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license: apache-2.0
language:
- en
tags:
- finance
- reinforcement-learning
- gym
- trading
- backtesting
- rust
pretty_name: Chapaty Environments
---
# Chapaty Environments
[](https://discord.gg/MmMAB6NCuK)
[](https://github.com/LenWilliamson/chapaty)
[](https://crates.io/crates/chapaty)
This dataset repository hosts the pre-compiled financial environments for [**Chapaty**](https://github.com/LenWilliamson/chapaty), a Rust library for building quantitative trading agents in financial markets.
Inspired by OpenAI Gymnasium, these datasets provide standardized, easily reproducible simulation states for training and backtesting agents.
## What are these files?
The datasets here are serialized using `.postcard` (a highly efficient binary format for Rust). They contain environment configurations based on the version of the crate you are using.
## Versioning
This repository uses **branches** to align with Chapaty crate releases (e.g., `v1.1.0`).
When you use Chapaty in Rust, the library automatically binds to the correct branch matching your crate version, ensuring your agents are always evaluated on consistent data.
## Usage in Rust
**Fast Track:** Use the [**Chapaty Starter Template**](https://github.com/LenWilliamson/chapaty-template) to instantly bootstrap a new project. It includes pre-configured AI prompts for backtesting with a LLM of your choice, built-in dashboard setups with [Quantstats](https://github.com/ranaroussi/quantstats), and best-practice strategy examples.
You do not need to download these files manually. Use the Chapaty crate to load them directly into your async Rust application:
```rust
use anyhow::{Context, Result};
use chapaty::prelude::*;
#[tokio::main]
async fn main() -> Result<()> {
// Select a preset (e.g., Daily BTC/USDT with SMA 20 & 50)
let preset = EnvPreset::BinanceBtcUsdt1dSma20Sma50;
// Configure I/O to fetch seamlessly from Hugging Face
let file_stem = preset.to_string();
let loc = StorageLocation::HuggingFace { version: None };
let cfg = IoConfig::new(loc).with_file_stem(&file_stem);
// Load the environment (downloads and caches locally on first run)
let mut env = chapaty::load(preset, &cfg)
.await
.context("Failed to load trading environment")?;
println!("Successfully loaded environment for {}!", preset);
Ok(())
}
```
## Available Presets
Presets encode exact data source IDs to reproduce identical environments. Current presets include:
* `binance_btc_usdt1d`: BTC/USDT Daily Spot
* `ninja_trader_cme6eh6_1m_5m_us_emp_high`: EUR/USD 1m/5m Futures with US Employment News
* `binance_btc_usdt1h_1m_volume_profile1d_100_usdt`: BTC/USDT Multi-resolution Spot with Volume Profile
* *(And many more—see the [Chapaty Crate Documentation](https://docs.rs/chapaty) for the full `EnvPreset` list).*
## Disclaimer
**Trading and investing involve substantial risk. You may lose some or all of your capital.**
These datasets and the Chapaty library are provided for **research and educational purposes only** and do not constitute financial advice.
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