semvec/pypi-packages huggingface dataset:
noglobal-magic 0.1.3
magic command for prohibit using global variables in Jupyter Notebook
License: MIT
Requires Python: >=3.7
Keywords: jupyter-notebook

# noglobal-magic

[![Tests](https://github.com/tokusumi/noglobal-magic/actions/workflows/testing.yml/badge.svg)](https://github.com/tokusumi/noglobal-magic/actions/workflows/testing.yml)
[![PyPI version](https://badge.fury.io/py/noglobal-magic.svg)](https://badge.fury.io/py/noglobal-magic)

For Jupyter Notebook user's, [noglobal-magic](https://github.com/tokusumi/noglobal-magic) find global variables in a local scope.

With:
* No need to wait executing a function
* `flake8` style ignoring-error annotation (`# noqa`)
* `no_global` magic command makes raise error, and `warn_global` tells a just warning

## Installation

Make sure you've this `noglobal-magic` (And the Python package `pyflakes`).

```shell
pip install noglobal-magic
```

## How to use

In a cell on Jupyter Notebook, load and activate this extension:

```notebook
%load_ext noglobal_magic
%no_global
```

You've ready to enjoy coding.

Let's see in [colab](https://colab.research.google.com/drive/1y7Zr-RD2RPcSTjs0ml6vswbc96_IKt2y?usp=sharing) how it works.
eb7calculator 0.0.1
A simple calculator
License: MIT
Keywords: python,calc,calculator,cal,simple,basic

# This is a basic calculator
It can be used to add , subtract , multiple, divide two integers

## Installation
```
pip3 install eb7calculator
```

## Import

```python
from eb7calculator import calculator as calc

# or

from eb7calculator.calculator import add, sub, mul, div

```

## usage
```python
from eb7calculator import calculator as calc

calc.add(1,2)
# output:3

calc.sub(2,1)
# output:1

calc.mul(10,2)
# outout:20

calc.div(10,5)
# output:2.0
```
betterlog 0.0.2
Colorful logging
License: MIT


# EasyLog [![Downloads](https://pepy.tech/badge/easylog)](https://pepy.tech/project/betterlog)
## _Log Easily_

Easylog is a colorful console printing
- Import the module
- Use one of functions
- ? Magic ?

## Features

- Header
- Ok
- Info
- Success
- Warning
- Error

## Quick Tutorial
### Simple usage:
![alt text](https://i.postimg.cc/hG73VxDs/code.png)

### Output:
![alt text](https://i.postimg.cc/NF06kq8t/Capture.png)

## License
MIT

Contact me at Discord: https://discord.gg/mRnF6ypYyu
**Free Software, Hell Yeah!**
nullpom 0.1.0
Library to easily run Null Importances.
License: MIT
Requires Python: >=3.7.1,<4.0.0
Keywords: null importance,feature selection,importance,kaggle

[![Test with pytest](https://github.com/tenajima/nullpom/actions/workflows/pytest.yml/badge.svg)](https://github.com/tenajima/nullpom/actions/workflows/pytest.yml)
[![Format with black](https://github.com/tenajima/nullpom/actions/workflows/black.yml/badge.svg)](https://github.com/tenajima/nullpom/actions/workflows/black.yml)

# nullpom

Library to easily run Null Importances.

## About Null Importances

Null Importances is feature selection process using target permutation tests actual importance significance against the distribution of feature importances when fitted to noise (shuffled target).

### Detail
- [paper](https://academic.oup.com/bioinformatics/article/26/10/1340/193348)
- [kaggle notebook](https://www.kaggle.com/ogrellier/feature-selection-with-null-importances)
- [japanese article](https://qiita.com/trapi/items/1d6ede5d492d1a9dc3c9)

# Output
![output](https://raw.githubusercontent.com/tenajima/nullpom/main/img/distribution_of_importance.png)

# Basic usage

```python
from nullpom import run_null_importance

result = run_null_importance(
    {"objective": "binary", "seed": 42},
     X_train=X_train,
    X_valid=X_valid,
    y_train=y_train,
    y_valid=y_valid,
)
```

# Install
```sh
pip install nullpom
```