Vue.js VS Django

But it does not deal with all the non-JSON objects, e.g. Map or other class instances that are not even JSON-serializable by default.

Best to use TypeScript, and ideally, it should only be needed to do such checks when dealing with foreign data.

When data comes from parsing JSON, the check above should be enough.

When authoring complicated library code that needs reflection, I think it's worth looking at Vue2's hilarous solution:

 https://github.com/vuejs/vue/blob/547a64e9b93d24ca5927f653710b5734fa909673/src/util/lang.js#L293

Recently, a ticket was added to our sprint with the goal of reducing packages with critical and high vulnerabilities in a legacy project. The task involved migrating a Vue 2 project using Vue CLI as the build tool to Vite.

Vue.js is a tool for building user interfaces. It's easy to use and works well for both small and big projects. I specifically love the team behind Vue and Nuxt! Highly recommend checking it out and giving it a try. It has 208k stars 🌟. Explore Vue.js here.

Repository: Vue.js

GitHub Repository - The main Vue.js repository.

Vuejs

Vue.js is a big favorite for making websites because it's easy to use and fits in well with other stuff. Many people worldwide are using it, and the community keeps growing.

Vue has a thriving ecosystem with a wide range of third-party libraries and plugins available for extending its functionality. These libraries cover everything from state management to routing, making it easy for developers to find solutions to common problems and enhance their development workflow. As of this writing, Vue has 200k GitHub stars.

6. Vue.js

After some hard work (the process is detailed here), I successfully submitted my first PR. I learned a tremendous amount during the review process. I hope to use this feedback to significantly improve my code quality and structure in future PRs.

Has it been merged into the GitHub repo? I wasn't aware of that and I don't see it here: https://github.com/django/django/tree/main/django/tasks/back...

import requests from concurrent.futures import ThreadPoolExecutor URLS = [ "https://www.python.org/", "https://www.djangoproject.com/", "https://flask.palletsprojects.com/", ] def fetch_url(url: str): print(f"Fetching {url}...") response = requests.get(url) print(f"Fetched {url} with status {response.status_code}") return len(response.content) with ThreadPoolExecutor(max_workers=5) as executor: # The map function runs `fetch_url` for each item in URLS results = executor.map(fetch_url, URLS) for url, length in zip(URLS, results): print(f"URL: {url}, Length: {length}")

If this is your first Django contribution, please add yourself to the AUTHORS file and submit a Contributor License Agreement.

Django remains relevant for content-heavy applications and admin interfaces. The batteries-included philosophy means you get authentication, admin panels, ORM, and form handling out of the box. For rapid prototyping or building MVPs where you need traditional CRUD operations, Django's productivity is hard to beat.

Django is a full-stack web framework that provides developers with all the necessary tools and functions they need to develop both the backend and a significant part of the frontend of a web application within a single framework.

Before git abused the terminology, a branch used to refer to a long-lived/persistent commit lineage, most often implemented as a commit-level flag/attribute,

OTOH, git branches are pointers to one single commit (with the git UI tentatively converting this information sometimes into "that commit, specifically" or sometimes as "all ancestors commits leading to that commit", with more or less success and consistency).

Where it matters (besides fostering good/consistent UX) is when you merge several (topological) branches together: git won't be able to tell if you just merged A into B or B into A. Although the content is identical at code-level, the semantic/intent of the merge is lost. Similarly, once the head has progressed so much ahead and your history is riddled with merges, you can't tell from the DAG where the individual features/PR/series start and end. This makes bisecting very hard: while hunting down a regression, you would rather avoid checking-out mid-series commits that might break the build, and instead stick to the series boundaries. You can't do that natively with git. That also makes maintaining concurrent versions unnecessarily difficult, and many projects are struggling with that: have you seen for instance Django¹ prefixing each and every commit with the (long-lived) branch name? That's what you get with git while most other VCSes (like Mercurial, my preference) got right from the start.

¹: https://github.com/django/django/commits/stable/6.0.x

That is, based on the current state of affairs [1] you may get more structure around tasks in the app (or django packages running tasks) which is probably a nice thing. That said, you will still need to have a backend implementation [2] and the easiest path there is a celery wrapper.

[1] https://github.com/django/django/blob/main/django/tasks/base...

The Bakery Demo project uses pip from Python for package management, and the Wagtail dot org website uses Poetry. The differences in connecting both were very subtle, with the bakery demo being the easier of the two. The overarching requirement was that you would have cloned the most recent version of Django from its GitHub repository. For the Bakery Demo, you would need a virtual environment and an installation of Django pointing to your local editable version via pip install -e /path/to/django. This virtual environment would contain your Django, editable version of Wagtail, and Bakery Demo website. For a poetry-based installation, modifying the project's pyproject.toml to point to a locally editable version of Django (or mounted volume of it, as in a potential case of containerization)

"settings.py" is your local configuration. The global default is still Chicago:

* https://github.com/django/django/blob/main/django/conf/globa...