Open-source alternatives to PENDAX SDK

pybroker is a Python algorithmic trading framework and quantitative technical analysis library designed for developing, testing, and optimizing trading strategies using historical market data. It functions as a trading strategy backtester and a financial performance evaluator, providing a structured environment to simulate trading rules and analyze their statistical reliability. The framework distinguishes itself through a market data integration layer that handles the fetching and caching of historical price data from external providers. It incorporates an event-driven backtesting engine and

Vibe-Trading is a system for automated financial trading and algorithmic market research. It uses autonomous agents to manage financial assets and execute trades based on predefined rules and logic. The project features a multi-agent collaborative workflow that coordinates specialized agents to perform joint research and risk reviews. It utilizes large language model orchestration to map natural language prompts to executable data loaders and backtesting functions. The platform includes capabilities for quantitative strategy backtesting and alpha benchmarking using information coefficients t

StockSharp is an algorithmic trading platform and quantitative framework used for developing and deploying trading robots across stock, forex, and cryptocurrency markets. It functions as a multi-asset trading gateway and a dedicated development environment for building, debugging, and scheduling automated strategies. The platform includes a visual strategy workflow editor that maps logic blocks to executable code and a simulation engine that replays historical tick data to validate trading logic. It utilizes a plugin-based broker integration system to normalize diverse exchange protocols into

Quantaxis is a quantitative trading framework designed for building, backtesting, and executing automated strategies across global equities, futures, and cryptocurrencies. It integrates an event-driven backtesting engine, a multi-market execution gateway for order routing, and a quantitative data pipeline for ingesting and storing multi-asset market data. The system features a Rust-accelerated financial library that utilizes Apache Arrow for high-performance technical indicator calculation and zero-copy data processing. It provides a containerized infrastructure model designed for orchestrati

Backtrader is a Python backtesting framework and algorithmic trading platform. It provides a toolkit for developing automated trading rules and simulating investment strategies using historical financial time-series data. The system functions as a quantitative analysis tool, combining a simulation engine for testing trading rules with a financial data visualizer that generates price action charts. It allows for the calculation of technical indicators and the evaluation of portfolio performance through risk-adjusted returns. The platform covers live trading integration via brokerage APIs and

This project is a Python library designed for the programmatic retrieval and analysis of diverse financial datasets. It functions as a comprehensive toolkit for quantitative research, providing a unified interface to fetch historical and real-time market data across asset classes including equities, futures, bonds, cryptocurrencies, and foreign exchange. By abstracting complex network requests into simple, parameter-driven functions, it enables users to integrate financial data into research workflows and automated trading systems. The library distinguishes itself through its scraper-based ag

This project is a cryptocurrency exchange API documentation portal. It provides a technical reference for integrating with REST and WebSocket interfaces to trade digital assets and stream market data. The site serves as a REST API reference with schema-driven endpoint descriptions and request-response examples, alongside a WebSocket data stream guide for receiving live order book updates and price feeds. The documentation is implemented as a markdown-based static site featuring client-side search indexing and hierarchical navigation. It uses schema-driven content generation and linked asset

This project provides technical documentation and reference guides for spot trading, including specifications for REST, WebSocket, and FIX protocols. It serves as a comprehensive resource for integrating with spot trading endpoints to execute trades, query account data, and fetch market statistics. The project distinguishes itself by supporting institutional-grade connectivity through the Financial Information eXchange standard and simple binary encoding to reduce latency and payload size. It also includes a dedicated sandbox environment for validating trading logic and strategies without fin

Python API for the Interactive Brokers on-line trading system.

Python Client for Interfacing with the Federal Reserve Bank of St. Louis' Economic Data API (FRED®)

Financial Data Extraction from Investing.com with Python

Python SDK for IEX Cloud

Cryptocurrency exchange API client for Julia

Fetch stock quote data from Yahoo Finance

Currency conversion library for Julia

This library provides convenient way to use Coinpaprika.com API in Python.

Official DexPaprika Python SDK: Pythonic access to cross-chain DEX data, prices, and pools with type hints and caching.

Python API for accessing Lake high frequency tick trades & order book data

Python wrapper for Yahoo! Finance API.

Python library to download market data via Bloomberg, Eikon, Quandl, Yahoo etc.

Obtain pre market and after hours stock prices for a given symbol

High level API for access to and analysis of financial data.

An open-source alternative to Yahoo Finance's market data APIs with higher reliability.

Cryptocurrency Exchange Websocket Data Feed Handler

Official Documentation for the Indodax APIs