Python Tutorial Level 1

Let's start with a small introduction to Python programming and then delve into three basic exercises.

Guido van Rossum, the creator of Python, was born in 1956 in the Netherlands. He developed a fascination with computers in secondary school when the institution acquired a computer. Guido further delved into his interest in computers by studying mathematics and computer science at the University of Amsterdam.

In university, he was introduced to the ABC programming language, which, although influential, Guido found it lacked in extensibility and flexibility. These limitations inspired him to create a programming language that would surpass them and meet the needs of programmers more proficiently.
Guido created Python during his time at the Netherlands’ National Research Institute for Mathematics and Computer Science (CWI), with its implementation starting in December 1989. He designed Python to prioritize readability and simplicity, drawing inspiration from other programming languages such as ABC, Modula-3, C, and Lisp.
The initial release of Python, version 0.9.0 in February 1991, already had classes with inheritance, exception handling, functions, and the core datatypes of list, dict, str, and so on. It drew considerable praise from the programming community for its versatility, and with each new release, Python progressively became more powerful, flexible, and useful.
Guido led the development of Python for nearly three decades while fostering a community-driven approach to its evolution. He held a role called the Benevolent Dictator For Life (BDFL), deciding the direction of Python until his resignation in 2018. Despite stepping down from his leadership role, he continues to contribute to the Python community.

Python is a popular high-level, interpreted programming language known for its easy syntax and readability.
Python is versatile and powerful, used in various domains:
web development
data analysis
artificial intelligence
game development.

Lab tutorial workbook: Using Jupyter Notebook for Python:

**Lab Tutorial Workbook: Introduction to Jupyter Notebook**
**1. Installing Jupyter Notebook** - Start by installing Python on your machine if you haven't already. You can download Python from the official Python website. - Once Python is installed, open your command prompt or terminal and run the following command to install Jupyter Notebook: ``` pip install jupyterlab ```
**2. Launching Jupyter Notebook** - Open your command prompt or terminal and navigate to the desired directory where you want to create your notebook. - Run the following command to launch Jupyter Notebook: ``` jupyter notebook ``` - This will open Jupyter Notebook in your default web browser.
**3. Creating a New Notebook** - In the Jupyter Notebook interface, click on the "New" drop-down menu on the right side and select "Python" to create a new Python notebook. - A new tab will open with an empty notebook.
**4. Notebook Cells** - A Jupyter Notebook is made up of cells, which can contain code, text, or visualizations. - By default, the first cell is a code cell. You can write Python code in it. - To add a new cell, click on the "+" button in the toolbar or press the "B" key on your keyboard while in command mode (press "Esc" to activate command mode). - To change the cell type, select the cell and go to the toolbar and select either "Code" or "Markdown" from the drop-down menu.
**5. Running Code** - To run a code cell, select the cell and press "Shift + Enter" or click the "Run" button in the toolbar. - Output from the code will appear below the cell. - You can also use shortcuts like "Ctrl + Enter" to run the cell and stay on the same cell.
**6. Editing and Formatting Text** - To add text to a notebook, create a markdown cell. - Double click on a markdown cell to edit its contents. - You can use Markdown syntax to format your text. For example: - To create headers, use "#" (e.g., "# Heading 1"). - To create bullet points, use "-" or "*" (e.g., "- Item 1").
**7. Saving and Exporting Notebooks** - To save your notebook, go to "File" and click on "Save and Checkpoint" or use the shortcut "Ctrl + S". - To export your notebook, go to "File", select "Download As", and choose the desired format (e.g., "Notebook (.ipynb)", "Python (.py)").
**8. Restarting and Clearing Output** - To restart the Python kernel (clear all variables and reset the notebook), go to "Kernel" and click on "Restart" or use the shortcut "0, 0" (press "0" twice). - To clear the output of a cell, select the cell and go to "Cell" and click on "Clear Output" or use the shortcut "Shift + O".
**9. Additional Resources** - Jupyter Notebook documentation: []( - Jupyter Notebook tutorials: [](
This lab tutorial workbook provides a basic introduction to Jupyter Notebook for Python. Explore the capabilities of Jupyter Notebook further to unlock its full potential for data analysis, visualization, and more. Happy coding!

Exercise 1: Hello, World!

The first program in any language is the classic "Hello, World!" program, designed to introduce the syntax for outputting information.
```python print("Hello, World!") ```


Let’s start by getting strong on the basics:
The File System
The Command Prompt

To run this code: 1. Open your Python environment (for instance IDLE or Anaconda, or use an online Python compiler like or Jupyter Notebook). 2. Copy and paste this code into the Python shell. 3. Press Enter, and it should print "Hello, World!".

Exercise 2: Variables and Types

Variables are containers for storing data values.

Unlike other programming languages, Python doesn't require declaring the variable type.

```python x = 20 y = 20.5 z = "Hello, Python" ```
In this example, `x` is an integer, `y` is a float (a number that allows for decimal points), and `z` is a string. You can check the type of any object with the `type()` function in python like this:
```python print(type(x)) ```
**Exercise 3: Conditional Statements**
Let's finish with an example of a conditional statement. Here, we'll use the `if` statement.
```python x = 10 y = 20 if y > x: print("y is greater than x") else: print("x is greater than y") ```
In this example, since 20 is greater than 10, the output will be "y is greater than x".
Take your time to practice and experiment with these exercises. Remember, the key to learning programming is consistent practice. Happy coding!

Epoch 1: Introduction to Python and Basic Programming
Introduction to Python
History and evolution of Python
Why Python is popular in enterprise IT and data analysis
Setting Up the Python Environment
Installing Python
Setting up an Integrated Development Environment (IDE)
Writing and executing the first Python script: "Hello, World!"
Basic Python Syntax and Variables
Python indentation and code structure
Variables: declaration, assignment, and data types
Control Structures: Conditional Statements
if, elif, and else statements
Simple program: A basic calculator
Control Structures: Loops
for and while loops
Simple program: Generating a Fibonacci sequence
Functions in Python
Defining and calling functions
Parameters and return values
Simple program: A function to check if a number is prime
Data Structures: Lists and Dictionaries
Lists: definition, indexing, and basic operations
Dictionaries: definition, keys, values, and basic operations
Simple program: A contact book using lists and dictionaries
File Input/Output
Reading from and writing to files
Handling different file formats (txt, csv)
Simple program: A basic file-based note-taking application
Epoch 2: Intermediate Python and Object-Oriented Programming
Introduction to Object-Oriented Programming (OOP)
Concepts: Classes, Objects, Inheritance, Polymorphism
Why OOP is crucial for enterprise applications
Defining Classes and Objects in Python
Creating classes and instantiating objects
Attributes and methods
Inheritance and Polymorphism in Python
Extending classes and overriding methods
Using polymorphism for flexible code design
Modeling the Enterprise Business Domain
Understanding business requirements
Designing classes to represent entities like Employees, Products, Orders, etc.
Simple program: A basic inventory management system
Error Handling and Exceptions
Understanding exceptions in Python
try, except, finally blocks
Creating custom exceptions
Modules and Packages
Organizing code using modules and packages
Importing and using external libraries
Epoch 3: Advanced Python and Enterprise Application Development
Advanced Data Structures: Sets and Tuples
Sets: definition and operations
Tuples: definition and use cases
Database Integration with Python
Introduction to SQL databases
Using Python to connect, query, and update databases
Simple program: A CRUD application for an enterprise database
Web Development with Python
Introduction to web frameworks like Flask or Django
Building a basic web application to showcase enterprise data
Data Analysis with Python
Introduction to libraries like Pandas and NumPy
Analyzing enterprise data to derive insights
Testing and Debugging in Python
Writing unit tests using unittest
Debugging techniques and tools
Deploying Python Applications in an Enterprise Environment
Understanding deployment options: local servers, cloud platforms, containers
Best practices for secure and scalable deployment
This outline provides a comprehensive journey from understanding Python's basics to deploying enterprise applications. Each step can be expanded upon with lectures, hands-on exercises, and projects to ensure a deep understanding of the concepts.

Epoch 4: Advanced Topics and Specialized Use-Cases
Python and Cloud Integration
Introduction to cloud platforms (e.g., AWS, Azure, Google Cloud)
Leveraging Python SDKs to interact with cloud services
Simple program: Automating cloud resource management using Python
Python for Data Visualization
Introduction to libraries like Matplotlib, Seaborn, and Plotly
Creating interactive dashboards and reports for enterprise stakeholders
Python and Machine Learning
Introduction to machine learning concepts
Using Python libraries like Scikit-learn for building ML models
Simple program: Predictive analytics for enterprise sales data
Python and API Development
Building RESTful APIs using frameworks like Flask and FastAPI
Securing, versioning, and deploying APIs for enterprise consumption
Concurrency and Parallelism in Python
Understanding threads, processes, and asynchronous programming
Leveraging Python for concurrent tasks in enterprise applications
Python and IoT (Internet of Things)
Introduction to IoT and its relevance in the enterprise domain
Using Python to interact with IoT devices and sensors
Simple program: Monitoring and reporting IoT device data in an enterprise setup
Python Best Practices and Code Optimization
Writing clean, efficient, and maintainable Python code
Performance optimization techniques and tools
Python and Cybersecurity
Understanding common security threats in enterprise applications
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