ENH: Added spss_to_datamodel script.

CHANGELOG.md

@@ -10,6 +10,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Added ###
 
 * Support for Python 3.12 and experimental support for 3.13
+* `spss_to_datamodel` script.
 
 ### Changed ###
 

setup.cfg

@@ -40,6 +40,7 @@ per-file-ignores = __init__.py:F401
 [options.entry_points]
 console_scripts =
   caosdb-crawler = caoscrawler.crawl:main
+  spss_to_datamodel = caoscrawler.conv_impl.spss:spss_to_datamodel_main
 
 [options.extras_require]
 h5_crawler =

src/caoscrawler/conv_impl/spss.py

@@ -18,14 +18,23 @@
 
 """Converter for SAV files (stored by SPSS)."""
 
+import argparse
+
 import pandas as pd
 import pyreadstat
+import yaml
 
 from .. import converters
 from ..stores import GeneralStore
 from ..structure_elements import (File, StructureElement)
 
 
+TYPES = {
+    "double": "DOUBLE",
+    "string": "TEXT",
+}
+
+
 class SPSSConverter(converters.TableConverter):
     """Converter for SAV files (stored by SPSS)."""
 
@@ -44,3 +53,94 @@ class SPSSConverter(converters.TableConverter):
         # embed()
 
         return self._children_from_dataframe(df)
+
+
+def spss_to_yaml(savfile: str, yamlfile: str) -> None:
+    """Parse the *.sav and create basic datamodel in ``yamlfile``.
+    """
+    _, meta = pyreadstat.read_sav(savfile, metadataonly=True)
+
+    enums: dict[str, list[str]] = {}
+    properties = {}
+
+    for name in meta.column_names:
+        prop = {
+            "datatype": TYPES[meta.readstat_variable_types[name]],
+        }
+        desc = meta.column_names_to_labels.get(name)
+        if desc and desc != name:
+            prop["description"] = desc
+        # Handle categorial variables
+        if var_label := meta.variable_to_label.get(name):
+            prop["datatype"] = var_label
+            vvl = meta.variable_value_labels[name]
+            # reproducible (and sensible) order
+            label_values = [vvl[key] for key in sorted(vvl.keys())]
+            if label_values not in enums.values():
+                enums[var_label] = label_values
+        properties[name] = prop
+
+    output = f"""# auto-generated data model from file "{savfile}".
+# To insert a datamodel into LinkAhead, run:
+#
+# python3 -m caosadvancedtools.models.parser datamodel.yaml --sync
+
+#
+# Code for creating enum records:
+#
+"""
+    for name, values in enums.items():
+        for line in f"""
+cont = db.Container()
+for value in {repr(values)}:
+    rec = db.Record(name=value).add_parent(name="{name}")
+    cont.append(rec)
+cont.insert()
+        """.splitlines(keepends=True):
+            if line.strip():
+                output += f"# {line}"
+    output += "#\n"
+
+    # Actual datamodel
+    output += """
+#########
+# Enums #
+#########
+
+"""
+    for name, values in enums.items():
+        output += f"""{name}:
+  description:
+  # possible values: {values}\n"""
+
+    output += ("""
+###############
+# RecordTypes #
+###############
+
+DummyRT:
+  description: Note: Change name and enter description.
+  recommended_properties:
+    """
+               + "    ".join(yaml.dump(properties,
+                                       allow_unicode=True,
+                                       sort_keys=False).splitlines(keepends=True)))
+
+    with open(yamlfile, encoding="utf-8", mode="w") as myfile:
+        myfile.write(output)
+
+
+def _parse_arguments():
+    """Parse the arguments."""
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('-i', '--input', help="The *.sav file.", required=True)
+    parser.add_argument('-o', '--outfile', help="Yaml filename to save the result", required=True)
+
+    return parser.parse_args()
+
+
+def spss_to_datamodel_main():
+    """The main function of this script."""
+    args = _parse_arguments()
+    spss_to_yaml(savfile=args.input, yamlfile=args.outfile)
+    print(f"Written datamodel to: {args.outfile}")