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In computer science, a for-loop or for loop is a control flow statement for specifying iteration. Specifically, a for-loop functions by running a section of code repeatedly until a certain condition has been satisfied. For-loops have two parts: a header and a body. The header defines the iteration and the body is the code executed once per ...
In computing, copy-and-patch compilation is a simple compiler technique intended for just-in-time compilation (JIT compilation) that uses pattern matching to match pre-generated templates to parts of an abstract syntax tree (AST) or bytecode stream, and emit corresponding pre-written machine code fragments that are then patched to insert memory addresses, register addresses, constants and ...
The definition of the term varies depending upon the community using it. In Ruby, [2] Python, [3] and many other dynamic programming languages, the term monkey patch only refers to dynamic modifications of a class or module at runtime, motivated by the intent to patch existing third-party code as a workaround to a bug or feature which does not act as desired.
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 ...
foreach is usually used in place of a standard for loop statement. Unlike other for loop constructs, however, foreach loops [1] usually maintain no explicit counter: they essentially say "do this to everything in this set", rather than "do this x times". This avoids potential off-by-one errors and makes code simpler to read.
In computing, the PATCH method is a request method in HTTP for making partial changes to an existing resource. [1] The PATCH method provides an entity containing a list of changes to be applied to the resource requested using the HTTP Uniform Resource Identifier (URI). [1] The list of changes are supplied in the form of a PATCH document. [1]
However, a generator is an object with persistent state, which can repeatedly enter and leave the same scope. A generator call can then be used in place of a list, or other structure whose elements will be iterated over. Whenever the for loop in the example requires the next item, the generator is called, and yields the next item.
Python 2.5 implements better support for coroutine-like functionality, based on extended generators ; Python 3.3 improves this ability, by supporting delegating to a subgenerator ; Python 3.4 introduces a comprehensive asynchronous I/O framework as standardized in PEP 3156, which includes coroutines that leverage subgenerator delegation