This vignette dives into the details of S7 classes and objects,
building on the basics discussed in vignette("S7")
. It will
cover validators, the finer details of properties, and finally how to
write your own constructors.
Validation
S7 classes can have an optional validator that
checks that the values of the properties are OK. A validator is a
function that takes the object (called self
) and returns
NULL
if it’s valid or returns a character vector listing
the problems.
Basics
In the following example we create a Range
class that
enforces that @start
and @end
are single
numbers, and that @start
is less than
@end
:
Range <- new_class("Range",
properties = list(
start = class_double,
end = class_double
),
validator = function(self) {
if (length(self@start) != 1) {
"@start must be length 1"
} else if (length(self@end) != 1) {
"@end must be length 1"
} else if (self@end < self@start) {
sprintf(
"@end (%i) must be greater than or equal to @start (%i)",
self@end,
self@start
)
}
}
)
You can typically write a validator as a series of
if
-else
statements, but note that the order of
the statements is important. For example, in the code above, we can’t
check that self@end < self@start
before we’ve checked
that @start
and @end
are length 1.
As we’ll discuss shortly, you can also perform validation on a per-property basis, so generally class validators should be reserved for interactions between properties.
When is validation performed?
Objects are validated automatically when constructed and when any property is modified:
x <- Range(1, 2:3)
#> Error: <Range> object properties are invalid:
#> - @end must be <double>, not <integer>
x <- Range(10, 1)
#> Error: <Range> object is invalid:
#> - @end (1) must be greater than or equal to @start (10)
x <- Range(1, 10)
x@start <- 20
#> Error: <Range> object is invalid:
#> - @end (10) must be greater than or equal to @start (20)
You can also manually validate()
an object if you use a
low-level R function to bypass the usual checks and balances of
@
:
Avoiding validation
Imagine you wanted to write a function that would shift a property to the left or the right:
shift <- function(x, shift) {
x@start <- x@start + shift
x@end <- x@end + shift
x
}
shift(Range(1, 10), 1)
#> <Range>
#> @ start: num 2
#> @ end : num 11
There’s a problem if shift
is larger than
@end
- @start
:
shift(Range(1, 10), 10)
#> Error: <Range> object is invalid:
#> - @end (10) must be greater than or equal to @start (11)
While the end result of shift()
will be valid, an
intermediate state is not. The easiest way to resolve this problem is to
set the properties all at once:
shift <- function(x, shift) {
props(x) <- list(
start = x@start + shift,
end = x@end + shift
)
x
}
shift(Range(1, 10), 10)
#> <Range>
#> @ start: num 11
#> @ end : num 20
The object is still validated, but it’s only validated once, after all the properties have been modified.
Properties
So far we’ve focused on the simplest form of property specification
where you use a named list to supply the desired type for each property.
This is a convenient shorthand for a call to
new_property()
. For example, the property definition of
range above is shorthand for:
Range <- new_class("Range",
properties = list(
start = new_property(class_double),
end = new_property(class_double)
)
)
Calling new_property()
explicitly allows you to control
aspects of the property other than its type. The following sections show
you how to add a validator, provide a default value, compute the
property value on demand, or provide a fully dynamic property.
Validation
You can optionally provide a validator for each property. For
example, instead of validating the length of start
and
end
in the validator of our Range
class, we
could implement those at the property level:
prop_number <- new_property(
class = class_double,
validator = function(value) {
if (length(value) != 1L) "must be length 1"
}
)
Range <- new_class("Range",
properties = list(
start = prop_number,
end = prop_number
),
validator = function(self) {
if (self@end < self@start) {
sprintf(
"@end (%i) must be greater than or equal to @start (%i)",
self@end,
self@start
)
}
}
)
Range(start = c(1.5, 3.5))
#> Error: <Range> object properties are invalid:
#> - @start must be length 1
#> - @end must be length 1
Range(end = c(1.5, 3.5))
#> Error: <Range> object properties are invalid:
#> - @start must be length 1
#> - @end must be length 1
Note that property validators shouldn’t include the name of the property in validation messages as S7 will add it automatically. This makes it possible to use the same property definition for multiple properties of the same type, as above.
Default value
The defaults of new_class()
create a class that can be
constructed with no arguments:
Empty <- new_class("Empty",
properties = list(
x = class_double,
y = class_character,
z = class_logical
))
Empty()
#> <Empty>
#> @ x: num(0)
#> @ y: chr(0)
#> @ z: logi(0)
The default values of the properties will be filled in with “empty”
instances. You can instead provide your own defaults by using the
default
argument:
Empty <- new_class("Empty",
properties = list(
x = new_property(class_numeric, default = 0),
y = new_property(class_character, default = ""),
z = new_property(class_logical, default = NA)
)
)
Empty()
#> <Empty>
#> @ x: num 0
#> @ y: chr ""
#> @ z: logi NA
A quoted call becomes a standard function promise in the default constructor, evaluated at the time the object is constructed.
Stopwatch <- new_class("Stopwatch", properties = list(
start_time = new_property(
class = class_POSIXct,
default = quote(Sys.time())
),
elapsed = new_property(
getter = function(self) {
difftime(Sys.time(), self@start_time, units = "secs")
}
)
))
args(Stopwatch)
#> function (start_time = Sys.time())
#> NULL
round(Stopwatch()@elapsed)
#> Time difference of 0 secs
round(Stopwatch(Sys.time() - 1)@elapsed)
#> Time difference of 1 secs
Computed properties
It’s sometimes useful to have a property that is computed on demand.
For example, it’d be convenient to pretend that our range has a length,
which is just the distance between @start
and
@end
. You can dynamically compute the value of a property
by defining a getter
:
Range <- new_class("Range",
properties = list(
start = class_double,
end = class_double,
length = new_property(
getter = function(self) self@end - self@start
)
)
)
x <- Range(start = 1, end = 10)
x
#> <Range>
#> @ start : num 1
#> @ end : num 10
#> @ length: num 9
Computed properties are read-only:
x@length <- 20
#> Error: Can't set read-only property <Range>@length
Dynamic properties
You can make a computed property fully dynamic so that it can be read
and written by also supplying a setter
.
A setter
is a function with arguments self
and value
that returns a modified object.
For example, we could extend the previous example to allow the
@length
to be set, by modifying the @end
of
the vector:
Range <- new_class("Range",
properties = list(
start = class_double,
end = class_double,
length = new_property(
class = class_double,
getter = function(self) self@end - self@start,
setter = function(self, value) {
if (!length(value)) {
# Do nothing if called with the constructor default
# value for this property, a zero-length double vector.
return(self)
}
self@end <- self@start + value
self
}
)
)
)
x <- Range(start = 1, end = 10)
x
#> <Range>
#> @ start : num 1
#> @ end : num 10
#> @ length: num 9
x@length <- 5
x
#> <Range>
#> @ start : num 1
#> @ end : num 6
#> @ length: num 5
Common Patterns
getter
, setter
, default
, and
validator
can be used to implement many common patterns of
properties.
Deprecated properties
A setter
+ getter
can be used to to
deprecate a property:
Person <- new_class("Person", properties = list(
first_name = class_character,
firstName = new_property(
class_character,
default = quote(first_name),
getter = function(self) {
warning("@firstName is deprecated; please use @first_name instead", call. = FALSE)
self@first_name
},
setter = function(self, value) {
if (identical(value, self@first_name)) {
return(self)
}
warning("@firstName is deprecated; please use @first_name instead", call. = FALSE)
self@first_name <- value
self
}
)
))
args(Person)
#> function (first_name = character(0), firstName = first_name)
#> NULL
hadley <- Person(firstName = "Hadley")
#> Warning: @firstName is deprecated; please use @first_name instead
hadley <- Person(first_name = "Hadley") # no warning
hadley@firstName
#> Warning: @firstName is deprecated; please use @first_name instead
#> [1] "Hadley"
hadley@firstName <- "John"
#> Warning: @firstName is deprecated; please use @first_name instead
hadley@first_name # no warning
#> [1] "John"
Required properties
You can make a property required by the constructor either by:
- relying on the validator to error with the default value, or by
- setting the property default to a quoted error call.
Person <- new_class("Person", properties = list(
name = new_property(
class_character,
validator = function(value) {
if (length(value) != 1 || is.na(value) || value == "")
"must be a non-empty string"
}
)
))
try(Person())
#> Error : <Person> object properties are invalid:
#> - @name must be a non-empty string
try(Person(1)) # class_character$validator() is also checked.
#> Error : <Person> object properties are invalid:
#> - @name must be <character>, not <double>
Person("Alice")
#> <Person>
#> @ name: chr "Alice"
Frozen properties
You can mark a property as read-only after construction by providing
a custom setter
.
Person <- new_class("Person", properties = list(
birth_date = new_property(
class_Date,
setter = function(self, value) {
if(!is.null(self@birth_date)) {
stop("@birth_date is read-only", call. = FALSE)
}
self@birth_date <- as.Date(value)
self
}
)))
person <- Person("1999-12-31")
try(person@birth_date <- "2000-01-01")
#> Error : @birth_date is read-only
Constructors
You can see the source code for a class’s constructor by accessing
the constructor
property:
Range@constructor
#> function (start = numeric(0), end = numeric(0), length = numeric(0))
#> {
#> start
#> end
#> length
#> S7::new_object(S7::S7_object(), start = start, end = end,
#> length = length)
#> }
In most cases, S7’s default constructor will be all you need. However, in some cases you might want something custom. For example, for our range class, maybe we’d like to construct it from a vector of numeric values, automatically computing the min and the max. To implement this we could do:
Range <- new_class("Range",
properties = list(
start = class_numeric,
end = class_numeric
),
constructor = function(x) {
new_object(S7_object(),
start = min(x, na.rm = TRUE),
end = max(x, na.rm = TRUE))
}
)
Range(c(10, 5, 0, 2, 5, 7))
#> <Range>
#> @ start: num 0
#> @ end : num 10
A constructor must always end with a call to
new_object()
. The first argument to
new_object()
should be an object of the parent
class (if you haven’t specified a parent
argument to
new_class()
, then you should use S7_object()
as the parent here). That argument should be followed by one named
argument for each property.
There’s one drawback of custom constructors that you should be aware of: any subclass will also require a custom constructor.