HABIT TRACKING APP

A python-powered command-line application for tracking and analyzing daily/weekly habits. Built with object-oriented and functional programming paradigms.

Features

1. Create Habits: Define habits by task name, periodicity, and category.
2. Track Completion: Record timestamps for habit completions.
3. Analyze Progress: Calculate streaks, filter habits by periodicity/category, and generate reports.
4. Data Management: Habits stored locally in an SQLite database.
5. Command-line UI: User-friendly interface with click.

Installation

1. Clone the repository:

   git clone https://github.com/mardlpz/habit-tracker.git  

2. Navigate to project directory:

   (Replace with actual local path to cloned repository.)

   cd path/to/habit-tracker

3. Create virtual environment:

   python -m venv .venv

4. Activate virtual environment:

   On macOS/Linux:

   source .venv/bin/activate 

   On Windows:

   .venv\Scripts\activate

5. Install dependencies:

   pip install -r requirements.txt

Usage

• Basic command-line interaction:

  python -m habit_tracker.cli <command> --[option]
  

1. Create habits

   • Command: create
   • Options:
     • Task name (mandatory, string): --task or --t
     • Periodicity (mandatory, 'daily' or 'weekly'): --periodicity or --p
     • Category (optional, default: general): --category or --c
   • Example:

   python -m habit_tracker.cli create --task "Exercise" --periodicity daily --category health

2. Complete a Habit

   • Command: complete
   • Options:
     • ID (mandatory): --id
   • Example:

   python -m habit_tracker.cli complete --id 4

3. List Habits

   • Command: list
   • Options (default: lists all habits):
     • Periodicity (optional, 'daily' or 'weekly'): --periodicity or --p
     • Category (optional): --category or --c
   • Example:

   python -m habit_tracker.cli list --periodicity weekly --category education

4. Analyze Habits

   • Command: analyze
   • Options:
     • ID (for specific habit analysis): --id
     • Periodicity: --periodicity or --p
     • Category: --category or --c
     • Longest streak: --longest-streak or --ls
     • Current streak: --current-streak or --cs
     • Completion rate: --completion-rate or --cr
     • Most struggled habit: --most-struggled or --ms
     • Weekly report: --weekly-report or --wr
     • Monthly report: --monthly-report or --mr
   • Example:

   python -m habit_tracker.cli analyze --longest-streak
   python -m habit_tracker.cli analyze --current-streak
   python -m habit_tracker.cli analyze --completion-rate
   python -m habit_tracker.cli analyze --most-struggled
   python -m habit_tracker.cli analyze --weekly-report
   python -m habit_tracker.cli analyze --monthly-report

*--most-struggled, --weekly-report, and --monthly-report do not apply for specific analysis by ID, cannot be performed on a single habit.

5. Delete a Habit

   • Command: delete
   • Options:
     • ID (mandatory): --id
   • Example:

   python -m habit_tracker.cli delete --id 4

6. Reset database

   • Command: reset
   • Example:

   python -m habit_tracker.cli reset

7. Exit and clear terminal

   • Command: exit
   • Example:

   python -m habit_tracker.cli exit

Persistence

Habit data is stored in an SQLite database contained within the file "habits.db" (data/habits.db). The database is automatically created if it doesn’t exist yet. When opening the file in an IDE such as PyCharm, habits and completions tables can be visualized in ascending and descending order. It is important to refresh the file after an operation has been performed on the database.

Sample Data

The application provides a file with sample data (sample_data.py) including 5 predefined habits with 4 weeks of tracking records each:

• Drink Water (Daily, Health)
• Yoga (Weekly, Health)
• Read (Daily, Education)
• Journal (Weekly, Mental Health)
• Meditate (Daily, Mental Health)

Load sample data into database with:

python sample_data.py

Testing

The application includes a collection of pytest test cases to validate the core functionality. The test fixtures provide sample habit data with predefined completion dates to ensure consistent and reproducible test results. Run the unit tests with:

pytest tests/

Deactivate virtual environment

Exit and deactivate the virtual environment with:

deactivate

Help & Documentation

All code is documented with descriptive Python docstrings for further clarification. To access the help documentation directly from the command-line interface use the following commands:

• General help:

  python -m habit_tracker.cli --help

• Command-specific help:

  python -m habit_tracker.cli analyze --help
  python -m habit_tracker.cli complete --help
  python -m habit_tracker.cli create --help
  python -m habit_tracker.cli delete --help
  python -m habit_tracker.cli exit --help
  python -m habit_tracker.cli list --help
  python -m habit_tracker.cli reset --help

Information

Author: Mariana Del Pozo Patrón
Python version: 3.12.3
Publish date: March 23, 2025
Object Oriented and Functional Programming with Python
International University of Applied Sciences