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Hyped Serve Extension

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Serve hyped data flows as REST APIs

Installation

You can install the add-on directly from PyPI using pip:

pip install hyped-extensions-serve

Getting Started

Hyped serve leverages the power of FastAPI to create a robust serving environment.

To get started, simply define your data pipeline and its expected input features in a Python script, and then serve it using hyped-extensions-serve.

Here's a basic example:

# app.py
from hyped import DataFlow
from hyped.typing import Mapping, Int
from hyped.extensions.serve import HypedAPI

# Define your input schema
class Inputs(Mapping):
    x: Int

# Define your data flow
flow = DataFlow[Inputs]()
flow = flow.build(collect={"y": flow.source["x"] * 2})

# Create the app to be served
app = HypedAPI().serve_flow(flow, prefix="/")

Once you've defined your app, you can serve it using uvicorn:

uvicorn app:app --host 0.0.0.0 --port 80

This will start the server, allowing you to interact with your data pipeline via HTTP requests.

Endpoints

The Hyped Serve API provides the following endpoints for interacting with your data pipeline:

Endpoint Method Description
/health GET Simple health check always returns "ok" and code 200.
/readiness GET Simple readiness check always returns "ok" and code 200.
<prefix>/readiness GET Readiness check to determine if the flow is ready to receive requests.
<prefix>/apply POST Apply the data flow to a single example. Expects a single example in JSON format.
<prefix>/batch POST Apply the data flow to a batch of data. Expects a list of examples.

Additionally, a Swagger UI API documentation is available at /docs.

Serving multiple Data Pipes

The serving environment also supports serving multiple data pipes simultaneously. You can configure this by providing multiple data pipes and their respective features.

# app.py

app = (
    HypedAPI()
    .serve_flow(flowA, prefix="/A")
    .serve_flow(flowB, prefix="/B")
)

This example demonstrates serving two different data pipes (pipe_one and pipe_two) with their corresponding features, each accessible via different prefixes (/one and /two).

Running Tests

Hyped Serve includes a suite of tests to ensure its functionality. You can run these tests using pytest:

pytest tests

Ensure that you have pytest installed in your environment. You can install it via pip:

pip install pytest

Running the tests will execute various test cases to validate the behavior of Hyped Serve.

License

tbd

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Credits

Author: open-hyped

Requires

Python >=3.10

Provides Extra

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