> For the complete documentation index, see [llms.txt](https://docs.shimoku.com/dev/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.shimoku.com/dev/releases/2022/v.0.10.md).
# v.0.10
{% hint style="danger" %}
This version has been deprecated. If used with the current API version it can produce unexpected behaviour or errors.
{% endhint %}
{% hint style="danger" %}
The package shimoku-api-python is no longer maintained
{% endhint %}
{% hint style="info" %}
To get the new version :gift::gift::gift:
{% endhint %}
```
pip install --upgrade shimoku-api-python
pip install --upgrade shimoku-components-catalog
```
{% hint style="info" %}
This version brings **Machine Learning** features through our API by the first time!!
{% endhint %}
### Fixes
* For readability, renamed `s.file.*` by `s.io.*`:
Before: `s.file.get_dataframe(...)`
Now: `s.io.get_dataframe(...)`
* Fixed IO for large dataframes now you can POST and GET dataframes of large sizes without size limit.
* Fix path and subpaths. Now Apps with multiple words can be sorted too: `s.plt.set_apps_orders()` and `s.plt.set_sub_path_orders()`
* Fixes in the default look\&feel of different charts and with new features to see data, download image, zoom in and out and change chart type:
* Heatmap `s.plt.heatmap()`
* Barchart `s.plt.bar()` and Linechart `s.plt.line()`
### Improvements
* Improvements in the Input Forms look\&feel
* Easier to initialize the Shimoku Client
```python
import shimoku_api_python as Shimoku
# Still allowed
s = Shimoku.Client(
config={'access_token': api_key},
universe_id=universe_id,
environment=environment
)
# Easier
s = Shimoku.Client(
access_token=api_key,
universe_id=universe_id,
environment=environment
)
```
* Added IO methods for Machine Learning models:
```python
from sklearn import svm
from sklearn import datasets
clf = svm.SVC()
X, y = datasets.load_iris(return_X_y=True)
clf.fit(X, y)
s.io.post_ai_model(
business_id=business_id,
app_name='test',
model_name='model-object-test',
model=clf,
)
model = s.io.get_ai_model(
business_id=business_id,
app_name='test',
model_name='model-object-test',
)
```
### New
* Added method to clear a whole business (tabula rasa) `shimoku.plt.clear_business()`
Before
```
s.plt.clear_business()
```
* Added method to retrieve input forms data
```
input_data: List[Dict] = s.plt.get_input_forms(menu_path='test/input-form')
```
### Machine Learning!
* **AI** for Machine Learning features. Now users can use Shimoku's Machine Learning from the SDK just passing a test dataframe and specifying the Model endpoint (ask to Shimoku about what endpoints are available). You can decide whether to add Explainability or not to the predictions
```python
df_pred, df_error = s.ai.predict_categorical(
df_test=df_test_fail,
model_endpoint=model_endpoint,
explain=False,
)
```
Also predictive tables have been added that create a table with the prediction
```python
target_column: str = 'NRO_POL'
column_to_predict: str = 'churn_probability'
menu_path: str = 'AI/Churn'
order: int = 0
s.ai.predictive_table(
df_test=df_test,
model_endpoint=model_endpoint,
target_column=target_column,
column_to_predict=column_to_predict,
prediction_type='categorical',
explain=True,
menu_path=menu_path, order=order,
add_filter_by_column_to_predict=False,
add_search_by_target_column=True,
extra_filter_columns=None,
extra_search_columns=None
)
```
---
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