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ray/python/ray/serve/examples/echo_full.py
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Python

"""
Full example of ray.serve module
"""
import time
import requests
import ray
import ray.serve as serve
from ray.serve.utils import pformat_color_json
# initialize ray serve system.
# blocking=True will wait for HTTP server to be ready to serve request.
serve.init(blocking=True)
# an endpoint is associated with an http URL.
serve.create_endpoint("my_endpoint", "/echo")
# a backend can be a function or class.
# it can be made to be invoked from web as well as python.
def echo_v1(flask_request, response="hello from python!"):
if serve.context.web:
response = flask_request.url
return response
serve.create_backend(echo_v1, "echo:v1")
backend_config_v1 = serve.get_backend_config("echo:v1")
# We can link an endpoint to a backend, the means all the traffic
# goes to my_endpoint will now goes to echo:v1 backend.
serve.link("my_endpoint", "echo:v1")
print(requests.get("http://127.0.0.1:8000/echo", timeout=0.5).text)
# The service will be reachable from http
print(ray.get(serve.get_handle("my_endpoint").remote(response="hello")))
# as well as within the ray system.
# We can also add a new backend and split the traffic.
def echo_v2(flask_request):
# magic, only from web.
return "something new"
serve.create_backend(echo_v2, "echo:v2")
backend_config_v2 = serve.get_backend_config("echo:v2")
# The two backend will now split the traffic 50%-50%.
serve.split("my_endpoint", {"echo:v1": 0.5, "echo:v2": 0.5})
# Observe requests are now split between two backends.
for _ in range(10):
print(requests.get("http://127.0.0.1:8000/echo").text)
time.sleep(0.5)
# You can also change number of replicas
# for each backend independently.
backend_config_v1.num_replicas = 2
serve.set_backend_config("echo:v1", backend_config_v1)
backend_config_v2.num_replicas = 2
serve.set_backend_config("echo:v2", backend_config_v2)
# As well as retrieving relevant system metrics
print(pformat_color_json(serve.stat()))