backtide

Test the idea. Trade the evidence.

A refreshingly simple backtesting and paper trading platform for retail investors


📜 Overview

General Information
Repository Project Status: Active License: MIT Downloads PyPI version
Build Publish Linting and tests codecov
Code Python uv-managed PEP8 ruff ty

Home Experiment
Results Paper trading
Storage Analysis

💡 Introduction

Backtide is an open-source backtesting platform for Python, built for retail investors who want to test trading ideas without drowning in complexity. A Rust-powered core keeps simulations and paper execution fast, while sensible defaults let you go from raw multi-exchange data to validated strategies in just a few lines of code. Run the same strategy objects against historical bars or public exchange WebSockets, without connecting a brokerage account.


❗ Why you should use Backtide?

  • Fast — Rust-powered engine runs backtests in a fraction of a second.
  • Simple — Sensible defaults mean a working backtest in minutes, not hours of configuration.
  • Flexible — Every parameter is exposed and customizable when you need full control.
  • Multi-exchange — Stocks, ETFs, forex and crypto from Yahoo, Binance, Kraken and more.
  • Batteries included — Built-in strategies and technical indicators out of the box.
  • Rich analytics — 20+ plots cover PnL, returns, drawdown and more.
  • Live paper trading — Apply strategies to Binance, Coinbase, or Kraken WebSocket candles with local simulated fills.
  • Interactive UI — A packaged Vue app configures, runs, and analyzes backtests and paper sessions visually.
  • Simple installation — Python wheels include the Rust extension and production frontend; users do not need Rust or Node.js.
  • Open source — MIT-licensed, community-driven and free forever.

Installation

Install the wheel and launch the local application:

pip install backtide
backtide launch

That single Python installation includes the compiled backend and web frontend.


📈 Performance

Based on comprehensive benchmarks:

Data download & storage

Operation Performance Use Case
OHLC download (1 symbol - 1m)* ~33ms Data ingestion
OHLC download (1 symbol - 1d)* ~31ms Data ingestion
Batch insert (100 bars) ~20ms Bulk processing
Batch insert (10k bars) ~45ms Bulk processing
Historical read (1000 bars) ~1.5ms Backtesting
Historical read (1M bars) ~711ms Backtesting

*Downloads hit real network endpoints. Yahoo Finance applies rate limits, so these numbers are meant as a reference, not as a real benchmark.


Backtest (11k bars)

Strategy Performance Use Case
Buy & Hold ~1.1ms Backtesting
ROC Rotation ~1.1ms Backtesting
RSRS Rotation ~1.1ms Backtesting
Multi-BB Rotation ~1.2ms Backtesting
ROC ~1.3ms Backtesting
Triple RSI Rotation ~1.5ms Backtesting
VCP ~1.5ms Backtesting
RSRS ~1.7ms Backtesting
Double Top ~2.2ms Backtesting
Momentum ~4.1ms Backtesting
SMA Naive ~4.2ms Backtesting
Alpha RSI Pro ~4.5ms Backtesting
Turtle Trading ~4.6ms Backtesting
Risk Averse ~4.9ms Backtesting
BB Mean Reversion ~5.5ms Backtesting
MACD ~6.3ms Backtesting
Adaptive RSI ~7.4ms Backtesting
SMA Crossover ~7.7ms Backtesting
Hybrid Alpha RSI ~7.9ms Backtesting
RSI ~8.8ms Backtesting

📘 Documentation

Relevant links
⭐ About Learn more about the package.
🚀 Getting started New to backtide? Here's how to get you started!
👨‍💻 User guide How to use backtide and its features.
🎛️ API Reference The detailed reference for backtide's API.
❔ FAQ Get answers to frequently asked questions.
🔧 Contributing Do you wan to contribute to the project? Read this before creating a PR.
🌳 Dependencies Which other packages does backtide depend on?
📃 License Copyright and permissions under the MIT license.__

Project links

Data verified by PyPI on Aug 20, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.3.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for tvdboom from gravatar.com tvdboom

Credits

Author: Mavs

GitHub Statistics

Data verified by PyPI on Aug 20, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python <3.15, >=3.11

Provides Extra

full

Tags

Trading Backtesting Financial markets Stocks ETF Forex Crypto

Classifiers

Report project as malware

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0.3.0

15 files

0.2.1

15 files

This release

0.2.0 This release

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0.1.5

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0.1.0

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