def testRunAll(self):
m = mox.Mox()
m.StubOutWithMock(main, "system")
m.StubOutWithMock(main, "read_from_file")
m.StubOutWithMock(main, "get_all")
m.StubOutWithMock(main, "get_directory")
main.get_directory("language", "problem", "variation").AndReturn("directory")
main.get_all().AndReturn([("language", "problem", "variation")])
main.inputs = [main.ProblemInput(10, 15, 20, 30, 40)]
main.TIMEOUT = 99
main.threads = [999]
main.system(
(
"" # 'timeout 99 ' # TODO timeout on ensisun
"/usr/bin/time -a -f %e -o "
"time-language-problem-variation-0-999.out "
"directory/main < "
"problem_10_15_20_30_40.in > /dev/null 1>&0 2>&0"
),
timeout=True,
)
main.read_from_file("time-language-problem-variation-0-999.out")
m.ReplayAll()
main.run_all()
m.VerifyAll()
m.UnsetStubs()
def test_big_text_get_and_sort_concordance_term(self):
"""
Checks if a context sorts right for a given term and can be found properly
"""
text = read_from_file('lab_1/data.txt')
tokens = tokenize(text)
expected = [['although', 'less', 'compact', 'than', 'tex', 'the',
'xml', 'structuring', 'promises', 'to', 'make', 'it',
'widely', 'usable', 'and', 'allows', 'for', 'instant',
'display']]
actual = sort_concordance(tokens, 'tex', 4, 14, True)
self.assertEqual(expected, actual)
def test_get_adjacent_words_several_contexts_big_text(self):
"""
Checks if adjacent words for a given term can be found in real text properly
"""
text = read_from_file('lab_1/data.txt')
tokens = tokenize(text)
expected = [['epithelial', 'channels'],
['means', 'aluminate'],
['by', 'bicarbonate'],
['the', 'salt']]
actual = get_adjacent_words(tokens, 'sodium', 1, 1)
self.assertEqual(expected, actual)
def test_get_concordance_several_contexts_big_text_right(self):
"""
Checks if contexts for a given term can be found in real text properly
Taking into consideration right context
"""
text = read_from_file('lab_1/data.txt')
tokens = tokenize(text)
expected = [['means', 'sodium', 'aluminate'],
['by', 'sodium', 'bicarbonate'],
['epithelial', 'sodium', 'channels'],
['the', 'sodium', 'salt']]
actual = sort_concordance(tokens, 'sodium', 1, 1, False)
self.assertEqual(expected, actual)
def test_big_text_get_concordance_term(self):
"""
Checks if a context for a given term can be found properly
"""
text = read_from_file('lab_1/data.txt')
tokens = tokenize(text)
expected = [['although', 'less', 'compact', 'than', 'tex', 'the',
'xml', 'structuring', 'promises', 'to', 'make', 'it',
'widely', 'usable', 'and', 'allows', 'for', 'instant',
'display', 'in', 'applications', 'such', 'as', 'web',
'browsers', 'and', 'facilitates', 'an', 'interpretation',
'of', 'its', 'meaning', 'in', 'mathematical', 'software', 'products']]
actual = get_concordance(tokens, 'tex', 4, 31)
self.assertEqual(expected, actual)
"""
Concordance implementation starter
"""
import os
import main
if __name__ == '__main__':
# use data.txt file to test your program
current_dir = os.path.dirname(os.path.abspath(__file__))
data = main.read_from_file(os.path.join(current_dir, 'data.txt'))
stop_words = main.read_from_file(
os.path.join(current_dir, 'stop_words.txt')).split('\n')
# here goes your logic: calling methods from concordance.py
tokens = main.tokenize(data)
print('tokens:', tokens[:10])
print('\n-----------------------------\n')
tokens = main.remove_stop_words(tokens,
stop_words) # old: 34 sec, new - 3.4 sec
print('tokens without stop words:', tokens[:10])
print('\n-----------------------------\n')
frequencies = main.calculate_frequencies(
tokens) # old: 116 sec, new: ~81 sec
print('frequency for the first word:', frequencies[tokens[0]])
print('\n-----------------------------\n')
top_10 = main.get_top_n_words(frequencies, 10)
print('top 10 words:', top_10)
"""
Concordance implementation starter
"""
from main import read_from_file
if __name__ == '__main__':
# use data.txt file to test your program
data = read_from_file('data.txt')
stop_words = []
# here goes your logic: calling methods from concordance.py
RESULT = None
# DO NOT REMOVE NEXT LINE - KEEP IT INTENTIONALLY LAST
assert RESULT == [(), ()], 'Concordance not working'
return rx
def print_results(data, id):
# wc(s)
print("--", id, ":", data["given_name"], data["family_name"])
print("\t" + data["ftechique"])
print("\t" + data["gender"])
print("\t" + data["age"], "years old")
print("\t" + data["height"] + "cm")
print("\t" + data["country"])
print("\t" + data["points"], "points")
print("\t" + data["place"] + "th", "place")
#print("\t" + data["categories"])
print()
if __name__ == "__main__":
d = main.read_from_file()
ars = sys.argv
ars.pop(0)
search_technique(d, make_regex(ars[0]))
"""
except Exception as e:
print(str(e))
print("Please enter arguments:")
print("[Fav. technique] [Height] [Gender] [Category]")
exit()
"""
import requests
import time
from main import read_from_file, save_to_file, convert_file
my_api_key = read_from_file("api_key.json")
my_api_key = my_api_key['bb_api_key']
# The 5 category links
#Motherboard - abcat0507008
motherboard="https://api.bestbuy.com/v1/products((categoryPath.id=abcat0507008&customerReviewAverage>=3.5))?&pageSize=100&format=json&show=categoryPath.id,name,regularPrice,salePrice,url,customerReviewAverage,manufacturer,image,longDescription&apiKey="
#CPU - abcat0507010
cpu="https://api.bestbuy.com/v1/products((categoryPath.id=abcat0507010&customerReviewAverage>=3.5))?&pageSize=100&format=json&show=categoryPath.id,name,regularPrice,salePrice,url,customerReviewAverage,manufacturer,image,longDescription&apiKey="
#CPU Cooler - pcmcat339900050006
cpucooler="https://api.bestbuy.com/v1/products((categoryPath.id=pcmcat339900050006&customerReviewAverage>=3.5))?&pageSize=100&format=json&show=categoryPath.id,name,regularPrice,salePrice,url,customerReviewAverage,manufacturer,image,longDescription&apiKey="
#Memory(RAM) - abcat0506000
ram="https://api.bestbuy.com/v1/products((categoryPath.id=abcat0506000&customerReviewAverage>=3.5))?&pageSize=100&format=json&show=categoryPath.id,name,regularPrice,salePrice,url,customerReviewAverage,manufacturer,image,longDescription&apiKey="
#Storage(SSD/HDD) - pcmcat270900050001
storage="https://api.bestbuy.com/v1/products((categoryPath.id=pcmcat270900050001&customerReviewAverage>=3.5))?&pageSize=100&format=json&show=categoryPath.id,name,regularPrice,salePrice,url,customerReviewAverage,manufacturer,image,longDescription&apiKey="
#GPU - abcat0507002
gpu="https://api.bestbuy.com/v1/products((categoryPath.id=abcat0507002&customerReviewAverage>=3.5))?&pageSize=100&format=json&show=categoryPath.id,name,regularPrice,salePrice,url,customerReviewAverage,manufacturer,image,longDescription&apiKey="
#PSU - abcat0507009
psu="https://api.bestbuy.com/v1/products((categoryPath.id=abcat0507009&customerReviewAverage>=3.5))?&pageSize=100&format=json&show=categoryPath.id,name,regularPrice,salePrice,url,customerReviewAverage,manufacturer,image,longDescription&apiKey="
url_bb = motherboard+my_api_key
#bb_json=requests.get(url_bb).json()