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Merge pull request #65 from linkml/sphinx-docs
Sphinx docs
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‎.github/workflows/doc_pages.yaml‎

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name: Sphinx Documentation
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on:
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push:
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branches: [ main ]
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jobs:
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build-docs:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@main
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with:
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fetch-depth: 0 # otherwise, you will failed to push refs to dest repo
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- name: Set up Python 3.
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uses: actions/setup-python@v3
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with:
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python-version: 3.9
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- name: Install Poetry.
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uses: snok/[email protected]
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- name: install
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run: poetry install -E docs
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- name: Build documentation.
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run: |
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mkdir gh-pages
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touch gh-pages/.nojekyll
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cd docs/
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poetry run sphinx-build -b html . _build
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cp -r _build/* ../gh-pages/
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- name: Deploy documentation.
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if: ${{ github.event_name == 'push' }}
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uses: JamesIves/[email protected]
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with:
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branch: gh-pages
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force: true
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folder: gh-pages

‎.gitignore‎

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node_modules
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typings
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dist
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schema_automator.egg-info/*

‎docs/Makefile‎

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# Minimal makefile for Sphinx documentation
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#
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# You can set these variables from the command line, and also
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# from the environment for the first two.
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SPHINXOPTS ?=
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SPHINXBUILD ?= sphinx-build
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SOURCEDIR = .
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BUILDDIR = _build
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# Put it first so that "make" without argument is like "make help".
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help:
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@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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.PHONY: help Makefile
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# Catch-all target: route all unknown targets to Sphinx using the new
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# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
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%: Makefile
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@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

‎docs/conf.py‎

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# Configuration file for the Sphinx documentation builder.
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#
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# This file only contains a selection of the most common options. For a full
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# list see the documentation:
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# https://www.sphinx-doc.org/en/master/usage/configuration.html
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# -- Path setup --------------------------------------------------------------
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# If extensions (or modules to document with autodoc) are in another directory,
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# add these directories to sys.path here. If the directory is relative to the
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# documentation root, use os.path.abspath to make it absolute, like shown here.
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#
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import os
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import sys
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sys.path.insert(0, os.path.abspath('../..'))
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# -- Project information -----------------------------------------------------
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project = 'Schema Automator'
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copyright = '2022, Chris Mungall'
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author = 'Chris Mungall'
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# The full version, including alpha/beta/rc tags
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# release = '0.1.4'
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# -- General configuration ---------------------------------------------------
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# Add any Sphinx extension module names here, as strings. They can be
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# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
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# ones.
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.githubpages',
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'sphinx.ext.autosectionlabel',
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'sphinx_rtd_theme',
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'sphinx_click',
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'sphinx.ext.viewcode',
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'sphinx.ext.todo',
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'sphinx.ext.coverage',
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'sphinx.ext.autosummary',
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'myst_parser',
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'sphinx.ext.intersphinx',
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'sphinxcontrib.mermaid'
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]
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# The suffix(es) of source filenames.
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# You can specify multiple suffix as a list of string:
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# source_suffix = ['.rst', '.md']
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source_suffix = ['.rst', '.md']
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# Add any paths that contain templates here, relative to this directory.
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templates_path = ['_templates']
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# List of patterns, relative to source directory, that match files and
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# directories to ignore when looking for source files.
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# This pattern also affects html_static_path and html_extra_path.
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exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
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# -- Options for HTML output -------------------------------------------------
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# The theme to use for HTML and HTML Help pages. See the documentation for
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# a list of builtin themes.
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#
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html_theme = 'sphinx_rtd_theme'
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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['_static']

‎docs/index.rst‎

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.. Schema Automator documentation master file, created by
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sphinx-quickstart on Fri Apr 22 13:19:04 2022.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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Welcome to Schema Automator's documentation!
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============================================
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.. toctree::
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:maxdepth: 2
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:caption: Contents:
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introduction
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intro/index
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`

‎docs/intro/cli.rst‎

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Command Line Usage
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------------------
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Annotating Enums
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~~~~~~~~~~~~~~~~
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This toolkit allows automated annotation of LinkML enums, mapping text
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strings to ontology terms.
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The command line tool ``annotate-enums`` takes a LinkML schema, with
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enums and fills in the ``meaning`` slots.
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See the `annotators <schema_automator/annotators/>`__ folder for docs
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Converting TSVs
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~~~~~~~~~~~~~~~
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The ``tsv2linkml`` command infers a single-class schema from a TSV
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datafile
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.. code:: bash
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tsv2linkml --help
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Usage: tsv2linkml [OPTIONS] TSVFILE
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Infer a model from a TSV
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Options:
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-o, --output TEXT Output file
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-c, --class_name TEXT Core class name in schema
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-n, --schema_name TEXT Schema name
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-s, --sep TEXT separator
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-E, --enum-columns TEXT column that is forced to be an enum
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--robot / --no-robot set if the TSV is a ROBOT template
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--help Show this message and exit.
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Example:
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.. code:: bash
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tsv2linkml tests/resources/biobank-specimens.tsv
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The ``tsvs2linkml`` command infers a multi-class schema from multiple
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TSV datafiles
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.. code:: bash
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tsvs2linkml --help
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Usage: tsvs2linkml [OPTIONS] [TSVFILES]...
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Infer a model from multiple TSVs
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Options:
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-o, --output TEXT Output file
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-n, --schema_name TEXT Schema name
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-s, --sep TEXT separator
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-E, --enum-columns TEXT column(s) that is forced to be an enum
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--enum-mask-columns TEXT column(s) that are excluded from being enums
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--max-enum-size INTEGER do not create an enum if more than max distinct
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members
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--enum-threshold FLOAT if the number of distinct values / rows is less
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than this, do not make an enum
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--robot / --no-robot set if the TSV is a ROBOT template
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--help Show this message and exit.
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Converting OWL
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~~~~~~~~~~~~~~
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.. code:: bash
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owl2linkml --help
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Usage: owl2linkml [OPTIONS] OWLFILE
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Infer a model from OWL Ontology
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Note: input must be in functional syntax
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Options:
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-n, --name TEXT Schema name
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--help Show this message and exit.
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Example:
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.. code:: bash
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owl2linkml -n prov tests/resources/prov.ofn > prov.yaml
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Note this works best on schema-style ontologies such as Prov
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**NOT** recommended for terminological-style ontologies such as OBO
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Converting RDF instance graphs
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: bash
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rdf2linkml --help
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Usage: rdf2linkml [OPTIONS] RDFFILE
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Infer a model from RDF instance data
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Options:
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-d, --dir TEXT [required]
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--help Show this message and exit.
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Converting JSON Instance Data
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: bash
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jsondata2linkml --help
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Usage: jsondata2linkml [OPTIONS] INPUT
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Infer a model from JSON instance data
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Options:
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--container-class-name TEXT name of root class
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-f, --format TEXT json or yaml (or json.gz or yaml.gz)
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--omit-null / --no-omit-null if true, ignore null values
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--help Show this message and exit.
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Converting JSON-Schema
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~~~~~~~~~~~~~~~~~~~~~~
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.. code:: bash
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jsonschema2linkml --help
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Usage: jsonschema2linkml [OPTIONS] INPUT
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Infer a model from JSON Schema
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Options:
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-n, --name TEXT ID of schema [required]
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-f, --format TEXT JSON Schema format - yaml or json
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-o, --output TEXT output path
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--help Show this message and exit.
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jsonschema2linkml example
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~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: bash
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poetry run jsonschema2linkml -n test-model -f yaml -o vrs-linkml.yaml cp tests/resources/jsonschema/vrs.schema.json

‎docs/intro/index.rst‎

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.. _get started:
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Get Started
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===============================
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.. toctree::
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:maxdepth: 3
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:caption: Contents:
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install
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cli

‎docs/intro/install.rst‎

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Installation
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------------
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``schema-automator`` and its components require Python 3.9 or greater.
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.. code:: bash
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chmod 755 environment.sh
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. environment.sh
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pip install -r requirements.txt
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pip install -e .

‎docs/introduction.rst‎

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LinkML Schema Automator
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=======================
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This is a toolkit that assists with:
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1. Bootstrapping LinkML models from instance data
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- TSVs and spreadsheets
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- SQLite databases
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- RDF instance graphs
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2. Bootstrapping a LinkML model from a different schema representation
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(i.e. opposite of a linkml.generator)
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- OWL (RDFS-like subset)
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- TODO: JSON-Schema, XSD, ShEx, SHACL, SQL DDL, FHIR, Python
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dataclasses/pydantic, etc
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3. Using automated methods to enhance a model
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- Using text mining and concept annotator APIs to enrich semantic
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enums
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- TODO: querying sparql endpoints to retrieve additional metadata
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These can be composed together. For example, run ``tsvs2linkml``
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followed by ``annotate-enums``
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The toolkit is still experimental. It is intended as an aid to schema
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creation rather than act as a formal conversion tool

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