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The HEA data adapter service.

Project description

HEA Server Data Adapters Microservice

Research Informatics Shared Resource, Huntsman Cancer Institute, Salt Lake City, UT

The HEA Data Adapters Microservice provides access to data files and databases.

Version 1

Initial release.

Runtime requirements

  • Python 3.10

Development environment

Build requirements

  • Any development environment is fine.
  • On Windows, you also will need:
  • On Mac, Xcode or the command line developer tools is required, found in the Apple Store app.
  • Python 3.10: Download and install Python 3.10 from https://www.python.org, and select the options to install for all users and add Python to your environment variables. The install for all users option will help keep you from accidentally installing packages into your Python installation's site-packages directory instead of to your virtualenv environment, described below.
  • Create a virtualenv environment using the python -m venv <venv_directory> command, substituting <venv_directory> with the directory name of your virtual environment. Run source <venv_directory>/bin/activate (or <venv_directory>/Scripts/activate on Windows) to activate the virtual environment. You will need to activate the virtualenv every time before starting work, or your IDE may be able to do this for you automatically. Note that PyCharm will do this for you, but you have to create a new Terminal panel after you newly configure a project with your virtualenv.
  • From the project's root directory, and using the activated virtualenv, run pip install wheel followed by pip install -r requirements_dev.txt. Do NOT run python setup.py develop. It will break your environment.

Running tests

Run tests with the pytest command from the project root directory. To improve performance, run tests in multiple processes with pytest -n auto.

Running integration tests

Trying out the APIs

This microservice has Swagger3/OpenAPI support so that you can quickly test the APIs in a web browser. Do the following:

  • Install Docker, if it is not installed already.
  • Run the run-swaggerui.py file in your terminal. This file contains some test objects that are loaded into a MongoDB Docker container.
  • Go to http://127.0.0.1:8080/docs in your web browser.

Once run-swaggerui.py is running, you can also access the APIs via curl or other tool. For example, in Windows PowerShell, execute:

Invoke-RestMethod -Uri http://localhost:8080/dataadapters/ -Method GET -Headers @{'accept' = 'application/json'}`

In MacOS or Linux, the equivalent command is:

curl -X GET http://localhost:8080/dataadapters/ -H 'accept: application/json'

Packaging and releasing this project

See the RELEASING.md file for details.

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