How To Export GitHub Pull Requests to CSV
Use Sourcetable AI To Analyze Any CSV
Introduction
Exporting GitHub pull requests to CSV can streamline data analysis and reporting. This guide provides step-by-step instructions to easily extract pull request data from GitHub.
We'll also explore how Sourcetable lets you analyze your exported data with AI in a simple to use spreadsheet.
Exporting GitHub Pull Requests to CSV Format
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Using the GitHub API
You can extract pull request information from a repository programmatically using the GitHub API. This method requires a personal access token for authentication. The GitHub API allows you to interact with pull requests and retrieve relevant data in a structured format such as JSON. This data can then be converted to CSV format using additional tools like jq or custom scripts.
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Using GitHub CLI
The GitHub CLI is a powerful tool to extract pull request information directly from the command line. The command "gh pr list" can be used to list pull requests in a repository. To get the status of the pull requests, use the command "gh pr status". These commands provide the necessary data that can be redirected into a CSV file using standard output redirection techniques in your terminal.
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Using PyGithub
PyGithub is a Python package that allows you to interact with the GitHub API in a more accessible way through Python scripting. PyGithub requires a personal access token for authentication. It can be used to access pull requests and export the retrieved data to CSV format. This method is particularly useful for integrating with Python-based data processing workflows.
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Using Excel Power Query
Excel's Power Query feature can be used to directly query the GitHub JSON API and retrieve pull request data. This method provides an intuitive interface within Excel to interact with the API, transform the data, and export it to CSV format. Authentication with a personal access token is still required to access the API.
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Combining Tools
Combining different tools can optimize the process of exporting pull request data to CSV. For instance, using the GitHub API with curl for data extraction and jq for formatting can be very effective. Similarly, start with GitHub CLI commands to list and gather pull request data, then utilize scripting or tools like PyGithub for conversion to CSV.
How to Export GitHub Pull Requests to CSV
Using the GitHub API
You can use the GitHub API to extract pull request information from a repository programmatically. This method allows you to interact with pull requests and export their data along with their statuses. To get started, refer to the GitHub REST API documentation for guidance on how to filter and search pull requests.
Using GitHub CLI
The GitHub CLI (command-line interface) offers a straightforward way to export pull request data to CSV format. The primary commands to use are gh pr list to list pull requests and gh pr status to get their statuses. You can combine these commands with other command-line tools to format and export the data to CSV.
Exporting Issues with GitHub CLI
Although primarily intended for issues, similar commands can be adapted for pull requests. For instance, you can use gh issue list --limit 1000 --state all | tr '\t' ',' > issues.csv to export issues data to CSV. Adjust these commands to target pull requests instead.
Using Third-Party Tools
Third-party tools like the Python package PyGithub offer additional methods to retrieve and export pull requests to CSV. Additionally, you can leverage GitHub's JSON API and tools like Power Query in Excel to convert JSON data into an Excel table format efficiently.
Using Command-Line Wrappers
The hub command-line wrapper for GitHub can be another efficient option. Use the command hub issue -f "%t,%l%n" > list.csv to format pull request data into CSV. Note that this requires creating a GitHub personal access token and downloading the latest hub executable. This method is supported on Windows using GitBash.
In summary, multiple methods exist to export GitHub pull requests to CSV format, whether through API interactions, GitHub CLI commands, or third-party tools. Choose the method that best fits your workflow and familiarity with the tools available.
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GitHub Pull Request Use Cases
Collaborative Code Review and Feedback |
Pull requests on GitHub facilitate collaboration by allowing team members to propose changes to a branch in a repository. This enables code reviews and discussions before integrating changes into the main codebase, ensuring high-quality and well-reviewed code. |
Sequential Code Integration |
Pull requests manage the process of merging changes from one branch into another. This allows for organized and sequential integration of features, bug fixes, or enhancements from a feature branch into a base branch, streamlining the workflow. |
Parallel Development |
GitHub pull requests support parallel work on code changes. Multiple branches can be developed simultaneously without impacting each other's progress. This speeds up development cycles and allows for efficient management of concurrent tasks. |
Improved Code Quality and Performance |
The review process enabled by pull requests helps improve the quality of the code and its performance. Collaborators can provide feedback, suggest improvements, and ensure that the proposed changes meet performance standards before they are merged. |
Continuous Updates and Follow-Up Commits |
Pull requests support continuous updates by allowing follow-up commits to a topic branch. If a proposed change requires further adjustments, developers can push additional commits to address feedback, keeping the pull request up-to-date. |
Enhanced Search and Filter Capabilities |
GitHub pull requests are searchable and filterable, making it easy to find specific pull requests among many. This feature aids in tracking the progress of various tasks and facilitates efficient project management. |
Branch-Based Workflow Management |
In GitHub flow, pull requests are an integral part of the lightweight, branch-based workflow. They enable a structured process of creating branches, making changes, pushing commits, and eventually merging the changes after review, ensuring a smooth and organized workflow. |
Discussion and Proposal Platform |
Pull requests act as a platform for proposing changes and discussing them in detail via comments. They facilitate collaboration by allowing discussions in issues before formalizing changes in pull requests, fostering team communication and consensus-building. |
Why Sourcetable is an Alternative for GitHub Pull Requests
Sourcetable is a powerful spreadsheet tool that centralizes all your data, pulling from multiple sources. Unlike GitHub pull requests, which are centered around code repositories and version control, Sourcetable focuses on data aggregation and real-time querying. This allows for more flexible data manipulation using a spreadsheet-like interface.
With Sourcetable, you can directly query your database in real-time, offering immediate access to the latest data. GitHub pull requests require a more rigid approach, focusing on code changes rather than direct data interaction. Sourcetable’s approach streamlines data-driven decision-making by simplifying how you access and manipulate your data.
For teams that need to integrate data from various sources and perform data analysis with ease, Sourcetable offers a more suitable environment. While GitHub pull requests are ideal for collaborative coding, Sourcetable's user-friendly interface facilitates comprehensive data management and analytics, making it a valuable alternative for data-focused teams.
Conclusion
Exporting GitHub pull requests to a CSV file is a straightforward process that can enhance your data analysis capabilities. By leveraging this export function, teams can efficiently track, analyze, and manage pull requests.
Utilizing CSV files simplifies the process of sharing and collaborating on data-driven tasks. This export function allows for seamless integration with various data analysis tools.
Sign up for Sourcetable to analyze your exported CSV data with AI in a simple-to-use spreadsheet.
Try Sourcetable For Free
Do anything you want in a spreadsheet using AI. No Excel skills required.
Try Sourcetable For A Smarter Spreadsheet Experience
Sourcetable makes it easy to do anything you want in a spreadsheet using AI. No Excel skills required.