Pull Requests Dataset Exploration Report
Gain a comprehensive understanding of pull request data with Keypup's Pull Requests Dataset Exploration Report. This indispensable tool investigates how pull request data from Git sources is precisely imported, normalized, and integrated into Keypup. By familiarizing yourself with the detailed structure and organization of your pull requests dataset, you can attain clearer insights into your development processes, contributing to more effective code integration, improved team collaboration, and elevated project outcomes.
Optimize Your Pull Request Processes
with the
Pull Requests Dataset Exploration Report
Gain a comprehensive understanding of pull request data with Keypup's Pull Requests Dataset Exploration Report. This indispensable tool investigates how pull request data from Git sources is precisely imported, normalized, and integrated into Keypup. By familiarizing yourself with the detailed structure and organization of your pull requests dataset, you can attain clearer insights into your development processes, contributing to more effective code integration, improved team collaboration, and elevated project outcomes.
From startups to large enterprises, Keypup serves all the unique complexities related to project size, structure and teams, including:
“Keypup is a highly useful and practical platform, boasting user-friendly features and lightning-fast report generation.
The service provided by customer support was excellent, showcasing their dedication to customer satisfaction. We are delighted to be part of the Keypup community.”
“Keypup has been instrumental in helping us gain a better perspective on our engineering activities and identifying bottlenecks. Its ease of use combined with its comprehensive features made a difference for us”
“Great product with great support!
‍
Keypup is extremely flexible in its reporting. Once you get your raw data connected, there is almost nothing it can't do. There is a wealth of tables, charts and other reports available. As Director of a software development team, I use Keypup to report on our work efficiencies to senior managment. Keypup makes this task very simple to produce each week.”
Deep Dive Into Your Pull Requests Data
To build the PR Dataset Exploration Report, we apply two filters on the report from the Issues and PRs Dataset: one date filter and one filter on the “Type” field to isolate pull requests only.
We then offer 20 columns with populated or calculated fields to facilitate your PR data exploration. These columns include:
- Created at: The date/time at which the PR was created.
- Title: The title, summary, or name of the PR.
- Author: The username of the person who created the PR. Note that usernames are app specific.
- Assignees: The list of people usernames declared as being assigned to the PR. Note that usernames are app specific.
- Body: The body of the PR in source format.
- Labels: The list of labels tagged to the PR. Labels are app-specific and case-sensitive.
- URL: The PR URL in the source application.
- First commit at: The date/time at which the first commit was made on a pull request.Â
- Due on: The due date of the PR. This due date takes into account resolved issues (e.g., a pull request resolving multiple issues will have a due on value equals to the earliest due date).
- Project: The name of the project associated with the PR
- State: The open/close state of the PR. Possible values are: CLOSED: The pull request was closed without being merged, DRAFT: The pull request is currently being worked on and is not ready to be looked at by others, MERGED: The pull request was merged, OPEN: The pull request is still active.
- Build status: The state of the Continuous Integration (CI) as exposed by the code management platforms (e.g., GitHub, GitLab). Possible values are: NONE: No builds detected, IN_PROGRESS: The build is pending or currently running, FAILURE: The build failed to complete due to an error, a timeout or because it was canceled, SUCCESS: The build completed successfully or was skipped, ACTION_REQUIRED: The build requires a manual action from the user.
- Merge at: The date/time at which the pull request was merged. The field will be null for pull requests which have been closed without merge.
- Merge by: The username of the person who merged the pull request. Note that usernames are app specific.
- Closed at: The date/time at which the PR was merged or closed.
- Line changed: This calculated field provides the number of lines of code added or deleted in the pull request (additions + deletions).
- Requested reviewers: The list of people usernames assigned as reviewers on the pull request. Note that usernames are app specific.
- Updated at: The date/time at which the PR was last updated.
- Head ref | branch: The branch of the head ref (source branch).
- Base ref | branch: The branch of the base ref (destination branch).
Key Benefits of the Pull Requests Dataset Exploration Report
Efficient Pull Request Management
Uncover the nuances of how pull request data is structured and utilized within your development projects. This report reveals the complexities of pull request management, offering insights into enhancing the efficiency and effectiveness of your code review and integration processes.
Deep Understanding of Development Dynamics
Through an in-depth analysis of the pull request data, identify key trends and patterns in your development activities. This understanding is crucial for recognizing and overcoming potential obstacles in your coding and reporting practices.
Seamless Workflow Integration
Employ the insights from this report to effectively integrate pull request data into your development workflow. Understanding the detailed data mapping and processing allows for the creation of more streamlined and productive development practices and metrics.
Data-Driven Development Enhancements
Use the comprehensive insights provided by the report to construct and monitor impactful metrics and make informed decisions regarding code reviews, team collaboration, and project timelines. The granularity of the data analysis equips you to customize your strategies to align with your project's specific requirements.
Leverage the Power of the Pull Requests Dataset Exploration Report
The Pull Requests Dataset Exploration Report is an essential asset for any team seeking to deepen their trust in and understanding of their pull request data. With this report, you can refine your code review strategies, enhance collaboration, and improve overall project development and reporting.
‍
Ready to elevate your development processes? Explore the Pull Requests Dataset Exploration Report and begin transforming your pull request management today.