Introduction to Python

Lecture 1 · 2026-03-03

The toolkit starting point for the course: managing Python environments and dependencies with uv, reviewing core Python syntax (containers, functions, list comprehensions), and introducing the scientific-computing ecosystem—NumPy arrays, indexing, and broadcasting, together with plotting in Matplotlib. Two supplementary handouts accompany the lecture: solving the dynamic-programming problem of the Brock–Mirman growth model by guess-and-verify, and vectorized programming together with its limits.

Materials

Readings

  • Python Software Foundation, Official Python 3 documentation, https://docs.python.org/3/.
  • Harris et al. (2020), “Array programming with NumPy,” Nature 585, 357–362.
  • Virtanen et al. (2020), “SciPy 1.0,” Nature Methods 17, 261–272.
  • McKinney (2010), “Data Structures for Statistical Computing in Python,” SciPy 2010.
  • Hunter (2007), “Matplotlib: A 2D Graphics Environment,” CiSE 9(3), 90–95.