Visual Crossing — The weather experts

Have you ever looked for a reliable API service to find weather details — historical, current or forecasts? If your Google search takes you to Visual Crossing, stop right there, because that is exactly what you’re looking for. Visual Crossing is the source for worldwide weather data, weather APIs, and geospatial mapping for businesses and professionals.

But why would you need bulk weather data? Perhaps you wish to build your own mobile application where your end users are can find weather data or alerts based on their current location or geolocation. Or you may be looking for historical weather data as a label for some Tensorflow model.

Visual Crossing, as per their website

the source for worldwide weather data, weather APIs, and geospatial mapping for businesses and professionals

They have pricing plans that will scale to any type of requirements — small or big.

If your project prototype requires to get bulk weather data, you can think about the Pay-as-you-go plan which is reasonably cheap. I believe, the monthly plan at USD 35 is good enough to cover the weather data needs of a small mobile application. Moreover, their APIs are so flexible so that you can decide on how you go about getting the data you wanted. If you want the data in bulk, you can get it in bulk. You want concurrent access, you got that covered too — even the basic monthly plan gives the power to do perform two requests at a time. If you have wanted just a day’s data you have that. They also support the Open Data Protocol to publish Visual Crossing Weather Data for retrieval by OData capable systems — should you be thinking at a large scale already. Once you subscribe to a plan, you will immediately feel, you’re home.

But ask me, what makes Visual Crossing so cool?

It is their reliable support team. You will get prompt replies to your questions via chat and email. Enhanced support and SLA options are available for Enterprise Customers.

Below is one of the many requests to the Visual Crossing Servers.

# Python Indeed
# Each of these requests have a query cost of one.
# Look up the API documentation to see what a query cost means.
import requests
URL = "{latitude},{longitude}/{date}/{date}"
# Geocodes for Time Square NY
latitude = '40.758896'
longitude = '-73.985130'
txDate = '2020-10-04'
r = requests.get(url = url, params = PARAMS)

r = requests.get(url = url, params = PARAMS)
except requests.RequestException:
# Deal with Request exception
except requests.ConnectionError:
# Deal with Connection Error
except Error as e:
# Deal with any other error
# At this point your data is ready
data = r.json()
# Voila! parse the json in the data.

So why delay? Subscribe and party !!

I am software design engineer with 7+ years of industrial experience