Expressiveness Benchmark

def process_tweets(data):
  result = []
  for value in data:
    if (value["language"] == "en" and
        value["is_retweet"] == "false"):
      result.append({
        "body": value["body"].lower(),
        "ts": value["ts"]
      })
  return result

def process_tweets(data):
  return [
    {"body": value["body"].lower(),
     "ts": value["ts"]}
    for value in data
    if value["language"] == "en" and
       value["is_retweet"] == "false" 
  ]

def process_tweets(data):
  result = data[
    (data.language == 'en') &
    (data.is_retweet == 'false')]
  result.body = result.body.apply(lambda s: s.lower())
  return result[["body", "ts"]]

process_tweets <- function(data) {
  data %>%
    filter(language == "en" & is_retweet == "false") %>%
    mutate(body = tolower(body)) %>%
    select(ts, body)
}

SELECT LOWER(body) as body, ts
FROM data
WHERE language = "en" and is_retweet = "false"

process_tweets:
  select lower[body], ts from data 
  where (is_retweet ~\: "false") and (language ~\: "en")