序列化
序列化就是将对象转化成文件
python转成json
python
import json
data = {
"数字": [1, 1.1, -1],
"字符串": ["aaaa", 'bbbb'],
"布尔值": [True, False],
"空值": None,
"列表": [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
"字典": [{"a": 1, "b": 2}, {"c": 3}]
}
with open("data.json", "w", encoding="utf-8") as f:
s = json.dumps(data, ensure_ascii=False)
f.write(s)
python转成yaml
python
import yaml
data = {
"数字": [1, 1.1, -1],
"字符串": ["aaaa", 'bbbb'],
"布尔值": [True, False],
"空值": None,
"列表": [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
"字典": [{"a": 1, "b": 2}, {"c": 3}]
}
with open("data.yaml", "w", encoding="utf-8") as f:
s = yaml.safe_dump(data, allow_unicode=True)
f.write(s)
反序列化
反序列化就是将文件转化成对象
json转成python
python
import json
with open("data.json", "r", encoding="utf-8") as f:
s = json.loads(f.read())
print(s)
yaml转成python
python
import yaml
with open("data.yaml", "r", encoding="utf-8") as f:
s = yaml.safe_load(f.read())
print(s)
# yaml可以完全兼容json
with open("data.json", "r", encoding="utf-8") as f:
s = yaml.safe_load(f.read())
print(s)
pytest的DDT数据驱动
**DDT:**数据驱动测试
**DDT数据驱动的本质:**测试框架根据数据文件的内容,来决定如何执行测试用例
实现思路:
(1)将用例参数的数据存放在(.json、.yaml等)文件中
(2)读取文件中的数据
(3)将数据传递给pytest(根据数据创建用例)
(4)在用例中使用数据
举例:
将从ddt_yaml.yaml文件中读取的数据内容打包成列表传递给@pytest.mark.parametrize()
yaml里面的内容(这里给出的数据不是纯yaml语法的格式):
python
- [1, 2]
- [2, 3]
- [3, 4]
- [0, -1]
用例实现:
python
mport pytest
import yaml
def add(a, b):
return a + b
with open("ddt_yaml.yaml", "r", encoding="utf-8") as f:
l = yaml.safe_load(f.read())
print(l)
@pytest.mark.parametrize(
"a, b",
l,
)
def test_abc(a, b):
c = add(a, b)
assert c == a + b
优点
-
方便用例的增加和减少(只需要改变文件里面的数据组数就可以控制用例数量)
-
方便对用例内容的修改