Update app.py

app.py

@@ -3,7 +3,9 @@ import hashlib
 from time import strftime, gmtime
 import streamlit as st
 from datetime import datetime, timedelta
-import pandas as pd  # Assuming you'll convert the data to a Pandas DataFrame
+import pandas as pd
+import csv
+from io import StringIO
 
 # Function to fetch data from ShareASale
 def fetch_shareasale_data(action_verb, affiliate_id, api_token, api_secret_key, api_version=1.4):
@@ -26,11 +28,16 @@ def fetch_shareasale_data(action_verb, affiliate_id, api_token, api_secret_key,
     call = request.Request(f'https://shareasale.com/x.cfm?{data}', headers=my_headers)
     
     try:
-        return_result = request.urlopen(call).read()
+        return_result = request.urlopen(call).read().decode('utf-8')
         return return_result
     except Exception as inst:
         return str(inst)
 
+# Parse CSV data to a Pandas DataFrame
+def parse_csv_to_df(csv_data):
+    csv_stream = StringIO(csv_data)
+    return pd.read_csv(csv_stream, delimiter='|')
+
 # Streamlit UI
 st.title("Affiliate Earnings Dashboard")
 st.sidebar.title("Settings")
@@ -50,10 +57,8 @@ if st.sidebar.button("Fetch Data"):
     action_verb = 'ledger'
     ledger_data = fetch_shareasale_data(action_verb, my_affiliate_id, api_token, api_secret_key)
     
-    # TODO: Parse the ledger_data into a Pandas DataFrame (or any other suitable data structure)
-    # For demonstration, let's assume `ledger_data_df` is a Pandas DataFrame containing the parsed ledger data
-    # ledger_data_df = some_parsing_function(ledger_data)
+    # Parse the CSV data into a DataFrame
+    df = parse_csv_to_df(ledger_data)
     
-    # Display data as a table
-    # st.table(ledger_data_df)
-    st.write("Replace this line with the parsed table data using st.table")
+    # Display the DataFrame as a table
+    st.write(df)