我正在尝试使用`stream将以下代码重构为lambda表达式,尤其是嵌套的foreach循环:
public static Result match (Response rsp) {
Exception lastex = null;
for (FirstNode firstNode : rsp.getFirstNodes()) {
for (SndNode sndNode : firstNode.getSndNodes()) {
try {
if (sndNode.isValid())
return parse(sndNode); //return the first match, retry if fails with ParseException
} catch (ParseException e) {
lastex = e;
}
}
}
//throw the exception if all elements failed
if (lastex != null) {
throw lastex;
}
return null;
}
我开始时:
rsp.getFirstNodes().forEach().?? // how to iterate the nested 2ndNodes?
答案 0 :(得分:18)
看看flatMap:
flatMap(Function<? super T,? extends Stream<? extends R>> mapper)
返回由替换每个元素的结果组成的流 此流的内容是由生成的映射流的内容 将提供的映射函数应用于每个元素。
代码示例假设isValid()
没有抛出
Optional<SndNode> sndNode = rsp.getFirstNodes()
.stream()
.flatMap(firstNode -> firstNode.getSndNodes().stream()) //This is the key line for merging the nested streams
.filter(sndNode -> sndNode.isValid())
.findFirst();
if (sndNode.isPresent()) {
try {
parse(sndNode.get());
} catch (ParseException e) {
lastex = e;
}
}
答案 1 :(得分:9)
我担心使用溪流和lambdas,你的表现可能会受到影响。您当前的解决方案返回第一个有效且可解析的节点,但是无法中断流上的操作,例如for-each(source)。
此外,因为您可以有两个不同的输出(返回结果或抛出异常),所以单行表达式无法执行此操作。
这是我想出的。它可能会给你一些想法:
public static Result match(Response rsp) throws Exception {
Map<Boolean, List<Object>> collect = rsp.getFirstNodes().stream()
.flatMap(firstNode -> firstNode.getSndNodes().stream()) // create stream of SndNodes
.filter(SndNode::isValid) // filter so we only have valid nodes
.map(node -> {
// try to parse each node and return either the result or the exception
try {
return parse(node);
} catch (ParseException e) {
return e;
}
}) // at this point we have stream of objects which may be either Result or ParseException
.collect(Collectors.partitioningBy(o -> o instanceof Result)); // split the stream into two lists - one containing Results, the other containing ParseExceptions
if (!collect.get(true).isEmpty()) {
return (Result) collect.get(true).get(0);
}
if (!collect.get(false).isEmpty()) {
throw (Exception) collect.get(false).get(0); // throws first exception instead of last!
}
return null;
}
如开头所述,可能存在性能问题,因为会尝试解析每个有效节点。
修改强>
为了避免解析所有节点,可以使用reduce
,但它更复杂和丑陋(需要额外的类)。这也显示了所有ParseException
而不是最后一个。
private static class IntermediateResult {
private final SndNode node;
private final Result result;
private final List<ParseException> exceptions;
private IntermediateResult(SndNode node, Result result, List<ParseException> exceptions) {
this.node = node;
this.result = result;
this.exceptions = exceptions;
}
private Result getResult() throws ParseException {
if (result != null) {
return result;
}
if (exceptions.isEmpty()) {
return null;
}
// this will show all ParseExceptions instead of just last one
ParseException exception = new ParseException(String.format("None of %s valid nodes could be parsed", exceptions.size()));
exceptions.stream().forEach(exception::addSuppressed);
throw exception;
}
}
public static Result match(Response rsp) throws Exception {
return Stream.concat(
Arrays.stream(new SndNode[] {null}), // adding null at the beginning of the stream to get an empty "aggregatedResult" at the beginning of the stream
rsp.getFirstNodes().stream()
.flatMap(firstNode -> firstNode.getSndNodes().stream())
.filter(SndNode::isValid)
)
.map(node -> new IntermediateResult(node, null, Collections.<ParseException>emptyList()))
.reduce((aggregatedResult, next) -> {
if (aggregatedResult.result != null) {
return aggregatedResult;
}
try {
return new IntermediateResult(null, parse(next.node), null);
} catch (ParseException e) {
List<ParseException> exceptions = new ArrayList<>(aggregatedResult.exceptions);
exceptions.add(e);
return new IntermediateResult(null, null, Collections.unmodifiableList(exceptions));
}
})
.get() // aggregatedResult after going through the whole stream, there will always be at least one because we added one at the beginning
.getResult(); // return Result, null (if no valid nodes) or throw ParseException
}
<强> EDIT2:强>
通常,在使用findFirst()
等终端运算符时,也可以使用延迟求值。因此,只需稍微更改一下需求(即返回null而不是抛出异常),就应该可以执行以下操作。但是,flatMap
findFirst
并不使用延迟评估(source),因此此代码会尝试解析所有节点。
private static class ParsedNode {
private final Result result;
private ParsedNode(Result result) {
this.result = result;
}
}
public static Result match(Response rsp) throws Exception {
return rsp.getFirstNodes().stream()
.flatMap(firstNode -> firstNode.getSndNodes().stream())
.filter(SndNode::isValid)
.map(node -> {
try {
// will parse all nodes because of flatMap
return new ParsedNode(parse(node));
} catch (ParseException e ) {
return new ParsedNode(null);
}
})
.filter(parsedNode -> parsedNode.result != null)
.findFirst().orElse(new ParsedNode(null)).result;
}
答案 2 :(得分:2)
尝试使用map
转换原始来源。
rsp.getFirstNodes().stream().map(FirstNode::getSndNodes)
.filter(sndNode-> sndNode.isValid())
.forEach(sndNode->{
// No do the sndNode parsing operation Here.
})
答案 3 :(得分:1)
您可以迭代嵌套循环,如下所示
sed '0,/\PIDFILE=\/var\/run\/Naming_Service.pid/ s//\PIDFILE_1234=\/var\/run\/Naming_Service_1234.pid\n\PIDFILE_1235=\/var\/run\/Naming_Service_1235.pid\n\PIDFILE_1236=\/var\/run\/Naming_Service_1236.pid\n /' script > newscript
sed '0,/\OPTIONS="-p ${PIDFILE}"/ s//\OPTIONS_1234="-p ${PIDFILE_1234} -ORBEndpoint iiop:\/\/10.12.23.34:1234"\n\OPTIONS_1235="-p ${PIDFILE_1235} -ORBEndpoint iiop:\/\/10.12.23.34:1235"\n\OPTIONS_1236="-p ${PIDFILE_1236} -ORBEndpoint iiop:\/\/10.12.23.34:1236"\n /' newscript > script
答案 4 :(得分:1)
有点晚了,但这是一种可读的方法:
use strict;
use warnings;
use Text::CSV_XS;
my $csv = Text::CSV_XS->new ({ binary => 1, auto_diag => 1, sep_char => ',', allow_whitespace => 1, allow_loose_quotes => 1});
open my $fh, "<", 'test.csv' or die "Unable to open test.csv: $!";
while (my $row = $csv->getline ($fh)) {
foreach my $filed (@$row) {
print "[$filed]";
}
print "\n";
}
close $fh;
解释:您可以获得 Result = rsp.getFirstNodes()
.stream()
.flatMap(firstNode -> firstNode.getSndNodes.stream())
.filter(secondNode::isValid))
.findFirst()
.map(node -> this.parseNode(node)).orElse(null);
和firstNodes
所有内容。在每个firstNode中输出n stream()
。您检查每个SndNodes
以查看有效的第一个。如果没有有效的SndNode,那么我们将得到一个空值。如果有,则会将其解析为SndNodes
parseMethod()不会改变原文:
Result
答案 5 :(得分:0)
您可以使用StreamSupport
提供stream
方法的事实,Spliterator
和Iterable
采用spliterator
方法。
然后,您只需要一种机制将您的结构展平为Iterable
- 就像这样。
class IterableIterable<T> implements Iterable<T> {
private final Iterable<? extends Iterable<T>> i;
public IterableIterable(Iterable<? extends Iterable<T>> i) {
this.i = i;
}
@Override
public Iterator<T> iterator() {
return new IIT();
}
private class IIT implements Iterator<T> {
// Pull an iterator.
final Iterator<? extends Iterable<T>> iit = i.iterator();
// The current Iterator<T>
Iterator<T> it = null;
// The current T.
T next = null;
@Override
public boolean hasNext() {
boolean finished = false;
while (next == null && !finished) {
if (it == null || !it.hasNext()) {
if (iit.hasNext()) {
it = iit.next().iterator();
} else {
finished = true;
}
}
if (it != null && it.hasNext()) {
next = it.next();
}
}
return next != null;
}
@Override
public T next() {
T n = next;
next = null;
return n;
}
}
}
public void test() {
List<List<String>> list = new ArrayList<>();
List<String> first = new ArrayList<>();
first.add("First One");
first.add("First Two");
List<String> second = new ArrayList<>();
second.add("Second One");
second.add("Second Two");
list.add(first);
list.add(second);
// Check it works.
IterableIterable<String> l = new IterableIterable<>(list);
for (String s : l) {
System.out.println(s);
}
// Stream it like this.
Stream<String> stream = StreamSupport.stream(l.spliterator(), false);
}
您现在可以直接从Iterable
流式传输。
最初的研究表明,这应该用flatMap
完成,但无论如何。