Python Training , study and exam guide
1 Introduction to Python
1.1 What is Python?
1.2 History of Python
1.3 Features of Python
1.4 Python Applications
1.5 Setting up the Python Environment
1.6 Running Your First Python Program
2 Python Basics
2.1 Python Syntax and Indentation
2.2 Variables and Data Types
2.2 1 Numbers
2.2 2 Strings
2.2 3 Lists
2.2 4 Tuples
2.2 5 Sets
2.2 6 Dictionaries
2.3 Operators
2.3 1 Arithmetic Operators
2.3 2 Comparison Operators
2.3 3 Logical Operators
2.3 4 Assignment Operators
2.3 5 Membership Operators
2.3 6 Identity Operators
2.4 Input and Output
2.4 1 Input Function
2.4 2 Output Function
2.5 Comments
2.5 1 Single-line Comments
2.5 2 Multi-line Comments
3 Control Flow
3.1 Conditional Statements
3.1 1 If Statement
3.1 2 If-Else Statement
3.1 3 Elif Statement
3.1 4 Nested If Statements
3.2 Loops
3.2 1 For Loop
3.2 2 While Loop
3.2 3 Nested Loops
3.3 Loop Control Statements
3.3 1 Break Statement
3.3 2 Continue Statement
3.3 3 Pass Statement
4 Functions
4.1 Defining Functions
4.2 Function Arguments
4.2 1 Positional Arguments
4.2 2 Keyword Arguments
4.2 3 Default Arguments
4.2 4 Variable-length Arguments
4.3 Return Statement
4.4 Lambda Functions
4.5 Scope of Variables
4.5 1 Local Variables
4.5 2 Global Variables
4.6 Recursion
5 Data Structures
5.1 Lists
5.1 1 List Operations
5.1 2 List Methods
5.1 3 List Comprehensions
5.2 Tuples
5.2 1 Tuple Operations
5.2 2 Tuple Methods
5.3 Sets
5.3 1 Set Operations
5.3 2 Set Methods
5.4 Dictionaries
5.4 1 Dictionary Operations
5.4 2 Dictionary Methods
5.5 Advanced Data Structures
5.5 1 Stacks
5.5 2 Queues
5.5 3 Linked Lists
6 Modules and Packages
6.1 Importing Modules
6.2 Creating Modules
6.3 Standard Library Modules
6.3 1 Math Module
6.3 2 Random Module
6.3 3 DateTime Module
6.4 Creating Packages
6.5 Installing External Packages
7 File Handling
7.1 Opening and Closing Files
7.2 Reading from Files
7.2 1 read()
7.2 2 readline()
7.2 3 readlines()
7.3 Writing to Files
7.3 1 write()
7.3 2 writelines()
7.4 File Modes
7.5 Working with CSV Files
7.6 Working with JSON Files
8 Exception Handling
8.1 Try and Except Blocks
8.2 Handling Multiple Exceptions
8.3 Finally Block
8.4 Raising Exceptions
8.5 Custom Exceptions
9 Object-Oriented Programming (OOP)
9.1 Classes and Objects
9.2 Attributes and Methods
9.3 Constructors and Destructors
9.4 Inheritance
9.4 1 Single Inheritance
9.4 2 Multiple Inheritance
9.4 3 Multilevel Inheritance
9.5 Polymorphism
9.6 Encapsulation
9.7 Abstraction
10 Working with Libraries
10.1 NumPy
10.1 1 Introduction to NumPy
10.1 2 Creating NumPy Arrays
10.1 3 Array Operations
10.2 Pandas
10.2 1 Introduction to Pandas
10.2 2 DataFrames and Series
10.2 3 Data Manipulation
10.3 Matplotlib
10.3 1 Introduction to Matplotlib
10.3 2 Plotting Graphs
10.3 3 Customizing Plots
10.4 Scikit-learn
10.4 1 Introduction to Scikit-learn
10.4 2 Machine Learning Basics
10.4 3 Model Training and Evaluation
11 Web Development with Python
11.1 Introduction to Web Development
11.2 Flask Framework
11.2 1 Setting Up Flask
11.2 2 Routing
11.2 3 Templates
11.2 4 Forms and Validation
11.3 Django Framework
11.3 1 Setting Up Django
11.3 2 Models and Databases
11.3 3 Views and Templates
11.3 4 Forms and Authentication
12 Final Exam Preparation
12.1 Review of Key Concepts
12.2 Practice Questions
12.3 Mock Exams
12.4 Exam Tips and Strategies
6 1 Importing Modules Explained

6 1 Importing Modules Explained

Key Concepts

Importing modules in Python allows you to use code from other files or libraries. The key concepts include:

1. Importing Standard Modules

Python comes with a set of standard modules that provide additional functionality. You can import these modules using the import statement.

Example:

import math

result = math.sqrt(16)
print(result)  # Output: 4.0
    

Analogy: Think of a toolbox where you can pick a specific tool (module) to perform a task (function).

2. Importing Specific Functions

Instead of importing the entire module, you can import specific functions from a module using the from ... import ... statement.

Example:

from math import sqrt

result = sqrt(16)
print(result)  # Output: 4.0
    

Analogy: Think of a toolbox where you only take the specific tool (function) you need, not the entire toolbox.

3. Aliasing Modules

You can give a module or function an alias using the as keyword to make it easier to reference in your code.

Example:

import math as m

result = m.sqrt(16)
print(result)  # Output: 4.0
    

Analogy: Think of a toolbox where you label a tool (module) with a shorter name for easier access.

4. Importing from Packages

Packages are collections of modules. You can import modules from packages using the from ... import ... statement.

Example:

from datetime import datetime

now = datetime.now()
print(now)  # Output: Current date and time
    

Analogy: Think of a toolbox (package) containing multiple smaller toolboxes (modules).

5. Creating and Importing Custom Modules

You can create your own modules by writing Python code in a file and then importing it into another script.

Example:

Create a file named mymodule.py with the following content:

# mymodule.py
def greet(name):
    return f"Hello, {name}!"
    

Then, in another script, import and use the custom module:

import mymodule

message = mymodule.greet("Alice")
print(message)  # Output: Hello, Alice!
    

Analogy: Think of creating your own toolbox (module) and using it in your projects.

Putting It All Together

By understanding and using these import techniques effectively, you can leverage existing code and create modular, reusable Python programs.

Example:

import math as m
from datetime import datetime
import mymodule

result = m.sqrt(16)
print(result)  # Output: 4.0

now = datetime.now()
print(now)  # Output: Current date and time

message = mymodule.greet("Alice")
print(message)  # Output: Hello, Alice!