我知道我的回答很具体，但是如果已经安装了PHP和Symfony，那么使用Symfony的YAML解析器会非常方便。

例如:

php -r "require '$SYMFONY_ROOT_PATH/vendor/autoload.php'; \
    var_dump(\Symfony\Component\Yaml\Yaml::parse(file_get_contents('$YAML_FILE_PATH')));"

这里我只是简单地使用var_dump来输出解析后的数组，当然你还可以做更多…：）

很难说，因为这取决于您希望解析器从YAML文档中提取什么。对于简单的情况，你可以使用grep、cut、awk等。对于更复杂的解析，您需要使用成熟的解析库，如Python的PyYAML或YAML::Perl。

可以将一个小脚本传递给一些解释器，比如Python。使用Ruby和它的YAML库的简单方法如下:

$ RUBY_SCRIPT="data = YAML::load(STDIN.read); puts data['a']; puts data['b']"
$ echo -e '---\na: 1234\nb: 4321' | ruby -ryaml -e "$RUBY_SCRIPT"
1234
4321

，其中data是来自yaml的值的散列(或数组)。

作为奖励，它可以很好地解析杰基尔的正面问题。

ruby -ryaml -e "puts YAML::load(open(ARGV.first).read)['tags']" example.md

另一种选择是将YAML转换为JSON，然后使用jq与JSON表示进行交互，从其中提取信息或编辑信息。

我写了一个简单的bash脚本，包含这个胶水-见Y2J项目在GitHub上

Whenever you need a solution for "How to work with YAML/JSON/compatible data from a shell script" which works on just about every OS with Python (*nix, OSX, Windows), consider yamlpath, which provides several command-line tools for reading, writing, searching, and merging YAML, EYAML, JSON, and compatible files. Since just about every OS either comes with Python pre-installed or it is trivial to install, this makes yamlpath highly portable. Even more interesting: this project defines an intuitive path language with very powerful, command-line-friendly syntax that enables accessing one or more nodes.

针对您的具体问题，在使用Python的本地包管理器或您的操作系统的包管理器安装yamlpath之后(yamlpath可以通过RPM对某些操作系统提供):

#!/bin/bash
# Read values directly from YAML (or EYAML, JSON, etc) for use in this shell script:
myShellVar=$(yaml-get --query=any.path.no[matter%how].complex source-file.yaml)

# Use the value any way you need:
echo "Retrieved ${myShellVar}"

# Perhaps change the value and write it back:
myShellVar="New Value"
yaml-set --change=/any/path/no[matter%how]/complex --value="$myShellVar" source-file.yaml

不过，您没有指定数据是一个简单的Scalar值，因此让我们提高赌注。如果你想要的结果是一个数组呢?更有挑战性的是，如果它是一个哈希数组，而你只想要每个结果的一个属性呢?进一步假设您的数据实际上分布在多个YAML文件中，并且您需要在单个查询中获得所有结果。这是一个更有趣的问题。所以，假设你有这两个YAML文件:

文件:data1.yaml

---
baubles:
  - name: Doohickey
    sku: 0-000-1
    price: 4.75
    weight: 2.7g
  - name: Doodad
    sku: 0-000-2
    price: 10.5
    weight: 5g
  - name: Oddball
    sku: 0-000-3
    price: 25.99
    weight: 25kg

文件:data2.yaml

---
baubles:
  - name: Fob
    sku: 0-000-4
    price: 0.99
    weight: 18mg
  - name: Doohickey
    price: 10.5
  - name: Oddball
    sku: 0-000-3
    description: This ball is odd

在应用数据2的更改后，如何仅报告库存中每个项目的sku。Yaml到data1。Yaml，所有从一个shell脚本?试试这个:

#!/bin/bash
baubleSKUs=($(yaml-merge --aoh=deep data1.yaml data2.yaml | yaml-get --query=/baubles/sku -))

for sku in "${baubleSKUs[@]}"; do
    echo "Found bauble SKU:  ${sku}"
done

你只需要几行代码就能得到你想要的东西:

Found bauble SKU:  0-000-1
Found bauble SKU:  0-000-2
Found bauble SKU:  0-000-3
Found bauble SKU:  0-000-4

如您所见，yamlpath将非常复杂的问题转化为简单的解决方案。注意，整个查询是作为一个流处理的;查询没有更改YAML文件，也没有临时文件。

I realize this is "yet another tool to solve the same question" but after reading the other answers here, yamlpath appears more portable and robust than most alternatives. It also fully understands YAML/JSON/compatible files and it does not need to convert YAML to JSON to perform requested operations. As such, comments within the original YAML file are preserved whenever you need to change data in the source YAML file. Like some alternatives, yamlpath is also portable across OSes. More importantly, yamlpath defines a query language that is extremely powerful, enabling very specialized/filtered data queries. It can even operate against results from disparate parts of the file in a single query.

If you want to get or set many values in the data at once -- including complex data like hashes/arrays/maps/lists -- yamlpath can do that. Want a value but don't know precisely where it is in the document? yamlpath can find it and give you the exact path(s). Need to merge multiple data file together, including from STDIN? yamlpath does that, too. Further, yamlpath fully comprehends YAML anchors and their aliases, always giving or changing exactly the data you expect whether it is a concrete or referenced value.

免责声明:我编写并维护了yamlpath，它是基于ruamel的。yaml是基于PyYAML的。因此，yamlpath完全符合标准。

使用Python的PyYAML或YAML::Perl等库最容易进行复杂的解析。

如果您希望将所有YAML值解析为bash值，请尝试此脚本。这也可以处理注释。参见下面的示例用法:

# pparse.py

import yaml
import sys
            
def parse_yaml(yml, name=''):
    if isinstance(yml, list):
        for data in yml:
            parse_yaml(data, name)
    elif isinstance(yml, dict):
        if (len(yml) == 1) and not isinstance(yml[list(yml.keys())[0]], list):
            print(str(name+'_'+list(yml.keys())[0]+'='+str(yml[list(yml.keys())[0]]))[1:])
        else:
            for key in yml:
                parse_yaml(yml[key], name+'_'+key)

            
if __name__=="__main__":
    yml = yaml.safe_load(open(sys.argv[1]))
    parse_yaml(yml)

test.yml

- folders:
  - temp_folder: datasets/outputs/tmp
  - keep_temp_folder: false

- MFA:
  - MFA: false
  - speaker_count: 1
  - G2P: 
    - G2P: true
    - G2P_model: models/MFA/G2P/english_g2p.zip
    - input_folder: datasets/outputs/Youtube/ljspeech/wavs
    - output_dictionary: datasets/outputs/Youtube/ljspeech/dictionary.dict
  - dictionary: datasets/outputs/Youtube/ljspeech/dictionary.dict
  - acoustic_model: models/MFA/acoustic/english.zip
  - temp_folder: datasets/outputs/tmp
  - jobs: 4
  - align:
    - config: configs/MFA/align.yaml
    - dataset: datasets/outputs/Youtube/ljspeech/wavs
    - output_folder: datasets/outputs/Youtube/ljspeech-aligned

- TTS:
  - output_folder: datasets/outputs/Youtube
  - preprocess:
    - preprocess: true
    - config: configs/TTS_preprocess.yaml # Default Config 
    - textgrid_folder: datasets/outputs/Youtube/ljspeech-aligned
    - output_duration_folder: datasets/outputs/Youtube/durations
    - sampling_rate: 44000 # Make sure sampling rate is same here as in preprocess config

需要YAML值的脚本:

yaml() {
    eval $(python pparse.py "$1")
}

yaml "test.yml"

# What python printed to bash:

folders_temp_folder=datasets/outputs/tmp
folders_keep_temp_folder=False
MFA_MFA=False
MFA_speaker_count=1
MFA_G2P_G2P=True
MFA_G2P_G2P_model=models/MFA/G2P/english_g2p.zip
MFA_G2P_input_folder=datasets/outputs/Youtube/ljspeech/wavs
MFA_G2P_output_dictionary=datasets/outputs/Youtube/ljspeech/dictionary.dict
MFA_dictionary=datasets/outputs/Youtube/ljspeech/dictionary.dict
MFA_acoustic_model=models/MFA/acoustic/english.zip
MFA_temp_folder=datasets/outputs/tmp
MFA_jobs=4
MFA_align_config=configs/MFA/align.yaml
MFA_align_dataset=datasets/outputs/Youtube/ljspeech/wavs
MFA_align_output_folder=datasets/outputs/Youtube/ljspeech-aligned
TTS_output_folder=datasets/outputs/Youtube
TTS_preprocess_preprocess=True
TTS_preprocess_config=configs/TTS_preprocess.yaml
TTS_preprocess_textgrid_folder=datasets/outputs/Youtube/ljspeech-aligned
TTS_preprocess_output_duration_folder=datasets/outputs/Youtube/durations
TTS_preprocess_sampling_rate=44000

使用bash访问变量:

echo "$TTS_preprocess_sampling_rate";
>>> 44000