Python Notes
HubHistory of Python - Complete Guide 2026Python Applications - Complete Guide 2026Python Features - Complete Guide 2026What is Python? - Complete Guide 2026Why Learn Python? - Complete Guide 2026Your First Python Program – Hello World & Beyond 2026How to Install Python on Windows, Mac & Linux – Complete Guide 2026Install VS Code for Python – Complete Setup Guide with Extensions 2026Python Environment Setup – Virtual Environments, pip & Project Structure 2026Python IDLE – Complete Guide for Beginners 2026Python CommentsPython Data TypesPython Input and OutputPython OperatorsPython SyntaxPython Strings BasicsPython Type CastingPython VariablesBreak, Continue and Pass in PythonElif Statement in PythonFor Loop in PythonIf-Else Statement in PythonIf Statement in PythonNested If in PythonPattern Programs in PythonWhile Loop in PythonDecorators in PythonFunction Arguments in PythonFunctions Basics in PythonGenerators in PythonLambda Functions in PythonRecursive Functions in PythonReturn Statement in PythonScope of Variables in PythonAbstraction in PythonClasses and Objects in PythonConstructors in PythonEncapsulation in PythonInheritance in PythonMagic Methods (Dunder Methods) in PythonMethod Overriding in PythonPolymorphism in PythonPython Comprehensions – List, Dict, Set & GeneratorPython Dictionaries – Key-Value StorePython Dictionary Methods – Complete ReferencePython List Methods – All Built-in MethodsPython Lists – Complete GuidePython Set Methods – Complete ReferencePython Sets – Unordered Unique CollectionsPython Tuples – Immutable SequencesPython Asynchronous Programming with asyncioPython Context ManagersAdvanced Python DecoratorsAdvanced Python GeneratorsPython Iterators - Advanced GuidePython Memory ManagementPython MultiprocessingPython MultithreadingCRUD Operations in Python DatabasesMySQL with Python (mysql-connector-python)ORM Introduction with SQLAlchemyPostgreSQL with Python (psycopg2)SQLite3 with PythonIntroduction to DjangoDjango Models and ORMDjango REST API with DRFDjango ViewsIntroduction to FlaskFlask RoutingFlask Templates with Jinja2Email Automation with PythonPDF Automation with PythonSelenium Web Automation with PythonTask Scheduler with PythonWeb Scraping with PythonData Analysis with PythonData Cleaning with PythonData Visualization ProjectData Visualization with MatplotlibNumPy IntroductionPandas IntroductionStatistical Visualization with SeabornClassification AlgorithmsClustering AlgorithmsIntroduction to Machine LearningMachine Learning Project: Churn PredictionModel Evaluation and SelectionRegression AlgorithmsSave pipeline (includes preprocessing + model)AI Assistant ProjectCalculator ProjectChatbot ProjectExpense Tracker ProjectFace Detection ProjectPassword Generator ProjectWeather App ProjectPython Coding Interview QuestionsPython OOP Interview Questions and AnswersPython Master CheatsheetPython Interview Questions and AnswersPython Best PracticesCommon Python Errors and SolutionsPython Debugging TechniquesPython Learning Resources
Comprehensive Python cheatsheet covering all important syntax, data structures, functions, OOP, libraries, and interview tips in one place with Hindi explanations.
Complete Python Reference Guide
Yeh cheatsheet Python ke saare important concepts ek jagah cover karta hai — interview se production code tak!
2. Operators
python example
# Arithmetic
5 + 3 # 8
5 - 3 # 2
5 * 3 # 15
5 / 3 # 1.667 (float division)
5 // 3 # 1 (floor division)
5 % 3 # 2 (modulus)
5 ** 3 # 125 (power)
# Comparison
== != < > <= >=
# Logical
and or not
# Identity
x is y # Same object?
x is not y
# Membership
x in lst # Is x in lst?
x not in lst
# Bitwise
& | ^ ~ << >>
# Walrus (Python 3.8+)
if (n := len(lst)) > 3:
print(f"Long list: {n}")3. String Operations
Example
s = "Hello, Python World!"
# Basic operations
len(s) # 20
s.upper() # "HELLO, PYTHON WORLD!"
s.lower() # "hello, python world!"
s.title() # "Hello, Python World!"
s.capitalize() # "Hello, python world!"
s.strip() # Remove leading/trailing whitespace
s.lstrip() # Left strip
s.rstrip() # Right strip
s.strip("!") # Remove specific chars
# Searching
s.find("Python") # 7 (index, -1 if not found)
s.index("Python") # 7 (index, ValueError if not found)
s.count("l") # 3
s.startswith("Hello") # True
s.endswith("!") # True
"Hello" in s # True
# Modifying
s.replace("World", "Universe") # New string
s.split(", ") # ['Hello', 'Python World!']
s.split() # Split on whitespace
", ".join(["a", "b", "c"]) # "a, b, c"
# Formatting
f"Hello, {name}!" # f-string
"Hello, {}!".format("World") # .format()
"%.2f" % 3.14159 # % formatting
f"{3.14159:.2f}" # f-string format
f"{1000000:,}" # "1,000,000"
f"{'center':^20}" # Centered in 20 chars
f"{'left':<20}" # Left aligned
f"{'right':>20}" # Right aligned
# Slicing
s[0] # 'H'
s[-1] # '!'
s[0:5] # 'Hello'
s[7:] # 'Python World!'
s[:5] # 'Hello'
s[::2] # Every other character
s[::-1] # Reverse string
# Check
s.isdigit() # All digits?
s.isalpha() # All letters?
s.isalnum() # All alphanumeric?
s.isupper() # All uppercase?
s.islower() # All lowercase?
s.isspace() # All whitespace?
4. List Operations
Example
lst = [3, 1, 4, 1, 5, 9, 2, 6]
# Add
lst.append(7) # Add to end
lst.insert(0, 0) # Insert at index
lst.extend([8, 9]) # Add multiple items
# Remove
lst.remove(1) # Remove first occurrence
popped = lst.pop() # Remove and return last
popped = lst.pop(2) # Remove and return at index
lst.clear() # Remove all
# Search
lst.index(5) # First occurrence index
lst.count(1) # Count occurrences
5 in lst # Membership check
# Sort
lst.sort() # In-place sort (ascending)
lst.sort(reverse=True) # Descending
lst.sort(key=lambda x: abs(x)) # Custom key
sorted(lst) # New sorted list
# Other
lst.reverse() # Reverse in-place
lst.copy() # Shallow copy
len(lst) # Length
sum(lst) # Sum
min(lst), max(lst) # Min, max
lst * 3 # [1,2,3,1,2,3,1,2,3]
lst1 + lst2 # Concatenate
# Slicing
lst[2:5] # Elements 2 to 4
lst[::2] # Every other
lst[::-1] # Reversed copy
# Comprehension
squares = [x**2 for x in range(10)]
evens = [x for x in lst if x % 2 == 0]
matrix_flat = [x for row in matrix for x in row]
5. Dictionary Operations
Example
d = {"name": "Alice", "age": 25, "city": "Delhi"}
# Access
d["name"] # "Alice" (KeyError if missing)
d.get("name") # "Alice" (None if missing)
d.get("phone", "N/A") # "N/A" (default if missing)
# Modify
d["email"] = "alice@example.com" # Add/update
d.update({"phone": "9876543210"}) # Update multiple
d.pop("age") # Remove and return
d.setdefault("level", "beginner") # Set if missing
# Views
d.keys() # dict_keys(['name', 'city', ...])
d.values() # dict_values(['Alice', 'Delhi', ...])
d.items() # dict_items([('name', 'Alice'), ...])
# Iteration
for key in d:
print(key, d[key])
for key, value in d.items():
print(f"{key}: {value}")
# Comprehension
squared = {k: v**2 for k, v in {"a": 2, "b": 3}.items()}
filtered = {k: v for k, v in d.items() if len(str(v)) > 3}
# Merge (Python 3.9+)
merged = d1 | d2 # New merged dict
d1 |= d2 # Update d1 with d2
# Useful patterns
from collections import defaultdict, Counter, OrderedDict
# defaultdict
dd = defaultdict(list)
dd["fruits"].append("apple")
dd["fruits"].append("banana")
print(dd) # defaultdict(<class 'list'>, {'fruits': ['apple', 'banana']})
# Counter
c = Counter(["a", "b", "a", "c", "a", "b"])
print(c.most_common(2)) # [('a', 3), ('b', 2)]
6. Set Operations
Example
s1 = {1, 2, 3, 4, 5}
s2 = {4, 5, 6, 7, 8}
# Basic operations
s1.add(6) # Add element
s1.remove(6) # Remove (KeyError if missing)
s1.discard(99) # Remove safely (no error)
s1.pop() # Remove arbitrary element
# Set operations
s1 | s2 # Union {1,2,3,4,5,6,7,8}
s1 & s2 # Intersection {4,5}
s1 - s2 # Difference {1,2,3}
s1 ^ s2 # Symmetric difference {1,2,3,6,7,8}
# Methods
s1.union(s2)
s1.intersection(s2)
s1.difference(s2)
s1.issubset(s2)
s1.issuperset(s2)
s1.isdisjoint(s2) # No common elements?
# Frozen set — immutable set
fs = frozenset([1, 2, 3])
# fs.add(4) # AttributeError!
7. Functions
Example
# Basic function
def greet(name, greeting="Hello"):
"""Docstring — always add!"""
return f"{greeting}, {name}!"
# *args — variable positional arguments
def total(*numbers):
return sum(numbers)
total(1, 2, 3, 4) # 10
# **kwargs — variable keyword arguments
def create(**details):
return details
create(name="Alice", age=25) # {'name': 'Alice', 'age': 25}
# Keyword-only arguments
def format_text(text, *, width=80, align="left"):
pass # width and align must be keyword args!
# Type hints
def add(a: int, b: int) -> int:
return a + b
# Lambda
square = lambda x: x ** 2
add = lambda a, b: a + b
# Higher-order functions
nums = [1, 2, 3, 4, 5]
squared = list(map(lambda x: x**2, nums))
evens = list(filter(lambda x: x%2==0, nums))
from functools import reduce
product = reduce(lambda x,y: x*y, nums) # 120
# Closures
def multiplier(factor):
def multiply(x):
return x * factor # factor from outer scope
return multiply
double = multiplier(2)
triple = multiplier(3)
print(double(5)) # 10
print(triple(5)) # 15
# Decorators
import functools
def my_decorator(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
print("Before")
result = func(*args, **kwargs)
print("After")
return result
return wrapper
@my_decorator
def say_hello():
print("Hello!")
8. OOP Cheatsheet
python example
class Animal:
species = "Mammal" # Class variable
def __init__(self, name, sound):
self.name = name # Instance variable
self._sound = sound # Protected
self.__secret = "hidden" # Private (name mangling)
def speak(self): # Instance method
return f"{self.name}: {self._sound}"
@classmethod
def get_species(cls): # Class method
return cls.species
@staticmethod
def is_valid_name(name): # Static method
return isinstance(name, str) and len(name) > 0
@property
def info(self): # Property (getter)
return f"{self.name} ({self.species})"
def __str__(self): # String representation
return self.name
def __repr__(self): # Developer repr
return f"Animal('{self.name}', '{self._sound}')"
def __eq__(self, other): # Equality
return self.name == other.name
class Dog(Animal):
def __init__(self, name, breed):
super().__init__(name, "Woof") # Parent init
self.breed = breed
def speak(self): # Override
return f"{super().speak()}! (I'm a {self.breed})"
# Abstract classes
from abc import ABC, abstractmethod
class Shape(ABC):
@abstractmethod
def area(self) -> float:
pass
# MRO
class A: pass
class B(A): pass
class C(A): pass
class D(B, C): pass
print(D.__mro__) # (D, B, C, A, object)9. Exception Handling
Example
# Basic
try:
result = 10 / 0
except ZeroDivisionError as e:
print(f"Error: {e}")
except (ValueError, TypeError) as e:
print(f"Multiple: {e}")
else:
print("No exception!")
finally:
print("Always runs")
# Raise exception
raise ValueError("Custom error message")
# Exception hierarchy
BaseException
├── SystemExit
├── KeyboardInterrupt
└── Exception
├── ValueError
├── TypeError
├── IndexError
├── KeyError
├── AttributeError
├── IOError/OSError
└── ...
# Custom exception
class CustomError(Exception):
def __init__(self, message, code=None):
super().__init__(message)
self.code = code
raise CustomError("Something went wrong", code=404)
# Context manager for cleanup
with open("file.txt") as f:
data = f.read()
# File auto-closed!
# suppress specific exceptions
from contextlib import suppress
with suppress(FileNotFoundError):
os.remove("nonexistent.txt")
10. File I/O
Example
import os
# Text file
with open("file.txt", "r") as f:
content = f.read() # Entire file
lines = f.readlines() # List of lines
for line in f: # Line by line (memory efficient)
pass
with open("file.txt", "w") as f: # Write (overwrites)
f.write("Hello\n")
f.writelines(["line1\n", "line2\n"])
with open("file.txt", "a") as f: # Append
f.write("New line\n")
# Binary file
with open("image.jpg", "rb") as f:
data = f.read()
with open("copy.jpg", "wb") as f:
f.write(data)
# File modes: r, w, a, x(exclusive), b(binary), +(read+write)
# "r" — read (default)
# "w" — write (creates/truncates)
# "a" — append
# "rb" — read binary
# "w+" — read+write
# Path operations
import os.path as path
from pathlib import Path # Modern approach
# os.path
path.exists("file.txt")
path.isfile("file.txt")
path.isdir("folder")
path.join("dir", "file.txt")
path.dirname("/path/to/file.txt") # "/path/to"
path.basename("/path/to/file.txt") # "file.txt"
# pathlib (modern)
p = Path("dir/file.txt")
p.exists()
p.name # "file.txt"
p.stem # "file"
p.suffix # ".txt"
p.parent # Path("dir")
p.read_text() # Read file content
p.write_text("content") # Write file
list(p.parent.glob("*.txt")) # Find files
# JSON
import json
data = {"name": "Alice", "age": 25}
json_str = json.dumps(data, indent=2) # Dict to JSON string
parsed = json.loads(json_str) # JSON string to dict
with open("data.json", "w") as f:
json.dump(data, f, indent=2) # Write to file
with open("data.json", "r") as f:
loaded = json.load(f) # Read from file
# CSV
import csv
# Write
with open("data.csv", "w", newline="") as f:
writer = csv.DictWriter(f, fieldnames=["name", "age"])
writer.writeheader()
writer.writerow({"name": "Alice", "age": 25})
# Read
with open("data.csv", "r") as f:
reader = csv.DictReader(f)
for row in reader:
print(row)
11. Comprehensions Summary
Example
# List comprehension
[expr for x in iterable]
[expr for x in iterable if condition]
[expr for x in a for y in b] # Nested
# Dict comprehension
{k: v for k, v in items}
{k: v for k, v in items if condition}
# Set comprehension
{expr for x in iterable}
# Generator expression
(expr for x in iterable)
sum(x**2 for x in range(100))
# Examples
squares = [x**2 for x in range(10)]
even_squares = [x**2 for x in range(10) if x%2==0]
word_lengths = {w: len(w) for w in ["apple", "banana", "cherry"]}
unique_vowels = {c for c in "Hello World" if c in "aeiouAEIOU"}
flat = [x for row in [[1,2],[3,4]] for x in row]
12. Itertools & Functools
Example
import itertools as it
from functools import partial, lru_cache, reduce
# itertools
it.count(1, 2) # 1, 3, 5, 7... (infinite)
it.cycle([1,2,3]) # 1, 2, 3, 1, 2, 3... (infinite)
it.repeat(5, 3) # 5, 5, 5
it.chain([1,2],[3,4]) # 1, 2, 3, 4
it.islice(gen, 10) # First 10
it.product([1,2],[3,4]) # Cartesian product
it.permutations([1,2,3],2) # Permutations
it.combinations([1,2,3],2) # Combinations
it.accumulate([1,2,3,4], lambda x,y: x+y) # [1,3,6,10]
it.groupby(sorted_data, key=lambda x: x[0]) # Group by key
it.takewhile(lambda x: x<5, count(0)) # Take while condition
it.dropwhile(lambda x: x<5, count(0)) # Drop while condition
# functools
@lru_cache(maxsize=128) # Memoization
def fib(n):
if n <= 1: return n
return fib(n-1) + fib(n-2)
double = partial(lambda x, y: x * y, 2) # Partial application
print(double(5)) # 10
total = reduce(lambda x, y: x + y, [1, 2, 3, 4, 5]) # 15
import functools
@functools.wraps # Copy function metadata in decorators
13. Concurrency Cheatsheet
Example
# Threading (I/O bound)
import threading
t = threading.Thread(target=func, args=(arg1,), daemon=True)
t.start()
t.join()
lock = threading.Lock()
with lock:
# critical section
pass
# Multiprocessing (CPU bound)
from multiprocessing import Process, Pool
p = Process(target=func, args=(arg1,))
p.start()
p.join()
with Pool(4) as pool:
results = pool.map(func, [1, 2, 3, 4])
# Asyncio (I/O bound, single thread)
import asyncio
async def main():
await asyncio.sleep(1)
results = await asyncio.gather(coro1(), coro2())
asyncio.run(main())
# concurrent.futures (high-level)
from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor
with ThreadPoolExecutor(max_workers=10) as executor:
futures = [executor.submit(func, arg) for arg in args]
results = [f.result() for f in futures]
14. Regex Cheatsheet
Example
import re
text = "Phone: +91-9876543210, Email: alice@gmail.com"
# Basic patterns
re.findall(r'\d+', text) # All digits
re.search(r'\w+@\w+\.\w+', text) # Email search
re.match(r'Hello', "Hello World") # Match at start
re.fullmatch(r'\d+', "12345") # Full string match
re.sub(r'\d', 'X', text) # Replace digits with X
re.split(r'[,\s]+', "a, b, c d") # Split on comma/space
# Patterns
. # Any character (except newline)
\d # Digit [0-9]
\D # Non-digit
\w # Word char [a-zA-Z0-9_]
\W # Non-word char
\s # Whitespace
\S # Non-whitespace
\b # Word boundary
^ # Start of string
$ # End of string
* # 0 or more
+ # 1 or more
? # 0 or 1
{n} # Exactly n times
{n,m} # n to m times
[abc] # Character class
[^abc] # Not in class
(a|b) # Alternation
(group) # Capture group
(?:group) # Non-capture group
# Flags
re.IGNORECASE # Case insensitive
re.MULTILINE # ^ and $ match line boundaries
re.DOTALL # . matches newline too
re.VERBOSE # Allow comments in pattern
15. Common Built-in Functions
Example
# Math
abs(-5) # 5
round(3.14159, 2) # 3.14
max(1, 2, 3) # 3
min(1, 2, 3) # 1
sum([1,2,3]) # 6
divmod(10, 3) # (3, 1)
pow(2, 10) # 1024
pow(2, 10, 100) # 1024 % 100 = 24
# Sequences
len([1,2,3]) # 3
sorted([3,1,2]) # [1, 2, 3]
reversed([1,2,3]) # iterator
enumerate([a,b]) # (0,a),(1,b)...
zip([1,2],[3,4]) # (1,3),(2,4)...
map(func, lst) # Apply func
filter(pred, lst) # Filter
any([T,F,F]) # True
all([T,T,T]) # True
# Type functions
type(x) # Type of x
isinstance(x, T) # Is x instance of T?
id(x) # Memory address
# I/O
print("Hello", end="\n", sep=" ")
input("Enter: ")
open("file.txt", "r")
# Others
range(10) # 0 to 9
range(1, 10, 2) # 1, 3, 5, 7, 9
hash(x) # Hash value
vars(obj) # __dict__ of object
dir(obj) # Attributes and methods
help(func) # Documentation
16. Python Best Practices — PEP 8 Quick Guide
python example
# Naming conventions
variable_name = "snake_case" # Variables
CONSTANT_VALUE = 42 # Constants
ClassName = "PascalCase" # Classes
_private = "single underscore" # Private by convention
__name_mangling = "dunder" # Private with mangling
# Spacing
x = 1 + 2 # Spaces around operators
def func(a, b): # Spaces after commas
pass # 4-space indentation
# Line length: max 79 chars (PEP 8) or 120 (PEP 8 relaxed)
# Imports (order: stdlib > third-party > local)
import os
import sys
import requests
import numpy as np
from mymodule import MyClass
# String formatting: prefer f-strings
name = "Alice"
greeting = f"Hello, {name}!" # ✅
greeting = "Hello, " + name + "!" # ❌ (concatenation)
greeting = "Hello, {}!".format(name) # OK but verbose
# Comparisons
if x is None: # ✅ (not ==)
if x is True: # ✅ (not ==)
if not x: # ✅ (truthy check)
if len(lst) == 0: # ❌
if not lst: # ✅
# Docstrings
def function(arg):
"""
Brief description.
Args:
arg: Description of argument
Returns:
Description of return value
Raises:
ValueError: When...
"""
passQuick Interview Reference
Example
# Most asked Python interview topics:
# 1. Data types & mutability
mutable = [list, dict, set, bytearray]
immutable = [int, float, str, tuple, frozenset, bytes]
# 2. List vs Tuple
lst = [1, 2, 3] # Mutable, slightly slower
tpl = (1, 2, 3) # Immutable, faster, hashable
# 3. == vs is
x = [1, 2]; y = [1, 2]
x == y # True (same value)
x is y # False (different objects)
None check: if x is None (not ==)
# 4. Deep vs Shallow copy
import copy
shallow = lst.copy() # copy.copy(lst)
deep = copy.deepcopy(lst) # Nested also copied
# 5. *args, **kwargs
def f(*args, **kwargs):
print(args) # tuple of positional
print(kwargs) # dict of keyword
# 6. Decorators
@decorator
def func(): pass
# Same as: func = decorator(func)
# 7. Generators
def gen(): yield 1; yield 2
# Lazy evaluation, memory efficient
# 8. Context managers
with open("f") as f: pass
# __enter__ and __exit__
# 9. GIL
# CPython: one thread at a time
# I/O bound: use threading
# CPU bound: use multiprocessing
# 10. List comprehension
[x**2 for x in range(10) if x%2==0]
Final Tip: Revision ke liye yeh cheatsheet print karo! Interviews mein concepts ke saath code examples dikhao. Practice makes perfect — LeetCode, HackerRank pe daily practice karo.
WoHoTech Python Master Course — Complete Syllabus
| Section | Topics |
|---|---|
| Advanced Python | Iterators, Generators, Decorators, Context Managers, Multithreading, Multiprocessing, Asyncio, Memory Management |
| Databases | SQLite3, MySQL, PostgreSQL, CRUD, SQLAlchemy ORM |
| Automation | Web Scraping, Selenium, Email, PDF, Task Scheduler |
| Interview Prep | Python Q&A, Coding Questions, OOP Q&A, Cheatsheet |
WoHoTech ke saath Python Master karo! 🚀
📤 Code Output Examples
Neeche kuch important code snippets ke outputs diye gaye hain jo interview mein commonly puchhe jaate hain:
python example
# Data Types Output
x = 42
print(type(x))
print(isinstance(x, int))
print(isinstance(x, (int, float)))Output
<class 'int'> True True
Example
# Type Conversion
print(list("hello"))
print(set([1, 1, 2, 3]))
print(bool(0), bool(""), bool([]), bool(None))
print(bool(1), bool("hi"))
Output
['h', 'e', 'l', 'l', 'o']
{1, 2, 3}
False False False False
True TrueExample
# Walrus Operator
lst = [1, 2, 3, 4, 5]
if (n := len(lst)) > 3:
print(f"Long list: {n}")
Output
Long list: 5
Example
# String Operations
s = "Hello, Python World!"
print(s.find("Python"))
print(s.count("l"))
print(s[::2])
print(s[::-1])
Output
7 3 Hlo yhnWrd !dlroW nohtyP ,olleH
python example
# f-string formatting
print(f"{3.14159:.2f}")
print(f"{1000000:,}")
print(f"{'center':^20}")Output
3.14
1,000,000
center Example
# List Comprehension
squares = [x**2 for x in range(6)]
evens = [x for x in range(10) if x % 2 == 0]
print(squares)
print(evens)
Output
[0, 1, 4, 9, 16, 25] [0, 2, 4, 6, 8]
Example
# Dictionary Operations
from collections import Counter
c = Counter(["a", "b", "a", "c", "a", "b"])
print(c.most_common(2))
Output
[('a', 3), ('b', 2)]python example
# Set Operations
s1 = {1, 2, 3, 4, 5}
s2 = {4, 5, 6, 7, 8}
print(s1 | s2)
print(s1 & s2)
print(s1 - s2)
print(s1 ^ s2)Output
{1, 2, 3, 4, 5, 6, 7, 8}
{4, 5}
{1, 2, 3}
{1, 2, 3, 6, 7, 8}python example
# Closures
def multiplier(factor):
def multiply(x):
return x * factor
return multiply
double = multiplier(2)
triple = multiplier(3)
print(double(5))
print(triple(5))Output
10 15
python example
# Generators
def gen():
yield 1
yield 2
yield 3
g = gen()
print(next(g))
print(next(g))
print(list(gen()))Output
1 2 [1, 2, 3]
python example
# MRO (Method Resolution Order)
class A: pass
class B(A): pass
class C(A): pass
class D(B, C): pass
print(D.__mro__)Output
(<class 'D'>, <class 'B'>, <class 'C'>, <class 'A'>, <class 'object'>)
Example
# functools reduce
from functools import reduce
product = reduce(lambda x, y: x * y, [1, 2, 3, 4, 5])
print(product)
Output
120
Example
# Deep vs Shallow Copy
import copy
original = [[1, 2], [3, 4]]
shallow = copy.copy(original)
deep = copy.deepcopy(original)
original[0][0] = 99
print(f"Original: {original}")
print(f"Shallow: {shallow}")
print(f"Deep: {deep}")
Output
Original: [[99, 2], [3, 4]] Shallow: [[99, 2], [3, 4]] Deep: [[1, 2], [3, 4]]
⚠️ Common Mistakes
Python beginners aur even experienced developers yeh mistakes commonly karte hain. Interview mein bhi yeh topics puchhe jaate hain! 🎯
1. Mutable Default Arguments ❌
Example
# ❌ WRONG — list share hoti hai across calls!
def add_item(item, lst=[]):
lst.append(item)
return lst
print(add_item("a")) # ['a']
print(add_item("b")) # ['a', 'b'] — Unexpected! 😱
# ✅ CORRECT — None use karo as default
def add_item(item, lst=None):
if lst is None:
lst = []
lst.append(item)
return lst
2. == vs is Confusion ❌
python example
# ❌ WRONG
if x == None: # Works but not Pythonic
pass
# ✅ CORRECT
if x is None: # Identity check for singletons
pass
# Note: Small integers (-5 to 256) are cached in CPython
a = 256; b = 256
print(a is b) # True (cached)
a = 257; b = 257
print(a is b) # False (not cached — different objects!)3. Modifying List During Iteration ❌
Example
# ❌ WRONG — list size change hota hai during loop!
nums = [1, 2, 3, 4, 5]
for n in nums:
if n % 2 == 0:
nums.remove(n)
print(nums) # [1, 3, 5]? NAHI! → [1, 3, 5] sometimes skip hota hai
# ✅ CORRECT — new list banao ya copy iterate karo
nums = [x for x in nums if x % 2 != 0]
4. Variable Scope — UnboundLocalError ❌
python example
# ❌ WRONG
count = 0
def increment():
count += 1 # UnboundLocalError! 😵
# ✅ CORRECT — global ya nonlocal use karo
count = 0
def increment():
global count
count += 15. Shallow Copy Trap ❌
Example
# ❌ WRONG — nested objects share hote hain!
original = [[1, 2], [3, 4]]
shallow = original.copy()
shallow[0][0] = 99
print(original[0][0]) # 99 — Original bhi change ho gaya! 😱
# ✅ CORRECT — deepcopy use karo for nested
import copy
deep = copy.deepcopy(original)
6. String Immutability Confusion ❌
Example
# ❌ WRONG — Strings are immutable!
s = "hello"
# s[0] = "H" # TypeError!
# ✅ CORRECT — new string banao
s = "H" + s[1:] # "Hello"
7. Late Binding in Closures ❌
Example
# ❌ WRONG — sab functions last value use karte hain!
funcs = [lambda: i for i in range(5)]
print([f() for f in funcs]) # [4, 4, 4, 4, 4] — Sab 4! 😱
# ✅ CORRECT — default argument se bind karo
funcs = [lambda i=i: i for i in range(5)]
print([f() for f in funcs]) # [0, 1, 2, 3, 4] ✅
✅ Key Takeaways
Yeh Python cheatsheet ke most important points hain jo aapko hamesha yaad rakhne chahiye: 💡
- 🐍 Mutable vs Immutable samajhna zaroori hai — list/dict/set mutable hain, str/tuple/int immutable. Interview mein yeh first question hota hai!
- 📝 f-strings use karo formatting ke liye — concatenation se avoid karo. Clean, fast, aur readable hai.
- 🔄 List comprehensions loops se zyada Pythonic aur fast hain — but readability sacrifice mat karo complex cases mein.
- 🧠 Generators use karo large data ke liye — memory efficient hain kyunki lazy evaluation karte hain.
- 🎭 Decorators samajhna must hai — Flask, Django, testing sab mein use hote hain.
@functools.wrapslagana mat bhoolna! - 📦 **
*argsaurkwargsflexible functions likhne ke liye essential hain — interview mein hamesha puchha jaata hai. - 🔒 Context managers (
withstatement) use karo file handling aur resource cleanup ke liye — manually close karna risky hai. - ⚡ Exception handling properly karo — bare
except:kabhi mat likho, specific exceptions catch karo. - 🧪
isvs==ka difference yaad rakho —isidentity check hai,==value comparison.Noneke liye hameshaisuse karo. - 🚀 PEP 8 follow karo — naming conventions, imports order, spacing. Production code mein yeh difference banata hai.
❓ FAQ
Q1: Python mein List aur Tuple mein kya difference hai? 🤔
Answer: List mutable hai (change kar sakte ho), Tuple immutable hai (change nahi hota). Tuple faster hai aur hashable bhi — isliye dictionary keys mein use ho sakta hai. Jab data change nahi hona chahiye, tuple use karo.
Q2: *args aur **kwargs kab use karte hain? 🎯
Answer: *args tab use karo jab aapko pata nahi kitne positional arguments aayenge (tuple ban jaata hai). **kwargs jab unknown keyword arguments accept karne ho (dict ban jaata hai). Dono saath mein bhi use ho sakte hain: def f(*args, **kwargs).
Q3: Python mein GIL kya hai aur CPU-bound tasks ke liye kya karna chahiye? ⚙️
Answer: GIL (Global Interpreter Lock) CPython mein ek lock hai jo ek time pe sirf ek thread ko execute hone deta hai. I/O-bound tasks ke liye threading/asyncio use karo, CPU-bound tasks ke liye multiprocessing use karo jo separate processes mein chalti hai.
Q4: Shallow copy aur Deep copy mein kya farak hai? 📋
Answer: Shallow copy sirf top-level copy karta hai — nested objects still shared rehte hain. Deep copy (copy.deepcopy()) puri nested structure ka independent copy banata hai. Nested lists/dicts ke liye hamesha deepcopy use karo.
Q5: Decorator kya hota hai aur kab use karte hain? 🎭
Answer: Decorator ek function hai jo doosre function ko modify karta hai bina uska code change kiye. @decorator syntax use hota hai. Use cases: logging, authentication, caching (@lru_cache), timing, access control. Flask mein @app.route bhi decorator hai!
Q6: Generator aur normal function mein kya difference hai? 🔄
Answer: Normal function return se ek value deta hai aur terminate ho jaata hai. Generator yield use karta hai — ek-ek value lazily produce karta hai aur state remember karta hai. Large datasets ke liye memory efficient — poora data memory mein load nahi hota.
Q7: Python mein with statement kya karta hai? 🔒
Answer: with statement context managers ke saath use hota hai. Yeh automatically resources cleanup karta hai (jaise file close karna) — chahe exception aaye ya na aaye. Internally __enter__() aur __exit__() methods call hote hain.
Q8: @staticmethod aur @classmethod mein kya difference hai? 🏗️
Answer: @staticmethod ko self ya cls nahi milta — utility function jaisa hai class ke andar. @classmethod ko cls milta hai (class reference) — factory methods aur alternative constructors banane ke liye use hota hai. @classmethod inheritance mein properly kaam karta hai.
🎯 Interview Questions
Quick-fire Python interview questions jo frequently puchhe jaate hain: 🔥
Q1: Python mein mutable aur immutable data types bataiye.
Answer: Mutable: list, dict, set, bytearray. Immutable: int, float, str, tuple, frozenset, bytes. Immutable objects ka hash fix hota hai, isliye dict keys mein use ho sakte hain.
Q2: == aur is mein kya difference hai?
Answer: == value comparison karta hai (content same hai?). is identity comparison karta hai (same object in memory?). None check ke liye hamesha is use karo: if x is None.
Q3: List comprehension aur generator expression mein kya difference hai?
Answer: List comprehension [x for x in range(10)] — poora list memory mein banata hai. Generator expression (x for x in range(10)) — lazily ek-ek value produce karta hai, memory efficient. Large data pe generator better hai.
Q4: Python mein self kya hai?
Answer: self current instance ka reference hai. Har instance method ka first parameter self hota hai. Isse instance variables access/modify karte hain. Python automatically pass karta hai — explicitly likhna padta hai definition mein.
Q5: deepcopy() kab zaroorat padti hai?
Answer: Jab nested objects (list of lists, dict of dicts) ko independently copy karna ho. shallow copy sirf outer object copy karta hai — inner objects shared rehte hain. copy.deepcopy() recursively sab copy karta hai.
Q6: Python mein decorator kaise kaam karta hai?
Answer: Decorator ek higher-order function hai. @decorator lagna matlab func = decorator(func). Original function ko wrap karta hai — extra functionality add karta hai (logging, timing, auth). @functools.wraps(func) lagao taaki original function metadata preserve ho.
Q7: try-except-else-finally ka execution order kya hai?
Answer: try → code execute hota hai. Agar exception aaye → except block. Agar NO exception → else block. finally → hamesha run hota hai (cleanup ke liye). Return statement bhi finally ke baad execute hota hai!
Q8: Python mein memory management kaise hota hai?
Answer: Python reference counting + garbage collector (cyclic references ke liye) use karta hai. Jab reference count 0 ho jaata hai, memory free hoti hai. gc module se garbage collection control kar sakte ho. Small integers (-5 to 256) aur interned strings cached rehte hain.
Q9: @staticmethod vs @classmethod vs regular method — kab kya use karna chahiye?
Answer: Regular method — instance-specific kaam ke liye (self milta hai). @classmethod — class-level operations, factory methods (cls milta hai, inheritance support). @staticmethod — utility function jo na instance na class pe depend kare (koi automatic parameter nahi milta).
Q10: Python mein multithreading ka limitation kya hai aur solution kya hai?
Answer: GIL (Global Interpreter Lock) — ek time pe sirf ek thread Python bytecode execute kar sakta hai. I/O-bound tasks ke liye threading kaam karti hai (GIL release hota hai I/O pe). CPU-bound ke liye multiprocessing module use karo — separate processes, separate GIL. Ya phir concurrent.futures.ProcessPoolExecutor use karo.
💡 Pro Tip: Interview mein sirf answer mat do — example code ke saath explain karo. Interviewer ko practical understanding dekhni hai, ratta nahi! Practice karo daily — WoHoTech ke saath Python Master karo! 🚀
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