semvec/pypi-packages huggingface dataset:
ml-model-quality-analysis 0.0.1
A package to perform quality analyses for Machine Learning models

# Quality Analysis for Machine Learning models

The three quality pillars are:

- **Functionality:** groups analyses that evaluate how ”well“ an AI module performs a
given task (i.e. assessing the suitability of an AI module for an application domain).


- **Comprehensibility:** groups analyses that try to open the blackbox and enable
stakeholders (model producers, users, or regulators) to interpret decisions and the
decision-making process. 


- **Robustness:** groups analyses that assess how the ML component responds to small
changes in the input. 


The latest release performs functionality and robustness analyses for image classification 
and regression models. The next versions will include comprehensibility analysis and accept text data.

# Installation

Using the PyPi package:
```
pip install ml-model-quality-analysis
```

# Notable Dependencies

TensorFlow 2.3 is required:
```
pip install tensorflow==2.3
```

# Getting Started

For examples on performing quality analysis for ML models, see the [Quality Report Notebook.](https://github.com/mariagrandury/ml-model-quality-analysis/blob/main/quality_report.ipynb)
env-paths 1.0.1
Returns the directory where the cache is located. This is different for each os.
Requires Python: >=3.8,<4.0

# env-paths <!-- TODO: badge -->

This package is a modified [sindresorhus/env\-paths from nodejs](https://github.com/sindresorhus/env-paths) for python.

Returns the directory where the cache is located. This is different for each os.



## Install

```
$ pip install env-paths
```


## Usage

```python
from env_paths import env_paths

paths = env_paths('MyApp')
paths.data
# => '/home/atu4403/.local/share/MyApp-python'

paths.config
# => '/home/atu4403/.config/MyApp-python'
```

## Related
- [sindresorhus/env\-paths: Get paths for storing things like data, config, cache, etc](https://github.com/sindresorhus/env-paths)


## License

MIT © [atu4403](https://github.com/atu4403)
simplelayout-Vincentius1990 0.0.1
A small example package
Requires Python: >=3.6

[![Work in Repl.it](https://classroom.github.com/assets/work-in-replit-14baed9a392b3a25080506f3b7b6d57f295ec2978f6f33ec97e36a161684cbe9.svg)](https://classroom.github.com/online_ide?assignment_repo_id=3695084&assignment_repo_type=AssignmentRepo)
# 3-simplelayout-package

## 简介

- 本次作业将大家完成的数据生成器进行打包，可供 pip 进行安装，发布到 [PyPI](https://pypi.org/)。同时使用 Sphinx 构建文档，发布到 [Read the Docs](https://readthedocs.org/)。


>**Sphinx** is a powerful documentation generator that has many great features for writing technical documentation including:
>- Generate web pages, printable PDFs, documents for e-readers (ePub), and more all from the same sources
>- You can use reStructuredText or Markdown to write documentation
>- An extensive system of cross-referencing code and documentation
>- Syntax highlighted code samples
>- A vibrant ecosystem of first and third-party extensions

- Python 生态的文档大都以 Sphinx 进行发布，例如 [Python 自身的官方文档](https://docs.python.org/3/)、[Pytorch 文档](https://pytorch.org/docs/stable/index.html) 等等。

- [Read the Docs](https://readthedocs.org/) 是一个可以自动化托管 Sphinx 文档的网站。

- Read the Docs 有上手教程，[参考](https://docs.readthedocs.io/en/stable/intro/getting-started-with-sphinx.html)。

## 要求

- 将个人完成的 `2-simplelayout-generator` 项目中的 `simplelayout` 目录复制到本次作业的 `src` 目录下。
- 编写 `setup.py`
  - 参考[官方文档](https://docs.python.org/3/distributing/index.html#reading-the-python-packaging-user-guide)，与 [Packaging and distributing projects](https://packaging.python.org/guides/distributing-packages-using-setuptools/)，正确配置 `setuptools.setup()`，确保能被 `pip` 正确安装，要求
    - package 名称设置为 `simplelayout-github账号名`
    - 正确包含 `src/simplelayout` 这个 package
    - `install_requires` 包含 `simplelayout` 的相关依赖
    - 正确配置 `entry_points`，使命令 `simplelayout` 对应 `simplelayout/__main__.py` 中的 `main()` 函数
- 参考 [文档](https://packaging.python.org/guides/distributing-packages-using-setuptools/#packaging-your-project)，正确打包
- 参考 [文档](https://packaging.python.org/guides/distributing-packages-using-setuptools/#id77)，正确上传到 PyPI
- 根据[参考教程](https://docs.readthedocs.io/en/stable/intro/getting-started-with-sphinx.html)，创建 `docs` 目录，并创建 `Sphinx` 项目。
  - 在执行 `sphinx-quickstart` 时输入相关信息
  - Sphinx 默认使用 rst 格式（[reStructuredText](https://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html) ）编写文档，可进行配置使用 [Markdown](https://docs.readthedocs.io/en/stable/intro/getting-started-with-sphinx.html#using-markdown-with-sphinx) 进行文档编写。
  - 选做：[参考](https://www.sphinx-doc.org/en/master/usage/extensions/napoleon.html) 配置 autodoc、napoleon 插件，自动生成 simplelayout 中的 docstring API。
  - 在本地生成正确的 Sphinx 文档
- 注册 [Read the Docs](https://readthedocs.org/)，将个人仓库中的文档正确托管
- 将个人项目 PyPI 仓库的链接、read the docs 链接以评论的方式发在 `Feedback` 上

## 注意

本次作业的在线测试分为以下部分：
1. 测试能否正确执行
  ```
  pip install .
  ```
  分值：1 分
1. 测试能否正确执行
  ```
  pip install .
  simplelayout -h
  ```
  分值：1 分

以上测试通过后，会在 `Feedback` 中打印相关信息（包括 PyPI 链接，生成图片），但不会对 `PyPI`、`Read the Docs` 自动测试