2. **Thoughtful, honest feedback.** We will consider every contribution on its merits, regardless of whether AI was used. We may not respond quickly—our review queue is long—but we will tell you clearly what works, what needs to change, and why.

collaborative, shared environment, and goals. We expect it to be followed in spirit as much as in
the letter.

Diversity Statement
-------------------

We encourage everyone to participate and are committed to building a community for all. Although we
may not be able to satisfy everyone, we all agree that everyone is equal.

Whenever a participant has made a mistake, we expect them to take responsibility for it. If someone

So, if we create a Pydantic object `user_in` like:

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

and then we call:

```Python
user_dict = user_in.model_dump()
```

we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).

And if we call:

```Python
print(user_dict)
```

  # Do a sanity check to make sure that we using the correct Python version
  python --version
fi

# TFCI Mac VM images do not have twine installed by default so we need to
# install it manually. We use Twine in nightly builds to upload Python packages
# to PyPI.
if [[ "$TFCI_MACOS_TWINE_INSTALL_ENABLE" == 1 ]]; then
  pip install twine==3.6.0
fi

# When cross-compiling with RBE, we need to copy the macOS sysroot to be

  </plugin>
  .
  .
  .
</plugins>

 *       under all environments. We could fight this by fully qualifying the annotation, but the
 *       result will be verbose and attention-grabbing.
 *   <li>We need to be careful about how we suppress {@code suite()} methods in {@code common.io}.
 *       The generated suite for {@code FooTest} ends up containing {@code FooTest} itself plus some
 *       other tests. We want to exclude the other tests (which Android can't handle) while

          // otherwise try to presize a StringBuilder
          // it is kind of lame that we need to construct a decoder to access this value.
          // if this is a concern we could add special cases for some known charsets (like utf8)
          // or we could avoid inputstreamreader and use the decoder api directly
          // TODO(lukes): in a real implementation we would need to handle overflow conditions

          // otherwise try to presize a StringBuilder
          // it is kind of lame that we need to construct a decoder to access this value.
          // if this is a concern we could add special cases for some known charsets (like utf8)
          // or we could avoid inputstreamreader and use the decoder api directly
          // TODO(lukes): in a real implementation we would need to handle overflow conditions

## Decision

We do not use Java serialization.
Instead, we use custom serialization where we explicitly describe how data objects should be serialized and deserialized.

For internal purposes, we use binary formats for their brevity.
We use the `Serializer` abstraction to separate the actual implementation of serialization from its uses.

When sharing data with external tools, we use JSON.

## Consequences

Then we use the request directly, and extract the body as `bytes`. This means that FastAPI won't even try to parse the request payload as JSON.

And then in our code, we parse that YAML content directly, and then we are again using the same Pydantic model to validate the YAML content: