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Pip provides a way to install user-defined projects locally with the use of setup.py file. This method requires the Python project to have the following file structure: This method requires the Python project to have the following file structure:
The program works on Windows, macOS and Linux. It is available as a binary bundle including the recent Python interpreter [4] or pip-installable package. [7] It can be installed via the operating-system package manager on Debian, Raspberry Pi, Ubuntu, and Fedora.
Before then, py2exe was made only for Python 2, [4] and it was necessary to use an alternative like cx_Freeze for Python 3 code. Although this program transforms a .py file to an .exe, it does not make it run faster because py2exe bundles the Python bytecode without converting it to machine-code.
The Python Package Index, abbreviated as PyPI (/ ˌ p aɪ p i ˈ aɪ /) and also known as the Cheese Shop (a reference to the Monty Python's Flying Circus sketch "Cheese Shop"), [2]: 8 [3]: 742 is the official third-party software repository for Python. [4] It is analogous to the CPAN repository for Perl [5]: 36 and to the CRAN repository for R.
Numba is used from Python, as a tool (enabled by adding a decorator to relevant Python code), a JIT compiler that translates a subset of Python and NumPy code into fast machine code. Pythran compiles a subset of Python 3 to C++ . [165] RPython can be compiled to C, and is used to build the PyPy interpreter of Python.
To further facilitate the setup of such environments, Conda can also install Python, the interpreter for the software packages itself. [17] Conda is written in the Python programming language, but can manage projects containing code written in any language, including multi-language projects.
A built-in file explorer, for interacting with the filesystem and managing projects; A "Find in Files" feature, allowing full regular expression search over a specified scope; An online help browser, allowing users to search and view Python and package documentation inside the IDE; A history log, recording every user command entered in each console
The non-Python library being called to perform the CPU-intensive task is not subject to the GIL and may concurrently execute many threads on multiple processors without restriction. Concurrency of Python code can only be achieved with separate CPython interpreter processes managed by a multitasking operating system.