yaml文件的读写
一、yaml文件基本语法
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
安装:
pip install pyyaml
1.列表
列表类型书写主要是 - 和 空格 的结合,不同的缩进表示层级,如下:
- 1 - '2' - 3 - 4 - # 嵌套列表的话就一个-加一个空格 - 5 # - '' - - - 6 # 这表示嵌套两层列表 - 7 - - - id: 11 # 列表套字典 name: 22 like: 33 #结果: [1, '2', '3 - 4', [5, ''], [[6, 7, None]], None, {'id': 11, 'name': 22, 'like': 33}]
2.字典
列表类型书写语法主要是 冒号,不同的缩进表示层级,如下:
dic1: 1 dic2: '2' dic3: [666,777,888] # 也支持列表 dic4: {'11':22,'22':'33'} # 支持字典 dict5: # 字典嵌套 name: 'xx' pwd: 'oo' like: # 字典套列表 - girl - ball - xxoo: 'ooxx' # 再嵌套列表 ooxx: xxoo #{'dic1': 1, #'dic2': '2', #'dic3': [666, 777, 888], #'dic4': {'11': 22, '22': '33'}, #'dict5': {'name': 'xx', 'pwd': 'oo', 'like': ['girl', 'ball', {'xxoo': 'ooxx', 'ooxx': 'xxoo'}]} #}
3.元祖
元祖语法和列表一样,只是加了个声明:
!!python/tuple # 列表转成元组声明语法 - name - age - class # (1, 2, 3)
4.多组数据
多组数据的分隔语法是 ---
--- !!python/tuple # 列表转成元组声明语法 - name - age - class --- name: 111 age: 222 --- - 1 - 2 #<generator object load_all at 0x000001A1C8ED2820> 读取出来是个生成器对象,需要迭代取值 #('name', 'age', 'class') #{'name': 111, 'age': 222} #[1, 2]
二、yaml文件的读写
1.读取单组数据
import yaml #pip install pyyaml with open('_tuple.yaml', encoding='utf-8') as f: # res = yaml.load(f,Loader=yaml.FullLoader) res = yaml.full_load(f) # 上面的简便写法 print(res) print(type(res)) for line in res: print(line)
2.读取多组数据
import yaml #pip install pyyaml with open('_tuple.yaml', encoding='utf-8') as f: res = yaml.load_all(f,Loader=yaml.FullLoader) res = yaml.full_load_all(f) # 上面的简便写法,返回的是一个生成器对象,需要迭代取值 print(res) print(type(res)) for line in res: print(line)
3.写单组数据
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()
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.写多组数据
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
参考:https://www.cnblogs.com/linuxchao/