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flowmachine.core.server.query_schemas.meaningful_locations

Class MeaningfulLocationsAggregateExposed

MeaningfulLocationsAggregateExposed(*, start_date: str, end_date: str, aggregation_unit: Union[flowmachine.core.spatial_unit.CellSpatialUnit, flowmachine.core.spatial_unit.GeomSpatialUnit], label: str, labels: Dict[str, Dict[str, dict]], tower_day_of_week_scores: Dict[str, float], tower_hour_of_day_scores: List[float], tower_cluster_radius: float = 1.0, tower_cluster_call_threshold: int = 0, event_types: Union[str, List[str], NoneType], subscriber_subset: Union[dict, NoneType] = None)
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Base class for exposed flowmachine queries. Note: this class and derived classes are not meant to be instantiated directly! Instead, they are instantiated automatically by the class FlowmachineQuerySchema. Example: FlowmachineQuerySchema().load({"query_kind": "dummy_query", "dummy_param": "foobar"})

Attributes

Methods

_flowmachine_query_obj

_flowmachine_query_obj
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Return the underlying flowmachine MeaningfulLocationsAggregate object.

Returns
  • ModalLocation

query_id

query_id
Source: flowmachine/core/server/query_schemas/base_exposed_query.py

Class MeaningfulLocationsAggregateSchema

MeaningfulLocationsAggregateSchema(*, only: Union[Sequence[str], Set[str], NoneType] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Union[Dict, NoneType] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Union[str, NoneType] = None)
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Base schema class with which to define custom schemas. Example usage: .. code-block:: python import datetime as dt from dataclasses import dataclass from marshmallow import Schema, fields @dataclass class Album: title: str release_date: dt.date class AlbumSchema(Schema): title = fields.Str() release_date = fields.Date() album = Album("Beggars Banquet", dt.date(1968, 12, 6)) schema = AlbumSchema() data = schema.dump(album) data # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'} :param only: Whitelist of the declared fields to select when instantiating the Schema. If None, all fields are used. Nested fields can be represented with dot delimiters. :param exclude: Blacklist of the declared fields to exclude when instantiating the Schema. If a field appears in both only and exclude, it is not used. Nested fields can be represented with dot delimiters. :param many: Should be set to True if obj is a collection so that the object will be serialized to a list. :param context: Optional context passed to :class:fields.Method and :class:fields.Function fields. :param load_only: Fields to skip during serialization (write-only fields) :param dump_only: Fields to skip during deserialization (read-only fields) :param partial: Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields. :param unknown: Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE. .. versionchanged:: 3.0.0 prefix parameter removed. .. versionchanged:: 2.0.0 __validators__, __preprocessors__, and __data_handlers__ are removed in favor of marshmallow.decorators.validates_schema, marshmallow.decorators.pre_load and marshmallow.decorators.post_dump. __accessor__ and __error_handler__ are deprecated. Implement the handle_error and get_attribute methods instead.

Attributes

Methods

dict_class

dict_class
Source: marshmallow/schema.py

set_class

set_class
Source: marshmallow/schema.py

Class MeaningfulLocationsBetweenDatesODMatrixExposed

MeaningfulLocationsBetweenDatesODMatrixExposed(*, start_date_a: str, end_date_a: str, start_date_b: str, end_date_b: str, aggregation_unit: Union[flowmachine.core.spatial_unit.CellSpatialUnit, flowmachine.core.spatial_unit.GeomSpatialUnit], label: str, labels: Dict[str, Dict[str, dict]], tower_day_of_week_scores: Dict[str, float], tower_hour_of_day_scores: List[float], tower_cluster_radius: float = 1.0, tower_cluster_call_threshold: int = 0, event_types: Union[str, List[str], NoneType], subscriber_subset: Union[dict, NoneType] = None)
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Base class for exposed flowmachine queries. Note: this class and derived classes are not meant to be instantiated directly! Instead, they are instantiated automatically by the class FlowmachineQuerySchema. Example: FlowmachineQuerySchema().load({"query_kind": "dummy_query", "dummy_param": "foobar"})

Attributes

Methods

_flowmachine_query_obj

_flowmachine_query_obj
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Return the underlying flowmachine MeaningfulLocationsAggregate object.

Returns
  • MeaningfulLocationsOD

query_id

query_id
Source: flowmachine/core/server/query_schemas/base_exposed_query.py

Class MeaningfulLocationsBetweenDatesODMatrixSchema

MeaningfulLocationsBetweenDatesODMatrixSchema(*, only: Union[Sequence[str], Set[str], NoneType] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Union[Dict, NoneType] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Union[str, NoneType] = None)
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Base schema class with which to define custom schemas. Example usage: .. code-block:: python import datetime as dt from dataclasses import dataclass from marshmallow import Schema, fields @dataclass class Album: title: str release_date: dt.date class AlbumSchema(Schema): title = fields.Str() release_date = fields.Date() album = Album("Beggars Banquet", dt.date(1968, 12, 6)) schema = AlbumSchema() data = schema.dump(album) data # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'} :param only: Whitelist of the declared fields to select when instantiating the Schema. If None, all fields are used. Nested fields can be represented with dot delimiters. :param exclude: Blacklist of the declared fields to exclude when instantiating the Schema. If a field appears in both only and exclude, it is not used. Nested fields can be represented with dot delimiters. :param many: Should be set to True if obj is a collection so that the object will be serialized to a list. :param context: Optional context passed to :class:fields.Method and :class:fields.Function fields. :param load_only: Fields to skip during serialization (write-only fields) :param dump_only: Fields to skip during deserialization (read-only fields) :param partial: Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields. :param unknown: Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE. .. versionchanged:: 3.0.0 prefix parameter removed. .. versionchanged:: 2.0.0 __validators__, __preprocessors__, and __data_handlers__ are removed in favor of marshmallow.decorators.validates_schema, marshmallow.decorators.pre_load and marshmallow.decorators.post_dump. __accessor__ and __error_handler__ are deprecated. Implement the handle_error and get_attribute methods instead.

Attributes

Methods

dict_class

dict_class
Source: marshmallow/schema.py

set_class

set_class
Source: marshmallow/schema.py

Class MeaningfulLocationsBetweenLabelODMatrixExposed

MeaningfulLocationsBetweenLabelODMatrixExposed(*, start_date: str, end_date: str, aggregation_unit: Union[flowmachine.core.spatial_unit.CellSpatialUnit, flowmachine.core.spatial_unit.GeomSpatialUnit], label_a: str, label_b: str, labels: Dict[str, Dict[str, dict]], tower_day_of_week_scores: Dict[str, float], tower_hour_of_day_scores: List[float], tower_cluster_radius: float = 1.0, tower_cluster_call_threshold: int = 0, event_types: Union[str, List[str], NoneType], subscriber_subset: Union[dict, NoneType] = None)
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Base class for exposed flowmachine queries. Note: this class and derived classes are not meant to be instantiated directly! Instead, they are instantiated automatically by the class FlowmachineQuerySchema. Example: FlowmachineQuerySchema().load({"query_kind": "dummy_query", "dummy_param": "foobar"})

Attributes

Methods

_flowmachine_query_obj

_flowmachine_query_obj
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Return the underlying flowmachine MeaningfulLocationsAggregate object.

Returns
  • MeaningfulLocationsOD

query_id

query_id
Source: flowmachine/core/server/query_schemas/base_exposed_query.py

Class MeaningfulLocationsBetweenLabelODMatrixSchema

MeaningfulLocationsBetweenLabelODMatrixSchema(*, only: Union[Sequence[str], Set[str], NoneType] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Union[Dict, NoneType] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Union[str, NoneType] = None)
Source: flowmachine/core/server/query_schemas/meaningful_locations.py

Base schema class with which to define custom schemas. Example usage: .. code-block:: python import datetime as dt from dataclasses import dataclass from marshmallow import Schema, fields @dataclass class Album: title: str release_date: dt.date class AlbumSchema(Schema): title = fields.Str() release_date = fields.Date() album = Album("Beggars Banquet", dt.date(1968, 12, 6)) schema = AlbumSchema() data = schema.dump(album) data # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'} :param only: Whitelist of the declared fields to select when instantiating the Schema. If None, all fields are used. Nested fields can be represented with dot delimiters. :param exclude: Blacklist of the declared fields to exclude when instantiating the Schema. If a field appears in both only and exclude, it is not used. Nested fields can be represented with dot delimiters. :param many: Should be set to True if obj is a collection so that the object will be serialized to a list. :param context: Optional context passed to :class:fields.Method and :class:fields.Function fields. :param load_only: Fields to skip during serialization (write-only fields) :param dump_only: Fields to skip during deserialization (read-only fields) :param partial: Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields. :param unknown: Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE. .. versionchanged:: 3.0.0 prefix parameter removed. .. versionchanged:: 2.0.0 __validators__, __preprocessors__, and __data_handlers__ are removed in favor of marshmallow.decorators.validates_schema, marshmallow.decorators.pre_load and marshmallow.decorators.post_dump. __accessor__ and __error_handler__ are deprecated. Implement the handle_error and get_attribute methods instead.

Attributes

Methods

dict_class

dict_class
Source: marshmallow/schema.py

set_class

set_class
Source: marshmallow/schema.py