instructure/canvas-lms · error · DataFormatError

The file is empty or does not contain valid assessment data.

Error message

The file is empty or does not contain valid assessment data.

What it means

RubricAssessmentImport#process_assessments raises DataFormatError when the parsed CSV yields no assessments by student — meaning the uploaded attachment produced zero valid rows (empty file or content the RubricAssessmentCSVImporter could not interpret).

Solutions

1. Download the provided assessment CSV template and populate it without changing header names
2. Ensure the file is a real comma-separated CSV (re-save from the spreadsheet app as 'CSV UTF-8')
3. Verify the file contains at least one data row with a valid student ID and scores
4. Check that the student IDs in the file exist in the course (also avoids error 487)

Example fix

// before
import_file(my_export.xlsx)
// after
csv = File.read("assessments.csv") # headers: student_id, criterion_id, points, comments
csv += "12345,Criterion1,10,good work\n" if csv.lines.size <= 1

csv = CSV.read(uploaded_path, headers: true)
raise "file has no data rows" if csv.empty?
raise "missing required headers" unless (csv.headers & REQUIRED_HEADERS) == REQUIRED_HEADERS

begin
  import.process
rescue DataFormatError => e
  flash[:error] = e.message
end

When it happens

Trigger: Uploading an empty CSV, a file with only headers, a wrong file type (e.g. xlsx saved with .csv extension but wrong encoding/content), or a CSV whose columns do not match the expected assessment format so the importer returns an empty hash.

Common situations: Users exporting from a spreadsheet but exporting the wrong sheet; CSV with wrong delimiter (semicolon vs comma); template columns renamed or reordered; uploading the rubric CSV instead of the assessments CSV.

Understand the failure class

Background: EmptyResultError / "no results found": when an API or scraper succeeds but returns zero rows — this error's family across 9 libraries.

Related errors

• Missing 'Rubric Name' in some rows.
• The file is empty or does not contain valid rubric data.
• Friendly description is too long (maximum is 255 characters)
• Invalid fields after ratings
• Invalid fields

AI-assisted analysis of instructure/canvas-lms@1c9f0bb801 (2026-09-15). Data as JSON: /api/errors/c05b832577bceef5. Report an issue: GitHub.

Appendix: source

Thrown at app/models/rubric_assessment_import.rb:117

    rescue => e
      ErrorReport.log_exception("rubric_assessments_import", e)
      update!(error_count: 1, error_data: [{ message: I18n.t("An error occurred while importing rubrics."), exception: e.message }])
      track_error
      job_failed!
    end
  end

  def track_error
    InstStatsd::Statsd.distributed_increment("#{assignment.class.to_s.downcase}.rubrics.csv_imported_with_error")
  end

  def process_assessments
    error_data = []

    rubric_association = assignment.rubric_association
    rubric = rubric_association.rubric
    assessments_by_student = RubricAssessmentCSVImporter.new(attachment, rubric, rubric_association).parse
    raise DataFormatError, I18n.t("The file is empty or does not contain valid assessment data.") if assessments_by_student.empty?

    total_assessments = assessments_by_student.keys.count

    students = User.where(id: assessments_by_student.keys).index_by(&:id)
    student_submissions = assignment.submissions.where(user_id: students.keys).index_by(&:user_id)

    assessments_by_student.each_with_index do |(student_id, assessment), student_index|
      student_to_assess = students[student_id.to_i]

      raise DataFormatError, I18n.t("Student with ID %{student_id} not found.", student_id:) unless student_to_assess
      raise UnauthorizedError unless rubric_association.user_can_assess_for?(assessor: user, assessee: student_to_assess)

      assessment = assessment.to_h do |criterion|
        [:"criterion_#{criterion[:id]}",
         {
           points: criterion[:points],
           comments: criterion[:comments],
           description: criterion[:rating]

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