dangotbanned
commented
1 month ago 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'
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
.encodein the fonction.mark_bar.encode()Long Code Block
```python 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