commit f5f2dfbec857be87c897c09c3ee957bcb90f6faa
Author: xenofem <xenofem@xeno.science>
Date:   Wed May 13 16:26:31 2020 -0400

    Markov bot

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..54beaf3
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,5 @@
+token
+*~
+corpus.txt
+markov.json
+env/
diff --git a/markov-bot.py b/markov-bot.py
new file mode 100755
index 0000000..8812b91
--- /dev/null
+++ b/markov-bot.py
@@ -0,0 +1,55 @@
+#!/usr/bin/env python3
+
+import discord
+import json
+import random
+import sys
+
+
+START = "__START"
+END = "__END"
+
+with open('markov.json') as f:
+    markov = json.load(f)
+
+def gen_sentence():
+    cur = START
+    output = []
+    while True:
+        cur = random.choice(markov[cur])
+        if cur == END:
+            break
+        output.append(cur)
+
+    return ' '.join(output)
+
+class MyClient(discord.Client):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+        self.bg_task = self.loop.create_task(self.background())
+
+    async def on_ready(self):
+        print('logged in as {0.user}'.format(self), file=sys.stderr)
+
+    async def on_message(self, message):
+        if message.author == self.user or self.user not in message.mentions:
+            return
+
+        await message.channel.send(gen_sentence())
+
+    async def background(self):
+        await self.wait_until_ready()
+        while not self.is_closed():
+            for guild in self.guilds:
+                try:
+                    channel = random.choice(guild.text_channels)
+                    await channel.send(gen_sentence())
+                except:
+                    pass
+            await asyncio.sleep(3600)
+
+client = MyClient()
+with open('token') as f:
+    token = f.read().strip()
+client.run(token)
diff --git a/markov-prep.py b/markov-prep.py
new file mode 100755
index 0000000..e16561b
--- /dev/null
+++ b/markov-prep.py
@@ -0,0 +1,30 @@
+#!/usr/bin/env python3
+
+import json
+
+START = "__START"
+END = "__END"
+
+with open('corpus.txt') as f:
+    corpus = f.read().split()
+
+markov = {}
+
+def markov_add(cur, nxt):
+    if cur not in markov:
+        markov[cur] = []
+    markov[cur].append(nxt)
+
+cur = START
+for word in corpus:
+    if len(word) == 0:
+        continue
+    markov_add(cur, word)
+    if word[-1] in '.?!':
+        markov_add(word, END)
+        cur = START
+    else:
+        cur = word
+
+with open('markov.json', 'w') as f:
+    json.dump(markov, f)