Backup automatico script del 2026-07-12 07:00

2026-07-12 07:00:03 +02:00
parent b5a2a814e2
commit 927f0d4184
18 changed files with 2365 additions and 422 deletions
@@ -0,0 +1,5 @@
+# Override opzionali per weekly-maintenance.sh (Pi-1 Master)
+# HOST_LABEL="Pi-1 (Master)"
+# DOCKER_IGNORE_IMAGES=("turni-app:live-latest")
+# REBOOT_ON_SUCCESS=false  # unico modo per saltare il reboot fisso di fine manutenzione
+# Cron consigliato: 0 4 * * 6 (nessun conflitto irrigazione, che gira su Pi2)
@@ -0,0 +1,6 @@
+# Override opzionali per weekly-maintenance.sh (Pi-2 Backup)
+# HOST_LABEL="Pi-2 (Backup)"
+# REBOOT_ON_SUCCESS=false  # unico modo per saltare il reboot fisso di fine manutenzione
+# CHECK_PIP3=true
+# DOCKER_IGNORE_IMAGES=("irrigazione:latest" "turni-app:beta-latest" "turni-app:alpha-latest")
+# Cron consigliato: 40 0 * * 6 (tra irrigazione serale ~19:30 e notturna ~02:30)
@@ -54,4 +54,4 @@ else
 fi

 # 5. Pulizia locale
-rm "$TEMP_FILE"
+sudo rm -f "$TEMP_FILE"
@@ -5,11 +5,20 @@
 #  Controlla solo che il Pi-2 sia vivo.
 # ================================================

-# --- CONFIGURAZIONE ---
-# 👇👇 INSERISCI I TUOI DATI VERI QUI 👇👇
-BOT_TOKEN="8155587974:AAF9OekvBpixtk8ZH6KoIc0L8edbhdXt7A4"
-CHAT_ID="64463169"
-# 👆👆 FINE MODIFICHE 👆👆
+ENV_FILE="/home/daniely/.config/watchdog_pi2.env"
+
+if [ ! -f "$ENV_FILE" ]; then
+    echo "Errore: file credenziali non trovato ($ENV_FILE)" >&2
+    exit 1
+fi
+
+# shellcheck source=/dev/null
+source "$ENV_FILE"
+
+if [ -z "$BOT_TOKEN" ] || [ -z "$CHAT_ID" ]; then
+    echo "Errore: BOT_TOKEN o CHAT_ID mancanti in $ENV_FILE" >&2
+    exit 1
+fi

 # Il bersaglio da controllare (Pi-2 Backup)
 TARGET_IP="192.168.128.81"
@@ -0,0 +1,454 @@
+#!/bin/bash
+# ==============================================================================
+#  Manutenzione settimanale Raspberry Pi
+#  Aggiorna OS, Pi-hole, EEPROM; verifica Docker/pip; report + Telegram.
+#  Conclude sempre con reboot host (salvo --no-reboot o REBOOT_ON_SUCCESS=false).
+#  Eseguire come root (cron root).
+# ==============================================================================
+
+set -uo pipefail
+
+CONF_FILE="/etc/weekly-maintenance.conf"
+LOG_FILE="/var/log/weekly-maintenance.log"
+REPORT_FILE="/var/log/weekly-maintenance-report.txt"
+TOKEN_FILE="/etc/telegram_dpc_bot_token"
+CHAT_ID="64463169"
+PIHOLE_BIN="/usr/local/bin/pihole"
+REBOOT_DELAY_MIN=2
+WATCHTOWER_IMAGE="nickfedor/watchtower:latest"
+WATCHTOWER_TIMEOUT=900
+
+HOST_LABEL="$(hostname -s)"
+REBOOT_ON_SUCCESS=true
+TELEGRAM_ENABLED=true
+CHECK_PIP3=false
+DOCKER_IGNORE_IMAGES=()
+DOCKER_PINNED_IMAGES=()
+
+declare -a ERRORS=()
+declare -a WARNINGS=()
+declare -a NOTES=()
+REBOOT_RECOMMENDED=false
+APT_CHANGED=false
+DOCKER_UPDATED=false
+
+for arg in "$@"; do
+    case "$arg" in
+        --no-reboot) REBOOT_ON_SUCCESS=false ;;
+    esac
+done
+
+# --- Configurazione host (override via /etc/weekly-maintenance.conf) ---
+case "$(hostname -s)" in
+    pi1)
+        HOST_LABEL="Pi-1 (Master)"
+        DOCKER_IGNORE_IMAGES=("turni-app:live-latest")
+        ;;
+    pi2)
+        HOST_LABEL="Pi-2 (Backup)"
+        CHECK_PIP3=true
+        DOCKER_IGNORE_IMAGES=("irrigazione:latest" "turni-app:beta-latest" "turni-app:alpha-latest")
+        ;;
+esac
+
+if [[ -f "$CONF_FILE" ]]; then
+    # shellcheck source=/dev/null
+    source "$CONF_FILE"
+fi
+
+# --- Utility ---
+log() {
+    printf '[%s] %s\n' "$(date '+%Y-%m-%d %H:%M:%S')" "$*" | tee -a "$LOG_FILE"
+}
+
+append_report() {
+    printf '%s\n' "$*" >> "$REPORT_FILE"
+}
+
+run_step() {
+    local title="$1"
+    shift
+    local output
+    local rc=0
+
+    log "▶ $title"
+    append_report ""
+    append_report "=== $title ==="
+
+    output="$("$@" 2>&1)" || rc=$?
+    if [[ -n "$output" ]]; then
+        append_report "$output"
+        log "$output"
+    fi
+
+    if [[ $rc -eq 0 ]]; then
+        NOTES+=("OK: $title")
+        log "✓ $title completato"
+    else
+        ERRORS+=("$title (exit $rc)")
+        log "✗ $title fallito (exit $rc)"
+    fi
+    return 0
+}
+
+load_telegram_token() {
+    if [[ ! -f "$TOKEN_FILE" ]]; then
+        WARNINGS+=("Token Telegram assente ($TOKEN_FILE): notifiche disabilitate")
+        TELEGRAM_ENABLED=false
+        return 1
+    fi
+    BOT_TOKEN=$(tr -d '\n\r' < "$TOKEN_FILE")
+    if [[ -z "$BOT_TOKEN" ]]; then
+        WARNINGS+=("Token Telegram vuoto: notifiche disabilitate")
+        TELEGRAM_ENABLED=false
+        return 1
+    fi
+    return 0
+}
+
+send_telegram() {
+    local msg="$1"
+    [[ "$TELEGRAM_ENABLED" == true ]] || return 0
+    curl -s --max-time 15 -X POST "https://api.telegram.org/bot${BOT_TOKEN}/sendMessage" \
+        -d "chat_id=${CHAT_ID}" \
+        --data-urlencode "text=${msg}" \
+        -d "parse_mode=Markdown" > /dev/null 2>&1 || true
+}
+
+send_telegram_document() {
+    [[ "$TELEGRAM_ENABLED" == true ]] || return 0
+    [[ -f "$REPORT_FILE" ]] || return 0
+    curl -s --max-time 30 -X POST "https://api.telegram.org/bot${BOT_TOKEN}/sendDocument" \
+        -F "chat_id=${CHAT_ID}" \
+        -F "document=@${REPORT_FILE}" \
+        -F "caption=Report completo ${HOST_LABEL}" > /dev/null 2>&1 || true
+}
+
+require_root() {
+    if [[ "${EUID:-$(id -u)}" -ne 0 ]]; then
+        echo "Eseguire come root (es. cron root)." >&2
+        exit 1
+    fi
+}
+
+image_is_ignored() {
+    local image="$1"
+    local ignored
+    for ignored in "${DOCKER_IGNORE_IMAGES[@]}"; do
+        [[ "$image" == "$ignored" ]] && return 0
+    done
+    return 1
+}
+
+ensure_watchtower_labels() {
+    command -v docker >/dev/null 2>&1 || return 0
+    local name image
+    while IFS= read -r line; do
+        [[ -z "$line" ]] && continue
+        name=${line%%|*}
+        image=${line#*|}
+        image_is_ignored "$image" || continue
+        docker update --label-add com.centurylinklabs.watchtower.enable=false "$name" >/dev/null 2>&1 || true
+    done < <(docker ps --format '{{.Names}}|{{.Image}}' 2>/dev/null || true)
+}
+
+run_watchtower() {
+    command -v docker >/dev/null 2>&1 || return 0
+
+    ensure_watchtower_labels
+
+    log "▶ Watchtower (run-once, container aggiornabili da registry)"
+    append_report ""
+    append_report "=== Watchtower run-once ==="
+
+    local output rc=0
+    output=$(docker run --rm \
+        -v /var/run/docker.sock:/var/run/docker.sock \
+        -e WATCHTOWER_CLEANUP=true \
+        -e WATCHTOWER_ROLLING_RESTART=true \
+        -e WATCHTOWER_TIMEOUT="${WATCHTOWER_TIMEOUT}" \
+        -e TZ=Europe/Rome \
+        "$WATCHTOWER_IMAGE" \
+        --run-once 2>&1) || rc=$?
+
+    if [[ -n "$output" ]]; then
+        append_report "$output"
+        printf '%s\n' "$output" | tail -30 | while IFS= read -r line; do log "$line"; done
+    fi
+
+    if [[ $rc -eq 0 ]]; then
+        NOTES+=("Watchtower run-once OK")
+        if grep -q "updated=[1-9]" <<< "$output"; then
+            DOCKER_UPDATED=true
+            REBOOT_RECOMMENDED=true
+            NOTES+=("Watchtower: container aggiornati")
+        fi
+    else
+        ERRORS+=("Watchtower run-once (exit $rc)")
+    fi
+}
+
+audit_apt() {
+    local holds
+    holds=$(apt-mark showhold 2>/dev/null || true)
+    if [[ -n "$holds" ]]; then
+        WARNINGS+=("Pacchetti apt bloccati (hold): ${holds//$'\n'/, }")
+        append_report "$holds"
+    fi
+
+    local upgradable
+    upgradable=$(apt list --upgradable 2>/dev/null | tail -n +2 || true)
+    if [[ -n "$upgradable" ]]; then
+        WARNINGS+=("Restano pacchetti non aggiornati dopo full-upgrade")
+        append_report "$upgradable"
+    fi
+}
+
+audit_pihole_versions() {
+    local out
+    out=$("$PIHOLE_BIN" -v 2>&1 || true)
+    append_report "$out"
+    if grep -qiE 'version is .*\(Latest: .*\)' <<< "$out"; then
+        while IFS= read -r line; do
+            local current latest
+            current=$(sed -n 's/.*Version is \([^ ]*\).*/\1/p' <<< "$line")
+            latest=$(sed -n 's/.*Latest: \([^)]*\).*/\1/p' <<< "$line")
+            if [[ -n "$current" && -n "$latest" && "$current" != "$latest" && "$current" != "N/A" ]]; then
+                WARNINGS+=("Pi-hole non allineato: $line")
+            fi
+        done <<< "$out"
+    fi
+}
+
+audit_eeprom() {
+    command -v rpi-eeprom-update >/dev/null 2>&1 || return 0
+    local out
+    out=$(rpi-eeprom-update 2>&1 || true)
+    append_report "$out"
+    if grep -qiE 'UPDATE REQUIRED|update available|NEW EEPROM' <<< "$out"; then
+        log "EEPROM: aggiornamento disponibile, applico..."
+        append_report ""
+        append_report "=== rpi-eeprom-update -a ==="
+        if rpi-eeprom-update -a >> "$REPORT_FILE" 2>&1; then
+            NOTES+=("EEPROM aggiornato")
+            REBOOT_RECOMMENDED=true
+        else
+            ERRORS+=("rpi-eeprom-update -a")
+        fi
+    else
+        NOTES+=("EEPROM: aggiornato")
+    fi
+}
+
+audit_docker() {
+    command -v docker >/dev/null 2>&1 || return 0
+
+    append_report ""
+    append_report "=== Docker audit ==="
+
+    local exited
+    exited=$(docker ps -a --filter "status=exited" --format '{{.Names}} ({{.Image}})' 2>/dev/null || true)
+    if [[ -n "$exited" ]]; then
+        WARNINGS+=("Container Docker fermati (Exited): ${exited//$'\n'/, }")
+        append_report "Exited:"
+        append_report "$exited"
+    fi
+
+    local name image
+    while IFS= read -r line; do
+        [[ -z "$line" ]] && continue
+        name=${line%%|*}
+        image=${line#*|}
+
+        image_is_ignored "$image" && continue
+
+        if [[ "$image" =~ ^[0-9a-f]{12}$ ]]; then
+            WARNINGS+=("Container '$name' usa immagine per ID ($image): preferire un tag versionato")
+        fi
+
+        local pinned
+        for pinned in "${DOCKER_PINNED_IMAGES[@]}"; do
+            if [[ "$image" == "$pinned" ]]; then
+                WARNINGS+=("Container '$name' usa tag bloccato ($pinned): Watchtower non passerà a :latest")
+            fi
+        done
+    done < <(docker ps --format '{{.Names}}|{{.Image}}' 2>/dev/null || true)
+}
+
+audit_pip3() {
+    [[ "$CHECK_PIP3" == true ]] || return 0
+    command -v pip3 >/dev/null 2>&1 || return 0
+
+    append_report ""
+    append_report "=== pip3 outdated (sistema) ==="
+    local outdated count
+    outdated=$(pip3 list --outdated --format=columns 2>/dev/null | tail -n +3 || true)
+    if [[ -n "$outdated" ]]; then
+        count=$(wc -l <<< "$outdated")
+        append_report "$outdated"
+        WARNINGS+=("pip3: $count pacchetti Python di sistema non aggiornati (aggiornamento manuale/consigliato in venv)")
+    else
+        NOTES+=("pip3: tutti aggiornati")
+    fi
+}
+
+build_telegram_summary() {
+    local icon status
+    if ((${#ERRORS[@]} > 0)); then
+        icon="🚨"
+        status="ERRORI"
+    elif ((${#WARNINGS[@]} > 0)); then
+        icon="⚠️"
+        status="WARNINGS"
+    else
+        icon="✅"
+        status="OK"
+    fi
+
+    local msg="${icon} *Manutenzione settimanale ${HOST_LABEL}*
+Stato: *${status}*
+Data: $(date '+%d/%m/%Y %H:%M')"
+
+    if [[ "$APT_CHANGED" == true ]]; then
+        msg+="
+📦 apt: pacchetti aggiornati"
+    fi
+    if [[ "$DOCKER_UPDATED" == true ]]; then
+        msg+="
+🐳 Docker: container aggiornati"
+    fi
+    if [[ "$REBOOT_ON_SUCCESS" == true ]]; then
+        msg+="
+🔄 Reboot host programmato tra ${REBOOT_DELAY_MIN} min (fine manutenzione)"
+    fi
+
+    if ((${#ERRORS[@]} > 0)); then
+        msg+="
+*Errori (${#ERRORS[@]}):*"
+        local e
+        for e in "${ERRORS[@]}"; do
+            msg+="
+• ${e}"
+        done
+    fi
+
+    if ((${#WARNINGS[@]} > 0)); then
+        msg+="
+*Avvisi (${#WARNINGS[@]}):*"
+        local w
+        local n=0
+        for w in "${WARNINGS[@]}"; do
+            ((n++)) || true
+            [[ $n -le 8 ]] && msg+="
+• ${w}"
+        done
+        if ((${#WARNINGS[@]} > 8)); then
+            msg+="
+• … +$((${#WARNINGS[@]} - 8)) avvisi (vedi report)"
+        fi
+    fi
+
+    if ((${#ERRORS[@]} == 0 && ${#WARNINGS[@]} == 0)); then
+        msg+="
+Tutto aggiornato. Log: \`${LOG_FILE}\`"
+    else
+        msg+="
+Report completo allegato o in \`${REPORT_FILE}\`"
+    fi
+
+    send_telegram "$msg"
+    if ((${#ERRORS[@]} > 0 || ${#WARNINGS[@]} > 0)); then
+        send_telegram_document
+    fi
+}
+
+# --- Main ---
+require_root
+
+: > "$REPORT_FILE"
+log "========== Inizio manutenzione settimanale ($HOST_LABEL) =========="
+append_report "Manutenzione settimanale - $HOST_LABEL"
+append_report "Avviata: $(date '+%Y-%m-%d %H:%M:%S')"
+append_report "Host: $(hostname -f) ($(hostname -I | awk '{print $1}'))"
+
+load_telegram_token || true
+
+# 1. Aggiornamento pacchetti sistema
+if apt update >> "$REPORT_FILE" 2>&1; then
+    NOTES+=("apt update OK")
+    log "✓ apt update"
+else
+    ERRORS+=("apt update")
+    log "✗ apt update fallito"
+fi
+
+BEFORE_UPGRADES=$(apt list --upgradable 2>/dev/null | tail -n +2 | wc -l || echo 0)
+if apt full-upgrade -y >> "$REPORT_FILE" 2>&1; then
+    NOTES+=("apt full-upgrade OK")
+    log "✓ apt full-upgrade"
+    AFTER_UPGRADES=$(apt list --upgradable 2>/dev/null | tail -n +2 | wc -l || echo 0)
+    if [[ "$BEFORE_UPGRADES" -gt "$AFTER_UPGRADES" ]] || [[ "$BEFORE_UPGRADES" -gt 0 ]]; then
+        APT_CHANGED=true
+        REBOOT_RECOMMENDED=true
+    fi
+else
+    ERRORS+=("apt full-upgrade")
+    log "✗ apt full-upgrade fallito"
+fi
+
+run_step "apt autoremove" apt autoremove -y
+audit_apt
+
+# 2. Pi-hole
+if [[ -x "$PIHOLE_BIN" ]]; then
+    run_step "pihole -up" "$PIHOLE_BIN" -up
+    audit_pihole_versions
+else
+    ERRORS+=("pihole non trovato in $PIHOLE_BIN")
+fi
+
+# 3. EEPROM firmware
+audit_eeprom
+
+# 4. Aggiornamento container Docker (Watchtower run-once, sostituisce il daemon schedulato)
+run_watchtower
+
+# 5. Audit residui
+audit_docker
+audit_pip3
+
+append_report ""
+append_report "=== Riepilogo ==="
+append_report "Errori: ${#ERRORS[@]}"
+append_report "Avvisi: ${#WARNINGS[@]}"
+if ((${#ERRORS[@]} > 0)); then
+    append_report "Dettaglio errori:"
+    printf '%s\n' "${ERRORS[@]}" >> "$REPORT_FILE"
+fi
+if ((${#WARNINGS[@]} > 0)); then
+    append_report "Dettaglio avvisi:"
+    printf '%s\n' "${WARNINGS[@]}" >> "$REPORT_FILE"
+fi
+append_report "Fine: $(date '+%Y-%m-%d %H:%M:%S')"
+
+build_telegram_summary
+
+# 6. Reboot fisso di conclusione (salvo --no-reboot o REBOOT_ON_SUCCESS=false in conf)
+if [[ "$REBOOT_ON_SUCCESS" == true ]]; then
+    log "Reboot host programmato tra ${REBOOT_DELAY_MIN} minuti (fine manutenzione settimanale)"
+    append_report ""
+    append_report "=== Reboot ==="
+    append_report "Programmato tra ${REBOOT_DELAY_MIN} minuti"
+    shutdown -r "+${REBOOT_DELAY_MIN}" "Manutenzione settimanale ${HOST_LABEL}" || {
+        ERRORS+=("shutdown -r (reboot programmato)")
+        log "✗ Impossibile programmare il reboot"
+    }
+else
+    log "Reboot disabilitato (--no-reboot o REBOOT_ON_SUCCESS=false)"
+    append_report ""
+    append_report "=== Reboot ==="
+    append_report "Saltato (disabilitato)"
+fi
+
+log "========== Fine manutenzione settimanale =========="
+exit $(( ${#ERRORS[@]} > 0 ? 1 : 0 ))
@@ -44,6 +44,7 @@ TARGETS=(
    "📶 WiFi Luca (.102)|192.168.128.102"
    "📶 WiFi Taverna (.103)|192.168.128.103"
    "📶 WiFi Dado (.104)|192.168.128.104"
+    "📶 WiFi Esterno (.108)|192.168.128.108"

    # CAMERE 📷 (Sottorete .135)
    "📷 Cam Matrimoniale|192.168.135.2"
@@ -0,0 +1,454 @@
+#!/bin/bash
+# ==============================================================================
+#  Manutenzione settimanale Raspberry Pi
+#  Aggiorna OS, Pi-hole, EEPROM; verifica Docker/pip; report + Telegram.
+#  Conclude sempre con reboot host (salvo --no-reboot o REBOOT_ON_SUCCESS=false).
+#  Eseguire come root (cron root).
+# ==============================================================================
+
+set -uo pipefail
+
+CONF_FILE="/etc/weekly-maintenance.conf"
+LOG_FILE="/var/log/weekly-maintenance.log"
+REPORT_FILE="/var/log/weekly-maintenance-report.txt"
+TOKEN_FILE="/etc/telegram_dpc_bot_token"
+CHAT_ID="64463169"
+PIHOLE_BIN="/usr/local/bin/pihole"
+REBOOT_DELAY_MIN=2
+WATCHTOWER_IMAGE="nickfedor/watchtower:latest"
+WATCHTOWER_TIMEOUT=900
+
+HOST_LABEL="$(hostname -s)"
+REBOOT_ON_SUCCESS=true
+TELEGRAM_ENABLED=true
+CHECK_PIP3=false
+DOCKER_IGNORE_IMAGES=()
+DOCKER_PINNED_IMAGES=()
+
+declare -a ERRORS=()
+declare -a WARNINGS=()
+declare -a NOTES=()
+REBOOT_RECOMMENDED=false
+APT_CHANGED=false
+DOCKER_UPDATED=false
+
+for arg in "$@"; do
+    case "$arg" in
+        --no-reboot) REBOOT_ON_SUCCESS=false ;;
+    esac
+done
+
+# --- Configurazione host (override via /etc/weekly-maintenance.conf) ---
+case "$(hostname -s)" in
+    pi1)
+        HOST_LABEL="Pi-1 (Master)"
+        DOCKER_IGNORE_IMAGES=("turni-app:live-latest")
+        ;;
+    pi2)
+        HOST_LABEL="Pi-2 (Backup)"
+        CHECK_PIP3=true
+        DOCKER_IGNORE_IMAGES=("irrigazione:latest" "turni-app:beta-latest" "turni-app:alpha-latest")
+        ;;
+esac
+
+if [[ -f "$CONF_FILE" ]]; then
+    # shellcheck source=/dev/null
+    source "$CONF_FILE"
+fi
+
+# --- Utility ---
+log() {
+    printf '[%s] %s\n' "$(date '+%Y-%m-%d %H:%M:%S')" "$*" | tee -a "$LOG_FILE"
+}
+
+append_report() {
+    printf '%s\n' "$*" >> "$REPORT_FILE"
+}
+
+run_step() {
+    local title="$1"
+    shift
+    local output
+    local rc=0
+
+    log "▶ $title"
+    append_report ""
+    append_report "=== $title ==="
+
+    output="$("$@" 2>&1)" || rc=$?
+    if [[ -n "$output" ]]; then
+        append_report "$output"
+        log "$output"
+    fi
+
+    if [[ $rc -eq 0 ]]; then
+        NOTES+=("OK: $title")
+        log "✓ $title completato"
+    else
+        ERRORS+=("$title (exit $rc)")
+        log "✗ $title fallito (exit $rc)"
+    fi
+    return 0
+}
+
+load_telegram_token() {
+    if [[ ! -f "$TOKEN_FILE" ]]; then
+        WARNINGS+=("Token Telegram assente ($TOKEN_FILE): notifiche disabilitate")
+        TELEGRAM_ENABLED=false
+        return 1
+    fi
+    BOT_TOKEN=$(tr -d '\n\r' < "$TOKEN_FILE")
+    if [[ -z "$BOT_TOKEN" ]]; then
+        WARNINGS+=("Token Telegram vuoto: notifiche disabilitate")
+        TELEGRAM_ENABLED=false
+        return 1
+    fi
+    return 0
+}
+
+send_telegram() {
+    local msg="$1"
+    [[ "$TELEGRAM_ENABLED" == true ]] || return 0
+    curl -s --max-time 15 -X POST "https://api.telegram.org/bot${BOT_TOKEN}/sendMessage" \
+        -d "chat_id=${CHAT_ID}" \
+        --data-urlencode "text=${msg}" \
+        -d "parse_mode=Markdown" > /dev/null 2>&1 || true
+}
+
+send_telegram_document() {
+    [[ "$TELEGRAM_ENABLED" == true ]] || return 0
+    [[ -f "$REPORT_FILE" ]] || return 0
+    curl -s --max-time 30 -X POST "https://api.telegram.org/bot${BOT_TOKEN}/sendDocument" \
+        -F "chat_id=${CHAT_ID}" \
+        -F "document=@${REPORT_FILE}" \
+        -F "caption=Report completo ${HOST_LABEL}" > /dev/null 2>&1 || true
+}
+
+require_root() {
+    if [[ "${EUID:-$(id -u)}" -ne 0 ]]; then
+        echo "Eseguire come root (es. cron root)." >&2
+        exit 1
+    fi
+}
+
+image_is_ignored() {
+    local image="$1"
+    local ignored
+    for ignored in "${DOCKER_IGNORE_IMAGES[@]}"; do
+        [[ "$image" == "$ignored" ]] && return 0
+    done
+    return 1
+}
+
+ensure_watchtower_labels() {
+    command -v docker >/dev/null 2>&1 || return 0
+    local name image
+    while IFS= read -r line; do
+        [[ -z "$line" ]] && continue
+        name=${line%%|*}
+        image=${line#*|}
+        image_is_ignored "$image" || continue
+        docker update --label-add com.centurylinklabs.watchtower.enable=false "$name" >/dev/null 2>&1 || true
+    done < <(docker ps --format '{{.Names}}|{{.Image}}' 2>/dev/null || true)
+}
+
+run_watchtower() {
+    command -v docker >/dev/null 2>&1 || return 0
+
+    ensure_watchtower_labels
+
+    log "▶ Watchtower (run-once, container aggiornabili da registry)"
+    append_report ""
+    append_report "=== Watchtower run-once ==="
+
+    local output rc=0
+    output=$(docker run --rm \
+        -v /var/run/docker.sock:/var/run/docker.sock \
+        -e WATCHTOWER_CLEANUP=true \
+        -e WATCHTOWER_ROLLING_RESTART=true \
+        -e WATCHTOWER_TIMEOUT="${WATCHTOWER_TIMEOUT}" \
+        -e TZ=Europe/Rome \
+        "$WATCHTOWER_IMAGE" \
+        --run-once 2>&1) || rc=$?
+
+    if [[ -n "$output" ]]; then
+        append_report "$output"
+        printf '%s\n' "$output" | tail -30 | while IFS= read -r line; do log "$line"; done
+    fi
+
+    if [[ $rc -eq 0 ]]; then
+        NOTES+=("Watchtower run-once OK")
+        if grep -q "updated=[1-9]" <<< "$output"; then
+            DOCKER_UPDATED=true
+            REBOOT_RECOMMENDED=true
+            NOTES+=("Watchtower: container aggiornati")
+        fi
+    else
+        ERRORS+=("Watchtower run-once (exit $rc)")
+    fi
+}
+
+audit_apt() {
+    local holds
+    holds=$(apt-mark showhold 2>/dev/null || true)
+    if [[ -n "$holds" ]]; then
+        WARNINGS+=("Pacchetti apt bloccati (hold): ${holds//$'\n'/, }")
+        append_report "$holds"
+    fi
+
+    local upgradable
+    upgradable=$(apt list --upgradable 2>/dev/null | tail -n +2 || true)
+    if [[ -n "$upgradable" ]]; then
+        WARNINGS+=("Restano pacchetti non aggiornati dopo full-upgrade")
+        append_report "$upgradable"
+    fi
+}
+
+audit_pihole_versions() {
+    local out
+    out=$("$PIHOLE_BIN" -v 2>&1 || true)
+    append_report "$out"
+    if grep -qiE 'version is .*\(Latest: .*\)' <<< "$out"; then
+        while IFS= read -r line; do
+            local current latest
+            current=$(sed -n 's/.*Version is \([^ ]*\).*/\1/p' <<< "$line")
+            latest=$(sed -n 's/.*Latest: \([^)]*\).*/\1/p' <<< "$line")
+            if [[ -n "$current" && -n "$latest" && "$current" != "$latest" && "$current" != "N/A" ]]; then
+                WARNINGS+=("Pi-hole non allineato: $line")
+            fi
+        done <<< "$out"
+    fi
+}
+
+audit_eeprom() {
+    command -v rpi-eeprom-update >/dev/null 2>&1 || return 0
+    local out
+    out=$(rpi-eeprom-update 2>&1 || true)
+    append_report "$out"
+    if grep -qiE 'UPDATE REQUIRED|update available|NEW EEPROM' <<< "$out"; then
+        log "EEPROM: aggiornamento disponibile, applico..."
+        append_report ""
+        append_report "=== rpi-eeprom-update -a ==="
+        if rpi-eeprom-update -a >> "$REPORT_FILE" 2>&1; then
+            NOTES+=("EEPROM aggiornato")
+            REBOOT_RECOMMENDED=true
+        else
+            ERRORS+=("rpi-eeprom-update -a")
+        fi
+    else
+        NOTES+=("EEPROM: aggiornato")
+    fi
+}
+
+audit_docker() {
+    command -v docker >/dev/null 2>&1 || return 0
+
+    append_report ""
+    append_report "=== Docker audit ==="
+
+    local exited
+    exited=$(docker ps -a --filter "status=exited" --format '{{.Names}} ({{.Image}})' 2>/dev/null || true)
+    if [[ -n "$exited" ]]; then
+        WARNINGS+=("Container Docker fermati (Exited): ${exited//$'\n'/, }")
+        append_report "Exited:"
+        append_report "$exited"
+    fi
+
+    local name image
+    while IFS= read -r line; do
+        [[ -z "$line" ]] && continue
+        name=${line%%|*}
+        image=${line#*|}
+
+        image_is_ignored "$image" && continue
+
+        if [[ "$image" =~ ^[0-9a-f]{12}$ ]]; then
+            WARNINGS+=("Container '$name' usa immagine per ID ($image): preferire un tag versionato")
+        fi
+
+        local pinned
+        for pinned in "${DOCKER_PINNED_IMAGES[@]}"; do
+            if [[ "$image" == "$pinned" ]]; then
+                WARNINGS+=("Container '$name' usa tag bloccato ($pinned): Watchtower non passerà a :latest")
+            fi
+        done
+    done < <(docker ps --format '{{.Names}}|{{.Image}}' 2>/dev/null || true)
+}
+
+audit_pip3() {
+    [[ "$CHECK_PIP3" == true ]] || return 0
+    command -v pip3 >/dev/null 2>&1 || return 0
+
+    append_report ""
+    append_report "=== pip3 outdated (sistema) ==="
+    local outdated count
+    outdated=$(pip3 list --outdated --format=columns 2>/dev/null | tail -n +3 || true)
+    if [[ -n "$outdated" ]]; then
+        count=$(wc -l <<< "$outdated")
+        append_report "$outdated"
+        WARNINGS+=("pip3: $count pacchetti Python di sistema non aggiornati (aggiornamento manuale/consigliato in venv)")
+    else
+        NOTES+=("pip3: tutti aggiornati")
+    fi
+}
+
+build_telegram_summary() {
+    local icon status
+    if ((${#ERRORS[@]} > 0)); then
+        icon="🚨"
+        status="ERRORI"
+    elif ((${#WARNINGS[@]} > 0)); then
+        icon="⚠️"
+        status="WARNINGS"
+    else
+        icon="✅"
+        status="OK"
+    fi
+
+    local msg="${icon} *Manutenzione settimanale ${HOST_LABEL}*
+Stato: *${status}*
+Data: $(date '+%d/%m/%Y %H:%M')"
+
+    if [[ "$APT_CHANGED" == true ]]; then
+        msg+="
+📦 apt: pacchetti aggiornati"
+    fi
+    if [[ "$DOCKER_UPDATED" == true ]]; then
+        msg+="
+🐳 Docker: container aggiornati"
+    fi
+    if [[ "$REBOOT_ON_SUCCESS" == true ]]; then
+        msg+="
+🔄 Reboot host programmato tra ${REBOOT_DELAY_MIN} min (fine manutenzione)"
+    fi
+
+    if ((${#ERRORS[@]} > 0)); then
+        msg+="
+*Errori (${#ERRORS[@]}):*"
+        local e
+        for e in "${ERRORS[@]}"; do
+            msg+="
+• ${e}"
+        done
+    fi
+
+    if ((${#WARNINGS[@]} > 0)); then
+        msg+="
+*Avvisi (${#WARNINGS[@]}):*"
+        local w
+        local n=0
+        for w in "${WARNINGS[@]}"; do
+            ((n++)) || true
+            [[ $n -le 8 ]] && msg+="
+• ${w}"
+        done
+        if ((${#WARNINGS[@]} > 8)); then
+            msg+="
+• … +$((${#WARNINGS[@]} - 8)) avvisi (vedi report)"
+        fi
+    fi
+
+    if ((${#ERRORS[@]} == 0 && ${#WARNINGS[@]} == 0)); then
+        msg+="
+Tutto aggiornato. Log: \`${LOG_FILE}\`"
+    else
+        msg+="
+Report completo allegato o in \`${REPORT_FILE}\`"
+    fi
+
+    send_telegram "$msg"
+    if ((${#ERRORS[@]} > 0 || ${#WARNINGS[@]} > 0)); then
+        send_telegram_document
+    fi
+}
+
+# --- Main ---
+require_root
+
+: > "$REPORT_FILE"
+log "========== Inizio manutenzione settimanale ($HOST_LABEL) =========="
+append_report "Manutenzione settimanale - $HOST_LABEL"
+append_report "Avviata: $(date '+%Y-%m-%d %H:%M:%S')"
+append_report "Host: $(hostname -f) ($(hostname -I | awk '{print $1}'))"
+
+load_telegram_token || true
+
+# 1. Aggiornamento pacchetti sistema
+if apt update >> "$REPORT_FILE" 2>&1; then
+    NOTES+=("apt update OK")
+    log "✓ apt update"
+else
+    ERRORS+=("apt update")
+    log "✗ apt update fallito"
+fi
+
+BEFORE_UPGRADES=$(apt list --upgradable 2>/dev/null | tail -n +2 | wc -l || echo 0)
+if apt full-upgrade -y >> "$REPORT_FILE" 2>&1; then
+    NOTES+=("apt full-upgrade OK")
+    log "✓ apt full-upgrade"
+    AFTER_UPGRADES=$(apt list --upgradable 2>/dev/null | tail -n +2 | wc -l || echo 0)
+    if [[ "$BEFORE_UPGRADES" -gt "$AFTER_UPGRADES" ]] || [[ "$BEFORE_UPGRADES" -gt 0 ]]; then
+        APT_CHANGED=true
+        REBOOT_RECOMMENDED=true
+    fi
+else
+    ERRORS+=("apt full-upgrade")
+    log "✗ apt full-upgrade fallito"
+fi
+
+run_step "apt autoremove" apt autoremove -y
+audit_apt
+
+# 2. Pi-hole
+if [[ -x "$PIHOLE_BIN" ]]; then
+    run_step "pihole -up" "$PIHOLE_BIN" -up
+    audit_pihole_versions
+else
+    ERRORS+=("pihole non trovato in $PIHOLE_BIN")
+fi
+
+# 3. EEPROM firmware
+audit_eeprom
+
+# 4. Aggiornamento container Docker (Watchtower run-once, sostituisce il daemon schedulato)
+run_watchtower
+
+# 5. Audit residui
+audit_docker
+audit_pip3
+
+append_report ""
+append_report "=== Riepilogo ==="
+append_report "Errori: ${#ERRORS[@]}"
+append_report "Avvisi: ${#WARNINGS[@]}"
+if ((${#ERRORS[@]} > 0)); then
+    append_report "Dettaglio errori:"
+    printf '%s\n' "${ERRORS[@]}" >> "$REPORT_FILE"
+fi
+if ((${#WARNINGS[@]} > 0)); then
+    append_report "Dettaglio avvisi:"
+    printf '%s\n' "${WARNINGS[@]}" >> "$REPORT_FILE"
+fi
+append_report "Fine: $(date '+%Y-%m-%d %H:%M:%S')"
+
+build_telegram_summary
+
+# 6. Reboot fisso di conclusione (salvo --no-reboot o REBOOT_ON_SUCCESS=false in conf)
+if [[ "$REBOOT_ON_SUCCESS" == true ]]; then
+    log "Reboot host programmato tra ${REBOOT_DELAY_MIN} minuti (fine manutenzione settimanale)"
+    append_report ""
+    append_report "=== Reboot ==="
+    append_report "Programmato tra ${REBOOT_DELAY_MIN} minuti"
+    shutdown -r "+${REBOOT_DELAY_MIN}" "Manutenzione settimanale ${HOST_LABEL}" || {
+        ERRORS+=("shutdown -r (reboot programmato)")
+        log "✗ Impossibile programmare il reboot"
+    }
+else
+    log "Reboot disabilitato (--no-reboot o REBOOT_ON_SUCCESS=false)"
+    append_report ""
+    append_report "=== Reboot ==="
+    append_report "Saltato (disabilitato)"
+fi
+
+log "========== Fine manutenzione settimanale =========="
+exit $(( ${#ERRORS[@]} > 0 ? 1 : 0 ))
@@ -207,6 +207,15 @@ def telegram_send_html(message_html: str, chat_ids: Optional[List[str]] = None)
            except Exception as e:
                LOGGER.exception("Telegram exception chat_id=%s err=%s", chat_id, e)

+    if sent_ok:
+        try:
+            import sys
+            sys.path.insert(0, "/home/daniely/docker/shared")
+            from loogle_core.alert_dispatcher import mirror_to_web
+            mirror_to_web(message_html, "civil_protection", "warning", is_html=True)
+        except Exception:
+            pass
+
    return sent_ok

 def load_state() -> dict:
@@ -12,12 +12,15 @@ import subprocess
 import tempfile
 import time
 from logging.handlers import RotatingFileHandler
-from typing import Optional, List, Tuple
+from typing import Any, Dict, Optional, List, Tuple

 DEBUG = os.environ.get("DEBUG", "0").strip() == "1"

 SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-LOG_FILE = os.path.join(SCRIPT_DIR, "daily_report.log")
+_default_log = os.path.join(SCRIPT_DIR, "daily_report.log")
+if not os.access(SCRIPT_DIR, os.W_OK):
+    _default_log = "/data/daily_report.log"
+LOG_FILE = os.environ.get("DAILY_REPORT_LOG", _default_log)

 TELEGRAM_CHAT_IDS = ["64463169", "24827341", "132455422", "5405962012"]

@@ -215,24 +218,24 @@ def docker_copy_db_to_temp() -> str:
        return ""


-def generate_report(db_path: str) -> Optional[str]:
+def generate_report_data(db_path: str) -> Optional[Dict[str, Any]]:
+    """Aggrega gli speedtest completati nelle ultime 24 ore."""
    now_utc = datetime.datetime.now(datetime.timezone.utc)
    window_start_utc = now_utc - datetime.timedelta(hours=24)

    try:
        conn = sqlite3.connect(db_path)
        cursor = conn.cursor()
-
-        # NOTA: non filtriamo su created_at (string compare fragile).
-        # Prendiamo le ultime MAX_ROWS righe completate e filtriamo in Python.
-        query = """
+        cursor.execute(
+            """
            SELECT download, upload, ping, created_at
            FROM results
            WHERE status = 'completed'
            ORDER BY created_at DESC
            LIMIT ?
-        """
-        cursor.execute(query, (MAX_ROWS,))
+            """,
+            (MAX_ROWS,),
+        )
        raw_rows = cursor.fetchall()
    except Exception as e:
        LOGGER.exception("Errore DB (%s): %s", db_path, e)
@@ -247,13 +250,14 @@ def generate_report(db_path: str) -> Optional[str]:
        LOGGER.info("Nessun test trovato.")
        return None

-    # Filtra realmente per datetime (ultime 24h) e ordina crescente
-    rows: List[Tuple[datetime.datetime, float, float, float]] = []
+    rows: List[Dict[str, Any]] = []
+    total_down = 0.0
+    total_up = 0.0
+    issues = 0
+
    for d_raw, u_raw, ping_raw, created_at in raw_rows:
        dt_utc = _parse_created_at_utc(created_at)
-        if not dt_utc:
-            continue
-        if dt_utc < window_start_utc or dt_utc > now_utc:
+        if not dt_utc or dt_utc < window_start_utc or dt_utc > now_utc:
            continue

        d_mbps = _to_mbps(d_raw)
@@ -263,60 +267,75 @@ def generate_report(db_path: str) -> Optional[str]:
        except Exception:
            ping_ms = 0.0

-        rows.append((dt_utc, d_mbps, u_mbps, ping_ms))
+        below = d_mbps < WARN_DOWN or u_mbps < WARN_UP
+        if below:
+            issues += 1

-    rows.sort(key=lambda x: x[0])
+        total_down += d_mbps
+        total_up += u_mbps
+        rows.append({
+            "time": dt_utc.astimezone().strftime("%H:%M"),
+            "created_at": dt_utc.astimezone().isoformat(),
+            "download_mbps": round(d_mbps, 1),
+            "upload_mbps": round(u_mbps, 1),
+            "ping_ms": round(ping_ms, 1),
+            "below_threshold": below,
+        })

-    LOGGER.debug("DB rows read=%s filtered_24h=%s (start=%s now=%s)",
-                 len(raw_rows), len(rows),
-                 window_start_utc.isoformat(timespec="seconds"),
-                 now_utc.isoformat(timespec="seconds"))
+    rows.sort(key=lambda r: r["created_at"])

    if not rows:
        LOGGER.info("Nessun test nelle ultime 24h dopo filtro datetime.")
        return None

-    header = "ORA  |  Dn |  Up | Pg |!"
-    sep    = "-----+-----+-----+----+-"
-
-    total_down = 0.0
-    total_up = 0.0
-    count = 0
-    issues = 0
-
+    count = len(rows)
+    avg_d = total_down / count
+    avg_u = total_up / count
    now_local = datetime.datetime.now()
-    msg = f"📊 **REPORT VELOCITÀ 24H**\n📅 {now_local.strftime('%d/%m/%Y')}\n\n"

+    return {
+        "date": now_local.strftime("%d/%m/%Y"),
+        "window_hours": 24,
+        "count": count,
+        "issues": issues,
+        "warn_download_mbps": WARN_DOWN,
+        "warn_upload_mbps": WARN_UP,
+        "avg_download_mbps": round(avg_d, 1),
+        "avg_upload_mbps": round(avg_u, 1),
+        "avg_download_ok": avg_d >= WARN_DOWN,
+        "avg_upload_ok": avg_u >= WARN_UP,
+        "rows": rows,
+    }
+
+
+def generate_report(db_path: str) -> Optional[str]:
+    data = generate_report_data(db_path)
+    if not data:
+        return None
+
+    header = "ORA  |  Dn |  Up | Pg |!"
+    sep = "-----+-----+-----+----+-"
+
+    msg = f"📊 **REPORT VELOCITÀ 24H**\n📅 {data['date']}\n\n"
    msg += "```text\n"
    msg += header + "\n"
    msg += sep + "\n"

-    for dt_utc, d_mbps, u_mbps, ping_ms in rows:
-        total_down += d_mbps
-        total_up += u_mbps
-        count += 1
-
-        flag = " "
-        if d_mbps < WARN_DOWN or u_mbps < WARN_UP:
-            issues += 1
-            flag = "!"
-
-        time_str = dt_utc.astimezone().strftime("%H:%M")
-
-        msg += f"{time_str:<5}|{int(round(d_mbps)):>5}|{int(round(u_mbps)):>5}|{int(round(ping_ms)):>4}|{flag}\n"
+    for row in data["rows"]:
+        flag = "!" if row["below_threshold"] else " "
+        msg += (
+            f"{row['time']:<5}|{int(round(row['download_mbps'])):>5}|"
+            f"{int(round(row['upload_mbps'])):>5}|{int(round(row['ping_ms'])):>4}|{flag}\n"
+        )

    msg += "```\n"

-    avg_d = total_down / count
-    avg_u = total_up / count
+    icon_d = "✅" if data["avg_download_ok"] else "⚠️"
+    icon_u = "✅" if data["avg_upload_ok"] else "⚠️"
+    msg += f"Ø ⬇️{icon_d}`{data['avg_download_mbps']:.0f} Mbps` ⬆️{icon_u}`{data['avg_upload_mbps']:.0f} Mbps`"

-    icon_d = "✅" if avg_d >= WARN_DOWN else "⚠️"
-    icon_u = "✅" if avg_u >= WARN_UP else "⚠️"
-
-    msg += f"Ø ⬇️{icon_d}`{avg_d:.0f} Mbps` ⬆️{icon_u}`{avg_u:.0f} Mbps`"
-
-    if issues > 0:
-        msg += f"\n\n⚠️ **{issues}** test sotto soglia (!)"
+    if data["issues"] > 0:
+        msg += f"\n\n⚠️ **{data['issues']}** test sotto soglia (!)"

    return msg

@@ -21,6 +21,7 @@ from __future__ import annotations

 import argparse
 import glob
+import json
 import logging
 import os
 import sys
@@ -692,6 +693,85 @@ def telegram_send_message(text: str, chat_id: str) -> bool:
        return False


+def build_fotovoltaico_json(
+    lat: float = HOME_LAT,
+    lon: float = HOME_LON,
+    maps_dir: Optional[str] = None,
+) -> Dict[str, Any]:
+    """Analisi completa per WebApp (senza Telegram)."""
+    now = datetime.now(TZINFO)
+    payload: Dict[str, Any] = {
+        "updated_at": now.strftime("%d/%m/%Y %H:%M"),
+        "plant": {
+            "kwp": round(P_PEAK_TOTAL_W / 1000, 2),
+            "inverter_kw": INVERTER_KW,
+            "panels": NUM_PANELS,
+        },
+        "maps": {"past": None, "future": None},
+        "past_days": [],
+        "future_days": [],
+        "models": [],
+        "has_real": False,
+    }
+
+    solaredge_api_key, solaredge_site_id = load_solaredge_config()
+    real_48h: Optional[Tuple[List[datetime], List[float]]] = None
+    if solaredge_api_key and solaredge_site_id:
+        real_48h = fetch_solaredge_energy_48h(solaredge_api_key, solaredge_site_id)
+        payload["has_real"] = bool(real_48h)
+
+    hist = fetch_historical_48h(lat, lon)
+    if hist:
+        times_past, _, power_past = hist
+        past_days = kwh_per_day_from_series(times_past, power_past)
+        real_by_date: Dict[str, float] = {}
+        if real_48h:
+            real_days = kwh_per_day_from_series(
+                [t.isoformat() for t in real_48h[0]],
+                real_48h[1],
+            )
+            real_by_date = {d: k for d, k in real_days}
+        for label, kwh in past_days:
+            row: Dict[str, Any] = {"date": label, "forecast_kwh": kwh}
+            if label in real_by_date:
+                row["real_kwh"] = real_by_date[label]
+            payload["past_days"].append(row)
+        if maps_dir:
+            os.makedirs(maps_dir, exist_ok=True)
+            rt, rp = (real_48h[0], real_48h[1]) if real_48h else (None, None)
+            img_past = plot_past_48h(times_past, power_past, real_times=rt, real_power_kw=rp)
+            with open(os.path.join(maps_dir, "fotovoltaico_past.png"), "wb") as f:
+                f.write(img_past)
+            payload["maps"]["past"] = "past"
+
+    fore_multi = fetch_forecast_72h_multi(lat, lon)
+    if fore_multi:
+        times_fut, power_series = fore_multi
+        payload["models"] = [s[0] for s in power_series]
+        fut_days_per_model = [
+            (name, kwh_per_day_from_series(times_fut, power_list))
+            for name, power_list in power_series
+        ]
+        dates = sorted({d for _, days_list in fut_days_per_model for d, _ in days_list})
+        for d in dates:
+            row = {"date": d, "models": []}
+            for name, days_list in fut_days_per_model:
+                val = next((k for lbl, k in days_list if lbl == d), None)
+                if val is not None:
+                    row["models"].append({"name": name, "kwh": val})
+            payload["future_days"].append(row)
+        if maps_dir:
+            os.makedirs(maps_dir, exist_ok=True)
+            img_fut = plot_future_72h(times_fut, power_series)
+            with open(os.path.join(maps_dir, "fotovoltaico_future.png"), "wb") as f:
+                f.write(img_fut)
+            payload["maps"]["future"] = "future"
+
+    if not payload["past_days"] and not payload["future_days"]:
+        payload["error"] = "Nessun dato disponibile"
+    return payload
+
+
 def main() -> int:
    parser = argparse.ArgumentParser(description="Previsione e analisi produzione fotovoltaico (ICON Italia)")
    parser.add_argument("--lat", type=float, default=HOME_LAT, help="Latitudine")
@@ -700,7 +780,15 @@ def main() -> int:
    parser.add_argument("--chat_id", type=str, default="", help="Chat ID per invio Telegram")
    parser.add_argument("--no-past", action="store_true", help="Salta grafico 48h passate")
    parser.add_argument("--no-future", action="store_true", help="Salta grafico 72h future")
+    parser.add_argument("--json", action="store_true", help="Output JSON per WebApp (no Telegram)")
+    parser.add_argument("--maps-dir", type=str, default="", help="Directory per salvare grafici PNG (con --json)")
    args = parser.parse_args()
+
+    if args.json:
+        maps_dir = args.maps_dir.strip() or None
+        print(json.dumps(build_fotovoltaico_json(args.lat, args.lon, maps_dir=maps_dir), ensure_ascii=False))
+        return 0
+
    lat, lon = args.lat, args.lon
    send_telegram = args.telegram and args.chat_id.strip()

@@ -6,20 +6,29 @@ import sys
 import logging
 import os
 import time
-from typing import Optional, List
+import json
+from typing import Optional, List, Dict, Any, Union
 from zoneinfo import ZoneInfo
 from dateutil import parser as date_parser
 from open_meteo_client import open_meteo_get
+from open_meteo_precip import (
+    CASA_LAT,
+    CASA_LON,
+    CASA_TZ,
+    daily_precip_from_hourly,
+    hourly_precip_mm,
+    is_casa,
+)

 # Setup logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)

 # --- CONFIGURAZIONE METEO ---
-HOME_LAT = 43.9356
-HOME_LON = 12.4296
+HOME_LAT = CASA_LAT
+HOME_LON = CASA_LON
 HOME_NAME = "🏠 Casa"
-TZ = "Europe/Berlin"
+TZ = CASA_TZ
 TZINFO = ZoneInfo(TZ)

 OPEN_METEO_URL = "https://api.open-meteo.com/v1/forecast"
@@ -300,10 +309,10 @@ def get_visibility_forecast(lat, lon):
        logger.error("Visibility request error: %s elapsed=%.2fs", e, time.time() - t0)
    return None

-def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT", timezone=None) -> str:
+def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT", timezone=None, as_json=False) -> Union[str, Dict[str, Any]]:
    t_total = time.time()
    # Determina se è Casa
-    is_home = (abs(lat - HOME_LAT) < 0.01 and abs(lon - HOME_LON) < 0.01)
+    is_home = is_casa(lat, lon)
    
    # Fuso per l'API: Casa = TZ; località = timezone esplicito/geocoding, altrimenti "auto" (Open-Meteo risolve da lat/lon)
    tz_for_api = timezone if timezone else (TZ if is_home else "auto")
@@ -446,6 +455,8 @@ def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT",
    
    # Separa in blocchi per giorno: cambia intestazione quando passa da 23 a 00
    blocks = []
+    json_blocks: List[Dict[str, Any]] = []
+    json_block_map: Dict[str, Dict[str, Any]] = {}
    header = f"{'LT':<2} {'T°':>4} {'h%':>3} {'mm':<3} {'Vento':<5} {'Nv%':>5} {'Sk':<2} {'Sx':<2}"
    separator = "-" * 31
    
@@ -506,8 +517,7 @@ def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT",
            Code = int(get_val(l_code[idx], 0))
            Rain = get_val(l_rain[idx], 0)
            Showers = get_val(l_showers[idx], 0) if idx < len(l_showers) else 0
-            # Per modelli che espongono rain+showers (es. ICON Italia), usa il totale se precipitation è assente/zero
-            Pr_display = max(Pr, Rain + Showers)
+            Pr_display = hourly_precip_mm(Pr, Rain, Showers)
            
            # Determina se è neve
            is_snowing = Sn > 0 or (Code in [71, 73, 75, 77, 85, 86])
@@ -582,6 +592,39 @@ def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT",
            sky_fmt = f"{sky}{uv_suffix}"

            current_block_lines.append(f"{dt.strftime('%H'):<2} {t_s:>4} {Rh:>3} {p_s:>3} {w_fmt} {cl_str:>5} {sky_fmt:<2} {sgx:<2}")
+
+            day_key = day_date.isoformat()
+            if day_key not in json_block_map:
+                day_label = f"{['Lun','Mar','Mer','Gio','Ven','Sab','Dom'][day_date.weekday()]} {day_date.day}"
+                json_block_map[day_key] = {"day_label": day_label, "date": day_key, "rows": []}
+                json_blocks.append(json_block_map[day_key])
+            json_block_map[day_key]["rows"].append({
+                "hour": dt.strftime("%H"),
+                "datetime": dt.isoformat(),
+                "temp_c": round(T, 1),
+                "temp_display": t_s,
+                "feels_offset": t_suffix,
+                "humidity": Rh,
+                "precip_mm": round(Pr_display, 1),
+                "precip_display": p_s,
+                "snow_cm": round(Sn, 1),
+                "weathercode": Code,
+                "wind_speed_kmh": round(Wspd, 0),
+                "wind_gust_kmh": round(Gust, 0),
+                "wind_display": w_txt.strip(),
+                "wind_cardinal": card,
+                "cloud_pct": cl_str,
+                "cloud_type": dominant_type,
+                "visibility_m": round(Vis, 0),
+                "uv_index": round(UV, 1),
+                "uv_suffix": uv_suffix,
+                "cape": round(Cape, 0),
+                "is_day": bool(IsDay),
+                "sky_icon": sky_fmt,
+                "side_icon": sgx,
+                "is_fog": is_fog,
+                "is_snow": is_snowing,
+            })
        
        hours_from_start += 1
    
@@ -593,7 +636,49 @@ def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT",
    if not blocks:
        return f"❌ Nessun dato da mostrare nelle prossime 48 ore (da {current_hour.strftime('%H:%M')})."
    
-    report = f"🌤️ *METEO REPORT*\n📍 {location_name}\n🧠 Fonte: {model_name}\n\n" + "\n\n".join(blocks)
+    daily_totals = daily_precip_from_hourly(hourly_c)
+    today_str = datetime.datetime.now(tz_to_use_info).date().isoformat()
+    tomorrow_str = (datetime.datetime.now(tz_to_use_info).date() + datetime.timedelta(days=1)).isoformat()
+    today_mm = daily_totals.get(today_str, 0.0)
+    tomorrow_mm = daily_totals.get(tomorrow_str, 0.0)
+    totals_line = (
+        f"\n\n💧 *Precip cumulata:* oggi {today_mm:.1f} mm | domani {tomorrow_mm:.1f} mm"
+    )
+
+    legend = {
+        "temp": "W=wind chill, H=heat index",
+        "precip": "G=grandine, Z=ghiacciato, N=neve",
+        "cloud": "FOG=nebbia",
+        "sky": "Icona condizioni (☀️🌧️⛈️…)",
+        "sx": "☃️ neve · 🧊 ghiaccio · ⚡/🌪️ temporali · 🥵 caldo · ☔️ pioggia · 💨 vento forte",
+        "uv": "E=UV estremo, H=UV alto",
+    }
+
+    if as_json:
+        return {
+            "location": location_name,
+            "model": model_name,
+            "timezone": tz_to_use,
+            "blocks": json_blocks,
+            "precip_totals": {"today_mm": round(today_mm, 1), "tomorrow_mm": round(tomorrow_mm, 1)},
+            "legend": legend,
+            "columns": [
+                {"key": "hour", "label": "LT", "title": "Ora locale"},
+                {"key": "temp_display", "label": "T°", "title": "Temperatura"},
+                {"key": "humidity", "label": "h%", "title": "Umidità"},
+                {"key": "precip_display", "label": "mm", "title": "Precipitazioni orarie"},
+                {"key": "wind_display", "label": "Vento", "title": "Direzione e intensità (km/h)"},
+                {"key": "cloud_pct", "label": "Nv%", "title": "Copertura nuvolosa"},
+                {"key": "sky_icon", "label": "Sk", "title": "Cielo"},
+                {"key": "side_icon", "label": "Sx", "title": "Indicatori secondari"},
+            ],
+        }
+
+    report = (
+        f"🌤️ *METEO REPORT*\n📍 {location_name}\n🧠 Fonte: {model_name}\n\n"
+        + "\n\n".join(blocks)
+        + totals_line
+    )
    logger.info("generate_weather_report ok elapsed=%.2fs", time.time() - t_total)
    return report

@@ -604,6 +689,7 @@ if __name__ == "__main__":
    args_parser.add_argument("--debug", action="store_true", help="Mostra dettaglio debug (nuvole, neve)")
    args_parser.add_argument("--chat_id", help="Chat ID Telegram per invio diretto (opzionale, può essere multiplo separato da virgola)")
    args_parser.add_argument("--timezone", help="Timezone IANA (es: Europe/Rome, America/New_York)")
+    args_parser.add_argument("--json", action="store_true", help="Output JSON strutturato (WebApp)")
    args = args_parser.parse_args()

    # Determina chat_ids se specificato
@@ -613,14 +699,21 @@ if __name__ == "__main__":

    # Genera report
    report = None
+    json_out = None
    if args.home:
-        report = generate_weather_report(HOME_LAT, HOME_LON, HOME_NAME, args.debug, "SM")
+        if args.json:
+            json_out = generate_weather_report(HOME_LAT, HOME_LON, HOME_NAME, args.debug, "SM", as_json=True)
+        else:
+            report = generate_weather_report(HOME_LAT, HOME_LON, HOME_NAME, args.debug, "SM")
    elif args.query:
        coords = get_coordinates(args.query)
        if coords:
            lat, lon, name, cc, geo_tz = coords
            tz = args.timezone or geo_tz
-            report = generate_weather_report(lat, lon, name, args.debug, cc, timezone=tz)
+            if args.json:
+                json_out = generate_weather_report(lat, lon, name, args.debug, cc, timezone=tz, as_json=True)
+            else:
+                report = generate_weather_report(lat, lon, name, args.debug, cc, timezone=tz)
        else:
            error_msg = f"❌ Città '{args.query}' non trovata."
            if chat_ids:
@@ -637,7 +730,9 @@ if __name__ == "__main__":
        sys.exit(1)

    # Invia o stampa
-    if chat_ids:
+    if args.json and json_out:
+        print(json.dumps(json_out, ensure_ascii=False))
+    elif chat_ids:
        telegram_send_markdown(report, chat_ids)
    else:
        print(report)
@@ -34,12 +34,24 @@ def log_line(message: str) -> None:
        pass

 def send_telegram(msg, chat_ids: Optional[List[str]] = None):
-    """
-    Args:
-        msg: Messaggio da inviare
-        chat_ids: Lista di chat IDs (default: TELEGRAM_CHAT_IDS)
-    """
-    if not BOT_TOKEN or "INSERISCI" in BOT_TOKEN: return
+    """Invia alert su Telegram e/o WebApp via alert_dispatcher."""
+    try:
+        import sys
+        sys.path.insert(0, "/home/daniely/docker/shared")
+        from loogle_core.alert_dispatcher import dispatch_alert
+        plain = msg.replace("*", "").replace("_", "").replace("`", "")
+        dispatch_alert(
+            "Degrado qualità linea",
+            plain,
+            category="net_quality",
+            severity="warning",
+            telegram_text=msg,
+        )
+        return
+    except Exception:
+        pass
+    if not BOT_TOKEN or "INSERISCI" in BOT_TOKEN:
+        return
    if chat_ids is None:
        chat_ids = TELEGRAM_CHAT_IDS
    url = f"https://api.telegram.org/bot{BOT_TOKEN}/sendMessage"
@@ -158,6 +158,15 @@ def telegram_send_markdown(message: str, chat_ids: Optional[List[str]] = None) -
            except Exception as e:
                LOGGER.exception("Errore invio Telegram chat_id=%s: %s", chat_id, e)

+    if ok_any:
+        try:
+            import sys
+            sys.path.insert(0, "/home/daniely/docker/shared")
+            from loogle_core.alert_dispatcher import mirror_to_web
+            mirror_to_web(message, "nowcast_120m", "warning", is_html=False)
+        except Exception:
+            pass
+
    return ok_any


@@ -0,0 +1,198 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Precipitazione unificata Open-Meteo per Casa (San Marino).
+
+Reference 0–72 h: ICON Italia (ARPAE 2i). Totale orario = max(precipitation, rain + showers).
+
+Copia autosufficiente per il container loogle-bot (/app); la sorgente condivisa
+resta in docker/shared/open_meteo/open_meteo_precip.py.
+"""
+
+from __future__ import annotations
+
+from collections import defaultdict
+from typing import Dict, List, Optional
+
+try:
+    from open_meteo_client import open_meteo_get
+except ImportError:
+    import requests
+
+    def open_meteo_get(url, params=None, headers=None, timeout=(5, 25), retries=3, backoff=0.8):
+        return requests.get(url, params=params, headers=headers or {}, timeout=timeout)
+
+OPEN_METEO_URL = "https://api.open-meteo.com/v1/forecast"
+DEFAULT_HEADERS = {"User-Agent": "open-meteo-precip/1.0"}
+
+CASA_LAT = 43.9356
+CASA_LON = 12.4296
+CASA_TZ = "Europe/Rome"
+ICON_ITALIA_MODEL = "italia_meteo_arpae_icon_2i"
+
+ICON_HOURLY_VARS = (
+    "precipitation,rain,showers,snowfall,weathercode,"
+    "temperature_2m,windspeed_10m,winddirection_10m"
+)
+ICON_DAILY_VARS = (
+    "precipitation_sum,rain_sum,showers_sum,snowfall_sum,weathercode,"
+    "temperature_2m_min,temperature_2m_max"
+)
+
+PRECIP_HOURLY_KEYS = ("precipitation", "rain", "showers", "snowfall")
+PRECIP_DAILY_KEYS = ("precipitation_sum", "rain_sum", "showers_sum", "snowfall_sum", "precipitation_hours")
+
+
+def is_casa(lat: float, lon: float, tol: float = 0.01) -> bool:
+    return abs(lat - CASA_LAT) < tol and abs(lon - CASA_LON) < tol
+
+
+def hourly_precip_mm(
+    precipitation: Optional[float] = None,
+    rain: Optional[float] = None,
+    showers: Optional[float] = None,
+) -> float:
+    p = float(precipitation or 0)
+    r = float(rain or 0)
+    s = float(showers or 0)
+    return max(p, r + s)
+
+
+def hourly_precip_at_index(hourly: Dict, index: int) -> float:
+    def g(key: str) -> Optional[float]:
+        arr = hourly.get(key) or []
+        if index >= len(arr):
+            return None
+        v = arr[index]
+        return float(v) if v is not None else None
+
+    return hourly_precip_mm(g("precipitation"), g("rain"), g("showers"))
+
+
+def hourly_precip_series(hourly: Dict) -> List[float]:
+    times = hourly.get("time") or []
+    return [hourly_precip_at_index(hourly, i) for i in range(len(times))]
+
+
+def daily_precip_from_hourly(hourly: Dict) -> Dict[str, float]:
+    times = hourly.get("time") or []
+    out: Dict[str, float] = defaultdict(float)
+    for i, t in enumerate(times):
+        if not t:
+            continue
+        out[str(t)[:10]] += hourly_precip_at_index(hourly, i)
+    return dict(out)
+
+
+def daily_precip_sum(daily: Dict, date_str: str) -> Optional[float]:
+    times = daily.get("time") or []
+    arr = daily.get("precipitation_sum") or []
+    for i, t in enumerate(times):
+        if str(t)[:10] == date_str[:10] and i < len(arr) and arr[i] is not None:
+            return float(arr[i])
+    return None
+
+
+def fetch_icon_italia(
+    lat: float,
+    lon: float,
+    tz: str = CASA_TZ,
+    forecast_days: int = 10,
+    past_days: int = 0,
+    headers: Optional[Dict[str, str]] = None,
+) -> Optional[Dict]:
+    params = {
+        "latitude": lat,
+        "longitude": lon,
+        "timezone": tz,
+        "forecast_days": forecast_days,
+        "models": ICON_ITALIA_MODEL,
+        "hourly": ICON_HOURLY_VARS,
+        "daily": ICON_DAILY_VARS,
+    }
+    if past_days:
+        params["past_days"] = past_days
+    try:
+        resp = open_meteo_get(
+            OPEN_METEO_URL,
+            params=params,
+            headers=headers or DEFAULT_HEADERS,
+        )
+        if resp.status_code == 200:
+            return resp.json()
+    except Exception:
+        pass
+    return None
+
+
+def _index_by_time(section: Dict) -> Dict[str, int]:
+    return {str(t): i for i, t in enumerate(section.get("time") or [])}
+
+
+def overlay_icon_precip_on_hourly(target: Dict, icon_hourly: Dict) -> Dict:
+    if not target or not icon_hourly:
+        return target
+    tgt_idx = _index_by_time(target)
+    icon_idx = _index_by_time(icon_hourly)
+    out = dict(target)
+    for key in PRECIP_HOURLY_KEYS:
+        arr = list(out.get(key) or [None] * len(out.get("time") or []))
+        while len(arr) < len(out.get("time") or []):
+            arr.append(None)
+        icon_arr = icon_hourly.get(key) or []
+        for t, i in tgt_idx.items():
+            j = icon_idx.get(t)
+            if j is not None and j < len(icon_arr):
+                arr[i] = icon_arr[j]
+        out[key] = arr
+    times = out.get("time") or []
+    out["precipitation"] = [hourly_precip_at_index(out, i) for i in range(len(times))]
+    return out
+
+
+def overlay_icon_precip_on_daily(target: Dict, icon_daily: Dict) -> Dict:
+    if not target or not icon_daily:
+        return target
+    tgt_idx = {str(t)[:10]: i for i, t in enumerate(target.get("time") or [])}
+    icon_idx = {str(t)[:10]: i for i, t in enumerate(icon_daily.get("time") or [])}
+    out = dict(target)
+    for key in PRECIP_DAILY_KEYS:
+        arr = list(out.get(key) or [None] * len(out.get("time") or []))
+        while len(arr) < len(out.get("time") or []):
+            arr.append(None)
+        icon_arr = icon_daily.get(key) or []
+        for d, i in tgt_idx.items():
+            j = icon_idx.get(d)
+            if j is not None and j < len(icon_arr):
+                arr[i] = icon_arr[j]
+        out[key] = arr
+    times = out.get("time") or []
+    psum = list(out.get("precipitation_sum") or [None] * len(times))
+    while len(psum) < len(times):
+        psum.append(None)
+    for d, j in icon_idx.items():
+        i = tgt_idx.get(d)
+        if i is None:
+            continue
+        arr = icon_daily.get("precipitation_sum") or []
+        if j < len(arr) and arr[j] is not None:
+            psum[i] = float(arr[j])
+    out["precipitation_sum"] = psum
+    return out
+
+
+def icon_precip_daily_totals(icon_data: Optional[Dict]) -> Dict[str, float]:
+    if not icon_data:
+        return {}
+    hourly = icon_data.get("hourly") or {}
+    if hourly.get("time"):
+        totals = daily_precip_from_hourly(hourly)
+        if totals:
+            return totals
+    daily = icon_data.get("daily") or {}
+    out: Dict[str, float] = {}
+    for i, t in enumerate(daily.get("time") or []):
+        arr = daily.get("precipitation_sum") or []
+        if i < len(arr) and arr[i] is not None:
+            out[str(t)[:10]] = float(arr[i])
+    return out
@@ -8,19 +8,32 @@ import argparse
 import datetime
 import os
 import sys
+import json
 from zoneinfo import ZoneInfo
 from collections import defaultdict, Counter, Counter
 from typing import List, Dict, Tuple, Optional
 from statistics import mean, median
 from open_meteo_client import open_meteo_get
+from open_meteo_precip import (
+    CASA_LAT,
+    CASA_LON,
+    CASA_TZ,
+    daily_precip_from_hourly,
+    fetch_icon_italia,
+    hourly_precip_at_index,
+    hourly_precip_series,
+    is_casa,
+    overlay_icon_precip_on_daily,
+    overlay_icon_precip_on_hourly,
+)

 # --- CONFIGURAZIONE DEFAULT ---
-DEFAULT_LAT = 43.9356
-DEFAULT_LON = 12.4296
+DEFAULT_LAT = CASA_LAT
+DEFAULT_LON = CASA_LON
 DEFAULT_NAME = "🏠 Casa (Strada Cà Toro,12 - San Marino)"

 # --- TIMEZONE ---
-TZ_STR = "Europe/Berlin"
+TZ_STR = CASA_TZ
 TZINFO = ZoneInfo(TZ_STR)

 # --- TELEGRAM CONFIG ---
@@ -34,6 +47,10 @@ TOKEN_FILE_VOLUME = "/Volumes/Pi2/etc/telegram_dpc_bot_token"
 SOGLIA_VENTO_KMH = 40.0
 MIN_MM_PER_EVENTO = 0.1

+# Giorni mostrati in tabella / WebApp (previsione 7 giorni)
+DISPLAY_FORECAST_DAYS = 7
+GIORNI_ITA_SHORT = ["Lun", "Mar", "Mer", "Gio", "Ven", "Sab", "Dom"]
+
 # --- MODELLI METEO ---
 # Modelli a breve termine (alta risoluzione, 48-72h)
 SHORT_TERM_MODELS = ["meteofrance_seamless", "icon_d2"]  # Usa seamless invece di arome_france_hd
@@ -235,6 +252,7 @@ def get_weather_multi_model(lat, lon, short_term_models, long_term_models, forec
                results[model] = None
    
    # Recupera modelli a lungo termine (3-10d): tre modelli per mediana (come Agent Irrigazione)
+    short_set = set(short_term_models or [])
    for model in (long_term_models or []):
        url = "https://api.open-meteo.com/v1/forecast"
        fd_long = LONG_TERM_FORECAST_DAYS.get(model, forecast_days)
@@ -276,13 +294,16 @@ def get_weather_multi_model(lat, lon, short_term_models, long_term_models, forec
                            snow_depth_cm.append(None)
                    hourly_data["snow_depth"] = snow_depth_cm
                    data["hourly"] = hourly_data
-                results[model] = data
-                results[model]["model_type"] = "long_term"
+                lt_key = f"{model}__long" if model in short_set else model
+                results[lt_key] = data
+                results[lt_key]["model_type"] = "long_term"
            else:
-                results[model] = None
+                lt_key = f"{model}__long" if model in short_set else model
+                results[lt_key] = None
        except Exception:
-            results[model] = None
-    
+            lt_key = f"{model}__long" if model in short_set else model
+            results[lt_key] = None
+
    return results


@@ -303,9 +324,13 @@ def _median_or_single(values):
    return median(nums)


-# Chiavi che esistono solo su ICON Italia (no merge, si tiene il valore da quel modello)
-HOURLY_KEYS_ICON_ONLY = ["snow_depth", "showers"]
-DAILY_KEYS_ICON_ONLY = ["showers_sum"]
+# Chiavi solo ICON Italia (precip 0–2d: niente mediana con AROME HD a San Marino)
+HOURLY_KEYS_ICON_ONLY = [
+    "snow_depth", "showers", "precipitation", "rain", "snowfall",
+]
+DAILY_KEYS_ICON_ONLY = [
+    "showers_sum", "precipitation_sum", "rain_sum", "snowfall_sum", "precipitation_hours",
+]


 def _merge_hourly_median(hourly_by_model, single_source_keys=None, single_source_model=None):
@@ -614,6 +639,23 @@ def merge_multi_model_forecast(models_data, forecast_days=10):
    
    return merged

+def format_day_label(day_index: int, daily_time_list, with_relative: bool = True) -> str:
+    """Etichetta calendario per indice giorno 0-based (es. Lun 12/07)."""
+    if daily_time_list and 0 <= day_index < len(daily_time_list):
+        raw = str(daily_time_list[day_index]).split("T")[0]
+        try:
+            dt = datetime.datetime.strptime(raw, "%Y-%m-%d")
+            cal = f"{GIORNI_ITA_SHORT[dt.weekday()]} {dt.strftime('%d/%m')}"
+            if with_relative:
+                if day_index == 0:
+                    return f"oggi ({cal})"
+                if day_index == 1:
+                    return f"domani ({cal})"
+            return cal
+        except ValueError:
+            pass
+    return f"giorno {day_index + 1}"
+
 def analyze_temperature_trend(daily_temps_max, daily_temps_min, days=10):
    """Analizza trend temperatura per identificare fronti caldi/freddi con dettaglio completo"""
    if not daily_temps_max or not daily_temps_min:
@@ -731,7 +773,7 @@ def analyze_weather_transitions(daily_weathercodes):
        if code in (95, 96, 99): return "temporale"
        return "variabile"
    
-    for i in range(1, min(len(daily_weathercodes), 8)):
+    for i in range(1, min(len(daily_weathercodes), DISPLAY_FORECAST_DAYS)):
        prev_code = daily_weathercodes[i-1] if i-1 < len(daily_weathercodes) else None
        curr_code = daily_weathercodes[i] if i < len(daily_weathercodes) else None
        prev_cat = get_category(prev_code)
@@ -1014,13 +1056,13 @@ def generate_practical_advice(trend, transitions, events_summary, daily_data):
    
    return advice

-def format_detailed_trend_explanation(trend, daily_data_list):
-    """Genera spiegazione dettagliata del trend temperatura su 10 giorni"""
+def format_detailed_trend_explanation(trend, daily_time_list=None, display_days=DISPLAY_FORECAST_DAYS):
+    """Genera spiegazione dettagliata del trend temperatura sui giorni in previsione."""
    if not trend:
        return ""
    
    explanation = []
-    explanation.append(f"📊 <b>EVOLUZIONE TEMPERATURE (10 GIORNI)</b>\n")
+    explanation.append(f"📊 <b>EVOLUZIONE TEMPERATURE ({display_days} GIORNI)</b>\n")
    
    # Trend principale con spiegazione chiara
    trend_type = trend["type"]
@@ -1052,13 +1094,16 @@ def format_detailed_trend_explanation(trend, daily_data_list):
    explanation.append(f"{trend_desc}{intensity_text}")
    explanation.append(f"{desc_text}")
    
-    # Aggiungi solo picchi significativi in modo sintetico
+    # Aggiungi solo picchi significativi in modo sintetico (entro i giorni in tabella)
    if trend.get("change_days"):
-        significant_changes = [c for c in trend["change_days"] if abs(c['delta']) > 3.0][:3]
+        significant_changes = [
+            c for c in trend["change_days"]
+            if abs(c["delta"]) > 3.0 and c["day"] < display_days
+        ][:3]
        if significant_changes:
            change_texts = []
            for change in significant_changes:
-                day_name = f"Giorno {change['day']+1}"
+                day_name = format_day_label(change["day"], daily_time_list or [])
                direction = "↑" if change['delta'] > 0 else "↓"
                change_texts.append(f"{direction} {day_name}: {change['from']:.0f}°→{change['to']:.0f}°C")
            if change_texts:
@@ -1068,7 +1113,35 @@ def format_detailed_trend_explanation(trend, daily_data_list):
    
    return "\n".join(explanation)

-def format_weather_context_report(models_data, location_name, country_code):
+def _apply_unified_precip(hourly: Dict, daily: Dict, casa: bool) -> Tuple[Dict, Dict]:
+    """Precip oraria/giornaliera da ICON Italia (ARPAE 2i) per Casa."""
+    if not casa or not hourly.get("time"):
+        return hourly, daily
+    hourly = dict(hourly)
+    daily = dict(daily)
+    icon = fetch_icon_italia(CASA_LAT, CASA_LON, CASA_TZ, forecast_days=10)
+    if icon:
+        icon_h = icon.get("hourly") or {}
+        icon_d = icon.get("daily") or {}
+        if icon_h.get("time"):
+            hourly = overlay_icon_precip_on_hourly(hourly, icon_h)
+        if icon_d.get("time"):
+            daily = overlay_icon_precip_on_daily(daily, icon_d)
+    hourly["precipitation"] = hourly_precip_series(hourly)
+    totals = daily_precip_from_hourly(hourly)
+    times = daily.get("time") or []
+    psum = list(daily.get("precipitation_sum") or [])
+    while len(psum) < len(times):
+        psum.append(None)
+    for i, t in enumerate(times):
+        d = str(t)[:10]
+        if d in totals:
+            psum[i] = round(totals[d], 2)
+    daily["precipitation_sum"] = psum
+    return hourly, daily
+
+
+def format_weather_context_report(models_data, location_name, country_code, as_json=False):
    """Genera report contestuale intelligente con ensemble multi-modello"""
    # Combina modelli a breve e lungo termine
    merged_data = merge_multi_model_forecast(models_data, forecast_days=10)
@@ -1079,6 +1152,10 @@ def format_weather_context_report(models_data, location_name, country_code):
    hourly = merged_data.get('hourly', {})
    daily = merged_data.get('daily', {})
    models_used = merged_data.get('models_used', [])
+    casa = country_code in ("SM", "IT")
+    hourly, daily = _apply_unified_precip(hourly, daily, casa)
+    merged_data["hourly"] = hourly
+    merged_data["daily"] = daily
    
    if not daily or not daily.get('time'):
        return "❌ Errore: Dati meteo incompleti"
@@ -1089,21 +1166,30 @@ def format_weather_context_report(models_data, location_name, country_code):
    models_text = " + ".join(models_used) if models_used else "Multi-modello"
    msg_parts.append(f"🌍 <b>METEO FORECAST</b>")
    msg_parts.append(f"{location_name.upper()}")
-    msg_parts.append(f"📡 <i>Ensemble: {models_text}</i>\n")
+    msg_parts.append(f"📡 <i>Ensemble: {models_text}</i>")
+    if casa:
+        msg_parts.append(f"💧 <i>Precipitazioni 0–2g: ICON Italia (ARPAE 2i)</i>\n")
+    else:
+        msg_parts.append("")
    
-    # ANALISI TREND TEMPERATURA (Fronti) - Completa su 10 giorni
+    # ANALISI TREND TEMPERATURA (Fronti) — allineato ai giorni mostrati in tabella
    daily_temps_max = daily.get('temperature_2m_max', [])
    daily_temps_min = daily.get('temperature_2m_min', [])
-    trend = analyze_temperature_trend(daily_temps_max, daily_temps_min, days=10)
+    daily_time_list = daily.get('time', [])
+    trend = analyze_temperature_trend(
+        daily_temps_max, daily_temps_min, days=DISPLAY_FORECAST_DAYS
+    )
+    trend_explanation = ""
    
    # Spiegazione dettagliata trend (sempre, anche se stabile)
    if trend:
-        trend_explanation = format_detailed_trend_explanation(trend, daily_data_list=[])
+        trend_explanation = format_detailed_trend_explanation(
+            trend, daily_time_list=daily_time_list, display_days=DISPLAY_FORECAST_DAYS
+        )
        if trend_explanation:
            msg_parts.append(trend_explanation)
    
    # ANALISI TRANSIZIONI METEO - Include anche precipitazioni prossimi giorni
-    daily_time_list = daily.get('time', [])  # Definito qui per uso successivo
    daily_weathercodes = daily.get('weathercode', [])
    transitions = analyze_weather_transitions(daily_weathercodes)
    
@@ -1115,12 +1201,10 @@ def format_weather_context_report(models_data, location_name, country_code):
    if transitions:
        significant_trans = [t for t in transitions if t.get("significant", False)]
        for trans in significant_trans[:5]:
-            day_names = ["oggi", "domani", "dopodomani", "fra 3 giorni", "fra 4 giorni", "fra 5 giorni", "fra 6 giorni"]
-            day_idx = trans["day"] - 1
-            if day_idx < len(day_names):
-                day_ref = day_names[day_idx]
-            else:
-                day_ref = f"fra {trans['day']} giorni"
+            day_idx = trans["day"]
+            if day_idx >= DISPLAY_FORECAST_DAYS:
+                continue
+            day_ref = format_day_label(day_idx, daily_time_list)
            weather_changes.append({
                "day": trans["day"],
                "day_ref": day_ref,
@@ -1193,17 +1277,15 @@ def format_weather_context_report(models_data, location_name, country_code):
        
        # Aggiungi solo se supera la soglia appropriata
        if precip_amount > threshold_mm:
-            day_names = ["oggi", "domani", "dopodomani"]
-            if day_idx < len(day_names):
-                weather_changes.append({
-                    "day": day_num,
-                    "day_ref": day_names[day_idx],
-                    "from": "variabile",
-                    "to": "precipitazioni",
-                    "type": "precip",
-                    "amount": precip_amount,
-                    "precip_symbol": precip_type_symbol
-                })
+            weather_changes.append({
+                "day": day_num,
+                "day_ref": format_day_label(day_idx, daily_time_list),
+                "from": "variabile",
+                "to": "precipitazioni",
+                "type": "precip",
+                "amount": precip_amount,
+                "precip_symbol": precip_type_symbol,
+            })
    
    if weather_changes:
        # Ordina per giorno
@@ -1227,7 +1309,7 @@ def format_weather_context_report(models_data, location_name, country_code):
    temp_max_list = daily.get('temperature_2m_max', [])
    
    # Limita ai giorni per cui abbiamo dati daily validi
-    max_days = min(len(daily_time_list), len(temp_min_list), len(temp_max_list), 10)
+    max_days = min(len(daily_time_list), len(temp_min_list), len(temp_max_list), DISPLAY_FORECAST_DAYS)
    
    # Mappa hourly per eventi dettagliati
    daily_map = defaultdict(list)
@@ -1250,7 +1332,10 @@ def format_weather_context_report(models_data, location_name, country_code):
        d_times = [hourly['time'][i] for i in indices if i < len(hourly.get('time', []))]
        d_codes = [hourly.get('weathercode', [])[i] for i in indices if i < len(hourly.get('weathercode', []))]
        d_probs = [hourly.get('precipitation_probability', [])[i] for i in indices if i < len(hourly.get('precipitation_probability', []))]
-        d_precip = [hourly.get('precipitation', [])[i] for i in indices if i < len(hourly.get('precipitation', []))]
+        d_precip = [
+            hourly_precip_at_index(hourly, i)
+            for i in indices if i < len(hourly.get('time', []))
+        ]
        d_snow = [hourly.get('snowfall', [])[i] for i in indices if i < len(hourly.get('snowfall', []))]
        d_winds = [hourly.get('windspeed_10m', [])[i] for i in indices if i < len(hourly.get('windspeed_10m', []))]
        d_winddir = [hourly.get('winddirection_10m', [])[i] for i in indices if i < len(hourly.get('winddirection_10m', []))]
@@ -1342,9 +1427,7 @@ def format_weather_context_report(models_data, location_name, country_code):
        events_summary.append(events_list)

        dt = datetime.datetime.strptime(day_date, "%Y-%m-%d")
-        # Nomi giorni in italiano
-        giorni_ita = ["Lun", "Mar", "Mer", "Gio", "Ven", "Sab", "Dom"]
-        day_str = f"{giorni_ita[dt.weekday()]} {dt.strftime('%d/%m')}"
+        day_str = f"{GIORNI_ITA_SHORT[dt.weekday()]} {dt.strftime('%d/%m')}"
        
        # Icona meteo principale basata sul weathercode del giorno
        wcode = daily.get('weathercode', [])[count] if count < len(daily.get('weathercode', [])) else None
@@ -1662,8 +1745,39 @@ def format_weather_context_report(models_data, location_name, country_code):
        # Aggiorna per il prossimo giorno
        prev_snow_depth_end = snow_depth_end if snow_depth_end is not None else prev_snow_depth_end
        msg_parts.append("")
-    
-    
+
+    if as_json:
+        def _serialize_day(d):
+            out = dict(d)
+            out["events"] = list(d.get("events") or [])
+            for k in ("t_min", "t_max", "precip_sum", "wind_max", "snowfall_sum", "rain_sum", "showers_sum"):
+                if out.get(k) is not None:
+                    out[k] = round(float(out[k]), 1)
+            for k in ("snow_depth_min", "snow_depth_max", "snow_depth_avg", "snow_depth_end"):
+                if out.get(k) is not None:
+                    out[k] = round(float(out[k]), 1)
+            return out
+
+        return {
+            "location": location_name,
+            "country_code": country_code,
+            "models": models_used,
+            "trend_html": trend_explanation if trend else "",
+            "weather_changes": weather_changes,
+            "days": [_serialize_day(d) for d in daily_details],
+            "columns": [
+                {"key": "day_str", "label": "Giorno"},
+                {"key": "weather_icon", "label": ""},
+                {"key": "t_min", "label": "Min°C"},
+                {"key": "t_max", "label": "Max°C"},
+                {"key": "precip_sum", "label": "Precip"},
+                {"key": "precip_detail", "label": "Tipo"},
+                {"key": "wind", "label": "Vento"},
+                {"key": "snow_depth_end", "label": "Manto cm"},
+                {"key": "events", "label": "Eventi"},
+            ],
+        }
+
    return "\n".join(msg_parts)

 def send_telegram(text, chat_id, token, debug_mode=False):
@@ -1689,6 +1803,8 @@ def main():
    parser.add_argument("--debug", action="store_true")
    parser.add_argument("--home", action="store_true")
    parser.add_argument("--timezone", help="Timezone IANA (es: Europe/Rome, America/New_York)")
+    parser.add_argument("--stdout", action="store_true", help="Stampa report su stdout invece di Telegram")
+    parser.add_argument("--json", action="store_true", help="Output JSON strutturato (WebApp)")
    args = parser.parse_args()

    token = get_bot_token()
@@ -1719,7 +1835,7 @@ def main():
    
    # Recupera dati multi-modello (breve + lungo termine) - selezione intelligente basata su country code
    # Determina se è Casa
-    is_home = (abs(lat - DEFAULT_LAT) < 0.01 and abs(lon - DEFAULT_LON) < 0.01)
+    is_home = is_casa(lat, lon)
    
    # Recupera dati multi-modello (breve + lungo termine)
    # - Per Casa: usa AROME Seamless e ICON-D2
@@ -1741,13 +1857,20 @@ def main():
        return
    
    # Genera report
+    if args.json:
+        payload = format_weather_context_report(models_data, name, cc, as_json=True)
+        print(json.dumps(payload, ensure_ascii=False))
+        return
+
    report = format_weather_context_report(models_data, name, cc)
    
    if debug_mode:
        report = f"🛠 <b>[DEBUG MODE]</b> 🛠\n\n{report}"
    
    # Invia
-    if token:
+    if args.stdout:
+        print(report)
+    elif token:
        success = False
        for chat_id in recipients:
            if send_telegram(report, chat_id, token, debug_mode):
@@ -25,11 +25,17 @@ def setup_logger() -> logging.Logger:
    logger.setLevel(logging.INFO)
    logger.handlers.clear()
    
-    fh = RotatingFileHandler(LOG_FILE, maxBytes=1_000_000, backupCount=5, encoding="utf-8")
-    fh.setLevel(logging.DEBUG)
    fmt = logging.Formatter("%(asctime)s %(levelname)s %(message)s")
-    fh.setFormatter(fmt)
-    logger.addHandler(fh)
+    log_path = os.environ.get("ROAD_WEATHER_LOG", LOG_FILE)
+    try:
+        fh = RotatingFileHandler(log_path, maxBytes=1_000_000, backupCount=5, encoding="utf-8")
+        fh.setLevel(logging.DEBUG)
+        fh.setFormatter(fmt)
+        logger.addHandler(fh)
+    except OSError:
+        sh = logging.StreamHandler()
+        sh.setFormatter(fmt)
+        logger.addHandler(sh)
    
    return logger

@@ -121,14 +127,43 @@ WEATHER_CODES = {
 # =============================================================================

 def get_google_maps_api_key() -> Optional[str]:
-    """Ottiene la chiave API di Google Maps da variabile d'ambiente."""
+    """Ottiene la chiave API di Google Maps da variabile d'ambiente o file condiviso."""
    api_key = os.environ.get('GOOGLE_MAPS_API_KEY', '').strip()
    if api_key:
        return api_key
    api_key = os.environ.get('GOOGLE_API_KEY', '').strip()
    if api_key:
        return api_key
-    # Debug: verifica tutte le variabili d'ambiente che contengono GOOGLE
+
+    for path in (
+        os.environ.get("GOOGLE_MAPS_API_KEY_FILE", ""),
+        "/etc/google_maps_api_key",
+        os.path.expanduser("~/.google_maps_api_key"),
+        os.path.join(SCRIPT_DIR, ".env"),
+    ):
+        if not path or not os.path.isfile(path):
+            continue
+        try:
+            if path.endswith(".env"):
+                with open(path, "r", encoding="utf-8") as f:
+                    for line in f:
+                        line = line.strip()
+                        if line.startswith("GOOGLE_MAPS_API_KEY="):
+                            v = line.split("=", 1)[1].strip().strip("'\"")
+                            if v:
+                                return v
+                        elif line.startswith("GOOGLE_API_KEY="):
+                            v = line.split("=", 1)[1].strip().strip("'\"")
+                            if v:
+                                return v
+            else:
+                with open(path, "r", encoding="utf-8") as f:
+                    v = f.read().strip()
+                    if v:
+                        return v
+        except OSError:
+            continue
+
    if os.environ.get('DEBUG_GOOGLE_MAPS', ''):
        google_vars = {k: v[:10] + '...' if len(v) > 10 else v for k, v in os.environ.items() if 'GOOGLE' in k.upper()}
        LOGGER.debug(f"Variabili GOOGLE trovate: {google_vars}")
@@ -433,7 +468,7 @@ def get_weather_data(lat: float, lon: float, model_slug: str) -> Optional[Dict]:
    url = f"https://api.open-meteo.com/v1/forecast"
    
    # Parametri base (aggiunto soil_temperature_0cm per analisi ghiaccio più accurata)
-    hourly_params = "temperature_2m,relative_humidity_2m,precipitation,rain,showers,snowfall,weathercode,visibility,wind_speed_10m,wind_gusts_10m,soil_temperature_0cm,dew_point_2m"
+    hourly_params = "temperature_2m,relative_humidity_2m,precipitation,rain,showers,snowfall,snow_depth,weathercode,visibility,wind_speed_10m,wind_gusts_10m,soil_temperature_0cm,dew_point_2m"
    
    # Aggiungi CAPE se disponibile (AROME Seamless o ICON)
    if model_slug in ["meteofrance_seamless", "italia_meteo_arpae_icon_2i", "icon_eu"]:
@@ -627,6 +662,242 @@ def analyze_past_24h_conditions(weather_data: Dict) -> Dict:
    }


+def summarize_point_weather(weather_data: Dict) -> Dict:
+    """Manto nevoso attuale e precipitazioni previste 12h/24h per un punto."""
+    result = {
+        "snow_depth_cm": None,
+        "rain_12h_mm": 0.0,
+        "rain_24h_mm": 0.0,
+        "snow_12h_cm": 0.0,
+        "snow_24h_cm": 0.0,
+    }
+    if not weather_data or "hourly" not in weather_data:
+        return result
+
+    hourly = weather_data["hourly"]
+    times = hourly.get("time", [])
+    if not times:
+        return result
+
+    now = datetime.datetime.now(datetime.timezone.utc)
+    rain = hourly.get("rain", [])
+    snowfall = hourly.get("snowfall", [])
+    snow_depth = hourly.get("snow_depth", [])
+
+    timestamps = []
+    for ts_str in times:
+        try:
+            if "Z" in ts_str:
+                ts = datetime.datetime.fromisoformat(ts_str.replace("Z", "+00:00"))
+            else:
+                ts = datetime.datetime.fromisoformat(ts_str)
+                if ts.tzinfo is None:
+                    ts = ts.replace(tzinfo=datetime.timezone.utc)
+            timestamps.append(ts)
+        except Exception:
+            continue
+
+    latest_depth_cm = None
+    for i, ts in enumerate(timestamps):
+        if i < len(snow_depth) and snow_depth[i] is not None and ts <= now:
+            latest_depth_cm = float(snow_depth[i]) * 100.0
+
+        if ts < now:
+            continue
+        hours_ahead = (ts - now).total_seconds() / 3600.0
+        if hours_ahead >= 24:
+            continue
+        r = rain[i] if i < len(rain) and rain[i] is not None else 0.0
+        snow = snowfall[i] if i < len(snowfall) and snowfall[i] is not None else 0.0
+        if hours_ahead < 12:
+            result["rain_12h_mm"] += float(r)
+            result["snow_12h_cm"] += float(snow)
+        result["rain_24h_mm"] += float(r)
+        result["snow_24h_cm"] += float(snow)
+
+    if latest_depth_cm is not None and latest_depth_cm >= 0.05:
+        result["snow_depth_cm"] = round(latest_depth_cm, 1)
+    result["rain_12h_mm"] = round(result["rain_12h_mm"], 1)
+    result["rain_24h_mm"] = round(result["rain_24h_mm"], 1)
+    result["snow_12h_cm"] = round(result["snow_12h_cm"], 1)
+    result["snow_24h_cm"] = round(result["snow_24h_cm"], 1)
+    return result
+
+
+RISK_BADGE_MAP = {
+    "neve": ("❄️", "Neve"),
+    "gelicidio": ("🔴🔴", "Gelicidio"),
+    "ghiaccio": ("🔴", "Ghiaccio"),
+    "brina": ("🟡", "Brina"),
+    "pioggia": ("🌧️", "Pioggia"),
+    "temporale": ("⛈️", "Temporale"),
+    "vento": ("💨", "Vento"),
+    "nebbia": ("🌫️", "Nebbia"),
+    "grandine": ("🌨️", "Grandine"),
+    "nessuno": ("✅", "Nessun rischio"),
+}
+
+
+def _first_dict(series):
+    """Prende il primo valore non-nullo (dict) da una serie pandas."""
+    for val in series:
+        if val is not None and (isinstance(val, dict) or (isinstance(val, str) and val != "")):
+            return val
+    return {}
+
+
+def _aggregate_route_points(df: pd.DataFrame):
+    """Raggruppa punti percorso con rischi effettivi e meteo riassuntivo."""
+    max_risk_per_point = df.groupby("point_index").agg({
+        "max_risk_level": "max",
+        "point_name": "first",
+        "past_24h": _first_dict,
+        "weather_summary": _first_dict,
+    }).sort_values("point_index")
+
+    seen_names = {}
+    unique_indices = []
+    for idx, row in max_risk_per_point.iterrows():
+        point_name = row["point_name"]
+        name_key = point_name.split("(")[0].strip()
+        past_24h = row.get("past_24h", {}) if isinstance(row.get("past_24h"), dict) else {}
+        has_snow_ice = past_24h.get("snow_present") or past_24h.get("ice_persistence_likely")
+
+        if name_key not in seen_names:
+            seen_names[name_key] = idx
+            unique_indices.append(idx)
+        else:
+            existing_idx = seen_names[name_key]
+            existing_row = max_risk_per_point.loc[existing_idx]
+            existing_past_24h = existing_row.get("past_24h", {}) if isinstance(existing_row.get("past_24h"), dict) else {}
+            existing_has_snow_ice = existing_past_24h.get("snow_present") or existing_past_24h.get("ice_persistence_likely")
+            if row["max_risk_level"] > existing_row["max_risk_level"]:
+                unique_indices.remove(existing_idx)
+                seen_names[name_key] = idx
+                unique_indices.append(idx)
+            elif row["max_risk_level"] == existing_row["max_risk_level"] and has_snow_ice and not existing_has_snow_ice:
+                unique_indices.remove(existing_idx)
+                seen_names[name_key] = idx
+                unique_indices.append(idx)
+
+    max_risk_per_point = max_risk_per_point.loc[unique_indices]
+
+    effective_risk_levels_dict = {}
+    for idx, row in max_risk_per_point.iterrows():
+        level = int(row["max_risk_level"])
+        past_24h = row.get("past_24h", {}) if isinstance(row.get("past_24h"), dict) else {}
+        if level == 0 and past_24h:
+            if past_24h.get("snow_present"):
+                level = 4
+            elif past_24h.get("ice_persistence_likely"):
+                level = 2
+        effective_risk_levels_dict[idx] = level
+
+    max_risk_per_point = max_risk_per_point.copy()
+    max_risk_per_point["effective_risk_level"] = max_risk_per_point.index.map(effective_risk_levels_dict)
+
+    risks_per_point = {}
+    for _, row in df[df["max_risk_level"] > 0].iterrows():
+        point_idx = row["point_index"]
+        if point_idx not in risks_per_point:
+            risks_per_point[point_idx] = {}
+        risk_type = row["risk_type"]
+        risk_level = row["risk_level"]
+        risk_desc = row["risk_description"]
+        if risk_type not in risks_per_point[point_idx] or risks_per_point[point_idx][risk_type]["level"] < risk_level:
+            risks_per_point[point_idx][risk_type] = {
+                "type": risk_type,
+                "desc": risk_desc,
+                "level": risk_level,
+            }
+
+    for idx, row in max_risk_per_point.iterrows():
+        effective_risk = row.get("effective_risk_level", 0)
+        max_risk = int(row["max_risk_level"])
+        if effective_risk > 0 and max_risk == 0:
+            if idx not in risks_per_point:
+                risks_per_point[idx] = {}
+            past_24h = row.get("past_24h", {}) if isinstance(row.get("past_24h"), dict) else {}
+            if effective_risk >= 4:
+                risk_type, risk_desc = "neve", "Neve presente"
+            elif effective_risk == 2:
+                risk_type = "ghiaccio"
+                min_temp = past_24h.get("min_temp_2m")
+                hours_below_2c = past_24h.get("hours_below_2c", 0)
+                if min_temp is not None:
+                    risk_desc = f"Ghiaccio persistente (Tmin: {min_temp:.1f}°C, {hours_below_2c}h <2°C)"
+                else:
+                    risk_desc = "Ghiaccio persistente"
+            elif effective_risk == 1:
+                risk_type = "brina"
+                min_temp = past_24h.get("min_temp_2m")
+                risk_desc = f"Brina possibile (Tmin: {min_temp:.1f}°C)" if min_temp is not None else "Brina possibile"
+            else:
+                continue
+            risks_per_point[idx][risk_type] = {"type": risk_type, "desc": risk_desc, "level": effective_risk}
+
+    return max_risk_per_point, risks_per_point
+
+
+def _primary_risk_for_point(risks: Dict, effective_risk: int) -> Tuple[str, str, List[str]]:
+    """Ritorna (badge, label, descrizioni) per il punto."""
+    type_order = ["neve", "gelicidio", "ghiaccio", "brina", "temporale", "pioggia", "vento", "nebbia", "grandine"]
+    risk_list = sorted(risks.values(), key=lambda x: x.get("level", 0), reverse=True) if risks else []
+    descriptions = [r.get("desc", "") for r in risk_list if r.get("desc")]
+
+    primary_type = risk_list[0]["type"] if risk_list else "nessuno"
+    for t in type_order:
+        if t in risks:
+            primary_type = t
+            break
+
+    if effective_risk >= 4 and "neve" not in risks:
+        primary_type = "neve"
+    elif effective_risk == 3 and primary_type == "nessuno":
+        primary_type = "gelicidio"
+    elif effective_risk == 2 and primary_type in ("nessuno", "brina"):
+        primary_type = "ghiaccio"
+    elif effective_risk == 1 and primary_type == "nessuno":
+        primary_type = "brina"
+
+    badge, label = RISK_BADGE_MAP.get(primary_type, ("⚠️", primary_type.capitalize()))
+    return badge, label, descriptions
+
+
+def build_route_points_table(df: pd.DataFrame) -> List[Dict]:
+    """Tabella punti notevoli per WebApp."""
+    if df.empty:
+        return []
+
+    max_risk_per_point, risks_per_point = _aggregate_route_points(df)
+    points = []
+
+    for idx, row in max_risk_per_point.iterrows():
+        effective_risk = int(row.get("effective_risk_level", 0))
+        risks = risks_per_point.get(idx, {})
+        badge, label, descriptions = _primary_risk_for_point(risks, effective_risk)
+        weather = row.get("weather_summary", {}) if isinstance(row.get("weather_summary"), dict) else {}
+
+        points.append({
+            "name": row["point_name"],
+            "risk": {
+                "badge": badge,
+                "label": label,
+                "descriptions": descriptions[:4],
+                "level": effective_risk,
+            },
+            "snow_depth_cm": weather.get("snow_depth_cm"),
+            "precip": {
+                "rain_12h_mm": weather.get("rain_12h_mm", 0.0),
+                "rain_24h_mm": weather.get("rain_24h_mm", 0.0),
+                "snow_12h_cm": weather.get("snow_12h_cm", 0.0),
+                "snow_24h_cm": weather.get("snow_24h_cm", 0.0),
+            },
+        })
+
+    return points
+
+
 # =============================================================================
 # ANALISI RISCHI METEO
 # =============================================================================
@@ -1098,12 +1369,14 @@ def analyze_route_weather_risks(city1: str, city2: str, model_slug: Optional[str
                'risk_description': 'Dati meteo non disponibili',
                'risk_value': 0.0,
                'max_risk_level': 0,
-                'point_name': point_name
+                'point_name': point_name,
+                'weather_summary': {},
            })
            continue
        
        # Analizza condizioni 24h precedenti
        past_24h = analyze_past_24h_conditions(weather_data)
+        weather_summary = summarize_point_weather(weather_data)
        
        # Analizza rischi (passa anche past_24h per analisi temporale evolutiva)
        risk_analysis = analyze_weather_risks(weather_data, model_slug, hours_ahead=24, past_24h_info=past_24h)
@@ -1121,7 +1394,8 @@ def analyze_route_weather_risks(city1: str, city2: str, model_slug: Optional[str
                'risk_value': 0.0,
                'max_risk_level': 0,
                'point_name': point_name,
-                'past_24h': past_24h  # Aggiungi analisi 24h precedenti anche se nessun rischio
+                'past_24h': past_24h,
+                'weather_summary': weather_summary,
            })
            continue
        
@@ -1161,7 +1435,8 @@ def analyze_route_weather_risks(city1: str, city2: str, model_slug: Optional[str
                        'risk_value': risk.get("value", 0.0),
                        'max_risk_level': hour_data["max_risk_level"],
                        'point_name': point_name,
-                        'past_24h': past_24h
+                        'past_24h': past_24h,
+                        'weather_summary': weather_summary,
                    })
            else:
                all_results.append({
@@ -1175,7 +1450,8 @@ def analyze_route_weather_risks(city1: str, city2: str, model_slug: Optional[str
                    'risk_value': 0.0,
                    'max_risk_level': 0,
                    'point_name': point_name,
-                    'past_24h': past_24h
+                    'past_24h': past_24h,
+                    'weather_summary': weather_summary,
                })
    
    if not all_results:
@@ -1193,141 +1469,13 @@ def format_route_weather_report(df: pd.DataFrame, city1: str, city2: str) -> str
    """Formatta report compatto dei rischi meteo lungo percorso."""
    if df.empty:
        return "❌ Nessun dato disponibile per il percorso."
-    
-    # Raggruppa per punto e trova rischio massimo + analisi 24h
-    # Usa funzione custom per past_24h per assicurarsi che venga preservato correttamente
-    def first_dict(series):
-        """Prende il primo valore non-nullo, utile per dict."""
-        for val in series:
-            if val is not None and (isinstance(val, dict) or (isinstance(val, str) and val != '')):
-                return val
-        return {}
-    
-    max_risk_per_point = df.groupby('point_index').agg({
-        'max_risk_level': 'max',
-        'point_name': 'first',
-        'past_24h': first_dict  # Usa funzione custom per preservare dict
-    }).sort_values('point_index')
-    
-    # Rimuovi duplicati per nome (punti con stesso nome ma indici diversi)
-    # Considera anche neve/ghiaccio persistente nella scelta
-    seen_names = {}
-    unique_indices = []
-    for idx, row in max_risk_per_point.iterrows():
-        point_name = row['point_name']
-        # Normalizza nome (rimuovi suffissi tra parentesi)
-        name_key = point_name.split('(')[0].strip()
-        past_24h = row.get('past_24h', {}) if isinstance(row.get('past_24h'), dict) else {}
-        has_snow_ice = past_24h.get('snow_present') or past_24h.get('ice_persistence_likely')
-        
-        if name_key not in seen_names:
-            seen_names[name_key] = idx
-            unique_indices.append(idx)
-        else:
-            # Se duplicato, mantieni quello con rischio maggiore O con neve/ghiaccio
-            existing_idx = seen_names[name_key]
-            existing_row = max_risk_per_point.loc[existing_idx]
-            existing_past_24h = existing_row.get('past_24h', {}) if isinstance(existing_row.get('past_24h'), dict) else {}
-            existing_has_snow_ice = existing_past_24h.get('snow_present') or existing_past_24h.get('ice_persistence_likely')
-            
-            # Priorità: rischio maggiore, oppure neve/ghiaccio se rischio uguale
-            if row['max_risk_level'] > existing_row['max_risk_level']:
-                unique_indices.remove(existing_idx)
-                seen_names[name_key] = idx
-                unique_indices.append(idx)
-            elif row['max_risk_level'] == existing_row['max_risk_level'] and has_snow_ice and not existing_has_snow_ice:
-                # Stesso rischio, ma questo ha neve/ghiaccio
-                unique_indices.remove(existing_idx)
-                seen_names[name_key] = idx
-                unique_indices.append(idx)
-    
-    # Filtra solo punti unici
-    max_risk_per_point = max_risk_per_point.loc[unique_indices]
-    
-    # Calcola effective_risk_level per ogni punto UNICO (considerando persistenza)
-    effective_risk_levels_dict = {}
-    for idx, row in max_risk_per_point.iterrows():
-        level = int(row['max_risk_level'])
-        past_24h = row.get('past_24h', {}) if isinstance(row.get('past_24h'), dict) else {}
-        
-        # Se livello è 0, verifica persistenza per assegnare livello appropriato
-        if level == 0 and past_24h:
-            if past_24h.get('snow_present'):
-                level = 4  # Neve presente
-            elif past_24h.get('ice_persistence_likely'):
-                # Se ice_persistence_likely è True, significa che c'è ghiaccio persistente
-                # (calcolato in analyze_past_24h_conditions basandosi su suolo gelato, 
-                #  precipitazioni con temperature basse, o neve presente)
-                # Quindi deve essere classificato come ghiaccio (livello 2), non brina
-                level = 2  # Ghiaccio persistente
-        
-        effective_risk_levels_dict[idx] = level
-    
-    # Aggiungi effective_risk_level al DataFrame
-    max_risk_per_point['effective_risk_level'] = max_risk_per_point.index.map(effective_risk_levels_dict)
-    
-    # Trova rischi unici per ogni punto (raggruppa per tipo, mantieni solo il più grave)
-    risks_per_point = {}
-    # Prima aggiungi rischi futuri (max_risk_level > 0)
-    for idx, row in df[df['max_risk_level'] > 0].iterrows():
-        point_idx = row['point_index']
-        if point_idx not in risks_per_point:
-            risks_per_point[point_idx] = {}
-        
-        risk_type = row['risk_type']
-        risk_level = row['risk_level']
-        risk_desc = row['risk_description']
-        
-        # Raggruppa per tipo di rischio, mantieni solo quello con livello più alto
-        if risk_type not in risks_per_point[point_idx] or risks_per_point[point_idx][risk_type]['level'] < risk_level:
-            risks_per_point[point_idx][risk_type] = {
-                'type': risk_type,
-                'desc': risk_desc,
-                'level': risk_level
-            }
-    
-    # Poi aggiungi punti con persistenza ma senza rischi futuri (max_risk_level == 0 ma effective_risk > 0)
-    for idx, row in max_risk_per_point.iterrows():
-        effective_risk = row.get('effective_risk_level', 0)
-        max_risk = int(row['max_risk_level'])
-        
-        # Se ha persistenza ma non rischi futuri, aggiungi rischio basato su persistenza
-        if effective_risk > 0 and max_risk == 0:
-            if idx not in risks_per_point:
-                risks_per_point[idx] = {}
-            
-            past_24h = row.get('past_24h', {}) if isinstance(row.get('past_24h'), dict) else {}
-            
-            # Determina tipo di rischio basandosi su effective_risk_level
-            if effective_risk >= 4:
-                risk_type = 'neve'
-                risk_desc = "Neve presente"
-            elif effective_risk == 2:
-                risk_type = 'ghiaccio'
-                # Determina descrizione basandosi su condizioni
-                min_temp = past_24h.get('min_temp_2m')
-                hours_below_2c = past_24h.get('hours_below_2c', 0)
-                if min_temp is not None:
-                    risk_desc = f"Ghiaccio persistente (Tmin: {min_temp:.1f}°C, {hours_below_2c}h <2°C)"
-                else:
-                    risk_desc = "Ghiaccio persistente"
-            elif effective_risk == 1:
-                risk_type = 'brina'
-                min_temp = past_24h.get('min_temp_2m')
-                if min_temp is not None:
-                    risk_desc = f"Brina possibile (Tmin: {min_temp:.1f}°C)"
-                else:
-                    risk_desc = "Brina possibile"
-            else:
-                continue  # Skip se non abbiamo un tipo valido
-            
-            # Aggiungi al dict rischi (usa idx come chiave, non point_idx)
-            risks_per_point[idx][risk_type] = {
-                'type': risk_type,
-                'desc': risk_desc,
-                'level': effective_risk
-            }
-    
+
+    max_risk_per_point, risks_per_point = _aggregate_route_points(df)
+    effective_risk_levels_dict = {
+        idx: int(row["effective_risk_level"])
+        for idx, row in max_risk_per_point.iterrows()
+    }
+
    # Verifica se la chiave Google Maps è disponibile
    api_key_available = get_google_maps_api_key() is not None
    
@@ -1820,3 +1968,46 @@ def generate_route_weather_map(df: pd.DataFrame, city1: str, city2: str, output_
        LOGGER.error(f"Errore salvataggio mappa: {e}")
        plt.close(fig)
        return False
+
+
+def build_road_json(city1: str, city2: str, maps_dir: str) -> Dict:
+    """Analisi percorso stradale per WebApp."""
+    if not PANDAS_AVAILABLE:
+        return {"error": "pandas/numpy non disponibili sul server"}
+
+    df = analyze_route_weather_risks(city1, city2, model_slug=None)
+    if df is None or df.empty:
+        return {"error": f"Impossibile analizzare il percorso {city1} → {city2}"}
+
+    report = format_route_weather_report(df, city1, city2)
+    os.makedirs(maps_dir, exist_ok=True)
+    import hashlib
+    key = hashlib.sha256(f"{city1}|{city2}".encode()).hexdigest()[:16]
+    map_name = f"road_{key}.png"
+    map_path = os.path.join(maps_dir, map_name)
+    map_ok = generate_route_weather_map(df, city1, city2, map_path)
+
+    plain = report.replace("*", "").replace("_", "").replace("`", "")
+    return {
+        "from": city1,
+        "to": city2,
+        "report": plain,
+        "map_id": map_name if map_ok else None,
+        "points": build_route_points_table(df),
+    }
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Road weather analysis")
+    parser.add_argument("city1")
+    parser.add_argument("city2")
+    parser.add_argument("--json", action="store_true")
+    parser.add_argument("--maps-dir", default="/tmp")
+    args = parser.parse_args()
+    if args.json:
+        print(json.dumps(build_road_json(args.city1, args.city2, args.maps_dir), ensure_ascii=False))
+    else:
+        if not PANDAS_AVAILABLE:
+            raise SystemExit("pandas richiesto")
+        df = analyze_route_weather_risks(args.city1, args.city2)
+        print(format_route_weather_report(df, args.city1, args.city2))
@@ -17,7 +17,7 @@ from dateutil import parser
 from open_meteo_client import open_meteo_get

 # =============================================================================
-# SEVERE WEATHER ALERT (next 48h) - Casa (LAT/LON)
+# SEVERE WEATHER ALERT (next 24h) - Casa (LAT/LON)
 #  - Wind gusts persistence: >= soglia per almeno 2 ore consecutive
 #  - Rain persistence: soglia (mm/3h) superata per almeno 2 ore (2 finestre 3h consecutive)
 #  - Convective storms (temporali severi): analisi combinata ICON Italia + AROME Seamless
@@ -62,7 +62,29 @@ RAIN_3H_LIMIT = 25.0
 PERSIST_HOURS = 2  # richiesta utente: >=2 ore

 # ----------------- HORIZON -----------------
-HOURS_AHEAD = 48  # Esteso a 48h per analisi temporali severi
+HOURS_AHEAD = 24  # Finestra di analisi e notifica: prossime 24 ore
+
+# ----------------- ANTI-GLITCH (previsioni spurie fuori scala) -----------------
+# Limiti fisici oltre i quali un valore orario viene scartato come non plausibile.
+GLITCH_MAX_PRECIP_H = 100.0   # mm/h
+GLITCH_MAX_GUSTS_KMH = 160.0  # km/h
+GLITCH_MAX_CAPE = 5500.0      # J/kg
+# Picco isolato: valore >> ore adiacenti (tipico artefatto numerico del modello).
+GLITCH_SPIKE_RATIO = 4.0
+GLITCH_SPIKE_MIN = {"precip": 8.0, "gusts": 35.0, "cape": 600.0}
+# Discordanza estrema AROME vs ICON sulla stessa ora → probabile glitch.
+GLITCH_CROSS_MODEL_RATIO = 4.0
+GLITCH_CROSS_MODEL_MIN = {"precip": 10.0, "gusts": 40.0, "cape": 700.0}
+# Temporali: almeno 2 ore significative consecutive (salvo bomba d'acqua estrema).
+STORM_MIN_CLUSTER_HOURS = 2
+STORM_ISOLATED_EXTREME_PRECIP_H = 40.0   # mm/h
+STORM_ISOLATED_EXTREME_PRECIP_3H = 60.0  # mm/3h
+
+# ----------------- RATE LIMITING NOTIFICHE (tutti i tipi) -----------------
+MAX_ALERT_MESSAGES_PER_DAY = 1       # massimo 1 messaggio Telegram/giorno
+MIN_GAP_HOURS_BETWEEN_ALERTS = 8.0   # distanza minima tra due messaggi
+# Escalation intra-giorno: ri-notifica solo se peggioramento netto
+RAIN_ESCALATION_MM_3H = 15.0       # +15 mm sul max 3h precedente

 # ----------------- CONVECTIVE STORM THRESHOLDS -----------------
 CAPE_LIGHTNING_THRESHOLD = 800.0  # J/kg - Soglia per rischio fulminazioni
@@ -90,15 +112,6 @@ SIGNIFICANT_PRECIP_H = 30.0          # mm/h - bomba d'acqua (nubifragio forte)
 SIGNIFICANT_PRECIP_3H = 50.0         # mm/3h - nubifragio forte su 3 ore
 SIGNIFICANT_STORM_SCORE = 55.0       # Storm Severity Score minimo per significativo

-# ----------------- RATE LIMITING NOTIFICHE TEMPORALI -----------------
-# Notifiche temporali "molto contingentate":
-#   - eventi imminenti (entro IMMINENT_HOURS): massimo 2 al giorno (cooldown 6h)
-#   - eventi solo nella finestra estesa (24-48h): massimo 1 al giorno
-IMMINENT_HOURS = 24
-MAX_STORM_ALERTS_IMMINENT_PER_DAY = 2
-MAX_STORM_ALERTS_EXTENDED_PER_DAY = 1
-MIN_GAP_HOURS_IMMINENT = 6.0
-
 # ----------------- FILES -----------------
 STATE_FILE = "/home/daniely/docker/telegram-bot/weather_state.json"
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
@@ -250,6 +263,15 @@ def telegram_send_html(message_html: str, chat_ids: Optional[List[str]] = None)
            except Exception as e:
                LOGGER.exception("Telegram exception chat_id=%s err=%s", chat_id, e)

+    if sent_ok:
+        try:
+            import sys
+            sys.path.insert(0, "/home/daniely/docker/shared")
+            from loogle_core.alert_dispatcher import mirror_to_web
+            mirror_to_web(message_html, "severe_weather", "warning", is_html=True)
+        except Exception as e:
+            LOGGER.debug("Web dispatch failed: %s", e)
+
    return sent_ok


@@ -266,8 +288,13 @@ def load_state() -> Dict:
        "last_storm_score": 0.0,
        "last_alert_type": None,  # Tipo di allerta: "VENTO", "PIOGGIA", "TEMPORALI", o lista combinata
        "last_alert_time": None,  # Timestamp ISO dell'ultima notifica
-        # Anti-spam temporali: conteggi giornalieri per finestra + dedup
-        "storm_daily": {},                # {"YYYY-MM-DD": {"imminent": int, "extended": int}}
+        # Anti-spam globale (tutti i tipi di allerta)
+        "alert_daily": {},           # {"YYYY-MM-DD": count messaggi inviati}
+        "last_alert_sent": None,     # ISO timestamp ultimo messaggio
+        "last_alert_signature": None,
+        "last_alert_signature_date": None,
+        # Legacy temporali (mantenuto per compatibilità stato)
+        "storm_daily": {},
        "storm_last_sent_imminent": None,
        "storm_last_sent_extended": None,
        "storm_last_signature": None,
@@ -292,6 +319,145 @@ def save_state(state: Dict) -> None:
        LOGGER.exception("State write error: %s", e)


+# =============================================================================
+# ANTI-GLITCH (filtra previsioni spurie / picchi isolati)
+# =============================================================================
+def _to_float(v, default: float = 0.0) -> float:
+    try:
+        if v is None:
+            return default
+        return float(v)
+    except (ValueError, TypeError):
+        return default
+
+
+def _physical_cap(field: str) -> float:
+    return {"precip": GLITCH_MAX_PRECIP_H, "gusts": GLITCH_MAX_GUSTS_KMH, "cape": GLITCH_MAX_CAPE}.get(
+        field, float("inf")
+    )
+
+
+def exceeds_physical_cap(field: str, value: float) -> bool:
+    return value > _physical_cap(field)
+
+
+def is_isolated_spike(series: List[float], idx: int, field: str) -> bool:
+    """Picco isolato: valore molto superiore alle ore adiacenti."""
+    if idx < 1 or idx >= len(series) - 1:
+        return False
+    cur = series[idx]
+    min_abs = GLITCH_SPIKE_MIN.get(field, 5.0)
+    if cur < min_abs:
+        return False
+    prev_v = series[idx - 1]
+    next_v = series[idx + 1]
+    nb_avg = (prev_v + next_v) / 2.0
+    if nb_avg < 0.05 and cur >= min_abs:
+        return True
+    if nb_avg > 0 and cur >= GLITCH_SPIKE_RATIO * nb_avg:
+        return True
+    return False
+
+
+def cross_model_outlier(arome_val: float, icon_val: float, field: str) -> bool:
+    """Discordanza estrema tra modelli sulla stessa ora."""
+    mn = GLITCH_CROSS_MODEL_MIN.get(field, 0.0)
+    hi = max(arome_val, icon_val)
+    lo = min(arome_val, icon_val)
+    if hi < mn:
+        return False
+    if lo < 0.1 and hi >= mn:
+        return True
+    if lo > 0 and hi / lo >= GLITCH_CROSS_MODEL_RATIO:
+        return True
+    return False
+
+
+def sanitize_hourly_values(
+    arome_vals: List,
+    icon_vals: Optional[List],
+    field: str,
+    start_idx: int,
+    end_idx: int,
+) -> Tuple[List[float], int]:
+    """Pulizia serie oraria AROME; valori glitch → 0. Ritorna (serie, n_glitch)."""
+    n = len(arome_vals)
+    floats = [_to_float(arome_vals[i] if i < n else 0) for i in range(n)]
+    glitches = 0
+    for i in range(start_idx, min(end_idx, n)):
+        v = floats[i]
+        if v <= 0:
+            continue
+        icon_v = _to_float(icon_vals[i] if icon_vals and i < len(icon_vals) else None, default=-1.0)
+        bad = exceeds_physical_cap(field, v)
+        if not bad:
+            bad = is_isolated_spike(floats, i, field)
+        if not bad and icon_vals is not None and icon_v >= 0:
+            bad = cross_model_outlier(v, icon_v, field)
+        if bad:
+            LOGGER.info(
+                "Anti-glitch: %s scartato idx=%d (AROME=%.1f%s)",
+                field, i, v,
+                f" ICON={icon_v:.1f}" if icon_v >= 0 else "",
+            )
+            floats[i] = 0.0
+            glitches += 1
+    return floats, glitches
+
+
+def hour_passes_convective_glitch(
+    idx: int,
+    cape: float,
+    precip: float,
+    gusts: float,
+    icon_precip: float,
+    icon_cape: float,
+    arome_precip_series: List[float],
+) -> bool:
+    """True se l'ora convettiva supera i controlli anti-glitch."""
+    if exceeds_physical_cap("cape", cape) or exceeds_physical_cap("precip", precip) or exceeds_physical_cap("gusts", gusts):
+        return False
+    if precip > 0 and is_isolated_spike(arome_precip_series, idx, "precip"):
+        return False
+    if precip > 0 and icon_precip >= 0 and cross_model_outlier(precip, icon_precip, "precip"):
+        return False
+    if cape >= GLITCH_SPIKE_MIN["cape"] and icon_cape >= 0 and cross_model_outlier(cape, icon_cape, "cape"):
+        return False
+    return True
+
+
+def filter_storm_cluster(sig_events: List[Dict]) -> List[Dict]:
+    """Richiede cluster temporale minimo (ore consecutive); isolati soppressi salvo estremi."""
+    if not sig_events:
+        return []
+    events = sorted(sig_events, key=lambda e: e.get("timestamp", ""))
+    max_consec = 1
+    run = 1
+    for i in range(1, len(events)):
+        try:
+            prev = parse_time_to_local(events[i - 1]["timestamp"])
+            cur = parse_time_to_local(events[i]["timestamp"])
+            gap_h = (cur - prev).total_seconds() / 3600.0
+            if gap_h <= 1.5:
+                run += 1
+            else:
+                max_consec = max(max_consec, run)
+                run = 1
+        except Exception:
+            run = 1
+    max_consec = max(max_consec, run)
+    if max_consec >= STORM_MIN_CLUSTER_HOURS:
+        return events
+    if len(events) == 1 or max_consec == 1:
+        ev = max(events, key=lambda e: float(e.get("precip", 0) or 0))
+        if (ev.get("precip", 0) >= STORM_ISOLATED_EXTREME_PRECIP_H
+                or ev.get("precip_3h", 0) >= STORM_ISOLATED_EXTREME_PRECIP_3H):
+            return events
+        LOGGER.info("Anti-glitch: evento temporale isolato (%dh) soppresso", max_consec)
+        return []
+    return events
+
+
 # =============================================================================
 # OPEN-METEO
 # =============================================================================
@@ -722,6 +888,8 @@ def analyze_convective_risk(icon_data: Dict, arome_data: Dict, times_base: List[
    
    # Se LPI non disponibile, usa CAPE da ICON come proxy (CAPE alto può indicare attività convettiva)
    icon_cape = icon_hourly.get("cape", []) or []
+    icon_precip = icon_hourly.get("precipitation", []) or []
+    icon_gusts = icon_hourly.get("wind_gusts_10m", []) or []
    # Se abbiamo CAPE da ICON ma non LPI, usiamo CAPE > 800 come indicatore di possibile attività elettrica
    if not icon_lpi and icon_cape:
        # Convertiamo CAPE in LPI proxy: CAPE > 800 = LPI > 0
@@ -730,6 +898,7 @@ def analyze_convective_risk(icon_data: Dict, arome_data: Dict, times_base: List[
    arome_cape = arome_hourly.get("cape", []) or []
    arome_gusts = arome_hourly.get("wind_gusts_10m", []) or []
    arome_precip = arome_hourly.get("precipitation", []) or []
+    arome_precip_floats = [_to_float(v) for v in arome_precip]
    
    # Allineamento: sincronizza timestamp (ICON e AROME possono avere risoluzioni diverse)
    # Per semplicità, assumiamo che abbiano la stessa risoluzione oraria e li allineiamo per indice
@@ -775,6 +944,14 @@ def analyze_convective_risk(icon_data: Dict, arome_data: Dict, times_base: List[
            except (ValueError, TypeError, IndexError):
                pass
        
+        icon_precip_i = _to_float(icon_precip[i] if i < len(icon_precip) else None, default=-1.0)
+        icon_cape_i = _to_float(icon_cape[i] if i < len(icon_cape) else None, default=-1.0)
+        if not hour_passes_convective_glitch(
+            i, cape_val, precip_val, gusts_val,
+            icon_precip_i, icon_cape_i, arome_precip_floats,
+        ):
+            continue
+        
        # Calcola Storm Severity Score (0-100)
        score = 0.0
        threats = []
@@ -834,8 +1011,8 @@ def format_convective_alert(storm_events: List[Dict], times: List[str], start_id
    if not storm_events:
        return ""
    
-    # Analisi estesa su 48 ore
-    storm_analysis = analyze_convective_storm_event(storm_events, times, start_idx, max_hours=48)
+    # Analisi estesa su finestra configurata
+    storm_analysis = analyze_convective_storm_event(storm_events, times, start_idx, max_hours=HOURS_AHEAD)
    
    # Calcola statistiche aggregate
    max_score = max(e["score"] for e in storm_events)
@@ -1008,8 +1185,7 @@ def storm_event_significance(event: Dict) -> List[str]:


 def filter_significant_storms(storm_events: List[Dict], now: datetime.datetime) -> List[Dict]:
-    """Mantiene solo gli eventi significativi, arricchendoli con 'lead_hours' e
-    'significance'."""
+    """Mantiene solo gli eventi significativi, con cluster minimo e anti-glitch."""
    out: List[Dict] = []
    for ev in storm_events or []:
        reasons = storm_event_significance(ev)
@@ -1023,7 +1199,7 @@ def filter_significant_storms(storm_events: List[Dict], now: datetime.datetime)
        e2["lead_hours"] = lead
        e2["significance"] = reasons
        out.append(e2)
-    return out
+    return filter_storm_cluster(out)


 def _today_key(now: datetime.datetime) -> str:
@@ -1042,40 +1218,65 @@ def _parse_iso_local(s: Optional[str]) -> Optional[datetime.datetime]:
        return None


-def prune_storm_daily(state: Dict, now: datetime.datetime) -> None:
+def prune_alert_daily(state: Dict, now: datetime.datetime) -> None:
    keep = {_today_key(now), _today_key(now - datetime.timedelta(days=1))}
-    daily = state.get("storm_daily", {}) or {}
-    state["storm_daily"] = {k: v for k, v in daily.items() if k in keep}
+    daily = state.get("alert_daily", {}) or {}
+    state["alert_daily"] = {k: v for k, v in daily.items() if k in keep}


-def can_notify_storm(category: str, now: datetime.datetime, state: Dict) -> Tuple[bool, str]:
+def build_alert_signature(alerts: List[str], wind_level: int, rain_max_3h: float, sig_storms: List[Dict]) -> str:
+    parts = []
+    if sig_storms:
+        reasons = set()
+        for ev in sig_storms:
+            reasons.update(ev.get("significance", []))
+        parts.append("storm:" + "+".join(sorted(reasons)))
+    if wind_level > 0:
+        parts.append(f"wind:{wind_level}")
+    if rain_max_3h >= RAIN_3H_LIMIT:
+        parts.append(f"rain:{rain_max_3h:.0f}")
+    return "|".join(parts) if parts else "none"
+
+
+def is_alert_escalation(
+    state: Dict,
+    signature: str,
+    wind_level: int,
+    rain_max_3h: float,
+) -> bool:
+    """Permette un secondo messaggio nello stesso giorno solo se peggioramento netto."""
+    prev_wind = int(state.get("wind_level", 0) or 0)
+    prev_rain = float(state.get("last_rain_3h", 0.0) or 0.0)
+    prev_sig = state.get("last_alert_signature") or ""
+    if wind_level > prev_wind:
+        return True
+    if rain_max_3h >= prev_rain + RAIN_ESCALATION_MM_3H:
+        return True
+    if signature != prev_sig and signature != "none" and prev_sig:
+        return True
+    return False
+
+
+def can_notify_message(now: datetime.datetime, state: Dict, allow_escalation: bool = False) -> Tuple[bool, str]:
    key = _today_key(now)
-    daily = state.setdefault("storm_daily", {})
-    day = daily.setdefault(key, {"imminent": 0, "extended": 0})
-    if category == "imminent":
-        if int(day.get("imminent", 0)) >= MAX_STORM_ALERTS_IMMINENT_PER_DAY:
-            return False, "cap giornaliero imminenti raggiunto"
-        last = _parse_iso_local(state.get("storm_last_sent_imminent"))
-        if last and (now - last).total_seconds() < MIN_GAP_HOURS_IMMINENT * 3600:
-            return False, "cooldown imminenti attivo"
-        return True, ""
-    if int(day.get("extended", 0)) >= MAX_STORM_ALERTS_EXTENDED_PER_DAY:
-        return False, "cap giornaliero estesi raggiunto"
+    count = int((state.get("alert_daily", {}) or {}).get(key, 0))
+    if count >= MAX_ALERT_MESSAGES_PER_DAY and not allow_escalation:
+        return False, "cap giornaliero messaggi raggiunto"
+    if count >= MAX_ALERT_MESSAGES_PER_DAY + 1:
+        return False, "cap escalation giornaliero raggiunto"
+    last = _parse_iso_local(state.get("last_alert_sent"))
+    if last and (now - last).total_seconds() < MIN_GAP_HOURS_BETWEEN_ALERTS * 3600:
+        return False, "cooldown alert attivo"
    return True, ""


-def record_notify_storm(category: str, now: datetime.datetime, state: Dict) -> None:
+def record_notify_message(now: datetime.datetime, state: Dict, signature: str) -> None:
    key = _today_key(now)
-    day = state.setdefault("storm_daily", {}).setdefault(key, {"imminent": 0, "extended": 0})
-    day[category] = int(day.get(category, 0)) + 1
-    state["storm_last_sent_" + category] = now.isoformat()
-
-
-def build_storm_signature(category: str, sig_events: List[Dict]) -> str:
-    reasons = set()
-    for ev in sig_events:
-        reasons.update(ev.get("significance", []))
-    return f"{category}|" + "+".join(sorted(reasons))
+    daily = state.setdefault("alert_daily", {})
+    daily[key] = int(daily.get(key, 0)) + 1
+    state["last_alert_sent"] = now.isoformat()
+    state["last_alert_signature"] = signature
+    state["last_alert_signature_date"] = key


 # =============================================================================
@@ -1276,9 +1477,9 @@ def rain_message(max_3h: float, start_hhmm: str, persist_h: int, rain_analysis:
        
        if end_time:
            end_str = end_time.strftime("%d/%m %H:%M")
-            msg_parts.append(f"⏱️ <b>Durata totale evento (48h):</b> ~{duration_h} ore (fino alle {end_str})")
+            msg_parts.append(f"⏱️ <b>Durata totale evento ({HOURS_AHEAD}h):</b> ~{duration_h} ore (fino alle {end_str})")
        else:
-            msg_parts.append(f"⏱️ <b>Durata totale evento (48h):</b> ~{duration_h} ore (in corso)")
+            msg_parts.append(f"⏱️ <b>Durata totale evento ({HOURS_AHEAD}h):</b> ~{duration_h} ore (in corso)")
        
        msg_parts.append(f"💧 <b>Accumulo totale previsto:</b> ~{total_mm:.1f} mm")
        msg_parts.append(f"🌧️ <b>Intensità massima oraria:</b> {max_intensity:.1f} mm/h")
@@ -1323,8 +1524,6 @@ def analyze(chat_ids: Optional[List[str]] = None, debug_mode: bool = False, lat:
        return

    times = times[:n]
-    gusts = gusts_arome[:n]
-    rain = rain_arome[:n]
    wcode = wcode_arome[:n]

    now = now_local()
@@ -1346,6 +1545,12 @@ def analyze(chat_ids: Optional[List[str]] = None, debug_mode: bool = False, lat:
        LOGGER.error("Invalid horizon window (start=%s end=%s).", start_idx, end_idx)
        return

+    # Anti-glitch su serie vento/pioggia prima dell'analisi di persistenza
+    rain, rain_glitch = sanitize_hourly_values(rain_arome[:n], rain_icon, "precip", start_idx, end_idx)
+    gusts, gust_glitch = sanitize_hourly_values(gusts_arome[:n], gusts_icon, "gusts", start_idx, end_idx)
+    if rain_glitch or gust_glitch:
+        LOGGER.info("Anti-glitch: %d ore pioggia, %d ore vento corrette", rain_glitch, gust_glitch)
+
    if DEBUG:
        LOGGER.debug("model=%s start_idx=%s end_idx=%s (hours=%s)",
                     model_used, start_idx, end_idx, end_idx - start_idx)
@@ -1413,109 +1618,62 @@ def analyze(chat_ids: Optional[List[str]] = None, debug_mode: bool = False, lat:
        if comp_rain:
            comparisons["rain"] = comp_rain

-    # --- Decide notifications ---
+    # --- Decide notifications (contenuto) ---
    alerts: List[str] = []
-    should_notify = False
-
-    # 1) Convective storms (temporali severi) - priorità alta
-    # Considera SOLO eventi significativi (fulminazioni forti / bombe d'acqua /
-    # downburst) e applica anti-spam a finestre + dedup giornaliero.
    sig_storms = filter_significant_storms(storm_events, now)
-    prune_storm_daily(state, now)
+    prune_alert_daily(state, now)
+
+    # 1) Temporali severi significativi
    if sig_storms:
-        has_imminent = any(e.get("lead_hours", 0.0) <= IMMINENT_HOURS for e in sig_storms)
-        storm_category = "imminent" if has_imminent else "extended"
-        storm_signature = build_storm_signature(storm_category, sig_storms)
-        today_key = _today_key(now)
-
-        send_storm = False
-        if debug_mode:
-            LOGGER.info("[DEBUG MODE] Bypass anti-spam: invio forzato per temporali severi")
-            send_storm = True
-        elif (state.get("storm_last_signature") == storm_signature
-              and state.get("storm_last_signature_date") == today_key):
-            LOGGER.info("Temporali: alert soppresso (dedup): situazione invariata già notificata oggi [%s]", storm_category)
-        else:
-            allowed, reason = can_notify_storm(storm_category, now, state)
-            if allowed:
-                send_storm = True
-            else:
-                LOGGER.info("Temporali: alert soppresso (rate-limit %s): %s", storm_category, reason)
-
-        if send_storm:
-            convective_msg = format_convective_alert(sig_storms, times, start_idx)
-            if convective_msg:
-                alerts.append(convective_msg)
-                should_notify = True
-                if not debug_mode:
-                    record_notify_storm(storm_category, now, state)
-                    state["storm_last_signature"] = storm_signature
-                    state["storm_last_signature_date"] = today_key
-
+        convective_msg = format_convective_alert(sig_storms, times, start_idx)
+        if convective_msg:
+            alerts.append(convective_msg)
        state["convective_storm_active"] = True
        state["last_storm_score"] = float(max(e["score"] for e in sig_storms))
    else:
        state["convective_storm_active"] = False
        state["last_storm_score"] = 0.0

-    # 2) Wind (persistent)
+    # 2) Vento persistente
    if wind_level_curr > 0:
-        prev_level = int(state.get("wind_level", 0) or 0)
-        if debug_mode or (not was_alarm) or (wind_level_curr > prev_level):
-            if debug_mode:
-                LOGGER.info("[DEBUG MODE] Bypass anti-spam: invio forzato per vento")
-            wind_msg = wind_message(wind_level_curr, wind_peak, wind_start, wind_run_len)
-            if "wind" in comparisons:
-                comp = comparisons["wind"]
-                wind_msg += f"\n⚠️ <b>Discordanza modelli</b>: AROME {comp['arome']:.0f} km/h | ICON {comp['icon']:.0f} km/h (scostamento {comp['diff_pct']:.0f}%)"
-            alerts.append(wind_msg)
-            should_notify = True
+        wind_msg = wind_message(wind_level_curr, wind_peak, wind_start, wind_run_len)
+        if "wind" in comparisons:
+            comp = comparisons["wind"]
+            wind_msg += f"\n⚠️ <b>Discordanza modelli</b>: AROME {comp['arome']:.0f} km/h | ICON {comp['icon']:.0f} km/h (scostamento {comp['diff_pct']:.0f}%)"
+        alerts.append(wind_msg)
        state["wind_level"] = wind_level_curr
        state["last_wind_peak"] = float(wind_peak)
    else:
        state["wind_level"] = 0
        state["last_wind_peak"] = 0.0

-    # 3) Rain (persistent)
+    # 3) Pioggia persistente
    if rain_persist >= PERSIST_HOURS and rain_max_3h >= RAIN_3H_LIMIT:
-        prev_rain = float(state.get("last_rain_3h", 0.0) or 0.0)
-        # "Meglio uno in più": notifica anche al primo superamento persistente,
-        # e ri-notifica se peggiora di >= +10mm sul massimo 3h
-        if debug_mode or (not was_alarm) or (rain_max_3h >= prev_rain + 10.0):
-            if debug_mode:
-                LOGGER.info("[DEBUG MODE] Bypass anti-spam: invio forzato per pioggia")
-            
-            # Analisi estesa su 48 ore per pioggia intensa
-            rain_analysis = None
-            if rain_start:
-                # Trova l'indice di inizio dell'evento cercando il timestamp corrispondente
-                rain_start_idx = -1
-                for i, t in enumerate(times):
-                    try:
-                        t_dt = parse_time_to_local(t)
-                        if ddmmyy_hhmm(t_dt) == rain_start:
-                            rain_start_idx = i
-                            break
-                    except Exception:
-                        continue
-                
-                if rain_start_idx >= 0 and rain_start_idx < len(times):
-                    # Usa soglia minima per considerare pioggia significativa (8 mm/h, coerente con RAIN_INTENSE_THRESHOLD_H)
-                    rain_analysis = analyze_rainfall_event(
-                        times=times,
-                        precipitation=rain,
-                        weathercode=wcode,
-                        start_idx=rain_start_idx,
-                        max_hours=48,
-                        threshold_mm_h=8.0  # Soglia per pioggia intensa
-                    )
-            
-            rain_msg = rain_message(rain_max_3h, rain_start, rain_persist, rain_analysis=rain_analysis)
-            if "rain" in comparisons:
-                comp = comparisons["rain"]
-                rain_msg += f"\n⚠️ <b>Discordanza modelli</b>: AROME {comp['arome']:.1f} mm | ICON {comp['icon']:.1f} mm (scostamento {comp['diff_pct']:.0f}%)"
-            alerts.append(rain_msg)
-            should_notify = True
+        rain_analysis = None
+        if rain_start:
+            rain_start_idx = -1
+            for i, t in enumerate(times):
+                try:
+                    t_dt = parse_time_to_local(t)
+                    if ddmmyy_hhmm(t_dt) == rain_start:
+                        rain_start_idx = i
+                        break
+                except Exception:
+                    continue
+            if rain_start_idx >= 0 and rain_start_idx < len(times):
+                rain_analysis = analyze_rainfall_event(
+                    times=times,
+                    precipitation=rain,
+                    weathercode=wcode,
+                    start_idx=rain_start_idx,
+                    max_hours=HOURS_AHEAD,
+                    threshold_mm_h=8.0,
+                )
+        rain_msg = rain_message(rain_max_3h, rain_start, rain_persist, rain_analysis=rain_analysis)
+        if "rain" in comparisons:
+            comp = comparisons["rain"]
+            rain_msg += f"\n⚠️ <b>Discordanza modelli</b>: AROME {comp['arome']:.1f} mm | ICON {comp['icon']:.1f} mm (scostamento {comp['diff_pct']:.0f}%)"
+        alerts.append(rain_msg)
        state["last_rain_3h"] = float(rain_max_3h)
    else:
        state["last_rain_3h"] = 0.0
@@ -1526,13 +1684,29 @@ def analyze(chat_ids: Optional[List[str]] = None, debug_mode: bool = False, lat:
        or (rain_persist >= PERSIST_HOURS and rain_max_3h >= RAIN_3H_LIMIT)
    )

-    # In modalità debug, forza invio anche se non ci sono allerte
+    should_notify = bool(alerts)
    debug_message_only = False
    if debug_mode and not alerts:
        LOGGER.info("[DEBUG MODE] Nessuna allerta, ma creo messaggio informativo")
        alerts.append("ℹ️ <i>Nessuna condizione meteo severa rilevata nelle prossime %s ore.</i>" % HOURS_AHEAD)
        should_notify = True
-        debug_message_only = True  # Segnala che è solo un messaggio debug, non una vera allerta
+        debug_message_only = True
+
+    alert_signature = build_alert_signature(alerts, wind_level_curr, rain_max_3h, sig_storms)
+
+    # --- Gate anti-spam globale (max 1/giorno + cooldown, escalation se peggioramento) ---
+    if should_notify and alerts and not debug_message_only:
+        today_key = _today_key(now)
+        if (state.get("last_alert_signature") == alert_signature
+                and state.get("last_alert_signature_date") == today_key):
+            LOGGER.info("Alert soppresso (dedup): situazione invariata già notificata oggi")
+            should_notify = False
+        elif not debug_mode:
+            escalation = is_alert_escalation(state, alert_signature, wind_level_curr, rain_max_3h)
+            allowed, reason = can_notify_message(now, state, allow_escalation=escalation)
+            if not allowed:
+                LOGGER.info("Alert soppresso (rate-limit): %s", reason)
+                should_notify = False

    # --- Send only on alerts (never on errors) ---
    if should_notify and alerts:
@@ -1564,7 +1738,6 @@ def analyze(chat_ids: Optional[List[str]] = None, debug_mode: bool = False, lat:
        # IMPORTANTE: Imposta alert_active = True solo se c'è una vera allerta,
        # non se è solo un messaggio informativo in modalità debug
        if not debug_message_only:
-            # Determina il tipo di allerta basandosi sulle condizioni attuali
            alert_types = []
            if sig_storms and len(sig_storms) > 0:
                alert_types.append("TEMPORALI SEVERI")
@@ -1577,6 +1750,8 @@ def analyze(chat_ids: Optional[List[str]] = None, debug_mode: bool = False, lat:
            state["alert_active"] = True
            state["last_alert_type"] = alert_types if alert_types else None
            state["last_alert_time"] = now.isoformat()
+            if ok:
+                record_notify_message(now, state, alert_signature)
            save_state(state)
        else:
            # In debug mode senza vere allerte, non modificare alert_active
@@ -1649,13 +1824,10 @@ def analyze(chat_ids: Optional[List[str]] = None, debug_mode: bool = False, lat:
            "last_storm_score": 0.0,
            "last_alert_type": None,
            "last_alert_time": None,
-            # Preserva i contatori giornalieri/cooldown temporali (i cap valgono
-            # per l'intera giornata anche dopo un all-clear); azzera solo la firma.
-            "storm_daily": state.get("storm_daily", {}),
-            "storm_last_sent_imminent": state.get("storm_last_sent_imminent"),
-            "storm_last_sent_extended": state.get("storm_last_sent_extended"),
-            "storm_last_signature": None,
-            "storm_last_signature_date": None,
+            "alert_daily": state.get("alert_daily", {}),
+            "last_alert_sent": state.get("last_alert_sent"),
+            "last_alert_signature": None,
+            "last_alert_signature_date": None,
        }
        save_state(state)
        return
@@ -115,13 +115,19 @@ def setup_logger() -> logging.Logger:
    logger.setLevel(logging.DEBUG if DEBUG else logging.INFO)
    logger.handlers.clear()

-    fh = RotatingFileHandler(LOG_FILE, maxBytes=1_000_000, backupCount=5, encoding="utf-8")
-    fh.setLevel(logging.DEBUG)
    fmt = logging.Formatter("%(asctime)s %(levelname)s %(message)s")
-    fh.setFormatter(fmt)
-    logger.addHandler(fh)
+    log_path = os.environ.get("SNOW_RADAR_LOG", LOG_FILE)
+    try:
+        fh = RotatingFileHandler(log_path, maxBytes=1_000_000, backupCount=5, encoding="utf-8")
+        fh.setLevel(logging.DEBUG)
+        fh.setFormatter(fmt)
+        logger.addHandler(fh)
+    except OSError:
+        sh = logging.StreamHandler()
+        sh.setFormatter(fmt)
+        logger.addHandler(sh)

-    if DEBUG:
+    if DEBUG and not any(isinstance(h, logging.StreamHandler) for h in logger.handlers):
        sh = logging.StreamHandler()
        sh.setLevel(logging.DEBUG)
        sh.setFormatter(fmt)
@@ -779,14 +785,106 @@ def main(chat_ids: Optional[List[str]] = None, debug_mode: bool = False, chat_id
            LOGGER.error("Errore generazione mappe")


+def collect_snow_radar_results(session) -> Tuple[List[Dict], List[Dict]]:
+    """Analizza tutte le località; ritorna (tutte le analisi, subset per mappe)."""
+    now = now_local()
+    center_lat, center_lon = 43.9356, 12.4296
+    all_rows: List[Dict] = []
+    map_results: List[Dict] = []
+
+    for i, loc in enumerate(LOCATIONS):
+        distance_km = calculate_distance_km(center_lat, center_lon, loc["lat"], loc["lon"])
+        data = get_forecast(session, loc["lat"], loc["lon"])
+        if not data:
+            continue
+        snow_analysis = analyze_snowfall_for_location(data, now)
+        if not snow_analysis:
+            continue
+
+        is_casa = loc["name"] == "Casa (Strada Cà Toro)"
+        has_snow = (
+            snow_analysis["snow_past_12h"] >= SNOW_THRESHOLD_CM
+            or snow_analysis["snow_next_12h"] >= SNOW_THRESHOLD_CM
+            or snow_analysis["snow_next_24h"] >= SNOW_THRESHOLD_CM
+        )
+        row = {
+            "name": loc["name"],
+            "lat": loc["lat"],
+            "lon": loc["lon"],
+            "distance_km": distance_km,
+            "has_snow": has_snow,
+            **snow_analysis,
+        }
+        all_rows.append(row)
+        if is_casa or has_snow:
+            map_results.append(row)
+        time.sleep(0.1)
+
+    return all_rows, map_results
+
+
+def build_snow_radar_json(maps_dir: Optional[str] = None) -> Dict:
+    """Analisi completa per WebApp (senza Telegram)."""
+    now = now_local()
+    center_lat, center_lon = 43.9356, 12.4296
+    total = len(LOCATIONS)
+
+    with requests.Session() as session:
+        configure_open_meteo_session(session, headers=HTTP_HEADERS)
+        all_rows, map_results = collect_snow_radar_results(session)
+
+    count_past = sum(1 for r in all_rows if r.get("snow_past_12h", 0) >= SNOW_THRESHOLD_CM)
+    count_future = sum(1 for r in all_rows if r.get("snow_next_24h", 0) >= SNOW_THRESHOLD_CM)
+    active = count_past > 0 or count_future > 0
+
+    payload: Dict = {
+        "active": active,
+        "updated_at": now.strftime("%d/%m/%Y %H:%M"),
+        "total_locations": total,
+        "count_past_12h": count_past,
+        "count_next_24h": count_future,
+        "locations": [
+            {
+                "name": r["name"],
+                "snow_past_12h": round(float(r.get("snow_past_12h", 0)), 1),
+                "snow_next_24h": round(float(r.get("snow_next_24h", 0)), 1),
+                "has_snow": bool(r.get("has_snow")),
+            }
+            for r in sorted(all_rows, key=lambda x: (-x.get("snow_next_24h", 0), x["name"]))
+            if r.get("has_snow")
+        ],
+        "maps": {"past": None, "future": None},
+    }
+
+    if active and maps_dir:
+        os.makedirs(maps_dir, exist_ok=True)
+        past_path = os.path.join(maps_dir, "snow_radar_past.png")
+        future_path = os.path.join(maps_dir, "snow_radar_future.png")
+        if generate_snow_map(map_results, center_lat, center_lon, past_path,
+                             data_field="snow_past_12h", title_suffix=" - Ultime 12h"):
+            payload["maps"]["past"] = "past"
+        if generate_snow_map(map_results, center_lat, center_lon, future_path,
+                             data_field="snow_next_24h", title_suffix=" - Prossime 24h"):
+            payload["maps"]["future"] = "future"
+
+    return payload
+
+
 if __name__ == "__main__":
    arg_parser = argparse.ArgumentParser(description="Snow Radar - Analisi neve in griglia 30km")
    arg_parser.add_argument("--debug", action="store_true", help="Invia messaggi solo all'admin (chat ID: %s)" % TELEGRAM_CHAT_IDS[0])
    arg_parser.add_argument("--chat_id", type=str, help="Chat ID specifico per invio messaggio (override debug mode)")
+    arg_parser.add_argument("--json", action="store_true", help="Output JSON per WebApp (no Telegram)")
+    arg_parser.add_argument("--maps-dir", type=str, default="", help="Directory per salvare mappe PNG (con --json)")
    args = arg_parser.parse_args()
-    
+
+    if args.json:
+        maps_dir = args.maps_dir.strip() or None
+        print(json.dumps(build_snow_radar_json(maps_dir=maps_dir), ensure_ascii=False))
+        raise SystemExit(0)
+
    # Se --chat_id è specificato, usa quello; altrimenti usa logica debug
    chat_id = args.chat_id if args.chat_id else None
    chat_ids = None if chat_id else ([TELEGRAM_CHAT_IDS[0]] if args.debug else None)
-    
+
    main(chat_ids=chat_ids, debug_mode=args.debug, chat_id=chat_id)