semvec/pypi-packages huggingface dataset:
i3-swallow 1.0.0
Swallow a terminal window in i3/sway
License: MIT
Requires Python: >=3.7,<4.0

<h1 align="center">
  Swallow
</h1>
<h4 align="center">Used to swallow (send to the scratchpad) a terminal window after a blocking application is run in i3 window manager</h4>

<p align="center">
  <img src="https://img.shields.io/badge/Maintained%3F-Yes-green?style=for-the-badge">
  <img src="https://img.shields.io/github/license/jamesofarrell/i3-swallow?style=for-the-badge">
  <img src="https://img.shields.io/github/issues/jamesofarrell/i3-swallow?color=violet&style=for-the-badge">
  <img src="https://img.shields.io/github/stars/jamesofarrell/i3-swallow?style=for-the-badge">
  <img src="https://img.shields.io/github/forks/jamesofarrell/i3-swallow?color=teal&style=for-the-badge">
  <img src="https://github.com/jamesofarrell/i3-swallow/blob/master/Swallow.gif">
</p>

## Information

This repo just packages [jamesofarrell/i3-swallow](https://github.com/jamesofarrell/i3-swallow) script using [Poetry](https://python-poetry.org/)
so it can be install using `pip`

## Requirements

- Unix system with i3 window manager, or i3 compatible window manager such as sway
- Python3.x+
- Python3.x+ Pip

## Installation Instruction

```bash
pip install --user i3-swallow
```

## Usage

```bash
swallow -h
```

## License

This Project is licensed under the MIT License. Check license file for more info.
involution-pytorch 0.0.2.2
Involution Operation - Pytorch
License: MIT
Keywords: artificial intelligence,deep learning,involution,convolution

# involution_pytorch
Unofficial PyTorch implementation of "Involution: Inverting the Inherence of Convolution for Visual Recognition" by Li et al. presented at CVPR 2021.

<br />

[[`abs`](https://arxiv.org/abs/2103.06255), [`pdf`](https://arxiv.org/pdf/2103.06255.pdf), [`Yannic's Video`](https://www.youtube.com/watch?v=pH2jZun8MoY)]

<img src="https://github.com/rish-16/involution_pytorch/blob/main/assets/model.png?raw=true" >

## Installation

You can install `involution_pytorch` via `pip`:

```bash
pip install involution_pytorch
```

## Usage

You can use the `Inv2d` layer as you would with any PyTorch layer:

```python
import torch
from involution_pytorch import Inv2d

inv = Inv2d(
    channels=16,
    kernel_size=3,
    stride=1
)

x = torch.rand(1, 16, 32, 32)
y = inv(x) # [1, 16, 32, 32]
```

> The paper talks about using Self-Attention for the dynamic kernel generation function. I'll try implementing it later if time permits.

## Contributing

If I've made any errors anywhere in the implementation, please do let me know by raising an issue. If there's any cool addition you want to introduce, all PRs appreciated!

## License

[MIT](https://github.com/rish-16/involution_pytorch/blob/main/LICENSE)
WPS2OpenGMS 1
This program is used to automatically encapsulate WPS models using the OpenGMS method.
License: MIT

该程序用于使用OpenGMS方法实现对52° North WPS模型的自动化封装。

#### 一、输入参数：

1、WPS服务的网络地址：

​	eg：http://geoprocessing.demo.52north.org/latest-wps/WebProcessingService

2、某一模型执行请求XML文件：

​	eg：echo.xml

#### 二、使用方法：

```python
from WPS2OpenGMS.wps2opengms import createWPS2OpenGMS 

createWPS2OpenGMS(“your_wps_url”,"wps_execute.xml")
```
deepNets 0.1.8
A basic deep learning tool
License: MIT
Keywords: deepLearning

Change Log
==========

0.1.8 (09/05/2021)
-------------------
- Deep learning library for constructing neutral networks
- Supports neural network modules(conv layers,fully-connected layers,non-linearities) and classification(softmax) functions.
- Ability to specify and train Convolutional Networks that process images.
- Developed with python and can be run in any machine.
redis-dumper 0.1.0
CLI utility and library for creating encrypted redis dump.
License: MIT
Requires Python: >=3.7

# Redis Dumper
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/redis_dumper?logo=python&style=flat-square)](https://python.org)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/redis_dumper?style=flat-square)](https://pypi.org/project/redis_dumper)
[![PyPi Package Version](https://img.shields.io/pypi/v/redis_dumper?style=flat-square)](https://pypi.org/project/redis_dumper)
[![GitHub Workflow Status (branch)](https://img.shields.io/github/workflow/status/DavisDmitry/redis_dumper/Tests/master?label=tests&style=flat-square)](https://github.com/DavisDmitry/redis_dumper/actions/workflows/tests.yml)
[![GitHub](https://img.shields.io/github/license/DavisDmitry/redis_dumper?style=flat-square)](https://github.com/DavisDmitry/redis_dumper/raw/master/LICENSE)

CLI utility and library for creating encrypted redis dump.
## Install
```shell
pip install redis_dumper
```
## Use in CLI
```shell
redis_dumper [OPTIONS] COMMAND [ARGS]...
```
## Use in your code
Examples:
```python
import io
import aioredis
import redis_dumper


REDIS_ADDR = 'redis://10.0.0.1:6379'
PASSWORD = 'qwerty'
FILE_PATH = 'mydump.rdump'


async def dump_to_file_example():
    await redis_dumper.dump_to_file(REDIS_ADDR, PASSWORD, FILE_PATH)


async def dump_to_bytesio_example():
    dump = await redis_dumper.dump_to_bytesio(REDIS_ADDR, PASSWORD)


async def restore_from_file_example():
    await redis_dumper.restore_from_file(REDIS_ADDR, PASSWORD, FILE_PATH)


async def restore_from_bytesio_example(dump: io.BytesIO):
    await redis_dumper.restore_from_bytesio(REDIS_ADDR, PASSWORD, dump)


# you can also use the already created aioredis.Redis instance
async def example_with_created_redis():
    redis = await aioredis.create_redis(REDIS_ADDR)
    dump = await redis_dumper.dump_to_bytesio(redis, PASSWORD)

```
thumbor-expire 0.1.3
Add timeout verification for thumbor
License: MIT
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*
Keywords: thumbor,expire

# thumbor-expire
Add timeout verification for thumbor

## Use 

* Server side

thumbor config file set `URL_SIGNER = thumbor_expire.base64_hmac_sha1_expire`


* Client side

use `from thumbor_expire.crypto import CryptoURL` class and pass expire argument, accept type `:obj:`int` | :obj:`float` | :obj:`datetime.timedelta` | \
        :obj:`datetime.datetime` | :obj:`datetime.time`, optional`
tags.py 0.8.7
A Tag helper.
License: MIT
Requires Python: >=3.5

## How to install using pip:

Stable:
```sh
pip install tags.py
```

Developement:
```sh
pip install git+https://github.com/proguy914629bot/tags.py
```

## Simple guide on how to use:

```py
from tags import Tag

tag = Tag()

#Without aliases:
tag.add_tag(r"{user}", "user123")

#With aliases called "{users}" and "{usr}":
tag.add_tag(r"{user}", "user123", r"{users}", r"{usr}")

#Converting the string:
string = r"{user} is the same as {users} and {usr}!"
tag.convert(string) # "user123 is the same as user123 and user123!"

#Getting a tag by name:
tag.get_tag("Insert-Name-Here")

#Getting a tag by id:
tag.get_tag("Insert-ID-Here")

#Get a tag ID by name:

#Way 1:
tag.get_tag("Insert-Name-Here").id

#Way 2:
tag.get_id("Insert-Name-Here")

#All these ways are the same. get_tag.id returns tag.get_id.
```

## Contribution:
You can contribute by forking this repository, or cloning this repository. This is fully open-sourced in [Github](https://github.com/proguy914629bot/tags.py).

## License:
MIT