Scientific Computing with Python
Obliczenia naukowe w języku Python

Please label the titles of emails from the course by [SCPy]:
[SCPy] Homework 1
It will help me to sort messages.
Please send emails (with the link to your repository) every week, after completion of your homework, before next classes.

WEEKS

• Week 1 - Introduction to Python
• Week 2 - Types and operations
• Week 3 - Statements
• Week 4 - Functions
• Week 5 - Modules
• Week 6 - Classes
• Week 7 - Exceptions (itertools)
• Week 8 - Decorators and metaclasses (numpy)
• Week 9 - Plotting with Python (matplotlib)
• Week 10 - Virtual environments (pandas)
• Week 11 - Numerical computing (scipy)
• Week 12 - Testing Python programs (networkx)
• Week 13 - Processing files (PIL)
• Week 14 - Monte Carlo simulations (numba)
• Week 15 - Simple GUI (tkinter)

REFERENCES

• Python Website https://www.python.org/, The Python Standard Library, The Python Language Reference.
• Mark Lutz, Learning Python, 5th Edition.
  Mark Lutz, Python. Wprowadzenie, Helion 2020.
• Hans Petter Langtangen, Python Scripting for Computational Science.
• Micha Gorelick, Ian Ozsvald, High Performace Python: Practical Performant Programming for Humans.
  Micha Gorelick, Ian Ozsvald, Python. Programuj szybko i wydajnie, Helion 2015.
• Robert Johansson, Numerical Python: Scientific Computing and Data Science Applications with NumPy, SciPy and Matplotlib, Apress 2019.
  Robert Johansson, Matematyczny Python. Obliczenia naukowe i analiza danych z użyciem NumPy, SciPy i Matplotlib, Helion 2021.
• Mark Lutz, Programming Python, 3rd Edition, O'Reilly 2006.
• Felix Zumstein, Python for Excel: A Modern Environment for Automation and Data Analysis. 2nd Edition, O'Reilly Media 2026.
  Felix Zumstein, Python i Excel. Nowoczesne środowisko do automatyzacji i analizy danych, Helion 2022, 2025.