def checkNewRegistration(self, user):
content = ""
player_name = self.request.get("player_name")
player_age = self.request.get("player_age")
if helpers.validateName(player_name) is False:
content = """
<div id="fail_message"><h3>Trouble! Your player name has some issues.<h3></div>
"""
if self.checkAlreadyExists(player_name):
content = (
content
+ """
<div id="fail_message"><h3>Dadgum it! Someone already took that name.<h3></div>
"""
)
if not helpers.is_number(player_age):
content = (
content
+ """
<div id="fail_message"><h3>It appears you didn't enter a valid number for your age. You do know your age, don't you?<h3></div>
"""
)
else:
player_age = int(player_age)
if player_age < 13 or player_age > 135:
content = (
content
+ """
<div id="fail_message"><h3>Your age is outside the valid range. Either you're too young or you're impossibly old.<h3></div>
"""
)
if content != "":
content = content + '<div><a href="/"><h3>Click here to return and try again.<h3></a></div>'
return content
def edit_balance(self, amount, opperation):
if is_number(amount) and float(amount) > 0 and amount <= self.balance:
if opperation == "+":
self.balance += float(amount)
elif opperation == "-":
self.balance -= float(amount)
self.save()
return True
else:
return False
def add():
# If new cost submitted
if request.method == "POST":
# Check number was submitted
# for cost per unit field
t = request.form.get("unitCost")
ppu = is_number(t)
# If not a number, prompt user
# for a number by using if statement
# in Jinja template to render error message
if not ppu:
return render_template("addcost.html", s=session["s"], ppu=ppu)
# Get variables from new cost form
cost_name = request.form.get("costName")
unit = request.form.get("unit")
currency = request.form.get("currency")
unit_cost = request.form.get("unitCost")
quantity = request.form.get("quantity")
# Calculate total amount of cost
cost_total = float(unit_cost) * float(quantity)
# Get id of project selected
x = db.execute(
"SELECT id FROM projects WHERE project_name = :project_name",
project_name=session["s"])
project_id = x[0]["id"]
# Add cost details to database
db.execute(
"INSERT INTO costs (project_id, cost_name, total_cost, unit, unit_cost, quantity, currency) VALUES (:project_id, :cost_name, :cost_total, :unit, :unit_cost, :quantity, :currency)",
project_id=project_id,
cost_name=cost_name,
cost_total=cost_total,
unit=unit,
unit_cost=unit_cost,
quantity=quantity,
currency=currency)
# If valid form submitted
# render table showing breakdown of
# all project costs
return redirect("/breakdown")
# If new cost from requested
# render cost form
else:
return render_template("addcost.html", s=session["s"])
def solve(input):
lines = input.splitlines()
letters = 'abcdefgh'
items = {}
for num in range(len(letters)):
items[letters[num]] = 0
items['a'] = 1
currentIndex = 0
i = 1
count = 0
while currentIndex < len(lines) and currentIndex >= 0:
i += 1
line = lines[currentIndex]
splitLine = line.split(" ")
command = splitLine[0]
key = splitLine[1]
value = 0
if len(splitLine) == 3:
if is_number(splitLine[2]):
value = int(splitLine[2])
else:
value = items[splitLine[2]]
if command == 'set':
items[key] = value
if command == 'sub':
items[key] -= value
if command == 'mul':
count += 1
items[key] *= value
if command == 'jnz':
if (is_number(key) and key != 0) or items[key] != 0:
currentIndex += value
else:
currentIndex += 1
else:
currentIndex += 1
return items['h']
def calc_avg_angles():
# TODO: To Be Continued...
sums = np.zeros(NUM_OF_ANGLES)
with open(ANGLES_PATH, 'r') as angles:
for line_count, line in enumerate(angles):
curr_angles = json.loads(line)
for n, angle in enumerate(curr_angles):
if is_number(angle[3]):
sums[n] += angle[3]
avgs = []
for i, j in enumerate(sums):
avgs.append(j / (line_count + 1))
with open(ANGLES_AVG_PATH, 'w') as avgs_file:
json.dump(avgs, avgs_file)
def solve(input):
lines = input.splitlines()
letters = 'abcdefghijklmnopqrstuvwxyz'
items = {}
for num in range(len(letters)):
items[letters[num]] = 0
lastPlayedSound = 0
recoveredSound = 0
currentIndex = 0
i = 1
while currentIndex < len(lines) and currentIndex >= 0:
i += 1
line = lines[currentIndex]
splitLine = line.split(" ")
command = splitLine[0]
key = splitLine[1]
value = 0
if len(splitLine) == 3:
if is_number(splitLine[2]):
value = int(splitLine[2])
else:
value = items[splitLine[2]]
if command == 'set':
items[key] = value
if command == 'add':
items[key] += value
if command == 'mul':
items[key] *= value
if command == 'mod':
items[key] = items[key] % value
if command == 'snd':
lastPlayedSound = items[key]
if command == 'jgz':
if items[key] > 0:
currentIndex += value
else:
currentIndex += 1
else:
currentIndex += 1
if command == 'rcv':
if items[key] > 0:
recoveredSound = lastPlayedSound
break
return recoveredSound
def golden_test(img_name):
img = cv2.imread(IMG_PATH + img_name)
lands = lands_from_img(img)
all_dists = all_distances(lands, allow_repeats=True)
rs = ratios(all_dists)
angs = angles(lands)
for i, j in enumerate(rs):
if abs(j[3] - PHI) < 0.005:
ang = angs[tuple(sorted((j[0], j[1], j[2])))]
if not is_number(ang) or ang < 90:
continue
p1 = tuple(lands[rs[i][0]])
p2 = tuple(lands[rs[i][1]])
p3 = tuple(lands[rs[i][2]])
draw_lines(img, p1, p2, p3)
cv2.imshow('golden-test', img)
cv2.imwrite('golden-test-angles.jpg', img)
cvwait()
from sklearn.svm import SVC
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import confusion_matrix
from sklearn.cross_validation import KFold
from sklearn.tree import DecisionTreeClassifier
from settings import *
from helpers import is_number
from functions import get_user_by_name, get_interesting_user, \
build_data_set, vectorize, StackOverflow
print "Running with feature level", FEATURES_LEVEL
user = sys.argv[1] if len(sys.argv) > 1 else DEFAULT_USER
if not is_number(user):
elem = get_user_by_name(user) if user else get_interesting_user()
if elem is None:
print "User '%s' not found" % user
exit(1)
user_id = int(elem.get("Id"))
else:
user_id = int(user)
print "Building ML model for user %d" % user_id
instances, classes, tags_cnt = build_data_set(user_id, FEATURES_LEVEL == 0)
print "Set built, %d(%d+%d) (ratio: %.2f)" % (len(classes),
classes.count(Classes.INTERESTED),
classes.count(Classes.UNKNOWN),
def solve(input):
lines = input.splitlines()
letters = 'abcdefghijklmnopqrstuvwxyz'
items1 = {}
items2 = {}
for num in range(len(letters)):
items1[letters[num]] = 0
items1['p'] = 0
for num in range(len(letters)):
items2[letters[num]] = 0
items2['p'] = 1
items1Queue = []
items2Queue = []
currentIndex1 = 0
currentIndex2 = 0
deadLocked1 = False
deadLocked2 = False
count = 0
while True:
if currentIndex1 >= 0 and currentIndex1 < len(lines):
line = lines[currentIndex1]
splitLine = line.split(" ")
command = splitLine[0]
key = splitLine[1]
value = 0
if len(splitLine) == 3:
if is_number(splitLine[2]):
value = int(splitLine[2])
else:
value = items1[splitLine[2]]
if command == 'set':
items1[key] = value
if command == 'add':
items1[key] += value
if command == 'mul':
items1[key] *= value
if command == 'mod':
items1[key] = items1[key] % value
if command == 'snd':
items2Queue.append(items1[key])
if command == 'jgz':
if (is_number(key) and int(key) > 0) or items1[key] > 0:
currentIndex1 += value
else:
currentIndex1 += 1
else:
if command != 'rcv' or (command == 'rcv'
and len(items1Queue) > 0):
currentIndex1 += 1
if command == 'rcv':
if len(items1Queue) > 0:
items1[key] = items1Queue[0]
items1Queue = items1Queue[1:]
else:
deadLocked1 = True
if currentIndex2 >= 0 and currentIndex2 < len(lines):
line = lines[currentIndex2]
splitLine = line.split(" ")
command = splitLine[0]
key = splitLine[1]
value = 0
if len(splitLine) == 3:
if is_number(splitLine[2]):
value = int(splitLine[2])
else:
value = items2[splitLine[2]]
if command == 'set':
items2[key] = value
if command == 'add':
items2[key] += value
if command == 'mul':
items2[key] *= value
if command == 'mod':
items2[key] = items2[key] % value
if command == 'snd':
items1Queue.append(items2[key])
count += 1
if command == 'jgz':
if (is_number(key) and int(key) > 0) or items2[key] > 0:
currentIndex2 += value
else:
currentIndex2 += 1
else:
if command != 'rcv' or (command == 'rcv'
and len(items2Queue) > 0):
currentIndex2 += 1
if command == 'rcv':
if len(items2Queue) > 0:
items2[key] = items2Queue[0]
items2Queue = items2Queue[1:]
else:
deadLocked2 = True
print(deadLocked1, deadLocked2)
if deadLocked1 and deadLocked2:
break
return count
def get_matching_columns(self, phrase, value, tags=[], table_name=""):
"""
Goes through all the tables
Matches with all columns
Returns potential matches
:param phrase: phrase for which we are figuring out query
:param value: value to be looked up in cached data
:return: list of (table_name, column_name)
"""
to_return = []
# it's possible that we get numbers as strings
if helpers.is_number(value):
value = float(value)
# go through all the tables
for table in self._columns.keys():
# if a table name is provided, search only in that table
if table_name.strip() != "" and table != table_name:
continue
# go through each column in the table
found_some_column = False
for column in self._columns[table]:
# check if types match
if type(value) == str and column[1] == "TEXT":
# check if it's a perfect match
if column[0] in self._distinct_values[table]:
match_result = self.match_with_values(
self._distinct_values[table][column[0]], value)
# sometimes we can have substring in names
# in such cases, let's make similarity score 0.5
if helpers.similarity_score(helpers.to_unicode(column[0]), helpers.to_unicode("name")) > 0.5 \
and any(value in string for string in self._distinct_values[table][column[0]]):
if match_result[0] < 0.5:
match_result = 0.5
if match_result[0] > 0:
to_return.append(table, column[0], match_result[0])
found_some_column = True
# TODO::Improve matching logic by considering a small error range
elif (type(value) == int
or type(value) == float) and (column[1] == "INTEGER"
or column[1] == "REAL"):
if column[0] in self._distinct_values[table]:
match_result = self.match_for_numbers(
self._distinct_values[table][column[0]], value)
if (match_result[0] > 0):
to_return.append(
(table, column[0], match_result[0]))
found_some_column = True
if not found_some_column:
# find the column which matches the most
match_score = 0.0
match_col = ""
for column in self._columns[table]:
col_score = self.match_with_column_name(
phrase, value, column[0], tags)
# TODO::Refine the filtering logic
if col_score > 0 and col_score > match_score:
match_score = col_score
match_col = column[0]
to_return.append((table, match_col, match_score))
return to_return
import numpy as np
from sklearn.svm import SVC
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import confusion_matrix
from sklearn.cross_validation import KFold
from sklearn.tree import DecisionTreeClassifier
from settings import *
from helpers import is_number
from functions import get_user_by_name, get_interesting_user, \
build_data_set, vectorize, StackOverflow
print "Running with feature level", FEATURES_LEVEL
user = sys.argv[1] if len(sys.argv) > 1 else DEFAULT_USER
if not is_number(user):
elem = get_user_by_name(user) if user else get_interesting_user()
if elem is None:
print "User '%s' not found" % user
exit(1)
user_id = int(elem.get("Id"))
else:
user_id = int(user)
print "Building ML model for user %d" % user_id
instances, classes, tags_cnt = build_data_set(user_id, FEATURES_LEVEL == 0)
print "Set built, %d(%d+%d) (ratio: %.2f)" % (
len(classes), classes.count(
Classes.INTERESTED), classes.count(Classes.UNKNOWN), ML_DATA_RATIO)
def get_matching_columns(self, phrase, value):
"""
Goes through all the tables
Matches with all columns
Returns potential matches
:param phrase: phrase for which we are figuring out query
:param value: value to be looked up in cached data
:return: list of (table_name, column_name)
"""
to_return = []
# it's possible that we get numbers as strings
if helpers.is_number(value):
value = float(value)
# go through all the tables
for table in self._columns.keys():
# go through each column in the table
found_some_column = False
for column in self._columns[table]:
# check if types match
if type(value) == str and column[1] == "TEXT":
# check if it's a perfect match
if column[0] in self._distinct_values[table] and \
value in self._distinct_values[table][column[0]]:
# it's a perfect match
to_return.append((table, column[0], 1))
found_some_column = True
elif column[0] in self._distinct_values[table] and \
any(value in string for string in self._distinct_values[table][column[0]]):
# it's an imperfect match
# TODO::Add better logic here based on string lengths, matching length, context, etc.
# scope for improvement
to_return.append((table, column[0], 0.5))
found_some_column = True
# TODO::Improve matching logic by considering a small error range
elif (type(value) == int
or type(value) == float) and (column[1] == "INT"
or column[1] == "REAL"):
if column[0] in self._distinct_values[table] and \
value in self._distinct_values[table][column[0]]:
# perfect match
to_return.append((table, column[0], 1))
found_some_column = True
if not found_some_column:
# find the column which matches the most
match_score = 0.0
match_col = ""
for column in self._columns[table]:
col_score = self.match_with_column_name(
phrase, value, column[0])
# TODO::Refine the filtering logic
if col_score > 0 and col_score > match_score:
match_score = col_score
match_col = column[0]
to_return.append((table, match_col, match_score))
return to_return