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QC.R
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# File src/library/tools/R/QC.R
# Part of the R package, https://www.R-project.org
#
# Copyright (C) 1995-2021 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# A copy of the GNU General Public License is available at
# https://www.R-project.org/Licenses/
## R CMD check uses
## .find_charset
## .check_namespace
## .check_package_depends
## .check_demo_index
## .check_vignette_index
## .check_package_subdirs
## .check_citation
## .check_package_ASCII_code
## .check_package_code_syntax
## .check_packages_used
## .check_package_code_shlib
## .check_package_code_startup_functions
## .check_package_code_assign_to_globalenv
## .check_package_code_attach
## .check_package_code_data_into_globalenv
## .check_code_usage_in_package
## .check_bogus_return
## .check_dotInternal
## .check_package_parseRd
## .check_Rd_xrefs
## undoc
## codoc
## codocData
## codocClasses
## checkDocFiles
## checkDocStyle
## checkFF
## checkS3methods
## checkReplaceFuns
## .check_package_datasets
## .check_package_compact_datasets
## .check_package_compact_sysdata
## .check_make_vars
## .createExdotR (testing.R)
## .runPackageTestsR (testing.R)
## .get_LaTeX_errors_from_log_file
## .check_package_CRAN_incoming
## checkRdContents
## R CMD build uses .check_package_subdirs
## NB: 'tools' cannot use NAMESPACE imports from utils, as it exists first
## "The language elements" : all are .Primitive *and* print as .Primitive("...")
langElts <- c("(", "{", ":", "~",
"<-", "<<-", "=",
"[", "[[", "[[<-", "[<-", "@", "@<-", "$", "$<-",
"&&", "||",
"break", "for", "function", "if", "next", "repeat", "return", "while")
## Code "existing conceptually" in base,
## typically function names of default methods for .Primitive s:
conceptual_base_code <- c("c.default")
##' a "default" print method (see NAMESPACE):
.print.via.format <- function(x, ...) {
writeLines(format(x, ...))
invisible(x)
}
## utility for whether Rd sources are available.
.haveRds <- function(dir)
{
## either source package or pre-2.10.0 installed package
dir.exists (file.path(dir, "man")) ||
file.exists(file.path(dir, "help", "paths.rds"))
}
### * undoc/F/out
undoc <-
function(package, dir, lib.loc = NULL)
{
## Argument handling.
## <NOTE>
## Earlier versions used to give an error if there were no Rd
## objects. This is not right: if there is code or data but no
## documentation, everything is undocumented ...
## </NOTE>
if(!missing(package)) {
if(length(package) != 1L)
stop("argument 'package' must be of length 1")
dirdir <- dirname(dir <- find.package(package, lib.loc))
## Using package installed in @code{dir} ...
is_base <- package == "base"
all_doc_topics <- Rd_aliases(package, lib.loc = dirdir)
## Load package into code_env.
if(!is_base)
.load_package_quietly(package, lib.loc)
code_env <- .package_env(package)
code_objs <- ls(envir = code_env, all.names = TRUE)
pkgname <- package
}
else {
if(missing(dir))
stop("you must specify 'package' or 'dir'")
pkgname <- basename(dir)
dirdir <- dirname(dir)
## Using sources from directory @code{dir} ...
if(!dir.exists(dir))
stop(gettextf("directory '%s' does not exist", dir),
domain = NA)
else
dir <- file_path_as_absolute(dir)
is_base <- pkgname == "base"
all_doc_topics <- Rd_aliases(dir = dir)
code_env <- new.env(hash = TRUE)
code_dir <- file.path(dir, "R")
if(dir.exists(code_dir)) {
dfile <- file.path(dir, "DESCRIPTION")
meta <- if(file_test("-f", dfile))
.read_description(dfile)
else
character()
.source_assignments_in_code_dir(code_dir, code_env, meta)
sys_data_file <- file.path(code_dir, "sysdata.rda")
if(file_test("-f", sys_data_file))
load(sys_data_file, code_env)
}
code_objs <- ls(envir = code_env, all.names = TRUE)
## Does the package have a NAMESPACE file? Note that when
## working on the sources we (currently?) cannot deal with the
## (experimental) alternative way of specifying the namespace.
if(file.exists(file.path(dir, "NAMESPACE"))) {
nsInfo <- parseNamespaceFile(pkgname, dirdir)
## Look only at exported objects (and not declared S3
## methods).
OK <- intersect(code_objs, nsInfo$exports)
for(p in nsInfo$exportPatterns)
OK <- c(OK, grep(p, code_objs, value = TRUE))
code_objs <- unique(OK)
}
}
## Find the data sets to work on.
data_dir <- file.path(dir, "data")
data_objs <- if(dir.exists(data_dir))
unlist(.try_quietly(list_data_in_pkg(dir = dir)),
use.names = FALSE)
else
character()
## There was a time when packages contained code or data (or both).
## But not anymore ...
if(!missing(package) && !length(code_objs) && !length(data_objs)
&& getOption("verbose"))
message("neither code nor data objects found")
if(!is_base) {
## Code objects in add-on packages with names starting with a
## dot are considered 'internal' (not user-level) by
## convention.
code_objs <- grep("^[^.].*", code_objs, value = TRUE)
## Note that this also allows us to get rid of S4 meta objects
## (with names starting with '.__C__' or '.__M__'; well, as long
## as there are none in base).
## Implicit generic functions exist to turn method dispatch on
## in this package, but their definition and documentation belongs
## to the package in their package slot, so eliminate any
## foreign generic functions from code_objs
if(.isMethodsDispatchOn()) {
is <- methods::is # speed
code_objs <-
Filter(function(f) {
fdef <- code_env[[f]] # faster than get()
## Running methods::is() on data sets can trigger
## loading additional packages for which startup
## messages et al need suppressing ...
if(suppressMessages(is(fdef, "genericFunction")))
fdef@package == pkgname
else
TRUE
},
code_objs)
}
## Allow group generics to be undocumented other than in base.
## In particular, those from methods partially duplicate base
## and are documented in base's groupGenerics.Rd.
code_objs <- setdiff(code_objs,
c("Arith", "Compare", "Complex", "Logic",
"Math", "Math2", "Ops", "Summary"))
}
undoc_things <-
list("code objects" =
unique(setdiff(code_objs, all_doc_topics)),
"data sets" =
unique(setdiff(data_objs, all_doc_topics)))
if(.isMethodsDispatchOn()) {
## Undocumented S4 classes?
S4_classes <- methods::getClasses(code_env)
## <NOTE>
## There is no point in worrying about exportClasses directives
## in a NAMESPACE file when working on a package source dir, as
## we only source the assignments, and hence do not get any
## S4 classes or methods.
## </NOTE>
## The bad ones:
S4_classes <-
S4_classes[vapply(S4_classes, utils:::topicName, " ",
type = "class", USE.NAMES = FALSE)
%notin% all_doc_topics]
undoc_things <-
c(undoc_things, list("S4 classes" = unique(S4_classes)))
}
if(.isMethodsDispatchOn()) {
## Undocumented S4 methods?
## <NOTE>
## There is no point in worrying about exportMethods directives
## in a NAMESPACE file when working on a package source dir, as
## we only source the assignments, and hence do not get any
## S4 classes or methods.
## </NOTE>
.make_S4_method_siglist <- function(g) {
mlist <- .get_S4_methods_list(g, code_env)
sigs <- .make_siglist(mlist) # s/#/,/g
if(length(sigs))
paste0(g, ",", sigs)
else
character()
}
S4_methods <- lapply(.get_S4_generics(code_env),
.make_S4_method_siglist)
S4_methods <- as.character(unlist(S4_methods, use.names = FALSE))
## The bad ones:
S4_methods <-
S4_methods[vapply(S4_methods, utils:::topicName, " ",
type="method", USE.NAMES = FALSE)
%notin% all_doc_topics]
undoc_things <-
c(undoc_things,
list("S4 methods" =
unique(sub("([^,]*),(.*)",
"generic '\\1' and siglist '\\2'",
S4_methods))))
}
if(is_base) {
## We use .ArgsEnv and .GenericArgsEnv in checkS3methods() and
## codoc(), so we check here that the set of primitives has not
## been changed.
ff <- as.list(baseenv(), all.names=TRUE)
prims <- names(ff)[vapply(ff, is.primitive, logical(1L))]
prototypes <- sort(c(names(.ArgsEnv), names(.GenericArgsEnv)))
extras <- setdiff(prototypes, prims)
if(length(extras))
undoc_things <- c(undoc_things, list(prim_extra=extras))
miss <- setdiff(prims, c(langElts, prototypes))
if(length(miss))
undoc_things <- c(undoc_things, list(primitives=miss))
}
class(undoc_things) <- "undoc"
undoc_things
}
format.undoc <-
function(x, ...)
{
.fmt <- function(i) {
tag <- names(x)[i]
msg <- switch(tag,
"code objects" =
gettext("Undocumented code objects:"),
"data sets" =
gettext("Undocumented data sets:"),
"S4 classes" =
gettext("Undocumented S4 classes:"),
"S4 methods" =
gettext("Undocumented S4 methods:"),
prim_extra =
gettext("Prototyped non-primitives:"),
gettextf("Undocumented %s:", tag))
c(msg,
## We avoid markup for indicating S4 methods, hence need to
## special-case output for these ...
if(tag == "S4 methods") {
strwrap(x[[i]], indent = 2L, exdent = 4L)
} else {
.pretty_format(x[[i]])
})
}
as.character(unlist(lapply(which(lengths(x) > 0L), .fmt)))
}
### * codoc
##
is_data_for_dataset <- function(e) ## trigger for data(foo) or data(foo, package="bar") and similar
length(e) >= 2L && e[[1L]] == quote(data) && e[[2L]] != quote(...) && length(e) <= 4L
codoc <-
function(package, dir, lib.loc = NULL,
use.values = NULL, verbose = getOption("verbose"))
{
has_namespace <- FALSE
## Argument handling.
if(!missing(package)) {
if(length(package) != 1L)
stop("argument 'package' must be of length 1")
dir <- find.package(package, lib.loc)
## Using package installed in @code{dir} ...
code_dir <- file.path(dir, "R")
if(!dir.exists(code_dir))
stop(gettextf("directory '%s' does not contain R code", dir),
domain = NA)
if(!.haveRds(dir))
stop(gettextf("directory '%s' does not contain Rd objects", dir),
domain = NA)
is_base <- basename(dir) == "base"
## Load package into code_env.
if(!is_base)
.load_package_quietly(package, lib.loc)
code_env <- .package_env(package)
objects_in_code <- sort(names(code_env))
dirdir <- dirname(dir)
## Does the package have a namespace?
if(packageHasNamespace(package, dirdir)) {
has_namespace <- TRUE
ns_env <- asNamespace(package)
S3Table <- get(".__S3MethodsTable__.", envir = ns_env)
functions_in_S3Table <- ls(S3Table, all.names = TRUE)
objects_in_ns <-
setdiff(sort(names(ns_env)),
c(".__NAMESPACE__.", ".__S3MethodsTable__."))
ns_S3_methods_db <- getNamespaceInfo(package, "S3methods")
ns_S3_methods <- if(is.null(ns_S3_methods_db))
character()
else
paste(ns_S3_methods_db[, 1L],
ns_S3_methods_db[, 2L],
sep = ".")
objects_in_code_or_namespace <-
unique(c(objects_in_code, objects_in_ns, ns_S3_methods))
objects_in_ns <- setdiff(objects_in_ns, objects_in_code)
}
else { ## typically only 'base'
objects_in_code_or_namespace <- objects_in_code
}
package_name <- package
}
else {
if(missing(dir))
stop("you must specify 'package' or 'dir'")
## Using sources from directory @code{dir} ...
if(!dir.exists(dir))
stop(gettextf("directory '%s' does not exist", dir), domain = NA)
## else
package_name <- basename(dir) # early, before resolving sym.links etc in next line:
dirdir <- dirname(dir) # early, ...
dir <- file_path_as_absolute(dir)
code_dir <- file.path(dir, "R")
if(!dir.exists(code_dir))
stop(gettextf("directory '%s' does not contain R code", dir),
domain = NA)
if(!.haveRds(dir))
stop(gettextf("directory '%s' does not contain Rd objects", dir),
domain = NA)
is_base <- package_name == "base"
code_env <- new.env(hash = TRUE)
dfile <- file.path(dir, "DESCRIPTION")
meta <- if(file_test("-f", dfile)) .read_description(dfile) else character()
.source_assignments_in_code_dir(code_dir, code_env, meta)
sys_data_file <- file.path(code_dir, "sysdata.rda")
if(file_test("-f", sys_data_file)) load(sys_data_file, code_env)
objects_in_code <- sort(names(code_env))
objects_in_code_or_namespace <- objects_in_code
## Does the package have a NAMESPACE file? Note that when
## working on the sources we (currently?) cannot deal with the
## (experimental) alternative way of specifying the namespace.
## Also, do not attempt to find S3 methods.
if(file.exists(file.path(dir, "NAMESPACE"))) {
has_namespace <- TRUE
objects_in_ns <- objects_in_code
functions_in_S3Table <- character()
ns_env <- code_env
nsInfo <- parseNamespaceFile(package_name, dirdir)
## Look only at exported objects.
OK <- intersect(objects_in_code, nsInfo$exports)
for(p in nsInfo$exportPatterns)
OK <- c(OK, grep(p, objects_in_code, value = TRUE))
objects_in_code <- unique(OK)
}
}
## Find the data sets to work on.
data_dir <- file.path(dir, "data")
if(dir.exists(data_dir)) {
data_sets_in_code_variables <-
.try_quietly(list_data_in_pkg(dir = dir))
data_sets_in_code <- names(data_sets_in_code_variables)
} else
data_sets_in_code <- data_sets_in_code_variables <- character()
## Find the function objects to work on.
functions_in_code <-
Filter(function(f) {
## This is expensive
f <- get(f, envir = code_env)
typeof(f) == "closure"
},
objects_in_code)
## Sourcing all R code files in the package is a problem for base,
## where this misses the .Primitive functions. Hence, when checking
## base for objects shown in \usage but missing from the code, we
## get the primitive functions from the version of R we are using.
## Maybe one day we will have R code for the primitives as well ...
## As from R 2.5.0 we do for most generics.
if(is_base) {
objects_in_base <-
sort(names(baseenv()))
objects_in_code <-
c(objects_in_code,
conceptual_base_code,
Filter(.is_primitive_in_base, objects_in_base),
c(".First.lib", ".Last.lib", ".Random.seed",
".onLoad", ".onAttach", ".onDetach", ".onUnload"))
objects_in_code_or_namespace <- objects_in_code
known_env <- .make_S3_primitive_generic_env(code_env, fixup=TRUE)
extras <- ls(known_env, all.names = TRUE)
functions_in_code <- c(functions_in_code, extras)
code_env <- known_env
known_env <- .make_S3_primitive_nongeneric_env(code_env)
extras <- ls(known_env, all.names = TRUE)
functions_in_code <- c(functions_in_code, extras)
code_env <- known_env
}
## Build a list with the formals of the functions in the code
## indexed by the names of the functions.
function_args_in_code <-
lapply(functions_in_code,
function(f) formals(get(f, envir = code_env))) # get is expensive
names(function_args_in_code) <- functions_in_code
if(has_namespace) {
functions_in_ns <-
Filter(function(f) {
f <- get(f, envir = ns_env) # get is expensive
is.function(f) && (length(formals(f)) > 0L)
},
objects_in_ns)
function_args_in_ns <-
lapply(functions_in_ns,
function(f) formals(get(f, envir = ns_env)))
names(function_args_in_ns) <- functions_in_ns
function_args_in_S3Table <-
lapply(functions_in_S3Table,
function(f) formals(get(f, envir = S3Table)))
names(function_args_in_S3Table) <- functions_in_S3Table
tmp <- c(function_args_in_code, function_args_in_S3Table,
function_args_in_ns)
keep <- !duplicated(names(tmp))
function_args_in_code <- tmp[keep]
functions_in_code <- names(function_args_in_code)
}
if(.isMethodsDispatchOn()) {
## <NOTE>
## There is no point in worrying about exportMethods directives
## in a NAMESPACE file when working on a package source dir, as
## we only source the assignments, and hence do not get any
## S4 classes or methods.
## </NOTE>
## <NOTE>
## In principle, we can get codoc checking for S4 methods
## documented explicitly using the \S4method{GENERIC}{SIGLIST}
## markup by adding the corresponding "pseudo functions" using
## the Rd markup as their name. However note that the formals
## recorded in the methods db only pertain to the signature, not
## to the ones of the function actually registered ... hence we
## use methods::unRematchDefinition() which knows how to extract
## the formals in the method definition from the
## function(ARGLIST) {
## .local <- function(FORMALS) BODY
## .local(ARGLIST)
## }
## redefinitions obtained by methods::rematchDefinition().
## </NOTE>
check_S4_methods <-
!isFALSE(as.logical(Sys.getenv("_R_CHECK_CODOC_S4_METHODS_")))
if(check_S4_methods) {
unRematchDef <- methods::unRematchDefinition
get_formals_from_method_definition <- function(m)
formals(unRematchDef(m))
lapply(.get_S4_generics(code_env),
function(f) {
mlist <- .get_S4_methods_list(f, code_env)
sigs <- .make_siglist(mlist)
if(!length(sigs)) return()
nm <- sprintf("\\S4method{%s}{%s}", f, sigs)
args <- lapply(mlist,
get_formals_from_method_definition)
names(args) <- nm
functions_in_code <<-
c(functions_in_code, nm)
function_args_in_code <<-
c(function_args_in_code, args)
})
}
}
check_codoc <- function(fName, ffd) {
## Compare the formals of the function in the code named 'fName'
## and formals 'ffd' obtained from the documentation.
ffc <- function_args_in_code[[fName]]
ident <- if(isFALSE(use.values)) {
ffc <- names(ffc)
ffd <- names(ffd)
identical(ffc, ffd)
} else {
identical(names(ffc), names(ffd)) &&
{
vffc <- as.character(ffc) # values
vffd <- as.character(ffd) # values
if(!isTRUE(use.values)) {
ind <- nzchar(vffd)
vffc <- vffc[ind]
vffd <- vffd[ind]
}
identical(vffc, vffd)
}
}
if(!ident)
list(list(name = fName, code = ffc, docs = ffd))
} #{check_codoc}
db <- if(!missing(package))
Rd_db(package, lib.loc = dirdir)
else
Rd_db(dir = dir)
names(db) <- db_names <- .Rd_get_names_from_Rd_db(db)
## pkg-defunct.Rd is not expected to list arguments
ind <- db_names %in% paste0(package_name, "-defunct")
db <- db[!ind]
db_names <- db_names[!ind]
db_usages <- lapply(db, .Rd_get_section, "usage")
## FIXME: all db_usages entries are full of "srcref" which are never used
db_usages <- lapply(db_usages, .parse_usage_as_much_as_possible)
ind <- vapply(db_usages,
function(x) !is.null(attr(x, "bad_lines")), NA, USE.NAMES=FALSE)
bad_lines <- lapply(db_usages[ind], attr, "bad_lines")
bad_doc_objects <- list()
functions_in_usages <- character()
variables_in_usages <- character()
data_sets_in_usages <- character()
functions_in_usages_not_in_code <- list()
data_sets_in_usages_not_in_code <- list()
variables_in_usages_not_in_code <- list()
objects_as_in <- c(objects_in_code_or_namespace
, names(compatibilityEnv()) # objects in other platforms
, if(missing(package) && str_parse_logic(meta["LazyData"], FALSE))
unlist(data_sets_in_code_variables, use.names = FALSE)
, if(is_base)
c("NA", "NULL", "Inf", "NaN", "TRUE", "FALSE", ".Autoloaded")
)
for(docObj in db_names) {
exprs <- db_usages[[docObj]]
if(!length(exprs)) next
## Get variable names and data set usages first, mostly for
## curiosity.
ind <- vapply(exprs, is.name, NA, USE.NAMES=FALSE)
if(any(ind)) {
variables <- sapply(exprs[ind], deparse)
variables_in_usages <- c(variables_in_usages, variables)
variables <- setdiff(variables, objects_as_in)
if(length(variables))
variables_in_usages_not_in_code[[docObj]] <- variables
exprs <- exprs[!ind]
}
exprs <- exprs[vapply(exprs, is.call, NA, USE.NAMES=FALSE)]
ind <- vapply(exprs, is_data_for_dataset, NA, USE.NAMES=FALSE)
if(any(ind)) {
data_sets <- sapply(exprs[ind],
function(e) as.character(e[[2L]]))
data_sets_in_usages <- c(data_sets_in_usages, data_sets)
data_sets <- setdiff(data_sets, data_sets_in_code)
if(length(data_sets))
data_sets_in_usages_not_in_code[[docObj]] <- data_sets
exprs <- exprs[!ind]
}
## Split out replacement function usages.
ind <- vapply(exprs, .is_call_from_replacement_function_usage, NA, USE.NAMES=FALSE)
replace_exprs <- exprs[ind]
exprs <- exprs[!ind]
## Ordinary functions.
functions <- vapply(exprs, function(e) as.character(e[[1L]]), "")
## Catch assignments: checkDocFiles() will report these, so drop
## them here.
## And also unary/binary operators
ind <- (functions %notin% c("<-", "=", "+", "-"))
exprs <- exprs[ind]
functions <- functions[ind]
functions <- .transform_S3_method_markup(as.character(functions))
ind <- functions %in% functions_in_code
bad_functions <-
mapply(functions[ind],
exprs[ind],
FUN = function(x, y)
check_codoc(x, as.pairlist(as.alist.call(y[-1L]))),
SIMPLIFY = FALSE)
## Replacement functions.
if(length(replace_exprs)) {
replace_funs <-
paste0(sapply(replace_exprs,
function(e) as.character(e[[2L]][[1L]])),
"<-")
replace_funs <- .transform_S3_method_markup(replace_funs)
functions <- c(functions, replace_funs)
ind <- (replace_funs %in% functions_in_code)
if(any(ind)) {
bad_replace_funs <-
mapply(replace_funs[ind],
replace_exprs[ind],
FUN = function(x, y)
check_codoc(x,
as.pairlist(c(as.alist.call(y[[2L]][-1L]),
as.alist.symbol(y[[3L]])))),
SIMPLIFY = FALSE)
bad_functions <-
c(bad_functions, bad_replace_funs)
}
}
bad_functions <- do.call("c", bad_functions)
if(length(bad_functions))
bad_doc_objects[[docObj]] <- bad_functions
## Determine functions with a \usage entry in the documentation
## but 'missing from the code'. If a package has a namespace, we
## really need to look at all objects in the namespace (hence
## 'objects_as_in' contains 'objects_in_code_or_namespace'),
## as one can access the internal
## symbols via ':::' and hence package developers might want to
## provide function usages for some of the internal functions.
## <FIXME>
## We may still have \S4method{}{} entries in functions, which
## cannot have a corresponding object in the code. Hence, we
## remove these function entries, but should really do better,
## by comparing the explicit \usage entries for S4 methods to
## what is actually in the code. We most likely also should do
## something similar for S3 methods.
ind <- grepl(.S4_method_markup_regexp, functions)
if(any(ind))
functions <- functions[!ind]
## </FIXME>
bad_functions <- setdiff(functions, objects_as_in)
if(length(bad_functions))
functions_in_usages_not_in_code[[docObj]] <- bad_functions
functions_in_usages <- c(functions_in_usages, functions)
}
## Determine (function) objects in the code without a \usage entry.
## Of course, these could still be 'documented' via \alias.
## </NOTE>
## Older versions only printed this information without returning it
## (in case 'verbose' was true). We now add this as an attribute to
## the bad_doc_objects returned.
## </NOTE>
objects_in_code_not_in_usages <-
setdiff(objects_in_code,
c(functions_in_usages, variables_in_usages))
functions_in_code_not_in_usages <-
intersect(functions_in_code, objects_in_code_not_in_usages)
## (Note that 'functions_in_code' does not necessarily contain all
## (exported) functions in the package.)
## Determine functions which have no usage but really should have.
## If there is no namespace (including base), we have no idea.
## If there is one, everything "exported" (in the package env)
## should also have a \usage, apart from
## * Defunct functions
## * S4 generics. Note that as per R-exts,
## exporting methods on a generic in the namespace will also
## export the generic, and exporting a generic in the namespace
## will also export its methods.
## so it seems there is really no way to figure out whether an
## exported S4 generic should have a \usage entry or not ...
functions_missing_from_usages <-
if(!has_namespace) character() else {
functions <- functions_in_code_not_in_usages
if(.isMethodsDispatchOn()) {
## Drop the functions which have S4 methods.
functions <-
setdiff(functions, names(.get_S4_generics(code_env)))
}
## Drop the defunct functions.
is_defunct <- function(f) {
f <- get(f, envir = code_env) # get is expensive
is.function(f) &&
is.call(b <- body(f)) &&
identical(as.character(b[[1L]]), ".Defunct")
}
functions[!vapply(functions, is_defunct, NA, USE.NAMES=FALSE)]
}
objects_missing_from_usages <-
if(!has_namespace) character() else {
c(functions_missing_from_usages,
setdiff(objects_in_code_not_in_usages,
c(functions_in_code, data_sets_in_code)))
}
attr(bad_doc_objects, "objects_in_code_not_in_usages") <-
objects_in_code_not_in_usages
attr(bad_doc_objects, "functions_in_code_not_in_usages") <-
functions_in_code_not_in_usages
attr(bad_doc_objects, "functions_in_usages_not_in_code") <-
functions_in_usages_not_in_code
attr(bad_doc_objects, "function_args_in_code") <-
function_args_in_code
attr(bad_doc_objects, "data_sets_in_usages_not_in_code") <-
data_sets_in_usages_not_in_code
if(config_val_to_logical(Sys.getenv("_R_CHECK_CODOC_VARIABLES_IN_USAGES_",
"FALSE"))) {
attr(bad_doc_objects, "variables_in_usages_not_in_code") <-
variables_in_usages_not_in_code
}
attr(bad_doc_objects, "objects_missing_from_usages") <-
objects_missing_from_usages
attr(bad_doc_objects, "functions_missing_from_usages") <-
functions_missing_from_usages
attr(bad_doc_objects, "has_namespace") <- has_namespace
attr(bad_doc_objects, "bad_lines") <- bad_lines
class(bad_doc_objects) <- "codoc"
bad_doc_objects
}
print.codoc <-
function(x, ...)
{
functions_in_usages_not_in_code <-
attr(x, "functions_in_usages_not_in_code")
if(length(functions_in_usages_not_in_code)) {
for(fname in names(functions_in_usages_not_in_code)) {
writeLines(gettextf("Functions or methods with usage in documentation object '%s' but not in code:",
fname))
.pretty_print(sQuote(unique(functions_in_usages_not_in_code[[fname]])))
writeLines("")
}
}
data_sets_in_usages_not_in_code <-
attr(x, "data_sets_in_usages_not_in_code")
if(length(data_sets_in_usages_not_in_code)) {
for(fname in names(data_sets_in_usages_not_in_code)) {
writeLines(gettextf("Data with usage in documentation object '%s' but not in code:",
fname))
.pretty_print(sQuote(unique(data_sets_in_usages_not_in_code[[fname]])))
writeLines("")
}
}
variables_in_usages_not_in_code <-
attr(x, "variables_in_usages_not_in_code")
if(length(variables_in_usages_not_in_code)) {
for(fname in names(variables_in_usages_not_in_code)) {
writeLines(gettextf("Variables with usage in documentation object '%s' but not in code:",
fname))
.pretty_print(sQuote(unique(variables_in_usages_not_in_code[[fname]])))
writeLines("")
}
}
## In general, functions in the code which only have an \alias but
## no \usage entry are not necessarily a problem---they might be
## mentioned in other parts of the Rd object documenting them, or be
## 'internal'. However, if a package has a namespace, then all
## *exported* functions should have \usage entries (apart from
## defunct functions and S4 generics, see the above comments for
## functions_missing_from_usages). Currently, this information is
## returned in the codoc object but not shown. Eventually, we might
## add something like
## functions_missing_from_usages <-
## attr(x, "functions_missing_from_usages")
## if(length(functions_missing_from_usages)) {
## writeLines("Exported functions without usage information:")
## .pretty_print(functions_in_code_not_in_usages)
## writeLines("")
## }
## similar to the above.
if(!length(x))
return(invisible(x))
has_only_names <- is.character(x[[1L]][[1L]][["code"]])
format_args <- function(s) {
if(!length(s))
"function()"
else if(has_only_names)
paste0("function(", paste(s, collapse = ", "), ")")
else {
s <- paste(deparse(s), collapse = "")
s <- gsub(" = ([,\\)])", "\\1", s)
s <- gsub("<unescaped bksl>", "\\", s, fixed = TRUE)
s <- gsub("^pairlist", "function", s)
gsub("^as.pairlist\\(alist\\((.*)\\)\\)$", "function(\\1)", s)
}
}
summarize_mismatches_in_names <- function(nfc, nfd) {
if(length(nms <- setdiff(nfc, nfd)))
writeLines(c(gettext(" Argument names in code not in docs:"),
strwrap(paste(nms, collapse = " "),
indent = 4L, exdent = 4L)))
if(length(nms <- setdiff(nfd, nfc)))
writeLines(c(gettext(" Argument names in docs not in code:"),
strwrap(paste(nms, collapse = " "),
indent = 4L, exdent = 4L)))
len <- min(length(nfc), length(nfd))
if(len) {
len <- seq_len(len)
nfc <- nfc[len]
nfd <- nfd[len]
ind <- which(nfc != nfd)
len <- length(ind)
if(len) {
if(len > 3L) {
writeLines(gettext(" Mismatches in argument names (first 3):"))
ind <- ind[1L:3L]
} else {
writeLines(gettext(" Mismatches in argument names:"))
}
for(i in ind) {
writeLines(sprintf(" Position: %d Code: %s Docs: %s",
i, nfc[i], nfd[i]))
}
}
}
}
summarize_mismatches_in_values <- function(ffc, ffd) {
## Be nice, and match arguments by names first.
nms <- intersect(names(ffc), names(ffd))
vffc <- ffc[nms]
vffd <- ffd[nms]
ind <- which(as.character(vffc) != as.character(vffd))
len <- length(ind)
if(len) {
if(len > 3L) {
writeLines(gettext(" Mismatches in argument default values (first 3):"))
ind <- ind[1L:3L]
} else {
writeLines(gettext(" Mismatches in argument default values:"))
}
for(i in ind) {
multiline <- FALSE
cv <- deparse(vffc[[i]])
if(length(cv) > 1L) {
cv <- paste(cv, collapse = "\n ")
multiline <- TRUE
}
dv <- deparse(vffd[[i]])
if(length(dv) > 1L) {
dv <- paste(dv, collapse = "\n ")
multiline <- TRUE
}
dv <- gsub("<unescaped bksl>", "\\", dv, fixed = TRUE)
sep <- if(multiline) "\n " else " "
writeLines(sprintf(" Name: '%s'%sCode: %s%sDocs: %s",
nms[i], sep, cv, sep, dv))
}
}
}
summarize_mismatches <- function(ffc, ffd) {
if(has_only_names)
summarize_mismatches_in_names(ffc, ffd)
else {
summarize_mismatches_in_names(names(ffc), names(ffd))
summarize_mismatches_in_values(ffc, ffd)
}
}
for(fname in names(x)) {
writeLines(gettextf("Codoc mismatches from documentation object '%s':",
fname))
xfname <- x[[fname]]
for(i in seq_along(xfname)) {
ffc <- xfname[[i]][["code"]]
ffd <- xfname[[i]][["docs"]]
writeLines(c(xfname[[i]][["name"]],
strwrap(gettextf("Code: %s", format_args(ffc)),
indent = 2L, exdent = 17L),
strwrap(gettextf("Docs: %s", format_args(ffd)),
indent = 2L, exdent = 17L)))
summarize_mismatches(ffc, ffd)
}
writeLines("")
}
invisible(x)
}
### * codocClasses
codocClasses <-
function(package, lib.loc = NULL)
{
## Compare the 'structure' of S4 classes in an installed package
## between code and documentation.
## Currently, only compares the slot names.
## <NOTE>
## This is patterned after the current codoc().
## It would be useful to return the whole information on class slot
## names found in the code and matching documentation (rather than
## just the ones with mismatches).
## Currently, we only return the names of all classes checked.
## </NOTE>
bad_Rd_objects <- structure(list(), class = "codocClasses")
## Argument handling.
if(length(package) != 1L)
stop("argument 'package' must be of length 1")
dir <- find.package(package, lib.loc)
if(!dir.exists(file.path(dir, "R")))
stop(gettextf("directory '%s' does not contain R code", dir),
domain = NA)
if(!.haveRds(dir))
stop(gettextf("directory '%s' does not contain Rd objects", dir),
domain = NA)
is_base <- basename(dir) == "base"
## Load package into code_env.
if(!is_base)
.load_package_quietly(package, lib.loc)
code_env <- .package_env(package)
if(!.isMethodsDispatchOn())
return(bad_Rd_objects)
S4_classes <- methods::getClasses(code_env)
if(!length(S4_classes)) return(bad_Rd_objects)
sApply <- function(X, FUN, ...) ## fast and special case - only
unlist(lapply(X = X, FUN = FUN, ...), recursive=FALSE, use.names=FALSE)
## Build Rd data base.
db <- Rd_db(package, lib.loc = dirname(dir))
## Need some heuristics now. When does an Rd object document just
## one S4 class so that we can compare (at least) the slot names?
## Try the following:
## 1) \docType{} identical to "class";
## 2) either exactly one \alias{} or only one ending in "-class"
## 3) a non-empty user-defined section 'Slots'.
## As going through the db to extract sections can take some time,
## we do the vectorized metadata computations first, and try to
## subscript whenever possible.
idx <- vapply(lapply(db, .Rd_get_doc_type), identical, NA, "class",