semvec/pypi-packages huggingface dataset:
django-cloudimage 1.0.1
Django wrapper for cloudimage.io
License: MIT
Keywords: django resize image

django-cloudimage
=================

A Django wrapper for https://cloudimage.io

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

Install via pip:

::

    pip install django-cloudimage

Usage
-----

1. Add to ``INSTALLED_APPS`` in ``settings.py`` ``'cloudimage',``
2. Add the ``CLOUDIMAGE_TOKEN`` in ``settings.py``
3. Add the include to urlpatterns in ``urls.py``
   ``urlpatterns = [ url(r'^media/', include('cloudimage.urls')), ]``
4. Load the template tag into a template ``{% load cloudimage %}``
5. Use the ``image`` tag. ``{% image 'path/to/image.jpg' width=100 %}``
   Visit the `CloudImage
   Docs <https://cloudimage.io/en/docs/introduction>`__ for all of the
   options. Convert parameters to kwargs.

Options
-------

Cache Control headers
~~~~~~~~~~~~~~~~~~~~~

It is highly recommended that if you use this package your site should
be sitting behind a CDN. Not sure what this is, check out
https://www.cloudflare.com/

Add to ``settings.py``

To set an expiration timeout use an integer in seconds. For example,
below the image is set to cache for an hour.

::

    CLOUDIMAGE_CACHE_CONTROL = 3600

This will output ``Cache-Control max-age=3600`` in the response header.

**The advanced option**

Any string you pass that doesn't convert to an int will be set in the
header.

::

    CLOUDIMAGE_CACHE_CONTROL = "no-cache"

This will output ``Cache-Control no-cache`` in the response header.

Caveats
-------

-  `KISS <https://en.wikipedia.org/wiki/KISS_principle>`__
-  The origional image must be accessable via a URL, so RSZ.IO can
   access it. I use
   `django-storages <https://django-storages.readthedocs.io/en/latest/>`__
   with AWS S3 to serve my media.
-  This is tested and used in production with Django 1.10 and 1.11 on
   Python 3.5 and 3.6. But this should work on older versions of Django
   and Python 2. Open an issue or pull request if not the case.

Versioning
----------

The package is following the Major.Minor.BugFix philosophy. So breaking
changes will increase the major number. New features will increase the
minor number.

So it is safe to put this line in your ``requirements.txt``

**All new features, no breaking features**

::

    django-cloudimage>=1.0.0,<2.0

**Just bugfixes**

::

    django-cloudimage>=1.0.0,<1.1

Release Notes
-------------

This project is using GitHub's release feature. Find the release notes
here https://github.com/g3rd/django-cloudimage/releases
humilis-sam 0.1.3
Humilis plug-in to deploy a SAM application
License: MIT

Humilis plug-in to deploy a SAM application
===================================================

[![PyPI](https://img.shields.io/pypi/v/humilis-sam.svg?style=flat)](https://pypi.python.org/pypi/humilis-sam)

A [humilis][humilis] plug-in layer that deploys a [SAM application][AWS SAM].

[AWS SAM]: https://github.com/awslabs/serverless-application-model/blob/master/versions/2016-10-31.md
[humilis]: https://github.com/humilis/humilis


## Installation


```
pip install humilis-sam
```


To install the development version:

```
pip install git+https://github.com/humilis/humilis-sam
```


## Development

Assuming you have [virtualenv][venv] installed:

[venv]: https://virtualenv.readthedocs.org/en/latest/

```
make develop
```

Configure humilis:

```
make configure
```


## Testing

You can test the deployment of a serverless API with:

```
make test
```

The test suite should destroy the deployed API automatically, but you
can make sure you are not leaving any infrastructure behind by manually
running:

```bash
make delete
```


## Examples

To see some examples of how to use this Humilis layer refer to the integration
tests :
```
tests/integration/humilis-sam-classic.yaml
tests/integration/humilis-sam-swagger.yaml
```

The SAM application can be deployed using a swagger file or not.
If you chose to use the swagger method, the swagger template will be generated
automatically and outputed next to your environment file.


## More information

See [humilis][humilis] documentation.

[humilis]: https://github.com/humilis/humilis/blob/master/README.md


## Contact

If you have questions, bug reports, suggestions, etc. please create an issue on
the [GitHub project page][github].

[github]: http://github.com/humilis/humilis-sam


## License

This software is licensed under the [MIT license][mit].

[mit]: http://en.wikipedia.org/wiki/MIT_License

See [License file][LICENSE].

[LICENSE]: https://github.com/humilis/humilis-sam/blob/master/LICENSE.txt


© 2017 Arnaud Charpentier, [Find Hotel][fh] and others.

[fh]: http://company.findhotel.net
mixem 0.1.4
Expectation-Maximization (EM) algorithm for fitting mixtures of probability distributions
License: MIT
Keywords: numeric em expectation maximization probability statistics distribution

mix'EM 
======


mixem is a pure-python implementation of the Expectation-Maximization (EM) algorithm for fitting mixtures of probability distributions. It works in Python 2 and Python 3 (tested with 2.7 and 3.5.1) and uses few dependencies (only NumPy and SciPy).


.. image:: http://i.imgur.com/kJgsHMG.png
   :scale: 50 %
   :alt: Old Faithful example
   :align: left


Features
--------

* Easy-to-use and fully-documented API
* Built-in support for several probability distributions
* Easily define custom probability distributions by implementing their probability density function and weighted log-likelihood

Documentation
-------------
Find the mix'EM documentation on `ReadTheDocs <https://mixem.readthedocs.org/en/latest/>`_.


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

::

    pip install mixem
GetIsolationSources 1.5.2
Retrieves isolation sources from NCBI given the set of sequences with specified accession numbers. Both nucleotide and protein accessions are accepted.
License: MIT
Keywords: bioinformatics,ncbi,entrez

**GetIsolationSources** is a small command line utility that, given fasta files containing GenBank IDs in sequence descriptions, generates a per sequence list of isolation sources and their distribution (i.e. number of sequences per isolation source).

It searches for IDs using regular expressions in accordance with [NCBI specifications](http://www.ncbi.nlm.nih.gov/Sequin/acc.html), so the format of description strings does not matter.

To obtain needed information it uses automated Entrez queries, so you need a working Internet connection to perform the analysis. Queries are made in accordance with NCBI load-balance regulations, therefore processing several thousand records may take several minutes or even longer.

It is distributed as a source code supporting python setup tools.

**GetIsolationSources uses [BioPython](http://biopython.org/wiki/Main_Page).** So if you're using source code distribution, the latest version of [BioPython](http://biopython.org/wiki/Main_Page) should be installed.

[**Downaloads**](https://github.com/allista/GetIsolationSource/releases)

***

**GetIsolationSources** by [**Allis Tauri**](https://github.com/allista) is licensed under the [MIT](https://github.com/allista/GetIsolationSources/blob/master/LICENSE) license.