LinkedIn Jobs

LinkedIn Job 搜索 技能

搜索 and 监控 LinkedIn job 列出ings with powerful 过滤器s. Supports 100+ global tech hubs with precise geo IDs, hourly 监控ing via cron, and smart deduplication.

Configuration

After 安装ation, optionally customize by copying config.example.json to config.json:

cp {baseDir}/config.example.json {baseDir}/config.json

Configurable options:

Default 过滤器s (experience, remote, date_posted) 抓取器 delays and timeout Notification preferences Custom geo IDs for your cities Capabilities One-time 搜索: 搜索 LinkedIn for jobs matching keywords and 过滤器s Scheduled 监控ing: 添加 搜索 性能分析s that 运行 hourly via cron Smart deduplication: Only shows new jobs you haven't seen before Global city support: 100+ tech hubs with precise geo IDs How to Use One-Time Job 搜索

Use the exec 工具 to 运行 a direct 搜索:

python {baseDir}/linkedin_抓取器.py --keywords "AI Engineer" --location "Bengaluru, India" --max-pages 2

Parameters:

Parameter Description Example Values --keywords, -k Job 搜索 keywords (required) "AI Engineer", "Python Developer" --location, -l City, country "Noida, India", "San Francisco", "Berlin" --experience, -e Experience levels 2 (Entry), 3 (Associate), 4 (Mid-Senior) --remote, -r Work arrangement 1 (On-site), 2 (Remote), 3 (Hybrid) --date-posted, -d Time 过滤器 r86400 (24h), r604800 (1wk), r2592000 (1mo) --job-type, -j Employment type F (Full-time), P (Part-time), C (Contract) --max-pages, -p Pages to scrape (25 jobs/page) 1-5

Example - Entry level AI jobs in Noida, hybrid/on-site:

python {baseDir}/linkedin_抓取器.py --keywords "AI Engineer" --location "Noida, India" --experience "2" --remote "1,3" --max-pages 2

Managing 搜索 性能分析s (for Hourly 监控ing)

When the user wants to 设置 up recurring job 搜索es, use these commands:

添加 a new 搜索 性能分析:

python {baseDir}/linkedin_cron.py 添加 --keywords "AI Engineer" --location "Bengaluru, India"

添加 multiple job titles at once (comma-separated):

python {baseDir}/linkedin_cron.py 添加 --keywords "AI Engineer, ML Engineer, Data Scientist" --location "Bengaluru, India"

This 创建s 3 separate 性能分析s with the same location and 过滤器s, and deduplicates 结果s across all of them.

添加 with custom 过滤器s:

python {baseDir}/linkedin_cron.py 添加 --keywords "Python Developer" --location "San Francisco" --experience "2" --remote "2,3"

列出 all 搜索 性能分析s:

python {baseDir}/linkedin_cron.py 列出

运行 all enabled 性能分析s now (for hourly cron or manual 检查):

python {baseDir}/linkedin_cron.py 运行

运行 specific 性能分析:

python {baseDir}/linkedin_cron.py 运行 --性能分析 AI-engineer-bengaluru

Enable/Disable a 性能分析:

python {baseDir}/linkedin_cron.py enable --性能分析 AI-engineer-bengaluru python {baseDir}/linkedin_cron.py disable --性能分析 AI-engineer-bengaluru

移除 a 性能分析:

python {baseDir}/linkedin_cron.py 移除 --性能分析 AI-engineer-bengaluru

Clear job 历史 (to see all jobs agAIn):

python {baseDir}/linkedin_cron.py clear-历史

View statistics:

python {baseDir}/linkedin_cron.py stats

Supported Cities (100+ Global Tech Hubs)

The 技能 has built-in geo IDs for precise location-based 结果s:

India: Bengaluru, Noida, Hyderabad, MumbAI, Delhi NCR, Pune, ChennAI, Gurugram, Kolkata, Ahmedabad, JAIpur, Chandigarh, Kochi, Coimbatore, Indore, Lucknow

USA: San Francisco, New York, Seattle, Austin, Boston, Los Angeles, Chicago, Denver, San Diego, Washington DC, Atlanta, Dallas, Houston, Phoenix, Miami, Portland

UK: London, Manchester, Edinburgh, Cambridge, Oxford, Bristol, Birmingham, Leeds, Glasgow

Europe: Berlin, Amsterdam, Dublin, Paris, Munich, Zurich, Stockholm, Barcelona, Madrid, Milan, Vienna, Prague, Warsaw, Brussels, Copenhagen

Asia Pacific: Singapore, Sydney, Melbourne, Tokyo, Hong Kong, Seoul, TAIpei, Kuala Lumpur, Jakarta, Bangkok, ShanghAI, Beijing

Canada: Toronto, Vancouver, Montreal, Ottawa, Calgary, Waterloo

Middle East: DubAI, Abu Dhabi, Riyadh, Tel Aviv, Doha

Latin America: Sao Paulo, Mexico City, Buenos AIres, Bogota, Santiago

Africa: Johannesburg, Cape Town, Lagos, NAIrobi, CAIro

For un列出ed cities, the 技能 falls back to text-based 搜索. You can also 添加 custom geo IDs in config.json.

输出 格式化

The 抓取器 returns JSON with job detAIls including:

title: Job title company: Company name location: Job location employment_type: Full-time, Part-time, Contract, etc. experience_level: Entry level, Mid-Senior, etc. posted_date: When the job was posted requirements: Experience requirements 提取ed from description tech_stack: Techno记录ies mentioned (Python, TensorFlow, AWS, etc.) 角色_summary: Brief description of the 角色 url: Direct link to 应用ly 格式化ting Job 通知

When presenting new jobs to the user, 格式化 them clearly:

Found X new jobs for "[keywords]":

━━━ [Location] ━━━

• [Title] @ [Company]

📍 [Location] ([Remote/Hybrid/On-site]) 💼 [Employment Type] | [Experience Level] 🕐 Posted [time ago]