SymPy: Symbolic Computation with Python

Sidhant Nagpal (~sidhantnagpal)


6

Votes

Description:

SymPy is a pure Python library for symbolic mathematics. 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 library. SymPy welcomes contributions from anyone, even if you are new to open source.
In the Devsprint we will replicate the Development workflow of the SymPy Project and help attendees start contributing.

Session Breakdown

  • Introduction to SymPy
  • Brief introduction to git
  • Development setup and workflow
  • Using GitHub issue tracker to find "Easy to fix" issues and working on them
  • Writing code to fix issues and following code style guidelines
  • Testing the code changes locally
  • Writing good commit messages and release notes entry
  • Making your first commit to SymPy and submitting a Pull Request
  • Getting your Pull Request merged
  • Reviewing other people’s code
  • Reporting issues

Prerequisites:

A basic knowledge of Python and Mathematics. No prior knowledge of SymPy or other Python libraries is required, although it is suggested that attendees be familiar with the IPython notebook, basics of git and have a brief idea about the contribution guidelines (optional, this will be covered in the session).

Content URLs:

GitHub repository: https://github.com/sympy/sympy
Gitter channel: https://gitter.im/sympy/sympy
SymPy docs: https://docs.sympy.org
SymPy website: https://www.sympy.org/en/index.html
SymPy live: https://live.sympy.org

Speaker Info:

SymPy India developers will be conducting the Dev Sprint:

  • Sidhant Nagpal: University of Delhi (NSIT) | Core Developer at SymPy, GSoC 2018
  • Ravicharan: IIIT Allahabad| Core Developer at SymPy, GSoC 2018

Section: Data science
Type: Dev Sprint
Target Audience: Beginner
Last Updated:

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