Metadata-Version: 2.1
Name: enlp
Version: 0.0.0
Summary: 
        Python library of NLP functions originally collated by Equinor Knowledge and AI Data Science team.
        
Home-page: UNKNOWN
Author: Equinor ASA
Author-email: clbi@equinor.com
License: UNKNOWN
Description: [![Build Status](https://travis-ci.org/equinor/eNLP.svg?branch=master)](https://travis-ci.org/equinor/eNLP)
        [![Azure Status](https://dev.azure.com/eNLP/eNLP/_apis/build/status/equinor.eNLP?branchName=master)](https://dev.azure.com/eNLP/eNLP/_build/latest?definitionId=1&branchName=master)
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        # Equinor Shared NLP Package
        This package contains functions often used in NLP ranging from processing to visualisation. The purpose behind the 
        package is to collect in one place common functions where a package can be installed to setup an nlp-focussed
        environment and most common nlp tasks can be carried out without having to install extra packages. 
        
        # INSTALLATION
        To install the package directly from github: 
        
            $ pip install git+https://github.com/equinor/eNLP.git
        
        If you wish to download the files directly and install, we recommend one of the 3 options as outlined below. Note that 
        the first two options use a Makefile.
        
        #####  Using the Makefile and conda environment:
        Download or clone the repo and run 
        
            $ make install_conda
        which will create a conda environment with the package installed and all the necessary requirements. Prior to using
        the package remember to change into your new environment.
        
            $ source activate enlp
            
        #####  Using the Makefile and pip requirements:   
        Download or clone the repo and run 
        
            $ make install
            
        ##### Without using the Makefile:
        Download or clone the repo and run
        
            $ pip install -r requirements.txt
            $ pip install . 
        
        # DEVELOPING AND CONTRIBUTING 
        We actively encourage others to contribute to the development of the package. 
        
        
        ### DEV INSTALLATION
        To install the extra requirements for development, the following options can be 
        followed:
        
        #####  Using the Makefile and conda environment:
        Download or clone the repo and run 
        
            $ make dev-install_conda
            $ source activate enlp
            
        #####  Using the Makefile and pip requirements:  
        Download or clone the repo and run 
        
            $ make dev-install
            
        ##### Without using the Makefile:
        Download or clone the repo and run
        
            $ pip install -r requirements-dev.txt
            $ pip install -e .
        
        
        
        ## CONTRIBUTING GUIDELINES
        Prior to contributing back to the package, please make the documentation and read the section on contributing. In 
        particular, prior to contributing please ensure all tests run and all new code is adequately documented and any 
        required new tests have been wrote.
        
        ## DEV DOCUMENTATION
        The documentation includes reference documentation for all functions as well as an example gallery.
        
        To make the documentation,
         
            $ make doc
        
        And then open the documentation and navigate to the example gallery,
        
            $ cd /docs/build/html
            $ open index.html
        .
        
        All new features should have clear doc strings and have their paths included in the relevant file under 
        `docs/source/api/`. 
        
        Examples of usage are also very welcome to be added to the example gallery.
        
        ## TESTING
        All new features should have tests written for them and should not break any of the old tests. To check tests run
        
            $ make tests
            
        
Keywords: nlp
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Mathematics
Description-Content-Type: text/markdown
