Dictionaries & sets
Key–value maps, uniqueness, counting, grouping, and fast lookups.
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():
…How to Count Tags with Sets and Dictionaries in Python
Count tag frequencies and collect unique tags from a list of dictionaries using Counter and sets in Python.
from collections import Counter
import json
def count_tags(entries):
"""Count tag frequencies across a list of entry dicts, using sets/dicts."""
tag_counter = Counter()
all_tags = set()
for entry in entries:
tags = set(entry["tags"])
all_tags.update(tags)
tag_counter.update(ta…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 Find the Intersection of Permission Sets in Python
This code defines a function that takes a list of permission sets and returns a set containing only the permissions common to all sets, with a short-circuit for empty results.
from typing import Set
def intersect_permissions(permission_sets: list[Set[str]]) -> Set[str]:
"""
Given a list of permission sets, return the common permissions
present in every set.
"""
if not permission_sets:
return set()
common = permission_sets[0]
for perm_set in permissi…How to Group a List of Dictionaries by Key in Python
Group a list of dictionaries by a specified key field using dict.setdefault to build a dictionary of lists.
def group_by_key(records, key):
grouped = {}
for record in records:
grouped.setdefault(record[key], []).append(record)
return grouped
if __name__ == "__main__":
data = [
{"name": "Alice", "dept": "engineering"},
{"name": "Bob", "dept": "sales"},
{"name": "Carol", "dept"…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…Browse by section
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Dictionaries & sets — Python code examples
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