hvtiRdatabuild 0.3.3

• write_analysis_set() builds a set from registered data only, because an analysis set is
  reused by other jobs. It refuses a working read of the study dataset, stops and writes
  nothing.

  • A dataset with no dated version, including one registered before dated versions (a
    manifest entry with no parquet), is refused before it is read and the message names
    hvtiRutilities::update_manifest(). Run it once to convert a legacy registration; sets
    already written read as before.
  • A registered dataset read as working because HVTI_DATA=working is set is refused with a
    message that says to unset HVTI_DATA.
  • In a final render or an Rscript run, hvtiRutilities' own gate may refuse the read first,
    with its own message.
  • Requires hvtiRutilities 1.5.3, the first release that signals a working read.

• The README points analysts to vignette("registered-datasets", package = "hvtiRutilities"),
  which explains dataset registration, version names and which version a job reads. It ships
  with hvtiRutilities 1.5.12 and later.

hvtiRdatabuild 0.3.1

• The test of an analysis set over a dataset registered before dated versions
  now writes the set as a datasets job would. hvtiRutilities' stage gate serves
  a dataset with no dated version only to the console and to datasets or
  descriptive jobs, so the test's non-interactive run was refused. Test-only.

hvtiRdatabuild 0.3.0

• Now requires R 4.4.0 or newer, up from 4.1.0, to match the rest of the
  HVTI family. hvtiR::install() installs the members together, and several
  already required 4.4.0, so on an older R the install failed whatever this
  package declared. Now requires hvtiRutilities 1.5.1.

• The build layer. Three pieces sit between dw_pull() and the analysis
  sets. build_dataset() joins a study's patient-level modules on its cohort
  and keeps repeated-event tables beside the result rather than widening them.
  derive_vars() runs the study's own R code, committed with the study, and
  takes back the data with an updated cohort. A cohort_record, from
  new_cohort_record(), append_cohort_stage() and cohort_summary(), carries
  inclusion, exclusion and attrition history through both, in order. A missing
  inclusion value is an error, not an implicit pass or exclusion. Duplicate
  source identifier columns are kept for audit, patient identifiers stay stable
  across joins, and the print() and str() methods and callback diagnostics
  never show a patient value. vignette("coming-from-sas") walks the build,
  study code and attrition through a synthetic example. dplyr moves from
  Suggests to Imports.

• A stale analysis set no longer stops a draft. read_analysis_set()
  reads a set whose parent or declaration has changed, and signals
  hvtiRutilities_stale_analysis_set with the write_analysis_set() call that
  updates it. A final render (HVTI_TEMPLATE_STRICT set, as
  render_job(final = TRUE) does) still stops, with the same commands. This
  reverses the earlier rule that every stale read stopped; a damaged set still
  stops in every render.

• An analysis set's parent is now the registered version of the built dataset
  when hvtiRutilities registered it as a dated parquet. Rebuilding
  built.sas7bdat without registering it no longer makes every set stale,
  because jobs read nothing new until hvtiRutilities::update_manifest()
  registers it. Sets written before this change name the SAS file as their
  parent, so each is stale once after the study's first update_manifest();
  write_analysis_set() refreshes it. A dataset still registered the old way
  is identified by its source, as before.

• write_analysis_set() and read_analysis_set() skip the line of text that
  hvtiRutilities 1.5.1 writes at the head of a manifest.yaml holding a
  registered dated version. Without this they stopped with "$ operator is
  invalid for atomic vectors" on every study registered from 1.5.1 on.

• write_analysis_set() refuses a set named for a registered dated version,
  such as built_20261008, before writing anything. Its parquet would have
  replaced that version, the registered data every job reads.

• DESCRIPTION now declares the Quarto command line tool in
  SystemRequirements. The vignettes have always needed it to build; the
  field makes that visible to installers and to R CMD check.

• Articles on the pkgdown site put the table of contents on the left and use
  the full width of the window, through pkgdown/extra.css. The installed
  vignettes are unchanged: the Quarto vignette engine renders them in its own
  minimal format, which has no sidebar layout.

hvtiRdatabuild 0.2.4

• Master datasets. Six new functions snapshot, lift and correct the master
  datasets that study builds read. read_master_config() reads a master.yml
  declaring a master's key, alternate keys and parent. snapshot_master()
  freezes its SAS builds as parquet and records which parent release each was
  built from, read from the run's log first. lift_master() loads a snapshot
  into the warehouse behind key and full-parity gates and creates the master's
  view. backfill_corrections(), propose_correction() and
  decide_correction() keep an append-only record of corrections the view
  applies. The bulk functions dry-run by default. See
  vignette("master-datasets"). duckdb and tidyselect join Suggests.

• An analysis set names its own event column. hvtiRutilities 1.4.0 made
  study registration endpoint-neutral: register_data() no longer takes
  event or time, and study_config() no longer carries a study-wide
  cohort. write_analysis_set() had counted n_events and n_censored from
  that cohort, so under 1.4.0 every write failed. A set now declares event:
  (one of its vars) to get both counts, and an expect on either count
  without one stops with a message naming the missing key. A set with no
  event records n alone. A set that relied on the study-wide cohort needs
  the one-line event: added, which also changes its declaration hash, so
  read_analysis_set() asks for one rewrite.
  hvtiRdatabuild now requires hvtiRutilities 1.4.0 or later, since its tests
  and registration fixture use the endpoint-neutral register_data().

• snapshot_oracle() can snapshot a dataset too large for memory. The new
  chunk_rows argument reads the SAS dataset a chunk at a time and writes the
  chunks as row groups of one parquet file. It also records a SHA-256 of the
  SAS source beside the parquet checksum, and writes a .meta.json sidecar
  holding each column's label, SAS format and type, so that metadata survives
  into systems that cannot read R attributes. jsonlite joins Suggests. The
  source checksum now brackets the read, taken before and after; a mismatch
  removes the parquet and stops rather than write a snapshot of a file that
  changed underneath it.

hvtiRdatabuild 0.2.3

• New publish_dataset(). A programmer can publish a mutable clinical-data
  draft as an immutable dated release. Publication preserves the draft bytes,
  verifies that the staged copy is readable, records its checksum and shape in
  dataset-catalog.yml, and serializes concurrent publishers with a catalog
  lock. Same-day corrections receive revision filenames; retrying identical
  bytes is idempotent, including recovery of a file moved before a failed
  catalog write.

• New withdraw_dataset_release(). Withdrawal records a reason and an
  optional replacement in the catalog without changing or deleting the
  published file. The package now requires hvtiRutilities 1.3.1, whose study
  workflow discovers, reviews, and explicitly adopts these releases.

hvtiRdatabuild 0.2.2

• Documentation no longer points dw_pull() users at a
  building-a-study-dataset vignette that does not exist, and the SAS migration
  guide no longer lists the shipped dw_connect() and dw_pull() as future
  work. Prose across the README, vignette and reference pages was tightened.

• The SAS migration guide now treats bd.SAStoR.sas outputs as general
  downstream data contracts rather than exports owned by their first consumer.
  It shows how the final selection becomes a shared analysis set while variable
  derivation remains in the build layer.

• Analysis-set declarations now reject duplicate variables and require every
  expected row/event count to be one non-negative whole number. This prevents
  duplicate parquet columns from being silently renamed and fractional counts
  from matching after integer truncation.

• Analysis sets resolve their outputs through the study's logical datasets
  directory, preserving numbered new studies and adopted legacy layouts.