OSVauco/ml/billing_agent.py

195 lines
8.2 KiB
Python

import os
import datetime
from google.cloud import bigquery
class BillingAgent:
def __init__(self):
self.project_id = os.environ.get("GOOGLE_CLOUD_PROJECT")
if not self.project_id:
raise ValueError("GOOGLE_CLOUD_PROJECT environment variable not set.")
self.billing_table = os.environ.get("BILLING_TABLE")
if not self.billing_table:
raise ValueError("BILLING_TABLE environment variable not set.")
self.bq_client = bigquery.Client(project=self.project_id)
# ── summary ──────────────────────────────────────────────────────────────
def get_summary(self):
query = f"""
SELECT
DATE(usage_start_time) AS usage_date,
project.id AS project_id,
service.description AS service,
SUM(cost) AS daily_cost
FROM `{self.billing_table}`
WHERE _PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 30 DAY)
GROUP BY usage_date, project_id, service
ORDER BY usage_date DESC, daily_cost DESC
LIMIT 100
"""
results = self.bq_client.query(query).result()
summary = [
{
"usage_date": str(row.usage_date),
"project_id": row.project_id,
"service": row.service,
"daily_cost": row.daily_cost,
}
for row in results
]
if not summary:
return {
"onboarding_status": {
"state": "awaiting_data",
"message": "Fakturaeksport er aktiv, men ingen data for siste 30 dager ennå.",
}
}
return {"summary": summary}
# ── forecast ─────────────────────────────────────────────────────────────
def get_forecast(self):
q7 = f"""
SELECT SUM(cost) + SUM(IFNULL(
(SELECT SUM(c.amount) FROM UNNEST(credits) c), 0)) AS total_cost
FROM `{self.billing_table}`
WHERE _PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY)
"""
total_7d = list(self.bq_client.query(q7).result())[0].total_cost or 0
daily_average = total_7d / 7
today = datetime.date.today()
next_month = datetime.date(
today.year + (1 if today.month == 12 else 0),
(today.month % 12) + 1, 1
)
remaining_days = (next_month - today).days
q_mtd = f"""
SELECT SUM(cost) + SUM(IFNULL(
(SELECT SUM(c.amount) FROM UNNEST(credits) c), 0)) AS total_cost
FROM `{self.billing_table}`
WHERE EXTRACT(MONTH FROM _PARTITIONTIME) = EXTRACT(MONTH FROM CURRENT_DATE())
AND EXTRACT(YEAR FROM _PARTITIONTIME) = EXTRACT(YEAR FROM CURRENT_DATE())
"""
mtd_cost = list(self.bq_client.query(q_mtd).result())[0].total_cost or 0
return {
"daily_average_last_7_days": daily_average,
"month_to_date_cost": mtd_cost,
"forecasted_remaining_cost": daily_average * remaining_days,
"total_monthly_forecast": mtd_cost + daily_average * remaining_days,
"remaining_days_in_month": remaining_days,
"data_note": "Prognose basert på siste 7 dager. BigQuery kan ha 24-48 timers forsinkelse.",
}
# ── anomalier ─────────────────────────────────────────────────────────────
def get_anomalies(self):
query = f"""
WITH daily_costs AS (
SELECT
service.description AS service,
DATE(_PARTITIONTIME) AS usage_date,
SUM(cost) + SUM(IFNULL(
(SELECT SUM(c.amount) FROM UNNEST(credits) c), 0)) AS daily_cost
FROM `{self.billing_table}`
WHERE _PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 14 DAY)
GROUP BY 1, 2
),
costs_with_avg AS (
SELECT
service, usage_date, daily_cost,
AVG(daily_cost) OVER (
PARTITION BY service ORDER BY usage_date
ROWS BETWEEN 7 PRECEDING AND 1 PRECEDING
) AS avg_7day
FROM daily_costs
)
SELECT service, daily_cost AS today_cost, avg_7day,
(daily_cost / avg_7day) AS ratio
FROM costs_with_avg
WHERE usage_date = CURRENT_DATE()
AND avg_7day > 0
AND daily_cost > (2.0 * avg_7day)
"""
results = self.bq_client.query(query).result()
return {
"anomalies": [
{
"service": row.service,
"today_cost": row.today_cost,
"avg_7d": row.avg_7day,
"ratio": row.ratio,
}
for row in results
]
}
# ── daglig historikk for bar-chart (CG6) ──────────────────────────────────
def get_daily_history(self, days: int = 30):
"""
Returnerer [{date: str, mtd: float}] for siste `days` dager, sortert ASC.
MTD (month-to-date) er kumulativ sum fra 1. i måneden til den dato.
"""
query = f"""
SELECT
DATE(usage_start_time) AS usage_date,
SUM(cost) + SUM(IFNULL(
(SELECT SUM(c.amount) FROM UNNEST(credits) c), 0)) AS day_cost
FROM `{self.billing_table}`
WHERE _PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(),
INTERVAL {int(days)} DAY)
GROUP BY usage_date
ORDER BY usage_date ASC
"""
results = list(self.bq_client.query(query).result())
history = []
mtd = 0.0
for row in results:
# Nullstill MTD ved månedsskifte
if history and row.usage_date.day == 1:
mtd = 0.0
mtd += float(row.day_cost or 0)
history.append({"date": str(row.usage_date), "mtd": round(mtd, 6)})
return history
# ── tjenester med SKU-detaljer (CG5) ─────────────────────────────────────
def get_service_totals(self, days: int = 30):
query = f"""
SELECT
service.description AS service,
sku.description AS sku,
SUM(cost) + SUM(IFNULL(
(SELECT SUM(c.amount) FROM UNNEST(credits) c), 0)) AS sku_cost
FROM `{self.billing_table}`
WHERE _PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(),
INTERVAL {int(days)} DAY)
GROUP BY service, sku
HAVING sku_cost > 0
ORDER BY service, sku_cost DESC
"""
results = self.bq_client.query(query).result()
services: dict = {}
for row in results:
svc = row.service
if svc not in services:
services[svc] = {"service": svc, "total_cost": 0.0, "skus": []}
services[svc]["total_cost"] = round(
services[svc]["total_cost"] + float(row.sku_cost), 6
)
services[svc]["skus"].append({
"sku": row.sku,
"sku_cost": round(float(row.sku_cost), 6),
})
return sorted(services.values(), key=lambda x: x["total_cost"], reverse=True)
if __name__ == '__main__':
agent = BillingAgent()
print("Summary:", agent.get_summary())
print("Forecast:", agent.get_forecast())
print("Anomalies:", agent.get_anomalies())
print("By-service:", agent.get_service_totals())
print("History:", agent.get_daily_history())