Skip to main content

Azure ML Data Preparation RustLex

Project description

Azure Machine Learning Data Prep RsLex

Azure Machine Learning Data Prep RsLex is a Rust implementation of Data Prep's capabilities to load, transform, and write data for machine learning workflows. You can interact with RsLex via the Data Prep SDK, azureml-dataprep, by calling use_rust_execution(True) before using the SDK.

Install the SDK

To install Azure Machine Learning Data Prep RsLex, use the following command:

pip install --upgrade azureml-dataprep-rslex

NOTE: This package is not intended for direct installation or usage. azureml-dataprep depends on this package.

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

azureml_dataprep_rslex-2.17.10-cp310-cp310-win_amd64.whl (16.5 MB view details)

Uploaded CPython 3.10 Windows x86-64

azureml_dataprep_rslex-2.17.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

azureml_dataprep_rslex-2.17.10-cp310-cp310-macosx_10_9_x86_64.whl (17.4 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

azureml_dataprep_rslex-2.17.10-cp39-cp39-win_amd64.whl (16.5 MB view details)

Uploaded CPython 3.9 Windows x86-64

azureml_dataprep_rslex-2.17.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

azureml_dataprep_rslex-2.17.10-cp39-cp39-macosx_10_9_x86_64.whl (17.4 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

azureml_dataprep_rslex-2.17.10-cp38-cp38-win_amd64.whl (16.5 MB view details)

Uploaded CPython 3.8 Windows x86-64

azureml_dataprep_rslex-2.17.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

azureml_dataprep_rslex-2.17.10-cp38-cp38-macosx_10_9_x86_64.whl (17.4 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

azureml_dataprep_rslex-2.17.10-cp37-cp37m-win_amd64.whl (16.5 MB view details)

Uploaded CPython 3.7m Windows x86-64

azureml_dataprep_rslex-2.17.10-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20.2 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

azureml_dataprep_rslex-2.17.10-cp37-cp37m-macosx_10_9_x86_64.whl (17.4 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 296df7911b2f54a2994bbbb2aaf10581ebd2cd6e3a7e3d2635b595345352b56d
MD5 790d1a920fc6798189d229046772d0e8
BLAKE2b-256 6c576b11f9c83b1b0b752b5dc1cafe918f9b4182819f117f6fea27dbcbca5c74

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1275101958c3fa87d356017fc311be2c7e81a854ef11d1e772bbe36307fdbe99
MD5 120cd77502e52a6b71a540fc34cab410
BLAKE2b-256 ef63e8af1e2cad4c12e0c988563023c7100f16a20176acaddfbd20cf2a21a2f9

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 307bd53c6f1ed08869f13ecefcc6e27452ef1e772973d632ca0fd49fbd591b6b
MD5 fc3a0dfd10c19812cb92d6d3bfb7107a
BLAKE2b-256 2c24c1b76f621df751f32e8555837b321c4b5fbdb6ac7a8e2a1edf884a0564c9

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 7d49af4c8c953319ebe9e68a02f3c169a3ae7466a8ada5740eba49485d6ed90b
MD5 4f1ad2d0d61a74bef8ce146ff4df983c
BLAKE2b-256 a8dde61bbba76d5c16ce5f971115c762e4ffb3c72418fc2432ef5c068f1f3419

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 95bacd386b2938a1d85293dc7e7907a7e88c83afabdf9cb3a8ee5f4715186fe2
MD5 aa3ac669dd79c23d38a0074cc401cd66
BLAKE2b-256 133f351f24cd609b5b3e95662c7cbd455907bee0b11648230db5ae88adbd4caa

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8d8bd65e9df3928a0cb21a717e3b76879db8885ba2a5ab57023260cee58a886b
MD5 7acc751d24a8c7bbcd818b3d33345ae3
BLAKE2b-256 82f903d44523f4163fcb2072ffdd71bf0222d8055bb51d9cea2164ca9da20c9d

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 cfd9ec574b6bff33a46099552a07875e24caf5d821c359e69c1a61b528df74eb
MD5 70b39faa9fcbbbbf13318b5814f4bd55
BLAKE2b-256 a910892236722ccb202c741af9d1af210de1b0a80f4713b0611c50f4c5d28207

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1c660dc10b86d865594aa51445d9fe121582ba2c7aede922abc871a0b607a4ba
MD5 d3837e89efaba575d41c452189ca57e6
BLAKE2b-256 c42b1bb1a198e758bd4985fbd61d6a7e7a83cc83fed66ea69c54d449399c4e6c

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3b40c8bcd6f9267f8447ab664ba9b23223b118f868852101d4a039d1914972ac
MD5 2d1a0e7799b946927fc633ef9c84c8f5
BLAKE2b-256 c97d99ec0c823176cbc8fafa187c4940cd6fce3c21d45b09a1816781a347fddd

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 0aca93fb95c687ee7a9c4690ce8bfefbe5644d286c22b016017bd45906938c34
MD5 527726e1169f65dbd7bb83e48b58f7a8
BLAKE2b-256 3cdabe3064432842eedbf9e37567ee3a40bf073db95cd76b8a28bf1b867f4919

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b0afe350f7012de7f50cb19ebeb85a1b2a45cfa9723a32d70ad301a94f82928b
MD5 f52bf2549149be42cbcc159423a7dc05
BLAKE2b-256 feb0c0b5441d8c777de1158cbd42f98ae9c06742729bf4b84bff65e3065c0b96

See more details on using hashes here.

File details

Details for the file azureml_dataprep_rslex-2.17.10-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for azureml_dataprep_rslex-2.17.10-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 82c1ab70e4baaa1cdf93dd1c10810501f90900304260171c8c57c7f20d9a5b43
MD5 14afecf7a89f261723ef89ef57246817
BLAKE2b-256 35d40afadabdf1839a677125ecf7e9ac93964961c0d85f7291905f67c6727dfd

See more details on using hashes here.

Supported by

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