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Python's large standard library [131] 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.
Choosing this arrangement saved considerably on Cython's development time, but modules have a dependency on the Python interpreter and standard library. Although most of the code is C-based, a small stub loader written in interpreted Python is usually required (unless the goal is to create a loader written entirely in C, which may involve work ...
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:
On Apple platforms, these functions are imported from the C standard library (which is imported from Foundation, AppKit or UIKit); on Linux, the developer needs to import Glibc, and ucrt on Windows. V (Vlang) uses GC by default, for user convenience, which can be turned off (-gc none). Users are free to manage memory manually.
Python (programming language) scientific libraries (36 P) Pages in category "Python (programming language) libraries" The following 43 pages are in this category, out of 43 total.
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.
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]