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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3c67a4b9cc2936a7735c731d515fa2157533c963 | 9bc93942dd89dcac95b5216a7bb70bf530e29236 | /pythonAlgo/DFS&BFS/등산경로.py | 240f7b03a8c86a9c4ef5479ac55bdf61ece999c8 | [] | no_license | zbqlr456/zbqlr456 | 65edccef49f63fa72d98aa58105b87797465a157 | 8b5811d8e7a9f7d3c28cb12450ae69c0ed44216b | refs/heads/main | 2022-12-25T06:11:10.931084 | 2022-12-13T06:55:15 | 2022-12-13T06:55:15 | 252,738,892 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 893 | py | import sys
di = [-1, 1, 0, 0]
dj = [0, 0, -1, 1]
def DFS(x,y):
global cnt
if x == end[0] and y == end[1]:
cnt += 1
else:
for d in range(4):
nexti = x + di[d]
nextj = y + dj[d]
if 0 <= nexti < n and 0 <= nextj < n and g[nexti][nextj] > g[x][y]:
DFS(nexti,nextj)
if __name__ == "__main__":
n = int(input())
g = [[] for _ in range(n)]
for i in range(n):
g[i] = list(map(int,input().split()))
start = [0,0,1e9]
end = [0,0,-1e9]
for i in range(n):
for j in range(n):
if g[i][j] < start[2]:
start[0] = i
start[1] = j
start[2] = g[i][j]
if g[i][j] > end[2]:
end[0] = i
end[1] = j
end[2] = g[i][j]
cnt = 0
DFS(start[0],start[1])
print(cnt)
| [
"zbqlr456@naver.com"
] | zbqlr456@naver.com |
d1ede18d2d2e4505c05518905e58bd32ee7fa1e2 | 0a1d48a2b740b5bd74505f2b392b92f56f99f880 | /app.py | 634594cf9fcaf5fc74cfe9c90b9814278995ac31 | [] | no_license | sarahoeri/Giraffe | 4dde173b42665250c51cd4f86e2404e4ade7b5d9 | 283b44714f07509879392b1455416df5ee246c51 | refs/heads/master | 2020-12-20T08:07:40.583411 | 2020-01-27T13:28:21 | 2020-01-27T13:28:21 | 236,009,706 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 894 | py | # Variables
character_name = "John"
character_age = "50"
isMale = True
print("there was once a man called " + character_name)
print("he was at an age of " + character_age)
# Functions
phrase = "Giraffe Academy"
print(phrase + " is developed now")
print(phrase.upper())
print(phrase.lower())
print(phrase.isupper())
print(phrase.upper().isupper())
print(len(phrase))
print(phrase[9])
print(phrase.index("raffe"))
print(phrase.replace("Academy", "School"))
# Numbers
print(5 * (4 +5))
myNum = 10
print(str(myNum) + " is my favourite number")
my_number = -0.54
print(abs(my_number))
print(pow(10, 8))
# to find max and min values
print(max(27, 88, 73, 109))
print(round(3.9))
from math import *
print(floor(9.5))
print(ceil(7.2))
print(sqrt(36))
# getting input from users
name = input("Enter your name: ")
age = input("Enter your age: ")
print("Heeey " + name + "!" " You are " + age)
| [
"oerisarah@gmail.com"
] | oerisarah@gmail.com |
5ba9e377fc2b1c5b3775045e195f5149da9627d2 | 8d14d526969d8e970254f08563ff2c6e6583dd35 | /Python/2019/ClassOrnek/kullanici.py | 235c35cfc5458e2c5b66ae4511e018339c8b2338 | [] | no_license | osmanraifgunes/MedipolCodes | c29db62896162c4b1a2c8c274877fff63149f826 | 943b014269e9a7b529e74741ce14447dbd7d5df5 | refs/heads/master | 2023-01-09T10:31:02.907945 | 2020-06-09T18:05:04 | 2020-06-09T18:05:04 | 218,612,787 | 6 | 13 | null | 2023-01-07T18:58:55 | 2019-10-30T19:59:16 | Python | UTF-8 | Python | false | false | 546 | py | import tkinter as tk
import Ornek
orn = Ornek.deneme2()
"""print (type(orn))
print (orn.acilis)"""
#orn.globalOzellik3 = 123
print (orn.globalOzellikGetter)
#print (orn.globalOzellik3)
#print (Ornek.deneme2.globalOzellik)
def topla(sayi1,sayi2):
return sayi1 + sayi2
orn.globalOzellikSetter = topla(5,55)
print (orn.globalOzellikGetter)
pencere = tk.Tk()
pencere.geometry('200x70')
etiket = tk.Label(text='Merhaba Zalim Dünya')
etiket.pack()
düğme = tk.Button(text='Tamam', command=pencere.destroy)
düğme.pack()
pencere.mainloop()
| [
"osmanraifgunes@gmail.com"
] | osmanraifgunes@gmail.com |
efb6d49912852567e840d7d060577207271bfb3d | 3a30af04ebb4970896de7554a3384e5777556b6d | /B_Transformation and ICP/slam_04_c_estimate_transform_question.py | d0c28e76f07ef6fac76727b9ddb40ecb2d8f7100 | [] | no_license | konanrobot/Filter-SLAM | be757e9b0ae0b2c4a2ee348d4d504130c939cbb8 | 52898bcc374baaf7a48df02ae51ed0000c673c4e | refs/heads/master | 2021-06-17T11:16:45.779883 | 2017-05-25T15:23:30 | 2017-05-25T15:23:30 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,182 | py | # For each cylinder in the scan, find its cartesian coordinates,
# in the world coordinate system.
# Find the closest pairs of cylinders from the scanner and cylinders
# from the reference, and the optimal transformation which aligns them.
# Then, output the scanned cylinders, using this transform.
# 04_c_estimate_transform
# XU Shang, 2015-08-18
from lego_robot import *
from slam_b_library import filter_step
from slam_04_a_project_landmarks import\
compute_scanner_cylinders, write_cylinders
from math import sqrt
# Given a list of cylinders (points) and reference_cylinders:
# For every cylinder, find the closest reference_cylinder and add
# the index pair (i, j), where i is the index of the cylinder, and
# j is the index of the reference_cylinder, to the result list.
# This is the function developed in slam_04_b_find_cylinder_pairs.
def find_cylinder_pairs(cylinders, reference_cylinders, max_radius):
cylinder_pairs = []
# --->>> Insert here your code from the last question,
# slam_04_b_find_cylinder_pairs.
return cylinder_pairs
# Given a point list, return the center of mass.
def compute_center(point_list):
# Safeguard against empty list.
if not point_list:
return (0.0, 0.0)
# If not empty, sum up and divide.
sx = sum([p[0] for p in point_list])
sy = sum([p[1] for p in point_list])
return (float(sx) / len(point_list), float(sy) / len(point_list))
# Given a left_list of points and a right_list of points, compute
# the parameters of a similarity transform: scale, rotation, translation.
# If fix_scale is True, use the fixed scale of 1.0.
# The returned value is a tuple of:
# (scale, cos(angle), sin(angle), x_translation, y_translation)
# i.e., the rotation angle is not given in radians, but rather in terms
# of the cosine and sine.
def estimate_transform(left_list, right_list, fix_scale = False):
# Compute left and right center.
lc = compute_center(left_list)
rc = compute_center(right_list)
# --->>> Insert here your code to compute lambda, c, s and tx, ty.
return la, c, s, tx, ty
# Given a similarity transformation:
# trafo = (scale, cos(angle), sin(angle), x_translation, y_translation)
# and a point p = (x, y), return the transformed point.
def apply_transform(trafo, p):
la, c, s, tx, ty = trafo
lac = la * c
las = la * s
x = lac * p[0] - las * p[1] + tx
y = las * p[0] + lac * p[1] + ty
return (x, y)
if __name__ == '__main__':
# The constants we used for the filter_step.
scanner_displacement = 30.0
ticks_to_mm = 0.349
robot_width = 150.0
# The constants we used for the cylinder detection in our scan.
minimum_valid_distance = 20.0
depth_jump = 100.0
cylinder_offset = 90.0
# The maximum distance allowed for cylinder assignment.
max_cylinder_distance = 300.0
# The start pose we obtained miraculously.
pose = (1850.0, 1897.0, 3.717551306747922)
# Read the logfile which contains all scans.
logfile = LegoLogfile()
logfile.read("robot4_motors.txt")
logfile.read("robot4_scan.txt")
# Also read the reference cylinders (this is our map).
logfile.read("robot_arena_landmarks.txt")
reference_cylinders = [l[1:3] for l in logfile.landmarks]
out_file = file("estimate_transform.txt", "w")
for i in xrange(len(logfile.scan_data)):
# Compute the new pose.
pose = filter_step(pose, logfile.motor_ticks[i],
ticks_to_mm, robot_width,
scanner_displacement)
# Extract cylinders, also convert them to world coordinates.
cartesian_cylinders = compute_scanner_cylinders(
logfile.scan_data[i],
depth_jump, minimum_valid_distance, cylinder_offset)
world_cylinders = [LegoLogfile.scanner_to_world(pose, c)
for c in cartesian_cylinders]
# For every cylinder, find the closest reference cylinder.
cylinder_pairs = find_cylinder_pairs(
world_cylinders, reference_cylinders, max_cylinder_distance)
# Estimate a transformation using the cylinder pairs.
trafo = estimate_transform(
[world_cylinders[pair[0]] for pair in cylinder_pairs],
[reference_cylinders[pair[1]] for pair in cylinder_pairs],
fix_scale = True)
# Transform the cylinders using the estimated transform.
transformed_world_cylinders = []
if trafo:
transformed_world_cylinders =\
[apply_transform(trafo, c) for c in
[world_cylinders[pair[0]] for pair in cylinder_pairs]]
# Write to file.
# The pose.
print >> out_file, "F %f %f %f" % pose
# The detected cylinders in the scanner's coordinate system.
write_cylinders(out_file, "D C", cartesian_cylinders)
# The detected cylinders, transformed using the estimated trafo.
write_cylinders(out_file, "W C", transformed_world_cylinders)
out_file.close()
| [
"xushangnjlh@gmail.com"
] | xushangnjlh@gmail.com |
a33eefbf9b26a91be2b862f3f88994ead11d060e | 27404287781cdbc9f66c75cb3f3bdc20e602740c | /util.py | ab9481c0d986c78301245646a4b725eb334e420f | [] | no_license | z-van-baars/Citigen | 20f713fe45f8a012a311c35c17b51f32ae7d948a | 0ce0eed94c7313741b65c1739befd017a322308a | refs/heads/master | 2022-04-23T18:08:53.620323 | 2020-04-29T05:16:08 | 2020-04-29T05:16:08 | 257,134,459 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,153 | py | import random
import math
import string
import pygame
CHARACTERS = (string.ascii_letters +
string.digits +
'-._~')
def generate_unique_key(length=8):
"""Returns a unique unicode key of length l, default=8"""
return ''.join(random.sample(CHARACTERS, length))
def generate_coordinate_pair(minmax):
x = random.randrange(minmax[0], minmax[1])
y = random.randrange(minmax[0], minmax[1])
return (x, y)
def get_midpoint(a, b):
x1 = (a[0] - b[0]) / 2.
y1 = (a[1] - b[1]) / 2.
return x1, y1
def coordinates_to_region_index(voronoi_object, coordinates):
vor = voronoi_object
xy1 = tuple(coordinates)
region_index = 0
for xyi in vor.point_region:
xy2 = tuple(vor.points[region_index])
if xy2[0] == xy1[0] and xy2[1] == xy1[1]:
return xyi
region_index += 1
print("no match found")
def coordinates_to_point_index(voronoi_object, coordinates):
vor = voronoi_object
xy1 = tuple(coordinates)
for point_index, point in enumerate(vor.points):
xy2 = tuple(point)
if xy2[0] == xy1[0] and xy2[1] == xy1[1]:
return point_index
def coord_list_match(list1, point_1):
for point_2 in list1:
if point_1[0] == point_2[0] and point_1[1] == point_2[1]:
return True
return False
def get_closest_edge(map_size, point):
distances = [(get_length(point, (point[0], -map_size * 0.5)), 0),
(get_length(point, (point[0], map_size * 0.5)), 1),
(get_length(point, (-map_size * 0.5, point[1])), 2),
(get_length(point, (map_size * 0.5, point[1])), 3)]
return sorted(distances, key=lambda d: d[0])[0][1]
def get_neighbors(dela, vertex):
# unpack vertex_neighbor_vertices just so it's easier to type
a = dela.vertex_neighbor_vertices[0]
b = dela.vertex_neighbor_vertices[1]
# The indices of neighboring vertices of 'vertex' are indptr[indices['vertex']:indices['vertex'+1]].
return b[a[vertex]: a[vertex + 1]]
def get_length(pt_A, pt_B):
"""Pythagorean Distance Formula, returns a float"""
a2 = (pt_A[0] - pt_B[0]) ** 2
b2 = (pt_A[1] - pt_B[1]) ** 2
c2 = math.sqrt(a2 + b2)
# reut
return round(c2, 3)
def lloyd_relaxation(vor):
"""A Pseudo-Lloyd relaxation function that just averages the points of resulting voronoi
polygons together and returns an approximated centroid. This will nicely spread out bunched
up dots, but it does have a tendency over time to spread points out, with a disproportionate
effect on points toward the edges of the graph.
A potential idea for future improvement is to have some kind of diff function that would compensate
for points drifting off the edge. Right now there's a cull function that takes place immediately
after this function is called that trims off any points that crept out of the scope of the graph.
This works and is fast but it does ultimately result in a reduction of the number of dots overall."""
relaxed_points = []
for r_index, region in enumerate(vor.regions):
corners = []
for vertex_index in region:
if vertex_index is not -1:
corners.append(vor.vertices[vertex_index])
# don't change any region centroids with vertices outside the voronoi
if -1 in region:
relaxed_points.append(vor.points[r_index - 1])
continue
# skip the dummy empty region
if len(region) < 3:
continue
centroid_lite = (int(sum(j[0] for j in corners) / len(corners)),
int(sum(k[1] for k in corners) / len(corners)))
relaxed_points.append(centroid_lite)
# there is a bug here where occasionally one point is dropped?
# only ever one, I'm confused
#
# if I uncomment this next line the assertion fails about 1:6 times
# assert len(relaxed_points) == len(vor.points)
return relaxed_points
def quit_check():
for event in pygame.event.get():
if event.type == pygame.QUIT:
pygame.display.quit()
pygame.quit()
| [
"zvanbaars@gmail.com"
] | zvanbaars@gmail.com |
85722f6d4dadf839b0b2b64b210aa5a325367cd5 | 5e0755091efd2d4ed61bead8aa38b45bab5a8b07 | /python/anyascii/_data/_1b0.py | 4d80487311c754b87a50572f39d147a8be20a53e | [
"ISC"
] | permissive | casept/anyascii | c27261d87257c17c47fe0e9fc77438437de94c1c | d4f426b91751254b68eaa84c6cd23099edd668e6 | refs/heads/master | 2022-12-05T07:13:53.075144 | 2020-08-07T07:55:50 | 2020-08-07T07:55:50 | 285,904,577 | 0 | 0 | ISC | 2020-08-07T19:20:00 | 2020-08-07T19:19:59 | null | UTF-8 | Python | false | false | 748 | py | b='e e a a a a i i i i u u u u u e e e e e o o o ka ka ka ka ka ka ka ka ka ka ka ka ki ki ki ki ki ki ki ki ku ku ku ku ku ku ku ke ke ke ke ke ke ko ko ko ko sa sa sa sa sa sa sa sa si si si si si si su su su su su su su su se se se se se so so so so so so so ta ta ta ta ti ti ti ti ti ti ti tu tu tu tu tu te te te te te te te te te to to to to to to to na na na na na na na na na ni ni ni ni ni ni ni ni nu nu nu ne ne ne ne ne ne ne no no no no no ha ha ha ha ha ha ha ha ha ha ha hi hi hi hi hi hi hi hu hu hu he he he he he he he ho ho ho ho ho ho ho ho ma ma ma ma ma ma ma mi mi mi mi mi mi mi mu mu mu mu me me me mo mo mo mo mo mo ya ya ya ya ya ya yu yu yu yu yo yo yo yo yo yo ra ra ra ra ri ri ri ri ri ri ri ru ru ru ru ru ru re re' | [
"hunter@hunterwb.com"
] | hunter@hunterwb.com |
9ae7e8b3abe41c13083a6010f9fb09895c3d755e | b1cf797d4d26553a6121d36bb560097260c462f3 | /math.py | 66fbbae7a20df53adfbce836f68c3f7215bfb13c | [] | no_license | gahlm/DarkOverLordsCreepyDungeon | 1bc8812094151354ed26f66234c50a765f7de911 | 9ab6b79ea27a6a7ac903f348ca7c2eedec337c34 | refs/heads/master | 2022-09-10T09:04:02.730706 | 2020-06-04T15:49:28 | 2020-06-04T15:49:28 | 269,231,222 | 0 | 1 | null | 2020-06-04T15:49:29 | 2020-06-04T01:22:10 | Python | UTF-8 | Python | false | false | 328 | py | import random
class Dice:
def __init__(self, name, value):
self.name = name
self.value = value
def get_dice(self):
return random.randrange(1, int(self.value + 1))
d2 = Dice("d2", 2)
d4 = Dice("d4", 4)
d6 = Dice("d6", 6)
d8 = Dice("d8", 8)
d10 = Dice("d10", 10)
dice = [d2, d4, d6, d8, d10]
| [
"noreply@github.com"
] | gahlm.noreply@github.com |
c51225515680be1d025e75852fbe272c51510692 | b40d57de3d06884822f9b4e7dee0c07bdb00ab29 | /ENV/bin/python-config | 518fa5a69982e217531e5a743f74856432984435 | [] | no_license | chrislupdx/URLshort | 44dc562cd3abd0eac3614f9472e6e87e0cd07462 | b74a0abcfc9091fd5469d6973df38040c39300c7 | refs/heads/master | 2020-03-26T06:45:52.837644 | 2018-10-29T20:47:07 | 2018-10-29T20:47:07 | 144,620,878 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,344 | #!/home/egh/Homework/URL/ENV/bin/python
import sys
import getopt
import sysconfig
valid_opts = ['prefix', 'exec-prefix', 'includes', 'libs', 'cflags',
'ldflags', 'help']
if sys.version_info >= (3, 2):
valid_opts.insert(-1, 'extension-suffix')
valid_opts.append('abiflags')
if sys.version_info >= (3, 3):
valid_opts.append('configdir')
def exit_with_usage(code=1):
sys.stderr.write("Usage: {0} [{1}]\n".format(
sys.argv[0], '|'.join('--'+opt for opt in valid_opts)))
sys.exit(code)
try:
opts, args = getopt.getopt(sys.argv[1:], '', valid_opts)
except getopt.error:
exit_with_usage()
if not opts:
exit_with_usage()
pyver = sysconfig.get_config_var('VERSION')
getvar = sysconfig.get_config_var
opt_flags = [flag for (flag, val) in opts]
if '--help' in opt_flags:
exit_with_usage(code=0)
for opt in opt_flags:
if opt == '--prefix':
print(sysconfig.get_config_var('prefix'))
elif opt == '--exec-prefix':
print(sysconfig.get_config_var('exec_prefix'))
elif opt in ('--includes', '--cflags'):
flags = ['-I' + sysconfig.get_path('include'),
'-I' + sysconfig.get_path('platinclude')]
if opt == '--cflags':
flags.extend(getvar('CFLAGS').split())
print(' '.join(flags))
elif opt in ('--libs', '--ldflags'):
abiflags = getattr(sys, 'abiflags', '')
libs = ['-lpython' + pyver + abiflags]
libs += getvar('LIBS').split()
libs += getvar('SYSLIBS').split()
# add the prefix/lib/pythonX.Y/config dir, but only if there is no
# shared library in prefix/lib/.
if opt == '--ldflags':
if not getvar('Py_ENABLE_SHARED'):
libs.insert(0, '-L' + getvar('LIBPL'))
if not getvar('PYTHONFRAMEWORK'):
libs.extend(getvar('LINKFORSHARED').split())
print(' '.join(libs))
elif opt == '--extension-suffix':
ext_suffix = sysconfig.get_config_var('EXT_SUFFIX')
if ext_suffix is None:
ext_suffix = sysconfig.get_config_var('SO')
print(ext_suffix)
elif opt == '--abiflags':
if not getattr(sys, 'abiflags', None):
exit_with_usage()
print(sys.abiflags)
elif opt == '--configdir':
print(sysconfig.get_config_var('LIBPL'))
| [
"christopherlu.pdx@gmail.com"
] | christopherlu.pdx@gmail.com | |
a35cbfcc66192e32df195659da657709620feccb | f4271f87915f2ce7f0906801485b41a67790ce59 | /cart/urls.py | c05d0b8d3b29a15683bce11264f1b6d0383afc9e | [] | no_license | ikeyurp/Courseily | 388560a85d6f4dcee767c01246bb8974ddf65949 | cd0c0be78c0a0061615951fbbac5e2c594741765 | refs/heads/main | 2023-03-19T05:29:56.486841 | 2021-03-14T18:30:32 | 2021-03-14T18:30:32 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 338 | py | from django.urls import path
from . import views
app_name = 'cart'
urlpatterns = [
path('', views.cart_detail, name='cart_detail'),
path('add/<slug:slug>/', views.cart_add, name='cart_add'),
path('remove/<slug:slug>', views.cart_remove, name='cart_remove'),
path('checkout', views.cart_checkout, name='cart_checkout'),
] | [
"keyurbhut12345@gmail.com"
] | keyurbhut12345@gmail.com |
5bceb0d3f3d2d2bd9a515aaf742430e092604d10 | 4d496a62949c25a4c5eabfc617d25d8f6bfbc713 | /Aula 7 Funções e Métodos.py | 32d749fdf169ab3480aa296823536d91fbf25579 | [] | no_license | Jhonnylibra/Aprendendo-Python | 57bede8a48e93f876353f36a5fe55533b72a0440 | fa03dbd688d9e2928f40275773c7a9e854ba1f3f | refs/heads/main | 2023-05-12T17:40:50.406002 | 2021-05-31T00:11:52 | 2021-05-31T00:11:52 | 367,945,375 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 589 | py |
class Calculadora:
def __init__(self, num1, num2):
self.valor_a = num1
self.valor_b = num2
# Funções retornam valores
def soma(self):
return self.valor_a + self.valor_b
def subtracao(self):
return self.valor_a - self.valor_b
def multip(self):
return self.valor_a * self.valor_b
def divisao(self):
return self.valor_a / self.valor_b
calculo = Calculadora (10,2)
print(calculo.valor_a)
print(calculo.soma())
print(calculo.subtracao())
print(calculo.multip())
print(calculo.divisao())
| [
"noreply@github.com"
] | Jhonnylibra.noreply@github.com |
16fe7899fdb89976f298c7e6c833803990bebb7f | e13584adb4d99aa355de6b4674d01e819a874b59 | /env/bin/python-config | c7510464bb7ec892148c05d85b1b771877a85b08 | [] | no_license | monetree/algoscale | d6a4b66c50faf6529a74301513ca42a9492b07d0 | 86b7fb4e8ea22fb84d64e2703905ab95bde827f3 | refs/heads/master | 2020-03-30T10:35:26.528734 | 2018-10-01T17:17:24 | 2018-10-01T17:17:24 | 151,126,850 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,355 | #!/home/soubhagya/Desktop/algoscale/env/bin/python
import sys
import getopt
import sysconfig
valid_opts = ['prefix', 'exec-prefix', 'includes', 'libs', 'cflags',
'ldflags', 'help']
if sys.version_info >= (3, 2):
valid_opts.insert(-1, 'extension-suffix')
valid_opts.append('abiflags')
if sys.version_info >= (3, 3):
valid_opts.append('configdir')
def exit_with_usage(code=1):
sys.stderr.write("Usage: {0} [{1}]\n".format(
sys.argv[0], '|'.join('--'+opt for opt in valid_opts)))
sys.exit(code)
try:
opts, args = getopt.getopt(sys.argv[1:], '', valid_opts)
except getopt.error:
exit_with_usage()
if not opts:
exit_with_usage()
pyver = sysconfig.get_config_var('VERSION')
getvar = sysconfig.get_config_var
opt_flags = [flag for (flag, val) in opts]
if '--help' in opt_flags:
exit_with_usage(code=0)
for opt in opt_flags:
if opt == '--prefix':
print(sysconfig.get_config_var('prefix'))
elif opt == '--exec-prefix':
print(sysconfig.get_config_var('exec_prefix'))
elif opt in ('--includes', '--cflags'):
flags = ['-I' + sysconfig.get_path('include'),
'-I' + sysconfig.get_path('platinclude')]
if opt == '--cflags':
flags.extend(getvar('CFLAGS').split())
print(' '.join(flags))
elif opt in ('--libs', '--ldflags'):
abiflags = getattr(sys, 'abiflags', '')
libs = ['-lpython' + pyver + abiflags]
libs += getvar('LIBS').split()
libs += getvar('SYSLIBS').split()
# add the prefix/lib/pythonX.Y/config dir, but only if there is no
# shared library in prefix/lib/.
if opt == '--ldflags':
if not getvar('Py_ENABLE_SHARED'):
libs.insert(0, '-L' + getvar('LIBPL'))
if not getvar('PYTHONFRAMEWORK'):
libs.extend(getvar('LINKFORSHARED').split())
print(' '.join(libs))
elif opt == '--extension-suffix':
ext_suffix = sysconfig.get_config_var('EXT_SUFFIX')
if ext_suffix is None:
ext_suffix = sysconfig.get_config_var('SO')
print(ext_suffix)
elif opt == '--abiflags':
if not getattr(sys, 'abiflags', None):
exit_with_usage()
print(sys.abiflags)
elif opt == '--configdir':
print(sysconfig.get_config_var('LIBPL'))
| [
"soubhagyakumar666@gmail.com"
] | soubhagyakumar666@gmail.com | |
a7a100d9fb9ff8d513977a88dd73613b8130d2ad | feecc591c08bf23f1ff78826549d326dd53d1f20 | /run_sampling_fixed_parameters.py | 3a34f23e01eea7a865c1bf7b58d87cf3d919d355 | [] | no_license | LoLab-MSM/CORM | cd732615021ef19c9f8ad89447acdcb8e7f14b83 | 71630627eb1e1afa80bd449acb8fde026ca2d6c0 | refs/heads/master | 2022-11-24T03:24:12.858546 | 2017-02-28T20:17:49 | 2017-02-28T20:17:49 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,620 | py | # -*- coding: utf-8 -*-
"""
Created on Wed Mar 23 16:58:34 2016
@author: Erin
"""
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 9 15:26:46 2014
@author: Erin
"""
from core import run_dream
from pysb.integrate import Solver
import numpy as np
from parameters import NormalParam
from scipy.stats import norm
import pysb
from corm import model as cox2_model
#pysb.integrate.weave_inline = None
#Initialize PySB solver object for simulations
tspan = np.linspace(0,10, num=100)
solver = Solver(cox2_model, tspan)
#Add import of experimental data here
#location = '/Users/Erin/git/COX2/exp_data/'
location= '/home/shockle/COX2_kinetics/exp_data'
exp_data_PG = np.loadtxt(location+'exp_data_pg.txt')
exp_data_PGG = np.loadtxt(location+'exp_data_pgg.txt')
exp_data_sd_PG = np.loadtxt(location+'exp_data_sd_pg.txt')
exp_data_sd_PGG = np.loadtxt(location+'exp_data_sd_pgg.txt')
#Experimental starting values of AA and 2-AG (all in microM)
exp_cond_AA = [0, .5, 1, 2, 4, 8, 16]
exp_cond_AG = [0, .5, 1, 2, 4, 8, 16]
#Experimentally measured parameter values
KD_AA_cat1 = np.log10(cox2_model.parameters['kr_AA_cat1'].value/cox2_model.parameters['kf_AA_cat1'].value)
kcat_AA1 = np.log10(cox2_model.parameters['kcat_AA1'].value)
KD_AG_cat1 = np.log10(cox2_model.parameters['kr_AG_cat1'].value/cox2_model.parameters['kf_AG_cat1'].value)
kcat_AG1 = np.log10(cox2_model.parameters['kcat_AG1'].value)
KD_AG_allo3 = np.log10(cox2_model.parameters['kr_AG_allo3'].value/cox2_model.parameters['kf_AG_allo3'].value)
kf_idxs = [i for i, param in enumerate(cox2_model.parameters) if 'kf' in param.name]
#generic kf in units of inverse microM*s (matches model units)
generic_kf = np.log10(1.5e4)
#Frozen probability distributions for likelihoods
like_PGs = norm(loc=exp_data_PG, scale=exp_data_sd_PG)
like_PGGs = norm(loc=exp_data_PGG, scale=exp_data_sd_PGG)
like_thermobox = norm(loc=1, scale=1e-2)
pysb_sampled_parameter_names = ['kr_AA_cat2', 'kcat_AA2', 'kr_AA_cat3', 'kcat_AA3', 'kr_AG_cat2', 'kr_AG_cat3', 'kcat_AG3', 'kr_AA_allo1', 'kr_AA_allo2', 'kr_AA_allo3', 'kr_AG_allo1', 'kr_AG_allo2']
kfs_to_change = ['kf_AA_cat2', 'kf_AA_cat3', 'kf_AG_cat2', 'kf_AG_cat3', 'kf_AA_allo1', 'kf_AA_allo2', 'kf_AA_allo3', 'kf_AG_allo1', 'kf_AG_allo2']
kf_idxs = [i for i, param in enumerate(cox2_model.parameters) if param.name in kfs_to_change]
print 'kf idxs: ',kf_idxs
#Likelihood function to generate simulated data that corresponds to experimental time points
def likelihood(parameter_vector):
#print 'model parameters before subbing: ',cox2_model.parameters
param_dict = {pname: pvalue for pname, pvalue in zip(pysb_sampled_parameter_names, parameter_vector)}
#print 'param dict: ',param_dict
for pname, pvalue in param_dict.items():
#Sub in parameter values at current location in parameter space
if 'kr' in pname:
cox2_model.parameters[pname].value = 10**(pvalue + generic_kf)
elif 'kcat' in pname:
cox2_model.parameters[pname].value = 10**pvalue
#print 'model parameters after subbing: ',cox2_model.parameters
PG_array = np.zeros((7,7), dtype='float64')
PGG_array = np.zeros((7,7), dtype='float64')
arr_row = 0
arr_col = 0
#Simulate and fill in arrays
for AA_init in exp_cond_AA:
for AG_init in exp_cond_AA:
cox2_model.parameters['AA_0'].value = AA_init
cox2_model.parameters['AG_0'].value = AG_init
solver.run()
PG_array[arr_row, arr_col] = solver.yobs['obsPG'][-1]
PGG_array[arr_row, arr_col] = solver.yobs['obsPGG'][-1]
if arr_col < 6:
arr_col += 1
else:
arr_col = 0
arr_row += 1
#mBid_pdf_pt = (sim_mBid - exp_data['norm_ICRP'])/mBid_sd
# np.log((np.exp(-(mBid_pdf_pt**2)/2)/(np.sqrt(2*np.pi)*mBid_sd)))
#pg_pdf_pt = (PG_array - exp_data_PG)/exp_data_sd_PG
#logp_PG_2 = np.sum(np.log((np.exp(-(pg_pdf_pt**2)/2)/np.sqrt(2*np.pi)*exp_data_sd_PG)))
#pgg_pdf_pt = (PGG_array - exp_data_PGG)/exp_data_sd_PGG
#logp_PGG_2 = np.sum(np.log((np.exp(-(pgg_pdf_pt**2)/2)/np.sqrt(2*np.pi)*exp_data_sd_PGG)))
logp_PG = np.sum(like_PGs.logpdf(PG_array))
logp_PGG = np.sum(like_PGGs.logpdf(PGG_array))
box1 = (1/(10**KD_AA_cat1))*(1/(10**param_dict['kr_AA_allo2']))*(10**param_dict['kr_AA_cat3'])*(10**param_dict['kr_AA_allo1'])
box2 = (1/(10**param_dict['kr_AA_allo1']))*(1/(10**param_dict['kr_AG_cat3']))*(10**param_dict['kr_AA_allo3'])*(10**KD_AG_cat1)
box3 = (1/(10**param_dict['kr_AG_allo1']))*(1/(10**param_dict['kr_AA_cat2']))*(10**param_dict['kr_AG_allo2'])*(10**KD_AA_cat1)
box4 = (1/(10**KD_AG_cat1))*(1/(10**KD_AG_allo3))*(10**param_dict['kr_AG_cat2'])*(10**param_dict['kr_AG_allo1'])
#box_pdf_pt = (box1 - 1)/1e-2
#logp_box1_2 = np.sum(np.log((np.exp(-(box_pdf_pt**2)/2)/np.sqrt(2*np.pi)*1e-2)))
logp_box1 = like_thermobox.logpdf(box1)
logp_box2 = like_thermobox.logpdf(box2)
logp_box3 = like_thermobox.logpdf(box3)
logp_box4 = like_thermobox.logpdf(box4)
#print 'logps: ',logp_PG,logp_PGG,logp_box1, logp_box2, logp_box3, logp_box4
#print 'logps 2: ',logp_PG_2, logp_PGG_2, logp_box1_2
total_logp = logp_PG + logp_PGG + logp_box1 + logp_box2 + logp_box3 + logp_box4
if np.isnan(total_logp):
total_logp = -np.inf
return total_logp
# Add PySB rate parameters as unobserved random variables
kd_AA_cat2 = NormalParam('KD_AA_cat2', value = 1, mu=np.log10(cox2_model.parameters['kr_AA_cat2'].value/cox2_model.parameters['kf_AA_cat2'].value), sd=1.5)
kcat_AA2 = NormalParam('kcat_AA2', value = 1, mu=np.log10(cox2_model.parameters['kcat_AA2'].value), sd=.66)
kd_AA_cat3 = NormalParam('KD_AA_cat3', value = 1, mu=np.log10(cox2_model.parameters['kr_AA_cat3'].value/cox2_model.parameters['kf_AA_cat3'].value), sd=1.5)
kcat_AA3 = NormalParam('kcat_AA3', value = 1, mu=np.log10(cox2_model.parameters['kcat_AA1'].value), sd=.66)
kd_AG_cat2 = NormalParam('KD_AG_cat2', value = 1, mu=np.log10(cox2_model.parameters['kr_AG_cat2'].value/cox2_model.parameters['kf_AG_cat2'].value), sd=1.5)
kd_AG_cat3 = NormalParam('KD_AG_cat3', value = 1, mu=np.log10(cox2_model.parameters['kr_AG_cat3'].value/cox2_model.parameters['kf_AG_cat3'].value), sd=1.5)
kcat_AG3 = NormalParam('kcat_AG3', value = 1, mu=np.log10(cox2_model.parameters['kcat_AG3'].value), sd=.66)
kd_AA_allo1 = NormalParam('KD_AA_allo1', value = 1, mu=np.log10(cox2_model.parameters['kr_AA_allo1'].value/cox2_model.parameters['kf_AA_allo1'].value), sd=1)
kd_AA_allo2 = NormalParam('KD_AA_allo2', value = 1, mu=np.log10(cox2_model.parameters['kr_AA_allo2'].value/cox2_model.parameters['kf_AA_allo2'].value), sd=1)
kd_AA_allo3 = NormalParam('KD_AA_allo3', value = 1, mu=np.log10(cox2_model.parameters['kr_AA_allo3'].value/cox2_model.parameters['kf_AA_allo3'].value), sd=1)
kd_AG_allo1 = NormalParam('KD_AG_allo1', value = 1, mu=np.log10(cox2_model.parameters['kr_AG_allo1'].value/cox2_model.parameters['kf_AG_allo1'].value), sd=1)
kd_AG_allo2 = NormalParam('KD_AG_allo2', value = 1, mu=np.log10(cox2_model.parameters['kr_AG_allo2'].value/cox2_model.parameters['kf_AG_allo2'].value), sd=1)
sampled_parameter_names = [kd_AA_cat2, kcat_AA2, kd_AA_cat3, kcat_AA3, kd_AG_cat2, kd_AG_cat3, kcat_AG3, kd_AA_allo1, kd_AA_allo2, kd_AA_allo3, kd_AG_allo1, kd_AG_allo2]
for param in sampled_parameter_names:
print 'param.mu: ',param.mu,' and standard deviation: ',param.sd
nchains = 5
#starts = np.zeros((5, 12))
#for chain in range(len(old_results[0:5])):
# for param_name in pysb_sampled_parameter_names:
# new_dim = new_ordering_dict[param_name]
# old_dim = old_ordering_dict[param_name]
# starts[chain][new_dim] = old_results[chain][old_dim]
#print 'starts: ',starts
#start_val = [param.mu for param in sampled_parameter_names]
#starts = start_val + (np.random.random((nchains, len(start_val)))*.01)
#starts = [np.array([param.mu for param in sampled_parameter_names]) for i in range(5)]
for idx in kf_idxs:
cox2_model.parameters[idx].value = 10**generic_kf
sampled_params, log_ps = run_dream(sampled_parameter_names, likelihood, niterations=20000, nchains=nchains, multitry=False, gamma_levels=4, adapt_gamma=True, history_thin=1, model_name='corm_dreamzs_5chain_redo', verbose=True)
for chain in range(len(sampled_params)):
np.save('corm_dreamzs_5chain_redo_sampled_params_chain_'+str(chain), sampled_params[chain])
np.save('corm_dreamzs_5chain_redo_logps_chain_'+str(chain), log_ps[chain]) | [
"erin.shockley@vanderbilt.edu"
] | erin.shockley@vanderbilt.edu |
0f6141d3b2eed8a6a8945815a306d2ecf31c065d | 05723c953a5ce5392c9db0210e4cfe13a1621e1c | /src/server.py | eca7891b271a408fcb0db35dd74c45c107ac4b50 | [
"MIT"
] | permissive | Shicheng-Guo/recountmethylation_server | 269bac8c81e7fbeb67a828ccd62294bded6f2b6a | e7cfaaca431f1b063c3ed2715f62de0a06845448 | refs/heads/master | 2023-06-16T02:57:03.050080 | 2021-07-08T17:49:47 | 2021-07-08T17:49:47 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 9,014 | py | #!/usr/bin/env python3
""" server.py
Authors: Sean Maden, Abhinav Nellore
Description:
Server script to manage an instance of the recount-methylation database.
Overview:
A recount-methylation instance consists of files (namely edirect query
results, experiment metadata in soft format, and methylation array intensity
data or 'idat' files) obtained from edirect queries and ftp-called downloads
from the Gene Expression Omnibus (GEO). RMDB is a recount-methylation Mongo
database that aggregates file metadata as documents, including experiement
(GSE) and sample (GSM) IDs, ftp addresses and file paths to downloaded
files, and a datetime-formatted date corresponding to last file update.
Files are versioned using NTP timestamps in filenames.
For best results, we recommend users attempt an initial setup of their
recount-methylation instance using default generated directory trees and
filenames, and do not directly change locations or names of files initially
downloaded.
Server Processes:
The server.py script manages process queues, error handling, and
coordination of recount-methylation. It currently uses Celery distributed
task queue to queue jobs synchronously. Jobs are brokered using RabbitMQ,
and queue details are backed up locally in a SQLite db. It is recommend you
consult the SQLite backend database for details about interruptions to
server operations.
Dependencies and Setup:
1. Recount-methylation primarily uses Python 3 for download handling and
file management. R is used for SOFT-to-JSON conversion, and for
preprocessing arrays. MetaSRA-pipeline, which runs using Python 2, is
used for mapping experiment metadata to ENCODE ontology terms, and we
recommend installing a fork of the original repo (available here:
<https://github.com/metamaden/MetaSRA-pipeline>).
2. Clone the recount-methylation-server repo from GitHub (available here:
<>).
3. To run recount-methylation server.py, follow all provided setup and
readme instructions. Also ensure the following resources are installed
and running:
* Celery (http://www.celeryproject.org/)
* RabbitMQ (https://www.rabbitmq.com/)
* MongoDB (https://www.mongodb.com/)
* SQLite (https://www.sqlite.org/)
"""
import subprocess, glob, sys, os, re
sys.path.insert(0, os.path.join("recountmethylation_server","src"))
import edirect_query, settings; settings.init()
from edirect_query import gsm_query, gse_query, gsequery_filter
from utilities import gettime_ntp, getlatest_filepath, querydict
from utilities import get_queryfilt_dict
def firsttime_run(filedir='recount-methylation-files',
run_timestamp=gettime_ntp()):
""" firsttime_run
On first setup, run new equeries and query filter.
Arguments:
* filedir (str): Dir name for db files.
* run_timestamp (str) : NTP timestamp or function to retrieve it.
Returns:
* gseidlist (list): List of valid GSE IDs.
"""
print("Beginning first time server run...")
equery_dest = settings.equerypath; temppath = settings.temppath
gse_query(); gsm_query()
gseqfile = getlatest_filepath(equery_dest,'gse_edirectquery')
gsmqfile = getlatest_filepath(equery_dest,'gsm_edirectquery')
gsequery_filter()
gsefiltpath = getlatest_filepath(equery_dest,'gsequery_filt')
if gsefiltpath:
gsefiltd = querydict(querypath=gsefiltpath,splitdelim=' ')
gseidlist = list(gsefiltd.keys())
print("GSE id list of len "+str(len(gseidlist))+" found. Returning...")
return gseidlist
else:
print("Error retrieving gse query filtered file. Returning...")
return None
return None
def scheduled_run(eqfilt_path=False, run_timestamp=gettime_ntp()):
""" scheduled_run
Tasks performed on regular schedule, after first setup. For the job
queue, a list of GSE IDs is returned. The id list is filtered on
existing GSE soft files to prioritize unrepresented experiments for
download.
Arguments:
* eqfilt_path (str) : Filepath to edirect query filter file.
* filedir (str) : Root name of files directory.
* run_timestamp (str) : NTP timestamp or function to retrieve it.
Returns:
* gse_list (list) : list of valid GSE IDs, or None if error occurs
"""
try:
gsefiltd = get_queryfilt_dict()
except:
print("No gse query filt file found, checking for GSE and GSM "
+"queries...")
gsequery_latest = getlatest_filepath(filepath=eqpath,
filestr='gse_edirectquery')
if not gsequery_latest:
gse_query()
gsmquery_latest = getlatest_filepath(eqpath,'gsm_edirectquery')
if not gsmquery_latest:
gsm_query()
print("Running filter on GSE query...")
gsequery_filter(); gsefiltd = get_queryfilt_dict()
# get list of GSE IDs from existing SOFT files
gsesoftfiles = os.listdir(settings.gsesoftpath)
print("GSE SOFT files: " + str(gsesoftfiles));rxgse=re.compile('GSE[0-9]*')
gseid_softexists = [str(rxgse.findall(softfn)[0]) for softfn in gsesoftfiles
if rxgse.findall(softfn)]
if gsefiltd:
gseid_listall = list(gsefiltd.keys())
print("GSE ID list of len "+str(len(gseid_listall)) + " found. Filtering..")
if gseid_softexists and len(gseid_softexists)>0:
gseid_filt = [gseid for gseid in gseid_listall
if not gseid in gseid_softexists]
else:
gseid_filt = gseid_listall
print("After filtering existing SOFT files, N = "+str(len(gseid_filt))
+" GSE IDs remain. Returning ID list...")
# if all GSE IDs represented, return all GSE IDs for brand new run
if len(gseid_filt)==len(gseid_listall):
gseid_filt = gseid_listall
return gseid_filt
else:
print("Error forming equery filt dictionary. Returning...")
return None
if __name__ == "__main__":
""" Recount-methylation sever server.py main
Code addresses various contingencies precluding generation of GSE ID
list. Once list can be made, it is used to populate a new Celery queue.
"""
print("Starting server.py..."); import subprocess, glob, sys, os, re
sys.path.insert(0, os.path.join("recountmethylation_server","src"))
import edirect_query, settings, argparse; settings.init()
from edirect_query import gsm_query, gse_query, gsequery_filter
from utilities import gettime_ntp, getlatest_filepath, querydict
from utilities import get_queryfilt_dict
from gse_celerytask import gse_task; from random import shuffle
gselist = [] # queue input, gse-based
qstatlist = [] # job status object, also stored at sqlite db
print("Getting timestamp...")
run_timestamp = gettime_ntp() # pass this result to child functions
# Parse the specified GSE ID.
parser = argparse.ArgumentParser(description='Arguments for server.py')
parser.add_argument("--gseid", type=str, required=False, default=None,
help='Option to enter valid GSE ID for immediate download.')
args = parser.parse_args()
# For the job queue, either from provided argument or automation
if args.gseid:
print("Provided GSE ID detected. Processing...")
gqd = get_queryfilt_dict()
qstatlist.append(gse_task(gse_id = args.gseid, gsefiltdict=gqd,
timestamp = run_timestamp))
else:
print("No GSE ID(s) provided. Forming ID list for job queue...")
files_dir = settings.filesdir
if os.path.exists(files_dir):
print("Directory : "+files_dir+" found.")
if not os.path.exists(settings.gsesoftpath):
print("Couldn't find path ",settings.gsesoftpath,
", making new dir..."); os.mkdir(settings.gsesoftpath)
print("Running scheduled_run...")
gselist = scheduled_run(run_timestamp=run_timestamp)
else:
print("Directory : "+files_dir+" not found. Creating filesdir and "
+"running firsttime_run...")
os.makedirs(files_dir, exist_ok=True)
gselist = firsttime_run(run_timestamp=run_timestamp)
if gselist:
print("Shuffling GSE ID list...")
shuffle(gselist) # randomize GSE ID order
print("Beginning job queue for GSE ID list of "+str(len(gselist))
+" samples...")
gqd = get_queryfilt_dict() # one eqfilt call for all jobs this run
for gse in gselist:
qstatlist.append(gse_task(gse_id=gse, gsefiltdict=gqd,
timestamp=run_timestamp))
else:
print("Error: valid gselist absent. Returning...") | [
"maden@ohsu.edu"
] | maden@ohsu.edu |
0a92c2795618c067dffe8514cc858a8d46a72240 | 4f88c6737240c902d1093d1bc250137aa28c3669 | /Hangman_game.py | a1f7e473ac23acf3cbdc22d67e72c729f6a03609 | [] | no_license | jaydeep283/Hangman-Game | 0a92bd540e85e428cbdb4710c2af7183097092f6 | 3e693bae05b02fb24011d9af713c57f99539fbf2 | refs/heads/main | 2023-07-05T17:23:34.040250 | 2021-08-28T15:19:36 | 2021-08-28T15:19:36 | 400,824,080 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,997 | py | # Hangman game which lets user to predict the letters from the random word chosen by program.
#For choosing word randomly
import random
#Path for text file containing all possible words.
WORDLIST_FILENAME = "words.txt"
def loadWords():
"""
Returns a list of valid words. Words are strings of lowercase letters.
"""
print("Loading word list from file...")
# inFile: file
inFile = open(WORDLIST_FILENAME, 'r')
# line: string
line = inFile.readline()
# wordlist: list of strings
wordlist = line.split()
print(" ", len(wordlist), "words loaded.")
return wordlist
def chooseWord(wordlist):
"""
wordlist (list): list of words (strings)
Returns a word from wordlist at random
"""
return random.choice(wordlist)
# Loading the list of words into the variable wordlist
# so that it can be accessed from anywhere in the program
wordlist = loadWords()
def isWordGuessed(secretWord, lettersGuessed):
'''
secretWord: string, the word the user is guessing
lettersGuessed: list, what letters have been guessed so far
returns: boolean, True if all the letters of secretWord are in lettersGuessed;
False otherwise
'''
sw_len = len(secretWord)
lg_len = len(lettersGuessed)
corr_guess = 0
for x in secretWord:
if x in lettersGuessed:
corr_guess = corr_guess + 1
if corr_guess == sw_len:
return True
else:
return False
def getGuessedWord(secretWord, lettersGuessed):
'''
secretWord: string, the word the user is guessing
lettersGuessed: list, what letters have been guessed so far
returns: string, comprised of letters and underscores that represents
what letters in secretWord have been guessed so far.
'''
g_str = ''
for x in secretWord:
if x in lettersGuessed:
g_str = g_str + x
else:
g_str = g_str + '_ '
return g_str
import string
def getAvailableLetters(lettersGuessed):
'''
lettersGuessed: list, what letters have been guessed so far
returns: string, comprised of letters that represents what letters have not
yet been guessed.
'''
avl_lett = ''
for x in string.ascii_lowercase:
if x not in lettersGuessed:
avl_lett = avl_lett + x
return avl_lett
def hangman(secretWord):
'''
secretWord: string, the secret word to guess.
Start of an interactive game of Hangman.
* At the start of the game, it shows how many letters are there in secret word.
* Asks the user to supply one guess (i.e. letter) per round.
* The user receives feedback immediately after each guess
about whether their guess appears in the computers word.
* After each round, it displays to the user the
partially guessed word so far, as well as letters that the
user has not yet guessed.
'''
print("Welcome to the game Hangman!")
len_sec_word = len(secretWord)
print("I am thinking of a word that is", len_sec_word, "letters long.")
print("________________________")
tot_guesses = 8 #Tracks the life i.e how many more times user can guess incorrect letter
mistakes_Made = 0
lettersGuessed = [] #Stores the letters guessed so far by the user.
avl_letters = getAvailableLetters(lettersGuessed)
while tot_guesses > 0:
print("You have", tot_guesses, "guesses left.")
print("Available letters: ", getAvailableLetters(lettersGuessed))
guess = input("Please guess a letter: ")
guess_lowercase = guess.lower()
if guess_lowercase in secretWord and guess_lowercase not in lettersGuessed:
lettersGuessed.append(guess_lowercase)
print("Good guess: ", getGuessedWord(secretWord, lettersGuessed))
elif guess_lowercase in secretWord and guess_lowercase in lettersGuessed:
print("Oops! You've already guessed that letter: ", getGuessedWord(secretWord, lettersGuessed))
else:
if guess_lowercase in lettersGuessed:
print("Oops! You've already guessed that letter: ", getGuessedWord(secretWord, lettersGuessed))
else:
print("Oops! That letter is not in my word: ", getGuessedWord(secretWord, lettersGuessed))
lettersGuessed.append(guess_lowercase)
tot_guesses = tot_guesses - 1
print("________________________")
if isWordGuessed(secretWord, lettersGuessed):
print("Congratulations, you won!")
break
if not isWordGuessed(secretWord, lettersGuessed):
print("Sorry, you ran out of guesses. The word was " + secretWord + ".")
# Start of the main program.
# Chooses random word and passes it to hangman function to start the game.
secretWord = chooseWord(wordlist)
hangman(secretWord)
| [
"noreply@github.com"
] | jaydeep283.noreply@github.com |
974a2d4a88ed7a61a78b987b186da95ea207fda6 | 64ada708c3ee39c624a223fa4881ce3689041606 | /Chapter3/list0303_2.py | 5aaa75fbb416c44e7ca982dafdd8633312280cfa | [] | no_license | kimcaptin/PythonGame_1 | 1173cf3ac356d29b1cb254b1607bd4528e0a28cc | af32318bf1e6ea73aa00fc4c72d07e1a5d7c5300 | refs/heads/main | 2023-01-04T05:46:02.782910 | 2020-10-28T06:53:30 | 2020-10-28T06:53:30 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 119 | py | gold = 100
if gold == 0:
print("소지금이 없습니다")
else:
print("구입을 계속하시겠습니까?")
| [
"jeipubmanager@gmail.com"
] | jeipubmanager@gmail.com |
b22322fe3489c5384a325c3f92dd5aed24dc2fdc | 1b88937115f698eaa40b3bf1f106bb5377ead4d5 | /django_base/playlist/models.py | 4f5ea70c37369e3a4cee3651a02f91c626d30e82 | [
"MIT"
] | permissive | gasbarroni8/best-channels | 259903ac6a280790e99fe5331570edd672027f59 | f82a9b51be6292945e3d4ef2cd2702ac4fdbe0cf | refs/heads/master | 2020-11-30T05:31:32.184496 | 2019-09-10T01:01:20 | 2019-09-10T01:01:20 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 861 | py | from django.db import models
from inner.models import Inner
class Playlist(models.Model):
HOT = 'hot'
NEW = 'new'
PLAYLIST_TYPE = (
(HOT, 'hot'),
(NEW, 'new'),
)
inner = models.ForeignKey(
Inner, related_name="playlist", on_delete=models.CASCADE)
channel_id = models.CharField(max_length=100, unique=True)
channel_title = models.CharField(max_length=200, unique=True, blank=True)
description = models.CharField(max_length=200, blank=True)
type = models.CharField(
max_length=10,
choices=PLAYLIST_TYPE,
default=HOT)
email = models.CharField(max_length=100, blank=True)
create_time = models.DateTimeField(auto_now_add=True)
update_time = models.DateTimeField(auto_now=True)
def __str__(self):
return self.channel_title + ' ---- ' + self.inner.name
| [
"wiwindson@outlook.com"
] | wiwindson@outlook.com |
0889868667158ce67e7e7dff2559b9c9c4e29d70 | f02cca2785c16a18e05fb9ccee40341c48cda9ec | /getprice.py | 397320eca28c622b63e2a050559a390127488de9 | [] | no_license | joshagoldstein/binance_notifications | b53045633855b0d40cc9268a3071a755b32cf90b | d58526f4d7695f9397ef20268c82d2ebcd511a5c | refs/heads/main | 2023-05-03T10:29:24.320118 | 2021-05-08T08:37:58 | 2021-05-08T08:37:58 | 365,339,210 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,769 | py | from binance.client import Client
import time
t = time.localtime()
current_time = time.strftime("%H:%M:%S", t)
client = Client('3wfiKJWWSW42XSsSw0Y4fxm9iVHMaZeQFSyIMqn6RzAG8s33CpXW8rrr1J4TzC5m', 'o8BfTLXoa1evd5FpLn1TD1WqpRg3bGfvKSzwmta7a9T0afHe1SrEYJyb8qqSLw9w')
#Get current price of each coin
# info = client.get_all_tickers()
# symbol=[]
# for dictionaries in info:
# ticker_price= list(dictionaries.values())
# if ticker_price[0][-4:]=='USDT':
# new_val=ticker_price[0][0:-4]+'/'+'USDT'
# ticker_price[0]=new_val
# symbol.append(ticker_price)
# symbol_sort=sorted(symbol, key=lambda x: float(x[1]), reverse=True)
#for pair in symbol_sort:
#print('The coin {} is currently valued at ${}'.format(pair[0],pair[1]))
# print(symbol[0][0][:3])
info = client.get_ticker()
tick_change={}
for ind in info:
if ind['symbol'][-4:]=='USDT':
sym=ind['symbol'][0:-4]+'/'+'USDT'
percent_change=float(ind['priceChangePercent'])
tick_change[sym]=percent_change
price=ind['lastPrice']
if percent_change < -5.0 or percent_change > 5.0:
print("The coin {} has changed {}% over the past 24 hours and is currently ${} as of {}".format(sym,percent_change,price,current_time))
sorted_tick_change=sorted(tick_change.items(), key=lambda x: x[1], reverse=True)
biggest_win=sorted_tick_change[0]
biggest_loser=sorted_tick_change[-1]
print('-'*100)
print('The winner of the day is {} with a massive growth of {}%!'.format(biggest_win[0],biggest_win[1]))
print('The WOAT of the day is {} with a piss poor performance of {}%!'.format(biggest_loser[0],biggest_loser[1]))
#print(ind.keys())
#val=list(ind.values())
#print(val)
#symbol, priceChange, priceChangePercent, lastPrice,
| [
"noreply@github.com"
] | joshagoldstein.noreply@github.com |
345a0494dccef9249e506fe626e36609d43e3f4a | 9e4967f0bbe29ee3a78b1e6a1d153f2c7156be13 | /tweetnacl_pure.py | 6c073d28bf78e0eb981f2b956eb202c266828fea | [] | no_license | rofl0r/backdoor-py | 981bf3fbd2bdd07ce3fe267ff3ad109d44ed9a84 | 2b0c65b86ee8af6a154ce2dbffc18a41a5332e66 | refs/heads/master | 2021-06-28T09:10:57.078374 | 2020-10-16T22:48:52 | 2020-10-16T22:48:52 | 176,001,354 | 7 | 1 | null | null | null | null | UTF-8 | Python | false | false | 43,929 | py | # -*- coding: utf-8 -*-
"""
taken from
https://github.com/jfindlay/pure_pynacl
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import sys
import os
from array import array
if sys.version_info < (2, 6):
raise NotImplementedError('pure_pynacl requires python-2.6 or later')
lt_py3 = sys.version_info < (3,)
lt_py33 = sys.version_info < (3, 3)
integer = long if lt_py3 else int
# "constants"
crypto_auth_hmacsha512256_tweet_BYTES = 32
crypto_auth_hmacsha512256_tweet_KEYBYTES = 32
crypto_box_curve25519xsalsa20poly1305_tweet_PUBLICKEYBYTES = 32
crypto_box_curve25519xsalsa20poly1305_tweet_SECRETKEYBYTES = 32
crypto_box_curve25519xsalsa20poly1305_tweet_BEFORENMBYTES = 32
crypto_box_curve25519xsalsa20poly1305_tweet_NONCEBYTES = 24
crypto_box_curve25519xsalsa20poly1305_tweet_ZEROBYTES = 32
crypto_box_curve25519xsalsa20poly1305_tweet_BOXZEROBYTES = 16
crypto_core_salsa20_tweet_OUTPUTBYTES = 64
crypto_core_salsa20_tweet_INPUTBYTES = 16
crypto_core_salsa20_tweet_KEYBYTES = 32
crypto_core_salsa20_tweet_CONSTBYTES = 16
crypto_core_hsalsa20_tweet_OUTPUTBYTES = 32
crypto_core_hsalsa20_tweet_INPUTBYTES = 16
crypto_core_hsalsa20_tweet_KEYBYTES = 32
crypto_core_hsalsa20_tweet_CONSTBYTES = 16
crypto_hashblocks_sha512_tweet_STATEBYTES = 64
crypto_hashblocks_sha512_tweet_BLOCKBYTES = 128
crypto_hashblocks_sha256_tweet_STATEBYTES = 32
crypto_hashblocks_sha256_tweet_BLOCKBYTES = 64
crypto_hash_sha512_tweet_BYTES = 64
crypto_hash_sha256_tweet_BYTES = 32
crypto_onetimeauth_poly1305_tweet_BYTES = 16
crypto_onetimeauth_poly1305_tweet_KEYBYTES = 32
crypto_scalarmult_curve25519_tweet_BYTES = 32
crypto_scalarmult_curve25519_tweet_SCALARBYTES = 32
crypto_secretbox_xsalsa20poly1305_tweet_KEYBYTES = 32
crypto_secretbox_xsalsa20poly1305_tweet_NONCEBYTES = 24
crypto_secretbox_xsalsa20poly1305_tweet_ZEROBYTES = 32
crypto_secretbox_xsalsa20poly1305_tweet_BOXZEROBYTES = 16
crypto_sign_ed25519_tweet_BYTES = 64
crypto_sign_ed25519_tweet_PUBLICKEYBYTES = 32
crypto_sign_ed25519_tweet_SECRETKEYBYTES = 64
crypto_stream_xsalsa20_tweet_KEYBYTES = 32
crypto_stream_xsalsa20_tweet_NONCEBYTES = 24
crypto_stream_salsa20_tweet_KEYBYTES = 32
crypto_stream_salsa20_tweet_NONCEBYTES = 8
crypto_verify_16_tweet_BYTES = 16
crypto_verify_32_tweet_BYTES = 32
class TypeEnum(object):
'''
order types used by pure_py(tweet)nacl for rapid type promotion
'''
u8 = 1
u32 = 2
u64 = 3
Int = 5
i64 = 7
integer = 11
class Int(integer):
'''
int types
'''
bits = array('i').itemsize*8
mask = (1 << bits - 1) - 1
signed = True
order = TypeEnum.Int
def __str__(self):
return integer.__str__(self)
def __repr__(self):
return 'Int(%s)' % integer.__repr__(self)
def __new__(self, val=0):
'''
ensure that new instances have the correct size and sign
'''
if val < 0:
residue = integer(-val) & self.mask
if self.signed:
residue = -residue
else:
residue = integer(val) & self.mask
return integer.__new__(self, residue)
def __promote_type(self, other, result):
'''
determine the largest type from those in self and other; if result is
negative and both self and other are unsigned, promote it to the least
signed type
'''
self_order = self.order
other_order = other.order if isinstance(other, Int) else TypeEnum.integer
if result < 0 and self_order < 5 and other_order < 5:
return Int
return self.__class__ if self_order > other_order else other.__class__
def __unary_typed(oper):
'''
return a function that redefines the operation oper such that the
result conforms to the type of self
'''
def operate(self):
'''
type the result to self
'''
return self.__class__(oper(self))
return operate
def __typed(oper):
'''
return a function that redefines the operation oper such that the
result conforms to the type of self or other, whichever is larger if
both are strongly typed (have a bits attribute); otherwise return the
result conforming to the type of self
'''
def operate(self, other):
'''
type and bitmask the result to either self or other, whichever is
larger
'''
result = oper(self, other)
return self.__promote_type(other, result)(result)
return operate
def __shift(oper):
'''
return a function that performs bit shifting, but preserves the type of
the left value
'''
def operate(self, other):
'''
emulate C bit shifting
'''
return self.__class__(oper(self, other))
return operate
def __invert():
'''
return a function that performs bit inversion
'''
def operate(self):
'''
emulate C bit inversion
'''
if self.signed:
return self.__class__(integer.__invert__(self))
else:
return self.__class__(integer.__xor__(self, self.mask))
return operate
# bitwise operations
__lshift__ = __shift(integer.__lshift__)
__rlshift__ = __shift(integer.__rlshift__)
__rshift__ = __shift(integer.__rshift__)
__rrshift__ = __shift(integer.__rrshift__)
__and__ = __typed(integer.__and__)
__rand__ = __typed(integer.__rand__)
__or__ = __typed(integer.__or__)
__ror__ = __typed(integer.__ror__)
__xor__ = __typed(integer.__xor__)
__rxor__ = __typed(integer.__rxor__)
__invert__ = __invert()
# arithmetic operations
if not lt_py3:
__ceil__ = __unary_typed(integer.__ceil__)
__floor__ = __unary_typed(integer.__floor__)
__int__ = __unary_typed(integer.__int__)
__abs__ = __unary_typed(integer.__abs__)
__pos__ = __unary_typed(integer.__pos__)
__neg__ = __unary_typed(integer.__neg__)
__add__ = __typed(integer.__add__)
__radd__ = __typed(integer.__radd__)
__sub__ = __typed(integer.__sub__)
__rsub__ = __typed(integer.__rsub__)
__mod__ = __typed(integer.__mod__)
__rmod__ = __typed(integer.__rmod__)
__mul__ = __typed(integer.__mul__)
__rmul__ = __typed(integer.__rmul__)
if lt_py3:
__div__ = __typed(integer.__div__)
__rdiv__ = __typed(integer.__rdiv__)
__floordiv__ = __typed(integer.__floordiv__)
__rfloordiv__ = __typed(integer.__rfloordiv__)
__pow__ = __typed(integer.__pow__)
__rpow__ = __typed(integer.__rpow__)
class IntArray(list):
'''
arrays of int types
'''
def __init__(self, typ, init=(), size=0):
'''
create array of ints
'''
self.typ = typ
if lt_py3 and isinstance(init, bytes):
init = [ord(i) for i in init]
if size:
init_size = len(init)
if init_size < size:
list.__init__(self, [typ(i) for i in init] + [typ() for i in range(size - init_size)])
else:
list.__init__(self, [typ(i) for i in init[:size]])
else:
list.__init__(self, [typ(i) for i in init])
def __str__(self):
return list.__str__(self)
def __repr__(self):
return 'IntArray(%s, init=%s)' % (self.typ, list.__repr__(self))
class u8(Int):
'''unsigned char'''
bits = array('B').itemsize*8
mask = (1 << bits) - 1
signed = False
order = TypeEnum.u8
def __repr__(self):
return 'u8(%s)' % integer.__repr__(self)
class u32(Int):
'''unsigned long'''
bits = array('L').itemsize*8
mask = (1 << bits) - 1
signed = False
order = TypeEnum.u32
def __repr__(self):
return 'u32(%s)' % integer.__repr__(self)
class u64(Int):
'''unsigned long long'''
bits = array('L' if lt_py33 else 'Q').itemsize*8
mask = (1 << bits) - 1
signed = False
order = TypeEnum.u64
def __repr__(self):
return 'u64(%s)' % integer.__repr__(self)
class i64(Int):
'''long long'''
bits = array('l' if lt_py33 else 'q').itemsize*8
mask = (1 << bits - 1) - 1
signed = True
order = TypeEnum.i64
def __repr__(self):
return 'i64(%s)' % integer.__repr__(self)
class gf(IntArray):
def __init__(self, init=()):
IntArray.__init__(self, i64, init=init, size=16)
def randombytes(c, s):
'''
insert s random bytes into c
'''
if lt_py3:
c[:s] = bytearray(os.urandom(s))
else:
c[:s] = os.urandom(s)
_0 = IntArray(u8, size=16)
_9 = IntArray(u8, size=32, init=[9])
gf0 = gf()
gf1 = gf([1])
_121665 = gf([0xDB41, 1])
D = gf([0x78a3, 0x1359, 0x4dca, 0x75eb, 0xd8ab, 0x4141, 0x0a4d, 0x0070, 0xe898, 0x7779, 0x4079, 0x8cc7, 0xfe73, 0x2b6f, 0x6cee, 0x5203])
D2 = gf([0xf159, 0x26b2, 0x9b94, 0xebd6, 0xb156, 0x8283, 0x149a, 0x00e0, 0xd130, 0xeef3, 0x80f2, 0x198e, 0xfce7, 0x56df, 0xd9dc, 0x2406])
X = gf([0xd51a, 0x8f25, 0x2d60, 0xc956, 0xa7b2, 0x9525, 0xc760, 0x692c, 0xdc5c, 0xfdd6, 0xe231, 0xc0a4, 0x53fe, 0xcd6e, 0x36d3, 0x2169])
Y = gf([0x6658, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666, 0x6666])
I = gf([0xa0b0, 0x4a0e, 0x1b27, 0xc4ee, 0xe478, 0xad2f, 0x1806, 0x2f43, 0xd7a7, 0x3dfb, 0x0099, 0x2b4d, 0xdf0b, 0x4fc1, 0x2480, 0x2b83])
def L32(x, c):
'''static u32 L32(u32 x, int c)'''
return (u32(x) << c) | ((u32(x) & 0xffffffff) >> (32 - c))
def ld32(x):
'''u32 ld32(const u8*x)'''
u = u32(x[3])
u = (u << 8) | u32(x[2])
u = (u << 8) | u32(x[1])
return (u << 8) | u32(x[0])
def dl64(x):
'''u64 dl64(const u8*x)'''
u = u64()
for i in range(8): u = (u << 8) | u8(x[i])
return u
def st32(x, u):
'''void st32(u8*x, u32 u)'''
for i in range(4): x[i] = u8(u); u >>= 8
return x
def ts64(x, u):
'''void ts64(u8*x, u64 u)'''
for i in range(7, -1, -1): x[i] = u8(u); u >>= 8
return x
def vn(x, y, n):
'''int vn(const u8*x, const u8*y, int n)'''
d = u32()
for i in range(n): d |= x[i] ^ y[i]
return (1 & ((d - 1) >> 8)) - 1
def crypto_verify_16_tweet(x, y):
'''int crypto_verify_16_tweet(const u8*x, const u8*y)'''
return vn(x, y, 16)
def crypto_verify_32_tweet(x, y):
'''int crypto_verify_32_tweet(const u8*x, const u8*y)'''
return vn(x, y, 32)
def core(out, in_, k, c, h):
'''void core(u8*out, const u8*in, const u8*k, const u8*c, int h)'''
w = IntArray(u32, size=16)
x = IntArray(u32, size=16)
y = IntArray(u32, size=16)
t = IntArray(u32, size=4)
for i in range(4):
x[5*i] = ld32(c[4*i:])
x[1 + i] = ld32(k[4*i:])
x[6 + i] = ld32(in_[4*i:])
x[11 + i] = ld32(k[16 + 4*i:])
for i in range(16): y[i] = x[i]
for i in range(20):
for j in range(4):
for m in range(4): t[m] = x[(5*j + 4*m)%16]
t[1] ^= L32(t[0] + t[3], 7)
t[2] ^= L32(t[1] + t[0], 9)
t[3] ^= L32(t[2] + t[1],13)
t[0] ^= L32(t[3] + t[2],18)
for m in range(4): w[4*j + (j + m)%4] = t[m]
for m in range(16): x[m] = w[m]
if h:
for i in range(16): x[i] += y[i]
for i in range(4):
x[5*i] -= ld32(c[4*i:])
x[6+i] -= ld32(in_[4*i:])
for i in range(4):
out[4*i:] = st32(out[4*i:], x[5*i])
out[16 + 4*i:] = st32(out[16 + 4*i:], x[6 + i])
else:
for i in range(16):
out[4*i:] = st32(out[4*i:], x[i] + y[i])
def crypto_core_salsa20_tweet(out, in_, k, c):
'''int crypto_core_salsa20_tweet(u8*out, const u8*in, const u8*k, const u8*c)'''
core(out, in_, k, c, False)
return 0
def crypto_core_hsalsa20_tweet(out, in_, k, c):
'''int crypto_core_hsalsa20_tweet(u8*out, const u8*in, const u8*k, const u8*c)'''
core(out, in_, k, c, True)
return 0
sigma = IntArray(u8, size=16, init=b'expand 32-byte k')
def crypto_stream_salsa20_tweet_xor(c, m, b, n, k):
'''int crypto_stream_salsa20_tweet_xor(u8*c, const u8*m, u64 b, const u8*n, const u8*k)'''
z = IntArray(u8, size=16)
x = IntArray(u8, size=64)
if not b: return 0
for i in range(8): z[i] = n[i]
c_off = 0 ; m_off = 0
while b >= 64:
crypto_core_salsa20_tweet(x, z, k, sigma)
for i in range(64): c[i + c_off] = (m[i + m_off] if m else 0) ^ x[i]
u = u32(1)
for i in range(8, 16):
u += u32(z[i])
z[i] = u
u >>= 8
b -= 64
c_off += 64
if m: m_off += 64
if b:
crypto_core_salsa20_tweet(x, z, k, sigma)
for i in range(b): c[i + c_off] = (m[i + m_off] if m else 0) ^ x[i]
return 0
def crypto_stream_salsa20_tweet(c, d, n, k):
'''int crypto_stream_salsa20_tweet(u8*c, u64 d, const u8*n, const u8*k)'''
return crypto_stream_salsa20_tweet_xor(c, IntArray(u8), d, n, k)
def crypto_stream_xsalsa20_tweet(c, d, n, k):
'''int crypto_stream_xsalsa20_tweet(u8*c, u64 d, const u8*n, const u8*k)'''
s = IntArray(u8, size=32)
crypto_core_hsalsa20_tweet(s, n, k, sigma)
return crypto_stream_salsa20_tweet(c, d, n[16:], s)
def crypto_stream_xsalsa20_tweet_xor(c, m, d, n, k):
'''int crypto_stream_xsalsa20_tweet_xor(u8*c, const u8*m, u64 d, const u8*n, const u8*k)'''
s = IntArray(u8, size=32)
crypto_core_hsalsa20_tweet(s, n, k, sigma)
return crypto_stream_salsa20_tweet_xor(c, m, d, n[16:], s)
def add1305(h, c):
'''void add1305(u32*h, const u32*c)'''
u = u32()
for j in range(17):
u += u32(h[j] + c[j])
h[j] = u & 255
u >>= 8
minusp = IntArray(u32, size=17, init=(5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 252))
def crypto_onetimeauth_poly1305_tweet(out, m, n, k):
'''int crypto_onetimeauth_poly1305_tweet(u8*out, const u8*m, u64 n, const u8*k)'''
s = u32()
u = u32()
x = IntArray(u32, size=17)
r = IntArray(u32, size=17)
h = IntArray(u32, size=17)
c = IntArray(u32, size=17)
g = IntArray(u32, size=17)
for j in range(16): r[j] = k[j]
r[3] &= 15
r[4] &= 252
r[7] &= 15
r[8] &= 252
r[11] &= 15
r[12] &= 252
r[15] &= 15
while n > 0:
c[:17] = 17*[u32()]
for j in range(16):
if j >= n: j -= 1 ; break
c[j] = m[j]
j += 1
c[j] = 1
m = m[j:]; n -= j
add1305(h, c)
for i in range(17):
x[i] = 0
for j in range(17): x[i] += h[j]*(r[i - j] if j <= i else 320*r[i + 17 - j])
for i in range(17): h[i] = x[i]
u = 0
for j in range(16):
u += h[j]
h[j] = u & 255
u >>= 8
u += h[16]; h[16] = u & 3
u = 5*(u >> 2)
for j in range(16):
u += h[j]
h[j] = u & 255
u >>= 8
u += h[16]; h[16] = u
for j in range(17): g[j] = h[j]
add1305(h, minusp)
s = -(h[16] >> 7)
for j in range(17): h[j] ^= s & (g[j] ^ h[j])
for j in range(16): c[j] = k[j + 16]
c[16] = 0
add1305(h, c)
for j in range(16): out[j] = h[j]
return 0
def crypto_onetimeauth_poly1305_tweet_verify(h, m, n, k):
'''int crypto_onetimeauth_poly1305_tweet_verify(const u8*h, const u8*m, u64 n, const u8*k)'''
x = IntArray(u8, size=16)
crypto_onetimeauth_poly1305_tweet(x, m, n, k)
return crypto_verify_16_tweet(h, x)
def crypto_secretbox_xsalsa20poly1305_tweet(c, m, d, n, k):
'''int crypto_secretbox_xsalsa20poly1305_tweet(u8*c, const u8*m, u64 d, const u8*n, const u8*k)'''
if d < 32: return -1
crypto_stream_xsalsa20_tweet_xor(c, m, d, n, k)
c_out = c[16:]
crypto_onetimeauth_poly1305_tweet(c_out, c[32:], d - 32, c)
c[16:] = c_out
c[:16] = 16*[u8()]
return 0
def crypto_secretbox_xsalsa20poly1305_tweet_open(m, c, d, n, k):
'''int crypto_secretbox_xsalsa20poly1305_tweet_open(u8*m, const u8*c, u64 d, const u8*n, const u8*k)'''
x = IntArray(u8, size=32)
if d < 32: return -1
crypto_stream_xsalsa20_tweet(x, 32, n, k)
if crypto_onetimeauth_poly1305_tweet_verify(c[16:], c[32:], d - 32, x) != 0: return -1
crypto_stream_xsalsa20_tweet_xor(m, c, d, n, k)
m[:32] = 32*[u8()]
return 0
def set25519(r, a):
'''void set25519(gf r, const gf a)'''
for i in range(16): r[i] = a[i]
def car25519(o):
'''void car25519(gf o)'''
c = i64()
for i in range(16):
o[i] += (i64(1) << 16)
c = o[i] >> 16
o[(i + 1)*(i < 15)] += c - 1 + 37*(c - 1)*(i == 15)
o[i] -= c << 16
def sel25519(p, q, b):
'''void sel25519(gf p, gf q, int b)'''
t = i64()
c = i64(~(b - 1))
for i in range(16):
t = c & (p[i] ^ q[i])
p[i] ^= t
q[i] ^= t
return p, q
def pack25519(o, n):
'''void pack25519(u8*o, const gf n)'''
b = int()
m = gf()
t = gf()
for i in range(16): t[i] = n[i]
car25519(t)
car25519(t)
car25519(t)
for j in range(2):
m[0] = t[0] - 0xffed
for i in range(1,15):
m[i] = t[i] - 0xffff - ((m[i - 1] >> 16) & 1)
m[i-1] &= 0xffff
m[15] = t[15] - 0x7fff - ((m[14] >> 16) & 1)
b = (m[15] >> 16) & 1
m[14] &= 0xffff
sel25519(t, m, 1 - b)
for i in range(16):
o[2*i] = t[i] & 0xff
o[2*i + 1] = t[i] >> 8
def neq25519(a, b):
'''int neq25519(const gf a, const gf b)'''
c = IntArray(u8, size=32)
d = IntArray(u8, size=32)
pack25519(c, a)
pack25519(d, b)
return crypto_verify_32_tweet(c, d)
def par25519(a):
'''u8 par25519(const gf a)'''
d = IntArray(u8, size=32)
pack25519(d, a)
return d[0] & 1
def unpack25519(o, n):
'''void unpack25519(gf o, const u8*n)'''
for i in range(16): o[i] = n[2*i] + (i64(n[2*i + 1]) << 8)
o[15] &= 0x7fff
def A(o, a, b):
'''void A(gf o, const gf a, const gf b)'''
for i in range(16): o[i] = a[i] + b[i]
def Z(o, a, b):
'''void Z(gf o, const gf a, const gf b)'''
for i in range(16): o[i] = a[i] - b[i]
def M(o, a, b):
'''void M(gf o, const gf a, const gf b)'''
t = IntArray(i64, size=31)
for i in range(16):
for j in range(16): t[i + j] += a[i]*b[j]
for i in range(15): t[i] += 38*t[i + 16]
for i in range(16): o[i] = t[i]
car25519(o)
car25519(o)
return o
def S(o, a):
'''void S(gf o, const gf a)'''
M(o, a, a)
def inv25519(o, i):
'''void inv25519(gf o, const gf i)'''
c = gf()
for a in range(16): c[a] = i[a]
for a in range(253, -1, -1):
S(c, c)
if a != 2 and a != 4: M(c, c, i)
for a in range(16): o[a] = c[a]
return o
def pow2523(o, i):
'''void pow2523(gf o, const gf i)'''
c = gf()
for a in range(16): c[a] = i[a]
for a in range(250, -1, -1):
S(c, c)
if a != 1: M(c, c, i)
for a in range(16): o[a] = c[a]
def crypto_scalarmult_curve25519_tweet(q, n, p):
'''int crypto_scalarmult_curve25519_tweet(u8*q, const u8*n, const u8*p)'''
z = IntArray(u8, size=32)
x = IntArray(i64, size=80)
r = i64()
a = gf()
b = gf()
c = gf()
d = gf()
e = gf()
f = gf()
for i in range(31): z[i] = n[i]
z[31] = (n[31] & 127) | 64
z[0] &= 248
unpack25519(x, p)
for i in range(16):
b[i] = x[i]
d[i] = a[i] = c[i] = 0
a[0] = d[0] = 1
for i in range(254, -1, -1):
r = (z[i >> 3] >> (i & 7)) & 1
sel25519(a, b, r)
sel25519(c, d, r)
A(e, a, c)
Z(a, a, c)
A(c, b, d)
Z(b, b, d)
S(d, e)
S(f, a)
M(a, c, a)
M(c, b, e)
A(e, a, c)
Z(a, a, c)
S(b, a)
Z(c, d, f)
M(a, c, _121665)
A(a, a, d)
M(c, c, a)
M(a, d, f)
M(d, b, x)
S(b, e)
sel25519(a, b, r)
sel25519(c, d, r)
for i in range(16):
x[i + 16] = a[i]
x[i + 32] = c[i]
x[i + 48] = b[i]
x[i + 64] = d[i]
x[32:] = inv25519(x[32:], x[32:])
x[16:] = M(x[16:], x[16:], x[32:])
pack25519(q, x[16:])
return 0
def crypto_scalarmult_curve25519_tweet_base(q, n):
'''int crypto_scalarmult_curve25519_tweet_base(u8*q, const u8*n)'''
return crypto_scalarmult_curve25519_tweet(q, n, _9)
def crypto_box_curve25519xsalsa20poly1305_tweet_keypair(y, x):
'''int crypto_box_curve25519xsalsa20poly1305_tweet_keypair(u8*y, u8*x)'''
randombytes(x, 32)
return crypto_scalarmult_curve25519_tweet_base(y, x)
def crypto_box_curve25519xsalsa20poly1305_tweet_beforenm(k, y, x):
'''int crypto_box_curve25519xsalsa20poly1305_tweet_beforenm(u8*k, const u8*y, const u8*x)'''
s = IntArray(u8, size=32)
crypto_scalarmult_curve25519_tweet(s, x, y)
return crypto_core_hsalsa20_tweet(k, _0, s, sigma)
def crypto_box_curve25519xsalsa20poly1305_tweet_afternm(c, m, d, n, k):
'''int crypto_box_curve25519xsalsa20poly1305_tweet_afternm(u8*c, const u8*m, u64 d, const u8*n, const u8*k)'''
return crypto_secretbox_xsalsa20poly1305_tweet(c, m, d, n, k)
def crypto_box_curve25519xsalsa20poly1305_tweet_open_afternm(m, c, d, n, k):
'''int crypto_box_curve25519xsalsa20poly1305_tweet_open_afternm(u8*m, const u8*c, u64 d, const u8*n, const u8*k)'''
return crypto_secretbox_xsalsa20poly1305_tweet_open(m, c, d, n, k)
def crypto_box_curve25519xsalsa20poly1305_tweet(c, m, d, n, y, x):
'''int crypto_box_curve25519xsalsa20poly1305_tweet(u8*c, const u8*m, u64 d, const u8*n, const u8*y, const u8*x)'''
k = IntArray(u8, size=32)
crypto_box_curve25519xsalsa20poly1305_tweet_beforenm(k, y, x)
return crypto_box_curve25519xsalsa20poly1305_tweet_afternm(c, m, d, n, k)
def crypto_box_curve25519xsalsa20poly1305_tweet_open(m, c, d, n, y, x):
'''int crypto_box_curve25519xsalsa20poly1305_tweet_open(u8*m, const u8*c, u64 d, const u8*n, const u8*y, const u8*x)'''
k = IntArray(u8, size=32)
crypto_box_curve25519xsalsa20poly1305_tweet_beforenm(k, y, x)
return crypto_box_curve25519xsalsa20poly1305_tweet_open_afternm(m, c, d, n, k)
def R(x, c):
'''u64 R(u64 x, int c)'''
return (u64(x) >> c) | (u64(x) << (64 - c))
def Ch(x, y, z):
'''u64 Ch(u64 x, u64 y, u64 z)'''
return (u64(x) & u64(y)) ^ (~u64(x) & u64(z))
def Maj(x, y, z):
'''u64 Maj(u64 x, u64 y, u64 z)'''
return (u64(x) & u64(y)) ^ (u64(x) & u64(z)) ^ (u64(y) & u64(z))
def Sigma0(x):
'''u64 Sigma0(u64 x)'''
return R(x, 28) ^ R(x, 34) ^ R(x, 39)
def Sigma1(x):
'''u64 Sigma1(u64 x)'''
return R(x, 14) ^ R(x, 18) ^ R(x, 41)
def sigma0(x):
'''u64 sigma0(u64 x)'''
return R(x, 1) ^ R(x, 8) ^ (x >> 7)
def sigma1(x):
'''u64 sigma1(u64 x)'''
return R(x, 19) ^ R(x, 61) ^ (x >> 6)
K = IntArray(u64, size=80, init=[
0x428a2f98d728ae22, 0x7137449123ef65cd, 0xb5c0fbcfec4d3b2f, 0xe9b5dba58189dbbc,
0x3956c25bf348b538, 0x59f111f1b605d019, 0x923f82a4af194f9b, 0xab1c5ed5da6d8118,
0xd807aa98a3030242, 0x12835b0145706fbe, 0x243185be4ee4b28c, 0x550c7dc3d5ffb4e2,
0x72be5d74f27b896f, 0x80deb1fe3b1696b1, 0x9bdc06a725c71235, 0xc19bf174cf692694,
0xe49b69c19ef14ad2, 0xefbe4786384f25e3, 0x0fc19dc68b8cd5b5, 0x240ca1cc77ac9c65,
0x2de92c6f592b0275, 0x4a7484aa6ea6e483, 0x5cb0a9dcbd41fbd4, 0x76f988da831153b5,
0x983e5152ee66dfab, 0xa831c66d2db43210, 0xb00327c898fb213f, 0xbf597fc7beef0ee4,
0xc6e00bf33da88fc2, 0xd5a79147930aa725, 0x06ca6351e003826f, 0x142929670a0e6e70,
0x27b70a8546d22ffc, 0x2e1b21385c26c926, 0x4d2c6dfc5ac42aed, 0x53380d139d95b3df,
0x650a73548baf63de, 0x766a0abb3c77b2a8, 0x81c2c92e47edaee6, 0x92722c851482353b,
0xa2bfe8a14cf10364, 0xa81a664bbc423001, 0xc24b8b70d0f89791, 0xc76c51a30654be30,
0xd192e819d6ef5218, 0xd69906245565a910, 0xf40e35855771202a, 0x106aa07032bbd1b8,
0x19a4c116b8d2d0c8, 0x1e376c085141ab53, 0x2748774cdf8eeb99, 0x34b0bcb5e19b48a8,
0x391c0cb3c5c95a63, 0x4ed8aa4ae3418acb, 0x5b9cca4f7763e373, 0x682e6ff3d6b2b8a3,
0x748f82ee5defb2fc, 0x78a5636f43172f60, 0x84c87814a1f0ab72, 0x8cc702081a6439ec,
0x90befffa23631e28, 0xa4506cebde82bde9, 0xbef9a3f7b2c67915, 0xc67178f2e372532b,
0xca273eceea26619c, 0xd186b8c721c0c207, 0xeada7dd6cde0eb1e, 0xf57d4f7fee6ed178,
0x06f067aa72176fba, 0x0a637dc5a2c898a6, 0x113f9804bef90dae, 0x1b710b35131c471b,
0x28db77f523047d84, 0x32caab7b40c72493, 0x3c9ebe0a15c9bebc, 0x431d67c49c100d4c,
0x4cc5d4becb3e42b6, 0x597f299cfc657e2a, 0x5fcb6fab3ad6faec, 0x6c44198c4a475817
])
def crypto_hashblocks_sha512_tweet(x, m, n):
'''int crypto_hashblocks_sha512_tweet(u8*x, const u8*m, u64 n)'''
z = IntArray(u64, size=8)
b = IntArray(u64, size=8)
a = IntArray(u64, size=8)
w = IntArray(u64, size=16)
t = u64()
for i in range(8): z[i] = a[i] = dl64(x[8*i:])
m_off = 0
while n >= 128:
for i in range(16): w[i] = dl64(m[8*i + m_off:])
for i in range(80):
for j in range(8): b[j] = a[j]
t = a[7] + Sigma1(a[4]) + Ch(a[4], a[5], a[6]) + K[i] + w[i%16]
b[7] = t + Sigma0(a[0]) + Maj(a[0], a[1], a[2])
b[3] += t
for j in range(8): a[(j + 1)%8] = b[j]
if i%16 == 15:
for j in range(16):
w[j] += w[(j + 9)%16] + sigma0(w[(j + 1)%16]) + sigma1(w[(j + 14)%16])
for i in range(8):
a[i] += z[i]; z[i] = a[i]
m_off += 128
n -= 128
for i in range(8): x[8*i:] = ts64(x[8*i:], z[i])
return n
iv = IntArray(u8, size=64, init=[
0x6a, 0x09, 0xe6, 0x67, 0xf3, 0xbc, 0xc9, 0x08,
0xbb, 0x67, 0xae, 0x85, 0x84, 0xca, 0xa7, 0x3b,
0x3c, 0x6e, 0xf3, 0x72, 0xfe, 0x94, 0xf8, 0x2b,
0xa5, 0x4f, 0xf5, 0x3a, 0x5f, 0x1d, 0x36, 0xf1,
0x51, 0x0e, 0x52, 0x7f, 0xad, 0xe6, 0x82, 0xd1,
0x9b, 0x05, 0x68, 0x8c, 0x2b, 0x3e, 0x6c, 0x1f,
0x1f, 0x83, 0xd9, 0xab, 0xfb, 0x41, 0xbd, 0x6b,
0x5b, 0xe0, 0xcd, 0x19, 0x13, 0x7e, 0x21, 0x79
])
def crypto_hash_sha512_tweet(out, m, n):
'''int crypto_hash_sha512_tweet(u8*out, const u8*m, u64 n)'''
h = IntArray(u8, size=64)
x = IntArray(u8, size=256)
b = u64(n)
for i in range(64): h[i] = iv[i]
crypto_hashblocks_sha512_tweet(h, m, n)
m_off = n
n &= 127
m_off -= n
x[:256] = 256*[u8()]
for i in range(n): x[i] = m[i + m_off]
x[n] = 128
n = 256 - 128*(n < 112)
x[n - 9] = b >> 61
x[n - 8:] = ts64(x[n - 8:], b << 3)
crypto_hashblocks_sha512_tweet(h, x, n)
for i in range(64): out[i] = h[i]
return 0
def add(p, q):
'''void add(gf p[4], gf q[4])'''
a = gf()
b = gf()
c = gf()
d = gf()
t = gf()
e = gf()
f = gf()
g = gf()
h = gf()
Z(a, p[1], p[0])
Z(t, q[1], q[0])
M(a, a, t)
A(b, p[0], p[1])
A(t, q[0], q[1])
M(b, b, t)
M(c, p[3], q[3])
M(c, c, D2)
M(d, p[2], q[2])
A(d, d, d)
Z(e, b, a)
Z(f, d, c)
A(g, d, c)
A(h, b, a)
M(p[0], e, f)
M(p[1], h, g)
M(p[2], g, f)
M(p[3], e, h)
def cswap(p, q, b):
'''void cswap(gf p[4], gf q[4], u8 b)'''
for i in range(4):
p[i], q[i] = sel25519(p[i], q[i], b)
def pack(r, p):
'''void pack(u8*r, gf p[4])'''
tx = gf()
ty = gf()
zi = gf()
inv25519(zi, p[2])
M(tx, p[0], zi)
M(ty, p[1], zi)
pack25519(r, ty)
r[31] ^= par25519(tx) << 7
def scalarmult(p, q, s):
'''void scalarmult(gf p[4], gf q[4], const u8*s)'''
set25519(p[0], gf0)
set25519(p[1], gf1)
set25519(p[2], gf1)
set25519(p[3], gf0)
for i in range(255, -1, -1):
b = u8((s[i//8] >> (i & 7)) & 1)
cswap(p, q, b)
add(q, p)
add(p, p)
cswap(p, q, b)
def scalarbase(p, s):
'''void scalarbase(gf p[4], const u8*s)'''
q = [gf() for i in range(4)]
set25519(q[0], X)
set25519(q[1], Y)
set25519(q[2], gf1)
M(q[3], X, Y)
scalarmult(p, q, s)
def crypto_sign_ed25519_tweet_keypair(pk, sk):
'''int crypto_sign_ed25519_tweet_keypair(u8*pk, u8*sk)'''
d = IntArray(u8, size=64)
p = [gf() for i in range(4)]
randombytes(sk, 32)
crypto_hash_sha512_tweet(d, sk, 32)
d[0] &= 248
d[31] &= 127
d[31] |= 64
scalarbase(p, d)
pack(pk, p)
for i in range(32): sk[32 + i] = pk[i]
return 0
L = IntArray(u64, size=32, init=[
0xed, 0xd3, 0xf5, 0x5c, 0x1a, 0x63, 0x12, 0x58, 0xd6, 0x9c, 0xf7, 0xa2, 0xde, 0xf9, 0xde, 0x14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0x10
])
def modL(r, x):
'''void modL(u8*r, i64 x[64])'''
carry = i64()
for i in range(63, 31, -1):
carry = 0
for j in range(i - 32, i - 12):
x[j] += carry - 16*x[i]*L[j - (i - 32)]
carry = (x[j] + 128) >> 8
x[j] -= carry << 8
j += 1
x[j] += carry
x[i] = 0
carry = 0
for j in range(32):
x[j] += carry - (x[31] >> 4)*L[j]
carry = x[j] >> 8
x[j] &= 255
for j in range(32): x[j] -= carry*L[j]
for i in range(32):
x[i + 1] += x[i] >> 8
r[i] = x[i] & 255
return r
def reduce(r):
'''void reduce(u8*r)'''
x = IntArray(i64, size=64)
for i in range(64): x[i] = u64(r[i])
r[:64] = 64*[u8()]
modL(r, x)
def crypto_sign_ed25519_tweet(sm, smlen, m, n, sk):
'''int crypto_sign_ed25519_tweet(u8*sm, u64*smlen, const u8*m, u64 n, const u8*sk)'''
d = IntArray(u8, size=64)
h = IntArray(u8, size=64)
r = IntArray(u8, size=64)
x = IntArray(i64, size=64)
p = [gf() for i in range(4)]
crypto_hash_sha512_tweet(d, sk, 32)
d[0] &= 248
d[31] &= 127
d[31] |= 64
# There is no (simple?) way to return this argument's value back to the
# user in python. Rather than redefining the return value of this function
# it is better to advise the user that ``smlen`` does not work as it does
# in the C implementation and that its value will be equal to ``n + 64``.
smlen = n + 64
for i in range(n): sm[64 + i] = m[i]
for i in range(32): sm[32 + i] = d[32 + i]
crypto_hash_sha512_tweet(r, sm[32:], n + 32)
reduce(r)
scalarbase(p, r)
pack(sm, p)
for i in range(32): sm[i + 32] = sk[i + 32]
crypto_hash_sha512_tweet(h, sm, n + 64)
reduce(h)
for i in range(64): x[i] = 0
for i in range(32): x[i] = u64(r[i])
for i in range(32):
for j in range(32): x[i + j] += h[i]*u64(d[j])
sm[32:] = modL(sm[32:], x)
return 0
def unpackneg(r, p):
'''int unpackneg(gf r[4], const u8 p[32])'''
t = gf()
chk = gf()
num = gf()
den = gf()
den2 = gf()
den4 = gf()
den6 = gf()
set25519(r[2], gf1)
unpack25519(r[1], p)
S(num, r[1])
M(den, num, D)
Z(num, num, r[2])
A(den, r[2], den)
S(den2, den)
S(den4, den2)
M(den6, den4, den2)
M(t, den6, num)
M(t, t, den)
pow2523(t, t)
M(t, t, num)
M(t, t, den)
M(t, t, den)
M(r[0], t, den)
S(chk, r[0])
M(chk, chk, den)
if neq25519(chk, num): M(r[0], r[0], I)
S(chk, r[0])
M(chk, chk, den)
if neq25519(chk, num): return -1
if par25519(r[0]) == (p[31] >> 7): Z(r[0], gf0, r[0])
M(r[3], r[0], r[1])
return 0
def crypto_sign_ed25519_tweet_open(m, mlen, sm, n, pk):
'''int crypto_sign_ed25519_tweet_open(u8*m, u64*mlen, const u8*sm, u64 n, const u8*pk)'''
t = IntArray(u8, size=32)
h = IntArray(u8, size=64)
p = [gf() for i in range(4)]
q = [gf() for i in range(4)]
mlen = -1
if n < 64: return -1
if unpackneg(q, pk): return -1
for i in range(n): m[i] = sm[i]
for i in range(32): m[i + 32] = pk[i]
crypto_hash_sha512_tweet(h, m, n)
reduce(h)
scalarmult(p, q, h)
scalarbase(q, sm[32:])
add(p, q)
pack(t, p)
n -= 64
if crypto_verify_32_tweet(sm, t):
for i in range(n): m[i] = 0
return -1
for i in range(n): m[i] = sm[i + 64]
# There is no (simple?) way to return this argument's value back to the
# user in python. Rather than redefining the return value of this function
# it is better to advise the user that ``mlen`` does not work as it does in
# the C implementation and that its value will be equal to ``-1`` if ``n <
# 64`` or decryption fails and ``n - 64`` otherwise.
mlen = n
return 0
| [
"rofl0r@users.noreply.github.com"
] | rofl0r@users.noreply.github.com |
337fc9acd874ec2fe78a22c97a899891aa30bc6e | cac5c5fc82a6f1a377786bca731996bbb6d67e70 | /lab8/perceptron.py | 6eef9b9e40d9d9237973383b3e6b92244c5d9d8e | [] | no_license | njordan3/Artificial-Intelligence | db81cfe92d28fe9a14b438140ac387587c892200 | a63f7d91e4fb8f1a36738a7999819c53870f2d04 | refs/heads/master | 2022-08-27T16:53:17.638856 | 2020-05-20T15:24:49 | 2020-05-20T15:24:49 | 265,606,840 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,649 | py | # Author: Nicholas Jordan
# Date: 4/7/20
# Lab 8: Perceptron Learning Algorithm Using Fisher's Iris Dataset
import csv
from random import seed
from random import random
filename = "iris.csv"
array = []
with open(filename, newline='') as csvfile:
csvreader = csv.reader(csvfile, delimiter=',')
for row in csvreader:
row = [float(i) for i in row]
array.append(row)
# simple 'expert system' that each sample runs through to get accuracy of the data
counter = 0
for row in array:
if row[2] > 0 and row[4] == -1:
counter+=1
accuracy = round(counter/len(array),2)
print("CSV species accuracy: {}%".format(accuracy*100))
# learning rate: small change to 'w' that gets made when the algorithm guesses wrong
alpha = 0.05
# seed random number generator
seed(1)
# 4 weights of random value to make guesses
#w = [random() for i in range(4)]
#theta = random()
w = [0,0,0,0]
theta = 0
# an epoch is a run through the whole dataset
for epoch in range(100):
errors = 0
for sample in array:
x = sample[:4]
yd = sample[4]
# feed forward
charge = x[0]*w[0] + x[1]*w[1] + x[2]*w[2] + x[3]*w[3] - theta
#print(charge, w[0], w[1], w[2], w[3], theta)
# sign activation function
if charge <= 0:
guess = -1
else:
guess = 1
# error correction
e = yd - guess
if e != 0:
for j in range(4):
w[j] = w[j] + alpha * x[j] * e
theta = theta + alpha * e * -1
errors+=1
print("EPOCH {}: Accuracy is {}%".format(epoch+1, round((len(array) - errors)/len(array)*100, 2)))
| [
"noreply@github.com"
] | njordan3.noreply@github.com |
f321eb6f45926063501fb2e517aa62032f931345 | 16516732031deb7f7e074be9fe757897557eee2d | /AtCoder/ABC144/B - 81.py | 20cb27b770682ca06d845b8961d895932b2f6ea9 | [] | no_license | cale-i/atcoder | 90a04d3228864201cf63c8f8fae62100a19aefa5 | c21232d012191ede866ee4b9b14ba97eaab47ea9 | refs/heads/master | 2021-06-24T13:10:37.006328 | 2021-03-31T11:41:59 | 2021-03-31T11:41:59 | 196,288,266 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 172 | py | # 2019/10/29
n=int(input())
for i in range(1,10):
for j in range(1,10):
if n==i*j:
print('Yes')
exit()
else:
print('No') | [
"calei078029@gmail.com"
] | calei078029@gmail.com |
dc507a14aa2d66870ccc251aaa3639821fae136b | d1b27a90037b3b7ad5a14cf77d28b6313104d8c5 | /backend/users/tasks.py | 191013ed3960dff89e30bbfabd4955c4a9537763 | [
"MIT"
] | permissive | zepplinsbass/imperial_assault | 66ad08c8dddc56e9300fbf33a597e2ce503b0ead | b6bd0ecef15962978308269f909573bef1c05bfc | refs/heads/main | 2023-04-14T03:53:48.455018 | 2021-04-20T13:23:58 | 2021-04-20T13:23:58 | 355,036,618 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 161 | py | from django.core import management
from imperial-assault import celery_app
@celery_app.task
def clearsessions():
management.call_command('clearsessions')
| [
"zepplinsbass@gmail.com"
] | zepplinsbass@gmail.com |
ed0549291501f587e1235fcff85f3db9dc1f164c | 358b5a026e0865af26bb1abd451b8a55bc478f11 | /Scripts/ClassifyMibigTsv.py | 67e1859ae98150ba7335b4c93ed18b375112aea3 | [] | no_license | OscarHoekstra/ClassifyNPDB | 0a38599f6e23d8af8748ed36a960f2024cee699b | 2fd2e30e16cabc324d2d1c17e692bc609c2e94df | refs/heads/master | 2020-04-18T13:44:06.499639 | 2019-03-22T11:21:41 | 2019-03-22T11:21:41 | 167,569,325 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,754 | py | #!/usr/bin/env python3
"""
Author: Oscar Hoekstra
Student Number: 961007346130
Email: oscarhoekstra@wur.nl
Description: Loads a TSV file with mibig compound-id, compound name and
smile strings, uploads the smiles to ClassyFire and creates a dictionary
with the compound id and name with the QueryID to retrieve the
classification later.
"""
import sys
from Scripts import Run_pyclassyfire4
import pickle
def LoadMibigTsv(InFile):
""" Loads a tsv file with all smiles available for the mibig dataset and
saves the mibig accession and compound-name as CompoundID and the smile
as Structure in a dictionary CompoundDict
"""
CompoundDict = {}
with open(InFile, 'r') as f:
f.readline()
File = f.readlines()
for line in File:
line = line.split('\t')
CompoundID = line[0]+"_"+line[1]
Structure = line[2]
if CompoundID in CompoundDict:
print('THIS SHOULD NOT HAPPEN,',
'There seems to be a duplicate in the mibig smile tsv file,',
'Check the file for errors!')
print(CompoundID)
exit(1)
if len(Structure) > 0:
CompoundDict[CompoundID] = Structure
return CompoundDict
def main(InFile):
# Create a dictionary with the mibig compounds and smiles.
CompoundDict = LoadMibigTsv(InFile)
QueryIDDict = Run_pyclassyfire4.PyClassifyStructureList(CompoundDict)
with open("PickledQueryIDDict.txt",'wb') as f:
pickle.dump(QueryIDDict, f)
print("Saved PickledQueryIDDict")
#Run_pyclassyfire4.GetPyclassyfireResults(QueryIDDict)
if __name__ == "__main__":
InFile = sys.argv[1]
main(InFile)
print("Done")
| [
"oscar.hoekstra@wur.nl"
] | oscar.hoekstra@wur.nl |
dcd45071d9de9c2cd68da8c294b12261666ef0c7 | 82fce9aae9e855a73f4e92d750e6a8df2ef877a5 | /Lab/venv/lib/python3.8/site-packages/OpenGL/WGL/I3D/swap_frame_lock.py | 55165c5511d39959c40ce8e2e34740a4e67b88d3 | [] | no_license | BartoszRudnik/GK | 1294f7708902e867dacd7da591b9f2e741bfe9e5 | 6dc09184a3af07143b9729e42a6f62f13da50128 | refs/heads/main | 2023-02-20T19:02:12.408974 | 2021-01-22T10:51:14 | 2021-01-22T10:51:14 | 307,847,589 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 574 | py | '''OpenGL extension I3D.swap_frame_lock
This module customises the behaviour of the
OpenGL.raw.WGL.I3D.swap_frame_lock to provide a more
Python-friendly API
The official definition of this extension is available here:
http://www.opengl.org/registry/specs/I3D/swap_frame_lock.txt
'''
from OpenGL.raw.WGL.I3D.swap_frame_lock import _EXTENSION_NAME
def glInitSwapFrameLockI3D():
'''Return boolean indicating whether this extension is available'''
from OpenGL import extensions
return extensions.hasGLExtension( _EXTENSION_NAME )
### END AUTOGENERATED SECTION | [
"rudnik49@gmail.com"
] | rudnik49@gmail.com |
354b8e8c9970c9f648bc4121fee221c159995f3d | 356c00aed4c9e45d5b9cae067dcb8d1bbb09cb1d | /backend/src/paruzorus/web/__init__.py | 182b8bdfe777d6f98b52d8d8ae2f3b4e16ac1fe0 | [] | no_license | TwistedSim/Paruzorus | 74fedd97696114918021daa3117c2e7ce8d6038a | e857881d0d9d359b677e3cc4bc7a9c79019ae097 | refs/heads/master | 2023-08-15T09:27:33.943014 | 2021-09-14T16:41:20 | 2021-09-14T16:41:20 | 349,588,484 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,063 | py | import base64
from logging import getLogger
from aiohttp import web
from aiohttp_middlewares import cors_middleware, error_middleware
from aiohttp_session import setup
from aiohttp_session.cookie_storage import EncryptedCookieStorage
from cryptography import fernet
from paruzorus.controllers.quiz_controller import QuizController
from paruzorus.providers.macaulay import MacAulayProvider
from paruzorus.species.sandpipers import TARGET_SPECIES
from paruzorus.web.api import create_api
logger = getLogger(__name__)
async def create_app():
app = web.Application(
middlewares=(
cors_middleware(allow_all=True),
error_middleware(),
)
)
fernet_key = fernet.Fernet.generate_key()
secret_key = base64.urlsafe_b64decode(fernet_key)
setup(app, EncryptedCookieStorage(secret_key))
provider = MacAulayProvider(TARGET_SPECIES)
app["quiz_controller"] = QuizController(provider)
api = await create_api()
app.add_subapp("/api", api)
logger.debug("App creation completed")
return app
| [
"bouchards@amotus.ca"
] | bouchards@amotus.ca |
3776da41918b7c075ae74dc769b3cd91266c96a7 | 92662baf27ff293ea9dc4ef84ef6e9f60a3683b2 | /BillBoard/user/views.py | d74b680769dba014a2f98f8b8590538a6b9f6ea8 | [] | no_license | AleenaVarghese/BillBoard | 3a3dc21946f4a3a52d42182f2bc1a9c1eabdce42 | 0cb7c9259eb351fe1ca3d54bb3e5c87cce62584e | refs/heads/master | 2020-06-23T21:44:55.884861 | 2019-07-25T05:20:11 | 2019-07-25T05:20:11 | 198,760,393 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,569 | py | from django.shortcuts import render
from boards.models import BillBoard
from django.views.generic import CreateView, ListView, DetailView, DeleteView, UpdateView
from .forms import BillBoardForm, BillBoardUpdateForm
from django.urls import reverse_lazy
from django.shortcuts import get_object_or_404
from boards.choices import *
from django import forms
from django.contrib.auth.mixins import LoginRequiredMixin
# Create your views here.
class BillBordListView(LoginRequiredMixin, ListView):
model = BillBoard
template_name = 'user/home.html' # <app>/<model>_<viewtype>.html
queryset = BillBoard.objects.all()
context_object_name = 'BillBord_list'
paginate_by = 3
ordering = ['city']
def get_queryset(self):
return BillBoard.objects.all().order_by('city')
class BillBoardCreateView(LoginRequiredMixin, CreateView):
model = BillBoard
template_name = 'user/addnew.html'
form_class = BillBoardForm
success_url = reverse_lazy('user:BillBord_list')
class BillBoardDeleteView(LoginRequiredMixin, DeleteView):
model = BillBoard
success_url = reverse_lazy('user:BillBord_list')
class BillBoardUpdateView(LoginRequiredMixin, UpdateView):
model = BillBoard
form_class = BillBoardUpdateForm
template_name = 'user/EditBillBoard.html'
success_url = reverse_lazy('user:BillBord_list')
def form_valid(self, form):
return super(BillBoardUpdateView, self).form_valid(form)
class BillBordSearchView(LoginRequiredMixin, ListView):
model = BillBoard
template_name = 'user/SearchBillBoard.html' # <app>/<model>_<viewtype>.html
context_object_name = 'BillBord_list'
def get_queryset(self):
search_query = self.request.GET.get('search', None)
try:
objects = BillBoard.objects.get(boardId= search_query)
except BillBoard.DoesNotExist:
return False
return BillBoard.objects.get(boardId= search_query)
class BillBordFilterView(LoginRequiredMixin, ListView):
model = BillBoard
template_name = 'user/home.html' # <app>/<model>_<viewtype>.html
context_object_name = 'BillBord_list'
paginate_by = 3
ordering = ['boardId']
def get_queryset(self):
search_query = self.request.GET.get('search', None)
try:
objects = BillBoard.objects.filter(city= search_query)
except BillBoard.DoesNotExist:
return False
return BillBoard.objects.filter(city= search_query)
| [
"aleenav.sayone@gmail.com"
] | aleenav.sayone@gmail.com |
9abbe07830ef42f726486d4859b96e0c7f30f1ef | 4cfdcb102dc1c8eed379401cc6edd2a6f423f937 | /pksig_all other code/pksig_cllww12_benchmark.py | 2d49a3269347b6e27536565d6b584b873c6660f8 | [] | no_license | zfwise/myCharmCode | daf10467d993cbc1c469271ab53234f2a84b6d3a | 15578a942ecd8f3a614714d3c04a7ce55b0fb7ca | refs/heads/master | 2021-01-18T18:12:19.482614 | 2013-04-26T14:08:32 | 2013-04-26T14:08:32 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 9,078 | py | from charm.toolbox.pairinggroup import PairingGroup,ZR,G1,G2,GT,pair
from charm.core.crypto.cryptobase import *
from charm.toolbox.IBEnc import IBEnc
from charm.schemes.pksig.pksig_cllww12 import Sign_Chen12
from charm.schemes.pksig.pksig_cllww12_swap import Sign_Chen12_swap
from charm.schemes.pksig.pksig_cllww12_swap_improved import Sign_Chen12_swap_improved
from charm.schemes.pksig.pksig_bls04 import IBSig
from charm.schemes.pksig.pksig_waters05 import IBE_N04_Sig
from charm.schemes.pksig.pksig_waters05_improved import IBE_N04_Sig_improved
from charm.schemes.pksig.pksig_waters09_improved import IBEWaters09_improved
from charm.toolbox.hash_module import Waters
import time
import string
import random
def randomStringGen(size=10, chars=string.ascii_uppercase + string.digits):
return ''.join(random.choice(chars) for x in range(size))
n = 200
#groupObj = PairingGroup('MNT224')
groupObj = PairingGroup('/home/zfwise/Downloads/pbc-0.5.12/param/f.param', param_file=True)
if(1):
m = "plese sign this message!!!!"
#cllww = Sign_Chen12(groupObj)
cllww = Sign_Chen12(groupObj)
cllwwKeyGenTime = 0.0
cllwwSignTime = 0.0
cllwwVerifyTime = 0.0
for i in range(0, n):
startTime = time.time()
(pk, sk) = cllww.keygen()
cllwwKeyGenTime += time.time() - startTime
m = randomStringGen()
startTime = time.time()
signature = cllww.sign(pk, sk, m)
cllwwSignTime += time.time() - startTime
startTime = time.time()
assert cllww.verify(pk, signature, m), "Invalid Verification!!!!"
cllwwVerifyTime += time.time() - startTime
print("CLLWW12_sign: Keygen %d times, average time %f ms" %(n, cllwwKeyGenTime/n*1000))
print("CLLWW12_sign: Sign random message %d times, average time %f ms" %(n, cllwwSignTime/n*1000))
print("CLLWW12_sign: Verify %d times, average time %f ms" %(n, cllwwVerifyTime/n*1000))
print("&%.2f () &%.2f () &%.2f ()" %(cllwwKeyGenTime/n*1000,
cllwwSignTime/n*1000,
cllwwVerifyTime/n*1000))
if(1):
m = "plese sign this message!!!!"
#cllww = Sign_Chen12(groupObj)
cllww = Sign_Chen12_swap(groupObj)
cllwwKeyGenTime = 0.0
cllwwSignTime = 0.0
cllwwVerifyTime = 0.0
for i in range(0, n):
startTime = time.time()
(pk, sk) = cllww.keygen()
cllwwKeyGenTime += time.time() - startTime
m = randomStringGen()
startTime = time.time()
signature = cllww.sign(pk, sk, m)
cllwwSignTime += time.time() - startTime
startTime = time.time()
assert cllww.verify(pk, signature, m), "Invalid Verification!!!!"
cllwwVerifyTime += time.time() - startTime
print("CLLWW12_sign_swap: Keygen %d times, average time %f ms" %(n, cllwwKeyGenTime/n*1000))
print("CLLWW12_sign_swap: Sign random message %d times, average time %f ms" %(n, cllwwSignTime/n*1000))
print("CLLWW12_sign_swap: Verify %d times, average time %f ms" %(n, cllwwVerifyTime/n*1000))
print("&%.2f () &%.2f () &%.2f ()" %(cllwwKeyGenTime/n*1000,
cllwwSignTime/n*1000,
cllwwVerifyTime/n*1000))
if(1):
m = "plese sign this message!!!!"
#cllww = Sign_Chen12(groupObj)
cllww = Sign_Chen12_swap_improved(groupObj)
cllwwKeyGenTime = 0.0
cllwwSignTime = 0.0
cllwwVerifyTime = 0.0
for i in range(0, n):
startTime = time.time()
(pk, sk) = cllww.keygen()
cllwwKeyGenTime += time.time() - startTime
m = randomStringGen()
startTime = time.time()
signature = cllww.sign(pk, sk, m)
cllwwSignTime += time.time() - startTime
startTime = time.time()
assert cllww.verify(pk, signature, m), "Invalid Verification!!!!"
cllwwVerifyTime += time.time() - startTime
print("CLLWW12_sign_swap_improved: Keygen %d times, average time %f ms" %(n, cllwwKeyGenTime/n*1000))
print("CLLWW12_sign_swap_improved: Sign random message %d times, average time %f ms" %(n, cllwwSignTime/n*1000))
print("CLLWW12_sign_swap_improved: Verify %d times, average time %f ms" %(n, cllwwVerifyTime/n*1000))
print("&%.2f () &%.2f () &%.2f ()" %(cllwwKeyGenTime/n*1000,
cllwwSignTime/n*1000,
cllwwVerifyTime/n*1000))
#groupObj = PairingGroup('MNT224')
#groupObj = PairingGroup('SS512')
if(1):
m = { 'a':"hello world!!!" , 'b':"test message" }
bls = IBSig(groupObj)
cllwwKeyGenTime = 0.0
cllwwSignTime = 0.0
cllwwVerifyTime = 0.0
for i in range(0, n):
startTime = time.time()
(pk, sk) = bls.keygen()
cllwwKeyGenTime += time.time() - startTime
m = {'a':randomStringGen() , 'b':randomStringGen()}
startTime = time.time()
sig = bls.sign(sk['x'], m)
cllwwSignTime += time.time() - startTime
startTime = time.time()
assert bls.verify(pk, sig, m), "Failure!!!"
cllwwVerifyTime += time.time() - startTime
print("Bls04: Keygen %d times, average time %f ms" %(n, cllwwKeyGenTime/n*1000))
print("Bls04: Sign random message %d times, average time %f ms" %(n, cllwwSignTime/n*1000))
print("Bls04: Verify %d times, average time %f ms" %(n, cllwwVerifyTime/n*1000))
print("&%.2f () &%.2f () &%.2f ()" %(cllwwKeyGenTime/n*1000,
cllwwSignTime/n*1000,
cllwwVerifyTime/n*1000))
#groupObj = PairingGroup('MNT159')
#groupObj = PairingGroup('SS512')
if(1):
ibe = IBE_N04_Sig(groupObj)
waters = Waters(groupObj)
msg = waters.hash("This is a test.")
cllwwKeyGenTime = 0.0
cllwwSignTime = 0.0
cllwwVerifyTime = 0.0
for i in range(0, n):
startTime = time.time()
(pk, sk) = ibe.keygen()
cllwwKeyGenTime += time.time() - startTime
msg = waters.hash(randomStringGen())
startTime = time.time()
sig = ibe.sign(pk, sk, msg)
cllwwSignTime += time.time() - startTime
startTime = time.time()
assert ibe.verify(pk, msg, sig), "Failed verification!"
cllwwVerifyTime += time.time() - startTime
print("Waters05: Keygen %d times, average time %f ms" %(n, cllwwKeyGenTime/n*1000))
print("Waters05: Sign random message %d times, average time %f ms" %(n, cllwwSignTime/n*1000))
print("Waters05: Verify %d times, average time %f ms" %(n, cllwwVerifyTime/n*1000))
print("&%.2f () &%.2f () &%.2f ()" %(cllwwKeyGenTime/n*1000,
cllwwSignTime/n*1000,
cllwwVerifyTime/n*1000))
if(1):
ibe = IBE_N04_Sig_improved(groupObj)
waters = Waters(groupObj)
msg = waters.hash("This is a test.")
cllwwKeyGenTime = 0.0
cllwwSignTime = 0.0
cllwwVerifyTime = 0.0
for i in range(0, n):
startTime = time.time()
(pk, sk) = ibe.keygen()
cllwwKeyGenTime += time.time() - startTime
msg = waters.hash(randomStringGen())
startTime = time.time()
sig = ibe.sign(pk, sk, msg)
cllwwSignTime += time.time() - startTime
startTime = time.time()
assert ibe.verify(pk, msg, sig), "Failed verification!"
cllwwVerifyTime += time.time() - startTime
print("Waters05_improved: Keygen %d times, average time %f ms" %(n, cllwwKeyGenTime/n*1000))
print("Waters05_improved: Sign random message %d times, average time %f ms" %(n, cllwwSignTime/n*1000))
print("Waters05_improved: Verify %d times, average time %f ms" %(n, cllwwVerifyTime/n*1000))
print("&%.2f () &%.2f () &%.2f ()" %(cllwwKeyGenTime/n*1000,
cllwwSignTime/n*1000,
cllwwVerifyTime/n*1000))
#grp = PairingGroup('MNT224')
#grp = PairingGroup('SS512')
if(1):
ibe = IBEWaters09_improved(groupObj)
m = "plese sign this message!!!!"
bls = IBSig(groupObj)
cllwwKeyGenTime = 0.0
cllwwSignTime = 0.0
cllwwVerifyTime = 0.0
for i in range(0, n):
startTime = time.time()
(mpk, msk) = ibe.keygen()
cllwwKeyGenTime += time.time() - startTime
m = randomStringGen()
startTime = time.time()
sigma = ibe.sign(mpk, msk, m)
cllwwSignTime += time.time() - startTime
startTime = time.time()
assert ibe.verify(mpk, sigma, m), "Invalid Verification!!!!"
cllwwVerifyTime += time.time() - startTime
print("Waters09: Keygen %d times, average time %f ms" %(n, cllwwKeyGenTime/n*1000))
print("Waters09: Sign random message %d times, average time %f ms" %(n, cllwwSignTime/n*1000))
print("Waters09: Verify %d times, average time %f ms" %(n, cllwwVerifyTime/n*1000))
print("&%.2f () &%.2f () &%.2f ()" %(cllwwKeyGenTime/n*1000,
cllwwSignTime/n*1000,
cllwwVerifyTime/n*1000))
| [
"zfwise@gwu.edu"
] | zfwise@gwu.edu |
67d0ed6cd877795ed91f5aacc2466ff064532e60 | 6b019cc6b08042a6bc915b39353217feabc45910 | /converter/biostudies.py | bd61f42e533aa97a8716ffa963eb74ec9ff5121a | [
"Apache-2.0"
] | permissive | ebi-ait/ingest-archiver | c13fa70c42c3649902eec1477b647af783c9b9df | 6d48111d9c050200869958991fcc6d10cd93b609 | refs/heads/dev | 2023-08-03T10:32:25.537418 | 2023-07-29T19:40:24 | 2023-07-29T19:40:24 | 234,517,272 | 2 | 4 | Apache-2.0 | 2022-08-16T14:12:18 | 2020-01-17T09:36:55 | Python | UTF-8 | Python | false | false | 8,590 | py | import copy
from datetime import datetime
from json_converter.json_mapper import JsonMapper
from json_converter.post_process import default_to
from converter import array_to_string
ACCNO_PREFIX_FOR_ORGANIZATIONS = "o"
ACCNO_PREFIX_FOR_AUTHORS = "a"
PUBLICATION_SPEC = {
'type': 'Publication',
'on': 'publications',
'attributes_to_include': {
'authors': "Authors",
'title': "Title",
'doi': 'doi',
'url': 'URL'
},
'attribute_handler': {
'authors': array_to_string
}
}
AUTHORS_SPEC = {
'type': 'Author',
'on': 'contributors',
'attributes_to_include': {
'name': 'Name',
'first_name': 'First Name',
'middle_initials': 'Middle Initials',
'last_name': 'Last Name',
'email': 'Email',
'phone': 'Phone',
'address': 'Address',
'orcid_id': 'Orcid ID'
}
}
FUNDING_SPEC = {
'type': 'Funding',
'on': 'funders',
'attributes_to_include': {
'grant_id': 'grant_id',
'grant_title': 'Grant Title',
'organization': 'Agency'
}
}
class BioStudiesConverter:
def __init__(self):
self.attributes = None
self.contributors = None
self.funders = None
self.publications = None
self.project_spec_base = [
{
'name': ['', default_to, 'Project Core - Project Short Name'],
'value': ['content.project_core.project_short_name']
},
{
'name': ['', default_to, 'HCA Project UUID'],
'value': ['uuid.uuid']
}
]
self.project_spec_section = {
'accno': ['', default_to, 'PROJECT'],
'type': ['', default_to, 'Study'],
'attributes': ['$array', [
{
'name': ['', default_to, 'Title'],
'value': ['content.project_core.project_title']
},
{
'name': ['', default_to, 'Description'],
'value': ['content.project_core.project_description']
}
],
True
]
}
def convert(self, hca_project: dict, additional_attributes: dict = None) -> dict:
converted_project = JsonMapper(hca_project).map({
'attributes': ['$array', self.project_spec_base, True],
'section': self.project_spec_section
})
self.add_release_date(converted_project, hca_project)
project_content = hca_project['content'] if 'content' in hca_project else None
if project_content:
self.__add_subsections_to_project(converted_project, project_content)
return converted_project
@staticmethod
def add_release_date(converted_project, hca_project):
release_date = hca_project.get('releaseDate')
if release_date:
converted_project.get('attributes').append(
{
'name': 'ReleaseDate',
'value': release_date
}
)
def __add_subsections_to_project(self, converted_project, project_content):
contributors = project_content.get('contributors')
funders = project_content.get('funders')
publications = project_content.get('publications')
if contributors or funders or publications:
converted_project['section']['subsections'] = []
converted_publications = self.add_attributes_by_spec(PUBLICATION_SPEC, project_content)
converted_organizations = []
project_content_with_structured_names = self.transform_author_names(project_content)
converted_authors = self.add_attributes_by_spec(AUTHORS_SPEC, project_content_with_structured_names) if contributors else []
BioStudiesConverter.__add_accno(converted_authors, ACCNO_PREFIX_FOR_AUTHORS)
BioStudiesConverter.__add_affiliation(contributors, converted_authors, converted_organizations)
converted_funders = self.add_attributes_by_spec(FUNDING_SPEC, project_content) if funders else []
converted_project['section']['subsections'] = \
converted_publications + converted_authors + converted_organizations + converted_funders
@staticmethod
def __add_accno(converted_authors, prefix):
for index, author in enumerate(converted_authors, start=1):
author['accno'] = prefix + str(index)
@staticmethod
def __add_affiliation(contributors: list, converted_authors: list, converted_organizations: list):
index = 1
for contributor in contributors:
affiliation = {}
if 'institution' in contributor:
author: dict = BioStudiesConverter.__get_author_by_name(contributor.get('name'), converted_authors)
affiliation['name'] = 'affiliation'
affiliation['reference'] = True
affiliation['value'] = 'o' + str(index)
author.get('attributes').append(affiliation)
converted_organizations.append(
BioStudiesConverter.__add_new_organization(contributor.get('institution'), index))
index += 1
@staticmethod
def __get_author_by_name(contributor_name: str, authors: list):
for author in authors:
for attribute in author.get('attributes'):
if attribute.get('name') == 'Name' and attribute.get('value') == contributor_name:
return author
return None
@staticmethod
def __add_new_organization(organization_name: str, index: int):
return \
{
'accno': ACCNO_PREFIX_FOR_ORGANIZATIONS + str(index),
'type': 'Organization',
'attributes': [
{
'name': 'Name',
'value': organization_name
}
]
}
@staticmethod
def transform_author_names(project_content: dict) -> dict:
project_content_with_structured_name = copy.deepcopy(project_content)
contributors = project_content_with_structured_name.get('contributors')
contributor: dict
for contributor in contributors:
full_name = contributor.get('name')
structured_name = BioStudiesConverter.convert_full_name(full_name)
contributor.update(structured_name)
return project_content_with_structured_name
@staticmethod
def add_attributes_by_spec(specification: dict, project_content: dict):
subsection_type_list = []
iterate_on = specification.get('on')
attributes_to_include: dict = specification.get('attributes_to_include')
for entity in project_content.get(iterate_on, []):
subsection_payload_element = {}
attribute_list = []
for attribute_key in attributes_to_include:
if entity.get(attribute_key):
attribute_handler = specification.get('attribute_handler', {}).get(attribute_key)
value = entity.get(attribute_key)
if attribute_handler:
value = attribute_handler(value)
attribute_list.append(
{
'name': attributes_to_include.get(attribute_key),
'value': value
}
)
if len(attribute_list) > 0:
subsection_payload_element.update(
{
'type': specification.get('type'),
'attributes': attribute_list
}
)
subsection_type_list.append(subsection_payload_element)
return subsection_type_list
@staticmethod
def convert_full_name(full_name: str) -> dict:
if full_name is None:
return {}
name_parts = full_name.split(',', 2)
first_name = name_parts[0]
if len(name_parts) <= 2:
middle_initials = None
last_name = name_parts[1]
else:
middle_initials = name_parts[1][0] if name_parts[1] else None
last_name = name_parts[2]
structured_name = {
'first_name': first_name,
'last_name': last_name
}
if middle_initials:
structured_name['middle_initials'] = middle_initials
return structured_name
| [
"karoly@ebi.ac.uk"
] | karoly@ebi.ac.uk |
af9e7b5aa228de28434df110fd779d32173f3e3f | ddaee32e64c1320245a0422a681e70ffeafe5c14 | /unit_tests.py | 8a2cfd895fc9b7dfbb302aa1e0979fc4aacfeb09 | [] | no_license | LiDuaDua/DecisionTree-with-REP-pruning | 4270c66df5355cf88cc384d23826d67aaca4dc23 | 8c80f33a00f1ce8bc92594b6ed6a70605948697e | refs/heads/master | 2021-01-19T16:02:46.494620 | 2017-04-14T07:23:23 | 2017-04-14T07:23:23 | 88,242,224 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,285 | py | import ID3, parse, random
import matplotlib.pyplot as plt
import numpy as np
def testID3AndEvaluate():
data = [dict(a=1, b=0, Class=1), dict(a=1, b=1, Class=1)]
tree = ID3.ID3(data, 0)
if tree != None:
ans = ID3.evaluate(tree, dict(a=1, b=0))
if ans != 1:
print "ID3 test failed."
else:
print "ID3 test succeeded."
else:
print "ID3 test failed -- no tree returned"
def testPruning():
data = [dict(a=1, b=0, Class=1), dict(a=1, b=1, Class=1), dict(a=0, b=1, Class=0), dict(a=0, b=0, Class=1)]
validationData = [dict(a=1, b=0, Class=1), dict(a=1, b=1, Class=1), dict(a=0, b=0, Class=0), dict(a=0, b=0, Class=0)]
tree = ID3.ID3(data, 0)
ID3.prune(tree, validationData)
if tree != None:
ans = ID3.evaluate(tree, dict(a=0, b=0))
if ans != 0:
print "pruning test failed."
else:
print "pruning test succeeded."
else:
print "pruning test failed -- no tree returned."
def testID3AndTest():
trainData = [dict(a=1, b=0, c=0, Class=1), dict(a=1, b=1, c=0, Class=1),
dict(a=0, b=0, c=0, Class=0), dict(a=0, b=1, c=0, Class=1)]
testData = [dict(a=1, b=0, c=1, Class=1), dict(a=1, b=1, c=1, Class=1),
dict(a=0, b=0, c=1, Class=0), dict(a=0, b=1, c=1, Class=0)]
tree = ID3.ID3(trainData, 0)
fails = 0
if tree != None:
acc = ID3.test(tree, trainData)
if acc == 1.0:
print "testing on train data succeeded."
else:
print "testing on train data failed."
fails = fails + 1
acc = ID3.test(tree, testData)
if acc == 0.75:
print "testing on test data succeeded."
else:
print "testing on test data failed."
fails = fails + 1
if fails > 0:
print "Failures: ", fails
else:
print "testID3AndTest succeeded."
else:
print "testID3andTest failed -- no tree returned."
# inFile - string location of the house data file
def testPruningOnHouseData(inFile):
withPruning = []
withoutPruning = []
data = parse.parse(inFile)
for i in range(100):
random.shuffle(data)
train = data[:len(data)/2]
valid = data[len(data)/2:3*len(data)/4]
test = data[3*len(data)/4:]
tree = ID3.ID3(train, 'democrat')
acc = ID3.test(tree, train)
print "training accuracy: ",acc
acc = ID3.test(tree, valid)
print "validation accuracy: ",acc
acc = ID3.test(tree, test)
print "test accuracy: ",acc
ID3.prune(tree, valid)
acc = ID3.test(tree, train)
print "pruned tree train accuracy: ",acc
acc = ID3.test(tree, valid)
print "pruned tree validation accuracy: ",acc
acc = ID3.test(tree, test)
print "pruned tree test accuracy: ",acc
withPruning.append(acc)
tree = ID3.ID3(train+valid, 'democrat')
acc = ID3.test(tree, test)
print "no pruning test accuracy: ",acc
withoutPruning.append(acc)
print withPruning
print withoutPruning
print "average with pruning",sum(withPruning)/len(withPruning)," without: ",sum(withoutPruning)/len(withoutPruning)
def accuPlot(Dic, title):
plt.figure()
plt.title('learning curve' + title + 'pruning')
plt.xlabel('Batch Size')
plt.ylabel('Accuracy')
plt.grid(True)
xList = []
yList = []
for keys in Dic:
xList.append(keys)
xList.sort()
for item in xList:
yList.append(Dic[item])
plt.plot(np.array(xList), np.array(yList))
plt.show()
def randomPlot(inFile):
withPruning = {}
withoutPruning = {}
withoutPruningTrain = []
withoutPruningValid = []
withoutPruningTest = []
withPruningTrain = []
withPruningValid = []
withPruningTest = []
data = parse.parse(inFile)
for i in range(100):
random.shuffle(data)
batchSize = random.randint(10, 300)
while batchSize in withoutPruning:
batchSize = random.randint(10, 300)
train = data[: int(batchSize * 0.7)]
valid = data[int(batchSize * 0.7):batchSize]
test = data[batchSize:]
tree = ID3.ID3(train, 'democrat')
'''
acc = ID3.test(tree, train)
#withoutPruningTrain.append(acc)
acc = ID3.test(tree, valid)
#withoutPruningValid.append(acc)
tree = ID3.ID3(train + valid, 'democrat')
acc = ID3.test(tree, test)
#withoutPruningTest.append(acc)
'''
ID3.prune(tree, valid)
# acc = ID3.test(tree, train)
# withPruningTrain.append(acc)
# acc = ID3.test(tree, valid)
# withPruningValid.append(acc)
acc = ID3.test(tree, test)
withPruning[batchSize] = acc
tree = ID3.ID3(train + valid, 'democrat')
acc = ID3.test(tree, test)
withoutPruning[batchSize] = acc
accuPlot(withoutPruning, 'without')
accuPlot(withPruning, 'with')
print len(withoutPruning), len(withPruning)
testID3AndEvaluate()
#root = ID3(preprocess("house_votes_84.data"), 0)
#print "root label", root.label
#print "\n\n\n\nBFS =++++++++++++++++++++++++++++\n", str(node.breadth_first_search(root))
testID3AndTest()
testPruning()
testPruningOnHouseData("house_votes_84.data")
randomPlot("house_votes_84.data")
| [
"bestlzl1994@gmail.com"
] | bestlzl1994@gmail.com |
aa8496b9327623dffb3ff03cf1fc191646340675 | bf9be62b49e1096e8983753e9a8606f9d4fdb987 | /beisia_app/memo/migrations/0003_lists_phone.py | 741b12afeda8026dab5ad46c8f656443ef9c00ba | [] | no_license | sakuraichigo/baisia | 6dbef747e8c77514e8e10985f5741c67a33412be | 4a77185420d761c64d3a336217d3d1c27b3c014a | refs/heads/master | 2023-01-30T19:36:17.810994 | 2020-12-11T07:10:03 | 2020-12-11T07:10:03 | 320,491,200 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 370 | py | # Generated by Django 3.0.5 on 2020-11-20 06:45
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('memo', '0002_lists_date'),
]
operations = [
migrations.AddField(
model_name='lists',
name='phone',
field=models.IntegerField(null=True),
),
]
| [
"sakura15yumy@gmail.com"
] | sakura15yumy@gmail.com |
0cbe171c509209bed85a34988e5940acc8efcb70 | e9c3c631eac669b211ff6ae99587916aba5ec71b | /Part5FeatureObtainer.py | 65ce9dcb9ba7afff8dca092cfcf74f3f09e92ded | [] | no_license | Shaun2h/Basic-HMM | 9d59759ba3ad1add3a5bd4c9682101d21420bb1d | 336b0ceae047d76c53ef147dec15863e63c4e2ed | refs/heads/master | 2020-04-06T21:47:53.452959 | 2019-01-24T08:37:28 | 2019-01-24T08:37:28 | 157,814,310 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 10,318 | py |
def line_feature(line,force_lowercase): # Returns the actual word, classification, and whether it is a punctuation
"""Place your lines here to process"""
holder = line.split()
classification = holder.pop()
string = "" # get completed word
for i in holder:
string += i
if force_lowercase:
string = string.lower()
if string.isalnum(): # is alphanumeric.
return string, classification, # False
else: # holds a punctuation. In all likelihood it shouldn't be a name anyway.
return string, classification # True
# Uncomment for punctuation handling. Not used in beta submission.
def converter(some_dict_of_dicts):
"""convert from raw counts to probabilities, based off containment in dictionary"""
for outerkey in some_dict_of_dicts.keys():
summer = 0
for innerkey in some_dict_of_dicts[outerkey]:
summer += some_dict_of_dicts[outerkey][innerkey]
for innerkey in some_dict_of_dicts[outerkey]:
some_dict_of_dicts[outerkey][innerkey] = some_dict_of_dicts[outerkey][innerkey] / summer
return some_dict_of_dicts
def file_parser(fileaddr, force_lowercase):
"""Grab your file addr and parse file for sentence"""
f = open(fileaddr, "r", encoding="UTF-8")
big_list = []
latest = []
for line in f:
if line != "\n": # is not empty line.
latest.append(line_feature(line, force_lowercase)) # obtain feature + tag
else:
big_list.append(latest)
latest = []
# for i in big_list:
# print(i)
f.close()
return big_list
def context_window_one_mle_tag_separation(sentences_list):
# gets for Word_Occurrences_in_tag/Total in tag.
# does not attempt to capture transition as it can be obtained from that of the other files
# instead, obtains the forward/backward words and the TAG.
# self word emission is not included
# this is the version that was originally included in the instructions.
# results in internal bias.
# If the word appears 400 times, 399 times in a 10,000 O-tag, vs 1 time in the 2 times
# I-negative tag, I negative emission is ruled as more likely.
# but on the other hand, you can always smooth for tags it doesn't appear as.
# some form of smoothing is required for unknown words.
# in this case, we will most likely use additive smoothing, or 1 + smoothing, just like the
# original instructions given.
forward_word = {}
backward_word = {}
start_tag_key = "_START_"
end_tag_key = "_STOP_"
for sentence in sentences_list:
for index in range(len(sentence)): # number of observations/tag in sentence
current_tag = sentence[index][1] # obtain current tag
######################################################################################
# BACKWARD EMISSION
if index != 0: # i.e not at the start of the sentence
word_before = sentence[index-1][0]
else: # next is at the end tag. i.e _END_TAG_
word_before = start_tag_key
if current_tag not in backward_word.keys(): # check if tag exists in back dict
backward_word[current_tag] = {}
try: # attempt to increment word, in its current tag
backward_word[current_tag][word_before] = \
backward_word[current_tag][word_before] + 1
except KeyError:
backward_word[current_tag][word_before] = 1
######################################################################################
# FORWARD EMISSION
if index + 1 < len(sentence):
# next is currently still in range of sentence's last word
next_word = sentence[index + 1][0]
else:
next_word = end_tag_key # next is stop.
if current_tag not in forward_word.keys(): # check if tag exists in back dict
forward_word[current_tag] = {}
try: # attempt to increment word, in its current tag
forward_word[current_tag][next_word] = \
forward_word[current_tag][next_word] + 1
except KeyError:
forward_word[current_tag][next_word] = 1
# print(forward_word)
# print(backward_word)
return forward_word, backward_word
def context_window_one_mle_own_word_distinction(sentences_list):
# Record all occurrences of words that occur before and after a central tag.
# i.e
# O B O
# Hello you twat
# then it records as Forward:{ B: {"Hello":1} } and Backward{ B: {"twat": 1} }
# Because of the way it is recorded, you get dictionaries with the TAG as it's header, and
# the number of occurrences of that word.
# The bias here is in some words always only leading up to one other particular tag in your set,
# which might not apply globally.
# This version like the previous, will lead to bias,
# as words that only appear as a particular foreword to a tag,
# will always result in the final result having that particular TAG.
# i.e if Hello only appears in B in the forward dictionary, but not in any other dictionary
# located inside forward, B will be the most likely TAG from that.
# Some form of smoothing is required.
forward_word = {}
backward_word = {}
start_tag_key = "_START_"
end_tag_key = "_STOP_"
list_of_tags = []
for sentence in sentences_list:
for index in range(len(sentence)): # number of observations/tag in sentence
current_tag = sentence[index][1] # obtain current tag
if current_tag not in list_of_tags:
list_of_tags.append(current_tag)
######################################################################################
# BACKWARD EMISSION
if index != 0: # i.e not at the start of the sentence
word_before = sentence[index-1][0]
else: # It's the starting of a sentence.
word_before = start_tag_key
# this acts as an indicator to tell us to disregard.
if word_before not in backward_word.keys() and word_before != start_tag_key:
# check if tag exists in back dict and is not START
backward_word[word_before] = {}
if word_before != start_tag_key: # ensure we disregard start tag
try: # attempt to increment word, in its current tag
backward_word[word_before][current_tag] = \
backward_word[word_before][current_tag] + 1
except KeyError:
backward_word[word_before][current_tag] = 1
######################################################################################
# FORWARD EMISSION
if index + 1 < len(sentence):
# next is currently still in range of sentence's last word
next_word = sentence[index + 1][0]
else:
next_word = end_tag_key # next is stop.
if next_word not in forward_word.keys() and next_word != end_tag_key:
# check if tag exists in back dict and is not STOP
forward_word[next_word] = {}
if next_word != end_tag_key: # ensure we aren't trying to count a stop tag.
try: # attempt to increment word, in its current tag
forward_word[next_word][current_tag] = \
forward_word[next_word][current_tag] + 1
except KeyError:
forward_word[next_word][current_tag] = 1
# training is more or less complete.
# print(forward_word)
# print(backward_word)
return forward_word, backward_word, list_of_tags
def add_unk_TAG_TOTAL1(provided_dict,list_of_tags):
# the version of a unk for the dictionary in the format of
# context_window_one_mle_own_word_distinction
# unk is estimated in the same way as the provided rule.
count = {}
for tag in list_of_tags:
count[tag] = 0
for word in provided_dict:
for tag in provided_dict[word]:
count[tag] = count[tag] + provided_dict[word][tag]
summer = 0
for tag in list_of_tags:
summer += count[tag]
for tag in list_of_tags:
count[tag] = count[tag]/summer
provided_dict["#UNK#"] = count
return provided_dict
def add_one_smoother_converter(either_word, tag_list):
"""add one smoothing is performed for every word. does not apply to unknowns."""
# this method is debatably fairer ish for words.
# you lose the information of how often that tag has appeared, and to an extent, whether the
# word should ever be in that tag, instead choosing to focus on allowing all words to be
# anything. Works best for words like "fucking", which can be used in literally any tag.
# in that case however
for outerkey in either_word.keys():
summer = 0
for innerkey in either_word[outerkey]:
summer += either_word[outerkey][innerkey]
temp_list = [] # to hold tags that did not appear
for innerkey in tag_list:
if innerkey in either_word[outerkey].keys():
either_word[outerkey][innerkey] = either_word[outerkey][innerkey] / summer
else:
temp_list.append(innerkey)
summer += 1 # incrememnt the summer for add one smoothing use
holdvalue = 1/summer # compute a add one smoothing tag probability
for tag in temp_list:
either_word[outerkey][tag] = holdvalue
return either_word
# testing stuff
#
# sentence_get = file_parser("EN/train", True)
# print("OWN WORD DISTINCTION")
# forward_dist, backward_dist, list_o_tags = context_window_one_mle_own_word_distinction(sentence_get)
# print(converter(forward_dist))
# print(converter(backward_dist))
# print(add_one_smoother_converter(forward_dist, list_o_tags))
# print(add_one_smoother_converter(backward_dist, list_o_tags))
"""
print("TAG SEPARATION")
forwardtag, backwardtag = context_window_one_mle_tag_separation(sentence_get)
print(converter(forwardtag))
print(converter(backwardtag))
"""
| [
"smurfination1@gmail.com"
] | smurfination1@gmail.com |
477db84e7b886bf239362f2011c9005cc081462c | 0a973640f0b02d7f3cf9211fcce33221c3a50c88 | /.history/src/qichamao_cmpInfo_20210129160650.py | 41a75bbec713f276826d997f9fcd49cf5f4aab93 | [] | no_license | JiajunChen123/IPO_under_review_crawler | 5468b9079950fdd11c5e3ce45af2c75ccb30323c | 031aac915ebe350ec816c05a29b5827fde588567 | refs/heads/main | 2023-02-26T08:23:09.622725 | 2021-02-04T10:11:16 | 2021-02-04T10:11:16 | 332,619,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,386 | py | import requests
from bs4 import BeautifulSoup
import time
# login = {'user':'13710149700',
# 'password':'123456'}
# 使用的网站是企查查
# requests.post('https://www.qichamao.com',data=login,headers=afterLogin_headers)
afterLogin_headers = {'Cookie':'qznewsite.uid=y4eseo3a1q4xbrwimor3o5tm; Hm_lvt_55ad112b0079dd9ab00429af7113d5e3=1611805092; qz.newsite=6C61702DD95709F9EE190BD7CCB7B62C97136BAC307B6F0B818EC0A943307DAB61627F0AC6CD818268C10D121B37F840C1EF255513480EC3012A7707443FE523DD7FF79A7F3058E5E7FB5CF3FE3544235D5313C4816B54C0CDB254F24D8ED5235B722BCBB23BE62B19A2370E7F0951CD92A731FE66C208D1BE78AA64758629806772055F7210C67D442DE7ABBE138EF387E6258291F8FBF85DFF6C785E362E2903705A0963369284E8652A61531293304D67EBB8D28775FBC7D7EBF16AC3CCA96F5A5D17; Hm_lpvt_55ad112b0079dd9ab00429af7113d5e3=1611892605',
'Referer':'https://www.qichamao.com/',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36'}
def get_compInfo(comp):
r = requests.get('https://www.qichamao.com/search/all/{}'.format(comp),headers=afterLogin_headers)
r.raise_for_status()
r.encoding = 'utf-8' #linux utf-8
soup = BeautifulSoup(r.text,features="html.parser")
url = 'http://www.qichamao.com' + soup.find(attrs={'class':'listsec_con'}).a['href']
# soup.find(attrs={'class':'listsec_con'})
time.sleep(5)
rs = requests.get(url,headers=afterLogin_headers)
rs.encoding='utf-8'
soup2 = BeautifulSoup(rs.text,'html.parser')
info = soup2.find(attrs={'class':'qd-table-body li-half f14'}).findAll('div')
info = [i.get_text().strip() for i in info]
compinfo = {'法定代表人':info[0],
'纳税人识别号':info[1],
'名称':info[2],
'机构代码':info[3],
'注册号':info[4],
'注册资本':info[5],
'统一社会信用代码':info[6],
'登记机关':info[7],
'经营状态':info[8],
'成立日期':info[9],
'企业类型':info[10],
'经营期限':info[11],
'所属地区':info[12],
'核准时间':info[13],
'企业地址':info[14],
'经营范围':info[15]}
return compinfo
if __name__ == '__main__':
compList =
| [
"chenjiajun.jason@outlook.com"
] | chenjiajun.jason@outlook.com |
2fefc1e52ae0e6cfbbfc6ff6ca2d377a99c5d549 | 39896b6ca41d589e2eccb3dcb0c716340a444afe | /tensorflow/2.定义变量variable.py | 6536225d9b0260abfb7dd04de5d6a3ff5a8fcf00 | [] | no_license | coco369/algorithm | 237bf5f7691a70bd98c90be5c604a16155448e86 | a069ae7ee6f4cb421ba3e44d13371716e75314b6 | refs/heads/master | 2022-12-29T10:48:11.282338 | 2020-10-13T10:25:46 | 2020-10-13T10:25:46 | 263,520,123 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 242 | py | import tensorflow as tf
"""
定义变量
"""
a = tf.Variable(1)
print('value:', a.numpy())
b = a + 1
print('value:', b.numpy())
c = tf.Variable(4)
c.assign_add(2)
print('value:', c.numpy())
c.assign_sub(1)
print('value:', c.numpy())
| [
"1571236356@qq.com"
] | 1571236356@qq.com |
b5ad7749f829100b0ef3b43a66a64a5e805ac245 | 469a4e535877e868c590ddfdeae7451b9ad3b5bf | /case3_form_filling/pybrain_rlklm/egreedy.py | 5158f189554052db45ebae2419cd98ed40d36147 | [
"BSD-2-Clause"
] | permissive | aalto-speech/rl-klm | 443c3c182e30d4fde75d44b80f13db929a99d9d9 | 1a48fc49c1afae581720dc2eab4055816b887cb2 | refs/heads/master | 2021-07-19T05:08:14.276118 | 2020-05-18T10:57:32 | 2020-05-18T10:57:32 | 163,522,009 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,564 | py | __author__ = "Thomas Rueckstiess, ruecksti@in.tum.de"
# MODIFIED by Katri Leino: Only select allowed actions in exploration.
from scipy import random, array
import numpy as np
from pybrain.rl.explorers.discrete.discrete import DiscreteExplorer
from pybrain.rl.environments.environment import Environment
class EpsilonGreedyExplorer(DiscreteExplorer):
""" A discrete explorer, that executes the original policy in most cases,
but sometimes returns a random action (uniformly drawn) instead. The
randomness is controlled by a parameter 0 <= epsilon <= 1. The closer
epsilon gets to 0, the more greedy (and less explorative) the agent
behaves.
"""
def __init__(self, epsilon = 0.3, decay = 0.9999):
DiscreteExplorer.__init__(self)
self.epsilon = epsilon
self.decay = decay
self.env = []
def _forwardImplementation(self, inbuf, outbuf):
""" Draws a random number between 0 and 1. If the number is less
than epsilon, a random action is chosen. If it is equal or
larger than epsilon, the greedy action is returned.
"""
assert self.module
# Choose action from allowed actions.
if random.random() < self.epsilon:
# Only select allowed actions
allowed_actions = np.where(np.array(self.env.visited_states) == 0)[0]
act = array([random.choice(allowed_actions)])
outbuf[:] = act
else:
outbuf[:] = inbuf
self.epsilon *= self.decay
| [
"katri.k.leino@aalto.fi"
] | katri.k.leino@aalto.fi |
af50ff57d4d23ba855a7064fe2d3e77f667e3432 | fa57716e950b1ad1970f158ac2346c9c918267a6 | /opengever/latex/tests/test_dossierlisting.py | 4847964ef8ff53fa86cb77fe71382dedf7f74b2a | [] | no_license | hellfish2/opengever.core | 1e76e04439f89518bb3f7bb021f83ae4fa4ff7fc | 954964872f73c0d18d5b0e0ab2dbf603849e4e87 | refs/heads/master | 2020-04-08T18:03:06.781579 | 2014-06-05T13:02:05 | 2014-06-05T13:02:05 | 20,575,363 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,328 | py | from ftw.pdfgenerator.interfaces import IBuilder
from ftw.pdfgenerator.interfaces import ILaTeXLayout
from ftw.pdfgenerator.interfaces import ILaTeXView
from ftw.testing import MockTestCase
from grokcore.component.testing import grok
from opengever.latex import dossierlisting
from opengever.latex.testing import LATEX_ZCML_LAYER
from zope.component import adaptedBy
from zope.component import getMultiAdapter
from zope.interface.verify import verifyClass
from zope.publisher.interfaces.browser import IDefaultBrowserLayer
class TestDossierListingPDFView(MockTestCase):
layer = LATEX_ZCML_LAYER
def test_is_registered(self):
context = self.create_dummy()
request = self.providing_stub([IDefaultBrowserLayer])
self.replay()
view = getMultiAdapter((context, request),
name='pdf-dossier-listing')
self.assertTrue(isinstance(
view, dossierlisting.DossierListingPDFView))
def test_render_adds_browser_layer(self):
context = request = self.create_dummy()
view = self.mocker.patch(
dossierlisting.DossierListingPDFView(context, request))
self.expect(view.allow_alternate_output()).result(False)
self.expect(view.export())
self.replay()
view.render()
self.assertTrue(dossierlisting.IDossierListingLayer.providedBy(
request))
class TestDossierListingLaTeXView(MockTestCase):
layer = LATEX_ZCML_LAYER
def test_component_is_registered(self):
context = self.create_dummy()
request = self.providing_stub([dossierlisting.IDossierListingLayer])
layout = self.providing_stub([ILaTeXLayout])
self.replay()
view = getMultiAdapter((context, request, layout), ILaTeXView)
self.assertEqual(type(view), dossierlisting.DossierListingLaTeXView)
def test_implements_interface(self):
self.assertTrue(ILaTeXView.implementedBy(
dossierlisting.DossierListingLaTeXView))
verifyClass(ILaTeXView, dossierlisting.DossierListingLaTeXView)
def test_adapts_layer(self):
context_iface, request_iface, layout_iface = adaptedBy(
dossierlisting.DossierListingLaTeXView)
self.assertEqual(request_iface, dossierlisting.IDossierListingLayer)
| [
"jone@jone.ch"
] | jone@jone.ch |
3394c6a751749a717887e0e98f938a281d9e151c | 46e7c10f91329d05b9200ab0e53950abc8ab6d8b | /app/user/tests/test_user_api.py | 2f0938d6300b9c0455c68a9de044229e3f302c5a | [
"MIT"
] | permissive | Romitha/recipe-api-django-rest | 4306f4c55a044768f5f4e56ad1a8a357c04a0eaf | d1b64ab2fe384eee8cff124168273ac7316bf72e | refs/heads/master | 2020-12-09T14:40:01.993169 | 2020-01-28T06:07:08 | 2020-01-28T06:07:08 | 233,336,519 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,834 | py | from django.test import TestCase
from django.contrib.auth import get_user_model
from django.urls import reverse
from rest_framework.test import APIClient
from rest_framework import status
CREATE_USER_URL = reverse('user:create')
TOKEN_URL = reverse('user:token')
ME_URL = reverse('user:me')
def create_user(**params):
return get_user_model().objects.create_user(**params)
class PublicUserApiTests(TestCase):
""" Test the user api public"""
def setUp(self):
self.client = APIClient()
def test_create_valid_user_success(self):
""" Test creating user with valid payload is successful"""
payload = {
'email': 'test@gmail.com',
'password': 'test123',
'name': 'Test Name'
}
res = self.client.post(CREATE_USER_URL, payload)
self.assertEqual(res.status_code, status.HTTP_201_CREATED)
user = get_user_model().objects.get(**res.data)
self.assertTrue(user.check_password(payload['password']))
self.assertNotIn('password', res.data)
def test_user_exists(self):
"""Test creating user that already exists fail"""
payload = {'email': 'test@gmail.com', 'password': 'test123'}
create_user(**payload)
res = self.client.post(CREATE_USER_URL, payload)
self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)
def test_password_too_short(self):
"""Test that the password must be more than 5 characters"""
payload = {'email': 'test@gmail.com', 'password': 'pw'}
res = self.client.post(CREATE_USER_URL, payload)
self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)
user_exists = get_user_model().objects.filter(
email=payload['email']
).exists()
self.assertFalse(user_exists)
def test_create_token_for_user(self):
"""Test that a token is created for the user"""
payload = {'email': 'test@gmail.com', 'password': 'test123'}
create_user(**payload)
res = self.client.post(TOKEN_URL, payload)
print(res)
self.assertIn('token', res.data)
self.assertEqual(res.status_code, status.HTTP_200_OK)
def test_create_token_invalid_credentials(self):
"""Test that token is not created if invalid credentials are given"""
create_user(email='test@londonappdev.com', password='testpass')
payload = {'email': 'test@londonappdev.com', 'password': 'wrong'}
res = self.client.post(TOKEN_URL, payload)
self.assertNotIn('token', res.data)
self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)
def test_create_token_no_user(self):
"""Test that token is not created if user doens't exist"""
payload = {'email': 'test@londonappdev.com', 'password': 'testpass'}
res = self.client.post(TOKEN_URL, payload)
self.assertNotIn('token', res.data)
self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)
def test_create_token_missing_field(self):
"""Test that email and password are required"""
res = self.client.post(TOKEN_URL, {'email': 'one', 'password': ''})
self.assertNotIn('token', res.data)
self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)
def test_retrieve_user_unauthorized(self):
"""Test that authentication is required for users"""
res = self.client.get(ME_URL)
self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)
class PrivateUserApiTests(TestCase):
"""Test API requests that require authentication"""
def setUp(self):
self.user = create_user(
email='test@mail.com',
password='testpass',
name='name'
)
self.client = APIClient()
self.client.force_authenticate(user=self.user)
def test_retrieve_profile_success(self):
"""Test retrieving profile for logged user"""
res = self.client.get(ME_URL)
self.assertEqual(res.status_code, status.HTTP_200_OK)
self.assertEqual(res.data, {
'name': self.user.name,
'email': self.user.email
})
def test_post_me_not_allowed(self):
"""Test that post is not allow on the url"""
res = self.client.post(ME_URL, {})
self.assertEqual(res.status_code, status.HTTP_405_METHOD_NOT_ALLOWED)
def test_update_user_profile(self):
"""Test update user profile for authenticate user"""
payload = {'name': 'new name', 'password': "newpassword123"}
res = self.client.patch(ME_URL, payload)
self.user.refresh_from_db()
self.assertEqual(self.user.name, payload['name'])
self.assertTrue(self.user.check_password(payload['password']))
self.assertEqual(res.status_code, status.HTTP_200_OK)
| [
"janith2011@gmail.com"
] | janith2011@gmail.com |
99b09c524ea449b6bbe9bf5eaacbfb72619c2baa | f4be48866d7d2181d563939cee82671b893ddbb9 | /kubecd/cli/__init__.py | cd5b30c9e7f93b6d691f26ac10bb7aeef69f7ed4 | [
"Apache-2.0"
] | permissive | cvega/kubecd | cd893639cf6e683caa6a94eea730cf956be3f0ed | 3e181d29caa4220c19dcd80ed44e5aaec1e6c955 | refs/heads/master | 2020-03-26T22:19:51.775077 | 2018-06-20T06:12:23 | 2018-06-20T06:12:23 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,260 | py | import argparse
import os
import sys
import argcomplete
import logging
from argcomplete import FilesCompleter
from blessings import Terminal
from .. import __version__
from .commands import (
apply_env,
dump_env,
indent_file,
init_contexts,
json2yaml,
lint_environment,
list_kind,
observe_new_image,
poll_registries,
use_env_context,
CliError,
)
t = Terminal()
logger = logging.getLogger(__name__)
def parser(prog='kcd') -> argparse.ArgumentParser:
p = argparse.ArgumentParser(prog=prog)
# not used yet, but left here as a reminder to not steal the -c flag
# p.add_argument('-c', '--config-file', help='path to configuration file')
p.add_argument(
'-f', '--environments-file',
help='KubeCD config file file (default $KUBECD_ENVIRONMENTS or "environments.yaml")',
metavar='FILE',
default=os.getenv('KUBECD_ENVIRONMENTS', 'environments.yaml')).completer = FilesCompleter(
allowednames=('.yaml', '.yml'), directories=False)
p.add_argument(
'--version',
help='Show version and exit.',
action='version',
version='kubecd ' + __version__)
p.add_argument('--verbose', '-v', help='Increase verbosity level', action='count', default=0)
s = p.add_subparsers(dest='command', title='Subcommands', description='Use one of these sub-commands:')
apply = s.add_parser('apply',
help='apply changes to Kubernetes')
apply.add_argument('--dry-run', '-n', action='store_true', default=False,
help='dry run mode, only print commands')
apply.add_argument('--debug', action='store_true', default=False,
help='run helm with --debug')
apply.add_argument('--releases', '-r', action='append',
help='apply only these releases')
apply.add_argument('--cluster', '-c', nargs='?', metavar='CLUSTER',
help='apply all environments in CLUSTER')
apply.add_argument('--init', action='store_true', default=False,
help='Initialize credentials and contexts')
apply.add_argument('env_name', nargs='?', metavar='ENV',
help='name of environment to apply, must be specified unless --cluster is')
apply.set_defaults(func=apply_env)
# diff = s.add_parser('diff', help='show diffs between running and git release')
# diff.add_argument('--releases', '-r', help='which releases to diff', action='append')
# diff.add_argument('env', nargs='?', help='name of environment')
# diff.set_defaults(func=diff_release)
poll_p = s.add_parser('poll',
help='poll for new images in registries')
poll_p.add_argument('--patch', '-p', action='store_true',
help='patch releases.yaml files with updated version')
poll_p.add_argument('--releases', '-r', action='append',
help='poll this specific release')
poll_p.add_argument('--image', '-i',
help='poll releases using this image')
poll_p.add_argument('--cluster', '-c',
help='poll all releases in this cluster')
poll_p.add_argument('env', nargs='?',
help='name of environment to poll')
poll_p.set_defaults(func=poll_registries)
dump_p = s.add_parser('dump',
help='dump commands for one or all environments')
dump_p.add_argument('env', nargs='?',
help='name of environment to dump')
dump_p.set_defaults(func=dump_env)
list_p = s.add_parser('list',
help='list clusters, environments or releases')
list_p.add_argument('kind', choices=['env', 'release', 'cluster'],
help='what to list')
list_p.set_defaults(func=list_kind)
indent_p = s.add_parser('indent',
help='canonically indent YAML files')
indent_p.add_argument('files', nargs='+',
help='file[s] to indent')
indent_p.set_defaults(func=indent_file)
observe = s.add_parser('observe',
help='observe a new image version')
observe.add_argument('--image', '-i', metavar='IMAGE:TAG',
help='the image, including tag')
observe.add_argument('--patch', action='store_true', default=False,
help='patch release files with updated tags')
observe.add_argument('--submit-pr', action='store_true', default=False,
help='submit a pull request with the updated tags')
observe.set_defaults(func=observe_new_image)
completion_p = s.add_parser('completion',
help='print shell completion script')
completion_p.set_defaults(func=print_completion, prog=prog)
j2y = s.add_parser('json2yaml', help='JSON to YAML conversion utility (stdin/stdout)')
j2y.set_defaults(func=json2yaml)
init = s.add_parser('init', help='Initialize credentials and contexts')
init.add_argument('--cluster',
help='Initialize contexts for all environments in a cluster')
init.add_argument('--dry-run', '-n', action='store_true',
help='print commands instead of running them')
init.add_argument('env_name', metavar='ENV', nargs='?',
help='environment to initialize')
init.add_argument('--contexts-only', action='store_true',
help='initialize contexts only, assuming that cluster credentials are set up')
init.set_defaults(func=init_contexts)
use = s.add_parser('use',
help='switch kube context to the specified environment')
use.add_argument('env', metavar='ENV',
help='environment name')
use.set_defaults(func=use_env_context)
lint = s.add_parser('lint',
help='inspect the contents of a release, exits with non-0 if there are issues')
lint.add_argument('--cluster',
help='Lint all environments in a cluster')
lint.add_argument('env_name', metavar='ENV', nargs='?',
help='environment name')
lint.set_defaults(func=lint_environment)
return p
def verbose_log_level(v):
if v == 0:
return logging.WARNING
if v == 1:
return logging.INFO
return logging.DEBUG
def print_completion(prog, **kwargs):
shell = os.path.basename(os.getenv('SHELL'))
if shell == 'bash' or shell == 'tcsh':
sys.stdout.write(argcomplete.shellcode(prog, shell=shell))
def main():
p = parser()
argcomplete.autocomplete(p)
args = p.parse_args()
kwargs = args.__dict__
if 'func' not in kwargs:
p.print_help(sys.stderr)
sys.exit(1)
func = kwargs['func']
del (kwargs['func'])
logging.basicConfig(stream=sys.stderr,
format='{levelname} {message}',
style='{',
level=verbose_log_level(args.verbose))
try:
func(**kwargs)
except CliError as e:
print('{t.red}ERROR{t.normal}: {msg}'.format(msg=str(e), t=t), file=sys.stderr)
if __name__ == '__main__':
main()
| [
"stig@zedge.net"
] | stig@zedge.net |
7a0b60792ed25223de52fbb3b5be3e40333b2e4a | 01a8424a51d61649a19128c446fbcc3e83d3d484 | /accounts/views.py | d39fa08d3f65bbeae235c1836e07b2b672b1aebb | [] | no_license | MarkyMOD/Real_Estate_Website | c25c68560a1cc294de17f97dee2535090155a27a | 97450fedfb597e865718aa09220949614f6c80de | refs/heads/master | 2022-12-23T21:35:30.129225 | 2019-07-11T21:12:01 | 2019-07-11T21:12:01 | 163,868,044 | 0 | 0 | null | 2022-11-22T03:11:06 | 2019-01-02T17:05:00 | Python | UTF-8 | Python | false | false | 2,857 | py | from django.shortcuts import render, redirect
from django.contrib import messages, auth
from django.contrib.auth.models import User
from contacts.models import Contact
# Create your views here.
def register(request):
if request.method == 'POST':
# Get form values
first_name = request.POST['first_name']
last_name = request.POST['last_name']
username = request.POST['username']
email = request.POST['email']
password = request.POST['password']
password2 = request.POST['password2']
# Check if Passwords Match
if password == password2:
# Check Username
if User.objects.filter(username=username).exists():
messages.error(request, 'That username is taken')
return redirect('register')
else:
# Check Email
if User.objects.filter(email=email).exists():
messages.error(request, 'That email is being used')
return redirect('register')
else:
# Looks Good
user = User.objects.create_user(username=username, password=password, email=email, first_name=first_name, last_name=last_name)
# Login After Register
auth.login(request, user)
messages.success(request, 'You are now logged in')
return redirect('index')
# If You Don't Want to Login After Register
# user.save()
# messages.success(request, 'You are now registered and can log in')
# return redirect('login')
else:
messages.error(request, 'Passwords do not match')
return redirect('register')
else:
return render(request, 'accounts/register.html')
def login(request):
if request.method == 'POST':
# Login
username = request.POST['username']
password = request.POST['password']
user = auth.authenticate(username=username, password=password)
if user is not None:
auth.login(request, user)
messages.success(request, 'You are now logged in')
return redirect('dashboard')
else:
messages.error(request, 'Invalid credential')
return redirect('login')
else:
return render(request, 'accounts/login.html')
def logout(request):
if request.method == 'POST':
auth.logout(request)
messages.success(request, 'You are now logged out')
return redirect('index')
def dashboard(request):
user_contacts = Contact.objects.order_by('-contact_date').filter(user_id=request.user.id)
context = {
'contacts': user_contacts
}
return render(request, 'accounts/dashboard.html', context) | [
"strictlybusinessemail242@gmail.com"
] | strictlybusinessemail242@gmail.com |
ea2bfba36cf210900ac9c97e85fdeeed2b902033 | bbd1b7f86e39f7bd3daf5d86ccdaa388a5fd0d74 | /decision_tree.py | 836cdea55e29220b46599851d387fc91e0932d38 | [] | no_license | westernmeadow/CS4210Assignment1 | de7a7d72a0e16543cd0210c4a9d5079d77fe4a1c | add2b1c29befed4b87a4ec5f7bb4cb09693df233 | refs/heads/main | 2023-04-13T17:53:04.402556 | 2021-04-09T21:32:58 | 2021-04-09T21:32:58 | 356,402,971 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,053 | py | #-------------------------------------------------------------------------
# AUTHOR: Wesley Kwan
# FILENAME: decision_tree
# SPECIFICATION: ID3 algorithm for contact lens data
# FOR: CS 4200- Assignment #1
# TIME SPENT: 30 min
#-----------------------------------------------------------*/
#IMPORTANT NOTE: DO NOT USE ANY ADVANCED PYTHON LIBRARY TO COMPLETE THIS CODE SUCH AS numpy OR pandas. You have to work here only with standard vectors and arrays
#importing some Python libraries
from sklearn import tree
import matplotlib.pyplot as plt
import csv
db = []
X = []
Y = []
#reading the data in a csv file
with open('contact_lens.csv', 'r') as csvfile:
reader = csv.reader(csvfile)
for i, row in enumerate(reader):
if i > 0: #skipping the header
db.append (row)
print(row)
#transform the original training features to numbers and add to the 4D array X. For instance Young = 1, Prepresbyopic = 2, Presbyopic = 3, so X = [[1, 1, 1, 1], [2, 2, 2, 2], ...]]
#--> add your Python code here
# X =
for instance in db:
transform = []
for attribute in range(len(instance)-1):
if instance[attribute] in ('Young', 'Myope', 'No', 'Reduced'):
transform.append(1)
elif instance[attribute] in ('Prepresbyopic', 'Hypermetrope', 'Yes', 'Normal'):
transform.append(2)
else:
transform.append(3)
X.append(transform)
print(X)
#transform the original training classes to numbers and add to the vector Y. For instance Yes = 1, No = 2, so Y = [1, 1, 2, 2, ...]
#--> addd your Python code here
# Y =
for instance in db:
if instance[len(instance)-1] == 'Yes':
Y.append(1)
else:
Y.append(2)
#fitting the decision tree to the data
clf = tree.DecisionTreeClassifier(criterion = 'entropy')
clf = clf.fit(X, Y)
#plotting the decision tree
tree.plot_tree(clf, feature_names=['Age', 'Spectacle', 'Astigmatism', 'Tear'], class_names=['Yes','No'], filled=True, rounded=True)
plt.show()
| [
"noreply@github.com"
] | westernmeadow.noreply@github.com |
0235c874286b4bdd4f3f54cb7327d8aef8741517 | 74e5b97fd7ead5f2d0a37c03c5109f23e05e2da4 | /write_csv.py | 6d4243b7f4831de6ad8c133adb4a60a4bf4253eb | [] | no_license | Dream-991029/Lago | e3c173e1d61389f8de729499d4234a5ebf361df6 | 0f7c87bddc0a981a898adc92d631bcb6a37db723 | refs/heads/master | 2023-07-23T20:12:08.712517 | 2021-09-10T06:03:23 | 2021-09-10T06:03:23 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,134 | py | import csv
from typing import List, NoReturn
class Csv(object):
"""
封装csv写入类。
该类包含列表嵌套字典所涉及到的一些常用属性。
属性:
file_path: string类型的目标文件路径
data_list: list类型的数据
count: int类型计数器
"""
def __init__(self) -> NoReturn:
pass
def append_csv(self, file_path: str, data_list: List, count: int) -> int:
"""
创建csv并追加数据
:param file_path: 目标文件路径
:param data_list: 数据列表(列表嵌套字典)
:param count: 计数器
:return num: 返回最终计数器数量
"""
with open(file_path, 'w+', encoding='GBK', newline='') as file:
f_csv = csv.DictWriter(file, data_list[0].keys())
# 回退指针到首行
file.seek(0)
if file.readline().strip("\n") == "":
f_csv.writeheader()
f_csv.writerows(data_list)
num = count + len(data_list)
print(f"{num}条数据, 写入完成!!!!!")
return num
| [
"981846339@qq.com"
] | 981846339@qq.com |
43471736de06cb51b5cd20be7f2654515cc9d4f7 | c074333c90e682646e49d4d9a085ac7cc265d3d5 | /mysite/polls/models.py | 487cee3c09377a9c7f07f528e879d105f100ab1f | [] | no_license | kHarshit/django_tutorial | 0bc9d15128621dabdabe7cd0f53a74a3baacf482 | 75bcdcf88dcd96076bdcf10ddcdca495784dca10 | refs/heads/master | 2020-05-28T13:20:10.285152 | 2017-02-20T18:57:49 | 2017-02-20T18:57:49 | 82,591,096 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 967 | py | from __future__ import unicode_literals
import datetime
from django.db import models
from django.utils import timezone
# Create your models here.
class Question(models.Model):
question_text = models.CharField(max_length=200)
pub_date = models.DateTimeField('date published')
def __str__(self):
return self.question_text
def was_published_recently(self):
return timezone.now() - datetime.timedelta(days=1) <= self.pub_date <= timezone.now()
# return self.pub_date >= timezone.now() - datetime.timedelta(days=1)
was_published_recently.admin_order_field = 'pub_date'
was_published_recently.boolean = True
was_published_recently.short_description = 'Published recently?'
class Choice(models.Model):
question = models.ForeignKey(Question, on_delete=models.CASCADE)
choice_text = models.CharField(max_length=200)
votes = models.IntegerField(default=0)
def __str__(self):
return self.choice_text | [
"harshitk.997@gmail.com"
] | harshitk.997@gmail.com |
db2708b2709b6d896c466cb05bbf921c3dac4c93 | 5be7ca1d2ee8353f966d50dd0957cad08c32d1d6 | /assignments/web_practice/second_practice/po_weixin/testcases/test_addcontact.py | 0373dcb2620bbcd4795a3893da387a2341ea419e | [] | no_license | InsaneLoafer/HogwartsLG4_ZT | 48a6b1d578bad48c92b541abb862dcb17c6d338e | 870c66565e34329122a7d1953035718c251c00e0 | refs/heads/master | 2023-01-14T13:40:37.264260 | 2020-11-22T09:40:29 | 2020-11-22T09:40:29 | 310,861,090 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,088 | py | #!/usr/bin/python3
# -*- coding: utf-8 -*-
# @Time : 2020/11/8 20:41
# @Author : ZhangTao
# @File : test_addcontact.py
import allure
import pytest
from assignments.web_practice.second_practice.po_weixin.pages.index_pages.index_page import IndexPage
@allure.feature('测试添加成员')
class TestAddContact:
username = 'aa'
acctid = '1234'
member_tel = '13411111111'
def setup(self):
self.index = IndexPage()
@allure.story("测试添加成员")
def test_addmember(self):
# 赋值addmember
with allure.step("点击添加成员"):
addmember = self.index.click_add_member()
# 进行addmember
with allure.step("输入成员姓名、账号、电话号码"):
addmember.add_member(self.username, self.acctid, self.member_tel)
# 添加成员姓名到报告中
allure.attach(self.username, '成员姓名', attachment_type=allure.attachment_type.TEXT )
assert addmember.get_member(self.username)
if __name__ == '__main__':
pytest.main('-v', 'test_addcontact.py') | [
"Insane_Loafer@163.com"
] | Insane_Loafer@163.com |
9bbca53ee48cb4bac59c71ec6959ecf7494d0554 | 039ad6224e8954f5889a388c5fd09faf53892746 | /socket-service/server/room.py | 20a71e662626d8470f5ade9f2ac66baa72908dfe | [
"MIT"
] | permissive | TheSmartMonkey/codenames | f70b0166f456d862409d5dc65d3de38daf86083f | a39946c8c705d50548f655838e4d32525c211e30 | refs/heads/master | 2023-04-22T05:49:41.586522 | 2020-05-12T19:29:03 | 2020-05-12T19:29:03 | 256,967,291 | 2 | 0 | MIT | 2021-05-06T20:05:19 | 2020-04-19T10:05:13 | JavaScript | UTF-8 | Python | false | false | 2,129 | py | import uuid
from types import SimpleNamespace
from game import CodenamesGame
from random import sample
class Room(object):
def __init__(self):
self.roomid=uuid.uuid1().hex
self.players={}
self.game=None
def addPlayer(self,playername,avatar,isAdmin):
if playername not in self.players:
team=sample(("blue","red"),1)[0]
if len(self.players)==0:
role=sample(("spymaster","player"),1)[0]
elif self.teamHasRole(team,"spymaster"):
if self.teamHasRole(team,"player"):
team=[t for t in ("blue","red") if t!=team][0]
if self.teamHasRole(team,"spymaster"):
role="player"
else:
role="spymaster"
else:
role="player"
else:
role="spymaster"
self.players[playername]=SimpleNamespace(
name=playername,
avatar=avatar,
team=team,
isAdmin=isAdmin,
role=role,
isReady=isAdmin)
return self.players[playername]
def teamHasRole(self,team,role):
return len([p for p in self.players.values() if p.team==team and p.role==role])>0
def deletePlayer(self,playername):
del self.players[playername]
def assignTeam(self,playername,team):
self.players[playername].team=team
return self.players[playername].__dict__
def assignRole(self,playername,role):
self.players[playername].role=role
return self.players[playername].__dict__
def getRole(self,playername):
return self.players[playername].role
def getPlayers(self):
return [player.__dict__ for player in self.players.values()]
def changePlayerStatus(self,playername,isReady):
self.players[playername].isReady=isReady
return self.players[playername].__dict__
def createGame(self,language):
self.game=CodenamesGame(language)
return self.game
| [
"gilles.vandelle@kelkoo.com"
] | gilles.vandelle@kelkoo.com |
89b107a01160959d3a7d92a2f824a53b46849515 | 7df7642c30f0cd09db47c42abe2738a00d8c9562 | /hearthstone/deckstrings.py | bb7ffc3007aa14a8b418ea181aab3366577b118e | [
"MIT"
] | permissive | mshirinyan/python-hearthstone | 601887c49385f041acd0c98c23170269b29ff5f5 | 3855e9565d45f0a5677fffe2f88cbe160cc6c7e1 | refs/heads/master | 2021-09-07T12:33:05.479242 | 2018-02-14T12:33:20 | 2018-02-14T16:05:20 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,991 | py | """
Blizzard Deckstring format support
"""
import base64
from io import BytesIO
from .enums import FormatType
DECKSTRING_VERSION = 1
def _read_varint(stream):
shift = 0
result = 0
while True:
c = stream.read(1)
if c == "":
raise EOFError("Unexpected EOF while reading varint")
i = ord(c)
result |= (i & 0x7f) << shift
shift += 7
if not (i & 0x80):
break
return result
def _write_varint(stream, i):
buf = b""
while True:
towrite = i & 0x7f
i >>= 7
if i:
buf += bytes((towrite | 0x80, ))
else:
buf += bytes((towrite, ))
break
return stream.write(buf)
class Deck:
@classmethod
def from_deckstring(cls, deckstring):
instance = cls()
instance.cards, instance.heroes, instance.format = parse_deckstring(deckstring)
return instance
@property
def as_deckstring(self):
return write_deckstring(self.cards, self.heroes, self.format)
def get_dbf_id_list(self):
return sorted(self.cards, key=lambda x: x[0])
def trisort_cards(cards):
cards_x1, cards_x2, cards_xn = [], [], []
for cardid, count in cards:
if count == 1:
list = cards_x1
elif count == 2:
list = cards_x2
else:
list = cards_xn
list.append((cardid, count))
return cards_x1, cards_x2, cards_xn
def parse_deckstring(deckstring):
decoded = base64.b64decode(deckstring)
data = BytesIO(decoded)
if data.read(1) != b"\0":
raise ValueError("Invalid deckstring")
version = _read_varint(data)
if version != DECKSTRING_VERSION:
raise ValueError("Unsupported deckstring version %r" % (version))
format = _read_varint(data)
try:
format = FormatType(format)
except ValueError:
raise ValueError("Unsupported FormatType in deckstring %r" % (format))
heroes = []
num_heroes = _read_varint(data)
for i in range(num_heroes):
heroes.append(_read_varint(data))
cards = []
num_cards_x1 = _read_varint(data)
for i in range(num_cards_x1):
card_id = _read_varint(data)
cards.append((card_id, 1))
num_cards_x2 = _read_varint(data)
for i in range(num_cards_x2):
card_id = _read_varint(data)
cards.append((card_id, 2))
num_cards_xn = _read_varint(data)
for i in range(num_cards_xn):
card_id = _read_varint(data)
count = _read_varint(data)
cards.append((card_id, count))
return cards, heroes, format
def write_deckstring(cards, heroes, format):
data = BytesIO()
data.write(b"\0")
_write_varint(data, DECKSTRING_VERSION)
_write_varint(data, int(format))
if len(heroes) != 1:
raise ValueError("Unsupported hero count %i" % (len(heroes)))
_write_varint(data, len(heroes))
for hero in heroes:
_write_varint(data, hero)
cards_x1, cards_x2, cards_xn = trisort_cards(cards)
for cardlist in cards_x1, cards_x2:
_write_varint(data, len(cardlist))
for cardid, _ in cardlist:
_write_varint(data, cardid)
_write_varint(data, len(cards_xn))
for cardid, count in cards_xn:
_write_varint(data, cardid)
_write_varint(data, count)
encoded = base64.b64encode(data.getvalue())
return encoded.decode("utf-8")
| [
"jerome@leclan.ch"
] | jerome@leclan.ch |
d9b2635bc34362ceaa4eafae793347d0f853fb78 | df4fa533c14ad84db4c69f3a029210874676c84a | /set4/print orime numbers in given range.py | 1b40b57dbae85559479b733287c4f2318c9081c6 | [] | no_license | JagadeeshMandala/python-programs | f9f5376092e2d1cf02e35a22fcedaab7fe842cdd | 07934980d3f971e390b1a0a641a002170a7ed0bd | refs/heads/master | 2023-08-28T21:04:29.446639 | 2021-11-03T05:52:53 | 2021-11-03T05:52:53 | 424,103,122 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 289 | py | lower=int(input("enter the lower range of number"))
higher=int(input("enter the higher range of number"))
for num in range(lower,higher+1):
if num>1:
for i in range(2,num):
if num%i==0:
break
else:
print(num,end=" ")
| [
"jagadeeshmandala888@gmail.com"
] | jagadeeshmandala888@gmail.com |
3ed6ce16285c35d94d8e6e78dde18c2cacac5da4 | 36746a067069f974056c562c0af559576c598497 | /scraper_karriera.py | 5ed8b15635859273e0f586401a387a88bb1e1a54 | [] | no_license | calogerobra/job_portal_scraper_medium_js | 042ac2867722e6cc2f36b104f40400693c7553e3 | 1ed3023bb18e626ddfcf53faf5dfd5e9bb2ecae6 | refs/heads/main | 2023-06-30T10:27:13.273603 | 2021-08-05T15:37:02 | 2021-08-05T15:37:02 | 393,088,796 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 15,473 | py | # Import general libraries
import datetime
import pandas as pd
from bs4 import BeautifulSoup as soup
import time
import csv
import requests
requests.packages.urllib3.disable_warnings()
import random
# Improt Selenium packages
from selenium import webdriver
from selenium.common.exceptions import NoSuchElementException as NoSuchElementException
from selenium.common.exceptions import WebDriverException as WebDriverException
from selenium.common.exceptions import ElementNotVisibleException as ElementNotVisibleException
from selenium.webdriver.chrome.options import Options
def request_page(url_string, verification, robust):
"""HTTP GET Request to URL.
Args:
url_string (str): The URL to request.
verification: Boolean certificate is to be verified
robust: If to be run in robust mode to recover blocking
Returns:
HTML code
"""
if robust:
loop = False
first = True
# Scrape contents in recovery mode
c = 0
while loop or first:
first = False
try:
uclient = requests.get(url_string, timeout = 60, verify = verification)
page_html = uclient.text
loop = False
return page_html
except requests.exceptions.ConnectionError:
c += 10
print("Request blocked, .. waiting and continuing...")
time.sleep(random.randint(10,60) + c)
loop = True
continue
except (requests.exceptions.ReadTimeout,requests.exceptions.ConnectTimeout):
print("Request timed out, .. waiting one minute and continuing...")
time.sleep(60)
loop = True
continue
else:
uclient = requests.get(url_string, timeout = 60, verify = verification)
page_html = uclient.text
loop = False
return page_html
def request_page_fromselenium(url_string, driver, robust):
""" Request HTML source code from Selenium web driver to circumvent mechanisms
active with HTTP requests
Args:
Selenium web driver
URL string
Returns:
HTML code
"""
if robust:
loop = False
first = True
# Scrape contents in recovery mode
c = 0
while loop or first:
first = False
try:
open_webpage(driver, url_string)
time.sleep(5)
page_html = driver.page_source
loop = False
return page_html
except WebDriverException:
c += 10
print("Web Driver problem, .. waiting and continuing...")
time.sleep(random.randint(10,60) + c)
loop = True
continue
else:
open_webpage(driver, url_string)
time.sleep(5)
page_html = driver.page_source
loop = False
return page_html
def set_driver(webdriverpath, headless):
"""Opens a webpage in Chrome.
Args:
url of webpage.
Returns:
open and maximized window of Chrome with webpage.
"""
options = Options()
if headless:
options.add_argument("--headless")
elif not headless:
options.add_argument("--none")
return webdriver.Chrome(webdriverpath, chrome_options = options)
def create_object_soup(object_link, verification, robust):
""" Create page soup out of an object link for a product
Args:
Object link
certificate verification parameter
robustness parameter
Returns:
tuple of beautiful soup object and object_link
"""
object_soup = soup(request_page(object_link, verification, robust), 'html.parser')
return (object_soup, object_link)
def make_soup(link, verification):
""" Create soup of listing-specific webpage
Args:
object_id
Returns:
soup element containing listings-specific information
"""
return soup(request_page(link, verification), 'html.parser')
def reveal_all_items(driver):
""" Reveal all items on the categroy web page of Albert Heijn by clicking "continue"
Args:
Selenium web driver
Returns:
Boolean if all items have been revealed
"""
hidden = True
while hidden:
try:
time.sleep(random.randint(5,7))
driver.find_element_by_css_selector('section#listing-home div.col-md-6.customlistinghome > a').click()
except (NoSuchElementException, ElementNotVisibleException):
hidden = False
return True
def open_webpage(driver, url):
"""Opens web page
Args:
web driver from previous fct and URL
Returns:
opened and maximized webpage
"""
driver.set_page_load_timeout(60)
driver.get(url)
driver.maximize_window()
def extract_listings_pages(first_page_html):
""" Extract pages using pagecount field on karriera page
Args:
URL
Robustness parameter
Certification verification parameter
Returns:
listings
"""
# Extract pages
pc_soup = soup(first_page_html, 'html.parser')
pc_list = pc_soup.findAll('div',{'class': 'pagination-nav'})[0].findAll('a', {'class': 'g-button no-text number'})
# Extract days online
return ['http://karriera.al/' + pc['href'] for pc in pc_list]
def make_jobs_list(base_url, robust, driver):
""" Extract item URL links + front information and return list of
all item links on web page
Args:
Base URL
Categroy tuples
Certificate verification parameter
Robustness parameter
Selenium web driver
Returns:
Dictionary with item URLs
"""
print("Start retrieving item links...")
on_repeat = False
first_run = True
front_contents = []
while on_repeat or first_run:
first_run = False
open_webpage(driver, base_url)
# Extract first page_html
first_page_html = driver.page_source
# Extract page count and loop over pages
pages = [driver.current_url]
pages = pages + extract_listings_pages(first_page_html)
# Loop over pages
for page in pages:
time.sleep(1)
# Within each page extract list of link, views, job city and days online
open_webpage(driver, page)
page_html = driver.page_source
page_soup = soup(page_html, 'html.parser')
front_content_container = page_soup.findAll('div', {'class': 'result-left col-sm-8 col-xs-12'})[0].table.tbody.findAll('tr')
for container in front_content_container:
container_content = container.findAll('td')
link = 'http://karriera.al' + container_content[0].a['href']
job_city = container_content[1].text
days_online = container_content[2].text
views = container_content[3].text
front_content = [link, job_city, days_online, views]
front_contents.append(front_content)
print('Retrieved', len(front_contents), 'item links!')
return front_contents
def create_elements(front_content_container, verification, robust):
"""Extracts the relevant information form the html container, i.e. object_id,
Args:
A container element + region, city, districts, url_string.
Returns:
A dictionary containing the information for one listing.
"""
object_soup = create_object_soup(front_content_container[0], verification, robust)[0]
object_link = front_content_container[0]
# Insert information from above
job_city = front_content_container[1]
days_online = front_content_container[2]
views = front_content_container[3]
# Parse contents
try:
content_container = object_soup.findAll('body', {'class': 'al'})[0].findAll('div', {'id': 'wrapper'})[0].findAll('div', {'class': 'post-job'})[0]
except:
content_container = []
try:
company_name = content_container.findAll('div', {'class': 'job-txt'})[0].h5.text
except:
company_name = ""
try:
contact_details_container = content_container.findAll('div', {'class': 'job-txt'})[0].ul.findAll('li')
contact_details = '|'.join([i.text for i in contact_details_container])
except:
contact_details = ''
try:
company_details_container = content_container.findAll('div', {'class':'row job-inside clear'})[0]
assert company_details_container.a.text == 'Rreth nesh'
company_details = company_details_container.p.text
except:
company_details = ""
try:
object_id_container = object_link.split('/')
object_id = object_id_container[5]
except:
object_id = ""
try:
job_category_container = content_container.findAll('div', {'class': 'col-sm-6 col-xs-12'})[0]
assert job_category_container.a.text == 'Kategoria'
job_category = job_category_container.span.text
except:
job_category = ""
try:
contract_type_container = content_container.findAll('div', {'class': 'col-sm-6 col-xs-12'})[1]
assert contract_type_container.a.text == 'Lloji i punës'
contract_type = contract_type_container.span.text
except:
contract_type = ""
# Flexibly extract job description
job_description = ""
for i in range(0,5):
try:
job_description_container = content_container.findAll('div', {'class': 'col-sm-12 col-xs-12'})[i]
assert job_description_container.a.text == 'Përshkrimi i Punës'
job_description = job_description_container.p.text
break
except AssertionError:
job_description = ""
# Flexibly extract job title
job_title = ""
for i in range(0,5):
try:
job_title_container = content_container.findAll('div', {'class': 'col-sm-12 col-xs-12'})[i]
assert job_title_container.a.text == 'Titulli i postimit *'
job_title = job_title_container.span.text
break
except AssertionError:
job_title = ""
# Flexibly extract requirements
requirements = ""
for i in range(0,5):
try:
requirements_container = content_container.findAll('div', {'class': 'col-sm-12 col-xs-12'})[i]
assert requirements_container.a.text == 'Kërkesat e profilit'
requirements = requirements_container.p.text
break
except:
requirements = ""
# Flexibly extract salary
salary = ""
for i in range(0,5):
try:
salary_container = content_container.findAll('div', {'class': 'col-sm-12 col-xs-12'})[i]
assert salary_container.a.text == 'Paga'
salary = salary_container.span.text
break
except:
salary = ""
# Flexibly extract additional information
add_information = ""
for i in range(0,5):
try:
add_information_container = content_container.findAll('div', {'class': 'col-sm-12 col-xs-12'})[i]
assert add_information_container.a.text == 'Tjetër (Opsionale)'
add_information = add_information_container.p.text
break
except:
add_information = ""
page_html = object_soup.prettify()
# Create a dictionary as output
return dict([("object_link", object_link),
("job_city", job_city),
("days_online", days_online),
("views", views),
("company_name", company_name),
("company_details", company_details),
("contact_details", contact_details),
("object_id", object_id),
("job_title", job_title),
("job_category", job_category),
("contract_type", contract_type),
("job_description", job_description),
("requirements", requirements),
("salary", salary),
("page_html", page_html),
("add_information", add_information)])
def scrape_karriera(verification, robust, front_contents):
"""Scraper for karriera job portal based on specified parameters.
In the following we would like to extract all the containers containing
the information on one listing. For this purpose we try to parse through
the html text and search for all elements of interest.
Args:
verification
robust
item_links
Returns:
Appended pandas dataframe with crawled content.
"""
# Define dictionary for output
input_dict = {}
frames = []
counter = 0
#skipper = 0
# Loop links
for front_content in front_contents:
time.sleep(random.randint(1,2))
print('Parsing URL', front_content[0])
# Set scraping time
now = datetime.datetime.now()
try:
input_dict.update(create_elements(front_content, verification, robust))
time.sleep(0.5)
# Create a dataframe
df = pd.DataFrame(data = input_dict, index =[now])
df.index.names = ['scraping_time']
frames.append(df)
except requests.exceptions.ConnectionError:
error_message = "Connection was interrupted, waiting a few moments before continuing..."
print(error_message)
time.sleep(random.randint(2,5) + counter)
continue
return pd.concat(frames).drop_duplicates(subset = 'object_link')
def main():
""" Note: Set parameters in this function
"""
# Set time stamp
now_str = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
# Set scraping parameters
base_url = 'http://karriera.al/al/result'
robust = True
webdriverpath = r"C:\Users\\Calogero\Documents\GitHub\job_portal_scraper_medium_js\chromedriver.exe"
# Set up a web driver
driver = set_driver(webdriverpath, False)
# Start timer
start_time = time.time() # Capture start and end time for performance
# Set verification setting for certifiates of webpage. Check later also certification
verification = True
# Execute functions for scraping
start_time = time.time() # Capture start and end time for performance
item_links = make_jobs_list(base_url, robust, driver)
driver.close()
appended_data = scrape_karriera(verification, robust, item_links)
# Split off HTML code for Giannis and team
appended_data = appended_data.drop("page_html",1)
# Write output to Excel
print("Writing to Excel file...")
time.sleep(1)
file_name = '_'.join(['C:\\Users\\Calogero\\Documents\\GitHub\\job_portal_scraper_medium_js\\data\\daily_scraping\\' +
str(now_str), 'karriera.xlsx'])
writer = pd.ExcelWriter(file_name, engine='xlsxwriter')
appended_data.to_excel(writer, sheet_name = 'jobs')
writer.save()
# Write to CSV
print("Writing to CSV file...")
appended_data.to_csv(file_name.replace('.xlsx', '.csv'), sep =";",quoting=csv.QUOTE_ALL)
end_time = time.time()
duration = time.strftime("%H:%M:%S", time.gmtime(end_time - start_time))
# For interaction and error handling
final_text = "Your query was successful! Time elapsed:" + str(duration)
print(final_text)
time.sleep(0.5)
# Execute scraping
if __name__ == "__main__":
main() | [
"70377216+calogerobra@users.noreply.github.com"
] | 70377216+calogerobra@users.noreply.github.com |
0599ad0639d06d818def4fa99b5cb87567b0b85f | 5ad255257f58705b8ce28121c0cc0d1000af1077 | /CI/1.Epopcon/intern/CI_company_category_dashboard/src/CI_company_category_dashboard.py | ed400d654387018b8ccfbe84c71ea5740685144d | [] | no_license | benepopds/epop_poi | 92e4301dbfbecf676f5b154d7b43108dff9ab82f | 153e5ef423e6a76f01037fe06ce354a6dc2268a7 | refs/heads/master | 2020-03-22T23:45:30.533090 | 2018-10-31T07:30:24 | 2018-10-31T07:30:24 | 140,827,236 | 1 | 4 | null | 2018-08-17T07:27:52 | 2018-07-13T09:31:18 | Python | UTF-8 | Python | false | false | 17,907 | py | import dash
from dash.dependencies import Input, Output, State
import dash_core_components as dcc
import dash_html_components as html
import dash_table_experiments as dt
import plotly.graph_objs as go
import plotly.plotly as py
import squarify
import json
import pandas as pd
import numpy as np
import plotly
import pickle
import datetime
#import dash_auth
import dash_auth
from sqlalchemy import create_engine
import pymysql, pandas as pd
pymysql.install_as_MySQLdb()
import MySQLdb
df = pd.read_parquet('TEMP_COMPANY_REFINE.PQ')
modify_dict = {}
VALID_USERNAME_PASSWORD_PAIRS = [
['admin1', 'epop0313'],
['admin2', 'epop0313'],
['admin3', 'epop0313'],
]
app = dash.Dash('auth')
auth = dash_auth.BasicAuth(
app,
VALID_USERNAME_PASSWORD_PAIRS
)
user_name = auth._username
print(type(auth))
print(auth._username)
print(type(auth._username))
## PQ 파일 sync 맞추는 작업은 나중에 서버 올라가고 나서 코어 여러개 쓰는 방안 고민해보기 (패럴)
#app = dash.Dash('auth')
app.layout = html.Div([
html.Div([dt.DataTable(rows=[{}], id='dt_words_pair')], id='div_words_pair', className="container", style={'width':'40%', 'height':'100%','display':'inline-block'}),
html.Div([html.Button(id='bt1', n_clicks=0, children="X" ) ], style={'text-align':'left', 'width':'10%', 'height':'100%', 'display': 'inline-block'}),
html.Div([dt.DataTable(rows=[{}], id='dt_cate_pair'),], id='div_cate_pair', className="container", style={'width':'40%', 'height':'100%','display':'inline-block'}),
html.Div([html.Div(id='my-div'),dcc.Input(id='cate', value='modify_cate', type='text'),dcc.Input(id='cate1', value='modify_cate1', type='text'),
html.Button(id='bt2', n_clicks=0, children="modify" )],),
html.Button(id='bt3', n_clicks=0, children = '상점찾기제외'),
html.Button(id='bt4', n_clicks=0, children = 'Sync DB - PQ'),
html.Div([dt.DataTable(rows=[{}], id='dt_pair_samples')], id='div_pair_samples', className="container", style={'width':'100%', 'height':'100%','display':'inline-block'}),
html.Div(id='result_div'),
html.Div(id='result_div2'),
html.Div(id='result_div3'),
html.Div(id='result_div4'),
], id='page', className="container", style={'text-align':'left', 'width':'100%', 'height':'100%','display':'inline-block'})
@app.callback(
Output('result_div4', component_property='children'),
[ Input('bt4', 'n_clicks')],
)
def click_save_button(n_clicks):
if n_clicks==0:
return None
engine = create_engine("mysql://eums:eums00!q@133.186.146.142:3306/eums-poi?charset=utf8mb4", encoding = 'utf8' , pool_size=50,pool_recycle=3600,connect_args={'connect_timeout':1000000} )
query = """select ID, CO_NAME, CO_NAME_R, REP_PHONE_NUM, ADDR, ROAD_ADDR, CATE_CODE, CATE, CATE1_CODE, CATE1, TAG, STATUS, MODIFIER, UPT_DT from TEMP_COMPANY """
df = pd.read_sql_query(query, engine)
df.to_parquet('TEMP_COMPANY_REFINE.PQ')
return 'PARQUET UPDATE SUCCESS'
## modify를 각 카테고리에서 가장 많은 count 로 업데이트
@app.callback(
Output('cate', 'value'),
[ Input('dt_words_pair', 'selected_row_indices') ],
[ State('dt_words_pair', 'rows') ]
)
## modify를 각 카테고리에서 가장 많은 count 로 업데이트
def update_modify_cate(selected_row_indices, rows):
if selected_row_indices == None or len(selected_row_indices) == 0:
return 'modify_cate'
result=""
selected_rows = [rows[index] for index in selected_row_indices]
w0, w1 = selected_rows[0]['pair'][0], selected_rows[0]['pair'][1]
df2 = df[(df['CO_NAME_R'].str.contains('{}.*{}'.format(w0, w1) , regex = True, na = False )) & ((df['STATUS'] == '0' ) | (df['STATUS'] == '1'))]
freq_cate = pd.DataFrame(df2.groupby(['CATE', 'CATE1']).CO_NAME.count()).reset_index().sort_values(by='CO_NAME', ascending=False)
result = freq_cate['CATE'].values[0]
return result
## modify1를 각 카테고리에서 가장 많은 count 로 업데이트
@app.callback(
Output('cate1', 'value'),
[ Input('dt_words_pair', 'selected_row_indices') ],
[ State('dt_words_pair', 'rows') ]
)
## modify1를 각 카테고리에서 가장 많은 count 로 업데이트
def update_modify_cate1(selected_row_indices, rows):
if selected_row_indices == None or len(selected_row_indices) == 0:
return 'modify_cate1'
result=""
selected_rows = [rows[index] for index in selected_row_indices]
w0, w1 = selected_rows[0]['pair'][0], selected_rows[0]['pair'][1]
df2 = df[(df['CO_NAME_R'].str.contains('{}.*{}'.format(w0, w1) , regex = True, na = False )) & ((df['STATUS'] == '0' ) | (df['STATUS'] == '1'))]
freq_cate = pd.DataFrame(df2.groupby(['CATE', 'CATE1']).CO_NAME.count()).reset_index().sort_values(by='CO_NAME', ascending=False)
result = freq_cate['CATE1'].values[0]
return result
@app.callback(
Output('result_div',component_property='children'),
[Input('bt3', 'n_clicks'),
Input('dt_pair_samples', 'selected_row_indices'),
Input('dt_pair_samples', 'rows'),],
[State('dt_cate_pair', 'selected_row_indices'),
State('dt_cate_pair', 'rows'),
State('dt_words_pair', 'selected_row_indices'),
State('dt_words_pair', 'rows'),
State('cate', 'value'),
State('cate1','value')]
)
def exclude_store(n_clicks, sample_indeces, sample_rows, cate_indeces, cate_rows, word_indeces, word_rows, modify_cate, modify_cate1):
if cate_indeces == None or len(cate_indeces) == 0:
return ""
if word_indeces == None or len(word_indeces) == 0:
return ""
if modify_cate == None or modify_cate1 == None or n_clicks == 0:
return ""
sel_word = [word_rows[i] for i in word_indeces][0]
sel_cate = [cate_rows[i] for i in cate_indeces][0]
w0 = sel_word['pair'][0] #내가찍은 pair 1
w1 = sel_word['pair'][1] #내가찍은 pair 2
cate_select = sel_cate['CATE'] #내가찍은 cate
cate1_select = sel_cate['CATE1'] #내가찍은 cate1
print(w0, w1, cate_select, cate1_select)
print('## test!!! ')
print(sample_indeces)
print(type(sample_indeces))
engine = create_engine("mysql://eums:eums00!q@133.186.146.142:3306/eums-poi?charset=utf8mb4", encoding = 'utf8' , pool_size=50,pool_recycle=3600,connect_args={'connect_timeout':1000000} )
#기존 CATE_CODE 가져옴
code_query = """select CODE from MEUMS_CODE where CODE_NAME = '{}' and GROUP_CODE = 'COMPCATE' and UPPER_CODE = '' """.format(cate_select)#, modify_cate1)
select_cate_code = pd.read_sql_query(code_query, engine)
before_cate_code = select_cate_code['CODE'][0]
#기존 CATE_CODE1 가져옴
code_query = """select CODE from MEUMS_CODE where CODE_NAME = '{}' and GROUP_CODE = 'COMPCATE' and UPPER_CODE = '{}' """.format(cate1_select, before_cate_code)
if cate1_select == "":
before_cate1_code = ""
else:
select_cate1_code = pd.read_sql_query(code_query, engine)
before_cate1_code = select_cate1_code['CODE'][0]
for i in range(0, len(sample_indeces)):
c = df[(df['CO_NAME'] == sample_rows[i]['CO_NAME']) & (df['REP_PHONE_NUM'] == sample_rows[i]['REP_PHONE_NUM']) & (df['CATE'] == cate_select) & (df['CATE1'] == cate1_select) & ( (df['STATUS'] == '0') | (df['STATUS'] == '1' ) ) ]
company_id = c['ID'].values[0]
origin_status = c['STATUS'].values[0]
query = """
UPDATE TEMP_COMPANY
SET STATUS = "{}", UPT_DT = "{}", MODIFIER = "{}"
where (STATUS=1 or STATUS=0) and CO_NAME = "{}" and REP_PHONE_NUM = "{}" and CATE="{}" and CATE1="{}"
""".format(-9, datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),auth._username, sample_rows[i]['CO_NAME'], sample_rows[i]['REP_PHONE_NUM'],cate_select, cate1_select)
print(query)
with engine.connect() as con:
con.execute(query)
query2 = """
INSERT INTO TEMP_COMPANY_EXCLUDE_HISTORY
SET COMPANY_ID = '{}', CO_NAME = '{}', CATE_CODE = '{}',CATE1_CODE = '{}', CATE = '{}', CATE1 = '{}', STATUS = '{}', MODIFIER = '{}', UPT_DT = '{}'
""".format(company_id, sample_rows[i]['CO_NAME'], before_cate_code, before_cate1_code, cate_select,cate1_select,origin_status ,auth._username ,datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
print(query2)
with engine.connect() as con:
con.execute(query2)
return '선택하신 정보의 STATUS 를 -9로 변경하였습니다.'
## DB값을 실제로 업데이트
@app.callback(
Output('result_div2', component_property='children'),
[Input('bt2', 'n_clicks'),],
[State('dt_cate_pair', 'selected_row_indices'),
State('dt_cate_pair', 'rows'),
State('dt_words_pair', 'selected_row_indices'),
State('dt_words_pair', 'rows'),
State('dt_pair_samples', 'selected_row_indices'),
State('dt_pair_samples', 'rows'),
State('cate', 'value'),
State('cate1','value')]
)
## DB값을 실제로 업데이트
def modify_print(n_clicks, cate_indeces, cate_rows, word_indeces, word_rows, sample_indeces, sample_rows, modify_cate, modify_cate1):
if cate_indeces == None or len(cate_indeces) == 0:
return None
if word_indeces == None or len(word_indeces) == 0:
return None
if modify_cate == None or modify_cate1 == None or n_clicks == 0:
return None
print(cate_indeces, len(cate_rows), word_indeces, len(word_rows))
sel_word = [word_rows[i] for i in word_indeces][0]
sel_cate = [cate_rows[i] for i in cate_indeces][0]
w0 = sel_word['pair'][0] #내가찍은 pair 1
w1 = sel_word['pair'][1] #내가찍은 pair 2
cate_select = sel_cate['CATE'] #내가찍은 cate
cate1_select = sel_cate['CATE1'] #내가찍은 cate1
print(w0, w1, cate_select, cate1_select)
print('## test!!! ')
print(sample_indeces)
print(type(sample_indeces))
engine = create_engine("mysql://eums:eums00!q@133.186.146.142:3306/eums-poi?charset=utf8mb4", encoding = 'utf8' , pool_size=50,pool_recycle=3600,connect_args={'connect_timeout':1000000} )
#UPDATE 할 CATE_CODE 가져옴 #cate_code = 바꿀 카테의 코드
code_query = """select CODE from MEUMS_CODE where CODE_NAME = '{}' and GROUP_CODE = 'COMPCATE' and UPPER_CODE = '' """.format(modify_cate)#, modify_cate1)
modi_cate_code = pd.read_sql_query(code_query, engine)
after_cate_code = modi_cate_code['CODE'][0]
#UPDATE 할 CATE_CODE1 가져옴 #cate1_code = 바꿀 카테1의 코드
code_query = """select CODE from MEUMS_CODE where CODE_NAME = '{}' and GROUP_CODE = 'COMPCATE' and UPPER_CODE = '{}' """.format(modify_cate1, after_cate_code)
if modify_cate1 =="":
after_cate1_code = ""
else:
modi_cate1_code = pd.read_sql_query(code_query, engine)
after_cate1_code = modi_cate1_code['CODE'][0]
#UPDATE 전 CATE_CODE 가져옴
code_query = """select CODE from MEUMS_CODE where CODE_NAME = '{}' and GROUP_CODE = 'COMPCATE' and UPPER_CODE = '' """.format(cate_select)#, modify_cate1)
select_cate_code = pd.read_sql_query(code_query, engine)
before_cate_code = select_cate_code['CODE'][0]
#UPDATE 전 CATE_CODE1 가져옴 #cate1_code = 바꿀 카테1의 코드
code_query = """select CODE from MEUMS_CODE where CODE_NAME = '{}' and GROUP_CODE = 'COMPCATE' and UPPER_CODE = '{}' """.format(cate1_select, before_cate_code)
if cate1_select == "":
before_cate1_code = ""
else:
select_cate1_code = pd.read_sql_query(code_query, engine)
before_cate1_code = select_cate1_code['CODE'][0]
for i in range(0, len(sample_indeces)):
c = df[(df['CO_NAME'] == sample_rows[i]['CO_NAME']) & (df['REP_PHONE_NUM'] == sample_rows[i]['REP_PHONE_NUM']) & (df['CATE'] == cate_select) & (df['CATE1'] == cate1_select) & ( (df['STATUS']=='0') | (df['STATUS'] == '1') ) ]
print('###')
print(c)
company_id = c['ID'].values[0]
query = """
UPDATE TEMP_COMPANY
SET CATE_CODE = "{}", CATE = "{}" , CATE1_CODE = "{}", CATE1 ="{}", UPT_DT = "{}", MODIFIER = "{}"
where (STATUS=1 or STATUS=0) and CO_NAME = "{}" and REP_PHONE_NUM = "{}" and CATE="{}" and CATE1="{}"
""".format(after_cate_code, modify_cate, after_cate1_code, modify_cate1, datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),auth._username, sample_rows[i]['CO_NAME'], sample_rows[i]['REP_PHONE_NUM'],cate_select, cate1_select)
print(query)
with engine.connect() as con:
con.execute(query)
query2 = """
INSERT INTO TEMP_COMPANY_UPDATE_HISTORY
SET COMPANY_ID = '{}', CO_NAME = '{}', PAIR1 = '{}', PAIR2 = '{}', ORG_CATE_CODE = '{}',ORG_CATE1_CODE = '{}', ORG_CATE = '{}', ORG_CATE1 = '{}', CATE_CODE = '{}', CATE1_CODE = '{}', CATE = '{}', CATE1 = '{}', MODIFIER = '{}', UPT_DT = '{}'
""".format(company_id, sample_rows[i]['CO_NAME'], w0,w1,before_cate_code, before_cate1_code, cate_select,cate1_select,after_cate_code, after_cate1_code,modify_cate, modify_cate1,auth._username ,datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
print(query2)
with engine.connect() as con:
con.execute(query2)
return 'DB 수정 완료'
#print div_cate_pair
@app.callback(
Output('div_cate_pair', 'children'),
[ Input('dt_words_pair', 'selected_row_indices') ],
[ State('dt_words_pair', 'rows') ]
)
def cate_pairs(selected_row_indices, rows):
if selected_row_indices == None or len(selected_row_indices) == 0:
return None
selected_rows = [rows[index] for index in selected_row_indices]
w0, w1 = selected_rows[0]['pair'][0], selected_rows[0]['pair'][1]
df2 = df[(df['CO_NAME_R'].str.contains('{}.*{}'.format(w0, w1) , regex = True, na = False )) & ((df['STATUS'] == '0' ) | (df['STATUS'] == '1'))]
print(df2)
freq_cate = pd.DataFrame(df2.groupby(['CATE', 'CATE1']).CO_NAME.count()).reset_index().sort_values(by='CO_NAME', ascending=False)
freq_cate.columns = ['CATE', 'CATE1', 'COUNT']
return dt.DataTable(
rows = freq_cate.to_dict('records'),
#columns = ['pair', 'pair_str', 'cnt'],
row_selectable=True,
filterable=True,
sortable=True,
selected_row_indices=[],
resizable=True,
max_rows_in_viewport=5,
editable=False,
column_widths=[100,100,300],
min_width=500,
id='dt_cate_pair'
)
#read pkl & show pair
@app.callback(
Output('div_words_pair', 'children'),
[ Input('bt1', 'n_clicks') ],
[ State('dt_words_pair', 'rows'), State('dt_words_pair', 'selected_row_indices') ]
)
def loading_pairs(n_clicks, rows, selected_row_indices):
if n_clicks == 0:
print('n_clicks == 0')
return dt.DataTable(
rows = pc.to_dict('records'),
columns = ['pair_str', 'cnt'],
row_selectable=True,
filterable=True,
sortable=True,
selected_row_indices=[],
resizable=True,
max_rows_in_viewport=5,
#min_width=400,
id='dt_words_pair'
)
else:
return None
#select pair print
@app.callback(
Output('my-div',component_property='children'),
[ Input('dt_words_pair', 'selected_row_indices') ],
[ State('dt_words_pair', 'rows') ]
)
def print_div(selected_row_indices, rows):
if selected_row_indices == None or len(selected_row_indices) == 0:
return None
selected_rows = [rows[index] for index in selected_row_indices]
w0, w1 = selected_rows[0]['pair'][0], selected_rows[0]['pair'][1]
print (w0, w1)
return w0, w1
#print select table
@app.callback(
Output('div_pair_samples', 'children'),
[ Input('dt_cate_pair', 'selected_row_indices') ],
[ State('dt_cate_pair', 'rows'), State('dt_words_pair', 'selected_row_indices'), State('dt_words_pair', 'rows') ]
)
def querying_pairs(cate_indeces, cate_rows, word_indeces, word_rows):
if cate_indeces == None or len(cate_indeces) == 0:
return None
if word_indeces == None or len(word_indeces) == 0:
return None
print(cate_indeces, len(cate_rows), word_indeces, len(word_rows))
sel_word = [word_rows[i] for i in word_indeces][0]
sel_cate = [cate_rows[i] for i in cate_indeces][0]
w0= sel_word['pair'][0]
w1= sel_word['pair'][1]
cate=sel_cate['CATE']
cate1=sel_cate['CATE1']
print(w0, w1, cate, cate1)
df2 = df[(df['CO_NAME_R'].str.contains('{}.*{}'.format(w0, w1) , regex = True, na = False )) & ((df['STATUS'] == '0' ) | (df['STATUS'] == '1')) & (df['CATE'] == cate) & (df['CATE1'] == cate1)]
df2 = df2[['CO_NAME', 'REP_PHONE_NUM', 'CATE', 'CATE1', 'TAG', 'ADDR', 'ROAD_ADDR']]
return dt.DataTable(
rows = df2.to_dict('records'),
#columns = ['pair', 'pair_str', 'cnt'],
row_selectable=True,
filterable=True,
sortable=True,
selected_row_indices=[],
resizable=True,
max_rows_in_viewport=20,
editable=False,
column_widths=[300,100,80,100,400,350,350],
min_width=1800,
id='dt_pair_samples'
)
app.css.append_css({
'external_url': 'https://codepen.io/chriddyp/pen/bWLwgP.css'
})
if __name__ == '__main__':
try:
words_pair_count_dontcare = pickle.load(open('words_pair_count_dontcare.list.pkl', 'rb'))
print('loading dontcare list')
except:
words_pair_count_dontcare = []
pc_list = pickle.load(open('words_pair_count_sorted.list.pkl', 'rb'))
pc_list = pc_list[:2000]
pc_list = [pce for pce in pc_list if pce not in words_pair_count_dontcare]
pc = pd.DataFrame(pc_list, columns=['pair','cnt'])
pc['pair_str'] = pc.pair.astype('str')
print('## user name ##')
print(user_name)
app.run_server(debug=False, host='0.0.0.0', port=8050)
| [
"rmsxor94@naver.com"
] | rmsxor94@naver.com |
deba1e3f47315ccc1ff205db11a6c8001b565e86 | 0ad589622461664e446e0f3b0063d6a8ad988838 | /thread.py | 10a35e2e00e0e271a3f8d7cebfd3d6b614cfc29d | [] | no_license | mrlam99n01/vim_file | d166ca0bd663839780f8cec553a9952c73137615 | 37dca98fc4c4a747545c82e8dbe0a3d5ade55c46 | refs/heads/master | 2023-02-08T08:33:17.441322 | 2021-01-02T13:05:23 | 2021-01-02T13:05:23 | 326,182,576 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 659 | py | import time
import concurrent.futures
start = time.perf_counter()
def do_something(seconds):
print('Sleeping 1 second...')
time.sleep(seconds)
return 'Done something ... '
with concurrent.futures.ThreadPoolExecutor() as executor:
results = [executor.submit(do_something,1) for _ in range(10)]
for f in concurrent.futures.as_completed(results):
print(f.result())
threads = []
# for _ in range(10):
# t = threading.Thread(target=do_something,args=[1.5])
# t.start()
# threads.append(t)
# for thread in threads:
# thread.join()
finish = time.perf_counter()
print(f'Finish in {round(finish-start,2)} second(s)')
| [
"mrlam99n01@gmail.com"
] | mrlam99n01@gmail.com |
ce1a0986a077a61178984b37c1a0e8b95eaab459 | a6e4672c5924732f9c4d509540f577a2d2115454 | /new_dawn_server/management/commands/create_super_user.py | 0fc41b80819dc830d42e81b2d48fa23d63f9955c | [] | no_license | new-dawn/new_dawn_server | 78f9e9e4815c589414e02ebadd7d9b41b059c6d4 | 31c39553cd919b8f8d2e24329822f383e7203ce2 | refs/heads/master | 2022-12-18T19:29:56.407943 | 2019-08-07T03:05:40 | 2019-08-07T03:05:40 | 156,310,163 | 0 | 0 | null | 2022-12-08T01:28:21 | 2018-11-06T01:51:43 | Python | UTF-8 | Python | false | false | 662 | py | import os
from django.contrib.auth.models import User
from django.core.management.base import BaseCommand
class Command(BaseCommand):
def handle(self, *args, **options):
if 'SUPER_USER_NAME' in os.environ and 'SUPER_USER_EMAIL' in os.environ and 'SUPER_USER_PASSWORD' in os.environ:
username = os.environ['SUPER_USER_NAME']
if not User.objects.filter(username=username).exists():
User.objects.create_superuser(
username, os.environ['SUPER_USER_EMAIL'], os.environ['SUPER_USER_PASSWORD'])
admin_user = User.objects.get(username=username)
print("Super User Created: " + admin_user.username)
print("Api-Key: " + admin_user.api_key.key) | [
"noreply@github.com"
] | new-dawn.noreply@github.com |
2dc34c03a5e5fc786e8c488d98eae17ebcdbda9c | 066a5d8c5f11dcd9183eebe8f808859a931d17fb | /polls/migrations/0001_initial.py | df878c22ab6c45fa24c43c4b1b7849b467d76d72 | [] | no_license | huangxinkid/mysite | 215b4ea787a7d683db3c5a4a869d83083b85eb92 | be774fad11b5f5406b65673a17c9e2db2599e550 | refs/heads/master | 2022-08-31T13:16:19.164454 | 2021-02-21T14:25:10 | 2021-02-21T14:25:10 | 204,312,992 | 1 | 0 | null | 2022-08-23T18:24:27 | 2019-08-25T15:25:56 | JavaScript | UTF-8 | Python | false | false | 1,165 | py | # Generated by Django 2.0.1 on 2019-08-25 13:30
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Choice',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('choice_text', models.CharField(max_length=200)),
('votes', models.IntegerField(default=0)),
],
),
migrations.CreateModel(
name='Question',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('question_text', models.CharField(max_length=200)),
('pub_date', models.DateTimeField(verbose_name='date published')),
],
),
migrations.AddField(
model_name='choice',
name='question',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='polls.Question'),
),
]
| [
"364296999@qq.com"
] | 364296999@qq.com |
dcdb1097b0de04146d7c8ec4355dd753d1332ac7 | d1f38423b37020f64a32eda523fb77e0cde23a05 | /Course_on_stepik/Python_on_stepik/python_bases_and_practice/part_1/week_2_practice_buffer.py | ae9208c801d32f0df059d2968ee980363d729f81 | [] | no_license | zarkaltair/Data-Scientist | 9f2c1234a4f1f014165d3389be9ab77c787c0226 | ca318046caff51977efff0762fa8f4704f77433a | refs/heads/master | 2021-06-12T08:08:40.787110 | 2021-04-19T17:55:10 | 2021-04-19T17:55:10 | 171,741,930 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 3,155 | py | '''
Вам дается последовательность целых чисел и вам нужно ее обработать и вывести на экран сумму первой пятерки чисел из этой последовательности, затем сумму второй пятерки, и т. д.
Но последовательность не дается вам сразу целиком. С течением времени к вам поступают её последовательные части. Например, сначала первые три элемента, потом следующие шесть, потом следующие два и т. д.
Реализуйте класс Buffer, который будет накапливать в себе элементы последовательности и выводить сумму пятерок последовательных элементов по мере их накопления.
Одним из требований к классу является то, что он не должен хранить в себе больше элементов, чем ему действительно необходимо, т. е. он не должен хранить элементы, которые уже вошли в пятерку, для которой была выведена сумма.
Класс должен иметь следующий вид
class Buffer:
def __init__(self):
# конструктор без аргументов
def add(self, *a):
# добавить следующую часть последовательности
def get_current_part(self):
# вернуть сохраненные в текущий момент элементы последовательности в порядке, в котором они были
# добавлены
'''
class Buffer:
def __init__(self):
# конструктор без аргументов
self.arr = []
def add(self, *a):
# добавить следующую часть последовательности
self.arr += a
while len(self.arr) >= 5:
s = sum(self.arr[:5])
print(s)
self.arr = self.arr[5:]
def get_current_part(self):
# вернуть сохраненные в текущий момент элементы последовательности в порядке, в котором они были добавлены
return self.arr
buf = Buffer()
buf.add(1, 2, 3)
buf.get_current_part() # вернуть [1, 2, 3]
buf.add(4, 5, 6) # print(15) – вывод суммы первой пятерки элементов
buf.get_current_part() # вернуть [6]
buf.add(7, 8, 9, 10) # print(40) – вывод суммы второй пятерки элементов
buf.get_current_part() # вернуть []
buf.add(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) # print(5), print(5) – вывод сумм третьей и четвертой пятерки
buf.get_current_part() # вернуть [1] | [
"zarkaltair@gmail.com"
] | zarkaltair@gmail.com |
0302cfab8147b8ca85bfdca9e6fde5623b1387b2 | b7c2de28db8bcfec43fcd537ce35e60f6fbc62fd | /portfolio/bin/python-config | 11be30d2806749a68c0b5c1a7ef6ca564f10490b | [] | no_license | Kzone-m/MyPortfolio | b128f1b27f7d410488f6d5aa6af40206e58251c6 | 3ff0ceb37b6ef82180bc2bd2d0cc6e0fb72d0954 | refs/heads/master | 2021-06-20T12:20:27.523689 | 2017-05-22T07:57:04 | 2017-05-22T07:57:04 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,357 | #!/Users/Kazune/PycharmProjects/portfolio/bin/python
import sys
import getopt
import sysconfig
valid_opts = ['prefix', 'exec-prefix', 'includes', 'libs', 'cflags',
'ldflags', 'help']
if sys.version_info >= (3, 2):
valid_opts.insert(-1, 'extension-suffix')
valid_opts.append('abiflags')
if sys.version_info >= (3, 3):
valid_opts.append('configdir')
def exit_with_usage(code=1):
sys.stderr.write("Usage: {0} [{1}]\n".format(
sys.argv[0], '|'.join('--'+opt for opt in valid_opts)))
sys.exit(code)
try:
opts, args = getopt.getopt(sys.argv[1:], '', valid_opts)
except getopt.error:
exit_with_usage()
if not opts:
exit_with_usage()
pyver = sysconfig.get_config_var('VERSION')
getvar = sysconfig.get_config_var
opt_flags = [flag for (flag, val) in opts]
if '--help' in opt_flags:
exit_with_usage(code=0)
for opt in opt_flags:
if opt == '--prefix':
print(sysconfig.get_config_var('prefix'))
elif opt == '--exec-prefix':
print(sysconfig.get_config_var('exec_prefix'))
elif opt in ('--includes', '--cflags'):
flags = ['-I' + sysconfig.get_path('include'),
'-I' + sysconfig.get_path('platinclude')]
if opt == '--cflags':
flags.extend(getvar('CFLAGS').split())
print(' '.join(flags))
elif opt in ('--libs', '--ldflags'):
abiflags = getattr(sys, 'abiflags', '')
libs = ['-lpython' + pyver + abiflags]
libs += getvar('LIBS').split()
libs += getvar('SYSLIBS').split()
# add the prefix/lib/pythonX.Y/config dir, but only if there is no
# shared library in prefix/lib/.
if opt == '--ldflags':
if not getvar('Py_ENABLE_SHARED'):
libs.insert(0, '-L' + getvar('LIBPL'))
if not getvar('PYTHONFRAMEWORK'):
libs.extend(getvar('LINKFORSHARED').split())
print(' '.join(libs))
elif opt == '--extension-suffix':
ext_suffix = sysconfig.get_config_var('EXT_SUFFIX')
if ext_suffix is None:
ext_suffix = sysconfig.get_config_var('SO')
print(ext_suffix)
elif opt == '--abiflags':
if not getattr(sys, 'abiflags', None):
exit_with_usage()
print(sys.abiflags)
elif opt == '--configdir':
print(sysconfig.get_config_var('LIBPL'))
| [
"kazune.miyagi92@gmail.com"
] | kazune.miyagi92@gmail.com | |
4f6a0062ff2121f83fa9c6e0e97d63db101af486 | 3b4a5d2c62fe2c6f4222be7c117b1a5d423f81a8 | /SYSTEM-B/main.py | ce3326a19454661ad9ff2fb5e97459eb4ef0489c | [] | no_license | PaulSiddharth/Statisctics | 56f5d391d7a1507b4fb57389ea5fcc5d7ca29945 | 23404cbfe528b7b4054b0034d73ef73b9dc62f8d | refs/heads/master | 2023-01-31T15:49:13.361493 | 2019-07-08T19:50:14 | 2019-07-08T19:50:14 | 195,870,792 | 0 | 0 | null | 2023-01-04T03:58:35 | 2019-07-08T19:03:41 | Vue | UTF-8 | Python | false | false | 1,166 | py | from flask import Flask
from flask import request
app = Flask(__name__)
@app.route("/")
def root():
"""
Root router
"""
return 'Welcome to BH Reco!'
@app.route("/generatenumber", methods=['GET'])
def generatenumber():
"""
Generate Random Number
"""
import random
import json
arr=[]
# Genterating 6 random numbers
for x in range(2):
arr.append(random.randrange(2,11,2))
arr.append(random.randrange(1,11,2))
arr.append(random.randrange(2,11,2))
arr.append(random.randrange(2,11,2))
return json.dumps(arr)
@app.route("/stats", methods=['GET'])
def stats():
"""
Generate Random Number
"""
import statistics
import json
arr=json.loads(request.args.get('entry'))
# # x is odd count
# # y is even count
result = {
"mean": statistics.mean(arr),
"median": statistics.median(arr),
"mode": statistics.variance(arr),
"deviation": statistics.stdev(arr)
}
return json.dumps(result)
if __name__ == "__main__":
app.run() | [
"siddhartha.paul@sap.com"
] | siddhartha.paul@sap.com |
cd69465ea34835feab0709e1ecd39a8742b02b67 | c28198fbc8ee472586eaef7ce1356fea52e822dc | /confirmation_mail/mail_confirm/mail_confirm/settings.py | 96694bf681bbec8c1a5e5dd84886ca6b7831494e | [] | no_license | CODEr-SaNjU/Confirm_mail | 2ec7de76d21631e9d75118521af997b6409c674c | d405d5b88c6af7ecbc9cbded3ab2ee75e2e48732 | refs/heads/master | 2023-05-05T08:54:23.950937 | 2022-05-18T14:14:40 | 2022-05-18T14:14:40 | 234,261,880 | 0 | 0 | null | 2023-04-21T22:10:48 | 2020-01-16T07:34:41 | Python | UTF-8 | Python | false | false | 3,378 | py | """
Django settings for mail_confirm project.
Generated by 'django-admin startproject' using Django 2.2.
For more information on this file, see
https://docs.djangoproject.com/en/2.2/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/2.2/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '#ec9^+0sn2y($%ol3tmug3r65ki6r=4+64y_l==f$ha&!zn=&$'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'register'
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'mail_confirm.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [os.path.join(BASE_DIR,'register/templates')],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'mail_confirm.wsgi.application'
# Database
# https://docs.djangoproject.com/en/2.2/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
#email_send
EMAIL_BACKEND = 'django.core.mail.backends.smtp.EmailBackend'
EMAIL_USE_TLS = True
EMAIL_HOST = 'smtp.gmail.com'
EMAIL_HOST_USER = 'gmail id here'
EMAIL_HOST_PASSWORD = 'gmail password'
EMAIL_PORT = 587
# Password validation
# https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/2.2/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/2.2/howto/static-files/
STATIC_URL = '/static/'
| [
"sanju2help@gmail.com"
] | sanju2help@gmail.com |
70bc84ae75d364f5e5d51b1a1aebb93a6249f0cb | acb8e84e3b9c987fcab341f799f41d5a5ec4d587 | /langs/4/ky2.py | 71729497763cd3bd7a28d0c2fe334d924ec8eb4b | [] | no_license | G4te-Keep3r/HowdyHackers | 46bfad63eafe5ac515da363e1c75fa6f4b9bca32 | fb6d391aaecb60ab5c4650d4ae2ddd599fd85db2 | refs/heads/master | 2020-08-01T12:08:10.782018 | 2016-11-13T20:45:50 | 2016-11-13T20:45:50 | 73,624,224 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 486 | py | import sys
def printFunction(lineRemaining):
if lineRemaining[0] == '"' and lineRemaining[-1] == '"':
if len(lineRemaining) > 2:
#data to print
lineRemaining = lineRemaining[1:-1]
print ' '.join(lineRemaining)
else:
print
def main(fileName):
with open(fileName) as f:
for line in f:
data = line.split()
if data[0] == 'kY2':
printFunction(data[1:])
else:
print 'ERROR'
return
if __name__ == '__main__':
main(sys.argv[1]) | [
"juliettaylorswift@gmail.com"
] | juliettaylorswift@gmail.com |
d352ea9e6b81a9572d3a7eada7b843cc47ffd773 | 31afebde0a0f52d14bdfeff55d6d2e3030bf7f62 | /crawlers/common_nlp/pdf_to_text.py | 28bf69b00b2e6e4861161ae02d28a868063e15f5 | [
"Apache-2.0"
] | permissive | FabioAyresInsper/Pesquisas | fb8f4a6e3835c49e7dd2d033b5f1e05cfc2448ba | ebc4a45b9953ff9d91a7284bd579ad02cf818e2a | refs/heads/master | 2020-03-17T22:11:42.741226 | 2018-05-29T12:23:11 | 2018-05-29T12:23:11 | 133,992,854 | 0 | 0 | null | 2018-05-18T18:53:39 | 2018-05-18T18:53:38 | null | UTF-8 | Python | false | false | 1,425 | py | from pdfminer.pdfparser import PDFParser
from pdfminer.pdfdocument import PDFDocument
from pdfminer.pdfpage import PDFPage
from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
from pdfminer.converter import PDFPageAggregator
from pdfminer.layout import LAParams, LTTextBox, LTTextLine
import PyPDF2
class pdf_to_text():
"""Converts pdf to text with pdfminer"""
def __init__(self):
pass
def convert_pdfminer(self, fname):
fp = open(fname, 'rb')
parser = PDFParser(fp)
doc = PDFDocument(parser)
rsrcmgr = PDFResourceManager()
laparams = LAParams()
device = PDFPageAggregator(rsrcmgr, laparams=laparams)
interpreter = PDFPageInterpreter(rsrcmgr, device)
text = ''
for page in PDFPage.create_pages(doc):
interpreter.process_page(page)
layout = device.get_result()
for lt_obj in layout:
if isinstance(lt_obj, LTTextBox) or isinstance(lt_obj, LTTextLine):
text += lt_obj.get_text()
return text
def convert_PyPDF2(self,fname):
pdfFileObj = open(fname,'rb')
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
text = ''
for i in range(pdfReader.numPages):
pageObj = pdfReader.getPage(i)
text += pageObj.extractText() + '\n'
return text
if __name__ == '__main__':
pass | [
"danilopcarlotti@gmail.com"
] | danilopcarlotti@gmail.com |
7d8f0504b3a317a137e02df5fcdf426b4e32f534 | f63db957cb63b3a37642d138d3092f8f897d6a53 | /roundup_getnodes/roundup/init.py | 7ecba91ef516ad7d261a828aa6e6dfd9f8dd374b | [
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"ZPL-2.1",
"ZPL-2.0"
] | permissive | fillarikanava/old-fillarikanava | c6fd819f95e675e6eddc674e71528c798b391967 | 8dbb89ea34c2aa98450e403ca2d7f17179edff8d | refs/heads/master | 2021-01-13T02:30:01.501771 | 2013-10-03T16:26:13 | 2013-10-03T16:26:13 | 13,201,013 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 6,395 | py | #
# Copyright (c) 2001 Bizar Software Pty Ltd (http://www.bizarsoftware.com.au/)
# This module is free software, and you may redistribute it and/or modify
# under the same terms as Python, so long as this copyright message and
# disclaimer are retained in their original form.
#
# IN NO EVENT SHALL BIZAR SOFTWARE PTY LTD BE LIABLE TO ANY PARTY FOR
# DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING
# OUT OF THE USE OF THIS CODE, EVEN IF THE AUTHOR HAS BEEN ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
# BIZAR SOFTWARE PTY LTD SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING,
# BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
# FOR A PARTICULAR PURPOSE. THE CODE PROVIDED HEREUNDER IS ON AN "AS IS"
# BASIS, AND THERE IS NO OBLIGATION WHATSOEVER TO PROVIDE MAINTENANCE,
# SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
#
# $Id: init.py,v 1.36 2005-12-03 11:22:50 a1s Exp $
"""Init (create) a roundup instance.
"""
__docformat__ = 'restructuredtext'
import os, errno, rfc822
from roundup import install_util, password
from roundup.configuration import CoreConfig
from roundup.i18n import _
def copytree(src, dst, symlinks=0):
"""Recursively copy a directory tree using copyDigestedFile().
The destination directory is allowed to exist.
If the optional symlinks flag is true, symbolic links in the
source tree result in symbolic links in the destination tree; if
it is false, the contents of the files pointed to by symbolic
links are copied.
This was copied from shutil.py in std lib.
"""
# Prevent 'hidden' files (those starting with '.') from being considered.
names = [f for f in os.listdir(src) if not f.startswith('.')]
try:
os.mkdir(dst)
except OSError, error:
if error.errno != errno.EEXIST: raise
for name in names:
srcname = os.path.join(src, name)
dstname = os.path.join(dst, name)
if symlinks and os.path.islink(srcname):
linkto = os.readlink(srcname)
os.symlink(linkto, dstname)
elif os.path.isdir(srcname):
copytree(srcname, dstname, symlinks)
else:
install_util.copyDigestedFile(srcname, dstname)
def install(instance_home, template, settings={}):
'''Install an instance using the named template and backend.
'instance_home'
the directory to place the instance data in
'template'
the directory holding the template to use in creating the instance data
'settings'
config.ini setting overrides (dictionary)
The instance_home directory will be created using the files found in
the named template (roundup.templates.<name>). A usual instance_home
contains:
config.ini
tracker configuration file
schema.py
database schema definition
initial_data.py
database initialization script, used to populate the database
with 'roundup-admin init' command
interfaces.py
(optional, not installed from standard templates) defines
the CGI Client and mail gateway MailGW classes that are
used by roundup.cgi, roundup-server and roundup-mailgw.
db/
the actual database that stores the instance's data
html/
the html templates that are used by the CGI Client
detectors/
the auditor and reactor modules for this instance
extensions/
code extensions to Roundup
'''
# At the moment, it's just a copy
copytree(template, instance_home)
# rename the tempate in the TEMPLATE-INFO.txt file
ti = loadTemplateInfo(instance_home)
ti['name'] = ti['name'] + '-' + os.path.split(instance_home)[1]
saveTemplateInfo(instance_home, ti)
# if there is no config.ini or old-style config.py
# installed from the template, write default config text
config_ini_file = os.path.join(instance_home, CoreConfig.INI_FILE)
if not os.path.isfile(config_ini_file):
config = CoreConfig(settings=settings)
config.save(config_ini_file)
def listTemplates(dir):
''' List all the Roundup template directories in a given directory.
Find all the dirs that contain a TEMPLATE-INFO.txt and parse it.
Return a list of dicts of info about the templates.
'''
ret = {}
for idir in os.listdir(dir):
idir = os.path.join(dir, idir)
ti = loadTemplateInfo(idir)
if ti:
ret[ti['name']] = ti
return ret
def loadTemplateInfo(dir):
''' Attempt to load a Roundup template from the indicated directory.
Return None if there's no template, otherwise a template info
dictionary.
'''
ti = os.path.join(dir, 'TEMPLATE-INFO.txt')
if not os.path.exists(ti):
return None
if os.path.exists(os.path.join(dir, 'config.py')):
print _("WARNING: directory '%s'\n"
"\tcontains old-style template - ignored"
) % os.path.abspath(dir)
return None
# load up the template's information
f = open(ti)
try:
m = rfc822.Message(open(ti))
ti = {}
ti['name'] = m['name']
ti['description'] = m['description']
ti['intended-for'] = m['intended-for']
ti['path'] = dir
finally:
f.close()
return ti
def writeHeader(name, value):
''' Write an rfc822-compatible header line, making it wrap reasonably
'''
out = [name.capitalize() + ':']
n = len(out[0])
for word in value.split():
if len(word) + n > 74:
out.append('\n')
n = 0
out.append(' ' + word)
n += len(out[-1])
return ''.join(out) + '\n'
def saveTemplateInfo(dir, info):
''' Save the template info (dict of values) to the TEMPLATE-INFO.txt
file in the indicated directory.
'''
ti = os.path.join(dir, 'TEMPLATE-INFO.txt')
f = open(ti, 'w')
try:
for name in 'name description intended-for path'.split():
f.write(writeHeader(name, info[name]))
finally:
f.close()
def write_select_db(instance_home, backend):
''' Write the file that selects the backend for the tracker
'''
dbdir = os.path.join(instance_home, 'db')
if not os.path.exists(dbdir):
os.makedirs(dbdir)
f = open(os.path.join(dbdir, 'backend_name'), 'w')
f.write(backend+'\n')
f.close()
# vim: set filetype=python sts=4 sw=4 et si :
| [
"rkarhila@iki.fi"
] | rkarhila@iki.fi |
a26bd92e4e80fe22862e8021588404a0bd9b2554 | 28c614942558229bb9adca33070331b04d454015 | /py/pantone-p-color-bridge-coated.py | b32073b70b4e7854182ebfab9d6ddb13602b0a57 | [] | no_license | qdv/Colorly | 95827b077b888251dea3a2ed58e8a37e98837409 | 6891a2d550a66e374c5da441b452256abccaffad | refs/heads/gh-pages | 2021-05-28T02:57:53.409957 | 2014-11-12T03:00:26 | 2014-11-12T03:00:26 | 100,415,084 | 1 | 0 | null | 2017-08-15T20:05:44 | 2017-08-15T20:05:44 | null | UTF-8 | Python | false | false | 106,974 | py | PALETTE = [
{
"name": "PANTONE Process Yellow CP",
"label": "process-yellow",
"hex": "#ffed00"
},
{
"name": "PANTONE Process Magenta CP",
"label": "process-magenta",
"hex": "#e3007d"
},
{
"name": "PANTONE Process Cyan CP",
"label": "process-cyan",
"hex": "#00a0e1"
},
{
"name": "PANTONE Process Black CP",
"label": "process-black",
"hex": "#2d2c2b"
},
{
"name": "PANTONE 100 CP",
"label": "100",
"hex": "#fff58d"
},
{
"name": "PANTONE 101 CP",
"label": "101",
"hex": "#fff26d"
},
{
"name": "PANTONE 102 CP",
"label": "102",
"hex": "#ffed00"
},
{
"name": "PANTONE Yellow CP",
"label": "yellow",
"hex": "#ffeb00"
},
{
"name": "PANTONE 103 CP",
"label": "103",
"hex": "#ddc600"
},
{
"name": "PANTONE 104 CP",
"label": "104",
"hex": "#c1a80d"
},
{
"name": "PANTONE 105 CP",
"label": "105",
"hex": "#988633"
},
{
"name": "PANTONE 7401 CP",
"label": "7401",
"hex": "#fff4cb"
},
{
"name": "PANTONE 7402 CP",
"label": "7402",
"hex": "#feeea5"
},
{
"name": "PANTONE 7403 CP",
"label": "7403",
"hex": "#fbde83"
},
{
"name": "PANTONE 7404 CP",
"label": "7404",
"hex": "#ffe234"
},
{
"name": "PANTONE 7405 CP",
"label": "7405",
"hex": "#ffd800"
},
{
"name": "PANTONE 7406 CP",
"label": "7406",
"hex": "#fcc900"
},
{
"name": "PANTONE 7407 CP",
"label": "7407",
"hex": "#d9a04a"
},
{
"name": "PANTONE 106 CP",
"label": "106",
"hex": "#fff159"
},
{
"name": "PANTONE 107 CP",
"label": "107",
"hex": "#ffee00"
},
{
"name": "PANTONE 108 CP",
"label": "108",
"hex": "#ffe500"
},
{
"name": "PANTONE 109 CP",
"label": "109",
"hex": "#ffde00"
},
{
"name": "PANTONE 110 CP",
"label": "110",
"hex": "#edbc00"
},
{
"name": "PANTONE 111 CP",
"label": "111",
"hex": "#be9d15"
},
{
"name": "PANTONE 112 CP",
"label": "112",
"hex": "#a58c1c"
},
{
"name": "PANTONE 113 CP",
"label": "113",
"hex": "#ffec3d"
},
{
"name": "PANTONE 114 CP",
"label": "114",
"hex": "#ffe82e"
},
{
"name": "PANTONE 115 CP",
"label": "115",
"hex": "#ffe52f"
},
{
"name": "PANTONE 116 CP",
"label": "116",
"hex": "#ffd600"
},
{
"name": "PANTONE 117 CP",
"label": "117",
"hex": "#dcab0b"
},
{
"name": "PANTONE 118 CP",
"label": "118",
"hex": "#b9911a"
},
{
"name": "PANTONE 119 CP",
"label": "119",
"hex": "#907d21"
},
{
"name": "PANTONE 127 CP",
"label": "127",
"hex": "#ffed7d"
},
{
"name": "PANTONE 128 CP",
"label": "128",
"hex": "#ffe659"
},
{
"name": "PANTONE 129 CP",
"label": "129",
"hex": "#ffde4f"
},
{
"name": "PANTONE 130 CP",
"label": "130",
"hex": "#fbb600"
},
{
"name": "PANTONE 131 CP",
"label": "131",
"hex": "#e29d14"
},
{
"name": "PANTONE 132 CP",
"label": "132",
"hex": "#b0811f"
},
{
"name": "PANTONE 133 CP",
"label": "133",
"hex": "#786024"
},
{
"name": "PANTONE 1205 CP",
"label": "1205",
"hex": "#fff2ab"
},
{
"name": "PANTONE 1215 CP",
"label": "1215",
"hex": "#ffec93"
},
{
"name": "PANTONE 1225 CP",
"label": "1225",
"hex": "#ffd14e"
},
{
"name": "PANTONE 1235 CP",
"label": "1235",
"hex": "#fcb909"
},
{
"name": "PANTONE 1245 CP",
"label": "1245",
"hex": "#cf981c"
},
{
"name": "PANTONE 1255 CP",
"label": "1255",
"hex": "#b48722"
},
{
"name": "PANTONE 1265 CP",
"label": "1265",
"hex": "#93712a"
},
{
"name": "PANTONE 120 CP",
"label": "120",
"hex": "#ffeb77"
},
{
"name": "PANTONE 121 CP",
"label": "121",
"hex": "#ffe566"
},
{
"name": "PANTONE 122 CP",
"label": "122",
"hex": "#ffde4a"
},
{
"name": "PANTONE 123 CP",
"label": "123",
"hex": "#ffcf2d"
},
{
"name": "PANTONE 124 CP",
"label": "124",
"hex": "#fcba00"
},
{
"name": "PANTONE 125 CP",
"label": "125",
"hex": "#c59418"
},
{
"name": "PANTONE 126 CP",
"label": "126",
"hex": "#a8841e"
},
{
"name": "PANTONE 7548 CP",
"label": "7548",
"hex": "#ffd900"
},
{
"name": "PANTONE 7549 CP",
"label": "7549",
"hex": "#fcc600"
},
{
"name": "PANTONE 7550 CP",
"label": "7550",
"hex": "#e3a418"
},
{
"name": "PANTONE 7551 CP",
"label": "7551",
"hex": "#bb8225"
},
{
"name": "PANTONE 7552 CP",
"label": "7552",
"hex": "#785b24"
},
{
"name": "PANTONE 7553 CP",
"label": "7553",
"hex": "#5c4932"
},
{
"name": "PANTONE 7554 CP",
"label": "7554",
"hex": "#463a2e"
},
{
"name": "PANTONE 7555 CP",
"label": "7555",
"hex": "#e7af10"
},
{
"name": "PANTONE 7556 CP",
"label": "7556",
"hex": "#cc971d"
},
{
"name": "PANTONE 7557 CP",
"label": "7557",
"hex": "#a7831f"
},
{
"name": "PANTONE 7558 CP",
"label": "7558",
"hex": "#9c782a"
},
{
"name": "PANTONE 7559 CP",
"label": "7559",
"hex": "#926e2a"
},
{
"name": "PANTONE 7560 CP",
"label": "7560",
"hex": "#7f6429"
},
{
"name": "PANTONE 7561 CP",
"label": "7561",
"hex": "#6d572c"
},
{
"name": "PANTONE 134 CP",
"label": "134",
"hex": "#ffe07f"
},
{
"name": "PANTONE 135 CP",
"label": "135",
"hex": "#ffcd55"
},
{
"name": "PANTONE 136 CP",
"label": "136",
"hex": "#fdc037"
},
{
"name": "PANTONE 137 CP",
"label": "137",
"hex": "#f8a60e"
},
{
"name": "PANTONE 138 CP",
"label": "138",
"hex": "#f3901b"
},
{
"name": "PANTONE 139 CP",
"label": "139",
"hex": "#bd7a21"
},
{
"name": "PANTONE 140 CP",
"label": "140",
"hex": "#7e5a25"
},
{
"name": "PANTONE 1345 CP",
"label": "1345",
"hex": "#ffda95"
},
{
"name": "PANTONE 1355 CP",
"label": "1355",
"hex": "#fecf7b"
},
{
"name": "PANTONE 1365 CP",
"label": "1365",
"hex": "#fab653"
},
{
"name": "PANTONE 1375 CP",
"label": "1375",
"hex": "#f69f29"
},
{
"name": "PANTONE 1385 CP",
"label": "1385",
"hex": "#e98520"
},
{
"name": "PANTONE 1395 CP",
"label": "1395",
"hex": "#a16424"
},
{
"name": "PANTONE 1405 CP",
"label": "1405",
"hex": "#734f25"
},
{
"name": "PANTONE 141 CP",
"label": "141",
"hex": "#ffd871"
},
{
"name": "PANTONE 142 CP",
"label": "142",
"hex": "#fec850"
},
{
"name": "PANTONE 143 CP",
"label": "143",
"hex": "#fbb838"
},
{
"name": "PANTONE 144 CP",
"label": "144",
"hex": "#f4921a"
},
{
"name": "PANTONE 145 CP",
"label": "145",
"hex": "#df851f"
},
{
"name": "PANTONE 146 CP",
"label": "146",
"hex": "#ac7022"
},
{
"name": "PANTONE 147 CP",
"label": "147",
"hex": "#79602e"
},
{
"name": "PANTONE 7408 CP",
"label": "7408",
"hex": "#fcbc00"
},
{
"name": "PANTONE 7409 CP",
"label": "7409",
"hex": "#fcb900"
},
{
"name": "PANTONE 7410 CP",
"label": "7410",
"hex": "#f7ab74"
},
{
"name": "PANTONE 7411 CP",
"label": "7411",
"hex": "#f3a654"
},
{
"name": "PANTONE 7412 CP",
"label": "7412",
"hex": "#dc7b2a"
},
{
"name": "PANTONE 7413 CP",
"label": "7413",
"hex": "#e77c26"
},
{
"name": "PANTONE 7414 CP",
"label": "7414",
"hex": "#c06326"
},
{
"name": "PANTONE 7562 CP",
"label": "7562",
"hex": "#cca360"
},
{
"name": "PANTONE 7563 CP",
"label": "7563",
"hex": "#ecae37"
},
{
"name": "PANTONE 7564 CP",
"label": "7564",
"hex": "#ef9a16"
},
{
"name": "PANTONE 7565 CP",
"label": "7565",
"hex": "#df8423"
},
{
"name": "PANTONE 7566 CP",
"label": "7566",
"hex": "#bb5f29"
},
{
"name": "PANTONE 7567 CP",
"label": "7567",
"hex": "#7f4926"
},
{
"name": "PANTONE 7568 CP",
"label": "7568",
"hex": "#6e4225"
},
{
"name": "PANTONE 7569 CP",
"label": "7569",
"hex": "#eb9816"
},
{
"name": "PANTONE 7570 CP",
"label": "7570",
"hex": "#e28f21"
},
{
"name": "PANTONE 7571 CP",
"label": "7571",
"hex": "#ce8325"
},
{
"name": "PANTONE 7572 CP",
"label": "7572",
"hex": "#b9742c"
},
{
"name": "PANTONE 7573 CP",
"label": "7573",
"hex": "#aa6a33"
},
{
"name": "PANTONE 7574 CP",
"label": "7574",
"hex": "#a2662f"
},
{
"name": "PANTONE 7575 CP",
"label": "7575",
"hex": "#81562a"
},
{
"name": "PANTONE 712 CP",
"label": "712",
"hex": "#fcd8b9"
},
{
"name": "PANTONE 713 CP",
"label": "713",
"hex": "#fac9a2"
},
{
"name": "PANTONE 714 CP",
"label": "714",
"hex": "#f7ae75"
},
{
"name": "PANTONE 715 CP",
"label": "715",
"hex": "#f28d3a"
},
{
"name": "PANTONE 716 CP",
"label": "716",
"hex": "#f07d24"
},
{
"name": "PANTONE 717 CP",
"label": "717",
"hex": "#ed6f24"
},
{
"name": "PANTONE 718 CP",
"label": "718",
"hex": "#dd5d26"
},
{
"name": "PANTONE 148 CP",
"label": "148",
"hex": "#fedba3"
},
{
"name": "PANTONE 149 CP",
"label": "149",
"hex": "#fccd8e"
},
{
"name": "PANTONE 150 CP",
"label": "150",
"hex": "#f7a94e"
},
{
"name": "PANTONE 151 CP",
"label": "151",
"hex": "#f07f21"
},
{
"name": "PANTONE 152 CP",
"label": "152",
"hex": "#ee7323"
},
{
"name": "PANTONE 153 CP",
"label": "153",
"hex": "#c96925"
},
{
"name": "PANTONE 154 CP",
"label": "154",
"hex": "#9c5426"
},
{
"name": "PANTONE 155 CP",
"label": "155",
"hex": "#ffe5b8"
},
{
"name": "PANTONE 156 CP",
"label": "156",
"hex": "#fdcf93"
},
{
"name": "PANTONE 157 CP",
"label": "157",
"hex": "#f7a856"
},
{
"name": "PANTONE 158 CP",
"label": "158",
"hex": "#ef7c2c"
},
{
"name": "PANTONE 159 CP",
"label": "159",
"hex": "#de6126"
},
{
"name": "PANTONE 160 CP",
"label": "160",
"hex": "#ae5426"
},
{
"name": "PANTONE 161 CP",
"label": "161",
"hex": "#633d24"
},
{
"name": "PANTONE 1485 CP",
"label": "1485",
"hex": "#f9b97a"
},
{
"name": "PANTONE 1495 CP",
"label": "1495",
"hex": "#f69f4d"
},
{
"name": "PANTONE 1505 CP",
"label": "1505",
"hex": "#f28935"
},
{
"name": "PANTONE Orange 021 CP",
"label": "orange-021",
"hex": "#ee7523"
},
{
"name": "PANTONE 1525 CP",
"label": "1525",
"hex": "#d85727"
},
{
"name": "PANTONE 1535 CP",
"label": "1535",
"hex": "#964727"
},
{
"name": "PANTONE 1545 CP",
"label": "1545",
"hex": "#613825"
},
{
"name": "PANTONE 1555 CP",
"label": "1555",
"hex": "#fbccaa"
},
{
"name": "PANTONE 1565 CP",
"label": "1565",
"hex": "#f7b185"
},
{
"name": "PANTONE 1575 CP",
"label": "1575",
"hex": "#f4954e"
},
{
"name": "PANTONE 1585 CP",
"label": "1585",
"hex": "#f07d28"
},
{
"name": "PANTONE 1595 CP",
"label": "1595",
"hex": "#e76625"
},
{
"name": "PANTONE 1605 CP",
"label": "1605",
"hex": "#ac5326"
},
{
"name": "PANTONE 1615 CP",
"label": "1615",
"hex": "#904926"
},
{
"name": "PANTONE 162 CP",
"label": "162",
"hex": "#fbcdad"
},
{
"name": "PANTONE 163 CP",
"label": "163",
"hex": "#f5a77f"
},
{
"name": "PANTONE 164 CP",
"label": "164",
"hex": "#f18446"
},
{
"name": "PANTONE 165 CP",
"label": "165",
"hex": "#ec6925"
},
{
"name": "PANTONE 166 CP",
"label": "166",
"hex": "#ea5d27"
},
{
"name": "PANTONE 167 CP",
"label": "167",
"hex": "#c95328"
},
{
"name": "PANTONE 168 CP",
"label": "168",
"hex": "#773a26"
},
{
"name": "PANTONE 7576 CP",
"label": "7576",
"hex": "#ea9550"
},
{
"name": "PANTONE 7577 CP",
"label": "7577",
"hex": "#ef8d5b"
},
{
"name": "PANTONE 7578 CP",
"label": "7578",
"hex": "#ee7024"
},
{
"name": "PANTONE 7579 CP",
"label": "7579",
"hex": "#eb6126"
},
{
"name": "PANTONE 7580 CP",
"label": "7580",
"hex": "#d0542b"
},
{
"name": "PANTONE 7581 CP",
"label": "7581",
"hex": "#834b38"
},
{
"name": "PANTONE 7582 CP",
"label": "7582",
"hex": "#674935"
},
{
"name": "PANTONE 1625 CP",
"label": "1625",
"hex": "#f6ae93"
},
{
"name": "PANTONE 1635 CP",
"label": "1635",
"hex": "#f39875"
},
{
"name": "PANTONE 1645 CP",
"label": "1645",
"hex": "#ef7b4d"
},
{
"name": "PANTONE 1655 CP",
"label": "1655",
"hex": "#ec6429"
},
{
"name": "PANTONE 1665 CP",
"label": "1665",
"hex": "#ea5727"
},
{
"name": "PANTONE 1675 CP",
"label": "1675",
"hex": "#b34428"
},
{
"name": "PANTONE 1685 CP",
"label": "1685",
"hex": "#8b3d27"
},
{
"name": "PANTONE 169 CP",
"label": "169",
"hex": "#f9c5b7"
},
{
"name": "PANTONE 170 CP",
"label": "170",
"hex": "#f49f80"
},
{
"name": "PANTONE 171 CP",
"label": "171",
"hex": "#f07f52"
},
{
"name": "PANTONE 172 CP",
"label": "172",
"hex": "#ec6439"
},
{
"name": "PANTONE 173 CP",
"label": "173",
"hex": "#e54f30"
},
{
"name": "PANTONE 174 CP",
"label": "174",
"hex": "#a13c28"
},
{
"name": "PANTONE 175 CP",
"label": "175",
"hex": "#793c32"
},
{
"name": "PANTONE 7583 CP",
"label": "7583",
"hex": "#d76428"
},
{
"name": "PANTONE 7584 CP",
"label": "7584",
"hex": "#ce5f25"
},
{
"name": "PANTONE 7585 CP",
"label": "7585",
"hex": "#c36132"
},
{
"name": "PANTONE 7586 CP",
"label": "7586",
"hex": "#a3522f"
},
{
"name": "PANTONE 7587 CP",
"label": "7587",
"hex": "#974c2e"
},
{
"name": "PANTONE 7588 CP",
"label": "7588",
"hex": "#7a4f38"
},
{
"name": "PANTONE 7589 CP",
"label": "7589",
"hex": "#553932"
},
{
"name": "PANTONE 7590 CP",
"label": "7590",
"hex": "#e6c3ad"
},
{
"name": "PANTONE 7591 CP",
"label": "7591",
"hex": "#d6895d"
},
{
"name": "PANTONE 7592 CP",
"label": "7592",
"hex": "#c35e37"
},
{
"name": "PANTONE 7593 CP",
"label": "7593",
"hex": "#a4452e"
},
{
"name": "PANTONE 7594 CP",
"label": "7594",
"hex": "#824837"
},
{
"name": "PANTONE 7595 CP",
"label": "7595",
"hex": "#784c37"
},
{
"name": "PANTONE 7596 CP",
"label": "7596",
"hex": "#533227"
},
{
"name": "PANTONE 7597 CP",
"label": "7597",
"hex": "#e14729"
},
{
"name": "PANTONE 7598 CP",
"label": "7598",
"hex": "#d64528"
},
{
"name": "PANTONE 7599 CP",
"label": "7599",
"hex": "#c5432a"
},
{
"name": "PANTONE 7600 CP",
"label": "7600",
"hex": "#8a3f2f"
},
{
"name": "PANTONE 7601 CP",
"label": "7601",
"hex": "#853c27"
},
{
"name": "PANTONE 7602 CP",
"label": "7602",
"hex": "#764428"
},
{
"name": "PANTONE 7603 CP",
"label": "7603",
"hex": "#603b25"
},
{
"name": "PANTONE 7604 CP",
"label": "7604",
"hex": "#f6ebe9"
},
{
"name": "PANTONE 7605 CP",
"label": "7605",
"hex": "#f3d1cc"
},
{
"name": "PANTONE 7606 CP",
"label": "7606",
"hex": "#eba8a2"
},
{
"name": "PANTONE 7607 CP",
"label": "7607",
"hex": "#d77a6d"
},
{
"name": "PANTONE 7608 CP",
"label": "7608",
"hex": "#b44e3f"
},
{
"name": "PANTONE 7609 CP",
"label": "7609",
"hex": "#8b3c34"
},
{
"name": "PANTONE 7610 CP",
"label": "7610",
"hex": "#6b3733"
},
{
"name": "PANTONE 7611 CP",
"label": "7611",
"hex": "#f1d3c9"
},
{
"name": "PANTONE 7612 CP",
"label": "7612",
"hex": "#deac9c"
},
{
"name": "PANTONE 7613 CP",
"label": "7613",
"hex": "#cf9886"
},
{
"name": "PANTONE 7614 CP",
"label": "7614",
"hex": "#b58c7e"
},
{
"name": "PANTONE 7615 CP",
"label": "7615",
"hex": "#886861"
},
{
"name": "PANTONE 7616 CP",
"label": "7616",
"hex": "#795754"
},
{
"name": "PANTONE 7617 CP",
"label": "7617",
"hex": "#5d3f3d"
},
{
"name": "PANTONE 7520 CP",
"label": "7520",
"hex": "#f8cdc3"
},
{
"name": "PANTONE 7521 CP",
"label": "7521",
"hex": "#d8ad9d"
},
{
"name": "PANTONE 7522 CP",
"label": "7522",
"hex": "#c87062"
},
{
"name": "PANTONE 7523 CP",
"label": "7523",
"hex": "#b86160"
},
{
"name": "PANTONE 7524 CP",
"label": "7524",
"hex": "#b04c4b"
},
{
"name": "PANTONE 7525 CP",
"label": "7525",
"hex": "#a76a52"
},
{
"name": "PANTONE 7526 CP",
"label": "7526",
"hex": "#903c27"
},
{
"name": "PANTONE 489 CP",
"label": "489",
"hex": "#fcd9c9"
},
{
"name": "PANTONE 488 CP",
"label": "488",
"hex": "#f8c4b7"
},
{
"name": "PANTONE 487 CP",
"label": "487",
"hex": "#f5aa95"
},
{
"name": "PANTONE 486 CP",
"label": "486",
"hex": "#f2907a"
},
{
"name": "PANTONE 485 CP",
"label": "485",
"hex": "#e52f2a"
},
{
"name": "PANTONE 484 CP",
"label": "484",
"hex": "#a53429"
},
{
"name": "PANTONE 483 CP",
"label": "483",
"hex": "#62352c"
},
{
"name": "PANTONE 176 CP",
"label": "176",
"hex": "#f7bdbf"
},
{
"name": "PANTONE 177 CP",
"label": "177",
"hex": "#f2928d"
},
{
"name": "PANTONE 178 CP",
"label": "178",
"hex": "#ed6c62"
},
{
"name": "PANTONE Warm Red CP",
"label": "warm-red",
"hex": "#e94d40"
},
{
"name": "PANTONE 179 CP",
"label": "179",
"hex": "#e74439"
},
{
"name": "PANTONE 180 CP",
"label": "180",
"hex": "#cd3936"
},
{
"name": "PANTONE 181 CP",
"label": "181",
"hex": "#7e312d"
},
{
"name": "PANTONE 1765 CP",
"label": "1765",
"hex": "#f5afb7"
},
{
"name": "PANTONE 1775 CP",
"label": "1775",
"hex": "#f39fa8"
},
{
"name": "PANTONE 1785 CP",
"label": "1785",
"hex": "#eb5e62"
},
{
"name": "PANTONE 1788 CP",
"label": "1788",
"hex": "#e7423c"
},
{
"name": "PANTONE 1795 CP",
"label": "1795",
"hex": "#e12b30"
},
{
"name": "PANTONE 1805 CP",
"label": "1805",
"hex": "#b92d38"
},
{
"name": "PANTONE 1815 CP",
"label": "1815",
"hex": "#7c2c2c"
},
{
"name": "PANTONE 1767 CP",
"label": "1767",
"hex": "#f7c2cd"
},
{
"name": "PANTONE 1777 CP",
"label": "1777",
"hex": "#ee788b"
},
{
"name": "PANTONE 1787 CP",
"label": "1787",
"hex": "#e9505f"
},
{
"name": "PANTONE Red 032 CP",
"label": "red-032",
"hex": "#e84751"
},
{
"name": "PANTONE 1797 CP",
"label": "1797",
"hex": "#d62a36"
},
{
"name": "PANTONE 1807 CP",
"label": "1807",
"hex": "#a3323b"
},
{
"name": "PANTONE 1817 CP",
"label": "1817",
"hex": "#5b3032"
},
{
"name": "PANTONE 7618 CP",
"label": "7618",
"hex": "#dc7852"
},
{
"name": "PANTONE 7619 CP",
"label": "7619",
"hex": "#d55338"
},
{
"name": "PANTONE 7620 CP",
"label": "7620",
"hex": "#b52f2d"
},
{
"name": "PANTONE 7621 CP",
"label": "7621",
"hex": "#b0282e"
},
{
"name": "PANTONE 7622 CP",
"label": "7622",
"hex": "#982b2d"
},
{
"name": "PANTONE 7623 CP",
"label": "7623",
"hex": "#8a2c2c"
},
{
"name": "PANTONE 7624 CP",
"label": "7624",
"hex": "#7e2b2a"
},
{
"name": "PANTONE 7625 CP",
"label": "7625",
"hex": "#e95040"
},
{
"name": "PANTONE 7626 CP",
"label": "7626",
"hex": "#e2352f"
},
{
"name": "PANTONE 7627 CP",
"label": "7627",
"hex": "#ba3232"
},
{
"name": "PANTONE 7628 CP",
"label": "7628",
"hex": "#a53236"
},
{
"name": "PANTONE 7629 CP",
"label": "7629",
"hex": "#6c3231"
},
{
"name": "PANTONE 7630 CP",
"label": "7630",
"hex": "#5f312b"
},
{
"name": "PANTONE 7631 CP",
"label": "7631",
"hex": "#583035"
},
{
"name": "PANTONE 7415 CP",
"label": "7415",
"hex": "#f7c8b8"
},
{
"name": "PANTONE 7416 CP",
"label": "7416",
"hex": "#ec6750"
},
{
"name": "PANTONE 7417 CP",
"label": "7417",
"hex": "#e74d3a"
},
{
"name": "PANTONE 7418 CP",
"label": "7418",
"hex": "#d54c5a"
},
{
"name": "PANTONE 7419 CP",
"label": "7419",
"hex": "#b35060"
},
{
"name": "PANTONE 7420 CP",
"label": "7420",
"hex": "#a32343"
},
{
"name": "PANTONE 7421 CP",
"label": "7421",
"hex": "#682535"
},
{
"name": "PANTONE 182 CP",
"label": "182",
"hex": "#f8c6d2"
},
{
"name": "PANTONE 183 CP",
"label": "183",
"hex": "#f3a0b0"
},
{
"name": "PANTONE 184 CP",
"label": "184",
"hex": "#ec667f"
},
{
"name": "PANTONE 185 CP",
"label": "185",
"hex": "#e6343e"
},
{
"name": "PANTONE 186 CP",
"label": "186",
"hex": "#d71e36"
},
{
"name": "PANTONE 187 CP",
"label": "187",
"hex": "#b02434"
},
{
"name": "PANTONE 188 CP",
"label": "188",
"hex": "#762732"
},
{
"name": "PANTONE 196 CP",
"label": "196",
"hex": "#fad5de"
},
{
"name": "PANTONE 197 CP",
"label": "197",
"hex": "#f4a7ba"
},
{
"name": "PANTONE 198 CP",
"label": "198",
"hex": "#e95071"
},
{
"name": "PANTONE 199 CP",
"label": "199",
"hex": "#e41941"
},
{
"name": "PANTONE 200 CP",
"label": "200",
"hex": "#cb1f40"
},
{
"name": "PANTONE 201 CP",
"label": "201",
"hex": "#a6243a"
},
{
"name": "PANTONE 202 CP",
"label": "202",
"hex": "#8b2636"
},
{
"name": "PANTONE 189 CP",
"label": "189",
"hex": "#f5b6c6"
},
{
"name": "PANTONE 190 CP",
"label": "190",
"hex": "#f190a5"
},
{
"name": "PANTONE 191 CP",
"label": "191",
"hex": "#ea5875"
},
{
"name": "PANTONE 192 CP",
"label": "192",
"hex": "#e6304c"
},
{
"name": "PANTONE 193 CP",
"label": "193",
"hex": "#cf2147"
},
{
"name": "PANTONE 194 CP",
"label": "194",
"hex": "#9e2440"
},
{
"name": "PANTONE 195 CP",
"label": "195",
"hex": "#7a313e"
},
{
"name": "PANTONE 1895 CP",
"label": "1895",
"hex": "#f7c9dc"
},
{
"name": "PANTONE 1905 CP",
"label": "1905",
"hex": "#f3a5bd"
},
{
"name": "PANTONE 1915 CP",
"label": "1915",
"hex": "#eb6189"
},
{
"name": "PANTONE 1925 CP",
"label": "1925",
"hex": "#e52457"
},
{
"name": "PANTONE 1935 CP",
"label": "1935",
"hex": "#d9184e"
},
{
"name": "PANTONE 1945 CP",
"label": "1945",
"hex": "#af2144"
},
{
"name": "PANTONE 1955 CP",
"label": "1955",
"hex": "#93243d"
},
{
"name": "PANTONE 705 CP",
"label": "705",
"hex": "#fdecef"
},
{
"name": "PANTONE 706 CP",
"label": "706",
"hex": "#fad5dc"
},
{
"name": "PANTONE 707 CP",
"label": "707",
"hex": "#f6bccc"
},
{
"name": "PANTONE 708 CP",
"label": "708",
"hex": "#f197ab"
},
{
"name": "PANTONE 709 CP",
"label": "709",
"hex": "#ed7087"
},
{
"name": "PANTONE 710 CP",
"label": "710",
"hex": "#e94b65"
},
{
"name": "PANTONE 711 CP",
"label": "711",
"hex": "#e52740"
},
{
"name": "PANTONE 698 CP",
"label": "698",
"hex": "#fbe3e8"
},
{
"name": "PANTONE 699 CP",
"label": "699",
"hex": "#f8cdda"
},
{
"name": "PANTONE 700 CP",
"label": "700",
"hex": "#f5b4c7"
},
{
"name": "PANTONE 701 CP",
"label": "701",
"hex": "#f08ba8"
},
{
"name": "PANTONE 702 CP",
"label": "702",
"hex": "#e1597a"
},
{
"name": "PANTONE 703 CP",
"label": "703",
"hex": "#c43750"
},
{
"name": "PANTONE 704 CP",
"label": "704",
"hex": "#a72b37"
},
{
"name": "PANTONE 203 CP",
"label": "203",
"hex": "#f6bbd3"
},
{
"name": "PANTONE 204 CP",
"label": "204",
"hex": "#f08ab0"
},
{
"name": "PANTONE 205 CP",
"label": "205",
"hex": "#e94c83"
},
{
"name": "PANTONE 206 CP",
"label": "206",
"hex": "#e41355"
},
{
"name": "PANTONE 207 CP",
"label": "207",
"hex": "#b91f4c"
},
{
"name": "PANTONE 208 CP",
"label": "208",
"hex": "#8b2345"
},
{
"name": "PANTONE 209 CP",
"label": "209",
"hex": "#74283d"
},
{
"name": "PANTONE 210 CP",
"label": "210",
"hex": "#f3aac6"
},
{
"name": "PANTONE 211 CP",
"label": "211",
"hex": "#ef84ac"
},
{
"name": "PANTONE 212 CP",
"label": "212",
"hex": "#ea5992"
},
{
"name": "PANTONE 213 CP",
"label": "213",
"hex": "#e63078"
},
{
"name": "PANTONE 214 CP",
"label": "214",
"hex": "#dd0868"
},
{
"name": "PANTONE 215 CP",
"label": "215",
"hex": "#b51a5a"
},
{
"name": "PANTONE 216 CP",
"label": "216",
"hex": "#832849"
},
{
"name": "PANTONE 7422 CP",
"label": "7422",
"hex": "#fbe3ea"
},
{
"name": "PANTONE 7423 CP",
"label": "7423",
"hex": "#ec6692"
},
{
"name": "PANTONE 7424 CP",
"label": "7424",
"hex": "#e73782"
},
{
"name": "PANTONE 7425 CP",
"label": "7425",
"hex": "#c82760"
},
{
"name": "PANTONE 7426 CP",
"label": "7426",
"hex": "#b9224f"
},
{
"name": "PANTONE 7427 CP",
"label": "7427",
"hex": "#a42539"
},
{
"name": "PANTONE 7428 CP",
"label": "7428",
"hex": "#6e283d"
},
{
"name": "PANTONE 7632 CP",
"label": "7632",
"hex": "#efe2e4"
},
{
"name": "PANTONE 7633 CP",
"label": "7633",
"hex": "#d7b4bb"
},
{
"name": "PANTONE 7634 CP",
"label": "7634",
"hex": "#d6708f"
},
{
"name": "PANTONE 7635 CP",
"label": "7635",
"hex": "#da386f"
},
{
"name": "PANTONE 7636 CP",
"label": "7636",
"hex": "#d01853"
},
{
"name": "PANTONE 7637 CP",
"label": "7637",
"hex": "#9a2e48"
},
{
"name": "PANTONE 7638 CP",
"label": "7638",
"hex": "#8e3048"
},
{
"name": "PANTONE 217 CP",
"label": "217",
"hex": "#f5c4dc"
},
{
"name": "PANTONE 218 CP",
"label": "218",
"hex": "#eb7faf"
},
{
"name": "PANTONE 219 CP",
"label": "219",
"hex": "#e42e83"
},
{
"name": "PANTONE Rubine Red CP",
"label": "rubine-red",
"hex": "#df066a"
},
{
"name": "PANTONE 220 CP",
"label": "220",
"hex": "#b61a5a"
},
{
"name": "PANTONE 221 CP",
"label": "221",
"hex": "#9c1f50"
},
{
"name": "PANTONE 222 CP",
"label": "222",
"hex": "#702342"
},
{
"name": "PANTONE 7639 CP",
"label": "7639",
"hex": "#9c747c"
},
{
"name": "PANTONE 7640 CP",
"label": "7640",
"hex": "#a3445e"
},
{
"name": "PANTONE 7641 CP",
"label": "7641",
"hex": "#9c294e"
},
{
"name": "PANTONE 7642 CP",
"label": "7642",
"hex": "#7a304d"
},
{
"name": "PANTONE 7643 CP",
"label": "7643",
"hex": "#6f2f49"
},
{
"name": "PANTONE 7644 CP",
"label": "7644",
"hex": "#5c2c40"
},
{
"name": "PANTONE 7645 CP",
"label": "7645",
"hex": "#552c3c"
},
{
"name": "PANTONE 223 CP",
"label": "223",
"hex": "#f09fc4"
},
{
"name": "PANTONE 224 CP",
"label": "224",
"hex": "#e76da4"
},
{
"name": "PANTONE 225 CP",
"label": "225",
"hex": "#e13c8b"
},
{
"name": "PANTONE 226 CP",
"label": "226",
"hex": "#e3007b"
},
{
"name": "PANTONE 227 CP",
"label": "227",
"hex": "#b81566"
},
{
"name": "PANTONE 228 CP",
"label": "228",
"hex": "#8f1f54"
},
{
"name": "PANTONE 229 CP",
"label": "229",
"hex": "#6b2343"
},
{
"name": "PANTONE 230 CP",
"label": "230",
"hex": "#f2b2d0"
},
{
"name": "PANTONE 231 CP",
"label": "231",
"hex": "#ea86b4"
},
{
"name": "PANTONE 232 CP",
"label": "232",
"hex": "#e36ca4"
},
{
"name": "PANTONE Rhodamine Red CP",
"label": "rhodamine-red",
"hex": "#da3f8d"
},
{
"name": "PANTONE 233 CP",
"label": "233",
"hex": "#d2067d"
},
{
"name": "PANTONE 234 CP",
"label": "234",
"hex": "#af196c"
},
{
"name": "PANTONE 235 CP",
"label": "235",
"hex": "#8c1f57"
},
{
"name": "PANTONE 670 CP",
"label": "670",
"hex": "#f9e1ed"
},
{
"name": "PANTONE 671 CP",
"label": "671",
"hex": "#f2cbe0"
},
{
"name": "PANTONE 672 CP",
"label": "672",
"hex": "#e9a6c9"
},
{
"name": "PANTONE 673 CP",
"label": "673",
"hex": "#e190bb"
},
{
"name": "PANTONE 674 CP",
"label": "674",
"hex": "#d04a92"
},
{
"name": "PANTONE 675 CP",
"label": "675",
"hex": "#be1378"
},
{
"name": "PANTONE 676 CP",
"label": "676",
"hex": "#a41b5b"
},
{
"name": "PANTONE 677 CP",
"label": "677",
"hex": "#f5e0eb"
},
{
"name": "PANTONE 678 CP",
"label": "678",
"hex": "#f1d3e4"
},
{
"name": "PANTONE 679 CP",
"label": "679",
"hex": "#f0c9df"
},
{
"name": "PANTONE 680 CP",
"label": "680",
"hex": "#d998bc"
},
{
"name": "PANTONE 681 CP",
"label": "681",
"hex": "#c56a9c"
},
{
"name": "PANTONE 682 CP",
"label": "682",
"hex": "#9c3b72"
},
{
"name": "PANTONE 683 CP",
"label": "683",
"hex": "#7b2350"
},
{
"name": "PANTONE 684 CP",
"label": "684",
"hex": "#f2d5e3"
},
{
"name": "PANTONE 685 CP",
"label": "685",
"hex": "#f0c6da"
},
{
"name": "PANTONE 686 CP",
"label": "686",
"hex": "#e6acca"
},
{
"name": "PANTONE 687 CP",
"label": "687",
"hex": "#cf86ad"
},
{
"name": "PANTONE 688 CP",
"label": "688",
"hex": "#bf6797"
},
{
"name": "PANTONE 689 CP",
"label": "689",
"hex": "#8f3366"
},
{
"name": "PANTONE 690 CP",
"label": "690",
"hex": "#5f2441"
},
{
"name": "PANTONE 510 CP",
"label": "510",
"hex": "#f7c8da"
},
{
"name": "PANTONE 509 CP",
"label": "509",
"hex": "#f4bcd2"
},
{
"name": "PANTONE 508 CP",
"label": "508",
"hex": "#efb0c9"
},
{
"name": "PANTONE 507 CP",
"label": "507",
"hex": "#e195b2"
},
{
"name": "PANTONE 506 CP",
"label": "506",
"hex": "#773344"
},
{
"name": "PANTONE 505 CP",
"label": "505",
"hex": "#6b353d"
},
{
"name": "PANTONE 504 CP",
"label": "504",
"hex": "#583037"
},
{
"name": "PANTONE 7429 CP",
"label": "7429",
"hex": "#f4cfe0"
},
{
"name": "PANTONE 7430 CP",
"label": "7430",
"hex": "#eeb6d0"
},
{
"name": "PANTONE 7431 CP",
"label": "7431",
"hex": "#de8db0"
},
{
"name": "PANTONE 7432 CP",
"label": "7432",
"hex": "#c75c88"
},
{
"name": "PANTONE 7433 CP",
"label": "7433",
"hex": "#b53569"
},
{
"name": "PANTONE 7434 CP",
"label": "7434",
"hex": "#a12c58"
},
{
"name": "PANTONE 7435 CP",
"label": "7435",
"hex": "#87214c"
},
{
"name": "PANTONE 691 CP",
"label": "691",
"hex": "#fae4e7"
},
{
"name": "PANTONE 692 CP",
"label": "692",
"hex": "#f2ccd6"
},
{
"name": "PANTONE 693 CP",
"label": "693",
"hex": "#e5aebf"
},
{
"name": "PANTONE 694 CP",
"label": "694",
"hex": "#d38fa3"
},
{
"name": "PANTONE 695 CP",
"label": "695",
"hex": "#bb6f83"
},
{
"name": "PANTONE 696 CP",
"label": "696",
"hex": "#933f50"
},
{
"name": "PANTONE 697 CP",
"label": "697",
"hex": "#873946"
},
{
"name": "PANTONE 496 CP",
"label": "496",
"hex": "#f8cedb"
},
{
"name": "PANTONE 495 CP",
"label": "495",
"hex": "#f7c4d4"
},
{
"name": "PANTONE 494 CP",
"label": "494",
"hex": "#f3a5bb"
},
{
"name": "PANTONE 493 CP",
"label": "493",
"hex": "#e88ba2"
},
{
"name": "PANTONE 492 CP",
"label": "492",
"hex": "#8c393e"
},
{
"name": "PANTONE 491 CP",
"label": "491",
"hex": "#7a3637"
},
{
"name": "PANTONE 490 CP",
"label": "490",
"hex": "#5a3029"
},
{
"name": "PANTONE 503 CP",
"label": "503",
"hex": "#f8dae0"
},
{
"name": "PANTONE 502 CP",
"label": "502",
"hex": "#f7ced5"
},
{
"name": "PANTONE 501 CP",
"label": "501",
"hex": "#eab0be"
},
{
"name": "PANTONE 500 CP",
"label": "500",
"hex": "#d08d99"
},
{
"name": "PANTONE 499 CP",
"label": "499",
"hex": "#77413e"
},
{
"name": "PANTONE 498 CP",
"label": "498",
"hex": "#67382f"
},
{
"name": "PANTONE 497 CP",
"label": "497",
"hex": "#4f332b"
},
{
"name": "PANTONE 5035 CP",
"label": "5035",
"hex": "#f3d9dc"
},
{
"name": "PANTONE 5025 CP",
"label": "5025",
"hex": "#e6bcc2"
},
{
"name": "PANTONE 5015 CP",
"label": "5015",
"hex": "#dcaeb7"
},
{
"name": "PANTONE 5005 CP",
"label": "5005",
"hex": "#b07781"
},
{
"name": "PANTONE 4995 CP",
"label": "4995",
"hex": "#9a5d69"
},
{
"name": "PANTONE 4985 CP",
"label": "4985",
"hex": "#834552"
},
{
"name": "PANTONE 4975 CP",
"label": "4975",
"hex": "#422a2a"
},
{
"name": "PANTONE 236 CP",
"label": "236",
"hex": "#f0bad5"
},
{
"name": "PANTONE 237 CP",
"label": "237",
"hex": "#e796be"
},
{
"name": "PANTONE 238 CP",
"label": "238",
"hex": "#d8619e"
},
{
"name": "PANTONE 239 CP",
"label": "239",
"hex": "#d04d93"
},
{
"name": "PANTONE 240 CP",
"label": "240",
"hex": "#c83b8a"
},
{
"name": "PANTONE 241 CP",
"label": "241",
"hex": "#b31c7b"
},
{
"name": "PANTONE 242 CP",
"label": "242",
"hex": "#802257"
},
{
"name": "PANTONE 2365 CP",
"label": "2365",
"hex": "#f4c8de"
},
{
"name": "PANTONE 2375 CP",
"label": "2375",
"hex": "#d482b3"
},
{
"name": "PANTONE 2385 CP",
"label": "2385",
"hex": "#c44a92"
},
{
"name": "PANTONE 2395 CP",
"label": "2395",
"hex": "#bf3a8a"
},
{
"name": "PANTONE 2405 CP",
"label": "2405",
"hex": "#ac207f"
},
{
"name": "PANTONE 2415 CP",
"label": "2415",
"hex": "#a2217a"
},
{
"name": "PANTONE 2425 CP",
"label": "2425",
"hex": "#892464"
},
{
"name": "PANTONE 243 CP",
"label": "243",
"hex": "#f0c3db"
},
{
"name": "PANTONE 244 CP",
"label": "244",
"hex": "#e3a6ca"
},
{
"name": "PANTONE 245 CP",
"label": "245",
"hex": "#d58bb9"
},
{
"name": "PANTONE 246 CP",
"label": "246",
"hex": "#b73f8c"
},
{
"name": "PANTONE 247 CP",
"label": "247",
"hex": "#af2f84"
},
{
"name": "PANTONE 248 CP",
"label": "248",
"hex": "#a2237f"
},
{
"name": "PANTONE 249 CP",
"label": "249",
"hex": "#812d64"
},
{
"name": "PANTONE 7646 CP",
"label": "7646",
"hex": "#b77992"
},
{
"name": "PANTONE 7647 CP",
"label": "7647",
"hex": "#b7417d"
},
{
"name": "PANTONE 7648 CP",
"label": "7648",
"hex": "#ad1971"
},
{
"name": "PANTONE 7649 CP",
"label": "7649",
"hex": "#9d1e6f"
},
{
"name": "PANTONE 7650 CP",
"label": "7650",
"hex": "#7e245f"
},
{
"name": "PANTONE 7651 CP",
"label": "7651",
"hex": "#6f2c5d"
},
{
"name": "PANTONE 7652 CP",
"label": "7652",
"hex": "#6c2c5b"
},
{
"name": "PANTONE 250 CP",
"label": "250",
"hex": "#ebc9e0"
},
{
"name": "PANTONE 251 CP",
"label": "251",
"hex": "#d5a7cb"
},
{
"name": "PANTONE 252 CP",
"label": "252",
"hex": "#c06fa8"
},
{
"name": "PANTONE Purple CP",
"label": "purple",
"hex": "#a73c8a"
},
{
"name": "PANTONE 253 CP",
"label": "253",
"hex": "#a43a89"
},
{
"name": "PANTONE 254 CP",
"label": "254",
"hex": "#993084"
},
{
"name": "PANTONE 255 CP",
"label": "255",
"hex": "#792f6a"
},
{
"name": "PANTONE 517 CP",
"label": "517",
"hex": "#f5d1e4"
},
{
"name": "PANTONE 516 CP",
"label": "516",
"hex": "#f0c5dd"
},
{
"name": "PANTONE 515 CP",
"label": "515",
"hex": "#e6adce"
},
{
"name": "PANTONE 514 CP",
"label": "514",
"hex": "#d58ebb"
},
{
"name": "PANTONE 513 CP",
"label": "513",
"hex": "#8f2c81"
},
{
"name": "PANTONE 512 CP",
"label": "512",
"hex": "#7e2b71"
},
{
"name": "PANTONE 511 CP",
"label": "511",
"hex": "#5b254b"
},
{
"name": "PANTONE 7436 CP",
"label": "7436",
"hex": "#f8e5f0"
},
{
"name": "PANTONE 7437 CP",
"label": "7437",
"hex": "#dcb8d6"
},
{
"name": "PANTONE 7438 CP",
"label": "7438",
"hex": "#d39ec6"
},
{
"name": "PANTONE 7439 CP",
"label": "7439",
"hex": "#c18fbd"
},
{
"name": "PANTONE 7440 CP",
"label": "7440",
"hex": "#b07bb1"
},
{
"name": "PANTONE 7441 CP",
"label": "7441",
"hex": "#a164a2"
},
{
"name": "PANTONE 7442 CP",
"label": "7442",
"hex": "#85448e"
},
{
"name": "PANTONE 2562 CP",
"label": "2562",
"hex": "#d3b5d5"
},
{
"name": "PANTONE 2572 CP",
"label": "2572",
"hex": "#bd89b9"
},
{
"name": "PANTONE 2582 CP",
"label": "2582",
"hex": "#995196"
},
{
"name": "PANTONE 2592 CP",
"label": "2592",
"hex": "#853f8b"
},
{
"name": "PANTONE 2602 CP",
"label": "2602",
"hex": "#772f81"
},
{
"name": "PANTONE 2612 CP",
"label": "2612",
"hex": "#702f7e"
},
{
"name": "PANTONE 2622 CP",
"label": "2622",
"hex": "#5a295e"
},
{
"name": "PANTONE 7653 CP",
"label": "7653",
"hex": "#a598a5"
},
{
"name": "PANTONE 7654 CP",
"label": "7654",
"hex": "#b486ad"
},
{
"name": "PANTONE 7655 CP",
"label": "7655",
"hex": "#b562a0"
},
{
"name": "PANTONE 7656 CP",
"label": "7656",
"hex": "#9a3d87"
},
{
"name": "PANTONE 7657 CP",
"label": "7657",
"hex": "#752d67"
},
{
"name": "PANTONE 7658 CP",
"label": "7658",
"hex": "#6d325e"
},
{
"name": "PANTONE 7659 CP",
"label": "7659",
"hex": "#623755"
},
{
"name": "PANTONE 524 CP",
"label": "524",
"hex": "#e6d0e5"
},
{
"name": "PANTONE 523 CP",
"label": "523",
"hex": "#d8bad8"
},
{
"name": "PANTONE 522 CP",
"label": "522",
"hex": "#c8a1c9"
},
{
"name": "PANTONE 521 CP",
"label": "521",
"hex": "#b384b7"
},
{
"name": "PANTONE 520 CP",
"label": "520",
"hex": "#683576"
},
{
"name": "PANTONE 519 CP",
"label": "519",
"hex": "#592f5f"
},
{
"name": "PANTONE 518 CP",
"label": "518",
"hex": "#502f48"
},
{
"name": "PANTONE 5245 CP",
"label": "5245",
"hex": "#eee3e7"
},
{
"name": "PANTONE 5235 CP",
"label": "5235",
"hex": "#e3d0da"
},
{
"name": "PANTONE 5225 CP",
"label": "5225",
"hex": "#d2b9c8"
},
{
"name": "PANTONE 5215 CP",
"label": "5215",
"hex": "#b796ab"
},
{
"name": "PANTONE 5205 CP",
"label": "5205",
"hex": "#835b75"
},
{
"name": "PANTONE 5195 CP",
"label": "5195",
"hex": "#5f3b52"
},
{
"name": "PANTONE 5185 CP",
"label": "5185",
"hex": "#462d3c"
},
{
"name": "PANTONE 5175 CP",
"label": "5175",
"hex": "#ecdbe6"
},
{
"name": "PANTONE 5165 CP",
"label": "5165",
"hex": "#e7d5e3"
},
{
"name": "PANTONE 5155 CP",
"label": "5155",
"hex": "#d2b5cd"
},
{
"name": "PANTONE 5145 CP",
"label": "5145",
"hex": "#a87ea0"
},
{
"name": "PANTONE 5135 CP",
"label": "5135",
"hex": "#89547a"
},
{
"name": "PANTONE 5125 CP",
"label": "5125",
"hex": "#6c385c"
},
{
"name": "PANTONE 5115 CP",
"label": "5115",
"hex": "#4d293f"
},
{
"name": "PANTONE 531 CP",
"label": "531",
"hex": "#e8cfe4"
},
{
"name": "PANTONE 530 CP",
"label": "530",
"hex": "#dbbbd8"
},
{
"name": "PANTONE 529 CP",
"label": "529",
"hex": "#c99fc8"
},
{
"name": "PANTONE 528 CP",
"label": "528",
"hex": "#b280b4"
},
{
"name": "PANTONE 527 CP",
"label": "527",
"hex": "#703383"
},
{
"name": "PANTONE 526 CP",
"label": "526",
"hex": "#683282"
},
{
"name": "PANTONE 525 CP",
"label": "525",
"hex": "#51295a"
},
{
"name": "PANTONE 256 CP",
"label": "256",
"hex": "#e8d3e6"
},
{
"name": "PANTONE 257 CP",
"label": "257",
"hex": "#d4b3d4"
},
{
"name": "PANTONE 258 CP",
"label": "258",
"hex": "#935397"
},
{
"name": "PANTONE 259 CP",
"label": "259",
"hex": "#70307b"
},
{
"name": "PANTONE 260 CP",
"label": "260",
"hex": "#622c67"
},
{
"name": "PANTONE 261 CP",
"label": "261",
"hex": "#5b2858"
},
{
"name": "PANTONE 262 CP",
"label": "262",
"hex": "#562d51"
},
{
"name": "PANTONE 2563 CP",
"label": "2563",
"hex": "#ccacd0"
},
{
"name": "PANTONE 2573 CP",
"label": "2573",
"hex": "#b28cbc"
},
{
"name": "PANTONE 2583 CP",
"label": "2583",
"hex": "#9b60a0"
},
{
"name": "PANTONE 2593 CP",
"label": "2593",
"hex": "#753c89"
},
{
"name": "PANTONE 2603 CP",
"label": "2603",
"hex": "#683381"
},
{
"name": "PANTONE 2613 CP",
"label": "2613",
"hex": "#5f3377"
},
{
"name": "PANTONE 2623 CP",
"label": "2623",
"hex": "#552f69"
},
{
"name": "PANTONE 7660 CP",
"label": "7660",
"hex": "#afa5b9"
},
{
"name": "PANTONE 7661 CP",
"label": "7661",
"hex": "#9a77a2"
},
{
"name": "PANTONE 7662 CP",
"label": "7662",
"hex": "#814489"
},
{
"name": "PANTONE 7663 CP",
"label": "7663",
"hex": "#6a307c"
},
{
"name": "PANTONE 7664 CP",
"label": "7664",
"hex": "#60317a"
},
{
"name": "PANTONE 7665 CP",
"label": "7665",
"hex": "#5f3b73"
},
{
"name": "PANTONE 7666 CP",
"label": "7666",
"hex": "#605064"
},
{
"name": "PANTONE 2567 CP",
"label": "2567",
"hex": "#be9dc7"
},
{
"name": "PANTONE 2577 CP",
"label": "2577",
"hex": "#a786b9"
},
{
"name": "PANTONE 2587 CP",
"label": "2587",
"hex": "#84579a"
},
{
"name": "PANTONE 2597 CP",
"label": "2597",
"hex": "#593684"
},
{
"name": "PANTONE 2607 CP",
"label": "2607",
"hex": "#523683"
},
{
"name": "PANTONE 2617 CP",
"label": "2617",
"hex": "#4c347b"
},
{
"name": "PANTONE 2627 CP",
"label": "2627",
"hex": "#3f2e61"
},
{
"name": "PANTONE 263 CP",
"label": "263",
"hex": "#e7dbeb"
},
{
"name": "PANTONE 264 CP",
"label": "264",
"hex": "#c4aed2"
},
{
"name": "PANTONE 265 CP",
"label": "265",
"hex": "#8f6ba8"
},
{
"name": "PANTONE 266 CP",
"label": "266",
"hex": "#5f418c"
},
{
"name": "PANTONE 267 CP",
"label": "267",
"hex": "#553986"
},
{
"name": "PANTONE 268 CP",
"label": "268",
"hex": "#4f357c"
},
{
"name": "PANTONE 269 CP",
"label": "269",
"hex": "#4c316b"
},
{
"name": "PANTONE 2635 CP",
"label": "2635",
"hex": "#c9bcdb"
},
{
"name": "PANTONE 2645 CP",
"label": "2645",
"hex": "#a699c6"
},
{
"name": "PANTONE 2655 CP",
"label": "2655",
"hex": "#8973ae"
},
{
"name": "PANTONE 2665 CP",
"label": "2665",
"hex": "#68559a"
},
{
"name": "PANTONE Violet CP",
"label": "violet",
"hex": "#443785"
},
{
"name": "PANTONE 2685 CP",
"label": "2685",
"hex": "#41367f"
},
{
"name": "PANTONE 2695 CP",
"label": "2695",
"hex": "#31294e"
},
{
"name": "PANTONE 270 CP",
"label": "270",
"hex": "#bec0df"
},
{
"name": "PANTONE 271 CP",
"label": "271",
"hex": "#9194c5"
},
{
"name": "PANTONE 272 CP",
"label": "272",
"hex": "#7679b4"
},
{
"name": "PANTONE 273 CP",
"label": "273",
"hex": "#253374"
},
{
"name": "PANTONE 274 CP",
"label": "274",
"hex": "#253062"
},
{
"name": "PANTONE 275 CP",
"label": "275",
"hex": "#262b52"
},
{
"name": "PANTONE 276 CP",
"label": "276",
"hex": "#26243a"
},
{
"name": "PANTONE 2705 CP",
"label": "2705",
"hex": "#a5a6d0"
},
{
"name": "PANTONE 2715 CP",
"label": "2715",
"hex": "#8282b9"
},
{
"name": "PANTONE 2725 CP",
"label": "2725",
"hex": "#5a549a"
},
{
"name": "PANTONE 2735 CP",
"label": "2735",
"hex": "#313682"
},
{
"name": "PANTONE 2745 CP",
"label": "2745",
"hex": "#2e3477"
},
{
"name": "PANTONE 2755 CP",
"label": "2755",
"hex": "#2c316d"
},
{
"name": "PANTONE 2765 CP",
"label": "2765",
"hex": "#262b50"
},
{
"name": "PANTONE 7667 CP",
"label": "7667",
"hex": "#6c85aa"
},
{
"name": "PANTONE 7668 CP",
"label": "7668",
"hex": "#6776aa"
},
{
"name": "PANTONE 7669 CP",
"label": "7669",
"hex": "#5b63a4"
},
{
"name": "PANTONE 7670 CP",
"label": "7670",
"hex": "#4f569c"
},
{
"name": "PANTONE 7671 CP",
"label": "7671",
"hex": "#4a4b91"
},
{
"name": "PANTONE 7672 CP",
"label": "7672",
"hex": "#45478d"
},
{
"name": "PANTONE 7673 CP",
"label": "7673",
"hex": "#4d568c"
},
{
"name": "PANTONE 7443 CP",
"label": "7443",
"hex": "#e9e9f3"
},
{
"name": "PANTONE 7444 CP",
"label": "7444",
"hex": "#c2c7e3"
},
{
"name": "PANTONE 7445 CP",
"label": "7445",
"hex": "#aaaad0"
},
{
"name": "PANTONE 7446 CP",
"label": "7446",
"hex": "#9090c2"
},
{
"name": "PANTONE 7447 CP",
"label": "7447",
"hex": "#53417c"
},
{
"name": "PANTONE 7448 CP",
"label": "7448",
"hex": "#46354d"
},
{
"name": "PANTONE 7449 CP",
"label": "7449",
"hex": "#382332"
},
{
"name": "PANTONE 7674 CP",
"label": "7674",
"hex": "#8f98c3"
},
{
"name": "PANTONE 7675 CP",
"label": "7675",
"hex": "#8489b8"
},
{
"name": "PANTONE 7676 CP",
"label": "7676",
"hex": "#7a6ba6"
},
{
"name": "PANTONE 7677 CP",
"label": "7677",
"hex": "#6f5298"
},
{
"name": "PANTONE 7678 CP",
"label": "7678",
"hex": "#624791"
},
{
"name": "PANTONE 7679 CP",
"label": "7679",
"hex": "#493987"
},
{
"name": "PANTONE 7680 CP",
"label": "7680",
"hex": "#47357f"
},
{
"name": "PANTONE 663 CP",
"label": "663",
"hex": "#f4f0f5"
},
{
"name": "PANTONE 664 CP",
"label": "664",
"hex": "#ede9f1"
},
{
"name": "PANTONE 665 CP",
"label": "665",
"hex": "#d7cfe5"
},
{
"name": "PANTONE 666 CP",
"label": "666",
"hex": "#a89ec4"
},
{
"name": "PANTONE 667 CP",
"label": "667",
"hex": "#776a9c"
},
{
"name": "PANTONE 668 CP",
"label": "668",
"hex": "#5a487d"
},
{
"name": "PANTONE 669 CP",
"label": "669",
"hex": "#382e58"
},
{
"name": "PANTONE 5315 CP",
"label": "5315",
"hex": "#e2e5ee"
},
{
"name": "PANTONE 5305 CP",
"label": "5305",
"hex": "#cecfe0"
},
{
"name": "PANTONE 5295 CP",
"label": "5295",
"hex": "#b8bbd2"
},
{
"name": "PANTONE 5285 CP",
"label": "5285",
"hex": "#8d8caf"
},
{
"name": "PANTONE 5275 CP",
"label": "5275",
"hex": "#4a4d7c"
},
{
"name": "PANTONE 5265 CP",
"label": "5265",
"hex": "#363862"
},
{
"name": "PANTONE 5255 CP",
"label": "5255",
"hex": "#29273f"
},
{
"name": "PANTONE 538 CP",
"label": "538",
"hex": "#dce8f1"
},
{
"name": "PANTONE 537 CP",
"label": "537",
"hex": "#ccddeb"
},
{
"name": "PANTONE 536 CP",
"label": "536",
"hex": "#a9bfd8"
},
{
"name": "PANTONE 535 CP",
"label": "535",
"hex": "#94abcb"
},
{
"name": "PANTONE 534 CP",
"label": "534",
"hex": "#1e3e6a"
},
{
"name": "PANTONE 533 CP",
"label": "533",
"hex": "#20334d"
},
{
"name": "PANTONE 532 CP",
"label": "532",
"hex": "#272b36"
},
{
"name": "PANTONE 7541 CP",
"label": "7541",
"hex": "#edf4f4"
},
{
"name": "PANTONE 7542 CP",
"label": "7542",
"hex": "#b9cfd4"
},
{
"name": "PANTONE 7543 CP",
"label": "7543",
"hex": "#abbac2"
},
{
"name": "PANTONE 7544 CP",
"label": "7544",
"hex": "#8699a4"
},
{
"name": "PANTONE 7545 CP",
"label": "7545",
"hex": "#4b606f"
},
{
"name": "PANTONE 7546 CP",
"label": "7546",
"hex": "#324655"
},
{
"name": "PANTONE 7547 CP",
"label": "7547",
"hex": "#1f2934"
},
{
"name": "PANTONE 552 CP",
"label": "552",
"hex": "#c9e2e8"
},
{
"name": "PANTONE 551 CP",
"label": "551",
"hex": "#a8d0dc"
},
{
"name": "PANTONE 550 CP",
"label": "550",
"hex": "#95c4d6"
},
{
"name": "PANTONE 549 CP",
"label": "549",
"hex": "#61a4ba"
},
{
"name": "PANTONE 548 CP",
"label": "548",
"hex": "#00414c"
},
{
"name": "PANTONE 547 CP",
"label": "547",
"hex": "#06373f"
},
{
"name": "PANTONE 546 CP",
"label": "546",
"hex": "#113036"
},
{
"name": "PANTONE 5455 CP",
"label": "5455",
"hex": "#d5e4e8"
},
{
"name": "PANTONE 5445 CP",
"label": "5445",
"hex": "#c6d9e2"
},
{
"name": "PANTONE 5435 CP",
"label": "5435",
"hex": "#acc8d6"
},
{
"name": "PANTONE 5425 CP",
"label": "5425",
"hex": "#7e9fb3"
},
{
"name": "PANTONE 5415 CP",
"label": "5415",
"hex": "#5d8299"
},
{
"name": "PANTONE 5405 CP",
"label": "5405",
"hex": "#436981"
},
{
"name": "PANTONE 5395 CP",
"label": "5395",
"hex": "#1d272d"
},
{
"name": "PANTONE 642 CP",
"label": "642",
"hex": "#e2eff6"
},
{
"name": "PANTONE 643 CP",
"label": "643",
"hex": "#d1e6f2"
},
{
"name": "PANTONE 644 CP",
"label": "644",
"hex": "#97c4de"
},
{
"name": "PANTONE 645 CP",
"label": "645",
"hex": "#6fa7ce"
},
{
"name": "PANTONE 646 CP",
"label": "646",
"hex": "#398ab9"
},
{
"name": "PANTONE 647 CP",
"label": "647",
"hex": "#00598c"
},
{
"name": "PANTONE 648 CP",
"label": "648",
"hex": "#11395d"
},
{
"name": "PANTONE 649 CP",
"label": "649",
"hex": "#e9f1f8"
},
{
"name": "PANTONE 650 CP",
"label": "650",
"hex": "#d5e4f0"
},
{
"name": "PANTONE 651 CP",
"label": "651",
"hex": "#a6c7e3"
},
{
"name": "PANTONE 652 CP",
"label": "652",
"hex": "#6da2cd"
},
{
"name": "PANTONE 653 CP",
"label": "653",
"hex": "#005d96"
},
{
"name": "PANTONE 654 CP",
"label": "654",
"hex": "#093e66"
},
{
"name": "PANTONE 655 CP",
"label": "655",
"hex": "#1b3455"
},
{
"name": "PANTONE 656 CP",
"label": "656",
"hex": "#e9f3fb"
},
{
"name": "PANTONE 657 CP",
"label": "657",
"hex": "#cfe3f4"
},
{
"name": "PANTONE 658 CP",
"label": "658",
"hex": "#abcfeb"
},
{
"name": "PANTONE 659 CP",
"label": "659",
"hex": "#6ea6d5"
},
{
"name": "PANTONE 660 CP",
"label": "660",
"hex": "#0075b7"
},
{
"name": "PANTONE 661 CP",
"label": "661",
"hex": "#004f96"
},
{
"name": "PANTONE 662 CP",
"label": "662",
"hex": "#173e7f"
},
{
"name": "PANTONE 7450 CP",
"label": "7450",
"hex": "#c7d6ec"
},
{
"name": "PANTONE 7451 CP",
"label": "7451",
"hex": "#94b6dd"
},
{
"name": "PANTONE 7452 CP",
"label": "7452",
"hex": "#7f9bcc"
},
{
"name": "PANTONE 7453 CP",
"label": "7453",
"hex": "#80add8"
},
{
"name": "PANTONE 7454 CP",
"label": "7454",
"hex": "#5a9ac1"
},
{
"name": "PANTONE 7455 CP",
"label": "7455",
"hex": "#215fa5"
},
{
"name": "PANTONE 7456 CP",
"label": "7456",
"hex": "#5676b3"
},
{
"name": "PANTONE 2706 CP",
"label": "2706",
"hex": "#d6dff0"
},
{
"name": "PANTONE 2716 CP",
"label": "2716",
"hex": "#a5b2d8"
},
{
"name": "PANTONE 2726 CP",
"label": "2726",
"hex": "#495ca1"
},
{
"name": "PANTONE 2736 CP",
"label": "2736",
"hex": "#2e3c89"
},
{
"name": "PANTONE 2746 CP",
"label": "2746",
"hex": "#263987"
},
{
"name": "PANTONE 2756 CP",
"label": "2756",
"hex": "#24367b"
},
{
"name": "PANTONE 2766 CP",
"label": "2766",
"hex": "#262a4f"
},
{
"name": "PANTONE 2708 CP",
"label": "2708",
"hex": "#bbd2eb"
},
{
"name": "PANTONE 2718 CP",
"label": "2718",
"hex": "#6588c0"
},
{
"name": "PANTONE 2728 CP",
"label": "2728",
"hex": "#265ca3"
},
{
"name": "PANTONE 2738 CP",
"label": "2738",
"hex": "#1e3f8b"
},
{
"name": "PANTONE 2748 CP",
"label": "2748",
"hex": "#213a80"
},
{
"name": "PANTONE 2758 CP",
"label": "2758",
"hex": "#223366"
},
{
"name": "PANTONE 2768 CP",
"label": "2768",
"hex": "#232a44"
},
{
"name": "PANTONE 2707 CP",
"label": "2707",
"hex": "#d3e5f4"
},
{
"name": "PANTONE 2717 CP",
"label": "2717",
"hex": "#b2cce8"
},
{
"name": "PANTONE 2727 CP",
"label": "2727",
"hex": "#5682bd"
},
{
"name": "PANTONE Blue 072 CP",
"label": "blue-072",
"hex": "#223c87"
},
{
"name": "PANTONE 2747 CP",
"label": "2747",
"hex": "#21397d"
},
{
"name": "PANTONE 2757 CP",
"label": "2757",
"hex": "#223263"
},
{
"name": "PANTONE 2767 CP",
"label": "2767",
"hex": "#23283f"
},
{
"name": "PANTONE 277 CP",
"label": "277",
"hex": "#b0d4ee"
},
{
"name": "PANTONE 278 CP",
"label": "278",
"hex": "#95c4e6"
},
{
"name": "PANTONE 279 CP",
"label": "279",
"hex": "#5396cc"
},
{
"name": "PANTONE Reflex Blue CP",
"label": "reflex-blue",
"hex": "#19428e"
},
{
"name": "PANTONE 280 CP",
"label": "280",
"hex": "#163f7a"
},
{
"name": "PANTONE 281 CP",
"label": "281",
"hex": "#193a6d"
},
{
"name": "PANTONE 282 CP",
"label": "282",
"hex": "#222b47"
},
{
"name": "PANTONE 283 CP",
"label": "283",
"hex": "#9dceec"
},
{
"name": "PANTONE 284 CP",
"label": "284",
"hex": "#68b4df"
},
{
"name": "PANTONE 285 CP",
"label": "285",
"hex": "#0077b9"
},
{
"name": "PANTONE 286 CP",
"label": "286",
"hex": "#00519b"
},
{
"name": "PANTONE 287 CP",
"label": "287",
"hex": "#004988"
},
{
"name": "PANTONE 288 CP",
"label": "288",
"hex": "#0f3f74"
},
{
"name": "PANTONE 289 CP",
"label": "289",
"hex": "#1c304a"
},
{
"name": "PANTONE 7681 CP",
"label": "7681",
"hex": "#9fb9db"
},
{
"name": "PANTONE 7682 CP",
"label": "7682",
"hex": "#6695c8"
},
{
"name": "PANTONE 7683 CP",
"label": "7683",
"hex": "#2d71b2"
},
{
"name": "PANTONE 7684 CP",
"label": "7684",
"hex": "#1b62a7"
},
{
"name": "PANTONE 7685 CP",
"label": "7685",
"hex": "#0059a1"
},
{
"name": "PANTONE 7686 CP",
"label": "7686",
"hex": "#004f93"
},
{
"name": "PANTONE 7687 CP",
"label": "7687",
"hex": "#004687"
},
{
"name": "PANTONE 545 CP",
"label": "545",
"hex": "#cfe8f6"
},
{
"name": "PANTONE 544 CP",
"label": "544",
"hex": "#c1e0f1"
},
{
"name": "PANTONE 543 CP",
"label": "543",
"hex": "#a9d0eb"
},
{
"name": "PANTONE 542 CP",
"label": "542",
"hex": "#63acd6"
},
{
"name": "PANTONE 541 CP",
"label": "541",
"hex": "#004870"
},
{
"name": "PANTONE 540 CP",
"label": "540",
"hex": "#053b56"
},
{
"name": "PANTONE 539 CP",
"label": "539",
"hex": "#192e3e"
},
{
"name": "PANTONE 290 CP",
"label": "290",
"hex": "#cdebf7"
},
{
"name": "PANTONE 291 CP",
"label": "291",
"hex": "#a7d8f2"
},
{
"name": "PANTONE 292 CP",
"label": "292",
"hex": "#65bbe5"
},
{
"name": "PANTONE 293 CP",
"label": "293",
"hex": "#00569d"
},
{
"name": "PANTONE 294 CP",
"label": "294",
"hex": "#00487c"
},
{
"name": "PANTONE 295 CP",
"label": "295",
"hex": "#0c3c61"
},
{
"name": "PANTONE 296 CP",
"label": "296",
"hex": "#1e2833"
},
{
"name": "PANTONE 2905 CP",
"label": "2905",
"hex": "#90d4f0"
},
{
"name": "PANTONE 2915 CP",
"label": "2915",
"hex": "#5ebde6"
},
{
"name": "PANTONE 2925 CP",
"label": "2925",
"hex": "#0099d4"
},
{
"name": "PANTONE 2935 CP",
"label": "2935",
"hex": "#006cb3"
},
{
"name": "PANTONE 2945 CP",
"label": "2945",
"hex": "#00609d"
},
{
"name": "PANTONE 2955 CP",
"label": "2955",
"hex": "#004266"
},
{
"name": "PANTONE 2965 CP",
"label": "2965",
"hex": "#183043"
},
{
"name": "PANTONE 297 CP",
"label": "297",
"hex": "#79d0ef"
},
{
"name": "PANTONE 298 CP",
"label": "298",
"hex": "#2dbeea"
},
{
"name": "PANTONE 299 CP",
"label": "299",
"hex": "#00a6df"
},
{
"name": "PANTONE 300 CP",
"label": "300",
"hex": "#0070b5"
},
{
"name": "PANTONE 301 CP",
"label": "301",
"hex": "#005f98"
},
{
"name": "PANTONE 302 CP",
"label": "302",
"hex": "#004664"
},
{
"name": "PANTONE 303 CP",
"label": "303",
"hex": "#0f3240"
},
{
"name": "PANTONE 7688 CP",
"label": "7688",
"hex": "#3ea8d5"
},
{
"name": "PANTONE 7689 CP",
"label": "7689",
"hex": "#049aca"
},
{
"name": "PANTONE 7690 CP",
"label": "7690",
"hex": "#007bb2"
},
{
"name": "PANTONE 7691 CP",
"label": "7691",
"hex": "#005f95"
},
{
"name": "PANTONE 7692 CP",
"label": "7692",
"hex": "#005280"
},
{
"name": "PANTONE 7693 CP",
"label": "7693",
"hex": "#004870"
},
{
"name": "PANTONE 7694 CP",
"label": "7694",
"hex": "#00456a"
},
{
"name": "PANTONE 2975 CP",
"label": "2975",
"hex": "#b2e1ee"
},
{
"name": "PANTONE 2985 CP",
"label": "2985",
"hex": "#59c7e9"
},
{
"name": "PANTONE 2995 CP",
"label": "2995",
"hex": "#00afe5"
},
{
"name": "PANTONE 3005 CP",
"label": "3005",
"hex": "#0083c7"
},
{
"name": "PANTONE 3015 CP",
"label": "3015",
"hex": "#006ea5"
},
{
"name": "PANTONE 3025 CP",
"label": "3025",
"hex": "#005372"
},
{
"name": "PANTONE 3035 CP",
"label": "3035",
"hex": "#003e4e"
},
{
"name": "PANTONE 7695 CP",
"label": "7695",
"hex": "#93c1d4"
},
{
"name": "PANTONE 7696 CP",
"label": "7696",
"hex": "#61a3ba"
},
{
"name": "PANTONE 7697 CP",
"label": "7697",
"hex": "#358fad"
},
{
"name": "PANTONE 7698 CP",
"label": "7698",
"hex": "#33728b"
},
{
"name": "PANTONE 7699 CP",
"label": "7699",
"hex": "#1e6581"
},
{
"name": "PANTONE 7700 CP",
"label": "7700",
"hex": "#005e7e"
},
{
"name": "PANTONE 7701 CP",
"label": "7701",
"hex": "#005f80"
},
{
"name": "PANTONE 7457 CP",
"label": "7457",
"hex": "#d9eff2"
},
{
"name": "PANTONE 7458 CP",
"label": "7458",
"hex": "#73bdd4"
},
{
"name": "PANTONE 7459 CP",
"label": "7459",
"hex": "#16a0c2"
},
{
"name": "PANTONE 7460 CP",
"label": "7460",
"hex": "#0091ca"
},
{
"name": "PANTONE 7461 CP",
"label": "7461",
"hex": "#0089c8"
},
{
"name": "PANTONE 7462 CP",
"label": "7462",
"hex": "#005b8c"
},
{
"name": "PANTONE 7463 CP",
"label": "7463",
"hex": "#103752"
},
{
"name": "PANTONE 304 CP",
"label": "304",
"hex": "#b2e0ed"
},
{
"name": "PANTONE 305 CP",
"label": "305",
"hex": "#73cde7"
},
{
"name": "PANTONE 306 CP",
"label": "306",
"hex": "#00b8e1"
},
{
"name": "PANTONE Process Blue CP",
"label": "process-blue",
"hex": "#0093d2"
},
{
"name": "PANTONE 307 CP",
"label": "307",
"hex": "#007cb3"
},
{
"name": "PANTONE 308 CP",
"label": "308",
"hex": "#005f81"
},
{
"name": "PANTONE 309 CP",
"label": "309",
"hex": "#003b47"
},
{
"name": "PANTONE 635 CP",
"label": "635",
"hex": "#bce4ec"
},
{
"name": "PANTONE 636 CP",
"label": "636",
"hex": "#a6dce9"
},
{
"name": "PANTONE 637 CP",
"label": "637",
"hex": "#52c4e1"
},
{
"name": "PANTONE 638 CP",
"label": "638",
"hex": "#00acd7"
},
{
"name": "PANTONE 639 CP",
"label": "639",
"hex": "#009bd1"
},
{
"name": "PANTONE 640 CP",
"label": "640",
"hex": "#0087bd"
},
{
"name": "PANTONE 641 CP",
"label": "641",
"hex": "#007ab4"
},
{
"name": "PANTONE 7702 CP",
"label": "7702",
"hex": "#2cb3d3"
},
{
"name": "PANTONE 7703 CP",
"label": "7703",
"hex": "#00a4c6"
},
{
"name": "PANTONE 7704 CP",
"label": "7704",
"hex": "#0088b1"
},
{
"name": "PANTONE 7705 CP",
"label": "7705",
"hex": "#006b93"
},
{
"name": "PANTONE 7706 CP",
"label": "7706",
"hex": "#006688"
},
{
"name": "PANTONE 7707 CP",
"label": "7707",
"hex": "#005c7a"
},
{
"name": "PANTONE 7708 CP",
"label": "7708",
"hex": "#005570"
},
{
"name": "PANTONE 628 CP",
"label": "628",
"hex": "#d5edee"
},
{
"name": "PANTONE 629 CP",
"label": "629",
"hex": "#aedee7"
},
{
"name": "PANTONE 630 CP",
"label": "630",
"hex": "#8bd3e2"
},
{
"name": "PANTONE 631 CP",
"label": "631",
"hex": "#00b7d5"
},
{
"name": "PANTONE 632 CP",
"label": "632",
"hex": "#009cc1"
},
{
"name": "PANTONE 633 CP",
"label": "633",
"hex": "#007da4"
},
{
"name": "PANTONE 634 CP",
"label": "634",
"hex": "#006b8e"
},
{
"name": "PANTONE 310 CP",
"label": "310",
"hex": "#8bd3e4"
},
{
"name": "PANTONE 311 CP",
"label": "311",
"hex": "#2fbed7"
},
{
"name": "PANTONE 312 CP",
"label": "312",
"hex": "#00aad4"
},
{
"name": "PANTONE 313 CP",
"label": "313",
"hex": "#009dcd"
},
{
"name": "PANTONE 314 CP",
"label": "314",
"hex": "#0089b0"
},
{
"name": "PANTONE 315 CP",
"label": "315",
"hex": "#006880"
},
{
"name": "PANTONE 316 CP",
"label": "316",
"hex": "#00464e"
},
{
"name": "PANTONE 3105 CP",
"label": "3105",
"hex": "#98d6e1"
},
{
"name": "PANTONE 3115 CP",
"label": "3115",
"hex": "#63c7d8"
},
{
"name": "PANTONE 3125 CP",
"label": "3125",
"hex": "#00adca"
},
{
"name": "PANTONE 3135 CP",
"label": "3135",
"hex": "#009ec2"
},
{
"name": "PANTONE 3145 CP",
"label": "3145",
"hex": "#008196"
},
{
"name": "PANTONE 3155 CP",
"label": "3155",
"hex": "#006675"
},
{
"name": "PANTONE 3165 CP",
"label": "3165",
"hex": "#004e58"
},
{
"name": "PANTONE 7709 CP",
"label": "7709",
"hex": "#53bbc8"
},
{
"name": "PANTONE 7710 CP",
"label": "7710",
"hex": "#00afc2"
},
{
"name": "PANTONE 7711 CP",
"label": "7711",
"hex": "#009bb1"
},
{
"name": "PANTONE 7712 CP",
"label": "7712",
"hex": "#00889d"
},
{
"name": "PANTONE 7713 CP",
"label": "7713",
"hex": "#008292"
},
{
"name": "PANTONE 7714 CP",
"label": "7714",
"hex": "#006f7a"
},
{
"name": "PANTONE 7715 CP",
"label": "7715",
"hex": "#006166"
},
{
"name": "PANTONE 317 CP",
"label": "317",
"hex": "#ceeae8"
},
{
"name": "PANTONE 318 CP",
"label": "318",
"hex": "#a4d9dd"
},
{
"name": "PANTONE 319 CP",
"label": "319",
"hex": "#66c5cb"
},
{
"name": "PANTONE 320 CP",
"label": "320",
"hex": "#009eaf"
},
{
"name": "PANTONE 321 CP",
"label": "321",
"hex": "#00909b"
},
{
"name": "PANTONE 322 CP",
"label": "322",
"hex": "#00747a"
},
{
"name": "PANTONE 323 CP",
"label": "323",
"hex": "#00595c"
},
{
"name": "PANTONE 7464 CP",
"label": "7464",
"hex": "#b2ded8"
},
{
"name": "PANTONE 7465 CP",
"label": "7465",
"hex": "#6ec4b2"
},
{
"name": "PANTONE 7466 CP",
"label": "7466",
"hex": "#00a9b2"
},
{
"name": "PANTONE 7467 CP",
"label": "7467",
"hex": "#00a0b2"
},
{
"name": "PANTONE 7468 CP",
"label": "7468",
"hex": "#007aa2"
},
{
"name": "PANTONE 7469 CP",
"label": "7469",
"hex": "#005e86"
},
{
"name": "PANTONE 7470 CP",
"label": "7470",
"hex": "#005b6e"
},
{
"name": "PANTONE 7471 CP",
"label": "7471",
"hex": "#addcd9"
},
{
"name": "PANTONE 7472 CP",
"label": "7472",
"hex": "#7ac9c3"
},
{
"name": "PANTONE 7473 CP",
"label": "7473",
"hex": "#1ca993"
},
{
"name": "PANTONE 7474 CP",
"label": "7474",
"hex": "#007b88"
},
{
"name": "PANTONE 7475 CP",
"label": "7475",
"hex": "#378185"
},
{
"name": "PANTONE 7476 CP",
"label": "7476",
"hex": "#005057"
},
{
"name": "PANTONE 7477 CP",
"label": "7477",
"hex": "#0f4b5a"
},
{
"name": "PANTONE 5523 CP",
"label": "5523",
"hex": "#cee6e6"
},
{
"name": "PANTONE 5513 CP",
"label": "5513",
"hex": "#b9dbde"
},
{
"name": "PANTONE 5503 CP",
"label": "5503",
"hex": "#9bc9cd"
},
{
"name": "PANTONE 5493 CP",
"label": "5493",
"hex": "#80b6bd"
},
{
"name": "PANTONE 5483 CP",
"label": "5483",
"hex": "#469099"
},
{
"name": "PANTONE 5473 CP",
"label": "5473",
"hex": "#00616b"
},
{
"name": "PANTONE 5463 CP",
"label": "5463",
"hex": "#152d31"
},
{
"name": "PANTONE 7716 CP",
"label": "7716",
"hex": "#009e99"
},
{
"name": "PANTONE 7717 CP",
"label": "7717",
"hex": "#008a83"
},
{
"name": "PANTONE 7718 CP",
"label": "7718",
"hex": "#00726d"
},
{
"name": "PANTONE 7719 CP",
"label": "7719",
"hex": "#006861"
},
{
"name": "PANTONE 7720 CP",
"label": "7720",
"hex": "#00605a"
},
{
"name": "PANTONE 7721 CP",
"label": "7721",
"hex": "#005a56"
},
{
"name": "PANTONE 7722 CP",
"label": "7722",
"hex": "#00504c"
},
{
"name": "PANTONE 324 CP",
"label": "324",
"hex": "#b2dedf"
},
{
"name": "PANTONE 325 CP",
"label": "325",
"hex": "#7dcbca"
},
{
"name": "PANTONE 326 CP",
"label": "326",
"hex": "#00ada7"
},
{
"name": "PANTONE 327 CP",
"label": "327",
"hex": "#008973"
},
{
"name": "PANTONE 328 CP",
"label": "328",
"hex": "#006c5c"
},
{
"name": "PANTONE 329 CP",
"label": "329",
"hex": "#005f53"
},
{
"name": "PANTONE 330 CP",
"label": "330",
"hex": "#024f45"
},
{
"name": "PANTONE 3242 CP",
"label": "3242",
"hex": "#9ad5d2"
},
{
"name": "PANTONE 3252 CP",
"label": "3252",
"hex": "#8bcfcb"
},
{
"name": "PANTONE 3262 CP",
"label": "3262",
"hex": "#00b2aa"
},
{
"name": "PANTONE 3272 CP",
"label": "3272",
"hex": "#00a095"
},
{
"name": "PANTONE 3282 CP",
"label": "3282",
"hex": "#008e7e"
},
{
"name": "PANTONE 3292 CP",
"label": "3292",
"hex": "#005e4d"
},
{
"name": "PANTONE 3302 CP",
"label": "3302",
"hex": "#094b3e"
},
{
"name": "PANTONE 3245 CP",
"label": "3245",
"hex": "#a0d6cc"
},
{
"name": "PANTONE 3255 CP",
"label": "3255",
"hex": "#8fd0c8"
},
{
"name": "PANTONE 3265 CP",
"label": "3265",
"hex": "#4dbcab"
},
{
"name": "PANTONE 3275 CP",
"label": "3275",
"hex": "#00a38e"
},
{
"name": "PANTONE 3285 CP",
"label": "3285",
"hex": "#009a81"
},
{
"name": "PANTONE 3295 CP",
"label": "3295",
"hex": "#007b62"
},
{
"name": "PANTONE 3305 CP",
"label": "3305",
"hex": "#054a3b"
},
{
"name": "PANTONE 3248 CP",
"label": "3248",
"hex": "#8ed1ce"
},
{
"name": "PANTONE 3258 CP",
"label": "3258",
"hex": "#69c4bc"
},
{
"name": "PANTONE 3268 CP",
"label": "3268",
"hex": "#00a68d"
},
{
"name": "PANTONE 3278 CP",
"label": "3278",
"hex": "#009870"
},
{
"name": "PANTONE 3288 CP",
"label": "3288",
"hex": "#008a69"
},
{
"name": "PANTONE 3298 CP",
"label": "3298",
"hex": "#006e52"
},
{
"name": "PANTONE 3308 CP",
"label": "3308",
"hex": "#0a4335"
},
{
"name": "PANTONE 566 CP",
"label": "566",
"hex": "#ddefe6"
},
{
"name": "PANTONE 565 CP",
"label": "565",
"hex": "#bee2d9"
},
{
"name": "PANTONE 564 CP",
"label": "564",
"hex": "#9dd5cd"
},
{
"name": "PANTONE 563 CP",
"label": "563",
"hex": "#79c6bd"
},
{
"name": "PANTONE 562 CP",
"label": "562",
"hex": "#007668"
},
{
"name": "PANTONE 561 CP",
"label": "561",
"hex": "#115d50"
},
{
"name": "PANTONE 560 CP",
"label": "560",
"hex": "#233e34"
},
{
"name": "PANTONE 573 CP",
"label": "573",
"hex": "#d6ece2"
},
{
"name": "PANTONE 572 CP",
"label": "572",
"hex": "#c6e5da"
},
{
"name": "PANTONE 571 CP",
"label": "571",
"hex": "#a6d8ca"
},
{
"name": "PANTONE 570 CP",
"label": "570",
"hex": "#72c5b2"
},
{
"name": "PANTONE 569 CP",
"label": "569",
"hex": "#008b71"
},
{
"name": "PANTONE 568 CP",
"label": "568",
"hex": "#006a56"
},
{
"name": "PANTONE 567 CP",
"label": "567",
"hex": "#194337"
},
{
"name": "PANTONE 559 CP",
"label": "559",
"hex": "#bedac9"
},
{
"name": "PANTONE 558 CP",
"label": "558",
"hex": "#acd1bf"
},
{
"name": "PANTONE 557 CP",
"label": "557",
"hex": "#92bea5"
},
{
"name": "PANTONE 556 CP",
"label": "556",
"hex": "#75aa8b"
},
{
"name": "PANTONE 555 CP",
"label": "555",
"hex": "#226343"
},
{
"name": "PANTONE 554 CP",
"label": "554",
"hex": "#1b563c"
},
{
"name": "PANTONE 553 CP",
"label": "553",
"hex": "#214237"
},
{
"name": "PANTONE 5595 CP",
"label": "5595",
"hex": "#d0e0d6"
},
{
"name": "PANTONE 5585 CP",
"label": "5585",
"hex": "#c3d7cc"
},
{
"name": "PANTONE 5575 CP",
"label": "5575",
"hex": "#9fbbaf"
},
{
"name": "PANTONE 5565 CP",
"label": "5565",
"hex": "#83a194"
},
{
"name": "PANTONE 5555 CP",
"label": "5555",
"hex": "#678a7c"
},
{
"name": "PANTONE 5545 CP",
"label": "5545",
"hex": "#486d63"
},
{
"name": "PANTONE 5535 CP",
"label": "5535",
"hex": "#233931"
},
{
"name": "PANTONE 5665 CP",
"label": "5665",
"hex": "#d7e2d6"
},
{
"name": "PANTONE 5655 CP",
"label": "5655",
"hex": "#c8d6c8"
},
{
"name": "PANTONE 5645 CP",
"label": "5645",
"hex": "#b7c9bb"
},
{
"name": "PANTONE 5635 CP",
"label": "5635",
"hex": "#9cb09e"
},
{
"name": "PANTONE 5625 CP",
"label": "5625",
"hex": "#728774"
},
{
"name": "PANTONE 5615 CP",
"label": "5615",
"hex": "#566d58"
},
{
"name": "PANTONE 5605 CP",
"label": "5605",
"hex": "#203226"
},
{
"name": "PANTONE 5527 CP",
"label": "5527",
"hex": "#d9e3df"
},
{
"name": "PANTONE 5517 CP",
"label": "5517",
"hex": "#c6d6d1"
},
{
"name": "PANTONE 5507 CP",
"label": "5507",
"hex": "#acc2bd"
},
{
"name": "PANTONE 5497 CP",
"label": "5497",
"hex": "#849e9b"
},
{
"name": "PANTONE 5487 CP",
"label": "5487",
"hex": "#5a756f"
},
{
"name": "PANTONE 5477 CP",
"label": "5477",
"hex": "#375450"
},
{
"name": "PANTONE 5467 CP",
"label": "5467",
"hex": "#1c2f2b"
},
{
"name": "PANTONE 621 CP",
"label": "621",
"hex": "#e4eee3"
},
{
"name": "PANTONE 622 CP",
"label": "622",
"hex": "#c3dcd0"
},
{
"name": "PANTONE 623 CP",
"label": "623",
"hex": "#a2c6b9"
},
{
"name": "PANTONE 624 CP",
"label": "624",
"hex": "#7ea99b"
},
{
"name": "PANTONE 625 CP",
"label": "625",
"hex": "#4f8678"
},
{
"name": "PANTONE 626 CP",
"label": "626",
"hex": "#1d6052"
},
{
"name": "PANTONE 627 CP",
"label": "627",
"hex": "#16362e"
},
{
"name": "PANTONE 331 CP",
"label": "331",
"hex": "#c5e5df"
},
{
"name": "PANTONE 332 CP",
"label": "332",
"hex": "#b7dfd8"
},
{
"name": "PANTONE 333 CP",
"label": "333",
"hex": "#8ccec3"
},
{
"name": "PANTONE Green CP",
"label": "green",
"hex": "#009e7a"
},
{
"name": "PANTONE 334 CP",
"label": "334",
"hex": "#00986e"
},
{
"name": "PANTONE 335 CP",
"label": "335",
"hex": "#008362"
},
{
"name": "PANTONE 336 CP",
"label": "336",
"hex": "#00684e"
},
{
"name": "PANTONE 337 CP",
"label": "337",
"hex": "#a9d9d0"
},
{
"name": "PANTONE 338 CP",
"label": "338",
"hex": "#8acdbd"
},
{
"name": "PANTONE 339 CP",
"label": "339",
"hex": "#00a783"
},
{
"name": "PANTONE 340 CP",
"label": "340",
"hex": "#009658"
},
{
"name": "PANTONE 341 CP",
"label": "341",
"hex": "#007e4f"
},
{
"name": "PANTONE 342 CP",
"label": "342",
"hex": "#006a4a"
},
{
"name": "PANTONE 343 CP",
"label": "343",
"hex": "#015640"
},
{
"name": "PANTONE 7723 CP",
"label": "7723",
"hex": "#42ad87"
},
{
"name": "PANTONE 7724 CP",
"label": "7724",
"hex": "#009b6d"
},
{
"name": "PANTONE 7725 CP",
"label": "7725",
"hex": "#00894f"
},
{
"name": "PANTONE 7726 CP",
"label": "7726",
"hex": "#007841"
},
{
"name": "PANTONE 7727 CP",
"label": "7727",
"hex": "#006739"
},
{
"name": "PANTONE 7728 CP",
"label": "7728",
"hex": "#006244"
},
{
"name": "PANTONE 7729 CP",
"label": "7729",
"hex": "#00563d"
},
{
"name": "PANTONE 3375 CP",
"label": "3375",
"hex": "#b0dbcd"
},
{
"name": "PANTONE 3385 CP",
"label": "3385",
"hex": "#9ed4c4"
},
{
"name": "PANTONE 3395 CP",
"label": "3395",
"hex": "#51ba9a"
},
{
"name": "PANTONE 3405 CP",
"label": "3405",
"hex": "#00a272"
},
{
"name": "PANTONE 3415 CP",
"label": "3415",
"hex": "#007f4c"
},
{
"name": "PANTONE 3425 CP",
"label": "3425",
"hex": "#006640"
},
{
"name": "PANTONE 3435 CP",
"label": "3435",
"hex": "#064a33"
},
{
"name": "PANTONE 344 CP",
"label": "344",
"hex": "#bbdec2"
},
{
"name": "PANTONE 345 CP",
"label": "345",
"hex": "#a0d2ab"
},
{
"name": "PANTONE 346 CP",
"label": "346",
"hex": "#84c696"
},
{
"name": "PANTONE 347 CP",
"label": "347",
"hex": "#00993e"
},
{
"name": "PANTONE 348 CP",
"label": "348",
"hex": "#00893c"
},
{
"name": "PANTONE 349 CP",
"label": "349",
"hex": "#006c38"
},
{
"name": "PANTONE 350 CP",
"label": "350",
"hex": "#245339"
},
{
"name": "PANTONE 351 CP",
"label": "351",
"hex": "#c7e4d1"
},
{
"name": "PANTONE 352 CP",
"label": "352",
"hex": "#afd9c0"
},
{
"name": "PANTONE 353 CP",
"label": "353",
"hex": "#a5d4b6"
},
{
"name": "PANTONE 354 CP",
"label": "354",
"hex": "#00a448"
},
{
"name": "PANTONE 355 CP",
"label": "355",
"hex": "#009b3d"
},
{
"name": "PANTONE 356 CP",
"label": "356",
"hex": "#007f37"
},
{
"name": "PANTONE 357 CP",
"label": "357",
"hex": "#005331"
},
{
"name": "PANTONE 7478 CP",
"label": "7478",
"hex": "#c5e3cd"
},
{
"name": "PANTONE 7479 CP",
"label": "7479",
"hex": "#7cc287"
},
{
"name": "PANTONE 7480 CP",
"label": "7480",
"hex": "#2cad6d"
},
{
"name": "PANTONE 7481 CP",
"label": "7481",
"hex": "#00a553"
},
{
"name": "PANTONE 7482 CP",
"label": "7482",
"hex": "#009d48"
},
{
"name": "PANTONE 7483 CP",
"label": "7483",
"hex": "#1e5d39"
},
{
"name": "PANTONE 7484 CP",
"label": "7484",
"hex": "#00573d"
},
{
"name": "PANTONE 7730 CP",
"label": "7730",
"hex": "#4a9e61"
},
{
"name": "PANTONE 7731 CP",
"label": "7731",
"hex": "#1b8f45"
},
{
"name": "PANTONE 7732 CP",
"label": "7732",
"hex": "#007e3a"
},
{
"name": "PANTONE 7733 CP",
"label": "7733",
"hex": "#00703c"
},
{
"name": "PANTONE 7734 CP",
"label": "7734",
"hex": "#225d38"
},
{
"name": "PANTONE 7735 CP",
"label": "7735",
"hex": "#38563a"
},
{
"name": "PANTONE 7736 CP",
"label": "7736",
"hex": "#37523e"
},
{
"name": "PANTONE 7737 CP",
"label": "7737",
"hex": "#71ae32"
},
{
"name": "PANTONE 7738 CP",
"label": "7738",
"hex": "#3ea83a"
},
{
"name": "PANTONE 7739 CP",
"label": "7739",
"hex": "#24a141"
},
{
"name": "PANTONE 7740 CP",
"label": "7740",
"hex": "#35993d"
},
{
"name": "PANTONE 7741 CP",
"label": "7741",
"hex": "#328d34"
},
{
"name": "PANTONE 7742 CP",
"label": "7742",
"hex": "#3b742e"
},
{
"name": "PANTONE 7743 CP",
"label": "7743",
"hex": "#396d2d"
},
{
"name": "PANTONE 358 CP",
"label": "358",
"hex": "#b8daab"
},
{
"name": "PANTONE 359 CP",
"label": "359",
"hex": "#abd39a"
},
{
"name": "PANTONE 360 CP",
"label": "360",
"hex": "#6ab653"
},
{
"name": "PANTONE 361 CP",
"label": "361",
"hex": "#2fa737"
},
{
"name": "PANTONE 362 CP",
"label": "362",
"hex": "#27a438"
},
{
"name": "PANTONE 363 CP",
"label": "363",
"hex": "#329134"
},
{
"name": "PANTONE 364 CP",
"label": "364",
"hex": "#3a752e"
},
{
"name": "PANTONE 7485 CP",
"label": "7485",
"hex": "#eff4de"
},
{
"name": "PANTONE 7486 CP",
"label": "7486",
"hex": "#c8dfa5"
},
{
"name": "PANTONE 7487 CP",
"label": "7487",
"hex": "#a8cf7f"
},
{
"name": "PANTONE 7488 CP",
"label": "7488",
"hex": "#8fc154"
},
{
"name": "PANTONE 7489 CP",
"label": "7489",
"hex": "#7db65b"
},
{
"name": "PANTONE 7490 CP",
"label": "7490",
"hex": "#719d3b"
},
{
"name": "PANTONE 7491 CP",
"label": "7491",
"hex": "#728534"
},
{
"name": "PANTONE 365 CP",
"label": "365",
"hex": "#d1e3a8"
},
{
"name": "PANTONE 366 CP",
"label": "366",
"hex": "#c2db98"
},
{
"name": "PANTONE 367 CP",
"label": "367",
"hex": "#abce72"
},
{
"name": "PANTONE 368 CP",
"label": "368",
"hex": "#66b231"
},
{
"name": "PANTONE 369 CP",
"label": "369",
"hex": "#5bb033"
},
{
"name": "PANTONE 370 CP",
"label": "370",
"hex": "#5e952d"
},
{
"name": "PANTONE 371 CP",
"label": "371",
"hex": "#556729"
},
{
"name": "PANTONE 372 CP",
"label": "372",
"hex": "#e2eaaf"
},
{
"name": "PANTONE 373 CP",
"label": "373",
"hex": "#d8e4a0"
},
{
"name": "PANTONE 374 CP",
"label": "374",
"hex": "#c6d97b"
},
{
"name": "PANTONE 375 CP",
"label": "375",
"hex": "#a2c640"
},
{
"name": "PANTONE 376 CP",
"label": "376",
"hex": "#8bbd29"
},
{
"name": "PANTONE 377 CP",
"label": "377",
"hex": "#82a527"
},
{
"name": "PANTONE 378 CP",
"label": "378",
"hex": "#556328"
},
{
"name": "PANTONE 580 CP",
"label": "580",
"hex": "#d9e8b9"
},
{
"name": "PANTONE 579 CP",
"label": "579",
"hex": "#d1e3aa"
},
{
"name": "PANTONE 578 CP",
"label": "578",
"hex": "#cbdfa0"
},
{
"name": "PANTONE 577 CP",
"label": "577",
"hex": "#b9d388"
},
{
"name": "PANTONE 576 CP",
"label": "576",
"hex": "#739936"
},
{
"name": "PANTONE 575 CP",
"label": "575",
"hex": "#5d7a30"
},
{
"name": "PANTONE 574 CP",
"label": "574",
"hex": "#425028"
},
{
"name": "PANTONE 5807 CP",
"label": "5807",
"hex": "#e5e8ca"
},
{
"name": "PANTONE 5797 CP",
"label": "5797",
"hex": "#d4d7ac"
},
{
"name": "PANTONE 5787 CP",
"label": "5787",
"hex": "#cdd2a2"
},
{
"name": "PANTONE 5777 CP",
"label": "5777",
"hex": "#afb478"
},
{
"name": "PANTONE 5767 CP",
"label": "5767",
"hex": "#91954b"
},
{
"name": "PANTONE 5757 CP",
"label": "5757",
"hex": "#717530"
},
{
"name": "PANTONE 5747 CP",
"label": "5747",
"hex": "#444a26"
},
{
"name": "PANTONE 5875 CP",
"label": "5875",
"hex": "#e6e4bd"
},
{
"name": "PANTONE 5865 CP",
"label": "5865",
"hex": "#dddbab"
},
{
"name": "PANTONE 5855 CP",
"label": "5855",
"hex": "#d0cd97"
},
{
"name": "PANTONE 5845 CP",
"label": "5845",
"hex": "#b8b26e"
},
{
"name": "PANTONE 5835 CP",
"label": "5835",
"hex": "#a9a156"
},
{
"name": "PANTONE 5825 CP",
"label": "5825",
"hex": "#8b8336"
},
{
"name": "PANTONE 5815 CP",
"label": "5815",
"hex": "#524d24"
},
{
"name": "PANTONE 5803 CP",
"label": "5803",
"hex": "#d9dfc5"
},
{
"name": "PANTONE 5793 CP",
"label": "5793",
"hex": "#c7cdab"
},
{
"name": "PANTONE 5783 CP",
"label": "5783",
"hex": "#b3bb95"
},
{
"name": "PANTONE 5773 CP",
"label": "5773",
"hex": "#979e73"
},
{
"name": "PANTONE 5763 CP",
"label": "5763",
"hex": "#737b49"
},
{
"name": "PANTONE 5753 CP",
"label": "5753",
"hex": "#626b3a"
},
{
"name": "PANTONE 5743 CP",
"label": "5743",
"hex": "#434e2e"
},
{
"name": "PANTONE 7492 CP",
"label": "7492",
"hex": "#dce19f"
},
{
"name": "PANTONE 7493 CP",
"label": "7493",
"hex": "#c9d7a3"
},
{
"name": "PANTONE 7494 CP",
"label": "7494",
"hex": "#a4bd99"
},
{
"name": "PANTONE 7495 CP",
"label": "7495",
"hex": "#889a28"
},
{
"name": "PANTONE 7496 CP",
"label": "7496",
"hex": "#718526"
},
{
"name": "PANTONE 7497 CP",
"label": "7497",
"hex": "#78715b"
},
{
"name": "PANTONE 7498 CP",
"label": "7498",
"hex": "#515731"
},
{
"name": "PANTONE 7744 CP",
"label": "7744",
"hex": "#d2cd04"
},
{
"name": "PANTONE 7745 CP",
"label": "7745",
"hex": "#b6b22d"
},
{
"name": "PANTONE 7746 CP",
"label": "7746",
"hex": "#a1a034"
},
{
"name": "PANTONE 7747 CP",
"label": "7747",
"hex": "#8f9036"
},
{
"name": "PANTONE 7748 CP",
"label": "7748",
"hex": "#8a8b36"
},
{
"name": "PANTONE 7749 CP",
"label": "7749",
"hex": "#7f7c27"
},
{
"name": "PANTONE 7750 CP",
"label": "7750",
"hex": "#75712a"
},
{
"name": "PANTONE 379 CP",
"label": "379",
"hex": "#ebe981"
},
{
"name": "PANTONE 380 CP",
"label": "380",
"hex": "#e3e049"
},
{
"name": "PANTONE 381 CP",
"label": "381",
"hex": "#d5d706"
},
{
"name": "PANTONE 382 CP",
"label": "382",
"hex": "#cfd500"
},
{
"name": "PANTONE 383 CP",
"label": "383",
"hex": "#b1b714"
},
{
"name": "PANTONE 384 CP",
"label": "384",
"hex": "#9b9c1f"
},
{
"name": "PANTONE 385 CP",
"label": "385",
"hex": "#7c762a"
},
{
"name": "PANTONE 386 CP",
"label": "386",
"hex": "#f4eb74"
},
{
"name": "PANTONE 387 CP",
"label": "387",
"hex": "#efe64d"
},
{
"name": "PANTONE 388 CP",
"label": "388",
"hex": "#eae34e"
},
{
"name": "PANTONE 389 CP",
"label": "389",
"hex": "#dddd41"
},
{
"name": "PANTONE 390 CP",
"label": "390",
"hex": "#ccd000"
},
{
"name": "PANTONE 391 CP",
"label": "391",
"hex": "#a2a01a"
},
{
"name": "PANTONE 392 CP",
"label": "392",
"hex": "#888321"
},
{
"name": "PANTONE 587 CP",
"label": "587",
"hex": "#f2ee9c"
},
{
"name": "PANTONE 586 CP",
"label": "586",
"hex": "#f1ec86"
},
{
"name": "PANTONE 585 CP",
"label": "585",
"hex": "#eae670"
},
{
"name": "PANTONE 584 CP",
"label": "584",
"hex": "#dddc34"
},
{
"name": "PANTONE 583 CP",
"label": "583",
"hex": "#c3c506"
},
{
"name": "PANTONE 582 CP",
"label": "582",
"hex": "#95921e"
},
{
"name": "PANTONE 581 CP",
"label": "581",
"hex": "#615c24"
},
{
"name": "PANTONE 393 CP",
"label": "393",
"hex": "#f9f090"
},
{
"name": "PANTONE 394 CP",
"label": "394",
"hex": "#fbed62"
},
{
"name": "PANTONE 395 CP",
"label": "395",
"hex": "#f6e726"
},
{
"name": "PANTONE 396 CP",
"label": "396",
"hex": "#f4e500"
},
{
"name": "PANTONE 397 CP",
"label": "397",
"hex": "#d1c500"
},
{
"name": "PANTONE 398 CP",
"label": "398",
"hex": "#bfb208"
},
{
"name": "PANTONE 399 CP",
"label": "399",
"hex": "#a69b19"
},
{
"name": "PANTONE 3935 CP",
"label": "3935",
"hex": "#fff283"
},
{
"name": "PANTONE 3945 CP",
"label": "3945",
"hex": "#ffec1f"
},
{
"name": "PANTONE 3955 CP",
"label": "3955",
"hex": "#ffe900"
},
{
"name": "PANTONE 3965 CP",
"label": "3965",
"hex": "#fae700"
},
{
"name": "PANTONE 3975 CP",
"label": "3975",
"hex": "#c6b301"
},
{
"name": "PANTONE 3985 CP",
"label": "3985",
"hex": "#9e8d1c"
},
{
"name": "PANTONE 3995 CP",
"label": "3995",
"hex": "#685d24"
},
{
"name": "PANTONE 600 CP",
"label": "600",
"hex": "#fff7b6"
},
{
"name": "PANTONE 601 CP",
"label": "601",
"hex": "#fcf3a3"
},
{
"name": "PANTONE 602 CP",
"label": "602",
"hex": "#fbf190"
},
{
"name": "PANTONE 603 CP",
"label": "603",
"hex": "#fceb44"
},
{
"name": "PANTONE 604 CP",
"label": "604",
"hex": "#fee900"
},
{
"name": "PANTONE 605 CP",
"label": "605",
"hex": "#f4da00"
},
{
"name": "PANTONE 606 CP",
"label": "606",
"hex": "#e4c800"
},
{
"name": "PANTONE 607 CP",
"label": "607",
"hex": "#fcf6bf"
},
{
"name": "PANTONE 608 CP",
"label": "608",
"hex": "#faf3a8"
},
{
"name": "PANTONE 609 CP",
"label": "609",
"hex": "#f7ee8f"
},
{
"name": "PANTONE 610 CP",
"label": "610",
"hex": "#f3e65c"
},
{
"name": "PANTONE 611 CP",
"label": "611",
"hex": "#e6d52c"
},
{
"name": "PANTONE 612 CP",
"label": "612",
"hex": "#d2be00"
},
{
"name": "PANTONE 613 CP",
"label": "613",
"hex": "#c0a90b"
},
{
"name": "PANTONE 461 CP",
"label": "461",
"hex": "#fcf0a5"
},
{
"name": "PANTONE 460 CP",
"label": "460",
"hex": "#faeb8d"
},
{
"name": "PANTONE 459 CP",
"label": "459",
"hex": "#f3e476"
},
{
"name": "PANTONE 458 CP",
"label": "458",
"hex": "#eedb5d"
},
{
"name": "PANTONE 457 CP",
"label": "457",
"hex": "#b39319"
},
{
"name": "PANTONE 456 CP",
"label": "456",
"hex": "#9e841e"
},
{
"name": "PANTONE 455 CP",
"label": "455",
"hex": "#61512b"
},
{
"name": "PANTONE 614 CP",
"label": "614",
"hex": "#f4f0c0"
},
{
"name": "PANTONE 615 CP",
"label": "615",
"hex": "#ede7ab"
},
{
"name": "PANTONE 616 CP",
"label": "616",
"hex": "#e4dc96"
},
{
"name": "PANTONE 617 CP",
"label": "617",
"hex": "#d7cc6f"
},
{
"name": "PANTONE 618 CP",
"label": "618",
"hex": "#b8aa3c"
},
{
"name": "PANTONE 619 CP",
"label": "619",
"hex": "#a1922c"
},
{
"name": "PANTONE 620 CP",
"label": "620",
"hex": "#8f8125"
},
{
"name": "PANTONE 7751 CP",
"label": "7751",
"hex": "#dfc853"
},
{
"name": "PANTONE 7752 CP",
"label": "7752",
"hex": "#e3c231"
},
{
"name": "PANTONE 7753 CP",
"label": "7753",
"hex": "#cba822"
},
{
"name": "PANTONE 7754 CP",
"label": "7754",
"hex": "#9e8734"
},
{
"name": "PANTONE 7755 CP",
"label": "7755",
"hex": "#857539"
},
{
"name": "PANTONE 7756 CP",
"label": "7756",
"hex": "#746737"
},
{
"name": "PANTONE 7757 CP",
"label": "7757",
"hex": "#665f40"
},
{
"name": "PANTONE 7758 CP",
"label": "7758",
"hex": "#e8d300"
},
{
"name": "PANTONE 7759 CP",
"label": "7759",
"hex": "#d4c100"
},
{
"name": "PANTONE 7760 CP",
"label": "7760",
"hex": "#908125"
},
{
"name": "PANTONE 7761 CP",
"label": "7761",
"hex": "#7e7734"
},
{
"name": "PANTONE 7762 CP",
"label": "7762",
"hex": "#626639"
},
{
"name": "PANTONE 7763 CP",
"label": "7763",
"hex": "#545832"
},
{
"name": "PANTONE 7764 CP",
"label": "7764",
"hex": "#515431"
},
{
"name": "PANTONE 7765 CP",
"label": "7765",
"hex": "#cec100"
},
{
"name": "PANTONE 7766 CP",
"label": "7766",
"hex": "#c0b307"
},
{
"name": "PANTONE 7767 CP",
"label": "7767",
"hex": "#ac9b18"
},
{
"name": "PANTONE 7768 CP",
"label": "7768",
"hex": "#96853c"
},
{
"name": "PANTONE 7769 CP",
"label": "7769",
"hex": "#766731"
},
{
"name": "PANTONE 7770 CP",
"label": "7770",
"hex": "#5e5236"
},
{
"name": "PANTONE 7771 CP",
"label": "7771",
"hex": "#4e472b"
},
{
"name": "PANTONE 4545 CP",
"label": "4545",
"hex": "#efe6bf"
},
{
"name": "PANTONE 4535 CP",
"label": "4535",
"hex": "#ded3aa"
},
{
"name": "PANTONE 4525 CP",
"label": "4525",
"hex": "#cebf8b"
},
{
"name": "PANTONE 4515 CP",
"label": "4515",
"hex": "#b6a264"
},
{
"name": "PANTONE 4505 CP",
"label": "4505",
"hex": "#99803a"
},
{
"name": "PANTONE 4495 CP",
"label": "4495",
"hex": "#7f672e"
},
{
"name": "PANTONE 4485 CP",
"label": "4485",
"hex": "#594929"
},
{
"name": "PANTONE 454 CP",
"label": "454",
"hex": "#dddcbb"
},
{
"name": "PANTONE 453 CP",
"label": "453",
"hex": "#d1cca7"
},
{
"name": "PANTONE 452 CP",
"label": "452",
"hex": "#b6b287"
},
{
"name": "PANTONE 451 CP",
"label": "451",
"hex": "#a49f6f"
},
{
"name": "PANTONE 450 CP",
"label": "450",
"hex": "#544a2b"
},
{
"name": "PANTONE 449 CP",
"label": "449",
"hex": "#524831"
},
{
"name": "PANTONE 448 CP",
"label": "448",
"hex": "#473f2b"
},
{
"name": "PANTONE 7499 CP",
"label": "7499",
"hex": "#fff7d2"
},
{
"name": "PANTONE 7500 CP",
"label": "7500",
"hex": "#f7ecca"
},
{
"name": "PANTONE 7501 CP",
"label": "7501",
"hex": "#f0e1be"
},
{
"name": "PANTONE 7502 CP",
"label": "7502",
"hex": "#e5d0a4"
},
{
"name": "PANTONE 7503 CP",
"label": "7503",
"hex": "#b8a979"
},
{
"name": "PANTONE 7504 CP",
"label": "7504",
"hex": "#9c7f63"
},
{
"name": "PANTONE 7505 CP",
"label": "7505",
"hex": "#89674b"
},
{
"name": "PANTONE 468 CP",
"label": "468",
"hex": "#edd8a5"
},
{
"name": "PANTONE 467 CP",
"label": "467",
"hex": "#e1cb9c"
},
{
"name": "PANTONE 466 CP",
"label": "466",
"hex": "#d3b47f"
},
{
"name": "PANTONE 465 CP",
"label": "465",
"hex": "#c19c5d"
},
{
"name": "PANTONE 464 CP",
"label": "464",
"hex": "#87592a"
},
{
"name": "PANTONE 463 CP",
"label": "463",
"hex": "#754f28"
},
{
"name": "PANTONE 462 CP",
"label": "462",
"hex": "#594733"
},
{
"name": "PANTONE 7506 CP",
"label": "7506",
"hex": "#feedcb"
},
{
"name": "PANTONE 7507 CP",
"label": "7507",
"hex": "#ffe3b6"
},
{
"name": "PANTONE 7508 CP",
"label": "7508",
"hex": "#f3d098"
},
{
"name": "PANTONE 7509 CP",
"label": "7509",
"hex": "#edbb7c"
},
{
"name": "PANTONE 7510 CP",
"label": "7510",
"hex": "#dc9a4d"
},
{
"name": "PANTONE 7511 CP",
"label": "7511",
"hex": "#c07722"
},
{
"name": "PANTONE 7512 CP",
"label": "7512",
"hex": "#b16724"
},
{
"name": "PANTONE 719 CP",
"label": "719",
"hex": "#fce1c4"
},
{
"name": "PANTONE 720 CP",
"label": "720",
"hex": "#f7caa5"
},
{
"name": "PANTONE 721 CP",
"label": "721",
"hex": "#f1b482"
},
{
"name": "PANTONE 722 CP",
"label": "722",
"hex": "#da8a4b"
},
{
"name": "PANTONE 723 CP",
"label": "723",
"hex": "#c46d28"
},
{
"name": "PANTONE 724 CP",
"label": "724",
"hex": "#9a4e26"
},
{
"name": "PANTONE 725 CP",
"label": "725",
"hex": "#824126"
},
{
"name": "PANTONE 475 CP",
"label": "475",
"hex": "#fcd5b8"
},
{
"name": "PANTONE 474 CP",
"label": "474",
"hex": "#fbcdab"
},
{
"name": "PANTONE 473 CP",
"label": "473",
"hex": "#f9bf9a"
},
{
"name": "PANTONE 472 CP",
"label": "472",
"hex": "#f1a069"
},
{
"name": "PANTONE 471 CP",
"label": "471",
"hex": "#bc5927"
},
{
"name": "PANTONE 470 CP",
"label": "470",
"hex": "#a15128"
},
{
"name": "PANTONE 469 CP",
"label": "469",
"hex": "#5a3424"
},
{
"name": "PANTONE 726 CP",
"label": "726",
"hex": "#f5dbc1"
},
{
"name": "PANTONE 727 CP",
"label": "727",
"hex": "#edccae"
},
{
"name": "PANTONE 728 CP",
"label": "728",
"hex": "#deaf8a"
},
{
"name": "PANTONE 729 CP",
"label": "729",
"hex": "#ca8c5b"
},
{
"name": "PANTONE 730 CP",
"label": "730",
"hex": "#a76939"
},
{
"name": "PANTONE 731 CP",
"label": "731",
"hex": "#774425"
},
{
"name": "PANTONE 732 CP",
"label": "732",
"hex": "#633c24"
},
{
"name": "PANTONE 4685 CP",
"label": "4685",
"hex": "#f0d8c3"
},
{
"name": "PANTONE 4675 CP",
"label": "4675",
"hex": "#e8ccb5"
},
{
"name": "PANTONE 4665 CP",
"label": "4665",
"hex": "#dab096"
},
{
"name": "PANTONE 4655 CP",
"label": "4655",
"hex": "#c69172"
},
{
"name": "PANTONE 4645 CP",
"label": "4645",
"hex": "#af7b55"
},
{
"name": "PANTONE 4635 CP",
"label": "4635",
"hex": "#985d38"
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{
"name": "PANTONE 4625 CP",
"label": "4625",
"hex": "#4c322a"
},
{
"name": "PANTONE 7513 CP",
"label": "7513",
"hex": "#f8ccba"
},
{
"name": "PANTONE 7514 CP",
"label": "7514",
"hex": "#e9b39d"
},
{
"name": "PANTONE 7515 CP",
"label": "7515",
"hex": "#da9a7c"
},
{
"name": "PANTONE 7516 CP",
"label": "7516",
"hex": "#a04e2e"
},
{
"name": "PANTONE 7517 CP",
"label": "7517",
"hex": "#894127"
},
{
"name": "PANTONE 7518 CP",
"label": "7518",
"hex": "#724f49"
},
{
"name": "PANTONE 7519 CP",
"label": "7519",
"hex": "#635249"
},
{
"name": "PANTONE 4755 CP",
"label": "4755",
"hex": "#e6d0c2"
},
{
"name": "PANTONE 4745 CP",
"label": "4745",
"hex": "#d8bdb1"
},
{
"name": "PANTONE 4735 CP",
"label": "4735",
"hex": "#d0afa3"
},
{
"name": "PANTONE 4725 CP",
"label": "4725",
"hex": "#ab8272"
},
{
"name": "PANTONE 4715 CP",
"label": "4715",
"hex": "#8d5a4a"
},
{
"name": "PANTONE 4705 CP",
"label": "4705",
"hex": "#714236"
},
{
"name": "PANTONE 4695 CP",
"label": "4695",
"hex": "#553024"
},
{
"name": "PANTONE 482 CP",
"label": "482",
"hex": "#e8d1c2"
},
{
"name": "PANTONE 481 CP",
"label": "481",
"hex": "#dfc1af"
},
{
"name": "PANTONE 480 CP",
"label": "480",
"hex": "#d4b09e"
},
{
"name": "PANTONE 479 CP",
"label": "479",
"hex": "#b27d66"
},
{
"name": "PANTONE 478 CP",
"label": "478",
"hex": "#703a2d"
},
{
"name": "PANTONE 477 CP",
"label": "477",
"hex": "#61382d"
},
{
"name": "PANTONE 476 CP",
"label": "476",
"hex": "#4a322a"
},
{
"name": "PANTONE 7527 CP",
"label": "7527",
"hex": "#ebe6d7"
},
{
"name": "PANTONE 7528 CP",
"label": "7528",
"hex": "#d7cdc1"
},
{
"name": "PANTONE 7529 CP",
"label": "7529",
"hex": "#c8bcb0"
},
{
"name": "PANTONE 7530 CP",
"label": "7530",
"hex": "#b1a498"
},
{
"name": "PANTONE 7531 CP",
"label": "7531",
"hex": "#847466"
},
{
"name": "PANTONE 7532 CP",
"label": "7532",
"hex": "#695a4f"
},
{
"name": "PANTONE 7533 CP",
"label": "7533",
"hex": "#43382d"
},
{
"name": "PANTONE 7534 CP",
"label": "7534",
"hex": "#e7e3d4"
},
{
"name": "PANTONE 7535 CP",
"label": "7535",
"hex": "#cac3b2"
},
{
"name": "PANTONE 7536 CP",
"label": "7536",
"hex": "#b1a994"
},
{
"name": "PANTONE 7537 CP",
"label": "7537",
"hex": "#b4bab0"
},
{
"name": "PANTONE 7538 CP",
"label": "7538",
"hex": "#9ba49a"
},
{
"name": "PANTONE 7539 CP",
"label": "7539",
"hex": "#939a98"
},
{
"name": "PANTONE 7540 CP",
"label": "7540",
"hex": "#505459"
},
{
"name": "PANTONE 427 CP",
"label": "427",
"hex": "#e3e6e6"
},
{
"name": "PANTONE 428 CP",
"label": "428",
"hex": "#d2d8db"
},
{
"name": "PANTONE 429 CP",
"label": "429",
"hex": "#aeb7bd"
},
{
"name": "PANTONE 430 CP",
"label": "430",
"hex": "#828d96"
},
{
"name": "PANTONE 431 CP",
"label": "431",
"hex": "#59656f"
},
{
"name": "PANTONE 432 CP",
"label": "432",
"hex": "#333c45"
},
{
"name": "PANTONE 433 CP",
"label": "433",
"hex": "#22282d"
},
{
"name": "PANTONE 420 CP",
"label": "420",
"hex": "#dcddd9"
},
{
"name": "PANTONE 421 CP",
"label": "421",
"hex": "#b8bcba"
},
{
"name": "PANTONE 422 CP",
"label": "422",
"hex": "#a1a5a6"
},
{
"name": "PANTONE 423 CP",
"label": "423",
"hex": "#8b8e8d"
},
{
"name": "PANTONE 424 CP",
"label": "424",
"hex": "#6c7173"
},
{
"name": "PANTONE 425 CP",
"label": "425",
"hex": "#424a4d"
},
{
"name": "PANTONE 426 CP",
"label": "426",
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},
{
"name": "PANTONE 441 CP",
"label": "441",
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},
{
"name": "PANTONE 442 CP",
"label": "442",
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},
{
"name": "PANTONE 443 CP",
"label": "443",
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},
{
"name": "PANTONE 444 CP",
"label": "444",
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},
{
"name": "PANTONE 445 CP",
"label": "445",
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},
{
"name": "PANTONE 446 CP",
"label": "446",
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{
"name": "PANTONE 447 CP",
"label": "447",
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{
"name": "PANTONE 413 CP",
"label": "413",
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},
{
"name": "PANTONE 414 CP",
"label": "414",
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{
"name": "PANTONE 415 CP",
"label": "415",
"hex": "#969992"
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{
"name": "PANTONE 416 CP",
"label": "416",
"hex": "#7a7d76"
},
{
"name": "PANTONE 417 CP",
"label": "417",
"hex": "#62655d"
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{
"name": "PANTONE 418 CP",
"label": "418",
"hex": "#51534c"
},
{
"name": "PANTONE 419 CP",
"label": "419",
"hex": "#222623"
},
{
"name": "PANTONE 400 CP",
"label": "400",
"hex": "#d6d2c9"
},
{
"name": "PANTONE 401 CP",
"label": "401",
"hex": "#bbb7af"
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{
"name": "PANTONE 402 CP",
"label": "402",
"hex": "#a69f98"
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{
"name": "PANTONE 403 CP",
"label": "403",
"hex": "#8c857d"
},
{
"name": "PANTONE 404 CP",
"label": "404",
"hex": "#766e67"
},
{
"name": "PANTONE 405 CP",
"label": "405",
"hex": "#5b544f"
},
{
"name": "PANTONE Black CP",
"label": "black",
"hex": "#2a2926"
},
{
"name": "PANTONE 406 CP",
"label": "406",
"hex": "#d7d1cc"
},
{
"name": "PANTONE 407 CP",
"label": "407",
"hex": "#bab2b0"
},
{
"name": "PANTONE 408 CP",
"label": "408",
"hex": "#a09693"
},
{
"name": "PANTONE 409 CP",
"label": "409",
"hex": "#867c7b"
},
{
"name": "PANTONE 410 CP",
"label": "410",
"hex": "#726564"
},
{
"name": "PANTONE 411 CP",
"label": "411",
"hex": "#534847"
},
{
"name": "PANTONE 412 CP",
"label": "412",
"hex": "#332d2d"
},
{
"name": "PANTONE 434 CP",
"label": "434",
"hex": "#ddd4d4"
},
{
"name": "PANTONE 435 CP",
"label": "435",
"hex": "#cabfc4"
},
{
"name": "PANTONE 436 CP",
"label": "436",
"hex": "#b4a4ad"
},
{
"name": "PANTONE 437 CP",
"label": "437",
"hex": "#78646d"
},
{
"name": "PANTONE 438 CP",
"label": "438",
"hex": "#493b3a"
},
{
"name": "PANTONE 439 CP",
"label": "439",
"hex": "#3a3232"
},
{
"name": "PANTONE 440 CP",
"label": "440",
"hex": "#302d2b"
},
{
"name": "PANTONE Warm Gray 1 CP",
"label": "warm-gray-1",
"hex": "#eceae7"
},
{
"name": "PANTONE Warm Gray 2 CP",
"label": "warm-gray-2",
"hex": "#dfdbd6"
},
{
"name": "PANTONE Warm Gray 3 CP",
"label": "warm-gray-3",
"hex": "#c9c3bf"
},
{
"name": "PANTONE Warm Gray 4 CP",
"label": "warm-gray-4",
"hex": "#b9b4b0"
},
{
"name": "PANTONE Warm Gray 5 CP",
"label": "warm-gray-5",
"hex": "#b0aba6"
},
{
"name": "PANTONE Warm Gray 6 CP",
"label": "warm-gray-6",
"hex": "#9f9792"
},
{
"name": "PANTONE Warm Gray 7 CP",
"label": "warm-gray-7",
"hex": "#948985"
},
{
"name": "PANTONE Warm Gray 8 CP",
"label": "warm-gray-8",
"hex": "#8a807b"
},
{
"name": "PANTONE Warm Gray 9 CP",
"label": "warm-gray-9",
"hex": "#7f716b"
},
{
"name": "PANTONE Warm Gray 10 CP",
"label": "warm-gray-10",
"hex": "#70635d"
},
{
"name": "PANTONE Warm Gray 11 CP",
"label": "warm-gray-11",
"hex": "#625650"
},
{
"name": "PANTONE Cool Gray 1 CP",
"label": "cool-gray-1",
"hex": "#e9eae9"
},
{
"name": "PANTONE Cool Gray 2 CP",
"label": "cool-gray-2",
"hex": "#e1e2e1"
},
{
"name": "PANTONE Cool Gray 3 CP",
"label": "cool-gray-3",
"hex": "#d3d4d3"
},
{
"name": "PANTONE Cool Gray 4 CP",
"label": "cool-gray-4",
"hex": "#bec1c2"
},
{
"name": "PANTONE Cool Gray 5 CP",
"label": "cool-gray-5",
"hex": "#b6b8b9"
},
{
"name": "PANTONE Cool Gray 6 CP",
"label": "cool-gray-6",
"hex": "#b1b4b6"
},
{
"name": "PANTONE Cool Gray 7 CP",
"label": "cool-gray-7",
"hex": "#95989c"
},
{
"name": "PANTONE Cool Gray 8 CP",
"label": "cool-gray-8",
"hex": "#878b8f"
},
{
"name": "PANTONE Cool Gray 9 CP",
"label": "cool-gray-9",
"hex": "#6e7175"
},
{
"name": "PANTONE Cool Gray 10 CP",
"label": "cool-gray-10",
"hex": "#575960"
},
{
"name": "PANTONE Cool Gray 11 CP",
"label": "cool-gray-11",
"hex": "#45474c"
},
{
"name": "PANTONE Black 2 CP",
"label": "black-2",
"hex": "#373426"
},
{
"name": "PANTONE Black 3 CP",
"label": "black-3",
"hex": "#262c26"
},
{
"name": "PANTONE Black 4 CP",
"label": "black-4",
"hex": "#383027"
},
{
"name": "PANTONE Black 5 CP",
"label": "black-5",
"hex": "#3f2e32"
},
{
"name": "PANTONE Black 6 CP",
"label": "black-6",
"hex": "#1f2428"
},
{
"name": "PANTONE Black 7 CP",
"label": "black-7",
"hex": "#343331"
}
] | [
"thomas@ether.com.au"
] | thomas@ether.com.au |
06230ecdcf31b4856ba0534b9ff9efc8622d69c9 | 47f172fae0a9a32c9928a0dc025f1515a6baa658 | /src/data/cifar10.py | ad3546655297e66c0b6f4e65e42751971d0ef2aa | [] | no_license | flasharrow1981/cifar10_tensorflow | 953fcc7f4cea2458f30db9f80f6a940156af5c1f | 05df8c9818219ba213ee21ff47c822d40aa10221 | refs/heads/master | 2021-08-19T12:51:31.260671 | 2017-11-26T10:28:21 | 2017-11-26T10:28:21 | 112,076,733 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 9,638 | py |
# coding: utf-8
# In[2]:
# %load cifar10.py
import pickle
import numpy
import random
import matplotlib.pyplot as plt
import platform
import cv2
import os
import tensorflow as tf
from PIL import Image
import numpy as np
class Corpus:
def __init__(self):
#self.load_cifar10('data/CIFAR10_data')
self.load_cifar10_dataset('/home/dp/down/cifar10/cifar-10-unpack/classify') #目标文件夹')
self._split_train_valid(valid_rate=0.9)
self.n_train = self.train_images.shape[0]
self.n_valid = self.valid_images.shape[0]
self.n_test = self.test_images.shape[0]
def _split_train_valid(self, valid_rate=0.9):
images, labels = self.train_images, self.train_labels
thresh = int(images.shape[0] * valid_rate)
self.train_images, self.train_labels = images[0:thresh,:,:,:], labels[0:thresh]
self.valid_images, self.valid_labels = images[thresh:,:,:,:], labels[thresh:]
#从分类文件夹中读取数据
def load_cifar10_dataset(self, directory):
images, labels = [], []
# 读取训练集
train_dir=os.path.join(directory,'train')
train_classlist=os.listdir(train_dir)
filenames=list()
labels=list()
for classes in train_classlist:
class_path=os.path.join(train_dir,classes)
filelist=os.listdir(class_path)
print('classname='+classes)
for file in filelist:
filefullName=os.path.join(class_path,file)
#filenames.append(filefullName)
#image_string = tf.read_file(filefullName)
#image_decoded = tf.image.decode_png(image_string, channels=3)
#image_resized = tf.image.resize_images(image_decoded, [32, 32])
image_decoded = Image.open(filefullName)
image_decoded = np.array(image_decoded, dtype=np.uint8)
# 此时已经是一个 np.array 了，可以对它进行任意处理
image_decoded.reshape(32, 32, 3)
image_decoded = image_decoded.astype(float)
images.append(image_decoded)
#labels.append(classes)
labels.append(train_classlist.index(classes))
#print(filefullName)
#print(filenames,labels)
training_data = list(zip(images,labels))
np.random.shuffle(training_data)
images,labels = zip(*training_data)
images = numpy.array(images, dtype='float')
labels = numpy.array(labels, dtype='int')
#print(images.shape)
#print(labels.shape)
self.train_images, self.train_labels = images, labels
# 读取测试集
images, labels = [], []
test_dir=os.path.join(directory,'test')
test_classlist=os.listdir(test_dir)
filenames=list()
labels=list()
for classes in test_classlist:
class_path=os.path.join(test_dir,classes)
filelist=os.listdir(class_path)
print('classname='+classes)
for file in filelist:
filefullName=os.path.join(class_path,file)
#filenames.append(filefullName)
#image_string = tf.read_file(filefullName)
#image_decoded = tf.image.decode_png(image_string, channels=3)
#image_resized = tf.image.resize_images(image_decoded, [32, 32])
image_decoded = Image.open(filefullName)
image_decoded = np.array(image_decoded, dtype=np.uint8)
# 此时已经是一个 np.array 了，可以对它进行任意处理
image_decoded.reshape(32, 32, 3)
image_decoded = image_decoded.astype(float)
images.append(image_decoded)
#labels.append(classes)
labels.append(train_classlist.index(classes))
#print(filefullName)
#print(filenames,labels)
test_data = list(zip(images,labels))
np.random.shuffle(test_data)
images,labels = zip(*test_data)
images = numpy.array(images, dtype='float')
labels = numpy.array(labels, dtype='int')
self.test_images, self.test_labels = images, labels
# 函数的功能时将filename对应的图片文件读进来，并缩放到统一的大小
def _parse_function(filename, label):
image_string = tf.read_file(filename)
image_decoded = tf.image.decode_png(image_string, channels=3)
image_resized = tf.image.resize_images(image_decoded, [32, 32])
#one_hot = tf.one_hot(label, 10) #one_hot = tf.one_hot(label, NUM_CLASSES)
return image_resized, label
#return image_resized, one_hot
def load_cifar10(self, directory):
# 读取训练集
images, labels = [], []
for filename in ['%s/data_batch_%d' % (directory, j) for j in range(1, 2)]:#in range(1, 6)]:
with open(filename, 'rb') as fo:
if 'Windows' in platform.platform():
cifar10 = pickle.load(fo, encoding='bytes')
elif 'Linux' in platform.platform():
cifar10 = pickle.load(fo, encoding='bytes')
for i in range(len(cifar10[b"labels"])):
image = numpy.reshape(cifar10[b"data"][i], (3, 32, 32))
image = numpy.transpose(image, (1, 2, 0))
image = image.astype(float)
images.append(image)
labels += cifar10[b"labels"]
images = numpy.array(images, dtype='float')
labels = numpy.array(labels, dtype='int')
self.train_images, self.train_labels = images, labels
# 读取测试集
images, labels = [], []
for filename in ['%s/test_batch' % (directory)]:
with open(filename, 'rb') as fo:
if 'Windows' in platform.platform():
cifar10 = pickle.load(fo, encoding='bytes')
elif 'Linux' in platform.platform():
cifar10 = pickle.load(fo, encoding='bytes')
for i in range(len(cifar10[b"labels"])):
image = numpy.reshape(cifar10[b"data"][i], (3, 32, 32))
image = numpy.transpose(image, (1, 2, 0))
image = image.astype(float)
images.append(image)
labels += cifar10[b"labels"]
images = numpy.array(images, dtype='float')
labels = numpy.array(labels, dtype='int')
self.test_images, self.test_labels = images, labels
def data_augmentation(self, images, mode='train', flip=False,
crop=False, crop_shape=(24,24,3), whiten=False,
noise=False, noise_mean=0, noise_std=0.01):
# 图像切割
if crop:
if mode == 'train':
images = self._image_crop(images, shape=crop_shape)
elif mode == 'test':
images = self._image_crop_test(images, shape=crop_shape)
# 图像翻转
if flip:
images = self._image_flip(images)
# 图像白化
if whiten:
images = self._image_whitening(images)
# 图像噪声
if noise:
images = self._image_noise(images, mean=noise_mean, std=noise_std)
return images
def _image_crop(self, images, shape):
# 图像切割
new_images = []
for i in range(images.shape[0]):
old_image = images[i,:,:,:]
left = numpy.random.randint(old_image.shape[0] - shape[0] + 1)
top = numpy.random.randint(old_image.shape[1] - shape[1] + 1)
new_image = old_image[left: left+shape[0], top: top+shape[1], :]
new_images.append(new_image)
return numpy.array(new_images)
def _image_crop_test(self, images, shape):
# 图像切割
new_images = []
for i in range(images.shape[0]):
old_image = images[i,:,:,:]
left = int((old_image.shape[0] - shape[0]) / 2)
top = int((old_image.shape[1] - shape[1]) / 2)
new_image = old_image[left: left+shape[0], top: top+shape[1], :]
new_images.append(new_image)
return numpy.array(new_images)
def _image_flip(self, images):
# 图像翻转
for i in range(images.shape[0]):
old_image = images[i,:,:,:]
if numpy.random.random() < 0.5:
new_image = cv2.flip(old_image, 1)
else:
new_image = old_image
images[i,:,:,:] = new_image
return images
def _image_whitening(self, images):
# 图像白化
for i in range(images.shape[0]):
old_image = images[i,:,:,:]
new_image = (old_image - numpy.mean(old_image)) / numpy.std(old_image)
images[i,:,:,:] = new_image
return images
def _image_noise(self, images, mean=0, std=0.01):
# 图像噪声
for i in range(images.shape[0]):
old_image = images[i,:,:,:]
new_image = old_image
for i in range(image.shape[0]):
for j in range(image.shape[1]):
for k in range(image.shape[2]):
new_image[i, j, k] += random.gauss(mean, std)
images[i,:,:,:] = new_image
return images
| [
"emailtocheng@sina.com"
] | emailtocheng@sina.com |
0586254129352bfb36f515bc01aaa91501665f1e | 1d785e0506163d2ba7746408bc4c3d365a1aa8b4 | /runserver.py | 8ffce111bc04b5de242bf5b025e9ac7495b3a40d | [] | no_license | vijaya22/loaners | 770e0af9872dfbb39022ca9d96d3e81200f307c6 | 6eb479f5936afebe173ed24a8c9b94a2551a5541 | refs/heads/master | 2021-01-15T12:49:22.955905 | 2016-04-03T12:09:30 | 2016-04-03T12:09:30 | 55,423,664 | 0 | 1 | null | 2017-10-29T13:11:09 | 2016-04-04T15:41:51 | CSS | UTF-8 | Python | false | false | 72 | py | from myapp import app
if __name__ == '__main__':
app.run(debug=True)
| [
"suyashgargsfam@gmail.com"
] | suyashgargsfam@gmail.com |
e5b6511e4d3f74222c3dbd31bce3b0057939db28 | 0023a88840b80b0a0bded858136748343b6ac725 | /muda/version.py | f5322bd12ed85650018482ee6633666c8b4c19d8 | [
"ISC"
] | permissive | jatinkhilnani/muda | 5b57df2dd3ced952d8b3500fc65fff5fbc64bd31 | 8b60b88c0597ad11b23680d1181334e4bc85ec6f | refs/heads/master | 2022-11-22T23:42:06.610313 | 2020-07-28T18:11:51 | 2020-07-28T18:11:51 | 261,575,849 | 0 | 0 | ISC | 2020-05-05T20:27:15 | 2020-05-05T20:27:14 | null | UTF-8 | Python | false | false | 108 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Version info"""
short_version = "0.4.1"
version = "0.4.1"
| [
"brian.mcfee@nyu.edu"
] | brian.mcfee@nyu.edu |
4deef57a4db017517753bdb28d72ce7cb6b01c94 | d4a569dcf616b7f05e53a44803e38196b436b8b9 | /Thesis@3.9.1/Lib/site-packages/mypy/typeshed/stdlib/2and3/math.pyi | 2988c5a0ac7e48bc4181fa8d5975f7e3ee0d0c16 | [
"MIT"
] | permissive | nverbois/TFE21-232 | ac3178d24939c872c02a671c0f1d8cc471af516b | 7113837b5263b5c508bfc6903cb6982b48aa7ee4 | refs/heads/main | 2023-06-05T18:50:59.207392 | 2021-06-25T19:54:40 | 2021-06-25T19:54:40 | 337,691,391 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,455 | pyi | # Stubs for math
# See: http://docs.python.org/2/library/math.html
from typing import Tuple, Iterable, SupportsFloat, SupportsInt, overload
import sys
e: float
pi: float
if sys.version_info >= (3, 5):
inf: float
nan: float
if sys.version_info >= (3, 6):
tau: float
def acos(__x: SupportsFloat) -> float: ...
def acosh(__x: SupportsFloat) -> float: ...
def asin(__x: SupportsFloat) -> float: ...
def asinh(__x: SupportsFloat) -> float: ...
def atan(__x: SupportsFloat) -> float: ...
def atan2(__y: SupportsFloat, __x: SupportsFloat) -> float: ...
def atanh(__x: SupportsFloat) -> float: ...
if sys.version_info >= (3,):
def ceil(__x: SupportsFloat) -> int: ...
else:
def ceil(__x: SupportsFloat) -> float: ...
def copysign(__x: SupportsFloat, __y: SupportsFloat) -> float: ...
def cos(__x: SupportsFloat) -> float: ...
def cosh(__x: SupportsFloat) -> float: ...
def degrees(__x: SupportsFloat) -> float: ...
if sys.version_info >= (3, 8):
def dist(__p: Iterable[SupportsFloat], __q: Iterable[SupportsFloat]) -> float: ...
def erf(__x: SupportsFloat) -> float: ...
def erfc(__x: SupportsFloat) -> float: ...
def exp(__x: SupportsFloat) -> float: ...
def expm1(__x: SupportsFloat) -> float: ...
def fabs(__x: SupportsFloat) -> float: ...
def factorial(__x: SupportsInt) -> int: ...
if sys.version_info >= (3,):
def floor(__x: SupportsFloat) -> int: ...
else:
def floor(__x: SupportsFloat) -> float: ...
def fmod(__x: SupportsFloat, __y: SupportsFloat) -> float: ...
def frexp(__x: SupportsFloat) -> Tuple[float, int]: ...
def fsum(__seq: Iterable[float]) -> float: ...
def gamma(__x: SupportsFloat) -> float: ...
if sys.version_info >= (3, 5):
def gcd(__x: int, __y: int) -> int: ...
if sys.version_info >= (3, 8):
def hypot(*coordinates: SupportsFloat) -> float: ...
else:
def hypot(__x: SupportsFloat, __y: SupportsFloat) -> float: ...
if sys.version_info >= (3, 5):
def isclose(
a: SupportsFloat,
b: SupportsFloat,
*,
rel_tol: SupportsFloat = ...,
abs_tol: SupportsFloat = ...
) -> bool: ...
def isinf(__x: SupportsFloat) -> bool: ...
if sys.version_info >= (3,):
def isfinite(__x: SupportsFloat) -> bool: ...
def isnan(__x: SupportsFloat) -> bool: ...
if sys.version_info >= (3, 8):
def isqrt(__n: int) -> int: ...
def ldexp(__x: SupportsFloat, __i: int) -> float: ...
def lgamma(__x: SupportsFloat) -> float: ...
def log(x: SupportsFloat, base: SupportsFloat = ...) -> float: ...
def log10(__x: SupportsFloat) -> float: ...
def log1p(__x: SupportsFloat) -> float: ...
if sys.version_info >= (3, 3):
def log2(__x: SupportsFloat) -> float: ...
def modf(__x: SupportsFloat) -> Tuple[float, float]: ...
def pow(__x: SupportsFloat, __y: SupportsFloat) -> float: ...
if sys.version_info >= (3, 8):
@overload
def prod(__iterable: Iterable[int], *, start: int = ...) -> int: ... # type: ignore
@overload
def prod(
__iterable: Iterable[SupportsFloat], *, start: SupportsFloat = ...
) -> float: ...
def radians(__x: SupportsFloat) -> float: ...
if sys.version_info >= (3, 7):
def remainder(__x: SupportsFloat, __y: SupportsFloat) -> float: ...
def sin(__x: SupportsFloat) -> float: ...
def sinh(__x: SupportsFloat) -> float: ...
def sqrt(__x: SupportsFloat) -> float: ...
def tan(__x: SupportsFloat) -> float: ...
def tanh(__x: SupportsFloat) -> float: ...
def trunc(__x: SupportsFloat) -> int: ...
| [
"38432529+nverbois@users.noreply.github.com"
] | 38432529+nverbois@users.noreply.github.com |
911a53b6fafdc87fa178c71b55ed5c02fd666fbe | 9123a6624cf7d327414f5a40ea6450eef835ac4d | /src/res/reset_hs.py | fdc6a184a5826c0c0b760ee51de9b9c6d2e7be0f | [
"Apache-2.0"
] | permissive | Ale-XYX/Flappe | 2718876c837c32a6464bd28dc886b5918b314b75 | 8199a99e44722765c01ee95f13b137336b0fba57 | refs/heads/master | 2021-10-23T09:24:45.353423 | 2019-03-16T20:41:37 | 2019-03-16T20:41:37 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 52 | py | import pickle
pickle.dump(0, open('hs.dat', 'wb'))
| [
"33987596+Pygasm@users.noreply.github.com"
] | 33987596+Pygasm@users.noreply.github.com |
4bcbdbb6bf47f706baea36af411230deefae2a74 | 45a2ab312c822b6ae426122402b68f93409d7fe3 | /webui-flask2/vizdoc_server.py | 3890d1668fedd4c6b1a79c2a0e476fbb9fc625a4 | [] | no_license | sai-r-susarla/visual-search | 9e1231aa076549924435263a280855d617e93d7c | 768b73233ed5c612ba575c9c65b1e0b156c118e9 | refs/heads/master | 2021-05-30T17:45:21.196702 | 2015-12-03T10:14:06 | 2015-12-03T10:14:06 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 12,229 | py | import os
from flask import request
from os import path
from flask.ext.pymongo import PyMongo
from flask import *
from functools import wraps
import json,time
from werkzeug import secure_filename
#import datetime
from vizdoc_config import *
#import vizdoc_user
#import vizdoc_anno
ALLOWED_EXTENSIONS = set(['txt', 'pdf', 'png', 'jpg', 'jpeg', 'gif','zip'])
UPLOAD_FOLDER = os.path.dirname(os.path.abspath(__name__))+'/static/images/'
print UPLOAD_FOLDER
app = Flask(__name__)
#mongo = PyMongo(app, config_prefix='MONGO2')
mongo = PyMongo(app)
# connect to another MongoDB database on the same host
#app.config['MONGO2_DBNAME'] = 'vizdoc_db'
#mongo = PyMongo(app, config_prefix='MONGO2')
def allowed_file(filename):
return '.' in filename and \
filename.rsplit('.', 1)[1] in ALLOWED_EXTENSIONS
#using this we can create, name a book and insert any num. of img files in it and store in appropriate place.The Global "UPLOAD FOLDER" is the location where the new book will be stored. Click "Add Book" in the UI to test it.
@app.route('/uploadbook', methods=['GET', 'POST'])
def upload_book():
# if request.method == 'POST':
uploaded_files = request.files.getlist("file[]")
dirname = request.form.get("foldername",None)
print (dirname)
#print type(UPLOAD_FOLDER)
#print type(dirname)
#BASE_DIR = 'http://localhost:5000' #'/home/vtbhat/vsearch_db'
#app.config['BASE_DIR'] = '/home/vtbhat/vsearch_db'
if not dirname == None:
abs_path = UPLOAD_FOLDER + dirname + '/'
print (abs_path)
if not os.path.exists(abs_path):
os.mkdir(abs_path)
else:
return "A book with this name already exists.. Please give another name."
filenames = []
for file in uploaded_files:
# Check if the file is one of the allowed types/extensions
if file and allowed_file(file.filename):
# Make the filename safe, remove unsupported chars
filename = secure_filename(file.filename)
# Move the file form the temporal folder to the upload
# folder we setup
#file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
file.save(abs_path + filename)
filenames.append(filename)
# Redirect the user to the uploaded_file route, which
# will basicaly show on the browser the uploaded file
#return "file(s) uploaded successfully"
# Load an html page with a link to each uploaded file
#return redirect(url_for('uploaded_files', filename=filename))
#return redirect(url_for('dir_listing', dirname=dirname))
return render_template('uploadbook.html',filenames=filenames)
#add any num. of pages(.jpg files) to an already created book.
@app.route('/uploadpage', methods=['GET', 'POST'])
def upload_file():
# if request.method == 'POST':
uploaded_files = request.files.getlist("file[]")
dirname = request.form.get("foldername",None)
print (dirname)
#print type(UPLOAD_FOLDER)
#print type(dirname)
#BASE_DIR = 'http://localhost:5000' #'/home/vtbhat/vsearch_db'
#app.config['BASE_DIR'] = '/home/vtbhat/vsearch_db'
filenames = []
for file in uploaded_files:
# Check if the file is one of the allowed types/extensions
if file and allowed_file(file.filename):
# Make the filename safe, remove unsupported chars
filename = secure_filename(file.filename)
# Move the file form the temporal folder to the upload
# folder we setup
#file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
file.save(UPLOAD_FOLDER + dirname + filename)
filenames.append(filename)
# Redirect the user to the uploaded_file route, which
# will basicaly show on the browser the uploaded file
#return "file(s) uploaded successfully"
# Load an html page with a link to each uploaded file
#return redirect(url_for('uploaded_files', filename=filename))
#return redirect(url_for('dir_listing', dirname=dirname))
return render_template('uploadpage.html',filenames=filenames)
@app.route('/upload/<filename>')
def uploaded_files(filename):
return send_from_directory(app.config['UPLOAD_FOLDER'],
filename)
#@app.route('/<path:req_path>')
#def dir_listing(req_path):
# BASE_DIR = ROOTDIR #'/home/vtbhat/vsearch_db'
#
# # Joining the base and the requested path
# abs_path = os.path.join(BASE_DIR, req_path)
#
# # Return 404 if path doesn't exist
# if not os.path.exists(abs_path):
# return abort(404)
#
# # Check if path is a file and serve
# if os.path.isfile(abs_path):
# return send_file(abs_path)
#
# # Show directory contents
# files = os.listdir(abs_path)
# return render_template('files.html', files=files)
app.secret_key = 'milan322'
@app.route('/')
def home():
return render_template('home.html')
@app.route('/logged_user')
def logged_home():
return render_template('hello.html')
#@app.route('/welcome')
#def welcome():
# return render_template('welcome.html')
def login_required(test):
@wraps(test)
def wrap(*args, **kwargs):
if 'logged_in' in session:
return test(*args, **kwargs)
else:
flash('you need to login first!')
return redirect(url_for('login'))
return wrap
@app.route('/logout')
def logout():
session.pop('logged_in',None)
flash('you were logged out !!')
return redirect (url_for('login'))
#This is the page which will be opened after login.
@app.route('/hello')
@login_required
def hello():
return render_template('hello.html')
@app.route('/login',methods=['GET','POST'])
def login():
error = None
if request.method == 'POST':
if request.form['username'] !='admin' or request.form['password'] !='admin':
error='Invalid Credentials, Please try again !!'
else:
session['logged_in']=True
return redirect(url_for('hello'))
return render_template('login.html',error=error)
#gives the list of all json files, recursively, present in ROOTDIR
@app.route('/getbooklist')
def filelist():
arr=[]
for root, dirs, files in os.walk(ROOTDIR):
#print('Found directory: %s' % root)
for file in files:
if file.endswith(".json"):
abspath = os.path.join(root,file)
newfile = str.replace(abspath, ROOTDIR, "");
print (newfile)
sendpath=newfile
data=sendpath[1]
# print('\t%s' % file)
#converting RAW data of python array element into json files.
arr.append(str(newfile))
# return '{"books":'+arr+'}'
print (arr)
return json.dumps(arr)
jsonfile = "filelist.json"
d={
"paths": ""
}
d['paths']=arr
json.dumps(d)
print (d)
with open(ROOTDIR + jsonfile, 'w') as outfile:
json.dump(d, outfile, sort_keys = True, indent = 4,ensure_ascii=False)
# print (s'Successfully saved!')
# return (d)
return send_from_directory(ROOTDIR,jsonfile)
#deletes annotations in mongodb provided both imagename and coordinates
@app.route('/delannoimgcoord/<image>',methods=['GET','POST'])
@app.route('/delannoimgcoord/<image>/<coord>',methods=['GET','POST'])
def delannoimgcord(coord,image=None):
mongo.db.pages.remove({"imagepath" : image, "coord": coord})
print "success"
#deletes all annotations related to an image at once
@app.route('/delannoimg/<image>',methods=['GET','POST'])
def delannoimg(image):
mongo.db.pages.remove({"imagepath" : image})
print "success"
#need to be checked
@app.route('/static/<path:filepath>')
def getFile(filepath):
print "Entered getFile"
abspath = ROOTDIR + "/" + filepath
print abspath
return send_file(abspath)
#returns the book.json showing all of it's images
@app.route('/getbooks/<bookid>', methods=['GET','POST'])
def getBook(bookid):
print "processing " + bookid
fname = PUBSTORE+"/books/"+bookid+".json"
print fname
return send_from_directory(PUBSTORE+"/books",bookid+".json")
#saves or inserts annotations, used imagepath and coord as keys
@app.route('/saveanno/<image>/<coord>/<ratings>/<name>/<text>/<comment>',methods=['GET','POST'])
def sveanno(image,coord,ratings,name,text,comment):
# impath = request.args.get('pagepath',type=str)
# coord = request.args.get('coord',type=str)
mongo.db.pages.insert(
{'imagepath': image, 'coord': coord,
"annotations" : { "ratings" : ratings, "name" : name, "text" : text, "comment" : comment } },
safe=True,upsert=True)
#retrives only one annotation, given an imagename.
@app.route('/retrieveanno/<imagename>')
def retrieveanno(imagename):
page = mongo.db.pages.find_one_or_404({'imagepath': imagename})
print page
#updates(replaces annotations for existing keys) an annotation privided an imagepath and coordinates. can be checked using form itself
@app.route('/form/<coords>',methods=['GET','POST'])
@app.route('/form/<coords>/<image>',methods=['GET','POST'])
def save_page(coords,image=None):
if 'submit' in request.form:
mongo.db.pages.update(
{'imagepath': image, 'coords': coords},
{'$set': {'ratings': request.form['ratings'], 'name': request.form['name'], 'text': request.form['text'], 'com': request.form['com']}},
safe=True, upsert=True)
return redirect(url_for('show_page', pagepath=pagepath))
#needs to be checked
@app.route('/getpage/<page>', methods=['GET','POST'])
def getpage(page):
pname = PUBSTORE+"/books/"+page+".json"
print pname
image = request.args.get('impath',type=str)
components = pname.split('/')
del components[-1]
extract = components[-1].split('.')
basename = extract[0]
extension = "_annotation.json"
finaljson = basename + extension
jsonpath = ROOTDIR + "/"+ '/'.join(components) + "/segments/" + basename + extension
print jsonpath
if path.exists(jsonpath):
with open(pname) as p:
bookjson=json.load(f)
print "all directory files"
return send_from_directory(PUBSTORE+"/books",basename+".json")
@app.route('/getanno/<coord>',methods=['GET','POST'])
@app.route('/getanno/<coord>/<imagepath>',methods=['GET','POST'])
def getanno(coord,imagepath=None):
# impath = request.args.get('imagepath',type=str)
# coord = request.args.get('coord',type=str)
print "getting mongodb contents"
anno = mongo.db.annotations.find_one_or_404({'coord':coord,'imagepath':imagepath})
print "successful"
print anno
# {'ratings': request.get('ratings'), 'name': request.get('name'),
# 'text': request.get('text'), 'comment': request.get('comment')},
# safe=True, upsert=True)
#runs imagesegmenter to produce rectangles on cliking an image
@app.route('/segment',methods=['GET','POST'])
def segment():
from imagestojson import *
jsonfile = jsonfile
clicked_image = request.args.get('imagepath',type=str)
print clicked_image
dividing = clicked_image.split('/')
extract = dividing[-1].split('.')
imgname = extract[0]
extension = "_segments.json"
finaljson = extract[0]+extension
jsonpath = "/static/segments/" + finaljson
if not path.exists(jsonpath):
rv1 = os.system("python imagestojson.py static/images/"+dividing[-1])
if rv1 == 0:
print "one script is succssful"
rv2 = os.system("python mainimgsegmenter.py -j static/"+jsonfile+" -b "+finaljson)
else:
print "file already exists"
return jsonify(result=jsonpath)
@app.route('/form')
def form():
image = request.args.get('image')
print image
coords = request.args.get('coords')
print coords
return render_template('form.html',page=None,image=image,coords=coords)
if __name__ == '__main__':
import doctest
doctest.testmod()
app.run(debug=True)
# app.run(host = '0.0.0.0',debug=True)
#def getAnnotations - complete
#def delAnnotation - done
#def genSegments - done
#def saveAllSegments - done
#def delSegment
| [
"sai.susarla@gmail.com"
] | sai.susarla@gmail.com |
b63d322ca7aefa38272299340d05171952a16de8 | f7b18d08eb75fb33d74239c98686afbed1c12d1c | /2016/california/scripts/california_election.py | e6c029d8faecb7df65de9aaa17dc9392556e9e46 | [] | permissive | democracyworks/hand-collection-to-vip | af0056a3357c90db4a50e16b3c3dd313ee48b3ef | b50aea21a46f1db7865c7c5561ae1057b6cd5ecd | refs/heads/master | 2022-11-20T10:27:35.191302 | 2022-11-10T15:33:38 | 2022-11-10T15:33:38 | 64,783,559 | 0 | 1 | BSD-3-Clause | 2022-08-08T14:20:45 | 2016-08-02T18:49:52 | Python | UTF-8 | Python | false | false | 9,375 | py | """
id,
date,
name,
election_type,
state_id,
is_statewide,
registration_info,
absentee_ballot_info,
results_uri,
polling_hours,
has_election_day_registration,
registration_deadline,
absentee_request_deadline,
hours_open_id
"""
import datetime
import csv
import config
from california_polling_location import PollingLocationTxt
import pandas as pd
class ElectionTxt(object):
def __init__(self, base_df, state_feed):
self.base_df = base_df
self.state_feed = state_feed
#print self.base_df
#print state_feed
def create_election_id(self, index):
"""Leading zeroes are added, if necessary, to maintain a
consistent id length.
"""
if index <= 9:
index_str = '000' + str(index)
elif index in range(10, 100):
index_str = '00' + str(index)
elif index in range(100, 1000):
index_str = '0' + str(index)
else:
index_str = str(index)
return 'e' + str(index_str)
def get_date(self):
"""#"""
return '2016-11-08'
def get_name(self):
"""#"""
return "2016 General Election"
def get_election_name(self):
return "2016 General"
def get_election_type(self):
"""#"""
return 'federal'
#def get_state_id(self):
# """#"""
# get state name, lower()
# pass
def create_state_id(self):
"""Creates the state_id by matching a key in the state_dict and retrieving
and modifying its value. A '0' is added, if necessary, to maintain a
consistent id length.
"""
# TODO: use fips code
for key, value in config.fips_dict.iteritems():
if key == config.state.lower():
state_num = value
if state_num <=9:
state_num = '0' + str(state_num)
else:
state_num = str(state_num)
return 'st' + state_num
def is_statewide(self):
"""#"""
return 'true'
def registration_info(self):
"""#"""
return ''
def absentee_ballot_info(self):
"""#"""
return ''
def results_uri(self):
"""#"""
return ''
def polling_hours(self, hours):
"""Takes hours from polling_location."""
return hours
def has_election_day_registration(self):
"""#"""
return 'false'
def registration_deadline(self, index):
"""Grab registration_deadline from state_feed document."""
for index, row in self.state_feed.iterrows():
if row['office_name'] == config.state:
return row['registration_deadline']
else:
print 'Missing value at row ' + str(index) + '.'
return ''
def absentee_request_deadline(self, index):
"""Grab ballot_request_deadline_display from state_feed document."""
for index, row in self.state_feed.iterrows():
if row['office_name'] == config.state:
return row['ballot_request_deadline']
else:
print 'Missing value at row ' + str(index) + '.'
return ''
def hours_open_id(self):
"""#"""
return ''
def build_election_txt(self):
"""
New columns that match the 'schedule.txt' template are inserted into the DataFrame, apply() is
used to run methods that generate the values for each row of the new columns.
"""
self.base_df['id'] = self.base_df.apply(
lambda row: self.create_election_id(row['index']), axis=1)
self.base_df['date'] = self.base_df.apply(
lambda row: self.get_date(), axis=1)
self.base_df['name'] = self.base_df.apply(
lambda row: self.get_name(), axis=1)
self.base_df['election_type'] = self.base_df.apply(
lambda row: self.get_election_type(), axis=1)
self.base_df['state_id'] = self.base_df.apply(
lambda row: self.create_state_id(), axis=1)
self.base_df['is_statewide'] = self.base_df.apply(
lambda row: self.is_statewide(), axis=1)
self.base_df['registration_info'] = self.base_df.apply(
lambda row: self.registration_info(), axis=1)
self.base_df['absentee_ballot_info'] = self.base_df.apply(
lambda row: self.absentee_ballot_info(), axis=1)
self.base_df['results_uri'] = self.base_df.apply(
lambda row: self.results_uri(), axis=1)
self.base_df['polling_hours'] = self.base_df.apply(
lambda row: self.polling_hours(row['hours']), axis=1)
self.base_df['has_election_day_registration'] = self.base_df.apply(
lambda row: self.has_election_day_registration(), axis=1)
#
self.base_df['registration_deadline'] = self.base_df.apply(
lambda row: self.registration_deadline(row['index']), axis=1)
self.base_df['absentee_request_deadline'] = self.base_df.apply(
lambda row: self.absentee_request_deadline(row['index']), axis=1)
self.base_df['hours_open_id'] = self.base_df.apply(
lambda row: self.hours_open_id(), axis=1)
#print self.base_df
return self.base_df
def write(self):
et = self.build_election_txt()
et.drop(['ocd-division', 'county', 'name', 'address_one', 'address_two', 'city', 'state', 'zip', 'start_time',
'end_time', 'start_date', 'end_date', 'appt_1', 'appt_2', 'appt_3', 'subject_to_change',
'index', 'address_line', 'directions',
'hours', 'photo_uri', 'hours_open_id', 'is_drop_box', 'is_early_voting', 'lat', 'long', 'latlng', 'source_id'], inplace=True, axis=1)
cols = ["id", "date", "name", "election_type", "state_id", "is_statewide", "registration_info",
'absentee_ballot_info', 'results_uri', "polling_hours", 'has_election_day_registration', 'registration_deadline',
'absentee_request_deadline', 'hours_open_id']
et = et.reindex(columns=cols)
print et
et.to_csv(config.output + 'election.txt', index=False, encoding='utf-8') # send to txt file
et.to_csv(config.output + 'election.csv', index=False, encoding='utf-8') # send to csv file
# def write_election_txt(self):
# output_path = "/home/acg/democracyworks/hand-collection-to-vip/minnesota/output/election.txt"
# try:
## f = open(output_path, 'ab')
# fieldnames = ['id', 'date', 'name', 'election_type', 'state_id', 'is_statewide',
# 'registration_info', 'absentee_ballot_info', 'results_uri',
# 'polling_hours', 'has_election_day_registration', 'registration_deadline',
# 'absentee_request_deadline', 'hours_open_id']
# writer = csv.DictWriter(f, fieldnames=fieldnames)
# writer.writeheader()
# writer.writerow({'id': self.create_id(),
# 'date': self.get_date(),
# 'name': self.get_name(),
# 'election_type': self.get_election_type(),
# 'state_id': self.create_state_id(),
# 'is_statewide': self.is_statewide(),
# 'registration_info': '',
# 'absentee_ballot_info': '',
# 'results_uri': self.results_uri(),
# 'polling_hours': '',
# 'has_election_day_registration': self.has_election_day_registration(),
# 'registration_deadline': self.registration_deadline(),
# 'absentee_request_deadline': self.absentee_request_deadline(),
# 'hours_open_id': self.hours_open_id()
# })
# finally:
# f.close()
if __name__ == '__main__':
early_voting_path = config.output + "intermediate_doc.csv"
#early_voting_path = "/Users/danielgilberg/Development/hand-collection-to-vip/polling_location/polling_location_input/kansas_early_voting_info.csv"
colnames = ['ocd-division', 'county', 'name', 'address_one', 'address_two', 'dirs', 'city', 'state', 'zip', 'start_time',
'end_time', 'start_date', 'end_date', 'appt_1', 'appt_2', 'appt_3', 'subject_to_change',
'index', 'address_line', 'directions',
'hours', 'photo_uri', 'hours_open_id', 'is_drop_box', 'is_early_voting', 'lat', 'long', 'latlng', 'source_id']
early_voting_df = pd.read_csv(early_voting_path, names=colnames, encoding='utf-8', skiprows=1)
early_voting_df['index'] = early_voting_df.index + 1
state_feed_path = config.data_folder + "state_feed_info.csv"
colnames = ['office_name', 'ocd_division', 'same_day_reg', 'election_date', 'election_name', 'registration_deadline',
"registration_deadline_display", 'ballot_request_deadline', 'ballot_request_deadline_display']
state_feed_df = pd.read_csv(state_feed_path, names=colnames, encoding='utf-8', skiprows=1)
state_feed_df['index'] = state_feed_df.index + 1
# print state_feed_df
et = ElectionTxt(early_voting_df, state_feed_df)
et.write() | [
"danielgilberg@gmail.com"
] | danielgilberg@gmail.com |
a81d0fda8526c9874b884eb9b04820a627082e31 | 21da6cac0e7e1786dc6749ba5fc744a231c5178d | /cbt/apps.py | 1ccb35ab7c2a2cc4d3924fbb872cef1d4e82d9be | [] | no_license | CodeLuminary/cbt-api-with-django | d3636d1ffdf8a022577345187ee9a8cb5119e29b | 4ee77a50f533326abe0f28450d1f9e4faec33cfe | refs/heads/main | 2023-09-01T06:13:55.525634 | 2021-11-05T14:02:40 | 2021-11-05T14:02:40 | 416,970,799 | 4 | 1 | null | null | null | null | UTF-8 | Python | false | false | 138 | py | from django.apps import AppConfig
class CbtConfig(AppConfig):
default_auto_field = 'django.db.models.BigAutoField'
name = 'cbt'
| [
"victorijoni@yahoo.com"
] | victorijoni@yahoo.com |
3298402de596ffc2f42925eca95072ff096b4bea | 44be0786a0d3e7022b3b8d1dfb34ac84bd91c77e | /mysite/settings.py | bd91ba17a69d5753fef9a6195cf6499a32132bfc | [] | no_license | tommytang088/my-first-blog | 49c9811af177117f2bdbab2104bad532177d803b | 0e4243440ba1ff20dc515227a23fe381dd94b304 | refs/heads/master | 2016-09-13T12:15:24.645188 | 2016-04-29T18:20:23 | 2016-04-29T18:20:23 | 57,331,268 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,238 | py | """
Django settings for mysite project.
Generated by 'django-admin startproject' using Django 1.9.5.
For more information on this file, see
https://docs.djangoproject.com/en/1.9/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.9/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.9/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '_mjrl+xw@t^#5kdj^7as*kju$4zzh*7lbx!6@tp879kn0d#bst'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'blog',
]
MIDDLEWARE_CLASSES = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.auth.middleware.SessionAuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'mysite.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'mysite.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.9/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/1.9/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.9/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'America/New_York'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.9/howto/static-files/
STATIC_URL = '/static/'
STATIC_ROOT = os.path.join(BASE_DIR, 'static')
| [
"tommy.tang@rbccm.com"
] | tommy.tang@rbccm.com |
bfa3bf4ddd1e536eee8ccd20e64290b2565cec39 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p03945/s800732169.py | 5d9f0dfa4044f793cd90924fc2efff0bfe5ae8fe | [] | no_license | Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 111 | py | line = list(input())
temp = line[0]
cnt = 0
for c in line[1:]:
if temp != c:
cnt += 1
temp = c
print(cnt) | [
"66529651+Aastha2104@users.noreply.github.com"
] | 66529651+Aastha2104@users.noreply.github.com |
dbea34b24e0169d9a319879a40f7625e53d7c6d2 | 0ce0e8ea2d4637b0825edfbe7bbd581ea2063c28 | /casescms/wsgi.py | 64b398c9e0334f247922062b235f2b682318057d | [] | no_license | tmusters/casescms | e6ecc96c5600f3e01a8ed2fb3cc00aa0358f9de3 | 6f41cd6e4709144e5ac8a375ed5a55bc561572ce | refs/heads/master | 2021-01-01T06:15:25.253609 | 2017-07-16T20:14:35 | 2017-07-16T20:14:35 | 97,394,769 | 0 | 0 | null | 2017-07-16T20:14:36 | 2017-07-16T16:08:15 | Python | UTF-8 | Python | false | false | 394 | py | """
WSGI config for casescms project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/1.11/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "casescms.settings")
application = get_wsgi_application()
| [
"tmusters@gmail.com"
] | tmusters@gmail.com |
5b0c9cf44a0fe6ae809bd608a0f229a4c1f18b66 | 4ce666c4ddc227a4a8afd6ebd185fc4a2fb6aed5 | /API/app.py | c3b4e157e3409803fe4872285a06fbfdc4e4ae29 | [] | no_license | Shrirama-Upadhya-A/Indoor_navigation_system-1 | 69b2fc212e44161dcc2659835450193b068c9e20 | e1cb0e01cf8fe094f35faf09dd4ca235040bc68a | refs/heads/master | 2022-03-21T18:10:50.830277 | 2019-10-21T11:13:25 | 2019-10-21T11:13:25 | 216,563,853 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,776 | py | from flask import Flask
from math import sin, cos, atan2, sqrt, pi
from flask import jsonify, request
import googlemaps
import os
import pandas as pd
PORT = 8000
app = Flask(__name__)
r_earth = 6378
def get_distance(slat, slng, vlat, vlng):
dlon = vlng - slng
dlat = vlat - slat
a = (sin(dlat/2))**2 + cos(slat) * cos(vlat) * (sin(dlon/2))**2
c = 2 * atan2(sqrt(a), sqrt(1-a))
distance = r_earth * c
return distance
@app.route('/grid_data', methods = ['POST'])
def grid_data():
data_in = request.json['data']
print(data_in)
latitude = request.json['data']['lat']
longitude = request.json['data']['lng']
count = 0
result_list = []
for i in range(-30, 30, 2):
for j in range(-30, 30, 2):
new_latitude = latitude + (i/1000 / r_earth) * (180 / pi)
new_longitude = longitude + (j/1000 / r_earth) * (180 / pi) / cos(latitude * pi/180)
count += 1
if new_latitude > latitude and new_longitude > longitude:
quad = 1
elif new_latitude < latitude and new_longitude > longitude:
quad = 2
elif new_latitude < latitude and new_longitude < longitude:
quad = 3
elif new_longitude > latitude and new_longitude < longitude:
quad = 4
result = {
'gid' : count,
'lat' : new_latitude,
'lng' : new_longitude,
'quad' : quad
}
result_list.append(result)
return jsonify(result=result_list)
@app.route('/grid_id', methods = ["POST"])
def grid_id():
data_in = request.json['data']
user_lat = request.json['data']['user_lat']
user_lng = request.json['data']['user_lng']
home_lat = request.json['data']['home_lat']
home_lng = request.json['data']['home_lng']
count = 0
result_list = []
for i in range(-30, 30, 2):
for j in range(-30, 30, 2):
new_latitude = home_lat + (i/1000 / r_earth) * (180 / pi)
new_longitude = home_lng + (j/1000 / r_earth) * (180 / pi) / cos(home_lat * pi/180)
count += 1
if new_latitude > home_lat and new_longitude > home_lng:
quad = 1
elif new_latitude < home_lat and new_longitude > home_lng:
quad = 2
elif new_latitude < home_lat and new_longitude < home_lng:
quad = 3
elif new_longitude > home_lat and new_longitude < home_lng:
quad = 4
result = {
'gid' : count,
'lat' : new_latitude,
'lng' : new_longitude,
'quad' : quad
}
result_list.append(result)
get_df = pd.DataFrame(result_list)
if user_lat > home_lat and user_lng > home_lng:
quad = 1
elif user_lat < home_lat and user_lng > home_lng:
quad = 2
elif user_lat < home_lat and user_lng < home_lng:
quad = 3
elif user_lat > home_lat and user_lng < home_lng:
quad = 4
user_range = get_df.loc[get_df['quad'] == quad]
user_range = user_range.reset_index()
user_range = user_range.drop(['index'], axis = 1)
min_distance = {
"gid" : 0,
"distance" : 10000
}
for i in range(user_range.shape[0]):
slat = user_range['lat'][i]
slng = user_range['lng'][i]
gid = user_range['gid'][i]
dist = get_distance(slat, slng, user_lat, user_lng)
if min_distance['distance'] > dist:
min_distance = {
"gid" : gid,
"distance" : dist
}
return jsonify(result = str(min_distance))
if __name__ == '__main__':
app.run(port=PORT, debug=True)
| [
"varun.muniaplle2017@vitstudent.ac.in"
] | varun.muniaplle2017@vitstudent.ac.in |
19c80295cf35ec53845b2aaba74ba2f9db072b47 | 30645acd9cd6bc9624603789706fbf76e2ac9822 | /Number Data type.py | 2209d5840e04d94b26ced311e643502405b1f41d | [] | no_license | Sahil4UI/PythonNewSept2020 | 9ba059b2e6d94ee8a6879d603c1d1d887643bbee | 6be4c6294f0df1d60fbf221c092bf3a409e94d32 | refs/heads/master | 2022-12-20T21:40:15.969728 | 2020-10-04T14:26:31 | 2020-10-04T14:26:31 | 299,897,378 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,275 | py | Python 3.7.8 (v3.7.8:4b47a5b6ba, Jun 27 2020, 04:47:50)
[Clang 6.0 (clang-600.0.57)] on darwin
Type "help", "copyright", "credits" or "license()" for more information.
>>> num1 = 10
>>> num2 = 7
>>> num1-num2
3
>>> num1+num2
17
>>> num1*num2
70
>>> num1/num2
1.4285714285714286
>>> #floor division
>>> num1//num2
1
>>> 22/7
3.142857142857143
>>> 22//7
3
>>> 5**3
125
>>> #**->power
>>> 10**3
1000
>>> 10**4
10000
>>> 22%7
1
>>> 5%2
1
>>> 10%6
4
>>> 9%6
3
>>> import math
>>> math.sqrt(25)
5.0
>>> math.sqrt(3)
1.7320508075688772
>>> math.sqrt(2)
1.4142135623730951
>>> math.gcd(10,20)
10
>>> math.gcd(6,9)
3
>>> math.factorial(5)
120
>>> 5*4*3*2*1
120
>>> math.fabs(90)
90.0
>>> math.fabs(-90)
90.0
>>> math.ceil(90)
90
>>> math.ceil(90.9)
91
>>> math.ceil(90.02)
91
>>> math.ceil(78.2)
79
>>> help(math)
Help on module math:
NAME
math
MODULE REFERENCE
https://docs.python.org/3.7/library/math
The following documentation is automatically generated from the Python
source files. It may be incomplete, incorrect or include features that
are considered implementation detail and may vary between Python
implementations. When in doubt, consult the module reference at the
location listed above.
DESCRIPTION
This module provides access to the mathematical functions
defined by the C standard.
FUNCTIONS
acos(x, /)
Return the arc cosine (measured in radians) of x.
acosh(x, /)
Return the inverse hyperbolic cosine of x.
asin(x, /)
Return the arc sine (measured in radians) of x.
asinh(x, /)
Return the inverse hyperbolic sine of x.
atan(x, /)
Return the arc tangent (measured in radians) of x.
atan2(y, x, /)
Return the arc tangent (measured in radians) of y/x.
Unlike atan(y/x), the signs of both x and y are considered.
atanh(x, /)
Return the inverse hyperbolic tangent of x.
ceil(x, /)
Return the ceiling of x as an Integral.
This is the smallest integer >= x.
copysign(x, y, /)
Return a float with the magnitude (absolute value) of x but the sign of y.
On platforms that support signed zeros, copysign(1.0, -0.0)
returns -1.0.
cos(x, /)
Return the cosine of x (measured in radians).
cosh(x, /)
Return the hyperbolic cosine of x.
degrees(x, /)
Convert angle x from radians to degrees.
erf(x, /)
Error function at x.
erfc(x, /)
Complementary error function at x.
exp(x, /)
Return e raised to the power of x.
expm1(x, /)
Return exp(x)-1.
This function avoids the loss of precision involved in the direct evaluation of exp(x)-1 for small x.
fabs(x, /)
Return the absolute value of the float x.
factorial(x, /)
Find x!.
Raise a ValueError if x is negative or non-integral.
floor(x, /)
Return the floor of x as an Integral.
This is the largest integer <= x.
fmod(x, y, /)
Return fmod(x, y), according to platform C.
x % y may differ.
frexp(x, /)
Return the mantissa and exponent of x, as pair (m, e).
m is a float and e is an int, such that x = m * 2.**e.
If x is 0, m and e are both 0. Else 0.5 <= abs(m) < 1.0.
fsum(seq, /)
Return an accurate floating point sum of values in the iterable seq.
Assumes IEEE-754 floating point arithmetic.
gamma(x, /)
Gamma function at x.
gcd(x, y, /)
greatest common divisor of x and y
hypot(x, y, /)
Return the Euclidean distance, sqrt(x*x + y*y).
isclose(a, b, *, rel_tol=1e-09, abs_tol=0.0)
Determine whether two floating point numbers are close in value.
rel_tol
maximum difference for being considered "close", relative to the
magnitude of the input values
abs_tol
maximum difference for being considered "close", regardless of the
magnitude of the input values
Return True if a is close in value to b, and False otherwise.
For the values to be considered close, the difference between them
must be smaller than at least one of the tolerances.
-inf, inf and NaN behave similarly to the IEEE 754 Standard. That
is, NaN is not close to anything, even itself. inf and -inf are
only close to themselves.
isfinite(x, /)
Return True if x is neither an infinity nor a NaN, and False otherwise.
isinf(x, /)
Return True if x is a positive or negative infinity, and False otherwise.
isnan(x, /)
Return True if x is a NaN (not a number), and False otherwise.
ldexp(x, i, /)
Return x * (2**i).
This is essentially the inverse of frexp().
lgamma(x, /)
Natural logarithm of absolute value of Gamma function at x.
log(...)
log(x, [base=math.e])
Return the logarithm of x to the given base.
If the base not specified, returns the natural logarithm (base e) of x.
log10(x, /)
Return the base 10 logarithm of x.
log1p(x, /)
Return the natural logarithm of 1+x (base e).
The result is computed in a way which is accurate for x near zero.
log2(x, /)
Return the base 2 logarithm of x.
modf(x, /)
Return the fractional and integer parts of x.
Both results carry the sign of x and are floats.
pow(x, y, /)
Return x**y (x to the power of y).
radians(x, /)
Convert angle x from degrees to radians.
remainder(x, y, /)
Difference between x and the closest integer multiple of y.
Return x - n*y where n*y is the closest integer multiple of y.
In the case where x is exactly halfway between two multiples of
y, the nearest even value of n is used. The result is always exact.
sin(x, /)
Return the sine of x (measured in radians).
sinh(x, /)
Return the hyperbolic sine of x.
sqrt(x, /)
Return the square root of x.
tan(x, /)
Return the tangent of x (measured in radians).
tanh(x, /)
Return the hyperbolic tangent of x.
trunc(x, /)
Truncates the Real x to the nearest Integral toward 0.
Uses the __trunc__ magic method.
DATA
e = 2.718281828459045
inf = inf
nan = nan
pi = 3.141592653589793
tau = 6.283185307179586
FILE
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/lib-dynload/math.cpython-37m-darwin.so
>>> math.floor(10.234242)
10
>>> 10**3
1000
>>> math.pow(10,3)
1000.0
>>> math.remainder(10,7)
3.0
>>> math.sqrt(90.87)
9.532575727472612
>>> #complex number
>>> x = 1+5z
SyntaxError: invalid syntax
>>> x = 1+5j
>>> x.real
1.0
>>> x.imag
5.0
>>> a=2+3j
>>> b=1+4j
>>> a+b
(3+7j)
>>> a-b
(1-1j)
>>> a*b
(-10+11j)
>>> a/b
(0.8235294117647058-0.29411764705882354j)
>>> | [
"noreply@github.com"
] | Sahil4UI.noreply@github.com |
8fdc36cb05bf5f2c8b637c9259fdc760acc76965 | b67efb7ac1832f2a70aa570f8025c69498a8cd71 | /setup.py | a56b26ffcf01291aa8264b1ca3a35448338471e2 | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT"
] | permissive | PogoHop/pgoapi-hsvr | f1513d7548075a7defd21f1018bd59afcb79d78f | b5761159e0240bbb81ef6c257fe2eb1bc1ce2d47 | refs/heads/master | 2021-01-12T11:17:55.334203 | 2016-11-05T12:48:38 | 2016-11-05T12:48:38 | 72,892,081 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 652 | py | #!/usr/bin/env python
import os
from setuptools import setup, find_packages
from pip.req import parse_requirements
setup_dir = os.path.dirname(os.path.realpath(__file__))
path_req = os.path.join(setup_dir, 'requirements.txt')
install_reqs = parse_requirements(path_req, session=False)
reqs = [str(ir.req) for ir in install_reqs]
setup(name='pgoapi',
author = 'tjado',
description = 'Pokemon Go API lib',
version = '1.1.6',
url = 'https://github.com/tejado/pgoapi',
download_url = "https://github.com/tejado/pgoapi/releases",
packages = find_packages(),
install_requires = reqs,
)
| [
"hoptional@gmail.com"
] | hoptional@gmail.com |
abb210cef1a84d366213fcde9dcbe381d737a29d | 143604a4668d4ccad1162e9ecfebe4e8839344de | /tests/util/test_price_extractor.py | 33cef22074129c595c003f3b559aa682bbe7b426 | [] | no_license | lzy7071/portfolio_tools | 58c86f8eded670b8e1f5f0b45c8aadadc4e091c3 | f688e22258e29c275e1d692b14a59d65f6e3f2a1 | refs/heads/master | 2020-09-06T00:30:18.364057 | 2020-03-11T20:26:23 | 2020-03-11T20:26:23 | 220,259,091 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 789 | py | import unittest
from portfolio_tools.util import price_extractor
import datetime as dt
class TestPriceExtractor(unittest.TestCase):
@classmethod
def setUpClass(cls):
companies = ['AAPL', 'GOOG']
cls.src = price_extractor.PriceExtractor(companies)
def test_price_extractor(self):
end_date_0 = dt.date(2019, 11, 6)
start_date_0 = dt.date(2019, 10, 27)
result_0 = self.src.get_prices(start_date_0, end_date_0)
self.assertAlmostEqual(result_0.loc['2019-10-28']['AAPL'], 248.3045196533203)
end_date_1 = dt.date(2019, 10, 27)
start_date_1 = dt.date(2019, 10, 27)
result_1 = self.src.get_prices(start_date_1, end_date_1)
self.assertAlmostEqual(result_1.loc['2019-10-28']['AAPL'], 248.3045196533203) | [
"zhouyang.lian@familian.life"
] | zhouyang.lian@familian.life |
8a5cbffd89ae328c913b84e3de4a409169ecddd1 | 86f860eab66ce0681cda293ee063e225747d113c | /Python_Collections/Sets/operations_set.py | 13d74e26c0b77fbdfb1b797616826e75fc456587 | [] | no_license | tkj5008/Luminar_Python_Programs | a1e7b85ad2b7537081bdedad3a5a4a2d9f6c1f07 | d47ef0c44d5811e7039e62938a90a1de0fe7977b | refs/heads/master | 2023-08-03T05:15:04.963129 | 2021-09-23T14:33:21 | 2021-09-23T14:33:21 | 403,316,476 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 144 | py | #1union
#2Intersection
#3Difference
a={1,2,3,4,5,6,7,8,9}
b={3,5,4,6,7,8,9,10}
print(a.union(b))
print(a.intersection(b))
print(a.difference(b)) | [
"thomas@gmail.com"
] | thomas@gmail.com |
ebe439ef72b5d614dd23234e7bcadf7d5fe6285a | 1d474eff74e7b83bc2fd4a52bdcb47cd1eb906d4 | /library/graph.py | a8916f44b2c28f94a9c793220de77b61bdbab2a7 | [] | no_license | spirosmastorakis/FSP_Engine | 4d7a5cbc495dfee8268e8e9e3bd8496cf2b74ecc | be06e767151babf3c9d02681770d54aa5543a646 | refs/heads/master | 2021-01-23T10:00:35.327934 | 2014-05-14T15:13:36 | 2014-05-14T15:13:36 | 19,502,402 | 3 | 2 | null | null | null | null | UTF-8 | Python | false | false | 4,456 | py | #!/usr/bin/env python
'''
Library functions for working w/graphs that are not specific to an algorithm.
'''
import logging
import networkx as nx
lg = logging.getLogger("cc")
def flatten(paths):
'''Compute and return flattened graph, given paths.
By flattened graph, we mean one created from the union of a set of paths.
@param paths: paths to flatten
@return flattened: flattened NetworkX Graph
'''
used = nx.Graph()
lg.debug("paths: %s" % paths)
for path in paths.values():
lg.debug("flattening path: %s" % path)
used.add_path(path)
return used
def loop_graph(n):
'''Return loop graph with n nodes.'''
g = nx.path_graph(n)
# Add loop edge
g.add_edge(g.number_of_nodes() - 1, 0)
return g
def set_unit_weights(g):
'''Set edge weights for NetworkX graph to 1 & return.'''
set_weights(g, 1.0)
def set_weights(g, weight):
'''Set edge weights for NetworkX graph to specified weight & return.'''
for src, dst in g.edges():
g[src][dst]['weight'] = weight
return g
def nx_graph_from_tuples(undir_tuples, dir_tuples = None):
g = nx.Graph()
for a, b, w in undir_tuples:
g.add_edge(a, b, weight = w)
if dir_tuples:
g = nx.DiGraph(g)
for a, b, w in dir_tuples:
g.add_edge(a, b, weight = w)
return g
def vertex_disjoint(paths):
'''Check if provided paths are vertex-disjoint.
@param paths: list of path lists
'''
vertices = set([])
for path in paths:
for n in path:
if n in vertices:
return False
vertices.add(n)
return True
def edge_disjoint(paths):
'''Check if provided paths are edge-disjoint.
@param paths: list of path lists
'''
edges = set([])
# Ensure edge disjointness
for path in paths:
for i, n in enumerate(path):
if i != len(path) - 1:
e = (n, path[i + 1])
if e in edges:
return False
edges.add(e)
e_rev = (path[i + 1], n)
if e_rev in edges:
return False
edges.add(e_rev)
return True
def pathlen(g, path):
'''Return sum of path weights.
@param g: NetworkX Graph
@param path: list of nodes
@return length: sum of path weights
'''
pathlen = 0
for i, n in enumerate(path):
if i != len(path) - 1:
pathlen += g[n][path[i+1]]['weight']
return pathlen
def edges_on_path(l):
'''Return list of edges on a path list.'''
return [(l[i], l[i + 1]) for i in range(len(l) - 1)]
def interlacing_edges(list1, list2):
'''Return edges in common between two paths.
Input paths are considered interlacing, even if they go in the opposite
direction across the same link. In that case, a single edge will be
return in whatever order NetworkX prefers for an undirected edge.
'''
l1 = edges_on_path(list1)
l1.extend(edges_on_path([i for i in reversed(list1)]))
l2 = edges_on_path(list2)
l2.extend(edges_on_path([i for i in reversed(list2)]))
combined = [e for e in l1 if e in l2]
return nx.Graph(combined).edges()
def flip_and_negate_path(g, path):
'''Return new directed graph with the given path flipped & negated.
@param g: NetworkX Graph (undirected)
@param path: list of nodes in path
@return g2: NetworkX DiGraph, modified
'''
g2 = nx.DiGraph(g)
for i, n in enumerate(path):
if i != len(path) - 1:
n_next = path[i + 1]
# Remove forward edge, leaving only reverse edge.
g2.remove_edge(n, n_next)
# Flip edge weight to negative of the original edge..
g2[n_next][n]['weight'] *= -1
return g2
def remove_edge_bidir(g, src, dst):
'''Remove edge plus one in opposite direction.
@param g: NetworkX DiGraph
@param src: source node
@param dst: destination node
'''
g.remove_edge(src, dst)
g.remove_edge(dst, src)
def add_edge_bidir(g, src, dst, weight = None):
'''Add edge plus one in opposite direction.
@param g: NetworkX DiGraph
@param src: source node
@param dst: destination node
@param weight: optional weight to set for both
'''
g.add_edge(src, dst)
g.add_edge(dst, src)
if weight:
g[src][dst]['weight'] = weight
g[dst][src]['weight'] = weight
| [
"spiros.mastorakis@gmail.com"
] | spiros.mastorakis@gmail.com |
d484570a7c3dc8fd04ecadb2edb816aaf3e2f4fd | aee507b29648fa3f05eaab130d04e7c03f24448c | /Task1.py | b88d6187fe2037f3ade2b220007fd0227b8edaa6 | [] | no_license | AkshadK7/Advanced_Programming_Python | e319fa83d361e71c507add3e9ca1a815c8754f5d | 16cfff53ecae5b7d91d9d0b4100c1f4904ecb30d | refs/heads/main | 2023-04-03T02:20:12.549956 | 2021-04-07T07:03:07 | 2021-04-07T07:03:07 | 336,991,398 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 456 | py | """
Q] Using a for loop, print a table of powers of x, where x ranges from 1 to 10. For each
value x, print the quantity x, x^2 and x^3 . Using tab characters in your print statement
to make the values line up nicely.
"""
# Program :
# Iterate 10 times from x = 1 to 10
for x in range(1, 11):
print( "For value of x : ", x)
print(x, '^', 2, '=', x**2)
print(x, '^', 3, '=', x**3)
print("\t")
# Copyright © 2020 by Akshad Kolhatkar
| [
"noreply@github.com"
] | AkshadK7.noreply@github.com |
8e7a504cb3086bd4ccec033b8f92e9008b8f392a | aea8fea216234fd48269e4a1830b345c52d85de2 | /fhir/resources/DSTU2/tests/test_healthcareservice.py | 54d52d232e42e533c559cbf4f0677d3b24adfda6 | [
"BSD-3-Clause"
] | permissive | mmabey/fhir.resources | 67fce95c6b35bfdc3cbbc8036e02c962a6a7340c | cc73718e9762c04726cd7de240c8f2dd5313cbe1 | refs/heads/master | 2023-04-12T15:50:30.104992 | 2020-04-11T17:21:36 | 2020-04-11T17:21:36 | 269,712,884 | 0 | 0 | NOASSERTION | 2020-06-05T17:03:04 | 2020-06-05T17:03:04 | null | UTF-8 | Python | false | false | 6,521 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Generated from FHIR 1.0.2.7202 on 2019-05-14.
# 2019, SMART Health IT.
import io
import json
import os
import unittest
from . import healthcareservice
from .fhirdate import FHIRDate
class HealthcareServiceTests(unittest.TestCase):
def instantiate_from(self, filename):
datadir = os.environ.get("FHIR_UNITTEST_DATADIR") or ""
with io.open(os.path.join(datadir, filename), "r", encoding="utf-8") as handle:
js = json.load(handle)
self.assertEqual("HealthcareService", js["resourceType"])
return healthcareservice.HealthcareService(js)
def testHealthcareService1(self):
inst = self.instantiate_from("healthcareservice-example.json")
self.assertIsNotNone(
inst, "Must have instantiated a HealthcareService instance"
)
self.implHealthcareService1(inst)
js = inst.as_json()
self.assertEqual("HealthcareService", js["resourceType"])
inst2 = healthcareservice.HealthcareService(js)
self.implHealthcareService1(inst2)
def implHealthcareService1(self, inst):
self.assertFalse(inst.appointmentRequired)
self.assertEqual(
inst.availabilityExceptions,
"Reduced capacity is available during the Christmas period",
)
self.assertEqual(
inst.availableTime[0].availableEndTime.date, FHIRDate("05:30:00").date
)
self.assertEqual(inst.availableTime[0].availableEndTime.as_json(), "05:30:00")
self.assertEqual(
inst.availableTime[0].availableStartTime.date, FHIRDate("08:30:00").date
)
self.assertEqual(inst.availableTime[0].availableStartTime.as_json(), "08:30:00")
self.assertEqual(inst.availableTime[0].daysOfWeek[0], "mon")
self.assertEqual(inst.availableTime[0].daysOfWeek[1], "tue")
self.assertEqual(inst.availableTime[0].daysOfWeek[2], "wed")
self.assertEqual(inst.availableTime[0].daysOfWeek[3], "thu")
self.assertEqual(inst.availableTime[0].daysOfWeek[4], "fri")
self.assertEqual(
inst.availableTime[1].availableEndTime.date, FHIRDate("04:30:00").date
)
self.assertEqual(inst.availableTime[1].availableEndTime.as_json(), "04:30:00")
self.assertEqual(
inst.availableTime[1].availableStartTime.date, FHIRDate("09:30:00").date
)
self.assertEqual(inst.availableTime[1].availableStartTime.as_json(), "09:30:00")
self.assertEqual(inst.availableTime[1].daysOfWeek[0], "sat")
self.assertEqual(inst.availableTime[1].daysOfWeek[1], "fri")
self.assertEqual(inst.characteristic[0].coding[0].display, "Wheelchair access")
self.assertEqual(
inst.comment,
"Providing Specialist psychology services to the greater Den Burg area, many years of experience dealing with PTSD issues",
)
self.assertEqual(inst.contained[0].id, "DenBurg")
self.assertEqual(inst.eligibility.coding[0].display, "DVA Required")
self.assertEqual(
inst.eligibilityNote,
"Evidence of application for DVA status may be sufficient for commencing assessment",
)
self.assertEqual(inst.id, "example")
self.assertEqual(inst.notAvailable[0].description, "Christmas/Boxing Day")
self.assertEqual(
inst.notAvailable[0].during.end.date, FHIRDate("2015-12-26").date
)
self.assertEqual(inst.notAvailable[0].during.end.as_json(), "2015-12-26")
self.assertEqual(
inst.notAvailable[0].during.start.date, FHIRDate("2015-12-25").date
)
self.assertEqual(inst.notAvailable[0].during.start.as_json(), "2015-12-25")
self.assertEqual(inst.notAvailable[1].description, "New Years Day")
self.assertEqual(
inst.notAvailable[1].during.end.date, FHIRDate("2016-01-01").date
)
self.assertEqual(inst.notAvailable[1].during.end.as_json(), "2016-01-01")
self.assertEqual(
inst.notAvailable[1].during.start.date, FHIRDate("2016-01-01").date
)
self.assertEqual(inst.notAvailable[1].during.start.as_json(), "2016-01-01")
self.assertEqual(inst.programName[0], "PTSD outreach")
self.assertEqual(
inst.publicKey,
"*** Base64 public key goes here to be used for secure messaging ***",
)
self.assertEqual(inst.referralMethod[0].coding[0].code, "phone")
self.assertEqual(inst.referralMethod[0].coding[0].display, "Phone")
self.assertEqual(inst.referralMethod[1].coding[0].code, "fax")
self.assertEqual(inst.referralMethod[1].coding[0].display, "Fax")
self.assertEqual(inst.referralMethod[2].coding[0].code, "elec")
self.assertEqual(inst.referralMethod[2].coding[0].display, "Secure Messaging")
self.assertEqual(inst.referralMethod[3].coding[0].code, "semail")
self.assertEqual(inst.referralMethod[3].coding[0].display, "Secure Email")
self.assertEqual(
inst.serviceName, "Consulting psychologists and/or psychology services"
)
self.assertEqual(inst.serviceType[0].type.coding[0].code, "394913002")
self.assertEqual(inst.serviceType[0].type.coding[0].display, "Psychotherapy")
self.assertEqual(
inst.serviceType[0].type.coding[0].system, "http://snomed.info/sct"
)
self.assertEqual(inst.serviceType[1].specialty[0].coding[0].code, "47505003")
self.assertEqual(
inst.serviceType[1].specialty[0].coding[0].display,
"Posttraumatic stress disorder",
)
self.assertEqual(
inst.serviceType[1].specialty[0].coding[0].system, "http://snomed.info/sct"
)
self.assertEqual(inst.serviceType[1].type.coding[0].code, "394587001")
self.assertEqual(inst.serviceType[1].type.coding[0].display, "Psychiatry")
self.assertEqual(
inst.serviceType[1].type.coding[0].system, "http://snomed.info/sct"
)
self.assertEqual(inst.telecom[0].system, "phone")
self.assertEqual(inst.telecom[0].use, "work")
self.assertEqual(inst.telecom[0].value, "(555) silent")
self.assertEqual(inst.telecom[1].system, "email")
self.assertEqual(inst.telecom[1].use, "work")
self.assertEqual(inst.telecom[1].value, "directaddress@example.com")
self.assertEqual(inst.text.status, "generated")
| [
"connect2nazrul@gmail.com"
] | connect2nazrul@gmail.com |
2eae2bccc3471614f6e26c9a445bc3a0e63bd35d | 92d8db95c71bbf851a2fed6c909bbf5dc3967e9c | /activity/views.py | 21f687581bbee4a7f1cc1fb9102ec8317ac17e85 | [] | no_license | HuShuai666/test | 68a77ea23bcf1f20d7a56e0f5fc8ae182bb30016 | 9d9cc50acf2f9e48f6a62b478a55bd01a0b0c0fb | refs/heads/master | 2020-04-01T10:39:40.469584 | 2018-10-15T15:41:25 | 2018-10-15T15:41:25 | 153,126,100 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,137 | py | import uuid
from rest_framework.response import Response
from rest_framework.views import APIView
from activity.models import Activity, Coupon, Notice
from activity.serializers import ActivitySerializer, NoticeSerializer
from rest_framework import exceptions, serializers
from authentication.models import User
from common.NewCornType import NewCornType
from register.models import Register, NewCornRecord
from common.execute_sql import dict_fetchall
import logging
logger = logging.getLogger('django')
class ActivityView(APIView):
def get(self, request):
params = request.query_params
if not params.get('name'):
raise exceptions.ValidationError('参数name(活动名称)不能为空')
activity = Activity.objects.filter(name=params.get('name'))
if not activity:
raise exceptions.ValidationError('未查询到当前活动信息')
serializer = ActivitySerializer(activity[0])
result = serializer.data
# 查询报名表中报名人数
user_count = Register.objects.filter(activity=1).count()
result['user_count'] = user_count
return Response(result)
class ActivityStartAtView(APIView):
def get(self, request):
params = request.query_params
if not params.get('name'):
raise exceptions.ValidationError('参数name(活动名称)不能为空')
activity = Activity.objects.filter(name=params.get('name'))
if not activity:
raise exceptions.ValidationError('未查询到当前活动信息')
serializer = ActivitySerializer(activity[0])
result = serializer.data
return Response(result['start_at'])
class CornView(APIView):
def get(self, request):
params = request.query_params
other_open_id = params.get('other_open_id')
nickname = params.get('nickname')
logger.info('*' * 70)
logger.info(params)
logger.info('*' * 70)
# 获取邀请码
coupon = params.get('coupon')
if not all((coupon, other_open_id, nickname)):
raise serializers.ValidationError('参数(coupon, other_open_id, nickname)均不能为空')
coupon = Coupon.objects.filter(code=coupon).first()
if not coupon:
raise serializers.ValidationError('您的优惠券码无效哦')
user = User.objects.filter(nick_name=nickname).first()
if not user:
raise serializers.ValidationError('您还未报名参加CP活动馆哦')
new_corn_record = NewCornRecord.objects.filter(operation=NewCornType.ACTIVITY_DONATE.value,
other_open_id=other_open_id, nickname=nickname,
coupon=coupon.code).first()
if new_corn_record:
raise serializers.ValidationError('您已使用过优惠券哦')
balance_record = NewCornRecord.objects.filter(user_id=user.open_id).latest('create_at')
NewCornRecord.objects.create(id=str(uuid.uuid4()), user_id=user.open_id,
operation=NewCornType.ACTIVITY_DONATE.value,
corn=coupon.corn, balance=balance_record.balance + coupon.corn,
extra='优惠券' + coupon.code + '赠送',
other_open_id=other_open_id, nickname=nickname, coupon=coupon.code)
return Response('优惠券使用成功，您已成功获得' + str(coupon.corn) + 'New币')
class NoticeView(APIView):
def get(self, request):
params = request.query_params
notice_id = params.get('notice_id')
if not notice_id:
raise serializers.ValidationError('参数notice_id不能为空')
notice = Notice.objects.filter(id=notice_id).first()
return Response(NoticeSerializer(notice).data)
class TestView(APIView):
def get(self, request):
sql = 'SELECT invitee,COUNT(*) as number from invitation GROUP BY invitee'
result = dict_fetchall(sql)
print(result)
return Response(result)
| [
"2313153604@qq.com"
] | 2313153604@qq.com |
cfe6fab25c27790ec99d7f067e35d953cc60db87 | 0b7c51035767007871302df94215ff56e6d10447 | /assessment/views.py | f59f80ed5fc82e35bd3befb5c3ccfd09e748796a | [] | no_license | judeakinwale/sms-lotus | d6c60f99fab55d040779f0255796e89a02465512 | 96bc60212066946cac247f5142f0bc44988372a1 | refs/heads/master | 2023-07-06T10:44:37.601515 | 2021-08-06T10:34:52 | 2021-08-06T10:34:52 | 379,289,006 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,704 | py | from django.shortcuts import render
from rest_framework import viewsets, permissions
from assessment import models, serializers
# Create your views here.
class QuizViewSet(viewsets.ModelViewSet):
queryset = models.Quiz.objects.all()
serializer_class = serializers.QuizSerializer
permission_classes = [permissions.IsAuthenticated | permissions.IsAdminUser]
def perform_create(self, serializer):
return serializer.save(supervisor=self.request.user)
class QuestionViewSet(viewsets.ModelViewSet):
queryset = models.Question.objects.all()
serializer_class = serializers.QuestionSerializer
permission_classes = [permissions.IsAuthenticated | permissions.IsAdminUser]
class AnswerViewSet(viewsets.ModelViewSet):
queryset = models.Answer.objects.all()
serializer_class = serializers.AnswerSerializer
permission_classes = [permissions.IsAuthenticated | permissions.IsAdminUser]
class QuizTakerViewSet(viewsets.ModelViewSet):
queryset = models.QuizTaker.objects.all()
serializer_class = serializers.QuizTakerSerializer
permission_classes = [permissions.IsAuthenticated | permissions.IsAdminUser]
def perform_create(self, serializer):
return serializer.save(student=self.request.user)
class ResponseViewSet(viewsets.ModelViewSet):
queryset = models.Response.objects.all()
serializer_class = serializers.ResponseSerializer
permission_classes = [permissions.IsAuthenticated | permissions.IsAdminUser]
class GradeViewSet(viewsets.ModelViewSet):
queryset = models.Grade.objects.all()
serializer_class = serializers.GradeSerializer
permission_classes = [permissions.IsAuthenticated | permissions.IsAdminUser]
| [
"judeakinwale@gmail.com"
] | judeakinwale@gmail.com |
b61e98b1e283ec7cc661c9f391b485c013e7a4b8 | 249a27b7617ca6eb3858016e63d1d9b4a8de1bff | /Script/Scanner de portas.py | a9b0e95d4ea55d399d54626b51bb00284c822869 | [
"MIT"
] | permissive | Samio-Santos/Scanner-de-portas | 634ef8c8574df7ff1be44c49c6a09399ace65720 | 16989150d4a618cd231a8d42513e2d7f6c369b84 | refs/heads/master | 2022-12-17T09:45:33.975707 | 2020-09-25T12:13:28 | 2020-09-25T12:13:28 | 298,557,240 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 826 | py | import socket
# Este script faz uma varredura e verifica quais portas estão abertas na rede.
def portscan(porta):
# Inserir o endereço ip local, por exemplo:
target = '192.168.0.1'
try:
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
scann = sock.connect_ex((target, porta))
if scann == 0:
print(f'A porta {porta} está aberta!')
sock.close()
else:
print(f'A porta {porta} está fechada!')
except:
return False
# Parametros para iniciar a varredura.
inicio = int(input('Porta inicial: '))
fim = int(input('Porta Final: '))
# Percorre todas as portas indicadas e mostra quais estão abertas e fechadas.
# chama a funcão PORTSCAN e inicia o procedimento.
for port in range(inicio, fim):
result = portscan(port)
| [
"71763791+Samio-Santos@users.noreply.github.com"
] | 71763791+Samio-Santos@users.noreply.github.com |
3f2de76a80d22d0304eed9ec2ccc9329b56d3957 | 440c2f17a64b718227bbc9ac1f799630d0f3233d | /Chapter05_Tree&Recurison/leetcode104.py | c600ee29ff408abb6aacab4d442a1c91352b07b3 | [] | no_license | HuichuanLI/alogritme-interview | 6fc84fdbfe1123c1e587eaf2df6b6e9fb2ca7dda | 0ac672a1582707fcaa6b6ad1f2a1d927034447df | refs/heads/master | 2023-02-05T03:29:14.458783 | 2020-12-25T14:04:17 | 2020-12-25T14:04:17 | 206,583,220 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 379 | py | # class TreeNode(object):
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution(object):
def maxDepth(self, root):
"""
:type root: TreeNode
:rtype: int
"""
if not root:
return 0
return max(self.maxDepth(root.left), self.maxDepth(root.right)) + 1
| [
"lhc14124908@163.com"
] | lhc14124908@163.com |
9f7e1de8ee9ed5cd715f59c8bd334aafe1daa5e5 | c302d680691695ee1de91ff4c32d554b66ad39ee | /api/delete/deleteItem.py | fd6cef881b3b9c33c33d9b6b4f9abfbd83a98b5a | [] | no_license | abdullah-ezzat/pycommerce | 11e6aefa026ac5c154de2ac667930103b66bcd6d | 1acbd4a94c89c1001751c031992dbca6f921e83f | refs/heads/master | 2023-08-16T12:33:04.370271 | 2023-08-14T12:02:30 | 2023-08-14T12:02:30 | 364,235,542 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 579 | py | from django.views.decorators.csrf import csrf_exempt
from abc import ABC, abstractmethod
from django.http.response import JsonResponse
from PyCommerce.models import cartTransactions
class IDeleteCartItem(ABC):
@abstractmethod
def delete_cart_item():
pass
class DeleteCartItem():
@csrf_exempt
def delete_cart_item(self, request, id):
if request.method == "DELETE":
cartTransactions.objects.filter(id=id).delete()
return JsonResponse('Deleted Successfully', safe=False)
delete_cart_item = DeleteCartItem().delete_cart_item
| [
"abdullahmohamedezzat21@gmail.com"
] | abdullahmohamedezzat21@gmail.com |
f486c3b5e7cc5cacf8cda0420dc58fb8424142cd | 2975a9701876253807ea0c05bf84acd07375a6bb | /core/tests.py | f2a59a5ec6197aa96aea57e9f69e8e4f9496699f | [] | no_license | NeOneSoft/BackEndMusicaAPI | c8268b5e9825e4e62a4c3a59f760e5c75834fc93 | 84f6cb778d2779d06f665c7b3a1d9a3281160ab3 | refs/heads/master | 2020-09-16T02:42:08.381383 | 2019-11-28T03:26:32 | 2019-11-28T03:26:32 | 223,624,541 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,596 | py | from django.contrib.auth.models import User
from rest_framework.test import APITestCase
class TokenTestCase(APITestCase):
def setUp(self):
self.user = User.objects.create_user(username='admin', password='admin', email='admin@gmail.com')
def test_authenticate(self):
result = self.client.post('/api/token/', {'username': 'admin', 'password': 'admin'})
assert 'access' in result.data
def test_valid_token(self):
result = self.client.post('/api/token/', {'username': 'admin', 'password': 'admin'})
token = result.data['access']
canciones_result = self.client.get('/api/v1/canciones/', HTTP_AUTHORIZATION='Bearer ' + token)
artistas_result = self.client.get('/api/v1/artistas/', HTTP_AUTHORIZATION='Bearer ' + token)
albumes_result = self.client.get('/api/v1/albumes/', HTTP_AUTHORIZATION='Bearer ' + token)
assert canciones_result.status_code, artistas_result == 200
assert albumes_result.status_code == 200
def test_valid_token(self):
result = self.client.post('/api/token/', {'username': 'admin', 'password': 'admin'})
token = result.data['access']
canciones_result = self.client.get('/api/v1/canciones/', HTTP_AUTHORIZATION='Bearer ' + token)
artistas_result = self.client.get('/api/v1/artistas/', HTTP_AUTHORIZATION='Bearer ' + token)
albumes_result = self.client.get('/api/v1/albumes/', HTTP_AUTHORIZATION='Bearer ' + token)
assert canciones_result, artistas_result.status_code == 200
assert albumes_result.status_code == 200
| [
"gonclapton@hotmail.com"
] | gonclapton@hotmail.com |
c695b8c93d0f33cd8389af9d4481160cd350534f | 266f2f192f87d908edd004e8c6b25f97e0262953 | /.parts/lib/node_modules/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/android.py | d9bbfdaf2314426a58e3ca262531c4db075c35ce | [] | no_license | jnbishop/XTOL | 80578d6b014699c4925a72b2c94082bd75faa74a | 78ea7bb1f6f5b89724f36e325e7cd33d852a33b6 | refs/heads/master | 2020-04-01T18:42:04.636127 | 2015-02-16T06:04:19 | 2015-02-16T06:04:19 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 121 | py | /home/action/.parts/packages/nodejs/0.10.35/lib/node_modules/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/android.py | [
"georgeavidon@optonline.net"
] | georgeavidon@optonline.net |
4aee57ad10d37198d7d95147c0fef7f2a6ecd32b | 48e124e97cc776feb0ad6d17b9ef1dfa24e2e474 | /sdk/python/pulumi_azure_native/dbforpostgresql/v20210410privatepreview/get_firewall_rule.py | f871372b76ea0ee2e5bf9e82f4b45c99f9d34b68 | [
"BSD-3-Clause",
"Apache-2.0"
] | permissive | bpkgoud/pulumi-azure-native | 0817502630062efbc35134410c4a784b61a4736d | a3215fe1b87fba69294f248017b1591767c2b96c | refs/heads/master | 2023-08-29T22:39:49.984212 | 2021-11-15T12:43:41 | 2021-11-15T12:43:41 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,111 | py | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
__all__ = [
'GetFirewallRuleResult',
'AwaitableGetFirewallRuleResult',
'get_firewall_rule',
'get_firewall_rule_output',
]
@pulumi.output_type
class GetFirewallRuleResult:
"""
Represents a server firewall rule.
"""
def __init__(__self__, end_ip_address=None, id=None, name=None, start_ip_address=None, type=None):
if end_ip_address and not isinstance(end_ip_address, str):
raise TypeError("Expected argument 'end_ip_address' to be a str")
pulumi.set(__self__, "end_ip_address", end_ip_address)
if id and not isinstance(id, str):
raise TypeError("Expected argument 'id' to be a str")
pulumi.set(__self__, "id", id)
if name and not isinstance(name, str):
raise TypeError("Expected argument 'name' to be a str")
pulumi.set(__self__, "name", name)
if start_ip_address and not isinstance(start_ip_address, str):
raise TypeError("Expected argument 'start_ip_address' to be a str")
pulumi.set(__self__, "start_ip_address", start_ip_address)
if type and not isinstance(type, str):
raise TypeError("Expected argument 'type' to be a str")
pulumi.set(__self__, "type", type)
@property
@pulumi.getter(name="endIpAddress")
def end_ip_address(self) -> str:
"""
The end IP address of the server firewall rule. Must be IPv4 format.
"""
return pulumi.get(self, "end_ip_address")
@property
@pulumi.getter
def id(self) -> str:
"""
Fully qualified resource ID for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}
"""
return pulumi.get(self, "id")
@property
@pulumi.getter
def name(self) -> str:
"""
The name of the resource
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="startIpAddress")
def start_ip_address(self) -> str:
"""
The start IP address of the server firewall rule. Must be IPv4 format.
"""
return pulumi.get(self, "start_ip_address")
@property
@pulumi.getter
def type(self) -> str:
"""
The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
"""
return pulumi.get(self, "type")
class AwaitableGetFirewallRuleResult(GetFirewallRuleResult):
# pylint: disable=using-constant-test
def __await__(self):
if False:
yield self
return GetFirewallRuleResult(
end_ip_address=self.end_ip_address,
id=self.id,
name=self.name,
start_ip_address=self.start_ip_address,
type=self.type)
def get_firewall_rule(firewall_rule_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
server_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetFirewallRuleResult:
"""
Represents a server firewall rule.
:param str firewall_rule_name: The name of the server firewall rule.
:param str resource_group_name: The name of the resource group. The name is case insensitive.
:param str server_name: The name of the server.
"""
__args__ = dict()
__args__['firewallRuleName'] = firewall_rule_name
__args__['resourceGroupName'] = resource_group_name
__args__['serverName'] = server_name
if opts is None:
opts = pulumi.InvokeOptions()
if opts.version is None:
opts.version = _utilities.get_version()
__ret__ = pulumi.runtime.invoke('azure-native:dbforpostgresql/v20210410privatepreview:getFirewallRule', __args__, opts=opts, typ=GetFirewallRuleResult).value
return AwaitableGetFirewallRuleResult(
end_ip_address=__ret__.end_ip_address,
id=__ret__.id,
name=__ret__.name,
start_ip_address=__ret__.start_ip_address,
type=__ret__.type)
@_utilities.lift_output_func(get_firewall_rule)
def get_firewall_rule_output(firewall_rule_name: Optional[pulumi.Input[str]] = None,
resource_group_name: Optional[pulumi.Input[str]] = None,
server_name: Optional[pulumi.Input[str]] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetFirewallRuleResult]:
"""
Represents a server firewall rule.
:param str firewall_rule_name: The name of the server firewall rule.
:param str resource_group_name: The name of the resource group. The name is case insensitive.
:param str server_name: The name of the server.
"""
...
| [
"noreply@github.com"
] | bpkgoud.noreply@github.com |
d9a54f9de4ed2a12a022dcf1a3a8cdd5df4601ff | d512ad00318ec1e06f58551adf678be372e59d3a | /File_Controller_Tools(Python)/Example_Code/Day1/File_Remove.py | e56d55c1a556d11ca93540c3ed19920493b775ba | [] | no_license | john911120/Java_ToyProject | aeb337f16cfd06b755fcd1b3d67ad3a68d6f4352 | 71c17a6edc4836257d9b72954742c80746c88046 | refs/heads/master | 2022-11-18T04:53:41.278766 | 2020-07-18T07:08:39 | 2020-07-18T07:08:39 | 270,526,236 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 232 | py | from os import remove
target_file = 'Dn3CV3EUcAETK63_Copy.jpg'
k = input('[%s] 파일을 삭제 하겠습니까?(y/n)'%target_file)
if k == 'y':
remove(target_file)
print('[%s]를 삭제했습니다.'%target_file)
| [
"noreply@github.com"
] | john911120.noreply@github.com |
b50a6aedcddc9733aaad753d771efdeafd33fbcb | fd9dd0b4aea0f55e2b35529462bf5fa7bd4f9d33 | /pos_num.py | 36afd7e3ff6b919ccdd28b42839a0f21c2ace73d | [] | no_license | mraines4/Python_wk1 | 833a48f6576cb2130c02516c69a537a1a4e0f158 | 88bb07b706a67254d795e616412b2baf70217e6c | refs/heads/master | 2020-04-23T16:05:43.731860 | 2019-02-19T20:28:39 | 2019-02-19T20:28:39 | 171,286,541 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 87 | py | numbers = [16, 2, 3, -8, 5, 10]
for pos in numbers:
if pos > 0:
print(pos) | [
"mraines4@DC-MacBook-Air.T-mobile.com"
] | mraines4@DC-MacBook-Air.T-mobile.com |
7ad3326cbaca85ab363d12b50eca96bafd2349e9 | 1fff39c8cffa4b273fa17473d8313f208b111a83 | /H1/1.2阶乘求和.py | 3904247cb0e12dab18912f52d4f195c1f233d39e | [] | no_license | pkuzhd/Python | 9c00c3c2f2969b7349a265ea816ada5df97657d3 | 54199d1189b4c2458cc525b3b1ad19b645b7c295 | refs/heads/master | 2021-01-19T08:17:22.440486 | 2017-04-28T16:25:58 | 2017-04-28T16:25:58 | 87,615,592 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 225 | py | n = int(input())
def factorailSum(n):
s = 0
for i in range(1,n+1):
m = 1 #m用来记录j的阶乘
for j in range(1,i+1):
m *= j
s += m
return s
print(factorailSum(n)) | [
"noreply@github.com"
] | pkuzhd.noreply@github.com |
c6149ab26615a39e47fb26a9271b478a2d9b3c09 | 9bd8facfe26300d12661c31272e2f87db36fc0aa | /site-form-works/car_admin/app/models.py | 691949186f52019c9dc5660ccad8065e9fe11531 | [] | no_license | x350/django | 9c75a85ba63ae1c7f7ee0a28b6dfcd73a6d507dc | 187dd00fcddb619ff102bf9b3913883774ead565 | refs/heads/master | 2022-12-07T05:13:54.383754 | 2019-05-28T21:40:55 | 2019-05-28T21:40:55 | 178,067,928 | 0 | 0 | null | 2022-11-22T03:13:37 | 2019-03-27T20:13:44 | Python | UTF-8 | Python | false | false | 780 | py | from django.db import models
class Car(models.Model):
brand = models.CharField(max_length=50, verbose_name='Бренд')
model = models.CharField(max_length=50, verbose_name='Модель')
def __str__(self):
return self.brand
def review_count(self):
return Review.objects.filter(car=self).count()
review_count.short_description = 'Количество обзоров'
brand.admin_order_field = '-id'
class Review(models.Model):
car = models.ForeignKey(Car, on_delete=models.CASCADE, verbose_name='Машина')
title = models.CharField(max_length=100, verbose_name='Название')
text = models.TextField()
car.admin_order_field = '-id'
def __str__(self):
return str(self.car) + ' ' + self.title
| [
"x350sh@gmail.com"
] | x350sh@gmail.com |
feb0a40e60b20afcc8c457b4c5ed4d50a1b52e62 | d229e1e9476e53ed5776135d0afdad0a5770d323 | /tests/test_topic_stock.py | 9a5099b42c01ba49126fb33c2cb6bb820d738626 | [
"Apache-2.0"
] | permissive | lukeone/eaiser | 5f4cecd8be0a8a888d36477e50cba1117b42e470 | 9d16b28f9cd5286ebe0da68c38bbedab16b15e68 | refs/heads/master | 2020-06-19T20:32:30.464830 | 2019-10-25T02:45:13 | 2019-10-25T02:45:13 | 196,861,341 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,381 | py | # -*- coding: utf-8 -*-
import pytest
from easier.topic.stock import Stock
from easier.context import Context
@pytest.fixture(scope="module")
def topic():
context = Context()
topic = Stock(context)
context.set_current(topic)
yield topic
topic.release()
@pytest.mark.usefixtures("topic")
class TestStock(object):
def test_normalize(self, topic):
assert topic.normalize("中国平安") == ["601318"]
assert topic.normalize(["中国平安"]) == ["601318"]
assert sorted(topic.normalize(["中国平安", "000725"])) == sorted(["601318", "000725"])
indexs = topic.normalize(["上证指数", "深圳成指", "沪深300指数", "上证50", "中小板", "创业板"])
indexs_std = ['sh', 'sz', 'hs300', 'sz50', 'zxb', 'cyb']
assert sorted(indexs) == sorted(indexs_std)
def test_get_realtime_quotation(self, topic):
assert topic.get_realtime_quotation([""]) is None
assert len(topic.get_realtime_quotation(["中国平安"])) == 1
assert len(topic.get_realtime_quotation(["中国平安", "000725"])) == 2
def test_get_stock_basis(self, topic):
basis = topic.get_stock_basis([""])
assert basis is None or basis.empty
assert len(topic.get_stock_basis(["中国平安"])) == 1
assert len(topic.get_stock_basis(["中国平安", "000725"])) == 2
| [
"luo86106@gmail.com"
] | luo86106@gmail.com |
3462cfff2ec738dd09b64149bfc88294d07a1c38 | b73106d844259b2ba4dc0d4c3177fdd5ee65457d | /run_all.py | ef1251a7f7aba7a93dc02c6b53834f0c2966a527 | [] | no_license | narendra-ism/task | 445764b044608848af6e134d76db0218337d301e | f4dfb3bb9bd0eac15f39e7414e7aa4a05704e4d1 | refs/heads/master | 2022-12-11T09:10:12.769150 | 2019-11-05T08:02:19 | 2019-11-05T08:02:19 | 218,512,728 | 0 | 0 | null | 2022-12-07T20:30:42 | 2019-10-30T11:33:32 | Python | UTF-8 | Python | false | false | 653 | py | import os
import time
print('zookeeper is starting')
a=['./confluent-4.1.0/bin/zookeeper-server-start -daemon ./confluent-4.1.0/etc/kafka/zookeeper.properties']
os.system(a[0])
time.sleep(10)
print('zookeeper is running')
print('')
print('kafka is starting')
b=['./confluent-4.1.0/bin/kafka-server-start -daemon ./confluent-4.1.0/etc/kafka/server.properties']
os.system(b[0])
time.sleep(10)
print('kafka is running')
print('')
print('create a topic in kafka: mytopic')
d=['./confluent-4.1.0/bin/kafka-topics --zookeeper 127.0.0.1:2181 --create --replication-factor 1 --partitions 1 --topic mytopic']
os.system(d[0])
time.sleep(5)
print('')
| [
"narendra11d@gmail.com"
] | narendra11d@gmail.com |
f3f977c51021182dec91d0c3e0df7f9325e5120d | bb7aa6e986d8371b65649ebf72eecd79a98eb465 | /pset7/houses/import.py | e620753627cdf16dd8cd7b6072c1fd224a1bf264 | [] | no_license | brendonn40/CS50 | 35253f9ab4cb9a9ea07f7099a10d5ed0e4f6fc76 | c99536dd935330ba61afa3617c25504216b59403 | refs/heads/master | 2022-04-13T20:38:25.995614 | 2020-04-09T14:20:05 | 2020-04-09T14:20:05 | 242,616,328 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 926 | py | from csv import DictReader
from sys import argv,exit
from cs50 import SQL
open(f"students.db", "w").close()
db = SQL("sqlite:///students.db")
if len(argv)!= 2:
print("Usage python import.py file.csv")
exit(1)
db.execute("CREATE TABLE students (id INT , first TEXT, middle TEXT, last TEXT, house TEXT,birth NUMERIC,PRIMARY KEY(id))")
id=1
with open (argv[1],"r") as characters:
reader = DictReader(characters)
for row in reader:
names = row["name"].split()
house = row["house"]
birth = row["birth"]
if len(names) == 3:
db.execute("INSERT INTO students (id, first , middle , last , house ,birth) VALUES(?, ?, ?, ?,?,?)",id,names[0],names[1],names[2],house,birth)
id+=1
else:
db.execute("INSERT INTO students (id , first , middle , last , house ,birth) VALUES(?, ?, ?, ?,?,?)",id,names[0],None,names[1],house,birth)
id+=1
| [
"noreply@github.com"
] | brendonn40.noreply@github.com |
7ce4ab6fcd870ee1929d1564be706a340aae55da | 652121d51e6ff25aa5b1ad6df2be7eb341683c35 | /examples/e2cylinder.py | e6cfcdcb96ff792080e988aeadbefe32b8a3509e | [] | no_license | jgalaz84/eman2 | be93624f1c261048170b85416e517e5813992501 | 6d3a1249ed590bbc92e25fb0fc319e3ce17deb65 | refs/heads/master | 2020-04-25T18:15:55.870663 | 2015-06-05T20:21:44 | 2015-06-05T20:21:44 | 36,952,784 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,482 | py | #!/usr/bin/env python
'''
====================
Author: Jesus Galaz - 02/March/2013, Last update: 29/October/2014
====================
# This software is issued under a joint BSD/GNU license. You may use the
# source code in this file under either license. However, note that the
# complete EMAN2 and SPARX software packages have some GPL dependencies,
# so you are responsible for compliance with the licenses of these packages
# if you opt to use BSD licensing. The warranty disclaimer below holds
# in either instance.
#
# This complete copyright notice must be included in any revised version of the
# source code. Additional authorship citations may be added, but existing
# author citations must be preserved.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 2111-1307 USA
'''
from EMAN2 import *
def main():
usage = """Program to generate a cylindrical mask. It can also create a cylindrical shell if
you specify the --height_inner and --radius_inner parameters, in addition to the
required outer --height and --radius.
"""
parser = EMArgumentParser(usage=usage,version=EMANVERSION)
parser.add_argument("--path",type=str,default=None,help="""Directory to store results in.
The default is a numbered series of directories containing the prefix 'cylmask';
for example, cylmask_02 will be the directory by default if 'cylmask_01'
already exists.""")
parser.add_argument("--verbose", "-v", help="""verbose level [0-9], higner number means
higher level of verboseness. Default=0.""",dest="verbose", action="store", metavar="n",type=int, default=0)
parser.add_argument("--ppid", type=int, help="""Set the PID of the parent process,
used for cross platform PPID""",default=-1)
parser.add_argument("--height", type=int, default=0,help="""Height of the cylindrical mask.""")
parser.add_argument("--heightinner", type=int, default=0,help="""Height for the inner boundary
if creating a cylindrical shell mask.""")
parser.add_argument("--radius",type=int,default=0,help="""Radius of the cylindrical mask.
Default=boxsize/2.""")
parser.add_argument("--radiusinner",type=int,default=0,help="""Radius for the inner boundary
if creating a cylindrical shell mask.
Default=boxsize/2.""")
parser.add_argument("--boxsize", type=int, default=0,help="""Size of the boxsize where the
cylindrical mask will live.""")
parser.add_argument("--axes",type=str,default='z',help="""Axes along which the mask will be
oriented. Default=z. You can supply more than one, separated with commas. For example:
--axes=x,y,z.""")
parser.add_argument("--rotation",type=str,default='',help="""Three comma separated Euler angles
az,alt,phi, to rotate the masks by before writing them out.""")
parser.add_argument("--translation",type=str,default='',help="""Three comma separated coordinates
x,y,z, to translate the masks by before writing them out.""")
parser.add_argument("--rotavg",action='store_true',default=False,help="""This will compute the rotational average of the mask(s) in addition to writing the cylindrical mask itself out.""")
(options, args) = parser.parse_args()
if not options.boxsize:
print "You must provide --boxsize > 4"
sys.exit(1)
elif options.boxsize < 5:
print "You must provide --boxsize > 4"
sys.exit(1)
if options.heightinner and not options.radiusinner:
print "If specifying --heightinner, you must also specify --radiusinner."
sys.exit(1)
if options.radiusinner and not options.heightinner:
print "If specifying --radiusinner, you must also specify --heightinner."
sys.exit(1)
from e2spt_classaverage import sptmakepath
options = sptmakepath( options, 'cylmask')
logger = E2init(sys.argv, options.ppid)
axes = options.axes.split(',')
print "After splitting, axes=", axes
#axisdict ={}
#for axis in axes:
# axisdict.update( { 'z } )
ts = {}
mask = cylinder(options)
rt=Transform()
if options.rotation or options.translation:
az=alt=phi=xc=yc=zc=0
if options.rotation:
angles=options.rotation.split(',')
az=float(angles[0])
alt=float(angles[1])
phi=float(angles[2])
if options.translation:
trans=options.translation.split(',')
xc=float(trans[0])
yc=float(trans[1])
zc=float(trans[2])
rt=Transform({'type':'eman','az':az,'alt':alt,'phi':phi,'tx':xc,'ty':yc,'tz':zc})
mask.transform( rt )
for axis in axes:
print "axis is", axis
if 'z' in axis or 'Z' in axis:
tz = Transform({'type':'eman','az':0,'alt':0,'phi':0})
print "added z transform"
ts.update({'z':tz})
if 'x' in axis or 'X' in axis:
tx = Transform({'type':'eman','az':0,'alt':90,'phi':90})
ts.update({'x':tx})
print "added x transform"
if 'y' in axis or 'Y' in axis:
ty = Transform({'type':'eman','az':0,'alt':90,'phi':0})
ts.update({'y':ty})
print "added y transform"
masknamebase = options.path + '/cylmask.hdf'
for a in ts:
maskt = mask.copy()
tag = 'R'+str( options.radius ).zfill( len( str( options.radius))) + 'H'+str( options.height ).zfill( len( str( options.radius)))
if options.radiusinner:
tag+='RI'+str( options.radiusinner ).zfill( len( str( options.radius)))
if options.heightinner:
'HI'+str( options.height ).zfill( len( str( options.radius)))
if a == 'z':
maskz=mask.copy()
maskname=masknamebase.replace('.hdf','_Z_') + tag + '.hdf'
maskz.transform( ts[a] )
maskz.write_image( maskname, 0 )
if options.rotavg:
rotavgname = maskname.replace('.','_ROTAVG.')
maskzrotavg = maskz.rotavg_i()
maskzrotavg.write_image( rotavgname , 0 )
if a == 'x':
maskx=mask.copy()
maskx.transform( ts[a] )
maskname=masknamebase.replace('.hdf','_X_') + tag + '.hdf'
maskx.write_image( maskname, 0 )
if options.rotavg:
rotavgname = maskname.replace('.','_ROTAVG.')
maskxrotavg = maskx.rotavg_i()
maskxrotavg.write_image( rotavgname , 0 )
if a == 'y':
masky=mask.copy()
masky.transform( ts[a] )
maskname=masknamebase.replace('.hdf','_Y_') + tag + '.hdf'
masky.write_image( maskname, 0 )
if options.rotavg:
rotavgname = maskname.replace('.','_ROTAVG.')
maskyrotavg = masky.rotavg_i()
maskyrotavg.write_image( rotavgname , 0 )
E2end(logger)
return
def cylinder( options ):
box = options.boxsize
mask = EMData( box, box, box)
mask.to_one()
if options.radius:
radius = options.radius
else:
radius = box/2.0
if options.height:
height = options.height
else:
height = box/2.0
maskout = mask.process("testimage.cylinder",{'height':height,'radius':radius})
finalmask = maskout
if options.heightinner and options.radiusinner:
maskin = mask.process("testimage.cylinder",{'height':options.heightinner,'radius':options.radiusinner})
finalmask = maskout - maskin
return finalmask
if __name__ == '__main__':
main()
| [
"jgalaz@gmail.com"
] | jgalaz@gmail.com |
387dabd782ce5ff9ef6a24211f7525578847f816 | ee8c4c954b7c1711899b6d2527bdb12b5c79c9be | /assessment2/amazon/run/core/controllers/dull.py | fe0bc212a62abe4ede34e4e1fbbd1c7e1de2186d | [] | no_license | sqlconsult/byte | 02ac9899aebea4475614969b594bfe2992ffe29a | 548f6cb5038e927b54adca29caf02c981fdcecfc | refs/heads/master | 2021-01-25T14:45:42.120220 | 2018-08-11T23:45:31 | 2018-08-11T23:45:31 | 117,135,069 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 362 | py | #!/usr/bin/env python3
from flask import Blueprint, Flask, render_template, request, url_for
controller = Blueprint('dull', __name__, url_prefix='/dull')
# @controller.route('/<string:title>', methods=['GET'])
# def lookup(title):
# if title == 'Republic': # TODO 2
# return render_template('republic.html') # TODO 2
# else:
# pass
| [
"sqlconsult@hotmail.com"
] | sqlconsult@hotmail.com |
0823c8bea45494d2905b0e5043439fae6e53ae03 | 1a7c7b6785ba275bad55ea24fc4ab82b7344adb6 | /Mission_to_Mars.py | 936f9d67e310d88cfa51161be42bb3770f219ab6 | [] | no_license | nicbrownrigg/Mission-to-Mars | 2565ad86102880448073daf4c55d13af539f9746 | f9517b8df7d0decf452ada1906d386e682db2d89 | refs/heads/main | 2023-07-18T10:12:58.761635 | 2021-08-23T03:52:27 | 2021-08-23T03:52:27 | 398,953,092 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,383 | py | # Import Splinter, BeautifulSoup, and Pandas
from splinter import Browser
from bs4 import BeautifulSoup as soup
import pandas as pd
from webdriver_manager.chrome import ChromeDriverManager
from flask import Flask, render_template, redirect, url_for
from flask_pymongo import PyMongo
import scraping
# Set up Splinter
executable_path = {'executable_path': ChromeDriverManager().install()}
browser = Browser('chrome', **executable_path, headless=False)
app = Flask(__name__)
# Visit the Mars news site
url = 'https://redplanetscience.com/'
browser.visit(url)
# Optional delay for loading the page
browser.is_element_present_by_css('div.list_text', wait_time=1)
# Convert the browser html to a soup object and then quit the browser
html = browser.html
news_soup = soup(html, 'html.parser')
slide_elem = news_soup.select_one('div.list_text')
slide_elem.find('div', class_='content_title')
# Use the parent element to find the first a tag and save it as `news_title`
news_title = slide_elem.find('div', class_='content_title').get_text()
news_title
# Use the parent element to find the paragraph text
news_p = slide_elem.find('div', class_='article_teaser_body').get_text()
news_p
# ## JPL Space Images Featured Image
# Visit URL
url = 'https://spaceimages-mars.com'
browser.visit(url)
# Find and click the full image button
full_image_elem = browser.find_by_tag('button')[1]
full_image_elem.click()
# Parse the resulting html with soup
html = browser.html
img_soup = soup(html, 'html.parser')
# find the relative image url
img_url_rel = img_soup.find('img', class_='fancybox-image').get('src')
img_url_rel
# Use the base url to create an absolute url
img_url = f'https://spaceimages-mars.com/{img_url_rel}'
img_url
# ## Mars Facts
df = pd.read_html('https://galaxyfacts-mars.com')[0]
df.head()
df.columns=['Description', 'Mars', 'Earth']
df.set_index('Description', inplace=True)
df
df.to_html()
browser.quit()
# Use flask_pymongo to set up mongo connection
app.config["MONGO_URI"] = "mongodb://localhost:27017/mars_app"
mongo = PyMongo(app)
@app.route("/")
def index():
mars = mongo.db.mars.find_one()
return render_template("index.html", mars=mars)
@app.route("/scrape")
def scrape():
mars = mongo.db.mars
mars_data = scraping.scrape_all()
mars.update({}, mars_data, upsert=True)
return redirect('/', code=302)
if __name__ == "__main__":
app.run() | [
"noreply@github.com"
] | nicbrownrigg.noreply@github.com |
bf842dabd136a3c999d9455ac2d5af0d645e01d4 | f231fd7cb34b042a91addf2e96468cc08ab785e3 | /courses/MITx/MITx 6.86x Machine Learning with Python-From Linear Models to Deep Learning/project2/mnist/part1/softmax.py | a457fb19cff54403aa402ebf63b391387f635ffd | [
"Apache-2.0"
] | permissive | xunilrj/sandbox | f1a0d7a1af536bea217bc713e748f04819c2480b | d65076ba487b8bf170368c9e0a0d23e0575fc09f | refs/heads/master | 2023-05-10T09:27:59.541942 | 2023-04-26T15:39:25 | 2023-04-26T15:39:25 | 64,613,121 | 8 | 5 | Apache-2.0 | 2023-03-07T01:57:24 | 2016-07-31T20:12:02 | C++ | UTF-8 | Python | false | false | 7,347 | py | import sys
sys.path.append("..")
import utils
from utils import *
import numpy as np
import matplotlib.pyplot as plt
import scipy.sparse as sparse
def augment_feature_vector(X):
"""
Adds the x[i][0] = 1 feature for each data point x[i].
Args:
X - a NumPy matrix of n data points, each with d - 1 features
Returns: X_augment, an (n, d) NumPy array with the added feature for each datapoint
"""
column_of_ones = np.zeros([len(X), 1]) + 1
return np.hstack((column_of_ones, X))
def compute_probabilities(X, theta, temp_parameter):
"""
Computes, for each datapoint X[i], the probability that X[i] is labeled as j
for j = 0, 1, ..., k-1
Args:
X - (n, d) NumPy array (n datapoints each with d features)
theta - (k, d) NumPy array, where row j represents the parameters of our model for label j
temp_parameter - the temperature parameter of softmax function (scalar)
Returns:
H - (k, n) NumPy array, where each entry H[j][i] is the probability that X[i] is labeled as j
"""
Xt = np.transpose(X)
theta_xt = (theta @ Xt) / temp_parameter
c = np.amax(theta_xt, axis=0)
exps = np.exp(theta_xt - c)
normalization = 1 / np.sum(exps, axis=0)
return normalization * exps
def compute_cost_function(X, Y, theta, lambda_factor, temp_parameter):
"""
Computes the total cost over every datapoint.
Args:
X - (n, d) NumPy array (n datapoints each with d features)
Y - (n, ) NumPy array containing the labels (a number from 0-9) for each
data point
theta - (k, d) NumPy array, where row j represents the parameters of our
model for label j
lambda_factor - the regularization constant (scalar)
temp_parameter - the temperature parameter of softmax function (scalar)
Returns
c - the cost value (scalar)
"""
with np.errstate(over='ignore',invalid='ignore',divide='ignore'):
logs = np.log(compute_probabilities(X, theta, temp_parameter))
return -np.average(
np.where(
np.logical_or(np.isinf(logs), np.isnan(logs)),
0, logs
)
) + lambda_factor/2 * np.sum(theta * theta)
def run_gradient_descent_iteration(X, Y, theta, alpha, lambda_factor, temp_parameter):
"""
Runs one step of batch gradient descent
Args:
X - (n, d) NumPy array (n datapoints each with d features)
Y - (n, ) NumPy array containing the labels (a number from 0-9) for each
data point
theta - (k, d) NumPy array, where row j represents the parameters of our
model for label j
alpha - the learning rate (scalar)
lambda_factor - the regularization constant (scalar)
temp_parameter - the temperature parameter of softmax function (scalar)
Returns:
theta - (k, d) NumPy array that is the final value of parameters theta
"""
n = X.shape[0]
k = theta.shape[0]
M = sparse.coo_matrix(([1]*n, (Y, range(n))), shape=(k,n)).toarray()
p = np.where(M,1,0) - compute_probabilities(X, theta, temp_parameter)
grad = (-1/(temp_parameter*n) * p.dot(X)) + (lambda_factor*theta)
return theta - alpha*grad
def update_y(train_y, test_y):
"""
Changes the old digit labels for the training and test set for the new (mod 3)
labels.
Args:
train_y - (n, ) NumPy array containing the labels (a number between 0-9)
for each datapoint in the training set
test_y - (n, ) NumPy array containing the labels (a number between 0-9)
for each datapoint in the test set
Returns:
train_y_mod3 - (n, ) NumPy array containing the new labels (a number between 0-2)
for each datapoint in the training set
test_y_mod3 - (n, ) NumPy array containing the new labels (a number between 0-2)
for each datapoint in the test set
"""
return (np.mod(train_y,3),np.mod(test_y,3))
def compute_test_error_mod3(X, Y, theta, temp_parameter):
"""
Returns the error of these new labels when the classifier predicts the digit. (mod 3)
Args:
X - (n, d - 1) NumPy array (n datapoints each with d - 1 features)
Y - (n, ) NumPy array containing the labels (a number from 0-2) for each
data point
theta - (k, d) NumPy array, where row j represents the parameters of our
model for label j
temp_parameter - the temperature parameter of softmax function (scalar)
Returns:
test_error - the error rate of the classifier (scalar)
"""
pred_Y = get_classification(X, theta, temp_parameter)
pred_Y = np.mod(pred_Y, 3)
return np.average(np.where(pred_Y == Y, 0, 1))
def softmax_regression(X, Y, temp_parameter, alpha, lambda_factor, k, num_iterations):
"""
Runs batch gradient descent for a specified number of iterations on a dataset
with theta initialized to the all-zeros array. Here, theta is a k by d NumPy array
where row j represents the parameters of our model for label j for
j = 0, 1, ..., k-1
Args:
X - (n, d - 1) NumPy array (n data points, each with d-1 features)
Y - (n, ) NumPy array containing the labels (a number from 0-9) for each
data point
temp_parameter - the temperature parameter of softmax function (scalar)
alpha - the learning rate (scalar)
lambda_factor - the regularization constant (scalar)
k - the number of labels (scalar)
num_iterations - the number of iterations to run gradient descent (scalar)
Returns:
theta - (k, d) NumPy array that is the final value of parameters theta
cost_function_progression - a Python list containing the cost calculated at each step of gradient descent
"""
X = augment_feature_vector(X)
theta = np.zeros([k, X.shape[1]])
cost_function_progression = []
for i in range(num_iterations):
cost_function_progression.append(compute_cost_function(X, Y, theta, lambda_factor, temp_parameter))
theta = run_gradient_descent_iteration(X, Y, theta, alpha, lambda_factor, temp_parameter)
return theta, cost_function_progression
def get_classification(X, theta, temp_parameter):
"""
Makes predictions by classifying a given dataset
Args:
X - (n, d - 1) NumPy array (n data points, each with d - 1 features)
theta - (k, d) NumPy array where row j represents the parameters of our model for
label j
temp_parameter - the temperature parameter of softmax function (scalar)
Returns:
Y - (n, ) NumPy array, containing the predicted label (a number between 0-9) for
each data point
"""
X = augment_feature_vector(X)
probabilities = compute_probabilities(X, theta, temp_parameter)
return np.argmax(probabilities, axis = 0)
def plot_cost_function_over_time(cost_function_history):
plt.plot(range(len(cost_function_history)), cost_function_history)
plt.ylabel('Cost Function')
plt.xlabel('Iteration number')
plt.show()
def compute_test_error(X, Y, theta, temp_parameter):
error_count = 0.
assigned_labels = get_classification(X, theta, temp_parameter)
return 1 - np.mean(assigned_labels == Y)
| [
"1985.daniel@gmail.com"
] | 1985.daniel@gmail.com |
976b1c3cf14d08fa85ce19b565a2bd70f48d89c9 | 12c66f064758507068d7cd9e97819fc20105407a | /src/add_cilin.py | 355241c1e979461be43a943aa55c69dbedb9cb48 | [] | no_license | whr94621/synextractor | 64b34b0f6187bb0fc0bbae602298663da4c2f2f1 | aa9fc786720a0113b01edd89cb5524029aa42421 | refs/heads/master | 2020-12-25T06:47:55.744622 | 2016-07-20T07:25:09 | 2016-07-20T07:25:09 | 63,651,121 | 12 | 2 | null | null | null | null | UTF-8 | Python | false | false | 1,296 | py | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 19 09:02:18 2016
@author: whr94621
"""
import tensorflow as tf
from synonym import Synonym
##################
# mutable params #
##################
top = 15
conf1 = 'configure.json'
conf2 = 'configure_1.json'
cilin = '../data/cilin.txt'
# the script
g1 = tf.Graph()
g2 = tf.Graph()
with g1.as_default():
syn1 = Synonym.load(conf1)
with g2.as_default():
syn2 = Synonym.load(conf2)
with open(cilin, 'r') as f, open('output.txt', 'w') as g:
for line in f:
line = line.strip().decode('utf8')
words = line.split()[1:]
tag = line.split()[0]
more_syns = set(words)
for word in words:
with g1.as_default():
syns1 = syn1.generate_synonyms(word, top)
with g2.as_default():
syns2 = syn2.generate_synonyms(word, top)
if syns1 and syns2:
syns_1 = syns1.values()[0]
syns_2 = syns2.values()[0]
syns_1 = [w.split('_')[0] for w in syns_1]
syns_2 = [w.split('_')[0] for w in syns_2]
syns = set(syns_1) & set(syns_2)
more_syns = more_syns | syns
new_line = '%s %s\n' % (tag, ' '.join(more_syns))
g.write(new_line.encode('utf8'))
| [
"whr94621@163.com"
] | whr94621@163.com |
75456499fe4c49df64a6eb1cc9eb3dc3a1039719 | 7dcb63e13c287ea5701840b22067b4d0302e2293 | /User/urls.py | a35aa43aa926bf93acbf8043da7b60180ac48e78 | [] | no_license | dpitkevics/Jooglin | a09fea1206591933631066ed230cfdeaa5573dc2 | ed7f6b78caf71ef446a1207a96cb30e7c2d767d9 | refs/heads/master | 2021-01-10T13:03:15.411244 | 2015-04-20T15:22:29 | 2015-04-20T15:22:29 | 32,028,245 | 0 | 0 | null | 2015-03-30T14:11:25 | 2015-03-11T16:24:54 | Python | UTF-8 | Python | false | false | 287 | py | from django.conf.urls import patterns, url
from User import views
urlpatterns = patterns('',
url(r'^login$', views.login, name='login'),
url(r'^get-balance/$', views.get_balance, name='get_balance'),
url(r'^get-experience/$', views.get_experience, name='get_experience'),
) | [
"daniels.pitkevics@gmail.com"
] | daniels.pitkevics@gmail.com |
435ac96107cd1300a5af9e79f7ec2474327ca74e | bbfaa2609b0a9775e89eaf261b5fa8a5b20445e0 | /backend/manage.py | 86ecd51d3529074253b3b121308e4264df0aa7cf | [] | no_license | crowdbotics-apps/in-the-mix-20320 | 9f8921718d9298154adc8278c04b25a9f7f8761b | a8e283776f3fb50049ddb830573e1cf0cfbfb743 | refs/heads/master | 2022-12-25T02:49:13.689263 | 2020-09-16T00:36:46 | 2020-09-16T00:36:46 | 295,881,723 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 636 | py | #!/usr/bin/env python
"""Django's command-line utility for administrative tasks."""
import os
import sys
def main():
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "in_the_mix_20320.settings")
try:
from django.core.management import execute_from_command_line
except ImportError as exc:
raise ImportError(
"Couldn't import Django. Are you sure it's installed and "
"available on your PYTHONPATH environment variable? Did you "
"forget to activate a virtual environment?"
) from exc
execute_from_command_line(sys.argv)
if __name__ == "__main__":
main()
| [
"team@crowdbotics.com"
] | team@crowdbotics.com |
a828c1cbad38ff9441e7096e89181cbdb0003fd5 | e16d86ae86e338a8091c9adeead4df5fe0451e0c | /fetcher.py | 68b7e69b37536e5d27ba1baa5b3b8608ece4f0a2 | [] | no_license | nekyian/xbmc-suggester | 6e40cf69268807637d096a5f3a0452bb8f17e8f1 | 6bfc5a5513634a64869bbb17321dc1b23062f7e2 | refs/heads/master | 2020-05-07T11:16:34.029906 | 2013-04-20T11:33:03 | 2013-04-20T11:33:03 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 901 | py | #!/usr/bin/python
# Import XBMC module
import xbmc
# First we need to create an object containing the getMusicInfoTag() class from XBMC.Player().
# This is in order to use the same instance of the class twice and not create a new class
# for every time we query for information.
# This is a bit important to notice, as creating many instances is rarely
# a good thing to do (unless you need it, but not in this case).
tag = xbmc.Player().getMusicInfoTag()
# Now tag contains the getMusicInfoTag() class which then again contains song information.
# Now we use this object to get the data by calling functions within that class:
artist = tag.getArtist()
title = tag.getTitle()
# Now you have two strings containing the information. An example of what you could do next is to print it:
print "Playing: " + artist + " - " + title
# This will produce i.e: "Playing: AC/DC - Back in black" | [
"dan.stativa@gmail.com"
] | dan.stativa@gmail.com |
a8dbb51ef0ca26def134a3942bb8d2f0822cf411 | 2836013e948f89165a0de1ed3feaf262f3a3a1f0 | /models/TextCNN_PGD.py | ff675206b4786a47ab9278fa4cdee3b413ee50d5 | [
"MIT"
] | permissive | zpyzl/adversarial | 66be9d48b884af1417c8f42122338ea4c193bb96 | 2a0376e5691c00ff39f5dd3fb496e544c39cb0e8 | refs/heads/master | 2023-03-09T17:13:28.819692 | 2021-03-03T01:57:43 | 2021-03-03T01:57:43 | 336,278,967 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,612 | py | # coding: UTF-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from utils import clamp, add_perturbed_labels
class Config(object):
"""配置参数"""
def __init__(self, dataset, embedding):
self.model_name = 'TextCNN'
self.train_path = dataset + '/data/train.txt' # 训练集
self.dev_path = dataset + '/data/dev.txt' # 验证集
self.test_path = dataset + '/data/test.txt' # 测试集
self.class_list = [x.strip() for x in open(
dataset + '/data/class.txt', encoding='utf-8').readlines()] # 类别名单
self.vocab_path = dataset + '/data/vocab.pkl' # 词表
self.save_path = dataset + '/saved_dict/' + self.model_name + '.ckpt' # 模型训练结果
self.log_path = dataset + '/log/' + self.model_name
self.embedding_pretrained = torch.tensor(
np.load(dataset + '/data/' + embedding)["embeddings"].astype('float32'))\
if embedding != 'random' else None # 预训练词向量
self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') # 设备
self.dropout = 0.5 # 随机失活
self.require_improvement = 1000 # 若超过1000batch效果还没提升，则提前结束训练
self.num_classes = len(self.class_list) # 类别数
self.n_vocab = 0 # 词表大小，在运行时赋值
self.num_epochs = 20 # epoch数
self.batch_size = 128 # mini-batch大小
self.pad_size = 32 # 每句话处理成的长度(短填长切)
self.learning_rate = 1e-3 # 学习率
self.embed = self.embedding_pretrained.size(1)\
if self.embedding_pretrained is not None else 300 # 字向量维度
self.filter_sizes = (2, 3, 4) # 卷积核尺寸
self.num_filters = 256 # 卷积核数量(channels数)
'''Convolutional Neural Networks for Sentence Classification'''
class Model(nn.Module):
def __init__(self, config):
super(Model, self).__init__()
if config.embedding_pretrained is not None:
self.embedding = nn.Embedding.from_pretrained(config.embedding_pretrained, freeze=False)
else:
self.embedding = nn.Embedding(config.n_vocab, config.embed, padding_idx=config.n_vocab - 1)
self.convs = nn.ModuleList(
[nn.Conv2d(1, config.num_filters, (k, config.embed)) for k in config.filter_sizes])
self.dropout = nn.Dropout(config.dropout)
self.fc = nn.Linear(config.num_filters * len(config.filter_sizes), config.num_classes)
def conv_and_pool(self, x, conv):
x = F.relu(conv(x)).squeeze(3)
x = F.max_pool1d(x, x.size(2)).squeeze(2)
return x
def forward(self, x, labels):
out = self.embedding(x[0])
out = out.unsqueeze(1)
out = torch.cat([self.conv_and_pool(out, conv) for conv in self.convs], 1)
out = self.dropout(out)
out = self.fc(out)
loss = F.cross_entropy(out, labels)
return out, loss
| [
"zpyzl@qq.com"
] | zpyzl@qq.com |
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