It is often the case that computer science classrooms use traditional grading practices where points are allocated to assignments, mistakes result in point deductions, and assignment scores are combined using some form of weighted averaging to determine grades. Unfortunately, traditional practices have been shown to reduce achievement, discourage students, and suppress effort to such an extent that some common elements of traditional grading practices have been termed toxic. Using grades to reward or punish student behavior does not encourage learning and instead increases anxiety and stress. These toxic elements are present throughout computing education and computer science classrooms in the form of late penalties, lack of credit for code that doesn’t compile or pass certain unit tests, among others. These types of metrics, that evaluate behavior are often influenced by implicit bias, factors outside of the classrooms (e.g., part-time employment), and family life situations (e.g., students who are caregivers). Often, students in these situations are disproportionately from low-socioeconomic backgrounds and predominantly students of color. Through this paper, we will present a case for adoption of equitable grading practices and a call for additional support in classroom and teaching technologies as well as support from administrations both at the department and university level. By adopting a community of practice approach, we argue that we can support new faculty making these changes, which would be more equitable and inclusive. Further, these practices have been shown to better support student learning and can help increase student learning gains and retention.