SIENTIAPDE-1712

Refactor MinioDataFramePayload usage across activities

- Updated instances of MinioDataFramePayload initialization in Gates, MLFlow, and Storage classes to use the new from_dict method for better data reconstruction from dictionaries.
- Enhanced the PredictionProcess workflow to utilize the updated payload handling.
- Added passthrough fixtures in tests to accommodate the new from_dict method for consistent testing behavior.
This commit is contained in:
vitor-aignosi
2026-03-20 15:52:04 -03:00
parent 8789e6693f
commit 67942c45e0
12 changed files with 155 additions and 31 deletions

View File

@@ -157,7 +157,7 @@ class Gates(MinioManager):
self.info('Performing input gate...', metadata)
filters = input_data['filters']
payload: MinioDataFramePayload = input_data['data']
payload = MinioDataFramePayload.from_dict(input_data['data'])
data = await payload.retrieve(self.minio_repository, metadata)
path_priority = input_data['path_priority']
@@ -236,7 +236,7 @@ class Gates(MinioManager):
filters = input_data['filters']
payload: MinioDataFramePayload = input_data['data']
payload = MinioDataFramePayload.from_dict(input_data['data'])
data = await payload.retrieve(self.minio_repository, metadata)
gate_type = input_data['type']
@@ -327,7 +327,7 @@ class Gates(MinioManager):
filters = input_data['filters']
payload: MinioDataFramePayload = input_data['data']
payload = MinioDataFramePayload.from_dict(input_data['data'])
data = await payload.retrieve(self.minio_repository, metadata)
gate_type = input_data['type']
@@ -465,7 +465,7 @@ class Gates(MinioManager):
self.info('Formatting transformed data...', metadata)
payload: MinioDataFramePayload = input_data['data']
payload = MinioDataFramePayload.from_dict(input_data['data'])
data = await payload.retrieve(self.minio_repository, metadata)
data['timestamp'] = data.index

View File

@@ -128,7 +128,7 @@ class MLFlow(MinioManager):
metadata = input_data['metadata']
self.info('Transforming data...', metadata)
payload: MinioDataFramePayload = input_data['data']
payload = MinioDataFramePayload.from_dict(input_data['data'])
data = await payload.retrieve(self.minio_repository, metadata)
model_name = input_data['model_name']
@@ -222,7 +222,7 @@ class MLFlow(MinioManager):
metadata = input_data['metadata']
self.info('Predicting data...', metadata)
payload: MinioDataFramePayload = input_data['data']
payload = MinioDataFramePayload.from_dict(input_data['data'])
data = await payload.retrieve(self.minio_repository, metadata)
model_name = input_data['model_name']
@@ -311,7 +311,7 @@ class MLFlow(MinioManager):
try:
# Payload-based retrain input (inline dict or MinIO offloaded).
payload: MinioDataFramePayload = input_data['data']
payload = MinioDataFramePayload.from_dict(input_data['data'])
data = await payload.retrieve(self.minio_repository, metadata)
except Exception as e:

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@@ -8,7 +8,6 @@ with workflow.unsafe.imports_passed_through():
# Extend the Temporal Postgres activities for convenient query -> MinIO export
import traceback
from datetime import timedelta
from io import BytesIO
from typing import Any
import pandas as pd
@@ -18,7 +17,7 @@ with workflow.unsafe.imports_passed_through():
from sientia_do.observability.metrics_controller import MetricsController
from sientia_do.repository.minio_repository import MinioRepository
from sientia_do.temporal.activities.postgres import Postgres
from sientia_do.temporal.constants import DATETIME_FORMAT_FILENAME, now
from sientia_do.temporal.constants import now
from laborious.utils.models.minio_dataframe_payload import MinioDataFramePayload
@@ -116,7 +115,7 @@ class Storage(Postgres, MinioManager):
Export a payload to PostgreSQL.
"""
metadata = input_data.get('metadata')
payload: MinioDataFramePayload = input_data['data']
payload = MinioDataFramePayload.from_dict(input_data['data'])
data = await payload.retrieve(self.minio_repository, metadata)
return await self.export_data_to_postgres(
@@ -142,7 +141,8 @@ class Storage(Postgres, MinioManager):
raise ValueError('Minio repository not initialized')
metadata = input_data.get('metadata', {})
prefix = input_data['prefix']
payload = MinioDataFramePayload.from_dict(input_data['data'])
prefix = payload.cleanup_prefix()
base = now()
cutoff = (base.replace(tzinfo=None) if base.tzinfo else base) - timedelta(
hours=self.retention_hours
@@ -206,7 +206,6 @@ class Storage(Postgres, MinioManager):
return report
def close(self) -> None:
"""Close Storage resources (MinIO client and Postgres engine)."""
Postgres.close(self)

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@@ -81,6 +81,38 @@ class MinioDataFramePayload:
object_prefix: str | None = None
uri: str | None = None
@classmethod
def from_dict(cls, raw: dict[str, Any] | 'MinioDataFramePayload') -> 'MinioDataFramePayload':
"""
Reconstruct a MinioDataFramePayload from a plain dict produced by Temporal serialization.
Temporal converts dataclass return values into plain dicts when crossing
workflow/activity boundaries. This method rebuilds the typed instance so
that methods like ``retrieve``, ``cleanup_prefix`` and ``has_data`` are
available on the receiving side.
If the argument is already a MinioDataFramePayload, it is returned as-is.
Args:
raw: Dict with keys matching the dataclass fields
(last_timestamp, status, data, bucket, object_key, object_prefix, uri),
or an existing MinioDataFramePayload instance.
Return:
MinioDataFramePayload: Reconstructed (or original) instance.
"""
if isinstance(raw, MinioDataFramePayload):
return raw
return cls(
last_timestamp=raw['last_timestamp'],
status=raw.get('status'),
data=raw.get('data'),
bucket=raw.get('bucket'),
object_key=raw.get('object_key'),
object_prefix=raw.get('object_prefix'),
uri=raw.get('uri'),
)
@staticmethod
def estimate_size_bytes(df: DataFrame) -> int:
"""
@@ -118,7 +150,6 @@ class MinioDataFramePayload:
except ValueError:
return None
@staticmethod
def cleanup_prefix(self) -> str | None:
"""
Return True if cleanup is enabled for this payload.

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@@ -38,8 +38,6 @@ class PredictionProcess:
8. Export Delegation: Delegates to FormatAndExportPrediction workflow
"""
cleanup_prefixes: set[str] = set()
@workflow.run
async def run(self, input_data: dict[str, Any]):
"""
@@ -90,8 +88,6 @@ class PredictionProcess:
model_config = input_data.get('model_config', {})
save_transform = input_data.get('save_transform', True)
prefix = data.cleanup_prefix()
try:
await self._run_prediction_pipeline(
input_data,
@@ -103,13 +99,12 @@ class PredictionProcess:
save_transform,
)
finally:
if self.cleanup_prefixes:
await workflow.execute_activity_method(
Activities.cleanup_minio_objects_expired,
{**metadata, 'prefix': prefix},
retry_policy=retry_policy,
start_to_close_timeout=timedelta(minutes=5),
)
await workflow.execute_activity_method(
Activities.cleanup_minio_objects_expired,
{**metadata, 'data': data},
retry_policy=retry_policy,
start_to_close_timeout=timedelta(minutes=5),
)
async def _run_prediction_pipeline(
self,

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@@ -7,6 +7,14 @@ from sientia_do.notifications.models import NotificationLevel
from laborious.activities.gates import Gates
@fixture(autouse=True)
def _passthrough_from_dict():
with patch(
'laborious.activities.gates.MinioDataFramePayload.from_dict', side_effect=lambda x: x
):
yield
def _minio_payload(retrieve_return, status=None):
"""
Build a MinioDataFramePayload-like test double with async retrieve.

View File

@@ -8,6 +8,14 @@ from sientia_do.temporal.constants import DATETIME_FORMAT, DATETIME_FORMAT_WITH_
from laborious.activities.mlflow import MLFlow
@fixture(autouse=True)
def _passthrough_from_dict():
with patch(
'laborious.activities.mlflow.MinioDataFramePayload.from_dict', side_effect=lambda x: x
):
yield
@patch('laborious.activities.mlflow.MLFlowRepository')
@patch('laborious.activities.mlflow.MinioRepository')
def test___init__(mock_minio_repository, mock_mlflow_repository):

View File

@@ -8,6 +8,15 @@ from sientia_do.temporal.activities.postgres import Postgres
from laborious.activities.storage import Storage
@fixture(autouse=True)
def _passthrough_from_dict():
with patch(
'laborious.activities.storage.MinioDataFramePayload.from_dict', side_effect=lambda x: x
):
yield
metadata = {
'metadata': {
'model_id': 'test_model_id',

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@@ -214,3 +214,55 @@ async def test_from_dataframe_offloaded(mock_now):
assert result.bucket == 'test-bucket'
assert result.uri == 's3://test-bucket/full/key.parquet'
minio.upload_file.assert_awaited_once()
def test_from_dict_inline():
raw = {
'last_timestamp': '2024-01-01T00:00:00+00:00',
'status': None,
'data': {'col1': {0: 'val1'}},
'bucket': None,
'object_key': None,
'object_prefix': None,
'uri': None,
}
payload = MinioDataFramePayload.from_dict(raw)
assert isinstance(payload, MinioDataFramePayload)
assert payload.last_timestamp == '2024-01-01T00:00:00+00:00'
assert payload.data == {'col1': {0: 'val1'}}
assert payload.object_key is None
def test_from_dict_offloaded():
raw = {
'last_timestamp': '2024-06-15T10:30:45+00:00',
'status': {'success': True},
'data': None,
'bucket': 'my-bucket',
'object_key': 'training_datasets/model/model-initial-2024-06-15_10-30-45.parquet',
'object_prefix': 'training_datasets/model',
'uri': 's3://my-bucket/training_datasets/model/model-initial-2024-06-15_10-30-45.parquet',
}
payload = MinioDataFramePayload.from_dict(raw)
assert isinstance(payload, MinioDataFramePayload)
assert payload.data is None
assert payload.bucket == 'my-bucket'
assert payload.object_key == raw['object_key']
assert payload.object_prefix == 'training_datasets/model'
assert payload.uri == raw['uri']
assert payload.status == {'success': True}
def test_from_dict_minimal_keys():
raw = {'last_timestamp': '2024-01-01'}
payload = MinioDataFramePayload.from_dict(raw)
assert payload.last_timestamp == '2024-01-01'
assert payload.data is None
assert payload.bucket is None
assert payload.object_key is None
def test_from_dict_passthrough_existing_instance():
original = MinioDataFramePayload(last_timestamp='2024-01-01', data={'a': 1}, bucket='b')
result = MinioDataFramePayload.from_dict(original)
assert result is original

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@@ -6,6 +6,15 @@ from laborious.activities.activities import Activities
from laborious.workflows.sub_workflows.prediction_process import PredictionProcess
@fixture(autouse=True)
def _passthrough_from_dict():
with patch(
'laborious.workflows.sub_workflows.prediction_process.MinioDataFramePayload.from_dict',
side_effect=lambda x: x,
):
yield
@fixture
def prediction_process():
return PredictionProcess()

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@@ -6,6 +6,15 @@ from laborious.activities.activities import Activities
from laborious.workflows.minimal_retrain import MinimalRetrain
@fixture(autouse=True)
def _passthrough_from_dict():
with patch(
'laborious.workflows.minimal_retrain.MinioDataFramePayload.from_dict',
side_effect=lambda x: x,
):
yield
@fixture
def minimal_retrain() -> MinimalRetrain:
return MinimalRetrain()

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@@ -1,4 +1,4 @@
from unittest.mock import ANY, AsyncMock, call, patch
from unittest.mock import ANY, AsyncMock, MagicMock, call, patch
from pytest import fixture, mark
@@ -22,12 +22,15 @@ metadata = {
@mark.asyncio
@patch(
'laborious.workflows.predictions_batch.MinioDataFramePayload.from_dict', side_effect=lambda x: x
)
@patch('laborious.workflows.predictions_batch.workflow', new_callable=AsyncMock)
async def test_run(workflow_mock: AsyncMock, predictions_batch: PredictionsBatch):
workflow_mock.execute_activity_method.return_value = {
'success': True,
'data': {'col': ['test_data']},
}
async def test_run(workflow_mock: AsyncMock, mock_from_dict, predictions_batch: PredictionsBatch):
activity_return = MagicMock()
activity_return.cleanup_prefix.return_value = None
workflow_mock.execute_activity_method.return_value = activity_return
input_data = {
'schedule_name': 'test_schedule',
'model_name': 'test_model',
@@ -62,7 +65,8 @@ async def test_run(workflow_mock: AsyncMock, predictions_batch: PredictionsBatch
)
prediction_input = {
'metadata': metadata,
'data': {'success': True, 'data': {'col': ['test_data']}},
'data': activity_return,
'cleanup_prefix': activity_return.cleanup_prefix(),
'schema': input_data['schema'],
'table_name': input_data['table_name'],
'transform_table_name': input_data['transform_table_name'],