tractatus/docs/api/examples-python.md

Python API Examples

Complete examples for integrating with the Tractatus Framework API using Python with the requests library.

Table of Contents

• Installation
• Authentication
• Documents
• Governance Services
• Audit Logs
• Error Handling

---

Installation

pip install requests

---

Authentication

Login and Store Token

import requests
from typing import Dict, Optional

API_BASE = "https://agenticgovernance.digital/api"
# For local development: API_BASE = "http://localhost:9000/api"

def login(email: str, password: str) -> Dict:
    """
    Authenticate and receive JWT token.

    Args:
        email: User email address
        password: User password

    Returns:
        dict: Contains 'token' and 'user' keys

    Raises:
        requests.HTTPError: If authentication fails
    """
    try:
        response = requests.post(
            f"{API_BASE}/auth/login",
            json={
                "email": email,
                "password": password
            }
        )
        response.raise_for_status()

        data = response.json()
        token = data['token']
        user = data['user']

        print(f"Login successful: {user['email']}")
        return {'token': token, 'user': user}

    except requests.HTTPError as e:
        if e.response.status_code == 429:
            print("Too many login attempts. Please wait 15 minutes.")
        elif e.response.status_code == 401:
            print("Invalid credentials")
        else:
            print(f"Login failed: {e}")
        raise


# Usage
result = login('admin@tractatus.local', 'your_password')
TOKEN = result['token']

Authenticated Session Class

import requests
from typing import Dict, Any, Optional

class TractatusAPI:
    """
    Client for interacting with the Tractatus Framework API.
    """

    def __init__(self, base_url: str = "https://agenticgovernance.digital/api"):
        self.base_url = base_url
        self.token: Optional[str] = None
        self.session = requests.Session()
        self.session.headers.update({
            'Content-Type': 'application/json'
        })

    def login(self, email: str, password: str) -> Dict:
        """Login and store authentication token."""
        response = self.session.post(
            f"{self.base_url}/auth/login",
            json={"email": email, "password": password}
        )
        response.raise_for_status()

        data = response.json()
        self.token = data['token']

        # Update session headers with auth token
        self.session.headers.update({
            'Authorization': f'Bearer {self.token}'
        })

        return data

    def get(self, endpoint: str, params: Optional[Dict] = None) -> Dict:
        """Make authenticated GET request."""
        if not self.token:
            raise ValueError("Not authenticated. Call login() first.")

        response = self.session.get(
            f"{self.base_url}{endpoint}",
            params=params
        )
        response.raise_for_status()
        return response.json()

    def post(self, endpoint: str, data: Dict) -> Dict:
        """Make authenticated POST request."""
        if not self.token:
            raise ValueError("Not authenticated. Call login() first.")

        response = self.session.post(
            f"{self.base_url}{endpoint}",
            json=data
        )
        response.raise_for_status()
        return response.json()


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'your_password')

# Now make authenticated requests
status = client.get('/governance/status')
print(status)

---

Documents

List All Documents

def list_documents(
    page: int = 1,
    limit: int = 50,
    quadrant: Optional[str] = None
) -> Dict:
    """
    Retrieve list of documents with optional filtering.

    Args:
        page: Page number (default: 1)
        limit: Results per page (default: 50)
        quadrant: Filter by quadrant (STRATEGIC, OPERATIONAL, etc.)

    Returns:
        dict: Contains 'documents' array and 'pagination' info
    """
    params = {
        'page': page,
        'limit': limit
    }

    if quadrant:
        params['quadrant'] = quadrant

    response = requests.get(
        f"{API_BASE}/documents",
        params=params
    )
    response.raise_for_status()

    data = response.json()
    return data


# Usage
result = list_documents(page=1, limit=10, quadrant='STRATEGIC')
print(f"Found {result['pagination']['total']} documents")

for doc in result['documents']:
    print(f"- {doc['title']} ({doc['quadrant']})")

Get Single Document

def get_document(identifier: str) -> Dict:
    """
    Retrieve a single document by ID or slug.

    Args:
        identifier: Document MongoDB ObjectId or URL slug

    Returns:
        dict: Document data

    Raises:
        requests.HTTPError: If document not found (404)
    """
    response = requests.get(f"{API_BASE}/documents/{identifier}")

    if response.status_code == 404:
        raise ValueError(f"Document not found: {identifier}")

    response.raise_for_status()
    data = response.json()
    return data['document']


# Usage (by slug)
doc = get_document('introduction-to-tractatus')
print(f"Title: {doc['title']}")
print(f"Quadrant: {doc['quadrant']}")

# Usage (by ID)
doc = get_document('672f821b6e820c0c7a0e0d55')
print(doc)

Search Documents

def search_documents(query: str) -> Dict:
    """
    Full-text search across all documents.

    Args:
        query: Search query string

    Returns:
        dict: Contains 'results' array and 'count'
    """
    response = requests.get(
        f"{API_BASE}/documents/search",
        params={'q': query}
    )
    response.raise_for_status()

    data = response.json()
    return data


# Usage
results = search_documents('boundary enforcement')
print(f"Found {results['count']} results")

for result in results['results']:
    print(f"- {result['title']} (score: {result['score']:.2f})")
    if 'excerpt' in result:
        print(f"  Excerpt: {result['excerpt'][:100]}...")

Create Document (Admin Only)

def create_document(
    client: TractatusAPI,
    title: str,
    slug: str,
    quadrant: str,
    content: str,
    status: str = 'published'
) -> Dict:
    """
    Create a new framework document (requires admin authentication).

    Args:
        client: Authenticated TractatusAPI client
        title: Document title
        slug: URL slug (lowercase, hyphens only)
        quadrant: One of: STRATEGIC, OPERATIONAL, TACTICAL, SYSTEM, STOCHASTIC
        content: Document content in Markdown format
        status: One of: draft, published, archived (default: published)

    Returns:
        dict: Created document

    Raises:
        requests.HTTPError: If creation fails (403 = forbidden, 409 = slug exists)
    """
    document_data = {
        'title': title,
        'slug': slug,
        'quadrant': quadrant,
        'content_markdown': content,
        'status': status
    }

    try:
        response = client.post('/documents', document_data)
        doc = response['document']
        print(f"Document created: {doc['_id']}")
        return doc

    except requests.HTTPError as e:
        if e.response.status_code == 403:
            print("Error: Admin role required")
        elif e.response.status_code == 409:
            print("Error: Slug already exists")
        raise


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'password')

new_doc = create_document(
    client=client,
    title='Advanced Boundary Enforcement Patterns',
    slug='advanced-boundary-enforcement',
    quadrant='OPERATIONAL',
    content='# Advanced Patterns\n\nThis document explores...',
    status='published'
)

---

Governance Services

InstructionPersistenceClassifier

def classify_instruction(
    client: TractatusAPI,
    text: str,
    context: Optional[Dict] = None
) -> Dict:
    """
    Classify an instruction by quadrant and persistence level.

    Args:
        client: Authenticated TractatusAPI client (admin)
        text: Instruction text to classify
        context: Optional context (source, session_id, etc.)

    Returns:
        dict: Classification with quadrant, persistence, temporal_scope,
              verification_required, reasoning, and confidence
    """
    if context is None:
        context = {}

    context.setdefault('source', 'user')
    context.setdefault('session_id', 'default')

    response = client.post('/governance/classify', {
        'text': text,
        'context': context
    })

    return response['classification']


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'password')

classification = classify_instruction(
    client,
    'Always use MongoDB on port 27027',
    {'source': 'user', 'session_id': 'sess_123'}
)

print(f"Quadrant: {classification['quadrant']}")
print(f"Persistence: {classification['persistence']}")
print(f"Temporal Scope: {classification['temporal_scope']}")
print(f"Confidence: {classification['confidence']:.2%}")
print(f"Reasoning: {classification['reasoning']}")

CrossReferenceValidator

def validate_action(
    client: TractatusAPI,
    action: Dict,
    context: Optional[Dict] = None
) -> Dict:
    """
    Validate a proposed action against instruction history.

    Detects conflicts and training pattern overrides (27027 failure mode).

    Args:
        client: Authenticated TractatusAPI client (admin)
        action: Action to validate (type, target, parameters, etc.)
        context: Optional context (messages, session_id, etc.)

    Returns:
        dict: Validation result with status, conflicts, and recommendation
    """
    if context is None:
        context = {}

    context.setdefault('messages', [])
    context.setdefault('session_id', 'default')

    response = client.post('/governance/validate', {
        'action': action,
        'context': context
    })

    return response['validation']


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'password')

action = {
    'type': 'database_config',
    'target': 'MongoDB',
    'parameters': {'port': 27017}
}

validation = validate_action(client, action)

if validation['status'] == 'REJECTED':
    print("❌ Action rejected")
    print(f"Reason: {validation['reason']}")

    for conflict in validation.get('conflicts', []):
        print(f"  Conflicts with: {conflict['text']} ({conflict['instruction_id']})")

    print(f"Recommendation: {validation['recommendation']}")

elif validation['status'] == 'APPROVED':
    print("✅ Action approved")

elif validation['status'] == 'WARNING':
    print("⚠️  Action has warnings")

BoundaryEnforcer

def enforce_boundary(
    client: TractatusAPI,
    action: Dict,
    context: Optional[Dict] = None
) -> Dict:
    """
    Check if an action crosses into values territory requiring human approval.

    Boundaries: privacy, ethics, sovereignty, strategic

    Args:
        client: Authenticated TractatusAPI client (admin)
        action: Action to check (type, description, impact, etc.)
        context: Optional context

    Returns:
        dict: Enforcement with decision (ALLOW/BLOCK/ESCALATE), boundary,
              reasoning, alternatives, and requiresHuman flag
    """
    if context is None:
        context = {}

    response = client.post('/governance/enforce', {
        'action': action,
        'context': context
    })

    return response['enforcement']


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'password')

action = {
    'type': 'policy_change',
    'description': 'Update privacy policy to enable more tracking',
    'impact': 'user_privacy'
}

enforcement = enforce_boundary(client, action)

if enforcement['decision'] == 'BLOCK':
    print("🚫 Action blocked - crosses values boundary")
    print(f"Boundary: {enforcement['boundary_crossed']}")
    print(f"Reason: {enforcement['reason']}")

    print("\nAlternatives:")
    for i, alt in enumerate(enforcement['alternatives'], 1):
        print(f"{i}. {alt}")

elif enforcement['decision'] == 'ALLOW':
    print("✅ Action allowed")

elif enforcement['decision'] == 'ESCALATE':
    print("⚠️  Action requires escalation")

ContextPressureMonitor

def analyze_pressure(
    client: TractatusAPI,
    context: Dict
) -> Dict:
    """
    Analyze session context pressure across multiple factors.

    Args:
        client: Authenticated TractatusAPI client (admin)
        context: Session context with tokenUsage, messageCount, errorCount, etc.

    Returns:
        dict: Pressure analysis with level (NORMAL/ELEVATED/HIGH/CRITICAL/DANGEROUS),
              score, factors, recommendation, and triggerHandoff flag
    """
    response = client.post('/governance/pressure', {
        'context': context
    })

    return response['pressure']


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'password')

context = {
    'tokenUsage': 120000,
    'tokenBudget': 200000,
    'messageCount': 45,
    'errorCount': 3,
    'complexOperations': 8,
    'sessionDuration': 3600
}

pressure = analyze_pressure(client, context)

print(f"Pressure Level: {pressure['level']}")
print(f"Score: {pressure['score']}%")

print("\nFactors:")
for factor, data in pressure['factors'].items():
    print(f"  {factor}: {data['value']} ({data['status']})")

print(f"\nRecommendation: {pressure['recommendation']}")

if pressure.get('triggerHandoff'):
    print("⚠️ Session handoff recommended")

if pressure.get('next_checkpoint'):
    print(f"Next checkpoint at: {pressure['next_checkpoint']} tokens")

MetacognitiveVerifier

def verify_action(
    client: TractatusAPI,
    action: Dict,
    reasoning: Dict,
    context: Optional[Dict] = None
) -> Dict:
    """
    Perform metacognitive verification on proposed action.

    Detects scope creep, misalignment, and provides confidence scoring.

    Args:
        client: Authenticated TractatusAPI client (admin)
        action: Action to verify (type, scope, complexity, etc.)
        reasoning: Reasoning for the action (intent, approach, risks, etc.)
        context: Optional context (requested, original_scope, etc.)

    Returns:
        dict: Verification with decision (APPROVED/REQUIRE_REVIEW/REJECTED),
              confidence, concerns, criteria scores, alternatives, and scopeCreep flag
    """
    if context is None:
        context = {}

    response = client.post('/governance/verify', {
        'action': action,
        'reasoning': reasoning,
        'context': context
    })

    return response['verification']


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'password')

action = {
    'type': 'refactor',
    'scope': 'Refactor 47 files across 5 system areas',
    'complexity': 'high'
}

reasoning = {
    'intent': 'Improve code organization',
    'approach': 'Extract shared utilities, consolidate duplicates',
    'risks': 'Potential breaking changes'
}

context = {
    'requested': 'Refactor authentication module',
    'original_scope': 'single module'
}

verification = verify_action(client, action, reasoning, context)

print(f"Decision: {verification['decision']}")
print(f"Confidence: {verification['confidence']:.2%}")

if verification['concerns']:
    print("\n⚠️  Concerns:")
    for concern in verification['concerns']:
        print(f"  [{concern['severity']}] {concern['type']}: {concern['detail']}")

if verification.get('scopeCreep'):
    print("\n🔴 Scope creep detected")

print("\nCriteria Scores:")
for criterion, score in verification['criteria'].items():
    print(f"  {criterion}: {score * 100:.0f}%")

if verification.get('alternatives'):
    print("\nAlternatives:")
    for i, alt in enumerate(verification['alternatives'], 1):
        print(f"{i}. {alt}")

---

Audit Logs

Get Audit Logs with Filtering

from datetime import datetime, timedelta
from typing import List, Optional

def get_audit_logs(
    client: TractatusAPI,
    page: int = 1,
    limit: int = 50,
    action: Optional[str] = None,
    user_id: Optional[str] = None,
    start_date: Optional[datetime] = None,
    end_date: Optional[datetime] = None
) -> Dict:
    """
    Retrieve audit logs with filtering and pagination.

    Args:
        client: Authenticated TractatusAPI client (admin)
        page: Page number (default: 1)
        limit: Results per page (default: 50, max: 100)
        action: Filter by action type
        user_id: Filter by user ID
        start_date: Filter by start date
        end_date: Filter by end date

    Returns:
        dict: Contains 'logs' array, 'total', and pagination info
    """
    params = {
        'page': page,
        'limit': limit
    }

    if action:
        params['action'] = action
    if user_id:
        params['userId'] = user_id
    if start_date:
        params['startDate'] = start_date.isoformat()
    if end_date:
        params['endDate'] = end_date.isoformat()

    response = client.get('/audit/audit-logs', params=params)
    return response


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'password')

# Get logs from the last 7 days
start_date = datetime.now() - timedelta(days=7)
logs_data = get_audit_logs(
    client,
    page=1,
    limit=20,
    action='validate_action',
    start_date=start_date
)

print(f"Total logs: {logs_data['total']}")

for log in logs_data['logs']:
    timestamp = log['timestamp']
    service = log['service']
    action = log['action']
    status = log['status']

    print(f"[{timestamp}] {service}: {action} - {status}")

    if log.get('details'):
        import json
        print(f"  Details: {json.dumps(log['details'], indent=2)}")

Get Audit Analytics

from datetime import datetime
from typing import Optional

def get_audit_analytics(
    client: TractatusAPI,
    start_date: Optional[datetime] = None,
    end_date: Optional[datetime] = None
) -> Dict:
    """
    Get aggregated analytics on audit activity.

    Args:
        client: Authenticated TractatusAPI client (admin)
        start_date: Start date for analytics period
        end_date: End date for analytics period

    Returns:
        dict: Analytics with total_events, by_service, by_status,
              rejection_rate, and period information
    """
    params = {}

    if start_date:
        params['startDate'] = start_date.isoformat()
    if end_date:
        params['endDate'] = end_date.isoformat()

    response = client.get('/audit/audit-analytics', params=params)
    return response['analytics']


# Usage
client = TractatusAPI()
client.login('admin@tractatus.local', 'password')

# Get analytics for October 2025
analytics = get_audit_analytics(
    client,
    start_date=datetime(2025, 10, 1),
    end_date=datetime(2025, 10, 31)
)

print(f"Total Events: {analytics['total_events']}")

print("\nBreakdown by Service:")
for service, count in analytics['by_service'].items():
    print(f"  {service}: {count}")

print("\nBreakdown by Status:")
for status, count in analytics['by_status'].items():
    print(f"  {status}: {count}")

print(f"\nRejection Rate: {analytics['rejection_rate']}%")

period = analytics['period']
print(f"\nPeriod: {period['start']} to {period['end']} ({period['days']} days)")

---

Error Handling

Comprehensive Error Handler

import requests
from typing import Callable, Any

def handle_api_errors(func: Callable) -> Callable:
    """
    Decorator for handling API errors consistently.
    """
    def wrapper(*args, **kwargs):
        try:
            return func(*args, **kwargs)

        except requests.HTTPError as e:
            status = e.response.status_code
            data = e.response.json() if e.response.text else {}

            error_handlers = {
                400: lambda: print(f"Bad Request: {data.get('message', 'Invalid input')}"),
                401: lambda: print("Unauthorized: Please login"),
                403: lambda: print(f"Forbidden: {data.get('message', 'Insufficient permissions')}"),
                404: lambda: print(f"Not Found: {data.get('message', 'Resource not found')}"),
                409: lambda: print(f"Conflict: {data.get('message', 'Resource already exists')}"),
                429: lambda: print(f"Rate Limit Exceeded: {data.get('message')}"),
                500: lambda: print(f"Internal Server Error: {data.get('errorId', 'Unknown')}")
            }

            handler = error_handlers.get(status, lambda: print(f"API Error {status}: {data.get('message')}"))
            handler()

            raise

        except requests.ConnectionError:
            print("Network Error: Unable to connect to API")
            print("Check your internet connection and API base URL")
            raise

        except requests.Timeout:
            print("Request Timeout: API did not respond in time")
            raise

        except Exception as e:
            print(f"Unexpected Error: {type(e).__name__}: {e}")
            raise

    return wrapper


# Usage
@handle_api_errors
def get_document_safe(identifier: str) -> Dict:
    return get_document(identifier)


doc = get_document_safe('some-slug')

Retry Logic with Exponential Backoff

import time
import requests
from typing import Callable, Any

def retry_with_backoff(
    func: Callable,
    max_retries: int = 3,
    base_delay: float = 1.0
) -> Any:
    """
    Retry function with exponential backoff.

    Args:
        func: Function to retry
        max_retries: Maximum number of retry attempts
        base_delay: Base delay in seconds (doubles each retry)

    Returns:
        Result of successful function call

    Raises:
        Exception: If all retries fail
    """
    for attempt in range(1, max_retries + 1):
        try:
            return func()

        except requests.HTTPError as e:
            # Don't retry on client errors (4xx except 429)
            if 400 <= e.response.status_code < 500 and e.response.status_code != 429:
                raise

            if attempt == max_retries:
                raise

            delay = base_delay * (2 ** (attempt - 1))
            print(f"Attempt {attempt} failed. Retrying in {delay}s...")
            time.sleep(delay)

        except (requests.ConnectionError, requests.Timeout) as e:
            if attempt == max_retries:
                raise

            delay = base_delay * (2 ** (attempt - 1))
            print(f"Network error. Retrying in {delay}s...")
            time.sleep(delay)


# Usage
def fetch_document():
    return get_document('some-slug')

doc = retry_with_backoff(fetch_document, max_retries=3, base_delay=1.0)

---

Complete Example: Full Integration

import requests
from typing import Dict, Optional, Any
from datetime import datetime

class TractatusClient:
    """
    Complete client for Tractatus Framework API.
    """

    def __init__(self, base_url: str = "https://agenticgovernance.digital/api"):
        self.base_url = base_url
        self.token: Optional[str] = None
        self.session = requests.Session()
        self.session.headers.update({'Content-Type': 'application/json'})

    def login(self, email: str, password: str) -> Dict:
        """Authenticate and store token."""
        response = self.session.post(
            f"{self.base_url}/auth/login",
            json={"email": email, "password": password}
        )
        response.raise_for_status()

        data = response.json()
        self.token = data['token']
        self.session.headers.update({'Authorization': f'Bearer {self.token}'})

        print(f"✅ Logged in as: {data['user']['email']}")
        return data

    def _request(self, method: str, endpoint: str, **kwargs) -> Dict:
        """Make authenticated request."""
        if not self.token:
            raise ValueError("Not authenticated. Call login() first.")

        response = self.session.request(
            method,
            f"{self.base_url}{endpoint}",
            **kwargs
        )
        response.raise_for_status()
        return response.json()

    def get_documents(self, **params) -> Dict:
        """List documents."""
        return self._request('GET', '/documents', params=params)

    def get_document(self, identifier: str) -> Dict:
        """Get single document."""
        return self._request('GET', f'/documents/{identifier}')

    def classify_instruction(self, text: str, context: Optional[Dict] = None) -> Dict:
        """Classify instruction."""
        return self._request('POST', '/governance/classify', json={
            'text': text,
            'context': context or {}
        })

    def validate_action(self, action: Dict, context: Optional[Dict] = None) -> Dict:
        """Validate action."""
        return self._request('POST', '/governance/validate', json={
            'action': action,
            'context': context or {}
        })

    def enforce_boundary(self, action: Dict, context: Optional[Dict] = None) -> Dict:
        """Check boundary enforcement."""
        return self._request('POST', '/governance/enforce', json={
            'action': action,
            'context': context or {}
        })

    def analyze_pressure(self, context: Dict) -> Dict:
        """Analyze context pressure."""
        return self._request('POST', '/governance/pressure', json={'context': context})

    def verify_action(self, action: Dict, reasoning: Dict, context: Optional[Dict] = None) -> Dict:
        """Metacognitive verification."""
        return self._request('POST', '/governance/verify', json={
            'action': action,
            'reasoning': reasoning,
            'context': context or {}
        })

    def get_audit_logs(self, **params) -> Dict:
        """Get audit logs."""
        return self._request('GET', '/audit/audit-logs', params=params)

    def get_audit_analytics(self, **params) -> Dict:
        """Get audit analytics."""
        return self._request('GET', '/audit/audit-analytics', params=params)


# Usage Example
def main():
    # Initialize client
    client = TractatusClient()

    # Login
    client.login('admin@tractatus.local', 'password')

    # Classify an instruction
    print("\n📋 Classifying instruction...")
    classification = client.classify_instruction(
        'Always use MongoDB on port 27027'
    )
    print(f"Quadrant: {classification['classification']['quadrant']}")
    print(f"Persistence: {classification['classification']['persistence']}")

    # Validate an action
    print("\n✅ Validating action...")
    validation = client.validate_action({
        'type': 'database_config',
        'target': 'MongoDB',
        'parameters': {'port': 27017}
    })
    print(f"Status: {validation['validation']['status']}")

    # Check boundary enforcement
    print("\n🚧 Checking boundary...")
    enforcement = client.enforce_boundary({
        'type': 'policy_change',
        'description': 'Update privacy policy',
        'impact': 'user_privacy'
    })
    print(f"Decision: {enforcement['enforcement']['decision']}")

    # Analyze pressure
    print("\n📊 Analyzing pressure...")
    pressure = client.analyze_pressure({
        'tokenUsage': 50000,
        'tokenBudget': 200000,
        'messageCount': 20
    })
    print(f"Level: {pressure['pressure']['level']}")

    # Get recent documents
    print("\n📚 Fetching documents...")
    docs = client.get_documents(limit=5)
    print(f"Found {docs['pagination']['total']} total documents")


if __name__ == '__main__':
    main()

---

Rate Limiting

The Tractatus API implements rate limiting:

• Login endpoint: 5 attempts per 15 minutes per IP
• General API: 100 requests per 15 minutes per IP

Handle rate limiting:

import time
import requests

def api_call_with_rate_limit(func):
    """Handle rate limiting with automatic retry."""
    try:
        return func()
    except requests.HTTPError as e:
        if e.response.status_code == 429:
            retry_after = int(e.response.headers.get('Retry-After', 60))
            print(f"⚠️ Rate limited. Waiting {retry_after} seconds...")
            time.sleep(retry_after)
            return func()
        raise


# Usage
result = api_call_with_rate_limit(lambda: get_document('some-slug'))

---

Type Hints and Data Classes

For better type safety, use Python data classes:

from dataclasses import dataclass
from typing import List, Optional
from enum import Enum

class Quadrant(Enum):
    STRATEGIC = "STRATEGIC"
    OPERATIONAL = "OPERATIONAL"
    TACTICAL = "TACTICAL"
    SYSTEM = "SYSTEM"
    STOCHASTIC = "STOCHASTIC"

class Persistence(Enum):
    HIGH = "HIGH"
    MEDIUM = "MEDIUM"
    LOW = "LOW"

class PressureLevel(Enum):
    NORMAL = "NORMAL"
    ELEVATED = "ELEVATED"
    HIGH = "HIGH"
    CRITICAL = "CRITICAL"
    DANGEROUS = "DANGEROUS"

@dataclass
class Classification:
    quadrant: Quadrant
    persistence: Persistence
    temporal_scope: str
    verification_required: str
    reasoning: str
    confidence: float

@dataclass
class ValidationResult:
    status: str
    reason: Optional[str] = None
    conflicts: List[Dict] = None
    recommendation: Optional[str] = None

@dataclass
class PressureAnalysis:
    level: PressureLevel
    score: float
    factors: Dict
    recommendation: str
    triggerHandoff: bool
    next_checkpoint: Optional[int] = None

---

For more information, see the API Reference and OpenAPI Specification.