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How to Create a Data Formatter Class in Python
A beginner-friendly helper class to format lists, dictionaries, and stored records into readable strings.
class DataFormatter:
"""Helper class for beginners to format common data types."""
def __init__(self, name="data"):
self.name = name
self.records = []
def add_record(self, key, value):
"""Add a key-value record to the formatter."""
self.records.append({"key": key, …Find Common Elements in List of Lists in Python
Return elements that appear in every sublist of a nested list, preserving duplicates with Counter intersection.
from collections import Counter
def common_elements(list_of_lists):
"""Return elements present in every sublist."""
if not list_of_lists:
return []
counts = Counter(list_of_lists[0])
for sublist in list_of_lists[1:]:
counts &= Counter(sublist)
return list(counts.elements())
if _…Generate Pascal's Triangle Rows in Python
Builds Pascal's triangle as a list of rows, where each inner value is the sum of the two values above it.
def generate_pascals_triangle(rows):
triangle = []
for row_num in range(rows):
row = [1] * (row_num + 1)
for col in range(1, row_num):
row[col] = triangle[row_num - 1][col - 1] + triangle[row_num - 1][col]
triangle.append(row)
return triangle
if __name__ == "__main__":
…How to Add Two Lists Elementwise in Python
Add two equal-length lists element by element using a list comprehension with zip, returning a new list of summed values.
def elementwise_add(list1, list2):
return [a + b for a, b in zip(list1, list2)]
if __name__ == "__main__":
list_a = [1, 2, 3, 4]
list_b = [10, 20, 30, 40]
result = elementwise_add(list_a, list_b)
print(result)How to Compare Two Lists Elementwise for Greater Flags in Python
Compare two equal-length lists element by element and return a list of booleans marking where list_a values are greater than list_b values.
def compare_lists_greater(list_a, list_b):
"""
Compare two lists elementwise and return a list of booleans
indicating whether each element in list_a is greater than the
corresponding element in list_b.
"""
if len(list_a) != len(list_b):
raise ValueError("Lists must have the same length"…How to Compute Jaccard Similarity in Python
Compute the Jaccard similarity between two lists by converting them to sets and dividing the intersection size by the union size.
def jaccard_similarity(list1, list2):
set1 = set(list1)
set2 = set(list2)
intersection = set1 & set2
union = set1 | set2
if not union:
return 0.0
return len(intersection) / len(union)
if __name__ == "__main__":
a = [1, 2, 3, 4, 5]
b = [3, 4, 5, 6, 7]
pri…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 Compute the Dot Product of Two Lists in Python
Compute the dot product of two equal-length numeric lists using a generator expression with zip and sum.
def dot_product(list1, list2):
"""
Compute the dot product of two numeric lists.
The lists must have the same length.
"""
if len(list1) != len(list2):
raise ValueError("Lists must have the same length")
return sum(a * b for a, b in zip(list1, list2))
if __name__ == "__main__":
…How to Flatten List of Dict Values in Python
This code flattens the values of a list of dictionaries into a single list, handling both list values and scalar values.
def flatten_dict_values(dicts):
flattened = []
for d in dicts:
for value in d.values():
if isinstance(value, list):
flattened.extend(value)
else:
flattened.append(value)
return flattened
if __name__ == "__main__":
data = [
{"a": …How to Split a List by a Predicate into Two Lists in Python
Partition any Python list into two lists based on a predicate: items that match go into one list, everything else into the other.
from typing import Callable, List, TypeVar
T = TypeVar("T")
def split_by_predicate(items: List[T], predicate: Callable[[T], bool]) -> tuple[List[T], List[T]]:
matching = []
non_matching = []
for item in items:
if predicate(item):
matching.append(item)
else:
non_mat…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 =…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 =…Flatten a Nested List in Python (Recursive Generator)
Recursively flatten arbitrarily nested lists into a single-level list using both a function and a generator with `yield from`.
def flatten(nested_list):
"""Recursively flatten a nested list into a single-level list."""
result = []
for item in nested_list:
if isinstance(item, list):
result.extend(flatten(item))
else:
result.append(item)
return result
def flatten_generator(nested_list):
…How to Parse Terraform Plan Output in Python
Parse mock Terraform plan output text into structured add, change, and destroy lists using Python.
import json
from typing import Dict, List
def parse_terraform_plan_output(plan_output_text: str) -> Dict[str, List[str]]:
"""
Parses a mock Terraform plan output text into a structured dictionary.
"""
parsed: Dict[str, List[str]] = {"add": [], "change": [], "destroy": []}
for line in plan_output_…How to List Failed Records in a Dead Letter Queue Mock in Python
A mock Dead Letter Queue stores failed processing records with error details and timestamps, lists them, and exports to JSON.
import json
from datetime import datetime, timedelta
import random
class DeadLetterQueue:
def __init__(self):
self.failed_records = []
def add_failed_record(self, record_id, payload, error_message):
self.failed_records.append({
"record_id": record_id,
"payload": paylo…How to Merge Multiple Data Sources in Python
A beginner-friendly helper that merges lists of dictionaries from multiple sources into one combined list using key filtering.
import json
def merge_pipeline_data(*data_sources, keys=()):
"""Merge multiple data sources (list of dicts) into a single list of merged dicts.
Args:
*data_sources: One or more lists of dictionaries.
keys: Tuple of keys to include from each source (empty means all keys).
Returns:
…How to Mock Poetry pyproject.toml Dependencies Sections in Python
Parse and extract dependency lists from Poetry-style pyproject.toml text using Python's standard library.
from pathlib import Path
import re
def parse_pyproject_dependencies(text):
"""Extract dependencies from a pyproject.toml style text."""
lines = text.splitlines()
sections = {
"dependencies": [],
"dev": [],
"optional": [],
}
current_section = None
patterns = {
…How to Use Array Typecodes for Compact Numeric Storage in Python
This code demonstrates how to use the `array` module with typecodes to store integers, floats, and bytes in a memory-efficient way compared to standard Python lists.
from array import array
def demonstrate_array_types():
# Compact integer arrays
small_ints = array('i', [1, 2, 3, 4, 5])
unsigned_ints = array('I', [10, 20, 30])
# Floating point arrays
floats = array('f', [1.5, 2.5, 3.5])
doubles = array('d', [1.123456789, 2.987654321])
# Charac…How to Mock Kafka Topic Partitions with a Python dict of lists
Mocks a Kafka topic and its partitions using a defaultdict of lists to simulate message production, consumption, and per-partition counts.
from collections import defaultdict
class KafkaTopicPartitionMock:
"""A simple mock for Kafka topic-partition assignment using dict of lists."""
def __init__(self, topic):
self.topic = topic
self.partitions = defaultdict(list) # partition_id -> list of messages
def produce(self, message…Redis LPUSH RPOP List Queue Mock in Python
Implements a FIFO queue using Redis lists with LPUSH and RPOP commands, simulating task processing in Python.
import redis
import time
r = redis.Redis(host='localhost', port=6379, db=0)
queue_key = 'task_queue'
# Push tasks onto the left side (LPUSH)
r.lpush(queue_key, 'task1')
r.lpush(queue_key, 'task2')
r.lpush(queue_key, 'task3')
# Mock processing: pop from the right side (RPOP) — FIFO order
while r.llen(queue_key) > 0:…How to Compute a Confusion Matrix in Python
Compute a multi-class confusion matrix from true and predicted labels using pure Python dictionaries and nested lists, then format it for readable output.
from collections import defaultdict
def compute_confusion_matrix(y_true, y_pred, labels):
"""Compute confusion matrix using Python dicts and nested lists."""
label_index = {label: i for i, label in enumerate(labels)}
matrix = [[0] * len(labels) for _ in range(len(labels))]
for true, pred in zip(y…How to build a maintenance mode page in Python
Mock a service maintenance status page that computes remaining downtime and lists affected features from a simple class.
from datetime import datetime
class MaintenanceMode:
"""Mock a maintenance mode status page for a service."""
def __init__(self, service_name: str, scheduled_end: str):
self.service_name = service_name
self.scheduled_end = datetime.fromisoformat(scheduled_end)
self.affected_featur…Browse by section
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