{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Command Registry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipylab import JupyterFrontEnd\n",
    "\n",
    "app = JupyterFrontEnd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## List all commands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.commands.list_commands()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a new console"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.commands.execute('console:create', {\n",
    "    'insertMode': 'split-right',\n",
    "    'kernelPreference': {\n",
    "        'shutdownOnClose': True,\n",
    "    }\n",
    "})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change the theme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.commands.execute('apputils:change-theme', { 'theme': 'JupyterLab Dark' })"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a new terminal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.commands.execute('terminal:create-new')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ready event\n",
    "\n",
    "Some functionalities might require the `JupyterFrontEnd` widget to be ready on the frontend first.\n",
    "\n",
    "This is for example the case when listing all the available commands, or retrieving the version with `app.version`.\n",
    "\n",
    "The `on_ready` method can be used to register a callback that will be fired when the frontend is ready."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipylab import JupyterFrontEnd\n",
    "from ipywidgets import Output\n",
    "\n",
    "app = JupyterFrontEnd()\n",
    "out = Output()\n",
    "\n",
    "def init():\n",
    "    # show the first 5 commands\n",
    "    cmds = app.commands.list_commands()[:5]\n",
    "    out.append_stdout(cmds)\n",
    "\n",
    "app.on_ready(init)\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or using `asyncio`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import asyncio\n",
    "\n",
    "app = JupyterFrontEnd()\n",
    "\n",
    "out = Output()\n",
    "\n",
    "async def init():\n",
    "    await app.ready()\n",
    "    cmds = app.commands.list_commands()[:5]\n",
    "    out.append_stdout(cmds)\n",
    "\n",
    "asyncio.create_task(init())\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add your own command\n",
    "\n",
    "Let's create a nice plot with `bqlot` and generate some random data.\n",
    "\n",
    "See https://github.com/bqplot/bqplot/blob/master/examples/Advanced%20Plotting/Animations.ipynb for more details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from bqplot import LinearScale, Lines, Bars, Axis, Figure\n",
    "from ipywidgets import IntSlider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xs = LinearScale()\n",
    "ys1 = LinearScale()\n",
    "ys2 = LinearScale()\n",
    "\n",
    "x = np.arange(20)\n",
    "y = np.cumsum(np.random.randn(20))\n",
    "y1 = np.random.rand(20)\n",
    "\n",
    "line = Lines(x=x, y=y, scales={'x': xs, 'y': ys1}, colors=['magenta'], marker='square')\n",
    "bar = Bars(x=x, y=y1, scales={'x': xs, 'y': ys2}, colorpadding=0.2, colors=['steelblue'])\n",
    "\n",
    "xax = Axis(scale=xs, label='x', grid_lines='solid')\n",
    "yax1 = Axis(scale=ys1, orientation='vertical', tick_format='0.1f', label='y', grid_lines='solid')\n",
    "yax2 = Axis(scale=ys2, orientation='vertical', side='right', tick_format='0.0%', label='y1', grid_lines='none')\n",
    "\n",
    "Figure(marks=[bar, line], axes=[xax, yax1, yax2], animation_duration=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now define a function to update the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def update_data():\n",
    "    line.y = np.cumsum(np.random.randn(20))\n",
    "    bar.y = np.random.rand(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "update_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function will now be called when the JupyterLab command is executed.\n",
    "\n",
    "> Commands can also custom [icons](./icons.ipynb) in place of `icon_class`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.commands.add_command('update_data', execute=update_data, label=\"Update Data\", icon_class=\"jp-PythonIcon\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Execute it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.commands.execute('update_data')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The slider should now be moving and taking random values.\n",
    "\n",
    "Also the list of commands gets updated with the newly added command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert 'random' in app.commands.list_commands()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's great, but the command doesn't visually show up in the palette yet. So let's add it!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add the command to the palette"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipylab.commands import CommandPalette"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "palette = CommandPalette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "palette.add_item('update_data', 'Python Commands')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Open the command palette on the left side and the command should show now be visible."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Remove a command\n",
    "\n",
    "To remove a command that was previously added:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.commands.remove_command('update_data')"
   ]
  }
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