# Release 0.8.23

!!!tip inline end "Need Help?"
    The SuperCowPowers team is happy to give any assistance needed when setting up AWS and SageWorks. So please contact us at [sageworks@supercowpowers.com](mailto:sageworks@supercowpowers.com) or on chat us up on [Discord](https://discord.gg/WHAJuz8sw8) 

The SageWorks framework continues to flex to support different real world use cases when operating a set of production machine learning pipelines.

**Note:** These release notes cover the changes from `0.8.22` to `0.8.23`


### General
Mostly bug fixes and minor API changes.

### API Changes

- **Removing `auto_one_hot` arg from `PandasToFeatures` and `DataSource.to_features()`**
    
    When creating a `PandasToFeatures` object or using `DataSource.to_features()` there was an optional argument `auto_one_hot`. This would try to automatically convert object/string columns to be one-hot encoded. In general this was only useful for 'toy' datasets but for more complex data we need to specify exactly which columns we want converted.
  
- **Adding optional `one_hot_columns` arg to `PandasToFeatures.set_input()` and `DataSource.to_features()`**  
    
    When calling either of these FeatureSet creation methods you can now add an option arg `one_hot_columns` as a list of columns that you would like to be one-hot encoded.
	
### Minor Bug Fixes
Our pandas dependency was outdated and causing an issue with an `include_groups` arg when outlier groups were computed. We've changed the requirements:

```
pandas>=2.1.2
to
pandas>=2.2.1
```
We also have a ticket for the logic change so that we avoid the deprecation warning.
 
### Improvements
The time to `ingest` new rows into a FeatureSet can take a LONG time. Calling the FeatureGroup AWS API and waiting on the results is what takes all the time.

There will hopefully be a series of optimizations around this process, the first one is simply increasing the number of workers/processes for the ingestion manager class.

```
feature_group.ingest(.., max_processes=8)
(has been changed to)
feature_group.ingest(..., max_processes=16, num_workers=4)
```

## Questions?
<img align="right" src="../../images/scp.png" width="180">

The SuperCowPowers team is happy to answer any questions you may have about AWS and SageWorks. Please contact us at [sageworks@supercowpowers.com](mailto:sageworks@supercowpowers.com) or on chat us up on [Discord](https://discord.gg/WHAJuz8sw8) 


