semvec/pypi-packages huggingface dataset:
anime-actions 0.1.0
Fetch anime action and reaction images easily.
Requires Python: >=3.7

# anime-actions

Anime-themed action and reaction image API wrapper for Python.

![PyPI](https://img.shields.io/pypi/v/anime-actions)
![License](https://img.shields.io/github/license/monabborhossain/anime-actions)
![Downloads](https://img.shields.io/pypi/dm/anime-actions)

---

## ✨ Features

- Simple API to fetch anime reaction/action images
- Over 30+ categories: hug, pat, slap, wave, etc.
- Zero dependencies
- Fully async support

---

## 🚀 Installation

```bash
pip install anime-actions
```

---

## 🧪 Example

```python
import anime_actions

img_url = anime_actions.hug()
print(img_url)  # Outputs a random hug image URL
```

---

## 📚 Available Actions

- hug
- pat
- slap
- kiss
- wave
- ...and many more!

See full list in the [documentation](https://pypi.org/project/anime-actions/).

---

## 🌟 Star This Project

If you like this project, please consider [starring it on GitHub](https://github.com/monabborhossain/anime-actions) — it really helps!

---

## 🧑‍💻 Contributing

Pull requests are welcome. For major changes, please open an issue first.

---

## 📄 License

MIT License — see `LICENSE` file for details.

---

## ☕ Support Me

[![Buy Me a Coffee](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/monabborhossain)
aimon-llamaindex 0.0.9
The AIMon SDK for LlamaIndex related functionalities.
Requires Python: >3.8.0

# 🎉 **Welcome to AIMon-LlamaIndex**

**aimon-llamaindex** is an AIMon extension that integrates AIMon's advanced LLM reliability tools—such as detectors for hallucination, instruction adherence, completeness, conciseness, and toxicity—into the LlamaIndex framework.

### Installation

To install the AIMon LlamaIndex package, use pip:

```bash
pip install aimon-llamaindex
```
dbComm 0.4.1
Module for communicating with a (MongoDB) database
Requires Python: >=3.7
Keywords: mongoDB, pymongo, database

# dbComm

A Python wrapper for pymongo with support for SSH tunneling and LDAP authentication.

## Features

- Simple MongoDB connection interface
- SSH tunnel support
- LDAP authentication
- GridFS file operations
- Comprehensive type hints

## Installation

```bash
pip install dbComm
```

## Quick Usage

```python
from dbComm import Mongo

# Connect to database
db = Mongo(host="localhost")
db.setDB("mydatabase")

# Create record
record_id = db.newRecord("mycollection", field1="value1", field2="value2")

# Retrieve record
record = db.getRecord("mycollection", record_id)
```

## Documentation

For full documentation, visit [docs/index.md](docs/index.md)

## License
see [LICENSE](LICENSE)
django-annotated-property 0.1.0
Decorator for Django model properties that checks if an annotation exists on the instance.
Requires Python: >=3.6

# Django Annotated Property

Decorator for Django model properties that returns annotated values when available, 
avoiding database queries (f.e. O(N) vs O(1) for N items).

If a queryset includes `annotated_<property>`, the decorator uses it instead of calling the original method.


## Example

```python
from django.db import models
from django_annotated_property.annotated_property import annotated_property

class Product(models.Model):
    name = models.CharField(max_length=100)
    price = models.DecimalField(max_digits=8, decimal_places=2)

class OrderItem(models.Model):
    product = models.ForeignKey(Product, on_delete=models.CASCADE)
    quantity = models.PositiveIntegerField()

    @annotated_property
    def total_price(self):
        return self.product.price * self.quantity
```

now you can use the `total_price` property in your views or templates:

```python
items = (
    OrderItem.objects
    .annotate(annotated_total_price=models.F('product__price') * models.F('quantity'))
)
for item in items:
    print(item.total_price)  # returns annotated_total_price instead of the original method
```

## TODO

- [ ] Add tests
compphysutils 0.4.2
Set of utilities for computational condensed matter physics
Requires Python: >=3.6

# CompPhysUtils
## Collection of Python utilities for Computational Condensed Matter Physicists

CompPhysUtils is a library of utilities that automate and simplify certain mundane tasks so that you
can spend more time investigating physical phenomena and less time generating coordinates of various
clusters, deciding on details of plots etc.

The development is in early stages and is based on collection of code generated during the author's
PhD study. More code will be present in the future, as well as documentation.

CompPhysUtils aims to be highly configurable and highly extensible. As a library, it is distributed
under the LGPL v3 license, so that you can use it pretty much without restriction, but if you decide
to change its functionality or extended the code itself significantly, you are required to share it
with the community.