techalib 0.1.0

Techalib: A TECHnical Analysis LIBrary

Techalib

Techalib is a fast, reliable, and ergonomic technical analysis library written in Rust, with seamless Python bindings.

Inspired by TA-LIB, Techalib has been extensively tested against it to ensure accuracy and performance.

🚧 Techalib is in active development. More features, indicators, and improvements will come.

📦 Installation

Rust

Available soon on Cargo

Python

Available soon on PyPI

📚 Documentation

Rust

Available soon

Python

Available soon

⚡ Benchmarks

Techalib matches TA-LIB in performance and, for specific indicators, achieves even faster execution through algorithmic optimizations.

📊 Supported indicators

The number of supported indicators is set to increase.

Category	Function name - Name	Status
Overlap
	bbands - Bollinger Bands	✅
	midpoint - MidPoint over period	✅
	midprice - Midpoint Price over period	✅
Moving Average	sma - Simple Moving Average	✅
	ema - Exponential Moving Average	✅
	wma - Weighted Moving Average	✅
	dema - Double Exponential Moving Average	✅
	tema - Triple Exponential Moving Average	✅
	trima - Triangular Moving Average	✅
	t3 - Tillson Triple Moving Average	✅
	kama - Kaufman Adaptive Moving Average	✅
Momentum
	macd - Moving Average Convergence Divergence	✅
	adx - Average Directional Movement Index	✅
	aroon - Aroon	✅
	dx - Directional Movement Index	✅
	minus_di - Minus Directional Indicator	✅
	minus_dm - Minus Directional Movement	✅
	plus_di - Plus Directional Indicator	✅
	plus_dm - Plus Directional Movement	✅
	roc - Rate of change	✅
	rocr - Rate of change ratio	✅
Oscillator	rsi - Relative Strength Index	✅
	aroonosc - Aroon Oscillator	✅
Volume
	ad - Chaikin A/D Line	✅
Volatility
	atr - Average True Range	✅

🤓 Contribution

To contribute to the techalib project, first fork the repository and create a new branch from upstream/main using a proper naming convention (feat/, fix/, etc.). Set up your development environment by installing Python, Rust, and project dependencies, then build the project and run tests. If you're adding a new indicator, use the provided tools to generate boilerplate code and test data, and follow the inserted TODO comments. Follow the commit message guidelines and rebase your branch onto the latest changes from upstream/main. Finally, open a pull request with a clear description, allow edits by maintainers, and be ready to respond to review feedback.

For a more detailed description please read this guidelines before submitting a pull request.