Grid2Op
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Overview
HEALTH SCORE
Concerning*
Partial score (2/3 categories)
27out of 65
Maintainer coverage is the lead risk. Development cadence is present but not enough to offset the structural risk. Security & Supply Chain is unavailable, so weights were redistributed.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Concerning*(27/65)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 2 days.
Bus factor
Only 2 active maintainers currently have merge rights.
Organization Diversity
Contributors span 21 organizations.
Project Achievements
Leaderboards
About
An open source Python framework designed for modeling and simulating sequential decision-making processes in power systems, primarily used for developing and evaluating intelligent control agents (e.g., using reinforcement learning) to manage and optimize grid operations
First commit
Software value
$205M
Tags
grid2op
reinforcement-learning
reinforcement-learning-environments
powergrid
powergrid-operation
gym-environments
reinforcement-learning-algorithms
baseline
grid
kpi
load-flow
powerflow
python
human-computer-interaction
License(s)
MPL-2.0
Apache-2.0
Data sources
Git
GitHub