name[::-1]<\/strong> reverses a string.<\/li>\n<\/ul>\n\n\n\n19. Iteration<\/h3>\n\n\n\n
Iteration is the process of going through items in a collection one by one. Every time you use a for loop on a list or string, you are iterating over it.<\/p>\n\n\n\n
20. Mutability<\/h3>\n\n\n\n
Mutability describes whether an object can be changed after it is created. Lists, dictionaries, and sets are mutable. Strings, tuples, and integers are immutable. This distinction matters for performance and for avoiding unexpected bugs.<\/p>\n\n\n\n
Section 3: Control Flow (Terms 21\u201329)<\/h2>\n\n\n\n
These python terms control how your code makes decisions and repeats actions. They are the logic engine of every program you write.<\/p>\n\n\n\n
21. Conditional Statement<\/h3>\n\n\n\n
A conditional statement runs code only when a specific condition is true. Python uses if<\/strong>, elif<\/strong>, and else<\/strong>.<\/p>\n\n\n\n\n- Example:<\/strong> if score >= 50: print(“Pass”) else: print(“Fail”)<\/strong><\/li>\n<\/ul>\n\n\n\n
22. For Loop<\/h3>\n\n\n\n
A for loop repeats a block of code for each item in a sequence. It runs a known number of times.<\/p>\n\n\n\n
\n- Example:<\/strong> for fruit in fruits: print(fruit)<\/strong> prints every item in the list.<\/li>\n<\/ul>\n\n\n\n
23. While Loop<\/h3>\n\n\n\n
A while loop repeats a block of code as long as a condition stays true. It runs an unknown number of times until the condition becomes false.<\/p>\n\n\n\n
\n- Example:<\/strong> while count < 10: count += 1<\/strong><\/li>\n<\/ul>\n\n\n\n
24. Break<\/h3>\n\n\n\n
Break immediately exits a loop, even if the loop condition is still true. Use it when you have found what you were looking for.<\/p>\n\n\n\n
\n- Example:<\/strong> if item == “mango”: break<\/strong><\/li>\n<\/ul>\n\n\n\n
25. Continue<\/h3>\n\n\n\n
Continue skips the rest of the current iteration and jumps straight to the next one. The loop does not exit \u2014 it just skips one round.<\/p>\n\n\n\n
\n- Example:<\/strong> if item == “banana”: continue<\/strong><\/li>\n<\/ul>\n\n\n\n
26. List Comprehension<\/h3>\n\n\n\n
List comprehension is a concise, readable way to create a new list in a single line of code.<\/p>\n\n\n\n
\n- Example:<\/strong> squares = [x<\/strong>2 for x in range(10)]** creates a list of squares from 0 to 81 in one line.<\/li>\n<\/ul>\n\n\n\n
27. Range<\/h3>\n\n\n\n
Range generates a sequence of numbers. Commonly used inside for loops to repeat an action a set number of times.<\/p>\n\n\n\n
\n- Example:<\/strong> range(1, 11)<\/strong> produces 1 to 10. range(0, 10, 2)<\/strong> produces 0, 2, 4, 6, 8.<\/li>\n<\/ul>\n\n\n\n
28. Exception<\/h3>\n\n\n\n
An exception is an error that occurs at runtime \u2014 when your program is already running. Common exceptions include ZeroDivisionError<\/strong>, TypeError<\/strong>, ValueError<\/strong>, and FileNotFoundError<\/strong>.<\/p>\n\n\n\n29. Try\/Except<\/h3>\n\n\n\n
A try\/except block catches exceptions and handles them gracefully so your program does not crash.<\/p>\n\n\n\n
\n- Example:<\/strong> try: result = 10 \/ 0 except ZeroDivisionError: print(“Cannot divide by zero”)<\/strong><\/li>\n<\/ul>\n\n\n\n
Section 4: Functions (Terms 30\u201338)<\/h2>\n\n\n\n
Functions are what make your code reusable and clean. These python terms are the foundation of structured, professional programming.<\/p>\n\n\n\n
30. Function<\/h3>\n\n\n\n
A function is a named, reusable block of code that performs a specific task. Defined with the def<\/strong> keyword. Call it by name whenever you need it.<\/p>\n\n\n\n\n- Example:<\/strong> def greet(name): return “Hello ” + name<\/strong><\/li>\n<\/ul>\n\n\n\n
31. Parameter<\/h3>\n\n\n\n
A parameter is the variable listed in a function’s definition. It acts as a placeholder for the value that will be passed in when the function is called.<\/p>\n\n\n\n
\n- Example:<\/strong> In def greet(name):<\/strong>, name<\/strong> is the parameter.<\/li>\n<\/ul>\n\n\n\n
32. Argument<\/h3>\n\n\n\n
An argument is the actual value you pass to a function when you call it. It fills in the parameter.<\/p>\n\n\n\n
\n- Example:<\/strong> In greet(“Riya”)<\/strong>, “Riya” is the argument.<\/li>\n<\/ul>\n\n\n\n
33. Return<\/h3>\n\n\n\n
Return sends a value back from a function to wherever it was called. A function without a return statement gives back None<\/strong> by default.<\/p>\n\n\n\n\n- Example:<\/strong> return total<\/strong><\/li>\n<\/ul>\n\n\n\n
34. Lambda Function<\/h3>\n\n\n\n
A lambda is a small anonymous function written in a single line. Used when you need a quick function without formally defining one.<\/p>\n\n\n\n
\n- Syntax:<\/strong> lambda arguments: expression<\/strong><\/li>\n\n\n\n
- Example:<\/strong> double = lambda x: x * 2<\/strong> \u2014 double(5)<\/strong> returns 10.<\/li>\n<\/ul>\n\n\n\n
35. Scope<\/h3>\n\n\n\n
Scope defines where a variable can be accessed in your program. A variable created inside a function has local scope and cannot be used outside it. A variable created at the top level has global scope.<\/p>\n\n\n\n
36. Recursion<\/h3>\n\n\n\n
Recursion is when a function calls itself to solve a problem by breaking it into smaller versions of the same problem. Every recursive function needs a base case to stop itself.<\/p>\n\n\n\n
\n- Example:<\/strong> A factorial function calls itself repeatedly until it reaches 1.<\/li>\n<\/ul>\n\n\n\n
37. Decorator<\/h3>\n\n\n\n
A decorator is a function that wraps another function to add extra behaviour without changing its original code. Written with the @<\/strong> symbol above the function definition.<\/p>\n\n\n\n\n- Example:<\/strong> @login_required<\/strong> ensures only logged-in users can call a function.<\/li>\n<\/ul>\n\n\n\n
38. Generator<\/h3>\n\n\n\n
A generator is a function that uses yield<\/strong> instead of return<\/strong>. It produces values one at a time instead of all at once, which makes it memory-efficient for large datasets.<\/p>\n\n\n\n\n- Example:<\/strong> def count_up(n): for i in range(n): yield i<\/strong><\/li>\n<\/ul>\n\n\n\n
Section 5: OOP (Terms 39\u201346)<\/h2>\n\n\n\n
Object-Oriented Programming is how large Python applications are structured. These python terms are heavily tested in interviews and used daily by professional developers.<\/p>\n\n\n\n
39. Class<\/h3>\n\n\n\n
A class is a blueprint for creating objects. It defines what attributes (data) and methods (behaviour) every object created from it will have.<\/p>\n\n\n\n
\n- Example:<\/strong> class Car:<\/strong> defines a Car blueprint.<\/li>\n<\/ul>\n\n\n\n
40. Object<\/h3>\n\n\n\n
An object is an instance of a class \u2014 one specific version built from the blueprint with its own data.<\/p>\n\n\n\n
\n- Example:<\/strong> my_car = Car()<\/strong> creates a Car object.<\/li>\n<\/ul>\n\n\n\n
41. Method<\/h3>\n\n\n\n
A method is a function defined inside a class. It always takes self<\/strong> as its first parameter, which refers to the object calling it.<\/p>\n\n\n\n\n- Example:<\/strong> def drive(self): print(“Driving”)<\/strong> is a method of the Car class.<\/li>\n<\/ul>\n\n\n\n
42. Attribute<\/h3>\n\n\n\n
An attribute is a variable that belongs to a class or its objects. It stores data about the object.<\/p>\n\n\n\n
\n- Example:<\/strong> self.brand = “Toyota”<\/strong> sets the brand attribute of a Car object.<\/li>\n<\/ul>\n\n\n\n
43. Constructor (init<\/strong>)<\/h3>\n\n\n\nThe constructor is a special method named init<\/strong> that runs automatically every time a new object is created. It sets up the object’s initial attributes.<\/p>\n\n\n\n\n- Example:<\/strong> def init(self, brand): self.brand = brand<\/strong><\/li>\n<\/ul>\n\n\n\n
44. Inheritance<\/h3>\n\n\n\n
Inheritance lets one class take on all the attributes and methods of another class. The child class can also add its own new methods or override existing ones.<\/p>\n\n\n\n
\n- Example:<\/strong> class ElectricCar(Car):<\/strong> inherits everything from Car.<\/li>\n<\/ul>\n\n\n\n
45. Encapsulation<\/h3>\n\n\n\n
Encapsulation means bundling an object’s data and methods together inside a class and restricting direct access to internal data. In Python, prefix an attribute with double underscores to make it private.<\/p>\n\n\n\n
\n- Example:<\/strong> self.__password = “secret”<\/strong><\/li>\n<\/ul>\n\n\n\n
46. Polymorphism<\/h3>\n\n\n\n
Polymorphism means different classes can share the same method name but behave differently when that method is called. It lets you write flexible code that works across multiple object types.<\/p>\n\n\n\n
\n- Example:<\/strong> A speak()<\/strong> method on a Dog<\/strong> class returns “Woof” while the same speak()<\/strong> method on a Cat<\/strong> class returns “Meow”.<\/li>\n<\/ul>\n\n\n\n
Section 6: Ecosystem (Terms 47\u201350)<\/h2>\n\n\n\n
These four python terms describe how Python code is organised and shared. Understanding them is essential for working on any real project.<\/p>\n\n\n\n
47. Module<\/h3>\n\n\n\n
A module is a single Python file (.py) that contains functions, classes, or variables you can import and reuse in other files. Python has many built-in modules like math<\/strong>, os<\/strong>, and datetime<\/strong>.<\/p>\n\n\n\n