azure-storage-file-datalake
Microsoft Azure File DataLake Storage Client Library for Python
Decision gist · record as of 2026-08-14
Yes. This is the official, actively maintained Azure SDK for Data Lake Storage Gen2 with no known vulnerabilities, low installation friction, and permissive MIT licensing. Install it if you need to interact with Azure Data Lake Storage from Python—it is the standard choice for this use case. Prerequisite: Python 3.9+ and an Azure storage account with hierarchical namespace enabled.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later and an existing Azure storage account with hierarchical namespace enabled.
- Low friction installation with a pure-Python wheel.
- Actively maintained with recent releases and no known vulnerabilities.
License · maintenance · safety
MIT License (permissive) — MIT License permits commercial and private use with minimal restrictions; you must include a copy of the license in distributions.
last release 2026-06-08 (67 days) · last repo commit 2026-08-14 · 5,587 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 37,198,883 downloads/mo, #728 on PyPI
Alternatives
Verify before relying
pip install azure-storage-file-datalake
from azure.storage.filedatalake import DataLakeServiceClient
service = DataLakeServiceClient.from_connection_string(conn_str="my_connection_string")- Whether async operations require additional setup beyond installing aiohttp as mentioned in the description.
- Performance characteristics and throughput limits for large-scale directory or ACL operations.
- Whether the package supports all Azure storage account types or only hierarchical namespace-enabled accounts.
What it is and what it does
azure-storage-file-datalake is the official Python client library for Azure Data Lake Storage Gen2, providing programmatic access to hierarchical file system operations on Azure storage accounts. It wraps the underlying Azure storage REST API and builds on azure-storage-blob and azure-core to deliver directory-level operations (create, rename, delete), atomic move operations, and permission management (get/set ACLs) for accounts with hierarchical namespace enabled.
The library exposes four main client types—DataLakeServiceClient for account-level operations, FileSystemClient for file system management, DatalakeDirectoryClient for directory operations, and DatalakeFileClient for file read/write/append—plus a lease client for resource locking. It supports both synchronous and asynchronous APIs, with async requiring an additional transport like aiohttp. Authentication is flexible, supporting SAS tokens, shared access keys, token credentials from azure-identity, or connection strings.
Use it for
- Upload, download, and manage files and directories in Azure Data Lake Storage from Python applications.
- Perform atomic rename and move operations on directories in hierarchical namespace-enabled storage accounts.
- Manage access control lists (ACLs) and permissions on files and directories programmatically.
- Build data pipeline or ETL workflows that interact with Azure Data Lake as a data source or sink.
- Enumerate and list paths within file systems for data discovery or metadata operations.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is the official, actively maintained Azure SDK for Data Lake Storage Gen2 with no known vulnerabilities, low installation friction, and permissive MIT licensing. Install it if you need to interact with Azure Data Lake Storage from Python—it is the standard choice for this use case. Prerequisite: Python 3.9+ and an Azure storage account with hierarchical namespace enabled.
Install
azure-storage-file-datalake on PyPI
Before you install
Low friction installation with a pure-Python wheel. Actively maintained with recent releases and no known vulnerabilities. Depends on azure-core and azure-storage-blob, which are stable Azure SDK components.
Requires Python 3.9 or later and an existing Azure storage account with hierarchical namespace enabled.
License in practice
MIT License permits commercial and private use with minimal restrictions; you must include a copy of the license in distributions.
Quickstart
pip install azure-storage-file-datalake
from azure.storage.filedatalake import DataLakeServiceClient
service = DataLakeServiceClient.from_connection_string(conn_str="my_connection_string")Verify before relying
- Whether async operations require additional setup beyond installing aiohttp as mentioned in the description.
- Performance characteristics and throughput limits for large-scale directory or ACL operations.
- Whether the package supports all Azure storage account types or only hierarchical namespace-enabled accounts.
Package facts
| License | MIT License permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesazure-coreazure-storage-blobtyping-extensionsisodate |
| Maintenance | Actively maintained 67 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 37,198,883 / month, #728 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/StableLicense :: OSI Approved :: MIT LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9 |
Evidence: azure_storage_file_datalake-12.25.0-py3-none-any.whl
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