# Copyright 2022 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Middleware for injecting client-side feature flags into the Context.""" import json import urllib.parse from tensorboard import context from tensorboard import errors class ClientFeatureFlagsMiddleware: """Middleware for injecting client-side feature flags into the Context. The client webapp is expected to include a json-serialized version of its FeatureFlags in the `X-TensorBoard-Feature-Flags` header or the `tensorBoardFeatureFlags` query parameter. This middleware extracts the header or query parameter value and converts it into the client_feature_flags property for the DataProvider's Context object, where client_feature_flags is a Dict of string keys and arbitrary value types. In the event that both the header and query parameter are specified, the values from the header will take precedence. """ def __init__(self, application): """Initializes this middleware. Args: application: The WSGI application to wrap (see PEP 3333). """ self._application = application def __call__(self, environ, start_response): header_feature_flags = self._parse_potential_header_param_flags( environ.get("HTTP_X_TENSORBOARD_FEATURE_FLAGS") ) query_string_feature_flags = self._parse_potential_query_param_flags( environ.get("QUERY_STRING") ) if not header_feature_flags and not query_string_feature_flags: return self._application(environ, start_response) # header flags take precedence for flag, value in header_feature_flags.items(): query_string_feature_flags[flag] = value ctx = context.from_environ(environ).replace( client_feature_flags=query_string_feature_flags ) context.set_in_environ(environ, ctx) return self._application(environ, start_response) def _parse_potential_header_param_flags(self, header_string): if not header_string: return {} try: header_feature_flags = json.loads(header_string) except json.JSONDecodeError: raise errors.InvalidArgumentError( "X-TensorBoard-Feature-Flags cannot be JSON decoded." ) if not isinstance(header_feature_flags, dict): raise errors.InvalidArgumentError( "X-TensorBoard-Feature-Flags cannot be decoded to a dict." ) return header_feature_flags def _parse_potential_query_param_flags(self, query_string): if not query_string: return {} try: query_string_json = urllib.parse.parse_qs(query_string) except ValueError: return {} # parse_qs returns the dictionary values as lists for each name. potential_feature_flags = query_string_json.get( "tensorBoardFeatureFlags", [] ) if not potential_feature_flags: return {} try: client_feature_flags = json.loads(potential_feature_flags[0]) except json.JSONDecodeError: raise errors.InvalidArgumentError( "tensorBoardFeatureFlags cannot be JSON decoded." ) if not isinstance(client_feature_flags, dict): raise errors.InvalidArgumentError( "tensorBoardFeatureFlags cannot be decoded to a dict." ) return client_feature_flags