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write_dependency_graph() /
read_dependency_graph() and write_split_spec()
/ read_split_spec(). The on-disk format is documented under
?write_dependency_graph and ?write_split_spec,
carries a schema_version field, and round-trips
NA values faithfully. This makes splitGraph
objects portable across R sessions and across language boundaries
(Python, Julia, CLI tools — anything that can read JSON). Requires
jsonlite (added to Suggests); a helpful error
is raised if it is not installed.adapter-cookbook, walks through three
small adapter patterns: a base-R leave-one-group-out adapter (executed),
a grouped-CV adapter built on rsample::group_vfold_cv()
(illustrative), and an ordered-evaluation adapter built on
rsample::rolling_origin() (illustrative). It also shows the
JSON cross-language handoff path.validate_graph() and validate_depgraph()
now accept a documented validation_overrides argument.
Currently supported override: allow_multi_subject_samples
(default FALSE); when TRUE, samples linked to
multiple subjects are not flagged by the semantic validator and
derive_split_constraints(mode = "subject") keeps the first
listed assignment instead of erroring. The override mechanism is now
first-class and merges into any graph-level override for the duration of
the call only.derive_split_constraints(mode = "subject") honors
allow_multi_subject_samples consistently with
validate_graph(). When the override is active and ambiguity
exists, the choice is recorded in metadata$warnings so it
is not invisible.query_paths() now applies a finite default safety cap
on max_length (8 edges) so that
igraph::all_simple_paths() cannot blow up on dense graphs.
Pass max_length = Inf to opt out and search exhaustively,
or any non-negative integer for an explicit cap. Negative values and
non-numeric inputs are rejected with a clear error.build_dependency_graph() returns a more useful error
when edge endpoints don’t match any node ID and the mismatch looks like
a prefix problem (e.g. edges built with from_prefix = TRUE
but nodes built with prefix = FALSE). The error now points
at the likely cause.graph_from_metadata() warns when it constructs
Outcome nodes from a numeric outcome_value
column (which produces outcome:0 / outcome:1
nodes that are usually not what the user wants). To silence the warning,
pass outcome_id (character class label) instead, or coerce
outcome_value to character first.schema_version is now explicitly
decoupled from the package version. Bumping the package will not bump
the schema; only an explicit, documented schema change should.These remain functional in 0.2.0 but emit .Deprecated()
warnings and are scheduled for removal in a future release. Use the
canonical names instead:
validate_graph(checks = …) → use
levels = … and severities = ….build_depgraph() → use
build_dependency_graph().validate_depgraph() → use
validate_graph().new_depgraph_nodes() → use
graph_node_set().new_depgraph_edges() → use
graph_edge_set().new_depgraph() → use
dependency_graph().outcome_id
(character) in their quick-start example instead of numeric
outcome_value, matching the new warning behavior.validation_overrides parameter and the
allow_multi_subject_samples key are now documented on
?build_dependency_graph /
?validate_graph.Initial public release. Highlights:
graph_from_metadata(), or from explicit node and edge
tables via create_nodes() / create_edges() /
build_dependency_graph().validate_graph()), typed query helpers, and projected
sample-dependency detection.derive_split_constraints()) for subject,
batch, study, time, and
composite modes, translated into a stable, tool-agnostic
split_spec via as_split_spec() with preflight
validation and leakage-risk summaries.plot() method for dependency_graph with a
typed, layered layout, per-type node colors, and an auto-generated
node-type legend.splitGraph emits split_spec objects
without runtime dependencies on downstream tooling. Adapters are
expected to live in consumer packages (e.g. packages built on top of
rsample) so that splitGraph itself stays
neutral.See the README for a full feature overview and a runnable Quick Start.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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