Computer aided algebra system (CAS) for different programming languages using SymEngine and SymPy

Shekhar Prasad Rajak (~Shekharrajak)


6

Votes

Description:

What do a mathematical students or normal people need to perform symbolic manipulation for the resolution of common problems?

A simple and interactive program that can do manipulation of mathematical expressions in symbolic form effectively.

SymPy is a pure Python library for symbolic mathematics that can be used as an interactive command line, using IPython and Jupyter notebook. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries.

This tutorial is intended to cover the basics as well as touch on more advanced topics and new features that are added recent years. We will start by showing how to install and configure this Python module. Then we will proceed to the basics of constructing and manipulating mathematical expressions in SymPy. We will also discuss the most common issues and differences from other computer algebra systems, and how to deal with them. In the remaining part of this tutorial we will show how to solve mathematical problems with SymPy.

This knowledge should be enough for attendees to start using SymPy for solving mathematical problems and hacking SymPy's internals (though hacking core modules may require additional expertise).

SymEngine is a standalone fast C++ symbolic manipulation library. Optional thin wrappers allow usage of the library from other languages (Python, Ruby, Julia, Haskell).

The workshop will also include a hands-on introduction to SymEngine in Python for the advantages of speed while using SymPy. This section would focus heavily on SymEngine's Python wrapper called SymEngine.py, and the various methodologies employed by it, the use of Cython, an account of the modules currently supporting the use of SymEngine, the subsequent impact on performance and the major projects using SymEngine. In addition to the above, there will also be a light introduction towards installation and usage of SymEngine library in Ruby, Haskell and Julia, through their respective wrappers.

Prerequisites:

We expect attendees of this tutorial to have basic knowledge of Python, C++, Ruby, Julia and mathematics. However, many more advanced topics for SymPy will be explained during presentation and basic examples for SymEngine wrappers. No prior knowledge of SymPy or other Python libraries is required, although it is suggested that attendees be familiar with the IPython notebook.

We recommend that the attendees install the Anaconda Python distribution which includes SymPy, NumPy, and IPython. Once Anaconda is installed simply type the following in a terminal to install the necessary packages:

$ conda install numpy ipython-notebook sympy

Other alternative installation instructions can be found here: http://docs.sympy.org/dev/install.html

SymEngine and its Python wrapper can be installed directly through:

$ conda install -c conda-forge python-symengine

Other alternative installation instructions can be found at:

Content URLs:

SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences.

The website for the workshop at PyCon India 2017 is here (You can find the introduction slides, the sphinx tutorial, and The exercises in form of IPython notebooks in the website navbar).

Note: that the notebooks are hosted statically, you can download from the repo and run locally to have an interactive session.

Speaker Info:

SymPy India developers will be conducting the workshop:

  • Amit Kumar, Core Developer & GSoC-cer at SymPy
  • Shekhar Prasad Rajak : NIT Warangal | Core Developer at SymPy GSoC 2016 | Solvers, Sets
  • Shikhar Jaiswal : IIT Patna | Student Developer at SymPy GSoC 2017 | SymPy - SymEngine Integration and Python Wrappers

Speaker Links:

Workshop resource website: https://shekharrajak.github.io/PyCon-SymPy-SymEngine/

Resource repository: https://github.com/Shekharrajak/PyCon-SymPy-SymEngine

SymPy website: http://www.sympy.org/en/index.html

SymPy live: http://live.sympy.org/

GitHub repository: https://github.com/sympy/sympy , https://github.com/symengine/symengine

Links to previous tutorials/talks

Section: Scientific Computing
Type: Workshops
Target Audience: Beginner
Last Updated:

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