semvec/pypi-packages huggingface dataset:
kaybee-bulma 0.2.31
Bulma-based theme for Kaybee
Keywords: sphinx theme blog website

kaybee_bulma theme for Kaybee and Sphinx
========================================

Kaybee is a Sphinx system for knowledge bases. ``kaybee_bulma`` is a theme
for Kaybee with the following goals:

- Based on the Bulma CSS framework

- Uses no HTML/CSS/JS from Sphinx

- Uses a modern toolchain (npm, SASS, webpack)

- Delivers a fast, attractive, mobile-oriented, and (later) offline
  web experience with unique capabilities

How To Release
--------------

Releases are driven by Travis. When a push is done with a tag, the Travis
build notices the tag and triggers the PyPI update. (Non-tagged pushes don't
trigger the PyPI part of ``.travis.yml``.)

#. Commit everything.

#. Bump the version using
   `bumpversion commands <https://github.com/peritus/bumpversion/issues/77#issuecomment-130696156>`_:

   - `bumpversion patch: 0.1.0 -> 0.1.1.dev0`

   - `bumpversion release: 0.1.1.dev0 -> 0.1.1`

   - `bumpversion minor: 0.1.1 -> 0.2.0.dev0`

   - `bumpversion dev: 0.2.0.dev0 -> 0.2.0.dev1`

   - `bumpversion release: 0.2.0.dev1 -> 0.2.0#. Tag the release.`

#. Commit, tag, push.

#. Run bumpversion to go back to dev

#. Run ``gitchangelog > CHANGES.rst`` to generate the history that goes into
   the package. Tip: Use the commit message prefixes from their `reference
   <https://github.com/vaab/gitchangelog/blob/master/src/gitchangelog/gitchangelog.rc.reference>`_

#. Commit, push (so people can see the history.)
simplesocket 0.3
simple implementation of python socket for creating server/client based programs supporting threading.

# simplesocket
simple implementation of python socket for creating server/client based programs supporting threading.

## Installation
```bash
pip3 install simplesocket
```

## Usage
in Server script import:

```python 3
from simplesocket import SimpleServer
```

and in Client script import:

```python 3
from simplesocket import SimpleClient
```
waldur-core 0.161.4
Waldur core is a core of Waldur cloud management service.

.. image:: https://travis-ci.org/opennode/waldur-core.svg?branch=develop
    :target: https://travis-ci.org/opennode/waldur-core
    :alt: Build status

Waldur Core
===========

Waldur Core is an open-source RESTful server for multi-tenant resource management. It provides an
easy way for sharing access to external systems. It is used as a platform for creating private and
public clouds.

Additional information can be found at http://docs.waldur.com.

Support
=======

Professional support options are available. Please contact info@opennodecloud.com for details.


Development environment setup
-----------------------------

Instructions here: https://github.com/opennode/waldur-core/blob/develop/docs/guide/install-from-src.rst.
scdn 0.0.2
Estimating high dimensional ODE models from convoluted observations with an application to fMRI

# Estimating high dimensional ODE models from convoluted observations with an application to fMRI
scdn is a Python-based package implementing sparse causal dynamic network analysis for convolution model, particular for Functional magnetic resonance imaging (fMRI) in our paper. It aims to provide a sparse dynamic network estimation not only for fMRI data but for other possible data that can be represented by convolution model. The introduction and explanation of parameters and ODE models can be found in [(1)]. For more details of convolution model, see [(2)]


## Getting Started

The examples provided in the repo have been tested in Mac os and Linux environment. This package supports both Python 2.7 and Python 3.6. 

These instructions will get you a copy of the project up running on your local machine for development and testing purposes. 

This package is also published in pypi.  For a quick installation, try

```
pip install scdn
```

### Prerequisites

What things you need to install the software and how to install them

```
See setup.py for details of packages requirements. 
```

### Installing from GitHub


Download the packages by using git clone https://github.com/xuefeicao/scdn.git

```
python setup.py install
```

If you experience problems related to installing the dependency Matplotlib on OSX, please see https://matplotlib.org/faq/osx_framework.html 

### Intro to our package
After installing our package locally, try to import scdn in your python environment and learn about package's function. 
```
from scdn.scdn_analysis import scdn_multi_sub
help(scdn_multi_sub)
```


### Examples
```
The examples subfolder includes two examples.
The first is a simulation generated from our data and another is from DCM.
```

## Running the tests

The test is going to be added in the future.

## Built With

* Python 2.7

## Compatibility
* Python 2.7
* Python 3.6 


## Authors

* **Xuefei Cao** - *Maintainer* - (https://github.com/xuefeicao)
* **Xi Luo** (http://bigcomplexdata.com/)
* **Björn Sandstede** (http://www.dam.brown.edu/people/sandsted/)


## License

This project is licensed under the MIT License - see the LICENSE file for details

[(1)]:http://www.fil.ion.ucl.ac.uk/~karl/Dynamic%20causal%20modelling.pdf
[(2)]:https://pdfs.semanticscholar.org/2127/7ee7b67970782bef59c9d657b144237bacbd.pdf
cdn-fmri 0.0.2
Implementations of Causal Dynamic Network Analysis of fMRI

# Causal Dynamic Network Modeling
cdn-fmri is a Python-based package implementing causal dynamic network analysis for Functional magnetic resonance imaging (fMRI). It aims to improve the dynamic causal modeling with the optimization based method. Our optimization-based method and algorithm compute efficiently the ODE parameters from fMRI data, instead of comparing potentially a huge number of candidate ODE models. For a detailed introduction of dynamic causal modeling, see [(1)].



## Getting Started
This package supports both python 2.7 and python 3.6.

The example provided in the repo has been tested in mac os and Linux environment. 

These instructions will get you a copy of the project up running on your local machine for development and testing purposes. 

This package is also published in pypi.  For a quick installation, try

```
pip install cdn-fmri 
```

### Prerequisites

What things you need to install the software and how to install them

```
See setup.py for details of packages requirements. 
```

### Installing from GitHub


Download the packages by using git clone https://github.com/xuefeicao/cdn.git

```
python setup.py install
```

If you experience problems related to installing the dependency Matplotlib on OSX, please see https://matplotlib.org/faq/osx_framework.html 

### Intro to our package
After installing our package locally, try to import cdn in your python environment and learn about package's function. 
Note: our package name in pypi is cdn-fmri.
```
import cdn.cdn_analysis as cdn_analysis
help(cdn_analysis.cdn_multi_sub)
```


### Examples
```
The examples subfolder includes a basic analysis of CDN analysis.
```

## Built With

* Python 2.7

## Compatibility
* python 2.7
* python 3.6 

## Authors

* **Xuefei Cao** - *Maintainer* - (https://github.com/xuefeicao)
* **Xi Luo** (http://bigcomplexdata.com/)
* **Björn Sandstede** (http://www.dam.brown.edu/people/sandsted/)


## License

This project is licensed under the MIT License - see the LICENSE file for details

[(1)]:http://www.fil.ion.ucl.ac.uk/~karl/Dynamic%20causal%20modelling.pdf
Structuralia 0.912
A toolset to work with proteins
Keywords: PDB,structure,protein

Structuralia
############

This suite of python scripts was built to access the PDB database and both prepare inputs and read generated output files.

It relies mainly on Biopython and Biopandas to manipulate PDB structures in convenient ways.

Simply run AccessPDB to perform some of these functions intuitively.

The Toolbox is packed up with functions that can be imported and used in your own scripts.

Installation
************
The scripts are available as a `PyPi project`_. Just install them with:

.. _`PyPi project`: https://pypi.org/project/Structuralia/



:code:`pip install Structuralia`



Prerequisites
*************

The following packages and external programs are used by Structuralia scripts and must be installed and in either the binaries path or python path.

Python packages
===============

  - progressbar
  - pandas
  - biopython
  - biopandas
  - pathlib
  - parasail

External software (must be installed separately)
================================================

  - `TM-align`_
  - `GESAMT`_

.. _`TM-align`: https://zhanglab.ccmb.med.umich.edu/TM-align/
.. _`GESAMT`: http://www.ccp4.ac.uk/html/gesamt.html


Author
******

Pedro Torres, Ph.D

Department Of Biochemistry
University of Cambridge
80 Tennis Court Road
Cambridge CB2 1GA

License
*******

This project is licensed under GNU license, provided along with the package - see `LICENSE`_.

.. _LICENSE: https://github.com/monteirotorres/Structuralia/blob/master/LICENSE