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#!/usr/bin/env python3
# package version
__version__ = '3.0.0-beta'
|
class BingException(Exception):
"""A generic exception for all bing-related exceptions. You can catch all exceptions with this."""
pass
class BadAuth(BingException):
"""An invalid authorization was passed in"""
pass
class NotEnoughResults(BingException):
"""There weren't enough results."""
pass
|
# Write a program that reads four integer numbers.
# It should add the first to the second number, integer divide the sum by the third number,
# and multiply the result by the fourth number. Print the final result.
i1 = int(input())
i2 = int(input())
i3 = int(input())
i4 = int(input())
result = i1 + i2
result = result // i3
result *= i4
print (result) |
file = {'a':'china',
'b':'us',
'c':'cuba'}
for name, country in file.items():
print(str(name.title()) + ' runs through ' + str(country.title()) + '.')
print(str(name.title()))
print(str(country.title()) + '\n') |
'''
Author:
Charles
Function:
set options.
'''
# for yolo1
yolo1_options = {
'info': 'yolo1_options',
'max_object': 50,
'backupdir': './backup',
'trainSet': '',
'testSet': '',
'trainlabpth': None,
'testlabpth': None,
'clsnamesfile': './names/coco.names',
'gpus': '0, 1',
'ngpus': 2,
'use_cuda': True,
'num_workers': 4,
'is_multiscale': False,
'by_stride': False,
'header_len': 4,
'weightfile': './weights/yolov1.weights',
'cfgfile': './cfg/yolov1.cfg',
'logsavefile': 'train.log',
'save_interval': 10,
'conf_thresh': 0.25,
'nms_thresh': 0.4,
'iou_thresh': 0.5,
'jitter': 0.2,
'mode': 'test'
}
# for yolo2
yolo2_options = {
'info': 'yolo2_options',
'max_object': 50,
'backupdir': './backup',
'trainSet': '',
'testSet': '',
'trainlabpth': None,
'testlabpth': None,
'clsnamesfile': './names/coco.names',
'gpus': '0, 1',
'ngpus': 2,
'use_cuda': True,
'num_workers': 4,
'is_multiscale': True,
'by_stride': False,
'header_len': 4,
'weightfile': './weights/yolov2.weights',
'cfgfile': './cfg/yolov2.cfg',
'logsavefile': 'train.log',
'save_interval': 10,
'conf_thresh': 0.25,
'nms_thresh': 0.4,
'iou_thresh': 0.5,
'jitter': 0.3,
'mode': 'test'
}
# for yolo3
yolo3_options = {
'info': 'yolo3_options',
'max_object': 50,
'backupdir': './backup',
'trainSet': '',
'testSet': '',
'trainlabpth': None,
'testlabpth': None,
'clsnamesfile': './names/coco.names',
'gpus': '1',
'ngpus': 1,
'use_cuda': True,
'num_workers': 4,
'is_multiscale': True,
'by_stride': True,
'header_len': 5,
'weightfile': './weights/yolov3.weights',
'cfgfile': './cfg/yolov3.cfg',
'logsavefile': 'train.log',
'save_interval': 10,
'conf_thresh': 0.25,
'nms_thresh': 0.4,
'iou_thresh': 0.5,
'jitter': 0.3,
'mode': 'test'
} |
# Cube coordinates: https://www.redblobgames.com/grids/hexagons/
d = open("input.txt").read().splitlines()
g = {}
for l in d:
i = 0
x, y, z = (0, 0, 0)
while i < len(l):
if l[i:].startswith('sw'):
x, y, z = x - 1, y, z + 1
i += 2
elif l[i:].startswith('se'):
x, y, z = x, y - 1, z + 1
i += 2
elif l[i:].startswith('nw'):
x, y, z = x, y + 1, z - 1
i += 2
elif l[i:].startswith('ne'):
x, y, z = x + 1, y, z - 1
i += 2
elif l[i] == 'w':
x, y, z = x - 1, y + 1, z
i += 1
elif l[i] == 'e':
x, y, z = x + 1, y - 1, z
i += 1
g[(x, y, z)] = not g.get((x, y, z), False)
print(sum(g.values()))
dirs = ((-1, 0, 1), (0, -1, 1), (0, 1, -1), (1, 0, -1), (-1, 1, 0), (1, -1, 0))
for i in range(100):
g_new = g.copy()
pos = set(g.keys())
for k in g:
for dx, dy, dz in dirs:
pos.add((k[0] + dx, k[1] + dy, k[2] + dz))
for k in pos:
n = 0
for dx, dy, dz in dirs:
n += g.get((k[0] + dx, k[1] + dy, k[2] + dz), False)
if n == 2:
g_new[k] = True
elif (n == 0 or n > 2) and g.get(k, False):
g_new[k] = False
g = g_new
print(sum(g.values()))
|
def cards_for_friends(w, h, n):
w2 = 1
while w % 2 == 0:
w2 *= 2
w = w / 2
h2 = 1
while h % 2 == 0:
h2 *= 2
h = h / 2
return w2 * h2 >= n
if __name__ == "__main__":
num_test = int(input())
for i in range(num_test):
w, h, n = [int(i) for i in input().split()]
if cards_for_friends(w, h, n):
print("YES")
else:
print("NO")
|
# -*- coding: utf-8 -*-
"""
Queues Directory
"""
|
def solution(citations):
"""[summary]
인용횟수를 담은 배열이 주어지면 그걸 토대로 H-index를 산출
Args:
citations (List[int]): 논문별 인용 횟수 [1:1000], e:=[0:10000]
Returns:
int: 발표한 논문 n편 중 h번 이상 인용된 논문이 h편 이상이고, 나머지 논문이 h편 이하 인용되었을때, max(h)
"""
h_index = 0
for i, c in enumerate(sorted(citations, reverse=True)):
if c < i + 1:
break
h_index += 1
return h_index
if __name__ == "__main__":
i = [3, 0, 6, 1, 5]
print(solution(i)) |
class FpSegmentator:
def __init__(self, bs = 16, th = 160):
self.blockSize = bs
self.threshHold = th
def segment(self, fpImg):
segmentedImg = fpImg
maskImg = fpImg
#Perform edge detection using Canny technique
blurImg = cv2.GaussianBlur(fpImg, (7,7), 0)
edgeImg = cv2.Canny(blurImg, 20, 70)
rows, cols, *ch = maskImg.shape
total = 0
sd = 0
size = self.blockSize ** 2
#Compute statistical features of each block in input fingerprint image
#And check if SD is less than the threshold value
for row in range(0,rows, self.blockSize):
for col in range(0,cols, self.blockSize):
try:
#Calculate total pixels here
for r in range(row,row + self.blockSize):
for c in range(col,col + self.blockSize):
total += edgeImg[r,c]
#Calculate total sd of the edgeImg here
for r in range(row,row + self.blockSize):
for c in range(col,col + self.blockSize):
sd += (edgeImg[r,c] - (total // size))**2
total_sd = math.sqrt(sd // self.blockSize)
#Assign white color to the region with lower threshold
if total_sd < self.threshHold:
for r in range(row,row + self.blockSize):
for c in range(col,col + self.blockSize):
segmentedImg[r,c] = 255
#Reset the sd and total pix for each block
total = 0
sd = 0
except IndexError as ie:
pass
return segmentedImg |
class Handler(object):
"""
Handler for the compass connected to the ruggeduino
NOTE - VARIABLES
PID - Dictionary of PID values
P - P value
I - I value
D - D value
robot - Instance of sparklebot class
NOTE - METHODS
calcPID(error) - Calculate the new PID values from the given error
getValue() - Gets the heading from the compass
"""
def __init__(self, robot, PID):
self.P = PID['P']
self.I = PID['I']
self.D = PID['D']
self.R = robot
self.lastError = 0
self.i = 0
if self.R.DEBUG:
print("P: ", self.P)
print("I: ", self.I)
print("D: ", self.D)
def calcPID(self, error):
"Calculate the new PID values from error"
p = abs(error)
self.i += error
d = abs(self.lastError) - abs(error)
pidVal = self.P * p + self.I * self.i + self.D * d
return pidVal
def getValue(self):
"Gets the heading from the compass"
heading = self.R.RH.command("e")
value = int(float(heading))
return(value)
|
s = input()
s = s.lower()
panagram = True
lst = []
for i in range(0,26):
lst.append(False)
for char in s:
if not char == " ":
lst[ord(char)-ord('a')]=True
for ch in lst:
if ch == False:
panagram = False
break
if(panagram==False):
print("Panagram Doesn't Exist")
else:
print("Panagram Exists")
|
"""
Given an 2D board, count how many battleships are in it. The battleships are represented with 'X's, empty slots are represented with '.'s. You may assume the following rules:
You receive a valid board, made of only battleships or empty slots.
Battleships can only be placed horizontally or vertically. In other words, they can only be made of the shape 1xN (1 row, N columns) or Nx1 (N rows, 1 column), where N can be of any size.
At least one horizontal or vertical cell separates between two battleships - there are no adjacent battleships.
Example:
X..X
...X
...X
In the above board there are 2 battleships.
Invalid Example:
...X
XXXX
...X
This is an invalid board that you will not receive - as battleships will always have a cell separating between them.
Follow up:
Could you do it in one-pass, using only O(1) extra memory and without modifying the value of the board?
"""
class Solution(object):
def countBattleships(self, board):
"""
:type board: List[List[str]]
:rtype: int
"""
solution = 0
for i in range(len(board)):
for j in range(len(board[i])):
if i == 0 and j == 0:
if board[i][j] == 'X':
solution += 1
elif i == 0:
if board[i][j] == 'X' and board[i][j-1] != 'X':
solution += 1
elif j == 0:
if board[i][j] == 'X' and board[i-1][j] != 'X':
solution += 1
else:
if board[i][j] == 'X' and board[i-1][j] != 'X' and board[i][j-1] != 'X':
solution += 1
return solution
|
def var_sum(*args):
"""
Variable argument sum
"""
total = 0
for arg in args:
try:
arg+1
total += arg
except TypeError: # invlid input hence return early
return
return total
def sum_of_n_natual_numbers(n):
"""
Returns sum of first n natural numbers
"""
try:
n+1
except TypeError: # invlid input hence return early
return
if n < 1: # invlid input hence return early
return
return n*(n+1) // 2
def sum_of_n_even_numbers(n):
"""
Returns sum of first n even numbers
"""
try:
n+1
except TypeError: # invlid input hence return early
return
if n < 0: # invlid input hence return early
return
return n*(n+1)
def sum_of_n_odd_numbers(n):
"""
Returns sum of first n odd numbers
"""
try:
n+1
except TypeError: # invlid input hence return early
return
if n < 0: # invlid input hence return early
return
return n*n
def sum_of_square_of_n_numbers(n):
"""
The sum of squares of first n natural numbers
∑ n^2 = 1^2 + 2^2 + 3^2 +....+ n^2
"""
try:
n+1
except TypeError: # invlid input hence return early
return
if n < 0: # invlid input hence return early
return
return n*(n+1)*(2*n+1)//6
|
class Solution(object):
def reverse(self, x):
rev_x = 0
if x >= 0: # positive
sign = + 1
elif x < 0: # negative
sign = -1
x = x * sign # remove sign for now
while x > 0:
rev_x = rev_x * 10 + x % 10
x = x/10
# check if output is within 32 bit bounds
if rev_x <= (-2**31) or rev_x >= (2**31):
rev_x = 0
print(rev_x*sign)
return rev_x*sign # restore the sign
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Date : 2017-07-05 16:53:19
# @Author : mayongze (1014057907@qq.com)
# @Link : https://github.com/mayongze
# @Version : 1.1.1.20170705
# 微信后台接口RUL 示例: http://www.*****.com/***.php
URL = ''
# sqlite 存储相对路径
SQLITE_PATH = 'database/demodatabase.db'
# sqlite 日志路径
SQLITE_LOG_PATH = 'sqliteDataProcess.log'
# 爬虫进程数
SPIDER_PROCESS_NUM = 3 |
x:str = ""
y:str = "123"
z:str = "abc"
for x in z:
print(x)
for x in y:
print(x)
|
def solution_one(numbers: list[int]) -> list[int]:
"""
timeComplexity: BigO(n^2)
spaceComplexity: BigO(n)
"""
result = []
for idx, i in enumerate(numbers):
tmp = 1
for idj, j in enumerate(numbers):
if idx == idj:
continue
tmp *= j
result.append(tmp)
return result
def solution_two(numbers: list[int]) -> list[int]:
"""
timeComplexity: BigO(2n)
spaceComplexity: BigO(n)
"""
total = 1
for n in numbers:
total *= n
result = []
for n in numbers:
result.append(total // n)
return result
if __name__ == "__main__":
print(solution_one([1, 2, 3, 4, 5]))
print(solution_two([1, 2, 3, 4, 5]))
|
"""Top-level package for ocr_package."""
__author__ = """Qunfei Wu"""
__email__ = 'qunfei.wu@outlook.com'
__version__ = '0.1.4'
|
# -*- coding: utf-8 -*-
# Copyright 2019 Cohesity Inc.
class BackupPolicyProtoScheduleEnd(object):
"""Implementation of the 'BackupPolicyProto_ScheduleEnd' model.
TODO: type model description here.
Attributes:
end_after_num_backups (long|int): The following field has been
deprecated. TODO(mark): Append "_DEPRECATED" to this field name
once iris has stopped referring to it. If specified, the backup
job will no longer be run after it has been run these many times.
end_time_usecs (long|int): If specified, the backup job will no longer
be run after this time.
"""
# Create a mapping from Model property names to API property names
_names = {
"end_after_num_backups":'endAfterNumBackups',
"end_time_usecs":'endTimeUsecs'
}
def __init__(self,
end_after_num_backups=None,
end_time_usecs=None):
"""Constructor for the BackupPolicyProtoScheduleEnd class"""
# Initialize members of the class
self.end_after_num_backups = end_after_num_backups
self.end_time_usecs = end_time_usecs
@classmethod
def from_dictionary(cls,
dictionary):
"""Creates an instance of this model from a dictionary
Args:
dictionary (dictionary): A dictionary representation of the object as
obtained from the deserialization of the server's response. The keys
MUST match property names in the API description.
Returns:
object: An instance of this structure class.
"""
if dictionary is None:
return None
# Extract variables from the dictionary
end_after_num_backups = dictionary.get('endAfterNumBackups')
end_time_usecs = dictionary.get('endTimeUsecs')
# Return an object of this model
return cls(end_after_num_backups,
end_time_usecs)
|
#!/usr/bin/env python
'''
test cases will be discovered by py.test by Python testing conventions
'''
class TestClass:
def test_f(self):
assert 42 == 42
def test_g(self):
assert " hello ".strip() == "hello"
|
test = {
'name': 'Problem 2',
'points': 2,
'suites': [
{
'cases': [
{
'code': r"""
>>> dogs = about(['dogs', 'hounds'])
>>> dogs('A paragraph about cats.')
False
>>> dogs('A paragraph about dogs.')
True
>>> dogs('Release the Hounds!')
True
>>> dogs('"DOGS" stands for Department Of Geophysical Science.')
True
>>> dogs('Do gs and ho unds don\'t count')
False
""",
'hidden': False,
'locked': False
}
],
'scored': True,
'setup': r"""
>>> from cats import about
""",
'teardown': '',
'type': 'doctest'
},
{
'cases': [
{
'code': r"""
>>> ab = about(['neurine', 'statutably', 'quantivalent', 'intrarachidian', 'itinerantly', 'cloaklet'])
>>> ab('unhollow simsim dcloakletB itinerantly cloakLet dQUaNtivalentJ gnEurinE fissiparity Mneurinel')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['unsimilar', 'conditioning', 'crystallogenical', 'mennom', 'foreannouncement', 'neomorph'])
>>> ab('#crystallogenIcalW podded reorganizationist neomorPhf hneomorphj')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['lactonic', 'ungroaning', 'intraepiphyseal', 'sporangiform', 'saccharate', 'hermeneutic', 'butanal', 'gregariously', 'splenopexy'])
>>> ab('Hsp\\leno?pexy qsacchar<ate, dungroaninGy pennate Ybutanal zbutana|l proterogyny')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['gendarme', 'tigerlike', 'countergabble', 'lollipop', 'regovern', 'acoelomate', 'walnut', 'combat', 'reattribution'])
>>> ab('tig;eRlikE fiscal nwaLnut cou(ntergab!bleg unsuccessiveness reattr<ibuTion acoeloma$te!U EgEndarme scrappily')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['multivoltine', 'nonpacifist', 'oviferous', 'postelection', 'multidigitate', 'reallege', 'intercavernous', 'marmose'])
>>> ab('sreAllege Omultivoltine postelEct>IonK Tpostelectiong ZposteLection')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['antimonarchial', 'archaeology', 'oopod', 'notchel'])
>>> ab('Hn`otcHelG packed saNtimonarchial a[ntimOna]rchiaLj dnotche}Lv')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['cf', 'tylostylus', 'civil', 'teleobjective'])
>>> ab('bty)loStyl.uss vexillar hciv~ilf oviparousness tylostylus gciviL ^CfH bridger plastochrone')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['croup', 'accompaniment', 'delabialize', 'erythematous', 'gossipdom'])
>>> ab('accomp=ani<mentY pleuronectoid petrographical gossi\\[pdomJ toetoe')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['basidiolichen', 'pruriently', 'elasticness', 'polony'])
>>> ab('exterior mannerable elastiCnessD bprurienTlyl eLasticneSs')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['umbellar', 'rambutan', 'southeasternmost', 'correction', 'inadhesion', 'featherfew'])
>>> ab('UmbellarB sparky coRrectionh tsoutheasternmoStW interradiation lumbEll]art')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['intercreate', 'sulpholipin', 'inkhornizer', 'lycanthropic', 'optimize'])
>>> ab('sulpholi*piN proctoparalysis rInkhornizer RlycanthropicY optimi`#zeg -optimizeo lycanthropicB lycanthrOpICK')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['uniformitarian'])
>>> ab('U-nif#ormitarianr uniformitarian buNi=formitaRian leucitis enantiopathia uniformitarian U-nif!ormitarian')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['pulicidal', 'choultry', 'caryopilite', 'unowed', 'overslaugh', 'unshriveled', 'ectodactylism'])
>>> ab('ectodactylisma ecT${odactylismL transform diaheliotropic carYopi?l~iteT aunowE-d,e ectodactyli]smI Rcaryop,iliT@eG .puli^Cidalk')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['stowbordman', 'scleromeninx', 'wringstaff'])
>>> ab('stowbordmaN porkfish scleromenInx updart nether')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['plumbosolvent', 'nearby', 'atriopore', 'conchiferous', 'zygostyle', 'glottidean', 'temulentive', 'khajur', 'chirognomy'])
>>> ab('glott;ID|eanD (aTrioPor[ed tem^ulenT/iveg Rplumbosolventt zygo[styleV pseudoacaccia pLumboSolve-ntm tEmulenTivEg sweetbrier')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['sylvanly', 'infinite', 'uncorked', 'subjacency', 'looplike', 'nasoethmoidal', 'capcase', 'communicableness', 'blown'])
>>> ab("infi!niTe eu.nCorkEd+ nasoethmoi-daL glooPlikes Bcommu[nicabl'eNesst")
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['sulpholysis', 'kalo', 'cecidiology', 'progne', 'cosiness', 'quotity'])
>>> ab('kaloI marsoon TcecidIology s`u,Lpholysism uprognez =sulphoLysisL ncec{idiologY')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['cameograph', 'cnidophore'])
>>> ab('unhushable monoprionidian UcameographL coccidia cnidophorev')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['inadequateness', 'capsulate', 'careers', 'sublanceolate'])
>>> ab('finadeQuate#ness]V clownship Sublan!ceol_atem capsulitis sublanceolatet chantry')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['kilneye', 'wistful', 'scorbutic', 'chichipe', 'antemeridian', 'metapolitical'])
>>> ab('Nmetapolitica}lm UmetapoliTica:l unapproximately ch+i@chipeD aNtemeRi^dianq')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['inefficacity', 'caulicule', 'autositic', 'zimme'])
>>> ab('ottajanite inEffIcacityv plasmodiocarp cc-Aul(iculex inefficaciTyX')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['playwrighting', 'hamated', 'encumberingly', 'closh', 'yugada', 'staphyloptosis', 'energeia', 'microclimatologic', 'pasang'])
>>> ab('=PlAYwrightInGX VpasA&ngw yugada energeia zpla,ywRIgh|ting CpAsangq')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['saltless', 'bailage', 'nonformation', 'yeven', 'argenteous', 'ha'])
>>> ab('iy:e.venN A[rgentEo]usT largenteous clamminess gbaILa.geY stoicism')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['overcrop', 'julian', 'gaub', 'roland'])
>>> ab('tenectomy UrOland haec Kover`c(ropb pneumatolitic roland overc]ropz GOvercrop Xroland')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['construction', 'upbid', 'weave'])
>>> ab('weave, amphidetic weave untotalled weAveN hweave weaveF pasticheur')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['immortalness', 'powell', 'indifferently', 'palatograph', 'capucine'])
>>> ab('enterer Qpalatograph implacement shepherdry indiff"er<ently')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['rorqual', 'tautomeric', 'unprejudicedly', 'disregardance', 'reconveyance', 'rebellow'])
>>> ab("quabird grebellOw] rebEl'l*owm rebell/]OWh learnt")
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['nightstock', 'catabaptist', 'aloud', 'ultramelancholy'])
>>> ab('ualouD/c mines push dnightsTock ial&oud')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['understrain', 'incoherentific'])
>>> ab('kun+derstraink munderstRain vaporiferousness silly palaeocrystalline cauliculus subnatural')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['accompliceship', 'dumpish', 'unqueried', 'incedingly', 'sudiform', 'neighborless'])
>>> ab('incedingly sequency sudiform dumpish YUnqueried Sdumpish Gneig}hbOrlessq KincedinglyX')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['undishonored', 'counterflange', 'justly', 'contralto', 'erythematous', 'intromissive'])
>>> ab('counterflange cOntra=\\lto IntromIssiven unperforate j,ustl#yi iNtromissIveS undishonored')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['replier', 'bending', 'uptree'])
>>> ab('replier uptr$eeC bantay salpingostaphyline aupTre[Er')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['matriculate', 'pandemy', 'fruited', 'draughtmanship', 'arboriform', 'oppugner', 'nucleonics', 'reducer'])
>>> ab('f@rui,ted reducer draughtmanshipD toxa PfrUited ZMatRi[culateA maTricuLatEi lmaTricuLate].D matriculate')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['unconjecturable', 'lithontriptor', 'paradoctor', 'retinopapilitis', 'unabsolvedness'])
>>> ab('u/nconjectura{bleJ unco(njEctUrable unconjecturable pAradoct<ord trenchermaking Aretinopapilitis')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['liminary', 'collectorship'])
>>> ab('pearlin unbrent vliminary>O Xlim;iNaryf collectorship liminary pretranscription fliminaryQ liminary')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['stuporose', 'didst', 'hexactinellidan', 'vacuome', 'pulicarious', 'semidead', 'gourdlike', 'powerboat'])
>>> ab('tvacuome hippometry sgourdlIKe satisfying hexactiNellidanT')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['surdation', 'piddler', 'unbatten', 'bemar', 'unfeeling', 'thermalgesia'])
>>> ab('unbatten tracksick pIddleRs munbatten ^BemaR piDdler*] news')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['undersweep', 'sportswomanly', 'nonlocal', 'lorate', 'histopathologist', 'trichiuroid'])
>>> ab('zoomorphize trichiuroid SportSwomanlyj Nonlocal nonlOcalA p{lorate/ NundersweepR thisto/pathologisT Klorate<')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['rewarehouse', 'noggen'])
>>> ab('CreWarEhous\\e rewarehouse pina desquamatory Mnoggeny threadweed')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['noologist'])
>>> ab('bagreef desiredly xnooL+ogist<E warmth unstainableness theomorphic eliasite')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['mockernut', 'boga', 'unzephyrlike', 'infragenual', 'dimmed', 'derelictness', 'morphologic'])
>>> ab('gopher lord dimmeDw Xmo$cke`rnuTC bogAY')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['parapteron'])
>>> ab('quinaldyl spiritland simply laver untakable nonsensitive xparapter>onA')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['priesteen', 'parapet', 'linenman', 'noneffervescent', 'metasaccharinic', 'unreversible', 'desiderata'])
>>> ab('desid@erataP Bnonefferve?s]centr des\\iDEra]tag linenmanx parapet k&unreversible desiderata~L (uNreversi~BleN')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['pulpit', 'cig', 'orbitelarian', 'overstress', 'voicelessness'])
>>> ab('xoV_Erst-ressR voi=c:elessness V)oicelessneSs psaltes NoRbitelarian')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['underdevelop', 'rejumble', 'crowkeeper', 'symphyllous', 'narratress'])
>>> ab('troolie underdevelOpw sym+phyl`lOusF undecidedly rrEjumbleR nnarRatressF')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['phonogrammically', 'dumpiness', 'preambition', 'halisteretic'])
>>> ab('jha}liStEretic" ha%listereti<c interimistic inexhaustive yogin yphonogrammicallyw smokefarthings dauntingly halisteretic')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['block', 'diluvialist', 'heriot', 'supersalient', 'hate', 'septation'])
>>> ab('=sep.tatiOnA handmaid hate Hhe}rio(tt zheRiot^$')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['cyclose', 'acrospore', 'raver', 'balzarine', 'neomorphic', 'lute', 'uranostaphylorrhaphy', 'thirteenfold'])
>>> ab('balzarine acrospore hluteY ,baLzarine UneOmorphIc')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['pedestal'])
>>> ab('valeta counselful pedestal nonstudious matral divata pedes}taL')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['gynospore', 'apodictically', 'villages', 'algebra', 'uprid', 'disadvise', 'yourselves', 'nondeference', 'overhardy'])
>>> ab('tetchy Xnondeferencex uovErhardYh dIsadvis}ef bridely orientator')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['lipomyxoma'])
>>> ab('shoreyer lipomyxoma cojuror squdge luxuriancy')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['unchangefulness', 'sublevation', 'protosyntonose', 'saddlelike', 'postlachrymal', 'antetype'])
>>> ab('OanTety>peW unchangefulness ootocous wuncHangefulnessx bagpipes saddlelike')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['coccygeal', 'dinothere', 'faradmeter', 'oversubtlety', 'dispensatorily', 'manganapatite'])
>>> ab('d~is&penSaTorilyc browbeater dIspensatorilyZ Omanganapatiteg amanganapatite mangaNapatItEG Hdispensatorily roulette')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['diactin', 'stirps', 'waverous', 'qualifying', 'sexuparous', 'realmless'])
>>> ab('Hstirpsj sexuparOusj waver>ousQ sexuparOus_R cqualIfying st_irPs# sexupaRous')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['headliner', 'dutiability', 'acquired', 'portfire', 'dilatometric', 'voicelet'])
>>> ab('Dvo)^icelEtB acquired inhaler sdilatome&trIc pour claut portfire@m Zhe-adlinerm')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['healsome', 'proceed', 'oxhorn', 'overskim', 'polemicist', 'injure', 'hygrophaneity', 'chairmender'])
>>> ab('sproceedf y|healso"me vpolemicisTW embrocate hygrophaneity Xproceed ThygroPhaneIty')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['schemist', 'pentahedrous', 'relativeness', 'solivagant', 'gloriously', 'epistolet'])
>>> ab('relativenesse pentahedrous Ygloriou#slyq foretalking Agloriously trelativen&esSA dschemist')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['carbonization', 'micropegmatitic', 'waterhorse', 'antisubstance', 'yucker', 'samely', 'dargsman'])
>>> ab('whank samely waterhorse usa;me,lYj antisubstance ddargsman micropegmatitic chack')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['unguidable', 'presentational', 'autoheterosis', 'nitrophytic'])
>>> ab('utrum cerebralist unguidable tpre,sEnta(tionaL AunguidabLE composure p#resen.tationaL autoheterosis')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['predative', 'paragrammatist'])
>>> ab('pRed@ati)veK abhiseka rpredAt(Ive h$paragrammatist/ GparagrammatistD prEdative')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['ripe', 'spatuliform'])
>>> ab('monopyrenous zspatuliform E:ripe lr#ip.ey cauligenous tod toddle')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['appliable', 'dysepulotic', 'opodeldoc', 'brainlessly'])
>>> ab('ortho hopodeldoc fappliableV postcolumellar rebounder')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['ameed', 'pneumonopleuritis', 'maidenweed'])
>>> ab("pnE-umO*NOpleuritis pNeumOnopLeuritis' pneumonopleuritis Eameed tabletary epneumOnopleuritis maidenweed")
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['broomwood', 'relatability', 'pearlite', 'epithecium', 'saddlenose'])
>>> ab('ape@arlite WrelatabilityR Zsaddl|enos$E piperidine commissariat aphasia')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['housewarming', 'hymenean', 'crepusculine', 'solecizer', 'overfearful'])
>>> ab('engloom electrotest crosscutting housewarmings SsoLecizErN solecizer vcrepus"culIn|eY tenementer LhouSewarmingQ')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['paradisic', 'unaffectionately', 'exordial', 'weaponshowing', 'rhombohedra', 'sparger'])
>>> ab('Orhombohedra lexordials subjunctively jrhombo@Hedra= paradis#icO')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['official', 'platybrachycephalous', 'pitometer', 'electrodepositor', 'superambitious'])
>>> ab('thundersquall pockmark Bpitome}t^er mplatybrachycephalousQ oFficial T;official piTometerH oddsman')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['hoseless', 'passivity', 'sparrowcide', 'salubrious'])
>>> ab('hoseless_ tonalist comboy coislander opa_ssivITys pAss[ivIty> psaLubrIousV hoseleSs')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['mischieve', 'dayfly', 'galvanomagnetic'])
>>> ab('dayfly\\_V dayflyU mischieVey ydayfly precipitantly dmischievey')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['notoriety', 'undersorcerer', 'pneumoperitonitis', 'balaenoidean', 'strawbreadth', 'postconnubial', 'cauligenous'])
>>> ab('siket unwhelped misexpend academically gemmipara cAuligEnous')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['wold', 'relieved', 'quicksandy', 'guaraguao', 'stalkless', 'unexhilarated', 'strifeproof'])
>>> ab('wo\\LdT funexhilarAt:ed& ejection comeuppance Erelieve"d woldg')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['unpermeated', 'myelocytic', 'nonindictable', 'pretuberculous', 'mesoxalyl', 'strombite', 'muscule', 'cheesemongerly'])
>>> ab('prETUb^eRcu,LoUsK mesoxalylN oxybutyric udal FmUS^*Culeh umye)locyticG')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['embrail', 'ferryboat', 'picky', 'wheerikins', 'uncrushed', 'monotelephone', 'foist', 'transempirical', 'gawkily'])
>>> ab('thujene eightpenny afois>tS wh\\eerik<insr Uncru-shed nonlaying ke.mBrail>n Wferryboat ferrybOat')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['imitationist', 'undershut', 'unmannerly', 'sterneber', 'nonappendicular', 'cityish', 'caimito'])
>>> ab('cityishu ycityisHm Zcaimito asterneBer On{{onappendiCularK')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['hookers', 'gardenmaker', 'postnatal', 'private', 'demagogy'])
>>> ab('gardenMakery teleological WhookersG u:demagogyB JHo=okersV')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['baillone', 'uncoacted', 'tarnisher', 'unwrinkled', 'pistareen', 'phacometer', 'aphyllous', 'thoraciform', 'megaron'])
>>> ab('megaronI +phacometeR havenership aphy-llOu/sw Rpistareene Run,cOactedT Gun$wrinkleDo :"pistareenK rpistareen/')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['unsloped', 'fucous'])
>>> ab('OunslopEd indissociable clitoridectomy undefectible predisponency multiplex')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['fracted', 'traducianistic', 'tinwork', 'vortically', 'massicot', 'pinite', 'barbarian', 'shank'])
>>> ab('ensigncy vortically =tiNwork yvortically fracted tinwork dustuck')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['angelhood', 'xiphydriid', 'longicorn', 'shadchan', 'mixableness', 'journals'])
>>> ab('Kmi>xablen"ess xiphydriid saltine longicorN longicornY')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['cervicectomy', 'vibraculoid', 'feminility', 'voluminously', 'hydroferrocyanate', 'canthotomy', 'unequableness', 'monomerous'])
>>> ab('dedendum voluminously feminilityJ monomerousr BmoNO%merOU>sM cornerwise')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['kymbalon', 'plastogamy', 'grumpily', 'tease', 'macrocytosis', 'planterdom', 'pantophile'])
>>> ab('jkym!b?alon pAntophile pla*stogamyy pAntophileJ phasmatid oligodendroglia')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['overprovidently', 'obdormition', 'precollect', 'productivity'])
>>> ab('aesthophysiology obdormition trabant obdo!Rmitionm }obdorMitionD cOverproviDeNtlyG doVe|rProVi+DenTlyK')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['baker', 'circumscribable', 'apostrophic', 'nap'])
>>> ab('apostrOphic troopfowl a{postrophic circumscribable foreroyal Z}(bakeR cIrcUmscrib@AbLe D%nApQ')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['tractioneering', 'contestant', 'berrier'])
>>> ab("Ktractioneering croucher z'tractioneering nonverminous capper")
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['afterturn', 'semispeculation'])
>>> ab('semispeculation semispeculationv coarbiter mydatoxine zincograph')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['subjectiveness'])
>>> ab('podagra waikness haulage semiprivacy insubordinate LsubjectiveNeSsH IsubjeCtiven-ess')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['ophiophagous', 'rice', 'piousness', 'vibrissae', 'diplocardiac'])
>>> ab('cap ophiophagous TdiplocarDIacW vibrissae droud hencote ]vibriss=ae')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['civicism', 'belletrist', 'vegetocarbonaceous', 'woodchuck', 'phacitis', 'warehouseful', 'intertwine'])
>>> ab('division rphaciTI]s)P vEgetocarbonaceous intertwineb warehouseful RVegetoCarbonaceouSd')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['longboat', 'cataria', 'pectination', 'immute', 'dicrotic', 'tressured', 'sluggard', 'hypothenal', 'acrologism'])
>>> ab('unstintingly t(ressuredt Nslug)gard@P QslUGgard immuteS')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['discover', 'fixative', 'suprasphanoidal', 'thickbrained'])
>>> ab('disc[overC suprasphanoidal engraft Psup:raSph@anoidaLU unintromitted ksup^rasphanOi]daLN unsaponifiable dIScoverw SupraspHano^ida\\l')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['unharnessed', 'fruitist', 'resolicit'])
>>> ab('U_Fruitis(t Z!unharnessed script VresolicitV mail')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['tom', 'spurgall', 'rampagious'])
>>> ab('tOM spurgallU centrosphere arouse tomX')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['bronze', 'turgidness', 'untailorly', 'untewed'])
>>> ab('TturgidneSsl rectilineal yuNtaIlorlYL bronzeA turgidness Iu(nTAilOrlY untailorly')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['gong', 'spondylium', 'agrammatism', 'yad', 'unintrusted', 'nosy'])
>>> ab('turrigerous dynamitism aminoacetophenone sPondyLiumt GnosyA lspondyliumV')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['tegularly', 'kilnrib', 'sulphonalism'])
>>> ab('tkilnrib/M wSulphO:nA"liSmR sUlph,onalismD tetrazolium ksUlphonalism tegularlyy')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['succeed', 'dumminess', 'tedder', 'bobsleigh', 'tenendum', 'slatternness', 'longsomeness'])
>>> ab('cs?ucceed longsomenessl lapwork Ab*obSleigh dumMiNes<su')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['biventer', 'fugle', 'estimated', 'racinglike', 'clavelization'])
>>> ab("UclavelizationT f@'ugle rfug*le progressionist estimated bi`veNtErj cLa\\vel`izationp esti(matEdG")
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['imbonity', 'axolemma', 'comendite', 'communicableness'])
>>> ab('foredevote parosteal comendi<}tex consent misken costiform scraggled Zimbo=]nity')
False
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['carpeting', 'equitriangular', 'unforgeability', 'antiharmonist', 'diasynthesis'])
>>> ab('cephaloplegic equitriangular antiharmonist unforgeability d`equitr)iangularB')
True
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ab = about(['autoimmunization', 'stepfatherhood'])
>>> ab('retinopapilitis encoop autoimmUnizatiOnn Fau]toImmunizAtionL unchance')
False
""",
'hidden': False,
'locked': False
}
],
'scored': True,
'setup': r"""
>>> from cats import about
""",
'teardown': '',
'type': 'doctest'
}
]
}
|
try:
answer = 10/0
number = int(input("Enter a number: "))
print(number)
except ZeroDivisionError as err:
print(err)
except ValueError:
print("Invalid Input")
# if only one except without any specification, it is too broad
|
class XForwardedForMiddleware(object):
"""
Middleware that sets REMOTE_ADDR to a proxy fwd IP address
"""
def __init__(self, get_response):
self.get_response = get_response
def __call__(self, request):
if 'HTTP_X_FORWARDED_FOR' in request.META:
x_fwd = request.META['HTTP_X_FORWARDED_FOR']
request.META['REMOTE_ADDR'] = x_fwd.split(",")[0].strip()
response = self.get_response(request)
return response
|
# =====================================Assign Trait Rarity==================================
# Each image is made up of a series of traits
# The weightings for each trait drive the rarity and add up to 100%
face = ["White", "Black"]
face_weights = [60, 40]
ears = ["No Earring", "Left Earring", "Right Earring", "Two Earrings"]
ears_weights = [25, 30, 44, 1]
eyes = ["Regular", "Small", "Rayban", "Hipster", "Focused"]
eyes_weights = [70, 10, 5 , 1 , 14]
hair = ['Up Hair', 'Down Hair', 'Mohawk', 'Red Mohawk', 'Orange Hair', 'Bubble Hair', 'Emo Hair',
'Thin Hair',
'Bald',
'Blonde Hair',
'Caret Hair',
'Pony Tails']
hair_weights = [10 , 10 , 10 , 10 ,10, 10, 10 ,10 ,10, 7 , 1 , 2]
mouth = ['Black Lipstick', 'Red Lipstick', 'Big Smile', 'Smile', 'Teeth Smile', 'Purple Lipstick']
mouth_weights = [10, 10,50, 10,15, 5]
nose = ['Nose', 'Nose Ring']
nose_weights = [90, 10] |
# Python - 2.7.6
def new_avg(arr, newavg):
n = __import__('math').ceil((len(arr) + 1) * newavg - sum(arr))
if n <= 0:
raise ValueError()
return n
|
class Enumerable:
@classmethod
def keys(cls):
return [x for x in cls.__dict__.keys() if not x.startswith('_')]
|
## Implementation of firstDuplicate in Python3
## Example Input : a = [2, 1, 3, 5, 3, 2]
## Example Output: 3
def firstDuplicate(a):
new_list=set()
for i in a:
if i not in new_list:
new_list.add(i)
else:
return i
return -1
if __name__=="__main__":
a = [2, 1, 3, 5, 3, 2]
print(firstDuplicate(a)) |
class SimulationUiSerializer():
def serialize(self, simulation):
# Get car metadata used for rendering
objects_metadata = {}
for car in simulation.cars.values():
objects_metadata[car.name] = {
"dim_x": car.dim[0],
"dim_y": car.dim[1],
"shape": "rectangle",
}
# serialize the setpoint
objects_metadata["setpoint"] = {
"pos_x": simulation.setpoint[0],
"pos_y": simulation.setpoint[1],
"shape": "circle",
"radius": 0.05,
"motion": "fixed" # Used to indicate that this is not meant to be something redrawn
}
# serialize time series data
timeseries = []
for state in simulation.data:
state_serialization = {}
for car in state.cars.values():
state_serialization[car.name] = self.serialize_car(car)
timeseries.append(state_serialization)
return {
"objects": objects_metadata,
"timeseries": timeseries
}
def serialize_car(self, car):
return {
"pos_x": car.x,
"pos_y": car.y
} |
# -*- coding: utf8 -*-
__version_info__ = (0, 7, 4)
__version__ = '%d.%d.%d' % __version_info__
|
'''
Byte 0 * * * * * * * 1 * * * * * * * 2 * * * * * * * 3 * * * * * * * -
| | | | |
bit 0 | 1 | 2 | 3 |
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 |
+-+-+-+-+-------+-+-------------+-------------------------------+
|F|R|R|R| opcode|M| Payload len | Extended payload length |
|I|S|S|S| (4) |A| (7) | (16/64) |
|N|V|V|V| |S| | (if payload len==126/127) |
| |1|2|3| |K| | |
+-+-+-+-+-------+-+-------------+ - - - - - - - - - - - - - - - +
| Extended payload length continued, if payload len == 127 |
+ - - - - - - - - - - - - - - - +-------------------------------+
| |Masking-key, if MASK set to 1 |
+-------------------------------+-------------------------------+
| Masking-key (continued) | Payload Data |
+-------------------------------- - - - - - - - - - - - - - - - +
: Payload Data continued ... :
+ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +
| Payload Data continued ... |
+---------------------------------------------------------------+
A single-frame unmasked text message
0x81 0x05 0x48 0x65 0x6c 0x6c 0x6f
[
(1, 0, 0, 0, 0, 0, 0, 1), # FIN = 1, RSV1 = 0, RSV2 = 0, RSV3 = 0, opcode = 1(text frame)
(0, 0, 0, 0, 0, 1, 0, 1), # MASK = 0, Payload_Len = 5(Server to Client, Payload len = 5bytes)
(0, 1, 0, 0, 1, 0, 0, 0), # ASCII, H
(0, 1, 1, 0, 0, 1, 0, 1), # ASCII, e
(0, 1, 1, 0, 1, 1, 0, 0), # ASCII, l
(0, 1, 1, 0, 1, 1, 0, 0), # ASCII, l
(0, 1, 1, 0, 1, 1, 1, 1) # ASCII, o
]
A single-frame masked text message
0x81 0x85 0x37 0xfa 0x21 0x3d 0x7f 0x9f 0x4d 0x51 0x58
[
(1, 0, 0, 0, 0, 0, 0, 1), # FIN = 1, RSV1 = 0, RSV2 = 0, RSV3 = 0, opcode = 1(text frame)
(1, 0, 0, 0, 0, 1, 0, 1), # MASK = 1, Payload_Len = 5
(0, 0, 1, 1, 0, 1, 1, 1), # = 0x37
(1, 1, 1, 1, 1, 0, 1, 0), # = 0xfa
(0, 0, 1, 0, 0, 0, 0, 1), # = 0x21
(0, 0, 1, 1, 1, 1, 0, 1), # = 0x3d MASK_KEY = 0x37fa213d
(0, 1, 1, 1, 1, 1, 1, 1), # = 0x7f 0x7f ^ 0x37 = 72, ASCII H
(1, 0, 0, 1, 1, 1, 1, 1), # = 0x9f 0x9f ^ 0xfa = 101, ASCII e
(0, 1, 0, 0, 1, 1, 0, 1), # = 0x4d 0x4d ^ 0x21 = 108, ASCII l
(0, 1, 0, 1, 0, 0, 0, 1), # = 0x51 0x51 ^ 0x3d = 108, ASCII l
(0, 1, 0, 1, 1, 0, 0, 0) # = 0x85 0x58 ^ 0x37 = 111, ASCII o
]
A fragmented unmasked text message
fragmented_1: 0x01 0x03 0x48 0x65 0x6c
[
(0, 0, 0, 0, 0, 0, 0, 1), # FIN = 0, RSV1 = 0, RSV2 = 0, RSV3 = 0, opcode = 1(text frame)
(0, 0, 0, 0, 0, 0, 1, 1), # MASK = 0, Payload_Len = 3
(0, 1, 0, 0, 1, 0, 0, 0), # ASCII H
(0, 1, 1, 0, 0, 1, 0, 1), # ASCII e
(0, 1, 1, 0, 1, 1, 0, 0) # ASCII l
]
fragmented_2: 0x80 0x02 0x6c 0x6f
[
(1, 0, 0, 0, 0, 0, 0, 0), # FIN = 1, RSV1 = 0, RSV2 = 0, RSV3 = 0, opcode = 1(continuation frame)
(0, 0, 0, 0, 0, 0, 1, 0), # MASK = 0, Payload = 2
(0, 1, 1, 0, 1, 1, 0, 0), # ASCII l
(0, 1, 1, 0, 1, 1, 1, 1) # ASCII o
]
Unmasked Ping request and masked Ping response
0x89 0x05 0x48 0x65 0x6c 0x6c 0x6f
[
(1, 0, 0, 0, 1, 0, 0, 1), # FIN = 1, RSV1 = 0, RSV2 = 0, RSV3 = 0, opcode = 0x9(ping frame)
(0, 0, 0, 0, 0, 1, 0, 1), # MASK = 0, Payload_Len = 5
(0, 1, 0, 0, 1, 0, 0, 0), # ASCII, H
(0, 1, 1, 0, 0, 1, 0, 1), # ASCII, e
(0, 1, 1, 0, 1, 1, 0, 0), # ASCII, l
(0, 1, 1, 0, 1, 1, 0, 0), # ASCII, l
(0, 1, 1, 0, 1, 1, 1, 1) # ASCII, o
]
256 bytes binary message in a single unmasked frame
0x82 0x7E 0x0100 [256 bytes of binary data]
[
(1, 0, 0, 0, 0, 0, 1, 0), # FIN = 1, RSV1 = 0, RSV2 = 0, RSV3 = 0, opcode = 0x2(binary frame)
(0, 1, 1, 1, 1, 1, 1, 0), # MASK = 0, Payload = 126
(0, 0, 0, 0, 0, 0, 0, 1),
(0, 0, 0, 0, 0, 0, 0, 0) # (if payload len == 126)Extended payload length(16-bit) = 256
... # 256 bytes of binary data
]
64KiB binary message in a single unmasked frame
0x82 0x7F 0x0000000000010000 [65536 bytes of binary data]
[
(1, 0, 0, 0, 0, 0, 1, 0), # FIN = 1, RSV1 = 0, RSV2 = 0, RSV3 = 0, opcode = 0x2(binary frame)
(0, 1, 1, 1, 1, 1, 1, 1), # MASK = 0, Payload_Len = 127
(0, 0, 0, 0, 0, 0, 0, 0),
(0, 0, 0, 0, 0, 0, 0, 0),
(0, 0, 0, 0, 0, 0, 0, 0),
(0, 0, 0, 0, 0, 0, 0, 0),
(0, 0, 0, 0, 0, 0, 0, 0),
(0, 0, 0, 0, 0, 0, 0, 1),
(0, 0, 0, 0, 0, 0, 0, 0),
(0, 0, 0, 0, 0, 0, 0, 0) # (if payload len == 127)Extended payload length(64-bit) = 65536
... # 65536 bytes of binary data
]
'''
|
"""
index: 014
problem: 백만 이하로 시작하는 우박수 중 가장 긴 과정을 거치는 것은?
"""
def main(N=1000000):
visited = dict()
max_cnt = 0
max_n = 0
for n in range(N, 0, -1):
temp = n
cnt = 0
while n != 1:
n = n // 2 if n % 2 == 0 else 3 * n + 1
if n not in visited:
visited[n] = cnt
cnt += 1
continue
if cnt > visited[n]:
visited[n] = cnt
cnt += 1
else:
break
if n == 1 and cnt > max_cnt:
max_cnt = cnt
max_n = temp
return max_n
print("\n", main())
|
# Tabuada com laços.
num = float(input('Digite um número: '))
for tabuada in range(1, 11):
print('{:.2f} x {:.2f} = {:.2f}' .format(num, tabuada, num * tabuada)) |
class PostgresRouter:
# List what contain apps what can use default database.
route_app_labels = {'auth', 'contenttypes', 'sessions', 'admin', 'user', 'vacancies', 'social_django'}
def db_for_read(self, model, **hints):
"""
Attempts to read models in route_app_labels apps go to default db.
"""
if model._meta.app_label in self.route_app_labels:
return 'default'
return None
def db_for_write(self, model, **hints):
"""
Attempts to write models in route_app_labels apps go to default db.
"""
if model._meta.app_label in self.route_app_labels:
return 'default'
return None
def allow_relation(self, obj1, obj2, **hints):
"""
Allow relations if a model in route_app_labels apps is
involved.
"""
if (
obj1._meta.app_label in self.route_app_labels or
obj2._meta.app_label in self.route_app_labels
):
return True
return None
def allow_migrate(self, db, app_label, model_name=None, **hints):
"""
Make sure the apps in route_app_labels only appear in the
default db.
"""
if app_label in self.route_app_labels:
return db == 'default'
return None
class MongoRouter:
# List what contain apps what can use mongo database.
route_app_labels = {
'task',
'competition',
'news'
}
def db_for_read(self, model, **hints):
"""
Attempts to read models in route_app_labels apps go to mongo db.
"""
if model._meta.app_label in self.route_app_labels:
return 'mongo'
return None
def db_for_write(self, model, **hints):
"""
Attempts to write models in route_app_labels apps go to mongo db.
"""
if model._meta.app_label in self.route_app_labels:
return 'mongo'
return None
def allow_relation(self, obj1, obj2, **hints):
"""
Allow relations if a model in route_app_labels apps is
involved.
"""
if (
obj1._meta.app_label in self.route_app_labels or
obj2._meta.app_label in self.route_app_labels
):
return True
return None
def allow_migrate(self, db, app_label, model_name=None, **hints):
"""
Make sure the apps in route_app_labels only appear in the
mongo db.
"""
if app_label in self.route_app_labels:
return db == 'mongo'
return None
|
# -*- coding: utf-8 -*-
"""Mixins to be implemented by user."""
class AuxiliaryMixin(object):
"""User defined mixin class for Auxiliary."""
def __init__(self, base_Class=None, **kwargs):
super(AuxiliaryMixin, self).__init__()
class CallMixin(object):
"""User defined mixin class for Call."""
def __init__(self, base_Usage=None, **kwargs):
super(CallMixin, self).__init__()
def client_and_supplier_are_operations(self, diagnostics=None, context=None):
"""self.base_Usage.client->forAll(oclIsKindOf(Operation)) and
self.base_Usage.supplier->forAll(oclIsKindOf(Operation))"""
raise NotImplementedError(
"operation client_and_supplier_are_operations(...) not yet implemented"
)
class CreateMixin(object):
"""User defined mixin class for Create."""
def __init__(self, base_BehavioralFeature=None, base_Usage=None, **kwargs):
super(CreateMixin, self).__init__()
def client_and_supplier_are_classifiers(self, diagnostics=None, context=None):
"""self.base_Usage->notEmpty() implies
(self.base_Usage.client->forAll(oclIsKindOf(Classifier)) and
self.base_Usage.supplier->forAll(oclIsKindOf(Classifier)))"""
raise NotImplementedError(
"operation client_and_supplier_are_classifiers(...) not yet implemented"
)
class DeriveMixin(object):
"""User defined mixin class for Derive."""
def __init__(self, computation=None, base_Abstraction=None, **kwargs):
super(DeriveMixin, self).__init__()
class DestroyMixin(object):
"""User defined mixin class for Destroy."""
def __init__(self, base_BehavioralFeature=None, **kwargs):
super(DestroyMixin, self).__init__()
class FileMixin(object):
"""User defined mixin class for File."""
def __init__(self, base_Artifact=None, **kwargs):
super(FileMixin, self).__init__()
class EntityMixin(object):
"""User defined mixin class for Entity."""
def __init__(self, base_Component=None, **kwargs):
super(EntityMixin, self).__init__()
class FocusMixin(object):
"""User defined mixin class for Focus."""
def __init__(self, base_Class=None, **kwargs):
super(FocusMixin, self).__init__()
class FrameworkMixin(object):
"""User defined mixin class for Framework."""
def __init__(self, base_Package=None, **kwargs):
super(FrameworkMixin, self).__init__()
class ImplementMixin(object):
"""User defined mixin class for Implement."""
def __init__(self, base_Component=None, **kwargs):
super(ImplementMixin, self).__init__()
def implements_specification(self, diagnostics=None, context=None):
"""self.base_Component.clientDependency.supplier->select(
oclIsKindOf(Classifier)).oclAsType(Classifier).extension_Specificaiton->
notEmpty()"""
raise NotImplementedError(
"operation implements_specification(...) not yet implemented"
)
class ImplementationClassMixin(object):
"""User defined mixin class for ImplementationClass."""
def __init__(self, base_Class=None, **kwargs):
super(ImplementationClassMixin, self).__init__()
def cannot_be_realization(self, diagnostics=None, context=None):
"""self.base_Class.extension_Realization->isEmpty()"""
raise NotImplementedError(
"operation cannot_be_realization(...) not yet implemented"
)
class InstantiateMixin(object):
"""User defined mixin class for Instantiate."""
def __init__(self, base_Usage=None, **kwargs):
super(InstantiateMixin, self).__init__()
def client_and_supplier_are_classifiers(self, diagnostics=None, context=None):
"""self.base_Usage.client->forAll(oclIsKindOf(Classifier)) and
self.base_Usage.supplier->forAll(oclIsKindOf(Classifier))"""
raise NotImplementedError(
"operation client_and_supplier_are_classifiers(...) not yet implemented"
)
class MetaclassMixin(object):
"""User defined mixin class for Metaclass."""
def __init__(self, base_Class=None, **kwargs):
super(MetaclassMixin, self).__init__()
class ModelLibraryMixin(object):
"""User defined mixin class for ModelLibrary."""
def __init__(self, base_Package=None, **kwargs):
super(ModelLibraryMixin, self).__init__()
class ProcessMixin(object):
"""User defined mixin class for Process."""
def __init__(self, base_Component=None, **kwargs):
super(ProcessMixin, self).__init__()
class RealizationMixin(object):
"""User defined mixin class for Realization."""
def __init__(self, base_Classifier=None, **kwargs):
super(RealizationMixin, self).__init__()
def cannot_be_implementation_class(self, diagnostics=None, context=None):
"""self.base_Classifier.extension_ImplementationClass->isEmpty()"""
raise NotImplementedError(
"operation cannot_be_implementation_class(...) not yet implemented"
)
class RefineMixin(object):
"""User defined mixin class for Refine."""
def __init__(self, base_Abstraction=None, **kwargs):
super(RefineMixin, self).__init__()
class ResponsibilityMixin(object):
"""User defined mixin class for Responsibility."""
def __init__(self, base_Usage=None, **kwargs):
super(ResponsibilityMixin, self).__init__()
class SendMixin(object):
"""User defined mixin class for Send."""
def __init__(self, base_Usage=None, **kwargs):
super(SendMixin, self).__init__()
def client_operation_sends_supplier_signal(self, diagnostics=None, context=None):
"""self.base_Usage.client->forAll(oclIsKindOf(Operation)) and
self.base_Usage.supplier->forAll(oclIsKindOf(Signal))"""
raise NotImplementedError(
"operation client_operation_sends_supplier_signal(...) not yet implemented"
)
class ServiceMixin(object):
"""User defined mixin class for Service."""
def __init__(self, base_Component=None, **kwargs):
super(ServiceMixin, self).__init__()
class SpecificationMixin(object):
"""User defined mixin class for Specification."""
def __init__(self, base_Classifier=None, **kwargs):
super(SpecificationMixin, self).__init__()
def cannot_be_type(self, diagnostics=None, context=None):
"""self.base_Classifier.extension_Type->isEmpty()"""
raise NotImplementedError("operation cannot_be_type(...) not yet implemented")
class SubsystemMixin(object):
"""User defined mixin class for Subsystem."""
def __init__(self, base_Component=None, **kwargs):
super(SubsystemMixin, self).__init__()
class TraceMixin(object):
"""User defined mixin class for Trace."""
def __init__(self, base_Abstraction=None, **kwargs):
super(TraceMixin, self).__init__()
class TypeMixin(object):
"""User defined mixin class for Type."""
def __init__(self, base_Class=None, **kwargs):
super(TypeMixin, self).__init__()
def cannot_be_specification(self, diagnostics=None, context=None):
"""self.base_Class.extension_Specification->isEmpty()"""
raise NotImplementedError(
"operation cannot_be_specification(...) not yet implemented"
)
class UtilityMixin(object):
"""User defined mixin class for Utility."""
def __init__(self, base_Class=None, **kwargs):
super(UtilityMixin, self).__init__()
def is_utility(self, diagnostics=None, context=None):
"""self.base_Class.feature->forAll(isStatic)"""
raise NotImplementedError("operation is_utility(...) not yet implemented")
class BuildComponentMixin(object):
"""User defined mixin class for BuildComponent."""
def __init__(self, base_Component=None, **kwargs):
super(BuildComponentMixin, self).__init__()
class MetamodelMixin(object):
"""User defined mixin class for Metamodel."""
def __init__(self, base_Model=None, **kwargs):
super(MetamodelMixin, self).__init__()
class SystemModelMixin(object):
"""User defined mixin class for SystemModel."""
def __init__(self, base_Model=None, **kwargs):
super(SystemModelMixin, self).__init__()
class DocumentMixin(object):
"""User defined mixin class for Document."""
def __init__(self, **kwargs):
super(DocumentMixin, self).__init__(**kwargs)
class ExecutableMixin(object):
"""User defined mixin class for Executable."""
def __init__(self, **kwargs):
super(ExecutableMixin, self).__init__(**kwargs)
class LibraryMixin(object):
"""User defined mixin class for Library."""
def __init__(self, **kwargs):
super(LibraryMixin, self).__init__(**kwargs)
class ScriptMixin(object):
"""User defined mixin class for Script."""
def __init__(self, **kwargs):
super(ScriptMixin, self).__init__(**kwargs)
class SourceMixin(object):
"""User defined mixin class for Source."""
def __init__(self, **kwargs):
super(SourceMixin, self).__init__(**kwargs)
|
a = float(input('Digite a primera nota: '))
b = float(input('Digite a segunda nota: '))
c = float(input('Digite a terceira nota:'))
d=(a+b+c)/3
if d<5:
print('O aluno atingiu a nota {:.2f} e por isso esta reprovado.'.format(d))
elif d<6.99:
print('O aluno atingiu a nota {:.2f} e por isso esta de recuperação.'.format(d))
else:
print('O aluno atingiu a nota {:.2f} e por isso esta aprovado.'.format(d))
print('FIM') |
# Automatically generated
# pylint: disable=all
get = [{'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 2.5, 'DefaultVCpus': 1, 'DefaultCores': 1, 'DefaultThreadsPerCore': 1, 'SizeInMiB': 3840, 'TotalSizeInGB': 4, 'Disks': [{'SizeInGB': 4, 'Count': 1, 'Type': 'ssd'}], 'NvmeSupport': 'unsupported', 'EncryptionSupport': 'supported', 'EbsOptimizedSupport': 'unsupported', 'NetworkPerformance': 'Moderate', 'MaximumNetworkInterfaces': 2, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': 'Moderate', 'MaximumNetworkInterfaces': 2}], 'Ipv4AddressesPerInterface': 6, 'Ipv6AddressesPerInterface': 0, 'Ipv6Supported': False, 'EnaSupport': 'unsupported', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['partition', 'spread'], 'InstanceType': 'm3.medium', 'CurrentGeneration': False, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs', 'instance-store'], 'SupportedVirtualizationTypes': ['hvm', 'paravirtual'], 'BareMetal': False, 'Hypervisor': 'xen', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 2.5}, 'VCpuInfo': {'DefaultVCpus': 1, 'DefaultCores': 1, 'DefaultThreadsPerCore': 1}, 'MemoryInfo': {'SizeInMiB': 3840}, 'InstanceStorageSupported': True, 'InstanceStorageInfo': {'TotalSizeInGB': 4, 'Disks': [{'SizeInGB': 4, 'Count': 1, 'Type': 'ssd'}], 'NvmeSupport': 'unsupported', 'EncryptionSupport': 'unsupported'}, 'EbsInfo': {'EbsOptimizedSupport': 'unsupported', 'EncryptionSupport': 'supported', 'NvmeSupport': 'unsupported'}, 'NetworkInfo': {'NetworkPerformance': 'Moderate', 'MaximumNetworkInterfaces': 2, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': 'Moderate', 'MaximumNetworkInterfaces': 2}], 'Ipv4AddressesPerInterface': 6, 'Ipv6AddressesPerInterface': 0, 'Ipv6Supported': False, 'EnaSupport': 'unsupported', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': True, 'AutoRecoverySupported': True, 'SupportedBootModes': ['legacy-bios']}, {'SupportedArchitectures': ['i386', 'x86_64'], 'SustainedClockSpeedInGhz': 2.5, 'DefaultVCpus': 1, 'DefaultCores': 1, 'DefaultThreadsPerCore': 1, 'SizeInMiB': 1024, 'EbsOptimizedSupport': 'unsupported', 'EncryptionSupport': 'supported', 'NvmeSupport': 'unsupported', 'NetworkPerformance': 'Low to Moderate', 'MaximumNetworkInterfaces': 2, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': 'Low to Moderate', 'MaximumNetworkInterfaces': 2}], 'Ipv4AddressesPerInterface': 2, 'Ipv6AddressesPerInterface': 2, 'Ipv6Supported': True, 'EnaSupport': 'unsupported', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['partition', 'spread'], 'InstanceType': 't2.micro', 'CurrentGeneration': True, 'FreeTierEligible': True, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'xen', 'ProcessorInfo': {'SupportedArchitectures': ['i386', 'x86_64'], 'SustainedClockSpeedInGhz': 2.5}, 'VCpuInfo': {'DefaultVCpus': 1, 'DefaultCores': 1, 'DefaultThreadsPerCore': 1}, 'MemoryInfo': {'SizeInMiB': 1024}, 'InstanceStorageSupported': False, 'EbsInfo': {'EbsOptimizedSupport': 'unsupported', 'EncryptionSupport': 'supported', 'NvmeSupport': 'unsupported'}, 'NetworkInfo': {'NetworkPerformance': 'Low to Moderate', 'MaximumNetworkInterfaces': 2, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': 'Low to Moderate', 'MaximumNetworkInterfaces': 2}], 'Ipv4AddressesPerInterface': 2, 'Ipv6AddressesPerInterface': 2, 'Ipv6Supported': True, 'EnaSupport': 'unsupported', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': True, 'DedicatedHostsSupported': False, 'AutoRecoverySupported': True, 'SupportedBootModes': ['legacy-bios']}, {'SupportedArchitectures': ['i386', 'x86_64'], 'SustainedClockSpeedInGhz': 2.4, 'DefaultVCpus': 1, 'DefaultCores': 1, 'DefaultThreadsPerCore': 1, 'SizeInMiB': 512, 'EbsOptimizedSupport': 'unsupported', 'EncryptionSupport': 'supported', 'NvmeSupport': 'unsupported', 'NetworkPerformance': 'Low to Moderate', 'MaximumNetworkInterfaces': 2, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': 'Low to Moderate', 'MaximumNetworkInterfaces': 2}], 'Ipv4AddressesPerInterface': 2, 'Ipv6AddressesPerInterface': 2, 'Ipv6Supported': True, 'EnaSupport': 'unsupported', 'EfaSupported': False, 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'uefi']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 2.5, 'DefaultVCpus': 32, 'DefaultCores': 16, 'DefaultThreadsPerCore': 2, 'ValidCores': [4, 6, 8, 10, 12, 14, 16], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 131072, 'TotalSizeInGB': 1200, 'Disks': [{'SizeInGB': 600, 'Count': 2, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'supported', 'EbsOptimizedSupport': 'default', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 4750, 'BaselineThroughputInMBps': 593.75, 'BaselineIops': 20000, 'MaximumBandwidthInMbps': 4750, 'MaximumThroughputInMBps': 593.75, 'MaximumIops': 20000}, 'NetworkPerformance': 'Up to 10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': 'Up to 10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'm5ad.8xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'nitro', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 2.5}, 'VCpuInfo': {'DefaultVCpus': 32, 'DefaultCores': 16, 'DefaultThreadsPerCore': 2, 'ValidCores': [4, 6, 8, 10, 12, 14, 16], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 131072}, 'InstanceStorageSupported': True, 'InstanceStorageInfo': {'TotalSizeInGB': 1200, 'Disks': [{'SizeInGB': 600, 'Count': 2, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'required'}, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 4750, 'BaselineThroughputInMBps': 593.75, 'BaselineIops': 20000, 'MaximumBandwidthInMbps': 4750, 'MaximumThroughputInMBps': 593.75, 'MaximumIops': 20000}, 'NvmeSupport': 'required'}, 'NetworkInfo': {'NetworkPerformance': 'Up to 10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': 'Up to 10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': False, 'AutoRecoverySupported': False, 'SupportedBootModes': ['legacy-bios', 'uefi']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.1, 'DefaultVCpus': 32, 'DefaultCores': 16, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 131072, 'TotalSizeInGB': 1200, 'Disks': [{'SizeInGB': 600, 'Count': 2, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'supported', 'EbsOptimizedSupport': 'default', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 6800, 'BaselineThroughputInMBps': 850.0, 'BaselineIops': 30000, 'MaximumBandwidthInMbps': 6800, 'MaximumThroughputInMBps': 850.0, 'MaximumIops': 30000}, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'm5d.8xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'nitro', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.1}, 'VCpuInfo': {'DefaultVCpus': 32, 'DefaultCores': 16, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 131072}, 'InstanceStorageSupported': True, 'InstanceStorageInfo': {'TotalSizeInGB': 1200, 'Disks': [{'SizeInGB': 600, 'Count': 2, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'required'}, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 6800, 'BaselineThroughputInMBps': 850.0, 'BaselineIops': 30000, 'MaximumBandwidthInMbps': 6800, 'MaximumThroughputInMBps': 850.0, 'MaximumIops': 30000}, 'NvmeSupport': 'required'}, 'NetworkInfo': {'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': True, 'AutoRecoverySupported': False, 'SupportedBootModes': ['legacy-bios', 'uefi']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 2.9, 'DefaultVCpus': 36, 'DefaultCores': 18, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 61440, 'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 4000, 'BaselineThroughputInMBps': 500.0, 'BaselineIops': 32000, 'MaximumBandwidthInMbps': 4000, 'MaximumThroughputInMBps': 500.0, 'MaximumIops': 32000}, 'NvmeSupport': 'unsupported', 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'unsupported', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'c4.8xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'xen', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 2.9}, 'VCpuInfo': {'DefaultVCpus': 36, 'DefaultCores': 18, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 61440}, 'InstanceStorageSupported': False, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 4000, 'BaselineThroughputInMBps': 500.0, 'BaselineIops': 32000, 'MaximumBandwidthInMbps': 4000, 'MaximumThroughputInMBps': 500.0, 'MaximumIops': 32000}, 'NvmeSupport': 'unsupported'}, 'NetworkInfo': {'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'unsupported', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': True, 'AutoRecoverySupported': True, 'SupportedBootModes': ['legacy-bios']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.4, 'DefaultVCpus': 36, 'DefaultCores': 18, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 73728, 'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 9500, 'BaselineThroughputInMBps': 1187.5, 'BaselineIops': 40000, 'MaximumBandwidthInMbps': 9500, 'MaximumThroughputInMBps': 1187.5, 'MaximumIops': 40000}, 'NvmeSupport': 'required', 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'c5.9xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'nitro', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.4}, 'VCpuInfo': {'DefaultVCpus': 36, 'DefaultCores': 18, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 73728}, 'InstanceStorageSupported': False, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 9500, 'BaselineThroughputInMBps': 1187.5, 'BaselineIops': 40000, 'MaximumBandwidthInMbps': 9500, 'MaximumThroughputInMBps': 1187.5, 'MaximumIops': 40000}, 'NvmeSupport': 'required'}, 'NetworkInfo': {'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': True, 'AutoRecoverySupported': True, 'SupportedBootModes': ['legacy-bios', 'uefi']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.4, 'DefaultVCpus': 36, 'DefaultCores': 18, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 73728, 'TotalSizeInGB': 900, 'Disks': [{'SizeInGB': 900, 'Count': 1, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'supported', 'EbsOptimizedSupport': 'default', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 9500, 'BaselineThroughputInMBps': 1187.5, 'BaselineIops': 40000, 'MaximumBandwidthInMbps': 9500, 'MaximumThroughputInMBps': 1187.5, 'MaximumIops': 40000}, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'c5d.9xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'nitro', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.4}, 'VCpuInfo': {'DefaultVCpus': 36, 'DefaultCores': 18, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 73728}, 'InstanceStorageSupported': True, 'InstanceStorageInfo': {'TotalSizeInGB': 900, 'Disks': [{'SizeInGB': 900, 'Count': 1, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'required'}, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 9500, 'BaselineThroughputInMBps': 1187.5, 'BaselineIops': 40000, 'MaximumBandwidthInMbps': 9500, 'MaximumThroughputInMBps': 1187.5, 'MaximumIops': 40000}, 'NvmeSupport': 'required'}, 'NetworkInfo': {'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '10 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': True, 'AutoRecoverySupported': False, 'SupportedBootModes': ['legacy-bios', 'uefi']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.6, 'DefaultVCpus': 48, 'DefaultCores': 24, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 98304, 'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 9500, 'BaselineThroughputInMBps': 1187.5, 'BaselineIops': 40000, 'MaximumBandwidthInMbps': 9500, 'MaximumThroughputInMBps': 1187.5, 'MaximumIops': 40000}, 'NvmeSupport': 'required', 'NetworkPerformance': '12 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '12 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'c5.12xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'nitro', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.6}, 'VCpuInfo': {'DefaultVCpus': 48, 'DefaultCores': 24, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 98304}, 'InstanceStorageSupported': False, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 9500, 'BaselineThroughputInMBps': 1187.5, 'BaselineIops': 40000, 'MaximumBandwidthInMbps': 9500, 'MaximumThroughputInMBps': 1187.5, 'MaximumIops': 40000}, 'NvmeSupport': 'required'}, 'NetworkInfo': {'NetworkPerformance': '12 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '12 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': False, 'AutoRecoverySupported': True, 'SupportedBootModes': ['legacy-bios', 'uefi']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.6, 'DefaultVCpus': 48, 'DefaultCores': 24, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 98304, 'TotalSizeInGB': 1800, 'Disks': [{'SizeInGB': 900, 'Count': 2, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'supported', 'EbsOptimizedSupport': 'default', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 9500, 'BaselineThroughputInMBps': 1187.5, 'BaselineIops': 40000, 'MaximumBandwidthInMbps': 9500, 'MaximumThroughputInMBps': 1187.5, 'MaximumIops': 40000}, 'NetworkPerformance': '12 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '12 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'c5d.12xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'nitro', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.6}, 'VCpuInfo': {'DefaultVCpus': 48, 'DefaultCores': 24, 'DefaultThreadsPerCore': 2, 'ValidCores': [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 98304}, 'InstanceStorageSupported': True, 'InstanceStorageInfo': {'TotalSizeInGB': 1800, 'Disks': [{'SizeInGB': 900, 'Count': 2, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'required'}, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 9500, 'BaselineThroughputInMBps': 1187.5, 'BaselineIops': 40000, 'MaximumBandwidthInMbps': 9500, 'MaximumThroughputInMBps': 1187.5, 'MaximumIops': 40000}, 'NvmeSupport': 'required'}, 'NetworkInfo': {'NetworkPerformance': '12 Gigabit', 'MaximumNetworkInterfaces': 8, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '12 Gigabit', 'MaximumNetworkInterfaces': 8}], 'Ipv4AddressesPerInterface': 30, 'Ipv6AddressesPerInterface': 30, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': False, 'AutoRecoverySupported': False, 'SupportedBootModes': ['legacy-bios', 'uefi']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.4, 'DefaultVCpus': 72, 'DefaultCores': 36, 'DefaultThreadsPerCore': 2, 'ValidCores': [4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 147456, 'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 19000, 'BaselineThroughputInMBps': 2375.0, 'BaselineIops': 80000, 'MaximumBandwidthInMbps': 19000, 'MaximumThroughputInMBps': 2375.0, 'MaximumIops': 80000}, 'NvmeSupport': 'required', 'NetworkPerformance': '25 Gigabit', 'MaximumNetworkInterfaces': 15, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '25 Gigabit', 'MaximumNetworkInterfaces': 15}], 'Ipv4AddressesPerInterface': 50, 'Ipv6AddressesPerInterface': 50, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'c5.18xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'nitro', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.4}, 'VCpuInfo': {'DefaultVCpus': 72, 'DefaultCores': 36, 'DefaultThreadsPerCore': 2, 'ValidCores': [4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 147456}, 'InstanceStorageSupported': False, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 19000, 'BaselineThroughputInMBps': 2375.0, 'BaselineIops': 80000, 'MaximumBandwidthInMbps': 19000, 'MaximumThroughputInMBps': 2375.0, 'MaximumIops': 80000}, 'NvmeSupport': 'required'}, 'NetworkInfo': {'NetworkPerformance': '25 Gigabit', 'MaximumNetworkInterfaces': 15, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '25 Gigabit', 'MaximumNetworkInterfaces': 15}], 'Ipv4AddressesPerInterface': 50, 'Ipv6AddressesPerInterface': 50, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': True, 'AutoRecoverySupported': True, 'SupportedBootModes': ['legacy-bios', 'uefi']}, {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.4, 'DefaultVCpus': 72, 'DefaultCores': 36, 'DefaultThreadsPerCore': 2, 'ValidCores': [4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36], 'ValidThreadsPerCore': [1, 2], 'SizeInMiB': 147456, 'TotalSizeInGB': 1800, 'Disks': [{'SizeInGB': 900, 'Count': 2, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'supported', 'EbsOptimizedSupport': 'default', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 19000, 'BaselineThroughputInMBps': 2375.0, 'BaselineIops': 80000, 'MaximumBandwidthInMbps': 19000, 'MaximumThroughputInMBps': 2375.0, 'MaximumIops': 80000}, 'NetworkPerformance': '25 Gigabit', 'MaximumNetworkInterfaces': 15, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '25 Gigabit', 'MaximumNetworkInterfaces': 15}], 'Ipv4AddressesPerInterface': 50, 'Ipv6AddressesPerInterface': 50, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False, 'SupportedStrategies': ['cluster', 'partition', 'spread'], 'InstanceType': 'c5d.18xlarge', 'CurrentGeneration': True, 'FreeTierEligible': False, 'SupportedUsageClasses': ['on-demand', 'spot'], 'SupportedRootDeviceTypes': ['ebs'], 'SupportedVirtualizationTypes': ['hvm'], 'BareMetal': False, 'Hypervisor': 'nitro', 'ProcessorInfo': {'SupportedArchitectures': ['x86_64'], 'SustainedClockSpeedInGhz': 3.4}, 'VCpuInfo': {'DefaultVCpus': 72, 'DefaultCores': 36, 'DefaultThreadsPerCore': 2, 'ValidCores': [4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36], 'ValidThreadsPerCore': [1, 2]}, 'MemoryInfo': {'SizeInMiB': 147456}, 'InstanceStorageSupported': True, 'InstanceStorageInfo': {'TotalSizeInGB': 1800, 'Disks': [{'SizeInGB': 900, 'Count': 2, 'Type': 'ssd'}], 'NvmeSupport': 'required', 'EncryptionSupport': 'required'}, 'EbsInfo': {'EbsOptimizedSupport': 'default', 'EncryptionSupport': 'supported', 'EbsOptimizedInfo': {'BaselineBandwidthInMbps': 19000, 'BaselineThroughputInMBps': 2375.0, 'BaselineIops': 80000, 'MaximumBandwidthInMbps': 19000, 'MaximumThroughputInMBps': 2375.0, 'MaximumIops': 80000}, 'NvmeSupport': 'required'}, 'NetworkInfo': {'NetworkPerformance': '25 Gigabit', 'MaximumNetworkInterfaces': 15, 'MaximumNetworkCards': 1, 'DefaultNetworkCardIndex': 0, 'NetworkCards': [{'NetworkCardIndex': 0, 'NetworkPerformance': '25 Gigabit', 'MaximumNetworkInterfaces': 15}], 'Ipv4AddressesPerInterface': 50, 'Ipv6AddressesPerInterface': 50, 'Ipv6Supported': True, 'EnaSupport': 'required', 'EfaSupported': False, 'EncryptionInTransitSupported': False}, 'PlacementGroupInfo': {'SupportedStrategies': ['cluster', 'partition', 'spread']}, 'HibernationSupported': True, 'BurstablePerformanceSupported': False, 'DedicatedHostsSupported': True, 'AutoRecoverySupported': False, 'SupportedBootModes': ['legacy-bios', 'uefi']}] # noqa: E501
def get_instances_list() -> list:
'''Returns list EC2 instances with HibernationSupported = True .'''
# pylint: disable=all
return get
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#!/usr/bin/env python3
class ProjectMain:
data = dict()
def __init__(self):
pass
def get_greeting(self):
return self.data.get('greeting')
def set_greeting(self, greeting = 'Hello user!'):
self.data.setdefault('greeting', greeting)
|
# Copyright (C) 2018 Google Inc.
# Licensed under http://www.apache.org/licenses/LICENSE-2.0 <see LICENSE file>
"""Names of pre and postfixes of methods used in various classes
in lower case."""
SELECT_PREFIX = "select_"
|
# V0
# V1
# https://blog.csdn.net/fuxuemingzhu/article/details/83539773
class Solution(object):
def beautifulArray(self, N):
"""
:type N: int
:rtype: List[int]
"""
res = [1]
while len(res) < N:
res = [2 * i - 1 for i in res] + [2 * i for i in res]
return [i for i in res if i <= N]
# V1'
# https://blog.csdn.net/fuxuemingzhu/article/details/83539773
# IDEA : ITERATION
class Solution(object):
def beautifulArray(self, N):
"""
:type N: int
:rtype: List[int]
"""
if N == 1: return [1]
odd = [i * 2 - 1 for i in self.beautifulArray(N / 2 + N % 2)]
even = [i * 2 for i in self.beautifulArray(N / 2)]
return odd + even
# V2
# Time: O(n)
# Space: O(n)
class Solution(object):
def beautifulArray(self, N):
"""
:type N: int
:rtype: List[int]
"""
result = [1]
while len(result) < N:
result = [i*2 - 1 for i in result] + [i*2 for i in result]
return [i for i in result if i <= N] |
class Rect(object):
def __init__(self, x, y, width, height):
self.x = x
self.y = y
self.width = width
self.height = height
self._x_center = x + (width / 2)
self._y_center = y + (height / 2)
@property
def x_center(self):
return int(self.x +(self.width / 2))
@property
def y_center(self):
return int(self.y +(self.height / 2))
def check_collision(self, other_rect):
if self.x + self.width in range(other_rect.x, other_rect.x + other_rect.width) and self.y + self.height in range(other_rect.y, other_rect.y + other_rect.height) or \
self.x in range(other_rect.x, other_rect.x + other_rect.width) and self.y in range(other_rect.y, other_rect.y + other_rect.height):
return True
return False |
"""
练习:将下列英文语句按照单词进行翻转.
转换前:To have a government that is of people by people for people
转换后:people for people by people of is that government a have To
"""
message = "To have a government that is of people by people for people"
list_datas = message.split(" ")
message = " ".join(list_datas[::-1])
print(message) |
class BankCodeValidationError(ValueError):
code = 'clabe.bank_code'
msg_template = 'código de banco no es válido'
class ClabeControlDigitValidationError(ValueError):
code = 'clabe.control_digit'
msg_template = 'clabe dígito de control no es válido'
|
def binary_search(array, target_value):
left = 0
right = len(array) - 1
while left <= right:
mid = (left + right) / 2
if array[mid] == target_value:
return mid
if array[mid] > target_value:
right = mid - 1
elif array[mid] < target_value:
left = mid + 1
return right + 1 |
# Datos de entrada
puntos=int(input("Puntuacion obtenida: "))
# Proceso
if puntos>0 and puntos<=100:
print("Usted obtenio 1 salario minimo.")
elif puntos>100 and puntos<=150:
print("Usted obtenio 2 salarios minimos")
elif puntos>150:
print("Usted obtenio 3 salarios minimos") |
def report(s):
l = list(s)
l.sort()
print(l)
s = {1, 2, 3, 4}
report(s)
report(s.intersection({1, 3}))
report(s.intersection([3, 4]))
print(s.intersection_update([1]))
report(s)
|
class RomMethod:
"""Base class for ROM methods."""
def __init__(self, sol_domain, rom_domain):
rom_dict = rom_domain.rom_dict
# Should have as many centering and normalization profiles as there are models
try:
assert len(rom_dict["cent_profs"]) == rom_domain.num_models
assert len(rom_dict["norm_fac_profs"]) == rom_domain.num_models
assert len(rom_dict["norm_sub_profs"]) == rom_domain.num_models
except AssertionError:
raise AssertionError("Feature scaling profiles must have as many files as there are models")
|
cars = ["Ford", "Volvo", "BMW"]
for x in cars:
print(x)
|
# Code for Vegeneres Cipher
# List of all the Alphabets using List Comprehension
lst = [chr(x) for x in range(65, 91)]
# Creating Vegeneres Table using for loops
# # 2D List to Store the Vegeneres Table
# arr = []
# for i in range(0, 26):
# # List to store rows Alphabets respective to their Index
# temp = []
# c = i
# for j in range(0, 26):
# # Appending the Alphabets in the temporary list(row)
# temp.append(lst[c % 26])
# c += 1
# # now Appending the row in the 2D list
# arr.append(temp)
# Provide Options
print("Welcome to Ph@ntom's Cipher :::")
print("1 >>> Encrypt")
print("2 >>> Decrypt")
# Input the Plain Text and the Corresponding Key
ch = int(input('>>>'))
if ch == 1:
print("Enter the Text to be Encrypted")
# Taking the input and converting into UpperCase
str = input('-->>>').upper()
print("Enter the Key")
# Taking the Key in UpperCase and Converting it into a List
Key = list(input("should contain NO Spaces >>>").upper())
# Length of the Key
l = len(Key)
# Removing any Spaces Available in the Plain Text
# Plain = list("".join(str.split()))
# List Containing the Cipher Text
Cipher = []
for i in range(len(str)):
if str[i] != ' ':
k = lst.index(Key[i % l])
m = lst.index(str[i])
Cipher.append(lst[(m + k) % 26])
else:
Cipher.append(' ')
# Print out the Cipher Text
print("The Encrypted Text is :::")
print("".join(Cipher))
elif ch == 2:
print("Enter the Text to be Derypted")
# Taking the input and converting into UpperCase
str = input('-->>>').upper()
print("Enter the Key")
# Taking the Key in UpperCase and Converting it into a List
Key = list(input("should contain NO Spaces >>>").upper())
# Length of the Key
l = len(Key)
# Removing any Spaces Available in the Encrypted Text
# Cipher = list("".join(str.split()))
# List Containing the Decrypted Text
Decipher = []
for i in range(len(str)):
if str[i] != ' ':
k = lst.index(Key[i % l])
m = lst.index(str[i])
Decipher.append(lst[(m - k) % 26])
else:
Decipher.append(' ')
# Print out the Decrypted Text
print("The Decrypted Text is :::")
print("".join(Decipher))
|
class BatteryChargeStatus(Enum,IComparable,IFormattable,IConvertible):
"""
Defines identifiers that indicate the current battery charge level or charging state information.
enum (flags) BatteryChargeStatus,values: Charging (8),Critical (4),High (1),Low (2),NoSystemBattery (128),Unknown (255)
"""
def __eq__(self,*args):
""" x.__eq__(y) <==> x==yx.__eq__(y) <==> x==yx.__eq__(y) <==> x==y """
pass
def __format__(self,*args):
""" __format__(formattable: IFormattable,format: str) -> str """
pass
def __ge__(self,*args):
pass
def __gt__(self,*args):
pass
def __init__(self,*args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
def __le__(self,*args):
pass
def __lt__(self,*args):
pass
def __ne__(self,*args):
pass
def __reduce_ex__(self,*args):
pass
def __str__(self,*args):
pass
Charging=None
Critical=None
High=None
Low=None
NoSystemBattery=None
Unknown=None
value__=None
|
{
"targets": [
{
"target_name": "node_statvfs",
"sources": [
"main.cpp"
],
"cflags!": [
"-fno-exceptions"
],
"cflags_cc!": [
"-fno-exceptions"
],
"cflags+": [
"-fvisibility=hidden"
],
"include_dirs": [
"<!(node -p \"require('node-addon-api').include_dir\")"
],
"defines": [
"NODE_ADDON_API_DISABLE_DEPRECATED",
"NAPI_VERSION=<(napi_build_version)"
]
}
]
}
|
# Smallest multiple
# Problem 5
# 2520 is the smallest number that can be divided by each of the numbers from 1 to 10 without any remainder.
# What is the smallest positive number that is evenly divisible by all of the numbers from 1 to 20?
def modular_sum(count, limit):
minimum = int(limit / 2) + 1
mods = list(range(minimum, limit)) # 11-19
s = 0
for n in mods:
s = s + count % n
return s
def solution(limit):
found = False
count = 0
while not found:
count = count + limit
if modular_sum(count, limit) == 0:
found = True
return count
def main():
ans = solution(10)
print(ans)
if __name__ == '__main__':
main()
|
# constants
db_name = "cryptodb"
salt = b'\x04\xa8y#AN\xba\xb0u\x0c\xd2\xbd"\x002pFWFEQvba[e021efg@fsa'
BS = 32
|
"""
PASSENGERS
"""
numPassengers = 4053
passenger_arriving = (
(5, 14, 9, 5, 2, 0, 9, 8, 8, 10, 0, 0), # 0
(5, 9, 6, 3, 1, 0, 0, 12, 5, 11, 4, 0), # 1
(5, 8, 9, 2, 2, 0, 6, 9, 5, 4, 3, 0), # 2
(7, 9, 13, 3, 3, 0, 7, 14, 5, 9, 2, 0), # 3
(4, 14, 11, 4, 0, 0, 4, 9, 9, 12, 4, 0), # 4
(3, 9, 9, 9, 3, 0, 10, 11, 5, 5, 2, 0), # 5
(9, 8, 10, 2, 0, 0, 8, 9, 4, 5, 1, 0), # 6
(5, 11, 5, 2, 3, 0, 6, 9, 9, 3, 1, 0), # 7
(2, 8, 5, 6, 1, 0, 7, 19, 6, 2, 4, 0), # 8
(6, 15, 6, 2, 8, 0, 10, 8, 7, 5, 3, 0), # 9
(5, 6, 10, 3, 2, 0, 7, 10, 8, 8, 4, 0), # 10
(5, 11, 8, 5, 0, 0, 8, 6, 3, 7, 0, 0), # 11
(2, 12, 14, 4, 4, 0, 6, 7, 3, 9, 4, 0), # 12
(4, 12, 7, 6, 5, 0, 15, 15, 4, 2, 5, 0), # 13
(3, 12, 7, 6, 5, 0, 8, 12, 5, 9, 4, 0), # 14
(4, 17, 10, 1, 5, 0, 11, 9, 9, 9, 3, 0), # 15
(8, 12, 7, 4, 2, 0, 6, 14, 5, 7, 6, 0), # 16
(7, 10, 10, 3, 2, 0, 9, 18, 8, 7, 4, 0), # 17
(3, 6, 11, 3, 7, 0, 9, 12, 6, 4, 0, 0), # 18
(9, 15, 12, 8, 2, 0, 13, 16, 7, 10, 3, 0), # 19
(4, 18, 6, 9, 5, 0, 13, 6, 6, 7, 3, 0), # 20
(6, 12, 7, 4, 3, 0, 5, 7, 8, 5, 4, 0), # 21
(11, 7, 11, 8, 5, 0, 13, 8, 12, 4, 2, 0), # 22
(7, 15, 13, 2, 1, 0, 7, 9, 6, 10, 4, 0), # 23
(8, 8, 9, 4, 3, 0, 7, 13, 9, 5, 1, 0), # 24
(5, 18, 10, 5, 4, 0, 8, 14, 8, 9, 0, 0), # 25
(2, 12, 10, 4, 2, 0, 15, 13, 9, 11, 1, 0), # 26
(5, 7, 11, 7, 0, 0, 8, 10, 8, 3, 1, 0), # 27
(6, 15, 16, 2, 3, 0, 5, 10, 7, 8, 1, 0), # 28
(6, 8, 8, 4, 1, 0, 7, 7, 2, 7, 4, 0), # 29
(4, 13, 12, 4, 1, 0, 6, 15, 9, 9, 3, 0), # 30
(6, 11, 11, 4, 2, 0, 8, 17, 11, 6, 3, 0), # 31
(4, 19, 5, 7, 2, 0, 4, 17, 6, 6, 1, 0), # 32
(3, 15, 9, 6, 3, 0, 6, 14, 6, 3, 5, 0), # 33
(6, 11, 6, 6, 0, 0, 11, 11, 7, 8, 4, 0), # 34
(7, 8, 4, 4, 6, 0, 8, 11, 6, 4, 3, 0), # 35
(4, 10, 15, 3, 3, 0, 6, 8, 7, 5, 3, 0), # 36
(2, 8, 1, 10, 3, 0, 10, 13, 3, 2, 2, 0), # 37
(5, 10, 9, 4, 3, 0, 9, 7, 6, 9, 1, 0), # 38
(5, 12, 5, 5, 0, 0, 8, 8, 12, 3, 5, 0), # 39
(4, 10, 14, 5, 2, 0, 8, 11, 8, 2, 5, 0), # 40
(5, 13, 9, 3, 1, 0, 5, 9, 7, 6, 3, 0), # 41
(7, 12, 8, 8, 3, 0, 9, 13, 9, 10, 2, 0), # 42
(9, 13, 10, 9, 0, 0, 7, 12, 7, 7, 1, 0), # 43
(1, 16, 13, 5, 2, 0, 10, 14, 10, 5, 2, 0), # 44
(6, 14, 14, 7, 2, 0, 9, 14, 6, 6, 5, 0), # 45
(4, 18, 8, 8, 2, 0, 17, 12, 9, 10, 3, 0), # 46
(10, 12, 6, 2, 3, 0, 9, 8, 5, 4, 7, 0), # 47
(4, 11, 4, 9, 1, 0, 8, 14, 7, 10, 0, 0), # 48
(6, 13, 7, 4, 3, 0, 8, 9, 6, 3, 4, 0), # 49
(9, 14, 8, 6, 4, 0, 7, 6, 6, 3, 3, 0), # 50
(3, 11, 8, 6, 3, 0, 9, 13, 5, 7, 2, 0), # 51
(6, 12, 11, 2, 2, 0, 3, 10, 6, 10, 3, 0), # 52
(9, 16, 9, 5, 1, 0, 5, 11, 13, 5, 2, 0), # 53
(6, 14, 13, 3, 3, 0, 5, 10, 10, 8, 4, 0), # 54
(2, 13, 6, 3, 4, 0, 7, 7, 7, 6, 1, 0), # 55
(4, 14, 8, 6, 1, 0, 6, 14, 8, 6, 3, 0), # 56
(5, 9, 7, 3, 3, 0, 6, 12, 7, 9, 2, 0), # 57
(3, 9, 9, 4, 4, 0, 5, 14, 7, 5, 3, 0), # 58
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 59
)
station_arriving_intensity = (
(4.769372805092186, 12.233629261363635, 14.389624839331619, 11.405298913043477, 12.857451923076923, 8.562228260869567), # 0
(4.81413961808604, 12.369674877683082, 14.46734796754499, 11.46881589673913, 12.953819711538461, 8.559309850543478), # 1
(4.8583952589991215, 12.503702525252525, 14.54322622107969, 11.530934782608696, 13.048153846153847, 8.556302173913043), # 2
(4.902102161984196, 12.635567578125, 14.617204169344474, 11.591602581521737, 13.14036778846154, 8.553205638586958), # 3
(4.94522276119403, 12.765125410353535, 14.689226381748071, 11.650766304347826, 13.230375, 8.550020652173911), # 4
(4.987719490781387, 12.892231395991162, 14.759237427699228, 11.708372961956522, 13.318088942307691, 8.546747622282608), # 5
(5.029554784899035, 13.01674090909091, 14.827181876606687, 11.764369565217393, 13.403423076923078, 8.54338695652174), # 6
(5.0706910776997365, 13.138509323705808, 14.893004297879177, 11.818703125, 13.486290865384618, 8.5399390625), # 7
(5.1110908033362605, 13.257392013888888, 14.956649260925452, 11.871320652173912, 13.56660576923077, 8.536404347826087), # 8
(5.1507163959613695, 13.373244353693181, 15.018061335154243, 11.922169157608696, 13.644281249999999, 8.532783220108696), # 9
(5.1895302897278315, 13.485921717171717, 15.077185089974291, 11.971195652173915, 13.719230769230771, 8.529076086956522), # 10
(5.227494918788412, 13.595279478377526, 15.133965094794343, 12.018347146739131, 13.791367788461539, 8.525283355978262), # 11
(5.2645727172958745, 13.701173011363636, 15.188345919023137, 12.063570652173912, 13.860605769230768, 8.521405434782608), # 12
(5.3007261194029835, 13.803457690183082, 15.240272132069407, 12.106813179347826, 13.926858173076925, 8.51744273097826), # 13
(5.335917559262511, 13.90198888888889, 15.289688303341899, 12.148021739130433, 13.99003846153846, 8.513395652173912), # 14
(5.370109471027217, 13.996621981534089, 15.336539002249355, 12.187143342391304, 14.050060096153846, 8.509264605978261), # 15
(5.403264288849868, 14.087212342171718, 15.380768798200515, 12.224124999999999, 14.10683653846154, 8.50505), # 16
(5.4353444468832315, 14.173615344854797, 15.422322260604112, 12.258913722826087, 14.16028125, 8.500752241847827), # 17
(5.46631237928007, 14.255686363636363, 15.461143958868895, 12.291456521739132, 14.210307692307696, 8.496371739130435), # 18
(5.496130520193152, 14.333280772569443, 15.4971784624036, 12.321700407608695, 14.256829326923079, 8.491908899456522), # 19
(5.524761303775241, 14.40625394570707, 15.530370340616965, 12.349592391304348, 14.299759615384616, 8.487364130434782), # 20
(5.552167164179106, 14.47446125710227, 15.56066416291774, 12.375079483695652, 14.339012019230768, 8.482737839673913), # 21
(5.578310535557506, 14.537758080808082, 15.588004498714653, 12.398108695652175, 14.374499999999998, 8.47803043478261), # 22
(5.603153852063214, 14.595999790877526, 15.612335917416454, 12.418627038043478, 14.40613701923077, 8.473242323369567), # 23
(5.62665954784899, 14.649041761363636, 15.633602988431875, 12.43658152173913, 14.433836538461538, 8.468373913043479), # 24
(5.648790057067603, 14.696739366319445, 15.651750281169667, 12.451919157608696, 14.457512019230768, 8.463425611413044), # 25
(5.669507813871817, 14.738947979797977, 15.66672236503856, 12.464586956521739, 14.477076923076922, 8.458397826086957), # 26
(5.688775252414398, 14.77552297585227, 15.6784638094473, 12.474531929347828, 14.492444711538463, 8.453290964673915), # 27
(5.7065548068481124, 14.806319728535353, 15.68691918380463, 12.481701086956523, 14.503528846153845, 8.448105434782608), # 28
(5.722808911325724, 14.831193611900254, 15.69203305751928, 12.486041440217392, 14.510242788461538, 8.44284164402174), # 29
(5.7375, 14.85, 15.69375, 12.4875, 14.512500000000001, 8.4375), # 30
(5.751246651214834, 14.865621839488634, 15.692462907608693, 12.487236580882353, 14.511678590425532, 8.430077267616193), # 31
(5.7646965153452685, 14.881037215909092, 15.68863804347826, 12.486451470588234, 14.509231914893617, 8.418644565217393), # 32
(5.777855634590792, 14.896244211647728, 15.682330027173915, 12.485152389705883, 14.50518630319149, 8.403313830584706), # 33
(5.790730051150895, 14.91124090909091, 15.67359347826087, 12.483347058823531, 14.499568085106382, 8.38419700149925), # 34
(5.803325807225064, 14.926025390624996, 15.662483016304348, 12.481043198529411, 14.492403590425532, 8.361406015742128), # 35
(5.815648945012788, 14.940595738636366, 15.649053260869564, 12.478248529411767, 14.48371914893617, 8.335052811094453), # 36
(5.8277055067135555, 14.954950035511365, 15.63335883152174, 12.474970772058823, 14.47354109042553, 8.305249325337332), # 37
(5.839501534526853, 14.969086363636364, 15.615454347826088, 12.471217647058824, 14.461895744680852, 8.272107496251873), # 38
(5.851043070652174, 14.983002805397728, 15.595394429347825, 12.466996875000001, 14.44880944148936, 8.23573926161919), # 39
(5.862336157289003, 14.99669744318182, 15.573233695652176, 12.462316176470589, 14.434308510638296, 8.196256559220389), # 40
(5.873386836636828, 15.010168359374997, 15.549026766304348, 12.457183272058824, 14.418419281914893, 8.153771326836583), # 41
(5.88420115089514, 15.023413636363639, 15.522828260869566, 12.451605882352942, 14.401168085106384, 8.108395502248875), # 42
(5.894785142263428, 15.03643135653409, 15.494692798913043, 12.445591727941178, 14.38258125, 8.060241023238381), # 43
(5.905144852941176, 15.049219602272727, 15.464675, 12.439148529411764, 14.36268510638298, 8.009419827586207), # 44
(5.915286325127877, 15.061776455965909, 15.432829483695656, 12.43228400735294, 14.341505984042554, 7.956043853073464), # 45
(5.925215601023019, 15.074100000000003, 15.39921086956522, 12.425005882352941, 14.319070212765958, 7.90022503748126), # 46
(5.934938722826087, 15.086188316761364, 15.363873777173913, 12.417321874999999, 14.295404122340427, 7.842075318590705), # 47
(5.944461732736574, 15.098039488636365, 15.326872826086957, 12.409239705882353, 14.27053404255319, 7.7817066341829095), # 48
(5.953790672953963, 15.10965159801136, 15.288262635869566, 12.400767095588236, 14.24448630319149, 7.71923092203898), # 49
(5.96293158567775, 15.121022727272724, 15.248097826086958, 12.391911764705883, 14.217287234042553, 7.65476011994003), # 50
(5.971890513107417, 15.132150958806818, 15.206433016304347, 12.38268143382353, 14.188963164893616, 7.588406165667167), # 51
(5.980673497442456, 15.143034375, 15.163322826086954, 12.373083823529411, 14.159540425531915, 7.5202809970015), # 52
(5.989286580882353, 15.153671058238638, 15.118821875, 12.363126654411765, 14.129045345744682, 7.450496551724138), # 53
(5.9977358056266, 15.164059090909088, 15.072984782608694, 12.352817647058824, 14.09750425531915, 7.379164767616192), # 54
(6.00602721387468, 15.174196555397728, 15.02586616847826, 12.342164522058825, 14.064943484042553, 7.306397582458771), # 55
(6.014166847826087, 15.184081534090907, 14.977520652173913, 12.331175, 14.031389361702129, 7.232306934032984), # 56
(6.022160749680308, 15.193712109375003, 14.92800285326087, 12.319856801470587, 13.996868218085105, 7.15700476011994), # 57
(6.030014961636829, 15.203086363636363, 14.877367391304347, 12.308217647058825, 13.961406382978723, 7.0806029985007495), # 58
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59
)
passenger_arriving_acc = (
(5, 14, 9, 5, 2, 0, 9, 8, 8, 10, 0, 0), # 0
(10, 23, 15, 8, 3, 0, 9, 20, 13, 21, 4, 0), # 1
(15, 31, 24, 10, 5, 0, 15, 29, 18, 25, 7, 0), # 2
(22, 40, 37, 13, 8, 0, 22, 43, 23, 34, 9, 0), # 3
(26, 54, 48, 17, 8, 0, 26, 52, 32, 46, 13, 0), # 4
(29, 63, 57, 26, 11, 0, 36, 63, 37, 51, 15, 0), # 5
(38, 71, 67, 28, 11, 0, 44, 72, 41, 56, 16, 0), # 6
(43, 82, 72, 30, 14, 0, 50, 81, 50, 59, 17, 0), # 7
(45, 90, 77, 36, 15, 0, 57, 100, 56, 61, 21, 0), # 8
(51, 105, 83, 38, 23, 0, 67, 108, 63, 66, 24, 0), # 9
(56, 111, 93, 41, 25, 0, 74, 118, 71, 74, 28, 0), # 10
(61, 122, 101, 46, 25, 0, 82, 124, 74, 81, 28, 0), # 11
(63, 134, 115, 50, 29, 0, 88, 131, 77, 90, 32, 0), # 12
(67, 146, 122, 56, 34, 0, 103, 146, 81, 92, 37, 0), # 13
(70, 158, 129, 62, 39, 0, 111, 158, 86, 101, 41, 0), # 14
(74, 175, 139, 63, 44, 0, 122, 167, 95, 110, 44, 0), # 15
(82, 187, 146, 67, 46, 0, 128, 181, 100, 117, 50, 0), # 16
(89, 197, 156, 70, 48, 0, 137, 199, 108, 124, 54, 0), # 17
(92, 203, 167, 73, 55, 0, 146, 211, 114, 128, 54, 0), # 18
(101, 218, 179, 81, 57, 0, 159, 227, 121, 138, 57, 0), # 19
(105, 236, 185, 90, 62, 0, 172, 233, 127, 145, 60, 0), # 20
(111, 248, 192, 94, 65, 0, 177, 240, 135, 150, 64, 0), # 21
(122, 255, 203, 102, 70, 0, 190, 248, 147, 154, 66, 0), # 22
(129, 270, 216, 104, 71, 0, 197, 257, 153, 164, 70, 0), # 23
(137, 278, 225, 108, 74, 0, 204, 270, 162, 169, 71, 0), # 24
(142, 296, 235, 113, 78, 0, 212, 284, 170, 178, 71, 0), # 25
(144, 308, 245, 117, 80, 0, 227, 297, 179, 189, 72, 0), # 26
(149, 315, 256, 124, 80, 0, 235, 307, 187, 192, 73, 0), # 27
(155, 330, 272, 126, 83, 0, 240, 317, 194, 200, 74, 0), # 28
(161, 338, 280, 130, 84, 0, 247, 324, 196, 207, 78, 0), # 29
(165, 351, 292, 134, 85, 0, 253, 339, 205, 216, 81, 0), # 30
(171, 362, 303, 138, 87, 0, 261, 356, 216, 222, 84, 0), # 31
(175, 381, 308, 145, 89, 0, 265, 373, 222, 228, 85, 0), # 32
(178, 396, 317, 151, 92, 0, 271, 387, 228, 231, 90, 0), # 33
(184, 407, 323, 157, 92, 0, 282, 398, 235, 239, 94, 0), # 34
(191, 415, 327, 161, 98, 0, 290, 409, 241, 243, 97, 0), # 35
(195, 425, 342, 164, 101, 0, 296, 417, 248, 248, 100, 0), # 36
(197, 433, 343, 174, 104, 0, 306, 430, 251, 250, 102, 0), # 37
(202, 443, 352, 178, 107, 0, 315, 437, 257, 259, 103, 0), # 38
(207, 455, 357, 183, 107, 0, 323, 445, 269, 262, 108, 0), # 39
(211, 465, 371, 188, 109, 0, 331, 456, 277, 264, 113, 0), # 40
(216, 478, 380, 191, 110, 0, 336, 465, 284, 270, 116, 0), # 41
(223, 490, 388, 199, 113, 0, 345, 478, 293, 280, 118, 0), # 42
(232, 503, 398, 208, 113, 0, 352, 490, 300, 287, 119, 0), # 43
(233, 519, 411, 213, 115, 0, 362, 504, 310, 292, 121, 0), # 44
(239, 533, 425, 220, 117, 0, 371, 518, 316, 298, 126, 0), # 45
(243, 551, 433, 228, 119, 0, 388, 530, 325, 308, 129, 0), # 46
(253, 563, 439, 230, 122, 0, 397, 538, 330, 312, 136, 0), # 47
(257, 574, 443, 239, 123, 0, 405, 552, 337, 322, 136, 0), # 48
(263, 587, 450, 243, 126, 0, 413, 561, 343, 325, 140, 0), # 49
(272, 601, 458, 249, 130, 0, 420, 567, 349, 328, 143, 0), # 50
(275, 612, 466, 255, 133, 0, 429, 580, 354, 335, 145, 0), # 51
(281, 624, 477, 257, 135, 0, 432, 590, 360, 345, 148, 0), # 52
(290, 640, 486, 262, 136, 0, 437, 601, 373, 350, 150, 0), # 53
(296, 654, 499, 265, 139, 0, 442, 611, 383, 358, 154, 0), # 54
(298, 667, 505, 268, 143, 0, 449, 618, 390, 364, 155, 0), # 55
(302, 681, 513, 274, 144, 0, 455, 632, 398, 370, 158, 0), # 56
(307, 690, 520, 277, 147, 0, 461, 644, 405, 379, 160, 0), # 57
(310, 699, 529, 281, 151, 0, 466, 658, 412, 384, 163, 0), # 58
(310, 699, 529, 281, 151, 0, 466, 658, 412, 384, 163, 0), # 59
)
passenger_arriving_rate = (
(4.769372805092186, 9.786903409090908, 8.63377490359897, 4.56211956521739, 2.5714903846153843, 0.0, 8.562228260869567, 10.285961538461537, 6.843179347826086, 5.755849935732647, 2.446725852272727, 0.0), # 0
(4.81413961808604, 9.895739902146465, 8.680408780526994, 4.587526358695651, 2.5907639423076922, 0.0, 8.559309850543478, 10.363055769230769, 6.881289538043478, 5.786939187017995, 2.4739349755366162, 0.0), # 1
(4.8583952589991215, 10.00296202020202, 8.725935732647814, 4.612373913043478, 2.609630769230769, 0.0, 8.556302173913043, 10.438523076923076, 6.918560869565217, 5.817290488431875, 2.500740505050505, 0.0), # 2
(4.902102161984196, 10.1084540625, 8.770322501606683, 4.636641032608694, 2.628073557692308, 0.0, 8.553205638586958, 10.512294230769232, 6.954961548913042, 5.846881667737789, 2.527113515625, 0.0), # 3
(4.94522276119403, 10.212100328282828, 8.813535829048842, 4.66030652173913, 2.6460749999999997, 0.0, 8.550020652173911, 10.584299999999999, 6.990459782608696, 5.875690552699228, 2.553025082070707, 0.0), # 4
(4.987719490781387, 10.313785116792928, 8.855542456619537, 4.6833491847826085, 2.663617788461538, 0.0, 8.546747622282608, 10.654471153846153, 7.025023777173913, 5.90369497107969, 2.578446279198232, 0.0), # 5
(5.029554784899035, 10.413392727272727, 8.896309125964011, 4.705747826086957, 2.680684615384615, 0.0, 8.54338695652174, 10.72273846153846, 7.058621739130436, 5.930872750642674, 2.603348181818182, 0.0), # 6
(5.0706910776997365, 10.510807458964646, 8.935802578727506, 4.72748125, 2.697258173076923, 0.0, 8.5399390625, 10.789032692307693, 7.0912218750000005, 5.95720171915167, 2.6277018647411614, 0.0), # 7
(5.1110908033362605, 10.60591361111111, 8.97398955655527, 4.7485282608695645, 2.7133211538461537, 0.0, 8.536404347826087, 10.853284615384615, 7.122792391304347, 5.982659704370181, 2.6514784027777774, 0.0), # 8
(5.1507163959613695, 10.698595482954543, 9.010836801092546, 4.768867663043478, 2.7288562499999993, 0.0, 8.532783220108696, 10.915424999999997, 7.153301494565217, 6.007224534061697, 2.6746488707386358, 0.0), # 9
(5.1895302897278315, 10.788737373737373, 9.046311053984574, 4.7884782608695655, 2.743846153846154, 0.0, 8.529076086956522, 10.975384615384616, 7.182717391304348, 6.030874035989716, 2.697184343434343, 0.0), # 10
(5.227494918788412, 10.87622358270202, 9.080379056876605, 4.807338858695652, 2.7582735576923074, 0.0, 8.525283355978262, 11.03309423076923, 7.2110082880434785, 6.053586037917737, 2.719055895675505, 0.0), # 11
(5.2645727172958745, 10.960938409090907, 9.113007551413881, 4.825428260869565, 2.7721211538461534, 0.0, 8.521405434782608, 11.088484615384614, 7.238142391304347, 6.0753383676092545, 2.740234602272727, 0.0), # 12
(5.3007261194029835, 11.042766152146465, 9.144163279241644, 4.8427252717391305, 2.7853716346153847, 0.0, 8.51744273097826, 11.141486538461539, 7.264087907608696, 6.096108852827762, 2.760691538036616, 0.0), # 13
(5.335917559262511, 11.121591111111112, 9.173812982005138, 4.859208695652173, 2.7980076923076918, 0.0, 8.513395652173912, 11.192030769230767, 7.288813043478259, 6.115875321336759, 2.780397777777778, 0.0), # 14
(5.370109471027217, 11.19729758522727, 9.201923401349612, 4.874857336956521, 2.810012019230769, 0.0, 8.509264605978261, 11.240048076923076, 7.312286005434782, 6.134615600899742, 2.7993243963068175, 0.0), # 15
(5.403264288849868, 11.269769873737372, 9.228461278920308, 4.88965, 2.8213673076923076, 0.0, 8.50505, 11.28546923076923, 7.334474999999999, 6.152307519280206, 2.817442468434343, 0.0), # 16
(5.4353444468832315, 11.338892275883836, 9.253393356362468, 4.903565489130434, 2.83205625, 0.0, 8.500752241847827, 11.328225, 7.3553482336956515, 6.168928904241644, 2.834723068970959, 0.0), # 17
(5.46631237928007, 11.40454909090909, 9.276686375321336, 4.916582608695652, 2.842061538461539, 0.0, 8.496371739130435, 11.368246153846156, 7.374873913043479, 6.184457583547558, 2.8511372727272724, 0.0), # 18
(5.496130520193152, 11.466624618055553, 9.298307077442159, 4.928680163043477, 2.8513658653846155, 0.0, 8.491908899456522, 11.405463461538462, 7.393020244565217, 6.198871384961439, 2.866656154513888, 0.0), # 19
(5.524761303775241, 11.525003156565655, 9.318222204370178, 4.939836956521739, 2.859951923076923, 0.0, 8.487364130434782, 11.439807692307692, 7.409755434782609, 6.212148136246785, 2.8812507891414136, 0.0), # 20
(5.552167164179106, 11.579569005681815, 9.336398497750643, 4.95003179347826, 2.8678024038461536, 0.0, 8.482737839673913, 11.471209615384614, 7.425047690217391, 6.224265665167096, 2.894892251420454, 0.0), # 21
(5.578310535557506, 11.630206464646465, 9.352802699228791, 4.95924347826087, 2.8748999999999993, 0.0, 8.47803043478261, 11.499599999999997, 7.438865217391305, 6.235201799485861, 2.907551616161616, 0.0), # 22
(5.603153852063214, 11.67679983270202, 9.367401550449872, 4.967450815217391, 2.8812274038461534, 0.0, 8.473242323369567, 11.524909615384614, 7.451176222826087, 6.244934366966581, 2.919199958175505, 0.0), # 23
(5.62665954784899, 11.719233409090908, 9.380161793059125, 4.974632608695652, 2.8867673076923075, 0.0, 8.468373913043479, 11.54706923076923, 7.461948913043478, 6.25344119537275, 2.929808352272727, 0.0), # 24
(5.648790057067603, 11.757391493055556, 9.391050168701799, 4.980767663043478, 2.8915024038461534, 0.0, 8.463425611413044, 11.566009615384614, 7.471151494565217, 6.260700112467866, 2.939347873263889, 0.0), # 25
(5.669507813871817, 11.79115838383838, 9.400033419023135, 4.985834782608695, 2.8954153846153843, 0.0, 8.458397826086957, 11.581661538461537, 7.478752173913043, 6.266688946015424, 2.947789595959595, 0.0), # 26
(5.688775252414398, 11.820418380681815, 9.40707828566838, 4.989812771739131, 2.8984889423076923, 0.0, 8.453290964673915, 11.593955769230769, 7.484719157608696, 6.271385523778919, 2.9551045951704538, 0.0), # 27
(5.7065548068481124, 11.84505578282828, 9.412151510282778, 4.992680434782609, 2.9007057692307687, 0.0, 8.448105434782608, 11.602823076923075, 7.489020652173913, 6.274767673521851, 2.96126394570707, 0.0), # 28
(5.722808911325724, 11.864954889520202, 9.415219834511568, 4.994416576086956, 2.902048557692307, 0.0, 8.44284164402174, 11.608194230769229, 7.491624864130435, 6.276813223007712, 2.9662387223800506, 0.0), # 29
(5.7375, 11.879999999999999, 9.41625, 4.995, 2.9025, 0.0, 8.4375, 11.61, 7.4925, 6.277499999999999, 2.9699999999999998, 0.0), # 30
(5.751246651214834, 11.892497471590906, 9.415477744565216, 4.994894632352941, 2.9023357180851064, 0.0, 8.430077267616193, 11.609342872340426, 7.492341948529411, 6.276985163043476, 2.9731243678977264, 0.0), # 31
(5.7646965153452685, 11.904829772727274, 9.413182826086956, 4.994580588235293, 2.901846382978723, 0.0, 8.418644565217393, 11.607385531914892, 7.49187088235294, 6.275455217391303, 2.9762074431818184, 0.0), # 32
(5.777855634590792, 11.916995369318181, 9.40939801630435, 4.994060955882353, 2.9010372606382977, 0.0, 8.403313830584706, 11.60414904255319, 7.491091433823529, 6.272932010869566, 2.9792488423295453, 0.0), # 33
(5.790730051150895, 11.928992727272727, 9.40415608695652, 4.993338823529412, 2.899913617021276, 0.0, 8.38419700149925, 11.599654468085104, 7.490008235294118, 6.269437391304347, 2.9822481818181816, 0.0), # 34
(5.803325807225064, 11.940820312499996, 9.39748980978261, 4.9924172794117645, 2.898480718085106, 0.0, 8.361406015742128, 11.593922872340425, 7.488625919117647, 6.264993206521739, 2.985205078124999, 0.0), # 35
(5.815648945012788, 11.952476590909091, 9.389431956521738, 4.9912994117647065, 2.896743829787234, 0.0, 8.335052811094453, 11.586975319148936, 7.486949117647059, 6.259621304347825, 2.988119147727273, 0.0), # 36
(5.8277055067135555, 11.96396002840909, 9.380015298913044, 4.989988308823529, 2.8947082180851056, 0.0, 8.305249325337332, 11.578832872340422, 7.484982463235293, 6.253343532608695, 2.9909900071022726, 0.0), # 37
(5.839501534526853, 11.97526909090909, 9.369272608695653, 4.988487058823529, 2.89237914893617, 0.0, 8.272107496251873, 11.56951659574468, 7.4827305882352935, 6.246181739130434, 2.9938172727272727, 0.0), # 38
(5.851043070652174, 11.986402244318182, 9.357236657608695, 4.98679875, 2.8897618882978717, 0.0, 8.23573926161919, 11.559047553191487, 7.480198125, 6.23815777173913, 2.9966005610795454, 0.0), # 39
(5.862336157289003, 11.997357954545455, 9.343940217391305, 4.984926470588235, 2.886861702127659, 0.0, 8.196256559220389, 11.547446808510635, 7.477389705882353, 6.22929347826087, 2.999339488636364, 0.0), # 40
(5.873386836636828, 12.008134687499997, 9.329416059782607, 4.982873308823529, 2.8836838563829783, 0.0, 8.153771326836583, 11.534735425531913, 7.474309963235294, 6.219610706521738, 3.002033671874999, 0.0), # 41
(5.88420115089514, 12.01873090909091, 9.31369695652174, 4.980642352941176, 2.880233617021277, 0.0, 8.108395502248875, 11.520934468085107, 7.4709635294117644, 6.209131304347826, 3.0046827272727277, 0.0), # 42
(5.894785142263428, 12.02914508522727, 9.296815679347825, 4.978236691176471, 2.8765162499999994, 0.0, 8.060241023238381, 11.506064999999998, 7.467355036764706, 6.1978771195652165, 3.0072862713068176, 0.0), # 43
(5.905144852941176, 12.03937568181818, 9.278805, 4.975659411764705, 2.8725370212765955, 0.0, 8.009419827586207, 11.490148085106382, 7.4634891176470575, 6.1858699999999995, 3.009843920454545, 0.0), # 44
(5.915286325127877, 12.049421164772726, 9.259697690217394, 4.972913602941176, 2.8683011968085106, 0.0, 7.956043853073464, 11.473204787234042, 7.459370404411764, 6.1731317934782615, 3.0123552911931815, 0.0), # 45
(5.925215601023019, 12.059280000000001, 9.239526521739132, 4.970002352941176, 2.8638140425531913, 0.0, 7.90022503748126, 11.455256170212765, 7.455003529411765, 6.159684347826087, 3.0148200000000003, 0.0), # 46
(5.934938722826087, 12.06895065340909, 9.218324266304347, 4.966928749999999, 2.859080824468085, 0.0, 7.842075318590705, 11.43632329787234, 7.450393124999999, 6.145549510869564, 3.0172376633522724, 0.0), # 47
(5.944461732736574, 12.07843159090909, 9.196123695652174, 4.9636958823529405, 2.854106808510638, 0.0, 7.7817066341829095, 11.416427234042551, 7.445543823529412, 6.130749130434782, 3.0196078977272727, 0.0), # 48
(5.953790672953963, 12.087721278409088, 9.17295758152174, 4.960306838235294, 2.8488972606382976, 0.0, 7.71923092203898, 11.39558904255319, 7.4404602573529415, 6.115305054347826, 3.021930319602272, 0.0), # 49
(5.96293158567775, 12.096818181818177, 9.148858695652175, 4.956764705882353, 2.8434574468085105, 0.0, 7.65476011994003, 11.373829787234042, 7.43514705882353, 6.099239130434783, 3.0242045454545443, 0.0), # 50
(5.971890513107417, 12.105720767045453, 9.123859809782608, 4.953072573529411, 2.837792632978723, 0.0, 7.588406165667167, 11.351170531914892, 7.429608860294118, 6.082573206521738, 3.026430191761363, 0.0), # 51
(5.980673497442456, 12.114427499999998, 9.097993695652173, 4.949233529411764, 2.8319080851063827, 0.0, 7.5202809970015, 11.32763234042553, 7.4238502941176465, 6.065329130434781, 3.0286068749999995, 0.0), # 52
(5.989286580882353, 12.122936846590909, 9.071293125, 4.945250661764706, 2.8258090691489364, 0.0, 7.450496551724138, 11.303236276595745, 7.417875992647058, 6.04752875, 3.030734211647727, 0.0), # 53
(5.9977358056266, 12.13124727272727, 9.043790869565216, 4.941127058823529, 2.8195008510638297, 0.0, 7.379164767616192, 11.278003404255319, 7.411690588235294, 6.0291939130434775, 3.0328118181818176, 0.0), # 54
(6.00602721387468, 12.139357244318182, 9.015519701086955, 4.93686580882353, 2.8129886968085103, 0.0, 7.306397582458771, 11.251954787234041, 7.405298713235295, 6.010346467391304, 3.0348393110795455, 0.0), # 55
(6.014166847826087, 12.147265227272724, 8.986512391304348, 4.9324699999999995, 2.8062778723404254, 0.0, 7.232306934032984, 11.225111489361701, 7.398705, 5.991008260869565, 3.036816306818181, 0.0), # 56
(6.022160749680308, 12.154969687500001, 8.95680171195652, 4.927942720588234, 2.7993736436170207, 0.0, 7.15700476011994, 11.197494574468083, 7.391914080882352, 5.9712011413043475, 3.0387424218750003, 0.0), # 57
(6.030014961636829, 12.16246909090909, 8.926420434782608, 4.923287058823529, 2.792281276595744, 0.0, 7.0806029985007495, 11.169125106382976, 7.384930588235295, 5.950946956521738, 3.0406172727272724, 0.0), # 58
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59
)
passenger_allighting_rate = (
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 0
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 1
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 2
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 3
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 4
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 5
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 6
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 7
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 8
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 9
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 10
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 11
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 12
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 13
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 14
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 15
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 16
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 17
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 18
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 19
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 20
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 21
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 22
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 23
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 24
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 25
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 26
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 27
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 28
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 29
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 30
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 31
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 32
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 33
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 34
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 35
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 36
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 37
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 38
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 39
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 40
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 41
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 42
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 43
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 44
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 45
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 46
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 47
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 48
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 49
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 50
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 51
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 52
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 53
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 54
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 55
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 56
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 57
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 58
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 59
)
"""
parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html
"""
#initial entropy
entropy = 258194110137029475889902652135037600173
#index for seed sequence child
child_seed_index = (
1, # 0
92, # 1
)
|
'''
Exercise 1:
Rewrite your pay computation to give the employee 1.5 times\
the hourly rate for hours worked above 40 hours.
----Example:
Enter Hours: 45
Enter Rate: 10
Pay: 475.0
Note: (40*10 + 5*10*1.5 = 475.0)
'''
hours = int(input('Enter Hours: '))
rate = float(input('Enter Rate: '))
if(hours>40):
pay = (40 + (hours-40) * 1.5) * rate
else:
pay = 40 * rate
print('Pay:', pay)
|
"""
{{ cookiecutter.project_short_description }}.
"""
__version__ = '{{ cookiecutter.version }}'
|
# -*- coding: utf-8 -*-
print ("O texto será ecoado na tela")
# O input() é usado somente para entrada de strings
# Caso seja digitado um numero, o mesmo será do tipo string
numero = input("Digite um numero: ")
texto = input("Digite um texto: ")
print(type(numero))
print(type(texto)) |
l = []
o = 0
i = 0
maior = menor = 0
for c in range(0,5):
n = int(input('Digite seu numero'))
if o == 0:
l.append(n)
o = 1
if o == 1:
maior = menor = n
o = 2
else:
if maior < n:
maior = n
l.append(n)
print('Seu numero foi adicionado no final da lista')
elif menor > n:
menor = n
l.insert(0, n)
print('Seu numero foi adicionado no começo da lista')
elif maior == n:
l.insert(l.index(n), n)
elif menor == n:
l.insert(l.index(n), n)
else:
h = 0
for y in range(0,len(l)):
if l[y] > n and h == 0:
i = l.index(l[y])
print(f'Seu numero foi adicionado na posição {l.index(l[y])}')
if l[y-1] != l[y]:
h = 1
l.insert(i, n)
print('=-'*20)
print(f'Sua lista foi {l}')
|
# !/usr/bin/env python
# -*-coding:utf-8 -*-
# Warning :The Hard Way Is Easier
"""
=================================================================================
【流水线】
=================================================================================
"""
def Solution(ori: list, k: int):
return
if __name__ == '__main__':
s = [5, 1, 1, 2, 2, 2]
print(Solution(s, k=2))
s = [5, 1, 1, 2, 2, 2, 4, 4, 5, 5, 1, 2, ]
print(Solution(s, 7))
|
# small filters to manupulate lists
class FilterModule(object):
# given a flat list (or tuple, or set), return a deduplicated list, i.e.,
# a list in which each unique item in the src list only occurs once
@staticmethod
def _uniq(src):
return list(set(src))
# given a list of list (e.g., [[a,b,c],[c,d,e],[e,f,g]]) return a flat
# list [a,b,c,c,d,e,e,f,g]
@staticmethod
def _flatten(src):
return [ item for sublist in src for item in sublist ]
def filters(self):
return {
'uniq': self._uniq,
'flatten': self._flatten,
}
|
def parse_like_term(term):
if term.startswith('^'):
stmt = '%s%%' % term[1:]
elif term.startswith('='):
stmt = term[1:]
else:
stmt = '%%%s%%' % term
return stmt
def get_primary_key(model):
"""
Return primary key name from a model
:param model:
Model class
"""
props = model._sa_class_manager.mapper.iterate_properties
for p in props:
if hasattr(p, 'columns'):
for c in p.columns:
if c.primary_key:
return p.key
return None
|
def bubble_sort(lst):
for passnum in range(len(lst) - 1, 0, -1):
for i in range(passnum):
if lst[i] > lst[i + 1]:
lst[i], lst[i + 1] = lst[i + 1], lst[i]
|
# -*- coding: utf-8 -*-
# Copyright (c) 2016-2017, Zhijiang Yao, Jie Dong and Dongsheng Cao
# All rights reserved.
# This file is part of the PyBioMed.
# The contents are covered by the terms of the BSD license
# which is included in the file license.txt, found at the root
# of the PyBioMed source tree.
"""
#####################################################################################
This module is used for checking whether the input protein sequence is valid amino acid
sequence. You can freely use and distribute it. If you hava any problem, you could
contact with us timely!
Authors: Zhijiang Yao and Dongsheng Cao.
Date: 2016.06.04
Email: gadsby@163.com
#####################################################################################
"""
AALetter = ["A", "R", "N", "D", "C", "E", "Q", "G", "H", "I", "L", "K", "M", "F", "P", "S", "T", "W", "Y", "V"]
def ProteinCheck(ProteinSequence):
"""
###################################################################################
Check whether the protein sequence is a valid amino acid sequence or not
Usage:
result=ProteinCheck(protein)
Input: protein is a pure protein sequence.
Output: if the check is no problem, result will return the length of protein.
if the check has problems, result will return 0.
###################################################################################
"""
NumPro = len(ProteinSequence)
for i in ProteinSequence:
if i not in AALetter:
flag = 0
break
else:
flag = NumPro
return flag
if __name__ == "__main__":
protein = "ADGCGVGEGTGQGPMCNCMCMKWVYADEDAADLESDSFADEDASLESDSFPWSNQRVFCSFADEDASU"
protein = "ADGC"
print(ProteinCheck(protein))
|
print('First Program!')
print('What is your name?')
my_Name = input()
print ('')
print ('Your names is: ' + my_Name )
|
# Description
# 中文
# English
# Given an input string, reverse the string word by word.
# Have you met this question in a real interview?
# Clarification
# What constitutes a word?
# A sequence of non-space characters constitutes a word and some words have punctuation at the end.
# Could the input string contain leading or trailing spaces?
# Yes. However, your reversed string should not contain leading or trailing spaces.
# How about multiple spaces between two words?
# Reduce them to a single space in the reversed string.
# Example
# Example 1:
# Input: "the sky is blue"
# Output: "blue is sky the"
# Explanation:
# return a reverse the string word by word.
# Example 2:
# Input: "hello world"
# Output: "world hello"
# Explanation:
# return a reverse the string word by word.
class Solution:
"""
@param: s: A string
@return: A string
"""
def reverseWords(self, s):
# write your code here
list_s = s.split()
list_s.reverse()
result = ' '.join(list_s)
return result
# 本参考程序来自九章算法,由 @九章算法 提供。版权所有,转发请注明出处。
# - 九章算法致力于帮助更多中国人找到好的工作,教师团队均来自硅谷和国内的一线大公司在职工程师。
# - 现有的面试培训课程包括:九章算法班,系统设计班,算法强化班,Java入门与基础算法班,Android 项目实战班,
# - Big Data 项目实战班,算法面试高频题班, 动态规划专题班
# - 更多详情请见官方网站:http://www.jiuzhang.com/?source=code
class Solution:
# @param s : A string
# @return : A string
def reverseWords(self, s):
# strip()去掉s头尾的空格,split()按照空格分割字符串,reversed翻转,''.join按照空格连接字符串
return ' '.join(reversed(s.strip().split()))
|
# input
with open('input.txt') as f:
lines = f.readlines()
# part 1
def process_line(mask, value):
output = ['0'] * 36
binval = bin(value)[2:]
for ii in range(len(binval)):
output[len(output)-1-ii] = binval[len(binval)-1-ii]
for ii in range(len(mask)):
if mask[ii] != 'X':
output[ii] = mask[ii]
return int(''.join(output), 2)
memory = {}
for line in lines:
items = line.strip().split(' = ')
if items[0] == 'mask':
mask = items[1]
else:
key = int(items[0].strip('mem[]'))
inval = int(items[1])
memory[key] = process_line(mask, inval)
ans1 = sum(memory.values())
# part 2
def decode(mask, value):
output = ['0'] * 36
binval = bin(value)[2:]
for ii in range(len(binval)):
output[len(output)-1-ii] = binval[len(binval)-1-ii]
for ii in range(len(mask)):
if mask[ii] != '0':
output[ii] = mask[ii]
return floating(output)
def floating(value):
if 'X' in value:
value_0 = value.copy()
value_1 = value.copy()
value_0[value.index('X')] = '0'
value_1[value.index('X')] = '1'
return floating(value_0) + floating(value_1)
return [int(''.join(value), 2)]
memory = {}
for line in lines:
items = line.strip().split(' = ')
if items[0] == 'mask':
mask = items[1]
else:
inkey = int(items[0].strip('mem[]'))
val = int(items[1])
keys = decode(mask, inkey)
for key in keys:
memory[key] = val
ans2 = sum(memory.values())
# output
answer = []
answer.append('Part 1: {}'.format(ans1))
answer.append('Part 2: {}'.format(ans2))
with open('solution.txt', 'w') as f:
f.writelines('\n'.join(answer)+'\n')
|
class GridOutOfBoundsException(Exception):
pass
class GridGenerateException(Exception):
pass
class InvalidDimensionsException(Exception):
pass |
def de_casteljau(t, coefs):
beta = [c for c in coefs] # values in this list are overridden
n = len(beta)
for j in range(1, n):
for k in range(n - j):
beta[k] = beta[k] * (1 - t) + beta[k + 1] * t
return beta[0];
P1 = [-20,0,-11]
P2 = [-10,0,-5]
P3 = [10,0,-5]
P4 = [20,0,-11]
coefs_x = [P1[0],P2[0],P3[0],P4[0]]
coefs_y = [P1[1],P2[1],P3[1],P4[1]]
coefs_z = [P1[2],P2[2],P3[2],P4[2]]
beta = coefs_x
print('x =' + str(de_casteljau(0.7, coefs_x)))
print('y =' + str(de_casteljau(0.7, coefs_y)))
print('z =' + str(de_casteljau(0.7, coefs_z)))
|
def author(name):
def wrapper(func):
func.author = name
return func
return wrapper
@author("Author")
def add2(num: int) -> int:
return num + 2
print(add2.author)
|
# TODO: Extract Class
"""
The Extract class will support data transformations and will be subclassed to allow for data to be transformed in
more complex ways.
The Extract feature should have support to be placed ANYWHERE within the ApiForm and should follow a pub-sub type model
I.e. Extract allows for real-time summaries and features to be extracted from the data.
pre_process = [
.
.
SubclassExtractFeaturePublishLatLong( subpub_model="firestore",
lam=lamdba x: [ x["data"]["lat"], x["data"]["long"] ],
mode="summary",
fmt_str="New data has been received with coordinates Lat: {} Long: {}"
)
.
.
]
stores = [
.
.
SubclassExtractFeatureSummarizeAverage( subpub_model="redis",
lam=lambda x: .
.
.
)
]
"""
class Extract(object):
def __init__(self):
pass
|
class Channel():
""" setup legs and feet to correspond to the correct channel """
LEFT_LEG_FRONT = 0 # channel 0
LEFT_LEG_BACK = 1 # channel 2
RIGHT_LEG_FRONT = 2 # channel 6
RIGHT_LEG_BACK = 3 # channel 4
LEFT_FOOT_FRONT = 0 # channel 1
LEFT_FOOT_BACK = 1 # channel 3
RIGHT_FOOT_FRONT = 2 # channel 7
RIGHT_FOOT_BACK = 3 # channel 5 |
# Definition for a binary tree node.
# class TreeNode(object):
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution(object):
def sortedArrayToBST(self, nums):
"""
:type nums: List[int]
:rtype: TreeNode
"""
return self.sortedArrayToBSTHelper(nums, 0, len(nums) - 1)
def sortedArrayToBSTHelper(self, nums, left, right):
if left > right:
return None
rootIdx = (left + right) // 2
root = TreeNode(nums[rootIdx])
root.left = self.sortedArrayToBSTHelper(nums, left, rootIdx - 1)
root.right = self.sortedArrayToBSTHelper(nums, rootIdx + 1, right)
return root
|
# encoding: utf-8
# module Tekla.Structures.Filtering.Categories calls itself Categories
# from Tekla.Structures, Version=2017.0.0.0, Culture=neutral, PublicKeyToken=2f04dbe497b71114
# by generator 1.145
# no doc
# no imports
# no functions
# classes
class AssemblyFilterExpressions(object):
# no doc
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Guid = None
IdNumber = None
Level = None
Name = None
Phase = None
PositionNumber = None
Prefix = None
Series = None
StartNumber = None
Type = None
class BoltFilterExpressions(object):
# no doc
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Length = None
Phase = None
SiteWorkshop = None
Size = None
Standard = None
class ComponentFilterExpressions(object):
# no doc
ConnectionCode = None
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Name = None
Phase = None
RunningNumber = None
class LoadFilterExpressions(object):
# no doc
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Group = None
Phase = None
Type = None
class LogicalAreaFilterExpressions(object):
# no doc
Building = None
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Section = None
Site = None
Story = None
class ObjectFilterExpressions(object):
# no doc
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Guid = None
IdNumber = None
IsComponent = None
Phase = None
Type = None
class ObjectTypesFilterExpressions(object):
# no doc
CategoryName = None
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
EntityName = None
class PartFilterExpressions(object):
# no doc
Class = None
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Finish = None
Lot = None
Material = None
Name = None
NumberingSeries = None
Phase = None
PositionNumber = None
Prefix = None
PrimaryPart = None
Profile = None
StartNumber = None
class ReferenceObjectFilterExpressions(object):
# no doc
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
class ReinforcingBarFilterExpressions(object):
# no doc
Class = None
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Diameter = None
JoinType = None
Length = None
Material = None
Name = None
NumberingSeries = None
Phase = None
Position = None
PositionNumber = None
Prefix = None
Shape = None
Size = None
StartNumber = None
class TaskFilterExpressions(object):
# no doc
ActualEndDate = None
ActualStartDate = None
Completeness = None
Critical = None
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Local = None
Name = None
PlannedEndDate = None
PlannedStartDate = None
class TemplateFilterExpressions(object):
# no doc
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
class WeldFilterExpressions(object):
# no doc
CustomBoolean = None
CustomDateTime = None
CustomNumber = None
CustomString = None
Phase = None
PositionNumber = None
ReferenceText = None
SizeAboveLine = None
SizeBelowLine = None
TypeAboveLine = None
TypeBelowLine = None
WeldingSite = None
|
reverse_list = []
def reverse_number(numbers):
for i in range(1,len(numbers)+1):
num = numbers.pop()
reverse_list.append(num)
print(reverse_list)
numbers = list(range(1,21))
print(numbers)
reverse_number(numbers)
|
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
def load_framework_dependencies():
http_archive(
name = "TensorFlowLiteC",
url = "https://dl.google.com/dl/cpdc/3895e5bf508673ae/TensorFlowLiteC-2.6.0.tar.gz",
sha256 = "a28ce764da496830c0a145b46e5403fb486b5b6231c72337aaa8eaf3d762cc8d",
build_file = "@//tests/ios/unit-test/test-imports-app:BUILD.TensorFlowLiteC",
strip_prefix = "TensorFlowLiteC-2.6.0",
)
http_archive(
name = "GoogleMobileAdsSDK",
url = "https://dl.google.com/dl/cpdc/e0dda986a9f84d14/Google-Mobile-Ads-SDK-8.10.0.tar.gz",
sha256 = "0726df5d92165912c9e60a79504a159ad9b7231dda851abede8f8792b266dba5",
build_file = "@//tests/ios/unit-test/test-imports-app:BUILD.GoogleMobileAds",
)
|
def initials(name):
names = name.title().split()
length = len(names) - 1
return '.'.join(a[0] if length != i else a for i, a in enumerate(names))
|
"""
Perfil do Usuário: Comece com uma cópia de user_profile.py, da página 210. Crie
um perfil seu chamado build_profile(), usndo seu primeiro nome e o sobrenome,
além de três outros pares chave_valor que o descrevam.
"""
def build_profile(first, last, **user_info):
"""Constrói um dicionário contendo tudo que sabemos sobre um usuário."""
profile = {}
profile['first_name'] = first
profile['last_name'] = last
for key, value in user_info.items():
profile[key] = value
return profile
user_profile = build_profile('Roberto', 'Monteiro', Profissão = 'Engenheiro Civil', Idade = 42, Estado_Civil = 'Casado')
for key, value in user_profile.items():
print(f'{key}: {value}') |
class Infinite_memory(list):
def __init__(self,*args):
list.__init__(self,*args)
def __getitem__(self, index):
if index>=len(self):
for _ in range((index-len(self))+1):
self.append(0)
return super().__getitem__(index)
def __setitem__(self, key, value):
if key>=len(self):
for _ in range((key-len(self))+1):
self.append(0)
return super().__setitem__(key, value)
def run_intcode(memory,input_stream=None,output_l=None):
global relative_base
relative_base=0
def suma(args):
memory[args[2]]=args[0]+args[1]
def mult(args):
memory[args[2]]=args[0]*args[1]
def inpt(args):
if input_stream:
memory[args[0]]=input_stream.pop(0)
else:
memory[args[0]]=int(input("escribe un numero, puto (1 para parte 1 2 para parte 2):"))
def output(args):
if output_l==None:
print(args[0])
else:
output_l.append(args[0])
def j_if_t(args):
if args[0]!=0:
return args[1]
def j_if_f(args):
if args[0]==0:
return args[1]
def less_than(args):
memory[args[2]]=int(args[0]<args[1])
def equals(args):
memory[args[2]]=int(args[0]==args[1])
def inc_rel_base(args):
global relative_base
relative_base+=args[0]
func_dict={1:suma,2:mult,3:inpt,4:output,5:j_if_t,6:j_if_f,7:less_than,8:equals,9:inc_rel_base}
writes_to_mem=[1,2,3,7,8]#instructions that write to memory
inc_dict={1:4,2:4,3:2,4:2,5:3,6:3,7:4,8:4,9:2}
i=0
while True:
opcode=str(memory[i])
param_bits=list(opcode[:-2])
opcode=int(opcode[-2:])
if opcode==99:
break
params=[]
for p in range(1,inc_dict[opcode]):
bit=0
if len(param_bits)>0:
bit=int(param_bits.pop())
if bit==2:
if (p==inc_dict[opcode]-1 and opcode in writes_to_mem): #write relative
params.append(relative_base+memory[i+p])
else: #read relative
params.append(memory[relative_base+memory[i+p]])
elif (p==inc_dict[opcode]-1 and opcode in writes_to_mem) or (bit==1): #read immediate or write positional
params.append(memory[i+p])
else: #default read positional
params.append(memory[memory[i+p]])
instruction=func_dict[opcode](params)
if instruction:
i=instruction
else:
i+=inc_dict[opcode]
with open("input1.txt","r") as f:
code=Infinite_memory(map(int,f.readline().split(",")))
out=[]
run_intcode(code,output_l=out)
print(len([out[i] for i in range(2,len(out),3) if out[i]==2])) |
# Python function to compute GCD of two numbers using recursion
def gcd(a,b):
if(b==0): # Base case
return a
else:
return gcd(b,a%b) # Recursive call
# Tester code
a=int(input("Enter first number:"))
b=int(input("Enter second number:"))
GCD=gcd(a,b)
print("GCD is: ")
print(GCD) |
def dpMakeChange(coinValueList,change,minCoins,coinsUsed):
for cents in range(change+1):
coinCount = cents
newCoin = 1
for j in [c for c in coinValueList if c <= cents]:
if minCoins[cents-j] + 1 < coinCount:
coinCount = minCoins[cents-j]+1
newCoin = j
minCoins[cents] = coinCount
coinsUsed[cents] = newCoin
return minCoins[change]
def printCoins(coinsUsed,change):
coin = change
while coin > 0:
thisCoin = coinsUsed[coin]
print(thisCoin)
coin = coin - thisCoin
def main():
amnt = 63
clist = [1,5,10,21,25]
coinsUsed = [0]*(amnt+1)
coinCount = [0]*(amnt+1)
print("Making change for",amnt,"requires")
print(dpMakeChange(clist,amnt,coinCount,coinsUsed),"coins")
print("They are:")
printCoins(coinsUsed,amnt)
print("The used list is as follows:")
print(coinsUsed)
main()
|
DEBUG = True
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3', # Add 'postgresql_psycopg2', 'mysql', 'sqlite3' or 'oracle'.
'NAME': 'db.sqlite3', # Or path to database file if using sqlite3.
}
}
# Make this unique, and don't share it with anybody.
SECRET_KEY = '^n4-$%m-w((n4=7g4j!(x3%=l68t=__j!24-3)0%bjd8i2e5th'
MIDDLEWARE_CLASSES = (
'django.middleware.common.CommonMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
)
ROOT_URLCONF = 'hostproof_auth.urls'
INSTALLED_APPS = (
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.sites',
'django.contrib.messages',
'hostproof_auth',
)
AUTH_USER_MODEL = 'hostproof_auth.User'
AUTHENTICATION_BACKENDS = (
'hostproof_auth.auth.ModelBackend',
)
|
x,y = input().split()
x,y = [float(x),float(y)]
if x == y == 0:
print("Origem")
elif x == 0:
print("Eixo Y")
elif y == 0:
print("Eixo X")
elif x > 0 and y > 0:
print("Q1")
elif x < 0 and y > 0:
print("Q2")
elif x < 0 and y < 0:
print("Q3")
else:
print("Q4")
|
# -*- coding: utf-8 -*-
def square(x):
return x * x
def cube(x):
return x * x * x
def quad(x):
return x * x * x * x
def my_map(func, arg_list):
result=[]
for i in arg_list:
result.append(func(i)) #square 함수 호출, func == square
return result
num_list=[1, 2, 3, 4, 5]
squares = my_map(square, num_list)
cubes = my_map(cube, num_list)
quads = my_map(quad, num_list)
print(squares)
print(cubes)
print(quads) |
"""
Good morning! Here's your coding interview problem for today.
This problem was asked by Apple.
Implement a queue using two stacks. Recall that a queue is a FIFO (first-in, first-out) data structure with the following methods: enqueue, which inserts an element into the queue, and dequeue, which removes it.
https://www.youtube.com/watch?v=AN0axYeLue0
https://www.geeksforgeeks.org/queue-using-stacks/
https://coderbyte.com/algorithm/implement-queue-using-two-stacks
"""
# implement stacks using plain lists with push and pop functions
stack1 = []
stack2 = []
# implement enqueue method by using only stacks
# and the append and pop functions
def enqueue(element):
stack1.append(element)
# implement dequeue method by pushing all elements
# from stack 1 into stack 2, which reverses the order
# and then popping from stack 2
def dequeue():
if len(stack2) == 0:
if len(stack1) == 0:
return 'Cannot dequeue because queue is empty'
while len(stack1) > 0:
stack2.append(stack1.pop())
return stack2.pop()
enqueue('a')
enqueue('b')
enqueue('c')
print(dequeue())
print(dequeue())
|
class Solution:
def countOrders(self, n: int) -> int:
kMod = int(1e9) + 7
ans = 1
for i in range(1, n + 1):
ans = ans * i * (i * 2 - 1) % kMod
return ans
|
#########################################
# InMoovArm.py
# more info @: http://myrobotlab.org/service/InMoovArm
#########################################
# this script is provided as a basic scripting guide
# most parts can be run by uncommenting them
# InMoov now can be started in modular pieces through the .config files from full script
# although this script is very short you can still
# do voice control of a InMoov head
# It uses WebkitSpeechRecognition, so you need to use Chrome as your default browser for this script t
#leftPort = "COM20" #modify port according to your board
rightPort = "COM7" #modify port according to your board
# start optional virtual arduino service, used for internal test and virtual inmoov
# virtual=True
if ('virtual' in globals() and virtual):
virtualArduinoRight = Runtime.start("virtualArduinoRight", "VirtualArduino")
virtualArduinoRight.connect(rightPort)
# end used for internal test
#to tweak the default voice
Voice="cmu-bdl-hsmm" #Male US voice
#Voice="cmu-slt-hsmm" #Default female for MarySpeech
mouth = Runtime.createAndStart("i01.mouth", "MarySpeech")
#mouth.installComponentsAcceptLicense(Voice)
mouth.setVoice(Voice)
##############
# starting InMoov service
i01 = Runtime.create("i01", "InMoov")
#Force Arduino to connect (fix Todo)
#left = Runtime.createAndStart("i01.left", "Arduino")
#left.connect(leftPort)
right = Runtime.createAndStart("i01.right", "Arduino")
right.connect(rightPort)
##############
# starting parts
i01.startEar()
# Start the webgui service without starting the browser
webgui = Runtime.create("WebGui","WebGui")
webgui.autoStartBrowser(False)
webgui.startService()
# Then start the browsers and show the WebkitSpeechRecognition service named i01.ear
webgui.startBrowser("http://localhost:8888/#/service/i01.ear")
# As an alternative you can use the line below to show all services in the browser. In that case you should comment out all lines above that starts with webgui.
# webgui = Runtime.createAndStart("webgui","WebGui")
i01.startMouth()
##############
#leftArm = Runtime.create("i01.leftArm","InMoovArm")
#tweak defaults LeftArm
#Velocity
#leftArm.bicep.setVelocity(-1)
#leftArm.rotate.setVelocity(-1)
#leftArm.shoulder.setVelocity(-1)
#leftArm.omoplate.setVelocity(-1)
#Mapping
#leftArm.bicep.map(0,90,45,96)
#leftArm.rotate.map(40,180,60,142)
#leftArm.shoulder.map(0,180,44,150)
#leftArm.omoplate.map(10,80,42,80)
#Rest position
#leftArm.bicep.setRest(5)
#leftArm.rotate.setRest(90)
#leftArm.shoulder.setRest(30)
#leftArm.omoplate.setRest(10)
#################
rightArm = Runtime.create("i01.rightArm","InMoovArm")
# tweak default RightArm
#Velocity
rightArm.bicep.setVelocity(-1)
rightArm.rotate.setVelocity(-1)
rightArm.shoulder.setVelocity(-1)
rightArm.omoplate.setVelocity(-1)
#Mapping
rightArm.bicep.map(0,90,45,96)
rightArm.rotate.map(40,180,75,130)
rightArm.shoulder.map(0,180,44,150)
rightArm.omoplate.map(10,80,43,80)
#Rest position
rightArm.bicep.setRest(5)
rightArm.rotate.setRest(90)
rightArm.shoulder.setRest(30)
rightArm.omoplate.setRest(10)
#################
i01 = Runtime.start("i01","InMoov")
#################
#i01.startLeftArm(leftPort)
i01.startRightArm(rightPort)
#################
#i01.leftArm.setAutoDisable(True)
i01.rightArm.setAutoDisable(True)
#################
# verbal commands
ear = i01.ear
ear.addCommand("attach everything", "i01", "enable")
ear.addCommand("disconnect everything", "i01", "disable")
ear.addCommand("attach left arm", "i01.leftArm", "enable")
ear.addCommand("disconnect left arm", "i01.leftArm", "disable")
ear.addCommand("attach right arm", "i01.rightArm", "enable")
ear.addCommand("disconnect right arm", "i01.rightArm", "disable")
ear.addCommand("rest", "python", "rest")
ear.addCommand("full speed", "python", "fullspeed")
ear.addCommand("arms front", "python", "armsFront")
ear.addCommand("da vinci", "python", "daVinci")
ear.addCommand("capture gesture", ear.getName(), "captureGesture")
ear.addCommand("manual", ear.getName(), "lockOutAllGrammarExcept", "voice control")
ear.addCommand("voice control", ear.getName(), "clearLock")
# Confirmations and Negations are not supported yet in WebkitSpeechRecognition
# So commands will execute immediatley
ear.addComfirmations("yes","correct","ya","yeah", "yes please", "yes of course")
ear.addNegations("no","wrong","nope","nah","no thank you", "no thanks")
############
ear.startListening()
def rest():
#i01.setArmVelocity("left", -1, -1, -1, -1)
i01.setArmVelocity("right", -1, -1, -1, -1)
#i01.moveArm("left",5,90,30,10)
i01.moveArm("right",5,90,30,10)
i01.mouth.speak("Ok, taking rest")
def fullspeed():
#i01.setArmVelocity("left", -1, -1, -1, -1)
i01.setArmVelocity("right", -1, -1, -1, -1)
i01.mouth.speak("All my servos are set to full speed")
def armsFront():
#i01.moveArm("left",13,115,100,20)
i01.moveArm("right",13,115,100,20)
i01.mouth.speak("Moving my arms in front of me")
def daVinci():
i01.startedGesture()
#i01.setArmSpeed("left", 0.80, 0.80, 0.80, 0.80)
i01.setArmVelocity("right", 40, 40, 40, 40)
#i01.moveArm("left",0,118,29,74)
i01.moveArm("right",0,118,29,74)
i01.mouth.speak("This is the pose of Leonardo Da Vinci")
sleep(10)
i01.finishedGesture()
#i01.setArmSpeed("left", 0.70, 0.70, 0.70, 0.70)
i01.setArmSpeed("right", 30, 30, 30, 30)
#i01.moveArm("left",5,90,30,10)
i01.moveArm("right",5,90,30,10) |
MODE_PLANNING = "Planning"
MODE_NLP = "NLP"
ROWS = 8 # rows in maze
COLS = 8 # columns in maze
GRID_DX = 20.0#20.0 # x-dimension of the grid world
GRID_DY = 10.0#20.0 # y-dimension of the grid world
GRID_DZ = 3.0 * .75 * .5# z-dimension of the grid world
MAX_STEPS = ROWS * COLS * 2 * 90# max number of steps - no need to visit each cell more then twice!
STEP_DELAY = 3.0 # number of seconds to wait between the sense-act-step repeats
NUDGE_X = -5.0 # shift the island in +x by ...
NUDGE_Y = -5.0 # shift the island in +y by ...
WALL_TEMPLATE = "data/shapes/wall/BrickWall.xml"
HISTORY_LENGTH = 5 # number of state-action pairs used to determine if the agent is stuck
OBSTACLE_MASK = 1 #0b0001
AGENT_MASK = 2 #0b0010
|
"""
"""
class Order:
pass |
fim = int(input('Digite o último número: '))
x = 1
while x <= fim:
print(x)
x = x + 2
|
# Copyright (C) 2016 Goban authors
#
# This software may be modified and distributed under the terms
# of the MIT license. See the LICENSE file for details.
class ColoredStone:
def __init__(self, color):
if color < 0:
raise Exception("invalid stone color")
self.__color = color
def get_color(self):
return self.__color
def set_color(self, color):
if color < 0:
raise Exception("invalid stone color")
self.__color = color
|
# MULTIPLY STRINGS LEETCODE SOLUTION:
# creating a class.
class Solution(object):
# creating a function to solve the problem.
def multiply(self, num1, num2):
# converting the given strings to integers.
num1 = int(num1)
num2 = int(num2)
# code to find the product of the integers.
product = num1 * num2
# returning the product as a string.
return str(product) |
def fibonacci(N):
"""Return all fibonacci numbers up to N. """
yield 0
if N == 0:
return
a = 0
b = 1
while b <= N:
yield b
a, b = b, a + b
print(list(fibonacci(0))) # [0]
print(list(fibonacci(1))) # [0, 1, 1]
print(list(fibonacci(50))) # [0, 1, 1, 2, 3, 5, 8, 13, 21, 34]
|
def stream_audio(p, chunk, job):
wf = wave.open(job, 'rb')
stream = p.open(format=p.get_format_from_width(wf.getsampwidth()),
channels=wf.getnchannels(),
rate=wf.getframerate(),
output=True)
data = wf.readframes(chunk)
while data != b'':
print(calculate_position_percent(wf.tell(), wf.getnframes()))
stream.write(data)
data = wf.readframes(chunk)
# Check queue and load next element
# stop stream (6)
stream.stop_stream()
stream.close()
wf.close()
return True
def check_audio_device(p):
p.get_default_output_device_info()
device_count = p.get_device_count()
for i in range(0, device_count):
yield p.get_device_info_by_index(i)["name"],p.get_device_info_by_index(i)["index"]
|
# i = 1
#
# while i <= 5:
# print(i)
# i = i + 1
#
# print("Done")
secret_number = 9
guess_count = 0
guess_limit = 3
while guess_count < guess_limit:
guess = int(input('Guess: '))
guess_count += 1
if guess == secret_number:
print('You won!')
break
else:
print("Sorry, you failed to guess the number")
|
# Tic-Tac-Toe
CROSS = "X"
CIRCLE = "O"
def make_grid():
return list(range(1, 10))
def print_start():
print("Welcome to tic-tac-toe!!!!")
def print_end(winner):
print(winner, "was the winner!!!")
def three_horizontal(grid, player):
for i in range(0,9,3):
if grid[i] == player and grid[i + 1] == player and grid[i + 2] == player:
return True
return False
def three_vertical(grid, player):
for i in range(3):
if grid[i] == player and grid[i + 3] == player and grid[i + 6] == player:
return True
return False
def three_diagonal(grid, player):
first_diagonal = grid[0] == player and grid[4] == player and grid[8] == player
second_diagonal = grid[2] == player and grid[4] == player and grid[6] == player
return first_diagonal or second_diagonal
def is_win(grid, player):
return (three_vertical(grid, player) or
three_horizontal(grid, player) or
three_diagonal(grid, player))
def is_tie(grid):
for i in grid:
if i is not CROSS and i is not CIRCLE:
return False
return True
def draw_grid(grid):
for i in range(0,9,3):
print(str(grid[i]) + "|" + str(grid[i + 1]) + "|" + str(grid[i + 2]))
if i < 6:
print("-----")
print("")
def is_empty(grid, location):
if str(grid[location]) not in CROSS + CIRCLE:
return True
return False
def input_step(player, board):
location = int(input("Where do you want to put your token? "))
if location < 1 or location > 9 or not is_empty(grid, location - 1):
print("Your input was not valid!")
input_step(player, board)
else:
set_board_value(board, player, location - 1)
def set_board_value(board, value, index):
board[index] = value
def change_players(player):
if player == CROSS:
return CIRCLE
else:
return CROSS
grid = make_grid()
current_player = CROSS
print_start()
while not (is_win(grid, change_players(current_player)) or is_tie(grid)):
draw_grid(grid)
input_step(current_player, grid)
current_player = change_players(current_player)
draw_grid(grid)
print_end(change_players(current_player))
|
# 16文字
str_sample_1 = '0123456789abcdef'
# 16文字(アンダースコア入り)
str_sample_2 = '01234_6789ab_def'
# 文字「7」を区切りに分解
divided_sample_1 = str_sample_1.split('7')
print(f'divided_sample_1 : {divided_sample_1} ←区切りとなった「7」は含まれない')
# 文字「_」を区切りに分解
divided_sample_2 = str_sample_2.split('_')
print(f'divided_sample_2 : {divided_sample_2} ←区切りとなった「_」は含まれない')
|
# https://leetcode.com/problems/longest-word-in-dictionary-through-deleting/
# Given a string s and a string array dictionary, return the longest string in the
# dictionary that can be formed by deleting some of the given string characters.
# If there is more than one possible result, return the longest word with the
# smallest lexicographical order. If there is no possible result, return the empty
# string.
################################################################################
# sort dict and check if key can be substr
class Solution:
def findLongestWord(self, s: str, dictionary: List[str]) -> str:
dictionary.sort(key=lambda x: (-len(x), x))
for key in dictionary:
# if key is a substr of s
if self.is_substr(key, s):
return key
return ''
def is_substr(self, substr, s):
i = j = 0
while i < len(substr) and j < len(s):
if substr[i] == s[j]: # move i only when there is a match
i += 1
j += 1
return i == len(substr)
|
# Copyright 2015 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
class Failure(Exception):
"""StoryTest Exception raised when an undesired but designed-for problem."""
class StoryTest(object):
"""A class for creating story tests.
The overall test run control flow follows this order:
test.WillRunStory
state.WillRunStory
state.RunStory
test.Measure
state.DidRunStory
test.DidRunStory
"""
def WillRunStory(self, platform):
"""Override to do any action before running the story.
This is run before state.WillRunStory.
Args:
platform: The platform that the story will run on.
"""
raise NotImplementedError()
def Measure(self, platform, results):
"""Override to take the measurement.
This is run only if state.RunStory is successful.
Args:
platform: The platform that the story will run on.
results: The results of running the story.
"""
raise NotImplementedError()
def DidRunStory(self, platform, results):
"""Override to do any action after running the story, e.g., clean up.
This is run after state.DidRunStory. And this is always called even if the
test run failed. The |results| object can be used to stored debugging info
related to run.
Args:
platform: The platform that the story will run on.
results: The results of running the story.
"""
raise NotImplementedError()
|
def process_bike_count_data(df):
"""
Process the provided dataframe: parse datetimes and rename columns.
"""
df.index = pd.to_datetime(df['dag'] + ' ' + df['tijdstip'], format="%d.%m.%y %H:%M:%S")
df = df.drop(['dag', 'tijdstip'], axis=1)
df = df.rename(columns={'noord': 'north', 'zuid':'south', 'actief': 'active'})
return df |
def print_function(args, fun):
for x in args:
print('f(', x,')=', fun(x), sep='')
def poly(x):
return 2 * x**2 - 4 * x + 2
print_function([x for x in range(-2, 3)], poly)
# [-2, -1, 0, 1, 2] |
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