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|
import argparse
import os
import shutil
import sys
import time
import traceback
from typing import Any, Dict, List, Optional, Tuple
from src.shapes import process_shapes
from src.common import get_all_feed_dates
from src.download import download_feed_from_url
from src.logger import get_logger
from src.report_writer import write_stop_json, write_stop_protobuf
from src.routes import load_routes
from src.services import get_active_services
from src.stop_times import get_stops_for_trips, StopTime
from src.stops import get_all_stops, get_all_stops_by_code, get_numeric_code
from src.street_name import get_street_name, normalise_stop_name
from src.trips import get_trips_for_services, TripLine
logger = get_logger("stop_report")
def parse_args():
parser = argparse.ArgumentParser(
description="Generate stop-based JSON reports for a date or date range."
)
parser.add_argument(
"--output-dir",
type=str,
default="./output/",
help="Directory to write reports to (default: ./output/)",
)
parser.add_argument("--feed-dir", type=str,
help="Path to the feed directory")
parser.add_argument(
"--feed-url",
type=str,
help="URL to download the GTFS feed from (if not using local feed directory)",
)
parser.add_argument(
"--force-download",
action="store_true",
help="Force download even if the feed hasn't been modified (only applies when using --feed-url)",
)
args = parser.parse_args()
if args.feed_dir and args.feed_url:
parser.error("Specify either --feed-dir or --feed-url, not both.")
if not args.feed_dir and not args.feed_url:
parser.error(
"You must specify either a path to the existing feed (unzipped) or a URL to download the GTFS feed from."
)
if args.feed_dir and not os.path.exists(args.feed_dir):
parser.error(f"Feed directory does not exist: {args.feed_dir}")
return args
def time_to_seconds(time_str: str) -> int:
"""
Convert HH:MM:SS to seconds since midnight.
Handles GTFS times that can exceed 24 hours (e.g., 25:30:00 for 1:30 AM next day).
"""
if not time_str:
return 0
parts = time_str.split(":")
if len(parts) != 3:
return 0
try:
hours, minutes, seconds = map(int, parts)
return hours * 3600 + minutes * 60 + seconds
except ValueError:
return 0
def normalize_gtfs_time(time_str: str) -> str:
"""
Normalize GTFS time format to standard HH:MM:SS (0-23 hours).
Converts times like 25:30:00 to 01:30:00.
Args:
time_str: Time in HH:MM:SS format, possibly with hours >= 24
Returns:
Normalized time string in HH:MM:SS format
"""
if not time_str:
return time_str
parts = time_str.split(":")
if len(parts) != 3:
return time_str
try:
hours, minutes, seconds = map(int, parts)
normalized_hours = hours % 24
return f"{normalized_hours:02d}:{minutes:02d}:{seconds:02d}"
except ValueError:
return time_str
def format_gtfs_time(time_str: str) -> str:
"""
Format GTFS time to HH:MM:SS, preserving hours >= 24.
"""
if not time_str:
return time_str
parts = time_str.split(":")
if len(parts) != 3:
return time_str
try:
hours, minutes, seconds = map(int, parts)
return f"{hours:02d}:{minutes:02d}:{seconds:02d}"
except ValueError:
return time_str
def is_next_day_service(time_str: str) -> bool:
"""
Check if a GTFS time represents a service on the next day (hours >= 24).
Args:
time_str: Time in HH:MM:SS format
Returns:
True if the time is >= 24:00:00, False otherwise
"""
if not time_str:
return False
parts = time_str.split(":")
if len(parts) != 3:
return False
try:
hours = int(parts[0])
return hours >= 24
except ValueError:
return False
def parse_trip_id_components(trip_id: str) -> Optional[Tuple[str, str, int]]:
"""
Parse a trip ID in format XXXYYY-Z or XXXYYY_Z where:
- XXX = line number (e.g., 003)
- YYY = shift/internal ID (e.g., 001)
- Z = trip number (e.g., 12)
Supported formats:
1. ..._XXXYYY_Z (e.g. "C1 01SNA00_001001_18")
2. ..._XXXYYY-Z (e.g. "VIGO_20241122_003001-12")
Returns tuple of (line, shift_id, trip_number) or None if parsing fails.
"""
try:
parts = trip_id.split("_")
if len(parts) < 2:
return None
# Try format 1: ..._XXXYYY_Z
# Check if second to last part is 6 digits (XXXYYY) and last part is numeric
if len(parts) >= 2:
shift_part = parts[-2]
trip_num_str = parts[-1]
if len(shift_part) == 6 and shift_part.isdigit() and trip_num_str.isdigit():
line = shift_part[:3]
shift_id = shift_part[3:6]
trip_number = int(trip_num_str)
return (line, shift_id, trip_number)
# Try format 2: ..._XXXYYY-Z
# The trip ID is the last part in format XXXYYY-Z
trip_part = parts[-1]
if "-" in trip_part:
shift_part, trip_num_str = trip_part.split("-", 1)
# shift_part should be 6 digits: XXXYYY
if len(shift_part) == 6 and shift_part.isdigit():
line = shift_part[:3] # First 3 digits
shift_id = shift_part[3:6] # Next 3 digits
trip_number = int(trip_num_str)
return (line, shift_id, trip_number)
return None
except (ValueError, IndexError):
return None
def build_trip_previous_shape_map(
trips: Dict[str, List[TripLine]],
stops_for_all_trips: Dict[str, List[StopTime]],
) -> Dict[str, Optional[str]]:
"""
Build a mapping from trip_id to previous_trip_shape_id.
Links trips based on trip ID structure (XXXYYY-Z) where trips with the same
XXX (line) and YYY (shift) and sequential Z (trip numbers) are connected
if the terminus of trip N matches the start of trip N+1.
Args:
trips: Dictionary of service_id -> list of trips
stops_for_all_trips: Dictionary of trip_id -> list of stop times
Returns:
Dictionary mapping trip_id to previous_trip_shape_id (or None)
"""
trip_previous_shape: Dict[str, Optional[str]] = {}
# Collect all trips across all services
all_trips_list: List[TripLine] = []
for trip_list in trips.values():
all_trips_list.extend(trip_list)
# Group trips by shift ID (line + shift combination)
trips_by_shift: Dict[str, List[Tuple[TripLine, int, str, str]]] = {}
for trip in all_trips_list:
parsed = parse_trip_id_components(trip.trip_id)
if not parsed:
continue
line, shift_id, trip_number = parsed
shift_key = f"{line}{shift_id}"
trip_stops = stops_for_all_trips.get(trip.trip_id)
if not trip_stops or len(trip_stops) < 2:
continue
first_stop = trip_stops[0]
last_stop = trip_stops[-1]
if shift_key not in trips_by_shift:
trips_by_shift[shift_key] = []
trips_by_shift[shift_key].append((
trip,
trip_number,
first_stop.stop_id,
last_stop.stop_id
))
# For each shift, sort trips by trip number and link consecutive trips
for shift_key, shift_trips in trips_by_shift.items():
# Sort by trip number
shift_trips.sort(key=lambda x: x[1])
# Link consecutive trips if their stops match
for i in range(1, len(shift_trips)):
current_trip, current_num, current_start_stop, _ = shift_trips[i]
prev_trip, prev_num, _, prev_end_stop = shift_trips[i - 1]
# Check if trips are consecutive (trip numbers differ by 1),
# if previous trip's terminus matches current trip's start,
# and if both trips have valid shape IDs
if (current_num == prev_num + 1 and
prev_end_stop == current_start_stop and
prev_trip.shape_id and
current_trip.shape_id):
trip_previous_shape[current_trip.trip_id] = prev_trip.shape_id
return trip_previous_shape
def get_stop_arrivals(feed_dir: str, date: str) -> Dict[str, List[Dict[str, Any]]]:
"""
Process trips for the given date and organize stop arrivals.
Also includes night services from the previous day (times >= 24:00:00).
Args:
feed_dir: Path to the GTFS feed directory
date: Date in YYYY-MM-DD format
Returns:
Dictionary mapping stop_code to lists of arrival information.
"""
from datetime import datetime, timedelta
stops = get_all_stops(feed_dir)
logger.info(f"Found {len(stops)} stops in the feed.")
active_services = get_active_services(feed_dir, date)
if not active_services:
logger.info("No active services found for the given date.")
logger.info(
f"Found {len(active_services)} active services for date {date}.")
# Also get services from the previous day to include night services (times >= 24:00)
prev_date = (datetime.strptime(date, "%Y-%m-%d") -
timedelta(days=1)).strftime("%Y-%m-%d")
prev_services = get_active_services(feed_dir, prev_date)
logger.info(
f"Found {len(prev_services)} active services for previous date {prev_date} (for night services).")
all_services = list(set(active_services + prev_services))
if not all_services:
logger.info("No active services found for current or previous date.")
return {}
trips = get_trips_for_services(feed_dir, all_services)
total_trip_count = sum(len(trip_list) for trip_list in trips.values())
logger.info(f"Found {total_trip_count} trips for active services.")
# Get all trip IDs
all_trip_ids = [trip.trip_id for trip_list in trips.values()
for trip in trip_list]
# Get stops for all trips
stops_for_all_trips = get_stops_for_trips(feed_dir, all_trip_ids)
logger.info(f"Precomputed stops for {len(stops_for_all_trips)} trips.")
# Build mapping from trip_id to previous trip's shape_id
trip_previous_shape_map = build_trip_previous_shape_map(
trips, stops_for_all_trips)
logger.info(
f"Built previous trip shape mapping for {len(trip_previous_shape_map)} trips.")
# Load routes information
routes = load_routes(feed_dir)
logger.info(f"Loaded {len(routes)} routes from feed.")
# Create a reverse lookup from stop_id to stop_code
stop_id_to_code = {}
for stop_id, stop in stops.items():
if stop.stop_code:
stop_id_to_code[stop_id] = get_numeric_code(stop.stop_code)
# Organize data by stop_code
stop_arrivals = {}
active_services_set = set(active_services)
prev_services_set = set(prev_services)
for service_id, trip_list in trips.items():
is_active = service_id in active_services_set
is_prev = service_id in prev_services_set
if not is_active and not is_prev:
continue
for trip in trip_list:
# Get route information once per trip
route_info = routes.get(trip.route_id, {})
route_short_name = route_info.get("route_short_name", "")
trip_headsign = getattr(trip, "headsign", "") or ""
trip_id = trip.trip_id
# Get stop times for this trip
trip_stops = stops_for_all_trips.get(trip.trip_id, [])
if not trip_stops:
continue
# Pair stop_times with stop metadata once to avoid repeated lookups
trip_stop_pairs = []
stop_names = []
for stop_time in trip_stops:
stop = stops.get(stop_time.stop_id)
trip_stop_pairs.append((stop_time, stop))
stop_names.append(stop.stop_name if stop else "Unknown Stop")
# Memoize street names per stop name for this trip and build segments
street_cache: dict[str, str] = {}
segment_names: list[str] = []
stop_to_segment_idx: list[int] = []
previous_street: str | None = None
for name in stop_names:
street = street_cache.get(name)
if street is None:
street = get_street_name(name) or ""
street_cache[name] = street
if street != previous_street:
segment_names.append(street)
previous_street = street
stop_to_segment_idx.append(len(segment_names) - 1)
# Precompute future street transitions per segment
future_suffix_by_segment: list[tuple[str, ...]] = [
()] * len(segment_names)
future_tuple: tuple[str, ...] = ()
for idx in range(len(segment_names) - 1, -1, -1):
future_suffix_by_segment[idx] = future_tuple
current_street = segment_names[idx]
future_tuple = (
(current_street,) + future_tuple
if current_street is not None
else future_tuple
)
segment_future_lists: dict[int, list[str]] = {}
first_stop_time, first_stop = trip_stop_pairs[0]
last_stop_time, last_stop = trip_stop_pairs[-1]
starting_stop_name = first_stop.stop_name if first_stop else "Unknown Stop"
terminus_stop_name = last_stop.stop_name if last_stop else "Unknown Stop"
starting_code = get_numeric_code(
first_stop.stop_code) if first_stop else ""
terminus_code = get_numeric_code(
last_stop.stop_code) if last_stop else ""
starting_name = normalise_stop_name(starting_stop_name)
terminus_name = normalise_stop_name(terminus_stop_name)
starting_time = first_stop_time.departure_time
terminus_time = last_stop_time.arrival_time
# Determine processing passes for this trip
passes = []
if is_active:
passes.append("current")
if is_prev:
passes.append("previous")
for mode in passes:
is_current_mode = (mode == "current")
for i, (stop_time, _) in enumerate(trip_stop_pairs):
stop_code = stop_id_to_code.get(stop_time.stop_id)
if not stop_code:
continue # Skip stops without a code
dep_time = stop_time.departure_time
if not is_current_mode:
# Previous day service: only include if calling_time >= 24:00:00 (night services rolling to this day)
if not is_next_day_service(dep_time):
continue
# Normalize times for display on current day (e.g. 25:30 -> 01:30)
final_starting_time = normalize_gtfs_time(
starting_time)
final_calling_time = normalize_gtfs_time(dep_time)
final_terminus_time = normalize_gtfs_time(
terminus_time)
# SSM should be small (early morning)
final_calling_ssm = time_to_seconds(final_calling_time)
else:
# Current day service: include ALL times
# Keep times as is (e.g. 25:30 stays 25:30)
final_starting_time = format_gtfs_time(starting_time)
final_calling_time = format_gtfs_time(dep_time)
final_terminus_time = format_gtfs_time(terminus_time)
# SSM should be large if > 24:00
final_calling_ssm = time_to_seconds(dep_time)
if stop_code not in stop_arrivals:
stop_arrivals[stop_code] = []
if segment_names:
segment_idx = stop_to_segment_idx[i]
if segment_idx not in segment_future_lists:
segment_future_lists[segment_idx] = list(
future_suffix_by_segment[segment_idx]
)
next_streets = segment_future_lists[segment_idx].copy()
else:
next_streets = []
trip_id_fmt = "_".join(trip_id.split("_")[1:3])
# Get previous trip shape_id if available
previous_trip_shape_id = trip_previous_shape_map.get(
trip_id, "")
stop_arrivals[stop_code].append(
{
"service_id": service_id.split("_")[1],
"trip_id": trip_id_fmt,
"line": route_short_name,
"route": trip_headsign,
"shape_id": getattr(trip, "shape_id", ""),
"stop_sequence": stop_time.stop_sequence,
"shape_dist_traveled": getattr(
stop_time, "shape_dist_traveled", 0
),
"next_streets": next_streets,
"starting_code": starting_code,
"starting_name": starting_name,
"starting_time": final_starting_time,
"calling_time": final_calling_time,
"calling_ssm": final_calling_ssm,
"terminus_code": terminus_code,
"terminus_name": terminus_name,
"terminus_time": final_terminus_time,
"previous_trip_shape_id": previous_trip_shape_id,
}
)
# Sort each stop's arrivals by arrival time
for stop_code in stop_arrivals:
# Filter out entries with None arrival_seconds
stop_arrivals[stop_code] = [
item for item in stop_arrivals[stop_code] if item["calling_ssm"] is not None
]
stop_arrivals[stop_code].sort(key=lambda x: x["calling_ssm"])
return stop_arrivals
def process_date(
feed_dir: str, date: str, output_dir: str
) -> tuple[str, Dict[str, int]]:
"""
Process a single date and write its stop JSON files.
Returns summary data for index generation.
"""
logger = get_logger(f"stop_report_{date}")
try:
logger.info(f"Starting stop report generation for date {date}")
stops_by_code = get_all_stops_by_code(feed_dir)
# Get all stop arrivals for the current date
stop_arrivals = get_stop_arrivals(feed_dir, date)
if not stop_arrivals:
logger.warning(f"No stop arrivals found for date {date}")
return date, {}
logger.info(
f"Writing stop reports for {len(stop_arrivals)} stops for date {date}"
)
# Write individual stop JSON files
writing_start_time = time.perf_counter()
for stop_code, arrivals in stop_arrivals.items():
write_stop_json(output_dir, date, stop_code, arrivals)
writing_end_time = time.perf_counter()
writing_elapsed = writing_end_time - writing_start_time
logger.info(
f"Finished writing stop JSON reports for date {date} in {writing_elapsed:.2f}s"
)
# Write individual stop JSON files
writing_start_time = time.perf_counter()
for stop_code, arrivals in stop_arrivals.items():
stop_by_code = stops_by_code.get(stop_code)
if stop_by_code is not None:
write_stop_protobuf(
output_dir,
date,
stop_code,
arrivals,
stop_by_code.stop_25829_x or 0.0,
stop_by_code.stop_25829_y or 0.0,
)
writing_end_time = time.perf_counter()
writing_elapsed = writing_end_time - writing_start_time
logger.info(
f"Finished writing stop protobuf reports for date {date} in {writing_elapsed:.2f}s"
)
logger.info(f"Processed {len(stop_arrivals)} stops for date {date}")
stop_summary = {
stop_code: len(arrivals) for stop_code, arrivals in stop_arrivals.items()
}
return date, stop_summary
except Exception as e:
logger.error(f"Error processing date {date}: {e}")
raise
def main():
args = parse_args()
output_dir = args.output_dir
feed_url = args.feed_url
if not feed_url:
feed_dir = args.feed_dir
else:
logger.info(f"Downloading GTFS feed from {feed_url}...")
feed_dir = download_feed_from_url(
feed_url, output_dir, args.force_download)
if feed_dir is None:
logger.info("Download was skipped (feed not modified). Exiting.")
return
all_dates = get_all_feed_dates(feed_dir)
if not all_dates:
logger.error("No valid dates found in feed.")
return
date_list = all_dates
# Ensure date_list is not empty before processing
if not date_list:
logger.error("No valid dates to process.")
return
logger.info(f"Processing {len(date_list)} dates")
# Dictionary to store summary data for index files
all_stops_summary = {}
for date in date_list:
_, stop_summary = process_date(feed_dir, date, output_dir)
all_stops_summary[date] = stop_summary
logger.info(
"Finished processing all dates. Beginning with shape transformation.")
# Process shapes, converting each coordinate to EPSG:25829 and saving as Protobuf
process_shapes(feed_dir, output_dir)
logger.info("Finished processing shapes.")
if feed_url:
if os.path.exists(feed_dir):
shutil.rmtree(feed_dir)
logger.info(f"Removed temporary feed directory: {feed_dir}")
if __name__ == "__main__":
try:
main()
except Exception as e:
logger = get_logger("stop_report")
logger.critical(f"An unexpected error occurred: {e}", exc_info=True)
traceback.print_exc()
sys.exit(1)
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