{
  "page": 1,
  "size": 50,
  "total": 245,
  "total2": 12,
  "items": [
    {
      "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "organization_id": "org-uuid",
      "quantity": 25000.0,
      "unit_id": "eur-unit-uuid",
      "unit": {
        "id": "eur-unit-uuid",
        "name": "EUR",
        "type": "fiat_currency"
      },
      "sector": "IT Services",
      "product_name": "Cloud Computing Services",
      "purchase_type": "spend_based",
      "expense_type": "services",
      "supplier_id": "supplier-uuid",
      "supplier": {
        "business_name": "AWS EMEA SARL",
        "country": "ES"
      },
      "purchase_date": "2024-01-15T00:00:00Z",
      "last_purchase_timestamp": "2024-01-16T10:30:00Z",
      "recycled": null,
      "country": "ES",
      "frequency": "monthly",
      "description": "Monthly AWS cloud infrastructure costs",
      "status": "active",
      "co2e": 2450.75,
      "ef": 0.098,
      "displayed_ggss": true,
      "custom_emission_factor_id": null,
      "file_url": null,
      "file_id": null,
      "file_name": null
    },
    {
      "id": "b2c3d4e5-f6g7-8901-bcde-fg2345678901",
      "organization_id": "org-uuid",
      "quantity": 15000.0,
      "unit_id": "eur-unit-uuid",
      "unit": {
        "id": "eur-unit-uuid",
        "name": "EUR",
        "type": "fiat_currency"
      },
      "sector": "Office Supplies",
      "product_name": "Printer Paper",
      "purchase_type": "spend_based",
      "expense_type": "goods",
      "supplier_id": "supplier-uuid-2",
      "supplier": {
        "business_name": "Office Depot Spain",
        "country": "ES"
      },
      "purchase_date": "2024-01-10T00:00:00Z",
      "last_purchase_timestamp": "2024-01-10T14:22:00Z",
      "recycled": 0.3,
      "country": "ES",
      "frequency": "quarterly",
      "description": "Q1 2024 office paper supplies",
      "status": "active",
      "co2e": 1825.50,
      "ef": 0.122,
      "displayed_ggss": true,
      "custom_emission_factor_id": null,
      "file_url": null,
      "file_id": null,
      "file_name": null
    }
  ]
}

{
  "detail": "Invalid filter format",
  "code": "VALIDATION_ERROR"
}

{
  "detail": "Not authorized",
  "code": "FORBIDDEN"
}

def get_purchases_dashboard():
    """Get purchases dashboard with top emitters"""

    response = requests.get(
        "https://api.dcycle.io/api/v1/purchases",
        headers=headers,
        params={
            "page": 1,
            "size": 100,
            "sort_by": "co2e:desc",
            "filter_by": "status:active"
        }
    )

    purchases = response.json()

    # Calculate totals
    total_emissions = sum(p['co2e'] or 0 for p in purchases['items'])
    total_spend = sum(
        p['quantity'] for p in purchases['items']
        if p['unit']['type'] == 'fiat_currency'
    )

    return {
        'purchases': purchases['items'],
        'total_active': purchases['total'],
        'total_errors': purchases['total2'],
        'total_emissions': total_emissions,
        'total_spend': total_spend
    }

# Usage
dashboard = get_purchases_dashboard()
print(f"Total emissions: {dashboard['total_emissions']:.2f} kg CO2e")
print(f"Total spend: {dashboard['total_spend']:.2f} EUR")

def get_purchases_by_sector(sector_name):
    """Get purchases filtered by sector"""

    response = requests.get(
        "https://api.dcycle.io/api/v1/purchases",
        headers=headers,
        params={
            "filter_by": f"sector:eq{sector_name}",
            "page": 1,
            "size": 100
        }
    )

    purchases = response.json()

    print(f"Purchases in {sector_name}: {purchases['total']}")
    for purchase in purchases['items']:
        print(f"  - {purchase['product_name']}: {purchase['co2e']:.2f} kg CO2e")

    return purchases

# Example: Get all IT Services purchases
it_purchases = get_purchases_by_sector("IT Services")

from datetime import datetime, timedelta

def get_recent_purchases(days=30):
    """Get purchases from the last N days"""

    # Note: Date filtering requires timestamp comparison
    # This example shows pagination through all results and client-side filtering
    all_purchases = []
    page = 1
    cutoff_date = datetime.now() - timedelta(days=days)

    while True:
        response = requests.get(
            "https://api.dcycle.io/api/v1/purchases",
            headers=headers,
            params={"page": page, "size": 100}
        )

        data = response.json()

        # Filter by date client-side
        for purchase in data['items']:
            purchase_date = datetime.fromisoformat(purchase['purchase_date'].replace('Z', '+00:00'))
            if purchase_date >= cutoff_date:
                all_purchases.append(purchase)

        if len(data['items']) < 100:
            break

        page += 1

    print(f"Purchases in last {days} days: {len(all_purchases)}")
    return all_purchases

# Get purchases from last 30 days
recent = get_recent_purchases(30)

def get_error_purchases():
    """Get purchases with errors for review"""

    response = requests.get(
        "https://api.dcycle.io/api/v1/purchases",
        headers=headers,
        params={
            "filter_by": "status:eqerror",
            "page": 1,
            "size": 100
        }
    )

    purchases = response.json()

    print(f"⚠️ Purchases with errors: {len(purchases['items'])}")

    for purchase in purchases['items']:
        print(f"\nPurchase ID: {purchase['id']}")
        print(f"  Product: {purchase['product_name']}")
        print(f"  Sector: {purchase['sector']}")
        print(f"  Date: {purchase['purchase_date']}")
        print(f"  Status: {purchase['status']}")

    return purchases

# Review error purchases
errors = get_error_purchases()

def analyze_emissions_by_sector():
    """Analyze total emissions grouped by sector"""

    # Get all active purchases
    all_purchases = []
    page = 1

    while True:
        response = requests.get(
            "https://api.dcycle.io/api/v1/purchases",
            headers=headers,
            params={
                "page": page,
                "size": 100,
                "filter_by": "status:active"
            }
        )

        data = response.json()
        all_purchases.extend(data['items'])

        if len(all_purchases) >= data['total']:
            break

        page += 1

    # Group by sector
    sectors = {}
    for purchase in all_purchases:
        sector = purchase['sector']
        if sector not in sectors:
            sectors[sector] = {
                'count': 0,
                'total_co2e': 0,
                'total_spend': 0
            }

        sectors[sector]['count'] += 1
        sectors[sector]['total_co2e'] += purchase['co2e'] or 0

        if purchase['unit']['type'] == 'fiat_currency':
            sectors[sector]['total_spend'] += purchase['quantity']

    # Sort by emissions
    sorted_sectors = sorted(
        sectors.items(),
        key=lambda x: x[1]['total_co2e'],
        reverse=True
    )

    print("Emissions by Sector:")
    print("-" * 70)
    for sector, data in sorted_sectors:
        print(f"{sector}:")
        print(f"  Purchases: {data['count']}")
        print(f"  Emissions: {data['total_co2e']:.2f} kg CO2e")
        print(f"  Spend: {data['total_spend']:.2f} EUR")
        print()

    return sorted_sectors

# Analyze emissions
analysis = analyze_emissions_by_sector()

# Good - Paginate through results
def get_all_purchases():
    all_purchases = []
    page = 1

    while True:
        response = requests.get(
            "https://api.dcycle.io/api/v1/purchases",
            headers=headers,
            params={"page": page, "size": 100}
        )

        data = response.json()
        all_purchases.extend(data['items'])

        if len(all_purchases) >= data['total']:
            break

        page += 1

    return all_purchases

# Good - Server-side filtering
response = requests.get(
    "https://api.dcycle.io/api/v1/purchases",
    headers=headers,
    params={"filter_by": "sector:eqIT Services"}
)

# Bad - Client-side filtering
response = requests.get("https://api.dcycle.io/api/v1/purchases", headers=headers)
it_purchases = [p for p in response.json()['items'] if p['sector'] == 'IT Services']

# Check error count
response = requests.get(
    "https://api.dcycle.io/api/v1/purchases",
    headers=headers,
    params={"page": 1, "size": 1}
)

error_count = response.json()['total2']
if error_count > 0:
    print(f"⚠️ {error_count} purchases need attention")

# Get top 20 emission sources
response = requests.get(
    "https://api.dcycle.io/api/v1/purchases",
    headers=headers,
    params={
        "sort_by": "co2e:desc",
        "page": 1,
        "size": 20
    }
)

top_emitters = response.json()['items']