Numpy
NumPy numerical computing with arrays. Use for numerical operations.From its SKILL.md
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SKILL.md
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NumPy
NumPy is the bedrock of the Python ecosystem. v2.0 (2024) brought the first major ABI change in 15 years, improving performance and API consistency.
When to Use
- Linear Algebra: Matrix multiplication, eigenvalues.
- Array Manipulation: Reshaping, broadcasting.
- Foundation: When building libraries (like PyTorch or Pandas).
Core Concepts
Broadcasting
The magic rule that allows array(3x1) + array(3) to work.
Dtypes
Precision matters. float32 vs float64.
Stride Tricks
Efficient memory views without copying data.
Best Practices (2025)
Do:
- Check v2.0 compat: Many old libraries broke with NumPy 2.0.
- Use
numpy.strings: New string kernels in v2.0 are much faster.
Don't:
- Don't write
forloops: Always vectorize operations.
References
What ships with it
Read from the repository
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