from datetime import datetime
from typing import Optional

import pandas as pd
from rich import box
from rich.console import Console
from rich.table import Table

console = Console()


def df_to_table(
    pandas_dataframe: pd.DataFrame,
    rich_table: Table,
    show_index: bool = True,
    index_name: Optional[str] = None,
) -> Table:
    """Convert a pandas.DataFrame obj into a rich.Table obj.

    Args:
        pandas_dataframe (DataFrame): A Pandas DataFrame to be converted to a rich Table.
        rich_table (Table): A rich Table that should be populated by the DataFrame values.
        show_index (bool): Add a column with a row count to the table. Defaults to True.
        index_name (str, optional): The column name to give to the index column. Defaults to None, showing no value.

    Returns:
        Table: The rich Table instance passed, populated with the DataFrame values."""

    if show_index:
        index_name = str(index_name) if index_name else ""
        rich_table.add_column(index_name)

    for column in pandas_dataframe.columns:
        rich_table.add_column(str(column))

    for index, value_list in enumerate(pandas_dataframe.values.tolist()):
        row = [str(index)] if show_index else []
        row += [str(x) for x in value_list]
        rich_table.add_row(*row)

    return rich_table


if __name__ == "__main__":
    sample_data = {
        "Date": [
            datetime(year=2019, month=12, day=20),
            datetime(year=2018, month=5, day=25),
            datetime(year=2017, month=12, day=15),
        ],
        "Title": [
            "Star Wars: The Rise of Skywalker",
            "[red]Solo[/red]: A Star Wars Story",
            "Star Wars Ep. VIII: The Last Jedi",
        ],
        "Production Budget": ["$275,000,000", "$275,000,000", "$262,000,000"],
        "Box Office": ["$375,126,118", "$393,151,347", "$1,332,539,889"],
    }
    df = pd.DataFrame(sample_data)

    # Initiate a Table instance to be modified
    table = Table(show_header=True, header_style="bold magenta")

    # Modify the table instance to have the data from the DataFrame
    table = df_to_table(df, table)

    # Update the style of the table
    table.row_styles = ["none", "dim"]
    table.box = box.SIMPLE_HEAD

    console.print(table)

import pandas as pd
from rich.text import Text
from rich.console import Console
from rich.table import Table

console = Console()


def table_to_df(rich_table: Table) -> pd.DataFrame:
    """Convert a rich.Table obj into a pandas.DataFrame obj with any rich formatting removed from the values.
    Args:
        rich_table (Table): A rich Table that should be populated by the DataFrame values.
    Returns:
        DataFrame: A pandas DataFrame with the Table data as its values."""

    table_data = {
        x.header: [Text.from_markup(y).plain for y in x.cells] for x in table.columns
    }
    return pd.DataFrame(table_data)


if __name__ == "__main__":
    # This example is taken from the rich documentation
    table = Table(show_header=True, header_style="bold magenta")
    table.add_column("Date", style="dim", width=12)
    table.add_column("Title")
    table.add_column("Production Budget", justify="right")
    table.add_column("Box Office", justify="right")
    table.add_row(
        "Dec 20, 2019",
        "Star Wars: The Rise of Skywalker",
        "$275,000,000",
        "$375,126,118",
    )
    table.add_row(
        "May 25, 2018",
        "[red]Solo[/red]: A Star Wars Story",
        "$275,000,000",
        "$393,151,347",
    )
    table.add_row(
        "Dec 15, 2017",
        "Star Wars Ep. VIII: The Last Jedi",
        "$262,000,000",
        "[bold]$1,332,539,889[/bold]",
    )

    # Show the rich Table
    console.print(table)

    # Convert the Table into a DataFrame
    df = table_to_df(table)
    print(df)