Deep Work Tracker is a productivity tool designed to help you track a state of peak concentration known as deep work. By incorporating deep work into your workflow, you can learn hard things and create high-quality work efficiently. This repository provides a simple solution for tracking your daily results.
To see a personal implementation of the Deep Work Tracker, please see this repository.
You can install this project by cloning the repository, forking the repository, or downloading the zip files.
To clone the repository, open a terminal and run the following command:
git clone git@github.com:your-username/deep_work_tracker.gitMake sure to replace your-username with your GitHub username.
To fork the repository, click on the Fork button in the top-right corner of this page. This will create a copy of the repository in your GitHub account.
To download the zip files, click on the Code button in the top-right corner of this page and then click on Download ZIP. Extract the zip files to a directory of your choice
- Pandas
- Matplotlib
- Seaborn
- Install the dependencies using pip:
pip install pandas matplotlib seaborn
-
Duplicate the
MONTH_YEARdirectory, making sure to replace MONTH and YEAR with the appropriate month and year for which you want to track your deep work hours. -
Add daily deep work hours to the
table.csvfile located in your duplicatedMONTH_YEARdirectory. For clarification purposes, we will use thetable.csvfile in the defaultMONTH_YEARdirectory:
Date,Reading,Writing,Coding,Mathematics
06-01-2023,1,0,2,1
06-02-2023,0,1,2,1
06-03-2023,0,0,2,1
06-04-2023,1,3,0,0
...
Note: a date in the “Date” column should be in the format MM-DD-YYYY.
- In your duplicated
MONTH_YEARdirectory, run the following script:
python update_monthly_summary.py
Three files will be generated in your MONTH_YEAR directory:
monthly_summary.mdfigures/monthly_breakdown.pngfigures/daily_breakdown.png
For the default MONTH_YEAR directory, monthly_summary.md will look like this:
Pull requests are welcome. For major changes, please open an issue first to discuss what you'd like to change.
This project is inspired by the principles and concepts introduced by Cal Newport in his book Deep Work: Rules for Focused Success in a Distracted World. We would like to express our gratitude to Cal Newport for his insightful work and for highlighting the importance of deep work in producing quality results.