v.db.select: Add column names and types to JSON (OSGeo#3090)

The JSON output now has column names and types under info/columns.

The example in documentation does not include the unclear note about booleans (a discussion for another place).

A command to reproduce the example output is now included.

Documentation and test of the new functionality are included.

vector/v.db.select/main.c

@@ -337,8 +337,32 @@ int main(int argc, char **argv)
     if (format == JSON) {
         if (flags.region->answer)
             fprintf(stdout, "{\"extent\":\n");
-        else
-            fprintf(stdout, "{\"records\":[\n");
+        else {
+            fprintf(stdout, "{\"info\":\n{\"columns\":[\n");
+            for (col = 0; col < ncols; col++) {
+                column = db_get_table_column(table, col);
+                if (col)
+                    fprintf(stdout, "},\n");
+                fprintf(stdout, "{\"name\":\"%s\",",
+                        db_get_column_name(column));
+                int sql_type = db_get_column_sqltype(column);
+                fprintf(stdout, "\"sql_type\":\"%s\",",
+                        db_sqltype_name(sql_type));
+
+                int c_type = db_sqltype_to_Ctype(sql_type);
+                fprintf(stdout, "\"is_number\":");
+                /* Same rules as for quoting, i.e., number only as
+                 * JSON or Python would see it and not numeric which may
+                 * include, e.g., date. */
+                if (c_type == DB_C_TYPE_INT || c_type == DB_C_TYPE_DOUBLE)
+                    fprintf(stdout, "true");
+                else
+                    fprintf(stdout, "false");
+            }
+
+            fprintf(stdout, "}\n]},\n");
+            fprintf(stdout, "\"records\":[\n");
+        }
     }
 
     /* fetch the data */

vector/v.db.select/testsuite/test_v_db_select.py

@@ -163,7 +163,19 @@
 1290,63600420,109186.835938,1291,1290,Zwe,63600422.4739,109186.832069
 """
 
-out_json = """{"records":[
+out_json = """\
+{"info":
+{"columns":[
+{"name":"cat","sql_type":"INTEGER","is_number":true},
+{"name":"onemap_pro","sql_type":"DOUBLE PRECISION","is_number":true},
+{"name":"PERIMETER","sql_type":"DOUBLE PRECISION","is_number":true},
+{"name":"GEOL250_","sql_type":"INTEGER","is_number":true},
+{"name":"GEOL250_ID","sql_type":"INTEGER","is_number":true},
+{"name":"GEO_NAME","sql_type":"CHARACTER","is_number":false},
+{"name":"SHAPE_area","sql_type":"DOUBLE PRECISION","is_number":true},
+{"name":"SHAPE_len","sql_type":"DOUBLE PRECISION","is_number":true}
+]},
+"records":[
 {"cat":1,"onemap_pro":963738.75,"PERIMETER":4083.97998,"GEOL250_":2,"GEOL250_ID":1,"GEO_NAME":"Zml","SHAPE_area":963738.608571,"SHAPE_len":4083.979839},
 {"cat":2,"onemap_pro":22189124,"PERIMETER":26628.261719,"GEOL250_":3,"GEOL250_ID":2,"GEO_NAME":"Zmf","SHAPE_area":22189123.2296,"SHAPE_len":26628.261112},
 {"cat":3,"onemap_pro":579286.875,"PERIMETER":3335.55835,"GEOL250_":4,"GEOL250_ID":3,"GEO_NAME":"Zml","SHAPE_area":579286.829631,"SHAPE_len":3335.557182},

vector/v.db.select/testsuite/test_v_db_select_json_csv.py

@@ -3,7 +3,7 @@
 # MODULE:       Test of v.db.select
 # AUTHOR(S):    Vaclav Petras <wenzeslaus gmail com>
 # PURPOSE:      Test parsing and structure of CSV and JSON outputs
-# COPYRIGHT:    (C) 2021 by Vaclav Petras the GRASS Development Team
+# COPYRIGHT:    (C) 2021-2023 by Vaclav Petras the GRASS Development Team
 #
 #               This program is free software under the GNU General Public
 #               License (>=v2). Read the file COPYING that comes with GRASS
@@ -173,6 +173,21 @@ def test_json_loads(self):
         """Load JSON with difficult values"""
         text = gs.read_command("v.db.select", map=self.vector_points, format="json")
         data = json.loads(text)
+
+        column_info = data["info"]["columns"]
+        self.assertEqual(column_info[0]["name"], "cat")
+        self.assertEqual(column_info[0]["sql_type"], "INTEGER")
+        self.assertEqual(column_info[0]["is_number"], True)
+        self.assertEqual(column_info[1]["name"], "x")
+        self.assertEqual(column_info[1]["sql_type"], "DOUBLE PRECISION")
+        self.assertEqual(column_info[1]["is_number"], True)
+        self.assertEqual(column_info[4]["name"], "owner_id")
+        self.assertEqual(column_info[4]["sql_type"], "INTEGER")
+        self.assertEqual(column_info[4]["is_number"], True)
+        self.assertEqual(column_info[5]["name"], "place_name")
+        self.assertEqual(column_info[5]["sql_type"], "TEXT")
+        self.assertEqual(column_info[5]["is_number"], False)
+
         data = data["records"]
         self.assertIsNone(data[2]["place_name"])
         self.assertEqual(data[3]["place_name"], 'The "Great" Place')

vector/v.db.select/v.db.select.html

@@ -105,24 +105,56 @@ <h4>JSON</h4>
 the columns were defined in the database.
 
 <p>
-Example with added indentation (note that booleans are not directly supported;
-here, an attribute is a string with value <tt>no</tt>):
+The JSON also contains information about columns stored under key
+<code>info</code>. Column names and types are under key <code>columns</code>.
+Each colum has SQL data type under <code>sql_type</code> in all caps.
+A boolean <code>is_number</code> specifies whether the value is a number, i.e.,
+integer or floating point number. The <code>is_number</code> value
+is aded for convenience and it is recommended to rely on the types derived
+from the JSON representation or the SQL types. The definition of
+<code>is_number</code> may change in the future.
+
+<p>
+Example with added indentation:
+
+<!--
+  Generated using:
+
+  v.db.select roadsmajor format=json where="cat in (1, 2)" \
+    columns="ROAD_NAME AS road_name, PROPYEAR + 2001 AS year, SHAPE_LEN as length" \
+    | jq
+-->
 
 <div class="code"><pre>
 {
+  "info": {
+    "columns": [
+      {
+        "name": "road_name",
+        "sql_type": "CHARACTER",
+        "is_number": false
+      },
+      {
+        "name": "year",
+        "sql_type": "INTEGER",
+        "is_number": true
+      },
+      {
+        "name": "length",
+        "sql_type": "DOUBLE PRECISION",
+        "is_number": true
+      }
+    ]
+  },
   "records": [
     {
-      "cat": 1,
       "road_name": "NC-50",
-      "multilane": "no",
       "year": 2001,
       "length": 4825.369405
     },
     {
-      "cat": 2,
       "road_name": "NC-50",
-      "multilane": "no",
-      "year": 2002,
+      "year": 2001,
       "length": 14392.589058
     }
   ]