dansk-register
A platform for epidemiological studies on the Danish national registers, and the study pipelines built on it.
The package contains no data. It is the code that reads a register delivery inside a secure research environment, builds cohorts and outcomes from it, and estimates and reports the results.
What is in it
| Package | Role |
|---|---|
dansk_register |
The reusable platform: register catalog and I/O, the staged-pipeline runner, matching, estimation, disclosure control, figure styling |
societal_costs |
Study II: societal costs of severe chronic disease in childhood |
edu_labour_trajectories |
Study III: educational and labour-market trajectories from age 18 |
The dependency direction is one way and enforced by a test: the platform never
imports a study, and studies never import each other. Code that turns out to be
general is lifted into dansk_register rather than shared sideways.
Layout
This directory is the private half of the PhD: the register platform, the three
study pipelines, and the crates they call. Public methods crates are
dependencies, not subdirectories. See ../admin/plans/code_consolidation.md for
why, and for the migration that produced this shape on 26 August 2026.
src/- the Python packages above plusparental_income(Study I) andregister_studies(the orchestration CLI), andsrc/rust/for the pyo3 extension. All of it ships in one maturin wheel; the platform is not separately installable.crates/- the Rust the studies call.register_runner(Parquet in, estimators out),cost_engine,cpi_deflateandperson_years(the three bridge CLIs),sas7bdat-writer(the only thing that writes the format the Danish register hosts deliver),register-delivery(the synthetic delivery the end-to-end tests run on), andsporskifte(track changes for Typst).checkouts/- gitignored reading copies of the public repos, cloned byjust checkouts. Never a build input.docs/- implementation documents only. Science goes to../studies/.
Six of the seven crates are members of one cargo workspace with one
Cargo.lock. sporskifte is not: it is a workspace of its own, and flattening
it would put a vello/wgpu graphics stack and three vendored pdf-rs forks into
this lockfile, which every --workspace command in the gate would then compile.
Dependencies that live elsewhere
| Crate | Source | Pinned by |
|---|---|---|
cohort_matching |
crates.io | 0.2.0 + Cargo.lock checksum |
semicontinuous_models |
crates.io | 0.2.0 + Cargo.lock checksum |
sas7bdat |
crates.io | 0.8 + Cargo.lock checksum |
scd |
git, main |
revision in Cargo.lock |
did_methods |
git, main |
revision in Cargo.lock |
sas7bdat-polars |
PyPI | ==0.9.2, exact by design |
The rule that produced this table: public code is consumed by version. If a
fix is needed in one of these, fix it upstream, release it, bump the pin. Never
vendor it, never path-depend across the boundary. cohort_matching was vendored
for a week in August 2026 and the copy cost more than it bought.
did_methods stays a git pin because its honest feature builds HiGHS from
C++, which is more than a crates.io release is currently worth. scd could
follow the other three to a version pin; 0.1.3 is published.
Install
pip install dansk-register-platform # everything, all three studies
pip install "dansk-register-platform[study2]" # names a study; installs the same files
pip install "dansk-register-platform[all]" # all three, explicitly
The distribution was renamed from dansk-register at 0.7.0, to get past the
analysis server mirror's 24-hour cache. The import packages are deliberately
unchanged, so nothing in this codebase or on the server imports anything
different; only pip install names the new one. The old name still resolves,
to a distribution that stopped being updated before the rename.
The estimators are written in polars and validated against R, so the pipeline
carries no numeric stack of its own. matplotlib is a base dependency because
numpy arrived on every real run anyway; what keeps the boundary real is that its
imports live under a figures package and a contract test fails the build if one
escapes into an estimator. Without a renderer every result is still produced and
the figure stage records that it could not draw.
repair is the only optional dependency: pyarrow, for register-repair-utf8
alone. Install it with pip install 'dansk-register-platform[repair]'. The same
kind of contract test keeps pyarrow out of everything else.
Commands
edu-labour --list-profiles # what each profile runs
edu-labour-preflight --raw-root PATH # what a delivery contains
edu-labour --output-dir RUN --profile production \
--raw-root PATH --allow-expensive-stages --resume
edu-labour-figures --bundle RUN/outputs/export --out figures
societal-costs --capability PATH # what this study needs vs. what a delivery has
societal-costs --output-dir RUN --profile production \
--raw-root PATH --allow-expensive-stages --diagnostics
societal-costs secondary_sensitivity --output-dir RUN # the arm no profile runs
register-repair-utf8 PATH --report utf8_scan.csv # find invalid UTF-8 in converted Parquet
register-repair-utf8 PATH --fix --report utf8_fix.csv
--allow-expensive-stages is required for production: matching scans the
whole delivery, and without the flag the runner refuses rather than silently
starting a multi-hour match. --profile production runs 19 stages but not
secondary_sensitivity, the analyse-only sensitivity and subgroup arm, which
reads a completed run and writes into a subdirectory of it.
register-repair-utf8 needs the repair extra and says so if it is missing.
Add --dry-run to any edu-labour invocation to resolve the plan and settings
without touching data.
Design notes
Stages talk through files. Every stage writes named artifacts into a run
directory and reads its inputs from there, so any stage can be re-run alone
against a previous run's outputs, and --resume can skip what is already done.
Estimators are written against polars. Aalen-Johansen, Fine-Gray, Cox and the multi-state occupancy are implemented directly rather than taken from a modelling library, and each is validated against reference values from R with those values checked into the tests. That keeps the numbers checkable line by line and avoids a dependency that may not install in an offline environment.
Disclosure control is part of the pipeline. Results leave the secure environment as a bundle of CSV tables with small cells suppressed and the estimates resting on them blanked. Figures are rendered from that bundle rather than from the raw artifacts, so a figure cannot show what the table beside it was not cleared to show.
What this covers, and what it does not
Secure-environment research is usually described with the Five Safes, and it is worth saying plainly which of the five a piece of software can touch at all.
| Safe projects | Your approval. Nothing here. |
| Safe people | Your institution's authorisation. Nothing here. |
| Safe settings | The host's environment — Statistics Denmark, Sundhedsdatastyrelsen. Nothing here. |
| Safe data | Partly here. Person identifiers are replaced with a study-local key, and an export is refused outright if a CPR-shaped value reaches it. |
| Safe outputs | Partly here. Small cells are suppressed, dependent estimates blanked, file types and sizes checked against the transfer rules, and every bundle carries a manifest saying what was done and what was not. |
"Partly" is the operative word in both rows. The output checks are cell-by-cell
and cannot see a small number recovered by differencing across tables; each
bundle's MANIFEST.txt says so in its own text. Running this framework is not a
substitute for your host's output review, and it does not make an
unapproved analysis approved.
Working on it
just lists everything. The gates, which are what CI runs:
just lint # both languages: ruff + three type checkers, rustfmt +
# clippy, and the three supply-chain audits
just rust-test # 207 Rust tests across the three crates, via nextest
just test # 2,953 Python tests, parallel
just gate # all three, in CI's order
and the loops:
just test-fast # 2,703 of them in ~15 s; everything but the real pipelines
just test-e2e # the 190 that run a real pipeline over a generated delivery
just types # ty + pyrefly: 0.7 s from cold, against mypy's 6 s
just typos # spell-check; not a gate, see _typos.toml
just mutants # would the tests have noticed? Slow, not a gate
prek install # optional: run the formatters before each commit
Two things worth knowing before the first full run:
The generated delivery is cached, not rebuilt. The end-to-end tier runs
against an 854 MB synthetic delivery, and it is byte-reproducible from its
inputs, so it is kept under target/test-deliveries/ keyed by a hash of the
generator, both catalogs and the parameters. It is built once and shared by
every xdist worker and every later run. REGISTER_DELIVERY_CACHE= (empty) turns
that off. See tests/full_delivery.py for why it is a cache rather than the
usual filelock recipe.
One pytest at a time. Overlapping full runs is what filled the disk on
25 August 2026. The suite now refuses to start the end-to-end tier below 8 GB
free, and says how to reclaim; REGISTER_STUDIES_MIN_FREE_GB=0 overrides it.
Status
Research code, developed alongside the studies it implements. The public API is not stable.
Documentation
docs/README.md is the index, and it says which document is a
standing contract and which is a finished pass kept because the code cites it.
Two worth naming: docs/open_questions.md is the
open-items register, and docs/REUSABILITY_ANALYSIS.md
is why the platform is shaped the way it is.
Knowledge rather than implementation — register semantics, methodology, study
protocols — lives in the PhD store, not here. docs/README.md states the rule
that decides which is which.
Licence
MIT. See LICENSE.
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