Modern tooling
uv, ruff, pyproject.toml, packaging, and current Python project workflows.
How to Generate a Mock devcontainer.json Config in Python
Build a reproducible devcontainer.json file with Python, composing name, image, extensions, forwarded ports, and a post-create command as a dict.
import json
from pathlib import Path
def create_devcontainer_config(
image: str = "mcr.microsoft.com/devcontainers/python:3.11",
name: str = "python-dev-container",
ports: list[int] | None = None,
post_create: str | None = None,
) -> dict:
config = {
"name": name,
"image": image,
…
How to Load and Inspect CSV Data with a Dataclass Helper in Python
This code defines a DataHelper dataclass that reads a CSV file into a list of dictionaries and prints basic dataset information.
from pathlib import Path
from dataclasses import dataclass
from typing import Any
@dataclass
class DataHelper:
"""Simple helper for loading and inspecting CSV data."""
filepath: Path
def load_csv(self, *, delimiter: str = ",") -> list[dict[str, Any]]:
"""Read CSV into a list of dictionaries."""
…
How to Save and Load JSON Files in Python
Create a simple data helper to save Python dictionaries as pretty-printed JSON files and load them back reliably using pathlib and the stdlib json module.
import json
from pathlib import Path
from typing import Any
def save_json(data: Any, filename: str) -> None:
"""Save data as pretty-printed JSON to the current directory."""
path = Path(filename)
with path.open("w", encoding="utf-8") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
def lo…
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…
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