semvec/pypi-packages huggingface dataset:
pyhfst 1.4.0
A pure Python implementation of HFST for using HFST optimized lookup transducers (with or without weights)
License: Apache-2.0
Keywords: hfst, fst, optimized lookup, hfstol, transducers

# Pyhfst

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7791470.svg)](https://doi.org/10.5281/zenodo.7791470)

Pyhfst is a pure Python implementation of HFST. The library makes it possible to use HFST optimized lookup FSTs without any C dependencies. Both weighted and unweighted FSTs are supported.

The library will run on all operting systems that support Python 3.

# Installation

    pip install pyhfst
    
Pyhfst can run way faster if you have Cython installed. After installing Cython, you must reinstall Pyhfst

    pip install cython
    pip install --upgrade --force-reinstall pyhfst --no-cache-dir

# Usage

    import pyhfst
    
    input_stream = pyhfst.HfstInputStream("./analyser")
    tr = input_stream.read()
    print(tr.lookup("voi"))
    
    >> [['voida+V+Act+Ind+Prs+Sg3', 0.0], ['voida+V+Act+Ind+Prs+ConNeg', 0.0], ['voida+V+Act+Ind+Prt+Sg3', 0.0], ['voida+V+Act+Imprt+Prs+ConNeg+Sg2', 0.0], ['voida+V+Act+Imprt+Sg2', 0.0], ['voi+N+Sg+Nom', 0.0], ['voi+Pcle', 0.0], ['voi+Interj', 0.0]]

# Citation

Please cite the library as follows:

Alnajjar, K., & Hämäläinen, M. (2023, December). PYHFST: A Pure Python Implementation of HFST. In Lightning Proceedings of NLP4DH and IWCLUL 2023 (pp. 32-35).

    @article{pyhfst_2023, 
        title={PyHFST: A Pure Python Implementation of HFST},
        author={Alnajjar, Khalid and H{\"a}m{\"a}l{\"a}inen, Mika},
        booktitle={Lightning Proceedings of NLP4DH and IWCLUL 2023},
        pages={32--35},
        year={2023} 
    }
bioat 0.16.4
bioat, a python package & command line toolkit for Bioinformatics and data science!
License: Apache-2.0
Requires Python: <4.0,>=3.10.0
Keywords: bioat, bioinformatics, data science, deep learning

# BioAT
the Bioinformatic Analysis Tools
## About bioat
Bref:  <u>**bioat**, a python **package** & **command line toolkit** for Bioinformatics and data science!</u>

Home: https://github.com/hermanzhaozzzz/bioat

License: Apache-2.0

| Name | Downloads | Version | Platforms | Test |
| --- | --- | --- | --- | --- |
|[![Conda Recipe](https://img.shields.io/badge/recipe-bioat-green.svg)](https://anaconda.org/conda-forge/bioat) | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/bioat.svg)](https://anaconda.org/conda-forge/bioat) | [![Conda Version](https://img.shields.io/conda/vn/conda-forge/bioat.svg)](https://anaconda.org/conda-forge/bioat) | [![Conda Platforms](https://img.shields.io/conda/pn/conda-forge/bioat.svg)](https://anaconda.org/conda-forge/bioat) | [![Azure Pipelines](https://dev.azure.com/conda-forge/feedstock-builds/_apis/build/status/bioat-feedstock?branchName=main)](https://dev.azure.com/conda-forge/feedstock-builds/_build/latest?definitionId=23719&branchName=main) |

## About author
Name: [赵华男 | Huanan Herman Zhao](https://scholar.google.com/citations?user=ojSVoWQAAAAJ&hl=en) |  EMail: hermanzhaozzzz AT gmail.com | [Zhihu](https://www.zhihu.com/people/hymanzhaozzzz) | [BLOG](http://zhaohuanan.cc)

## Installation
```shell
# supported platform: Linux / MacOS (intel & arm64) / Windows
pip install --upgrade bioat
# use conda
conda install -c conda-forge bioat
```

## Usage
```shell
# list commands
bioat list
# check version
bioat version
# check information about bioat
bioat about

# example usage
bioat bam remove_clip --help
samtools view -h test_sorted_n.bam | bioat bam remove_clip | tail
```
[circos plot](docs/demo_circos-plot.ipynb)

## Doc

See [Doc](https://bioat.readthedocs.io/en/latest/)

## Citation
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15093444.svg)](https://doi.org/10.5281/zenodo.15093444)

```latex
@software{huanan_herman_zhao_2025_15093444,
  author       = {Huanan Herman Zhao},
  title        = {BioAT, a python package \& command line toolkit for
                   bioinformatics and data science
                  },
  month        = mar,
  year         = 2025,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.15093444},
  url          = {https://doi.org/10.5281/zenodo.15093444},
  swhid        = {swh:1:dir:19b60f4b0b93f490798727c05ab41a3222b555a1
                   ;origin=https://doi.org/10.5281/zenodo.15093443;vi
                   sit=swh:1:snp:793130e9e84df8cf427ab2b6a69c0dc77146
                   1e6a;anchor=swh:1:rel:dc0fa360dfdaf99222cf7db99e8e
                   e9e898ac1c64;path=hermanzhaozzzz-bioat-4b611f2
                  },
}
```