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,
)

# Your model definition code goes here

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

Metadata

Release files for aporia 3.38.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for aporia 3.38.0
File	Size	Uploaded
aporia-3.38.0.tar.gz	45.2 kB	Feb 4, 2025	Details

Built distribution (wheel)

Table of built distributions (wheels) for aporia 3.38.0
File	Interpreter	ABI	Platform	Reset
aporia-3.38.0-py3-none-any.whl 67.4 kB Feb 4, 2025	Python 3	none	any	Details

Total release size: 112.7 kB

Release files / aporia-3.38.0.tar.gz

Download URL	aporia-3.38.0.tar.gz
Size	45.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`7c21c1da388bf289265e79503dbda665dd41d0b81c0ca1c800608511992257e8`
BLAKE2b-256 checksum How to use checksums	`ffd4d1e4c4d6bbd5f1a5f925f9dc02c3f1d80bea712d3aa7d7b1b2d9e4d65542`
Upload date	Feb 4, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/2.0.1 CPython/3.10.16 Linux/6.5.0-1025-azure`

Release files / aporia-3.38.0-py3-none-any.whl

Download URL	aporia-3.38.0-py3-none-any.whl
Size	67.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`8e42f08bb3df4a2987a36d73337ec418d6eeb9dfb4dedb95393788d15396d5f5`
BLAKE2b-256 checksum How to use checksums	`340f6729eca142786651790bf03f0205b1737e787dc11f4d58960e1140eb072f`
Upload date	Feb 4, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/2.0.1 CPython/3.10.16 Linux/6.5.0-1025-azure`