Financial Data Science (FinDS) API Reference

Designed to support financial data science workflows, the FinDS Python package demonstrates how to use database engines such as SQL, Redis, and MongoDB to manage and access large datasets, including:

• Core financial databases such as CRSP, Compustat, IBES, and TAQ

• Public economic data APIs from sources like FRED and the Bureau of Economic Analysis (BEA)

• Structured and unstructured data from academic and research websites

Its companion Financial Data Science Python Notebooks provides practical examples and templates for applying:

• Financial econometrics and time series modeling

• Graph analytics, event studies, and backtesting strategies

• Machine learning for predictive analytics

• Natural language processing (NLP) to extract insights from financial text

• Neural networks and large language models (LLMs) for advanced decision-making

Documentation:

• Financial Data Science Notebooks

• Download PDF

• FinDS API reference

Github repos:

• FinDS package

• Jupyter notebooks

Modules:

• finds.database
• finds.structured
• finds.backtesting
• finds.unstructured
• finds.readers
• finds.recipes
• finds.utils