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How to Translate Characters in a String with str.maketrans in Python
Build and apply character translation tables with str.maketrans and str.translate to replace, delete, or remap letters in a Python string.
def translate_demo():
# Build a translation table: a→1, e→2, i→3, o→4, u→5
table = str.maketrans("aeiou", "12345")
text = "Hello, Python world! Keep coding, friend."
translated = text.translate(table)
print(f"Original: {text}")
print(f"Translated: {translated}")
# Example wit…How to Build a Frequency Map from a List in Python
This code builds a dictionary that maps each unique element in a list to its count using the Counter class from the collections module.
from collections import Counter
def build_frequency_map(values):
"""Return a dictionary mapping each unique value to its frequency."""
return dict(Counter(values))
if __name__ == "__main__":
data = ["apple", "banana", "apple", "cherry", "banana", "apple"]
freq_map = build_frequency_map(data)
prin…How to Pass a Function as a Callback to map and filter in Python
Shows how to apply custom functions to every element of a list using map and filter callbacks in Python.
def double(x):
return x * 2
def is_even(x):
return x % 2 == 0
if __name__ == "__main__":
numbers = [1, 2, 3, 4, 5]
doubled = list(map(double, numbers))
evens = list(filter(is_even, numbers))
print("Original:", numbers)
print("Doubled:", doubled)
print("Evens:", evens)How to Use a Dispatch Table in Python (Map Strings to Functions)
Maps string command names to callable functions in a dictionary, then dispatches calls safely with error handling.
def add(a, b):
return a + b
def subtract(a, b):
return a - b
def multiply(a, b):
return a * b
def divide(a, b):
if b == 0:
raise ValueError("Division by zero")
return a / b
dispatch = {
"add": add,
"subtract": subtract,
"multiply": multiply,
"divide": divide,
}
def…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…Build a File Index by Relative Path Hash Map in Python
Recursively walk a directory and map normalized relative paths to absolute file paths using a defaultdict hash map.
import os
from collections import defaultdict
def build_file_index(root_dir):
index = defaultdict(list)
for dirpath, dirnames, filenames in os.walk(root_dir):
for filename in filenames:
full_path = os.path.join(dirpath, filename)
relative_path = os.path.relpath(full_path, roo…How to Group Files by Extension in Python
Group file names by their file extension using a dictionary and pathlib, producing a simple clear mapping for beginners.
from pathlib import Path
def group_data_by_extension(files: list[Path]) -> dict[str, list[str]]:
"""Group file names by their extension."""
grouped: dict[str, list[str]] = {}
for file in files:
ext = file.suffix.lower()
grouped.setdefault(ext, []).append(file.name)
return grouped
if…Read a CSV File with csv.DictReader in Python
Read a CSV file as a list of dictionaries, using csv.DictReader to map each row to column names.
import csv
from pathlib import Path
def read_csv_with_dictreader(file_path):
data = []
with open(file_path, mode='r', newline='', encoding='utf-8') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
data.append(row)
return data
if __name__ == "__main__":
# Cre…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)…Check Invertible Mapping for Duplicate Values in Python
Detect duplicate values among (key, value) pairs to ensure the mapping is invertible, using a dictionary for O(1) lookups.
def invertible_after_dedup(pairs):
"""
Check whether a set of (key, value) pairs is invertible,
i.e., no duplicate values exist for different keys.
"""
seen = {}
for key, value in pairs:
if value in seen and seen[value] != key:
return False, f"Duplicate value '{value}' for k…How to Index a List of Records by Unique ID in Python
Build a dictionary that maps each record's unique id to the record itself from a list of dictionaries.
from typing import List, Dict, Any
def index_by_id(records: List[Dict[str, Any]], id_field: str = "id") -> Dict[Any, Dict[str, Any]]:
"""Build a dictionary mapping each record's unique id to the record itself."""
return {record[id_field]: record for record in records}
if __name__ == "__main__":
sample_re…How to Map Dictionary Values with a Transformation Function in Python
Create a reusable function that applies a transformation to every value in a dictionary and returns a new dict.
def transform_dict_values(d, func):
"""Apply a transformation function to every value in a dictionary."""
return {key: func(value) for key, value in d.items()}
if __name__ == "__main__":
original = {"a": 1, "b": 2, "c": 3}
doubled = transform_dict_values(original, lambda x: x * 2)
print(doubled)
…How to Use ChainMap for Layered Config Lookup in Python
This code demonstrates using collections.ChainMap to combine multiple dictionaries into a single layered lookup, where earlier maps override later ones.
from collections import ChainMap
defaults = {"theme": "light", "lang": "en", "debug": False}
user = {"lang": "de", "auto_save": True}
runtime = {"debug": True}
config = ChainMap(runtime, user, defaults)
if __name__ == "__main__":
print("theme:", config["theme"])
print("lang:", config["lang"])
print("deb…How to Use MappingProxyType to Create Immutable Dict Views in Python
Create a read-only, immutable view of a dictionary using MappingProxyType from the types module, while the original dict stays mutable.
from types import MappingProxyType
config = {"debug": True, "port": 8080}
# Create an immutable read-only view of the dict
read_only_config = MappingProxyType(config)
print(f"Read-only value: {read_only_config['debug']}")
print(f"Dict is mapping: {isinstance(read_only_config, dict)}")
# Original dict can still be …Python Factory Method: Create Shapes by Type String
A factory method that maps a type string to a concrete shape class and returns an instance, with runtime error handling.
class Shape:
def draw(self):
raise NotImplementedError
class Circle(Shape):
def draw(self):
return "Drawing a circle"
class Square(Shape):
def draw(self):
return "Drawing a square"
class Triangle(Shape):
def draw(self):
return "Drawing a triangle"
class ShapeFact…Find Maximum Distance Between Identical Elements in Python
Compute the maximum index distance between any two identical elements in a list using a dictionary to track first occurrences.
from collections import defaultdict
def max_distance_between_identical(nums):
first_occurrence = {}
max_dist = 0
for i, num in enumerate(nums):
if num in first_occurrence:
dist = i - first_occurrence[num]
max_dist = max(max_dist, dist)
else:
first_occur…How to Combine filter and map with a List Comprehension in Python
This Python code demonstrates how to combine filtering and mapping in a single list comprehension and shows the equivalent filter() and map() approach.
def square(x):
return x * x
def is_even(x):
return x % 2 == 0
numbers = [1, 2, 3, 4, 5, 6, 7, 8]
result = [square(x) for x in numbers if is_even(x)]
print(f"Original numbers: {numbers}")
print(f"Squares of even numbers: {result}")
# Combined filter + map equivalent
filtered = filter(is_even, numbers)
mapp…How to Map Strings to Uppercase in Python
Loops through a list of strings and builds a new list with each string converted to uppercase.
strings = ["hello", "world", "python", "skillset"]
uppercased = []
for s in strings:
uppercased.append(s.upper())
print(uppercased)Dict Comprehension to Map Keys to Lengths in Python
Build a dictionary that maps each word to its character count using a dictionary comprehension.
words = ["apple", "banana", "cherry", "date", "elderberry"]
word_lengths = {word: len(word) for word in words}
print(word_lengths)How to Lazily Transform Items in Python with a Generator
Map a transform function over an iterable lazily with a generator so items are processed on demand, not up front.
def lazy_map(items, transform):
for item in items:
yield transform(item)
def double(x):
return x * 2
def upper(s):
return s.upper()
if __name__ == "__main__":
numbers = [1, 2, 3, 4, 5]
doubled = lazy_map(numbers, double)
print("Doubled numbers:", end=" ")
for value in doubled:
…How to Use starmap() to Unpack Tuple Arguments in Python
Use itertools.starmap to apply a function to each tuple in an iterable, unpacking tuple elements as separate arguments and returning an iterator of results.
from itertools import starmap
def multiply(a, b):
return a * b
if __name__ == "__main__":
pairs = [(2, 3), (4, 5), (6, 7), (8, 9)]
results = list(starmap(multiply, pairs))
print(results)Memory efficient map over large file in Python
A generator-based streaming map that processes a large file line by line without loading the whole file into memory.
import sys
def process_lines(file_path):
"""Memory-efficient map over a large file: yields processed lines."""
with open(file_path, 'r') as f:
for line in f:
# Example mapping: strip whitespace and uppercase
yield line.strip().upper()
if __name__ == "__main__":
# Use a sma…Route Tool Call Name to Python Handler Dict
Routes a tool call name to the correct Python handler function using a dictionary lookup, returning an error for unknown tools.
def get_name():
return {"name": "Alice"}
def get_age():
return {"age": 30}
def get_email():
return {"email": "alice@example.com"}
handlers = {
"get_name": get_name,
"get_age": get_age,
"get_email": get_email,
}
def route(tool_call):
handler = handlers.get(tool_call["name"])
if handl…How to Map Network Drive Paths to Local Paths in Python
Convert mock SMB network drive paths (like 'S:\reports\q1.xlsx') to local placeholder paths and back using a simple mapping dictionary in Python.
"""Map mock SMB network drive paths to local placeholder paths."""
from dataclasses import dataclass
@dataclass(frozen=True)
class NetworkDrive:
letter: str
remote_path: str
DRIVES = {
"S:": NetworkDrive("S", r"\\server01\shares\sales"),
"M:": NetworkDrive("M", r"\\server02\media\movies"),
"X:": …Browse by section
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