Python库 | pyimporters-dummy-0.1.264.tar.gz

## Requirements - Python 3.8+ - Flit to put Python packages and modules on PyPI - Pydantic for the data parts. ## Installation ``` pip install flit pip install pyimporters-dummy ``` ## Publish the Python Package to PyPI - Increment the version of your package in the `__init__.py` file: ``` """An amazing package!""" __version__ = 'x.y.z' ``` - Publish ``` flit publish ``` ## Write your own pyimporters plugin - Git clone the pyimporters_dummy project ``` git clone git@bitbucket.org:kairntech/pyimporters_dummy.git ``` - Rename the project with your own format name <new_format> ``` mv pyimporters_dummy pyimporters_<new_format> ``` - Delete the .git directory ``` rm -r -f pyimporters_<new_format>/.git ``` - Change to the new pyimporters_<new_format> directory ``` cd pyimporters_<new_format> ``` - Rename the package directory project ``` mv pyimporters_dummy pyimporters_<new_format> ``` - Rename the python file implementation ``` mv pyimporters_<new_format>/dummy.py pyimporters_<new_format>/<new_format>.py ``` - Rename the python tests file implementation ``` mv tests/test_dummy.py tests/test_<new_format>.py ``` - Edit the pyproject.toml file to change a few lines and add your additional requirements ``` [tool.flit.metadata] module = "pyimporters_<new_format>" ... requires = [ "pyimporters_plugins>=0.1.61", "additional_requirement1", "additional_requirement2", ... "additional_requirementN", ] dist-name = "pyimporters-<new_format>" ... [tool.flit.entrypoints."pyimporters.plugins"] <new_format> = "pyimporters_<new_format>.<new_format>:NewFormatKnowledgeParser" ``` - Write the implementation and test of your new format in python using your favorite IDE ``` @dataclass class NewFormatOptions(KnowledgeParserOptions): """ Options for the new format knowledge import """ foo : str = Query("bar", description="Dummy parameter") NewFormatOptionsModel = NewFormatOptions.__pydantic_model__ class NewFormatKnowledgeParser(KnowledgeParserBase): def parse(self, source : Path, options: Union[KnowledgeParserOptions, Dict[str, Any]], bar : Bar) -> Generator[Term, None, None]: options = NewFormatOptions(**options) if isinstance(options, dict) else options # Initialize the progress indicator number of terms to read so that the progress indicator can send feedback to the end user bar.max = 100 bar.start() # yield as many terms as you want, advancing the progress indicator each time bar.next() yield Term(identifier=options.foo, preferredForm=options.foo) # Terminate the progress indicator bar.finish() @classmethod def get_schema(cls) -> KnowledgeParserOptions: return NewFormatOptions @classmethod def get_model(cls) -> Type[BaseModel]: return NewFormatOptionsModel ```