Get a monthly ads review with recommendations

from datetime import date, timedelta
from clickruntime import on_trigger, credentials, http, ai, notify

CUSTOMER_ID = "1234567890"

def gaql(query):
    headers = {"Authorization": f"Bearer {credentials.connection('google', 'ads')}",
               "developer-token": credentials.secret("GOOGLE_ADS_DEVELOPER_TOKEN")}
    batches = http.post(f"https://googleads.googleapis.com/v21/customers/{CUSTOMER_ID}/googleAds:searchStream",
                        headers=headers, json={"query": query}).json()
    return [row for b in batches for row in b.get("results", [])]


def month_rows(start, end):
    return gaql("SELECT campaign.name, metrics.cost_micros, metrics.clicks, metrics.conversions, metrics.conversions_value "
                f"FROM campaign WHERE segments.date BETWEEN '{start}' AND '{end}'")

@on_trigger
def run(event):
    end = date.today().replace(day=1) - timedelta(days=1)
    prev_end = end.replace(day=1) - timedelta(days=1)
    fmt = lambda rows: "\n".join(f"{r['campaign']['name']}: ${int(r['metrics'].get('costMicros', 0)) / 1e6:,.0f} cost, "
                                 f"{r['metrics'].get('clicks', 0)} clicks, {float(r['metrics'].get('conversions', 0)):.0f} conv" for r in rows)
    data = f"Last month:\n{fmt(month_rows(end.replace(day=1), end))}\n\nMonth before:\n{fmt(month_rows(prev_end.replace(day=1), prev_end))}"
    analysis = ai.generate(data, system="Compare the two months. Give 3 takeaways and 3 concrete suggestions.", max_output_tokens=500).text
    notify.email_me(f"Google Ads: {end:%B %Y}", f"{analysis}\n\n{data}")
    return {"sent": True}