Pytest data parameterization & data driven

Parameterization uses ：
@pytest.mark.parametrize(argnames,argvalues)
argnames： Variables to parameterize ,string（ Comma separated ）,list,tuple
argvalues： Parameterized values ,list,list[tuple]

Use string：@pytest.mark.parametrize(‘a,b’,[(10,20),(30,40)])
Use list：@pytest.mark.parametrize([‘a’,‘b’],[(10,20),(30,40)])
Use tuple：@pytest.mark.parametrize((‘a’,‘b’),[(10,20),(30,40)])

Use yaml Data parameterization ：
yaml Realization list：
list
- 10
- 20
- 30
yaml Implement Dictionary ：
dict
by:id
locator:name
action:click
yaml Nesting ：
-
- by:id
- locator:name
- action:click
load yaml file ：yaml.safe_load(open(“./test.yaml”))

Data driven
brief introduction
Data driven is the change of data, which drives the execution of automatic test , Finally, it causes the test results to change . Simply speaking , It's the application of parameterization . Test cases with small amount of data can use code parameterization to realize data-driven , In case of large amount of data, it is recommended to use a structured file （ for example yaml,json） To store data , Then read the data in the test case .
Application scenarios
App、web、 Interface automation testing
1. Data driven test steps
2. Data driven test data
3. Configured data driver