blocks|key|2528892|text|试试opencsv。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2528893|它可以做你需要的所有事情，包括(尤其是)处理引用值中的内嵌分隔符(例如"a,b",+"c"解析为["a,b",+"c"])|style|CODE|2528894|我已经成功地使用了它，并且我喜欢它。|2528895|编辑：|2528896|因为opencsv只处理单字符分隔符，所以您可以这样解决这个问题：|2528897|String+input;
char+someCharNotInInput+=+'%7C';
String+delimiter+=+"abc";+//+or+whatever
input.replaceAll(delimiter,+someCharNotInInput);
new+CSVReader(input,+someCharNotInInput);+//+etc
//+Put+it+back+into+each+value+read
value.replaceAll(someCharNotInInput,+delimiter);+//+in+case+it's+inside+delimiters|code-block|syntax|javascript|2528898|entityMap|0|LINK|mutability|MUTABLE|url|http://opencsv.sourceforge.net/^0|2|7|0|0|Z|A|1C|C|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|10|8|@]|9|@$A|11|B|12|1|13]]|C|$]]|$1|D|3|E|5|6|7|14|8|@$A|15|B|16|F|G]|$A|17|B|18|F|G]]|9|@]|C|$]]|$1|H|3|I|5|6|7|19|8|@]|9|@]|C|$]]|$1|J|3|K|5|6|7|1A|8|@]|9|@]|C|$]]|$1|L|3|M|5|6|7|1B|8|@]|9|@]|C|$]]|$1|N|3|O|5|P|7|1C|8|@]|9|@]|C|$Q|R]]|$1|S|3|-4|5|6|7|1D|8|@]|9|@]|C|$]]]|T|$U|$5|V|W|X|C|$Y|Z]]]]

Try <a href="http://opencsv.sourceforge.net/" rel="nofollow noreferrer">opencsv</a>.
It does everything you need, including (and especially) handling embedded delimiters within quoted values (eg <code>&quot;a,b&quot;, &quot;c&quot;</code> parses as <code>[&quot;a,b&quot;, &quot;c&quot;]</code>)
I've used it successfully and I liked it.
<h3>Edited:</h3>
Since opencsv handles only single-character separators, you could work around this thus:
<pre><code>String input;
char someCharNotInInput = '|';
String delimiter = &quot;abc&quot;; // or whatever
input.replaceAll(delimiter, someCharNotInInput);
new CSVReader(input, someCharNotInInput); // etc
// Put it back into each value read
value.replaceAll(someCharNotInInput, delimiter); // in case it's inside delimiters
</code></pre>

blocks|key|2738784|text|这是一个好问题。这个问题对我来说并不明显，直到我看了javadocs，意识到opencsv只支持字符作为分隔符，而不是字符串……|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2738785|这里有几个建议的变通方法(+Groovy中的示例可以转换为java)。|2738786|忽略隐式中间字段|2738787|继续使用OpenCSV，但忽略空字段。显然，这是一种欺骗，但它可以很好地解析行为良好的数据。|2738788|++++CSVParser+csv+=+new+CSVParser((char)'%7C')

++++String[]+result+=+csv.parseLine('J%7C%7CProject+report%7C%7C"F,+G,+I"%7C%7C1')

++++assert+result[0]+==+"J"
++++assert+result[2]+==+"Project+report"
++++assert+result[4]+==+"F,+G,+I"
++++assert+result[6]+==+"1"|code-block|syntax|javascript|2738789|或|2738790|++++CSVParser+csv+=+new+CSVParser((char)'%7C')

++++String[]+result+=+csv.parseLine('J%7C%7C%7CProject+report%7C%7C%7C"F,+G,+I"%7C%7C%7C1')

++++assert+result[0]+==+"J"
++++assert+result[3]+==+"Project+report"
++++assert+result[6]+==+"F,+G,+I"
++++assert+result[9]+==+"1"|2738791|滚你自己的|2738792|使用Java+String+tokenizer方法。|2738793|++++def+result+=+'J%7C%7C%7CProject+report%7C%7C%7C"F,+G,+I"%7C%7C%7C1'.tokenize('%7C%7C%7C')

++++assert+result[0]+==+"J"
++++assert+result[1]+==+"Project+report"
++++assert+result[2]+==+"\"F,+G,+I\""
++++assert+result[3]+==+"1"|2738794|这种方法的缺点是您无法忽略引号字符或转义分隔符。|2738795|更新|2738796|与其对数据进行预处理，改变其内容，为什么不将上述两种方法结合在一个两步的过程中：|2738797|2738798|使用“滚动您自己的”来首先验证数据。拆分每一行并证明它包含所需的字段数。|ordered-list-item|2738799|使用“忽略字段”方法来分析验证的数据，确保在知道已指定正确的字段数的情况下安全。|2738800|2738801|效率不是很高，但可能比编写自己的CSV解析器更容易:-)|2738802|entityMap|0|LINK|mutability|MUTABLE|url|http://opencsv.sourceforge.net/apidocs/au/com/bytecode/opencsv/CSVParser.html|1|http://docs.oracle.com/javase/1.4.2/docs/api/java/util/StringTokenizer.html^0|Q|8|0|0|0|0|0|0|0|0|0|E|9|1|0|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1N|8|@]|9|@$A|1O|B|1P|1|1Q]]|C|$]]|$1|D|3|E|5|6|7|1R|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|1S|8|@]|9|@]|C|$]]|$1|H|3|I|5|6|7|1T|8|@]|9|@]|C|$]]|$1|J|3|K|5|L|7|1U|8|@]|9|@]|C|$M|N]]|$1|O|3|P|5|6|7|1V|8|@]|9|@]|C|$]]|$1|Q|3|R|5|L|7|1W|8|@]|9|@]|C|$M|N]]|$1|S|3|T|5|6|7|1X|8|@]|9|@]|C|$]]|$1|U|3|V|5|6|7|1Y|8|@]|9|@$A|1Z|B|20|1|21]]|C|$]]|$1|W|3|X|5|L|7|22|8|@]|9|@]|C|$M|N]]|$1|Y|3|Z|5|6|7|23|8|@]|9|@]|C|$]]|$1|10|3|11|5|6|7|24|8|@]|9|@]|C|$]]|$1|12|3|13|5|6|7|25|8|@]|9|@]|C|$]]|$1|14|3|-4|5|6|7|26|8|@]|9|@]|C|$]]|$1|15|3|16|5|17|7|27|8|@]|9|@]|C|$]]|$1|18|3|19|5|17|7|28|8|@]|9|@]|C|$]]|$1|1A|3|-4|5|6|7|29|8|@]|9|@]|C|$]]|$1|1B|3|1C|5|6|7|2A|8|@]|9|@]|C|$]]|$1|1D|3|-4|5|6|7|2B|8|@]|9|@]|C|$]]]|1E|$1F|$5|1G|1H|1I|C|$1J|1K]]|1L|$5|1G|1H|1I|C|$1J|1M]]]]

This is a good question. The problem was not obvious to me until I looked at the <a href="http://opencsv.sourceforge.net/apidocs/au/com/bytecode/opencsv/CSVParser.html" rel="nofollow">javadocs</a> and realised that opencsv only supports a character as a separator, not a string....

Here's a couple of suggested work-arounds (Examples in Groovy can be converted to java).

<h1>Ignore implicit intermediary fields</h1>

Continue to Use OpenCSV, but ignore the empty fields. Obviously this is a cheat, but it will work fine for parsing well-behaved data. 

<pre><code> CSVParser csv = new CSVParser((char)'|')

 String[] result = csv.parseLine('J||Project report||"F, G, I"||1')

 assert result[0] == "J"
 assert result[2] == "Project report"
 assert result[4] == "F, G, I"
 assert result[6] == "1"
</code></pre>

or

<pre><code> CSVParser csv = new CSVParser((char)'|')

 String[] result = csv.parseLine('J|||Project report|||"F, G, I"|||1')

 assert result[0] == "J"
 assert result[3] == "Project report"
 assert result[6] == "F, G, I"
 assert result[9] == "1"
</code></pre>

<h1>Roll your own</h1>

Use the Java String <a href="http://docs.oracle.com/javase/1.4.2/docs/api/java/util/StringTokenizer.html" rel="nofollow">tokenizer</a> method. 

<pre><code> def result = 'J|||Project report|||"F, G, I"|||1'.tokenize('|||')

 assert result[0] == "J"
 assert result[1] == "Project report"
 assert result[2] == "\"F, G, I\""
 assert result[3] == "1"
</code></pre>

Disadvantage of this approach is that you lose the ability to ignore quote characters or escape separators..

<h1>Update</h1>

Instead of pre-processing the data, altering it's content, why not combine both of the above approaches in a two step process:

<ol>
<li>Use the "roll your own" to first validate the data. Split each line and prove that it contains the requiste number of fields.</li>
<li>Use the "field ignoring" approach to parse the validated data, secure in the knowledge that the correct number of fields have been specified.</li>
</ol>

Not very efficient, but possibly easier that writing your own CSV parser :-)

blocks|key|2738895|text|这些解决方案对我都不起作用，因为它们都假设您可以将整个CSV文件存储在内存中，从而允许简单的replaceAll类型操作。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2738896|我知道这很慢，但我用的是Scanner。它有许多令人惊讶的功能，并使滚动您自己的简单CSV阅读器与任何字符串，您想要的记录分隔符。它还可以让您解析非常大的CSV文件(我以前做过10+It的单个文件)，因为您可以一次读取一条记录。|2738897|Scanner+s+=+new+Scanner(inputStream,+"UTF-8").useDelimiter(">%7C\n");|code-block|syntax|javascript|2738898|我更喜欢更快的解决方案，但我还没有找到支持它的库。自2017年初以来，FasterXML已经开放了一张票来添加这一功能：https://github.com/FasterXML/jackson-dataformats-text/issues/14|2738899|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/FasterXML/jackson-dataformats-text/issues/14^0|1A|A|0|C|7|0|0|1O|1R|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@$9|X|A|Y|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|Z|8|@$9|10|A|11|B|C]]|D|@]|E|$]]|$1|H|3|I|5|J|7|12|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|13|8|@]|D|@$9|14|A|15|1|16]]|E|$]]|$1|O|3|-4|5|6|7|17|8|@]|D|@]|E|$]]]|P|$Q|$5|R|S|T|E|$U|V]]]]

None of these solutions worked for me, because they all assumed you could store the entire CSV file in memory allowing for easy <code>replaceAll</code> type actions.

I know it's slow, but I went with <code>Scanner</code>. It has a surprising number of features, and makes rolling your own simple CSV reader with any string you want as a record delimiter. It also lets you parse very large CSV files (I've done 10GB single files before), since you can read records one at a time.

<pre><code>Scanner s = new Scanner(inputStream, "UTF-8").useDelimiter("&gt;|\n");
</code></pre>

I would prefer a faster solution, but no library I've found supports it. FasterXML has had an open ticket to add this funcitonality since early 2017: <a href="https://github.com/FasterXML/jackson-dataformats-text/issues/14" rel="nofollow noreferrer">https://github.com/FasterXML/jackson-dataformats-text/issues/14</a>

Is there any Java open source library that supports multi-character (i.e., String with length > 1) separators (delimiters) for CSV?

By definition, CSV = Comma-Separated Values data with a single character (',') as the delimiter. However, many other single-character alternatives exist (e.g., tab), making CSV to stand for "Character-Separated Values" data (essentially, DSV: Delimiter-Separated Values data).

Main Java open source libraries for CSV (e.g., <a href="http://opencsv.sourceforge.net/" rel="noreferrer">OpenCSV</a>) support virtually any character as the delimiter, but not string (multi-character) delimiters. So, for data separated with strings like "|||" there is no other option than preprocessing the input in order to transform the string to a single-character delimiter. From then on, the data can be parsed as single-character separated values.

It would therefore be nice if there was a library that supported string separators natively, so that no preprocessing was necessary. This would mean that CSV now standed for "CharSequence-Separated Values" data. :-)

Java CSV parser with string separator (multi-character)

文件存储

Java

有没有Java开源库支持CSV的multi-character (长度大于1的字符串)分隔符(分隔符)？根据定义，CSV =以逗号分隔的数据以单个字符('，')作为分隔符。然而，还有许多其他的单字符替代(例如，制表符)，使得CSV代表“字符分隔值”数据(本质上是DSV:分隔符分隔值数据)。CSV的主要Java开源库(例...

问带字符串分隔符(多字符)的Java CSV解析器
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