Create oracle-output target data file schema

Usage

create_oracle_output_schema(hub_path, na = c("NA", ""), ignore_files = NULL)

Arguments

hub_path: Either a character string path to a local Modeling Hub directory or an object of class <SubTreeFileSystem> created using functions s3_bucket() or gs_bucket() by providing a string S3 or GCS bucket name or path to a Modeling Hub directory stored in the cloud. For more details consult the Using cloud storage (S3, GCS) in the arrow package. The hub must be fully configured with valid admin.json and tasks.json files within the hub-config directory.
na: A character vector of strings to interpret as missing values. Only applies to CSV files. The default is c("NA", ""). Useful when actual character string "NA" values are used in the data. In such a case, use empty cells to indicate missing values in your files and set na = "".
ignore_files: A character vector of file names (not paths) or file prefixes to ignore when discovering model output files to include in dataset connections. Parent directory names should not be included. Common non-data files such as "README" and ".DS_Store" are ignored automatically, but additional files can be excluded by specifying them here.

Value

an arrow <schema> class object

Examples

#' # Clone example hub
tmp_hub_path <- withr::local_tempdir()
example_hub <- "https://github.com/hubverse-org/example-complex-forecast-hub.git"
gert::git_clone(url = example_hub, path = tmp_hub_path)
# Create target oracle-output schema
create_oracle_output_schema(tmp_hub_path)
#> Schema
#> location: string
#> target_end_date: date32[day]
#> target: string
#> output_type: string
#> output_type_id: string
#> oracle_value: double
#  target oracle-output schema from a cloud hub
s3_hub_path <- s3_bucket("example-complex-forecast-hub")
create_oracle_output_schema(s3_hub_path)
#> Schema
#> location: string
#> target_end_date: date32[day]
#> target: string
#> output_type: string
#> output_type_id: string
#> oracle_value: double