heaserver-data-adapters 1.0.0a24
The HEA data adapter service.
Requires Python: >=3.10

# HEA Server Data Adapters Microservice
[Research Informatics Shared Resource](https://risr.hci.utah.edu), [Huntsman Cancer Institute](https://healthcare.utah.edu/huntsmancancerinstitute/),
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:
    * 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: 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
* 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 to `true`.

### 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](RELEASING.md) file for details.