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Find Data From a String in Python: Stats, Clean, Keywords
Three helper functions for beginners: compute character/word/sentence stats, normalize whitespace and case, and extract unique sorted keywords from a string.
def get_text_stats(text):
"""Return basic statistics about a string."""
words = text.split()
sentences = text.replace('!', '.').replace('?', '.').split('.')
sentences = [s for s in sentences if s.strip()]
return {
'characters': len(text),
'words': len(words),
'sentences': le…Check if List is Sorted Ascending in Python
Verify that a list is sorted in ascending order using the all() function and a generator expression.
def is_sorted_ascending(lst):
return all(lst[i] <= lst[i + 1] for i in range(len(lst) - 1))
if __name__ == "__main__":
test_lists = [
[1, 2, 3, 4, 5],
[1, 3, 2, 4, 5],
[5, 4, 3, 2, 1],
[1, 1, 2, 2, 3],
[10],
[]
]
for lst in test_lists:
print(f"{l…How to Check if a List is Sorted in Descending Order in Python
This code defines a function that returns True if a given list is sorted in descending order, using a generator expression with all() to compare each adjacent pair.
def is_descending(lst):
"""Return True if list is sorted in descending order."""
return all(lst[i] >= lst[i + 1] for i in range(len(lst) - 1))
if __name__ == "__main__":
test_cases = [
[5, 4, 3, 2, 1],
[3, 3, 2, 1],
[1, 2, 3],
[10, 8, 9],
[]
]
for case in …How to Compute Percentile Value from Sorted List in Python
Compute any percentile value from a sorted list using linear interpolation between ranks.
def percentile(sorted_data, percentile_value):
"""Return the value below which `percentile_value`% of data falls."""
if not sorted_data:
raise ValueError("Cannot compute percentile of empty list")
if not 0 <= percentile_value <= 100:
raise ValueError("Percentile must be between 0 and 100")
…How to Find the Median of a List in Python
Compute the median of an unsorted numeric list using the statistics module in Python.
import statistics
def median_of_list(numbers):
return statistics.median(numbers)
if __name__ == "__main__":
sample = [7, 3, 1, 4, 9, 2, 8]
print(median_of_list(sample))How to Merge Two Sorted Lists in Python
Merge two sorted lists into one sorted list using a two-pointer loop, then extend with remaining elements.
def merge_sorted_lists(list1, list2):
merged = []
i = j = 0
while i < len(list1) and j < len(list2):
if list1[i] <= list2[j]:
merged.append(list1[i])
i += 1
else:
merged.append(list2[j])
j += 1
merged.extend(list1[i:])
merged…How to Sort a List in Python in Ascending and Descending Order
This code demonstrates three ways to sort a list in Python: returning a new sorted list with sorted(), reversing the sort order, and sorting a list in place with the list.sort() method.
def get_sorted_data(numbers):
"""Return a new list sorted in ascending order."""
return sorted(numbers)
def reverse_sort(data):
"""Return a new list sorted in descending order."""
return sorted(data, reverse=True)
def sort_in_place(data):
"""Sort the given list in place (modifies original)."""
…How to Sort a List of Dictionaries by a Key in Python
Sort a list of dictionaries by a specified key field, optionally in descending order, using Python's built-in sorted() function.
def sort_dicts_by_key(data, key, reverse=False):
return sorted(data, key=lambda item: item.get(key), reverse=reverse)
if __name__ == "__main__":
people = [
{"name": "Alice", "age": 30},
{"name": "Bob", "age": 25},
{"name": "Charlie", "age": 35},
]
sorted_by_age = sort_dicts_b…How to Sort a List of Tuples by the Second Element in Python
Sorts a list of tuples by the second element using the sorted() function with a lambda key, preserving the original list.
def sort_tuples_by_second(tuples_list):
"""Sort a list of tuples by the second element."""
return sorted(tuples_list, key=lambda x: x[1])
if __name__ == "__main__":
data = [(1, 5), (3, 2), (2, 8), (4, 1)]
sorted_data = sort_tuples_by_second(data)
print("Original list:", data)
print("Sorted by…How to Sort a List of Dictionaries by Key with a Lambda in Python
Sort a list of dictionaries ascending or descending by one of their keys using sorted() with a lambda as the key function — a beginner-friendly pattern.
def get_students():
return [
{"name": "alice", "score": 85},
{"name": "bob", "score": 92},
{"name": "carol", "score": 78},
{"name": "dave", "score": 92},
]
students = get_students()
sorted_by_score = sorted(students, key=lambda s: s["score"])
print("Sorted by score (ascending)…How to Use Lambda Sorting Keys in Python
Learn to sort lists of dictionaries using lambda functions as key arguments in Python's sorted() method.
# Demonstrate lambda as a sorting key function
students = [
{"name": "Alice", "grade": 88},
{"name": "Bob", "grade": 92},
{"name": "Charlie", "grade": 75},
{"name": "Diana", "grade": 95}
]
# Sort by grade (ascending) using a lambda key
sorted_by_grade = sorted(students, key=lambda student: student["g…How to Use a Lambda Sort Key in Python
Sort a list of strings by length, then alphabetically, using a lambda function as the sorting key in Python.
def sort_words(words):
"""Sort words by length, then alphabetically using a lambda key."""
return sorted(words, key=lambda word: (len(word), word))
if __name__ == "__main__":
sample_words = ["apple", "kiwi", "banana", "fig", "cherry"]
result = sort_words(sample_words)
print("Original:", sampl…How to implement binary search in Python
Standalone binary search function that returns the index of a target in a sorted list, or -1 if not found.
def binary_search(arr, target):
left, right = 0, len(arr) - 1
while left <= right:
mid = (left + right) // 2
if arr[mid] == target:
return mid
elif arr[mid] < target:
left = mid + 1
else:
right = mid - 1
return -1
if __name__ ==…Profile Python functions with cProfile
Profile a Python program with cProfile, capture the stats in memory, and print a sorted performance report.
import cProfile
import pstats
import io
def slow_function():
total = 0
for i in range(100000):
total += i ** 2
return total
def medium_function():
return sum(range(10000))
def fast_function():
return sum(range(100))
def main():
result1 = slow_function()
result2 = medium_func…Sort a List of Dictionaries by Key in Python
Uses a lambda function with sorted() to order a list of dictionaries by a specified key, like price.
def get_items():
return [
{"name": "apple", "price": 3},
{"name": "banana", "price": 1},
{"name": "cherry", "price": 2},
]
if __name__ == "__main__":
items = get_items()
sorted_items = sorted(items, key=lambda item: item["price"])
for item in sorted_items:
print(f"{…Create an In-Memory SQLite Table and Query It in Python
This code creates an in-memory SQLite database, defines an employees table, inserts sample rows, and runs a filtered query with sorted results.
import sqlite3
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
cursor.execute("""
CREATE TABLE employees (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
department TEXT NOT NULL,
salary REAL
)
""")
employees = [
(1, "Alice", "Engineering", 95000),
(2, "Bob", "…How to Merge Sorted Chunk Files in Python
Merge multiple sorted text files into one sorted output file using a heap for efficient k-way merging.
import heapq
def merge_sorted_chunks(chunks, output_path):
"""Merge multiple sorted iterables into single sorted output file."""
with open(output_path, "w") as out_f:
# Open all chunk files
handles = [open(chunk, "r") for chunk in chunks]
try:
# Heap of (value, index) tupl…How to Sort Files by Name and Size in Python
Sort a list of file dictionaries by name then size using Python's sorted() with a lambda key.
from pathlib import Path
def sort_files_data(files):
"""Sort a list of file dictionaries by name, then by size."""
return sorted(files, key=lambda f: (f["name"], f["size"]))
if __name__ == "__main__":
files_data = [
{"name": "report.pdf", "size": 2048},
{"name": "data.csv", "size": 1024},…How to Write a Dict to a Pretty JSON File with Indent in Python
Serializes a Python dictionary to a readable JSON file using json.dump with indentation and sorted keys, then prints the file contents to stdout.
import json
from pathlib import Path
data = {
"name": "Python",
"version": 3.12,
"features": ["simple", "readable", "powerful"],
"nested": {"creator": "Guido van Rossum", "year": 1991}
}
output_path = Path("output.json")
with output_path.open("w", encoding="utf-8") as f:
json.dump(data, f, inden…Reassemble File Parts into Original File Bytes in Python
Read sorted part files from a directory and concatenate their bytes into the original file.
import os
import sys
from pathlib import Path
def reassemble_parts(parts_dir: Path, output_path: Path) -> int:
"""
Reassemble file parts into the original file.
Args:
parts_dir: Directory containing the part files
output_path: Path where the reassembled file will be written
Returns:
…Build adjacency dict graph from edges in Python
Convert a list of edges into an undirected adjacency dictionary, mapping each node to its neighbors, with sorted output.
def build_adjacency_dict(edges):
graph = {}
for u, v in edges:
if u not in graph:
graph[u] = []
if v not in graph:
graph[v] = []
graph[u].append(v)
graph[v].append(u)
return graph
if __name__ == "__main__":
edges = [(1, 2), (2, 3), (3, 4), (4, 1)…How to Convert a Counter to a Plain Dict with Sorted Items in Python
This code converts a collections.Counter into a regular dictionary with items sorted by key, useful for stable, readable output.
from collections import Counter
def counter_to_sorted_dict(counter):
"""Convert a Counter to a plain dict with sorted items."""
return dict(sorted(counter.items()))
if __name__ == "__main__":
# Example usage
data = Counter(['apple', 'banana', 'apple', 'cherry', 'banana', 'date', 'apple'])
print("…How to Count Word Frequencies in Python with Counter and Sets
This code processes a text string by lowercasing, splitting into words, counting frequencies with Counter, and extracting unique and sorted word lists using sets.
from collections import Counter
def process_text(text):
words = text.lower().split()
word_counts = Counter(words)
unique_words = set(words)
sorted_words = sorted(unique_words)
return {
"total_words": len(words),
"unique_words": len(unique_words),
"word_frequencies": di…How to Normalize Data in Python with Dictionaries and Sets
Normalize a list of dicts by keeping selected keys, stripping/lowercasing strings, and extracting unique sorted values using set comprehension.
def normalize_data(data, keys):
"""
Normalize a list of dictionaries by keeping only specified keys
and converting values to proper types.
"""
normalized = []
for item in data:
clean_item = {}
for key in keys:
value = item.get(key)
if isinstance(value, st…Browse by section
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