Added generalization using panderas (#84)

See linkml/linkml#671

Added ability to parse a table on the web

Adding more documentation

docs/packages/generalizers.rst

@@ -10,6 +10,277 @@ Generalizers take example data and *generalizes* to a schema
    Generalization is inherently a heuristic process, this should be viewed as a bootstrapping process
    that *semi*-automates the creation of a new schema for you.
 
+Generalizing from a single TSV
+-----------------
+
+.. code-block::
+
+    schemauto  generalize-csv tests/resources/NWT_wildfires_biophysical_2016.tsv -o wildfire.yaml
+
+The schema will have a slot for every column, e,g:
+
+.. code-block:: yaml
+
+    classes:
+      Observation:
+        slots:
+        - site
+        - plot
+        - plot_size
+        - date
+        - observer
+
+Ranges will be auto-inferred, e.g.:
+
+.. code-block:: yaml
+
+    slots:
+      site:
+        examples:
+        - value: ZF20-105
+        range: string
+      plot:
+        examples:
+        - value: '6'
+        range: integer
+      plot_size:
+        examples:
+        - value: 10X10
+        range: plot_size_enum
+      date:
+        examples:
+        - value: '2016-07-09'
+        range: datetime
+
+Enums will be automatically inferred:
+
+.. code-block:: yaml
+
+    enums:
+      plot_size_enum:
+        permissible_values:
+          10X10:
+            description: 10X10
+          5x5:
+            description: 5x5
+          2.5X2.5:
+            description: 2.5X2.5
+          5X5:
+            description: 5X5
+          3x3:
+            description: 3x3
+      ecosystem_enum:
+        permissible_values:
+          Open Fen:
+            description: Open Fen
+          Treed Fen:
+            description: Treed Fen
+          Black Spruce:
+            description: Black Spruce
+          Poor Fen:
+            description: Poor Fen
+          Fen:
+            description: Fen
+          Lowland:
+            description: Lowland
+          Upland:
+            description: Upland
+          Bog:
+            description: Bog
+          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.
+
+For example, given a file ``envo.tsv``:
+
+.. csv-table:: environments
+    :header: envo term id, envo term label
+
+    ENVO_01000752,area of barren land
+    ENVO_01001570,terrestrial ecoregion
+    ENVO_01001581,sea surface layer
+    ENVO_01001582,forest floor
+
+And a file file ``samples.tsv``:
+
+.. csv-table:: samples
+    :header: BIOSAMPLE_ID,BIOSAMPLE_NAME,ENVO_BIOME_ID,ENVO_FEATURE_ID,ENVO_MATERIAL_ID
+
+    156554,"Enriched cells from forest soil in Barre Woods Harvard Forest LTER site, Petersham, Massachusetts, United States - Alteio_BWOrgControl_Nextera2",ENVO_01000174,ENVO_01000159,ENVO_00002261
+    156649,"Enriched cells from forest soil in Barre Woods Harvard Forest LTER site, Petersham, Massachusetts, United States - Alteio_BWOrgHeat_Nextera5",ENVO_01000174,ENVO_01000159,ENVO_00005781
+    156728,"Enriched cells from forest soil in Barre Woods Harvard Forest LTER site, Petersham, Massachusetts, United States - Alteio_BWOrgHeat_Nextera84",ENVO_01000174,ENVO_01000159,ENVO_00005781
+    156738,"Enriched cells from forest soil in Barre Woods Harvard Forest LTER site, Petersham, Massachusetts, United States - Alteio_BWMinControl_Nextera2",ENVO_01000174,ENVO_01001275,ENVO_00002261
+
+We can create a multi-class schema, with foreign keys inferred:
+
+.. code-block::
+
+    schemauto generalize-tsvs --infer-foreign-keys sample.tsv envo.tsv
+
+This will generate a schema with two classes, where the join between the sample table and the term table
+is inferred:
+
+.. code-block:: yaml
+
+classes:
+  sample:
+    slots:
+    - BIOSAMPLE_ID
+    - BIOSAMPLE_NAME
+    - ENVO_BIOME_ID
+    - ENVO_FEATURE_ID
+    - ENVO_MATERIAL_ID
+  envo:
+    slots:
+    - ENVO_ID
+    - ENVO_LABEL
+
+slots:
+  BIOSAMPLE_ID:
+    range: integer
+  BIOSAMPLE_NAME:
+    range: string
+  ENVO_BIOME_ID:
+    examples:
+    - value: ENVO_01000022
+    range: envo
+  ENVO_FEATURE_ID:
+    range: envo
+  ENVO_MATERIAL_ID:
+    range: envo
+  ENVO_ID:
+    identifier: true
+    range: string
+  ENVO_LABEL:
+    range: string
+
+Generalizing from tables on the web
+-----------------
+
+You can use ``generalize-htmltable``
+
+.. code-block::
+
+    schemauto  generalize-htmltable  https://www.nature.com/articles/s41467-022-31626-4/tables/1
+
+Will generate:
+
+.. code-block:: yaml
+
+    name: example
+    description: example
+    id: https://w3id.org/example
+    imports:
+    - linkml:types
+    prefixes:
+      linkml: https://w3id.org/linkml/
+      example: https://w3id.org/example
+    default_prefix: example
+    slots:
+      GWAS trait:
+        examples:
+        - value: "\xC2"
+        range: string
+      Peak GWAS SNP:
+        examples:
+        - value: rs2974298
+        range: string
+      Gene:
+        examples:
+        - value: SMIM19
+        range: string
+      NK cell cis eSNP:
+        examples:
+        - value: rs2974348
+        range: string
+      TWAS Z score:
+        examples:
+        - value: '3.809'
+        range: string
+      TWAS P value:
+        examples:
+        - value: '0.0001'
+        range: string
+    classes:
+      example:
+        slots:
+        - GWAS trait
+        - Peak GWAS SNP
+        - Gene
+        - NK cell cis eSNP
+        - TWAS Z score
+        - TWAS P value
+
+Generalizing from JSON
+-----------
+
+
+
+Packages
+--------
+
 .. currentmodule:: schema_automator.generalizers
 
 .. autoclass:: CsvDataGeneralizer

docs/packages/importers.rst

@@ -14,6 +14,31 @@ Importers are the opposite of `Generalizers <https://linkml.io/linkml/generators
    representation that lacks `inheritance <https://linkml.io/linkml/schemas/inheritance.html>`_, no ``is_a`` slots
    will be created.
 
+Importing from JSON-Schema
+---------
+
+The ``import-json-schema`` command can be used:
+
+.. code-block::
+
+    schemauto import-json-schema tests/resources/model_card.schema.json
+
+Importing from OWL
+---------
+
+You can import from a schema-style OWL ontology. This must be in functional syntax
+
+Use robot to convert ahead of time:
+
+.. code-block::
+
+    robot convert -i schemaorg.ttl -o schemaorg.ofn
+    schemauto import-owl schemaorg.ofn
+
+
+Packages
+-------
+
 .. currentmodule:: schema_automator.importers
 
 .. autoclass:: JsonSchemaImportEngine