119 lines
3.4 KiB
Python
119 lines
3.4 KiB
Python
"""Table components."""
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from typing import Any, List, Optional
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from pynecone.components.component import Component
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from pynecone.components.tags import Tag
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from pynecone.utils import format, imports, types
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from pynecone.var import BaseVar, Var
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class Gridjs(Component):
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"""A component that wraps a nivo bar component."""
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library = "gridjs-react"
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class DataTable(Gridjs):
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"""A data table component."""
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tag = "Grid"
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# The data to display. Either a list of dictionaries or a pandas dataframe.
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data: Any
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# The columns to display.
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columns: Var[List]
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# Enable a search bar.
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search: Var[bool]
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# Enable sorting on columns.
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sort: Var[bool]
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# Enable resizable columns.
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resizable: Var[bool]
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# Enable pagination.
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pagination: Var[bool]
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@classmethod
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def get_alias(cls) -> Optional[str]:
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"""Get the alias for the component.
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Returns:
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The alias.
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"""
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return "DataTableGrid"
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@classmethod
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def create(cls, *children, **props):
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"""Create a datatable component.
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Args:
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*children: The children of the component.
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**props: The props to pass to the component.
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Returns:
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The datatable component.
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Raises:
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ValueError: If a pandas dataframe is passed in and columns are also provided.
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"""
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data = props.get("data")
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# If data is a pandas dataframe and columns are provided throw an error.
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if (
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types.is_dataframe(type(data))
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or (isinstance(data, Var) and types.is_dataframe(data.type_))
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) and props.get("columns"):
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raise ValueError(
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"Cannot pass in both a pandas dataframe and columns to the data_table component."
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)
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# If data is a list and columns are not provided, throw an error
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if (
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(isinstance(data, Var) and issubclass(data.type_, List))
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or issubclass(type(data), List)
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) and not props.get("columns"):
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raise ValueError(
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"column field should be specified when the data field is a list type"
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)
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# Create the component.
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return super().create(
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*children,
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**props,
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)
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def _get_imports(self) -> imports.ImportDict:
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return imports.merge_imports(
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super()._get_imports(), {"": {"gridjs/dist/theme/mermaid.css"}}
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)
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def _render(self) -> Tag:
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if isinstance(self.data, Var):
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self.columns = BaseVar(
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name=f"{self.data.name}.columns"
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if types.is_dataframe(self.data.type_)
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else f"{self.columns.name}",
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type_=List[Any],
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state=self.data.state,
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)
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self.data = BaseVar(
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name=f"{self.data.name}.data"
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if types.is_dataframe(self.data.type_)
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else f"{self.data.name}",
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type_=List[List[Any]],
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state=self.data.state,
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)
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# If given a pandas df break up the data and columns
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if types.is_dataframe(type(self.data)):
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self.columns = Var.create(list(self.data.columns.values.tolist())) # type: ignore
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self.data = Var.create(format.format_dataframe_values(self.data)) # type: ignore
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# Render the table.
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return super()._render()
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