Open-source alternatives to Alpha Vantage

QuantMuse is an algorithmic trading platform and quantitative trading framework that integrates large language models with mathematical analysis to automate market insights and trading strategies. It functions as a system for building, backtesting, and executing strategies using both historical and real-time market data. The framework is distinguished by its use of large language models for financial analysis and sentiment extraction from news and social media. It utilizes autonomous agents with chain-of-thought reasoning to generate market intelligence and strategic reports, while employing

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

FinanceDatabase is a system of data repositories and interfaces providing a corporate fundamental database, a financial market data API, and an SEC filings aggregator. It functions as a financial valuation engine and a macroeconomic indicator feed, offering a programmatic way to access market quotes, corporate fundamentals, and official regulatory disclosures. The project distinguishes itself through an institutional ownership tracker that monitors fund holdings, insider trading activity, and political financial disclosures. It also includes a dedicated tool for extracting and analyzing offic

VectorBT is a vectorized trading strategy backtesting framework that simulates thousands of strategy configurations in a single pass over historical price data. It operates as a parameter optimization engine, a portfolio performance analyzer, a technical indicator calculator, and a financial data fetcher, all built around a DataFrame-centric data model that uses NumPy broadcasting for signal alignment and compiled code acceleration for performance. The framework distinguishes itself through its ability to run large-scale parameter sweeps by constructing every combination of strategy parameter

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

This project is a Python wrapper for the TA-Lib C library, serving as a financial technical analysis library and quantitative trading tool. It provides a collection of mathematical functions designed to analyze market price movements, identify trading signals, and recognize candlestick patterns within financial data. The library focuses on the computation of trend, momentum, and volume metrics. It includes specialized tools for candlestick pattern recognition to detect recurring price action shapes in both historical and real-time data. The system integrates with NumPy arrays to process cont

This is a library of cryptocurrency trading algorithms and technical analysis strategies designed for use with the Freqtrade trading bot. The project provides a collection of pre-defined rules and mathematical indicators used to automate the buying and selling of digital assets. The repository focuses on algorithmic trading strategies and bot-driven asset management to remove manual execution from cryptocurrency trades. It enables quantitative trading analysis by allowing the development and testing of rule-based logic against historical market data. The system utilizes class-based strategy

jscamp is a full-stack web development and education project focused on mastering JavaScript, TypeScript, and AI integration. It provides a structured curriculum and interactive exercises covering language fundamentals, frontend engineering, and backend API development. The project distinguishes itself through the implementation of autonomous AI agents capable of complex task automation, such as modifying files, managing servers, and executing API calls. It includes advanced AI development tools for conversational querying, real-time code suggestions, and automated repository analysis to gene

pyalgotrade is a Python algorithmic trading library designed for developing, backtesting, and executing automated trading strategies. It provides a comprehensive framework for financial strategy backtesting, a technical analysis library for computing mathematical indicators, and connectors for cryptocurrency exchange integration. The project distinguishes itself by supporting sentiment-based trading through the integration of real-time social media feeds and keyword streams. It features a quantitative trading visualization tool for plotting price action and portfolio equity curves, along with

The Google API Node.js client is a development kit designed for integrating Google Cloud services into server-side JavaScript applications. It provides generated interfaces that map application calls to remote service endpoints, enabling developers to execute requests and interact with cloud resources through a unified library. The library distinguishes itself through a modular architecture that allows developers to install specific service submodules individually, which optimizes application bundle sizes and improves startup performance. It also features automated OAuth2 token lifecycle mana

This project is a Go library that provides a programmatic interface for interacting with generative AI services. It serves as a comprehensive software development kit for integrating large language models into applications, enabling developers to perform tasks such as text and chat completion, image generation, and audio transcription. The library distinguishes itself through a unified infrastructure designed for robust network communication and service management. It features structured request mapping and error normalization to ensure type-safe interactions and simplified debugging. Further

Instaloader is a Python library and command-line utility designed for the automated retrieval, archiving, and analysis of Instagram content. It provides a programmatic interface to fetch media, captions, and metadata from public or private profiles, hashtags, and stories, while maintaining persistent user sessions for authorized access. The tool distinguishes itself through robust archive management and traffic control mechanisms. It supports incremental synchronization, allowing users to resume interrupted downloads and update local collections without redundant requests. To ensure reliable

The Azure SDK for .NET is a collection of client and management libraries that enable .NET applications to interact with cloud services through a consistent, well-defined programming model. It provides a unified interface for authenticating, configuring HTTP pipelines, and calling service methods either synchronously or asynchronously, with support for pagination, long-running operations, and structured error handling. The SDK distinguishes itself through comprehensive authentication options, including connection strings, OAuth token credentials, managed identity, service principals, and deve

The Google API PHP Client Library is a development kit for interacting with Google Cloud services and APIs. It provides standardized service interfaces to retrieve and manipulate data, serving as a comprehensive SDK for executing network requests across Google cloud platforms. The library features a specialized authentication handler for OAuth 2.0, managing authorization flows, access tokens, and offline access via refresh tokens. It includes a service account authenticator that uses JSON key files or application default credentials for server-to-server communication, as well as mechanisms fo

This repository is a collection of Python code examples that demonstrate how to use Google Cloud Platform services and APIs. Each sample is organized as a self-contained directory with its own dependencies, making it independently runnable and testable. The samples rely on Google's auto-generated Python client libraries and standardize invocation through command-line argument parsing, with configuration read from environment variables for portability across development and CI environments. The examples cover authentication setup using the gcloud CLI, along with practical demonstrations for se

The Google Workspace CLI is a command-line interface and Google API client designed to automate tasks across Google Workspace services. It functions as a cloud productivity automator that uses the Google Discovery Service to dynamically generate command structures and parameter requirements at runtime. The project distinguishes itself by providing a specialized AI agent toolset, exposing a server over standard input and output to provide structured tool definitions and skills for AI clients. It includes security layers for AI content sanitization to protect against prompt injection and utiliz

Telethon is a Python asynchronous API wrapper and client library designed for interacting with the Telegram API. It implements the MTProto protocol to enable programmatic communication for both user accounts and bots. The project serves as a development framework for building custom Telegram clients and automating account actions. It provides the tooling necessary to create automated bots that manage group interactions and channel communications. The library supports messaging data integration and the automation of messaging workflows. It handles the translation of high-level calls into the

Botpress is a conversational AI builder and LLM agent platform used to design chatbot workflows and orchestrate agents powered by large language models. It provides a framework for managing the entire lifecycle of these agents, from initial creation through to deployment across various production environments. The platform includes a custom integration SDK for developing and publishing third-party connectors that extend agent capabilities. These tools allow for the creation of custom plugins that connect AI agents to external APIs and third-party services. The system supports both visual des

The Google API JavaScript Client Library is an official client for calling Google APIs directly from browser applications. It provides a programmatic interface to exchange data and execute service requests while managing request construction and response parsing. The library features dynamic client discovery, which loads machine-readable metadata at runtime to automatically generate request methods and parameter validation for various endpoints. It also includes an authentication client that handles OAuth 2.0 authorization flows to securely manage user identity and access tokens in the browse

AkShare is a Python financial data library and programmatic interface designed for fetching real-time and historical stock, currency, and economic market data. It serves as a quantitative data acquisition tool for gathering the large-scale financial datasets required for economic research and quantitative analysis. The library provides a unified interface to retrieve datasets from various official and commercial providers, removing the need to write custom scrapers for individual financial sources. It maps standardized function calls to diverse third-party sources to normalize varying respons

This project is a cross-platform messaging client that implements a secure, real-time communication protocol. It provides a comprehensive development toolkit, including a database library and messaging SDK, which allows for the creation of custom messaging applications that maintain synchronized state across multiple devices. The core architecture relies on an asynchronous event-driven model to ensure responsive performance while managing persistent local database synchronization with server-side state. The client distinguishes itself through a robust end-to-end encryption layer that supports

Zenbot is an automated cryptocurrency trading bot designed to execute trades on exchanges based on technical analysis and predefined risk parameters. It functions as a technical analysis engine that processes market data through mathematical indicators to generate actionable trade signals. The system includes a genetic algorithm strategy optimizer to automatically discover the most profitable parameter configurations. It provides multiple simulation environments, including a trading strategy backtester for replaying historical data and a paper trading simulator for testing strategies against

Hikyuu is a quantitative trading framework designed for developing, backtesting, and executing systematic trading strategies. It functions as a high-speed system that combines a financial time-series library, a multi-factor analysis tool, and a quantitative backtesting engine to support comprehensive trading research. The framework is distinguished by its high-speed computing core, which utilizes multi-threaded execution to process large volumes of market data for technical indicator generation. It supports a modular strategy composition model where signal, risk, and fund management component

Panda Factor is a quantitative trading infrastructure and alpha factor framework. It serves as a backend system for building, calculating, and managing mathematical signals designed to predict the price movements of financial assets. The project functions as a technical indicator engine that generates quantitative metrics from price and volume data. It utilizes a financial data pipeline to automate the synchronization of market data from multiple providers on a nightly schedule. The system provides capabilities for quantitative alpha generation and the construction of financial indicators us

RQAlpha is a Python-native quantitative trading backtesting framework and live trading execution system. It provides an event-driven engine for simulating trading strategies against historical market data, with realistic transaction costs, slippage models, and corporate action handling. The platform supports multi-asset class trading including stocks, futures, options, and REITs, with separate sub-accounts for different asset types and configurable margin requirements. The framework distinguishes itself through a plugin-based extensible architecture that allows users to swap out core componen

This is a pandas-based technical analysis library and financial feature engineering tool. It serves as a vectorized indicator calculator that transforms raw price and volume data into derived metrics for time series analysis. The library uses a NumPy-based engine to perform mathematical operations across entire arrays, avoiding iterative loops to maintain high performance. It organizes technical indicators into a modular class hierarchy with a consistent interface, allowing for bulk feature generation and the direct appending of results as new columns to a pandas DataFrame. The system covers

quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering, and algorithmic trading. It serves as a centralized library of documentation covering mathematical models, financial instruments, and systematic trading strategies. The project integrates AI-driven capabilities through a modular retrieval-augmented generation framework that extracts structured data from research papers and news. It features a multi-agent workflow engine designed to discover and validate predictive alpha factors, alongside tools for local large language model