semvec/pypi-packages huggingface dataset:
mbs-cn 0.0.7
 博客管理器，可以管理多个博客的文章 
License: MIT
Keywords: blog 博客 博客园 简书

# mbs
博客管理器，可以管理多个博客的文章。

## 使用

### 1 安装

```shell
pip install mbs-cn
```

### 2 命令

```shell
usage: mbs [-h] [-cs] [-n CATEGORY MARKDOWN_FILE_PATH] [-d TITLE] [-sc FOLDER] [-uo PATH] [-ua FOLDER]

博客管理器

optional arguments:
  -h, --help            显示当前帮助信息，然后退出
  -cs, --categories     显示所有分类
  -n CATEGORY MARKDOWN_FILE_PATH, --new-post CATEGORY MARKDOWN_FILE_PATH
                        要上传的 markdown 文件的分类和路径
  -d TITLE, --delete TITLE
                        要删除的文章标题
  -sc FOLDER, --scan-changed-files FOLDER
                        扫描目标文件中所有有变化的文件
  -uo PATH, --update-one PATH
                        更新一个文件
  -ua FOLDER, --update-all FOLDER
                        更新指定目录中的所有文件
```

### 3 当前支持的博客

- 博客园
- 简书
- 思否
- 个人网站 / 博客

简书的图片不支持外链，所以采用异步的方式将所有外链图片上传到简书的图床中。
对于支持外链图片的博客，默认使用外链图片，不会上传到对应博客的图床。

### 4 问题

- [ ] 部分代码写得难看，因为能使用，暂时就没有优化

### 5 debug

默认日志是保存在文件里，不在终端输出，但有时可能会遇到执行一条命令后终端没有任何输出，查看日志或者启动 debug 可能会有帮助。

日志文件路径：

- windows  `%APPDATA%\mbs\mbs.log`
- Linux/Mac `$HOME/.config/mbs/mbs.log`

开启 debug 模式可以在终端也输出日志，因为日志文件一样可以看，所以此功能作用不大。开启方式为在当前终端设置环境变量`MBS_DEBUG=1`。

### 6 注意

当前仅对使用`mbs`上传的文章进行管理，其他已经上传的文章，需要自己想办法将有关数据添加到数据库中。

数据库文件与日志文件在同一个目录中。

### 7 效果图

1. 检查更新

![截屏2021-05-28 20.20.08](https://cdn.jsdelivr.net/gh/thep0y/image-bed/md/1622205011340.png)

![截屏2021-05-28 20.21.05](https://cdn.jsdelivr.net/gh/thep0y/image-bed/md/1622204816227.png)
toppics 0.1.1
A Python CLI for adding pre-defined topics to a GitHub repository.
License: MIT
Requires Python: >=3.6,<4.0
Keywords: toppics,cli,topics,github,api

# toppics

[![PyPI](https://img.shields.io/pypi/v/toppics)](https://pypi.org/project/toppics/)
[![Release](https://github.com/joaopalmeiro/toppics/actions/workflows/release.yml/badge.svg)](https://github.com/joaopalmeiro/toppics/actions/workflows/release.yml)
[![security: bandit](https://img.shields.io/badge/security-bandit-yellow.svg)](https://github.com/PyCQA/bandit)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

A Python CLI for adding pre-defined topics to a GitHub repository.

## Development

- `poetry install`
- `poetry shell`

## Tech Stack

- [Click](https://click.palletsprojects.com/) (for the interface)

### Packaging and Development

- [Poetry](https://python-poetry.org/)
- [Mypy](http://mypy-lang.org/)
- [isort](https://pycqa.github.io/isort/)
- [Black](https://github.com/psf/black)
- [Flake8](https://flake8.pycqa.org/)
  - [flake8-bugbear](https://github.com/PyCQA/flake8-bugbear)
  - [flake8-comprehensions](https://github.com/adamchainz/flake8-comprehensions)
  - [pep8-naming](https://github.com/PyCQA/pep8-naming)
  - [flake8-builtins](https://github.com/gforcada/flake8-builtins)
- [Bandit](https://bandit.readthedocs.io/)

This CLI was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [`joaopalmeiro/cookiecutter-templates/python-cli`](https://github.com/joaopalmeiro/cookiecutter-templates) project template.

## Notes

- [Replace all repository topics](https://docs.github.com/en/rest/reference/repos#replace-all-repository-topics).
- [ghapi](https://ghapi.fast.ai/) documentation:
  - `repos.replace_all_topics(owner, repo, names)`.
- [regex101](https://regex101.com/) website.
- [Click 7](https://click.palletsprojects.com/en/7.x/) documentation:
  - [Utils](https://click.palletsprojects.com/en/7.x/utils/).
- [Click 8](https://click.palletsprojects.com/en/8.0.x/) documentation.
- `toppics https://github.com/joaopalmeiro/toppics "Python CLI"`.
Japanese-BPE-Tokenizer 0.1.2
Mecab-based BPE toknizer for Japanese text
License: MIT

# Byte Pair Encoding for Japanese Language

## Summary
The package applies Mecab and Byte Pair Encoding algorithms to tokenize Japanese text.

## Usage
To train a new tokenizer, import the module
```
from jpn_bpe_tokenizer import MecabBPETrainTokenizer
```

Instantiate the object
```
tokenizer = MecabBPETrainTokenizer()
```

Set the arguments with the text, vocab_size and special_tokens to train the tokenizer
```
tokenizer.train(files,
                vocab_size=52000,
                special_tokens=["<pad>", "<unk>", "
", "
", "<mask>"])
```

Save the trained config files
```
tokenizer.save_model('config')
```

When you have config files, use them to tokenize new text with a tokenizer object
```
from jpn_bpe_tokenizer import MecabBPETokenizer

tokenizer = MecabBPETokenizer('config/vocab.json','config/merges.txt')
```