Open Source Python Web Analytics Software

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Web site statistic system - The sytem collects any sort of data about a web site, store in a data base and present statistics in html form (popularity of the site, speed or quality of service, state of the server, traffic to other sites, etc. ).

PostHog is an all‑in‑one open‑source platform for product and web analytics—offering event-based analytics, session recording, feature flagging, A/B testing, cohorts, and more—that you can self‑host, with full support for data privacy and enterprise compliance. Sync data from external tools like Stripe, Hubspot, your data warehouse, and more. Query it alongside your product data. Run custom filters and transformations on your incoming data. Send it to 25+ tools or any webhook in real time or batch export large amounts to your warehouse. Capture traces, generations, latency, and cost for your LLM-powered app.

This project aims to create a Python SQLite based data offline/online analytics program targetted mainly on web analytics. The main development would involve a complete python powered (C/C++ intermediate wrappers if required) sqlite analysis engine.

Modern, privacy-friendly, and detailed web analytics that works without cookies or JS. There are a lot of web analytics tools. Unfortunately, most of them come with the following caveats. They require handing all of your visitors' info to a third-party company They use cookies to track visitors across sessions, so you need to have those annoying cookie notices. They collect so much personal data that even the NSA is jealous. They are closed source and/or expensive, often with limited data portability. They are hard to use. Shynet has none of these caveats. You host it yourself, so the data is yours. It works without cookies, so you don't need any intrusive cookie notices. It collects just enough data to be useful, but not enough to be creepy. It's open source and intended to be self-hosted. And you may even find the interface easy to use.

A web script for counting unique hits and stores the http header information for each hit in a MySQL database. The script also creates a .html document for viewing all hits contained in the database. The script is written in python.