zhanymkanov / fastapi_production_template Goto Github PK

from redis.asyncio import Redis
ModuleNotFoundError: No module named 'redis.asyncio'; 'redis' is not a package

Hi,Brother, how to solve this error reported by redis.

How come when using Authorize from the Docs page we sent data in bytes?

But when using the '''auth/users/tokens'' endpoint form the data comes in a dict.

Hello, fast API has released a newer version 0.100 that is compatible with pydantic v2. Any plans to update this project to support updated versions?

excuse me，could u plz tell me how to run in windows without docker、？

hello,sir.
i wtite a log.ini,pass it for the para of log_config in uvicorn.run('main:app', host="127.0.0.1", port=8051, log_config="log.ini").

besides, i initializes class of logger by：self._logger = logging.getLogger(name) in some file.

i found that the log generated by self._logger can be found in the log file defined by "log_config".

so,question is:

1. why?
2. how can i output some dynamic log to the log file formally?

Followed the readme with first time only
After running docker compose, the app container exists with just this one line in the log

2024-05-03 15:18:43 /usr/bin/env: ‘bash\r’: No such file or directory

Currently, custom exceptions do not get a place on documentation. I have tried responses={}, but with no luck. What's the correct thing to do here? Create a custom pydantic model just for it to show on docs?

In the conftest.py the event loop is being replaced with a new one. This is no longer supported with pytest_asyncio and results in this warning:

Replacing the event_loop fixture with a custom implementation is deprecated
  and will lead to errors in the future.
  If you want to request an asyncio event loop with a scope other than function
  scope, use the "scope" argument to the asyncio mark when marking the tests.
  If you want to return different types of event loops, use the event_loop_policy
  fixture.

Hi,
Thank you for your great work!

Something is unclear for me according to "FastAPI Best Practices" and this repo.

If this repository would have the same multi-module structure (src/auth/models.py, src/posts/models.py), the alembic will not see these models during the autogenerate, because we need import Base and all models we want to track somewhere in one place.

How do you handle this?

Is the alembic/env.py the best place to do these imports?

For example:

from src.models import Base  # noqa
from src.auth.models import User # noqa
from src.posts.models import Post # noqa

target_metadata = Base.metadata

I think explicit imports in env.py is not a bad idea, because we can control which models alembic will be tracking.

But what is the best practice?

The on_event(startup and shutdown) has been depreciated
https://fastapi.tiangolo.com/advanced/events/

Reference on lifespan protocol:
https://asgi.readthedocs.io/en/latest/specs/lifespan.html

I can create a pull request but wanted to open the issue before proposing changes.

Any plans to add an open source license?

app          | pydantic_core._pydantic_core.ValidationError: 1 validation error for PublicAPIsResponse
app          |   Invalid JSON: expected value at line 1 column 1 [type=json_invalid, input_value=b'You have reached maximum request limit.', input_type=bytes]
app          |     For further information visit https://errors.pydantic.dev/2.3/v/json_invalid

It looks like there is some sort of rate limiting on the Public API request, might have something to do with the httpx user agent? Not sure if anyone has encountered this, as the endpoint is perfectly accessible through the browser.

According to start-dev.sh, it can take LOG_CONFIG

But this is static value.

We can change to
logconfig = os.getenv("LOG_CONFIG", "/src/logging_production.ini")

What do you think? This will make LOG_CONFIG in .env has meaning for both dev and prod environment.

Hello, fast API has released a newer version 0.100 that is compatible with pydantic v2. Any plans to update this project to support updated versions?

Hi, and thanks for sharing this! It's always interesting to see how others are structuring their FastAPI projects. Looking over this repo I did have one question I hope you don't mind me asking (please close if you'd rather not have questions).

In your subclass of the pydantic BaseModel you set the json_dumps function to use an orjson based implementation. My understanding of pydantic means this function will be used whenever model_subclass.json() is called. However, fastAPI won't actually call .json() and instead will just use its jsonable_encoder function when returning pydantic models from an endpoint.

I know one can directly return a Response class to skip the fastAPI validation so potentially you could be doing something like:

@router.get("/endpoint", response_model=SomeModel)
def get_model():
    some_model = SomeModel(...)
    return ORJSONResponse(content=json.loads(some_model.json()))

But it would be cool if there was a way to set this up without having to explicitly call .json(). So I'd like to understand how you are using this json_dumps function in practice if you don't mind sharing?