delta-sharing
Python Connector for Delta Sharing
Decision gist · record as of 2026-08-14
Yes. Delta Sharing is actively maintained, production-stable, has no known vulnerabilities, and low install friction. It solves a real problem—secure cross-platform data sharing without data movement—and is widely used (top 5000 PyPI packages). Install it if you need to consume shared Delta Lake or Parquet tables via the Delta Sharing protocol; be aware that some systems may require Rust to build the native wrapper.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Rust toolchain may be required on some systems to build delta-kernel-rust-sharing-wrapper from source; Python >= 3.10 required.
- Low install friction with a pure-wheel distribution.
- The package depends on delta-kernel-rust-sharing-wrapper, which may require building from source in some environments (requiring Rust), but this is documented.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and redistribution with minimal restrictions—suitable for most organizational data-sharing scenarios.
last release 2026-08-10 (4 days) · last repo commit 2026-08-12 · 956 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,460,664 downloads/mo, #3,880 on PyPI
Alternatives
Verify before relying
pip install delta-sharing
from delta_sharing import DeltaSharingClient
client = DeltaSharingClient(share_credentials_path)- Specific performance characteristics or throughput limits for large dataset transfers.
- Authentication and credential management details beyond what the docs reference.
- Whether all Delta Lake and Parquet table features are fully supported by the client.
What it is and what it does
Delta Sharing is a Python client for an open protocol that lets organizations securely share access to Delta Lake and Parquet tables across different computing platforms in real time. Rather than copying or moving data, it provides direct read access to remote tables, which you can load into pandas DataFrames or Spark DataFrames (when running in PySpark). The library wraps the delta-kernel-rust-sharing-wrapper to handle the protocol details, and depends on pandas, pyarrow, fsspec, requests, aiohttp, yarl, and jwcrypto for HTTP communication, filesystem abstraction, and cryptographic credential handling.
You install it via pip, though some environments may need to build the Rust wrapper from source. It requires Python 3.10 or later. The library is actively maintained, recently released, and positioned as production-stable. It has no known security vulnerabilities and is widely downloaded, making it a mature choice for organizations implementing Delta Sharing data-exchange workflows.
Use it for
- Load a shared Delta Lake table from a remote provider into a local pandas DataFrame for analysis.
- Access Parquet tables published via Delta Sharing without copying data to your infrastructure.
- Build a PySpark job that reads shared tables directly via the Delta Sharing protocol.
- Integrate cross-organization data sharing into a data pipeline without ETL overhead.
- Query shared datasets in real time from multiple organizations in a federated analytics setup.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Delta Sharing is actively maintained, production-stable, has no known vulnerabilities, and low install friction. It solves a real problem—secure cross-platform data sharing without data movement—and is widely used (top 5000 PyPI packages). Install it if you need to consume shared Delta Lake or Parquet tables via the Delta Sharing protocol; be aware that some systems may require Rust to build the native wrapper.
Install
delta-sharing on PyPI
Before you install
Low install friction with a pure-wheel distribution. The package depends on delta-kernel-rust-sharing-wrapper, which may require building from source in some environments (requiring Rust), but this is documented. Actively maintained with a recent release and steady repository activity.
Rust toolchain may be required on some systems to build delta-kernel-rust-sharing-wrapper from source; Python >= 3.10 required.
License in practice
Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and redistribution with minimal restrictions—suitable for most organizational data-sharing scenarios.
Quickstart
pip install delta-sharing
from delta_sharing import DeltaSharingClient
client = DeltaSharingClient(share_credentials_path)Verify before relying
- Specific performance characteristics or throughput limits for large dataset transfers.
- Authentication and credential management details beyond what the docs reference.
- Whether all Delta Lake and Parquet table features are fully supported by the client.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 8 packagesdelta-kernel-rust-sharing-wrapperpandaspyarrowfsspecrequestsaiohttpyarljwcrypto |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,460,664 / month, #3,880 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 :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Topic :: Software Development :: Libraries :: Python Modules |
Evidence: delta_sharing-1.4.2-py3-none-any.whl
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See also delta-spark · mltable · delta-kernel-rust-sharing-wrapper · deltalake · hops-deltalake · deltalite · pyspark-pandas · pyspark-client · pyarrowfs-adlgen2 · shared