Module aoe2netwrapper.models.strings

aoe2netwrapper.models.strings

---

This module contains the model objects to encapsulate the responses from the endpoint at https://aoe2.net/api/strings

Any confusing with a specific attribute being an INTEGER in the models can be cleared by checking the corresponding string the API / system attributes to this ID.

View Source

"""

aoe2netwrapper.models.strings

-----------------------------

This module contains the model objects to encapsulate the responses from the endpoint at

https://aoe2.net/api/strings

Any confusing with a specific attribute being an INTEGER in the models can be cleared by checking the

corresponding string the API / system attributes to this ID.

"""

from typing import List, Optional

from pydantic import BaseModel, Field

class AgeString(BaseModel):

    """An object to encapsulate any entry for the available age strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'age' ID")

class CivilizationString(BaseModel):

    """An object to encapsulate any entry for the available civilization strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'civ' ID")

class GameTypeString(BaseModel):

    """An object to encapsulate any entry for the available game type strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'game_type' ID")

class LeaderBoardString(BaseModel):

    """An object to encapsulate any entry for the available leaderboard strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'leaderboard' ID")

class MapSizeString(BaseModel):

    """An object to encapsulate any entry for the available map size strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'map_size' ID")

class MapTypeString(BaseModel):

    """An object to encapsulate any entry for the available map type strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'map_type' ID")

class RatingTypeString(BaseModel):

    """An object to encapsulate any entry for the available rating type strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'rating_type' ID")

class ResourcesString(BaseModel):

    """An object to encapsulate any entry for the available resources strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'resources' ID")

class SpeedString(BaseModel):

    """An object to encapsulate any entry for the available speed strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'speed' ID")

class VictoryString(BaseModel):

    """An object to encapsulate any entry for the available victory strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'victory' ID")

class VisibilityString(BaseModel):

    """An object to encapsulate any entry for the available visibiliity strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'visibility' ID")

class StringsResponse(BaseModel):

    """An object to encapsulate the response from the strings API endpoint."""

    language: Optional[str] = Field(None, description="Language of the returned strings")

    age: Optional[List[AgeString]] = Field(None, description="List of all strings and their IDs for ages")

    civ: Optional[List[CivilizationString]] = Field(

        None, description="List of all strings and their IDs for civilizations"

    )

    game_type: Optional[List[GameTypeString]] = Field(

        None, description="List of all strings and their IDs for game types"

    )

    leaderboard: Optional[List[LeaderBoardString]] = Field(

        None, description="List of all strings and their IDs for leaderboards"

    )

    map_size: Optional[List[MapSizeString]] = Field(

        None, description="List of all strings and their IDs for map sizes"

    )

    map_type: Optional[List[MapTypeString]] = Field(

        None, description="List of all strings and their IDs for map types"

    )

    rating_type: Optional[List[RatingTypeString]] = Field(

        None, description="List of all strings and their IDs for rating types"

    )

    resources: Optional[List[ResourcesString]] = Field(

        None, description="List of all strings and their IDs for resources"

    )

    speed: Optional[List[SpeedString]] = Field(

        None, description="List of all strings and their IDs for game speeds"

    )

    victory: Optional[List[VictoryString]] = Field(

        None, description="List of all strings and their IDs for victory types"

    )

    visibility: Optional[List[VisibilityString]] = Field(

        None, description="List of all strings and their IDs for visibility"

    )

Classes

AgeString

class AgeString(
    __pydantic_self__,
    **data: Any
)

View Source

class AgeString(BaseModel):

    """An object to encapsulate any entry for the available age strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'age' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

CivilizationString

class CivilizationString(
    __pydantic_self__,
    **data: Any
)

View Source

class CivilizationString(BaseModel):

    """An object to encapsulate any entry for the available civilization strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'civ' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

GameTypeString

class GameTypeString(
    __pydantic_self__,
    **data: Any
)

View Source

class GameTypeString(BaseModel):

    """An object to encapsulate any entry for the available game type strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'game_type' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

LeaderBoardString

class LeaderBoardString(
    __pydantic_self__,
    **data: Any
)

View Source

class LeaderBoardString(BaseModel):

    """An object to encapsulate any entry for the available leaderboard strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'leaderboard' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

MapSizeString

class MapSizeString(
    __pydantic_self__,
    **data: Any
)

View Source

class MapSizeString(BaseModel):

    """An object to encapsulate any entry for the available map size strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'map_size' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

MapTypeString

class MapTypeString(
    __pydantic_self__,
    **data: Any
)

View Source

class MapTypeString(BaseModel):

    """An object to encapsulate any entry for the available map type strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'map_type' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

RatingTypeString

class RatingTypeString(
    __pydantic_self__,
    **data: Any
)

View Source

class RatingTypeString(BaseModel):

    """An object to encapsulate any entry for the available rating type strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'rating_type' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

ResourcesString

class ResourcesString(
    __pydantic_self__,
    **data: Any
)

View Source

class ResourcesString(BaseModel):

    """An object to encapsulate any entry for the available resources strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'resources' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

SpeedString

class SpeedString(
    __pydantic_self__,
    **data: Any
)

View Source

class SpeedString(BaseModel):

    """An object to encapsulate any entry for the available speed strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'speed' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

StringsResponse

class StringsResponse(
    __pydantic_self__,
    **data: Any
)

View Source

class StringsResponse(BaseModel):

    """An object to encapsulate the response from the strings API endpoint."""

    language: Optional[str] = Field(None, description="Language of the returned strings")

    age: Optional[List[AgeString]] = Field(None, description="List of all strings and their IDs for ages")

    civ: Optional[List[CivilizationString]] = Field(

        None, description="List of all strings and their IDs for civilizations"

    )

    game_type: Optional[List[GameTypeString]] = Field(

        None, description="List of all strings and their IDs for game types"

    )

    leaderboard: Optional[List[LeaderBoardString]] = Field(

        None, description="List of all strings and their IDs for leaderboards"

    )

    map_size: Optional[List[MapSizeString]] = Field(

        None, description="List of all strings and their IDs for map sizes"

    )

    map_type: Optional[List[MapTypeString]] = Field(

        None, description="List of all strings and their IDs for map types"

    )

    rating_type: Optional[List[RatingTypeString]] = Field(

        None, description="List of all strings and their IDs for rating types"

    )

    resources: Optional[List[ResourcesString]] = Field(

        None, description="List of all strings and their IDs for resources"

    )

    speed: Optional[List[SpeedString]] = Field(

        None, description="List of all strings and their IDs for game speeds"

    )

    victory: Optional[List[VictoryString]] = Field(

        None, description="List of all strings and their IDs for victory types"

    )

    visibility: Optional[List[VisibilityString]] = Field(

        None, description="List of all strings and their IDs for visibility"

    )

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

VictoryString

class VictoryString(
    __pydantic_self__,
    **data: Any
)

View Source

class VictoryString(BaseModel):

    """An object to encapsulate any entry for the available victory strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'victory' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

VisibilityString

class VisibilityString(
    __pydantic_self__,
    **data: Any
)

View Source

class VisibilityString(BaseModel):

    """An object to encapsulate any entry for the available visibiliity strings and their respective IDs."""

    id: Optional[int] = Field(None, description="ID for this specific string value")

    string: Optional[str] = Field(None, description="String value for this specific 'visibility' ID")

---

Ancestors (in MRO)

• pydantic.main.BaseModel
• pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    update: 'DictStrAny' = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name	Type	Description	Default
include	None	fields to include in new model	None
exclude	None	fields to exclude from new model, as with values this takes precedence over include	None
update	None	values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data	None
deep	None	set to True to make a deep copy of the model	None

Returns:

Type	Description
None	new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None,
    by_alias: bool = False,
    skip_defaults: bool = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().