59dd54c049
* add workflow to check dependencies on release branch * rename action to follow convention of other actions * update workflow * bump poetry version * relock deps * update check to ignore pyright and ruff * oops, you saw nothing * split dep check in two job * fix frontend dep check * fix stuff * hmm yeah * nope nope nope * sigh * bump js versions for some packages * fix some warnings in tests * fix tests * try some options * try to set asyncio policy * debug dep check * fix attempt for backend dep * clean up output for backend check * run bun outdated on reflex-web to catch most of the packages * fix python version * fix python version * add missing env * fix bun command * fix workdir of frontend check * update packages version * up-pin plotly.js version * add debug ouput * clean frontend dep check output * fix output * fix async tests for redis * relock poetry.lock * Non-async functions do not need pytest_asyncio.fixture * test_state: close StateManagerRedis connection in test to avoid warning --------- Co-authored-by: Masen Furer <m_github@0x26.net>
134 lines
4.1 KiB
Python
134 lines
4.1 KiB
Python
"""Table components."""
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from __future__ import annotations
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from typing import Any, Dict, List, Union
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from reflex.components.component import Component
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from reflex.components.tags import Tag
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from reflex.utils import types
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from reflex.utils.imports import ImportDict
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from reflex.utils.serializers import serialize
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from reflex.vars.base import LiteralVar, Var, is_computed_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@6.1.1"
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lib_dependencies: List[str] = ["gridjs@6.2.0"]
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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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alias = "DataTableGrid"
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# The data to display. Either a list of lists or a pandas dataframe.
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data: Any
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# The list of columns to display. Required if data is a list and should not be provided
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# if the data field is a dataframe
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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[Union[bool, Dict]]
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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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columns = props.get("columns")
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# The annotation should be provided if data is a computed var. We need this to know how to
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# render pandas dataframes.
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if is_computed_var(data) and data._var_type == Any:
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raise ValueError(
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"Annotation of the computed var assigned to the data field should be provided."
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)
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if (
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columns is not None
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and is_computed_var(columns)
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and columns._var_type == Any
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):
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raise ValueError(
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"Annotation of the computed var assigned to the column field should be provided."
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)
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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._var_type))
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) and columns is not None:
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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 types._issubclass(data._var_type, List))
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or issubclass(type(data), List)
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) and columns is None:
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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 add_imports(self) -> ImportDict:
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"""Add the imports for the datatable component.
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Returns:
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The import dict for the component.
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"""
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return {"": "gridjs/dist/theme/mermaid.css"}
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def _render(self) -> Tag:
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if isinstance(self.data, Var) and types.is_dataframe(self.data._var_type):
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self.columns = self.data._replace(
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_js_expr=f"{self.data._js_expr}.columns",
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_var_type=List[Any],
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)
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self.data = self.data._replace(
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_js_expr=f"{self.data._js_expr}.data",
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_var_type=List[List[Any]],
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)
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if types.is_dataframe(type(self.data)):
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# If given a pandas df break up the data and columns
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data = serialize(self.data)
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if not isinstance(data, dict):
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raise ValueError("Serialized dataframe should be a dict.")
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self.columns = LiteralVar.create(data["columns"])
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self.data = LiteralVar.create(data["data"])
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# Render the table.
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return super()._render()
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