pip-tools
| docker-django | pip-tools | |
|---|---|---|
| 4 | 58 | |
| 6 | 7,472 | |
| - | 0.7% | |
| 5.4 | 8.9 | |
| 14 days ago | 16 days ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
docker-django
- Can you (developers who've worked professionally with Djano) share a Django project Dockerfile and docker-compose files with what you consider best practices?
- I am deploying my project and it is all in containers . I am currently using a Postgres docker image for my dev instance . How do I just release the updated code instead of wiping my db each time ?
-
Do you recommend using Pipenv or the default VirtualEnv for Django + Docker setup?
You can find an example here : https://github.com/Atem18/docker-django/blob/main/docker-images/Dockerfile
-
How do you develop with docker and django? Do I have to constantly rebuild docker?
Here you go : https://github.com/Atem18/docker-django
pip-tools
-
Pyenv – lets you easily switch between multiple versions of Python
> Why is the "requirements.txt" file a stupid flat listing of all transitive dependencies with pinned versions? It makes it harder to change library versions even if there are no true conflicts.
My friend, here is what you seek: https://github.com/jazzband/pip-tools
requirements.txt is flat because it's really the output of `pip freeze`. It's supposed to completely and exactly rebuild the environment. Unfortunately it's far too flexible and people abuse it by putting in only direct dependencies etc.
If you're writing packages, you don't need a requirements.txt at all, by the way. Package dependencies (only direct dependencies) live in pyproject.toml with the rest of the package config. requirements.txt (and pip tools) are only for when you want to freeze the whole environment, like for a server deployment.
-
lockfiles for hatch projects
For all my projects I found myself regenerating manual lock files using complex shell commands with pip-compile to get a reproducible environments across devices using a custom pre-install-command. I finally decided that instead of hacking together the same solution on all my projects I would build a plugin that handles this complexity for me.
-
Setting up Django in a Better Way in 5 Minutes and Understanding How It Works
Instead of venv, we are using pip-tools in this starter kit. pip-tools take things further in dependency management. Check out what pip-tools does in their official GitHub repo. In short, it helps your project find the best match for the dependent packages. For example, you might need two packages A and B in your project that requires same package C under the hood. But A requires any version of C from 1.0.1 to 1.0.10 and B requires any version of C from 1.0.7 to 1.0.15. Pip tools will automatically compile the version of 'C' that suits for both of your packages.
-
just-pip-tools: An example of managing python dependencies as layered lock files with just and pip-tools
I've created a small project called just-pip-tools that combines pip-tools and just to manage Python dependencies in a layered approach. This isn't a magic bullet; it's a set of files you can adapt to your needs.
-
Maintaining virtual environments
For small projects I recommend pip-tools. Just write packet list in requirements.in and pip-compile compile a requirements.txt with comments.
-
how to upgrade psycopg2 to psycopg3 as per django latest documentation
Take a look at pip-tools, great package. https://github.com/jazzband/pip-tools
- Single-file scripts that download their dependencies
-
What are people using to organize virtual environments these days?
pip-tools
-
How to know what a package depend on when pip is installing it?
I recommend generating a lockfile to document this information, as you might do with pip-tools.
-
A not so unfortunate sharp edge in Pipenv
Check out pip-tools [1] which does exactly that, albeit in a slightly more polished way.
[1]: https://github.com/jazzband/pip-tools
What are some alternatives?
docker-django-example - A production ready example Django app that's using Docker and Docker Compose.
Poetry - Python packaging and dependency management made easy
PDM - A modern Python package and dependency manager supporting the latest PEP standards
Pipenv - Python Development Workflow for Humans.
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
pip - The Python package installer
miniforge - A conda-forge distribution.
hatch - Modern, extensible Python project management
wheel - Adoption analysis of Python Wheels: https://pythonwheels.com/
dephell - :package: :fire: Python project management. Manage packages: convert between formats, lock, install, resolve, isolate, test, build graph, show outdated, audit. Manage venvs, build package, bump version.
Curdling - Concurrent package manager for Python