Skip to main content

Python library of NLP functions originally collated by Equinor Knowledge and AI Data Science team.

Project description

Build Status Azure Status OS-support Codacy Badge

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

enlp-0.0.0.tar.gz (3.2 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

enlp-0.0.0-py3.7.egg (35.7 kB view details)

Uploaded Egg

enlp-0.0.0-py3-none-any.whl (19.4 kB view details)

Uploaded Python 3

File details

Details for the file enlp-0.0.0.tar.gz.

File metadata

  • Download URL: enlp-0.0.0.tar.gz
  • Upload date:
  • Size: 3.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.21.0 setuptools/42.0.1.post20191125 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.7.5

File hashes

Hashes for enlp-0.0.0.tar.gz
Algorithm Hash digest
SHA256 ef687de339f581498629d4cf114b3d8112717286aec13d890d7e4036f9bf0031
MD5 f978fa409eec0c34e5079a8012539a62
BLAKE2b-256 de66ff5cfcc5b7af134addd49837d5a4c15ec40e8b707820857c5e2b1bf5ab9f

See more details on using hashes here.

File details

Details for the file enlp-0.0.0-py3.7.egg.

File metadata

  • Download URL: enlp-0.0.0-py3.7.egg
  • Upload date:
  • Size: 35.7 kB
  • Tags: Egg
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.21.0 setuptools/42.0.1.post20191125 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.7.5

File hashes

Hashes for enlp-0.0.0-py3.7.egg
Algorithm Hash digest
SHA256 2b22319d3eb50877e83e293fdc470b00e04ee63efa59c3f681c196f2aad5145d
MD5 1a954fadca98cb41796ca491933c763b
BLAKE2b-256 e285067740cbdd10fb590014dbbf1189dc87be7b2cf5cd32e227edfb3a4fb9c0

See more details on using hashes here.

File details

Details for the file enlp-0.0.0-py3-none-any.whl.

File metadata

  • Download URL: enlp-0.0.0-py3-none-any.whl
  • Upload date:
  • Size: 19.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.21.0 setuptools/42.0.1.post20191125 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.7.5

File hashes

Hashes for enlp-0.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4666af1752360b1ad1ef5214598983d6e06b183c741e257169c4599188e0b904
MD5 c8afdbfde225ec4e9ab5d784f219005c
BLAKE2b-256 503f849cad44ce82503b1998ec34f75a5bea2322a92c0f2e7b10fcd77522fdae

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page