Functional testing for frontend and API testing for all services

Usage for functional testing for frontend

• Tests will be automatically run by travis daily. It tests only finance-vix and gdp-uk core datasets.

  • If travis build fails, we can check it on travis logs
  • else, frontend works fine for the following tests

  property	test	output
  id	timestamp	timestamp
  name	dataset name	dataset name
  page_status	status code and description	status code and description
  page_title	page title	OK OR NOT OK
  dataset_title	dataset title	OK OR NOT OK
  readme	readme	OK OR NOT OK
  csv_links	all csv links	status code and description
  json_links	json links	status code and description
  zip_links	zip links	status code and description
  datapackage_json	datapackage.json	status code and description
  total_load_time	total loading time	in milliseconds
  script_laod_time	script loading time	in milliseconds
  layout_load_time	layouts loading time	in milliseconds
  tables	preview table	OK OR NOT OK
  graphs	graph	OK OR NOT OK

Usage for API testing for all services

Tests will be automatically run by travis daily. Environmental vairables to set up: DOMAIN - domain address, testing or production SPECSTORE - spectore API, testing or production API - API, testing or production AUTH_TOKEN - Authorization token AUTH_TOKEN_PERMISSION - Permission token for a service, in our case rawstore OWNERID - ownerid, in this test, we use examples

It tests API for the following services:

• specstore status
• specstore info
• specstore upload
• auth permission for a service
• auth check an authentication token validity
• auth change the username
• auth receive authorization public key
• metastore search
• metastore search events
• resolver username to userid
• bitstore(rawstore) get authorized upload URL
• bitstore(rawstore) get information regarding the datastore

Validation test

Validation test is located in test/validation.test.js, and it covers the following cases:

• small dataset
  • cause CSV to fail after validation
  • multiple resources
  • datasets that fail validation but not pipeline(duplicated row)
  • multiple errors per file
  • public(unlisted)
• big dataset
  • cause CSV to fail before validation
  • Different validation errors(invalid metadata and data)
• processing dataset by providing invalid flow.yml
• redirection dataset
  • private dataset
• all specstore statuses for above mentioned datasets