2f:[] 2d:{"title":"Simple Distance Matrix Example - API","cells":[{"id":0,"value":"# Simple Distance Matrix Example - API","pinned":false,"hidden":false,"mode":"md"},{"id":7,"value":"viewof apiKey = secret2(\"apiKey\", {\n title: \"NextBillion.ai API Key\",\n submit: \"Set\",\n description:\n \"Contact support@nextbillion.ai to get your API key\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":91,"value":"md`Change the addresses below if you want to modify the inputs`","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"addresses = [\n \"detroit,mi\",\n \"43017\",\n \"CMH\",\n \"toledo,oh\",\n \"erie,pa\",\n \"memphis,tn\",\n \"pittsburgh,pa\"\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":94,"value":"md`Step 1 is to geocode all of the input addresses to retrieve latitude,longitude pairs for each location.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":22,"value":"geocodedAddresses = {\n let geocodes = [];\n\n for (let i = 0; i < addresses.length; i++) {\n let resp = await fetch(\n `${geocodeURL}?key=${apiKey}&q=${addresses[i]}&at=${searchBiasLocation}&in=countryCode:USA&limit=1`\n ).then();\n geocodes.push(await resp.json());\n }\n return geocodes;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":98,"value":"md`Step 2 is to use the geocoded addresses to setup a balanced distance matrix request between each point. We define each point as an individual origin and destination.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":31,"value":"theDM = {\n let origs = \"\";\n let dests = \"\";\n geocodedAddresses.forEach((a) => {\n origs += `${a.items[0].position.lat},${a.items[0].position.lng}|`;\n dests += `${a.items[0].position.lat},${a.items[0].position.lng}|`;\n });\n origs = origs.substring(0, origs.length - 1);\n dests = dests.substring(0, dests.length - 1);\n\n let response = await fetch(\n `${dmURL}?key=${apiKey}&origins=${origs}&destinations=${dests}&mode=4w`\n ).then((dmResp) => dmResp.json());\n return response;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":103,"value":"md`Display a formatted table of the results - in this case we display the distance in Km between each location.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":37,"value":"\n \n \n \n ${addresses.map(a => htl.html``)}\n \n \n \n ${theDM.rows.map((dm,idx) => htl.html`\n \n ${dm.elements.map(el => htl.html``)}\n `)}\n \n

${theDM.localDatetime}	${a}
${addresses[idx]}	${(el.distance.value/1000).toFixed(0)}

","pinned":false,"hidden":false,"mode":"html"},{"id":9,"value":"import { secret2 } from \"@nbai/nextbillion-ai-dependencies\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":18,"value":"dmURL = \"https://api.nextbillion.io/distancematrix/json\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"geocodeURL = \"https://api.nextbillion.io/h/geocode\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":26,"value":"searchBiasLocation = \"40.1177,-83.1265\"","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W2f","stdlib":"1","titling":"auto"}