Tsukasa-credit-card-gag-scam
zpy
Tsukasa-credit-card-gag-scam | zpy | |
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17 | 35 | |
11 | 70 | |
- | - | |
8.5 | 9.1 | |
6 days ago | 2 days ago | |
Python | Shell | |
- | Do What The F*ck You Want To Public 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.
Tsukasa-credit-card-gag-scam
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How can I export my project with pythonautogui?
One workaround that I can think of would be to build everything using GitHub Actions, as then your own system would not matter at all. I have a great example project for that, all you really need to do is create a YAML file in a directory called .github/WORKFLOWS (the filename itself doesn't really matter), you can use this as a base. Just gotta swap out Nuitka for PyInstaller (if you want to), and change how the dependencies are installed. This makes it so that whenever you push a Git tag with a version number (say, v1.0.0), GitHub will then run this script, build executables (on any operating systems you want, no less), then create a release with them available for download. Mine also adds a changelog, but you can just remove that part.
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Created an app at work, how to distribute?
If your company uses GitHub or GitLab, be it internal or the online version, you could create a release on the project page with your built binaries attached for download. One of my projects should work fine as an example. The releases page is linked on the sidebar. The neat thing with this is that you can automate the whole build and release process; I get a new release whenever I push a Git tag with a version number.
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Module not found Error in Python.
Ideally you'd make your project "installable", and use absolute imports for everything. This way, when your project is installed as a package, assuming there are no circular dependencies any part of it can import from any other part. Mainly this makes the job of your unit tests a lot easier. Either of these two examples will probably showcase that just fine.
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Python imports on Linux $PATH
However, if that's not the case for your project, such as if you have an extra src directory separating the repository root and the package(s), you'll need to be explicit. In another project I did exactly that:
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What libraries should I learn?
I used it in this project as a test, before I made the decision to transition all my projects from Pylint and Flake8 to Ruff: https://github.com/Diapolo10/Tsukasa-credit-card-gag-scam
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How to get directories to properly work in Python?
One of my own projects handles this with a function, which then gets used thorough the program:
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Blackjack project review
Instead of keeping all the code at the repository root, maybe consider a more traditional project structure. As far as examples go, I've got this for an executable, and I think this works for a more complex project.
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How do I distribute a Python package with a C++ extension module.
None of my current projects build platform-dependent releases, but I think this example is close enough. It would just take some tweaking.
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Tips for sharing personal projects.
I did something like that myself. I found Bleeplo's video about an attempt at recreating a certain meme image as a real tkinter program, and I enjoyed the idea so much I ended up making a fork of the project, improved upon the original, and even made a pull request to the original project with some of my cleanup. Forked projects always link back to the original, and all forks are visible from the original's settings.
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having trouble with publishing a package
pyproject.toml already lists the dependencies, requirements.txt is not needed nor used in the newer standard. In fact, it can list your development dependencies as well, like here for example.
zpy
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This Week In Python
zpy – Zsh helpers for Python venvs, with uv or pip-tools
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Canonical blocked installing, or uninstalling pip packages on Ubuntu 23.04, what it can be done to solve these issues?
If your interactive shell is zsh, you could give my project zpy a try, particularly the function pipz that it provides, which is a lightweight pipx clone with great completions and good speed.
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As if there weren't enough packaging tools already: mitsuhiko/rye: an experimental alternative to poetry/pip/pipenv/venv/virtualenv/pdm/hatch/…
I can immediately see some things rye is doing differently, like keeping the venvs themselves free of pip and pip-tools. I wonder in your explorations if you've tried rtx for managing python installations, or my own zpy wrapper of pip-tools+venv (which can also replace pipx).
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How do I build up my package's extra dependencies from groups of dependencies in a pyproject.toml?
My patterns in this regard aren't exactly mainstream, as I use flit+pip-tools+zpy (the latter being my own Zsh interface for Python dependency and environment operations), but FWIW here's how I go about nested requirements.
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What is your workflow for managing virtual environments for personal projects?
For managing venvs and dependencies and apps, I use my own frontend to pip-tools + venv, zpy. And for running tasks which require an activated venv, I use nox.
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One Does Not Simply 'pip install'
If anyone's interested in a pipx clone with excellent tab completion, I would appreciate any feedback on pipz, a function of my zsh plugin for python environment and dependency management: zpy
https://github.com/andydecleyre/zpy
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pipenv or virtualenv ?
For concise and practical interactive usage of those tools, with excellent tab completion, I made the Zsh frontend zpy.
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How to know what a package depend on when pip is installing it?
I also use my own Zsh wrapper functions with it, so for example: https://i.imgur.com/YX8bWy8.png
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I moved away from Poetry for Python
I'm a big fan of (and small contributor to) pip-tools, but both poetry and pipenv offer management of more stuff, which understandably appeals to folks seeking a simple comprehensible workflow.
Pip-tools is also a bit lower level, offering flexibility and compatibility which I relish, but also requiring more attention from the user to set things up as they wish.
If you or anyone else enjoying pip-tools is a Zsh user and interested in trying out my higher level functions to ease interactive use of pip-tools, venvs, and also isolated app installs (like pipx), I would love some feedback on zpy: https://github.com/AndydeCleyre/zpy
I'm very happy to answer any questions about it right here or as GitHub issues.
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Any recent updates in dependency management?
This is FAR from some big mainstream thing, but I use (and am happy to answer any questions about) my own Zsh frontend to venv+pip-tools+pip, zpy.
What are some alternatives?
python-ms - A Python equivalent to the JavaScript ms package
hatch - Modern, extensible Python project management
buutti_maze_solver - A solver for two mazes
agkozak-zsh-prompt - A fast, asynchronous Zsh prompt with color ASCII indicators of Git, exit, SSH, virtual environment, and vi mode status. Framework-agnostic and customizable.
Mouse-controller - eee
wheezy.template - A lightweight template library.
Quick-Kopy
taskipy - the complementary task runner for python
Mouse-controller - eee
zplug - :hibiscus: A next-generation plugin manager for zsh
escapyde - Yet another ANSI escape sequence library for Python - now modernised!
tox-pin-deps - Run tox environments with strictly pinned dependencies (and no project or code changes).