---
id: energyquantified
version: "0.15.1"
license: unclear
license_treatment: permissive
maintenance: active
---

# energyquantified — Energy Quantified Time series API client.

License: permissive · Maintenance: active · Downloads: 228.6K/mo

## What it is and what it does

energyquantified is a Python client for Energy Quantified's time series API, designed to fetch energy market data directly into your Python environment. It handles authentication, metadata caching, rate-limiting, and automatic retries, and provides full-text search across thousands of data series covering forecasts, OHLC data, and period-based metrics. The library integrates seamlessly with pandas and polars for downstream analysis.

You initialize a client with an API key, search for data series by name or attributes, load time series within a date range, and convert results to pandas or polars DataFrames. It supports timezone handling, unit conversions, and aggregation options. Requires Python 3.10 or later and an active Energy Quantified account (trial users get 30 days of history).

Use it for:

- Fetch historical wind and solar production data for energy market analysis or forecasting models
- Build dashboards that pull live energy prices and forecasts into pandas DataFrames for reporting
- Retrieve OHLC and SRMC data for backtesting trading strategies on energy commodities
- Aggregate multi-series energy data across regions and resolutions for research or compliance reporting

## Worth the install?

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

A Python client library for querying Energy Quantified's time series database, enabling access to thousands of energy market data series with pandas and polars integration.

Yes, if you have an Energy Quantified account and need programmatic access to energy market time series. The package is actively maintained, has low install friction, carries a permissive license, and integrates well with standard data analysis tools. No known vulnerabilities. Requires Python 3.10+ and a valid API key.

## Install

pip install energyquantified
uv add energyquantified
poetry add energyquantified

## Installing energyquantified

Before you install: Low friction install with five lightweight runtime dependencies. The package is actively maintained with a recent release; last commit was 2026-07-22.

License in practice: Licensed under Apache License 2.0 (permissive), allowing commercial and private use with minimal restrictions.

Quickstart:

pip install energyquantified

from energyquantified import EnergyQuantified
from datetime import date, timedelta

eq = EnergyQuantified(api_key='your_api_key')
curves = eq.metadata.curves(q='de wind production actual')
timeseries = eq.timeseries.load(
    curves[0],
    begin=date.today() - timedelta(days=10),
    end=date.today()
)
pd_df = timeseries.to_pandas_dataframe()

Requires Python 3.10 or later and a valid Energy Quantified API key (account creation required).

Verify before relying:

- Whether the API key requirement and trial account limitations affect typical use cases
- Performance characteristics when handling large time series datasets
- Specific data series coverage and update frequency from Energy Quantified's database

## Package facts

- License: not declared (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 228.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

energy market data API client, time series database access, energy data retrieval python, power market data API, energy quantified client library, energy-data, time-series-api, financial-data

[View on SkillFed](https://skillfed.io/packages/energyquantified) · [View on PyPI](https://pypi.org/project/energyquantified/)