Pyxet Documentation

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Pyxet Documentation#

pyxet is a Python library that provides a pythonic interface for XetHub. Xethub is simple git-based system capable of storing TBs of ML data and models in a single repository, with block-level data deduplication that enables hundreds of versions of similar data to be stored without requiring much storage.

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Features#

pyxet provides 3 components:

1. A fsspec interface that allows compatible libraries such as Pandas, Polars and Duckdb to directly access any version of any file in a Xet repository. See below for some examples.

2. A command line interface inspired by AWSCLI that allows files to be uploaded to and downloaded from Xet repository conveniently and efficiently.

3. A file system mount mechanism that allows any version of any Xet repository to be mounted. This works on Mac, Linux, and Windows 11 Pro.

Installation#

The easiest to authenticate is to signup on XetHub and obtain a username and access token. You should write this down.

Set up your virtualenv with:

`sh $ python -m venv .venv $ . .venv/bin/activate `

Then, install pyxet with:

`sh $ pip install pyxet `

Authentication#

There are three ways to authenticate with XetHub:

Command Line#

xet login -e <email> -u <username> -p <personal_access_token>

Xet login will write to authentication information to ~/.xetconfig

Environment Variable#

Environment variables may be sometimes more convenient:

export XET_USER_EMAIL = <email>
export XET_USER_NAME = <username>
export XET_USER_TOKEN = <personal_access_token>

In Python#

Finally if in a notebook environment, or a non-persistent environment, we also provide a method to authenticate directly from Python. Note that this must be the first thing you run before any other operation:

import pyxet
pyxet.login(<username>, <personal_access_token>, <email>)

Quickstart#

Read a CSV file:

import pyxet            # make xet:// protocol available
import pandas as pd     # assumes pip install pandas has been run

df = pd.read_csv('xet://xethub.com:XetHub/titanic/main/titanic.csv')

Checkout the rest of the documentation for detailed usage examples!

Encountering Issues?#

Please file a bug here, or report on our Slack! We are constant making improvements, especially with usability and performance.

Introduction

API Reference

Use Cases

API Documentation

Contents