李顺东
ae681575b9
- Add technical documentation (技术方案.md) with system architecture and design details - Create FastAPI application structure with modular organization (api, core, models, services, utils) - Implement job data crawler service with incremental collection from third-party API - Add Kafka service integration with Docker Compose configuration for message queue - Create data models for job listings, progress tracking, and API responses - Implement REST API endpoints for data consumption (/consume, /status) and task management - Add progress persistence layer using SQLite for tracking collection offsets - Implement date filtering logic to extract data published within 7 days - Create API client service for third-party data source integration - Add configuration management with environment-based settings - Include Docker support with Dockerfile and docker-compose.yml for containerized deployment - Add logging configuration and utility functions for date parsing - Include requirements.txt with all Python dependencies and README documentation
14 lines
294 B
Python
14 lines
294 B
Python
"""数据模型"""
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from .job import JobData
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from .progress import CrawlProgress, CrawlStatus
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from .response import ApiResponse, ConsumeResponse, StatusResponse
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__all__ = [
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"JobData",
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"CrawlProgress",
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"CrawlStatus",
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"ApiResponse",
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"ConsumeResponse",
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"StatusResponse"
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]
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