Commit a draft from after the first working session

.gitignore

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+__pycache__
+config.py

bot.py

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+from mastodon import Mastodon
+import config
+import memory
+import time
+
+secret_file = config.user + '.secret'
+
+def register():
+    Mastodon.create_app(
+            config.user,
+            api_base_url = config.instance,
+            to_file = secret_file
+            )
+
+def connect(password):
+    api = Mastodon(
+            client_id = secret_file,
+            api_base_url = config.instance
+            )
+    api.log_in(
+            )
+
+def scalar(a, b):
+    return len(a.intersection(b))
+
+def answer(db, notifications):
+    for notification in notifications:
+        if notification.type == 'mention':
+            indexed_input = db.index(notification.status.content)
+            reply = memory.find_best_quote(db, indexed_input)
+
+def main():
+    api = connect(???)
+    db = memory.init('pratchett')
+    last = None
+    while True:
+        notifications = api.notifications(since_id=last)
+        if len(notifications) > 0:
+            last = notifications[0]
+            answer(db, notifications)
+        else:
+            time.sleep(config.delay)

config.py.default

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+instance = HOSTNAME_OF_THE_INSTANCE_HOSTING_THE_BOT
+user = USER_ACCOUNT_OF_THE_BOT
+email = EMAIL_ACCOUNT_OF_THE_BOT
+delay = HOW_OFTEN_DOES_THE_BOT_LOOK_FOR_NEW_MESSAGES

memory.py

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+import csv
+import json
+
+WORD_THRESHOLD = 4
+
+def build_db(inputCSV, outputJSON):
+    db = []
+    with open(inputCSV, 'r') as file:
+        csv_reader = csv.reader(file, delimiter=',')
+        data = False
+        for row in csv_reader:
+            if data:
+                db.append(row + (index(row[1]),))
+            else:
+                data = True
+    with open(outputJSON, 'w') as file:
+        json.dump(serialize(db), file)
+    return db
+
+def serialize(db):
+    return list(map(lambda row: (row[0], row[1], list(row[2])), db))
+
+def unserialize(db):
+    return list(map(lambda row: (row[0], row[1], set(row[2])), db))
+
+def open_db(filePath):
+    with open(filePath, 'r') as file:
+        return unserialize(json.load(file))
+
+def scalar(a, b):
+    return len(a.intersection(b))
+
+def find_best_quote(db, indexed_input)
+    max_score = None
+    for entry in db:
+
+
+def index(text):
+    words = map(lambda w: ''.join([c for c in w if c.isalpha()]), text.split(' '))
+    important_words = set([w for w in words if len(w) > WORD_THRESHOLD])
+    return important_words