feat(grafana): show proved active app work
This commit is contained in:
igor04091968
@@ -60,6 +60,7 @@ def build_lines_for_day(host, report_date):
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rows = WORKTIME.aggregate_rows(events, bounds["start"], bounds["end"], host)
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hourly_rows = WORKTIME.aggregate_hourly_rows(events, bounds["start"], bounds["end"], host)
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summary = WORKTIME.build_report_summary(rows)
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true_active_apps = WORKTIME.build_true_active_apps(host, report_date)
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lines = []
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daily_ts = _timestamp_ns(bounds["start"])
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@@ -118,6 +119,28 @@ def build_lines_for_day(host, report_date):
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daily_ts,
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)
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)
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for app in true_active_apps:
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lines.append(
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_line(
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"aw_true_active_app_daily",
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{
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"host": host,
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"application": app["application"],
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"report_date": report_date.isoformat(),
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},
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{
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"proved_work_seconds": int(app.get("proved_work_seconds", 0) or 0),
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"evidence_events": int(app.get("evidence_events", 0) or 0),
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"proved_work_human": app.get("proved_work_human", ""),
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"proved_work_hhmm": app.get("proved_work_hhmm", ""),
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"last_action": app.get("last_action", ""),
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"last_action_local": app.get("last_action_local", ""),
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"last_action_utc": app.get("last_action_utc", ""),
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},
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daily_ts,
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)
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)
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return [line for line in lines if line]
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@@ -28,8 +28,40 @@ def test_build_lines_for_day_emits_daily_hourly_and_summary(monkeypatch):
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]
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monkeypatch.setattr(MODULE.WORKTIME, "fetch_events_for_date", lambda host, report_date: (bounds, events))
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monkeypatch.setattr(MODULE.WORKTIME, "build_true_active_apps", lambda host, report_date: [])
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lines = MODULE.build_lines_for_day("SHARKON2025", date(2026, 5, 14))
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assert any(line.startswith("aw_rdp_worktime_daily,") for line in lines)
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assert any(line.startswith("aw_rdp_worktime_hourly,") for line in lines)
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assert any(line.startswith("aw_rdp_worktime_summary_daily,") for line in lines)
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def test_build_lines_for_day_emits_true_active_app_daily(monkeypatch):
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bounds = MODULE.WORKTIME.get_report_bounds(date(2026, 5, 14))
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monkeypatch.setattr(MODULE.WORKTIME, "fetch_events_for_date", lambda host, report_date: (bounds, []))
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monkeypatch.setattr(
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MODULE.WORKTIME,
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"build_true_active_apps",
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lambda host, report_date: [
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{
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"application": "1С",
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"proved_work_seconds": 2040,
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"proved_work_human": "34 мин",
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"proved_work_hhmm": "00:34",
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"last_action": "1С:Предприятие",
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"last_action_local": "09:42",
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"last_action_utc": "2026-05-14T06:42:00Z",
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"evidence_events": 7,
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}
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],
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)
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lines = MODULE.build_lines_for_day("SHARKON2025", date(2026, 5, 14))
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true_active_line = next(line for line in lines if line.startswith("aw_true_active_app_daily,"))
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assert "application=1С" in true_active_line
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assert "report_date=2026-05-14" in true_active_line
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assert "proved_work_seconds=2040i" in true_active_line
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assert "evidence_events=7i" in true_active_line
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assert 'last_action="1С:Предприятие"' in true_active_line
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@@ -196,7 +196,7 @@
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},
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"targets": [
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{
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"query": "from(bucket: \"aw_metrics\")\n |> range(start: -14d)\n |> filter(fn: (r) => r._measurement == \"aw_rdp_worktime_summary_daily\" and (r._field == \"users_count\" or r._field == \"total_active_seconds\") and r.host == \"${host}\")\n |> group(columns:[\"report_date\",\"_field\"])\n |> last()\n |> group()\n |> pivot(rowKey:[\"report_date\"], columnKey:[\"_field\"], valueColumn:\"_value\")\n |> sort(columns:[\"report_date\"])\n |> tail(n:2)\n |> limit(n:1)\n |> map(fn:(r) => ({ r with _value: float(v: r.total_active_seconds) / float(v: r.users_count) / 3600.0 }))",
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"query": "from(bucket: \"aw_metrics\")\n |> range(start: -14d)\n |> filter(fn: (r) => r._measurement == \"aw_rdp_worktime_summary_daily\" and (r._field == \"users_count\" or r._field == \"total_active_seconds\") and r.host == \"${host}\")\n |> group(columns:[\"report_date\",\"_field\"])\n |> last()\n |> group()\n |> pivot(rowKey:[\"report_date\"], columnKey:[\"_field\"], valueColumn:\"_value\")\n |> sort(columns:[\"report_date\"])\n |> tail(n:2)\n |> limit(n:1)\n |> map(fn:(r) => ({ r with _value: float(v: r.total_active_seconds) / float(v: r.users_count) / 3600.0 }))\n |> keep(columns:[\"_value\"])",
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"refId": "A"
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}
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],
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@@ -497,6 +497,206 @@
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],
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"title": "Подробно: последние 7 дней по сотрудникам",
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"type": "table"
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},
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{
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"datasource": {
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"type": "influxdb",
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"uid": "influxdb_aw"
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},
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"description": "Строгий показатель: время засчитывается только когда есть foreground window, not-AFK и дополнительное evidence-событие действия пользователя.",
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"fieldConfig": {
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"defaults": {
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"color": {
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"mode": "thresholds"
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},
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"decimals": 2,
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"thresholds": {
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"mode": "absolute",
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"steps": [
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{
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"color": "green"
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}
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]
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},
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"unit": "h"
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},
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"overrides": []
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},
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"gridPos": {
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"h": 4,
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"w": 8,
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"x": 0,
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"y": 33
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},
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"id": 11,
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"options": {
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"colorMode": "value",
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"graphMode": "none",
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"justifyMode": "center",
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"orientation": "auto",
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"reduceOptions": {
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"calcs": [
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"lastNotNull"
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],
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"fields": "",
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"values": false
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},
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"textMode": "auto"
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},
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"targets": [
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{
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"query": "import \"date\"\nimport \"strings\"\nimport \"timezone\"\noption location = timezone.location(name: \"Europe/Moscow\")\ntoday = strings.substring(v: string(v: date.add(d: 3h, to: date.truncate(t: now(), unit: 1d))), start: 0, end: 10)\nfrom(bucket: \"aw_metrics\")\n |> range(start: -3d)\n |> filter(fn: (r) => r._measurement == \"aw_true_active_app_daily\" and r._field == \"proved_work_seconds\" and r.host == \"${host}\" and r.report_date == today)\n |> group(columns:[\"application\"])\n |> last()\n |> group()\n |> sum()\n |> map(fn:(r)=>({ r with _value: float(v:r._value) / 3600.0 }))",
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"refId": "A"
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}
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],
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"title": "Сегодня: доказанная работа по приложениям",
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"type": "stat"
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},
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{
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"datasource": {
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"type": "influxdb",
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"uid": "influxdb_aw"
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},
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"description": "Приложения, где работа доказана связкой: активная RDP-сессия, не AFK, foreground окно и evidence-событие.",
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"fieldConfig": {
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"defaults": {
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"custom": {
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"align": "auto",
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"cellOptions": {
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"type": "auto"
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},
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"inspect": false
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}
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},
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"overrides": [
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{
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"matcher": {
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"id": "byName",
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"options": "Часы"
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},
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"properties": [
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{
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"id": "unit",
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"value": "h"
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},
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{
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"id": "decimals",
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"value": 2
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}
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]
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},
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{
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"matcher": {
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"id": "byName",
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"options": "Evidence"
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},
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"properties": [
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{
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"id": "decimals",
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"value": 0
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}
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]
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}
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]
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},
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"gridPos": {
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"h": 9,
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"w": 16,
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"x": 8,
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"y": 33
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},
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"id": 12,
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"options": {
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"cellHeight": "sm",
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"footer": {
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"countRows": false,
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"fields": "",
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"reducer": [
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"sum"
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],
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"show": false
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},
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"showHeader": true
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},
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"targets": [
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{
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"query": "import \"date\"\nimport \"strings\"\nimport \"timezone\"\noption location = timezone.location(name: \"Europe/Moscow\")\ntoday = strings.substring(v: string(v: date.add(d: 3h, to: date.truncate(t: now(), unit: 1d))), start: 0, end: 10)\nbase = from(bucket: \"aw_metrics\")\n |> range(start: -3d)\n |> filter(fn: (r) => r._measurement == \"aw_true_active_app_daily\" and r.host == \"${host}\" and r.report_date == today)\n\nnums = base\n |> filter(fn: (r) => r._field == \"proved_work_seconds\" or r._field == \"evidence_events\")\n |> group(columns:[\"application\",\"_field\"])\n |> last()\n |> group()\n |> pivot(rowKey:[\"application\",\"report_date\"], columnKey:[\"_field\"], valueColumn:\"_value\")\n\ntexts = base\n |> filter(fn: (r) => r._field == \"last_action\" or r._field == \"last_action_local\")\n |> group(columns:[\"application\",\"_field\"])\n |> last()\n |> group()\n |> pivot(rowKey:[\"application\",\"report_date\"], columnKey:[\"_field\"], valueColumn:\"_value\")\n\njoin(tables: {n: nums, t: texts}, on: [\"application\", \"report_date\"])\n |> map(fn:(r)=>({ r with hours: float(v:r.proved_work_seconds) / 3600.0 }))\n |> sort(columns:[\"proved_work_seconds\"], desc:true)\n |> keep(columns:[\"report_date\",\"application\",\"hours\",\"last_action_local\",\"last_action\",\"evidence_events\"])\n |> rename(columns:{report_date:\"Дата\", application:\"Приложение\", hours:\"Часы\", last_action_local:\"Последнее действие\", last_action:\"Контекст\", evidence_events:\"Evidence\"})",
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"refId": "A"
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}
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],
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"title": "Сегодня: доказанная работа по приложениям - детали",
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"type": "table"
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},
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{
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"datasource": {
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"type": "influxdb",
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"uid": "influxdb_aw"
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},
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"description": "История доказанной работы по приложениям. Нули означают, что foreground/AFK есть, но нет достаточного evidence действия.",
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"fieldConfig": {
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"defaults": {
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"custom": {
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"drawStyle": "bars",
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"lineInterpolation": "linear",
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"barAlignment": 0,
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"lineWidth": 1,
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"fillOpacity": 35,
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"gradientMode": "none",
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"spanNulls": false,
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"insertNulls": false,
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"showPoints": "never",
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"pointSize": 5,
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"stacking": {
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"mode": "normal",
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"group": "A"
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},
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"axisPlacement": "auto",
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"axisLabel": "",
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"axisColorMode": "text",
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"axisBorderShow": false,
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"scaleDistribution": {
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"type": "linear"
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},
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"hideFrom": {
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"tooltip": false,
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"viz": false,
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"legend": false
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},
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"thresholdsStyle": {
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"mode": "off"
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}
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},
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"unit": "h"
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},
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"overrides": []
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},
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"gridPos": {
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"h": 8,
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"w": 24,
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"x": 0,
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"y": 42
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},
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"id": 13,
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"options": {
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"legend": {
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"calcs": [],
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"displayMode": "list",
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"placement": "bottom",
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"showLegend": true
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},
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"tooltip": {
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"mode": "multi",
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"sort": "desc"
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}
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},
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"targets": [
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{
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"query": "from(bucket: \"aw_metrics\")\n |> range(start: -14d)\n |> filter(fn: (r) => r._measurement == \"aw_true_active_app_daily\" and r._field == \"proved_work_seconds\" and r.host == \"${host}\")\n |> group(columns:[\"application\",\"report_date\"])\n |> last()\n |> map(fn:(r)=>({ r with _value: float(v:r._value) / 3600.0 }))\n |> group(columns:[\"application\"])",
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"refId": "A"
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}
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],
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"title": "Доказанная работа по дням и приложениям",
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"type": "timeseries"
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}
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],
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"refresh": "10m",
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