Installing (1.x)


Installing Fabric 2.0 or above? Looking for non-PyPI downloads or source code checkout instructions? See Installing.

This document includes legacy notes on installing Fabric 1.x. Users are strongly encouraged to upgrade to 2.x when possible.

Basic installation

Fabric is best installed via pip; to ensure you get Fabric 1 instead of the new but incompatible Fabric 2, specify <2.0:

$ pip install 'fabric<2.0'

All advanced pip use cases work too, such as installing the latest copy of the v1 development branch:

$ pip install -e 'git+'

Or cloning the Git repository and running:

$ git checkout v1
$ pip install -e .

within it.

Your operating system may also have a Fabric package available (though these are typically older and harder to support), typically called fabric or python-fabric. E.g.:

$ sudo apt-get install fabric


Make sure to confirm which major version is currently packaged!


In order for Fabric’s installation to succeed, you will need four primary pieces of software:

  • the Python programming language;

  • the setuptools packaging/installation library;

  • the Python Paramiko SSH library;

  • and Paramiko’s dependency, Cryptography.

and, if using parallel execution mode,

Please read on for important details on each dependency – there are a few gotchas.


Fabric requires Python version 2.5+.


Setuptools comes with most Python installations by default; if yours doesn’t, you’ll need to grab it. In such situations it’s typically packaged as python-setuptools, py26-setuptools or similar.


An optional dependency, the multiprocessing library is included in Python’s standard library in version 2.6 and higher. If you’re using Python 2.5 and want to make use of Fabric’s parallel execution features you’ll need to install it manually; the recommended route, as usual, is via pip. Please see the multiprocessing PyPI page for details.


Early versions of Python 2.6 (in our testing, 2.6.0 through 2.6.2) ship with a buggy multiprocessing module that appears to cause Fabric to hang at the end of sessions involving large numbers of concurrent hosts. If you encounter this problem, either use env.pool_size / -z to limit the amount of concurrency, or upgrade to Python >=2.6.3.

Python 2.5 is unaffected, as it requires the PyPI version of multiprocessing, which is newer than that shipped with Python <2.6.3.