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Python syntax and semantics
The syntax of the Python programming language is the set of rules that defines how a Python program will be written and interpreted (by both the runtime system and by human readers). The Python language has many similarities to Perl, C, and Java. However, there are some definite differences between the languages. It supports multiple programming paradigms, including structured, object-oriented programming, and functional programming, and boasts a dynamic type system and automatic memory management.
Python's syntax is simple and consistent, adhering to the principle that "There should be one—and preferably only one—obvious way to do it."[citation needed] The language incorporates built-in data types and structures, control flow mechanisms, first-class functions, and modules for better code reusability and organization. Python also uses English keywords where other languages use punctuation, contributing to its uncluttered visual layout.
The language provides robust error handling through exceptions, and includes a debugger in the standard library for efficient problem-solving. Python's syntax, designed for readability and ease of use, makes it a popular choice among beginners and professionals alike.
Python was designed to be a highly readable language. It has a relatively uncluttered visual layout and uses English keywords frequently where other languages use punctuation. Python aims to be simple and consistent in the design of its syntax, encapsulated in the mantra "There should be one— and preferably only one —obvious way to do it", from the Zen of Python.
This mantra is deliberately opposed to the Perl and Ruby mantra, "there's more than one way to do it".
Python 3 has 35 keywords or reserved words; they cannot be used as identifiers.
In addition, Python 3 also has 4 soft keywords, including type added in Python 3.12. Unlike regular hard keywords, soft keywords are reserved words only in the limited contexts where interpreting them as keywords would make syntactic sense. These words can be used as identifiers elsewhere, in other words, match and case are valid names for functions and variables.
Function annotations (type hints) are defined in PEP 3107. They allow attaching data to the arguments and return of a function. The behaviour of annotations is not defined by the language, and is left to third party frameworks. For example, a library could be written to handle static typing:
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Python syntax and semantics
The syntax of the Python programming language is the set of rules that defines how a Python program will be written and interpreted (by both the runtime system and by human readers). The Python language has many similarities to Perl, C, and Java. However, there are some definite differences between the languages. It supports multiple programming paradigms, including structured, object-oriented programming, and functional programming, and boasts a dynamic type system and automatic memory management.
Python's syntax is simple and consistent, adhering to the principle that "There should be one—and preferably only one—obvious way to do it."[citation needed] The language incorporates built-in data types and structures, control flow mechanisms, first-class functions, and modules for better code reusability and organization. Python also uses English keywords where other languages use punctuation, contributing to its uncluttered visual layout.
The language provides robust error handling through exceptions, and includes a debugger in the standard library for efficient problem-solving. Python's syntax, designed for readability and ease of use, makes it a popular choice among beginners and professionals alike.
Python was designed to be a highly readable language. It has a relatively uncluttered visual layout and uses English keywords frequently where other languages use punctuation. Python aims to be simple and consistent in the design of its syntax, encapsulated in the mantra "There should be one— and preferably only one —obvious way to do it", from the Zen of Python.
This mantra is deliberately opposed to the Perl and Ruby mantra, "there's more than one way to do it".
Python 3 has 35 keywords or reserved words; they cannot be used as identifiers.
In addition, Python 3 also has 4 soft keywords, including type added in Python 3.12. Unlike regular hard keywords, soft keywords are reserved words only in the limited contexts where interpreting them as keywords would make syntactic sense. These words can be used as identifiers elsewhere, in other words, match and case are valid names for functions and variables.
Function annotations (type hints) are defined in PEP 3107. They allow attaching data to the arguments and return of a function. The behaviour of annotations is not defined by the language, and is left to third party frameworks. For example, a library could be written to handle static typing: