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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…
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…
Convert Image to ASCII Art in Python
Convert any image to ASCII art by resizing, converting to grayscale, and mapping pixel brightness to characters using Pillow.
from PIL import Image
import sys
ASCII_CHARS = "@%#*+=-:. "
def resize_image(image, new_width=100):
"""Resize image maintaining aspect ratio."""
width, height = image.size
ratio = height / width
new_height = int(new_width * ratio * 0.55) # 0.55 adjusts for font aspect ratio
return image.resize((…
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…
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 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 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 …
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)
Implement Insert Delete GetRandom O(1) in Python
Build a RandomizedSet class that supports insert, delete, and get_random in average O(1) time using a list and a dictionary mapping values to indices.
import random
class RandomizedSet:
def __init__(self):
self.values = []
self.index_map = {}
def insert(self, val):
if val in self.index_map:
return False
self.index_map[val] = len(self.values)
self.values.append(val)
return True
def delete(self…
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:
…
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:": …
Generate an OpenAPI Spec from Mock Routes in Python
This Python script generates an OpenAPI 3.0 specification from a simple mock routes dictionary, mapping each HTTP method to response examples.
import json
from pathlib import Path
def generate_openapi_spec(routes: dict, title: str = "Mock API", version: str = "1.0.0") -> dict:
paths = {}
for route, methods in routes.items():
path_item = {}
for method, response_data in methods.items():
method = method.lower()
…
Consistent Hashing Cache Shard in Python
A minimal consistent hashing ring with virtual nodes that distributes cache keys across shards and minimizes re-mapping when a node is removed.
import hashlib
import bisect
class ConsistentHashRing:
def __init__(self, nodes=None, replicas=3):
self.replicas = replicas
self.ring = {}
self.sorted_keys = []
if nodes:
for node in nodes:
self.add_node(node)
def _hash(self, key):
return i…
How to Mock Kedro Pipeline Nodes in Python
Create a modular Kedro pipeline with node functions, namespacing, and input/output mapping to mock pipeline execution locally.
from kedro.pipeline import Pipeline, node
from kedro.pipeline.modular_pipeline import pipeline as modular_pipeline
def preprocess(data: list) -> list:
"""Clean data by removing None values."""
return [item for item in data if item is not None]
def transform(data: list) -> list:
"""Add 1 to each numeric…
Consistent Hashing with Virtual Buckets in Python
This code maps many virtual buckets onto a few physical buckets using a consistent hashing ring, ensuring balanced distribution with minimal remapping when physical buckets change.
import random
class VirtualBuckets:
"""Maps many virtual buckets onto few physical buckets using consistent hashing."""
def __init__(self, physical_buckets, virtual_factor=100):
self.physical = list(physical_buckets)
self.virtual_factor = virtual_factor
self.ring = []
self…
How to Implement Consistent Hashing in Python
Build a consistent hash ring in Python that distributes keys across nodes and minimizes remapping when nodes are added or removed.
import hashlib
from bisect import bisect_right
class ConsistentHashRing:
def __init__(self, nodes, replicas=3):
self.replicas = replicas
self.ring = {}
self.sorted_keys = []
for node in nodes:
self.add_node(node)
def _hash(self, key):
return int(hashlib.md…
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