Install the necessary dependencies.
```sh
pip install flask requests
```

Following is an example lambda handler.
```py
from flask import Flask, request, abort, make_response
import requests

app = Flask(__name__)
@app.route('/', methods=['POST'])
def get_webhook():
	if request.method == 'POST':
		# obtain the request event from the 'POST' call
		event = request.json

		object_context = event["getObjectContext"]

        with open(RELEASE_NOTES_FILE, "w") as f:
            f.writelines(lines)
        sys.exit(0)

    print("No release header found")
    sys.exit(1)


if __name__ == "__main__":

  "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)'
  "$python" -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
fi
# Import tf nightly wheel built with numpy2 from PyPI in numpy1 env for testing.
# This aims to maintain TF compatibility with NumPy 1.x until 2025 b/361369076.
if [[ "$TFCI_WHL_NUMPY_VERSION" == 1 ]]; then

# the __path__ so that "from tensorflow.foo import bar" works.
# We're using bitwise, but there's nothing special about that.
_API_MODULE = _sys.modules[__name__].bitwise  # pylint: disable=undefined-variable
_current_module = _sys.modules[__name__]
_tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__))
if not hasattr(_current_module, "__path__"):
  __path__ = [_tf_api_dir]
elif _tf_api_dir not in __path__:

        ModelField(
            field_info=FieldInfo(annotation=model),
            name=model.__name__,
            mode="validation",
        )
        for model in flat_validation_models
    ]
    flat_serialization_model_fields = [
        ModelField(
            field_info=FieldInfo(annotation=model),
            name=model.__name__,
            mode="serialization",
        )
        for model in flat_serialization_models

    logging.info("Creating PR")
    pr = repo.create_pull(title=message, body=message, base="master", head=branch_name)
    logging.info(f"Created PR: {pr.number}")
    logging.info("Finished")


if __name__ == "__main__":

    ],
):
    all_good = True
    for path in doc_paths:
        res = process_one_page(path)
        all_good = all_good and res

    if not all_good:
        raise typer.Exit(code=1)


if __name__ == "__main__":

    logging.info("Creating PR")
    pr = r.create_pull(title=message, body=message, base="master", head=branch_name)
    logging.info(f"Created PR: {pr.number}")
    logging.info("Finished")


if __name__ == "__main__":

  var_str = '\n'.join(f'{k}="{v}"'
                      for k, v in converted_vars.items())
  # The string can then be piped into `source`, to re-set the
  # 'converted' variables.
  print(var_str)


if __name__ == '__main__':
  parser = argparse.ArgumentParser(description=(
      'Convert MSYS paths in environment variables to Windows paths.'))
  parser.add_argument('--blacklist',
                      nargs='*',

            ),
        ] = True,
    ):
        self.model = OpenIdConnectModel(
            openIdConnectUrl=openIdConnectUrl, description=description
        )
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    def make_not_authenticated_error(self) -> HTTPException:
        return HTTPException(
            status_code=HTTP_401_UNAUTHORIZED,
            detail="Not authenticated",