Janis Eccarius
283c6728d4
13 separate DB connections on index page caused readiness probe timeout. Now all counts share one connection. BrokenPipeError on probe disconnect silenced. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
286 lines
11 KiB
YAML
Executable File
286 lines
11 KiB
YAML
Executable File
apiVersion: v1
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kind: ConfigMap
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metadata:
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name: spark-analytics-webview
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labels:
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app.kubernetes.io/name: spark-analytics
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app.kubernetes.io/part-of: nowchess
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data:
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serve.py: |
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#!/usr/bin/env python3
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"""Spark analytics results viewer — queries PostgreSQL analytics tables, serves HTML tables."""
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import html
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import os
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import re
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import psycopg2
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import psycopg2.extras
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from http.server import BaseHTTPRequestHandler, HTTPServer
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PORT = int(os.environ.get("PORT", "8080"))
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_url = os.environ.get("NOWCHESS_JDBC_URL", "")
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_m = re.match(r"jdbc:postgresql://([^:/]+)(?::(\d+))?/([^?]+)", _url)
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DB_HOST = _m.group(1) if _m else "localhost"
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DB_PORT = int(_m.group(2)) if (_m and _m.group(2)) else 5432
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DB_NAME = _m.group(3) if _m else "nowchess"
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DB_USER = os.environ.get("NOWCHESS_DB_USER", "nowchess")
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DB_PASS = os.environ.get("NOWCHESS_DB_PASS", "")
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# Each tuple: (url-slug, display label, postgres table name)
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DATASETS = [
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("opening-book", "Opening Book (Top 1000)", "analytics_opening_stats"),
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("player-stats", "Player Statistics", "analytics_player_stats"),
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("cluster-archetypes", "Cluster Archetypes", "analytics_cluster_archetypes"),
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("component-sizes", "Graph Component Sizes", "analytics_component_sizes"),
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("game-length", "Game Length Distribution", "analytics_game_length_distribution"),
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("game-length-by-result", "Game Length by Result", "analytics_game_length_by_result"),
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("color-advantage", "Color Advantage", "analytics_color_advantage"),
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("elo-distribution", "ELO Distribution", "analytics_elo_distribution"),
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("time-control", "Time Control Analysis", "analytics_time_control_stats"),
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("hourly-activity", "Hourly Activity", "analytics_hourly_activity"),
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("weekly-activity", "Weekly Activity", "analytics_weekly_activity"),
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("rating-mismatch", "Rating Mismatch (Upsets)", "analytics_rating_mismatch"),
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("termination-stats", "Termination Types", "analytics_termination_stats"),
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]
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CSS = """
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* { box-sizing: border-box; }
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body { font-family: 'Segoe UI', sans-serif; margin: 0; background: #0d1117; color: #c9d1d9; }
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header { background: #161b22; border-bottom: 1px solid #30363d; padding: 1rem 2rem; }
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header h1 { margin: 0; color: #58a6ff; font-size: 1.25rem; font-weight: 600; }
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header span { color: #8b949e; font-size: 0.875rem; margin-left: 0.5rem; }
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main { padding: 1.5rem 2rem; }
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h2 { color: #e6edf3; font-size: 1rem; font-weight: 600; margin: 0 0 1rem; }
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.cards { display: grid; grid-template-columns: repeat(auto-fill, minmax(260px, 1fr)); gap: 1rem; }
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.card { background: #161b22; border: 1px solid #30363d; border-radius: 8px; padding: 1rem; }
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.card h3 { margin: 0 0 0.5rem; font-size: 0.9rem; color: #58a6ff; }
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.card a { text-decoration: none; color: inherit; display: block; }
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.card a:hover .card-label { text-decoration: underline; }
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.badge { display: inline-block; background: #21262d; border: 1px solid #30363d;
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border-radius: 12px; padding: 1px 8px; font-size: 0.75rem; color: #8b949e; }
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.badge.ready { border-color: #238636; color: #3fb950; }
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.back { color: #58a6ff; text-decoration: none; font-size: 0.875rem; }
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.back:hover { text-decoration: underline; }
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.meta { color: #8b949e; font-size: 0.8rem; margin: 0.5rem 0 1rem; }
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table { width: 100%; border-collapse: collapse; font-size: 0.8rem; }
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thead th { background: #161b22; position: sticky; top: 0; padding: 6px 12px;
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text-align: left; color: #8b949e; border-bottom: 1px solid #30363d;
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font-weight: 600; white-space: nowrap; }
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tbody td { padding: 5px 12px; border-bottom: 1px solid #21262d; }
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tbody tr:hover td { background: #161b22; }
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.table-wrap { overflow-x: auto; border: 1px solid #30363d; border-radius: 6px; }
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.notice { background: #161b22; border: 1px solid #30363d; border-radius: 6px;
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padding: 1.5rem; color: #8b949e; }
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"""
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def get_conn():
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return psycopg2.connect(host=DB_HOST, port=DB_PORT, dbname=DB_NAME, user=DB_USER, password=DB_PASS)
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def all_row_counts() -> dict:
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counts = {}
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try:
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with get_conn() as conn:
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with conn.cursor() as cur:
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for _, _, table in DATASETS:
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try:
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cur.execute(f"SELECT COUNT(*) FROM {table}")
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counts[table] = cur.fetchone()[0]
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except Exception:
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conn.rollback()
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counts[table] = -1
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except Exception:
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for _, _, table in DATASETS:
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counts.setdefault(table, -1)
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return counts
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def fetch_rows(table: str, limit: int = 10_000):
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with get_conn() as conn:
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with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur:
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cur.execute(f"SELECT * FROM {table} LIMIT %s", (limit,))
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rows = cur.fetchall()
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if not rows:
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return [], []
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headers = list(rows[0].keys())
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data = [
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[str(row[h]) if row[h] is not None else "" for h in headers]
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for row in rows
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]
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return headers, data
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def page(title: str, body: str) -> str:
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return (
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f"<!doctype html><html lang=en><head><meta charset=utf-8>"
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f"<meta name=viewport content='width=device-width,initial-scale=1'>"
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f"<title>{html.escape(title)} — Spark Analytics</title>"
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f"<style>{CSS}</style></head><body>"
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f"<header><h1>Spark Analytics</h1><span>NowChess · staging</span></header>"
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f"<main>{body}</main></body></html>"
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)
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def index_html() -> str:
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counts = all_row_counts()
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cards = ""
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for slug, label, table in DATASETS:
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count = counts.get(table, -1)
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if count > 0:
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badge = f'<span class="badge ready">{count} rows</span>'
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elif count == 0:
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badge = '<span class="badge">no data yet</span>'
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else:
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badge = '<span class="badge">table missing</span>'
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cards += (
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f'<div class="card"><a href="/{slug}">'
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f'<div class="card-label"><h3>{html.escape(label)}</h3></div>'
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f"{badge}</a></div>"
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)
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return page("Results", f"<h2>Datasets</h2><div class='cards'>{cards}</div>")
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def table_html(slug: str, label: str, table: str) -> str:
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back = '<a class="back" href="/">← All datasets</a>'
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try:
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headers, rows = fetch_rows(table)
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except Exception as e:
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return page(
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label,
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f"{back}<h2>{html.escape(label)}</h2>"
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f"<div class='notice'>Error querying {html.escape(table)} on {html.escape(DB_HOST)}:{DB_PORT}/{html.escape(DB_NAME)}: {html.escape(str(e))}</div>",
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)
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if not headers:
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return page(
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label,
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f"{back}<h2>{html.escape(label)}</h2>"
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"<div class='notice'>No data yet. Run the CronJob first, then check back.</div>",
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)
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ths = "".join(f"<th>{html.escape(h)}</th>" for h in headers)
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trs = "".join(
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"<tr>" + "".join(f"<td>{html.escape(str(c))}</td>" for c in row) + "</tr>"
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for row in rows[:10_000]
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)
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truncated = f" (showing first 10 000 of {len(rows)})" if len(rows) > 10_000 else ""
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return page(
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label,
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f"{back}<h2>{html.escape(label)}</h2>"
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f"<p class='meta'>{len(rows)} rows{truncated}</p>"
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f"<div class='table-wrap'><table><thead><tr>{ths}</tr></thead>"
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f"<tbody>{trs}</tbody></table></div>",
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)
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SLUG_MAP = {s: (label, table) for s, label, table in DATASETS}
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class Handler(BaseHTTPRequestHandler):
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def log_message(self, fmt, *args):
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pass
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def do_GET(self):
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path = self.path.split("?")[0].lstrip("/")
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if path == "" or path == "index.html":
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self._send(index_html())
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elif path in SLUG_MAP:
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label, table = SLUG_MAP[path]
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self._send(table_html(path, label, table))
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else:
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self.send_response(404)
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self.end_headers()
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def _send(self, body: str):
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data = body.encode("utf-8")
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self.send_response(200)
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self.send_header("Content-Type", "text/html; charset=utf-8")
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self.send_header("Content-Length", str(len(data)))
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self.end_headers()
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try:
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self.wfile.write(data)
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except BrokenPipeError:
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pass
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if __name__ == "__main__":
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server = HTTPServer(("0.0.0.0", PORT), Handler)
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print(f"Listening on :{PORT} DB={DB_HOST}:{DB_PORT}/{DB_NAME} JDBC_URL={_url!r}", flush=True)
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server.serve_forever()
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---
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: spark-analytics-webview
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labels:
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app.kubernetes.io/name: spark-analytics
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app.kubernetes.io/part-of: nowchess
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spec:
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replicas: 0
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strategy:
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type: Recreate
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selector:
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matchLabels:
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app: spark-analytics-webview
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template:
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metadata:
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labels:
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app: spark-analytics-webview
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app.kubernetes.io/name: spark-analytics
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app.kubernetes.io/part-of: nowchess
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spec:
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securityContext:
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runAsNonRoot: true
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runAsUser: 65534
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fsGroup: 65534
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containers:
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- name: webview
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image: python:3.12-slim
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command: ["sh", "-c", "pip install psycopg2-binary --quiet --no-cache-dir --target=/tmp/pkg && PYTHONPATH=/tmp/pkg python /scripts/serve.py"]
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ports:
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- containerPort: 8080
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env:
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- name: PORT
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value: "8080"
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- name: NOWCHESS_JDBC_URL
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valueFrom:
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secretKeyRef:
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name: ncs-db-secrets
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key: STORE_DB_URL
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- name: NOWCHESS_DB_USER
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valueFrom:
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secretKeyRef:
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name: ncs-db-secrets
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key: STORE_DB_USER
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- name: NOWCHESS_DB_PASS
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valueFrom:
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secretKeyRef:
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name: ncs-db-secrets
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key: STORE_DB_PASSWORD
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volumeMounts:
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- name: scripts
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mountPath: /scripts
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readinessProbe:
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httpGet:
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path: /
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port: 8080
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initialDelaySeconds: 15
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periodSeconds: 10
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resources:
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requests:
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cpu: 10m
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memory: 64Mi
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limits:
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cpu: 200m
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memory: 256Mi
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volumes:
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- name: scripts
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configMap:
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name: spark-analytics-webview
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defaultMode: 0755
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---
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apiVersion: v1
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kind: Service
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metadata:
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name: spark-analytics-webview
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labels:
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app.kubernetes.io/name: spark-analytics
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app.kubernetes.io/part-of: nowchess
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spec:
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selector:
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app: spark-analytics-webview
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ports:
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- name: http
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port: 8080
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targetPort: 8080
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