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galaxy: use bulk_create whenever possible

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This is a big performance gain, especially for the tests.

Examples:

----

`./manage.py test galaxy.tests.GalaxyTest.test_full_galaxy_state`

Measurements averaged over 3 run on *my machine*™:
Before: 2min15s
After: 1m41s

----

`./manage.py generate_galaxy_test_data --user-pack-count 1`

Before: 48s
After: 25s

----

`./manage.py rule_galaxy` (for 600 citizen, corresponding to 1 user-pack)

Before: 14m4s
After: 12m34s
This commit is contained in:
Skia
2023-04-19 18:10:42 +02:00
parent bb365e4ee5
commit 6328b0c9e9
4 changed files with 170 additions and 111 deletions
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76
galaxy/models.py
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@ -348,8 +348,20 @@ class Galaxy(models.Model):
f"{rulable_users_count} citizen have been listed. Starting to rule."
)
stars = GalaxyStar.objects.filter(galaxy=self)
stars = []
self.logger.info("Creating stars for all citizen")
for user in rulable_users:
star = GalaxyStar(
owner=user, galaxy=self, mass=self.compute_user_score(user)
)
stars.append(star)
GalaxyStar.objects.bulk_create(stars)
stars = {}
for star in GalaxyStar.objects.filter(galaxy=self):
stars[star.owner.id] = star
self.logger.info("Creating lanes between stars")
# Display current speed every $speed_count_frequency users
speed_count_frequency = max(rulable_users_count // 10, 1) # ten time at most
global_avg_speed_accumulator = 0
@ -360,44 +372,36 @@ class Galaxy(models.Model):
user1_count += 1
rulable_users_count2 = len(rulable_users)
star1, created = stars.get_or_create(owner=user1)
if created:
star1.galaxy = self
star1.save()
if star1.mass == 0:
star1.mass = self.compute_user_score(user1)
star1.save()
star1 = stars[user1.id]
user_avg_speed = 0
user_avg_speed_count = 0
tstart = time.time()
lanes = []
for user2_count, user2 in enumerate(rulable_users, start=1):
self.logger.debug("")
self.logger.debug(
f"\t> Examining '{user1}' ({user1_count}/{rulable_users_count}) with '{user2}' ({user2_count}/{rulable_users_count2})"
)
star2, created = stars.get_or_create(owner=user2)
if created:
star2.galaxy = self
star2.save()
star2 = stars[user2.id]
users_score, family, pictures, clubs = Galaxy.compute_users_score(
user1, user2
)
distance = self.scale_distance(users_score)
if distance < 30: # TODO: this needs tuning with real-world data
GalaxyLane(
star1=star1,
star2=star2,
distance=distance,
family=family,
pictures=pictures,
clubs=clubs,
).save()
lanes.append(
GalaxyLane(
star1=star1,
star2=star2,
distance=distance,
family=family,
pictures=pictures,
clubs=clubs,
)
)
if user2_count % speed_count_frequency == 0:
tend = time.time()
@ -410,6 +414,8 @@ class Galaxy(models.Model):
)
tstart = time.time()
GalaxyLane.objects.bulk_create(lanes)
self.logger.info("")
t_global_end = time.time()
@ -480,15 +486,27 @@ class Galaxy(models.Model):
F("owner__nick_name"),
Value(")"),
)
stars = GalaxyStar.objects.filter(galaxy=self).annotate(
owner_name=Case(
When(owner__nick_name=None, then=without_nickname),
default=with_nickname,
stars = (
GalaxyStar.objects.filter(galaxy=self)
.order_by(
"owner"
) # This helps determinism for the tests and doesn't cost much
.annotate(
owner_name=Case(
When(owner__nick_name=None, then=without_nickname),
default=with_nickname,
)
)
)
lanes = GalaxyLane.objects.filter(star1__galaxy=self).annotate(
star1_owner=F("star1__owner__id"),
star2_owner=F("star2__owner__id"),
lanes = (
GalaxyLane.objects.filter(star1__galaxy=self)
.order_by(
"star1"
) # This helps determinism for the tests and doesn't cost much
.annotate(
star1_owner=F("star1__owner__id"),
star2_owner=F("star2__owner__id"),
)
)
json = GalaxyDict(
nodes=[