Altair - Boxplot border to be set black and median line red

I want to set a black border color to the boxplot of a altair graph, i try to add stroke parameter to black on the encoding chanel but this overrided my red median line to black.

This is the code I am trying:

def plot_hourly_boxplot_altair(data, column, session_state=None):
    # Convert 'fecha' column to datetime format
    data['fecha'] = pd.to_datetime(data['fecha'])
    
    # Filter out rows where the specified column has NaN values
    data = data.dropna(subset=[column])

    if session_state and not session_state.zero_values:
        # Erase 0 values from the data
        data = data[data[column] != 0]

    # filter the data to just get the date range selected
    data = range_selector(data, min_date=session_state.min_date, max_date=session_state.max_date)

    # filter the data to just get the days of the week selected
    if session_state.days:
        data = data[data['fecha'].dt.dayofweek.isin(session_state.days)]

    if data.empty:
        print(f"No valid data for column '{column}'.")
        return None

    # Create a boxplot using Altair with x axis as the hour of the day on 24 h format and
    # y axis as the demand that is on the data[column]
    data['fecha'] = data['fecha'].dt.strftime('%Y-%m-%dT%H:%M:%S') 
          
    boxplot = alt.Chart(data).mark_boxplot(size = 23,median={'color': 'red'}).encode(
        x=alt.X('hours(fecha):N', title='Hora', axis=alt.Axis(format='%H'), sort='ascending'),
        y=alt.Y(f'{column}:Q', title='Demanda [kW]'),
        stroke = alt.value('black'),  # Set thke color of the boxplot
        strokeWidth=alt.value(1),  # Set the width of the boxplot
        # color=alt.value('#4C72B0'),  # Set the color of the boxplot
        color=alt.value('#2d667a'),  # Set the color of the bars
        opacity=alt.value(1),  # Set the opacity of the bars           
        tooltip=[alt.Tooltip('hours(fecha):N', title='Hora')]  # Customize the tooltip
    )
    chart = (boxplot).properties(
        width=600,  # Set the width of the chart
        height=600,  # Set the height of the chart
        title=(f'Boxplot de demanda de potencia {column}')  # Remove date from title
    ).configure_axis(
        labelFontSize=12,  # Set the font size of axis labels
        titleFontSize=14,  # Set the font size of axis titles
        grid=True,
        # color of labels of x-axis and y-axis is black
        labelColor='black',
        # x-axis and y-axis titles are bold
        titleFontWeight='bold',
        # color of x-axis and y-axis titles is black
        titleColor='black',
        gridColor='#4C72B0',  # Set the color of grid lines
        gridOpacity=0.2  # Set the opacity of grid lines
    ).configure_view(
        strokeWidth=0,  # Remove the border of the chart
        fill='#FFFFFF'  # Set background color to white
    )

    return chart  # Enable zooming and panning

and this is my result:

I tryed conditional stroke with this code:

        stroke=alt.condition(
            alt.datum._argmax == 'q3',  # condition for the stroke color (for the box part)
            alt.value('black'),         # color for the stroke
            alt.value('red')            # color for the median line
        ),

but got median and border red as seen here:

how can i achieve my objective? i.e a red median line and black border. I also saw this note on the altair documentation

Note: The stroke encoding has higher precedence than color, thus may override the color encoding if conflicting encodings are specified.

is there any way to achieve this?

You can set the properties of the box components inside mark_boxplot as mentioned here in the docs, rather than via the encoding:

import altair as alt
from vega_datasets import data

source = data.cars()

alt.Chart(source).mark_boxplot(
    color='lightblue',
    box={'stroke': 'black'},  # Could have used MarkConfig instead
    median=alt.MarkConfig(stroke='red'),  # Could have used a dict instead
).encode(
    alt.X("Miles_per_Gallon:Q").scale(zero=False),
    alt.Y("Origin:N"),
)

The advantage of using MarkConfig instead of a dict is that you can view all the available parameter names in the help popup.