Merge branch 'enhancement/tutorial_serialization' into 'dev'

Enhancement/tutorial serialization

See merge request cdd/QSPRpred!190

CHANGELOG.md

@@ -1,49 +1,17 @@
 # Change Log
 
-From v3.0.2 to v3.1.0
+From v3.1.1 to v3.1.2
 
 ## Fixes
 
-- Fixed a bug in `QSPRDataset` where property transformations were not applied.
-- Fixed a bug where an attached standardizer would be refit when calling
-  `QSPRModel.predictMols` with `use_applicability_domain=True`.
-- Fixed random seed not set in `FoldsFromDataSplit.iterFolds` for `ClusterSplit`.
 
 ## Changes
 
-- renamed `PandasDataTable.transform` to `PandasDataTable.transformProperties`
-- moved `imputeProperties`, `dropEmptyProperties` and `hasProperty` from `MoleculeTable`
-  to `PandasDataTable`.
-- removed `getProperties`, `addProperty`, `removeProperty`, now use `PandasDataTable`
-  methods directly.
-- Since the way descriptors are saved has changed, this release is incompatible with
-  previous data sets and models. However, these can be easily converted to the new
-  format by adding
-  a prefix with descriptor set name to the old descriptor tables. Feel free to contact
-  us if you require assistance with this.
-- Due to some changes in `rdkit-2023.9.6`, the `add_rdkit`
-  option for molecule tables temporarily might not work.
-  This also affects the current ChemProp integration, which was not adapted to 2.0.0 yet.  
-  In order to prevent these issues, QSPRpred now forces rdkit version `rdkit-2023.9.5`, 
-  but we will be working on resolving these.
 
 ## New Features
 
-- Descriptors are now saved with prefixes to indicate the descriptor sets. This reduces
-  the chance of name collisions when using multiple descriptor sets.
-- Added new methods to `MoleculeTable` and `QSARDataset` for more fine-grained control
-  of clearing, dropping and restoring of descriptor sets calculated for the dataset.
-    - `dropDescriptorSets` will drop descriptors associated with the given descriptor
-      sets.
-    - `dropDescriptors` will drop individual descriptors associated with the given
-      descriptor sets and properties.
-    - All drop actions are restorable with `restoreDescriptorSets` unless explicitly
-      cleared from the data set with the `clear` parameter of `dropDescriptorSets`.
-- Added a proper API for parallelization backend selection and configuration (see
-  documentation of `ParallelGenerator` and `JITParallelGenerator` for more information).
-- Clusters can now be added to a `MoleculeTable` with `addClusters` and retrieved with
-  `getClusters`, similar to scaffolds.
+- added a tutorial on model and data serialization
 
 ## Removed Features
 
-- removed support for PyBoost since the project was abandoned by the original developers and is [no longer maintained](https://github.com/sb-ai-lab/Py-Boost/graphs/contributors)
+

tutorials/README.md

@@ -44,9 +44,11 @@ the [documentation pages](https://cddleiden.github.io/QSPRpred/docs/).
         - [Logging](basics/modelling/logging.ipynb): How to set-up logging.
         - [Model Assessment](basics/modelling/model_assessment.ipynb): How to assess the
           performance of a model.
-    - Benchmarking
-        - [Benchmarking](basics/benchmarking/benchmarking.ipynb): How to benchmark
+    - Other
+        - [Benchmarking](basics/other/benchmarking.ipynb): How to benchmark
           QSPRpred.
+        - [Serialization](basics/other/serialization.ipynb): How to save and
+          load datasets and models.
 - **Advanced**
     - Data
         - [Parallelization](advanced/data/parallelization.ipynb): How to parallelize