/push_system.py
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"""
推送接口通用schema
## 响应相关
1. BaseResponseSchema: 所有接口响应的基础schema
2. BasePushResponseSchema: 推送接口响应的基础schema，包含push_id
3. PushResultSchema: 查询推送结果的schema
## 请求相关
4. BaseCreateRequestSchema[T]: 创建资源的基础请求schema（泛型），业务数据在data字段
5. BaseUpdateRequestSchema[T]: 更新资源的基础请求schema（泛型），业务数据在data字段
6. BaseDeleteRequestSchema: 删除资源的基础请求schema，只需resource_id
7. BulkPushRequestSchema: 批量推送请求的schema
## 说明
- 所有元数据字段（timestamp, nonce, signature, uid, push_id）在请求体最外层
- push_id使用UUIDv7格式，支持时间排序，同时作为幂等键和查询键
- 业务数据嵌套在data字段中（删除操作除外，只需resource_id）
- 所有业务Schema必须继承BasePushData，确保包含project_type字段
- resource_id在外层，用于标识要操作的资源（更新/删除时必填）
- 使用泛型T可快速定义各业务的请求schema，T必须继承BasePushData
"""
from pydantic import BaseModel, Field
from typing import TypeVar, Generic, Optional, List, Dict, Any
from ..project.enums import ProjectType
# 定义泛型
T = TypeVar('T', bound='BasePushData')
# ==================== 业务数据基类 ====================
class BasePushData(BaseModel):
"""
所有推送业务数据的基类
所有业务Schema必须继承此类，确保包含project_type字段
"""
project_type: ProjectType = Field(..., description="项目类型：offshore_wind/pumped_storage/photovoltaic等")
# ==================== Mixin ====================
class SignatureMixin(BaseModel):
"""签名字段混入"""
timestamp: int = Field(..., description="毫秒级 Unix 时间戳")
nonce: str = Field(..., description="随机字符串，防止重放攻击")
sign: str = Field(..., description="签名字符串")
uid: str = Field(..., description="集团侧用户id")
class PushRequestMixin(BaseModel):
"""推送ID字段混入"""
push_id: str = Field(..., description="推送ID，客户端生成的唯一标识（UUIDv7，支持时间排序）")
# ==================== 响应相关 ====================
class BaseResponseSchema(BaseModel):
"""所有接口响应的基础schema"""
code: int = 200
message: Optional[str] = "OK"
data: Optional[T] = None
class BasePushResponseSchema(BaseModel):
"""推送接口响应的基础schema"""
biz_id: str | None = Field(None, description="资源ID（create操作成功后返回新创建的ID，update/delete返回原ID）")
class PushResultSchema(BaseModel):
"""查询推送结果的schema"""
push_id: str = Field(..., description="推送ID（客户端生成的UUIDv7）")
status: str = Field(..., description="推送状态：queued/processing/success/failed")
result: Dict[str, Any] | None = Field(None, description="处理结果（成功时包含created_id等信息）")
error: str | None = Field(None, description="错误信息（失败时）")
created_at: str = Field(..., description="推送创建时间（ISO 8601格式）")
updated_at: str = Field(..., description="推送更新时间（ISO 8601格式）")
class PushIdsSchema(BaseModel):
"""支持从请求体接收的 push_ids 列表字符串（逗号拼接）"""
push_ids: Optional[str] = Field(None, description="推送id字符串逗号拼接")
# ==================== 请求相关 ====================
class BaseCreateRequestSchema(SignatureMixin, PushRequestMixin, BaseModel, Generic[T]):
"""
创建资源的基础请求schema（泛型）
泛型T必须继承BasePushData，确保包含project_type字段
使用示例:
class ProjectInputSchema(BasePushData):
name: str = Field(...)
capacity: float = Field(...)
class ProjectCreateRequest(BaseCreateRequestSchema[ProjectInputSchema]):
pass
"""
# 业务数据（嵌套）
data: T = Field(..., description="业务数据")
class BaseUpdateRequestSchema(SignatureMixin, PushRequestMixin, BaseModel, Generic[T]):
"""
更新资源的基础请求schema（泛型）
泛型T必须继承BasePushData，确保包含project_type字段
resource_id在外层，用于标识要更新的资源
使用示例:
class ProjectInputSchema(BasePushData):
name: str = Field(...)
capacity: float = Field(...)
class ProjectUpdateRequest(BaseUpdateRequestSchema[ProjectInputSchema]):
pass
"""
# 资源标识
biz_id: str = Field(..., description="要更新的资源ID,类型id,如project传project_id,unit传unit_id")
# 业务数据（嵌套）
data: T = Field(..., description="业务数据（只需包含要更新的字段）")
class BaseDeleteRequestSchema(SignatureMixin, PushRequestMixin, BaseModel):
"""
删除资源的基础请求schema
使用示例:
class ProjectDeleteRequest(BaseDeleteRequestSchema):
pass
"""
# 资源标识
biz_id: str = Field(..., description="要删除的资源ID")
class BulkPushItem(PushRequestMixin, BaseModel):
"""
批量推送中的单个项目
注意：
- action为create时：data必填，resource_id留空
- action为update时：data和resource_id都必填
- action为delete时：resource_id必填，data留空
- data必须继承BasePushData，确保包含project_type字段
"""
action: str = Field(..., description="操作类型：create/update/delete")
resource_id: str | None = Field(None, description="资源ID（update/delete时必填，create时留空）")
data: BasePushData | None = Field(None, description="业务数据（create/update时必填，delete时留空，必须包含project_type字段）")
class BulkPushItemResult(BaseModel):
"""批量推送中单个项目的处理结果"""
push_id: str = Field(..., description="推送ID（对应请求中的push_id）")
status: str = Field(..., description="处理状态：queued/processing/success/failed")
resource_id: str | None = Field(None, description="资源ID（create成功时返回新ID，update/delete返回原ID）")
error: str | None = Field(None, description="错误信息（失败时）")
class BulkPushRequestSchema(SignatureMixin, BaseModel):
"""
批量推送请求的schema
一次请求可推送多条数据，每条都有独立的幂等键和操作类型
"""
# 批量数据
items: List[BulkPushItem] = Field(..., description="批量推送的数据列表")
class BulkPushResponseSchema(BaseResponseSchema):
"""批量推送响应的schema"""
batch_id: str = Field(..., description="批量推送的批次ID")
total: int = Field(..., description="总数量")
results: List[BulkPushItemResult] = Field(..., description="每条数据的处理结果，包含push_id和resource_id")
schemas/common/validators.py
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from datetime import datetime
from typing import Annotated
from pydantic import AfterValidator
from functools import lru_cache
import re
# 预编译正则表达式，避免重复编译
DATE_PATTERN = re.compile(r'^\d{4}-\d{2}-\d{2}$')
TIMESTAMP_PATTERNS = {
'iso_z': re.compile(r'^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\.\d+Z$'),
'iso_offset': re.compile(r'^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\.\d+\+00:00$'),
'simple_space': re.compile(r'^\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}$'),
'simple_t': re.compile(r'^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}$'),
}
@lru_cache(maxsize=1024) # 缓存最近1024个不同的日期
def _validate_date_cached(v: str) -> str:
"""缓存版本的日期验证"""
# 快速格式检查（避免无效字符串进入 strptime）
if not DATE_PATTERN.match(v):
raise ValueError(f"日期格式应为 YYYY-MM-DD，实际为: {v}")
# 验证日期有效性（例如排除 2023-02-30）
datetime.strptime(v, "%Y-%m-%d")
return v
def validate_date(v: str) -> str:
"""校验日期格式为 YYYY-MM-DD"""
if v is None or v == "":
return v
return _validate_date_cached(v)
@lru_cache(maxsize=2048) # 时间戳变化更多，给更大的缓存
def _validate_timestamp_cached(v: str) -> str:
"""缓存版本的时间戳验证"""
# 按常见程度排序，优先检查最可能的格式
if TIMESTAMP_PATTERNS['iso_z'].match(v):
datetime.strptime(v, "%Y-%m-%dT%H:%M:%S.%fZ")
elif TIMESTAMP_PATTERNS['simple_space'].match(v):
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
elif TIMESTAMP_PATTERNS['simple_t'].match(v):
datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
elif TIMESTAMP_PATTERNS['iso_offset'].match(v):
datetime.strptime(v, "%Y-%m-%dT%H:%M:%S.%f+00:00")
else:
# 兜底逻辑：如果正则都不匹配，尝试原来的逻辑
try:
if v.endswith('Z'):
datetime.strptime(v, "%Y-%m-%dT%H:%M:%S.%fZ")
elif v.endswith('+00:00'):
datetime.strptime(v, "%Y-%m-%dT%H:%M:%S.%f+00:00")
else:
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
except ValueError:
raise ValueError("时间戳格式应为 YYYY-MM-DDTHH:MM:SS.sssZ、+00:00、YYYY-MM-DD HH:MM:SS 或 YYYY-MM-DDTHH:MM:SS")
return v
def validate_timestamp(v: str) -> str:
"""校验时间戳格式"""
if v is None or v == "":
return v
return _validate_timestamp_cached(v)
# 定义新类型
DateStr = Annotated[str, AfterValidator(validate_date)]
TimestampStr = Annotated[str, AfterValidator(validate_timestamp)]
# 可选：提供缓存统计功能用于调试
def get_cache_stats():
"""获取缓存统计信息，用于性能调试"""
return {
'date_cache': _validate_date_cached.cache_info(),
'timestamp_cache': _validate_timestamp_cached.cache_info(),
}
def clear_validation_cache():
"""清空验证缓存（用于测试或内存清理）"""
_validate_date_cached.cache_clear()
_validate_timestamp_cached.cache_clear()
schemas/company/company.py
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from pydantic import BaseModel, Field, field_validator
from typing import List, Optional, Literal
from ..common.base import BaseResponseWithID
class CompanyResponse(BaseResponseWithID):
code: str = Field(..., description="公司编码")
company_type: str = Field(..., description="公司类型")
name: str = Field(..., description="公司名称")
short_name: str = Field(..., description="公司简称")
parent_id: Optional[str] = Field(None, description="父公司ID")
path: List[str] = Field(default_factory=list, description="公司路径 [..., 上级id, 本身id]")
path_name: List[str] = Field(default_factory=list, description="公司路径名称 [..., 上级名称, 本身名称]")
province: Optional[str] = Field(None, description="省份编码") # 存省份编码
city: Optional[str] = Field(None, description="城市编码") # 存城市编码
sort: int = Field(0, description="排序")
status: str = Field("", description="公司状态")
company_nature: Optional[list] = Field(..., description="公司性质")
credit_code: Optional[str] = Field(None, description="信用代码", examples=["914403007109310121"])
city_name: Optional[str] = Field(None, description="城市名称", examples=[None])
province_name: Optional[str] = Field(None, description="省份名称", examples=[None])
parent_name: Optional[str] = Field(None, description="父级公司名称", examples=[None])
@field_validator(
"path",
"path_name",
mode="before"
)
def formate_null_to_list(cls, field_value):
if field_value is None:
return []
return field_value
class CompanyListResponse(BaseModel):
page: int
page_size: int
total: int
list: List[CompanyResponse] = []
schemas/construction/construction.py
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from pydantic import BaseModel, Field, field_validator, model_validator
from fastapi import HTTPException
from typing import List, Optional, Literal
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
class PlanNode(BaseModel):
date: DateStr = Field(..., description="计划节点时间", examples=["2024-01-01"])
quantity: float = Field(..., description="计划完成量", examples=[100.0])
is_audit: Optional[bool] = Field(False, description="是否已审核", examples=[False])
@field_validator("quantity")
def validate_price(cls, v):
"""验证金额必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='计划完成量不能小于等于0')
return v
class ConstructionResponse(BaseResponseWithID):
"""
施工任务模型，存储在CouchDB中的施工任务文档
"""
id : str = Field(..., description="施工任务ID")
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
contract_id: Optional[str] = Field(None, description="所属合同ID", examples=["contract456"])
show_name: str = Field(..., description="展示名称", examples=["桩基础施工任务"])
construction_section: str = Field(..., description="施工区域", examples=["GF"])
status: Optional[int] = Field(None, description="施工状态", examples=[0])
task_type: str = Field(..., description="施工任务类型", examples=["zjcsgg"])
plan_start_date: Optional[DateStr] = Field(None, description="计划开工时间", examples=["2024-01-01"])
plan_complete_date: Optional[DateStr] = Field(None, description="计划完工时间", examples=["2024-06-01"])
actual_complete_date: Optional[DateStr] = Field(None, description="实际完工时间", examples=["2024-05-30"])
complete_quantity: float = Field(0.0, description="实际完成量累计", examples=[0.0])
complete_rate: float = Field(0.0, description="实际完成率(%)", examples=[0.0])
contract_quantity: Optional[float] = Field(None, description="设计量", examples=[1000.0])
plan_node: List[PlanNode] = Field(default_factory=list, description="计划节点列表")
statistic_date: Optional[DateStr] = Field(None, description="统计节点时间", examples=["2024-05-31"])
# sort: int = Field(0, description="排序字段", examples=[0])
is_crucial:Optional[bool] = Field(False, description="是否为关键线路")
# 2025-10-20新增字段，延迟时间
delay_days: Optional[int] = Field(None, description="延迟时间（天）", examples=[0])
class ConstructionCreate(BaseModel):
"""
施工任务创建模型
不对应operation
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
contract_id: Optional[str] = Field(None, description="所属合同ID", examples=["contract456"])
show_name: str = Field(..., description="展示名称", examples=["桩基础施工任务"])
construction_section: str = Field(..., description="施工区域", examples=["GF"])
task_type: str = Field(..., description="施工任务类型", examples=["zjcsgg"])
is_crucial:Optional[bool] = Field(False, description="是否为关键线路")
class ConstructionUpdate(BaseModel):
"""
施工任务更新模型
CONSTRUCTION_BASE_INFO = "construction.base_info"
"""
id: str = Field(..., description="施工任务ID")
contract_id: Optional[str] = Field(None, description="所属合同ID", examples=["contract456"])
show_name: str | None = Field(None, description="展示名称（仅QT类施工可以修改名称）", examples=["桩基础施工任务"])
is_crucial:bool | None = Field(False, description="是否为关键线路")
class ConstructionPlanUpdate(BaseModel):
"""
施工计划更新模型
对应 CONSTRUCTION_PLAN = "construction.plan"
业务逻辑说明：
- API要求计划节点时间必须晚于计划开工日期（不能等于）
- 自动清理脏数据：如果 plan_node 有2个或以上节点，删除：
1. 开头节点：如果其 date 等于 plan_start_date
2. 结尾节点：如果其 date 等于 plan_complete_date
- 这样避免提交包含边界节点的数据导致API报错
"""
id: str = Field(..., description="施工任务ID")
plan_start_date: Optional[str] = Field(None, description="计划开工时间", examples=["2024-01-01"])
plan_complete_date: Optional[str] = Field(None, description="计划完工时间", examples=["2024-01-01"])
contract_quantity: float = Field(..., description="设计量")
plan_node: Optional[List[PlanNode]] = Field(default_factory=list, description="计划节点列表")
@field_validator("contract_quantity")
def validate_price(cls, v):
"""验证金额必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='设计量不能小于0')
return v
@model_validator(mode='after')
def clean_plan_nodes(self):
"""
清理计划节点列表中的边界节点
如果 plan_node 有2个或以上节点，删除：
- 开头节点：date 等于 plan_start_date
- 结尾节点：date 等于 plan_complete_date
这避免了API报错"计划节点时间必须晚于计划开工日期"
"""
if not self.plan_node or len(self.plan_node) < 2:
return self
cleaned_nodes = list(self.plan_node)
# 删除开头的边界节点
if (self.plan_start_date and
cleaned_nodes and
cleaned_nodes[0].date == self.plan_start_date):
cleaned_nodes.pop(0)
# 删除结尾的边界节点
if (self.plan_complete_date and
cleaned_nodes and
cleaned_nodes[-1].date == self.plan_complete_date):
cleaned_nodes.pop()
self.plan_node = cleaned_nodes
return self
schemas/construction/construction_detail.py
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from pydantic import BaseModel, Field,field_validator
from ..common.datetime import get_current_date
from fastapi import HTTPException
from typing import List, Optional, Literal
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
from ..common.enums import ApprovalStatus
from datetime import datetime
class ConstructionDetailResponse(BaseResponseWithID):
"""
物资明细返回值
"""
id: str = Field(..., description="施工任务明细ID")
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
parent_id: str = Field(..., description="所属施工任务ID", examples=["task789"])
rate: Optional[float] = Field(None, description="实际完成率", examples=[0.0])
quantity: float = Field(0.0, ge=0, description="实际完成量累计", examples=[0.0])
date: DateStr = Field(..., description="节点日期", examples=["2024-05-31"])
status: Optional[int] = Field(None, description="进度状态", examples=[0])
change_count: int = Field(0, description="变更次数", examples=[0])
remark: Optional[str] = Field(None, description="备注")
is_complete: Optional[bool] = Field(
None, description="是否为全部完成", examples=[False]
)
class ConstructionDetailCreate(BaseModel):
"""
施工明细创建模型
CONSTRUCTION_DETAIL = "construction.detail"
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
parent_id: str = Field(..., description="所属施工任务ID", examples=["task789"])
quantity: float = Field(0.0, ge=0, description="实际完成量累计", examples=[0.0])
date: DateStr = Field(..., description="节点日期", examples=["2024-05-31"])
remark: Optional[str] = Field(None, description="备注")
is_complete: Optional[bool] = Field(
False, description="是否为全部完成", examples=[False]
)
confirmation_time: str | None = Field(None, description="确认时间", examples=["2025-12-17 11:13:49"])
approval_time: str | None = Field(None, description="审批时间", examples=["2025-12-17 11:13:49"])
approval_status: ApprovalStatus = Field("registered", description="审批状态", examples=["registered"])
@field_validator("approval_status")
def validate_approval_status(cls, v):
"""验证审批字段"""
try:
return ApprovalStatus(v) # 尝试转换
except ValueError:
raise HTTPException(400, f"审批状态 '{v}' 无效")
@field_validator("confirmation_time", "approval_time")
def validate_time(cls, v):
"""验证时间"""
if v is None:
return v
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
raise HTTPException(detail=f'{v}时间格式错误，应为：2025-12-17 11:13:49', status_code=400)
return v
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='实际完成量累计不能小于0')
return v
@field_validator("date")
def validate_date(cls, v):
if v > get_current_date():
raise HTTPException(detail='节点日期不能大于今天', status_code=400)
return v
class ConstructionDetailUpdate(BaseModel):
"""
施工明细更新模型
CONSTRUCTION_DETAIL = "construction.detail"
"""
id: str = Field(..., description="施工任务明细ID")
quantity: Optional[float] = Field(None, ge=0, description="实际完成量累计", examples=[0.0])
date: Optional[DateStr] = Field(None, description="节点日期", examples=["2024-05-31"])
remark: Optional[str] = Field(None, description="备注")
is_complete: Optional[bool] = Field(
None, description="是否为全部完成", examples=[False]
)
confirmation_time: str | None = Field(None, description="确认时间", examples=["2025-12-17 11:13:49"])
approval_time: str | None = Field(None, description="审批时间", examples=["2025-12-17 11:13:49"])
approval_status: ApprovalStatus | None = Field("registered", description="审批状态", examples=["registered"])
@field_validator("approval_status")
def validate_approval_status(cls, v):
"""验证审批字段"""
if v is None:
return v
try:
return ApprovalStatus(v) # 尝试转换
except ValueError:
raise HTTPException(400, f"审批状态 '{v}' 无效")
@field_validator("confirmation_time", "approval_time")
def validate_time(cls, v):
"""验证时间"""
if v is None:
return v
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
raise HTTPException(detail=f'{v}时间格式错误，应为：2025-12-17 11:13:49', status_code=400)
return v
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v is None:
return None
if v < 0:
raise HTTPException(status_code=400, detail='实际完成量累计不能小于0')
return v
@field_validator("date")
def validate_date(cls, v):
if v is None:
return None
if v > get_current_date():
raise HTTPException(detail='节点日期不能大于今天', status_code=400)
return v
class ConstructionDetailBulkUpdate(BaseModel):
detail_list: List[ConstructionDetailUpdate]
schemas/contract/contract.py
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from pydantic import BaseModel, Field,field_validator
from typing import List, Optional, Literal
from ..common.datetime import datetime_date,get_current_date
from fastapi import HTTPException
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
class ContractResponse(BaseResponseWithID):
"""
合同返回信息
"""
id : str = Field(..., description="合同ID")
project_id: str = Field("", description="所属项目ID")
name: str = Field("", description="合同名称")
short_name: str = Field("", description="合同简称")
code: str = Field("", description="合同编码")
contract_type: str = Field("", description="合同类型")
currency: str = Field("CNY", description="币种")
manager_name: str = Field("", description="负责人姓名")
manager_phone: str = Field("", description="负责人电话")
sign_company: str = Field("", description="签订公司")
company_id: str = Field("", description="签订公司id")
sign_date: DateStr = Field("", description="签订日期", examples=["2023-10-01"])
credit_code: Optional[str] = Field("", description="签订公司信用代码")
total_price: float = Field(0.0, description="合同金额")
sub_name: Optional[str] = Field(None, description="合同子标题")
class ContractCreate(BaseModel):
"""
创建合同
CONTRACT = "contract"
"""
name: str|None = Field(None, description="合同名称")
sub_name:str|None= Field(None, description="合同子标题")
code: str = Field("", description="合同编码")
contract_type: str = Field("", description="合同类型")
project_id: str = Field("", description="所属项目ID")
currency: str = Field("CNY", description="币种")
manager_name: str = Field("", description="负责人姓名")
manager_phone: str = Field("", description="负责人电话")
sign_company: str = Field("", description="签订公司")
company_id: Optional[str] = Field(None, description="签订公司id")
sign_date: DateStr = Field("", description="签订日期", examples=["2023-10-01"])
credit_code: Optional[str] = Field(None, description="签订公司信用代码")
total_price: float = Field(0.0, description="合同金额")
@field_validator("total_price")
def validate_price(cls, v):
"""验证金额必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='合同金额不能小于0')
return v
@field_validator('sign_date')
def validate_actual_date_not_future(cls, v: str) -> str:
if v == "":
return ""
try:
actual = datetime_date(v)
except ValueError:
raise HTTPException(status_code=400, detail='日期格式为(YYYY-MM-DD)')
today = datetime_date(get_current_date())
if actual > today:
raise HTTPException(status_code=400, detail='签约日期不能晚于今天')
return v
class ContractUpdate(BaseModel):
"""
更新合同
CONTRACT = "contract"
"""
id : str = Field(..., description="合同ID")
sub_name:str|None= Field(None, description="合同子标题")
currency: str|None = Field(None, description="币种")
manager_name: str|None= Field(None, description="负责人姓名")
manager_phone: str|None= Field(None, description="负责人电话")
sign_company: str|None= Field(None, description="签订公司")
company_id: Optional[str] = Field(None, description="签订公司id")
sign_date: str|None = Field(None, description="签订日期", examples=["2023-10-01"])
credit_code: Optional[str] = Field(None, description="签订公司信用代码")
total_price: float|None= Field(None, description="合同金额")
@field_validator("total_price")
def validate_price(cls, v):
"""验证金额必须为非负数"""
if v is None:
return None
if v < 0:
raise HTTPException(status_code=400, detail='合同金额不能小于0')
return v
@field_validator('sign_date')
def validate_actual_date_not_future(cls, v: str):
if v is None:
return None
if v == "":
return ""
try:
actual = datetime_date(v)
except ValueError:
raise HTTPException(status_code=400, detail='日期格式为(YYYY-MM-DD)')
today = datetime_date(get_current_date())
if actual > today:
raise HTTPException(status_code=400, detail='签约日期不能晚于今天')
return v
schemas/contract_settlement/contract_settlement.py
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from pydantic import Field, BaseModel,field_validator,model_validator
from fastapi import HTTPException
from typing import List, Optional, Literal
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
class PlanNode(BaseModel):
date: DateStr = Field(..., description="计划节点时间", examples=["2024-01-01"])
quantity: float = Field(..., description="计划完成量", examples=[100.0])
is_audit: Optional[bool] = Field(False, description="是否已审核", examples=[False])
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证计划完成量必须大于0"""
if v < 0:
raise HTTPException(status_code=400, detail='计划完成量不能小于0')
return v
class ContractSettlementResponse(BaseResponseWithID):
"""
合同结算返回
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
contract_id: str = Field(..., description="所属合同ID", examples=["contract456"])
contract_type: Optional[str] = Field(None, description="合同类型")
show_name: Optional[str] = Field(None, description="合同简称", examples=["主变采购合同"])
complete_price: float = Field(0.0, description="实际完成金额", examples=[100000.0])
contract_price: float = Field(0.0, description="合同金额", examples=[120000.0])
actual_complete_date: Optional[DateStr] = Field(None, description="实际结束时间", examples=["2024-06-30"])
actual_start_date: Optional[DateStr] = Field(None, description="实际开始时间", examples=["2024-01-01"])
plan_complete_date: Optional[DateStr] = Field(None, description="计划结束时间", examples=["2024-06-30"])
plan_start_date: Optional[DateStr] = Field(None, description="计划开始时间", examples=["2024-01-01"])
plan_node: List[PlanNode] = Field(default_factory=list, description="计划节点列表")
status: Optional[int] = Field(None,description="供货状态", examples=[0])
# 2025-10-20新增字段，延迟时间
delay_days: Optional[int] = Field(None, description="延迟时间（天）", examples=[0])
statistic_date: Optional[DateStr] = Field(
None, description="统计节点截止日期", examples=["2024-05-31"]
)
class ContractSettlementCreate(BaseModel):
"""
合同结算创建模型
CONTRACT_SETTLEMENT_BASE_INFO = "contract_settlement.base_info"
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
contract_id: str = Field(..., description="所属合同ID", examples=["contract456"])
show_name: Optional[str] = Field(None, description="合同简称", examples=["主变采购合同"])
class ContractSettlementUpdate(BaseModel):
"""
合同结算更新模型
CONTRACT_SETTLEMENT_BASE_INFO = "contract_settlement.base_info"
"""
id: str = Field(..., description="合同结算ID")
contract_id: str = Field(..., description="所属合同ID", examples=["contract456"])
show_name: Optional[str] = Field(None, description="合同简称", examples=["主变采购合同"])
class ContractSettlementPlanUpdate(BaseModel):
"""
合同结算计划节点更新模型
CONTRACT_SETTLEMENT_PLAN_NODE = "contract_settlement.plan_node"
开始时间和金额在合同中维护，这里只维护计划节点和计划结束时间
业务逻辑说明：
- API要求计划节点时间必须晚于计划开始时间（不能等于）
- 自动清理脏数据：如果 plan_node 有2个或以上节点，删除边界节点
"""
id: str = Field(..., description="合同结算ID")
plan_start_date: Optional[DateStr] = Field(None, exclude=True, description="计划开始时间（不推往后端，仅用于本地首节点清洗）", examples=["2024-06-30"])
plan_complete_date: Optional[DateStr] = Field(None, description="计划结束时间", examples=["2024-06-30"])
plan_node: List[PlanNode] = Field(default_factory=list, description="计划节点列表")
@model_validator(mode='after')
def clean_plan_nodes(self):
"""
清理计划节点列表中的边界节点
注：settlement的plan_start_date在contract中维护，此处利用外部提供的辅助字段清除非法首尾节点。
"""
if not self.plan_node or len(self.plan_node) < 2:
return self
cleaned_nodes = list(self.plan_node)
# 删除开头的边界节点
if (self.plan_start_date and
cleaned_nodes and
cleaned_nodes[0].date == self.plan_start_date):
cleaned_nodes.pop(0)
# 删除结尾的边界节点
if (self.plan_complete_date and
cleaned_nodes and
cleaned_nodes[-1].date == self.plan_complete_date):
cleaned_nodes.pop()
self.plan_node = cleaned_nodes
return self
schemas/contract_settlement/contract_settlement_detail.py
+128
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from pydantic import Field, BaseModel,field_validator
from fastapi import HTTPException
from ..common.datetime import get_current_date
from typing import List, Optional, Literal
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
from ..common.enums import ApprovalStatus
from datetime import datetime
class ContractSettlementDetailResponse(BaseResponseWithID):
"""
合同结算明细返回模型
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
parent_id: str = Field(..., description="所属合同结算ID", examples=["settlement789"])
date: DateStr = Field(..., description="结算日期", examples=["2024-05-31"])
quantity: float = Field(..., description="合同金额", examples=[0])
remark: Optional[str] = Field(None, description="填报备注", examples=[""])
is_complete: Optional[bool] = Field(None, description="是否完成", examples=[False])
write_off_rate: Optional[float] = Field(None, description="核销率", examples=[0.0])
change_count: int = Field(0, description="变更次数", examples=[0])
status: Optional[int] = Field(None, description="进度状态", examples=[0])
rate: Optional[float] = Field(None, description="实际完成率", examples=[0.0])
class ContractSettlementDetailCreate(BaseModel):
"""
合同结算明细创建模型
CONTRACT_SETTLEMENT_DETAIL = "contract_settlement.detail"
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
parent_id: str = Field(..., description="所属合同结算ID", examples=["settlement789"])
date: DateStr = Field(..., description="结算日期", examples=["2024-05-31"])
quantity: float = Field(..., description="合同金额", examples=[0])
remark: Optional[str] = Field(None, description="填报备注", examples=[""])
is_complete: bool = Field(False, description="是否完成", examples=[False])
write_off_rate: Optional[float] = Field(None, description="核销率", examples=[0.0])
confirmation_time: str | None = Field(None, description="确认时间", examples=["2025-12-17 11:13:49"])
approval_time: str | None = Field(None, description="审批时间", examples=["2025-12-17 11:13:49"])
approval_status: ApprovalStatus = Field("registered", description="审批状态", examples=["registered"])
@field_validator("approval_status")
def validate_approval_status(cls, v):
"""验证审批字段"""
try:
return ApprovalStatus(v) # 尝试转换
except ValueError:
raise HTTPException(400, f"审批状态 '{v}' 无效")
@field_validator("confirmation_time", "approval_time")
def validate_time(cls, v):
"""验证时间"""
if v is None:
return v
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
raise HTTPException(detail=f'{v}时间格式错误，应为：2025-12-17 11:13:49', status_code=400)
return v
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='合同金额不能小于0')
return v
@field_validator("date")
def validate_date(cls, v):
if v > get_current_date():
raise HTTPException(detail='结算日期不能大于今天', status_code=400)
return v
class ContractSettlementDetailUpdate(BaseModel):
"""
合同结算明细更新模型
CONTRACT_SETTLEMENT_DETAIL = "contract_settlement.detail"
"""
id: str = Field(..., description="合同明细ID")
date: DateStr | None = Field(None, description="结算日期", examples=["2024-05-31"])
quantity: float | None = Field(None, description="合同金额", examples=[0])
remark: str | None = Field(None, description="填报备注", examples=[""])
is_complete: bool | None = Field(None, description="是否完成", examples=[False])
write_off_rate: float | None = Field(None, description="核销率", examples=[0.0])
confirmation_time: str | None = Field(None, description="确认时间", examples=["2025-12-17 11:13:49"])
approval_time: str | None = Field(None, description="审批时间", examples=["2025-12-17 11:13:49"])
approval_status: ApprovalStatus | None = Field("registered", description="审批状态", examples=["registered"])
@field_validator("approval_status")
def validate_approval_status(cls, v):
"""验证审批字段"""
if v is None:
return v
try:
return ApprovalStatus(v) # 尝试转换
except ValueError:
raise HTTPException(400, f"审批状态 '{v}' 无效")
@field_validator("confirmation_time", "approval_time")
def validate_time(cls, v):
"""验证时间"""
if v is None:
return v
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
raise HTTPException(detail=f'{v}时间格式错误，应为：2025-12-17 11:13:49', status_code=400)
return v
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v is None:
return None
if v < 0:
raise HTTPException(status_code=400, detail='合同金额不能小于0')
return v
@field_validator("date")
def validate_date(cls, v):
if v is None:
return None
if v > get_current_date():
raise HTTPException(detail='结算日期不能大于今天', status_code=400)
return v
class ContractSettlementDetailBulkUpdate(BaseModel):
detail_list: List[ContractSettlementDetailUpdate]
schemas/material/material.py
+147
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from pydantic import Field, BaseModel,field_validator,model_validator
from fastapi import HTTPException
from typing import List, Optional, Literal
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
class PlanNode(BaseModel):
date: DateStr = Field(..., description="计划节点时间", examples=["2024-01-01"])
quantity: float = Field(..., description="计划完成量", examples=[100.0])
is_audit: Optional[bool] = Field(False, description="是否已审核", examples=[False])
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='计划完成量不能小于等于0')
return v
class MaterialResponse(BaseResponseWithID):
"""
供货模型
"""
id : str = Field(..., description="物资ID", examples=["material123"])
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
contract_id: str = Field("", description="所属合同ID", examples=["contract456"])
show_name: str = Field("", description="展示名称", examples=["主变"])
material_type: str = Field("", description="物资类型")
contract_quantity: float = Field(0.0, description="合同数量", examples=[1000.0])
plan_start_quantity: float = Field(
0.0, description="计划首批到货量", examples=[1000.0]
)
complete_quantity: float = Field(0.0, description="实际到货累计", examples=[0.0])
complete_rate: float = Field(0.0, description="实际到货率(%)", examples=[0.0])
plan_start_date: Optional[DateStr] = Field(
None, description="计划首批到货时间", examples=["2024-01-01"]
)
plan_complete_date: Optional[DateStr] = Field(
None, description="计划全部到货时间", examples=["2024-06-01"]
)
actual_start_date: Optional[DateStr] = Field(
None, description="实际首批到货时间", examples=["2024-01-15"]
)
actual_complete_date: Optional[DateStr] = Field(
None, description="实际全部到货时间", examples=["2024-06-10"]
)
plan_node: List[PlanNode] = Field(default_factory=list, description="计划节点列表")
status: Optional[int] = Field(None, description="供货状态", examples=[0])
# 2025-10-20新增字段，延迟时间
delay_days: Optional[int] = Field(None, description="延迟时间（天）", examples=[0])
statistic_date: Optional[DateStr] = Field(
None, description="统计节点截止日期", examples=["2024-05-31"]
)
class MaterialCreate(BaseModel):
"""
创建物资
MATERIAL_BASE_INFO = "material.base_info"
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
contract_id: str = Field(..., description="所属合同ID", examples=["contract456"])
show_name: str = Field(..., description="展示名称", examples=["主变"])
material_type: str = Field(..., description="物资类型")
contract_quantity: float = Field(0.0, description="合同数量", examples=[1000.0])
@field_validator("contract_quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='合同数量不能小于0')
return v
class MaterialUpdate(BaseModel):
"""
更新物资
MATERIAL_BASE_INFO = "material.base_info"
"""
id: str = Field(..., description="物资ID", examples=["material123"])
contract_id: Optional[str] = Field(None, description="所属合同ID", examples=["contract456"])
show_name: Optional[str] = Field(None, description="展示名称", examples=["主变"])
class MaterialPlanUpdate(BaseModel):
"""
物资计划更新模型
MATERIAL_PLAN = "material.plan"
业务逻辑说明：
- API要求计划节点时间必须晚于计划首批到货时间（不能等于）
- 自动清理脏数据：如果 plan_node 有2个或以上节点，删除：
1. 开头节点：如果其 date 等于 plan_start_date
2. 结尾节点：如果其 date 等于 plan_complete_date
- 这样避免提交包含边界节点的数据导致API报错
"""
id: str = Field(..., description="物资ID", examples=["material123"])
plan_start_quantity: Optional[float] = Field(
None, description="计划首批到货量", examples=[1000.0]
)
plan_start_date: Optional[str] = Field(None, description="计划首批到货时间", examples=["2024-01-01"])
plan_complete_date: Optional[str] = Field(None, description="计划全部到货时间", examples=["2024-06-01"])
contract_quantity: float = Field(..., description="合同数量", examples=[1000.0])
plan_node: Optional[List[PlanNode]] = Field(default_factory=list, description="计划节点列表")
@field_validator("contract_quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='合同数量不能小于0')
return v
@field_validator("plan_start_quantity")
def validate_plan_start_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='计划首批到货量不能小于0')
return v
@model_validator(mode='after')
def clean_plan_nodes(self):
"""
清理计划节点列表中的边界节点
如果 plan_node 有2个或以上节点，删除：
- 开头节点：date 等于 plan_start_date
- 结尾节点：date 等于 plan_complete_date
这避免了API报错“计划节点时间必须晚于计划首批到货时间”
"""
if not self.plan_node or len(self.plan_node) < 2:
return self
cleaned_nodes = list(self.plan_node)
# 删除开头的边界节点
if (self.plan_start_date and
cleaned_nodes and
cleaned_nodes[0].date == self.plan_start_date):
cleaned_nodes.pop(0)
# 删除结尾的边界节点
if (self.plan_complete_date and
cleaned_nodes and
cleaned_nodes[-1].date == self.plan_complete_date):
cleaned_nodes.pop()
self.plan_node = cleaned_nodes
return self
schemas/material/material_detail.py
+132
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from pydantic import Field, BaseModel,field_validator
from fastapi import HTTPException
from ..common.datetime import get_current_date
from typing import List, Optional, Literal
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
from ..common.enums import ApprovalStatus
from datetime import datetime
class MaterialDetailResponse(BaseResponseWithID):
"""
物资明细模型，存储在CouchDB中的物资明细文档
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
parent_id: str = Field(..., description="所属物资ID", examples=["material789"])
date: DateStr = Field(..., description="实际到货日期", examples=["2024-05-31"])
rate: Optional[float] = Field(None, description="实际到货率(%)", examples=[0.0])
quantity: float = Field(0.0, ge=0, description="实际到货量累计", examples=[0.0])
status: Optional[int] = Field(None, description="状态 0:正常 1:超前 -1:延误", examples=[0])
remark: Optional[str] = Field(None, description="填报备注", examples=[""])
is_complete: Optional[bool] = Field(
None, description="是否为全部到货", examples=[False]
)
class MaterialDetailCreate(BaseModel):
"""
物资明细创建模型
MATERIAL_DETAIL = "material.detail"
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
parent_id: str = Field(..., description="所属物资ID", examples=["material789"])
quantity: float = Field(0.0, ge=0, description="实际到货量累计", examples=[0.0])
date: DateStr = Field(..., description="实际到货日期", examples=["2024-05-31"])
remark: Optional[str] = Field(None, description="填报备注", examples=[""])
is_complete: Optional[bool] = Field(
None, description="是否为全部到货", examples=[False]
)
confirmation_time: str | None = Field(None, description="确认时间", examples=["2025-12-17 11:13:49"])
approval_time: str | None = Field(None, description="审批时间", examples=["2025-12-17 11:13:49"])
approval_status: ApprovalStatus = Field("registered", description="审批状态", examples=["registered"])
@field_validator("approval_status")
def validate_approval_status(cls, v):
"""验证审批字段"""
try:
return ApprovalStatus(v) # 尝试转换
except ValueError:
raise HTTPException(400, f"审批状态 '{v}' 无效")
@field_validator("confirmation_time", "approval_time")
def validate_time(cls, v):
"""验证时间"""
if v is None:
return v
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
raise HTTPException(detail=f'{v}时间格式错误，应为：2025-12-17 11:13:49', status_code=400)
return v
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='实际完成量累计不能小于0')
return v
@field_validator("date")
def validate_date(cls, v):
if v > get_current_date():
raise HTTPException(detail='节点日期不能大于今天', status_code=400)
return v
class MaterialDetailUpdate(BaseModel):
"""
物资明细更新模型
MATERIAL_DETAIL = "material.detail"
"""
id: str = Field(..., description="物资明细ID")
quantity: Optional[float] = Field(None, ge=0, description="实际到货量累计", examples=[0.0])
date: Optional[DateStr] = Field(None, description="实际到货日期", examples=["2024-05-31"])
remark: Optional[str] = Field(None, description="填报备注", examples=[""])
is_complete: Optional[bool] = Field(
None, description="是否为全部到货", examples=[False]
)
confirmation_time: str | None = Field(None, description="确认时间", examples=["2025-12-17 11:13:49"])
approval_time: str | None = Field(None, description="审批时间", examples=["2025-12-17 11:13:49"])
approval_status: ApprovalStatus | None = Field("registered", description="审批状态", examples=["registered"])
@field_validator("approval_status")
def validate_approval_status(cls, v):
"""验证审批字段"""
if v is None:
return v
try:
return ApprovalStatus(v) # 尝试转换
except ValueError:
raise HTTPException(400, f"审批状态 '{v}' 无效")
@field_validator("confirmation_time", "approval_time")
def validate_time(cls, v):
"""验证时间"""
if v is None:
return v
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
raise HTTPException(detail=f'{v}时间格式错误，应为：2025-12-17 11:13:49', status_code=400)
return v
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v is None:
return None
if v < 0:
raise HTTPException(status_code=400, detail='实际完成量累计不能小于0')
return v
@field_validator("date")
def validate_date(cls, v):
if v is None:
return None
if v > get_current_date():
raise HTTPException(detail='节点日期不能大于今天', status_code=400)
return v
class MaterialDetailBulkUpdate(BaseModel):
detail_list: List[MaterialDetailUpdate]
schemas/power/power.py
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from pydantic import Field, BaseModel,field_validator,model_validator
from fastapi import HTTPException
from typing import List, Optional, Literal
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
class PlanNode(BaseModel):
date: DateStr = Field(..., description="计划节点时间", examples=["2024-01-01"])
quantity: float = Field(..., description="计划完成量", examples=[100.0])
is_audit: Optional[bool] = Field(False, description="是否已审核", examples=[False])
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证计划到场人数必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='计划节点人数不能小于0')
return v
class PowerResponse(BaseResponseWithID):
"""
力能模型
"""
code: Optional[str] = Field(
"personnel",
description="力能类型(人员模块拓展为力能模块，可以在本字段保存人员/机具等编码)",
examples=["personnel"],
)
project_id: str = Field(..., description="所属项目", examples=["project123"])
contract_id: Optional[str] = Field(
None,
description="所属合同(目前前端页面显示没有按这个字段，仅通过脚本绑定了epc合同，用于接口数据推送。后续行为待讨论)",
examples=["contract456"],
)
show_name: str = Field("", description="展示名称", examples=["施工班组A"])
status: Optional[int] = Field(None, description="人员状态", examples=[0])
plan_attendance: int = Field(
0,
description="计划出勤人数(暂时定为最后一次报明细时的计划出勤人数)",
examples=[10],
)
actual_daily_attendance: int = Field(0, description="实际日均出勤", examples=[8])
attendance_rate: float = Field(0.0, description="出勤率", examples=[0.8])
statistic_date: Optional[DateStr] = Field(
None, description="统计节点", examples=["2024-05-31"]
)
plan_exit_date: Optional[DateStr] = Field(
None, description="计划退场时间", examples=["2024-06-30"]
)
actual_exit_date: Optional[DateStr] = Field(
None, description="实际退场时间", examples=["2024-07-05"]
)
plan_node: List[PlanNode] = Field(default_factory=list, description="计划节点列表")
plan_start_date: Optional[DateStr] = Field(
None, description="计划首批到场时间", examples=["2024-05-01"]
)
plan_start_quantity: int = Field(0, description="计划首批到场人数", examples=[5], ge=0)
actual_start_date: Optional[DateStr] = Field(
None, description="实际首批到场时间", examples=["2024-05-02"]
)
actual_start_quantity: Optional[int] = Field(
None, description="实际首批到场人数", examples=[4]
)
class PowerCreate(BaseModel):
"""
创建力能
POWER_BASE_INFO = "personnel.base_info"
"""
project_id: str = Field(..., description="所属项目ID", examples=["project123"])
contract_id: Optional[str] = Field(
None, description="所属合同ID", examples=["contract456"]
)
#show_name: str = Field(..., description="展示名称", examples=["施工班组A"])
code: Optional[str] = Field(
"personnel",
description="力能类型(人员模块拓展为力能模块，可以在本字段保存人员/机具等编码)",
examples=["personnel"],
)
class PowerUpdate(BaseModel):
"""
更新力能
POWER_BASE_INFO = "personnel.base_info"
"""
id: str = Field(..., description="力能ID")
contract_id: Optional[str] = Field(
None, description="所属合同ID", examples=["contract456"]
)
#show_name: Optional[str] = Field(None, description="展示名称", examples=["施工班组A"])
class PowerPlanUpdate(BaseModel):
"""
力能计划更新模型
POWER_PLAN = "personnel.plan"
业务逻辑说明：
- API要求计划节点时间必须晚于计划首批到场时间（不能等于）
- 自动清理脏数据：如果 plan_node 有2个或以上节点，删除边界节点
"""
id: str = Field(..., description="力能ID")
plan_start_date: str = Field(..., description="计划首批到场时间")
plan_start_quantity: int = Field(..., description="计划首批到场人数")
plan_exit_date: DateStr = Field(
..., description="计划退场时间", examples=["2024-06-30"]
)
plan_node: List[PlanNode] = Field(default_factory=list, description="计划节点列表")
@field_validator("plan_start_quantity")
def validate_quantity(cls, v):
"""验证计划首批到场人数必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='计划首批进场人数必须大于等于0')
return v
@model_validator(mode='after')
def clean_plan_nodes(self):
"""
清理计划节点列表中的边界节点
如果 plan_node 有2个或以上节点，删除：
- 开头节点：date 等于 plan_start_date
- 结尾节点：date 等于 plan_exit_date
这避免了API报错“计划节点时间必须晚于计划首批到场时间”
"""
if not self.plan_node or len(self.plan_node) < 2:
return self
cleaned_nodes = list(self.plan_node)
# 删除开头的边界节点
if (self.plan_start_date and
cleaned_nodes and
cleaned_nodes[0].date == self.plan_start_date):
cleaned_nodes.pop(0)
# 删除结尾的边界节点
if (self.plan_exit_date and
cleaned_nodes and
cleaned_nodes[-1].date == self.plan_exit_date):
cleaned_nodes.pop()
self.plan_node = cleaned_nodes
return self
schemas/power/power_detail.py
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from pydantic import Field, BaseModel,field_validator
from fastapi import HTTPException
from ..common.datetime import get_current_date
from typing import List, Optional, Literal
from ..common.validators import DateStr
from ..common.base import BaseResponseWithID
from ..common.enums import ApprovalStatus
from datetime import datetime
class PowerDetail(BaseResponseWithID):
"""
力能配置明细
"""
project_id: str = Field(..., description="所属项目", examples=["project123"])
parent_id: str = Field(..., description="所属力能配置ID", examples=["personnel789"])
date: DateStr = Field(..., description="本次日期", examples=["2024-05-31"])
quantity: int = Field(..., description="累计完成量", examples=[0], ge=0)
remark: Optional[str] = Field(None, description="填报备注", examples=[""])
is_complete: Optional[bool] = Field(
None, description="是否为全部退场", examples=[False]
)
change_count: int = Field(0, description="变更次数", examples=[0])
status: Optional[int] = Field(None, description="进度状态", examples=[0])
rate: Optional[float] = Field(None, description="出勤率", examples=[0])
class PowerDetailCreate(BaseModel):
"""
力能配置明细创建模型
POWER_DETAIL = "power.detail"
"""
project_id: str = Field(..., description="所属项目", examples=["project123"])
parent_id: str = Field(..., description="所属力能配置ID", examples=["personnel789"])
date: DateStr = Field(..., description="本次日期", examples=["2024-05-31"])
quantity: int = Field(..., description="累计完成量", examples=[0], ge=0)
remark: Optional[str] = Field(None, description="填报备注", examples=[""])
is_complete: Optional[bool] = Field(
None, description="是否为全部退场", examples=[False]
)
confirmation_time: str | None = Field(None, description="确认时间", examples=["2025-12-17 11:13:49"])
approval_time: str | None = Field(None, description="审批时间", examples=["2025-12-17 11:13:49"])
approval_status: ApprovalStatus = Field("registered", description="审批状态", examples=["registered"])
@field_validator("approval_status")
def validate_approval_status(cls, v):
"""验证审批字段"""
try:
return ApprovalStatus(v) # 尝试转换
except ValueError:
raise HTTPException(400, f"审批状态 '{v}' 无效")
@field_validator("confirmation_time", "approval_time")
def validate_time(cls, v):
"""验证时间"""
if v is None:
return v
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
raise HTTPException(detail=f'{v}时间格式错误，应为：2025-12-17 11:13:49', status_code=400)
return v
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v < 0:
raise HTTPException(status_code=400, detail='实际完成量累计不能小于0')
return v
@field_validator("date")
def validate_date(cls, v):
if v > get_current_date():
raise HTTPException(detail='节点日期不能大于今天', status_code=400)
return v
class PowerDetailUpdate(BaseModel):
"""
力能配置明细更新模型
POWER_DETAIL = "power.detail"
"""
id: str = Field(..., description="力能配置明细ID")
date: Optional[DateStr] = Field(None, description="本次日期", examples=["2024-05-31"])
quantity: Optional[int] = Field(None, description="累计完成量", examples=[0], ge=0)
remark: Optional[str] = Field(None, description="填报备注", examples=[""])
is_complete: Optional[bool] = Field(
None, description="是否为全部退场", examples=[False]
)
confirmation_time: str | None = Field(None, description="确认时间", examples=["2025-12-17 11:13:49"])
approval_time: str | None = Field(None, description="审批时间", examples=["2025-12-17 11:13:49"])
approval_status: ApprovalStatus | None = Field("registered", description="审批状态", examples=["registered"])
@field_validator("approval_status")
def validate_approval_status(cls, v):
"""验证审批字段"""
if v is None:
return v
try:
return ApprovalStatus(v) # 尝试转换
except ValueError:
raise HTTPException(400, f"审批状态 '{v}' 无效")
@field_validator("confirmation_time", "approval_time")
def validate_time(cls, v):
"""验证时间"""
if v is None:
return v
try:
datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
except ValueError:
raise HTTPException(detail=f'{v}时间格式错误，应为：2025-12-17 11:13:49', status_code=400)
return v
@field_validator("quantity")
def validate_quantity(cls, v):
"""验证实际完成量累计必须为非负数"""
if v is None:
return None
if v < 0:
raise HTTPException(status_code=400, detail='实际完成量累计不能小于0')
return v
@field_validator("date")
def validate_date(cls, v):
if v is None:
return None
if v > get_current_date():
raise HTTPException(detail='节点日期不能大于今天', status_code=400)
return v
class PowerDetailBulkUpdate(BaseModel):
detail_list: List[PowerDetailUpdate]
schemas/project/enums.py
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from enum import Enum
from pydantic import BaseModel, Field
class ProgressType(str, Enum):
"""推进分类枚举"""
A = "A"
B = "B"
C = "C"
class KeyConstraints(str, Enum):
NONE = "NONE"
LAND = "LAND"
TRANSMISSION = "TRANSMISSION"
BOTH = "BOTH"
QT = "QT"
class DBTCSCORE(BaseModel):
year: str = Field(..., description="评分年份, yyyy格式")
is_jg: bool = Field(..., description="是否为工达标投产")
score: float = Field(..., description="集团考核评分")
class ProjectType(str, Enum):
"""项目类型枚举"""
PHOTOVOLTAIC = "photovoltaic" # 光伏
OFFSHORE_WIND = "offshore_wind" # 海风
ONSHORE_WIND = "onshore_wind" # 陆风
HYDROPOWER = "hydropower" # 水电
THERMAL_POWER = "thermal_power" # 火电
PUMPED_STORAGE = "pumped_storage" # 抽蓄
GAS_TURBINE = "gas_turbine" # 气电
schemas/project/project.py
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"""
项目全部信息的增删查改模板，聚合了项目相关schema
"""
from pydantic import BaseModel, Field, field_serializer
from typing import Optional
from .project_base import (
ProjectResponseBase,
ProjectEnsureCapacity,
ProjectClimbCapacity,
ProjectChallengeCapacity,
ProjectActualConstruction,
ProjectPlanConstruction,
ProjectInvestmentDecision,
ProjectKeyConstraints,
ProjectProductionCapacity,
ProjectCompleteInvestment,
ProjectDynamicInvestment
)
from ..project_extensions.preparation import PreparationDetail
from ..project_extensions.production import ProductionDetail
from ..project_extensions.project_detail import ProjectDetailProject
from ..project_extensions.generator_unit import (
GeneratorUnitProject,
PostGeneratorUnits
)
from ..project_extensions.lar import (
LarDetailSchema,
LarChangeListSchema,
LarChangeUpdateSchema,
LarMainInfoUpdateSchema,
LarResettlementSchema,
LarInvestmentSchema, LarChangeDetailSchema
)
from ..project_extensions.contract_change import (
ContractChangeResponse,
PostContractChange
)
from ..project_multi_type import (
PhotovoltaicExtension,
OnShoreWindExtension,
OffShoreWindExtension,
HydropowerExtension,
PumpedStorageExtension,
GasTurbineExtension,
ThermalPowerExtension
)
class ProjectInfoResponse(BaseModel):
"""
项目全部信息响应模型
"""
project: ProjectResponseBase = Field(..., description="项目基本信息")
project_detail: list[ProjectDetailProject] = Field(..., description="项目容量信息")
generator_units: list[GeneratorUnitProject] = Field(..., description="发电单元信息列表(仅限水电、抽蓄、煤电、气电)")
lar: Optional[LarDetailSchema] = Field(None, description="移民征地信息(仅限水电、抽蓄)")
lar_change: list[LarChangeDetailSchema] = Field(default_factory=list, description="移民变更信息列表(仅限水电、抽蓄)")
contract_changes: list[ContractChangeResponse] = Field(..., description="合同变更信息列表(仅限水电、抽蓄、煤电、气电)")
# 扩展字段
photovoltaic_extension: PhotovoltaicExtension | None = Field(None, description="光伏项目扩展信息")
onshore_wind_extension: OnShoreWindExtension | None = Field(None, description="陆风项目扩展信息")
offshore_wind_extension: OffShoreWindExtension | None = Field(None, description="海风项目扩展信息")
hydropower_extension: HydropowerExtension | None = Field(None, description="水电项目扩展信息")
pumped_storage_extension: PumpedStorageExtension | None = Field(None, description="抽蓄项目扩展信息")
gas_turbine_extension: GasTurbineExtension | None = Field(None, description="燃气轮机项目扩展信息")
thermal_power_extension: ThermalPowerExtension | None = Field(None, description="火电项目扩展信息")
# 投产节点
production_list: list[ProductionDetail] = Field(default_factory=list, description="投产节点列表")
# 里程碑节点
preparation_list: list[PreparationDetail] = Field(default_factory=list, description="里程碑节点列表")
schemas/project/project_base.py
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"""
项目数据推送相关schema
"""
from typing import List, Optional
from fastapi import HTTPException
from pydantic import Field, BaseModel, field_validator
from ..common.push_system import BaseUpdateRequestSchema
from ..common.base import BaseResponseWithID
from ..common.datetime import get_current_date
from ..common.validators import DateStr
from .enums import ProgressType, KeyConstraints, DBTCSCORE
class ProjectResponseBase(BaseResponseWithID):
"""
项目基础信息, 复制自project_model
不进行继承，通过检查器确保字段和模型一致
"""
# 基础信息-不允许更改
id : str = Field(..., description="项目ID", examples=["uuid"])
project_type: str = Field("", description="项目类型")
region_name: List[str] = Field(default_factory=list, description="项目所属区域名称", examples=[["华东", "江苏"]])
region_path: List[str] = Field(default_factory=list, description="项目所属区域路径", examples=[["110000", "120000", "120001"]])
province: str = Field("", description="省份(region_path第一个)", examples=["110000"])
is_domestic :bool=Field(True, description="是否是国内项目")
company_id: str = Field("", description="所属公司ID", examples=["company123"])
company_name: str = Field("", description="所属公司名称", examples=["国电投江苏公司"])
syxs: Optional[str] = Field(None, description="升压站型式")
sub_type: Optional[str] = Field(None, description="光伏类别")
scgc_type: Optional[str] = Field(None, description="送出工程建设方式")
# 基础信息-允许更改
address: str = Field("", description="项目地址", examples=["某省某市某区"])
code: str = Field("", description="项目编码", examples=["XM2025001"])
name: str = Field(..., description="项目名称", examples=["XX新能源项目"])
short_name: str = Field("", description="项目简称", examples=["XX项目"])
manager_name: str = Field("", description="负责人姓名", examples=["张三"])
manager_phone: str = Field("", description="负责人电话", examples=["13800000000"])
# 容量信息
authorization_date: Optional[DateStr] = Field(None, description="核准日期", examples=["2024-01-01"])
authorized_capacity: float = Field(0.0, description="核准容量（万千瓦）", examples=[10.0])
# 投决
investment_decision_capacity: Optional[float] = Field(None, description="投资决策容量", examples=[8.0])
investment_decision_date: Optional[DateStr] = Field(None, description="投资决策日期", examples=["2024-02-01"])
# 开工
plan_construction_capacity: float = Field(0.0, description="本年度计划开工容量", examples=[5.0])
plan_construction_date: Optional[DateStr] = Field(None, description="本年度计划开工日期", examples=["2024-03-01"])
actual_construction_capacity: float = Field(0.0, description="本年度实际开工容量", examples=[4.0])
actual_construction_date: Optional[DateStr] = Field(None, description="本年度实际开工日期", examples=["2024-04-01"])
accumulated_construction_capacity: float = Field(0.0, description="累计开工容量", examples=[12.0])
constructing_capacity: float = Field(0.0, description="在建容量", examples=[6.0])
# 投产
ensure_production_capacity: float = Field(0.0, description="本年度确保投产容量", examples=[3.0])
challenge_production_capacity: float = Field(0.0, description="本年度揭榜投产容量", examples=[2.0])
climb_production_capacity: float = Field(0.0, description="本年度登高投产容量", examples=[1.0])
plan_production_date: Optional[DateStr] = Field(None, description="计划投产日期", examples=["2024-08-01"])
plan_full_production_date: Optional[DateStr] = Field(None, description="计划全部投产日期", examples=["2024-09-01"])
actual_production_date: Optional[DateStr] = Field(None, description="实际投产日期", examples=["2024-08-15"])
actual_full_production_date: Optional[DateStr] = Field(None, description="实际全投日期", examples=["2024-09-10"])
production_capacity: Optional[float] = Field(0.0, description="本年度投产容量", examples=[2.0])
production_date: Optional[DateStr] = Field(None, description="本年度首批投产日期", examples=["2024-09-01"])
total_production_capacity: Optional[float] = Field(0.0, description="全部投产容量", examples=[2.0])
# 投资
dynamic_investment: float = Field(0.0, description="动态总投资", examples=[100000.0])
complete_investment: float = Field(0.0, description="完成投资", examples=[80000.0])
# 其他信息
progress_type: ProgressType = Field(..., description="推进分类", examples=[ProgressType.A])
key_constraints: KeyConstraints = Field(KeyConstraints.NONE, description="关键制约", examples=[KeyConstraints.NONE])
key_constraints_remark: Optional[str] = Field("", description="关键制约备注", examples=["无"])
status: Optional[str] = Field(None, description="项目状态")
apply_file_ids: List[str] = Field(default_factory=list, description="申请表附件ID列表", examples=[[]])
# 拓展信息
dbtc_score_list: Optional[list] = Field(default_factory=list, description='达标投产评分列表') # 这里项目用的是list而不是List
class ProjectResponseBaseList(BaseModel):
page: int
page_size: int
total: int
list: List[ProjectResponseBase] = []
# ==================== Update ====================
class KeyConstraintsRemarkMixin:
"""关键制约备注校验混入类"""
@field_validator("key_constraints_remark")
def validate_key_constraints_remark(cls, v):
if v is None:
return v
if len(v) > 500:
raise HTTPException(detail="关键制约备注不能超过500个字符", status_code=400)
return v
class AuthorizationDateMixin:
"""关键制约备注校验混入类"""
@field_validator("authorization_date")
def validate_actual_date(cls, v):
if v is None:
return v
if v > get_current_date():
raise HTTPException(detail='核准/备案日期不能大于今天', status_code=400)
return v
class ProjectBaseInfoUpdate(BaseModel, KeyConstraintsRemarkMixin, AuthorizationDateMixin):
"""
项目基本信息 PROJECT_BASE_INFO
"""
# 基础信息-允许更改
id: str = Field(..., description="项目id", examples=["uuid"])
address: str | None = Field(None, description="项目地址", examples=["某省某市某区"])
code: str | None = Field(None, description="项目编码", examples=["XM2025001"])
name: str = Field(..., description="项目名称", examples=["XX新能源项目"])
short_name: str | None = Field(None, description="项目简称", examples=["XX项目"])
manager_name: str | None = Field(None, description="负责人姓名", examples=["张三"])
manager_phone: str | None = Field(None, description="负责人电话", examples=["13800000000"])
# 其他信息
progress_type: ProgressType = Field(..., description="推进分类", examples=[ProgressType.A])
key_constraints: KeyConstraints | None = Field(None, description="关键制约", examples=[KeyConstraints.NONE])
key_constraints_remark: str | None = Field(None, description="关键制约备注", examples=["无"])
apply_file_ids: List[str] | None = Field(None, description="申请表附件ID列表", examples=[[]])
# 拓展信息
dbtc_score_list: list[DBTCSCORE] | None = Field(None, description='达标投产评分列表') # 这里项目用的是list而不是List
# 核准
authorization_date: DateStr | None = Field(None, description="核准日期", examples=["2024-01-01"])
authorized_capacity: float | None = Field(None, description="核准容量（万千瓦）", examples=[10.0])
class _ProductionPlanNode(BaseModel):
year: int = Field(..., description="计划年份", examples=[2024])
capacity: float = Field(..., description="确保投产容量", examples=[3.0])
class ProjectEnsureCapacity(BaseModel):
"""
PROJECT_ENSURE_CAPACITY
填写项目确保投产容量列表，系统根据列表自动计算ensure_production_capacity字段
"""
# 确保投产容量
ensure_production_capacity_list : list[_ProductionPlanNode] = Field(..., description="确保投产容量列表（每次必须填写全部）")
class ProjectClimbCapacity(BaseModel):
"""
PROJECT_CLIMB_CAPACITY
填写项目登高投产容量列表，系统根据列表自动计算climb_production_capacity字段
"""
# 登高投产容量
climb_production_capacity_list : list[_ProductionPlanNode] = Field(..., description="登高投产容量列表（每次必须填写全部）")
class ProjectChallengeCapacity(BaseModel):
"""
PROJECT_CHALLENGE_CAPACITY
填写项目揭榜投产容量列表，系统根据列表自动计算challenge_production_capacity字段
"""
# 揭榜投产容量
challenge_production_capacity_list : list[_ProductionPlanNode] = Field(..., description="揭榜投产容量列表（每次必须填写全部）")
class _ActualNodeData(BaseModel):
capacity: float = Field(..., description="实际节点容量", examples=[4.0])
date: DateStr = Field(..., description="实际节点日期", examples=["2024-04-01"])
class ProjectActualConstruction(BaseModel):
"""
PROJECT_ACTUAL_CONSTRUCTION
项目实际开工节点
系统根据实际开工节点自动计算以下字段：
actual_construction_capacity 本年度实际开工容量
actual_construction_date 本年度实际开工日期
accumulated_construction_capacity 累计开工容量
constructing_capacity 在建容量
"""
actual_construction_list : list[_ActualNodeData] | None = Field(None, description="实际开工节点列表（每次必须填写全部）")
class _PlanNodeData(BaseModel):
capacity: float = Field(..., description="计划节点容量", examples=[5.0])
date: DateStr = Field(..., description="本年度计日期", examples=["2024-03-01"])
@field_validator("capacity")
def validate_capacity(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="节点容量必须大于等于0")
return v
class ProjectPlanConstruction(BaseModel):
"""
PROJECT_PLAN_CONSTRUCTION
项目计划开工节点
系统根据计划开工节点自动计算：
plan_construction_capacity 本年度计划开工容量
plan_construction_date 本年度计划开工日期
"""
plan_construction_list : list[_PlanNodeData] | None = Field(None, description="计划开工节点列表（每次必须填写全部）")
class ProjectInvestmentDecision(BaseModel):
"""
PROJECT_INVESTMENT_DECISION
投资决策容量和日期
"""
investment_decision_capacity: float = Field(..., description="投资决策容量", examples=[8.0])
investment_decision_date: DateStr = Field(..., description="投资决策日期", examples=["2024-02-01"])
@field_validator("investment_decision_date")
def validate_investment_decision_date(cls, v):
if v is None:
return v
if v > get_current_date():
raise HTTPException(detail='投资决策日期不能大于今天', status_code=400)
return v
@field_validator("investment_decision_capacity")
def validate_investment_decision_capacity(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="投资决策容量必须大于等于0")
return v
class ProjectKeyConstraints(BaseModel, KeyConstraintsRemarkMixin):
"""
PROJECT_KEY_CONSTRAINTS
关键制约
"""
key_constraints: KeyConstraints | None = Field(None, description="关键制约", examples=[KeyConstraints.NONE])
key_constraints_remark: str | None = Field(None, description="关键制约备注", examples=["无"])
class _ActualProductionNode(BaseModel):
capacity: float = Field(..., description="实际投产容量", examples=[2.0])
date: DateStr = Field(..., description="实际投产日期", examples=["2024-08-15"])
@field_validator("capacity")
def validate_capacity(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="实际投产容量必须大于等于0")
return v
@field_validator("date")
def validate_date(cls, v):
if v is None:
return v
if v > get_current_date():
raise HTTPException(detail='实际投产日期不能大于今天', status_code=400)
return v
class ProjectProductionCapacity(BaseModel):
"""
PROJECT_PRODUCTION_CAPACITY
填写项目投产数据
每个项目在各年份或一年内可能有多次实际投产
系统会根据投产节点列表数据，自动计算
production_capacity 本年度投产容量
production_date 本年度首批投产日期
total_production_capacity 全部投产容量
"""
plan_production_date: DateStr | None = Field(None, description="集团公司计划投产日期", examples=["2024-08-01"])
plan_full_production_date: DateStr | None = Field(None, description="集团公司计划全部投产日期", examples=["2024-09-01"])
ic_plan_first_production_date: DateStr | None = Field(None, description="区域公司计划首批投产日期(只有新能源需要)",examples=["2024-08-01"])
ic_plan_full_production_date: DateStr | None = Field(None, description="区域公司计划全投日期(只有新能源需要)",examples=["2024-09-01"])
actual_production_date: DateStr | None = Field(None, description="实际投产日期(只有新能源需要)", examples=["2024-08-15"])
actual_full_production_date: DateStr | None = Field(None, description="实际全投日期(只有新能源需要)", examples=["2024-09-10"])
actual_production_list : list[_ActualProductionNode] | None = Field(None, description="实际投产节点列表(每次必须填写全部)(只有新能源需要)")
@field_validator("actual_production_date")
def validate_actual_production_date(cls, v):
if v is None:
return v
if v > get_current_date():
raise HTTPException(detail='实际投产日期不能大于今天', status_code=400)
return v
@field_validator("actual_full_production_date")
def validate_actual_full_production_date(cls, v):
if v is None:
return v
if v > get_current_date():
raise HTTPException(detail='实际全投日期不能大于今天', status_code=400)
return v
class ProjectCompleteInvestment(BaseModel):
"""
PROJECT_COMPLETE_INVESTMENT
完成投资投资
"""
complete_investment: float = Field(..., description="完成投资", examples=[80000.0])
@field_validator("complete_investment")
def validate_complete_investment(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400,detail="完成投资必须大于等于0")
return v
class ProjectSettlementInvestment(BaseModel):
"""
PROJECT_SETTLEMENT_INVESTMENT
合同结算投资情况
"""
implementation_estimate: float = Field(..., description="执行概算", examples=[80000.0])
static_total_investment: float = Field(..., description="静态总投资", examples=[80000.0])
completed_investment: float = Field(..., description="完成投资", examples=[80000.0])
dynamic_investment: float = Field(..., description="动态总投资", examples=[80000.0])
@field_validator("implementation_estimate")
def validate_implementation_estimate(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400,detail="执行概算必须大于等于0")
return v
@field_validator("static_total_investment")
def validate_static_total_investment(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="静态总投资必须大于等于0")
return v
@field_validator("completed_investment")
def validate_completed_investment(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="完成投资必须大于等于0")
return v
@field_validator("dynamic_investment")
def validate_dynamic_investment(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="动态总投资必须大于等于0")
return v
class ProjectDynamicInvestment(BaseModel):
"""
PROJECT_DYNAMIC_INVESTMENT
"""
# 动态总投资
dynamic_investment: float | None = Field(None, description="动态总投资", examples=[100000.0])
@field_validator("dynamic_investment")
def validate_dynamic_investment(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="动态总投资必须大于等于0")
return v
# ======================= 水电抽蓄专用 =============================
# ==================== 枚举说明 用于文档自动生成 ====================
schemas/project_extensions/contract_change.py
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"""
contract_change相关schemea
"""
from ..common.validators import DateStr
from pydantic import BaseModel, Field
from typing import Optional
from ..common.base import BaseResponseWithID
from pydantic import field_validator
from fastapi import HTTPException
class ContractChangeResponse(BaseResponseWithID):
"""
合同变更模型
"""
id: Optional[str] = Field(default=None, description="合同变更ID")
project_id : Optional[str] = Field(None, description="所属项目ID")
contract_id: Optional[str] = Field(None, description="关联合同ID")
name: Optional[str] = Field(None, description="合同名称")
sub_name: Optional[str] = Field(None, description="合同子标题（epc合同和pc合同会有子标题）")
sign_company:Optional[str] = Field(None, description="签约公司")
title: Optional[str] = Field(None, description="变更事项")
reason: Optional[str] = Field(None, description="变更理由")
before_amount: Optional[float] = Field(None, description="变更前金额")
after_amount: Optional[float] = Field(None, description="变更后金额")
change_count: Optional[float] = Field(None, description="变更金额")
change_rate: Optional[str] = Field(None, description="变更比例")
change_time: Optional[str] = Field(None, description="变更时间(格式：YYYY-MM-DD)")
attachment_ids:Optional[list] = Field(None, description="附件ID列表")
attachment_names:Optional[list] = Field(None, description="附件名称列表")
created_at:Optional[str]=Field(None, description="创建时间")
created_by_name: Optional[str] = Field(None, description="创建人名称")
class PostContractChange(BaseModel):
"""
合同变更请求（水火抽蓄气电）
PROJECT_CONTRACT_CHANGE = "project.contract-change"
"""
id: str = Field(..., description="合同变更ID，更新时传入，创建时不传")
project_id: str = Field(..., description="所属项目ID")
contract_id: str = Field(..., description="合同ID")
title: str = Field(..., description="变更事项")
reason: str = Field(..., description="变更理由")
before_amount: float = Field(..., description="变更前金额")
after_amount: float = Field(..., description="变更后金额")
change_time: DateStr = Field(..., description="变更时间(格式：YYYY-MM-DD)")
attachment_ids: list = Field(..., description="附件ID列表")
@field_validator("after_amount")
def validate_after_amount(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="变更后金额必须小于等于0")
return v
class CreateContractChange(BaseModel):
"""
创建合同变更请求（水火抽蓄气电）
PROJECT_CONTRACT_CHANGE = "project.contract-change"
"""
project_id: str = Field(..., description="所属项目ID")
contract_id: str = Field(..., description="合同ID")
title: str = Field(..., description="变更事项")
reason: str = Field(..., description="变更理由")
before_amount: float = Field(..., description="变更前金额")
after_amount: float = Field(..., description="变更后金额")
change_time: DateStr = Field(..., description="变更时间(格式：YYYY-MM-DD)")
attachment_ids: list = Field(..., description="附件ID列表")
@field_validator("after_amount")
def validate_after_amount(cls, v: float) -> float:
if v < 0:
raise HTTPException(status_code=400, detail="变更后金额不能小于0")
return v
schemas/project_extensions/generator_unit.py
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from pydantic import BaseModel, Field,field_validator
from typing import Optional
from ..common.base import BaseResponseWithID
from ..common.datetime import datetime_date,get_current_date
from fastapi import HTTPException
class GeneratorUnitProject(BaseResponseWithID):
project_id : Optional[str]= Field(None, description="项目ID")
serial_number: Optional[int] = Field(None, description="机组序号")
approval_status:Optional[str]=Field(None, description="审批状态")
capacity: Optional[float] = Field(None, description="单机容量(MW)")
plan_production_date: Optional[str] = Field(None, description="计划投产日期")
actual_production_date: Optional[str] = Field(None, description="实际投产日期")
class PostGeneratorUnits(BaseModel):
model_config = {"populate_by_name": True}
id:str = Field(..., description="机组ID")
project_id: str = Field(..., description="所属项目ID")
actual_production_date: str = Field(..., alias="actual_date", description="实际投产日期(格式：YYYY-MM-DD)")
@field_validator('actual_production_date', mode="before")
def validate_actual_date_not_future(cls, v: str) -> str:
if v == "":
return ""
try:
actual = datetime_date(v)
except ValueError:
raise HTTPException(status_code=400,detail='日期格式为(YYYY-MM-DD)')
today = datetime_date(get_current_date())
if actual > today:
raise HTTPException(status_code=400,detail='机组日期不能晚于今天')
return v
schemas/project_extensions/lar.py
+206
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"""
移民征地相关schema
"""
from pydantic import BaseModel, Field, field_validator
from typing import Optional, List
from ..common.base import BaseResponseWithID
from ..common.validators import DateStr
from ..common.datetime import get_current_date
class LarDetailSchema(BaseResponseWithID):
id: str = Field(..., description="移民征地id")
project_id: Optional[str] = Field(None, description="项目ID")
plan_resettlement_pop: Optional[int] = Field(None, description="计划搬迁人数")
completed_resettlement_pop: Optional[int] = Field(None, description="完成搬迁人数")
plan_investment_amt: Optional[float] = Field(None, description="计划投资金额 ")
completed_investment_amt: Optional[float] = Field(None, description="完成投资金额 ")
plan_urban_comp: Optional[float] = Field(None, description="计划城镇补偿金额 ")
actual_urban_comp: Optional[float] = Field(None, description="实际城镇补偿金额 ")
plan_rural_comp: Optional[float] = Field(None, description="计划农村补偿金额 ")
actual_rural_comp: Optional[float] = Field(None, description="实际农村补偿金额 ")
plan_spec_project_reconstr: Optional[float] = Field(None, description="计划专项工程复建 ")
actual_spec_project_reconstr: Optional[float] = Field(None, description="实际专项工程复建 ")
plan_reservoir_bottom_cleanup: Optional[float] = Field(None, description="计划库底清理 ")
actual_reservoir_bottom_cleanup: Optional[float] = Field(None, description="实际库底清理 ")
class LarMainInfoUpdateSchema(BaseResponseWithID):
id: str = Field(..., description="移民征地id")
project_id: str = Field(..., description="项目id")
plan_urban_comp: float = Field(..., description="计划城镇补偿金额 ")
actual_urban_comp: float = Field(..., description="实际城镇补偿金额 ")
plan_rural_comp: float = Field(..., description="计划农村补偿金额 ")
actual_rural_comp: float = Field(..., description="实际农村补偿金额 ")
plan_spec_project_reconstr: float = Field(..., description="计划专项工程复建 ")
actual_spec_project_reconstr: float = Field(..., description="实际专项工程复建 ")
plan_reservoir_bottom_cleanup: float = Field(..., description="计划库底清理 ")
actual_reservoir_bottom_cleanup: float = Field(..., description="实际库底清理 ")
@field_validator(
"plan_urban_comp",
"actual_urban_comp",
"plan_rural_comp",
"actual_rural_comp",
"plan_spec_project_reconstr",
"actual_spec_project_reconstr",
"plan_reservoir_bottom_cleanup",
"actual_reservoir_bottom_cleanup",
mode="before",
)
def check_amount_field(cls, v):
from fastapi import HTTPException
if v is None or v == "":
raise HTTPException(detail='金额字段不能为空', status_code=400)
if float(v) < 0:
raise HTTPException(detail='金额字段需大于等于0', status_code=400)
return v
class LarResettlementSchema(BaseResponseWithID):
id: str = Field(..., description="移民征地id")
project_id: str = Field(..., description="项目id")
plan_resettlement_pop: int = Field(..., description="计划搬迁人数")
completed_resettlement_pop: int = Field(..., description="完成搬迁人数")
@field_validator(
"plan_resettlement_pop",
"completed_resettlement_pop",
mode="before",
)
def check_amount_field(cls, v):
from fastapi import HTTPException
if v is None or v == "":
raise HTTPException(detail='搬迁人数不能为空', status_code=400)
if float(v) < 0:
raise HTTPException(detail='搬迁人数需大于等于0', status_code=400)
return v
class LarInvestmentSchema(BaseResponseWithID):
id: str = Field(..., description="移民征地id")
project_id: str = Field(..., description="项目id")
plan_investment_amt: float = Field(..., description="计划投资金额")
completed_investment_amt: float = Field(..., description="完成投资金额")
@field_validator(
"plan_investment_amt",
"completed_investment_amt",
mode="before",
)
def check_amount_field(cls, v):
from fastapi import HTTPException
if v is None or v == "":
raise HTTPException(detail='金额字段不能为空', status_code=400)
if float(v) < 0:
raise HTTPException(detail='金额字段数需大于等于0', status_code=400)
return v
class LarChangeDetailSchema(BaseResponseWithID):
project_id: str = Field(..., description="项目ID")
title: Optional[str] = Field(None, description="变更事项")
reason: Optional[str] = Field(None, description="变更理由")
before_amount: Optional[float] = Field(None, description="变更前金额")
after_amount: Optional[float] = Field(None, description="变更后金额")
change_time: Optional[str] = Field(None, description="变更时间")
attachment_ids: List[str] = Field(default_factory=list, description="附件ID列表", examples=[[]])
created_at: Optional[str] = Field(None, description="创建时间")
created_by_name: Optional[str] = Field(None, description="创建人")
change_amount: Optional[float] = Field(None, description="变更金额")
change_percentage: Optional[str] = Field('', description="变更比例")
approval_status: Optional[str] = Field(None, description="审批状态")
attachment_info: List[dict] = Field(
default_factory=list, description="文件信息", examples=[[
{
"id": "54a0daf903a04c8e87cea1175458459d",
"name": "54a0daf903a04c8e87cea1175458459d.pdf",
"original_name": "新用户注册申请表-项目公司.pdf",
"url": "/api/file_download/54a0daf903a04c8e87cea1175458459d"
}
]]
)
class LarChangeInfoSchema(BaseResponseWithID):
title: Optional[str] = Field(None, description="变更事项")
reason: Optional[str] = Field(None, description="变更理由")
before_amount: Optional[float] = Field(None, description="变更前金额")
after_amount: Optional[float] = Field(None, description="变更后金额")
change_time: Optional[str] = Field(None, description="变更时间")
attachment_ids: List[str] = Field(default_factory=list, description="附件ID列表", examples=[[]])
approval_status: Optional[str] = Field(None, description="审批状态")
before_amount_is_edit: Optional[bool] = Field(None, description="变更前金额是否可编辑")
changed_count: Optional[int] = Field(None, description="已办更次数")
class LarChangeListSchema(BaseModel):
page: int
page_size: int
total: int
list: List[LarChangeDetailSchema]
class LarChangeCreateSchema(BaseModel):
title: str = Field(..., description="变更事项")
reason: str = Field(..., description="变更理由")
before_amount: float = Field(..., description="变更前金额")
after_amount: float = Field(..., description="变更后金额")
change_time: DateStr = Field(..., description="变更时间")
attachment_ids: List[str] = Field(default_factory=list, description="附件ID列表", examples=[[]])
project_id: str = Field(..., description="项目id")
@field_validator(
"before_amount",
"after_amount",
mode="before",
)
def check_amount_field(cls, v):
from fastapi import HTTPException
if v is None or v == "":
raise HTTPException(detail='金额字段不能为空', status_code=400)
if float(v) < 0:
raise HTTPException(detail='金额字段需大于等于0', status_code=400)
return v
@field_validator(
"change_time",
mode="before",
)
def check_actual_time_field(cls, v):
from fastapi import HTTPException
if v is None or v == "":
raise HTTPException(detail='移民变更时间必填', status_code=400)
if v > get_current_date():
raise HTTPException(detail='移民变更时间不能大于当前日期', status_code=400)
return v
class LarChangeUpdateSchema(LarChangeCreateSchema):
id: str = Field(..., description="移民变更id")
schemas/project_extensions/preparation.py
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from pydantic import BaseModel, Field,field_validator
from typing import Optional
from ..common.base import BaseResponseWithID
from ..common.datetime import datetime_date,get_current_date
from fastapi import HTTPException
from ..common.validators import DateStr
class PostPreparation(BaseModel):
id:str = Field(..., description="里程碑ID")
code: str= Field(..., description="里程碑的节点编码")
acquire_date: DateStr|None = Field(None,description="取得时间")
is_exist: bool= Field(..., description="是否取得")
@field_validator('acquire_date')
def validate_acquire_date(cls, v: Optional[DateStr]) -> Optional[DateStr]:
if v is None:
return None
try:
actual = datetime_date(v)
except ValueError:
raise HTTPException(status_code=400,detail='日期格式为(YYYY-MM-DD)')
today = datetime_date(get_current_date())
if actual > today:
raise HTTPException(status_code=400,detail='取得时间不能晚于今天')
return v
class PreparationDetail(BaseResponseWithID):
id: Optional[str] = Field(None, description="里程碑ID")
project_id: Optional[str] = Field(None, description="项目ID")
code: Optional[str] = Field(None, description="里程碑节点编码")
acquire_date: Optional[DateStr] = Field(None, description="取得时间")
is_exist: Optional[bool] = Field(None, description="是否取得")
approval_status: Optional[str] = Field(None, description="审批状态")
name: Optional[str] = Field(None, description="里程碑名称")
group: Optional[str] = Field(None, description="分组条件", examples=['KGTJLS'])
is_acquired: Optional[int] = Field(0, description="是否取得")
schemas/project_extensions/production.py
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from pydantic import BaseModel, Field, field_validator
from typing import Optional
from ..common.base import BaseResponseWithID
from ..common.datetime import datetime_date, get_current_date
from fastapi import HTTPException
from ..common.validators import DateStr
class PostProduction(BaseModel):
id: str = Field(..., description="投产节点ID")
code: str = Field(..., description="节点编码")
acquire_date: DateStr | None = Field(None, description="取得时间")
is_exist: bool = Field(..., description="是否取得")
@field_validator('acquire_date')
def validate_acquire_date(cls, v: Optional[DateStr]) -> Optional[DateStr]:
if v is None:
return None
try:
actual = datetime_date(v)
except ValueError:
raise HTTPException(status_code=400, detail='日期格式为(YYYY-MM-DD)')
today = datetime_date(get_current_date())
if actual > today:
raise HTTPException(status_code=400, detail='取得时间不能晚于今天')
return v
class ProductionDetail(BaseResponseWithID):
id: Optional[str] = Field(None, description="投产节点ID")
project_id: Optional[str] = Field(None, description="项目ID")
code: Optional[str] = Field(None, description="投产节点编码")
acquire_date: Optional[DateStr] = Field(None, description="取得时间")
is_exist: Optional[bool] = Field(None, description="是否取得")
approval_status: Optional[str] = Field(None, description="审批状态")
name: Optional[str] = Field(None, description="投产节点名称")
is_acquired: Optional[int] = Field(0, description="是否取得")
schemas/project_extensions/project_detail.py
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"""
项目容量信息schema
只提供返回，不提供更新接口
"""
from enum import Enum
from pydantic import BaseModel, Field
from typing import Optional, List
from ..common.base import BaseResponseWithID
class ProjectDetailKey(str, Enum):
"""项目子类类型枚举"""
PLAN_CONSTRUCTION = "plan_construction" # 计划在建容量
ACTUAL_CONSTRUCTION = "actual_construction" # 实际在建容量
PRODUCTION = "production" # 投产容量
ENSURE_PRODUCTION = "ensure_production" # 确保容量
CLIMB_PRODUCTION = "climb_production" # 登高容量
CHALLENGE_PRODUCTION = "challenge_production" # 揭榜容量
COMPLETE_INVESTMENT = "complete_investment" # 完成投资容量
class CapacityItem(BaseModel):
year: Optional[int] = Field(None, description='年')
date: Optional[str] = Field(None, description="日期，格式YYYY-MM-DD")
capacity: float = Field(..., description='容量')
is_audit: Optional[bool] = Field(False, description='是否可编辑')
class ProjectDetailProject(BaseResponseWithID):
project_id:str= Field(..., description="所属项目ID", examples=["project123"])
key: Optional[ProjectDetailKey] = Field(None, description='项目子类类型')
value: Optional[List[CapacityItem]] = Field(None, description='项目子类类型值')
schemas/project_multi_type/__init__.py
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from .photovotaic import PhotovoltaicExtension
from .onshore_wind import OnShoreWindExtension
from .offshore_wind import OffShoreWindExtension
from .hydropower import HydropowerExtension
from .pumped_storage import PumpedStorageExtension
from .gas_turbine import GasTurbineExtension
from .thermal_power import ThermalPowerExtension
schemas/project_multi_type/gas_turbine.py
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from pydantic import BaseModel, Field
from typing import List, Optional, Literal
from ..common.validators import DateStr
class GasTurbineExtension(BaseModel):
"""
燃气轮机项目特定字段
"""
pass

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