aws-python-helper 0.30.1

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
• External MongoDB: Connect to multiple MongoDB clusters simultaneously
• SQS Consumers: Same pattern to process SQS messages (single or batch mode)
• 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
• Authentication middleware: Built-in token-based authentication
• JSON utilities: Automatic serialization of MongoDB types
• Type hints: Modern Python with type annotations
• Async/await: Full support for asynchronous operations

🔧 Installation

pip install aws-python-helper

📦 Quick Reference

All available classes and functions:

Class / Function	Import	Purpose
API	aws_python_helper.api.base	Base class for REST endpoints
api_handler	aws_python_helper.api.handler	Generic handler for API Gateway
SQSConsumer	aws_python_helper.sqs.consumer_base	Base class for SQS consumers
sqs_handler	aws_python_helper.sqs.handler	Factory handler for SQS
SNSPublisher	aws_python_helper.sns.publisher	Base class for SNS publishers
Lambda	aws_python_helper.lambda_standalone.base	Base class for Standalone Lambdas
lambda_handler	aws_python_helper.lambda_standalone.handler	Factory handler for Lambda
FargateTask	aws_python_helper.fargate.task_base	Base class for Fargate tasks
FargateExecutor	aws_python_helper.fargate.executor	Launches Fargate tasks from Lambda
fargate_handler	aws_python_helper.fargate.handler	Entry point handler for Fargate
MongoJSONEncoder	aws_python_helper.utils.json_encoder	JSON encoder for MongoDB types
mongo_json_dumps	aws_python_helper.utils.json_encoder	Helper to serialize MongoDB types
serialize_mongo_types	aws_python_helper.utils.serializer	Recursively serialize MongoDB types
UnauthorizedError	aws_python_helper.api.exceptions	401 authentication exception
ForbiddenError	aws_python_helper.api.exceptions	403 authorization exception

📂 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
    │
    └── topic/                        # SNS Publishers
        └── order_created.py           # OrderCreatedTopic

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.extract_content_message(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')
        )

    def build_message(self, constitution_id, title, event_type='title_indexed'):
        return {
            'content': {
                'constitution_id': constitution_id,
                'title': title,
                'event_type': event_type
            },
            'attributes': {
                'event_type': event_type   # Used for SNS subscription filtering
            }
        }

2. Use the topic from anywhere:

from src.topic.title_indexed import TitleIndexedTopic

# In a consumer, API or task
topic = TitleIndexedTopic()

# Publish a single message
await topic.publish(topic.build_message('123', 'My Constitution'))

# Publish multiple messages in batch
messages = [
    topic.build_message('id1', 'Constitution A'),
    topic.build_message('id2', 'Constitution B'),
]
await topic.publish(messages)

Message format — every message must have a content key:

{
    'content': {...},              # Required: message body (any dict)
    'attributes': {...},           # Optional: SNS message attributes for filtering
    'subject': 'Optional subject'  # Optional: message subject
}

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 on the same cluster
        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)

The pattern is always: self.db.<database_name>.<collection_name>.<motor_operation>()

External MongoDB Clusters

Connect to additional MongoDB clusters using EXTERNAL_MONGODB_CONNECTIONS:

EXTERNAL_MONGODB_CONNECTIONS='[
    {"name": "ClusterDockets", "connection_string": "mongodb+srv://cluster.mongodb.net"},
    {"name": "ClusterAnalytics", "connection_string": "mongodb+srv://analytics.mongodb.net"}
]'

The credentials from MONGO_DB_USER / MONGO_DB_PASSWORD are automatically injected into the connection strings.

Access external clusters via self.external_db:

class AddressAPI(API):
    async def process(self):
        # Access external cluster: self.external_db.<ClusterName>.<database>.<collection>
        addresses = await self.external_db.ClusterDockets.smart_data.addresses.find(
            {'town': self.data['town']}
        ).to_list(100)

        self.set_body({'addresses': addresses})

self.external_db is available in API, SQSConsumer, Lambda, and FargateTask.

🔄 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

🧩 API Class Reference

All properties and methods available inside an API subclass:

Request Properties

Property	Type	Description
self.data	dict	Request body (POST/PUT) or query params (GET)
self.headers	dict	HTTP request headers
self.path_parameters	dict	URL path parameters (e.g. /users/123 → {'id': '123'})
self.query_parameters	dict	Query string parameters
self.db	DatabaseProxy	Access to main MongoDB cluster
self.external_db	ExternalDatabaseProxy	Access to external MongoDB clusters
self.current_user	dict | None	Authenticated user document (requires REQUIRE_AUTH=true)
self.is_authenticated	bool	Whether the request is authenticated
self.auth_data	dict | None	Full authentication data

Response Methods

Method	Description
self.set_code(code: int)	Set HTTP response status code
self.set_body(body: Any)	Set response body (auto-serialized to JSON)
self.set_header(key: str, value: str)	Add a single response header
self.set_headers(headers: dict)	Set multiple response headers at once

Methods to Override

Method	Required	Description
async validate()	Optional	Validate request data, raise exceptions to reject
async process()	Required	Main business logic

class UserGetAPI(API):
    async def validate(self):
        # Access path params: /users/123 → self.path_parameters = {'id': '123'}
        if not self.path_parameters.get('id'):
            raise ValueError("User ID is required")

    async def process(self):
        user_id = self.path_parameters['id']
        user = await self.db.users_db.users.find_one({'_id': user_id})

        if not user:
            self.set_code(404)
            self.set_body({'error': 'User not found'})
            return

        self.set_code(200)
        self.set_body({'data': user})
        self.set_header('X-Resource-Id', user_id)

🔐 Authentication

The framework includes a built-in token-based authentication middleware.

Configuration

REQUIRE_AUTH=true            # Enable authentication (default: false)
AUTH_DB_NAME=my_database     # MongoDB database where tokens are stored
AUTH_BYPASS_TOKEN=secret123  # Master token to bypass auth (for internal use)

Using the authenticated user

When REQUIRE_AUTH=true, every request must include a valid Authorization: Bearer <token> header. The authenticated user is available via self.current_user:

class OrderListAPI(API):
    async def process(self):
        # self.current_user contains the user document from MongoDB
        user_id = self.current_user['_id']

        orders = await self.db.orders_db.orders.find(
            {'user_id': user_id}
        ).to_list(100)

        self.set_body({'data': orders})

Auth exceptions

Use these exceptions in your validate() or process() methods:

from aws_python_helper.api.exceptions import UnauthorizedError, ForbiddenError

class AdminOnlyAPI(API):
    async def validate(self):
        if not self.is_authenticated:
            raise UnauthorizedError("Authentication required")  # Returns 401

        if self.current_user.get('role') != 'admin':
            raise ForbiddenError("Admin access required")       # Returns 403

🎯 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

🏗️ Architecture Overview

Typical flow for event-driven architectures using this framework:

┌──────────┐     ┌─────────────┐     ┌──────────────────────────────────────┐
│  Client  │────▶│ API Gateway │────▶│  Lambda: api_handler                 │
└──────────┘     └─────────────┘     │  (src/api/resource/post.py)          │
                                     │  → validates, queries MongoDB,        │
                                     │    publishes to SNS                   │
                                     └────────────────┬─────────────────────┘
                                                      │
                                                      ▼
                                             ┌─────────────────┐
                                             │   SNS Topic     │
                                             │ (fanout/filter) │
                                             └────────┬────────┘
                                      ┌───────────────┼───────────────┐
                                      ▼               ▼               ▼
                               ┌────────────┐  ┌────────────┐  ┌────────────┐
                               │  SQS Queue │  │  SQS Queue │  │  SQS Queue │
                               │  Platform A│  │  Platform B│  │  Platform C│
                               └─────┬──────┘  └─────┬──────┘  └─────┬──────┘
                                     │               │               │
                                     ▼               ▼               ▼
                               ┌──────────────────────────────────────────────┐
                               │  Lambda: sqs_handler                         │
                               │  (src/consumer/platform_consumer.py)         │
                               │  → groups messages, acquires sessions,        │
                               │    launches Fargate tasks                     │
                               └───────────────────┬──────────────────────────┘
                                                   │  FargateExecutor.run_task()
                                                   ▼
                               ┌──────────────────────────────────────────────┐
                               │  Fargate Task: fargate_handler               │
                               │  (src/task/my-task/task.py)                  │
                               │  → scrapes/processes data,                   │
                               │    writes results to MongoDB                  │
                               └──────────────────────────────────────────────┘

🔐 Environment Variables

MongoDB Configuration

The framework supports two ways to configure MongoDB:

Option 1: Full Connection String

# Full URI with embedded credentials
MONGODB_URI=mongodb+srv://user:[e-mail]/dbname?retryWrites=true&w=majority
# or
MONGO_DB_URI=mongodb+srv://user:[e-mail]/dbname

Option 2: Separate Components (Recommended for Terraform)

# Host without credentials
MONGO_DB_HOST=mongodb+srv://cluster.mongodb.net

# Credentials (more secure)
MONGO_DB_USER=admin
MONGO_DB_PASSWORD=my-secure-password

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

Benefits of separate components:

• ✅ Better security: credentials separate from host
• ✅ Easy integration with Terraform/AWS Secrets Manager
• ✅ Passwords with special characters are handled automatically
• ✅ More flexible for different environments

The framework automatically:

1. URL-encodes the password (handles @, :, /, etc.)
2. Builds the full URI
3. Initializes the connection

Terraform Example

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

All Environment Variables

Variable	Required	Description
MONGODB_URI or MONGO_DB_URI	One of these or components below	Full MongoDB connection string
MONGO_DB_HOST	Alt. to URI	MongoDB host (e.g. mongodb+srv://cluster.net)
MONGO_DB_USER	Alt. to URI	MongoDB username
MONGO_DB_PASSWORD	Alt. to URI	MongoDB password
MONGO_DB_NAME	Optional	Default database name
MONGO_DB_OPTIONS	Optional	Connection options (e.g. retryWrites=true&w=majority)
EXTERNAL_MONGODB_CONNECTIONS	Optional	JSON array of external cluster configurations
REQUIRE_AUTH	Optional	Enable authentication middleware (true/false)
AUTH_DB_NAME	If REQUIRE_AUTH=true	MongoDB database for token validation
AUTH_BYPASS_TOKEN	Optional	Master token to bypass authentication
ECS_CLUSTER	Fargate only	ECS cluster name for FargateExecutor
ECS_SUBNETS	Fargate only	Comma-separated subnet IDs for Fargate tasks
AWS_REGION	Fargate/SNS/SQS	AWS region
AWS_ACCOUNT_ID	SQS get_queue_url	AWS account ID
SERVICE_NAME	SQS get_queue_url	Service name prefix for queue name
QUEUE_NAME	SQS get_queue_url	Queue name segment
ENV	SQS get_queue_url	Environment suffix (e.g. prod, dev)

📊 Advanced Features

SQS Consumer - Batch Mode

By default, consumers process messages one by one ("single" mode). Use "batch" mode when you need to group or bulk-process messages:

from aws_python_helper.sqs.consumer_base import SQSConsumer

class OrderConsumer(SQSConsumer):

    @property
    def processing_mode(self) -> str:
        return "batch"

    async def process_batch(self, records):
        # Group records by some key before processing
        grouped = {}
        for record in records:
            message_id = record.get('messageId')
            body = self.extract_content_message(record)
            key = body.get('region', 'default')
            grouped.setdefault(key, []).append((message_id, body))

        for region, messages in grouped.items():
            try:
                # Bulk operation for the whole group
                docs = [msg[1] for msg in messages]
                await self.db.orders_db.orders.insert_many(docs)
            except Exception as e:
                # Mark individual messages as failed
                for message_id, _ in messages:
                    self.add_message_failed(message_id, str(e))

Key methods in SQSConsumer:

Method / Property	Description
self.extract_content_message(record)	Parse message body (handles SNS → SQS wrapping automatically)
self.parse_body(record)	Alias for extract_content_message
self.add_message_failed(message_id, error)	Mark a message for retry (batch mode)
self.get_queue_url()	Get the SQS queue URL (uses AWS_REGION, AWS_ACCOUNT_ID, SERVICE_NAME, QUEUE_NAME, ENV)
self.db	Access to main MongoDB cluster
self.external_db	Access to external MongoDB clusters

Retry behavior:

• Messages marked with add_message_failed() are reported via reportBatchItemFailures
• AWS SQS retries only the failed messages, not the whole batch
• Successful messages in the same batch are not retried

SNS Publisher - Batch Publishing

topic = TitleIndexedTopic()

# Publish multiple messages in a single call
await topic.publish([
    {'content': {'id': 'id1', 'title': 'Title 1'}, 'attributes': {'type': 'created'}},
    {'content': {'id': 'id2', 'title': 'Title 2'}, 'attributes': {'type': 'updated'}},
    {'content': {'id': 'id3', 'title': 'Title 3'}},  # attributes are optional
])

SNS - Message Attributes for Filtering

Use attributes to filter which SQS subscriptions receive each message:

class EventTopic(SNSPublisher):
    def __init__(self):
        super().__init__(topic_arn=os.getenv('EVENTS_SNS_TOPIC_ARN'))

    def build_message(self, payload, event_type, priority='normal'):
        return {
            'content': payload,
            'attributes': {
                'event_type': event_type,   # SQS subscriptions can filter on this
                'priority': priority
            }
        }

# Usage
topic = EventTopic()
await topic.publish(topic.build_message(
    payload={'order_id': '123', 'amount': 99.99},
    event_type='order_created',
    priority='high'
))

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']}")

JSON Utilities for MongoDB Types

When returning MongoDB documents in API responses or exporting data, use the built-in serializers to handle ObjectId, datetime, Decimal128, and other BSON types:

import json
from aws_python_helper.utils.json_encoder import MongoJSONEncoder, mongo_json_dumps
from aws_python_helper.utils.serializer import serialize_mongo_types

# Use as json.dumps cls parameter
json_str = json.dumps(my_mongo_doc, cls=MongoJSONEncoder)

# Helper function
json_str = mongo_json_dumps(my_mongo_doc)

# Convert a document in-place (dict → JSON-serializable dict)
clean_doc = serialize_mongo_types(my_mongo_doc)

Types automatically converted:

MongoDB Type	Converts to
ObjectId	str
datetime	ISO 8601 string
date	ISO 8601 string
Decimal128	float
Decimal	float
Binary	base64 str
UUID	str
bytes	base64 str
set	list

Common use case — exporting query results to JSON files:

from aws_python_helper.utils.json_encoder import MongoJSONEncoder

class ExportResultsAPI(API):
    async def process(self):
        records = await self.db.orders_db.orders.find({}).to_list(1000)

        # Write to file with MongoJSONEncoder
        with open('/tmp/export.json', 'w') as f:
            json.dump(records, f, cls=MongoJSONEncoder, ensure_ascii=False, indent=2)

🤝 Contributing

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

📄 License

MIT