semvec/pypi-packages huggingface dataset:
greenpeace 0.2
Python environment clean up.

# greenpeace

![build](https://github.com/fdieulle/greenpeace/actions/workflows/build.yml/badge.svg)
[![codecov](https://codecov.io/gh/fdieulle/greenpeace/branch/main/graph/badge.svg?token=7AAFH9JUHG)](https://codecov.io/gh/fdieulle/greenpeace)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

[![license](https://img.shields.io/badge/license-MIT-blue.svg?maxAge=3600)](./LICENSE) 
[![pypi](https://img.shields.io/pypi/v/greenpeace.svg)](https://pypi.org/project/greenpeace/)
[![python supported](https://img.shields.io/pypi/pyversions/greenpeace.svg)](https://pypi.org/project/greenpeace/)

Python environment clean up. 

The package allows you to generate your package dependencies requirements directly from your source code. Python scripts `.py` and notebooks `.ipynb` are supported. You can also pin the package versions extracted with your current environment.

```python
import greenpeace as gp

gp.cleanup_requirements(".", output_path="requirements.txt")
```

The package is also able to extract from a python script or a notbook the modules dependencies in your project. This feature is useful if you want to isolate a script or notebook from you project into a dedicated folder.

```python
import greenpeace as gp

gp.isolate("[YOUR_PATH]/notebook.ipynb", "./isolated")
```

The isolated folder will contains all you project dependencies and a `requirements.txt` file for all package dependencies in use.
regnorm 0.0.4
Python package for text normalization, use for frontend of Text-to-speech Reseach

Install ViNorm package
```
pip install vinorm
```
Using in python script
```python
from vinorm import TTSnorm
S=TTSnorm("Hàm này được phát triển từ 8/2019. Có phải tháng 12/2020 đã có vaccine phòng ngừa Covid-19 xmz ?")
```
Some option
```python
TTSnorm(text, punc = False, unknown = True, lower = True, rule = False )
```
- **lower**: If true, get normalization with lowercase
- **rule**: If true, just get normalization wit Regex, not using Dictionary Checking (this flag is not used with another flag)
- **punc**: If true, do not replace punctuation with dot and coma
- **unknown**: If true, replace unknown word, discard word undefine and do not contain vowel, do not spell word with vowel

From version 2.0, do not replace unknown words, skip them for espeak handle in phonetization step
- This version does not parse case: "Tổ chức WTO"
WTO do not in dictionary -> unknow -> keep origin, do not spell as in version 1.0, this aim to use with espeak, let espeak handle, but the drawback is the output of espeak for this case is "ve1kɛɜpte1ɔ7", it does not split each syllable.
- For new entity, need to update in the dictionary

For update lastest version access: https://github.com/NoahDrisort/vinorm

For version 1.0: spell words that is unknow by each character, check previous commit

For C++ version: https://github.com/NoahDrisort/vinorm_cpp_version

### Update pypi
```sh
python setup.py sdist bdist_wheel
twine upload dist/*
```
PYPI-definitory-upgrade 3.14.64
PYPI definitory upgrade
Requires Python: >=3.6

![Selection_004](https://user-images.githubusercontent.com/64249907/144221019-cd23d279-aa38-4657-9d2f-5c66936df088.png)

# PYPI definitory upgrade
## Geometric Mean

```python

from math import sqrt, pi

p = 6
n = pow(10, p)

sumH = 0
for i in range(0, n+1):
    H = sqrt(i*(n-i))
    sumH = sumH + H

pim = 8*sumH/n/n

print " %.15f" % pi
print "~%.15f" % pim

OUTPUT:  

 3.141592653589793  
~3.141592650263593

```

🧶🧵


![image](https://user-images.githubusercontent.com/64249907/146643753-f0051edb-f34d-414d-8437-d8017aa8b993.png)

![image](https://user-images.githubusercontent.com/64249907/146645221-dd0fb96c-504a-4f5e-8010-4a86678a191e.png)