* **Harder code search and refactoring**: Searching for identifiers, method names, or documentation becomes more difficult when multiple spellings exist for the same concept
* **Inconsistent API surface**: Public APIs with mixed spelling conventions appear less professional and polished

	}
	m := b.grow(n)
	b.buf = b.buf[:m]
}

// Write appends the contents of p to the buffer, growing the buffer as
// needed. The return value n is the length of p; err is always nil. If the
// buffer becomes too large, Write will panic with [ErrTooLarge].
func (b *Buffer) Write(p []byte) (n int, err error) {
	b.lastRead = opInvalid
	m, ok := b.tryGrowByReslice(len(p))
	if !ok {
		m = b.grow(len(p))
	}

    mod.engine.dispose()


def test_crud_app(client: TestClient):
    # TODO: this warns that SQLModel.from_orm is deprecated in Pydantic v1, refactor
    # this if using obj.model_validate becomes independent of Pydantic v2
    with warnings.catch_warnings(record=True):
        warnings.simplefilter("always")
        # No heroes before creating
        response = client.get("heroes/")

    mod.engine.dispose()


def test_crud_app(client: TestClient):
    # TODO: this warns that SQLModel.from_orm is deprecated in Pydantic v1, refactor
    # this if using obj.model_validate becomes independent of Pydantic v2
    with warnings.catch_warnings(record=True):
        warnings.simplefilter("always")
        # No heroes before creating
        response = client.get("heroes/")

## Number validations: floats, greater than and less than { #number-validations-floats-greater-than-and-less-than }

Number validations also work for `float` values.

  # Find all Python py_test targets not tagged "no_pip" or "manual", excluding
  # any targets in ignored packages. Combine this list of targets into a bazel
  # query list (e.g. the list becomes "target+target2+target3")

## Recap { #recap }

With what you have seen up to now, you can set up a secure **FastAPI** application using standards like OAuth2 and JWT.

In almost any framework handling the security becomes a rather complex subject quite quickly.

```Python
q: str | None = None
```

////

//// tab | Python 3.9+

```Python
q: Union[str, None] = None
```

////

What we will do is wrap that with `Annotated`, so it becomes:

//// tab | Python 3.10+

```Python
q: Annotated[str | None] = None
```

////

//// tab | Python 3.9+

```Python
q: Annotated[Union[str, None]] = None
```

////

It can't handle nested models very well. So, if the JSON body in the request is a JSON object that has inner fields that in turn are nested JSON objects, it cannot be properly documented and validated.

            // Check if this parent is in our local pomMap
            Path parentPath = findParentInPomMap(parent, pomMap);
            if (parentPath != null) {
                // Parent is local, so it becomes our new candidate
                lastLocalParent = parentPath;

                // Load the parent model to continue walking up
                Path parentTempPath = tempDir.resolve(commonRoot.relativize(parentPath));