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optimizely/python-sdk | optimizely/bucketer.py | Bucketer.bucket | def bucket(self, experiment, user_id, bucketing_id):
""" For a given experiment and bucketing ID determines variation to be shown to user.
Args:
experiment: Object representing the experiment for which user is to be bucketed.
user_id: ID for user.
bucketing_id: ID to be used for bucketing the... | python | def bucket(self, experiment, user_id, bucketing_id):
""" For a given experiment and bucketing ID determines variation to be shown to user.
Args:
experiment: Object representing the experiment for which user is to be bucketed.
user_id: ID for user.
bucketing_id: ID to be used for bucketing the... | [
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig._generate_key_map | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
Returns... | python | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig._deserialize_audience | def _deserialize_audience(audience_map):
""" Helper method to de-serialize and populate audience map with the condition list and structure.
Args:
audience_map: Dict mapping audience ID to audience object.
Returns:
Dict additionally consisting of condition list and structure on every audience o... | python | def _deserialize_audience(audience_map):
""" Helper method to de-serialize and populate audience map with the condition list and structure.
Args:
audience_map: Dict mapping audience ID to audience object.
Returns:
Dict additionally consisting of condition list and structure on every audience o... | [
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_typecast_value | def get_typecast_value(self, value, type):
""" Helper method to determine actual value based on type of feature variable.
Args:
value: Value in string form as it was parsed from datafile.
type: Type denoting the feature flag type.
Return:
Value type-casted based on type of feature variab... | python | def get_typecast_value(self, value, type):
""" Helper method to determine actual value based on type of feature variable.
Args:
value: Value in string form as it was parsed from datafile.
type: Type denoting the feature flag type.
Return:
Value type-casted based on type of feature variab... | [
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_experiment_from_key | def get_experiment_from_key(self, experiment_key):
""" Get experiment for the provided experiment key.
Args:
experiment_key: Experiment key for which experiment is to be determined.
Returns:
Experiment corresponding to the provided experiment key.
"""
experiment = self.experiment_key_... | python | def get_experiment_from_key(self, experiment_key):
""" Get experiment for the provided experiment key.
Args:
experiment_key: Experiment key for which experiment is to be determined.
Returns:
Experiment corresponding to the provided experiment key.
"""
experiment = self.experiment_key_... | [
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_experiment_from_id | def get_experiment_from_id(self, experiment_id):
""" Get experiment for the provided experiment ID.
Args:
experiment_id: Experiment ID for which experiment is to be determined.
Returns:
Experiment corresponding to the provided experiment ID.
"""
experiment = self.experiment_id_map.get... | python | def get_experiment_from_id(self, experiment_id):
""" Get experiment for the provided experiment ID.
Args:
experiment_id: Experiment ID for which experiment is to be determined.
Returns:
Experiment corresponding to the provided experiment ID.
"""
experiment = self.experiment_id_map.get... | [
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_group | def get_group(self, group_id):
""" Get group for the provided group ID.
Args:
group_id: Group ID for which group is to be determined.
Returns:
Group corresponding to the provided group ID.
"""
group = self.group_id_map.get(group_id)
if group:
return group
self.logger.e... | python | def get_group(self, group_id):
""" Get group for the provided group ID.
Args:
group_id: Group ID for which group is to be determined.
Returns:
Group corresponding to the provided group ID.
"""
group = self.group_id_map.get(group_id)
if group:
return group
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_audience | def get_audience(self, audience_id):
""" Get audience object for the provided audience ID.
Args:
audience_id: ID of the audience.
Returns:
Dict representing the audience.
"""
audience = self.audience_id_map.get(audience_id)
if audience:
return audience
self.logger.error... | python | def get_audience(self, audience_id):
""" Get audience object for the provided audience ID.
Args:
audience_id: ID of the audience.
Returns:
Dict representing the audience.
"""
audience = self.audience_id_map.get(audience_id)
if audience:
return audience
self.logger.error... | [
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_variation_from_key | def get_variation_from_key(self, experiment_key, variation_key):
""" Get variation given experiment and variation key.
Args:
experiment: Key representing parent experiment of variation.
variation_key: Key representing the variation.
Returns
Object representing the variation.
"""
... | python | def get_variation_from_key(self, experiment_key, variation_key):
""" Get variation given experiment and variation key.
Args:
experiment: Key representing parent experiment of variation.
variation_key: Key representing the variation.
Returns
Object representing the variation.
"""
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_variation_from_id | def get_variation_from_id(self, experiment_key, variation_id):
""" Get variation given experiment and variation ID.
Args:
experiment: Key representing parent experiment of variation.
variation_id: ID representing the variation.
Returns
Object representing the variation.
"""
vari... | python | def get_variation_from_id(self, experiment_key, variation_id):
""" Get variation given experiment and variation ID.
Args:
experiment: Key representing parent experiment of variation.
variation_id: ID representing the variation.
Returns
Object representing the variation.
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_event | def get_event(self, event_key):
""" Get event for the provided event key.
Args:
event_key: Event key for which event is to be determined.
Returns:
Event corresponding to the provided event key.
"""
event = self.event_key_map.get(event_key)
if event:
return event
self.l... | python | def get_event(self, event_key):
""" Get event for the provided event key.
Args:
event_key: Event key for which event is to be determined.
Returns:
Event corresponding to the provided event key.
"""
event = self.event_key_map.get(event_key)
if event:
return event
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_attribute_id | def get_attribute_id(self, attribute_key):
""" Get attribute ID for the provided attribute key.
Args:
attribute_key: Attribute key for which attribute is to be fetched.
Returns:
Attribute ID corresponding to the provided attribute key.
"""
attribute = self.attribute_key_map.get(attrib... | python | def get_attribute_id(self, attribute_key):
""" Get attribute ID for the provided attribute key.
Args:
attribute_key: Attribute key for which attribute is to be fetched.
Returns:
Attribute ID corresponding to the provided attribute key.
"""
attribute = self.attribute_key_map.get(attrib... | [
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_feature_from_key | def get_feature_from_key(self, feature_key):
""" Get feature for the provided feature key.
Args:
feature_key: Feature key for which feature is to be fetched.
Returns:
Feature corresponding to the provided feature key.
"""
feature = self.feature_key_map.get(feature_key)
if feature:... | python | def get_feature_from_key(self, feature_key):
""" Get feature for the provided feature key.
Args:
feature_key: Feature key for which feature is to be fetched.
Returns:
Feature corresponding to the provided feature key.
"""
feature = self.feature_key_map.get(feature_key)
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_rollout_from_id | def get_rollout_from_id(self, rollout_id):
""" Get rollout for the provided ID.
Args:
rollout_id: ID of the rollout to be fetched.
Returns:
Rollout corresponding to the provided ID.
"""
layer = self.rollout_id_map.get(rollout_id)
if layer:
return layer
self.logger.error... | python | def get_rollout_from_id(self, rollout_id):
""" Get rollout for the provided ID.
Args:
rollout_id: ID of the rollout to be fetched.
Returns:
Rollout corresponding to the provided ID.
"""
layer = self.rollout_id_map.get(rollout_id)
if layer:
return layer
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_variable_value_for_variation | def get_variable_value_for_variation(self, variable, variation):
""" Get the variable value for the given variation.
Args:
variable: The Variable for which we are getting the value.
variation: The Variation for which we are getting the variable value.
Returns:
The variable value or None ... | python | def get_variable_value_for_variation(self, variable, variation):
""" Get the variable value for the given variation.
Args:
variable: The Variable for which we are getting the value.
variation: The Variation for which we are getting the variable value.
Returns:
The variable value or None ... | [
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_variable_for_feature | def get_variable_for_feature(self, feature_key, variable_key):
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Args:
feature_key: The key of the feature for which we are getting the variable.
variable_key: The key of the variable we are getting.
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""" Get the variable with the given variable key for the given feature.
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feature_key: The key of the feature for which we are getting the variable.
variable_key: The key of the variable we are getting.
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experiment_key: Key for experiment.
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optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_forced_variation | def get_forced_variation(self, experiment_key, user_id):
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experiment_key: Key for experiment.
user_id: The user ID.
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""" Gets the forced variation key for the given user and experiment.
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experiment_key: Key for experiment.
user_id: The user ID.
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optimizely/python-sdk | optimizely/event_dispatcher.py | EventDispatcher.dispatch_event | def dispatch_event(event):
""" Dispatch the event being represented by the Event object.
Args:
event: Object holding information about the request to be dispatched to the Optimizely backend.
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event: Object holding information about the request to be dispatched to the Optimizely backend.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely._validate_instantiation_options | def _validate_instantiation_options(self, datafile, skip_json_validation):
""" Helper method to validate all instantiation parameters.
Args:
datafile: JSON string representing the project.
skip_json_validation: Boolean representing whether JSON schema validation needs to be skipped or not.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely._validate_user_inputs | def _validate_user_inputs(self, attributes=None, event_tags=None):
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attributes: Dict representing user attributes.
event_tags: Dict representing metadata associated with an event.
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event_tags: Dict representing metadata associated with an event.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely._send_impression_event | def _send_impression_event(self, experiment, variation, user_id, attributes):
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experiment: Experiment for which impression event is being sent.
variation: Variation picked for user for the given experiment.
user_id: ID for user.
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experiment: Experiment for which impression event is being sent.
variation: Variation picked for user for the given experiment.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely._get_feature_variable_for_type | def _get_feature_variable_for_type(self, feature_key, variable_key, variable_type, user_id, attributes):
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feature_key: Key of the feature whose variable's value is being accessed.
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feature_key: Key of the feature whose variable's value is being accessed.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely.activate | def activate(self, experiment_key, user_id, attributes=None):
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Args:
experiment_key: Experiment which needs to be activated.
user_id: ID for user.
attributes: Dict representing user attributes and values which need to be recorded.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely.track | def track(self, event_key, user_id, attributes=None, event_tags=None):
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event_key: Event key representing the event which needs to be recorded.
user_id: ID for user.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_variation | def get_variation(self, experiment_key, user_id, attributes=None):
""" Gets variation where user will be bucketed.
Args:
experiment_key: Experiment for which user variation needs to be determined.
user_id: ID for user.
attributes: Dict representing user attributes.
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experiment_key: Experiment for which user variation needs to be determined.
user_id: ID for user.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely.is_feature_enabled | def is_feature_enabled(self, feature_key, user_id, attributes=None):
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Args:
feature_key: The key of the feature for which we are determining if it is enabled or not for the given user.
user_id: ID for user.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_enabled_features | def get_enabled_features(self, user_id, attributes=None):
""" Returns the list of features that are enabled for the user.
Args:
user_id: ID for user.
attributes: Dict representing user attributes.
Returns:
A list of the keys of the features that are enabled for the user.
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""" Returns the list of features that are enabled for the user.
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user_id: ID for user.
attributes: Dict representing user attributes.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_feature_variable_boolean | def get_feature_variable_boolean(self, feature_key, variable_key, user_id, attributes=None):
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_feature_variable_double | def get_feature_variable_double(self, feature_key, variable_key, user_id, attributes=None):
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feature_key: Key of the feature whose variable's value is being accessed.
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experiment_key: A string key identifying the experiment.
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optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_forced_variation | def get_forced_variation(self, experiment_key, user_id):
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experiment_key: A string key identifying the experiment.
user_id: The user ID.
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""" Gets the forced variation for a given user and experiment.
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experiment_key: A string key identifying the experiment.
user_id: The user ID.
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optimizely/python-sdk | optimizely/helpers/audience.py | is_user_in_experiment | def is_user_in_experiment(config, experiment, attributes, logger):
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config: project_config.ProjectConfig object representing the project.
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optimizely/python-sdk | optimizely/event_builder.py | BaseEventBuilder._get_common_params | def _get_common_params(self, user_id, attributes):
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user_id: ID for user.
attributes: Dict representing user attributes and values which need to be recorded.
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user_id: ID for user.
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optimizely/python-sdk | optimizely/event_builder.py | EventBuilder._get_required_params_for_impression | def _get_required_params_for_impression(self, experiment, variation_id):
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experiment: Experiment for which impression needs to be recorded.
variation_id: ID for variation which would be presented to user.
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experiment: Experiment for which impression needs to be recorded.
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optimizely/python-sdk | optimizely/event_builder.py | EventBuilder._get_required_params_for_conversion | def _get_required_params_for_conversion(self, event_key, event_tags):
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event_key: Key representing the event which needs to be recorded.
event_tags: Dict representing metadata associated with the event.
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event_key: Key representing the event which needs to be recorded.
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optimizely/python-sdk | optimizely/event_builder.py | EventBuilder.create_impression_event | def create_impression_event(self, experiment, variation_id, user_id, attributes):
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experiment: Experiment for which impression needs to be recorded.
variation_id: ID for variation which would be presented to user.
user_id: I... | python | def create_impression_event(self, experiment, variation_id, user_id, attributes):
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event_key: Key representing the event which needs to be recorded.
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optimizely/python-sdk | optimizely/helpers/condition.py | _audience_condition_deserializer | def _audience_condition_deserializer(obj_dict):
""" Deserializer defining how dict objects need to be decoded for audience conditions.
Args:
obj_dict: Dict representing one audience condition.
Returns:
List consisting of condition key with corresponding value, type and match.
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obj_dict: Dict representing one audience condition.
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optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator._get_condition_json | def _get_condition_json(self, index):
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index: Index of the condition.
Returns:
String: Audience condition JSON.
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optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator.is_value_type_valid_for_exact_conditions | def is_value_type_valid_for_exact_conditions(self, value):
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Args:
value: Value to validate.
Returns:
Boolean: True if value is a string, boolean, or number. Otherwise False.
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optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator.exists_evaluator | def exists_evaluator(self, index):
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index: Index of the condition to be evaluated.
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optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator.greater_than_evaluator | def greater_than_evaluator(self, index):
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index: Index of the condition to be evaluated.
Returns:
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optimizely/python-sdk | optimizely/helpers/condition.py | ConditionDecoder.object_hook | def object_hook(self, object_dict):
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optimizely/python-sdk | optimizely/decision_service.py | DecisionService._get_bucketing_id | def _get_bucketing_id(self, user_id, attributes):
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user_id: ID for user.
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optimizely/python-sdk | optimizely/decision_service.py | DecisionService.get_forced_variation | def get_forced_variation(self, experiment, user_id):
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experiment: Object representing the experiment for which user is to be bucketed.
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experiment: Object representing the experiment for which user is to be bucketed.
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optimizely/python-sdk | optimizely/decision_service.py | DecisionService.get_experiment_in_group | def get_experiment_in_group(self, group, bucketing_id):
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optimizely/python-sdk | optimizely/notification_center.py | NotificationCenter.add_notification_listener | def add_notification_listener(self, notification_type, notification_callback):
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notification_type: A string representing the notification type from .helpers.enums.NotificationTypes
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optimizely/python-sdk | optimizely/notification_center.py | NotificationCenter.remove_notification_listener | def remove_notification_listener(self, notification_id):
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notification_id: The numeric id passed back from add_notification_listener
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The function returns boolean true if found and removed, false otherwise.
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optimizely/python-sdk | optimizely/notification_center.py | NotificationCenter.send_notifications | def send_notifications(self, notification_type, *args):
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optimizely/python-sdk | optimizely/helpers/condition_tree_evaluator.py | and_evaluator | def and_evaluator(conditions, leaf_evaluator):
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optimizely/python-sdk | optimizely/helpers/condition_tree_evaluator.py | not_evaluator | def not_evaluator(conditions, leaf_evaluator):
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optimizely/python-sdk | optimizely/helpers/condition_tree_evaluator.py | evaluate | def evaluate(conditions, leaf_evaluator):
""" Top level method to evaluate conditions.
Args:
conditions: Nested array of and/or conditions, or a single leaf condition value of any type.
Example: ['and', '0', ['or', '1', '2']]
leaf_evaluator: Function which will be called to evaluate leaf co... | python | def evaluate(conditions, leaf_evaluator):
""" Top level method to evaluate conditions.
Args:
conditions: Nested array of and/or conditions, or a single leaf condition value of any type.
Example: ['and', '0', ['or', '1', '2']]
leaf_evaluator: Function which will be called to evaluate leaf co... | [
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Parisson/TimeSide | timeside/core/analyzer.py | data_objet_class | def data_objet_class(data_mode='value', time_mode='framewise'):
"""
Factory function for Analyzer result
"""
classes_table = {('value', 'global'): GlobalValueObject,
('value', 'event'): EventValueObject,
('value', 'segment'): SegmentValueObject,
... | python | def data_objet_class(data_mode='value', time_mode='framewise'):
"""
Factory function for Analyzer result
"""
classes_table = {('value', 'global'): GlobalValueObject,
('value', 'event'): EventValueObject,
('value', 'segment'): SegmentValueObject,
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Parisson/TimeSide | timeside/core/analyzer.py | JSON_NumpyArrayEncoder | def JSON_NumpyArrayEncoder(obj):
'''Define Specialize JSON encoder for numpy array'''
if isinstance(obj, np.ndarray):
return {'numpyArray': obj.tolist(),
'dtype': obj.dtype.__str__()}
elif isinstance(obj, np.generic):
return np.asscalar(obj)
else:
print type(obj)
... | python | def JSON_NumpyArrayEncoder(obj):
'''Define Specialize JSON encoder for numpy array'''
if isinstance(obj, np.ndarray):
return {'numpyArray': obj.tolist(),
'dtype': obj.dtype.__str__()}
elif isinstance(obj, np.generic):
return np.asscalar(obj)
else:
print type(obj)
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Parisson/TimeSide | timeside/core/analyzer.py | AnalyzerResult.render | def render(self):
'''Render a matplotlib figure from the analyzer result
Return the figure, use fig.show() to display if neeeded
'''
fig, ax = plt.subplots()
self.data_object._render_plot(ax)
return fig | python | def render(self):
'''Render a matplotlib figure from the analyzer result
Return the figure, use fig.show() to display if neeeded
'''
fig, ax = plt.subplots()
self.data_object._render_plot(ax)
return fig | [
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Parisson/TimeSide | timeside/core/analyzer.py | Analyzer.new_result | def new_result(self, data_mode='value', time_mode='framewise'):
'''
Create a new result
Attributes
----------
data_object : MetadataObject
id_metadata : MetadataObject
audio_metadata : MetadataObject
frame_metadata : MetadataObject
label_metadata ... | python | def new_result(self, data_mode='value', time_mode='framewise'):
'''
Create a new result
Attributes
----------
data_object : MetadataObject
id_metadata : MetadataObject
audio_metadata : MetadataObject
frame_metadata : MetadataObject
label_metadata ... | [
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label_metadata : MetadataObject
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Parisson/TimeSide | timeside/core/preprocessors.py | downmix_to_mono | def downmix_to_mono(process_func):
'''
Pre-processing decorator that downmixes frames from multi-channel to mono
Downmix is achieved by averaging all channels
>>> from timeside.core.preprocessors import downmix_to_mono
>>> @downmix_to_mono
... def process(analyzer,frames,eod):
... prin... | python | def downmix_to_mono(process_func):
'''
Pre-processing decorator that downmixes frames from multi-channel to mono
Downmix is achieved by averaging all channels
>>> from timeside.core.preprocessors import downmix_to_mono
>>> @downmix_to_mono
... def process(analyzer,frames,eod):
... prin... | [
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Downmix is achieved by averaging all channels
>>> from timeside.core.preprocessors import downmix_to_mono
>>> @downmix_to_mono
... def process(analyzer,frames,eod):
... print 'Frames, eod inside process :'
... pr... | [
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Parisson/TimeSide | timeside/core/preprocessors.py | frames_adapter | def frames_adapter(process_func):
'''
Pre-processing decorator that adapt frames to match input_blocksize and
input_stepsize of the decorated analyzer
>>> from timeside.core.preprocessors import frames_adapter
>>> @frames_adapter
... def process(analyzer,frames,eod):
... analyzer.frames... | python | def frames_adapter(process_func):
'''
Pre-processing decorator that adapt frames to match input_blocksize and
input_stepsize of the decorated analyzer
>>> from timeside.core.preprocessors import frames_adapter
>>> @frames_adapter
... def process(analyzer,frames,eod):
... analyzer.frames... | [
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Parisson/TimeSide | timeside/server/models.py | Item.get_uri | def get_uri(self):
"""Return the Item source"""
if self.source_file and os.path.exists(self.source_file.path):
return self.source_file.path
elif self.source_url:
return self.source_url
return None | python | def get_uri(self):
"""Return the Item source"""
if self.source_file and os.path.exists(self.source_file.path):
return self.source_file.path
elif self.source_url:
return self.source_url
return None | [
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Parisson/TimeSide | timeside/server/models.py | Item.get_audio_duration | def get_audio_duration(self):
"""
Return item audio duration
"""
decoder = timeside.core.get_processor('file_decoder')(
uri=self.get_uri())
return decoder.uri_total_duration | python | def get_audio_duration(self):
"""
Return item audio duration
"""
decoder = timeside.core.get_processor('file_decoder')(
uri=self.get_uri())
return decoder.uri_total_duration | [
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Parisson/TimeSide | timeside/server/models.py | Item.get_results_path | def get_results_path(self):
"""
Return Item result path
"""
result_path = os.path.join(RESULTS_ROOT, self.uuid)
if not os.path.exists(result_path):
os.makedirs(result_path)
return result_path | python | def get_results_path(self):
"""
Return Item result path
"""
result_path = os.path.join(RESULTS_ROOT, self.uuid)
if not os.path.exists(result_path):
os.makedirs(result_path)
return result_path | [
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Parisson/TimeSide | timeside/plugins/decoder/utils.py | get_uri | def get_uri(source):
"""
Check a media source as a valid file or uri and return the proper uri
"""
import gst
src_info = source_info(source)
if src_info['is_file']: # Is this a file?
return get_uri(src_info['uri'])
elif gst.uri_is_valid(source): # Is this a valid URI source for... | python | def get_uri(source):
"""
Check a media source as a valid file or uri and return the proper uri
"""
import gst
src_info = source_info(source)
if src_info['is_file']: # Is this a file?
return get_uri(src_info['uri'])
elif gst.uri_is_valid(source): # Is this a valid URI source for... | [
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Parisson/TimeSide | timeside/plugins/decoder/utils.py | sha1sum_file | def sha1sum_file(filename):
'''
Return the secure hash digest with sha1 algorithm for a given file
>>> from timeside.core.tools.test_samples import samples
>>> wav_file = samples["C4_scale.wav"]
>>> print sha1sum_file(wav_file)
a598e78d0b5c90da54a77e34c083abdcd38d42ba
'''
import hashlib... | python | def sha1sum_file(filename):
'''
Return the secure hash digest with sha1 algorithm for a given file
>>> from timeside.core.tools.test_samples import samples
>>> wav_file = samples["C4_scale.wav"]
>>> print sha1sum_file(wav_file)
a598e78d0b5c90da54a77e34c083abdcd38d42ba
'''
import hashlib... | [
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>>> print sha1sum_file(wav_file)
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Parisson/TimeSide | timeside/plugins/decoder/utils.py | sha1sum_url | def sha1sum_url(url):
'''Return the secure hash digest with sha1 algorithm for a given url
>>> url = "https://github.com/yomguy/timeside-samples/raw/master/samples/guitar.wav"
>>> print sha1sum_url(url)
08301c3f9a8d60926f31e253825cc74263e52ad1
'''
import hashlib
import urllib
from cont... | python | def sha1sum_url(url):
'''Return the secure hash digest with sha1 algorithm for a given url
>>> url = "https://github.com/yomguy/timeside-samples/raw/master/samples/guitar.wav"
>>> print sha1sum_url(url)
08301c3f9a8d60926f31e253825cc74263e52ad1
'''
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import urllib
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Parisson/TimeSide | timeside/plugins/decoder/utils.py | sha1sum_numpy | def sha1sum_numpy(np_array):
'''
Return the secure hash digest with sha1 algorithm for a numpy array
'''
import hashlib
return hashlib.sha1(np_array.view(np.uint8)).hexdigest() | python | def sha1sum_numpy(np_array):
'''
Return the secure hash digest with sha1 algorithm for a numpy array
'''
import hashlib
return hashlib.sha1(np_array.view(np.uint8)).hexdigest() | [
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Parisson/TimeSide | timeside/core/tools/package.py | import_module_with_exceptions | def import_module_with_exceptions(name, package=None):
"""Wrapper around importlib.import_module to import TimeSide subpackage
and ignoring ImportError if Aubio, Yaafe and Vamp Host are not available"""
from timeside.core import _WITH_AUBIO, _WITH_YAAFE, _WITH_VAMP
if name.count('.server.'):
#... | python | def import_module_with_exceptions(name, package=None):
"""Wrapper around importlib.import_module to import TimeSide subpackage
and ignoring ImportError if Aubio, Yaafe and Vamp Host are not available"""
from timeside.core import _WITH_AUBIO, _WITH_YAAFE, _WITH_VAMP
if name.count('.server.'):
#... | [
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Parisson/TimeSide | timeside/core/tools/package.py | check_vamp | def check_vamp():
"Check Vamp host availability"
try:
from timeside.plugins.analyzer.externals import vamp_plugin
except VampImportError:
warnings.warn('Vamp host is not available', ImportWarning,
stacklevel=2)
_WITH_VAMP = False
else:
_WITH_VAMP = ... | python | def check_vamp():
"Check Vamp host availability"
try:
from timeside.plugins.analyzer.externals import vamp_plugin
except VampImportError:
warnings.warn('Vamp host is not available', ImportWarning,
stacklevel=2)
_WITH_VAMP = False
else:
_WITH_VAMP = ... | [
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Parisson/TimeSide | timeside/plugins/grapher/utils.py | im_watermark | def im_watermark(im, inputtext, font=None, color=None, opacity=.6, margin=(30, 30)):
"""imprints a PIL image with the indicated text in lower-right corner"""
if im.mode != "RGBA":
im = im.convert("RGBA")
textlayer = Image.new("RGBA", im.size, (0, 0, 0, 0))
textdraw = ImageDraw.Draw(textlayer)
... | python | def im_watermark(im, inputtext, font=None, color=None, opacity=.6, margin=(30, 30)):
"""imprints a PIL image with the indicated text in lower-right corner"""
if im.mode != "RGBA":
im = im.convert("RGBA")
textlayer = Image.new("RGBA", im.size, (0, 0, 0, 0))
textdraw = ImageDraw.Draw(textlayer)
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Parisson/TimeSide | timeside/plugins/analyzer/utils.py | nextpow2 | def nextpow2(value):
"""Compute the nearest power of two greater or equal to the input value"""
if value >= 1:
return 2**np.ceil(np.log2(value)).astype(int)
elif value > 0:
return 1
elif value == 0:
return 0
else:
raise ValueError('Value must be positive') | python | def nextpow2(value):
"""Compute the nearest power of two greater or equal to the input value"""
if value >= 1:
return 2**np.ceil(np.log2(value)).astype(int)
elif value > 0:
return 1
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return 0
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Parisson/TimeSide | timeside/core/processor.py | FixedSizeInputAdapter.blocksize | def blocksize(self, input_totalframes):
"""Return the total number of frames that this adapter will output
according to the input_totalframes argument"""
blocksize = input_totalframes
if self.pad:
mod = input_totalframes % self.buffer_size
if mod:
... | python | def blocksize(self, input_totalframes):
"""Return the total number of frames that this adapter will output
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blocksize = input_totalframes
if self.pad:
mod = input_totalframes % self.buffer_size
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Parisson/TimeSide | timeside/core/processor.py | ProcessPipe.append_processor | def append_processor(self, proc, source_proc=None):
"Append a new processor to the pipe"
if source_proc is None and len(self.processors):
source_proc = self.processors[0]
if source_proc and not isinstance(source_proc, Processor):
raise TypeError('source_proc must be a Pr... | python | def append_processor(self, proc, source_proc=None):
"Append a new processor to the pipe"
if source_proc is None and len(self.processors):
source_proc = self.processors[0]
if source_proc and not isinstance(source_proc, Processor):
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Parisson/TimeSide | timeside/plugins/analyzer/externals/vamp_plugin.py | simple_host_process | def simple_host_process(argslist):
"""Call vamp-simple-host"""
vamp_host = 'vamp-simple-host'
command = [vamp_host]
command.extend(argslist)
# try ?
stdout = subprocess.check_output(command,
stderr=subprocess.STDOUT).splitlines()
return stdout | python | def simple_host_process(argslist):
"""Call vamp-simple-host"""
vamp_host = 'vamp-simple-host'
command = [vamp_host]
command.extend(argslist)
# try ?
stdout = subprocess.check_output(command,
stderr=subprocess.STDOUT).splitlines()
return stdout | [
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Parisson/TimeSide | timeside/plugins/grapher/spectrogram_lin.py | SpectrogramLinear.set_scale | def set_scale(self):
"""generate the lookup which translates y-coordinate to fft-bin"""
f_min = float(self.lower_freq)
f_max = float(self.higher_freq)
y_min = f_min
y_max = f_max
for y in range(self.image_height):
freq = y_min + y / (self.image_height - 1.0) ... | python | def set_scale(self):
"""generate the lookup which translates y-coordinate to fft-bin"""
f_min = float(self.lower_freq)
f_max = float(self.higher_freq)
y_min = f_min
y_max = f_max
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Parisson/TimeSide | timeside/core/tools/hdf5.py | dict_from_hdf5 | def dict_from_hdf5(dict_like, h5group):
"""
Load a dictionnary-like object from a h5 file group
"""
# Read attributes
for name, value in h5group.attrs.items():
dict_like[name] = value | python | def dict_from_hdf5(dict_like, h5group):
"""
Load a dictionnary-like object from a h5 file group
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# Read attributes
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Parisson/TimeSide | timeside/plugins/decoder/array.py | ArrayDecoder.get_frames | def get_frames(self):
"Define an iterator that will return frames at the given blocksize"
nb_frames = self.input_totalframes // self.output_blocksize
if self.input_totalframes % self.output_blocksize == 0:
nb_frames -= 1 # Last frame must send eod=True
for index in xrange(... | python | def get_frames(self):
"Define an iterator that will return frames at the given blocksize"
nb_frames = self.input_totalframes // self.output_blocksize
if self.input_totalframes % self.output_blocksize == 0:
nb_frames -= 1 # Last frame must send eod=True
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Parisson/TimeSide | timeside/core/component.py | implementations | def implementations(interface, recurse=True, abstract=False):
"""Returns the components implementing interface, and if recurse, any of
the descendants of interface. If abstract is True, also return the
abstract implementations."""
result = []
find_implementations(interface, recurse, abstract, result... | python | def implementations(interface, recurse=True, abstract=False):
"""Returns the components implementing interface, and if recurse, any of
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Parisson/TimeSide | timeside/core/component.py | find_implementations | def find_implementations(interface, recurse, abstract, result):
"""Find implementations of an interface or of one of its descendants and
extend result with the classes found."""
for item in MetaComponent.implementations:
if (item['interface'] == interface and (abstract or not item['abstract'])):
... | python | def find_implementations(interface, recurse, abstract, result):
"""Find implementations of an interface or of one of its descendants and
extend result with the classes found."""
for item in MetaComponent.implementations:
if (item['interface'] == interface and (abstract or not item['abstract'])):
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Parisson/TimeSide | timeside/core/grapher.py | Grapher.draw_peaks | def draw_peaks(self, x, peaks, line_color):
"""Draw 2 peaks at x"""
y1 = self.image_height * 0.5 - peaks[0] * (self.image_height - 4) * 0.5
y2 = self.image_height * 0.5 - peaks[1] * (self.image_height - 4) * 0.5
if self.previous_y:
self.draw.line(
[self.prev... | python | def draw_peaks(self, x, peaks, line_color):
"""Draw 2 peaks at x"""
y1 = self.image_height * 0.5 - peaks[0] * (self.image_height - 4) * 0.5
y2 = self.image_height * 0.5 - peaks[1] * (self.image_height - 4) * 0.5
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Parisson/TimeSide | timeside/core/grapher.py | Grapher.draw_peaks_inverted | def draw_peaks_inverted(self, x, peaks, line_color):
"""Draw 2 inverted peaks at x"""
y1 = self.image_height * 0.5 - peaks[0] * (self.image_height - 4) * 0.5
y2 = self.image_height * 0.5 - peaks[1] * (self.image_height - 4) * 0.5
if self.previous_y and x < self.image_width - 1:
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"""Draw 2 inverted peaks at x"""
y1 = self.image_height * 0.5 - peaks[0] * (self.image_height - 4) * 0.5
y2 = self.image_height * 0.5 - peaks[1] * (self.image_height - 4) * 0.5
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Parisson/TimeSide | timeside/core/grapher.py | Grapher.draw_anti_aliased_pixels | def draw_anti_aliased_pixels(self, x, y1, y2, color):
""" vertical anti-aliasing at y1 and y2 """
y_max = max(y1, y2)
y_max_int = int(y_max)
alpha = y_max - y_max_int
if alpha > 0.0 and alpha < 1.0 and y_max_int + 1 < self.image_height:
current_pix = self.pixel[int(... | python | def draw_anti_aliased_pixels(self, x, y1, y2, color):
""" vertical anti-aliasing at y1 and y2 """
y_max = max(y1, y2)
y_max_int = int(y_max)
alpha = y_max - y_max_int
if alpha > 0.0 and alpha < 1.0 and y_max_int + 1 < self.image_height:
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Parisson/TimeSide | timeside/plugins/grapher/spectrogram_log.py | SpectrogramLog.post_process | def post_process(self):
""" Apply last 2D transforms"""
self.image.putdata(self.pixels)
self.image = self.image.transpose(Image.ROTATE_90) | python | def post_process(self):
""" Apply last 2D transforms"""
self.image.putdata(self.pixels)
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Parisson/TimeSide | timeside/plugins/encoder/mp3.py | Mp3Encoder.write_metadata | def write_metadata(self):
"""Write all ID3v2.4 tags to file from self.metadata"""
import mutagen
from mutagen import id3
id3 = id3.ID3(self.filename)
for tag in self.metadata.keys():
value = self.metadata[tag]
frame = mutagen.id3.Frames[tag](3, value)
... | python | def write_metadata(self):
"""Write all ID3v2.4 tags to file from self.metadata"""
import mutagen
from mutagen import id3
id3 = id3.ID3(self.filename)
for tag in self.metadata.keys():
value = self.metadata[tag]
frame = mutagen.id3.Frames[tag](3, value)
... | [
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btimby/fulltext | fulltext/__main__.py | main | def main(args=sys.argv[1:]):
"""Extract text from a file.
Commands:
extract - extract text from path
check - make sure all deps are installed
Usage:
fulltext extract [-v] [-f] <path>...
fulltext check [-t]
Options:
-f, --file Open file first.
... | python | def main(args=sys.argv[1:]):
"""Extract text from a file.
Commands:
extract - extract text from path
check - make sure all deps are installed
Usage:
fulltext extract [-v] [-f] <path>...
fulltext check [-t]
Options:
-f, --file Open file first.
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fulltext extract [-v] [-f] <path>...
fulltext check [-t]
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btimby/fulltext | fulltext/__init__.py | is_binary | def is_binary(f):
"""Return True if binary mode."""
# NOTE: order matters here. We don't bail on Python 2 just yet. Both
# codecs.open() and io.open() can open in text mode, both set the encoding
# attribute. We must do that check first.
# If it has a decoding attribute with a value, it is text mod... | python | def is_binary(f):
"""Return True if binary mode."""
# NOTE: order matters here. We don't bail on Python 2 just yet. Both
# codecs.open() and io.open() can open in text mode, both set the encoding
# attribute. We must do that check first.
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btimby/fulltext | fulltext/__init__.py | handle_path | def handle_path(backend_inst, path, **kwargs):
"""
Handle a path.
Called by `get()` when provided a path. This function will prefer the
backend's `handle_path()` if one is provided Otherwise, it will open the
given path then use `handle_fobj()`.
"""
if callable(getattr(backend_inst, 'handle... | python | def handle_path(backend_inst, path, **kwargs):
"""
Handle a path.
Called by `get()` when provided a path. This function will prefer the
backend's `handle_path()` if one is provided Otherwise, it will open the
given path then use `handle_fobj()`.
"""
if callable(getattr(backend_inst, 'handle... | [
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btimby/fulltext | fulltext/__init__.py | handle_fobj | def handle_fobj(backend, f, **kwargs):
"""
Handle a file-like object.
Called by `get()` when provided a file-like. This function will prefer the
backend's `handle_fobj()` if one is provided. Otherwise, it will write the
data to a temporary file and call `handle_path()`.
"""
if not is_binary... | python | def handle_fobj(backend, f, **kwargs):
"""
Handle a file-like object.
Called by `get()` when provided a file-like. This function will prefer the
backend's `handle_fobj()` if one is provided. Otherwise, it will write the
data to a temporary file and call `handle_path()`.
"""
if not is_binary... | [
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btimby/fulltext | fulltext/__init__.py | backend_from_mime | def backend_from_mime(mime):
"""Determine backend module object from a mime string."""
try:
mod_name = MIMETYPE_TO_BACKENDS[mime]
except KeyError:
msg = "No handler for %r, defaulting to %r" % (mime, DEFAULT_MIME)
if 'FULLTEXT_TESTING' in os.environ:
warn(msg)
el... | python | def backend_from_mime(mime):
"""Determine backend module object from a mime string."""
try:
mod_name = MIMETYPE_TO_BACKENDS[mime]
except KeyError:
msg = "No handler for %r, defaulting to %r" % (mime, DEFAULT_MIME)
if 'FULLTEXT_TESTING' in os.environ:
warn(msg)
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btimby/fulltext | fulltext/__init__.py | backend_from_fname | def backend_from_fname(name):
"""Determine backend module object from a file name."""
ext = splitext(name)[1]
try:
mime = EXTS_TO_MIMETYPES[ext]
except KeyError:
try:
f = open(name, 'rb')
except IOError as e:
# The file may not exist, we are being asked... | python | def backend_from_fname(name):
"""Determine backend module object from a file name."""
ext = splitext(name)[1]
try:
mime = EXTS_TO_MIMETYPES[ext]
except KeyError:
try:
f = open(name, 'rb')
except IOError as e:
# The file may not exist, we are being asked... | [
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btimby/fulltext | fulltext/__init__.py | backend_from_fobj | def backend_from_fobj(f):
"""Determine backend module object from a file object."""
if magic is None:
warn("magic lib is not installed; assuming mime type %r" % (
DEFAULT_MIME))
return backend_from_mime(DEFAULT_MIME)
else:
offset = f.tell()
try:
f.seek... | python | def backend_from_fobj(f):
"""Determine backend module object from a file object."""
if magic is None:
warn("magic lib is not installed; assuming mime type %r" % (
DEFAULT_MIME))
return backend_from_mime(DEFAULT_MIME)
else:
offset = f.tell()
try:
f.seek... | [
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btimby/fulltext | fulltext/__init__.py | backend_inst_from_mod | def backend_inst_from_mod(mod, encoding, encoding_errors, kwargs):
"""Given a mod and a set of opts return an instantiated
Backend class.
"""
kw = dict(encoding=encoding, encoding_errors=encoding_errors,
kwargs=kwargs)
try:
klass = getattr(mod, "Backend")
except AttributeEr... | python | def backend_inst_from_mod(mod, encoding, encoding_errors, kwargs):
"""Given a mod and a set of opts return an instantiated
Backend class.
"""
kw = dict(encoding=encoding, encoding_errors=encoding_errors,
kwargs=kwargs)
try:
klass = getattr(mod, "Backend")
except AttributeEr... | [
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btimby/fulltext | fulltext/__init__.py | get | def get(path_or_file, default=SENTINAL, mime=None, name=None, backend=None,
encoding=None, encoding_errors=None, kwargs=None,
_wtitle=False):
"""
Get document full text.
Accepts a path or file-like object.
* If given, `default` is returned instead of an error.
* `backend` is eithe... | python | def get(path_or_file, default=SENTINAL, mime=None, name=None, backend=None,
encoding=None, encoding_errors=None, kwargs=None,
_wtitle=False):
"""
Get document full text.
Accepts a path or file-like object.
* If given, `default` is returned instead of an error.
* `backend` is eithe... | [
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btimby/fulltext | fulltext/util.py | hilite | def hilite(s, ok=True, bold=False):
"""Return an highlighted version of 'string'."""
if not term_supports_colors():
return s
attr = []
if ok is None: # no color
pass
elif ok: # green
attr.append('32')
else: # red
attr.append('31')
if bold:
attr.ap... | python | def hilite(s, ok=True, bold=False):
"""Return an highlighted version of 'string'."""
if not term_supports_colors():
return s
attr = []
if ok is None: # no color
pass
elif ok: # green
attr.append('32')
else: # red
attr.append('31')
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attr.ap... | [
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btimby/fulltext | fulltext/util.py | fobj_to_tempfile | def fobj_to_tempfile(f, suffix=''):
"""Context manager which copies a file object to disk and return its
name. When done the file is deleted.
"""
with tempfile.NamedTemporaryFile(
dir=TEMPDIR, suffix=suffix, delete=False) as t:
shutil.copyfileobj(f, t)
try:
yield t.name
... | python | def fobj_to_tempfile(f, suffix=''):
"""Context manager which copies a file object to disk and return its
name. When done the file is deleted.
"""
with tempfile.NamedTemporaryFile(
dir=TEMPDIR, suffix=suffix, delete=False) as t:
shutil.copyfileobj(f, t)
try:
yield t.name
... | [
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