semvec/pypi-packages huggingface dataset:
django-stubs-patch 0.1.0
A pmypy django-stubs patch work for python3.6
Requires Python: >=3.6.1

# django-stubs-patch

[![Release](https://img.shields.io/github/v/release/mrlyc/django-stubs-patch)](https://img.shields.io/github/v/release/mrlyc/django-stubs-patch)
[![Build status](https://img.shields.io/github/actions/workflow/status/mrlyc/django-stubs-patch/main.yml?branch=main)](https://github.com/mrlyc/django-stubs-patch/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/mrlyc/django-stubs-patch/branch/main/graph/badge.svg)](https://codecov.io/gh/mrlyc/django-stubs-patch)
[![Commit activity](https://img.shields.io/github/commit-activity/m/mrlyc/django-stubs-patch)](https://img.shields.io/github/commit-activity/m/mrlyc/django-stubs-patch)
[![License](https://img.shields.io/github/license/mrlyc/django-stubs-patch)](https://img.shields.io/github/license/mrlyc/django-stubs-patch)

A pmypy django-stubs patch work for python3.6

- **Github repository**: <https://github.com/mrlyc/django-stubs-patch/>
- **Documentation** <https://mrlyc.github.io/django-stubs-patch/>

## Getting started with your project

First, create a repository on GitHub with the same name as this project, and then run the following commands:

``` bash
git init -b main
git add .
git commit -m "init commit"
git remote add origin git@github.com:mrlyc/django-stubs-patch.git
git push -u origin main
```

Finally, install the environment and the pre-commit hooks with

```bash
make install
```

You are now ready to start development on your project! The CI/CD
pipeline will be triggered when you open a pull request, merge to main,
or when you create a new release.

To finalize the set-up for publishing to PyPi or Artifactory, see
[here](https://fpgmaas.github.io/cookiecutter-poetry/features/publishing/#set-up-for-pypi).
For activating the automatic documentation with MkDocs, see
[here](https://fpgmaas.github.io/cookiecutter-poetry/features/mkdocs/#enabling-the-documentation-on-github).
To enable the code coverage reports, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/codecov/).

## Releasing a new version

- Create an API Token on [Pypi](https://pypi.org/).
- Add the API Token to your projects secrets with the name `PYPI_TOKEN` by visiting
[this page](https://github.com/mrlyc/django-stubs-patch/settings/secrets/actions/new).
- Create a [new release](https://github.com/mrlyc/django-stubs-patch/releases/new) on Github.
Create a new tag in the form ``*.*.*``.

For more details, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/cicd/#how-to-trigger-a-release).

---

Repository initiated with [fpgmaas/cookiecutter-poetry](https://github.com/fpgmaas/cookiecutter-poetry).
ai-commands 1.0.0
A Python package for simple but complex computer functions.
Requires Python: >=3.7
Keywords: python,AI,sentiment analysis,natural language processing

# ai_commands

![Package Logo](https://github.com/MKM12345/ai_commands/blob/main/logo.png)

[![Python Version](https://img.shields.io/badge/Python-%3E%3D%203.7-blue?style=plastic.svg)](https://www.python.org/downloads/)
[![PyPI Version](https://img.shields.io/badge/pypi%20package-0.1.0-4DC71F?style=plastic.svg)](https://pypi.org/project/ai_commands/)
[![First Timer Friendly](https://img.shields.io/badge/first%20timer-friendly-4DC71F?style=plastic.svg)](https://github.com/MKM12345/ai_commands/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)
[![Tests](https://img.shields.io/badge/tests-all%20passing-4DC71F?style=plastic.svg)](https://github.com/MKM12345/ai_commands/actions)

## Overview

`ai_commands` is a Python package designed to simplify common AI-related tasks such as performing sentiment analysis on text data. It provides a collection of functions and utilities to streamline various AI tasks, making it easier for developers to work with artificial intelligence and natural language processing.

### Features

- **Text Variation Generation**: Use the `ai_similarise` function to generate text variations by replacing words with synonyms and shuffling sentence structure.
- **Sentiment Analysis**: Employ the `analyze_sentiment` function to perform sentiment analysis on text, providing sentiment labels and scores.

## Installation

You can install `ai_commands` using pip:
`pip install ai-commands`

## Usage
Here's how you can use ai_commands in your Python projects:

```
import ai_commands

# Generate text variations
original_message = "Sorry, you lost the game!"
similar_message = ai_commands.ai_similarise(original_message)
print("Similar Message:", similar_message)

# Perform sentiment analysis
text_to_analyze = "I love this product. It's fantastic!"
sentiment_result = ai_commands.analyze_sentiment(text_to_analyze)
print("Sentiment Analysis Result:", sentiment_result)

```
## Documentation
For detailed usage instructions and additional functions, please refer to the documentation.

## Support and Contributions
ai_commands is an open-source project, and contributions from the community are welcome! If you have ideas for improvements or new features, please check out our contribution guidelines.

## License
ai_commands is licensed under the MIT License.
imgbox 1.0.8
用 pillow 画目标检测的框，支持中文（自带字体）

用 pillow 画目标检测的框，支持中文（自带字体）

用法见

[→ test.py](test.py)

```py
#!/usr/bin/env python

from imgbox import imgbox
from PIL import Image
from os.path import abspath, dirname, join

DIR = dirname(abspath(__file__))
img = join(DIR, 'test.webp')
img = Image.open(img)
imgbox(img, ('测试', (30, 30, 60, 60)))
img.save(join(DIR, 'box.webp'), quality=80)
```
TEI-IIIF 0.9.2
A Python CLI app that pulls data from TEI-XML files and transforms them to conformant IIIF Annotation manifests.
Requires Python: >=3.7

# TEI-IIIF Converter

## Introduction
TEI-IIIF turns angle brackets into curly brackets. 

To put it in more descriptive terms, it is a Python CLI application that pulls data from [TEI](https://tei-c.org) XML and transforms to conformant [IIIF](https://iiif.io) Annotation manifests, as described in the [IIIF Presentation API 3.0](https://iiif.io/api/presentation/3.0/#56-annotation).

TEI-IIIF generates a `.json` manifest for each `<div>` in a given XML file. Within each `<div>` it targets `<p>` elements with a `facs` attribute, which are used as `target` values in the output manifests. It uses `lxml`'s `etree.tostring` method to pull the children of targeted `<p>` elements, saving them as the `value` for that given target. 

## Installation

`pip install TEI-IIIF`

## Basic use
- Settings can be found in `settings.yaml`. If you have installed `tei_iiif` in a virtual environment using `venv`, you can find `settings.yaml` in `your_directory/venv/lib/python[version]/site-packages/tei-iiif`.
- Specify the `base_url` where you are hosting your XML. This can be either a URI (e.g. `https://foo.bar/baz/transcriptions/`) or a local source (e.g. `./projects/foo-bar/transcriptions/`). In both cases, remember the trailing `/`. Once this has been set, TEI-IIIF can be run from the command line, with the file you wish to convert passed as an argument:

`python3 tei_iiif -m transcription.xml`

## Considerations
- Because TEI-IIIF uses `etree.tostring` to produce the text for annotations, it captures both tags and text and replicates them. Depending on the input XML, the manifests it outputs may need to be sanitised in order to be used in production, or you may need to sanitise or simplify the XML prior to processing. As use cases can differ dramatically from project to project, TEI-IIIF does not attempt to sanitise output body text.
- However, TEI-IIIF does include regex to sanitise `facs` attributes such that they use `#xywh=` formatting for image selectors. This can be changed according to your use case in `settings.py`
 - By default TEI-IIIF assumes you have XML structured in a format roughly equivalent to the following:

```
<div n="1">
	<p facs=“https://facsimile-server.com/iiif/foo-bar/p1/571,152,1951,1076”>
		<children>...</children>
	</p>
	<p facs="https://facsimile-server.com/iiif/foo-bar/p1/675,728,1949,1320”>
		<children>...</children>
	</p>
</div>
<div n="2">
	<p facs="https://facsimile-server.com/iiif/foo-bar/p2/571,152,1951,1076">
		<children>...</children>
	</p>
	<p facs="https://facsimile-server.com/iiif/foo-bar/p2/675,728,1949,1320">
		<children>...</children>
	</p>
</div>
```

- If your XML differs dramatically from the below then you can change the XPath in `xmlparser.py` and `divjson.py`.
- TEI-IIIF defaults to the [base TEI namespace URI](http://www.tei-c.org/ns/1.0). This can be changed in `settings.yaml`.