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]
Is it possible to get the cookies when someone hits the API? I need to read the cookies for each request.
#app.get("/")
async def root(text: str, sessionKey: str = Header(None)):
print(sessionKey)
return {"message": text+" returned"}
if __name__ == "__main__":
uvicorn.run("main:app", host="0.0.0.0", port=5001 ,reload=True)
You can do it in the same way you are accessing the headers in your example (see docs):
from fastapi import Cookie
#app.get("/")
async def root(text: str, sessionKey: str = Header(None), cookie_param: int | None = Cookie(None)):
print(cookie_param)
return {"message": f"{text} returned"}
Option 1
Use the Request object to get the cookie you wish, as described in Starlette documentation.
from fastapi import Request
#app.get('/')
async def root(request: Request):
print(request.cookies.get('sessionKey'))
return 'OK'
Option 2
Use the Cookie parameter, as described in FastAPI documentation.
from fastapi import Cookie
#app.get('/')
async def root(sessionKey: str = Cookie(None)):
print(sessionKey)
return 'OK'
I'm trying to send a request to an api using pytest through httpx.AsynClient
#pytest.mark.anyio
async def test_device_create_with_data(self, client, random_uuid):
device_create = DeviceCreateFactory.build(subId=random_uuid)
json = device_create.json(by_alias=True)
response = await client.post("/device", json=json)
assert response.status_code == 200
Client fixture:
from httpx import AsyncClient
#pytest.fixture(scope="session")
async def client():
async with AsyncClient(
app=app,
base_url="http://test/api/pc",
headers={"Content-Type": "application/json"}
) as client:
yield client
API endpoint:
#device_router.post("/device", response_model=CommonResponse)
async def create_device(device: DeviceCreate):
_, err = await crud_device.create_device(device)
if err:
return get_common_response(400, err)
return get_common_response(200, "ok")
Schemas:
class DeviceBase(BaseModel):
device_id: StrictStr = Field(..., alias='deviceId')
device_name: StrictStr = Field(..., alias='deviceName')
device_type: StrictStr = Field(..., alias='deviceType')
age_mode: AgeModeType = Field(..., alias='ageMode')
class Config:
allow_population_by_field_name = True
validate_all = True
validate_assignment = True
class DeviceCreate(DeviceBase):
sub_id: StrictStr = Field(..., alias='subId')
class Config:
orm_mode = True
Factory:
from pydantic_factories import ModelFactory
from app.core.schemas.device import DeviceCreate
class DeviceCreateFactory(ModelFactory):
__model__ = DeviceCreate
And i'm getting a 422 error with following response content:
"message":"bad request","details":{"deviceId":"field required","deviceName":"field required","deviceType":"field required","ageMode":"field required","subId":"field required"}
Then i examined the data of the request being sent and got:
b'"{\\"deviceId\\": \\"de\\", \\"deviceName\\": \\"\\", \\"deviceType\\": \\"\\", \\"ageMode\\": \\"child\\", \\"subId\\": \\"11aded61-9966-4be1-a781-387f75346811\\"}"'
Seems like everything is okay, but where is the trouble then?
I've tried to examine the request data in exception handler of 422
I've made:
#app.exception_handler(RequestValidationError)
async def validation_exception_handler(request: Request, exc: RequestValidationError):
print(await request.json())
response = validation_error_response(exc)
return JSONResponse(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
content=jsonable_encoder(response.dict())
)
But code after print is unreachable, because await request.json() never ends and runs forever trying to print a request json
Is there a way to manage this problem?
Thanks for any suggest!
P.S.
python version: 3.8.9
fastapi version: 0.68.1
httpx version: 0.21.1
You're double encoding your content as JSON - you're both asking for it to be returned as a JSON string, and then telling your request method to encode it as JSON a second time. json= as an argument to the method on the client converts the given data to JSON - it does not expect already serialized JSON.
You can see this in your request string because it starts with " and not with { as you'd expect:
b'"{\
^
Instead build your model around a dictionary - or as I'd prefer in a test - build the request by hand, so that you're testing how you imagine an actual request should look like.
You can use dict in the same was as you'd use json for a Pydantic model:
device_create = DeviceCreateFactory.build(subId=random_uuid)
response = await client.post("/device", json=device_create.dict(by_alias=True))
assert response.status_code == 200
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]
Is there a way to download a file through FastAPI? The files we want are located in an Azure Datalake and retrieving them from the lake is not an issue, the problem occurs when we try to get the bytes we get from the datalake down to a local machine.
We have tried using different modules in FastAPI such as starlette.responses.FileResponse and fastapi.Response with no luck.
In Flask this is not an issue and can be done in the following manner:
from io import BytesIO
from flask import Flask
from werkzeug import FileWrapper
flask_app = Flask(__name__)
#flask_app.route('/downloadfile/<file_name>', methods=['GET'])
def get_the_file(file_name: str):
the_file = FileWrapper(BytesIO(download_file_from_directory(file_name)))
if the_file:
return Response(the_file, mimetype=file_name, direct_passthrough=True)
When running this with a valid file name the file automatically downloads. Is there equivalent way to this in FastAPI?
Solved
After some more troubleshooting I found a way to do this.
from fastapi import APIRouter, Response
router = APIRouter()
#router.get('/downloadfile/{file_name}', tags=['getSkynetDL'])
async def get_the_file(file_name: str):
# the_file object is raw bytes
the_file = download_file_from_directory(file_name)
if the_file:
return Response(the_file)
So after a lot of troubleshooting and hours of looking through documentation, this was all it took, simply returning the bytes as Response(the_file).
After some more troubleshooting I found a way to do this.
from fastapi import APIRouter, Response
router = APIRouter()
#router.get('/downloadfile/{file_name}', tags=['getSkynetDL'])
async def get_the_file(file_name: str):
# the_file object is raw bytes
the_file = download_file_from_directory(file_name)
if the_file:
return Response(the_file)
So after a lot of troubleshooting and hours of looking through documentation, this was all it took, simply returning the bytes as Response(the_file) with no extra parameters and no extra formatting for the raw bytes object.
As far as I know, you need to set media_type to the adequate type. I did that with some code a year ago and it worked fine.
#app.get("/img/{name}")
def read(name: str, access_token_cookie: str=Cookie(None)):
r = internal.get_data(name)
if r is None:
return RedirectResponse(url="/static/default.png")
else:
return Response(content=r["data"], media_type=r["mime"])
r is a dictionary with the data as raw bytes and mime the type of the data as given by PythonMagick.
To add a custom filename to #Markus's answer, in case your api's path doesn't end with a neat filename or you want to determine a custom filename from server side and give to the user:
from fastapi import APIRouter, Response
router = APIRouter()
#router.get('/downloadfile/{file_name}', tags=['getSkynetDL'])
async def get_the_file(file_name: str):
# the_file object is raw bytes
the_file = download_file_from_directory(file_name)
filename1 = make_filename(file_name) # a custom filename
headers1 = {'Content-Disposition': f'attachment; filename="{filename1}"'}
if the_file:
return Response(the_file, headers=headers1)