Ga4 Common Reports

import os
from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    RunReportRequest, DateRange, Metric, Dimension,
    FilterExpression, Filter, OrderBy,
)

PROPERTY = f"properties/{os.environ['GA4_PROPERTY_ID']}"
client = BetaAnalyticsDataClient()

req = RunReportRequest(
    property=PROPERTY,
    date_ranges=[DateRange(start_date="30daysAgo", end_date="yesterday")],
    metrics=[Metric(name="activeUsers")],
    dimensions=[Dimension(name="date")],
    order_bys=[OrderBy(dimension=OrderBy.DimensionOrderBy(dimension_name="date"))],
)
resp = client.run_report(req)
for r in resp.rows:
    print(f"{r.dimension_values[0].value} {r.metric_values[0].value}")

# MAU (last 30 days)
mau = client.run_report(RunReportRequest(
    property=PROPERTY,
    date_ranges=[DateRange(start_date="29daysAgo", end_date="yesterday")],
    metrics=[Metric(name="activeUsers")],
))
mau_count = int(mau.rows[0].metric_values[0].value) if mau.rows else 0

# WAU (last 7 days)
wau = client.run_report(RunReportRequest(
    property=PROPERTY,
    date_ranges=[DateRange(start_date="6daysAgo", end_date="yesterday")],
    metrics=[Metric(name="activeUsers")],
))
wau_count = int(wau.rows[0].metric_values[0].value) if wau.rows else 0

print(f"MAU: {mau_count:,}   WAU: {wau_count:,}   Ratio (engagement): {wau_count/mau_count:.2%}")

req = RunReportRequest(
    property=PROPERTY,
    date_ranges=[DateRange(start_date="7daysAgo", end_date="yesterday")],
    metrics=[Metric(name="screenPageViews"), Metric(name="activeUsers"), Metric(name="averageSessionDuration")],
    dimensions=[Dimension(name="pagePath")],
    order_bys=[OrderBy(metric=OrderBy.MetricOrderBy(metric_name="screenPageViews"), desc=True)],
    limit=25,
)
resp = client.run_report(req)
print(f"{'Path':<60} {'Views':>8} {'Users':>8} {'AvgSec':>8}")
for r in resp.rows:
    print(f"{r.dimension_values[0].value[:58]:<60} "
          f"{r.metric_values[0].value:>8} {r.metric_values[1].value:>8} "
          f"{float(r.metric_values[2].value):>8.1f}")

req = RunReportRequest(
    property=PROPERTY,
    date_ranges=[DateRange(start_date="30daysAgo", end_date="yesterday")],
    metrics=[Metric(name="activeUsers"), Metric(name="sessions"), Metric(name="engagedSessions")],
    dimensions=[Dimension(name="sessionDefaultChannelGrouping")],
    order_bys=[OrderBy(metric=OrderBy.MetricOrderBy(metric_name="activeUsers"), desc=True)],
)
resp = client.run_report(req)
print(f"{'Channel':<28} {'Users':>10} {'Sessions':>10} {'Engaged%':>10}")
for r in resp.rows:
    users = int(r.metric_values[0].value)
    sess = int(r.metric_values[1].value)
    eng = int(r.metric_values[2].value)
    eng_rate = eng / sess if sess else 0
    print(f"{r.dimension_values[0].value:<28} {users:>10,} {sess:>10,} {eng_rate:>9.1%}")

# Weekly active users for the last 8 weeks
req = RunReportRequest(
    property=PROPERTY,
    date_ranges=[DateRange(start_date="56daysAgo", end_date="yesterday")],
    metrics=[Metric(name="activeUsers")],
    dimensions=[Dimension(name="isoYearIsoWeek")],
    order_bys=[OrderBy(dimension=OrderBy.DimensionOrderBy(dimension_name="isoYearIsoWeek"))],
)
resp = client.run_report(req)
for r in resp.rows:
    print(f"{r.dimension_values[0].value}  {r.metric_values[0].value}")

def step_users(event_name, days_ago=7):
    return int(client.run_report(RunReportRequest(
        property=PROPERTY,
        date_ranges=[DateRange(start_date=f"{days_ago}daysAgo", end_date="yesterday")],
        metrics=[Metric(name="activeUsers")],
        dimension_filter=FilterExpression(filter=Filter(
            field_name="eventName",
            string_filter=Filter.StringFilter(
                match_type=Filter.StringFilter.MatchType.EXACT,
                value=event_name,
            ),
        )),
    )).rows[0].metric_values[0].value)

# Example funnel: landed → engaged → signed up → purchased
steps = [
    ("session_start",  step_users("session_start")),
    ("user_engagement", step_users("user_engagement")),
    ("sign_up",         step_users("sign_up")),
    ("purchase",        step_users("purchase")),
]
top = steps[0][1] or 1
print(f"{'Step':<20} {'Users':>10} {'% of top':>10}")
for name, count in steps:
    print(f"{name:<20} {count:>10,} {count/top:>9.1%}")