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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 .
A collection may provide multiple iterators via its interface that provide items in different orders, such as forwards and backwards. An iterator is often implemented in terms of the structure underlying a collection implementation and is often tightly coupled to the collection to enable the operational semantics of the iterator.
Python coding style is covered in PEP 8. [176] Outstanding PEPs are reviewed and commented on by the Python community and the steering council. [175] Enhancement of the language corresponds with the development of the CPython reference implementation. The mailing list python-dev is the primary forum for the language's development.
Blackburn and McKinley's ulterior reference counting method in 2003 [8] combines deferred reference counting with a copying nursery, observing that the majority of pointer mutations occur in young objects. This algorithm achieves throughput comparable with the fastest generational copying collectors with the low bounded pause times of reference ...
PyCharm was released to the market of the Python-focused IDEs to compete with PyDev (for Eclipse) or the more broadly focused Komodo IDE by ActiveState. [ citation needed ] The beta version of the product was released in July 2010, with the 1.0 arriving 3 months later.
Requests is an HTTP client library for the Python programming language. [2] [3] Requests is one of the most downloaded Python libraries, [2] with over 300 million monthly downloads. [4] It maps the HTTP protocol onto Python's object-oriented semantics. Requests's design has inspired and been copied by HTTP client libraries for other programming ...
These libraries are generally not written in Python, and Python code in another thread can be executed while a call to one of these underlying processes takes place. The non-Python library being called to perform the CPU-intensive task is not subject to the GIL and may concurrently execute many threads on multiple processors without restriction.
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.