semvec/pypi-packages huggingface dataset:
dbuy-webassets-webpack 0.1.7
Webpack filter for webassets
License: MIT
Keywords: webpack,webassets,django assets,pyramid assets


Webpack filter for webassets
-------------------------------

.. image:: https://travis-ci.org/suryakencana/webassets-webpack.svg?branch=master
    :target: https://travis-ci.org/suryakencana/webassets-webpack


Filter for for compiling assets using `Webpack <https://webpack.js.org>`_ and
`webassets <http://webassets.readthedocs.org>`_.

Basic usage
```````````

.. code:: python

    from webassets.filter import register_filter
    from webassets_browserify import Webpack

    register_filter(Webpack)


Usage with Django
`````````````````

This requires `django-assets <http://django-assets.readthedocs.org>`_.

.. code:: python

    from django_assets import Bundle, register
    from webassets.filter import register_filter
    from webassets_webpack import Webpack

    register_filter(Webpack)

    js = Bundle('js/main.js', filters='webpack', output='bundle.js',
                depends='js/**/*.js')
    register('js_all', js)
ltsv2json 1.0.2
LTSV-to-JSON converter
License: MIT

ltsv2json
=========

.. image:: https://travis-ci.org/hoffa/ltsv2json.svg?branch=master
   :target: https://travis-ci.org/hoffa/ltsv2json

Reads LTSV from ``stdin`` and prints JSON to ``stdout``.

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

::

  pip install ltsv2json

Usage
-----

::

  $ printf "world:bar\thello:foo\nworld:turtle" | ltsv2json
  {"world":"bar","hello":"foo"}
  {"world":"turtle"}
pjbcma 0.0.5
An assistant for using pyjags
License: MIT

# Bayesian Cognitive Modeling with `pyjgags` assistant

This is a project to port the code examples in Lee and Wagenmakers' 2013 textbook [Bayesian Cognitive Modeling: A Practical Course](https://bayesmodels.com/) from MATLAB into Python, using the [pyjags](https://github.com/tmiasko/pyjags) package for interfacing Python code with the `JAGS` Gibbs sampling application.

The main contribution is the module `pjbcmassistant`, which contains convenience classes `ModelHandler` and `SampleHandler` for easily interfacing with `pyjags`, and for performing basic analysis on the model samples it produces.

### Quick Start:
The notebook [PyJAGS-BCM Usage Guide](https://github.com/icushman/pjBCM/blob/master/GettingStarted/PyJAGS-BCM%20Usage%20Guide.ipynb) provides a demonstration and overview of how to use the module for building and analyzing models.

See the [full documentation](https://github.com/icushman/pjBCM/blob/master/docs.md) for details on all methods provided by the module.

*NOTE:*  
In addition to dependencies listed in requirements.txt, this module requires that `JAGS` (which is not a Python package) be successfully installed on your system prior to configuring `pyjags`. See the [JAGS website](http://mcmc-jags.sourceforge.net/) and the [pyjags installation instructions](https://pyjags.readthedocs.io/en/latest/getting_started.html) for details.