leads-optimizer/slack_reporter.py

import json
import requests
import config
from datetime import datetime


ALERT_LOSS_EUR = 200    # pérdida absoluta > 200€ → alerta
ALERT_MARGIN_PCT = -50  # margen % < -50% → alerta
TOP_N = 5               # campañas a mostrar en rankings


def _parse_metricas(metricas_json: str) -> dict:
    try:
        return json.loads(metricas_json) if metricas_json else {}
    except (json.JSONDecodeError, TypeError):
        return {}


def _last_n_days_sum(md: dict, n: int) -> dict:
    days = sorted(md.keys())[-n:]
    return {
        "coste":   round(sum(md[d].get("coste",   0) for d in days), 2),
        "ingreso": round(sum(md[d].get("ingreso", 0) for d in days), 2),
        "margen":  round(sum(md[d].get("margen",  0) for d in days), 2),
        "n_days":  len(days),
    }


def _fmt_eur(v: float) -> str:
    sign = "+" if v > 0 else ""
    return f"{sign}{v:,.0f}€".replace(",", ".")


def _curso(name: str, max_len: int = 42) -> str:
    return name[:max_len] + ("…" if len(name) > max_len else "")


def build_and_send(collected: list, dry_run: bool) -> None:
    if not config.SLACK_WEBHOOK_URL:
        print("  ⚠️  SLACK_WEBHOOK_URL no configurada, omitiendo envío.")
        return

    now = datetime.now()

    fco = [item for item in collected if item["campaign"]["curso"].lower().startswith("fco_")]

    # ── Totales del mes ──────────────────────────────────────────────────────
    inv_total = round(sum(item["metrics"].get("cost", 0) for item in fco), 2)

    ing_sumatorio = round(sum(
        sum(d.get("ingreso", 0) for d in _parse_metricas(item["campaign"].get("metricas_diarias", "{}")).values())
        for item in fco
    ), 2)
    ing_leads_ppl = round(sum(item["analysis"]["revenue_estimado"] for item in fco), 2)

    margen_sumatorio  = round(ing_sumatorio  - inv_total, 2)
    margen_leads_ppl  = round(ing_leads_ppl  - inv_total, 2)
    pct_sumatorio     = round(margen_sumatorio  / ing_sumatorio  * 100, 1) if ing_sumatorio  > 0 else 0.0
    pct_leads_ppl     = round(margen_leads_ppl  / ing_leads_ppl  * 100, 1) if ing_leads_ppl  > 0 else 0.0

    # ── Últimos 5 días (desde MetricasDiarias) ───────────────────────────────
    last5_rows = []
    for item in fco:
        md = _parse_metricas(item["campaign"].get("metricas_diarias", "{}"))
        s = _last_n_days_sum(md, 5)
        if s["n_days"] == 0:
            continue
        last5_rows.append({
            "curso":   item["campaign"]["curso"],
            "margen":  s["margen"],
            "ingreso": s["ingreso"],
            "coste":   s["coste"],
        })
    last5_rows.sort(key=lambda x: x["margen"])
    worst_last5 = last5_rows[:TOP_N]
    best_last5  = list(reversed(last5_rows[-TOP_N:]))

    # ── Mes en curso ─────────────────────────────────────────────────────────
    month_rows = []
    for item in fco:
        cost = item["metrics"].get("cost", 0)
        rev  = item["analysis"]["revenue_estimado"]
        loss = round(rev - cost, 2)
        pct  = round(item["analysis"]["margen"] * 100, 1)
        month_rows.append({
            "curso":      item["campaign"]["curso"],
            "margen":     loss,
            "margen_pct": pct,
            "ingreso":    round(rev, 2),
            "coste":      round(cost, 2),
        })
    month_rows.sort(key=lambda x: x["margen"])
    worst_month = month_rows[:TOP_N]
    best_month  = list(reversed(month_rows[-TOP_N:]))

    # ── Alertas ──────────────────────────────────────────────────────────────
    alerts = [
        r for r in month_rows
        if r["margen"] < -ALERT_LOSS_EUR or r["margen_pct"] < ALERT_MARGIN_PCT
    ]
    alerts.sort(key=lambda x: x["margen"])

    # ── Construir bloques ─────────────────────────────────────────────────────
    mode = "🔵 DRY RUN" if dry_run else "⚡ PRODUCCIÓN"

    blocks = [
        {
            "type": "header",
            "text": {"type": "plain_text", "text": f"LEADS OPTIMIZER — {now.strftime('%d/%m/%Y %H:%M')}  {mode}"},
        },
        {
            "type": "section",
            "text": {
                "type": "mrkdwn",
                "text": (
                    f"📊 *RESUMEN DEL MES*\n"
                    f"Inversión: *{inv_total:,.0f}€*\n"
                    f"Ingreso por sumatorio: *{ing_sumatorio:,.0f}€*  |  Margen por sumatorio: *{_fmt_eur(margen_sumatorio)}* ({pct_sumatorio}%)\n"
                    f"Ingreso LeadsxPPL: *{ing_leads_ppl:,.0f}€*  |  Margen por LeadsxPPL: *{_fmt_eur(margen_leads_ppl)}* ({pct_leads_ppl}%)"
                ).replace(",", "."),
            },
        },
    ]

    if alerts:
        alert_lines = "\n".join(
            f"  🔴 `{_curso(a['curso'])}` → Pérdida *{_fmt_eur(a['margen'])}* ({a['margen_pct']}%)"
            for a in alerts
        )
        blocks.append({"type": "divider"})
        blocks.append({
            "type": "section",
            "text": {
                "type": "mrkdwn",
                "text": f"🚨 *ALERTAS — CAMPAÑAS CON PÉRDIDAS IMPORTANTES*\n{alert_lines}",
            },
        })

    blocks.append({"type": "divider"})

    def _ranking_text(rows, label, show_pct=False):
        lines = []
        for i, r in enumerate(rows, 1):
            pct_str = f" ({r['margen_pct']}%)" if show_pct else ""
            lines.append(f"  {i}. `{_curso(r['curso'])}` → *{_fmt_eur(r['margen'])}*{pct_str}")
        return f"{label}\n" + "\n".join(lines)

    blocks.append({
        "type": "section",
        "fields": [
            {
                "type": "mrkdwn",
                "text": _ranking_text(worst_last5, "📉 *PEOR — ÚLTIMOS 5 DÍAS*"),
            },
            {
                "type": "mrkdwn",
                "text": _ranking_text(best_last5, "📈 *MEJOR — ÚLTIMOS 5 DÍAS*"),
            },
        ],
    })

    blocks.append({"type": "divider"})

    blocks.append({
        "type": "section",
        "fields": [
            {
                "type": "mrkdwn",
                "text": _ranking_text(worst_month, "📉 *PEOR — MES EN CURSO*", show_pct=True),
            },
            {
                "type": "mrkdwn",
                "text": _ranking_text(best_month, "📈 *MEJOR — MES EN CURSO*", show_pct=True),
            },
        ],
    })

    payload = {"blocks": blocks}
    try:
        resp = requests.post(config.SLACK_WEBHOOK_URL, json=payload, timeout=10)
        if resp.status_code != 200:
            print(f"  ⚠️  Slack respondió {resp.status_code}: {resp.text[:200]}")
    except Exception as e:
        print(f"  ⚠️  Error enviando a Slack: {e}")