greends-ipython

Introduction to Python 2025/2026

Masters in Data Science applied to agricultural and food sciences, environment, and forestry engineering.

Instructor: Manuel Campagnolo (mlc@isa.ulisboa.pt)

Teaching assistant: Mekaela Stevenson (mekaela@edu.ulisboa.pt)

Online resources for the course

• Required: CS50’s Introduction to Programming with Python: lectures (videos and notes), problems sets, shorts; The platform allows you to test your code at the CS50 codespace for the proposed problems (you need to have your own GitHub account to access the codespace).
• Python Programming course at PP.fi: same features as CS50 but to test your solutions to problems you are required to pass previous tests
• Learn Python with Scrimba, Olof Paulson: interactive lectures (videos), examples and exercises
• Introduction to Python (VScode): interactive step by step lectures and exercises, real-time quizzes.
• Basic concepts and features of the Python language and system: The Python Tutorial at python.org.
• Fenix webpage for the course (https://fenix.isa.ulisboa.pt/courses/intpy-846413499991952): administrative information and final grades
• Moodle (https://elearning.ulisboa.pt/course/view.php?id=11236): assignments; submissions; detailed grades and comments
• If you curious about the story of Python, check out this video. In this video, you’ll learn about the output of >>> import this and many other anecdotes about Python.

Course contents: the course will cover some topics in CS50P and PP.fi

CS50P	Contents	PP.fi	Contents
Lecture 0	Creating Code with Python; Functions; Bugs; Strings and Parameters; Formatting Strings; More on Strings; Integers or int; Readability Wins; Float Basics; More on Floats; Def; Returning Values	Part 1	Intro; I/O; More about variables; Arithmetic operations; Conditional statements
Lecture 1	Conditionals, if Statements, Control FlowModulo; Creating Our Own Parity Function; Pythonic; match	Part 2	Programming terminology; More conditionals; Combining conditions; Simple loops
Lecture 2	Loops; While Loops; For Loops; Improving with User Input; More About Lists; Length; Dictionaries, More on code modularity	Part 3	Loops with conditions; Working with strings; More loops; Defining functions
		Part 4	The Visual Studio Code editor, Python interpreter and built-in debugging tool; More functions; Lists; Definite iteration; Print statement formatting; More strings and lists
		Part 5	More lists; References; Dictionary; Tuple
Lecture 3	Exceptions, Runtime Errors, try, else, Creating a Function to Get an Integer, pass	Part 6	Reading files; Writing files; Handling errors; Local and global variables
Lecture 4	Libraries, Random, Statistics, Command-Line Arguments, slice, Packages, APIs, Making Your Own Libraries	Part 7	Modules; Randomness; Times and dates; Data processing; Creating your own modules; More Python features
Lecture 5	Unit Tests; assert; pytest; Testing Strings; Organizing Tests into Folders
Lecture 6	File I/O; open; with; CSV; Binary Files and PIL
Lecture 7	Regular Expressions; Case Sensitivity; Cleaning Up User Input; Extracting User Input
Lecture 8	Object-Oriented Programming; Classes; raise; Decorators; Class Methods; Static Methods; Inheritance; Inheritance and Exceptions; Operator Overloading	Part 8	Objects and methods; Classes and objects; Defining classes; Defining methods; More examples of classes
		Part 9	Objects and references; Objects as attributes; Encapsulation; Scope of methods; Class attributes; More examples with classes
		Part 10	Class hierarchies; Access modifiers; Object oriented programming techniques; Developing a larger application
Lecture 9	set; Global Variables; Constants; Type Hints; Docstrings; argparse; Unpacking; args and kwargs; map; List Comprehensions; filter; Dictionary Comprehensions; enumerate; Generators and Iterators	Part 11	List comprehensions; More comprehensions; Recursion; More recursion examples
		Part 12	Functions as arguments; Generators; Functional programming; Regular expressions

Class 1 (September 12, 2025): data types, variables, functions

1. The recommendation for this class is to code in the CS50 cloud environment (VScode). Two steps: 1. log in into your github account; 2. access your code space at https://cs50.dev/. This environment allows you to test automatically your scripts for the CS50 problem sets.
2. Some useful keyworks for the command line interface (CLI) in terminal:
   • code filename.py to create a new file
   • ls to list files in folder
   • cp filename newfilename to copy a file, e.g. cp ..\hello.py farewell.py (.. represents parent folder)
   • mv filename newfilename to rename or move file, e.g. my farewell.py goodbye.py or mv farewell.py .. (move one folder up)
   • rm filename to delete (remove) file
   • mkdir foldername to create new folder
   • cd foldername change directory, e.g. cd ..
   • rmdir foldername to delete folder
   • clear to clear terminal window
3. The REPL (interactive Read-Eval-Print-Loop) environment: see https://realpython.com/interacting-with-python/
4. All values in Python have a type. The primitive data types are: integer, float, string, Boolean, and None (see https://www.geeksforgeeks.org/python/primitive-data-types-vs-non-primitive-data-types-in-python/)
   • strings (str), variables, print (a function), parameters (e.g. end=), input, comments, formatted strings (f"..."), .strip(), .title (methods)
   • integers (int), operations for integers, casting (e.g. str to int)
   • floating point values (float), round, format floats (e.g. f"{z:.2f})
   • True, False, and, or, not
5. Functions, def, return
6. Suggested problems: CS50 Problem set 0