def generate_header():
r_list = RandomList()
header_dict = {}
# cookie
cookie_str = '''
_T_WM=bd80db78b4ed27825deaa022e62b0c4d; ALF=1490583082; SCF=AsAX-nl6za_tqmlP7Wc4KZBfnM5lvn6m2-lc1hztSI7kOIqTS7AgSwx49SYl9Zp0VjD5FBSRDRdqq9zWMjoHnq8.; SUB=_2A251t6DpDeRxGeRN61EX9CrJyjyIHXVXW8ChrDV6PUNbktBeLVenkW00qpJdPx7uyVWiIrZ6o3dbKcj-1Q..; SUBP=0033WrSXqPxfM725Ws9jqgMF55529P9D9Wh3LNHVkce-0__UlEggblno5JpX5KMhUgL.Foz0ehecShBfeK52dJLoIEBLxK.L1-qLBK.LxK.L1-qLBK.LxKqLBoqLBKqLxKnLBoqL1h-t; SUHB=08JKhus4sxO2oe; SSOLoginState=1488179386
'''.strip()
header_dict['Cookie'] = cookie_str
header_dict['Accept-Language'] = 'zh-CN,zh;q=0.8'
header_dict['User-Agent'] = r_list.get_random_ua()
header_dict['Accept'] = 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8'
#header_dict['Accept-Encoding'] = 'gzip, deflate, sdch'
header_dict['Cache-Control'] = 'max-age=0'
header_dict['Connection'] = 'keep-alive'
header_dict['Host'] = 'weibo.cn'
header_dict['Referer'] = 'weibo.cn/2303644510/info' # r_list.get_random(referers)
header_dict['Upgrade-Insecure-Requests'] = '1'
return header_dict
class FontManager():
def __init__(self, fontSize):
self.fontSize = fontSize
self.allFonts = QtGui.QFontDatabase().families(QtGui.QFontDatabase.Latin)
self.randomList = RandomList(len(self.allFonts))
def step(self):
return self.allFonts[self.randomList.step()]
def changeFontSize(self, delta):
self.fontSize += delta
class FontManager():
def __init__(self, fontSize):
self.fontSize = fontSize
self.allFonts = QtGui.QFontDatabase().families(
QtGui.QFontDatabase.Latin)
self.randomList = RandomList(len(self.allFonts))
def step(self):
return self.allFonts[self.randomList.step()]
def changeFontSize(self, delta):
self.fontSize += delta
def run():
def set_led_color():
led.color = Color(*colors_list.values)
def change_led_color():
colors_list.shuffle()
set_led_color()
led = RGBLED(PIN_RED, PIN_GREEN, PIN_BLUE)
button = Button(PIN_BUTTON)
colors_list = RandomList(3, MIN_VALUE, MAX_VALUE)
set_led_color()
button.when_pressed = change_led_color
pause()
class IdeazMultipleLists(object):
'''
- This class takes a list of text files from the commandline.
- Each text file i stores N_i lines.
- By calling step(), one item from each file is selected and returned as a list of strings.
- There are in total \prod_i N_i combinations.
- Algorithm:
-- There are \prod_i N_i combinations
-- A candidate is randomly selected from the range 0..N_combinations-1
-- A candidate is represented as a linear combination
candidate = i + N_i*j + N_i * N_j*k + ...
-- i, j, k are computed by alternating mod and division
'''
def __init__(self, filenames):
self.filenames = filenames
self.data, self.list_lengths = self.parseCommandLine(filenames)
N_combinations = np.prod(self.list_lengths)
self.candidates = RandomList(N_combinations)
def parseCommandLine(self, filenames):
data = []
list_lengths = []
for fn in filenames:
data.append([line.strip() for line in open(fn, 'r')])
list_lengths.append(len(data[-1]))
return data, list_lengths
def getRawIndices(self, candidate):
rawIndices = np.array([np.mod(candidate, self.list_lengths[0])],
dtype=np.uint32)
for i, length in enumerate(self.list_lengths[:-1]):
candidate = np.uint32(candidate / length)
rawIndices = np.append(rawIndices,
np.mod(candidate, self.list_lengths[i + 1]))
return rawIndices
def getSelectedData(self, data, rawIndices):
selectedData = []
for i, rawIndex in enumerate(rawIndices):
selectedData.append(data[i][rawIndex])
return selectedData
def step(self):
rawIndices = self.getRawIndices(self.candidates.step())
return self.getSelectedData(self.data, rawIndices)
def getNrOfLayers(self):
return len(self.filenames)
class IdeazMultipleLists(object):
'''
- This class takes a list of text files from the commandline.
- Each text file i stores N_i lines.
- By calling step(), one item from each file is selected and returned as a list of strings.
- There are in total \prod_i N_i combinations.
- Algorithm:
-- There are \prod_i N_i combinations
-- A candidate is randomly selected from the range 0..N_combinations-1
-- A candidate is represented as a linear combination
candidate = i + N_i*j + N_i * N_j*k + ...
-- i, j, k are computed by alternating mod and division
'''
def __init__(self, filenames):
self.filenames = filenames
self.data, self.list_lengths = self.parseCommandLine(filenames)
N_combinations = np.prod(self.list_lengths)
self.candidates = RandomList(N_combinations)
def parseCommandLine(self, filenames):
data = []
list_lengths = []
for fn in filenames:
data.append([line.strip() for line in open(fn, 'r')])
list_lengths.append(len(data[-1]))
return data, list_lengths
def getRawIndices(self, candidate):
rawIndices = np.array([np.mod(candidate, self.list_lengths[0])], dtype=np.uint32)
for i, length in enumerate(self.list_lengths[:-1]):
candidate = np.uint32(candidate/length)
rawIndices = np.append(rawIndices, np.mod(candidate, self.list_lengths[i+1]))
return rawIndices
def getSelectedData(self, data, rawIndices):
selectedData = []
for i, rawIndex in enumerate(rawIndices):
selectedData.append(data[i][rawIndex])
return selectedData
def step(self):
rawIndices = self.getRawIndices(self.candidates.step())
return self.getSelectedData(self.data, rawIndices)
def getNrOfLayers(self):
return len(self.filenames)
class IdeazOneList(object):
def __init__(self, filenames, N_layers):
self.data = self.parseCommandLine(filenames)
self.setNrOfLayers(N_layers)
def setNrOfLayers(self, N_layers):
self.N_layers = N_layers
self.N_combinations = np.prod(len(self.data)-np.arange(N_layers))
self.candidates = RandomList(self.N_combinations)
def parseCommandLine(self, filenames):
data = []
for fn in filenames:
data += [line.strip() for line in open(fn, 'r')]
return data
def getRawIndices(self, candidate):
N = len(self.data);
rawIndices = np.array([np.mod(candidate, N)], dtype=np.uint32)
for i in np.arange(self.N_layers-1):
candidate = np.uint32(candidate/(N-i))
rawIndices = np.append(rawIndices, np.mod(candidate, N-i-1))
return rawIndices
def getFineIndices(self, rawIndices):
allIndices = np.arange(self.N_combinations)
fineIndices = np.array([], dtype=np.uint32)
for i in np.arange(self.N_layers):
fineIndices = np.append(fineIndices, allIndices[rawIndices[i]])
allIndices = np.delete(allIndices, rawIndices[i])
return fineIndices
def getSelectedData(self, fineIndices):
selectedData = []
for i in fineIndices:
selectedData.append(self.data[i])
return selectedData
def step(self):
rawIndices = self.getRawIndices(self.candidates.step())
fineIndices = self.getFineIndices(rawIndices)
return self.getSelectedData(fineIndices)
def getNrOfLayers(self):
return self.N_layers
class IdeazOneList(object):
def __init__(self, filenames, N_layers):
self.data = self.parseCommandLine(filenames)
self.setNrOfLayers(N_layers)
def setNrOfLayers(self, N_layers):
self.N_layers = N_layers
self.N_combinations = np.prod(len(self.data) - np.arange(N_layers))
self.candidates = RandomList(self.N_combinations)
def parseCommandLine(self, filenames):
data = []
for fn in filenames:
data += [line.strip() for line in open(fn, 'r')]
return data
def getRawIndices(self, candidate):
N = len(self.data)
rawIndices = np.array([np.mod(candidate, N)], dtype=np.uint32)
for i in np.arange(self.N_layers - 1):
candidate = np.uint32(candidate / (N - i))
rawIndices = np.append(rawIndices, np.mod(candidate, N - i - 1))
return rawIndices
def getFineIndices(self, rawIndices):
allIndices = np.arange(self.N_combinations)
fineIndices = np.array([], dtype=np.uint32)
for i in np.arange(self.N_layers):
fineIndices = np.append(fineIndices, allIndices[rawIndices[i]])
allIndices = np.delete(allIndices, rawIndices[i])
return fineIndices
def getSelectedData(self, fineIndices):
selectedData = []
for i in fineIndices:
selectedData.append(self.data[i])
return selectedData
def step(self):
rawIndices = self.getRawIndices(self.candidates.step())
fineIndices = self.getFineIndices(rawIndices)
return self.getSelectedData(fineIndices)
def getNrOfLayers(self):
return self.N_layers
'''
Created on 2016年1月12日
# encoding: utf-8
@author: tcliu
'''
from random_list import RandomList
R = RandomList(10, 100)
lst = R.gen()
#lst = [1, 3, 5, 3, 9]
def bucket_sort(lst=[]):
sorted_list = []
lenth = max(lst) - min(lst) + 1
bucket = [0] * lenth
for item in lst:
bucket[item - min(lst)] += 1
for i in range(len(bucket)):
if bucket[i] > 0:
sorted_list.extend([(i + min(lst))] * bucket[i])
print(sorted_list)
return sorted_list
bucket_sort(lst)
'''
Created on 2016年1月18日
# encoding: utf-8
@author: tcliu
'''
from random_list import RandomList
R = RandomList(5, 10)
lst = R.gen()
def path_sort(list, start_index, end_index):
flag = list[end_index]
i = start_index - 1
for j in range(start_index, end_index):
if list[j] > flag:
pass
else:
i += 1
tmp = list[i]
list[i] = list[j]
list[j] = tmp
tmp = list[end_index]
list[end_index] = list[i + 1]
list[i + 1] = tmp
return i + 1
def Quick_sort(list, start_index, end_index):
'''
Created on 2016年1月13日
# encoding: utf-8
@author: tcliu
'''
from random_list import RandomList
R = RandomList(5, 10)
lst = R.gen()
def bubble_sort(l = []):
for i in range(len(l)):
for j in range(len(l) - i -1):
if l[j] > l[j + 1]:
#(l[j + 1], i[j]) = (l[j], l[j + 1])
l[j], l[j+1] = l[j+1], l[j]
else:
continue
print(l)
bubble_sort(lst)
def __init__(self, fontSize):
self.fontSize = fontSize
self.allFonts = QtGui.QFontDatabase().families(QtGui.QFontDatabase.Latin)
self.randomList = RandomList(len(self.allFonts))
def setNrOfLayers(self, N_layers):
self.N_layers = N_layers
self.N_combinations = np.prod(len(self.data) - np.arange(N_layers))
self.candidates = RandomList(self.N_combinations)
def __init__(self, filenames):
self.filenames = filenames
self.data, self.list_lengths = self.parseCommandLine(filenames)
N_combinations = np.prod(self.list_lengths)
self.candidates = RandomList(N_combinations)
def __init__(self, filenames):
self.filenames = filenames
self.data, self.list_lengths = self.parseCommandLine(filenames)
N_combinations = np.prod(self.list_lengths)
self.candidates = RandomList(N_combinations)
def setNrOfLayers(self, N_layers):
self.N_layers = N_layers
self.N_combinations = np.prod(len(self.data)-np.arange(N_layers))
self.candidates = RandomList(self.N_combinations)
def __init__(self, fontSize):
self.fontSize = fontSize
self.allFonts = QtGui.QFontDatabase().families(
QtGui.QFontDatabase.Latin)
self.randomList = RandomList(len(self.allFonts))