Inherited Input Types

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Summary

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README.md

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

Goal: demonstrate a study adding to the demographics input it inherits from a shared level, keeping the shared file and field type, to derive AGEGR1 and HTGR1.

Input: two spec files, read root-first:

spec_shared.yaml names the demographics file once, stores AGE as an integer, and groups subjects by age;
spec_study.yaml is the entry: it names the shared level as its parent, stores the height it collects as a number, groups subjects by height, and declares the complete output.

Variables:

AGEGR1 is <65 or >=65 from the collected age; a subject aged exactly 65 falls in the older group;
HTGR1 is <170 or >=170 from the collected height in centimetres; a height of exactly 170 falls in the taller group.

Note: the study's entry for the demographics input joins the shared one detail by detail: the file location and the age type come from the shared level, and the height type from the study. Neither level restates what the other declares, and both groupings read numbers.

YAML specification

2 spec files

spec_shared.yaml
Edit31 lines
1yamaa: "1.0"2type: spec3domain: ADSL4keys: [USUBJID]56# Every study reads its demographics file under this name, with AGE stored as7# an integer.8input:9  DM:10    path: input/dm.csv11    types:12      AGE: int13base: DM1415columns:16  - name: USUBJID17    type: str18    label: Unique Subject Identifier19    derivation: DM.USUBJID2021  - name: AGEGR122    type: str23    label: Pooled Age Group 124    derivation:25      cut:26        source: DM.AGE27        breaks: [65]28        labels: ['<65', '>=65']2930metadata:31  scope: shared
spec_study.yaml
Edit28 lines
1yamaa: "1.0"2type: spec3model: ADaM4parent: spec_shared.yaml56# Merged into the inherited DM input: the study adds the type of the field7# only it collects, and keeps the inherited path and the inherited AGE type.8input:9  DM:10    types:11      HEIGHTCM: float1213output:14  path: adsl.csv15  columns: [USUBJID, AGEGR1, HTGR1]1617columns:18  - name: HTGR119    type: str20    label: Pooled Height Group 121    derivation:22      cut:23        source: DM.HEIGHTCM24        breaks: [170]25        labels: ['<170', '>=170']2627metadata:28  scope: study

Inputs

Under review1 source file

input/dm.csv

Edit3 rows

input/dm.csv
USUBJID	AGE	HEIGHTCM
	34	172
	65	160
	71	181

Expected output

Under review3 expected rows

expected/adsl.csv

Edit3 rows

expected/adsl.csv
USUBJID	AGEGR1	HTGR1
	<65	>=170
	>=65	<170
	>=65	>=170

Shaded columns are derived— = missing value

Human review and assessment

Variable Name	Variable Label	Type	Length	Controlled Terms or Format	Origin	Core	Conversion Definition	Variable Type	Variable Order	Comments for Define
HTGR1	Pooled Height Group 1	Char			Derived		Band DM.HEIGHTCM at 170 into "<170" and ">=170", intervals closed on the left.	SDTM	1

Version	Date	Author	Description
1.7	2026-10-20	yamaa docs build	Read 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
1.6	2026-10-17	yamaa docs build	Describe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.5	2026-10-17	yamaa docs build	Name 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
1.4	2026-10-15	yamaa docs build	State datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
1.3	2026-09-29	yamaa docs build	Show study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.2	2026-09-29	yamaa docs build	Classify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.1	2026-09-29	yamaa docs build	Resolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0		yamaa docs build	Initial generation from spec.yaml

R

Edit3 lines

1library(yamaa)23yamaa_spec("spec_study.yaml")$run()$output

Python

Edit3 lines

1import yamaa23yamaa.spec("spec_study.yaml").run().output

input/dm.csv

expected/adsl.csv

Your review

Mapping spec

yamaa code

R

Python