Get a recap two days after each campaign

from datetime import datetime, timedelta, timezone
from clickruntime import on_trigger, http, credentials, ai, notify, state

def mailchimp(method, path, **kw):
    key = credentials.secret("MAILCHIMP_API_KEY")
    r = http.request(method, f"https://{key.split('-')[-1]}.api.mailchimp.com/3.0{path}", auth=("clickruntime", key), **kw)
    r.raise_for_status()
    return r.json() if r.content else None

@on_trigger
def run(event):
    now = datetime.now(timezone.utc)
    done = set(state.get("recapped") or [])
    sent = mailchimp("GET", "/campaigns", params={"status": "sent", "count": 50, "sort_field": "send_time", "sort_dir": "DESC"})["campaigns"]
    reports = {c["id"]: mailchimp("GET", f"/reports/{c['id']}") for c in sent}
    avg_open = sum(r["opens"]["open_rate"] for r in reports.values()) / max(len(reports), 1)
    avg_click = sum(r["clicks"]["click_rate"] for r in reports.values()) / max(len(reports), 1)
    for c in sent:
        age = now - datetime.fromisoformat(c["send_time"].replace("Z", "+00:00"))
        if c["id"] in done or age < timedelta(hours=48):
            continue
        r = reports[c["id"]]
        links = mailchimp("GET", f"/reports/{c['id']}/click-details", params={"count": 5})["urls_clicked"]
        facts = (f"Subject: {c['settings']['subject_line']}\nOpen {r['opens']['open_rate']:.1%} (avg {avg_open:.1%}), "
                 f"click {r['clicks']['click_rate']:.1%} (avg {avg_click:.1%})\nTop links: {[l['url'] for l in links]}")
        note = ai.generate(f"In 3 sentences, what worked and what didn't:\n{facts}", max_output_tokens=200).text
        notify.email_me(f"Recap: {c['settings']['subject_line']}", f"{facts}\n\n{note}")
        done.add(c["id"])
    state.set("recapped", list(done)[-200:])
    return {"recapped": len(done)}