YAML文件读取和写入
YAML文件读取和写入
前言
yaml文件是什么？yaml文件其实也是一种配置文件类型，相比较ini，conf，py配置文件来说，更加的简洁，操作也更加简单，同时可以存放不同类型的数据，不会改变原有数据类型，所有的数据类型在读取时都会原样输出，yaml文件依赖python的第三方库PyYaml模块，pip install PyYaml
读取yaml
1.读取字典
1.1单组数据
config.yaml
logger:
name: python25
level: WARNING
description: 12
excel:
file: ~
sheet: null
yaml_read.py
import yaml
def read_yaml():
with open("config.yaml", encoding='utf-8') as f:
data = yaml.load(f.read(), Loader=yaml.FullLoader)
print(data)
print(data["logger"]["name"])
read_yaml()
输出
{'logger': {'name': 'python25', 'level': 'WARNING', 'description': 12}, 'excel': {'file': None, 'sheet': None}}
python25
1.2多组字典数据读取
config.yaml
logger:
name: python25
level: WARNING
description: 12
excel:
file: ~
sheet: null
---
student:
name: lihua
age: 12
yaml_read.py
import yaml
def read_yaml():
with open("config.yaml", encoding='utf-8') as f:
data = yaml.load_all(f.read(), Loader=yaml.FullLoader)
print(data)
for i in data:
print(i)
read_yaml()
输出：
<generator object load_all at 0x0000024FA91894C0>
{'logger': {'name': 'python25', 'level': 'WARNING', 'description': 12}, 'excel': {'file': None, 'sheet': None}}
{'student': {'name': 'lihua', 'age': 12}}
通过输出结果及yaml存储内容可以看出，当yaml文件存储多组数据在一个yaml文件中时，需要使用3个横杆分割，读取数据时需要使用load_all方法，而且此方法返回一个生成器，需要使用for循环迭代读取每一组数据下面再看一下yaml如何存储列表类型数据
2 读取列表
config.yaml
- name
- age
- class
yaml_read.py
import yaml
def read_yaml():
with open("config.yaml", encoding='utf-8') as f:
data = yaml.load(f.read(), Loader=yaml.FullLoader)
print(data)
read_yaml()
输出
['name', 'age', 'class']
3读取元祖
config.yaml
--- !!python/tuple # 列表转成元组
- name
- age
- class
---
age: !!str 18 # int 类型转换为str
read_yaml.py
import yaml
def read_yaml():
with open("config.yaml", encoding='utf-8') as f:
data = yaml.load_all(f.read(), Loader=yaml.FullLoader)
print(data)
for i in data:
print(i)
read_yaml()
输出
<generator object load_all at 0x000001DD08D694C0>
['name', 'age', 'class']
{'age': '18'}
4 写入yaml文件
4.1 写入单组数据
response = {
"status": 1,
"code": "1001",
"data": [
{
"id": 80,
"regname": "toml",
"pwd": "QW&@JBK!#&#($*@HLNN",
"mobilephone": "13691579846",
"leavemount": "0.00",
"type": "1",
"regtime": "2019-08-14 20:24:45.0"
},
{
"id": 81,
"regname": "toml",
"pwd": "QW&@JBK!#&#($*@HLNN",
"mobilephone": "13691579846",
"leavemount": "0.00",
"type": "1",
"regtime": "2019-08-14 20:24:45.0"
}
],
"msg": "获取用户列表成功"
}
import yaml
def write_yaml():
with open("config.yaml", encoding='utf-8',mode='w') as f:
try:
yaml.dump(data=response,stream=f,allow_unicode=True)
except Exception as e:
print(e)
write_yaml()
写入后的文件config.yaml为
c
ode: '1001'
data:
- id: 80
leavemount: '0.00'
mobilephone: '13691579846'
pwd: QW&@JBK!#&#($*@HLNN
regname: toml
regtime: '2019-08-14 20:24:45.0'
type: '1'
- id: 81
leavemount: '0.00'
mobilephone: '13691579846'
pwd: QW&@JBK!#&#($*@HLNN
regname: toml
regtime: '2019-08-14 20:24:45.0'
type: '1'
msg: 获取用户列表成功
status: 1
4.2写入多组数据
response = {
"status": 1,
"code": "1001",
"data": [
{
"id": 80,
"regname": "toml",
"pwd": "QW&@JBK!#&#($*@HLNN",
"mobilephone": "13691579846",
"leavemount": "0.00",
"type": "1",
"regtime": "2019-08-14 20:24:45.0"
},
{
"id": 81,
"regname": "toml",
"pwd": "QW&@JBK!#&#($*@HLNN",
"mobilephone": "13691579846",
"leavemount": "0.00",
"type": "1",
"regtime": "2019-08-14 20:24:45.0"
}
],
"msg": "获取用户列表成功"
}
info = {
"name": "linux超",
"age": 18
}
import yaml
def write_yaml():
with open("config.yaml", encoding='utf-8',mode='w') as f:
try:
yaml.dump_all(documents=[response,info],stream=f,allow_unicode=True)
except Exception as e:
print(e)
write_yaml()
写入后的config.yaml为
code: '1001'
data:
- id: 80
leavemount: '0.00'
mobilephone: '13691579846'
pwd: QW&@JBK!#&#($*@HLNN
regname: toml
regtime: '2019-08-14 20:24:45.0'
type: '1'
- id: 81
leavemount: '0.00'
mobilephone: '13691579846'
pwd: QW&@JBK!#&#($*@HLNN
regname: toml
regtime: '2019-08-14 20:24:45.0'
type: '1'
msg: 获取用户列表成功
status: 1
---
age: 18
name: linux超
出处: 博客园Linux超的技术博客–https://www.cnblogs.com/linuxchao/
作者: Linux超