def generateMarkovModel(): markovmodel = markov.main() markovmodel.generatemelody() pickler = picklejar.system() pickler.write("markovmodel", markovmodel)
def index(): # perhaps change this variable to random_sentences final_sentence = markov.main(text_list) # then push that sententence into your data structure # then create an algorithm to grab a random index from the data structure # set that to final_sentence '''NOTE: once your page has been loaded 1000's of times, your data structure of going to be huge. Time complexity is still O(1), but it could start to take up lots of space. If it gets to that, consider migrating your data to a database, and doing a fetch <~~~ don't optimize for this until you need to. ''' return render_template('index.html', final_sentence=final_sentence)
def parse_json(): """ takes in POST data as JSON from Node app and converts values to make them accessible to rest of Flask app """ if request.method == 'GET': # only executed with HTTP GET requests return """Please send a POST request to use this application. For additional information on use of this API, documentation can be found at: https://github.com/fchikwekwe/name-ly-API. """ params = request.get_json() # get the user's answers and add file extension name_number = params['nameNumber'] gender = params['gender'] + '.txt' cultural = params['cultural'] + '.txt' literary = params['literary'] + '.txt' markov_name = markov.main(name_number, gender, cultural, literary, 'corpus.txt') return jsonify(name=markov_name)
def test_first_integration(capsys): markov.main() out, err = capsys.readouterr() assert out == "hi there friend.\n", """\
import twitter import markov message = markov.main() print message api_file = open('api.txt') api_contents = api_file.read() api_contents_list = api_contents.split() api_dict = {} for item in api_contents_list: key_value = item.split(',') api_dict[key_value[0]] = key_value[1] api = twitter.Api( consumer_key = api_dict['api_key'], consumer_secret = api_dict['api_secret'], access_token_key = api_dict['access_token'], access_token_secret = api_dict['access_token_secret'] ) status = api.PostUpdate(message)
def submit(): their_input = request.form['input'] print "POST" # print their_input foo = markov.main(their_input) return render_template('template.html', my_string=foo)
def random_sentence(): return render_template("main.html", sentence=main())
import sys, random sys.path.insert(0, './src') import markov from flask import Flask, render_template app = Flask(__name__) markov_chain = markov.main() @app.route("/") def home(): generate_sentence = markov_chain.generate_sentence(25) # return render_template("main.html", sentence=generate_sentence) return generate_sentence if __name__ == "__main__": app.run(debug=True)
import os import twitter from markov import main TWITTER_CONSUMER_KEY = os.environ["TWITTER_CONSUMER_KEY"] TWITTER_CONSUMER_SECRET = os.environ["TWITTER_CONSUMER_SECRET"] TWITTER_ACCESS_TOKEN = os.environ["TWITTER_ACCESS_TOKEN"] TWITTER_ACCESS_TOKEN_SECRET = os.environ["TWITTER_ACCESS_TOKEN_SECRET"] api = twitter.Api( consumer_key=TWITTER_CONSUMER_KEY, consumer_secret=TWITTER_CONSUMER_SECRET, access_token_key=TWITTER_ACCESS_TOKEN, access_token_secret=TWITTER_ACCESS_TOKEN_SECRET ) text = main("markov_waka.txt","markov_seagulls.txt") status = api.PostUpdate(text)
def return_json(): """ Demonstration of api; returns json result """ json_name = markov.main(10, 'masculine.txt', 'fantasy.txt', 'modern.txt', 'corpus.txt') return jsonify(json_name)
import twitter import markov message = markov.main() print message api_file = open("lanakeys.txt").read() api_keys = api_file.split() api_dict = {} for item in api_keys: key_value = item.split(':') api_dict[key_value[0]] = key_value[1] api = twitter.Api(consumer_key=api_dict['consumer_key'], consumer_secret=api_dict['consumer_secret'], access_token_key=api_dict['access_token_key'], access_token_secret=api_dict['access_token_secret']) status = api.PostUpdate(message)
# main script, uses other modules to generate sentences from flask import Flask, render_template # from stochastic_sampling import weighted_random import markov import re app = Flask(__name__) app.markov = markov.main() @app.route("/") def sentence_generator(): """ """ final_sentence = app.markov.create_sentence() return render_template("main.html", sentence=final_sentence)
import twitter import markov import secret api = twitter.Api(consumer_key=CON_SEC, consumer_secret=CON_SEC_KEY, access_token_key=TOKEN, access_token_secret=TOKEN_KEY) msg = markov.main() print msg status = api.PostUpdate(msg)
def generateWavandKey(): content = markov.main().generatemelody() contentsize = sys.getsizeof(content) key = "" return [content, contentsize, key]
def index(): """ Demonstration of api; returns a web template""" index_name = markov.main(10, 'feminine.txt', 'fantasy.txt', 'modern.txt', 'corpus.txt') return render_template('index.html', index_name=index_name)
async def on_message(message): author = message.author if message.content.startswith('<@241600786470010881>'): output = main(message.content) await client.send_message(message.channel, output)
import os import twitter from markov import main TWITTER_CONSUMER_KEY = os.environ["TWITTER_CONSUMER_KEY"] TWITTER_CONSUMER_SECRET = os.environ["TWITTER_CONSUMER_SECRET"] TWITTER_ACCESS_TOKEN = os.environ["TWITTER_ACCESS_TOKEN"] TWITTER_ACCESS_SECRET = os.environ["TWITTER_ACCESS_SECRET"] api = twitter.Api(consumer_key=TWITTER_CONSUMER_KEY, consumer_secret=TWITTER_CONSUMER_SECRET, access_token_key=TWITTER_ACCESS_TOKEN, access_token_secret=TWITTER_ACCESS_SECRET) tweet_string = main() status = api.PostUpdate(tweet_string) print tweet_string print status