Agrego cálculo de porcentaje de uso de campos a nivel global a los in…

…dicadores de red de nodos
datosgobar · May 9, 2017 · 3b17e95 · 3b17e95
1 parent 0c08972
commit 3b17e95
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Showing 2 changed files with 25 additions and 5 deletions.
diff --git a/pydatajson/core.py b/pydatajson/core.py
@@ -769,6 +769,7 @@ def generate_catalogs_indicators(self, catalogs, central_catalog=None):
         network_indicators = {}  # Para la red global
         indicators_list = []
 
+        fields = {}
         for catalog in catalogs:
             # Obtengo summary para los indicadores del estado de los metadatos
             summary = self.generate_datasets_summary(catalog)
@@ -803,11 +804,15 @@ def generate_catalogs_indicators(self, catalogs, central_catalog=None):
 
             # Agrego porcentaje de campos recomendados/optativos usados
             fields_count = self._count_required_and_optional_fields(catalog)
-            total_rec = fields_count['total_recomendado']
-            total_opt = fields_count['total_optativo']
 
-            recomendados_pct = float(fields_count['recomendado']) / total_rec
-            optativos_pct = float(fields_count['optativo']) / total_opt
+            # Sumo a la cuenta total de campos usados/totales
+            fields = helpers.add_dicts(fields_count, fields)
+
+            recomendados_pct = float(fields_count['recomendado']) / \
+                fields_count['total_recomendado']
+            optativos_pct = float(fields_count['optativo']) / \
+                fields_count['total_optativo']
+
             result.update({
                 'campos_recomendados_pct': round(recomendados_pct, 2),
                 'campos_optativos_pct': round(optativos_pct, 2)
@@ -828,11 +833,19 @@ def generate_catalogs_indicators(self, catalogs, central_catalog=None):
 
         network_indicators.update(indicators_total)
         # Los porcentuales no se pueden sumar, tienen que ser recalculados
+
         total_pct = float(network_indicators['datasets_meta_ok_cant']) / \
                     (network_indicators['datasets_meta_ok_cant'] +
                      network_indicators['datasets_meta_error_cant']) * 100
         network_indicators['datasets_meta_ok_pct'] = round(total_pct, 2)
 
+        rec_pct = float(fields['recomendado']) / fields['total_recomendado']
+        opt_pct = float(fields['optativo']) / fields['total_optativo']
+
+        network_indicators.update({
+            'campos_recomendados_pct': round(rec_pct, 2),
+            'campos_optativos_pct': round(opt_pct, 2)
+        })
         network_indicators['catalogos_cant'] = len(catalogs)
         return indicators_list, network_indicators
 

diff --git a/tests/test_core.py b/tests/test_core.py
@@ -901,7 +901,14 @@ def test_network_indicators(self):
             'distribuciones_cant': 7,
             'datasets_meta_ok_cant': 3,
             'datasets_meta_error_cant': 1,
-            'datasets_meta_ok_pct': 100 * float(3) / 4
+            'datasets_meta_ok_pct': 100 * float(3) / 4,
+            'distribuciones_formatos_cant': {
+                'CSV': 2,
+                'XLSX': 1,
+                'PDF': 1
+            },
+            'campos_optativos_pct': 0.22,
+            'campos_recomendados_pct': 0.55
         }
 
         for k,v in expected.items():