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Topics

Python Basics

Introduction to PythonInstalling PythonPython SyntaxPython CommentsPython VariablesPython Data TypesPython Type ConversionPython OperatorsPython Input/OutputPython Indentation

Control Structures

Python If...ElsePython While LoopsPython For LoopsPython Break and ContinuePython Pass StatementPython Match-Case Statements

Python Data Structures

Python ListsPython TuplesPython SetsPython DictionariesPython ArraysPython List Comprehension

Python Functions

Defining Python FunctionsPython Function ArgumentsPython Function Return ValuesPython Lambda FunctionsPython Recursive FunctionsPython Global and Local Variables

Python OOP

Python Classes and ObjectsPython InheritancePython EncapsulationPython PolymorphismPython Method OverridingPython Abstract Classes

Python Modules and Packages

Creating Python ModulesImporting Python ModulesPython Built-in ModulesPython Package Management (pip)Creating Python Packages

Python File Handling

Python File Open/ClosePython File ReadPython File WritePython File ManagementPython Directory Handling

Python Exception Handling

Python Try...ExceptPython User-defined ExceptionsPython Raise KeywordPython Finally Clause

Python Advanced Topics

Python IteratorsPython GeneratorsPython DecoratorsPython Context ManagersPython Regular ExpressionsPython MultithreadingPython Multiprocessing

Python Standard Library

Python Math ModulePython Random ModulePython DateTime ModulePython JSON ModulePython OS ModulePython Sys Module

Python Data Manipulation

Python String ManipulationPython List OperationsPython Dictionary OperationsPython Set Operations

Python Testing

Python Unit TestingPython DoctestPython PytestPython Test-Driven Development

Python Performance

Python Code OptimizationPython ProfilingPython Memory ManagementPython Caching Techniques

Python and Databases

Python SQLitePython MySQL ConnectorPython PostgreSQLPython MongoDB

Python Web Scraping

Python Requests LibraryPython BeautifulSoupPython Scrapy Basics

Python and APIs

Python REST API BasicsPython API AuthenticationPython API Data Handling

Python Built-in Modules

Python's built-in modules are pre-installed libraries that come with the Python installation. These modules provide a wide range of functionalities, allowing developers to perform various tasks without writing code from scratch.

Understanding Built-in Modules

Built-in modules are an integral part of Python's "batteries included" philosophy. They offer ready-to-use functions and classes for common programming tasks, enhancing productivity and code reusability.

Importing Built-in Modules

To use a built-in module, you need to import it first. There are several ways to import modules in Python:


import module_name
from module_name import function_name
from module_name import *
import module_name as alias

Common Built-in Modules

Python offers numerous built-in modules. Here are some frequently used ones:

  • math: Mathematical functions and constants
  • random: Generate random numbers and make selections
  • datetime: Date and time manipulation
  • os: Interact with the operating system
  • sys: System-specific parameters and functions

Example: Using the math Module

The Python Math Module provides mathematical functions for complex calculations. Here's a simple example:


import math

radius = 5
area = math.pi * math.pow(radius, 2)
print(f"The area of a circle with radius {radius} is {area:.2f}")

Example: Using the random Module

The Python Random Module is useful for generating random numbers and making random selections:


import random

# Generate a random integer between 1 and 10
random_number = random.randint(1, 10)
print(f"Random number: {random_number}")

# Choose a random item from a list
fruits = ['apple', 'banana', 'cherry', 'date']
chosen_fruit = random.choice(fruits)
print(f"Randomly chosen fruit: {chosen_fruit}")

Best Practices

  • Import only the functions you need to optimize performance
  • Use aliases for modules with long names to improve code readability
  • Familiarize yourself with common built-in modules to avoid reinventing the wheel
  • Consult the official Python documentation for comprehensive module information

Conclusion

Python's built-in modules are powerful tools that significantly enhance the language's capabilities. By leveraging these pre-installed libraries, developers can write more efficient and concise code. As you progress in your Python journey, exploring and mastering these modules will greatly improve your programming skills and productivity.

Remember to check the Python Package Management (pip) guide for installing additional third-party modules to further extend Python's functionality.