LLY-DML is part of the LILY project and is a Quantum Machine Learning model. It uses so-called L-Gates. These gates are Machine Learning gates that modify their state based on an input to map to a desired state of an input.
This PR refactors the Reader class by removing its previous methods and introducing the following new methods to align with the updated specifications:
fileCheck()
checkLog()
createLog()
dataConsistency()
Additionally:
Unit Testing: A new file, tests/test_reader.py, includes unit tests for each method in the Reader class. These tests are executed using pytest:
pytest tests/test_reader.py
Each test is autonomous, creating its own necessary environment to verify the behavior of Reader methods.
Code Consistency: The main.py and test.py files in the root directory have been updated to maintain compatibility with the refactored Reader class.
Reader Class Update as per Issue #18
This PR refactors the
Readerclass by removing its previous methods and introducing the following new methods to align with the updated specifications:fileCheck()checkLog()createLog()dataConsistency()Additionally:
Unit Testing: A new file,
tests/test_reader.py, includes unit tests for each method in theReaderclass. These tests are executed usingpytest:Each test is autonomous, creating its own necessary environment to verify the behavior of
Readermethods.Code Consistency: The
main.pyandtest.pyfiles in the root directory have been updated to maintain compatibility with the refactoredReaderclass.Fixes #18