Doc fixes & more metadata in pyproject for PyPI (#147)

* Add more pkg metadata including link to repo & docs

* Add link to repo & other minor doc fixes

* Fix properties in pyproject for poetry

* Fixes in docs to reduce sphinx warnings

The only remaining warning are related to metamodels docs.

* Add utilities package to index of docs

Author: dalito

CONTRIBUTING.md

@@ -29,7 +29,7 @@ For running tests, we use `pytest`.
 ## Discussion
 
 If you run into any issues or find certain functionality not documented/explained properly then feel free to 
-raise a ticket in the project's [issue tracker](https://github.com/linkml/issues). 
+raise a ticket in the project's [issue tracker](https://github.com/linkml/schema-automator/issues). 
 There are issue templates to capture certain types of issues.
 
 ## First Time Contributors
@@ -73,7 +73,7 @@ with a 'Do Not Merge' label.
 ## How to Report a Bug
 
 We recommend making a new ticket for each bug that you encounter while working with KGX. Please be sure to provide
-sufficient context for a bug you are reporting. There are [Issue Templates](https://github.com/linkml/issues/new/choose) 
+sufficient context for a bug you are reporting. There are [Issue Templates](https://github.com/linkml/schema-automator/issues/new/choose) 
 that you can use as a starting point.
 
 ## How to Request an Enhancement

docs/_static/.gitkeep

@@ -1,24 +1,24 @@
-.. cli:
+.. _cli:
 
-Command Line
-============
+Command Line Interface
+======================
 
-All Schema Automator functionality is available via the ``schemauto`` command
+All Schema Automator functionality is available via the ``schemauto`` command.
 
 Preamble
 --------
 
-.. warning ::
+.. warning::
 
    Previous versions had specific commands like ``tsv2linkml`` these are now deprecated.
    Instead these are now *subcommands* of the main ``schemauto`` command, and have been renamed.
 
-.. note ::
+.. note::
 
    we follow the `CLIG <https://clig.dev/>`_ guidelines as far as possible
 
 Main commands
----------
+-------------
 
 .. currentmodule:: schema_automator.cli
 

docs/cli.rst

@@ -1,13 +1,15 @@
 LinkML Schema Automator
-============================================
+=======================
 
 Schema Automator is a toolkit for bootstrapping and automatically enhancing schemas from a variety of sources.
 
+The project is open source (BSD 3-clause license) and hosted on `GitHub <https://github.com/linkml/schema-automator>`_.
+
 Use cases include:
 
 1. Inferring an initial schema or data dictionary from a dataset that is a collection of TSVs
 2. Automatically annotating schema elements and enumerations using the BioPortal annotator
-3. Importing from a language like RDFS/OWL
+3. Importing from a language like RDFS/OWL/SQL
 
 The primary output of Schema Automator is a `LinkML Schema <https://linkml.io/linkml>`_. This can be converted to other
 schema frameworks, including:
@@ -23,7 +25,6 @@ schema frameworks, including:
    :maxdepth: 3
    :caption: Contents:
 
-   index
    introduction
    install
    cli

docs/index.rst

@@ -1,8 +1,8 @@
 Installation
-======
+============
 
 Direct Installation
-------------
+-------------------
 
 ``schema-automator`` and its components require Python 3.9 or greater.
 
@@ -17,7 +17,7 @@ To check this works:
    schemauto --help
 
 Running via Docker
-------------
+------------------
 
 You can use the `Schema Automator Docker Container <https://hub.docker.com/r/linkml/schema-automator>`_
 

docs/install.rst

@@ -1,15 +1,13 @@
-.. _introduction:
-
 Introduction
-=======================
+============
 
 This is a toolkit that assists with generating and enhancing schemas and data models from a variety
 of sources.
 
 The primary end target is a `LinkML <https://linkml.io>`_ schema, but the framework can be used
 to generate JSON-Schema, SHACL, SQL DDL etc via the `LinkML Generator <https://linkml.io/linkml/generators>`_ framework.
 
-All functionality is available via a :ref:`cli`. In future there will be a web-based interface.
+All functionality is available via a :ref:`CLI <cli>`. In future there will be a web-based interface.
 The functionality is also available by using the relevant Python :ref:`packages`.
 
 Generalization from Instance Data
@@ -24,7 +22,7 @@ Generalizers allow you to *bootstrap* a schema by generalizing from existing dat
 * RDF instance graphs
 
 Importing from alternative modeling frameworks
----------------------------------
+----------------------------------------------
 
 See :ref:`importers`
 
@@ -35,7 +33,7 @@ See :ref:`importers`
 In future other frameworks will be supported
 
 Annotating schemas
----------------------------------
+------------------
 
 See :ref:`annotators`
 
@@ -46,7 +44,7 @@ Annotators to provide ways to automatically add metadata to your schema, includi
 * Annotate using Large Language Models (LLMs)
 
 General Utilities
----------------------------------
+-----------------
 
-See :ref:`utilitiess`
+See :ref:`utilities`
 

docs/introduction.rst

@@ -8,16 +8,6 @@ metamodels in order to define transformations.
    :maxdepth: 3
    :caption: Contents:
 
-   index
    cadsr/index
    frictionless/index
    dosdp/index
-   fhir/index
-
-
-Indices and tables
-==================
-
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`

docs/metamodels/index.rst

@@ -1,7 +1,5 @@
-.. annotators:
-
 Annotators
-=========
+==========
 
 Importers take an existing schema and *annotate* it with information
 

docs/packages/annotators.rst

@@ -1,7 +1,5 @@
-.. generalizers:
-
 Generalizers
-=========
+============
 
 Generalizers take example data and *generalizes* to a schema
 
@@ -11,7 +9,7 @@ Generalizers take example data and *generalizes* to a schema
    that *semi*-automates the creation of a new schema for you.
 
 Generalizing from a single TSV
------------------
+------------------------------
 
 .. code-block::
 
@@ -90,65 +88,9 @@ Enums will be automatically inferred:
           Lowland Black Spruce:
             description: Lowland Black Spruce
 
-Chaining an annotator
------------------
-
-If you provide an ``--annotator`` option you can auto-annotate enums:
-
-.. code-block::
-
-    schemauto  generalize-csv \
-        --annotator bioportal:envo \
-        tests/resources/NWT_wildfires_biophysical_2016.tsv \
-        -o wildfire.yaml
-
-.. code-block:: yaml
-
-      ecosystem_enum:
-        from_schema: https://w3id.org/MySchema
-        permissible_values:
-          Open Fen:
-            description: Open Fen
-            meaning: ENVO:00000232
-            exact_mappings:
-            - ENVO:00000232
-          Treed Fen:
-            description: Treed Fen
-            meaning: ENVO:00000232
-            exact_mappings:
-            - ENVO:00000232
-          Black Spruce:
-            description: Black Spruce
-          Poor Fen:
-            description: Poor Fen
-            meaning: ENVO:00000232
-            exact_mappings:
-            - ENVO:00000232
-          Fen:
-            description: Fen
-            meaning: ENVO:00000232
-          Lowland:
-            description: Lowland
-          Upland:
-            description: Upland
-            meaning: ENVO:00000182
-          Bog:
-            description: Bog
-            meaning: ENVO:01000534
-            exact_mappings:
-            - ENVO:01000535
-            - ENVO:00000044
-            - ENVO:01001209
-            - ENVO:01000527
-          Lowland Black Spruce:
-            description: Lowland Black Spruce
-
-The annotation can also be run as a separate step
-
-See :ref:`annotators`
 
 Generalizing from multiple TSVs
-------------
+-------------------------------
 
 You can use the ``generalize-tsvs`` command to generalize from *multiple* TSVs, with
 foreign key linkages auto-inferred.
@@ -217,7 +159,7 @@ slots:
     range: string
 
 Generalizing from tables on the web
------------------
+-----------------------------------
 
 You can use ``generalize-htmltable``
 
@@ -274,12 +216,69 @@ Will generate:
         - TWAS P value
 
 Generalizing from JSON
------------
+----------------------
 
+tbw
 
+Chaining an annotator
+---------------------
+
+If you provide an ``--annotator`` option you can auto-annotate enums:
+
+.. code-block::
+
+    schemauto  generalize-csv \
+        --annotator bioportal:envo \
+        tests/resources/NWT_wildfires_biophysical_2016.tsv \
+        -o wildfire.yaml
+
+.. code-block:: yaml
+
+      ecosystem_enum:
+        from_schema: https://w3id.org/MySchema
+        permissible_values:
+          Open Fen:
+            description: Open Fen
+            meaning: ENVO:00000232
+            exact_mappings:
+            - ENVO:00000232
+          Treed Fen:
+            description: Treed Fen
+            meaning: ENVO:00000232
+            exact_mappings:
+            - ENVO:00000232
+          Black Spruce:
+            description: Black Spruce
+          Poor Fen:
+            description: Poor Fen
+            meaning: ENVO:00000232
+            exact_mappings:
+            - ENVO:00000232
+          Fen:
+            description: Fen
+            meaning: ENVO:00000232
+          Lowland:
+            description: Lowland
+          Upland:
+            description: Upland
+            meaning: ENVO:00000182
+          Bog:
+            description: Bog
+            meaning: ENVO:01000534
+            exact_mappings:
+            - ENVO:01000535
+            - ENVO:00000044
+            - ENVO:01001209
+            - ENVO:01000527
+          Lowland Black Spruce:
+            description: Lowland Black Spruce
+
+The annotation can also be run as a separate step
+
+See :ref:`annotators`
 
-Packages
---------
+Packages for generalizing
+-------------------------
 
 .. currentmodule:: schema_automator.generalizers
 

docs/packages/generalizers.rst

@@ -1,5 +1,3 @@
-.. importers:
-
 Importers
 =========
 
@@ -15,7 +13,7 @@ Importers are the opposite of `Generators <https://linkml.io/linkml/generators/i
    will be created.
 
 Importing from JSON-Schema
----------
+--------------------------
 
 The ``import-json-schema`` command can be used:
 
@@ -24,7 +22,7 @@ The ``import-json-schema`` command can be used:
     schemauto import-json-schema tests/resources/model_card.schema.json
 
 Importing from Kwalify
----------
+----------------------
 
 The ``import-kwalify`` command can be used:
 
@@ -33,7 +31,7 @@ The ``import-kwalify`` command can be used:
     schemauto import-kwalify tests/resources/test.kwalify.yaml
 
 Importing from OWL
----------
+------------------
 
 You can import from a schema-style OWL ontology. This must be in functional syntax
 
@@ -45,7 +43,7 @@ Use robot to convert ahead of time:
     schemauto import-owl schemaorg.ofn
 
 Importing from SQL
----------
+------------------
 
 You can import a schema from a SQL database
 
@@ -65,7 +63,7 @@ For example, for the `RNA Central public database <https://rnacentral.org/help/p
     schemauto import-sql postgresql+psycopg2://reader:[email protected]:5432/pfmegrnargs
 
 Importing from caDSR
----------
+--------------------
 
 caDSR is an ISO-11179 compliant metadata registry. The ISO-11179 conceptual model can be mapped to LinkML. The
 canonical mapping maps a CDE onto a LinkML *slot*.
@@ -79,8 +77,8 @@ NCI implements a JSON serialization of ISO-11197. You can import this JSON and c
     schemauto import-cadsr "cdes/*.json"
 
 
-Packages
--------
+Packages for importing
+----------------------  
 
 .. currentmodule:: schema_automator.importers