semvec/pypi-packages huggingface dataset:
aldryn-forms-recaptcha-plugin 1.0.0.3
A simple invisible recaptcha v3 implementation

# Aldryn Forms Recaptcha Plugin

This python module is open-source, available here: https://gitlab.com/what-digital/aldryn-forms-recaptcha-plugin/


## Setup

`pip install aldryn-forms-recaptcha-plugin`

Add the following to your `settings.py`: 

```
INSTALLED_APPS = [
    'aldryn_forms_recaptcha_plugin',
    'snowpenguin.django.recaptcha3',  # must be below the plugin
]
RECAPTCHA_PUBLIC_KEY = env('RECAPTCHA_PUBLIC_KEY', '123')
RECAPTCHA_PRIVATE_KEY = env('RECAPTCHA_PRIVATE_KEY', '123')
# set this to 0 (or 1) to deactivate (or always activate) the captcha protection
RECAPTCHA_SCORE_THRESHOLD = 0.85
```

If you're using bootstrap4, beware that django renders the form errors with class `invalid-feedback`, which is invisible in bs4.


## Versioning and Packages

- versioning is done in versioning in `aldryn_forms_recaptcha_plugin/__init__.py`
- for each version a tag is added to the gitlab repository in the form of `^(\d+\.)?(\d+\.)?(\*|\d+)$`, example: 0.0.10

- There is a PyPI version which relies on the gitlab tags (the download_url relies on correct gitlab tags being set): https://pypi.org/project/aldryn-forms-recaptcha-plugin/
- There is a DjangoCMS / Divio Marketplace add-on which also relies on the gitlab tags: https://marketplace.django-cms.org/en/addons/browse/aldryn-forms-recaptcha-plugin/

In order to release a new version of the Divio add-on:

- Increment version number in `addons-dev/aldryn-forms-recaptcha-plugin/aldryn_forms_recaptcha_plugin/__init__.py`
- divio addon validate
- divio addon upload
- Then git add, commit and tag with the version number and push to the repo

```
git add .
git commit -m "<message>"
git tag 0.0.XX
git push origin 0.0.19
```

Then, in order to release a new pypi version:

- python3 setup.py sdist bdist_wheel
- twine upload --repository-url https://test.pypi.org/legacy/ dist/*
- twine upload dist/*

### Development

- Run `pip install -e ../aldryn-forms-recaptcha-plugin/` in your demo project
- You can open aldryn_forms_recaptcha_plugin in pycharm and set the python interpreter of the demo project to get proper django support and code completion.


## Dependencies

- aldryn_forms
pyramaterised 1.0.2
Library for building, simulating and measuring Parameterised Quantum Circuits (PQCs).
Requires Python: >=3.10

<h1 align="center">
<img src="images/repo_logo.png" width="650">
</h1><br>

## About:
`pyramaterised` is a framework for creating and measuring Parameterised Quantum Circuits (PQCs)
in Python, by acting as a wrapper around the [`QuTIP` library](https://qutip.org/). A series of PQCs from the
literature have been implemented using the framework alongside various collated capacity
measures.

<h1 align="center">
<img src="images/explainer.png" width="1200">
</h1>

## Usage:
Simply run in your current (virtual) environment:
```
pip install pyramaterised
```
Check out `example.py` or `tests.py` for examples of the framework in action.

## Circuits:

<h1 align="center">
<img src="images/circuits.png" width="1200">
</h1>

A diagram of some of the circuits available in the library (custom circuits can be easily constructed). NPQC diagram from [[1]](https://arxiv.org/abs/2107.14063), XXZ and TFIM circuits adapted from [[2]](https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.1.020319) and fermionic circuit diagram from [[3]](https://www.science.org/doi/10.1126/science.abb9811).

## Capacity measures:
Capacity measures tell you how well an aspect of a PQC is performing, *e.g,* entanglement measures the amount of entanglement generated by the circuit, expressibility describes how well an *N* qubit circuit explores the *N* qubit Hilbert space.
- [Entanglement](https://arxiv.org/abs/quant-ph/0305094)
- [Expressibility](https://arxiv.org/abs/1905.10876)
- [QFIM](https://arxiv.org/abs/1909.05074)
- [Effective Quantum Dimension](https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.2.040309)
- [Rényi Entropy of Magic](https://arxiv.org/pdf/2106.12587)
- [GKP Magic](https://arxiv.org/abs/2109.13018)
- Effective Hilbert Space - new measure based on finding the subspace that minimises a circuit's expressibility.

## Technical decisions:
- Python: de-facto scientific programming language, interoperability with QuTIP important.
- Object oriented: circuits being comprised of layers of gates with similar shared behaviours seemed a good fit.
- Designed to allow users to create PQCs more easily than writing every gate by hand in QuTIP or similar program.

## Acknowledgements
Thanks to the `numpy`, `scipy`, `matplotlib` and `QuTIP` libraries.
Thanks to F. Roberts and T. Haug for their help.
docker-compose-reloaded 0.1
A python CLI tool to update stacks on event triggers

# docker-compose-reloaded
A python CLI tool to update stacks on event triggers like MQTT

> [!WARNING]  
> This project is just out of the oven and will introduce some breaking changes soon.

## Installation
The script can be installed via pip:
```bash
pip install docker-compose-reloaded
```

## Configuration

> [!NOTE]
> The default config path is `/etc/docker-compose-reloaded/config.json`.
> But you can change it with the `-f` option.

You can give it a quick start and use the [example config](./examples/mqtt.json),
which will restart some docker stacks if certain images are updated. The event
trigger in this exampel is an MQTT message to one of the subscribed topics.

### List of configuration options
| Option | Long Option | Description |
|--------|-------------|-------------|
| `-f`   | `--file`    | Config file path
| `-r`   | `--reload`  | Tims [s] to check for config changes


## Fire it up!
With the config present, you can just run
```bash
dcr run
```
or (if you have a custom config location)
```bash
dcr run -f /path/to/your/config.json
```
picalib 0.6.0
PiCa is lightweight and minimalist package for autodiff.


# PiCa

### PiCa is lightweight and minimalist package for autodiff.

#### This library is still under development, so it is recommended that it is only used on an experimental basis!

#### PiCa provides:
- Representing mathematical functions using computational graphs.
- Evaluation of functions
-  Obtain the derivatives of the variables of the function

#### Contribution:
The PiCa library is still under development, so you may not find some nodes you want to work with. More features will be added to the library continuously, and anyone is free to make a pull request. To make a pull request, it is important to point out the changes you have made and why you have made them. 


#### Installation



```bash
pip install picalib
```
#### Documentation:

[Docs](https://pica.readthedocs.io/en/latest/)

#### Code: 

[Github](https://github.com/PhilanthropiCat/PiCa)