Open-source alternatives to TradingView API

FundamentalAnalysis is a comprehensive financial analysis library, quantitative finance framework, and macroeconomic data integrator. It provides tools for computing financial ratios, executing corporate health metrics, and pricing derivatives and bonds using mathematical models. The project integrates diverse data streams, including global economic indicators, real-time market quotes, and standardized corporate financial statements. It features a technical analysis engine for generating momentum and volatility indicators, as well as a portfolio performance analyzer for tracking risk-adjusted

This project is a comprehensive market data toolkit and financial analysis system specifically designed for China A-shares. It serves as a data pipeline for retrieving real-time quotes, aggregating corporate financial statements, and automating equity research. The system distinguishes itself through specialized monitors for institutional capital movements, including Northbound fund flows, margin trading balances, and large block transactions. It also features a dedicated options Greeks calculator for ETF derivatives and tools to gauge market sentiment via retail popularity rankings and trend

tqsdk-python is a quantitative trading SDK and framework designed for developing automated strategies for futures, options, and stocks using Python. It functions as an algorithmic trading engine and financial market data API, providing the tools necessary to backtest strategies, analyze historical data, and execute live trades across multiple brokerage accounts. The project distinguishes itself through a specialized option analytics library that calculates Greeks, implied volatility, and volatility surfaces using the Black-Scholes model. It further supports complex order execution patterns, s

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

easyquotation is a Python library that provides access to Chinese stock market data, including real-time quotes, historical daily candlestick prices, exchange-traded fund details, and a stock code database sync utility. It retrieves live trading data from Chinese exchanges, A-shares, and Hong Kong listed stocks without requiring manual API key configuration, offering a unified interface to multiple public data feeds. The library combines several market data providers behind a single query interface, using asynchronous I/O to handle parallel requests and a polling engine that delivers sub-seco

Backtrader is a Python framework designed for the development, backtesting, and live execution of algorithmic trading strategies. It provides a comprehensive environment for quantitative finance, allowing users to simulate trading logic against historical market data or connect directly to brokerage platforms for automated real-time trading. The project distinguishes itself through a unified event-driven architecture that treats backtesting and live trading with the same API. This consistency is supported by a flexible data-feed abstraction layer that normalizes diverse financial sources, ena

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 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

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

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

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

zvt is a quantitative trading framework designed for building, backtesting, and executing algorithmic trading strategies. It functions as a modular system that integrates a financial data pipeline for market data collection, an algorithmic backtesting engine for strategy evaluation, and an event-driven trading system to automate market executions. The project distinguishes itself through a hybrid approach to signal management, using a dynamic tagging system that combines automated quantitative logic with human intervention. It includes a quantitative analysis dashboard for visualizing researc

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

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

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

QuantAxis is a quantitative trading platform and algorithmic trading framework. It provides a comprehensive local environment for backtesting strategies, managing financial market data, and executing trades across stocks, futures, and options markets. The system distinguishes itself through a distributed task scheduler that spreads asynchronous computations and heavy mathematical workloads across a network of remote agents. It incorporates a multi-account trading interface to standardize the monitoring of positions and the execution of orders across various brokerage accounts. The platform c

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

QuantResearch is a quantitative research framework and specialized toolkit for algorithmic simulation, financial time-series analysis, and systematic trading. It provides an event-driven backtesting environment for validating strategies against historical tick and bar data, alongside a dedicated portfolio optimization engine for calculating asset weights and risk metrics. The project distinguishes itself through a machine learning finance toolkit that implements recurrent neural networks for price prediction and reinforcement learning for derivative pricing. It also features advanced statisti

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

Kronos is a financial time-series forecasting framework and quantitative trading strategy simulator. It functions as a research environment designed to analyze historical market data, train predictive models, and evaluate the performance of automated trading signals. The platform distinguishes itself through its deep learning sequence predictors and probabilistic market modeling tools. By utilizing sequence-based architectures and statistical sampling, the system generates multiple potential price trajectories and volatility estimates to quantify uncertainty. It also supports transfer learnin

Awesome-quant is a curated directory of open-source software libraries and tools designed for quantitative finance, algorithmic trading, and financial data analysis. It serves as a central hub for discovering resources that support the entire lifecycle of financial modeling, from raw data ingestion to complex statistical research. The repository organizes specialized tools into categorized collections, enabling users to identify solutions for high-performance numerical computing, technical indicator calculation, and derivative pricing. It highlights frameworks that facilitate the construction

Abu is an algorithmic trading framework designed for the development, backtesting, and optimization of automated trading strategies. It functions as a quantitative financial analysis library that processes time-series data to identify market trends, volatility patterns, and key price levels. The platform distinguishes itself through a modular architecture that integrates diverse financial data sources and a rule-based engine for automated risk management. It enables users to construct complex trading signals by layering technical indicators and machine learning models, while simultaneously en

Lean is an algorithmic trading engine and quantitative finance platform designed for the development, backtesting, and live execution of automated trading strategies. It provides a comprehensive framework for processing time-series market data, managing multi-asset portfolios, and conducting quantitative research across diverse financial markets. The platform distinguishes itself through a modular, event-driven architecture that decouples strategy logic from data ingestion and brokerage connectivity. By utilizing standardized interfaces for data providers and brokerage abstractions, it enable

FinRL is a reinforcement learning framework designed for the development, training, and backtesting of automated trading strategies. It functions as a quantitative finance toolkit that integrates deep learning algorithms with financial market simulations to address complex portfolio management and asset allocation tasks. The platform provides an end-to-end pipeline for transforming raw market data into actionable trading models. The project distinguishes itself through a layered, modular architecture that separates data processing, environment simulation, and agent training. This design allow