Aporia Python SDK
Aporia's Python SDK is a powerful tool designed to streamline ML monitoring and observability.
Define your models, monitors, dashboards, segments, custom metrics, and other ML Observability resources as code, just like in Terraform or Pulumi. The SDK also enables you to query metrics from Aporia to integrate with other platforms.
Key Features
- ML Monitoring as Code: Make it easier to manage and track changes by managing your models, dashboards, segments, and other ML Observability resources as code.
- CI/CD Integration: Integrate with your CI/CD pipeline to automatically monitor all your models with Aporia.
- Query Metrics: Fetch metrics directly from Aporia's platform to inform decisions or to use in other applications.
- Data Source Integration: You can define and integrate multiple types of data sources, like S3, Snowflake, Glue Data Catalog, Databricks, and others. This allows your models to leverage a wide range of data for training and inference.
- Pythonic Interface: Use the familiar Python programming paradigm to interact with Aporia.
Installation
You can install the Aporia SDK using pip:
pip install aporia
Quickstart
Define models as code
import datetime
import os
from aporia import Aporia, MetricDataset, MetricParameters, TimeRange
import aporia.as_code as aporia
aporia_token = os.environ["APORIA_TOKEN"]
aporia_account = os.environ["APORIA_ACCOUNT"]
aporia_workspace = os.environ["APORIA_WORKSPACE"]
stack = aporia.Stack(
token=aporia_token,
account=aporia_account,
workspace=aporia_workspace,
)
stack.apply(yes=True, rollback=False, config_path="config.json")
Query Metrics using the SDK
This example shows how you can use the Aporia SDK to query metrics from a model:
from datetime import datetime
from aporia import (
Aporia,
MetricDataset,
MetricParameters,
TimeRange,
DatasetType,
)
aporia_token = os.environ["APORIA_TOKEN"]
aporia_account = os.environ["APORIA_ACCOUNT"]
aporia_workspace = os.environ["APORIA_WORKSPACE"]
aporia_client = Aporia(
token=aporia_token,
account_name=aporia_account,
workspace_name=aporia_workspace,
)
last_week_dataset = MetricDataset(
dataset_type=DatasetType.SERVING,
time_range=TimeRange(
start=datetime.now() - datetime.timedelta(days=7),
end=datetime.now(),
),
)
metrics = aporia_client.query_metrics(
model_id=model_id,
metrics=[
MetricParameters(
dataset=MetricDataset(dataset_type=DatasetType.SERVING),
name="count",
),
],
)
print(f"The model had {metrics[0]} predictions last week")
Refer to the official Aporia documentation for detailed information on how to use the SDK.
Development
This package uses Poetry for dependency management. To install dependencies, use:
poetry install