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About this episode
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Summary
Looking for an open source alternative to Mathematica or MatLab for solving algebraic equations? Look no further than the excellent SymPy project. It is a well built and easy to use Computer Algebra System (CAS) and in this episode we spoke with the current project maintainer Aaron Meurer about its capabilities and when you might want to use it.
Brief Introduction
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- We are recording today on January 18th, 2016 and your hosts as usual are Tobias Macey and Chris Patti
- Today we are interviewing Aaron Meurer about SymPy
Interview with Aaron Meurer
- Introductions
- How did you get introduced to Python? – Chris
- What is Sympy and what kinds of problems does it aim to solve? – Chris
- How did the SymPy project get started? – Tobias
- How did you get started with the SymPy project? – Chris
- Are there any limits to the complexity of the equations SymPy can model and solve? – Chris
- How does SymPy compare to similar projects in other languages? – Tobias
- How does Sympy render results using such beautiful mathematical symbols when the inputs are simple ASCII? – Chris
- What are some of the challenges in creating documentation for a project like SymPy that is accessible to non-experts while still having the necessary information for professionals in the fields of mathematics? – Tobias
- Which fields of academia and business seem to be most heavily represented in the users of SymPy? – Tobias
- What are some of the uses of Sympy in education outside of the obvious like students checking their homework? – Chris
- How does SymPy integrate with the Jupyter Notebook? – Chris
- Is SymPy generally used more as an interactive mathematics environment or as a library integrated within a larger application? – Tobias
- What were the challenges moving SymPy from Python 2 to Python 3? – Chris
- Are there features of Python 3 that simplify your work on SymPy or that make it possible to add new features that would have been too difficult previously? – Tobias
- Were there any performance bottlenecks you needed to overcome in creating Sympy? – Chris
- What are some of the interesting design or implementation challenges you’ve found when creating and maintaining SymPy? – Chris
- Are there any new features or major updates to SymPy that are planned? – Tobias
- How is the evolution of SymPy managed from a feature perspective? Have there been any occasions in recent memory where a pull request had to be rejected because it didn’t fit with the vision for the project? – Tobias
- Which of the features of SymPy do you find yourself using most often? – Tobias
Picks
- Tobias
- Chris
- Aaron
Keep In Touch
Links
- Project Euler
- Richardson’s Theorem
- Doing Math With Python by Amit Saha (and Aaron’s book review)
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
Hosts & guests
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