My program is trying to determine the City, state, and country based on some text, for example "New york yankee stadium" I want to get New york city, NY, USA. I am using Google places API to do this. According to the documentations, the API should return a list of address component https://developers.google.com/places/web-service/details. However, right now its only returning formatted address "1 E 161st St, Bronx, NY 10451, United States".
here is my web service url
https://maps.googleapis.com/maps/api/place/textsearch/json?key=MY_KEY&query=new%20york%20yankee%20stadium
Anyone familiar with google places API that can let me know if I am not writting the right query or parameter?
{
"html_attributions" : [],
"results" : [
{
"formatted_address" : "1 E 161st St, Bronx, NY 10451, United States",
"geometry" : {
"location" : {
"lat" : 40.82964260000001,
"lng" : -73.9261745
},
"viewport" : {
"northeast" : {
"lat" : 40.83279975,
"lng" : -73.92236575000001
},
"southwest" : {
"lat" : 40.82643674999999,
"lng" : -73.93052034999999
}
}
},
"icon" : "https://maps.gstatic.com/mapfiles/place_api/icons/generic_business-71.png",
"id" : "3d78036d61d35f48650bda737226432b57d82511",
"name" : "Yankee Stadium",
"opening_hours" : {
"open_now" : true,
"weekday_text" : []
},
"photos" : [
{
"height" : 540,
"html_attributions" : [
"\u003ca href=\"https://maps.google.com/maps/contrib/101696810905045719819/photos\"\u003eYankee Stadium\u003c/a\u003e"
],
"photo_reference" : "CoQBdwAAAIxmCLrNS_XZ2FcJqVvRVtBUlNYMBVTVKppOWBu7sICj2q70cqJARBoJlTcZpydbMTzURKWWMVJhYpVCqsnia5pjmDhjvjsTirrEnAc6gvmRYKuUwgewB9Re--FulXzXZ5DY3P9fkwIwuc4U9BJVbqHD5O-N6SbbHcqn4XHUj_OdEhCoNPZ3kiNJhxOCGdYG5O4DGhTqVfUjdq7JzasqYATvQxkL1-H3xg",
"width" : 1242
}
],
"place_id" : "ChIJcWnnWiz0wokRCB6aVdnDQEk",
"rating" : 4.4,
"reference" : "CmRRAAAA5dHiw1YmLxW60_jITBZjMiUs48L4aVUqlPnPDpN_ySa7rw8kPp04WWk0qf8mG-kkMFSNzh39lP0YwfynW54tLcY4s_EYbAPvNWTMe6wXHm_FJiVbI0Lfenyxz4yOTzunEhDgI64EWoXkQe9k45y6qP3-GhSVSdCMPPZA3joFbnYGV-bqo2e0lw",
"types" : [ "stadium", "point_of_interest", "establishment" ]
}
],
"status" : "OK"
}
Its a two step process, first search and get the place_id from google places search service,
use the returned place_id and pass it with another call to receive the individual address components,
https://maps.googleapis.com/maps/api/place/details/json?place_id=ChIJcWnnWiz0wokRCB6aVdnDQEk&key=
{"html_attributions": [],
"result": {
"address_components": [
{
"long_name": "1",
"short_name": "1",
"types": [
"street_number"
]
},
{
"long_name": "East 161st Street",
"short_name": "E 161st St",
"types": [
"route"
]
},
{
"long_name": "Concourse",
"short_name": "Concourse",
"types": [
"neighborhood",
"political"
]
},
{
"long_name": "Bronx",
"short_name": "Bronx",
"types": [
"sublocality_level_1",
"sublocality",
"political"
]
},
{
"long_name": "Bronx County",
"short_name": "Bronx County",
"types": [
"administrative_area_level_2",
"political"
]
},
Related
I need to return AppointmentTypes as a FHIR resource. Unfortunately, I couldn't find it as an official FHIR resource format.
My best guess would be to create a Basic resource, like this:
{
"resourceType": "Basic",
"id" : "id-of-appointment-type",
"identifier" : [
{
"use" : "secondary",
"system" : "http://myUrl/myIdentifier",
"value" : "7"
}
],
"code" : {
"coding": [
{
"system": "http://myUrl/appointment-type",
"code": "appointment-type"
}
]
},
"text" : {
"status" : "generated",
"div" : "<div xmlns=\"http://www.w3.org/1999/xhtml\">AppointmentType</div>"
},
"extension": [
{
"url": "http://myUrl/appointment-type-name",
"valueString": "New Patient"
},
{
"url": "http://myUrl/appointment-type-availability",
"valueBoolean": true
}
],
"meta" : {
"lastUpdated" : "2020-05-27T00:00:00.000Z"
}
}
Would this be the right way to create the AppointmentType resource?
I don't see any obvious issues, but did you evaluate using CodeSystem? You can define properties on CodeSystem codes which would be able to distinguish available from non-available appointment types - and that would work better with Appointment, where 'type' is expected to be a code.
I am using the Autocomplete API to get results 'biased' for current location with the following request:
https://maps.googleapis.com/maps/api/place/autocomplete/json?input=kuli&types=(regions)&key=[KEY]
The API returns the following response:
{
"predictions" : [
{
"description" : "Kulim Kedah Malaysia",
...
"types" : [ "locality", "political", "geocode" ]
},
{
"description" : "Kuliyapitiya, North Western Province, Sri Lanka",
...
"types" : [ "locality", "political", "geocode" ]
},
{
"description" : "Kulithalai, Tamil Nadu, India",
...
"types" : [ "locality", "political", "geocode" ]
},
{
"description" : "Kuligów, Poland",
...
"types" : [ "locality", "political", "geocode" ]
},
{
"description" : "Kulin, Western Australia, Australia",
...
"types" : [ "locality", "political", "geocode" ]
}
],
"status" : "OK"
}
As you can see above, the response does not bias for location. The doc says that the IP Address is taken into account when returning "near" locations. But from the response, the Indian locations are not returned first over others (The request IP address is Indian).
Even, when I pass location parameter with lat,long, as:
https://maps.googleapis.com/maps/api/place/autocomplete/json?input=kuli&types=(regions)&location=lat,long&key=[KEY]
still the Indian results are not prioritized over other response.
How do I make the API return location 'biased' over IP address or location coordinates? Thank you for your time.
Add components to your url: &components=country:IN
https://maps.googleapis.com/maps/api/place/autocomplete/json?input=kuli&components=country:IN&types=(regions)&location=lat,long&key=[KEY]
I am setting the return to true, but when i complete the payment on square, the app does not redirect on its own.
{
"amount_money": {
"amount" : "100",
"currency_code" : "USD"
},
"auto_return":true,
"callback_url" : "https://floating-inlet-19449.herokuapp.com/redirect",
"client_id" : "sq0idp-U8x6mJyLFtHuhCfv9sqL5g",
"version": "1.3",
"notes": "notes for the transaction",
"options" : {
"supported_tender_types" : ["CREDIT_CARD"]
}
auto_return should be nested in the options object, like this:
{
"amount_money": { "amount" : 100, "currency_code" : "USD" },
"callback_url" : "https://floating-inlet-19449.herokuapp.com/redirect",
"client_id" : "sq0idp-U8x6mJyLFtHuhCfv9sqL5g",
"version": "1.3",
"notes": "notes for the transaction",
"options" : {
"supported_tender_types" : ["CREDIT_CARD"],
"auto_return": true
}
When I make the following request (note the language=en part!) with latitude & longitude for Warsaw, Poland,
https://maps.googleapis.com/maps/api/geocode/json?latlng=52.23,21.01&language=en
I get a result list which includes the following:
Result 3 (neighborhood):
{
"address_components" : [
{
"long_name" : "Śródmieście Północne",
"short_name" : "Śródmieście Północne",
"types" : [ "neighborhood", "political" ]
},
{
"long_name" : "Śródmieście",
"short_name" : "Śródmieście",
"types" : [ "sublocality_level_1", "sublocality", "political" ]
},
{
"long_name" : "Warszawa", <-- city in Polish
"short_name" : "Warszawa",
"types" : [ "locality", "political" ]
},
{
"long_name" : "Warszawa",
"short_name" : "Warszawa",
"types" : [ "administrative_area_level_3", "political" ]
},
{
"long_name" : "Warszawa",
"short_name" : "Warszawa",
"types" : [ "administrative_area_level_2", "political" ]
},
{
"long_name" : "mazowieckie", <-- region in Polish
"short_name" : "mazowieckie",
"types" : [ "administrative_area_level_1", "political" ]
},
{
"long_name" : "Poland",
"short_name" : "PL",
"types" : [ "country", "political" ]
}
],
[...]
"place_id" : "ChIJjaxkh4rMHkcR1lza9qbbnrU",
"types" : [ "neighborhood", "political" ]
}
Result 4 (sublocality_level_1):
{
"address_components" : [
{
"long_name" : "Śródmieście",
"short_name" : "Śródmieście",
"types" : [ "sublocality_level_1", "sublocality", "political" ]
},
{
"long_name" : "Warsaw", <-- city in English
"short_name" : "Warsaw",
"types" : [ "locality", "political" ]
},
{
"long_name" : "Warszawa",
"short_name" : "Warszawa",
"types" : [ "administrative_area_level_3", "political" ]
},
{
"long_name" : "Warszawa",
"short_name" : "Warszawa",
"types" : [ "administrative_area_level_2", "political" ]
},
{
"long_name" : "Masovian Voivodeship", <-- region in English
"short_name" : "Masovian Voivodeship",
"types" : [ "administrative_area_level_1", "political" ]
},
{
"long_name" : "Poland",
"short_name" : "PL",
"types" : [ "country", "political" ]
}
],
[...]
"place_id" : "ChIJ8e41PvbMHkcRit4n8qe36Ns",
"types" : [ "sublocality_level_1", "sublocality", "political" ]
},
The main problem with this is the inconsistency for the same address components (locality, administrative_area_level_1) - sometimes English (as requested), sometimes the local language. Without some other ID to know that these refer to the same administrative reality, I can't be sure of that, unless I used another source of English & local geo names and did some pattern matching.
Is there a way to get around this problem? Or could someone suggest a reverse geocoding service not having such issues?
Many thanks!
I ran into the same problem. I wrote an if/else group to grab location data in order of preference.
foreach ($data->results[0]->address_components as $stuff) {
// city
if ($stuff->types[0] == 'locality') {
$zip->locality_short = $stuff->short_name;
$zip->locality_long = $stuff->long_name;
} elseif ($stuff->types[0] == 'sublocality_level_1') {
$zip->locality_short = $stuff->short_name;
$zip->locality_long = $stuff->long_name;
} elseif ($stuff->types[0] == 'neighborhood') {
$zip->locality_short = $stuff->short_name;
$zip->locality_long = $stuff->long_name;
}
// state
if ($stuff->types[0] == 'administrative_area_level_1') {
$zip->location_short = $stuff->short_name;
$zip->location_long = $stuff->long_name;
}
// country
if ($stuff->types[0] == 'country') {
$zip->country_short = $stuff->short_name;
$zip->country_long = $stuff->long_name;
}
}
Please, observe:
MongoDB shell version: 2.4.1
connecting to: test
> use dummy
switched to db dummy
> db.invoices.find({'items.nameTags': /^z/}, {_id: 1}).explain()
{
"cursor" : "BtreeCursor items.nameTags_1_created_1_special_1__id_1_items.qty_1_items.total_1 multi",
"isMultiKey" : true,
"n" : 55849,
"nscannedObjects" : 223568,
"nscanned" : 223568,
"nscannedObjectsAllPlans" : 223568,
"nscannedAllPlans" : 223568,
"scanAndOrder" : false,
"indexOnly" : false,
"nYields" : 86,
"nChunkSkips" : 0,
"millis" : 88864,
"indexBounds" : {
"items.nameTags" : [
[
"z",
"{"
],
[
/^z/,
/^z/
]
],
"created" : [
[
{
"$minElement" : 1
},
{
"$maxElement" : 1
}
]
],
"special" : [
[
{
"$minElement" : 1
},
{
"$maxElement" : 1
}
]
],
"_id" : [
[
{
"$minElement" : 1
},
{
"$maxElement" : 1
}
]
],
"items.qty" : [
[
{
"$minElement" : 1
},
{
"$maxElement" : 1
}
]
],
"items.total" : [
[
{
"$minElement" : 1
},
{
"$maxElement" : 1
}
]
]
},
"server" : "IL-Mark-LT:27017"
}
>
Here is the definition of the index:
> db.system.indexes.find({name : 'items.nameTags_1_created_1_special_1__id_1_items.qty_1_items.total_1'}).pretty()
{
"v" : 1,
"key" : {
"items.nameTags" : 1,
"created" : 1,
"special" : 1,
"_id" : 1,
"items.qty" : 1,
"items.total" : 1
},
"ns" : "dummy.invoices",
"name" : "items.nameTags_1_created_1_special_1__id_1_items.qty_1_items.total_1"
}
>
Finally, here is an example invoice document (with just 2 items):
> db.invoices.findOne({itemCount: 2})
{
"_id" : "85923",
"customer" : "Wgtd Fm 91",
"businessNo" : "314227928",
"billTo_name" : "Wgtd Fm 91",
"billTo_addressLine1" : "3839 Ross Street",
"billTo_addressLine2" : "Kingston, ON",
"billTo_postalCode" : "K7L 4V4",
"purchaseOrderNo" : "boi",
"terms" : "COD",
"shipDate" : "2013-07-10",
"shipVia" : "Moses Transportation Inc.",
"rep" : "Snowhite",
"items" : [
{
"qty" : 4,
"name" : "CA 7789",
"desc" : "3 pc. Coffee Table set (Silver)",
"price" : 222.3,
"total" : 889.2,
"nameTags" : [
"ca 7789",
"a 7789",
" 7789",
"7789",
"789",
"89",
"9"
],
"descTags" : [
"3",
"pc",
"c",
"coffee",
"offee",
"ffee",
"fee",
"ee",
"e",
"table",
"able",
"ble",
"le",
"e",
"set",
"et",
"t",
"silver",
"ilver",
"lver",
"ver",
"er",
"r"
]
},
{
"qty" : 4,
"name" : "QP 8681",
"desc" : "Ottoman Bed",
"price" : 1179.1,
"total" : 4716.4,
"nameTags" : [
"qp 8681",
"p 8681",
" 8681",
"8681",
"681",
"81",
"1"
],
"descTags" : [
"ottoman",
"ttoman",
"toman",
"oman",
"man",
"an",
"n",
"bed",
"ed",
"d"
]
}
],
"itemCount" : 2,
"discount" : "10%",
"delivery" : 250,
"hstPercents" : 13,
"subTotal" : 5605.6,
"totalBeforeHST" : 5295.04,
"total" : 5983.4,
"totalDiscount" : 560.56,
"hst" : 688.36,
"modified" : "2012-10-08",
"created" : "2014-06-25",
"version" : 0
}
>
My problem is that mongodb does not use index only according to the aforementioned explain() output. Why? After all I only request the _id field, which is part of the index.
In general, I feel that I am doing something very wrong. My invoices collection has 65,000 invoices with the total of 3,291,092 items. It took almost 89 seconds to explain() the query.
What am I doing wrong?
You are using arrays and subdocuments. Covered Indexes dont work with either of these.
From the mongo docs:
An index cannot cover a query if:
any of the indexed fields in any of the documents in the collection includes an array. If an indexed field is an array, the index becomes a multi-key index index and cannot support a covered query.
any of the indexed fields are fields in subdocuments. To index fields in subdocuments, use dot notation. For example, consider a collection users with documents of the following form:
http://docs.mongodb.org/manual/tutorial/create-indexes-to-support-queries/