Dataset: Commits from pull requests
Entity: Commit
Field ID: message
Type: Text
Description: The message describing the content of the commit.
Source: App
From: |
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Github (Commits) |
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Gitlab (Commits) |
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Bitbucket (Commits) |
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Azure DevOps (Commits) |
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Jira | N/A |
ClickUp | N/A |
Trello | N/A |
Reporting Use Cases
The Message field from the Commits dataset provides the descriptive text for each code change, offering invaluable context about the intent behind the work. If your team follows a consistent naming convention (like Conventional Commits), this field can be transformed from simple text into a powerful tool for categorization and analysis.
Filtering by Keyword: You can create highly specific reports by searching for patterns within the commit message.
Find Bug Fixes: A filter like
Message ~ "(?i)fix|bug"will find all commits that are likely related to bug fixes.Track Work by Ticket: You can find all commits related to a specific Jira ticket with a filter such as
Message ~ "PROJ-1234".Enforce Conventions: Identify commits that don't adhere to your team's standards with a negative filter, for example,
Message !~ "^(feat|fix|chore)".
Context in List Reports: In any drilldown or list of individual commits, including the message as a dimension is essential for providing clear, human-readable context for each change.
Custom Formulas for Advanced Categorization: This is the most powerful use of the commit message. By parsing the text, you can create structured reports on your development activities.
Commit Type Analysis: You can create a pie chart showing the breakdown of your work by using a custom formula dimension that categorizes each commit. For example,
IF_MATCH(message, "^fix", "Bugfix", "^feat", "Feature", "^chore", "Chore", "Other").Grouping by Issue: If your commit messages reference issue keys, you can create a dimension that groups all commits by the issue they relate to, using a formula like
REGEX_EXTRACT(message, "[A-Z]+-\\d+"). This allows you to see all the code changes associated with a single task.