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PyPI version License: MIT Python Versions

OMERO.RuleTagger (Previously Known as OMERO.Autotagger)

A Python package for automated tagging of OMERO objects based on customizable rules and regex.

It works by walking the omero model as described by the omero-py wrappers and the underlying ObjectI classes. After the walk it compares a given reference value against the value it walked to, then tags if the condition passes.

Known Limitations

  • Currently impossible to add arguments to the model walk
    • For example a you can't filter a condition to only check annotations in a certain namespace
    • This example could be fixed by comparing the 'ns' property against the desired value, but it still won't filter
  • Cannot specify objects to operate on within the rules file.
    • Planned addition in schemav2 but wanted to get this out and get some feedback for schemav2
  • Doesn't handle Annotations very well.
    • This is because the omero-py package doesn't have getters for specific annotation types
      • This causes AttributeErrors
    • Map and Table Annotations especially need extra thought to be able to meaningfully rule against
  • Also doesn't handle properties
    • Due to the compilation process, we need getters to access properties
    • Could be possible to add with some lambda
      • Decided to leave as is for now because most properties have a getter (thanks java!)
  • Pretty slow and inefficient
    • Makes more requests than it needs to
    • Causes it to take longer than it needs to
    • Decided to leave as is for readability sake
      • We run it once a night, could probably do it once a week
      • Both walking and recursion can get complex, tried my best to stay legible (unlike my first implementation)

Documentation

For a proper in-depth explanation of the tool use the documentation.

Installation

Install using pip:

pip install omero-ruletagger

Dependencies

  • Python ≥3.8
  • PyYAML
  • inflect
  • omero-py

Usage

Command Line Interface

The package provides three main commands:

  1. Validate rules:
omero-ruletagger validate rules.yml
  1. Apply tags:
omero-ruletagger run rules.yml -O "Image:123" -O "Dataset:456"
  1. Dry run:
omero-ruletagger dry-run rules.yml -O "Image:789" -o results.csv

Connection Options

  • -s, --server: OMERO server hostname
  • -p, --port: OMERO server port
  • -u, --user: OMERO username
  • -w, --password: OMERO password
  • -k, --key: Existing session key
  • -S, --secure: Use secure connection
  • --sudo: Connect as administrator
  • -v, --verbose: Enable verbose logging

Rule Configuration

Create a YAML file defining your tagging rules. Example:

# test_rules.yml
- capture: "([^-.]+)"
  blacklist:
    - 1

- name: "FALSE"
  rules:
    - attribute_path: ["image", "roicount"]
      operation: lt
      value: 1

- name: "TRUE"
  rules:
    - attribute_path: ["image", "roi", "count"]
      operation: gt
      value: 0

- name: "Subtractive"
  absolute: false
  type: subtractive
  rules:
    - attribute_path: ["image", "roi","count"]
      operation: gt
      value: 0

- name: "UselessAND_TRUE"
  rules:
    - attribute_path: ["image", "roi", "shape", "strokecolor"]
      operation: eq
      value: 255
    - attribute_path: ["image", "roi", "shape", "count"]
      operation: eq
      value: 1

- name: "InherentlyFalseAND"
  rules:
    - attribute_path: ["image", "roi", "shape", "strokecolor"]
      operation: eq
      value: 255
    - attribute_path: ["image", "roi", "shape", "strokecolor"]
      operation: eq
      value: 254

- name: "DescriptionTest"
  rules:
    - attribute_path: ["image", "descriptions"]
      operation: match
      value: ".*test.*"

- name: "PhysicalSizeTest"
  rules:
    - attribute_path: ["image", "primarypixel", "physicalsizex"]
      operation: eq
      value: 1000
    - attribute_path: ["image", "primarypixel", "physicalsizey"]
      operation: eq
      value: 1000
    - attribute_path: ["image", "primarypixel", "physicalsizex", "unit", "name"]
      operation: eq
      value: "MICROMETER"

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE.txt file for details.

Links