stravalib.model.AthleteStats#

pydantic model stravalib.model.AthleteStats[source]#

Summary totals for rides, runs and swims, as shown in an athlete’s public profile. Non-public activities are not counted for these totals.

Show JSON schema
{
   "title": "AthleteStats",
   "description": "Summary totals for rides, runs and swims, as shown in an athlete's public\nprofile. Non-public activities are not counted for these totals.",
   "type": "object",
   "properties": {
      "all_ride_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "all_run_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "all_swim_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "biggest_climb_elevation_gain": {
         "anyOf": [
            {
               "type": "number"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Biggest Climb Elevation Gain"
      },
      "biggest_ride_distance": {
         "anyOf": [
            {
               "type": "number"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Biggest Ride Distance"
      },
      "recent_ride_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "recent_run_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "recent_swim_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "ytd_ride_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "ytd_run_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      },
      "ytd_swim_totals": {
         "anyOf": [
            {
               "$ref": "#/$defs/ActivityTotals"
            },
            {
               "type": "null"
            }
         ],
         "default": null
      }
   },
   "$defs": {
      "ActivityTotals": {
         "description": "Contains a set of total values for an activity including\nelapsed time, moving time, distance and elevation gain.",
         "properties": {
            "achievement_count": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Achievement Count"
            },
            "count": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Count"
            },
            "distance": {
               "anyOf": [
                  {
                     "type": "number"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Distance"
            },
            "elapsed_time": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Elapsed Time"
            },
            "elevation_gain": {
               "anyOf": [
                  {
                     "type": "number"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Elevation Gain"
            },
            "moving_time": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Moving Time"
            }
         },
         "title": "ActivityTotals",
         "type": "object"
      }
   }
}

Fields:
field all_ride_totals: ActivityTotals | None = None#

The all time ride stats for the athlete.

field all_run_totals: ActivityTotals | None = None#

The all time run stats for the athlete.

field all_swim_totals: ActivityTotals | None = None#

The all time swim stats for the athlete.

field biggest_climb_elevation_gain: DistanceType | None = None#

The highest climb ridden by the athlete.

field biggest_ride_distance: DistanceType | None = None#

The longest distance ridden by the athlete.

classmethod construct(_fields_set: set[str] | None = None, **values: Any) → Self#
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.

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]#
classmethod from_orm(obj: Any) → Self#
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#
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#
!!! abstract “Usage Documentation”

[model_copy](../concepts/serialization.md#model_copy)

Returns a copy of the model.

!!! note

The underlying instance’s [__dict__][object.__dict__] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

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 | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, round_trip: bool = False, warnings: bool | Literal['none', 'warn', 'error'] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False) → dict[str, Any]#
!!! abstract “Usage Documentation”

[model_dump](../concepts/serialization.md#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].

  • fallback – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.

  • 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 | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, round_trip: bool = False, warnings: bool | Literal['none', 'warn', 'error'] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False) → str#
!!! abstract “Usage Documentation”

[model_dump_json](../concepts/serialization.md#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].

  • fallback – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.

  • 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(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, by_alias: bool | None = None, by_name: bool | 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.

  • by_alias – Whether to use the field’s alias when validating against the provided input data.

  • by_name – Whether to use the field’s name when validating against the provided input data.

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, by_alias: bool | None = None, by_name: bool | None = None) → Self#
!!! abstract “Usage Documentation”

[JSON Parsing](../concepts/json.md#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.

  • by_alias – Whether to use the field’s alias when validating against the provided input data.

  • by_name – Whether to use the field’s name when validating against the provided input data.

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, by_alias: bool | None = None, by_name: bool | 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.

  • by_alias – Whether to use the field’s alias when validating against the provided input data.

  • by_name – Whether to use the field’s name when validating against the provided input data.

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_obj(obj: Any) → 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 recent_ride_totals: ActivityTotals | None = None#

The recent (last 4 weeks) ride stats for the athlete.

field recent_run_totals: ActivityTotals | None = None#

The recent (last 4 weeks) run stats for the athlete.

field recent_swim_totals: ActivityTotals | None = None#

The recent (last 4 weeks) swim stats for the athlete.

classmethod schema(by_alias: bool = True, ref_template: str = '#/$defs/{model}') → Dict[str, Any]#
classmethod schema_json(*, by_alias: bool = True, ref_template: str = '#/$defs/{model}', **dumps_kwargs: Any) → str#
classmethod update_forward_refs(**localns: Any) → None#
classmethod validate(value: Any) → Self#
field ytd_ride_totals: ActivityTotals | None = None#

The year to date ride stats for the athlete.

field ytd_run_totals: ActivityTotals | None = None#

The year to date run stats for the athlete.

field ytd_swim_totals: ActivityTotals | None = None#

The year to date swim stats for the athlete.