Python for Engineers and Scientists

Find out how practicing scientists, engineers, and students of science and engineering can use Python to help make their work more efficient.

Introduction

• Become a better engineer or scientist with Python
• What you should know

1. Installation

• macOS installation
• Windows and Linux installation
• Working with Jupyter notebooks
• Using the exercise files

2. Make It Fast

• Making Python code fast
• Introduction to NumPy arrays
• Matrix operations with NumPy
• Linear algebra and sparse matrices with NumPy and SciPy
• Code generation with Numba and Cython
• Wrapping legacy code with Cython, CFFI, and F2PY
• Challenge: Diffusion equation
• Solution: Diffusion equation

3. Make It Right

• Making Python code right
• Symbolic computation with SymPy
• Units, constants, timescales, and more with Astropy
• Differential equations with SciPy
• Interpolation and optimization with SciPy
• Debugging with ipdb
• Challenge: Planetary conjunctions
• Solution: Planetary conjunctions

4. Make It Easy

• Making Python code easy
• Web resources with requests and JSON
• Tables with pandas
• Scientific datasets with HDF5
• Automation with Python scripts
• Scientific workflows with Snakemake
• Challenge: Perfect numbers
• Solution: Perfect numbers

Conclusion

• Next steps