Stateful Functions is an Apache Flink library that simplifies building distributed stateful applications. It's based on functions with persistent state that can interact dynamically with strong consistency guarantees.
Stateful Functions makes it possible to combine a powerful approach to state and composition with the elasticity, rapid scaling/scale-to-zero and rolling upgrade capabilities of FaaS implementations like AWS Lambda and modern resource orchestration frameworks like Kubernetes. With these features, it addresses two of the most cited shortcomings of many FaaS setups today: consistent state and efficient messaging between functions.
This README is meant as a brief walkthrough on the StateFun Python SDK and how to set things up to get yourself started with Stateful Functions in Python.
For a fully detailed documentation, please visit the official docs.
For code examples, please take a look at the examples.
The JVM-based Stateful Functions implementation has a RequestReply extension (a protocol and an implementation) that allows calling into any HTTP endpoint that implements that protocol. Although it is possible to implement this protocol independently, this is a minimal library for the Python programing language that:
Allows users to define and declare their functions in a convenient way.
Dispatches an invocation request sent from the JVM to the appropriate function previously declared.
from statefun import StatefulFunctions
functions = StatefulFunctions()
@functions.bind("demo/greeter")
def greet(context, message: LoginEvent):
print("Hey " + message.user_name)
This code declares a function with a FunctionType("demo", "greeter") and binds the greet Python instance to it.
from statefun import RequestReplyHandler handler = RequestReplyHandler(functions)
For example, using Flask:
@app.route('/statefun', methods=['POST'])
def handle():
response_data = handler(request.data)
response = make_response(response_data)
response.headers.set('Content-Type', 'application/octet-stream')
return response
if __name__ == "__main__":
app.run()
This creates an HTTP server that accepts requests from the Stateful Functions cluster and dispatches it to the handler.
The remaining step would be to declare this function type in a module.yaml
functions:
- function:
meta:
kind: http
type: demo/greeter
spec:
endpoint: http://<end point url>/statefun
states:
- foo
- bar
- baz
The request reply protocol requires that the state names would be registered in the module YAML file under the states section (see the example above). The state values could be absent (None or a google.protobuf.Any) and they can be generally obtained via the context parameter:
@functions.bind("demo/greeter")
def greet(context, message: LoginEvent):
session = context['session']
if not session:
session = start_session(message)
context['session'] = session
...
python3 -m venv venv source venv/bin/activate
pip3 install .
python3 -m unittest tests
There are multiple ways to enhance the Stateful Functions API for different types of applications; the runtime and operations will also evolve with the developments in Apache Flink.
You can learn more about how to contribute in the Apache Flink website. For code contributions, please read carefully the Contributing Code section and check the Stateful Functions component in Jira for an overview of ongoing community work.
The code in this repository is licensed under the Apache Software License 2.