initial commit

.gitignore

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+venv
+.ipynb_checkpoints
+__pycache__

README.md

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+# Self-updating Voila Dashboard Example
+
+This is an example to create a self-updating dashboard, which gets data from an api interface.
+
+This example contains `requiremements.txt` for dependencies.
+
+## Local Setup
+
+To test locally (with venv):
+
+```
+python -m venv venv
+source activate venv/bin/activate
+pip install -r requirements.txt
+gunicorn api:app -b 127.0.0.1:9999 --daemon
+voila dashboard.ipynb
+```
+
+To test locally (with conda):
+
+```
+conda env create self-updating-dashboard
+conda activate create self-updating-dashboard
+pip install -r requirements.txt
+gunicorn api:app -b 127.0.0.1:9999 --daemon
+voila dashboard.ipynb
+```
+
+This will open a new browser tab at http://localhost:8866 serving the dashboard.

api.py

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+# Let's get this party started!
+import falcon
+import json
+import random
+import numpy
+
+
+# Falcon follows the REST architectural style, meaning (among
+# other things) that you think in terms of resources and state
+# transitions, which map to HTTP verbs.
+class SampleAPI(object):
+    def on_get(self, req, resp):
+        """Handles GET requests"""
+        resp.status = falcon.HTTP_200  
+        resp.content_type = 'application/json'
+        resp.body = json.dumps([numpy.random.normal(size = 2).tolist() for x in range(random.randint(100,1000))])
+
+app = falcon.API()
+
+app.add_route('/api', SampleAPI())

dashboard.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 0,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import asyncio\n",
+    "\n",
+    "%matplotlib widget\n",
+    "import ipympl\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import requests\n",
+    "import json\n",
+    "\n",
+    "\n",
+    "SLEEP = 0.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 0,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_api_data():\n",
+    "    try:\n",
+    "        r = requests.get(\"http://127.0.0.1:9999/api\")\n",
+    "        return json.loads(r.text)\n",
+    "    except:\n",
+    "        raise Exception(\"Could not connect to the API server!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 0,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2ff4c6ed411c49cf9e09b847412025ac",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Task pending coro=<do() running at <ipython-input-4-27831e97e6cd>:12>>"
+      ]
+     },
+     "execution_count": 0,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_tasks = asyncio.all_tasks()\n",
+    "for task in all_tasks:\n",
+    "    task.cancel()\n",
+    "\n",
+    "\n",
+    "fig1, axes1 = plt.subplots()\n",
+    "fig1.suptitle(\"Self-updating API data\", fontsize=20)\n",
+    "plt.show(fig1)\n",
+    "axes1.cla()\n",
+    "\n",
+    "\n",
+    "async def do():\n",
+    "    while True:\n",
+    "        api_data = get_api_data()\n",
+    "        data1 = pd.DataFrame(api_data, columns=['horizontal','vertical'])\n",
+    "        axes1.cla()\n",
+    "        data1.plot(kind=\"scatter\", x='horizontal', y='vertical', ax=axes1)\n",
+    "        plt.draw()\n",
+    "        await asyncio.sleep(SLEEP)\n",
+    "\n",
+    "asyncio.create_task(do())"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

requirements.txt

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+jupyterlab
+ipympl
+pandas
+numpy
+falcon
+gunicorn
+requests