updates on create_visualisations page in microgrowth to make the sele… (#51)

* updates on create_visualisations page in microgrowth to make the selected plotting parameters persist between pages

* update explanation of use of js for checking preselected boxes in aggrid when reloading the table

* 🎨 format

* Replace JS grid-restore hack with an explicit save-selection button

Drop the JsCode-based re-check of preselected AgGrid rows on mount
(flagged in review as odd to see JS for this). Instead, only persist
the checked rows into session state when the user clicks a "Save
selection" button, so navigating away and back no longer wipes the
saved selection just because the grid remounts unchecked.

* Replace AgGrid selection with a native data_editor checkbox column

The previous "Save selection" button still read live state off an
AgGrid component, which remounts unchecked on page navigation - so
clicking Save after navigating back silently wrote an empty selection
over the previously saved one. st.data_editor is a first-party
Streamlit widget whose checked state is rebuilt from session state on
every render, so it reflects the saved selection correctly right after
navigating back, and Save now reliably captures what's shown. Also
drops the now-unused streamlit-aggrid dependency.

* update streamlit to 1.59 so sample selection table can st.dataframe with multiselect. remove aggrid dependency

* add claude skills to git ignore

---------

Co-authored-by: Henry Webel <heweb@dtu.dk>
Co-authored-by: enryh <noreply@anthropic.com>

Author: 3 people

.gitignore

@@ -2,3 +2,7 @@
 .pytest_cache
 *.egg-info
 *.pyc
+
+# Streamlit agent skills (environment-specific symlinks)
+.agents/skills/developing-with-streamlit
+.claude/skills/developing-with-streamlit

MicroGrowth/README.md

@@ -273,7 +273,6 @@ The threshold is configurable and affects how conservatively phase transitions a
 - xlrd (for .xls file support)
 - growthcurves (core analysis package)
 - streamlit_sortables
-- streamlit-aggrid
 
 See `requirements.txt` or `environment.yaml` for specific versions.
 

MicroGrowth/environment.yaml

@@ -8,14 +8,13 @@ dependencies:
   - pandas=2.3.3
   - scipy=1.16.3
   - plotly=6.3.1
-  - streamlit=1.52.0
+  - streamlit=1.59.2
   - openpyxl=3.1.5 # .xlsx support
   - xlrd=2.0.2 # .xls support (legacy)
   - pip:
       - kaleido==0.2.1
       - streamlit-plotly-events
       - streamlit-sortables==0.3.1
-      - streamlit-aggrid==1.2.1
       - st_selectable_grid==1.0.0
       - pyod==2.0.7
       - growthcurves>=0.7.1

MicroGrowth/requirements.txt

@@ -3,11 +3,10 @@ pandas==2.3.3
 scipy==1.16.3
 plotly==6.3.1
 kaleido==0.2.1
-streamlit==1.52.0
+streamlit==1.59.2
 openpyxl==3.1.5
 xlrd==2.0.2
 growthcurves>=0.7.1
 pyod==2.0.7
 streamlit_sortables==0.3.1
-streamlit-aggrid==1.2.1
 st_selectable_grid==1.0.0

MicroGrowth/src/ui_functions/create_visualizations_ui.py

@@ -4,10 +4,43 @@
 import streamlit as st
 from src.functions.visualization_functions import _unique_preserve_order
 from src.styling import data_grid_style
-from st_aggrid import AgGrid, GridOptionsBuilder, GridUpdateMode
 from streamlit_sortables import sort_items
 
 
+def _persistent_selectbox(container, label, options, store_key):
+    """Selectbox whose selection survives page navigation via a plain state key."""
+    wkey = f"{store_key}_widget"
+    stored = st.session_state.get(store_key)
+    st.session_state.setdefault(wkey, stored if stored in options else options[0])
+    value = container.selectbox(label, options, key=wkey)
+    st.session_state[store_key] = value
+    return value
+
+
+def _persistent_sortable(order_key, label, values, sig_extra=None):
+    """Drag-sortable list whose order survives navigation; empty values keep the order."""
+    sig_key = f"{order_key}_sig"
+    ver_key = f"{order_key}_ver"
+    st.session_state.setdefault(order_key, [])
+    st.session_state.setdefault(ver_key, 0)
+    if values:
+        order = [v for v in st.session_state[order_key] if v in values]
+        order += [v for v in values if v not in order]
+        st.session_state[order_key] = order
+
+        sig = (sig_extra, tuple(values))
+        if st.session_state.get(sig_key) != sig:
+            st.session_state[sig_key] = sig
+            st.session_state[ver_key] += 1
+
+        st.markdown(f"**{label}**")
+        st.session_state[order_key] = sort_items(
+            st.session_state[order_key],
+            key=f"{order_key}_sortable_{st.session_state[ver_key]}",
+        )
+    return [v for v in st.session_state[order_key] if v in values]
+
+
 def ui_growth_selection_container(plates: dict) -> dict:
     """Render the sample selection container and return selection context."""
     # Build options once per rerun.
@@ -43,87 +76,44 @@ def ui_growth_selection_container(plates: dict) -> dict:
     # -----------------------------
     sel_key = "growth_combined_sel"
     sel = st.session_state.setdefault(sel_key, {})
-    st.session_state[sel_key] = {sid: bool(sel.get(sid, False)) for sid in ids}
-    sel = st.session_state[sel_key]
-    grid_ver_key = "sample_selection_grid_ver"
-    st.session_state.setdefault(grid_ver_key, 0)
-
-    def _selected_ids():
-        return [sid for sid in ids if sel.get(sid, False)]
-
-    def _selected_opt_rows(sel_ids: list[str]) -> pd.DataFrame:
-        if not sel_ids:
-            return opt.iloc[0:0].copy()
-        return opt[opt["_id"].isin(sel_ids)].copy()
 
     # -----------------------------
     # UI: Step 1 selection (outside form so grid changes rerun)
     # -----------------------------
     with st.container(border=True):
         st.header("Step 1. Select Samples for Visualization")
 
-        # Apply styling for data grid (moved to styling.py)
         data_grid_style()
 
-        # Prepare dataframe for display with selection column
         if has_split:
             display_cols = ["Plate", "Sample Name", "Strain", "Condition", "Wells"]
         else:
             display_cols = ["Plate", "Sample Name", "Wells"]
 
-        display_df = opt[display_cols + ["_id"]].copy()
-
-        gb = GridOptionsBuilder.from_dataframe(display_df)
-        gb.configure_selection(
-            "multiple",
-            use_checkbox=True,
-            rowMultiSelectWithClick=True,
-        )
-        gb.configure_column("_id", hide=True)
-        gb.configure_columns(display_cols, editable=False)
-        if display_cols:
-            gb.configure_column(
-                display_cols[0],
-                headerCheckboxSelection=True,
-                checkboxSelection=True,
-            )
-        grid_options = gb.build()
-        pre_selected_rows = [idx for idx, sid in enumerate(ids) if sel.get(sid, False)]
-        grid_response = AgGrid(
-            display_df,
-            gridOptions=grid_options,
-            update_mode=GridUpdateMode.SELECTION_CHANGED,
-            pre_selected_rows=pre_selected_rows,
-            fit_columns_on_grid_load=True,
+        # selection_default only applies when the widget's keyed state is absent,
+        # so it restores the saved ticks on returning from another page.
+        event = st.dataframe(
+            opt[display_cols],
+            hide_index=True,
+            width="stretch",
             height=400,
-            width="100%",
-            key=f"sample_selection_grid_{st.session_state[grid_ver_key]}",
-        )
-        selected_rows = grid_response.get("selected_rows")
-        if selected_rows is None:
-            selected_ids = set()
-        elif isinstance(selected_rows, pd.DataFrame):
-            selected_ids = set(
-                selected_rows.get("_id", pd.Series([], dtype=str)).tolist()
-            )
-        elif isinstance(selected_rows, list):
-            if selected_rows and isinstance(selected_rows[0], dict):
-                selected_ids = {
-                    row.get("_id") for row in selected_rows if row.get("_id")
+            on_select="rerun",
+            selection_mode="multi-row",
+            selection_default={
+                "selection": {
+                    "rows": [i for i, sid in enumerate(ids) if sel.get(sid, False)]
                 }
-            else:
-                selected_ids = {row for row in selected_rows if isinstance(row, str)}
-        else:
-            selected_ids = set()
-        for sid in ids:
-            sel[sid] = sid in selected_ids
-
-        sel_ids = _selected_ids()
-        sel_opt = _selected_opt_rows(sel_ids)
-        sel_sample_names = (
-            _unique_preserve_order(sel_opt["Sample Name"].astype(str).tolist())
-            if not sel_opt.empty
-            else []
+            },
+            key="sample_selection_grid",
+        )
+
+        chosen = set(event.selection.rows)
+        st.session_state[sel_key] = {sid: i in chosen for i, sid in enumerate(ids)}
+
+        sel_ids = [sid for i, sid in enumerate(ids) if i in chosen]
+        sel_opt = opt[opt["_id"].isin(sel_ids)].copy()
+        sel_sample_names = _unique_preserve_order(
+            sel_opt["Sample Name"].astype(str).tolist()
         )
 
     return {
@@ -139,22 +129,6 @@ def _selected_opt_rows(sel_ids: list[str]) -> pd.DataFrame:
 @st.fragment
 def ui_growth_stats_controls_container(has_split: bool, sel_opt: pd.DataFrame) -> dict:
     """Render growth stats controls and return form selections."""
-    # -----------------------------
-    # Order state (stats x-axis + legend)
-    # -----------------------------
-    x_order_key = "growth_stats_x_order"
-    x_order_sig_key = "growth_stats_x_order_sig"
-    x_order_ver_key = "growth_stats_x_order_ver"
-
-    leg_order_key = "growth_stats_legend_order"
-    leg_order_sig_key = "growth_stats_legend_order_sig"
-    leg_order_ver_key = "growth_stats_legend_order_ver"
-
-    st.session_state.setdefault(x_order_key, [])
-    st.session_state.setdefault(x_order_ver_key, 0)
-    st.session_state.setdefault(leg_order_key, [])
-    st.session_state.setdefault(leg_order_ver_key, 0)
-
     with st.container(border=True):
         st.header("Step 2. option a) Plot Growth Statistics")
 
@@ -165,17 +139,11 @@ def ui_growth_stats_controls_container(has_split: bool, sel_opt: pd.DataFrame) -
             group_choices += ["Strain", "Condition"]
 
         cA, cB = st.columns([1, 1])
-        x_col = cA.selectbox(
-            "X-axis column",
-            options=x_choices,
-            index=0,
-            key="growth_stats_x_col",
+        x_col = _persistent_selectbox(
+            cA, "X-axis column", x_choices, "growth_stats_x_col"
         )
-        legend_group = cB.selectbox(
-            "Legend grouping",
-            options=group_choices,
-            index=0,
-            key="growth_stats_legend_group",
+        legend_group = _persistent_selectbox(
+            cB, "Legend grouping", group_choices, "growth_stats_legend_group"
         )
         legend_col = None if legend_group == "None" else legend_group
 
@@ -190,53 +158,15 @@ def ui_growth_stats_controls_container(has_split: bool, sel_opt: pd.DataFrame) -
             else []
         )
 
-        # drag ordering: x-axis
-        cur_x_order = [v for v in st.session_state[x_order_key] if v in x_vals]
-        for v in x_vals:
-            if v not in cur_x_order:
-                cur_x_order.append(v)
-        st.session_state[x_order_key] = cur_x_order
-
-        x_sig = (x_col, tuple(x_vals))
-        if st.session_state.get(x_order_sig_key) != x_sig:
-            st.session_state[x_order_sig_key] = x_sig
-            st.session_state[x_order_ver_key] += 1
-
-        if x_vals:
-            st.markdown("**Drag to set x-axis order:**")
-            st.session_state[x_order_key] = sort_items(
-                st.session_state[x_order_key],
-                key=f"growth_stats_x_sortable_{st.session_state[x_order_ver_key]}",
-            )
-
-        # drag ordering: legend
-        if legend_col:
-            cur_leg_order = [
-                v for v in st.session_state[leg_order_key] if v in legend_vals
-            ]
-            for v in legend_vals:
-                if v not in cur_leg_order:
-                    cur_leg_order.append(v)
-            st.session_state[leg_order_key] = cur_leg_order
-
-            leg_sig = (legend_col, tuple(legend_vals))
-            if st.session_state.get(leg_order_sig_key) != leg_sig:
-                st.session_state[leg_order_sig_key] = leg_sig
-                st.session_state[leg_order_ver_key] += 1
-
-            if legend_vals:
-                st.markdown("**Drag to set legend order:**")
-                st.session_state[leg_order_key] = sort_items(
-                    st.session_state[leg_order_key],
-                    key=f"growth_stats_leg_sortable_{st.session_state[leg_order_ver_key]}",
-                )
-
-    x_ordered = [v for v in st.session_state[x_order_key] if v in x_vals]
-    legend_ordered = (
-        [v for v in st.session_state[leg_order_key] if v in legend_vals]
-        if legend_col
-        else []
-    )
+        x_ordered = _persistent_sortable(
+            "growth_stats_x_order", "Drag to set x-axis order:", x_vals, x_col
+        )
+        legend_ordered = _persistent_sortable(
+            "growth_stats_legend_order",
+            "Drag to set legend order:",
+            legend_vals,
+            legend_col,
+        )
 
     return {
         "x_col": x_col,
@@ -251,51 +181,30 @@ def ui_growth_curves_controls_container(
     max_t: float, sel_sample_names: list[str]
 ) -> dict:
     """Render growth curves controls and return form selections."""
-    # -----------------------------
-    # Order state (curves sample order: mean+reps)
-    # -----------------------------
-    curves_order_key = "growth_curves_sample_order"
-    curves_order_sig_key = "growth_curves_sample_order_sig"
-    curves_order_ver_key = "growth_curves_sample_order_ver"
-    st.session_state.setdefault(curves_order_key, [])
-    st.session_state.setdefault(curves_order_ver_key, 0)
-
     with st.container(border=True):
         st.header("Step 2. option b) Plot Growth Curves")
 
+        # Persist across navigation via a plain key; re-seed widget when absent.
+        tw_key = "growth_curves_time_window"
+        tw_wkey = f"{tw_key}_widget"
+        lo0, hi0 = st.session_state.get(tw_key, (0.0, min(72.0, max_t)))
+        lo0 = min(max(float(lo0), 0.0), max_t)
+        hi0 = min(max(float(hi0), lo0), max_t)
+        st.session_state.setdefault(tw_wkey, (lo0, hi0))
         curves_t0, curves_t1 = st.slider(
             "Mean/replicates plot time window (hours)",
             0.0,
             max_t,
-            (0.0, min(72.0, max_t)),
             step=0.5,
-            key="growth_curves_time_window",
+            key=tw_wkey,
         )
+        st.session_state[tw_key] = (curves_t0, curves_t1)
 
-        # drag ordering: sample names (specific to mean+reps)
-        cur_curves_order = [
-            v for v in st.session_state[curves_order_key] if v in sel_sample_names
-        ]
-        for v in sel_sample_names:
-            if v not in cur_curves_order:
-                cur_curves_order.append(v)
-        st.session_state[curves_order_key] = cur_curves_order
-
-        curves_sig = tuple(sel_sample_names)
-        if st.session_state.get(curves_order_sig_key) != curves_sig:
-            st.session_state[curves_order_sig_key] = curves_sig
-            st.session_state[curves_order_ver_key] += 1
-
-        if sel_sample_names:
-            st.markdown("**Drag to set Sample Name order (mean/replicates):**")
-            st.session_state[curves_order_key] = sort_items(
-                st.session_state[curves_order_key],
-                key=f"growth_curves_sortable_{st.session_state[curves_order_ver_key]}",
-            )
-
-    curves_ordered = [
-        v for v in st.session_state[curves_order_key] if v in sel_sample_names
-    ]
+        curves_ordered = _persistent_sortable(
+            "growth_curves_sample_order",
+            "Drag to set Sample Name order (mean/replicates):",
+            sel_sample_names,
+        )
 
     return {
         "curves_t0": curves_t0,

pyproject.toml

@@ -23,7 +23,9 @@ dependencies = [
     "scipy",
     "matplotlib",
     "seaborn",
-    "streamlit>=1.52.0",
+    # 1.56.0 added st.dataframe(selection_default=...), which Step 1 sample
+    # selection needs to restore ticked rows after page navigation.
+    "streamlit>=1.56.0",
     "growthcurves",
 ]
 # use requirements.txt instead of pyproject.toml for dependencies