IPython¶

IPython is an enhanced version of Python interpreter,which provides features of great interest to scientists. Theinline modeallows graphics and plots to be displayed in the terminal (Qt based version).Moreover, thenotebook mode supports literate programming and reproduciblescience generating a web-based Python notebook. This notebook allows you tostore chunks of Python code along side the results and additional comments(HTML, LaTeX, Markdown). The notebook can then be shared and exported in variousfile formats.

NumPy¶

NumPy is a low level library written in C (andFORTRAN) for high level mathematical functions. NumPy cleverly overcomes theproblem of running slower algorithms on Python by using multidimensional arraysand functions that operate on arrays. Any algorithm can then be expressed as afunction on arrays, allowing the algorithms to be run quickly.

NumPy is part of the SciPy project, and is released as a separate library sopeople who only need the basic requirements can use it without installing therest of SciPy.

NumPy is compatible with Python versions 2.4 through to 2.7.2 and 3.1+.

Numba¶

Numba is a NumPy aware Python compiler(just-in-time (JIT) specializing compiler) which compiles annotated Python (andNumPy) code to LLVM (Low Level Virtual Machine) through special decorators.Briefly, Numba uses a system that compiles Python code with LLVM to code whichcan be natively executed at runtime.

SciPy¶

SciPy is a library that uses NumPy for more mathematicalfunctions. SciPy uses NumPy arrays as the basic data structure, and comeswith modules for various commonly used tasks in scientific programming,including linear algebra, integration (calculus), ordinary differential equationsolving and signal processing.

Matplotlib¶

Matplotlib is a flexible plottinglibrary for creating interactive 2D and 3D plots that can also be saved asmanuscript-quality figures. The API in many ways reflects that ofMATLAB, easing transition of MATLABusers to Python. Many examples, along with the source code to re-create them,are available in thematplotlib gallery.

Pandas¶

Pandas is data manipulation librarybased on Numpy which provides many useful functions for accessing,indexing, merging and grouping data easily. The main data structure (DataFrame)is close to what could be found in the R statistical package; that is,heterogeneous data tables with name indexing, time series operations andauto-alignment of data.

Rpy2¶

Rpy2 is a Python binding for the Rstatistical package allowing the execution of R functions from Python andpassing data back and forth between the two environments. Rpy2 is the objectoriented implementation of theRpybindings.

PsychoPy¶

PsychoPy is a library for cognitive scientistsallowing the creation of cognitive psychology and neuroscience experiments.The library handles presentation of stimuli, scripting of experimental designand data collection.

Unofficial Windows Binaries for Python Extension Packages¶

Many people who do scientific computing are on Windows, yet many of thescientific computing packages are notoriously difficult to build and install onthis platform.Christoph Gohlkehowever, has compiled a list of Windows binaries for many useful Pythonpackages. The list of packages has grown from a mainly scientific Pythonresource to a more general list. If you’re on Windows, you may want to check itout.

Anaconda¶

Continuum Analytics offers theAnacondaPython Distribution whichincludes all the common scientific Python packages as well as many packagesrelated to data analytics and big data. Anaconda itself is free, andContinuum sells a number of proprietary add-ons. Free licenses for theadd-ons are available for academics and researchers.

Canopy¶

Canopy is another scientificPython distribution, produced byEnthought.A limited ‘Canopy Express’ variant is available for free, but Enthoughtcharges for the full distribution. Free licenses are available for academics.