fundamental of python --- vivek singh shekawat

# Fundamentals of Python: A Comprehensive Guide

Python is a versatile and powerful programming language that has gained immense popularity in recent years. Known for its simplicity and readability, Python is an ideal choice for beginners and experienced programmers alike. This comprehensive guide covers the fundamentals of Python, providing a solid foundation for anyone looking to learn this dynamic language.

## Introduction to Python

### What is Python?

Python is a high-level, interpreted programming language designed by Guido van Rossum and first released in 1991. Its design philosophy emphasizes code readability and simplicity, making it an excellent language for beginners. Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming.

### Why Learn Python?

Python's popularity stems from its versatility and ease of use. Here are some key reasons to learn Python:

- **Simplicity**: Python's syntax is straightforward and easy to learn, making it accessible to beginners.
- **Versatility**: Python can be used for web development, data analysis, artificial intelligence, machine learning, automation, and more.
- **Community Support**: Python has a large and active community, providing a wealth of resources, libraries, and frameworks.
- **Job Market**: Python skills are in high demand, making it a valuable language to learn for career opportunities.

## Setting Up Python

### Installation

To start coding in Python, you need to install it on your computer. Python is available for various operating systems, including Windows, macOS, and Linux. Follow these steps to install Python:

1. **Download Python**: Visit the official Python website (https://www.python.org) and download the latest version of Python for your operating system.
2. **Run the Installer**: Follow the installation instructions specific to your operating system. Ensure you select the option to add Python to your system PATH during installation.
3. **Verify Installation**: Open a command prompt or terminal and type `python --version` to verify the installation. You should see the installed Python version displayed.

### Integrated Development Environment (IDE)

An Integrated Development Environment (IDE) enhances your coding experience by providing tools and features to write, debug, and manage code efficiently. Some popular Python IDEs include:

- **PyCharm**: A powerful IDE specifically for Python, offering advanced features for professional developers.
- **Visual Studio Code**: A lightweight, versatile code editor with excellent Python support through extensions.
- **Jupyter Notebook**: An interactive web-based environment, ideal for data analysis and visualization.

## Basic Syntax and Data Types

### Hello, World!

The traditional first program in any language is the "Hello, World!" program. In Python, this is straightforward:

```python
print("Hello, World!")
```

1. by Vivek Singh Shekhawat

2. Index Introduction to Python Features of Python Benefits of Python Python Syntax Python Comments Python Data Types Python Variables Python Casting Python Strings Python Booleans Python Operators Python List Python Dictionaries Python Tuples Python Sets If-Else If - Elif – else For loop While loop Break Statement Continue Statement Pass Statement

3. Introduction to Python Python is a high-level, interpreted programming language known for its simplicity and readability. It is versatile and can be used for web development, scientific computing, and data analysis. Python is also popular for its large standard library and active community support.

4. Python Syntax 1 Structure Python's syntax follows a clear and consistent structure, making it easy to write and understand code. 2 Indentation Indentation is crucial in Python and is used to denote blocks of code, ensuring readability and enforcing good programming practices. 3 Case Sensitivity Python is case-sensitive, meaning upper and lower case letters are treated differently, which affects variable names and function calls.

5. Python Comments 1 Explanation Comments in Python begin with the # symbol and are used to explain the code, provide context, and make notes for future reference . Comments are ignored by the Python interpreter . 2 Documentation Comments also play a vital role in generating documentation, helping other developers understand the code's functionality. 3 Best Practices Using comments effectively is considered a best practice and greatly enhances code maintenance and collaboration.

6. Python Data Types Fundamental Types Python supports fundamental data types such as integers, floating-point numbers, strings, and booleans. Derived Types Derived data types include lists, tuples, sets, dictionaries, and other custom-defined data structures.

7. Python Variables Naming Variable names in Python can contain letters, numbers, and underscores. They must start with a letter or an underscore. Variable names are case-sensitive. Assignment Variables in Python are created by assigning a value using the “=“ operator, and data types are inferred based on the assigned value. Scope and usage Understanding variable scope is essential to prevent naming conflicts and ensure proper variable access within different parts of the code. Variables are commonly used to store and manipulate data in Python programs. They allow for dynamic and flexible programming by allowing values to be stored and updated as needed. Variables can be used in mathematical operations, string manipulation, and more .

8. Python Casting Implicit Casting Python automatically converts data types in certain situations, such as when performing operations between different types. Explicit Casting Explicit casting allows the programmer to manually convert data from one type to another using built-in functions.

9. Python Strings 1 Manipulation Strings in Python can be manipulated using various built-in functions such as concatenation, slicing, and formatting. 2 Immutability Once a string is created, it cannot be modified. Any operation on a string creates a new string object. 3 Escape Characters Special characters can be inserted into strings using escape sequences, denoted by a backslash (\).

10. Python Booleans True Represents a true value or the result of a comparison that is true in Python. False Represents a false value or the result of a comparison that is false in Python. Program print(10 > 9) print(10 == 9) print(10 < 9) Output: True False False

11. Python Operators Arithmetic Comparison Logical Assignment Membership Identity Bitwise Identity Operators used to compare the objects is  Returns True if both variables are the same object x is y is not Returns True if both variables are not the same object x is not y

12. in  Returns True if a sequence with the specified value is present in the object x in y not in Returns True if a sequence with the specified value is not present in the object x not in y Membership Operator Membership operators are used to test if a sequence is presented in an object Operator Name Description Example &  AND Sets each bit to 1 if both bits are 1 x & y | OR Sets each bit to 1 if one of two bits is 1 x | y ^ XOR Sets each bit to 1 if only one of two bits is 1 x ^ y ~ NOT Inverts all the bits ~x << Zero fill left shift Shift left x << 2 >> Signed right shift Shift right x >> 2 Bitwise Operator Bitwise operators are used to compare (binary) numbers

13. Operators Precedence

14. Python Lists Python lists are ordered, mutable, and allow duplicate elements. They are a versatile data type, often used to store and manipulate collections of data. Lists are defined by square brackets and can contain any data type.

15. Creating Lists Simple Syntax Lists are created by placing a comma-separated sequence of elements in square brackets. Concatenating Lists New lists can be created by adding two or more lists together using the + operator. Using List Comprehension It provides an elegant way to create lists based on existing lists.

16. Accessing List Items 1 Indexing Access elements by referring to the index number. The index starts at 0. 2 Negative Indexing Access elements from the end of the list using negative indexing. 3 Slicing Get a specific segment of a list using slicing. It includes a start and stop index.

17. Modifying List Items Assigning Values Modify a specific item by referring to its index. Appending Items Add new items at the end of the list using the append() method. Extending Lists Add the elements of another list to the current list using the extend() method.

18. Join Lists 1 Using the extend() method Add the elements of one list to another with the extend() method. 2 Using the + operator Combine two lists by simply using the + operator.

19. # Define a list my_list = [1, 2, 3, 4, 5] # Indexing: Modify the value at index 2 index = 2 my_list [index] = 10 # Appending: Append an element to the list element_to_append = 6 my_list.append ( element_to_append ) # Extending: Add elements from another list to the current list list_to_extend = [7, 8, 9] my_list.extend ( list_to_extend ) # Print the modified list print("Modified List:", my_list ) Output : Modified List: [1, 2, 10, 4, 5, 6, 7, 8, 9]

20. Slicing Lists 3 Use of Start and Stop Specify the start and stop index to extract a part of a list. 2 Step in Slicing Use a step to return every nth item within a specified range.

21. Adding Items to a List Using append() Add items to the end of the list using the append() method. Using insert() Insert an element at a specified position using the insert() method.

22. Removing Items from a List Method Description remove() Remove the first occurrence of a specified value. pop() Remove the item at the given position and return it. clear() Remove all the items from the list.

23. List Methods 1 Common Methods Explore methods like sort(), reverse(), and count() to manipulate lists. 2 Copying Lists Learn methods for creating a shallow or deep copy of a list.

24. # Define an empty list my_list = [] # Append elements to the list my_list.append (1) my_list.append (2) my_list.append (3) # List after appending elements: [1, 2, 3] # Insert an element at a specific index my_list.insert (1, 4) # List after inserting element: [1, 4, 2, 3] # Remove an element from the list my_list.remove (2) # List after removing element: [1, 4, 3] # Pop an element from the list popped_element = my_list.pop () # Popped element: 3 # List after popping: [1, 4] # Pop an element at a specific index popped_element_at_index = my_list.pop (1) # Popped element at index 1: 4 # List after popping at index 1: [1] # Get the index of an element index = my_list.index (1) # Index of element 1: 0 # Extend the list with another list other_list = [5, 6, 7] my_list.extend( other_list ) # List after extending with another list: [1, 5, 6, 7] # Sort the list my_list.sort () # List after sorting: [1, 5, 6, 7] # Reverse the list my_list.reverse () # List after reversing: [7, 6, 5, 1] # Access elements by index element_at_index_2 = my_list [2] # Element at index 2: 5 # Slicing sliced_list = my_list [1:4] # Sliced list: [6, 5, 1] # Length of the list length_of_list = len ( my_list ) # Length of the list: 4 # Count occurrences of an element count_of_5 = my_list.count (5) # Count of element 5: 1 # Clear the list my_list.clear () # List after clearing: []

25. # Define a tuple my_tuple = (1, 2, 3) # Print the tuple print("Tuple:", my_tuple ) # Tuple: (1, 2, 3) # Access elements by index element_at_index_1 = my_tuple [1] # Element at index 1: 2 # Slicing sliced_tuple = my_tuple [0:2] # Sliced tuple: (1, 2) # Length of the tuple length_of_tuple = len ( my_tuple ) # Length of the tuple: 3 # Count occurrences of an element count_of_2 = my_tuple.count (2) # Count of element 2: 1 # Get the index of an element index_of_3 = my_tuple.index (3) # Index of element 3: 2

26. Python Dictionaries

27. # Define an empty dictionary my_dict = {} # Add key-value pairs to the dictionary my_dict ['a'] = 1 my_dict ['b'] = 2 my_dict ['c'] = 3 # Print the dictionary print("Dictionary after adding key-value pairs:", my_dict ) # Dictionary after adding key-value pairs: {'a': 1, 'b': 2, 'c': 3} # Access value by key value_of_a = my_dict ['a'] # Value of key 'a': 1 # Modify value by key my_dict ['b'] = 5 # Dictionary after modifying value: {'a': 1, 'b': 5, 'c': 3} # Add new key-value pair my_dict ['d'] = 4 # Dictionary after adding new key-value pair: {'a': 1, 'b': 5, 'c': 3, 'd': 4} # Remove key-value pair removed_value = my_dict.pop ('b') # Removed value: 5 # Dictionary after removing key-value pair: {'a': 1, 'c': 3, 'd': 4} # Get keys keys = my_dict.keys () # Keys: dict_keys (['a', 'c', 'd']) # Get values values = my_dict.values () # Values: dict_values ([1, 3, 4]) # Check if key exists is_key_exists = 'b' in my_dict # Is 'b' in dictionary: False # Clear the dictionary my_dict.clear () # Dictionary after clearing: {}

28. If – else If-else statements in Python are used to make decisions based on certain conditions. They allow the program to execute different code blocks based on the evaluation of a condition. # Define a variable x = 10 # Check if x is greater than 5 if x > 5: print("x is greater than 5") else: print("x is not greater than 5") Output : x is greater than 5

29. If - elif – else Elif statements in Python are used to add additional conditions to if-else statements. They allow the program to check for multiple conditions and execute different code blocks based on the first condition that evaluates to true. # Define a variable x = 10 # Check conditions using if- elif -else statements if x > 5: print("x is greater than 5") elif x == 5: print("x is equal to 5") else: print("x is less than 5") Output : x is greater than 5

30. Flow Chart of for loop

31. Flow Chart of Nested loop

32. Flow Chart of While loop

33. Feature while Loop for Loop Purpose Executes a block of code repeatedly as long as a condition is true Iterates over a sequence and executes a block of code for each element Syntax ```python ```python while condition: for item in sequence: # Code block to be executed # Code block to be executed ``` ``` Iteration Condition Condition is evaluated at the beginning of each iteration Iteration over a sequence controls the loop Loop Control Manual control required to break out of the loop Automatically iterates over each element in the sequence Common Use Cases When the number of iterations is not known beforehand When iterating over a sequence or collection of items Examples ```python ```python x = 0 fruits = ["apple", "banana", "cherry"] while x < 5: for fruit in fruits: print(x) print(fruit) x += 1 ``` ``` Output apple 1 banana 2 cherry 3 4 Difference between While loop and For loop

34. Break Statement The break statement terminates the loop immediately when it's encountered. Program: for i in range(5): if i == 3: break print( i ) Output: 1 2

35. Continue Statement The continue statement skips the current iteration of the loop and the control flow of the program goes to the next iteration. Program : for i in range(5): if i == 3: continue print( i ) Output: 1 2 4

36. P ass Statement The pass statement is used as a placeholder for future code. When the pass statement is executed, nothing happens, but you avoid getting an error when empty code is not allowed. Program : n = 10 for i in range(n): # pass can be used as placeholder # when code is to added later pass Output: No output