Python Notes
Introduction to Python and installation:
Python is a widely used general-purpose, high level programming language known for its simplicity and
readability. It’s used widely across different fields, from web development and data analysis to automation
and game development. Python’s syntax is straightforward and looks like English, making it easy to learn
and understand.
There are two major Python versions-
Python 2 and Python 3.
• On 16 October 2000, Python 2.0 was released with many new features.
• On 3rd December 2008, Python 3.0 was released with more testing and includes new features.
Python has several key features that make it popular among programmers:
1. Simple and Readable Syntax: Python’s code structure is straightforward, making it easy to read
and write, even for beginners.
2. Interpreted Language: Python runs line-by-line, which allows for immediate feedback and
easier debugging.
3. Dynamically Typed: Variables in Python do not require explicit type definitions, as types are
assigned automatically during execution.
4. High-Level Language: Python handles complex programming tasks like memory management
behind the scenes, so you can focus more on logic.
5. Object-Oriented: Python supports object-oriented programming, allowing you to create reusable
code components and build structured applications.
6. Portable: Python can run on multiple platforms, including Windows, Mac, and Linux, making it
highly versatile for different environments.
7. Extensive Standard Library: Python includes a vast library with built-in modules and functions
for handling a wide variety of programming tasks.
8. Supports Multiple Paradigms: Python is flexible and supports procedural, object-oriented, and
functional programming.
9. Embeddable and Extensible: Python can be embedded in other languages or extended with
languages like C/C++, allowing integration with other applications and systems.
,Python’s syntax is designed to be simple and readable compared to many other languages, making it great
for beginners. Here’s a quick comparison to highlight this:
No Braces: Python uses indentation instead of braces {} to mark code blocks, which makes it cleaner.
# Python
if age > 18:
print("Adult")
// Java
if (age > 18) {
System.out.println("Adult");
}
No Type Declarations: You don’t need to specify types in Python; the language figures it out.
age = 25 # Python infers the type
java
int age = 25; // In Java, you must specify the type
Python IDE
A Python IDE (Integrated Development Environment) is a tool that provides a comprehensive
environment for writing, testing, and debugging Python code. IDEs are designed to make coding easier by
offering features like code completion, syntax highlighting, and debugging tools, all in one place. Here’s a
breakdown of some popular Python IDEs and their features:
1. IDLE (Integrated Development and Learning Environment)
● Bundled with Python: IDLE comes pre-installed with Python, so you don’t need to download
anything extra.
● Simple Interface: IDLE is a lightweight, easy-to-use editor with basic features, making it ideal
for beginners.
● Features: Syntax highlighting, code completion, and a built-in interactive shell to test code
snippets.
,2. PyCharm
● Developed by JetBrains: PyCharm is one of the most popular Python IDEs, known for its
extensive features.
● Advanced Features: It has intelligent code completion, real-time error detection, and a powerful
debugger.
● Versions: PyCharm has a free Community edition (great for beginners) and a paid Professional
edition with more advanced features for web development, data science, and more.
3. VS Code (Visual Studio Code)
● Free and Highly Customizable: VS Code is a powerful, open-source editor developed by
Microsoft, with a wide variety of plugins for Python.
● Lightweight with Extensions: It’s not a full IDE by default but can be extended to become one.
The Python extension adds features like linting, debugging, code completion, and an integrated
terminal.
● Cross-Platform: Available on Windows, macOS, and Linux.
4. Jupyter Notebook
● Interactive Coding: Jupyter is popular for data science and machine learning because it allows
you to write code in cells and see outputs immediately, including visualizations.
● Markdown Support: You can add explanations, images, and formatted text, making it ideal for
tutorials, data analysis, and presentations.
● Web-Based: Runs in your browser, making it accessible and shareable.
5. Spyder
● For Data Science: Spyder is a scientific Python IDE, popular among data scientists and
researchers.
● Data Analysis Tools: It includes features like variable explorers and data viewers, which help in
analyzing data interactively.
● Integration with Anaconda: Spyder comes with the Anaconda distribution, which is commonly
used for data science and machine learning environments.
Keyword- Python keywords (or reserved words) are special words that have specific meanings and
purposes within the language. These keywords are part of Python’s syntax and cannot be used as
identifiers (e.g., variable names, function names) because they are reserved by the language.
List of Python Keywords:
As of Python 3.10, here are the main keywords:
, 1. False - Boolean value for false.
2. None - Represents a null or no value.
3. True - Boolean value for true.
4. and - Logical AND operator.
5. as - Used to create an alias.
6. assert - For debugging; checks if a condition is true.
7. async - Used to declare asynchronous functions.
8. await - Waits for the completion of an async function.
9. break - Exits the current loop prematurely.
10.class - Defines a class.
11.continue - Skips the rest of the loop and moves to the next iteration.
12.def - Defines a function.
13.del - Deletes a reference to an object.
14.elif - Else if condition, used in conditional statements.
15.else - Used in conditional statements for alternatives.
16.except - Catches exceptions in try-except blocks.
17.finally - Executes code at the end of a try block, regardless of exceptions.
18.for - Used to create a for loop.
19.from - Imports specific parts of a module.
20.global - Declares a global variable.
21.if - Used for conditional statements.
22.import - Imports modules.
23.in - Checks if a value exists within a sequence or container.
24.is - Checks if two variables point to the same object.
25.lambda - Creates an anonymous function.
26.nonlocal - Declares a non-local variable within a nested function.
27.not - Logical NOT operator.
28.or - Logical OR operator.
29.pass - Does nothing; acts as a placeholder.
30.raise - Raises an exception.
31.return - Exits a function and optionally returns a value.
32.try - Begins a block that handles exceptions.
33.while - Used to create a while loop.
34.with - Used to wrap code that needs resource management.
35.yield - Pauses a function and returns a value; used with generators.
In Python, an identifier is a name used to identify a variable, function, class, module, or other object.
Identifiers are essential for coding because they allow you to reference and manipulate data in your
programs.
Introduction to Python and installation:
Python is a widely used general-purpose, high level programming language known for its simplicity and
readability. It’s used widely across different fields, from web development and data analysis to automation
and game development. Python’s syntax is straightforward and looks like English, making it easy to learn
and understand.
There are two major Python versions-
Python 2 and Python 3.
• On 16 October 2000, Python 2.0 was released with many new features.
• On 3rd December 2008, Python 3.0 was released with more testing and includes new features.
Python has several key features that make it popular among programmers:
1. Simple and Readable Syntax: Python’s code structure is straightforward, making it easy to read
and write, even for beginners.
2. Interpreted Language: Python runs line-by-line, which allows for immediate feedback and
easier debugging.
3. Dynamically Typed: Variables in Python do not require explicit type definitions, as types are
assigned automatically during execution.
4. High-Level Language: Python handles complex programming tasks like memory management
behind the scenes, so you can focus more on logic.
5. Object-Oriented: Python supports object-oriented programming, allowing you to create reusable
code components and build structured applications.
6. Portable: Python can run on multiple platforms, including Windows, Mac, and Linux, making it
highly versatile for different environments.
7. Extensive Standard Library: Python includes a vast library with built-in modules and functions
for handling a wide variety of programming tasks.
8. Supports Multiple Paradigms: Python is flexible and supports procedural, object-oriented, and
functional programming.
9. Embeddable and Extensible: Python can be embedded in other languages or extended with
languages like C/C++, allowing integration with other applications and systems.
,Python’s syntax is designed to be simple and readable compared to many other languages, making it great
for beginners. Here’s a quick comparison to highlight this:
No Braces: Python uses indentation instead of braces {} to mark code blocks, which makes it cleaner.
# Python
if age > 18:
print("Adult")
// Java
if (age > 18) {
System.out.println("Adult");
}
No Type Declarations: You don’t need to specify types in Python; the language figures it out.
age = 25 # Python infers the type
java
int age = 25; // In Java, you must specify the type
Python IDE
A Python IDE (Integrated Development Environment) is a tool that provides a comprehensive
environment for writing, testing, and debugging Python code. IDEs are designed to make coding easier by
offering features like code completion, syntax highlighting, and debugging tools, all in one place. Here’s a
breakdown of some popular Python IDEs and their features:
1. IDLE (Integrated Development and Learning Environment)
● Bundled with Python: IDLE comes pre-installed with Python, so you don’t need to download
anything extra.
● Simple Interface: IDLE is a lightweight, easy-to-use editor with basic features, making it ideal
for beginners.
● Features: Syntax highlighting, code completion, and a built-in interactive shell to test code
snippets.
,2. PyCharm
● Developed by JetBrains: PyCharm is one of the most popular Python IDEs, known for its
extensive features.
● Advanced Features: It has intelligent code completion, real-time error detection, and a powerful
debugger.
● Versions: PyCharm has a free Community edition (great for beginners) and a paid Professional
edition with more advanced features for web development, data science, and more.
3. VS Code (Visual Studio Code)
● Free and Highly Customizable: VS Code is a powerful, open-source editor developed by
Microsoft, with a wide variety of plugins for Python.
● Lightweight with Extensions: It’s not a full IDE by default but can be extended to become one.
The Python extension adds features like linting, debugging, code completion, and an integrated
terminal.
● Cross-Platform: Available on Windows, macOS, and Linux.
4. Jupyter Notebook
● Interactive Coding: Jupyter is popular for data science and machine learning because it allows
you to write code in cells and see outputs immediately, including visualizations.
● Markdown Support: You can add explanations, images, and formatted text, making it ideal for
tutorials, data analysis, and presentations.
● Web-Based: Runs in your browser, making it accessible and shareable.
5. Spyder
● For Data Science: Spyder is a scientific Python IDE, popular among data scientists and
researchers.
● Data Analysis Tools: It includes features like variable explorers and data viewers, which help in
analyzing data interactively.
● Integration with Anaconda: Spyder comes with the Anaconda distribution, which is commonly
used for data science and machine learning environments.
Keyword- Python keywords (or reserved words) are special words that have specific meanings and
purposes within the language. These keywords are part of Python’s syntax and cannot be used as
identifiers (e.g., variable names, function names) because they are reserved by the language.
List of Python Keywords:
As of Python 3.10, here are the main keywords:
, 1. False - Boolean value for false.
2. None - Represents a null or no value.
3. True - Boolean value for true.
4. and - Logical AND operator.
5. as - Used to create an alias.
6. assert - For debugging; checks if a condition is true.
7. async - Used to declare asynchronous functions.
8. await - Waits for the completion of an async function.
9. break - Exits the current loop prematurely.
10.class - Defines a class.
11.continue - Skips the rest of the loop and moves to the next iteration.
12.def - Defines a function.
13.del - Deletes a reference to an object.
14.elif - Else if condition, used in conditional statements.
15.else - Used in conditional statements for alternatives.
16.except - Catches exceptions in try-except blocks.
17.finally - Executes code at the end of a try block, regardless of exceptions.
18.for - Used to create a for loop.
19.from - Imports specific parts of a module.
20.global - Declares a global variable.
21.if - Used for conditional statements.
22.import - Imports modules.
23.in - Checks if a value exists within a sequence or container.
24.is - Checks if two variables point to the same object.
25.lambda - Creates an anonymous function.
26.nonlocal - Declares a non-local variable within a nested function.
27.not - Logical NOT operator.
28.or - Logical OR operator.
29.pass - Does nothing; acts as a placeholder.
30.raise - Raises an exception.
31.return - Exits a function and optionally returns a value.
32.try - Begins a block that handles exceptions.
33.while - Used to create a while loop.
34.with - Used to wrap code that needs resource management.
35.yield - Pauses a function and returns a value; used with generators.
In Python, an identifier is a name used to identify a variable, function, class, module, or other object.
Identifiers are essential for coding because they allow you to reference and manipulate data in your
programs.
