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SMaHT Data Portal

Overview

This repository serves as SMaHT Portal for the Data Analysis Center. It is an ENCODED style system modeled after previous iterations (fourfront, cgap-portal) previously developed by the Park Lab. In this iteration, the majority of code in this repository is UI, data model and DevOps related. Core data models common to our projects can be found in the encoded-core repository, while core back-end features can be found in our snovault repository.

Build status

Installation

smaht-portal is known to work with Python 3.11.x, it is strongly recommended to work on this version. There is no particular recommended patch version, but the latest one available should do. It is best practice to create a fresh Python virtualenv using one of these versions before proceeding to the following steps. These instructions are intended for Mac OSX. If using Linux, similar instructions apply but advanced knowledge is assumed.

Step 0: Obtain Credentials

Obtain AWS keys. These will need to added to your environment variables or through the AWS CLI (installed later in this process).

Step 1: Verify Homebrew Itself

Verify that homebrew is working properly:

$ brew doctor

Step 2: Install Homebrewed Dependencies

Install or update dependencies:

$ brew install libevent libmagic libxml2 libxslt openssl postgresql graphviz nginx python3
$ brew install freetype libjpeg libtiff littlecms webp  # Required by Pillow
$ brew cask install adoptopenjdk8
$ brew install opensearch node@16

  • If installation of adtopopenjdk8 fails due to an ambiguity, it should work to do this instead:

    $ brew cask install homebrew/cask-versions/adoptopenjdk8

Step 3: Running Make

Run make:

$ make build

Step 4: Running the Application Locally

Start the application locally

In one terminal startup the database servers and nginx proxy with:

$ make deploy1

This will first clear any existing data in /tmp/encoded. Then postgres and elasticsearch servers will be initiated within /tmp/encoded. An nginx proxy running on port 8000 will be started. The servers are started, and finally the test set will be loaded.

In a second terminal, run the app with:

$ make deploy2

Indexing will then proceed in a background thread similar to the production setup.

Running tests

The unit tests in general require AWS credentials. Some will run without them, but most will fail. You will need various AWS Access Credentials set and in addition $GLOBAL_ENV_BUCKET.

Python Testing

To run the unit test suite:

$ make test

To run individual tests:

$ pytest -vvk <test_name>