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Summary

Lifecycle: draftEditUnder review
What this benchmark means
README.md

Public entries: Python and R. Passing coverage requires an installed inventory.

Goal: report what a run did in one table: the run and its outcome, the input it read, the rows it built, each output column, and every check it evaluated, held or violated, in the order the run evaluated it.

Input: subject-level records with an AGE each; one age (214) falls outside the expected 18-to-100 range.

Checks:

  • not_missing on AGE: held, every age is present.
  • range on AGE: violated by the age outside 18-to-100; it is a warning, so the run still succeeds and the run report lists the offending subject.
  • row_count: held, the run produced at least one row.

The run report (adsl-checks.csv) has one row per item, named by its kind (KIND): the run with its outcome (OUTCOME) and output row count, the input with the records and bytes read, the rows built from the records read, one column row per output column with its missing values and longest text, and one check row per check. Every row names the dataset (ARTIFACT), its place in the spec (SPEC_PATH) and its subject (NAME). A check row also carries its optional label (ID), the column it covers (TARGET), the rule it applies (RULE), its SEVERITY, and how many units failed out of how many it examined (COUNT, TOTAL): rows for a row-by-row check and the whole dataset as one unit for row_count. A held check leaves CONDITION and KEYS empty and has empty details ({}).

Note: the report says what was read, built and checked, and for a violated check what broke and for whom: its KEYS list every offending subject, so it can be investigated without stopping the run, and its DETAILS hold the remaining facts.

Inputs

Under review
1 source file

input/dm.csv

Edit
3 rows
input/dm.csv
STUDYIDUSUBJIDAGE
STUDY0130
STUDY01214
STUDY0145

Expected output

Under review
11 expected rows

expected/adsl-checks.csv

Edit
8 rows
expected/adsl-checks.csv
ARTIFACTKINDSPEC_PATHNAMEIDTARGETRULESEVERITYOUTCOMECONDITIONCOUNTTOTALKEYSDETAILS
adsl.csvrunoutput—————succeeded—3——{}
adsl.csvinputinput.DMDM——————3——{"bytes":66,"path":"input/dm.csv","profile":"csv"}
adsl.csvrowsbaseDM——————33—{}
adsl.csvcolumncolumns.USUBJIDUSUBJID——————03—{"max_length":3}
adsl.csvcolumncolumns.AGEAGE——————03—{}
adsl.csvcheckcolumns.AGE.verifications[0].not_missingnot_missing—AGECHECK-5errorheld—03—{}
adsl.csvcheckcolumns.AGE.verifications[1].rangerange—AGECHECK-7warningviolatedrange_failed13[{"USUBJID":"S-2"}]{"column":"AGE"}
adsl.csvcheckverifications[0].row_countrow_count——CHECK-13errorheld—01—{}

expected/adsl.csv

Edit
3 rows
expected/adsl.csv
USUBJIDAGE
30
214
45
Shaded columns are derived— = missing value

Human review and assessment

Your review

2 questions and your comments · View benchmark discussions

Mapping spec

Generated from the benchmark YAML; do not edit by hand

Dataset NameVariable NameVariable LabelTypeCodelist/Controlled TermsCoreComputational MethodOrigin
ADSLUSUBJIDUnique Subject IdentifiercharacterCopy value from DM.USUBJID.Predecessor
ADSLAGEAgenumericCopy value from DM.AGE.Predecessor
VersionDateAuthorDescriptionReviewerSign-off
1.72026-10-20yamaa docs buildRead a specification in the 1.0 surface as its 0.5 counterpart; state that missing values stay missing where a mapping declares no missing handler, and leave out a declared missing answer that restates a handler's default
1.62026-10-17yamaa docs buildDescribe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.52026-10-17yamaa docs buildName collected precision in words instead of letter codes; state imputation fallbacks, minimum source precision, bounds ignored outside the collected period, and invalid text with no handler as an error; describe date and datetime shifts, imputation flag codes, and partial text giving no date part
1.42026-10-15yamaa docs buildState datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
1.32026-09-29yamaa docs buildShow study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.22026-09-29yamaa docs buildClassify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.12026-09-29yamaa docs buildResolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0yamaa docs buildInitial generation from spec.yaml

yamaa code

Public calls generated from benchmark.yaml; results must match the expected output

R

Edit
3 lines
library(yamaa)yamaa_spec("spec.yaml")$run()$output

Python

Edit
3 lines
import yamaayamaa.spec("spec.yaml").run().output