feat(1c): decouple company intelligence from 1c names
This commit is contained in:
igor04091968
@@ -130,18 +130,18 @@ def main() -> int:
|
||||
daily_rows = query_rows(
|
||||
client,
|
||||
"""
|
||||
SELECT infobase, organization, counterparty, d, docs_total, amount_total
|
||||
FROM analytics_1c.v_counterparty_daily
|
||||
ORDER BY infobase, counterparty, d
|
||||
SELECT infobase, organization, company_entity_key, source_counterparty, d, docs_total, amount_total
|
||||
FROM analytics_1c.v_company_activity_daily
|
||||
ORDER BY infobase, company_entity_key, d
|
||||
""",
|
||||
)
|
||||
if not daily_rows:
|
||||
print("no counterparty rows in analytics_1c.v_counterparty_daily; nothing to refresh")
|
||||
print("no company activity rows in analytics_1c.v_company_activity_daily; nothing to refresh")
|
||||
return 0
|
||||
|
||||
grouped: dict[tuple[str, str, str], list[DailyPoint]] = defaultdict(list)
|
||||
grouped: dict[tuple[str, str, str, str], list[DailyPoint]] = defaultdict(list)
|
||||
for row in daily_rows:
|
||||
key = (row["infobase"], row["organization"], row["counterparty"])
|
||||
key = (row["infobase"], row["organization"], row["company_entity_key"], row.get("source_counterparty") or row["company_entity_key"])
|
||||
grouped[key].append(
|
||||
DailyPoint(
|
||||
d=row["d"],
|
||||
@@ -151,26 +151,26 @@ def main() -> int:
|
||||
)
|
||||
|
||||
cases_map = {
|
||||
(row["infobase"], row["counterparty"]): int(row["open_cases_total"] or 0)
|
||||
(row["infobase"], row["company_entity_key"]): int(row["open_cases_total"] or 0)
|
||||
for row in query_rows(
|
||||
client,
|
||||
"""
|
||||
SELECT infobase, entity_id AS counterparty, countIf(status != 'closed') AS open_cases_total
|
||||
SELECT infobase, entity_id AS company_entity_key, countIf(status != 'closed') AS open_cases_total
|
||||
FROM analytics_1c.cases
|
||||
WHERE entity_type = 'counterparty'
|
||||
GROUP BY infobase, counterparty
|
||||
GROUP BY infobase, company_entity_key
|
||||
""",
|
||||
)
|
||||
}
|
||||
detections_map = {
|
||||
(row["infobase"], row["counterparty"]): int(row["detections_total"] or 0)
|
||||
(row["infobase"], row["company_entity_key"]): int(row["detections_total"] or 0)
|
||||
for row in query_rows(
|
||||
client,
|
||||
"""
|
||||
SELECT infobase, entity_id AS counterparty, count() AS detections_total
|
||||
SELECT infobase, entity_id AS company_entity_key, count() AS detections_total
|
||||
FROM analytics_1c.detections
|
||||
WHERE entity_type = 'counterparty' AND status != 'closed'
|
||||
GROUP BY infobase, counterparty
|
||||
GROUP BY infobase, company_entity_key
|
||||
""",
|
||||
)
|
||||
}
|
||||
@@ -205,8 +205,8 @@ def main() -> int:
|
||||
forecast_rows: list[list[Any]] = []
|
||||
signal_rows: list[list[Any]] = []
|
||||
|
||||
for (infobase, _organization, counterparty), points in grouped.items():
|
||||
if normalize_company_key(counterparty) in excluded_company_keys:
|
||||
for (infobase, _organization, company_entity_key, source_counterparty), points in grouped.items():
|
||||
if normalize_company_key(source_counterparty) in excluded_company_keys:
|
||||
continue
|
||||
points.sort(key=lambda p: p.d)
|
||||
filled = fill_daily_series(points)
|
||||
@@ -223,8 +223,8 @@ def main() -> int:
|
||||
amount_7d = float(sum(p.amount_total for p in last_7))
|
||||
amount_prev_7d = float(sum(p.amount_total for p in prev_7))
|
||||
days_since_last_activity = (date.today() - latest_day).days
|
||||
open_cases_total = cases_map.get((infobase, counterparty), 0)
|
||||
detections_total = detections_map.get((infobase, counterparty), 0)
|
||||
open_cases_total = cases_map.get((infobase, company_entity_key), 0)
|
||||
detections_total = detections_map.get((infobase, company_entity_key), 0)
|
||||
company_state = company_state_map.get(infobase, {})
|
||||
current_status = str(company_state.get("current_status") or "")
|
||||
active_locks = int(company_state.get("active_locks") or 0)
|
||||
@@ -245,7 +245,7 @@ def main() -> int:
|
||||
generated_at,
|
||||
latest_day,
|
||||
infobase,
|
||||
counterparty,
|
||||
company_entity_key,
|
||||
int(horizon),
|
||||
metric,
|
||||
float(baseline),
|
||||
@@ -261,29 +261,29 @@ def main() -> int:
|
||||
|
||||
signals: list[tuple[str, int, str, str]] = []
|
||||
if days_since_last_activity >= 14 and (docs_prev_7d > 0 or amount_prev_7d > 0):
|
||||
signals.append(("inactive_company", 85, "high", f"Нет активности по компании {counterparty} уже {days_since_last_activity} дн."))
|
||||
signals.append(("inactive_company", 85, "high", f"Нет активности по компании {source_counterparty} уже {days_since_last_activity} дн."))
|
||||
if amount_prev_7d > 0 and amount_7d < amount_prev_7d * 0.5:
|
||||
signals.append(("amount_drop", 70, "high", f"Активность по компании {counterparty} упала более чем на 50% неделя к неделе."))
|
||||
signals.append(("amount_drop", 70, "high", f"Активность по компании {source_counterparty} упала более чем на 50% неделя к неделе."))
|
||||
if docs_prev_7d > 0 and docs_7d == 0:
|
||||
signals.append(("docs_stopped", 55, "medium", f"По компании {counterparty} прекратился поток документов за последние 7 дней."))
|
||||
signals.append(("docs_stopped", 55, "medium", f"По компании {source_counterparty} прекратился поток документов за последние 7 дней."))
|
||||
if current_status == "busy" or active_locks > 0 or temp_db_present > 0:
|
||||
score = min(85, 45 + active_locks * 5 + temp_db_present * 10)
|
||||
signals.append(("base_busy", score, severity_score_to_label(score), f"Файловая база компании {counterparty} занята: status={current_status}, locks={active_locks}, tempDb={temp_db_present}."))
|
||||
signals.append(("base_busy", score, severity_score_to_label(score), f"Файловая база компании {source_counterparty} занята: status={current_status}, locks={active_locks}, tempDb={temp_db_present}."))
|
||||
if scheduler_touched > 0 and current_activity_score >= 15:
|
||||
signals.append(("scheduler_activity", 35, "medium", f"По компании {counterparty} есть активность scheduler и повышенный activity score {current_activity_score}."))
|
||||
signals.append(("scheduler_activity", 35, "medium", f"По компании {source_counterparty} есть активность scheduler и повышенный activity score {current_activity_score}."))
|
||||
if open_cases_total > 0:
|
||||
signals.append(("open_cases", min(95, 40 + open_cases_total * 10), severity_score_to_label(min(95, 40 + open_cases_total * 10)), f"По компании {counterparty} есть открытые кейсы: {open_cases_total}."))
|
||||
signals.append(("open_cases", min(95, 40 + open_cases_total * 10), severity_score_to_label(min(95, 40 + open_cases_total * 10)), f"По компании {source_counterparty} есть открытые кейсы: {open_cases_total}."))
|
||||
if detections_total > 0:
|
||||
signals.append(("open_detections", min(90, 35 + detections_total * 5), severity_score_to_label(min(90, 35 + detections_total * 5)), f"По компании {counterparty} есть активные detections: {detections_total}."))
|
||||
signals.append(("open_detections", min(90, 35 + detections_total * 5), severity_score_to_label(min(90, 35 + detections_total * 5)), f"По компании {source_counterparty} есть активные detections: {detections_total}."))
|
||||
|
||||
for signal_type, score, severity, summary in signals:
|
||||
signal_rows.append(
|
||||
[
|
||||
generated_at,
|
||||
infobase,
|
||||
counterparty,
|
||||
f"{signal_type}:{infobase}:{counterparty}",
|
||||
severity,
|
||||
[
|
||||
generated_at,
|
||||
infobase,
|
||||
company_entity_key,
|
||||
f"{signal_type}:{infobase}:{company_entity_key}",
|
||||
severity,
|
||||
int(score),
|
||||
signal_type,
|
||||
summary,
|
||||
|
||||
Reference in New Issue
Block a user