53 lines
2.0 KiB
R
53 lines
2.0 KiB
R
##
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# R script to get data from PublicStuff
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# Note that the API version at https://www.publicstuff.com/developers#!/API is v2.0,
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# but this only includes requests up to a certain date. Use v2.1 for recent requests.
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library(jsonlite)
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library(rjson)
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library(dplyr)
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# Grab city view for Grand Forks
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gfk <- rjson::fromJSON(file="https://www.publicstuff.com/api/2.1/city_view?space_id=15174")
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## Make a data frame of request_type IDs and names
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gfk_request_types <- as.data.frame(t(sapply(gfk$response$request_types$request_types,
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function(x) c(x$request_type$id, x$request_type$name))))
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# Add column names
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names(gfk_request_types) <- c("request_type_id","request_type_name")
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# Loop through request types and get n most recent in each category
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# Unix timestamp from a week ago
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today <- as.numeric(as.POSIXct(Sys.time()))
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week_ago <- today-604800
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# For all request types, get (at most) 10 requests from the last week from the PublicStuff API.
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gfk_requests <- lapply(gfk_request_types$request_type_id,
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function(x) jsonlite::fromJSON(paste0("https://www.publicstuff.com/api/2.1/requests_list?request_type_id=",
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x,"&after_timestamp=",week_ago,"&limit=10")))
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# Pull out exactly the data we need
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gfk_requests <- lapply(gfk_requests, function(x) x$response$requests$request)
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# Drop null list items
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gfk_requests <- Filter(Negate(is.null), gfk_requests)
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# Drop images (in fact, there is image_thumbnail in the data we want,
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# and we can just replace small_ with large_ to get a bigger image later!)
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drop_image <- function(x){
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if(class(x$primary_attachment) == "data.frame") {
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x$primary_attachment <- NULL
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}
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return(x)
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}
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gfk_requests <- lapply(gfk_requests, drop_image)
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# Put the requests together in a data frame
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gfk_requests <- bind_rows(gfk_requests)
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#### Tweeting
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# After tweeting, write a small text file that has the last timestamp that was tweeted. Use that for grabbing future requests.
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