blob_id stringlengths 40 40 | directory_id stringlengths 40 40 | path stringlengths 2 616 | content_id stringlengths 40 40 | detected_licenses listlengths 0 69 | license_type stringclasses 2 values | repo_name stringlengths 5 118 | snapshot_id stringlengths 40 40 | revision_id stringlengths 40 40 | branch_name stringlengths 4 63 | visit_date timestamp[us] | revision_date timestamp[us] | committer_date timestamp[us] | github_id int64 2.91k 686M ⌀ | star_events_count int64 0 209k | fork_events_count int64 0 110k | gha_license_id stringclasses 23 values | gha_event_created_at timestamp[us] | gha_created_at timestamp[us] | gha_language stringclasses 220 values | src_encoding stringclasses 30 values | language stringclasses 1 value | is_vendor bool 2 classes | is_generated bool 2 classes | length_bytes int64 2 10.3M | extension stringclasses 257 values | content stringlengths 2 10.3M | authors listlengths 1 1 | author_id stringlengths 0 212 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
092387bcba67b21a15b981de3f667e91d5946785 | f94a331acc066ba3bdf1fb97dac8bfc7e281b3ee | /web/lists.py | b4d940a30e87a209c6a22f2d397eaf12d5e61a58 | [] | no_license | Yelesee/mirab | a066b43743d35b2d5f34d1e069f1f8bf4e6349f7 | 9049e3792a6e8e84738ba002666d31f9bdddad7c | refs/heads/v1.0 | 2022-12-12T22:59:52.790388 | 2019-02-25T07:27:39 | 2019-02-25T07:27:39 | 172,456,977 | 0 | 0 | null | 2022-12-08T02:29:51 | 2019-02-25T07:35:31 | JavaScript | UTF-8 | Python | false | false | 313 | py | import os
import xml.etree.ElementTree as et
base_path = os.path.dirname(os.path.realpath(__file__))
xml_file = os.path.join(base_path, "data/fuzzy.xml")
tree = et.parse(xml_file)
print(xml_file)
# class Fuzzy_xml:
# def__init__(self,input_nums,output_nums,rule_nums):
# def new_file(inputs,outputs,rules):
| [
"ebadia9094@yahoo.com"
] | ebadia9094@yahoo.com |
08e11d74b9d5f478d16696a5a8db8c9c85bb2500 | 52f96db06b294fc06283e6a6c19e0c41a693475d | /custom-addons/librarymanagement/models/book.py | c224e78fdd4c0d57dc4834643a59c44571b29059 | [] | no_license | sifat-bs23/odoo_learning | 1e151b2969c794fa9198368dd25351e6ec55b348 | 32fb977ff45a273e3fd2a30955121595e9997298 | refs/heads/master | 2021-05-25T16:17:06.375730 | 2020-04-16T13:58:18 | 2020-04-16T13:58:18 | 253,821,786 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,038 | py | from odoo import models, fields, api
class Book(models.Model):
_name = 'book'
_description = 'This will contain all the book information'
@api.depends('price')
def _set_category(self):
for rec in self:
if rec.price >= 500:
rec.category = 'high'
elif 500 > rec.price >= 250:
rec.category = 'normal'
else:
rec.category = 'low'
name = fields.Char(string='Book Name', max_lngth=100, required=True)
author = fields.Many2many('author', string='Author Name')
editor = fields.Char(string='Editors', max_length=100)
edition = fields.Char(string='Edition', max_length=50)
isbn = fields.Char(string='ISBN Number', max_length=50)
image = fields.Binary(sring='Photo')
price = fields.Float(string='Price', digits=(4, 2))
category = fields.Selection([
('high', 'Elite'), ('normal', 'Normal'), ('low', 'Low Grade')
], compute='_set_category')
total_copy = fields.Integer(string='Total Copies')
| [
"sifat.hassan@bs-23.net"
] | sifat.hassan@bs-23.net |
7d9fe3560f0a5fce28f2f4deb1a47ed7d695be36 | 638d0d770f47cdafff2bdfb9c47f74efe2cfda02 | /seem to work.py | b94b4bebec82083a4c244634eb08d79e2ab64182 | [] | no_license | Ranranxz/pp-code | 47badea8d54d73ec5fe83cf9fb71f9d5cd93ce4c | 2692d6b096dfa470c00016cff7bdfa1c906a679d | refs/heads/master | 2020-03-15T16:33:47.281187 | 2018-05-06T05:25:51 | 2018-05-06T05:25:51 | 132,237,449 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 27,374 | py | #Evan Long Ma & Sherry Zhuang
#elm454 xz1741
#24 Points!
import datetime
import math
import random
#Perhaps pass in a seed
seed = 2195
random.seed(seed)
#Sets the number to aim for
win = 24
#User score #Not actually a constant, but yeah
POINTS = 0
#Playing Cards / Numbers
a, b, c, d = 2, 4, 3, 6
#a, b, c, d = 4, 4, 7, 7
COUNT_OF_NUMBER = 4
NUMBER_TO_BE_CAL = win
#Regarding printouts
showrules = True
showrulesinside = False
last = ""
#controls states
st = 0
# count games
count = 0
#Main game
while count < 10:
while st == 0:
number_lst = [a,b,c,d]
formula_lst = [str(a),str(b),str(c),str(d)]
count += 1
#recursive solver
def solve(n):
if(1 == n):
if NUMBER_TO_BE_CAL - number_lst[0] == 0:
print("The answer is: " + formula_lst[0] + " = " + str(win) + "\n\n")
return True
else:
return False
else:
for i in range(0, n):
for j in range(i+1, n):
x = number_lst[i]
y = number_lst[j]
#**********************************
# Move the meaingful forward
# answer saved in [i]
# number[j]can just be overwritten by the last number
# *******************************
number_lst[j] = number_lst[n - 1]
form_x = formula_lst[i]
form_y = formula_lst[j]
formula_lst[j] = formula_lst[n - 1]
# cal x+y
formula_lst[i] = '(' + form_x + '+' + form_y + ')'
number_lst[i] = x + y
if ( solve(n - 1) ):
return True
# cal x-y
formula_lst[i] = '(' + form_x + '-' + form_y + ')'
number_lst[i] = x - y
if ( solve(n - 1) ):
return True
# cal y-x
formula_lst[i] = '(' + form_y + '-' + form_x + ')'
number_lst[i] = y - x
if ( solve(n - 1) ):
return True
# cal (x*y)
formula_lst[i] = '(' + form_x + '*' + form_y + ')'
number_lst[i] = x * y
if ( solve(n - 1) ):
return True
# cal (x/y)
if (y != 0) :
formula_lst[i] = '(' + form_x + '/' + form_y + ')'
number_lst[i] = x / y
if ( solve(n - 1) ):
return True
# (x//y)
formula_lst[i] = '(' + form_x + '//' + form_y + ')'
number_lst[i] = x // y
if ( solve(n - 1) ):
return True
#(x%y)
formula_lst[i] = '(' + form_x + '%' + form_y + ')'
number_lst[i] = x % y
if ( solve(n - 1) ):
return True
# cal (y/x)
if (x != 0) :
formula_lst[i] = '(' + form_y + '/' + form_x + ')'
number_lst[i] = y / x
if ( solve(n - 1) ):
return True
#(y//x)
formula_lst[i] = '(' + form_y + '//' + form_x + ')'
number_lst[i] = y // x
if ( solve(n - 1) ):
return True
#(y % x)
formula_lst[i] = '(' + form_y + '%' + form_x + ')'
number_lst[i] = y % x
if ( solve(n - 1) ):
return True
# cal(x ** y)
formula_lst[i] = '(' + form_x + '**' + form_y + ')'
if (x == 1 or (x == 0 and y >= 0)
or (x == 2 and abs(y) <= 9) or (x == 3 and abs(y) <= 6)
or (x == 4 and abs(y) <= 5) or (x == 5 and abs(y) <= 4)
or (x == 6 and abs(y) <= 3) or (x == 7 and abs(y) <= 3)
or (x == 8 and abs(y) <= 3) or (x == 9 and abs(y) <= 3)
or (x == 10 and abs(y) <= 3) or (x == 11 and abs(y) <= 2)
or (x == 12 and abs(y) <= 2) or (x == 13 and abs(y) <= 2)):
number_lst[i] = x ** y
if ( solve(n - 1) ):
return True
# cal(y ** x)
formula_lst[i] = '(' + form_y + '**' + form_x + ')'
if (y == 1 or (y == 0 and x >= 0)
or (y == 2 and abs(x) <= 9) or (y == 3 and abs(x) <= 6)
or (y == 4 and abs(x) <= 5) or (y == 5 and abs(x) <= 4)
or (y == 6 and abs(x) <= 3) or (y == 7 and abs(x) <= 3)
or (y == 8 and abs(x) <= 3) or (y == 9 and abs(x) <= 3)
or (y == 10 and abs(x) <= 3) or (y == 11 and abs(x) <= 2)
or (y == 12 and abs(x) <= 2) or (y == 13 and abs(x) <= 2)):
number_lst[i] = y ** x
if ( solve(n - 1) ):
return True
#All the factorials
if y >= 0 and (int(y) - y == 0):
# cal(!(y) + x)
formula_lst[i] = '(!(' + form_y + ')' + "+" + form_x + ')'
if y <= 6:
number_lst[i] = math.factorial(y) + x
if ( solve(n - 1) ):
return True
# cal(!(y) - x)
formula_lst[i] = '(!(' + form_y + ')' + "-" + form_x + ')'
if y <= 6:
number_lst[i] = math.factorial(y) - x
if ( solve(n - 1) ):
return True
# cal(!(y) * x)
formula_lst[i] = '(!(' + form_y + ')' + "*" + form_x + ')'
if y <= 6:
number_lst[i] = math.factorial(y) * x
if ( solve(n - 1) ):
return True
# cal(!(y) / x)
if x != 0:
formula_lst[i] = '(!(' + form_y + ')' + "/" + form_x + ')'
if y <= 6:
number_lst[i] = math.factorial(y) / x
if ( solve(n - 1) ):
return True
# cal(!(y) // x)
formula_lst[i] = '(!(' + form_y + ')' + "//" + form_x + ')'
if y <= 6:
number_lst[i] = math.factorial(y) // x
if ( solve(n - 1) ):
return True
# cal(!(y) % x)
formula_lst[i] = '(!(' + form_y + ')' + "%" + form_x + ')'
if y <= 6:
number_lst[i] = math.factorial(y) % x
if ( solve(n - 1) ):
return True
# cal(!(y) ** x)
formula_lst[i] = '(!(' + form_y + ')' + "**" + form_x + ')'
if (y <= 6 and (y == 0 or y == 1 or (y == 2 and abs(x) <= 9)
or (y == 3 and abs(x) <= 3) or (y == 4 and abs(x) <= 3)
or (y == 5 and abs(x) <= 2) or (y == 6 and abs(x) <= 1))):
number_lst[i] = math.factorial(y) ** x
if ( solve(n - 1) ):
return True
#Double
if x >= 0 and (int(x) - x == 0):
# cal(!(y) + !(x))
formula_lst[i] = '(!(' + form_y + ')' + " + !(" + form_x + '))'
if y <= 6 and x <= 6:
number_lst[i] = math.factorial(y) + math.factorial(x)
if ( solve(n - 1) ):
return True
# cal(!(y) - !(x)))
formula_lst[i] = '(!(' + form_y + ')' + " - !(" + form_x + '))'
if y <= 6 and x <= 6:
number_lst[i] = math.factorial(y) - math.factorial(x)
if ( solve(n - 1) ):
return True
# cal(!(y) * !(x))
formula_lst[i] = '(!(' + form_y + ')' + " * !(" + form_x + '))'
if y <= 6 and x <= 6:
number_lst[i] = math.factorial(y) * math.factorial(x)
if ( solve(n - 1) ):
return True
# cal(!(y) / !(x))
formula_lst[i] = '(!(' + form_y + ')' + " / !(" + form_x + ')'
if y <= 6 and x <= 6:
number_lst[i] = math.factorial(y) / math.factorial(x)
if ( solve(n - 1) ):
return True
# cal(!(y) // !(x))
formula_lst[i] = '(!(' + form_y + ')' + " // !(" + form_x + '))'
if y <= 6 and x <= 6:
number_lst[i] = math.factorial(y) // math.factorial(x)
if ( solve(n - 1) ):
return True
# cal(!(y) % !(x))
formula_lst[i] = '(!(' + form_y + ')' + " % !(" + form_x + '))'
if y <= 6 and x <= 6:
number_lst[i] = math.factorial(y) % math.factorial(x)
if ( solve(n - 1) ):
return True
# cal(!(y) ** !(x))
formula_lst[i] = '(!(' + form_y + ')' + " ** !(" + form_x + '))'
if (y <= 6 and (y == 0 or y == 1 or (y == 2 and abs(x) <= 4)
or (y == 3 and abs(x) <= 3) or (y == 4 and abs(x) <= 2)
or (y == 5 and abs(x) <= 2) or (y == 6 and abs(x) <= 1))):
number_lst[i] = math.factorial(y) ** math.factorial(x)
if ( solve(n - 1) ):
return True
#All the factorials part 2
if x >= 0 and (int(x) - x == 0):
# cal(!(x) + y)
formula_lst[i] = '(!(' + form_x + ')' + "+" + form_y + ')'
if x <= 6:
number_lst[i] = math.factorial(x) + y
if ( solve(n - 1) ):
return True
# cal(!(x) - y)
formula_lst[i] = '(!(' + form_x + ')' + "-" + form_y + ')'
if x <= 6:
number_lst[i] = math.factorial(x) - y
if ( solve(n - 1) ):
return True
# cal(!(x) * y)
formula_lst[i] = '(!(' + form_x + ')' + "*" + form_y + ')'
if x <= 6:
number_lst[i] = math.factorial(x) * y
if ( solve(n - 1) ):
return True
# cal(!(x) / y)
if y != 0:
formula_lst[i] = '(!(' + form_x + ')' + "/" + form_y + ')'
if x <= 6:
number_lst[i] = math.factorial(x) / y
if ( solve(n - 1) ):
return True
# cal(!(x) // y)
formula_lst[i] = '(!(' + form_x + ')' + "//" + form_y + ')'
if x <= 6:
number_lst[i] = math.factorial(x) // y
if ( solve(n - 1) ):
return True
# cal(!(x) % y)
formula_lst[i] = '(!(' + form_x + ')' + "%" + form_y + ')'
if x <= 6:
number_lst[i] = math.factorial(x) % y
if ( solve(n - 1) ):
return True
# cal(!(x) ** y)
formula_lst[i] = '(!(' + form_x + ')' + "**" + form_y + ')'
if (x <= 6 and (x == 0 or x == 1 or (x == 2 and abs(y) <= 9)
or (x == 3 and abs(y) <= 3) or (x == 4 and abs(y) <= 3)
or (x == 5 and abs(y) <= 2) or (x == 6 and abs(y) <= 1))):
number_lst[i] = math.factorial(x) ** y
if ( solve(n - 1) ):
return True
#Double
if y >= 0 and (int(y) - y == 0):
# cal(!(x) + !(y))
formula_lst[i] = '(!(' + form_x + ')' + " + !(" + form_y + '))'
if x <= 6 and y <= 6:
number_lst[i] = math.factorial(x) + math.factorial(y)
if ( solve(n - 1) ):
return True
# cal(!(x) - !(y))
formula_lst[i] = '(!(' + form_x + ')' + " - !(" + form_y + '))'
if x <= 6 and y <= 6:
number_lst[i] = math.factorial(x) - math.factorial(y)
if ( solve(n - 1) ):
return True
# cal(!(x) * !(y))
formula_lst[i] = '(!(' + form_x + ')' + " * !(" + form_y + '))'
if x <= 6 and y <= 6:
number_lst[i] = math.factorial(x) * math.factorial(y)
if ( solve(n - 1) ):
return True
# cal(!(x) / !(y))
formula_lst[i] = '(!(' + form_x + ')' + " / !(" + form_y + ')'
if x <= 6 and y <= 6:
number_lst[i] = math.factorial(x) / math.factorial(y)
if ( solve(n - 1) ):
return True
# cal(!(x) // !(y))
formula_lst[i] = '(!(' + form_x + ')' + " // !(" + form_y + '))'
if x <= 6 and y <= 6:
number_lst[i] = math.factorial(x) // math.factorial(y)
if ( solve(n - 1) ):
return True
# cal(!(x) % !(y))
formula_lst[i] = '(!(' + form_x + ')' + " % !(" + form_y + '))'
if x <= 6 and y <= 6:
number_lst[i] = math.factorial(x) % math.factorial(y)
if ( solve(n - 1) ):
return True
# cal(!(x) ** !(y))
formula_lst[i] = '(!(' + form_x + ')' + " ** !(" + form_y + '))'
if (x <= 6 and (x == 0 or x == 1 or (x == 2 and abs(y) <= 4)
or (x == 3 and abs(y) <= 3) or (x == 4 and abs(y) <= 2)
or (x == 5 and abs(y) <= 2) or (x == 6 and abs(y) <= 1))):
number_lst[i] = math.factorial(x) ** math.factorial(y)
if ( solve(n - 1) ):
return True
# resume and recursion
number_lst[i] = x
number_lst[j] = y
formula_lst[i] = form_x
formula_lst[j] = form_y
return False
if showrules:
print("Here are the rules:\nEnter \"hide\" to hide them, and \"show\" to show them\n")
print("Create a mathematical expression that equals the goal number!")
print("Traditionally only +-*/ are used, but try these for fun.")
print("% is for modulus (A%B), // for integer division (A//B), and ** for exponents (A**B)")
print("! can be used for factorial, though you type it special:\nYou do !(A) for the factorial of A")
print("Use every card once, no more, no less.")
print("If your expression has errors, we will show the first error.")
print("Be sure to use *, \"AB\" doesn't render as \"A\"*\"B\".\n")
print("You can skip questions by just typing \"skip\"")
print("If your expression is 卡ing, or takes too long,\npress Control-C on your keyboard to try with another expression")
if last == "WIN":
print("\nWIN-WIN-WIN-WIN-WIN")
print("Total points:", POINTS, "\n\n")
elif last == "SKIP":
print("\nSkipSkipSkip")
print("Total points:", POINTS, "\n\n")
st = 1
#To measure time
start = datetime.datetime.now()
while st == 1:
if showrulesinside:
print("Here are the rules:\nEnter \"hide\" to hide them, and \"show\" to show them\n")
print("Create a mathematical expression that equals the goal number!")
print("Traditionally only +-*/ are used, but try these for fun.")
print("% is for modulus (A%B), // for integer division (A//B), and ** for exponents (A**B)")
print("! can be used for factorial, though you type it special:\nYou do !(A) for the factorial of A")
print("Use every card once, no more, no less.")
print("If your expression has errors, we will show the first error.")
print("Be sure to use *, \"AB\" doesn't render as \"A\"*\"B\".\n")
print("You can skip questions by just typing \"skip\"")
print("If your expression is 卡ing, or takes too long,\npress Control-C on your keyboard to try with another expression")
showrulesinside = False
print("\n---\nCARDS:")
print("a:", a, "b:", b, "c:", c, "d:", d, end="\n\n")
print("Okay, try to make an expression that equals", win)
status = 0
sol = input("Please enter your expression (or skip/show/hide)\n(e.g. a*b*(d-c), like you would in standard python code):\n")
soln = win-1
try:
#If the expression is invalid, flip status to -1/2/3/4 etc.
status = 1
#Counts the incidence of a/b/c/d respectively.
aa = 0
bb = 0
cc = 0
dd = 0
#Checking every character in the string inputted
itt = 0
#Allow skipping the round
if sol.lower() == "skip":
st = "SKIP"
break
#Showing and hiding the rules
if sol.lower() == "show":
showrules = True
showrulesinside = True
continue
if sol.lower() == "hide":
showrules = False
continue
for i in sol.lower():
#Using the notation of ! before a parentheses as
#meaning factorial, change that to math.factorial for python to use.
if i == "!":
sol = sol[:itt]+"math.factorial"+sol[itt+1:]
#No self-inputting numbers
if i.isdigit():
status = -1
break
#Can't use a card/number more than once
elif i.isalpha():
if i == "a":
aa += 1
if aa >= 2:
status = -2
break
elif i == "b":
bb += 1
if bb >= 2:
status = -2
break
elif i == "c":
cc += 1
if cc >= 2:
status = -2
break
elif i == "d":
dd += 1
if dd >= 2:
status = -2
break
itt +=1
#Must use every card/number once
if aa + bb + cc + dd < 4 and status > 0:
status = -3
#Restrict calling math or random functions (but allow the factorial we implemented)
if sol.lower().find("math.factorial") > -1:
pass
elif sol.lower().find("math") > -1 or sol.lower().find("random") > -1:
status = -4
#If the input doesn't seem to be cheating, evaluate it
if status > 0:
soln = eval(sol.lower())
#Otherwise help print out the error that was found
#(only shows the first error found, since we want to calculate faster)
elif status == -1:
print("---\n\nNot a valid expression (used numbers):\n")
elif status == -2:
print("---\n\nNot a valid expression (used a card twice):\n")
elif status == -3:
print("---\n\nNot a valid expression (didn't use a card):\n")
elif status == -4:
print("---\n\nNot a valid expression (cannot use math or random etc. python import functions):\n")
except:
print("---\n\nTry again, not a valid python expression:\n")
continue
#If the evaluation succeeds and equals the goal number, count the win.
if soln == win:
end = datetime.datetime.now()
elapsed = end - start
#print("\n\n", elapsed.seconds, ".", elapsed.microseconds, " seconds", sep="")
time = elapsed.seconds + elapsed.microseconds/1000000
print("\n\nWin!\n===============================")
print(time, "seconds")
#Points added are the seconds of time left per 30 second round.
if 60 - time > 0:
POINTS += 60 - time
st = "WIN"
else:
end = datetime.datetime.now()
elapsed = end - start
#print("\n\n", elapsed.seconds, ".", elapsed.microseconds, " seconds", sep="")
time = elapsed.seconds + elapsed.microseconds/1000000
if 60 - time > 0:
print("---\n\nTry again.\n")
else:
if solve(4):
st = 'SKIP'
else:
print('There is no solution for this turn\n')
st = 'SKIP'
while st == "WIN":
print("Total points:", POINTS, "\n\n")
#Create new cards randomly
a, b, c, d = random.randint(1, 13), random.randint(1, 13), random.randint(1, 13), random.randint(1, 13)
last = "WIN"
st = 0
while st == "SKIP":
print("\n=====\nTotal points: Still", POINTS, "\n\n")
#Create new cards randomly
a, b, c, d = random.randint(1, 13), random.randint(1, 13), random.randint(1, 13), random.randint(1, 13)
last = "SKIP"
st = 0
| [
"noreply@github.com"
] | Ranranxz.noreply@github.com |
040710ef3328e04430cb79776b0696da99b525c8 | 3ea1e5ae80bbbfd5fac30fba33c594b91bec26a8 | /chat_screen_rcc.py | 7e4975a6201a5ec599fb0d933ea7ff813d8b19a0 | [] | no_license | kanekou/fix_ui_teams | f79c583d7281208cbe81ee70fcf23729ce468ebf | 29926406987bec212a00e6140250fb81c7b34ff6 | refs/heads/master | 2022-11-11T22:57:50.252816 | 2020-06-30T10:53:19 | 2020-06-30T10:53:19 | 268,749,971 | 0 | 0 | null | 2020-06-30T10:53:21 | 2020-06-02T08:52:21 | Python | UTF-8 | Python | false | false | 75,290 | py | # Resource object code (Python 3)
# Created by: object code
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# WARNING! All changes made in this file will be lost!
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qt_resource_struct = b"\
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def qInitResources():
QtCore.qRegisterResourceData(0x03, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(0x03, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| [
"e165726@ie.u-ryukyu.ac.jp"
] | e165726@ie.u-ryukyu.ac.jp |
5ec6d10e4c98aaf3908bec7ef9e08c081eb6147c | 39059b51a3d475972d0099ba32d575027f663abe | /tonic/environments/builders.py | 3adec879664b117d51a2f4b60fdb750576ba5b97 | [
"MIT"
] | permissive | fabiopardo/tonic | 1a8935772a0f1989263497d8b7d3e81b7b7b202d | 0e20c894ee68278ab68322de61bb2c7204a11d5f | refs/heads/master | 2023-02-23T10:36:04.941496 | 2021-12-10T16:10:25 | 2021-12-10T16:10:25 | 251,397,334 | 410 | 44 | MIT | 2023-02-21T08:59:57 | 2020-03-30T18:43:22 | Python | UTF-8 | Python | false | false | 5,357 | py | '''Environment builders for popular domains.'''
import os
import gym.wrappers
import numpy as np
from tonic import environments
from tonic.utils import logger
def gym_environment(*args, **kwargs):
'''Returns a wrapped Gym environment.'''
def _builder(*args, **kwargs):
return gym.make(*args, **kwargs)
return build_environment(_builder, *args, **kwargs)
def bullet_environment(*args, **kwargs):
'''Returns a wrapped PyBullet environment.'''
def _builder(*args, **kwargs):
import pybullet_envs # noqa
return gym.make(*args, **kwargs)
return build_environment(_builder, *args, **kwargs)
def control_suite_environment(*args, **kwargs):
'''Returns a wrapped Control Suite environment.'''
def _builder(name, *args, **kwargs):
domain, task = name.split('-')
environment = ControlSuiteEnvironment(
domain_name=domain, task_name=task, *args, **kwargs)
time_limit = int(environment.environment._step_limit)
return gym.wrappers.TimeLimit(environment, time_limit)
return build_environment(_builder, *args, **kwargs)
def build_environment(
builder, name, terminal_timeouts=False, time_feature=False,
max_episode_steps='default', scaled_actions=True, *args, **kwargs
):
'''Builds and wrap an environment.
Time limits can be properly handled with terminal_timeouts=False or
time_feature=True, see https://arxiv.org/pdf/1712.00378.pdf for more
details.
'''
# Build the environment.
environment = builder(name, *args, **kwargs)
# Get the default time limit.
if max_episode_steps == 'default':
max_episode_steps = environment._max_episode_steps
# Remove the TimeLimit wrapper if needed.
if not terminal_timeouts:
assert type(environment) == gym.wrappers.TimeLimit, environment
environment = environment.env
# Add time as a feature if needed.
if time_feature:
environment = environments.wrappers.TimeFeature(
environment, max_episode_steps)
# Scale actions from [-1, 1]^n to the true action space if needed.
if scaled_actions:
environment = environments.wrappers.ActionRescaler(environment)
environment.name = name
environment.max_episode_steps = max_episode_steps
return environment
def _flatten_observation(observation):
'''Turns OrderedDict observations into vectors.'''
observation = [np.array([o]) if np.isscalar(o) else o.ravel()
for o in observation.values()]
return np.concatenate(observation, axis=0)
class ControlSuiteEnvironment(gym.core.Env):
'''Turns a Control Suite environment into a Gym environment.'''
def __init__(
self, domain_name, task_name, task_kwargs=None, visualize_reward=True,
environment_kwargs=None
):
from dm_control import suite
self.environment = suite.load(
domain_name=domain_name, task_name=task_name,
task_kwargs=task_kwargs, visualize_reward=visualize_reward,
environment_kwargs=environment_kwargs)
# Create the observation space.
observation_spec = self.environment.observation_spec()
dim = sum([np.int(np.prod(spec.shape))
for spec in observation_spec.values()])
high = np.full(dim, np.inf, np.float32)
self.observation_space = gym.spaces.Box(-high, high, dtype=np.float32)
# Create the action space.
action_spec = self.environment.action_spec()
self.action_space = gym.spaces.Box(
action_spec.minimum, action_spec.maximum, dtype=np.float32)
def seed(self, seed):
self.environment.task._random = np.random.RandomState(seed)
def step(self, action):
try:
time_step = self.environment.step(action)
observation = _flatten_observation(time_step.observation)
reward = time_step.reward
# Remove terminations from timeouts.
done = time_step.last()
if done:
done = self.environment.task.get_termination(
self.environment.physics)
done = done is not None
self.last_time_step = time_step
# In case MuJoCo crashed.
except Exception as e:
path = logger.get_path()
os.makedirs(path, exist_ok=True)
save_path = os.path.join(path, 'crashes.txt')
error = str(e)
with open(save_path, 'a') as file:
file.write(error + '\n')
logger.error(error)
observation = _flatten_observation(self.last_time_step.observation)
observation = np.zeros_like(observation)
reward = 0.
done = True
return observation, reward, done, {}
def reset(self):
time_step = self.environment.reset()
self.last_time_step = time_step
return _flatten_observation(time_step.observation)
def render(self, mode='rgb_array', height=None, width=None, camera_id=0):
'''Returns RGB frames from a camera.'''
assert mode == 'rgb_array'
return self.environment.physics.render(
height=height, width=width, camera_id=camera_id)
# Aliases.
Gym = gym_environment
Bullet = bullet_environment
ControlSuite = control_suite_environment
| [
"f.pardo16@imperial.ac.uk"
] | f.pardo16@imperial.ac.uk |
7d66147e500b398a9f5308c4ea26ed20ffa4bac2 | 471377c48fbbfab434a051056ee064d2cf1e14b4 | /19_LittleJhool.py | c8b023d2c6338dbeb7e271edb60536646de1e3e8 | [] | no_license | Shruthi21/Algorithms-DataStructures | 8d87b782be7521dc3db15fa283be5f93d9050a9a | e611c6197e0addeaae130e0d93d7f65816b23cd5 | refs/heads/master | 2020-12-02T16:16:38.744745 | 2017-08-07T08:57:58 | 2017-08-07T08:57:58 | 96,529,354 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 841 | py | def main():
binary = [ 0 , 1 ]
binary_input = []
previous = 0
b = raw_input()
six_consecutive = 1
binary_input=map(int,list(b))
for i in range(0,len(binary_input)):
if i == 0:
previous = binary_input[i] # initialization
six_consecutive = six_consecutive + 1
else:
if previous == binary_input[i]:
six_consecutive = six_consecutive + 1
elif six_consecutive > 0:
six_consecutive = 1
previous = binary_input[i]
if six_consecutive == 6:
print 'Sorry, sorry!'
break
if six_consecutive < 6:
print "Good luck!"
if __name__ == '__main__':
main()
| [
"noreply@github.com"
] | Shruthi21.noreply@github.com |
f7d527b4cb3399a586c4de1066be16535514bece | 86720e15074e3c6bc28d344347cfd05a2bc54116 | /chat/migrations/0003_chatting_reply_message.py | 06898f29e613d0ca6e27d310754e9360cdbb4746 | [] | no_license | JboscoFrancis/Django_BlogChat | 4afc255fce0af0fcac59dedc1e0324c9c1f75df6 | 65cfd7063872f423c6fc20b1a533da44efc95e8b | refs/heads/master | 2023-02-03T19:13:54.231051 | 2020-12-20T07:45:08 | 2020-12-20T07:45:08 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 392 | py | # Generated by Django 3.1.4 on 2020-12-18 04:45
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('chat', '0002_chatting'),
]
operations = [
migrations.AddField(
model_name='chatting',
name='reply_message',
field=models.TextField(max_length=200, null=True),
),
]
| [
"jbfrancis60@gmail.com"
] | jbfrancis60@gmail.com |
608e45d914006c465c96828ec596f5dca36f2ded | 6a4e1e5826147b0ba939ed3a293fd25e47ff41b9 | /build/lib/glycowork/helper/func.py | f987412a02613f7929cdf4e59168c9100ffb95f2 | [
"MIT"
] | permissive | thomas-wiese/glycowork | 8080d5de324d100f3d97b6a7174b8e6cad5e96f9 | 2eea648f674bfe5ad3ae12956e3c619f51619718 | refs/heads/master | 2023-06-01T22:52:53.980082 | 2021-04-21T09:55:07 | 2021-04-21T09:55:07 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 808 | py | import pandas as pd
def unwrap(nested_list):
"""converts a nested list into a flat list"""
out = [item for sublist in nested_list for item in sublist]
return out
def find_nth(haystack, needle, n):
"""finds n-th instance of motif
haystack -- string to search for motif
needle -- motif
n -- n-th occurrence in string
returns starting index of n-th occurrence in string
"""
start = haystack.find(needle)
while start >= 0 and n > 1:
start = haystack.find(needle, start+len(needle))
n -= 1
return start
def load_file(file):
"""loads .csv files from glycowork package
file -- name of the file to be loaded [string]
"""
try:
temp = pd.read_csv("../glycan_data/" + file)
except:
temp = pd.read_csv("glycowork/glycan_data/" + file)
return temp
| [
"daniel@bojar.net"
] | daniel@bojar.net |
503cbc78d9f6e0910d577259e1c733d92a4a3a30 | 2eff2b24d5b6f5dffc42c9cbde6102ec9317502f | /src/Calculator.py | 8893fae57e0cb5134c33ea8b75b81954ec9c8cbf | [] | no_license | JakobKallestad/Python-Kattis | 599a14e71a8d5c52aae779b8db3d35f0e4d01e88 | 51656964e79cc861e53f574785aacb213ef10b46 | refs/heads/master | 2022-10-24T23:12:45.599813 | 2021-12-08T12:31:54 | 2021-12-08T12:31:54 | 156,881,692 | 2 | 1 | null | 2022-10-02T12:36:57 | 2018-11-09T15:34:09 | Python | UTF-8 | Python | false | false | 147 | py |
while True:
try:
line = input()
result = eval(line)
print("{:.2f}".format(result))
except EOFError:
break
| [
"Jakob.Kallestad@student.uib.no"
] | Jakob.Kallestad@student.uib.no |
5e502e6a8f31e345307af4c6bcc63e0a2132c326 | 4dbaea97b6b6ba4f94f8996b60734888b163f69a | /LeetCode/48.py | c4d4841c02151f4c9dd1b1d227a3fef532cd49d0 | [] | no_license | Ph0en1xGSeek/ACM | 099954dedfccd6e87767acb5d39780d04932fc63 | b6730843ab0455ac72b857c0dff1094df0ae40f5 | refs/heads/master | 2022-10-25T09:15:41.614817 | 2022-10-04T12:17:11 | 2022-10-04T12:17:11 | 63,936,497 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 667 | py | class Solution:
def rotate(self, matrix):
"""
:type matrix: List[List[int]]
:rtype: void Do not return anything, modify matrix in-place instead.
"""
matrix_len = len(matrix)
for i in range(matrix_len // 2):
for j in range(matrix_len - matrix_len // 2):
tmp = matrix[i][j]
matrix[i][j] = matrix[matrix_len - j - 1][i]
matrix[matrix_len - j - 1][i] = matrix[matrix_len - i - 1][matrix_len - j - 1]
matrix[matrix_len - i - 1][matrix_len - j - 1] = matrix[j][matrix_len - i - 1]
matrix[j][matrix_len - i - 1] = tmp | [
"54panguosheng@gmail.com"
] | 54panguosheng@gmail.com |
d41c16e629b4e5deaf26083d8fcecd79a433675b | 7f4191f0e12a70d465b15762ce83b57b4976d448 | /Chapter8/Xtreme_InjectCrawler/XtremeWebAPP/xtreme_server/migrations/0006_initial.py | 27e52ef1bae65d1cc75b98e05ce6a9b297056084 | [] | no_license | PacktPublishing/Hands-On-Penetration-Testing-with-Python | 33f72df57b9158e002f78330c1242e1fde777898 | 7b11c8e63e4ac350ba138161f60f7ce4c08ed7cd | refs/heads/master | 2023-02-06T04:52:12.475428 | 2023-01-30T10:03:47 | 2023-01-30T10:03:47 | 131,272,051 | 79 | 40 | null | null | null | null | UTF-8 | Python | false | false | 12,669 | py | # -*- coding: utf-8 -*-
from south.utils import datetime_utils as datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Adding model 'Project'
db.create_table(u'xtreme_server_project', (
('project_name', self.gf('django.db.models.fields.CharField')(max_length=50, primary_key=True)),
('start_url', self.gf('django.db.models.fields.URLField')(max_length=200)),
('query_url', self.gf('django.db.models.fields.URLField')(max_length=200)),
('allowed_extensions', self.gf('django.db.models.fields.TextField')()),
('allowed_protocols', self.gf('django.db.models.fields.TextField')()),
('consider_only', self.gf('django.db.models.fields.TextField')()),
('exclude_fields', self.gf('django.db.models.fields.TextField')()),
('status', self.gf('django.db.models.fields.CharField')(default='Not Set', max_length=50)),
('login_url', self.gf('django.db.models.fields.URLField')(max_length=200)),
('logout_url', self.gf('django.db.models.fields.URLField')(max_length=200)),
('username', self.gf('django.db.models.fields.TextField')()),
('password', self.gf('django.db.models.fields.TextField')()),
('username_field', self.gf('django.db.models.fields.TextField')(default='Not Set')),
('password_field', self.gf('django.db.models.fields.TextField')(default='Not Set')),
('auth_mode', self.gf('django.db.models.fields.TextField')()),
))
db.send_create_signal(u'xtreme_server', ['Project'])
# Adding model 'Page'
db.create_table(u'xtreme_server_page', (
(u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('URL', self.gf('django.db.models.fields.URLField')(max_length=200)),
('content', self.gf('django.db.models.fields.TextField')(blank=True)),
('visited', self.gf('django.db.models.fields.BooleanField')(default=False)),
('auth_visited', self.gf('django.db.models.fields.BooleanField')(default=False)),
('status_code', self.gf('django.db.models.fields.CharField')(max_length=256, blank=True)),
('connection_details', self.gf('django.db.models.fields.TextField')(blank=True)),
('project', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xtreme_server.Project'])),
('page_found_on', self.gf('django.db.models.fields.URLField')(max_length=200, blank=True)),
))
db.send_create_signal(u'xtreme_server', ['Page'])
# Adding model 'Form'
db.create_table(u'xtreme_server_form', (
(u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('project', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xtreme_server.Project'])),
('form_found_on', self.gf('django.db.models.fields.URLField')(max_length=200)),
('form_name', self.gf('django.db.models.fields.CharField')(max_length=512, blank=True)),
('form_method', self.gf('django.db.models.fields.CharField')(default='GET', max_length=10)),
('form_action', self.gf('django.db.models.fields.URLField')(max_length=200, blank=True)),
('form_content', self.gf('django.db.models.fields.TextField')(blank=True)),
('auth_visited', self.gf('django.db.models.fields.BooleanField')(default=False)),
('input_field_list', self.gf('django.db.models.fields.TextField')(blank=True)),
))
db.send_create_signal(u'xtreme_server', ['Form'])
# Adding model 'InputField'
db.create_table(u'xtreme_server_inputfield', (
(u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('form', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xtreme_server.Form'])),
('input_type', self.gf('django.db.models.fields.CharField')(default='input', max_length=256, blank=True)),
))
db.send_create_signal(u'xtreme_server', ['InputField'])
# Adding model 'Vulnerability'
db.create_table(u'xtreme_server_vulnerability', (
(u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('form', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xtreme_server.Form'])),
('details', self.gf('django.db.models.fields.TextField')(blank=True)),
))
db.send_create_signal(u'xtreme_server', ['Vulnerability'])
# Adding model 'Settings'
db.create_table(u'xtreme_server_settings', (
(u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('allowed_extensions', self.gf('django.db.models.fields.TextField')()),
('allowed_protocols', self.gf('django.db.models.fields.TextField')()),
('consider_only', self.gf('django.db.models.fields.TextField')()),
('exclude_fields', self.gf('django.db.models.fields.TextField')()),
('username', self.gf('django.db.models.fields.TextField')()),
('password', self.gf('django.db.models.fields.TextField')()),
('auth_mode', self.gf('django.db.models.fields.TextField')()),
))
db.send_create_signal(u'xtreme_server', ['Settings'])
# Adding model 'LearntModel'
db.create_table(u'xtreme_server_learntmodel', (
(u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('project', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xtreme_server.Project'])),
('page', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xtreme_server.Page'])),
('form', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xtreme_server.Form'])),
('query_id', self.gf('django.db.models.fields.TextField')()),
('learnt_model', self.gf('django.db.models.fields.TextField')(blank=True)),
))
db.send_create_signal(u'xtreme_server', ['LearntModel'])
def backwards(self, orm):
# Deleting model 'Project'
db.delete_table(u'xtreme_server_project')
# Deleting model 'Page'
db.delete_table(u'xtreme_server_page')
# Deleting model 'Form'
db.delete_table(u'xtreme_server_form')
# Deleting model 'InputField'
db.delete_table(u'xtreme_server_inputfield')
# Deleting model 'Vulnerability'
db.delete_table(u'xtreme_server_vulnerability')
# Deleting model 'Settings'
db.delete_table(u'xtreme_server_settings')
# Deleting model 'LearntModel'
db.delete_table(u'xtreme_server_learntmodel')
models = {
u'xtreme_server.form': {
'Meta': {'object_name': 'Form'},
'auth_visited': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'form_action': ('django.db.models.fields.URLField', [], {'max_length': '200', 'blank': 'True'}),
'form_content': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
'form_found_on': ('django.db.models.fields.URLField', [], {'max_length': '200'}),
'form_method': ('django.db.models.fields.CharField', [], {'default': "'GET'", 'max_length': '10'}),
'form_name': ('django.db.models.fields.CharField', [], {'max_length': '512', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'input_field_list': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
'project': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xtreme_server.Project']"})
},
u'xtreme_server.inputfield': {
'Meta': {'object_name': 'InputField'},
'form': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xtreme_server.Form']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'input_type': ('django.db.models.fields.CharField', [], {'default': "'input'", 'max_length': '256', 'blank': 'True'})
},
u'xtreme_server.learntmodel': {
'Meta': {'object_name': 'LearntModel'},
'form': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xtreme_server.Form']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'learnt_model': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
'page': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xtreme_server.Page']"}),
'project': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xtreme_server.Project']"}),
'query_id': ('django.db.models.fields.TextField', [], {})
},
u'xtreme_server.page': {
'Meta': {'object_name': 'Page'},
'URL': ('django.db.models.fields.URLField', [], {'max_length': '200'}),
'auth_visited': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'connection_details': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
'content': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'page_found_on': ('django.db.models.fields.URLField', [], {'max_length': '200', 'blank': 'True'}),
'project': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xtreme_server.Project']"}),
'status_code': ('django.db.models.fields.CharField', [], {'max_length': '256', 'blank': 'True'}),
'visited': ('django.db.models.fields.BooleanField', [], {'default': 'False'})
},
u'xtreme_server.project': {
'Meta': {'object_name': 'Project'},
'allowed_extensions': ('django.db.models.fields.TextField', [], {}),
'allowed_protocols': ('django.db.models.fields.TextField', [], {}),
'auth_mode': ('django.db.models.fields.TextField', [], {}),
'consider_only': ('django.db.models.fields.TextField', [], {}),
'exclude_fields': ('django.db.models.fields.TextField', [], {}),
'login_url': ('django.db.models.fields.URLField', [], {'max_length': '200'}),
'logout_url': ('django.db.models.fields.URLField', [], {'max_length': '200'}),
'password': ('django.db.models.fields.TextField', [], {}),
'password_field': ('django.db.models.fields.TextField', [], {'default': "'Not Set'"}),
'project_name': ('django.db.models.fields.CharField', [], {'max_length': '50', 'primary_key': 'True'}),
'query_url': ('django.db.models.fields.URLField', [], {'max_length': '200'}),
'start_url': ('django.db.models.fields.URLField', [], {'max_length': '200'}),
'status': ('django.db.models.fields.CharField', [], {'default': "'Not Set'", 'max_length': '50'}),
'username': ('django.db.models.fields.TextField', [], {}),
'username_field': ('django.db.models.fields.TextField', [], {'default': "'Not Set'"})
},
u'xtreme_server.settings': {
'Meta': {'object_name': 'Settings'},
'allowed_extensions': ('django.db.models.fields.TextField', [], {}),
'allowed_protocols': ('django.db.models.fields.TextField', [], {}),
'auth_mode': ('django.db.models.fields.TextField', [], {}),
'consider_only': ('django.db.models.fields.TextField', [], {}),
'exclude_fields': ('django.db.models.fields.TextField', [], {}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'password': ('django.db.models.fields.TextField', [], {}),
'username': ('django.db.models.fields.TextField', [], {})
},
u'xtreme_server.vulnerability': {
'Meta': {'object_name': 'Vulnerability'},
'details': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
'form': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xtreme_server.Form']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'})
}
}
complete_apps = ['xtreme_server'] | [
"furqankhan08@gmail.com"
] | furqankhan08@gmail.com |
e98f6fa0b77ada500f2989e87256f196bf55a3a7 | c0201cc5b557bf067e0ced652cf7a65b3a881c8f | /parser.py | 48c442a21b5b161dc2185eb7d83d33ff103d438e | [] | no_license | salerno/MacrosPython | 94e931c3c06203145c38f60412d5afd12d0ab5df | c33b956b863a10b362ff64e51cd24572d071cf28 | refs/heads/master | 2021-01-17T15:31:15.073178 | 2016-05-24T09:15:19 | 2016-05-24T09:15:19 | 18,142,746 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,223 | py | import os
import glob
from tempfile import mkstemp
from shutil import move
from os import remove, close
def replace(file_path, file_path_out, pattern, subst):
#Create temp file
#abs_path = mkstemp()
#new_file = open(abs_path,'w')
new_file = open(file_path_out,'w')
old_file = open(file_path)
for line in old_file:
new_file.write(line.replace(pattern, subst))
#close temp file
new_file.close()
old_file.close()
#Remove original file
#remove(file_path)
#Move new file
#move(abs_path, file_path)
path = '/Users/salerno/Desktop/FinitiCHEF/'
path_out = '/Users/salerno/Desktop/FinitiCHEF/CodeReadFiles/'
##current directory
#for filename in os.listdir(os.getcwd()):
##directory specified in path
#for filename in os.listdir(path):
for filename in glob.glob(os.path.join(path, 'CH*.pdf')):
# do stuff
print(filename)
print(path_out+filename.split('/')[-1])
replace(filename,path_out+filename.split('/')[-1],'Creator (TeX)','Creator (Rob)')
print(path_out+filename.split('/')[-1])
print(path_out+'new'+filename.split('/')[-1])
replace(path_out+filename.split('/')[-1],path_out+'new'+filename.split('/')[-1],'/Producer (pdfTeX-1.40.14)','') | [
"salerno@RobMac.local"
] | salerno@RobMac.local |
2751437f81253f6762b521912bf1187f9551bfb7 | bfdab27f224d9cac02e319fe55b53172fbf8d1a2 | /motion_editor_core/data/atlas_old/motions/drive_pull_right.py | a5356f2535ecc1d9343c53befe481a534536d151 | [] | no_license | tu-darmstadt-ros-pkg/motion_editor | c18294b4f035f737ff33d1dcbdfa87d4bb4e6f71 | 178a7564b18420748e1ca4413849a44965823655 | refs/heads/master | 2020-04-06T12:37:30.763325 | 2016-09-15T14:11:48 | 2016-09-15T14:11:48 | 35,028,245 | 2 | 3 | null | 2015-05-05T13:20:27 | 2015-05-04T10:18:22 | Python | UTF-8 | Python | false | false | 2,338 | py | { 'drive_pull_right': { 'l_arm': [],
'l_leg': [],
'r_arm': [ { 'duration': 1.0,
'name': u'vm_arm_r_retract_up',
'positions': [ -0.2258,
-0.5361,
3.1416,
-2.3456,
-0.3547,
-1.5618],
'starttime': 0.0},
{ 'duration': 1.0,
'name': u'vm_arm_r_retract_up_up',
'positions': [ -0.2258,
-1.2716,
3.1416,
-2.3562,
-0.3547,
-1.5618],
'starttime': 1.0},
{ 'duration': 1.0,
'name': u'vm_arm_r_retract_up_right',
'positions': [ -0.2258,
-1.2716,
3.1416,
-1.4144,
-0.3547,
-0.759],
'starttime': 2.0},
{ 'duration': 1.0,
'name': u'vm_arm_r_retract_down',
'positions': [ -0.2258,
1.3963,
3.1416,
-1.4144,
-0.3547,
-0.759],
'starttime': 3.0}],
'r_leg': [],
'torso': []}}
| [
"martin.sven.oehler@gmail.com"
] | martin.sven.oehler@gmail.com |
d6fb7ae0e44140ca334a1a60b46e34cd2524ea5d | 8b2c7ce8de3b158104f8442c5aabb234f6c17807 | /plato/venv/lib/python3.5/token.py | b05d72f7392865fb7fab9cefa7034a9328f4802b | [] | no_license | dylancashman/active_model_selection | 586536dfc92bc3c51a88c8a8352ae29f8f6279f8 | 6f4f73ff0c7fd2c1e57ecb7677e7188d38484e6d | refs/heads/master | 2023-01-31T23:22:47.466576 | 2020-02-19T14:29:09 | 2020-02-19T14:29:09 | 209,342,677 | 0 | 1 | null | 2023-01-12T12:02:39 | 2019-09-18T15:27:55 | Python | UTF-8 | Python | false | false | 51 | py | /Users/dylancashman/anaconda/lib/python3.5/token.py | [
"dylan.cashman@annkissam.com"
] | dylan.cashman@annkissam.com |
7e7db89059aa6482d6801ca06d86ca389c337e25 | 4ca821475c57437bb0adb39291d3121d305905d8 | /models/research/swivel/vecs.py | 61a2b7a852dd4c1a577d240c1c990423ddcbb77c | [
"Apache-2.0"
] | permissive | yefcion/ShipRec | 4a1a893b2fd50d34a66547caa230238b0bf386de | c74a676b545d42be453729505d52e172d76bea88 | refs/heads/master | 2021-09-17T04:49:47.330770 | 2018-06-28T02:25:50 | 2018-06-28T02:25:50 | 112,176,613 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 3,226 | py | # Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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 mmap
import numpy as np
import os
from six import string_types
class Vecs(object):
def __init__(self, vocab_filename, rows_filename, cols_filename=None):
"""Initializes the vectors from a text vocabulary and binary data."""
with open(vocab_filename, 'r') as lines:
self.vocab = [line.split()[0] for line in lines]
self.word_to_idx = {word: idx for idx, word in enumerate(self.vocab)}
n = len(self.vocab)
with open(rows_filename, 'r') as rows_fh:
rows_fh.seek(0, os.SEEK_END)
size = rows_fh.tell()
# Make sure that the file size seems reasonable.
if size % (4 * n) != 0:
raise IOError(
'unexpected file size for binary vector file %s' % rows_filename)
# Memory map the rows.
dim = size / (4 * n)
rows_mm = mmap.mmap(rows_fh.fileno(), 0, prot=mmap.PROT_READ)
rows = np.matrix(
np.frombuffer(rows_mm, dtype=np.float32).reshape(n, dim))
# If column vectors were specified, then open them and add them to the
# row vectors.
if cols_filename:
with open(cols_filename, 'r') as cols_fh:
cols_mm = mmap.mmap(cols_fh.fileno(), 0, prot=mmap.PROT_READ)
cols_fh.seek(0, os.SEEK_END)
if cols_fh.tell() != size:
raise IOError('row and column vector files have different sizes')
cols = np.matrix(
np.frombuffer(cols_mm, dtype=np.float32).reshape(n, dim))
rows += cols
cols_mm.close()
# Normalize so that dot products are just cosine similarity.
self.vecs = rows / np.linalg.norm(rows, axis=1).reshape(n, 1)
rows_mm.close()
def similarity(self, word1, word2):
"""Computes the similarity of two tokens."""
idx1 = self.word_to_idx.get(word1)
idx2 = self.word_to_idx.get(word2)
if not idx1 or not idx2:
return None
return float(self.vecs[idx1] * self.vecs[idx2].transpose())
def neighbors(self, query):
"""Returns the nearest neighbors to the query (a word or vector)."""
if isinstance(query, string_types):
idx = self.word_to_idx.get(query)
if idx is None:
return None
query = self.vecs[idx]
neighbors = self.vecs * query.transpose()
return sorted(
zip(self.vocab, neighbors.flat),
key=lambda kv: kv[1], reverse=True)
def lookup(self, word):
"""Returns the embedding for a token, or None if no embedding exists."""
idx = self.word_to_idx.get(word)
return None if idx is None else self.vecs[idx]
| [
"yefcion@163.com"
] | yefcion@163.com |
14f97daa71e3031be3ebe6b910952c419df9c3af | c9edc9db802cc0b86821d1ed2db0f4564e8e91f5 | /products/models.py | d012c3d217c208223fc5a90a42a3fdd57516224f | [
"Apache-2.0"
] | permissive | jojordan3/website_django | aa2b0afd7ba98842bf368a1619592f369add75d4 | b743e70f26a94d692ffe6b4c74489bb8a3daf076 | refs/heads/master | 2022-12-22T00:12:30.313233 | 2019-05-23T00:04:06 | 2019-05-23T00:04:06 | 186,329,708 | 0 | 0 | NOASSERTION | 2022-12-08T05:08:55 | 2019-05-13T02:10:56 | HTML | UTF-8 | Python | false | false | 3,990 | py | from django.db import models
from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger
from wagtail.core.models import Page, Orderable
from wagtail.core.fields import RichTextField
from wagtail.images.edit_handlers import ImageChooserPanel
from wagtail.images.models import Image
from wagtail.admin.edit_handlers import (
FieldPanel, MultiFieldPanel, InlinePanel
)
from modelcluster.fields import ParentalKey
from modelcluster.tags import ClusterTaggableManager
from taggit.models import Tag, TaggedItemBase
from utils.models import RelatedLink
# Product page
class ProductIndexPageRelatedLink(Orderable, RelatedLink):
page = ParentalKey(
'products.ProductIndexPage', related_name='related_links'
)
class ProductIndexPage(Page):
subtitle = models.CharField(max_length=255, blank=True)
intro = RichTextField(blank=True)
feed_image = models.ForeignKey(
'wagtailimages.Image',
null=True,
blank=True,
on_delete=models.SET_NULL,
related_name='+'
)
indexed_fields = ('intro', )
@property
def products(self):
# Get list of live blog pages that are descendants of this page
products = ProductPage.objects.live().descendant_of(self)
return products
@property
def tag_list(self):
tag_ids = ProductPageTag.objects.all().values_list('tag_id', flat=True)
return Tag.objects.filter(pk__in=tag_ids)
def get_context(self, request):
# Get products
products = self.products
# Filter by tag
tag = request.GET.get('tag')
if tag:
products = products.filter(tags__name=tag)
# Pagination
page = request.GET.get('page')
paginator = Paginator(products, 12) # Show 10 products per page
try:
products = paginator.page(page)
except PageNotAnInteger:
products = paginator.page(1)
except EmptyPage:
products = paginator.page(paginator.num_pages)
# Update template context
context = super(ProductIndexPage, self).get_context(request)
context['products'] = products
return context
ProductIndexPage.content_panels = [
FieldPanel('title', classname="full title"),
FieldPanel('subtitle'),
FieldPanel('intro', classname="full"),
InlinePanel('related_links', label="Related links"),
]
ProductIndexPage.promote_panels = [
MultiFieldPanel(Page.promote_panels, "Common page configuration"),
ImageChooserPanel('feed_image'),
]
class ProductPageRelatedLink(Orderable, RelatedLink):
page = ParentalKey('products.ProductPage', related_name='related_links')
class ProductPageTag(TaggedItemBase):
content_object = ParentalKey(
'products.ProductPage', related_name='tagged_items'
)
def __unicode__(self):
return self.name
class ProductPage(Page):
price = models.CharField(max_length=255, blank=True)
description = RichTextField(blank=True)
intro = models.CharField(max_length=255, blank=True)
tags = ClusterTaggableManager(through=ProductPageTag, blank=True)
image = models.ForeignKey(
Image,
null=True,
blank=True,
on_delete=models.SET_NULL,
related_name='+'
)
feed_image = models.ForeignKey(
Image,
null=True,
blank=True,
on_delete=models.SET_NULL,
related_name='+'
)
indexed_fields = ('title', 'intro', 'biography')
ProductPage.content_panels = [
FieldPanel('title', classname="title"),
FieldPanel('intro', classname="full"),
FieldPanel('price', classname="full"),
FieldPanel('description', classname="full"),
ImageChooserPanel('image'),
FieldPanel('link_demo'),
FieldPanel('tags'),
InlinePanel('related_links', label="Related links"),
]
ProductPage.promote_panels = [
MultiFieldPanel(Page.promote_panels, "Common page configuration"),
ImageChooserPanel('feed_image'),
]
| [
"joanne.k.m.jordan@gmail.com"
] | joanne.k.m.jordan@gmail.com |
f9bcb3dcc1970423f97e39ba9072f214fd2b4bf9 | a2a14995c95e024644623ea26add2f27d186ea16 | /go.py | dff7c109c90a18c87abe03834f8ab27f33530049 | [
"MIT"
] | permissive | swdevbali/lit | 89db51ae912770ac4030a3c491ad775a68b95a4b | dbc01ee8e4e600a0a43e49ffd18873653cc3f7cc | refs/heads/master | 2021-01-21T00:25:50.001045 | 2013-02-16T13:52:50 | 2013-02-16T13:52:50 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,447 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import windows as winutils
from datetime import datetime
from utils import Query
from PyQt4.QtCore import (
Qt,
QAbstractListModel,
QMutex,
QMutexLocker
)
import itertools
import logging
from lcs import lcs
NAME_LIMIT = 42
class Task(object):
def __init__(self, hwnd, query, usetime):
self.hwnd = hwnd
self.query = query
self.usetime = usetime
def use(self):
self.usetime = datetime.now()
@property
def digest(self):
if len(self.name) > NAME_LIMIT:
shortname = self.name[:NAME_LIMIT - 3] + '...'
else:
shortname = self.name
if self.filename:
return '%s (%s)' % (shortname, self.filename)
else:
return shortname
@property
def title(self):
return self.name
@property
def fullname(self):
if self.filename:
return self.title + self.filename
else:
return self.title
@property
def filename(self):
if not hasattr(self, '_filename'):
self._filename = winutils.get_app_name(self.hwnd)
return self._filename
@property
def name(self):
return winutils.window_title(self.hwnd)
@property
def icon(self):
if not hasattr(self, '_icon'):
self._icon = winutils.get_window_icon(self.hwnd)
return self._icon
class WindowModel(QAbstractListModel):
NAME_ROLE = Qt.DisplayRole
HWND_ROLE = Qt.UserRole
def __init__(self, items):
self.super.__init__()
self.items = items
@property
def super(self):
return super(WindowModel, self)
def rowCount(self, parent):
return len(self.items)
def columnCount(self, parent):
return 1
def data(self, index, role):
if not index.isValid():
return None
if role == Qt.TextAlignmentRole:
return int(Qt.AlignLeft | Qt.AlignVCenter)
elif role == Qt.DisplayRole:
return self.items[index.row()].digest
elif role == Qt.DecorationRole:
return self.items[index.row()].icon
elif role == Qt.UserRole:
return self.items[index.row()].hwnd
else:
return None
class Go(object):
def __init__(self, worker, client):
self.tasks = {}
self.mutex = QMutex()
self.worker = worker
self.client = client
@property
def name(self):
return 'g'
def lit(self, query, upper_bound, finished, *args, **kargs):
self.worker.do(
make=lambda: WindowModel(
self.sorted_active_runnable(
query,
winutils.top_level_windows()
)[:upper_bound]
),
catch=finished,
main=True
)
def sorted_active_runnable(self, query, hwnds):
with QMutexLocker(self.mutex):
# update query and collect active ones
self._refresh_tasks(hwnds, query)
active_tasks = [self.tasks[h] for h in hwnds]
# sort by last use
if not query:
return sorted(active_tasks, key=lambda t: t.usetime, reverse=True)
titles = [task.fullname.lower() for task in active_tasks]
def f(task, title):
return task.query.distance_to(title)
ds = [f(task, title) * (10 ** len(query)) for task, title in zip(active_tasks, titles)]
best = ds[0]
for i in itertools.takewhile(lambda i: ds[i] == best, range(len(ds))):
ds[i] -= len(lcs(query, titles[i]))
#return sorted(active_tasks, key=f)
return [task for i, task in sorted(enumerate(active_tasks), key=lambda i: ds[i[0]])]
def _refresh_tasks(self, hwnds, query=None):
for hwnd in hwnds:
if not hwnd in self.tasks:
self.tasks[hwnd] = Task(
hwnd=hwnd,
usetime=datetime.now(),
query=Query(
text='' if query is None else query,
insertion_cost=1,
first_insertion_cost=50,
prepend_first_insertion_cost=5,
append_first_insertion_cost=10,
deletion_cost=100,
substitution_cost=100,
transposition_cost=10
)
)
elif not query is None:
self.tasks[hwnd].query.update(query.lower())
def update_usetime(self, hwnd):
"""Update with one time delay."""
if hasattr(self, 'after_select') and self.after_select:
self.after_select()
self.after_select = self.tasks[hwnd].use
def select(self, content, index):
# check content type
if not isinstance(content, WindowModel):
logging.info('wrong content type {}'.format(type(content)))
return
for hwnd in winutils.top_level_windows():
if content.data(index, WindowModel.HWND_ROLE) == hwnd:
self._refresh_tasks([hwnd])
self.client.goto(hwnd=hwnd)
self.update_usetime(hwnd)
return
# remove invalid tasks
del self.tasks[content.data(index, WindowModel.HWND_ROLE)]
| [
"answeror@gmail.com"
] | answeror@gmail.com |
0659d7826f012a4a77173ff1cd94f53a96dcf0ad | 1db2e2238b4ef9c1b6ca3b99508693ee254d6904 | /develop/align_atoms/make_alignment.py | e2c2c5a27921bc05091c8e561cda56f058e951c7 | [] | no_license | pgreisen/pythonscripts | 8674e08095f76edf08ef2059300349218079724c | 0aadf8f96d19b306c1bc44a772e766a06fe3408b | refs/heads/master | 2021-07-06T23:54:57.774342 | 2021-06-08T19:36:36 | 2021-06-08T19:36:36 | 22,017,192 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,251 | py | import os,shutil,sys
from translate_rotate import *
class pdbfile:
# Requires floating point number
# Returns floating point with correct
# number of digits for pdb
def set_number_digits(self,number):
return '%.3f' %number
def set_length_digit(self,number):
lngth = len(number)
if lngth == 7:
return ' '+number
if lngth == 6:
return ' '+number
if lngth == 5:
return ' '+number
if lngth == 4:
return ' '+number
else:
return number
# Method to get data from each rotamer
def get_data_to_align(self,filename):
tmp_chi = open(filename,'r')
atoms = ['ZN1','ZN2','O5','O1']
dic = {}
for line in tmp_chi:
tmp = line.split()
if tmp[2] in atoms:
dic[tmp[2]] = line
wrt = open('tmp.pdb','w')
wrt.write(str(dic['ZN2']))
wrt.write(str(dic['ZN1']))
wrt.write(str(dic['O5']))
wrt.write(str(dic['O1']))
wrt.close()
# took directory with conformations of ligand ensemble
# if we generate the ensemble after the alignment this is not
# necessary
# Returns a list with transformed coordinates
def get_aligned_coor(self,path,VIZ,templateFile,crystal_coor):
RMSD_TRESHOLD = 0.8
obj = align_to_substrate()
files = os.listdir(path)
outfile = []
# Reading data from crystal structure where one wants
# the alignment from
cry_data,atom_names = obj.get_data(crystal_coor)
for fl in files:
ph = path+'/'+fl
rd = open(ph,'r')
# Hvad indeholder denne file og hvor er den genereret
# Filen indeholder data fra modellen, altsaa de data
# som vi har lavet for vores model system
self.get_data_to_align(ph)
fname = 'tmp.pdb'
# her faar vi navne
sub_data,atom_names = obj.get_data(fname)
# Superimpose substrate data in crystal structure
# getting the translation and rotation matrix
t_m, r_m = obj.get_rotate_translate(sub_data,cry_data)
# Getting the transformed coordinates
nw = obj.get_transformed_coor(sub_data,cry_data)
rmsd_align = obj.get_rmsd(nw,cry_data)
print 'rmsd_align',rmsd_align
print 'rmsd ', rmsd_align
if rmsd_align < RMSD_TRESHOLD:
# We transform the original data
sub,at = obj.get_data(ph)
# The transformed coordinates
# what is their construction
t_c = dot(sub,r_m)+t_m
# Writing the coordinates
# Files name of coordinates is
# Writing to a file called superimposed.pdb
obj.write_pdb(at,t_c)
# Rosetta naming convention file which is generated
# earlier.
# File for rosetta with the correct naming
# I/O of file
sp_file = open('superimposed.pdb','r')
rosetta = open(templateFile,'r')
fileOne = sp_file.readlines()
fileTwo = rosetta.readlines()
rosetta.close()
# Variable to count line number in other file
# used to insert at the right line
ct = 0
for i in fileTwo:
ln = fileOne[ct].split()
# A very temporary fix for the number greater 100
x = self.set_number_digits(float(ln[6]))
y = self.set_number_digits(float(ln[7]))
z = self.set_number_digits(float(ln[8]))
x = self.set_length_digit(x)
y = self.set_length_digit(y)
z = self.set_length_digit(z)
i = str(i[0:30])+x+y+z+str(i[55:81])
outfile.append(i)
ct = ct +1
outfile.append(VIZ)
return outfile
| [
"pgreisen@gmail.com"
] | pgreisen@gmail.com |
99698bb2efe8e38a571b025d7779967c2f87dbd9 | 1af52277feb54a8e8ae075200b1eae4c82d7b65c | /parsers/NG.py | 0cd46a03349038419241dd06e7b8f0c23d3406cf | [
"MIT"
] | permissive | joshjauregi/electricitymap-contrib | ff2ded473ced98e3442cb9ef9f89d40905c481f2 | 4207cae9ee6f751b6c755b130b5c38ede26071db | refs/heads/master | 2023-03-11T10:30:33.960119 | 2021-02-19T09:48:13 | 2021-02-19T09:48:13 | 341,297,623 | 0 | 0 | MIT | 2021-02-22T21:40:53 | 2021-02-22T18:29:09 | null | UTF-8 | Python | false | false | 3,056 | py | #!/usr/bin/env python3
"""Parser for the electricity grid of Nigeria"""
import arrow
import logging
import requests
from bs4 import BeautifulSoup
LIVE_PRODUCTION_API_URL = "https://www.niggrid.org/GenerationLoadProfileBinary?readingDate={0}&readingTime={1}"
TYPE_MAPPING = {"hydro": "hydro", "gas": "gas", "gas/steam": "gas", "steam": "gas"}
def extract_name_tech(company):
parts = company.split("(")
tech = parts[1].strip(")").lower()
return parts[0], TYPE_MAPPING[tech]
def template_response(zone_key, datetime, source):
return {
"zoneKey": zone_key,
"datetime": datetime,
"production": {
"gas": 0.0,
"hydro": 0.0,
},
"storage": {},
"source": source,
}
def fetch_production(
zone_key=None,
session=None,
target_datetime=None,
logger=logging.getLogger(__name__),
):
"""Requests the last known production mix (in MW) of a given zone
Arguments:
zone_key (optional) -- used in case a parser is able to fetch multiple zones
session (optional) -- request session passed in order to re-use an existing session
target_datetime (optional) -- used if parser can fetch data for a specific day, a string in the form YYYYMMDD
logger (optional) -- handles logging when parser is run
Return:
A list of dictionaries in the form:
{
'zoneKey': 'FR',
'datetime': '2017-01-01T00:00:00Z',
'production': {
'biomass': 0.0,
'coal': 0.0,
'gas': 0.0,
'hydro': 0.0,
'nuclear': null,
'oil': 0.0,
'solar': 0.0,
'wind': 0.0,
'geothermal': 0.0,
'unknown': 0.0
},
'storage': {
'hydro': -10.0,
},
'source': 'mysource.com'
}
"""
if target_datetime is not None:
timestamp = arrow.get(target_datetime).to("Africa/Lagos").replace(minute=0)
else:
timestamp = arrow.now(tz="Africa/Lagos").replace(minute=0)
dt_day = timestamp.format("DD/MM/YYYY")
dt_hm = timestamp.format("HH:mm")
fullUrl = LIVE_PRODUCTION_API_URL.format(dt_day, dt_hm)
r = session or requests.session()
resp = r.get(fullUrl)
try:
soup = BeautifulSoup(resp.text, "html.parser")
table = soup.find("table", {"id": "MainContent_gvGencoLoadProfiles"})
rows = table.find_all("tr")[1:-1] # ignore header and footer rows
except AttributeError:
raise LookupError("No data currently available for Nigeria.")
result = template_response(zone_key, timestamp.datetime, "niggrid.org")
for row in rows:
_, company, mw, _ = map(lambda row: row.text.strip(), row.find_all("td"))
_, tech = extract_name_tech(company)
result["production"][tech] += float(mw)
return [result]
if __name__ == "__main__":
"""Main method, never used by the Electricity Map backend, but handy for testing."""
print(fetch_production())
print(fetch_production(target_datetime=arrow.get("20210110", "YYYYMMDD")))
| [
"noreply@github.com"
] | joshjauregi.noreply@github.com |
1a24a1dd54c80829aabc3695256b1fe53a23ca48 | 00a5e7bfc42d222f77fceea22bc18aad736f5311 | /TwoPointers/Find-Duplicate-Number.py | a16e578f3f51063a6518a4638be45f9b65b44a49 | [] | no_license | alvinwang922/Data-Structures-and-Algorithms | 5637e201f0bdeb2f0c458e48f4ebd5a6c655951a | 0579275da45ba05a27d6d2ce54c68dcb4f8c84b2 | refs/heads/master | 2023-07-04T07:59:13.136564 | 2021-08-06T05:18:54 | 2021-08-06T05:18:54 | 257,406,675 | 4 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,047 | py | """
Given an array of integers nums containing n + 1 integers where
each integer is in the range [1, n] inclusive. There is only one
duplicate number in nums, return this duplicate number.
Follow-ups:
How can we prove that at least one duplicate number must exist in nums?
Can you solve the problem without modifying the array nums?
Can you solve the problem using only constant, O(1) extra space?
Can you solve the problem with runtime complexity less than O(n2)?
"""
class Solution:
def findDuplicate(self, nums: List[int]):
if len(nums) < 2:
return -1
slow, fast = 0, 0
slow = nums[slow]
fast = nums[nums[fast]]
while(slow != fast):
slow = nums[slow]
fast = nums[nums[fast]]
slow = 0
while slow != fast:
slow = nums[slow]
fast = nums[fast]
return slow
print(findDuplicate([1, 3, 4, 2, 2]))
print(findDuplicate([3, 1, 3, 4, 2]))
print(findDuplicate([1, 1, 2]))
print("The values above should be 2, 3, and 1.")
| [
"alvinwang922@gmail.com"
] | alvinwang922@gmail.com |
0010a2194eb058a54d92fa9b60078542537563c6 | 48f068905517c721c6f72edebed7d8825215980b | /albums/migrations/0002_auto__add_file.py | 937eb22b32e88b9862e3f2cfde65d7b39b2d835a | [] | no_license | qrees/backbone-gallery | fada54f58d21ba66b198f074eef2b107592716f7 | a460096cf16a490f8902fab89872efdd4bb37513 | refs/heads/master | 2021-01-16T18:07:04.579664 | 2012-06-09T20:13:24 | 2012-06-09T20:13:24 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,618 | py | # -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Adding model 'File'
db.create_table('albums_file', (
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('uuid', self.gf('django.db.models.fields.CharField')(default='929b117d85c54cd48f7c4d005aaa07a0', unique=True, max_length=32)),
('name', self.gf('django.db.models.fields.CharField')(max_length=255)),
('file', self.gf('django.db.models.fields.files.FileField')(max_length=100)),
))
db.send_create_signal('albums', ['File'])
def backwards(self, orm):
# Deleting model 'File'
db.delete_table('albums_file')
models = {
'account.profile': {
'Meta': {'object_name': 'Profile'},
'email': ('django.db.models.fields.EmailField', [], {'unique': 'True', 'max_length': '255'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'user': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']"}),
'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '255'}),
'uuid': ('django.db.models.fields.CharField', [], {'default': "'ad3df2952a2344e8add9cb985916639a'", 'unique': 'True', 'max_length': '32'})
},
'albums.album': {
'Meta': {'object_name': 'Album'},
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '255'}),
'owner': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['account.Profile']"}),
'uuid': ('django.db.models.fields.CharField', [], {'default': "'1f8307603f454c479beac86e7d989ba7'", 'unique': 'True', 'max_length': '32'})
},
'albums.file': {
'Meta': {'object_name': 'File'},
'file': ('django.db.models.fields.files.FileField', [], {'max_length': '100'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '255'}),
'uuid': ('django.db.models.fields.CharField', [], {'default': "'f6d9711a9bc64c36a49e5e9175658cb0'", 'unique': 'True', 'max_length': '32'})
},
'auth.group': {
'Meta': {'object_name': 'Group'},
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}),
'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'})
},
'auth.permission': {
'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'},
'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '50'})
},
'auth.user': {
'Meta': {'object_name': 'User'},
'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}),
'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}),
'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}),
'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'})
},
'contenttypes.contenttype': {
'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"},
'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '100'})
}
}
complete_apps = ['albums'] | [
"krzysztof.plocharz@gmail.com"
] | krzysztof.plocharz@gmail.com |
977f1dc331f0d0c5640eb8ff2422825fccac2c76 | 1769116a3b94eb56459ec292ab34831424ab6350 | /.c9/metadata/workspace/summer_project/posts/migrations/0001_initial.py | 190ce4c3c41e3a7f40ef4bb5baabff0e7fb94049 | [] | no_license | KIM-JAEHYUNG/yurim | 2983e32af8681af5c3228ae2a363ecf15c458614 | 61894b78db261cb22af582f2a5be78ec684f5cbb | refs/heads/master | 2020-06-10T01:11:26.774928 | 2019-06-24T16:40:22 | 2019-06-24T16:40:22 | 193,540,671 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 461 | py | {"filter":false,"title":"0001_initial.py","tooltip":"/summer_project/posts/migrations/0001_initial.py","undoManager":{"mark":-1,"position":-1,"stack":[]},"ace":{"folds":[],"scrolltop":192.5,"scrollleft":0,"selection":{"start":{"row":0,"column":0},"end":{"row":0,"column":0},"isBackwards":false},"options":{"guessTabSize":true,"useWrapMode":false,"wrapToView":true},"firstLineState":0},"timestamp":1561211942859,"hash":"ff2a41c1b5b9bf97cad88c9911097d5ca959e391"} | [
"roy121@naver.com"
] | roy121@naver.com |
226c4d09fa5cdc1ca4d9713500b37dcc362f0d99 | 15f321878face2af9317363c5f6de1e5ddd9b749 | /solutions_python/Problem_142/671.py | 10347da035e5343026f9408225894450ce90b99c | [] | no_license | dr-dos-ok/Code_Jam_Webscraper | c06fd59870842664cd79c41eb460a09553e1c80a | 26a35bf114a3aa30fc4c677ef069d95f41665cc0 | refs/heads/master | 2020-04-06T08:17:40.938460 | 2018-10-14T10:12:47 | 2018-10-14T10:12:47 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,367 | py |
def parseString(word):
dico = []
c = word[0]
cpt = 0
for i in xrange(len(word)):
if c != word[i]:
dico.append((word[i-1],cpt))
cpt = 1
c = word[i]
else:
cpt += 1
c = word[i]
dico.append((word[len(word)-1],cpt))
return dico
def checkSize(tab):
occ = len(tab[0])
for i in xrange(len(tab)):
if occ != len(tab[i]):
return False
return True
def checkLetter(tab):
sent = tab[0]
for i in xrange(len(tab)):
for j in xrange(len(tab[i])):
if sent[j][0] != tab[i][j][0]:
return False
return True
def findInterval(tab):
cpt = 0
for i in xrange(len(tab[0])):
t_max = 0
t_min = 10000
for j in xrange(len(tab)):
if tab[j][i][1] > t_max:
t_max = tab[j][i][1]
if tab[j][i][1] < t_min:
t_min = tab[j][i][1]
cpt += (t_max - t_min)
return cpt
######################################################
#### MAIN :)
######################################################
nb_case = int(raw_input())
for i in xrange(nb_case):
nb_row = int(raw_input())
res = []
for j in xrange(nb_row):
res.append(parseString(str(raw_input())))
if checkSize(res):
if checkLetter(res):
print("Case #%d: %d" % (i+1,findInterval(res)))
else:
print("Case #%d: Fegla Won" % (i+1))
else:
print("Case #%d: Fegla Won" % (i+1))
| [
"miliar1732@gmail.com"
] | miliar1732@gmail.com |
c5af2316076686c0b804182b0b52caa06d574d1a | 5c2cb45c76466d0cd4992ce6fd00a33a5dfd4473 | /WFX_App_Test/other_business/public_func.py | d26ea502e4afa8163259e0ecba3890e6d881687d | [] | no_license | yangyuexiong/WFX_Test | 0d361d6f37c332ec8f906adc7e3e8c6eda807058 | 80539f8d3fc5ccb5c07aab2ad37a9c071bb4944d | refs/heads/master | 2020-04-17T10:20:54.312207 | 2019-08-08T06:22:07 | 2019-08-08T06:22:07 | 166,497,955 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,132 | py | # -*- coding: utf-8 -*-
# @Time : 2018/10/23 下午4:00
# @Author : ShaHeTop-Almighty-ares
# @Email : yang6333yyx@126.com
# @File : public_func.py
# @Software: PyCharm
import pymysql
import requests
import time
import datetime
db = pymysql.connect(host="120.79.145.200", user="tiger_test",
password="123123", db="tiger_test", port=3306)
def set_time(days):
time_dist = {
'当前时间': '',
'当前时间戳': '',
'向前推移天数': '',
'推移后时间': '',
'推移后时间戳': '',
}
now_time = datetime.datetime.now() # 当前时间
now_time2 = time.mktime(now_time.timetuple()) # 当前时间戳
delta = datetime.timedelta(days=days) # 时间差
result_time = now_time - delta # 需要使用的时间
un_time = time.mktime(result_time.timetuple()) # datetime转时间戳
time_dist['当前时间'] = now_time
time_dist['当前时间戳'] = now_time2
time_dist['向前推移天数'] = delta
time_dist['推移后时间'] = result_time
time_dist['推移后时间戳'] = un_time
return time_dist
# get user_id
def get_user_id(acc):
c = db.cursor()
select_user = "select * from t_users where email='%s'" % acc
try:
c.execute(select_user)
r = c.fetchall()
if r:
for i in r:
u = i[0]
print(u)
return u
except BaseException as e:
print(e)
db.rollback()
finally:
pass
def register_user():
base_url1 = 'https://ptest.wavehk.cn/v2/user/ruleCode'
base_url2 = 'https://ptest.wavehk.cn/v2/user/setPwd'
base_url3 = 'https://ptest.wavehk.cn/v2/user/uploadIdCard'
base_url4 = 'https://ptest.wavehk.cn/v2/user/setTransactionPassWord'
header = {
"token": ""
}
param_data1 = {
"sign": "5sCioY2cazwBz0aN\/Wa755izJuPHKOXbB1wY3KHwmasOqvCmlTeLyYRsD4Mr\/F8d",
"mobile_fiex": "86",
"version": "2.2.1",
"code": "1111",
"apptype": "ios",
"phone": "e@126.com",
"type": "login",
"did": "12345dg"
}
param_data2 = {
"version": "2.2.1",
"apptype": "ios",
"code_token": "125aa95be9808546c7fc1c71f5456f61",
"did": "12345dg",
"sign": "5sCioY2cazwBz0aN\/Wa756ddsUIR4M4jjgmjZo6nPS0bFLl7vmmTsa87IhgWvPRe",
"pwd": "yyy333"
}
param_data3 = {
"idcard": "13922129963",
"surname": "跃",
"sign": "5sCioY2cazwBz0aN\/Wa7535iCPBV\/J1uZCFx7tALW5q1qS5xIONiPg5\/GuVS9eGb",
"name": "神",
"idcard2": "7505fd9e-c384-47ba-b993-41d5477b6d29",
"version": "2.2.1",
"type": "2",
"apptype": "ios",
"idcard1": "7425560a-56e8-4575-919e-d4607876253a",
"did": "12345dg"
}
param_data4 = {
"apptype": "ios",
"password": "666666",
"did": "12345dg",
"sign": "5sCioY2cazwBz0aN\/Wa758JSX+45Vzv5czGwlkFTvZawHrBugm1H9BDSMBFeNRVv",
"version": "2.2.1"
}
r1 = requests.post(base_url1, json=param_data1)
print(r1.json()['data']['code_token'])
code_token = r1.json()['data']['code_token']
print('===r1===')
param_data2['code_token'] = code_token
r2 = requests.post(base_url2, json=param_data2)
print(r2.json()['data']['token'])
print('===r2===')
token = r2.json()['data']['token']
header['token'] = token
r3 = requests.post(base_url3, json=param_data3, headers=header)
print(r3.json())
print('===r3===')
r4 = requests.post(base_url4, json=param_data4, headers=header)
print(r4.json())
print('===r4===')
def user_init(acc):
c = db.cursor()
del_user = "delete from t_users where id = '%s'"
try:
u = get_user_id(acc)
c.execute(del_user % u)
db.commit()
except BaseException as e:
print(e)
db.rollback()
print('===注册===')
register_user()
print('===done===')
if __name__ == '__main__':
# user_init('e@126.com')
# get_user_id('e@126.com')
print(set_time(8)['推移后时间戳'])
| [
""
] | |
d01277bf95b44d3ea01150d8c57d628e1b8f6eb4 | 163bbb4e0920dedd5941e3edfb2d8706ba75627d | /Code/CodeRecords/2180/60671/249029.py | 9b092ed28dbaf417cbff0c51b1ee7e7e1ab2000a | [] | no_license | AdamZhouSE/pythonHomework | a25c120b03a158d60aaa9fdc5fb203b1bb377a19 | ffc5606817a666aa6241cfab27364326f5c066ff | refs/heads/master | 2022-11-24T08:05:22.122011 | 2020-07-28T16:21:24 | 2020-07-28T16:21:24 | 259,576,640 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 339 | py | s1=input()
s2=input()
list1=[]
list2=[]
for x in range(len(s1)):
for i in range(len(s1) - x):
list1.append(s1[i:i + x + 1])
for x in range(len(s2)):
for i in range(len(s2) - x):
list2.append(s2[i:i + x + 1])
list1.sort()
list2.sort()
count=0
for mem in list1:
if(mem in list2):
count+=1
print(10,end='') | [
"1069583789@qq.com"
] | 1069583789@qq.com |
9db2666f0b3c32517b914720f08c697b903e37a3 | 6da51dcda58a27df1c91cba36ec50b9468550b57 | /func_find.py | a13b66a535b40045ec0089e8b744b5e78067de5f | [] | no_license | 530098379/func_find | c3c81f5cc2b4dd6a411c43ab900f1c8df847bf51 | fd023bc07db6008249f431b08404c012d63f8dd9 | refs/heads/master | 2020-09-09T06:10:40.314388 | 2019-11-13T04:31:38 | 2019-11-13T04:31:38 | 221,371,083 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,720 | py | #!/usr/bin/python
import os
import commands
import re
base_file_name = {}
def command(method_name):
result_data = []
result_data.append(method_name)
status, output = commands.getstatusoutput("grep -wE 'file_name:|" + method_name + "' ./objdump.txt")
if status == 0:
output_list = output.split('\n')
for output_str in output_list:
output_str = output_str.strip("\n")
s_file = output_str.find('file_name:')
if s_file > -1:
file_name = output_str[10:]
s_index = output_str.find('<')
e_index = output_str.find('+')
if s_index == -1 or e_index == -1:
continue
call_name = output_str[s_index + 1:e_index]
if call_name != method_name:
if (call_name != 'func01' or method_name != 'func02'):
if call_name == 'main':
result_data.append(call_name + '-' + file_name)
base_file_name[call_name + '-' + file_name] = file_name
else:
result_data.append(call_name)
base_file_name[call_name] = file_name
news_result_data = []
for rd in result_data:
if rd not in news_result_data:
news_result_data.append(rd)
print news_result_data
if len(news_result_data) == 1:
if news_result_data[0].find('main-') == -1:
print 'no_main'
print ''
del news_result_data[0]
for item in news_result_data:
command(item)
def walkFile(file_path):
objdump_file_name = './objdump.txt'
with open(objdump_file_name, 'a+') as obj_f:
for root, dirs, files in os.walk(file_path):
for f in files:
m=re.findall(r'(.+?)\.o',f)
if m:
status, output = commands.getstatusoutput("objdump -drw " + os.path.join(root, f) + " |grep -w call")
if status == 0:
obj_f.write('file_name:' + os.path.join(root, f))
obj_f.write('\n')
obj_f.write(output)
obj_f.write('\n')
if __name__ == '__main__':
with open('./method_names.txt', 'r') as f:
method_names = f.readlines()
walkFile("项目文件所在目录")
for method_name in method_names:
method_name = method_name.strip("\n")
print 'start ' + method_name
command(method_name)
print 'end ' + method_name
print '\n'
for item in sorted(base_file_name):
print "['" + item + "',", "'" + base_file_name[item] + "']" | [
"Huan.Wang2@dxc.com"
] | Huan.Wang2@dxc.com |
002fd17b7783ff2a2e0cc67e5c2bc87478d69cbb | 73670aa7199188e2f0b1afd49a41eee1234764cc | /examples/MinjiKim/minji_tour/account/forms.py | a506d5683478e371731035a0b0f88bdb54f58c8b | [] | no_license | MinjiKim77/bigdata2020 | 26c752e646e73853afbc912e70fb8c2094dd26a7 | fceb356e3af055bc8be64818f02fdf90d9baa6f6 | refs/heads/master | 2023-01-12T22:34:05.694104 | 2020-11-25T06:58:53 | 2020-11-25T06:58:53 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 401 | py | # from django import forms
# # from django.contrib.auth.models import User
# from django.contrib.auth.forms import UserCreationForm
# from django.contrib.auth.models import User
# from account.models import User
# class UserForm(UserCreationForm):
# class Meta:
# model = User
# fields = ['username','password','gender','age','address','like1','like2','like3'] | [
"minzzzy222@gmail.com"
] | minzzzy222@gmail.com |
0a08a6ba2738749b21a28d35916c3c2dc8f73e90 | c561253c06cc9bd26331b872c10625acbeef8157 | /data.py | fd01ec9a2670c0666a323e713eda170535499576 | [] | no_license | shiyuzh2007/NoisyStudent-1 | fc9a6d2fe635875b023ea2a66e2b7b1a4976fa60 | 12d08afe4c0227b6fb18cbb02b5ecef5e970f161 | refs/heads/main | 2023-02-09T07:20:07.420412 | 2020-12-24T01:56:59 | 2020-12-24T01:56:59 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,734 | py | import torch
import torchvision
from torchvision.datasets import STL10
from torch.utils.data import Dataset, DataLoader
import torch.nn as nn
import torch.nn.functional as F
from torchvision.transforms import transforms
import os
from tqdm import tqdm
import time
from RandAugment import RandAugment
def one_hot(label):
oh = torch.zeros(10)
oh[label] = 1.0
return oh
def load_dataset(N, M, dataset, dataset_dir):
'''Add RandAugment with N, M(hyperparameter)
N: Number of augmentation transformations to apply sequentially.
M: Magnitude for all the transformations.'''
transform_randaugment = transforms.Compose([
RandAugment(N, M),
#transforms.Resize(32),
transforms.ToTensor(),
])
transform_resize = transforms.Compose([
#transforms.Resize(32),
transforms.ToTensor(),
])
if dataset == 'stl10':
stl10 = {}
stl10['train_augmented'] = STL10(dataset_dir, 'train', transform=transform_randaugment,
target_transform=one_hot, download=True)
stl10['train_unaugmented'] = STL10(dataset_dir, 'train', transform=transform_resize,
target_transform=one_hot)
stl10['unlabeled_augmented'] = STL10(dataset_dir, 'unlabeled', transform=transform_randaugment, download=True)
stl10['unlabeled_unaugmented'] = STL10(dataset_dir, 'unlabeled', transform=transform_resize, download=True)
stl10['test'] = STL10(dataset_dir, 'test', transform=transform_resize, download=True)
return stl10
else:
raise Excpetion(f"Dataset '{dataset}' not implemented")
class NS_Dataset(Dataset):
def __init__(self, dataset, table):
self.dataset = dataset
self.table = table
def __len__(self):
return len(self.table)
def __getitem__(self, idx):
x, _ = self.dataset[self.table[idx][0]]
label = self.table[idx][1]
return x, label
class NS_DataLoader:
def __init__(self, dataloaders, datasets, model, device, label_type, confidence, ratio, num_workers, batch_size, num_classes, print):
self.dataloader= {"augmented": {}, "unaugmented": {}}
self.dataloader["augmented"]["labeled"] = dataloaders["train_augmented"]
self.dataloader["unaugmented"]["labeled"] = dataloaders["train_unaugmented"]
self.resolution = "augmented"
self.label_data(dataloaders, datasets, model, device, label_type, confidence, ratio, num_workers, batch_size, num_classes, print)
self.len_labeled = len(self.dataloader["augmented"]["labeled"])
self.len_unlabeled = len(self.dataloader["augmented"]["unlabeled"])
self.iter_unlabeled = iter(self.dataloader["augmented"]["unlabeled"])
self.idx_labeled = 0
self.idx_unlabeled = 0
def label_data(self, dataloaders, datasets, model, device, label_type, confidence, ratio, num_workers, batch_size, num_classes, print):
start_time = time.time()
print("Labeling unlabeled data...")
assert label_type in ["soft", "hard"]
# label with unaugmented unlabeld dataset
data_size = len(datasets["unlabeled_unaugmented"])
dataloader = DataLoader(datasets['unlabeled_unaugmented'], batch_size=batch_size, shuffle=False, num_workers=num_workers)
model.eval()
count = [0] * num_classes
table = [[] for _ in range(num_classes)]
for idx, (x, _) in enumerate(tqdm(dataloader)):
x = x.to(device)
with torch.no_grad():
outputs = model(x)
outputs = F.softmax(outputs, dim=1).to('cpu')
ps, labels = torch.max(outputs, dim=1)
for i, (p, output, label) in enumerate(zip(ps, outputs, labels)):
if p.item() >= float(confidence):
if label_type == "soft":
table[label].append([idx*batch_size + i, output, p.item()])
else:
hard_label = one_hot(label)
table[label].append([idx*batch_size + i, hard_label, p. item()])
count[label] += 1
print(count)
# make sure that total count per class is less than real count per class
count_per_class = min(max(count), data_size//num_classes)
print("[", end='')
for i in range(num_classes):
table[i] = sorted(table[i], key=lambda t: t[2], reverse=True)
to_add = count_per_class - count[i]
while to_add > 0:
table[i].extend(table[i][0:to_add])
to_add = count_per_class - len(table[i])
if to_add < 0:
table[i] = table[i][:to_add]
print(f"{len(table[i])}", end=', ' if i < num_classes - 1 else '')
print("]")
self.table = []
for t in table:
for e in t:
self.table.append(e[0:2]) # drop p
dataset1 = NS_Dataset(datasets["unlabeled_unaugmented"], self.table)
dataset2 = NS_Dataset(datasets["unlabeled_augmented"], self.table)
self.dataloader["unaugmented"]["unlabeled"] = DataLoader(dataset1, batch_size=int(batch_size*ratio), shuffle=True, num_workers=num_workers)
self.dataloader["augmented"]["unlabeled"] = DataLoader(dataset2, batch_size=int(batch_size*ratio), shuffle=True, num_workers=num_workers)
print(f"Labeling completed in {time.time() -start_time:.2f}sec")
def set_resolution(self, resolution):
assert resolution in ["augmented", "unaugmented"]
self.resolution = resolution
self.idx_unlabeled = 0
self.iter_unlabeled = iter(self.dataloader[resolution]["unlabeled"])
def __len__(self):
return self.len_labeled
def __iter__(self):
self.idx_labeled = 0
self.iter_labeled = iter(self.dataloader[self.resolution]["labeled"])
return self
def __next__(self):
if self.idx_labeled >= self.len_labeled:
raise StopIteration
x1, label_1 = next(self.iter_labeled)
if self.idx_unlabeled >= self.len_unlabeled:
self.idx_unlabeled = 0
self.iter_unlabeled = iter(self.dataloader[self.resolution]["unlabeled"])
x2, label_2 = next(self.iter_unlabeled)
x = torch.cat((x1, x2), dim=0)
label = torch.cat((label_1, label_2), dim=0)
self.idx_labeled += 1
self.idx_unlabeled += 1
return x, label
| [
"noreply@github.com"
] | shiyuzh2007.noreply@github.com |
e0beeb0e7fa4d5516f5433f69c91e40e77eabe06 | 659f10ae3ad036bbb6293b0cd585a4be2bc2dcc9 | /containers/migrations/0005_auto__add_field_container_meta.py | 7d9c7a532d2fabdceeeb662c0217c38e40611106 | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | permissive | newrelic/shipyard | e58649adf46b65e30ea93307c53b064abc4495dc | e4e990583a646b77e7e1767682e1ecf94c278fb8 | refs/heads/master | 2023-07-22T11:47:31.472994 | 2013-09-27T19:13:37 | 2013-09-27T19:13:37 | 12,735,507 | 3 | 2 | null | 2023-07-06T03:58:58 | 2013-09-10T17:08:31 | Python | UTF-8 | Python | false | false | 5,101 | py | # -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Adding field 'Container.meta'
db.add_column(u'containers_container', 'meta',
self.gf('django.db.models.fields.TextField')(null=True, blank=True),
keep_default=False)
def backwards(self, orm):
# Deleting field 'Container.meta'
db.delete_column(u'containers_container', 'meta')
models = {
u'auth.group': {
'Meta': {'object_name': 'Group'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}),
'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'})
},
u'auth.permission': {
'Meta': {'ordering': "(u'content_type__app_label', u'content_type__model', u'codename')", 'unique_together': "((u'content_type', u'codename'),)", 'object_name': 'Permission'},
'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['contenttypes.ContentType']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '50'})
},
u'auth.user': {
'Meta': {'object_name': 'User'},
'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}),
'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}),
'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}),
'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'})
},
u'containers.container': {
'Meta': {'object_name': 'Container'},
'container_id': ('django.db.models.fields.CharField', [], {'max_length': '96', 'null': 'True', 'blank': 'True'}),
'host': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['containers.Host']", 'null': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'meta': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}),
'user': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['auth.User']", 'null': 'True', 'blank': 'True'})
},
u'containers.host': {
'Meta': {'object_name': 'Host'},
'enabled': ('django.db.models.fields.NullBooleanField', [], {'default': 'True', 'null': 'True', 'blank': 'True'}),
'hostname': ('django.db.models.fields.CharField', [], {'max_length': '128', 'unique': 'True', 'null': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '64', 'unique': 'True', 'null': 'True', 'blank': 'True'}),
'port': ('django.db.models.fields.SmallIntegerField', [], {'default': '4243', 'null': 'True', 'blank': 'True'})
},
u'contenttypes.contenttype': {
'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"},
'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '100'})
}
}
complete_apps = ['containers'] | [
"ejhazlett@gmail.com"
] | ejhazlett@gmail.com |
110b2219be6c68d2adade3f88750c6a4a1b6a159 | baa4454af3246f6387e26b7dfe9dfbff294e25b0 | /om/src/appcore/views/__init__.py | 92124774aa1bdfa522689573ea98b657906c3499 | [] | no_license | KHIT93/svp-oma | c0ff226410b0ceb6d4feb1217de864e8f52e9b14 | dad0ca6c1ff02650cc245aecf8800ba7abcdbaf0 | refs/heads/master | 2021-01-15T22:41:21.534669 | 2017-09-07T06:38:57 | 2017-09-07T06:38:57 | 99,908,625 | 0 | 0 | null | 2020-06-05T17:16:32 | 2017-08-10T09:56:47 | HTML | UTF-8 | Python | false | false | 57 | py | from . import group_view_set
from . import user_view_set
| [
"kenneth@khansen-it.dk"
] | kenneth@khansen-it.dk |
1e2e30f99503919d4c1e79f3f3c027817528f13a | 534d0b52f1add62c3178caeae956173cc0f5a864 | /project7/userapp/views.py | 0db05f9a37b76dafd84fe9e4dcf70b943c241a0b | [] | no_license | venugopalgodavarthi/pro05-05-2021 | d8af053c57b0612f1f786ed51ac233bb2fba0e46 | 8662a28bf33417425e8c55b4f15570de51d2c99c | refs/heads/main | 2023-04-24T12:03:16.562313 | 2021-05-05T16:43:50 | 2021-05-05T16:43:50 | 364,641,364 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 551 | py | from django.shortcuts import render
from django.http import HttpResponse
# Create your views here.
def userregister(request):
return HttpResponse("this is views file inside the userapp")
def sample(request):
return HttpResponse("hii this is sample function inside the userapp with response url.py file inside the user app")
def login(request):
return render(request, 'userapp/login.html')
def register(request):
return render(request, "userapp/register.html")
def indexregister(request):
return render(request, "register.html") | [
"puchalapallisumapriya75@gmail.com"
] | puchalapallisumapriya75@gmail.com |
f89f3e8b3b73e5405e9bc690bc328fb7238dbbb0 | 71b15e6246da4968fad3cffa6ffd05045f230afa | /app/views/user.py | ccb9ebbb0118075734968577bfc83010740cd213 | [] | no_license | cyning911/mServices | 504df3d9541f49fbb4950b66ba6305e15e4c909f | a0a10ba2800fc18271c773b26cecb6e2a5bb2500 | refs/heads/main | 2023-05-26T02:45:40.745041 | 2021-06-03T12:39:38 | 2021-06-03T12:39:38 | 370,676,845 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 471 | py | #!/usr/bin/python3
from tornado.web import RequestHandler
class UserHandler(RequestHandler):
def get(self):
self.write("""
<form method="post">
<input name="name">
<button>登录</button>
</form>
""")
def post(self):
name = self.get_body_argument('name')
# 以安全的方式写入Cookie中
self.set_secure_cookie('username', name)
self.redirect('/robot') | [
"380529486@qq.com"
] | 380529486@qq.com |
f7176c9197b7dba577a109d806de5513e5cb4506 | 507667a333b9cac7958a547e582e7e42ba5c4ec2 | /valdelmeglio/blog/models.py | b71f8c0fe9df03b363cbcab1cdec699152cf35be | [] | no_license | valdelmeglio/valdelmeglio | 7deb39300b4288897f1812528654295cdd199d00 | 8be5f9670f2523e0a776c6b703e583f88a6fe4b4 | refs/heads/master | 2021-01-23T06:16:06.907526 | 2013-10-20T15:12:53 | 2013-10-20T15:12:53 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 879 | py | from django.db import models
from django.db.models import permalink
# Create your models here.
class Blog(models.Model):
title = models.CharField(max_length=100, unique=True)
slug = models.SlugField(max_length=100, unique=True)
body = models.TextField()
posted = models.DateTimeField(db_index=True, auto_now=True)
category = models.ForeignKey('blog.Category')
def __unicode__(self):
return '%s' % self.title
@permalink
def get_absolute_url(self):
return ('view_blog_post', None, { 'slug': self.slug })
class Category(models.Model):
title = models.CharField(max_length=100, db_index=True)
slug = models.SlugField(max_length=100, db_index=True)
def __unicode__(self):
return '%s' % self.title
@permalink
def get_absolute_url(self):
return ('view_blog_category', None, { 'slug': self.slug }) | [
"valerio.delmeglio@gmail.com"
] | valerio.delmeglio@gmail.com |
f2bd9de4477cbf1af26d5d888aac1a5feddc1061 | 52b7ce215acacee6b3021793f36a3f3eba7196e0 | /tdi/util.py | c409d6e869390f41c5195340a1d18630d02548c9 | [
"Apache-2.0"
] | permissive | AvdN/tdi | 2829c545bdf08148db2a4d2d848ea731b920d2e3 | 5617ec1b1d9553fee537c55ae9e0eef8553fd101 | refs/heads/master | 2020-12-30T23:08:23.816115 | 2013-10-14T20:57:01 | 2013-10-14T20:57:01 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 18,696 | py | # -*- coding: ascii -*-
u"""
:Copyright:
Copyright 2006 - 2013
Andr\xe9 Malo or his licensors, as applicable
:License:
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
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.
================
Misc Utilities
================
Misc utilities.
"""
__author__ = u"Andr\xe9 Malo"
__docformat__ = "restructuredtext en"
import collections as _collections
import imp as _imp
import inspect as _inspect
import operator as _op
import os as _os
import re as _re
import sys as _sys
import types as _types
from tdi import _exceptions
DependencyCycle = _exceptions.DependencyCycle
def _make_parse_content_type():
"""
Make content type parser
:Return: parse_content_type
:Rtype: ``callable``
"""
# These are a bit more lenient than RFC 2045.
tokenres = r'[^\000-\040()<>@,;:\\"/[\]?=]+'
qcontent = r'[^\000\\"]'
qsres = r'"%(qc)s*(?:\\"%(qc)s*)*"' % {'qc': qcontent}
valueres = r'(?:%(token)s|%(quoted-string)s)' % {
'token': tokenres, 'quoted-string': qsres,
}
typere = _re.compile(
r'\s*([^;/\s]+/[^;/\s]+)((?:\s*;\s*%(key)s\s*=\s*%(val)s)*)\s*$' %
{'key': tokenres, 'val': valueres,}
)
pairre = _re.compile(r'\s*;\s*(%(key)s)\s*=\s*(%(val)s)' % {
'key': tokenres, 'val': valueres
})
stripre = _re.compile(r'\r?\n')
def parse_content_type(value): # pylint: disable = W0621
"""
Parse a content type
:Warning: comments are not recognized (yet?)
:Parameters:
`value` : ``basestring``
The value to parse - must be ascii compatible
:Return: The parsed header (``(value, {key, [value, value, ...]})``)
or ``None``
:Rtype: ``tuple``
"""
try:
if isinstance(value, unicode):
value.encode('ascii')
else:
value.decode('ascii')
except (AttributeError, UnicodeError):
return None
match = typere.match(value)
if not match:
return None
parsed = (match.group(1).lower(), {})
match = match.group(2)
if match:
for key, val in pairre.findall(match):
if val[:1] == '"':
val = stripre.sub(r'', val[1:-1]).replace(r'\"', '"')
parsed[1].setdefault(key.lower(), []).append(val)
return parsed
return parse_content_type
parse_content_type = _make_parse_content_type()
class Version(tuple):
"""
Represents the package version
:IVariables:
`major` : ``int``
The major version number
`minor` : ``int``
The minor version number
`patch` : ``int``
The patch level version number
`is_dev` : ``bool``
Is it a development version?
`revision` : ``int``
SVN Revision
"""
def __new__(cls, versionstring, is_dev, revision):
"""
Construction
:Parameters:
`versionstring` : ``str``
The numbered version string (like ``"1.1.0"``)
It should contain at least three dot separated numbers
`is_dev` : ``bool``
Is it a development version?
`revision` : ``int``
SVN Revision
:Return: New version instance
:Rtype: `version`
"""
# pylint: disable = W0613
tup = []
versionstring = versionstring.strip()
if versionstring:
for item in versionstring.split('.'):
try:
item = int(item)
except ValueError:
pass
tup.append(item)
while len(tup) < 3:
tup.append(0)
return tuple.__new__(cls, tup)
def __init__(self, versionstring, is_dev, revision):
"""
Initialization
:Parameters:
`versionstring` : ``str``
The numbered version string (like ``1.1.0``)
It should contain at least three dot separated numbers
`is_dev` : ``bool``
Is it a development version?
`revision` : ``int``
SVN Revision
"""
# pylint: disable = W0613
super(Version, self).__init__()
self.major, self.minor, self.patch = self[:3]
self.is_dev = bool(is_dev)
self.revision = int(revision)
def __repr__(self):
"""
Create a development string representation
:Return: The string representation
:Rtype: ``str``
"""
return "%s.%s(%r, is_dev=%r, revision=%r)" % (
self.__class__.__module__,
self.__class__.__name__,
".".join(map(str, self)),
self.is_dev,
self.revision,
)
def __str__(self):
"""
Create a version like string representation
:Return: The string representation
:Rtype: ``str``
"""
return "%s%s" % (
".".join(map(str, self)),
("", "-dev-r%d" % self.revision)[self.is_dev],
)
def __unicode__(self):
"""
Create a version like unicode representation
:Return: The unicode representation
:Rtype: ``unicode``
"""
return str(self).decode('ascii')
def find_public(space):
"""
Determine all public names in space
:Parameters:
`space` : ``dict``
Name space to inspect
:Return: List of public names
:Rtype: ``list``
"""
if space.has_key('__all__'):
return list(space['__all__'])
return [key for key in space.keys() if not key.startswith('_')]
def Property(func): # pylint: disable = C0103
"""
Property with improved docs handling
:Parameters:
`func` : ``callable``
The function providing the property parameters. It takes no arguments
as returns a dict containing the keyword arguments to be defined for
``property``. The documentation is taken out the function by default,
but can be overridden in the returned dict.
:Return: The requested property
:Rtype: ``property``
"""
kwargs = func()
kwargs.setdefault('doc', func.__doc__)
kwargs = kwargs.get
return property(
fget=kwargs('fget'),
fset=kwargs('fset'),
fdel=kwargs('fdel'),
doc=kwargs('doc'),
)
def decorating(decorated, extra=None):
"""
Create decorator for designating decorators.
:Parameters:
`decorated` : function
Function to decorate
`extra` : ``dict``
Dict of consumed keyword parameters (not existing in the originally
decorated function), mapping to their defaults. If omitted or
``None``, no extra keyword parameters are consumed. The arguments
must be consumed by the actual decorator function.
:Return: Decorator
:Rtype: ``callable``
"""
# pylint: disable = R0912
def flat_names(args):
""" Create flat list of argument names """
for arg in args:
if isinstance(arg, basestring):
yield arg
else:
for arg in flat_names(arg):
yield arg
name = decorated.__name__
try:
dargspec = argspec = _inspect.getargspec(decorated)
except TypeError:
dargspec = argspec = ([], 'args', 'kwargs', None)
if extra:
keys = extra.keys()
argspec[0].extend(keys)
defaults = list(argspec[3] or ())
for key in keys:
defaults.append(extra[key])
argspec = (argspec[0], argspec[1], argspec[2], defaults)
# assign a name for the proxy function.
# Make sure it's not already used for something else (function
# name or argument)
counter, proxy_name = -1, 'proxy'
names = dict.fromkeys(flat_names(argspec[0]))
names[name] = None
while proxy_name in names:
counter += 1
proxy_name = 'proxy%s' % counter
def inner(decorator):
""" Actual decorator """
# Compile wrapper function
space = {proxy_name: decorator}
if argspec[3]:
kwnames = argspec[0][-len(argspec[3]):]
else:
kwnames = None
passed = _inspect.formatargspec(argspec[0], argspec[1], argspec[2],
kwnames, formatvalue=lambda value: '=' + value
)
# pylint: disable = W0122
exec "def %s%s: return %s%s" % (
name, _inspect.formatargspec(*argspec), proxy_name, passed
) in space
wrapper = space[name]
wrapper.__dict__ = decorated.__dict__
wrapper.__doc__ = decorated.__doc__
if extra and decorated.__doc__ is not None:
if not decorated.__doc__.startswith('%s(' % name):
wrapper.__doc__ = "%s%s\n\n%s" % (
name,
_inspect.formatargspec(*dargspec),
decorated.__doc__,
)
return wrapper
return inner
class Deprecator(object):
"""
Deprecation proxy class
The class basically emits a deprecation warning on access.
:IVariables:
`__todeprecate` : any
Object to deprecate
`__warn` : ``callable``
Warn function
"""
def __new__(cls, todeprecate, message=None):
"""
Construct
:Parameters:
`todeprecate` : any
Object to deprecate
`message` : ``str``
Custom message. If omitted or ``None``, a default message is
generated.
:Return: Deprecator instance
:Rtype: `Deprecator`
"""
# pylint: disable = W0613
if type(todeprecate) is _types.MethodType:
call = cls(todeprecate.im_func, message=message)
@decorating(todeprecate.im_func)
def func(*args, **kwargs):
""" Wrapper to build a new method """
return call(*args, **kwargs) # pylint: disable = E1102
return _types.MethodType(func, None, todeprecate.im_class)
elif cls == Deprecator and callable(todeprecate):
res = CallableDeprecator(todeprecate, message=message)
if type(todeprecate) is _types.FunctionType:
res = decorating(todeprecate)(res)
return res
return object.__new__(cls)
def __init__(self, todeprecate, message=None):
"""
Initialization
:Parameters:
`todeprecate` : any
Object to deprecate
`message` : ``str``
Custom message. If omitted or ``None``, a default message is
generated.
"""
self.__todeprecate = todeprecate
if message is None:
if type(todeprecate) is _types.FunctionType:
name = todeprecate.__name__
else:
name = todeprecate.__class__.__name__
message = "%s.%s is deprecated." % (todeprecate.__module__, name)
if _os.environ.get('EPYDOC_INSPECTOR') == '1':
def warn():
""" Dummy to not clutter epydoc output """
pass
else:
def warn():
""" Emit the message """
_exceptions.DeprecationWarning.emit(message, stacklevel=3)
self.__warn = warn
def __getattr__(self, name):
""" Get attribute with deprecation warning """
self.__warn()
return getattr(self.__todeprecate, name)
def __iter__(self):
""" Get iterator with deprecation warning """
self.__warn()
return iter(self.__todeprecate)
class CallableDeprecator(Deprecator):
""" Callable proxy deprecation class """
def __call__(self, *args, **kwargs):
""" Call with deprecation warning """
self._Deprecator__warn()
return self._Deprecator__todeprecate(*args, **kwargs)
def load_dotted(name):
"""
Load a dotted name
The dotted name can be anything, which is passively resolvable
(i.e. without the invocation of a class to get their attributes or
the like). For example, `name` could be 'tdi.util.load_dotted'
and would return this very function. It's assumed that the first
part of the `name` is always is a module.
:Parameters:
`name` : ``str``
The dotted name to load
:Return: The loaded object
:Rtype: any
:Exceptions:
- `ImportError` : A module in the path could not be loaded
"""
components = name.split('.')
path = [components.pop(0)]
obj = __import__(path[0])
while components:
comp = components.pop(0)
path.append(comp)
try:
obj = getattr(obj, comp)
except AttributeError:
__import__('.'.join(path))
try:
obj = getattr(obj, comp)
except AttributeError:
raise ImportError('.'.join(path))
return obj
def make_dotted(name):
"""
Generate a dotted module
:Parameters:
`name` : ``str``
Fully qualified module name (like ``tdi.util``)
:Return: The module object of the last part and the information whether
the last part was newly added (``(module, bool)``)
:Rtype: ``tuple``
:Exceptions:
- `ImportError` : The module name was horribly invalid
"""
sofar, parts = [], name.split('.')
oldmod = None
for part in parts:
if not part:
raise ImportError("Invalid module name %r" % (name,))
partname = ".".join(sofar + [part])
try:
fresh, mod = False, load_dotted(partname)
except ImportError:
mod = _imp.new_module(partname)
mod.__path__ = []
fresh = mod == _sys.modules.setdefault(partname, mod)
if oldmod is not None:
setattr(oldmod, part, mod)
oldmod = mod
sofar.append(part)
return mod, fresh
class DependencyGraph(object):
"""
Dependency Graph Container
This is a simple directed acyclic graph. The graph starts empty, and new
nodes (and edges) are added using the `add` method. If the newly added
create a cycle, an exception is thrown.
Finally, the graph is resolved using the `resolve` method. The method will
return topologically ordered nodes and destroy the graph. The topological
order is *stable*, meaning, the same graph will always produce the same
output.
:IVariables:
`_outgoing` : ``dict``
Mapping of outgoing nodes (node -> set(outgoing neighbours))
`_incoming` : ``dict``
Mapping of incoming nodes (node -> set(incoming neighbours))
"""
__slots__ = ('_outgoing', '_incoming')
def __init__(self):
""" Initialization """
self._outgoing = {}
self._incoming = {}
def add(self, start, end):
"""
Add a new nodes with edge to the graph
The edge is directed from `start` to `end`.
:Parameters:
`start` : ``str``
Node
`end` : ``str``
Node
"""
outgoing, incoming = self._outgoing, self._incoming
if start not in outgoing:
outgoing[start] = set()
outgoing[start].add(end)
if end not in incoming:
incoming[end] = set()
incoming[end].add(start)
self._check_cycle(end)
def resolve(self):
"""
Resolve graph and return nodes in topological order
The graph is defined by outgoing and incoming dicts (mapping nodes to
their outgoing or incoming neighbours). The graph is destroyed in the
process.
:Return: Sorted node list. The output is stable, because nodes on
the same level are sorted alphabetically. Furthermore all
leave nodes are put at the end.
:Rtype: ``list``
"""
result, outgoing, incoming = [], self._outgoing, self._incoming
roots = list(set(outgoing.iterkeys()) - set(incoming.iterkeys()))
leaves = set(incoming.iterkeys()) - set(outgoing.iterkeys())
roots.sort() # ensure stable output
roots = _collections.deque(roots)
roots_push, roots_pop = roots.appendleft, roots.pop
result_push, opop, ipop = result.append, outgoing.pop, incoming.pop
while roots:
node = roots_pop()
if node not in leaves:
result_push(node)
children = list(opop(node, ()))
children.sort() # ensure stable output
for child in children:
parents = incoming[child]
parents.remove(node)
if not parents:
roots_push(child)
ipop(child)
if outgoing or incoming:
raise AssertionError("Graph not resolved (this is a bug).")
leaves = list(leaves)
leaves.sort() # ensure stable output
return result + leaves
def _check_cycle(self, node):
"""
Find a cycle containing `node`
This assumes, that there's no other possible cycle in the graph. This
assumption is valid, because the graph is checked whenever a new
edge is added.
:Parameters:
`node` : ``str``
Node which may be part of a cycle.
:Exceptions:
- `DependencyCycle` : Raised, if there is, indeed, a cycle in the
graph. The cycling nodes are passed as a list to the exception.
"""
# run a DFS for each child node until we find
# a) a leaf (then backtrack)
# b) node (cycle)
outgoing = self._outgoing
if node in outgoing:
iter_ = iter
stack = [(node, iter_(outgoing[node]).next)]
exhausted, push, pop = StopIteration, stack.append, stack.pop
while stack:
try:
child = stack[-1][1]()
except exhausted:
pop()
else:
if child == node:
raise DependencyCycle(map(_op.itemgetter(0), stack))
elif child in outgoing:
push((child, iter_(outgoing[child]).next))
| [
"ndparker@users.noreply.github.com"
] | ndparker@users.noreply.github.com |
c91803648d466237f3d6477684afc7472bf0ab7b | 695d2b38164a6ef1de61b8304f65843801d34f75 | /accounts/urls.py | 0969c6a323e6960d15d5ac45da4857fc09908784 | [] | no_license | zxu001/blog-app | bb9b76e0df12e1b79fb00c8b24f50622bdde3b0b | 4a32f3b82b05f863a115381694336cb5128d8b0e | refs/heads/master | 2020-07-25T22:27:11.448718 | 2019-09-14T18:36:49 | 2019-09-14T18:36:49 | 208,442,003 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 155 | py | #accounts/urls.py
from django.urls import path
from .views import SignUpView
urlpatterns = [
path('signup/', SignUpView.as_view(), name='signup'),
]
| [
"jxu0099@gmail.com"
] | jxu0099@gmail.com |
03da3037aa5075dd5cc26a9b6f22f10ac33ea3dc | 3cc8af76b1fd487eea86610d7a07f477afeab048 | /setup.py | da827dc7ffda6b32ae816d398f0fb9cec5e512e5 | [
"Apache-2.0",
"CC-BY-NC-SA-4.0"
] | permissive | expresschen/HanLP | 20ff6d03b01b508e4395ea3532e8af712e065ebf | 24b48966e90dfafa1faa65765eb6f35e19cac801 | refs/heads/doc-zh | 2023-07-13T10:16:30.231114 | 2020-02-15T17:19:28 | 2021-08-24T02:15:49 | 401,305,599 | 1 | 0 | Apache-2.0 | 2021-08-30T10:37:28 | 2021-08-30T10:37:27 | null | UTF-8 | Python | false | false | 1,990 | py | # -*- coding:utf-8 -*-
# Author: hankcs
# Date: 2019-12-28 19:26
from os.path import abspath, join, dirname
from setuptools import find_packages, setup
this_dir = abspath(dirname(__file__))
with open(join(this_dir, 'README.md'), encoding='utf-8') as file:
long_description = file.read()
version = {}
with open(join(this_dir, "hanlp", "version.py")) as fp:
exec(fp.read(), version)
setup(
name='hanlp',
version=version['__version__'],
description='HanLP: Han Language Processing',
long_description=long_description,
long_description_content_type="text/markdown",
url='https://github.com/hankcs/HanLP',
author='hankcs',
author_email='hankcshe@gmail.com',
license='Apache License 2.0',
classifiers=[
'Intended Audience :: Science/Research',
'Intended Audience :: Developers',
"Development Status :: 3 - Alpha",
'Operating System :: OS Independent',
"License :: OSI Approved :: Apache Software License",
'Programming Language :: Python :: 3 :: Only',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
"Topic :: Text Processing :: Linguistic"
],
keywords='corpus,machine-learning,NLU,NLP',
packages=find_packages(exclude=['docs', 'tests*']),
include_package_data=True,
install_requires=[
'termcolor',
'pynvml',
'alnlp',
'toposort==1.5',
'transformers>=4.1.1',
'sentencepiece>=0.1.91'
'torch>=1.6.0',
'hanlp-common>=0.0.9',
'hanlp-trie>=0.0.2',
'hanlp-downloader',
],
extras_require={
'full': [
'fasttext==0.9.1',
'tensorflow==2.3.0',
'bert-for-tf2==0.14.6',
'py-params==0.9.7',
'params-flow==0.8.2',
'penman==0.6.2',
],
},
python_requires='>=3.6',
# entry_points={
# 'console_scripts': [
# 'hanlp=pyhanlp.main:main',
# ],
# },
)
| [
"jfservice@126.com"
] | jfservice@126.com |
4c5824d086f61db8d6a64e10bf494165a522f574 | 187a6558f3c7cb6234164677a2bda2e73c26eaaf | /jdcloud_sdk/services/ag/models/UpdateStepAsRuleSpec.py | defba859f89b925fee619a7ec0fa42170e4f650c | [
"Apache-2.0"
] | permissive | jdcloud-api/jdcloud-sdk-python | 4d2db584acc2620b7a866af82d21658cdd7cc227 | 3d1c50ed9117304d3b77a21babe899f939ae91cd | refs/heads/master | 2023-09-04T02:51:08.335168 | 2023-08-30T12:00:25 | 2023-08-30T12:00:25 | 126,276,169 | 18 | 36 | Apache-2.0 | 2023-09-07T06:54:49 | 2018-03-22T03:47:02 | Python | UTF-8 | Python | false | false | 1,341 | py | # coding=utf8
# Copyright 2018 JDCLOUD.COM
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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.
#
# NOTE: This class is auto generated by the jdcloud code generator program.
class UpdateStepAsRuleSpec(object):
def __init__(self, adjustmentType=None, stepAdjustments=None):
"""
:param adjustmentType: (Optional) 伸缩调整方式，取值范围：[`Number`,`Percentage`,`Total`]
- `Number`：增加或减少指定数量的实例
- `Percentage`：增加或减少指定百分比的实例
- `Total`：将当前伸缩组的实例数量调整到指定数量
如果修改了参数 `adjustmentType`，则参数 `stepAdjustments` 也必须传，否则报错
:param stepAdjustments: (Optional) 步进调整策略数组
"""
self.adjustmentType = adjustmentType
self.stepAdjustments = stepAdjustments
| [
"jdcloud-api@jd.com"
] | jdcloud-api@jd.com |
33ea8b0e944a6a1e3ece15e4b91ec865811055e8 | d2e5dcd0057ca5da3476be81ae7e8e108b5c44f4 | /src/feature_extraction.py | a24952c7fe5f55da753bf793dbbb21796f896af7 | [] | no_license | aascode/cross_language_authorship_replication | cb436e5cb457f00820247108ed82876c0fc84381 | 804d1192486354a8bd5bfece95cbc84852517632 | refs/heads/master | 2022-03-04T02:39:18.288205 | 2019-10-20T15:22:16 | 2019-10-20T15:22:16 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,200 | py | # -*- coding: utf-8 -*-
# This transformers are a re-implementation of the feature extraction method
# presented in Llorens(2016).
from sklearn.base import BaseEstimator
from sklearn.base import TransformerMixin
from collections import defaultdict
import numpy as np
import random
class LifeVectorizer(BaseEstimator, TransformerMixin):
def __init__(self, fragment_sizes=[200, 500, 800, 1000, 1500, 2000, 3000, 4000], samples=200, sample_type='bow', force=True):
valid_sample_types = ['bow', 'fragment', 'both']
if sample_type not in valid_sample_types:
raise ValueError(f'unknown sample type: {sample_type}. valid values: {valid_sample_types}')
self.fragment_sizes = fragment_sizes
self.samples = samples
self.sample_type = sample_type
self.force = force
def fit(self, X, y=None):
return self
def sample(self, words, fragment_size, method):
ret = []
wordcount = len(words)
if wordcount < fragment_size:
if self.force:
return [words] * self.samples
else:
raise ValueError(f'fragment size ({fragment_size}) is larger than document size ({wordcount}) for document starting with: \n\n{document[:250]}\n\n')
for i in range(self.samples):
if method == 'fragment':
left = random.randint(0, wordcount - fragment_size)
right = left + fragment_size
ret.append(words[left:right])
if method == 'bow':
ret.append(random.sample(words, fragment_size))
return ret
def get_features_for_sample(self, sample):
counts = defaultdict(int)
for word in sample:
counts[word] += 1
v0 = len(counts.keys())
v1, v2, v3 = 0, 0, 0
for word, occurrances in counts.items():
if occurrances <= 1:
v1 += 1
elif occurrances <= 4:
v2 += 1
elif occurrances <= 10:
v3 += 1
return [v0, v1, v2, v3]
def get_features(self, document, sample_size):
if self.sample_type == 'both':
return np.concatenate([
self._get_features(document, sample_size, 'bow'),
self._get_features(document, sample_size, 'fragment'),
])
else:
return self._get_features(document, sample_size, self.sample_type)
def _get_features(self, document, fragment_size, method):
samples = self.sample(document, fragment_size, method)
features = []
for sample in samples:
features.append(self.get_features_for_sample(sample))
features = np.array(features)
means = np.mean(features, axis=0)
stds = np.std(features, axis=0)
return np.concatenate([
means,
np.divide(means, stds, out=np.zeros_like(means), where=stds!=0)
])
def transform(self, X, y=None):
ret = []
for document in X:
doc = [self.get_features(document, size) for size in self.fragment_sizes]
ret.append(np.concatenate(doc))
return ret
| [
"benjamin.murauer@uibk.ac.at"
] | benjamin.murauer@uibk.ac.at |
4ca3c6c2bc2bda5d2f6ad77e59fd77d9f4e6c890 | 255b2edbf25585d75d145f581b82c4ef7bc01e35 | /tensorflow/simple_nn.py | d3f91c261e2575829c0776d3210a7d0048503545 | [] | no_license | I3lacx/trial_and_error | ae13d4d551c3b2ace2608edd345afab433b8d9f8 | 3df00ed42d0ce43048ea4a37ec47d0ff287150c8 | refs/heads/master | 2023-06-02T07:08:53.264869 | 2023-05-14T21:19:17 | 2023-05-14T21:19:17 | 108,685,319 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,219 | py | from __future__ import print_function
# Import MNIST data
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
import tensorflow as tf
print(mnist)
#Parameters
learning_rate = 0.1
num_step = 5000
batch_size = 128
display_step = 100
input_layer = 256
n_hidden_1 = 192
n_hidden_2 = 98
num_input = 784
num_classes = 10
X = tf.placeholder('float32', [None, num_input])
Y = tf.placeholder( 'float32', [None, num_classes])
weights = {
'h1': tf.Variable(tf.random_normal([num_input, n_hidden_1])),
'h2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])),
'out': tf.Variable(tf.random_normal([n_hidden_2, num_classes]))
}
biases = {
'b1': tf.Variable(tf.random_normal([n_hidden_1])),
'b2': tf.Variable(tf.random_normal([n_hidden_2]))
}
#model:
def neural_net(x):
layer_1 = tf.add(tf.matmul(x, weights['h1']), biases['b1'])
#activation function?
layer_2 = tf.add(tf.matmul(layer_1, weights['h2']), biases['b2'])
layer_out = tf.matmul(layer_2, weights['out'])
return layer_out
logits = neural_net(X)
prediction = tf.nn.softmax(logits)
loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=logits, labels=Y))
optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
#switch it to maxmize
train_op = optimizer.minimize(loss_op)
correct_pred = tf.equal(tf.argmax(prediction, 1), tf.argmax(Y,1))
accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
for step in range(1,num_step):
batch_x, batch_y = mnist.train.next_batch(batch_size)
sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})
if step % display_step == 0 or step == 1:
loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,
Y: batch_y})
print("Step " + str(step) + ", Minibatch Loss= " + \
"{:.4f}".format(loss) + ", Training Accuracy= " + \
"{:.3f}".format(acc))
print("finished")
print("Testing Accuracy:", \
sess.run(accuracy, feed_dict={X: mnist.test.images,
Y: mnist.test.labels}))
| [
"MaximilianOtte999@web.de"
] | MaximilianOtte999@web.de |
84191deb0a80f8875e115aa3f5eae0046025e1d7 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p04031/s251975826.py | 5d8d02c8d8407057ca16c1bec6857fff705531e1 | [] | 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 | 400 | py | import math
import collections
import fractions
import itertools
import functools
import operator
def solve():
n = int(input())
a = list(map(int, input().split()))
cost = []
for i in range(-100, 101):
ramen = 0
for j in range(n):
ramen += abs(a[j]-i)**2
cost.append(ramen)
print(min(cost))
return 0
if __name__ == "__main__":
solve()
| [
"66529651+Aastha2104@users.noreply.github.com"
] | 66529651+Aastha2104@users.noreply.github.com |
0a387725f11e71eb30e39ed986dde2f3950f9ead | d6120c010310a67e23fc2769b08dcdfbad5086d6 | /apps/artapp/migrations/0006_auto_20180709_1202.py | f0cb05d8d9afdc3986400a5325e46b8b845985f5 | [] | no_license | hlsl/XSProject | 67cb83c5d4cdd5cb3c81e336c27df2d4235d5c8f | ee8a8e703721e01d101ea1f3c0e87492375c64ab | refs/heads/master | 2020-03-22T04:50:05.948901 | 2018-07-10T11:15:01 | 2018-07-10T11:15:01 | 139,524,575 | 0 | 0 | null | 2018-07-10T01:30:50 | 2018-07-03T03:35:31 | JavaScript | UTF-8 | Python | false | false | 838 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-07-09 12:02
from __future__ import unicode_literals
import DjangoUeditor.models
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('artapp', '0005_auto_20180705_1000'),
]
operations = [
migrations.AlterModelOptions(
name='art',
options={'verbose_name': '文章', 'verbose_name_plural': '文章'},
),
migrations.AlterModelOptions(
name='arttag',
options={'verbose_name': '分类标签', 'verbose_name_plural': '分类标签'},
),
migrations.AlterField(
model_name='art',
name='summary',
field=DjangoUeditor.models.UEditorField(blank=True, default='', verbose_name='概述'),
),
]
| [
"dummer@yeah.net"
] | dummer@yeah.net |
3ea66a4a06134c93851ec7511a4ad8bc0c57d43e | 17ab268c09df85a22a0af0179bb9ab54dd976eb7 | /codeNLP/tools/filterStopWords.py | 96e174f147338195cd7d61a45ae03a9c6420b987 | [] | no_license | remarkableJ/python | 89255fee4c0c6cc8b64a8f45279f7cd641ac521f | 9bcfad4f3819f8fead71e558feee6610cf0ae15b | refs/heads/master | 2020-05-20T21:04:24.569963 | 2018-09-09T13:38:01 | 2018-09-09T13:38:01 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,875 | py | # -*- coding: utf-8 -*-
# writer : lgy
# data : 2017-07-31
import MyCode.config
import ReadFile
# 过滤标点符号和停用词
def filterStopWords(sentences,file=MyCode.config.StopWordPath+'stop_2.txt'):
stopWords = ReadFile.readStopWord(file)
filterSentences = []
noFilterSentences = []
for sentence in sentences:
filter_words = []
nofilterWords = []
for sen in sentence:
nofilterWords.append(sen)
if sen not in stopWords:
filter_words.append(sen)
filterSentences.append(filter_words)
noFilterSentences.append(nofilterWords)
return filterSentences,noFilterSentences
def filterStopWordsInSentences(par_sentences):
# file = "../../Data/StopWords/stop.txt"
stopWords = ReadFile.readStopWord(MyCode.config.StopWordPath + 'stop_2.txt')
filter_Par_Sentences = []
for par_sentence in par_sentences:
filterSentences = []
for sen in par_sentence:
words = []
for word in sen:
if word not in stopWords:
words.append(word)
filterSentences.append(words)
filter_Par_Sentences.append(filterSentences)
return filter_Par_Sentences
def filterStopWords(Words):
New_words = []
stopWords = ReadFile.readStopWord(MyCode.config.StopWordPath + 'stop_2.txt')
for word in Words:
if word not in stopWords:
New_words.append(word)
return New_words
def filterStopWordFromSentences(sentences):
stopWords = ReadFile.readStopWord(MyCode.config.StopWordPath + 'stop_2.txt')
filter_sentences = []
for sentence in sentences:
filter_sentence = []
for w in sentence:
if w not in stopWords:
filter_sentence.append(w)
filter_sentences.append(filter_sentence)
return filter_sentences
| [
"liguoyu@ainirobot.com"
] | liguoyu@ainirobot.com |
f95f8a329e6279fc0ee59df351c887432ee6fec1 | 93736e8d0d5517eb73af91eeda6e9b0f4b07439e | /Python/Intro_Python/exercise3.py | e85c0cc0eae27917d1839cebdafb0e37e1cd146e | [] | no_license | aayushgupta97/TTN | 0de1a5d3a25d7399d68a81ea51f17233f81029e0 | 324466cbdf0a9b0953dd4ae574bd0b3f753c4fd7 | refs/heads/master | 2020-04-21T12:18:25.721602 | 2019-04-15T11:09:13 | 2019-04-15T11:09:13 | 169,557,867 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,564 | py | from abc import ABC, abstractmethod
class Box(ABC):
def add(self, *items):
raise NotImplementedError()
def empty(self):
raise NotImplementedError()
def count(self):
raise NotImplementedError()
class Item():
def __init__(self, name, value):
self.name = name
self.value = value
class ListBox(Box):
def __init__(self):
self._items = []
def add(self, *items):
self._items.extend(items)
def empty(self):
items = self._items
self._items = []
return items
def count(self):
return len(self._items)
# class DictBox(Box):
# def __init__(self):
# self._items = {}
# def add(self, *items):
# self._items.update(dict((i.name, i) for i in items))
# def empty(self):
# items = list(self._items.values())
# self._items = {}
# return items
# def count(self):
# return len(self._items)
# #repack
# def repack_boxes(*boxes):
# items = []
# for box in boxes:
# items.extend(box.empty())
# while items:
# for box in boxes:
# try:
# box.add(items.pop())
# except IndexError:
# break
# box1 = ListBox()
# box1.add(Item(str(i), i) for i in range(20))
# box2 = ListBox()
# box2.add(Item(str(i), i) for i in range(9))
# # box3 = DictBox()
# # box3.add(Item(str(i), i) for i in range(5))
# repack_boxes(box1, box2) #, box2, box3
# print(box1.count())
# print(box2.count())
# # print(box3.count())
| [
"aayushgupta2097@gmail.com"
] | aayushgupta2097@gmail.com |
24cbee6b70175ffd217555f9478d5d346eaebf22 | 0263a6373da695bbad2fd132143e34bcb3d8340f | /store/views/checkout.py | 9221753408e76f6f81b3b6bb7dae8737f53aba27 | [] | no_license | milanjuneja/Django-E-Commerse | bab39fe54cd9961701a25ff010e7d80f79e468fa | f2cccc95b52e340d5db060221eece965fc69a0b6 | refs/heads/main | 2023-02-16T21:33:54.110995 | 2021-01-18T05:48:09 | 2021-01-18T05:48:09 | 330,564,314 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 981 | py | from django.shortcuts import render, redirect
from store.models import Customer
from store.models.product import Product
from django.views import View
from store.models.orders import Order
class CheckOut(View):
def post(self, request):
address = request.POST.get('address')
phone = request.POST.get('phone')
customer = request.session.get('customer')
cart = request.session.get('cart')
products = Product.get_product_by_id(list(cart.keys()))
print(address, phone, customer, cart, products)
for product in products:
order = Order(customer=Customer(id=customer),
product=product,
price=product.price,
address=address,
phone=phone,
quantity=cart.get(str(product.id)))
order.save()
request.session['cart'] = {}
return redirect('cart')
| [
"milan.juneja97@gmail.com"
] | milan.juneja97@gmail.com |
b2c18894797ee2043d24a28316aa7e6884bcfeb3 | 14e25d5a772e44b2fb123a8b75f940361464eaa3 | /ejercicio41.py | fc1620aa218ec94715832454195bb9ddf2637e85 | [] | no_license | Lusarom/progAvanzada | 2805584f4bdc5c5cf39765d689f40b9a14d7f60f | d77d4ec77f9ff0e7e43dd9bd7598592778bdcb9a | refs/heads/master | 2020-08-03T07:08:53.216289 | 2019-12-16T02:06:17 | 2019-12-16T02:06:17 | 211,664,072 | 1 | 3 | null | null | null | null | UTF-8 | Python | false | false | 796 | py | #Exercise 41: Note To Frequency
#The following table lists an octave of music notes, beginning with middle C, along
#with their frequencies (Hz)
#Note Frequency
# C4 261.63
# D4 293.66
# E4 329.63
# F4 349.23
# G4 392.00
# A4 440.00
# B4 493.88
nombre = input('Inserta el nombre de la nota:')
nota = nombre[0].upper()
octave = int(nombre[1])
frequencia = -1
if nota == "C":
frequencia = 261.63
elif nota == "D":
frequencia = 293.66
elif nota == "E":
frequencia = 329.63
elif nota == "F":
frequencia = 349.23
elif nota == "G":
frequencia = 392.00
elif nota == "A":
frequencia = 440.00
elif nota == "B":
frequencia = 493.88
frequencia /= 2 ** (4 - octave)
print('La nota es:' ,nota, 'frequencia es ',(frequencia), 'Hz')
| [
"noreply@github.com"
] | Lusarom.noreply@github.com |
f2e9d1fa4f806aa5430bcc405d3ed2f4ea3e94d2 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p03165/s926838179.py | 74a1ba1007c89e718147b0b4242828dcbc0a88f7 | [] | 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 | 594 | py | s = input()
t = input()
dp = [[0]*(len(t)+1) for _ in range(len(s)+1)]
for i in range(len(s)):
for j in range(len(t)):
if s[i]==t[j]:
dp[i+1][j+1] = dp[i][j]+1
else:
if dp[i+1][j] < dp[i][j+1]:
dp[i+1][j+1] = dp[i][j+1]
else:
dp[i+1][j+1] = dp[i+1][j]
i = len(s)-1
j = len(t)-1
ans = ''
while i>=0 and j>=0:
if s[i]==t[j]:
ans += t[j]
i -= 1
j -= 1
else:
if dp[i][j+1]>dp[i+1][j]:
i -= 1
else:
j -= 1
print(ans[::-1]) | [
"66529651+Aastha2104@users.noreply.github.com"
] | 66529651+Aastha2104@users.noreply.github.com |
c75c16694e0598bee07205e690fd35c553bb7685 | f8ebbecd484cd143ca2bc2f2359435a364ea2dc7 | /Source Code/haarcascade_lefteye_2splits.py | d579aefacc962d2569f1ca3125d08096a1d8c21a | [] | no_license | AABelkhiria/Face-recognition | 59f5d50d2429ea4d5cb643baa0423f21c61261c2 | 5f91b5f90e457d55f768d723c8e8aa45ba1a788e | refs/heads/master | 2020-03-19T06:33:56.168234 | 2018-06-04T14:20:23 | 2018-06-04T14:20:23 | 136,033,473 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 733 | py | import numpy as np
import cv2
cap = cv2.VideoCapture(0)
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
# Our operations on the frame come here
## gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
face_cascade = cv2.CascadeClassifier('haarcascade_lefteye_2splits.xml')
faces = face_cascade.detectMultiScale(frame, 1.05, 5)
print("Found " +str(len(faces))+ " face(s)")
for (x,y,w,h) in faces:
cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
# Display the resulting frame
cv2.imshow('frame',frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
| [
"noreply@github.com"
] | AABelkhiria.noreply@github.com |
3f1e308d19e893b1fe84b6721c00d7b57e975f55 | 3e8622172a0a31627234e75a07f8ce915b2c901c | /sentilizer_api/src/vader/vader.py | 769a1b202cb50bfa1f58fcd5b82efffb7bbb3180 | [] | no_license | PrajaktaShirke29/sentimentAnalysis | e7ef83f435b69b9ab05100e6fd2369b99dc3326c | d20a6bf5f3ef6f5003b12536d927716eb84af5ee | refs/heads/master | 2023-07-21T08:33:47.196285 | 2020-04-21T14:18:00 | 2020-04-21T14:18:00 | 257,611,298 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 532 | py | import argparse
from nltk.sentiment.vader import SentimentIntensityAnalyzer
import operator
if __name__ == '__main__':
parser = argparse.ArgumentParser(description = 'Vader Sentiment analyser')
parser.add_argument('-s', action = 'store', type = str)
args = parser.parse_args()
if args.s:
scores = SentimentIntensityAnalyzer().polarity_scores(args.s)
del scores['compound']
sorted_scores = sorted(scores.items(), key=operator.itemgetter(1), reverse=True)
print(sorted_scores[0][0])
| [
"Prajakta.Shirke@harbingergroup.com"
] | Prajakta.Shirke@harbingergroup.com |
b34428c03f3dc5ed5527de94dfbd57c52ba5683d | 574e5ea9a23872bad38da2f41c60a0dec67e8149 | /cmd/templates/app/core/common.py | 80261a513c0513846ae262ac9605cf7e6fb40fac | [
"Apache-2.0"
] | permissive | ysyisyourbrother/brandnew-flask | 4c4ac5f4cc22507c3cef9dd1a5e55eee56351c6c | 5b83728d1312156f4e6c596f3ffc11f5def7dfae | refs/heads/master | 2023-06-25T22:12:32.219691 | 2021-07-28T17:44:52 | 2021-07-29T10:51:13 | 390,447,459 | 4 | 0 | null | null | null | null | UTF-8 | Python | false | false | 94 | py | # _*_ coding: utf-8 _*_
# Common helper functions for development
__author__ = "{{.Author}}" | [
"brandonye@qq.com"
] | brandonye@qq.com |
414908b6d2f0b67a5c1636a4d6d492fc710c1c6d | 71e4295f8642dabd5c9cd4a6717a7b39497596f6 | /generate_demo_data.py | c1c68cb7f6edd699e4cee738bfa85b8c1040639f | [
"BSD-3-Clause"
] | permissive | sixfeetup/PythonBooster_CSV | b464c1601d4534c9b90461e71c171abab0da46e4 | 8bab25edff355e1f793de4778ef603994e8e818c | refs/heads/master | 2021-08-29T08:48:45.501835 | 2020-06-30T17:49:42 | 2020-06-30T17:49:42 | 148,793,676 | 0 | 0 | BSD-3-Clause | 2021-08-23T20:43:20 | 2018-09-14T13:38:23 | Jupyter Notebook | UTF-8 | Python | false | false | 426 | py | import csv
from mimesis import Generic
g = Generic()
with open('games.csv','w', newline='') as f:
writer = csv.writer(f)
header = ['Title', 'Platform', 'Rating', 'High Score']
writer.writerow(header)
for _ in range(100):
row = [
g.games.game(),
g.games.gaming_platform(),
g.games.pegi_rating(),
g.games.score()
]
writer.writerow(row)
| [
"calvin@sixfeetup.com"
] | calvin@sixfeetup.com |
e91848d3129b01eeac17497f4be7ff57f9e5a2d5 | 215cafb0a79338a2a268c19629f07df20cf68f76 | /venv/bin/pip-3.8 | 6de21cb3dcc8b330bf64648feb3896c8b6bb5f2d | [] | no_license | safwanvk/erp | c95741c5873ebaa53a8a96093928745e02000be9 | d4e427dbb6b71eb9aa6e2d15a039e2e669c53cbe | refs/heads/master | 2022-12-08T12:38:36.817514 | 2020-08-16T15:10:55 | 2020-08-16T15:10:55 | 287,913,687 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 262 | 8 | #!/home/safwan/Desktop/projects/erp-pro/erp/venv/bin/python
# -*- coding: utf-8 -*-
import re
import sys
from pip._internal.cli.main import main
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
sys.exit(main())
| [
"safwanvalakundil@gmail.com"
] | safwanvalakundil@gmail.com |
bdcc68d3b044dabea63235f27546be33eb8561a2 | 908b6096ddebd0ab62c39ece41e210951abb78ea | /season_scripts/toggle_staking.py | d9f2a40c29fb8bbc81fa606d225a1bf4a006995a | [] | no_license | han-so1omon/Token-Staking-Upgrade | 154f86ef2c32dc4e6357be8abf3f538c8636bd5f | 39282e4f11b6ff568a0d8a00f4b533448929aeba | refs/heads/master | 2020-03-31T16:04:11.438429 | 2019-01-26T18:46:10 | 2019-01-26T18:46:10 | 152,361,191 | 2 | 9 | null | 2018-11-30T21:02:16 | 2018-10-10T04:03:42 | WebAssembly | UTF-8 | Python | false | false | 610 | py | import subprocess
import argparse
from config import *
import sys
parser = argparse.ArgumentParser()
parser.add_argument(
"-s",
dest="on_switch",
help="1/0 turn on/off stakebreak")
args = parser.parse_args()
try:
on_switch = int(args.on_switch)
except:
print('on_switch must be an int: currently it is a %s' % type(args.on_switch))
print('correct example: python toggle_staking.py -s 1')
sys.exit()
cmd = \
'cleos --url ' + URL + \
' push action ' + OWNER + \
' stakebreak \'{"on_switch":"%d"}\' -p ' % on_switch + OWNER
print(cmd)
subprocess.call(cmd, shell=True)
| [
"lucius.dickerson@gmail.com"
] | lucius.dickerson@gmail.com |
ecdd46216ba5a0bcaa02f2e1e21b9208c650fb0c | d542ff94db2e7d93fd87bf4780aad1170ef2605c | /zipscript.py | 783a369711a5fa56d89966b47e5703028c8cd9c9 | [] | no_license | ddo6/490Itinerary | 23488227801c47cbc9d6ac63c14dcf7095641dd4 | 2384c2e2cec56db36851d81b896a35594721e6d1 | refs/heads/master | 2021-01-24T16:33:43.514152 | 2018-05-10T17:07:39 | 2018-05-10T17:07:39 | 123,201,245 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,991 | py | #!/usr/bin/env python
import zipfile
import sys
import os
version = input("What version is this? (Please contact admin if unsure) :")
def zip_folder(folder_path, output_path):
"""Zip the contents of an entire folder (with that folder included
in the archive). Empty subfolders will be included in the archive
as well.
"""
parent_folder = os.path.dirname(folder_path)
# Retrieve the paths of the folder contents.
contents = os.walk(folder_path)
try:
zip_file = zipfile.ZipFile(output_path, 'w', zipfile.ZIP_DEFLATED)
for root, folders, files in contents:
# Include all subfolders, including empty ones.
for folder_name in folders:
absolute_path = os.path.join(root, folder_name)
relative_path = absolute_path.replace(parent_folder + '\\',
'')
print "Adding '%s' to archive." % absolute_path
zip_file.write(absolute_path, relative_path)
for file_name in files:
absolute_path = os.path.join(root, file_name)
relative_path = absolute_path.replace(parent_folder + '\\',
'')
print "Adding '%s' to archive." % absolute_path
zip_file.write(absolute_path, relative_path)
print "'%s' created successfully." % output_path
except IOError, message:
print message
sys.exit(1)
except OSError, message:
print message
sys.exit(1)
except zipfile.BadZipfile, message:
print message
sys.exit(1)
finally:
zip_file.close()
## TEST ##
if __name__ == '__main__':
#Change the folder path here to the folder you want to zip
zip_folder(r'/home/dina/phpscripts',
r'/home/dina/testdirectory'+str(version)+'.zip')
# zip_folder(r'folder_path',
# r'/home/dina/testdirectory.zip')
| [
"noreply@github.com"
] | ddo6.noreply@github.com |
7637392ea0f3d70bc4dd195e25a899139441b659 | f561eb1ec22cc8e980decdbc634b852857e0e0a0 | /json_model/libs.py | 4efda94a983cb941d235d777d7f46c1309a70aba | [
"BSD-3-Clause"
] | permissive | richlysakowski/json-model | 4db763b4f1351a3b36cf93c2adfcc409c8fcdbce | 370cc9273cdf88bbf1d95b3a488f3fcb486f99d8 | refs/heads/master | 2021-12-30T06:15:32.980153 | 2018-02-06T14:24:35 | 2018-02-06T14:24:35 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,235 | py | import json
from json_model.validators import Validation
class JsonModelBase(type):
@classmethod
def __set_fields(cls, namespace):
namespace['fields'] = []
for name, attr in namespace.items():
if hasattr(attr, 'field_type'):
namespace['fields'].append(name)
return namespace['fields']
def __new__(mcs, name, bases, namespace):
mcs.__set_fields(namespace)
instance = super().__new__(mcs, name, bases, namespace)
instance.validation = Validation(namespace['fields'])
return instance
class JsonModel(metaclass=JsonModelBase):
def __init__(self, **fields):
for field, value in fields.items():
setattr(self, field, value)
def get_json_fields(self):
from json_model.fields import ForeignField
fields = dict()
for name in self.fields:
field = getattr(self, name, None)
if isinstance(field, ForeignField):
fields[name] = field.value.get_json_fields()
else:
fields[name] = field.value
return fields
def to_json(self):
"""Returns json object."""
return json.dumps(self.get_json_fields())
| [
"slawek@thecapitals.nl"
] | slawek@thecapitals.nl |
5e60e4b3dc3fb76f42297185b977877bbdcf4dc6 | 86a72346ee1e501934d8ee657cd762e5af173335 | /hpshare/__init__.py | 3a328206ec24d469ab92471d2b8d023d97b99c47 | [] | no_license | n37r06u3/hpShare | 2cf54974cab50c4ecd95570a1f8a004b6c5f107e | b38af79751b5eb3e68486ac2775620f6ab58709c | refs/heads/master | 2020-12-30T19:10:53.096603 | 2015-02-15T08:49:02 | 2015-02-15T08:49:02 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 88 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Created by i@BlahGeek.com at 2015-01-29
| [
"blahgeek@gmail.com"
] | blahgeek@gmail.com |
0ca25af8f9a6904667000b51d71a2b47c62013f5 | 4e206fe25d0389db9ec05d5c6795e6179c19dc6d | /stories/forms.py | 1c558771bc65ff027462a204be2668aba79ae52e | [] | no_license | elena/first-contrib | b053d73dd131b658db904abca7225646ecef82f6 | d7d94a4d9865c9881ed0505fa2049a7cbb55d3b3 | refs/heads/master | 2023-07-22T00:41:34.442794 | 2023-07-15T02:29:46 | 2023-07-15T02:29:46 | 17,080,871 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,345 | py | import calendar
from django import forms
from stories.models import Story
from crispy_forms import helper, layout
from ckeditor.widgets import CKEditorWidget
from crispy_forms.bootstrap import PrependedText
from crispy_forms.layout import Fieldset, Field, ButtonHolder, Button, Submit
NONE_TEXT = ' ---'
class StoryForm(forms.ModelForm):
project = forms.CharField(required=False,
label="Project Name or Description",
help_text="The first project you contributed to.",
)
project_description = forms.CharField(required=False,
help_text="Just a quick description, in case the project isn't famous."
)
vcs = forms.MultipleChoiceField(
widget=forms.SelectMultiple(), choices = Story.CHOICES_VCS,
required=False, label="Version Control Used",
)
comms = forms.MultipleChoiceField(
widget=forms.SelectMultiple(), choices = Story.CHOICES_COMMS,
required=False, label="Communication Methods",
)
vcs_other = forms.CharField(required=False, label='',
widget=forms.TextInput(attrs={'placeholder': "Other: SCCS, RSC"})
)
comms_other = forms.CharField(required=False, label='',
widget=forms.TextInput(attrs={'placeholder': "Other"})
)
year = forms.ChoiceField(required=False, help_text=" ",
choices = [('', NONE_TEXT)]+[(year, year) for year in xrange(2013, 1959, -1)],
)
month = forms.ChoiceField(required=False, help_text=" ",
choices = [('', NONE_TEXT)]+zip(xrange(0,13), list(calendar.month_name)),
)
experience = forms.CharField(required=False,
#placeholder="Why? How much work? Who did you talk to?",
widget=CKEditorWidget()
)
skill_professional = forms.ChoiceField(required=False,
label = "Professional",
choices = [('', NONE_TEXT)]+Story.CHOICES_ASSESS,
help_text = "Professional experience",
)
skill_language = forms.ChoiceField(required=False,
label = "Technical",
choices = [('', NONE_TEXT)]+Story.CHOICES_ASSESS,
help_text = "Ability with skills required"
)
skill_vcs = forms.ChoiceField(required=False,
label = "Version Control",
choices = [('', NONE_TEXT)]+Story.CHOICES_ASSESS,
help_text = "Knowledge of VCS used",
)
preferred_name = forms.CharField(required=False)
full_name = forms.CharField(required=False)
github = forms.CharField(required=False, label=' ')
twitter = forms.CharField(required=False, label=' ')
website = forms.URLField(required=False)
other = forms.URLField(required=False,
label = "Another URL",
)
known_as_1 = forms.CharField(required=False, label="Known as",
widget=forms.TextInput(attrs={'placeholder': "BDFL, core, contributor"})
)
for_project_1 = forms.CharField(required=False, label="for Project/s")
known_as_2 = forms.CharField(required=False, label="Known as",
widget=forms.TextInput(attrs={'placeholder': "BDFL, core, contributor"})
)
for_project_2 = forms.CharField(required=False, label="for Project/s")
class Meta:
model = Story
def __init__(self, *args, **kwargs):
super(StoryForm, self).__init__(*args, **kwargs)
self.helper = helper.FormHelper()
self.helper.form_class = 'form-inline'
self.helper.field_template = 'bootstrap3/layout/inline_field.html'
self.helper.layout = layout.Layout(
Fieldset('What year did you make your first contribution? (approximately)',
Field('year'),
Field('month'),
#layout.HTML('<br /><br />'),
Field('project', css_class='part-width'),
#Field('project_description', css_class='full-width'),
# ),
# Fieldset('What form of Version Control did you use?',
layout.HTML('<br />'),
Field('vcs'),
Field('comms'),
layout.HTML('<br />'),
Field('vcs_other'),
Field('comms_other'),
layout.HTML('<br /><br />'),
# 'vcs_other',
),
Fieldset('About you',
layout.HTML('''<p><strong>All fields are optional.</strong> No information provided here will be redistributed or used for any other purpose than displaying on this website.<br />Although your story nearly certainly won't pass moderation if you don't give us an idea of who you are.</p>'''),
Field('preferred_name', css_class='part-width'),
Field('full_name', css_class='part-width'),
layout.HTML('<br />'),
PrependedText('github', 'github/', placeholder="[username]"),
PrependedText('twitter', '@', placeholder="twitter"),
layout.HTML('<div> </div>'),
Field('website', css_class='full-width'),
Field('other', css_class='full-width'),
# ),
# Fieldset(' ',
layout.HTML('<div> </div>'),
Field('known_as_1', placeholder="BDFL, core, contributor"),
Field('for_project_1', placeholder="for Project/s"),
layout.HTML('<br />'),
'known_as_2',
'for_project_2',
layout.HTML('<br /><br /><br />'),
),
Fieldset('"Self Assessed" skill level the first time you contributed to Free Software:',
Field('skill_language'),
Field('skill_professional'),
Field('skill_vcs'),
layout.HTML('<br /><br />'),
),
Fieldset('Story about the experience',
layout.HTML('<p><strong>Why</strong> did you get involved? How much work was involved (hopefully not much for your first commit!)?<br>'),
layout.HTML('How did you get in contact with the project? Who was involved? Did anything interesting happen?<br>'),
layout.HTML('Why did you keep contributing?</p>'),
'experience',
),
ButtonHolder(
Button('preview', 'Preview', css_class='preview btn btn-primary'),
Submit('submit', 'Submit', css_class='btn btn-primary'),
Button('reset', 'Cancel', css_class='btn')
)
)
def clean(self, *args, **kwargs):
clean_data = super(StoryForm, self).clean(*args, **kwargs)
for k,v in clean_data.iteritems():
if v == u'':
clean_data[k] = None
#raise Exception(clean_data)
if clean_data['vcs']:
clean_data['vcs'] = ', '.join(clean_data['vcs'])
if clean_data['comms']:
clean_data['comms'] = ', '.join(clean_data['comms'])
return clean_data
# # check name unique
# name = clean_data.get('name')
# person = Person.objects.filter(name=name)
# if person:
# raise forms.ValidationError('Yo, that name is taken ~')
# # check event exists
# event = Event.objects.filter(current=True)
# if not event:
# raise forms.ValidationError("Hey! There aren't any current events. Go tell an organiser to activate an event.")
# return clean_data
| [
"github@elena.net.au"
] | github@elena.net.au |
65a9558526de57a3cce453bed9d0ada7b8144b71 | 015268e9e0fca38db052553cabcff3bf7ec000ac | /projeto_smge/projeto_smge/__init__.py | 75b0861c0504f2bd659fbb198f38d5fea3cc74e6 | [] | no_license | bussola/desativado | b3fb998e5b0e9097688a66d43746d4e40e6f6f37 | 03d1b92d755555da0f90dda457ac76033cdaffc4 | refs/heads/master | 2021-01-20T22:11:46.380787 | 2017-12-05T19:57:30 | 2017-12-05T19:57:30 | 101,802,908 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 235 | py | #from __future__ import absolute_import, unicode_literals
# This will make sure the app is always imported when Django starts so
# that shared_task will use this app.
#from .celery import app as celery_app
#__all__ = ['celery_app']
| [
"vbussola@yahoo.com"
] | vbussola@yahoo.com |
31bf11143eb70e639f5b01a1c13e7b84f495d5a7 | f1ed5dfb5e4e082bea000b01fc25eabd89d64ce9 | /youlil/frontend/web/handlers/topic.py | 854e86c299e4abe585d08791b92b7b332280e431 | [] | no_license | sharecqy/you-learn-i-learn | 8a5fd9fa248a3535463c2d18b4b1b9a965b4410e | 39a52ea3b332b70fdf037e13d1b15bbe1752fd90 | refs/heads/master | 2021-01-20T06:59:50.377356 | 2014-07-26T14:43:59 | 2014-07-26T14:43:59 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 13,287 | py | import tornado.web
from tornado.web import asynchronous
from tornado import gen
from web.handlers.base import BaseRequestHandler
from bson.son import SON
import datetime
import time
import markdown2
"""
This topic module is to provide some functions to let users communicate or discuss topics.
user could add a topic,vote a topic,comment a topic,tag a topic,revise other user's topic(help
others write better English).
"""
class TopicIndexHandler(BaseRequestHandler):
@property
def hottest_topics(self):
self._ht=self.settings['cached']['hottest_topic'].get_data()
return self._ht
"""
This topic index handler will response the request about topic.
we can have different methods of ranking.
1.time && voting
2.Popularity
3.tag based recommendation
4.new topic
so forth
"""
@asynchronous
@gen.engine
def get(self):
next,page_num=(self.get_argument('next',2),
self.get_argument('pg',0))
if next=="0":page_num=max(0,int(page_num)-1)
if next=="1":page_num=int(page_num)+1
response=yield gen.Task(self.db.topic.find,{},skip=page_num*20,limit=20,
sort=[("time_index",-1)],fields={'title':1,'content':1,'username':1,'comments':1,'tags':1,'statistic':1})
topics= response[0][0]
#print topics
user={'username':self.session.get('username')}
for topic in topics:
topic['comments_num']=len(topic['comments'])
#topic['vote_num']=topic['statistic']['push']-topic['statistic']['pull']
#self.cache.setex('tp'+topic['_id'],{'push':topic['statistic']['push'],'pull':topic['statistic']['pull']},3600)
if self.request.headers['User-Agent']!="Android":
context=self.get_context({'user':user,'newest_topics':topics,'hottest_topics':self.hottest_topics,'page_num':page_num})
self.write(self.render.topicindex(context))
else:
self.write({'topics':topics,'page_num':page_num})
self.finish()
class TopicHandler(BaseRequestHandler):
"""
This handler is to return the topic content given by a specific topic id.
we will return:
1.topic info
2.comments info
"""
@asynchronous
@gen.engine
def get(self):
topic_id=self.get_argument('tp')
response1,response2=yield [gen.Task(self.db.topic.find_one,{'_id':float(topic_id)},fields={'title':1,'content':1,'username':1,'tags':1,'statistic':1,'comments':1,'user_id':1}) ,
gen.Task(self.db.comment.find,{'topic_id':float(topic_id)},fields={'content':1,'username':1,'statistic':1})]
topic=response1[0][0]
comments=response2[0][0]
user={'username':self.session.get('username')}
user_id=self.session.get('user')
if user_id==topic["user_id"]:
topic['editable']=True
else:
topic['editable']=False
topic['content']=markdown2.markdown(topic['content'])
topic['vote_num']=topic['statistic']['push']-topic['statistic']['pull']
#for comment in comments:
# self.cache.setex('com'+comment['_id'],{'push':comment['push'],'pull':comment['pull']},1800)
if self.request.headers['User-Agent']!="Android":
context=self.get_context({'user':user,'topic':topic,'comments':comments})
self.write(self.render.topic(context))
else:
self.write({'topic':topic,'comments':comments})
self.finish()
class AddTopicHandler(BaseRequestHandler):
"""
A topic collection contains fields:
0.Id
1.category.
2.title
3.content
4.tags
5.posted time
6.writer(user id,user name)
7.statistic(comments num,push,pull)
8.modification(content,time,writer)
9.comments Ids
10.paid attention users
"""
@tornado.web.authenticated
def get(self):
category="test"#self.get_argument('category')
user={'username':self.session.get('username')}
context=self.get_context({'user':user,'category':category})
self.write(self.render.addtopic(context))
@asynchronous
@gen.engine
@tornado.web.authenticated
def post(self):
title,content,category,tags=(self.get_argument('title'),
self.get_argument('content'),
self.get_argument('category'),
self.get_argument('tags'))
print title
print content
tags=tags.split()
command = SON()
command['findandmodify'] = 'autoincrease'
command['query'] = { '_id' : "topic_id" }
command['update'] = { '$inc': { 'seq': long(1) } }
#command['new'] = True
#command['upsert'] = True
response1=yield gen.Task(self.db.command,
command)
topic_id=response1[0][0]['value']['seq']
user_id=self.session.get('user')
username=self.session.get('username')
time1 = datetime.datetime.now()
time2 = int(time.mktime(time1.timetuple()))
response2=yield gen.Task(self.db.topic.insert,{"_id":topic_id,
"title":title,
"content":content,
"category":category,
"user_id":user_id,
"username":username,
"statistic":{"comment":0,"push":0,"pull":0},
"posted_time":time1,
"time_index":time2,
"comments":[],
"tags":tags,
"careusers":[],
})
self.redirect('/topicindex')
class EditTopicHandler(BaseRequestHandler):
"""
"""
@asynchronous
@gen.engine
@tornado.web.authenticated
def get(self):
topic_id=self.get_argument('tp')
response=yield gen.Task(self.db.topic.find_one,{'_id':float(topic_id)})
topic=response[0][0]
print response
print topic
if len(topic):
user={'username':self.session.get('username')}
context=self.get_context({'user':user,'topic_id':topic['_id'],'title':topic['title'],
'content':topic['content'],'category':topic['category'],'tags':' '.join(topic['tags'])})
self.write(self.render.edittopic(context))
self.finish()
else:
self.redirect(''.join(['/topic?tp=',topic_id]))
@asynchronous
@gen.engine
@tornado.web.authenticated
def post(self):
topic_id,title,content,tags=(self.get_argument('tp'),
self.get_argument('title'),
self.get_argument('content'),
self.get_argument('tags'))
tags=tags.split()
response=yield gen.Task(self.db.topic.update,{"_id":float(topic_id)},
{"$set":{"title":title,"content":content,"tags":tags}})
self.redirect(''.join(['/topic?tp=',topic_id]))
class DeleteTopicHandler(BaseRequestHandler):
"""
"""
@asynchronous
@gen.engine
@tornado.web.authenticated
def post(self):
pass
class VoteTopicHandler(BaseRequestHandler):
"""
This handler is to handle the voting from user.
Key problem is how to limit a user's voting time for a given topic or comments
"""
@asynchronous
@gen.engine
@tornado.web.authenticated
def post(self):
topic_id,comment_id,push=(self.get_argument('tp',''),
self.get_argument('com',''),
self.get_argument('push',0))
if topic_id:
voted_tp=self.session.get('voted_tp',[])
if topic_id in voted_tp:
self.write('voted')
else:
if len(voted_tp)>20:
voted_tp=voted_tp[10:]
voted_tp.append(topic_id)
self.session.set('voted_tp',voted_tp)
if push:
response=yield gen.Task(self.db.topic.update,{"_id":float(topic_id)},
{"$inc":{"statistic.push":int(1)}})
else:
response=yield gen.Task(self.db.topic.update,{"_id":float(topic_id)},
{"$inc":{"statistic.pull":int(1)}})
self.write('ok')
else:
self.write('voted')
self.finish()
class VoteCommentHandler(BaseRequestHandler):
"""
This handler is to handle the voting from user.
Key problem is how to limit a user's voting time for a given topic or comments
"""
@asynchronous
@gen.engine
@tornado.web.authenticated
def post(self):
comment_id,push=(self.get_argument('com',''),
self.get_argument('push',0))
if comment_id:
voted_com=self.session.get('voted_com',[])
if comment_id in voted_com:
self.write('voted')
else:
if len(voted_com)>20:
voted_com=voted_com[10:]
voted_com.append(comment_id);
self.session.set('voted_com',voted_com)
if push:
response=yield gen.Task(self.db.comment.update,{"_id":float(comment_id)},
{"$inc":{"statistic.push":int(1)}})
else:
response=yield gen.Task(self.db.comment.update,{"_id":float(comment_id)},
{"$inc":{"statistic.pull":int(1)}})
self.write('ok')
else:
self.write('voted')
self.finish()
class AddTPCommentHandler(BaseRequestHandler):
"""
comments 0.comment Id
1.content
2.writer(user id,user name)
3.comment time
4.modification(list[time,write,content])
7.statistic(reply num,push,pull)
8.topic Id
"""
@asynchronous
@gen.engine
@tornado.web.authenticated
def get(self):
pass
@asynchronous
@gen.engine
@tornado.web.authenticated
def post(self):
topic_id,comment=(self.get_argument('tp'),
self.get_argument('comment'))
print comment
command = SON()
command['findandmodify'] = 'autoincrease'
command['query'] = { '_id' : "comment_id" }
command['update'] = { '$inc': { 'seq': long(1) } }
#command['new'] = True
#command['upsert'] = True
response1=yield gen.Task(self.db.command,
command)
comment_id=response1[0][0]['value']['seq']
user_id=self.session.get('user')
username=self.session.get('username')
time1 = datetime.datetime.now()
time2 = int(time.mktime(time1.timetuple()))
request2,request3=yield [gen.Task(self.db.topic.update,{'_id':float(topic_id)},{'$push':{'comments':comment_id}}),
gen.Task(self.db.comment.insert,{'_id':comment_id,
'content':comment,
'user_id':user_id,
'username':username,
"statistic":{"push":0,"pull":0},
'comment_time':time1,
'time_index':time2,
'modif':[],
'topic_id':float(topic_id),
})]
self.redirect(''.join(['/topic?tp=',topic_id]))
class EditCommentsHandler(BaseRequestHandler):
"""
"""
@asynchronous
@gen.engine
@tornado.web.authenticated
def post(self):
pass
class DeleteCommentsHandler(BaseRequestHandler):
"""
"""
@asynchronous
@gen.engine
@tornado.web.authenticated
def post(self):
pass
class ReviseHandler(BaseRequestHandler):
"""
"""
@asynchronous
@gen.engine
@tornado.web.authenticated
def get(self):
pass
| [
"qingyu.cqy@alibaba-inc.com"
] | qingyu.cqy@alibaba-inc.com |
726fdcd541c6b3cd7d6e08d9071d8e1a703bedd9 | 6b2bf44d986896dac8e5738ef18037e995adbb20 | /spass/serializers.py | 5ab5c91d18495c16ce35c35bb4a979b69211e7f2 | [
"MIT"
] | permissive | RobertoMarroquin/visor_spass | 394279a83d8c4cde59fe7e7f09a8570fe6ecbc94 | c5ad15ae69a728bffc5d63e028567da5f559719f | refs/heads/main | 2023-07-05T13:31:13.247470 | 2021-08-09T22:33:12 | 2021-08-09T22:33:12 | 388,918,704 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,663 | py | from rest_framework import serializers
from .models import GovernmentPurchase, Job, GovernmentInstitution
class GovernmentPurchaseSerializer(serializers.ModelSerializer):
government_institution_id = serializers.SlugRelatedField(source='government_institution', read_only=True, slug_field='id')
government_institution = serializers.StringRelatedField()
seller = serializers.StringRelatedField()
seller_id = serializers.SlugRelatedField(source='seller', read_only=True, slug_field='id')
purchase_order = serializers.StringRelatedField()
purchase_order_url = serializers.SlugRelatedField(source='purchase_order', read_only=True, slug_field='url')
class Meta:
model = GovernmentPurchase
fields = ['id','government_institution_id','government_institution','seller','description','award_date',
'price','purchase_order', 'purchase_order_url', 'seller_id']
class SupplierSerializer(serializers.ModelSerializer):
class Meta:
model = GovernmentPurchase
fields = ['id','government_institution_id','government_institution','seller','description','award_date',
'price','purchase_order']
class GovernmentInstitutionSerializer(serializers.ModelSerializer):
name = serializers.StringRelatedField()
class Meta:
model = GovernmentInstitution
fields = ['id','name']
class JobSerializer(serializers.ModelSerializer):
natural_person = serializers.CharField(source='natural_person.complete_name')
class Meta:
model = Job
fields = ['id','job_name','nominal_job_name','natural_person','monthly_salary','start_date','academic_degree',
'work_area']
| [
"robma96@gmail.com"
] | robma96@gmail.com |
1d8e77394bd73508cee5a29ddb0c29f34fbbefe0 | cb83ef2c71bc0ca5cc9a4061a61093088cc9f3e6 | /experiments.py | 2c53d61a9065a708d831daafabb14d9d29e9bdd3 | [] | no_license | Vee27/Heart-Disease-Analysis | 1fa83618e8577f7e9d950ef403b79c920777938e | cc92fb89d6b4df85e2867e5ef39f5df531e325cb | refs/heads/main | 2023-04-19T20:40:59.909304 | 2021-05-04T16:59:28 | 2021-05-04T16:59:28 | 364,322,993 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,982 | py | """
Heart Disease Analysis using ML algorithms from scikit-learn
(Logistic Regression, SVM, KNN, Gaussian Naiive Bayes, Decision Trees, Random Forest)
"""
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.svm import SVC
from sklearn.naive_bayes import GaussianNB
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report, confusion_matrix
from sklearn.ensemble import RandomForestClassifier
# Read data
df = pd.read_csv(r'data/heart.csv')
# print(df.head())
# first step is to convert all categorical to numerical values
a = pd.get_dummies(df['cp'], prefix="cp") # representing chest pain [0-3]
b = pd.get_dummies(df['thal'], prefix="thal") # thalassemia [0-2]
c = pd.get_dummies(df['slope'], prefix="slope") # [0-2]
# append the converted numerical values as new columns
temp_df = [df, a, b, c]
df = pd.concat(temp_df, axis=1)
# drop the columns with the categorical values
df.drop(columns=['cp', 'thal', 'slope'])
# dropping the class / target labels from the train data
X = df.drop(['target'], axis=1)
y = df.target.values
# Normalize
x = (X - np.min(X)) / (np.max(X) - np.min(X)).values
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=42)
print(x_train.shape, x_test.shape)
print(y_train.shape, y_test.shape)
def train_and_predict(classifier):
# fit the train data to classifier
model = classifier.fit(x_train, y_train)
# predict on test data
predictions = model.predict(x_test)
# evaluate the model
score_ = model.score(x_test, y_test)
conf = confusion_matrix(y_test, predictions)
report = classification_report(y_test, predictions)
print(conf)
print(report)
return score_ * 100
# Accuracy with Logistic Regression Classifier
acc_lr = train_and_predict(LogisticRegression())
print("Test Accuracy {:.2f}%".format(acc_lr))
# KNN Model
acc_knn = train_and_predict(KNeighborsClassifier(n_neighbors=2)) # n_neighbors means the k value
print("{} NN Test Accuracy: {:.2f}%".format(2, acc_knn))
# to find best k value
scoreList = []
for i in range(1, 20):
knn = KNeighborsClassifier(n_neighbors=i)
knn.fit(x_train, y_train)
# append all the scores
scoreList.append(knn.score(x_test, y_test))
plt.plot(range(1, 20), scoreList)
plt.xticks(np.arange(1, 20, 1))
plt.xlabel("K value")
plt.ylabel("Score")
plt.title('Score with different K Values')
plt.show()
# print the maximum score
acc = max(scoreList) * 100
print("Maximum KNN Score is {:.2f}%".format(acc))
# SVM
acc_svm = train_and_predict(SVC(random_state = 1))
print("Test Accuracy with SVM Algorithm: {:.2f}%".format(acc_svm))
# Naive-Bayes
acc_nb = train_and_predict(GaussianNB())
print("Test Accuracy with Naive Bayes: {:.2f}%".format(acc))
# Decision Tree Classifier
acc_dt = train_and_predict(DecisionTreeClassifier())
print("Test Accuracy with Decision Tree: {:.2f}%".format(acc_dt))
# Random Forest Classification
acc_rf = train_and_predict(RandomForestClassifier(n_estimators=100, random_state=1))
print("Test Accuracy with Random Forest: {:.2f}%".format(acc_rf))
# plot the accuracies of all the classifiers
# add all the classifiers a s a dictionary
accuracies = {'Logistic Regression': acc_lr, 'KNN': acc_knn, 'SVM': acc_svm, 'Gaussian NB': acc_nb,
'Decision Tree': acc_dt, 'Random Forest': acc_rf}
colors = ["blue", "green", "orange", "yellow", "lightblue", "lightgreen"]
plt.figure(figsize=(12, 4))
plt.yticks(np.arange(0, 100, 10))
plt.ylabel("Accuracy (in %)")
plt.xlabel("Classifiers")
sns.barplot(x=list(accuracies.keys()), y=list(accuracies.values()), palette=colors)
plt.show()
| [
"noreply@github.com"
] | Vee27.noreply@github.com |
9f2833105773edd29e1268cc3705ad9ff9dc2a1c | 98be00ee32971cade82d10c067aff532c3394a62 | /Competitions/Xtreme/xplore.py | f6e47c98fc808d7cc0c5fe1f897956f31365aa4a | [] | no_license | vigneshhari/Competitive_solutions | 5ab34933ea8d84eab67bdef9bb9e4562f6b90782 | 7a35e1386e5cff71cb5746b6797ccc0f03ceb3f4 | refs/heads/master | 2023-01-11T02:53:01.456863 | 2022-12-29T13:50:03 | 2022-12-29T13:50:03 | 115,146,700 | 4 | 2 | null | 2019-10-26T09:15:03 | 2017-12-22T20:03:51 | Python | UTF-8 | Python | false | false | 4,010 | py | import json
from collections import defaultdict
authors_citations = defaultdict(list)
for i in range(input()):
data = raw_input()
temp = json.loads(data)
citation_count = temp["citing_paper_count"]
for i in temp["authors"]["authors"]:
authors_citations[i["full_name"]].append(citation_count)
answers = defaultdict(list)
for i in authors_citations:
values = authors_citations[i]
values.sort()
length = len(values)
out = 0
for j in range(length):
if( length - j >= values[j] ):
out = values[j]
else:
if(values[j] > length - j and length - j > out ):
out = length - j
answers[out].append(i)
temp = sorted(answers.keys())
temp = temp[::-1]
for i in temp:
for k in sorted(answers[i]):
print k , i
"""
10
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Echo"}, {"author_order": 2,"affiliation": "","full_name": "Bravo"}, {"author_order": 3,"affiliation": "","full_name": "Alfa"}]},"title": "Article Title 1","article_number": "1","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 9,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Charlie"}, {"author_order": 2,"affiliation": "","full_name": "Bravo"}]},"title": "Article Title 2","article_number": "2","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 9,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Echo"}, {"author_order": 2,"affiliation": "","full_name": "Delta"}, {"author_order": 3,"affiliation": "","full_name": "Alfa"}, {"author_order": 4,"affiliation": "","full_name": "Charlie"}]},"title": "Article Title 3","article_number": "3","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 4,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Charlie"}]},"title": "Article Title 4","article_number": "4","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 9,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Charlie"}, {"author_order": 2,"affiliation": "","full_name": "Echo"}, {"author_order": 3,"affiliation": "","full_name": "Alfa"}]},"title": "Article Title 5","article_number": "5","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 5,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Charlie"}, {"author_order": 2,"affiliation": "","full_name": "Echo"}]},"title": "Article Title 6","article_number": "6","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 6,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Delta"}]},"title": "Article Title 7","article_number": "7","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 4,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Charlie"}]},"title": "Article Title 8","article_number": "8","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 9,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Delta"}, {"author_order": 2,"affiliation": "","full_name": "Charlie"}]},"title": "Article Title 9","article_number": "9","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 4,"publisher": "IEEE"}
{"authors": {"authors": [{"author_order": 1,"affiliation": "","full_name": "Bravo"}, {"author_order": 2,"affiliation": "","full_name": "Echo"}]},"title": "Article Title 10","article_number": "10","publication_title": "Publication Title 1","publication_number": "7","citing_paper_count": 6,"publisher": "IEEE"}
"""
# Solved Completely
| [
"vichuhari100@gmail.com"
] | vichuhari100@gmail.com |
5e40148313d967893ab32e54903c81736a9b30fa | fbce960eb1c5c848fe294d7f5711d5a263780b81 | /preg_api/test_case_h5/test_expert_response/test_historical_Income.py | 8d922c49f9d2f25ba1281c5336e042118454c665 | [] | no_license | Crazy-bear/pregTest | 91033a8e91b74d9f2c68f5441264efc6ce374797 | 64c46d94a75057557e7a714e9ddbd7499ca5eb68 | refs/heads/master | 2020-06-19T13:01:01.497203 | 2019-07-24T12:07:54 | 2019-07-24T12:07:54 | 196,716,764 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,177 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019/7/18 11:24
# @Author : Bear
# @Site :
# @File : test_historical_Income.py
# @Software: PyCharm
# 历史收入
import unittest
import requests
from preg_api.common.login import *
class HistoricalIncome(unittest.TestCase):
'''历史收入'''
def setUp(self) -> None:
self.t_skey = login('evan10@qq.com', '123456')
# pprint(self.t_skey)
def test_historical_income(self):
'''默认当前月份之前的历史收入'''
querystring = {"month": ""}
headers = {'Cookie': 't_skey' + '=' + self.t_skey}
r = requests.request('POST', h5_historical_income_url, headers=headers, params=querystring)
# pprint(r.json())
status_code = r.status_code
ret = r.json()['ret']
msg = r.json()['msg']
try:
self.assertEqual(200, status_code)
self.assertEqual('0', ret)
self.assertIn('ok', msg)
except AssertionError:
raise AssertionError('获取历史数据失败：' + msg)
def tearDown(self) -> None:
pass
if __name__ == '__main__':
unittest.main()
| [
"x_scorpio@outlook.com"
] | x_scorpio@outlook.com |
6d57c6855dd53ede783641ec65bed681aa69e10a | 1196fe960947b4a7d6bba5df6cdfc7010bb118fb | /examples/apikeys/apikeys.py | 8b921f815ddb9dc3eea6e33e1ad7b042f43026be | [
"MIT"
] | permissive | Nextdoor/sendgrid-python | a4afe5cda9015c7cf6a3a1303785fda05e844277 | a7c834b6391775b796969ef65a3ef259ccabf0f0 | refs/heads/master | 2021-01-22T11:12:08.221546 | 2016-04-22T21:20:07 | 2016-04-22T21:20:07 | 56,885,507 | 0 | 0 | null | 2016-04-22T21:11:50 | 2016-04-22T21:11:49 | null | UTF-8 | Python | false | false | 1,657 | py | import sendgrid
import json
import os
sg = sendgrid.SendGridAPIClient(apikey='YOUR_SENDGRID_API_KEY')
# You can also store your API key an .env variable 'SENDGRID_API_KEY'
##################################################
# List all API Keys belonging to the authenticated user #
# GET /api_keys #
response = sg.client.api_keys.get()
print(response.status_code)
print(response.response_body)
print(response.response_headers)
##################################################
# Update the name & scopes of an API Key #
# PUT /api_keys/{api_key_id} #
data = {'sample': 'data'}
api_key_id = "test_url_param"
response = sg.client.api_keys._(api_key_id).put(request_body=data)
print(response.status_code)
print(response.response_body)
print(response.response_headers)
##################################################
# Update API keys #
# PATCH /api_keys/{api_key_id} #
data = {'sample': 'data'}
api_key_id = "test_url_param"
response = sg.client.api_keys._(api_key_id).patch(request_body=data)
print(response.status_code)
print(response.response_body)
print(response.response_headers)
##################################################
# Get an existing API Key #
# GET /api_keys/{api_key_id} #
api_key_id = "test_url_param"
response = sg.client.api_keys._(api_key_id).get()
print(response.status_code)
print(response.response_body)
print(response.response_headers)
##################################################
# Delete API keys #
# DELETE /api_keys/{api_key_id} #
api_key_id = "test_url_param"
response = sg.client.api_keys._(api_key_id).delete()
print(response.status_code)
print(response.response_body)
print(response.response_headers)
| [
"elmer@thinkingserious.com"
] | elmer@thinkingserious.com |
924d6ab26e8bec12678ab7a53eb74bb6df50eb5f | e7e4272b1db42427bb0d689b609683ad04bfcfd2 | /ex31.py | a9c41ca463cde2622bdba09fe568419ef1f8fedd | [] | no_license | ZayX0/pythonthehardway | edfd4e286109e7033267c5bee7988c65927b5b5b | bd6ecc47fe2e4ad75f458b90f3ae5f1467736c7e | refs/heads/master | 2020-05-26T13:28:38.649890 | 2017-07-21T16:41:25 | 2017-07-21T16:41:25 | 85,001,739 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,225 | py | print "You enter a dark room with two doors. Do you go through door #1 or door #2?"
door = raw_input("> ")
if door == "1":
print "Welcome to the Matrix, do you take the red pill, or blue?"
print "1) Red Pill"
print "2) Blue Pill"
pill = raw_input("> ")
if pill == "1":
print "That pill was actually poison...you're dead"
elif pill == "2":
print "You have been granted super powers for eternity, congrats!"
else:
print "You wake up in your bed and realize it was all a dream."
elif door == "2":
print "You hear a voice asking you to close your eyes and take 3 steps forward..."
print "1) Follow the voices instructions"
print "2) Ignore the instructions entirely"
voice = raw_input("> ")
if voice == "1":
print "It was an evil spirit and you walked into its mouth and it ate you, tough break"
elif voice == "2":
print "You do your own thing and close the door back as you hear the voice grumble, congrats you survived"
else:
print "You stand frozen and are now stuck in this dark room forever...should have made a valid choice"
else:
print "You have broken the space time continuim and see a Game Over screen"
| [
"ireed@indeed.com"
] | ireed@indeed.com |
df55ffe5751d160215654f44ca59df406536a410 | c03edd979ad6fd4a8abd155e3e63bcefbd93d5c2 | /Image/band_stats.py | 7b83630a66a15155d6b74a944ca88a2b17ef34e5 | [
"MIT"
] | permissive | xiangtaoxu/earthengine-py-examples | 538dafc88a22a351b762ba02df09db583df955bb | 76ae8e071a71b343f5e464077afa5b0ed2f9314c | refs/heads/master | 2022-11-03T03:16:11.933616 | 2020-06-12T15:47:52 | 2020-06-12T15:47:52 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,987 | py |
import ee
import geemap
# Create a map centered at (lat, lon).
Map = geemap.Map(center=[40, -100], zoom=4)
# get highest value
def maxValue(img, scale=30):
max_value = img.reduceRegion(**{
'reducer': ee.Reducer.max(),
'geometry': img.geometry(),
'scale': scale,
'maxPixels': 1e9
})
return max_value
# get lowest value
def minValue(img, scale=30):
min_value = img.reduceRegion(**{
'reducer': ee.Reducer.min(),
'geometry': img.geometry(),
'scale': scale,
'maxPixels': 1e9
})
return min_value
# get mean value
def meanValue(img, scale=30):
mean_value = img.reduceRegion(**{
'reducer': ee.Reducer.mean(),
'geometry': img.geometry(),
'scale': scale,
'maxPixels': 1e9
})
return mean_value
# get standard deviation
def stdValue(img, scale=30):
std_value = img.reduceRegion(**{
'reducer': ee.Reducer.stdDev(),
'geometry': img.geometry(),
'scale': scale,
'maxPixels': 1e9
})
return std_value
dataset = ee.Image('USGS/NED')
dem = dataset.select('elevation')
# dem = ee.Image('srtm90_v4')
vis_params = {'min': 0, 'max': 3000}
Map.addLayer(dem, vis_params, 'NED', False)
roi = ee.Geometry.Polygon(
[[[-120.18204899532924, 38.53481618819663],
[-120.18204899532924, 36.54889033300136],
[-116.75431462032924, 36.54889033300136],
[-116.75431462032924, 38.53481618819663]]])
image = dem.clip(roi)
Map.centerObject(image, 9)
Map.addLayer(image, vis_params, 'DEM')
scale = image.projection().nominalScale()
print("Resolution: ", scale.getInfo())
scale = 30
print("Minimum value: ", minValue(image, scale).get('elevation').getInfo())
print("Maximum value: ", maxValue(image, scale).get('elevation').getInfo())
print("Average value: ", meanValue(image, scale).get('elevation').getInfo())
print("Standard deviation: ", stdValue(image, scale).get('elevation').getInfo())
# Display the map.
Map
| [
"giswqs@gmail.com"
] | giswqs@gmail.com |
6237c8ef3080a951cd2332c5cad12316c75816fd | a97a0a9f2b3cdd47e0637999312cdb2b1c89a81c | /DiplomaProject/urls.py | de1dec0f2bc900c3bbb35a2ff2720fa6fa7d183b | [] | no_license | dimatodorov/researchtranslator | cb65a33206471710a85fd9b698b20b5502045703 | 19f534a45e6c55727a424f39ec8de4980d2f6e41 | refs/heads/main | 2023-06-14T15:48:02.374014 | 2021-07-06T07:53:54 | 2021-07-06T07:53:54 | 383,379,744 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 921 | py | """DiplomaProject URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path, include
urlpatterns = [
path('grappelli/', include('grappelli.urls')), # grappelli URLS
path('admin/', admin.site.urls), # admin site
path('', include('main.urls')),
#path('admin/', admin.site.urls),
]
| [
"dmitrijtodorov99@gmail.com"
] | dmitrijtodorov99@gmail.com |
88ff13ad78ec68d9136709107884863ba6d3744a | ca33751ab2f06c0aa0713fb31bf26fc27b11ac12 | /casestudy/thumb_generator.py | 8d8895897b5078d0b58a4fa3d45eef2f7ba1b1c6 | [] | no_license | Bert-Proesmans/NDA-WPO-1718 | 0b801fce6342869c44f7fca7100fbf906741a052 | 7e3dcb3eb8f949664c046c7bc9adc7e23ef96da8 | refs/heads/master | 2021-08-30T12:09:10.437698 | 2017-12-15T16:47:24 | 2017-12-15T16:47:24 | 113,320,809 | 0 | 0 | null | 2017-12-06T13:35:47 | 2017-12-06T13:35:46 | null | UTF-8 | Python | false | false | 358 | py | from PIL import Image
import glob, os
"""
Create thumbnail images in the current working directory.
Needs PILLOW to be installed!
(Works on Python3.X)
"""
size = 700, 700
for infile in glob.glob("*.jpg", recursive=False):
file, ext = os.path.splitext(infile)
im = Image.open(infile)
im.thumbnail(size)
im.save(file + ".thumb.jpg", "JPEG")
| [
"bproesmans@hotmail.com"
] | bproesmans@hotmail.com |
98514ddd3f18865987b28d44972d3f79f20cc8cd | fc81f937a325ff27c4d466ef7ea708d16c59376e | /brain_games/engine.py | 3ad225b5df73d6a97730a3a56d895e9b58994c16 | [] | no_license | Persimmonboy/python-project-lvl1 | e34b8fd9d93ff0d209439ec2436e3eddca232f14 | e6d9b6956f5f683513dea6707da2122702e0a97b | refs/heads/main | 2023-03-17T21:35:41.480824 | 2022-07-09T13:37:37 | 2022-07-09T13:37:37 | 233,594,368 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 788 | py | import prompt
def welcome():
print("Welcome to the Brain Games!")
def get_user_name():
name = prompt.string('May I have your name? ')
print("Hello, {}!".format(name))
return name
def run_engine(game_name):
i = 0
welcome()
name = get_user_name()
print(game_name.TASK)
while i < 3:
answer, value = game_name.game_script()
print("Question: {}".format(value))
user_answer = prompt.string('Your answer: ')
if answer == user_answer:
print("Correct!")
i += 1
else:
print(f"'{user_answer}' is wrong answer ;(."
f"Correct answer was '{answer}'.\n"
f"Let's try again, {name}!")
return
print("Congratulations, {}!".format(name))
| [
"shakhbazianartem@gmail.com"
] | shakhbazianartem@gmail.com |
9242782550ab6ddf1a26238b272e633e1ed1d3c8 | c342c8b9b2437d6474b9ae7da154ba47c6fc447c | /src/data/memory_store.py | 81d6cb406f3ba13f5011c2669584a64d0cdc0b4a | [] | no_license | nezaj/menu-api | 0d5118f3a1392f85e51700b5e8ac234bac605518 | bcf759b91893bf72821323c41f963923d9184e68 | refs/heads/master | 2021-01-10T07:09:15.664561 | 2015-11-16T21:28:45 | 2015-11-16T21:28:45 | 44,832,757 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,572 | py | """
Store implementation using in-memory data
"""
import json
import os
from .store_interface import StoreInterface
class MemoryStore(object):
__implements__ = (StoreInterface, )
def __init__(self, data_dir):
self.data_dir = data_dir
self.data = self._load_data(data_dir)
def _load_data(self, data_dir):
"""
Loads data from directory defined in settings. We expect there can be
multiple collections of data and that each collection lives in its
own subdirectory. As a result, we go through each directory and load
it's data into it's own key.
"""
data = {}
for d in os.listdir(data_dir):
subd = os.path.join(data_dir, d)
if os.path.isdir(subd):
data[d] = self._load_json_files(subd)
return data
def _load_json_files(self, data_dir):
"""
Return a dictionary representing a collection of json from the given
data directory.
We iterate through each json file and load it's data. We then key
the data in each file by the id defined in the file itself.
"""
collection = {}
for item in os.listdir(data_dir):
df = os.path.join(data_dir, item)
if df.endswith(".json"):
jd = self._load_json_file(df)
d_id, d_meta = self._process_json(jd)
collection[d_id] = d_meta
return collection
@staticmethod
def _load_json_file(f):
with open(f) as jf:
jd = json.load(jf)
return jd
@staticmethod
def _process_json(jd):
jd_id = jd["id"]
return jd_id, jd
def create_item(self, collection_id, params):
c = self.data[collection_id]
item_id, item = self._process_json(params)
c[item_id] = item
return item
def delete_item(self, collection_id, item_id):
collection = self.get_collection(collection_id)
item = self.get_item(collection_id, item_id)
if collection and item:
del collection[item_id]
return item
def get_collection(self, collection_id):
return self.data.get(collection_id)
def get_item(self, collection_id, item_id):
collection = self.get_collection(collection_id)
if collection:
return collection.get(item_id)
def update_item(self, collection_id, item_id, params):
item = self.get_item(collection_id, item_id)
if item:
item.update(params)
return item
| [
"joeaverbukh@gmail.com"
] | joeaverbukh@gmail.com |
7ebec6c0a7924a9438dc5a473cc822f219125df8 | 402ed5374ab189c8599b56864c5ce066f34b26c6 | /tests/test_pdf_normal.py | e1fa17bd053bb3771266064aae86ee311b5c241c | [
"BSD-3-Clause"
] | permissive | kailiu77/zfit | db354e9c3eb4a41274af5363834fe231823c6d66 | 8bddb0ed3a0d76fde0aa2cdbf74434b0ee0ae8bb | refs/heads/master | 2020-10-01T23:49:55.751825 | 2019-12-06T15:48:47 | 2019-12-06T15:48:47 | 227,650,723 | 1 | 0 | BSD-3-Clause | 2019-12-12T16:33:54 | 2019-12-12T16:33:53 | null | UTF-8 | Python | false | false | 2,899 | py | # Copyright (c) 2019 zfit
import numpy as np
import pytest
import tensorflow as tf
import zfit
from zfit import Parameter
from zfit.models.dist_tfp import Gauss
from zfit.core.testing import setup_function, teardown_function, tester
mu1_true = 1.
mu2_true = 2.
mu3_true = 0.6
sigma1_true = 1.4
sigma2_true = 2.3
sigma3_true = 1.8
test_values = np.random.uniform(low=-3, high=5, size=100)
norm_range1 = (-4., 2.)
obs1 = 'obs1'
limits1 = zfit.Space(obs=obs1, limits=(-0.3, 1.5))
def create_gauss():
mu1 = Parameter("mu1a", mu1_true)
mu2 = Parameter("mu2a", mu2_true)
mu3 = Parameter("mu3a", mu3_true)
sigma1 = Parameter("sigma1a", sigma1_true)
sigma2 = Parameter("sigma2a", sigma2_true)
sigma3 = Parameter("sigma3a", sigma3_true)
gauss1 = Gauss(mu=mu1, sigma=sigma1, obs=obs1, name="gauss1a")
normal1 = Gauss(mu=mu1, sigma=sigma1, obs=obs1, name="normal1a")
gauss2 = Gauss(mu=mu2, sigma=sigma2, obs=obs1, name="gauss2a")
normal2 = Gauss(mu=mu2, sigma=sigma2, obs=obs1, name="normal2a")
gauss3 = Gauss(mu=mu3, sigma=sigma3, obs=obs1, name="gauss3a")
normal3 = Gauss(mu=mu3, sigma=sigma3, obs=obs1, name="normal3a")
return gauss1, gauss2, gauss3, normal1, normal2, normal3
# gauss1, gauss2, gauss3, normal1, normal2, normal3 = create_gauss()
def test_gauss1():
gauss1, gauss2, gauss3, normal1, normal2, normal3 = create_gauss()
probs1 = gauss1.pdf(x=test_values, norm_range=norm_range1)
probs1_tfp = normal1.pdf(x=test_values, norm_range=norm_range1)
probs1 = zfit.run(probs1)
probs1_tfp = zfit.run(probs1_tfp)
np.testing.assert_allclose(probs1, probs1_tfp, rtol=1e-2)
probs1_unnorm = gauss1.pdf(x=test_values, norm_range=False)
probs1_tfp_unnorm = normal1.pdf(x=test_values, norm_range=False)
probs1_unnorm = zfit.run(probs1_unnorm)
probs1_tfp_unnorm = zfit.run(probs1_tfp_unnorm)
assert not np.allclose(probs1_tfp, probs1_tfp_unnorm, rtol=1e-2)
assert not np.allclose(probs1, probs1_unnorm, rtol=1e-2)
# np.testing.assert_allclose(probs1_unnorm, probs1_tfp_unnorm, rtol=1e-2)
def test_truncated_gauss():
high = 2.
low = -0.5
truncated_gauss = zfit.pdf.TruncatedGauss(mu=1, sigma=2, low=low, high=high, obs=limits1)
gauss = zfit.pdf.Gauss(mu=1., sigma=2, obs=limits1)
probs_truncated = truncated_gauss.pdf(test_values)
probs_gauss = gauss.pdf(test_values)
probs_truncated_np, probs_gauss_np = zfit.run([probs_truncated, probs_gauss])
bool_index_inside = np.logical_and(low < test_values, test_values < high)
inside_probs_truncated = probs_truncated_np[bool_index_inside]
outside_probs_truncated = probs_truncated_np[np.logical_not(bool_index_inside)]
inside_probs_gauss = probs_gauss_np[bool_index_inside]
assert inside_probs_gauss == pytest.approx(inside_probs_truncated, rel=1e-3)
assert all(0 == outside_probs_truncated)
| [
"mayou36@jonas.eschle.com"
] | mayou36@jonas.eschle.com |
5b10c950f8fcf1e96b9c084789c5eda625ace98c | af86b0e6af32771176b406e30dbcfd951cb64b26 | /monster1/models.py | cbfec7a0c1a7ab74bc622647d37f7a3e63ba8bc4 | [] | no_license | HALOGENMAN/monster | ca779acc3252a79a3b8a6f4cd671efebd2a742a0 | 31e39f58d0f7d9257e96f20f8d30e411390bac38 | refs/heads/master | 2022-12-18T00:55:52.198817 | 2019-12-04T16:50:18 | 2019-12-04T16:50:18 | 225,797,994 | 0 | 0 | null | 2022-12-08T06:16:47 | 2019-12-04T06:42:34 | Python | UTF-8 | Python | false | false | 222 | py | from django.db import models
# Create your models here.
class Data(models.Model):
name = models.CharField(max_length=1100)
email = models.EmailField(max_length=100)
def __str__(self):
return self.name | [
"Shayak.malakar.159@gmail.com"
] | Shayak.malakar.159@gmail.com |
5e825524eee64cc9ad540794c888975ee345791c | 4bd5f1f5d364ca59ca78522c797c959d356ad9a6 | /tutorial/items.py | 7df4b3707d282eaf58f0f4d602098a519bdf0bdc | [] | no_license | zhangzhang18/scrapy | 1af67be8313536016400edb72910c553e37798f0 | cc3e3ec126cebde04941ba440014d4faa92383ca | refs/heads/master | 2021-01-17T08:36:06.738176 | 2017-03-05T02:31:53 | 2017-03-05T02:31:53 | 83,939,216 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 775 | py | # -*- coding: utf-8 -*-
# items.py：用来定义需要保存的变量，其中的变量用Field来定义，有点像python的字典
import scrapy
from scrapy.item import Item, Field
class TutorialItem(Item):
# define the fields for your item here like:
# name = scrapy.Field()
parent_title = Field()
parent_url = Field()
second_title = Field()
second_url = Field()
path = Field()
link_title = Field()
link_url = Field()
head = Field()
content = Field()
pass
class W3schoolItem(Item):
title = Field()
link = Field()
desc = Field()
class Website(Item):
headTitle = Field()
description = Field()
url = Field()
class DmozItem(Item):
title = Field()
link = Field()
desc = Field()
| [
"1326222521@qq.com"
] | 1326222521@qq.com |
3e70f5bce473ccd4c866c43a7f594f03af071dca | f569978afb27e72bf6a88438aa622b8c50cbc61b | /douyin_open/EnterprisePersonaPersonaCreate/api/__init__.py | d436a85b96fd99e2b5e5d7a6b654b4348bb48850 | [] | no_license | strangebank/swagger-petstore-perl | 4834409d6225b8a09b8195128d74a9b10ef1484a | 49dfc229e2e897cdb15cbf969121713162154f28 | refs/heads/master | 2023-01-05T10:21:33.518937 | 2020-11-05T04:33:16 | 2020-11-05T04:33:16 | 310,189,316 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 208 | py | from __future__ import absolute_import
# flake8: noqa
# import apis into api package
from douyin_open.EnterprisePersonaPersonaCreate.api.enterprise_im_persona_create_api import EnterpriseImPersonaCreateApi
| [
"strangebank@gmail.com"
] | strangebank@gmail.com |
3be1a2bcc32f48f75753470e76bcfb598ff908c5 | 7179c77f220e5adf1354292c1d3069e0e37bd10f | /Rush00/moviemon/views/load.py | 1a0aedac92ea9e0a1b7a4fa0e255005123d2ce39 | [] | no_license | MishinK/Django_pool | 09d7244e5ba397dba2d3797b0c3fc6b08862d2dd | 484271c63c299c53bf59dacc2412927e818b8096 | refs/heads/main | 2023-09-03T18:14:01.176740 | 2021-11-11T06:23:45 | 2021-11-11T06:23:45 | 426,892,862 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,767 | py | from django.shortcuts import redirect, render
from django.views.generic import TemplateView
from moviemon.utils.game import load_slot, load_slot_info
optionState = {
'slot': 0,
'isLoad': False,
}
class Load(TemplateView):
template_name = "load.html"
context = {
"btnA": "Load"
}
def get(self, request):
key = request.GET.get('key', None)
if key and key == 'up':
optionState['isLoad'] = False
optionState['slot'] -= 1 if optionState['slot'] > 0 else 0
elif key and key == 'down':
optionState['isLoad'] = False
optionState['slot'] += 1 if optionState['slot'] < 2 else 0
if key and key == 'a':
if optionState['isLoad'] == True:
optionState['isLoad'] = False
return redirect('worldmap')
elif load_slot(('A', 'B', 'C')[optionState['slot']]):
optionState['isLoad'] = True
elif key and key == 'b':
return redirect('title')
slots = load_slot_info()
score = 'Free' if slots.get('A', None) is None else slots.get('A').get('score', 'Free')
self.context['A'] = "Slot 🅰 : {}".format(score)
score = 'Free' if slots.get('B', None) is None else slots.get('B').get('score', 'Free')
self.context['B'] = "Slot 🅱 : {}".format(score)
score = 'Free' if slots.get('C', None) is None else slots.get('C').get('score', 'Free')
self.context['C'] = "Slot 🅲 : {}".format(score)
self.context['active'] = optionState['slot']
self.context['btnA'] = 'Load'
if optionState['isLoad'] == True:
self.context['btnA'] = 'Start game'
return render(request, self.template_name, self.context)
| [
"mka456@yandex.ru"
] | mka456@yandex.ru |
7b71ab524da218d37807a9e97239462be3bd6ee4 | ad02585a6698b7219ff71418fd23412d91941373 | /predict_naive/extract_gallery_features.py | 60580e1e68cb2b17975b3b5d451b686ea2954cb8 | [] | no_license | bmsknight/DensenetReID | b6d3e10f462a11521c28b59c6d07d7c01b99cc17 | b3d4bd1053a2ab5175245b6e581129d21dc4e1e1 | refs/heads/master | 2020-03-30T15:36:53.259940 | 2018-10-03T06:14:37 | 2018-10-03T06:14:37 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,380 | py | import os
import pickle
from keras import Model
from keras.preprocessing import image
from keras.models import load_model
from keras.applications.densenet import preprocess_input
import numpy as np
from keras_preprocessing.image import ImageDataGenerator
trained_model = load_model('../market_trained_model_epoch5_resnet50.h5')
# trained_model.summary()
feature_extraction_model = Model(trained_model.inputs, trained_model.get_layer("avg_pool").output)
# feature_extraction_model.summary()
test_path = '/home/niruhan/PycharmProjects/DensenetReID/market_for_keras/test/bounding_box_test/'
test_names = os.listdir(test_path)
np.savetxt('test_names_epoch5_resnet50.txt', test_names, fmt='%s')
reid_feature_list = np.empty([19732, 2048])
print 'hi'
for name_index in range(len(test_names)):
if name_index % 500 == 0:
print name_index
img_path = test_path + test_names[name_index]
img = image.load_img(img_path, target_size=(224, 224))
img_data = image.img_to_array(img)
img_data = np.expand_dims(img_data, axis=0)
img_data = preprocess_input(img_data)
reid_feature_list[name_index] = feature_extraction_model.predict(img_data)
np.savetxt('gallery_feature_list_epoch5_resnet50.txt', reid_feature_list, fmt='%f')
# for feature in reid_feature_list:
# dist = np.linalg.norm(feature - reid_feature_list[3])
# print dist
print 'hi'
| [
"niruhanv@gmail.com"
] | niruhanv@gmail.com |
58506d8532bd19ab89a45b9d8de2155539bfb648 | a52029409372b6a31fd9ccb37ecfd18749db1c66 | /HW04/hw04.py | 6f30a0f80af67375d42899c038c9d635cab77a6b | [] | no_license | greenlodka/HW_Python | 6d169cedb9119ec1de6e9a04a846025dffa53a8c | 982f41c61ca80cf780c7aa6b4b4e312c0be02bc9 | refs/heads/master | 2023-06-05T04:59:13.766105 | 2021-06-26T21:25:35 | 2021-06-26T21:25:35 | 299,719,587 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 264 | py | while True:
s = input("Введите слово: ")
if not s:
break
s1 = s.lower()
s2 = s1.strip("'!«»()-[]{};:'\\,= <>./?@#$%^&*_~'")
for i, letter in enumerate(s2):
if i < (len(s2) // 2):
print(letter)
| [
"green_submarine@mail.ru"
] | green_submarine@mail.ru |
75405ee23581b787a1027732cbd795beaff076ae | d184f941dfbbdc479fc7747bab5f7b2e625665a2 | /paginaPersonal/views.py | 59d99b4317cc57de7a84992a69e5391aeb7e9390 | [] | no_license | DanielRuiz14/mipagina | 67d62cc57636d46eaf7511c8783a6ab5102baaba | 8f021373c9e7db6f63a276664872f84b73da519d | refs/heads/master | 2023-02-15T23:22:45.354432 | 2021-01-15T13:50:54 | 2021-01-15T13:50:54 | 329,897,089 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 183 | py | from django.shortcuts import render
from django.http import HttpResponse
# Create your views here.
def inicio(request):
return HttpResponse("Prueba de funcionamiento. Hola Fran") | [
"0619466123@uma.es"
] | 0619466123@uma.es |
d44f23bdc3a2ebd7b826cebb9d784a04528b90e6 | 5af277b5819d74e61374d1d78c303ac93c831cf5 | /tabnet/experiment_covertype.py | c00ea76b7c9058be7df642fae0d69184a435f921 | [
"Apache-2.0"
] | permissive | Ayoob7/google-research | a2d215afb31513bd59bc989e09f54667fe45704e | 727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7 | refs/heads/master | 2022-11-11T03:10:53.216693 | 2020-06-26T17:13:45 | 2020-06-26T17:13:45 | 275,205,856 | 2 | 0 | Apache-2.0 | 2020-06-26T16:58:19 | 2020-06-26T16:58:18 | null | UTF-8 | Python | false | false | 6,699 | py | # coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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.
"""Experiment to train and evaluate the TabNet model on Forest Covertype."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from absl import app
import data_helper_covertype
import numpy as np
import tabnet_model
import tensorflow as tf
# Run Tensorflow on GPU 0
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
# Training parameters
TRAIN_FILE = "data/train_covertype.csv"
VAL_FILE = "data/val_covertype.csv"
TEST_FILE = "data/test_covertype.csv"
MAX_STEPS = 1000000
DISPLAY_STEP = 5000
VAL_STEP = 10000
SAVE_STEP = 40000
INIT_LEARNING_RATE = 0.02
DECAY_EVERY = 500
DECAY_RATE = 0.95
BATCH_SIZE = 16384
SPARSITY_LOSS_WEIGHT = 0.0001
GRADIENT_THRESH = 2000.0
SEED = 1
def main(unused_argv):
# Fix random seeds
tf.set_random_seed(SEED)
np.random.seed(SEED)
# Define the TabNet model
tabnet_forest_covertype = tabnet_model.TabNet(
columns=data_helper_covertype.get_columns(),
num_features=data_helper_covertype.NUM_FEATURES,
feature_dim=128,
output_dim=64,
num_decision_steps=6,
relaxation_factor=1.5,
batch_momentum=0.7,
virtual_batch_size=512,
num_classes=data_helper_covertype.NUM_CLASSES)
column_names = sorted(data_helper_covertype.FEATURE_COLUMNS)
print(
"Ordered column names, corresponding to the indexing in Tensorboard visualization"
)
for fi in range(len(column_names)):
print(str(fi) + " : " + column_names[fi])
# Input sampling
train_batch = data_helper_covertype.input_fn(
TRAIN_FILE, num_epochs=100000, shuffle=True, batch_size=BATCH_SIZE)
val_batch = data_helper_covertype.input_fn(
VAL_FILE,
num_epochs=10000,
shuffle=False,
batch_size=data_helper_covertype.N_VAL_SAMPLES)
test_batch = data_helper_covertype.input_fn(
TEST_FILE,
num_epochs=10000,
shuffle=False,
batch_size=data_helper_covertype.N_TEST_SAMPLES)
train_iter = train_batch.make_initializable_iterator()
val_iter = val_batch.make_initializable_iterator()
test_iter = test_batch.make_initializable_iterator()
feature_train_batch, label_train_batch = train_iter.get_next()
feature_val_batch, label_val_batch = val_iter.get_next()
feature_test_batch, label_test_batch = test_iter.get_next()
# Define the model and losses
encoded_train_batch, total_entropy = tabnet_forest_covertype.encoder(
feature_train_batch, reuse=False, is_training=True)
logits_orig_batch, _ = tabnet_forest_covertype.classify(
encoded_train_batch, reuse=False)
softmax_orig_key_op = tf.reduce_mean(
tf.nn.sparse_softmax_cross_entropy_with_logits(
logits=logits_orig_batch, labels=label_train_batch))
train_loss_op = softmax_orig_key_op + SPARSITY_LOSS_WEIGHT * total_entropy
tf.summary.scalar("Total loss", train_loss_op)
# Optimization step
global_step = tf.train.get_or_create_global_step()
learning_rate = tf.train.exponential_decay(
INIT_LEARNING_RATE,
global_step=global_step,
decay_steps=DECAY_EVERY,
decay_rate=DECAY_RATE)
optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
with tf.control_dependencies(update_ops):
gvs = optimizer.compute_gradients(train_loss_op)
capped_gvs = [(tf.clip_by_value(grad, -GRADIENT_THRESH,
GRADIENT_THRESH), var) for grad, var in gvs]
train_op = optimizer.apply_gradients(capped_gvs, global_step=global_step)
# Model evaluation
# Validation performance
encoded_val_batch, _ = tabnet_forest_covertype.encoder(
feature_val_batch, reuse=True, is_training=False)
_, prediction_val = tabnet_forest_covertype.classify(
encoded_val_batch, reuse=True)
predicted_labels = tf.cast(tf.argmax(prediction_val, 1), dtype=tf.int32)
val_eq_op = tf.equal(predicted_labels, label_val_batch)
val_acc_op = tf.reduce_mean(tf.cast(val_eq_op, dtype=tf.float32))
tf.summary.scalar("Val accuracy", val_acc_op)
# Test performance
encoded_test_batch, _ = tabnet_forest_covertype.encoder(
feature_test_batch, reuse=True, is_training=False)
_, prediction_test = tabnet_forest_covertype.classify(
encoded_test_batch, reuse=True)
predicted_labels = tf.cast(tf.argmax(prediction_test, 1), dtype=tf.int32)
test_eq_op = tf.equal(predicted_labels, label_test_batch)
test_acc_op = tf.reduce_mean(tf.cast(test_eq_op, dtype=tf.float32))
tf.summary.scalar("Test accuracy", test_acc_op)
# Training setup
model_name = "tabnet_forest_covertype_model"
init = tf.initialize_all_variables()
init_local = tf.local_variables_initializer()
init_table = tf.tables_initializer(name="Initialize_all_tables")
saver = tf.train.Saver()
summaries = tf.summary.merge_all()
with tf.Session() as sess:
summary_writer = tf.summary.FileWriter("./tflog/" + model_name, sess.graph)
sess.run(init)
sess.run(init_local)
sess.run(init_table)
sess.run(train_iter.initializer)
sess.run(val_iter.initializer)
sess.run(test_iter.initializer)
for step in range(1, MAX_STEPS + 1):
if step % DISPLAY_STEP == 0:
_, train_loss, merged_summary = sess.run(
[train_op, train_loss_op, summaries])
summary_writer.add_summary(merged_summary, step)
print("Step " + str(step) + " , Training Loss = " +
"{:.4f}".format(train_loss))
else:
_ = sess.run(train_op)
if step % VAL_STEP == 0:
feed_arr = [
vars()["summaries"],
vars()["val_acc_op"],
vars()["test_acc_op"]
]
val_arr = sess.run(feed_arr)
merged_summary = val_arr[0]
val_acc = val_arr[1]
print("Step " + str(step) + " , Val Accuracy = " +
"{:.4f}".format(val_acc))
summary_writer.add_summary(merged_summary, step)
if step % SAVE_STEP == 0:
saver.save(sess, "./checkpoints/" + model_name + ".ckpt")
if __name__ == "__main__":
app.run(main)
| [
"copybara-worker@google.com"
] | copybara-worker@google.com |
57d543bd339a845f929b5dfb54476a2082fe169e | ad9215878796db25f63f93f11608b5748726eafc | /shop.py | 202b240b8f52aeb1642369f09fba11f621fa6329 | [] | no_license | DmitriyZaika88/shop-automation-testing | 9ac84374451f48e6439aefc61573db6ad9b4bad1 | 6c4971465e32476bef5c064619a6557a8652e460 | refs/heads/master | 2023-07-14T00:54:28.340327 | 2021-08-23T10:05:27 | 2021-08-23T10:05:27 | 399,054,394 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,976 | py | import time
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium import webdriver
driver = webdriver.Chrome()
driver.maximize_window()
# Product page representation
#1
driver.get("http://practice.automationtesting.in/")
time.sleep(0.5)
#2
my_account_menu = driver.find_element_by_partial_link_text('My Account')
my_account_menu.click()
time.sleep(0.5)
login_email = driver.find_element_by_id('username')
login_email.send_keys('dmitriydmz1997@gmail.com')
time.sleep(0.5)
login_password = driver.find_element_by_id('password')
login_password.send_keys('Dmitriy1Dmitriy2')
time.sleep(0.5)
login_btn = driver.find_element_by_css_selector("[value='Login']")
login_btn.click()
time.sleep(0.5)
#3
shopTab = driver.find_element_by_id('menu-item-40')
shopTab.click()
time.sleep(0.5)
#4
driver.execute_script("window.scrollBy(0, 300);")
time.sleep(1)
book_HTML5Forms_link = driver.find_element_by_partial_link_text('HTML5 Forms')
book_HTML5Forms_link.click()
time.sleep(1)
#5
book_name_header = driver.find_element_by_class_name('entry-title')
HTML_5_Forms_text = book_name_header.text
assert HTML_5_Forms_text == "HTML5 Forms" # Проверка присутствия на странице элемента "HTML5 Forms"
print('Элемент', HTML_5_Forms_text, 'найден')
# Number of goods in category
#1
driver.get("http://practice.automationtesting.in/")
time.sleep(0.5)
#2
my_account_menu = driver.find_element_by_partial_link_text('My Account')
my_account_menu.click()
time.sleep(0.5)
login_email = driver.find_element_by_id('username')
login_email.send_keys('dmitriydmz1997@gmail.com')
time.sleep(0.5)
login_password = driver.find_element_by_id('password')
login_password.send_keys('Dmitriy1Dmitriy2')
time.sleep(0.5)
login_btn = driver.find_element_by_css_selector("[value='Login']")
login_btn.click()
time.sleep(0.5)
#3
shopTab = driver.find_element_by_id('menu-item-40')
shopTab.click()
time.sleep(0.5)
#4
driver.get("http://practice.automationtesting.in/shop/")
time.sleep(0.5)
category_html5 = driver.find_element_by_css_selector('.cat-item-19 > a')
category_html5.click()
time.sleep(0.5)
#5
number_of_goods = driver.find_element_by_class_name('type-product')
number_of_goods = number_of_goods.get_attribute("class='type-product'")
if number_of_goods < 3:
print("Меньше")
if number_of_goods > 3:
print("Больше")
else:
print("Равно")
# Sorting of goods
#1
driver.get("http://practice.automationtesting.in/")
time.sleep(0.5)
#2
my_account_menu = driver.find_element_by_partial_link_text('My Account')
my_account_menu.click()
time.sleep(0.5)
login_email = driver.find_element_by_id('username')
login_email.send_keys('dmitriydmz1997@gmail.com')
time.sleep(0.5)
login_password = driver.find_element_by_id('password')
login_password.send_keys('Dmitriy1Dmitriy2')
time.sleep(0.5)
login_btn = driver.find_element_by_css_selector("[value='Login']")
login_btn.click()
time.sleep(0.5)
#3
shopTab = driver.find_element_by_id('menu-item-40')
shopTab.click()
time.sleep(0.5)
#4
default_sorting_check = driver.find_element_by_css_selector('[value="menu_order"]')
default_sorting_check = default_sorting_check.get_attribute('selected')
if default_sorting_check is not None:
print('Выбрана сортировка по умолчанию')
else:
print('Сортировка по умолчанию не выбрана')
time.sleep(0.5)
#5
from selenium.webdriver.support.select import Select
sorting = driver.find_element_by_class_name("orderby")
select = Select(sorting)
select.select_by_value("price")
time.sleep(0.5)
#6
default_sorting_check = driver.find_element_by_css_selector('[value="menu_order"]')
#7
default_sorting_check = driver.find_element_by_css_selector('[value="menu_order"]')
default_sorting_check = default_sorting_check.get_attribute('selected')
if default_sorting_check is not None:
print('Выбрана сортировка по умолчанию')
else:
print('Сортировка по умолчанию не выбрана')
time.sleep(0.5)
# Visibility and sale of goods
#1
driver.get("http://practice.automationtesting.in/")
time.sleep(0.5)
#2
my_account_menu = driver.find_element_by_partial_link_text('My Account')
my_account_menu.click()
time.sleep(0.5)
login_email = driver.find_element_by_id('username')
login_email.send_keys('dmitriydmz1997@gmail.com')
time.sleep(0.5)
login_password = driver.find_element_by_id('password')
login_password.send_keys('Dmitriy1Dmitriy2')
time.sleep(0.5)
login_btn = driver.find_element_by_css_selector("[value='Login']")
login_btn.click()
time.sleep(0.5)
#3
shopTab = driver.find_element_by_id('menu-item-40')
shopTab.click()
time.sleep(0.5)
#4
book_AndroidQSG_link = driver.find_element_by_partial_link_text('Android Quick Start Guide')
book_AndroidQSG_link.click()
time.sleep(1)
#5 Из-за символа не получается провести проверку. При добавлении переменной с символом тест падает
old_price_check = driver.find_element_by_css_selector('.price > del > span')
old_price_text = old_price_check.text
#old_price_symbol = driver.find_element_by_class_name('woocommerce-Price-currencySymbol')
assert old_price_text == "600.00" # Проверка присутствия на странице элемента "Logout"
print('Элемент', old_price_text, 'найден')
new_price_check = driver.find_element_by_css_selector('.price > ins > span:')
new_price_text = new_price_check.text
#old_price_symbol = driver.find_element_by_class_name('woocommerce-Price-currencySymbol')
assert new_price_text == "450.00" # Проверка присутствия на странице элемента "Logout"
print('Элемент', new_price_text, 'найден')
#6
closeBtn = WebDriverWait(driver,5 ).until(
EC.invisibility_of_element_located((By.ID, "fullResImage")))
img = driver.find_element_by_class_name('wp-post-image')
img.click()
#7
closeBtn = WebDriverWait(driver,5 ).until(
EC.invisibility_of_element_located((By.ID, "fullResImage")))
img = driver.find_element_by_class_name('wp-post-image')
img.click()
#8 Здесь баг: is not clickable at point (649, 457). Курсор не попадает в область крестика
closeBtn = WebDriverWait(driver,5 ).until(
EC.element_to_be_clickable((By.CLASS_NAME, "pp_close")))
cross_btn = driver.find_element_by_class_name('pp_close')
cross_btn.click()
# Basket price check
#1
driver.get("http://practice.automationtesting.in/")
time.sleep(0.5)
#2
shopTab = driver.find_element_by_id('menu-item-40')
shopTab.click()
time.sleep(0.5)
#3
basket_price_btn = driver.find_element_by_css_selector('[data-product_id="182"]')
basket_price_btn.click()
time.sleep(2)
#4
cart_item_num = driver.find_element_by_css_selector('.cartcontents')
cart_item_num_text = cart_item_num.text
assert cart_item_num_text == "1 Item" # Проверка присутствия на странице элемента "1 item"
print('Элемент', cart_item_num_text, 'найден')
cart_item_price = driver.find_element_by_class_name('amount')
cart_item_price_text = cart_item_price.text
assert cart_item_price_text == "₹180.00" # Проверка присутствия на странице элемента "₹180.00"
print('Элемент', cart_item_price_text, 'найден')
#5
cart_link = driver.find_element_by_class_name('wpmenucart-contents')
cart_link.click()
#6
subtotal_text = WebDriverWait(driver,5 ).until(
EC.text_to_be_present_in_element_value((By.CSS_SELECTOR, "td.Subtotal > .amount"), "180.00"))
#7
total_text = WebDriverWait(driver,5 ).until(
EC.text_to_be_present_in_element_value((By.CSS_SELECTOR, "td.Total > strong > span.amount"), "189.00"))
# Basket
#1
driver.get("http://practice.automationtesting.in/")
time.sleep(0.5)
#2
shopTab = driver.find_element_by_id('menu-item-40')
shopTab.click()
time.sleep(0.5)
#3
driver.execute_script("window.scrollBy(0, 300);")
time.sleep(1)
add_to_cart_btn_1 = driver.find_element_by_css_selector('[data-product_id="182"]')
add_to_cart_btn_1.click()
time.sleep(1)
add_to_cart_btn_2 = driver.find_element_by_css_selector('[data-product_id="180"]')
add_to_cart_btn_2.click()
time.sleep(1)
#4
cart_link = driver.find_element_by_class_name('wpmenucart-contents')
cart_link.click()
time.sleep(1)
#5
remove_1st_book = driver.find_element_by_css_selector('tbody > tr.cart_item > .product-remove > a')
remove_1st_book.click()
time.sleep(3)
#6
undo_remove_link = driver.find_element_by_partial_link_text('Undo?')
undo_remove_link.click()
time.sleep(2)
#7
quantity_of_goods = driver.find_element_by_css_selector('.quantity > input').clear().setAttribute("value", "3");
#8
upd_basket = driver.find_element_by_css_selector('.coupon > .button')
upd_basket.click()
#9
#10
#11
| [
"Dmitriydmz1997@gmail.com"
] | Dmitriydmz1997@gmail.com |
0e661a1faffd285eca4c6596e64d64cb048d3a80 | d6c8eca6a554a5e5456f59b01710ec383289c997 | /restroom_challenge.py | f8c0269c51010047fc7ca49a0289b2f61b319156 | [] | no_license | ospahiu/Code_golfs | 1b6e9e7fb8bd0581c8f664feeeaaa86a2ddd11b5 | eb95903f0c94fa6a665ad443b57822139d8a65b2 | refs/heads/master | 2021-01-11T00:27:43.209369 | 2016-10-10T22:03:35 | 2016-10-10T22:03:35 | 70,532,457 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,200 | py | # Answer to -> http://codegolf.stackexchange.com/questions/89241/be-respectful-in-the-restroom#89241
import itertools
# Non-golf
def find_furthest_stall(input_string):
input_string = input_string
a = [not bool(int(i)) for i in input_string]
y = {i : item for i, item in enumerate(a)}
d = {i : abs(i[0]-i[1]) for i in list(itertools.combinations(y.keys(), 2))}
largest = [0,0]
for key, value in d.iteritems():
if value >= largest[1] and (y[key[0]] or y[key[1]]):
largest[0] = key[0] if y[key[0]] else key[1]
largest[1] = value
stall_pipe = '|' + '|'.join(['-' if int(i) else ' ' for i in input_string]) + '|'
print('Input:\n{} OR {}'.format(stall_pipe, input_string))
print('Output:\n{}\n'.format(largest[0]))
# Test out.
for sequence in ['101', '001011', '101000011', '100000110000', '11110000001', '10', '10100']:
find_furthest_stall(sequence)
# Golfed
y={i:j for i,j in enumerate(not bool(int(i))for i in'100000110000')}
d={i:abs(i[0]-i[1])for i in list(itertools.combinations(y.keys(),2))}
q=[0,0]
for k,v in d.iteritems():
if v>=q[1]and(y[k[0]]or y[k[1]]):q[0]=k[0]if y[k[0]]else k[1];q[1]=v
print('Largest -> {}'.format(q[0]))
| [
"noreply@github.com"
] | ospahiu.noreply@github.com |
7d8af894f2c76cc47cf868d00ed53d834dc11006 | 138f2550bb088a0597e1e71124d9ae32b1fe59c9 | /xbrr/edinet/reader/element_schema.py | b78030ff98b2a4b89b4ca5131bc6e0a11deb5645 | [
"MIT"
] | permissive | chakki-works/xbrr | 9009539e1821c3d9c815f694eb52158ccbbeeb78 | a9783acbb6c23eb0be0e1fbfb47e5b0b0e2cbfb8 | refs/heads/master | 2022-07-22T22:30:17.054418 | 2021-06-16T13:27:40 | 2021-06-16T13:27:40 | 182,622,738 | 23 | 5 | MIT | 2022-07-15T18:42:36 | 2019-04-22T04:26:21 | Python | UTF-8 | Python | false | false | 1,947 | py | from xbrr.base.reader.base_element_schema import BaseElementSchema
class ElementSchema(BaseElementSchema):
def __init__(self,
name="", reference="", label="", alias="",
abstract="", data_type="",
period_type="", balance=""):
super().__init__()
self.name = name
self.reference = reference
self.label = label
self.alias = alias
self.abstract = abstract
self.data_type = data_type
self.period_type = period_type
self.balance = balance
def set_alias(self, alias):
self.alias = alias
return self
@classmethod
def create_from_reference(cls, reader, reference,
label_kind="", label_verbose=False):
name = reference.split("#")[-1]
label = ""
abstract = ""
data_type = ""
period_type = ""
balance = ""
if reader.xbrl_dir:
_def = reader.read_by_link(reference)
if label_kind is not None:
label = _def.label(label_kind, label_verbose)
xsd = _def.xsd
abstract = xsd["abstract"]
data_type = xsd["type"]
if "xbrli:periodType" in xsd.attrs:
period_type = xsd["xbrli:periodType"]
if "xbrli:balance" in xsd.attrs:
balance = xsd["xbrli:balance"]
instance = cls(name=name, reference=reference, label=label,
abstract=abstract, data_type=data_type,
period_type=period_type, balance=balance)
return instance
def to_dict(self):
return {
"name": self.name,
"reference": self.reference,
"label": self.label,
"abstract": self.abstract,
"data_type": self.data_type,
"period_type": self.period_type,
"balance": self.balance
}
| [
"icoxfog417@yahoo.co.jp"
] | icoxfog417@yahoo.co.jp |
bb394288997b3ae09c3bf5e93b767c0a5aa8fcdb | 7ad616ab89e9b67bd27df2df3c8ca7487c5e4564 | /ood/4_stack_overflow.py | 102433a9d98dbc8f0d47c4101d2b370291a90a1b | [] | no_license | zihuaweng/algorithm-snacks | cd7643c7d80d0bcb680336231214c1700fe74cc9 | aa3d88f861bb8b0aceb7ef6c6d05523f54202d77 | refs/heads/master | 2023-01-13T11:03:04.395542 | 2020-11-10T04:42:41 | 2020-11-10T04:42:41 | 149,380,311 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 3,997 | py | #!/usr/bin/env python3
# coding: utf-8
class QuestionStatus(Enum):
OPEN, CLOSED, ON_HOLD, DELETED = 1, 2, 3, 4
class QuestionClosingRemark(Enum):
DUPLICATE, OFF_TOPIC, TOO_BROAD, NOT_CONSTRUCTIVE, NOT_A_REAL_QUESTION, PRIMARILY_OPINION_BASED = 1, 2, 3, 4, 5, 6
class AccountStatus(Enum):
ACTIVE, CLOSED, CANCELED, BLACKLISTED, BLOCKED = 1, 2, 3, 4, 5
# For simplicity, we are not defining getter and setter functions. The reader can
# assume that all class attributes are private and accessed through their respective
# public getter methods and modified only through their public methods function.
class Account:
def __init__(self, id, password, name, address, email, phone, status=AccountStatus.Active):
self.__id = id
self.__password = password
self.__name = name
self.__address = address
self.__email = email
self.__phone = phone
self.__status = status
self.__reputation = 0
def reset_password(self):
None
class Member:
def __init__(self, account):
self.__account = account
self.__badges = []
def get_reputation(self):
return self.__account.get_reputation()
def get_email(self):
return self.__account.get_email()
def create_question(self, question):
None
def create_tag(self, tag):
None
class Admin(Member):
def block_member(self, member):
None
def unblock_member(self, member):
None
class Moderator(Member):
def close_question(self, question):
None
def undelete_question(self, question):
None
class Badge:
def __init__(self, name, description):
self.__name = name
self.__description = description
class Tag:
def __init__(self, name, description):
self.__name = name
self.__description = description
self.__daily_asked_frequency = 0
self.__weekly_asked_frequency = 0
# import datetime
class Notification:
def __init__(self, id, content):
self.__notification_id = id
self.__created_on = datetime.datetime.now()
self.__content = content
def send_notification(self):
None
import datetime
class Photo:
def __init__(self, id, path, member):
self.__photo_id = id
self.__photo_path = path
self.__creation_date = datetime.datetime.now()
self.__creating_member = member
def delete(self):
None
# import datetime
class Bounty:
def __init__(self, reputation, expiry):
self.__reputation = reputation
self.__expiry = expiry
def modify_reputation(self, reputation):
None
from abc import ABC, abstractmethod
class Search(ABC):
def search(self, query):
None
import datetime
class Question(Search):
def __init__(self, title, description, bounty, asking_member):
self.__title = title
self.__description = description
self.__view_count = 0
self.__vote_count = 0
self.__creation_time = datetime.datetime.now()
self.__update_time = datetime.datetime.now()
self.__status = QuestionStatus.OPEN
self.__closing_remark = QuestionClosingRemark.DUPLICATE
self.__bounty = bounty
self.__asking_member = asking_member
self.__photos = []
self.__comments = []
self.__answers = []
def close(self):
None
def undelete(self):
None
def add_comment(self, comment):
None
def add_bounty(self, bounty):
None
def search(self, query):
# return all questions containing the string query in their title or description.
None
class Comment:
def __init__(self, text, member):
self.__text = text
self.__creation_time = datetime.datetime.now()
self.__flag_count = 0
self.__vote_count = 0
self.__asking_member = member
def increment_vote_count(self):
None
class Answer:
def __init__(self, text, member):
self.__answer_text = text
self.__accepted = False
self.__vote_count = 0
self.__flag_count = 0
self.__creation_time = datetime.datetime.now()
self.__creating_member = member
self.__photos = []
def increment_vote_count(self):
None | [
"zihuaw2@uci.edu"
] | zihuaw2@uci.edu |
2421b66b402fbd831d2d695ed5f8d3c492c5cbe2 | 065b20697aa6479b52a064ad1362ce1278cfb939 | /users/migrations/0002_testtable.py | f2e7d5e740944ad3d0a7563cfdbd7953e72c7a15 | [] | no_license | RagnarSmari/redstarcereal-dev | 8ca8169dc06f24dec527ab6eec7c2f1560b94adc | 05c17d31693015b1bc97fe46304fdf7c7cd17b0f | refs/heads/master | 2023-04-20T05:04:00.514162 | 2021-05-14T22:53:06 | 2021-05-14T22:53:06 | 363,891,999 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 575 | py | # Generated by Django 3.2 on 2021-05-03 09:49
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('users', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='TestTable',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('test_name', models.CharField(max_length=100)),
('test_char', models.CharField(max_length=100)),
],
),
]
| [
"arnist91@gmail.com"
] | arnist91@gmail.com |
e4d0cbc32a9cf12c10502cc359e90a7d7aa975a6 | ea77dabd55623cd9352b991fd08d7900eceea70f | /perch/errors.py | 125cf83f87aed1c34ea8b7b6116e1bd78d71b4a6 | [
"BSD-3-Clause"
] | permissive | BrianHicks/perch | 688c604e47d939620e7a50a05e1385632fcc7673 | 2d4ae099422745836361ade069723f6f6cb33fef | refs/heads/master | 2020-04-12T02:44:26.403224 | 2013-10-11T16:19:05 | 2013-10-11T16:19:05 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 112 | py | class PerchError(Exception):
pass
class BadRunner(Exception):
pass
class BadExit(Exception):
pass
| [
"brian.hicks@rockfishinteractive.com"
] | brian.hicks@rockfishinteractive.com |
b208e49da531e72d4264b91f912ebd1523d749d6 | 731c3f2f85f6002725322eedc0b2c8b5e74f610e | /0-jakc/jakc_hr/__openerp__.py | 2df1fff1bd5ba0cb87ac4230b96c9fe3ed3e6001 | [] | no_license | babarlhr/project-0021 | 1ac824657f893c8f25d6eb3b839051f350d7cc9d | e30b8a9f5d2147d3ca5b56b69ec5dbd22f712a91 | refs/heads/master | 2021-09-22T15:45:47.431000 | 2018-09-11T14:59:49 | 2018-09-11T14:59:52 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 398 | py | # -*- coding: utf-8 -*-
{
'name': 'Jakc Labs - HR Enhancement',
'version': '9.0.0.1.0',
'category': 'General',
'license': 'AGPL-3',
'summary': 'HR Enchancement',
'author': "Jakc Labs",
'website': 'http://www.jakc-labs.com/',
'depends': [
'hr'
],
'data': [
'views/jakc_hr_view.xml',
],
'installable': True,
'application': True,
}
| [
"wahhid@gmail.com"
] | wahhid@gmail.com |
1e675ea36d339816edb3d3368dcdddf19a443116 | 9a8b2183171b35ad11c0021479be1d7b905544b4 | /Code/Learning/checking_sgd_weight.py | 07f3badcfdcd0516abb2886cae77c614f0e4bbe8 | [] | no_license | Serhiy-Shekhovtsov/KDD-Cup | e6977e06c549905aa7a3e1508526bd0a79e6972f | d4470117865d68b588afd4f7440128ef4dfd231e | refs/heads/master | 2020-12-24T17:44:33.565903 | 2015-06-03T20:52:27 | 2015-06-03T20:52:27 | 35,604,881 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,066 | py | import cPickle
import csv
import numpy as np
import random
from numpy import squeeze
import pandas as pd
from sklearn import svm, cross_validation, preprocessing, ensemble
from sklearn.decomposition import TruncatedSVD
from sklearn.linear_model import SGDClassifier
from sklearn.metrics import roc_auc_score
from decompose import load_decomposed
from utils import *
n_factors = 105
subsample = .6
operation_name = data_size + "accuracy per weight 2. sgd. %i factors" % n_factors
log(operation_name)
results_file_name = results_dir + operation_name + datetime.now().strftime('%Y-%m-%d %H-%M-%S') + ".csv"
train_data = load_decomposed(n_factors, alg="sparsesvd")
train_data = preprocessing.scale(train_data)
n_items = train_data.shape[0]
train_indices = np.load(clean_data_dir + data_size + "train_indices.npy")
train_labels = pd.read_csv(labels_dir + data_size + 'appetency.labels', header=None)
train_labels = squeeze(train_labels.values)[train_indices]
train_labels[train_labels == -1] = 0
results = []
for weight in np.arange(.45, 1, .005):
log("calculating train and test accuracy, weight = %0.4f" % weight)
clf = SGDClassifier(loss='log', class_weight={0: 1, 1: weight})
log("running cross_val_score")
scores = cross_validation.cross_val_score(clf, train_data, train_labels, cv=7,
verbose=4, scoring='roc_auc')
log("train on whole train val set")
clf.fit(train_data, train_labels)
log("predict")
train_result = clf.predict_proba(train_data)
train_result = train_result[:, 1]
train_accuracy = roc_auc_score(train_labels, train_result)
log("weight %0.1f, train accuracy: %0.4f, test accuracy: %0.4f" % (weight, train_accuracy, scores.mean()),
bcolors.OKBLUE)
results.append([weight, train_accuracy, scores.mean()])
with open(results_file_name, 'w') as fp:
a = csv.writer(fp, delimiter=',', lineterminator='\n')
a.writerows(results)
cPickle.dump(results_file_name, open(results_dir + "latest_result.txt", "w"))
log("done")
| [
"Serhiy.Shekhovtsov@gmail.com"
] | Serhiy.Shekhovtsov@gmail.com |
3a1fe4c62e23309f597c1d3b676e04e3f0075837 | e9bd0c269d33a2f2492987b095d06afa1246e723 | /practico_vectores/ejercicio2.py | 2c709d94d5583cdb6ac9a7709290937f25c3c468 | [] | no_license | Nelcyberth86/IntroProgramacion | 08378388293f8662300469936275007cc84e3ace | 2a054ecd36402f3b41aceaeeeec0bd04a07335ba | refs/heads/master | 2023-01-21T12:16:12.090547 | 2020-12-04T22:12:38 | 2020-12-04T22:12:38 | 296,443,821 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 728 | py | #Diseñar un programa que lea como entrada dos vectores de tamaño 5 y devuelva el vector suma.
#Ejemplo: si tenemos los vectores V1 = (a1, a2, …, a5) y V2 = (b1, b2, …, b5) el vector suma se define como el vector obtenido
#de sumar componente a componente: V1 + V2 = (a1+ b1, a2+ b2, …, a5+ b5).
#import array as np
v1 = []
v2 = []
suma = []
print("llene el primer vector")
for i in range(0,5):
num1 = int(input("ingrese un caracter: "))
v1.append(num1)
print("llene el segundo vector")
for i in range(0, 5):
num2 = int(input("ingrese un caracter:"))
v2.append(num2)
suma=[]
print("suma de los vectores")
for i in range(0,5):
num=v1[i]+v2[i]
suma.append(num)
print(v1)
print(v2)
print(suma)
| [
"mishel.maraz2003@gmail.com"
] | mishel.maraz2003@gmail.com |
b368bdacb89515b66e15c2e2a308319970ccdfe3 | b80875542b4ccd8edd533faf85e96a83361a61f7 | /WebSite/wsgi.py | 9c932aed3e4a9f37d257028c944f037f63f40eb6 | [] | no_license | Vitaly00700/my-first-app | cbe262594aeef519218a2787c1950f8077897af1 | da158c7db7989fe6f04ca7d786a5f79750f0a441 | refs/heads/master | 2021-01-19T08:41:19.797129 | 2017-04-08T20:38:39 | 2017-04-08T20:38:39 | 87,663,022 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 391 | py | """
WSGI config for WebSite 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/1.9/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "WebSite.settings")
application = get_wsgi_application()
| [
"My@mail.com"
] | My@mail.com |
91b6b76a311bc1f86fdb741e4608f8220dbde146 | 30d61ce0b728f31a830db6b6b1954a32551990b2 | /src/gui_config/custom/sr_source_mode_tab.py | b2a24e0a0387ec82695aca2a32af5633db14603c | [
"MIT"
] | permissive | hgiesel/anki_set_randomizer | 6755dc8489b703887c55a5427bbbdab858f58a65 | 1a9a22480eb6c0e7f421dc08d36d14920e43dd3e | refs/heads/master | 2022-08-24T05:45:13.339132 | 2020-01-15T17:04:26 | 2020-01-30T13:56:50 | 197,258,760 | 5 | 0 | MIT | 2022-07-20T17:28:42 | 2019-07-16T19:56:27 | JavaScript | UTF-8 | Python | false | false | 1,391 | py | from aqt.qt import QWidget
from ...lib.config import deserialize_source_mode, deserialize_cloze_options, deserialize_occlusion_options
from ..sr_source_mode_tab_ui import Ui_SRSourceModeTab
class SRSourceModeTab(QWidget):
def __init__(self):
super().__init__()
self.ui = Ui_SRSourceModeTab()
self.ui.setupUi(self)
def setupUi(self, source_mode):
cloze_options = source_mode.cloze_options
self.ui.clozeShortcutsEnabledCheckBox.setChecked(cloze_options.shortcuts_enabled)
self.ui.clozeVsPrefixLineEdit.setText(cloze_options.vs_prefix)
self.ui.clozeOpenDelimLineEdit.setText(cloze_options.open_delim)
self.ui.clozeCloseDelimLineEdit.setText(cloze_options.close_delim)
def exportClozeOptions(self):
return deserialize_cloze_options({
'shortcutsEnabled': self.ui.clozeShortcutsEnabledCheckBox.isChecked(),
'vsPrefix': self.ui.clozeVsPrefixLineEdit.text(),
'openDelim': self.ui.clozeOpenDelimLineEdit.text(),
'closeDelim': self.ui.clozeCloseDelimLineEdit.text(),
})
def exportOcclusionOptions(self):
return deserialize_occlusion_options({})
def exportData(self):
return deserialize_source_mode({
'clozeOptions': self.exportClozeOptions(),
'occlusionOptions': self.exportOcclusionOptions(),
})
| [
"hengiesel@gmail.com"
] | hengiesel@gmail.com |
0d0984c7488238d344fdb54c616d0b315b496f66 | 8d5de5544d72635a37395fe681a73fd8c7c79004 | /tv_ratings_frontend/ratings_frontend/urls.py | e98cdeca775bfa7fc6c87392881ffe44f8f9051a | [] | no_license | OktayGardener/AIProject | 84d195add957ade2021ae359d6648548e7f17103 | abc8f897872451618dc85ee5ddc0cff718084f6a | refs/heads/master | 2021-01-15T11:30:49.857033 | 2016-01-28T21:33:45 | 2016-01-28T21:33:45 | 43,515,388 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 239 | py | from django.conf.urls import url, patterns
from ratings_frontend import views
urlpatterns = patterns('',
url(r'^$', views.index, name='index'),
url(r'^search/$', views.search, name='search'))
| [
"bcoopercs@live.com"
] | bcoopercs@live.com |
832720b68f71395bcb1f886ad4f682245dcbca17 | a13795d2aa56dab51e4dd723954332c110ade546 | /trove/backup/state.py | b0c4676622dcdfa3250316210b718a27fc2f09ab | [
"Apache-2.0"
] | permissive | phunv-bka/trove | 5304903b413e487d3c2c03560f4a08fbde4db70d | 2d301d0a21863c6c0fbb9e854c7eb8ad8f19bbc1 | refs/heads/master | 2020-09-22T17:13:40.048544 | 2020-02-02T22:45:40 | 2020-02-02T22:45:40 | 225,281,715 | 1 | 0 | Apache-2.0 | 2019-12-02T03:59:00 | 2019-12-02T03:58:59 | null | UTF-8 | Python | false | false | 913 | py | # Copyright 2014 OpenStack Foundation
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, 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.
#
class BackupState(object):
NEW = "NEW"
BUILDING = "BUILDING"
SAVING = "SAVING"
COMPLETED = "COMPLETED"
FAILED = "FAILED"
DELETE_FAILED = "DELETE_FAILED"
RUNNING_STATES = [NEW, BUILDING, SAVING]
END_STATES = [COMPLETED, FAILED, DELETE_FAILED]
| [
"robert.myers@rackspace.com"
] | robert.myers@rackspace.com |
223bd273f49b7e533b590ec4dc1f9394ef62d3c7 | bfbe642d689b5595fc7a8e8ae97462c863ba267a | /bin/Python27/Lib/site-packages/OMPython/OMTypedParser.py | a0e4c90b6d536f97341c456f18de90f519d82e80 | [
"MIT",
"LicenseRef-scancode-other-permissive"
] | permissive | mcanthony/meta-core | 0c0a8cde1669f749a4880aca6f816d28742a9c68 | 3844cce391c1e6be053572810bad2b8405a9839b | refs/heads/master | 2020-12-26T03:11:11.338182 | 2015-11-04T22:58:13 | 2015-11-04T22:58:13 | 45,806,011 | 1 | 0 | null | 2015-11-09T00:34:22 | 2015-11-09T00:34:22 | null | UTF-8 | Python | false | false | 4,041 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "Martin Sjölund"
__license__ = """
This file is part of OpenModelica.
Copyright (c) 1998-CurrentYear, Open Source Modelica Consortium (OSMC),
c/o Linköpings universitet, Department of Computer and Information Science,
SE-58183 Linköping, Sweden.
All rights reserved.
THIS PROGRAM IS PROVIDED UNDER THE TERMS OF THE BSD NEW LICENSE OR THE
GPL VERSION 3 LICENSE OR THE OSMC PUBLIC LICENSE (OSMC-PL) VERSION 1.2.
ANY USE, REPRODUCTION OR DISTRIBUTION OF THIS PROGRAM CONSTITUTES
RECIPIENT'S ACCEPTANCE OF THE OSMC PUBLIC LICENSE OR THE GPL VERSION 3,
ACCORDING TO RECIPIENTS CHOICE.
The OpenModelica software and the OSMC (Open Source Modelica Consortium)
Public License (OSMC-PL) are obtained from OSMC, either from the above
address, from the URLs: http://www.openmodelica.org or
http://www.ida.liu.se/projects/OpenModelica, and in the OpenModelica
distribution. GNU version 3 is obtained from:
http://www.gnu.org/copyleft/gpl.html. The New BSD License is obtained from:
http://www.opensource.org/licenses/BSD-3-Clause.
This program is distributed WITHOUT ANY WARRANTY; without even the implied
warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE, EXCEPT AS
EXPRESSLY SET FORTH IN THE BY RECIPIENT SELECTED SUBSIDIARY LICENSE
CONDITIONS OF OSMC-PL.
Author : Anand Kalaiarasi Ganeson, ganan642@student.liu.se, 2012-03-19
Version: 1.0
"""
__status__ = "Prototype"
__maintainer__ = "https://openmodelica.org"
from pyparsing import *
import sys
def convertNumbers(s,l,toks):
n = toks[0]
try:
return int(n)
except ValueError, ve:
return float(n)
def convertString(s,s2):
return s2[0].replace("\\\"",'"')
def convertDict(d):
return dict(d[0])
def convertTuple(t):
return tuple(t[0])
omcRecord = Forward()
omcValue = Forward()
TRUE = Keyword("true").setParseAction( replaceWith(True) )
FALSE = Keyword("false").setParseAction( replaceWith(False) )
NONE = (Keyword("NONE") + Suppress("(") + Suppress(")") ).setParseAction( replaceWith(None) )
SOME = (Suppress( Keyword("SOME") ) + Suppress("(") + omcValue + Suppress(")") )
omcString = QuotedString(quoteChar='"',escChar='\\', multiline = True).setParseAction( convertString )
omcNumber = Combine( Optional('-') + ( '0' | Word('123456789',nums) ) +
Optional( '.' + Word(nums) ) +
Optional( Word('eE',exact=1) + Word(nums+'+-',nums) ) )
ident = Word(alphas+"_",alphanums+"_") | Combine( "'" + Word(alphanums+"!#$%&()*+,-./:;<>=?@[]^{}|~ ") + "'" )
fqident = Forward()
fqident << ( (ident + "." + fqident) | ident )
omcValues = delimitedList( omcValue )
omcTuple = Group( Suppress('(') + Optional(omcValues) + Suppress(')') ).setParseAction(convertTuple)
omcArray = Group( Suppress('{') + Optional(omcValues) + Suppress('}') ).setParseAction(convertTuple)
omcValue << ( omcString | omcNumber | omcRecord | omcArray | omcTuple | SOME | TRUE | FALSE | NONE | Combine(fqident) )
recordMember = delimitedList( Group( ident + Suppress('=') + omcValue ) )
omcRecord << Group( Suppress('record') + Suppress( ident ) + Dict( recordMember ) + Suppress('end') + Suppress( ident ) + Suppress(';') ).setParseAction(convertDict)
omcGrammar = omcValue + StringEnd()
omcNumber.setParseAction( convertNumbers )
def parseString(string):
return omcGrammar.parseString(string)[0]
if __name__ == "__main__":
testdata = """
(1.0,{{1,true,3},{"4\\"
",5.9,6,NONE ( )},record ABC
startTime = ErrorLevel.warning,
'stop*Time' = SOME(1.0)
end ABC;})
"""
expected = (1.0, ((1, True, 3), ('4"\n', 5.9, 6, None), {"'stop*Time'": 1.0, 'startTime': 'ErrorLevel.warning'}))
results = parseString(testdata)
if results <> expected:
print "Results:",results
print "Expected:",expected
print "Failed"
sys.exit(1)
print "Matches expected output",
print type(results),repr(results)
| [
"kevin.m.smyth@gmail.com"
] | kevin.m.smyth@gmail.com |
6ddbc8154053d1a105be3ce47e7b58a27e253eb8 | de479d4a8af0e070b2bcae4186b15a8eb74971fb | /cn/iceknc/study/k_python_mini_web/__init__.py | 2c29f9732decc87fd29a825cf08dd49ab11e8eb8 | [] | no_license | iceknc/python_study_note | 1d8f6e38be57e4dc41a661c0a84d6ee223c5a878 | 730a35890b77ecca3d267fc875a68e96febdaa85 | refs/heads/master | 2020-05-19T18:44:55.957392 | 2019-09-27T01:15:54 | 2019-09-27T01:15:54 | 185,160,232 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 152 | py | # -*- coding: utf-8 -*-
# @Author: 徐志鹏
# @Date : 2019/5/29
# @Desc :
def main():
pass
if __name__ == "__main__":
main()
| [
"xzhipeng@lifecare.cn"
] | xzhipeng@lifecare.cn |
f66be245d49c0500c212fbf3f7565976f9419b1f | 80755ce68bf894bfa7c7cec50051b18a6069c552 | /nkamg_malware/collector/samples/file_monitor.py | 0d59cd857a599c427bd46b6fa686fa151a915729 | [
"Apache-2.0"
] | permissive | NKQiuKF/malware_update | 6538c9308dd7b476b687fca4ea120209207257bc | a875b5011fee2486da5618e01da61d730d6ac0dd | refs/heads/master | 2022-10-17T09:08:34.605641 | 2019-09-02T09:00:45 | 2019-09-02T09:00:45 | 205,817,190 | 0 | 0 | null | 2022-10-06T18:33:50 | 2019-09-02T08:59:47 | JavaScript | UTF-8 | Python | false | false | 2,497 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#Nankai University Information Security
#QiuKF 1055419050@qq.com
#get file results at fixed time
#create processed.csv at sub dirctories
#create Total_File_Data.csv at /collection
from multiprocessing import Process,Pool
import os
import pandas as pd
import time
import sys
sys.path.append('../core/')
from setting import SAMPLES_PATH
#samples_path='/data/malware/'
def merge_file():
data = {"sha256":[],"type":[]}
total_df=pd.DataFrame(data)
chr=['0','1','2','3','4','5','6','7','8','9','a','b','c','d','e','f']
for first in chr:
sub_dir_list=make_file_dir(first)
for each in sub_dir_list:
sub_pd=pd.read_csv(SAMPLES_PATH+each+'processed.csv')
total=[total_df,sub_pd]
total_df=pd.concat(total)
print 'concat '+each+'processed.csv'
total_df.to_csv('Total_File_Data.csv',index=False)
def exe_file(first_dir):
count=0
#print 'test'
print 'Run task %s (%s)...' % (first_dir, os.getpid())
child_dir=make_file_dir(first_dir)
#print child_dir
for each_dir in child_dir:
data = {"sha256":[],"type":[]}
processed_df=pd.DataFrame(data)
all_files=os.listdir(SAMPLES_PATH+each_dir)
for each_file in all_files:
file_command = os.popen('file ' +SAMPLES_PATH+each_dir+each_file)
#print 'file ' +SAMPLES_PATH+each_dir+each_file
read_data= file_command.read()
tmp=read_data[read_data.index(':') + 2 : read_data.index('\n')]
#print tmp
processed_df.loc[len(processed_df)]=[each_file,tmp]
processed_df.to_csv(SAMPLES_PATH+each_dir+'processed.csv',index=False)
print 'created '+SAMPLES_PATH+each_dir+'processed.csv'
def make_file_dir(first):
ret=[]
chr_list=['0','1','2','3','4','5','6','7','8','9','a','b','c','d','e','f']
tmp=''
for second in chr_list:
two='/'+second
for third in chr_list:
three=two+'/'+third+'/'
ret.append(first+three)
#print len(ret)
#print ret
return ret
def main():
#print SAMPLES_PATH
print('Parent process %s.' %os.getpid())
#dic_list=make_file_dir()
first_dic=['0','1','2','3','4','5','6','7','8','9','a','b','c','d','e','f']
p=Pool(16)
for each in first_dic:
#print each
p.apply_async(exe_file,args=(each,))
p.close()
p.join()
print 'start merging file results...'
merge_file()
#is_apk('1.apk')
#is_apk(base_path+'three')
if __name__=='__main__':
while True:
main()
time.sleep(36000)
| [
"453341288@qq.com"
] | 453341288@qq.com |
8e52ad24863a5c0430c1ebff7ba718862d63854b | 518d14bbb2e3a417baeabbfdcf39a636c66cdf96 | /test.py | d943a45a421a8ed204768df2d1797c230535163b | [] | no_license | vladimirstarygin/Dali_samplers | 4139757f8cac9e78c8976a866c360e0cc66e12c0 | 8eb201d8f428fd3724db483bfa4407b9e94e5597 | refs/heads/main | 2023-07-16T10:27:49.944998 | 2021-08-19T09:01:41 | 2021-08-19T09:01:41 | 397,875,642 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,733 | py | import nvidia.dali.fn as fn
import nvidia.dali.types as types
from nvidia.dali.pipeline import Pipeline
from collections import Counter
from dsampler.samplers.simple_sampler import SimpleSampler
from dsampler.samplers.random_sampler import RandomSampler
from dsampler.samplers.balanced_sampler import WeightedRandomSampler
from dsampler.samplers.nclass_sampler import NClassRandomOverSampler
from nvidia.dali.plugin.pytorch import DALIClassificationIterator as PyTorchIterator
from nvidia.dali.plugin.pytorch import LastBatchPolicy
image_dir_path = ''
annotation_path = ''
sampler = NClassRandomOverSampler(image_dir=image_dir_path,
anno_path=annotation_path,
anno_type='.json',
batch_size=32,
shuffle = True)
def ExternalSourcePipeline(batch_size, num_threads, device_id, external_data):
pipe = Pipeline(batch_size, num_threads, device_id)
with pipe:
jpegs, labels = fn.external_source(source=external_data, num_outputs=2)
images = fn.decoders.image(jpegs, device="mixed")
images = fn.resize(images, resize_x=240, resize_y=240)
output = fn.cast(images, dtype=types.UINT8)
pipe.set_outputs(output, labels)
return pipe
pipe = ExternalSourcePipeline(batch_size=32, num_threads=2, device_id = 0,
external_data = sampler)
pii = PyTorchIterator(pipe, last_batch_padded=True, last_batch_policy=LastBatchPolicy.PARTIAL)
epochs = 1
for e in range(epochs):
for i, data in enumerate(pii):
labs = data[0]['label'].reshape(-1).numpy()
c = Counter(labs)
print(c)
#print("epoch: {}, iter {}, real batch size: {}".format(e, i, len(data[0]["data"])))
pii.reset() | [
"vladimir.starygin@tevian.ru"
] | vladimir.starygin@tevian.ru |
d11fcc621b8ff6431ec6612fc692ddbf576a5e4a | d484fee99ae905a82ebb1185ef9fa2c203e0d81a | /utils/time_tool.py | 4c2b771ce4ad558f2efecb6d7cb95062468c3022 | [
"Apache-2.0"
] | permissive | liqiwudao/job | f64a3354707715bd0effa6b072ae86c74614f76c | de95c56627336060234755ab8bbe0510ed112573 | refs/heads/master | 2021-01-25T11:14:18.697252 | 2017-06-10T04:22:08 | 2017-06-10T04:22:08 | 93,915,155 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,787 | py | # -*- coding:utf-8 -*-
import arrow
from functools import partial
import time
import datetime
def comment_time(now, date):
difference = int((now - date).total_seconds())
if difference < 3600:
r_time, remainder, = divmod(difference, 60)
r_time = r_time if not remainder else r_time + 1
r_time = u"%s 分钟前" % (r_time)
elif difference >= 3600 and difference < 86400:
r_time, remainder, = divmod(difference, 3600)
r_time = r_time if not remainder else r_time + 1
r_time = u"%s 小时前" % (r_time)
elif difference >= 86400 and difference < 2592000:
r_time, remainder, = divmod(difference, 86400)
r_time = r_time if not remainder else r_time + 1
r_time = u"%s 天前" % (r_time)
elif difference >= 2592000 and difference < 31536000:
r_time, remainder, = divmod(difference, 2592000)
r_time = r_time if not remainder else r_time + 1
r_time = u"%s 月前" % (r_time)
elif difference >= 31536000:
r_time, remainder, = divmod(difference, 31536000)
r_time = r_time if not remainder else r_time + 1
r_time = u"%s 年前" % (r_time)
return r_time
now = arrow.now
utcnow = arrow.utcnow
prc_tz = 'PRC' # MUST uppercase!
def prcnow():
return utcnow().to(prc_tz)
def prctoday():
return prcnow().date()
def span_range(start, end, frame, tz=None):
return arrow.Arrow.span_range(frame, start, end, tz=tz)
def time_range(start, end, frame, tz=None):
return arrow.Arrow.range(frame, start, end, tz=tz)
span_range_by_minute = partial(span_range, frame='minute')
span_range_by_hour = partial(span_range, frame='hour')
span_range_by_day = partial(span_range, frame='day')
prc_span_range_by_minute = partial(span_range, frame='minute', tz=prc_tz)
prc_span_range_by_hour = partial(span_range, frame='hour', tz=prc_tz)
prc_span_range_by_day = partial(span_range, frame='day', tz=prc_tz)
prc_range_by_minute = partial(time_range, frame='minute', tz=prc_tz)
prc_range_by_hour = partial(time_range, frame='hour', tz=prc_tz)
prc_range_by_day = partial(time_range, frame='day', tz=prc_tz)
def utc_today_int():
return int(arrow.utcnow().format('YYYYMMDD'))
def prc_today_int():
return int(prcnow().format('YYYYMMDD'))
def utc_from_today_int(date_int):
return arrow.Arrow.strptime(str(date_int), '%Y%m%d')
def prc_from_today_int(date_int):
return arrow.Arrow.strptime(str(date_int), '%Y%m%d', tzinfo=prc_tz)
def timestamp(is_float=False):
if is_float:
return arrow.utcnow().float_timestamp
else:
return arrow.utcnow().timestamp
def utc_from_timestamp(ts):
return arrow.Arrow.utcfromtimestamp(ts)
def prc_from_timestamp(ts):
return arrow.Arrow.fromtimestamp(ts, prc_tz)
| [
"zjw2227680283@qq.com"
] | zjw2227680283@qq.com |
8180678a33cdb2dffadc6c12d15a0a4bd2b9f267 | 4553a804b8410b37eeb49d4c106afc39f4f49f0b | /Linear Regression.py | 5cc2715b830119c370869d6ed58d14e6244ae0bc | [] | no_license | SwaraDeshpande/Linear-regression | af763232afbdf5b3a0b07786099c15ea8d0d2dfb | 79864fdf3e3eea5c49afc0e5f6125149aba9321e | refs/heads/master | 2020-12-31T20:44:17.294464 | 2020-02-07T22:10:51 | 2020-02-07T22:10:51 | 239,024,711 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,613 | py | #!/usr/bin/env python
# coding: utf-8
# In[1]:
# In[2]:
# write your code here
import numpy as np
import pandas as pd
import matlablib.plot as plt
import pylab as pb
from sklearn import linear_model
get_ipython().run_line_magic('matplotlib', 'inline')
get_ipython().system('wget -O FuelConsumption.csv https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/FuelConsumptionCo2.csv')
#reading the data
df = pd.read_csv("FuelConsumption.csv")
df.head()
#summarizing the data
desc = df.describe()
#selecting some features
cdf = df[['ENGINESIZE','CYLINDERS','CO2EMISSIONS','FUELCONSUMPTION_COMB']]
cdf.head(9)
#plotting each of these features
viz= cdf[['ENGINESIZE','CYLINDERS','CO2EMISSIONS','FUELCONSUMPTION_COMB']]
viz.history()
plt.show()
#plot linear regression cylinder vs emission
plt.scatter(cdf.CYLINDERS , cdf.CO2EMISSIONS , color ='red') #plotting the data values as points in red color
plt.xlabel("Cylinders") #giving the x-axis label
plt.ylabel("Emission") #giving the yiaxis label
plt.show()
#Creating train and test dataset
msk = np.random.rand(len(df)) < 0.8
train = cdf[msk]
test = cdf[tmsk]
#training the data distribution
plt.scatter(train.CYLINDERS, train.CO2EMISSIONS, color='blue')
plt.xlabel("Cylinders")
plt.ylabel("Emission")
plt.show()
#modelling the data
regr = linear_model.LinearRegression()
train_x = np.asanyarray(train[['CYLINDERS']])
train_y = np.asanyarray(train[['CO2EMISSIONS']])
regr.fit (train_x, train_y)
# The coefficients
print ('Coefficients: ', regr.coef_)
print ('Intercept: ',regr.intercept_)
# In[ ]:
| [
"noreply@github.com"
] | SwaraDeshpande.noreply@github.com |
511798e6d590c52b0ee9951d0b743ac2aaca2d67 | a1a99f8e7b2d790562707895acaba9d973e84add | /env/bin/pip3 | 459cd0f051d8f816c5f37fbb0c5906f5ff4af43a | [] | no_license | BartSu/Python_Flask_API | 766042cf6d6100d65855db9bde9895b028fca1e7 | 3c9448e8861125ccef38fb5312cde4e01ebaa91b | refs/heads/master | 2020-08-12T18:58:56.732314 | 2019-10-13T13:27:37 | 2019-10-13T13:27:37 | 214,824,135 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 247 | #!/Users/BartSu/Desktop/project/env/bin/python3.6
# -*- coding: utf-8 -*-
import re
import sys
from pip._internal import main
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(main())
| [
"subo@kean.edu"
] | subo@kean.edu | |
aad94c1ec526a6e1682bdd067423c5046f7a44bc | 1250846cadc2538fb0ded57a41e6ec01492c89b1 | /mask.py | 68c78068fffadc8b9b35a1caf9287b1039fc913f | [] | no_license | PradhyuS86/Legacy-with-Flask-API | b1330a1312ed38de537881441e52f7a94368f2f0 | 16e071908ca07d6bf4fd76dceb78969e9d081702 | refs/heads/master | 2021-01-20T15:31:47.764009 | 2017-05-09T19:06:55 | 2017-05-09T19:06:55 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,444 | py | # -*- coding: utf-8 -*-
from __future__ import unicode_literals, absolute_import
import logging
import re
import six
from collections import OrderedDict
from inspect import isclass
from .errors import RestError
log = logging.getLogger(__name__)
LEXER = re.compile(r'\{|\}|\,|[\w_:\-\*]+')
class MaskError(RestError):
'''Raised when an error occurs on mask'''
pass
class ParseError(MaskError):
'''Raised when the mask parsing failed'''
pass
class Mask(OrderedDict):
'''
Hold a parsed mask.
:param str|dict|Mask mask: A mask, parsed or not
:param bool skip: If ``True``, missing fields won't appear in result
'''
def __init__(self, mask=None, skip=False, **kwargs):
self.skip = skip
if isinstance(mask, six.text_type):
super(Mask, self).__init__()
self.parse(mask)
elif isinstance(mask, (dict, OrderedDict)):
super(Mask, self).__init__(mask, **kwargs)
else:
self.skip = skip
super(Mask, self).__init__(**kwargs)
def parse(self, mask):
'''
Parse a fields mask.
Expect something in the form::
{field,nested{nested_field,another},last}
External brackets are optionals so it can also be written::
field,nested{nested_field,another},last
All extras characters will be ignored.
:param str mask: the mask string to parse
:raises ParseError: when a mask is unparseable/invalid
'''
if not mask:
return
mask = self.clean(mask)
fields = self
previous = None
stack = []
for token in LEXER.findall(mask):
if token == '{':
if previous not in fields:
raise ParseError('Unexpected opening bracket')
fields[previous] = Mask(skip=self.skip)
stack.append(fields)
fields = fields[previous]
elif token == '}':
if not stack:
raise ParseError('Unexpected closing bracket')
fields = stack.pop()
elif token == ',':
if previous in (',', '{', None):
raise ParseError('Unexpected coma')
else:
fields[token] = True
previous = token
if stack:
raise ParseError('Missing closing bracket')
def clean(self, mask):
'''Remove unecessary characters'''
mask = mask.replace('\n', '').strip()
# External brackets are optional
if mask[0] == '{':
if mask[-1] != '}':
raise ParseError('Missing closing bracket')
mask = mask[1:-1]
return mask
def apply(self, data):
'''
Apply a fields mask to the data.
:param data: The data or model to apply mask on
:raises MaskError: when unable to apply the mask
'''
from . import fields
# Should handle lists
if isinstance(data, (list, tuple, set)):
return [self.apply(d) for d in data]
elif isinstance(data, (fields.Nested, fields.List, fields.Polymorph)):
return data.clone(self)
elif type(data) == fields.Raw:
return fields.Raw(default=data.default, attribute=data.attribute, mask=self)
elif data == fields.Raw:
return fields.Raw(mask=self)
elif isinstance(data, fields.Raw) or isclass(data) and issubclass(data, fields.Raw):
# Not possible to apply a mask on these remaining fields types
raise MaskError('Mask is inconsistent with model')
# Should handle objects
elif (not isinstance(data, (dict, OrderedDict)) and hasattr(data, '__dict__')):
data = data.__dict__
return self.filter_data(data)
def filter_data(self, data):
'''
Handle the data filtering given a parsed mask
:param dict data: the raw data to filter
:param list mask: a parsed mask tofilter against
:param bool skip: whether or not to skip missing fields
'''
out = {}
for field, content in self.items():
if field == '*':
continue
elif isinstance(content, Mask):
nested = data.get(field, None)
if self.skip and nested is None:
continue
elif nested is None:
out[field] = None
else:
out[field] = content.apply(nested)
elif self.skip and field not in data:
continue
else:
out[field] = data.get(field, None)
if '*' in self.keys():
for key, value in data.items():
if key not in out:
out[key] = value
return out
def __str__(self):
return '{{{0}}}'.format(','.join([
''.join((k, str(v))) if isinstance(v, Mask) else k
for k, v in self.items()
]))
def apply(data, mask, skip=False):
'''
Apply a fields mask to the data.
:param data: The data or model to apply mask on
:param str|Mask mask: the mask (parsed or not) to apply on data
:param bool skip: If rue, missing field won't appear in result
:raises MaskError: when unable to apply the mask
'''
return Mask(mask, skip).apply(data)
| [
"noreply@github.com"
] | PradhyuS86.noreply@github.com |
9b900d3fa4cad7cbc4bed1a9c17a96a974529dae | 6b6667b5d2e59265fbfcdc3974b6384b93340df3 | /hdiyf/utils.py | c45d28411143b875ad2f0ebb85bd786251e370c4 | [] | no_license | lmanhes/hdiyf-backend | e62f00b160575519df4dc03e14c9ee37333d1731 | 494210e1e346b06c9079810c822608cf4d7f923c | refs/heads/main | 2022-12-31T08:27:35.917704 | 2020-10-12T18:22:01 | 2020-10-12T18:22:01 | 301,686,794 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,474 | py | import numpy as np
import torch
import torch.nn as nn
from gensim.models import KeyedVectors
def calculate_maxlen(docs, percentile=90):
return int(np.percentile(np.array([len(doc) for doc in docs]), percentile))
def init_embedding(input_embedding):
"""
Initialize embedding tensor with values from the uniform distribution.
:param input_embedding: embedding tensor
"""
bias = np.sqrt(3.0 / input_embedding.size(1))
nn.init.uniform_(input_embedding, -bias, bias)
def load_word2vec_embeddings(word2vec_file, word_map, from_object=False):
"""
Load pre-trained embeddings for words in the word map.
:param word2vec_file: location of the trained word2vec model
:param word_map: word map
:return: embeddings for words in the word map, embedding size
"""
if from_object:
w2v = word2vec_file
else:
# Load word2vec model into memory
w2v = KeyedVectors.load_word2vec_format(word2vec_file,
binary=True,
unicode_errors='ignore')
# Create tensor to hold embeddings for words that are in-corpus
bias = np.sqrt(3.0 / w2v.vector_size)
embeddings = np.random.uniform(-bias, bias, size=(len(word_map), w2v.vector_size))
# Read embedding file
for word in word_map:
if word in w2v.vocab:
embeddings[word_map[word]] = w2v[word]
return embeddings, w2v.vector_size | [
"narraflow@gmail.com"
] | narraflow@gmail.com |
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