Is it possible to return a generator in an Azure Function? I am trying to stream data while it is being created. I tried the following with no luck:
def main(req: func.HttpRequest) -> func.HttpResponse:
def gen():
for i in range(10):
yield i
return func.HttpResponse(gen(), mimetype='text/html')
The above yielded TypeError: reponse is expected to be either of str, bytes, or bytearray, got generator. Is it possible to do something like this in an Azure Function? I don't necessarily require it to be in Python, but it would be preferred.
I guess this should be possible, May be have a look at this example, you might need to convert the response to a Object/Disctionary.
If you want to return the number in the generator suppose you could return the list(gen()). It will act like the below pic.
I return the return func.HttpResponse(str(list(gen())),status_code=200), hope this is what you want, if you still have other problem please feel free to let me know.
If your purpose is use flask to return a generator you could refer to the below code.
import logging
import azure.functions as func
import json, os
from flask import stream_with_context, request, Response
from flask.app import Flask
app = Flask(__name__)
#app.route('/')
def hello_world():
def generate():
yield 'Hello '
yield 'world11'
return Response(stream_with_context(generate()))
def main(req: func.HttpRequest) -> func.HttpResponse:
logging.info('Python HTTP trigger function processed a request.')
uri=req.params['uri']
with app.test_client() as c:
doAction = {
"GET": c.get(uri).data,
"POST": c.post(uri).data
}
resp = doAction.get(req.method).decode()
return func.HttpResponse(resp, mimetype='text/html')
Here is the test result pic.
Related
We are writing a web service using Python FastAPI that is going to be hosted in Kubernetes. For auditing purposes, we need to save the raw JSON body of the request/response for specific routes. The body size of both request and response JSON is about 1MB, and preferably, this should not impact the response time.
How can we do that?
Option 1 - Using Middleware
You could use a Middleware. A middleware takes each request that comes to your application, and hence, allows you to handle the request before it is processed by any specific endpoint, as well as the response, before it is returned to the client. To create a middleware, you use the decorator #app.middleware("http") on top of a function, as shown below. As you need to consume the request body from the stream inside the middleware—using either request.body() or request.stream(), as shown in this answer (behind the scenes, the former method actually calls the latter, see here)—then it won't be available when you later pass the request to the corresponding endpoint. Thus, you can follow the approach described in this post to make the request body available down the line (i.e., using the set_body function below). As for the response body, you can use the same approach as described in this answer to consume the body and then return the response to the client. Either option described in the aforementioned linked answer would work; the below, however, uses Option 2, which stores the body in a bytes object and returns a custom Response directly (along with the status_code, headers and media_type of the original response).
To log the data, you could use a BackgroundTask, as described in this answer and this answer. A BackgroundTask will run only once the response has been sent (see Starlette documentation as well); thus, the client won't have to be waiting for the logging to complete before receiving the response (and hence, the response time won't be noticeably impacted).
Note
If you had a streaming request or response with a body that wouldn't fit into your server's RAM (for example, imagine a body of 100GB on a machine running 8GB RAM), it would become problematic, as you are storing the data to RAM, which wouldn't have enough space available to accommodate the accumulated data. Also, in case of a large response (e.g., a large FileResponse or StreamingResponse), you may be faced with Timeout errors on client side (or on reverse proxy side, if you are using one), as you would not be able to respond back to the client, until you have read the entire response body (as you are looping over response.body_iterator). You mentioned that "the body size of both request and response JSON is about 1MB"; hence, that should normally be fine (however, it is always a good practice to consider beforehand matters, such as how many requests your API is expected to be serving concurrently, what other applications might be using the RAM, etc., in order to rule whether this is an issue or not). If you needed to, you could limit the number of requests to your API endpoints using, for example, SlowAPI (as shown in this answer).
Limiting the usage of the middleware to specific routes only
You could limit the usage of the middleware to specific endpoints by:
checking the request.url.path inside the middleware against a
pre-defined list of routes for which you would like to log the
request and response, as described in this answer (see
"Update" section),
or using a sub application, as demonstrated in this
answer
or using a custom APIRoute class, as demonstrated in Option 2
below.
Working Example
from fastapi import FastAPI, APIRouter, Response, Request
from starlette.background import BackgroundTask
from fastapi.routing import APIRoute
from starlette.types import Message
from typing import Dict, Any
import logging
app = FastAPI()
logging.basicConfig(filename='info.log', level=logging.DEBUG)
def log_info(req_body, res_body):
logging.info(req_body)
logging.info(res_body)
async def set_body(request: Request, body: bytes):
async def receive() -> Message:
return {'type': 'http.request', 'body': body}
request._receive = receive
#app.middleware('http')
async def some_middleware(request: Request, call_next):
req_body = await request.body()
await set_body(request, req_body)
response = await call_next(request)
res_body = b''
async for chunk in response.body_iterator:
res_body += chunk
task = BackgroundTask(log_info, req_body, res_body)
return Response(content=res_body, status_code=response.status_code,
headers=dict(response.headers), media_type=response.media_type, background=task)
#app.post('/')
def main(payload: Dict[Any, Any]):
return payload
In case you would like to perform some validation on the request body—for example, ensruing that the request body size is not exceeding a certain value—instead of using request.body(), you can process the body one chunk at a time using the .stream() method, as shown below (similar to this answer).
#app.middleware('http')
async def some_middleware(request: Request, call_next):
req_body = b''
async for chunk in request.stream():
req_body += chunk
...
Option 2 - Using custom APIRoute class
You can alternatively use a custom APIRoute class—similar to here and here—which, among other things, would allow you to manipulate the request body before it is processed by your application, as well as the response body before it is returned to the client. This option also allows you to limit the usage of this class to the routes you wish, as only the endpoints under the APIRouter (i.e., router in the example below) will use the custom APIRoute class .
It should be noted that the same comments mentioned in Option 1 above, under the "Note" section, apply to this option as well. For example, if your API returns a StreamingResponse—such as in /video route of the example below, which is streaming a video file from an online source (public videos to test this can be found here, and you can even use a longer video than the one used below to see the effect more clearly)—you may come across issues on server side, if your server's RAM can't handle it, as well as delays on client side (and reverse proxy server, if using one) due to the whole (streaming) response being read and stored in RAM, before it is returned to the client (as explained earlier). In such cases, you could exclude such endpoints that return a StreamingResponse from the custom APIRoute class and limit its usage only to the desired routes—especially, if it is a large video file, or even live video that wouldn't likely make much sense to have it stored in the logs—simply by not using the #<name_of_router> decorator (i.e., #router in the example below) for such endpoints, but rather using the #<name_of_app> decorator (i.e., #app in the example below), or some other APIRouter or sub application.
Working Example
from fastapi import FastAPI, APIRouter, Response, Request
from starlette.background import BackgroundTask
from starlette.responses import StreamingResponse
from fastapi.routing import APIRoute
from starlette.types import Message
from typing import Callable, Dict, Any
import logging
import httpx
def log_info(req_body, res_body):
logging.info(req_body)
logging.info(res_body)
class LoggingRoute(APIRoute):
def get_route_handler(self) -> Callable:
original_route_handler = super().get_route_handler()
async def custom_route_handler(request: Request) -> Response:
req_body = await request.body()
response = await original_route_handler(request)
if isinstance(response, StreamingResponse):
res_body = b''
async for item in response.body_iterator:
res_body += item
task = BackgroundTask(log_info, req_body, res_body)
return Response(content=res_body, status_code=response.status_code,
headers=dict(response.headers), media_type=response.media_type, background=task)
else:
res_body = response.body
response.background = BackgroundTask(log_info, req_body, res_body)
return response
return custom_route_handler
app = FastAPI()
router = APIRouter(route_class=LoggingRoute)
logging.basicConfig(filename='info.log', level=logging.DEBUG)
#router.post('/')
def main(payload: Dict[Any, Any]):
return payload
#router.get('/video')
def get_video():
url = 'https://storage.googleapis.com/gtv-videos-bucket/sample/ForBiggerBlazes.mp4'
def gen():
with httpx.stream('GET', url) as r:
for chunk in r.iter_raw():
yield chunk
return StreamingResponse(gen(), media_type='video/mp4')
app.include_router(router)
You may try to customize APIRouter like in FastAPI official documentation:
import time
from typing import Callable
from fastapi import APIRouter, FastAPI, Request, Response
from fastapi.routing import APIRoute
class TimedRoute(APIRoute):
def get_route_handler(self) -> Callable:
original_route_handler = super().get_route_handler()
async def custom_route_handler(request: Request) -> Response:
before = time.time()
response: Response = await original_route_handler(request)
duration = time.time() - before
response.headers["X-Response-Time"] = str(duration)
print(f"route duration: {duration}")
print(f"route response: {response}")
print(f"route response headers: {response.headers}")
return response
return custom_route_handler
app = FastAPI()
router = APIRouter(route_class=TimedRoute)
#app.get("/")
async def not_timed():
return {"message": "Not timed"}
#router.get("/timed")
async def timed():
return {"message": "It's the time of my life"}
app.include_router(router)
As the other answers did not work for me and I searched quite extensively on stackoverflow to fix this problem, I will show my solution below.
The main issue is that when using the request body or response body many of the approaches/solutions offered online do simply not work as the request/response body is consumed in reading it from the stream.
To solve this issue I adapted an approach that basically reconstructs the request and response after reading them. This is heavily based on the comment by user 'kovalevvlad' on https://github.com/encode/starlette/issues/495.
Custom middleware is created that is later added to the app to log all requests and responses. Note that you need some kind of logger to store your logs.
from json import JSONDecodeError
import json
import logging
from typing import Callable, Awaitable, Tuple, Dict, List
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.requests import Request
from starlette.responses import Response, StreamingResponse
from starlette.types import Scope, Message
# Set up your custom logger here
logger = ""
class RequestWithBody(Request):
"""Creation of new request with body"""
def __init__(self, scope: Scope, body: bytes) -> None:
super().__init__(scope, self._receive)
self._body = body
self._body_returned = False
async def _receive(self) -> Message:
if self._body_returned:
return {"type": "http.disconnect"}
else:
self._body_returned = True
return {"type": "http.request", "body": self._body, "more_body": False}
class CustomLoggingMiddleware(BaseHTTPMiddleware):
"""
Use of custom middleware since reading the request body and the response consumes the bytestream.
Hence this approach to basically generate a new request/response when we read the attributes for logging.
"""
async def dispatch( # type: ignore
self, request: Request, call_next: Callable[[Request], Awaitable[StreamingResponse]]
) -> Response:
# Store request body in a variable and generate new request as it is consumed.
request_body_bytes = await request.body()
request_with_body = RequestWithBody(request.scope, request_body_bytes)
# Store response body in a variable and generate new response as it is consumed.
response = await call_next(request_with_body)
response_content_bytes, response_headers, response_status = await self._get_response_params(response)
# Logging
# If there is no request body handle exception, otherwise convert bytes to JSON.
try:
req_body = json.loads(request_body_bytes)
except JSONDecodeError:
req_body = ""
# Logging of relevant variables.
logger.info(
f"{request.method} request to {request.url} metadata\n"
f"\tStatus_code: {response.status_code}\n"
f"\tRequest_Body: {req_body}\n"
)
# Finally, return the newly instantiated response values
return Response(response_content_bytes, response_status, response_headers)
async def _get_response_params(self, response: StreamingResponse) -> Tuple[bytes, Dict[str, str], int]:
"""Getting the response parameters of a response and create a new response."""
response_byte_chunks: List[bytes] = []
response_status: List[int] = []
response_headers: List[Dict[str, str]] = []
async def send(message: Message) -> None:
if message["type"] == "http.response.start":
response_status.append(message["status"])
response_headers.append({k.decode("utf8"): v.decode("utf8") for k, v in message["headers"]})
else:
response_byte_chunks.append(message["body"])
await response.stream_response(send)
content = b"".join(response_byte_chunks)
return content, response_headers[0], response_status[0]
We are writing a web service using Python FastAPI that is going to be hosted in Kubernetes. For auditing purposes, we need to save the raw JSON body of the request/response for specific routes. The body size of both request and response JSON is about 1MB, and preferably, this should not impact the response time.
How can we do that?
Option 1 - Using Middleware
You could use a Middleware. A middleware takes each request that comes to your application, and hence, allows you to handle the request before it is processed by any specific endpoint, as well as the response, before it is returned to the client. To create a middleware, you use the decorator #app.middleware("http") on top of a function, as shown below. As you need to consume the request body from the stream inside the middleware—using either request.body() or request.stream(), as shown in this answer (behind the scenes, the former method actually calls the latter, see here)—then it won't be available when you later pass the request to the corresponding endpoint. Thus, you can follow the approach described in this post to make the request body available down the line (i.e., using the set_body function below). As for the response body, you can use the same approach as described in this answer to consume the body and then return the response to the client. Either option described in the aforementioned linked answer would work; the below, however, uses Option 2, which stores the body in a bytes object and returns a custom Response directly (along with the status_code, headers and media_type of the original response).
To log the data, you could use a BackgroundTask, as described in this answer and this answer. A BackgroundTask will run only once the response has been sent (see Starlette documentation as well); thus, the client won't have to be waiting for the logging to complete before receiving the response (and hence, the response time won't be noticeably impacted).
Note
If you had a streaming request or response with a body that wouldn't fit into your server's RAM (for example, imagine a body of 100GB on a machine running 8GB RAM), it would become problematic, as you are storing the data to RAM, which wouldn't have enough space available to accommodate the accumulated data. Also, in case of a large response (e.g., a large FileResponse or StreamingResponse), you may be faced with Timeout errors on client side (or on reverse proxy side, if you are using one), as you would not be able to respond back to the client, until you have read the entire response body (as you are looping over response.body_iterator). You mentioned that "the body size of both request and response JSON is about 1MB"; hence, that should normally be fine (however, it is always a good practice to consider beforehand matters, such as how many requests your API is expected to be serving concurrently, what other applications might be using the RAM, etc., in order to rule whether this is an issue or not). If you needed to, you could limit the number of requests to your API endpoints using, for example, SlowAPI (as shown in this answer).
Limiting the usage of the middleware to specific routes only
You could limit the usage of the middleware to specific endpoints by:
checking the request.url.path inside the middleware against a
pre-defined list of routes for which you would like to log the
request and response, as described in this answer (see
"Update" section),
or using a sub application, as demonstrated in this
answer
or using a custom APIRoute class, as demonstrated in Option 2
below.
Working Example
from fastapi import FastAPI, APIRouter, Response, Request
from starlette.background import BackgroundTask
from fastapi.routing import APIRoute
from starlette.types import Message
from typing import Dict, Any
import logging
app = FastAPI()
logging.basicConfig(filename='info.log', level=logging.DEBUG)
def log_info(req_body, res_body):
logging.info(req_body)
logging.info(res_body)
async def set_body(request: Request, body: bytes):
async def receive() -> Message:
return {'type': 'http.request', 'body': body}
request._receive = receive
#app.middleware('http')
async def some_middleware(request: Request, call_next):
req_body = await request.body()
await set_body(request, req_body)
response = await call_next(request)
res_body = b''
async for chunk in response.body_iterator:
res_body += chunk
task = BackgroundTask(log_info, req_body, res_body)
return Response(content=res_body, status_code=response.status_code,
headers=dict(response.headers), media_type=response.media_type, background=task)
#app.post('/')
def main(payload: Dict[Any, Any]):
return payload
In case you would like to perform some validation on the request body—for example, ensruing that the request body size is not exceeding a certain value—instead of using request.body(), you can process the body one chunk at a time using the .stream() method, as shown below (similar to this answer).
#app.middleware('http')
async def some_middleware(request: Request, call_next):
req_body = b''
async for chunk in request.stream():
req_body += chunk
...
Option 2 - Using custom APIRoute class
You can alternatively use a custom APIRoute class—similar to here and here—which, among other things, would allow you to manipulate the request body before it is processed by your application, as well as the response body before it is returned to the client. This option also allows you to limit the usage of this class to the routes you wish, as only the endpoints under the APIRouter (i.e., router in the example below) will use the custom APIRoute class .
It should be noted that the same comments mentioned in Option 1 above, under the "Note" section, apply to this option as well. For example, if your API returns a StreamingResponse—such as in /video route of the example below, which is streaming a video file from an online source (public videos to test this can be found here, and you can even use a longer video than the one used below to see the effect more clearly)—you may come across issues on server side, if your server's RAM can't handle it, as well as delays on client side (and reverse proxy server, if using one) due to the whole (streaming) response being read and stored in RAM, before it is returned to the client (as explained earlier). In such cases, you could exclude such endpoints that return a StreamingResponse from the custom APIRoute class and limit its usage only to the desired routes—especially, if it is a large video file, or even live video that wouldn't likely make much sense to have it stored in the logs—simply by not using the #<name_of_router> decorator (i.e., #router in the example below) for such endpoints, but rather using the #<name_of_app> decorator (i.e., #app in the example below), or some other APIRouter or sub application.
Working Example
from fastapi import FastAPI, APIRouter, Response, Request
from starlette.background import BackgroundTask
from starlette.responses import StreamingResponse
from fastapi.routing import APIRoute
from starlette.types import Message
from typing import Callable, Dict, Any
import logging
import httpx
def log_info(req_body, res_body):
logging.info(req_body)
logging.info(res_body)
class LoggingRoute(APIRoute):
def get_route_handler(self) -> Callable:
original_route_handler = super().get_route_handler()
async def custom_route_handler(request: Request) -> Response:
req_body = await request.body()
response = await original_route_handler(request)
if isinstance(response, StreamingResponse):
res_body = b''
async for item in response.body_iterator:
res_body += item
task = BackgroundTask(log_info, req_body, res_body)
return Response(content=res_body, status_code=response.status_code,
headers=dict(response.headers), media_type=response.media_type, background=task)
else:
res_body = response.body
response.background = BackgroundTask(log_info, req_body, res_body)
return response
return custom_route_handler
app = FastAPI()
router = APIRouter(route_class=LoggingRoute)
logging.basicConfig(filename='info.log', level=logging.DEBUG)
#router.post('/')
def main(payload: Dict[Any, Any]):
return payload
#router.get('/video')
def get_video():
url = 'https://storage.googleapis.com/gtv-videos-bucket/sample/ForBiggerBlazes.mp4'
def gen():
with httpx.stream('GET', url) as r:
for chunk in r.iter_raw():
yield chunk
return StreamingResponse(gen(), media_type='video/mp4')
app.include_router(router)
You may try to customize APIRouter like in FastAPI official documentation:
import time
from typing import Callable
from fastapi import APIRouter, FastAPI, Request, Response
from fastapi.routing import APIRoute
class TimedRoute(APIRoute):
def get_route_handler(self) -> Callable:
original_route_handler = super().get_route_handler()
async def custom_route_handler(request: Request) -> Response:
before = time.time()
response: Response = await original_route_handler(request)
duration = time.time() - before
response.headers["X-Response-Time"] = str(duration)
print(f"route duration: {duration}")
print(f"route response: {response}")
print(f"route response headers: {response.headers}")
return response
return custom_route_handler
app = FastAPI()
router = APIRouter(route_class=TimedRoute)
#app.get("/")
async def not_timed():
return {"message": "Not timed"}
#router.get("/timed")
async def timed():
return {"message": "It's the time of my life"}
app.include_router(router)
As the other answers did not work for me and I searched quite extensively on stackoverflow to fix this problem, I will show my solution below.
The main issue is that when using the request body or response body many of the approaches/solutions offered online do simply not work as the request/response body is consumed in reading it from the stream.
To solve this issue I adapted an approach that basically reconstructs the request and response after reading them. This is heavily based on the comment by user 'kovalevvlad' on https://github.com/encode/starlette/issues/495.
Custom middleware is created that is later added to the app to log all requests and responses. Note that you need some kind of logger to store your logs.
from json import JSONDecodeError
import json
import logging
from typing import Callable, Awaitable, Tuple, Dict, List
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.requests import Request
from starlette.responses import Response, StreamingResponse
from starlette.types import Scope, Message
# Set up your custom logger here
logger = ""
class RequestWithBody(Request):
"""Creation of new request with body"""
def __init__(self, scope: Scope, body: bytes) -> None:
super().__init__(scope, self._receive)
self._body = body
self._body_returned = False
async def _receive(self) -> Message:
if self._body_returned:
return {"type": "http.disconnect"}
else:
self._body_returned = True
return {"type": "http.request", "body": self._body, "more_body": False}
class CustomLoggingMiddleware(BaseHTTPMiddleware):
"""
Use of custom middleware since reading the request body and the response consumes the bytestream.
Hence this approach to basically generate a new request/response when we read the attributes for logging.
"""
async def dispatch( # type: ignore
self, request: Request, call_next: Callable[[Request], Awaitable[StreamingResponse]]
) -> Response:
# Store request body in a variable and generate new request as it is consumed.
request_body_bytes = await request.body()
request_with_body = RequestWithBody(request.scope, request_body_bytes)
# Store response body in a variable and generate new response as it is consumed.
response = await call_next(request_with_body)
response_content_bytes, response_headers, response_status = await self._get_response_params(response)
# Logging
# If there is no request body handle exception, otherwise convert bytes to JSON.
try:
req_body = json.loads(request_body_bytes)
except JSONDecodeError:
req_body = ""
# Logging of relevant variables.
logger.info(
f"{request.method} request to {request.url} metadata\n"
f"\tStatus_code: {response.status_code}\n"
f"\tRequest_Body: {req_body}\n"
)
# Finally, return the newly instantiated response values
return Response(response_content_bytes, response_status, response_headers)
async def _get_response_params(self, response: StreamingResponse) -> Tuple[bytes, Dict[str, str], int]:
"""Getting the response parameters of a response and create a new response."""
response_byte_chunks: List[bytes] = []
response_status: List[int] = []
response_headers: List[Dict[str, str]] = []
async def send(message: Message) -> None:
if message["type"] == "http.response.start":
response_status.append(message["status"])
response_headers.append({k.decode("utf8"): v.decode("utf8") for k, v in message["headers"]})
else:
response_byte_chunks.append(message["body"])
await response.stream_response(send)
content = b"".join(response_byte_chunks)
return content, response_headers[0], response_status[0]
Usage of async/await was presented in Flask 2.0. (https://flask.palletsprojects.com/en/2.0.x/async-await/)
I am using Flask-RestX so is it possible to use async/await in RestX requests handlers?
Something like:
#api.route('/try-async')
class MyResource(Resource):
#api.expect(some_schema)
async def get(self):
result = await async_function()
return result
is not working and when I try to reach this endpoint I'm getting error:
TypeError: Object of type coroutine is not JSON serializable
Is there any info on that?
Package versions:
flask==2.0.1
flask-restx==0.4.0
and I've also installed flask[async] as documentation suggests.
I've gotten around this by using an internal redirect
#api.route('/try-async')
class MyResource(Resource):
#api.expect(some_schema)
def get(self):
return redirect(url_for('.hidden_async'), code=307)
#api.route('/hidden-async', methods=['GET'])
async def hidden_async():
result = await async_function()
return result
Redirecting with code=307 will ensure any method and body are unchanged after the redirect (Link). So passing data to the async function is possible as well.
#api.route('/try-async')
class MyResource(Resource):
#api.expect(some_schema)
def post(self):
return redirect(url_for('.hidden_async'), code=307)
#api.route('/hidden-async', methods=['POST'])
async def hidden_async():
data = request.get_json()
tasks = [async_function(d) for d in data]
result = await asyncio.gather(tasks)
return result
Suppose I have an API for signup. I want to get data from the request and validate it in a Util function that I wrote and placed in another directory (see signup API and my Util directory in the picture). If validation goes fail, I want to return the HTTP response directly from that Util function. How can I achieve this?
In the init.py
from utils.common_utils import validate
def main(req: func.HttpRequest) -> func.HttpResponse:
req_body = validate(req)
# other stuff
return func.HttpResponse("ok", status_code=200)
and in my util function (validate function)
def validate(input):
if ...:
return func.HttpResponse("check your input", status_code=406)
As far as I know, I don't think it can return HttpResponse directly from that Util function and exit the main function. In your code, you can just return HttpResponse to req_body and then execute the following code of main function.
But I think if you write the code like below, it can also meet your requirement. It's the same thing.
def main(req: func.HttpRequest) -> func.HttpResponse:
req_body = validate(req)
if req_body.status_code == 406:
return req_body
return func.HttpResponse("ok", status_code=200)
I have created one HttpTrigger Azure functions using python. But I want to create another one HttpTrigger Azure Functions using python in the same project. In this application I want to execute first HttpTrigger Azure functions after that second HttpTrigger Azure functions execute. How can I implement that?
Because in Python Azure Functions there is no Durable Functions. That's why I am not able to understood how can I execute one after another azure function executes.
Assumed there are two HttpTrigger functions HttpTriggerA and HttpTriggerB, a direct solution in my mind is to request the public url of HttpTriggerA from HttpTriggerB function via a HTTP client request using requests, as the code below in my first version of HttpTriggerB code.
import logging
import azure.functions as func
import requests
from urllib.parse import urlparse
def main(req: func.HttpRequest) -> func.HttpResponse:
logging.info('Python HTTP trigger function processed a request.')
name = req.params.get('name') or 'Peter Pan'
codeA = req.params.get('codeA') or ''
o = urlparse(req.url)
if not name:
try:
req_body = req.get_json()
except ValueError:
pass
else:
name = req_body.get('name')
if name:
print("B be invoked.")
resp = requests.get(f"{o.scheme}://{o.netloc}/api/HttpTriggerA?name={name}&code={codeA}")
return func.HttpResponse(f"Hello {name}! from B {resp.status_code == 200 and resp.text or ''}")
else:
return func.HttpResponse(
"Please pass a name on the query string or in the request body",
status_code=400
)
However, it will not work after I test the code above on local or on Azure. It will hang at the code line resp = requests.get(f"{o.scheme}://{o.netloc}/api/HttpTriggerA?name={name}&code={codeA}"), when I access the url http(s)://<the host of local or Azure>:<7071 or 80>/api/HttpTriggerB?name=Peter%20Pan&code=<code for HttpTriggerB>&codeA=<code for HttpTriggerA>. The reason for the hang issue seems to be caused by functions running in singleton or in single thread.
So I switched to the other solution to use Ajax request from the html content of HttpTriggerB. It works as I wish as the figure below.
Here is my code for HttpTriggerB function, the HttpTriggerA function is simply generated by func new.
import logging
import azure.functions as func
#import requests
from urllib.parse import urlparse
def main(req: func.HttpRequest) -> func.HttpResponse:
logging.info('Python HTTP trigger function processed a request.')
name = req.params.get('name') or 'Peter Pan'
codeA = req.params.get('codeA') or ''
o = urlparse(req.url)
if not name:
try:
req_body = req.get_json()
except ValueError:
pass
else:
name = req_body.get('name')
if name:
print("B be invoked.")
#resp = requests.get(f"{o.scheme}://{o.netloc}/api/httptriggera?name={name}&code={req.params.get('codeA')}")
html = """
<script src="https://code.jquery.com/jquery-3.4.1.min.js"></script>
Hello """+name+"""! from B<br/>
<span id="A"></span>
<script>
$.when(
$.get('"""+o.scheme+'://'+o.netloc+'/api/HttpTriggerA?name='+name+'&code='+codeA+"""'),
$.ready
).done(function( data ) {
$( "#A" ).html( data[0] );
});
</script>
"""
return func.HttpResponse(html, mimetype="text/html")
else:
return func.HttpResponse(
"Please pass a name on the query string or in the request body",
status_code=400
)
Hope it helps.