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gridstatus

API to access energy data

With conditionsPyPI Information AnalysisReleased Apr 202693.7K downloads / moPure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — gridstatus-0.36.0-py3-none-any.whl
v0.36.0 · released 2026-04-21 · Python <3.15,>=3.10 · 22 runtime deps: beautifulsoup4, certifi, cryptography, filelock, frozendict, h11, lxml, openpyxl

Yes, if you need programmatic access to raw electricity market data from US or Canadian ISOs and can handle minimally-processed data. The library is actively maintained, has low install friction, and covers a wide range of ISOs. However, for production systems requiring guaranteed uptime and data quality, the maintainers recommend their hosted GridStatus.io API instead. License is permissive (BSD 3-Clause) and no known vulnerabilities are recorded.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.10 or higher.
  • Some ISO parsers require environment variables for authentication or API access (see .env.template in repository).
  • Low friction install with a pure-Python wheel.

License · maintenance · safety

(unclear) — BSD 3-Clause license (unclear SPDX classification in metadata). Permits commercial and private use with attribution and liability disclaimer; derivative works allowed under same terms.

last release 2026-04-21 (115 days) · last repo commit 2026-08-13 · 439 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 93,663 downloads/mo, #13,373 on PyPI

Verify before relying

pip install gridstatus

import gridstatus

# Fetch CAISO data
data = gridstatus.CAISO().get_load()
  • Whether all 10 supported ISOs are equally well-maintained and have current data coverage
  • Latency and update frequency for real-time data from each ISO
  • Rate limits or throttling policies for data access
  • Whether production use should prefer the hosted GridStatus.io API over this library
Same gist for agents: .md · .json

What it is and what it does

gridstatus is a Python library that normalizes access to electricity market data across multiple Independent System Operators in North America. It abstracts away the different data formats and APIs that each ISO publishes, presenting a consistent interface for fetching supply, demand, and pricing information. The library depends on pandas for data manipulation, requests for HTTP access, and several parsing libraries (beautifulsoup4, lxml, pdfplumber, openpyxl, xlrd) to handle the variety of data formats ISOs publish—some as APIs, others as web-scraped pages or file downloads.

The package is maintained by Grid Status and actively developed (last release 2026-04-21, last commit 2026-08-13). It is designed for research, analysis, and integration into energy market monitoring tools. The documentation notes that this library provides minimally-processed raw data; for production use cases, the maintainers recommend their hosted API instead. Installation is straightforward and requires Python 3.10 or higher.

Use it for

  • Fetch real-time or historical electricity demand and supply data from a specific ISO for market analysis
  • Build a monitoring dashboard that aggregates pricing data across multiple ISOs for comparison
  • Integrate grid status data into an energy trading or forecasting model
  • Analyze historical load patterns and pricing trends across North American electricity markets
  • Scrape and normalize electricity data for research or academic energy studies

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, if you need programmatic access to raw electricity market data from US or Canadian ISOs and can handle minimally-processed data.

The library is actively maintained, has low install friction, and covers a wide range of ISOs. However, for production systems requiring guaranteed uptime and data quality, the maintainers recommend their hosted GridStatus.io API instead. License is permissive (BSD 3-Clause) and no known vulnerabilities are recorded.

Install

gridstatus on PyPI

Before you install

Low friction install with a pure-Python wheel. Active maintenance (last commit 2026-08-13) and 439 GitHub stars. Requires Python 3.10+ and supports current versions. Some parsers require environment variables for API credentials.

Requires Python 3.10 or higher. Some ISO parsers require environment variables for authentication or API access (see .env.template in repository).

License in practice

BSD 3-Clause license (unclear SPDX classification in metadata). Permits commercial and private use with attribution and liability disclaimer; derivative works allowed under same terms.

Quickstart

pip install gridstatus

import gridstatus

# Fetch CAISO data
data = gridstatus.CAISO().get_load()

Verify before relying

  • Whether all 10 supported ISOs are equally well-maintained and have current data coverage
  • Latency and update frequency for real-time data from each ISO
  • Rate limits or throttling policies for data access
  • Whether production use should prefer the hosted GridStatus.io API over this library

Package facts

LicenseNot declared unclear
Python supportSupports the current Python release <3.15,>=3.10
Install frictionLow. Pure-Python wheel
Runtime dependencies
22 packages
beautifulsoup4certificryptographyfilelockfrozendicth11lxmlopenpyxlpandaspdfplumberplotlyrequestsrpds-pysetuptoolstabulatetermcolortqdmurllib3virtualenvxlrdxmltodictzipp
MaintenanceActively maintained 115 days since the last release
Last repo commit
First released
Downloads93,663 / month, #13,373 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14

Evidence: gridstatus-0.36.0-py3-none-any.whl

Tags

Capabilities
electricity market data apiiso grid data pythoncaiso miso ercot datapower grid pricing dataenergy supply demand dataindependent system operator apireal-time electricity datagrid status data access
Topics
energy-datamarket-datagrid-monitoring
PyPI keywords
energyindependent system operator

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See also energyzero · openbb-us-eia · power-grid-model · opower · pandapower · entsoe-py · energyquantified · wapi-python · pyTibber · amberelectric