semvec/pypi-packages huggingface dataset:
sagar 0.2.1
Structures of Alloys Generation And Recognition
License: MIT
Keywords: crystal material strucutre DFT

sagar
=====

.. image :: https://travis-ci.org/scut-ccmp/sagar.svg?branch=master
    :target: https://travis-ci.org/scut-ccmp/sagar
    :alt: Build Status

.. image ::https://codecov.io/gh/scut-ccmp/sagar/branch/master/graph/badge.svg
    :target: https://codecov.io/gh/scut-ccmp/sagar
    :alt: codecov

.. image :: https://readthedocs.org/projects/sagar/badge/?version=latest
    :target: https://sagar.readthedocs.io/
    :alt: Documentation Status

.. image :: https://badges.frapsoft.com/os/mit/mit.svg?v=103
    :target: https://opensource.org/licenses/mit-license.php
    :alt: MIT Licence

.. image :: https://badges.frapsoft.com/os/v1/open-source.svg?v=103
    :target: https://opensource.org/licenses/mit-license.php
    :alt: Open Source Love

.. image :: https://img.shields.io/pypi/pyversions/ansicolortags.svg
    :target: https://pypi.python.org/pypi/ansicolortags/
    :alt: PyPI pyversions

Introduction
++++++++++++

sagar is short for (S)Tructures of (A)lloys (G)eneration (A)nd (R)ecognition.

It is a library with some uitils to deal grid site
 structures.
audio-utils 0.0.1
Miscellaneous audio processing scripts.
License: MIT
Keywords: audio internet-archive

|Build Status| |Documentation Status|

Audio utils
-----------

Miscellaneous audio processing tools.

For users
=========

-  `Autogenerated Docs on readthedocs (might be
   broken) <http://audio_utils.readthedocs.io/en/latest/>`__.
-  Manually and periodically generated docs
   `here <https://sanskrit-coders.github.io/audio_utils/build/html/>`__
-  For detailed examples and help, please see individual module files in
   this package.

Installation or upgrade:
------------------------

-  ``sudo pip install audio_utils -U``
-  ``sudo pip install git+https://github.com/sanskrit-coders/audio_utils/@master -U``
-  `Web <https://pypi.python.org/pypi/audio_utils>`__.

For contributors
================

Contact
-------

Have a problem or question? Please head to
`github <https://github.com/sanskrit-coders/audio_utils>`__.

Packaging
---------

-  ~/.pypirc should have your pypi login credentials.

::

   python setup.py bdist_wheel
   twine upload dist/* --skip-existing

Build documentation
-------------------

-  sphinx html docs can be generated with ``cd docs; make html``

Testing
-------

Run ``pytest`` in the root directory.

Auxiliary tools
---------------

-  |Build Status|
-  |Documentation Status|
-  `pyup <https://pyup.io/account/repos/github/sanskrit-coders/audio_utils/>`__

.. |Build Status| image:: https://travis-ci.org/sanskrit-coders/audio_utils.svg?branch=master
   :target: https://travis-ci.org/sanskrit-coders/audio_utils
.. |Documentation Status| image:: https://readthedocs.org/projects/audio_utils/badge/?version=latest
   :target: http://audio_utils.readthedocs.io/en/latest/?badge=latest
async_freesia 0.1.2
A concise and lightweight web framework.✨
License: MIT
Keywords: freesia

![freesia](./images/logo.png)

## Introduction
Freesia is a concise and lightweight async web framework. Its api is inspired by Flask.

## Installation
```bash
pip install async-freesia
```

## Docs
You can find the project's detailed API documentation on [here](https://freesia.readthedocs.io/en/latest/?).

## Example
*hello world*
```python
from freesia import Freesia

app = Freesia()

@app.route('/hello/<name>')
async def hello(request, name):
    return "Hello, " + name + "!"

if __name__ == "__main__":
    app.run()
```

*middleware*
```python
from freesia import Freesia

app = Freesia()

@app.route("/<name>")
async def hello(request, name):
    print("enter user handler")
    return "hello, " + name


async def middleware1(request, handler):
    print("enter middleware1")
    res = await handler()
    print("exit middleware1")
    return res + " !"


async def middleware2(request, handler):
    print("enter middleware2")
    res = await handler()
    print("exit middleware2")
    return res + " :D"


app.use([middleware1, middleware2])

if __name__ == "__main__":
    app.run()
```

*session*
```python
from freesia import Freesia, set_up_session, get_session, Response
from freesia.session import SimpleCookieSession

app = Freesia()

@app.route("/")
async def hello(request):
    s = await get_session(request)
    if "count" not in s:
        s["count"] = 1
        return Response(text="Hello, stranger!")
    else:
        s["count"] += 1
        return Response(text="I've seen you %d times" % s["count"])

if __name__ == "__main__":
    set_up_session(app, SimpleCookieSession)
    app.run()
```

## More
You can see more exmaple and usags in [docs](https://freesia.readthedocs.io/en/latest/?) and [examples](./examples).
spines 0.0.6
Backbones for parameterized models.
License: MIT
Keywords: spines parameterized models

# Spines

<img width="20%" align="right" src="./docs/_static/images/spines_logo_256.png" alt="Spines Logo" style="margin-left: 10px;">

*Skeletons for parameterized models.*

[![Build Status](https://travis-ci.org/douglasdaly/spines.svg?branch=master)](https://travis-ci.org/douglasdaly/spines)
[![Coverage Status](https://coveralls.io/repos/github/douglasdaly/spines/badge.svg)](https://coveralls.io/github/douglasdaly/spines)
[![Documentation Status](https://readthedocs.org/projects/spines/badge/?version=latest)](https://spines.readthedocs.io/en/latest/?badge=latest)
[![PyPI](https://img.shields.io/pypi/v/spines.svg)](https://pypi.org/project/spines/)
[![Status](https://img.shields.io/pypi/status/spines.svg)](https://pypi.org/project/spines/)
[![Python Versions](https://img.shields.io/pypi/pyversions/spines.svg)](https://pypi.org/project/spines/)

**Important:** This software is still in it's early alpha phase and is 
constantly in flux.  It will likely change significantly.


## Installation

To install spines use your package manager of choice, an example using 
`pipenv` would be:

```bash
$ pipenv install spines
```


## About

Spines is a library which provides a consistent (and hopefully familiar) 
framework for building predictive models.  It's core Model class is 
similar, in structure, to some of scikit-learn's underlying Estimator 
classes - but with a single set of unified functions for all models, 
namely:

- Construct
- Fit
- Train
- Predict
- Error
- Score

The ```predict``` method is the only one that's required to be 
implemented, though the others are likely useful most of the time (and 
often required to take advantage of some of the additional features 
provided by spines).

Spines was built because the process of developing a model could be 
significantly aided by an intelligent framework keeping tabs on changes, 
storing results and helping you iterate. The purpose of spines was to 
give a simple (and not too opinionated) interface/skeleton for models as 
well as provide some helpful utilities for the model building process.
To accomplish this spines provides some useful key features:

- Standardized format for models of all types.
- Automatic version management.
- Storing intermediate/iterative results during the model development
  and training/fitting process.
- A unified storage format for models to facilitate collaboration,
  training and deployment.


## Documentation

The latest documentation is hosted on 
[read the docs](https://spines.readthedocs.io/ "Spines ReadTheDocs").


## License

This project is licensed under the MIT License, for more information see 
the [LICENSE](https://github.com/douglasdaly/spines/blob/master/LICENSE) 
file.