Skip to main content

Data Preparation Toolkit Transforms using Ray

Project description

DPK Python Transforms

installation

The transforms are delivered as a standard pyton library available on pypi and can be installed using pip install:

python -m pip install data-prep-toolkit-transforms[all] or python -m pip install data-prep-toolkit-transforms[ray, all] or python -m pip install data-prep-toolkit-transforms[language]

installing the python transforms will also install data-prep-toolkit

installing the ray transforms will also install data-prep-toolkit[ray]

List of Transforms in current package

Note: This list includes the transforms that were part of the release starting with data-prep-toolkit-transforms:0.2.1. This list may not always reflect up to date information. Users are encourage to raise an issue in git when they discover missing components or packages that are listed below but not in the current release they get from pypi.

Release notes:

1.0.1.dev1

Added Gneissweb transforms
fdedup fix for windows

1.0.1.dev0

PR #979 (code_profiler)

1.0.0.a6

Added Profiler
Added Resize

1.0.0.a5

Added Pii Redactor
Relax fasttext requirement >= 0.9.2

1.0.0.a4

Added missing ray implementation for lang_id, doc_quality, tokenization and filter
Added ray notebooks for lang id, Doc Quality, tokenization, and Filter

1.0.0.a3

Added code_profiler

1.0.0.a2

Relax dependencies on pandas (use latest or whatever is installed by application) Relax dependencies on requests (use latest or whatever is installed by application)

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-py3-none-any.whl
Algorithm Hash digest
SHA256 11d72ace139228e9ee522aebb02ffccd61fa8137d7aa9a6ba6629db04ff508ac
MD5 6180af119e6dca007af6ee180cab4b17
BLAKE2b-256 1dedc8bef6e62d90b4b84f2a2ad506f392d33f45bd36423acc0325a8d67ed264

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-9-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-9-py3-none-any.whl
Algorithm Hash digest
SHA256 7c871938b49c170e7348ec1c3a00812d3faada5fae14c5ec9c2a6fdc71429d6e
MD5 f1b9550c1a553a9c07ce1007b3f43351
BLAKE2b-256 891768428cd51675cf31a912db67ac7a2abcb566e43b4320fc5966202e003d89

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-8-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-8-py3-none-any.whl
Algorithm Hash digest
SHA256 483979a28b5b78b14dd8ed85ea20706ce23af2b06e9ebd9eb1c971ed1e7c73a4
MD5 0d603ead8e243e39d91f46639032e464
BLAKE2b-256 a56f163669f3c64910d06e2aab09f5db9f70b56f47e24a1ce33889bf818919a0

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-7-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-7-py3-none-any.whl
Algorithm Hash digest
SHA256 74373ea5609a033efa41433ec5b5915d6a00ad095f40eedf5eda9b32aa4f7905
MD5 1bcebcd0def2d1fc06cbded170976e49
BLAKE2b-256 fded019dfc9e264a27a95d46a4ffbaf571567aa6a8733dae9e34a7a43e7138e0

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-6-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-6-py3-none-any.whl
Algorithm Hash digest
SHA256 326ce84807d10c520de39e7be752bc75afc3ca80778040adcc3ab1399b6e9429
MD5 25cb49f5103f2e315df56713164a96c2
BLAKE2b-256 373e699bde3476f87cca66ee775b96d1fa0f9840ff3744af585ac29157473312

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-5-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-5-py3-none-any.whl
Algorithm Hash digest
SHA256 74d61f9174744b10659eb33dc47e28c43ddadc30aa87ab33ab3a355cefce81dc
MD5 a1738b2803b271522eca0c121ea66dd8
BLAKE2b-256 1674af50945c273f9638ca73d632f84a26573d9052c35d7f748d650cafb481c4

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-4-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-4-py3-none-any.whl
Algorithm Hash digest
SHA256 430e5e03e7b93f4b74ded12dc96678f5403424af4a0d55980c405ed47874f80f
MD5 6bdef1aeaed0f8d0302adffe83a4b418
BLAKE2b-256 aa99d387dc36193eae445d3f0fedfd9e056a87b6e07c1930af7f2f9fc6c932ab

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-3-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-3-py3-none-any.whl
Algorithm Hash digest
SHA256 144ee472275cf1fdd6f705e77e6093ef376fc8ccf94e1a41e25ee4d8c57f1bcb
MD5 4c5697413db9bb85032f306f52ab3e9f
BLAKE2b-256 a36082a8cb96397c2f83a79f222d6858f63028a8ab6fa1476778311dda9a2684

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-2-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-2-py3-none-any.whl
Algorithm Hash digest
SHA256 226d2c1d96548773f6920f10a3d1807cec9d52140d1275a85ea2e0c347cd017b
MD5 9bd9ea0224c11049a640ac973a9ffb4e
BLAKE2b-256 e82fa54851ada52bf9432e314c39b2a8daa92ad2ae44da6730e0aef05932e48b

See more details on using hashes here.

File details

Details for the file data_prep_toolkit_transforms-1.0.1.dev1-1-py3-none-any.whl.

File metadata

File hashes

Hashes for data_prep_toolkit_transforms-1.0.1.dev1-1-py3-none-any.whl
Algorithm Hash digest
SHA256 46970087474785ea4444136d831b7e63f8c2a67992d35717f2e2a8ca26af3719
MD5 68a0e294041b651fd08ec2a27ecc5341
BLAKE2b-256 2decfc0ceb26b114f8039de1b099031c368ddba0abeb345bbd5a4a7dd1d3a23a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page