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Last active March 24, 2021 16:21
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pygraphviz.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "pygraphviz.ipynb",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyNivO3+8PhOfVg0cE2xT1s8",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/domvwt/92ac81c57c5729db9f465d63c116f9d3/pygraphviz.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "nzh0V_Z2hMGM"
},
"source": [
"!apt-get install libgraphviz-dev > /dev/null\n",
"!apt-get install fonts-roboto > /dev/null\n",
"!pip install pygraphviz > /dev/null"
],
"execution_count": 1,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "WVnC7ryMhQth"
},
"source": [
"import pygraphviz as pgv\n",
"from dataclasses import dataclass\n",
"from IPython.display import Image\n",
"\n",
"def draw(G):\n",
" return Image(pgv.AGraph(G.to_string()).draw(format='png', prog='dot'))"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "GJtyXS5bV_MP"
},
"source": [
"# Define font\n",
"font = \"roboto\"\n",
"fontcolour = \"#222222\"\n",
"\n",
"# Define palette\n",
"# https://coolors.co/\n",
"# pal = [\"264653\",\"2a9d8f\",\"e9c46a\",\"f4a261\",\"e76f51\"]\n",
"# pal = [\"22577a\",\"38a3a5\",\"57cc99\",\"80ed99\",\"c7f9cc\"]\n",
"# pal = [\"004e64\",\"00a5cf\",\"9fffcb\",\"25a18e\",\"7ae582\"]\n",
"pal = [\"023047\",\"219ebc\",\"8ecae6\",\"ffb703\",\"fb8500\"]\n",
"\n",
"strong = \"cc\"\n",
"subtle = \"33\"\n",
"\n",
"pal0 = [\"#\" + x for x in pal]\n",
"pal1 = [x + strong for x in pal0]\n",
"pal2 = [x + subtle for x in pal0]\n",
"\n",
"colorset = lambda x: {\"color\": pal1[x], \"fillcolor\": pal2[x]}\n",
"\n",
"# Node and Subgraph styles\n",
"@dataclass\n",
"class Style:\n",
" db = dict(shape=\"cylinder\", **colorset(0))\n",
" code = dict(shape=\"rect\", **colorset(1))\n",
" conf = dict(shape=\"note\", color=\"#555555\", fillcolor=\"#fbfbfb\")\n",
" file = dict(shape=\"folder\", **colorset(2))\n",
" modl = dict(shape=\"egg\", **colorset(4))\n",
" rprt = dict(shape=\"cds\", **colorset(3))\n",
"\n",
" subg = dict(color=\"#ffffff00\", bgcolor=pal0[1] + \"11\", style=\"rounded\")"
],
"execution_count": 3,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 520
},
"id": "tavZ92DmkVhk",
"outputId": "eac91e14-60f8-4167-e2b1-85d6887cf0bd"
},
"source": [
"G = pgv.AGraph(directed=True, splines=\"ortho\", rankdir=\"LR\", labelloc=\"t\", size=20)\n",
"\n",
"# Graph attributes\n",
"G.graph_attr[\"label\"] = \"Prediction Serving Process\"\n",
"G.graph_attr[\"fontname\"] = font\n",
"G.graph_attr[\"fontsize\"] = 11\n",
"G.graph_attr[\"fontcolor\"] = fontcolour\n",
"G.graph_attr[\"size\"] = \"30.0,45.0!\"\n",
"\n",
"# Node attributes\n",
"G.node_attr[\"fontname\"] = font\n",
"G.node_attr[\"fontsize\"] = 10\n",
"G.node_attr[\"fontcolor\"] = fontcolour\n",
"G.node_attr[\"style\"] = \"filled\"\n",
"G.node_attr[\"penwidth\"] = 1\n",
"\n",
"# Edge attributes\n",
"G.edge_attr[\"arrowsize\"] = 0.7\n",
"G.edge_attr[\"penwidth\"] = 0.7\n",
"G.edge_attr[\"color\"] = fontcolour\n",
"\n",
"# Node labels\n",
"source_db = \"Feature\\nStore\"\n",
"conf_etl = \"ETL\\nConfig\"\n",
"conf_predict = \"Predict\\nConfig\"\n",
"etl_script = \"Data\\nProcessing\"\n",
"pred_script = \"Inference\"\n",
"monitor_script = \"Monitoring\"\n",
"model_object = \"Model\"\n",
"interim_output = \"Interim\\nFile\"\n",
"final_output = \"Output\\nFile\"\n",
"target_db = \"Prod\"\n",
"report_file = \"\\nReport \\nDashboard \\n\\n\"\n",
"\n",
"\n",
"# Define Nodes\n",
"G.add_node(source_db, **Style.db)\n",
"G.add_node(model_object, **Style.modl)\n",
"\n",
"c1 = G.add_subgraph(name=\"cluster_1\", label=\"Config Files\", **Style.subg)\n",
"\n",
"c1.add_node(conf_etl, **Style.conf)\n",
"c1.add_node(conf_predict, **Style.conf)\n",
"\n",
"G.add_node(etl_script, **Style.code)\n",
"G.add_node(pred_script, **Style.code)\n",
"G.add_node(monitor_script, **Style.code)\n",
"\n",
"G.add_node(interim_output, **Style.file)\n",
"G.add_node(final_output, **Style.file)\n",
"G.add_node(report_file, **Style.rprt)\n",
"\n",
"c2 = G.add_subgraph(name=\"cluster_2\", label=\" IT Managed \", **Style.subg)\n",
"c2.add_node(target_db, **Style.db)\n",
" \n",
" \n",
"# Define Edges\n",
"G.add_edge(source_db, etl_script)\n",
"G.add_edge(conf_etl, etl_script, style=\"dotted\")\n",
"G.add_edge(conf_predict, pred_script, style=\"dotted\")\n",
"G.add_edge(model_object, pred_script)\n",
"G.add_edge(etl_script, interim_output)\n",
"G.add_edge(interim_output, pred_script)\n",
"G.add_edge(pred_script, final_output)\n",
"G.add_edge(final_output, target_db, style=\"dashed\")\n",
"G.add_edge(final_output, monitor_script)\n",
"G.add_edge(monitor_script, report_file)\n",
" \n",
"draw(G)"
],
"execution_count": 4,
"outputs": [
{
"output_type": "execute_result",
"data": {
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"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {
"tags": []
},
"execution_count": 4
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "6Zud65kFKbLz"
},
"source": [
"pgv.AGraph(G.to_string()).draw(\"process-graph.png\", format='png', prog='dot')"
],
"execution_count": 5,
"outputs": []
}
]
}
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