semvec/pypi-packages huggingface dataset:
pyfferaph 0.0.1a4
PYthon Functions For Extended, Reproducible Analysis and graPH
Requires Python: >=3.6, <4
Keywords: network,protein,pyfferaph

# Installation

```
conda create -n pyfferaph python=3.6
conda activate pyfferaph
```

On linux:
```
pip install --upgrade pyfferaph
```

On Mac/Windows, you need first to install the dependencies.

```
conda install -c conda-forge MDAnalysis
pip install --upgrade pyfferaph
```

```bash
# filter_pyff
# ============
#
# filter_pyff script works on adjacency matrix files, such as as those outputted by Pyinteraph (add reference)
# The script is designed to:

#1) return and save to file a macro_iin.dat file starting from separete interaction matrices (salt bridges, hydrogen bonds, hydrophobic interactions)
# Each interaction in each interaction matrix is retained only if above a certaint treshold value (-p option) if provided (default value 0.0).
# The filtered matrices arte then combined to generate a macro_iin.dat file,
# an edge between two nodes is drawn if that interaction is above treshold in at least one filterd interaction matrix

threshold=5.0
filter_pyff -d sb_graph.dat -d hb_graph.dat -d hc_graph.dat -p $threshold -o out_macro_iin.dat

#2) Generate an intercation network G based on either separate interaction matrices or a macro IIN file. A topology file is required (option -g)
# compute all shortest paths between a set of source and target residues defined in a json formatted input file (option -z).
# A json-formatted file can be obtained with:

filter_pyff -j template.json

# A score is assigned for each path of a given source-target pair.
# Identify the best path (or equally best pahts) among all paths connecting source and target residues
# Calculate the communication robustness index for each source-target pathway (a pathway is define as the set of all the shortest paths connecting source and taget)
# Print to file all the above mentioned informations. The script saves one file for each source residue. Eache file contains all patht between that source and all the target resiudes.

#starting from separete interaction matrices:

filter_pyff -d sb_graph.dat -d hb_graph.dat -d hc_graph.dat -p $treshold -o out_macro_iin.dat -g topol.gro -z z_file.json

#starting from a macro_iin.dat file

filter_pyff -i macro_iin.dat -g topol.gro -z z_file.json

#3) Compute the selective betweeness for a given redidue (option -s) considering all shortest path between a given source and target file (option -t)

filter_pyff -d sb_graph.dat -d hb_graph.dat -d hc_graph.dat -p $treshold -o out_macro_iin.dat -g topol.gro -s RES1 -t RES2 RES3

#or

filter_pyff -i macro_iin.dat -g topol.gro -s RES1 -t RES2 RES3
```
Multporn 0.0.1
python library used to interact with multporn.net via python
Requires Python: >=3.6

![Pip Package](https://github.com/pyporn-san/MPdownloader/workflows/Upload%20Python%20Package/badge.svg)
# python multporn scraper

multporn is a Python library used to interact with [multporn](https://multporn.net/) via python.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install multporn.

```bash
pip install multporn
```

## Usage

```python
from multporn import Multporn

comic = Multporn("https://multporn.net/comics/between_friends")

print(comic) # Between Friends
print(comic.tags) # ['Best', 'Blowjob', 'Cunnilingus', 'Lolicon', 'Oral sex', 'Stockings', 'Straight', 'Straight Shota', 'Virgin']
comic.downloadImages() # Downloads the comic to /comic/Between Friends/
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[GPL V3.0](https://choosealicense.com/licenses/gpl-3.0/)