Top Related Projects
⚡ Serverless Framework – Effortlessly build apps that auto-scale, incur zero costs when idle, and require minimal maintenance using AWS Lambda and other managed cloud services.
Serverless Python
Pulumi - Infrastructure as Code in any programming language 🚀
💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
FastAPI framework, high performance, easy to learn, fast to code, ready for production
Quick Overview
Chalice is a Python serverless microframework for AWS. It allows you to quickly create and deploy serverless applications using AWS Lambda and Amazon API Gateway, with minimal configuration and boilerplate code. Chalice simplifies the process of building serverless APIs and functions on AWS.
Pros
- Easy to use and quick to get started
- Seamless integration with AWS services
- Automatic handling of API Gateway configuration
- Built-in support for common patterns like CORS and authentication
Cons
- Limited to AWS ecosystem
- May not be suitable for complex applications with specific requirements
- Less flexibility compared to using AWS services directly
- Learning curve for developers new to serverless architecture
Code Examples
- Creating a simple API endpoint:
from chalice import Chalice
app = Chalice(app_name='hello-world')
@app.route('/')
def index():
return {'hello': 'world'}
- Handling URL parameters:
@app.route('/users/{user_id}')
def get_user(user_id):
return {'user_id': user_id}
- Using AWS services with Chalice:
from chalice import Chalice
import boto3
app = Chalice(app_name='s3-example')
s3 = boto3.client('s3')
@app.route('/list-buckets')
def list_buckets():
response = s3.list_buckets()
return {'buckets': [b['Name'] for b in response['Buckets']]}
Getting Started
- Install Chalice:
pip install chalice
- Create a new Chalice project:
chalice new-project hello-world
cd hello-world
- Deploy the application:
chalice deploy
This will create and deploy a simple Chalice application to AWS Lambda and API Gateway. You can then modify the app.py
file to add your own routes and functionality.
Competitor Comparisons
⚡ Serverless Framework – Effortlessly build apps that auto-scale, incur zero costs when idle, and require minimal maintenance using AWS Lambda and other managed cloud services.
Pros of Serverless
- Multi-cloud support (AWS, Azure, Google Cloud, etc.)
- Larger ecosystem with more plugins and integrations
- More flexible and customizable for complex architectures
Cons of Serverless
- Steeper learning curve due to more configuration options
- Potentially slower deployment times for large projects
- Requires more setup for simple AWS Lambda functions
Code Comparison
Serverless:
service: my-service
provider:
name: aws
runtime: nodejs14.x
functions:
hello:
handler: handler.hello
Chalice:
from chalice import Chalice
app = Chalice(app_name='my-app')
@app.route('/')
def hello():
return {'hello': 'world'}
Summary
Serverless offers a more versatile, multi-cloud solution with extensive customization options, making it suitable for complex projects across various cloud providers. However, this comes at the cost of a steeper learning curve and potentially slower deployments.
Chalice, being AWS-specific, provides a simpler, more streamlined experience for AWS Lambda development, especially for Python developers. It offers faster setup and deployment for basic AWS serverless applications but lacks the flexibility and ecosystem of Serverless.
Choose Serverless for multi-cloud, complex architectures, or when extensive customization is needed. Opt for Chalice when focusing solely on AWS and prioritizing simplicity in Python-based Lambda function development.
Serverless Python
Pros of Zappa
- Supports multiple Python web frameworks (Flask, Django, etc.)
- Offers more advanced features like custom domains and SSL certificates
- Provides built-in support for scheduled tasks and cron jobs
Cons of Zappa
- Steeper learning curve due to more complex configuration options
- May require more manual setup for certain AWS resources
- Less integrated with AWS-specific services compared to Chalice
Code Comparison
Zappa deployment configuration:
{
"dev": {
"app_function": "my_app.app",
"aws_region": "us-east-1",
"profile_name": "default",
"project_name": "my-project",
"runtime": "python3.8"
}
}
Chalice deployment configuration:
from chalice import Chalice
app = Chalice(app_name='my-project')
@app.route('/')
def index():
return {'hello': 'world'}
Both Zappa and Chalice aim to simplify serverless deployments on AWS, but they have different approaches. Zappa offers more flexibility and supports various web frameworks, while Chalice provides a more streamlined experience with tighter AWS integration. The choice between them depends on your specific project requirements and familiarity with AWS services.
Pulumi - Infrastructure as Code in any programming language 🚀
Pros of Pulumi
- Multi-cloud support, allowing deployment to various cloud providers
- Supports multiple programming languages (Python, JavaScript, Go, etc.)
- More flexible and powerful for complex infrastructure setups
Cons of Pulumi
- Steeper learning curve, especially for those new to infrastructure as code
- Requires more setup and configuration compared to Chalice's simplicity
- Can be overkill for simple serverless applications
Code Comparison
Chalice (Python):
from chalice import Chalice
app = Chalice(app_name='helloworld')
@app.route('/')
def index():
return {'hello': 'world'}
Pulumi (Python):
import pulumi
from pulumi_aws import lambda_
def handler(event, context):
return {'statusCode': 200, 'body': 'Hello, World!'}
lambda_.Function('my-lambda',
code=pulumi.AssetArchive({'.': pulumi.FileArchive('./')}),
handler='index.handler',
runtime='python3.8',
role='arn:aws:iam::account-id:role/lambda-role')
Summary
Chalice is more focused on AWS serverless applications and offers a simpler, more opinionated approach. Pulumi provides broader cloud support and more flexibility but with increased complexity. Choose based on your project requirements and team expertise.
💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
Pros of LocalStack
- Emulates a wide range of AWS services locally, allowing for comprehensive testing without incurring cloud costs
- Supports multiple programming languages and frameworks, not limited to Python
- Provides a more realistic AWS environment simulation, including networking and IAM features
Cons of LocalStack
- Steeper learning curve and more complex setup compared to Chalice's simplicity
- May not always perfectly mirror AWS behavior, leading to potential discrepancies
- Requires more system resources to run the full suite of emulated services
Code Comparison
Chalice (Python):
from chalice import Chalice
app = Chalice(app_name='helloworld')
@app.route('/')
def index():
return {'hello': 'world'}
LocalStack (AWS CLI equivalent):
aws --endpoint-url=http://localhost:4566 s3 mb s3://my-bucket
aws --endpoint-url=http://localhost:4566 s3 cp file.txt s3://my-bucket/
aws --endpoint-url=http://localhost:4566 lambda create-function --function-name my-func --runtime python3.8 --handler lambda.handler --zip-file fileb://lambda.zip
Note: LocalStack doesn't have its own SDK; it uses existing AWS SDKs or CLI commands with a different endpoint URL.
FastAPI framework, high performance, easy to learn, fast to code, ready for production
Pros of FastAPI
- Faster performance due to asynchronous support and Starlette framework
- More comprehensive documentation and larger community support
- Built-in API documentation with Swagger UI and ReDoc
Cons of FastAPI
- Requires more setup and configuration for AWS deployment
- Less integrated with AWS services compared to Chalice
- Steeper learning curve for developers new to asynchronous programming
Code Comparison
FastAPI:
from fastapi import FastAPI
app = FastAPI()
@app.get("/")
async def root():
return {"message": "Hello World"}
Chalice:
from chalice import Chalice
app = Chalice(app_name='helloworld')
@app.route('/')
def index():
return {'hello': 'world'}
Summary
FastAPI is a modern, fast web framework for building APIs with Python, offering high performance and automatic API documentation. It's more versatile but requires additional setup for AWS deployment. Chalice, on the other hand, is specifically designed for AWS Lambda and API Gateway, providing seamless integration with AWS services but with less flexibility for non-AWS environments. The choice between the two depends on your specific use case and deployment requirements.
Convert designs to code with AI
Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual CopilotREADME
=========== AWS Chalice
.. image:: https://badges.gitter.im/awslabs/chalice.svg :target: https://gitter.im/awslabs/chalice?utm_source=badge&utm_medium=badge :alt: Gitter .. image:: https://readthedocs.org/projects/chalice/badge/?version=latest :target: http://aws.github.io/chalice/?badge=latest :alt: Documentation Status
.. image:: https://aws.github.io/chalice/_images/chalice-logo-whitespace.png :target: https://aws.github.io/chalice/ :alt: Chalice Logo
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:
.. code-block:: python
from chalice import Chalice
app = Chalice(app_name="helloworld")
@app.route("/")
def index():
return {"hello": "world"}
Tasks that run on a periodic basis:
.. code-block:: python
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:
.. code-block:: python
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:
.. code-block:: python
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 <http://aws.github.io/chalice/>
__.
Quickstart
.. quick-start-begin
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 Python 3.7 through python 3.12.
You can find the latest versions of python on the
Python download page <https://www.python.org/downloads/>
_.
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
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 <http://boto3.readthedocs.io/en/latest/guide/configuration.html>
__.
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:
.. code-block:: python
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
.
.. quick-start-end
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 <https://aws.github.io/chalice/tutorials/index.html>
__- Choose from among several guided tutorials that will give you step-by-step examples of various features of Chalice.
Topics <https://aws.github.io/chalice/topics/index.html>
__ - Deep dive into documentation on specific areas of Chalice. This contains more detailed documentation than the tutorials.API Reference <https://aws.github.io/chalice/api.html>
__ - 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
Top Related Projects
⚡ Serverless Framework – Effortlessly build apps that auto-scale, incur zero costs when idle, and require minimal maintenance using AWS Lambda and other managed cloud services.
Serverless Python
Pulumi - Infrastructure as Code in any programming language 🚀
💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
FastAPI framework, high performance, easy to learn, fast to code, ready for production
Convert designs to code with AI
Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual Copilot