black and flake8 linter fixes

parsons/action_builder/action_builder.py

@@ -279,7 +279,7 @@ def add_section_field_values_to_record(
             {
                 "action_builder:name": tag,
                 "action_builder:field": field,
-                "action_builder:section": section
+                "action_builder:section": section,
             }
             for field, tag in field_values.items()
         ]

test/test_action_builder/test_action_builder.py

@@ -127,7 +127,7 @@ def setUp(self, m):
 
         self.fake_field_values = {
             "Fake Field 2": "Fake Tag 5",
-            self.fake_field_1: self.fake_tag_4
+            self.fake_field_1: self.fake_tag_4,
         }
 
         self.fake_tagging = [
@@ -140,7 +140,7 @@ def setUp(self, m):
                 "action_builder:name": "Fake Tag 5",
                 "action_builder:field": "Fake Field 2",
                 "action_builder:section": self.fake_section,
-            }
+            },
         ]
 
         self.fake_entity_id = "fake-entity-id-1"
@@ -162,7 +162,7 @@ def setUp(self, m):
                     "status": "unsubscribed",
                     "source": "api",
                 }
-            ]
+            ],
         }
 
         self.fake_upsert_person = {
@@ -179,9 +179,9 @@ def setUp(self, m):
                         "action_builder:identifier": "action_builder:fake-email-id-1",
                         "address": "fakey@mcfakerson.com",
                         "address_type": "Work",
-                        "status": "unsubscribed"
+                        "status": "unsubscribed",
                     }
-                ]
+                ],
             }
         }
 
@@ -197,7 +197,7 @@ def setUp(self, m):
                     "created_date": self.fake_datetime,
                     "modified_date": self.fake_datetime,
                 }
-            }
+            },
         }
 
         self.fake_update_person = {
@@ -234,7 +234,8 @@ def test_get_all_records(self, m):
             text=json.dumps({"_embedded": {"osdi:tags": []}}),
         )
         assert_matching_tables(
-            self.bldr._get_all_records(self.campaign, "tags"), Table(self.fake_tags_list)
+            self.bldr._get_all_records(self.campaign, "tags"),
+            Table(self.fake_tags_list),
         )
 
     @requests_mock.Mocker()
@@ -274,14 +275,15 @@ def prepare_dict_key_intersection(self, dict1, dict2):
         # Internal method to compare a reference dict to a new incoming one, keeping only common
         # keys whose values are not lists (i.e. nested).
 
-        common_keys = {key for key, value in dict1.items() if key in dict2
-                       and not isinstance(value, list)}
+        common_keys = {
+            key
+            for key, value in dict1.items()
+            if key in dict2 and not isinstance(value, list)
+        }
 
-        dict1_comp = {key: value for key, value in dict1.items()
-                      if key in common_keys}
+        dict1_comp = {key: value for key, value in dict1.items() if key in common_keys}
 
-        dict2_comp = {key: value for key, value in dict2.items()
-                      if key in common_keys}
+        dict2_comp = {key: value for key, value in dict2.items() if key in common_keys}
 
         return dict1_comp, dict2_comp
 
@@ -291,7 +293,9 @@ def test_upsert_entity(self, m):
 
         # Flatten and remove items added for spreadable arguments
         upsert_person = self.fake_upsert_person["person"]
-        upsert_response = self.bldr._upsert_entity(self.fake_upsert_person, self.campaign)
+        upsert_response = self.bldr._upsert_entity(
+            self.fake_upsert_person, self.campaign
+        )
 
         person_comp, upsert_response_comp = self.prepare_dict_key_intersection(
             upsert_person, upsert_response
@@ -348,15 +352,13 @@ def tagging_callback(self, request, context):
         tagging_data = post_data["add_tags"]
 
         # Force the sort to allow for predictable comparison
-        return sorted(tagging_data, key=lambda k: k['action_builder:name'])
+        return sorted(tagging_data, key=lambda k: k["action_builder:name"])
 
     @requests_mock.Mocker()
     def test_add_section_field_values_to_record(self, m):
         m.post(f"{self.api_url}/people", json=self.tagging_callback)
         add_tags_response = self.bldr.add_section_field_values_to_record(
-            self.fake_entity_id,
-            self.fake_section,
-            self.fake_field_values
+            self.fake_entity_id, self.fake_section, self.fake_field_values
         )
         self.assertEqual(add_tags_response, self.fake_tagging)
 

useful_resources/sample_code/ngpvan_sample_printedlist.py

@@ -3,20 +3,27 @@
 This script pulls turf information (i.e. precinct name, list number, people count, door count, etc.)
 from a specificed NGP VAN folder and creates a master check list and pdf printouts to circumvent
 the sometimes lengthy process in VAN.
-To use the script, be sure to set your environmental variables for VAN_API_KEY and GOOGLE_DRIVE_CREDENTIALS. 
-The blog post explaining contextual information for this script can be found here: . 
-Please also note that due to the inability to test the script, I decided to pare it down. It does not 
-include turf prioritization, apartment demarcation, and walkability scores as shown in the blog post.
+
+To use the script, be sure to set your environmental variables for VAN_API_KEY and
+GOOGLE_DRIVE_CREDENTIALS.
+
+The blog post explaining contextual information for this script can be found here: .
+
+Please also note that due to the inability to test the script,
+I decided to pare it down. It does not include turf prioritization, apartment demarcation,
+and walkability scores as shown in the blog post.
+
 To execute the script, run:
-    python3 ngpvan_sample_printedlist.py --van_folder_name="{Name of NGP VAN folder where printed lists are stored}" --gsheet_uri={URI for gsheet where NGP VAN data will be stored}""
+    python3 ngpvan_sample_printedlist.py \
+    --van_folder_name="{Name of NGP VAN folder where printed lists are stored}" \
+    --gsheet_uri="{URI for gsheet where NGP VAN data will be stored}"
 """
 
-import pandas as pd
 from fpdf import FPDF
 from parsons import VAN, GoogleSheets, Table
-import json
 import click
 
+
 # ~~~~~~~~~~~~~~ Get Printed and Saved List Info From VAN ~~~~~~~~~~~~~~~~#