test deployment

webpage/docs/python-guide/01_Python_Basics/01_Syntax.md

@@ -1,10 +1,8 @@
 # Syntax 
 
-## Understanding Python Syntax
-
 Think of Python syntax as the punctuation of the programming world. Just as improper punctuation can lead to misunderstandings in human language, incorrect syntax in Python can cause miscommunication and errors.
 
-### Example: Printing a Friendly Message
+## Example: Printing a Friendly Message
 
 Let's start with a simple example - printing a friendly message to the console:
 
@@ -15,7 +13,7 @@ print("Hello, Bob")
 
 This code snippet will execute successfully, and you'll see the output: `Hello, Bob`.
 
-### Dealing with Syntax Errors
+## Dealing with Syntax Errors
 
 Now, let's intentionally introduce a syntax error by removing one parenthesis:
 
@@ -26,7 +24,7 @@ print("Hello, Bob"
 
 Your code editor will likely raise an error, indicating a missing parenthesis. If you attempt to run this code, a syntax error will occur. Always ensure that you respect the syntax rules.
 
-### Handling Quotation Marks
+## Handling Quotation Marks
 
 Quotation marks are essential in Python to define strings. Make sure to start and end them correctly:
 
@@ -37,7 +35,7 @@ print("Hello, Bob)
 
 Here, Python will raise a syntax error, signaling that you haven't respected the rules. Always close the quotes properly to avoid such errors.
 
-### Case Sensitivity in Python
+## Case Sensitivity in Python
 
 Python is case-sensitive. For instance, the `print` function must be written in lowercase:
 

webpage/docs/python-guide/01_Python_Basics/02_Comments.md

@@ -1,4 +1,4 @@
-# Clean Code and Commenting Practices
+# Commenting
 
 In this guide, we'll explore the use of comments in Python code and the importance of maintaining clean and readable code. While it's crucial to write code that is self-explanatory, comments can be valuable for adding context or reminders.
 

webpage/docs/python-guide/01_Python_Basics/04_Constants.md

@@ -2,9 +2,7 @@
 
 In Python, constants are not explicitly defined, but we rely on a naming convention to indicate that a variable should be treated as a constant, meaning its value should not be changed throughout the program. Typically, constant variable names are written in uppercase characters.
 
-## Examples
-
-### Example 1: Pi as a Constant
+## Example 1: Pi as a Constant
 
 ```python
 # Define pi as a constant
@@ -18,7 +16,7 @@ area = PI * radius**2
 print(f"The area of a circle with radius {radius} is: {area}")
 ```
 
-### Example 2: Version Number as a Constant
+## Example 2: Version Number as a Constant
 
 ```python
 # Define the version number as a constant

webpage/docs/python-guide/01_Python_Basics/07_Shortcut_Format.md

@@ -1,7 +1,5 @@
 # Shortcut
 
-Have you ever found yourself typing Python code in a hurry, only to realize later that it looks messy and lacks proper formatting? Well, fear not! This README introduces a handy shortcut to quickly format your code and make it more readable.
-
 ## The Problem
 
 Consider the following poorly formatted Python code snippet:

webpage/docs/python-guide/01_Python_Basics/08_Integers.md

@@ -1,12 +1,8 @@
 # Integer Data Type
 
-In this repository, we'll explore Python data types in more detail, focusing on the integer data type. Each data type will be explained thoroughly with code snippets and examples.
-
-## Definition
-
 An integer in Python represents any whole number. It can be positive, negative, or zero.
 
-### Examples
+## Examples
 
 ```python
 # Creating integers

webpage/docs/python-guide/01_Python_Basics/09_Floats.md

@@ -1,11 +1,7 @@
 
 # Floats
 
-In this lesson, we will explore the use of decimal numbers, or floats, in Python. Floats are used to represent numbers with decimal points.
-
-## Examples
-
-### Defining Float Constants
+## Defining Float Constants
 
 ```python
 # Example: Defining pi as a float
@@ -15,14 +11,14 @@ pi: float = 3.1415
 percent: float = 0.50
 ```
 
-### Representing Height in Meters
+## Representing Height in Meters
 
 ```python
 # Example: Defining height in meters as a float
 height_in_meters: float = 1.72
 ```
 
-### Performing Mathematical Operations
+## Performing Mathematical Operations
 
 ```python
 # Example: Performing mathematical operations with floats
@@ -42,7 +38,7 @@ result_multiplication = a * b  # Output: 0.75
 result_division = a / b  # Output: 0.3333333333333333 (approximately 1/3)
 ```
 
-### Type Annotations with Floats
+## Type Annotations with Floats
 
 ```python
 # Example: Type annotations with floats and integers
@@ -55,4 +51,7 @@ float_value: float = 10  # Integer can be assigned to a float
 float_from_int: float = 1.0  # This is compatible
 ```
 
-**Important Note:** While integers can easily be converted to floats, attempting to assign a float to an integer without explicit conversion will result in a warning. Python cannot easily convert a float to an integer without rounding. Even if the float appears as a whole number, like 1.0, it remains incompatible with integers.
+**Important Note:** 
+- While integers can easily be converted to floats, attempting to assign a float to an integer without explicit conversion will result in a warning. 
+- Python cannot easily convert a float to an integer without rounding. 
+- Even if the float appears as a whole number, like 1.0, it remains incompatible with integers.

webpage/docs/python-guide/01_Python_Basics/10_Operators.md

@@ -1,7 +1,5 @@
 # Numeric Operations
 
-In this example, we'll explore the various arithmetic operators available in Python for numeric data types. We'll cover basic arithmetic operators, floor division, exponentiation, modulus, and introduce assignment operators for efficient coding.
-
 ## Arithmetic Operators
 
 ```python
@@ -68,11 +66,7 @@ x %= 3   # Output: 0 (modulus)
 
 Feel free to experiment with these examples to deepen your understanding of Python's numeric operations. If you have any questions or need further clarification, refer to the comments and explanations provided in the code snippets. Happy coding!
 
-# Comparison Operators in Python
-
-This README.md file provides an overview of comparison operators in Python and includes code snippets with examples to illustrate their usage.
-
-## Introduction
+# Comparison Operators
 
 Comparison operators in Python are used to compare values and return a boolean based on the result of the comparison. This can be useful for making decisions in your code based on the relationships between different variables.
 

webpage/docs/python-guide/01_Python_Basics/19_Dictionaries.md

@@ -1,4 +1,3 @@
-
 # Dictionary
 
 In Python, dictionaries provide a convenient way to store data using a key-value pair structure. This part introduces you to the basics of dictionaries and includes code snippets with examples.

webpage/docs/python-guide/01_Python_Basics/20_None.md

@@ -1,4 +1,4 @@
-# None Type in Python
+# None Type
 
 The `None` type in Python is a special data type used to represent the absence of a value or the concept of nothing. It is often returned by certain functions to indicate that no meaningful value is available. 
 

webpage/docs/python-guide/01_Python_Basics/22_Truthy_and_Falsy.md

@@ -1,4 +1,4 @@
-# Truthy and Falsy Values in Python
+# Truthy and Falsy Values
 
 In Python, every object can be categorized as either truthy or falsy. While the most explicit examples are the `True` and `False` booleans, it's important to note that these booleans are essentially constants representing 1 and 0, respectively. You can use any non-zero number as truthy and zero as falsy. For instance, using 1 instead of `True` and 0 instead of `False` is completely valid.
 

webpage/docs/python-guide/01_Python_Basics/23_Comparing_Floats.md

@@ -1,4 +1,4 @@
-# Floating Point Precision in Python
+# Floating Point Precision
 
 Floating-point arithmetic is a fundamental aspect of computational mathematics, yet it presents challenges due to the limitations of precision in representing real numbers. This tutorial critically examines these challenges within the Python programming language and provides rigorous solutions for addressing them using the `isclose` function from the `math` module.
 

webpage/docs/python-guide/01_Python_Basics/24_Scopes.md

@@ -1,4 +1,4 @@
-# Understanding Python Scopes
+#  Scopes
 
 In Python, scopes define the accessibility and lifespan of variables within different regions of a program. Scoping rules determine how variables and names are resolved in nested contexts, affecting how values are assigned, modified, and accessed throughout the code. Understanding Python's scope mechanism is crucial for writing clean, maintainable, and bug-free code. This tutorial provides an in-depth explanation of Python scopes, supplemented by illustrative code snippets.
 

webpage/docs/python-guide/01_Python_Basics/25_Global.md

@@ -1,3 +1,2 @@
 # Global
 
-Write your description or instructions here.

webpage/docs/python-guide/01_Python_Basics/26_Nonlocal.md

@@ -1,3 +1,2 @@
 # Nonlocal
 
-Write your description or instructions here.

webpage/docs/python-guide/01_Python_Basics/27_Doc_Strings.md

@@ -1,3 +1,2 @@
 # Doc Strings
 
-Write your description or instructions here.

webpage/docs/python-guide/01_Python_Basics/28_F-Strings.md

@@ -1,3 +1,2 @@
 # F-Strings
 
-Write your description or instructions here.

webpage/docs/python-guide/01_Python_Basics/29_Assertions.md

@@ -1,3 +1,2 @@
 # Assertions
 
-Write your description or instructions here.