gendesign/backend/app/services/objective_etl.py
bot-backend 14f3ef2019
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fix(week-review): backend-аудит v2 — 82 фиксов (#1660)
Co-authored-by: bot-backend <bot-backend@gendsgn.local>
Co-committed-by: bot-backend <bot-backend@gendsgn.local>
2026-06-17 17:13:38 +00:00

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"""ETL: SQLite Антона (/sf/) → наша PG (objective_* таблицы).
Reusable библиотека вокруг логики `data/sql/71_etl_anton_sqlite_to_pg.py`.
Используется Celery-task `tasks.objective_etl.import_anton_objective` и
admin-endpoint `POST /api/v1/admin/scrape/objective`.
Файл-источник по умолчанию: settings.objective_anton_sqlite_path
(на проде смонтирован bind-mount-ом docker-compose из /opt/gendesign/site-finder).
Стратегия:
- lots: INSERT … ON CONFLICT (objective_lot_id) DO UPDATE
- crm: INSERT … ON CONFLICT (report_month, group_name, project_name,
corpus_name, room_bucket) DO UPDATE
- mapping: дедупликация по (objective_complex_name, objective_group),
потом INSERT … ON CONFLICT DO UPDATE
Heartbeat / прогресс (для UI) выставляется через callback `progress_cb`,
который Celery-task передаёт со UPDATE objective_scrape_runs.
"""
from __future__ import annotations
import logging
import re
import sqlite3
from collections.abc import Callable
from contextlib import closing
from datetime import date
from pathlib import Path
from typing import Any
import psycopg
logger = logging.getLogger(__name__)
def _bulk_upsert(cur: psycopg.Cursor, sql_template: str, rows: list[tuple]) -> None:
"""Эмулирует psycopg2.extras.execute_values для psycopg v3.
`sql_template` должен содержать литеральное `VALUES %s` — заменим
на `VALUES (%s, %s, ..., %s)` с числом placeholder'ов = len(rows[0])
и пошлём через executemany. В psycopg3 executemany использует
pipeline-mode, так что overhead на сетевые round-trips минимален.
"""
if not rows:
return
n_cols = len(rows[0])
values_placeholder = "(" + ",".join(["%s"] * n_cols) + ")"
sql = sql_template.replace("VALUES %s", "VALUES " + values_placeholder)
cur.executemany(sql, rows)
GROUP_NAME = "Екатеринбург" # У Антона в SQLite нет колонки group_name
# ── helpers ─────────────────────────────────────────────────────────────────
def _parse_date(s) -> date | None:
if s is None or s == "":
return None
try:
return date.fromisoformat(str(s)[:10])
except (ValueError, TypeError):
return None
def _parse_month_to_first_day(s) -> date | None:
if not s:
return None
try:
y, m = str(s).split("-")
return date(int(y), int(m), 1)
except (ValueError, TypeError):
return None
def _normalize_rooms(s) -> int | None:
if not s:
return None
sl = str(s).strip().lower()
if "студ" in sl:
return 0
m = re.match(r"^(\d+)", sl)
if m:
return min(int(m.group(1)), 5)
return None
def _bool_from_yes(v) -> bool | None:
if v is None or v == "":
return None
s = str(v).strip().lower()
if s in ("да", "true", "1", "yes"):
return True
if s in ("нет", "false", "0", "no"):
return False
return None
def _site_id_to_obj_id(s) -> int | None:
"""'jk:49854' → 49854. 'parcel:...' → None."""
if not s:
return None
s = str(s)
if s.startswith("jk:"):
try:
return int(s[3:])
except ValueError:
return None
return None
def _to_int(v) -> int | None:
if v is None or v == "":
return None
try:
return int(v)
except (TypeError, ValueError):
return None
def _to_num(v) -> float | None:
if v is None or v == "":
return None
try:
return float(v)
except (TypeError, ValueError):
return None
# ── row mappings ────────────────────────────────────────────────────────────
def _row_to_lot(r: sqlite3.Row, snapshot_date: date) -> tuple:
return (
r["lot_id"],
r["project_id"],
r["project"],
r["developer"],
r["city"],
r["district"],
r["corpus"],
r["address"],
r["obj_class"],
r["section"],
_to_int(r["floor"]),
r["lot_num"],
r["room_kind"],
_parse_date(r["sales_start"]),
_parse_date(r["plan_date"]),
_parse_date(r["fact_date"]),
_to_int(r["readiness_pct"]),
r["construction_stage"],
r["finish_type"],
r["status"],
_bool_from_yes(r["sold"]),
r["rooms_dev"],
r["rooms_pd"],
r["rooms_obj"],
_normalize_rooms(r["rooms_obj"]),
_to_num(r["area_dev"]),
_to_num(r["area_pd"]),
_to_num(r["budget_rub"]),
_to_num(r["price_per_m2"]),
_to_num(r["offer_price"]),
_to_num(r["delta_price_rub"]),
_to_num(r["delta_price_pct"]),
r["price_method"],
_parse_date(r["price_set_date"]),
_parse_date(r["price_actual_date"]),
_parse_date(r["contract_date"]),
_parse_date(r["register_date"]),
r["deal_type"],
r["buyer_type"],
r["register_num"],
r["encumbrance"],
r["bank"],
_parse_date(r["encumbrance_start"]),
_parse_date(r["egrn_actual_date"]),
snapshot_date,
)
_LOT_INSERT = """
INSERT INTO objective_lots (
objective_lot_id, objective_project_id, project_name, developer, city,
district, corpus_name, address, class, section, floor, lot_number,
premise_kind, sales_start_date, plan_completion_date, actual_completion_date,
readiness_pct, construction_stage, finishing, status, is_sold,
rooms_dev_site, rooms_pd, rooms_objective, rooms_int,
area_dev_site, area_pd,
price_calculated_total_rub, price_per_m2_rub, price_offer_total_rub,
price_delta_rub, price_delta_pct, pricing_method, price_set_date,
price_actual_date, contract_date, registration_date, contract_type,
buyer_type, registration_number, encumbrance_type, bank_name,
encumbrance_start_date, egrn_actual_date, snapshot_date
) VALUES %s
ON CONFLICT (objective_lot_id) DO UPDATE SET
project_name = EXCLUDED.project_name,
developer = EXCLUDED.developer, district = EXCLUDED.district,
corpus_name = EXCLUDED.corpus_name, address = EXCLUDED.address,
class = EXCLUDED.class, section = EXCLUDED.section, floor = EXCLUDED.floor,
lot_number = EXCLUDED.lot_number, premise_kind = EXCLUDED.premise_kind,
sales_start_date = EXCLUDED.sales_start_date,
plan_completion_date = EXCLUDED.plan_completion_date,
actual_completion_date = EXCLUDED.actual_completion_date,
readiness_pct = EXCLUDED.readiness_pct,
construction_stage = EXCLUDED.construction_stage,
finishing = EXCLUDED.finishing,
status = EXCLUDED.status, is_sold = EXCLUDED.is_sold,
rooms_dev_site = EXCLUDED.rooms_dev_site,
rooms_pd = EXCLUDED.rooms_pd,
rooms_objective = EXCLUDED.rooms_objective,
rooms_int = EXCLUDED.rooms_int,
area_dev_site = EXCLUDED.area_dev_site, area_pd = EXCLUDED.area_pd,
price_calculated_total_rub = EXCLUDED.price_calculated_total_rub,
price_per_m2_rub = EXCLUDED.price_per_m2_rub,
price_offer_total_rub = EXCLUDED.price_offer_total_rub,
price_delta_rub = EXCLUDED.price_delta_rub,
price_delta_pct = EXCLUDED.price_delta_pct,
pricing_method = EXCLUDED.pricing_method,
price_set_date = EXCLUDED.price_set_date,
price_actual_date = EXCLUDED.price_actual_date,
contract_date = EXCLUDED.contract_date,
registration_date = EXCLUDED.registration_date,
contract_type = EXCLUDED.contract_type, buyer_type = EXCLUDED.buyer_type,
registration_number = EXCLUDED.registration_number,
encumbrance_type = EXCLUDED.encumbrance_type,
bank_name = EXCLUDED.bank_name,
encumbrance_start_date = EXCLUDED.encumbrance_start_date,
egrn_actual_date = EXCLUDED.egrn_actual_date,
snapshot_date = EXCLUDED.snapshot_date,
updated_at = NOW()
"""
def _row_to_crm(r: sqlite3.Row) -> tuple:
return (
_parse_month_to_first_day(r["month"]),
GROUP_NAME,
r["project"],
r["developer"],
r["district"],
r["obj_class"],
r["corpus"],
r["rooms_bucket"],
_normalize_rooms(r["rooms_bucket"]),
_parse_date(r["sales_start"]),
_parse_date(r["plan_date"]),
_parse_date(r["fact_date"]),
_to_int(r["months_in_sales"]),
_to_int(r["lots_pd"]),
_to_num(r["area_pd"]),
# ДДУ — у Антона нет
None,
None,
None,
None,
None,
None,
None,
# ДКП
None,
None,
None,
None,
None,
None,
None,
# Всего
_to_int(r["deals_total"]),
_to_int(r["deals_priced"]),
_to_num(r["sold_volume_m2"]),
_to_num(r["sold_volume_m2"]),
None,
_to_num(r["avg_price_m2"]),
_to_num(r["avg_area_m2"]),
# Offer
_to_int(r["stock_lots"]),
_to_num(r["stock_m2"]),
None,
_to_num(r["stock_avg_price_m2"]),
)
_CRM_INSERT = """
INSERT INTO objective_corpus_room_month (
report_month, group_name, project_name, developer, district, class,
corpus_name, room_bucket, rooms_int,
sales_start_date, plan_completion_date, actual_completion_date,
months_in_realization, lots_pd_count, lots_pd_area,
deals_ddu_count, deals_ddu_count_priced, deals_ddu_vol_m2,
deals_ddu_vol_m2_priced, deals_ddu_sum_mln_rub,
deals_ddu_avg_price_thousand_rub_per_m2, deals_ddu_avg_area_m2,
deals_dkp_count, deals_dkp_count_priced, deals_dkp_vol_m2,
deals_dkp_vol_m2_priced, deals_dkp_sum_mln_rub,
deals_dkp_avg_price_thousand_rub_per_m2, deals_dkp_avg_area_m2,
deals_total_count, deals_total_count_priced, deals_total_vol_m2,
deals_total_vol_m2_priced, deals_total_sum_mln_rub,
deals_total_avg_price_thousand_rub_per_m2, deals_total_avg_area_m2,
offer_count, offer_area_m2, offer_sum_mln_rub,
offer_avg_price_thousand_rub_per_m2
) VALUES %s
ON CONFLICT (report_month, group_name, project_name, corpus_name, room_bucket)
DO UPDATE SET
developer = EXCLUDED.developer, district = EXCLUDED.district,
class = EXCLUDED.class, rooms_int = EXCLUDED.rooms_int,
sales_start_date = EXCLUDED.sales_start_date,
plan_completion_date = EXCLUDED.plan_completion_date,
actual_completion_date = EXCLUDED.actual_completion_date,
months_in_realization = EXCLUDED.months_in_realization,
lots_pd_count = EXCLUDED.lots_pd_count,
lots_pd_area = EXCLUDED.lots_pd_area,
deals_total_count = EXCLUDED.deals_total_count,
deals_total_count_priced = EXCLUDED.deals_total_count_priced,
deals_total_vol_m2 = EXCLUDED.deals_total_vol_m2,
deals_total_vol_m2_priced = EXCLUDED.deals_total_vol_m2_priced,
deals_total_avg_price_thousand_rub_per_m2 = EXCLUDED.deals_total_avg_price_thousand_rub_per_m2,
deals_total_avg_area_m2 = EXCLUDED.deals_total_avg_area_m2,
offer_count = EXCLUDED.offer_count,
offer_area_m2 = EXCLUDED.offer_area_m2,
offer_avg_price_thousand_rub_per_m2 = EXCLUDED.offer_avg_price_thousand_rub_per_m2,
fetched_at = NOW()
"""
def _row_to_mapping(r: sqlite3.Row) -> tuple | None:
obj_id = _site_id_to_obj_id(r["site_id"])
if obj_id is None:
return None
return (
r["project"],
None,
GROUP_NAME,
obj_id,
False,
r["method"],
_to_num(r["score"]),
"imported_from_anton_sf",
)
_MAP_INSERT = """
INSERT INTO objective_complex_mapping (
objective_complex_name, objective_project_id, objective_group,
domrf_obj_id, is_reviewed, match_method, match_score, note
) VALUES %s
ON CONFLICT (objective_complex_name, objective_group) DO UPDATE SET
domrf_obj_id = EXCLUDED.domrf_obj_id,
match_method = EXCLUDED.match_method,
match_score = EXCLUDED.match_score,
note = EXCLUDED.note,
updated_at = NOW()
"""
# ── orchestration ───────────────────────────────────────────────────────────
def _etl_lots(
sl: sqlite3.Connection, pg, batch_size: int, progress_cb: Callable[[int], None] | None
) -> int:
snap = date.today()
cur = sl.execute("SELECT * FROM objective_lots")
n = 0
batch: list[tuple] = []
pg_cur = pg.cursor()
while True:
rows = cur.fetchmany(batch_size)
if not rows:
break
for r in rows:
batch.append(_row_to_lot(r, snap))
if len(batch) >= batch_size:
_bulk_upsert(pg_cur, _LOT_INSERT, batch)
pg.commit()
n += len(batch)
batch.clear()
if progress_cb and n % (batch_size * 5) == 0:
progress_cb(n)
if batch:
_bulk_upsert(pg_cur, _LOT_INSERT, batch)
pg.commit()
n += len(batch)
pg_cur.close()
if progress_cb:
progress_cb(n)
return n
def _etl_crm(
sl: sqlite3.Connection, pg, batch_size: int, progress_cb: Callable[[int], None] | None
) -> tuple[int, int]:
cur = sl.execute("SELECT * FROM objective_corp_month")
n = 0
skipped = 0
batch: list[tuple] = []
pg_cur = pg.cursor()
while True:
rows = cur.fetchmany(batch_size)
if not rows:
break
for r in rows:
t = _row_to_crm(r)
if not t[0] or not t[2] or not t[6] or not t[7]:
skipped += 1
continue
batch.append(t)
if len(batch) >= batch_size:
_bulk_upsert(pg_cur, _CRM_INSERT, batch)
pg.commit()
n += len(batch)
batch.clear()
if batch:
_bulk_upsert(pg_cur, _CRM_INSERT, batch)
pg.commit()
n += len(batch)
pg_cur.close()
if progress_cb:
progress_cb(n)
return n, skipped
def _etl_mapping(sl: sqlite3.Connection, pg) -> tuple[int, int]:
cur = sl.execute("SELECT * FROM jk_objective_match ORDER BY score DESC NULLS LAST")
rows = cur.fetchall()
seen: set[tuple] = set()
batch: list[tuple] = []
skipped_dups = 0
for r in rows:
t = _row_to_mapping(r)
if t is None:
continue
key = (t[0], t[2]) # (complex_name, group)
if key in seen:
skipped_dups += 1
continue
seen.add(key)
batch.append(t)
if not batch:
return 0, skipped_dups
pg_cur = pg.cursor()
_bulk_upsert(pg_cur, _MAP_INSERT, batch)
pg.commit()
pg_cur.close()
return len(batch), skipped_dups
# ── public API ──────────────────────────────────────────────────────────────
def get_sqlite_info(sqlite_path: str | Path) -> dict[str, Any]:
"""Метаданные SQLite-файла без полного запуска ETL.
Используется в admin-coverage endpoint чтобы UI знал свежесть данных,
размер файла и сколько потенциально rows будет залито.
"""
p = Path(sqlite_path)
info: dict[str, Any] = {
"path": str(p),
"exists": p.exists(),
}
if not p.exists():
return info
st = p.stat()
info["size_bytes"] = st.st_size
info["modified_at"] = st.st_mtime # epoch seconds
try:
with closing(sqlite3.connect(p)) as c:
info["lots"] = c.execute("SELECT COUNT(*) FROM objective_lots").fetchone()[0]
info["corp_room_month"] = c.execute(
"SELECT COUNT(*) FROM objective_corp_month"
).fetchone()[0]
info["mappings"] = c.execute("SELECT COUNT(*) FROM jk_objective_match").fetchone()[0]
except sqlite3.Error as e:
info["error"] = str(e)
return info
def run_etl(
sqlite_path: str | Path,
db_url: str,
*,
batch_size: int = 2000,
progress_cb: Callable[[str, int], None] | None = None,
) -> dict[str, int]:
"""Полный ETL: SQLite → PG.
Args:
sqlite_path: путь к analysis.db (на проде — bind-mount /data/anton-sqlite/...)
db_url: postgresql://… connection string
batch_size: размер batch для execute_values (default 2000)
progress_cb: optional callback(stage: str, n_rows: int) для UI прогресса
Returns:
dict с counts: {'lots', 'corp_room_month', 'mappings', 'crm_skipped',
'mapping_dups_skipped'}
Raises:
FileNotFoundError если SQLite не найден
psycopg.Error при ошибках БД
"""
p = Path(sqlite_path)
if not p.exists():
raise FileNotFoundError(f"SQLite не найден: {p}")
logger.info("ETL Anton SQLite → PG: %s", p)
sl = sqlite3.connect(p)
sl.row_factory = sqlite3.Row
pg = psycopg.connect(db_url)
try:
if progress_cb:
progress_cb("mapping_start", 0)
n_map, dups = _etl_mapping(sl, pg)
logger.info(" mapping: %d upserted, %d dups skipped", n_map, dups)
if progress_cb:
progress_cb("mapping_done", n_map)
if progress_cb:
progress_cb("crm_start", 0)
n_crm, crm_skipped = _etl_crm(
sl,
pg,
batch_size,
lambda n: progress_cb("crm_progress", n) if progress_cb else None,
)
logger.info(" crm: %d upserted, %d skipped", n_crm, crm_skipped)
if progress_cb:
progress_cb("crm_done", n_crm)
if progress_cb:
progress_cb("lots_start", 0)
n_lots = _etl_lots(
sl,
pg,
batch_size,
lambda n: progress_cb("lots_progress", n) if progress_cb else None,
)
logger.info(" lots: %d upserted", n_lots)
if progress_cb:
progress_cb("lots_done", n_lots)
finally:
sl.close()
pg.close()
return {
"lots": n_lots,
"corp_room_month": n_crm,
"mappings": n_map,
"crm_skipped": crm_skipped,
"mapping_dups_skipped": dups,
}