semvec/pypi-packages huggingface dataset:
asciisciit 0.3.0
asciisciit is a Python toolbox for displaying and converting images, movies, and camera feeds into ascii.
License: MIT
Keywords: ascii,opencv,PIL,terminal

asciisciit is a Python toolbox for displaying and
converting images, movies, gifs, and webcam feeds into ASCII.  It uses
Numpy, and PIL for image processing, OpenCV for camera access, ffmpeg for
video writing, and is tested on windows and linux.
ankix 0.2.0.1
New file format for Anki with improved review intervals and Peewee SQLite powered
License: MIT
Keywords: anki,spaced-repetition,SRS

# Ankix

[![PyPI version shields.io](https://img.shields.io/pypi/v/ankix.svg)](https://pypi.python.org/pypi/ankix/)
[![PyPI license](https://img.shields.io/pypi/l/ankix.svg)](https://pypi.python.org/pypi/ankix/)

New file format for Anki with improved review intervals. Pure [peewee](https://github.com/coleifer/peewee) SQLite database, no zipfile. Available to work with on Jupyter Notebook.

## Usage

On Jupyter Notebook,

```python
>>> from ankix import ankix, db as a
>>> ankix.init('test.ankix')  # A file named 'test.ankix' will be created.
>>> ankix.import_apkg('foo.apkg')  # Import the contents from 'foo.apkg'
>>> iter_quiz = a.iter_quiz()
>>> card = next(iter_quiz)
>>> card
'A flashcard is show on Jupyter Notebook. You can click to change card side, to answer-side.'
'It is HTML, CSS, Javascript, Image enabled. Cloze test is also enabled. Audio is not yet tested.'
>>> card.right()  # Mark the card as right
>>> card.wrong()  # Mark the card as wrong
>>> card.mark()  # Add the tag 'marked' to the note.
```

You can directly make use of Peewee capabilities,

```python
 >>> a.Card.select().join(a.Note).where(a.Note.data['field_a'] == 'bar')[0]
 'The front side of the card is shown.'
```

## Adding new cards

Adding new cards is now possible. This has been tested in https://github.com/patarapolw/zhlib/blob/master/zhlib/export.py#L15

```python
from ankix import ankix, db as a
ankix.init('test.ankix')
a_model = a.Model.add(
    name='foo',
    templates=[
        a.TemplateMaker(
            name='Forward', 
            question=Q_FORMAT,
            answer=A_FORMAT
        ),
        a.TemplateMaker(
            name='Reverse', 
            question=Q_FORMAT,
            answer=A_FORMAT)
    ],
    css=CSS,
    js=JS
)
# Or, a_model = a.Model.get(name='foo')
for record in records:
    a.Note.add(
        data=record,
        model=a_model,
        card_to_decks={
            'Forward': 'Forward deck',
            'Reverse': 'Reverse deck'
        },
        tags=['bar', 'baz']
    )
```

## Installation

```commandline
$ pip install ankix
```

## Plans

- Test by using it a lot.
punica-neo-boa 0.4.9
A simplified Python compiler for the Neo Virtual Machine to support ontology-python-punica
License: MIT
Requires Python: >=3.6
Keywords: compiler NEO .avm blockchain smartcontract development dApp

# punica-neo-boa

## Overview

The `punica-neo-boa` compiler is a tool fork from the branch of [ontio](https://github.com/ontio/neo-boa) and simplifies the project to support [python-punica](https://github.com/ontio-community/punica-python) .

The compiler supports a subset of the Python language ( in the same way that a _boa constrictor_ is a subset of the Python snake species)


#### What does it currently do

- Compiles a subset of the Python language to the `.avm` format for use in the [Ontology](https://github.com/ontio/ontology)
- Works for Python 3.6+
- supports dictionaries


#### What will it do

- Compile a larger subset of the Python language

## Installation

Installation requires a Python 3.6 or later environment.

```
pip install obox-neo-boa
```

## License

- Open-source [MIT](LICENSE.md).
- Main author is [@localhuman](https://github.com/localhuman).


## Donations

Accepted at __ATEMNPSjRVvsXmaJW4ZYJBSVuJ6uR2mjQU__
neldermead 0.0.12
Nelder-Mead for numerical optimization in Python
License: MIT
Keywords: optimization,Nelder-Mead

# neldermead

Nelder-Mead implementation

[![CircleCI](https://circleci.com/gh/nmasahiro/neldermead.svg?style=shield)](https://circleci.com/gh/nmasahiro/neldermead)

## Getting Started


### Prerequisites

You need only [NumPy](http://www.numpy.org/) that is the package for scientific computing.

### Installing

Please run the following command.

```bash
$ pip install neldermead
```

## Example

This is a simple example that objective function is sphere function.

```python
import numpy as np
from neldermead import NelderMead

dim = 3
f = lambda x: np.sum(x**2)
simplex = np.zeros([dim, dim + 1])
for i in range(dim + 1):
    simplex[:, i] = np.array([np.random.rand() for _ in range(dim)])
nm = NelderMead(dim, f, simplex)

x_best, f_best = nm.optimize(100)
print("x_best:{}, f_best:{}".format(x_best, f_best))
#x_best:[[-1.48045204e-08]
# [-1.80962770e-08]
# [ 5.08040874e-08]], f_best:3.1277043680572982e-15
```


## Versioning

We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/nmasahiro/neldermead/tags). 


## License

This project is licensed under the MIT License - see the [LICENSE](https://github.com/nmasahiro/neldermead/blob/master/LISENCE) file for details