# API Client Patterns

## Base API Client Pattern

Using requests.Session for connection pooling:

```python
# api_client.py
import requests
from typing import Dict, List, Optional
from config import config

class TweedeKamerAPI:
    def __init__(self):
        self.odata_base_url = "https://gegevensmagazijn.tweedekamer.nl/OData/v4/2.0"
        self.session = requests.Session()
        self.session.headers.update({
            "Accept": "application/json",
            "User-Agent": "Dutch-Political-Compass-Tool/1.0",
        })
    
    def get_motions(
        self,
        start_date: datetime = None,
        end_date: datetime = None,
        limit: int = 500,
    ) -> List[Dict]:
        """Get motions with voting results using OData API."""
        if not start_date:
            start_date = datetime.now() - timedelta(days=730)
        
        try:
            voting_records, besluit_meta = self._get_voting_records(
                start_date, end_date, limit
            )
            return self._process_voting_records(voting_records, besluit_meta)
        except Exception as e:
            print(f"Error fetching motions from API: {e}")
            return []
```

## OData Pagination Pattern

Handle server-side pagination with $skip:

```python
def _get_voting_records(
    self, 
    start_date: datetime, 
    end_date: datetime = None, 
    limit: int = 50000
) -> tuple:
    """Fetch with automatic pagination."""
    
    filter_query = (
        f"GewijzigdOp ge {start_date.strftime('%Y-%m-%d')}T00:00:00Z"
        " and StemmingsSoort ne null"
        " and Verwijderd eq false"
    )
    
    page_size = 250  # API caps $top at 250
    base_url = f"{self.odata_base_url}/Besluit"
    base_params = {
        "$filter": filter_query,
        "$top": page_size,
        "$expand": "Stemming",
        "$orderby": "GewijzigdOp desc",
    }
    
    all_records = []
    skip = 0
    
    while len(all_records) < limit:
        params = {**base_params, "$skip": skip}
        response = self.session.get(
            base_url, 
            params=params, 
            timeout=config.API_TIMEOUT
        )
        response.raise_for_status()
        data = response.json()
        
        besluit_page = data.get("value", [])
        if not besluit_page:
            break
        
        # Process page
        for besluit in besluit_page:
            all_records.extend(self._extract_votes(besluit))
        
        skip += page_size
    
    return all_records
```

## Retry with Backoff Pattern

For transient failures:

```python
# ai_provider.py
import time
import random
from requests.exceptions import ConnectionError

def _post_with_retries(
    path: str, 
    json: dict, 
    retries: int = 3
) -> requests.Response:
    """POST with exponential backoff retry."""
    
    backoff = 0.5
    for attempt in range(1, retries + 1):
        try:
            resp = requests.post(url, json=json, headers=headers, timeout=10)
            
            # Handle rate limiting
            if resp.status_code == 429:
                if attempt == retries:
                    raise ProviderError("Rate limited")
                
                retry_after = resp.headers.get("Retry-After")
                if retry_after:
                    time.sleep(int(retry_after))
                else:
                    sleep = backoff * (2 ** (attempt - 1))
                    sleep += random.uniform(0, sleep * 0.1)
                    time.sleep(sleep)
                continue
            
            # Handle server errors
            if 500 <= resp.status_code < 600:
                if attempt == retries:
                    raise ProviderError(f"Server error: {resp.status_code}")
                time.sleep(backoff * (2 ** (attempt - 1)))
                continue
            
            return resp
            
        except ConnectionError as exc:
            if attempt == retries:
                raise ProviderError(f"Connection error: {exc}")
            time.sleep(backoff * (2 ** (attempt - 1)))
    
    raise ProviderError("Failed after retries")
```

## Batch Processing Pattern

Process items in batches to manage API limits:

```python
def get_embeddings_with_retry(
    texts: List[str],
    batch_size: int = 50,
    retries: int = 3,
) -> List[Optional[List[float]]]:
    """Process embeddings in batches with fallback to single items."""
    
    results = [None] * len(texts)
    
    i = 0
    while i < len(texts):
        end = min(len(texts), i + batch_size)
        chunk = texts[i:end]
        
        # Try batch first
        try:
            emb_chunk = get_embeddings_batch(chunk)
            for j, emb in enumerate(emb_chunk):
                results[i + j] = emb
            i = end
            continue
        except Exception:
            pass
        
        # Fallback: single items
        for j, text in enumerate(chunk):
            try:
                results[i + j] = get_embedding(text)
            except Exception:
                results[i + j] = None
        
        i = end
    
    return results
```

## Response Validation Pattern

Validate API responses before processing:

```python
def _process_response(self, response: requests.Response) -> Dict:
    """Validate and parse API response."""
    
    response.raise_for_status()
    data = response.json()
    
    if "value" not in data:
        raise ValueError("Unexpected response format: missing 'value' key")
    
    return data

def _validate_besluit(self, besluit: Dict) -> bool:
    """Check required fields exist."""
    required = ["Id", "GewijzigdOp"]
    return all(field in besluit for field in required)
```

## Error Handling Patterns

Always provide safe fallbacks:

```python
def safe_api_call(self, endpoint: str, params: Dict = None) -> List[Dict]:
    """Call API with error handling and fallback."""
    try:
        response = self.session.get(
            endpoint, 
            params=params, 
            timeout=config.API_TIMEOUT
        )
        response.raise_for_status()
        data = response.json()
        return data.get("value", [])
    except requests.Timeout:
        _logger.warning(f"API timeout for {endpoint}")
        return []
    except requests.HTTPError as e:
        _logger.error(f"HTTP error: {e}")
        return []
    except Exception as e:
        _logger.error(f"API call failed: {e}")
        return []
```

## Session Management

Reuse session for connection pooling:

```python
class TweedeKamerAPI:
    def __init__(self):
        self.session = requests.Session()
        self.session.headers.update({
            "Accept": "application/json",
            "User-Agent": "Dutch-Political-Compass-Tool/1.0",
        })
    
    def close(self):
        """Clean up session when done."""
        self.session.close()
    
    def __enter__(self):
        return self
    
    def __exit__(self, *args):
        self.close()

# Usage
with TweedeKamerAPI() as api:
    motions = api.get_motions(start_date)
```