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The Python Distribution Utilities (distutils) Python module was first added to the Python standard library in the 1.6.1 release, in September 2000, and in the 2.0 release, in October 2000, nine years after the first Python release in February 1991, with the goal of simplifying the process of installing third-party Python packages.
This is the philosophy that is used in the C and C++ standard libraries. By contrast, Guido van Rossum, designer of Python, has embraced a much more inclusive vision of the standard library. Python attempts to offer an easy-to-code, object-oriented, high-level language. [citation needed] In the Python tutorial, he writes:
Python's large standard library [132] provides tools suited to many tasks and is commonly cited as one of its greatest strengths. For Internet-facing applications, many standard formats and protocols such as MIME and HTTP are supported.
All collections provided by the standard library implement the IntoIterator trait (meaning they define the into_iter() method). Iterators themselves implement the Iterator trait, which requires defining the next() method. Furthermore, any type implementing Iterator is automatically provided an implementation for IntoIterator that returns itself.
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 .
One of the very useful aspects of Python is the concept of collection (or container) types. In general a collection is an object that contains other objects in a way that is easily referenced or indexed. Collections come in two basic forms: sequences and mappings. The ordered sequential types are lists (dynamic arrays), tuples, and strings.
De facto standard for matrix/tensor operations in Python. Pandas , a library for data manipulation and analysis. SageMath is a large mathematical software application which integrates the work of nearly 100 free software projects and supports linear algebra, combinatorics, numerical mathematics, calculus, and more.
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.