def test_update_history_webusage_without_history(spark, main_summary_data):
main_summary = spark.createDataFrame(*main_summary_data)
usage, os, locales, top10addon = agg_usage(main_summary,
date='20180201',
period=1,
sample_factor=100.0 / 1,
country_list=['DE'])
usage_df = usage.toPandas()
os_df = os.toPandas()
locales_df = locales.toPandas()
top10addon_df = top10addon.toPandas()
fxhealth, webusage = all_metrics_per_day(['DE'],
usage_pd_df=usage_df,
os_pd_df=os_df,
locales_pd_df=locales_df,
topaddons_pd_df=top10addon_df)
updated_webusage = update_history(webusage, None)
expected_webusage = {
'DE': [{
"date": "2018-02-01",
"metrics": {
"pct_TP": 50.0,
"pct_addon": 100.0,
"os": {
u"Mac OS X": 50.0,
u"Windows 10": 50.0
},
"locale": {
u"en-US": 50.0,
u"DE": 50.0
},
"top10addons": {
u'SHA-1 deprecation staged rollout': 100.0
}
}
}],
'All': [{
"date": "2018-02-01",
"metrics": {
"pct_TP": 50.0,
"pct_addon": 100.0,
"os": {
u"Mac OS X": 50.0,
u"Windows 10": 50.0
},
"locale": {
u"en-US": 50.0,
u"DE": 50.0
},
"top10addons": {
u'SHA-1 deprecation staged rollout': 100.0
}
}
}]
}
assert expected_webusage == updated_webusage
def test_update_history_fxhealth_without_history(spark, main_summary_data):
main_summary = spark.createDataFrame(*main_summary_data)
usage, os, locales, top10addon = agg_usage(main_summary,
date='20180201',
period=1,
sample_factor=100.0 / 1,
country_list=['DE'])
usage_df = usage.toPandas()
os_df = os.toPandas()
locales_df = locales.toPandas()
top10addon_df = top10addon.toPandas()
fxhealth, webusage = all_metrics_per_day(['DE'],
usage_pd_df=usage_df,
os_pd_df=os_df,
locales_pd_df=locales_df,
topaddons_pd_df=top10addon_df)
updated_fxhealth = update_history(fxhealth, None)
expected_fxhealth = {
'DE': [{
"date": "2018-02-01",
"metrics": {
"avg_daily_usage(hours)": 300.0 / 3600 / 2.0,
"avg_intensity": 1.0,
"pct_latest_version": 50.0,
"MAU": 200.0,
"YAU": 200.0,
"pct_new_user": 50.0
}
}],
'All': [{
"date": "2018-02-01",
"metrics": {
"avg_daily_usage(hours)": 300.0 / 3600 / 2.0,
"avg_intensity": 1.0,
"pct_latest_version": 50.0,
"MAU": 200.0,
"YAU": 200.0,
"pct_new_user": 50.0
}
}]
}
assert expected_fxhealth == updated_fxhealth
def test_processing_one_day(spark, main_summary_data):
main_summary = spark.createDataFrame(*main_summary_data)
usage, locales, top10addon = agg_usage(main_summary,
date='20180201',
period=1,
sample_factor=100.0 / 1,
country_list=['DE'])
usage_df = usage.toPandas()
locales_df = locales.toPandas()
top10addon_df = top10addon.toPandas()
fxhealth, webusage = all_metrics_per_day(['DE'],
usage_pd_df=usage_df,
locales_pd_df=locales_df,
topaddons_pd_df=top10addon_df)
expected_fxhealth = {
'DE': {
"date": "2018-02-01",
"metrics": {
"avg_daily_usage(hours)": 300.0 / 3600 / 2.0,
"avg_intensity": 1.0,
"pct_latest_version": 50.0,
"MAU": 200.0,
"YAU": 200.0,
"pct_new_user": 50.0
}
},
'All': {
"date": "2018-02-01",
"metrics": {
"avg_daily_usage(hours)": 300.0 / 3600 / 2.0,
"avg_intensity": 1.0,
"pct_latest_version": 50.0,
"MAU": 200.0,
"YAU": 200.0,
"pct_new_user": 50.0
}
}
}
expected_webusage = {
'DE': {
"date": "2018-02-01",
"metrics": {
"pct_TP": 50.0,
"pct_addon": 100.0,
"locale": {
u"en-US": 50.0,
u"DE": 50.0
},
"top10addons": {
u'SHA-1 deprecation staged rollout': 100.0
}
}
},
'All': {
"date": "2018-02-01",
"metrics": {
"pct_TP": 50.0,
"pct_addon": 100.0,
"locale": {
u"en-US": 50.0,
u"DE": 50.0
},
"top10addons": {
u'SHA-1 deprecation staged rollout': 100.0
}
}
}
}
assert expected_fxhealth == fxhealth
assert expected_webusage == webusage