warehouse
ESLint
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warehouse | ESLint | |
---|---|---|
274 | 379 | |
3,468 | 24,231 | |
0.7% | 1.0% | |
9.7 | 9.7 | |
about 9 hours ago | 7 days ago | |
Python | JavaScript | |
Apache License 2.0 | MIT 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.
warehouse
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Smooth Packaging: Flowing from Source to PyPi with GitLab Pipelines
python3 -m pip install \ --trusted-host test.pypi.org --trusted-host test-files.pythonhosted.org \ --index-url https://test.pypi.org/simple/ \ --extra-index-url https://pypi.org/simple/ \ piper_whistle==$(python3 -m src.piper_whistle.version)
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Pickling Python in the Cloud via WebAssembly
In my experience so far, I can use a vast amount of the Python Standard Library to build Wasm-powered serverless applications. The caveat I currently understand is that Python’s implementation of TCP and UDP sockets, as well as Python libraries that use threads, processes, and signal handling behind the scenes, will not compile to Wasm. It is worth noting that a similar caveat exists with libraries that I find on The Python Package Index (PyPI) site. While these caveats might limit what can be compiled to Wasm, there are still a ton of extremely powerful libraries to leverage.
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Introducing Flama for Robust Machine Learning APIs
We believe that poetry is currently the best tool for this purpose, besides of being the most popular one at the moment. This is why we will use poetry to manage the dependencies of our project throughout this series of posts. Poetry allows you to declare the libraries your project depends on, and it will manage (install/update) them for you. Poetry also allows you to package your project into a distributable format and publish it to a repository, such as PyPI. We strongly recommend you to learn more about this tool by reading the official documentation.
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PyPI Packaging
From there, I needed to learn a bit about PyPi or Python Package Index, which is the home for all the wonderful packages that you know if you have ever run the handy pip install command. PyPi has a pretty quick and easy onboarding, which requires a secured account be created and, for the purposes of submitting packages from CLI, an API token be generated. This can be done in your PyPi profile. Once logg just navigate to https://pypi.org/manage/account/ and scroll down to the API tokens section. Click “Add Token” and follow the few steps to generate an API token which is your access point to uploading packages. With all this in place, I was able to use twine to handle the package upload. First I needed to install twine, again as simple as pip install twine. In order for twine to access my API token during the package upload process, it needed to read it from .pypirc file that contains the token info. For some that file may exist already, for me I was required to create it. Working in windows I simply used a text editor to create it in my home user directory ($HOME/.pypirc). The file contents had a TOML like format looked like this:
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Releasing my Python Project
I have published the package to Python Package Index, commonly called PyPi, and in this post, I'll be sharing the steps I had to follow in the process.
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Publishing my open source project to PyPI!
Register at PyPI.org
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Show HN: I mirrored all the code from PyPI to GitHub
According to the stats on the original link, there are over 25,000 identified secret ids/keys/tokens in the data. And it looks like that's just identifiable secrets, e.g. "Google API Keys" that I'm guessing are identifiable because they have a specific pattern, and may be missing other secrets that use less recognizable patterns.
I mean, sure, compared to the 478,876 Projects claimed on https://pypi.org/, that's a pretty small minority. On the other hand, I'd guess a many Python packages don't use these particular services, or even need to connect to a remote service at all, so the area for this class of mistake should be even smaller.
And mistakes do happen, but that's a pretty big thing to miss if you are knowingly publishing your code with the expectation other people will be reading it.
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Pezzo v0.5 - Dashboards, Caching, Python Client, and More!
PyPi package
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Modifying keywords in python package
Does pypi.org display the Union of all keywords, the keywords of the most recent release, the keywords of the first release or some other weird combination like the intersection?
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PyPI Requires 2FA for New User Registrations
https://peps.python.org/pep-0458/
Here's the in-progress roadmap: https://github.com/pypi/warehouse/issues/10672
If there's particular issues you believe you could pick off to help achieve the goal, much appreciated!
ESLint
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To Review or Not to Review: The Debate on Mandatory Code Reviews
Automating code checks with static code analysis allows us to enforce code styling effectively. By integrating tools into our workflow, we can identify errors at an early stage, while coding instead of blocking us at the end. For instance, flake8 checks Python code for style and errors, eslint performs similar checks for JavaScript, and prettier automatically formats code to maintain consistency.
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Biome.js : Prettier+ESLint killer ?
If you're a developer, you're surely familiar with Prettier and ESLint. With over 8 years of existence, they have established themselves as references in the JavaScript ecosystem.
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Most basic code formatting
eslint is used to avoid code errors
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How to use Lefthooks in your node project?
No lint errors: The committed code does not contain any lint errors (eslint).
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Git Project Configuration With Husky and ESLint
Let’s walk through the steps for a one-time setup to configure husky pre-commit and pre-push hooks, ESLint with code styles conventions, prettier code formatter, and lint-staged. Husky automatically runs a script on each commit or push. This is useful for linting files to enforce code styles that keeps the entire code base following conventions.
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What is an Abstract Syntax Tree in Programming?
GitHub | Website
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Shared Tailwind Setup For Micro Frontend Application with Nx Workspace
ESLint: A pluggable and configurable linter tool for identifying and reporting on patterns in JavaScript.
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6 Tools To Help Keep Your Dependencies And Code More Secure
ESLint
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Six Factors That Raise The Risk Of Bugs In A Codebase
1. Lack of Static Code Analysis Static code analysis tools like TypeScript and ESLint play a crucial role in identifying and preventing bugs. TypeScript provides static typing, enhancing the robustness of the code. ESLint detects issues and enforces coding standards. The absence of these tools can significantly elevate the likelihood of bugs due to the lack of early detection and guidance provided during development.
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Linting
The industry standard for JavaScript is ESLint. VS Code has an ESLint extension. Here is a guide.
What are some alternatives?
devpi
XO - ❤️ JavaScript/TypeScript linter (ESLint wrapper) with great defaults
bandersnatch
Standard - 🌟 JavaScript Style Guide, with linter & automatic code fixer
localshop - local pypi server (custom packages and auto-mirroring of pypi)
prettier - Prettier is an opinionated code formatter.
Poe the Poet - A task runner that works well with poetry.
JSHint - JSHint is a tool that helps to detect errors and potential problems in your JavaScript code
scribd-downloader
JSLint - JSLint, The JavaScript Code Quality and Coverage Tool
Python Packages Project Generator - 🚀 Your next Python package needs a bleeding-edge project structure.
Babel (Formerly 6to5) - 🐠 Babel is a compiler for writing next generation JavaScript.