merge: resolve main.py conflict (keep landing + pilot + users routers)
This commit is contained in:
lekss361
commit
53598cc874
10 changed files with 1342 additions and 0 deletions
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@ -30,6 +30,7 @@ from app.schemas.parcel import (
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RiskZone,
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)
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from app.services.exporters.layout_tz_pdf import render_layout_tz_pdf
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from app.services.exporters.snapshot_pdf import generate_snapshot_pdf
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from app.services.site_finder.best_layouts import get_best_layouts
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from app.services.site_finder.cadastre_fetch import (
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cad_exists_in_db,
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@ -43,6 +44,7 @@ from app.services.site_finder.custom_pois import (
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get_overlaps_for_scoring as _get_custom_poi_overlaps,
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)
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from app.services.site_finder.gate_verdict import compute_gate_verdict
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from app.services.site_finder.poi_score import PoiScoreResponse, compute_poi_weighted_top7
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from app.services.site_finder.quarter_dump_lookup import (
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get_connection_points,
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get_quarter_dump_data,
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@ -1701,6 +1703,217 @@ def analyze_parcel(
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except Exception as e:
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logger.warning("parcel_meta query failed for %s: %s", cad_num, e)
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# B5-1) EGRN block — расширенные данные из cad_parcels (SF-B5)
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egrn_block: dict[str, Any] = {}
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try:
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egrn_row = (
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db.execute(
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text("""
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SELECT cost_value AS cadastral_value_rub,
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cost_index AS cost_index_per_m2,
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land_record_category_type AS land_category,
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permitted_use_established_by_document AS permitted_use_text,
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cost_registration_date AS last_egrn_update_date,
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land_record_area AS area_m2,
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ownership_type,
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right_type,
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status,
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readable_address,
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registration_date
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FROM cad_parcels
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WHERE cad_num = CAST(:c AS text)
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LIMIT 1
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"""),
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{"c": cad_num},
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)
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.mappings()
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.first()
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)
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if egrn_row:
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_cad_val = (
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float(egrn_row["cadastral_value_rub"])
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if egrn_row["cadastral_value_rub"] is not None
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else None
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)
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_area_m2 = float(egrn_row["area_m2"]) if egrn_row["area_m2"] is not None else None
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_idx = egrn_row["cost_index_per_m2"]
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_cad_per_m2: float | None = None
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if _idx is not None:
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_cad_per_m2 = float(_idx)
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elif _cad_val is not None and _area_m2 and _area_m2 > 0:
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_cad_per_m2 = round(_cad_val / _area_m2, 2)
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egrn_block = {
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"cadastral_value_rub": _cad_val,
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"cadastral_value_per_m2": _cad_per_m2,
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"land_category": egrn_row["land_category"],
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"permitted_use_text": egrn_row["permitted_use_text"],
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"last_egrn_update_date": (
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egrn_row["last_egrn_update_date"].isoformat()
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if egrn_row["last_egrn_update_date"] is not None
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else None
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),
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"area_m2": _area_m2,
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"ownership_type": egrn_row["ownership_type"],
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"right_type": egrn_row["right_type"],
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"parcel_status": egrn_row["status"],
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"address": egrn_row["readable_address"],
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"registration_date": (
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egrn_row["registration_date"].isoformat()
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if egrn_row["registration_date"] is not None
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else None
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),
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}
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except Exception as e:
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logger.warning("egrn_block query failed for %s: %s", cad_num, e)
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# B5-2) Encumbrance block — ЗОУИТ из cad_zouit (SF-B5)
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encumbrance_block: dict[str, Any] = {
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"has_zouit": False,
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"zouit_types": [],
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"zouit_count": 0,
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}
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try:
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zouit_rows = (
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db.execute(
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text("""
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SELECT type_zone, name_by_doc
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FROM cad_zouit
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WHERE ST_Intersects(geom, ST_GeomFromText(:wkt, 4326))
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ORDER BY id
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"""),
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{"wkt": geom_wkt},
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)
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.mappings()
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.all()
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)
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if zouit_rows:
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_zouit_types = list({r["type_zone"] for r in zouit_rows if r["type_zone"]})
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encumbrance_block = {
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"has_zouit": True,
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"zouit_types": _zouit_types,
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"zouit_count": len(zouit_rows),
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}
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except Exception as e:
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logger.warning("encumbrance_block query failed for %s: %s", cad_num, e)
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# B5-3) Red lines block — пересечение с cad_red_lines (SF-B5)
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red_lines_block: dict[str, Any] = {"intersects": False, "count": 0}
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try:
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rl_row = (
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db.execute(
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text("""
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SELECT COUNT(*) AS cnt
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FROM cad_red_lines
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WHERE ST_Intersects(
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geom::geometry,
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ST_GeomFromText(:wkt, 4326)
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)
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"""),
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{"wkt": geom_wkt},
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)
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.mappings()
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.first()
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)
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if rl_row:
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_rl_cnt = int(rl_row["cnt"])
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red_lines_block = {
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"intersects": _rl_cnt > 0,
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"count": _rl_cnt,
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}
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except Exception as e:
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logger.warning("red_lines_block query failed for %s: %s", cad_num, e)
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# B5-4) Metro placeholder — заполнится после merge 22h metro scraper
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metro_block: dict[str, Any] = {"nearest_top3": None}
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# B5-5) District price ranges из objective_lots (SF-B5)
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district_price_block: dict[str, Any] = {
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"district_price_per_m2_min": None,
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"district_price_per_m2_max": None,
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"district_price_per_m2_median": None,
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"district_price_sample_size": None,
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}
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if district_row and district_row["district_name"]:
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try:
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dp_row = (
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db.execute(
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text("""
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SELECT
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MIN(price_per_m2_rub) AS price_min,
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MAX(price_per_m2_rub) AS price_max,
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PERCENTILE_CONT(0.5) WITHIN GROUP (
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ORDER BY price_per_m2_rub
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) AS price_median,
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COUNT(*) AS sample_size
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FROM objective_lots
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WHERE district = CAST(:dn AS text)
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AND price_per_m2_rub IS NOT NULL
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AND price_per_m2_rub BETWEEN 30000 AND 600000
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"""),
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{"dn": district_row["district_name"]},
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)
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.mappings()
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.first()
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)
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if dp_row and dp_row["sample_size"] and int(dp_row["sample_size"]) > 0:
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district_price_block = {
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"district_price_per_m2_min": (
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round(float(dp_row["price_min"])) if dp_row["price_min"] else None
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),
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"district_price_per_m2_max": (
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round(float(dp_row["price_max"])) if dp_row["price_max"] else None
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),
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"district_price_per_m2_median": (
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round(float(dp_row["price_median"])) if dp_row["price_median"] else None
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),
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"district_price_sample_size": int(dp_row["sample_size"]),
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}
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except Exception as e:
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logger.warning("district_price_block query failed for %s: %s", cad_num, e)
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# B5-6) Risk indicators — flood_zone из cad_risk_zones + noise_score + geology proxy (SF-B5)
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risks_block: dict[str, Any] = {
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"flood_zone": False,
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"noise_score": round(noise_score, 2),
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"geology_risk_label": None,
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}
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try:
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flood_row = (
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db.execute(
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text("""
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SELECT COUNT(*) AS cnt
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FROM cad_risk_zones
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WHERE ST_Intersects(
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geom::geometry,
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ST_GeomFromText(:wkt, 4326)
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)
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AND (risk_type ILIKE '%flood%' OR risk_type ILIKE '%подтоп%'
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OR risk_type ILIKE '%затоп%')
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"""),
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{"wkt": geom_wkt},
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)
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.mappings()
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.first()
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)
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_flood = bool(flood_row and int(flood_row["cnt"]) > 0)
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# Geology proxy через hydrology flood_risk_flag (уже посчитан выше)
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_geo_flood = hydrology.get("flood_risk_flag", False) if hydrology else False
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_has_flood = _flood or _geo_flood
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# geology_risk_label: high если flooding, medium если шум > 65дБ, иначе low
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if _has_flood:
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_geo_label: str | None = "high"
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elif noise_db_max >= 65.0:
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_geo_label = "medium"
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else:
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_geo_label = "low"
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risks_block = {
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"flood_zone": _has_flood,
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"noise_score": round(noise_score, 2),
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"geology_risk_label": _geo_label,
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}
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except Exception as e:
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logger.warning("risks_block query failed for %s: %s", cad_num, e)
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# 10) Market trend — динамика цен ДДУ в радиусе 3 км за 6 vs предыдущие 6 месяцев
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market_trend: dict[str, Any] | None = None
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try:
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@ -2299,6 +2512,16 @@ def analyze_parcel(
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},
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# #254: custom POI scoring — user-defined points (via X-Session-Id header).
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"custom_poi_score_items": custom_poi_items,
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# SF-B5: EGRN + encumbrance + red_lines + metro + district prices + risks
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"egrn": egrn_block,
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"encumbrance": encumbrance_block,
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"red_lines": red_lines_block,
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"metro": metro_block,
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"district_price_per_m2_min": district_price_block["district_price_per_m2_min"],
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"district_price_per_m2_max": district_price_block["district_price_per_m2_max"],
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"district_price_per_m2_median": district_price_block["district_price_per_m2_median"],
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"district_price_sample_size": district_price_block["district_price_sample_size"],
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"risks": risks_block,
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}
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@ -2455,6 +2678,56 @@ def get_isochrones(
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}
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@router.get(
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"/{cad_num}/poi-score",
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response_model=PoiScoreResponse,
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summary="POI weighted top-7 (B6)",
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)
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async def get_poi_score(
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cad_num: str,
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db: Annotated[Session, Depends(get_db)],
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radius_m: Annotated[int, Query(ge=100, le=5000)] = 2000,
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) -> PoiScoreResponse:
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"""Вернуть top-7 ближайших POI для участка, взвешенных по формуле:
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weight = (1 / (distance_m + 100)) * category_weight
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POI берутся из osm_poi_ekb в заданном радиусе (default 2000м).
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Отсортированы по weight DESC — наиболее значимые объекты первыми.
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"""
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# Получить координаты центроида участка из геометрических таблиц
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coord_row = (
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db.execute(
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text("""
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SELECT ST_X(ST_Centroid(g.geom)) AS lon,
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ST_Y(ST_Centroid(g.geom)) AS lat
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FROM (
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SELECT geom FROM cad_quarters_geom WHERE cad_number = :c
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UNION ALL
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SELECT geom FROM cad_buildings WHERE cad_num = :c
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UNION ALL
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SELECT geom FROM cad_parcels_geom WHERE cad_num = :c
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) g
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LIMIT 1
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"""),
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{"c": cad_num},
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)
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.mappings()
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.first()
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)
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if not coord_row:
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raise HTTPException(
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status_code=404,
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detail=f"Геометрия для {cad_num} не найдена.",
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)
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lat = float(coord_row["lat"])
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lon = float(coord_row["lon"])
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return compute_poi_weighted_top7(db, cad_num, lat, lon, radius_m=radius_m)
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@router.post("/{cad_num}/competitors", response_model=CompetitorsResponse)
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async def get_parcel_competitors(
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cad_num: str,
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@ -2532,3 +2805,189 @@ async def get_parcel_best_layouts_pdf(
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except Exception as exc:
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logger.error("best_layouts PDF endpoint failed for %s: %s", cad_num, exc)
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raise HTTPException(status_code=500, detail="Internal server error") from exc
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@router.get(
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"/{cad_num}/snapshot.pdf",
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summary="1-page PDF snapshot участка (НСПД + POI + конкуренты)",
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)
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def parcel_snapshot_pdf(
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cad_num: str,
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db: Annotated[Session, Depends(get_db)],
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) -> Response:
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"""Генерирует одностраничный PDF-снимок участка (A4).
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Содержимое:
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- Header: кадастровый номер, адрес, район, площадь
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- Block 1: 5 KPI (площадь, кадастровая стоимость, категория, ВРИ, дата обновления)
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- Block 2: Топ-7 POI по взвешенному баллу (из osm_poi_ekb, радиус 1 км)
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- Block 3: Топ-5 конкурентов (из domrf_kn_objects, радиус 3 км)
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- Footer: gendsgn.ru + дата генерации
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Не является официальной выпиской ЕГРН — только аналитические данные НСПД.
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Генерация <2 сек. Открывается в Adobe Reader / Chrome.
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"""
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# 1) Получить метаданные участка из cad_parcels
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parcel_row = (
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db.execute(
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text("""
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SELECT readable_address AS address,
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land_record_area AS area_m2,
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land_record_category_type AS land_category,
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permitted_use_established_by_document AS vri,
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cost_value AS cadastral_cost,
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updated_at AS last_update
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FROM cad_parcels
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WHERE cad_num = CAST(:c AS text)
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LIMIT 1
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"""),
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{"c": cad_num},
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)
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.mappings()
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.first()
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)
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if not parcel_row:
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raise HTTPException(
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status_code=404,
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detail=f"Участок {cad_num} не найден в БД. Используйте POST /analyze для загрузки.",
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)
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# 2) Получить геометрию (WKT) для POI / competitor queries
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geom_row = (
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db.execute(
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text("""
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SELECT ST_AsText(COALESCE(
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(SELECT geom FROM cad_parcels_geom WHERE cad_num = CAST(:c AS text) LIMIT 1),
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(SELECT geom FROM cad_parcels WHERE cad_num = CAST(:c AS text) LIMIT 1)
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)) AS wkt
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"""),
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{"c": cad_num},
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)
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.mappings()
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.first()
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)
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geom_wkt: str | None = geom_row["wkt"] if geom_row else None
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# 3) POI в радиусе 1 км (только если есть геометрия)
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poi_rows: list[dict[str, Any]] = []
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if geom_wkt:
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poi_rows = [
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dict(r)
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for r in db.execute(
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text("""
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SELECT category,
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name,
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ST_Distance(
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p.geom::geography,
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ST_Centroid(ST_GeomFromText(:wkt, 4326))::geography
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) AS distance_m
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FROM osm_poi_ekb p
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WHERE ST_DWithin(
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p.geom::geography,
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ST_Centroid(ST_GeomFromText(:wkt, 4326))::geography,
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1000
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)
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ORDER BY distance_m ASC
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LIMIT 50
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"""),
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{"wkt": geom_wkt},
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)
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.mappings()
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.all()
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]
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# 4) Конкуренты в радиусе 3 км (только если есть геометрия)
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competitor_rows: list[dict[str, Any]] = []
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if geom_wkt:
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competitor_rows = [
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dict(r)
|
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for r in db.execute(
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text("""
|
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WITH latest_obj AS (
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SELECT DISTINCT ON (obj_id) *
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FROM domrf_kn_objects
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WHERE latitude IS NOT NULL
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ORDER BY obj_id, snapshot_date DESC NULLS LAST
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)
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SELECT obj_id,
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comm_name,
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dev_name,
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obj_class,
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flat_count,
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ST_Distance(
|
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ST_SetSRID(ST_MakePoint(o.longitude, o.latitude), 4326)::geography,
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ST_Centroid(ST_GeomFromText(:wkt, 4326))::geography
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) AS distance_m
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FROM latest_obj o
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WHERE ST_DWithin(
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ST_SetSRID(ST_MakePoint(o.longitude, o.latitude), 4326)::geography,
|
||||
ST_Centroid(ST_GeomFromText(:wkt, 4326))::geography,
|
||||
3000
|
||||
)
|
||||
ORDER BY flat_count DESC NULLS LAST
|
||||
LIMIT 20
|
||||
"""),
|
||||
{"wkt": geom_wkt},
|
||||
)
|
||||
.mappings()
|
||||
.all()
|
||||
]
|
||||
|
||||
# 5) Получить district (через пересечение с ekb_districts если есть геом)
|
||||
district: str | None = None
|
||||
if geom_wkt:
|
||||
district_row = (
|
||||
db.execute(
|
||||
text("""
|
||||
SELECT d.district_name
|
||||
FROM ekb_districts d
|
||||
WHERE ST_Contains(d.geom, ST_Centroid(ST_GeomFromText(:wkt, 4326)))
|
||||
LIMIT 1
|
||||
"""),
|
||||
{"wkt": geom_wkt},
|
||||
)
|
||||
.mappings()
|
||||
.first()
|
||||
)
|
||||
if district_row:
|
||||
district = district_row["district_name"]
|
||||
|
||||
# 6) Форматировать last_update
|
||||
raw_update = parcel_row["last_update"]
|
||||
last_update_str: str | None = None
|
||||
if raw_update is not None:
|
||||
try:
|
||||
last_update_str = raw_update.strftime("%d.%m.%Y")
|
||||
except AttributeError:
|
||||
last_update_str = str(raw_update)[:10]
|
||||
|
||||
# 7) Сгенерировать PDF
|
||||
try:
|
||||
pdf_bytes = generate_snapshot_pdf(
|
||||
cad_num=cad_num,
|
||||
address=parcel_row["address"],
|
||||
district=district,
|
||||
area_m2=float(parcel_row["area_m2"]) if parcel_row["area_m2"] is not None else None,
|
||||
cadastral_cost_rub=(
|
||||
float(parcel_row["cadastral_cost"])
|
||||
if parcel_row["cadastral_cost"] is not None
|
||||
else None
|
||||
),
|
||||
land_category=parcel_row["land_category"],
|
||||
vri=parcel_row["vri"],
|
||||
last_update=last_update_str,
|
||||
poi_rows=poi_rows,
|
||||
competitor_rows=competitor_rows,
|
||||
competitors_limit=5,
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.error("snapshot PDF generation failed for %s: %s", cad_num, exc)
|
||||
raise HTTPException(status_code=500, detail="Ошибка генерации PDF") from exc
|
||||
|
||||
cad_safe = cad_num.replace(":", "-")
|
||||
return Response(
|
||||
content=pdf_bytes,
|
||||
media_type="application/pdf",
|
||||
headers={"Content-Disposition": f'attachment; filename="snapshot-{cad_safe}.pdf"'},
|
||||
)
|
||||
|
|
|
|||
74
backend/app/api/v1/pilot.py
Normal file
74
backend/app/api/v1/pilot.py
Normal file
|
|
@ -0,0 +1,74 @@
|
|||
"""Pilot request lead-gen endpoint.
|
||||
|
||||
POST /api/v1/pilot/request — принимает заявку на пилот (лид с лендинга или страницы анализа),
|
||||
сохраняет в таблицу pilot_requests.
|
||||
Telegram-уведомление — TODO (creds не настроены, см. #307 SF-B3).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import Annotated, Any, Literal
|
||||
|
||||
from fastapi import APIRouter, Depends, Request
|
||||
from pydantic import BaseModel, EmailStr, Field
|
||||
from sqlalchemy import text
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from app.core.db import get_db
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
class PilotRequestInput(BaseModel):
|
||||
name: str = Field(min_length=2, max_length=200)
|
||||
phone: str | None = Field(default=None, max_length=50)
|
||||
email: EmailStr | None = None
|
||||
company: str | None = Field(default=None, max_length=200)
|
||||
message: str | None = Field(default=None, max_length=2000)
|
||||
source: Literal["landing", "analyze_page", "other"] = "landing"
|
||||
|
||||
|
||||
@router.post("/request")
|
||||
async def create_pilot_request(
|
||||
payload: PilotRequestInput,
|
||||
request: Request,
|
||||
db: Annotated[Session, Depends(get_db)],
|
||||
) -> dict[str, Any]:
|
||||
"""Сохраняет заявку на пилот в pilot_requests."""
|
||||
user_agent = request.headers.get("user-agent")
|
||||
|
||||
row = (
|
||||
db.execute(
|
||||
text(
|
||||
"""
|
||||
INSERT INTO pilot_requests (name, phone, email, company, message, source, user_agent)
|
||||
VALUES (:name, :phone, :email, :company, :message, :source, :user_agent)
|
||||
RETURNING CAST(id AS text), created_at
|
||||
"""
|
||||
),
|
||||
{
|
||||
"name": payload.name,
|
||||
"phone": payload.phone,
|
||||
"email": str(payload.email) if payload.email else None,
|
||||
"company": payload.company,
|
||||
"message": payload.message,
|
||||
"source": payload.source,
|
||||
"user_agent": user_agent,
|
||||
},
|
||||
)
|
||||
.mappings()
|
||||
.one()
|
||||
)
|
||||
|
||||
db.commit()
|
||||
|
||||
logger.info("pilot_request saved id=%s source=%s", row["id"], payload.source)
|
||||
|
||||
return {
|
||||
"id": row["id"],
|
||||
"created_at": row["created_at"].isoformat(),
|
||||
"status": "received",
|
||||
}
|
||||
|
|
@ -26,6 +26,7 @@ from app.api.v1 import (
|
|||
landing,
|
||||
parcels,
|
||||
photos,
|
||||
pilot,
|
||||
trade_in,
|
||||
users,
|
||||
)
|
||||
|
|
@ -102,6 +103,7 @@ app.include_router(
|
|||
)
|
||||
app.include_router(trade_in.router, prefix="/api/v1/trade-in", tags=["trade-in"])
|
||||
app.include_router(landing.router, prefix="/api/v1", tags=["landing"])
|
||||
app.include_router(pilot.router, prefix="/api/v1/pilot", tags=["pilot"])
|
||||
app.include_router(users.router, prefix="/api/v1", tags=["users"])
|
||||
|
||||
|
||||
|
|
|
|||
204
backend/app/services/exporters/snapshot_pdf.py
Normal file
204
backend/app/services/exporters/snapshot_pdf.py
Normal file
|
|
@ -0,0 +1,204 @@
|
|||
"""Генерация одностраничного PDF-снимка кадастрового участка.
|
||||
|
||||
Использует WeasyPrint + Jinja2. Шрифты — DejaVu Sans из системы (Dockerfile)
|
||||
или из пакета weasyprint (font fallback). Шаблон: app/templates/parcel_snapshot.html.
|
||||
"""
|
||||
|
||||
import datetime
|
||||
import logging
|
||||
import pathlib
|
||||
from typing import Any
|
||||
|
||||
from jinja2 import Environment, FileSystemLoader, select_autoescape
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Путь к директории шаблонов (относительно этого файла — 2 уровня вверх, затем templates)
|
||||
_TEMPLATE_DIR = pathlib.Path(__file__).parent.parent / "templates"
|
||||
|
||||
# Системные пути DejaVu Sans (Ubuntu/Debian Docker-образ + Alpine резерв)
|
||||
_DEJAVU_CANDIDATES: list[str] = [
|
||||
"/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
|
||||
"/usr/share/fonts/dejavu/DejaVuSans.ttf",
|
||||
"/usr/share/fonts/TTF/DejaVuSans.ttf",
|
||||
]
|
||||
|
||||
_CATEGORY_RU: dict[str, str] = {
|
||||
"school": "Школа",
|
||||
"kindergarten": "Детский сад",
|
||||
"pharmacy": "Аптека",
|
||||
"hospital": "Больница",
|
||||
"shop_mall": "ТЦ",
|
||||
"shop_supermarket": "Супермаркет",
|
||||
"shop_small": "Магазин",
|
||||
"park": "Парк",
|
||||
"bus_stop": "Автобус",
|
||||
"metro_stop": "Метро",
|
||||
"tram_stop": "Трамвай",
|
||||
}
|
||||
|
||||
# Веса POI-категорий — должны совпадать с _POI_WEIGHTS в parcels.py.
|
||||
# Дублированы здесь чтобы exporter не импортировал из api-слоя.
|
||||
_POI_WEIGHTS: dict[str, float] = {
|
||||
"school": 1.5,
|
||||
"kindergarten": 1.5,
|
||||
"pharmacy": 0.8,
|
||||
"hospital": 0.6,
|
||||
"shop_mall": 1.2,
|
||||
"shop_supermarket": 1.0,
|
||||
"shop_small": 0.5,
|
||||
"park": 1.8,
|
||||
"bus_stop": 0.3,
|
||||
"metro_stop": 1.5,
|
||||
"tram_stop": -0.5,
|
||||
}
|
||||
|
||||
_WALK_SPEED_M_PER_MIN: float = 80.0 # ~5 км/ч
|
||||
|
||||
|
||||
def _find_font_url() -> str:
|
||||
"""Вернуть file:// URL для DejaVu Sans или пустую строку (system fallback).
|
||||
|
||||
WeasyPrint умеет сам находить системные шрифты через fonttools/fontconfig,
|
||||
поэтому пустая строка допустима — шрифт тогда подбирается CSS generic.
|
||||
"""
|
||||
for path in _DEJAVU_CANDIDATES:
|
||||
if pathlib.Path(path).exists():
|
||||
return f"file://{path}"
|
||||
logger.warning(
|
||||
"snapshot_pdf: DejaVu Sans не найден в стандартных путях — используем system fallback"
|
||||
)
|
||||
return ""
|
||||
|
||||
|
||||
def _format_cost(value: float | None) -> str:
|
||||
"""Форматировать кадастровую стоимость в читаемый вид (млн/тыс ₽)."""
|
||||
if value is None:
|
||||
return "—"
|
||||
if value >= 1_000_000:
|
||||
return f"{value / 1_000_000:.1f} млн ₽"
|
||||
if value >= 1_000:
|
||||
return f"{value / 1_000:.0f} тыс ₽"
|
||||
return f"{value:.0f} ₽"
|
||||
|
||||
|
||||
def _build_poi_items(poi_rows: list[dict[str, Any]], limit: int = 7) -> list[dict[str, Any]]:
|
||||
"""Вычислить weighted_score для каждого POI и вернуть топ-N отсортированных.
|
||||
|
||||
Формула: weighted_score = weight * max(0, 1 - distance_m / 1000)
|
||||
Отрицательные вклады (трамвай) — не включаем в топ-список.
|
||||
"""
|
||||
items: list[dict[str, Any]] = []
|
||||
for p in poi_rows:
|
||||
cat: str = p.get("category", "")
|
||||
w = _POI_WEIGHTS.get(cat, 0.0)
|
||||
distance_m = float(p.get("distance_m") or 0)
|
||||
decay = max(0.0, 1.0 - distance_m / 1000.0)
|
||||
score = round(w * decay, 2)
|
||||
if score <= 0:
|
||||
continue
|
||||
walk_min = max(1, round(distance_m / _WALK_SPEED_M_PER_MIN))
|
||||
items.append(
|
||||
{
|
||||
"category_ru": _CATEGORY_RU.get(cat, cat),
|
||||
"name": p.get("name") or "",
|
||||
"distance_m": round(distance_m),
|
||||
"walk_min": walk_min,
|
||||
"weighted_score": score,
|
||||
}
|
||||
)
|
||||
items.sort(key=lambda x: x["weighted_score"], reverse=True)
|
||||
return items[:limit]
|
||||
|
||||
|
||||
def generate_snapshot_pdf(
|
||||
*,
|
||||
cad_num: str,
|
||||
address: str | None,
|
||||
district: str | None,
|
||||
area_m2: float | None,
|
||||
cadastral_cost_rub: float | None,
|
||||
land_category: str | None,
|
||||
vri: str | None,
|
||||
last_update: str | None,
|
||||
poi_rows: list[dict[str, Any]],
|
||||
competitor_rows: list[dict[str, Any]],
|
||||
competitors_limit: int = 5,
|
||||
) -> bytes:
|
||||
"""Сгенерировать PDF-снимок участка (1 страница A4).
|
||||
|
||||
Аргументы:
|
||||
cad_num: кадастровый номер.
|
||||
address: адрес из cad_parcels.
|
||||
district: район города.
|
||||
area_m2: площадь в кв. м (конвертируем в га для отображения).
|
||||
cadastral_cost_rub: кадастровая стоимость в рублях.
|
||||
land_category: категория земель.
|
||||
vri: вид разрешённого использования.
|
||||
last_update: строка даты последнего обновления данных.
|
||||
poi_rows: сырые строки из osm_poi_ekb (category, name, distance_m).
|
||||
competitor_rows: строки конкурентов из domrf_kn_objects.
|
||||
competitors_limit: сколько конкурентов выводить (3-5 по ТЗ).
|
||||
|
||||
Возвращает: bytes PDF-документа.
|
||||
"""
|
||||
# WeasyPrint импортируем локально — тяжёлый; не нужен при импорте модуля
|
||||
try:
|
||||
from weasyprint import HTML
|
||||
except ImportError as exc:
|
||||
raise RuntimeError(
|
||||
"WeasyPrint не установлен. Добавь 'weasyprint>=62.0' в pyproject.toml."
|
||||
) from exc
|
||||
|
||||
env = Environment(
|
||||
loader=FileSystemLoader(str(_TEMPLATE_DIR)),
|
||||
autoescape=select_autoescape(["html"]),
|
||||
)
|
||||
template = env.get_template("parcel_snapshot.html")
|
||||
|
||||
area_ha = f"{area_m2 / 10_000:.2f}" if area_m2 else "—"
|
||||
poi_items = _build_poi_items(poi_rows, limit=7)
|
||||
|
||||
# Конкуренты — берём топ N ближайших (уже отсортированы по flat_count DESC;
|
||||
# переупорядочиваем по distance_m для удобства чтения)
|
||||
competitors_display = sorted(
|
||||
competitor_rows[:competitors_limit],
|
||||
key=lambda r: float(r.get("distance_m") or 0),
|
||||
)
|
||||
competitors_ctx: list[dict[str, Any]] = [
|
||||
{
|
||||
"comm_name": r.get("comm_name"),
|
||||
"dev_name": r.get("dev_name"),
|
||||
"obj_class": r.get("obj_class"),
|
||||
"flat_count": r.get("flat_count"),
|
||||
"distance_m": round(float(r.get("distance_m") or 0)),
|
||||
}
|
||||
for r in competitors_display
|
||||
]
|
||||
|
||||
generated_at = datetime.datetime.now(tz=datetime.UTC).strftime("%d.%m.%Y %H:%M UTC")
|
||||
|
||||
html_str = template.render(
|
||||
cad_num=cad_num,
|
||||
address=address,
|
||||
district=district,
|
||||
area_ha=area_ha,
|
||||
cadastral_cost=_format_cost(cadastral_cost_rub),
|
||||
land_category=land_category,
|
||||
vri=vri,
|
||||
last_update=last_update or "—",
|
||||
poi_items=poi_items,
|
||||
competitors=competitors_ctx,
|
||||
generated_at=generated_at,
|
||||
font_url=_find_font_url(),
|
||||
)
|
||||
|
||||
logger.info(
|
||||
"snapshot_pdf: rendering PDF for %s (%d POI, %d competitors)",
|
||||
cad_num,
|
||||
len(poi_items),
|
||||
len(competitors_ctx),
|
||||
)
|
||||
|
||||
pdf_bytes: bytes = HTML(string=html_str, base_url=str(_TEMPLATE_DIR)).write_pdf()
|
||||
return pdf_bytes
|
||||
159
backend/app/services/site_finder/poi_score.py
Normal file
159
backend/app/services/site_finder/poi_score.py
Normal file
|
|
@ -0,0 +1,159 @@
|
|||
"""POI weighted score для Site Finder (B6).
|
||||
|
||||
Формула: weight = (1 / (distance_m + 100)) * category_weight
|
||||
|
||||
Возвращает top-7 ближайших POI из osm_poi_ekb, отсортированных по weight DESC.
|
||||
Категории и их веса согласованы с _POI_WEIGHTS в parcels.py.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import Any
|
||||
|
||||
from pydantic import BaseModel
|
||||
from sqlalchemy import text
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Веса по категории — согласованы с _POI_WEIGHTS в parcels.py + новые из vault B6.
|
||||
# Задача: "2GIS-style ranking", метро самое приоритетное.
|
||||
CATEGORY_WEIGHTS: dict[str, float] = {
|
||||
"metro_stop": 6.0,
|
||||
"school": 5.0,
|
||||
"kindergarten": 4.5,
|
||||
"hospital": 4.0,
|
||||
"shop_supermarket": 3.5,
|
||||
"shop_mall": 4.0,
|
||||
"park": 3.5,
|
||||
"bus_stop": 4.5,
|
||||
"tram_stop": 2.0,
|
||||
"pharmacy": 2.5,
|
||||
"shop_small": 2.0,
|
||||
"default": 1.0,
|
||||
}
|
||||
|
||||
|
||||
class PoiScoreItem(BaseModel):
|
||||
"""Один POI в ranked-ответе."""
|
||||
|
||||
name: str | None
|
||||
category: str
|
||||
distance_m: float
|
||||
weight: float
|
||||
address: str | None
|
||||
|
||||
|
||||
class PoiScoreResponse(BaseModel):
|
||||
cad_num: str
|
||||
radius_m: int
|
||||
top_poi: list[PoiScoreItem]
|
||||
|
||||
|
||||
def _category_weight(category: str) -> float:
|
||||
"""Вернуть вес категории. Если не знаем — default."""
|
||||
return CATEGORY_WEIGHTS.get(category, CATEGORY_WEIGHTS["default"])
|
||||
|
||||
|
||||
def compute_poi_weighted_top7(
|
||||
db: Any,
|
||||
cad_num: str,
|
||||
lat: float,
|
||||
lon: float,
|
||||
radius_m: int = 2000,
|
||||
top_n: int = 7,
|
||||
) -> PoiScoreResponse:
|
||||
"""Найти top-N POI вокруг (lat, lon) в radius_m, ранжировать по weighted score.
|
||||
|
||||
Запрос к osm_poi_ekb через ST_DWithin + ST_Distance.
|
||||
Формула: weight = (1 / (distance_m + 100)) * category_weight
|
||||
|
||||
Args:
|
||||
db: SQLAlchemy Session
|
||||
cad_num: кадастровый номер (для ответа)
|
||||
lat: широта центроида участка
|
||||
lon: долгота центроида участка
|
||||
radius_m: радиус поиска в метрах (default 2000)
|
||||
top_n: количество POI в ответе (default 7)
|
||||
|
||||
Returns:
|
||||
PoiScoreResponse с отсортированными по weight DESC POI.
|
||||
"""
|
||||
# ST_DWithin с geography=true использует метры напрямую.
|
||||
# ST_Distance тоже в метрах при geography=true.
|
||||
rows = (
|
||||
db.execute(
|
||||
text("""
|
||||
SELECT
|
||||
p.name,
|
||||
p.category,
|
||||
p.tags,
|
||||
CAST(
|
||||
ST_Distance(
|
||||
p.geom::geography,
|
||||
ST_SetSRID(ST_MakePoint(:lon, :lat), 4326)::geography
|
||||
) AS double precision
|
||||
) AS distance_m
|
||||
FROM osm_poi_ekb p
|
||||
WHERE ST_DWithin(
|
||||
p.geom::geography,
|
||||
ST_SetSRID(ST_MakePoint(:lon, :lat), 4326)::geography,
|
||||
:radius_m
|
||||
)
|
||||
ORDER BY distance_m ASC
|
||||
LIMIT :limit
|
||||
"""),
|
||||
{
|
||||
"lat": lat,
|
||||
"lon": lon,
|
||||
"radius_m": radius_m,
|
||||
"limit": top_n * 10, # запрашиваем больше, потом ранжируем
|
||||
},
|
||||
)
|
||||
.mappings()
|
||||
.all()
|
||||
)
|
||||
|
||||
logger.debug(
|
||||
"poi_score: cad=%s lat=%.5f lon=%.5f radius=%dm → %d candidates",
|
||||
cad_num,
|
||||
lat,
|
||||
lon,
|
||||
radius_m,
|
||||
len(rows),
|
||||
)
|
||||
|
||||
items: list[PoiScoreItem] = []
|
||||
for row in rows:
|
||||
distance_m = float(row["distance_m"])
|
||||
category = row["category"] or "default"
|
||||
cat_weight = _category_weight(category)
|
||||
weight = (1.0 / (distance_m + 100.0)) * cat_weight
|
||||
|
||||
# Адрес из tags jsonb если есть
|
||||
tags: dict[str, str] = row["tags"] or {}
|
||||
addr_parts = [
|
||||
tags.get("addr:street"),
|
||||
tags.get("addr:housenumber"),
|
||||
]
|
||||
address = ", ".join(p for p in addr_parts if p) or None
|
||||
|
||||
items.append(
|
||||
PoiScoreItem(
|
||||
name=row["name"],
|
||||
category=category,
|
||||
distance_m=round(distance_m, 1),
|
||||
weight=round(weight, 6),
|
||||
address=address,
|
||||
)
|
||||
)
|
||||
|
||||
# Сортировка по weight DESC, берём top_n
|
||||
items.sort(key=lambda x: x.weight, reverse=True)
|
||||
top_items = items[:top_n]
|
||||
|
||||
return PoiScoreResponse(
|
||||
cad_num=cad_num,
|
||||
radius_m=radius_m,
|
||||
top_poi=top_items,
|
||||
)
|
||||
240
backend/app/templates/parcel_snapshot.html
Normal file
240
backend/app/templates/parcel_snapshot.html
Normal file
|
|
@ -0,0 +1,240 @@
|
|||
<!DOCTYPE html>
|
||||
<html lang="ru">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<title>Карточка участка {{ cad_num }}</title>
|
||||
<style>
|
||||
@font-face {
|
||||
font-family: 'DejaVu Sans';
|
||||
src: url('{{ font_url }}') format('truetype');
|
||||
}
|
||||
* { box-sizing: border-box; margin: 0; padding: 0; }
|
||||
body {
|
||||
font-family: 'DejaVu Sans', Arial, sans-serif;
|
||||
font-size: 10pt;
|
||||
color: #1a1a2e;
|
||||
background: #ffffff;
|
||||
padding: 20mm 18mm 18mm 18mm;
|
||||
}
|
||||
/* ── HEADER ── */
|
||||
.header {
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: flex-start;
|
||||
border-bottom: 2px solid #2563eb;
|
||||
padding-bottom: 8px;
|
||||
margin-bottom: 14px;
|
||||
}
|
||||
.header-left h1 {
|
||||
font-size: 14pt;
|
||||
font-weight: bold;
|
||||
color: #2563eb;
|
||||
}
|
||||
.header-left .subtitle {
|
||||
font-size: 9pt;
|
||||
color: #64748b;
|
||||
margin-top: 2px;
|
||||
}
|
||||
.header-right {
|
||||
text-align: right;
|
||||
font-size: 8pt;
|
||||
color: #64748b;
|
||||
}
|
||||
/* ── SECTION TITLE ── */
|
||||
.section-title {
|
||||
font-size: 10pt;
|
||||
font-weight: bold;
|
||||
color: #1e3a5f;
|
||||
background: #eff6ff;
|
||||
padding: 4px 8px;
|
||||
border-left: 3px solid #2563eb;
|
||||
margin-bottom: 8px;
|
||||
}
|
||||
/* ── KPI GRID ── */
|
||||
.kpi-grid {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 6px;
|
||||
margin-bottom: 14px;
|
||||
}
|
||||
.kpi-card {
|
||||
flex: 1 1 140px;
|
||||
border: 1px solid #cbd5e1;
|
||||
border-radius: 4px;
|
||||
padding: 7px 10px;
|
||||
background: #f8fafc;
|
||||
}
|
||||
.kpi-card .kpi-label {
|
||||
font-size: 7.5pt;
|
||||
color: #64748b;
|
||||
margin-bottom: 2px;
|
||||
}
|
||||
.kpi-card .kpi-value {
|
||||
font-size: 11pt;
|
||||
font-weight: bold;
|
||||
color: #1e3a5f;
|
||||
}
|
||||
/* ── TABLE ── */
|
||||
table {
|
||||
width: 100%;
|
||||
border-collapse: collapse;
|
||||
font-size: 8.5pt;
|
||||
margin-bottom: 14px;
|
||||
}
|
||||
table thead tr th {
|
||||
background: #1e3a5f;
|
||||
color: #ffffff;
|
||||
padding: 5px 8px;
|
||||
text-align: left;
|
||||
font-weight: bold;
|
||||
}
|
||||
table tbody tr:nth-child(even) td {
|
||||
background: #f1f5f9;
|
||||
}
|
||||
table tbody tr td {
|
||||
padding: 4px 8px;
|
||||
border-bottom: 1px solid #e2e8f0;
|
||||
color: #1a1a2e;
|
||||
}
|
||||
.badge {
|
||||
display: inline-block;
|
||||
padding: 1px 6px;
|
||||
border-radius: 10px;
|
||||
font-size: 7.5pt;
|
||||
font-weight: bold;
|
||||
}
|
||||
.badge-green { background: #dcfce7; color: #166534; }
|
||||
.badge-yellow { background: #fef9c3; color: #854d0e; }
|
||||
.badge-blue { background: #dbeafe; color: #1e40af; }
|
||||
/* ── FOOTER ── */
|
||||
.footer {
|
||||
position: fixed;
|
||||
bottom: 12mm;
|
||||
left: 18mm;
|
||||
right: 18mm;
|
||||
border-top: 1px solid #cbd5e1;
|
||||
padding-top: 5px;
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
font-size: 7.5pt;
|
||||
color: #94a3b8;
|
||||
}
|
||||
.disclaimer {
|
||||
font-size: 7pt;
|
||||
color: #94a3b8;
|
||||
margin-top: 4px;
|
||||
font-style: italic;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
|
||||
<!-- HEADER -->
|
||||
<div class="header">
|
||||
<div class="header-left">
|
||||
<h1>GenDesign — Карточка участка</h1>
|
||||
<div class="subtitle">Данные НСПД / ЕГРНsource: cad_parcels. Не является официальной выпиской ЕГРН.</div>
|
||||
</div>
|
||||
<div class="header-right">
|
||||
<strong>{{ cad_num }}</strong><br/>
|
||||
{{ district or '—' }}<br/>
|
||||
{{ address or '—' }}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- BLOCK 1: KPI -->
|
||||
<div class="section-title">Основные характеристики</div>
|
||||
<div class="kpi-grid">
|
||||
<div class="kpi-card">
|
||||
<div class="kpi-label">Площадь</div>
|
||||
<div class="kpi-value">{{ area_ha }} га</div>
|
||||
</div>
|
||||
<div class="kpi-card">
|
||||
<div class="kpi-label">Кадастровая стоимость</div>
|
||||
<div class="kpi-value">{{ cadastral_cost }}</div>
|
||||
</div>
|
||||
<div class="kpi-card">
|
||||
<div class="kpi-label">Категория земель</div>
|
||||
<div class="kpi-value">{{ land_category or '—' }}</div>
|
||||
</div>
|
||||
<div class="kpi-card">
|
||||
<div class="kpi-label">ВРИ</div>
|
||||
<div class="kpi-value">{{ vri or '—' }}</div>
|
||||
</div>
|
||||
<div class="kpi-card">
|
||||
<div class="kpi-label">Последнее обновление</div>
|
||||
<div class="kpi-value">{{ last_update or '—' }}</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- BLOCK 2: Top-7 POI -->
|
||||
<div class="section-title">Ближайшая инфраструктура (топ-7 по взвешенному баллу)</div>
|
||||
{% if poi_items %}
|
||||
<table>
|
||||
<thead>
|
||||
<tr>
|
||||
<th>Категория</th>
|
||||
<th>Название</th>
|
||||
<th>Расстояние</th>
|
||||
<th>Пешком</th>
|
||||
<th>Балл</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{% for poi in poi_items %}
|
||||
<tr>
|
||||
<td>{{ poi.category_ru }}</td>
|
||||
<td>{{ poi.name or '—' }}</td>
|
||||
<td>{{ poi.distance_m }} м</td>
|
||||
<td>{{ poi.walk_min }} мин</td>
|
||||
<td><span class="badge badge-blue">{{ poi.weighted_score }}</span></td>
|
||||
</tr>
|
||||
{% endfor %}
|
||||
</tbody>
|
||||
</table>
|
||||
{% else %}
|
||||
<p style="color:#64748b; font-size:8.5pt; margin-bottom:14px;">POI в радиусе 1 км не найдены.</p>
|
||||
{% endif %}
|
||||
|
||||
<!-- BLOCK 3: Competitors -->
|
||||
<div class="section-title">Конкуренты в радиусе 3 км (топ {{ competitors|length }})</div>
|
||||
{% if competitors %}
|
||||
<table>
|
||||
<thead>
|
||||
<tr>
|
||||
<th>ЖК / Объект</th>
|
||||
<th>Застройщик</th>
|
||||
<th>Класс</th>
|
||||
<th>Квартир</th>
|
||||
<th>Расстояние</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{% for c in competitors %}
|
||||
<tr>
|
||||
<td>{{ c.comm_name or '—' }}</td>
|
||||
<td>{{ c.dev_name or '—' }}</td>
|
||||
<td>{{ c.obj_class or '—' }}</td>
|
||||
<td>{{ c.flat_count or '—' }}</td>
|
||||
<td>{{ c.distance_m }} м</td>
|
||||
</tr>
|
||||
{% endfor %}
|
||||
</tbody>
|
||||
</table>
|
||||
{% else %}
|
||||
<p style="color:#64748b; font-size:8.5pt; margin-bottom:14px;">Конкурентов в радиусе 3 км не обнаружено.</p>
|
||||
{% endif %}
|
||||
|
||||
<div class="disclaimer">
|
||||
Не является выпиской из ЕГРН. Данные носят аналитический характер.
|
||||
Для официальной выписки: rosreestr.gov.ru
|
||||
</div>
|
||||
|
||||
<!-- FOOTER -->
|
||||
<div class="footer">
|
||||
<span>gendsgn.ru — GenDesign Analytics</span>
|
||||
<span>Сформировано: {{ generated_at }}</span>
|
||||
</div>
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
|
@ -22,6 +22,7 @@ dependencies = [
|
|||
"tenacity>=9.0.0",
|
||||
"pillow>=10.4.0",
|
||||
"weasyprint>=62.0",
|
||||
"jinja2>=3.1.0",
|
||||
"ezdxf>=1.3.0",
|
||||
"openpyxl>=3.1.0",
|
||||
"pandas>=2.2.0",
|
||||
|
|
|
|||
168
backend/tests/test_poi_score.py
Normal file
168
backend/tests/test_poi_score.py
Normal file
|
|
@ -0,0 +1,168 @@
|
|||
"""Tests for POI weighted score service (B6).
|
||||
|
||||
Юнит-тесты для чистой функции — без DB.
|
||||
"""
|
||||
|
||||
from app.services.site_finder.poi_score import (
|
||||
CATEGORY_WEIGHTS,
|
||||
PoiScoreResponse,
|
||||
_category_weight,
|
||||
compute_poi_weighted_top7,
|
||||
)
|
||||
|
||||
# ── unit: _category_weight ─────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_category_weight_metro():
|
||||
"""Метро имеет наибольший вес из всех категорий."""
|
||||
metro_w = _category_weight("metro_stop")
|
||||
for cat in CATEGORY_WEIGHTS:
|
||||
if cat != "metro_stop" and cat != "default":
|
||||
assert metro_w >= _category_weight(
|
||||
cat
|
||||
), f"metro_stop weight {metro_w} должен быть >= {cat} weight {_category_weight(cat)}"
|
||||
|
||||
|
||||
def test_category_weight_unknown_returns_default():
|
||||
w = _category_weight("unknown_category_xyz")
|
||||
assert w == CATEGORY_WEIGHTS["default"]
|
||||
|
||||
|
||||
def test_category_weight_all_positive():
|
||||
"""Все веса в CATEGORY_WEIGHTS должны быть положительными (B6 — ranking, не штраф)."""
|
||||
for cat, w in CATEGORY_WEIGHTS.items():
|
||||
assert w > 0, f"Вес {cat}={w} должен быть > 0"
|
||||
|
||||
|
||||
# ── unit: weight formula ratio ─────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_weight_formula_ratio():
|
||||
"""Ближний объект той же категории должен иметь больший вес."""
|
||||
cat = "school"
|
||||
cw = _category_weight(cat)
|
||||
w_near = (1.0 / (100.0 + 100.0)) * cw # 100м
|
||||
w_far = (1.0 / (1000.0 + 100.0)) * cw # 1000м
|
||||
assert w_near > w_far
|
||||
|
||||
|
||||
def test_weight_formula_category_dominates_at_equal_distance():
|
||||
"""При одинаковом расстоянии метро должно быть впереди автобусной остановки."""
|
||||
dist = 500.0
|
||||
w_metro = (1.0 / (dist + 100.0)) * _category_weight("metro_stop")
|
||||
w_bus = (1.0 / (dist + 100.0)) * _category_weight("bus_stop")
|
||||
assert w_metro > w_bus
|
||||
|
||||
|
||||
# ── unit: compute_poi_weighted_top7 with mock DB ───────────────────────────────
|
||||
|
||||
|
||||
class _MockMappings:
|
||||
def __init__(self, data: list[dict]) -> None:
|
||||
self._data = data
|
||||
|
||||
def all(self) -> list[dict]:
|
||||
return self._data # type: ignore[return-value]
|
||||
|
||||
|
||||
class _MockResult:
|
||||
def __init__(self, data: list[dict]) -> None:
|
||||
self._data = data
|
||||
|
||||
def mappings(self) -> "_MockMappings":
|
||||
return _MockMappings(self._data)
|
||||
|
||||
|
||||
class _MockDb:
|
||||
"""Минимальный мок SQLAlchemy Session для тестирования без БД."""
|
||||
|
||||
def __init__(self, rows: list[dict]) -> None:
|
||||
self._rows = rows
|
||||
|
||||
def execute(self, *_args: object, **_kwargs: object) -> _MockResult:
|
||||
return _MockResult(self._rows)
|
||||
|
||||
|
||||
def _make_row(name: str, category: str, distance_m: float) -> dict:
|
||||
return {
|
||||
"name": name,
|
||||
"category": category,
|
||||
"tags": {},
|
||||
"distance_m": distance_m,
|
||||
}
|
||||
|
||||
|
||||
def test_top7_returns_at_most_7():
|
||||
rows = [_make_row(f"POI {i}", "school", float(i * 50)) for i in range(1, 20)]
|
||||
db = _MockDb(rows)
|
||||
result = compute_poi_weighted_top7(db, "66:41:0204016:10", 56.838, 60.605)
|
||||
assert isinstance(result, PoiScoreResponse)
|
||||
assert len(result.top_poi) <= 7
|
||||
|
||||
|
||||
def test_top7_sorted_by_weight_desc():
|
||||
rows = [
|
||||
_make_row("Дальняя школа", "school", 1500.0),
|
||||
_make_row("Метро", "metro_stop", 300.0),
|
||||
_make_row("Близкая школа", "school", 100.0),
|
||||
]
|
||||
db = _MockDb(rows)
|
||||
result = compute_poi_weighted_top7(db, "66:41:0204016:10", 56.838, 60.605)
|
||||
weights = [item.weight for item in result.top_poi]
|
||||
assert weights == sorted(weights, reverse=True), "top_poi должны быть по weight DESC"
|
||||
|
||||
|
||||
def test_metro_beats_school_at_equal_distance():
|
||||
"""Метро в 300м должно быть на первом месте перед школой в 300м (равное расстояние)."""
|
||||
rows = [
|
||||
_make_row("Школа №1", "school", 300.0),
|
||||
_make_row("Метро Чкаловская", "metro_stop", 300.0),
|
||||
]
|
||||
db = _MockDb(rows)
|
||||
result = compute_poi_weighted_top7(db, "66:41:0204016:10", 56.838, 60.605)
|
||||
assert (
|
||||
result.top_poi[0].category == "metro_stop"
|
||||
), "При равном расстоянии метро (category_weight=6.0) должно быть выше школы (5.0)"
|
||||
|
||||
|
||||
def test_metro_first_when_close():
|
||||
"""Метро в 50м должно быть на первом месте перед школой в 300м."""
|
||||
rows = [
|
||||
_make_row("Школа №1", "school", 300.0),
|
||||
_make_row("Метро Чкаловская", "metro_stop", 50.0),
|
||||
]
|
||||
db = _MockDb(rows)
|
||||
result = compute_poi_weighted_top7(db, "66:41:0204016:10", 56.838, 60.605)
|
||||
assert result.top_poi[0].category == "metro_stop", (
|
||||
"Метро (weight=6.0) в 50м должно быть впереди школы (weight=5.0) в 300м — "
|
||||
f"metro_weight={(1/(50+100))*6:.5f} vs school_weight={(1/(300+100))*5:.5f}"
|
||||
)
|
||||
|
||||
|
||||
def test_empty_db_returns_empty_top_poi():
|
||||
db = _MockDb([])
|
||||
result = compute_poi_weighted_top7(db, "66:41:0204016:10", 56.838, 60.605)
|
||||
assert result.top_poi == []
|
||||
assert result.cad_num == "66:41:0204016:10"
|
||||
assert result.radius_m == 2000
|
||||
|
||||
|
||||
def test_address_built_from_tags():
|
||||
rows = [
|
||||
{
|
||||
"name": "Магазин",
|
||||
"category": "shop_small",
|
||||
"tags": {"addr:street": "ул. Ленина", "addr:housenumber": "10"},
|
||||
"distance_m": 200.0,
|
||||
}
|
||||
]
|
||||
db = _MockDb(rows)
|
||||
result = compute_poi_weighted_top7(db, "test", 56.838, 60.605)
|
||||
assert result.top_poi[0].address == "ул. Ленина, 10"
|
||||
|
||||
|
||||
def test_address_none_when_no_tags():
|
||||
rows = [_make_row("Парк", "park", 400.0)]
|
||||
db = _MockDb(rows)
|
||||
result = compute_poi_weighted_top7(db, "test", 56.838, 60.605)
|
||||
assert result.top_poi[0].address is None
|
||||
14
backend/uv.lock
generated
14
backend/uv.lock
generated
|
|
@ -568,6 +568,7 @@ dependencies = [
|
|||
{ name = "geopandas" },
|
||||
{ name = "httpx" },
|
||||
{ name = "ijson" },
|
||||
{ name = "jinja2" },
|
||||
{ name = "numpy" },
|
||||
{ name = "openpyxl" },
|
||||
{ name = "pandas" },
|
||||
|
|
@ -608,6 +609,7 @@ requires-dist = [
|
|||
{ name = "geopandas", specifier = ">=1.0.0" },
|
||||
{ name = "httpx", specifier = ">=0.27.0" },
|
||||
{ name = "ijson", specifier = ">=3.2.0" },
|
||||
{ name = "jinja2", specifier = ">=3.1.0" },
|
||||
{ name = "numpy", specifier = ">=2.0.0" },
|
||||
{ name = "openpyxl", specifier = ">=3.1.0" },
|
||||
{ name = "pandas", specifier = ">=2.2.0" },
|
||||
|
|
@ -871,6 +873,18 @@ wheels = [
|
|||
{ url = "https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl", hash = "sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12", size = 7484, upload-time = "2025-10-18T21:55:41.639Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "jinja2"
|
||||
version = "3.1.6"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "markupsafe" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/df/bf/f7da0350254c0ed7c72f3e33cef02e048281fec7ecec5f032d4aac52226b/jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d", size = 245115, upload-time = "2025-03-05T20:05:02.478Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67", size = 134899, upload-time = "2025-03-05T20:05:00.369Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "joblib"
|
||||
version = "1.5.3"
|
||||
|
|
|
|||
21
data/sql/118_pilot_requests.sql
Normal file
21
data/sql/118_pilot_requests.sql
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
BEGIN;
|
||||
|
||||
CREATE TABLE IF NOT EXISTS pilot_requests (
|
||||
id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
name text NOT NULL,
|
||||
phone text,
|
||||
email text,
|
||||
company text,
|
||||
message text,
|
||||
source text, -- 'landing', 'analyze_page', etc
|
||||
user_agent text,
|
||||
created_at timestamptz NOT NULL DEFAULT NOW(),
|
||||
notified_at timestamptz -- when Telegram sent
|
||||
);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS pilot_requests_created_idx
|
||||
ON pilot_requests (created_at DESC);
|
||||
|
||||
COMMENT ON TABLE pilot_requests IS '#307 SF-B3 lead generation, опционально notified в Telegram.';
|
||||
|
||||
COMMIT;
|
||||
Loading…
Add table
Reference in a new issue