Managing files on the workbench

The allofus package includes several functions designed to help you manage and transfer files between your personal workspace and a shared bucket in Google BigQuery. Understanding the difference between these two storage locations is crucial:

Listing Files

In Your Workspace

Use aou_ls_workspace() to list files in your workspace. This function is handy for quickly checking which files you have stored locally.


In Your Bucket

Similarly, aou_ls_bucket() lists files in your bucket. This function can be used to view files that you or your collaborators have saved for shared access.


You can also use the pattern argument with these functions to filter the listed files based on a naming pattern.

aou_ls_workspace(pattern = "*.csv")
aou_ls_bucket(pattern = "project_*.csv")

Transferring Files

These functions are used in conjunction with R’s reading and writing functions. You can store any type of data in both the workspace and the bucket.

From Workspace to Bucket

Once you’ve processed or created a file in your workspace, you might want to move it to the bucket for permanent storage or to share it with collaborators. Use aou_workspace_to_bucket() for this purpose.

write.csv(data, "file1.csv")

From Bucket to Workspace

If you need to use a file that a collaborator has saved to the bucket, or if you want to retrieve a file after deleting your environment, use aou_bucket_to_workspace().

data <- read.csv("file2.csv")

Workflow Example

Here’s a typical workflow using these functions:

  1. List files in your workspace : Check what files you currently have.
  2. Process or create files : Perform your data analysis or other work in R.
  3. Save files to your workspace : Use R’s file handling functions like write.csv() or write.rds().
  4. Transfer to the bucket for sharing or permanent storage : Use aou_workspace_to_bucket().
  5. Access shared files from the bucket : Use aou_bucket_to_workspace() to bring files into your workspace as needed.

Important Considerations