initial commit

markov.py

@@ -0,0 +1,47 @@
+import markovify
+import twitter
+import itertools
+import argparse
+
+## Command line parser
+parser = argparse.ArgumentParser(description='Process some integers.')
+parser.add_argument('filepath', metavar='CREDENTIALS', type=str, help='an integer for the accumulator')
+parser.add_argument('--text', dest='corpus', metavar='CORPUS', type=str, help='path to the text you wish to analyze')
+args = parser.parse_args()
+
+## Function to help process credentials file
+def drop_tag(str):
+    parsed = itertools.dropwhile(lambda x: x!= ':', str)
+    str2 = "".join(parsed)
+    parsed2 = itertools.dropwhile(lambda x: x == ' ' or x == ':', str2)
+    return "".join(parsed2)
+
+## Open file with credentials
+with open(args.filepath) as f:
+    content = f.readlines()
+
+## Process api keys etc.
+content = [drop_tag(x.strip()) for x in content] 
+
+# Get raw text of markov chain as string.
+with open(args.corpus) as f:
+    text = f.read()
+
+# Build the model.
+text_model = markovify.Text(text)
+
+# create twitter api object
+api = twitter.Api(consumer_key=content[0],
+                      consumer_secret=content[1],
+                      access_token_key=content[2],
+                      access_token_secret=content[3])
+
+# Generate three randomly-generated sentences of no more than 140 characters and tweet them.
+selected = False
+while selected == False:
+    str_potentially = text_model.make_short_sentence(140)
+    if not("http" in str_potentially):
+        status = api.PostUpdate(str_potentially)
+        print(status.text) # verify it worked
+        selected = True
+