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Based on our record, GitHub seems to be a lot more popular than iPython. While we know about 2469 links to GitHub, we've tracked only 20 mentions of iPython. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The real fragility is in trying to constrain arguments. The docs are explicit that a pattern like Bash(curl http://github.com/ *) fails to do what it looks like it does. It won't match curl -X GET http://github.com/... (option before the URL), curl https://github.com/... (different protocol), curl -L http://bit.ly/xyz (redirects to GitHub), URL=http://github.com && curl $URL (variable), or curl http://github.com... - Source: dev.to / 1 day ago
Fallback chains โ og:title โ twitter:title โ- SSRF protection โ if you fetch user-supplied URLs, you MUST block
localhost, RFC-1918 ranges, and internal hostnames, or your preview endpoint is a proxy into your own infrastructure- Caching โ you do not want to re-fetch a URL on every render
- Rate limiting โ a public...
- Source: dev.to / 3 days ago
$ git pull Remote: Repository not found. Fatal: repository 'https://github.com//.git/' not found. - Source: dev.to / 5 days ago
// ==UserScript== // @name GitHub -> Obsidian Task // @namespace obsidian // @version 1.0 // @match https://github.com/*/*/issues/* // @match https://github.com/*/*/pull/* // @grant GM_setClipboard // ==/UserScript== (function () { 'use strict'; function getTitle() { return document.querySelector("bdi")?.textContent.trim(); } function copyTask() { ... - Source: dev.to / 7 days ago
Import requests From bs4 import BeautifulSoup From datetime import datetime Def fetch_github_trending(): url = "https://github.com/trending?since=daily" response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') repos = [] for article in soup.select('article.Box-row'): repo_link = article.select_one('h2 a')['href'] stars_today =... - Source: dev.to / 8 days ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
As alluded to in Poetry2Nix Development Flake with Matplotlib GTK Support, Iโm currently in the process of getting my โnewโ python workflow up to speed. My second problem, after dependency and environment management, was that fancy REPLs like ipython or ptpython donโt jazz well with the standard comint based inferior python repl that comes with python-mode. One can basically only run ipython with the... - Source: dev.to / about 2 years ago
Third, if possible use a command line interpreter to test things out. I recommend ipython for this purpose. You can use your browser's developer console this way if you are learning Javascript. Source: over 3 years ago
IJulia is an interactive notebook environment powered by the Julia programming language. Its backend is integrated with that of the Jupyter environment. The interface is web-based, similar to the iPython notebook. It is open-source and cross-platform. - Source: dev.to / over 3 years ago
Also, take a look at installing iPthon to give you a much richer shell environment. This underpins Jupyter Notebooks, so is well known, proven and trusted. Source: over 3 years ago
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Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...
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Spyder - The Scientific Python Development Environment