semvec/pypi-packages huggingface dataset:
pyffmpeg-bin 1.8.0.1
FFmpeg wrapper for python
Keywords: ffmpeg,FFmpeg,audio,pyffmpeg

# pyffmpeg-bin

FFmpeg wrapper for python.

Same as pyffmpeg but its unserialised.

This unserialised version means the ffmpeg binary comes with it as a binary and needs
not be built at runtime.

The beautiful thing about it is that it comes with its own FFmpeg executable. It is compressed, making it the smallest you can find. And becuase its cross-platform and python 3, it is the only option available for building cross-platform apps with ffmpeg in python.


## Installation
    pip install pyffmpeg

## Usage
```python
from pyffmpeg import FFmpeg

inp = 'path/to/music_folder/f.mp4'
out = 'path/to/music_folder/f.mp3'

ff = FFmpeg()

output_file = ff.convert(inp, out)

print(output_file)


```

## Advanced Usage
```python
from pyffmpeg import FFmpeg
```

### Use a global directory to store all converted files
```python
ff = FFmpeg('path/to/app_folder')
ff.convert('path/to/music_folder/f.mp3', 'f.wav')
```

### Overwrite (Default is set to True)
```python
ff.overwrite = False # do not overwrite but exit immediately
```

## Wiki
The wiki can be located [here](https://github.com/deuteronomy-works/pyffmpeg/wiki)
canvasutils 0.4.1
Utilities for interacting with Canvas using Python and the canvasapi.
Requires Python: >=3.7,<4.0

# CanvasUtils
[![PyPI version](https://badge.fury.io/py/canvasutils.svg)](https://badge.fury.io/py/canvasutils)

Utilities for interacting with Canvas using Python and the canvasapi.

## Installation

```bash
pip install canvasutils
```

`canvasutils` depends on the `ipywidgets` packages. To make sure widgets render correctly in notebooks, you may need to enable the widgets extension in Jupyter following [these instructions in the ipywidgets docs](https://ipywidgets.readthedocs.io/en/latest/user_install.html#installation), in particular, follow [these instructions](https://ipywidgets.readthedocs.io/en/latest/user_install.html#installing-the-jupyterlab-extension) if using Jupyter Lab.

## Features

- Submit files to Canvas from within a Jupyter notebook with user-friendly widgets.
- Convert files to formats like `.html` from with canvas.
- Create assignments (coming)
- Create assignment rubrics (coming)

## Dependencies

See the file [pyproject.toml](pyproject.toml), under the section `[tool.poetry.dependencies]`.

## Usage

### Assignment Submission in Jupyter

The submit module is made to be used within a Jupyter notebook (.ipynb file). See the provided [example.ipynb](example.ipynb). There are two available submission interfaces, widget-based drop-down menus, or text-based entries.

#### Widget Submission

![widget_gif](docs/img/canvasutils_widget.gif)

```python
api_url = "https://canvas.instructure.com/"
course_code = 123456

from canvasutils.submit import submit
submit(course_code, api_url=api_url, token=False)  # token=False allows you to enter token interactively
```

#### Text-based Submission

![text_gif](docs/img/canvasutils_text.gif)

```python
submit(course_code, api_url=api_url, token=False, no_widgets=True)
```

### Notebook Conversion in Jupyter

Note that this command will convert the most recently saved version of a notebook. *You should save your notebook before executing this command in a cell*.

```python
from canvasutils.submit import convert_notebook
convert_notebook('example.ipynb', to_format="html")

Notebook successfully converted!
```

## Contributors

Contributions are welcomed and recognized. You can see a list of contributors in the [contributors tab](https://github.com/TomasBeuzen/canvasutils/graphs/contributors).

### Credits

This package was originally based on [this repository](https://github.com/eagubsi/JupyterCanvasSubmit) created by Emily Gubski and Steven Wolfram.
extPep-identifier-blackjack 0.0.9
Extended peptides identification given mass-spec search result and custom proteomic database
Requires Python: >=3.6

# ExtPep_identifier
_Xinhao Shao @Collage of Pharmacy, University of Illinois at Chicago_<br/>
## Purpose of the script
ExtPep_identifier allows researchers to efficiently identify potential extended peptides given mass-spec search results
and custom database. The extended peptides can be identified after mapping all of the identified peptides to a custom extended
database, followed by a standard non-extended database.
## Usage
**1. Package installation**<br/>
Install the package by running:<br/>
_pip install extPep-identifier-blackjack==0.0.9(or current version)_<br/><br/>
**2. Import the package**<br/>
_import ExtPep_identifier_<br/><br/>
**3. Prepare for a few parameters before calling main function**<br/>
\# a list of identified peptides strings, ex. ['PEPTIDE','TIDEPEP']<br/>
_peptide_list=your_peptide_getter_function(search_result_file)_ <br/><br/>
\# a dictionary structure with identified peptide with key, the number of times such peptide being identified as value, ex. {'PEPTIDE':4,'TIDEPEP':5}<br/>
_psm_dictionary = your_psm_getter_function(search_result_file)_ <br/><br/>
\# a dictionary structure with protein ID as key, it's extended sequence as value, ex. {'P1':'PEPTIDEPEP'}<br/>
_merged_protein_dictionary = your_fasta_reader(custom_ext_database_file_path)_<br/><br/>
\# a dictionary structure with protein ID as key, it's original sequence as value, ex. {'P1':'PEPTIDEP'}<br/>
_original_protein_dictionary = your_fasta_reader(original_db_file_path)_<br/><br/>
**4. Calling main function**<br/>
_ext_pep_list, ext_psm_list, ext_protein_set 
= ExtPep_identifier.\_\_main\_\_(peptide_list,psm_dictionary,merged_protein_dictionary,original_protein_dictionary)_




## How to cite:
_Kyle Mangano, Tanja Florin, Xinhao Shao, Dorota Klepacki, Irina Chelysheva, Zoya Ignatova, Yu Gao, Alexander Mankin,  View ORCID ProfileNora VÃ¡zquez-Laslop
"Genome-wide effects of the antimicrobial peptide apidaecin on translation termination", accepted by eLife_