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Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions.
Numarray and Numeric were the predecessors of NumPy. Numarray was created as an alternative to Numeric because the latter was cumbersome to use when efficiency for large array operations was a priority. Howver, numarray was less efficient for small arrays, and thus could not replace Numeric. Many packages of the early SciPy ecosystem supported both Numeric and numarray, with the choice made at build time.
The last bugfix release of the Python 2.4 series, which started with 2.4.0, released on 2004-11-30. Python 2.5 was released on 2006-09-19.
NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities.
Pyx is a Python package for the generation of PostScript, PDF, and SVG files. It combines an abstraction of the PostScript drawing model with a TeX/LaTeX interface. Complex tasks like 2d and 3d plots in publication-ready quality are built out of these primitives.
rpy2 is a redesign and rewrite of rpy. It is providing a low-level interface to R from Python, a proposed high-level interface, including wrappers to graphical libraries, as well as R-like structures and functions.
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It’s based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow.
Coverage measures code coverage, typically during test execution. It uses the code analysis tools and tracing hooks provided in the Python standard library to determine which lines are executable, and which have been executed.
NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities.
This package provides a Python library intended for use in automated tests. One difficulty when testing software is that the code under test might need to read or write to files in the local file system. If the file system is not set up in just the right way, it might cause a spurious error during the test. The pyfakefs library provides a solution to problems like this by mocking file system interactions. In other words, it arranges for the code under test to interact with a fake file system instead of the real file system. The code under test requires no modification to work with pyfakefs.
Unittest2 is a replacement for the unittest module in the Python standard library.
The lxml XML toolkit is a Pythonic binding for the C libraries libxml2 and libxslt.
The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.
This is a backport of the standard library typing module to Python versions older than 3.5. Typing defines a standard notation for Python function and variable type annotations. The notation can be used for documenting code in a concise, standard format, and it has been designed to also be used by static and runtime type checkers, static analyzers, IDEs and other tools.
Wcwidth measures the number of terminal column cells of wide-character codes. It is useful for those implementing a terminal emulator, or programs that carefully produce output to be interpreted by one. It is a Python implementation of the wcwidth and wcswidth C functions specified in POSIX.1-2001 and POSIX.1-2008.
This module is primarily a backport of the Python 3.2 contextlib to earlier Python versions. Like contextlib, it provides utilities for common tasks involving decorators and context managers. It also contains additional features that are not part of the standard library.
Mock is a library for testing in Python. It allows you to replace parts of your system under test with mock objects and make assertions about how they have been used. This library is now part of Python (since Python 3.3), available via the unittest.mock module.
Directory iteration function like os.listdir(), except that instead of returning a list of bare filenames, it yields DirEntry objects that include file type and stat information along with the name. Using scandir() increases the speed of os.walk() by 2-20 times (depending on the platform and file system) by avoiding unnecessary calls to os.stat() in most cases.
This package is part of the Python standard library since version 3.5.
Enum34 is the new Python stdlib enum module available in Python 3.4 backported for previous versions of Python from 2.4 to 3.3.
importlib_metadata is a library which provides an API for accessing an installed Python package's metadata, such as its entry points or its top-level name. This functionality intends to replace most uses of pkg_resources entry point API and metadata API. Along with importlib.resources in Python 3.7 and newer, this can eliminate the need to use the older and less efficient pkg_resources package.
Nose extends the unittest library to make testing easier.
This library brings functools.singledispatch from Python 3.4 to Python 2.6-3.3.
NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities. Version 1.8 is the last one to contain the numpy.oldnumeric API that includes the compatibility layer numpy.oldnumeric with NumPy's predecessor Numeric.