""" import_tickets.py — Fireside Communications · INC ticket ingestion (raw-first) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Loads the client's field-ops INC ticket snapshots into the `tickets` schema — the source of the FleetOps "Tickets" map. tickets.inc — incidents / customer faults STRICTLY INC: CRQ (new-installation) exports are out of scope and not processed here. `tickets.crq` stays in the schema but is not fed by this pipeline. RAW-FIRST: each row stores only `ticket_id` + `raw` (the source record as jsonb). Everything downstream reads from `raw` (resilient to source schema drift). The DB derives `geom` (see migrations): feed coords (raw lat/lng) -> location geocode (tickets.geo_locations) -> cluster centroid (tickets.geo_clusters) -> none. Source data: the n8n hourly S3 export (see n8n-hourly-s3-full-data-exports.md) writes a full current-state snapshot CSV per hour to the `tickets` bucket at automations/inc/.csv (e.g. 2026-06-15T17-00-00.csv) There is NO latest pointer, NO metadata envelope, and NO deltas — each file is a flat CSV (header + rows). We ingest the NEWEST file: - skip-if-unchanged: if its S3 ETag matches the last processed file's ETag we skip the DB write (the export re-emits byte-identical content most hours); - drop is_alarm=true rows + the "EXPORT STOPPED…" truncation-sentinel row; - drop derivable / provenance / zero-info columns (see DROP_FIELDS); - normalize region -> lowercase, raw_status -> UPPERCASE; - upsert on ticket_id (PRIMARY KEY → no duplication; never delete, so closure history accumulates), and record snapshot freshness in tickets.import_meta; - on success, MOVE the file to automations/inc/processed/ (copy + delete). Geocoding (two layers, both via a KEYED provider — public Nominatim rate-limits): --geocode-clusters one coordinate per cluster (coarse fallback; ~50 lookups) --geocode-locations precise per-location for ACTIONABLE INC tickets: parses the real place out of location_name (region+cluster+location_name, network codes stripped), geocodes it, caches in tickets.geo_locations, then re-resolves geoms. Provider/key from env: GEOCODER_PROVIDER (locationiq|opencage), GEOCODER_API_KEY. Usage (needs DATABASE_URL + RUSTFS_* + GEOCODER_* env; see .env.example): python import_tickets.py --from-bucket --apply python import_tickets.py --inc-csv 2026-06-15T17-00-00.csv --apply python import_tickets.py --geocode-clusters --apply python import_tickets.py --geocode-locations --apply Pre-requisite: migration applied (run_migrations.py) — tickets.inc/crq + geo_clusters + geo_locations + reporting.fn_tickets_for_map. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ """ from __future__ import annotations import argparse import csv import io import math import os import re import time from datetime import datetime, timezone, timedelta import boto3 import requests import psycopg2.extras from botocore.config import Config as BotoConfig from shared import clean, get_conn, get_logger log = get_logger("import_tickets") # ── INC ingestion config ────────────────────────────────────────────────────── _TABLE = "tickets.inc" _DATASET = "inc" _BUCKET = os.getenv("TICKETS_BUCKET", "tickets") _INC_PREFIX = "automations/inc/" _PROCESSED_PREFIX = "automations/inc/processed/" _EAT = timezone(timedelta(hours=3)) # Africa/Nairobi — filenames + data are EAT # Garbage row the source leaks (commonly the first data line): its ticket_id is the # message itself. Matched by prefix so position/exact-tail don't matter. _SENTINEL_PREFIX = "EXPORT STOPPED" # Columns dropped before building `raw`: derivable (week_*), the client's row-level # export provenance (source_s3_*, source_snapshot_id), and zero-information columns # (department=always FTTH, source_type=duplicate of service_type). We KEEP # service_type and `bucket` (the latter is a closed/pending lifecycle flag). DROP_FIELDS = frozenset({ "week_start", "week_end", "source_s3_bucket", "source_s3_key", "source_snapshot_id", "department", "source_type", }) # Only files matching automations/inc/.csv (NOT processed/, NOT the # leftover latest.csv/, latest.json/, full/ prefixes). _CSV_KEY_RE = re.compile(r"^automations/inc/(\d{4}-\d{2}-\d{2}T\d{2}-\d{2}-\d{2})\.csv$") # Geocoder (keyed) — public Nominatim rate-limits bulk, so we use LocationIQ/OpenCage. _PROVIDER = os.getenv("GEOCODER_PROVIDER", "locationiq").lower() _API_KEY = os.getenv("GEOCODER_API_KEY", "") _GEOCODE_INTERVAL_S = float(os.getenv("GEOCODER_MIN_INTERVAL_S", "1.1")) _last_geocode_at = 0.0 # ── data loading (CSV · newest-file · ETag skip-if-unchanged) ─────────────────── # The n8n hourly export writes a full current-state CSV per hour to # automations/inc/.csv (no latest pointer, no envelope, no deltas). # We ingest the NEWEST file; if its S3 ETag matches the last processed file's ETag # we skip the DB write (the export re-emits byte-identical content most hours). # S3 access is via boto3 (no aws-CLI dependency → runs cleanly in a slim container). def _s3_client(): """boto3 S3 client for the rustfs endpoint (force path-style addressing).""" return boto3.client( "s3", endpoint_url=os.environ["RUSTFS_ENDPOINT"], aws_access_key_id=os.environ["RUSTFS_ACCESS_KEY"], aws_secret_access_key=os.environ["RUSTFS_SECRET_KEY"], region_name=os.getenv("RUSTFS_REGION", "us-east-1"), config=BotoConfig(s3={"addressing_style": "path"}, signature_version="s3v4", retries={"max_attempts": 3, "mode": "standard"}), ) def _ts_from_key(key: str) -> datetime | None: """EAT timestamp embedded in an automations/inc/.csv key (or None).""" m = _CSV_KEY_RE.match(key) if not m: return None try: # regex shape can match an impossible date (e.g. 9999-99-99T…) — don't crash the sort return datetime.strptime(m.group(1), "%Y-%m-%dT%H-%M-%S").replace(tzinfo=_EAT) except ValueError: return None def _list_inc_csvs(s3) -> list[tuple[str, str]]: """[(key, etag)] for every automations/inc/.csv (excludes processed/ + dirs).""" out: list[tuple[str, str]] = [] for page in s3.get_paginator("list_objects_v2").paginate(Bucket=_BUCKET, Prefix=_INC_PREFIX): for it in page.get("Contents", []): if _CSV_KEY_RE.match(it["Key"]): out.append((it["Key"], (it.get("ETag") or "").strip('"'))) return out def _get_text(s3, key: str) -> str: """Download an object's body as UTF-8 text.""" return s3.get_object(Bucket=_BUCKET, Key=key)["Body"].read().decode("utf-8") def _last_processed_etag() -> str | None: """ETag of the most recently ingested INC file (from tickets.import_meta).""" with get_conn() as conn: with conn.cursor() as cur: cur.execute( "SELECT metadata->>'source_etag' FROM tickets.import_meta WHERE dataset = %s", (_DATASET,), ) row = cur.fetchone() return row[0] if row else None def _parse_csv(text: str) -> list[dict]: return list(csv.DictReader(io.StringIO(text))) def _load_csv_local(path: str) -> list[dict]: with open(path, encoding="utf-8", newline="") as f: return list(csv.DictReader(f)) def _move_processed(s3, keys: list[str]) -> None: """Archive listed INC csv objects to automations/inc/processed/ (copy + delete).""" for key in keys: dst = _PROCESSED_PREFIX + key.rsplit("/", 1)[-1] s3.copy_object(Bucket=_BUCKET, CopySource={"Bucket": _BUCKET, "Key": key}, Key=dst) s3.delete_object(Bucket=_BUCKET, Key=key) log.info("archived %s -> %s", key, dst) # ── row preparation (filter · drop columns · normalize) ───────────────────────── def _keep_row(row: dict) -> bool: """Drop alarm rows + the truncation-sentinel; require a real ticket_id.""" tid = clean(row.get("ticket_id")) if not tid or tid.startswith(_SENTINEL_PREFIX): return False return clean(row.get("is_alarm")) != "true" def _prepare(row: dict) -> dict: """Strip DROP_FIELDS and normalize region/raw_status — returns the `raw` payload.""" r = {k: v for k, v in row.items() if k not in DROP_FIELDS} if r.get("region"): r["region"] = r["region"].lower() if r.get("raw_status"): r["raw_status"] = r["raw_status"].upper() return r # ── upsert (raw-first) ──────────────────────────────────────────────────────── def _record_meta(cur, meta: dict, records_ingested: int) -> None: """Upsert the INC snapshot metadata (powers map freshness + holds source_etag). Runs on the caller's cursor so the row upsert and the meta write commit together — a half-written state (rows in, meta stale) breaks skip-if-unchanged. """ cur.execute( """INSERT INTO tickets.import_meta (dataset, export_type, exported_at, snapshot_date, source_schema, source_table, row_count, records_ingested, n8n_execution_id, metadata, ingested_at) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, now()) ON CONFLICT (dataset) DO UPDATE SET export_type = EXCLUDED.export_type, exported_at = EXCLUDED.exported_at, snapshot_date = EXCLUDED.snapshot_date, source_schema = EXCLUDED.source_schema, source_table = EXCLUDED.source_table, row_count = EXCLUDED.row_count, records_ingested = EXCLUDED.records_ingested, n8n_execution_id = EXCLUDED.n8n_execution_id, metadata = EXCLUDED.metadata, ingested_at = now()""", (_DATASET, clean(meta.get("export_type")), clean(meta.get("exported_at")), clean(meta.get("snapshot_date")), clean(meta.get("source_schema")), clean(meta.get("source_table")), meta.get("row_count"), records_ingested, clean(meta.get("n8n_execution_id")), psycopg2.extras.Json(meta)), ) def upsert(rows: list[dict], apply: bool, meta: dict | None = None) -> int: meta = meta or {} kept = [r for r in rows if _keep_row(r)] payload = [(clean(r["ticket_id"]), psycopg2.extras.Json(_prepare(r))) for r in kept] log.info("%s: %d rows read, %d kept, %d dropped (alarm/sentinel/no-id)", _TABLE, len(rows), len(payload), len(rows) - len(payload)) if not apply: log.info("DRY-RUN — nothing written to %s. Use --apply.", _TABLE) return len(payload) with get_conn() as conn: with conn.cursor() as cur: psycopg2.extras.execute_values( cur, f"INSERT INTO {_TABLE} (ticket_id, raw) VALUES %s " "ON CONFLICT (ticket_id) DO UPDATE SET raw = EXCLUDED.raw, ingested_at = now()", payload, page_size=500, ) # same transaction as the upsert: rows + snapshot meta commit atomically _record_meta(cur, meta, len(payload)) log.info("upserted %d rows into %s", len(payload), _TABLE) return len(payload) def _capture_history() -> None: """Append new closures + upsert today's backlog snapshot (tickets.capture_history).""" with get_conn() as conn: with conn.cursor() as cur: cur.execute("SELECT tickets.capture_history()") log.info("history: %s", cur.fetchone()[0]) def ingest(args) -> None: # Local-file path (dev): ingest a single CSV, no bucket / no archive. if args.inc_csv: rows = _load_csv_local(args.inc_csv) name = os.path.basename(args.inc_csv) ts = _ts_from_key(_INC_PREFIX + name) meta = {"export_type": "full", "source_s3_key": name, "row_count": len(rows)} if ts: meta["exported_at"] = ts.isoformat() upsert(rows, args.apply, meta=meta) return # --from-bucket: newest INC csv → skip-if-unchanged → ingest → archive. s3 = _s3_client() listing = _list_inc_csvs(s3) if not listing: log.info("no INC csv files under %s — nothing to do", _INC_PREFIX) return listing.sort(key=lambda ke: _ts_from_key(ke[0]) or datetime.min.replace(tzinfo=_EAT)) all_keys = [k for k, _ in listing] newest_key, newest_etag = listing[-1] log.info("newest INC file: %s (etag=%s; %d file(s) present)", newest_key, newest_etag, len(listing)) last_etag = _last_processed_etag() if newest_etag and newest_etag == last_etag: log.info("etag unchanged from last processed (%s) — skipping DB write", last_etag) if args.apply: _move_processed(s3, all_keys) _capture_history() # still record today's snapshot even when unchanged else: log.info("DRY-RUN — would archive %d file(s) to %s", len(all_keys), _PROCESSED_PREFIX) return rows = _parse_csv(_get_text(s3, newest_key)) ts = _ts_from_key(newest_key) meta = {"export_type": "full", "source_s3_key": newest_key, "source_etag": newest_etag, "row_count": len(rows)} if ts: meta["exported_at"] = ts.isoformat() upsert(rows, args.apply, meta=meta) if args.apply: _move_processed(s3, all_keys) _capture_history() else: log.info("DRY-RUN — would archive %d file(s) to %s", len(all_keys), _PROCESSED_PREFIX) # ── place extraction (strip network codes, keep the real place) ─────────────── # Leading site-code prefixes (NW_, CO_, ADR_MNT_, COAST_, …) — applied repeatedly. _PREFIX_RE = re.compile(r"^(?:NW|NE|NM|SW|SE|CO|COAST|ADR|MNT|CMT|DR|NAIROBI|FIBER\w*)[\s_]+") # 'NW' is the one site-code that the source also glues straight onto the place with # no separator (NWKIAMBU, NWRIDGE, NWTHE — ~1.7k rows in a single snapshot). Safe to # split because no place/word starts with "NW"; the other codes (CO/NE/SE/DR…) begin # real words (COAST, NEW, SEASONS, DRIVE) so we only strip THOSE when delimited above. _GLUED_NW_RE = re.compile(r"^NW(?=[A-Z])") # Inline network/work-order codes to drop wherever they appear. _CODE_RE = re.compile( r"\b(?:SDUS|SDU|MDUS|MDU|FDT\s*\d*|AP|CLUSTER\s*\d*[A-Z]?|PHASE\s*\d+|CL\s*\d+|MNT|SITE|ADR)\b" ) # Trailing '-' after the final hyphen: a unit/instruction code, not a place. # Dropped only when it LOOKS like one — a unit number (37, F32, 3C, 302), a short # code (<=3 chars: E, NB, KKK), or an instruction phrase (CALL ON ARRIVAL, TBC, NA). # A real word tail (…-MALL) is kept. _UNIT_TAIL_RE = re.compile(r"^[A-Z]{0,2}\d+[A-Z]{0,3}$") _TAIL_INSTRUCTION_TOKENS = frozenset({ "CALL", "TO", "NA", "NB", "TBC", "NULL", "NONE", "NIL", "OOO", "OBT", "PENDING", "CONFIRM", "CHECK", "CLIENT", "ON", }) def extract_place(location_name: str | None) -> str: """Pull the human place/landmark out of a coded location_name string. e.g. 'NW_RUIRU KAMAKIS_DEEP EAST APARTMENT-37' -> 'RUIRU KAMAKIS DEEP EAST APARTMENT' 'NWKIAMBU_KIRIGITI_MWANJA APARTMENTS-TBC' -> 'KIAMBU KIRIGITI MWANJA APARTMENTS' """ s = (location_name or "").upper().strip() if not s: return "" # drop the trailing '-' only when it's a unit/instruction code, not a # real word (so '…-37'/'…-CALL ON ARRIVAL' drop but '…-MALL' is kept) if "-" in s: head, _, tail = s.rpartition("-") head, tail = head.strip(), tail.strip() first = tail.split()[0] if tail else "" if head and (not tail or len(tail) <= 3 or _UNIT_TAIL_RE.match(tail) or first in _TAIL_INSTRUCTION_TOKENS): s = head s = s.replace("_", " ") # strip leading site-code prefixes (may be stacked: ADR MNT KAHAWA…; or glued: NWKIAMBU) prev = None while prev != s: prev = s s = _PREFIX_RE.sub("", s).strip() s = _GLUED_NW_RE.sub("", s).strip() s = _CODE_RE.sub(" ", s) s = re.sub(r"\s+", " ", s).strip(" ,-") return s def compose_query(location_name: str | None, cluster: str | None, region: str | None) -> str: parts = [p for p in (extract_place(location_name), clean(cluster), clean(region), "Kenya") if p] return ", ".join(dict.fromkeys(parts)) # de-dupe while preserving order def compose_queries(location_name: str | None, cluster: str | None, region: str | None) -> list[str]: """Ordered geocode candidates, most → least specific (two-pass estate fallback). Building-level location_names (e.g. 'KAHAWA WENDANI ALVO HOUSE') aren't in OSM, so the precise query 404s. We then fall back to the estate (leading tokens of the place) — each still constrained to the cluster viewbox + distance check by the caller, so a coarse hit lands in the right neighbourhood (tighter than the bare cluster centroid). We deliberately do NOT add a pure-cluster candidate: that would just reproduce the cluster centroid while mislabelling it geo_source='location'; a truly unmatchable ticket should keep its honest cluster-centroid fallback. e.g. 'KAHAWA WENDANI ALVO HOUSE' -> ['KAHAWA WENDANI ALVO HOUSE, WENDANI, nairobi, Kenya', 'KAHAWA WENDANI, nairobi, Kenya', 'KAHAWA, nairobi, Kenya'] """ region_part, cluster_part = clean(region), clean(cluster) place = extract_place(location_name) toks = place.split() out: list[str] = [] def add(*parts: str | None) -> None: q = ", ".join(dict.fromkeys([p for p in parts if p] + ["Kenya"])) if q and q != "Kenya" and q not in out: out.append(q) add(place, cluster_part, region_part) # 1. full precise if len(toks) > 2: add(" ".join(toks[:2]), region_part) # 2. estate (leading 2 tokens) if len(toks) > 1: add(toks[0], region_part) # 3. leading token (broad estate) return out # ── keyed geocoder ──────────────────────────────────────────────────────────── def _throttle() -> None: global _last_geocode_at wait = _GEOCODE_INTERVAL_S - (time.monotonic() - _last_geocode_at) if wait > 0: time.sleep(wait) _last_geocode_at = time.monotonic() def _haversine_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float: dlat, dlng = math.radians(lat2 - lat1), math.radians(lng2 - lng1) a = (math.sin(dlat / 2) ** 2 + math.cos(math.radians(lat1)) * math.cos(math.radians(lat2)) * math.sin(dlng / 2) ** 2) return 2 * 6371.0 * math.asin(math.sqrt(a)) def geocode(query: str, viewbox: tuple | None = None) -> tuple[float, float, float | None] | None: """Forward-geocode via the configured keyed provider. (lat, lng, confidence) | None. `viewbox` = (min_lon, min_lat, max_lon, max_lat) constrains results to a box around the cluster centroid (bounded), which stops the geocoder matching a landmark name in the wrong city. """ if not _API_KEY: log.error("GEOCODER_API_KEY is not set — cannot geocode (provider=%s)", _PROVIDER) return None _throttle() try: if _PROVIDER == "opencage": params = {"key": _API_KEY, "q": query, "limit": 1, "countrycode": "ke", "no_annotations": 1} if viewbox: params["bounds"] = "%s,%s,%s,%s" % viewbox r = requests.get("https://api.opencagedata.com/geocode/v1/json", params=params, timeout=15) r.raise_for_status() res = (r.json().get("results") or []) if res: g = res[0]["geometry"] return float(g["lat"]), float(g["lng"]), res[0].get("confidence") else: # locationiq (default) params = {"key": _API_KEY, "q": query, "format": "json", "limit": 1, "countrycodes": "ke"} if viewbox: params["viewbox"] = "%s,%s,%s,%s" % viewbox params["bounded"] = 1 r = requests.get("https://us1.locationiq.com/v1/search", params=params, timeout=15) if r.status_code == 404: # LocationIQ returns 404 for "no matches" return None r.raise_for_status() hits = r.json() if hits: h = hits[0] return float(h["lat"]), float(h["lon"]), float(h.get("importance") or 0) except (requests.RequestException, ValueError, KeyError) as e: log.warning("geocode failed for %r: %s", query, e) return None # ── cluster gazetteer (coarse fallback) ─────────────────────────────────────── def geocode_clusters(apply: bool) -> None: with get_conn() as conn: with conn.cursor() as cur: cur.execute( """ SELECT key, region FROM ( SELECT tickets.norm_cluster(raw->>'cluster') AS key, (array_agg(raw->>'region'))[1] AS region FROM tickets.inc WHERE raw->>'cluster' IS NOT NULL GROUP BY 1 UNION SELECT tickets.norm_cluster(raw->>'cluster'), (array_agg(raw->>'region'))[1] FROM tickets.crq WHERE raw->>'cluster' IS NOT NULL GROUP BY 1 ) z WHERE key IS NOT NULL AND NOT EXISTS (SELECT 1 FROM tickets.geo_clusters g WHERE g.cluster_key = z.key AND g.geom IS NOT NULL) """ ) todo = cur.fetchall() log.info("%d clusters to geocode", len(todo)) if not apply: for key, region in todo: log.info(" would geocode cluster: %s (%s)", key, region) return written = 0 for key, region in todo: hit = geocode(f"{key}, {region}, Kenya" if region else f"{key}, Kenya") if not hit: continue lat, lng, _ = hit with get_conn() as conn: with conn.cursor() as cur: cur.execute( """INSERT INTO tickets.geo_clusters (cluster_key, region, lat, lng, source, verified) VALUES (%s, %s, %s, %s, %s, false) ON CONFLICT (cluster_key) DO UPDATE SET region = EXCLUDED.region, lat = EXCLUDED.lat, lng = EXCLUDED.lng, source = EXCLUDED.source""", (key, region, lat, lng, _PROVIDER), ) written += 1 _resolve() log.info("gazetteer: %d clusters written (unverified — review tickets.geo_clusters)", written) # ── per-location geocoding (precise; actionable INC) ────────────────────────── # A location geocode is only trusted if it lands within this radius of the # cluster centroid; otherwise the geocoder matched the landmark in the wrong # place and we fall back to the cluster centroid. _MAX_KM_FROM_CLUSTER = float(os.getenv("GEOCODER_MAX_KM", "25")) _VIEWBOX_DEG = 0.2 # ~22 km half-box around the cluster centroid def geocode_locations(apply: bool) -> None: with get_conn() as conn: with conn.cursor() as cur: cur.execute( """ SELECT t.key, t.location_name, t.cluster, t.region, gc.lat AS clat, gc.lng AS clng FROM ( SELECT tickets.norm_cluster(raw->>'location_name') AS key, (array_agg(raw->>'location_name'))[1] AS location_name, (array_agg(raw->>'cluster'))[1] AS cluster, (array_agg(raw->>'region'))[1] AS region, tickets.norm_cluster((array_agg(raw->>'cluster'))[1]) AS ckey FROM tickets.inc WHERE (raw->>'is_actionable')::boolean AND raw->>'location_name' IS NOT NULL AND tickets.norm_cluster(raw->>'location_name') IS NOT NULL AND NOT EXISTS (SELECT 1 FROM tickets.geo_locations gl WHERE gl.query_key = tickets.norm_cluster(raw->>'location_name') AND gl.geom IS NOT NULL) GROUP BY 1 ) t LEFT JOIN tickets.geo_clusters gc ON gc.cluster_key = t.ckey """ ) todo = cur.fetchall() log.info("%d actionable-INC locations to geocode (provider=%s)", len(todo), _PROVIDER) if not apply: for key, loc, cluster, region, clat, clng in todo[:50]: log.info(" %s -> %s", key, " | ".join(compose_queries(loc, cluster, region))) return written = missed = coarse = 0 for key, loc, cluster, region, clat, clng in todo: viewbox = None if clat is not None and clng is not None: viewbox = (clng - _VIEWBOX_DEG, clat - _VIEWBOX_DEG, clng + _VIEWBOX_DEG, clat + _VIEWBOX_DEG) # two-pass: precise → estate → cluster; accept the FIRST in-range hit. A wrong-area # match (> MAX_KM from the cluster centroid) is skipped so we try a coarser query. hit = used = None for i, cand in enumerate(compose_queries(loc, cluster, region)): g = geocode(cand, viewbox) if not g: continue lat, lng, conf = g if (clat is not None and clng is not None and _haversine_km(lat, lng, clat, clng) > _MAX_KM_FROM_CLUSTER): continue hit, used = g, cand if i > 0: coarse += 1 break if not hit: missed += 1 # no match even coarsely — keeps cluster-centroid fallback continue lat, lng, conf = hit with get_conn() as conn: with conn.cursor() as cur: cur.execute( """INSERT INTO tickets.geo_locations (query_key, location_name, cluster, region, query, lat, lng, confidence, provider) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s) ON CONFLICT (query_key) DO UPDATE SET location_name = EXCLUDED.location_name, cluster = EXCLUDED.cluster, region = EXCLUDED.region, query = EXCLUDED.query, lat = EXCLUDED.lat, lng = EXCLUDED.lng, confidence = EXCLUDED.confidence, provider = EXCLUDED.provider""", (key, loc, cluster, region, used, lat, lng, conf, _PROVIDER), ) written += 1 log.info(" geocoded %s -> %.5f, %.5f", used, lat, lng) n = _resolve() log.info("locations: %d accepted (%d via estate/cluster fallback), %d unmatched; " "re-resolved geom on %d tickets (unverified — review tickets.geo_locations)", written, coarse, missed, n) def _resolve() -> int: with get_conn() as conn: with conn.cursor() as cur: cur.execute("SELECT tickets.resolve_ticket_geoms()") return cur.fetchone()[0] # ── entrypoint ──────────────────────────────────────────────────────────────── def main() -> None: ap = argparse.ArgumentParser(description="Ingest INC tickets from CSV (raw-first) + geocode") ap.add_argument("--apply", action="store_true", help="Write to DB (default: dry-run)") ap.add_argument("--from-bucket", action="store_true", help="Ingest the newest INC csv from the rustfs tickets bucket (aws CLI); " "skips if unchanged (ETag) and archives processed files") ap.add_argument("--inc-csv", default=None, help="Local INC tickets CSV file (dev)") ap.add_argument("--geocode-clusters", action="store_true", help="Geocode distinct clusters into the gazetteer, then re-resolve geoms") ap.add_argument("--geocode-locations", action="store_true", help="Geocode actionable-INC location_names precisely (keyed provider), then re-resolve") ap.add_argument("--capture-history", action="store_true", help="Run tickets.capture_history() standalone (closure_events + daily snapshot)") args = ap.parse_args() if args.geocode_clusters: geocode_clusters(apply=args.apply) return if args.geocode_locations: geocode_locations(apply=args.apply) return if args.capture_history: _capture_history() return if not (args.from_bucket or args.inc_csv): ap.error("provide --from-bucket, --inc-csv, --geocode-clusters, --geocode-locations, or --capture-history") ingest(args) if __name__ == "__main__": main()