Skip to main content

Generate Azure Data Factory objects from configuration

Project description

Ingenii Azure Data Factory Generator

Python based generator to create Azure Data Factory pipelines from configurations.

This package integrates easily with the Ingenii Azure Data Platform, but this package can be used independently as long as some required linked services and data sets are created ahead of time. These are detailed in the sections below.

  • Current Version: 0.1.4

Package installation

Install the package using pip with

pip install azure_data_factory_generator

or, for a particular version

pip install azure_data_factory_generator==0.1.4

Alternatively, add it to your requirements.txt file.

Use the package by calling it directly with the locations of your config files and the folder that the generated objects should be placed within:

python -m azure_data_factory_generator path/to/config/files/folder path/to/generated/files/folder

Using the package

For details on using the package please refer to the Azure Data Factory Usage documentation.

Version History

  • 0.1.4: Add object annotations to track what is managed by this package
  • 0.1.3: Extend schedule to handle when only the hours of the dayt are specified
  • 0.1.2: Change the name of the secret name for the SAS URI to access the config tables
  • 0.1.1: Add schedule generation from configuration, many more tests
  • 0.1.0: Initial package, FTP/SFTP connections with basic authentication

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

File details

Details for the file azure_data_factory_generator-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: azure_data_factory_generator-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 18.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.2 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.8

File hashes

Hashes for azure_data_factory_generator-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 5b0340d41913e6ba78c1be76229f5e93782107826a871a324ffed92ede86c550
MD5 6227efcbd6e4221a132985991efd2d0c
BLAKE2b-256 2c6ed4d83d0f5cabbec1a9af5449de8ede312a418db43e0b29d0e4bf40d1e177

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page