litio 1.3.0

A simple tool for testing

A simple tool for testing

litio

how to use

example 1: The basics

install

pip install litio

run

litio -c litio-config.yml

litio-config.yml:

name: My Awesome Title

tests:
  firsth-test: # test name
    path: ./tests/test1.py # path to python file
    functions: # functions list
      - pow: # function name
          inputs: # inputs
            # arguments with name of parameters
            base: 2
            exponent: 2
          expected:
            value: 4 # expected value
            comparator: Equals

test1.py:

def pow(base, exponent):
    return base**exponent

example 2: If something fails?

test2.py:

def pow(base, exponent):
    return base / exponent # it's obviously not working.

litio-config.yml:

name: My Awesome Title
api-key: YOUR_OPENAI_API_KEY_ENVIRONMENT_VARIABLE # the name of the environment variable, NOT THE API KEY!
tests:
  failed-test:
    path: ./tests/test2.py
    functions: 
      - pow:
          inputs:
            base: 2
            exponent: 2
          expected:
            value: 4
            comparator: Equals
          verbose: true 
          auto-fix: true # auto fix function using AI if call fails

how auto-fix works?

The "auto-fix" parameter instructs litio to use artificial intelligence to automatically repair and replace the function in the source code. If you prefer to confirm before consulting AI, you can use the "use-ai" parameter instead of "auto-fix."

example 3: if a tests is not ready yet?

test3.py:

def coming_soon():
    pass # it's not ready yet

litio-config.yml:

name: My Awesome Title
tests:
  not-ready-test:
    path: ./tests/test3.py
    functions: 
      - coming_soon:
          expected:
            value: i am not ready yet
            comparator: Equals
          ignore: true # ignore this test and continue

Litio config file reference

name paramater

• The name parameter is the title of the config file.

api-key parameter

• The api-key parameter is the name of the environment variable that contains the OpenAI API key, NOT THE API KEY!

output-style parameter

• The output-style parameter is the style of the output. It can be capybara or classic for now.

tests parameter

• The tests parameter is a dictionary of tests.

Tests structure

• The test name is the name of the test.
• The path parameter is the path to the Python file that contains the functions, methods or classmethods to test.
• The functions parameter is a list of functions to test.

Looks like this:

...
tests:
  first-test:
    path: ./src/utils.py
    functions:
      - add: # function name
          ...

Function structure

• The function name is the name of the function.
• The inputs parameter is a dictionary of inputs.
• The expected parameter is a dictionary with expected value and comparator.
• The verbose parameter is a boolean that indicates whether to print the full function call.
• The auto-fix parameter is a boolean that indicates whether to use AI to automatically fix the function. Only can be used with the Equals comparator.
• The use-ai parameter is a boolean that indicates whether to use AI to fix the function. Only can be used with the Equals comparator.
• The ignore parameter is a boolean that indicates whether to ignore the function.

Looks like this:

...
tests:
  first-test:
    path: ./src/utils.py
    functions:
      - FUNCTION_NAME: # (e.g. subtract)
          inputs:
            a: 1 # arguments with name of parameters
            b: 2 # must be the same as the name of the parameter
          expected:
            value: -1 # expected value
            comparator: Equals

Using methods

The syntax for a method is the same as that of a function, except that you need to add the "instance" parameter with the values to instantiate an object of that class.

Looks like this:

...
tests:
  first-test:
    path: ./src/utils.py
    functions:
      - Person.get_age:
          instance:
            name: John
            age: 30
          expected:
            value: 30
            comparator: Equals

The expected parameter

• The comparator parameter is the way to compare the expected value.
• The value parameter is the expected value.

• you can access the attributes of the returned object using the dot notation. Look like this:

...
- add_lists:
    inputs:
      a: [1, 2]
      b: [3, 4]
    expected:
      # the value returned is [1, 2, 3, 4]
      value.0: 1 # access to value[0]
      comparator: Equals

you also can use ranges:

...
- add_lists:
    inputs:
      a: [1, 2]
      b: [3, 4]
    expected:
      # the value returned is [1, 2, 3, 4]
      value.1;3: 1 # access to the range value[1:3]
      # NOTE: use semicolon(;) to indicate the range(e.g. value.1;3), not the colon(:) because conflict with the yaml syntax
      comparator: Equals

you can also use spacing in the range:

...
- add_lists:
    inputs:
      a: [1, 2]
      b: [3, 4]
    expected:
      value.;;2: [1, 3] # access to value[::2]
      comparator: Equals

you also can access to a key in the dictionary:

...
- add_dicts:
    inputs:
      a: {"a": 1, "b": 2}
      b: {"c": 3, "d": 4}
    expected:
      value.a: 1
      comparator: Equals

you also can use dot notation multiple times:

...
- add_dicts:
    inputs:
      a: {"a": {"b": 1}}
      b: {"c": {"d": 2}}
    expected:
      value.a.b: 1 # access to value["a"]["b"]
      comparator: Equals

if function returns an object, you can access to the attributes of that object using the dot notation:

...
- create_person_object:
    inputs:
      name: John
      age: 30
    expected:
      value.name: John # access to value.name
      comparator: Equals



## What comparators are there?

- `Equals`
- `Greater`
- `Less`
- `GreaterOrEqual`
- `LessOrEqual`
- `NotEquals`
- `Is`
- `IsNot`
- `IsNone`
- `IsNotNone`
- `IsInstance`
- `IsNotInstance`