semvec/pypi-packages huggingface dataset:
mojimoji 0.0.13
A fast converter between Japanese hankaku and zenkaku characters
Requires Python: >=3.7
Keywords: japanese

mojimoji
========

.. image:: https://github.com/studio-ousia/mojimoji/actions/workflows/test.yml/badge.svg
    :target: https://github.com/studio-ousia/mojimoji/actions/workflows/test.yml

.. image:: https://img.shields.io/pypi/v/mojimoji.svg
    :target: https://pypi.org/project/mojimoji/

.. image:: https://static.pepy.tech/personalized-badge/mojimoji?period=total&units=international_system&left_color=grey&right_color=orange&left_text=pip%20downloads
    :target: https://pypi.org/project/mojimoji/


A Cython-based fast converter between Japanese hankaku and zenkaku characters.

Installation
------------

.. code-block:: bash

    $ pip install mojimoji

Examples
--------

Zenkaku to Hankaku
^^^^^^^^^^^^^^^^^^

.. code-block:: python

    >>> import mojimoji
    >>> print(mojimoji.zen_to_han('アイウａｂｃ０１２'))
    ｱｲｳabc012
    >>> print(mojimoji.zen_to_han('アイウａｂｃ０１２', kana=False))
    アイウabc012
    >>> print(mojimoji.zen_to_han('アイウａｂｃ０１２', digit=False))
    ｱｲｳabc０１２
    >>> print(mojimoji.zen_to_han('アイウａｂｃ０１２', ascii=False))
    ｱｲｳａｂｃ012

Hankaku to Zenkaku
^^^^^^^^^^^^^^^^^^

.. code-block:: python

    >>> import mojimoji
    >>> print(mojimoji.han_to_zen('ｱｲｳabc012'))
    アイウａｂｃ０１２
    >>> print(mojimoji.han_to_zen('ｱｲｳabc012', kana=False))
    ｱｲｳａｂｃ０１２
    >>> print(mojimoji.han_to_zen('ｱｲｳabc012', digit=False))
    アイウａｂｃ012
    >>> print(mojimoji.han_to_zen('ｱｲｳabc012', ascii=False))
    アイウabc０１２


Benchmarks
----------

Library versions
^^^^^^^^^^^^^^^^

- mojimoji: 0.0.1
- `zenhan <https://pypi.python.org/pypi/zenhan>`_: 0.4
- `unicodedata <http://docs.python.org/2/library/unicodedata.html>`_: Bundled with Python 2.7.3

Results
^^^^^^^

.. code-block:: python

    In [19]: s = 'ＡＢＣＤＥＦＧ０１２３４５' * 10

    In [20]: %time for n in range(1000000): mojimoji.zen_to_han(s)
    CPU times: user 2.86 s, sys: 0.10 s, total: 2.97 s
    Wall time: 2.88 s

    In [21]: %time for n in range(1000000): unicodedata.normalize('NFKC', s)
    CPU times: user 5.43 s, sys: 0.12 s, total: 5.55 s
    Wall time: 5.44 s

    In [22]: %time for n in range(1000000): zenhan.z2h(s)
    CPU times: user 69.18 s, sys: 0.11 s, total: 69.29 s
    Wall time: 69.48 s

Links
-----
- `mojimoji-rs <https://github.com/europeanplaice/mojimoji-rs>`_: The Rust implementation of mojimoji
- `gomojimoji <https://github.com/rusq/gomojimoji>`_: The Go implementation of mojimoji
secdoc 0.1.2
A package for working with protein secondary structure
Requires Python: >=3.6

# SecDoc
## A simple Python module for working with protein secondary structure

# Pre-requisites
The following Python packages are required in order to use this package:
- `Biopython`; may require manual installation
- `subprocess` and `itertools`; these packages are included in most Python distributions.

Biopython also requires a working installation of DSSP in order to perform the required operations. The program can be installed with `sudo apt install dssp` on Debian Linux systems. For other platforms, consult the relevant package repository.

A full readme will be here eventually.