### Introduction We all know that Cloud technologies and Machine Learning are extremely advancing, therefore, we need to utilize this. AWS(Amazon Web Services) has a service called Polly reads a text, now this service uses Machine Learning in the background, but that is not the scope of this post. ### A bit about the project I extracted weather data by using the OWM(Open Weather Map) API for two cities in Hungary: Budapest and Miskolc. My goal with this project was that everyone has a fast lifestyle, that we do not have the time to check the weather. SO that is why I created this so, for example, you can do your work while listening the weather data. This also can be enriched with news data, so I tried to use news API and enrich this application. Polly will read the top-news headlines. The code was written in R (using R studio) and below I will show my code. #### Importing libraries and setting global variables Here I am using the **owmr** and **tidyverse** libraries. The owmr library is the interface that R has with OWM. I saved my API key somewhere safe in my directory and externally load it. ```r # SETTING THE ENVIRONMENT #----------------------------------------- library(owmr) library(tidyverse) #I will get my API key that is stored in my project directory, #and make it global #If you want to use this code, #then name the file API_KEY and #put the API key in the file. API_KEY <- read_file("API_KEY") Sys.setenv(OWM_API_KEY = API_KEY) ``` #### Specifying the location that I want to get weather data Here I am trying to get the weather data with the API. In order to do that I need to get the id of the cities, that are defined by the API. So the tibble owm_cities contains the id and coordinates of the cities. ```r # ASSIGNING CITIES #----------------------------------------- #The city that I am interested in is Budapest and Deprecen(Hungarian Cities) desired_city <- c("Budapest","Miskolc") #In the package there is a tibble with the cities" head(owm_cities) # I am getting the id of the cities id_of_cities <- owm_cities %>% filter(nm %in% desired_city) %>% select(id,nm) ``` #### Getting the weather data Here I am getting the data from the API, but the data is in format that is hard to work on, however owmr package has a nice function called owmr_as_tibble that transforms the API response from a complicated object to a tibble. ```r # GETTING CURRENT WEATHER DATA # ------------------------------------------------- #Getting the current weather data for this cities response_from_API <- get_current_for_group(id_of_cities$id) class(response_from_API) #Because the format that response_from_API has it is not formated well enough #I will use a function that turns the list and owmr_group in tibble response_from_API response_tibble <- owmr_as_tibble(response_from_API) ``` ### Here I am trying to get the forecast ```r # FORECAST WEATHER DATA # ------------------------------------------------- #getting the forecast forecast_Budapest <- get_forecast("Budapest") forecast_Miskolc <- get_forecast("Miskolc") #making them a tibble forecast_Budapest <- owmr_as_tibble(forecast_Budapest) forecast_Budapest forecast_Miskolc <- owmr_as_tibble(forecast_Miskolc) #Well I am intereste in getting the first 9 hours of the data, or the first 3 hours to # the third 3 hour interval. forecast_Budapest <-forecast_Budapest %>% select(weather_main, temp,humidity,weather_description,wind_speed) forecast_Miskolc <-forecast_Miskolc %>% select(weather_main, temp,humidity,weather_description,wind_speed) ``` #### Saving data to AWS S3 Because data is so important, I will try to store it in S3 as well, just like back-up. ```r # SAVING FILES TO UPLOAD TO S3 #-------------------------------------- #For Budapest write_csv(forecast_Budapest,path = "Budapest_forecast.csv") #For Miskolc write_csv(forecast_Miskolc,path = "Miskolc_forecast.csv") # GETTING READY TO UPLOAD THE DATA IN S3 #-------------------------------------- #getting the keys keyTable <- read.csv("credentials.csv", header = T) AWS_ACCESS_KEY_ID <- as.character(keyTable$Access.key.ID) AWS_SECRET_ACCESS_KEY <- as.character(keyTable$Secret.access.key) #making the Sys.setenv("AWS_ACCESS_KEY_ID" = "AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY" = "AWS_SECRET_ACCESS_KEY", "AWS_DEFAULT_REGION" = "eu-west-1") keyTable # UPLOADING DATA TO S3 #-------------------------------------- #importing library library(aws.s3) #name of my bucket bucket_name <- "sebair-selmani-1803425" #putting the forecast-data.Rdata in the bucket put_object("forecast-data.RData", bucket = bucket_name) #putting the current data put_object("current-data.RData", bucket = bucket_name) ``` #### The interesting part where I use Polly ```r # USING POLLY TO READ DATA #-------------------------------------- #READING THE CURRENT WEATHER library(aws.polly) library(aws.signature) response_tibble$ welcome<- synthesize("Welcome to my app user", voice = "Joanna") # the temp is in kelvins current_weather_Budapest <- synthesize(paste0("The current temprature in",as.character(desired_city[1]),"is", as.character((response_tibble$temp[1])-273.15),"and the humidity is" ,as.character(response_tibble$humidity[1],"and the weather description", response_tibble$weather_description[1],response_tibble$weather_main[1])),voice = "Ivy") current_weather_Miskolc <- synthesize(paste0("The current temprature in",as.character(desired_city[2]),"is", as.character((response_tibble$temp[2])-273.15),"and the humidity is" ,as.character(response_tibble$humidity[2],"and the weather description", response_tibble$weather_description[2],response_tibble$weather_main[2])),voice = "Ivy") #READING THE FORECAST FOR THE NEXT 3 HOURS, BUT I HAVE DATA FOR THE NEXT 9 HOURS forecast_weather_Budapest <- synthesize(paste0("The weather in the next 3 hours in", desirec_city[1], " The tempature will be ",forecast_Budapest$temp[1], "The humidity will be",forecast_Budapest$humidity[1], "and the overall description will be" ,forecast_Budapest$weather_description),voice = "Ivy") forecast_weather_Miskolc <- synthesize(paste0("The weather in the next 3 hours in", desirec_city[2], " The tempature will be ",forecast_Miskolc$temp[1], "The humidity will be",forecast_Miskolc$humidity[1], "and the overall description will be" ,forecast_Miskolc$weather_description),voice = "Ivy") # PLAYING WITH AUDACIOUS PLAYER library("tuneR") setWavPlayer("audacious") play(current_weather_Budapest) play(current_weather_Miskolc) play(forecast_weather_Budapest) play(forecast_weather_Miskolc) ``` #### Getting news from Google news API and playing only the headlines ```r # GETTING NEWS DATA FROM GOOGLE NEWS API #-------------------------------------- library(rvest) library(jsonlite) #my google news api key API_KEY_NEWS <- read_file("API_NEWS") # for getting the top news url <- paste0("https://newsapi.org/v2/top-headlines?country=hu&apiKey=",API_KEY_NEWS) data <- fromJSON(url_fake) data$articles$title #READING ONLY THE HEADLINES lapply(data$articles$title , function(inp){ title <- synthesize(inp,voice = "Ivy") play(title) }) goodbye <- synthesize("It was a pleasure to work with you. I wish you a happy day",voice = "Ivy") play(goodbye) ``` Well we came to the end of the project. This is only a mini project that can be developed to a full mobile application, but I will leave that for the future.

sebair_selmani

AWS Polly to read current weather and news

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