pip can be used to achieve various levels of repeatable environments. This page walks through increasingly stricter definitions of what “repeatable” means.
Pinning the package versions#
Pinning package versions of your dependencies in the requirements file protects you from bugs or incompatibilities in newly released versions:
SomePackage == 1.2.3 DependencyOfSomePackage == 4.5.6
Pinning refers to using the
== operator to require the package to be a
A requirements file, containing pinned package versions can be generated using pip freeze. This would pin not only the top-level packages, but also all of their transitive dependencies. Performing the installation using --no-deps would provide an extra dose of insurance against installing anything not explicitly listed.
This strategy is easy to implement and works across OSes and architectures. However, it trusts the locations you’re fetching the packages from (like PyPI) and the certificate authority chain. It also relies on those locations not allowing packages to change without a version increase. (PyPI does protect against this.)
Beyond pinning version numbers, you can add hashes against which to verify downloaded packages:
FooProject == 1.2 --hash=sha256:2cf24dba5fb0a30e26e83b2ac5b9e29e1b161e5c1fa7425e73043362938b9824
This protects against a compromise of PyPI or the HTTPS certificate chain. It also guards against a package changing without its version number changing (on indexes that allow this). This approach is a good fit for automated server deployments.
Hash-checking mode is a labour-saving alternative to running a private index server containing approved packages: it removes the need to upload packages, maintain ACLs, and keep an audit trail (which a VCS gives you on the requirements file for free). It can also substitute for a vendored library, providing easier upgrades and less VCS noise. It does not, of course, provide the availability benefits of a private index or a vendored library.
pip-tools is a package that builds upon pip, and provides a good workflow for managing and generating requirements files.
Using a wheelhouse (AKA Installation Bundles)#
pip wheel can be used to generate and package all of a project’s dependencies, with all the compilation performed, into a single directory that can be converted into a single archive. This archive then allows installation when index servers are unavailable and avoids time-consuming recompilation.
Creating the bundle, on a modern Unix system:
$ tempdir=$(mktemp -d /tmp/wheelhouse-XXXXX) $ python -m pip wheel -r requirements.txt --wheel-dir=$tempdir $ cwd=`pwd` $ (cd "$tempdir"; tar -cjvf "$cwd/bundled.tar.bz2" *)
Installing from the bundle, on a modern Unix system:
$ tempdir=$(mktemp -d /tmp/wheelhouse-XXXXX) $ (cd $tempdir; tar -xvf /path/to/bundled.tar.bz2) $ python -m pip install --force-reinstall --no-index --no-deps $tempdir/*
Note that such a wheelhouse contains compiled packages, which are typically OS and architecture-specific, so these archives are not necessarily portable across machines.
Hash-checking mode can also be used along with this method (since this uses a requirements file as well), to ensure that future archives are built with identical packages.
Beware of the
setup_requires keyword arg in
setup.py. The (rare)
packages that use it will cause those dependencies to be downloaded by
setuptools directly, skipping pip’s protections. If you need to use such a
package, see Controlling setup_requires.