Python API to CSV Data Pipeline Project

Students often learn Python syntax but do not know how to connect it to real data. A small API-to-CSV pipeline is a good bridge from beginner Python to data science and automation.

Project idea: activity summary

Imagine a fictional school activity API returns public-style event counts. The program should request data, validate fields, and write a CSV summary.

import csv
import requests

url = "https://example.com/api/events"
response = requests.get(url, timeout=10)
records = response.json()

clean_rows = []
for item in records:
    if "name" in item and "participants" in item:
        clean_rows.append({
            "name": item["name"],
            "participants": int(item["participants"])
        })

with open("event_summary.csv", "w", newline="") as file:
    writer = csv.DictWriter(file, fieldnames=["name", "participants"])
    writer.writeheader()
    writer.writerows(clean_rows)

What students learn

• HTTP requests and JSON parsing.
• Defensive checks before trusting data fields.
• Type conversion from API values.
• Writing structured CSV output.
• Separating collection, cleaning, and reporting.

Extension

Add error handling for failed requests, missing fields, and unexpected values. Then create a chart of the top five events by participation.