Module aoe2netwrapper.models.leaderboard

aoe2netwrapper.models.leaderboard

---

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

View Source

"""

aoe2netwrapper.models.leaderboard

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

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

https://aoe2.net/api/leaderboard

"""

from typing import Any, List, Optional

from pydantic import BaseModel, Field

class LeaderBoardSpot(BaseModel):

    """An object to encapsulate any entry in the leaderboard ranking."""

    profile_id: Optional[int] = Field(None, description="The ID attributed to the player by AoE II")

    rank: Optional[int] = Field(None, description="The player's rank on the ladder")

    rating: Optional[int] = Field(None, description="The player's rating in the ELO system")

    steam_id: Optional[int] = Field(None, description="ID of the player on the Steam platform")

    icon: Optional[Any] = Field(None, description="The player's icon")

    name: Optional[str] = Field(None, description="The player's in-game name")

    clan: Optional[str] = Field(None, description="The player's clan / team")

    country: Optional[str] = Field(None, description="Country the player connected from")

    previous_rating: Optional[int] = Field(None, description="Player's rating at their last match")

    highest_rating: Optional[int] = Field(None, description="Highest rating achieved by the player")

    streak: Optional[int] = Field(None, description="Current number of consecutive wins")

    lowest_streak: Optional[int] = Field(None, description="Lowest streak achieved by this player")

    highest_streak: Optional[int] = Field(None, description="Highest streak achieved by this player")

    games: Optional[int] = Field(None, description="The total amount of games played by the player")

    wins: Optional[int] = Field(None, description="Total amount of wins")

    losses: Optional[int] = Field(None, description="Total amount of losses")

    drops: Optional[int] = Field(None, description="Number of games the player dropped out of")

    last_match: Optional[int] = Field(None, description="Timestamp of the last game played")

    last_match_time: Optional[int] = Field(None, description="Timestamp of the last game played")

class LeaderBoardResponse(BaseModel):

    """An object to encapsulate the response from the leaderboard API."""

    total: Optional[int] = Field(None, description="Total number of entries in the leaderboard")

    leaderboard_id: Optional[int] = Field(None, description="ID of the leaderboard queried, aka game type")

    start: Optional[int] = Field(None, description="Starting rank of the first entry in the response")

    count: Optional[int] = Field(None, description="Number of entries returned")

    leaderboard: Optional[List[LeaderBoardSpot]] = Field(None, description="List of LeaderBoardSport entries")

Classes

LeaderBoardResponse

class LeaderBoardResponse(
    __pydantic_self__,
    **data: Any
)

View Source

class LeaderBoardResponse(BaseModel):

    """An object to encapsulate the response from the leaderboard API."""

    total: Optional[int] = Field(None, description="Total number of entries in the leaderboard")

    leaderboard_id: Optional[int] = Field(None, description="ID of the leaderboard queried, aka game type")

    start: Optional[int] = Field(None, description="Starting rank of the first entry in the response")

    count: Optional[int] = Field(None, description="Number of entries returned")

    leaderboard: Optional[List[LeaderBoardSpot]] = Field(None, description="List of LeaderBoardSport entries")

---

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().

LeaderBoardSpot

class LeaderBoardSpot(
    __pydantic_self__,
    **data: Any
)

View Source

class LeaderBoardSpot(BaseModel):

    """An object to encapsulate any entry in the leaderboard ranking."""

    profile_id: Optional[int] = Field(None, description="The ID attributed to the player by AoE II")

    rank: Optional[int] = Field(None, description="The player's rank on the ladder")

    rating: Optional[int] = Field(None, description="The player's rating in the ELO system")

    steam_id: Optional[int] = Field(None, description="ID of the player on the Steam platform")

    icon: Optional[Any] = Field(None, description="The player's icon")

    name: Optional[str] = Field(None, description="The player's in-game name")

    clan: Optional[str] = Field(None, description="The player's clan / team")

    country: Optional[str] = Field(None, description="Country the player connected from")

    previous_rating: Optional[int] = Field(None, description="Player's rating at their last match")

    highest_rating: Optional[int] = Field(None, description="Highest rating achieved by the player")

    streak: Optional[int] = Field(None, description="Current number of consecutive wins")

    lowest_streak: Optional[int] = Field(None, description="Lowest streak achieved by this player")

    highest_streak: Optional[int] = Field(None, description="Highest streak achieved by this player")

    games: Optional[int] = Field(None, description="The total amount of games played by the player")

    wins: Optional[int] = Field(None, description="Total amount of wins")

    losses: Optional[int] = Field(None, description="Total amount of losses")

    drops: Optional[int] = Field(None, description="Number of games the player dropped out of")

    last_match: Optional[int] = Field(None, description="Timestamp of the last game played")

    last_match_time: Optional[int] = Field(None, description="Timestamp of the last game played")

---

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().