pip_set_params: Get or set unbound parameters

In pipeflow: Fast Interactive Data Analysis Pipelines

Get or set unbound parameters

Description

pip_get_params() returns the current default values of all unbound parameters of a pipeline or view (parameters wired to another step's output via ~step_name are excluded), including those of locked steps. pip_set_params() updates these parameters for the whole pipeline or view. Steps whose values change are marked as outdated, together with their downstream dependents (steps that have never run stay "new"). Values that are identical() to the stored ones are skipped and don't outdate any step, unless force = TRUE.

Usage

pip_get_params(x)

pip_set_params(
  x,
  params = list(),
  unknown = c("warn", "ignore", "error"),
  force = FALSE
)

Arguments

x	A pipeflow pip or view.
params	Named list of parameters to set
unknown	How to handle params that are not defined in any of the selected steps, including locked ones: "warn" (default) signals a warning and sets the remaining parameters, "ignore" does so silently, and "error" fails before anything is changed.
force	Logical. If TRUE, every step that has one of the params is outdated (together with its downstream steps), even if the values are identical() to the stored ones. This refreshes steps whose inputs are environments or reference objects that were modified in place.

Value

For pip_get_params(), a named list of unbound parameter values; if the same parameter name appears in multiple steps, the first occurrence in pipeline order is returned. For pip_set_params(), the updated pipeline or view, invisibly.

Note

Parameters of locked steps are never changed and their state remains unchanged. pip_get_params() still returns them, so if a locked step comes first among the steps that share a parameter name, pip_get_params() keeps returning the locked step's value after the parameter was set.

An environment (or a reference object such as an R6 object) that was modified in place is identical to the stored one, so setting it again doesn't outdate the step unless force = TRUE.

Examples

p <- pip_new() |>
  pip_add("load", \(n = 10) seq_len(n)) |>
  pip_add("scale", \(x = ~load, factor = 0.5) x * factor)

# See all unbound/adjustable parameters before running
pip_get_params(p) # list(n = 10, factor = 0.5)
(pip_run(p))

# Updating params marks affected steps (and their dependents) outdated
pip_set_params(p, params = list(n = 5, factor = 2.0))
p
(pip_run(p))

# Setting the same values again doesn't outdate any step
pip_set_params(p, params = list(n = 5, factor = 2.0))
p

# Use force = TRUE to outdate the steps anyway
pip_set_params(p, params = list(n = 5, factor = 2.0), force = TRUE)
p

# Setting a parameter that is not defined in the pipeline yields a warning

pip_set_params(p, params = list(nope = 1))


# ... which can be silenced or turned into an error
pip_set_params(p, params = list(nope = 1), unknown = "ignore")
try(pip_set_params(p, params = list(nope = 1), unknown = "error"))

pipeflow documentation built on Oct. 13, 2026, 5:06 p.m.