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Cheatsheet

Everything You Need to Know About Python

Built-in Types
# primitives
x = 1             # integer
x = 1.2           # float
x = True          # bool
x = None          # null
x = float('inf')  # infinity (float)

# objects
x = [1, 2, 3] # list (Array)
x = (1, 2, 3) # tuple (Immutable Array)
x = {1: "a"}  # dict (HashMap)
x = {1, 2, 3} # set
x = "abc123"  # str (Immutable String)
n = 7
str(n)   # '7'
int('7') #  7

x = [1,2,3]
set(x)   # {1,2,3}
tuple(x) # (1,2,3)

s = {1,2,3}
list(s)  # [3,1,2]  (sets don't store order)

Basic Operations

a = [1] # array with the number 1 in it
b = [1]

a == b  # True, compares value
a is b  # False, compares memory location (exact comparison)

1 / 2    # .5 (division)
1 % 2    # 1 (remainder)
1 // 2   # 0 (division, rounding down)
2 ** 5   # 32 (power, 2^5)

Falsy Values

In Python, you can use anything as a boolean. Things that "feel false" like None, 0, and empty data structures evaluate to False.

a = None
b = []
c = [15]

if a:
    print('This does not print') 
if b:
    print('This does not print') 
if c:
    print('This prints')

Loops with range

for i in range(4):
    # 0 1 2 3

for i in range(1, 4):
    # 1 2 3

for i in range(1, 6, 2): # loop in steps of 2
    # 1 3 5

for i in range(3, -1, -1): # loop backwards
    # 3 2 1 0

Loops over Data Structures

arr = ["a", "b"]
for x in arr:
    # "a" "b"

hmap = {"a": 4, "b": 5}
for x in hmap:
    # "a" "b"

List Features

x = [1,2] + [3,4]  # [1,2,3,4]
x = [0, 7]*2       # [0,7,0,7], don't use this syntax for 2D arrays

x = [0,1,2,3]
x[2:]     # [2,3]
x[:2]     # [0,1]
x[1:4]    # [1,2,3] 
x[3::-1]  # [3,2,1]
x[-1]     # 3

y = reversed(x)  # reversed array of x
x.reverse()      # reverses x in-place using no extra memory
sorted(x)        # sorted array of x
x.sort()         # sorts x in-place using no extra memory

 

List Comprehensions

Python has nice syntax for creating Arrays. Here's an example:

Generator Comprehensions

Generator Comprehensions are List Comprehensions, but they generate values lazily and can stop early. To do a generator comprehension, just use () instead of [].




Note that () can mean a tuple, or it can mean a generator. It just depends on context. You can think of Generator Comprehensions as being implemented exactly the same as List Comprehensions, but replacing the word return with yield (you don't have to know about this for an interview).

String Features





Set Features





Functions

You declare a function using the def keyword:




All variables you declare inside a function in Python are local. In most cases you need to use nonlocal if you want to set variables outside a function, like below with x and y.





Anonymous Functions

You can also declare a function in-line, using the keyword lambda. This is just for convenience. These two statements are both the same function:





Boolean Operators

You can use the any function to check if any value is true, and the all to check if all values are true.





Ternary Operator

Most languages have a "Ternary operator" that gives you a value based on an if statement. Here's Python's:





Newlines

You can write something on multiple lines by escaping the newline, or just using parentheses.





Object Destructuring

You can assign multiple variables at the same time. This is especially useful for swapping variables. Here are a few examples:





Python Reference

Here's a refrence to the offical Python docs.

https://docs.python.org/3/library/index.html

The Built-in Functions and Built-in Types sections are the most useful parts to skim, although it's totally optional reading. The docs are not formatted in a very readable way.

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