| name | numpy |
| description | NumPy numerical computing with arrays. Use for numerical operations. |
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
for loops: Always vectorize operations.
References