{
  "type": "tool_call",
  "seq": 51,
  "ts": "2026-11-08T02:10:15.588Z",
  "name": "write",
  "turn": 1,
  "input": {
    "path": "/sandbox/repo/clickhouse-demo/example.py",
    "content": "#!/usr/bin/env python3\n\"\"\"Minimal ClickHouse example using the official Python SDK (clickhouse-connect).\n\nEverything runs against a *hosted* ClickHouse over HTTPS. No local server, no\nDocker, no long-running commands.\n\nTwo modes, chosen automatically from the connection settings:\n\n1. Public playground (default, zero credentials)\n   host = play.clickhouse.com, user = play\n   -> read-only. We run analytics against the real datasets ClickHouse hosts\n      there (~37M Hacker News rows, ~43M cell towers).\n\n2. Your own instance (ClickHouse Cloud trial, or any reachable server)\n   Set CLICKHOUSE_HOST / CLICKHOUSE_USER / CLICKHOUSE_PASSWORD\n   -> the script also does the full write lifecycle:\n      CREATE TABLE -> INSERT -> analytical SELECTs -> DROP TABLE.\n\nUsage:\n    python3 example.py                       # playground, read-only analytics\n    CLICKHOUSE_HOST=<host> \\\n    CLICKHOUSE_USER=<user> \\\n    CLICKHOUSE_PASSWORD=<pw> \\\n    python3 example.py                       # your instance, full read+write\n\nEnv vars (all optional):\n    CLICKHOUSE_HOST      default: play.clickhouse.com\n    CLICKHOUSE_PORT      default: 443\n    CLICKHOUSE_USER      default: play\n    CLICKHOUSE_PASSWORD  default: \"\"\n    CLICKHOUSE_DATABASE  default: default\n    CLICKHOUSE_SECURE    default: true  (set to \"false\" for plain HTTP servers)\n\"\"\"\n\nfrom __future__ import annotations\n\nimport os\nimport random\nimport sys\nimport time\nimport uuid\nfrom datetime import datetime, timedelta, timezone\n\nimport clickhouse_connect\nfrom clickhouse_connect.driver.exceptions import ClickHouseError\n\n# --------------------------------------------------------------------------\n# Connection settings\n# --------------------------------------------------------------------------\n\nPLAYGROUND_HOST = \"play.clickhouse.com\"\n\nHOST = os.getenv(\"CLICKHOUSE_HOST\", PLAYGROUND_HOST)\nPORT = int(os.getenv(\"CLICKHOUSE_PORT\", \"443\"))\nUSER = os.getenv(\"CLICKHOUSE_USER\", \"play\")\nPASSWORD = os.getenv(\"CLICKHOUSE_PASSWORD\", \"\")\nDATABASE = os.getenv(\"CLICKHOUSE_DATABASE\", \"default\")\nSECURE = os.getenv(\"CLICKHOUSE_SECURE\", \"true\").lower() not in (\"0\", \"false\", \"no\")\n\n# The public playground grants no DDL privileges, so only attempt the write\n# lifecycle when we are pointed at an instance we actually own.\nWRITABLE = HOST != PLAYGROUND_HOST\n\nDEMO_DB = \"pi_demo\"\nDEMO_TABLE = f\"{DEMO_DB}.page_events\"\n\nCOUNTRIES = [\"US\", \"DE\", \"GB\", \"JP\", \"BR\", \"IN\", \"FR\", \"CA\"]\nDEVICES = [\"desktop\", \"mobile\", \"tablet\"]\nPATHS = [\"/\", \"/pricing\", \"/docs\", \"/blog\", \"/signup\", \"/docs/quickstart\"]\nTAGS = [\"organic\", \"paid\", \"referral\", \"mobile-app\", \"eu\", \"trial\", \"returning\"]\n\n\n# --------------------------------------------------------------------------\n# Small helpers\n# --------------------------------------------------------------------------\n\n\ndef section(title: str) -> None:\n    print(f\"\\n{'=' * 72}\\n{title}\\n{'=' * 72}\")\n\n\ndef build_client():\n    \"\"\"Create an HTTPS client. This is the whole 'connection pool' story:\n    clickhouse-connect keeps a pool inside the client, so create one and reuse it.\"\"\"\n    return clickhouse_connect.get_client(\n        host=HOST,\n        port=PORT,\n        username=USER,\n        password=PASSWORD,\n        database=DATABASE,\n        secure=SECURE,\n        interface=\"https\" if SECURE else \"http\",\n        # Sensible defaults for a demo; tune per workload.\n        connect_timeout=15,\n        send_receive_timeout=60,\n    )\n\n\ndef show(client, sql: str, title: str, params: dict | None = None) -> None:\n    \"\"\"Run a SELECT and print the result plus what the server told us it cost.\"\"\"\n    section(title)\n    print(sql.strip(), \"\\n\")\n\n    started = time.perf_counter()\n    result = client.query(sql, parameters=params)\n    wall_ms = (time.perf_counter() - started) * 1000\n\n    widths = [len(str(c)) for c in result.column_names]\n    rows = [[(\"\" if v is None else v) for v in row] for row in result.result_rows]\n    for row in rows:\n        for i, v in enumerate(row):\n            widths[i] = max(widths[i], len(str(v)))\n\n    def fmt(values):\n        return \" | \".join(str(v).ljust(w) for v, w in zip(values, widths))\n\n    print(fmt(result.column_names))\n    print(\"-+-\".join(\"-\" * w for w in widths))\n    for row in rows:\n        print(fmt(row))\n\n    summary = result.summary or {}\n    read_rows = summary.get(\"read_rows\", \"n/a\")\n    read_bytes = summary.get(\"read_bytes\", \"n/a\")\n    print(\n        f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms | \"\n        f\"server scanned {read_rows} rows / {int(read_bytes) / 1e6:.1f} MB\"\n        if str(read_bytes).isdigit()\n        else f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms\"\n    )\n\n\ndef table_exists(client, database: str, table: str) -> bool:\n    res = client.query(\n        \"SELECT count() FROM system.tables WHERE database = {db:String} AND name = {tbl:String}\",\n        parameters={\"db\": database, \"tbl\": table},\n    )\n    return int(res.result_rows[0][0]) > 0\n\n\n# --------------------------------------------------------------------------\n# Part 1: read / analytics (works on any instance that has the demo datasets)\n# --------------------------------------------------------------------------\n\n\ndef analytics_demo(client) -> None:\n    if not table_exists(client, \"default\", \"hackernews\"):\n        section(\"Part 1: analytics demo\")\n        print(\"Skipped: this instance has no `default.hackernews` dataset.\")\n        print(\"(The public playground hosts it; a fresh ClickHouse Cloud does not.)\")\n        return\n\n    show(\n        client,\n        \"\"\"\n        SELECT\n            by                    AS author,\n            count()               AS stories,\n            round(avg(score), 1)  AS avg_score,\n            max(score)            AS best_score\n        FROM default.hackernews\n        WHERE type = 'story' AND score > 0 AND by != ''\n        GROUP BY author\n        ORDER BY stories DESC\n        LIMIT 8\n        \"\"\",\n        \"Part 1a: GROUP BY over ~37M rows (aggregation is ClickHouse's bread and butter)\",\n    )\n\n    show(\n        client,\n        \"\"\"\n        SELECT\n            toYear(time)          AS year,\n            count()               AS items,\n            countIf(type = 'story') AS stories,\n            round(quantile(0.95)(score), 1) AS p95_score\n        FROM default.hackernews\n        WHERE time >= toDateTime('2015-01-01')\n        GROUP BY year\n        ORDER BY year DESC\n        LIMIT 6\n        \"\"\",\n        \"Part 1b: time bucketing + quantiles (quantile is approximate and very fast)\",\n    )\n\n    show(\n        client,\n        \"\"\"\n        SELECT\n            radio                          AS technology,\n            count()                        AS towers,\n            round(avg(averageSignal), 1)   AS avg_signal\n        FROM default.cell_towers\n        GROUP BY technology\n        ORDER BY towers DESC\n        \"\"\",\n        \"Part 1c: Enum8 column, second dataset (~43M rows)\",\n    )\n\n    # Server-side parameter binding: values are sent separately from the SQL,\n    # so no string interpolation / injection risk.\n    show(\n        client,\n        \"\"\"\n        SELECT id, time, score, left(title, 60) AS title\n        FROM default.hackernews\n        WHERE type = 'story' AND score >= {min_score:Int32}\n        ORDER BY score DESC\n        LIMIT 5\n        \"\"\",\n        \"Part 1d: parameterised query (bind variables, not string building)\",\n        params={\"min_score\": 3000},\n    )\n\n    # Optional: pandas integration (query_df) if pandas is installed.\n    try:\n        import pandas  # noqa: F401\n    except ImportError:\n        print(\"\\n(pandas not installed - skipping query_df demo)\")\n        return\n\n    section(\"Part 1e: client.query_df() -> pandas DataFrame\")\n    df = client.query_df(\n        \"\"\"\n        SELECT toStartOfMonth(time) AS month, count() AS items\n        FROM default.hackernews\n        WHERE time >= toDateTime('2020-01-01')\n        GROUP BY month\n        ORDER BY month DESC\n        LIMIT 8\n        \"\"\"\n    )\n    print(df.to_string(index=False))\n    print(f\"\\ndtypes:\\n{df.dtypes}\")\n\n\n# --------------------------------------------------------------------------\n# Part 2: write lifecycle (needs an instance where we have DDL rights)\n# --------------------------------------------------------------------------\n\n\ndef generate_rows(n: int = 5_000) -> list[list]:\n    \"\"\"Fake page-view events, newest first-ish, spread over the last hour.\"\"\"\n    rng = random.Random(42)  # deterministic so the demo output is stable\n    now = datetime.now(timezone.utc).replace(tzinfo=None)\n    rows = []\n    for i in range(n):\n        rows.append(\n            [\n                now - timedelta(seconds=rng.randint(0, 3600)),   # event_time\n                rng.randint(1, 500),                             # user_id\n                uuid.uuid4(),                                    # session_id\n                rng.choice(COUNTRIES),                           # country\n                rng.choice(DEVICES),                             # device\n                rng.choice(PATHS),                               # path\n                rng.randint(20, 8_000),                          # duration_ms\n                rng.sample(TAGS, k=rng.randint(1, 3)),           # tags (Array)\n                {\"plan\": rng.choice([\"free\", \"pro\"]), \"v\": \"2\"}, # Map(String,String)\n            ]\n        )\n    return rows\n\n\ndef write_demo(client) -> None:\n    section(\"Part 2: write lifecycle (CREATE -> INSERT -> SELECT -> DROP)\")\n\n    client.command(f\"CREATE DATABASE IF NOT EXISTS {DEMO_DB}\")\n    client.command(f\"DROP TABLE IF EXISTS {DEMO_TABLE}\")\n    client.command(\n        f\"\"\"\n        CREATE TABLE {DEMO_TABLE}\n        (\n            event_time  DateTime64(3, 'UTC'),\n            user_id     UInt64,\n            session_id  UUID,\n            country     LowCardinality(String),\n            device      Enum8('desktop' = 1, 'mobile' = 2, 'tablet' = 3),\n            path        String,\n            duration_ms UInt32,\n            tags        Array(LowCardinality(String)),\n            attributes  Map(String, String)\n        )\n        ENGINE = MergeTree\n        PARTITION BY toYYYYMM(event_time)\n        ORDER BY (country, user_id, event_time)\n        TTL toDateTime(event_time) + INTERVAL 30 DAY\n        \"\"\"\n    )\n    print(f\"created {DEMO_TABLE} (MergeTree, partitioned by month, TTL 30 days)\")\n\n    rows = generate_rows()\n    columns = [\n        \"event_time\",\n        \"user_id\",\n        \"session_id\",\n        \"country\",\n        \"device\",\n        \"path\",\n        \"duration_ms\",\n        \"tags\",\n        \"attributes\",\n    ]\n\n    started = time.perf_counter()\n    client.insert(DEMO_TABLE, rows, column_names=columns)\n    ms = (time.perf_counter() - started) * 1000\n    print(\n        f\"inserted {len(rows):,} rows in {ms:.0f} ms \"\n        f\"({len(rows) / max(ms, 1) * 1000:,.0f} rows/s) - native columnar insert, no SQL text\"\n    )\n\n    show(\n        client,\n        f\"\"\"\n        SELECT\n            country,\n            count()                          AS events,\n            uniqExact(user_id)               AS users,\n            round(quantile(0.95)(duration_ms)) AS p95_ms,\n            round(avg(duration_ms))          AS avg_ms\n        FROM {DEMO_TABLE}\n        GROUP BY country\n        ORDER BY events DESC\n        \"\"\",\n        \"Part 2a: aggregate what we just wrote\",\n    )\n\n    show(\n        client,\n        f\"\"\"\n        SELECT\n            toStartOfTenMinutes(event_time) AS bucket,\n            count()                         AS events,\n            countIf(device = 'mobile')      AS mobile_events\n        FROM {DEMO_TABLE}\n        GROUP BY bucket\n        ORDER BY bucket\n        \"\"\",\n        \"Part 2b: time-series rollup\",\n    )\n\n    show(\n        client,\n        f\"\"\"\n        SELECT\n            tag,\n            count()                    AS events,\n            uniqExact(user_id)         AS users\n        FROM {DEMO_TABLE}\n        ARRAY JOIN tags AS tag\n        GROUP BY tag\n        ORDER BY events DESC\n        LIMIT 5\n        \"\"\",\n        \"Part 2c: ARRAY JOIN (explode an Array column into rows)\",\n    )\n\n    show(\n        client,\n        f\"\"\"\n        SELECT\n            attributes['plan']         AS plan,\n            count()                    AS events,\n            round(avg(duration_ms))    AS avg_ms\n        FROM {DEMO_TABLE}\n        GROUP BY plan\n        ORDER BY events DESC\n        \"\"\",\n        \"Part 2d: read out of a Map column\",\n    )\n\n    show(\n        client,\n        f\"\"\"\n        SELECT\n            name,\n            engine,\n            total_rows,\n            formatReadableSize(total_bytes) AS on_disk,\n            formatReadableSize(data_compressed_bytes) AS compressed\n        FROM system.tables\n        WHERE database = '{DEMO_DB}' AND name = 'page_events'\n        \"\"\",\n        \"Part 2e: what the engine did with our data (compression ratio is the fun part)\",\n    )\n\n    client.command(f\"DROP TABLE IF EXISTS {DEMO_TABLE}\")\n    print(f\"cleaned up: dropped {DEMO_TABLE}\")\n\n\n# --------------------------------------------------------------------------\n\n\ndef main() -> int:\n    section(\"Connecting\")\n    print(\n        f\"host     : {HOST}:{PORT} ({'https' if SECURE else 'http'})\\n\"\n        f\"user     : {USER}\\n\"\n        f\"database : {DATABASE}\\n\"\n        f\"mode     : {'read + write' if WRITABLE else 'read-only (public playground)'}\"\n    )\n\n    try:\n        client = build_client()\n        version = client.server_version\n        tz = client.server_tz\n        print(f\"server   : ClickHouse {version} ({tz})\")\n    except ClickHouseError as exc:\n        print(f\"\\nCould not connect: {exc}\", file=sys.stderr)\n        print(\n            \"\\nTroubleshooting:\\n\"\n            \"  - ClickHouse Cloud: use the HTTPS endpoint on port 8443 and the\\n\"\n            \"    'default' user + password from the console (SQL console -> connect).\\n\"\n            \"  - Check CLICKHOUSE_HOST has no scheme/path, e.g. abc123.eu-west-1.aws.clickhouse.cloud\\n\"\n            \"  - Self-hosted plain HTTP on 8123: set CLICKHOUSE_SECURE=false and CLICKHOUSE_PORT=8123\",\n            file=sys.stderr,\n        )\n        return 1\n\n    try:\n        analytics_demo(client)\n\n        if WRITABLE:\n            write_demo(client)\n        else:\n            section(\"Part 2: write lifecycle\")\n            print(\n                \"Skipped: play.clickhouse.com is read-only \"\n                \"(CREATE TABLE returns ACCESS_DENIED, code 497).\\n\"\n                \"Point the script at your own instance to see it:\\n\\n\"\n                \"  CLICKHOUSE_HOST=<your-host> CLICKHOUSE_USER=<user> \\\\\\n\"\n                \"  CLICKHOUSE_PASSWORD=<password> python3 example.py\\n\\n\"\n                \"A free ClickHouse Cloud trial ($300 of credits / 30 days) is enough.\"\n            )\n\n        section(\"Done\")\n        print(\"All queries ran over HTTPS against a hosted ClickHouse. No local server needed.\")\n        return 0\n    except ClickHouseError as exc:\n        print(f\"\\nClickHouse error: {exc}\", file=sys.stderr)\n        return 1\n    finally:\n        try:\n            client.close()\n        except Exception:\n            pass\n\n\nif __name__ == \"__main__\":\n    raise SystemExit(main())\n"
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-9fe50ddd92a8ee0b",
  "tool_kind": "file_edit"
}

{
  "type": "tool_result",
  "seq": 53,
  "ts": "2026-11-08T02:10:15.588Z",
  "turn": 1,
  "output": {
    "content": [
      {
        "text": "Successfully wrote 14999 bytes to /sandbox/repo/clickhouse-demo/example.py",
        "type": "text"
      }
    ]
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-9fe50ddd92a8ee0b",
  "is_error": false,
  "tool_kind": "file_edit"
}

{
  "type": "tool_call",
  "seq": 52,
  "ts": "2026-11-08T02:10:15.588Z",
  "name": "write",
  "turn": 1,
  "input": {
    "path": "/sandbox/repo/clickhouse-demo/http_api.sh",
    "content": "#!/usr/bin/env bash\n# Zero-dependency ClickHouse demo: the raw HTTP interface with curl.\n#\n# ClickHouse speaks HTTP natively (8443/TLS or 8123/plain), so any language with\n# an HTTP client works. The SDKs are just convenience wrappers over this.\n#\n#   ./http_api.sh              # public playground (read-only, no credentials)\n#   CLICKHOUSE_HOST=<host> CLICKHOUSE_USER=<user> CLICKHOUSE_PASSWORD=<pw> ./http_api.sh\nset -euo pipefail\n\nHOST=\"${CLICKHOUSE_HOST:-play.clickhouse.com}\"\nPORT=\"${CLICKHOUSE_PORT:-443}\"\nUSER_NAME=\"${CLICKHOUSE_USER:-play}\"\nPASSWORD=\"${CLICKHOUSE_PASSWORD:-}\"\n\nif [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n  URL=\"https://${HOST}:${PORT}/?user=${USER_NAME}\"\n  AUTH=()\nelse\n  URL=\"https://${HOST}:${PORT}/\"\n  AUTH=(-H \"X-ClickHouse-User: ${USER_NAME}\" -H \"X-ClickHouse-Key: ${PASSWORD}\")\nfi\n\nrun() { # run \"<label>\" \"<sql>\" [extra curl args...]\n  local label=\"$1\" sql=\"$2\"; shift 2\n  printf '\\n== %s\\n' \"$label\"\n  printf '%s\\n\\n' \"$sql\"\n  curl -sS --max-time 60 \"${AUTH[@]}\" \"$@\" \"$URL\" --data-binary \"$sql\"\n}\n\necho \"host: ${HOST}:${PORT}  user: ${USER_NAME}\"\n\nrun \"1. server version (plain text is the default format)\" \"SELECT version()\"\n\nrun \"2. JSONCompact output (?param_format=... or FORMAT clause)\" \\\n\"SELECT number AS n, number * number AS square\nFROM system.numbers\nLIMIT 5\nFORMAT JSONCompact\"\n\nrun \"3. aggregation over a hosted dataset (~37M rows)\" \\\n\"SELECT toYear(time) AS year, count() AS items, round(avg(score), 1) AS avg_score\nFROM default.hackernews\nWHERE time >= toDateTime('2019-01-01')\nGROUP BY year\nORDER BY year DESC\nLIMIT 6\nFORMAT PrettyCompactMonoBlock\"\n\nrun \"4. bind parameters via the query string (never interpolate user input)\" \\\n\"SELECT id, score, left(title, 50) AS title\nFROM default.hackernews\nWHERE type = 'story' AND score >= {min_score:Int32}\nORDER BY score DESC\nLIMIT 3\nFORMAT TSVWithNames\" \\\n  --get --data-urlencode 'query=SELECT id, score, left(title, 50) AS title\nFROM default.hackernews\nWHERE type = '\"'\"'story'\"'\"' AND score >= {min_score:Int32}\nORDER BY score DESC\nLIMIT 3\nFORMAT TSVWithNames' --data-urlencode 'param_min_score=4000'\n\nrun \"5. query metadata: how many rows/bytes the server actually read\" \\\n\"SELECT count() FROM default.hackernews\nSETTINGS send_progress_in_http_headers = 0\nFORMAT JSONCompact\"\n\nrun \"6. system tables = free observability (slow query log, parts, merges)\" \\\n\"SELECT query_duration_ms, read_rows, formatReadableSize(read_bytes) AS read, query\nFROM system.query_log\nWHERE type = 'QueryFinish' AND query NOT LIKE '%query_log%'\nORDER BY event_time DESC\nLIMIT 3\nFORMAT Vertical\" || true\n\nif [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n  printf '\\n== 7. writes are blocked on the public playground (expected)\\n'\n  curl -sS --max-time 30 \"$URL\" --data-binary \\\n    'CREATE TABLE default.nope_from_demo (x UInt8) ENGINE = Memory' || true\n  printf '\\n\\nUse your own ClickHouse Cloud instance for the write path.\\n'\nfi\n"
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-ba2256f633ce7e15",
  "tool_kind": "file_edit"
}

{
  "type": "tool_result",
  "seq": 54,
  "ts": "2026-11-08T02:10:15.588Z",
  "turn": 1,
  "output": {
    "content": [
      {
        "text": "Successfully wrote 2910 bytes to /sandbox/repo/clickhouse-demo/http_api.sh",
        "type": "text"
      }
    ]
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-ba2256f633ce7e15",
  "is_error": false,
  "tool_kind": "file_edit"
}

{
  "type": "tool_call",
  "seq": 71,
  "ts": "2026-11-08T02:11:09.813Z",
  "name": "write",
  "turn": 1,
  "input": {
    "path": "/sandbox/repo/clickhouse-demo/http_api.sh",
    "content": "#!/usr/bin/env bash\n# Zero-dependency ClickHouse demo: the raw HTTP interface with curl.\n#\n# ClickHouse speaks HTTP natively (8443/TLS or 8123/plain), so any language with\n# an HTTP client works; the official SDKs are convenience wrappers over this.\n#\n#   ./http_api.sh                     # public playground (read-only, no credentials)\n#   CLICKHOUSE_HOST=<host> \\\n#   CLICKHOUSE_USER=<user> \\\n#   CLICKHOUSE_PASSWORD=<pw> ./http_api.sh   # your own instance\nset -euo pipefail\n\nHOST=\"${CLICKHOUSE_HOST:-play.clickhouse.com}\"\nPORT=\"${CLICKHOUSE_PORT:-443}\"\nUSER_NAME=\"${CLICKHOUSE_USER:-play}\"\nPASSWORD=\"${CLICKHOUSE_PASSWORD:-}\"\n\nif [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n  URL=\"https://${HOST}:${PORT}/?user=${USER_NAME}\"\n  AUTH=()\nelse\n  URL=\"https://${HOST}:${PORT}/\"\n  AUTH=(-H \"X-ClickHouse-User: ${USER_NAME}\" -H \"X-ClickHouse-Key: ${PASSWORD}\")\nfi\n\npost() { # post \"<label>\" \"<sql>\"\n  printf '\\n== %s\\n\\n%s\\n\\n' \"$1\" \"$2\"\n  curl -sS --max-time 60 \"${AUTH[@]}\" \"$URL\" --data-binary \"$2\"\n}\n\nget() { # get \"<label>\" \"<sql>\" \"<param_name>=<value>\"\n  printf '\\n== %s\\n\\n%s\\n\\n' \"$1\" \"$2\"\n  curl -sS --max-time 60 \"${AUTH[@]}\" \"$URL\" --get \\\n    --data-urlencode \"query=$2\" --data-urlencode \"$3\"\n}\n\necho \"host: ${HOST}:${PORT}   user: ${USER_NAME}\"\n\npost \"1. server version (TabSeparated is the default output format)\" \\\n\"SELECT version()\"\n\npost \"2. ask for JSON with a FORMAT clause (JSONCompact, JSONEachRow, CSV, Parquet...)\" \\\n\"SELECT number AS n, number * number AS square\nFROM system.numbers\nLIMIT 5\nFORMAT JSONCompact\"\n\npost \"3. aggregation over a hosted dataset (~37M rows)\" \\\n\"SELECT toYear(time) AS year, count() AS items, round(avg(score), 1) AS avg_score\nFROM default.hackernews\nWHERE time >= toDateTime('2019-01-01')\nGROUP BY year\nORDER BY year DESC\nLIMIT 6\nFORMAT PrettyCompactMonoBlock\"\n\nget \"4. bind parameters on the query string (never interpolate user input into SQL)\" \\\n\"SELECT id, score, left(title, 50) AS title\nFROM default.hackernews\nWHERE type = 'story' AND score >= {min_score:Int32}\nORDER BY score DESC\nLIMIT 3\nFORMAT TSVWithNames\" \\\n\"param_min_score=4000\"\n\npost \"5. server-side query settings travel as query-string args / SETTINGS clause\" \\\n\"SELECT count() AS rows_read\nFROM default.hackernews\nSETTINGS max_threads = 2, max_memory_usage = 1000000000\nFORMAT JSONCompact\"\n\npost \"6. system tables are free observability (query_log, parts, merges, metrics)\" \\\n\"SELECT query_duration_ms, read_rows, formatReadableSize(read_bytes) AS read, left(query, 60) AS query\nFROM system.query_log\nWHERE type = 'QueryFinish' AND query NOT LIKE '%query_log%'\nORDER BY event_time DESC\nLIMIT 3\nFORMAT Vertical\"\n\nif [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n  printf '\\n== 7. writes are blocked on the public playground (expected: ACCESS_DENIED 497)\\n\\n'\n  curl -sS --max-time 30 \"$URL\" --data-binary \\\n    'CREATE TABLE default.nope_from_demo (x UInt8) ENGINE = Memory' || true\n  printf '\\n\\nPoint CLICKHOUSE_HOST at your own ClickHouse Cloud instance for the write path.\\n'\nfi\n"
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-a19a359a1eed146c",
  "tool_kind": "file_edit"
}

{
  "type": "tool_result",
  "seq": 73,
  "ts": "2026-11-08T02:11:09.813Z",
  "turn": 1,
  "output": {
    "content": [
      {
        "text": "Successfully wrote 2999 bytes to /sandbox/repo/clickhouse-demo/http_api.sh",
        "type": "text"
      }
    ]
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-a19a359a1eed146c",
  "is_error": false,
  "tool_kind": "file_edit"
}

{
  "type": "tool_call",
  "seq": 72,
  "ts": "2026-11-08T02:11:09.813Z",
  "name": "write",
  "turn": 1,
  "input": {
    "path": "/sandbox/repo/clickhouse-demo/requirements.txt",
    "content": "clickhouse-connect>=0.7.0\n"
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-9e7f67ebf0ebb453",
  "tool_kind": "file_edit"
}

{
  "type": "tool_result",
  "seq": 74,
  "ts": "2026-11-08T02:11:09.813Z",
  "turn": 1,
  "output": {
    "content": [
      {
        "text": "Successfully wrote 26 bytes to /sandbox/repo/clickhouse-demo/requirements.txt",
        "type": "text"
      }
    ]
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-9e7f67ebf0ebb453",
  "is_error": false,
  "tool_kind": "file_edit"
}

{
  "type": "tool_call",
  "seq": 85,
  "ts": "2026-11-08T02:11:44.546Z",
  "name": "edit",
  "turn": 1,
  "input": {
    "path": "/sandbox/repo/clickhouse-demo/http_api.sh",
    "edits": [
      {
        "newText": "post \"2. ask for JSON with a FORMAT clause (JSONCompact, JSONEachRow, CSV, Parquet...)\" \\\n\"SELECT arrayJoin([1, 2, 3, 4, 5]) AS n, n * n AS square\nFORMAT JSONCompact\"",
        "oldText": "post \"2. ask for JSON with a FORMAT clause (JSONCompact, JSONEachRow, CSV, Parquet...)\" \\\n\"SELECT number AS n, number * number AS square\nFROM system.numbers\nLIMIT 5\nFORMAT JSONCompact\""
      },
      {
        "newText": "printf '\\n== 5. output format can also be set as an HTTP query-string arg (default_format=CSV)\\n\\n'\ncurl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}&default_format=CSV\" --data-binary \\\n\"SELECT id, score, left(title, 40) AS title\nFROM default.hackernews\nWHERE score > 4000\nORDER BY score DESC\nLIMIT 3\"\n# On an instance you own (not readonly) you can also tune the server per query:\n#   ... FROM default.hackernews SETTINGS max_threads = 2, max_memory_usage = 1000000000\n\npost \"6. system tables = free observability (here: what is on this server)\" \\\n\"SELECT database, count() AS tables, formatReadableSize(sum(total_bytes)) AS on_disk,\n        sum(total_rows) AS rows\nFROM system.tables\nWHERE database NOT IN ('system', 'INFORMATION_SCHEMA', 'information_schema')\nGROUP BY database\nORDER BY sum(total_bytes) DESC\nLIMIT 5\nFORMAT PrettyCompactMonoBlock\"\n# On your own instance the interesting ones are system.query_log (slow queries),\n# system.parts (data layout), system.merges and system.metrics.",
        "oldText": "post \"5. server-side query settings travel as query-string args / SETTINGS clause\" \\\n\"SELECT count() AS rows_read\nFROM default.hackernews\nSETTINGS max_threads = 2, max_memory_usage = 1000000000\nFORMAT JSONCompact\"\n\npost \"6. system tables are free observability (query_log, parts, merges, metrics)\" \\\n\"SELECT query_duration_ms, read_rows, formatReadableSize(read_bytes) AS read, left(query, 60) AS query\nFROM system.query_log\nWHERE type = 'QueryFinish' AND query NOT LIKE '%query_log%'\nORDER BY event_time DESC\nLIMIT 3\nFORMAT Vertical\""
      }
    ]
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-a26047184dc10592",
  "tool_kind": "file_edit"
}

{
  "type": "tool_result",
  "seq": 86,
  "ts": "2026-11-08T02:11:44.546Z",
  "turn": 1,
  "output": {
    "content": [
      {
        "text": "Successfully replaced 2 block(s) in /sandbox/repo/clickhouse-demo/http_api.sh.",
        "type": "text"
      }
    ],
    "details": {
      "diff": "    ...\n 39 post \"1. server version (TabSeparated is the default output format)\" \\\n 40 \"SELECT version()\"\n 41 \n 42 post \"2. ask for JSON with a FORMAT clause (JSONCompact, JSONEachRow, CSV, Parquet...)\" \\\n-43 \"SELECT number AS n, number * number AS square\n-44 FROM system.numbers\n-45 LIMIT 5\n+43 \"SELECT arrayJoin([1, 2, 3, 4, 5]) AS n, n * n AS square\n 46 FORMAT JSONCompact\"\n 47 \n 48 post \"3. aggregation over a hosted dataset (~37M rows)\" \\\n 49 \"SELECT toYear(time) AS year, count() AS items, round(avg(score), 1) AS avg_score\n    ...\n 62 LIMIT 3\n 63 FORMAT TSVWithNames\" \\\n 64 \"param_min_score=4000\"\n 65 \n-66 post \"5. server-side query settings travel as query-string args / SETTINGS clause\" \\\n-67 \"SELECT count() AS rows_read\n+64 printf '\\n== 5. output format can also be set as an HTTP query-string arg (default_format=CSV)\\n\\n'\n+65 curl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}&default_format=CSV\" --data-binary \\\n+66 \"SELECT id, score, left(title, 40) AS title\n 68 FROM default.hackernews\n-69 SETTINGS max_threads = 2, max_memory_usage = 1000000000\n-70 FORMAT JSONCompact\"\n+68 WHERE score > 4000\n+69 ORDER BY score DESC\n+70 LIMIT 3\"\n+71 # On an instance you own (not readonly) you can also tune the server per query:\n+72 #   ... FROM default.hackernews SETTINGS max_threads = 2, max_memory_usage = 1000000000\n 71 \n-72 post \"6. system tables are free observability (query_log, parts, merges, metrics)\" \\\n-73 \"SELECT query_duration_ms, read_rows, formatReadableSize(read_bytes) AS read, left(query, 60) AS query\n-74 FROM system.query_log\n-75 WHERE type = 'QueryFinish' AND query NOT LIKE '%query_log%'\n-76 ORDER BY event_time DESC\n-77 LIMIT 3\n-78 FORMAT Vertical\"\n+74 post \"6. system tables = free observability (here: what is on this server)\" \\\n+75 \"SELECT database, count() AS tables, formatReadableSize(sum(total_bytes)) AS on_disk,\n+76         sum(total_rows) AS rows\n+77 FROM system.tables\n+78 WHERE database NOT IN ('system', 'INFORMATION_SCHEMA', 'information_schema')\n+79 GROUP BY database\n+80 ORDER BY sum(total_bytes) DESC\n+81 LIMIT 5\n+82 FORMAT PrettyCompactMonoBlock\"\n+83 # On your own instance the interesting ones are system.query_log (slow queries),\n+84 # system.parts (data layout), system.merges and system.metrics.\n 79 \n 80 if [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n 81   printf '\\n== 7. writes are blocked on the public playground (expected: ACCESS_DENIED 497)\\n\\n'\n 82   curl -sS --max-time 30 \"$URL\" --data-binary \\\n    ...",
      "patch": "--- /sandbox/repo/clickhouse-demo/http_api.sh\n+++ /sandbox/repo/clickhouse-demo/http_api.sh\n@@ -39,11 +39,9 @@\n post \"1. server version (TabSeparated is the default output format)\" \\\n \"SELECT version()\"\n \n post \"2. ask for JSON with a FORMAT clause (JSONCompact, JSONEachRow, CSV, Parquet...)\" \\\n-\"SELECT number AS n, number * number AS square\n-FROM system.numbers\n-LIMIT 5\n+\"SELECT arrayJoin([1, 2, 3, 4, 5]) AS n, n * n AS square\n FORMAT JSONCompact\"\n \n post \"3. aggregation over a hosted dataset (~37M rows)\" \\\n \"SELECT toYear(time) AS year, count() AS items, round(avg(score), 1) AS avg_score\n@@ -62,21 +60,29 @@\n LIMIT 3\n FORMAT TSVWithNames\" \\\n \"param_min_score=4000\"\n \n-post \"5. server-side query settings travel as query-string args / SETTINGS clause\" \\\n-\"SELECT count() AS rows_read\n+printf '\\n== 5. output format can also be set as an HTTP query-string arg (default_format=CSV)\\n\\n'\n+curl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}&default_format=CSV\" --data-binary \\\n+\"SELECT id, score, left(title, 40) AS title\n FROM default.hackernews\n-SETTINGS max_threads = 2, max_memory_usage = 1000000000\n-FORMAT JSONCompact\"\n+WHERE score > 4000\n+ORDER BY score DESC\n+LIMIT 3\"\n+# On an instance you own (not readonly) you can also tune the server per query:\n+#   ... FROM default.hackernews SETTINGS max_threads = 2, max_memory_usage = 1000000000\n \n-post \"6. system tables are free observability (query_log, parts, merges, metrics)\" \\\n-\"SELECT query_duration_ms, read_rows, formatReadableSize(read_bytes) AS read, left(query, 60) AS query\n-FROM system.query_log\n-WHERE type = 'QueryFinish' AND query NOT LIKE '%query_log%'\n-ORDER BY event_time DESC\n-LIMIT 3\n-FORMAT Vertical\"\n+post \"6. system tables = free observability (here: what is on this server)\" \\\n+\"SELECT database, count() AS tables, formatReadableSize(sum(total_bytes)) AS on_disk,\n+        sum(total_rows) AS rows\n+FROM system.tables\n+WHERE database NOT IN ('system', 'INFORMATION_SCHEMA', 'information_schema')\n+GROUP BY database\n+ORDER BY sum(total_bytes) DESC\n+LIMIT 5\n+FORMAT PrettyCompactMonoBlock\"\n+# On your own instance the interesting ones are system.query_log (slow queries),\n+# system.parts (data layout), system.merges and system.metrics.\n \n if [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n   printf '\\n== 7. writes are blocked on the public playground (expected: ACCESS_DENIED 497)\\n\\n'\n   curl -sS --max-time 30 \"$URL\" --data-binary \\\n",
      "firstChangedLine": 43
    }
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-a26047184dc10592",
  "is_error": false,
  "tool_kind": "file_edit"
}

{
  "type": "tool_call",
  "seq": 89,
  "ts": "2026-11-08T02:11:49.629Z",
  "name": "edit",
  "turn": 1,
  "input": {
    "path": "/sandbox/repo/clickhouse-demo/http_api.sh",
    "edits": [
      {
        "newText": "if [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n  URL=\"https://${HOST}:${PORT}/?user=${USER_NAME}\"\n  AUTH=()\n  SEP=\"&\"   # URL already carries a query string\nelse\n  URL=\"https://${HOST}:${PORT}/\"\n  AUTH=(-H \"X-ClickHouse-User: ${USER_NAME}\" -H \"X-ClickHouse-Key: ${PASSWORD}\")\n  SEP=\"?\"\nfi",
        "oldText": "if [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n  URL=\"https://${HOST}:${PORT}/?user=${USER_NAME}\"\n  AUTH=()\nelse\n  URL=\"https://${HOST}:${PORT}/\"\n  AUTH=(-H \"X-ClickHouse-User: ${USER_NAME}\" -H \"X-ClickHouse-Key: ${PASSWORD}\")\nfi"
      },
      {
        "newText": "curl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}${SEP}default_format=CSV\" --data-binary \\",
        "oldText": "curl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}&default_format=CSV\" --data-binary \\"
      }
    ]
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-b905ae1fd1c0a06b",
  "tool_kind": "file_edit"
}

{
  "type": "tool_result",
  "seq": 90,
  "ts": "2026-11-08T02:11:49.629Z",
  "turn": 1,
  "output": {
    "content": [
      {
        "text": "Successfully replaced 2 block(s) in /sandbox/repo/clickhouse-demo/http_api.sh.",
        "type": "text"
      }
    ],
    "details": {
      "diff": "    ...\n 17 \n 18 if [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n 19   URL=\"https://${HOST}:${PORT}/?user=${USER_NAME}\"\n 20   AUTH=()\n+21   SEP=\"&\"   # URL already carries a query string\n 21 else\n 22   URL=\"https://${HOST}:${PORT}/\"\n 23   AUTH=(-H \"X-ClickHouse-User: ${USER_NAME}\" -H \"X-ClickHouse-Key: ${PASSWORD}\")\n+25   SEP=\"?\"\n 24 fi\n 25 \n 26 post() { # post \"<label>\" \"<sql>\"\n 27   printf '\\n== %s\\n\\n%s\\n\\n' \"$1\" \"$2\"\n    ...\n 61 FORMAT TSVWithNames\" \\\n 62 \"param_min_score=4000\"\n 63 \n 64 printf '\\n== 5. output format can also be set as an HTTP query-string arg (default_format=CSV)\\n\\n'\n-65 curl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}&default_format=CSV\" --data-binary \\\n+67 curl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}${SEP}default_format=CSV\" --data-binary \\\n 66 \"SELECT id, score, left(title, 40) AS title\n 67 FROM default.hackernews\n 68 WHERE score > 4000\n 69 ORDER BY score DESC\n    ...",
      "patch": "--- /sandbox/repo/clickhouse-demo/http_api.sh\n+++ /sandbox/repo/clickhouse-demo/http_api.sh\n@@ -17,11 +17,13 @@\n \n if [[ \"$HOST\" == \"play.clickhouse.com\" ]]; then\n   URL=\"https://${HOST}:${PORT}/?user=${USER_NAME}\"\n   AUTH=()\n+  SEP=\"&\"   # URL already carries a query string\n else\n   URL=\"https://${HOST}:${PORT}/\"\n   AUTH=(-H \"X-ClickHouse-User: ${USER_NAME}\" -H \"X-ClickHouse-Key: ${PASSWORD}\")\n+  SEP=\"?\"\n fi\n \n post() { # post \"<label>\" \"<sql>\"\n   printf '\\n== %s\\n\\n%s\\n\\n' \"$1\" \"$2\"\n@@ -61,9 +63,9 @@\n FORMAT TSVWithNames\" \\\n \"param_min_score=4000\"\n \n printf '\\n== 5. output format can also be set as an HTTP query-string arg (default_format=CSV)\\n\\n'\n-curl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}&default_format=CSV\" --data-binary \\\n+curl -sS --max-time 60 \"${AUTH[@]}\" \"${URL}${SEP}default_format=CSV\" --data-binary \\\n \"SELECT id, score, left(title, 40) AS title\n FROM default.hackernews\n WHERE score > 4000\n ORDER BY score DESC\n",
      "firstChangedLine": 21
    }
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-b905ae1fd1c0a06b",
  "is_error": false,
  "tool_kind": "file_edit"
}

{
  "type": "tool_call",
  "seq": 93,
  "ts": "2026-11-08T02:11:56.401Z",
  "name": "edit",
  "turn": 1,
  "input": {
    "path": "/sandbox/repo/clickhouse-demo/example.py",
    "edits": [
      {
        "newText": "    # The server reports what each query actually cost - the single most useful\n    # thing for learning ClickHouse, because cost is driven by rows/bytes read.\n    summary = result.summary or {}\n    read_rows = str(summary.get(\"read_rows\", \"\"))\n    read_bytes = str(summary.get(\"read_bytes\", \"\"))\n    footer = f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms\"\n    if read_rows.isdigit() and read_bytes.isdigit():\n        footer += f\" | server scanned {int(read_rows):,} rows / {int(read_bytes) / 1e6:.1f} MB\"\n    print(footer)",
        "oldText": "    summary = result.summary or {}\n    read_rows = summary.get(\"read_rows\", \"n/a\")\n    read_bytes = summary.get(\"read_bytes\", \"n/a\")\n    print(\n        f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms | \"\n        f\"server scanned {read_rows} rows / {int(read_bytes) / 1e6:.1f} MB\"\n        if str(read_bytes).isdigit()\n        else f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms\"\n    )"
      }
    ]
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-abbfd1fc7b19a7bf",
  "tool_kind": "file_edit"
}

{
  "type": "tool_result",
  "seq": 94,
  "ts": "2026-11-08T02:11:56.401Z",
  "turn": 1,
  "output": {
    "content": [
      {
        "text": "Successfully replaced 1 block(s) in /sandbox/repo/clickhouse-demo/example.py.",
        "type": "text"
      }
    ],
    "details": {
      "diff": "     ...\n 118     print(\"-+-\".join(\"-\" * w for w in widths))\n 119     for row in rows:\n 120         print(fmt(row))\n 121 \n+122     # The server reports what each query actually cost - the single most useful\n+123     # thing for learning ClickHouse, because cost is driven by rows/bytes read.\n 122     summary = result.summary or {}\n-123     read_rows = summary.get(\"read_rows\", \"n/a\")\n-124     read_bytes = summary.get(\"read_bytes\", \"n/a\")\n-125     print(\n-126         f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms | \"\n-127         f\"server scanned {read_rows} rows / {int(read_bytes) / 1e6:.1f} MB\"\n-128         if str(read_bytes).isdigit()\n-129         else f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms\"\n-130     )\n+125     read_rows = str(summary.get(\"read_rows\", \"\"))\n+126     read_bytes = str(summary.get(\"read_bytes\", \"\"))\n+127     footer = f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms\"\n+128     if read_rows.isdigit() and read_bytes.isdigit():\n+129         footer += f\" | server scanned {int(read_rows):,} rows / {int(read_bytes) / 1e6:.1f} MB\"\n+130     print(footer)\n 131 \n 132 \n 133 def table_exists(client, database: str, table: str) -> bool:\n 134     res = client.query(\n     ...",
      "patch": "--- /sandbox/repo/clickhouse-demo/example.py\n+++ /sandbox/repo/clickhouse-demo/example.py\n@@ -118,17 +118,17 @@\n     print(\"-+-\".join(\"-\" * w for w in widths))\n     for row in rows:\n         print(fmt(row))\n \n+    # The server reports what each query actually cost - the single most useful\n+    # thing for learning ClickHouse, because cost is driven by rows/bytes read.\n     summary = result.summary or {}\n-    read_rows = summary.get(\"read_rows\", \"n/a\")\n-    read_bytes = summary.get(\"read_bytes\", \"n/a\")\n-    print(\n-        f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms | \"\n-        f\"server scanned {read_rows} rows / {int(read_bytes) / 1e6:.1f} MB\"\n-        if str(read_bytes).isdigit()\n-        else f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms\"\n-    )\n+    read_rows = str(summary.get(\"read_rows\", \"\"))\n+    read_bytes = str(summary.get(\"read_bytes\", \"\"))\n+    footer = f\"\\n{len(rows)} rows | wall {wall_ms:.0f} ms\"\n+    if read_rows.isdigit() and read_bytes.isdigit():\n+        footer += f\" | server scanned {int(read_rows):,} rows / {int(read_bytes) / 1e6:.1f} MB\"\n+    print(footer)\n \n \n def table_exists(client, database: str, table: str) -> bool:\n     res = client.query(\n",
      "firstChangedLine": 122
    }
  },
  "run_id": "cmw76z9wv05ih0iu2ppf8kcmo",
  "tool_id": "chatcmpl-tool-abbfd1fc7b19a7bf",
  "is_error": false,
  "tool_kind": "file_edit"
}

{
  "type": "tool_call",
  "seq": 97,
  "ts": "2026-11-08T02:12:14.564Z",
  "name": "write",
  "turn": 1,
  "input": {
    "path": "/sandbox/repo/clickhouse-demo/README.md",
    "content": "# ClickHouse demo — hosted only, no local server\n\nA minimal, runnable ClickHouse example that talks to a **hosted** ClickHouse over\nHTTPS. Nothing is installed or started locally except a Python package.\n\n```\nclickhouse-demo/\n├── example.py        # official Python SDK (clickhouse-connect): analytics + write lifecycle\n├── http_api.sh       # the same ideas over the raw HTTP interface with curl (zero deps)\n├── requirements.txt  # clickhouse-connect\n└── README.md\n```\n\n## Run it\n\n```bash\npip install -r requirements.txt     # only clickhouse-connect (+ pandas if you want query_df)\n\npython3 example.py                  # default: public playground, no credentials\n./http_api.sh                       # same, with curl\n```\n\nDefault target is ClickHouse's own hosted playground, `play.clickhouse.com`\n(user `play`, no password, free). It carries real datasets — ~37M Hacker News\nrows, ~43M cell towers, ClickBench, NOAA — so the analytics are genuine\nmulti-million-row aggregations that return in ~100 ms.\n\n### Against your own instance (ClickHouse Cloud, or any reachable server)\n\n```bash\nCLICKHOUSE_HOST=<your>.<region>.aws.clickhouse.cloud \\\nCLICKHOUSE_USER=default \\\nCLICKHOUSE_PASSWORD=<password> \\\npython3 example.py\n```\n\nSelf-hosted plain HTTP: `CLICKHOUSE_SECURE=false CLICKHOUSE_PORT=8123`.\n\n## What it shows\n\n**Read path** (`example.py` Part 1, runs anywhere the datasets exist):\n\n| # | Idea | Query shape |\n|---|------|-------------|\n| 1a | Columnar aggregation | `GROUP BY` + `avg`/`max` over 37M rows |\n| 1b | Time bucketing + quantiles | `toYear(time)`, `countIf`, `quantile(0.95)` |\n| 1c | `Enum8` columns | second dataset, 43M rows |\n| 1d | Bind parameters | `{min_score:Int32}` — values sent separately from SQL |\n| 1e | pandas integration | `client.query_df()` returns a typed DataFrame |\n\nEach result prints what the server reported it cost (`read_rows`, `read_bytes`),\nwhich is the thing to watch in ClickHouse: cost tracks bytes read, not rows\nreturned. Example footer from a real run:\n\n```\n8 rows | wall 140 ms | server scanned 37,171,166 rows / 435.4 MB\n```\n\n**Write path** (`example.py` Part 2, needs DDL rights):\n`CREATE DATABASE` → `CREATE TABLE` (MergeTree, monthly partitions, `ORDER BY`\nprimary key, `TTL`) → `client.insert()` of 5,000 generated rows (native columnar\ninsert, no SQL text) → aggregations → `ARRAY JOIN` → `Map` column access →\n`system.tables` compression stats → `DROP TABLE` cleanup.\n\n**HTTP API** (`http_api.sh`): output formats via `FORMAT` clause and the\n`default_format` URL arg, query-string bind parameters (`param_min_score=...`),\nauth headers (`X-ClickHouse-User` / `X-ClickHouse-Key`), `system` tables.\n\n## Pricing\n\nVerified against `clickhouse.com/pricing` (N. Virginia / us-east-1) in Nov 2026.\n\n* **Open-source ClickHouse: free, forever** (Apache-2.0). Self-host and the only\n  cost is your hardware/ops. This demo's read path costs **$0** — the playground\n  is free.\n* **ClickHouse Cloud (the hosted product): pure consumption pricing.** Compute and\n  storage are metered separately, and **compute scales to zero when idle**, so an\n  idle dev instance bills storage only.\n  * One **compute unit = 2 vCPUs + 8 GiB RAM**, metered per minute, billed per\n    compute-unit-hour:\n    | Plan | Compute | Storage | Notes |\n    |------|---------|---------|-------|\n    | Basic | **$0.2181**/unit/hr | $25.30 per 1 TB/mo | up to 1 TB storage, 8–12 GiB total memory, single replica |\n    | Scale | **$0.2985**/unit/hr | $25.30 per 1 TB/mo | 2+ AZs, unlimited storage, autoscaling, private networking |\n    | Enterprise | **$0.3903**/unit/hr | $25.30 per 1 TB/mo | CMEK, compliance, scheduled upgrades |\n  * Storage is $25.30 per TB-month ≈ **$0.0247/GB-month** (~$2.53 for 100 GB),\n    after ClickHouse's typical 5–10x compression.\n  * Egress: public internet from **$0.1152/GB**, inter-region from **$0.0312/GB**.\n    Ingest from ClickPipes is priced per connector type.\n  * Trial: every new organisation gets **$300 of credits over 30 days**, no card\n    charged until credits are gone. Change plan later without migration.\n  * Rough maths: one always-on Basic compute unit ≈ 0.2181 × 730 h ≈ **$159/mo**\n    compute + storage. A hobby project that idles most of the day costs a few\n    dollars; ClickHouse's own guidance is ~1:25 memory-to-storage for real-time\n    analytics, so size memory first.\n\n## Verified vs. not\n\n* **Ran green:** the whole read path of `example.py` and `http_api.sh` against\n  `play.clickhouse.com` (ClickHouse 26.10.3.7).\n* **Not executed:** Part 2 (write lifecycle). The playground is hard read-only —\n  `CREATE DATABASE`, `CREATE TABLE` and even `CREATE TEMPORARY TABLE` all return\n  `ACCESS_DENIED (code 497)` for user `play`, and no ClickHouse Cloud credentials\n  were available in this environment. Every Part-2 statement was therefore\n  validated against the live server's parser with `EXPLAIN AST` / `EXPLAIN\n  SYNTAX` (all OK), and the insert payload was dry-run for column/type shape, but\n  it has not been executed end-to-end. Point the script at a real instance (the\n  $300 trial is enough) to run it.\n* Also blocked on the playground: `system.numbers`, `system.query_log`,\n  `system.parts`, and changing settings such as `max_threads` (readonly mode).\n  `http_api.sh` sticks to what the playground allows and notes the alternatives.\n\n## Notes for extending it\n\n* One client object = one connection pool; create it once and reuse it.\n* Use bind parameters (`{name:Type}` + `parameters=`), never f-strings, for values.\n* Batch inserts (thousands of rows per `insert()`); ClickHouse hates many tiny\n  inserts — they create parts and force merges.\n* `ORDER BY` is the primary key/skip index: put your most selective filter\n  columns first. `PARTITION BY` should be coarse (month), never high-cardinality.\n* `LowCardinality(String)` for enums-ish columns, `Array`/`Map`/`Nested` instead\n  of join tables — ClickHouse prefers denormalised wide tables.\n"
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