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https://github.com/rust-ta/kand

A Blazingly Fast Technical Analysis Library in Rust and Python.
https://github.com/rust-ta/kand

finance financial indicator quant series-analysis stocks ta-lib technical-analysis

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A Blazingly Fast Technical Analysis Library in Rust and Python.

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README 

        


  Kand Logo





  

    Crates.io

  

  

    Docs.rs

  

  

    PyPI Version

  

  

    Python Versions

  

  

    CI Status

  

  

    License

  





  Documentation:

  Rust

  -

  Python

  |

  Repository:

  GitHub





  Kand: A Blazingly Fast Technical Analysis Library, written in Rust.




> ⚠️ **Development Status**: This project is under active development. APIs may change, and some features might not be fully implemented or tested yet. Contributions and feedback are welcome!





  

    EMA Performance Comparison

  






  EMA calculation performance comparison across different implementations.




## Why Kand?



- **⚡ Unmatched Performance**

  Built in Rust, delivering blazing speed and memory safety, rivaling TALib’s peak.



- **🔓 Multithreading Unleashed**

  Breaks free from Python’s GIL, enabling seamless parallel processing beyond single-threaded limits.



- **⚙️ Real-Time Incremental Core**

  O(1) complexity updates, redefining high-efficiency computation.



- **🚀 Native Zero-Copy**

  Deeply integrated with NumPy, ensuring lossless data flow at maximum speed.



- **📊 Pioneering Indicators**

  Features advanced tools like Vegas, VWAP, and Supertrend, pushing analysis frontiers.



- **📦 Lightweight & Effortless**

  Ultra-compact package with one-line install—no bloat, no complex dependencies.



- **💻 Universal Compatibility**

  Runs flawlessly across macOS, Linux, and Windows.



Dive deeper at our [official documentation](https://rust-ta.github.io/kand/about).



#### Python API



The Python interface of `kand` leverages PyO3 for ultra-low latency bindings (~7ns overhead) to the Rust core, seamlessly integrating with NumPy for zero-copy operations and true thread-safe calculations. Below are examples for batch and incremental usage.



```python

import numpy as np

from kand import ema



# Batch EMA computation with zero-copy NumPy integration

prices = np.array([10.0, 11.0, 12.0, 13.0, 14.0], dtype=np.float64)

ema_values = ema(prices, period=3)



# Incremental EMA update for streaming data

prev_ema = 13.5

new_price = 15.0

new_ema = ema_inc(new_price, prev_ema, period=3)

```



**Key Features:**



- **Zero-Copy**: Operates directly on NumPy arrays, avoiding memory duplication.

- **GIL-Free**: Rust backend releases the Python GIL, enabling parallel execution.

- **Incremental Updates**: O(1) complexity for real-time applications.



---



#### Rust API



The Rust interface in `kand` provides a high-performance, type-safe implementation of EMA with flexible parameter control. It supports both Vec and ndarray inputs for batch and incremental calculations, as shown below.



```rust

use kand::ohlcv::ema;

use ndarray::Array1;



// Batch EMA calculation over a price series

let prices = vec![10.0, 11.0, 12.0, 13.0, 14.0];

let mut ema_values = vec![0.0; prices.len()];

ema::ema(&prices, 3, None, &mut ema_values)?;



// Batch EMA with ndarray for scientific workflows

let prices = Array1::from_vec(vec![10.0, 11.0, 12.0, 13.0, 14.0]);

let mut ema_values = Array1::zeros(prices.len());

ema::ema(&prices, 3, None, &mut ema_values)?;



// Constant-time incremental EMA update

let prev_ema = 13.5;

let new_price = 15.0;

let new_ema = ema::ema_inc(new_price, prev_ema, 3, None)?;

```



**Key Features:**



- **Memory Efficiency**: Leverages mutable buffers (`&mut Vec` or `&mut Array1`) to store results, slashing memory allocations.

- **Error Handling**: Returns `Result<(), KandError>` or `Result` for reliable failure detection (e.g., invalid period, NaN inputs).

- **Incremental Design**: O(1) updates tailored for real-time systems.



---



## Setup



### Python



Get started with Kand in one command - no extra configuration needed:



```bash

pip install kand

```



### Rust



You can take latest release from [`crates.io`](https://crates.io/crates/kand), or if you want to use the latest features / performance improvements point to the `main` branch of this repo.



```toml

[dependencies]

kand = { git = "https://github.com/rust-ta/kand", rev = "" }

```



Recommend Rust version `>=1.80`.



## Functions List



### OHLCV Based



- [x] **AD** - Chaikin A/D Line

- [x] **ADOSC** - Chaikin A/D Oscillator

- [x] **ADR** - Average Daily Range

- [x] **ADX** - Average Directional Movement Index

- [x] **ADXR** - Average Directional Movement Index Rating

- [ ] **APO** - Absolute Price Oscillator

- [x] **AROON** - Aroon

- [x] **AROONOSC** - Aroon Oscillator

- [x] **ATR** - Average True Range

- [x] **BBANDS** - Bollinger Bands

- [x] **BOP** - Balance Of Power

- [x] **CCI** - Commodity Channel Index

- [x] **CDL_DOJI** - Doji

- [x] **CDL_DRAGONFLY_DOJI** - Dragonfly Doji

- [x] **CDL_GRAVESTONE_DOJI** - Gravestone Doji

- [x] **CDL_HAMMER** - Hammer

- [x] **CDL_INVERTED_HAMMER** - Inverted Hammer

- [x] **CDL_LONG_LOWER_SHADOW** - Long Lower Shadow

- [x] **CDL_LONG_UPPER_SHADOW** - Long Upper Shadow

- [x] **CDL_MARUBOZU** - Marubozu

- [ ] **CMO** - Chande Momentum Oscillator

- [x] **DEMA** - Double Exponential Moving Average

- [x] **DX** - Directional Movement Index

- [x] **EMA** - Exponential Moving Average

- [x] **ECL** - Expanded Camarilla Levels **[Untested]**

- [x] **HA** - Heikin Ashi Chart

- [ ] **HT_DCPERIOD** - Hilbert Transform - Dominant Cycle Period

- [ ] **HT_DCPHASE** - Hilbert Transform - Dominant Cycle Phase

- [ ] **HT_PHASOR** - Hilbert Transform - Phasor Components

- [ ] **HT_SINE** - Hilbert Transform - SineWave

- [ ] **HT_TRENDLINE** - Hilbert Transform - Instantaneous Trendline

- [ ] **HT_TRENDMODE** - Hilbert Transform - Trend vs Cycle Mode

- [ ] **KAMA** - Kaufman Adaptive Moving Average

- [ ] **LINEARREG** - Linear Regression

- [ ] **LINEARREG_ANGLE** - Linear Regression Angle

- [ ] **LINEARREG_INTERCEPT** - Linear Regression Intercept

- [ ] **LINEARREG_SLOPE** - Linear Regression Slope

- [x] **MACD** - Moving Average Convergence/Divergence **[Unstable]**

- [ ] **MACDEXT** - MACD with controllable MA type

- [ ] **MAMA** - MESA Adaptive Moving Average

- [x] **MEDPRICE** - Median Price

- [x] **MFI** - Money Flow Index **[No Incremental]**

- [x] **MIDPOINT** - MidPoint over period

- [x] **MIDPRICE** - Midpoint Price over period

- [x] **MINUS_DI** - Minus Directional Indicator

- [x] **MINUS_DM** - Minus Directional Movement

- [x] **MOM** - Momentum

- [x] **NATR** - Normalized Average True Range

- [x] **OBV** - On Balance Volume

- [x] **PLUS_DI** - Plus Directional Indicator

- [x] **PLUS_DM** - Plus Directional Movement

- [ ] **PPO** - Percentage Price Oscillator

- [ ] **RENKO** - Renko Chart

- [x] **RMA** - Rolling Moving Average

- [x] **ROC** - Rate of change : ((price/prevPrice)-1)*100

- [x] **ROCP** - Rate of change Percentage: (price-prevPrice)/prevPrice

- [x] **ROCR** - Rate of change ratio: (price/prevPrice)

- [x] **ROCR100** - Rate of change ratio 100 scale: (price/prevPrice)*100

- [x] **RSI** - Relative Strength Index

- [x] **SAR** - Parabolic SAR

- [ ] **SAREXT** - Parabolic SAR - Extended

- [x] **SMA** - Simple Moving Average

- [x] **STOCH** - Stochastic **[No Incremental]**

- [ ] **STOCHF** - Stochastic Fast

- [ ] **STOCHRSI** - Stochastic Relative Strength Index

- [x] **SUPERTREND** - Super Trend Indicator

- [x] **T3** - Triple Exponential Moving Average (T3)

- [x] **TEMA** - Triple Exponential Moving Average

- [x] **TRANGE** - True Range

- [x] **TRIMA** - Triangular Moving Average

- [x] **TRIX** - 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA

- [ ] **TSF** - Time Series Forecast

- [x] **TYPPRICE** - Typical Price

- [ ] **ULTOSC** - Ultimate Oscillator

- [x] **VEGAS** - VEGAS Channel and Trend Boundary EMAs **[Untested]**

- [x] **VWAP** - Volume Weighted Average Price

- [x] **WCLPRICE** - Weighted Close Price

- [x] **WILLR** - Williams' %R

- [x] **WMA** - Weighted Moving Average



### Statistical Analysis



- [ ] **ALPHA** - Alpha: Measures excess returns over market

- [ ] **BETA** - Beta: Measures sensitivity to market volatility

- [ ] **CALMAR** - Calmar Ratio: Annual return to maximum drawdown ratio

- [ ] **CORREL** - Pearson's Correlation Coefficient

- [ ] **DRAWDOWN** - Maximum Drawdown: Maximum potential loss

- [ ] **KELLY** - Kelly Criterion: Optimal position sizing

- [x] **MAX** - Highest value over a specified period

- [x] **MIN** - Lowest value over a specified period

- [ ] **SHARPE** - Sharpe Ratio: Risk-adjusted return measure

- [ ] **SORTINO** - Sortino Ratio: Downside risk-adjusted returns

- [x] **STDDEV** - Standard Deviation

- [x] **SUM** - Summation

- [x] **VAR** - Variance

- [ ] **WINRATE** - Win Rate: Strategy success probability



## Contributing



We are passionate about supporting contributors of all levels of experience and would love to see

you get involved in the project. See the

[contributing guide](https://github.com/rust-ta/kand/blob/main/CONTRIBUTING.md) to get started.



## License



This project is licensed under either of the following licenses, at your option:

- Apache License, Version 2.0, ([LICENSE-APACHE](LICENSE-APACHE) or

  )

- MIT license ([LICENSE-MIT](LICENSE-MIT) or )



Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in kand by you, as defined in the Apache-2.0 license, shall be dually licensed as above, without any additional terms or conditions.