Metadata-Version: 2.1
Name: wellcomeml
Version: 2020.5.0
Summary: Utilities for managing nlp models and for processing text-related data at Wellcome Data Labs
Home-page: https://github.com/wellcometrust/datalabs/tree/master/code/wellcomeml/
Author: Wellcome Trust DataLabs Team
Author-email: Grp_datalabs-datascience@Wellcomecloud.onmicrosoft.com
License: ['__license__']
Description: [![Build Status](https://travis-ci.com/wellcometrust/WellcomeML.svg?token=cssCZpnz8YDs4Hb4K5pS&branch=master)](https://travis-ci.com/wellcometrust/WellcomeML) [![codecov](https://codecov.io/gh/wellcometrust/wellcomeml/branch/master/graph/badge.svg)](https://codecov.io/gh/wellcometrust/wellcomeml)
        
        # WellcomeML utils
        
        This package contains common utility functions for usual tasks at Wellcome Data Labs. In particular:
        
        
        | modules | description| 
        |---|---|
        | **io** | manipulating data, in and out S3, and processing |
        | **ml** | wrappers for processing texts, vectorisers and classifiers |
        | **spacy** | common utils for converting data form and to spacy/prodigy format |
        | **mis/viz** | any other utils, including Wellcome colour palletes | 
        
        For more in depth information see the `/examples` folder and [release notes](https://github.com/wellcometrust/WellcomeML/releases).
        
        ## 1. Quickstart
        Installing from a release wheel: Download the wheel [from aws](https://datalabs-public.s3.eu-west-2.amazonaws.com/wellcomeml/wellcomeml-2020.1.0-py3-none-any.whl)
        and pip install it:
        
        ```bash
        pip install wellcomeml-2020.1.0-py3-none-any.whl
        ```
        
        This will install the "vanilla" package. In order to install the deep-learning functionality
        (torch/transformers/spacy transformers):
        
        ```bash
        pip install wellcomeml-2020.1.0-py3-none-any.whl[deep-learning]
        ```
        
        
        ## 2. Development
        
        ### 2.1 Build local virtualenv
        
        ```
        make
        ```
        
        ### 2.2 Build the wheel (and upload to aws s3)
        
        After making changes, in order to buil a new wheel, run:
        
        ```
        make dist
        ```
        
        ### 2.3 (Optional) Installing from other locations
        
        ```
        pip3 install <relative path to this folder>
        ```
        
        ### 2.4 Transformers
        
        Some experimental features (currently `wellcomeml.ml.SemanticEquivalenceClassifier`) require a version of `transformers` that is not compatible with `spacy-transformers`. To develop those features:
        
        ```bash
        export WELLCOMEML_ENV=development_transformers
        pip install -r requirements_transformers.txt --upgrade
        ```
        
        On OSX, ff you get a message complaining about the rust compiler, install and initialise it with:
        
        ```
        brew install rustup
        rustup-init
        ```
        
        ## 3. Example usage of some modules
        
        Examples can be found in the subfolder `examples`.
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Provides-Extra: deep-learning
