semvec/pypi-packages huggingface dataset:
SendTextSMTP 0.4.11
A simple package to simplify the process to send text messages using the SMTP mail protocol.
Requires Python: >=3.6

# SendTextSMTP
A simple package to simplify the process to send text messages using the SMTP mail protocol.

## SETUP

You will need a app password if you are utilizing Gmail as your source email. 
Reference this help article: https://support.google.com/accounts/answer/185833?hl=en


## USAGE

### Import the module
  `import SendTextSMTP`

### Setting up the source email
  `messenger = SendTextSMTP.SMTP("YOUR_SOURCE_EMAIL", "YOUR_APP_PASSWORD", "YOUR_SMTP_SERVER", SMTP_PORT)`
  Using YOUR_SMTP_SERVER should look like `"smtp.gmail.com"` and SMTP_PORT `587` for gmail as an example.

### Sending a text message
  messenger.send_message("PHONE_NUMBER@CARRIER.COM", "MESSAGE")
  Note that for texts with multiple lines, you can use \r to indicate a newline.
python-hatch-template-win 0.0.1
hatch template win
Requires Python: >=3.12

# python-hatch-template-win

[![PyPI - Version](https://img.shields.io/pypi/v/python-hatch-template-win.svg)](https://pypi.org/project/python-hatch-template-win)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/python-hatch-template-win.svg)](https://pypi.org/project/python-hatch-template-win)

---

## Table of Contents

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install python-hatch-template-win
```

## License

`python-hatch-template-win` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.

## hatch-template

hatch new に型チェックなどを入れたもの。

```

```
sfmp 1.0.1
Separate images automatically
Requires Python: <4,>=3.5
Keywords: separate, images, automatically, cluster, feature, deeplearning

# sfmp (separate for me please)

Sfmp is a tool to quickly separate images using clustering based on features extracted through a convolutional neural network.
It's really lightweight, using only a mobilenetv2 for feature extraction and kmeans for clustering.

## Installation

To install sfmp, follow there steps:

For cpu
```
pip install "sfmp[cpu]"
```

For cuda 11.X
```
pip install "sfmp[gpu]"
```

For cuda 12.X
```
pip install "sfmp[gpu]" --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/
```

## Usage

### Command Line Interface

You can use sfmp from the command line by providing a list of globs:

```
sfmp ../examples/*.jpg ../examples2/*.jpg
```

If you want to use CUDA:


```
sfmp ../examples/*.jpg ../examples2/*.jpg --provider CUDAExecutionProvider
```

Check all execution providers [here](https://onnxruntime.ai/docs/execution-providers/).

To specify the number of clusters:

```
sfmp ../examples/*.jpg ../examples2/*.jpg --n_clusters 2
```

or output dir

To specify the number of clusters:

```
sfmp ../examples/*.jpg ../examples2/*.jpg --output_path result
```

### Example

Before
```
.
├── cat.1.jpg
├── cat.2.jpg
├── dog.3061.jpg
└── dog.3062.jpg
```

```
sfmp ../examples/*.jpg --n_clusters 2
```

After

```
├── cluster_0000
│   ├── dog.3061.jpg
│   └── dog.3062.jpg
└── cluster_0001
    ├── cat.1.jpg
    └── cat.2.jpg
```
decorator-retry 0.1.9
Retry functions and async functions
Requires Python: <4.0,>=3.8

# A simple decorator for retry functions  

```python
@retry(ValueError, KeyError,
         retry = True, 
         attempts = 3,
         wait = 1,
         reraise = True,
         logger = logging.debug
         )
def func():
   pass
```
## Decorator parameters

### exceptions

*SPECIFIED* exception types.

### retry

if retry is True , retry when the decorated function throws the *SPECIFIED* exceptions.   
if retry is False , retry when the decorated function throws the *UNSPECIFIED* exceptions.   
Default is True.

### attempts

The number of retries attempted. Default is 3.  

### wait

The wait interval between retries (second).   
Default is 1 second.

### reraise

If reraise is True, when an exception is thrown by the decorated function, that exception will be rethrown. If raraise is False, then None is returned instead.   
Default is True.

### logger

The logger function will be used when the decorated function raise exception.
Default is logging.warning.