azureml-dataprep
Azure ML Data Preparation SDK is used to load, transform, and write data for machine learning workflows
Decision gist · record as of 2026-08-14
Yes, if you are building on Azure ML and need data preparation within that ecosystem. No, if you need a general-purpose data manipulation library or are working outside Azure ML—use pandas, polars, or dask instead. The package's 'internal' designation and lack of standalone documentation suggest it is meant as a dependency, not a primary tool.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.10; intended for use within Azure ML workflows, not as a standalone library.
- Low install friction with a pure-Python wheel distribution.
- Actively maintained as of 18 days ago.
License · maintenance · safety
(unclear) — Licensed under a proprietary license with unclear terms. Review Microsoft's licensing documentation before deploying in production or redistributing.
last release 2026-07-27 (18 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 997,554 downloads/mo, #4,544 on PyPI
Alternatives
Verify before relying
pip install azureml-dataprep
import azureml.dataprep as dprep
df = dprep.read_csv('data.csv')- Specific data formats and transformations supported beyond 'load, transform, write'
- Whether direct use outside Azure ML environments is supported despite the 'internal' disclaimer
- Performance characteristics and scalability limits for large datasets
What it is and what it does
Azure ML Data Prep is a data handling SDK designed for machine learning workflows on Azure. It provides utilities to load, transform, and write data in formats suitable for ML pipelines. The package is marked as internal and not intended for direct use, suggesting it is primarily consumed as a dependency of higher-level Azure ML tools rather than as a standalone library.
The package supports Python 3.10 through 3.13 and has low install friction via a pure-Python wheel. Its runtime dependencies include Azure identity services, serialization tools (cloudpickle), and configuration utilities (jsonschema, pyyaml), reflecting its role within the Azure ML ecosystem. No known security vulnerabilities are recorded.
Use it for
- Prepare and load data within Azure ML training pipelines and experiments
- Transform tabular data (CSV, Parquet, etc.) for ML model ingestion in Azure environments
- Write processed datasets back to cloud storage as part of ML workflows
- Handle data serialization and schema validation in distributed ML jobs on Azure
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building on Azure ML and need data preparation within that ecosystem.
No, if you need a general-purpose data manipulation library or are working outside Azure ML—use pandas, polars, or dask instead. The package's 'internal' designation and lack of standalone documentation suggest it is meant as a dependency, not a primary tool.
Install
azureml-dataprep on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Actively maintained as of 18 days ago. Depends on several Azure and utility packages (cloudpickle, jsonschema, pyyaml) that are standard in ML environments.
Requires Python >=3.10; intended for use within Azure ML workflows, not as a standalone library.
License in practice
Licensed under a proprietary license with unclear terms. Review Microsoft's licensing documentation before deploying in production or redistributing.
Quickstart
pip install azureml-dataprep
import azureml.dataprep as dprep
df = dprep.read_csv('data.csv')Verify before relying
- Specific data formats and transformations supported beyond 'load, transform, write'
- Whether direct use outside Azure ML environments is supported despite the 'internal' disclaimer
- Performance characteristics and scalability limits for large datasets
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesazureml-dataprep-nativeazureml-dataprep-rslexcloudpickleazure-identityjsonschemapyyamlpip |
| Maintenance | Actively maintained 18 days since the last release |
| First released | |
| Downloads | 997,554 / month, #4,544 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 :: Science/ResearchLicense :: Other/Proprietary LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/Engineering |
Evidence: azureml_dataprep-5.5.0-py3-none-any.whl
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See also azureml-dataprep-native · azureml-dataprep-rslex · azureml-pipeline · azureml-pipeline-core · azure-ml-component · azureml-dataset-runtime · azureml-automl-core · azureml-pipeline-steps · azureml-train-automl-client · azureml-sdk