Code Time Metrics

Code Time tracks a set of time-based metrics directly from your editor or IDE. This page defines each metric and how it’s measured.

Code Time

Code time captures any period of activity (e.g. editing, browsing, reading code) in your editor or IDE.

Code time starts when you focus your editor and ends after 15 minutes of inactivity. Activity includes actions you take in your code editor, such as typing, focusing your editor, opening and closing files, and switching projects.

For example, if you’re writing code, but pause to visit Stack Overflow, and return to writing code within 15 minutes, the entire elapsed time will count toward your code time. If, however, you’re writing code, but stop to conduct research for an hour, and return to writing code, the time spent researching will not count toward your code time.

Active code time is time you spend actively editing code in your editor or IDE. It captures periods of intense focus and flow.

Active code time begins incrementing when you start typing and ends if you allow more than 10 minutes to elapse without typing. If you are inactive for more than 10 minutes, your active code time will stop at your last minute of typing.

For example, if you’re writing code, but pause to think about your next line of code, and return to writing code within a few minutes the entire time elapsed will count toward your active code time. If you need to quickly check GitLens for code changes or review another function in your codebase, that will also be counted toward your active code time. If you need to quickly leave your editor to conduct research or visit Stack Overflow, and return to writing code within 10 minutes, the time spent outside the editor will also count toward your active code time.

Code Time Session

A code time session is a distinct block of code time. Code Time captures any period of activity in your editor or IDE, including a 15-minute timeout to capture short periods of time spent outside your editor.

Code time sessions are helpful in identifying and protecting your best code times.

Code Day Length

Code day length is the total duration between your first and last coding activity each day. It is an approximation for length of day worked and helps you think about when your work day starts and ends.

For example, if you begin coding at 10am, the start of your code day will be 10am. During the workday, you may need to attend meetings, collaborate with coworkers, or research something new. If you resume coding at 2pm and stop coding at 4pm, your code day length will be 6 hours (10am to 4pm).

Coding Velocity

Coding Velocity is a composite metric of your coding activity that we use to automatically detect when you are in flow using machine learning. Velocity scores typically range from 1 (low velocity) to 100 (high velocity).

The primary use of coding velocity is triggering Flow Mode, a feature of our Code Time extension. Flow Mode makes it easy to eliminate distractions, mute notifications, and stay focused when you are in flow. You can quickly toggle Zen mode or enter full screen. If you connect a Slack workspace, you can pause notifications, update your profile status, and set your presence to away. You can configure Flow Mode by clicking the gear icon in the Code Time sidebar.

Meeting Time

Meeting time, quite simply, is time spent in meetings. Comparing meetings and code time helps you measure how much time you spend in meetings compared to how much time you spend actively coding.

We combine meetings data from work calendars and time tracking metrics from Code Time. By comparing meetings and code time, you can begin to understand the impact of meetings on your productivity.

Meetings are an obvious enemy of flow. Even short meetings can disrupt productive coding sessions. They can also interfere with peak code times. Meetings displace not just an hour of work, but your team’s best hour of work. In worst case scenarios, scheduling too many meetings pushes productive work to non-work hours, like nights and weekends. That leads to burnout and poor work-life balance.

Better data leads to better decisions. Team leaders can learn how to streamline their team’s schedules to avoid unnecessary meetings that interfere with deep work. Effective teams will strike the right balance between meetings and coding that works best for them.