Have Python code compiled in the blink on an eye with the help of this powerful interpreter with an implemented Just-in-Time compiler. #Python implementation #JIT compiler #Application development #Development #JIT #Develop
The backbone of every application is represented by an unimaginable amount of lines of code that make each function properly serve its purpose. There are various programming languages out there, some easier than others or with more features. PyPy is one of them and aims to provide a little more speed than CPython when it comes to compiling and processing.
Since the application does not require you to go through a setup process you can easily keep it on a removable storage device and attend to your work wherever you are. If you've been using Python, then no accommodation problems should be encountered, because syntax writing is the same.
One of the biggest advantages is the complete compatibility with even the most recent versions of Python, letting you import past work and process it faster. Some of the most commonly used libraries in Python can be run using the application, such as Pylons, Pyglet, Nevow and Django.
Another useful feature is the implemented JIT (just in time) compiler. This enables the application to have Python code turned into instructions that your computer can read in no time.
Developed as a faster means of interpreting Python code than CPython, the application mostly focuses on speed and compatibility. This enables it to run more advanced features not having to encode low level details into it.
Taking everything into consideration, we can say that PyPy makes for a worthy competitor to the commonly used CPython interpreter. It's constantly being tested and updated so that compatibility between it and Python remains intact. Overall, it's a little utility worth having installed if you prefer Python as a programming language.
What's new in PyPy 2.6.0:
- ssue2005: ignore errors on closing random file handles while importing a module (cpython compatibility)
- issue2013: added constants to _ssl for TLS 1.1 and 1.2
- issue2014: Add PyLong_FromUnicode to cpyext.
- issue2017: On non-Linux-x86 platforms, reduced the memory impact of creating a lot of greenlets/tasklets. Particularly useful on Win32 and on ARM, where you used to get a MemoryError after only 2500-5000 greenlets (the 32-bit address space is exhausted).
PyPy 2.6.0
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- Windows All
- file size:
- 26.4 MB
- filename:
- pypy-2.6.0-win32.zip
- main category:
- Programming
- developer:
- visit homepage
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