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_visitors(self):
"""Test unique visitors API call."""
# Create the metric.
kind = metric_kind(code=VISITORS_METRIC_CODE, save=True)
metric(kind=kind, start=date.today(), end=date.today(), value=42,
save=True)
# There should be 42 visitors.
r = self._get_api_result('kpi_visitors')
eq_(r['objects'][0]['visitors'], 42)
def test_l10n_coverage(self):
"""Test l10n coverage API call."""
# Create the metrics
kind = metric_kind(code=L10N_METRIC_CODE, save=True)
metric(kind=kind, start=date.today(), end=date.today(), value=56,
save=True)
# The l10n coverage should be 56%.
r = self._get_api_result('kpi_l10n_coverage')
eq_(r['objects'][0]['coverage'], 56)
def test_l10n_coverage(self):
"""Test l10n coverage API call."""
# Create the metrics
kind = metric_kind(code=L10N_METRIC_CODE, save=True)
metric(kind=kind, start=date.today(), end=date.today(), value=56,
save=True)
# The l10n coverage should be 56%.
r = self._get_api_result('kpi_l10n_coverage')
eq_(r['objects'][0]['coverage'], 56)
def test_visitors(self):
"""Test unique visitors API call."""
# Create the metric.
kind = metric_kind(code=VISITORS_METRIC_CODE, save=True)
metric(kind=kind, start=date.today(), end=date.today(), value=42,
save=True)
# There should be 42 visitors.
r = self._get_api_result('kpi_visitors')
eq_(r['objects'][0]['visitors'], 42)
def test_update_visitors_cron(self, visits):
"""Verify the cron job inserts the right rows."""
visitor_kind = metric_kind(code=VISITORS_METRIC_CODE, save=True)
visits.return_value = {"2012-01-13": 42, "2012-01-14": 193, "2012-01-15": 33}
update_visitors_metric()
metrics = Metric.objects.filter(kind=visitor_kind).order_by("start")
eq_(3, len(metrics))
eq_(42, metrics[0].value)
eq_(193, metrics[1].value)
eq_(date(2012, 01, 15), metrics[2].start)
def test_update_visitors_cron(self, visits):
"""Verify the cron job inserts the right rows."""
visitor_kind = metric_kind(code=VISITORS_METRIC_CODE, save=True)
visits.return_value = {'2012-01-13': 42,
'2012-01-14': 193,
'2012-01-15': 33}
update_visitors_metric()
metrics = Metric.objects.filter(kind=visitor_kind)
eq_(3, len(metrics))
eq_(42, metrics[0].value)
eq_(193, metrics[1].value)
eq_(date(2012, 01, 15), metrics[2].start)
def test_visitors(self):
"""Test unique visitors API call."""
# Create a reply
kind = metric_kind(code=VISITORS_METRIC_CODE, save=True)
metric(kind=kind, start=date.today(), end=date.today(), value=42,
save=True)
# There should be only one active contributor.
url = reverse('api_dispatch_list',
kwargs={'resource_name': 'kpi_visitors',
'api_name': 'v1'})
response = self.client.get(url + '?format=json')
eq_(200, response.status_code)
r = json.loads(response.content)
eq_(r['objects'][0]['visitors'], 42)
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 _make_sphinx_metric_kinds(self):
click_kind = metric_kind(code='search clickthroughs:sphinx:clicks',
save=True)
search_kind = metric_kind(code='search clickthroughs:sphinx:searches',
save=True)
return click_kind, search_kind
def _make_contributor_metric_kinds(self):
metric_kind(code=AOA_CONTRIBUTORS_METRIC_CODE, save=True)
metric_kind(code=KB_ENUS_CONTRIBUTORS_METRIC_CODE, save=True)
metric_kind(code=KB_L10N_CONTRIBUTORS_METRIC_CODE, save=True)
metric_kind(code=SUPPORT_FORUM_CONTRIBUTORS_METRIC_CODE, save=True)
def _make_elastic_metric_kinds(self):
click_kind = metric_kind(code='search clickthroughs:elastic:clicks',
save=True)
search_kind = metric_kind(code='search clickthroughs:elastic:searches',
save=True)
return click_kind, search_kind
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 _make_contributor_metric_kinds(self):
metric_kind(code=AOA_CONTRIBUTORS_METRIC_CODE, save=True)
metric_kind(code=KB_ENUS_CONTRIBUTORS_METRIC_CODE, save=True)
metric_kind(code=KB_L10N_CONTRIBUTORS_METRIC_CODE, save=True)
metric_kind(code=SUPPORT_FORUM_CONTRIBUTORS_METRIC_CODE, save=True)
def _make_elastic_metric_kinds(self):
click_kind = metric_kind(code='search clickthroughs:elastic:clicks',
save=True)
search_kind = metric_kind(code='search clickthroughs:elastic:searches',
save=True)
return click_kind, search_kind
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)
