Azure ML Data Preparation RustLex

These details have not been verified by PyPI

Project links

Homepage

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

These details have not been verified by PyPI

Project links

Homepage

Release history Release notifications | RSS feed

This version

2.25.7

Jul 10, 2026

2.25.6

Jul 2, 2026

2.25.5

Jun 24, 2026

2.25.4

Apr 9, 2026

2.25.3

Feb 9, 2026

2.25.2

Dec 2, 2025

2.25.1

Aug 13, 2025

2.25.0

Jul 18, 2025

2.24.6

Jul 2, 2025

2.24.5

Mar 26, 2025

2.24.4

Jan 24, 2025

2.24.3

Dec 31, 2024

2.24.2

Dec 21, 2024

2.24.1

Nov 29, 2024

2.24.0

Nov 1, 2024

2.23.8

Feb 27, 2025

2.23.7

Nov 7, 2024

2.23.6

Oct 11, 2024

2.23.5

Sep 11, 2024

2.23.4

Aug 29, 2024

2.23.3

Aug 16, 2024

2.23.2

Aug 15, 2024

2.23.1

Jul 23, 2024

2.23.0

Jun 28, 2024

2.22.5

Nov 8, 2024

2.22.4

Sep 11, 2024

2.22.3

Aug 16, 2024

2.22.2

Jan 24, 2024

2.22.1

Jan 17, 2024

2.22.0

Dec 23, 2023

2.21.1

Dec 18, 2023

2.21.0

Dec 8, 2023

2.20.4

Apr 15, 2024

2.20.3

Mar 19, 2024

2.20.2

Mar 13, 2024

2.20.1

Dec 19, 2023

2.20.0

Nov 8, 2023

2.19.8

Feb 2, 2024

2.19.7

Jan 11, 2024

2.19.6

Oct 18, 2023

2.19.5

Sep 27, 2023

2.19.3

Sep 15, 2023

2.19.2

Sep 1, 2023

2.19.1

Aug 12, 2023

2.19.0

Aug 12, 2023

2.18.7

Aug 11, 2023

2.18.6

Aug 3, 2023

2.18.5

Jul 31, 2023

2.18.4

Jul 2, 2023

2.18.3

Jun 6, 2023

2.18.2

Jun 1, 2023

2.18.1

May 27, 2023

2.18.0

May 25, 2023

2.17.12

Jun 1, 2023

2.17.11

May 12, 2023

2.17.10

May 11, 2023

2.17.9

May 9, 2023

2.17.8

May 5, 2023

2.17.7

Apr 27, 2023

2.17.6

Apr 21, 2023

2.17.5

Apr 4, 2023

2.16.4

Mar 16, 2023

2.15.2

Jan 13, 2023

2.14.0

Oct 26, 2022

2.13.0

Oct 21, 2022

2.12.1

Sep 26, 2022

2.11.4

Oct 4, 2022

2.10.0

Sep 6, 2022

2.9.1

Aug 27, 2022

2.8.1

Jul 15, 2022

2.7.1

Jun 23, 2022

2.6.3

May 27, 2022

2.5.5

Jun 4, 2022

2.4.3

Apr 19, 2022

2.3.1

Feb 16, 2022

2.2.0

Dec 31, 2021

2.1.1

Dec 15, 2021

2.0.3

Nov 12, 2021

1.21.2

Oct 7, 2021

1.20.2

Sep 8, 2021

1.19.1

Aug 16, 2021

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.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

azureml_dataprep_rslex-2.25.7-pp39-pypy39_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (25.8 MB view details)

Uploaded Jul 10, 2026 PyPymanylinux: glibc 2.17+ ARM64

azureml_dataprep_rslex-2.25.7-pp39-pypy39_pp73-manylinux1_x86_64.whl (26.6 MB view details)

Uploaded Jul 10, 2026 PyPy

azureml_dataprep_rslex-2.25.7-pp38-pypy38_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (25.8 MB view details)

Uploaded Jul 10, 2026 PyPymanylinux: glibc 2.17+ ARM64

azureml_dataprep_rslex-2.25.7-pp38-pypy38_pp73-manylinux1_x86_64.whl (26.6 MB view details)

Uploaded Jul 10, 2026 PyPy

azureml_dataprep_rslex-2.25.7-cp313-cp313-win_amd64.whl (18.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.13Windows x86-64

azureml_dataprep_rslex-2.25.7-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (25.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.13manylinux: glibc 2.17+ ARM64

azureml_dataprep_rslex-2.25.7-cp313-cp313-manylinux1_x86_64.whl (26.6 MB view details)

Uploaded Jul 10, 2026 CPython 3.13

azureml_dataprep_rslex-2.25.7-cp313-cp313-macosx_10_13_x86_64.whl (18.3 MB view details)

Uploaded Jul 10, 2026 CPython 3.13macOS 10.13+ x86-64

azureml_dataprep_rslex-2.25.7-cp312-cp312-win_amd64.whl (18.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.12Windows x86-64

azureml_dataprep_rslex-2.25.7-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (25.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.12manylinux: glibc 2.17+ ARM64

azureml_dataprep_rslex-2.25.7-cp312-cp312-manylinux1_x86_64.whl (26.6 MB view details)

Uploaded Jul 10, 2026 CPython 3.12

azureml_dataprep_rslex-2.25.7-cp312-cp312-macosx_10_13_x86_64.whl (18.3 MB view details)

Uploaded Jul 10, 2026 CPython 3.12macOS 10.13+ x86-64

azureml_dataprep_rslex-2.25.7-cp311-cp311-win_amd64.whl (18.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.11Windows x86-64

azureml_dataprep_rslex-2.25.7-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (25.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.11manylinux: glibc 2.17+ ARM64

azureml_dataprep_rslex-2.25.7-cp311-cp311-manylinux1_x86_64.whl (26.6 MB view details)

Uploaded Jul 10, 2026 CPython 3.11

azureml_dataprep_rslex-2.25.7-cp311-cp311-macosx_10_13_x86_64.whl (18.3 MB view details)

Uploaded Jul 10, 2026 CPython 3.11macOS 10.13+ x86-64

azureml_dataprep_rslex-2.25.7-cp310-cp310-win_amd64.whl (18.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.10Windows x86-64

azureml_dataprep_rslex-2.25.7-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (25.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.10manylinux: glibc 2.17+ ARM64

azureml_dataprep_rslex-2.25.7-cp310-cp310-manylinux1_x86_64.whl (26.6 MB view details)

Uploaded Jul 10, 2026 CPython 3.10

azureml_dataprep_rslex-2.25.7-cp310-cp310-macosx_10_13_x86_64.whl (18.3 MB view details)

Uploaded Jul 10, 2026 CPython 3.10macOS 10.13+ x86-64

azureml_dataprep_rslex-2.25.7-cp39-cp39-win_amd64.whl (18.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.9Windows x86-64

azureml_dataprep_rslex-2.25.7-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (25.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.9manylinux: glibc 2.17+ ARM64

azureml_dataprep_rslex-2.25.7-cp39-cp39-manylinux1_x86_64.whl (26.6 MB view details)

Uploaded Jul 10, 2026 CPython 3.9

azureml_dataprep_rslex-2.25.7-cp39-cp39-macosx_10_9_x86_64.whl (18.3 MB view details)

Uploaded Jul 10, 2026 CPython 3.9macOS 10.9+ x86-64

azureml_dataprep_rslex-2.25.7-cp38-cp38-win_amd64.whl (18.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.8Windows x86-64

azureml_dataprep_rslex-2.25.7-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (25.8 MB view details)

Uploaded Jul 10, 2026 CPython 3.8manylinux: glibc 2.17+ ARM64

azureml_dataprep_rslex-2.25.7-cp38-cp38-manylinux1_x86_64.whl (26.6 MB view details)

Uploaded Jul 10, 2026 CPython 3.8

azureml_dataprep_rslex-2.25.7-cp38-cp38-macosx_10_9_x86_64.whl (18.3 MB view details)

Uploaded Jul 10, 2026 CPython 3.8macOS 10.9+ x86-64

File details

Details for the file azureml_dataprep_rslex-2.25.7-pp39-pypy39_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl.

File metadata

Download URL: azureml_dataprep_rslex-2.25.7-pp39-pypy39_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
Upload date: Jul 10, 2026
Size: 25.8 MB
Tags: PyPy, manylinux: glibc 2.17+ ARM64
Uploaded using Trusted Publishing? No
Uploaded via: twine/6.2.0 CPython/3.12.10

File hashes

Hashes for azureml_dataprep_rslex-2.25.7-pp39-pypy39_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
Algorithm	Hash digest
SHA256	`d9e95b769f4f035b8c4919f1a7a7a94f700e6b0ec4c848fbf98744ebf39e71ad`
MD5	`aea5392191937d433406d3f86de86c5d`
BLAKE2b-256	`88f39def3bf2e0f0324e6b86d628f4793cb486d2d785babee8352f1d6752fe46`

Algorithm	Hash digest
SHA256	`684e8f6600da0d46cf90b3f588228e87bd75ee594fbcf2a67c147dd58001b20d`
MD5	`c65f75034eda68b30627be626c957469`
BLAKE2b-256	`53c381d975cd163e972e30eda8289dcbdfd6f59bc100369fe833846e67fd04ca`

Algorithm	Hash digest
SHA256	`0390691dd757c4c76d7bad715cedaf4f9b063485f27d5b8e0186c6b6c3995eee`
MD5	`47a35fe317368e21e88639cd12cb103e`
BLAKE2b-256	`65d07677aec22b2c9cede2446356ff8e3e3d9fbb887f04d4996c1e87dc0c4726`

Algorithm	Hash digest
SHA256	`55452c048d9e24d0b57df8ad1efb9a9294c9cba68073637874fbbc218ef26a9d`
MD5	`d699e2e651f38e3ef1979310590a4982`
BLAKE2b-256	`d50cda1db2a025af2d307225fe605eed1cc51daa9dfdf3531c528ecfe4977010`

Algorithm	Hash digest
SHA256	`5bb7b264c81e6669a768349df98a7c3a46131da532f91df9fe700ced9e0f80cf`
MD5	`124429966ef8e199ffc90567d4b5626b`
BLAKE2b-256	`d2c3c5a7d29fcd9f6705d8377c34920c796cd1d030e9981c32f1377523be567d`

Algorithm	Hash digest
SHA256	`6aa1f3f69be5970775b878e0317a39ea627f2f20c6c56c3f46be64546118fc52`
MD5	`5bdcf56bd4396eb00024c8e1714c889c`
BLAKE2b-256	`b4f8d55029acdd5e7d890d231627276de78bb385f9cc7055a86a307e06af7607`

Algorithm	Hash digest
SHA256	`39e5614b7efc75e09c32ed4b3fbd9a5c66bde5dcf15fff4013c9689cd866e9bf`
MD5	`feb9797ea384882a1818ae45d2c58fc0`
BLAKE2b-256	`9af8c112bf3d7746282f7cd6821c48347f41ab0be5ce340e9a41c07f8b405ca8`

Algorithm	Hash digest
SHA256	`0f4561beef670ef4883e14d0d1084f9ae319b4bdfc74618db6163430e684ccc3`
MD5	`c97547159e0c2c73c510dadf9441b244`
BLAKE2b-256	`f8de35828cb81b6a199ed40272c3c02291f30dddea4b18a6db260b0ccb9adebd`

Algorithm	Hash digest
SHA256	`c0f1d6e1d6546397def8e16e8650b8b13a09ab34642b45f4f98ee074527f3346`
MD5	`e62e468d7384035352af61cfad134210`
BLAKE2b-256	`545397706a7994e604bff2da9d855b3be07d9e9c16e4c6a7684259d6db813c33`

Algorithm	Hash digest
SHA256	`fce5aa116edc2017dff4cb1da698721254b4bbe8d835a3a6a651798ebb00a2f0`
MD5	`03e849505ece412df67f5abb86567e0c`
BLAKE2b-256	`63178d89b2a6c7570f7de3dd26e600713a2ad48d28bb8e982a21b299b64d5a6f`

Algorithm	Hash digest
SHA256	`581c440fc751b069ec44ba456c4985d9a72d53af3bfaf7eb72e1cafe4630f50d`
MD5	`c210fe53ba7335f0d921c17a61b3473e`
BLAKE2b-256	`dc948df9780102fb26dc776c64178ee653e1b0b931215ffe3b2901c562c642c7`

Algorithm	Hash digest
SHA256	`18f5a62139c8e634e9346f90700e6627956af031fd72a5724a7ad9100efec53e`
MD5	`610386d2143f8a6a5effa3730e4a452b`
BLAKE2b-256	`5c4d9bcca577a9e3bd7091d4096d27464a17698c962fa73860705154c04be036`

Algorithm	Hash digest
SHA256	`27e670f14f5e010ec84449072766f9a96848499c92ff2ab651258ff90cdfe47b`
MD5	`d5cdd7a4e6cabfe7b5f150db565334e3`
BLAKE2b-256	`9c7b02e29ffd715777b0d68c36399e690e8cf81462e090128cef8ae8ebc7c9b9`

Algorithm	Hash digest
SHA256	`6ef95efd22851ad2e704a04c4a1387b53226d07a42f0d5545107660e6946dcc5`
MD5	`8aff22c791a580844f2acf0a93748c78`
BLAKE2b-256	`5fe4c8f65b1d4e961e8980c499a6e0e41f7ca3cdcc1b4ca679896a0b265529fb`

Algorithm	Hash digest
SHA256	`1fac45ad7a2b348d542339ca7185692524937001a1b9983e73df3b7c1389d348`
MD5	`d414ab6754735f6c11623d051675920d`
BLAKE2b-256	`5ba4e14b7c47f994d195319f84022597428ace1575a32104315891e8237d887e`

Algorithm	Hash digest
SHA256	`56311fd59cb788c27f5227ca4dbcfb563a812f61d9cd00ae08916baeff65e385`
MD5	`dfdee30e49469116c57ec8198bbc1c47`
BLAKE2b-256	`a5d7a06a6cf5926fbffad4d9449d3be02b6f3902e470ff1a91ce14b02978fd40`

Algorithm	Hash digest
SHA256	`6a62926005e050d434f8df70a60c5ca9ee93dd959ca2db91af619a94b63f1289`
MD5	`d38a29ebafec6b5a095c3cc9f94ee3e5`
BLAKE2b-256	`fabad7ed9975fe799da7823c4fb561a55b1d95b3eed2540b0d44065087bebfb0`

Algorithm	Hash digest
SHA256	`53c16f64d4704145368d9abd83840d1acb61345b9d1ee8d4d2439b2a382d2d82`
MD5	`a7a20caa7f0950f6f7a0124609bbe330`
BLAKE2b-256	`1375499f91c70612390b160903021c4e2e80c66d1c7562233509364b5cac7feb`

Algorithm	Hash digest
SHA256	`a7bb3b795eeed35db8a7869a43a241f3aca082a1659bd085d2a6c70084c9c352`
MD5	`57a200cb42ff3ef6c397ffa3c21115f5`
BLAKE2b-256	`1d8bf395a77590dc6222cf717c64ba647167b62a18ffe646c881fd9e373e4022`

Algorithm	Hash digest
SHA256	`b247f576bcece0ae63e892c61ca9257f000b11185e66f847441e8bc7ba744c89`
MD5	`73879c07124fdda21261b5036e26dba8`
BLAKE2b-256	`fa518d0253715ae8261c2d8469f08ac41285a4360be5b86d42885166b2c9f37f`

Algorithm	Hash digest
SHA256	`9f751c8b9452da82d5bf2ed126bc166e1dfc926eea5ae8a0b14ae2bb9725e898`
MD5	`60ee5f765004fa6cfd5dd79eebc6c28a`
BLAKE2b-256	`b7753404abf1242075873d171940bf75e2054b742dd9823a1b808d27daf2053e`

azureml-dataprep-rslex 2.25.7

Navigation

Verified details

Maintainers

Unverified details

Project links

Meta

Classifiers

Project description

Azure Machine Learning Data Prep RsLex

Install the SDK

Project details

Verified details

Maintainers

Unverified details

Project links

Meta

Classifiers

Release history Release notifications | RSS feed

Download files

Source Distributions

Built Distributions

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

Algorithm	Hash digest
SHA256	`79d3112b2694b522c43a8f264c6aa4f5bff03d96780293dbf931f417d82defae`
MD5	`4657b589286b73ed0bc800e4bef2db7c`
BLAKE2b-256	`a1b3a5a46761e47c939036cc92bd39d660501ed98aec49a57df79be40be6071e`

Algorithm	Hash digest
SHA256	`6d99da68fdbb6c3476e8d620479b73fe6c2b899c4c67386d7ec06d32e3aefb25`
MD5	`1e43f00d02e2f995a0b70146ffd704cc`
BLAKE2b-256	`2db1a1a93ecfff611f8d47b49641f850c6298176d6e8df1b55c9ca0a1df442ee`

Algorithm	Hash digest
SHA256	`df1c9a3efc55e9abb66506e92c024d2e3cf2ce92d8bb6685b06bda186beb7ff7`
MD5	`bc8d7ddab6342d75cb6649825fd1d87b`
BLAKE2b-256	`ceb91b82c89cd085c5bbda9a3cbdff7139f8b67f9e33dada7cb565af5a0ed243`

Algorithm	Hash digest
SHA256	`b35a58589aba117477b87d0e8b50072568c4de40c942184d7f78e6c8b7224add`
MD5	`ac7a2707ee7ef7453b65aa1ecf82379a`
BLAKE2b-256	`13efc83072a18a3765274e857d3c960d16a4eb0a0ca4ef6210222cd0400e3a5f`

Algorithm	Hash digest
SHA256	`5bd41599bda714fd5a290e221b61da5f883deefa52dd47e134e6da341a2b5a64`
MD5	`818cb14744191effc3dbbe9997024323`
BLAKE2b-256	`1884a115f470f847dd1c5af57096c042076e7dd98fe54357e3cdc40ea5e72115`

Algorithm	Hash digest
SHA256	`842f39d6ac08e78e91431d3e933cad9ce2b68fa1a911f96e2668654ac784a165`
MD5	`75222e9328d735527745a22d596008d7`
BLAKE2b-256	`a774b3ef9c567c8098c6e8efca3856fd47612fb671fafea0eaf82111f9625353`

Algorithm	Hash digest
SHA256	`4be37c5b4eba716199501ed6f31df5f0c96ab3d1ea4562559e9210e0818204ba`
MD5	`17050452c7f185d575f488048bed7047`
BLAKE2b-256	`1168d551086acfc100bf38226ee7e46deaf5d4e06b185ba658405feb898b0af9`