semvec/pypi-packages huggingface dataset:
dataflow-cookiecutter 1.0.0a3
Command-line utility for creating Dataflow projects

# dataflow-cookiecutter [![Build Status](https://dev.azure.com/ljvmiranda/ljvmiranda/_apis/build/status/ljvmiranda921.dataflow-cookiecutter?branchName=master)](https://dev.azure.com/ljvmiranda/ljvmiranda/_build/latest?definitionId=5&branchName=master) ![PyPI](https://img.shields.io/pypi/v/dataflow-cookiecutter?color=light-green&label=pypi&logo=python&logoColor=white)

**Tired of copy-pasting your ad-hoc Dataflow modules?** Then you can use this
[cookiecutter](https://github.com/cookiecutter/cookiecutter) command-line
tool to easily generate standardized Dataflow templates! :zap:

![dataflow-cookiecutter demo](assets/demo.gif)

## Installation

You can install `dataflow-cookiecutter` from PyPI:

```sh
pip install dataflow-cookiecutter
```

In addition, you can also clone this repository and install locally:

```sh
git clone https://github.com/ljvmiranda921/dataflow-cookiecutter.git
cd dataflow-cookiecutter
python3 setup.py install
```

## Usage

You can create a Dataflow project by executing the command:

```sh
$ dataflow-cookiecutter new
```

**Choose from a variety of our premade templates.** See all available templates
by running `dataflow-cookiecutter ls`. For example, you can create a Google
Cloud Storage (GCS) to BigQuery (BQ) pipeline via:

```sh
$ dataflow-cookiecuter new -t GCSToBQ
```

Lastly, our templates are **highly-compatible to your trusty, old
`cookiecutter`** command-line tool (be sure to use `cookiecutter`>=1.7.1!):

```sh
$ cookiecutter https://github.com/ljvmiranda921/dataflow-cookiecutter \
   --directory <directory-to-desired-template> 
```


## FAQ

- **Why are you still wrapping cookiecutter?**  This started as my learning
    project to see how cookiecutter's internals work. While building the alpha
    version, I realized that I can add more functionality to this CLI more than
    templating, so wrapping Cookiecutter seems to be a good approach.
- **I already have cookiecutter, can I use it with your templates?** Yes of
    course! Look at the Usage section above! However, ensure that your
    cookecutter version is `>=1.7.1` so that you can use the `--directory`
    flag!
- **Why are you using Python 3 for Dataflow templates?** It's 2020, we
    shouldn't be supporting [legacy Python](https://pythonclock.org/?1)
    anymore. Besides, Dataflow now has [streaming support in Python
    3](https://cloud.google.com/blog/products/data-analytics/introducing-python-3-python-streaming-support-from-cloud-dataflow).
    See more developments for Beam support in Python 3  in their
    [issue tracker](https://issues.apache.org/jira/browse/BEAM-1251).
pyhtmd 1.0.2
A Python HTML to Markdown parser
Keywords: html,markdown,parser,pyhtmd

# 一款Python版本的HTML转markdown解析器，不使用任何第三方工具，实验demo

请勿使用于生成环境，这个只是一次尝试demo项目

## 注意：

- 无法解析多层级HTML
- 只能是单Node
- 这项目目前只针对 [tensorflow-docs](https://github.com/veaba/tensorflow-docs) 项目
- 存在个别自定义标签无法识别，基本可以适用平常场景
- python官方html_parser https://docs.python.org/zh-cn/3.7/library/html.parser.html
- html.parser 源码 https://github.com/python/cpython/blob/3.7/Lib/html/parser.py
- 不支持美化后的HTML内容，需要内容紧凑
## parser
- [x] single html node element
- [x] infinite html list node element
- [x] img
- [x] head html node element

## todo 开发中 
- 核心的问题是，粘在一起的代码如何拆分？
- 本质还是要分割的，但具体怎么分割呢？
- table

## bug
- 已解决list算法问题：
    - 当前的list 标签算法无法解析这种结构：
    - 因为算法中，假定是依次序性ul组成结束的标签
    - 核心算法一：算出开始标签的level
    - 核心算法二：根据左边的开始标签索引值算出其所对应的右边索引值序列，我自己给他起了一个炫酷拽炸天的名字：标记逆序奇偶互斥算法
    - 上面两个算法我自己算出来的，第一个花了两天，第二个花了1-2周

## install 

> pip install pyhtmd


## usage

```python
from pyhtmd import Pyhtmd
html="<code> Hello, world ! by Pyhtmd. </code>"
md= Pyhtmd(html)
content=md.markdown()
print(content) # `Hello, world ! by Pyhtmd.`
```

## API
Pyhtmd(html,
 language="",
 img=True
)

- language：类型 string （js、python、java等）
- img:{Boolean}，默认True，可以不需要img渲染
```python
from pyhtmd import Pyhtmd
html="<pre><code>import time\n print(time.time()) </code><pre>"
md= Pyhtmd(html,language="python")
content=md.markdown()
print(content) # `Hello, world ! by Pyhtmd.`
```