def test_update_l10n_metric_cron(self):
"""Verify the cron job creates the correct metric."""
l10n_kind = metric_kind(code=L10N_METRIC_CODE, save=True)
# Create the en-US document with an approved revision.
doc = document(save=True)
rev = revision(
document=doc,
is_approved=True,
save=True)
time.sleep(1)
# Create an es translation
es_doc = document(parent=doc, locale='es', save=True)
revision(
document=es_doc,
is_approved=True,
based_on=rev,
save=True)
# Run it and verify results.
# Value should be 100%
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(100, metrics[0].value)
# Update the en-US document
rev2 = revision(
document=doc,
is_approved=True,
save=True)
# Run it and verify results.
# Value should be 0%
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(0, metrics[0].value)
time.sleep(1)
# Create a pt-BR translation
ptBR_doc = document(parent=doc, locale='pt-BR', save=True)
revision(
document=ptBR_doc,
is_approved=True,
based_on=rev,
save=True)
# Run it and verify results.
# Value should be 50%
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(50, metrics[0].value)
def test_update_l10n_metric_cron(self, visits_by_locale, _get_top_docs):
"""Verify the cron job creates the correct metric."""
l10n_kind = metric_kind(code=L10N_METRIC_CODE, save=True)
# Create the en-US document with an approved revision.
doc = document(save=True)
rev = revision(
document=doc,
is_approved=True,
is_ready_for_localization=True,
save=True)
# Create an es translation that is up to date.
es_doc = document(parent=doc, locale='es', save=True)
revision(
document=es_doc,
is_approved=True,
based_on=rev,
save=True)
# Create a de translation without revisions.
document(parent=doc, locale='de', save=True)
# Mock some calls.
visits_by_locale.return_value = {
'en-US': 100,
'de': 20,
'es': 10,
'fr': 10,
}
_get_top_docs.return_value = [doc]
# Run it and verify results. Values sould be 25% (1/1 * 10/40).
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(25, metrics[0].value)
def test_update_l10n_metric_cron(self, visits_by_locale, _get_top_docs):
"""Verify the cron job creates the correct metric."""
l10n_kind = metric_kind(code=L10N_METRIC_CODE, save=True)
# Create the en-US document with an approved revision.
doc = document(save=True)
rev = revision(
document=doc, significance=MEDIUM_SIGNIFICANCE, is_approved=True, is_ready_for_localization=True, save=True
)
# Create an es translation that is up to date.
es_doc = document(parent=doc, locale="es", save=True)
revision(document=es_doc, is_approved=True, based_on=rev, save=True)
# Create a de translation without revisions.
document(parent=doc, locale="de", save=True)
# Mock some calls.
visits_by_locale.return_value = {"en-US": 50, "de": 20, "es": 25, "fr": 5}
_get_top_docs.return_value = [doc]
# Run it and verify results.
# Value should be 75% (1/1 * 25/100 + 1/1 * 50/100)
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(75, metrics[0].value)
# Create a new revision with TYPO_SIGNIFICANCE. It shouldn't
# affect the results.
revision(
document=doc, significance=TYPO_SIGNIFICANCE, is_approved=True, is_ready_for_localization=True, save=True
)
Metric.objects.all().delete()
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(75, metrics[0].value)
# Create a new revision with MEDIUM_SIGNIFICANCE. The coverage
# should now be 62% (0.5/1 * 25/100 + 1/1 * 50/100)
m1 = revision(
document=doc, significance=MEDIUM_SIGNIFICANCE, is_approved=True, is_ready_for_localization=True, save=True
)
Metric.objects.all().delete()
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(62, metrics[0].value)
# And another new revision with MEDIUM_SIGNIFICANCE makes the
# coverage 50% (1/1 * 50/100).
m2 = revision(
document=doc, significance=MEDIUM_SIGNIFICANCE, is_approved=True, is_ready_for_localization=True, save=True
)
Metric.objects.all().delete()
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(50, metrics[0].value)
# If we remove the two MEDIUM_SIGNIFICANCE revisions and add a
# MAJOR_SIGNIFICANCE revision, the coverage is 50% as well.
m1.delete()
m2.delete()
revision(
document=doc, significance=MAJOR_SIGNIFICANCE, is_approved=True, is_ready_for_localization=True, save=True
)
Metric.objects.all().delete()
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(50, metrics[0].value)
def test_update_l10n_metric_cron(self, visitors_by_locale, _get_top_docs):
"""Verify the cron job creates the correct metric."""
l10n_kind = metric_kind(code=L10N_METRIC_CODE, save=True)
# Create the en-US document with an approved revision.
doc = document(save=True)
rev = revision(document=doc,
significance=MEDIUM_SIGNIFICANCE,
is_approved=True,
is_ready_for_localization=True,
save=True)
# Create an es translation that is up to date.
es_doc = document(parent=doc, locale='es', save=True)
revision(document=es_doc, is_approved=True, based_on=rev, save=True)
# Create a de translation without revisions.
document(parent=doc, locale='de', save=True)
# Mock some calls.
visitors_by_locale.return_value = {
'en-US': 50,
'de': 20,
'es': 25,
'fr': 5,
}
_get_top_docs.return_value = [doc]
# Run it and verify results.
# Value should be 75% (1/1 * 25/100 + 1/1 * 50/100)
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(75, metrics[0].value)
# Create a new revision with TYPO_SIGNIFICANCE. It shouldn't
# affect the results.
revision(document=doc,
significance=TYPO_SIGNIFICANCE,
is_approved=True,
is_ready_for_localization=True,
save=True)
Metric.objects.all().delete()
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(75, metrics[0].value)
# Create a new revision with MEDIUM_SIGNIFICANCE. The coverage
# should now be 62% (0.5/1 * 25/100 + 1/1 * 50/100)
m1 = revision(document=doc,
significance=MEDIUM_SIGNIFICANCE,
is_approved=True,
is_ready_for_localization=True,
save=True)
Metric.objects.all().delete()
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(62, metrics[0].value)
# And another new revision with MEDIUM_SIGNIFICANCE makes the
# coverage 50% (1/1 * 50/100).
m2 = revision(document=doc,
significance=MEDIUM_SIGNIFICANCE,
is_approved=True,
is_ready_for_localization=True,
save=True)
Metric.objects.all().delete()
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(50, metrics[0].value)
# If we remove the two MEDIUM_SIGNIFICANCE revisions and add a
# MAJOR_SIGNIFICANCE revision, the coverage is 50% as well.
m1.delete()
m2.delete()
revision(document=doc,
significance=MAJOR_SIGNIFICANCE,
is_approved=True,
is_ready_for_localization=True,
save=True)
Metric.objects.all().delete()
update_l10n_metric()
metrics = Metric.objects.filter(kind=l10n_kind)
eq_(1, len(metrics))
eq_(50, metrics[0].value)