feat(spp_gis_report): re-land metric disaggregation in GIS reports (from #76)

Re-lands the spp_gis_report portion of reverted PR #76. Depends on the
spp_metric_service breakdown expansion (Wave-2 PR) and transitively on
spp_cel_domain (#275) — do not merge before them.

Author: gonzalesedwin1123

spp_gis_report/__init__.py

@@ -1,3 +1,84 @@
+import logging
+
+from psycopg2 import sql
+
 from . import controllers
 from . import models
 from . import wizards
+
+_logger = logging.getLogger(__name__)
+
+# Mapping: old boolean field name -> dimension technical name
+_BOOL_TO_DIMENSION = {
+    "disaggregate_by_gender": "gender",
+    "disaggregate_by_age": "age_group",
+    "disaggregate_by_disability": "disability_status",
+}
+
+
+def _migrate_boolean_disaggregation(env):
+    """Post-init hook: migrate boolean disaggregation flags to dimension_ids.
+
+    Looks up reports that had boolean flags set and links them to the
+    corresponding spp.demographic.dimension records. Logs a warning
+    (does not crash) if a dimension record is not found.
+    """
+    cr = env.cr
+
+    # Check if the old boolean columns still exist
+    cr.execute(
+        """
+        SELECT column_name FROM information_schema.columns
+        WHERE table_name = 'spp_gis_report'
+          AND column_name IN ('disaggregate_by_gender', 'disaggregate_by_age', 'disaggregate_by_disability')
+        """
+    )
+    existing_columns = {row[0] for row in cr.fetchall()}
+
+    if not existing_columns:
+        _logger.info("No legacy boolean disaggregation columns found, skipping migration")
+        return
+
+    # Get the m2m relation table name
+    Dimension = env["spp.demographic.dimension"]
+
+    for bool_field, dim_name in _BOOL_TO_DIMENSION.items():
+        if bool_field not in existing_columns:
+            continue
+
+        # Find reports with this boolean set. bool_field is a trusted column
+        # name from _BOOL_TO_DIMENSION; quote it safely via psycopg2.sql.
+        query = sql.SQL("SELECT id FROM spp_gis_report WHERE {col} = true").format(col=sql.Identifier(bool_field))
+        cr.execute(query)
+        report_ids = [row[0] for row in cr.fetchall()]
+        if not report_ids:
+            continue
+
+        dimension = Dimension.search([("name", "=", dim_name)], limit=1)
+        if not dimension:
+            _logger.warning(
+                "Dimension '%s' not found, cannot migrate %d reports with %s=True",
+                dim_name,
+                len(report_ids),
+                bool_field,
+            )
+            continue
+
+        # Insert m2m links (skip duplicates)
+        for report_id in report_ids:
+            cr.execute(
+                """
+                INSERT INTO spp_gis_report_spp_demographic_dimension_rel
+                    (spp_gis_report_id, spp_demographic_dimension_id)
+                VALUES (%s, %s)
+                ON CONFLICT DO NOTHING
+                """,
+                (report_id, dimension.id),
+            )
+
+        _logger.info(
+            "Migrated %d reports from %s=True to dimension '%s'",
+            len(report_ids),
+            bool_field,
+            dim_name,
+        )

spp_gis_report/__manifest__.py

@@ -1,6 +1,6 @@
 {
     "name": "OpenSPP GIS Reports",
-    "version": "19.0.2.0.1",
+    "version": "19.0.2.1.0",
     "category": "OpenSPP",
     "summary": "Geographic visualization and reporting for social protection data",
     "author": "OpenSPP.org, OpenSPP",
@@ -10,6 +10,7 @@
     "depends": [
         "spp_area",
         "spp_gis",
+        "spp_metric_service",
         "spp_registry",
         "spp_vocabulary",
         "spp_cel_domain",
@@ -47,6 +48,7 @@
             "spp_gis_report/static/src/css/gis_report.css",
         ],
     },
+    "post_init_hook": "_migrate_boolean_disaggregation",
     "installable": True,
     "application": False,
     "auto_install": False,

spp_gis_report/controllers/geojson.py

@@ -100,23 +100,19 @@ def list_reports(self):
             for report in reports:
                 admin_levels = report.data_ids.mapped("area_level") if report.data_ids else []
 
-                report_list.append(
-                    {
-                        "code": report.code,
-                        "name": report.name,
-                        "category": report.category_id.name if report.category_id else None,
-                        "last_refresh": (report.last_refresh.isoformat() if report.last_refresh else None),
-                        "admin_levels_available": sorted(set(admin_levels)),
-                        "has_disaggregation": any(
-                            [
-                                report.disaggregate_by_gender,
-                                report.disaggregate_by_age,
-                                report.disaggregate_by_disability,
-                                report.disaggregate_by_tag_ids,
-                            ]
-                        ),
-                    }
-                )
+                report_data = {
+                    "code": report.code,
+                    "name": report.name,
+                    "category": report.category_id.name if report.category_id else None,
+                    "last_refresh": (report.last_refresh.isoformat() if report.last_refresh else None),
+                    "admin_levels_available": sorted(set(admin_levels)),
+                    "has_disaggregation": bool(report.dimension_ids) or bool(report.disaggregate_by_tag_ids),
+                }
+                if report.dimension_ids:
+                    report_data["disaggregation_dimensions"] = [
+                        {"name": d.name, "label": d.label} for d in report.dimension_ids
+                    ]
+                report_list.append(report_data)
 
             return self._json_response({"reports": report_list})
 

spp_gis_report/models/area_ext.py

@@ -153,7 +153,15 @@ def get_gis_layers(self, view_id=None, view_type="gis", **options):
             # Build legend info from thresholds for display purposes only.
             thresholds = report.threshold_ids.sorted("sequence")
             if thresholds:
-                layer_dict["report_legend"] = [{"color": t.color, "label": t.label} for t in thresholds]
+                layer_dict["report_legend"] = [
+                    {
+                        "color": t.color,
+                        "label": t.label,
+                        "min_value": t.min_value,
+                        "max_value": t.max_value,
+                    }
+                    for t in thresholds
+                ]
                 layer_dict["report_legend_title"] = report.name
 
             # Build pre-computed features for report layer