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Episode 3: Playlist Redux

Use Metaflow to load the statistics generated from Episode 2 Is this Data Science and recommend movies from a genre with highest median gross box office

Showcasing:

  • Using data artifacts generated from other flows.

Before playing this episode:

Run 'Episode 02-statistics: Is this Data Science?'

To play this episode:

If you haven't yet pulled the tutorials to your current working directory, you can follow the instructions here.

  1. cd tutorials/03-playlist-redux
  2. Rscript playlist.R show
  3. Rscript playlist.R run

In this PlayListReduxFlow, we reuse the genre median gross box office statistics computed from MoviesStatsFlow, pick the genre with the highest median gross box office, and create a randomized playlist of movies of this picked genre.

library(metaflow)

# Use the Metaflow client to retrieve the latest successful run from our
# MovieStatsFlow and assign them as data artifacts in this flow.
start <- function(self){
# Loads the movie data into a data frame
self$df <- read.csv("./movies.csv", stringsAsFactors=FALSE)

message("Using metadata provider: ", get_metadata())

flow <- flow_client$new("MovieStatsFlow")
run <- run_client$new(flow, flow$latest_successful_run)
message("Using analysis from: ", run$pathspec)

self$genre_stats <- run$artifact("stats")
}

# Pick some movies from the genre with highest median gross box office
# which we calculated in MovieStatsFlow
pick_movie <- function(self){
sort_order <- order(self$genre_stats$median, decreasing=TRUE)
sorted_stats <- self$genre_stats[sort_order, ]

self$picked_genre <- sorted_stats$genres[1]

message("Picked genre: ", self$picked_genre, " with the highest median gross box office.")

# generate a randomized playlist of titles of the picked genre
movie_by_genre <- self$df[self$df$genre == self$picked_genre, ]
shuffled_rows <- sample(nrow(movie_by_genre))
self$playlist <- movie_by_genre[shuffled_rows, ]
}

# Print out the picked movies
end <- function(self){
message("Playlist for movies in picked genre: ", self$picked_genre)
for (i in 1:nrow(self$playlist)){
message(sprintf("Pick %d: %s", i, self$playlist$movie_title[i]))

if (i >= self$top_k) break;
}
}

metaflow("PlayListReduxFlow") %>%
parameter("top_k",
help = "The number of movies to recommend in the playlist.",
default = 5,
type = "int") %>%
step(step = "start",
r_function = start,
next_step = "pick_movie") %>%
step(step = "pick_movie",
r_function = pick_movie,
next_step = "end") %>%
step(step = "end",
r_function = end) %>%
run()