GTFS Schedule Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 5.0.1 at 2024-06-08T07:42:52Z,
for the dataset file:///tmp/1_in.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included

Feed Info

Publisher Name:
Transdev Pays de la Loire
Publisher URL:
https://www.transdev-paysdelaloire.com/open-data
Feed Language:
French
Feed Start Date:
2023-01-02
Feed End Date:
2024-12-31

Files included

  1. agency.txt
  2. calendar.txt
  3. calendar_dates.txt
  4. fare_attributes.txt
  5. fare_rules.txt
  6. feed_info.txt
  7. routes.txt
  8. shapes.txt
  9. stop_times.txt
  10. stops.txt
  11. trips.txt

Counts

  • Agencies: 1
  • Blocks: 3
  • Routes: 3
  • Shapes: 27
  • Stops: 30
  • Trips: 126

GTFS Features included (?) GTFS features provide a standardized vocabulary to define and describe features that are officially adopted in GTFS.

Fares V1ShapesFeed InformationRoute ColorsHeadsignsWheelchair AccessibilityBikes AllowanceLocation Types

Specification Compliance report

110 notices reported (0 errors, 110 warnings, 0 infos)

Notice Code Severity Total
equal_shape_distance_diff_coordinates_distance_below_threshold WARNING 7

equal_shape_distance_diff_coordinates_distance_below_threshold

Two consecutive points have equal shape_dist_traveled and different lat/lon coordinates in shapes.txt and the distance between the two points is less than 1.11m.

When sorted by shape.shape_pt_sequence, the values for shape_dist_traveled must increase along a shape. Two consecutive points with equal values for shape_dist_traveled and small difference of coordinates (less than 1.11 m distance) result in a warning.

You can see more about this notice here.

shapeId (?) The id of the faulty shape. csvRowNumber (?) The row number from `shapes.txt`. shapeDistTraveled (?) The faulty record's `shape_dist_traveled` value. shapePtSequence (?) The faulty record's `shapes.shape_pt_sequence`. prevCsvRowNumber (?) The row number from `shapes.txt` of the previous shape point. prevShapeDistTraveled (?) The previous shape point's `shape_dist_traveled` value. prevShapePtSequence (?) The previous record's `shapes.shape_pt_sequence`. actualDistanceBetweenShapePoints (?) Actual distance traveled along the shape from the first shape point to the previous shape point.
"002R15AL47" 7792 0.0 2 7791 0.0 1 0.44650796615832167
"003R09AL4724" 12320 4334.0 162 12319 4334.0 161 0.24076227457941113
"002R14AL47" 7613 9281.0 293 7612 9281.0 292 0.019985179343997392
"003R09AL47" 11834 4334.0 162 11833 4334.0 161 0.24076227457941113
"003R11AL47" 12806 4334.0 162 12805 4334.0 161 0.205745691612316
"003R11AL47" 12807 4334.0 163 12806 4334.0 162 0.44650796615832167
"001A01AL47" 537 11019.0 536 536 11019.0 535 0.286564920848721
expired_calendar WARNING 8

expired_calendar

Dataset should not contain date ranges for services that have already expired.

This warning takes into account the calendar_dates.txt file as well as the calendar.txt file.

You can see more about this notice here.

csvRowNumber (?) The row of the faulty record. serviceId (?) The service id of the faulty record.
2 "1"
3 "2"
4 "3"
10 "25"
5 "4"
11 "26"
12 "27"
13 "28"
missing_recommended_column WARNING 1

missing_recommended_column

A recommended 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.
"stop_times.txt" "timepoint"
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.
"agency.txt" "agency_name" "illygo" 2
"stops.txt" "stop_name" "giratoire allée du perquoi" 27
trip_coverage_not_active_for_next7_days WARNING 1

trip_coverage_not_active_for_next7_days

Trips data should be valid for at least the next seven days.

This notice is triggered if the date range where a significant number of trips are running ends in less than 7 days.

You can see more about this notice here.

currentDate (?) Current date (YYYYMMDD format). serviceWindowStartDate (?) The start date of the majority service window. serviceWindowEndDate (?) The end date of the majority service window.
"20240608" "20230104" "20231227"
trip_distance_exceeds_shape_distance_below_threshold WARNING 91

trip_distance_exceeds_shape_distance_below_threshold

The distance between the last shape point and last stop point is less than the 11.1m threshold.

You can see more about this notice here.

Only the first 50 of 91 affected records are displayed below.

tripId (?) The faulty record's trip id. shapeId (?) The faulty record's shape id. maxTripDistanceTraveled (?) The faulty record's trip max distance traveled. maxShapeDistanceTraveled (?) The faulty record's shape max distance traveled. geoDistanceToShape (?) The distance in meters between the shape and the stop.
"8-15335620645" "001A01AL47" 11331.0 11329.0 5.347238488287024
"8-15335620646" "001A01AL47" 11331.0 11329.0 5.347238488287024
"8-15335620647" "001A01AL47" 11331.0 11329.0 5.347238488287024
"8-15335620648" "001A01AL47" 11331.0 11329.0 5.347238488287024
"8-15335620649" "001A01AL47" 11331.0 11329.0 5.347238488287024
"8-15436414982" "002R08AL47" 14412.0 14411.0 2.5752498852533496
"8-15453782032" "003A02AL47" 23999.0 23994.0 3.812500407623922
"8-15436742667" "002R10AL47" 9777.0 9775.0 9.228998371266421
"8-15453913099" "003A04AL47" 16861.0 16846.0 3.812500407623922
"8-15437332481" "002A05AL471" 4572.0 4568.0 9.204066756002671
"8-15437266950" "002R12AL47" 14412.0 14411.0 2.5752498852533496
"8-15453782033" "003A02AL47" 23999.0 23994.0 3.812500407623922
"8-15436742668" "002R10AL47" 9777.0 9775.0 9.228998371266421
"8-15335686182" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686192" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335620650" "001A01AL47" 11331.0 11329.0 5.347238488287024
"8-15335620651" "001A01AL47" 11331.0 11329.0 5.347238488287024
"8-15436808203" "002R14AL47" 13858.0 13849.0 9.204066756002671
"8-15436677131" "002A07AL47" 13829.0 13819.0 5.347238488287024
"8-15453782034" "003A02AL47" 23999.0 23994.0 3.812500407623922
"8-15436808204" "002R14AL47" 13858.0 13849.0 9.204066756002671
"8-15436677132" "002A07AL47" 13829.0 13819.0 5.347238488287024
"8-15453913100" "003A04AL47" 16861.0 16846.0 3.812500407623922
"8-15335686184" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686185" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686193" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686187" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686194" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686189" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686195" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686191" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15335686196" "001R13AL47" 11388.0 11382.0 5.347238488287024
"8-15336734726" "001A01AL4724" 11377.0 11368.0 5.347238488287024
"8-15336734725" "001A01AL4724" 11377.0 11368.0 5.347238488287024
"8-15336734724" "001A01AL4724" 11377.0 11368.0 5.347238488287024
"8-15336734723" "001A01AL4724" 11377.0 11368.0 5.347238488287024
"8-15336734722" "001A01AL4724" 11377.0 11368.0 5.347238488287024
"8-15454044162" "003A02AL4724" 23999.0 23994.0 3.812500407623922
"8-15454109697" "003A04AL4724" 16861.0 16846.0 3.812500407623922
"8-15454240773" "003R11AL4724" 24001.0 23995.0 2.5752498852533496
"8-15437529089" "002A05AL4724" 4572.0 4568.0 9.204066756002671
"8-15454044161" "003A02AL4724" 23999.0 23994.0 3.812500407623922
"8-15454306309" "003A13AL4724" 18139.0 18124.0 3.812500407623922
"8-15336800262" "001R13AL4724" 11518.0 11509.0 5.347238488287024
"8-15336734721" "001A01AL4724" 11377.0 11368.0 5.347238488287024
"8-15454240772" "003R11AL4724" 24001.0 23995.0 2.5752498852533496
"8-15454044163" "003A02AL4724" 23999.0 23994.0 3.812500407623922
"8-15454109698" "003A04AL4724" 16861.0 16846.0 3.812500407623922
"8-15454240771" "003R11AL4724" 24001.0 23995.0 2.5752498852533496
"8-15336800261" "001R13AL4724" 11518.0 11509.0 5.347238488287024