semvec/pypi-packages huggingface dataset:
videoclusters 0.0.4
Python library to perform clustering computations on GPU.
Requires Python: >=3.7

# videoclusters

Python library to perform clustering computations on GPU.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install videoclusters.

```bash
pip install videoclusters
```

## Usage example

```python
from videoclusters.centroid_based.KMeans import KMeans

# initialization of the cluster
kmeans_cluster = KMeans(num_clusters=2)

# initialization of uneven distributed data
data = torch.randint(low=1,
                     high=10,
                     size=(100, 2),
                     dtype=torch.float32).to('cuda')

data[50:] = torch.randint(low=20,
                          high=30,
                          size=(50, 2),
                          dtype=torch.float32).to('cuda')

# starting computation
result = kmeans_cluster.fit_predict(data)
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[MIT](https://choosealicense.com/licenses/mit/)
Novalib 0.0.1
• Script Very Nice To Helping Programmer .
Requires Python: >=3.9

<h1 align="center">Nova_Tools</h1>
<p align="center">It's a beautiful project that helps developers program.</p>

![](https://img.shields.io/badge/NOVA-TOOLS-orange?style=for-the-badge&logo=python.svg) 
<p align="center">
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</p>
<p align="center">
<img alt="Nova-Tools' Github Stats" src="https://github-readme-stats.vercel.app/api?username=NOVA1321&show_icons=true&include_all_commits=true&hide_border=true" />

</p>
<p align="center">
<a href="#"><img title="telegram Num" src="https://img.shields.io/badge/telegram%20Num-ArabShadows-red.svg?style=for-the-badge&logo=telegram"></a>
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<p align="center">
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</p>

## Installation :
```
pip install Nova-Tools
```
### Logan Usage

``` python
from NovaTools import Nova_Tools

## Follow us on social media
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django-cloudflare-restrictor 1.0.2
Django package to restrict access just to cloudflare workers
Requires Python: >=3.6

### Overview

The django-cloudflare-restrictor package provides a convient way to restrict access to your application server, such that it will only respond to requests that come via cloudflare's network.

### Installation

Install the package from pypi

```
pip install django-cloudflare-restrictor
```

Add to `INSTALLED APPS` in your settings file 

```
INSTALLED_APPS = [
    'django_cloudflare_restrictor',
    ...
```

And add to `MIDDLEWARE` in your settings file

```
MIDDLEWARE = [
    'django_cloudflare_restrictor.middleware.CloudflareRestrictorMiddleware',
    ...
 ]
```

Set the additional settings as desired

```
CLOUDFLARE_RESTRICTOR_ENABLED = True
CLOUDFLARE_RESTRICTOR_ADDITIONAL_NETWORKS = ["127.0.0.0/8"]
CLOUDFLARE_RESTRICTOR_EXCLUDE_PATHS = [
    '^/cron/$',
]
```

If you want to confirm that the IP blocks stored in the django-cloudflare-restrictor package are up to date you can use the `check_cloudflare_ips` command. This will log a warning if the IP addresses are out of date.

```
python manage.py check_cloudflare_ips
```

Based on historical evidence, it appears that Cloudflare gives around 1 month's advance notice of IP address changes, by publishing the new addresses in advance on their site. Updates to these lists are very infrequent (approx once per every 2 years)