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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…How to Build a Text Processor in Python
This code defines functions to count words, sentences, and find the longest word in a text, then prints basic statistics like uppercase and lowercase versions.
def count_words(text):
return len(text.split())
def count_sentences(text):
sentence_endings = ".!?"
count = 0
for char in text:
if char in sentence_endings:
count += 1
return count
def longest_word(text):
words = text.split()
if not words:
return ""
retur…How to Inspect String Statistics in Python
A beginner-friendly function that returns detailed statistics about a string, including length, word count, character types, and easy text transformations.
def inspect_text(text: str) -> dict:
"""Return useful stats about a string for beginners."""
words = text.split()
return {
"length": len(text),
"word_count": len(words),
"uppercase": sum(1 for ch in text if ch.isupper()),
"lowercase": sum(1 for ch in text if ch.islower()),
…How to Summarize Text Statistics in Python
This function returns basic statistics about a string, including character, word, and sentence counts, plus case and digit counts.
def summarize_text(text):
"""Return basic statistics about a string."""
words = text.split()
return {
"characters": len(text),
"words": len(words),
"sentences": text.count(".") + text.count("!") + text.count("?"),
"uppercase": sum(c.isupper() for c in text),
"lowerca…String helpers in Python: stats, reverse, and remove vowels
Three beginner-friendly Python functions compute text statistics, reverse word order, and strip vowels from a string.
def text_stats(text: str) -> dict:
"""Return basic statistics for a given text string."""
words = text.split()
return {
"characters": len(text),
"words": len(words),
"sentences": text.count(".") + text.count("!") + text.count("?"),
"uppercase": sum(1 for c in text if c.isupp…Generate Data Helper for Beginners in Python
Define two functions that create a random list of integers and then compute basic summary statistics like count, total, average, maximum, and minimum using simple loops.
from random import randint
def build_dataset(size: int, max_val: int) -> list[int]:
data = []
for _ in range(size):
data.append(randint(1, max_val))
return data
def summarize(data: list[int]) -> dict[str, float]:
total = 0
maximum = data[0]
minimum = data[0]
for value in data:
…How to Calculate the Average of a List of Numbers in Python
Compute the arithmetic mean of a numeric list using Python's built-in sum() and len() functions, returning 0.0 for an empty list.
def calculate_average(numbers):
if not numbers:
return 0.0
return sum(numbers) / len(numbers)
if __name__ == "__main__":
sample_numbers = [10, 20, 30, 40, 50]
result = calculate_average(sample_numbers)
print(f"Average: {result}")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 Find the Mode in a Python List
Find the most frequent value (mode) in a Python list using the collections.Counter class, handling empty lists and ties.
from collections import Counter
def find_mode(numbers):
if not numbers:
return None
counts = Counter(numbers)
max_count = max(counts.values())
modes = [num for num, count in counts.items() if count == max_count]
return modes[0] if len(modes) == 1 else modes
if __name__ == "__main__":
…How to Standardize a List with Z-Score Normalization in Python
This code computes the z-score for each number in a list, standardizing the data to have zero mean and unit variance using the statistics module.
import statistics
def z_score_normalize(values):
"""Standardize a list of numbers using z-score normalization."""
if not values or len(values) < 2:
raise ValueError("Need at least 2 values for meaningful z-score normalization")
mean = statistics.mean(values)
std_dev = statistics.stdev(val…How to Summarize a List of Numbers in Python
Loop over a list of numbers to compute total, count, average, min, and max, then return them in a dictionary.
def summarize_numbers(numbers):
"""Return a dict with basic stats for a list of numbers."""
total = 0
count = 0
smallest = numbers[0]
largest = numbers[0]
for num in numbers:
total += num
count += 1
if num < smallest:
smallest = num
if num > largest:…How to check list items by type and emptiness in Python
Loop through a list with enumerate(), classify each item as empty, number, or text, and print a formatted status for each element.
def check_data(data):
"""Check each item in a list and print whether it's valid."""
for i, item in enumerate(data):
if item is None or item == "":
status = "empty"
elif isinstance(item, (int, float)):
status = "number"
else:
status = "text"
pr…How to summarize and transform lists in Python
Compute count, sum, min, max, and average for a list and multiply each element by a factor using simple loops and built-in functions.
def summarize(data):
"""Return a summary of a list: count, sum, min, max, average."""
count = len(data)
total = sum(data)
minimum = min(data)
maximum = max(data)
average = total / count if count else 0
return count, total, minimum, maximum, average
def multiply_elements(data, factor=2):
…Add Type Hints to Function Parameters and Return in Python
Add type hints to function parameters and return values in Python for clearer, more maintainable code using the typing module.
from typing import List, Optional, Dict
def average(numbers: List[float]) -> float:
return sum(numbers) / len(numbers)
def full_name(first: str, last: Optional[str] = "") -> str:
return f"{first} {last}".strip()
def build_user(name: str, age: int, email: Optional[str] = None) -> Dict[str, object]:
us…How to Create a Counter Closure in Python
Build a closure in Python that remembers and increments a counter across calls without using global variables.
def create_counter(start=0):
count = start
def increment():
nonlocal count
count += 1
return count
return increment
if __name__ == "__main__":
counter = create_counter(10)
print(counter())
print(counter())
print(counter())How to Write a Context Manager Class in Python
Define a class with __enter__ and __exit__ to manage file resources safely using the with statement.
class FileReader:
def __init__(self, filename, mode="r"):
self.filename = filename
self.mode = mode
self.file = None
def __enter__(self):
self.file = open(self.filename, self.mode)
return self.file
def __exit__(self, exc_type, exc_val, exc_tb):
if self.file…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…Write a Pure Function Without Side Effects in Python
Defines a pure function that adds one to a number without modifying external state.
def add_one(x: int) -> int:
"""Adds 1 to the input without modifying any external state."""
return x + 1
if __name__ == "__main__":
original = 5
result = add_one(original)
print(f"Original: {original}")
print(f"Result: {result}")
print(f"Original unchanged: {original}")How to Assert Preconditions with Descriptive Messages in Python
Use Python's assert statement with a custom message to validate function preconditions and fail fast with clear diagnostics.
def divide(dividend, divisor):
assert divisor != 0, f"Divisor must be non-zero, got {divisor!r}"
return dividend / divisor
if __name__ == "__main__":
print(divide(10, 2))
try:
divide(10, 0)
except AssertionError as e:
print(f"AssertionError: {e}")How to Build an Error Code Enum in Python
Define an API error code enum with descriptions and build structured error payloads for HTTP responses.
from enum import Enum
class APIErrorCode(Enum):
SUCCESS = 0
BAD_REQUEST = 400
UNAUTHORIZED = 401
FORBIDDEN = 403
NOT_FOUND = 404
CONFLICT = 409
INTERNAL_ERROR = 500
def describe_error(code):
descriptions = {
APIErrorCode.SUCCESS: "Request completed successfully",
APIE…Implement a Context Manager That Suppresses Exceptions in Python
Shows how to write a custom context manager that catches specified exceptions and optionally re-raises others, plus the stdlib contextlib.suppress alternative.
import contextlib
class SuppressExceptions:
def __init__(self, *exceptions):
self.exceptions = exceptions
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
if exc_type is None:
return False
if not self.exceptions or exc_type in se…Map Exception Type to HTTP Status Code in Python
Maps Python exception types to appropriate HTTP status codes using a dictionary lookup for consistent API error handling.
EXCEPTION_STATUS_MAP = {
ValueError: 400,
KeyError: 400,
TypeError: 400,
PermissionError: 403,
FileNotFoundError: 404,
AttributeError: 404,
TimeoutError: 408,
NotImplementedError: 501,
ConnectionError: 503,
}
def status_code_for(exception_type):
try:
return EXCEPTION_S…Audit File Permissions Across a Project in Python
Walks through every file and directory in a project tree and prints POSIX permissions plus owner UID.
import os
import stat
from pathlib import Path
def audit_file_permissions(project_root):
"""Walk through project_root and print path, owner, and permissions for every file."""
results = []
for root, dirs, files in os.walk(project_root):
for name in files + dirs:
full_path = os.path.joi…Browse by section
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