Summary
IPython (Interactive Python) is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language, that offers introspection, rich media, shell syntax, tab completion, and history. IPython provides the following features: Interactive shells (terminal and Qt-based). A browser-based notebook interface with support for code, text, mathematical expressions, inline plots and other media. Support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into one's own projects. Tools for parallel computing. IPython is a NumFOCUS fiscally sponsored project. IPython is based on an architecture that provides parallel and distributed computing. IPython enables parallel applications to be developed, executed, debugged and monitored interactively, hence the I (Interactive) in IPython. This architecture abstracts out parallelism, enabling IPython to support many different styles of parallelism including: Single program, multiple data (SPMD) parallelism Multiple program, multiple data (MPMD) parallelism Message passing using MPI Task parallelism Data parallelism Combinations of these approaches Custom user defined approaches With the release of IPython 4.0, the parallel computing capabilities were made optional and released under the ipyparallel python package. And most of the capabilities of ipyparallel are now covered by more mature libraries like Dask. IPython frequently draws from SciPy stack libraries like NumPy and SciPy, often installed alongside one of many Scientific Python distributions. IPython provides integration with some libraries of the SciPy stack, notably matplotlib, producing inline graphs when used with the Jupyter notebook. Python libraries can implement IPython specific hooks to customize rich object display. SymPy for example implements rendering of mathematical expressions as rendered LaTeX when used within IPython context, and Pandas dataframe use an HTML representation.
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Cython
Cython (ˈsaɪθɒn) is a superset of the programming language Python, which allows developers to write Python code (with optional, C-inspired syntax extensions) that yields performance comparable to that of C. Cython is a compiled language that is typically used to generate CPython extension modules. Annotated Python-like code is compiled to C (also usable from e.g. C++) and then automatically wrapped in interface code, producing extension modules that can be loaded and used by regular Python code using the import statement, but with significantly less computational overhead at run time.
Notebook interface
A notebook interface or computational notebook is a virtual notebook environment used for literate programming, a method of writing computer programs. Some notebooks are WYSIWYG environments including executable calculations embedded in formatted documents; others separate calculations and text into separate sections. Notebooks share some goals and features with spreadsheets and word processors but go beyond their limited data models. Modular notebooks may connect to a variety of computational back ends, called "kernels".
Matplotlib
Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK. There is also a procedural "pylab" interface based on a state machine (like OpenGL), designed to closely resemble that of MATLAB, though its use is discouraged. SciPy makes use of Matplotlib. Matplotlib was originally written by John D. Hunter.
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