feat: initial implementation taller-wox.fitlabs.dev

Portal FastAPI + 5 endpoints REST para Bootcamp Agentic AI con
watsonx Orchestrate (FactorIT). Single container, Coolify-ready.

- Landing brandeado FIT con formulario de registro (honeypot anti-bot)
- Tokens itsdangerous para descargas (24h expiry)
- 5 endpoints API: historical/available procedures, member-insights,
  schedule, generate-report (Jinja2 + Plotly)
- SQLite con upsert-on-email para leads + log de descargas
- Admin endpoints (HTTP Basic): leads.json, leads.csv, stats
- 23 tests pytest pasando
- Dockerfile listo para Coolify con volúmenes persistentes
  (/app/leads.db, /app/app/data/reports_output, /app/material)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

app/db.py

@@ -0,0 +1,128 @@
+import sqlite3
+from contextlib import contextmanager
+from pathlib import Path
+from typing import Iterator
+
+from app.config import get_settings
+
+SCHEMA = """
+CREATE TABLE IF NOT EXISTS leads (
+    id                INTEGER PRIMARY KEY AUTOINCREMENT,
+    nombre            TEXT NOT NULL,
+    email             TEXT NOT NULL UNIQUE,
+    empresa           TEXT NOT NULL,
+    ip                TEXT,
+    user_agent        TEXT,
+    consent           INTEGER NOT NULL DEFAULT 0,
+    times_registered  INTEGER NOT NULL DEFAULT 1,
+    created_at        TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+    last_seen         TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+);
+
+CREATE TABLE IF NOT EXISTS downloads (
+    id            INTEGER PRIMARY KEY AUTOINCREMENT,
+    lead_email    TEXT NOT NULL,
+    filename      TEXT NOT NULL,
+    ip            TEXT,
+    downloaded_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+);
+
+CREATE INDEX IF NOT EXISTS idx_downloads_email ON downloads(lead_email);
+CREATE INDEX IF NOT EXISTS idx_downloads_filename ON downloads(filename);
+"""
+
+
+@contextmanager
+def _conn() -> Iterator[sqlite3.Connection]:
+    settings = get_settings()
+    db_path = Path(settings.db_path)
+    db_path.parent.mkdir(parents=True, exist_ok=True)
+    conn = sqlite3.connect(str(db_path))
+    conn.row_factory = sqlite3.Row
+    try:
+        yield conn
+        conn.commit()
+    finally:
+        conn.close()
+
+
+def init_db() -> None:
+    with _conn() as conn:
+        conn.executescript(SCHEMA)
+
+
+def upsert_lead(
+    nombre: str,
+    email: str,
+    empresa: str,
+    ip: str | None,
+    user_agent: str | None,
+    consent: bool,
+) -> int:
+    with _conn() as conn:
+        cur = conn.execute(
+            """
+            INSERT INTO leads (nombre, email, empresa, ip, user_agent, consent)
+            VALUES (?, ?, ?, ?, ?, ?)
+            ON CONFLICT(email) DO UPDATE SET
+                nombre = excluded.nombre,
+                empresa = excluded.empresa,
+                ip = excluded.ip,
+                user_agent = excluded.user_agent,
+                consent = excluded.consent,
+                times_registered = times_registered + 1,
+                last_seen = CURRENT_TIMESTAMP
+            RETURNING id
+            """,
+            (nombre, email, empresa, ip, user_agent, 1 if consent else 0),
+        )
+        return cur.fetchone()["id"]
+
+
+def get_lead_by_email(email: str) -> dict | None:
+    with _conn() as conn:
+        row = conn.execute(
+            "SELECT * FROM leads WHERE email = ?", (email,)
+        ).fetchone()
+        return dict(row) if row else None
+
+
+def log_download(lead_email: str, filename: str, ip: str | None) -> None:
+    with _conn() as conn:
+        conn.execute(
+            "INSERT INTO downloads (lead_email, filename, ip) VALUES (?, ?, ?)",
+            (lead_email, filename, ip),
+        )
+
+
+def list_leads(limit: int = 100, offset: int = 0) -> list[dict]:
+    with _conn() as conn:
+        rows = conn.execute(
+            "SELECT * FROM leads ORDER BY id ASC LIMIT ? OFFSET ?",
+            (limit, offset),
+        ).fetchall()
+        return [dict(r) for r in rows]
+
+
+def stats() -> dict:
+    with _conn() as conn:
+        total_leads = conn.execute("SELECT COUNT(*) AS c FROM leads").fetchone()["c"]
+        total_downloads = conn.execute("SELECT COUNT(*) AS c FROM downloads").fetchone()["c"]
+        per_file = {
+            r["filename"]: r["c"]
+            for r in conn.execute(
+                "SELECT filename, COUNT(*) AS c FROM downloads GROUP BY filename"
+            ).fetchall()
+        }
+        top_empresas = [
+            {"empresa": r["empresa"], "count": r["c"]}
+            for r in conn.execute(
+                "SELECT empresa, COUNT(*) AS c FROM leads GROUP BY empresa ORDER BY c DESC LIMIT 5"
+            ).fetchall()
+        ]
+        return {
+            "total_leads": total_leads,
+            "total_downloads": total_downloads,
+            "downloads_por_archivo": per_file,
+            "top_5_empresas": top_empresas,
+        }