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How can I access the /docs or custom routes end point while using fastapi as backend for supertokens?

I am using supertokens to build an authentication system and using fastApi as backend but while using their prebuild UI and already setup backend code in python, I am not able to access the 127.0.0.0:3000/docs endpoint. It is showing only a blank page.
Also, the custom routes that I have built in my API are not working and accessible.
Here is the code that I have written
#app.get("/sessioninfo")
async def secure_api(s: SessionContainer = Depends(verify_session())):
return {
"sessionHandle": s.get_handle(),
"userId": s.get_user_id(),
"accessTokenPayload": s.get_access_token_payload(),
}
Here is the app_info part of init function in supertokens
app_info = InputAppInfo(
app_name="demoApp",
api_domain="http://localhost:3001",
website_domain="http://localhost:3000",
)
After hitting the API with port 3000 and endpoint /sessioninfo I am getting blankpage
localhost:3000/session_info
And for localhost:3001/session_info I am getting an internal server error.
localhost:3001/session_info

localhost:3000/session_info won't respond with session info because it's being handled by the front end.
But localhost:3001/session_info should work. This error is likely to be happening because of python/dependency versions.
Update: As per this GH comment, this error is likely to be coming from Python 3.11. So maybe try a different version of python
I hope this helps :)

Why does this gRPC call from the Google Secret Manager API hang when run by Apache?

In short:
I have a Django application being served up by Apache on a Google Compute Engine VM.
I want to access a secret from Google Secret Manager in my Python code (when the Django app is initialising).
When I do 'python manage.py runserver', the secret is successfully retrieved. However, when I get Apache to run my application, it hangs when it sends a request to the secret manager.
Too much detail:
I followed the answer to this question GCP VM Instance is not able to access secrets from Secret Manager despite of appropriate Roles. I have created a service account (not the default), and have given it the 'cloud-platform' scope. I also gave it the 'Secret Manager Admin' role in the web console.
After initially running into trouble, I downloaded the a json key for the service account from the web console, and set the GOOGLE_APPLICATION_CREDENTIALS env-var to point to it.
When I run the django server directly on the VM, everything works fine. When I let Apache run the application, I can see from the logs that the service account credential json is loaded successfully.
However, when I make my first API call, via google.cloud.secretmanager.SecretManagerServiceClient.list_secret_versions , the application hangs. I don't even get a 500 error in my browser, just an eternal loading icon. I traced the execution as far as:
grpc._channel._UnaryUnaryMultiCallable._blocking, line 926 : 'call = self._channel.segregated_call(...'
It never gets past that line. I couldn't figure out where that call goes so I couldnt inspect it any further than that.
Thoughts
I don't understand GCP service accounts / API access very well. I can't understand why this difference is occurring between the django dev server and apache, given that they're both using the same service account credentials from json. I'm also surprised that the application just hangs in the google library rather than throwing an exception. There's even a timeout option when sending a request, but changing this doesn't make any difference.
I wonder if it's somehow related to the fact that I'm running the django server under my own account, but apache is using whatever user account it uses?
Update
I tried changing the user/group that apache runs as to match my own. No change.
I enabled logging for gRPC itself. There is a clear difference between when I run with apache vs the django dev server.
On Django:
secure_channel_create.cc:178] grpc_secure_channel_create(creds=0x17cfda0, target=secretmanager.googleapis.com:443, args=0x7fe254620f20, reserved=(nil))
init.cc:167] grpc_init(void)
client_channel.cc:1099] chand=0x2299b88: creating client_channel for channel stack 0x2299b18
...
timer_manager.cc:188] sleep for a 1001 milliseconds
...
client_channel.cc:1879] chand=0x2299b88 calld=0x229e440: created call
...
call.cc:1980] grpc_call_start_batch(call=0x229daa0, ops=0x20cfe70, nops=6, tag=0x7fe25463c680, reserved=(nil))
call.cc:1573] ops[0]: SEND_INITIAL_METADATA...
call.cc:1573] ops[1]: SEND_MESSAGE ptr=0x21f7a20
...
So, a channel is created, then a call is created, and then we see gRPC start to execute the operations for that call (as far as I read it).
On Apache:
secure_channel_create.cc:178] grpc_secure_channel_create(creds=0x7fd5bc850f70, target=secretmanager.googleapis.com:443, args=0x7fd583065c50, reserved=(nil))
init.cc:167] grpc_init(void)
client_channel.cc:1099] chand=0x7fd5bca91bb8: creating client_channel for channel stack 0x7fd5bca91b48
...
timer_manager.cc:188] sleep for a 1001 milliseconds
...
timer_manager.cc:188] sleep for a 1001 milliseconds
...
So, we a channel is created... and then nothing. No call, no operations. So the python code is sitting there waiting for gRPC to make this call, which it never does.

The problem appears to be that the forking behaviour of Apache breaks gRPC somehow. I couldn't nail down the precise cause, but after I began to suspect that forking was the issue, I found this old gRPC issue that indicates that forking is a bit of a tricky area.
I tried to reconfigure Apache to use a different 'Multi-processing Module', but as my experience in this is limited, I couldn't get gRPC to work under any of them.
In the end, I switched to using nginx/uwsgi instead of Apache/mod_wsgi, and I did not have the same issue. If you're trying to solve a problem like this and you have to use Apache, I'd advice further investigating Apache forking, how gRPC handles forking, and the different MPMs available for Apache.

I'm facing a similar issue. When running my Flask Application with eventlet==0.33.0 and gunicorn https://github.com/benoitc/gunicorn/archive/ff58e0c6da83d5520916bc4cc109a529258d76e1.zip#egg=gunicorn==20.1.0. When calling secret_client.access_secret_version it hangs forever.
It used to work fine with an older eventlet version, but we needed to upgrade to the latest version of eventlet due to security reasons.

I experienced a similar issue and I was able to solve with the following:
import grpc.experimental.gevent as grpc_gevent
from gevent import monkey
from google.cloud import secretmanager
monkey.patch_all()
grpc_gevent.init_gevent()
client = secretmanager.SecretManagerServiceClient()

Azure functions Error: Error "SyntaxError: Unexpected token S in JSON at position 0" occurred while parsing the response body - Service Unavailable

I am getting the error while deploying the Azure function from the local system.
I wen through some blogs and it is stating that my function is unable to connect with the Azure storage account which has the functions meta data.
Also, The function on the portal is showing the error as: Azure Functions runtime is unreachable
Earlier my function was running but after integrating the function with a Azure premium App service plan it has stooped working. My assumption is that my app service plan having some restriction for the inbound/outbound traffic rule and Due to this it is unable to establish the connection with the function's associated storage account.
Also, I would like to highlight that if a function is using the premium plan then we have to add few other configuration properties.
WEBSITE_CONTENTAZUREFILECONNECTIONSTRING = "DefaultEndpointsProtocol=https;AccountName=blob_container_storage_acc;AccountKey=dummy_value==;EndpointSuffix=core.windows.net"
WEBSITE_CONTENTSHARE = "my-function-name"
For the WEBSITE_CONTENTSHARE property I have added the function app name but I am not sure with the value.
Following is the Microsoft document reference for the function properties
Microsoft Function configuration properties link
Can you please help me to resolve the issue.
Note: I am using python for the Azure functions.

I have created a new function app with Premium plan and selected the interpreter as Python. When we select Python, OS will be automatically Linux.
Below is the message we get to create functions for Premium plan function App:
Your app is currently in read only mode because Elastic Premium on Linux requires running from a package.
PortalScreenshot
We need to create, deploy and run function apps from a package, refer to the documentation on how we can run functions from package.
Documentation
Make sure to add all your local.settings.json configurations to Application Settings in function app.

Not sure of what kind of Azure Function you are using but usually when there is a Storage Account associated, we need to specify the AzureWebJobsStorage field in the serviceDependencies.json file inside Properties folder. And when I had faced the same error, the cause was that while publishing the azure function from local, some settings from the local.settings.json were missing in the Application Settings of the app service under Configuration blade.
There can be few more things which you can recheck:
Does the storage account you are trying to use existing still or is deleted by any chance.
While publishing the application from local, using the web deploy method, the publish profile is correct or has any issues.
Disabling the function app and then stopping the app service before redeploying it.
Hope any of the above mentions help you diagnose and solve the issue.

The thing is that there is a difference in how the function deployed using Consumption vs Premium service plan.
Consumption - working out of the box.
Premium - need to add the WEBSITE_RUN_FROM_PACKAGE = 1 in the function Application settings. (see https://learn.microsoft.com/en-us/azure/azure-functions/run-functions-from-deployment-package for full details)

Unauthenticated error using gcloud-python to connect to google bigtable

I've set up a Google Cloud BigTable cluster on my project. The main codebase for the project runs within a standard Python App Engine environment, which can't use the gcloud-python library because of the reliance on grpcio. To get around this, I've set up a Python App Engine Flexible Environment service within the same project and written a very simple Flask server to run on it, which I can then hit from my standard environment. The code looks something like this:
from gcloud import bigtable
app = Flask(__name__)
client = bigtable.Client(project=bigtable_config.PROJECT_ID, read_only=True)
cluster = client.cluster(bigtable_config.ZONE_ID, bigtable_config.CLUSTER_ID)
table = cluster.table(bigtable_config.TABLE_ID)
#app.route("/query/<start_key>/<end_key>")
def run_query(start_key, end_key):
if not client.is_started():
client.start()
row_data = table.read_rows(start_key=start_key, end_key=end_key)
row_data.consume_all()
// do some stuff to the row data here, get results
return jsonify(results)
I can run this code locally and it works great. I can deploy it to my service and it continues to work great. However, if the service sits idle for some period of time (I've typically noticed it after about an hour), then every request I make starts failing with this error:
NetworkError(code=StatusCode.UNAUTHENTICATED, details="Request had invalid authentication credentials.")
If I redeploy the service, it starts working again. I do not observe this behavior when I'm running the service locally.
What am I doing wrong? I'm assuming I'm making some mistake in my setup of the client, where it's not properly using the app engine credentials. Do I need to kill the client and restart it when I encounter this error?

This issue is being tracked at github.

Why is my Facebook application with error 104 ("invalid signature")?

I am trying to develop a Facebook application using PyFacebook (hosted on Google App Engine). It's an FBML application (runs in a Facebook canvas instead of an iframe). I'm having problems getting any API calls to function. The sequence looks like this:
fb = facebook.Faceboook(api_key, secret_key)
fb.session_key = cherrypy.request.params['fb_sig_session_key']
fb.uid =cherrypy.request.params['fb_sig_user']
Then if I try, for example:
user = fb.users.getLoggedInUser()
This will fail with:
Error 104: Incorrect signature
I'm not sure where I'm going wrong. I've verified that the api_key and secret_key are correct (many, many times). The application has been added to my account. I've even been able to get a desktop application working; my problem is only with this web-hosted version.
Thanks for your help!

Deleting the Facebook application and re-creating it, then configuring my code with the new API key and secret key, resolved this problem.