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How to Use __getstate__ and __setstate__ for Pickle in Python
Customize Python object serialization with the pickle __getstate__ and __setstate__ hooks to control exactly what data is stored and how it is restored.
import pickle
class Temperature:
def __init__(self, celsius):
self.celsius = celsius
def __getstate__(self):
"""Customize what gets pickled."""
state = self.__dict__.copy()
# Convert to Fahrenheit for storage (simulate transformation)
state['fahrenheit'] = (self.celsiu…
How to Use __slots__ in Python Classes for Memory Efficiency
Defines classes with __slots__ to prevent dynamic attribute creation and reduce memory usage, including inheritance with additional slots.
```python
class Person:
__slots__ = ("name", "age")
def __init__(self, name: str, age: int):
self.name = name
self.age = age
def greet(self) -> str:
return f"Hi, I'm {self.name} and I'm {self.age} years old."
class Employee(Person):
__slots__ = ("role",)
def __init__(se…
How to Use abstractmethod in Python
Define an abstract base class with abstract methods to enforce a common interface across subclasses.
import abc
class Shape(abc.ABC):
@abc.abstractmethod
def area(self):
"""Calculate area of the shape."""
@abc.abstractmethod
def perimeter(self):
"""Calculate perimeter of the shape."""
class Rectangle(Shape):
def __init__(self, width, height):
self.width = width
s…
How to implement a Facade class to simplify subsystem calls in Python
Use a Facade class to wrap complex subsystem interactions behind a simple start() method, hiding the details and providing a clean interface.
class CPU:
def freeze(self):
print("CPU: freezing")
def jump(self, position):
print(f"CPU: jumping to {position}")
def execute(self):
print("CPU: executing")
class Memory:
def load(self, position, data):
print(f"Memory: loading '{data}' at {position}")
class HardDr…
Implement the Strategy Pattern with Interchangeable Algorithm Classes in Python
Uses abstract base classes to define a SortStrategy interface, then swaps between BubbleSort and QuickSort at runtime.
from abc import ABC, abstractmethod
from typing import List
class SortStrategy(ABC):
@abstractmethod
def sort(self, data: List[int]) -> List[int]:
pass
class BubbleSort(SortStrategy):
def sort(self, data: List[int]) -> List[int]:
result = data[:]
n = len(result)
for i in…
Memento Pattern in Python: Save and Restore Object State
Implement the Memento design pattern to snapshot and restore an object's state, demonstrated with a text editor undo feature.
class TextEditor:
def __init__(self, text="", cursor_pos=0):
self.text = text
self.cursor_pos = cursor_pos
def type_text(self, new_text):
self.text += new_text
self.cursor_pos += len(new_text)
def move_cursor(self, pos):
self.cursor_pos = max(0, min(pos, len(self.t…
Observer Pattern in Python: Notify Listeners
Implement the Observer design pattern in Python with a Subject class that manages listeners and notifies them with messages.
class Subject:
def __init__(self):
self._observers = []
def attach(self, observer):
self._observers.append(observer)
def detach(self, observer):
self._observers.remove(observer)
def notify(self, message):
for observer in self._observers:
observer.update(me…
Python Abstract Class with Concrete Subclasses
Define an abstract base class with abstract methods and implement them in concrete subclasses like Rectangle and Circle.
from abc import ABC, abstractmethod
class Shape(ABC):
@abstractmethod
def area(self):
pass
@abstractmethod
def perimeter(self):
pass
class Rectangle(Shape):
def __init__(self, width, height):
self.width = width
self.height = height
def area(self):
ret…
Template Method Pattern in Python: Define Base Class with Algorithm Steps
Create a template method base class using ABC that defines the skeleton of an algorithm while letting subclasses implement specific steps.
from abc import ABC, abstractmethod
class DataProcessor(ABC):
"""Template method that defines the skeleton of an algorithm."""
def process(self):
"""Template method - defines the sequence of steps."""
self.load_data()
self.clean_data()
self.transform_data()
self.s…
Understanding Multiple Inheritance Method Resolution Order in Python
This code demonstrates how Python's MRO determines which greet method is called in a diamond inheritance scenario, and prints the full MRO for class D.
class A:
def greet(self):
return "Hello from A"
class B(A):
def greet(self):
return "Hello from B"
class C(A):
def greet(self):
return "Hello from C"
class D(B, C):
pass
if __name__ == "__main__":
d = D()
print(d.greet())
print(D.__mro__)
Unit of Work Pattern: Track Changes, Commit, and Rollback in Python
This code defines a UnitOfWork class that tracks operations (add) and supports commit to apply changes and rollback to revert them, using a dataclass-based logger.
from dataclasses import dataclass, field
from typing import Any, Callable, List, Tuple
@dataclass
class UnitOfWork:
log: List[Tuple[str, Callable, tuple, dict]] = field(default_factory=list)
def track(self, operation: str, fn: Callable, *args, **kwargs):
self.log.append((operation, fn, args, kwargs)…
Visitor Pattern in Python: Double Dispatch Demo
Demonstrates the Visitor design pattern with double dispatch so operations on Dog and Cat objects are selected at runtime without modifying their classes.
class Animal:
def accept(self, visitor):
visitor.visit(self)
class Dog(Animal):
def speak(self):
return "Woof!"
class Cat(Animal):
def speak(self):
return "Meow!"
class SoundVisitor:
def visit(self, animal):
if isinstance(animal, Dog):
return self.visit_do…
Binary Search for Ship Capacity in Python
Use binary search to find the minimum ship capacity that can transport all packages within a given number of days.
def ship_within_days(weights, days):
def can_ship(capacity):
current = 0
needed_days = 1
for weight in weights:
if current + weight > capacity:
needed_days += 1
current = 0
current += weight
return needed_days <= days
low …
Binary Search on Answer in Python: Koko Eating Bananas
Find the minimum eating speed so Koko finishes all banana piles within a given hour limit using binary search on the answer.
import math
def min_eating_speed(piles, h):
"""Return minimum integer eating speed K so Koko finishes within h hours."""
def hours_needed(speed):
return sum(math.ceil(p / speed) for p in piles)
low, high = 1, max(piles)
while low < high:
mid = (low + high) // 2
if hours_needed…
Container With Most Water: Two-Pointer Solution in Python
Find the maximum water a container can hold from a list of heights using an efficient two-pointer technique in O(n) time.
from typing import List
def max_water_container(heights: List[int]) -> int:
left, right = 0, len(heights) - 1
max_area = 0
while left < right:
width = right - left
height = min(heights[left], heights[right])
area = width * height
max_area = max(max_area, area)
…
Find All Triplets with Sum Zero in Python
This code finds all unique triplets in an array that sum to zero using a sorted array and two-pointer technique.
def find_triplets(nums):
nums.sort()
n = len(nums)
triplets = []
for i in range(n - 2):
if i > 0 and nums[i] == nums[i - 1]:
continue
left, right = i + 1, n - 1
while left < right:
total = nums[i] + nums[left] + nums[right]
if total == 0:
…
Find Longest Consecutive Sequence in Python
Find the length of the longest consecutive elements sequence in an unsorted array using a set for O(n) lookups.
def longest_consecutive_length(nums):
num_set = set(nums)
longest = 0
for num in num_set:
if num - 1 not in num_set:
current = num
current_streak = 1
while current + 1 in num_set:
current += 1
current_streak += 1
…
Find Longest Increasing Subsequence Length in Python
Compute the length of the longest increasing subsequence in an array using dynamic programming.
def longest_increasing_subsequence(nums):
if not nums:
return 0
dp = [1] * len(nums)
for i in range(1, len(nums)):
for j in range(i):
if nums[i] > nums[j]:
dp[i] = max(dp[i], dp[j] + 1)
return max(dp)
if __name__ == "__main__":
# Demo with…
Find Minimum in Rotated Sorted List in Python
Uses binary search to find the minimum element in a rotated sorted list in O(log n) time.
def find_min(nums):
left, right = 0, len(nums) - 1
while left < right:
mid = (left + right) // 2
if nums[mid] > nums[right]:
left = mid + 1
else:
right = mid
return nums[left]
if __name__ == "__main__":
rotated = [4, 5, 6, 7, 0, 1, 2]
print(f"Minimu…
Find Missing Numbers, Duplicates, and Ranges in Python
Analyze a list to identify missing numbers, duplicate values, and contiguous ranges using sets and the Counter class.
def find_missing_duplicates_ranges(numbers):
"""Find missing numbers, duplicates, and ranges in a list."""
from collections import Counter
if not numbers:
return {"missing": [], "duplicates": [], "ranges": []}
full_range = set(range(min(numbers), max(numbers) + 1))
present = set(n…
Find Peak Element in Python Using Binary Search
A binary search solution that finds any peak element (an element strictly greater than its neighbors) in an unsorted array in O(log n) time.
def find_peak_element(nums):
left, right = 0, len(nums) - 1
while left < right:
mid = (left + right) // 2
if nums[mid] > nums[mid + 1]:
right = mid
else:
left = mid + 1
return left
if __name__ == "__main__":
test1 = [1, 2, 3, 1]
tes…
Find the Duplicate Number in Python Using Floyd's Cycle Detection
Detects the duplicate integer in an array of n+1 numbers (values 1 to n) in O(n) time and O(1) space using Floyd's cycle detection algorithm applied to a linked-list model.
def find_duplicate(nums):
slow = nums[0]
fast = nums[0]
# Phase 1: Find intersection point of the cycle
while True:
slow = nums[slow]
fast = nums[nums[fast]]
if slow == fast:
break
# Phase 2: Find the start of the cycle (the duplicate)
slow = nums[0…
Find the Majority Element in Python with Boyer-Moore Vote
Use Boyer-Moore majority vote to find the element appearing more than n/2 times in an array in O(n) time and O(1) space.
def majority_element(nums):
candidate = None
count = 0
for num in nums:
if count == 0:
candidate = num
count += 1 if num == candidate else -1
return candidate
if __name__ == "__main__":
nums = [2, 2, 1, 1, 1, 2, 2]
result = majority_element(nums)
print(f"Major…
Find two unique numbers in an array with Python
Returns the two numbers that appear exactly once in a list where every other number appears twice, using XOR bit manipulation.
def find_two_odd(arr):
"""Return the two numbers that appear exactly once, while all others appear twice."""
xor_all = 0
for num in arr:
xor_all ^= num
# xor_all now equals the XOR of the two unique numbers.
# Find a set bit (any bit where they differ).
diff_bit = xor_all & (-xor_all)
…
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