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{
"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"
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"nbformat": 4,
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