def setUp(self):
super(SkillDomainUnitTests, self).setUp()
skill_contents = skill_domain.SkillContents(
state_domain.SubtitledHtml(
'1', '<p>Explanation</p>'), [
state_domain.SubtitledHtml('2', '<p>Example 1</p>')],
state_domain.RecordedVoiceovers.from_dict(
{'voiceovers_mapping': {'1': {}, '2': {}}}),
state_domain.WrittenTranslations.from_dict(
{'translations_mapping': {'1': {}, '2': {}}}))
misconceptions = [skill_domain.Misconception(
self.MISCONCEPTION_ID, 'name', '<p>notes</p>',
'<p>default_feedback</p>')]
rubrics = [
skill_domain.Rubric(
constants.SKILL_DIFFICULTIES[0], '<p>Explanation 1</p>'),
skill_domain.Rubric(
constants.SKILL_DIFFICULTIES[1], '<p>Explanation 2</p>'),
skill_domain.Rubric(
constants.SKILL_DIFFICULTIES[2], '<p>Explanation 3</p>')]
self.skill = skill_domain.Skill(
self.SKILL_ID, 'Description', misconceptions, rubrics,
skill_contents, feconf.CURRENT_MISCONCEPTIONS_SCHEMA_VERSION,
feconf.CURRENT_RUBRIC_SCHEMA_VERSION,
feconf.CURRENT_SKILL_CONTENTS_SCHEMA_VERSION, 'en', 0, 1,
None, False
)
def get_skill_from_model(skill_model):
"""Returns a skill domain object given a skill model loaded
from the datastore.
Args:
skill_model: SkillModel. The skill model loaded from the
datastore.
Returns:
skill. A Skill domain object corresponding to the given
skill model.
"""
# Ensure the original skill model does not get altered.
versioned_skill_contents = {
'schema_version': skill_model.skill_contents_schema_version,
'skill_contents': copy.deepcopy(skill_model.skill_contents)
}
versioned_misconceptions = {
'schema_version': skill_model.misconceptions_schema_version,
'misconceptions': copy.deepcopy(skill_model.misconceptions)
}
versioned_rubrics = {
'schema_version': skill_model.rubric_schema_version,
'rubrics': copy.deepcopy(skill_model.rubrics)
}
# Migrate the skill if it is not using the latest schema version.
if (skill_model.skill_contents_schema_version !=
feconf.CURRENT_SKILL_CONTENTS_SCHEMA_VERSION):
_migrate_skill_contents_to_latest_schema(versioned_skill_contents)
if (skill_model.misconceptions_schema_version !=
feconf.CURRENT_MISCONCEPTIONS_SCHEMA_VERSION):
_migrate_misconceptions_to_latest_schema(versioned_misconceptions)
if (skill_model.rubric_schema_version !=
feconf.CURRENT_RUBRIC_SCHEMA_VERSION):
_migrate_rubrics_to_latest_schema(versioned_rubrics)
return skill_domain.Skill(
skill_model.id, skill_model.description,
[
skill_domain.Misconception.from_dict(misconception)
for misconception in versioned_misconceptions['misconceptions']
], [
skill_domain.Rubric.from_dict(rubric)
for rubric in versioned_rubrics['rubrics']
], skill_domain.SkillContents.from_dict(
versioned_skill_contents['skill_contents']),
versioned_misconceptions['schema_version'],
versioned_rubrics['schema_version'],
versioned_skill_contents['schema_version'],
skill_model.language_code,
skill_model.version, skill_model.next_misconception_id,
skill_model.superseding_skill_id, skill_model.all_questions_merged,
skill_model.prerequisite_skill_ids, skill_model.created_on,
skill_model.last_updated)
def setUp(self):
super(SkillDomainUnitTests, self).setUp()
skill_contents = skill_domain.SkillContents(
'Explanation', ['Example 1'])
misconceptions = [skill_domain.Misconception(
self.MISCONCEPTION_ID, 'name', 'notes', 'default_feedback')]
self.skill = skill_domain.Skill(
self.SKILL_ID, 'Description', misconceptions,
skill_contents, feconf.CURRENT_MISCONCEPTIONS_SCHEMA_VERSION,
feconf.CURRENT_SKILL_CONTENTS_SCHEMA_VERSION, 'en', 0
)
def get_skill_from_model(skill_model, run_conversion=True):
"""Returns a skill domain object given a skill model loaded
from the datastore.
Args:
skill_model: SkillModel. The skill model loaded from the
datastore.
run_conversion: bool. If true, the the skill's schema version will
be checked against the current schema version. If they do not match,
the skill will be automatically updated to the latest schema
version.
Returns:
skill. A Skill domain object corresponding to the given
skill model.
"""
# Ensure the original skill model does not get altered.
versioned_skill_contents = {
'schema_version': skill_model.skill_contents_schema_version,
'skill_contents': copy.deepcopy(skill_model.skill_contents)
}
versioned_misconceptions = {
'schema_version': skill_model.misconceptions_schema_version,
'misconceptions': copy.deepcopy(skill_model.misconceptions)
}
# Migrate the skill if it is not using the latest schema version.
if (run_conversion and skill_model.skill_contents_schema_version !=
feconf.CURRENT_SKILL_CONTENTS_SCHEMA_VERSION):
_migrate_skill_contents_to_latest_schema(versioned_skill_contents)
if (run_conversion and skill_model.misconceptions_schema_version !=
feconf.CURRENT_MISCONCEPTIONS_SCHEMA_VERSION):
_migrate_misconceptions_to_latest_schema(versioned_misconceptions)
return skill_domain.Skill(
skill_model.id, skill_model.description,
[
skill_domain.Misconception.from_dict(misconception)
for misconception in versioned_misconceptions['misconceptions']
], skill_domain.SkillContents.from_dict(
versioned_skill_contents['skill_contents']),
versioned_misconceptions['schema_version'],
versioned_skill_contents['schema_version'],
skill_model.language_code,
skill_model.version, skill_model.next_misconception_id,
skill_model.superseding_skill_id, skill_model.all_questions_merged,
skill_model.created_on, skill_model.last_updated)
def setUp(self):
super(SkillDomainUnitTests, self).setUp()
skill_contents = skill_domain.SkillContents(
state_domain.SubtitledHtml(
'1', 'Explanation'), [
state_domain.SubtitledHtml('2', 'Example 1')], {})
misconceptions = [skill_domain.Misconception(
self.MISCONCEPTION_ID, 'name', 'notes', 'default_feedback')]
self.skill = skill_domain.Skill(
self.SKILL_ID, 'Description', misconceptions,
skill_contents, feconf.CURRENT_MISCONCEPTIONS_SCHEMA_VERSION,
feconf.CURRENT_SKILL_CONTENTS_SCHEMA_VERSION, 'en', 0, 1,
None, False
)
def test_job_when_skills_have_math_rich_text_components_with_svgs(self):
valid_html_1 = (
'<oppia-noninteractive-math math_content-with-value="{&q'
'uot;raw_latex&quot;: &quot;(x - a_1)(x - a_2)(x - a'
'_3)...(x - a_n-1)(x - a_n)&quot;, &quot;svg_filenam'
'e&quot;: &quot;file1.svg&quot;}"></oppia-noninte'
'ractive-math>'
)
valid_html_2 = (
'<oppia-noninteractive-math math_content-with-value="{&'
'quot;raw_latex&quot;: &quot;+,+,+,+&quot;, &'
'quot;svg_filename&quot;: &quot;file2.svg&quot;}">'
'</oppia-noninteractive-math>'
)
example_1 = skill_domain.WorkedExample(
state_domain.SubtitledHtml('2', valid_html_1),
state_domain.SubtitledHtml('3', '<p>Example Explanation 1</p>')
)
skill_contents1 = skill_domain.SkillContents(
state_domain.SubtitledHtml(
'1', '<p>Explanation</p>'), [example_1],
state_domain.RecordedVoiceovers.from_dict({
'voiceovers_mapping': {
'1': {}, '2': {}, '3': {}
}
}),
state_domain.WrittenTranslations.from_dict({
'translations_mapping': {
'1': {}, '2': {}, '3': {}
}
})
)
misconceptions1 = [skill_domain.Misconception(
0, 'name', '<p>misconception html1</p>',
'<p>misconception html2</p>', True)]
rubrics1 = [
skill_domain.Rubric(
constants.SKILL_DIFFICULTIES[0], [valid_html_2]),
skill_domain.Rubric(
constants.SKILL_DIFFICULTIES[1], ['<p>Explanation 2</p>']),
skill_domain.Rubric(
constants.SKILL_DIFFICULTIES[2], ['<p>Explanation 3</p>'])]
skill1 = skill_domain.Skill(
'skill_id1', 'Description', misconceptions1, rubrics1,
skill_contents1, feconf.CURRENT_MISCONCEPTIONS_SCHEMA_VERSION,
feconf.CURRENT_RUBRIC_SCHEMA_VERSION,
feconf.CURRENT_SKILL_CONTENTS_SCHEMA_VERSION, 'en', 0, 1,
None, False, ['skill_id_2']
)
skill_services.save_new_skill(self.albert_id, skill1)
job_id = (
skill_jobs_one_off.SkillMathRteAuditOneOffJob.create_new())
skill_jobs_one_off.SkillMathRteAuditOneOffJob.enqueue(job_id)
self.process_and_flush_pending_tasks()
output = skill_jobs_one_off.SkillMathRteAuditOneOffJob.get_output(
job_id)
overall_result = ast.literal_eval(output[0])
expected_skill1_info = {
'skill_id': 'skill_id1',
'latex_strings_with_svg': [
'(x - a_1)(x - a_2)(x - a_3)...(x - a_n-1)(x - a_n)', '+,+,+,+']
}
skill_latex_info = overall_result[1]
self.assertEqual(skill_latex_info[0], expected_skill1_info)
