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NumPy best practices: arrays and performance v1.0.0

Use this resource to write vectorized numerical code with NumPy

New

  • 406 downloads
  • 228 likes
  • 210 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install numpy-vectorized-array-code

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent writes or reviews NumPy code: array creation and manipulation, indexing, data types, vectorization and memory management. It also applies validation and linear algebra rules.

Mostly picked by

Updated November 2, 2026

Card for the “NumPy best practices: arrays and performance” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
Apache-2.0

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What you get

  • SKILL.md: principles, array creation and manipulation
  • SKILL.md: indexing, data types and vectorization
  • SKILL.md: memory management, validation, random numbers and linear algebra

Good fit for

  • Your Python loop over arrays is too slow
  • You move scientific computations into production code

Not for

    Tags

    • numpy
    • vectorization
    • arrays
    • numerical computing

    About

    You say

    “Replace this double loop over a matrix with vectorized NumPy operations.”

    Card for the “NumPy best practices: arrays and performance” skill

    Skill published by mindrally under the Apache-2.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to write vectorized numerical code with NumPy
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE11.3 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md4 KB

    Origin and licence

    Listed unmodified

    Author
    mindrally
    Source
    github.com/mindrally/skills/tree/7682ca77710e0971eab4e0ae5dddfa281aea0ba5/numpy-best-practices
    Licence
    Apache-2.0

    Notice

    « numpy-best-practices » (mindrally, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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