5 Ways to Save Excel Power Query to IDE

In the realm of data manipulation, Microsoft Excel stands as an enduring tool, constantly evolving to meet the demands of data analysts and casual users alike. A significant upgrade in Excel's repertoire is the Power Query Editor, an advanced feature for extracting, transforming, and loading (ETL) data from various sources. However, many users find the traditional Excel interface limiting for complex query editing. That's where integrating Power Query with an Integrated Development Environment (IDE) comes into play. Here are five effective ways to export and save your Power Query code to an IDE, enhancing your productivity and coding experience:

1. Manual Copy-Paste Method

The simplest approach, albeit manual, involves copying the M code directly from Excel's Power Query Editor and pasting it into your preferred IDE:

• Open Power Query Editor in Excel.
• Select the step you wish to export by clicking on its respective icon in the Applied Steps pane.
• Right-click on the query's name in the Queries pane, choose Advanced Editor, and copy all the M code.
• Open your IDE, and create a new file (often with a .m extension, although this isn't mandatory).
• Paste the copied M code into the IDE.

This method is straightforward but can be time-consuming if you're managing multiple queries or large codebases.

💡 Note: Remember to ensure that all references and dependencies are preserved when manually copying and pasting.

2. VBA Macro Export

VBA (Visual Basic for Applications) can be used to automate the process of exporting Power Query scripts:

• Open Excel's VBA editor.
• Create a module and insert the following code:

      Sub ExportPowerQueryCode()
          Dim query As WorkbookQuery
          Dim code As String
          Dim queryName As String
  
          For Each query In ThisWorkbook.Queries
              queryName = query.Name
              code = query.Formula
  
              ' Save the code as an .m file in your desired folder
              Open "C:\YourFolder\" & queryName & ".m" For Output As #1
              Write #1, code
              Close #1
          Next query
      End Sub
      

• Run the macro to export all Power Query M code into separate files.

Ensure your file path in the code points to the desired directory for saving the exported files.

3. Using Power Query to Export Itself

This meta technique uses Power Query to export its own code:

• In Power Query, create a new blank query.
• Add a new column with this expression:

   = "let " & Text.FromBinary(Excel.CurrentWorkbook(){[Name="Query"]}[Content])

• Expand the new column to see the full M code.
• Export this query as a .m file to your IDE, similar to the VBA method.

🛠 Note: This method provides a way to review or compare versions of your code over time.

4. Command Line Interface (CLI) Tools

Advanced users might leverage CLI tools like pnpx from the Office Toolset to export Power Query files:

• Install Node.js and the necessary tools.
• Use the command:

  pnpx excel-query-export --file "path-to-excel-file" --output "path-to-output-directory"

• The tool will export all Power Query scripts to .m files in the specified directory.

Ensure you have the right permissions and path settings for your environment.

5. Power Query Scripts API

The Power Query Scripts API, part of Microsoft's Graph API, can be used to programmatically export and manage Power Query scripts:

• Configure your app's permissions in Azure AD to access Excel files.
• Use the Microsoft Graph API to export the Power Query:

      GET https://graph.microsoft.com/beta/me/drive/items/{item-id}/workbook/scripts/{script-id}
      

• Save the retrieved script to a local file or directly into an IDE.

📝 Note: This approach requires Azure AD setup and API access, which might be overkill for non-enterprise users.

Integrating Power Query with an IDE not only speeds up your coding process but also provides version control, advanced debugging features, and a more sophisticated development environment. Whether you prefer the simplicity of copy-pasting or the automation of scripting, these methods offer flexibility for developers at all levels. Embrace these techniques to enhance your data transformation workflow, making it more efficient and less error-prone. The key is choosing the method that best suits your skill level, time constraints, and organizational resources. With this knowledge, you're now equipped to explore the vast potential of Power Query in a more powerful and controlled development environment.