semvec/pypi-packages huggingface dataset:
pytunnel 2.4.2
A TCP tunnel server/client by Python.
Keywords: pytunnel,tunnel,proxy,socket

pytunnel
===============
A TCP tunnel server/client by Python.

Install
===============
```
 pip install pytunnel
```

Useage
===============
If you want local computer port 8080 can be access through server(IP:192.168.1.102) port 1090

Setp1. Run the following command at server computer:

```bash
python -m pytunnel --bind 0.0.0.0:1990
```

It will start a tunnel server at port 1990.

Setp2. Run the following command at local computer:
```bash
python -m pytunnel --port 1090 --target 127.0.0.1:8080 --server 192.168.1.102:1990
```

It will make a tunnel with 192.168.1.102:1090 and 127.0.0.1:8080.

Now, you can open 192.168.1.102:1090 to access the local computer port 8080.

Other
===============

You can use ```-e``` to set the password:

```bash
# server
python -m pytunnel --bind 0.0.0.0:1990 -e "abcdef"
# client
python -m pytunnel --port 1090 --target 127.0.0.1:8080 --server 192.168.1.102:1990 -e "abcdef"
```

Client can use ```-c``` to excute a command at the server computer:

```bash
# show server status
python -m pytunnel --server 192.168.1.102:1990 -c "status"

# let server exit
python -m pytunnel --server 192.168.1.102:1990 -c "exit"

# kill some client, the client-key can found with "status" command
python -m pytunnel --server 192.168.1.102:1990 -c "kill client-key"
```

[Click to view more information!](https://github.com/sintrb/pytunnel)


CHANGES
===============
1.0.0

- First version

2.0.0

- Optimize data package

2.1.0

- Fix bugs
- Use multiprocessing to improve throughput capacity

2.3.0

- Add watch dog to check status
Time-Corrector 1.0.1
An acquisition time correction tool based on the retention index system for LC-MS data
Keywords: LC-MS,RI system,RT Correct,MS Data

In large-scale metabolomic analysis, it is crucial to preprocess and integrate the raw LC-MS data from run to run, determining the accuracy of follow-up statistical comparation and qualitative analysis. Currently, various peak alignment algorithms have been developed, such as the Joint aligner algorithm and the kernel estimation procedure based algorithm in XCMS. Above algorithms rely on the accurate m/z and RT of features to align chromatographic peaks, and can effectively correct random RT shifts caused by variations in column temperature and slight differences in biological samples. However, their ability to correct systematic RT shifts caused by variations in mobile phase composition, column, and instrumental conditions remains limited. Particularly in large-scale metabolomics analysis, severe systematic RT shifts can result in misalignment or cross-alignment of peaks, leading to reduced alignment accuracy and, in turn, affecting downstream statistical analysis and identification of metabolites. N-alkylglycine RI system can well correct the drift of RT. Based on this, we consider that RI technique can be used as a “time corrector” to adjust the acquisition time during the whole LC-MS analysis process.
dpyselfembed 0.0.4
A package to allow discord users to use embeds again

# dpyselfembed
A way for selfbots to send embeds again.  
It uses [Rauf's embed generator](https://embed.rauf.wtf/).

### Install
> ```bash
> $ pip install dpyselfembed
> ```

### Example
> ```python
> import dpyselfembed
> 
> embed = dpyselfembed.Embed("dpyselfembed", 
>   description="A way for selfbots to send embeds again.", 
>   colour="ff0000"
> )
> embed.set_author("Benny")
> 
> url = embed.generate_url(hide_url=True) # You can also convert the embed to a string.
> print(url) # The url will be put in your ctx.send() content.
> ```

### Limitations
> Because the embeds are web embeds there are limitations.  
> - No footers.
> - Max 350 character description.

### Credits
> Used code from [Discord.py Self Embed](https://github.com/bentettmar/discord.py-self_embed)
noteyXMLParser 0.2.10
Music XML Parser

my parser

https://betterscientificsoftware.github.io/python-for-hpc/tutorials/python-pypi-packaging/

create Package:
sudo rm -rf dist/
python setup.py check
python setup.py sdist
python setup.py bdist_wheel --universal

upload:
twine upload dist/\*

TODO:
https://blog.dennisokeeffe.com/blog/2021-08-11-automating-pip-package-deployment-with-github-actions