GET /api/v1/history¶

import requests

response = requests.get(
    "https://api.reputeapi.com/api/v1/history",
    params={"domain": "example.com"},
    headers={"X-API-Key": "your-api-key"}
)

result = response.json()

print(f"Total snapshots: {result['total_snapshots']}")
print(f"\nRecent scores:")

for snapshot in result['snapshots'][:10]:
    print(f"  {snapshot['timestamp']}: {snapshot['score']}/100")

import requests
from datetime import datetime

def analyze_trend(domain: str, days: int = 30):
    """Analyze security score trends"""

    response = requests.get(
        "https://api.reputeapi.com/api/v1/history",
        params={"domain": domain, "days": days},
        headers={"X-API-Key": "your-api-key"}
    )

    result = response.json()
    snapshots = result['snapshots']

    if len(snapshots) < 2:
        print("Not enough data for trend analysis")
        return

    # Calculate trend
    first_score = snapshots[-1]['score']
    last_score = snapshots[0]['score']
    change = last_score - first_score

    print(f"Domain: {domain}")
    print(f"Period: Last {days} days")
    print(f"First Score: {first_score}/100")
    print(f"Latest Score: {last_score}/100")
    print(f"Change: {change:+d} points")

    if change > 0:
        print("✓ Score improved!")
    elif change < 0:
        print("⚠ Score declined!")
    else:
        print("→ Score unchanged")

    # Show issue trend
    first_critical = snapshots[-1]['critical_issues']
    last_critical = snapshots[0]['critical_issues']

    print(f"\nCritical Issues: {first_critical} → {last_critical}")

analyze_trend("example.com", days=30)

import requests
import matplotlib.pyplot as plt
from datetime import datetime

def plot_score_history(domain: str):
    """Plot security score over time"""

    response = requests.get(
        "https://api.reputeapi.com/api/v1/history",
        params={"domain": domain, "limit": 90},
        headers={"X-API-Key": "your-api-key"}
    )

    result = response.json()
    snapshots = result['snapshots']

    # Extract data
    dates = [datetime.fromisoformat(s['timestamp'].replace('Z', '+00:00'))
             for s in snapshots]
    scores = [s['score'] for s in snapshots]

    # Plot
    plt.figure(figsize=(12, 6))
    plt.plot(dates, scores, marker='o', linewidth=2)
    plt.axhline(y=90, color='g', linestyle='--', label='Excellent (90+)')
    plt.axhline(y=75, color='y', linestyle='--', label='Good (75+)')
    plt.axhline(y=50, color='r', linestyle='--', label='Fair (50+)')
    plt.xlabel('Date')
    plt.ylabel('Security Score')
    plt.title(f'Mailflow Security Score History - {domain}')
    plt.legend()
    plt.grid(True, alpha=0.3)
    plt.tight_layout()
    plt.savefig(f'{domain}_history.png')
    plt.show()

plot_score_history("example.com")

def generate_compliance_report(domain: str, days: int = 90):
    """Generate quarterly compliance report"""

    response = requests.get(
        "https://api.reputeapi.com/api/v1/history",
        params={"domain": domain, "days": days},
        headers={"X-API-Key": "your-api-key"}
    )

    result = response.json()
    snapshots = result['snapshots']

    # Calculate metrics
    avg_score = sum(s['score'] for s in snapshots) / len(snapshots)
    min_score = min(s['score'] for s in snapshots)
    max_score = max(s['score'] for s in snapshots)

    above_threshold = sum(1 for s in snapshots if s['score'] >= 75)
    compliance_rate = (above_threshold / len(snapshots)) * 100

    print(f"""
    Quarterly Security Report - {domain}
    Period: Last {days} days

    Score Metrics:
      Average: {avg_score:.1f}/100
      Minimum: {min_score}/100
      Maximum: {max_score}/100

    Compliance:
      Target: 75/100 or higher
      Compliance Rate: {compliance_rate:.1f}%
      ({above_threshold}/{len(snapshots)} checks above threshold)
    """)

def detect_regressions(domain: str):
    """Alert if score has dropped recently"""

    response = requests.get(
        "https://api.reputeapi.com/api/v1/history",
        params={"domain": domain, "limit": 10},
        headers={"X-API-Key": "your-api-key"}
    )

    snapshots = response.json()['snapshots']

    if len(snapshots) < 2:
        return

    latest = snapshots[0]
    previous = snapshots[1]

    score_change = latest['score'] - previous['score']

    if score_change < -5:  # Score dropped by 5+ points
        print(f"⚠ REGRESSION DETECTED for {domain}!")
        print(f"Score dropped from {previous['score']} to {latest['score']}")
        print(f"Critical issues: {previous['critical_issues']} → {latest['critical_issues']}")
        # Send alert via email/Slack/etc.

def track_improvement_progress(domain: str, days: int = 30):
    """Track security improvements over time"""

    response = requests.get(
        "https://api.reputeapi.com/api/v1/history",
        params={"domain": domain, "days": days},
        headers={"X-API-Key": "your-api-key"}
    )

    snapshots = response.json()['snapshots']

    # Reverse to chronological order
    snapshots.reverse()

    milestones = {
        50: "Fair security",
        75: "Good security",
        90: "Excellent security"
    }

    for milestone, description in milestones.items():
        milestone_reached = next(
            (s for s in snapshots if s['score'] >= milestone),
            None
        )

        if milestone_reached:
            print(f"✓ Reached {milestone}/100 ({description}) on {milestone_reached['timestamp']}")
        else:
            print(f"○ Not yet reached {milestone}/100 ({description})")