A set of command line tools to help you keep your pip
-based packages fresh,
even when you've pinned them. You do pin them, right? (In building your Python application and its dependencies for production, you want to make sure that your builds are predictable and deterministic.)
Similar to pip
, pip-tools
must be installed in each of your project's
virtual environments:
$ source /path/to/venv/bin/activate
(venv) $ python -m pip install pip-tools
Note: all of the remaining example commands assume you've activated your project's virtual environment.
The pip-compile
command lets you compile a requirements.txt
file from
your dependencies, specified in either setup.py
or requirements.in
.
Run it with pip-compile
or python -m piptools compile
. If you use
multiple Python versions, you can also run py -X.Y -m piptools compile
on
Windows and pythonX.Y -m piptools compile
on other systems.
pip-compile
should be run from the same virtual environment as your
project so conditional dependencies that require a specific Python version,
or other environment markers, resolve relative to your project's
environment.
Note: If pip-compile
finds an existing requirements.txt
file that
fulfils the dependencies then no changes will be made, even if updates are
available. To compile from scratch, first delete the existing
requirements.txt
file, or see Updating requirements for alternative
approaches.
Suppose you have a Django project, and want to pin it for production.
If you have a setup.py
with install_requires=['django']
, then run
pip-compile
without any arguments:
$ pip-compile
#
# This file is autogenerated by pip-compile
# To update, run:
#
# pip-compile
#
asgiref==3.2.3
# via django
django==3.0.3
# via my_django_project (setup.py)
pytz==2019.3
# via django
sqlparse==0.3.0
# via django
pip-compile
will produce your requirements.txt
, with all the Django
dependencies (and all underlying dependencies) pinned.
If you don't use setup.py
(it's easy to write one), you can create a
requirements.in
file to declare the Django dependency:
# requirements.in
django
Now, run pip-compile requirements.in
:
$ pip-compile requirements.in
#
# This file is autogenerated by pip-compile
# To update, run:
#
# pip-compile requirements.in
#
asgiref==3.2.3
# via django
django==3.0.3
# via -r requirements.in
pytz==2019.3
# via django
sqlparse==0.3.0
# via django
And it will produce your requirements.txt
, with all the Django dependencies
(and all underlying dependencies) pinned.
pip-compile
generates a requirements.txt
file using the latest versions
that fulfil the dependencies of setup.py
or requirements.in
.
If pip-compile
finds an existing requirements.txt
file that fulfils the
dependencies then no changes will be made, even if updates are available.
To force pip-compile
to update all packages in an existing
requirements.txt
, run pip-compile --upgrade
.
To update a specific package to the latest or a specific version use the
--upgrade-package
or -P
flag:
# only update the django package
$ pip-compile --upgrade-package django
# update both the django and requests packages
$ pip-compile --upgrade-package django --upgrade-package requests
# update the django package to the latest, and requests to v2.0.0
$ pip-compile --upgrade-package django --upgrade-package requests==2.0.0
You can combine --upgrade
and --upgrade-package
in one command, to
provide constraints on the allowed upgrades. For example to upgrade all
packages whilst constraining requests to the latest version less than 3.0:
$ pip-compile --upgrade --upgrade-package 'requests<3.0'
If you would like to use Hash-Checking Mode available in pip
since
version 8.0, pip-compile
offers --generate-hashes
flag:
$ pip-compile --generate-hashes requirements.in
#
# This file is autogenerated by pip-compile
# To update, run:
#
# pip-compile --generate-hashes requirements.in
#
asgiref==3.2.3 \
--hash=sha256:7e06d934a7718bf3975acbf87780ba678957b87c7adc056f13b6215d610695a0 \
--hash=sha256:ea448f92fc35a0ef4b1508f53a04c4670255a3f33d22a81c8fc9c872036adbe5 \
# via django
django==3.0.3 \
--hash=sha256:2f1ba1db8648484dd5c238fb62504777b7ad090c81c5f1fd8d5eb5ec21b5f283 \
--hash=sha256:c91c91a7ad6ef67a874a4f76f58ba534f9208412692a840e1d125eb5c279cb0a \
# via -r requirements.in
pytz==2019.3 \
--hash=sha256:1c557d7d0e871de1f5ccd5833f60fb2550652da6be2693c1e02300743d21500d \
--hash=sha256:b02c06db6cf09c12dd25137e563b31700d3b80fcc4ad23abb7a315f2789819be \
# via django
sqlparse==0.3.0 \
--hash=sha256:40afe6b8d4b1117e7dff5504d7a8ce07d9a1b15aeeade8a2d10f130a834f8177 \
--hash=sha256:7c3dca29c022744e95b547e867cee89f4fce4373f3549ccd8797d8eb52cdb873 \
# via django
To output the pinned requirements in a filename other than
requirements.txt
, use --output-file
. This might be useful for compiling
multiple files, for example with different constraints on django to test a
library with both versions using tox:
$ pip-compile --upgrade-package 'django<1.0' --output-file requirements-django0x.txt
$ pip-compile --upgrade-package 'django<2.0' --output-file requirements-django1x.txt
Or to output to standard output, use --output-file=-
:
$ pip-compile --output-file=- > requirements.txt
$ pip-compile - --output-file=- < requirements.in > requirements.txt
Any valid pip
flags or arguments may be passed on with pip-compile
's
--pip-args
option, e.g.
$ pip-compile requirements.in --pip-args "--retries 10 --timeout 30"
You might be wrapping the pip-compile
command in another script. To avoid
confusing consumers of your custom script you can override the update command
generated at the top of requirements files by setting the
CUSTOM_COMPILE_COMMAND
environment variable.
$ CUSTOM_COMPILE_COMMAND="./pipcompilewrapper" pip-compile requirements.in
#
# This file is autogenerated by pip-compile
# To update, run:
#
# ./pipcompilewrapper
#
asgiref==3.2.3
# via django
django==3.0.3
# via -r requirements.in
pytz==2019.3
# via django
sqlparse==0.3.0
# via django
If you have different environments that you need to install different but compatible packages for, then you can create layered requirements files and use one layer to constrain the other.
For example, if you have a Django project where you want the newest 2.1
release in production and when developing you want to use the Django debug
toolbar, then you can create two *.in
files, one for each layer:
# requirements.in
django<2.2
At the top of the development requirements dev-requirements.in
you use -c
requirements.txt
to constrain the dev requirements to packages already
selected for production in requirements.txt
.
# dev-requirements.in
-c requirements.txt
django-debug-toolbar
First, compile requirements.txt
as usual:
$ pip-compile
#
# This file is autogenerated by pip-compile
# To update, run:
#
# pip-compile
#
django==2.1.15
# via -r requirements.in
pytz==2019.3
# via django
Now compile the dev requirements and the requirements.txt
file is used as
a constraint:
$ pip-compile dev-requirements.in
#
# This file is autogenerated by pip-compile
# To update, run:
#
# pip-compile dev-requirements.in
#
django-debug-toolbar==2.2
# via -r dev-requirements.in
django==2.1.15
# via
# -c requirements.txt
# django-debug-toolbar
pytz==2019.3
# via
# -c requirements.txt
# django
sqlparse==0.3.0
# via django-debug-toolbar
As you can see above, even though a 2.2
release of Django is available, the
dev requirements only include a 2.1
version of Django because they were
constrained. Now both compiled requirements files can be installed safely in
the dev environment.
To install requirements in production stage use:
$ pip-sync
You can install requirements in development stage by:
$ pip-sync requirements.txt dev-requirements.txt
You might use pip-compile
as a hook for the pre-commit.
See pre-commit docs for instructions.
Sample .pre-commit-config.yaml
:
repos:
- repo: https://github.com/jazzband/pip-tools
rev: 6.3.0
hooks:
- id: pip-compile
You might want to customize pip-compile
args by configuring args
and/or files
, for example:
repos:
- repo: https://github.com/jazzband/pip-tools
rev: 6.3.0
hooks:
- id: pip-compile
files: ^requirements/production\.(in|txt)$
args: [--index-url=https://example.com, requirements/production.in]
If you have multiple requirement files make sure you create a hook for each file.
repos:
- repo: https://github.com/jazzband/pip-tools
rev: 5.3.1
hooks:
- id: pip-compile
name: pip-compile setup.py
files: ^(setup\.py|requirements\.txt)$
- id: pip-compile
name: pip-compile requirements-dev.in
args: [requirements-dev.in]
files: ^requirements-dev\.(in|txt)$
- id: pip-compile
name: pip-compile requirements-lint.in
args: [requirements-lint.in]
files: ^requirements-lint\.(in|txt)$
- id: pip-compile
name: pip-compile requirements.txt
args: [requirements.txt]
files: ^requirements\.(in|txt)$
Now that you have a requirements.txt
, you can use pip-sync
to update
your virtual environment to reflect exactly what's in there. This will
install/upgrade/uninstall everything necessary to match the
requirements.txt
contents.
Run it with pip-sync
or python -m piptools sync
. If you use multiple
Python versions, you can also run py -X.Y -m piptools sync
on Windows and
pythonX.Y -m piptools sync
on other systems.
pip-sync
must be installed into and run from the same virtual
environment as your project to identify which packages to install
or upgrade.
Be careful: pip-sync
is meant to be used only with a
requirements.txt
generated by pip-compile
.
$ pip-sync
Uninstalling flake8-2.4.1:
Successfully uninstalled flake8-2.4.1
Collecting click==4.1
Downloading click-4.1-py2.py3-none-any.whl (62kB)
100% |................................| 65kB 1.8MB/s
Found existing installation: click 4.0
Uninstalling click-4.0:
Successfully uninstalled click-4.0
Successfully installed click-4.1
To sync multiple *.txt
dependency lists, just pass them in via command
line arguments, e.g.
$ pip-sync dev-requirements.txt requirements.txt
Passing in empty arguments would cause it to default to requirements.txt
.
Any valid pip install
flags or arguments may be passed with pip-sync
's
--pip-args
option, e.g.
$ pip-sync requirements.txt --pip-args "--no-cache-dir --no-deps"
Note: pip-sync
will not upgrade or uninstall packaging tools like
setuptools
, pip
, or pip-tools
itself. Use python -m pip install --upgrade
to upgrade those packages.
Generally, yes. If you want a reproducible environment installation available from your source control,
then yes, you should commit both requirements.in
and requirements.txt
to source control.
Note that if you are deploying on multiple Python environments (read the section below),
then you must commit a separate output file for each Python environment.
We suggest to use the {env}-requirements.txt
format
(ex: win32-py3.7-requirements.txt
, macos-py3.10-requirements.txt
, etc.).
The dependencies of a package can change depending on the Python environment in which it is installed. Here, we define a Python environment as the combination of Operating System, Python version (3.7, 3.8, etc.), and Python implementation (CPython, PyPy, etc.). For an exact definition, refer to the possible combinations of PEP 508 environment markers.
As the resulting requirements.txt
can differ for each environment, users must
execute pip-compile
on each Python environment separately to generate a
requirements.txt
valid for each said environment. The same requirements.in
can
be used as the source file for all environments, using PEP 508 environment markers as
needed, the same way it would be done for regular pip
cross-environment usage.
If the generated requirements.txt
remains exactly the same for all Python
environments, then it can be used across Python environments safely. But users
should be careful as any package update can introduce environment-dependant
dependencies, making any newly generated requirements.txt
environment-dependant too.
As a general rule, it's advised that users should still always execute pip-compile
on each targeted Python environment to avoid issues.
- pipdeptree to print the dependency tree of the installed packages.
requirements.in
/requirements.txt
syntax highlighting:- requirements.txt.vim for Vim.
- Python extension for VS Code for VS Code.
- pip-requirements.el for Emacs.
This section lists pip-tools
features that are currently deprecated.
- In future versions, the
--allow-unsafe
behavior will be enabled by default. Use--no-allow-unsafe
to keep the old behavior. It is recommended to pass the--allow-unsafe
now to adapt to the upcoming change.
The table below summarizes the latest pip-tools
versions with the required
pip
and Python versions. Generally, pip-tools
supports the same Python
versions as the required pip
versions.
pip-tools | pip | Python |
---|---|---|
4.5.* | 8.1.3 - 20.0.2 | 2.7, 3.5 - 3.8 |
5.0.0 - 5.3.0 | 20.0 - 20.1.1 | 2.7, 3.5 - 3.8 |
5.4.0 | 20.1 - 20.3.* | 2.7, 3.5 - 3.8 |
5.5.0 | 20.1 - 20.3.* | 2.7, 3.5 - 3.9 |
6.0.0 - 6.3.1 | 20.3 - 21.2.* | 3.6 - 3.9 |
6.4.0 | 21.2 - 21.3.* | 3.6 - 3.10 |
6.5.0+ | 21.2+ | 3.7 - 3.10 |