{ "cells": [ { "cell_type": "code", "execution_count": null, "id": "9d16b24a", "metadata": {}, "outputs": [], "source": [ "from datetime import timedelta\n", "from typing import Any\n", "from temporalio import client\n", "from temporalio.client import WorkflowHandle\n", "\n", "\n", "async def start_workflow_advanced(\n", " temporal_client: client.Client,\n", " workflow_name: str,\n", " workflow_input: dict[str, Any],\n", " workflow_id: str,\n", " task_queue: str,\n", " execution_timeout: timedelta | None = None,\n", " run_timeout: timedelta | None = None,\n", " task_timeout: timedelta | None = None,\n", ") -> WorkflowHandle:\n", " handle = await temporal_client.start_workflow(\n", " workflow=workflow_name,\n", " arg=workflow_input,\n", " id=workflow_id or f\"{workflow_name}-{id(workflow_input)}\",\n", " task_queue=task_queue,\n", " execution_timeout=execution_timeout,\n", " run_timeout=run_timeout,\n", " task_timeout=task_timeout,\n", " )\n", " \n", " return handle" ] }, { "cell_type": "code", "execution_count": null, "id": "5e344fb0", "metadata": {}, "outputs": [], "source": [ "input_data = {\n", " \"debug_data_package\": False,\n", " \"execution_timeout_seconds\": 300,\n", " \"fill_missing_tags\": False,\n", " \"filters\": {\n", " \"NULL_VALUES_FILTER\": {\n", " \"policy\": \"DISCARD\"\n", " },\n", " \"OUT_OF_BOUNDS_FILTER\": {\n", " \"policy\": \"DISCARD\"\n", " }\n", " },\n", " \"frequency\": \"30s\",\n", " \"max_retry_policy\": 1,\n", " \"model_config\": {\n", " \"predict_flavor\": \"sklearn\",\n", " \"retention_minutes\": 0,\n", " \"target\": \"CI-W3A05F1\",\n", " \"transform_flavor\": \"sklearn\"\n", " },\n", " \"model_id\": \"10\",\n", " \"model_name\": \"Pi Web API Test Model\",\n", " \"model_tags\": {\n", " \"CI-W3W03S1\": {\n", " \"aggr_func\": \"avg\",\n", " \"data_range\": [\n", " -100000,\n", " 100000\n", " ],\n", " \"webid\": \"F1DP-7fYgsRTtUOa7V9NIwSujATFUAAAUElIQVZDXENJLVczVzAzUzE\"\n", " },\n", " \"CI-W3A05F1\": {\n", " \"aggr_func\": \"lts\",\n", " \"data_range\": [\n", " -100000,\n", " 100000\n", " ],\n", " \"webid\": \"F1DP-7fYgsRTtUOa7V9NIwSujAkVMAAAUElIQVZDXENJLVczQTA1RjE\"\n", " }\n", " },\n", " \"pi_web_api_query\": {\n", " \"endpoint\": \"/streamsets/recorded\",\n", " \"period\": \"*-1d\",\n", " \"max_count\": 1,\n", " \"api_timeout\": 5\n", " },\n", " \"offset\": \"0m\",\n", " \"retention_time\": 3600,\n", " \"schedule_name\": \"pi-web-api-scouter-test\",\n", " \"schema\": \"sientia_data\",\n", " \"table_name\": \"laborious_data\",\n", " \"task_timeout_seconds\": 300,\n", " \"trigger_laborious\": False,\n", " \"updated_at\": \"2025-08-13 18:35:01.600000+0000\",\n", " \"workflow_type\": \"pi_web_api_scouter\"\n", "}" ] }, { "cell_type": "code", "execution_count": null, "id": "9350bff3", "metadata": {}, "outputs": [], "source": [ "from temporalio import client\n", "\n", "temporal_client = await client.Client.connect(\n", " target_host=\"localhost:7233\",\n", " namespace=\"scouter\"\n", ")\n" ] }, { "cell_type": "code", "execution_count": null, "id": "45712d7a", "metadata": {}, "outputs": [], "source": [ "\n", "import datetime\n", "\n", "now = datetime.datetime.now()\n", "\n", "handle = await start_workflow_advanced(\n", " temporal_client=temporal_client,\n", " workflow_name='pi_web_api_scouter',\n", " workflow_input=input_data,\n", " workflow_id='test_workflow_id_' + now.strftime('%Y%m%d%H%M%S'),\n", " task_queue='pi-web-api-scouter-queue',\n", " execution_timeout=timedelta(seconds=30),\n", " run_timeout=timedelta(seconds=30),\n", " task_timeout=timedelta(seconds=30),\n", ")\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "d065d0de", "metadata": {}, "outputs": [], "source": [ "import re\n", "def camel_to_kebab(text: str) -> str:\n", " \"\"\"Convert camelCase or PascalCase to kebab-case.\"\"\"\n", " text = re.sub('(.)([A-Z][a-z]+)', r'\\1-\\2', text)\n", " text = re.sub('([a-z0-9])([A-Z])', r'\\1-\\2', text)\n", " return text.lower()\n", "\n", "print(camel_to_kebab('PiWebApiScouter'))\n" ] }, { "cell_type": "code", "execution_count": null, "id": "72af4236", "metadata": {}, "outputs": [], "source": [ "import requests\n", "from time import sleep\n", "\n", "# Obter web id das seguintes tags:\n", "TAG_NAMES = [\n", " \"CI-W3A05F1\",\n", " \"CI-W3W03S1\",\n", " \"CI-W3W03I1\",\n", " \"CI-W3K01T1\",\n", " \"CI-W3W01A3\",\n", " \"CI-W3W01A2\",\n", " \"CI-W3W01A1\",\n", " \"CI-J3P01T1A\",\n", " \"CI-W3A50T1\",\n", " \"CI-W3A55T1\",\n", " \"CI-W3A55P1\",\n", " \"CI-W3V33P1\",\n", " \"CI-W3E01F1\",\n", " \"CI-W3A50A3\",\n", " \"CI-W3A50A2\",\n", " \"CI-W3A50A1\",\n", " \"CI-W3A50P1\",\n", " \"CI-W3W01P1\",\n", " \"CI-W3A71P1\",\n", " \"CI-W3W01P2\",\n", " \"CI-W3A71P2\",\n", " \"CI-W3A71P3\",\n", " \"CI-J3J01S1\",\n", " \"CI-W3P17S1\",\n", " \"CI-J3P03S1\",\n", " \"CI-W3K01S1\",\n", " \"CI-W3K14P1\",\n", " \"CI-W3K01T4\",\n", " \"CI-W3K01T2\",\n", " \"CI-W3A65_SO3\",\n", " \"CI-W3A65_Cl\",\n", " \"CI-W3_C3S\",\n", " \"CI-W3_MS\",\n", " \"CI-W3_MA\",\n", " \"CI-W3_PL\",\n", " \"CI-W3_CAO\",\n", " \"CI-W3V04P3\",\n", " \"CI-W3V04P1\",\n", " \"CI-W3W01G1\",\n", " \"CI-W3V21F1\",\n", " \"CI-W3V21P1\",\n", " \"CI-W3V30F1\",\n", " \"CI-W3V33P1\",\n", " \"CI-W3W01A1_AI\",\n", " \"CI-W3W01A2_AI\"\n", "]\n", "url = 'https://pivision.votorantimcimentos.com/piwebapi/dataservers/F1DS-7fYgsRTtUOa7V9NIwSujAUElIQVZD/points?namefilter={tag}'\n", "\n", "headers = {\n", " 'Content-Type': 'application/json',\n", " 'Accept': 'application/json',\n", " 'X-Requested-With': 'piwebapistreams', # Header recomendado pelo PI Web API\n", 'Authorization': "Basic " + __import__('os').environ.get('PI_WEB_API_BASIC_AUTH', '') "}\n", "\n", "web_ids = {}\n", "\n", "for tag in TAG_NAMES:\n", " response = requests.get(url.replace('{tag}', tag), headers=headers).json()\n", " web_ids[tag] = {\n", " 'webid': response['Items'][0]['WebId'],\n", " 'aggr_func': 'lts',\n", " 'data_range': [-100000, 100000],\n", " }\n", " sleep(0.5)\n" ] }, { "cell_type": "code", "execution_count": null, "id": "55793801", "metadata": {}, "outputs": [], "source": [ "import json\n", "json.dump(web_ids, open('web_ids.json', 'w'), indent=4)\n", "web_ids" ] }, { "cell_type": "code", "execution_count": null, "id": "a83b3cb4", "metadata": {}, "outputs": [], "source": [ "from scouter.activities.api import API\n", "from unittest.mock import MagicMock, AsyncMock\n", "from pandas import DataFrame, concat\n", "import json\n", "from time import sleep\n", "\n", "web_ids = json.load(open('web_ids.json'))\n", "\n", "api = API(\n", " base_url='https://pivision.votorantimcimentos.com/piwebapi',\n", " auth_type='basic',\n", auth_token=__import__('os').environ.get('PI_WEB_API_BASIC_AUTH', ''), " logger=MagicMock(),\n", " notification_handler=AsyncMock(),\n", " metrics_controller=AsyncMock(),\n", ")\n", "\n", "start_time = 1800\n", "pace = 30\n", "\n", "data = DataFrame()\n", "\n", "for i in range(start_time, 0, -pace):\n", " j = i - pace\n", " print(f'Getting data for chunk -{i} to -{j} days')\n", " try:\n", " chunk = DataFrame(api.get_tag_values(\n", " input_data={\n", " 'endpoint': '/streamsets/recorded',\n", " 'web_ids': web_ids,\n", " 'period': f'*-{i}d',\n", " 'end_time': f'*-{j}d'.replace('-0d', ''),\n", " 'max_count': None,\n", " 'api_timeout': 5,\n", " 'metadata': {}\n", " }\n", " ))\n", " except Exception as e:\n", " chunk = DataFrame(api.get_tag_values(\n", " input_data={\n", " 'endpoint': '/streamsets/recorded',\n", " 'web_ids': web_ids,\n", " 'period': f'*-{i}d',\n", " 'end_time': f'*-{j}d'.replace('-0d', ''),\n", " 'max_count': None,\n", " 'api_timeout': 5,\n", " 'metadata': {}\n", " }\n", " ))\n", " sleep(1)\n", "\n", " data = concat([data, chunk])\n", "\n", "base_data = data\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "2e2ef295", "metadata": {}, "outputs": [], "source": [ "trunc_spec = 's'\n", "\n", "base_data['truncated_timestamp'] = base_data['timestamp'].dt.floor(trunc_spec)\n", "\n", "# drop timestamp NaT\n", "base_data = base_data[base_data['timestamp'].notna()]\n", "base_data.sort_values(by='truncated_timestamp', inplace=True)\n", "\n", "display(base_data)\n", "\n", "base_data.drop_duplicates(subset=['truncated_timestamp', 'name'], keep='last', inplace=True)" ] }, { "cell_type": "code", "execution_count": null, "id": "ae7b5889", "metadata": {}, "outputs": [], "source": [ "data = base_data.pivot(index='truncated_timestamp', columns='name', values='value')\n", "\n", "data.sort_index(inplace=True)\n", "\n", "# replace Nan with upper row value\n", "data.ffill(inplace=True)\n", "#data.bfill(inplace=True)\n", "data.dropna(inplace=True)\n", "\n", "data['timestamp'] = data.index\n", "\n", "data.reset_index(drop=True, inplace=True)\n", "\n", "display(data)\n" ] }, { "cell_type": "code", "execution_count": null, "id": "4782290f", "metadata": {}, "outputs": [], "source": [ "to_insert_data = data.melt(id_vars=['timestamp'], var_name='variable', value_name='value')\n", "to_insert_data['model_id'] = '111'\n", "to_insert_data.drop_duplicates(subset=['timestamp', 'variable'], keep='last', inplace=True)\n", "to_insert_data = to_insert_data.sort_values(by='timestamp', ascending=False)\n", "to_insert_data.to_csv('data.csv', index=False)" ] }, { "cell_type": "code", "execution_count": 3, "id": "a36d48d1", "metadata": {}, "outputs": [], "source": [ "from sientia_do.temporal.activities.postgres import Postgres\n", "from unittest.mock import MagicMock, AsyncMock\n", "\n", "postgres_interface = Postgres(\n", " host='localhost',\n", " port=5432,\n", " dbname='sientia',\n", " user='sientia',\n", " password='sientia',\n", " min_connections=1,\n", " max_connections=200,\n", " logger=MagicMock(),\n", " notification_handler=AsyncMock(),\n", " metrics_controller=AsyncMock(),\n", ")\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "713ecb2e", "metadata": {}, "outputs": [], "source": [ "from pandas import read_csv\n", "from time import sleep\n", "to_insert_data = read_csv('data.csv')\n" ] }, { "cell_type": "code", "execution_count": null, "id": "f269b8e7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Inserting chunk 0 to 100000\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/grezewave/Documents/projects/sientia/sientia-dataops-scouter_temporal/venv/lib/python3.11/site-packages/sientia_do/observability/sientia_monitoring.py:80: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited\n", " self.metrics_controller.start()\n", "RuntimeWarning: Enable tracemalloc to get the object allocation traceback\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Inserting chunk 100000 to 200000\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/grezewave/Documents/projects/sientia/sientia-dataops-scouter_temporal/venv/lib/python3.11/site-packages/sientia_do/observability/sientia_monitoring.py:80: RuntimeWarning: coroutine 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'AsyncMockMixin._execute_mock_call' was never awaited\n", " self.metrics_controller.start()\n", "RuntimeWarning: Enable tracemalloc to get the object allocation traceback\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Inserting chunk 10700000 to 10800000\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/grezewave/Documents/projects/sientia/sientia-dataops-scouter_temporal/venv/lib/python3.11/site-packages/sientia_do/observability/sientia_monitoring.py:80: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited\n", " self.metrics_controller.start()\n", "RuntimeWarning: Enable tracemalloc to get the object allocation traceback\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Inserting chunk 10800000 to 10900000\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/grezewave/Documents/projects/sientia/sientia-dataops-scouter_temporal/venv/lib/python3.11/site-packages/sientia_do/observability/sientia_monitoring.py:80: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited\n", " self.metrics_controller.start()\n", "RuntimeWarning: Enable tracemalloc to get the object allocation traceback\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Inserting chunk 10900000 to 11000000\n" ] } ], "source": [ "\n", "chunk_start = 10900000\n", "chunk_end = 20000000\n", "\n", "chunk_size = 100000\n", "\n", "chunk_pace = chunk_start\n", "while chunk_pace < chunk_end:\n", " print(f'Inserting chunk {chunk_pace} to {chunk_pace+chunk_size}')\n", " chunk = to_insert_data.iloc[chunk_pace:chunk_pace+chunk_size]\n", " await postgres_interface.export_data_to_postgres(\n", " input_data={\n", " 'data': chunk,\n", " 'table_name': 'laborious_data',\n", " 'schema': 'sientia_data',\n", " 'unique_columns': ['timestamp', 'variable', 'model_id'],\n", " 'on_conflict': 'ignore',\n", " 'metadata': {}\n", " }\n", " )\n", " sleep(10)\n", " chunk_pace += chunk_size" ] }, { "cell_type": "code", "execution_count": null, "id": "2e0e3d5a", "metadata": {}, "outputs": [], "source": [ "item = web_ids['CI-W3A05F1']['webid']\n", "\n", "requests.get(\n", " f'https://pivision.votorantimcimentos.com/piwebapi/streamsets/recorded',\n", " params={\n", " 'webid': item,\n", " 'startTime': '*-1d',\n", " 'endtime': '*',\n", " \"maxCount\": 1,\n", " },\n", " headers=headers\n", ").json()" ] }, { "cell_type": "code", "execution_count": null, "id": "f8c425e2", "metadata": {}, "outputs": [], "source": [ "from pandas import read_csv, to_datetime\n", "\n", "df = read_csv('/home/grezewave/Downloads/laborious_data_202512220821.csv')\n", "data = df.pivot(index='timestamp', columns='variable', values='value')\n", "data['timestamp'] = data.index\n", "\n", "#Remove tz from timestamp\n", "data['timestamp'] = to_datetime(data['timestamp'])\n", "data['timestamp'] = data['timestamp'].dt.tz_localize(None)\n", "\n", "# Back to string and add \"\"\n", "data['timestamp'] = data['timestamp'].dt.strftime('%Y-%m-%d %H:%M:%S')\n", "data.reset_index(drop=True, inplace=True)\n", "data.to_csv('VC-model-data.csv', index=False)\n", "\n", "display(data)" ] }, { "cell_type": "code", "execution_count": 1, "id": "2bd5569d", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " model_id variable value timestamp \\\n", "0 111 CI-W3V30F1 8.514851 2026-01-20 19:41:23+0000 \n", "1 111 CI-W3A71P3 -2.308690 2026-01-20 19:41:23+0000 \n", "2 111 CI-J3P01T1A 228.900000 2026-01-20 19:41:23+0000 \n", "3 111 CI-W3W03I1 75.367424 2026-01-20 19:41:23+0000 \n", "4 111 CI-J3J01S1 87.999020 2026-01-20 19:41:23+0000 \n", "... ... ... ... ... \n", "9993055 111 CI-W3V30F1 6.846108 2025-01-21 11:35:08+0000 \n", "9993056 111 CI-W3K14P1 38.096770 2025-01-21 11:35:08+0000 \n", "9993057 111 CI-W3A50T1 364.250000 2025-01-21 11:35:08+0000 \n", "9993058 111 CI-W3A55T1 871.682300 2025-01-21 11:35:08+0000 \n", "9993059 111 CI-W3W01P1 -2.356829 2025-01-21 11:35:08+0000 \n", "\n", " created_at \n", "0 2026-01-20 23:28:18+0000 \n", "1 2026-01-20 23:28:18+0000 \n", "2 2026-01-20 23:28:18+0000 \n", "3 2026-01-20 23:28:18+0000 \n", "4 2026-01-20 23:28:18+0000 \n", "... ... \n", "9993055 2026-01-21 00:18:50+0000 \n", "9993056 2026-01-21 00:18:50+0000 \n", "9993057 2026-01-21 00:18:50+0000 \n", "9993058 2026-01-21 00:18:50+0000 \n", "9993059 2026-01-21 00:18:50+0000 \n", "\n", "[9993060 rows x 5 columns]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from pandas import read_parquet\n", "\n", "df = read_parquet('~/Downloads/data_2026-01-21_11-32-10.parquet')\n", "\n", "display(df)\n", "\n" ] } ], "metadata": { "kernelspec": { "display_name": "venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 }