oracle-ads 2.6.4

Oracle Accelerated Data Science SDK

Oracle Accelerated Data Science SDK (ADS)

The Oracle Accelerated Data Science (ADS) SDK is maintained by the Oracle Cloud Infrastructure (OCI) Data Science service team. It speeds up common data science activities by providing tools that automate and simplify common data science tasks. Additionally, provides data scientists a friendly pythonic interface to OCI services. Some of the more notable services are OCI Data Science, Model Catalog, Model Deployment, Jobs, Data Flow, Object Storage, Vault, Big Data Service, Data Catalog, and the Autonomous Database. ADS gives you an interface to manage the life cycle of machine learning models, from data acquisition to model evaluation, interpretation, and model deployment.

With ADS you can:

• Read datasets from Oracle Object Storage, Oracle RDBMS (ATP/ADW/On-prem), AWS S3 and other sources into Pandas dataframes.
• Use feature types to characterize your data, create meaning summary statistics and plot. Use the warning and validation system to test the quality of your data.
• Tune models using hyperparameter optimization with the ADSTuner tool.
• Generate detailed evaluation reports of your model candidates with the ADSEvaluator module.
• Save machine learning models to the OCI Data Science Model Catalog.
• Deploy models as HTTP endpoints with Model Deployment.
• Launch distributed ETL, data processing, and model training jobs in Spark with OCI Data Flow.
• Train machine learning models in OCI Data Science Jobs.
• Manage the life cycle of conda environments through the ads conda command line interface (CLI).

Installation

You have various options when installing ADS.

Installing the oracle-ads base package

  $ python3 -m pip install oracle-ads

Installing extras libraries

The all-optional module will install all optional dependencies.

  $ python3 -m pip install oracle-ads[all-optional]

To work with gradient boosting models, install the boosted module. This module includes XGBoost and LightGBM model classes.

  $ python3 -m pip install oracle-ads[boosted]

For big data use cases using Oracle Big Data Service (BDS), install the bds module. It includes the following libraries, ibis-framework[impala], hdfs[kerberos] and sqlalchemy.

  $ python3 -m pip install oracle-ads[bds]

To work with a broad set of data formats (for example, Excel, Avro, etc.) install the data module. It includes the fastavro, openpyxl, pandavro, asteval, datefinder, htmllistparse, and sqlalchemy libraries.

  $ python3 -m pip install oracle-ads[data]

To work with geospatial data install the geo module. It includes the geopandas and libraries from the viz module.

  $ python3 -m pip install oracle-ads[geo]

Install the notebook module to use ADS within a OCI Data Science service notebook session. This module installs ipywidgets and ipython libraries.

  $ python3 -m pip install oracle-ads[notebook]

To work with ONNX-compatible run times and libraries designed to maximize performance and model portability, install the onnx module. It includes the following libraries, onnx, onnxruntime, onnxmltools, skl2onnx, xgboost, lightgbm and libraries from the viz module.

  $ python3 -m pip install oracle-ads[onnx]

For infrastructure tasks, install the opctl module. It includes the following libraries, oci-cli, docker, conda-pack, nbconvert, nbformat, and inflection.

  $ python3 -m pip install oracle-ads[opctl]

For hyperparameter optimization tasks install the optuna module. It includes the optuna and libraries from the viz module.

  $ python3 -m pip install oracle-ads[optuna]

Install the tensorflow module to include tensorflow and libraries from the viz module.

  $ python3 -m pip install oracle-ads[tensorflow]

For text related tasks, install the text module. This will include the wordcloud, spacy libraries.

  $ python3 -m pip install oracle-ads[text]

Install the torch module to include pytorch and libraries from the viz module.

  $ python3 -m pip install oracle-ads[torch]

Install the viz module to include libraries for visualization tasks. Some of the key packages are bokeh, folium, seaborn and related packages.

  $ python3 -m pip install oracle-ads[viz]

Note

Multiple extra dependencies can be installed together. For example:

  $ python3 -m pip install  oracle-ads[notebook,viz,text]

Documentation

• Oracle Accelerated Data Science SDK (ADS) Documentation
• OCI Data Science and AI services Examples
• Oracle AI & Data Science Blog
• OCI Documentation

Examples

Load data from Object Storage

  import ads
  from ads.common.auth import default_signer
  import oci
  import pandas as pd

  ads.set_auth(auth="api_key", oci_config_location=oci.config.DEFAULT_LOCATION, profile="DEFAULT")
  bucket_name = <bucket_name>
  key = <key>
  namespace = <namespace>
  df = pd.read_csv(f"oci://{bucket_name}@{namespace}/{key}", storage_options=default_signer())

Load data from ADB

This example uses SQL injection safe binding variables.

  import ads
  import pandas as pd

  connection_parameters = {
      "user_name": "<user_name>",
      "password": "<password>",
      "service_name": "<tns_name>",
      "wallet_location": "<file_path>",
  }

  df = pd.DataFrame.ads.read_sql(
      """
      SELECT *
      FROM SH.SALES
      WHERE ROWNUM <= :max_rows
      """,
      bind_variables={ max_rows : 100 },
      connection_parameters=connection_parameters,
  )

Contributing

This project welcomes contributions from the community. Before submitting a pull request, please review our contribution guide CONTRIBUTING.md.

Find Getting Started instructions for developers in README-development.md

Security

Consult the security guide SECURITY.md for our responsible security vulnerability disclosure process.

License

Copyright (c) 2020, 2022 Oracle and/or its affiliates. Licensed under the Universal Permissive License v1.0