GTFS Schedule Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 7.1.0 at 2026-01-23T16:35:42Z,
for the dataset file:///shared/petaluma-transit.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included

Feed Info

Publisher Name:
Connexionz Ltd
Feed Email:
N/A
Feed Language:
English
Feed Start Date:
2026-01-19
Feed End Date:
2027-12-31

Files included

  1. agency.txt
  2. calendar.txt
  3. calendar_dates.txt
  4. fare_attributes.txt
  5. fare_leg_rules.txt
  6. fare_media.txt
  7. fare_products.txt
  8. fare_transfer_rules.txt
  9. feed_info.txt
  10. rider_categories.txt
  11. routes.txt
  12. shapes.txt
  13. stop_times.txt
  14. stops.txt
  15. trips.txt

Counts

  • Agencies: 1
  • Blocks: 43
  • Routes: 12
  • Shapes: 35
  • Stops: 451
  • Trips: 951

Specification Compliance report

29 notices reported (2 errors, 4 warnings, 23 infos)

Notice Code Severity Total
fare_transfer_rule_missing_transfer_count ERROR 1

fare_transfer_rule_missing_transfer_count

A row from fare_transfer_rules.txt has from_leg_group_id equal to to_leg_group_id, but has no transfer_count specified.

Per the spec, transfer_count is required if the two leg group ids are equal.

You can see more about this notice here.

csvRowNumber (?) The row of the faulty record.
2
missing_required_column ERROR 1

missing_required_column

A required column is missing in the input file.

You can see more about this notice here.

filename (?) The name of the faulty file. fieldName (?) The name of the missing column.
"rider_categories.txt" "is_default_fare_category"
leading_or_trailing_whitespaces WARNING 1

leading_or_trailing_whitespaces

The value in CSV file has leading or trailing whitespaces.

This notice is emitted for values protected with double quotes since whitespaces for non-protected values are trimmed automatically by CSV parser.

The validator strips whitespaces from protected values. We do not see any use case when such a whitespace may be needed. On the other hand, some real-world feeds use trailing whitespaces for some values and omit them for the others. This is causing the largest problem when a primary key and a foreign key differ just by a whitespace: it is clear that they are intended to be the same, that is why we always strip whitespaces.

You can see more about this notice here.

filename (?) The name of the faulty file. csvRowNumber (?) The row of the faulty record. fieldName (?) Faulty record's field name. fieldValue (?) Faulty value.
"stops.txt" 451 "stop_name" " Wilson Avenue & Villa Street"
missing_feed_contact_email_and_url WARNING 1

missing_feed_contact_email_and_url

Best Practices for feed_info.txt suggest providing at least one of feed_contact_email and feed_contact_url.

You can see more about this notice here.

csvRowNumber (?) The row number of the validated record.
2
mixed_case_recommended_field WARNING 2

mixed_case_recommended_field

This field has customer-facing text and should use Mixed Case (should contain upper and lower case letters).

This field contains customer-facing text and should use Mixed Case (upper and lower case letters) to ensure good readability when displayed to riders. Avoid the use of abbreviations throughout the feed (e.g. St. for Street) unless a location is called by its abbreviated name (e.g. “JFK Airport”). Abbreviations may be problematic for accessibility by screen reader software and voice user interfaces.

Good examples:
Field Text Dataset
"Schwerin, Hauptbahnhof" Verkehrsverbund Berlin-Brandenburg
"Red Hook/Atlantic Basin" NYC Ferry
"Campo Grande Norte" Carris
Bad examples:
Field Text
"GALLERIA MALL"
"3427 GG 17"
"21 Clark Rd Est"

You can see more about this notice here.

filename (?) Name of the faulty file. fieldName (?) Name of the faulty field. fieldValue (?) Faulty value. csvRowNumber (?) The row number of the faulty record.
"routes.txt" "route_short_name" "20cc" 3
"routes.txt" "route_short_name" "20cw" 4
unknown_column INFO 23

unknown_column

A column name is unknown.

You can see more about this notice here.

filename (?) The name of the faulty file. fieldName (?) The name of the unknown column. index (?) The index of the faulty column.
"fare_leg_rules.txt" "fare_leg_name" 2
"fare_leg_rules.txt" "from_timeframe_id" 6
"fare_leg_rules.txt" "to_timeframe_id" 7
"fare_leg_rules.txt" "min_distance" 8
"fare_leg_rules.txt" "max_distance" 9
"fare_leg_rules.txt" "distance_type" 10
"fare_leg_rules.txt" "service_id" 11
"fare_products.txt" "bundle_amount" 5
"fare_products.txt" "duration_start" 6
"fare_products.txt" "duration_amount" 7
"fare_products.txt" "duration_unit" 8
"fare_products.txt" "duration_type" 9
"fare_products.txt" "offset_amount" 10
"fare_products.txt" "offset_unit" 11
"fare_products.txt" "service_id" 12
"fare_products.txt" "timeframe_id" 13
"fare_products.txt" "timeframe_type" 14
"fare_products.txt" "cap_required" 15
"fare_products.txt" "min_amount" 17
"fare_products.txt" "max_amount" 18
"fare_transfer_rules.txt" "spanning_limit" 3
"rider_categories.txt" "min_age" 3
"rider_categories.txt" "max_age" 4