ome-types: OME dataclasses for python
autogenerated dataclasses for a pythonic interface into the OME data model: http://www.openmicroscopy.org/Schemas/OME/2016-06
It converts the ome.xsd schema into a set of python dataclasses and types.
As an example, the
OME/Image
model will be rendered as the following dataclass in ome_types/model/image.py
from dataclasses import field
from datetime import datetime
from typing import List, Optional
from pydantic.dataclasses import dataclass
from .annotation_ref import AnnotationRef
from .experiment_ref import ExperimentRef
from .experimenter_group_ref import ExperimenterGroupRef
from .experimenter_ref import ExperimenterRef
from .imaging_environment import ImagingEnvironment
from .instrument_ref import InstrumentRef
from .microbeam_manipulation_ref import MicrobeamManipulationRef
from .objective_settings import ObjectiveSettings
from .pixels import Pixels
from .roi_ref import ROIRef
from .simple_types import ImageID
from .stage_label import StageLabel
@dataclass
class Image:
id: ImageID
pixels: Pixels
acquisition_date: Optional[datetime] = None
annotation_ref: List[AnnotationRef] = field(default_factory=list)
description: Optional[str] = None
experiment_ref: Optional[ExperimentRef] = None
experimenter_group_ref: Optional[ExperimenterGroupRef] = None
experimenter_ref: Optional[ExperimenterRef] = None
imaging_environment: Optional[ImagingEnvironment] = None
instrument_ref: Optional[InstrumentRef] = None
microbeam_manipulation_ref: List[MicrobeamManipulationRef] = field(default_factory=list)
name: Optional[str] = None
objective_settings: Optional[ObjectiveSettings] = None
roi_ref: List[ROIRef] = field(default_factory=list)
stage_label: Optional[StageLabel] = None
ome_autogen.convert_schema(url, target) is the main function. It accepts an
xsd file path (only test on an ome.xsd), and a target directory, and writes a
human-readable module, that will validate OME XML, provide pythonic method
naming, and provides full typing support for IDEs, etc...
Install
from pip
pip install ome-types
the autogenerated model is already included, but, to include dependencies
required for re-generating the model, use the [autogen] extra
pip install ome-types[autogen]
or, to install from source
git clone https://github.com/tlambert03/ome-types.git
cd ome-types
pip install -e .
Usage
The model is not checked into source, but it is included when you pip install
the package (and it will be built automatically at ome_types/model if it
doesn't exist the first time you import the package.)
from ome_types import OME # the root class
# or specific objects
from ome_types.model import Image, Pixels, Plate # etc...
There is a convenience function that accepts xml, and outputs a validated OME model (if it fails validation, an exception is raised):
from ome_types import from_xml
metadata = from_xml(xml)
where xml in that example can be a path to a file, a URI of a
resource, an opened file-like object, an Element instance, an ElementTree
instance, or a literal string containing the XML data.
all attributes and variable names follow the OME data model, but camelCaseNames
have been replaced with pythonic snake_case_names
Work in progress!
This is a work in progress and will absolutely need refining. Feel free to submit an issue or a PR if you try it out and have requests.
1 maintainer
Metadata
1 maintainer
Release files for ome-types 0.0.1
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|---|---|---|---|---|
| ome_types-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 125.5 kB
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