Project name: Recipe Selector and Analyzer

Welcome to Recipe Selector and Analyzer!

Video presentation of the project: Recipe Selector and Analyzer preview

Link for the web application: Recipe Selector and Analyzer

Description:

There are a lot of recipes but to find one that is really great is hard. Recipe Selector and Analyzer is created to solve this problem. It gives a great opportunity to find the dreamed recipe. There are a lot of recipes in the google but there is information only from what and how to cook the dish, but Recipe Selector and Analyzer can help to find different recipes and to get the full information about them. To search the recipes you can use two oprions: Complex Search and Meal Generator. Complex search is a search that helps to find recipes based on the user's wishes. Meal Generator is used to generate recipes for the day.

The information that user can get:

• comparison characteristics of the selected recipes;
• needed ingredients to cook the portion of all dishes;
• analysis of nutrition composition of all recipes for one serving;
• recipes' links;

Table of contents:

• Input/Output

• Program Structure

• Installation

• Usage example

• Contributing

• Credit

• License

Input/Output data

The input data for the Complex Search: main ingredient, ingredients to include and to exclude, cuisine, diet, dish type, the number of recipes to output. It is ESSENTIAL to input the main ingredient and number of recipes, but other input is optional.

The input data for the Meal Generator: number of calories, diet, ingredients to exclude. User сan not even enter anything and press the button to get the results. Using this option user can get only three recipes.

The output data of the Recipe Selector and Analyzer for Complex Search and Meal Generator are rather the same:

• table with comparative characteristics of selected recipes:
  • healthiness;
  • health score;
  • popularity;
  • cheap to cook or not;
  • cooking time;
  • number of calories;
  • cuisines they belong to;
  • diets they belong to;
  • dish types they belong to;
• table with the ingredients you need for a portion of the dishes separately;
• bar charts with all recipes' nutrition composition that provide their analysis;
• all recipes' links;

If user uses Meal Generator, there is also displayed the pie chart with the the comparison of fats, carbohydrates and protein in dishes per day.

Program structure

Program consists of such modules as:

• arrays.py - consists of needed data structures for the research. There are Array and DynamicArray classes that are needed to for the ADT implementation and data storage.
• recipe_search_adt.py - consists of the needed RecipeSearch ADT. This ADT is used to get the information about recipes' names and ids. RecipeSearch ADT also helps to select the recies in a random way.
• recipe_data_adt.py - consists of the needed SecipeData ADT. This ADT is used as a container of the main information about selected recipes and is used to obtain the information needed for the analysis.
• default_information - consists of the needed default information for the investigation such as list of needed diets, dish types, cuisines, etc.
• errors.py - there are dictionaries that returns API if it is a bad request. This module is used to define whether there are results for different user inputs.
• main_functions.py - consists of the functions that are needed to get the information using API, there are also functions to check if user's input is valid and if the information from the Internet is not in errors.py. also, there are needed functions to plot the data for both Complex Search and Meal Generator.
• complex_dashboard - consists of the main function to get the information for the Complex Search and also there is Dash layout that is responsible for the output results of the data analysis for Complex Search option.
• meal_gen_dashboard - contains of the function to plot the needed data for the Meal Generator and also there is Dash layout that is responsible for the output results of the data analysis for Meal Genarator option.
• flask_app.py - contains of three functions to create three main pages of the app: Home, Complex Search and Meal Generator.
• wsgi.py - the main function that runs the program and is responsible for the transition between the flask pages and dash pages.

If you want to know more just have a look at the documentation page, that consists of the all needeed information about main classes and functions.

Link for the documentation folder: docs

Installation:

Prerequisities:

If you want to run the program locally you need firstly to install such libraries:

pip install requests

pip install flask

pip install dash

pip install plotly

pip install pandas

Also you need to get an API key on Rapid API

Then you need only:

git clone https://github.com/khristinakokolus/cource_work_2nd_term.git

After that you shound run wsgi.py to see the work of the program.

Usage example

After following the link of the web application you will see:

After that you can choose Complex Search or Meal Generator

If you chose Complex Search, you will see:

Here is an example of search query:

Example of output data:

If you chose Meal Generator, you will see:

Here is an example of search query:

Example of output data:

Contributing:

Please refer to project's style and contribution guidelines for submitting patches and additions. In general, the "fork-and-pull" Git workflow.

1.Fork the repo on GitHub

2.Clone the project to your own machine

3.Commit changes to your own branch

4.Push your work back up to your fork

5.Submit a Pull request so that we can review your changes

Credit:

• Khrystyna Kokolus, Ukrainian Catholic University, 2020

License:

MIT LICENSE