CSCSEC151: Python Programming (Theory Notes)

Unit 1: Introduction

Basic Elements

Python code is built from these basic elements:

• Python Character Set: The set of valid characters, including letters (A-Z, a-z), digits (0-9), and special symbols.
• Python Tokens: The smallest individual unit in a program.
  • Keyword: Reserved words with special meanings (e.g., if, for, def, True).
  • Identifier: Names given to variables, functions, etc. (e.g., my_var, age).
  • Literal: Constant data values (e.g., 10, "Hello", 3.14).
  • Operator: Symbols that perform operations (e.g., +, =, >).
  • Punctuator: Symbols used to structure the code (e.g., (, ), #, :).

Variables, L-value, R-value, and Comments

• Variables: A named location in memory used to store data. You create one by assigning a value: age = 25.
• l-value and r-value:
  • l-value (Locator value): Refers to a memory location. An identifier that can be on the *left-hand side* of an assignment (e.g., the age in age = 25).
  • r-value (Read value): Refers to a data value. An expression that can be on the *right-hand side* of an assignment (e.g., the 25 in age = 25, or age + 1).
• Comments: Text ignored by the interpreter, used to explain code. In Python, single-line comments start with #.

Data Types

Python is dynamically-typed, meaning you don't need to declare a variable's type.

• Immutable: Cannot be changed after creation (e.g., numbers, strings, tuples).
• Mutable: Can be changed after creation (e.g., lists, dictionaries, sets).

Operators

• Arithmetic: +, -, *, / (float division), // (floor division), % (modulus), ** (exponent).
• Relational: ==, !=, >, <, >=, <=.
• Logical: and, or, not.
• Assignment: =
• Augmented Assignment: +=, -=, *=, etc.
• Identity: is, is not (Checks if two variables point to the *same* object in memory).
• Membership: in, not in (Checks if a value is present in a sequence).

Expressions, Type Conversion, and I/O

• Expression: A combination of values, variables, and operators that evaluates to a single value (e.g., x + 5).
• Statement: A complete instruction that Python can execute (e.g., x = 5).
• Type Conversion (Casting):
  • Implicit: Python automatically converts types (e.g., int + float becomes float).
  • Explicit: You force a type change using functions like int(), float(), str().
• Input/Output:
  • input("Prompt: "): Accepts data from the console. Returns a string.
  • print(...): Displays output to the console.

   name = input("Enter your name: ") age_str = input("Enter your age: ") age = int(age_str) # Explicit conversion print("Hello,", name, "you are", age, "years old.") 

Unit 2: Flow of Control & Strings

Flow of Control

• Indentation: Python uses indentation (spaces or tabs) to define code blocks, not curly braces {}. This is mandatory.
• Sequential: Code executes from top to bottom, one line at a time.
• Conditional (Selection):
  • if: Executes a block if a condition is true.
  • if-else: Executes one block if true, another if false.
  • if-elif-else: A chain of conditions.

     if x > 10: print("Large") elif x > 5: print("Medium") else: print("Small") 

• Iterative (Loops):
  • for loop: Iterates over a sequence (like a list, string, or range()).

     for i in range(5): # i will be 0, 1, 2, 3, 4 print(i) 

  • while loop: Repeats a block as long as a condition is true.

     count = 0 while count < 5: print(count) count += 1 

  • break: Exits the loop immediately.
  • continue: Skips the rest of the current iteration and moves to the next.

Strings

• Introduction: An immutable sequence of characters.
• Operations:
  • + (Concatenation): "Hello" + " " + "World"
  • * (Repetition): "Go" * 3 (produces "GoGoGo")
  • in (Membership): "H" in "Hello" (produces True)
  • Slicing: s[start:end:step]. Very powerful.

     s = "Python" s[0] # 'P' s[1:4] # 'yth' s[:3] # 'Pyt' s[-1] # 'n' (last character) s[::-1] # 'nohtyP' (reverses the string) 

• Traversing: Use a for loop: for char in my_string: print(char)
• Built-in Functions/Methods: len(), .upper(), .lower(), .find(), .split(), .strip().

Unit 3: Lists, Tuples, Sets, Dictionaries & Modules

Lists

• Introduction: A mutable (changeable), ordered sequence of elements.
• Indexing/Slicing: Works just like strings.
• Operations: +, *, in, len().
• Methods: .append(item), .insert(index, item), .pop(index), .remove(item), .sort(), .reverse().
• Nested Lists: Lists within lists (e.g., matrix = [[1,2],[3,4]]).

Tuples

• Introduction: An immutable (unchangeable), ordered sequence. Defined with parentheses ().
• Use Case: Use when you want to ensure data is not accidentally changed. They are faster than lists.
• Operations: Indexing, slicing, concatenation, repetition, len().

Set

• Introduction: A mutable, unordered collection of unique elements. Defined with curly braces {} (or set() for an empty set).
• Adding/Removing: .add(item), .remove(item).
• Set Operations:
  • | (Union): set1 | set2
  • & (Intersection): set1 & set2
  • - (Difference): set1 - set2

Dictionary

• Introduction: A mutable, unordered collection of key-value pairs. Defined with {}.
• Accessing: my_dict['key']. Accessing a non-existent key causes an error.
• Mutability:
  • Add/Modify: my_dict['new_key'] = "new_value"
• Traversing:

   for key in my_dict: print(key, my_dict[key]) for key, value in my_dict.items(): print(key, value) 

• Methods: .keys(), .values(), .items(), .get(key) (safe access, returns None if key not found).

Python Modules

• A module is a Python file (.py) containing functions and variables.
• import : Imports the whole module. You access members with module.member.

   import math print(math.pi) 

• from import : Imports a specific member into your namespace.

   from math import pi print(pi) 

Unit 4: Functions & Modules

Python Functions

• Definition: A reusable block of code, defined with the def keyword.

   def greet(name): print("Hello,", name) 

• Call: You execute the function by writing its name: greet("Alice").
• Arguments: Data passed into a function.
  • Default arguments: def greet(name="Guest")
  • Keyword arguments: greet(name="Alice")
• Pass by Object Reference:
  • If you pass an immutable object (like a string, int), the function cannot change the original.
  • If you pass a mutable object (like a list), the function *can* change the original.
• Recursion: A function that calls itself. Must have a base case to stop.
  • Advantages: Elegant solution for some problems (e.g., factorial, tree traversal).
  • Disadvantages: Can be slow and consume a lot of memory (risk of "stack overflow").
• Scope and Lifetime:
  • Local Scope: Variables defined inside a function. Only exist while the function is running.
  • Global Scope: Variables defined outside all functions. Accessible everywhere.

Python Modules and Packages

• Module: A single .py file.
• Package: A collection of modules in a directory. The directory must contain a file named __init__.py (can be empty).

Unit 5: Files, Exceptions, and Plotting

Python Files

Used to read from and write to files on your disk.

Best Practice (with open): This automatically closes the file for you.

 # Writing to a file (overwrites) with open("output.txt", "w") as f: f.write("Hello, file!\n") f.write("This is a new line.\n") # Reading from a file with open("output.txt", "r") as f: content = f.read()print(content) 

Modes: "r" (read), "w" (write, overwrites), "a" (append), "r+" (read/write).

Exception Handling

How to handle errors gracefully without crashing the program.

• try: The block of code that *might* cause an error.
• except: The block that runs *if* an error occurs. You can catch specific exceptions (e.g., ZeroDivisionError, FileNotFoundError).
• finally: This block runs *no matter what* (whether an error occurred or not). Used for cleanup.

 try: x = 10 / 0 except ZeroDivisionError: print("You cannot divide by zero!") finally: print("This always runs.") 

• User-defined Exception: You can create your own exceptions by inheriting from the Exception class.

Python Graph Plotting using Matplotlib

Matplotlib is a powerful library for creating static, animated, and interactive visualizations.

Installation: You must first install it: pip install matplotlib

Basic Example (Line Plot):

 import matplotlib.pyplot as plt x = [1, 2, 3, 4] y = [2, 4, 1, 5] plt.plot(x, y) # Create the line plot plt.title("Simple Line Plot") plt.xlabel("X-Axis") plt.ylabel("Y-Axis") plt.show() # Display the plot 

Other common plots include plt.bar() (bar chart), plt.hist() (histogram), and plt.pie() (pie chart).