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# 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
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