Describe the shared, common framework

ylab-common-scripts (ylabcommon)

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Suggested structure:

ylabcommon a shared utilities, hybrid classes for microscopy dataset reconstruction pipelines developed by YLab.

This framework provides share classes, codesi, and Microscope-specific loaders such as:

• Thorlab microscopy pipeline

• Keyence microscopy pipeline

• Reuse for others only in future

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The framework is built on top of BioIO and provides standardized tools for:

• image stacking

• metadata extraction

• dataset validation

• OME output writing

• dataset reporting

Repository Structure

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Features:

• BioIO-based microscopy IO

• automatic stack reconstruction

• metadata standardization

• dataset validation

• OME-TIFF writing

• dataset summary reports

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Installation

Clone repository:

git clone https://github.com/ylabjp/ylab-common-scripts.git
cd ylab-common-scripts

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Setup virtual environment using uv

uv sync

Install package and dependencies in editable mode

uv pip install -e .

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Dependency Note

This package is intended to be used as a dependency of microscope-specific pipelines.

Example dependency:

ylabcommon = { git = "https://github.com/ylabjp/ylab-common-scripts" }

During development/work locally use local path:

ylabcommon = { path = "../YlabCommonScripts/ylab-common-scripts", editable = true }

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If environment issues occur:, don't worry run diagnostic script

source env_common_fix.sh

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Run Unit/pytest

-Unit tests (default)

pytest \
  --ignore src/ylabcommon/analysis/ \
  --ignore=src/ylabcommon/utils       % Just ignore these folder

-Local dataset validation

uv run pytest tests/ -m integration\_bioio
  --local-tiff-dir "Your local tiff's directory path"
  --local-xml \

-Google Drive dataset

uv run pytest tests \
  -v -m gdrive -s --gdrive-folder \
  --gdrive-folder "URL" \
  --gdrive-sa-json "/credentials.json"

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Future Work

• extended validation tools

• improved metadata handling

• additional report utilities

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