https://github.com/energyquantified/eq-python-client

Python library for Montel EQ's Time Series API.

https://github.com/energyquantified/eq-python-client

Science Score: 26.0%

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    Low similarity (13.6%) to scientific vocabulary

Keywords

api-client data-analysis energy-data energy-market integration pandas power-market python time-series
Last synced: 5 months ago · JSON representation

Repository

Python library for Montel EQ's Time Series API.

Basic Info
Statistics
  • Stars: 24
  • Watchers: 5
  • Forks: 4
  • Open Issues: 5
  • Releases: 43
Topics
api-client data-analysis energy-data energy-market integration pandas power-market python time-series
Created over 5 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog License

README.md

Energy Quantified Python Client

Apache License version 2.0 Python 3.7+ Wheel

Documentation | Python package | GitHub repository

The Python library for Energy Quantified's Time Series API. It allows you to access thousands of data series directly from Energy Quantified's time series database. It integrates with the popular pandas library and the polars libarary for high-performance data analysis and manipulation.

Developed for Python 3.7+.

```python from datetime import date, timedelta from energyquantified import EnergyQuantified

Initialize client

eq = EnergyQuantified(api_key='')

Freetext search (filtering on attributes is also supported)

curves = eq.metadata.curves(q='de wind production actual')

Load time series data

curve = curves[0] timeseries = eq.timeseries.load( curve, begin=date.today() - timedelta(days=10), end=date.today() )

Convert to Pandas data frame

pddf = timeseries.topandas_dataframe()

Convert to Polars data frame

pldf = timeseries.topolars_dataframe() ```

Full documentation available at Read the Docs.

Features

  • Simple authentication
  • Metadata caching
  • Rate-limiting and automatic retries on network errors
  • Full-text search and keyword search for curves and powerplants
  • Forecasts- and time series data
  • Period-based data
  • OHLC data with SRMC calculations
  • Shows your subscription for each data series
  • Support for timezones, resolutions, aggregations and unit conversions
  • Easy-to-use filters for issue dates and forecast types
  • Push feed for live updates on data modifications
  • Integrates with pandas and polars

Note: A user account with an API key is required to use this library. Create an account on Energy Quantified's home page. Trial users get access to 30 days of history.

Installation

Install with pip:

```bash

Install

pip install energyquantified

Upgrade

pip install --upgrade energyquantified ```

Documentation

Find the documentation at Read the Docs.

License

The Energy Quantified Python client is licensed under the Apache License version 2.0.

Owner

  • Name: Energy Quantified
  • Login: energyquantified
  • Kind: organization
  • Location: Oslo, Norway

Forecasting prices and fundamentals for power market professionals.

GitHub Events

Total
  • Create event: 20
  • Release event: 7
  • Issues event: 29
  • Watch event: 7
  • Delete event: 12
  • Issue comment event: 10
  • Push event: 44
  • Pull request review event: 3
  • Pull request review comment event: 5
  • Pull request event: 23
  • Fork event: 2
Last Year
  • Create event: 20
  • Release event: 7
  • Issues event: 29
  • Watch event: 7
  • Delete event: 12
  • Issue comment event: 10
  • Push event: 44
  • Pull request review event: 3
  • Pull request review comment event: 5
  • Pull request event: 23
  • Fork event: 2

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 127
  • Total Committers: 5
  • Avg Commits per committer: 25.4
  • Development Distribution Score (DDS): 0.457
Past Year
  • Commits: 44
  • Committers: 5
  • Avg Commits per committer: 8.8
  • Development Distribution Score (DDS): 0.477
Top Committers
Name Email Commits
Jon Moen Drange j****e@g****m 69
Jon Moen Drange j****d 24
fredriksvendsen f****2@g****m 23
Konstantin Pelz k****n@e****m 10
Konstantin Pelz K****z@p****e 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 76
  • Total pull requests: 79
  • Average time to close issues: 3 months
  • Average time to close pull requests: 10 days
  • Total issue authors: 12
  • Total pull request authors: 6
  • Average comments per issue: 0.42
  • Average comments per pull request: 0.16
  • Merged pull requests: 73
  • Bot issues: 0
  • Bot pull requests: 4
Past Year
  • Issues: 16
  • Pull requests: 24
  • Average time to close issues: 17 days
  • Average time to close pull requests: 2 days
  • Issue authors: 9
  • Pull request authors: 6
  • Average comments per issue: 0.19
  • Average comments per pull request: 0.08
  • Merged pull requests: 20
  • Bot issues: 0
  • Bot pull requests: 2
Top Authors
Issue Authors
  • jonmd (28)
  • fredriksvendsen (21)
  • komape (18)
  • pfwnicks (1)
  • caju-bit (1)
  • atemmo (1)
  • chrjx (1)
  • MartinGJespersen (1)
  • MathiasLorenz (1)
  • risosoky (1)
  • stanton119 (1)
  • igramatk (1)
Pull Request Authors
  • fredriksvendsen (37)
  • jonmd (25)
  • komape (12)
  • dependabot[bot] (5)
  • pfwnicks (2)
  • vakili (2)
Top Labels
Issue Labels
enhancement (40) documentation (24) bug (8) question (8) wontfix (2) good first issue (2) invalid (1) dependencies (1)
Pull Request Labels
enhancement (39) documentation (29) bug (13) dependencies (11)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 103,879 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 43
  • Total maintainers: 1
pypi.org: energyquantified

Energy Quantified Time series API client.

  • Versions: 43
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 103,879 Last month
Rankings
Downloads: 1.6%
Dependent packages count: 10.1%
Average: 14.6%
Stargazers count: 17.1%
Dependent repos count: 21.6%
Forks count: 22.6%
Maintainers (1)
Last synced: 6 months ago

Dependencies

requirements.txt pypi
  • Sphinx ==3.3.1
  • docutils ==0.17
  • python-dateutil >=2.8.0,<2.9
  • pytz *
  • recommonmark ==0.6.0
  • requests >=2.3,<3
  • twine *
  • tzlocal *
  • wheel *
setup.py pypi
  • python-dateutil >=2.8.0,<2.9
  • pytz *
  • requests >=2.3,<3
  • tzlocal *