Analysis updated 2026-05-18
Upload your own Zerodha trade history to see how each trade scored against technical indicators.
Compare your actual trading decisions to what a simple rules based system would have done.
Identify which past trades broke discipline around stop losses or profit targets.
| themicrocapinvestor/aardtradeanalytics | 0xallam/my-recipe | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | Python | Python | Python |
| Last pushed | — | 2022-11-22 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 2/5 | 4/5 |
| Audience | general | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires your own Kite Connect API credentials and a manually exported Tradebook CSV from Zerodha.
AARD Tradebook Analytics is a personal tool built by a developer named Ayush that gives traders an honest look back at their own past trades. You upload an export of your trade history from the Indian brokerage Zerodha, and the app rebuilds each completed buy and sell into full round trip trades. It then scores every entry and exit point using technical analysis measures such as Stage Analysis, a composite technical score, and Relative Strength, all measured as they actually stood on your trade's real dates rather than today. Each trade is also replayed forward using a simple, fixed set of rules (a trailing stop loss, a profit target, and a maximum holding period) so you can compare what you actually did against what a plain, disciplined system would have done instead. To use it, you need your own Kite Connect developer credentials from Zerodha and a manually downloaded Tradebook CSV file, since that export is not available through their regular API. Everything runs using your own credentials and your own data, nothing is shared or stored on a central server. Setup involves installing Python dependencies, filling in your API keys, and running the app with Streamlit, a tool for building simple web apps in Python. You log in through Zerodha's Kite link each day, since the login expires every morning. The project only evaluates trades that are fully closed, since an open position has not yet had the chance to prove itself right or wrong, and it skips certain hard to match stock listings while reporting that they were skipped rather than hiding them. The replay strategy used for comparison is intentionally simple and is meant as a plain baseline, not a claim that it is the best possible trading system. This is explicitly not investment advice or a signal generating tool. It only describes what already happened in your trading history. The project is not affiliated with Zerodha or Kite Connect, and it is released under the MIT License, so anyone can use, change, and redistribute the code, including for commercial purposes, as long as the license notice stays with it.
A personal Streamlit tool that reconstructs your Zerodha trade history and scores each trade against technical indicators to show what disciplined trading would have looked like.
Mainly Python. The stack also includes Python, Streamlit, Kite Connect API.
Free to use, modify, and redistribute, including for commercial purposes, as long as you keep the license notice.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.