My-Algo-Trading-Code

This contains all the code I have written for the signal generation and the front test where I fetch data using Dhan API

The code

Although I own the code, the coding itself was done entirely using GPT-5.4-xhigh, GPT-5.5-xhigh and Claude Opus 4.7 on Max effort. GPT wrote majority of the signal generators and the data fetch files. Claude wrote the big one - the multithreaded Front Test worker. I just did the reviews and the testing

What is included?

• Data extractors which extract historical data for NIFTY/BANKNIFTY/FINNIFTY indices
• The backtest files I used to backtest
• The signal generators I created to generate signals
• The main front test file which uses miltithreading to execute all strategies together

Pro Tip

You might have to adjust the import addresses from which the files are to be imported because the files are in different directories in my local machine(fixed in the latest Claude commit)

Repository structure

.
├── Nifty Multi Strategy Front Test - Master File.py   # multithreaded paper-trading runner
├── Data Extractors/                                   # 1m OHLC downloaders + shared helper
├── My Backtest Files (For Reference)/                 # backtesting.py-based backtests
└── Signal Generators/                                 # strategy / signal logic modules

Each subfolder has its own Readme.md with the details.

Setup

1. Python 3.10+ (I'm running 3.13).
2. Install dependencies:

   pip install dhanhq pandas numpy backtesting python-dotenv
   

3. Set Dhan credentials as environment variables:

   DHAN_CLIENT_CODE=your_client_code
   DHAN_TOKEN_ID=your_access_token
   

   The backtests and the front-test master file additionally each load a local .env from their own folder for tunable strategy parameters.

Typical workflow

1. Pull historical data — e.g. python "Data Extractors/Nifty 1m 5Y Data Fetch Dhan.py". The CSV lands in Backtest Outputs/.
2. Run a backtest against that CSV — e.g. python "My Backtest Files (For Reference)/Nifty Renko Strategy Backtest.py".
3. Once a strategy looks good, run Nifty Multi Strategy Front Test - Master File.py for paper-traded multi-strategy execution.

The Backtest Outputs/ folder is .gitignore-d, so generated CSVs/logs stay local.