from __future__ import annotations
from typing import TYPE_CHECKING, Any, Optional, Sequence, Iterable
if TYPE_CHECKING:
from ...client_SYNC import Client
from ..paginator import HasMorePaginator, Bidirectional, CursorPaginator
from ...models.flair import UserFlairAssociation
from ...model_loaders.flair import load_user_flair_association
[docs]class UserFlairAssociationPaginator(
HasMorePaginator[UserFlairAssociation], Bidirectional, CursorPaginator[UserFlairAssociation]):
def __init__(self,
client: Client,
url: str,
*,
limit: Optional[int] = 1000,
) -> None:
super().__init__()
self.limit: Optional[int] = limit
("")
self.direction: bool = True
("")
self.client: Client = client
("")
self.url: str = url
("")
self._after: str = ''
self._before: str = ''
self._has_after: bool = True
self._has_before: bool = True
[docs] def get_cursor(self) -> str:
return self._after if self.direction else self._before
[docs] def set_cursor(self, value: str) -> None:
if self.direction:
self._after = value
else:
self._before = value
[docs] def has_more(self) -> bool:
return self._has_after if self.direction else self._has_before
[docs] def set_has_more(self, value: bool) -> None:
if self.direction:
self._has_after = value
else:
self._has_before = value
def _generate_params(self) -> Iterable[tuple[str, str]]:
if self.limit is not None:
yield ('limit', str(self.limit))
if self.direction:
if self._after:
yield ('after', self._after)
else:
if self._before:
yield ('before', self._before)
def _fetch_data(self) -> Any:
params = dict(self._generate_params())
data = self.client.request('GET', self.url, params=params)
children = data['users']
suggested_forward_cursor = data.get('after', '')
suggested_backward_cursor = data.get('before', '')
if children:
self._after = suggested_forward_cursor
self._before = suggested_backward_cursor
self._has_after = bool(suggested_forward_cursor)
self._has_before = bool(suggested_backward_cursor)
return data
[docs] def fetch(self) -> Sequence[UserFlairAssociation]:
data = self._fetch_data()
return [load_user_flair_association(d) for d in data['users']]