Serializes the recipe (the weighting method, not the data) to a human-readable
YAML file: the base-weight column, the non-probability flag, and every step's id,
type and parameters. The file is a versionable metadata artifact you can review
in a pull request, archive next to the quality report, or reference from a
metadata system. Read it back with read_recipe().
Arguments
- object
a
weighting_spec(or a prepped one; only the recipe is written, never the weights or the data).- file
path to the
.yml/.yamlfile to write.- timestamp
whether to record the write time (UTC) in the file. Default
TRUE; setFALSEfor byte-identical output across writes of the same recipe (cleaner version-control diffs).
Details
Formulas and captured column expressions are stored as text. A reference_sample()
is stored as a descriptor only (its microdata is not metadata), so a step that
calibrates or pseudo-weights against a reference must be given that reference
again when the recipe is reconstructed. Small control-totals tables (for example
a tidy poststratification total) are serialized in full; a data frame larger than
10,000 rows is treated as microdata and rejected (route it through
reference_sample()).
A recipe is portable only if its captured expressions reference columns of the
data (for example respondent = responded). An expression that referenced
objects from your R session (say respondent = id %in% ids_resp) is stored as
text but cannot be reconstructed elsewhere, and will error at prep().
See also
Other recipe serialization:
read_recipe()
Examples
spec <- weighting_spec(sample_survey, base_weights = pw) |>
step_nonresponse(respondent = responded, method = "weighting_class", by = "region") |>
step_calibrate(method = "raking", margins = list(region = c(table(population$region))))
f <- tempfile(fileext = ".yml")
write_recipe(spec, f)