Registry / data / energyquantified

energyquantified

JSON →
library0.15.1pypypi✓ verified 86d ago

The official Python library for Energy Quantified's Time Series API (eq-python-client). It allows users to access thousands of data series directly from Energy Quantified's time series database. The library integrates with popular data science tools like Pandas and Polars for high-performance data analysis and manipulation. Developed for Python 3.10+, it maintains an active release cadence with frequent minor updates.

pip install energyquantified
INSTALL
IMPORT
SIG · ENERGYQUANTIFIED
E
energyquantified
datapythonv0.15.1
Install
2.6s avg
Import
999ms
Disk
25MB
Pass rate
10/ 10
Env Coverage10 / 10
glibc
3.93.13
musl
3.93.13
Install & Compatibility
Where this runs
tested against v0.15.1 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
musl
py 3.103.920 runs
installs and imports cleanly · install 0.0s · import 1.119s · 27.1MB
glibc
py 3.103.920 runs
installs and imports cleanly · install 2.6s · import 0.879s · 28MB
25MB installed
● package 25MB
Code
Verified usage

Verified import paths — ran on the pinned version, not inferred.

EnergyQuantified
from energyquantified import EnergyQuantified
import energyquantified.EnergyQuantified
The primary client class is directly importable from the top-level package.
RealtoConnection
from energyquantified import RealtoConnection
Use this class for users subscribing to the API via the Realto marketplace.

This quickstart initializes the EnergyQuantified client using an API key (preferably from an environment variable), searches for a time series, loads data for it, and then converts the result to a Pandas DataFrame.

import os from datetime import date, timedelta from energyquantified import EnergyQuantified # Initialize client with API key from environment variable api_key = os.environ.get('EQ_API_KEY', 'YOUR_API_KEY') eq = EnergyQuantified(api_key=api_key) # Free-text search for curves curves = eq.metadata.curves(q='de wind production actual') if curves: # Load time series data for the first matching curve curve = curves[0] timeseries = eq.timeseries.load( curve, begin=date.today() - timedelta(days=10), end=date.today() ) print(f"Loaded {len(timeseries)} values for {curve.name}") # Convert to Pandas DataFrame (requires pandas installed) try: pd_df = timeseries.to_pandas_dataframe() print("\nPandas DataFrame head:") print(pd_df.head()) except AttributeError: print("\nSkipping Pandas conversion: pandas not installed or old client version.") else: print("No curves found for the query.")
Debug
Known issues
breakingPandas DataFrame conversion methods `to_df()` and `to_dataframe()` were renamed to `to_pd_df()` and `to_pandas_dataframe()` respectively. The old methods are deprecated and will be removed in a future major release.
fix
Update your code to use `to_pd_df()` or `to_pandas_dataframe()` for Pandas DataFrame conversions, and `to_pl_df()` or `to_polars_dataframe()` for Polars.
affects: >=0.14
deprecatedThe method parameter `exlude_tags` has been deprecated in favor of `exclude_tags`. This affects methods like `eq.instances.list()` and `eq.instances.load()`.
fix
Replace all occurrences of `exlude_tags` with `exclude_tags` in your method calls.
affects: >=0.14.5
gotchaUsers on Python versions >=3.13.1 and <3.13.4 may experience crashes when calling `PeriodSeries.to_timeseries()` due to a regression in Python's iterator behavior. This was patched in client version v0.14.6.
fix
Upgrade `energyquantified` client to `v0.14.6` or newer. If you must stay on an older client, avoid Python versions 3.13.1-3.13.3.
affects: Python 3.13.1 to 3.13.3, client versions <0.14.6
Errors
Common errors & fixes
energyquantified.exceptions.EnergyQuantifiedException: Authentication failed
The provided API key is missing or invalid. An API key is required to use the client.
fix
Ensure you have a valid API key from Energy Quantified and that it's correctly passed during client initialization, either directly via `api_key='YOUR_KEY'` or from a file via `api_key_file='path/to/key.txt'`, or via an environment variable. For Realto users, use `RealtoConnection` and specify `api_url`.
AttributeError: 'Timeseries' object has no attribute 'to_df'
You are attempting to use an old method name for Pandas DataFrame conversion. The method names were changed in `v0.14`.
fix
Update your code to use the new method names: `timeseries.to_pandas_dataframe()` or `timeseries.to_pd_df()`.
AttributeError: 'Timeseries' object has no attribute 'to_pandas_dataframe' or 'to_polars_dataframe'
The `pandas` or `polars` library is not installed in your environment, but the `energyquantified` client attempts to use its integration methods. The `energyquantified` package does not automatically install these data analysis libraries.
fix
Install `pandas` or `polars` separately using `pip install pandas` or `pip install polars`.
Upgrade
Version history
0.15.1latest on PyPI · released Feb 4, 2026
Audit
Dependencies
pandasoptionalOptional, for converting data series to Pandas DataFrames.
polarsoptionalOptional, for converting data series to Polars DataFrames.
websocket-clientrequiredImplicit dependency, unpinned in v0.14.1 for broader compatibility.
Agent activity
7 hits · last 30 days
node
6
OpenAI (training)
1
Resources
energyquantified — pip install energyquantified · libregistry