Jupyter, ChatGPT, Copilot (Part 3): Real-World Code Examples

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import requests
import pandas as pd

# 1. Fire the request
response = requests.get("https://api.example.com/v1/complex-endpoint", 
                        headers={"Authorization": "Bearer YOUR_TOKEN"})
data = response.json()

# 2. Instead of print(data), use Jupyter's ability to explore
# Let's see the top-level keys
print(f"Keys: {data.keys()}")

# 3. Flatten nested structures to understand the schema
df = pd.json_normalize(data['items'])
df.head() # Shows a beautiful interactive table

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import json
import matplotlib.pyplot as plt

# Load a sample of your production logs
with open('logs_sample.json') as f:
    logs = [json.loads(line) for line in f]

# Extract response times
latencies = [log['duration_ms'] for log in logs if 'duration_ms' in log]

# Visualize the distribution
plt.hist(latencies, bins=50, color='skyblue', edgecolor='black')
plt.title('Distribution of Response Times')
plt.xlabel('ms')
plt.ylabel('Frequency')
plt.axvline(x=500, color='red', linestyle='--', label='SLA Threshold')
plt.legend()
plt.show()

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def calculate_score(likes, views, age_hours):
    # A simple decay-based ranking algorithm
    return (likes * 0.8 + views * 0.2) / (age_hours + 2)**1.5

# Test with different scenarios
scenarios = [
    {"likes": 100, "views": 1000, "age": 1},   # New & Popular
    {"likes": 500, "views": 5000, "age": 24},  # Old & Very Popular
    {"likes": 10, "views": 50, "age": 0.5}     # Brand New
]

for s in scenarios:
    score = calculate_score(s['likes'], s['views'], s['age'])
    print(f"Scenario: {s}, Score: {score:.4f}")

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# STEP 1: Check current state
count = db.execute("SELECT COUNT(*) FROM users WHERE status = 'pending'").fetchone()[0]
print(f"Found {count} pending users.")

# STEP 2: Run the migration (only if count is reasonable)
if count < 1000:
    db.execute("UPDATE users SET status = 'active' WHERE status = 'pending'")
    print("Migration complete.")
else:
    print("ERROR: Too many users to migrate safely in one go!")

# STEP 3: Verify
new_count = db.execute("SELECT COUNT(*) FROM users WHERE status = 'pending'").fetchone()[0]
print(f"Remaining pending users: {new_count}")