semvec/pypi-packages huggingface dataset:
niceman 0.1.0
Neuroimaging Computational Environments Manager

NICEMAN
=======

NICEMAN aims to simplify creation and management of computing
environments in Neuroimaging. While concentrating on Neuroimaging
use-cases, it is by no means is limited to this field of science and
tools will find utility in other fields as well.

Status
======

NICEMAN is under initial rapid development to establish core
functionality. While the code base is still growing the focus is
increasingly shifting towards robust and safe operation with a sensible
API. There has been no major public release yet, as organization and
configuration are still subject of considerable reorganization and
standardization.

See `CONTRIBUTING.md <CONTRIBUTING.md>`__ if you are interested in
internals and/or contributing to the project.

Code status:
------------

-  |Travis tests status| travis-ci.org (master branch)

-  |codecov.io|

-  |Documentation|

Installation
============

Debian-based systems
--------------------

On Debian-based systems we recommend to enable
`NeuroDebian <http://neuro.debian.net>`__ from which we will soon
provide recent releases of NICEMAN (as soon as there is something to
release). We will also provide backports of all necessary packages from
that repository.

Other Linux'es, OSX (Windows yet TODO) via pip
----------------------------------------------

By default, installation via pip installs core functionality of niceman
allowing for managing datasets etc. Additional installation schemes are
available, so you could provide enhanced installation via
``pip install niceman[SCHEME]`` where ``SCHEME`` could be

-  tests to also install dependencies used by unit-tests battery of the
   niceman
-  full to install all of possible dependencies.

For installation through ``pip`` you would need some external
dependencies not shipped from it (e.g. ``docker``, ``singularity``,
etc.) for which please refer to the next section.

Dependencies
------------

Our ``setup.py`` and corresponding packaging describes all necessary
dependencies. On Debian-based systems we recommend to enable
`NeuroDebian <http://neuro.debian.net>`__ since we use it to provide
backports of recent fixed external modules we depend upon. Additionally,
if you would like to develop and run our tests battery see
`CONTRIBUTING.md <CONTRIBUTING.md>`__ regarding additional dependencies.

Later we will provide bundled installations of NICEMAN across popular
platforms.

License
=======

MIT/Expat

Disclaimer
==========

It is in a alpha stage -- **nothing** is set in stone yet and nothing is
usable ATM -- subscribe and wait for the first release.

.. |Travis tests status| image:: https://secure.travis-ci.org/ReproNim/niceman.png?branch=master
   :target: https://travis-ci.org/ReproNim/niceman
.. |codecov.io| image:: https://codecov.io/github/ReproNim/niceman/coverage.svg?branch=master
   :target: https://codecov.io/github/ReproNim/niceman?branch=master
.. |Documentation| image:: https://readthedocs.org/projects/NICEMAN/badge/?version=latest
   :target: http://niceman.rtfd.org
vislparser 0.0.5
Automatic calls to VISL online parser

# Python VISL Parser
Python module for automating calls to the morphosyntactic parser online for portuguese [VISL](http://visl.sdu.dk/visl/pt/parsing/automatic/parse.php).

## Getting Started
The following instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

### Prerequisites
- Clone this repo
- Install `virtualenvwrapper` following the steps listed [here](https://medium.com/@gitudaniel/installing-virtualenvwrapper-for-python3-ad3dfea7c717)
- Create your venv using the command:
```
mkvirtualenv --python=<your_python3.6_installation_dir> <your_env_name>
```
- Install the needed modules using the command:
```
pip install -r requirements.pip
```
After that you shold be able to work just fine.

## Usage
To use the module you have just to import and call the `parse` method.

Example:
```python
import vislparser

vislparser.parse('Bom dia')

# [
#     {'word': 'bom', 'stem': 'bom', 'semantic_tags': [], 'word_class_tag': 'ADJ', 'other_tags': 'M S', 'syntatic_tag': '@>N'}, 
#     {'word': 'dia', 'stem': 'dia', 'semantic_tags': ['temp', 'dur', 'per', 'unit'], 'word_class_tag': 'N', 'other_tags': 'M S', 'syntatic_tag': '@NPHR'}
# ]
```

## Now GO TO WORK!