add line_function.py

line_fucntion.py

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+import pandas as pd
+#DEF ZONE
+def line_header(CHANNEL_LINE):
+    LINE_HEADER = {"Content-Type": "application/json", "Authorization": f"Bearer {CHANNEL_LINE}"}
+    return LINE_HEADER
+
+def add_new_line_audience(file_path, audience_name, id_column='line_uid', description_key='description', is_ifa_audience="false"):
+    '''
+    Generates a payload for creating a new LINE audience based on a CSV file containing user IDs.
+    Args:
+        file_path (str): The path to the CSV file containing the audience data.
+        audience_name (str): The name or description of the audience, which will be included in the payload.
+        id_column (str, optional): The column name in the CSV file that contains the unique audience IDs. Default is 'line_uid'.
+        description_key (str, optional): The key name used in the payload for the audience description. Default is 'description'.
+        is_ifa_audience (str, optional): A flag indicating whether the audience is an IFA audience. Default is "false".
+    Returns:
+        dict: A dictionary payload with the following structure:
+            {
+                "description_key": "audience_name",
+                "isIfaAudience": "is_ifa_audience",
+                "audiences": [{"id": audience_id_1}, {"id": audience_id_2}, ...]
+            }
+        The 'audiences' list will contain the unique audience IDs found in the specified `id_column` of the CSV.
+    '''
+    
+    df = pd.read_csv(file_path)
+    payload = {
+        description_key: audience_name,
+        "isIfaAudience": is_ifa_audience,
+        "audiences": []
+    }
+
+    # Loop through the unique audience IDs and add them to the payload
+    for audience_id in df[id_column].unique():
+        payload["audiences"].append({"id": audience_id})
+
+    return payload
+
+
+def update_line_audience(file_path, audience_id):
+    '''
+    Generates a payload to update an existing LINE audience group with user IDs from a CSV file.
+    Args:
+        file_path (str): The path to the CSV file containing the audience data.
+        audience_id (int or str): The ID of the existing audience group that needs to be updated.
+    Returns:
+        dict: A dictionary payload with the following structure:
+            {
+                "audienceGroupId": audience_id,
+                "audiences": [{"id": audience_id_1}, {"id": audience_id_2}, ...]
+            }
+        The 'audiences' list will contain the unique audience IDs found in the 'line_uid' column of the CSV.
+    '''
+    
+    # Load the CSV into a DataFrame
+    df = pd.read_csv(file_path)
+    
+    # Prepare the payload with the audience group ID and empty audiences list
+    payload = {
+        "audienceGroupId": int(audience_id),
+        "audiences": []
+    }
+
+    # Loop through the unique audience IDs and add them to the payload
+    for audience_id in df['line_uid'].unique():
+        payload["audiences"].append({"id": audience_id})
+
+    return payload
+
+
+def single_message(message):
+    json =  {
+            "type": "text",
+            "text": f"{message}",
+          }
+    return json
+
+
+def message_push(to, messageObject):
+    json = {
+        "to": to,
+        "messages":messageObject
+        }
+    return json
+
+def image_map_single(altText, imageLink, ladingpage, width, height):
+    data =  {
+        "type": "imagemap",
+        "baseUrl": imageLink,
+        "altText": altText,
+        "baseSize": {
+            "width": int(width),
+            "height": int(height)
+        },  "actions": [
+            {
+            "type": "uri",
+            "linkUri": ladingpage,
+            "area": {
+                "x": 0,
+                "y": 0,
+                "width": int(width),
+                "height": int(height)
+            }
+            }]
+        }
+    return data

requirements.txt

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+pandas==2.2.
+gradio==4.44.1