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Pins for R#

The pins R package provides a way for R users to easily share data sets, models, and other R objects. Your resources may be text files (CSV, JSON, etc.), R objects (.Rds, .Rda, etc.) or any other format you use to share data. Pinned objects can be stored on a variety of "boards", including local folders (to share on a networked drive or with dropbox), Posit Connect, Amazon S3, and more.

Sharing data can be useful in many situations, for example:

  1. Multiple pieces of content require the same input data. Rather than copying that data, each piece of content references a single source of truth hosted on Posit Connect.

  2. Content depends on data or model objects that need to be regularly updated. Rather than redeploying the content each time the data changes, use a pinned resource and update only the data. The data update can occur using a scheduled R Markdown document. Your content will read the newest data on each run.

  3. You need to share resources that aren't structured for traditional tools like databases. For example, models saved as R objects aren't easy to store in a database. Rather than using email or file systems to share data files, use Posit Connect to host these resources as pins.

Pins and large data sets

An important factor in determining whether or not to use a pin is the size of the data or object in use. As a general rule of thumb, we don't recommend using pins with files over 500 MB. If you find yourself routinely pinning data larger than this, then you might need to reconsider your data engineering pipeline. Please see Reading and writing data to learn more.

Recommended Resource: Pro Tips for Pins

Create a Pin Board#

Posit Connect is easy to use as a board for pinning R objects. Create a board to use with pins::board_rsconnect(). This function takes an auth argument which informs how you will authenticate to Posit Connect.

Use auth = "envvar" if you have already defined CONNECT_SERVER and CONNECT_API_KEY as environment variables in your R session.

board <- board_rsconnect(auth = "envvar")

Posit Connect will automatically apply values for these environment variables for deployed content at run time, so there is no need to include them in your code (never a best practice) or specify them in the Vars Pane unless your server administrator has disabled that function.


The automatic generation of these environment variables may be disabled for security reasons. Reach out to your Posit Connect server administrator or review the Admin Guide for additional details.

Read and Write Pins#

Once you have a pin board, you can write data to it with pin_write():

mtcars <- tibble::as_tibble(mtcars)
board %>% pin_write(mtcars, "mtcars")

The first argument is the object to save (usually a data frame, but it can be any R object), and the second argument gives the "name" of pin. On Posit Connect, this name will be used along with your Username to retrieve or read data from the pin. Running the code above should yield a success message that looks something like this: Writing to pin 'my.username/mtcars'.

After you’ve pinned an object, you can read it back with pin_read():

board %>% pin_read("my.username/mtcars")

Pin Metadata#

Every pin is accompanied by some metadata that you can access with pin_meta(). This will return the metadata generated by default. Pins from Posit Connect will have a url and content_id.

When creating the pin, you can override the default description or provide additional metadata that is stored with the data:

board %>% pin_write(mtcars, 
  description = "Data extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973–74 models).",
  metadata = list(
    source = "Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391–411."

Learn more about Pin Metadata.

Using a Pin#

Once a pin has been deployed, it is easy to share the pin with colleagues. You can either share the link to the pin in Posit Connect, or colleagues can search for resources using the pin package within the RStudio IDE.

See Sharing tidied data to learn more.

You can manage content settings for deployed pins just like you would for other content types. For example, you can manage access controls to pins to determine who should be able to view and utilize the resource.

Posit Connect provides a preview of pinned data objects, their metadata, and a direct download link which can be accessed at the content url:

Example of a Pin on Posit Connect.

Updating a Pin#

Pins are objects; they are not backed by source code and so they cannot be directly scheduled. A common pattern for updating pinned data on a schedule is to run pins::pin_write() inside a scheduled R Markdown document. Writing to the same pin multiple times creates a version history which can be accessed under the "More" button dropdown menu.