A package to simplify working with the Apache Atlas REST APIs for Atlas and Azure Purview.
Project description
PyApacheAtlas: A Python SDK for Azure Purview and Apache Atlas
PyApacheAtlas lets you work with the Azure Purview and Apache Atlas APIs in a Pythonic way. Supporting bulk loading, custom lineage, custom type definition and more from an SDK and Excel templates / integration.
The package supports programmatic interaction and an Excel template for low-code uploads.
Using Excel to Accelerate Metadata Uploads
- Bulk upload entities.
- Upload entities / assets for built-in or custom types.
- Supports adding glossary terms to entities.
- Supports adding classifications to entities.
- Supports creating relationships between entities (e.g. columns of a table).
- Creating custom lineage between existing entities.
- Defining Purview Column Mappings / Column Lineage.
- Bulk upload custom type definitions.
- Bulk upload of classification definitions (Purview Classification Rules not supported).
Using the Pythonic SDK for Purview and Atlas
The PyApacheAtlas package itself supports those operations and more for the advanced user:
- Programmatically create Entities, Types (Entity, Relationship, etc.).
- Perform partial updates of an entity (for non-complex attributes like strings or integers).
- Extracting entities by guid or qualified name.
- Creating custom lineage with Process and Entity types.
- Working with the glossary.
- Uploading terms.
- Downloading individual or all terms.
- Working with classifications.
- Classify one entity with multiple classifications.
- Classify multiple entities with a single classification.
- Remove classification ("declassify") from an entity.
- Working with relationships.
- Able to create arbitrary relationships between entities.
- e.g. associating a given column with a table.
- Deleting types (by name) or entities (by guid).
- Performing "What-If" analysis to check if...
- Your entities are valid types.
- Your entities are missing required attributes.
- Your entities are using undefined attributes.
- Azure Purview's Search: query, autocomplete, suggest, browse.
- Authentication to Azure Purview using azure-identity and Service Principal
- Authentication to Apache Atlas using basic authentication of username and password.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyapacheatlas-0.16.0.tar.gz
(65.3 kB
view details)
Built Distribution
File details
Details for the file pyapacheatlas-0.16.0.tar.gz
.
File metadata
- Download URL: pyapacheatlas-0.16.0.tar.gz
- Upload date:
- Size: 65.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.18
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 26990f5d757ce487553f32d0c2355d96032a54fa940763b81c6f961eb81754d4 |
|
MD5 | 3999c752be21661f85d602c92042c5f0 |
|
BLAKE2b-256 | 247b7f10106aaebd8497981d85a8774970e14320c2888dc4e071971b106fb7e9 |
File details
Details for the file pyapacheatlas-0.16.0-py3-none-any.whl
.
File metadata
- Download URL: pyapacheatlas-0.16.0-py3-none-any.whl
- Upload date:
- Size: 77.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.18
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7294f4ca46b117b60da326fb188ac18cffb1939aa20094cba79fbd55d8aede4e |
|
MD5 | e22a5d54661b840f338112145b592e73 |
|
BLAKE2b-256 | 801f4c83a5939c9218aa84e024424bff96120e44a8111a99cf5a90f095fa3dee |