semvec/pypi-packages huggingface dataset:
shellang 0.0.7
shell customizing language
Requires Python: >=3.6

# shellang
```
tags:
	<b>: bold
	<u>: underlined
	<red>: red color
	<black>: black color
	<yellow>: yellow color
	<green>: green color
	<blue>: blue color
	<l>:list
	</>: finish or reset
```
using shellang you can customize your console
a test program using direct strings
```python
import shellang
shellang.load('<blue>hello</> from <u> python'>
```
### using <l> (list)
```python
import shellang
shellang.load('''<b><blue>hello</>
<l>list 1
<l>list2
<u>end''')
if you want to do with files
1. create New file with extention as '.shellang' or any other like'.txt'
```python
import shellang
shellang.load('file: filename')
```
### if you want to show files in this folder
```python
import shellang
shellang.load('file: sys:ls')#without space
```
#### in tags remove spaces do not put <span  style="color:red;">&lt; red &gt;</span> use only <span  style="color:green;">&lt;red&gt;</span> 
more features will be adding
fabada 0.1
Fully Adaptive Bayesian Algorithm for Data Analysis FABADA
Requires Python: >=3.5
Keywords: Astronomy,Image Denoising,Bayesian

FABADA is a novel non-parametric noise reduction technique which arise from the point of view of Bayesian inference that iteratively evaluates possible smoothed models of the data, obtaining an estimation of the underlying signal that is statistically compatible with the noisy measurements. Iterations stop based on the evidence $E$ and the $\chi^2$ statistic of the last smooth model, and we compute the expected value of the signal as a weighted average of the smooth models.
You can find the entire paper describing the new procces in (introduce link to arxiv).