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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Pipe Data Through a List of Transform Functions in Python
Applies a sequence of functions to an initial value using functools.reduce, creating a reusable pipe utility.
from functools import reduce
def pipe(data, *transforms):
return reduce(lambda value, func: func(value), transforms, data)
def double(x):
return x * 2
def add_one(x):
return x + 1
def to_string(x):
return f"Result: {x}"
if __name__ == "__main__":
initial = 5
result = pipe(initial, double, …How to Write a Python Decorator with functools.wraps
Create a decorator that wraps a function while preserving its metadata using functools.wraps.
from functools import wraps
def logger(func):
@wraps(func)
def wrapper(*args, **kwargs):
print(f"Calling {func.__name__}")
return func(*args, **kwargs)
return wrapper
@logger
def greet(name):
"""Return a friendly greeting."""
return f"Hello, {name}!"
if __name__ == "__main__":…How to Dump a Debugging Repr for Unknown Types in Python
Build a fallback repr that shows dataclass fields or object attributes for any value, handy when debugging unknown types.
import dataclasses
from typing import Any
@dataclasses.dataclass
class Sample:
name: str
values: list[int]
def dump_repr(obj: Any) -> str:
"""Return a concise but complete repr for debugging unknown types."""
if dataclasses.is_dataclass(obj):
fields = ", ".join(
f"{field.name}={…How to Validate JSON in Python and Catch JSONDecodeError
A robust Python function that attempts to parse JSON strings and returns a boolean plus either the parsed data or a descriptive error message when decoding fails.
import json
def validate_json(json_string):
"""Try to parse JSON, return (is_valid, data_or_error)."""
try:
data = json.loads(json_string)
return True, data
except json.JSONDecodeError as e:
return False, f"Invalid JSON: {e}"
if __name__ == "__main__":
test_inputs = [
…How to check for None and raise helpful errors in Python
A defensive function that explicitly validates data, keys, and values — raising descriptive ValueError and KeyError exceptions before returning a result.
def get_value(data, key):
if data is None:
raise ValueError("data cannot be None")
if key not in data:
raise KeyError(f"key '{key}' not found in data")
result = data[key]
if result is None:
raise ValueError(f"value for key '{key}' is None")
return result
if __name__ == "__…Automatically Highlight Data Validation Errors Inside Excel Files in Python
Load an Excel file with openpyxl, iterate over cells, and highlight invalid data (empty, negative) with a red fill and error message.
import openpyxl
from openpyxl.styles import PatternFill
from pathlib import Path
def highlight_validation_errors(filepath: str, output_path: str = None):
wb = openpyxl.load_workbook(filepath)
red_fill = PatternFill(start_color="FF0000", end_color="FF0000", fill_type="solid")
for sheet in wb.worksheet…Build a Command-Line To-Do List Application with Data Persistence in Python
A persistent command-line to-do list that saves tasks as JSON, supporting add, show, toggle done, and quit commands.
import json
import os
TODO_FILE = "todos.json"
def load_todos():
if not os.path.exists(TODO_FILE):
return []
with open(TODO_FILE, "r") as f:
return json.load(f)
def save_todos(todos):
with open(TODO_FILE, "w") as f:
json.dump(todos, f, indent=2)
def show_todos(todos):
if not…Build a Simple ETL Pipeline in Python
A simple ETL pipeline that reads JSON Lines, transforms records with filtering and normalization, and writes the result to JSON.
import json
from pathlib import Path
def read_input(file_path: Path) -> list[dict]:
"""Read JSON lines file into list of dicts."""
with file_path.open("r", encoding="utf-8") as f:
return [json.loads(line) for line in f if line.strip()]
def transform(records: list[dict]) -> list[dict]:
"""Transf…Convert File Data to a Dictionary in Python
This function scans a directory and converts each file's metadata (name, size, extension) into a structured dictionary for easy access.
from pathlib import Path
def convert_files_data(directory: str) -> dict:
data = {}
base = Path(directory)
if not base.exists():
return data
for file in base.iterdir():
if file.is_file():
data[file.name] = {
"size": file.stat().st_size,
"exten…Create a Local File Versioning System Using Pure Python
Track file changes locally by copying versions with SHA-256 hashes and JSON metadata using only the Python standard library.
import os
import shutil
import hashlib
import json
import time
from pathlib import Path
class LocalFileVersioning:
def __init__(self, target_dir="versioned_files", versions_dir="versions"):
self.target_dir = Path(target_dir)
self.versions_dir = Path(versions_dir)
self.metadata_file = self.…Create a Python Tool That Generates Professional Excel Dashboards
Generate a professional sales dashboard in an Excel workbook with styled headers, a bar chart, and formatted number cells using the openpyxl library.
import openpyxl
from openpyxl.chart import BarChart, Reference
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from openpyxl.utils import get_column_letter
def create_sales_dashboard(workbook_path: str) -> None:
"""Generate a professional sales dashboard in an Excel workbook."""
wb = op…Create an In-Memory SQLite Table and Query It in Python
This code creates an in-memory SQLite database, defines an employees table, inserts sample rows, and runs a filtered query with sorted results.
import sqlite3
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
cursor.execute("""
CREATE TABLE employees (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
department TEXT NOT NULL,
salary REAL
)
""")
employees = [
(1, "Alice", "Engineering", 95000),
(2, "Bob", "…Detect Outliers in CSV Data Using Z-Score in Python
Read a CSV file and detect outliers in a numeric column by computing z-scores, flagging those exceeding a given threshold — no machine learning required.
import csv
import statistics
from math import sqrt
def detect_outliers(csv_path, column_name, threshold=2.0):
"""Detect outliers in a numeric column using z-score method."""
values = []
with open(csv_path, 'r', newline='') as f:
reader = csv.DictReader(f)
if column_name not in reader.field…Export List of Dicts to CSV in Python
Write a list of dictionaries (dataframe-like) to a CSV file with headers using the standard library csv module and verify by reading it back.
import csv
def export_to_csv(data, filename):
"""Export a list of dicts to a CSV file."""
if not data:
print("No data to export")
return
# Get column names from the keys of the first dict
fieldnames = list(data[0].keys())
with open(filename, 'w', newline='', encoding='utf…Export SQLite Query Results to CSV in Python
Connects to a SQLite database, runs a query, and writes the result rows and column headers to a CSV file using the standard library.
import sqlite3
import csv
def export_query_to_csv(db_path, query, csv_path):
conn = sqlite3.connect(db_path)
cursor = conn.cursor()
cursor.execute(query)
rows = cursor.fetchall()
column_names = [description[0] for description in cursor.description]
with open(csv_path, 'w', newline='', encodi…File Data Helper Functions in Python
Read and write text and JSON files, and list files in a directory, using pathlib-based helper functions.
from pathlib import Path
def load_text_file(filepath):
"""Read a text file and return its contents as a string."""
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"File not found: {filepath}")
return path.read_text(encoding="utf-8")
def save_text_file(filepath, content):
…How to Bulk Insert Rows into SQLite in Python
Insert many rows into an SQLite table in one call with cursor.executemany, then verify them with a SELECT query.
import sqlite3
# Create an in-memory database and a table
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
cursor.execute("CREATE TABLE products (name TEXT, price REAL, quantity INTEGER)")
# Data to insert in bulk
products = [
("Laptop", 999.99, 5),
("Mouse", 19.99, 50),
("Keyboard", 49.99, 30),…How to Convert CSV Column Types While Reading in Python
Read a CSV file and automatically convert column values to int, float, str, or bool based on type suffixes in the header names.
import csv
from pathlib import Path
from typing import Any
def read_csv_with_types(filepath: str) -> list[dict[str, Any]]:
"""Read CSV and convert column types based on header suffixes."""
converters = {
"int": int,
"float": float,
"str": str,
"bool": lambda v: v.strip().lower(…How to Copy a File with shutil.copy2 in Python
Copy a file while preserving metadata like timestamps and permissions using Python's shutil.copy2 and pathlib.
import shutil
from pathlib import Path
source = Path("sample.txt")
destination = Path("sample_copy.txt")
source.write_text("Hello, PythonSkillset!")
if __name__ == "__main__":
shutil.copy2(source, destination)
copied = destination.read_text()
print(f"Copied content: {copied}")
print(f"Source exists:…How to Fetch Weather Data from a Public API in Python
Fetches and parses weather data from a free public API using only the Python standard library.
import urllib.request
import json
def get_weather(city):
base_url = f"https://wttr.in/{city}?format=j1"
with urllib.request.urlopen(base_url) as response:
data = json.loads(response.read().decode())
current = data["current_condition"][0]
temp = current["temp_C"]
desc = current["weatherDesc…How to Filter CSV Rows by Column Value in Python
Filter CSV rows based on a column value condition using the standard csv module and a lambda function.
import csv
def filter_csv(input_file, output_file, column, condition):
with open(input_file, newline='', encoding='utf-8') as infile, \
open(output_file, 'w', newline='', encoding='utf-8') as outfile:
reader = csv.DictReader(infile)
fieldnames = reader.fieldnames
writer = csv.Dict…How to Generate an Inventory Report of All Files in Python
Walk a directory tree, collect metadata for every file, and write a CSV inventory report using Python's os, pathlib, and csv modules.
import os
import csv
from pathlib import Path
from datetime import datetime
def generate_inventory_report(root_dir: str = "/", output_file: str = "inventory_report.csv"):
headers = ["File Path", "Size (bytes)", "Last Modified", "File Type"]
rows = []
start_time = datetime.now()
for dirpath, dirna…How to Handle Missing Values in a CSV Numeric Column in Python
Clean missing entries in a CSV numeric column by filling them with the mean, median, a custom value, or dropping rows.
import csv
from pathlib import Path
import statistics
def clean_csv_numeric(input_path: str, output_path: str, column: str, strategy: str = "mean") -> None:
"""
Handles missing values in a numeric column of a CSV file.
Strategies: 'mean', 'median', 'drop', or 'fill' with a specified value.
"""
row…How to List File Information in a Directory with Python
A helper that walks a directory and returns each file's name, size, and extension as a list of dictionaries.
from pathlib import Path
def get_files_data(directory: str) -> list[dict]:
"""Return basic info about all files in a directory."""
files = []
for path in Path(directory).iterdir():
if path.is_file():
files.append({
"name": path.name,
"size": path.stat()…Browse by section
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