Voici une requête qui reproduit les scores de gamification et fournit une ventilation détaillée de qui a obtenu quoi et pourquoi :
-- [params]
-- date :start_date
-- date :end_date
-- int :day_visited_score_value = 1
-- int :time_read_score_value = 1
-- int :posts_read_score_value = 1
-- int :posts_created_score_value = 2
-- int :topics_created_score_value = 5
-- int :likes_received_score_value = 1
-- int :likes_given_score_value = 1
-- int :solutions_score_value = 10
-- int :flag_created_score_value = 10
-- int :user_invited_score_value = 10
WITH visits AS (
SELECT
uv.user_id,
COUNT(*) AS user_visits,
COUNT(*) * :day_visited_score_value AS visits_score
FROM user_visits uv
WHERE uv.visited_at BETWEEN :start_date AND :end_date
GROUP BY uv.user_id
),
time_read AS (
SELECT
uv.user_id,
SUM(uv.time_read) /3600 AS time_read,
SUM(uv.time_read) /3600 * :time_read_score_value AS time_read_score
FROM user_visits uv
WHERE uv.visited_at BETWEEN :start_date AND :end_date
AND uv.time_read >= 60
GROUP BY uv.user_id
),
posts_read AS (
SELECT
uv.user_id,
SUM(uv.posts_read) AS posts_read,
SUM(uv.posts_read) /100 * :posts_read_score_value AS posts_read_score
FROM user_visits uv
WHERE uv.visited_at BETWEEN :start_date AND :end_date
AND uv.posts_read >= 5
GROUP BY uv.user_id
),
posts_created AS (
SELECT
p.user_id,
COUNT(*) AS posts_created,
COUNT(*) * :posts_created_score_value AS posts_created_score
FROM posts p
INNER JOIN topics t ON t.id = p.topic_id
WHERE p.deleted_at IS NULL
AND t.archetype <> 'private_message'
AND p.wiki IS FALSE
AND p.created_at::date BETWEEN :start_date AND :end_date
GROUP BY p.user_id
),
topics_created AS (
SELECT
t.user_id,
COUNT(*) AS topics_created,
COUNT(*) * :topics_created_score_value AS topics_created_score
FROM topics t
WHERE t.deleted_at IS NULL
AND t.archetype <> 'private_message'
AND t.created_at::date BETWEEN :start_date AND :end_date
GROUP BY t.user_id
),
likes_received AS (
SELECT
p.user_id,
COUNT(*) AS likes_received,
COUNT(*) * :likes_received_score_value AS likes_received_score
FROM post_actions pa
INNER JOIN posts p ON p.id = pa.post_id
INNER JOIN topics t ON t.id = p.topic_id
WHERE p.deleted_at IS NULL
AND t.archetype <> 'private_message'
AND p.wiki IS FALSE
AND post_action_type_id = 2
AND pa.created_at::date BETWEEN :start_date AND :end_date
GROUP BY p.user_id
),
likes_given AS (
SELECT
pa.user_id AS user_id,
COUNT(*) AS likes_given,
COUNT(*) * :likes_given_score_value AS likes_given_score
FROM post_actions pa
INNER JOIN posts p ON p.id = pa.post_id
INNER JOIN topics t ON t.id = p.topic_id
WHERE p.deleted_at IS NULL
AND t.archetype <> 'private_message'
AND p.wiki IS FALSE
AND post_action_type_id = 2
AND pa.created_at::date BETWEEN :start_date AND :end_date
GROUP BY pa.user_id
),
solutions AS (
SELECT
p.user_id,
COUNT(ta.answer_post_id) AS solutions,
COUNT(ta.answer_post_id) * :solutions_score_value AS solutions_score
FROM discourse_solved_solved_topics st
JOIN discourse_solved_topic_answers ta ON ta.solved_topic_id = st.id
INNER JOIN topics t ON st.topic_id = t.id
INNER JOIN posts p ON p.id = ta.answer_post_id
WHERE p.deleted_at IS NULL
AND t.deleted_at IS NULL
AND t.archetype <> 'private_message'
AND p.user_id <> t.user_id
AND ta.updated_at::date BETWEEN :start_date AND :end_date
GROUP BY p.user_id
),
flags AS (
SELECT
r.created_by_id AS user_id,
COUNT(*) AS flags,
COUNT(*) * :flag_created_score_value AS flags_score
FROM reviewables r
WHERE created_at::date BETWEEN :start_date AND :end_date
AND status = 1
GROUP BY user_id
),
invites AS (
SELECT
inv.invited_by_id AS user_id,
SUM(inv.redemption_count) AS invites,
(SUM(inv.redemption_count) * :user_invited_score_value)::int AS invites_score
FROM invites inv
WHERE inv.created_at::date BETWEEN :start_date AND :end_date
AND inv.redemption_count > 0
GROUP BY inv.invited_by_id
)
SELECT
u.id AS user_id,
(
COALESCE(v.visits_score,0) +
COALESCE(tr.time_read_score,0) +
COALESCE(pr.posts_read_score,0) +
COALESCE(pc.posts_created_score,0) +
COALESCE(tc.topics_created_score,0) +
COALESCE(lr.likes_received_score,0) +
COALESCE(lg.likes_given_score,0) +
COALESCE(s.solutions_score,0) +
COALESCE(f.flags_score,0) +
COALESCE(i.invites_score,0)
) AS "Total Cheers",
COALESCE(v.user_visits,0) || ' (' || COALESCE(v.visits_score,0) || ')' AS "Visits (cheers)",
COALESCE(tr.time_read,0) || 'hrs' || ' (' || COALESCE(tr.time_read_score,0) || ')' AS "Time Read
(cheers)",
COALESCE(pr.posts_read,0) || ' (' || COALESCE(pr.posts_read_score,0) || ')' AS "Posts Read
(cheers)",
COALESCE(pc.posts_created,0) || ' (' || COALESCE(pc.posts_created_score,0) || ')' AS "Posts Created
(cheers)",
COALESCE(tc.topics_created,0) || ' (' || COALESCE(tc.topics_created_score,0) || ')'AS "Topics
Created (cheers)",
COALESCE(lr.likes_received,0) || ' (' || COALESCE(lr.likes_received_score,0) || ')' AS "Likes
Received (cheers)",
COALESCE(lg.likes_given,0) || ' (' || COALESCE(lg.likes_given_score,0) || ')' AS "Likes Given
(cheers)",
COALESCE(s.solutions,0) || ' (' || COALESCE(s.solutions_score,0) || ')'AS "Solutions (cheers)",
COALESCE(f.flags,0) || ' (' || COALESCE(f.flags_score,0) || ')' AS "Agreed Flags (cheers)",
COALESCE(i.invites,0) || ' (' || COALESCE(i.invites_score,0) || ')' AS "Invites Redeemed (cheers)"
FROM users u
LEFT JOIN visits v ON v.user_id = u.id
LEFT JOIN posts_read pr USING (user_id)
LEFT JOIN time_read tr USING (user_id)
LEFT JOIN flags f USING (user_id)
LEFT JOIN posts_created pc USING (user_id)
LEFT JOIN topics_created tc USING (user_id)
LEFT JOIN likes_given lg USING (user_id)
LEFT JOIN likes_received lr USING (user_id)
LEFT JOIN solutions s USING (user_id)
LEFT JOIN invites i USING (user_id)
WHERE u.id > 0
AND u.id NOT IN (SELECT user_id FROM group_users WHERE group_id = 3)
ORDER BY "Total Cheers" DESC
LIMIT 100
Il y a une dérive des scores lorsque la période d’analyse s’allonge, car la version officielle de la gamification arrondit des éléments comme le temps passé et le nombre de messages lus sur une base quotidienne, tandis que cette requête cumule tout, y compris les restes. Cependant, elle reste très utile pour vérifier à quoi ressembleraient d’éventuels changements de vos paramètres de scoring par défaut, sans avoir à recalculer tous les scores en direct de votre site.
Elle n’inclut également personne du groupe @staff, bien que ce soit assez simple à modifier si vous le souhaitez. 
Selon la taille de votre site, vous devrez peut-être réduire l’échelle de temps ou les groupes ciblés pour éviter les dépassements de délai d’exécution.
