RTU_Programming_Languages_Python_Fall_2025

Python portion of Programming Languages Course at RTU Fall 2025

🐍 Python Programming – 5-Week Continuation Course (Revised)

This 5-week course introduces Python to students who have completed the C Programming course and already know C++ and/or Java.
It emphasizes translating structured C-style programming into idiomatic Python and prepares students for data-oriented and scripting tasks.
Each week includes one lecture (2×45 min) and one lab (2×45 min).

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📅 Weekly Overview

Week	Topic	Focus Keywords
1	Python Basics, Branching & Iteration	syntax, variables, input/output, if, for, while, basic functions
2	Functions, Strings & Iteration Patterns	parameters, return values, scope, string operations, slicing
3	Core Data Structures & Functional Tools	lists, tuples, sets, dicts, comprehensions, map, filter, zip, apply
4	File I/O, Modules & Exceptions	reading/writing files, modularity, error handling
5	Object-Oriented Python & Project Integration	classes, testing, integration with C parser project

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Week 1 – Python Basics, Branching & Iteration

Lecture

• Python syntax vs C syntax: indentation, comments, dynamic typing
• Variables, literals, and basic data types (int, float, bool, str)
• Input/output using input() and formatted print() (f-strings)
• Arithmetic and comparison operators
• Conditional statements (if, elif, else)
• Loops: for and while (no nested data structures yet)
• Basic function definition and calling (def, return)

Lab

• Convert C arithmetic and looping examples into Python
• Write a small calculator using user input and branching
• Create a simple menu-driven program using loops and functions
• Explore Python’s range() and indentation rules

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Week 2 – Functions, Strings & Iteration Patterns

Lecture

• Function parameters, return values, and default arguments
• Local vs global variables; scoping rules
• String basics and operations: concatenation, repetition, indexing, slicing
• String methods: split(), join(), strip(), replace(), find()
• Iterating through strings and sequences (for char in string)
• Reusable code style: docstrings and comments

Lab

• Implement text-based arithmetic analyzer using functions
• Write helper functions for counting characters and words
• Explore string slicing and iteration patterns
• Practice writing functions that transform and return text results

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Week 3 – Core Data Structures & Functional Tools

Lecture

• Lists, tuples, sets, and dictionaries: creation, indexing, iteration
• Mutability and immutability concepts
• List methods and slicing
• Dictionary key–value operations and nested structures
• Set operations: union, intersection, difference
• Comprehensions (list, dict, set)
• Functional programming tools: map(), filter(), zip(), apply() (from Pandas preview)
• When to use loops vs comprehensions vs functional style

Lab

• Build simple datasets (lists/dicts) and compute aggregates
• Practice comprehensions and transformations
• Implement frequency counter for arithmetic operators and operands
• Experiment with map() and filter() to process lists

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Week 4 – File I/O, Modules & Exceptions

Lecture

• Reading/writing text files with open() and with
• Basic CSV and JSON handling
• Organizing code into modules; import, from, as
• Exception handling: try, except, finally
• Reusing modular design concepts from C

Lab

• Read/write structured data from files
• Create helper module arithutils.py
• Handle division-by-zero and invalid inputs gracefully
• Log program output to file

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Week 5 – Object-Oriented Python & Project Integration

Lecture

• Classes and objects; defining __init__ and instance methods
• Encapsulation and inheritance basics
• Magic methods (__str__, __repr__)
• Unit testing with unittest and pytest
• Integrating C and Python components conceptually (data types, APIs)

Lab

• Implement Expression class with evaluation method
• Write and run unit tests
• Package project as a module with documentation
• Bonus: visualize expression tree recursively

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🧩 Course Outcomes

By the end of the course, students will be able to:

• Write readable, modular Python code using branching, iteration, and functions
• Work fluently with strings, lists, tuples, sets, and dictionaries
• Employ comprehensions and functional programming tools for data transformation
• Handle files and exceptions safely
• Organize code into reusable modules and classes
• Integrate and test Python programs effectively
• Transition smoothly from C-style logic to expressive, idiomatic Python