redivis

package Redivis

The redivis package, available via library("redivis"). Through its various methods, you can create, update, query, and read from resources on Redivis.

To avoid conflicts with other packages and base R function names, redivis's top level functions are hosted in the redivis namespace, and accessible via the redivis$ prefix. This means that code written for Redivis in Python, R, and Javascript is quite similar.

Previous versions of redivis-r recommended accessing top-level methods via the redivis:: syntax (e.g., redivis::user()). This syntax is deprecated, and we recommend migrating existing code to use the $ syntax.

Methods

redivis$connect_dbi()	Construct a globally scoped DBI connection across Redivis.
redivis$current_notebook()	Construct a reference to the current notebook. Can only be called within a Redivis notebook.
redivis$current_user()	Construct a reference to the currently authenticated user.
redivis$current_workflow()	Construct a reference to the current workflow. Can only be called within a Redivis notebook, or if a default workflow is set.
redivis$datasource(source)	Construct a new Datasource instance. Can only be called if a default workflow is set. Otherwise, use the workflow$datasource() constructor.
redivis$make_api_request([method, path, query, ...])	Call the Redivis API directly, for advanced use cases.
redivis$notebook(name)	Construct a new Notebook instance.
redivis$parameter(name)	Construct a new Parameter instance.
redivis$organization(name)	Construct a new Organization instance.
redivis$query(query)	Execute a SQL query, returning a Query instance.
redivis$table(name)	Construct a new Table instance. This method can only be called if default workflow / dataset is set (this is automatically set within a Redivis notebook to that notebook's workflow).
redivis$transform(name)	Construct a new Transform instance.
redivis$user(name)	Construct a new User instance.

Examples

devtools::install_github("redivis/redivis-r")
library("redivis")

organization <- redivis$organization("Demo")
# organization$list_datasets(), organization$dataset("Iris species"), etc...

dataset <- organization$dataset("iris_species")
table <- dataset$table("iris")  
# table$to_tibble(), etc...
# In a notebook, can do redivis$table("_source_") to reference the source table

query <- redivis$query("
    SELECT * 
    FROM demo.iris_species.iris 
    WHERE SepalLengthCm > 5
")
# query$to_tibble(), etc...