title | description |
---|---|
REST API |
Core utility |
Event handler for Amazon API Gateway REST and HTTP APIs, and Application Loader Balancer (ALB).
- Lightweight routing to reduce boilerplate for API Gateway REST/HTTP API and ALB
- Seamless support for CORS, binary and Gzip compression
- Integrates with Data classes utilities{target="_blank"} to easily access event and identity information
- Built-in support for Decimals JSON encoding
- Support for dynamic path expressions
- Router to allow for splitting up the handler across multiple files
You must have an existing API Gateway Proxy integration{target="_blank"} or ALB{target="_blank"} configured to invoke your Lambda function. There is no additional permissions or dependencies required to use this utility.
This is the sample infrastructure for API Gateway we are using for the examples in this documentation.
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: Hello world event handler API Gateway
Globals:
Api:
TracingEnabled: true
Cors: # see CORS section
AllowOrigin: "'https://example.com'"
AllowHeaders: "'Content-Type,Authorization,X-Amz-Date'"
MaxAge: "'300'"
BinaryMediaTypes: # see Binary responses section
- '*~1*' # converts to */* for any binary type
Function:
Timeout: 5
Runtime: python3.8
Tracing: Active
Environment:
Variables:
LOG_LEVEL: INFO
POWERTOOLS_LOGGER_SAMPLE_RATE: 0.1
POWERTOOLS_LOGGER_LOG_EVENT: true
POWERTOOLS_METRICS_NAMESPACE: MyServerlessApplication
POWERTOOLS_SERVICE_NAME: my_api-service
Resources:
ApiFunction:
Type: AWS::Serverless::Function
Properties:
Handler: app.lambda_handler
CodeUri: api_handler/
Description: API handler function
Events:
ApiEvent:
Type: Api
Properties:
Path: /{proxy+} # Send requests on any path to the lambda function
Method: ANY # Send requests using any http method to the lambda function
Before you decorate your functions to handle a given path and HTTP method(s), you need to initialize a resolver.
A resolver will handle request resolution, include one or more routers, and give you access to the current event via typed properties.
For resolvers, we provide: APIGatewayRestResolver
, APIGatewayHttpResolver
, and ALBResolver
.
???+ info
We will use APIGatewayRestResolver
as the default across examples.
When using Amazon API Gateway REST API to front your Lambda functions, you can use APIGatewayRestResolver
.
Here's an example on how we can handle the /hello
path.
???+ info
We automatically serialize Dict
responses as JSON, trim whitespace for compact responses, and set content-type to application/json
.
=== "app.py"
```python hl_lines="3 7 9 12 18"
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
@app.get("/hello")
@tracer.capture_method
def get_hello_universe():
return {"message": "hello universe"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "hello_event.json"
This utility uses `path` and `httpMethod` to route to the right function. This helps make unit tests and local invocation easier too.
```json hl_lines="4-5"
{
"body": "hello",
"resource": "/hello",
"path": "/hello",
"httpMethod": "GET",
"isBase64Encoded": false,
"queryStringParameters": {
"foo": "bar"
},
"multiValueQueryStringParameters": {},
"pathParameters": {
"hello": "/hello"
},
"stageVariables": {},
"headers": {
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
"Accept-Encoding": "gzip, deflate, sdch",
"Accept-Language": "en-US,en;q=0.8",
"Cache-Control": "max-age=0",
"CloudFront-Forwarded-Proto": "https",
"CloudFront-Is-Desktop-Viewer": "true",
"CloudFront-Is-Mobile-Viewer": "false",
"CloudFront-Is-SmartTV-Viewer": "false",
"CloudFront-Is-Tablet-Viewer": "false",
"CloudFront-Viewer-Country": "US",
"Host": "1234567890.execute-api.us-east-1.amazonaws.com",
"Upgrade-Insecure-Requests": "1",
"User-Agent": "Custom User Agent String",
"Via": "1.1 08f323deadbeefa7af34d5feb414ce27.cloudfront.net (CloudFront)",
"X-Amz-Cf-Id": "cDehVQoZnx43VYQb9j2-nvCh-9z396Uhbp027Y2JvkCPNLmGJHqlaA==",
"X-Forwarded-For": "127.0.0.1, 127.0.0.2",
"X-Forwarded-Port": "443",
"X-Forwarded-Proto": "https"
},
"multiValueHeaders": {},
"requestContext": {
"accountId": "123456789012",
"resourceId": "123456",
"stage": "Prod",
"requestId": "c6af9ac6-7b61-11e6-9a41-93e8deadbeef",
"requestTime": "25/Jul/2020:12:34:56 +0000",
"requestTimeEpoch": 1428582896000,
"identity": {
"cognitoIdentityPoolId": null,
"accountId": null,
"cognitoIdentityId": null,
"caller": null,
"accessKey": null,
"sourceIp": "127.0.0.1",
"cognitoAuthenticationType": null,
"cognitoAuthenticationProvider": null,
"userArn": null,
"userAgent": "Custom User Agent String",
"user": null
},
"path": "/Prod/hello",
"resourcePath": "/hello",
"httpMethod": "POST",
"apiId": "1234567890",
"protocol": "HTTP/1.1"
}
}
```
=== "response.json"
```json
{
"statusCode": 200,
"headers": {
"Content-Type": "application/json"
},
"body": "{\"message\":\"hello universe\"}",
"isBase64Encoded": false
}
```
When using Amazon API Gateway HTTP API to front your Lambda functions, you can use APIGatewayHttpResolver
.
???+ note
Using HTTP API v1 payload? Use APIGatewayRestResolver
instead. APIGatewayHttpResolver
defaults to v2 payload.
Here's an example on how we can handle the /hello
path.
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayHttpResolver
tracer = Tracer()
logger = Logger()
app = APIGatewayHttpResolver()
@app.get("/hello")
@tracer.capture_method
def get_hello_universe():
return {"message": "hello universe"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_HTTP)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
When using Amazon Application Load Balancer to front your Lambda functions, you can use ALBResolver
.
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import ALBResolver
tracer = Tracer()
logger = Logger()
app = ALBResolver()
@app.get("/hello")
@tracer.capture_method
def get_hello_universe():
return {"message": "hello universe"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.APPLICATION_LOAD_BALANCER)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
You can use /path/{dynamic_value}
when configuring dynamic URL paths. This allows you to define such dynamic value as part of your function signature.
=== "app.py"
```python hl_lines="9 11"
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
@app.get("/hello/<name>")
@tracer.capture_method
def get_hello_you(name):
return {"message": f"hello {name}"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "sample_request.json"
```json
{
"resource": "/hello/{name}",
"path": "/hello/lessa",
"httpMethod": "GET",
...
}
```
You can also nest paths as configured earlier in our sample infrastructure: /{message}/{name}
.
=== "app.py"
```python hl_lines="9 11"
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
@app.get("/<message>/<name>")
@tracer.capture_method
def get_message(message, name):
return {"message": f"{message}, {name}"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "sample_request.json"
```json
{
"resource": "/{message}/{name}",
"path": "/hi/michael",
"httpMethod": "GET",
...
}
```
???+ note We recommend having explicit routes whenever possible; use catch-all routes sparingly.
You can use a regex string to handle an arbitrary number of paths within a request, for example .+
.
You can also combine nested paths with greedy regex to catch in between routes.
???+ warning We will choose the more explicit registered route that match incoming event.
=== "app.py"
```python hl_lines="5"
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
app = APIGatewayRestResolver()
@app.get(".+")
def catch_any_route_after_any():
return {"path_received": app.current_event.path}
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "sample_request.json"
```json
{
"resource": "/any/route/should/work",
"path": "/any/route/should/work",
"httpMethod": "GET",
...
}
```
You can use named decorators to specify the HTTP method that should be handled in your functions. As well as the
get
method already shown above, you can use post
, put
, patch
, delete
, and patch
.
=== "app.py"
```python hl_lines="9-10"
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
# Only POST HTTP requests to the path /hello will route to this function
@app.post("/hello")
@tracer.capture_method
def get_hello_you():
name = app.current_event.json_body.get("name")
return {"message": f"hello {name}"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "sample_request.json"
```json
{
"resource": "/hello/{name}",
"path": "/hello/lessa",
"httpMethod": "GET",
...
}
```
If you need to accept multiple HTTP methods in a single function, you can use the route
method and pass a list of
HTTP methods.
=== "app.py"
```python hl_lines="9-10"
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
# PUT and POST HTTP requests to the path /hello will route to this function
@app.route("/hello", method=["PUT", "POST"])
@tracer.capture_method
def get_hello_you():
name = app.current_event.json_body.get("name")
return {"message": f"hello {name}"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "sample_request.json"
```json
{
"resource": "/hello/{name}",
"path": "/hello/lessa",
"httpMethod": "GET",
...
}
```
???+ note It is usually better to have separate functions for each HTTP method, as the functionality tends to differ depending on which method is used.
By integrating with Data classes utilities{target="_blank"}, you have access to request details, Lambda context and also some convenient methods.
These are made available in the response returned when instantiating APIGatewayRestResolver
, for example app.current_event
and app.lambda_context
.
Within app.current_event
property, you can access query strings as dictionary via query_string_parameters
, or by name via get_query_string_value
method.
You can access the raw payload via body
property, or if it's a JSON string you can quickly deserialize it via json_body
property.
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
app = APIGatewayRestResolver()
@app.get("/hello")
def get_hello_you():
query_strings_as_dict = app.current_event.query_string_parameters
json_payload = app.current_event.json_body
payload = app.current_event.body
name = app.current_event.get_query_string_value(name="name", default_value="")
return {"message": f"hello {name}"}
def lambda_handler(event, context):
return app.resolve(event, context)
Similarly to Query strings, you can access headers as dictionary via app.current_event.headers
, or by name via get_header_value
.
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
app = APIGatewayRestResolver()
@app.get("/hello")
def get_hello_you():
headers_as_dict = app.current_event.headers
name = app.current_event.get_header_value(name="X-Name", default_value="")
return {"message": f"hello {name}"}
def lambda_handler(event, context):
return app.resolve(event, context)
By default, we return 404
for any unmatched route.
You can use not_found
decorator to override this behaviour, and return a custom Response
.
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import content_types
from aws_lambda_powertools.event_handler.api_gateway import APIGatewayRestResolver, Response
from aws_lambda_powertools.event_handler.exceptions import NotFoundError
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
@app.not_found
@tracer.capture_method
def handle_not_found_errors(exc: NotFoundError) -> Response:
# Return 418 upon 404 errors
logger.info(f"Not found route: {app.current_event.path}")
return Response(
status_code=418,
content_type=content_types.TEXT_PLAIN,
body="I'm a teapot!"
)
@app.get("/catch/me/if/you/can")
@tracer.capture_method
def catch_me_if_you_can():
return {"message": "oh hey"}
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
You can use exception_handler
decorator with any Python exception. This allows you to handle a common exception outside your route, for example validation errors.
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import content_types
from aws_lambda_powertools.event_handler.api_gateway import APIGatewayRestResolver, Response
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
@app.exception_handler(ValueError)
def handle_value_error(ex: ValueError):
metadata = {"path": app.current_event.path}
logger.error(f"Malformed request: {ex}", extra=metadata)
return Response(
status_code=400,
content_type=content_types.TEXT_PLAIN,
body="Invalid request",
)
@app.get("/hello")
@tracer.capture_method
def hello_name():
name = app.current_event.get_query_string_value(name="name")
if name is not None:
raise ValueError("name query string must be present")
return {"message": f"hello {name}"}
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
You can easily raise any HTTP Error back to the client using ServiceError
exception.
???+ info If you need to send custom headers, use Response class instead.
Additionally, we provide pre-defined errors for the most popular ones such as HTTP 400, 401, 404, 500.
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
from aws_lambda_powertools.event_handler.exceptions import (
BadRequestError,
InternalServerError,
NotFoundError,
ServiceError,
UnauthorizedError,
)
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
@app.get(rule="/bad-request-error")
def bad_request_error():
# HTTP 400
raise BadRequestError("Missing required parameter")
@app.get(rule="/unauthorized-error")
def unauthorized_error():
# HTTP 401
raise UnauthorizedError("Unauthorized")
@app.get(rule="/not-found-error")
def not_found_error():
# HTTP 404
raise NotFoundError
@app.get(rule="/internal-server-error")
def internal_server_error():
# HTTP 500
raise InternalServerError("Internal server error")
@app.get(rule="/service-error", cors=True)
def service_error():
raise ServiceError(502, "Something went wrong!")
# alternatively
# from http import HTTPStatus
# raise ServiceError(HTTPStatus.BAD_GATEWAY.value, "Something went wrong)
def handler(event, context):
return app.resolve(event, context)
When using Custom Domain API Mappings feature, you must use strip_prefixes
param in the APIGatewayRestResolver
constructor.
Scenario: You have a custom domain api.mydomain.dev
and set an API Mapping payment
to forward requests to your Payments API, the path argument will be /payment/<your_actual_path>
.
This will lead to a HTTP 404 despite having your Lambda configured correctly. See the example below on how to account for this change.
=== "app.py"
```python hl_lines="7"
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver(strip_prefixes=["/payment"])
@app.get("/subscriptions/<subscription>")
@tracer.capture_method
def get_subscription(subscription):
return {"subscription_id": subscription}
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "sample_request.json"
```json
{
"resource": "/subscriptions/{subscription}",
"path": "/payment/subscriptions/123",
"httpMethod": "GET",
...
}
```
???+ note
After removing a path prefix with strip_prefixes
, the new root path will automatically be mapped to the path argument of /
.
For example, when using `strip_prefixes` value of `/pay`, there is no difference between a request path of `/pay` and `/pay/`; and the path argument would be defined as `/`.
You can configure CORS at the APIGatewayRestResolver
constructor via cors
parameter using the CORSConfig
class.
This will ensure that CORS headers are always returned as part of the response when your functions match the path invoked.
=== "app.py"
```python hl_lines="9 11"
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler.api_gateway import APIGatewayRestResolver, CORSConfig
tracer = Tracer()
logger = Logger()
cors_config = CORSConfig(allow_origin="https://example.com", max_age=300)
app = APIGatewayRestResolver(cors=cors_config)
@app.get("/hello/<name>")
@tracer.capture_method
def get_hello_you(name):
return {"message": f"hello {name}"}
@app.get("/hello", cors=False) # optionally exclude CORS from response, if needed
@tracer.capture_method
def get_hello_no_cors_needed():
return {"message": "hello, no CORS needed for this path ;)"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "response.json"
```json
{
"statusCode": 200,
"headers": {
"Content-Type": "application/json",
"Access-Control-Allow-Origin": "https://www.example.com",
"Access-Control-Allow-Headers": "Authorization,Content-Type,X-Amz-Date,X-Amz-Security-Token,X-Api-Key"
},
"body": "{\"message\":\"hello lessa\"}",
"isBase64Encoded": false
}
```
=== "response_no_cors.json"
```json
{
"statusCode": 200,
"headers": {
"Content-Type": "application/json"
},
"body": "{\"message\":\"hello lessa\"}",
"isBase64Encoded": false
}
```
???+ tip
Optionally disable CORS on a per path basis with cors=False
parameter.
Pre-flight (OPTIONS) calls are typically handled at the API Gateway level as per our sample infrastructure, no Lambda integration necessary. However, ALB expects you to handle pre-flight requests.
For convenience, we automatically handle that for you as long as you setup CORS in the constructor level.
For convenience, these are the default values when using CORSConfig
to enable CORS:
???+ warning
Always configure allow_origin
when using in production.
Key | Value | Note |
---|---|---|
allow_origin{target="_blank"}: str |
* |
Only use the default value for development. Never use * for production unless your use case requires it |
allow_headers{target="_blank"}: List[str] |
[Authorization, Content-Type, X-Amz-Date, X-Api-Key, X-Amz-Security-Token] |
Additional headers will be appended to the default list for your convenience |
expose_headers{target="_blank"}: List[str] |
[] |
Any additional header beyond the safe listed by CORS specification{target="_blank"}. |
max_age{target="_blank"}: int |
`` | Only for pre-flight requests if you choose to have your function to handle it instead of API Gateway |
allow_credentials{target="_blank"}: bool |
False |
Only necessary when you need to expose cookies, authorization headers or TLS client certificates. |
You can use the Response
class to have full control over the response, for example you might want to add additional headers or set a custom Content-type.
=== "app.py"
```python hl_lines="11-16"
import json
from aws_lambda_powertools.event_handler.api_gateway import APIGatewayRestResolver, Response
app = APIGatewayRestResolver()
@app.get("/hello")
def get_hello_you():
payload = json.dumps({"message": "I'm a teapot"})
custom_headers = {"X-Custom": "X-Value"}
return Response(
status_code=418,
content_type="application/json",
body=payload,
headers=custom_headers,
)
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "response.json"
```json
{
"body": "{\"message\":\"I\'m a teapot\"}",
"headers": {
"Content-Type": "application/json",
"X-Custom": "X-Value"
},
"isBase64Encoded": false,
"statusCode": 418
}
You can compress with gzip and base64 encode your responses via compress
parameter.
???+ warning
The client must send the Accept-Encoding
header, otherwise a normal response will be sent.
=== "app.py"
```python hl_lines="5 7"
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
app = APIGatewayRestResolver()
@app.get("/hello", compress=True)
def get_hello_you():
return {"message": "hello universe"}
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "sample_request.json"
```json
{
"headers": {
"Accept-Encoding": "gzip"
},
"httpMethod": "GET",
"path": "/hello",
...
}
```
=== "response.json"
```json
{
"body": "H4sIAAAAAAACE6tWyk0tLk5MT1WyUspIzcnJVyjNyyxLLSpOVaoFANha8kEcAAAA",
"headers": {
"Content-Encoding": "gzip",
"Content-Type": "application/json"
},
"isBase64Encoded": true,
"statusCode": 200
}
```
For convenience, we automatically base64 encode binary responses. You can also use in combination with compress
parameter if your client supports gzip.
Like compress
feature, the client must send the Accept
header with the correct media type.
???+ warning This feature requires API Gateway to configure binary media types, see our sample infrastructure for reference.
=== "app.py"
```python hl_lines="4 7 11"
import os
from pathlib import Path
from aws_lambda_powertools.event_handler.api_gateway import APIGatewayRestResolver, Response
app = APIGatewayRestResolver()
logo_file: bytes = Path(os.getenv("LAMBDA_TASK_ROOT") + "/logo.svg").read_bytes()
@app.get("/logo")
def get_logo():
return Response(status_code=200, content_type="image/svg+xml", body=logo_file)
def lambda_handler(event, context):
return app.resolve(event, context)
```
=== "logo.svg"
```xml
<?xml version="1.0" encoding="utf-8"?>
<!-- Generator: Adobe Illustrator 19.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0) -->
<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
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```
=== "sample_request.json"
```json
{
"headers": {
"Accept": "image/svg+xml"
},
"httpMethod": "GET",
"path": "/logo",
...
}
```
=== "response.json"
```json
{
"body": "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",
"headers": {
"Content-Type": "image/svg+xml"
},
"isBase64Encoded": true,
"statusCode": 200
}
```
You can enable debug mode via debug
param, or via POWERTOOLS_EVENT_HANDLER_DEBUG
environment variable.
This will enable full tracebacks errors in the response, print request and responses, and set CORS in development mode.
???+ danger This might reveal sensitive information in your logs and relax CORS restrictions, use it sparingly.
It's best to use for local development only!
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
app = APIGatewayRestResolver(debug=True)
@app.get("/hello")
def get_hello_universe():
return {"message": "hello universe"}
def lambda_handler(event, context):
return app.resolve(event, context)
You can instruct API Gateway handler to use a custom serializer to best suit your needs, for example take into account Enums when serializing.
import json
from enum import Enum
from json import JSONEncoder
from typing import Dict
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
class CustomEncoder(JSONEncoder):
"""Your customer json encoder"""
def default(self, obj):
if isinstance(obj, Enum):
return obj.value
try:
iterable = iter(obj)
except TypeError:
pass
else:
return sorted(iterable)
return JSONEncoder.default(self, obj)
def custom_serializer(obj) -> str:
"""Your custom serializer function APIGatewayRestResolver will use"""
return json.dumps(obj, cls=CustomEncoder)
# Assigning your custom serializer
app = APIGatewayRestResolver(serializer=custom_serializer)
class Color(Enum):
RED = 1
BLUE = 2
@app.get("/colors")
def get_color() -> Dict:
return {
# Color.RED will be serialized to 1 as expected now
"color": Color.RED,
"variations": {"light", "dark"},
}
As you grow the number of routes a given Lambda function should handle, it is natural to split routes into separate files to ease maintenance - That's where the Router
feature is useful.
Let's assume you have app.py
as your Lambda function entrypoint and routes in users.py
, this is how you'd use the Router
feature.
=== "users.py"
We import **Router** instead of **APIGatewayRestResolver**; syntax wise is exactly the same.
```python hl_lines="5 8 12 15 21"
import itertools
from typing import Dict
from aws_lambda_powertools import Logger
from aws_lambda_powertools.event_handler.api_gateway import Router
logger = Logger(child=True)
router = Router()
USERS = {"user1": "details_here", "user2": "details_here", "user3": "details_here"}
@router.get("/users")
def get_users() -> Dict:
# /users?limit=1
pagination_limit = router.current_event.get_query_string_value(name="limit", default_value=10)
logger.info(f"Fetching the first {pagination_limit} users...")
ret = dict(itertools.islice(USERS.items(), int(pagination_limit)))
return {"items": [ret]}
@router.get("/users/<username>")
def get_user(username: str) -> Dict:
logger.info(f"Fetching username {username}")
return {"details": USERS.get(username, {})}
# many other related /users routing
```
=== "app.py"
We use `include_router` method and include all user routers registered in the `router` global object.
```python hl_lines="7 10-11"
from typing import Dict
from aws_lambda_powertools import Logger
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
from aws_lambda_powertools.utilities.typing import LambdaContext
import users
logger = Logger()
app = APIGatewayRestResolver()
app.include_router(users.router)
def lambda_handler(event: Dict, context: LambdaContext):
return app.resolve(event, context)
```
In the previous example, users.py
routes had a /users
prefix. This might grow over time and become repetitive.
When necessary, you can set a prefix when including a router object. This means you could remove /users
prefix in users.py
altogether.
=== "app.py"
```python hl_lines="9"
from typing import Dict
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
from aws_lambda_powertools.utilities.typing import LambdaContext
import users
app = APIGatewayRestResolver()
app.include_router(users.router, prefix="/users") # prefix '/users' to any route in `users.router`
def lambda_handler(event: Dict, context: LambdaContext):
return app.resolve(event, context)
```
=== "users.py"
```python hl_lines="11 15"
from typing import Dict
from aws_lambda_powertools import Logger
from aws_lambda_powertools.event_handler.api_gateway import Router
logger = Logger(child=True)
router = Router()
USERS = {"user1": "details", "user2": "details", "user3": "details"}
@router.get("/") # /users, when we set the prefix in app.py
def get_users() -> Dict:
...
@router.get("/<username>")
def get_user(username: str) -> Dict:
...
# many other related /users routing
```
This sample project contains a Users function with two distinct set of routes, /users
and /health
. The layout optimizes for code sharing, no custom build tooling, and it uses Lambda Layers to install Lambda Powertools.
=== "Project layout"
```python hl_lines="1 8 10 12-15"
.
├── Pipfile # project app & dev dependencies; poetry, pipenv, etc.
├── Pipfile.lock
├── README.md
├── src
│ ├── __init__.py
│ ├── requirements.txt # sam build detect it automatically due to CodeUri: src, e.g. pipenv lock -r > src/requirements.txt
│ └── users
│ ├── __init__.py
│ ├── main.py # this will be our users Lambda fn; it could be split in folders if we want separate fns same code base
│ └── routers # routers module
│ ├── __init__.py
│ ├── health.py # /users routes, e.g. from routers import users; users.router
│ └── users.py # /users routes, e.g. from .routers import users; users.router
├── template.yml # SAM template.yml, CodeUri: src, Handler: users.main.lambda_handler
└── tests
├── __init__.py
├── unit
│ ├── __init__.py
│ └── test_users.py # unit tests for the users router
│ └── test_health.py # unit tests for the health router
└── functional
├── __init__.py
├── conftest.py # pytest fixtures for the functional tests
└── test_main.py # functional tests for the main lambda handler
```
=== "template.yml"
```yaml hl_lines="22-23"
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: Example service with multiple routes
Globals:
Function:
Timeout: 10
MemorySize: 512
Runtime: python3.9
Tracing: Active
Architectures:
- x86_64
Environment:
Variables:
LOG_LEVEL: INFO
POWERTOOLS_LOGGER_LOG_EVENT: true
POWERTOOLS_METRICS_NAMESPACE: MyServerlessApplication
POWERTOOLS_SERVICE_NAME: users
Resources:
UsersService:
Type: AWS::Serverless::Function
Properties:
Handler: users.main.lambda_handler
CodeUri: src
Layers:
# Latest version: https://awslabs.github.io/aws-lambda-powertools-python/latest/#lambda-layer
- !Sub arn:aws:lambda:${AWS::Region}:017000801446:layer:AWSLambdaPowertoolsPython:4
Events:
ByUser:
Type: Api
Properties:
Path: /users/{name}
Method: GET
AllUsers:
Type: Api
Properties:
Path: /users
Method: GET
HealthCheck:
Type: Api
Properties:
Path: /status
Method: GET
Outputs:
UsersApiEndpoint:
Description: "API Gateway endpoint URL for Prod environment for Users Function"
Value: !Sub "https://${ServerlessRestApi}.execute-api.${AWS::Region}.amazonaws.com/Prod"
AllUsersURL:
Description: "URL to fetch all registered users"
Value: !Sub "https://${ServerlessRestApi}.execute-api.${AWS::Region}.amazonaws.com/Prod/users"
ByUserURL:
Description: "URL to retrieve details by user"
Value: !Sub "https://${ServerlessRestApi}.execute-api.${AWS::Region}.amazonaws.com/Prod/users/test"
UsersServiceFunctionArn:
Description: "Users Lambda Function ARN"
Value: !GetAtt UsersService.Arn
```
=== "src/users/main.py"
```python hl_lines="8 14-15"
from typing import Dict
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
from aws_lambda_powertools.logging.correlation_paths import APPLICATION_LOAD_BALANCER
from aws_lambda_powertools.utilities.typing import LambdaContext
from .routers import health, users
tracer = Tracer()
logger = Logger()
app = APIGatewayRestResolver()
app.include_router(health.router)
app.include_router(users.router)
@logger.inject_lambda_context(correlation_id_path=API_GATEWAY_REST)
@tracer.capture_lambda_handler
def lambda_handler(event: Dict, context: LambdaContext):
return app.resolve(event, context)
```
=== "src/users/routers/health.py"
```python hl_lines="4 6-7 10"
from typing import Dict
from aws_lambda_powertools import Logger
from aws_lambda_powertools.event_handler.api_gateway import Router
router = Router()
logger = Logger(child=True)
@router.get("/status")
def health() -> Dict:
logger.debug("Health check called")
return {"status": "OK"}
```
=== "tests/functional/test_users.py"
```python hl_lines="3"
import json
from src.users import main # follows namespace package from root
def test_lambda_handler(apigw_event, lambda_context):
ret = main.lambda_handler(apigw_event, lambda_context)
expected = json.dumps({"message": "hello universe"}, separators=(",", ":"))
assert ret["statusCode"] == 200
assert ret["body"] == expected
```
This utility is optimized for fast startup, minimal feature set, and to quickly on-board customers familiar with frameworks like Flask — it's not meant to be a fully fledged framework.
Event Handler naturally leads to a single Lambda function handling multiple routes for a given service, which can be eventually broken into multiple functions.
Both single (monolithic) and multiple functions (micro) offer different set of trade-offs worth knowing.
???+ tip TL;DR. Start with a monolithic function, add additional functions with new handlers, and possibly break into micro functions if necessary.
A monolithic function means that your final code artifact will be deployed to a single function. This is generally the best approach to start.
Benefits
- Code reuse. It's easier to reason about your service, modularize it and reuse code as it grows. Eventually, it can be turned into a standalone library.
- No custom tooling. Monolithic functions are treated just like normal Python packages; no upfront investment in tooling.
- Faster deployment and debugging. Whether you use all-at-once, linear, or canary deployments, a monolithic function is a single deployable unit. IDEs like PyCharm and VSCode have tooling to quickly profile, visualize, and step through debug any Python package.
Downsides
- Cold starts. Frequent deployments and/or high load can diminish the benefit of monolithic functions depending on your latency requirements, due to Lambda scaling model{target="_blank"}. Always load test to pragmatically balance between your customer experience and development cognitive load.
- Granular security permissions. The micro function approach enables you to use fine-grained permissions & access controls, separate external dependencies & code signing at the function level. Conversely, you could have multiple functions while duplicating the final code artifact in a monolithic approach.
- Regardless, least privilege can be applied to either approaches.
- Higher risk per deployment. A misconfiguration or invalid import can cause disruption if not caught earlier in automated testing. Multiple functions can mitigate misconfigurations but they would still share the same code artifact. You can further minimize risks with multiple environments in your CI/CD pipeline.
A micro function means that your final code artifact will be different to each function deployed. This is generally the approach to start if you're looking for fine-grain control and/or high load on certain parts of your service.
Benefits
- Granular scaling. A micro function can benefit from the Lambda scaling model{target="_blank"} to scale differently depending on each part of your application. Concurrency controls and provisioned concurrency can also be used at a granular level for capacity management.
- Discoverability. Micro functions are easier do visualize when using distributed tracing. Their high-level architectures can be self-explanatory, and complexity is highly visible — assuming each function is named to the business purpose it serves.
- Package size. An independent function can be significant smaller (KB vs MB) depending on external dependencies it require to perform its purpose. Conversely, a monolithic approach can benefit from Lambda Layers{target="_blank"} to optimize builds for external dependencies.
Downsides
- Upfront investment. Python ecosystem doesn't use a bundler — you need a custom build tooling to ensure each function only has what it needs and account for C bindings for runtime compatibility{target="_blank"}. Operations become more elaborate — you need to standardize tracing labels/annotations, structured logging, and metrics to pinpoint root causes.
- Engineering discipline is necessary for both approaches. Micro-function approach however requires further attention in consistency as the number of functions grow, just like any distributed system.
- Harder to share code. Shared code must be carefully evaluated to avoid unnecessary deployments when that changes. Equally, if shared code isn't a library, your development, building, deployment tooling need to accommodate the distinct layout.
- Slower safe deployments. Safely deploying multiple functions require coordination — AWS CodeDeploy deploys and verifies each function sequentially. This increases lead time substantially (minutes to hours) depending on the deployment strategy you choose. You can mitigate it by selectively enabling it in prod-like environments only, and where the risk profile is applicable.
- Automated testing, operational and security reviews are essential to stability in either approaches.
You can test your routes by passing a proxy event request where path
and httpMethod
.
=== "test_app.py"
```python hl_lines="18-24"
from dataclasses import dataclass
import pytest
import app
@pytest.fixture
def lambda_context():
@dataclass
class LambdaContext:
function_name: str = "test"
memory_limit_in_mb: int = 128
invoked_function_arn: str = "arn:aws:lambda:eu-west-1:809313241:function:test"
aws_request_id: str = "52fdfc07-2182-154f-163f-5f0f9a621d72"
return LambdaContext()
def test_lambda_handler(lambda_context):
minimal_event = {
"path": "/hello",
"httpMethod": "GET",
"requestContext": { # correlation ID
"requestId": "c6af9ac6-7b61-11e6-9a41-93e8deadbeef"
}
}
app.lambda_handler(minimal_event, lambda_context)
```
=== "app.py"
```python
from aws_lambda_powertools import Logger
from aws_lambda_powertools.logging import correlation_paths
from aws_lambda_powertools.event_handler import APIGatewayRestResolver
logger = Logger()
app = APIGatewayRestResolver() # API Gateway REST API (v1)
@app.get("/hello")
def get_hello_universe():
return {"message": "hello universe"}
# You can continue to use other utilities just as before
@logger.inject_lambda_context(correlation_id_path=correlation_paths.API_GATEWAY_REST)
def lambda_handler(event, context):
return app.resolve(event, context)
```
What's the difference between this utility and frameworks like Chalice?
Chalice is a full featured microframework that manages application and infrastructure. This utility, however, is largely focused on routing to reduce boilerplate and expects you to setup and manage infrastructure with your framework of choice.
That said, Chalice has native integration with Lambda Powertools{target="_blank"} if you're looking for a more opinionated and web framework feature set.
What happened to ApiGatewayResolver
?
It's been superseded by more explicit resolvers like APIGatewayRestResolver
, APIGatewayHttpResolver
, and ALBResolver
.
ApiGatewayResolver
handled multiple types of event resolvers for convenience via proxy_type
param. However,
it made it impossible for static checkers like Mypy and IDEs IntelliSense to know what properties a current_event
would have due to late bound resolution.
This provided a suboptimal experience for customers not being able to find all properties available besides common ones between API Gateway REST, HTTP, and ALB - while manually annotating app.current_event
would work it is not the experience we want to provide to customers.
ApiGatewayResolver
will be deprecated in v2 and have appropriate warnings as soon as we have a v2 draft.