semvec/pypi-packages huggingface dataset:
azzlem-django-notifications 0.1.9
Notifications for django
License: MIT
Requires Python: <4.0,>=3.10

# Django Notifications

## Описание
**Django Notifications** — это приложение для управления уведомлениями в Django. Оно позволяет отслеживать изменения в моделях и отображать уведомления в админ-панели.

## Установка

1. Установите пакет через `poetry` или `pip`:
   ```sh
   poetry add azzlem-django-notifications
   ```
   или
   ```sh
   pip install azzlem-django-notifications
   ```

2. Добавьте `django_notifications` в **INSTALLED_APPS** в `settings.py` (в начало списка):
   ```python
   INSTALLED_APPS = [
       "django_notifications",
       # другие приложения...
   ]
   ```

## Настройка

### 1. Добавление URL-маршрутов

В файле `urls.py` основного проекта добавьте маршрут для уведомлений:
   ```python
   from django.urls import path
   from django_notifications.views import get_notifications
   
   urlpatterns = [
       path("django_notifications/admin/notifications/", get_notifications, name="notifications"),
   ]
   ```

### 2. Настройка отслеживаемых моделей

В `settings.py` укажите модели, за которыми нужно следить:
   ```python
   TRACKED_MODELS = [
       "appname.ModelName",  # Замените на ваши модели
   ]
   ```

### 3. Подключение кастомной админки (если используется)

Если у вас кастомная админка, добавьте `CustomAdminSite`:
   ```python
   from django_notifications.admin import CustomAdminSite
   from django.contrib import admin
   
   class MyAdminSite(CustomAdminSite, admin.AdminSite):
       pass
   ```

## Использование
После настройки уведомления будут автоматически создаваться при изменении отслеживаемых моделей. Вы сможете просматривать их в админке по пути:
```
/admin/notifications/
```

## Лицензия
Проект распространяется под лицензией **MIT**.

---

📧 **Контакты:** Если у вас есть вопросы или предложения, пишите на [azzlem.sid@gmail.com](mailto:azzlem.sid@gmail.com).
netoptim 0.1
Network Optimization Python Code
License: MIT

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# 🖧 netoptim

> Network Optimization Python Code

A longer description of your project goes here...

## Dependencies

- [luk036/ellalgo](https://github.com/luk036/ellalgo)
- [luk036/mywheel](https://github.com/luk036/mywheel)
- [luk036/digraphx](https://github.com/luk036/digraphx)
- networkx
- numpy

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## 👉 Note

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toktkn 0.1.2
a minimal byte-pair encoding tokenizer implementation
License: MIT
Keywords: nlp, python, maturin, pyo3

# 🪙 toktkn

toktkn is a [BPE](https://en.wikipedia.org/wiki/Byte_pair_encoding) tokenizer implemented in rust and exposed in python using [pyo3](https://github.com/PyO3/pyo3) bindings.

```python
from toktkn import BPETokenizer, TokenizerConfig

# create new tokenizer
config = TokenizerConfig(vocab_size: 10)
bpe = BPETokenizer(config)

# build encoding rules on some corpus
bpe.train("some really interesting training data here...")
text = "rust is pretty fun 🦀"

assert bpe.decode(bpe.encode(text)) == text

# serialize to disk
bpe.save_pretrained("tokenizer.json")
del(bpe)
bpe = BPETokenizer.from_pretrained("tokenizer.json")
assert(len(bpe)==10)
```

# Install 

Install `toktkn` from PyPI with the following

```
pip install toktkn
```

**Note:** if you want to build from source make sure cargo is installed!


# Performance

slightly faster than openai & a lot quicker than 🤗!

![alt text](performance.png)

Performance measured on 2.5MB from the [wikitext](https://huggingface.co/datasets/wikitext) test split using openai's [tiktoken gpt2 tokenizer](https://github.com/openai/tiktoken) with `tiktoken==0.6.0` and the [implementation from 🤗 tokenizers](https://huggingface.co/openai-community/gpt2) at `tokenizers==0.19.1`