AttributeError when displaying image on streamlit web app

Question

I am trying to display results of PM4PY algorithm on streamlit webApp. I was advised to display it as image (it doesn't need to be image if you have other recommendation), however I am facing AttributeError: 'NoneType' object has no attribute 'read' when doing so - the error is coming from image.open()

case_id	activity_id	timestamp
1	Accepted	2021-12-20T15:52:47
1	Awaiting Documentation	2021-12-20T14:57:58
1	Complete Activated	2021-12-20T14:59:14
2	Approved	2021-12-20T14:57:59

My code:

import pm4py
import streamlit as st
from PIL import Image

@st.cache
def prepare_df():
    df1 = df[["case_id", "activity_id", "timestamp"]]
    df1["case_id"] = df1["case_id"].astype(str)
    df1["activity_id"] = df1["activity_id"].astype(str)
    df_log = pm4py.format_dataframe(df1, case_id='case_id', activity_key='activity_id', timestamp_key='timestamp')
    return df_log

df_log = prepare_df()

bpm_discovery = st.container()

map2 = pm4py.discover_heuristics_net(df_log)
image2 = Image.open(pm4py.view_heuristics_net(map2))

with bpm_discovery:
     st.image(image2, caption=‘Heuristic Minners algorithm’)

The error I am getting:

AttributeError: 'NoneType' object has no attribute 'read'
Traceback:
File "C:\Users\HAXY8W\PycharmProjects\processAnalysisApp\venv\lib\site-packages\streamlit\scriptrunner\script_runner.py", line 443, in _run_script
    exec(code, module.__dict__)
File "C:\Users\HAXY8W\PycharmProjects\processAnalysisApp\processAnalysis.py", line 83, in <module>
    image2 = Image.open(pm4py.view_heuristics_net(map2))
File "C:\Users\HAXY8W\PycharmProjects\processAnalysisApp\venv\lib\site-packages\PIL\Image.py", line 3074, in open
    fp = io.BytesIO(fp.read())

ferdy · Accepted Answer · 2022-04-05 04:48:14Z

2

Convert the net to png and show it by streamlit. There is also an option to save in memory (commented out).

Code

import pm4py
import streamlit as st
# from PIL import Image
import pandas as pd
import io


d = {
    'case_id': [1, 1, 1, 2],
    'activity_id': ['Accepted', 'Awaiting Documentation',
    'Complete Activated', 'Approved'],
    'timestamp': ['2021-12-20T15:52:47', '2021-12-20T14:57:58',
    '2021-12-20T14:59:14', '2021-12-20T14:57:59']
}

@st.cache
def prepare_df(df):
    df1 = df[["case_id", "activity_id", "timestamp"]]
    df1["case_id"] = df1["case_id"].astype(str)
    df1["activity_id"] = df1["activity_id"].astype(str)
    df_log = pm4py.format_dataframe(df1, case_id='case_id', activity_key='activity_id', timestamp_key='timestamp')
    return df_log

st.title('pm4py on streamlit')

df = pd.DataFrame(d)

df_log = prepare_df(df)

bpm_discovery = st.container()

map2 = pm4py.discover_heuristics_net(df_log)

# 1. Save to file and show it by streamlit.
fn = 'a.png'
pm4py.save_vis_heuristics_net(map2, fn)

# 2. Save to memory.
# image2 = io.BytesIO(pm4py.view_heuristics_net(map2))

with bpm_discovery:
     st.image(fn, caption='Heuristic Minners algorithm')

Output

answered Apr 5, 2022 at 4:48

ferdy

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1 Comment

Sam.H Over a year ago

thanks. The first one worked (saving as png) the memory solution didn't work, gave me the same error when rendering on the webApp

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