Installation and Setup¶
Install ADS CLI¶
Prerequisites
Linux/Mac (Intel CPU)
For Mac on M series - Experimental.
For Windows: Use Windows Subsystem for Linux (WSL)
python >=3.8, <=3.10
ads
cli provides a command line interface to Jobs API related features. Set up your development environment, build docker images compliant with Notebook session and Data Science Jobs, build and publish conda pack locally, start distributed training, etc.
Installation
Install ADS and enable CLI:
python3 -m pip install "oracle-ads[opctl]"
Tip
ads opctl
subcommand lets you setup your local development envrionment for Data Science Jobs. More information can be found by running ads opctl -h
Install oracle-ads
SDK¶
Data Science Conda Environments¶
ADS is installed in the data science conda environments. Upgrade your existing oracle-ads package by running -
$ python3 -m pip install oracle-ads --upgrade
Install in Local Environments¶
You have various options when installing ADS.
Installing the oracle-ads
base package¶
$ python3 -m pip install oracle-ads
Installing extras libraries¶
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 following libraries: fastavro
, openpyxl
, pandavro
, asteval
, datefinder
, htmllistparse
, and sqlalchemy
.
$ 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 the Oracle Cloud Infrastructure 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]"
For Spark tasks install the spark
module.
$ python3 -m pip install "oracle-ads[spark]"
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]"
See pyproject.toml
file [project.optional-dependencies]
section for full list of modules and its list of extra libraries.
Note
Multiple extra dependencies can be installed together. For example:
$ python3 -m pip install "oracle-ads[notebook,viz,text]"