TypeError: FacetedEncoding.init() got multiple values for argument 'self'

[gaspardc-met]

What happened?

Using a complex altair chart in streamlit, worked in 5.3.0, and broke with 5.4.0 and then 5.4.1.
It seems to be an altair issue: TypeError: FacetedEncoding.init() got multiple values for argument 'self'

I tried to reproduce the error with the plot code and anonymized example data.
The error didn't show up neither with altair alone nor streamlit+altair.

However, it might give you an idea of the plot I use. The error happens in the first call to .encode in the fonction .mark_bar.encode()

Long Code Block

import functools

import altair as alt
import numpy as np
import pandas as pd
import streamlit as st

# Mocked dependencies and constants
CMAP_BINS = [0, 0.25, 0.5, 0.75, 1.0]
CMAP_COLORS = ["#f7fbff", "#c6dbef", "#6baed6", "#2171b5", "#08306b"]


def custom_blues():
    bins = [0, 0.25, 0.5, 0.75, 1.0]
    colors = ["#f7fbff", "#c6dbef", "#6baed6", "#2171b5", "#08306b"]
    return bins, colors


def chronogram_legend(target="load", pump_toggle=False):
    legend = "Load Legend"
    short_legend = "Load"
    extra = None
    return legend, short_legend, extra


def chronogram_processing(chronogram, timedelta="60min", filter_load=True):
    data = chronogram.copy()
    data["start_time"] = data.index
    data["end_time"] = data.index + pd.Timedelta(timedelta)
    return data.reset_index(drop=True)


def get_machines_starts_and_stops(chronogram, timedelta="60min", separator_dt=None):
    starts_and_stops = alt.Chart(pd.DataFrame({"x": [], "y": []}))
    starts_and_stops_texts = alt.Chart(pd.DataFrame({"x": [], "y": []}))
    return starts_and_stops, starts_and_stops_texts


def get_vertical_separator(separator_dt, labels_y="", y_field="machine"):
    separator = alt.Chart(pd.DataFrame({"x": [], "y": []}))
    separator_labels = alt.Chart(pd.DataFrame({"x": [], "y": []}))
    return separator, separator_labels


@st.cache_data(show_spinner=False, ttl=60 * 60)  # TTL in seconds
def plot_chronogram(
    chronogram: pd.DataFrame,
    formatted=".0f",
    target="load",
    timedelta="60min",
    filter_load=True,
    expand: bool = False,
    pump_toggle: bool = False,
    display_starts_and_stops: bool = False,
    separator_dt: pd.Timestamp = None,
):
    legend, short_legend, _ = chronogram_legend(target=target, pump_toggle=pump_toggle)
    data = chronogram_processing(chronogram=chronogram, timedelta=timedelta, filter_load=filter_load)
    if expand:
        data = data.set_index("start_time").sort_index().reset_index()
        data.loc[28:, "end_time"] = data.loc[28:, "end_time"] + pd.Timedelta("45T")

    if target == "pressure":
        bins, colors = custom_blues()
        scale = alt.Scale(domain=bins, range=colors, type="ordinal")
    elif target == "load":
        scale = alt.Scale(domain=CMAP_BINS, range=CMAP_COLORS, type="threshold")
    else:
        scale = alt.Scale(scheme="blues")

    sort_order = [""] + data["machine"].sort_values().unique().tolist()

    chart = (
        alt.Chart(data)
        .mark_bar()
        .encode(
            x=alt.X("start_time:T", title="Horizon Temporel"),
            x2=alt.X2("end_time:T"),
            y=alt.Y("machine:N", title="Utilisation: Groupes ou AFC", sort=sort_order),
            color=alt.Color(
                "load:Q",
                title=short_legend,
                scale=scale,
                legend=alt.Legend(title=legend),
            ),
            stroke=alt.value("white"),
            strokeWidth=alt.value(2),
            tooltip=[
                alt.Tooltip("start_time:T", format="%Y-%m-%d", title="Date"),
                alt.Tooltip("start_time:T", format="%H:%M", title="Heure"),
                alt.Tooltip("load:Q", format=formatted, title=legend),
            ],
        )
    ).properties(
        title=f"Chronogramme d'opération: {legend}",
        width=800,
        height=350,
    )

    text = (
        alt.Chart(data)
        .mark_text(dx=0, dy=0, color="white", fontSize=10)
        .encode(
            x=alt.X("mid_time:T"),
            y=alt.Y("machine:N", sort=None),
            text=alt.Text("load:Q", format=formatted),
            tooltip=[
                alt.Tooltip("start_time:T", format="%Y-%m-%d", title="Date"),
                alt.Tooltip("start_time:T", format="%H:%M", title="Heure"),
                alt.Tooltip("load:Q", format=formatted, title=legend),
            ],
        )
        .transform_calculate(mid_time="datum.start_time + (datum.end_time - datum.start_time)/2")
        .transform_filter((alt.datum.load >= 0.0) & (alt.datum.load != 0.01))
    )

    text_hot = (
        alt.Chart(data)
        .mark_text(dx=0, dy=0, color="white", fontSize=10)
        .encode(
            x=alt.X("mid_time:T"),
            y=alt.Y("machine:N", sort=None),
            text=alt.value("Chaud"),
            tooltip=alt.value(None),
        )
        .transform_calculate(mid_time="datum.start_time + (datum.end_time - datum.start_time)/2")
        .transform_filter(alt.datum.load == 0.01)
    )

    all_charts = [chart, text, text_hot]

    if display_starts_and_stops:
        starts_and_stops, starts_and_stops_texts = get_machines_starts_and_stops(
            chronogram=chronogram,
            timedelta=timedelta,
            separator_dt=separator_dt,
        )
        all_charts += [starts_and_stops, starts_and_stops_texts]

    display_separator = separator_dt is not None and separator_dt > chronogram.index.min()
    if display_separator:
        separator, separator_labels = get_vertical_separator(separator_dt=separator_dt, labels_y="", y_field="machine")
        all_charts += [separator, separator_labels]

    composed = (
        functools.reduce(lambda a, b: a + b, all_charts)
        .configure_legend(orient="right", titleOrient="right")
        .configure_axis(labelFontSize=12, titleFontSize=12)
    )

    return composed


# Main block to generate and display the chart
if __name__ == "__main__":
    # Generate fake data
    date_range = pd.date_range(start="2022-01-01", periods=48, freq="30min")
    data = pd.DataFrame(index=date_range)
    data["machine"] = np.random.choice(["A", "B", "C"], size=len(data))
    data["load"] = np.random.rand(len(data))

    # Call the plotting function
    chart = plot_chronogram(chronogram=data)

    st.altair_chart(chart)

What would you like to happen instead?

No response

Which version of Altair are you using?

altair: 5.4.1
python: 3.11

[dangotbanned]

Using a complex altair chart in streamlit, worked in 5.3.0, and broke with 5.4.0 and then 5.4.1. It seems to be an altair issue: TypeError: FacetedEncoding.init() got multiple values for argument 'self'

I tried to reproduce the error with the plot code and anonymized example data. The error didn't show up neither with altair alone nor streamlit+altair.

@gaspardc-met could you provide the traceback please?

I'm unsure what FacetedEncoding.init() is referring to, as that isn't a method on alt.FacetedEncoding:

Repro

import altair as alt

>>> alt.FacetedEncoding().init()

Traceback

AttributeError                            Traceback (most recent call last)
Cell In[17], line 3
      1 import altair as alt
----> 3 alt.FacetedEncoding().init()

File c:/../altair/altair/utils/schemapi.py:1063, in SchemaBase.__getattr__(self, attr)
   1061 except AttributeError:
   1062     _getattr = super().__getattribute__
-> 1063 return _getattr(attr)

AttributeError: 'FacetedEncoding' object has no attribute 'init'