stravalib.model.BestEffort#
- pydantic model stravalib.model.BestEffort[source]#
Class representing a best effort (e.g. best time for 5k)
Show JSON schema
{ "title": "BestEffort", "description": "Class representing a best effort (e.g. best time for 5k)", "type": "object", "properties": { "pr_activity_id": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Pr Activity Id" }, "distance": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Distance" }, "elapsed_time": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Elapsed Time" }, "id": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Id" }, "is_kom": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": null, "title": "Is Kom" }, "start_date": { "anyOf": [ { "format": "date-time", "type": "string" }, { "type": "null" } ], "default": null, "title": "Start Date" }, "start_date_local": { "anyOf": [ { "format": "date-time", "type": "string" }, { "type": "null" } ], "default": null, "title": "Start Date Local" }, "activity": { "anyOf": [ { "$ref": "#/$defs/MetaActivity" }, { "type": "null" } ], "default": null }, "athlete": { "anyOf": [ { "$ref": "#/$defs/MetaAthlete" }, { "type": "null" } ], "default": null }, "average_cadence": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Average Cadence" }, "average_heartrate": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Average Heartrate" }, "average_watts": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Average Watts" }, "device_watts": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": null, "title": "Device Watts" }, "end_index": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "End Index" }, "hidden": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": null, "title": "Hidden" }, "kom_rank": { "anyOf": [ { "maximum": 10, "minimum": 1, "type": "integer" }, { "type": "null" } ], "default": null, "title": "Kom Rank" }, "max_heartrate": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Max Heartrate" }, "moving_time": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Moving Time" }, "name": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "title": "Name" }, "pr_rank": { "anyOf": [ { "maximum": 3, "minimum": 1, "type": "integer" }, { "type": "null" } ], "default": null, "title": "Pr Rank" }, "segment": { "anyOf": [ { "$ref": "#/$defs/SummarySegment" }, { "type": "null" } ], "default": null }, "start_index": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Start Index" } }, "$defs": { "AthletePrEffort": { "description": "An object that holds athlete PR effort attributes.", "properties": { "effort_count": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Effort Count" }, "pr_activity_id": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Pr Activity Id" }, "pr_date": { "anyOf": [ { "format": "date-time", "type": "string" }, { "type": "null" } ], "default": null, "title": "Pr Date" }, "pr_elapsed_time": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Pr Elapsed Time" }, "distance": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Distance" }, "start_date": { "anyOf": [ { "format": "date-time", "type": "string" }, { "type": "null" } ], "default": null, "title": "Start Date" }, "start_date_local": { "anyOf": [ { "format": "date-time", "type": "string" }, { "type": "null" } ], "default": null, "title": "Start Date Local" }, "is_kom": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": null, "title": "Is Kom" } }, "title": "AthletePrEffort", "type": "object" }, "AthleteSegmentStats": { "description": "A structure being returned for segment stats for current athlete.", "properties": { "pr_activity_id": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Pr Activity Id" }, "distance": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Distance" }, "elapsed_time": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Elapsed Time" }, "id": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Id" }, "is_kom": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": null, "title": "Is Kom" }, "start_date": { "anyOf": [ { "format": "date-time", "type": "string" }, { "type": "null" } ], "default": null, "title": "Start Date" }, "start_date_local": { "anyOf": [ { "format": "date-time", "type": "string" }, { "type": "null" } ], "default": null, "title": "Start Date Local" }, "effort_count": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Effort Count" }, "pr_date": { "anyOf": [ { "format": "date", "type": "string" }, { "type": "null" } ], "default": null, "title": "Pr Date" } }, "title": "AthleteSegmentStats", "type": "object" }, "LatLon": { "description": "Stores lat / lon values or None.", "items": { "type": "number" }, "maxItems": 2, "minItems": 2, "title": "LatLon", "type": "array" }, "MetaActivity": { "description": "Represents an identifiable activity with lazily loaded properties to\ncollect this activity's comments, zones, kudos and photos.", "properties": { "bound_client": { "anyOf": [ {}, { "type": "null" } ], "default": null, "title": "Bound Client" }, "id": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Id" } }, "title": "MetaActivity", "type": "object" }, "MetaAthlete": { "description": "Represents an identifiable athlete with lazily loaded property to obtain\nthis athlete's summary stats.", "properties": { "bound_client": { "anyOf": [ {}, { "type": "null" } ], "default": null, "title": "Bound Client" }, "id": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Id" }, "resource_state": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Resource State" } }, "title": "MetaAthlete", "type": "object" }, "RelaxedActivityType": { "description": "This object supports allowing an array of Literal values to be used for\nActivity Type. by default, the generated `strava_model` module only allows\na Literal that includes types: `Ride` and `Run`.", "enum": [ "AlpineSki", "BackcountrySki", "Canoeing", "Crossfit", "EBikeRide", "Elliptical", "Golf", "Handcycle", "Hike", "IceSkate", "InlineSkate", "Kayaking", "Kitesurf", "NordicSki", "Ride", "RockClimbing", "RollerSki", "Rowing", "Run", "Sail", "Skateboard", "Snowboard", "Snowshoe", "Soccer", "StairStepper", "StandUpPaddling", "Surfing", "Swim", "Velomobile", "VirtualRide", "VirtualRun", "Walk", "WeightTraining", "Wheelchair", "Windsurf", "Workout", "Yoga" ], "title": "RelaxedActivityType", "type": "string" }, "SummarySegment": { "description": "Contains summary information for a specific segment\n\nNotes\n-----\nSeveral attributes represent overrides from the superclass to support\naccurate typing.", "properties": { "bound_client": { "anyOf": [ {}, { "type": "null" } ], "default": null, "title": "Bound Client" }, "activity_type": { "anyOf": [ { "$ref": "#/$defs/RelaxedActivityType" }, { "type": "null" } ], "default": null }, "athlete_pr_effort": { "anyOf": [ { "$ref": "#/$defs/AthletePrEffort" }, { "type": "null" } ], "default": null }, "athlete_segment_stats": { "anyOf": [ { "$ref": "#/$defs/AthleteSegmentStats" }, { "type": "null" } ], "default": null }, "average_grade": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Average Grade" }, "city": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "title": "City" }, "climb_category": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Climb Category" }, "country": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "title": "Country" }, "distance": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Distance" }, "elevation_high": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Elevation High" }, "elevation_low": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Elevation Low" }, "end_latlng": { "anyOf": [ { "$ref": "#/$defs/LatLon" }, { "type": "null" } ], "default": null }, "id": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "title": "Id" }, "maximum_grade": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Maximum Grade" }, "name": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "title": "Name" }, "private": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": null, "title": "Private" }, "start_latlng": { "anyOf": [ { "$ref": "#/$defs/LatLon" }, { "type": "null" } ], "default": null }, "state": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "title": "State" } }, "title": "SummarySegment", "type": "object" } } }
- Fields:
- Validators:
- field activity: MetaActivity | None = None#
- field athlete: MetaAthlete | None = None#
- field average_heartrate: float | None = None#
The heart heart rate of the athlete during this effort
- copy(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, update: Dict[str, Any] | None = None, deep: bool = False) Self#
Returns a copy of the model.
- !!! warning “Deprecated”
This method is now deprecated; use model_copy instead.
If you need include or exclude, use:
`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `- Parameters:
include – Optional set or mapping specifying which fields to include in the copied model.
exclude – Optional set or mapping specifying which fields to exclude in the copied model.
update – Optional dictionary of field-value pairs to override field values in the copied model.
deep – If True, the values of fields that are Pydantic models will be deep-copied.
- Returns:
A copy of the model with included, excluded and updated fields as specified.
- field device_watts: bool | None = None#
For riding efforts, whether the wattage was reported by a dedicated recording device
- dict(*, include: Set[int] | Set[str] | Mapping[int, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, exclude: Set[int] | Set[str] | Mapping[int, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) Dict[str, Any]#
Whether this effort should be hidden when viewed within an activity
- json(*, include: Set[int] | Set[str] | Mapping[int, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, exclude: Set[int] | Set[str] | Mapping[int, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = PydanticUndefined, models_as_dict: bool = PydanticUndefined, **dumps_kwargs: Any) str#
- field kom_rank: int | None = None#
The rank of the effort on the global leaderboard if it belongs in the top 10 at the time of upload
- Constraints:
ge = 1
le = 10
- classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) Self#
Creates a new instance of the Model class with validated data.
Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.
- !!! note
model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.
- Parameters:
_fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.
values – Trusted or pre-validated data dictionary.
- Returns:
A new instance of the Model class with validated data.
- model_copy(*, update: Mapping[str, Any] | None = None, deep: bool = False) Self#
Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy
Returns a copy of the model.
- Parameters:
update – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.
deep – Set to True to make a deep copy of the model.
- Returns:
New model instance.
- model_dump(*, mode: Literal['json', 'python'] | str = 'python', include: Set[int] | Set[str] | Mapping[int, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, exclude: Set[int] | Set[str] | Mapping[int, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, context: Any | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, round_trip: bool = False, warnings: bool | Literal['none', 'warn', 'error'] = True, serialize_as_any: bool = False) dict[str, Any]#
Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- Parameters:
mode – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.
include – A set of fields to include in the output.
exclude – A set of fields to exclude from the output.
context – Additional context to pass to the serializer.
by_alias – Whether to use the field’s alias in the dictionary key if defined.
exclude_unset – Whether to exclude fields that have not been explicitly set.
exclude_defaults – Whether to exclude fields that are set to their default value.
exclude_none – Whether to exclude fields that have a value of None.
round_trip – If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
serialize_as_any – Whether to serialize fields with duck-typing serialization behavior.
- Returns:
A dictionary representation of the model.
- model_dump_json(*, indent: int | None = None, include: Set[int] | Set[str] | Mapping[int, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, exclude: Set[int] | Set[str] | Mapping[int, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, Set[int] | Set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, context: Any | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, round_trip: bool = False, warnings: bool | Literal['none', 'warn', 'error'] = True, serialize_as_any: bool = False) str#
Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json
Generates a JSON representation of the model using Pydantic’s to_json method.
- Parameters:
indent – Indentation to use in the JSON output. If None is passed, the output will be compact.
include – Field(s) to include in the JSON output.
exclude – Field(s) to exclude from the JSON output.
context – Additional context to pass to the serializer.
by_alias – Whether to serialize using field aliases.
exclude_unset – Whether to exclude fields that have not been explicitly set.
exclude_defaults – Whether to exclude fields that are set to their default value.
exclude_none – Whether to exclude fields that have a value of None.
round_trip – If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
serialize_as_any – Whether to serialize fields with duck-typing serialization behavior.
- Returns:
A JSON string representation of the model.
- property model_extra: dict[str, Any] | None#
Get extra fields set during validation.
- Returns:
A dictionary of extra fields, or None if config.extra is not set to “allow”.
- property model_fields_set: set[str]#
Returns the set of fields that have been explicitly set on this model instance.
- Returns:
- A set of strings representing the fields that have been set,
i.e. that were not filled from defaults.
- classmethod model_json_schema(by_alias: bool = True, ref_template: str = '#/$defs/{model}', schema_generator: type[~pydantic.json_schema.GenerateJsonSchema] = <class 'pydantic.json_schema.GenerateJsonSchema'>, mode: ~typing.Literal['validation', 'serialization'] = 'validation') dict[str, Any]#
Generates a JSON schema for a model class.
- Parameters:
by_alias – Whether to use attribute aliases or not.
ref_template – The reference template.
schema_generator – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications
mode – The mode in which to generate the schema.
- Returns:
The JSON schema for the given model class.
- classmethod model_parametrized_name(params: tuple[type[Any], ...]) str#
Compute the class name for parametrizations of generic classes.
This method can be overridden to achieve a custom naming scheme for generic BaseModels.
- Parameters:
params – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.
- Returns:
String representing the new class where params are passed to cls as type variables.
- Raises:
TypeError – Raised when trying to generate concrete names for non-generic models.
- model_post_init(_BaseModel__context: Any) None#
Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.
- classmethod model_rebuild(*, force: bool = False, raise_errors: bool = True, _parent_namespace_depth: int = 2, _types_namespace: MappingNamespace | None = None) bool | None#
Try to rebuild the pydantic-core schema for the model.
This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.
- Parameters:
force – Whether to force the rebuilding of the model schema, defaults to False.
raise_errors – Whether to raise errors, defaults to True.
_parent_namespace_depth – The depth level of the parent namespace, defaults to 2.
_types_namespace – The types namespace, defaults to None.
- Returns:
Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.
- classmethod model_validate(obj: Any, *, strict: bool | None = None, from_attributes: bool | None = None, context: Any | None = None) Self#
Validate a pydantic model instance.
- Parameters:
obj – The object to validate.
strict – Whether to enforce types strictly.
from_attributes – Whether to extract data from object attributes.
context – Additional context to pass to the validator.
- Raises:
ValidationError – If the object could not be validated.
- Returns:
The validated model instance.
- classmethod model_validate_json(json_data: str | bytes | bytearray, *, strict: bool | None = None, context: Any | None = None) Self#
Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing
Validate the given JSON data against the Pydantic model.
- Parameters:
json_data – The JSON data to validate.
strict – Whether to enforce types strictly.
context – Extra variables to pass to the validator.
- Returns:
The validated Pydantic model.
- Raises:
ValidationError – If json_data is not a JSON string or the object could not be validated.
- classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None) Self#
Validate the given object with string data against the Pydantic model.
- Parameters:
obj – The object containing string data to validate.
strict – Whether to enforce types strictly.
context – Extra variables to pass to the validator.
- Returns:
The validated Pydantic model.
- classmethod parse_file(path: str | Path, *, content_type: str | None = None, encoding: str = 'utf8', proto: DeprecatedParseProtocol | None = None, allow_pickle: bool = False) Self#
- classmethod parse_raw(b: str | bytes, *, content_type: str | None = None, encoding: str = 'utf8', proto: DeprecatedParseProtocol | None = None, allow_pickle: bool = False) Self#
- field pr_rank: int | None = None#
The rank of the effort on the athlete’s leaderboard if it belongs in the top 3 at the time of upload
- Constraints:
ge = 1
le = 3
- classmethod schema_json(*, by_alias: bool = True, ref_template: str = '#/$defs/{model}', **dumps_kwargs: Any) str#
- field segment: SummarySegment | None = None#