azure-datalake-store
Azure Data Lake Store Filesystem Client Library for Python
Decision gist · record as of 2026-08-14
Yes, if you are already committed to Azure Data Lake Store Gen1 and need Python filesystem access. The low install friction, permissive MIT license, and lack of known vulnerabilities make it safe to use. However, the aging maintenance status (437 days since last release) and Alpha classification suggest checking whether Microsoft recommends this library for new projects or whether you should evaluate newer Azure SDK alternatives first.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Azure credentials (tenant ID, username, password) and an active Azure Data Lake Store account to authenticate and connect.
- Low install friction with only two runtime dependencies (cffi and requests).
- Maintenance is aging—last release was 437 days ago, though the repository remains active with a recent commit on 2025-06-03.
License · maintenance · safety
MIT License (permissive) — MIT License (permissive) allows use in commercial and private projects with minimal restrictions, requiring only attribution and inclusion of the license notice.
last release 2025-06-03 (437 days) · last repo commit 2025-06-03 · 76 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 23,057,159 downloads/mo, #959 on PyPI
Alternatives
Verify before relying
pip install azure-datalake-store
from azure.datalake.store import core, lib
token = lib.auth(tenant_id, username, password)
adl = core.AzureDLFileSystem(token, store_name=store_name)
adl.ls('')
with adl.open('file.csv') as f:
print(f.readline())- Current status of Azure Data Lake Store service support—whether this library remains the recommended client for new projects or if migration to newer SDKs is advised.
- Compatibility with modern Azure authentication methods (e.g., managed identities, service principal certificate-based auth) beyond the basic username/password flow shown.
What it is and what it does
azure-datalake-store is a Python client library for interacting with Microsoft Azure Data Lake Store as a filesystem. It abstracts ADLS operations into familiar file-system calls—listing directories, reading and writing files, checking file sizes—and supports file-like objects that work with standard Python tools like pandas. The library includes multithreaded upload and download capabilities with progress tracking, allowing efficient bulk transfers with configurable chunk sizes and thread counts.
The package depends on cffi and requests for low-level operations and HTTP communication. It exposes both a programmatic API (core.AzureDLFileSystem) and a command-line interface for interactive exploration of ADLS. Authentication is handled through lib.auth, which accepts tenant ID, username, and password. The library is classified as Alpha and has not received a release in 437 days, though the repository remains archived=false with recent commits.
Use it for
- Read CSV or Parquet files directly from Azure Data Lake into pandas DataFrames without downloading locally first.
- Batch download entire directory trees from ADLS to local storage using multithreaded transfers with progress callbacks.
- Upload large files to ADLS with automatic chunking and retry logic, tracking progress via callback functions.
- List and inspect file metadata (permissions, size, modification time) in ADLS directories programmatically.
- Integrate ADLS file operations into Python data pipelines that need to read from or write to cloud storage.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already committed to Azure Data Lake Store Gen1 and need Python filesystem access.
The low install friction, permissive MIT license, and lack of known vulnerabilities make it safe to use. However, the aging maintenance status (437 days since last release) and Alpha classification suggest checking whether Microsoft recommends this library for new projects or whether you should evaluate newer Azure SDK alternatives first.
Install
azure-datalake-store on PyPI
Before you install
Low install friction with only two runtime dependencies (cffi and requests). Maintenance is aging—last release was 437 days ago, though the repository remains active with a recent commit on 2025-06-03.
Requires Azure credentials (tenant ID, username, password) and an active Azure Data Lake Store account to authenticate and connect.
License in practice
MIT License (permissive) allows use in commercial and private projects with minimal restrictions, requiring only attribution and inclusion of the license notice.
Quickstart
pip install azure-datalake-store
from azure.datalake.store import core, lib
token = lib.auth(tenant_id, username, password)
adl = core.AzureDLFileSystem(token, store_name=store_name)
adl.ls('')
with adl.open('file.csv') as f:
print(f.readline())Verify before relying
- Current status of Azure Data Lake Store service support—whether this library remains the recommended client for new projects or if migration to newer SDKs is advised.
- Compatibility with modern Azure authentication methods (e.g., managed identities, service principal certificate-based auth) beyond the basic username/password flow shown.
Package facts
| License | MIT License permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagescffirequests |
| Maintenance | Aging 437 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 23,057,159 / month, #959 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaLicense :: OSI Approved :: MIT LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.9 |
Evidence: azure_datalake_store-1.0.1-py2.py3-none-any.whl
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