I have implemented a test function in pytest which loads data from files, casts it into Python objects and provides a new object for each test.
Each one of these objects contains a request I need to make to the server and the expected responses, the function looks like this:
#pytest.mark.asyncio
#pytest.mark.parametrize('test', TestLoader.load(JSONTest, 'json_tests'))
async def test_json(test: JSONTest, groups: Set[TestGroup], client: httpx.AsyncClient):
skip_if_not_in_groups(test, groups)
request = Request(url=test.url, body=test.body.dict())
response = await client.post(request.url, json=request.body)
# Assertions down here...
Many times I send many requests that contain the same http endpoint with the same body so the response is the same, but I'm testing for different things in the response.
Because of that I thought of implementing an in-memory cache so that for each test run the same requests won't be implemented twice.
What I've tried to do is create a request object, with its own __hash__ implementation and use the #asyncstdlib.lru_cache on the function, it didn't seem to work.
# Does not work...
#asyncstdlib.lru_cache
async def send_request(request: Request, client: httpx.AsyncClient):
return await client.post(request.url, json=request.body)
#pytest.mark.asyncio
#pytest.mark.parametrize('test', TestLoader.load(JSONTest, 'json_tests'))
async def test_json(test: JSONTest, groups: Set[TestGroup], client: httpx.AsyncClient):
skip_if_not_in_groups(test, groups)
request = Request(url=test.url, body=test.body.dict())
response = await send_request(request)
The client I'm using: httpx.AsyncClient also implements __hash__, it's coming from a pytest.fixture in conftest.py and it has a scope of 'session':
# conftest.py
#pytest.fixture(scope='session')
def event_loop(request):
loop = asyncio.get_event_loop_policy().new_event_loop()
yield loop
loop.close()
#pytest.fixture(scope='session')
async def client() -> httpx.AsyncClient:
async with httpx.AsyncClient() as client:
yield client
Just let go of the opaque 3rd party cache, and cache yourself.
Since you don't require cleaning-up the cache during a single execution, a plain dictionary will work:
_cache = {}
async def send_request(request: Request, client: httpx.AsyncClient):
if request.url not in _cache:
_cache[request.url] = await client.post(request.url, json=request.body)
return _cache[request.url]
Related
Below is simple server written with FastAPI and running with Uvicorn.
In order to send the value to the next hop, the '/destination' url, I need to pass the value to the forward_request method.
In this implementation, passing the value is easy, because the calls' depth is just 1 function more.
But if I have a function that calls a function that calls a function...., I need to pass the value again and again and...
Is there a simpler way to share the value downstream without passing it?
Is there a way, without using inspect or some dark magic, to understand what is the scope that the function forward_request lives in?
Why am I asking this question?
I am using Jaeger for tracing and I need to forward the header x-request-id that I receive in the 1st server (/source in this example) to the 2nd server (/destination in this example).
If FastAPI\Uvicorn processed just 1 request at a time, I could have shared the value as a singleton class and access it from anywhere, but since requests are handled in parallel, the function forward_request doesn't have the context of who called it.
Some black magic
Function forward_request can inspect the call stack and figure from it, what is the value that was received, but that is one ugly way to do things.
Server Code
import asyncio
import aiohttp as aiohttp
from fastapi import FastAPI, Request
import uvicorn
from datetime import datetime
app = FastAPI()
#app.get("/source")
async def route1(value: int, request: Request):
print(f'source {value}')
start = datetime.now().strftime("%H:%M:%S")
await asyncio.sleep(5)
resp: dict = await forward_request(value)
end = datetime.now().strftime("%H:%M:%S")
return {
"start": start,
"end": end,
"value": value,
"resp": resp
}
#app.get("/destination")
async def route2(value, request: Request):
print(f'destination {value}')
start = datetime.now().strftime("%H:%M:%S")
await asyncio.sleep(5)
end = datetime.now().strftime("%H:%M:%S")
return {
"start": start,
"end": end,
"value": value
}
async def forward_request(value: int) -> dict:
async with aiohttp.ClientSession() as session:
async with session.get('http://127.0.0.1:5000/destination', params={'value': value}) as resp:
resp = await resp.json()
return resp
if __name__ == "__main__":
uvicorn.run("main2:app", host="127.0.0.1", port=5000, log_level="info", workers=1)
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]
I am using Quart App.
I am calling a service in my before_serving(app_initionalization) function and I do not want to call that in pytests. Actually, I want to disable my before_serving function or something like mock it.
import pytest
#pytest.mark.asyncio
async def test_my_api_call(test_app: Pint, headers: dict):
test_client = test_app.test_client()
response = await test_client.get("/get_user", headers)
assert response.status_code == 200
This is my test_app.
#pytest.fixture(name="test_app", scope="function")
async def _test_app(s3_client, tmp_path, async_mongodb):
os.environ["BLOB_STORE"] = str(tmp_path)
db_config['db'] = async_mongodb
async with app.test_app() as test_app:
yield test_app
Your fixture will run the before-serving startup functions as it uses the test_app,
async with app.test_app() as test_app:
As you don't wish to run these you can change your fixture to,
#pytest.fixture(name="test_app", scope="function")
async def _test_app(s3_client, tmp_path, async_mongodb):
os.environ["BLOB_STORE"] = str(tmp_path)
db_config['db'] = async_mongodb
return app
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