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title | tags | date | aliases | canonicalURL | description | summary | ||||
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pip-tools for Python dependencies management |
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2023-03-02T13:07:26.381756+00:00 |
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/pip-tools-for-python-dependencies-management | Here's how and why I use pip-tools for my side-projects. | Here's how and why I use pip-tools for my side-projects. |
📖 Story time
At the end of 2020, I wrote an article entitled [Poetry for Python dependencies management]({{< ref "poetry-python-dependencies-management" >}}). I described ITSF's requirements for a dependencies management system and how we found Poetry useful. After updating our internal projects, I tackled my side projects and moved them to Poetry.
The requirements from late 2020 were the following:
- It must manage transitive dependencies1 for us. Developers should only have to specify the direct dependencies of their projects. Transitive dependencies and the exact versions to install must be defined by the tool.
- Any conflicts in dependencies must prevent their installation and break the build.
- Adding a dependency after the initial setup must check for compatibility with existing direct and transitive dependencies.
- It must fit into a Docker-based workflow while still being easy to use in a development environment.
- It must permit reproducible builds. We must be able to checkout the source code at a specific version and build the app as it was released this day with the exact same versions of all the packages.
- It should have features for building and publishing packages on PyPI (or a private package registry).
- Bonus point if it can export to the requirements.txt format for compatibility.
At the time, we considered pipenv
, poetry
and pip-tools
, and chose Poetry because it was the only one checking all the boxes.
Two years later, these requirements haven't changed, but I now find Poetry to be too complex and moved all my active side projects to pip-tools
.
pip-tools
regroups two utilities. The first generates a requirements.txt
from a source, and the other takes the generated file and syncs the virtual environment to the described state. It fits well in the UNIX philosophy of one tool doing one thing and doing it well.
It doesn't try to manage your virtual environments, it doesn't try to build and publish packages... It just manages your dependencies.
👨🏻🔧 My new workflow
I'm using two source requirements files:
requirements.in
for the production dependenciesrequirements-dev.in
for the development dependencies
Then, I use pip-compile
to generate three files:
requirements.txt
for the production dependencies, generated fromrequirements.in
constraints.txt
for the constraints the production dependencies must impose on development dependencies, generated fromrequirements.in
2requirements-dev.txt
for the development dependencies, generated fromrequirements-dev.txt
andconstraints.txt
.
And finally pip-sync
updates my virtualenv, adding missing packages and removing old ones.
📑 Samples
Here's what the source files look like for this blog:
# requirements.in
django[argon2]>=4.1,<5.0
django-cleanup>=6.0
django-environ>=0.9.0
# ...
# requirements-dev.in
-c constraints.txt
pre-commit>=2.7
pytest>=7.0
# ...
🪄 Invoke
The commands used to compile the three files are:
pip-compile -q --allow-unsafe --resolver=backtracking --generate-hashes requirements.in
pip-compile -q --allow-unsafe --resolver=backtracking --strip-extras -o constraints.txt requirements.in
pip-compile -q --allow-unsafe --resolver=backtracking --generate-hashes requirements-dev.in
This is a lot to remember and I have a terrible memory, so I'm using invoke to call the commands for me.
# tasks.py
from pathlib import Path
from invoke import Context, task
BASE_DIR = Path(__file__).parent.resolve(strict=True)
@task
def update_dependencies(ctx: Context, *, sync: bool = True) -> None:
return compile_dependencies(ctx, update=True, sync=sync)
@task
def compile_dependencies(
ctx: Context, *, update: bool = False, sync: bool = False
) -> None:
common_args = "-q --allow-unsafe --resolver=backtracking"
if update:
common_args += " --upgrade"
with ctx.cd(BASE_DIR):
ctx.run(
f"pip-compile {common_args} --generate-hashes requirements.in",
pty=True,
echo=True,
)
ctx.run(
f"pip-compile {common_args} --strip-extras -o constraints.txt requirements.in",
pty=True,
echo=True,
)
ctx.run(
f"pip-compile {common_args} --generate-hashes requirements-dev.in",
pty=True,
echo=True,
)
if sync:
sync_dependencies(ctx)
@task
def sync_dependencies(ctx: Context) -> None:
with ctx.cd(BASE_DIR):
ctx.run("pip-sync requirements.txt requirements-dev.txt", pty=True, echo=True)
Invoke is a sort of Makefile, but written in Python.
$ invoke --list # shorter: inv -l
Available tasks:
compile-dependencies
sync-dependencies
update-dependencies
$ inv compile-dependencies
# Runs the commands...
📦 Add/update dependencies
Now when I need to add a dependency, I first edit the relevant *.in
file, then I run inv compile-dependencies
to compile all the files without updating the existing dependencies and finally inv sync-dependencies
to really install them locally (or shorter with inv compile-dependencies -s
).
If I want to update my dependencies, a simple inv update-dependencies
is all I need.
After that, I commit all the *.in
and *.txt
files so that my future self and other people can reproduce my build.
In other words:
echo "new_package>=1.2" >> requirements.in
inv compile-dependencies -s
git add *.in *.txt
git commit -m "Add new_package"
👀 Missing compilation?
In order to avoid forgetting to compile my dependencies, I added a few pre-commit hooks to my projects:
repos:
- repo: https://github.com/jazzband/pip-tools
rev: 6.12.2
hooks:
- id: pip-compile
name: pip-compile requirements.txt
args: [-q, --allow-unsafe, --resolver=backtracking, --generate-hashes, requirements.in]
files: ^requirements\.(in|txt)$
- id: pip-compile
name: pip-compile constraints.txt
args: [-q, --allow-unsafe, --resolver=backtracking, --strip-extras, --output-file=constraints.txt, requirements.in]
files: ^requirements\.in|constraints\.txt$
- id: pip-compile
name: pip-compile requirements-dev.txt
args: [-q, --allow-unsafe, --resolver=backtracking, --generate-hashes, requirements-dev.in]
files: ^requirements-dev\.(in|txt)$
These will run the pip-compile
commands whenever the source or compiled files have changed to ensure the compiled files are up to date with the sources before committing. It won't update the dependencies though, as it's not desirable here.
🔀 Transition
Moving from Poetry to pip-tools was really easy since all the hard work was already done. I just took the dependencies listed in pyproject.toml
, copied them over to the *.in
files and compiled the *.txt
👨🏻💻 Developer experience
The beauty with all this is that I now have regular requirements.txt
files that I can pass to pip install -r
. It means potential collaborators don't need to worry about pip-tools
. Or that I don't need yet another binary in my Docker images.
I can just rely on
pip
, and it's relaxing.
-
A transitive dependency is the dependency of a dependency. For example, my app relies on the
requests
package for HTTP requests. This package relies on several others to do its job, likecertifi
,chardet
, etc. These are transitive dependencies because my app doesn't rely directly on them. ↩︎ -
I first used
requirements.txt
as the constraint file but I had some issues with extras. I now generate a separateconstraints.txt
file with--strip-extras
to avoid this. ↩︎