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.

Flask is a micro web framework based on the Werkzeug toolkit and Jinja2 template engine. It is called a micro framework because it does not presume or force a developer to use a particular tool or library.

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 library brings the Olson tz database into Python. It allows accurate and cross platform timezone calculations using Python 2.4 or higher. It also solves the issue of ambiguous times at the end of daylight saving time. Almost all of the Olson timezones are supported.

SCons is a software construction tool. Think of SCons as an improved, cross-platform substitute for the classic Make utility with integrated functionality similar to autoconf/automake and compiler caches such as ccache. In short, SCons is an easier, more reliable and faster way to build software.

The libnl suite is a collection of libraries providing APIs to netlink protocol based Linux kernel interfaces. Netlink is an IPC mechanism primarily between the kernel and user space processes. It was designed to be a more flexible successor to ioctl to provide mainly networking related kernel configuration and monitoring interfaces.

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.

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Pluggy is an extraction of the plugin manager as used by Pytest but stripped of Pytest specific details.

PIDDLE is designed for vector graphics -- i.e., drawing of primitives such as lines and ellipses, rather than manipulation of individual pixels.

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.

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.

Pytest is a testing tool that provides auto-discovery of test modules and functions, detailed info on failing assert statements, modular fixtures, and many external plugins.

Cython is an optimising static compiler for both the Python programming language and the extended Cython programming language. It makes writing C extensions for Python as easy as Python itself.

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.

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.

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.

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python.

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.

MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors.

mpi4py is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point and collective communications of any picklable Python object as well as optimized communications of Python objects (such as NumPy arrays) that expose a buffer interface.