GitLab's dashboard and statistical functions and data analysis

GitLab’s dashboard, statistical functions and data analysis

As a version control system and source code hosting platform, GitLab not only provides powerful code management functions, but also Provides rich dashboards and statistical functions as well as data analysis tools to help teams better understand project progress and make data-driven decisions. This article will introduce GitLab's dashboard and statistical functions and provide specific code examples.

1. Dashboard function

GitLab's dashboard function provides a centralized view that summarizes various information, helping users quickly understand the overall status of the project and the work status of team members.

1. Project Overview

The project overview of the dashboard can display key indicators of the project, such as repository size, number of branches, number of merge requests, etc. With a concise view, teams can quickly understand the overall situation of the project, allowing for better planning and decision-making.

Sample code:

GET /projects/:id

2. Member dynamics

GitLab’s dashboard can also display dynamic information of team members, including new merge requests and submissions code, comments posted, etc. This feature can help team members keep abreast of each other's work progress and collaborate better.

Sample code:

GET /dashboard/activity

3. Errors and exceptions

The dashboard can also display error and exception information in the project in real time, such as compilation errors, deployment Failure etc. By discovering and handling these issues in a timely manner, teams can develop and maintain more efficiently.

Sample code:

GET /projects/:id/errors

2. Statistical function

GitLab’s statistical function can help the team gain an in-depth understanding of the running status of the project, so as to make data-driven decisions and optimization.

1. Code Quality

GitLab can perform statistical analysis on the code quality of the project, including code specifications, complexity, duplicate code and other indicators. Through these indicators, the team can promptly discover and repair low-quality code and improve the maintainability and scalability of the project.

Sample code:

GET /projects/:id/quality

2. Merge request

GitLab can perform statistical analysis on merge request indicators, including the number of merge requests and average processing time , pass rate, etc. Through these metrics, the team can understand the status of merge requests and optimize and improve accordingly.

Sample code:

GET /projects/:id/merge_requests

3. Test coverage

GitLab can perform statistical analysis on the test coverage of the project to help the team understand the test coverage. , thereby optimizing tests and improving code quality.

Sample code:

GET /projects/:id/test_coverage

3. Data analysis

In addition to the dashboard and statistical functions, GitLab also provides a wealth of data analysis tools to help the team make better use of Project data for decision-making and optimization.

1. Event log

GitLab can record various events in the project, such as code submission, merge request, build success, etc. The team can analyze these event logs to understand the overall operation of the project and discover potential problems and optimization points.

Sample code:

GET /projects/:id/events

2. Insight report

GitLab can generate insight reports, including project activity, contributor ranking, and merge request processing time wait. The team can use these reports to understand the overall status of the project and identify problems and areas for improvement.

Sample code:

GET /projects/:id/insights

Conclusion

GitLab’s dashboard and statistics capabilities and data analysis tools provide teams with the tools to better understand project progress and make data-driven decisions convenient. By using these features appropriately, teams can better manage and optimize projects, improve collaboration efficiency and code quality.

(Note: The above code examples are only demonstrations, not complete API interfaces. Please refer to GitLab official documentation for specific usage)

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