Source code for pybdl.access.attributes

"""Access layer for attributes API endpoints."""

from typing import Any

import pandas as pd

from pybdl.access.base import BaseAccess


[docs] class AttributesAccess(BaseAccess): """Access layer for attributes API, converting responses to DataFrames."""
[docs] def list_attributes( self, page_size: int | None = None, max_pages: int | None = None, **kwargs: Any, ) -> pd.DataFrame: """ List all attributes as a DataFrame. Args: page_size: Number of results per page (defaults to config.page_size or 100). max_pages: Maximum number of pages to fetch (None for all pages). **kwargs: Additional parameters passed to API layer (e.g., lang, format, extra_query). Returns: DataFrame with attributes data. """ if page_size is None: page_size = self._get_default_page_size() data = self.api_client.list_attributes(page_size=page_size, max_pages=max_pages, **kwargs) return self._to_dataframe(data)
[docs] def get_attribute( self, attribute_id: str, **kwargs: Any, ) -> pd.DataFrame: """ Retrieve metadata details for a specific attribute as a DataFrame. Args: attribute_id: Attribute identifier. **kwargs: Additional parameters passed to API layer (e.g., lang, format, extra_query). Returns: DataFrame with attribute metadata. """ data = self.api_client.get_attribute(attribute_id, **kwargs) return self._to_dataframe(data)
[docs] async def alist_attributes( self, page_size: int | None = None, max_pages: int | None = None, **kwargs: Any, ) -> pd.DataFrame: """ Asynchronously list all attributes as a DataFrame. Args: page_size: Number of results per page (defaults to config.page_size or 100). max_pages: Maximum number of pages to fetch (None for all pages). **kwargs: Additional parameters passed to API layer (e.g., lang, format, extra_query). Returns: DataFrame with attributes data. """ if page_size is None: page_size = self._get_default_page_size() data = await self.api_client.alist_attributes(page_size=page_size, max_pages=max_pages, **kwargs) return self._to_dataframe(data)
[docs] async def aget_attribute( self, attribute_id: str, **kwargs: Any, ) -> pd.DataFrame: """ Asynchronously retrieve metadata details for a specific attribute as a DataFrame. Args: attribute_id: Attribute identifier. **kwargs: Additional parameters passed to API layer (e.g., lang, format, extra_query). Returns: DataFrame with attribute metadata. """ data = await self.api_client.aget_attribute(attribute_id, **kwargs) return self._to_dataframe(data)