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Dependencies

Setting up

Ensure that you have python 2.7.x installed , and python path added to your environment variables. You can download and install python at https://www.python.org/downloads/release/python-2713/

You can install all dependies at once (at a go ) by running pip install -r requirements.txt at the root of the application folder.

Alternatively, you could follow the following steps to install dependencies one after the other;

  1. Install Jupyther notebook with the command
         pip install jupyter
  2. Install APScheduler with the command
         pip install apscheduler
  3. Install PyMysql with the command
         pip install pymysql
  4. Install SQLAlchemy with the command
         pip install sqlalchemy
    
    
    

The Database

The database is a MySQL database. Please install mysql database on your local server or host.

The API interacts with the database using SQLAchemy ORM.

The API also runs a process, that syncs data from a remotely hosted MySQL database on the AWARE Framework dashboard (https://api.awareframework.com)

Setting up and running

To setup and run the API, please follow the following steps

  1. Follow the steps in setting up, descbribed above in Setting up section, to start with
  2. open the command prompt at the root of the application (codes) folder
  3. run the command
        python run.py
  4. The command in step 3 will start the FLASK built in web server with the address http://localhost:5000 , or a similar address. The actual address will be displayed in the command prompt.
  5. The base URL to use to run the API will be http://localhost:5000/care/ .
  6. You can now send request to the api using a web browser or a rest client like

The API Resources

Endpoint Uniform Interface Description
/care/handover *** GET Returns a list of handover entries
/care/handover/<patient_id> *** GET Returns a list of handover entries for patient with id patient_id

Note: All Endpoints marked *** has optional parameters;

  • start - include entries starting from start timestamp
  • end -include entries ending at end timestamp
  • grouping - present data for patients in DAILY, WEEKLY, MONTHLY averages

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