The HEA volumes service
Project description
HEA Volumes Microservice
Research Informatics Shared Resource, Huntsman Cancer Institute, Salt Lake City, UT
The HEA Volumes Microservice The HEA volumes service.
Version 1.3.0
- We now pass the type_display_name property in volume Collection+JSON templates.
- Caching optimizations.
Version 1.2.0
- Hid some attributes from the heaobject.volume.Volume properties card.
- Added account_id attribute to the heaobject.volume.Volume properties card.
- Removed the type name filter from volume queries. We now use heaobject.account.AccountView ids for the account id filter.
Version 1.1.0
- Support filtering volumes by account id and type name.
Version 1.0.2
- Improved performance.
Version 1.0.1
- Improved performance.
Version 1
Initial release.
Runtime requirements
- Python 3.10 or 3.11
Development environment
Build requirements
- Any development environment is fine.
- On Windows, you also will need:
- Build Tools for Visual Studio 2019, found at https://visualstudio.microsoft.com/downloads/. Select the C++ tools.
- git, found at https://git-scm.com/download/win.
- On Mac, Xcode or the command line developer tools is required, found in the Apple Store app.
- Python 3.10 or 3.11: 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.
- Upgrade pip to version 21.1.2 or greater with
python -m pip install --upgrade pip
. - Create a virtualenv environment using the
python -m venv <venv_directory>
command, substituting<venv_directory>
with the directory name of your virtual environment. Runsource <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 -r requirements_dev.txt
. Do NOT runpython 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
- Install Docker
- On Windows, install pywin32 version >= 223 from https://github.com/mhammond/pywin32/releases. In your venv, make sure that
include-system-site-packages
is set totrue
.
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.
- Have a heaserver-registry docker image in your Docker cache. You can generate one using the Dockerfile in the heaserver-registry project.
- Have a heaserver-folders docker image in your Docker cache. You can generate one using the Dockerfile in the heaserver-folders project.
- 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/volumes/ -Method GET -Headers @{'accept' = 'application/json'}`
In MacOS or Linux, the equivalent command is:
curl -X GET http://localhost:8080/volumes/ -H 'accept: application/json'
Packaging and releasing this project
See the RELEASING.md file for details.
Project details
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