Habit Tracking Application

Table of contents

1. Overview

2. Running the project

    2.1 Prerequisites

    2.2 Installing the project

3. Using the project

    3.1 Running the cli

    3.2 Start Rest API (Swagger UI)

4. Testing

5. Calculation rules for a Streak

6. Technology choices

7. Bibliography

1. Overview

Everybody wants to stop unhealthy habits and create good habits in its place. They are turning to technology for assistance to achieve this. I was tasked to create a backend for a habit tracking application that will assist users to reach their goals.

2. Running the project

2.1 Prerequisites

Python 3.7 or later. (Python 3.10.3 was used for development). Download the latest version here

2.2 Installing the project

• Clone the repository locally

• Open CommandPrompt on Windows or Terminal on Mac to the cloned folder

• Go to the root folder (OOFPP-Habits-Phase3) of the project where you will see a setup.py file

• Run the following command

  pip install .
  

• If you see Successfully installed OOFPP-Habits-Phase3-1.0 the application is ready to be used.

3. Using the project

3.1 Running the cli

From the CommandPrompt or Terminal window, go to the habits_backend folder (OOFPP-Habits-Phase3) of the application. Run the following command to see the cli help menu.

python main.py --help

You should see the following help menu

To load or clear the test data, you can run the following commands

python main.py data-clear
python main.py data-seed

Analysis cli commands

Show all the tracked habits (Habit that was completed at least once. The testing data has habits that was not completed.)

python main.py analyse-tracked-habits

Habits with the same periodicity ('daily','weekly','monthly')

python analyse-equal-periodicity --frequency daily

Longest streak for a specific habit

python main.py analyse-streak-habit --habit_id 1

Longest streak for any habit

python main.py analyse-longest-streak

3.2 Start Rest API (Swagger UI)

From the CommandPrompt or Terminal window, go to the habits_backend folder (OOFPP-Habits-Phase3) of the application.

Run the following command to start the REST API.

python main.py start-rest-api

To see the OpenAPI documentation browse to http://127.0.0.1:8000/docs or http://localhost:8000/docs

Using the Swagger interface

• Click on the color coded method (e.g. GET /habits/{id} to open up the interface)
• Click on the Try it out button
• If there are details required, fill it in e.g. habit_id
• Click on the blue Execute button

You can use the seed and clear methods under data section to load/clear testing data

4. Testing

Tests was created using pytest.

To run the tests, follow the following steps

• Open a CommandPrompt or Terminal window

• Go to the tests folder in the root (OOFPP-Habits-Phase3) of the application

• To execute all the analysis tests, run the following command

  pytest test_modules_analysis.py
  

  View running tests from Command Prompt

  

  View running tests in the IDE

  

• To execute all the cli tests, run the following command

  pytest test_main.py
  

• To run individual tests, run the following commands

  pytest test_modules_analysis.py::test_is_tracked_true
  pytest test_modules_analysis.py::test_is_tracked_false
  pytest test_modules_analysis.py::test_is_equal_period_true
  pytest test_modules_analysis.py::test_is_equal_period_false
  

5. Calculation rules for a Streak

• Day:
  • Less than or equal to 1 day is counted as a day. (e.g. "2022-04-27T14:17:45" to "2022-04-28T15:57:21" is one day)
  • Hours, minutes and seconds are ignored.
  • If the day count is more than 1, the streak was broken
• Week:
  • Less than or equal to 7 days is treated as a week.
  • Hours, minutes and seconds are ignored.
  • If the week count is more than 1, the streak was broken
• Month
  • Less than or equal to a month is treated as a month
  • Days, hours, minutes and seconds are ignored.
  • If the year count is more than 1, the streak was broken

6. Technology choices

• Python version 3.10.3 (Project requirement to use 3.7 or later.)
• PyCharm 2022.1.1 (Popular IDE / source-code editor that runs on Windows, Linux and macOS. I found that it works better than Visual Studio Code for python development.)
• sqlite3 (It is a library that provides lightweight disk-based database to persist the data.)
• pytest (Framework for writing tests.)
• FastAPI (Framework for building APIs with python. This will provide an alternative for the CLI.)
• click (Python library for creating command line interfaces.)
• Pylint (Linting tool that checks for coding errors and enforce coding standards.)
• Swagger UI (Interactive exploration to call and test your API from the browser.)
• SQLAlchemy (Accessing data stored in the database.)
• pydantic (Data parsing and validation.)

7. Bibliography

1. n.a. (n.d). Google Python Style Guide – Naming https://google.github.io/styleguide/pyguide.html#316-naming
2. Lutz, M (2013). OOP: The Big Picture, Learning Python 5th Edition. O’Reilly
3. Marcus, S (2021, July 16). Test Driven Development with pytest https://stackabuse.com/test-driven-development-with-pytest/
4. n.a. (n.d). Zalando RESTful API and Event Guidelines https://opensource.zalando.com/restful-api-guidelines/
5. n.a. (n.d). FastAPI - SQL (Relational) Databases https://fastapi.tiangolo.com/tutorial/sql-databases/
6. n.a. (n.d). click https://click.palletsprojects.com/en/8.1.x/
7. Martin, Robert C (2012, August 13) – The Clean Architecture https://blog.cleancoder.com/uncle-bob/2012/08/13/the-clean-architecture.html