High-performance, asynchronous and cache-aware Scala library for looking up the weather.

Used in Snowplow to power the Weather Enrichment for incoming events.

Scala Weather contains APIs to 2 weather providers: OpenWeatherMap and Dark Sky. It allows you to fetch the current weather, historical weather and weather forecasts for any city (OWM only) or geo coordinates.

We provide caching and basic clients for both providers - OwmClient and OwmCacheClient for OpenWeatherMap, DarkSkyClient and DarkSkyCacheClient for Dark Sky.

The latest version of Scala Weather is 2.0.0, which is cross-built against Scala 2.12 & 2.13.

If you're using SBT, add the following lines to your build file:

libraryDependencies += "com.snowplowanalytics" %% "scala-weather" % "2.0.0"

Note: All of the clients take F as a type parameter. It can be any type that has an instance of cats.effect.Sync, here we use cats.effect.IO. We also provide instances for cats.Eval and cats.Id in cases side-effects are needed (e.g. Spark or Beam)

First sign up to OpenWeatherMap to get your API key.

Unfortunately, with the free plan you can only perform current weather and forecast lookups; for historical data access you need to subscribe to the history plan. If you use the free plan all historyBy... methods will return failures.

Once you have your API key, you can create a client:

import scala.concurrent.duration._
import com.snowplowanalytics.weather.providers.openweather.CreateOWM
import cats.{Eval, Id}
import cats.effect.IO
val client = CreateOWM[IO].create(
  "history.openweathermap.org", "YOUR_KEY", timeout = 1.seconds, ssl = true)
// using Eval and Id
val evalClient = CreateOWM[Eval].create(
  "history.openweathermap.org", "YOUR_KEY", timeout = 1.seconds, ssl = true)
val idClient = CreateOWM[Id].create(
  "history.openweathermap.org", "YOUR_KEY", timeout = 1.seconds, ssl = true)

OpenWeatherMap provides several hosts for API with various benefits, which you can pass as the first argument:

• api.openweathermap.org - free access, recommended
• history.openweathermap.org - paid, history only
• pro.openweathermap.org - paid, faster, SSL-enabled

Both the caching and normal clients offer the same set of public methods:

• forecastById
• forecastByName
• forecastByCoords
• currentById
• currentByName
• currentByCoords
• historyById
• historyByName
• historyByCoords

These methods were designed to follow OpenWeatherMap's own API calls as closely as possible. All of these calls receive similar arguments to those described in OpenWeatherMap API documentation. For example, to receive a response equivalent to this API call: api.openweathermap.org/data/2.5/weather?lat=35&lon=139&appid=YOURKEY, run the following code:

import com.snowplowanalytics.weather.errors.WeatherError
import com.snowplowanalytics.weather.providers.openweather.responses.Current
val weatherInLondon: IO[Either[WeatherError, Current]] = client.currentByCoords(35.0f, 139.0f)
// using Eval and Id
val evalWeatherInLondon: Eval[Either[WeatherError, Current]] = evalClient.currentByCoords(35.0f, 139.0f)
val idWeatherInLondon: Either[WeatherError, Current] = idClient.currentByCoords(35.0f, 139.0f)

Notice that all temperature fields are in Kelvin, which is the OpenWeatherMap default (OWM only supports unit preference for the current weather).

Scala Weather doesn't try to validate your arguments (except of course their types), so invalid calls like this one:

// Count is supposed to be positive
val forecast: IO[Either[WeatherError, Current]] = client.forecastById(3070325, cnt=-1)

will still be executed and OpenWeatherMap will decide how to handle it (in this case, it will ignore negative count).

The caching client is created like this:

val cachingClient = CreateOWM[IO].create(
  "history.openweathermap.org", "YOUR_KEY", timeout = 1.seconds, ssl = true, cacheSize = 5000, geoPrecision = 2)

More on cacheSize and geoPrecision below.

Sign up here to receive the API key. Dark Sky currently allows for 1000 free requests per day.

Similar to OpenWeatherMap, to create a basic client you can use the factories in the DarkSky object:

import com.snowplowanalytics.weather.providers.darksky.DarkSky
import cats.{Eval, Id}
import cats.effect.IO

val client = CreateOWM[IO].create(
  "history.openweathermap.org", "YOUR_KEY", timeout = 1.seconds)
// using Eval and Id
val evalClient = CreateDarkSky[Eval].create(
  "history.openweathermap.org", "YOUR_KEY", timeout = 1.seconds)
val idClient = CreateDarkSky[Id].create(
  "history.openweathermap.org", "YOUR_KEY", timeout = 1.seconds)

Dark Sky API is much simpler than OWM, it consists only of two functions, namely forecast and timeMachine

• forecast returns the current weather and the forecast for next week
• timeMachine returns the observed or forecast weather for the specified date in the past or the future

Example:

import java.time.ZonedDateTime
import com.snowplowanalytics.weather.errors.WeatherError
import com.snowplowanalytics.weather.providers.darksky.responses.DarkSkyResponse
// Fetches weather a year ago in New York
val response: IO[Either[WeatherError, DarkSkyResponse]] =
  client.timeMachine(40.71f, 74.0f, ZonedDateTime.now().minusYears(1))

Unlike OpenWeatherMap, Dark Sky does not provide geocoding features, meaning you must know the latitude and longitude of the location.

Scala Weather provides a cache as part of the weather.providers.openweather.OwmCacheClient or weather.providers.darksky.DarkSkyCacheClient. It uses an LRU cache under the hood and only works for historical lookups. OpenWeatherMap restricts the number of history lookups you can make on the paid plans, so this cache helps to minimize requests, especially when run from a "big data" frameworks.

Note that the results of common methods like historyById, currentByCoords etc are not cached. To employ the cache, you need to use:

• for OWM cachingHistoryByCoords
• for Dark Sky cachingTimeMachine

The following client factory arguments help to tune the cache:

• cacheSize determines how many daily weather reports for a location can be stored in the cache before entries start getting evicted
• geoPrecision determines how precise your cache will be from geospatial perspective

This essentially rounds the decimal places part of the geo coordinate to the specified part of 1. Some example settings:

• Setting to 1 will round both 32.05 and 32.4 to 32.0 (so 1/1)
• Setting to 2 will round 32.4 to 32.5, and 30.1 to 30.0 (so, 1/2)
• Setting to 5 will round 42.11 to 42.2 (so, 1/5)

In the worst precision case (geoPrecision == 1), our geo-locations for the weather will be up to ~60km out. But you need to note that the primary sources of weather inaccuracies are not usually distance, but things like urban/suburbian area, or rapid extreme weather changes, or the distance to the closest weather station (hundreds kilometers in some rare cases).

So, you can consider 1 as a good default value; it's strongly discouraged to set it higher than 10.

OwmCacheClient and DarkSkyCacheClient's internal cache stores responses in a map, which key is computed roughly as:

round(latitude), round(longitude), beginningOfDay

After the first request, it will try to fetch information for this exact place (round(latitude), round(longitude)) for the given day. The OWM cache value usually consists of several (8-24) Weather objects, each with its own timestamps.

cachingHistoryByCoords in the OWM client will return the closest weather for the specified timestamp and leave the others in the cache. For example, the following code will make only one request to OpenWeatherMap, but return 3 distinct results:

cachingTimeMachine in the Dark Sky client will return the whole DarkSkyResponse for the specified day. The field currently will be omitted, so the user must rely on the hourly or daily fields.

The return type of both caching clients creation is wrapped in the effect type, as the creation of the underlying cache allocates mutable state.

import com.snowplowanalytics.weather.providers.openweather.OpenWeatherMap
import cats.effect.IO

val action = for {
  client <- CreateOWM[IO].create("history.openweathermap.org", "YOUR_KEY", timeout = 1.seconds, ssl = true, cacheSize = 10, geoPrecision = 1)
  response1 <- client.cachingHistoryByCoords(10.4f, 32.1f, 1514765952)   // Jan 1 12:19:12 2018.
  response2 <- client.cachingHistoryByCoords(10.1f, 32.312f, 1514821267) // Jan 1 15:41:07 2018. From cache
  response3 <- client.cachingHistoryByCoords(10.2f, 32.4f, 1514776320)   // Jan 1 03:12:00 2018. From cache
} yield (response1, response2, response3)

action.unsafeRunSync()

Scala Weather is copyright 2015-2022 Snowplow Analytics Ltd.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License.

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.