Database and Exploration
Learn about database and exploration conda environments.
A description of the Oracle Property Graph 24.1 for CPU on Python 3.8 (version 1.0) conda environment.
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Released |
February 9, 2024 |
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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: |
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Python Version |
3.8 |
| Slug | pypgx2410_p38_cpu_v1 |
| Object Storage Path |
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Top Libraries |
For a complete list of preinstalled Python libraries, see pypgx2410_p38_cpu_v1.txt. |
A description of the Oracle Property Graph 23.4 for CPU on Python 3.8 (version 1.0) conda environment.
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Released |
December 1, 2023 |
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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 |
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Python Version |
3.8.16 |
| Slug | pypgx2340_p38_cpu_v1 |
| Object Storage Path |
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Top Libraries |
For a complete list of preinstalled Python libraries, see pypgx2340_p38_cpu_v1.txt. |