feat: add board_connect for Posit Connect, formerly RStudio

Author: machow

docs/api/constructors.rst

@@ -12,6 +12,6 @@ Board Constructors
    ~board_s3
    ~board_gcs
    ~board_azure
-   ~board_rsconnect
+   ~board_connect
    ~board_url
    ~board

docs/api/index.rst

@@ -36,8 +36,10 @@ Boards abstract over different storage backends, making it easy to share data in
      - Use an Azure storage container as a board
    * - :func:`.board_folder`, :func:`.board_local`, :func:`.board_temp`
      - Use a local folder as a board
+   * - :func:`.board_connect`
+     - Use Posit Connect as a board
    * - :func:`.board_rsconnect`
-     - Use RStudio Connect as a board
+     - Alias for Posit Connect board (it was formerly called RStudio Connect)
    * - :func:`.board_s3`
      - Use an S3 bucket as a board
    * - :func:`.board_gcs`

docs/getting_started.Rmd

@@ -46,7 +46,7 @@ Here are a few options:
 board = board_local() # share data across R sessions on the same computer
 board = board_folder("~/Dropbox") # share data with others using dropbox
 board = board_folder("Z:\\my-team\pins") # share data using a shared network drive
-board = board_rsconnect() # share data with RStudio Connect
+board = board_connect() # share data with Posit Connect
 ```
 
 
@@ -88,7 +88,7 @@ If you find yourself routinely pinning data larger that this, you might need to
 
 <!-- #region -->
 ```{note}
-If you are using the RStudio Connect board (`board_rsconnect`), then you must specify your pin name as
+If you are using the Posit Connect board (`board_connect`), then you must specify your pin name as
 `<user_name>/<content_name>`. For example, `hadley/sales-report`.
 ```
 <!-- #endregion -->

docs/intro.md

@@ -21,7 +21,7 @@ kernelspec:
 ```
 
 The pins package publishes data, models, and other Python objects, making it easy to share
-You can pin objects to a variety of pin *boards*, including folders (to share on a networked drive or with services like DropBox), RStudio Connect, Amazon S3, Google Cloud Storage, and Azure Datalake.
+You can pin objects to a variety of pin *boards*, including folders (to share on a networked drive or with services like DropBox), Posit Connect, Amazon S3, Google Cloud Storage, and Azure Datalake.
 Pins can be automatically versioned, making it straightforward to track changes, re-run analyses on historical data, and undo mistakes.
 
 You can use pins from R as well as Python. For example, you can use one language to read a pin created with the other. Learn more about [pins for R](https://pins.rstudio.com).
@@ -67,14 +67,14 @@ board.pin_read("mtcars")
 ```
 
 A board on your computer is good place to start, but the real power of pins comes when you use a board that's shared with multiple people.
-To get started, you can use `board_folder()` with a directory on a shared drive or in DropBox, or if you use [RStudio Connect](https://www.rstudio.com/products/connect/) you can use `board_rsconnect()`:
+To get started, you can use `board_folder()` with a directory on a shared drive or in DropBox, or if you use [Posit Connect](https://www.posit.co/products/connect/) you can use `board_connect()`:
 
 +++
 
 ```python
-from pins import board_rsconnect
+from pins import board_connect
 
-board = board_rsconnect()
+board = board_connect()
 
 board.pin_write(tidy_sales_data, "hadley/sales-summary", type = "csv")
 #> Writing pin:
@@ -89,13 +89,13 @@ Then, someone else (or an automated report) can read and use your pin:
 +++
 
 ```python
-board = board_rsconnect()
+board = board_connect()
 board.pin_read("hadley/sales-summary")
 ```
 
 +++
 
-You can easily control who gets to access the data using the RStudio Connect permissions pane.
+You can easily control who gets to access the data using the Posit Connect permissions pane.
 
 The pins package also includes boards that allow you to share data on services like
 Amazon's S3 (`board_s3()`), Google Cloud Storage (`board_gcs()`), and Azure Datalake (`board_azure()`).

pins/__init__.py

@@ -18,6 +18,7 @@
     board_github,
     board_urls,  # DEPRECATED
     board_url,
+    board_connect,
     board_rsconnect,
     board_azure,
     board_s3,

pins/constructors.py

@@ -31,8 +31,8 @@ def board_deparse(board: BaseBoard):
 
     The example below deparses a board connected to RStudio Connect.
 
-    >>> board_deparse(board_rsconnect(server_url="http://example.com", api_key="xxx"))
-    "board_rsconnect(server_url='http://example.com')"
+    >>> board_deparse(board_connect(server_url="http://example.com", api_key="xxx"))
+    "board_connect(server_url='http://example.com')"
 
     Note that the deparsing an RStudio Connect board does not keep the api_key,
     which is sensitive information. In this case, you can set the CONNECT_API_KEY
@@ -55,7 +55,7 @@ def board_deparse(board: BaseBoard):
 
     if prot == "rsc":
         url = board.fs.api.server_url
-        return f"board_rsconnect(server_url={repr(url)}{allow_pickle})"
+        return f"board_connect(server_url={repr(url)}{allow_pickle})"
     elif prot == "file":
         return f"board_folder({repr(board.board)}{allow_pickle})"
     elif prot == ["s3", "s3a"]:
@@ -353,7 +353,7 @@ def board_url(path: str, pin_paths: dict, cache=DEFAULT, allow_pickle_read=None)
     )
 
 
-def board_rsconnect(
+def board_connect(
     server_url=None, versioned=True, api_key=None, cache=DEFAULT, allow_pickle_read=None
 ):
     """Create a board to read and write pins from an RStudio Connect instance.
@@ -375,7 +375,7 @@ def board_rsconnect(
     ::
 
        server_url = "https://connect.rstudioservices.com"
-       board = board_rsconnect(server_url)
+       board = board_connect(server_url)
 
     In order to read a public pin, use board_manual with the public pin url.
 
@@ -406,6 +406,9 @@ def board_rsconnect(
     )
 
 
+board_rsconnect = board_connect
+
+
 def board_s3(path, versioned=True, cache=DEFAULT, allow_pickle_read=None):
     """Create a board to read and write pins from an AWS S3 bucket folder.