{
  "items": [
    {
      "id": "660e8400-e29b-41d4-a716-446655440000",
      "vehicle_id": "550e8400-e29b-41d4-a716-446655440000",
      "status": "success",
      "data": {
        "fuel_consumed": 45.5,
        "distance_km": 450,
        "fuel_efficiency": 10.1,
        "period": "2024-11-01 to 2024-11-30"
      },
      "total_energy_kwh": 1500.00,
      "created_at": "2024-11-01T08:00:00Z",
      "updated_at": "2024-11-01T08:00:00Z"
    },
    {
      "id": "660e8400-e29b-41d4-a716-446655440001",
      "vehicle_id": "550e8400-e29b-41d4-a716-446655440000",
      "status": "success",
      "data": {
        "fuel_consumed": 52.3,
        "distance_km": 520,
        "fuel_efficiency": 9.9,
        "period": "2024-10-01 to 2024-10-31"
      },
      "created_at": "2024-10-01T08:00:00Z",
      "updated_at": "2024-10-01T08:00:00Z"
    }
  ],
  "total": 12,
  "page": 1,
  "size": 50,
  "filter_hash": "a1b2c3d4e5f67890"
}

{
  "detail": "Invalid API key",
  "code": "INVALID_API_KEY"
}

{
  "code": "VEHICLE_NOT_FOUND",
  "detail": "Vehicle with id=UUID('...') not found"
}

{
  "detail": [
    {
      "loc": ["query", "status"],
      "msg": "value is not a valid enumeration member; permitted: 'active', 'success', 'loading', 'error'",
      "type": "type_error.enum"
    }
  ]
}

def get_successful_consumptions(vehicle_id):
    """Get all successfully processed consumption records"""
    response = requests.get(
        f"https://api.dcycle.io/v1/vehicles/{vehicle_id}/consumptions",
        headers=headers,
        params={"status": ["success"], "size": 100}
    )

    return response.json()["items"]

# Get consumptions
consumptions = get_successful_consumptions(
    "550e8400-e29b-41d4-a716-446655440000"
)

total_fuel = sum(c["data"]["fuel_consumed"] for c in consumptions)
total_distance = sum(c["data"]["distance_km"] for c in consumptions)

print(f"Total fuel: {total_fuel} liters")
print(f"Total distance: {total_distance} km")
print(f"Average efficiency: {total_distance / total_fuel:.2f} km/l")

def check_consumption_status(vehicle_id):
    """Check status of all consumption records"""
    response = requests.get(
        f"https://api.dcycle.io/v1/vehicles/{vehicle_id}/consumptions",
        headers=headers,
        params={"size": 100}
    )

    consumptions = response.json()["items"]
    status_summary = {
        "active": 0,
        "success": 0,
        "loading": 0,
        "error": 0
    }

    for consumption in consumptions:
        status = consumption["status"]
        status_summary[status] += 1

    return status_summary

# Check status
summary = check_consumption_status(
    "550e8400-e29b-41d4-a716-446655440000"
)

print("Consumption Status Summary:")
for status, count in summary.items():
    print(f"  {status}: {count}")

def export_consumption_data(vehicle_id):
    """Export all consumption data to CSV"""
    response = requests.get(
        f"https://api.dcycle.io/v1/vehicles/{vehicle_id}/consumptions",
        headers=headers,
        params={"status": ["success"], "size": 100}
    )

    consumptions = response.json()["items"]

    import csv
    with open(f"consumption_{vehicle_id}.csv", "w", newline="") as f:
        writer = csv.DictWriter(
            f,
            fieldnames=["date", "fuel_consumed", "distance_km", "efficiency"]
        )
        writer.writeheader()

        for c in consumptions:
            data = c["data"]
            writer.writerow({
                "date": c["created_at"],
                "fuel_consumed": data.get("fuel_consumed"),
                "distance_km": data.get("distance_km"),
                "efficiency": data.get("fuel_efficiency")
            })

    print(f"Exported {len(consumptions)} records")

# Export data
export_consumption_data("550e8400-e29b-41d4-a716-446655440000")

def analyze_efficiency_trends(vehicle_id):
    """Analyze fuel efficiency trends for a vehicle"""
    response = requests.get(
        f"https://api.dcycle.io/v1/vehicles/{vehicle_id}/consumptions",
        headers=headers,
        params={"status": ["success"], "size": 100}
    )

    consumptions = response.json()["items"]
    consumptions.sort(key=lambda x: x["created_at"])

    efficiencies = [
        {
            "date": c["created_at"],
            "efficiency": c["data"].get("fuel_efficiency")
        }
        for c in consumptions
        if c["data"].get("fuel_efficiency")
    ]

    if efficiencies:
        avg_efficiency = sum(e["efficiency"] for e in efficiencies) / len(efficiencies)
        min_efficiency = min(e["efficiency"] for e in efficiencies)
        max_efficiency = max(e["efficiency"] for e in efficiencies)

        print(f"Average efficiency: {avg_efficiency:.2f} km/l")
        print(f"Min efficiency: {min_efficiency:.2f} km/l")
        print(f"Max efficiency: {max_efficiency:.2f} km/l")

    return efficiencies

# Analyze trends
trends = analyze_efficiency_trends("550e8400-e29b-41d4-a716-446655440000")