20_diagramas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88baf641-4d8f-46c0-b6c0-734c7854d4ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "#default_exp diagrams"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fde9610c-0370-4c4e-a3ff-12d96e71ac88",
   "metadata": {},
   "source": [
    "# Diagrams\n",
    "\n",
    "> Helpers to draw pipeline/application config diagrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b17246ff-a08d-4765-b069-23680f60a765",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ! conda install -c conda-forge graphviz python-graphviz "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98ba2ea3-c8b9-4767-a1f0-55f5983f7c26",
   "metadata": {},
   "outputs": [],
   "source": [
    "#export\n",
    "from typing import List, Optional, Tuple, Dict\n",
    "from collections import defaultdict\n",
    "\n",
    "from hopeit.dataobjects import dataobject, dataclass\n",
    "from hopeit.app.config import AppConfig, EventType\n",
    "from hopeit.testing.apps import config\n",
    "from graphviz import Digraph\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4891b38b-6f7a-43fb-84ec-22aacf01ac79",
   "metadata": {},
   "outputs": [],
   "source": [
    "#export\n",
    "@dataobject\n",
    "@dataclass\n",
    "class Port:\n",
    "    id: str\n",
    "    label: str\n",
    "\n",
    "@dataobject\n",
    "@dataclass\n",
    "class Node:\n",
    "    id: str\n",
    "    label: str\n",
    "    inputs: List[Port]\n",
    "    outputs: List[Port]\n",
    "    shape: str = \"box\"\n",
    "    color: str = \"#AACCAA\"\n",
    "    fontsize: str = \"14\"\n",
    "        \n",
    "    def __hash__(self):\n",
    "        return hash(self.id)\n",
    "    \n",
    "    def __eq__(self, other):\n",
    "        return self.id == other.id\n",
    "    \n",
    "@dataobject\n",
    "@dataclass\n",
    "class Edge:\n",
    "    id: str\n",
    "    label: str\n",
    "    source: Node\n",
    "    dest: Node\n",
    "\n",
    "@dataobject\n",
    "@dataclass\n",
    "class Graph:\n",
    "    nodes: List[Node]\n",
    "    edges: List[Edge]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3cf37726-e08b-4500-8320-49a1fa2cd345",
   "metadata": {},
   "outputs": [],
   "source": [
    "#export\n",
    "def _extract_nodes(config: AppConfig, streams: bool = True) -> List[Node]:\n",
    "    nodes = []\n",
    "    for event_name, event_info in config.events.items():\n",
    "        \n",
    "        inputs = []\n",
    "        if event_info.type in (EventType.GET, EventType.POST):\n",
    "            port = Port(id=f\"{event_name}.{event_info.type.value}\", label=event_info.type.value)\n",
    "            inputs.append(port)\n",
    "            nodes.append(Node(\n",
    "                id=port.id, \n",
    "                label=port.label, \n",
    "                inputs=[], \n",
    "                outputs=[port],\n",
    "                shape=\"point\"\n",
    "            ))\n",
    "        elif event_info.type == (EventType.STREAM):\n",
    "            inputs.append(Port(id=f\">{event_info.read_stream.name}\", label=event_info.read_stream.name))\n",
    "        \n",
    "        outputs = []\n",
    "        if event_info.write_stream:\n",
    "            if streams:\n",
    "                outputs.append(Port(id=event_info.write_stream.name, label=event_info.write_stream.name))\n",
    "                stream_in = Port(id=event_info.write_stream.name, label=event_info.write_stream.name)\n",
    "                stream_out = Port(id=f\">{event_info.write_stream.name}\", label=event_info.write_stream.name)\n",
    "                nodes.append(Node(\n",
    "                    id=stream_in.id,\n",
    "                    label=f\"\\u2192 {stream_in.label} \\u2192\",\n",
    "                    inputs=[stream_in],\n",
    "                    outputs=[stream_out],\n",
    "                    shape='Mrecord',\n",
    "                    color='#AAAAFF',\n",
    "                    fontsize=\"10\"\n",
    "                ))\n",
    "            else:\n",
    "                outputs.append(Port(id=f\">{event_info.write_stream.name}\", label=event_info.write_stream.name))\n",
    "        \n",
    "        nodes.append(Node(\n",
    "            id=event_name,\n",
    "            label=event_name,\n",
    "            inputs=inputs,\n",
    "            outputs=outputs\n",
    "        ))\n",
    "    return nodes\n",
    "\n",
    "PortMap = Dict[str, List[Node]]\n",
    "\n",
    "def _index_node_input_outputs(nodes: List[Node]) -> Tuple[PortMap, PortMap]:\n",
    "    inputs, outputs = defaultdict(set), defaultdict(set)\n",
    "    for node in nodes:\n",
    "        for port in node.inputs:\n",
    "            inputs[port.id].add(node)\n",
    "        for port in node.outputs:\n",
    "            outputs[port.id].add(node)\n",
    "    return inputs, outputs\n",
    "\n",
    "def _get_edges(port: str, from_nodes: List[Node], to_nodes: List[Node]):\n",
    "    return [\n",
    "        Edge(id=port, label=port, source=from_node, dest=to_node)\n",
    "        for from_node in from_nodes for to_node in to_nodes\n",
    "    ]\n",
    "\n",
    "def _extract_edges(inputs: PortMap, outputs: PortMap) -> List[Edge]:\n",
    "    edges = []\n",
    "    for port, from_nodes in outputs.items():\n",
    "        to_nodes = inputs.get(port, [])\n",
    "        edges.extend(_get_edges(port, from_nodes, to_nodes))\n",
    "    return edges\n",
    "            \n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fd6642be-d929-4721-89fe-14f8ad3362d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#export\n",
    "def draw_graph(config: AppConfig, show_streams: bool = True):\n",
    "    nodes = _extract_nodes(config, show_streams)\n",
    "    inputs, outputs = _index_node_input_outputs(nodes)\n",
    "    edges = _extract_edges(inputs, outputs)\n",
    "    \n",
    "    dot = Digraph(comment='Graph')\n",
    "    \n",
    "    for node in nodes:\n",
    "        dot.node(node.id, node.label, shape=node.shape, style='filled', fillcolor=node.color, fontsize=node.fontsize)\n",
    "        \n",
    "    for edge in edges:\n",
    "        dot.edge(edge.source.id, edge.dest.id, \"\")\n",
    "        \n",
    "    return dot\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "64560fa9-489b-4673-ab38-9867f3216029",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Converted 00_jobs.ipynb.\n",
      "Converted 01_create-sample-data.ipynb.\n",
      "Converted 02_preprocess.ipynb.\n",
      "Converted 03_feature-calc.ipynb.\n",
      "Converted 04_training-data.ipynb.\n",
      "Converted 05_train-model.ipynb.\n",
      "Converted 06_submit-training-pipeline.ipynb.\n",
      "Converted 07_prepare-db.ipynb.\n",
      "Converted 08_predict.ipynb.\n",
      "Converted 09_find-orders.ipynb.\n",
      "Converted 20_diagramas.ipynb.\n",
      "Converted 99_tools.ipynb.\n",
      "Converted index.ipynb.\n"
     ]
    }
   ],
   "source": [
    "!nbdev_build_lib"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9b68675-5c41-432f-9ec5-31b24c758b51",
   "metadata": {},
   "source": [
    "### Example diagramas from config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7496ef41-6628-4c06-9b43-ec734302dc50",
   "metadata": {},
   "outputs": [
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       "<text text-anchor=\"middle\" x=\"195.65\" y=\"-595.74\" font-family=\"Times,serif\" font-size=\"10.00\">→ fraud_poc.training.submit_training_pipeline →</text>\n",
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       "<title>fraud_poc.training.data.preprocess</title>\n",
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       "<text text-anchor=\"middle\" x=\"195.65\" y=\"-450.74\" font-family=\"Times,serif\" font-size=\"10.00\">→ fraud_poc.training.data.preprocess →</text>\n",
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       "<!-- data.feature&#45;calc -->\n",
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       "<!-- fraud_poc.training.data.feature_calc -->\n",
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       "<title>fraud_poc.training.data.feature_calc</title>\n",
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       "<text text-anchor=\"middle\" x=\"195.65\" y=\"-305.74\" font-family=\"Times,serif\" font-size=\"10.00\">→ fraud_poc.training.data.feature_calc →</text>\n",
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       "<!-- data.training&#45;data -->\n",
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       "<title>fraud_poc.training.data.feature_calc&#45;&gt;data.training&#45;data</title>\n",
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       "<title>fraud_poc.training.data.training_data</title>\n",
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       "<text text-anchor=\"middle\" x=\"94.65\" y=\"-160.74\" font-family=\"Times,serif\" font-size=\"10.00\">→ fraud_poc.training.data.training_data →</text>\n",
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       "<!-- fraud_poc.training.data.training_data&#45;&gt;model.train -->\n",
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       "<title>fraud_poc.training.data.training_data&#45;&gt;model.train</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M94.65,-145.43C94.65,-137.67 94.65,-128.28 94.65,-119.56\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"98.15,-119.4 94.65,-109.4 91.15,-119.4 98.15,-119.4\"/>\n",
       "</g>\n",
       "<!-- data.training&#45;data&#45;&gt;fraud_poc.training.data.training_data -->\n",
       "<g id=\"edge12\" class=\"edge\">\n",
       "<title>data.training&#45;data&#45;&gt;fraud_poc.training.data.training_data</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M123.45,-217.93C119.08,-209.83 113.76,-199.96 108.88,-190.91\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"111.85,-189.04 104.02,-181.9 105.69,-192.36 111.85,-189.04\"/>\n",
       "</g>\n",
       "<!-- fraud_poc.training.data.prepare_db -->\n",
       "<g id=\"node12\" class=\"node\">\n",
       "<title>fraud_poc.training.data.prepare_db</title>\n",
       "<path fill=\"#aaaaff\" stroke=\"black\" d=\"M218.89,-145.5C218.89,-145.5 376.4,-145.5 376.4,-145.5 382.4,-145.5 388.4,-151.5 388.4,-157.5 388.4,-157.5 388.4,-169.5 388.4,-169.5 388.4,-175.5 382.4,-181.5 376.4,-181.5 376.4,-181.5 218.89,-181.5 218.89,-181.5 212.89,-181.5 206.89,-175.5 206.89,-169.5 206.89,-169.5 206.89,-157.5 206.89,-157.5 206.89,-151.5 212.89,-145.5 218.89,-145.5\"/>\n",
       "<text text-anchor=\"middle\" x=\"297.65\" y=\"-160.74\" font-family=\"Times,serif\" font-size=\"10.00\">→ fraud_poc.training.data.prepare_db →</text>\n",
       "</g>\n",
       "<!-- data.prepare&#45;db&#45;&gt;fraud_poc.training.data.prepare_db -->\n",
       "<g id=\"edge13\" class=\"edge\">\n",
       "<title>data.prepare&#45;db&#45;&gt;fraud_poc.training.data.prepare_db</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M283.24,-217.93C285.36,-210.08 287.92,-200.58 290.3,-191.77\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"293.73,-192.46 292.96,-181.9 286.97,-190.64 293.73,-192.46\"/>\n",
       "</g>\n",
       "<!-- fraud_poc.training.model.train -->\n",
       "<g id=\"node14\" class=\"node\">\n",
       "<title>fraud_poc.training.model.train</title>\n",
       "<path fill=\"#aaaaff\" stroke=\"black\" d=\"M25.05,-0.5C25.05,-0.5 164.24,-0.5 164.24,-0.5 170.24,-0.5 176.24,-6.5 176.24,-12.5 176.24,-12.5 176.24,-24.5 176.24,-24.5 176.24,-30.5 170.24,-36.5 164.24,-36.5 164.24,-36.5 25.05,-36.5 25.05,-36.5 19.05,-36.5 13.05,-30.5 13.05,-24.5 13.05,-24.5 13.05,-12.5 13.05,-12.5 13.05,-6.5 19.05,-0.5 25.05,-0.5\"/>\n",
       "<text text-anchor=\"middle\" x=\"94.65\" y=\"-15.74\" font-family=\"Times,serif\" font-size=\"10.00\">→ fraud_poc.training.model.train →</text>\n",
       "</g>\n",
       "<!-- model.train&#45;&gt;fraud_poc.training.model.train -->\n",
       "<g id=\"edge14\" class=\"edge\">\n",
       "<title>model.train&#45;&gt;fraud_poc.training.model.train</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M94.65,-72.93C94.65,-65.17 94.65,-55.78 94.65,-47.06\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"98.15,-46.9 94.65,-36.9 91.15,-46.9 98.15,-46.9\"/>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<graphviz.dot.Digraph at 0x10cd9df40>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from hopeit.testing.apps import config\n",
    "from fraud_poc.diagrams import draw_graph\n",
    "\n",
    "training_config = config('config/training-pipeline.json')\n",
    "dot = draw_graph(training_config, show_streams=True)\n",
    "dot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0374d1d0-ee74-45a8-92a8-41d7ee7be08a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
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       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 79.6)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"white\" stroke=\"transparent\" points=\"-4,4 -4,-79.6 204.04,-79.6 204.04,4 -4,4\"/>\n",
       "<!-- live.predict.POST -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>live.predict.POST</title>\n",
       "<ellipse fill=\"#aaccaa\" stroke=\"black\" cx=\"39.68\" cy=\"-73.8\" rx=\"1.8\" ry=\"1.8\"/>\n",
       "</g>\n",
       "<!-- live.predict -->\n",
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       "<title>live.predict</title>\n",
       "<polygon fill=\"#aaccaa\" stroke=\"black\" points=\"79.54,-36 -0.18,-36 -0.18,0 79.54,0 79.54,-36\"/>\n",
       "<text text-anchor=\"middle\" x=\"39.68\" y=\"-13.8\" font-family=\"Times,serif\" font-size=\"14.00\">live.predict</text>\n",
       "</g>\n",
       "<!-- live.predict.POST&#45;&gt;live.predict -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>live.predict.POST&#45;&gt;live.predict</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M39.68,-71.87C39.68,-68.64 39.68,-57.55 39.68,-46.35\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"43.18,-46.26 39.68,-36.26 36.18,-46.26 43.18,-46.26\"/>\n",
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       "<title>test.find_orders.GET</title>\n",
       "<ellipse fill=\"#aaccaa\" stroke=\"black\" cx=\"148.68\" cy=\"-73.8\" rx=\"1.8\" ry=\"1.8\"/>\n",
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       "</g>\n",
       "<!-- test.find_orders.GET&#45;&gt;test.find_orders -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>test.find_orders.GET&#45;&gt;test.find_orders</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M148.68,-71.87C148.68,-68.64 148.68,-57.55 148.68,-46.35\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"152.18,-46.26 148.68,-36.26 145.18,-46.26 152.18,-46.26\"/>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<graphviz.dot.Digraph at 0x10d210280>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from hopeit.testing.apps import config\n",
    "from fraud_poc.diagrams import draw_graph\n",
    "\n",
    "service_config = config('config/fraud-service.json')\n",
    "dot = draw_graph(service_config)\n",
    "dot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7048173-003d-44cb-b949-8dc25ca23d5e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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