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Btrccts

Btrccts is an MIT-licensed Python library for backtesting cryptocurrency trading strategies and running them live through CCXT. It provides a backtest exchange with an interface compatible with CCXT; performance metrics require an additional library.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Btrccts — OpenViST project profile in Exchanges & Trading.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Btrccts when developing a Python trading algorithm and you can provide the historical market data needed for backtesting, or when you want to run an algorithm live through a CCXT exchange instance.

Who it is for

  • Python developers building cryptocurrency trading algorithms.
  • Strategy authors who want to use a CCXT-compatible exchange interface for both backtesting and live runs.

Documented uses

  • Run an algorithm over a selected historical date range and interval.
  • Read exchange OHLCV data and create exchange orders through a CCXT-style interface.
  • Switch an algorithm to live mode using the CLI.
Before you choose

Requirements & limits

The project is a public GitHub repository with an MIT license. Its README describes installation through the Python package manager and from a repository clone.

  • Backtest data must be supplied by the user and cover the full test period at one-minute intervals.
  • Live exchange credentials are read from the configuration directory.
  • Live mode can place exchange orders; it is enabled with the --live command-line parameter.
  • Performance metrics for trades and orders are outside the library’s stated scope and require an additional library.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Prepare historical data for a backtest

Provide the OHLCV data Btrccts requires for a chosen backtest period.

Before you start

  • A Btrccts algorithm and Python environment.
  • User-provided OHLCV CSV data covering the full test period at one-minute intervals.

Steps

  1. Run the algorithm with --help to find the data directory.

  2. Place the OHLCV file under data_directory/ohlcv/EXCHANGE/BASE/QUOTE.csv.

  3. Format the CSV with open, high, low, close and volume columns and timestamps.

  4. Run the algorithm with --start-date and --end-date for the period covered by the file.

Expected outcome

The algorithm has historical OHLCV data available for its specified backtest period.

Guide limitations

  • Btrccts does not provide the data files.
  • The data must cover the complete period and use one-minute intervals.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
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Sources checked
6 October 2026
Original website title
btrccts/btrccts · Official homepage title · retained in its source language
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