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")
