dask-awkward
Awkward Array meets Dask
Decision gist · record as of 2026-08-14
Yes. Dask-awkward is actively maintained, production-ready, has no security vulnerabilities, and carries a permissive license. Install friction is low and its dependency tree is clean. It solves a real problem—distributed computation on complex, nested data—that has no obvious alternative in the Python ecosystem. Install it if you work with Awkward Arrays at scale or need lazy evaluation of nested structures across multiple workers.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Low friction installation with a pure-Python wheel.
- Actively maintained as of August 2026 with recent commits; marked Production/Stable.
License · maintenance · safety
BSD-3-Clause (permissive) — BSD-3-Clause is permissive; you may use, modify, and distribute this package freely in commercial or private projects provided you include the license notice.
last release 2026-02-24 (171 days) · last repo commit 2026-08-11 · 70 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 404,206 downloads/mo, #6,913 on PyPI
Alternatives
Verify before relying
pip install dask-awkward
import dask_awkward as dak
import awkward as ak
# Create a dask-backed awkward array
data = ak.Array([[1, 2], [3, 4, 5]])
dask_data = dak.from_awkward(data, npartitions=2)
result = dask_data.compute()- Whether the package handles all Awkward Array operations or only a subset in distributed mode.
- Performance characteristics and scalability limits for typical workloads.
- Whether it supports GPU acceleration through Dask's GPU backends.
What it is and what it does
Dask-awkward bridges two libraries: Awkward Array, which handles complex, nested, and ragged data structures, and Dask, which orchestrates distributed and lazy computation. The package lets you partition Awkward Arrays across multiple workers and compute on them in parallel, useful for scientific and data-analysis workflows where data doesn't fit in memory or where you want to exploit multiple cores. It depends on awkward, dask, cachetools, and typing-extensions.
The library is actively maintained, marked Production/Stable, and supports Python 3.10 through 3.14. Installation is straightforward via pip or conda-forge. It has no known security vulnerabilities and carries a permissive BSD-3-Clause license, making it suitable for both open-source and commercial use.
Use it for
- Process large nested datasets (e.g., physics event data) that exceed single-machine memory by distributing computation across a cluster.
- Perform lazy, out-of-core analysis on ragged or columnar data without loading everything into RAM upfront.
- Parallelize scientific computations on complex data structures across multiple CPU cores on a single machine.
- Build data pipelines that combine Awkward Array's flexible data model with Dask's task scheduling and fault tolerance.
- Integrate nested-data processing into existing Dask workflows for machine learning or data science projects.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Dask-awkward is actively maintained, production-ready, has no security vulnerabilities, and carries a permissive license. Install friction is low and its dependency tree is clean. It solves a real problem—distributed computation on complex, nested data—that has no obvious alternative in the Python ecosystem. Install it if you work with Awkward Arrays at scale or need lazy evaluation of nested structures across multiple workers.
Install
dask-awkward on PyPI
Before you install
Low friction installation with a pure-Python wheel. Actively maintained as of August 2026 with recent commits; marked Production/Stable. Depends on four runtime packages (awkward, dask, cachetools, typing-extensions), all established libraries.
Requires Python 3.10 or later.
License in practice
BSD-3-Clause is permissive; you may use, modify, and distribute this package freely in commercial or private projects provided you include the license notice.
Quickstart
pip install dask-awkward
import dask_awkward as dak
import awkward as ak
# Create a dask-backed awkward array
data = ak.Array([[1, 2], [3, 4, 5]])
dask_data = dak.from_awkward(data, npartitions=2)
result = dask_data.compute()Verify before relying
- Whether the package handles all Awkward Array operations or only a subset in distributed mode.
- Performance characteristics and scalability limits for typical workloads.
- Whether it supports GPU acceleration through Dask's GPU backends.
Package facts
| License | BSD-3-Clause permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesawkwardcachetoolsdasktyping-extensions |
| Maintenance | Actively maintained 171 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 404,206 / month, #6,913 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Information TechnologyIntended Audience :: Science/ResearchLicense :: OSI Approved :: BSD LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: MathematicsTopic :: Scientific/Engineering :: PhysicsTopic :: Software Development |
Evidence: dask_awkward-2026.2.1-py3-none-any.whl
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See also awkward-cpp · awkward-pandas · awkward · awkward0 · dask · dask-image · fastjet · dask-ml · distributed · dask-glm