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README.md

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Overview

Flower is a data collection and visualization system made for the Renewable Energy Scholars at Bucknell University. It is made of several components that require each other to function. The purpose of the project is to make research easier as well as publicize the sustainability efforts at Bucknell.

How to use this project

There are README.mds in each of the main directories for how to use each component of the project. You will need a MySQL DB running (/backend/sql), run the Flask server (/backend), compile the React code and run the php server (/web), and put code on the Raspberry Pis (/raspberrypi), and load programs onto Arduinos (/arduino).

Running system at Bucknell

We suggest running this system with Bucknell linuxremote servers because that is what we developed on. Any other system is not guarenteed to work, but we will have instructions to give it a shot.

If attempting to run on Bucknell systems, we advise cloning the repo into a user's ~/public_html/ directory (create it if it doesn't exist) to enable the Bucknell Apache server to handle the web page serving.

The system needs to be run on linuxremote3 for the below part to function.

Now go into the script directory and run:

./restart_flask.sh

If any changes need to be done to the flask server, just run that script again to restart it

API Keys and Deployment Specific Values

API Keys and other deployment specific values have been removed from the repo to ensure security and flexibility for different deployments. You will NEED to complete steps 1-6 to have any component of the project to work.

  1. Create a file called config.json in the repo's root directory.
  2. Add this code:
{
  "DB_URL" : "",
  "DB_USERNAME" : "",
  "DB_PASSWORD" : "",
  "DB_NAME": ""
}
  1. Fill out all values of the empty strings with information for your DB/API key info
  2. Create a file called deployment.json in the repo's root directory. There are all things unique to your deployment.
  3. Add this code:
{
 "APPROVAL_LINK": "",
  "FLASK_SERVER": "",
  "GOOGLE_CLIENT_ID": "",
  "REDIRECT_URL": "" 
}
  1. Fill out all values of the empty string with the information for your deployment
  2. Access the values where needed:
    • Python: 
      import json
with open('path/to/config.json', 'r') as f:
    config = json.load(f)

config['KEY_NAME']
    • PHP: 
      $config = json_decode(file_get_contents("path/to/config.json"));
printf("%s", $config->KEY_NAME);
    • JS: !!!This should only be used with the deployment.json so that DB credentials or other important information isn't leaked on the client side with config.json 
      <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script> 
<script type="text/javascript" src="../common/load-deployment.js" ></script>
...
deploy_config["KEY_NAME"]

KEY_NAME is the key string in your config file such as DB_NAME or FLASK_SERVER.

This config.json and deployment.json won't get committed because it is in the .gitignore so you will need to do this for each clone of the repo, but it should persist unless you delete the file.

Linters

Python - autopep8

To install autopep8 run

pip install autopep8

Install the python-autopep8 package in Atom with either apm install python-autopep8 or through the built in Atom package manager.

Then to run the linter in Atom, highlight all of the text you want to format and then press Ctrl-shift-p and type in autopep8 and then press Enter to format the Python code.

You can also run it from the command line with autopep8 [--in-place] [other-options] filename.