litio 1.6.1

A simple tool for testing

A simple tool for testing

litio

how to use

example 1: The basics

install

pip install litio

run

litio run

litio.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.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.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 commands

• run

  • Action: Runs the tests.
  • parameters:
    • --verbose(aliases: -V): Prints the full function call.
    • --output(aliases: -o): The style of the output. It can be capybara or classic or you can install a custom style.
    • --ai/--no-ai: enable/disable auto-fix using AI.

• install

  • Action: Installs a Litio package.
  • parameters:
    • module: The name of the module to install, must be in format author/module or author/module@version.
    • --upgrade(aliases: -u): install the latest version of the module.

• uninstall

• Action: Uninstalls a Litio package.
• parameters:
  • module: The name of the module to uninstall, must be in format author/module.

Litio config file reference

The config file must be in YAML format and named litio.yml

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

How can i create a module?

Every module must have a litio.py file in root directory.

Example module for output styles:

litio.py

import ... # your dependecies here

def my_own_output_style(args):
    ... # your code here

litio = {
  'output': {
    'my-own-output-style-name': my_own_output_style
  }
}

When your module is ready to use, you can publish it to github and install it using litio install you/your-module-name example: litio install lizardwine/litio-package

litio dictionary reference

you can repleace any litio function

• output: you can add and replace any output style

  • classic: classic output
  • capybara: capybara output

• options: you can add and replace any option for litio command

  • --version: shows the litio version and exit

• sub_commands: you can add and replace any sub command

  • run: run the tests in litio.yml
  • install: install a module
  • uninstall: uninstall a module

• utils: you can add and replace any utility

  • extract_function_code: extract the code of a function from a file
  • Args: set self attributes from a dictionary
  • OutputArgs: an organizer for the output arguments
  • params_to_dict: convert a list of parameters to a dictionary
  • eval_param_values: evaluate the values of a list of parameters
  • Kwargs: set self attributes from a keyword arguments

• tester: you can replace the tester function

  • test: test a function with the given inputs and expected values

• ai: you can add or replace any AI powered function

  • BugFixer: class for bug fixing
  • fix_bug: fix a bug in a function with BugFixer

If you module has dependencies, you must add them in requirements.txt file in root directory.