---
id: delta-sharing
version: "1.4.2"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# delta-sharing — Python Connector for Delta Sharing

License: permissive · Maintenance: active · Downloads: 1.5M/mo

## 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 above — verify before relying.

Delta Sharing is a Python client library for the Delta Sharing protocol, enabling you to load shared Delta Lake and Parquet tables as pandas or Spark DataFrames from remote data providers.

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

pip install delta-sharing
uv add delta-sharing
poetry add delta-sharing

## Installing delta-sharing

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.

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)

Rust toolchain may be required on some systems to build delta-kernel-rust-sharing-wrapper from source; Python >= 3.10 required.

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_current
- Install friction: low
- Maintenance: active
- Downloads: 1.5M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

delta sharing python client, read shared delta lake tables, cross-platform data sharing, secure dataset exchange, delta lake connector, parquet table sharing, pandas dataframe from delta sharing, data-sharing, delta-lake, cross-platform

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