Сustom Widgets and Tabs

• Support widgets order for include_widgets parameter
• Support an ability to add a custom widget to Tabs with include_widgets parameter
• Moved options to a separate module
• Added options to specify statistical tests for DataDrift and TargetDrift Dashboards:
  stattest_func - to set a custom statistical test for all the features
  feature_stattest_func - to set a custom statistical tests for each individual feature
  cat_target_stattest_func - to set a custom statistical test for categorical target
  num_target_stattest_func - to set a custom statistical test for numerical target
• Refactored Widgets and Tabs for simpler customisation

Customizable Dashboards

• Supported custom list of Widgets for Tabs in Dashboard with help of verbose_level and include_widgets parameters
• Added parameter verbose_level: 0 - to create a Tab with the shortest list of Widgets, 1 - to create a full Tab
• Added parameter include_widgets : ["Widget Name 1", "Widget Name 2", etc]. This parameter overwrites verbose_level (if both are specified) and allows to set a custom list of Widgets
• Added Tab.list_widgets() method to list all the available Widgets for the current Tab
• Created Options entity to specify Widgets and Tabs customisable settings
• Created ColumnMapping entity instead column_mapping python dictionary

Fix: dependency on PyYaml version 6.0

Removed PyYAML~=6.0 from the dependencies

Code Style and Object Types Checks

• Added flake8 for code style checks
• Added mypy for object types checks
• Improved code style
• Added contribution guide

Support for widget visualization in Colab, Pylab, Kaggle, Deepnote

1. Supported dashboard visualization in Google Colab
2. Supported dashboard visualization in python Pylab
3. Added a parameter mode for dashboard.show(), which can take the following options:

• auto - the default option. Ideally, you will not need to specify the value for mode and use the default. But, if it does not work (in case we failed to determine the environment automatically), consider setting the correct value explicitly.
• nbextention - to show the UI using nbextension. Use this option to display dashboards in jupyter notebooks (should work automatically).
• inline - to insert the UI directly into the cell. Use this option for Google Colab, Kaggle Kernels and Deepnote. For Google Colab this should work automatically, for Kaggle Kernels and Deepnote option should be specified explicitly.

Support for widget visualization in Colab and Pylab

• Supported dashboard visualization in Google Colab
• Supported dashboard visualization in python Pylab
• Added a parameter to switch on pylab visualization model: dashboard.show(mode='pylab')

Data Drift Monitoring with Grafana

• Added a way to calculate metrics with moving window
• Added metrics logging to Prometheus
• Added an example of Data Drift Monitoring with Prometheus and Grafana
• Added a config for Data drift dashboard at Grafana

Fix: Regression Performance Dashboard

Fix for #61

UI and architecture update

• Added the source code for the UI (now it can be built from the source)
• Created utils.py with helper functions
• Added config for Pylint
• Added some unit tests

Dataset Drift and Customised Bins

Added the following options to configure data drift report:

• 'drift_conf_level' confidence level for the individual features (default value = 0.95)
• 'drift_features_share' - share of the drifted features to detect dataset drift (default value = 0.5)
• 'xbins' - the custom bins to plot in the datadrift table
• 'nbinsx' - the custom number of bins to plot in the datadrift table

If share of the features drifted at the 'drift_conf_level' confidence level is higher than the 'drift_features_share' threshold, than Dataset drift will be detected. Otherwise Dataset drift will not be detected.