Describe your environment. I am using a Python Azure Function where I use SQLAlchemy with async engine using postgres+asyncpg to make database queries based on the content of the request. I used the steps in their documentation to make it work, but and I added 'sqlalchemy' to trace_integrations instead of 'requests'.
from opencensus.extension.azure.functions import OpenCensusExtension
from opencensus.trace import config_integration
config_integration.trace_integrations(["sqlalchemy"])
OpenCensusExtension.configure()
Steps to reproduce.
Try integrating sqlalchemy in a Python Azure Function with asyncpg and an async engine of SQLAlchemy using async sessions.
What is the expected behavior?
I would like to see how long each query takes and some additional properties but I get them duplicated as seen below.
What is the actual behavior?
Strange thing is that one is the child of a span that already has a trace for that query.
Additional context.
I am not sure if this library is not prepared for async or it is because of sessions, connections, etc.
For illustration I made this with pg_sleep, but it is the same with "normal" queries.
Describe your environment. I am using a Python Azure Function where I use SQLAlchemy with async engine using postgres+asyncpg to make database queries based on the content of the request. I used the steps in their documentation to make it work, but and I added 'sqlalchemy' to trace_integrations instead of 'requests'.
Steps to reproduce. Try integrating sqlalchemy in a Python Azure Function with asyncpg and an async engine of SQLAlchemy using async sessions.
What is the expected behavior? I would like to see how long each query takes and some additional properties but I get them duplicated as seen below.
What is the actual behavior? Strange thing is that one is the child of a span that already has a trace for that query.![image](https://user-images.githubusercontent.com/80851806/230719253-638013b9-2a62-4d43-b315-b2cac9f682f8.png)
Additional context. I am not sure if this library is not prepared for async or it is because of sessions, connections, etc. For illustration I made this with pg_sleep, but it is the same with "normal" queries.