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.

从技术上讲，YAML提供了比JSON多得多的东西(YAML v1.2是JSON的超集):

评论 锚和继承- 3个相同项目的例子: item1: &anchor_name 名称:测试 title:测试标题 第二条:* anchor_name item3: < <: * anchor_name #你可以添加额外的东西。 .．.

大多数情况下，人们不会使用这些额外的功能，主要的区别是YAML使用缩进，而JSON使用括号。这使得YAML(对于训练有素的眼睛)更加简洁和可读。

选择哪一个?

YAML额外的特性和简洁的符号使它成为配置文件(非用户提供的文件)的好选择。 JSON有限的特性、广泛的支持和更快的解析使其成为互操作性和用户提供数据的绝佳选择。

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

绕过深奥的理论

这回答了标题，而不是细节，因为大多数人只是从谷歌上的搜索结果中阅读标题，就像我一样，所以我觉得有必要从web开发人员的角度解释。

YAML uses space indentation, which is familiar territory for Python developers. JavaScript developers love JSON because it is a subset of JavaScript and can be directly interpreted and written inside JavaScript, along with using a shorthand way to declare JSON, requiring no double quotes in keys when using typical variable names without spaces. There are a plethora of parsers that work very well in all languages for both YAML and JSON. YAML's space format can be much easier to look at in many cases because the formatting requires a more human-readable approach. YAML's form while being more compact and easier to look at can be deceptively difficult to hand edit if you don't have space formatting visible in your editor. Tabs are not spaces so that further confuses if you don't have an editor to interpret your keystrokes into spaces. JSON is much faster to serialize and deserialize because of significantly less features than YAML to check for, which enables smaller and lighter code to process JSON. A common misconception is that YAML needs less punctuation and is more compact than JSON but this is completely false. Whitespace is invisible so it seems like there are less characters, but if you count the actual whitespace which is necessary to be there for YAML to be interpreted properly along with proper indentation, you will find YAML actually requires more characters than JSON. JSON doesn't use whitespace to represent hierarchy or grouping and can be easily flattened with unnecessary whitespace removed for more compact transport.

房间里的大象:互联网本身

JavaScript显然以巨大的优势统治着网络，JavaScript开发人员更喜欢使用JSON作为数据格式，以及流行的web api，因此在进行一般意义上的web编程时，很难争论使用YAML还是JSON，因为在团队环境中你可能会被压倒。事实上，大多数web程序员甚至不知道YAML的存在，更不用说考虑使用它了。

如果你正在做任何web编程，JSON是默认的方式，因为使用JavaScript时不需要翻译步骤，所以在这种情况下，你必须提出一个更好的参数来使用YAML而不是JSON。

如果您关心更好的解析速度，那么可以选择将数据存储在JSON中。我必须从其他用户修改文件的位置解析数据，因此我使用YAML，因为与JSON相比，它提供了更好的可读性。 你还可以在YAML文件中添加注释，这在JSON文件中是做不到的。

如果你不需要YAML有而JSON没有的任何特性，我更喜欢JSON，因为它非常简单，并且得到广泛支持(有很多语言的库)。YAML更复杂，支持更少。我不认为解析速度或内存使用会有太大的不同，而且可能不是程序性能的主要部分。