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How to Unescape HTML Entities in Python
Convert HTML entities like & and < back to their literal characters using the standard library html module.
import html
def unescape_html_entities(text: str) -> str:
"""Convert HTML entities like & to their character equivalents."""
return html.unescape(text)
if __name__ == "__main__":
sample = "Tom & Jerry <cartoon> "classic" 'fun' © 2024"
result = unescape_html_enti…How to build a text helper in Python for beginners
This code provides easy-to-use functions for cleaning text, removing punctuation, counting word frequencies, and summarizing strings — perfect for beginners.
def clean_text(text: str) -> str:
"""Clean and normalize a text string."""
text = text.strip()
text = text.replace(" ", " ")
text = text.capitalize()
text = text.replace(".", ".")
return text
def remove_punctuation(text: str) -> str:
"""Remove common punctuation marks from a string."""
…How to parse key=value pairs in Python
Parse a single line of key=value pairs separated by a delimiter into a Python dictionary.
def parse_key_value_pairs(line: str, delimiter: str = "&") -> dict:
"""Parse a single line of key=value pairs into a dictionary."""
pairs = {}
for token in line.split(delimiter):
if not token.strip():
continue
key, _, value = token.partition("=")
pairs[key.strip()] = val…Normalize unicode accents to ASCII in Python
This code converts accented Unicode characters to ASCII equivalents using the standard library's unicodedata module.
import unicodedata
def normalize_accents(text: str) -> str:
"""Convert accented unicode characters to ASCII equivalents."""
decomposed = unicodedata.normalize('NFD', text)
ascii_text = ''.join(
char for char in decomposed
if unicodedata.category(char) != 'Mn'
)
return unicodedata.n…Python String Helper Functions for Beginners
A set of beginner-friendly Python functions that count words, reverse text, convert to title case, strip punctuation, and compute character frequency from a string.
def count_words(text):
"""Count the number of words in a string."""
return len(text.split())
def reverse_text(text):
"""Reverse the entire string."""
return text[::-1]
def title_case(text):
"""Capitalize the first letter of each word."""
return text.title()
def remove_punctuation(text):
…Remove Substring Occurrences Case-Insensitively in Python
This code removes every case-insensitive occurrence of a given substring from a text string using a simple looping approach.
def remove_occurrences_ci(text: str, substring: str) -> str:
"""Remove all case-insensitive occurrences of substring from text."""
if not substring:
return text
result = []
i = 0
lower_text = text.lower()
lower_sub = substring.lower()
sub_len = len(substring)
while i <…Text Processor Functions for Beginners in Python
Demonstrates simple text-processing utilities: word counting, word reversal, whitespace normalization, and lowercase conversion using basic string methods.
def count_words(text):
"""Return the number of words in a string."""
return len(text.split())
def reverse_words(text):
"""Return the text with words in reverse order."""
return ' '.join(text.split()[::-1])
def remove_extra_spaces(text):
"""Return text with extra whitespace collapsed to a single s…How to Build a Text Processor with Lists and Loops in Python
A beginner-friendly Python script that analyzes text by counting sentences, words, and word lengths using lists and for loops, then prints the results.
def process_text(text):
"""Simple text processor for beginners using lists and loops."""
sentences = text.replace('!', '.').replace('?', '.').split('.')
words = text.split()
word_counts = []
for sentence in sentences:
sentence_word_count = len(sentence.split())
word_counts.appe…How to Process Text Lines with Lists and Loops in Python
This code processes a list of text lines by stripping whitespace, converting to uppercase, and reporting character counts per line and totals.
def process_text(lines):
"""Convert a list of text lines to uppercase and report line statistics."""
processed = []
total_chars = 0
for index, line in enumerate(lines, start=1):
cleaned = line.strip().upper()
processed.append(cleaned)
total_chars += len(cleaned)
pri…How to Process Text into Words in Python
Splits a string into words, strips punctuation, and returns a list of uppercase words using a loop.
def convert_text_processor(text):
words = text.split()
processed = []
for word in words:
clean = word.strip('.,!?;:')
if len(clean) > 0:
processed.append(clean.upper())
return processed
if __name__ == "__main__":
sample_text = "Hello, world! This is a Python e…How to Process Text with Lists and Loops in Python
A beginner-friendly text processor that splits a sentence into words, filters by length, counts vowels, and reports results using lists and loops.
text = "Python makes text processing easy and fun"
words = text.lower().split()
print("Words in the sentence:")
for index, word in enumerate(words, start=1):
print(f"{index}. {word}")
filtered_words = [word for word in words if len(word) > 3]
print(f"\nWords longer than 3 characters: {filtered_words}")
letter…How to Process Text with Lists and Loops in Python
Iterate over a list of text lines to count words, show uppercase versions, and report character counts per line.
# text_processor.py
def process_text(lines):
"""Count words, show uppercase, and count characters per line."""
total_words = 0
print("Line-by-line analysis:")
for i, line in enumerate(lines, start=1):
words = line.split()
total_words += len(words)
print(f" Line {i}: {len(words…Count Words in Python with Dictionaries and Sets
Text analysis example that counts total words, finds unique words with a set, and tallies character frequencies with a dictionary.
def analyze_text(text: str) -> dict:
"""Count words, find unique words, and show common characters."""
words = text.lower().split()
word_count = len(words)
unique_words = set(words)
char_counts = {}
for word in words:
for char in word:
if char.isalpha():
…Count word frequency in Python with dict and Counter
Count how often each word appears in a string using Counter, converted to a plain dict, and print results alphabetically.
from collections import Counter
import re
def count_word_frequency(text):
words = re.findall(r'\b\w+\b', text.lower())
return dict(Counter(words))
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog. The dog barks, and the fox runs."
frequency = count_word_frequency(…How to Count Word Frequencies in Python
Count how often each word appears in a string and list the unique words using Python dictionaries and sets.
def text_processor(text):
words = text.lower().split()
word_count = {}
for word in words:
word_count[word] = word_count.get(word, 0) + 1
unique_words = set(words)
return word_count, unique_words
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog and t…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 Count Words and Find Common Words in Python with Dictionaries and Sets
Build a simple text processor that counts unique words with dictionaries and finds common words across text halves using sets.
def process_text(text):
"""Process text: count unique words with counts, find common words."""
words = text.lower().replace(",", "").replace(".", "").split()
word_counts = {}
for word in words:
word_counts[word] = word_counts.get(word, 0) + 1
total_words = len(words)
unique_wo…How to Validate Text and Count Words in Python
Count word frequencies, find unique and repeated words in a text using Python dictionaries and sets for beginner text validation.
def validate_text(text):
words = text.lower().split()
word_counts = {}
for word in words:
cleaned = word.strip('.,!?;:"\'')
if cleaned:
word_counts[cleaned] = word_counts.get(cleaned, 0) + 1
unique_words = set(word_counts.keys())
repeated_words = {word for word…How to count words and find unique words in Python
Build a beginner-friendly text processor that counts word frequencies, finds unique words, and identifies words with vowels using dictionaries and sets.
def text_processor(text):
words = text.lower().replace(",", "").replace(".", "").split()
word_count = {}
for word in words:
word_count[word] = word_count.get(word, 0) + 1
unique_words = set(words)
vowels = set("aeiou")
words_with_vowels = {word for word in unique_words if vowe…Text Processor with Dictionaries and Sets in Python
Build a simple text processor that counts word frequencies with a dictionary and tracks unique words with a set.
def analyze_text(text):
words = text.lower().split()
word_freq = {}
unique_words = set()
for word in words:
clean_word = word.strip('.,!?;:')
if clean_word:
word_freq[clean_word] = word_freq.get(clean_word, 0) + 1
unique_words.add(clean_word)
return…How to Estimate Token Count in Python
Estimates tokens in a text string using a whitespace and punctuation heuristic without external libraries.
def estimate_tokens(text: str) -> int:
"""Estimate token count using whitespace and punctuation heuristics."""
if not text:
return 0
words = text.split()
total_punctuation = sum(1 for char in text if char in ".,!?;:")
special_tokens = sum(1 for char in text if char in "\n\t")
# Rough …How to Build an argparse CLI That Filters File Lines by Keyword in Python
This Python script is a command-line tool built with argparse that reads a text file and prints only the lines that contain (or don't contain) a given keyword.
import argparse
import sys
def main():
parser = argparse.ArgumentParser(description="Filter lines from a file by keyword.")
parser.add_argument("input", type=str, help="File to read")
parser.add_argument("keyword", type=str, help="Keyword to filter lines")
parser.add_argument("--contains", action="sto…Build a Simple Log Graph in Python
Create a basic one-dimensional bar chart from log lines by counting occurrences of leading numeric keys.
import heapq
def log_graph(log_lines: list[str]) -> str:
"""Build a simple per-line, one-dimensional visual graph from log entries."""
counts: dict[int, int] = {}
for line in log_lines:
tokens = line.split()
if tokens:
try:
idx = int(tokens[0])
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