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ScientificPython is a collection of Python modules that are useful for scientific computing. Most modules are rather general (Geometry, physical units, automatic derivatives, ...) whereas others are more domain-specific (e.g. netCDF and PDB support). The library is currently not actively maintained and works only with Python 2 and NumPy < 1.9.
Pluggy is an extraction of the plugin manager as used by Pytest but stripped of Pytest specific details.
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.
This library brings functools.singledispatch from Python 3.4 to Python 2.6-3.3.
This package provides an implementation of importlib.resources for older versions of 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.
Python bindings for GLib, GObject, and GIO.
The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization.
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.
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.
Python's built-in itertools module implements a number of iterator building blocks inspired by constructs from APL, Haskell, and SML. more-itertools includes additional building blocks for working with iterables.
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.
This package provides a pathlib-compatible Zipfile object wrapper. It provides a backport of the Path object.
Pyro is a Distributed Object Technology system written in Python that is designed to be easy to use. It resembles Java's Remote Method Invocation (RMI). It has less similarity to CORBA, which is a system and language independent Distributed Object Technology and has much more to offer than Pyro or RMI. Pyro 3.x is no longer maintained. New projects should use Pyro4 instead, which is the new Pyro version that is actively developed.
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.
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.
MMTK is a library for molecular simulations with an emphasis on biomolecules. It provides widely used methods such as Molecular Dynamics and normal mode analysis, but also basic routines for implementing new methods for simulation and analysis. The library is currently not actively maintained and works only with Python 2 and NumPy < 1.9.
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. Six supports every Python version since 2.5. It is contained in only one Python file, so it can be easily copied into your project.
This Python library allows reading and writing to the Excel XLSX, XLSM, XLTX and XLTM file formats that are defined by the Office Open XML (OOXML) standard.
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.
The goal of pathlib2 is to provide a backport of standard pathlib module which tracks the standard library module, so all the newest features of the standard pathlib can be used also on older Python versions.
Pathlib offers a set of classes to handle file system paths. It offers the following advantages over using string objects:
No more cumbersome use of os and os.path functions. Everything can be done easily through operators, attribute accesses, and method calls.
Embodies the semantics of different path types. For example, comparing Windows paths ignores casing.
Well-defined semantics, eliminating any inconsistencies or ambiguities (forward vs. backward slashes, etc.).
Unittest2 is a replacement for the unittest module in the Python standard library.
Qt is a cross-platform application and UI framework for developers using C++ or QML, a CSS & JavaScript like language.
The Georgia Tech Network Simulator (GTNets) is designed to allow network researchers to conduct simulation-based experiments to observe the behavior of moderate to large scale computer networks under a variety of conditions. The GTNets environment allows the creation of simulation network topologies (consisting of nodes and their associated communication links), and end–user applications describing the flow of data over the simulated topology.