Oracle Cloud Infrastructure Documentation

Database and Exploration

Learn about database and exploration conda environments.

Oracle Database and Data Exploration for CPU (version 1.0)

A description of the Oracle Database and Data Exploration for CPU on Python 3.8 (version 1.0)conda environment.

Released

December 1, 2022

Description

Work with Oracle on-premise and Cloud databases (ADW, ATP) from within `pandas` using the ADS accessor, or from a notebook use the ipython-sql` magics like `%sql SELECT * from SH.SALES where rownum <= 5 to run SQL and capture the result in the notebook. ADS has improved the type mapping between pandas to make queries and inserts faster. This pack includes support for Oracle Database and SQLite. Use this pack to create ETL jobs in notebooks, batch transform data, and to perform database queries. The pre-installed`oracle-ads SDK helps working with data in Object Storage, or in the Oracle Database.

To get started with this conda environment, review the Getting Started notebook, using the Launcher.

Python Version

3.8
Slug

dbexp_p38_cpu_v1
Object Storage Path 
oci://service-conda-packs@id19sfcrra6z/service_pack/cpu/Oracle_Database_and_Data_Exploration_for_CPU_Python_3.8/1.0/dbexp_p38_cpu_v1

Top Libraries

  • ipython-sql (v0.3.9)

  • oracle-ads (v2.6.8)

  • oracledb (v1.1.1)

  • sqlalchemy (v1.4.39)

For a complete list of preinstalled Python libraries, see dbexp_p38_cpu_v1.txt.
Oracle Property Graph 24.1 for CPU on Python 3.8 (version 1.0)

A description of the Oracle Property Graph 24.1 for CPU on Python 3.8 (version 1.0) conda environment.

Released

February 9, 2024

Description

This package lets you include graph analytics in your OCI Data Science Notebook. It contains two components (1) PyPGX, and (2) Autonomous Database Graph Client. PyPGX is a graph toolkit and library to create, query and analyze graphs in a Graph Server (PGX), from an OCI Data Science Notebook. The Autonomous Database Graph Client helps you run graph queries and analytics on graphs stored in Autonomous Database, connecting from the notebook to an Autonomous Database instance and running queries and analytics in Graph Studio, a feature of Autonomous Database.

Graph queries are enabled by the Property Graph Query Language (PGQL), a SQL-like language to query graphs. Graph analytics includes over 60 pre-built algorithms, including graph machine learning algorithms.

Graph query and analytics enable you to find hidden insights in data. When your data is represented as a graph, data entities are modeled as graph vertices and relationships between entites are modeled as graph edges. Graphs enable traversal of implicit relationships in data for the discovery of valuable and actionable insights in your data.

To get started with the PyPGX environment, review the notebook example `getting-started.ipynb`, using the Launcher.

To get started with Autonomous Database Graph client, review the notebook example `graph_insight-autonomous_database.ipynb`, using the Launcher.

Also you can check out the documentation by clicking on the following links:

  1. PyPGX
  2. OPG4PY

Python Version

3.8
Slug pypgx2410_p38_cpu_v1
Object Storage Path 
oci://service-conda-packs@id19sfcrra6z/service_pack/cpu/Oracle_Property_Graph_24.1_for_CPU_on_Python_3.8/1.0/pypgx2410_p38_cpu_v1

Top Libraries

  • oracle-ads (v2.10.0)

  • oracle-graph-embedded (v24.1.0)

For a complete list of preinstalled Python libraries, see pypgx2410_p38_cpu_v1.txt.
Oracle Property Graph 23.4 for CPU on Python 3.8 (version 1.0)

A description of the Oracle Property Graph 23.4 for CPU on Python 3.8 (version 1.0) conda environment.

Released

December 1, 2023

Description

This package enables you to include graph analytics in your OCI Data Science Notebook. It contains two components (1) PyPGX, and (2) Autonomous Database Graph Client. PyPGX is a graph toolkit and library to create, query and analyze graphs in a Graph Server (PGX), from an OCI Data Science Notebook. The Autonomous Database Graph Client helps you run graph queries and analytics on graphs stored in Autonomous Database, connecting from the notebook to an Autonomous Database instance and running queries and analytics in Graph Studio, a feature of Autonomous Database.

Graph queries are enabled by the Property Graph Query Language (PGQL), a SQL-like language to query graphs. Graph analytics includes over 60 pre-built algorithms, including graph machine learning algorithms.

Graph query and analytics enable you to find hidden insights in data. When your data is represented as a graph, data entities are modeled as graph vertices and relationships between entites are modeled as graph edges. Graphs enable traversal of implicit relationships in data for the discovery of valuable and actionable insights in your data.

To get started with the PyPGX environment, review the notebook example, getting-started.ipynb, in the Notebook Examples launcher button.

To get started with Autonomous Database Graph client, review the notebook example, graph_insight-autonomous_database.ipyn in the Notebook Examples launcher button.

Also you can check out the documentation by clicking on the following links:

1. PyPGX

2. OPG4PY

Python Version

3.8.16
Slug pypgx2340_p38_cpu_v1
Object Storage Path 
oci://service-conda-packs@id19sfcrra6z/service_pack/cpu/Oracle_Property_Graph_23.4_for_CPU_on_Python_3.8/1.0/pypgx2340_p38_cpu_v1

Top Libraries

  • oracle-ads (v2.9.0)

  • oracle-graph-client (v23.4.0)

For a complete list of preinstalled Python libraries, see pypgx2340_p38_cpu_v1.txt.