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  2. py2exe - Wikipedia

    en.wikipedia.org/wiki/Py2exe

    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. It may even run slower than using the Python interpreter directly because of startup overhead.

  3. RPyC - Wikipedia

    en.wikipedia.org/wiki/RPyC

    The execute function, that executes the given code on the server: conn.execute("print 'hello world'") Remote operations return something called a NetProxy, which is an intermediate object that reflects any operation performed locally on it to the remote object. For example, conn.modules.sys.path is a NetProxy for the sys.path object of the server.

  4. Interpreter (computing) - Wikipedia

    en.wikipedia.org/wiki/Interpreter_(computing)

    Perl, Raku, Python, MATLAB, and Ruby are examples of the second, while UCSD Pascal is an example of the third type. Source programs are compiled ahead of time and stored as machine independent code, which is then linked at run-time and executed by an interpreter and/or compiler (for JIT systems).

  5. Shebang (Unix) - Wikipedia

    en.wikipedia.org/wiki/Shebang_(Unix)

    #!/usr/bin/env python3 – Execute with a Python interpreter, using the env program search path to find it #!/bin/false – Do nothing, but return a non-zero exit status , indicating failure. Used to prevent stand-alone execution of a script file intended for execution in a specific context, such as by the . command from sh/bash, source from ...

  6. PyPy - Wikipedia

    en.wikipedia.org/wiki/PyPy

    Most Python code runs well on PyPy except for code that depends on CPython extensions, which either does not work or incurs some overhead when run in PyPy. PyPy itself is built using a technique known as meta-tracing, which is a mostly automatic transformation that takes an interpreter as input and produces a tracing just-in-time compiler as

  7. CPython - Wikipedia

    en.wikipedia.org/wiki/CPython

    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.

  8. MicroPython - Wikipedia

    en.wikipedia.org/wiki/MicroPython

    MicroPython consists of a Python compiler to bytecode and a runtime interpreter of that bytecode. The user is presented with an interactive prompt (the REPL) to execute supported commands immediately. Included are a selection of core Python libraries; MicroPython includes modules which give the programmer access to low-level hardware. [4]

  9. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...