About this course
Python is a high-level, interpreted programming language known for its simplicity and readability, making it an excellent choice for beginners and seasoned developers alike. Guido van Rossum created Python in the late 1980s, and since then, it has gained immense popularity due to its versatility, ease of learning, and robust community support.
One of Python's key features is its clean and straightforward syntax, which emphasizes code readability and reduces the time needed for development and debugging. Its syntax resembles pseudo-code, making it easier to express complex ideas with fewer lines of code compared to other languages. This simplicity contributes to Python's wide adoption in various domains, including web development, data science, artificial intelligence, machine learning, and automation.
Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming, allowing developers to choose the approach that best suits their needs. It comes with a vast standard library that provides modules and packages for performing various tasks, such as file I/O, networking, database access, and more, without the need for third-party dependencies.
Furthermore, Python's extensive ecosystem includes a rich collection of third-party libraries and frameworks that extend its capabilities for specific applications. For web development, frameworks like Django and Flask offer powerful tools for building scalable and secure web applications. In the field of data science and machine learning, libraries such as NumPy, pandas, and TensorFlow enable researchers and engineers to analyze large datasets and develop sophisticated machine learning models.
Python's cross-platform compatibility ensures that code written in Python can run on different operating systems without modification, enhancing its portability and flexibility. Additionally, Python's dynamic typing and automatic memory management simplify memory allocation and deallocation, reducing the risk of memory leaks and other memory-related errors.
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Python is a high-level, interpreted programming language known for its simplicity and readability, making it an excellent choice for beginners and seasoned developers alike. Guido van Rossum created Python in the late 1980s, and since then, it has gained immense popularity due to its versatility, ease of learning, and robust community support.
To install Python on your system, you can follow these general steps:
Download Python: Visit the official Python website at https://www.python.org/downloads/. Choose the version of Python you want to install (usually the latest stable version) and download the installer for your operating system (Windows, macOS, or Linux).
Run the Installer: Once the download is complete, run the installer executable file. On Windows, you may need to select the option to add Python to the system PATH during installation for easier command-line access.
Follow Installation Wizard: Follow the prompts in the installation wizard. You can choose the installation location, customize the installation (optional), and select additional features to install.
Verify Installation: After the installation is complete, you can verify that Python has been installed correctly by opening a command prompt (Windows) or terminal (macOS/Linux) and typing python --version or python3 --version. This command should display the installed Python version.
Install a Text Editor or IDE (Optional): While Python comes with its built-in IDLE (Integrated Development and Learning Environment), you may prefer using a text editor or integrated development environment (IDE) for writing Python code. Some popular options include Visual Studio Code, PyCharm, Sublime Text, Atom, and Spyder.
Start Coding: Once Python is installed, you're ready to start coding! You can create Python scripts using your preferred text editor or IDE, save them with a .py extension, and run them using the Python interpreter.
A Python dictionary is a powerful data structure that stores key-value pairs. It allows you to associate each key with a corresponding value, enabling efficient retrieval and manipulation of data. In Python, dictionaries are denoted by curly braces {}, with each key-value pair separated by a colon :.
Dictionaries are versatile and can store various types of data, including integers, strings, lists, tuples, or even other dictionaries. Keys within a dictionary must be unique, but values can be duplicated.
One of the main advantages of dictionaries is their fast access time. Instead of searching through the entire collection of elements, Python can quickly locate a value associated with a specific key using a technique called hashing.
Python dictionaries are commonly used in various applications, including data processing, web development, and scientific computing. They provide an efficient and flexible way to organize and manipulate data, making them an essential tool for Python programmers.
Sets are used to store multiple items in a single variable.
Set is one of 4 built-in data types in Python used to store collections of data, the other 3 are List, Tuple, and Dictionary, all with different qualities and usage.
A set is a collection which is unordered, unchangeable*, and unindexed.
Note :- Set items are unchangeable, but you can remove items and add new items.
There are several ways to join two or more sets in Python.
The union() and update() methods joins all items from both sets.
The intersection() method keeps ONLY the duplicates.
The difference() method keeps the items from the first set that are not in the other set(s).
The symmetric_difference() method keeps all items EXCEPT the duplicates.
In Python, a tuple is an immutable sequence of values, typically used to store collections of heterogeneous data. Unlike lists, tuples cannot be modified once created, making them suitable for storing data that should not be changed, such as coordinates or configuration settings.
Tuples are defined using parentheses () and can contain any number of elements separated by commas. Even though tuples are immutable, they can contain mutable objects like lists.
Tuples are commonly used for returning multiple values from functions, as keys in dictionaries, and for data that should remain constant throughout the program execution.
A Python list is a versatile and mutable data structure that can hold a collection of items of any data type, such as integers, strings, or even other lists. Lists are created using square brackets and can be modified by adding, removing, or modifying elements. They support indexing, slicing, and various built-in methods for manipulation. Lists are commonly used for storing and organizing data in Python programs, providing a flexible way to work with collections of items.
Arithmetic operators in Python are symbols used to perform basic mathematical calculations such as addition, subtraction, multiplication, division, exponentiation, and modulus. The plus + operator adds two operands, the minus - operator subtracts the second operand from the first, the asterisk * operator multiplies operands, and the forward slash / operator divides the first operand by the second. Additionally, the double asterisk ** operator raises the first operand to the power of the second operand, and the percent % operator returns the remainder of the division. These operators are essential for numerical computations and are extensively used in Python programming
Assignment operators in Python are used to assign values to variables. They include the basic assignment operator =, as well as compound assignment operators like +=, -=, *=, /=, and %=. These operators combine arithmetic operations with assignment, making code more concise and readable. For example, x += 5 is equivalent to x = x + 5. Understanding assignment operators is essential for efficient and elegant Python programming, as they streamline the process of updating variable values within your code.
Comparison operators in Python are used to compare values and determine the relationship between them. These operators include == for equality, != for inequality, > for greater than, < for less than, >= for greater than or equal to, and <= for less than or equal to. They return a Boolean value (True or False) based on the comparison result. These operators are fundamental for conditional statements and decision-making processes in Python programming.
Logical operators in Python, including and, or, and not, are used to combine conditional statements and evaluate multiple conditions simultaneously. and returns True if both conditions are true, or returns True if at least one condition is true, and not negates the result of a condition. These operators are essential for creating complex decision-making structures and controlling program flow based on multiple conditions. Understanding logical operators is crucial for writing efficient and robust Python code.
Identity operators in Python, 'is' and 'is not', compare the memory addresses of two objects to determine their identity. 'is' returns True if both variables refer to the same object, while 'is not' returns True if they refer to different objects. These operators are useful for checking object identity, especially with mutable objects like lists and dictionaries. They provide a precise way to determine if two variables point to the same location in memory, ensuring accurate comparison in Python programs.
Strings :-
Strings in python are surrounded by either single quotation marks, or double quotation marks.
'hello' is the same as "hello".
The description of "Strings are Arrays" can be explained as follows:
In many programming languages, including Python, JavaScript, and C, strings are treated as arrays of characters. This means that a string can be accessed and manipulated similarly to an array.
Slicing strings in Python refers to the process of extracting specific portions or substrings from a larger string. Python provides a concise and powerful syntax for slicing strings using square brackets [] along with start and end index values.
The "Python - Modify Strings" module provides a comprehensive overview of various string manipulation techniques in Python. Through this module, learners will gain proficiency in modifying and manipulating strings to suit different programming requirements. The module covers essential topics such as string concatenation, slicing, formatting, replacing, and searching. Additionally, it explores advanced string manipulation techniques using regular expressions.
String Concatenation:
String concatenation is the process of combining two or more strings into a single string. In programming, strings are sequences of characters, and concatenation allows you to join these sequences together. In most programming languages, including Python, Java, JavaScript, and others, string concatenation is achieved using the concatenation operator (+) or specific string concatenation functions or methods.
Escape Characters:
Escape characters are special characters that are used to perform specific tasks within strings, such as inserting newlines, tabs, or quotation marks, that would otherwise be difficult to represent directly. Escape characters are preceded by a backslash () in most programming languages.
\n: Newline
\t: Tab
": Double quotation mark
': Single quotation mark
Python Variables :-
Variables are containers for storing data values.
x = 50
y = "Raj Kumar Singh"
print(x)
print(y)
Get the Type :-
You can get the data type of a variable with the type() function.
x = 16
y = "Inlearn Classes"
print(type(x))
print(type(y))
In Python, comments are used to annotate code for better understanding and documentation. There are two types of comments in Python:
Single-Line Comments: Single-line comments start with the # character and continue until the end of the line. They are used to add short descriptions or notes to specific lines of code.
# This is a single-line comment
x = 10 # Assigning the value 10 to variable x
Multi-Line Comments (Docstrings): Multi-line comments, also known as docstrings, are enclosed within triple quotes (''' or """). They are typically used for function, module, or class documentation. While they are not technically comments, they serve a similar purpose of providing documentation.
'''
This is a multi-line comment (docstring).
It provides documentation for the function below.
'''
def my_function():
"""
This is also a multi-line comment (docstring).
It provides documentation for the function.
"""
pass
The if...else statement in Python allows you to execute different blocks of code based on whether a specified condition is true or false. It provides a way to create decision-making logic in your Python programs.
x = 10
if x > 10:
print("x is greater than 10")
elif x == 10:
print("x is equal to 10")
else:
print("x is less than 10")
Python While Loops
Python has two primitive loop commands :-
--> while loops
--> for loops
1. The while Loop :- With the while loop we can execute a set of statements as long as a condition is true.
Python For Loops
A for loop is used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string).
1. The break Statement :- With the break statement we can stop the loop before it has looped through all the items.
2. The continue Statement :- With the continue statement we can stop the current iteration of the loop, and continue with the next.
3. The range() Function :- To loop through a set of code a specified number of times, we can use the range() function.