run.ipynb

{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_multiple_event_triggers"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio plotly pypistats"]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import pypistats\n", "from datetime import date\n", "from dateutil.relativedelta import relativedelta\n", "import pandas as pd\n", "\n", "pd.options.plotting.backend = \"plotly\"\n", "\n", "\n", "def get_plot(lib, time):\n", "    data = pypistats.overall(lib, total=True, format=\"pandas\")\n", "    data = data.groupby(\"category\").get_group(\"with_mirrors\").sort_values(\"date\")\n", "    start_date = date.today() - relativedelta(months=int(time.split(\" \")[0]))\n", "    data = data[(data['date'] > str(start_date))]\n", "    chart = data.plot(x=\"date\", y=\"downloads\")\n", "    return chart\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    gr.Markdown(\n", "        \"\"\"\n", "        ## Pypi Download Stats \ud83d\udcc8\n", "        See live download stats for all of Hugging Face's open-source libraries \ud83e\udd17\n", "        \"\"\")\n", "    with gr.Row():\n", "        lib = gr.Dropdown([\"transformers\", \"datasets\", \"huggingface-hub\", \"gradio\", \"accelerate\"], label=\"Library\")\n", "        time = gr.Dropdown([\"3 months\", \"6 months\", \"9 months\", \"12 months\"], label=\"Downloads over the last...\")\n", "\n", "    plt = gr.Plot()\n", "    # You can add multiple event triggers in 2 lines like this\n", "    for event in [lib.change, time.change]:\n", "        event(get_plot, [lib, time], [plt])\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}