示例#1
0
    def __init__(self, bot):
        threading.Thread.__init__(self)
        self.db = MongoConnector()
        self.db.connect(cp['DATABASE']['Address'], cp['DATABASE']['Name'])
        self.collection = cp['DATABASE']['MonitoringCollection']

        self.telegram_bot = bot

        self.running = True

        print('Reward crawler started')
示例#2
0
def main():
    tornado.options.options['logging'] = "INFO"
    tornado.options.parse_command_line()

    io_loop = tornado.ioloop.IOLoop.instance()

    app = make_app()

    # MongoConnector is our mongodb connector
    mongo_connector = MongoConnector('test_database',
                                     mongo_address=settings.MONGO_ADDRESS)
    app.mongo_connector = mongo_connector
    # PikaConnector is our rabbitmq consumer
    app.pika_connector = PikaConnector(
        io_loop, mongo_connector, rabbitmq_address=settings.RABBITMQ_ADDRESS)
    app.pika_connector.run()

    try:
        app.listen(8888)
        io_loop.start()

    except KeyboardInterrupt:
        app.pika_connector.stop()
示例#3
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import time
import logging
import datetime
import re

# Enable logging
logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
                    level=logging.INFO)

logger = logging.getLogger(__name__)

cp = ConfigParser()
cp.optionxform = str
cp.read('../config.ini')

db = MongoConnector()
db.connect(cp['DATABASE']['Address'], cp['DATABASE']['Name'])

blockchain = BlockchainConnector()
blockchain.connect(cp['POSTGRES'])

monitoring_collection = cp['DATABASE']['MonitoringCollection']

CRAWLER_SLEEP_TIME = 120

NEW_TRANSACTION_MESSAGE_TEMPLATE = 'New transaction for "{}" ({}): {} XSN'
telegram_bot_token = cp['TELEGRAM']['SecretKey']

DATE_FORMAT = '%d/%m/%Y %H:%M:%S'
ADD_ADDRESS_MESSAGE = 'Enter address for '
ADD_NAME_MESSAGE = 'Enter monitor name'
示例#4
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            classifications = clf.predict_proba(transformed)
            #print("classifications", classifications)

            sorted_prob_themes = sorted(
                [(prob, theme_nr)
                 for prob, theme_nr in zip(classifications[0], classes)],
                reverse=True)
            sorted_themes = [
                int(theme_nr) for (prob, theme_nr) in sorted_prob_themes
            ]
            print("Used logistic regression classification")

        sorted_themes_using_topic_connection = self.rank_according_to_topic_connection(
            document_id, sorted_themes, potential_theme_dict)

        for theme in all_theme_nrs:  # themes that have no associate documents or description, and therefore aren't classifier ranked, are ranked as last
            if theme not in sorted_themes_using_topic_connection:
                sorted_themes_using_topic_connection.append(theme)
        themes_str = [
            str(theme) for theme in sorted_themes_using_topic_connection
        ]
        return themes_str


if __name__ == '__main__':
    mc = MongoConnector()
    ts = ThemeSorter(mc)
    ts.retrain_model("61ea6c0301c7c1346b1ff9f4")
    print(ts.rank_themes_for_document("61ea6c0301c7c1346b1ff9f4", "14"))
示例#5
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    def get(self):
        global mongoConnector

        word_document = mongoConnector.getDocumentByWord(
            request.args.get("word")[1:-1])
        return word_document.guessNextWord()


class Ping(Resource):
    def get(self):

        return "Alive"


if __name__ == "__main__":

    if len(sys.argv) != 5:
        print("Usage: problem3.py <host> <port> <database> <collection>")
        sys.exit(-1)

    mongoConnector = MongoConnector(sys.argv[1], int(sys.argv[2]), sys.argv[3],
                                    sys.argv[4])

    app = Flask(__name__)
    api = Api(app)

    api.add_resource(Ping, '/')
    api.add_resource(Next, '/gutenberg/predict/next/')
    api.add_resource(Guess, '/gutenberg/predict/random/')

    app.run(debug=True)
示例#6
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    import topics2themes.make_topic_models as make_topic_models
    from topics2themes.mongo_connector import MongoConnector
    from topics2themes.theme_sorter import ThemeSorter
    from topics2themes.environment_configuration import *
    from topics2themes.topic_model_constants import *


app = Flask(__name__, template_folder="user_interface")

if RUN_LOCALLY:
    CORS(app)
else:
    app.config['MONGO_CONNECT'] = False

try:
    mongo_con = MongoConnector()
except:
    e = sys.exc_info()
    print("The following error occurred: ")
    print(e)
    print("The pymongo database might not be running")
    mongo_con = MongoConnector()
    exit(1)

theme_sort = ThemeSorter(mongo_con)

# To not have a lot of space in the output
app.config['JSONIFY_PRETTYPRINT_REGULAR'] = False

def get_more_exception_info():
    trace_back = traceback.format_exc()