semvec/pypi-packages huggingface dataset:
john-resume 1.0.0
A package for ease of access to the greatest resume available
Requires Python: >=2.7

# John's resume!

I am currently making the most programmer'y resume that I can think of. That means I have to do stupid stuff like adding it to pip. Because why not? Wouldn't be much of a developer resume if it doesn't have:
 * Version control
 * Automated tests
 * Full CI/CD pipeline
 * Automatic deployment
 * Legacy support

And more!

This is totally dumb, but if you're interested [head over to my website](https://www.jmgundersen.net/) and let's be dumb together.

Parameters to use this dumb script:
```
 -f : For fast printout
 --json : If you prefer getting the printout in a json format
 -h : for help
```

To run the program just use the command "john-resume":
```
john-resume //Prints the resume
john-resume -f //Prints the resume really fast
```

Note that the script requires an interest connection, as this is an always online service.
torch-lfilter 0.0.3
Bring lowpass filtering to PyTorch!

# torch_lfilter

Bring low pass filtering to PyTorch!

This pytorch extension offers a PyTorch alternative for Scipy's
`lfilter` - with gradient tracking.

## CPU tensors only (efficiently...)

Although it's certainly the goal to implement an efficient CUDA
lfilter in C++, for now only the CPU version is implemented in C++.
That said, the implementation is reasonably fast and doing the
filtering on the CPU might be a viable option. Moreover, the
pure-python implementation works on all devices.

## Installation

The library can be installed with pip:

```
pip install torch_lfilter
```

Please note that no pre-built wheels exist. This means that `pip` will
attempt to install the library from source. Make sure you have the
necessary dependencies installed for your OS.

## Dependencies

### Linux

On Linux, having PyTorch installed is often enough to be able install
the library (along with the typical developer tools for your
distribution). Run the following inside a conda environment:

```
conda install pytorch -c pytorch
pip install torch_lfilter
```

### Windows

On Windows, the installation process is a bit more involved as
typically the build dependencies are not installed. To install those,
download **Visual Studio Community 2017** from
[here](https://my.visualstudio.com/Downloads?q=visual%20studio%202017&wt.mc_id=o~msft~vscom~older-downloads).
During installation, go to **Workloads** and select the following
workloads:

- Desktop development with C++
- Python development

Then go to **Individual Components** and select the following
additional items:

- C++/CLI support
- VC++ 2015.3 v14.00 (v140) toolset for desktop

After installation, run the following commands _inside_ a **x64 Native
Tools Command Prompt for VS 2017**, after activating your conda
environment:

```
conda install pytorch -c pytorch
pip install torch_lfilter
```

## License

© Floris Laporte 2020, [GPLv3](license)
VaniMonitoring 1.0.0
Small monitoring server with discord webhook integration
Requires Python: >=3.6

# VaniMonitoring Server

VaniMonitoring это маленький мониторинг хостинга с Discord интеграцией!

### Настройка конфига
При первой инициализации у вас будет создан конфиг под именем `vanimonitoringconfig.py`, в нем вы увидите подобный текст:
```py
  hostIp = '' # You server IP
  hostName = '' # You Host Name
  response_time = 5 # time for response cycle
  discord_integration = False # Discord integration
  discord_webhook_url = '' # Discord integration
```
Разберем все подробно. <br>
hostIp - IP Адрес хостинга который вы будете прослушивать
hostName - Имя хотя, чисто графический сахар (Нужно для Discord интеграции)
response_time - Частота повтороного прослушивания хостинга, не рекомендуется ставить меньше 5
discord_integration - Включена ли интеграция с Discord
discord_webhook_url - Если интеграция включена, нужно сюда вписать ссылку на вебхук.
### Требуемые библиотеки
Если pip не установил все нужные библиотеки, установите их вручную.
```cmd
pip install colorama
pip install discord-webhook
```

## Приятного использования Vani Monitoring!