Dictionaries & sets
Key–value maps, uniqueness, counting, grouping, and fast lookups.
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(…Get Nested Dict Value with Default in Python
Access values deep inside a nested dictionary using a dotted path string, returning a default when any key is missing.
def get_nested(d, path, default=None):
"""Walk a nested dict along a dotted path, returning default if missing."""
current = d
for key in path.split("."):
if isinstance(current, dict) and key in current:
current = current[key]
else:
return default
return current
…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 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…How to Parse Data Into Dictionaries and Sets in Python
Parses raw student strings into a dictionary of lists and finds unique courses using a set.
from collections import defaultdict
def parse_students(raw_data):
"""Parse raw student strings into a dictionary of lists."""
parsed = defaultdict(list)
for entry in raw_data:
name, _, course = entry.partition(":")
parsed[course.strip()].append(name.strip())
return dict(parsed)
def fi…How to Parse Query String to Dict with Duplicate Keys in Python
Convert a URL query string into a Python dictionary, merging duplicate keys into lists while keeping single values as scalars.
from urllib.parse import parse_qs
def parse_query_to_dict(query_string):
parsed = parse_qs(query_string, keep_blank_values=True)
return {key: values if len(values) > 1 else values[0] for key, values in parsed.items()}
if __name__ == "__main__":
query = "name=John&name=Jane&age=30&city=&city=Paris&empty…How to Serialize a Dictionary to a Query String in Python
Convert a Python dictionary into a URL-encoded query string using the standard library's urllib.parse.urlencode function.
import urllib.parse
def dict_to_query_string(params):
"""Serialize a dictionary to a URL query string."""
return urllib.parse.urlencode(params)
if __name__ == "__main__":
data = {
"name": "Alice Johnson",
"age": 30,
"city": "New York",
"interests": ["coding", "hiking"]
…How to convert string values to int or float in Python dicts
Recursively convert string values in nested dicts and lists to ints or floats when possible, leaving other strings untouched.
def coerce_str_values(data):
"""Recursively convert string values that look like ints or floats."""
if isinstance(data, dict):
return {key: coerce_str_values(val) for key, val in data.items()}
elif isinstance(data, list):
return [coerce_str_values(item) for item in data]
elif isinstance…Parse Env Vars into Typed Dict in Python
Convert a list of environment variable names into a dictionary with automatically detected types (bool, int, float, or string), defaulting missing vars to None.
import os
from typing import Any, Dict
def parse_env_vars(env_names: list[str], env: Dict[str, str] | None = None) -> Dict[str, Any]:
"""Parse a list of environment variable names into a typed dict.
Each variable is parsed as:
- bool: "true"/"false" (case-insensitive)
- int: if it can be converted t…Browse by section
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Dictionaries & sets — Python code examples
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