像这样访问YAML文件中列表的任何元素:

global:
  registry:
    url: dtr-:5000/
    repoPath:
  dbConnectionString: jdbc:oracle:thin:@x.x.x.x:1521:abcd

您可以使用以下python脚本:

import yaml

with open("/some/path/to/yaml.file", 'r') as f:
    valuesYaml = yaml.load(f, Loader=yaml.FullLoader)

print(valuesYaml['global']['dbConnectionString'])

#!/usr/bin/env python

import sys
import yaml

def main(argv):

    with open(argv[0]) as stream:
        try:
            #print(yaml.load(stream))
            return 0
        except yaml.YAMLError as exc:
            print(exc)
            return 1

if __name__ == "__main__":
    sys.exit(main(sys.argv[1:]))

例子:

defaults.yaml

url: https://www.google.com

environment.py

from ruamel import yaml

data = yaml.safe_load(open('defaults.yaml'))
data['url']

Read_yaml_file函数返回所有数据到字典中。

def read_yaml_file(full_path=None, relative_path=None):
    if relative_path is not None:
        resource_file_location_local = ProjectPaths.get_project_root_path() + relative_path
    else:
        resource_file_location_local = full_path

    with open(resource_file_location_local, 'r') as stream:
        try:
            file_artifacts = yaml.safe_load(stream)
        except yaml.YAMLError as exc:
            print(exc)
    return dict(file_artifacts.items())

使用Python 2+3(和unicode)读写YAML文件

# -*- coding: utf-8 -*-
import yaml
import io

# Define data
data = {
    'a list': [
        1, 
        42, 
        3.141, 
        1337, 
        'help', 
        u'€'
    ],
    'a string': 'bla',
    'another dict': {
        'foo': 'bar',
        'key': 'value',
        'the answer': 42
    }
}

# Write YAML file
with io.open('data.yaml', 'w', encoding='utf8') as outfile:
    yaml.dump(data, outfile, default_flow_style=False, allow_unicode=True)

# Read YAML file
with open("data.yaml", 'r') as stream:
    data_loaded = yaml.safe_load(stream)

print(data == data_loaded)

创建YAML文件

a list:
- 1
- 42
- 3.141
- 1337
- help
- €
a string: bla
another dict:
  foo: bar
  key: value
  the answer: 42

常见的文件结尾

.yml 和 .yaml

选择

CSV: Super simple format (read & write) JSON: Nice for writing human-readable data; VERY commonly used (read & write) YAML: YAML is a superset of JSON, but easier to read (read & write, comparison of JSON and YAML) pickle: A Python serialization format (read & write) ⚠️ Using pickle with files from 3rd parties poses an uncontrollable arbitrary code execution risk. MessagePack (Python package): More compact representation (read & write) HDF5 (Python package): Nice for matrices (read & write) XML: exists too *sigh* (read & write)

对于您的应用程序，以下内容可能很重要:

其他编程语言的支持 读写能力 紧凑性(文件大小)

请参见:数据序列化格式的比较

如果您正在寻找一种创建配置文件的方法，您可能想要阅读我的简短文章Python中的配置文件

我用ruame .yaml。详情和辩论在这里。

from ruamel import yaml

with open(filename, 'r') as fp:
    read_data = yaml.load(fp)

ruamel的用法yaml兼容(一些简单的可解决的问题)PyYAML的旧用法，正如我提供的链接中所述，使用

from ruamel import yaml

而不是

import yaml

它会解决你的大部分问题。

编辑:PyYAML并没有死，只是在另一个地方维护了它。