Awkward Array

Overview

Use this skill to apply Awkward 2.0 best practices for jagged arrays, especially in HEP-style event data models. Keep guidance lean in this file and load reference notes only when needed.

Core workflow

1. Build an event data model (records) with

   ak.zip

   .
2. Filter early at the event level.
3. Perform combinatorics or derived calculations.
4. Add derived fields back into the record with

   ak.with_field

   .
5. Repeat until the final values are present in the EDM.

Reference guide

Load only the reference files that matches the task:

• references/best-practices.md

  : use when setting overall approach or reminding about Awkward 2.0 usage and axes.

• references/records.md

  : use when building records or adding fields.

• references/filtering-aggregation.md

  : use for boolean masking,

  ak.sum

  /

  ak.count

  /

  ak.num

  , and axis guidance.

• references/sorting.md

  : use for

  ak.sort

  .

• references/combinatorics.md

  : use for pairings or n-way combinations (

  ak.cartesian

  ,

  ak.combinations

  ).

• references/argmin-argmax.md

  : use when selecting min/max elements in jagged lists.

• references/flattening.md

  : use for

  ak.flatten

  behavior and axis rules.

• references/numpy-interop.md

  : use when mixing NumPy operations with Awkward arrays.

• references/pitfalls.md

  : use for common API mistakes and missing functions.

• references/awkward-files.md

  : use for file I/O patterns (read/write) with Awkward arrays.

Constraints

• Use Awkward 2.0 APIs and syntax only.
• Avoid

  axis=None

  unless the function explicitly supports it.
• Ensure

  awkward

  is listed as a dependency in the active environment (venv plus

  pyproject.toml

  or

  requirements.txt

  ).