[MAINTENANCE]Update PandasProfiling and GreatExpectations (#87)

* updated pp and gx

---------

Co-authored-by: bvolodarskiy <bvolodarskiy@provectus.com>

functions/allure_report/mapper.py

@@ -73,9 +73,9 @@ def get_test_name(file):
 def get_suit_name(file, i):
     if "column" in i["expectation_config"]["kwargs"]:
         column = i["expectation_config"]["kwargs"]["column"]
-        data_asset_name = file["meta"]["batch_kwargs"]["data_asset_name"]
+        data_asset_name = file["meta"]["active_batch_definition"]["data_asset_name"]
         return f"{data_asset_name}.{column}"
-    return file["meta"]["batch_kwargs"]["data_asset_name"]
+    return file["meta"]["active_batch_definition"]["data_asset_name"]
 
 
 def get_jira_ticket(file):
@@ -103,11 +103,14 @@ def get_stop_suit_time():
 
 
 def parse_datetime(date_str):
-    return datetime.timestamp(datetime.strptime(date_str, '%Y%m%dT%H%M%S.%fZ')) * 1000
+    if '+00:00' in date_str:
+        return datetime.timestamp(datetime.strptime(date_str, '%Y-%m-%dT%H:%M:%S.%f+00:00')) * 1000
+    else:
+        return datetime.timestamp(datetime.strptime(date_str, '%Y%m%dT%H%M%S.%fZ')) * 1000
 
 
 def get_start_test_time(file):
-    return parse_datetime(file['meta']['run_id']['run_name'])
+    return parse_datetime(file['meta']['run_id']['run_time'])
 
 
 def get_stop_test_time(file):
@@ -116,7 +119,7 @@ def get_stop_test_time(file):
 
 def get_params(file):
     params = file['expectation_config']['kwargs']
-    del params['result_format']
+    del params['batch_id']
     results = []
     for param in params:
         if isinstance(params[param], list):
@@ -140,7 +143,7 @@ def get_test_description(file):
     for f in file["result"]:
         if str(f) != "observed_value":
             result = result + "\n" + \
-                f"{str(f)}: {str(file['result'][f])}" + "\n"
+                     f"{str(f)}: {str(file['result'][f])}" + "\n"
     return result
 
 
@@ -198,7 +201,7 @@ def create_categories_json(json_name, key):
     result = json.dumps(data)
     s3.Object(qa_bucket,
               f"allure/{json_name}{key}/result/categories.json").put(
-                Body=bytes(result.encode("UTF-8")))
+        Body=bytes(result.encode("UTF-8")))
 
 
 def get_uuid(i, json_name, key):
@@ -242,7 +245,7 @@ def create_suit_json(json_name, key, validate_id):
                 {
                     "name": "severity",
                     "value": get_severity(i)
-            }
+                }
             ],
             "links": [get_jira_ticket(i)],
             "name": get_test_name(i),

functions/data_test/data_source_factory.py

@@ -5,16 +5,24 @@
 
 ENV = os.environ['ENVIRONMENT']
 
+
 class DataSourceFactory:
-    
+
     @staticmethod
-    def create_data_source(engine, qa_bucket_name, extension, run_name, table_name, coverage_config):
+    def create_data_source(
+            engine,
+            qa_bucket_name,
+            extension,
+            run_name,
+            table_name,
+            coverage_config):
         if engine == 's3':
             return S3DataSource(extension)
         elif engine == 'athena':
             return AthenaDataSource(qa_bucket_name, table_name)
         elif engine == 'redshift':
-            return RedshiftDataSource(qa_bucket_name, run_name, table_name, coverage_config)
+            return RedshiftDataSource(
+                qa_bucket_name, run_name, table_name, coverage_config)
         elif engine == 'hudi':
             return HudiDataSource(qa_bucket_name, run_name, table_name)
         else:
@@ -43,7 +51,7 @@ def read(self, source):
                 return wr.s3.read_json(path=source, lines=True), source
         else:
             return wr.s3.read_parquet(path=source), source
-        
+
 
 class AthenaDataSource(DataSource):
     def __init__(self, qa_bucket_name, table_name):
@@ -76,9 +84,10 @@ def read(self, source):
             redshift_db = os.environ['REDSHIFT_DB']
             redshift_secret = os.environ['REDSHIFT_SECRET']
             try:
-                sort_keys_config = json.loads(
-                    wr.s3.read_json(path=f"s3://{self.qa_bucket_name}/test_configs/sort_keys.json").to_json())
-                sort_key = list(map(str.lower, sort_keys_config[self.table_name]["sortKey"]))
+                sort_keys_config = json.loads(wr.s3.read_json(
+                    path=f"s3://{self.qa_bucket_name}/test_configs/sort_keys.json").to_json())
+                sort_key = list(map(str.lower,
+                                    sort_keys_config[self.table_name]["sortKey"]))
             except KeyError:
                 sort_key = ['update_dt']
             try:
@@ -87,29 +96,34 @@ def read(self, source):
                 target_table = None
             if target_table:
                 table_name = target_table
-            con = wr.redshift.connect(secret_id=redshift_secret, dbname=redshift_db)
+            con = wr.redshift.connect(
+                secret_id=redshift_secret, dbname=redshift_db)
             try:
                 nunique = final_df.nunique()[sort_key][0]
-            except (KeyError,IndexError) as e:
+            except (KeyError, IndexError) as e:
                 nunique = final_df.nunique()[sort_key]
             if nunique > 1:
                 min_key = final_df[sort_key].min()
                 max_key = final_df[sort_key].max()
-                if type(min_key) != str or type(max_key) != str:
+                if not isinstance(
+                        min_key,
+                        str) or not isinstance(
+                        max_key,
+                        str):
                     min_key = final_df[sort_key].min()[0]
                     max_key = final_df[sort_key].max()[0]
                 sql_query = f"SELECT * FROM public.{self.table_name} WHERE {sort_key[0]} between \\'{min_key}\\' and \\'{max_key}\\'"
             else:
                 key = final_df[sort_key].values[0]
-                if type(key) != str:
+                if not isinstance(key, str):
                     key = str(key[0])
                 sql_query = f"SELECT * FROM {table_name}.{table_name} WHERE {sort_key[0]}=\\'{key}\\'"
             path = f"s3://{self.qa_bucket_name}/redshift/{self.table_name}/"
             final_df = self.unload_final_df(sql_query, con, path)
         return final_df, source
 
     def unload_final_df(self, sql_query, con, path):
-        try: 
+        try:
             final_df = wr.redshift.unload(
                 sql=sql_query,
                 con=con,
@@ -119,20 +133,27 @@ def unload_final_df(self, sql_query, con, path):
             con.close()
         return final_df
 
+
 class HudiDataSource(DataSource):
     def __init__(self, qa_bucket_name, run_name, table_name):
         self.qa_bucket_name = qa_bucket_name
         self.run_name = run_name
         self.table_name = table_name
 
     def read(self, source):
-        columns_to_drop = ['_hoodie_commit_time', '_hoodie_commit_seqno', '_hoodie_record_key',
-                           '_hoodie_partition_path', '_hoodie_file_name']
-        pk_config = wr.s3.read_json(path=f"s3://{self.qa_bucket_name}/test_configs/pks.json")
+        columns_to_drop = [
+            '_hoodie_commit_time',
+            '_hoodie_commit_seqno',
+            '_hoodie_record_key',
+            '_hoodie_partition_path',
+            '_hoodie_file_name']
+        pk_config = wr.s3.read_json(
+            path=f"s3://{self.qa_bucket_name}/test_configs/pks.json")
         parquet_args = {
             'timestamp_as_object': True
         }
-        df = wr.s3.read_parquet(path=source, pyarrow_additional_kwargs=parquet_args)
+        df = wr.s3.read_parquet(path=source,
+                                pyarrow_additional_kwargs=parquet_args)
         try:
             primary_key = pk_config[self.table_name][0]
         except KeyError:
@@ -147,12 +168,16 @@ def read(self, source):
                 ctas_approach=False,
                 s3_output=f"s3://{self.qa_bucket_name}/athena_results/"
             )
-            final_df = data[data['dms_load_at'].isin(keys)].reset_index(drop=True)
+            final_df = data[data['dms_load_at'].isin(
+                keys)].reset_index(drop=True)
             try:
                 path = final_df['_hoodie_commit_time'].iloc[0]
             except IndexError:
                 raise IndexError('Keys from CDC not found in HUDI table')
-            final_df = final_df.drop(columns_to_drop, axis=1).reset_index(drop=True)
+            final_df = final_df.drop(
+                columns_to_drop,
+                axis=1).reset_index(
+                drop=True)
             return final_df, path
         else:
             keys = df.groupby(primary_key)['dms_load_at'].max().tolist()

functions/data_test/data_test.py

@@ -32,7 +32,7 @@ def handler(event, context):
     mapping_config = json.loads(
         s3.Object(qa_bucket_name, "test_configs/mapping.json").get()["Body"]
         .read().decode("utf-8"))
-    if type(source_input) is not list:
+    if not isinstance(source_input, list):
         source = [source_input]
     else:
         source = source_input
@@ -54,11 +54,13 @@ def handler(event, context):
     final_ds, path = prepare_final_ds(source, engine, source_root, run_name,
                                       source_name, suite_coverage_config)
 
-    profile_link, folder_key, config = profile_data(final_ds, suite_name,
-                                                    cloudfront, source_root,
-                                                    source_covered,
-                                                    mapping_config, run_name)
-    validate_id = validate_data(final_ds, suite_name, config)
+    profile_link, folder_key, saved_context, data_asset = profile_data(
+        final_ds, suite_name, cloudfront, source_root, source_covered, mapping_config, run_name)
+    validate_id = validate_data(
+        final_ds,
+        suite_name,
+        saved_context,
+        data_asset)
     test_suite = f"{cloudfront}/data_docs/validations/{validate_id}.html"
 
     report = {