1. YAML简介
YAML是可读性高,用来表达数据序列化格式的,专用于写配置文件的语言。YAML文件其实也是一种配置文件类型,后缀名是.yaml或.yml都可以。其以数据为中心,使用空白,缩进,分行组织数据,从而使得表示更加简洁。
2. 语法规则
- 大小写敏感
- 使用缩进表示层级关系
- 使用空格键缩进,而非Tab键缩进
- 缩进的空格数目不重要,只需要相同层级的元素左侧对齐
- 文件中的字符串不需要使用引号标注,但若字符串包含有特殊字符则需用引号标注
- 注释标识为 #
3. 文件数据结构
对象:键值对的集合(简称"映射或字典")
键值对用冒号 “:” 结构表示 冒号与值之间需用空格分隔
数组:一组按序排列的值(简称"序列或列表")
数组前加有 “-” 符号 符号与值之间需用空格分隔
纯量(scalars):单个的、不可再份的值(如:字符串、bool值、整数、浮点数、时间、日期、null等)
None值可用null,也可用~
表示
4. YAML数据格式示例
# 对象:yaml键值对;即Python中字典
user: 'admin'
pwd: 'admin@123'
site: "www.yaml.com"
# 解析后: {'user': 'admin', 'password': 'admin@123', 'site': 'www.yaml.com'}
# 2. 数组:yaml键值对中嵌套数组
user2:
- a
- b
- c
user3:
- d
# 解析后:{'user2':['a','b','c'],'user3':['d']}
# 3. 纯量
val_name: name # 字符串: {'val_name': 'name'}
spec_val: "name\n" # 特殊字符串: {'spec_val': 'name\n'}
pi_val: 3.14 # 数字: {'pi_val': 3.14}
bol_val: true # 布尔值: {'bol_val': true}
nul_val: null # null值: {'nul_val': None}
nul_val: ~ # null值: {'nul_val': None}
time_val: 2023-02-03t22:33:22.33-03:00 # 时间值:{'time_val': datetime.datetime(2023, 2, 3, 22, 33, 22, 330000)}
date_val: 2024-01-01 # 日期值:{'date_val': datetime.date(2024, 1, 1)}
# 4. 引用
name: &name 白云
tester: *name
# 相当于
name: 白云
tester: 白云
# 解析后内容:{'name': '白云', 'tester': '白云'}
# 5. 强制转换
str: !!str 3.14
int: !!int "666"
# 输出: {'str': '3.14','int': 123}
5. 安装yaml库
pip install pyyaml
6. 读取YAML
6.1 读取键值对或嵌套键值对
yaml文件内容为:
user1:
name: xm
stu: 101
user2:
name: xh
stu: 102
user3:
name: xl
stu: 103
程序代码:
import yaml
import os
class ReadYAML(object):
def read_yaml(self,yaml_file):
with open(yaml_file,'r',encoding='utf-8') as f:
file_data = f.read()
print("file_data类型:",type(file_data))
data = yaml.safe_load(file_data)
print("data类型:",type(data))
return data
if __name__ == "__main__":
base_name = os.path.dirname(os.path.realpath(__file__))
yaml_path = os.path.join(base_name,'test.yaml')
ry = ReadYAML()
res = ry.read_yaml(yaml_path)
print(res)
输出结果:
file_data类型: <class 'str'>
data类型: <class 'dict'>
{'user1': {'name': 'xm', 'stu': 101}, 'user2': {'name': 'xh', 'stu': 102}, 'user3': {'name': 'xl', 'stu': 103}}
6.2 读取数组类型
yaml文件内容为:
class1:
- stu1
- stu2
- stu3
class2:
- stu2
程序代码:
import yaml
import os
class ReadArraysYAML(object):
def read_yaml(self,yaml_file):
with open(yaml_file,'r',encoding='utf-8') as f:
file_data = f.read()
# print("file_data类型:",type(file_data))
data = yaml.safe_load(file_data)
# print("data类型:",type(data))
return data
if __name__ == "__main__":
base_name = os.path.dirname(os.path.realpath(__file__))
yaml_path = os.path.join(base_name,'arrays.yaml')
ry = ReadArraysYAML()
res = ry.read_yaml(yaml_path)
print(res)
输出结果:
{'class1': ['stu1', 'stu2', 'stu3'], 'class2': ['stu2']}
6.3 多文档同在一份yaml文件中时的读取方法
yaml文件内容:
# 分段yaml文件中存在多个文档
---
animal1: dog
age: 1
---
animal2: cat
age: 2
程序代码:
"""
多文档同在一份yaml文件中时的读取方法(使用yaml.safe_load_all())
"""
import yaml
import os
def get_yaml_load_all(yaml_file):
file = open(yaml_file,'r',encoding='utf-8')
file_data = file.read()
file.close()
all_data = yaml.safe_load_all(file_data)
for data in all_data:
print(data)
if __name__ == "__main__":
current_path = os.path.dirname(__file__)
print(current_path)
yaml_path = os.path.join(current_path,'muti.yaml')
get_yaml_load_all(yaml_path)
输出结果:
d:\PyProject\YAML
{'animal1': 'dog', 'age': 1}
{'animal2': 'cat', 'age': 2}
6.4 向YAML文档写入
程序代码:
"""
使用yaml.dump()方法将列表或字典数据写入进已存在的yaml文档
"""
import yaml
import os
def generate_yaml_doc(yaml_file):
py_object = {'school':'Fxxking U','student':['stu1','stu2']}
file = open(yaml_file,'w',encoding='utf-8')
yaml.safe_dump(py_object,file)
file.close()
if __name__ == "__main__":
current_path = os.path.dirname(__file__)
print(current_path)
yaml_path = os.path.join(current_path,'generateYAML.yaml')
generate_yaml_doc(yaml_path)
写入后,YAML文档内容:
school: Fxxking U
student:
- stu1
- stu2
注:若想要以追加的形式写入,只需将open()中的’w’改为’a’即可
6.5 更新/修改 YAML文件内容
修改前YAML文件内容:
school: Fxxking U
student:
- stu1
- stu2
程序代码:
import yaml
import os
from readArraysYAML import ReadArraysYAML
def update_yaml(k,v,yaml_file):
readY = ReadArraysYAML()
old_data = readY.read_yaml(yaml_file)
old_data[k] = v # 修改读取的数据,如果k不存在则新增一组键值对
with open(yaml_file,'w',encoding='utf-8') as f:
yaml.safe_dump(old_data,f)
if __name__ == "__main__":
current_path = os.path.dirname(__file__)
yaml_path = os.path.join(current_path,'generateYAML.yaml')
k = 'school'
v = 'SZ U'
update_yaml(k,v,yaml_path)
修改后,YAML文件内容:
school: SZ U
student:
- stu1
- stu2
7. 使用ruamel模块将数据转换为标准的yaml内容
安装ruamel库
pip install ruamel.yaml
程序代码:
from ruamel import yaml
import os
def generate_yaml_doc_ruamel(yaml_file):
py_object = {'file_type':'ruamel_yaml','school':'Fxxking U','student':['c','d']}
with open(yaml_file,'w',encoding='utf-8') as f:
yaml.dump(py_object,f,Dumper=yaml.RoundTripDumper)
if __name__ == "__main__":
current_path = os.path.dirname(__file__)
yaml_path = os.path.join(current_path,'ruamelGenerateYAML.yaml')
generate_yaml_doc_ruamel(yaml_path)
print("写入成功!")
写入后,YAML文件内容:
file_type: ruamel_yaml
school: Fxxking U
student:
- c
- d
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