eurostat
Eurostat Python Package
Decision gist · record as of 2026-08-14
Yes, if you need to access Eurostat data programmatically. The package is stable, permissive-licensed, and has no known vulnerabilities. However, dormant maintenance (last release 792 days ago) means you should verify that the Eurostat API endpoint has not changed and that deprecated SDMX functions still work for your use case before committing to it in production.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires network access to Eurostat's SDMX 2.1 API endpoint; no local data is included.
- Low friction: pure Python wheel with only pandas and requests as runtime dependencies.
- Maintenance is dormant—last release was 792 days ago—but the package is marked Production/Stable and has no known vulnerabilities.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use, modify, and distribute this package freely in both open and closed projects with minimal restrictions.
last release 2024-06-13 (792 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 100,128 downloads/mo, #12,998 on PyPI
Alternatives
Verify before relying
pip install eurostat
import eurostat
# Get table of contents as dataframe
toc_df = eurostat.get_toc_df()
# Get parameters for a dataset
pars = eurostat.get_pars('demo_r_d2jan')
# Get parameter values
values = eurostat.get_par_values('demo_r_d2jan', 'sex')- Whether the Eurostat API endpoint remains stable and unchanged since the last release 792 days ago.
- Current status of the SDMX functions marked as deprecated in version 1.0.0 and scheduled for removal in 2.0.0.
- Whether the package handles authentication or rate-limiting for the Eurostat API.
What it is and what it does
Eurostat is a Python client for querying European statistical databases—primarily Eurostat, but also COMEXT, DG COMP, DG EMPL, and DG GROW—via the SDMX 2.1 web services API. It lets you browse available datasets, fetch their metadata and parameter definitions, and download data into pandas dataframes or as lists of tuples. The package wraps HTTP requests to Eurostat's dissemination API, handling the SDMX protocol details so you don't have to.
The package depends only on pandas and requests, making it lightweight to install. It requires Python 3.5 or later. Note that the package underwent a major rewrite in version 1.0.0 to adapt to Eurostat's API migration; some SDMX functions are now deprecated and will be removed in a future release, though they remain available with alert messages.
Use it for
- Download employment, GDP, or regional economic data from Eurostat for analysis in pandas.
- Query the Eurostat table of contents to discover available datasets and filter by keyword.
- Retrieve parameter definitions and allowed values for a dataset to construct filtered data requests.
- Fetch trade data from COMEXT or labor statistics from DG EMPL for economic research.
- Automate periodic data pulls from Eurostat into a data pipeline or research workflow.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to access Eurostat data programmatically.
The package is stable, permissive-licensed, and has no known vulnerabilities. However, dormant maintenance (last release 792 days ago) means you should verify that the Eurostat API endpoint has not changed and that deprecated SDMX functions still work for your use case before committing to it in production.
Install
eurostat on PyPI
Before you install
Low friction: pure Python wheel with only pandas and requests as runtime dependencies. Maintenance is dormant—last release was 792 days ago—but the package is marked Production/Stable and has no known vulnerabilities.
Requires network access to Eurostat's SDMX 2.1 API endpoint; no local data is included.
License in practice
MIT license is permissive; you can use, modify, and distribute this package freely in both open and closed projects with minimal restrictions.
Quickstart
pip install eurostat
import eurostat
# Get table of contents as dataframe
toc_df = eurostat.get_toc_df()
# Get parameters for a dataset
pars = eurostat.get_pars('demo_r_d2jan')
# Get parameter values
values = eurostat.get_par_values('demo_r_d2jan', 'sex')
Verify before relying
- Whether the Eurostat API endpoint remains stable and unchanged since the last release 792 days ago.
- Current status of the SDMX functions marked as deprecated in version 1.0.0 and scheduled for removal in 2.0.0.
- Whether the package handles authentication or rate-limiting for the Eurostat API.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.5 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagespandasrequests |
| Maintenance | Dormant 792 days since the last release |
| First released | |
| Downloads | 100,128 / month, #12,998 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Financial and Insurance IndustryIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Topic :: Office/BusinessTopic :: Office/Business :: FinancialTopic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Information AnalysisTopic :: Utilities |
Evidence: eurostat-1.1.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “eurostat data download”
- eurostatFetches statistical data and metadata from Eurostat and related…
- pandas-datareaderFetches macroeconomic and factor data from remote sources like FRED,…
- sdmx1Reads, writes, and exchanges statistical data and metadata in SDMX…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also sdmx1 · imfp · wbdata · pantab · fredapi · stats-can · statsbombpy · gspread-dataframe · pandas-td · pandas-read-xml