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Python library to download market data via Bloomberg, Eikon, Quandl, Yahoo etc.
The main features of cuemacro/findatapy are: Data Sources, Data Storage and Sources, Financial Analytics, Market Data Sources.
Projects with overlapping indexed features include: openbb-finance/openbbterminal — OpenBBTerminal is a Python financial data platform and command line interface designed for aggregating and analyzing… ranaroussi/yfinance — This library is a Python-based tool for retrieving historical and real-time financial market data from public sources.… pydata/pandas-datareader — Extract data from a wide range of Internet sources into a pandas DataFrame. jerbouma/fundamentalanalysis — FundamentalAnalysis is a comprehensive financial analysis library, quantitative finance framework, and macroeconomic… akfamily/akshare — This project is a Python library designed for the programmatic retrieval and analysis of diverse financial datasets.… mcdallas/wallstreet — Real time stock and option data.
This library is a Python-based tool for retrieving historical and real-time financial market data from public sources. It functions as a programmatic interface for downloading stock prices, dividends, financial statements, and corporate calendars, allowing users to perform automated research and analysis on various market assets. The project distinguishes itself by structuring retrieved financial time series directly into tabular data frames, which facilitates mathematical analysis and manipulation of market metrics. It supports efficient data retrieval through multi-threaded batch downloadin
OpenBBTerminal is a Python financial data platform and command line interface designed for aggregating and analyzing market data from diverse APIs. It serves as a quantitative analysis tool for processing stock, crypto, and derivative datasets to identify market trends and build investment strategies. The project utilizes a pluggable financial API framework with an adapter-based architecture, allowing external financial data providers to be integrated as independent modules. This system standardizes information from public and proprietary sources into a unified layer to support cross-asset an
Real time stock and option data.
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