def as_tuples(strs):
res = []
for line in strs:
page_nos = [int(x) for x in words(line)]
for link in group2(page_nos):
res += [link]
return res
def frequency_count(filename):
word_count = Counter()
with open(filename) as inp:
for line in inp:
for word in words(line):
word_count[word] += 1
return word_count
def index_of_words(filename):
index = defaultdict(list)
with open(filename) as inp:
i = 0
for line in inp:
for word in words(line):
i += 1
index[word] += [i]
return index
def main():
filename = '/usr/share/dict/words'
words_list = []
with open(filename) as inp:
for line in inp:
words_list += words(line)
reversed_words = reverse_strings(words_list)
res = reverse_strings(sorted(reversed_words))
for word in res:
print(word)
def evaluate(string):
operand_stack = LinkedStack()
operator_stack = LinkedStack()
tokens = (tok.strip() for tok in words(string))
for tok in tokens:
if is_operator(tok):
operator_stack.push(tok)
elif tok == ')':
evaluate_single(operand_stack, operator_stack)
else:
operand_stack.push(tok)
print(operand_stack)
def index_of_words_(filename):
index = BinarySearchTree()
with open(filename) as inp:
i = 0
for line in inp:
for word in words(line):
i += 1
if word in index:
index[word] = index[word] + [i]
else:
index[word] = [i]
return index
def main():
corrections = {}
with open('../misspellings.txt') as misspellings_corrrections:
for line in misspellings_corrrections:
misspelling, correct = split_line(line)
corrections[misspelling] = correct
for line in stdin:
for word in words(line):
if word in corrections:
print(corrections[word])
else:
print(word)
def readFloatMatrixOrVector():
dimens = words(readStringArray(1)[0])
dimens = [int(n) for n in dimens]
if len(dimens) == 1:
line = readStringArray(1)[0]
return line_as_floats(line)
[nb_row, nb_col] = dimens
array = readStringArray(nb_row)
res = []
for row in array:
res += [line_as_floats(row)]
return res
def infix_to_postfix(string):
operand_stack = LinkedStack()
operator_stack = LinkedStack()
tokens = (tok.strip() for tok in words(string))
for tok in tokens:
print(operator_stack)
print(operand_stack)
if tok == '(':
continue
# operand_stack.push(tok)
elif is_operator(tok):
operator_stack.push(tok)
elif tok == ')':
b, a = operand_stack.pop(), operand_stack.pop()
op = operator_stack.pop()
# res = '[' + a + ' ' + b + op + ']'
res = a + ' ' + b + ' ' + op
operand_stack.push(res)
else:
operand_stack.push(tok)
print(operand_stack)
q = Queue()
q.enqueue(val)
queue.enqueue(q)
while len(queue) > 1:
q1 = queue.dequeue()
q2 = queue.dequeue()
queue.enqueue(merge(q1, q2))
return tuple(queue.dequeue())
if __name__ == "__main__":
a = Queue()
a.enqueue(1)
a.enqueue(2)
a.enqueue(4)
b = Queue()
b.enqueue(2)
b.enqueue(5)
b.enqueue(6)
print(merge(a, b))
a = [random.randrange(10) for i in range(100)]
print(merge_sort(a))
filename = sys.argv[1]
with open(filename) as lines:
wordslist = [word for line in lines for word in words(line)]
print(merge_sort(wordslist))
import sys
from distance import squared_distance
from ioutils import read_strings
from strutils import words
if __name__ == "__main__":
x = float(sys.argv[1])
y = float(sys.argv[2])
z = float(sys.argv[3])
array = read_strings()
res = []
def closest(x, y, z, v1, v2):
if squared_distance([x, y, z], v1) < squared_distance([x, y, z], v2):
return v1
return v2
for line in array:
[xi, yi, zi] = words(line)[0:3]
[xi, yi, zi] = [float(xi), float(yi), float(zi)]
if res == []:
res = [xi, yi, zi]
else:
res = closest(x, y, z, res, [xi, yi, xi])
print(res)
import sys
import re
from strutils import words
from array_utils import shannon_entropy_list
filename = sys.argv[1]
with open(filename) as corpus:
wordlist = []
for line in corpus:
for word in words(line):
word = word.lower()
word = re.sub(r'[^a-z]', '', word)
wordlist += [word]
print(shannon_entropy_list(wordlist))
def line_as_floats(line):
return [float(x) for x in words(line)]
from ioutils import read_strings
from strutils import words
if __name__ == "__main__":
array = read_strings()
for line in array:
words_array = words(line)
name = ' '.join(words_array[0:-2])
a = int(words_array[-2])
b = int(words_array[-1])
res = a / b
print('%25s' % name, '%3d' % a, '%3d' % b, '%3.3f' % res)
from ioutils import read_strings
from strutils import words
array = read_strings()
mtot = 0
mxtot = 0
mytot = 0
for line in array:
[m, x, y] = words(line)[0:3]
m, x, y = float(m), float(x), float(y)
mtot += m
mxtot += (m * x)
mytot += (m * y)
print(mxtot / mtot, mytot / mtot)
def main():
lexicon = build_lexicon('../words.utf-8.txt')
for line in stdin:
for word in words(line):
if word not in lexicon:
print(word)
