Need to Press "st.button" Button Twice for it to Function

I’m encountering an issue with my Streamlit app where I need to press the “Optimize” button twice for it to initiate the optimization process. I’ve tried various approaches to resolve this, but the issue persists.

Here’s a relevant excerpt of my code:

# ... [earlier parts of the code] ...

def on_optimize_button_click():
    st.session_state['optimization_results'] = None
    st.session_state['optimized'] = True
    # ... [rest of the optimization logic] ...

if st.button('Otimizar', on_click=on_optimize_button_click):
    # This block is expected to trigger the optimization process
    pass

# Rendering optimization results if available
if st.session_state.get('optimization_results'):
    render_optimization_results(
        etapas,
        st.session_state['optimization_results'],
        st.session_state['input_values'],
        st.session_state.get('recup_metal', None)
    )
    st.write(f"Otimização concluída em {st.session_state.get('elapsed_time', 0):.2f} segundos.")

# ... [rest of the code] ...

Key Points:

  • The ‘Optimize’ button requires two clicks to initiate the on_optimize_button_click function on the first attempt.
  • Subsequent attempts to trigger the function work as expected with a single click.
  • The issue seems to be isolated to the initial interaction with the button.

I am seeking insights into why this behavior occurs and how to ensure that the button responds correctly with a single click from the start.

Any guidance or suggestions would be greatly appreciated.

Thank you!

  1. Running locally
  2. Not deployed
  3. Newest streamlit and python versions.

I don’t have time to test but I don’t understand how you can make that work, no matter how many clicks. st.session_state['optimization_results'] is always None after you click the button. Or an important part of the code is missing.

PS. I tested your code and indeed on_optimize_button_click is called on each button click, including the first one. Of course render_optimization_results is never called because st.session_state.get('optimization_results') is always None.

I would recommend EITHER doing
if st.button()...
OR
st.button(..., on_click=...)

Not both – if you use both, then you will essentially be doing two different pieces of code that will run on every button press. Pick one, and it should work fine. The main difference between the two is that the on_click version will run at the beginning of the script, and the if st.button()... version will not.

Here’s a great detailed explanation of button behavior: Button behavior and examples - Streamlit Docs

1 Like

I am reaching out to seek additional assistance regarding an ongoing issue I have encountered in my Streamlit application. Despite having explored and attempted various solutions suggested in the forum, the problem persists, and I find myself in need of more in-depth guidance.

Issue Description: I am experiencing an issue where users need to click twice on the “Optimize” button in my application to trigger the function on the first attempt. This behavior changes to a single click in subsequent attempts unless the user switches tabs within our web app. In that case, the two-click requirement returns. The issue does not occur if the user modifies any values in input_df, wherein a single click suffices for optimization.

Attempted Resolutions: I have tried the following solutions based on the forum discussions and Streamlit documentation:

  • Ensuring proper initialization of variables in st.session_state.
  • Structuring the button logic to ensure the associated function is called only when the button is pressed.
  • Checking for conditional rendering logic to ensure widgets are rendered as expected.

Despite these efforts, the issue remains unresolved.

Request for a Meeting: Given the complexity of the issue and the importance of resolving it promptly for our users, I am kindly requesting the possibility of scheduling a call or meeting with a knowledgeable member of the Streamlit community. This would provide an opportunity for a more detailed discussion and potentially expedite the resolution of the problem.

I am available for a call in English and can adapt to the time zone preferences of the person assisting me.

Thank you very much for your attention and support. I am looking forward to any assistance or guidance the Streamlit community can provide.

Best regards,

Gabriel Gomes

Hey @Gabriel_Gomes, unfortunately our team is not able to meet live to help debug apps, but we’re happy to keep helping you debug in this forum thread.

Have you changed your code to only use if st.button()... or st.button(..., on_click=...) (not both)?

As part of my efforts to resolve issues with my Streamlit application, specifically related to the ‘Optimize’ button, I’ve implemented and tried several approaches:

  1. Automatic Execution on Page Load: I set up the application to automatically execute the optimization function, on_optimize_button_click, when the page initially loads. This was intended to simulate an initial click on the ‘Optimize’ button, hoping to avoid the need for a second click to activate the function.
  2. State Initialization with st.session_state: To manage the app’s state effectively, I utilized Streamlit’s st.session_state. I initialized various variables in the initialize_state function to ensure the app started with a consistent state. This was crucial in managing the behavior of the ‘Optimize’ button.
  3. Adjusting Function Definitions: I encountered a ‘NameError’ due to the order of function definitions. To resolve this, I reorganized the code so that on_optimize_button_click was defined before being called in initialize_state. This ensured all functions were properly recognized within the script.
  4. Simulating Button Click: I tried simulating a button click by auto-invoking the optimization function on the initial page load. This approach was taken to circumvent the issue of requiring an additional manual click for the first operation.
  5. Preparing Comprehensive DataFrame: I made sure that input_df included all necessary features for the model’s prediction. This involved aligning input_df with the original data structure used in training the model.
  6. Streamlining Button Code: Additionally, I revised the implementation of the ‘Optimize’ button in my Streamlit code. Initially, I was using both if st.button() and st.button(..., on_click=...) for the button functionality. I realized this might be causing issues, so I changed the code to only use one of these methods – either if st.button() or st.button(..., on_click=...), but not both simultaneously. This was done in an effort to simplify the button’s logic and potentially resolve the clicking issue, but not worked.

Hi @Gabriel_Gomes,

Here’s a screen recording of what I see when I run the following code:

import streamlit as st

def on_optimize_button_click():
    st.write("button clicked")
    st.session_state['optimization_results'] = None
    st.session_state['optimized'] = True
    # ... [rest of the optimization logic] ...

st.button('Otimizar', on_click=on_optimize_button_click)

# Rendering optimization results if available
if st.session_state.get('optimization_results'):
    render_optimization_results(
        etapas,
        st.session_state['optimization_results'],
        st.session_state['input_values'],
        st.session_state.get('recup_metal', None)
    )
    st.write(f"Otimização concluída em {st.session_state.get('elapsed_time', 0):.2f} segundos.")

Is this different from what you’re seeing when you run that code?

Thank you for the follow-up and for running the test code. The code snippet you’ve provided is indeed a simplified version of my implementation. While the core logic of the button click function (on_optimize_button_click) and the conditional rendering of optimization results is similar, my actual implementation is a bit more complex. Here are some key differences and additional context:

  1. Complexity in Optimization Logic:
  • My on_optimize_button_click function involves more than just setting state variables. It includes complex optimization logic that interacts with a machine learning model and processes data from a Streamlit session state.
  1. Session State Initialization:
  • I have a custom initialization function to set up various session state variables at the start. This initialization might be affecting the behavior of the button click, especially during the first run of the app.
  1. Conditional Rendering Based on Multiple States:
  • In my application, the rendering of optimization results depends on multiple session state variables, not just optimization_results. This adds an extra layer of conditional checks that might be impacting the button’s behavior.
  1. Issue with the First Click:
  • The primary issue I’m facing is that upon the first interaction with the page, the ‘Otimizar’ button requires two clicks to trigger the optimization process and render the results. Subsequent clicks behave as expected (a single click is sufficient while i do not change the streamlit internal page).

Could there be a specific reason why the first click on the ‘Otimizar’ button doesn’t seem to trigger the on_optimize_button_click function properly only on the first interaction? This behavior resets when navigating away and back to the page or on page refresh.

Any insights or suggestions on how to resolve this particular issue would be greatly appreciated.

In all of your code snippets that I have tested (here and in the other thread), on_optimize_button_click is called on every button click, including the first one.

Post a piece of code that we can run and shows the issue in the simplest possible way. Test it before posting to make sure it actually shows the issue. Then, hopefully, somebody will be able to spot what is wrong and tell you how to fix it.

I am having similar issues. Is the button on your app inside a tab or some similar structure? In that case, I think the first click is interpreted as selecting the tab instead of clicking the button, so that’s why you need the second click to actually click the button. This behavior is not intuitive at all but I haven’t been able to find a proper solution until now.

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