semvec/pypi-packages huggingface dataset:
gmsh_interop 2019.1
A parser for GMSH's .msh format
License: MIT

Interoperability between Python and Gmsh
========================================

This package allows Python to interoperate with the `gmsh <http://gmsh.info/>`_
mesh generator.

This package contains:

* ``gmsh_interop.reader`` to read gmsh's ``.msh`` file format.
* ``gmsh_interop.runner`` to run gmsh under program control and process its output.

Its contents was extracted from `meshpy <https:///github.com/inducer/meshpy>`_
to escape its obnoxious licensing.

Links:

* `Github <https://github.com/inducer/gmsh_interop>`_
* `Python package index <https://pypi.org/project/gmsh_interop/>`_

----

gmsh_interop is licensed to you under the MIT/X Consortium license:

Copyright (c) 2009-17 Andreas Kloeckner and Contributors.

Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"), to deal in the Software without
restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following
conditions:

The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
aidu 0.0.1
Artifical Intelligence, Do
License: MIT
Requires Python: >=3.6.0


# aidu

Artificial Intelligence, Do

## License

[Apache Version 2.0](LICENSE)

```text
Copyright 2019 Alexander W. Wong
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
```
harmonique 0.0.3
a sad little personal static blog generator
License: MIT
Keywords: static-site blog markdown python

# Introduction

A sad little static blog generator. Nothing fancy.

## Installation

Run:

```
pip install harmonique
```

## Example blog project

Clone/download this repository and check out the `example` directory.

## Commands


### Compile everything, including drafts

```bash
harmonique dev
```

### Compile published, skip drafts

```bash
harmonique prod
```

Append `serve` on the commands above to run the local server that
serves the output files at `localhost:8889`. The server also watches
for file changes and rebuilds. Works with both `dev` and `prod` modes.
romanify 0.0.8
Roman numbers converting library
License: MIT
Requires Python: >3.4.*, <4

romanify
========

.. image:: https://coveralls.io/repos/github/JaneTurueva/py-romanify/badge.svg?branch=master
    :target: https://coveralls.io/github/JaneTurueva/py-romanify?branch=master
    :alt: Coveralls

.. image:: https://travis-ci.org/JaneTurueva/py-romanify.svg
    :target: https://travis-ci.org/JaneTurueva/py-romanify
    :alt: Travis CI

.. image:: https://img.shields.io/pypi/v/romanify.svg
    :target: https://pypi.python.org/pypi/romanify/
    :alt: Latest Version

.. image:: https://img.shields.io/pypi/wheel/romanify.svg
    :target: https://pypi.python.org/pypi/romanify/

.. image:: https://img.shields.io/pypi/pyversions/romanify.svg
    :target: https://pypi.python.org/pypi/romanify/

.. image:: https://img.shields.io/pypi/l/romanify.svg
    :target: https://pypi.python.org/pypi/romanify/


Roman numbers converting library.

Library uses following mapping:

========  ===========
Arabic    Roman
========  ===========
M         1000
CM        900
D         500
CD        400
C         100
XC        90
L         50
XL        40
X         10
IX        9
V         5
IV        4
I         1
========  ===========

Installation
------------

.. code-block:: shell

    pip install romanify


Command-line usage
------------------
.. code-block:: shell

    romanify 101
    > CI


Library usage
-------------
.. code-block:: shell

    from romanify import romanify

    print(romanify(101))


Versioning
==========

This software follows `Semantic Versioning`_

.. _Semantic Versioning: http://semver.org/
datazoo 0.0.3
The deep learning datasets provider
License: MIT

# Data zoo

This repository provides unified access to multiple datasets.

## Usage

First of all, you have to import data_provider from datazoo package:

```
from datazoo import data_provider
```

Then, you can select dataset from the list and get iterable:

```
# Dataset object
fashionmnist = data_provider(
	dataset='fashionmnist',	data_dir='data/fashionmnist/', split='test',
	download=True, columns=['index', 'image', 'class']
)

print('Dataset length:', len(fashionmnist))

# Iterate over samples
for i in fashionmnist:
    print(i) 
```

## Classification

### Single-label datasets

| Dataset | Name in data provider | Number of classes | Number of samples | Source | Auto downloading |
| --- | ---: | ---: | ---: | ---: | ---: |
| MNIST | `mnist` | 10 | 60 000 / 10 000 | torchvision | Yes |
| Fashion MNIST | `fashionmnist`| 10 | 60 000 / 10 000 | torchvision | Yes |
| CIFAR-10 | `cifar10` | 10 | 50 000 / 10 000 | torchvision | Yes |
| CIFAR-100 | `cifar100` | 100 | 50 000 / 10 000 | torchvision | Yes |
| [Indoor Scene Recognition](http://web.mit.edu/torralba/www/indoor.html) | `indoor_scene_recon` | 67 | 15620 | -- | Yes |
| [The Street View House Numbers (SVHN)](http://ufldl.stanford.edu/housenumbers/) | `svhn_cropped` | 10 | 73257 digits for training, 26032 digits for testing, and 531131 additional | -- | Yes |
| [Linnaeus5](http://chaladze.com/l5/) | `linnaeus5` | 5 classes: berry, bird, dog, flower, other (negative set) | 1200 training images, 400 test images per class | -- | Yes |
| [COIL-100](http://www1.cs.columbia.edu/CAVE/software/softlib/coil-100.php) | `coil100` | 100 (100 objects) | 7200 images | -- | Yes |

<!-- ### Multiple labels datasets -->
<!-- 
## Segmentation

| Dataset | Number of classes | Number of samples | Description | Source |
| --- | ---: | ---: | ---: | ---: |
| ADE20k | 10 | 60 000 / 10 000 | General-purpose scene parsing | torchvision | -->

## License
This software is covered by MIT License.