gaspardc-met
commented
3 months ago Still cannot manage to reproduce the error with dummy data, but these are basically the plot operations:
numpy==2.1.0 Pandas==2.2.2 streamlit==1.37.0
import pandas as pd
import altair as alt
import streamlit as st
import functools
import numpy as np
import random
# Dummy data for the chronogram
data = pd.DataFrame(
{
"start_time": pd.date_range("2023-01-01", periods=100, freq="H").tz_localize("Europe/Paris"),
"end_time": pd.date_range("2023-01-01 01:00", periods=100, freq="H").tz_localize("Europe/Paris"),
"asset": ["Asset " + str(i % 5) for i in range(100)],
"load": [float(np.random.uniform(40, 100)) for _ in range(100)],
}
)
# Set most 'load' values for 'Asset 0' to NaN or None
asset_0_indices = data[data["asset"] == "Asset 0"].index
indices_to_nullify = random.sample(list(asset_0_indices), k=len(asset_0_indices) - 2) # Keep only 2 non-NaN
data.loc[indices_to_nullify, "load"] = np.nan # Set
data = data.reset_index()
# Placeholder functions for processing and legend (you would replace these with actual logic)
def chronogram_legend(target, pump_toggle):
return "Legend", "Short Legend", "Other Info"
def chronogram_processing(chronogram, timedelta, filter_load):
return chronogram # Simply returns the input data in this dummy example
def custom_blues():
return ["low", "medium", "high"], ["#dceefb", "#86c7f3", "#1f77b4"]
def get_assets_starts_and_stops(chronogram, timedelta, separator_dt):
# Simple dummy start/stop markers within the range
starts_and_stops = alt.Chart(chronogram).mark_rule(color="red").encode(x="start_time:T")
starts_and_stops_texts = (
alt.Chart(chronogram)
.mark_text(align="left", dx=5, dy=-5, color="red")
.encode(x="start_time:T", text=alt.value("Start/Stop"))
)
return starts_and_stops, starts_and_stops_texts
def get_vertical_separator(separator_dt, labels_y, y_field):
return None, None # Placeholder for the actual function output
# Main function with dummy data and simplified inputs
def plot_chronogram(
data: 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,
):
# Get legend information
legend, short_legend, _ = chronogram_legend(target=target, pump_toggle=pump_toggle)
# Process the data (dummy in this case)
st.write(data.dtypes)
# Example of expanding the time (dummy logic here)
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")
# Set up the color scale (dummy logic here)
if target == "pressure":
bins, colors = custom_blues()
scale = alt.Scale(domain=bins, range=colors, type="ordinal")
elif target == "load":
scale = alt.Scale(domain=[0, 50, 100], range=["#f7fbff", "#6baed6", "#08306b"], type="threshold")
else:
scale = alt.Scale(scheme="blues")
# Define the sorting order for the y-axis
sort_order = [""] + data["asset"].sort_values().unique().tolist()
# Main bar chart
chart = (
alt.Chart(data)
.mark_bar()
.encode(
x=alt.X("start_time:T", title="Horizon Temporel"),
x2=alt.X2("end_time:T", title=""),
y=alt.Y("asset: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=1100,
height=350,
)
# Text overlay layer
text = (
alt.Chart(data)
.mark_text(dx=0, dy=0, color="white", fontSize=25)
.encode(
x=alt.X("mid_time:T", title=""),
y=alt.Y("asset:N", title="Utilisation: Groupes ou AFC", 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")
# Additional text layer for a specific condition
text_hot = (
alt.Chart(data)
.mark_text(dx=0, dy=0, color="white", fontSize=25)
.encode(
x=alt.X("mid_time:T", title=""),
y=alt.Y("asset:N", title="Utilisation: Groupes ou AFC", sort=None),
text=alt.value("Chaud"),
tooltip=alt.value(None),
)
).transform_calculate(mid_time="datum.start_time + (datum.end_time - datum.start_time)/2")
# Store all charts to be layered
all_charts = [chart, text, text_hot]
# Example of including start and stop markers (dummy logic here)
if display_starts_and_stops:
starts_and_stops, starts_and_stops_texts = get_assets_starts_and_stops(
chronogram=data,
timedelta=timedelta,
separator_dt=separator_dt,
)
all_charts += [starts_and_stops, starts_and_stops_texts]
# Example of adding a vertical separator (dummy logic here)
display_separator = separator_dt is not None and separator_dt > data.index.min()
if display_separator:
separator, separator_labels = get_vertical_separator(separator_dt=separator_dt, labels_y="", y_field="asset")
all_charts += [separator, separator_labels]
# Combine all chart layers
composed = (
functools.reduce(lambda a, b: a + b, all_charts)
.configure_legend(orient="right", titleOrient="right")
.configure_axis(labelFontSize=15, titleFontSize=15)
)
# Display the composed chart in Streamlit
st.altair_chart(altair_chart=composed, use_container_width=True)
# Test the function with dummy data
plot_chronogram(data=data, display_starts_and_stops=True)
dangotbanned
What happened?
When trying to create an altair chart within a streamlit application, I run into
Uncaught Exception: dictionary changed size during iteration. Running altair 5.4.0 here, and downgrading to 5.3.0 seemed to solve this specific issue at the moment.This is with streamlit caching removed: Error stack:
I have had this error intermittently in the past, only on cloud deployments, and with altair 5.2.0. Since at the time it was intermittent and in production I attributed it at the time to a streamlit cache issue (https://github.com/streamlit/streamlit/issues/8409) Now this error is happening locally, even when I remove any caching mechanism, and it's not intermittent, it never works for that specific plot. Downgrading to altair 5.3.0 seemed to fix the issue on this specific plot for now.
I'm working on a minimal reproduction code example, but at the moment it fails to produce this error on my side with dummy data.
What would you like to happen instead?
No response
Which version of Altair are you using?
5.4.0