RusTalib, the Crustacean Financial Analyst 🦀

Meet Rustalib, your steadfast crustacean companion for navigating the currents of financial markets! This comprehensive Rust library, rustalib, provides a powerful toolkit for calculating technical indicators, all powered by the high-performance Polars DataFrame library.

Whether you're charting, backtesting, or building live trading systems, Rustalib is here to help you process market data with speed and precision.

Technical Indicators Library Icon

Project Overview

rustalib provides a robust, extensible, and efficient toolkit for quantitative finance, algorithmic trading, and data science in Rust. The library is designed for:

Fast, vectorized computation using Polars DataFrames
Easy integration with modern Rust data workflows
Modular design: Use only the indicators you need
Extensibility: Add your own indicators easily

Whether you are backtesting, researching, or building production trading systems, this crate offers a solid foundation for technical analysis in Rust.

Features

Wide range of indicators: Moving averages, oscillators, volatility, volume, trend, momentum, and more
Convenience functions: Add a suite of indicators to your DataFrame in one call
CSV and DataFrame workflows: Read, process, and save data efficiently
Well-documented and tested

Implemented Indicators

Moving Averages: SMA, EMA, WMA
Oscillators: RSI, MACD (line & signal)
Volatility: Bollinger Bands, %B, ATR, Garman-Klass Volatility
Volume: On-Balance Volume (OBV), Chaikin Money Flow (CMF)
Other: Price returns, daily range, lagged prices, rolling returns/volatility, cyclical time features

Installation

Add to your Cargo.toml:

[dependencies]
rustalib = "*" # Or specify a version
polars = { version = "0.46", features = ["lazy", "dtype-full"] }

Minimum Rust version: 1.70+
Polars compatibility: 0.46+

Usage Examples

1. Calculate a Simple Moving Average (SMA)

use polars::prelude::*;
use ta_lib_in_rust::indicators::moving_averages::calculate_sma;

fn main() -> PolarsResult<()> {
    let close = Series::new("close", &[10.0, 11.0, 12.0, 11.5, 12.5]);
    let mut df = DataFrame::new(vec![close.into()])?;
    let sma_3 = calculate_sma(&df, "close", 3)?;
    df.with_column(sma_3)?;
    println!("{}", df);
    Ok(())
}

2. Combine Multiple Indicators

use polars::prelude::*;
use ta_lib_in_rust::indicators::{
    moving_averages::calculate_ema,
    oscillators::calculate_rsi,
    volatility::calculate_bollinger_bands,
};

fn main() -> PolarsResult<()> {
    let close = Series::new("close", &[100.0, 102.0, 104.0, 103.0, 105.0]);
    let mut df = DataFrame::new(vec![close.clone().into()])?;
    let ema_3 = calculate_ema(&df, "close", 3)?;
    let rsi_3 = calculate_rsi(&df, 3, "close")?;
    let (bb_mid, bb_up, bb_low) = calculate_bollinger_bands(&df, 3, 2.0, "close")?;
    df = df.with_columns([ema_3, rsi_3, bb_mid, bb_up, bb_low])?;
    println!("{}", df);
    Ok(())
}

3. Reading Data from CSV and Saving Results

let df = CsvReadOptions::default()
    .with_has_header(true)
    .try_into_reader_with_file_path(Some("data.csv".into()))?
    .finish()?;

// Important: Ensure column names are lowercase for compatibility with indicators
let mut df = df.lazy()
    .select([
        col("Symbol").alias("symbol"),
        col("Timestamp").alias("timestamp"),
        col("Open").alias("open"),
        col("High").alias("high"),
        col("Low").alias("low"),
        col("Close").alias("close"),
        col("Volume").cast(DataType::Float64).alias("volume"),
    ])
    .collect()?;

// ... apply indicators ...
CsvWriter::new(std::io::BufWriter::new(std::fs::File::create("results.csv")?))
    .finish(&mut df)?;

Advanced Examples

See the examples/ directory for:

Basic indicator usage (SMA, EMA, RSI, MACD, Bollinger Bands, etc.)
CSV workflows for real-world data
Multi-stock analysis with cross-asset comparisons
Saving and analyzing results

Important Notes

Column Name Sensitivity

This library expects lowercase column names (open, high, low, close, volume) in DataFrames. When working with CSVs that might have different case formats (e.g., Open, High, etc.), make sure to rename the columns using Polars' selection and aliasing capabilities as shown in the examples above.

Contributing

Contributions are welcome! Please:

Open issues for bugs, questions, or feature requests
Submit pull requests for new indicators or improvements
Follow Rust best practices and add tests/docs for new code

License

MIT License. See LICENSE for details.

rustalib 1.0.8