How to Install and Uninstall python3-dask Package on Kali Linux
Last updated: November 06,2024
1. Install "python3-dask" package
Please follow the steps below to install python3-dask on Kali Linux
$
sudo apt update
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$
sudo apt install
python3-dask
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2. Uninstall "python3-dask" package
This guide let you learn how to uninstall python3-dask on Kali Linux:
$
sudo apt remove
python3-dask
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the python3-dask package on Kali Linux
Package: python3-dask
Source: dask
Version: 2023.12.1+dfsg-2
Installed-Size: 5011
Maintainer: Debian Python Team
Architecture: all
Depends: python3-fsspec, python3-toolz, python3-click, python3-cloudpickle, python3-importlib-metadata, python3-packaging, python3-partd, python3-yaml, python3:any
Recommends: python3-numpy, python3-pandas, python3-requests
Suggests: ipython, python-dask-doc, python3-blosc, python3-boto, python3-distributed, python3-graphviz, python3-h5py, python3-jinja2, python3-psutil, python3-scipy, python3-skimage, python3-sklearn, python3-sqlalchemy, python3-tables
Size: 920800
SHA256: cd5feeacd003239815ea9cd6f5b13fa2c512ef10c1392a01b1df145189139007
SHA1: c436e192475f50bfa54c61a7b300de52bc4ed0f4
MD5sum: 37f40263dd5759aa96fe8eddd9472f92
Description: Minimal task scheduling abstraction for Python 3
Dask is a flexible parallel computing library for analytics,
containing two components.
.
1. Dynamic task scheduling optimized for computation. This is similar
to Airflow, Luigi, Celery, or Make, but optimized for interactive
computational workloads.
2. "Big Data" collections like parallel arrays, dataframes, and lists
that extend common interfaces like NumPy, Pandas, or Python iterators
to larger-than-memory or distributed environments. These parallel
collections run on top of the dynamic task schedulers.
.
This contains the Python 3 version.
Description-md5:
Homepage: https://github.com/dask/dask
Section: python
Priority: optional
Filename: pool/main/d/dask/python3-dask_2023.12.1+dfsg-2_all.deb
Source: dask
Version: 2023.12.1+dfsg-2
Installed-Size: 5011
Maintainer: Debian Python Team
Architecture: all
Depends: python3-fsspec, python3-toolz, python3-click, python3-cloudpickle, python3-importlib-metadata, python3-packaging, python3-partd, python3-yaml, python3:any
Recommends: python3-numpy, python3-pandas, python3-requests
Suggests: ipython, python-dask-doc, python3-blosc, python3-boto, python3-distributed, python3-graphviz, python3-h5py, python3-jinja2, python3-psutil, python3-scipy, python3-skimage, python3-sklearn, python3-sqlalchemy, python3-tables
Size: 920800
SHA256: cd5feeacd003239815ea9cd6f5b13fa2c512ef10c1392a01b1df145189139007
SHA1: c436e192475f50bfa54c61a7b300de52bc4ed0f4
MD5sum: 37f40263dd5759aa96fe8eddd9472f92
Description: Minimal task scheduling abstraction for Python 3
Dask is a flexible parallel computing library for analytics,
containing two components.
.
1. Dynamic task scheduling optimized for computation. This is similar
to Airflow, Luigi, Celery, or Make, but optimized for interactive
computational workloads.
2. "Big Data" collections like parallel arrays, dataframes, and lists
that extend common interfaces like NumPy, Pandas, or Python iterators
to larger-than-memory or distributed environments. These parallel
collections run on top of the dynamic task schedulers.
.
This contains the Python 3 version.
Description-md5:
Homepage: https://github.com/dask/dask
Section: python
Priority: optional
Filename: pool/main/d/dask/python3-dask_2023.12.1+dfsg-2_all.deb