07088e60e9
Phase 1 Backend Implementation: - ✅ MongoDB data models (Keyword, Pipeline, User, Application) - ✅ Pydantic schemas for all models with validation - ✅ KeywordService: Full CRUD, filtering, pagination, stats, toggle status - ✅ PipelineService: Full CRUD, start/stop/restart, logs, config management - ✅ Keywords API: 8 endpoints with complete functionality - ✅ Pipelines API: 11 endpoints with complete functionality - ✅ Updated TODO.md to reflect completion Key Features: - Async MongoDB operations with Motor - Comprehensive filtering and pagination support - Pipeline logging system - Statistics tracking for keywords and pipelines - Proper error handling with HTTP status codes - Type-safe request/response models Files Added: - models/: 4 data models with PyObjectId support - schemas/: 4 schema modules with Create/Update/Response patterns - services/: KeywordService (234 lines) + PipelineService (332 lines) Files Modified: - api/keywords.py: 40 → 212 lines (complete implementation) - api/pipelines.py: 25 → 300 lines (complete implementation) - TODO.md: Updated checklist with completed items Next Steps: - UserService with authentication - ApplicationService for OAuth2 - MonitoringService - Redis integration - Frontend implementation 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
56 lines
2.0 KiB
Python
56 lines
2.0 KiB
Python
from datetime import datetime
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from typing import Optional, Dict, Any
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from pydantic import BaseModel, Field
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from bson import ObjectId
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class PyObjectId(ObjectId):
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"""Custom ObjectId type for Pydantic"""
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@classmethod
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def __get_validators__(cls):
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yield cls.validate
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@classmethod
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def validate(cls, v):
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if not ObjectId.is_valid(v):
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raise ValueError("Invalid ObjectId")
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return ObjectId(v)
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@classmethod
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def __get_pydantic_json_schema__(cls, field_schema):
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field_schema.update(type="string")
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class Keyword(BaseModel):
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"""Keyword data model for pipeline management"""
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id: Optional[PyObjectId] = Field(default=None, alias="_id")
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keyword: str = Field(..., min_length=1, max_length=200)
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category: str = Field(..., description="Category: people, topics, companies")
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status: str = Field(default="active", description="Status: active, inactive")
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pipeline_type: str = Field(default="all", description="Pipeline type: rss, translation, all")
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priority: int = Field(default=5, ge=1, le=10, description="Priority level 1-10")
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metadata: Dict[str, Any] = Field(default_factory=dict)
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created_at: datetime = Field(default_factory=datetime.utcnow)
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updated_at: datetime = Field(default_factory=datetime.utcnow)
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created_by: Optional[str] = Field(default=None, description="User ID who created this keyword")
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class Config:
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populate_by_name = True
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arbitrary_types_allowed = True
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json_encoders = {ObjectId: str}
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json_schema_extra = {
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"example": {
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"keyword": "도널드 트럼프",
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"category": "people",
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"status": "active",
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"pipeline_type": "all",
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"priority": 8,
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"metadata": {
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"description": "Former US President",
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"aliases": ["Donald Trump", "Trump"]
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},
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"created_by": "admin"
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}
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}
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