Looking Up a User’s Location’s Info

You may want to customize the user’s experience based on where they are. For example calling .. code:: python

#create a user you are interested in based on their ip. Other fields (coordinates, time, etc) can also be included example_user = User(ip=”143.127.128.10”)

result = brein.temporal_data(example_user)

will result in a dictionary of timely information for the location the ip address resolves to (San Jose), for example:

#wrap the result in json.dumps() for readability
print(json.dumps(result,indent=4))

{
    "time": {
        "epochDayName": "Monday",
        "localYear": 2016,
        "epoch": 1477945062,
        "timezone": "America/Los_Angeles",
        "localDay": 31,
        "epochSecond": 42,
        "epochMinute": 17,
        "epochDay": 31,
        "localMonth": 10,
        "localMinute": 17,
        "localDayName": "Monday",
        "epochHour": 20,
        "epochMonth": 10,
        "epochYear": 2016,
        "localFormatIso8601": "2016-10-31T13:17:42-07:00",
        "localSecond": 42,
        "localHour": 13,
        "epochFormatIso8601": "2016-10-31T20:17:42+00:00"
    },
    "holidays": [
        {
            "source": "United Nations",
            "types": [
                "SPECIAL_DAY"
            ],
            "holiday": "World Cities Day"
        },
        {
            "source": "Public Information",
            "types": [
                "HALLMARK"
            ],
            "holiday": "Halloween"
        }
    ],
    "weather": {
        "lastMeasured": 1477935065,
        "precipitation": {
            "precipitationType": "none",
            "precipitationAmount": 0.0
        },
        "windStrength": 1.4,
        "cloudCover": 48.0,
        "temperature": 13.161000000000001,
        "description": "scattered clouds",
        "measuredAt": {
            "lon": -121.767731,
            "lat": 37.23328
        }
    },
    "location": {
        "country": "US",
        "granularity": "city",
        "city": "San Jose",
        "lon": -121.827179,
        "lat": 37.366051,
        "state": "CA"
    }
}

Looking Up Information About a Location

Instead of looking up information based off a user’s location, you can just supply the location’s information directly. For example, you could get yesterday’s weather in San Francisco by running:

from breinify import Breinify
import time
import math

apiKey = "938D-3120-64DD-413F-BB55-6573-90CE-473A"

brein = Breinify(apiKey)

yesterday = math.floor(time.time()) - 24*60*60

result = brein.temporal_data(location_free_text="San Francisco, CA", unixtime = yesterday)

print("Yesterday in %s, the weather was %s with a temperature of %d F."%(result['location']['city'], result['weather']['description'], result['weather']['temperatureF']))

Which will print something similar to “Yesterday in San Francisco, the weather was overcast clouds with a temperature of 64 F.”