Strict Join with Cardinality Enforcement

Performs a join operation that fails if the specified cardinality constraint is violated. Use this to catch unexpected many-to-many relationships early.

Usage

join_strict(
  x,
  y,
  by,
  type = c("left", "right", "inner", "full"),
  expect = c("1:1", "1:m", "1:many", "m:1", "many:1", "m:m", "many:many"),
  ...
)

Arguments

x

A data frame (left table).

y

A data frame (right table).

by

A character vector of column names to join by.

type

Character. The type of join to perform. One of "left" (default), "right", "inner", "full".

expect

Character. The expected cardinality relationship. One of:

"1:1"

Each key in x matches at most one key in y, and vice versa

"1:m" or "1:many"

Each key in x can match multiple keys in y, but each key in y matches at most one key in x

"m:1" or "many:1"

Each key in y can match multiple keys in x, but each key in x matches at most one key in y

"m:m" or "many:many"

No cardinality constraints (allows all relationships)

...

Additional arguments passed to the underlying join function.

Value

The joined data frame if the cardinality constraint is satisfied. Throws an error if the constraint is violated.

See also

join_spy(), left_join_spy()

Examples

orders <- data.frame(id = 1:3, product = c("A", "B", "C"))
customers <- data.frame(id = 1:3, name = c("Alice", "Bob", "Carol"))

# This succeeds (1:1 relationship)
join_strict(orders, customers, by = "id", expect = "1:1")

# This would fail if customers had duplicate ids
if (FALSE) { # \dontrun{
customers_dup <- data.frame(id = c(1, 1, 2), name = c("A1", "A2", "B"))
join_strict(orders, customers_dup, by = "id", expect = "1:1")
# Error: Expected 1:1 relationship but found 1:many
} # }