workspace is an R package designed to simplify the creation and
management of workspaces. Its main goal is to provide a standardized
solution for organizing and sharing data in applications that require
workspace management.
This package is aimed at developers and analysts seeking to standardize
data management in multi-environment or cross-application contexts. With
workspace, creating, manipulating, and sharing organized archives
becomes straightforward.
- Generation of structured archives:
- Supports adding datasets in parquet format.
- Enables storing JSON files for semi-structured data.
- Handles R objects stored in RDS format.
- Enhanced interoperability:
- Provides a well-defined and consistent structure for organizing data.
- Facilitates data exchange and processing across different applications or environments.
- Offers tools to easily read and store data within workspaces.
You can install the development version of workspace from GitHub with:
# install.packages("pak")
pak::pak("ardata-fr/workspace")This is a basic example which shows you how to create a workspace:
library(workspace)
z <- new_workspace()
# store datasets
z <- store_dataset(x = z, dataset = iris, name = "iris_dataset")
z <- store_dataset(x = z, dataset = mtcars, name = "mtcars")
# store json
json_str <- paste0("{\"first_name\": \"John\",\"last_name\": \"Smith\",\"is_alive\": true,",
"\"age\": 27, \"address\": { \"street_address\": \"21 2nd Street\",",
"\"city\": \"New York\",\"state\": \"NY\",\"postal_code\": \"10021-3100\"",
"}}")
z <- store_json(
x = z,
name = "json-example",
json_str = json_str,
filename = "json-example.json",
timestamp = "2023-11-12 11:37:41",
subdir = "blah"
)
# pack workspace as a zip to share it
workspace_zip_file <- tempfile(fileext = ".zip")
pack_workspace(x = z, file = workspace_zip_file)
#> [1] "/private/var/folders/08/2qdvv0q95wn52xy6mxgj340r0000gn/T/RtmpDu03jK/file79c764187a07.zip"This is a basic example which shows you how to extract data from a workspace:
z <- unpack_workspace(file = workspace_zip_file)
list_object_in_workspace(z)
#> # A tibble: 3 × 5
#> file name subdir type timestamp
#> <chr> <chr> <chr> <chr> <chr>
#> 1 datasets/iris_dataset.parquet iris_dataset datasets dataset 2025-01-11 12:30:…
#> 2 datasets/mtcars.parquet mtcars datasets dataset 2025-01-11 12:30:…
#> 3 assets/blah/json-example.json json-example blah json 2023-11-12 11:37:…
dataset <- read_dataset_in_workspace(z, name = "mtcars")
print(head(dataset))
#> # A tibble: 6 × 11
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
# store json
json_str <- read_json_str_in_workspace(z, name = "json-example", subdir = "blah")
substr(json_str, 1, 20) |> print()
#> [1] "{\"first_name\": \"John"wo
8000
rkspace can be useful for managing user imported datasets in Shiny
apps. The example shows how to create, add datasets, pack and unpack the
user’s workspace.
library(workspace)
library(shiny)
library(readr)
library(shinyWidgets)
# Define UI for application that draws a histogram
ui <- fluidPage(
tags$h4("Add datasets to workspace"),
shiny::fileInput(
inputId = "file",
label = "Upload dataset",
accept = c("csv")
),
textInput(
inputId = "name",
label = "Dataset name"
),
actionButton(
inputId = "new",
label = "Add to workspace",
accept = c("csv")
),
tags$hr(),
tags$h4("Import/export workspace"),
shiny::fileInput(
inputId = "import",
label = "Import workspace",
accept = c("zip")
),
downloadButton(
outputId = "downloadData",
label = "Export workspace"
),
tags$hr(),
tags$h4("Display workspace"),
tableOutput("workspace"),
selectInput(
inputId = "selector",
label = "Display table preview",
choices = character()
),
tableOutput("table")
)
server <- function(input, output) {
rv <- reactiveValues(
curr_dataset = NULL,
ws = workspace::new_workspace(),
summary = NULL
)
# Import csv file ----------
observe({
req(input$file)
rv$curr_dataset <- shinyWidgets::execute_safely({
readr::read_csv(input$file$datapath, show_col_types = FALSE)
})
updateTextInput(
inputId = "name",
value = tools::file_path_sans_ext(input$file$name)
)
})
# Add new data set to workspace
observeEvent(input$new, {
dataset <- req(rv$curr_dataset)
req(rv$ws)
rv$ws <- workspace::store_dataset(x = rv$ws, dataset = dataset, name = trimws(input$name))
rv$summary <- workspace::list_object_in_workspace(rv$ws)
})
# Display workspace metadata --------------
output$workspace <- renderTable({
req(rv$summary)
rv$summary
})
observe({
req(nrow(rv$summary) > 0)
updateSelectInput(
inputId = "selector",
choices = rv$summary$name
)
})
output$table <- renderTable({
req(input$selector)
workspace::read_dataset_in_workspace(x = rv$ws, name = input$selector) |>
head()
})
# Export workspace ------------
output$downloadData <- downloadHandler(
filename = function() {
paste("workspace-", Sys.Date(), ".zip", sep = "")
},
content = function(file) {
workspace::pack_workspace(x = rv$ws, file = file)
}
)
# Import workspace ----------
observeEvent(input$import, {
rv$ws <- workspace::unpack_workspace(file = input$import$datapath)
rv$summary <- workspace::list_object_in_workspace(rv$ws)
})
}
shinyApp(ui = ui, server = server)