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  • Getting started
  • User guide
  • API reference
  • Contributor guide
  • Release history

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  • 10 minutes to Awkward Array
  • Converting arrays
    • NumPy
    • Python objects
    • JSON
    • Arrow and Parquet
    • Pandas
    • Generic buffers
    • ROOT via RDataFrame
  • Creating new arrays
    • Arrays of lists
    • Arrays of records
    • Arrays of missing data
    • Arrays of strings
    • Unflattening and grouping
    • ArrayBuilder (easy & general)
    • Direct constructors (fastest)
  • Examining arrays
    • Data type
    • Single item detail [todo]
    • Listing fields/keys/columns
    • Simple slicing [todo]
    • Checking validity [todo]
  • Numerical math
    • NumPy functions [todo]
    • Awkward broadcasting [todo]
    • Reducing (sum/min/any/all) [todo]
    • Statistics (mean/var/std) [todo]
    • Using argmin/argmax [todo]
    • On GPUs [todo]
  • Working with strings
    • Reading UTF-8 binary streams
    • Extracting substrings with regex
    • Splitting and joining
  • Filtering data
    • By number of items [todo]
    • Cuts vs. masks [todo]
    • Using ragged arrays
    • Using arrays with missing values
  • Restructuring data
    • Zip/unzip and project
    • Adding fields to records
    • Renaming records [todo]
    • Flattening for plots
    • Padding/clipping for machine learning
    • Concatenating and interleaving [todo]
    • Sorting [todo]
  • Combinatorics
    • Cartesian and "n choose k" [todo]
    • Best match between collections [todo]
  • Using arrays in Numba
    • Supported features [todo]
    • Building array output [todo]
    • Working with CUDA
  • Specialized behavior
    • Subclassing Array/Record [todo]
    • Overriding NumPy functions [todo]
    • In Numba [todo]
    • For physics: Lorentz vectors [todo]
    • Differentiation using JAX
    • Building Awkward Arrays in C++
  • User guide
  • Using arrays in Numba

Using arrays in Numba#

  • Supported features [todo]
  • Building array output [todo]
  • Working with CUDA

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How to find the best match between two collections using Cartesian (cross) product

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Awkward Array features that are supported in Numba-compiled functions
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© Copyright 2022, Awkward Array development team.

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Support for this work was provided by NSF cooperative agreement OAC-1836650 (IRIS-HEP), grant OAC-1450377 (DIANA/HEP), PHY-1520942 (US-CMS LHC Ops), and OAC-2103945 (Awkward Array).

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