semvec/pypi-packages huggingface dataset:
Texo 0.0.4
Sentiment Analysis Multiple language and for all products
Keywords: python,Sentiment,NLP,Tokenizer,Text-Analyzer,sockets,torch,PIL,torchvision

# Texo

Under construction! Not ready for use yet! Currently experimenting and planning!

Developed by Sourabh Singh from Neuroins(c) 2023

## Examples of How To Use (Buggy Alpha Version)

Predicating Sentimental Analysis in English

```python
from Texo.Sentimental.Analysis import Sentitweeten

Analysis = Sentitweeten()
Out = Analysis.Tweet_analy('Analysis this Tweet')
print(out)
```

Predicating Sentimental Analysis in Hindi

```python
from Texo.Sentimental.Analysis import Sentitweeten

Analysis = Sentitweethn()
Out = Analysis.Tweet_anal('Analysis this Tweet')
print(out)
```

Find all stop_words from Text

```python
from Texo.Word.texo import tex
x = tex()
er = x.stop_words('This is a sample text with some stop words in it.')
print(er)
```


Find Summary from Text and number of Points of user Choice

```python
from Texo.Word.texo import tex
x = tex()

text = "In literary theory, a text is any object that can be  whether this object is a work of  an arrangement of buildings on a city block, or styles of clothing. " \
       "It is a coherent set of signs that transmits some kind of informative message." \
       "This set of signs is considered in terms of the informative message's content, rather than in terms of its physical form or the medium in which it is represented.  " \
       "Within the field of literary criticism, also refers to the original information content of a particular piece of writing; that is, the "text" of a work is that primal symbolic arrangement of letters as originally composed, apart from later alterations, deterioration, commentary, translations, paratext, etc." \
       "et eleifend tortor mauris in dui. Vivamus ut pulvinar mauris, eget fermentum metus. " \
       "Cras nec varius ipsum. Sed sed neque vel ante vulputate gravida id a nisl. " \
       "Praesent facilisis imperdiet elit at rhoncus. Morbi ac scelerisque risus."

summary = x.summary(text, num_bullet_points=10)
print(summary)
```


Unet for Image

```python
from Texo.Unet import UnetM
im = UnetM()
im.Imageprepocess('image_path')

#Display image
im.show()
```

Tokenize of Text and pos
```python
from Texo.Word.texo import tex

#tokenize text without stop-words
tokenize = tex()
words = tokenize.tokenize('This is going Awesome')
print(words)

#tokenize text with stop-words
tokenize = tex()
words = tokenize.tokenize_stopwords('This is going Awesome')
print(words)

#find POS from tokens and return pos in form of array
tokenize = tex()
tokens = ['Running', 'dogs', 'are', 'happier', 'than', 'walked', 'dogs', 'in', 'parks.']
words = tokenize.pos_tag(tokens)
print(words)

#return output in form of token of array
#Display image
im.show()
```
BookerEpubTool 2023.7.9.1
iBooker/ApacheCN 知识库抓取工具
Requires Python: >=3.6
Keywords: wiki,知识库,document,文档,crawler,爬虫

# BookerEpubTool

iBooker/ApacheCN 知识库抓取工具

## 安装

通过pip（推荐）：

```
pip install BookerEpubTool
```

从源码安装：

```
pip install git+https://github.com/apachecn/BookerEpubTool
```

## 使用说明

```
epub-tool -h
```

## 协议

本项目基于 SATA 协议发布。

您有义务为此开源项目点赞，并考虑额外给予作者适当的奖励。

## 赞助我们

![](https://home.apachecn.org/img/about/donate.jpg)

## 另见

+   [ApacheCN 学习资源](https://docs.apachecn.org/)
+   [计算机电子书](http://it-ebooks.flygon.net)
+   [布客新知](http://flygon.net/ixinzhi/)
dspace-cliente 0.1.0
DSpace Rest Client for Python
Requires Python: >=3.11,<4.0

DSpace rest client for v7 or above
=====================================

## Goals
- [ ] Implement all endpoints on DSpace Rest Contract
- [ ] Configurable by default
- [ ] All authentication methods
- [ ] Async support

## Features
- Authenticaion using login/password
- Autorefresh token
- Auto XSRF token
- Objects are pydantic friendly not dicts
jirawiki2docx 1.0.1
Convert Jira wiki to DOCX format effectively
Requires Python: >=3.7

# JiraWiki2Docx

JiraWiki2Docx is a Python 3 library that converts Jira wiki text to Microsoft Word (docx) format. It provides a convenient way to migrate Jira wiki content to Word documents, allowing users to preserve the formatting and structure of their Jira wiki pages.

## Installation

You can install jirawiki2docx using pip:

```
pip install jirawiki2docx
``` 

## Usage

To use jirawiki2docx, follow these steps:

1.  Import the JiraWiki2Docx class:

	```
    from jirawiki2docx import JiraWiki2Docx
    ``` 

2.  Create an instance of the JiraWiki2Docx class, providing the Jira wiki text as input:

	```
	jira_text = "Your Jira wiki text here..."
	converter = JiraWiki2Docx(jira_text)
	``` 

3.  Parse the Jira wiki text and generate the Word document:

	```
    document = converter.parseJira2Docx()
    ```

4.  Optionally, save the resulting document to a file:

	```
    converter.parseJira2Docx(save_to_file=True, output_filename="output.docx")
    ```

5. Alternatively, you can use an existing `docx.Document` object and append the converted Jira wiki text to it's content:

	```
	existing_document = docx.Document()
	jira_converter.parseJira2Docx(existing_document)
	```

## Example

Here's a complete example that demonstrates the usage of JiraWiki2Docx:

```
from docx import Document
from jirawiki2docx import JiraWiki2Docx

# Jira wiki text
jira_text = """
h1. Heading 1

This is a paragraph.

h2. Heading 2

* Item 1
* Item 2

h3. Heading 3

||Heading 1||Heading 2||
|Cell 1|Cell 2|

This is another paragraph.
"""

# Create a Document object
document = Document()

# Create an instance of JiraWiki2Docx and parse the Jira wiki text
converter = JiraWiki2Docx(jira_text, document)

# Parse Jira markup and convert to Word document with optional arguments to save created/modified document to file or just return as object
converter.parseJira2Docx(save_to_file=True, output_filename="output.docx")
```

The resulting Word document will contain the converted Jira wiki content with appropriate headings, lists, and tables.

## Supported Jira Wiki Syntax

JiraWiki2Docx supports the following Jira wiki syntax:

-   Headings (h1 to h6)
-   Unordered lists (*, -, #)
-   Tables (||)
-   Text effects (bold, italics, deleted, inserted, superscript, subscript, and color)

Please note that JiraWiki2Docx may not support all Jira wiki syntax and rendering options.

## License

JiraWiki2Docx is released under the MIT License. See the [LICENSE](https://github.com/deitar/jirawiki2docx/blob/main/LICENSE) file for more details.

## Conclusion

JiraWiki2Docx simplifies the process of converting Jira wiki markup to Word documents. Whether you need to share Jira content with stakeholders or generate printable reports, this library provides an easy-to-use solution. Give it a try and streamline your Jira content management and distribution process.
BookerMarkdownTool 2023.7.9.1
iBooker/ApacheCN 知识库抓取工具
Requires Python: >=3.6
Keywords: wiki,知识库,document,文档,crawler,爬虫

# BookerMarkdownTool

iBooker/ApacheCN 知识库抓取工具

## 安装

通过pip（推荐）：

```
pip install BookerMarkdownTool
```

从源码安装：

```
pip install git+https://github.com/DracoUnion/BookerMarkdownTool
```

需要 Node 和`to-markdown`包。

## 使用说明

```
md-tool -h
```

## 协议

本项目基于 SATA 协议发布。

您有义务为此开源项目点赞，并考虑额外给予作者适当的奖励。

## 赞助我们

![](https://home.apachecn.org/img/about/donate.jpg)

## 另见

+   [ApacheCN 学习资源](https://docs.apachecn.org/)
+   [计算机电子书](http://it-ebooks.flygon.net)
+   [布客新知](http://flygon.net/ixinzhi/)