7/26/23, 8:16 PM Python 101: Learn the 5 Must-Know Concepts
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
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, 7/26/23, 8:16 PM Python 101: Learn the 5 Must-Know Concepts
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
A decorator function is a function that takes another
function as input and returns a new function.
Decorators can be used to add functionality to an
existing function without modifying its code directly.
For example, you can use a decorator to log the input
and output of a function:
def logger(func): def inner(*args,
**kwargs): print("Input:", args,
kwargs) output = func(*args,
**kwargs) print("Output:",
output) return output return
inner@loggerdef add(x, y): return x +
y
https://solidpoint.ai/s/mMv6OSuitWw 2/6
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
https://solidpoint.ai/s/mMv6OSuitWw 1/6
, 7/26/23, 8:16 PM Python 101: Learn the 5 Must-Know Concepts
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
A decorator function is a function that takes another
function as input and returns a new function.
Decorators can be used to add functionality to an
existing function without modifying its code directly.
For example, you can use a decorator to log the input
and output of a function:
def logger(func): def inner(*args,
**kwargs): print("Input:", args,
kwargs) output = func(*args,
**kwargs) print("Output:",
output) return output return
inner@loggerdef add(x, y): return x +
y
https://solidpoint.ai/s/mMv6OSuitWw 2/6
