bbg-fetch

bbg-fetch provides Bloomberg Desktop API request/response data in pandas DataFrames for quantitative research.

It wraps BDP-, BDH-, and BDS-style requests and selected research workflows. Live requests require a running Bloomberg Terminal, suitable entitlements, and Bloomberg’s separately installed blpapi. Streaming and intraday subscriptions are outside this project’s scope.

Task guides

• Install, connect, and diagnose — install the two packages, establish the local Desktop API boundary, and isolate failures without exposing data.

• Request reference, historical, and bulk data — choose between high-level fetchers and bdp/bdh/bds, with their exact pandas output contracts.

• Specialised research workflows — use option, volatility, futures, fixed-income, and index-constituent workflows within their stated limits.

Choosing a client

• Choosing a Bloomberg Python client — a dated, source-linked comparison with direct Bloomberg blpapi, xbbg, and blp; each option has use cases it serves best.

Start here

• Installation and connection prerequisites — install blpapi and bbg-fetch and understand the local Terminal boundary.

• First success without a Terminal — verify the installed public API without claiming a Bloomberg connection.

• Top-level API reference — inspect the real top-level request, shaping, and research workflow exports.

• Troubleshooting — diagnose installation, session, entitlement, field, and empty-response failures.

Project links

• Source

• Issues

• PyPI

• Changelog

• License

• Citation metadata

Documentation

• Installation and connection prerequisites
  • What you need
  • Install Bloomberg’s Python API
  • Install bbg-fetch
  • Live Desktop API boundary
• Install, connect, and diagnose
  • The problem
  • Prerequisites and supported environment
  • Install the two packages
  • Verify without opening a Bloomberg session
  • Run one redacted live diagnostic
  • Classify failures
  • What can be checked without a Terminal
  • Failure-report checklist
  • Non-goals and next links
• Request reference, historical, and bulk data
  • The problem
  • Prerequisites
  • Choose the request layer
  • Exact output contracts
  • Minimal live example
  • Adjustments, overrides, and dates
  • Batching and request size
  • Missing data and failure modes
  • Session lifetime and shutdown
  • Examples, API, and source
  • Non-goals
• Specialised research workflows
  • The problem
  • Option chains and put-call parity
  • Volatility time series and surfaces
  • Futures chains and generic histories
  • Fixed-income and issuer reference data
  • Index constituents and weights
  • Request-size and failure discipline
  • API, examples, and non-goals
• Choosing a Bloomberg Python client
  • No universal recommendation
  • Side-by-side scope
  • When each choice is a better fit
  • Why pdblp is not a current comparison target
  • Decision checklist
• First success without a Terminal
  • Expected evidence
  • Authoritative script
  • Next steps
• Top-level API reference
  • Detailed reference
  • Top-level modules
• Troubleshooting
  • No module named blpapi
  • Connection or session startup fails
  • A request times out
  • The result is empty
  • A field or security error is returned
  • The package imports but a live request fails