{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gradio 简介"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://0.0.0.0:4099\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://localhost:4099/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import gradio as gr\n",
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "def plotly_plot():\n",
    "    # prepare some data\n",
    "    x = [\"Math\", \"Business\", \"Statistics\", \"IT\", \"Commerce\"]\n",
    "    y = [68, 73, 82, 74, 85]\n",
    "    data = pd.DataFrame()\n",
    "    data['Subject'] = x\n",
    "    data['Score'] = y\n",
    "    # create a new plot\n",
    "    p = px.bar(data, x='Subject', y='Score')\n",
    "\n",
    "    return p\n",
    "\n",
    "# show the results\n",
    "outputs = gr.Plot()\n",
    "\n",
    "demo = gr.Interface(fn=plotly_plot, inputs=None, outputs=outputs)\n",
    "\n",
    "# demo.launch()\n",
    "demo.launch(server_name=\"0.0.0.0\", server_port=4099, share=False, inbrowser=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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