Read content from the connector — read

Generic implementing of how to read content from the different connector objects:

ConnectorDBI: Uses DBI::dbReadTable() to read the table from the DBI connection.

ConnectorFS: Uses read_file() to read a given file. The underlying function used, and thereby also the arguments available through ... depends on the file extension.

The file is located using internal function, which searches for files matching the provided name. If multiple files match and no extension is specified, it will use the default extension (configurable via options(connector.default_ext = "csv"), defaults to "csv").

ConnectorLogger: Logs the read operation and calls the underlying connector method.

Usage

read_cnt(connector_object, name, ...)

# S3 method for class 'ConnectorDBI'
read_cnt(connector_object, name, ...)

# S3 method for class 'ConnectorFS'
read_cnt(connector_object, name, ...)

# S3 method for class 'ConnectorLogger'
read_cnt(connector_object, name, ...)

Arguments

connector_object: Connector The connector object to use.
name: character Name of the content to read, write, or remove. Typically the table name.
...: Additional arguments passed to the method for the individual connector.

Value

R object with the content. For rectangular data a data.frame.

Examples

# Read table from DBI database
cnt <- connector_dbi(RSQLite::SQLite())

cnt |>
  write_cnt(iris, "iris")

cnt |>
  list_content_cnt()
#> [1] "iris"

cnt |>
  read_cnt("iris") |>
  head()
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1          5.1         3.5          1.4         0.2  setosa
#> 2          4.9         3.0          1.4         0.2  setosa
#> 3          4.7         3.2          1.3         0.2  setosa
#> 4          4.6         3.1          1.5         0.2  setosa
#> 5          5.0         3.6          1.4         0.2  setosa
#> 6          5.4         3.9          1.7         0.4  setosa

# Write and read a CSV file using the file storage connector

folder <- withr::local_tempdir("test", .local_envir = .GlobalEnv)

cnt <- connector_fs(folder)

cnt |>
  write_cnt(iris, "iris.csv")

cnt |>
  read_cnt("iris.csv") |>
  head()
#> → Found one file: /tmp/Rtmpp1dzyw/test1ebe3dc535a1/iris.csv
#> Rows: 150 Columns: 5
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (1): Species
#> dbl (4): Sepal.Length, Sepal.Width, Petal.Length, Petal.Width
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> # A tibble: 6 × 5
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#>          <dbl>       <dbl>        <dbl>       <dbl> <chr>  
#> 1          5.1         3.5          1.4         0.2 setosa 
#> 2          4.9         3            1.4         0.2 setosa 
#> 3          4.7         3.2          1.3         0.2 setosa 
#> 4          4.6         3.1          1.5         0.2 setosa 
#> 5          5           3.6          1.4         0.2 setosa 
#> 6          5.4         3.9          1.7         0.4 setosa 

# Add logging to a file system connector
folder <- withr::local_tempdir("test", .local_envir = .GlobalEnv)

cnt <- connectors(data = connector_fs(folder)) |> add_logs()

cnt$data |>
  write_cnt(iris, "iris.csv")
#> {"time":"2025-08-20 06:16:03","type":"write","file":"iris.csv @ /tmp/Rtmpp1dzyw/test1ebe477b5f4b"}

cnt$data |>
  read_cnt("iris.csv", show_col_types = FALSE) |>
  head()
#> → Found one file: /tmp/Rtmpp1dzyw/test1ebe477b5f4b/iris.csv
#> {"time":"2025-08-20 06:16:03","type":"read","file":"iris.csv @ /tmp/Rtmpp1dzyw/test1ebe477b5f4b"}
#> # A tibble: 6 × 5
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#>          <dbl>       <dbl>        <dbl>       <dbl> <chr>  
#> 1          5.1         3.5          1.4         0.2 setosa 
#> 2          4.9         3            1.4         0.2 setosa 
#> 3          4.7         3.2          1.3         0.2 setosa 
#> 4          4.6         3.1          1.5         0.2 setosa 
#> 5          5           3.6          1.4         0.2 setosa 
#> 6          5.4         3.9          1.7         0.4 setosa