Fix Streamlit Grid State: The Ultimate 2025 Solution

# The "old" way of manually preserving edits
if "edited_df" not in st.session_state:
    st.session_state.edited_df = my_initial_dataframe

edited_data = st.data_editor(
    st.session_state.edited_df,
    key="my_manual_editor"
)

# Manually update the state after the widget runs
st.session_state.edited_df = edited_data
    

The 2025 Game-Changer: Introducing Persistent Grid State

The latest evolution in Streamlit directly tackles this headache. The core data grid components have been enhanced with a simple yet transformative parameter: persist_state. This is the ultimate solution we've been waiting for.

By setting persist_state=True, you instruct Streamlit to automatically manage the grid’s internal state—edits, sorting, filtering, and all—behind the scenes. It uses st.session_state under the hood, but it abstracts away all the manual boilerplate. You just flip a switch.

Let's see it in action. Here’s how you handle stateful edits now:

# The new, elegant 2025 solution
edited_df = st.data_editor(
    my_initial_dataframe,
    key="my_magic_editor",
    persist_state=True # <-- This is the magic!
)

# That's it. The state is handled automatically.
# You can now use edited_df for other logic.
    

Look at that. The code is cleaner, more readable, and far less error-prone. You declare your grid, tell it to remember its state, and Streamlit handles the rest. This single parameter is a massive quality-of-life improvement for anyone building data-heavy applications.

How It Works Under the Hood

So what’s happening when you set persist_state=True? It’s not black magic, but it’s close. When the component runs, it does the following:

1. It uses its unique key (e.g., "my_magic_editor") to look for a corresponding state object in st.session_state.
2. On the first run, it finds nothing, so it renders with the initial data and stores its default state in st.session_state["_grid_state_my_magic_editor"].
3. On subsequent runs, it finds the state object, applies the saved filters, sorting, and edits before rendering, and displays the grid exactly as the user left it.
4. Any new interactions update this state object automatically.

This approach gives you the best of both worlds: the simplicity of the Streamlit model and the robust statefulness of a traditional web app, without the manual overhead.

A Practical Workflow: Editing and Saving

Let's put this into a real-world scenario. You want to load a CSV, let a user edit it in a grid, and then save their changes with the click of a button. This is now incredibly straightforward.

import streamlit as st
import pandas as pd

@st.cache_data
def load_data():
    # In a real app, load from a database or file
    data = {
        'product': ['A', 'B', 'C', 'D'],
        'price': [10.0, 20.5, 15.0, 7.75],
        'inventory': [100, 50, 80, 120]
    }
    return pd.DataFrame(data)

df_original = load_data()

st.header("Product Inventory Editor")
st.write("Edit prices and inventory levels below. Your changes will be remembered as you interact with the app.")

# The stateful data editor is the star of the show
edited_df = st.data_editor(
    df_original,
    num_rows="dynamic",
    key="product_editor",
    persist_state=True
)

# Add a button to perform an action with the edited data
if st.button("Commit Changes"):
    # Compare the dataframes to see what changed
    if not edited_df.equals(df_original):
        st.success("Changes saved! 🎉")
        # In a real app, you would save `edited_df` to a database or file
        st.write("New Data:")
        st.dataframe(edited_df)
        # You could add logic here to clear the state if needed
        # del st.session_state["_grid_state_product_editor"]
    else:
        st.info("No changes were made.")
    

In this example, the user can freely edit the grid. They can add new rows, change prices, and their work is never lost on a rerun. The `edited_df` variable always holds the most current version of the data, ready to be used whenever the "Commit Changes" button is pressed.

When Manual State is Still Your Friend

Is persist_state=True a silver bullet? Almost. There are still scenarios where you might need more granular control. For instance, if you need to programmatically reset the grid's state from another widget, you can still interact with the underlying session state object directly.

Streamlit's philosophy is to provide sensible defaults and high-level APIs, while always leaving the door open for custom logic. This new feature is the perfect embodiment of that principle. It handles 95% of use cases with a single line, freeing up your mental energy to focus on the other 5%.

The Takeaway

Managing state in interactive applications is a classic challenge. With the introduction of persistent state in its core components, Streamlit has transformed a common point of friction into a moment of delight. What once required careful, manual boilerplate code is now a single, declarative argument.

So next time you're building an interactive table or grid, remember the power of persist_state=True. Give your grid a perfect memory and give your users the seamless, intuitive experience they deserve. Happy building!