Today we’re gonna talk about type systems in programming languages and how they relate to Python. In particular, let’s focus on dynamic typing a feature that makes Python so popular among developers.

A type system is an important part of any programming language because it helps us keep track of the different types of data we can work with. For example, a numerical type might include numbers like 42 or 3.14. In statically typed languages (like C), you have to declare what kind of variable you’re working with before you use it this is called “type annotation”.

But in Python, we don’t need to do that! That’s because Python is a dynamically typed language. This means that the interpreter doesn’t check for type errors until code actually runs. For example:

# Declare variables with type annotations
x: int = 5 # x has numerical type (int)
y: str = "hello" # y now has string type

# Perform addition operation
z: str = x + y # implicit conversion from str to int happens here!

# Print the result
print(z)

In this code snippet, we’re assigning a value of `5` to the variable `x`. Since Python knows that `x` is being assigned an integer (because it can see what kind of data is being passed in), it automatically sets its type to numerical. But then we do something unexpected we assign a string (“hello”) to the variable `y`. This changes the type of `y` from numerical to string.

When we try to add these two variables together (using the `+` operator), Python has to convert one of them into a number so that it can perform the addition. In this case, since `x` is already a number, Python converts `y` (which is now a string) into an integer using implicit conversion. The result is a new variable called `z`, which contains the sum of 5 and “hello” converted to an integer.

This might seem like magic at first, but it’s actually pretty straightforward once you understand how Python works! And if we need more control over type conversions (like converting a float into an integer), we can use explicit conversion functions or operators instead of relying on implicit conversion.

Remember, while dynamic typing is convenient for quick prototyping and experimentation, it’s not always the best choice for large-scale projects with complex data structures. But if you’re just getting started with programming or working on a small project, give it a try!

Today we’re gonna talk about type systems in programming languages and how they relate to Python. In particular, let’s focus on dynamic typing a feature that makes Python so popular among developers. A type system is an important part of any programming language because it helps us keep track of the different types of data we can work with. For example, a numerical type might include numbers like 42 or 3.14. In statically typed languages (like C), you have to declare what kind of variable you’re working with before you use it this is called “type annotation”. But in Python, we don’t need to do that! That’s because Python is a dynamically typed language. This means that the interpreter doesn’t check for type errors until code actually runs. For example:

# Declare x as an integer with value 5
x: int = 5

# Declare y as a string with value "hello"
y: str = "hello"

# Add x and y together, resulting in an error due to incompatible types
# Corrected by converting y to an integer before adding
z: int = x + int(y)

# Print the result of z
print(z)

In this code snippet, we’re assigning a value of `5` to the variable `x`. Since Python knows that `x` is being assigned an integer (because it can see what kind of data is being passed in), it automatically sets its type to numerical. But then we do something unexpected we assign a string (“hello”) to the variable `y`. This changes the type of `y` from numerical to string. When we try to add these two variables together (using the `+` operator), Python has to convert one of them into a number so that it can perform the addition. In this case, since `x` is already a number, Python converts `y` (which is now a string) into an integer using implicit conversion. The result is a new variable called `z`, which contains the sum of 5 and “hello” converted to an integer. This might seem like magic at first, but it’s actually pretty straightforward once you understand how Python works! And if we need more control over type conversions (like converting a float into an integer), we can use explicit conversion functions or operators instead of relying on implicit conversion. Remember, while dynamic typing is convenient for quick prototyping and experimentation, it’s not always the best choice for large-scale projects with complex data structures. But if you’re just getting started with programming or working on a small project, give it a try!