196b1aa708
Requirements follow the release; only sientia_model>=0.12.0 (RegressionMetrics), model-library@0.13.1 and scikit-learn==1.8.0 (local) are kept from this branch.
101 lines
3.5 KiB
Python
101 lines
3.5 KiB
Python
from temporalio import workflow
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with workflow.unsafe.imports_passed_through():
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from datetime import timedelta
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from typing import Any
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from sientia_do.temporal.constants import DATETIME_FORMAT_WITH_TZ
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from sientia_do.temporal.policies import retry_policy
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from laborious.activities.activities import Activities
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@workflow.defn(name='simple_metrics')
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class SimpleMetrics:
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@workflow.run
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async def run(self, input_data: dict[str, Any]):
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"""
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Execute the simple metrics workflow.
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"""
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metadata = {
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'metadata': {
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'model_id': input_data['model_id'],
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'model_name': input_data['model_name'],
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'workflow_name': 'simple_metrics',
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'schedule_name': input_data['schedule_name'],
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}
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}
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model_id = input_data['model_id']
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interval_minutes = input_data['interval_minutes']
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model_config = input_data['model_config']
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target_name = model_config['target']
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model_type = model_config.get('model_type')
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thresholds = model_config.get('simple_metrics_thresholds')
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# Built from internal Temporal workflow config, not user input (bandit B608).
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query = f"""
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select p."timestamp", p.prediction, ld.value as "target"
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from "{input_data['schema']}"."{input_data['predictions_table_name']}" p
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inner join "{input_data['schema']}"."{input_data['data_table_name']}" ld
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on p."timestamp" = ld."timestamp"
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where
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p.model_id = '{model_id}' and
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p.prediction is not null and
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ld.variable = '{target_name}' and
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ld.value is not null and
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p."timestamp" >= NOW() - INTERVAL '{interval_minutes} minutes'
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order by
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p."timestamp" desc;
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""" # nosec
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target_data = await workflow.execute_activity_method(
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Activities.load_custom_query,
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{
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**metadata,
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'query': query,
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'datetime_columns': ['timestamp'],
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'orient': 'records',
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},
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retry_policy=retry_policy,
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start_to_close_timeout=timedelta(seconds=300),
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)
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if not target_data:
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return
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simple_metrics = await workflow.execute_local_activity_method(
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Activities.calculate_simple_metrics,
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{
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**metadata,
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'model_id': model_id,
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'target_data': target_data,
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'metrics': input_data.get('metrics', ['rmse', 'mse', 'mae', 'r2']),
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'interval_minutes': interval_minutes,
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'model_type': model_type,
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'thresholds': thresholds,
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},
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retry_policy=retry_policy,
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start_to_close_timeout=timedelta(seconds=300),
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)
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if not simple_metrics:
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return
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await workflow.execute_activity_method(
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Activities.export_data_to_postgres,
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{
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**metadata,
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'data': simple_metrics,
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'schema': input_data['schema'],
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'table_name': input_data['target_table_name'],
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'timestamp_conversion': {
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'column': 'timestamp',
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'format': DATETIME_FORMAT_WITH_TZ,
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},
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},
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retry_policy=retry_policy,
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start_to_close_timeout=timedelta(seconds=300),
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)
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