aws-python-helper 0.30.0

AWS Python Helper Framework

AWS Python Framework

Mini-framework to create REST APIs, SQS Consumers, SNS Publishers, Fargate Tasks, and Standalone Lambdas with Python in AWS Lambda.

🚀 Features

• Reusable single handler: A single handler for all your API routes
• Dynamic controller loading: Routing based on convention
• OOP structure: Object-oriented programming for your code
• Flexible MongoDB: Direct access to multiple databases without models
• SQS Consumers: Same pattern to process SQS messages
• SNS Publishers: Same pattern to publish messages to SNS topics
• Fargate Tasks: Same pattern to run tasks in Fargate containers
• Standalone Lambdas: Create lambdas invocable directly with AWS SDK
• Type hints: Modern Python with type annotations
• Async/await: Full support for asynchronous operations

🔧 Installation

# Install dependencies
pip install -r requirements.txt

# Configure MongoDB URI
export MONGODB_URI="mongodb://localhost:27017"

📂 Project Structure

This framework follows a convention-based folder structure. Here's the recommended organization:

your-project/
└── src/
    ├── api/                           # REST APIs
    │   └── users/                     # Resource folder (kebab-case)
    │       ├── get.py                 # GET /users/123 -> UserGetAPI
    │       ├── list.py                # GET /users -> UserListAPI
    │       ├── post.py                # POST /users -> UserPostAPI
    │       ├── put.py                 # PUT /users/123 -> UserPutAPI
    │       └── delete.py              # DELETE /users/123 -> UserDeleteAPI
    │
    ├── consumer/                     # SQS Consumers (direct files)
    │   ├── user_created.py            # user-created -> UserCreatedConsumer
    │   ├── title_indexed.py           # title-indexed -> TitleIndexedConsumer
    │   └── order_processed.py         # order-processed -> OrderProcessedConsumer
    │
    ├── lambda/                        # Standalone Lambdas (folders)
    │   ├── generate-route/            # generate-route -> GenerateRouteLambda
    │   │   └── main.py
    │   ├── sync-carrier/              # sync-carrier -> SyncCarrierLambda
    │   │   └── main.py
    │   └── process-payment/           # process-payment -> ProcessPaymentLambda
    │       └── main.py
    │
    └── task/                         # Fargate Tasks (folders)
        ├── search-tax-by-town/        # search-tax-by-town -> SearchTaxByTownTask
        │   ├── main.py                # Entry point
        │   └── task.py                # Task class
        └── process-data/              # process-data -> ProcessDataTask
            ├── main.py
            └── task.py

Naming Conventions

The framework uses automatic class name detection based on your folder/file structure:

Type	Handler Name	File Path	Class Name
API	N/A	src/api/users/list.py	UsersListAPI
Consumer	user-created	src/consumer/user_created.py	UserCreatedConsumer
Lambda	generate-route	src/lambda/generate-route/main.py	GenerateRouteLambda
Task	search-tax-by-town	src/task/search-tax-by-town/task.py	SearchTaxByTownTask

Rules:

• Handler names use kebab-case (e.g., user-created, generate-route)
• Consumer files use snake_case (e.g., user_created.py)
• Lambda folders use kebab-case (e.g., generate-route/)
• Task folders use kebab-case (e.g., search-tax-by-town/)
• Class names always use PascalCase with suffix (e.g., UserCreatedConsumer)

📝 Basic Usage

Create an Endpoint

1. Create your API class in src/api/constitutions/list.py:

from aws_python_helper.api.base import API

class ConstitutionListAPI(API):
    async def process(self):
        # Direct access to MongoDB
        constitutions = await self.db.constitution_db.constitutions.find().to_list(100)
        self.set_body(constitutions)

2. The routing is automatic:

• GET /constitutions → src/api/constitutions/list.py
• GET /constitutions/123 → src/api/constitutions/get.py
• POST /constitutions → src/api/constitutions/post.py

3. Configure the generic handler (src/handlers/api_handler.py):

from aws_python_helper.api.handler import api_handler
handler = api_handler

Create an SQS Consumer

1. Create your consumer in src/consumer/title_indexed.py:

from aws_python_helper.sqs.consumer_base import SQSConsumer

class TitleIndexedConsumer(SQSConsumer):
    async def process_record(self, record):
        body = self.parse_body(record)
        # Your logic here
        await self.db.constitution_db.titles.insert_one(body)

2. Configure the handler in src/handlers/sqs_handler.py:

from aws_python_helper.sqs.handler import sqs_handler

# Create a handler for each consumer and export it
title_indexed_handler = sqs_handler('title-indexed')

__all__ = ['title_indexed_handler']

Create a Standalone Lambda

Standalone lambdas are functions that can be invoked directly using the AWS SDK, without an HTTP endpoint. They're perfect for internal operations, integrations, and background processing tasks.

Differences with APIs:

• No API Gateway - invoked directly with AWS SDK
• No HTTP methods or routing
• Can be called from other lambdas, Step Functions, or any AWS service
• Perfect for internal microservices communication

1. Create your lambda class in src/lambda/generate-route/main.py:

from aws_python_helper.lambda_standalone.base import Lambda
from datetime import datetime

class GenerateRouteLambda(Lambda):
    async def validate(self):
        # Validate input data
        if 'shipping_id' not in self.data:
            raise ValueError("shipping_id is required")
        
        if not isinstance(self.data['shipping_id'], str):
            raise TypeError("shipping_id must be a string")
    
    async def process(self):
        # Your business logic here
        shipping_id = self.data['shipping_id']
        
        # Access to MongoDB
        shipping = await self.db.deliveries.shippings.find_one(
            {'_id': shipping_id}
        )
        
        if not shipping:
            raise ValueError(f"Shipping {shipping_id} not found")
        
        # Create route
        route = {
            'shipping_id': shipping_id,
            'carrier_id': shipping.get('carrier_id'),
            'status': 'pending',
            'created_at': datetime.utcnow()
        }
        
        result = await self.db.deliveries.routes.insert_one(route)
        
        self.logger.info(f"Route created: {result.inserted_id}")
        
        # Return result
        return {
            'route_id': str(result.inserted_id),
            'shipping_id': shipping_id
        }

2. Configure the handler in src/handlers/lambda_handler.py:

from aws_python_helper.lambda_standalone.handler import lambda_handler

# Create a handler for each lambda and export it
generate_route_handler = lambda_handler('generate-route')
sync_carrier_handler = lambda_handler('sync-carrier')
process_payment_handler = lambda_handler('process-payment')

__all__ = [
    'generate_route_handler',
    'sync_carrier_handler',
    'process_payment_handler'
]

Note: The handler name 'generate-route' (kebab-case) will automatically look for:

• Folder: src/lambda/generate-route/ (kebab-case)
• File: main.py
• Class: GenerateRouteLambda

3. Invoke from another Lambda or API using boto3:

import boto3
import json

lambda_client = boto3.client('lambda')

# Invoke synchronously (RequestResponse)
response = lambda_client.invoke(
    FunctionName='GenerateRouteLambda',
    InvocationType='RequestResponse',
    Payload=json.dumps({
        'data': {
            'shipping_id': '507f1f77bcf86cd799439011'
        }
    })
)

result = json.loads(response['Payload'].read())
# {'success': True, 'data': {'route_id': '...', 'shipping_id': '...'}}

if result['success']:
    print(f"Route created: {result['data']['route_id']}")
else:
    print(f"Error: {result['error']}")

4. Invoke asynchronously (fire and forget):

# Invoke asynchronously (Event)
lambda_client.invoke(
    FunctionName='GenerateRouteLambda',
    InvocationType='Event',  # Asynchronous
    Payload=json.dumps({
        'data': {
            'shipping_id': '507f1f77bcf86cd799439011'
        }
    })
)
# Returns immediately without waiting for the result

Naming Convention:

Lambda Name (kebab-case)	Folder	File	Class
generate-route	src/lambda/generate-route/	main.py	GenerateRouteLambda
sync-carrier	src/lambda/sync-carrier/	main.py	SyncCarrierLambda
process-payment	src/lambda/process-payment/	main.py	ProcessPaymentLambda
send-notification	src/lambda/send-notification/	main.py	SendNotificationLambda

Common Use Cases:

• Internal microservices communication
• Background data processing
• Integration with external services
• Scheduled tasks (with EventBridge)
• Step Functions workflows
• Cross-service operations

Publish to SNS

1. Create your topic in src/topic/title_indexed.py:

from aws_python_helper.sns.publisher import SNSPublisher
import os

class TitleIndexedTopic(SNSPublisher):
    def __init__(self):
        super().__init__(
            topic_arn=os.getenv('TITLE_INDEXED_SNS_TOPIC_ARN')
        )
    
    async def publish_message(self, constitution_id, title):
        await self.publish({
            'constitution_id': constitution_id,
            'title': title,
            'event_type': 'title_indexed'
        })

2. Use the topic from anywhere:

from src.topics.title_indexed import TitleIndexedTopic

# In a consumer, API or task
topic = TitleIndexedTopic()
await topic.publish_indexed('123', 'My Constitution')

Run a Fargate Task

1. Create your task in src/task/search-tax-by-town/task.py:

from aws_python_helper.fargate.task_base import FargateTask

class SearchTaxByTownTask(FargateTask):

    async def execute(self):
        town = self.require_env('TOWN')
        self.logger.info(f"Processing town: {town}")
        
        # Access to DB
        docs = await self.db.smart_data.address.find({'town': town}).to_list()
        
        # Your logic here
        for doc in docs:
            # Process document
            pass

2. Create the entry point in src/task/search-tax-by-town/main.py:

from aws_python_helper.fargate.handler import fargate_handler
import sys

if __name__ == '__main__':
    exit_code = fargate_handler('search-tax-by-town')
    sys.exit(exit_code)

3. Create the Dockerfile in src/task/search-tax-by-town/Dockerfile:

FROM python:3.10.12-slim
WORKDIR /app

# Install dependencies
COPY requirements.txt /app/framework_requirements.txt
COPY src/task/search-tax-by-town/requirements.txt /app/task_requirements.txt
RUN pip install -r /app/framework_requirements.txt && \
    pip install -r /app/task_requirements.txt

# Copy code
COPY aws_python_helper /app/aws_python_helper
COPY config.py /app/config.py
COPY task /app/task
COPY task/search-tax-by-town/main.py /app/main.py

ENV PYTHONUNBUFFERED=1
CMD ["python", "main.py"]

4. Invoke from Lambda:

from aws_python_helper.fargate.executor import FargateExecutor

def handler(event, context):
    executor = FargateExecutor()
    task_arn = executor.run_task(
        'search-tax-by-town',
        envs={'town': 'Norwalk', 'only_tax': 'true'}
    )
    return {'taskArn': task_arn}

🗄️ Access to MongoDB

The framework provides flexible access to multiple databases:

class MyAPI(API):
    async def process(self):
        # Access to different databases
        user = await self.db.users_db.users.find_one({'_id': user_id})
        
        # Another database
        await self.db.analytics_db.logs.insert_one({'action': 'view'})
        
        # Multiple collections
        titles = await self.db.constitution_db.titles.find().to_list(100)
        articles = await self.db.constitution_db.articles.find().to_list(100)

🔄 Routing Convention

The framework uses convention over configuration for the routing:

Request	Loaded file
GET /users	api/users/list.py
GET /users/123	api/users/get.py
POST /users	api/users/post.py
PUT /users/123	api/users/put.py
DELETE /users/123	api/users/delete.py
GET /users/123/posts	api/users/posts/list.py
GET /users/123/posts/456	api/users/posts/get.py

Logic:

• The parts with even indices (0,2,4...) are directories
• The parts with odd indices (1,3,5...) are path parameters
• GET with odd number of parts → list method
• GET with even number of parts → get method
• Other methods use their name directly

🎯 Complete Example

# src/api/constitutions/list.py
from aws_python_helper.api.base import API

class ConstitutionListAPI(API):
    async def validate(self):
        if 'limit' in self.data:
            limit = int(self.data['limit'])
            if limit > 1000:
                raise ValueError("Limit cannot exceed 1000")
    
    async def process(self):
        # Build filters
        filters = {}
        if 'country' in self.data:
            filters['country'] = self.data['country']
        
        # Query MongoDB
        limit = int(self.data.get('limit', 100))
        results = await self.db.constitution_db.constitutions.find(
            filters
        ).limit(limit).to_list(limit)
        
        # Count total
        total = await self.db.constitution_db.constitutions.count_documents(filters)
        
        # Register in analytics
        await self.db.analytics_db.searches.insert_one({
            'filters': filters,
            'result_count': len(results)
        })
        
        # Response
        self.set_body({
            'data': results,
            'total': total
        })
        self.set_header('X-Total-Count', str(total))

🔗 Integration Example: API + Standalone Lambda

Here's a complete example showing how an API can invoke a standalone lambda:

Scenario: An API endpoint that creates a shipping and then asynchronously generates its route using a standalone lambda.

1. The API endpoint (src/api/shippings/post.py):

from aws_python_helper.api.base import API
import boto3
import json

class ShippingPostAPI(API):
    async def validate(self):
        required_fields = ['customer_id', 'address', 'items']
        for field in required_fields:
            if field not in self.data:
                raise ValueError(f"{field} is required")
    
    async def process(self):
        # Create shipping in database
        shipping = {
            'customer_id': self.data['customer_id'],
            'address': self.data['address'],
            'items': self.data['items'],
            'status': 'pending',
            'route_pending': True
        }
        
        result = await self.db.deliveries.shippings.insert_one(shipping)
        shipping_id = str(result.inserted_id)
        
        # Invoke standalone lambda asynchronously to generate route
        lambda_client = boto3.client('lambda')
        lambda_client.invoke(
            FunctionName='GenerateRouteLambda',
            InvocationType='Event',  # Asynchronous
            Payload=json.dumps({
                'data': {'shipping_id': shipping_id}
            })
        )
        
        self.set_code(201)
        self.set_body({
            'shipping_id': shipping_id,
            'status': 'pending',
            'message': 'Shipping created, route generation in progress'
        })

2. The standalone lambda (src/lambda/generate-route/main.py):

from aws_python_helper.lambda_standalone.base import Lambda

class GenerateRouteLambda(Lambda):
    async def validate(self):
        if 'shipping_id' not in self.data:
            raise ValueError("shipping_id is required")
    
    async def process(self):
        shipping_id = self.data['shipping_id']
        
        # Get shipping details
        shipping = await self.db.deliveries.shippings.find_one(
            {'_id': shipping_id}
        )
        
        if not shipping:
            raise ValueError(f"Shipping {shipping_id} not found")
        
        # Generate optimal route
        route = await self.calculate_optimal_route(shipping)
        
        # Save route
        route_result = await self.db.deliveries.routes.insert_one(route)
        
        # Update shipping
        await self.db.deliveries.shippings.update_one(
            {'_id': shipping_id},
            {'$set': {
                'route_id': route_result.inserted_id,
                'route_pending': False,
                'status': 'scheduled'
            }}
        )
        
        return {
            'route_id': str(route_result.inserted_id),
            'shipping_id': shipping_id
        }
    
    async def calculate_optimal_route(self, shipping):
        # Your route calculation logic here
        return {
            'shipping_id': shipping['_id'],
            'carrier_id': shipping.get('carrier_id'),
            'estimated_duration': 60,
            'status': 'pending'
        }

3. Configure handlers (src/handlers/lambda_handler.py):

from aws_python_helper.lambda_standalone.handler import lambda_handler

generate_route_handler = lambda_handler('generate-route')

__all__ = ['generate_route_handler']

Benefits of this pattern:

• API responds immediately (better UX)
• Route generation happens in the background
• Decoupled services (easier to maintain)
• Can retry lambda independently if it fails
• Scalable architecture

🔐 Environment Variables

MongoDB Configuration

El framework soporta dos formas de configurar MongoDB:

Opción 1: Connection String Completa

# URI completa con credenciales incluidas
MONGODB_URI=mongodb+srv://user:[e-mail]/dbname?retryWrites=true&w=majority
# o
MONGO_DB_URI=mongodb+srv://user:[e-mail]/dbname

Opción 2: Componentes Separados (Recomendado para Terraform)

# Host sin credenciales
MONGO_DB_HOST=mongodb+srv://cluster.mongodb.net

# Credenciales separadas (más seguro)
MONGO_DB_USER=admin
MONGO_DB_PASSWORD=my-secure-password

# Opcionales
MONGO_DB_NAME=my_database
MONGO_DB_OPTIONS=retryWrites=true&w=majority

Ventajas de usar componentes separados:

• ✅ Mejor seguridad: credenciales separadas del host
• ✅ Fácil integración con Terraform/AWS Secrets Manager
• ✅ Contraseñas con caracteres especiales se manejan automáticamente
• ✅ Más flexible para diferentes entornos

El framework automáticamente:

1. URL-encodea la contraseña (maneja @, :, /, etc.)
2. Construye la URI completa
3. Inicializa la conexión

Ejemplo en Terraform

environment_variables = {
  MONGO_DB_HOST     = module.mongodb.connection_string
  MONGO_DB_USER     = module.mongodb.database_user
  MONGO_DB_PASSWORD = module.mongodb.database_password
}

Rest Environment Variables

📊 Advanced Features

SNS Publisher - Batch Publishing

# Publish multiple messages
topic = TitleIndexedTopic()
await topic.publish_batch_indexed([
    {'constitution_id': 'id1', 'title': 'Title 1'},
    {'constitution_id': 'id2', 'title': 'Title 2'},
    {'constitution_id': 'id3', 'title': 'Title 3'}
])

Fargate - Run multiple tasks

executor = FargateExecutor()
task_arns = executor.run_task_batch(
    'search-tax-by-town',
    [
        {'town': 'Norwalk'},
        {'town': 'Stamford'},
        {'town': 'Bridgeport'}
    ]
)

Fargate - Check task status

executor = FargateExecutor()
task_arn = executor.run_task('my-task', {'param': 'value'})

# Check task status
status = executor.get_task_status(task_arn)
print(f"Status: {status['status']}")
print(f"Started at: {status['started_at']}")

SNS - Message Attributes

# Publish with attributes for SNS filtering
topic = ConstitutionCreatedTopic()
await topic.publish_created(
    constitution_id='123',
    title='New Constitution',
    country='Ecuador',
    year=2023,
    created_by='user_456',
    attributes={'priority': 'high', 'region': 'latam'}
)

🤝 Contributing

If you find bugs or want to add features, please create a PR!

📄 License

MIT