- we also seem to have information like the plugin lifecycle model that's buried inside the maven execution model
- we also seem to have artifact information tangled inside the plugin model
- we have to deal with scripting implementations (groovy, beanshell, ruby)
- we need to deal with a shared context for plugins, like the guarded mojos

  DefaultExpressionEvaluator used within. See the above discussion for more
  on why this evaluator is bad. We need to provide either an alternative
  implementation under a different roleHint, or else replace the
  BasicComponentConfigurator.

* Other

  We may need to define a new lifecycle/phase to contextualize a mojo right
  before it's used, and reset it's state afterward. Up to now, the approach

///

We are going to include this `APIRouter` in the main `FastAPI` app, but first, let's check the dependencies and another `APIRouter`.

## Dependencies { #dependencies }

We see that we are going to need some dependencies used in several places of the application.

So we put them in their own `dependencies` module (`app/dependencies.py`).

        // Before we update the version of the artifact, we need to know
        // whether we are working on a transitive dependency or not. This
        // allows depMgmt to always override transitive dependencies, while
        // explicit child override depMgmt (viz. depMgmt should only
        // provide defaults to children, but should override transitives).

pushd "${TFCI_OUTPUT_DIR}"

# Unpack the wheel to get all the file contents. The pure python wheel we built
# above is tagged with "py3-none-any". We cannot change the tags by simply
# renaming the wheels as uploading to PyPI would fail with "File already exists"
# error. In order to upload to PyPI, we unpack the wheel and change the tag
# inside a metadata file to the one we want (e.g cp38-cp38-win_amd) and then

    using a job called "copybara".

**5. Copy to Google Internal codebase and run internal CI**

-   Once the PR is in the Google codebase, we make sure it integrates well with
    its dependencies and the rest of the system.
-   Rarely, If the tests fail at this stage, we cannot merge the code.
-   If needed, we may come to you to make some changes. At times, it may not be

Now we are going to update our dependencies.

We want to get the `current_user` *only* if this user is active.

So, we create an additional dependency `get_current_active_user` that in turn uses `get_current_user` as a dependency.

Both of these dependencies will just return an HTTP error if the user doesn't exist, or if is inactive.

## Consequences

* X
* Y
* Z
```

## Status

ACCEPTED

## Consequences

* We start to use Architectural Decision Records
* We use the proposed template from this ADR
* We locate `.md` files in the folder `/architecture/standards`
* We highly encourage usage of ADR to communicate decisions

termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a

Let's look at how we can make that work.

## pytest.mark.anyio { #pytest-mark-anyio }