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How to Compare Dataclass Instances by Specific Fields in Python
Use @dataclass(order=True) with field(compare=False) to control which fields determine ordering and equality between instances.
from dataclasses import dataclass, field
from typing import Any
@dataclass(order=True)
class Person:
name: str = field(compare=False)
age: int
height_cm: float
priority: int = field(compare=False, default=0)
def __repr__(self):
return f"Person(name={self.name!r}, age={self.age}, height={s…
How to Implement Rich Comparison Ordering in Python Classes
This code demonstrates how to implement rich comparison operators (like <, <=, >, >=, ==, !=) in a Python class by defining __lt__ and __eq__, enabling sorting and ordering of custom objects.
class Task:
def __init__(self, priority, name):
self.priority = priority
self.name = name
def __lt__(self, other):
if not isinstance(other, Task):
return NotImplemented
return self.priority < other.priority
def __eq__(self, other):
if not isinstance(oth…
Depth First Search Traversal Order in Python
Recursive depth-first search that returns the visit order of nodes in an adjacency list graph starting from a given node.
def dfs_order(adj, start):
visited = set()
order = []
def dfs(node):
visited.add(node)
order.append(node)
for neighbor in adj.get(node, []):
if neighbor not in visited:
dfs(neighbor)
dfs(start)
return order
if __name__ == "__main__":
# Dem…
Find Elements in One Python List but Not Another
Return a new list containing only the elements from list A that are not present in list B, preserving duplicates and order.
def difference_elements(a, b):
"""Return elements present in list a but not in list b."""
set_b = set(b)
return [item for item in a if item not in set_b]
if __name__ == "__main__":
a = [1, 2, 3, 4, 5, 3, 2]
b = [2, 4, 6]
result = difference_elements(a, b)
print(f"A: {a}")
print(f"B: {b…
How to Compute the Cartesian Product of Two Lists in Python
Generates all ordered pairs from two lists using itertools.product and prints each combination.
from itertools import product
# Two small input lists
list_a = [1, 2, 3]
list_b = ["x", "y"]
# Compute the Cartesian product
result = list(product(list_a, list_b))
# Display the result
print("Cartesian product of", list_a, "and", list_b, "is:")
for pair in result:
print(pair)
How to Get the Breadth-First Traversal Order of a Graph in Python
Performs a breadth-first search on an adjacency list and returns the order nodes are visited, using a deque for efficient queue operations.
from collections import deque
def bfs_order(adjacency, start=0):
"""Return the order nodes are visited in a breadth-first traversal."""
visited = set()
order = []
queue = deque([start])
visited.add(start)
while queue:
node = queue.popleft()
order.append(node)
for neig…
How to Heapify a List into a Min Heap with heapq in Python
Convert any list into a valid min heap in-place using Python's heapq.heapify(), then pop the smallest element to verify heap order.
import heapq
data = [5, 3, 8, 1, 9, 2, 7, 4, 6]
print("Original list:", data)
heapq.heapify(data)
print("Min heap:", data)
popped = heapq.heappop(data)
print("Smallest element popped:", popped)
print("Heap after pop:", data)
How to Remove Banned Values from a List in Python
Filters a list by removing elements present in a banned set, preserving the original order.
def remove_banned(values, banned):
banned_set = set(banned)
return [item for item in values if item not in banned_set]
if __name__ == "__main__":
values = [1, 2, 3, 4, 5, 2, 6, 3, 7]
banned = [2, 3]
result = remove_banned(values, banned)
print(result)
How to Remove Duplicates in Python Preserving Order
Removes duplicate items from a list while keeping the first occurrence order intact using a set for fast membership checks.
def remove_duplicates_preserving_order(items):
seen = set()
result = []
for item in items:
if item not in seen:
seen.add(item)
result.append(item)
return result
if __name__ == "__main__":
sample = [3, 1, 2, 1, 3, 4, 2, 5]
unique_items = remove_duplicates_preserv…
Move Zeroes to End in Python Maintaining Order
In-place algorithm that moves all zeroes to the end of a list while preserving the relative order of non-zero elements.
def move_zeroes(nums):
non_zero_index = 0
for i in range(len(nums)):
if nums[i] != 0:
nums[non_zero_index], nums[i] = nums[i], nums[non_zero_index]
non_zero_index += 1
return nums
if __name__ == "__main__":
example = [0, 1, 0, 3, 12]
result = move_zeroes(example)
…
Reorder a List by Odd Even Indices in Python
Splits a list into two sublists based on 1-based index parity, then concatenates odd-indexed elements before even-indexed ones.
def reorder_by_odd_even(items):
"""Reorders a list so that elements at odd indices come first,
followed by elements at even indices (1-based).
Example: [0,1,2,3,4,5,6] -> [1,3,5,0,2,4,6]
"""
odds = [items[i] for i in range(1, len(items), 2)]
evens = [items[i] for i in range(0, len(items), …
Segregate Negative Numbers Before Positives in Python
Reorders a list so all negative numbers appear before non-negative numbers while preserving the original relative order of elements.
def segregate_negatives(numbers):
"""Segregate negatives before positives without altering relative order."""
negatives = [n for n in numbers if n < 0]
positives = [n for n in numbers if n >= 0]
return negatives + positives
if __name__ == "__main__":
sample = [3, -1, 4, -5, 2, -9, 0]
result =…
Sort list by multiple keys with tuple ordering in Python
Sort a list of dictionaries by multiple criteria — surname, age, then score descending — using a tuple key and negation.
def sort_multi_key(data):
# Sorts by surname, then age, then score descending
return sorted(
data,
key=lambda person: (
person['surname'].lower(),
person['age'],
-person['score'] # negative to reverse sort by score
)
)
if __name__ == "__main__"…
Stable merge two lists by custom comparator in Python
Merge two lists into one sorted output using a custom comparator while maintaining the original order of equal elements.
from functools import cmp_to_key
def compare(x, y):
# Custom comparator: sorts by length first, then by original index for stability
if len(x) != len(y):
return len(x) - len(y)
return 0 # Equal keys preserve original order (stable)
def merge_stable(left, right, cmp_func):
result = []
i =…
Stable sort preserving equal order demo in Python
Demonstrates Python's stable sort, showing that elements with equal sort keys retain their original relative order.
from operator import itemgetter
def stable_sort_demo():
data = [(3, "first"), (1, "second"), (3, "third"), (1, "fourth"), (2, "fifth")]
print("Original:", data)
# Sort by first element (the tuple's first value), keeping relative order of equal items
sorted_data = sorted(data, key=itemgetter(0))
…
How to Generate Permutations of Length r in Python
Generate all ordered arrangements of length r from a given list of elements using itertools.permutations.
from itertools import permutations
def generate_permutations(elements, r):
"""Generate all r-length permutations of the given elements."""
return list(permutations(elements, r))
if __name__ == "__main__":
elements = ['A', 'B', 'C']
r = 2
result = generate_permutations(elements, r)
print(f"Ele…
Merge Data with Comprehension and Generator in Python
Merge user and order data using a dictionary comprehension for lookups and a generator expression to filter and transform orders.
def merge_data(users, orders):
"""
Merge user and order data using a dictionary comprehension
and a generator expression for filtering.
"""
# Build a lookup: user_id -> user name
user_map = {user["id"]: user["name"] for user in users}
# Generator: yield orders with user names attached
…
How to Sort a List of Dictionaries by Key in Python
A reusable helper function that sorts a list of dictionaries by a specified key, with optional descending order support.
from typing import List
def sort_records(records: List[dict], key: str, descending: bool = False) -> List[dict]:
"""Sort a list of dictionaries by a specified key."""
return sorted(records, key=lambda record: record[key], reverse=descending)
def demonstrate_sorting() -> None:
users = [
{"name": …
How to Use ThreadPoolExecutor in Python for Parallel Processing
Use ThreadPoolExecutor with executor.map to run a function over many inputs concurrently and collect ordered results.
def worker(item):
return item * item
if __name__ == "__main__":
from concurrent.futures import ThreadPoolExecutor
numbers = list(range(1, 11))
with ThreadPoolExecutor(max_workers=4) as executor:
results = list(executor.map(worker, numbers))
print("Input: ", numbers)
print("Results:", …
Sort Python list by query param order_by
Sort a list of dataclass objects dynamically by a field name passed as a query param, with asc/desc direction support.
from dataclasses import dataclass
@dataclass
class Item:
name: str
price: int
def sort_items(items, order_by, direction="asc"):
if order_by not in ("name", "price"):
raise ValueError(f"Unsupported sort field: {order_by}")
reverse = direction.lower() == "desc"
return sorted(items, key=l…
How to Implement a Priority Queue for Messages in Python
Build a message priority queue with heapq and dataclasses that pops messages by priority, using sequence numbers to keep insertion order.
import heapq
from dataclasses import dataclass, field
from typing import Any
@dataclass(order=True)
class Message:
priority: int
sequence: int = field(compare=False)
content: str = field(compare=False)
class PriorityQueue:
def __init__(self):
self._heap = []
def push(self, priority: int,…
How to Partition and Order Kafka-Style Messages by Key in Python
Group messages with the same key into ordered buckets using hashing and a defaultdict, mimicking Kafka partition ordering.
from dataclasses import dataclass
from collections import defaultdict
@dataclass
class Message:
key: str
content: str
def partition_and_order(messages, num_partitions=3):
partitions = defaultdict(list)
for msg in messages:
partition_id = hash(msg.key) % num_partitions
partitions[parti…
Cache Warming with Python: Preload Hot Keys
Demonstrates a simple LRU-like cache with a warm method that preloads hot keys with mock values using OrderedDict.
import time
from collections import OrderedDict
class CacheWarm:
def __init__(self, capacity=3):
self.capacity = capacity
self.cache = OrderedDict()
self.hot_keys = []
def warm(self, keys):
"""Preload hot keys into cache with mock values."""
for key in keys:
…
How to Use Redis ZADD and ZRANGE in Python
Add members to a Redis sorted set with ZADD and retrieve them in score order with ZRANGE in Python.
import redis
client = redis.Redis(host='localhost', port=6379, db=0)
client.delete('scores')
members = {'alice': 30, 'bob': 20, 'carol': 50}
for name, score in members.items():
client.zadd('scores', {name: score})
result = client.zrange('scores', 0, -1)
print(result)
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