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V2 upgrades, reputation, hourly price
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@cryptobench
cryptobench committed Feb 24, 2024
1 parent 9aceaef commit bda800e
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Showing 5 changed files with 124 additions and 152 deletions.
23 changes: 23 additions & 0 deletions stats-backend/api2/migrations/0015_offer_hourly_price_glm_offer_hourly_price_usd.py
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@@ -0,0 +1,23 @@
# Generated by Django 4.1.7 on 2024-02-23 22:31

from django.db import migrations, models


class Migration(migrations.Migration):

dependencies = [
('api2', '0014_node_uptime_created_at'),
]

operations = [
migrations.AddField(
model_name='offer',
name='hourly_price_glm',
field=models.FloatField(blank=True, null=True),
),
migrations.AddField(
model_name='offer',
name='hourly_price_usd',
field=models.FloatField(blank=True, null=True),
),
]
2 changes: 2 additions & 0 deletions stats-backend/api2/models.py
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Expand Up @@ -36,6 +36,8 @@ class Offer(models.Model):
created_at = models.DateTimeField(auto_now_add=True)
monthly_price_glm = models.FloatField(null=True, blank=True)
monthly_price_usd = models.FloatField(null=True, blank=True)
hourly_price_glm = models.FloatField(null=True, blank=True)
hourly_price_usd = models.FloatField(null=True, blank=True)
is_overpriced = models.BooleanField(default=False)
overpriced_compared_to = models.ForeignKey(
EC2Instance, on_delete=models.CASCADE, null=True
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214 changes: 66 additions & 148 deletions stats-backend/api2/scanner.py
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Expand Up @@ -28,171 +28,89 @@ def update_providers_info(node_props):
now = timezone.now()
days_in_current_month = calendar.monthrange(now.year, now.month)[1]
seconds_current_month = days_in_current_month * 24 * 60 * 60
hours_in_current_month = days_in_current_month * 24
glm_usd_value = GLM.objects.get(id=1)
print(f"Updating {len(node_props)} providers")
for prop in node_props:
data = json.loads(prop)
provider_id = data["node_id"]
wallet = data["wallet"]
unique_providers.add(provider_id) # Add provider to the set
obj, created = Node.objects.get_or_create(node_id=provider_id)
if created:
print(f"Created new provider: {prop}")
offerobj = Offer.objects.create(
properties=data, provider=obj, runtime=data["golem.runtime.name"]
)
if data["golem.runtime.name"] == "vm":
vectors = {}
for key, value in enumerate(data["golem.com.usage.vector"]):
vectors[value] = key
monthly_pricing = (
(
data["golem.com.pricing.model.linear.coeffs"][
vectors["golem.usage.duration_sec"]
]
* seconds_current_month
)
+ (
data["golem.com.pricing.model.linear.coeffs"][
vectors["golem.usage.cpu_sec"]
]
* seconds_current_month
* data["golem.inf.cpu.threads"]
)
+ data["golem.com.pricing.model.linear.coeffs"][-1]
offerobj, offercreated = Offer.objects.get_or_create(
provider=obj, runtime=data["golem.runtime.name"]
)
if data["golem.runtime.name"] == "vm":
vectors = {}
for key, value in enumerate(data["golem.com.usage.vector"]):
vectors[value] = key
monthly_pricing = (
(
data["golem.com.pricing.model.linear.coeffs"][
vectors["golem.usage.duration_sec"]
]
* seconds_current_month
)
if not monthly_pricing:
print(f"Monthly price is {monthly_pricing}")
offerobj.monthly_price_glm = monthly_pricing
offerobj.monthly_price_usd = (
monthly_pricing * glm_usd_value.current_price
+ (
data["golem.com.pricing.model.linear.coeffs"][
vectors["golem.usage.cpu_sec"]
]
* seconds_current_month
* data["golem.inf.cpu.threads"]
)
vcpu_needed = data.get("golem.inf.cpu.threads", 0)
memory_needed = data.get("golem.inf.mem.gib", 0.0)
closest_ec2 = (
EC2Instance.objects.annotate(
cpu_diff=Abs(F("vcpu") - vcpu_needed),
memory_diff=Abs(F("memory") - memory_needed),
)
.order_by("cpu_diff", "memory_diff", "price_usd")
.first()
+ data["golem.com.pricing.model.linear.coeffs"][-1]
)
if not monthly_pricing:
print(f"Monthly price is {monthly_pricing}")
offerobj.monthly_price_glm = monthly_pricing
offerobj.monthly_price_usd = monthly_pricing * glm_usd_value.current_price
offerobj.hourly_price_glm = monthly_pricing / hours_in_current_month
offerobj.hourly_price_usd = (
offerobj.monthly_price_usd / hours_in_current_month
)
vcpu_needed = data.get("golem.inf.cpu.threads", 0)
memory_needed = data.get("golem.inf.mem.gib", 0.0)
closest_ec2 = (
EC2Instance.objects.annotate(
cpu_diff=Abs(F("vcpu") - vcpu_needed),
memory_diff=Abs(F("memory") - memory_needed),
)
.order_by("cpu_diff", "memory_diff", "price_usd")
.first()
)

# Compare and update the Offer object
if closest_ec2 and monthly_pricing:
offer_price_usd = monthly_pricing * glm_usd_value.current_price
ec2_monthly_price = closest_ec2.price_usd * 730

offer_is_more_expensive = offer_price_usd > ec2_monthly_price
offer_is_cheaper = offer_price_usd < ec2_monthly_price

# Update Offer object fields for expensive comparison
offerobj.is_overpriced = offer_is_more_expensive
offerobj.overpriced_compared_to = (
closest_ec2 if offer_is_more_expensive else None
)
offerobj.times_more_expensive = (
offer_price_usd / float(ec2_monthly_price)
if offer_is_more_expensive
else None
)

# Update Offer object fields for cheaper comparison
offerobj.cheaper_than = closest_ec2 if offer_is_cheaper else None
offerobj.times_cheaper = (
float(ec2_monthly_price) / offer_price_usd
if offer_is_cheaper
else None
)

else:
# print(
# "No matching EC2Instance found or monthly pricing is not available."
# )
offerobj.is_overpriced = False
offerobj.overpriced_compared_to = None
offerobj.save()
obj.wallet = wallet
# Verify each node's status
is_online = check_node_status(obj.node_id)
# Compare and update the Offer object
if closest_ec2 and monthly_pricing:
offer_price_usd = monthly_pricing * glm_usd_value.current_price
ec2_monthly_price = closest_ec2.price_usd * 730

obj.online = is_online
obj.save()
else:
offerobj, offercreated = Offer.objects.get_or_create(
provider=obj, runtime=data["golem.runtime.name"]
)
if data["golem.runtime.name"] == "vm":
vectors = {}
for key, value in enumerate(data["golem.com.usage.vector"]):
vectors[value] = key
monthly_pricing = (
(
data["golem.com.pricing.model.linear.coeffs"][
vectors["golem.usage.duration_sec"]
]
* seconds_current_month
)
+ (
data["golem.com.pricing.model.linear.coeffs"][
vectors["golem.usage.cpu_sec"]
]
* seconds_current_month
* data["golem.inf.cpu.threads"]
)
+ data["golem.com.pricing.model.linear.coeffs"][-1]
offer_is_more_expensive = offer_price_usd > ec2_monthly_price
offer_is_cheaper = offer_price_usd < ec2_monthly_price

# Update Offer object fields for expensive comparison
offerobj.is_overpriced = offer_is_more_expensive
offerobj.overpriced_compared_to = (
closest_ec2 if offer_is_more_expensive else None
)
if not monthly_pricing:
print(f"Monthly price is {monthly_pricing}")
offerobj.monthly_price_glm = monthly_pricing
offerobj.monthly_price_usd = (
monthly_pricing * glm_usd_value.current_price
offerobj.times_more_expensive = (
offer_price_usd / float(ec2_monthly_price)
if offer_is_more_expensive
else None
)

vcpu_needed = data.get("golem.inf.cpu.threads", 0)
memory_needed = data.get("golem.inf.mem.gib", 0.0)
closest_ec2 = (
EC2Instance.objects.annotate(
cpu_diff=Abs(F("vcpu") - vcpu_needed),
memory_diff=Abs(F("memory") - memory_needed),
)
.order_by("cpu_diff", "memory_diff", "price_usd")
.first()
# Update Offer object fields for cheaper comparison
offerobj.cheaper_than = closest_ec2 if offer_is_cheaper else None
offerobj.times_cheaper = (
float(ec2_monthly_price) / offer_price_usd
if offer_is_cheaper
else None
)

# Compare and update the Offer object
if closest_ec2 and monthly_pricing:
offer_price_usd = monthly_pricing * glm_usd_value.current_price
ec2_monthly_price = closest_ec2.price_usd * 730

offer_is_more_expensive = offer_price_usd > ec2_monthly_price
offer_is_cheaper = offer_price_usd < ec2_monthly_price

# Update Offer object fields for expensive comparison
offerobj.is_overpriced = offer_is_more_expensive
offerobj.overpriced_compared_to = (
closest_ec2 if offer_is_more_expensive else None
)
offerobj.times_more_expensive = (
offer_price_usd / float(ec2_monthly_price)
if offer_is_more_expensive
else None
)

# Update Offer object fields for cheaper comparison
offerobj.cheaper_than = closest_ec2 if offer_is_cheaper else None
offerobj.times_cheaper = (
float(ec2_monthly_price) / offer_price_usd
if offer_is_cheaper
else None
)

else:
# print(
# "No matching EC2Instance found or monthly pricing is not available."
# )
offerobj.is_overpriced = False
offerobj.overpriced_compared_to = None
else:
# print(
# "No matching EC2Instance found or monthly pricing is not available."
# )
offerobj.is_overpriced = False
offerobj.overpriced_compared_to = None

offerobj.properties = data
offerobj.save()
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2 changes: 2 additions & 0 deletions stats-backend/api2/serializers.py
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Expand Up @@ -23,6 +23,8 @@ class Meta:
"properties",
"updated_at",
"monthly_price_usd",
"hourly_price_usd",
"hourly_price_glm",
"is_overpriced",
"overpriced_compared_to",
"suggest_env_per_hour_price",
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35 changes: 31 additions & 4 deletions stats-backend/api2/tasks.py
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Expand Up @@ -30,11 +30,38 @@

@app.task
def v2_network_online_to_redis():
data = Node.objects.filter(online=True)
serializer = NodeSerializer(data, many=True)
test = json.dumps(serializer.data, default=str)
# Fetch and process data from the external domain
response = requests.get(
"https://reputation.dev-test.golem.network/v1/providers/scores"
)
if response.status_code == 200:
external_data = response.json()
success_rate_mapping = {
provider["providerId"]: provider["scores"]["successRate"]
for provider in external_data["providers"]
}

# Fetch your existing nodes
data = Node.objects.filter(online=True)
serializer = NodeSerializer(data, many=True)
serialized_data = serializer.data

r.set("v2_online", test)
# Attach successRate to each node if the providerId matches
for node in serialized_data:
node_id = node["node_id"]
if node_id in success_rate_mapping:
node["taskReputation"] = success_rate_mapping[node_id]
else:
node["taskReputation"] = None

# Serialize and save to Redis
test = json.dumps(serialized_data, default=str)
r.set("v2_online", test)
else:
print(
"Failed to retrieve data from the reputation system!", response.status_code
)
pass


@app.task
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