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Another Python cheat sheet
- string
- int, float
- lists:
names = ["Scarlett Johansson", "Anne Hathaway", "Jessica Alba"]
- tuples: immutable collections of elements separated by commas and enclosed in parentheses
tup = ('Checkers', 1945, 'Washington')
print(tup)
- sets: mutable collections of objects separated by commas and enclosed in curly brackets or the set function
my_set = set(['Checkers', 1945, 'Washington'])
print(my_set)
- dictionaries: unordered collections that contain key:value pairs separated by commas and enclosed in curly brackets
movies = {"Actresses": ["Scarlett Johansson", "Anne Hathaway", "Jessica Alba"], "Directors": ["Sofia Coppola", "Nacho Vigalondo", "James Cameron"]}
Each Python object can have a name. Python has internal optimizations, for example with integers:
- it uses the same memory slot for integers less than 256
-
num = 7
andnum2 = 7
point to the same memory slot - likewise, values such as
none
ortrue
(orfalse
) point to the same object in memory
num,num2 = 7,2
. While it's possible, don't overuse it. It's less readable.
names = ["Scarlett", "Anne", "Jessica"]
for actress in actresses:
print(actress)
It's a convenient, compact and more readable syntax for lists and loops:
numbers = [n for n in range(112) if n%3 == 0]
print(numbers)
There are comprehensions for sets and dictionaries too.
Read the documentation about exceptions. You must know them.
Python modules are files containing reusable functions, like a toolbox. It's relatively easy to import any module with the keyword import
in other python files, making the code more modular and easier to maintain.
You can import built-in modules, third-party libraries and even your own modules.
An essential module you have to know is the itertools module.
It allows you to handle lists and dictionaries in a very efficient way, optimizing the memory usage.
pip is the package installer for Python. You can use it to download any package or module.
import json
data = {
"fire": "starter"
}
with open("myfile.json", "w") as dest:
json.dump(data, dest, indent="\t")
The above code write JSON data in myfile.json
. Regular expressions Import the re package
Python has the splat operator (*) which is universally used as the multiply operator in math, but Python adds extra functionalities if it's used in front of a variable.
def straight_forward(func, *args, **kwargs):
return func(*args, **kwargs)
With the above function, I can forward any function regardless of the parameters.
Lambda functions are anonymous functions that evaluate expressions only.
def make_lambda(n):
return lambda a: a + n
if __name__ == "__main__":
# code
Python is a great choice if you want to learn machine learning, data science and other trendy topics:
Data is the new Oil
And Python might help you to build your own drilling rig.
When Python is correctly installed on your machine, you can execute Python with Visual Studio code via the terminal. In addition, you'll get helpful and free VS code extensions to speed up your dev.
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