https://github.com/cran/XML
Tip revision: 17ba60d446f6da77b1143f704f7e0af6839b1d9b authored by CRAN Team on 16 March 2021, 12:52:45 UTC
version 3.99-0.6
version 3.99-0.6
Tip revision: 17ba60d
xmlHashTree.Rd
\name{xmlHashTree}
\alias{xmlHashTree}
\title{Constructors for trees stored as flat list of nodes with
information about parents and children.}
\description{
These (and related internal) functions allow us to represent trees as
a simple, non-hierarchical collection of nodes along with
corresponding tables that identify the parent and child relationships.
This is different from representing a tree as a list of lists of lists
... in which each node has a list of its own children. In a
functional language like R, it is not possible then for the children
to be able to identify their parents.
We use an environment to represent these flat trees. Since these are
mutable without requiring the change to be reassigned, we can modify a
part of the tree locally without having to reassign the top-level
object.
We can use either a list (with names) to store the nodes or a hash
table/associative array that uses names. There is a non-trivial
performance difference.
}
\usage{
xmlHashTree(nodes = list(), parents = character(), children = list(),
env = new.env(TRUE, parent = emptyenv()))
}
\arguments{
\item{nodes}{ a collection of existing nodes that are to be added to
the tree. These are used to initialize the tree. If this is
specified, you must also specify \code{children} and \code{parents}.
}
\item{parents}{ the parent relationships for the nodes given by \code{nodes}.}
\item{children}{the children relationships for the nodes given by \code{nodes}.}
\item{env}{an environment in which the information for the tree will
be stored. This is essentially the tree object as it allows us to
modify parts of the tree without having to reassign the top-level
object. Unlike most R data types, environments are mutable.
}
}
\value{
An \code{xmlHashTree} object has an accessor method via
\code{$} for accessing individual nodes within the tree.
One can use the node name/identifier in an expression such as
\code{tt$myNode} to obtain the element.
The name of a node is either its XML node name or if that is already
present in the tree, a machine generated name.
One can find the names of all the nodes using the
\code{objects} function since these trees are regular
environments in R.
Using the \code{all = TRUE} argument, one can also find the
\dQuote{hidden} elements that make define the tree's structure.
These are \code{.children} and \code{.parents}.
The former is an (hashed) environment. Each element is identified by the
node in the tree by the node's identifier (corresponding to the
name of the node in the tree's environment).
The value of that element is simply a character vector giving the
identifiers of all of the children of that node.
The \code{.parents} element is also an environemnt.
Each element in this gives the pair of node and parent identifiers
with the parent identifier being the value of the variable in the
environment. In other words, we look up the parent of a node
named 'kid' by retrieving the value of the variable 'kid' in the
\code{.parents} environment of this hash tree.
The function \code{.addNode} is used to insert a new node into the
tree.
The structure of this tree allows one to easily travers all nodes,
navigate up the tree from a node via its parent. Certain tasks are
more complex as the hierarchy is not implicit within a node.
}
\references{\url{http://www.w3.org/XML}}
\author{ Duncan Temple Lang }
\seealso{
\code{\link{xmlTreeParse}}
\code{\link{xmlTree}}
\code{\link{xmlOutputBuffer}}
\code{\link{xmlOutputDOM}}
}
\examples{
f = system.file("exampleData", "dataframe.xml", package = "XML")
tr = xmlHashTree()
xmlTreeParse(f, handlers = list(.startElement = tr[[".addNode"]]))
tr # print the tree on the screen
# Get the two child nodes of the dataframe node.
xmlChildren(tr$dataframe)
# Find the names of all the nodes.
objects(tr)
# Which nodes have children
objects(tr$.children)
# Which nodes are leaves, i.e. do not have children
setdiff(objects(tr), objects(tr$.children))
# find the class of each of these leaf nodes.
sapply(setdiff(objects(tr), objects(tr$.children)),
function(id) class(tr[[id]]))
# distribution of number of children
sapply(tr$.children, length)
# Get the first A node
tr$A
# Get is parent node.
xmlParent(tr$A)
f = system.file("exampleData", "allNodeTypes.xml", package = "XML")
# Convert the document
r = xmlInternalTreeParse(f, xinclude = TRUE)
ht = as(r, "XMLHashTree")
ht
# work on the root node, or any node actually
as(xmlRoot(r), "XMLHashTree")
# Example of making copies of an XMLHashTreeNode object to create a separate tree.
f = system.file("exampleData", "simple.xml", package = "XML")
tt = as(xmlParse(f), "XMLHashTree")
xmlRoot(tt)[[1]]
xmlRoot(tt)[[1, copy = TRUE]]
table(unlist(eapply(tt, xmlName)))
# if any of the nodes had any attributes
# table(unlist(eapply(tt, xmlAttrs)))
}
\keyword{IO}
\concept{XML}