Stub out Python script to generate Markov chains.

bin/311_ebooks.py

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+
+
+import markovify #https://github.com/jsvine/markovify
+import sqlite3 #to read db
+
+# Open the db
+conn = sqlite3.connect('requests.sqlite')
+c = conn.cursor()
+
+def get_descriptions():
+    c.execute('SELECT description FROM requests')
+    data = c.fetchall()
+    return(data)
+
+# Get descriptions and convert to strings from tuples
+b = ["".join(str(x)) for x in get_descriptions()]
+
+# Build the model.
+text_model = markovify.Text(b)
+
+# Print three randomly-generated sentences of no more than 280 characters
+for i in range(3):
+    print(text_model.make_short_sentence(280))