create a collage with the best 9 tweets from the tweet activity data

best9oftweets.R

# code adapted from http://www.masalmon.eu/2017/12/30/best9of2017/

library(purrr)
library(webshot) #webshot::install_phantomjs()
library(magick)
library(dplyr)
library(glue)

# load all the CSV files in the data folder downloaded from https://analytics.twitter.com/user/<username>/tweets
my_tweets <- file.path("data", list.files("data", pattern = "^tweet_activity_metrics_")) %>% map_df(readr::read_csv)

# select the 9 best tweets
my_best_tweets <- my_tweets %>% 
  mutate(score = retweets + likes / 2 + replies) %>% # custom score, I don't only using the likes
  arrange(desc(score)) %>% 
  slice(1:9)

# take screenchot of the best tweets and save them in temporary files
my_best_tweets_shots_paths <- my_best_tweets %>% 
  select(`Tweet id`, `Tweet permalink`) %>% 
  mutate(
    webshot_filepath = webshot(
      url = `Tweet permalink`, 
      file = rerun(9, tempfile(pattern = "shot_", fileext = ".png")) %>% unlist(), 
      cliprect = c(0, 150, 650, 650)
      )
    )

# collage is made column by column
# then the columns are assembled in one image
make_col <- function(path, color, geometry) {
  tmp <- tempfile(fileext = ".png")
  image_read(path) %>% 
    image_border(color = color, geometry = geometry) %>% 
    image_append(stack = TRUE) %>% # append pictures vertically
    image_write(tmp)
  return(tmp)
}

my_best_tweets_shots_paths %>% 
  mutate(column = rep(1:3, 3)) %>% # assign each tweet to a column
  group_by(column) %>% 
  summarise(col_image = make_col(webshot_filepath, color = "#777777", geometry = "30x30")) %>% 
  pull(col_image) %>% 
  image_read() %>% 
  image_append(stack = FALSE) %>% # append column pictures horizontally
  image_border(color = "#777777", geometry = "30x30") %>% 
  image_write("best9of2017.png")