Create a fork of a dataset

Source: R/fork-and-merge.R

Forking a dataset makes a copy of the data that is linked by Crunch's version control system to the original dataset. When you make edits to a fork, users of the original dataset do not see the changes.

forkDataset(
  dataset,
  name = defaultForkName(dataset),
  draft = FALSE,
  ...,
  project = folder(dataset)
)

Arguments

dataset

The CrunchDataset to fork

name

character name to give the fork. If omitted, one will be provided for you

draft

logical: Should the dataset be a draft, visible only to those with edit permissions? Default is FALSE.

...

Additional dataset metadata to provide to the fork

project

A ProjectFolder object, string path that could be passed to cd() relative to the root project, or a URL for a ProjectFolder. Defaults to the same folder as the existing dataset.

Value

The new fork, a CrunchDataset.

Details

A common strategy for revising a dataset that has been shared with others is to fork it, make changes to the fork, and then merge those changes back into the original dataset. This workflow allows you to edit a dataset and review changes before publishing them, so that you don't accidentally send your clients incorrect data. For more on this workflow, see vignette("fork-and-merge", package = "crunch").

See also

mergeFork()

Examples

if (FALSE) { # \dontrun{
# Defaults to being placed in the same project folder as the original dataset
ds_fork <- forkDataset(ds)

# But you can specify a project by path, `ProjectFolder` object or URL
ds_fork2 <- forkDataset(ds, project = "/Client1/forks/")
ds_fork3 <- forkDataset(ds, project = projects()[["My forks"]])
ds_fork4 <- forkDataset(ds, project = "https://app.crunch.io/api/projects/abc/")
} # }