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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})
In computer programming, a collection is an abstract data type that is a grouping of items that can be used in a polymorphic way. Often, the items are of the same data type such as int or string . Sometimes the items derive from a common type; even deriving from the most general type of a programming language such as object or variant .
The standard type hierarchy of Python 3. In computer science and computer programming, a data type (or simply type) is a collection or grouping of data values, usually specified by a set of possible values, a set of allowed operations on these values, and/or a representation of these values as machine types. [1]
Programming languages can have multiple implementations. Different implementations can be written in different languages and can use different methods to compile or interpret code. For example, implementations of Python include: [9] CPython, the reference implementation of Python; IronPython, an implementation targeting the .NET Framework ...
Other examples include interpreter directives: 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:
While high-level languages such as Python or Haskell use unbounded integers by default, lower-level programming languages such as C or assembly language typically operate on finitely-sized machine words, which are more suitably modeled using the integers modulo (where n is the bit width of a machine word). There are several abstract domains ...
Stop-and-copy garbage collection in a Lisp architecture: [1] Memory is divided into working and free memory; new objects are allocated in the former. When it is full (depicted), garbage collection is performed: All data structures still in use are located by pointer tracing and copied into consecutive locations in free memory.
An example is whether a closure in a Lisp-like language is implemented using closures in the interpreter language or implemented "manually" with a data structure explicitly storing the environment. The more features implemented by the same feature in the host language, the less control the programmer of the interpreter has; for example, a ...