GitHub Desktop
GitKraken
SourceTree
SmartGit
Fork
TortoiseGit
Tower
GitHub
PyPy
cx_Freeze
bbfreeze
Numba
Cython
PyInstaller
PyOxidizer
asciinema
GitHub DesktopBased on our record, GitHub Desktop seems to be a lot more popular than PyPy. While we know about 136 links to GitHub Desktop, we've tracked only 9 mentions of PyPy. 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.
Optional: You can also download GitHub Desktop (https://desktop.github.com) if you prefer a GUI version, but this guide focuses on Git Bash to understand the basics. - Source: dev.to / 7 months ago
Download the latest version from the GitHub Desktop website. - Source: dev.to / over 1 year ago
Iโm not going to dive into Git commands here โ you can find plenty of tutorials online. If youโre not a fan of using the plain terminal CLI, you can also manage repositories with tools like GitHub Desktop or SourceTree, which provide a more visual, intuitive interface. - Source: dev.to / almost 2 years ago
Using terminal commands isnโt necessary for basic adoption of Git with Corticon Studio files, though. There are various tools that will allow us to bypass the command line when defining rules, including the built-in Eclipse plugin for Git version control. If youโll be storing your assets on GitHub, though, an even easier solution is GitHub Desktop, a free desktop software that GitHub offers. It can be used in... - Source: dev.to / almost 2 years ago
Nix currently is akin to git's "porcelain": powerful but esoteric. However, much like git evolved into exoteric, user-friendly tools such as git-flow, GitHub Desktop, and Tower to become user-friendly, many developers are building abstractions, wrappers, and utilities to simplify Nix usage. Let's briefly look at a few of these tools now. - Source: dev.to / almost 2 years ago
There are quite a few JITs: JIT-compiler for Python https://pypy.org/ Python enhancement proposal for JIT in CPython https://peps.python.org/pep-0744/ And there are several JIT-compilers for various subsets of Python, usually with focus on numerical code and often with GPU support, for example Numba https://numba.pydata.org/numba-doc/dev/user/jit.html Taichi Lang https://github.com/taichi-dev/taichi. - Source: Hacker News / 6 months ago
Gains than using either compiler alone. This uses the PyPy JIT framework to speed up a RISC-V simulator. https://pypy.org/ https://github.com/pydrofoil/pydrofoil Pydrofoil: A fast RISC-V emulator generated from the Sail model, using PyPy's JIT. - Source: Hacker News / over 1 year ago
"On average, PyPy is 4.4 times faster than CPython 3.7." https://pypy.org/. - Source: Hacker News / over 1 year ago
If you're going the pure Python route, don't forget to try PyPy[1], an alternative JITed implementation of the language. A seriously underrated project, IMHO. Most time it speeds up execution by a factor of 2x-4x, but improvements of about two orders of magnitude are not unheard of. See for example [2]. Numeric, long-running code shoud suit PyPy optimizations well. [1] https://pypy.org/ [2]... - Source: Hacker News / almost 2 years ago
Python: My Python-foo is limited, so I only ported the last problem (a simple while loop) and ran it with PyPy. It takes a bit less of time:. - Source: dev.to / over 2 years ago
GitKraken - The intuitive, fast, and beautiful cross-platform Git client.
cx_Freeze - cx_Freeze is a set of scripts and modules for freezing Python scripts into executables in much the...
SourceTree - Mac and Windows client for Mercurial and Git.
bbfreeze - create stand-alone executables from python scripts
SmartGit - SmartGit is a front-end for the distributed version control system Git and runs on Windows, Mac OS...
Numba - Numba gives you the power to speed up your applications with high performance functions written...