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Interpreters have a wide variety of instructions which are specialized to perform different tasks, but you will commonly find interpreter instructions for basic mathematical operations, branching, and memory management, making most interpreters Turing complete. Many interpreters are also closely integrated with a garbage collector and debugger.
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 ...
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
An interpreter is composed of two parts: a parser and an evaluator. After a program is read as input by an interpreter, it is processed by the parser. The parser breaks the program into language components to form a parse tree. The evaluator then uses the parse tree to execute the program. [3]
Concurrency of Python code can only be achieved with separate CPython interpreter processes managed by a multitasking operating system. This complicates communication between concurrent Python processes , though the multiprocessing module mitigates this somewhat; it means that applications that really can benefit from concurrent Python-code ...
This is an accepted version of this page This is the latest accepted revision, reviewed on 5 January 2025. Language for communicating instructions to a machine The source code for a computer program in C. The gray lines are comments that explain the program to humans. When compiled and run, it will give the output "Hello, world!". A programming language is a system of notation for writing ...
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 ...
Two examples of this directing an interpreter are: The Unix "shebang" – #! – used on the first line of a script to point to the interpreter to be used. "Magic comments" identifying the encoding a source file is using, [21] e.g. Python's PEP 263. [22] The script below for a Unix-like system shows both of these uses: