TestTubeYumYums

TestTubeYumYums is a Django-based application designed to provide custom food recommendations to users based on their blood test results. The application utilizes React and Tailwind (both CDN-based) for the front-end and PostgreSQL for the database.

Tech Stack

• Django
• React (CDN-based)
• Tailwind (CDN-based)
• PostgreSQL

Distinctiveness and Complexity

TestTubeYumYums aims to target a unique blend of the health, pathology, and nutrition sectors by offering users food recommendations based on their blood test reports. The project takes a unique approach because it is uncommon to find applications that use blood test results to recommend foods based on nutritional deficits and excess. Actually, the original plan was to integrate the app with a public API that would provide dietary options based on a range of nutrients. However, because there isn't a similar API available, a self-made food database that is integrated into the programme and accessible as a CSV file makes recommendations. The intricacy of the project is found in its algorithm, which examines blood test results according to variations in report parameters and related illnesses, extracts nutrients that are lacking, compares those deficiencies to the user's precise vitamin and mineral reports, and retrieves food recommendations from the local CSV database based on the nutritional content of the items.

A multi-page registration form with responsiveness, validated entries, bespoke error messages, and incomplete submissions is another element of the project.

extra Files and their usage

food_data.csv

CSV database of food items that contains name of food, their description, image link and all nutritional infos includidng average serving(named recommended portion).

tailwind.config

Helps in using Tailwind CSS through CDN

LICENSE, .gitignore and README.md

Self-explanatory names

test_tube_yum_yums > apps.py

Modified to load csv database whenever the app is initialized. Also, when the tables are created for the first time in database, CBC and VitMin tables are populated with high and low range values provided by Dr. LalPathLab.

test_tube_yum_yums > analysis_messages.py

Contains pre-wrote analysis messages for possible combinations of CBC parameters.

test_tube_yum_yums > api_codes.py

No longer in use.

test_tube_yum_yums > cbc_analyser.py

Contains helper functions to return nutrient variation based on low and high CBC parameters

test_tube_yum_yums > food_codes.py

Contains a global dictionary which links each nutrient with it's field name in database and how much of that nutrient is considered high/low differentiator in a food item.

test_tube_yum_yums > helpers.py

Contains functions that take in reports and ranges and return dictionary of report analysis and recommended food items.

test_tube_yum_yums > nutrient_imbalance.py

Contains info about what type of parameter deviation can point towards which kind of nutrient imbalance.

test_tube_yum_yums > signals.py

Utilizes Django's in-built post migration signals for populating first two rows of CBC model and VitMin model when the migrations are made for the very first time.

yum_yums > models.py

Contains schema for food items stored in database

Installation

1. Clone this repository:

   git clone https://github.com/jijivishu/TestTubeYumYums.git

2. Switch to the project directory and create a Python virtual environment:

   cd TestTubeYumYums
   python -m venv env

3. Activate the virtual environment:

   • Windows:

   env\Scripts\activate

   • macOS/Linux:

   source env/bin/activate

   • Windows (using bash):

   source env/Scripts/activate

4. Install the required packages:

   pip install -r requirements.txt

5. Create a .env file in the root directory with the following content:

   DB_NAME=test_tube_yum_yums_db
   DB_USER=postgres
   DB_PASSWORD=postgres
   DB_HOST=localhost
   DB_PORT=5432

   Note: For the next step, ensure that PostgreSQL is running at port 5432 on localhost with the username and password set to postgres and the database name set to test_tube_yum_yums_db. Modify the .env file created in previous step, if needed, for database customisation.
   

6. Create migrations:

   python manage.py makemigrations
   python manage.py migrate

7. Load food data from csv file to database:

   python manage.py load_food_data food_data.csv

8. Run the application:

   python manage.py runserver

   Access the application at http://127.0.0.1:8000/. Ensure an internet connection.

Registration

The registration process consists of three steps, with the first step being mandatory. Users provide their name, email (unique identifier), date of birth, and password in the first step. Subsequent steps collect additional information such as country, weight, height, blood pressure, and diabetes data.

Working

Food recommendations are provided based on users' previous test reports. If a user has no test reports uploaded, they are prompted to do so. Users can upload test reports through the '/add' route, customizing the ranges associated with a test report at the time of upload.

Upon submission, users are redirected to the home page, where they can view recommended food items based on their test results and analysis report.

Future Expectations

Minor:

• Display nutritional values of individual food items on click.
• Allow partial page submission in the registration form.

Major:

• Migrate to React instead of using CDN.
• Install Tailwind instead of using CDN.
• Customize food recommendations based on BMI, location, diabetic info, and blood pressure info.
• Consider previous test reports when analyzing the current test report.

Contributing

Please read our Contribution Guidelines before contributing to the project.

Thank you for using TestTubeYumYums!