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This is a comparison of the features of the type systems and type checking of multiple programming languages.. Brief definitions A nominal type system means that the language decides whether types are compatible and/or equivalent based on explicit declarations and names.
Smalltalk, Ruby, Python, and Self are all "strongly typed" in the sense that typing errors are prevented at runtime and they do little implicit type conversion, but these languages make no use of static type checking: the compiler does not check or enforce type constraint rules.
Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Readability counts. However, Python features regularly violate these principles and have received criticism for adding unnecessary language bloat. [81] Responses to these criticisms are that the Zen of Python is a ...
Multiparadigm languages support more than one programming paradigm. They allow a program to use more than one programming style. The goal is to allow programmers to use the best tool for a job, admitting that no one paradigm solves all problems in the easiest or most efficient way.
PyPy (/ ˈ p aɪ p aɪ /) is an implementation of the Python programming language. [2] PyPy often runs faster than the standard implementation CPython because PyPy uses a just-in-time compiler. [3] 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 ...
An interpreter is a program that reads another program, typically as text, [4] as seen in languages like Python. [2] Interpreters read code, and produce the result directly. [8] Interpreters typically read code line by line, and parse it to convert and execute the code as operations and actions. [9]
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})
The process of verifying and enforcing the constraints of types—type checking—may occur at compile time (a static check) or at run-time (a dynamic check). If a language specification requires its typing rules strongly, more or less allowing only those automatic type conversions that do not lose information, one can refer to the process as strongly typed; if not, as weakly typed.