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Python Programming Language Tutorial Part -1

What is Python?

Python is a high-level, interpreted, and general-purpose programming language. Created in the late 1980s by Guido van Rossum, Python has since become one of the most popular programming languages in the world. Python’s popularity is due in part to its simplicity, ease of use, and wide range of applications.

Python is an interpreted language, which means that code is executed line by line by an interpreter. This makes Python a good choice for rapid application development and prototyping. Python is also a high-level language, which means that it is designed to be easily readable and understandable by humans. Python code is often said to be “executable pseudo-code” because of its readability.

Python’s versatility is another reason for its popularity. Python can be used for web development, data analysis, machine learning, scientific computing, game development, and much more. Python has a vast and active community that creates and maintains libraries and frameworks for various applications. Some popular libraries and frameworks for Python include NumPy, Pandas, Django, Flask, and TensorFlow.

Overall, Python’s simplicity, ease of use, and wide range of applications make it a popular choice for both beginners and experienced programmers alike.

Advantages and Disadvantages of Python

Python is a popular programming language that has many advantages and some disadvantages. Here are some of the main advantages and disadvantages of using Python:

Advantages of Python:

  1. Easy to Learn and Read: Python has a simple and intuitive syntax that is easy to learn and read. This makes it an excellent choice for beginners and experienced programmers alike.
  2. Large Community and Support: Python has a large and active community that creates and maintains libraries, frameworks, and tools for various applications. This means that you can easily find solutions to problems or get help when you need it.
  3. Versatile: Python is a versatile language that can be used for a wide range of applications, including web development, data analysis, machine learning, scientific computing, game development, and much more.
  4. Rapid Development: Python’s simplicity and ease of use make it an excellent choice for rapid application development and prototyping.
  5. Cross-Platform: Python is a cross-platform language that can run on Windows, macOS, and Linux. This makes it easy to develop and deploy applications across multiple platforms.

Disadvantages of Python:

  1. Slower Speed: Python is an interpreted language, which means that it is slower than compiled languages like C or Java. This can be a disadvantage for applications that require high performance or real-time processing.
  2. Not Ideal for Mobile Computing: Python is not an ideal choice for mobile computing applications, as it is not as efficient as native languages like Java or Swift.
  3. Weak in Mobile Computing: Python is weak in mobile computing because there is no standard Python distribution for mobile devices, and mobile operating systems like iOS and Android do not support Python natively.
  4. Less Secure: Python’s dynamic nature and the use of third-party libraries and frameworks can make it less secure than compiled languages that have built-in security features.
  5. Database Access: Python’s database access library is not as powerful as other languages like Java, which can make it more challenging to work with large or complex databases.

Overall, Python’s advantages, such as its simplicity, versatility, and large community, make it a popular choice for programming, while its disadvantages, such as its slower speed and weaker mobile computing, should be taken into consideration when selecting a language for a specific application.

Syntax of Python

The syntax of Python is straightforward and easy to understand. Python uses indentation to define code blocks instead of curly braces, making the code more readable. Here is an example of the basic syntax of Python:

# This is a comment
# Variables
x = 5
y = "Hello, World!"

# Print statements
print(x)
print(y)

# Conditional statements
if x > 3:
print("x is greater than 3")
else:
print("x is less than or equal to 3")

# Loop statements
for i in range(5):
print(i)

# Functions
def add_numbers(a, b):
return a + b

result = add_numbers(3, 5)
print(result)
In Python, a hashtag (#) is used to add comments to the code. Comments are ignored by the interpreter and are used to add notes or explanations to the code.

Variables in Python are created using the equals sign (=). Python is a dynamically typed language, meaning that variables do not need to be declared before they are used. Instead, Python infers the data type of the variable based on the value assigned to it.

Print statements are used to display output to the console. In Python, print statements are written using the print() function.

Conditional statements are used to execute code based on a condition. In Python, the if-else statement is used for conditional statements.

Loop statements are used to repeat code. In Python, the for loop is used to iterate over a sequence of values, and the while loop is used to repeat code until a condition is met.

Functions are blocks of code that can be called multiple times. In Python, functions are defined using the def keyword, followed by the name of the function and the parameters it takes. The return statement is used to return a value from the function.

Overall, Python’s syntax is intuitive and easy to learn, making it an excellent choice for beginners and experienced programmers alike.

Python Comments

In Python, comments are used to add explanatory notes or annotations to code. They are ignored by the interpreter and do not affect the program’s execution. Comments can be single-line or multi-line, and are denoted by the hash symbol (#) for single-line comments or triple quotes (”’ ”’) for multi-line comments.

Here are some examples of how to use comments in Python:

Single-line comment:

# This is a single-line comment

Multi-line comment:

'''
This is a
multi-line
comment
'''

Comments are useful for explaining complex or ambiguous code, documenting code for future reference, and communicating with other developers who may be working on the same project. It’s important to use comments sparingly and only when necessary, as too many comments can make code harder to read and maintain.

Variables of Python

In Python, variables are used to store data values that can be used throughout a program. Variables in Python are dynamically typed, meaning that the type of data that a variable holds can change during the execution of a program.

To create a variable in Python, you simply need to assign a value to a variable name. Here is an example of how to create a variable in Python:

# Assigning a value to a variable
x = 5
y = "Hello, World!"

# Printing the value of a variable
print(x)
print(y)
In this example, the variables x and y are created and assigned the values 5 and "Hello, World!" respectively. The print() function is then used to display the values of the variables in the console.

Python variable names can contain letters, numbers, and underscores, but they cannot begin with a number. Variable names are case-sensitive, so x and X are two different variables. It is also good practice to choose variable names that are descriptive and meaningful.

Python supports several different types of data that can be stored in variables, including:

  • Numeric data types (integers, floats, and complex numbers)
  • String data type
  • Boolean data type
  • List data type
  • Tuple data type
  • Set data type
  • Dictionary data type

Variables can be used in Python to perform calculations, store user input, or manipulate data. Understanding how to use variables is a fundamental part of programming in Python.

Data Types of Python

Python is a popular and versatile programming language used in various fields, such as data analysis, machine learning, web development, and more. One of the essential features of Python is its data types. Data types in Python refer to the classification or categorization of data items. In this article, we will explore the different data types available in Python.

  1. Numeric Data Types

Numeric data types in Python include integers, floats, and complex numbers. Integers are whole numbers with no decimal points, while floats are numbers with decimal points. Complex numbers have a real and imaginary part.

  1. String Data Type

Strings are sequences of characters enclosed in single or double quotes. Strings are immutable, meaning that once a string is created, it cannot be changed. However, you can create a new string by concatenating two or more strings.

  1. Boolean Data Type

The Boolean data type represents true or false values. It is used in conditional statements to determine which path to take in a program’s execution.

  1. List Data Type

Lists are used to store a collection of items. Items in a list are separated by commas and enclosed in square brackets. Lists can contain any data type, including other lists.

  1. Tuple Data Type

Tuples are similar to lists but are immutable, meaning that once a tuple is created, it cannot be changed. Tuples are enclosed in parentheses and can contain any data type.

  1. Set Data Type

A set is an unordered collection of unique items. Sets are enclosed in curly braces and are used to perform mathematical operations such as union, intersection, and difference.

  1. Dictionary Data Type

Dictionaries are used to store key-value pairs. The keys must be unique and are used to access the corresponding values. Dictionaries are enclosed in curly braces and consist of key-value pairs separated by colons.

In conclusion, Python’s data types provide flexibility and versatility to programmers, making it a popular choice for various applications. Understanding the different data types available in Python is crucial for writing efficient and effective code. By leveraging the appropriate data type for each situation, developers can write more readable and maintainable code.

Python Numbers

In Python, numbers are a data type used to represent numeric values in code. There are three main types of numbers in Python: integers, floating-point numbers, and complex numbers.

Integers: Integers, denoted as “int” in Python, are whole numbers with no fractional component. They can be positive, negative, or zero. Integers in Python have no upper or lower limit to their size and can be arbitrarily large or small. Examples of integers in Python include 0, 1, -2, 10, and 1000.

Floating-point numbers: Floating-point numbers, denoted as “float” in Python, are numbers with a decimal point or an exponent. They can also be positive, negative, or zero. Floating-point numbers are used to represent real-world values with decimal places, such as measurements or currency. Examples of floating-point numbers in Python include 3.14, -2.5, and 1.0e-5.

Complex numbers: Complex numbers, denoted as “complex” in Python, are numbers with both a real and imaginary component. They are represented in Python as a combination of a real number and an imaginary number, written as “a + bj” where “a” is the real part and “b” is the imaginary part. Examples of complex numbers in Python include 3 + 2j and -1 + 4j.

Python also provides a variety of built-in functions and operators for working with numbers, such as addition (+), subtraction (-), multiplication (*), division (/), and exponentiation (**). Additionally, Python provides several modules for performing advanced mathematical operations, such as the math module and the numpy module.

Python Casting

In Python, casting refers to the process of converting a value from one data type to another. Python provides several built-in functions for casting, including int(), float(), str(), and bool().

Here are some examples of how to use casting in Python:

Casting to integer:

x = 3.14
y = int(x)
print(y) # Output: 3

Casting to floating-point number:

x = 5
y = float(x)
print(y) # Output: 5.0

Casting to string:

x = 10
y = str(x)
print(y) # Output: "10"

Casting to boolean:

x = ""
y = bool(x)
print(y) # Output: False

In addition to the built-in functions, Python also provides a way to create custom classes that define their own casting behavior. This is done by defining special methods, such as int() or float(), which allow instances of the class to be cast to the desired data type. However, this is an advanced topic and beyond the scope of this explanation.

Python String

In Python, a string is a data type used to represent text. Strings are defined using single quotes (‘…’) or double quotes (“…”), and can contain any combination of letters, numbers, and symbols. Here are some examples of how to define strings in Python:

my_string = "Hello, World!" # Using double quotes
another_string = 'This is a string' # Using single quotes

Strings can be manipulated using a variety of built-in functions and operators, such as concatenation (+), repetition (*), and slicing ([]). Here are some examples:

Concatenation:

first_name = "John"
last_name = "Doe"
full_name = first_name + " " + last_name
print(full_name) # Output: "John Doe"

Repetition:

my_string = "abc"
repeated_string = my_string * 3
print(repeated_string) # Output: "abcabcabc"

Slicing:

my_string = "Hello, World!"
substring = my_string[0:5] # Get the first 5 characters
print(substring) # Output: "Hello"

Python also provides many built-in methods for manipulating strings, such as upper(), lower(), strip(), split(), and join(). Here are some examples:

Upper and lower case:

my_string = "Hello, World!"
upper_case = my_string.upper()
lower_case = my_string.lower()
print(upper_case) # Output: "HELLO, WORLD!"
print(lower_case) # Output: "hello, world!"

Stripping whitespace:

my_string = " Hello, World! "
stripped_string = my_string.strip()
print(stripped_string) # Output: "Hello, World!"

Splitting and joining strings:

my_string = "Hello, World!"
split_string = my_string.split(", ")
joined_string = "-".join(split_string)
print(split_string) # Output: ["Hello", "World!"]
print(joined_string) # Output: "Hello-World!"

These are just a few examples of what you can do with strings in Python. Strings are an important and versatile data type in Python, and are used extensively in many programming applications.

Python Operator

In Python, an operator is a symbol or keyword used to perform operations on one or more operands. There are several types of operators in Python, including arithmetic operators, comparison operators, logical operators, identity operators, membership operators, and assignment operators.

Here are some examples of the different types of operators in Python:

Arithmetic operators:

x = 10
y = 3

print(x + y) # Output: 13
print(x - y) # Output: 7
print(x * y) # Output: 30
print(x / y) # Output: 3.3333...
print(x % y) # Output: 1
print(x ** y) # Output: 1000

Comparison operators:

x = 10
y = 3

print(x > y) # Output: True
print(x < y) # Output: False
print(x == y) # Output: False
print(x != y) # Output: True
print(x >= y) # Output: True
print(x <= y) # Output: False

Logical operators:

x = True
y = False

print(x and y) # Output: False
print(x or y) # Output: True
print(not x) # Output: False

Identity operators:

x = ["apple", "banana"]
y = ["apple", "banana"]
z = x

print(x is z) # Output: True
print(x is y) # Output: False
print(x == y) # Output: True

Membership operators:

x = "Hello, World!"
print("H" in x) # Output: True
print("h" in x) # Output: False
print("!" not in x) # Output: False

Assignment operators:

x = 10
x += 5 # Same as x = x + 5
print(x) # Output: 15

y = 5
y **= 3 # Same as y = y ** 3
print(y) # Output: 125

These are just a few examples of the different types of operators in Python. Operators are an essential part of the language and are used extensively in many programming applications.

Python Boolean

In Python, a boolean is a data type used to represent logical values, such as True or False. Booleans are primarily used in conditional statements and loops to control the flow of a program.

In Python, the True and False keywords are used to represent boolean values. Here are some examples:

x = True
y = False

print(x) # Output: True
print(y) # Output: False

Booleans can be combined using logical operators such as and, or, and not. Here are some examples:

x = True
y = False

print(x and y) # Output: False
print(x or y) # Output: True
print(not x) # Output: False

Booleans can also be created by comparing values using comparison operators such as ==, !=, <, >, <=, and >=. Here are some examples:

x = 5
y = 10

print(x == y) # Output: False
print(x != y) # Output: True
print(x < y) # Output: True
print(x > y) # Output: False
print(x <= y) # Output: True
print(x >= y) # Output: False

In Python, many functions and operators return boolean values, which can be used in conditional statements and loops. For example:

my_list = [1, 2, 3, 4, 5]

if 3 in my_list:
print("3 is in the list")
else:
print("3 is not in the list")

This code will output “3 is in the list”, because the “in” operator returns True if the value is in the list. Booleans are an important part of Python and are used extensively in many programming applications.

Harshvardhan Mishra

Hi, I'm Harshvardhan Mishra. Tech enthusiast and IT professional with a B.Tech in IT, PG Diploma in IoT from CDAC, and 6 years of industry experience. Founder of HVM Smart Solutions, blending technology for real-world solutions. As a passionate technical author, I simplify complex concepts for diverse audiences. Let's connect and explore the tech world together! If you want to help support me on my journey, consider sharing my articles, or Buy me a Coffee! Thank you for reading my blog! Happy learning! Linkedin

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