Site: Optimize dojo stats and update dashboard layout #959
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dojo_plugin/utils/stats.py
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| challenge_ids = [c.challenge_id for c in dojo.challenges] | ||
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| stats = db.session.execute( | ||
| text(""" | ||
| SELECT | ||
| COUNT(DISTINCT user_id) as total_users, | ||
| COUNT(*) as total_solves | ||
| FROM submissions | ||
| WHERE type = 'correct' | ||
| AND challenge_id = ANY(:challenge_ids) | ||
| """), |
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The new raw SQL in get_dojo_stats() now counts all correct submissions for the dojo’s challenge IDs without the filters that dojo.solves() previously applied. Admin solves, hidden users, challenges that aren’t yet visible, and optional challenges all contribute to total_users and total_solves, whereas the old implementation excluded them by default. This inflates the dashboard statistics and can leak activity for hidden or unreleased challenges. Consider reproducing the filter set from dojo.solves() so the numbers match what the rest of the site treats as public progress.
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dojo_plugin/utils/stats.py
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| challenge_ids = [c.challenge_id for c in dojo.challenges] | ||
|
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||
| stats = db.session.execute( | ||
| text(""" | ||
| SELECT | ||
| COUNT(DISTINCT user_id) as total_users, | ||
| COUNT(*) as total_solves | ||
| FROM submissions | ||
| WHERE type = 'correct' | ||
| AND challenge_id = ANY(:challenge_ids) | ||
| """), | ||
| {"challenge_ids": challenge_ids} |
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When a dojo has no challenges, challenge_ids is an empty list. Executing challenge_id = ANY(:challenge_ids) with an empty list causes PostgreSQL to raise cannot determine type of empty array, resulting in a 500 when the stats page is rendered for a freshly created dojo. The previous implementation simply returned zeros in this case. Guard against an empty list (return zeros early or cast the parameter to a typed empty array) before running the SQL.
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Updated get_dojo_stats and ran testing by adding synthetic users with solves. Two indexes were added to optimize these properly. I have provided my test results showing execution time with and without the new indexes: Note Tested against a dojo locally with 730k synthetic solves. Total Solves:Using DISTINCT & Without New Indexes
Using DISTINCT & With New Indexes
Using GROUP BY & Without New Indexes
Using GROUP BY & With New Indexes
Recent Solves:Without New Index
With New Indexes
Total New Indexes: 2 
Note Performance improvements are dependent on adding 2 indexes. Synthetic Users + Solves:from datetime import datetime, timedelta
NUM_USERS = 3000
BATCH = 200
PREFIX = "synthetic"
MAX_DAYS = 90
chals = Challenges.query.order_by(Challenges.id.asc()).all()
total = len(chals)
now = datetime.now()
solves_to_insert = []
for i in range(NUM_USERS):
is_hidden = (i % 100 == 0)
is_admin = (i % 500 == 0)
u = Users(
name=f"{PREFIX}-{i}",
email=f"{PREFIX}-{i}@email.com",
hidden=is_hidden,
type="admin" if is_admin else "user"
)
db.session.add(u)
pct = (abs(hash(f"{i}-seed-42")) % 100) / 100.0
k = int(pct * total)
if k > 0:
for j in range(k):
days_ago = abs(hash(f"solve-{i}-{j}")) % MAX_DAYS
solve_time = now - timedelta(days=days_ago)
chal_idx = abs(hash(f"chal-{i}-{j}")) % total
solves_to_insert.append((solve_time, u, chals[chal_idx]))
db.session.commit()
print(f"Created {NUM_USERS} users")
solves_to_insert.sort(key=lambda x: x[0])
for idx, (solve_time, user, challenge) in enumerate(solves_to_insert):
db.session.add(Solves(challenge=challenge, user=user, date=solve_time))
if (idx + 1) % BATCH == 0:
db.session.commit()
print(f"Committed {idx + 1} solves")
db.session.commit()
print(f"Done. Created {len(solves_to_insert)} solves dated within the last {MAX_DAYS} days.") |
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2 participants
Updates the dojo stats function and updates the stats dashboard to simplify the displayed stats. The
get_dojo_stats()function now uses direct SQL queries, removed chart and trend data. The stat dashboard has been redesigned to fit the updated results of the stats function.(Award logic is unchanged; I do not have any awards data locally)
Backend stats calculation:
Frontend dashboard redesign:
UI and styling improvements: