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Last active December 16, 2022 17:03
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visualizing-streaming-data.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"authorship_tag": "ABX9TyMdHnqFTfr+hOv/G4/WjKnr",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/awmatheson/1649948ea76f721cbc91eac0a9b6e93b/visualizing-streaming-data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "RZ1PTK1xGjzO",
"outputId": "5959fe71-46e3-433c-ae36-d1107ee7c744"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Collecting bytewax\n",
" Downloading bytewax-0.13.1-cp38-cp38-manylinux_2_27_x86_64.whl (8.7 MB)\n",
"\u001b[K |████████████████████████████████| 8.7 MB 3.8 MB/s \n",
"\u001b[?25hCollecting multiprocess>=0.70\n",
" Downloading multiprocess-0.70.14-py38-none-any.whl (132 kB)\n",
"\u001b[K |████████████████████████████████| 132 kB 20.9 MB/s \n",
"\u001b[?25hRequirement already satisfied: dill>=0.3.5 in /usr/local/lib/python3.8/dist-packages (from bytewax) (0.3.6)\n",
"Installing collected packages: multiprocess, bytewax\n",
"Successfully installed bytewax-0.13.1 multiprocess-0.70.14\n"
]
}
],
"source": [
"!pip install bytewax"
]
},
{
"cell_type": "code",
"source": [
"import json\n",
"from random import randint\n",
"from time import sleep\n",
"from datetime import datetime\n",
"\n",
"from bytewax.dataflow import Dataflow\n",
"from bytewax.execution import run_main, spawn_cluster\n",
"from bytewax.inputs import ManualInputConfig\n",
"from bytewax.outputs import ManualOutputConfig\n",
"\n",
"# Add data to input topic\n",
"sensors = [\n",
" {\"sensor_id\":\"a12\"}, \n",
" {\"sensor_id\":\"a34\"}, \n",
" {\"sensor_id\":\"a56\"}, \n",
" {\"sensor_id\":\"a78\"}, \n",
" {\"sensor_id\":\"a99\"}\n",
" ]\n",
"\n",
"def input_builder(worker_index, worker_count, state):\n",
" def gen_input():\n",
" for i in range(50):\n",
" sleep(0.1)\n",
" dt = datetime.now()\n",
" for sensor in sensors:\n",
" sensor_reading = sensor\n",
" sensor_reading['created_at'] = dt\n",
" sensor_reading['value'] = randint(0,100)\n",
" \n",
" yield None, sensor_reading\n",
" \n",
" return gen_input()\n",
"\n",
"flow = Dataflow()\n",
"flow.input('gen_sensor', ManualInputConfig(input_builder))\n"
],
"metadata": {
"id": "cVcZRSvG0Gvj"
},
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from IPython.display import display, HTML, Javascript\n",
"\n",
"def build_chart():\n",
" display(HTML('''\n",
" <canvas id=\"myChart\"></canvas>\n",
" <script src=\"https://cdn.jsdelivr.net/npm/chart.js@4.0.1/dist/chart.umd.min.js\"></script>\n",
" <script src=\"https://cdn.jsdelivr.net/npm/chart.js/dist/chart.min.js\"></script>\n",
" <script src=\"https://cdn.jsdelivr.net/npm/chartjs-adapter-date-fns/dist/chartjs-adapter-date-fns.bundle.min.js\"></script>\n",
" <script src=\"https://cdn.jsdelivr.net/npm/chartjs-plugin-streaming@2.0.0\"></script>\n",
" <script>\n",
" var ctx = document.getElementById('myChart').getContext('2d');\n",
" const autocolors = window['chartjs-plugin-autocolors'];\n",
" var chart = new Chart(ctx, {\n",
" // The type of chart we want to create\n",
" type: 'line',\n",
"\n",
" // The data for our dataset\n",
" data: {\n",
" datasets: []\n",
" },\n",
"\n",
" // Configuration options go here\n",
" options: {\n",
" animation: false, // disable animations\n",
" plugins: {\n",
" streaming: {\n",
" frameRate: 5 // chart is drawn 5 times every second\n",
" }\n",
" },\n",
" scales: {\n",
" x: {\n",
" type: 'time',\n",
" }\n",
" }\n",
" }\n",
" });\n",
" \n",
" \n",
" function addData(label, value){\n",
" // check if dataset exists\n",
" const exists = chart.data.datasets.findIndex(o => o.label === label)\n",
" // if not add the dataset\n",
" if(exists === -1) {\n",
" const randomColor = Math.floor(Math.random()*16777215).toString(16);\n",
" chart.data.datasets.push({label: label, data: [value], borderColor : \"#\" + randomColor})\n",
" } else {\n",
" const len = chart.data.datasets.find(o => o.label === label).data.push(value)\n",
" // optional windowing\n",
" if(len > 10) {\n",
" chart.data.datasets.find(o => o.label === label).data.shift()\n",
" }\n",
" }\n",
"\n",
" chart.update();\n",
" }\n",
" </script>\n",
" '''))\n",
" \n",
"build_chart()\n",
"\n",
"def output_builder(worker_index, worker_count):\n",
" return plot\n",
"\n",
"def plot(sensor_reading):\n",
" data_str = '{' + f'''x: \"{sensor_reading['created_at']}\", y: {sensor_reading['value']}''' + '}'\n",
" dis_str = f'''addData(\"{sensor_reading['sensor_id']}\", {data_str})'''\n",
" display(Javascript(dis_str))\n",
"\n",
"flow.capture(ManualOutputConfig(output_builder))\n",
"run_main(flow)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 378
},
"id": "z4Los6ppHRq2",
"outputId": "9535f51f-ae7b-43ec-849b-bac73d40ff15"
},
"execution_count": 4,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.HTML object>"
],
"text/html": [
"\n",
" <canvas id=\"myChart\"></canvas>\n",
" <script src=\"https://cdn.jsdelivr.net/npm/chart.js@4.0.1/dist/chart.umd.min.js\"></script>\n",
" <script src=\"https://cdn.jsdelivr.net/npm/chart.js/dist/chart.min.js\"></script>\n",
" <script src=\"https://cdn.jsdelivr.net/npm/chartjs-adapter-date-fns/dist/chartjs-adapter-date-fns.bundle.min.js\"></script>\n",
" <script src=\"https://cdn.jsdelivr.net/npm/chartjs-plugin-streaming@2.0.0\"></script>\n",
" <script>\n",
" var ctx = document.getElementById('myChart').getContext('2d');\n",
" const autocolors = window['chartjs-plugin-autocolors'];\n",
" var chart = new Chart(ctx, {\n",
" // The type of chart we want to create\n",
" type: 'line',\n",
"\n",
" // The data for our dataset\n",
" data: {\n",
" datasets: []\n",
" },\n",
"\n",
" // Configuration options go here\n",
" options: {\n",
" animation: false, // disable animations\n",
" plugins: {\n",
" streaming: {\n",
" frameRate: 5 // chart is drawn 5 times every second\n",
" }\n",
" },\n",
" scales: {\n",
" x: {\n",
" type: 'time',\n",
" }\n",
" }\n",
" }\n",
" });\n",
" \n",
" \n",
" function addData(label, value){\n",
" // check if dataset exists\n",
" const exists = chart.data.datasets.findIndex(o => o.label === label)\n",
" // if not add the dataset\n",
" if(exists === -1) {\n",
" const randomColor = Math.floor(Math.random()*16777215).toString(16);\n",
" chart.data.datasets.push({label: label, data: [value], borderColor : \"#\" + randomColor})\n",
" } else {\n",
" const len = chart.data.datasets.find(o => o.label === label).data.push(value)\n",
" // optional windowing\n",
" if(len > 10) {\n",
" chart.data.datasets.find(o => o.label === label).data.shift()\n",
" }\n",
" }\n",
"\n",
" chart.update();\n",
" }\n",
" </script>\n",
" "
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
],
"application/javascript": [
"addData(\"a12\", {x: \"2022-12-13 21:05:17.666278\", y: 64})"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
],
"application/javascript": [
"addData(\"a12\", {x: \"2022-12-13 21:05:17.666278\", y: 64})"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
],
"application/javascript": [
"addData(\"a34\", {x: \"2022-12-13 21:05:17.666278\", y: 63})"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"addData(\"a34\", {x: \"2022-12-13 21:05:17.666278\", y: 63})"
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{
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"<IPython.core.display.Javascript object>"
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"application/javascript": [
"addData(\"a56\", {x: \"2022-12-13 21:05:17.666278\", y: 38})"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"application/javascript": [
"addData(\"a56\", {x: \"2022-12-13 21:05:17.666278\", y: 38})"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
],
"application/javascript": [
"addData(\"a78\", {x: \"2022-12-13 21:05:17.666278\", y: 41})"
]
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"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"addData(\"a78\", {x: \"2022-12-13 21:05:17.666278\", y: 41})"
]
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"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"application/javascript": [
"addData(\"a99\", {x: \"2022-12-13 21:05:17.666278\", y: 55})"
]
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"metadata": {}
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{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"addData(\"a99\", {x: \"2022-12-13 21:05:17.666278\", y: 55})"
]
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"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"application/javascript": [
"addData(\"a12\", {x: \"2022-12-13 21:05:17.791582\", y: 99})"
]
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"metadata": {}
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{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"addData(\"a12\", {x: \"2022-12-13 21:05:17.791582\", y: 99})"
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"metadata": {}
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{
"output_type": "display_data",
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"<IPython.core.display.Javascript object>"
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"addData(\"a34\", {x: \"2022-12-13 21:05:17.791582\", y: 0})"
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"metadata": {}
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{
"output_type": "display_data",
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"<IPython.core.display.Javascript object>"
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{
"output_type": "display_data",
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"metadata": {}
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{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"application/javascript": [
"addData(\"a78\", {x: \"2022-12-13 21:05:17.791582\", y: 88})"
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"metadata": {}
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{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"application/javascript": [
"addData(\"a78\", {x: \"2022-12-13 21:05:17.791582\", y: 88})"
]
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"metadata": {}
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{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
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"application/javascript": [
"addData(\"a99\", {x: \"2022-12-13 21:05:17.791582\", y: 12})"
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{
"output_type": "display_data",
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"text/plain": [
"<IPython.core.display.Javascript object>"
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"application/javascript": [
"addData(\"a12\", {x: \"2022-12-13 21:05:17.906975\", y: 46})"
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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"metadata": {}
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