semvec/pypi-packages huggingface dataset:
voicebot-accounts 0.2
A reusable Django accounts app.
License: MIT

## Configuring Template Base in Django

This guide will help you configure a base template path in your Django settings and use it in your templates.

### Step 1: Define `TEMPLATE_BASE` in `settings.py`

Add the following line to your `settings.py` file:

```python
# settings.py
TEMPLATE_BASE = 'base.html'  # Define your base template path
```

### Step 2: Add the Context Processor to settings.py

```python
# settings.py
TEMPLATES = [
    {
        .....
        'OPTIONS': {
            'context_processors': [
                .......
                'voicebot_accounts.context_processors.template_base',  # Add your custom context processor here
                .......
            ],
        },
        .....
    },
]
```
soraya 0.0.9
Soraya is a package that selects the most important features using an innovative hybrid method for both regression and classification problems.
License: MIT
Requires Python: >=3.6


### soraya 
**Soraya** is a package for selecting the most important features that has been developed using an innovative **hybrid method**. Soraya identifies and selects the most relevant features for **regression** and **classification** tasks.


### Installation
 The following libraries and packages are utilized by **soraya**: **scikit-learn**, **shap**, **tqdm**, **numpy**, **xgboost** and **pandas**.Therefore, it’s necessary to install all these packages. If you encounter an **error**, it is probably due to the conflict of different versions of the packages, so be sure to install the following versions using the commands below:

pip install scikit-learn==1.3.2 , pip install shap==0.44.1 , pip install tqdm==4.66.4 , pip install numpy==1.24.4 , pip install xgboost==2.0.3 , pip install pandas==2.0.3


**Note:** If you encounter any difficulties installing these packages on your local system, you can utilize the **Google colab** environment to install and utilize them seamlessly.

### How to use soraya
After installing soraya, simply execute the following two lines of code.
> from soraya import Main 

> print(Main())