dataganger 0.6.1

CRAN resubmission changes requested on 2026-07-10.

• DESCRIPTION now quotes the package name 'shiny' correctly in the Description field.
• read_input() examples are now self-contained, executable, and no longer use commented-out code.
• export_synthetic(), make_agent_bundle(), and export_diagnostic_package() examples now write only to temporary paths and no longer use \dontrun{}.
• Audited exported write functions, examples, tests, and vignettes for home-filespace writes; package examples now stay within tempfile() / tempdir().

dataganger 0.6.0

One minimal export bundle, a Configure page with no silent defaults, and a package-wide audit pass: privacy fixes, an honest engine story, honest privacy wording, and a lighter dependency footprint.

Privacy fixes

• k-anonymity now runs before column renaming. Previously, with name_strategy = "generic", generic renaming ran first and recorded the name map before enforce_kanon() dropped direct identifiers and applied suppression — so bundles could under-protect. Both engine paths now enforce k-anonymity first. Bundles generated with generic names on earlier versions may be under-protected; regenerate them.
• The manifest and the privacy report now agree on a single exact-row-match number: export_synthetic() uses the same roles-derived exclusion rule as privacy_check_post().
• Seeded synthesis is fully deterministic: decimal_places() samples long columns with a deterministic stride instead of sample(), removing an RNG side effect.
• The app’s theme no longer references Google Fonts at all (bslib::font_google() replaced with plain family strings served from the packaged self-hosted files); the no-network source guard now also scans inst/app/.

Bundle & agent skill

• Export bundles use one minimal layout: synthetic_data.csv at the root, human/ (human.md with the privacy report folded in, plus optional comparison_report.html), and agent/ (recipe.yaml = combined spec + roles, AGENT.md, manifest.json). data_dictionary.csv, load_data.R, analysis.qmd, ai-readme.md, privacy_report.txt, and the separate spec.yaml/roles.yaml are gone. CLI synthesize gains --recipe <recipe.yaml>; --spec/--roles remain supported. compact and include_dictionary are deprecated no-ops.
• export_synthetic() honors its code_readiness argument: when supplied, the bundle gains agent/code_readiness_report.json; make_agent_bundle() computes it automatically, so every agent bundle now ships the structural-compatibility report.
• Both shipped skills (AGENT.md in every bundle and using-dataganger-bundles) rewritten to the minimal bundle contract.

Engine

• "auto" is a real engine alias in synth_spec(), synthesize_data(), the CLI (--engine <auto|internal|synthpop>), and spec YAML. An explicit "auto" behaves exactly like leaving the engine unset: the engine is derived from the objective and dataganger.disable_synthpop is respected.
• The misleading engine_required spec field is retired; spec printing reports the explicit engine or auto (derived from objective).

App (Shiny)

• Compare now separates Univariate and Bivariate views. The Bivariate view uses an X-by-synthetic interaction test to show whether predictor-outcome relationships changed, with outcome-specific effect sizes and p-value fidelity colors.
• Exported comparison reports now include the relationship-interaction table, using data-column order to define predictor then outcome.
• Synthesis controls are folded into collapsed Advanced settings, keeping the generation review focused on the effective configuration.
• Generation guidance now invites users to review, generate, or go back to adjust settings, and the data panel automatically previews each newly generated synthetic dataset.
• When synthpop is unavailable, the upload attestation recommends installing it for correlation-aware synthesis.
• Configure has no silent defaults: Q1 (Points to a person?) and Q2 (Sensitive?) start blank for every column — auto-detected values no longer pre-select — and generation is gated until every column has an explicit answer to both questions. Explicit UI answers are tracked separately (user_identifies / user_sensitive) so CLI synthesis is unaffected.
• The upload fail-safe flags only direct-identifier candidates (ID patterns / free text), no longer sensitive-named columns such as income; flagged columns get a “potential identifier” pill and semantically-coloured actions.
• Categorical comparisons are now inference-aware like numeric ones: colored by a chi-square/Fisher distributional p-value with TVD as the displayed effect size; the SMD definition is shown on the effect column.
• Assorted Configure/Compare/Generate polish: bottom Confirm-and-Continue, calmer attestation wording (with a disable-internet note), preserve-panel highlight, per-question help tied to table columns, and a generation fidelity recap.

Docs

• Sensitive-column wording is honest and consistent everywhere: quasi-identifying columns are “grouped with k-anonymity so no rare combination survives”; sensitive non-identifying columns are “recreated from its distribution; exact values are not copied — attribute-level protection is not yet applied”. The former “protected from linkage” claim is gone.
• Engine documentation matches reality (demo → internal; development → synthpop when installed; analytics → synthpop + risk acknowledgement).
• detect_roles() documents the two-axis columns; assorted roxygen and vignette corrections; the startup message is reduced to version + run_app().

Dependencies & internals

• purrr, tidyr, and vctrs dropped from Imports (unused); plotly moved to Suggests with an install gate in the Compare module.
• check_code_readiness() now documents and reports that haven_labelled → character is the expected round-trip for now.
• Internal hygiene: unified ID-name regex, NULL/NA-safe role lookups (a roles object missing a column no longer errors), helper relocations, and dead-code removal.

dataganger 0.5.0

Privacy gating, UI/CLI parity, an agent skill, and a provable no-network guarantee.

• Comparison stats are now inference-aware for numeric variables: the Compare view shows mean SMD, SD ratio, and median standardized difference, each coloured by their t/F/Wilcoxon p-value bands; min/max remain value-only.
• UI export bundles now include spec.yaml and roles.yaml, and CLI synthesize --roles can reuse the full role matrix so UI and CLI runs reproduce byte-identical output with the same seed.
• The app now opens with a hard no-direct-identifiers attestation gate, then runs an early assistive fail-safe immediately after upload to flag possible direct identifiers before Objective / Configure. Once attested, Configure’s first question collapses to none / combination. The two questions are framed as the remaining risks after direct identifiers: linkage (combination) and sensitivity.
• Added an agents-only packaged SKILL.md plus dataganger skill [--out <file>] so an AI can drive the package to generate synthetic data without ever reading the real data; fixed ai-readme.md so dropped columns are not listed as NA (NA).
• No-network guarantee: web fonts are now self-hosted (no Google Fonts CDN), so the app makes no external requests; report_issue() prints a copy-paste GitHub issue instead of opening a browser (the Shiny button shows a copyable modal). A shipped runtime trap test and source guard prove the package makes no network calls, and a Linux unshare -rn CI job runs the suite with no network at all.
• New vignette("privacy-and-ai-workflow") documents the privacy gating ladder, the two ways to use the package with AI, and the no-network guarantee.

dataganger 0.4.0

Configure redesign around two intrinsic privacy questions.

• The Configure step now classifies each column by answering two independent questions — does it point to a person (identifies: none / combination / direct) and is it sensitive (sensitive) — and derives the treatment rather than asking the user to pick it. The two questions are shown prominently above the per-column table.
• k-anonymity membership now reads both axes, so a column that is both identifying-in-combination and sensitive is covered. Numeric quasi-identifiers are no longer coarsened into NA bins.
• Each column row has an Action override column exposing the Action (synthesize / pass through / drop) and data-type overrides directly.
• The Generate step now shows a per-column review table (points to a person?, sensitive?, action, and a plain-English outcome) so choices can be verified before generating.
• Objective selection uses a single Protection meter, makes development the default objective, and rewrites the per-objective detail panel around consistent dimensions for use, values, relationships, identifiers, and sensitive / rare data.
• Synthesis Settings labels are more human-readable, with matching synth_spec() documentation for the current settings surface.
• The per-column data preview includes a filter so you can inspect one variable at a time while reviewing the Configure step.
• export_synthetic(compact = ) supports two bundle variants: the compact app download and the full CLI / agent bundle. # dataganger 0.3.5

Generation, comparison, and export clarity pass:

• Generate page now shows a read-only “Column decisions” snapshot (the Configure table as final, non-editable values) so choices can be reviewed before generating.
• New report_issue() helper plus an in-app Report a problem button open a pre-filled GitHub issue with environment details, without sending anything automatically.
• The engine recap resolves to the engine actually used (e.g. synthpop (auto)) after generation, instead of always showing auto.
• The Regenerate button is disabled until the first generation, so it no longer duplicates Generate on the initial visit.
• Exact-row-match count moved into the result stats; the redundant verbatim Result box was removed.
• Compare page treats geography columns as categorical, so they get an original-vs-synthetic comparison instead of being skipped.
• Export page gains a generation summary: original rows/columns, how many columns were synthesized, passed through, and dropped, and the final synthetic dimensions.
• Internal: the cancellable-synthesis subprocess no longer uses a ::: self-reference (clearing an R CMD check NOTE); spelling WORDLIST expanded.

dataganger 0.3.4

Configure page clarity pass:

• Integer-valued columns now display without spurious decimals (e.g. 127, not 127.00) by detecting whole-valued numerics, not just R integer storage.
• The column-roles table renames “Simulation” to Action, folds the recommendation inline into the TYPE control (... (recommended)), drops the redundant recommended_role column, and adds a per-row info tooltip with a plain-English reason and the storage type.
• Setting a column’s Action to Drop or Pass through now greys out and disables its TYPE and DISCLOSURE selectors and no longer blocks generation; pass-through columns carry a “real values - verify before sharing” note.
• Disclosure-detection reason strings rewritten in plain English.
• Collapsible help now uses an obvious +/- affordance.

dataganger 0.3.3

• pkgload removed from Suggests (uses .__DEVTOOLS__ namespace check directly).
• CRAN-readiness: cran-comments.md refreshed with accurate 0/0/2 NOTE explanations.
• Added pkgdown site generation via GitHub Actions (_pkgdown.yml + workflows).
• Planning artifacts (docs/superpowers/, todo.md) migrated out of the package root.

dataganger 0.3.2

Disclosure roles

• detect_roles() is now conservative: it only auto-assigns a disclosure role when confident (a clear direct identifier, or a known-sensitive column name). All other columns are left unselected rather than defaulted to quasi-identifier. This fixes the root cause of the 100%-NA synthetic output: measures, counts, dates, and low-cardinality categoricals are no longer silently treated as quasi-identifiers.
• The Configure page now requires an explicit disclosure role for every column before generating. A live counter shows how many are still unselected. None is a valid explicit choice; empty is not.
• k-anonymity fires only on columns the user marks as quasi-identifiers. The max_suppress_frac feasibility backstop is retained as defense-in-depth.
• CLI: spec YAML accepts a disclosure_roles: mapping (column -> role) so disclosure decisions are reproducible from the command line.

dataganger 0.3.1

• Bug fix — CUSUM hang (Bug 5): Synthesis no longer hangs on datasets with character-stored date columns (e.g. “Jun 8, 2019”) or other high-cardinality character columns. The root cause was two-fold: (1) character date strings were classified “unknown” and passed to synthpop as a 2000+-level factor, causing CART to enumerate billions of split candidates; (2) even moderate-cardinality character columns (>20 distinct values) used as CART predictors trigger the same 2^(k-1) blowup at k=34. Fix: detect_roles() now detects date strings (ISO, “Mon DD YYYY”, MM/DD/YY) via regex and classifies them as “date”; and a new synthpop_bridge_cols() function excludes any character column with >20 distinct values from synthpop’s CART, synthesizes it independently via the marginal engine, and stitches it back into the output in the original column order. Generation on the CUSUM test file (41 k rows, 14 columns) now completes in under 10 seconds at both 50-row and 5000-row target sizes.

• P1 — Configure busy indicator: the Upload page now shows a “Profiling data…” / “Detecting column roles…” progress bar while the app analyses the uploaded file, so users know the app is working rather than frozen.

• P2 — Row count first: the Row count (n) input is now the first item in the Configure advanced-settings panel.

• P3 — Role-reactive row suggestion: suggest_min_rows() gains a data parameter; when called with data and roles, it recomputes the coverage estimate over only the columns that are still being synthesized. Dropping an ID or excluded column now immediately lowers the suggested row count on the Configure page.

• P4 — Case IDs render as character: columns detected as ID candidates are coerced to character in the data-panel preview, so a numeric case ID displays as “1078541” instead of “1,078,541.00”.

• P5 — Column summary stats: the Configure page now shows a per-column summary section below the synthesis settings. Continuous columns get a min / Q1 / median / Q3 / max / mean / SD table; categorical columns get a top-5 frequency table with counts and percentages.

• P6 — Generation progress bar + timer: while synthesis is running, the Generation page displays a MM:SS elapsed-time counter and an animated progress bar. Both update every second.

dataganger 0.3.0

• Cancellable background synthesis: the Shiny Generation step now runs the synthesize -> compare -> privacy pipeline in a background process (via callr), so the app stays responsive and a Cancel button can stop a long or stuck run. Falls back to synchronous in-process generation when callr is unavailable or the package is dev-loaded. The dataganger.synthesis_async option forces the deterministic synchronous path for tests and CI.

• Coverage-based row-count suggestion: profile_data() now carries cross-column coverage (distinct joint combinations of categorical columns plus the largest per-column level count), and the new suggest_min_rows() function turns that into a sufficient synthetic row count - capped at 5000, floored at the largest level count, and never above the original. The Configuration row-count slider pre-fills with the suggestion, shows an inline hint, and warns when set below the coverage floor. The Upload step shows a coverage-summary card.

• Diagnostics for long-running synthesis: dg_log / dg_timeit emit per-phase progress to the R console when options(dataganger.verbose = TRUE), and check_cancel() polls options(dataganger.cancel) at column boundaries for cooperative cancellation. .onAttach() prints a startup hint with the package version and how to launch the app and CLI.

• Free-text detection now head-samples to 1000 rows, bounding a hot path that could slow the transition into Configure on wide or long-string data.

• synthesize_marginal() trusts the detected role instead of recomputing the free-text heuristic, removing a redundant pass over character columns.

• The Comparison step no longer shows a stale full table on first transition: the first comparable variable renders correctly without needing a click.

• The Configuration step shows inline help for each disclosure role (None, Direct identifier, Quasi-identifier, Sensitive) with a short example.

• callr and pkgload added to Suggests.

dataganger 0.2.2

• The Column Roles step now shows a non-blocking notice when the uploaded data looks like an aggregated counts table rather than individual records, since disclosure control assumes individual-level microdata.

• New option dataganger.disable_synthpop: set options(dataganger.disable_synthpop = TRUE) to steer objective-derived synthesis onto the internal engine even when synthpop is installed. Intended for environments where a synthpop synthesis is undesirable or can hang unattended (for example continuous integration). An explicit engine = "synthpop" request is still honoured.

dataganger 0.2.1

• Shiny app interface refinements: the Objective step shows each purpose’s details on selection and uses consistent “more bars = stronger” meters, including an Anonymity meter for resistance to re-identification. Each synthesis engine (auto, internal, synthpop) now has a plain-language explainer. The Generation step shows a configuration recap (including advanced settings) with an “Adjust settings” shortcut back to Configuration. The Comparison step has a wrapping variable grid and a clearer original vs. synthetic explainer. The Export step downloads a single bundle (synthetic data as CSV, documentation, comparison report, and an analysis notebook), with an optional save-to-folder for sessions run locally.

• Every bundle now includes analysis.qmd, a Quarto report with runnable R code and reference Python code to read both the original and synthetic data and compare them (summary statistics, distribution plots, and DataGangeR’s fidelity metrics).

• The Shiny synthesis spec exposes an engine selector (auto / internal / synthpop) with an inline note on whether synthpop is installed.

• Ship an agent skill (inst/skills/using-dataganger-bundles/) describing how AI agents should consume a bundle: never access the real data, ask the human for a go-ahead before touching the synthetic data, and where to save work.

• Fixed interpolate() so bundle helper files (e.g. load_data.R) render their templates instead of shipping literal placeholders.

• DataGangeR now routes relationship-preserving objectives to the optional synthpop engine when installed. Please cite: Nowok B, Raab GM, Dibben C (2016). “synthpop: Bespoke Creation of Synthetic Data in R.” Journal of Statistical Software, 74(11), 1-26. doi:10.18637/jss.v074.i11

• Initial CRAN-ready scaffold.