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awkward-cpp

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awkward-cpp provides the highly optimized C++ and CUDA kernels and compiled extensions that power the Awkward Array library (version 2.x). It serves as a performance backend, enabling NumPy-like idioms for nested, variable-sized data structures to run at compiled speeds. The library itself is not intended for direct end-user interaction but is a core dependency of the main `awkward` package. It is currently at version 52 and maintains an active release cadence aligned with `awkward` releases.

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Install & Compatibility
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Code
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awkward-cpp provides low-level kernels and does not expose a direct Python API for end-users. Its features are integrated into the 'awkward' library's public API.

Functionality is accessed via the 'awkward' library, e.g., 'import awkward as ak'

Demonstrates basic usage of the Awkward Array library, which internally utilizes `awkward-cpp` for efficient computation. Users typically interact with the `awkward` API, not `awkward-cpp` directly.

import awkward as ak import numpy as np # Create a nested, variable-sized Awkward Array array = ak.Array([[1, 2, 3], [], [4, 5]]) print(f"Original Array: {array}, type: {array.type}") # Perform a vectorized operation (e.g., multiply by 2) result = array * 2 print(f"Result of array * 2: {result}, type: {result.type}") # Use a NumPy ufunc directly (works because of Awkward's NumPy-like behavior) sum_per_list = ak.sum(array, axis=1) print(f"Sum per list: {sum_per_list}, type: {sum_per_list.type}")
Debug
Known footguns
breakingAs of `awkward` version 2.9.0 (and consequently `awkward-cpp` version 52 and later), Python 3.9 is no longer supported. Users must upgrade to Python 3.10 or newer.
gotchaawkward-cpp primarily provides CPU kernels. For GPU acceleration, `awkward` leverages CuPy and specific CUDA kernels. Users must explicitly use `ak.to_backend('cuda')` and ensure CuPy is installed if they intend to run operations on a GPU, as `awkward-cpp` does not handle GPU computation itself.
gotchaAwkward Arrays are designed to be immutable, meaning operations create new arrays rather than modifying existing ones in-place. However, if an Awkward Array is created from a mutable underlying data structure (like a NumPy array), modifying the original data structure in-place will also modify the Awkward Array referencing it. To prevent this, make an explicit deep copy using `ak.copy()`.
gotchaWhile `awkward-cpp` is installable directly via pip, it is primarily a low-level dependency. Attempting to import or use it directly for high-level data manipulation will not work as it does not expose a public Python API for end-users. All high-level functionality is provided by the `awkward` library.
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Resources
githubhttps://github.com/scikit-hep/awkward-1.0 ↗
packagehttps://pypi.org/project/awkward-cpp/ ↗
docshttps://awkward-array.org ↗
changeloghttps://github.com/scikit-hep/awkward-1.0/releases ↗