class TestUtils: u = Utils() def test_extract_contents_of_one_bracket(self): s = "J6 (Birmingham)" assert self.u.extract_contents_of_nested_brackets(s) ==\ ["Birmingham"] def test_extract_contents_of_multiple_brackets(self): s = "J6 (Birmingham) and J7 (Birmingham (N) / Walsall)" assert self.u.extract_contents_of_nested_brackets(s) ==\ ["Birmingham", "Birmingham (N) / Walsall"] def test_extract_contents_of_multiple_brackets2(self): s = "J6 (Birmingham) and J7 (Birmingham (N) / Walsall (S))" assert self.u.extract_contents_of_nested_brackets(s) ==\ ["Birmingham", "Birmingham (N) / Walsall (S)"] def test_extract_contents_of_multiple_brackets3(self): s = "J6 (Birmingham (S)) and J7 (Birmingham (N) / Walsall (S))" assert self.u.extract_contents_of_nested_brackets(s) ==\ ["Birmingham (S)", "Birmingham (N) / Walsall (S)"]
printf.INFO(args.debug, "Detaching snapshot disk from " + args.backup_vm) response = detach_disk(bkpid, disk_id) printf.DEBUG(args.debug, "Detach Response: " + str(response.status_code)) time.sleep(10) # # Main #===== if __name__ == "__main__": ### ### Initial Variable creation and setup ### utils = Utils() vmid = None bkpid = None snapname = None snapid = None vm_disks = None now = datetime.datetime.now() date = now.strftime("%Y%m%d-%H%M") ### ### Argument Parsing ### parser = argparse.ArgumentParser( description="Process command line arguments")
import os import sys sys.path.insert(0, os.path.dirname(__file__) + '/..') from lib.process_data import ProcessData from lib.utils import Utils JSON_FILE = Utils().get_full_path("data/plaintext/rent.json") OUT_FILE = Utils().get_full_path("data/categoty/rent.json") process_data = Utils().process_data_json(JSON_FILE, OUT_FILE)
import os import json import sys sys.path.insert(0, os.path.dirname(__file__) + '/..') from underthesea import word_sent from textblob.classifiers import NaiveBayesClassifier from textblob import TextBlob from lib.classifier.base_classifier import CerberusBaseClassifier from lib.utils import Utils JSON_FILE = Utils().get_full_path("data/training/rent.json") class CerberusRentClassifier(CerberusBaseClassifier): def __init__(self): print("initialized CerberusRent") with open(JSON_FILE) as data_file: self.classifier = NaiveBayesClassifier(data_file, format="json")