基准测试结果

下面是在Python和Perl上比较YAML和JSON加载时间的基准测试结果

JSON要快得多，但牺牲了一些可读性和注释等特性

测试方法

在一台快速机器上连续运行100次，平均秒数 数据集是一个3.44MB的JSON文件，包含从维基百科抓取的电影数据 https://raw.githubusercontent.com/prust/wikipedia-movie-data/master/movies.json 链接来源:https://github.com/jdorfman/awesome-json-datasets

结果

Python 3.8.3 timeit
    JSON:            0.108
    YAML CLoader:    3.684
    YAML:           29.763

Perl 5.26.2 Benchmark::cmpthese
    JSON XS:         0.107
    YAML XS:         0.574
    YAML Syck:       1.050

Perl 5.26.2 Dumbbench (Brian D Foy, excludes outliers)
    JSON XS:         0.102
    YAML XS:         0.514
    YAML Syck:       1.027

差异:

YAML, depending on how you use it, can be more readable than JSON JSON is often faster and is probably still interoperable with more systems It's possible to write a "good enough" JSON parser very quickly Duplicate keys, which are potentially valid JSON, are definitely invalid YAML. YAML has a ton of features, including comments and relational anchors. YAML syntax is accordingly quite complex, and can be hard to understand. It is possible to write recursive structures in yaml: {a: &b [*b]}, which will loop infinitely in some converters. Even with circular detection, a "yaml bomb" is still possible (see xml bomb). Because there are no references, it is impossible to serialize complex structures with object references in JSON. YAML serialization can therefore be more efficient. In some coding environments, the use of YAML can allow an attacker to execute arbitrary code.

观察:

Python programmers are generally big fans of YAML, because of the use of indentation, rather than bracketed syntax, to indicate levels. Many programmers consider the attachment of "meaning" to indentation a poor choice. If the data format will be leaving an application's environment, parsed within a UI, or sent in a messaging layer, JSON might be a better choice. YAML can be used, directly, for complex tasks like grammar definitions, and is often a better choice than inventing a new language.

从技术上讲，YAML是JSON的超集。这意味着，至少在理论上，YAML解析器可以理解JSON，但不一定反过来。

在“YAML:与JSON的关系”一节中可以看到官方规范。

总的来说，我喜欢YAML的某些东西是JSON中没有的。

正如@jdupont指出的，YAML在视觉上更容易看。事实上，YAML主页本身就是有效的YAML，但是它很容易被人阅读。 YAML能够使用“锚”引用YAML文件中的其他项。因此，它可以像在MySQL数据库中一样处理关系信息。 YAML在YAML文件中嵌入其他序列化格式(如JSON或XML)方面更加健壮。

在实践中，最后两点可能对您或我所做的事情都不重要，但从长远来看，我认为YAML将是一种更健壮、更可行的数据序列化格式。

现在，AJAX和其他web技术倾向于使用JSON。YAML目前更多地用于脱机数据处理。例如，它默认包含在基于c语言的OpenCV计算机视觉包中，而JSON则没有。

您将发现JSON和YAML的C库。YAML的库往往更新，但我过去使用它们没有遇到过麻烦。参见Yaml-cpp的例子。

GIT 和 YAML

其他答案都很好。先读这些。但是我还要加上另一个有时使用YAML的原因:git。

越来越多的编程项目使用git存储库进行分发和归档。而且，虽然git回购的历史记录可以同样存储JSON和YAML文件，但用于跟踪和显示文件更改的“diff”方法是面向行的。由于YAML被迫面向行，因此YAML文件中的任何小更改都更容易被人看到。

当然，JSON文件确实可以通过对字符串/键进行排序和添加缩进来“变得漂亮”。但这不是默认的，我很懒。

就我个人而言，我通常使用JSON进行系统到系统的交互。我经常将YAML用于配置文件、静态文件和跟踪文件。(我通常也避免添加YAML关系锚。生命太短暂，没有时间去寻找循环。)

此外，如果速度和空间真的是一个问题，我都不用。你可能想看看BSON。

基准测试结果

下面是在Python和Perl上比较YAML和JSON加载时间的基准测试结果

JSON要快得多，但牺牲了一些可读性和注释等特性

测试方法

在一台快速机器上连续运行100次，平均秒数 数据集是一个3.44MB的JSON文件，包含从维基百科抓取的电影数据 https://raw.githubusercontent.com/prust/wikipedia-movie-data/master/movies.json 链接来源:https://github.com/jdorfman/awesome-json-datasets

结果

Python 3.8.3 timeit
    JSON:            0.108
    YAML CLoader:    3.684
    YAML:           29.763

Perl 5.26.2 Benchmark::cmpthese
    JSON XS:         0.107
    YAML XS:         0.574
    YAML Syck:       1.050

Perl 5.26.2 Dumbbench (Brian D Foy, excludes outliers)
    JSON XS:         0.102
    YAML XS:         0.514
    YAML Syck:       1.027

I find both YAML and JSON to be very effective. The only two things that really dictate when one is used over the other for me is one, what the language is used most popularly with. For example, if I'm using Java, Javascript, I'll use JSON. For Java, I'll use their own objects, which are pretty much JSON but lacking in some features, and convert it to JSON if I need to or make it in JSON in the first place. I do that because that's a common thing in Java and makes it easier for other Java developers to modify my code. The second thing is whether I'm using it for the program to remember attributes, or if the program is receiving instructions in the form of a config file, in this case I'll use YAML, because it's very easily human read, has nice looking syntax, and is very easy to modify, even if you have no idea how YAML works. Then, the program will read it and convert it to JSON, or whatever is preferred for that language. In the end, it honestly doesn't matter. Both JSON and YAML are easily read by any experienced programmer.