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/config/config.yml.docker

@@ -0,0 +1,39 @@
+# Docker环境配置文件
+# 复制此文件为 config.yml 并修改账号密码
+
+# 应用配置
+app:
+  name: job-crawler
+  version: 1.0.0
+  debug: false
+
+# 八爪鱼API配置
+api:
+  base_url: https://openapi.bazhuayu.com
+  username: "your_username"
+  password: "your_password"
+  batch_size: 100
+  # 多任务配置
+  tasks:
+    - id: "00f3b445-d8ec-44e8-88b2-4b971a228b1e"
+      name: "青岛招聘数据"
+      enabled: true
+    - id: "task-id-2"
+      name: "任务2"
+      enabled: false
+
+# Kafka配置（Docker内部网络）
+kafka:
+  bootstrap_servers: kafka:29092
+  topic: job_data
+  consumer_group: job_consumer_group
+
+# 采集配置
+crawler:
+  interval: 300
+  filter_days: 7
+  max_workers: 5
+
+# 数据库配置
+database:
+  path: /app/data/crawl_progress.db