Python 101: Learn the 5 Must-Know Concepts
Tech With Tim
5 Important Python Concepts Every
Developer Should Know
If you're interested in becoming a developer who writes any type
of code in Python, then you need to understand these five
important Python concepts. These are what I see most beginner
and intermediate Python programmers making a ton of mistakes
with and misunderstanding when they're reading through
production code. The goal of this blog is to make sure that when
you're reading through production Python code, you understand
what's happening. You know the concept, and then you can
reproduce that code and write your own pull requests and own
features using Python code that other developers will understand
and expect. So with that said, let's get into the concepts.
Mutable vs Immutable Types
An immutable type is something that cannot change, while a
mutable type is something that can change. Examples of
immutable types in Python include strings, integers, floats,
booleans, bytes, and tuples. Examples of mutable types include
lists, sets, and dictionaries. It's important to understand the
difference between these types because it can affect how your
code behaves. For example, when you make changes to a
mutable object, those changes will be reflected in all variables
that reference that object.
List Comprehensions
List comprehensions are a way to create a new list from an
existing iterable. They allow you to write a for loop inside of a list
and can help simplify code. For example, you can use a list
comprehension to create a list of all even numbers from 0 to 10:
x = [i for i in range(10) if i % 2 == 0]
This will create a list containing the numbers 0, 2, 4, 6, and 8.
Decorator Functions
Tech With Tim
5 Important Python Concepts Every
Developer Should Know
If you're interested in becoming a developer who writes any type
of code in Python, then you need to understand these five
important Python concepts. These are what I see most beginner
and intermediate Python programmers making a ton of mistakes
with and misunderstanding when they're reading through
production code. The goal of this blog is to make sure that when
you're reading through production Python code, you understand
what's happening. You know the concept, and then you can
reproduce that code and write your own pull requests and own
features using Python code that other developers will understand
and expect. So with that said, let's get into the concepts.
Mutable vs Immutable Types
An immutable type is something that cannot change, while a
mutable type is something that can change. Examples of
immutable types in Python include strings, integers, floats,
booleans, bytes, and tuples. Examples of mutable types include
lists, sets, and dictionaries. It's important to understand the
difference between these types because it can affect how your
code behaves. For example, when you make changes to a
mutable object, those changes will be reflected in all variables
that reference that object.
List Comprehensions
List comprehensions are a way to create a new list from an
existing iterable. They allow you to write a for loop inside of a list
and can help simplify code. For example, you can use a list
comprehension to create a list of all even numbers from 0 to 10:
x = [i for i in range(10) if i % 2 == 0]
This will create a list containing the numbers 0, 2, 4, 6, and 8.
Decorator Functions
