Modern tooling
uv, ruff, pyproject.toml, packaging, and current Python project workflows.
Data Conversion Helper Functions in Python
A set of beginner-friendly helper functions to convert between JSON strings and Python data, parse dates, and read/write files using pathlib.
from datetime import datetime
from pathlib import Path
import json
def to_json(data, indent=2):
"""Convert Python data to pretty-printed JSON string."""
return json.dumps(data, indent=indent, default=str)
def from_json(json_string):
"""Parse JSON string back into Python data."""
return json.loads(jso…How to Format Data with Python's datetime and JSON Helpers
A beginner-friendly set of helper functions to format dates and safely read/write JSON files in Python.
from datetime import datetime
from pathlib import Path
import json
def format_today(pattern: str = "%Y-%m-%d") -> str:
"""Return today's date formatted with the given pattern."""
return datetime.now().strftime(pattern)
def load_json(file_path: str) -> dict:
"""Read and parse a JSON file safely."""
…How to Mock Twine Upload to TestPyPI in Python
Simulate a twine upload to TestPyPI with a dry-run mock function that validates distribution files and prints the intended upload action without any network call.
import subprocess
import sys
# Mock twine upload to TestPyPI using subprocess dry-run
def mock_twine_upload(dist_file: str, repo_url: str = "https://test.pypi.org/legacy/") -> None:
"""Simulate twine upload by checking dist file and printing intended action."""
if not dist_file.endswith((".whl", ".tar.gz")):
…How to Type Check a Mock with pyright in Python
Shows how pyright validates a mock function against a TypedDict and Callable signature before runtime.
from typing import TypedDict, Callable
class User(TypedDict):
id: int
name: str
def get_user_name(user_id: int, get_user: Callable[[int], User]) -> str:
user = get_user(user_id)
return user["name"]
def mock_get_user(user_id: int) -> User:
return {"id": user_id, "name": f"User {user_id}"}
if…How to Validate Data with a Simple Dict-Based Rules Helper in Python
Validates a dictionary against a set of callable rules, printing pass/fail per field and returning an overall boolean.
import json
from pathlib import Path
from typing import Any, Callable
def validate_data(
data: dict[str, Any],
rules: dict[str, Callable[[Any], bool]],
path: Path | None = None,
) -> bool:
"""Validate a dict against a set of simple rules."""
all_valid = True
for field, validator in rules.item…Browse by section
Each section groups closely related Python snippets.
Modern tooling — Python code examples
What you will find here
This page collects modern tooling snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.