fix comment

sdk/documentintelligence/azure-ai-documentintelligence/samples/aio/sample_analyze_custom_documents_async.py

@@ -29,20 +29,43 @@
 
 import os
 import asyncio
-import sys
+
+def print_table(header_names, table_data):
+    """Print a two-dimensional array like a table.
+
+    Based on provided column header names and two two-dimensional array data, print the strings like table.
+
+    Args:
+        header_names: An array of string, it's the column header names.  e.g. ["name", "gender", "age"]
+        table_data: A two-dimensional array, they're the table data.  e.g. [["Mike", "M", 25], ["John", "M", 19], ["Lily", "F", 23]]
+    Return: None
+        It's will print the string like table in output window. e.g.
+         Name    Gender    Age
+         Mike    M         25
+         John    M         19     
+         Lily    F         23
+    """
+    max_len_list = []
+    for i in range(len(header_names)):
+        col_values = list(map(lambda row: len(str(row[i])), table_data))
+        col_values.append(len(str(header_names[i])))
+        max_len_list.append(max(col_values))
+
+    row_format_str = "".join(map(lambda len: f"{{:<{len + 4}}}", max_len_list))
+
+    print(row_format_str.format(*header_names))
+    for row in table_data:
+        print(row_format_str.format(*row))
+
 
 async def analyze_custom_documents(custom_model_id):
-    path_of_parents = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..")
     path_to_sample_documents = os.path.abspath(
-        os.path.join(path_of_parents, "./sample_forms/forms/Form_1.jpg")
+        os.path.join(os.path.abspath(__file__), "..", "..", "./sample_forms/forms/Form_1.jpg")
     )
-    sys.path.append(path_of_parents)
-
     # [START analyze_custom_documents]
     from azure.core.credentials import AzureKeyCredential
     from azure.ai.documentintelligence.aio import DocumentIntelligenceClient
     from azure.ai.documentintelligence.models import AnalyzeResult
-    from helper import utils
 
     endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
     key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
@@ -101,7 +124,7 @@ async def analyze_custom_documents(custom_model_id):
                                 )
                                 row_data = list(map(extract_value_by_col_name, col_names))
                                 table_rows.append(row_data)
-                        utils.print_table(col_names, table_rows)
+                        print_table(col_names, table_rows)
     print("-----------------------------------")
     # [END analyze_custom_documents]
 

sdk/documentintelligence/azure-ai-documentintelligence/samples/sample_analyze_custom_documents.py

@@ -29,6 +29,33 @@
 
 import os
 
+def print_table(header_names, table_data):
+    """Print a two-dimensional array like a table.
+
+    Based on provided column header names and two two-dimensional array data, print the strings like table.
+
+    Args:
+        header_names: An array of string, it's the column header names.  e.g. ["name", "gender", "age"]
+        table_data: A two-dimensional array, they're the table data.  e.g. [["Mike", "M", 25], ["John", "M", 19], ["Lily", "F", 23]]
+    Return: None
+        It's will print the string like table in output window. e.g.
+         Name    Gender    Age
+         Mike    M         25
+         John    M         19     
+         Lily    F         23
+    """
+    max_len_list = []
+    for i in range(len(header_names)):
+        col_values = list(map(lambda row: len(str(row[i])), table_data))
+        col_values.append(len(str(header_names[i])))
+        max_len_list.append(max(col_values))
+
+    row_format_str = "".join(map(lambda len: f"{{:<{len + 4}}}", max_len_list))
+
+    print(row_format_str.format(*header_names))
+    for row in table_data:
+        print(row_format_str.format(*row))
+
 
 def analyze_custom_documents(custom_model_id):
     path_to_sample_documents = os.path.abspath(
@@ -38,7 +65,6 @@ def analyze_custom_documents(custom_model_id):
     from azure.core.credentials import AzureKeyCredential
     from azure.ai.documentintelligence import DocumentIntelligenceClient
     from azure.ai.documentintelligence.models import AnalyzeResult
-    from helper import utils
 
     endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
     key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
@@ -97,7 +123,7 @@ def analyze_custom_documents(custom_model_id):
                                 )
                                 row_data = list(map(extract_value_by_col_name, col_names))
                                 table_rows.append(row_data)
-                        utils.print_table(col_names, table_rows)
+                        print_table(col_names, table_rows)
 
     print("------------------------------------")
     # [END analyze_custom_documents]