Flask in Five
summary
Repository clones and a single setup.command Bash script create a Python venv, install numpy pandas flask, and scaffold app/, static/, templates/ and move a tab‑delimited S&P 500 file into data. Exporting FLASK_APP to the provided lightning app and running flask serves an HTML table that randomly selects 10 of 500 symbols on each refresh. The site runs locally in under five minutes with debug off and the page renders as shown.
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