def unenroll(events, experiment):
return agg_any(
all_([
events.event_category == 'normandy',
events.event_method == 'unenroll',
events.event_string_value == experiment.experiment_slug,
]))
def test_agg_any(spark):
df = register_fixture(spark)
res = df.groupBy('client_id').agg(
mm.agg_any(df.bool_col).alias('metric_value')).toPandas().set_index(
'client_id').metric_value
assert res['aaaa'] == 1
assert res['bb'] == 0
assert res['ccc'] == 1
assert res['dd'] == 0
def view_about_protections(events):
return agg_any(
all_([
events.event_object == 'protection_report',
events.event_method == 'show',
]))
def view_about_logins(events):
return agg_any(
all_([
events.event_method == 'open_management',
events.event_category == 'pwmgr',
]))
def unenroll_addon_expt(tssp):
return agg_any(tssp.payload.data.study_state == 'exit')
through a Firefox SAP and which are not monetizable.
Learn more in the
[search data documentation](https://docs.telemetry.mozilla.org/datasets/search.html).
"""
# noqa:E501
),
)
#: Metric: ...
unenroll = Metric(
name="unenroll",
data_source=normandy_events,
select_expr=agg_any("""
event_category = 'normandy'
AND event_method = 'unenroll'
AND event_string_value = '{experiment_slug}'
"""),
friendly_name="Unenrollments",
description=dedent("""\
Counts the number of clients with an experiment unenrollment event.
"""),
bigger_is_better=False,
)
#: Metric: ...
view_about_logins = Metric(
name="view_about_logins",
data_source=events,
select_expr=agg_any("""
event_method = 'open_management'
from textwrap import dedent
from mozanalysis.metrics import agg_any
from mozanalysis.segments import Segment, SegmentDataSource
clients_last_seen = SegmentDataSource(
name="clients_last_seen",
from_expr="`moz-fx-data-shared-prod.telemetry.clients_last_seen`",
window_start=0,
window_end=0,
)
regular_users_v3 = Segment(
name="regular_users_v3",
data_source=clients_last_seen,
select_expr=agg_any("is_regular_user_v3"),
friendly_name="Regular users (v3)",
description=dedent("""\
Clients who used Firefox on at least 14 of the 27 days prior to enrolling.
This segment is characterized by high retention.
"""),
)
new_or_resurrected_v3 = Segment(
name="new_or_resurrected_v3",
data_source=clients_last_seen,
select_expr="LOGICAL_OR(COALESCE(is_new_or_resurrected_v3, TRUE))",
friendly_name="New or resurrected users (v3)",
description=dedent("""\
Clients who used Firefox on none of the 27 days prior to enrolling.
"""),
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
from mozanalysis.metrics import agg_any
from mozanalysis.segments import Segment, SegmentDataSource
clients_last_seen = SegmentDataSource(
name='clients_last_seen',
from_expr="`moz-fx-data-shared-prod.telemetry.clients_last_seen`",
window_start=0,
window_end=0,
)
regular_users_v3 = Segment(
name='regular_users_v3',
data_source=clients_last_seen,
select_expr=agg_any('is_regular_user_v3'),
)
new_or_resurrected_v3 = Segment(
name='new_or_resurrected_v3',
data_source=clients_last_seen,
select_expr="LOGICAL_OR(COALESCE(is_new_or_resurrected_v3, TRUE))",
)
weekday_regular_v1 = Segment(
name='weekday_regular_v1',
data_source=clients_last_seen,
select_expr=agg_any('is_weekday_regular_v1'),
)
allweek_regular_v1 = Segment(
