#5 Incorporated transaction error code generation logic into gen_tran…

…s_status() function

scripts/app/gen_trans_data.py

@@ -4,7 +4,6 @@
 import cons
 from utilities.gen_country_codes_map import gen_country_codes_map
 from utilities.align_country_codes import align_country_codes
-from utilities.gen_trans_error_codes import gen_trans_error_codes
 from utilities.gen_trans_rejection_rates import gen_trans_rejection_rates
 from utilities.gen_trans_status import gen_trans_status
 
@@ -88,14 +87,10 @@ def gen_trans_data(user_data, device_obj, card_obj, ip_obj, transaction_obj, app
     trans_data['card_country_code']  = trans_data['card_country_code'].replace(country_codes_map)
     trans_data['ip_country_code']  = trans_data['ip_country_code'].replace(country_codes_map)
 
-    # generate transaction status
-    trans_data['transaction_status'] = trans_data['transaction_hash'].replace(transaction_obj.transaction_hashes_status_dict)
+    # generate transaction status and error code
     rejection_rates_dict = gen_trans_rejection_rates(trans_data = trans_data)
-    trans_data['transaction_status'] = trans_data.apply(lambda series: gen_trans_status(series = series, rejection_rates_dict = rejection_rates_dict), axis = 1)
+    trans_data[['transaction_status', 'transaction_error_code']] = trans_data.apply(lambda series: gen_trans_status(series = series, rejection_rates_dict = rejection_rates_dict, rejection_codes = transaction_obj.rejection_codes), result_type = 'expand', axis = 1)
 
-    # add transaction status and error codes
-    trans_data['transaction_error_code'] = gen_trans_error_codes(trans_data = trans_data, trans_status_col = 'transaction_status', rejection_codes = transaction_obj.rejection_codes)
-
     # sort data by transaction date
     trans_data = trans_data.sort_values(by = 'transaction_date').reset_index(drop = True)
     return trans_data

scripts/utilities/gen_trans_status.py

@@ -3,7 +3,7 @@
 import cons
 
 
-def gen_trans_status(series, rejection_rates_dict):
+def gen_trans_status(series, rejection_rates_dict, rejection_codes):
     """Generates the transaction status for a pandas series from the transaction level telecom payments data given the rejection rates dictionary from the same data
 
     Parameters
@@ -12,63 +12,55 @@ def gen_trans_status(series, rejection_rates_dict):
         A pandas series from the transaction level telecom payments data
     rejection_rates_dict : dict
         Rejection rates generated the transaction level telecom payments data
+    rejection_codes : dict
+        A dictionary of rejection codes and assoicated proportions
 
     Returns
     -------
     str
         The transaction status for the pandas series
     """
     # set country code columns
-    country_code_columns = [
-        "registration_country_code",
-        "ip_country_code",
-        "card_country_code",
-    ]
+    country_code_columns = ["registration_country_code","ip_country_code","card_country_code"]
+
     if series['card_hash'] == series['card_hash']:
         # add rejections based on crime rates within country codes
-        if rejection_rates_dict["country_code_trans_reject_rate_dict"][
-            np.random.choice(a=series[country_code_columns].dropna().to_list(), size=1)[0]
-        ] >= random.uniform(0, 1):
+        if rejection_rates_dict["country_code_trans_reject_rate_dict"][np.random.choice(a=series[country_code_columns].dropna().to_list(), size=1)[0]] >= random.uniform(0, 1):
             status = "rejected"
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
         # add rejections based on domain frequencies
-        elif rejection_rates_dict["domain_email_trans_reject_rate_dict"][
-            series["email_domain"]
-        ] >= random.uniform(0, 1):
+        elif rejection_rates_dict["domain_email_trans_reject_rate_dict"][series["email_domain"]] >= random.uniform(0, 1):
             status = "rejected"
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
         # add rejections based on inconsistent country codes
-        elif cons.data_model_inconsistent_country_codes_rejection_rate[
-            series[country_code_columns].dropna().nunique()
-        ] >= random.uniform(0, 1):
+        elif cons.data_model_inconsistent_country_codes_rejection_rate[series[country_code_columns].dropna().nunique()] >= random.uniform(0, 1):
             status = "rejected"
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
         # add rejections based on shared ips, cards and devices
-        elif series["device_hash"] == series["device_hash"] and rejection_rates_dict[
-            "shared_devices_reject_rate_dict"
-        ][series["device_hash"]] >= random.uniform(0, 1):
+        elif series["device_hash"] == series["device_hash"] and rejection_rates_dict["shared_devices_reject_rate_dict"][series["device_hash"]] >= random.uniform(0, 1):
             status = "rejected"
-        elif series["ip_hash"] == series["ip_hash"] and rejection_rates_dict[
-            "shared_ips_reject_rate_dict"
-        ][series["ip_hash"]] >= random.uniform(0, 1):
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
+        elif series["ip_hash"] == series["ip_hash"] and rejection_rates_dict["shared_ips_reject_rate_dict"][series["ip_hash"]] >= random.uniform(0, 1):
             status = "rejected"
-        elif series["card_hash"] == series["card_hash"] and rejection_rates_dict[
-            "shared_cards_reject_rate_dict"
-        ][series["card_hash"]] >= random.uniform(0, 1):
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
+        elif series["card_hash"] == series["card_hash"] and rejection_rates_dict["shared_cards_reject_rate_dict"][series["card_hash"]] >= random.uniform(0, 1):
             status = "rejected"
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
         # add rejections based on counts of devices, ips and cards
-        elif rejection_rates_dict["count_devices_reject_rate_dict"][
-            series["userid"]
-        ] >= random.uniform(0, 1):
+        elif rejection_rates_dict["count_devices_reject_rate_dict"][series["userid"]] >= random.uniform(0, 1):
             status = "rejected"
-        elif rejection_rates_dict["count_ips_reject_rate_dict"][
-            series["userid"]
-        ] >= random.uniform(0, 1):
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
+        elif rejection_rates_dict["count_ips_reject_rate_dict"][series["userid"]] >= random.uniform(0, 1):
             status = "rejected"
-        elif rejection_rates_dict["count_cards_reject_rate_dict"][
-            series["userid"]
-        ] >= random.uniform(0, 1):
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
+        elif rejection_rates_dict["count_cards_reject_rate_dict"][series["userid"]] >= random.uniform(0, 1):
             status = "rejected"
+            error_code = np.random.choice(a=list(rejection_codes.keys()),p=list(rejection_codes.values()),size=1)[0]
         # otherwise return successful status
         else:
-            status = series["transaction_status"]
+            status = np.random.choice(a=['successful', 'pending'], size=1, p=[0.98, 0.02])[0]
+            error_code = np.nan
     else:
         status = np.random.choice(a=['successful', 'pending'], size=1, p=[0.98, 0.02])[0]
-    return status
+        error_code = np.nan
+    return [status, error_code]