EDIutils (version 1.0.3)

read_data_entity: Read data entity

Description

Read data entity

Usage

read_data_entity(packageId, entityId, env = "production")

Value

(raw) Raw bytes (i.e. application/octet-stream) to be parsed by a reader function appropriate for the data type

Arguments

packageId

(character) Data package identifier

entityId

(character) Data entity identifier

env

(character) Repository environment. Can be: "production", "staging", or "development".

See Also

Other Accessing: read_data_entity_checksum(), read_data_entity_names(), read_data_entity_name(), read_data_entity_resource_metadata(), read_data_entity_sizes(), read_data_entity_size(), read_data_package_archive(), read_data_package_citation(), read_data_package_doi(), read_data_package_error(), read_data_package_from_doi(), read_data_package_report_checksum(), read_data_package_report_resource_metadata(), read_data_package_report_summary(), read_data_package_report(), read_data_package_resource_metadata(), read_data_package(), read_evaluate_report_summary(), read_evaluate_report(), read_metadata_checksum(), read_metadata_dublin_core(), read_metadata_entity(), read_metadata_format(), read_metadata_resource_metadata(), read_metadata()

Examples

if (FALSE) {

# Read names and IDs of data entities in package "edi.1047.1"
res <- read_data_entity_names(packageId = "edi.1047.1")
res
#>                           entityId                entityName
#> 1 3abac5f99ecc1585879178a355176f6d        Environmentals.csv
#> 2 f6bfa89b48ced8292840e53567cbf0c8               ByCatch.csv
#> 3 c75642ddccb4301327b4b1a86bdee906               Chinook.csv
#> 4 2c9ee86cc3f3ffc729c5f18bfe0a2a1d             Steelhead.csv
#> 5 785690848dd20f4910637250cdc96819 TrapEfficiencyRelease.csv
#> 6 58b9000439a5671ea7fe13212e889ba5 TrapEfficiencySummary.csv
#> 7 86e61c1a501b7dcf0040d10e009bfd87        TrapOperations.csv

# Read raw bytes of the 3rd data entity
raw <- read_data_entity(packageId = "edi.1047.1", entityId = res$entityId[3])
head(raw)
#> [1] ef bb bf 44 61 74

# Parse with .csv reader
data <- readr::read_csv(file = raw)
data
#> # A tibble: 105,325 x 20
#> Date   trapVisitID subSiteName  catchRawID releaseID commonName     n
#>                                   
#>   1 1/8/2~         330 North Chann~      32409         0 Chinook s~     1
#> 2 1/8/2~         330 North Chann~      32412         0 Chinook s~     1
#> 3 1/8/2~         330 North Chann~      32410         0 Chinook s~     1
#> 4 1/8/2~         330 North Chann~      32408         0 Chinook s~     1
#> 5 1/8/2~         330 North Chann~      32406         0 Chinook s~     1
#> 6 1/8/2~         322 North Chann~      31958         0 Chinook s~     1
#> 7 1/8/2~         322 North Chann~      31975         0 Chinook s~     1
#> 8 1/8/2~         322 North Chann~      31974         0 Chinook s~     1
#> 9 1/8/2~         322 North Chann~      31973         0 Chinook s~     1
#> 10 1/8/2~         322 North Chann~      31972         0 Chinook s~     1
#> # ... with 105,315 more rows, and 13 more variables:
#> #   atCaptureRun , finalRun , finalRunMethod ,
#> #   lifeStage , forkLength , weight , mort ,
#> #   fishOrigin , markType , CatchRaw.comments ,
#> #   specimenTypeID , physicalSpecimenCode ,
#> #   Specimen.comments 
}