semvec/pypi-packages huggingface dataset:
mqc 2.0.2
MQC is a Genome-scale metabolic network model quality control tool
Requires Python: >=3.6

# MQC: Genome-scale metabolic network model quality control tool

-----------------

## What is it?

**MQC** is a Genome-scale metabolic network model quality control tool

## Installing CPLEX Commercial Package

To use this program, you need to install the CPLEX commercial package. Follow these steps:

1. Visit the [IBM website](https://www.ibm.com/analytics/cplex-optimizer) and download the CPLEX installation package suitable for your operating system.

2. Install CPLEX by following the instructions provided with the downloaded installation package.

3. After the installation is complete, ensure that the correct environment variables are set so that your program can find CPLEX. You may need to add the installation directory of CPLEX to the PATH environment variable.


If you encounter any issues, refer to the [IBM CPLEX documentation](https://www.ibm.com/support/knowledgecenter/SSSA5P_12.10.0/COS_KC_home.html) or contact their support team.

OR 

```
$ cd /hpcfs/fhome/mao_zt/project/MCModel/cplex_new/CPLEX221/python  
$ python setup.py install
```
## Install this program. 

You can do this via pip by running the following command:

   ```
   pip install mqc
   from mqc import main
   model_control_infos, final_model = main.run(model_file:str,output_dir:str)
   ```
   ```
   mqc --file path/model.xml --outputdir path/outputdir
   ```
## JSON 转网页

通过安装mqc包进行质控，得到的json文件可以转为网页，便于可视化观看，下面提供3种途径：

1. Windows端打开https://d1e9ilirjteg2w.cloudfront.net/tools/mqc-viewer.zip， 下载mqc-viewer.zip压缩包，解压后打开其中的exe文件，上传质控后的json文件即可

2. 通过网页https://mqc.biodesign.ac.cn/view 上传

3. Mac端打开https://d1e9ilirjteg2w.cloudfront.net/tools/mqc.dmg， 下载macOS的安装包mqc.dmg进行上传

## Run the example

```sh
# get projects
git clone http://172.16.25.29/dengxiao/mqc.git

cd mqc

# create env

conda env create -f environments.yaml

conda activate mqc


# run
python start.py -h

# 结果输出在当前路径
python start.py --file ./mqc/test_data/bigg_data/iCN718.xml 

# 指定结果输出路径
python start.py --file ./mqc/test_data/bigg_data/iCN718.xml -o /tmp/test1
```

input : model file

output : 
    result.json :  self.result_file
    new model file : f"{cfg.ROOT}/{model.id}.xml" or f"{cfg.ROOT}/{model.id}.json" (mqc/utils.py - write_final_model())
vsoneliner 0.0.2.post1
Commandline program for creating Python script for VSPipe
Requires Python: >=3
Keywords: VapourSynth

# vsoneliner

vsoneliner generates VapourSynth script file for VSPipe from commandline. It is for the situation where only the simplest VapourSynth script is needed, and where writing and keeping a script file becomes cumbersome.  

Install vsoneliner:  
```sh
python -m pip install vsoneliner
```

An Example of using vsoneliner using [fish shell](https://fishshell.com/):  
```fish
INPUT=(realpath "input.mkv") vspipe (python -m vsoneliner "import mvsfunc as mvf" "r\"$INPUT\" |> core.lsmas.LWLibavSource |> mvf.Depth\$(depth=10) |> .set_output()") -c y4m - | x264 --demuxer y4m --output "output.mkv" -
```
Excerpt:  
```
python -m vsoneliner "import mvsfunc as mvf" "r\"$INPUT\" |> core.lsmas.LWLibavSource |> mvf.Depth\$(depth=10) |> .set_output()"
```

* Each positional argument to vsoneliner corresponds to one line in the resulting Python script. In this example, we have two lines: `import mvsfunc as mvf` and `r"INPUT" |> core.lsmas.LWLibavSource |> mvf.Depth$(depth=10) |> .set_output()`.  
* vsoneliner by default imports `from vapoursynth import core` and `import vapoursynth as vs`, but any additional imports have to be written manually, such as `import mvsfunc as mvf` in the example.  
* vsoneliner accepts [Coconut](https://coconut-lang.org/) language in the commandline. Coconut language's syntax is a strict superset of Python, which means if you don't want to learn it, you can write vanilla Python code and it will work just fine. Here in this example, `r"INPUT" |> core.lsmas.LWLibavSource |> mvf.Depth$(depth=10) |> .set_output()` transpiles to `mvf.Depth(core.lsmas.LWLibavSource(r"INPUT"), depth=10).set_output()`.  
* vsoneliner saves the commands to a Python file with `.vpy` file extension and then print the path to the file to stdout before exiting. Use `$()` in a POSIX shell to feed this file to vspipe. vsoneliner also accepts `--verbose` argument, with which vsoneliner will also print the path to the file to stderr.
Fkillera 1.0.0
A simple package for Fkillera
Requires Python: >=3.6

```markdown
# Fkillera

A simple Python package for Fkillera including addition and multiplication.

## Installation

```
sh
pip install Fkillera
```
## Usage

```
python
from Fkillera import add_matrices, multiply_matrices

matrix1 = [[1, 2], [3, 4]]
matrix2 = [[5, 6], [7, 8]]

# Add matrices
result_add = add_matrices(matrix1, matrix2)
print(result_add)  # Output: [[6, 8], [10, 12]]

# Multiply matrices
result_multiply = multiply_matrices(matrix1, matrix2)
print(result_multiply)  # Output: [[19, 22], [43, 50]]