Fixed issue with Predictor model

Fixed issue with Predictor model
Added repr for Predictor and PredictionOutcome

Author: chillymosh

docs/changelog.rst

@@ -24,13 +24,15 @@ Master
             - :func:`~twitchio.Client.update_chatter_color`
         - Add ``duration`` and ``vod_offset`` attributes to :class:`~twitchio.Clip`
         - Added repr for :class:`~twitchio.CustomReward`
+        - Added repr for :class:`~twitchio.PredictionOutcome`
         - Add extra attributes to :class:`~twitchio.UserBan`
     - Bug fixes
         - Added ``self.registered_callbacks = {}`` to :func:`~twitchio.Client.from_client_credentials`
         - Allow empty or missing initial_channels to trigger :func:`~twitchio.Client.event_ready`
         - Corrected :func:`twitchio.CustomRewardRedemption.fulfill` endpoint typo and creation
         - Corrected :func:`twitchio.CustomRewardRedemption.refund` endpoint typo and creation
         - Changed :func:`~twitchio.Client.join_channels` logic to handle bigger channel lists better
+        - Corrected :class:`~twitchio.Predictor` slots and user keys, repr has also been added
 
 - ext.commands
     - Bug fixes

twitchio/models.py

@@ -1090,13 +1090,15 @@ class Predictor:
         Number of Channel Points won by the user.
     """
 
-    __slots__ = ("outcome_id", "title", "channel_points", "color")
+    __slots__ = ("channel_points_used", "channel_points_won", "user")
 
     def __init__(self, http: "TwitchHTTP", data: dict):
         self.channel_points_used: int = data["channel_points_used"]
         self.channel_points_won: int = data["channel_points_won"]
-        self.user = PartialUser(http, data["user"]["id"], data["user"]["name"])
+        self.user = PartialUser(http, data["user_id"], data["user_login"])
 
+    def __repr__(self):
+        return f"<Predictor user={self.user} channel_points_used={self.channel_points_used} channel_points_won={self.channel_points_won}>"
 
 class PredictionOutcome:
     """
@@ -1129,7 +1131,11 @@ def __init__(self, http: "TwitchHTTP", data: dict):
         if data["top_predictors"]:
             self.top_predictors: List[Predictor] = [Predictor(http, x) for x in data["top_predictors"]]
         else:
+ 
             self.top_predictors: List[Predictor] = None
+    def __repr__(self):
+        return f"<PredictionOutcome outcome_id={self.outcome_id} title={self.title} channel_points={self.channel_points} color={self.color} users={self.users}>"
+
 
     @property
     def colour(self) -> str: