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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.
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 ...
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 ...
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IDLE (short for Integrated Development and Learning Environment) [2] [3] is an integrated development environment for Python, which has been bundled with the default implementation of the language since 1.5.2b1. [4] [5] It is packaged as an optional part of the Python packaging with many Linux distributions.
With Stackless Python, a running program is split into microthreads that are managed by the language interpreter itself, not the operating system kernel—context switching and task scheduling is done purely in the interpreter (these are thus also regarded as a form of green thread). Microthreads manage the execution of different subtasks in a ...
In computer science, an interpreter is a computer program that directly executes instructions written in a programming or scripting language, without requiring them previously to have been compiled into a machine language program. An interpreter generally uses one of the following strategies for program execution: