Keywords In Python with Example

In this article, I am going to discuss the List of Reserved Keywords in Python with example, Python keywords list, how many keywords in Python, use of keywords in Python, what are keywords in Python and many more. so keep reading the article till last.

What are Keywords In Python?

Keywords, also known as reserved words, are special words in Python that have predefined meanings and purposes. They serve as building blocks for creating Python programs. Unlike identifiers (variable or function names), you cannot use keywords as names for your variables or functions because they are reserved for specific language features and operations.

How Many Keywords in Python?

How Many Keywords Are There in Python?

Python, known for its simplicity and readability, maintains a relatively small and carefully chosen set of keywords compared to some other programming languages. These keywords are predefined and have specific meanings and purposes in Python’s syntax. Understanding how many keywords there are in Python is essential for programmers, as it gives insight into the core building blocks of the language.

Current Count of Keywords in Python

As of Python 3.10, there are 35 keywords in the Python programming language. These keywords are standardized and remain consistent across different Python implementations and versions. The list of keywords may evolve slightly with each new Python release to accommodate language enhancements, but the core set remains stable.

Here is a list of the 35 reserved keywords in Python along with brief explanations of their functionalities:

  1. False: Represents the Boolean value “false.”
  2. None: Represents the absence of a value or a null object.
  3. True: Represents the Boolean value “true.”
  4. and: Used for logical conjunction (logical “and”).
  5. as: Used for aliasing when importing modules.
  6. assert: Used for debugging and testing to check if a condition is true.
  7. async: Declares an asynchronous function or block.
  8. await: Used to pause and wait for the completion of an asynchronous task.
  9. break: Exits the current loop prematurely.
  10. class: Defines a class.
  11. continue: It Skips the rest of the current iteration and proceeds to the next one.
  12. def: Defines a function or method.
  13. del: Deletes an object or an item from a container.
  14. elif: Used in conditional statements (short for “else if”).
  15. else: Used in conditional statements when the if condition is not met.
  16. except: Handles exceptions in a try-except block.
  17. finally: Defines a block of code to be executed, regardless of whether an exception occurs.
  18. for: Creates a loop for iterating over sequences.
  19. from: Used in import statements to specify where to import from.
  20. global: Declares a variable as global within a function.
  21. if: Initiates a conditional statement.
  22. import: Imports modules or packages.
  23. in: Checks for membership in sequences (e.g., lists, tuples).
  24. is: Compares object identity (whether two objects are the same).
  25. lambda: Defines anonymous functions (lambda functions).
  26. nonlocal: Declares a variable as non-local within a nested function.
  27. not: Performs logical negation (logical “not”).
  28. or: Performs logical disjunction (logical “or”).
  29. pass: Acts as a placeholder for an empty code block.
  30. raise: Raises an exception explicitly.
  31. return: Exits a function and returns a value.
  32. try: Initiates error handling with a try-except block.
  33. while: Defines a loop with a conditional exit.
  34. with: Defines a context manager for resource management.
  35. yield: Used in generator functions to yield a value.

These reserved keywords are the foundation of Python’s syntax and are essential for creating structured and functional Python programs. Understanding their roles and functionalities is crucial for effective Python programming.

Types of Keywords in Python

Keywords in Python can be categorized into three main types, each serving a specific purpose and role within the language. Understanding these types is crucial for effectively using Python keywords in your code. Here’s an in-depth look at each type:

1. Reserved Keywords

Reserved keywords, also known as core keywords, are the fundamental building blocks of Python’s syntax. They have predefined meanings and play integral roles in creating the structure of Python programs. These keywords cannot be used as variable names or function names because they are reserved for specific language features and operations. Some examples of reserved keywords include:

  • if: Used to define conditional statements.
  • else: Used in conjunction with if to specify alternative actions.
  • while: Defines a loop that continues while a certain condition is true.
  • for: Used to iterate over a sequence (such as a list or string).
  • def: Used to define user-defined functions.
  • return: Used to exit a function and return a value.
  • class: Used to create a class, a blueprint for creating objects.
  • import: Used to include modules or libraries in your code.

These are just a few examples of reserved keywords. They form the backbone of Python programming by allowing you to create conditional statements, loops, functions, and more.

2. Built-in Keywords

Built-in keywords, also referred to as built-in functions, are words reserved for specific functions and operations provided by Python’s standard library. These keywords are not part of the core syntax like reserved keywords, but they are essential for various programming tasks. Examples of built-in keywords include:

  • print: Used to display output on the console.
  • len: Returns the length of a sequence (e.g., a list or string).
  • type: Returns the data type of an object.
  • range: Generates a sequence of numbers.

Built-in keywords simplify common programming tasks by providing pre-defined functions that you can readily use in your code.

3. Special Keywords

Special keywords in Python are unique words with specific meanings and usages. They are not as numerous as reserved and built-in keywords, but they are significant for specific purposes. Some examples of special keywords include:

  • True: Represents the boolean value “true.”
  • False: Represents the boolean value “false.”
  • None: It Represents a null object or absence of a value.

Special keywords are crucial in Python for working with boolean values and indicating the absence of data.

Keywords In Object Oriented Programming

Keywords in Python play a fundamental role in object-oriented programming (OOP), just as they do in other programming paradigms. They help define and control the behavior of classes, objects, and inheritance. Here’s how Python keywords are used in OOP:

1.. Class Keyword: The class keyword is used to define a new class, which is the blueprint for creating objects. It specifies the properties (attributes) and behaviors (methods) that the objects of the class will have. For example:

class Car:
    def __init__(self, make, model):
        self.make = make
        self.model = model
    def start_engine(self):
        print(f"The {self.make} {self.model}'s engine is running.")

In this example, we define a Car class with attributes make and model, and a method start_engine.

2. self Keyword: In Python, self is used within methods to refer to the instance of the class. It is the first parameter in all instance methods and is used to access and modify instance variables. For example:

class Car:
    def __init__(self, make, model):
        self.make = make
        self.model = model
    def start_engine(self):
        print(f"The {self.make} {self.model}'s engine is running.")

In the start_engine method, self is used to access the make and model attributes of the instance.

3. __init__ Method: The __init__ method is a special method used for initializing objects. It is automatically called when an object is created from a class and allows you to set initial values for object attributes. It is commonly used to perform setup tasks. For example:

class Car:
    def __init__(self, make, model):
        self.make = make
        self.model = model

Here, the __init__ method initializes the make and model attributes when a Car object is created.

4. Inheritance Keywords: Python provides keywords like class, super, and isinstance that are crucial for implementing inheritance in OOP. These keywords allow you to create subclasses, call methods of the parent class, and check the class hierarchy. For example:

class ElectricCar(Car):
    def __init__(self, make, model, battery_capacity):
        super().__init__(make, model)  # Calling the parent class's constructor
        self.battery_capacity = battery_capacity

Here, we create a ElectricCar subclass that inherits from the Car class using super() to call the parent class’s constructor.

5. classmethod and staticmethod : These are decorators in Python that allow you to define methods that are associated with the class rather than instances. They are often used in class-level operations and utility functions. For example:

class MathUtils:
    def add(a, b):
        return a + b

Here, the add method is defined as a static method and can be called on the class itself, not just on instances.


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