deploy: 4e25da6

Author: mwouts

_sources/advanced_parameters.ipynb

@@ -2,32 +2,28 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "722020df",
+   "id": "8948530e",
    "metadata": {},
    "source": [
     "# Dash\n",
     "\n",
-    "ITables includes a Dash component since v2.3.0.\n",
-    "\n",
-    "## Displaying a DataFrame\n",
-    "\n",
     "If you wish to display a DataFrame which content is fixed (not reacting to the other controls in the application), you just need to import `ITable` from `itables.dash` and add it to your layout like here:\n",
     "\n",
-    "```{include} ../apps/dash/1_display_only.py\n",
+    "```{include} ../../apps/dash/1_display_only.py\n",
     ":code: python\n",
     "```\n",
     "\n",
     "## Selected rows\n",
     "\n",
     "Listening to the selected rows is simply done by adding `select=True` to the `ITable` call, and then implementing a callback on `Input(\"my_dataframe\", \"selected_rows\")`.\n",
     "\n",
-    "```{include} ../apps/dash/2_selected_rows.py\n",
+    "```{include} ../../apps/dash/2_selected_rows.py\n",
     ":code: python\n",
     "```\n",
     "\n",
     "## Updating the DataFrame\n",
     "\n",
-    "The `ITable` component has many properties. These properties (data, columns, selected rows etc) need to be updated in a consistent way. Therefore we recommend that you list the outputs with `ITableOutputs(\"my_dataframe\")` in your callback, and update them with `updated_itable_outputs` which takes the same arguments as `show`, e.g. `df`, `caption`, `selected_rows`, etc, like in the below (extracted from this [example app](https://github.com/mwouts/itables/tree/main/apps/dash/3_update_table.py)):\n",
+    "The `ITable` component has many properties. These properties (table content, selected rows etc) need to be updated in a consistent way. Therefore we recommend that you list the outputs with `ITableOutputs(\"my_dataframe\")` in your callback, and update them with `updated_itable_outputs` which takes the same arguments as `show`, e.g. `df`, `caption`, `selected_rows`, etc, like in the below (extracted from this [example app](https://github.com/mwouts/itables/tree/main/apps/dash/3_update_table.py)):\n",
     "\n",
     "```python\n",
     "from itables.dash import ITable, ITableOutputs, updated_itable_outputs\n",
@@ -60,13 +56,7 @@
     "    return updated_itable_outputs(\n",
     "        caption=caption, selected_rows=selected_rows, current_dt_args=dt_args, **kwargs\n",
     "    )\n",
-    "```\n",
-    "\n",
-    "## Limitations\n",
-    "\n",
-    "Compared to `show`, the `ITable` component has the same limitations as the [Jupyter Widget](widget.md#limitations)\n",
-    "or the [Streamlit component](streamlit.md#limitations),\n",
-    "e.g. structured headers are not available, you can't pass JavaScript callback, etc."
+    "```"
    ]
   }
  ],

_sources/advanced_parameters.md

@@ -14,27 +14,23 @@ kernelspec:
 
 # Dash
 
-ITables includes a Dash component since v2.3.0.
-
-## Displaying a DataFrame
-
 If you wish to display a DataFrame which content is fixed (not reacting to the other controls in the application), you just need to import `ITable` from `itables.dash` and add it to your layout like here:
 
-```{include} ../apps/dash/1_display_only.py
+```{include} ../../apps/dash/1_display_only.py
 :code: python
 ```
 
 ## Selected rows
 
 Listening to the selected rows is simply done by adding `select=True` to the `ITable` call, and then implementing a callback on `Input("my_dataframe", "selected_rows")`.
 
-```{include} ../apps/dash/2_selected_rows.py
+```{include} ../../apps/dash/2_selected_rows.py
 :code: python
 ```
 
 ## Updating the DataFrame
 
-The `ITable` component has many properties. These properties (data, columns, selected rows etc) need to be updated in a consistent way. Therefore we recommend that you list the outputs with `ITableOutputs("my_dataframe")` in your callback, and update them with `updated_itable_outputs` which takes the same arguments as `show`, e.g. `df`, `caption`, `selected_rows`, etc, like in the below (extracted from this [example app](https://github.com/mwouts/itables/tree/main/apps/dash/3_update_table.py)):
+The `ITable` component has many properties. These properties (table content, selected rows etc) need to be updated in a consistent way. Therefore we recommend that you list the outputs with `ITableOutputs("my_dataframe")` in your callback, and update them with `updated_itable_outputs` which takes the same arguments as `show`, e.g. `df`, `caption`, `selected_rows`, etc, like in the below (extracted from this [example app](https://github.com/mwouts/itables/tree/main/apps/dash/3_update_table.py)):
 
 ```python
 from itables.dash import ITable, ITableOutputs, updated_itable_outputs
@@ -68,9 +64,3 @@ def update_table(checklist, caption, selected_rows, dt_args):
         caption=caption, selected_rows=selected_rows, current_dt_args=dt_args, **kwargs
     )
 ```
-
-## Limitations
-
-Compared to `show`, the `ITable` component has the same limitations as the [Jupyter Widget](widget.md#limitations)
-or the [Streamlit component](streamlit.md#limitations),
-e.g. structured headers are not available, you can't pass JavaScript callback, etc.