Now that I have clean data from slack in DB, I can do a lot of interesting things with it 🤩

Top contributors (all time)

iex(12)> SlackUtility.Analytics.get_top_contributors
[debug] QUERY OK source="client_messages" db=5.2ms
SELECT u1."name", u1."real_name", count(c0."id") FROM "client_messages" AS c0 INNER JOIN "users" AS u1 ON u1."client_id" = c0."user_id" GROUP BY u1."name", u1."real_name" ORDER BY count(c0."id") DESC LIMIT 10 []
[
  {"abhishekbose87", "Abhishek", 1016},
  {"tuxcanfly", "Javed Khan", 228},
  {"pravin.310", "Pravin Singh", 153},
  {"suhasmotwani90", "Suhas M", 93},
  {"devagul93", "Devansh Gulhane", 63},
  {"phanimahesh", "Phani Mahesh", 52},
  {"mail", "Divyendu Singh", 48},
  {"rusrushal13", "Rushal Verma", 39},
  {"prank7", "Prashant Abhishek", 39},
  {"arpit", "Arpit Choudhury", 35}
]

Top contributors (last 10 days)

iex(18)> SlackUtility.Analytics.get_top_contributors
[debug] QUERY OK source="client_messages" db=4.1ms
SELECT u1."name", u1."real_name", count(c0."id") FROM "client_messages" AS c0 INNER JOIN "users" AS u1 ON u1."client_id" = c0."user_id" WHERE (c0."created_at" >= $1) GROUP BY u1."name", u1."real_name" ORDER BY count(c0."id") DESC LIMIT 10 [{2019, 2, 26}]
[
  {"abhishekbose87", "Abhishek", 83},
  {"rusrushal13", "Rushal Verma", 15},
  {"phanimahesh", "Phani Mahesh", 13},
  {"pravin.310", "Pravin Singh", 12},
  {"bsaaravind", "Aravind Balla", 9},
  {"sbanskota08", "Sarup Banskota", 8},
  {"ankitankit_arora", "Ankit Arora", 7},
  {"himvais", "Himanshu Vaishnav", 7},
  {"<http://nilesh.tr|nilesh.tr>", "anon", 5},
  {"souvikhaldar32", "Souvik Haldar", 5}
]