semvec/pypi-packages huggingface dataset:
tkinterDev4 4.0.1
tkinter超级工具库，仅为Windows开发支持
Requires Python: >=3.6

# tkinterDev

`tkinter`高级工具包，实现了许多高级功能，我会持续更新的。😁😁😁

关于文档的更多内容请查看[我的主页](https:/xiangqinxi.github.io/tkinterDev/%E5%AE%89%E8%A3%85/)
关于超详细文档请查看[tkinterDev Docs](https://tkdev-docs.netlify.app/)
____
## 依赖问题
这个库拥有许多好用的功能，但是很多功能的代价就是需要依赖库，如果想要体验到完整内容就可以使用pip下载以下所有的库。

- [pywin32](https://pypi.org/project/pywin/) 实现诸多高级功能需要的
- [win32mica](https://pypi.org/project/win32mica/) 实现云母高级特效需要的
- [BlurWindow](https://pypi.org/project/BlurWindow/) 实现亚克力高级特效需要的
- [darkdetect](https://pypi.org/project/darkdetect/) 用于检测是否是深色主题或是浅色主题
- [Deprecated](https://pypi.org/project/Deprecated/) 用于标记一些废弃的组件
- [tkcap](https://pypi.org/project/tkcap) 用于截取窗口图片
```bash
pip install pywin32
```
```bash
pip install win32mica
```
```bash
pip install BlurWindow
```
```bash
pip install darkdetect
```
```bash
pip install tkcap
```
```bash
pip install Deprecated
```
```bash
pip install plyer
```
____
## 版本信息
4.0.0b0
测试发布

4.0.0b1
tkdev库更名为tkdev4

4.0.b2
修复导入错误

4.0.0
补充一些注释

____
fastaai-preproc 0.3
Protein predictions and HMM searches
Requires Python: >=3

# FastAAI

Author: Kenji Gerhardt
Email:  Kenji.Gerhardt@gmail.com
Author: Carlos Ruiz Perez
Email:  carlos.vernichtung@gmail.com

FastAAI uses tetramer frequency over shared universal sincle copy proteins to rapidly and accurately estimate average whole-genome amino acid identity.
py-templater 0.1.10
utility tool that generates code files from user-defined templates
Requires Python: >=3.7
Keywords: python,template,cli

# py-templater

![pypi build](https://img.shields.io/github/workflow/status/h3x4g0ns/py-templater/pypi-build)
[![PyPI version](https://badge.fury.io/py/py-templater.svg)](https://badge.fury.io/py/py-templater)

## About this Project

Python utility tool that generates code files from user-defined templates. Save files/directories and user-defined templates, and load them on the fly whenever you need access to your boilerplate templates.

## Getting Started

### Prerequisites

You will need `typer` and `rich` in order to use `py-templater`. These should install as dependencies by default.

```sh
pip install py-templater typer rich
```

> ⚠️ Warning<br>
> `py-templater` only works on Linux and macOS machines

### Usage

```sh
templater --help
                                                                                                                   
  Usage: templater [OPTIONS] COMMAND [ARGS]...                                                                      
                                                                                                                   
Options
  --install-completion          Install completion for the current shell.                                        
  --show-completion             Show completion for the current shell, to copy it or customize the installation.
  --help                        Show this message and exit.

Commands
  add       Add a new template
  gen       Generates file(s) from templates
  list      List current current templates
  rm        Delete a template
  view      View template head
```

#### `add`

Allows user to define a file/directory as new template

```sh
templater add --help

  Usage: templater add [OPTIONS] NAME PATH

Arguments
  name      template name
  path      path to original file/directory
```

#### `gen`

Generates any user defined templates in the current working directory

```sh
templater gen --help

  Usage: templater gen [OPTIONS] NAME

Arguments
  name      template name
```

#### `list`

Lists all user-defined templates and corresponding metadata

```sh
templater list --help
  
  Usage: templater list [OPTIONS]
```

#### `rm`

Allows user to delete any user-defined templates

```sh
templater rm --help

  Usage: templater rm [OPTIONS]
```

#### `view`

Views head snippet of template

```sh
templater view --help

  Usage: templater view [OPTIONS] NAME [N]

Arguments
  name      template name
  n         (default: 5) numbers of lines to show
wellradpy 2.1
A Python package to calculate the radius of influence and radius of investigation of pumping wells.
Keywords: groundwater wells hydraulics

# WellRadPy

WellRadPy ("Well Radius Python") is a Python package for calculating the radius
of influence and radius of investigation of pumping wells. These quantities
frequently need to be estimated in well hydraulics and aquifer testing (also
called well testing in petroleum engineering). In particular, calculating the
radius of investigation is critical for the design and the interpretation of
pumping tests. This package implements solutions for both drawdown and recovery
phases of pumping tests.

Note that radius of influence and radius of investigation are different
concepts. Furthermore, there are various ways by which each radius may be
precisely defined. This package implements most definitions.

## References

* Bresciani, E., Shandilya, R.N., Kang, P.K., Lee, S., 2020. Well radius of
influence and radius of investigation: What exactly are they and how to
estimate them? Journal of Hydrology, 583: 124646.
https://doi.org/10.1016/j.jhydrol.2020.124646.

* Bresciani, E., Shandilya, R.N., Kang, P.K., Lee, S., 2020. Evolution of the
radius of investigation during recovery tests. Journal of Hydrology,
590: 125346. https://doi.org/10.1016/j.jhydrol.2020.125346.

## Usage

WellRadPy is simple and its use is straightforward. The ``/examples`` directory
in the [GitHub repository](https://github.com/etiennebresciani/wellradpy)
contains scripts where the functions for calculating radius of influence and
radius of investigation are exemplified.

Help can also be obtained by typing ``help(function_path)`` in the Python
console.

## Installation

### For simple use

1. From the command line, type ``pip install wellradpy``. This will download
the latest release of the package from the PyPI repository and install it.

### For development

1. Clone (or download) the sources from the
[GitHub repository](https://github.com/etiennebresciani/wellradpy).
2. From the project directory, type ``pip install -e .``.
This will install the current directory, so that you can both modify the
package and use it at the same time.

### Dependencies

WellRadPy depends on the Python packages NumPy and SciPy (>= 1.2.0). These
will be automatically installed with any of the above installation methods.

## Authors

* **Etienne Bresciani**
([etiennebresciani](https://github.com/etiennebresciani))

## License

This project is licensed under the MIT License &ndash; see the
[LICENSE.txt](LICENSE.txt) file for details.

## Acknowledgements

* Korea Ministry of Science and ICT through the Korea Research Fellowship
program of the National Research Foundation of Korea (2016H1D3A1908042)
* Korea Institute of Science and Technology (KIST) through the Future Research
Program (2E29660, 2E30510)
* Korea Ministry of Environment (MOE) through the Subsurface Environment
Management (SEM) Project of the Korea Environment Industry & Technology
Institute (KEITI) (2018002440006)