presence scanner working yay

src/data_types/presence.py

@@ -10,32 +10,61 @@ class Presence:
         self.most_used_reaction = ""
         self.most_used_reaction_count = 0
         self.used_reaction_total = 1
+        self.used_reaction_all_total = 1
         self.channel_usage = defaultdict(int)
+        self.channel_total = defaultdict(int)
         self.mentions = defaultdict(int)
+        self.mention_others = defaultdict(int)
+        self.msg_count = 0
+        self.total_msg = 0
+        self.mention_count = 0
 
-    def to_string(self, *, show_top_channel: bool, show_mentioned: bool) -> List[str]:
+    def to_string(self, *, show_top_channel: bool, member_specific: bool) -> List[str]:
         ret = []
+        if member_specific:
+            ret += [
+                f"- **messages**: {self.msg_count} ({100*self.msg_count/self.total_msg:.0f}% of server's)"
+            ]
         if show_top_channel:
             top_channel = sorted(self.channel_usage)[-1]
             channel_sum = sum(self.channel_usage.values())
+            found_in = sorted(
+                self.channel_usage,
+                key=lambda k: self.channel_usage[k] / self.channel_total[k],
+            )[-1]
             ret += [
-                f"- **most visited channel**: {channel_mention(top_channel)} ({self.channel_usage[top_channel]:,} msg, {100*self.channel_usage[top_channel]//channel_sum:.0f}%)"
+                f"- **most visited channel**: {channel_mention(top_channel)} ({self.channel_usage[top_channel]:,} msg, {100*self.channel_usage[top_channel]//channel_sum:.0f}%)",
+                f"- **mostly found in**: {channel_mention(found_in)} ({self.channel_usage[found_in]:,} msg, {100*self.channel_usage[found_in]//self.channel_total[found_in]:.0f}% of channel's)",
             ]
-        if show_mentioned:
+        if member_specific:
             if len(self.mentions) > 0:
                 top_mention = sorted(self.mentions)[-1]
                 mention_sum = sum(self.mentions.values())
                 ret += [
-                    f"- **mentioned**: {plural(mention_sum, 'time')}",
+                    f"- **was mentioned**: {plural(mention_sum, 'time')} ({100*mention_sum/self.mention_count:.0f}% of server's)",
                     f"- **mostly mentioned by**: {mention(top_mention)} ({plural(self.mentions[top_mention], 'time')}, {100*self.mentions[top_mention]//mention_sum:.0f}%)",
                 ]
             else:
-                ret += [f"- **mentioned**: 0 times"]
+                ret += ["- **was mentioned**: 0 times"]
+            if len(self.mention_others) > 0:
+                top_mention = sorted(self.mention_others)[-1]
+                mention_sum = sum(self.mention_others.values())
+                ret += [
+                    f"- **mentioned others**: {plural(mention_sum, 'time')} ({100*mention_sum/self.mention_count:.0f}% of server's)",
+                    f"- **mostly mentioned**: {mention(top_mention)} ({plural(self.mention_others[top_mention], 'time')}, {100*self.mention_others[top_mention]//mention_sum:.0f}%)",
+                ]
+            else:
+                ret += ["- **was mentioned**: 0 times"]
         if self.used_reaction_total > 0:
+            # ({self.used_reaction_total/self.used_reaction_all_total})
             ret += [
                 f"- **reactions**: {plural(self.used_reaction_total, 'time')}",
                 f"- **most used reaction**: {self.most_used_reaction} ({plural(self.most_used_reaction_count, 'time')}, {100*self.most_used_reaction_count/self.used_reaction_total:.0f}%)",
             ]
+            if member_specific:
+                ret[
+                    -2
+                ] += f" ({100*self.used_reaction_total/self.used_reaction_all_total:.0f}% of server's)"
         else:
-            ret += [f"- **reactions**: 0 times"]
+            ret += ["- **reactions**: 0 times"]
         return ret

src/scanners/full_scanner.py

@@ -35,9 +35,13 @@ class FullScanner(Scanner):
         self.freq = Frequency()
         self.comp = Composition()
         self.pres = Presence()
-        # Create emotes dict from custom emojis of the guild
+        self.member_specific = len(self.members) > 0
         # Create emotes dict from custom emojis of the guild
         self.emotes = get_emote_dict(message.channel.guild)
+        if self.member_specific:
+            self.emotes_all = get_emote_dict(message.channel.guild)
+        else:
+            self.emotes_all = {}
         return True
 
     def compute_message(self, channel: ChannelLogs, message: MessageLog):
@@ -47,6 +51,8 @@ class FullScanner(Scanner):
         EmotesScanner.analyse_message(
             message, self.emotes, self.raw_members, all_emojis=True
         )
+        if self.member_specific:
+            EmotesScanner.analyse_message(message, self.emotes_all, [], all_emojis=True)
         return not message.bot and (
             len(self.raw_members) == 0 or message.author in self.raw_members
         )
@@ -54,7 +60,7 @@ class FullScanner(Scanner):
     def get_results(self, intro: str) -> List[str]:
         FrequencyScanner.compute_results(self.freq)
         CompositionScanner.compute_results(self.comp, self.emotes)
-        PresenceScanner.compute_results(self.pres, self.emotes)
+        PresenceScanner.compute_results(self.pres, self.emotes, self.emotes_all)
         res = [intro]
         res += ["__Frequency__:"]
         res += self.freq.to_string()
@@ -63,6 +69,6 @@ class FullScanner(Scanner):
         res += ["__Presence__:"]
         res += self.pres.to_string(
             show_top_channel=len(self.channels) > 1,
-            show_mentioned=(len(self.members) > 0),
+            member_specific=self.member_specific,
         )
         return res

src/scanners/presence_scanner.py

@@ -31,24 +31,31 @@ class PresenceScanner(Scanner):
 
     async def init(self, message: discord.Message, *args: str) -> bool:
         self.pres = Presence()
+        self.member_specific = len(self.members) > 0
         # Create emotes dict from custom emojis of the guild
         self.emotes = get_emote_dict(message.channel.guild)
+        if self.member_specific:
+            self.emotes_all = get_emote_dict(message.channel.guild)
+        else:
+            self.emotes_all = {}
         return True
 
     def compute_message(self, channel: ChannelLogs, message: MessageLog):
         EmotesScanner.analyse_message(
             message, self.emotes, self.raw_members, all_emojis=True
         )
+        if self.member_specific:
+            EmotesScanner.analyse_message(message, self.emotes_all, [], all_emojis=True)
         return PresenceScanner.analyse_message(
             channel, message, self.pres, self.raw_members
         )
 
     def get_results(self, intro: str) -> List[str]:
-        PresenceScanner.compute_results(self.pres, self.emotes)
+        PresenceScanner.compute_results(self.pres, self.emotes, self.emotes_all)
         res = [intro]
         res += self.pres.to_string(
             show_top_channel=(len(self.channels) > 1),
-            show_mentioned=(len(self.members) > 0),
+            member_specific=self.member_specific,
         )
         return res
 
@@ -64,15 +71,27 @@ class PresenceScanner(Scanner):
         if not message.bot and (len(raw_members) == 0 or message.author in raw_members):
             impacted = True
             pres.channel_usage[channel.id] += 1
+            pres.msg_count += 1
+            for mention in message.mentions:
+                pres.mention_others[mention] += 1
+        pres.channel_total[channel.id] += 1
         for mention in message.mentions:
             if mention in raw_members:
-                pres.mentions[mention] += 1
+                pres.mentions[message.author] += 1
+            pres.mention_count += 1
+        pres.total_msg += 1
         return impacted
 
     @staticmethod
-    def compute_results(pres: Presence, emotes: Dict[str, Emote]):
+    def compute_results(
+        pres: Presence, emotes: Dict[str, Emote], emotes_all: Dict[str, Emote]
+    ):
         # calculate total reactions
         pres.used_reaction_total = sum([emote.reactions for emote in emotes.values()])
+        if len(emotes_all) > 0:
+            pres.used_reaction_all_total = sum(
+                [emote.reactions for emote in emotes_all.values()]
+            )
         if pres.used_reaction_total > 0:
             # calculate most used reaction
             pres.most_used_reaction = sorted(emotes, key=lambda k: emotes[k].reactions)[