Updating apex function to use tracker network

app/apex_legends.py

@@ -1,117 +1,80 @@
-import datetime
 import discord
 import os
 import requests
 
 
 def get_player(player):
-    # player = player.lower()
-    # url = "https://public-api.tracker.gg/v2/apex/standard/profile/origin/" + player
-    # headers = {
-    #     "User-Agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64)",
-    #     "accept": "application/json",
-    #     "TRN-Api-Key": os.getenv("tracker_network_token"),
-    # }
+    url = "https://public-api.tracker.gg/v2/apex/standard/profile/origin/" + player
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64)",
+        "accept": "application/json",
+        "TRN-Api-Key": os.getenv("tracker_network_token"),
+    }
 
-    url = (
-        "https://api.mozambiquehe.re/bridge?auth=%s&player=%s&platform=PC&merge=True"
-        % (
-            os.getenv("apex_api_key"),
-            player,
-        )
-    )
-    # print(url)
-    response = requests.get(url).json()
+    response = requests.get(url).json()["data"]
 
     # Build the embed
     embed = discord.Embed(description="-------", color=discord.Color.red(), type="rich")
-    embed.set_thumbnail(url=response["global"]["rank"]["rankImg"])
-    embed.set_author(name="Apex stats for %s" % response["global"]["name"])
-    embed.add_field(
-        name="**Rank**",
-        value="%s, %s"
-        % (
-            response["global"]["rank"]["rankName"],
-            response["global"]["rank"]["rankScore"],
-        ),
-        inline=False,
-    )
-    embed.add_field(
-        name="**Current level**",
-        value="%s, %s%% of the way to next level"
-        % (
-            response["global"]["level"],
-            response["global"]["toNextLevelPercent"],
-        ),
-        inline=False,
+    embed.set_thumbnail(url=response["platformInfo"]["avatarUrl"])
+    embed.set_author(
+        name="Apex stats for %s" % response["platformInfo"]["platformUserId"],
+        icon_url=response["segments"][0]["stats"]["peakRankScore"]["metadata"][
+            "iconUrl"
+        ],
     )
 
-    gameplay_stats = {
-        "kills": "Total kills",
-        "kd": "K/D",
-        "executions": "Executions",
-        "revives": "Revies",
-        "games_played": "Games Played",
-        "headshots": "Headshots",
-    }
+    embed.add_field(
+        name="**Current Rank**",
+        value=response["segments"][0]["stats"]["peakRankScore"]["displayName"],
+        inline=True,
+    )
 
-    embed.add_field(name="Totals", value="-------", inline=False)
-    for stat, readable in gameplay_stats.items():
+    embed.add_field(name="Account Wide stats", value="-----", inline=False)
+    stats_we_care_about = ["wins", "level", "kills", "damage", "headshots", "revives"]
+    for stat in stats_we_care_about:
         embed.add_field(
-            name="**%s**" % readable,
-            value=response["total"][stat]["value"],
+            name="**%s**" % response["segments"][0]["stats"][stat]["displayName"],
+            value=response["segments"][0]["stats"][stat]["displayValue"],
             inline=True,
         )
 
+    all_legends = response["segments"][1:]
+    # Calculate their most effective legends
+    embed.add_field(name="Bests", value="-----", inline=False)
+
     embed.add_field(
-        name="Stats per legend", value="---------------------", inline=False
+        name="**Legend with most kills**",
+        value="%s: %s"
+        % (
+            find_best(all_legends, key="kills")["metadata"]["name"],
+            find_best(all_legends, key="kills")["stats"]["kills"]["displayValue"],
+        ),
+    )
+    embed.add_field(
+        name="**Legend with most wins**",
+        value="%s: %s"
+        % (
+            find_best(all_legends, key="wins")["metadata"]["name"],
+            find_best(all_legends, key="wins")["stats"]["wins"]["displayValue"],
+        ),
+    )
+    embed.add_field(
+        name="**Legend with most damage**",
+        value="%s: %s"
+        % (
+            find_best(all_legends, key="damage")["metadata"]["name"],
+            find_best(all_legends, key="damage")["stats"]["damage"]["displayValue"],
+        ),
+    )
+    embed.add_field(
+        name="**Legend with most revives**",
+        value="%s: %s"
+        % (
+            find_best(all_legends, key="revives")["metadata"]["name"],
+            find_best(all_legends, key="revives")["stats"]["revives"]["displayValue"],
+        ),
     )
-    legends = response["legends"]["all"]
-    for legend in legends:
-        if "data" in response["legends"]["all"][legend] and legend != "Global":
-            data = response["legends"]["all"][legend]["data"]
-            smush = {x["key"]: x for x in data}
 
-            try:
-                legends_kills = smush["specialEvent_kills"]["value"] or 0
-                legends_damage = smush["specialEvent_damage"]["value"] or 0
-                legends_wins = smush["specialEvent_wins"]["value"] or 0
-
-                embed.add_field(
-                    name=legend,
-                    value="Total kills: %s\nTotal Damage: %s\nTotal Wins: %s"
-                    % (legends_kills, legends_damage, legends_wins),
-                )
-            except Exception as e:
-                print("%s threw an exception on %s" % (legend, e))
-                pass
-
-    # best_weapon = find_best(response["weapons"], "kills")
-
-    # embed.add_field(
-    #     name=":trophy:**Best Weapon**:trophy:",
-    #     value="%s\nkills: %s\naccuracy: %s\nHeadshots: %s"
-    #     % (
-    #         best_weapon["weaponName"],
-    #         best_weapon["kills"],
-    #         best_weapon["accuracy"],
-    #         best_weapon["headshotKills"],
-    #     ),
-    #     inline=True,
-    # )
-
-    # favorite_class = find_best(response["classes"], "secondsPlayed")
-
-    # embed.add_field(
-    #     name=":trophy:**Favorite Class**:trophy:",
-    #     value="%s\nKDR: %s\nTime Played: %s"
-    #     % (
-    #         favorite_class["characterName"],
-    #         favorite_class["killDeath"],
-    #         str(datetime.timedelta(seconds=favorite_class["secondsPlayed"])),
-    #     ),
-    #     inline=True,
-    # )
     return embed
 
 
@@ -123,4 +86,4 @@ def find_best(blob, key):
     and the key to use to make that distinction, for example, for weapons, you could use kills
     """
 
-    return max(blob, key=lambda x: x[key])
+    return max(blob, key=lambda x: x["stats"][key]["value"] if key in x else 0)