Python In The Job Market
summary
JobTech builds a pipeline that extracts skills from millions of online job posts weekly using Python and packages like FlashText, regular expressions, scikit‑learn, pandas, BeautifulSoup and Scrapy. Empirical numbers: Python appears ~6,000 times in job ads over July 2017–Apr 2018 (~500/month); simple dictionary checks take ~600µs but a 127k keyword list costs ~200ms (scales to hours over millions of docs). FlashText outperforms regex once keyword count >300 and beats regex by orders of magnitude on 137k terms, but needs preprocessing for extra whitespace and can miss spaced variants so regex is kept as a fallback.
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chapters (5)
- 0:00Introduction
- 2:11Python marketability in Singapore
- 3:59Python tools at JobTech
- 5:43Text extraction methods demo
- 15:29Results and summary
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