From 6a89fc4e0cb40c4cfd9e4c09143379facf87f662 Mon Sep 17 00:00:00 2001
From: Nathan Jager <84308084+NaJager@users.noreply.github.com>
Date: Thu, 18 May 2023 14:23:41 +0200
Subject: [PATCH] Fix infinite loading if streamer hasn't been streaming

Current behavior for the Analytics dashboard when a streamer hasn't gone live within the selected timeframe is an infinitely loading graph. To fix this, I propose the following change which will instead try to fetch the last known point balance and display a straight line as the graph.
---
 .../classes/AnalyticsServer.py                   | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/TwitchChannelPointsMiner/classes/AnalyticsServer.py b/TwitchChannelPointsMiner/classes/AnalyticsServer.py
index b77eb25..3a08b11 100644
--- a/TwitchChannelPointsMiner/classes/AnalyticsServer.py
+++ b/TwitchChannelPointsMiner/classes/AnalyticsServer.py
@@ -51,6 +51,8 @@ def filter_datas(start_date, end_date, datas):
         else datetime.now()
     ).replace(hour=23, minute=59, second=59).timestamp() * 1000
 
+    original_series = datas["series"]
+    
     if "series" in datas:
         df = pd.DataFrame(datas["series"])
         df["datetime"] = pd.to_datetime(df.x // 1000, unit="s")
@@ -66,6 +68,20 @@ def filter_datas(start_date, end_date, datas):
     else:
         datas["series"] = []
 
+    # If no data is found within the timeframe, that usually means the streamer hasn't streamed within that timeframe
+    # We create a series that shows up as a straight line on the dashboard, with 'No Stream' as labels 
+    if len(datas["series"]) == 0: 
+        new_end_date = start_date; 
+        new_start_date = 0; 
+        df = pd.DataFrame(original_series)
+        df["datetime"] = pd.to_datetime(df.x // 1000, unit="s")
+
+        # Attempt to get the last known balance from before the provided timeframe
+        df = df[(df.x >= new_start_date) & (df.x <= new_end_date)]
+        last_balance = df.drop(columns="datetime").sort_values(by=["x", "y"], ascending=True).to_dict("records")[-1]['y'] 
+
+        datas["series"] = [{'x': start_date, 'y': last_balance, 'z': 'No Stream'}, {'x': end_date, 'y': last_balance, 'z': 'No Stream'}]; 
+        
     if "annotations" in datas:
         df = pd.DataFrame(datas["annotations"])
         df["datetime"] = pd.to_datetime(df.x // 1000, unit="s")