beaapi
BEA API Python package
Decision gist · record as of 2026-08-14
Yes. beaapi is actively maintained, has no known vulnerabilities, installs with minimal friction, and is the official Python interface to BEA's economic data. If you need U.S. economic statistics—GDP, trade, industry output, or regional data—this is the right tool. The only prerequisite is obtaining a free API key.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- You must register for a free BEA API key at https://apps.bea.gov/api/signup/ before making any data requests.
- Low friction to install; depends only on pandas.
- The package is actively maintained with recent commits and is in beta status, suitable for production use with the understanding that the API surface may evolve.
License · maintenance · safety
CC0 (permissive) — Licensed under CC0 (public domain), so you may use, modify, and distribute the package freely without attribution requirements or restrictions.
last release 2026-02-17 (178 days) · last repo commit 2026-02-17 · 66 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 153,316 downloads/mo, #10,885 on PyPI
Alternatives
Verify before relying
pip install beaapi
import beaapi
beakey = 'YOUR_36_DIGIT_API_KEY'
bea_tbl = beaapi.get_data(beakey, datasetname='NIPA', TableName='T20305', Frequency='Q', Year='2015')- Whether the package handles rate limiting or pagination for large data requests automatically.
- Performance characteristics when querying across multiple datasets or years simultaneously.
- Whether offline metadata caching is fully functional or requires periodic API calls.
What it is and what it does
beaapi is a Python wrapper around the U.S. Bureau of Economic Analysis public data API. It simplifies access to BEA's economic datasets—including NIPA tables, GDP by industry, international trade accounts, and regional data—by providing functions to list available datasets, discover parameters and their allowed values, search metadata by keyword, and retrieve data directly into pandas DataFrames.
The package handles the HTTP communication and response parsing, so you work with structured data immediately. It requires only pandas as a runtime dependency and supports current Python versions. You supply an API key (obtained free from BEA) and call functions like `get_data()` to fetch specific tables, `get_parameter_list()` to explore what parameters a dataset accepts, and `search_metadata()` to find tables by keyword. The result is always a DataFrame, making downstream analysis straightforward.
Use it for
- Retrieve quarterly or annual NIPA tables for macroeconomic analysis and forecasting.
- Query GDP-by-industry data to analyze sectoral economic performance over time.
- Access international trade and investment position data for cross-border economic research.
- Search metadata to discover which BEA tables contain specific economic indicators.
- Build automated data pipelines that fetch updated economic statistics on a schedule.
- Combine BEA data with other sources in a pandas workflow for integrated economic analysis.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
beaapi is actively maintained, has no known vulnerabilities, installs with minimal friction, and is the official Python interface to BEA's economic data. If you need U.S. economic statistics—GDP, trade, industry output, or regional data—this is the right tool. The only prerequisite is obtaining a free API key.
Install
beaapi on PyPI
Before you install
Low friction to install; depends only on pandas. The package is actively maintained with recent commits and is in beta status, suitable for production use with the understanding that the API surface may evolve.
You must register for a free BEA API key at https://apps.bea.gov/api/signup/ before making any data requests.
License in practice
Licensed under CC0 (public domain), so you may use, modify, and distribute the package freely without attribution requirements or restrictions.
Quickstart
pip install beaapi
import beaapi
beakey = 'YOUR_36_DIGIT_API_KEY'
bea_tbl = beaapi.get_data(beakey, datasetname='NIPA', TableName='T20305', Frequency='Q', Year='2015')Verify before relying
- Whether the package handles rate limiting or pagination for large data requests automatically.
- Performance characteristics when querying across multiple datasets or years simultaneously.
- Whether offline metadata caching is fully functional or requires periodic API calls.
Package facts
| License | CC0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepandas |
| Maintenance | Actively maintained 178 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 153,316 / month, #10,885 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: EducationIntended Audience :: Financial and Insurance IndustryIntended Audience :: Science/ResearchLicense :: Public DomainOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsProgramming Language :: Python :: 3 |
Evidence: beaapi-0.2.0-py3-none-any.whl
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