---
id: entsoe-py
version: "0.8.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# entsoe-py — A python API wrapper for ENTSO-E

License: permissive · Maintenance: active · Downloads: 464.6K/mo

## What it is and what it does

entsoe-py is a Python wrapper around the ENTSO-E (European Network of Transmission System Operators for Electricity) REST API, providing structured access to European electricity market and grid data. The package offers two client interfaces: EntsoeRawClient returns data in its native XML or ZIP format, while EntsoePandasClient automatically parses results into Pandas Series or DataFrames for easier analysis. It handles common operational concerns like splitting requests that span more than one year and managing large batches of API calls transparently.

The package depends on requests for HTTP communication, pytz for timezone handling, beautifulsoup4 for XML parsing, and pandas for data structuring. It is actively maintained, classified as Production/Stable, and supports Python 3.9, 3.10, and 3.11. The API surface includes methods for querying day-ahead prices, generation forecasts, load data, cross-border flows, capacity information, and balancing market data across European countries and interconnections.

Use it for:

- Retrieve day-ahead electricity prices for specific European countries to analyze market trends or build pricing models.
- Query wind and solar generation forecasts and actual generation data for renewable energy analysis and grid planning.
- Fetch cross-border electricity flow data to study interconnection patterns and network congestion between countries.
- Obtain load forecasts and actual load data for demand-side analysis and capacity planning.
- Build time-series datasets of electricity market data for machine learning or statistical analysis of European energy markets.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides Python clients to query the ENTSO-E API for European electricity transmission system data, returning results as raw XML/ZIP or parsed Pandas DataFrames.

Yes. The package is actively maintained, has no known vulnerabilities, uses a permissive MIT license, and installs with low friction. It is the standard Python interface to ENTSO-E data and is well-suited for anyone working with European electricity market or grid data. Verify that you can obtain an API key and that the endpoints you need are currently supported.

## Install

pip install entsoe-py
uv add entsoe-py
poetry add entsoe-py

## Installing entsoe-py

Before you install: Low install friction with four common dependencies (requests, pytz, beautifulsoup4, pandas). Package is actively maintained with a recent release and 716 repository stars, indicating stable, established use.

License in practice: MIT license permits commercial and private use with minimal restrictions, making it suitable for most projects without legal concern.

Quickstart:

pip install entsoe-py

from entsoe import EntsoePandasClient
import pandas as pd

client = EntsoePandasClient(api_key='your_api_key')
start = pd.Timestamp('20171201', tz='Europe/Brussels')
end = pd.Timestamp('20180101', tz='Europe/Brussels')
prices = client.query_day_ahead_prices('BE', start=start, end=end)

Requires a valid ENTSO-E API key (obtainable from the ENTSO-E transparency platform); timestamps must be pandas Timestamp objects with timezone information.

Verify before relying:

- Whether API key registration is free or has usage limits beyond what the fact sheet indicates.
- Performance characteristics for large date ranges or high-frequency queries.
- Whether all ENTSO-E API endpoints are currently supported or if some have been deprecated.

## Package facts

- License: MIT (permissive)
- Python support: unspecified
- Install friction: low
- Maintenance: active
- Downloads: 464.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

ENTSO-E API client, european electricity data, transmission system operator API, power grid data python, energy market data API, cross-border electricity flows, day-ahead prices API, energy-data, api-client, time-series

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