#!/usr/bin/env bash
# hns_dispatch.sh — parallel HNS player deep-scrape dispatcher
# ──────────────────────────────────────────────────────────────
# Author:  dradulic@outlook.com / damir@rinet.one
# Date:    2026-05-05
# Version: 1.0
# Description:
#   Reads a shard file of HNS player IDs (one per line) and invokes
#   /opt/pgz-sport/scripts/hns_player_deep.py --player <ID> --no-telegram
#   sequentially for each ID. Designed to be launched 5x in parallel
#   (one per shard) so 5 worker processes each chew through ~175 IDs.
#
# Usage:
#   bash /opt/pgz-sport/scripts/hns_dispatch.sh <shard_file> <worker_id>
#   bash /opt/pgz-sport/scripts/hns_dispatch.sh /tmp/hns_shard_aa 1
#
# Per-worker log: /tmp/hns_worker_<worker_id>.log
# Each player attempt: ~1s (HTTP + parse + UPSERT).
# Stagger workers manually with `sleep N &&` when launching.

set -u

SHARD_FILE="${1:?usage: hns_dispatch.sh <shard_file> <worker_id>}"
WORKER_ID="${2:?usage: hns_dispatch.sh <shard_file> <worker_id>}"
LOG="/tmp/hns_worker_${WORKER_ID}.log"
SCRIPT="/opt/pgz-sport/scripts/hns_player_deep.py"

cd /opt/pgz-sport || exit 2

echo "[$(date -Iseconds)] worker=${WORKER_ID} shard=${SHARD_FILE} start ($(wc -l < "$SHARD_FILE") IDs)" >> "$LOG"

count=0
ok=0
fail=0
while IFS= read -r ID; do
    [ -z "$ID" ] && continue
    count=$((count + 1))
    if python3 "$SCRIPT" --player "$ID" --no-telegram >> "$LOG" 2>&1; then
        ok=$((ok + 1))
    else
        fail=$((fail + 1))
        echo "[$(date -Iseconds)] worker=${WORKER_ID} FAIL id=${ID}" >> "$LOG"
    fi
    # tiny politeness pause; HNS is light traffic but 5 parallel workers
    # = 5 req/s aggregate; small jitter helps avoid bursts
    sleep 0.2
done < "$SHARD_FILE"

echo "[$(date -Iseconds)] worker=${WORKER_ID} done count=${count} ok=${ok} fail=${fail}" >> "$LOG"