BT
Kismuz/btgym
Scalable, event-driven, deep-learning-friendly backtesting library
1.0k 260 +0/wk
GitHub
a3c advantage-actor-critic algorithmic-trading-library algoritmic-trading backtesting-trading-strategies backtrader deep-reinforcement-learning gym-environment hacktoberfest openai-gym policy-gradient policy-optimisation
Trend
0
Star & Fork Trend (18 data points)
Stars
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Growth Velocity
Kismuz/btgym has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | btgym | Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow | dreamerv2 | SimplerEnv |
|---|---|---|---|---|
| Stars | 1.0k | 1.0k | 1.0k | 1.0k |
| Forks | 260 | 423 | 211 | 186 |
| Weekly Growth | +0 | +1 | +0 | +3 |
| Language | Python | Jupyter Notebook | Python | Jupyter Notebook |
| Sources | 1 | 1 | 1 | 1 |
| License | LGPL-3.0 | N/A | MIT | MIT |
Capability Radar vs Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow
btgym
Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow
Maintenance Activity 0
Last code push 1684 days ago.
Community Engagement 100
Fork-to-star ratio: 25.2%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 70
Licensed under LGPL-3.0. Copyleft — check compatibility requirements.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.