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An alternative is to use underscores; this is common in the C family (including Python), with lowercase words, being found for example in The C Programming Language (1978), and has come to be known as snake case or snail case.
Snake case (sometimes stylized autologically as snake_case) is the naming convention in which each space is replaced with an underscore (_) character, and words are written in lowercase. It is a commonly used naming convention in computing , for example for variable and subroutine names, and for filenames .
Python's name is derived from the British comedy group Monty Python, whom Python creator Guido van Rossum enjoyed while developing the language. Monty Python references appear frequently in Python code and culture; [190] for example, the metasyntactic variables often used in Python literature are spam and eggs instead of the traditional foo and ...
CSBwin was reverse engineered from the game's Atari assembler code to a pure C version in months of work. [309] [310] In 2014 Christophe Fontanel released another reverse engineering project which tries to recreate all existing versions. [311] [312] E.T. the Extra-Terrestrial: 1982 2006 Arcade: Atari: In 2006, decompiled by Dennis Debro.
To demonstrate the value of the escape sequence feature, to output the text Foo on one line and Bar on the next line, the code must output a newline between the two words. The following code achieves the goal via text formatting and a hard-coded ASCII character value for newline (0x0A).
Some languages, notably C, promptly adopted underscores as word separators, and identifiers such as end_of_file are still prevalent in C programs and libraries (as well as in later languages influenced by C, such as Perl and Python). However, some languages and programmers chose to avoid underscores and adopted camel case instead.
A snippet of C code which prints "Hello, World!". The syntax of the C programming language is the set of rules governing writing of software in C. It is designed to allow for programs that are extremely terse, have a close relationship with the resulting object code, and yet provide relatively high-level data abstraction.
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus.