Python Automation Skill

When to Use

Use this skill when creating Python scripts for automations, data processing, API calls, or utility tasks.

Golden Rules

•Virtual environment always — never install globally
•Secrets in .env — never hardcode API keys
•Logger not print — easier to debug later
•Fail loud — if something breaks, make it obvious

Quick Start Template

python

#!/usr/bin/env python3
"""What this script does in one line."""

import logging
import os
from pathlib import Path

from dotenv import load_dotenv

load_dotenv()

# Config
API_KEY = os.environ["API_KEY"]
OUTPUT_DIR = Path("output")

# Logging
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(message)s")
log = logging.getLogger(__name__)


def main():
    log.info("Starting")
    OUTPUT_DIR.mkdir(exist_ok=True)
    
    # Your code here
    
    log.info("Done")


if __name__ == "__main__":
    main()

Virtual Environment

bash

python3 -m venv venv
source venv/bin/activate
pip3 install python-dotenv requests
pip3 freeze > requirements.txt

Add to .gitignore:

code

venv/
.env
__pycache__/

Secrets

Create .env:

code

API_KEY=your-key-here

Create .env.example (commit this):

code

API_KEY=

Load in script:

python

from dotenv import load_dotenv
load_dotenv()

API_KEY = os.environ["API_KEY"]

Logging

python

log.info(f"Processing {len(items)} items")
log.warning(f"Skipping bad record: {record}")
log.error(f"Failed: {e}")

Error Handling

Keep it simple — catch what you expect, let the rest crash loudly:

python

try:
    response = requests.get(url, timeout=30)
    response.raise_for_status()
except requests.RequestException as e:
    log.error(f"Request failed: {e}")
    raise

Files

Use pathlib:

python

from pathlib import Path

output_dir = Path("output")
output_dir.mkdir(exist_ok=True)

file_path = output_dir / "results.csv"
file_path.write_text(content, encoding="utf-8")

HTTP Requests

python

import requests

response = requests.get(url, timeout=30)
response.raise_for_status()
data = response.json()

CSV Output

python

import csv

with open("output.csv", "w", newline="", encoding="utf-8") as f:
    writer = csv.DictWriter(f, fieldnames=["name", "url", "price"])
    writer.writeheader()
    writer.writerows(data)

Before You're Done

• Runs without errors
• No hardcoded secrets
• requirements.txt exists
• .env.example documents needed vars
• You'll understand it in 3 months