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VerticaPy version 1.0.2

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@mail4umar mail4umar released this 08 Mar 21:17
· 115 commits to master since this release
8236e90

This minor release has some significant feature additions with other changes. Some salient ones are listed below:

⚠️ Please note that this list may be incomplete, and for a comprehensive overview, including additional features, refer to the changelogs.

Pipelines (Beta)

  • Pipelines is a YAML-based configuration for defining machine learning workflows, simplifying the process of setting up and managing machine learning pipelines.
  • For beginners, it provides an easy-to-learn alternative to Python and SQL reducing the initial barriers to entry for creating models.
  • For more experienced users, it offers templating features to enhance modularity, minimize errors, and promote efficient code reuse in machine learning projects.

Performance

  • We have enhanced the QueryProfiler to improve its robustness.
  • Introducing a completely new Query Profiler Interface, enabling users to navigate through various queries and access them without the need to re-enter all the code. All of this can be accomplished using only your mouse within Jupyter Notebook environments.

These updates significantly enhance the accessibility, debugging, and enhancement capabilities of your queries.

OAuth Refresh Tokens (Beta)

  • We have updated the connector to accept OAuth refresh tokens.
  • Additioanlly we have added a prompt option for verticapy.connection.new_connection. This allows the user to enter the secrets discretly with a masked display.

Multi-TimeSeries (Beta)

We added a new Time Series class: TimeSeriesByCategory. This allows the users to build multiple models based off on a category. The number of models created
are equal to the categories. This saves users time to create multiple models separately. For more information please see verticapy.machine_learning.vertica.tsa.ensemble.TimeSeriesByCategory.

Plots

  • Two new plots have been added for plotly that were previously missing:

    • verticapy.machine_learning.vertica.decomposition.plot_scree
    • verticapy.machine_learning.vertica.decomposition.plot_var

Unit Tests

  • We continue to shift our old tests to the new more robust format.

Examples

  • Most of the examples <https://github.com/vertica/VerticaPy/tree/master/examples>_ have been updated with the latest verticapy format.

Release Notes

Changelogs

Installation

The release will be on available on the defaults and can be installed using:

python3 -m pip install verticapy

If you want to install extra features, use:

python3 -m pip install verticapy[all]

Please report any issues on our GitHub page

Contributors

We would like to extend our thanks to all the contributors who made this release possible:

If you would like to contribute then please visit our updated contributing guidelines.