Python Cheatsheet
This page is a quick reference for Python concepts and methods that show up constantly in DSA and competitive programming. If you're just starting out, don't worry, every snippet here is explained line by line 😊
Core Syntax​
Swap, Unpacking, Multiple Assignment​
Swap and unpack values in Python
a, b = b, a # Swaps a and b without a temp variable
x, y, z = 1, 2, 3 # Assigns 1->x, 2->y, 3->z
first, *mid, last = [10, 20, 30, 40] # first=10, mid=[20,30], last=40
Ternary Operator​
Ternary expression in Python
ans = x if x > y else y # Returns x if x > y, otherwise returns y
Built-ins Functions​
zip, enumerate​
zip and enumerate in Python
for i, v in enumerate(arr): # i=index (0,1,2...), v=value (arr[0],arr[1],...)
pass
for a, b in zip(A, B): # Pairs elements from A and B, stops at shortest
pass
map, filter​
map and filter in Python
nums = list(map(int, input().split())) # Reads space-separated integers from input, e.g "1 2 3" -> [1, 2, 3]
evens = list(filter(lambda n: n % 2 == 0, nums)) # Keeps only even numbers, e.g [1,2,3,4] -> [2,4]
sorted, reversed​
sorted and reversed in Python
sorted_nums = sorted(nums) # Returns a new sorted list, original unchanged
sorted_by_key = sorted(pairs, key=lambda p: p[1]) # Sorts pairs by second element
for x in reversed(nums): # Iterates in reverse order without creating a new list
pass
any, all, sum, round​
any, all, sum and round in Python
ok = any(x < 0 for x in nums) # Returns True if at least one element is negative
ok2 = all(x >= 0 for x in nums) # Returns True if all elements are non-negative
s = sum(nums) # Returns sum of all elements
r = round(3.14159, 2) # Rounds to 2 decimal places, i.e r = 3.14
Comprehensions​
Creating/Manipulating List / Set / Dictionary with Conditions​
Comprehensions in Python
squares = [x * x for x in range(10)] # [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
evens = [x for x in range(20) if x % 2 == 0] # [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
unique = {c.lower() for c in "AaBbCC"} # {'a', 'b', 'c'} — duplicates removed
pos = {i: v for i, v in enumerate(nums) if v > 0} # Dict of index->value for positive elements only
collections (Main concepts/functions for DSA)​
collections imports in Python
from collections import defaultdict, Counter, deque, namedtuple
defaultdict​
defaultdict in Python
g = defaultdict(list) # Returns [] for missing keys instead of raising KeyError
g[u].append(v) # Safe to append without checking if key exists first
Counter​
Counter in Python
freq = Counter("banana") # Counts occurrences: {'a':3, 'n':2, 'b':1}
top = freq.most_common(2) # Returns top 2 most frequent: [('a', 3), ('n', 2)]
deque (O(1) pops from both ends)​
deque in Python
q = deque([1, 2, 3]) # deque = [1, 2, 3]
q.append(4) # Add to right, deque = [1, 2, 3, 4]
q.appendleft(0) # Add to left, deque = [0, 1, 2, 3, 4]
q.pop() # Remove right, deque = [0, 1, 2, 3]
q.popleft() # Remove left, deque = [1, 2, 3]
namedtuple​
namedtuple in Python
Point = namedtuple("Point", ["x", "y"]) # Creates a lightweight class with fields x and y
p = Point(2, 5) # p.x = 2, p.y = 5
Strings​
Formatting (f-strings)​
f-strings in Python
name = "Ada"
score = 42
msg = f"{name} scored {score}" # msg = "Ada scored 42"
Common Methods: join, split, replace, strip​
String methods in Python
parts = "a,b,c".split(",") # Splits by comma, parts = ['a', 'b', 'c']
s = "-".join(parts) # Joins with dash, s = "a-b-c"
t = "hello world".replace("world", "python") # t = "hello python"
u = " padded \n".strip() # Removes leading/trailing whitespace, u = "padded"
Functional Tools​
lambda​
lambda in Python
key_fn = lambda p: (p[0], -p[1]) # Anonymous function: sorts by first element asc, second element desc
functools.partial​
functools partial in Python
from functools import partial
def add(a, b):
return a + b
add10 = partial(add, 10) # Fixes first argument as 10
add10(5) # i.e 10 + 5 = 15
lru_cache (Memoization)​
lru_cache memoization in Python
from functools import lru_cache
@lru_cache(maxsize=None) # Caches results of previous calls, avoids recomputation
def fib(n):
if n < 2:
return n
return fib(n - 1) + fib(n - 2) # fib(5) -> 5, computed once and cached
Iteration Patterns (itertools)​
itertools import in Python
import itertools as it
combinations, permutations, product​
Combinations permutations and product in Python
list(it.combinations([1, 2, 3, 4], 2)) # All 2-element combos (order doesn't matter): [(1,2),(1,3),...]
list(it.permutations([1, 2, 3], 2)) # All 2-element arrangements (order matters): [(1,2),(1,3),...]
list(it.product([0, 1], repeat=3)) # Cartesian product: [(0,0,0),(0,0,1),(0,1,0),...]
Error Handling and Context Managers​
try/except/finally​
try except finally in Python
try:
x = int("42") # Attempts to parse string to int
except ValueError:
x = 0 # Runs if parsing fails
finally:
pass # Always runs regardless of exception
with (Context Managers)​
Context manager with statement in Python
with open("input.txt", "r", encoding="utf-8") as f: # Automatically closes file after block
data = f.read() # Reads entire file content into data
OOP Basics​
Classes, Inheritance​
Class inheritance in Python
class Base:
def ping(self):
return "base" # Default implementation
class Child(Base):
def ping(self):
return "child" # Overrides Base's ping()
c = Child()
print(c.ping()) # "child"
Abstract Base Classes (ABC)​
Abstract base class in Python
from abc import ABC, abstractmethod
class Solver(ABC):
@abstractmethod
def solve(self) -> int: # Subclasses must implement solve(), cannot instantiate Solver directly
raise NotImplementedError
__slots__ (Memory Optimization)​
slots in Python
class Node:
__slots__ = ("val", "next") # Restricts attributes to only val and next, reduces memory usage
def __init__(self, val, nxt=None):
self.val = val
self.next = nxt
n = Node(1) # n.val = 1, n.next = None
Advanced Topics​
Generators​
Generator function in Python
def gen(n):
for i in range(n):
yield i * i # Yields one value at a time instead of building a full list
list(gen(4)) # [0, 1, 4, 9] — generated lazily
Coroutines (Async Basics)​
Async coroutine in Python
import asyncio
async def task():
await asyncio.sleep(0.1) # Non-blocking wait, allows other tasks to run
return 1
dataclasses​
dataclass in Python
from dataclasses import dataclass
@dataclass
class Edge:
u: int
v: int
w: int = 1 # Default weight is 1
e = Edge(0, 1) # e.u=0, e.v=1, e.w=1
e2 = Edge(0, 1, 5) # e2.u=0, e2.v=1, e2.w=5
Walrus Operator (:=)​
Walrus operator in Python
if (n := len(nums)) > 0: # Assigns len(nums) to n and checks if > 0 in one step
avg = sum(nums) / n # Reuses n without calling len() again