You'll need to set the BIGQUERY_TEST_PROJECT (name of a project) and
BIGQUERY_TEST_BUCKET (name of bucket) env vars in order to run bigrquery
tests locally. I recommend creating a new project because the tests involve
both reading and writing in BigQuery and Cloud Storage.
The BIGQUERY_TEST_PROJECT must have billing enabled for the project. While
logged in, via bq_auth(), as a user with permission to work in
BIGQUERY_TEST_PROJECT, run bq_test_init() once to perform some setup.
Usage
bq_test_project()
bq_test_init(name = "basedata")
bq_test_dataset(name = random_name(), location = "US")
bq_testable()
bq_authable()
gs_test_bucket()
gs_test_object(name = random_name())Value
bq_test_project() returns the name of a project suitable for use in
testing. bq_test_dataset() creates a temporary dataset whose lifetime is
tied to the lifetime of the object that it returns.
Testing
In tests, bq_test_project() (and hence bq_test_dataset()) will
automatically skip if auth and a test project are not available.
Examples
ds <- bq_test_dataset()
bq_mtcars <- bq_table_upload(bq_table(ds, "mtcars"), mtcars)
# dataset and table will be automatically deleted when ds is GC'd