chalice-nuclei-ai 1.29.2

Microframework - Nuclei FORK

This is a fork of aws/chalice which contains custom features/fixes:

• Added option to configure the Ephemeral Storage available to a function.

• Added option to configure Maximum Concurrency for an SQS trigger.

• Fixed middleware for non-route blueprint functions

There are a few caveats with blueprint middleware:

• Registering a middleware function on a Blueprint just registers it on the app. There is no support for registering a middleware function on JUST the blueprint.

• For the middleware to work, you must import the chalice app file AFTER instantiating the blueprint, this must be done AFTER the instantiation to prevent import cycles. See the below example.

#### FILE app.py ####
from chalice import Chalice
from chalicelib.a_blueprint import a_bp

def noop_middleware(event, get_response):
    print("Hello world from Middleware")
    return get_response(event)

app = Chalice(__name__)

# The ordering of these registrations is NOT important
app.register_blueprint(a_bp)
app.register_middleware(noop_middleware, 'all')

#### FILE chalicelib/a_blueprint.py ####
from chalice import Blueprint

a_bp = Blueprint(__name__)

import app # AFTER the instantiation of `a_bp`

@a_bp.schedule("rate(1 hour)")
def hourly(event):
    print("Hello World from a Blueprint")

Chalice is a framework for writing serverless apps in python. It allows you to quickly create and deploy applications that use AWS Lambda. It provides:

• A command line tool for creating, deploying, and managing your app

• A decorator based API for integrating with Amazon API Gateway, Amazon S3, Amazon SNS, Amazon SQS, and other AWS services.

• Automatic IAM policy generation

You can create Rest APIs:

from chalice import Chalice

app = Chalice(app_name="helloworld")

@app.route("/")
def index():
    return {"hello": "world"}

Tasks that run on a periodic basis:

from chalice import Chalice, Rate

app = Chalice(app_name="helloworld")

# Automatically runs every 5 minutes
@app.schedule(Rate(5, unit=Rate.MINUTES))
def periodic_task(event):
    return {"hello": "world"}

You can connect a lambda function to an S3 event:

from chalice import Chalice

app = Chalice(app_name="helloworld")

# Whenever an object is uploaded to 'mybucket'
# this lambda function will be invoked.

@app.on_s3_event(bucket='mybucket')
def handler(event):
    print("Object uploaded for bucket: %s, key: %s"
          % (event.bucket, event.key))

As well as an SQS queue:

from chalice import Chalice

app = Chalice(app_name="helloworld")

# Invoke this lambda function whenever a message
# is sent to the ``my-queue-name`` SQS queue.

@app.on_sqs_message(queue='my-queue-name')
def handler(event):
    for record in event:
        print("Message body: %s" % record.body)

And several other AWS resources.

Once you’ve written your code, you just run chalice deploy and Chalice takes care of deploying your app.

$ chalice deploy
...
https://endpoint/dev

$ curl https://endpoint/api
{"hello": "world"}

Up and running in less than 30 seconds. Give this project a try and share your feedback with us here on Github.

The documentation is available here.

Quickstart

In this tutorial, you’ll use the chalice command line utility to create and deploy a basic REST API. This quickstart uses Python 3.7, but AWS Chalice supports all versions of python supported by AWS Lambda, which includes python3.6, python3.7, python3.8, python3.9, python3.10. You can find the latest versions of python on the Python download page.

To install Chalice, we’ll first create and activate a virtual environment in python3.7:

$ python3 --version
Python 3.7.3
$ python3 -m venv venv37
$ . venv37/bin/activate

Next we’ll install Chalice using pip:

$ python3 -m pip install chalice-nuclei-ai

You can verify you have chalice installed by running:

$ chalice --help
Usage: chalice [OPTIONS] COMMAND [ARGS]...
...

Credentials

Before you can deploy an application, be sure you have credentials configured. If you have previously configured your machine to run boto3 (the AWS SDK for Python) or the AWS CLI then you can skip this section.

If this is your first time configuring credentials for AWS you can follow these steps to quickly get started:

$ mkdir ~/.aws
$ cat >> ~/.aws/config
[default]
aws_access_key_id=YOUR_ACCESS_KEY_HERE
aws_secret_access_key=YOUR_SECRET_ACCESS_KEY
region=YOUR_REGION (such as us-west-2, us-west-1, etc)

If you want more information on all the supported methods for configuring credentials, see the boto3 docs.

Creating Your Project

The next thing we’ll do is use the chalice command to create a new project:

$ chalice new-project helloworld

This will create a helloworld directory. Cd into this directory. You’ll see several files have been created for you:

$ cd helloworld
$ ls -la
drwxr-xr-x   .chalice
-rw-r--r--   app.py
-rw-r--r--   requirements.txt

You can ignore the .chalice directory for now, the two main files we’ll focus on is app.py and requirements.txt.

Let’s take a look at the app.py file:

from chalice import Chalice

app = Chalice(app_name='helloworld')


@app.route('/')
def index():
    return {'hello': 'world'}

The new-project command created a sample app that defines a single view, /, that when called will return the JSON body {"hello": "world"}.

Deploying

Let’s deploy this app. Make sure you’re in the helloworld directory and run chalice deploy:

$ chalice deploy
Creating deployment package.
Creating IAM role: helloworld-dev
Creating lambda function: helloworld-dev
Creating Rest API
Resources deployed:
  - Lambda ARN: arn:aws:lambda:us-west-2:12345:function:helloworld-dev
  - Rest API URL: https://abcd.execute-api.us-west-2.amazonaws.com/api/

You now have an API up and running using API Gateway and Lambda:

$ curl https://qxea58oupc.execute-api.us-west-2.amazonaws.com/api/
{"hello": "world"}

Try making a change to the returned dictionary from the index() function. You can then redeploy your changes by running chalice deploy.

Next Steps

You’ve now created your first app using chalice. You can make modifications to your app.py file and rerun chalice deploy to redeploy your changes.

At this point, there are several next steps you can take.

• Tutorials - Choose from among several guided tutorials that will give you step-by-step examples of various features of Chalice.

• Topics - Deep dive into documentation on specific areas of Chalice. This contains more detailed documentation than the tutorials.

• API Reference - Low level reference documentation on all the classes and methods that are part of the public API of Chalice.

If you’re done experimenting with Chalice and you’d like to cleanup, you can use the chalice delete command, and Chalice will delete all the resources it created when running the chalice deploy command.

$ chalice delete
Deleting Rest API: abcd4kwyl4
Deleting function aws:arn:lambda:region:123456789:helloworld-dev
Deleting IAM Role helloworld-dev

Feedback

We’d also love to hear from you. Please create any Github issues for additional features you’d like to see over at https://github.com/aws/chalice/issues. You can also chat with us on gitter: https://gitter.im/awslabs/chalice