Managing GitHub issues efficiently requires exporting data for analysis and reporting. This guide covers the process of exporting GitHub issues to CSV format, facilitating a streamlined workflow for data handling.
We'll also explore how Sourcetable allows you to analyze your exported data with AI in a simple-to-use spreadsheet.
The GitHub CLI tool is a convenient way to export issues from a GitHub repository to a CSV file. To get started, install the CLI by running brew install gh. After installation, log in to GitHub using gh auth login. You can then export the issues by executing the command gh issue list --limit 1000 --state all | tr '\t' ',' > issues.csv. This will create an issues.csv file using comma delimiters. If you prefer semicolons, replace ',' with ';'.
To export issues from a private repository, you can use the curl command combined with the GitHub API. This requires a personal access token for authentication. Run curl -i https://api.github.com/repos/
Issues can be exported and converted from JSON to CSV using a jq expression. Use the command gh issue list --limit 10000 --state all --json number,title,assignees,state,url | jq -r '["number","title","assignees","state","url"], (.[] | [.number, .title, (.assignees | if .|length==0 then "Unassigned" elif .|length>1 then map(.login)|join(",") else .[].login end) , .state, .url]) | @tsv' > issues-$(date '+%Y-%m-%d').tsv. This exports the issues with specified fields and converts the JSON output to a tab-separated values file.
The hub command-line tool also supports exporting GitHub issues to CSV. The command hub issue -f "%t,%l%n" > list.csv exports issues with titles and labels separated by commas. For more options and detailed exports, use hub issue -s all -d 2019-08-20 -o updated --include-pulls -f "%U|%t|%S|%cI|%uI|%L%n" > issues.csv. This command includes various issue attributes such as URLs, states, and timestamps.
PyGithub is a Python package that can be used to export GitHub issues to CSV. First, install the package and authenticate using a personal access token. Use Python scripts to query issues from a repository and write the data into a CSV file. This method allows flexibility in choosing and formatting issue attributes.
GitHub issues can be exported to CSV using Excel's Power Query feature. Start by querying the GitHub API to get issues in JSON format. Convert the JSON response into an Excel table by transforming the data in Power Query. After creating the table, save it as a CSV file. This method is useful for users familiar with Excel and needing to keep data updated regularly.
The Export Pull Requests package is another tool that can be used to export issues to a CSV file. Similar to other CLI tools, this package offers various customization options and supports exporting detailed issue attributes into a CSV format, providing a comprehensive data export solution.
The GitHub CLI is an effective tool for exporting GitHub issues to CSV format. First, install the GitHub CLI by running the command brew install gh. Next, authenticate by running gh auth login.
To export issues, use the command gh issue list --limit 1000 --state all | tr '\t' ',' > issues.csv. This command will generate a file named issues.csv with comma delimiters. For semicolon delimiters, use gh issue list --limit 1000 --state all | tr ';' ',' > issues.csv.
To export issues from private repositories, you must use the curl command alongside the GitHub API. The command is curl -i https://api.github.com/repos/
The output will be in JSON format. To convert the JSON to CSV, use jq alongside curl with the command gh issue list --limit 10000 --state all --json number,title,assignees,state,url | jq -r '["number","title","assignees","state","url"], (.[] | [.number, .title, (.assignees | if .|length==0 then "Unassigned" elif .|length>1 then map(.login)|join(",") else .[].login end), .state, .url]) | @tsv' > issues-$(date '+%Y-%m-%d').tsv.
Power BI and Power Query can also be used to export GitHub issues to CSV. These tools require knowledge of converting JSON to an Excel table format. First, use the GitHub API to obtain issues in JSON format.
Authenticate the request with a personal access token. Use Power Query in Excel to transform the JSON data into a table. Once in table format, save it as a CSV file. This method supports filtering options for more refined data exports.
Another method for exporting GitHub issues to CSV involves using the Python package PyGithub. PyGithub allows for programmatic access to GitHub's data, making it possible to automate the process of exporting issues.
First, install PyGithub and authenticate with your personal access token. Create a script to fetch the issues and write them to a CSV file. This method is particularly useful for users comfortable with writing Python scripts and looking to automate their workflows.
The hub command-line wrapper for GitHub provides another solution. Use the command hub issue -f "%t,%l%n" > list.csv to export issues into a CSV file. This command structures the output using custom delimiters for better compatibility with your data processing tools.
Exporting GitHub issues to CSV can be done via multiple methods utilizing GitHub CLI, curl, Power BI, Python, and the hub tool. Choose the method that best fits your technical capabilities and needs. Each of these tools provides versatile options to ensure you can effectively manage and analyze your GitHub issues data.
Bug Reporting and Feature Requests |
GitHub Issues is essential for reporting bugs and requesting new features. The ability to link a pull request to an issue indicates progress on fixes and automatically closes issues upon merging. This streamlines the debugging and feature implementation process, ensuring clear communication and efficient resolution. |
Team Collaboration |
Utilizing GitHub Issues for team collaboration involves tracking day-to-day tasks and making collective decisions on improvements. By assigning issues and using @mentions, teams can ensure that every member is aware of their responsibilities, making it easier to manage and prioritize work. |
Project Management |
GitHub Issues integrates project planning and execution, breaking down large projects into manageable tasks. It provides progress indicators, milestones, and the ability to convert tasks into separate issues, making it simple to navigate and update project hierarchies. |
Tracking Work Types |
GitHub Issues can track various types of work, including release tracking, large initiatives, and documentation feedback. This versatility allows project managers to have a consolidated view of all ongoing tasks and their statuses, improving overall project coordination. |
Support Requests and Documentation Feedback |
GitHub Issues allows you to process support requests and submit documentation feedback. These capabilities ensure that user and developer inputs are collected, reviewed, and acted upon, fostering continuous improvement of the project. |
Enhanced Discussion and Clarity |
Hosting discussions and clarifying tasks within GitHub Issues helps maintain a clear communication channel. The use of Markdown, attachments, and templates further enhances this clarity, making it easier for team members to express ideas and share best practices. |
Parallel Workflows |
Breaking down large issues into smaller ones allows team members to work in parallel. This approach leads to the creation of smaller pull requests, which are easier to review and manage. Automating these processes minimizes busy work and optimizes team efficiency. |
Filtering and Searching |
GitHub Issues offers powerful filtering, sorting, and searching capabilities, allowing users to focus on the most relevant tasks. This feature enhances the ability to keep track of issues and pull requests, ensuring important work is not overlooked. |
Sourcetable offers a streamlined solution for managing data by integrating multiple data sources into a single spreadsheet. This empowers users to perform real-time queries and manipulate data efficiently, unlike the more segmented approach of GitHub Issues.
With Sourcetable, you can extract data directly from databases in real-time, ensuring that you always work with the most current information available. This eliminates the delay and inconvenience often associated with traditional issue tracking tools like GitHub Issues.
Sourcetable's spreadsheet-like interface simplifies data manipulation, making it more intuitive and user-friendly. This allows teams to analyze and manage data more effectively, boosting productivity and collaboration compared to the issue tracking interface of GitHub Issues.
First, install the GitHub CLI using `brew install gh`. Then, log into the CLI with `gh auth login`. Navigate to your repository using `cd
You can use the GitHub API to export issues in JSON format. Use the URL `https://api.github.com/repos/
Yes, you can use the PyGithub package in Python to export GitHub issues to CSV. This involves querying the GitHub API for issues data and then writing that data to a CSV file.
To use a different delimiter, modify the command accordingly. For example, to use a semicolon as the delimiter, use `gh issue list --limit 1000 --state all | tr ',' ' ' | tr '\t' ';' > issues.csv`.
Yes, Power BI can query the GitHub API for issues data. It requires a query using the API and an Authorization header for authentication. The JSON data returned can be converted to a table within Power BI and then exported as a CSV.
Exporting GitHub issues to CSV is a straightforward process that enhances your data analysis capabilities. Detailed tracking and automated workflows become seamless with the exported data.
Now that you have your GitHub issues in a CSV file, leverage this data to uncover insights and optimize your projects.
Sign up for Sourcetable to analyze your exported CSV data with AI in a user-friendly spreadsheet.