feat(job_crawler): initialize job crawler service with kafka integration

- 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

job_crawler/requirements.txt

@@ -0,0 +1,8 @@
+fastapi==0.109.0
+uvicorn==0.27.0
+httpx==0.27.0
+kafka-python==2.0.2
+apscheduler==3.10.4
+pydantic==2.5.3
+python-dotenv==1.0.0
+PyYAML==6.0.1