Overview

trk is a simple pandas-friendly timetracking application for the command line.

You can use it to swiftly create, report, analyze, and plot time units. Time is stored in pandas-friendly human-readable plain-text CSV files.

Comma separated values

trk stores each time unit in plain text in comma separated values (CSV) files. trk CSV files can be stored anywhere, including git-managed repos stored on GitHub, dropbox folders, or encrypted proton-drive folders. Proton is a "privacy by default" encrypted suite of tools, including email, that over 100 million people use to stay private and secure online.

Comma-separated files contain tables (rows and columns) of data and can be opened using popular editors such as vim, emacs, or notepad++. They can also be opened Excel.

Activities

Each CSV files contains a column that can optionally contain an activity. Activities can streamline analyzing and plotting groups of time slots.

Support for multiple projects

trk supports multiple projects. Each project can be maintained as a git-managed repo (repository). Git is a popular version control system used by millions to ensure that none of their work is lost and that collaborators can work together seamlessly on a single project with minimal conflicts, even if they are working on the same file at the same time. In a project managed by git, each person works without anyone hoovering over their shoulder or deleting their edits as they add them, as can occur with tools such as Google docs. Once a researcher is happy with their edits, they can share them with fellow collaborators by doing a "Pull Request" or PR as the cool kids say.

trk is intended to work in a git repo containing a project developed by multiple researchers. The project time for each researcher is stored in one CSV file per researcher. This ensures that there are no conflicts in the CSV files as multiple researchers work on the same project at the same time.

The project CSV files can be stored within the git-managed project or outside of the project directory. The location of the projct CSV files is set when time tracking is initialized within the repo using trk init --csvdir. If the --csvdir is ommitted, the CSV files are stored in the root directory of the project repo. An example of initializing trk to store store CSV files within a project subdirectory is: trk init --csvdir doc/timetracking/. The subdirectory doc/timetracking/ must be created by the researcher, which is commonly done with mkdir -p doc/timetracking. The CSV files can be hand-edited, if desired by a researcher.

export

Multiple CSV files are concatenated (strung together one by one) into a single CSV file using the trk export command.

Multi-platform support

trk is compatible with most operating systems. You can download it using pip, the package manager for Python packages or you can build from a cloned repo.

Libre software and open-source

trk is written in Python. Ideas and inspirations are heartily welcome.