Adds a pool summary endpoint

src/apps/api/app.py

@@ -29,6 +29,7 @@ def output_json(data, code, headers=None):
 api.add_resource(endpoints.CreditsProjectsAggregation, '/credits/agg/projects')
 api.add_resource(endpoints.CreditsMethodologiesAggregation, '/credits/agg/methodologies')
 api.add_resource(endpoints.CreditsVintageAggregation, '/credits/agg/vintage')
+api.add_resource(endpoints.CreditsPoolAggregation, '/credits/agg/pool')
 api.add_resource(endpoints.CreditsPoolVintageAggregation, '/credits/agg/pool/vintage')
 api.add_resource(endpoints.CreditsPoolMethodologyAggregation, '/credits/agg/pool/methodology')
 api.add_resource(endpoints.CreditsPoolDatesAggregation, '/credits/agg/pool/<string:freq>')

src/apps/api/endpoints/__init__.py

@@ -7,6 +7,7 @@
     CreditsProjectsAggregation,
     CreditsMethodologiesAggregation,
     CreditsVintageAggregation,
+    CreditsPoolAggregation,
     CreditsPoolVintageAggregation,
     CreditsPoolMethodologyAggregation,
     CreditsPoolDatesAggregation,

src/apps/api/endpoints/credits.py

@@ -63,6 +63,9 @@ def get_credits(self, bridge=None):
         # Return credits
         return Service().filter(bridge, pool, status)
 
+    def get_pool_credits(self, bridge=None):
+        return self.get_credits(bridge).pool_analysis()
+
 
 class CreditsRaw(AbstractCredits):
     @layout_cache.cached(query_string=True)
@@ -164,7 +167,19 @@ class CreditsPoolVintageAggregation(AbstractCredits):
     )
     @helpers.with_output_formatter
     def get(self):
-        credits = self.get_credits().vintage_agg().pool_summary("vintage")
+        credits = self.get_pool_credits().vintage_agg().pool_summary("vintage")
+        return credits
+
+
+class CreditsPoolAggregation(AbstractCredits):
+    @layout_cache.cached(query_string=True)
+    @helpers.with_errors_handler
+    @helpers.with_help(
+        f"""{BASE_HELP}
+        """
+    )
+    def get(self):
+        credits = self.get_pool_credits().pool_summary().resolve().to_dict(orient='records')[0]
         return credits
 
 
@@ -178,7 +193,7 @@ class CreditsPoolMethodologyAggregation(AbstractCredits):
     )
     @helpers.with_output_formatter
     def get(self):
-        credits = self.get_credits().methodologies_agg().pool_summary("methodology")
+        credits = self.get_pool_credits().methodologies_agg().pool_summary("methodology")
         return credits
 
 
@@ -193,7 +208,7 @@ class CreditsPoolDatesAggregation(AbstractCredits):
     @helpers.with_output_formatter
     def get(self, freq):
         date_column = self.get_default_date_field()
-        credits = self.get_credits().date_agg(date_column, freq).pool_summary(date_column)
+        credits = self.get_pool_credits().date_agg(date_column, freq).pool_summary(date_column)
         return credits
 
 

src/apps/api/test.py

@@ -13,6 +13,7 @@
     "credits/agg/projects",
     "credits/agg/methodologies",
     "credits/agg/vintage",
+    "credits/agg/pool",
     "credits/agg/pool/vintage",
     "credits/agg/pool/methodology",
     "credits/agg/pool/daily",

src/apps/services/credits.py

@@ -110,8 +110,9 @@ def methodologies_agg(self, df):
         df = df.groupby("methodology")
         return df
 
+
     @chained_cached_command()
-    def pool_summary(self, df, date_field):
+    def pool_summary(self, df, kept_fields=[]):
         columns = [
             "quantity",
             "total_quantity",
@@ -121,16 +122,27 @@ def pool_summary(self, df, date_field):
             "nbo_quantity",
             "mco2_quantity"
         ]
+        if isinstance(df, pd.DataFrame):
+            df = df.groupby(lambda x: True)
+
+        if not isinstance(kept_fields, list):
+            kept_fields = [kept_fields]
 
         def summary(df):
             res_df = pd.DataFrame()
-            res_df[date_field] = [df[date_field].iloc[0]]
+            for kept_field in kept_fields:
+                res_df[kept_field] = [df[kept_field].iloc[0]]
 
+            not_pooled_quantity = df["total_quantity"].sum()
             for column in columns:
                 if column in df:
-                    res_df[column] = [df[column].sum()]
+                    column_quantity = df[column].sum()
+                    res_df[column] = [column_quantity]
+                    if column not in ["quantity", "total_quantity"]:
+                        not_pooled_quantity -= column_quantity
+            res_df["not_pooled_quantity"] = [not_pooled_quantity]
+
             return res_df
-
         df = df.apply(summary).reset_index(drop=True)
         return df
 
@@ -187,7 +199,9 @@ def filter_pool_quantity(self, df, quantity_column):
 
         return df
 
-    def drop_duplicates(self, df):
+    @chained_cached_command()
+    def pool_analysis(self, df):
+        """When analysing pools we need a subset of the data"""
         df = df.drop_duplicates(subset=["token_address"], keep="first")
         df = df.reset_index(drop=True)
         return df