mongodb

govgis-nov2023-mongodb.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c603abb7838d15686f3f8c4e6f210c1af2f81981ee3e2767c119f05dbc16983a
+size 1129192237

to_mongodb.ipynb

@@ -0,0 +1,209 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "14762a5e-0193-4de6-ac54-549b0309dd2c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import asyncio\n",
+    "import json\n",
+    "import os\n",
+    "import random\n",
+    "import uuid\n",
+    "from glob import glob\n",
+    "\n",
+    "import aiofiles\n",
+    "import nest_asyncio\n",
+    "from pymongo import MongoClient"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a93723c1-0972-4f52-ae23-8e44e7861230",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nest_asyncio.apply()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "12db86f4-0321-4f87-be6e-0088fe7aac3e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "output_dir = os.path.abspath(\"./output_tryagain\")\n",
+    "\n",
+    "jsonfiles = glob(os.path.join(output_dir, \"*.json\"))\n",
+    "\n",
+    "len(jsonfiles)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7ee6e661-9d22-4635-a912-92a15d21b5f0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "client = MongoClient(r'mongodb://root:example@mongo:27017/')\n",
+    "\n",
+    "db = client['govgis-nov2023']\n",
+    "\n",
+    "services_collection = db.services\n",
+    "\n",
+    "layers_collection = db.layers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5baaccb7-ef62-4d0c-b936-b6ef70befc44",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "errors = []\n",
+    "\n",
+    "\n",
+    "def create_uuid(input_str: str) -> str:\n",
+    "    # Consistent random UUIDs based on input string\n",
+    "    # https://nathanielknight.ca/articles/consistent_random_uuids_in_python.html\n",
+    "    random.seed(input_str)\n",
+    "    return str(uuid.UUID(bytes=bytes(random.getrandbits(8) for _ in range(16)), version=4))\n",
+    "\n",
+    "\n",
+    "async def read_data():\n",
+    "    # Async generator to yield file content one by one\n",
+    "    for f in jsonfiles:\n",
+    "        async with aiofiles.open(f, 'r') as infile:\n",
+    "            content = await infile.read()\n",
+    "            yield json.loads(content)\n",
+    "\n",
+    "\n",
+    "def process_metadata(metadata, additional_fields={}):\n",
+    "    # Process metadata and add any additional fields\n",
+    "    processed_md = {k: v for k, v in metadata.items() if k not in ['folders', 'services', 'layers']}\n",
+    "    processed_md.update(additional_fields)\n",
+    "    processed_md[\"original_id\"] = processed_md.get(\"id\", None)\n",
+    "    processed_md[\"id\"] = processed_md[\"hash\"]\n",
+    "    del processed_md[\"hash\"]\n",
+    "\n",
+    "    return processed_md\n",
+    "\n",
+    "\n",
+    "def get_type(layer: dict) -> str:\n",
+    "    return layer.get(\"type\", \"unknown\").lower().replace(\" \", \"_\").strip()\n",
+    "\n",
+    "\n",
+    "async def main():\n",
+    "    async for server in read_data():\n",
+    "        server_md = process_metadata(server[\"metadata\"],\n",
+    "                                     {\"url\": server['metadata']['url'], \"hash\": create_uuid(server['metadata']['url'])})\n",
+    "        for service in server['services']:\n",
+    "            service_md = process_metadata(service[\"metadata\"],\n",
+    "                                          {\"url\": service['url'], \"hash\": create_uuid(service['url']),\n",
+    "                                           \"server\": server_md})\n",
+    "            service_md['layers'] = []\n",
+    "\n",
+    "            layer_dict = {}\n",
+    "\n",
+    "            for layer in service['metadata']['layers']:\n",
+    "                layer_md = process_metadata(layer, {\"url\": layer['url'], \"hash\": create_uuid(layer['url']),\n",
+    "                                                    \"service\": service_md[\"id\"]})\n",
+    "                layer_type = get_type(layer)\n",
+    "                service_md['layers'].append(dict(type=layer_type, layer_id=layer_md['id']))\n",
+    "                if layer_type not in layer_dict:\n",
+    "                    layer_dict[layer_type] = []\n",
+    "                layer_dict[layer_type].append(layer_md)\n",
+    "\n",
+    "            if len(service_md) > 0:\n",
+    "                services_collection.insert_one(service_md)\n",
+    "\n",
+    "            for k, layers in layer_dict.items():\n",
+    "                if len(layers) > 0:\n",
+    "                    try:\n",
+    "                        db[k].insert_many(layers)\n",
+    "                    except OverflowError:\n",
+    "                        for layer in layers:\n",
+    "                            try:\n",
+    "                                db[k].insert_one(layer)\n",
+    "                            except OverflowError:\n",
+    "                                for c in ['drawingInfo', 'classBreakInfos']:\n",
+    "                                    if c in layer:\n",
+    "                                        del layer[c]\n",
+    "                                try:\n",
+    "                                    db[k].insert_one(layer)\n",
+    "                                except OverflowError:\n",
+    "                                    errors.append(layer)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "67190800-bbfd-4bd3-a616-ec6b57050c96",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 4min 22s, sys: 25.6 s, total: 4min 48s\n",
+      "Wall time: 6min 25s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "\n",
+    "# Run the async main function\n",
+    "asyncio.run(main())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "56bc67d5-fd8d-4dda-9939-111ce484bb3f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(errors)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.11.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}