Scenario

A JSON file contains user activity logs with various events. You need to analyze the logs and generate a report showing how many events each user performed.

Task

Write a Python script at /home/interview/count_events.py that reads /home/interview/activity_logs.json, counts the number of events per user, and saves the results as a JSON file to /home/interview/user_event_counts.json.

Example

Expected output format in /home/interview/user_event_counts.json:

{
  "user_123": 5,
  "user_456": 12,
  "user_789": 3
}

Step 1: Examine the log file structure

head -n 30 /home/interview/activity_logs.json

Review the JSON structure to understand the log entry format and identify the user identifier field.

Step 2: Create the Python script

nano /home/interview/count_events.py

Write a script that reads the logs, counts events per user, and saves the results:

import json

# Read activity logs
with open('/home/interview/activity_logs.json', 'r') as f:
    logs = json.load(f)

# Count events per user
user_event_counts = {}

for log in logs:
    user_id = log['user_id']
    user_event_counts[user_id] = user_event_counts.get(user_id, 0) + 1

# Save results
with open('/home/interview/user_event_counts.json', 'w') as f:
    json.dump(user_event_counts, f, indent=2)

print(f"Processed {len(logs)} log entries")
print(f"Total users: {len(user_event_counts)}")

Step 3: Run the script

python3 /home/interview/count_events.py

Step 4: Verify the output

cat /home/interview/user_event_counts.json

Should show a JSON object with user IDs as keys and their event counts as values.