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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2020/6/21 11:13
# @Author : CoderCharm
# @File : custom_exc.py
# @Software: PyCharm
# @Desc :
"""
自定义异常
"""
class PostParamsError(Exception):
def __init__(self, err_desc: str = "POST请求参数错误"):
self.err_desc = err_desc
class TokenAuthError(Exception):
def __init__(self, err_desc: str = "token认证失败"):
self.err_desc = err_desc
|
s = input()
y = int(input())
n = int(input())
c = 0
for i in s:
if int(i) <= y:
c += 1
for i in range(n):
for j in range(2, n-1):
if int(s[i:j+i]) <= y:
c += 1
print(c)
'''
qx = [i for i in range(input1)]
for i, j in input3:
if i == 1:
qx = qx[1:]
if i == 2:
qx.remove(j)
if i == 3:
return qx.index(j)
'''
|
def to_braket(array):
""" helper for pretty printing """
state = []
basis = ('|00>', '|10>', '|01>', '|11>')
for im, base_state in zip(array, basis):
if im:
if abs(im.imag)>0.001:
state.append(f'{im.real:.1f}{base_state}')
else:
state.append(f'({im:.1f}){base_state}')
return " + ".join(state)
|
def is_balanced(s):
pairs = {"(": ")", "[": "]", "{": "}"}
stack = []
for ch in s:
if ch in pairs:
stack.append(ch)
else:
if len(stack) == 0:
return False
if pairs[stack.pop()] != ch:
return False
return len(stack) == 0
|
def generate(label):
(
bbox_xmin,
bbox_ymin,
bbox_xmax,
bbox_ymax,
img_width,
img_height
) = (
label.get('xmin'),
label.get('ymin'),
label.get('xmax'),
label.get('ymax'),
label.get('img_width'),
label.get('img_height')
)
dw = 1. / img_width
dh = 1. / img_height
x = (bbox_xmin + bbox_xmax) / 2.0
y = (bbox_ymin + bbox_ymax) / 2.0
w = bbox_xmax - bbox_xmin
h = bbox_ymax - bbox_ymin
x = x * dw
w = w * dw
y = y * dh
h = h * dh
return (x, y, w, h)
|
"""
A solution should include:
1. Benchmark scenario;
2. get_actions() method;
3. get_states() method.
"""
# Specify benchmark scenario below.
BENCHMARK = "" # Benchmark name goes here...
# Specify get_action() method below.
def get_actions(state):
# get_actions() code goes here...
return
# Specify get_state() method below.
def get_states(env, **kwargs):
# get_states() code goes here...
return
|
print("hello")
count=1
if count<1:
print("yes")
else:
print("no")
|
"""
Determine whether an integer is a palindrome. An integer is a palindrome when it reads the same backward as forward.
Example 1:
Input: 121
Output: true
Example 2:
Input: -121
Output: false
Explanation: From left to right, it reads -121. From right to left, it becomes 121-. Therefore it is not a palindrome.
Example 3:
Input: 10
Output: false
Explanation: Reads 01 from right to left. Therefore it is not a palindrome.
Follow up:
Coud you solve it without converting the integer to a string?
判断一个数是不是回文数？ 既然已经知道如何反转了， 直接反转一发
"""
class Solution:
def isPalindrome(self, x):
"""
:type x: int
:rtype: bool
"""
if x == 0:
return True
if x < 0 or x % 10 == 0:
return False
m = 0
y = x
while (x > 0):
m = m * 10 + x % 10
x //= 10
return m == y
|
# functions
print("Demonstrating functions....")
def fun():
print("Printing my function: fun")
def fun1():
print("Printing my function: fun1")
def multiply(x, y):
z = x * y
return z
mulnum = multiply(150, 160)
print(f"The return value is {mulnum}")
# Demonstrating lambda functions
# Lambda functions are anonymous functions
x = lambda a: a + 10
print(f'The value of x is {x}')
y = x(5)
print(f'The value of y is {y}')
|
class MCP3008():
def __init__(self, channel):
self.fake_val = 0
def value(self, pin=None):
return self.fake_val
|
firt_tuple = (5,5,4,6,1,2,3)
new_list = list(firt_tuple)
new_tuple = tuple(new_list)
print(len(firt_tuple))
print(max(new_list))
print(min(new_tuple))
|
# Please note that if you uncomment and press multiple times, the program will keep appending to the file.
def cap_four(name):
new_name = name[0].upper() + name[1:3] + name[3].upper() + name[4:]
return new_name
# Check
answer = cap_four('macdonald')
print(answer)
|
class Solution:
def isPalindrome(self, s: str) -> bool:
s=s.lower()
s=[x for x in s if x.isalnum() ]
return s==s[::-1]
|
#Создание двух таблиц Вижинера
tablu = [[0 for i in range(0, 26)] for j in range(0, 26)]
tabll = [[0 for i in range(0, 26)] for j in range(0, 26)]
alphu = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
alphl = "abcdefghijklmnopqrstuvwxyz"
s1 = ""
s2 = ""
for i in range(26):
s1 = alphu[i:]
s2 = alphu[:i]
s = s1 + s2
for j in range(26):
tablu[i][j] = s[j]
for i in range(26):
s1 = alphl[i:]
s2 = alphl[:i]
s = s1 + s2
for j in range(26):
tabll[i][j] = s[j]
#Функция шифрования
def enc(inp, k):
i = 0
j = 0
rez = ""
while i < len(inp):
if k[j] in alphu:
b = alphu.index(k[j])
else:
b = alphl.index(k[j])
if inp[i] in alphu:
a = alphu.index(inp[i])
rez += tablu[a][b]
else:
a = alphl.index(inp[i])
rez += tabll[a][b]
i += 1
j += 1
if j == len(k):
j = 0
return rez
#Функция дешифровки
def dec(inp, k):
i = 0
j = 0
rez = ""
while i < len(inp):
g = 0
f = True
if k[j] in alphu:
b = tablu[g].index(k[j])
elif k[j] in alphl:
b = tabll[g].index(k[j])
while g < 26 and f:
if inp[i] in alphu:
au = tablu[g].index(inp[i])
if au == b:
rez += tablu[g][0]
f = False
elif inp[i] in alphl:
al = tabll[g].index(inp[i])
if al == b:
rez += tabll[g][0]
f = False
g += 1
i += 1
j += 1
if j == len(k):
j = 0
return rez
|
#Faça um Programa que leia 20 números inteiros e
#armazene-os num vetor. Armazene os números pares no
#vetor PAR e os números IMPARES no vetor impar. Imprima
#os três vetores.
vetor=[]
vetorP=[]
vetorI=[]
for c in range(0,7):
vetor.append(int(input("Informe um numero: ")))
if(vetor[c]%2==0):
vetorP.append(vetor[c])
else:
vetorI.append(vetor[c])
print(vetor)
print(vetorP)
print(vetorI)
|
print('\033[31m-=-' * 9)
print('\033[35mCalculador de Média')
print('\033[31m-=-' * 9)
n1 = float(input('\033[94mPrimeira nota do aluno: '))
n2 = float(input('Segunda nota do aluno: '))
print('\033[94mA média entre \033[1m{:.1f}\033[22m e \033[1m{:.1f}\033[22m é igual a \033[1m{:.1f}\033[22m.'
.format(n1, n2, (n1 + n2) / 2))
|
if _:
l = 2
else:
l = []
|
class Solution(object):
def partition(self, s):
"""
:type s: str
:rtype: List[List[str]]
"""
substring = []
substrings = []
self.recursive(s, substring, substrings)
return substrings
def recursive(self, s, substring, substrings):
if not s:
substrings.append(substring)
return None
for i in range(1, len(s) + 1):
if self.isPalindrome(s[0:i]):
self.recursive(s[i:len(s)], substring + [s[0:i]], substrings)
def isPalindrome(self, s):
return s == s[::-1]
|
MONTHS = {
'january': 1,
'february': 2,
'march': 3,
'april': 4,
'may': 5,
'june': 6,
'july': 7,
'august': 8,
'september': 9,
'october': 10,
'november': 11,
'december': 12,
}
SHORT_MONTH = [
'',
'Jan', 'Feb', 'Mar', 'Apr',
'May', 'Jun', 'Jul', 'Aug',
'Sep', 'Oct', 'Nov', 'Dec',
]
|
# Iterative approach - Time-Complexity = O(k), Space-Complexity = O(1)
# k is the no of digits
def replaceZeros(num):
num += calculateAddedValue(num)
return num
def calculateAddedValue(num):
decimal_place = 1
result = 0
if num == 0:
result += decimal_place * 5
while num > 0:
if num % 10 == 0:
result += (5 * decimal_place)
num = num // 10
decimal_place = decimal_place * 10
return result
a = 102
print(replaceZeros(a))
"""def replaceZero(str):
a = list(str)
for i in range(len(a)):
if a[i] == '0':
a[i] = '5'
a ="".join(a)
return a
"""
|
# Copyright (c) 2009 Google Inc. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
{
'targets': [
{
'target_name': 'subdir_file',
'type': 'none',
'msvs_cygwin_shell': 0,
'actions': [
{
'action_name': 'make-subdir-file',
'inputs': [
'make-subdir-file.py',
],
'outputs': [
'<(PRODUCT_DIR)/subdir_file.out',
],
'action': [
'python', '<(_inputs)', '<@(_outputs)',
],
'process_outputs_as_sources': 1,
}
],
},
],
}
|
"""Project Euler problem 3"""
def sqrt(number):
"""Returns the square root of the specified number as an int, rounded down"""
assert number >= 0
offset = 1
while offset ** 2 <= number:
offset *= 2
count = 0
while offset > 0:
if (count + offset) ** 2 <= number:
count += offset
offset //= 2
return count
def smallest_prime_factor(number):
"""Returns the smallest prime factor of the specified number"""
assert number >= 2
for potential in range(2, sqrt(number) + 1):
if number % potential == 0:
return potential
return number
def calculate(number):
"""Returns the largest prime factor of the specified number"""
while True:
smallest = smallest_prime_factor(number)
if number > smallest:
number //= smallest
else:
answer = number
return answer
if __name__ == "__main__":
print(calculate(600851475143))
|
# nCk
n, m = map(int, input().split(' '))
# numerator
numerator = 1
for i in range(0, m):
numerator *= n
n -= 1
# denominator
denominator = 1
for i in range(m, 0, -1):
denominator *= i
print(numerator // denominator)
|
# -*- coding: utf-8 -*-
"""
Created on Sun Jun 24 16:26:56 2018
@author: joshu
"""
letter_z = 'z'
num_3 = '3'
a_space = ' '
# Check if all characters are numbers
print("Is z a letter or number: ", letter_z.isalnum())
# Checks if all characters are alphabetical
print("Is z a letter: ", letter_z.isalpha())
# Check if num_3 is a number
print("Is 3 a number: ", num_3.isdigit())
# Checks if letter_z is lowercase
print("Is z a lowercase: ", letter_z.islower())
# Checks if letter_z is uppercase
print("Is z a uppercase: ", letter_z.isupper())
# Checks if a_space is a space
print("Is a space a space: ", a_space.isspace())
def isfloat(str_val):
try:
float(str_val)
return True
except ValueError:
return False
print("Is Pi a float: ",isfloat(3.14))
|
'''
Problem Statement:
-----------------
Given an array A of size N of integers. Your task is to find the minimum and maximum elements in the array.
Example 1:
---------
Input:
N = 6
A[] = {3, 2, 1, 56, 10000, 167}
Output:
min = 1, max = 10000
Example 2:
----------
Input:
N = 5
A[] = {1, 345, 234, 21, 56789}
Output:
min = 1, max = 56789
'''
# Link ---> https://practice.geeksforgeeks.org/problems/find-minimum-and-maximum-element-in-an-array4428/1
# Code:
def getMinMax(a , n):
ls = []
min = a[0]
max = a[0]
for i in a:
if(min > i):
min = i;
elif(max < i):
max = i;
ls.append(min)
ls.append(max)
return ls
|
class Enum(object):
def __init__(self, plugin, node):
if node.tag != 'enum':
raise ValueError('expected <enum>, got <%s>' % node.tag)
self.plugin = plugin
self.name = node.attrib['name']
self.item_prefix = node.attrib.get('item-prefix', '')
self.base = int(node.attrib.get('base', 0))
self.items = [n.attrib['name'] for n in node.findall('item')]
|
connChoices = (
{'name': 'automatic',
'rate': {'min': 0, 'max': 5000, 'def': 0},
'conn': {'min': 0, 'max': 100, 'def': 0},
'automatic': 1},
{'name': 'unlimited',
'rate': {'min': 0, 'max': 5000, 'def': 0, 'div': 50},
'conn': {'min': 4, 'max': 100, 'def': 4}},
{'name': 'dialup/isdn',
'rate': {'min': 3, 'max': 8, 'def': 5},
'conn': {'min': 2, 'max': 3, 'def': 2},
'initiate': 12},
{'name': 'dsl/cable slow',
'rate': {'min': 10, 'max': 48, 'def': 13},
'conn': {'min': 4, 'max': 20, 'def': 4}},
{'name': 'dsl/cable fast',
'rate': {'min': 20, 'max': 100, 'def': 40},
'conn': {'min': 4, 'max': 30, 'def': 6}},
{'name': 'T1',
'rate': {'min': 100, 'max': 300, 'def': 150},
'conn': {'min': 4, 'max': 40, 'def': 10}},
{'name': 'T3+',
'rate': {'min': 400, 'max': 2000, 'def': 500},
'conn': {'min': 4, 'max': 100, 'def': 20}},
{'name': 'seeder',
'rate': {'min': 0, 'max': 5000, 'def': 0, 'div': 50},
'conn': {'min': 1, 'max': 100, 'def': 1}},
{'name': 'SUPER-SEED', 'super-seed': 1}
)
connChoiceList = map(lambda x: x['name'], connChoices)
|
#
# PySNMP MIB module HUAWEI-MA5200-DEVICE-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/HUAWEI-MA5200-DEVICE-MIB
# Produced by pysmi-0.3.4 at Wed May 1 13:46:33 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
Integer, ObjectIdentifier, OctetString = mibBuilder.importSymbols("ASN1", "Integer", "ObjectIdentifier", "OctetString")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ConstraintsIntersection, SingleValueConstraint, ValueSizeConstraint, ConstraintsUnion, ValueRangeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsIntersection", "SingleValueConstraint", "ValueSizeConstraint", "ConstraintsUnion", "ValueRangeConstraint")
hwFrameIndex, hwSlotIndex = mibBuilder.importSymbols("HUAWEI-DEVICE-MIB", "hwFrameIndex", "hwSlotIndex")
hwMA5200Mib, = mibBuilder.importSymbols("HUAWEI-MIB", "hwMA5200Mib")
HWFrameType, HWPCBType, HWPortType, HWSubPCBType = mibBuilder.importSymbols("HUAWEI-TC-MIB", "HWFrameType", "HWPCBType", "HWPortType", "HWSubPCBType")
VlanIdOrNone, VlanId = mibBuilder.importSymbols("Q-BRIDGE-MIB", "VlanIdOrNone", "VlanId")
ModuleCompliance, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ModuleCompliance", "NotificationGroup")
Integer32, Counter64, iso, MibScalar, MibTable, MibTableRow, MibTableColumn, ModuleIdentity, IpAddress, MibIdentifier, TimeTicks, Unsigned32, Counter32, NotificationType, ObjectIdentity, Gauge32, Bits = mibBuilder.importSymbols("SNMPv2-SMI", "Integer32", "Counter64", "iso", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "ModuleIdentity", "IpAddress", "MibIdentifier", "TimeTicks", "Unsigned32", "Counter32", "NotificationType", "ObjectIdentity", "Gauge32", "Bits")
MacAddress, DisplayString, DateAndTime, TextualConvention, RowStatus, TruthValue = mibBuilder.importSymbols("SNMPv2-TC", "MacAddress", "DisplayString", "DateAndTime", "TextualConvention", "RowStatus", "TruthValue")
hwMA5200Device = ModuleIdentity((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201))
if mibBuilder.loadTexts: hwMA5200Device.setLastUpdated('200408300900Z')
if mibBuilder.loadTexts: hwMA5200Device.setOrganization(' NanJing Institute,Huawei Technologies Co.,Ltd. HuiHong Mansion,No.91 BaiXia Rd. NanJing, P.R. of China Zipcode:210001 Http://www.huawei.com E-mail:support@huawei.com ')
if mibBuilder.loadTexts: hwMA5200Device.setContactInfo('The MIB contains objects of module MA5200 device.')
if mibBuilder.loadTexts: hwMA5200Device.setDescription('Huawei ma5200 device mib.')
hw52DevSlot = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 1))
hw52DevSlotNum = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 255))).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevSlotNum.setStatus('current')
if mibBuilder.loadTexts: hw52DevSlotNum.setDescription(' The slot number. ')
hw52DevSubSlotNum = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 1, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 255))).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevSubSlotNum.setStatus('current')
if mibBuilder.loadTexts: hw52DevSubSlotNum.setDescription(' THe sub Slot number. ')
hw52DevPortNum = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 1, 3), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 255))).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevPortNum.setStatus('current')
if mibBuilder.loadTexts: hw52DevPortNum.setDescription(' The port number. ')
hw52DevPortOperateStatus = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 1, 4), Integer32()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevPortOperateStatus.setStatus('current')
if mibBuilder.loadTexts: hw52DevPortOperateStatus.setDescription(' The port Operate Status. ')
hw52DevSlotTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 2))
hw52DevSlotReset = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 2, 1006)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevSlotReset.setStatus('current')
if mibBuilder.loadTexts: hw52DevSlotReset.setDescription(' The trap report of slot reset. ')
hw52DevSlotRegOK = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 2, 1007)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevSlotRegOK.setStatus('current')
if mibBuilder.loadTexts: hw52DevSlotRegOK.setDescription(' The trap report of slot register OK. ')
hw52DevSlotPlugOut = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 2, 1008)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevSlotPlugOut.setStatus('current')
if mibBuilder.loadTexts: hw52DevSlotPlugOut.setDescription(' The trap report of slot plug out. ')
hwHdDev = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 5))
hwHdDevTable = MibTable((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 5, 1), )
if mibBuilder.loadTexts: hwHdDevTable.setStatus('current')
if mibBuilder.loadTexts: hwHdDevTable.setDescription(' This table contains harddisk information. ')
hwHdDevEntry = MibTableRow((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 5, 1, 1), ).setIndexNames((0, "HUAWEI-DEVICE-MIB", "hwFrameIndex"), (0, "HUAWEI-DEVICE-MIB", "hwSlotIndex"), (0, "HUAWEI-MA5200-DEVICE-MIB", "hwHdDevIndex"))
if mibBuilder.loadTexts: hwHdDevEntry.setStatus('current')
if mibBuilder.loadTexts: hwHdDevEntry.setDescription(' The table entry of harddisk information. ')
hwHdDevIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 5, 1, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 65535)))
if mibBuilder.loadTexts: hwHdDevIndex.setStatus('current')
if mibBuilder.loadTexts: hwHdDevIndex.setDescription(' The index of harddisk information table. ')
hwHdDevSize = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 5, 1, 1, 2), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: hwHdDevSize.setStatus('current')
if mibBuilder.loadTexts: hwHdDevSize.setDescription(' Total Size in Octets of harddisk memory. ')
hwHdDevFree = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 5, 1, 1, 3), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: hwHdDevFree.setStatus('current')
if mibBuilder.loadTexts: hwHdDevFree.setDescription(' Unused Size in Octets of harddisk memory. ')
hw52DevPortTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 6))
hw52DevPortUp = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 6, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSubSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortOperateStatus"))
if mibBuilder.loadTexts: hw52DevPortUp.setStatus('current')
if mibBuilder.loadTexts: hw52DevPortUp.setDescription(' Port up. ')
hw52DevPortDown = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 6, 2)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSubSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortOperateStatus"))
if mibBuilder.loadTexts: hw52DevPortDown.setStatus('current')
if mibBuilder.loadTexts: hw52DevPortDown.setDescription(' Port down. ')
hw52DevUserAttackInfo = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 7))
hw52DevUserIPAddr = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 7, 1), IpAddress()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevUserIPAddr.setStatus('current')
if mibBuilder.loadTexts: hw52DevUserIPAddr.setDescription(" The user's IP address. ")
hw52DevUserMac = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 7, 2), MacAddress()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevUserMac.setStatus('current')
if mibBuilder.loadTexts: hw52DevUserMac.setDescription(" The user's MAC address. ")
hw52DevUserIndex = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 7, 3), Integer32()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevUserIndex.setStatus('current')
if mibBuilder.loadTexts: hw52DevUserIndex.setDescription(' The index of user, could be vlan id, Session id or VCD according with the type of user. ')
hw52DevUserOuterVlan = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 7, 4), VlanIdOrNone()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevUserOuterVlan.setStatus('current')
if mibBuilder.loadTexts: hw52DevUserOuterVlan.setDescription(' The outer vlan. ')
hw52DevUserAttack = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 8))
hw52DevUserAttackTrap = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 8, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserIPAddr"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserMac"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSubSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserIndex"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserOuterVlan"))
if mibBuilder.loadTexts: hw52DevUserAttackTrap.setStatus('current')
if mibBuilder.loadTexts: hw52DevUserAttackTrap.setDescription(' The trap report of user attack. ')
hw52TrapSwitch = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 9))
hw52HwdeviceOrBasetrap = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 9, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3))).clone(namedValues=NamedValues(("disable", 1), ("hwdevice", 2), ("basetrap", 3)))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: hw52HwdeviceOrBasetrap.setStatus('current')
if mibBuilder.loadTexts: hw52HwdeviceOrBasetrap.setDescription(' Trap switches between basetrap and hwdevice. ')
hw52DevMemUsage = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 10))
hw52DevMemUsageThreshold = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 10, 1), Integer32()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevMemUsageThreshold.setStatus('current')
if mibBuilder.loadTexts: hw52DevMemUsageThreshold.setDescription(' Memory usage threshold. ')
hw52DevMemUsageTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 11))
hw52DevMemUsageAlarm = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 11, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevMemUsageThreshold"))
if mibBuilder.loadTexts: hw52DevMemUsageAlarm.setStatus('current')
if mibBuilder.loadTexts: hw52DevMemUsageAlarm.setDescription(' Memory usage alarm. ')
hw52DevMemUsageResume = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 11, 2)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevMemUsageThreshold"))
if mibBuilder.loadTexts: hw52DevMemUsageResume.setStatus('current')
if mibBuilder.loadTexts: hw52DevMemUsageResume.setDescription(' Memory usage alarm resum. ')
hw52DevStartupFileFail = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 12))
hw52DevDefaultStartupFileName = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 12, 1), OctetString()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevDefaultStartupFileName.setStatus('current')
if mibBuilder.loadTexts: hw52DevDefaultStartupFileName.setDescription(' Default startup file name. ')
hw52DevCurrentStartupFileName = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 12, 2), OctetString()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevCurrentStartupFileName.setStatus('current')
if mibBuilder.loadTexts: hw52DevCurrentStartupFileName.setDescription(' Current startup file name. ')
hw52DevStartupFileFailTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 13))
hw52DevStartupFileReloadAlarm = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 13, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevDefaultStartupFileName"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevCurrentStartupFileName"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevStartupFileReloadAlarm.setStatus('current')
if mibBuilder.loadTexts: hw52DevStartupFileReloadAlarm.setDescription(' Startup file load fail alarm. ')
hw52DevDiskSelfTestFail = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 14))
hw52DevDiskSelfTestDiskType = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 14, 1), OctetString()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevDiskSelfTestDiskType.setStatus('current')
if mibBuilder.loadTexts: hw52DevDiskSelfTestDiskType.setDescription(' Disk type: cfcard or harddisk. ')
hw52DevDiskSelfTestFailStep = MibScalar((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 14, 2), OctetString()).setMaxAccess("accessiblefornotify")
if mibBuilder.loadTexts: hw52DevDiskSelfTestFailStep.setStatus('current')
if mibBuilder.loadTexts: hw52DevDiskSelfTestFailStep.setDescription(' Disk self-test fail step. ')
hw52DevDiskSelfTestFailTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 15))
hw52DevDiskSelfTestFailAlarm = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 15, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevDiskSelfTestDiskType"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevDiskSelfTestFailStep"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevDiskSelfTestFailAlarm.setStatus('current')
if mibBuilder.loadTexts: hw52DevDiskSelfTestFailAlarm.setDescription(' Disk selftest error alarm. ')
hw52DevCfUnregisterTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 16))
hw52DevCfUnregisteredAlarm = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 16, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevCfUnregisteredAlarm.setStatus('current')
if mibBuilder.loadTexts: hw52DevCfUnregisteredAlarm.setDescription(' Cf card unregistered. ')
hw52DevHpt372ErrorTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 17))
hw52DevHpt372ErrorAlarm = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 17, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevHpt372ErrorAlarm.setStatus('current')
if mibBuilder.loadTexts: hw52DevHpt372ErrorAlarm.setDescription(' Hpt372 occur error. ')
hw52DevHarddiskUsageTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 18))
hw52DevHarddiskUsageAlarm = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 18, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevHarddiskUsageAlarm.setStatus('current')
if mibBuilder.loadTexts: hw52DevHarddiskUsageAlarm.setDescription(' Harddisk usage alarm. ')
hw52DevHarddiskUsageResume = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 18, 2)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevHarddiskUsageResume.setStatus('current')
if mibBuilder.loadTexts: hw52DevHarddiskUsageResume.setDescription(' Harddisk usage alarm resume. ')
hw52PacketError = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 19))
hw52InPacketErrorTrap = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 19, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSubSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortNum"))
if mibBuilder.loadTexts: hw52InPacketErrorTrap.setStatus('current')
if mibBuilder.loadTexts: hw52InPacketErrorTrap.setDescription(' In packet error. ')
hw52OutPacketErrorTrap = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 19, 2)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSubSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortNum"))
if mibBuilder.loadTexts: hw52OutPacketErrorTrap.setStatus('current')
if mibBuilder.loadTexts: hw52OutPacketErrorTrap.setDescription(' Out packet error. ')
hw52DevCfcardUsageTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 20))
hw52DevCfcardUsageAlarm = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 20, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevCfcardUsageAlarm.setStatus('current')
if mibBuilder.loadTexts: hw52DevCfcardUsageAlarm.setDescription(' Cfcard usage alarm. ')
hw52DevCfcardUsageResume = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 20, 2)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevCfcardUsageResume.setStatus('current')
if mibBuilder.loadTexts: hw52DevCfcardUsageResume.setDescription(' Cfcard usage alarm resume. ')
hw52DevFlashUsageTrap = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 21))
hw52DevFlashUsageAlarm = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 21, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevFlashUsageAlarm.setStatus('current')
if mibBuilder.loadTexts: hw52DevFlashUsageAlarm.setDescription(' Flash usage alarm. ')
hw52DevFlashUsageResume = NotificationType((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 21, 2)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"))
if mibBuilder.loadTexts: hw52DevFlashUsageResume.setStatus('current')
if mibBuilder.loadTexts: hw52DevFlashUsageResume.setDescription(' Flash usage alarm resume. ')
hw52DevConformance = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 200))
hw52DevCompliances = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 200, 1))
hw52DevCompliance = ModuleCompliance((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 200, 1, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotGroup"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevHdTableGroup"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevTrapsGroup"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevTrapObjectsGroup"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
hw52DevCompliance = hw52DevCompliance.setStatus('current')
if mibBuilder.loadTexts: hw52DevCompliance.setDescription('The compliance statement for systems supporting the this module.')
hw52DevObjectGroups = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 200, 2))
hw52DevSlotGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 200, 2, 1)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSubSlotNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortNum"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortOperateStatus"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
hw52DevSlotGroup = hw52DevSlotGroup.setStatus('current')
if mibBuilder.loadTexts: hw52DevSlotGroup.setDescription('The MA5200 device slot group objects.')
hw52DevHdTableGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 200, 2, 2)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hwHdDevSize"), ("HUAWEI-MA5200-DEVICE-MIB", "hwHdDevFree"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
hw52DevHdTableGroup = hw52DevHdTableGroup.setStatus('current')
if mibBuilder.loadTexts: hw52DevHdTableGroup.setDescription('The MA5200 device harddisk information table group.')
hw52DevTrapsGroup = NotificationGroup((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 200, 2, 3)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotReset"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotRegOK"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevSlotPlugOut"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortUp"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevPortDown"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserAttackTrap"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevMemUsageAlarm"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevMemUsageResume"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevStartupFileReloadAlarm"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevDiskSelfTestFailAlarm"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevCfUnregisteredAlarm"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevHpt372ErrorAlarm"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevHarddiskUsageAlarm"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevHarddiskUsageResume"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52InPacketErrorTrap"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52OutPacketErrorTrap"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevCfcardUsageAlarm"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevCfcardUsageResume"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevFlashUsageAlarm"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevFlashUsageResume"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
hw52DevTrapsGroup = hw52DevTrapsGroup.setStatus('current')
if mibBuilder.loadTexts: hw52DevTrapsGroup.setDescription('The MA5200 device traps group.')
hw52DevTrapObjectsGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 2011, 2, 6, 2, 201, 200, 2, 4)).setObjects(("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserIPAddr"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserMac"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserIndex"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevUserOuterVlan"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52HwdeviceOrBasetrap"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevMemUsageThreshold"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevDefaultStartupFileName"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevCurrentStartupFileName"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevDiskSelfTestDiskType"), ("HUAWEI-MA5200-DEVICE-MIB", "hw52DevDiskSelfTestFailStep"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
hw52DevTrapObjectsGroup = hw52DevTrapObjectsGroup.setStatus('current')
if mibBuilder.loadTexts: hw52DevTrapObjectsGroup.setDescription('The objects of MA5200 device traps group.')
mibBuilder.exportSymbols("HUAWEI-MA5200-DEVICE-MIB", hwHdDevFree=hwHdDevFree, hw52DevHarddiskUsageResume=hw52DevHarddiskUsageResume, hw52DevConformance=hw52DevConformance, hw52DevObjectGroups=hw52DevObjectGroups, hw52DevMemUsageTrap=hw52DevMemUsageTrap, hw52DevHdTableGroup=hw52DevHdTableGroup, hw52DevTrapObjectsGroup=hw52DevTrapObjectsGroup, hw52DevSubSlotNum=hw52DevSubSlotNum, hw52DevCfcardUsageResume=hw52DevCfcardUsageResume, hw52DevHpt372ErrorAlarm=hw52DevHpt372ErrorAlarm, hw52HwdeviceOrBasetrap=hw52HwdeviceOrBasetrap, hw52DevMemUsageResume=hw52DevMemUsageResume, hwHdDevIndex=hwHdDevIndex, hw52DevUserAttackInfo=hw52DevUserAttackInfo, hw52DevSlotReset=hw52DevSlotReset, hw52DevSlot=hw52DevSlot, hw52DevMemUsageAlarm=hw52DevMemUsageAlarm, hw52DevUserIndex=hw52DevUserIndex, hw52DevFlashUsageAlarm=hw52DevFlashUsageAlarm, hw52DevMemUsageThreshold=hw52DevMemUsageThreshold, hw52DevDefaultStartupFileName=hw52DevDefaultStartupFileName, hw52DevHarddiskUsageAlarm=hw52DevHarddiskUsageAlarm, hw52DevPortTrap=hw52DevPortTrap, hw52DevUserIPAddr=hw52DevUserIPAddr, hw52TrapSwitch=hw52TrapSwitch, hwHdDevEntry=hwHdDevEntry, hw52DevDiskSelfTestFail=hw52DevDiskSelfTestFail, hw52DevSlotPlugOut=hw52DevSlotPlugOut, hwHdDevSize=hwHdDevSize, hw52DevUserAttack=hw52DevUserAttack, hw52DevPortUp=hw52DevPortUp, hw52DevStartupFileFail=hw52DevStartupFileFail, hw52DevDiskSelfTestDiskType=hw52DevDiskSelfTestDiskType, hw52DevDiskSelfTestFailAlarm=hw52DevDiskSelfTestFailAlarm, hw52DevCfUnregisteredAlarm=hw52DevCfUnregisteredAlarm, hw52DevTrapsGroup=hw52DevTrapsGroup, hw52DevCurrentStartupFileName=hw52DevCurrentStartupFileName, hw52DevFlashUsageTrap=hw52DevFlashUsageTrap, hw52DevCompliances=hw52DevCompliances, hw52DevSlotGroup=hw52DevSlotGroup, hwHdDev=hwHdDev, hw52DevDiskSelfTestFailTrap=hw52DevDiskSelfTestFailTrap, hw52PacketError=hw52PacketError, hw52InPacketErrorTrap=hw52InPacketErrorTrap, hw52DevStartupFileFailTrap=hw52DevStartupFileFailTrap, hw52DevCfUnregisterTrap=hw52DevCfUnregisterTrap, hw52DevCfcardUsageTrap=hw52DevCfcardUsageTrap, hw52DevHarddiskUsageTrap=hw52DevHarddiskUsageTrap, hw52DevCfcardUsageAlarm=hw52DevCfcardUsageAlarm, hw52DevFlashUsageResume=hw52DevFlashUsageResume, hw52DevDiskSelfTestFailStep=hw52DevDiskSelfTestFailStep, hw52DevUserOuterVlan=hw52DevUserOuterVlan, hw52DevUserAttackTrap=hw52DevUserAttackTrap, hw52DevUserMac=hw52DevUserMac, hw52DevPortDown=hw52DevPortDown, hwHdDevTable=hwHdDevTable, hw52DevCompliance=hw52DevCompliance, hw52DevPortNum=hw52DevPortNum, hw52DevHpt372ErrorTrap=hw52DevHpt372ErrorTrap, hw52DevStartupFileReloadAlarm=hw52DevStartupFileReloadAlarm, hw52DevMemUsage=hw52DevMemUsage, hw52DevSlotNum=hw52DevSlotNum, hw52DevPortOperateStatus=hw52DevPortOperateStatus, hwMA5200Device=hwMA5200Device, PYSNMP_MODULE_ID=hwMA5200Device, hw52DevSlotRegOK=hw52DevSlotRegOK, hw52OutPacketErrorTrap=hw52OutPacketErrorTrap, hw52DevSlotTrap=hw52DevSlotTrap)
|
# -*- coding: utf-8 -*-
'''
File name: code\the_millionth_number_with_at_least_one_million_prime_factors\sol_615.py
Author: Vaidic Joshi
Date created: Oct 20, 2018
Python Version: 3.x
'''
# Solution to Project Euler Problem #615 :: The millionth number with at least one million prime factors
#
# For more information see:
# https://projecteuler.net/problem=615
# Problem Statement
'''
Consider the natural numbers having at least 5 prime factors, which don't have to be distinct. Sorting these numbers by size gives a list which starts with:
32=2⋅2⋅2⋅2⋅2
48=2⋅2⋅2⋅2⋅3
64=2⋅2⋅2⋅2⋅2⋅2
72=2⋅2⋅2⋅3⋅3
80=2⋅2⋅2⋅2⋅5
96=2⋅2⋅2⋅2⋅2⋅3
...
So, for example, the fifth number with at least 5 prime factors is 80.
Find the millionth number with at least one million prime factors. Give your answer modulo 123454321.
'''
# Solution
# Solution Approach
'''
'''
|
BOT_NAME = 'podcast_scraper'
SPIDER_MODULES = ['podcast_scraper.spiders']
NEWSPIDER_MODULE = 'podcast_scraper.spiders'
SCHEDULER_DEBUG = 'True'
LOG_LEVEL = 'DEBUG'
# LOG_FILE = './logs/log.txt'
# app.py will use OUTPUT_BUCKET to generate an OUTPUT_URI
# using OUTPUT_BUCKET and spider_name.
OUTPUT_BUCKET = 'output-rss-bucket-name'
ITEM_PIPELINES = {
'scrapy_podcast_rss.pipelines.PodcastPipeline': 300,
}
|
"""3. Inference with Quantized Models
=====================================
This is a tutorial which illustrates how to use quantized GluonCV
models for inference on Intel Xeon Processors to gain higher performance.
The following example requires ``GluonCV>=0.4`` and ``MXNet-mkl>=1.6.0b20190829``. Please follow `our installation guide <../../index.html#installation>`__ to install or upgrade GluonCV and nightly build of MXNet if necessary.
Introduction
------------
GluonCV delivered some quantized models to improve the performance and reduce the deployment costs for the computer vision inference tasks. In real production, there are two main benefits of lower precision (INT8). First, the computation can be accelerated by the low precision instruction, like Intel Vector Neural Network Instruction (VNNI). Second, lower precision data type would save the memory bandwidth and allow for better cache locality and save the power. The new feature can get up to 4X performance speedup in the latest `AWS EC2 C5 instances <https://aws.amazon.com/blogs/aws/now-available-new-c5-instance-sizes-and-bare-metal-instances/>`_ under the `Intel Deep Learning Boost (VNNI) <https://www.intel.ai/intel-deep-learning-boost/>`_ enabled hardware with less than 0.5% accuracy drop.
Please checkout `verify_pretrained.py <https://raw.githubusercontent.com/dmlc/gluon-cv/master/scripts/classification/imagenet/verify_pretrained.py>`_ for imagenet inference,
`eval_ssd.py <https://raw.githubusercontent.com/dmlc/gluon-cv/master/scripts/detection/ssd/eval_ssd.py>`_ for SSD inference, and `test.py <https://raw.githubusercontent.com/dmlc/gluon-cv/master/scripts/segmentation/test.py>`_
for segmentation inference.
Performance
-----------
GluonCV supports some quantized classification models, detection models and segmentation models.
For the throughput, the target is to achieve the maximum machine efficiency to combine the inference requests together and get the results by one iteration. From the bar-chart, it is clearly that the fusion and quantization approach improved the throughput from 2.68X to 7.24X for selected models.
Below CPU performance is collected with dummy input from AWS EC2 C5.12xlarge instance with 24 physical cores.
.. figure:: https://user-images.githubusercontent.com/34727741/64021961-a9105280-cb67-11e9-989e-76a29e58530d.png
:alt: Gluon Quantization Performance
.. table::
:widths: 45 5 5 10 10 5 10 10
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| Model | Dataset | Batch Size | C5.12xlarge FP32 | C5.12xlarge INT8 | Speedup | FP32 Accuracy | INT8 Accuracy |
+=======================+==========+============+==================+==================+=========+=================+=================+
| ResNet50 V1 | ImageNet | 128 | 191.17 | 1384.4 | 7.24 | 77.21%/93.55% | 76.08%/93.04% |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| MobileNet 1.0 | ImageNet | 128 | 565.21 | 3956.45 | 7.00 | 73.28%/91.22% | 71.94%/90.47% |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| SSD-VGG 300* | VOC | 224 | 19.05 | 113.62 | 5.96 | 77.4 | 77.38 |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| SSD-VGG 512* | VOC | 224 | 6.78 | 37.62 | 5.55 | 78.41 | 78.38 |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| SSD-resnet50_v1 512* | VOC | 224 | 28.59 | 143.7 | 5.03 | 80.21 | 80.25 |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| SSD-mobilenet1.0 512* | VOC | 224 | 65.97 | 212.59 | 3.22 | 75.42 | 74.70 |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| FCN_resnet101 | VOC | 1 | 5.46 | 26.33 | 4.82 | 97.97% | 98.00% |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| PSP_resnet101 | VOC | 1 | 3.96 | 10.63 | 2.68 | 98.46% | 98.45% |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| Deeplab_resnet101 | VOC | 1 | 4.17 | 13.35 | 3.20 | 98.36% | 98.34% |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| FCN_resnet101 | COCO | 1 | 5.19 | 26.22 | 5.05 | 91.28% | 90.96% |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| PSP_resnet101 | COCO | 1 | 3.94 | 10.60 | 2.69 | 91.82% | 91.88% |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
| Deeplab_resnet101 | COCO | 1 | 4.15 | 13.56 | 3.27 | 91.86% | 91.98% |
+-----------------------+----------+------------+------------------+------------------+---------+-----------------+-----------------+
Quantized SSD models are evaluated with ``nms_thresh=0.45``, ``nms_topk=200``. For segmentation models, the accuracy metric is pixAcc.
Demo usage for SSD
------------------
.. code:: bash
# set omp to use all physical cores of one socket
export KMP_AFFINITY=granularity=fine,noduplicates,compact,1,0
export CPUs=`lscpu | grep 'Core(s) per socket' | awk '{print $4}'`
export OMP_NUM_THREADS=$(CPUs)
# with Pascal VOC validation dataset saved on disk
python eval_ssd.py --network=mobilenet1.0 --quantized --data-shape=512 --batch-size=224 --dataset=voc --benchmark
Usage:
::
SYNOPSIS
python eval_ssd.py [-h] [--network NETWORK] [--deploy]
[--model-prefix] [--quantized]
[--data-shape DATA_SHAPE] [--batch-size BATCH_SIZE]
[--benchmark BENCHMARK] [--num-iterations NUM_ITERATIONS]
[--dataset DATASET] [--num-workers NUM_WORKERS]
[--num-gpus NUM_GPUS] [--pretrained PRETRAINED]
[--save-prefix SAVE_PREFIX] [--calibration CALIBRATION]
[--num-calib-batches NUM_CALIB_BATCHES]
[--quantized-dtype {auto,int8,uint8}]
[--calib-mode CALIB_MODE]
OPTIONS
-h, --help show this help message and exit
--network NETWORK base network name
--deploy whether load static model for deployment
--model-prefix MODEL_PREFIX
load static model as hybridblock.
--quantized use int8 pretrained model
--data-shape DATA_SHAPE
input data shape
--batch-size BATCH_SIZE
eval mini-batch size
--benchmark BENCHMARK run dummy-data based benchmarking
--num-iterations NUM_ITERATIONS number of benchmarking iterations.
--dataset DATASET eval dataset.
--num-workers NUM_WORKERS, -j NUM_WORKERS
number of data workers
--num-gpus NUM_GPUS number of gpus to use.
--pretrained PRETRAINED
load weights from previously saved parameters.
--save-prefix SAVE_PREFIX
saving parameter prefix
--calibration quantize model
--num-calib-batches NUM_CALIB_BATCHES
number of batches for calibration
--quantized-dtype {auto,int8,uint8}
quantization destination data type for input data
--calib-mode CALIB_MODE
calibration mode used for generating calibration table
for the quantized symbol; supports 1. none: no
calibration will be used. The thresholds for
quantization will be calculated on the fly. This will
result in inference speed slowdown and loss of
accuracy in general. 2. naive: simply take min and max
values of layer outputs as thresholds for
quantization. In general, the inference accuracy
worsens with more examples used in calibration. It is
recommended to use `entropy` mode as it produces more
accurate inference results. 3. entropy: calculate KL
divergence of the fp32 output and quantized output for
optimal thresholds. This mode is expected to produce
the best inference accuracy of all three kinds of
quantized models if the calibration dataset is
representative enough of the inference dataset.
Calibration Tool
----------------
GluonCV also delivered calibration tool for users to quantize their models into int8 with their own dataset. Currently, calibration tool only supports hybridized gluon models. Below is an example of quantizing SSD model.
.. code:: bash
# Calibration
python eval_ssd.py --network=mobilenet1.0 --data-shape=512 --batch-size=224 --dataset=voc --calibration --num-calib-batches=5 --calib-mode=naive
# INT8 Inference
python eval_ssd.py --network=mobilenet1.0 --data-shape=512 --batch-size=224 --deploy --model-prefix=./model/ssd_512_mobilenet1.0_voc-quantized-naive
The first command will launch naive calibration to quantize your ssd_mobilenet1.0 model to int8 by using a subset (5 batches) of your given dataset. Users can tune the int8 accuracy by setting different calibration configurations. After calibration, quantized model and parameter will be saved on your disk. Then, the second command will load quantized model as a symbolblock for inference.
Users can also quantize their own gluon hybridized model by using `quantize_net` api. Below are some descriptions.
API:
::
CODE
from mxnet.contrib.quantization import *
quantized_net = quantize_net(network, quantized_dtype='auto',
exclude_layers=None, exclude_layers_match=None,
calib_data=None, data_shapes=None,
calib_mode='naive', num_calib_examples=None,
ctx=mx.cpu(), logger=logging)
Parameters
network : Gluon HybridBlock
Defines the structure of a neural network for FP32 data types.
quantized_dtype : str
The quantized destination type for input data. Currently support 'int8'
, 'uint8' and 'auto'.
'auto' means automatically select output type according to calibration result.
Default value is 'int8'.
exclude_layers : list of strings
A list of strings representing the names of the symbols that users want to excluding
exclude_layers_match : list of strings
A list of strings wildcard matching the names of the symbols that users want to excluding
from being quantized.
calib_data : mx.io.DataIter or gluon.DataLoader
A iterable data loading object.
data_shapes : list
List of DataDesc, required if calib_data is not provided
calib_mode : str
If calib_mode='none', no calibration will be used and the thresholds for
requantization after the corresponding layers will be calculated at runtime by
calling min and max operators. The quantized models generated in this
mode are normally 10-20% slower than those with calibrations during inference.
If calib_mode='naive', the min and max values of the layer outputs from a calibration
dataset will be directly taken as the thresholds for quantization.
If calib_mode='entropy', the thresholds for quantization will be
derived such that the KL divergence between the distributions of FP32 layer outputs and
quantized layer outputs is minimized based upon the calibration dataset.
calib_layer : function
Given a layer's output name in string, return True or False for deciding whether to
calibrate this layer. If yes, the statistics of the layer's output will be collected;
otherwise, no information of the layer's output will be collected. If not provided,
all the layers' outputs that need requantization will be collected.
num_calib_examples : int or None
The maximum number of examples that user would like to use for calibration.
If not provided, the whole calibration dataset will be used.
ctx : Context
Defines the device that users want to run forward propagation on the calibration
dataset for collecting layer output statistics. Currently, only supports single context.
Currently only support CPU with MKL-DNN backend.
logger : Object
A logging object for printing information during the process of quantization.
Returns
network : Gluon SymbolBlock
Defines the structure of a neural network for INT8 data types.
"""
|
def fib(n_max):
n, a, b = 0, 0, 1
while n < n_max:
yield b
a, b = b, a + b
n = n + 1
list = fib(int(input("Input a number:")))
print(next(list))
for o in list:
print(o)
|
"""
Universidad del Valle de Guatemala
CC----
thompson.py
Proposito: AFN ya establecido
"""
class AFN:
def __init__(self, start, end):
self.start = start
self.end = end # start and end states
end.is_end = True
self.text = "State Inicial: {}| State Final: {}".format(self.start,self.end)
#Recursion \ afn n veces /
#state-set es como un stack --> \ afn1 /
# \______afn0____/
def addstate(self, state, state_set): # add state + recursively add epsilon transitions
if state in state_set:
return
state_set.add(state)
for eps in state.epsilon:
self.addstate(eps, state_set)
def __str__(self) -> str:
return self.text
def match(self,s):
current_states = set() # set es para ordernarlos set([3, 4, 1, 4, 5]) --> {1, 3, 4, 5}
self.addstate(self.start, current_states)
#print("Set inicial: " )
#for i in current_states:
# print(i)
#print(current_states.keys())
#print(current_states)
for c in s:
#print(s)
next_states = set()
#test = "State: {} | Transitions: {}.".format(state,state.transitions[c])
for state in current_states:
#print(state.transitions.keys())
if c in state.transitions.keys():
print("State original: {} ".format(state))
trans_state = state.transitions[c]
#print("Char: " + c)
self.addstate(trans_state, next_states)
#print(c)
current_states = next_states
#for s in current_states:
# print(s)
for s in current_states:
#si el caracter llega a un estado final, termine y se hace match el input del automata creado
if s.is_end:
return True
return False
|
"""Sparse Array"""
def sparse_array():
r"""https://www.hackerrank.com/challenges/sparse-arrays?
There are $N$ strings. Each string's length is no more than 20 characters.
There are also $Q$ queries. For each query, you are given a string,
and you need to find out how many times this string occurred previously.
Input Format
The first line contains N, the number of strings.
The next $N$ lines each contain a string.
The $N + 2^{nd}$ line contains $Q$, the number of queries.
The following $Q$ lines each contain a query string.
Constraints
$
1 \le N \le 1000\\
1 \le Q \le 1000\\
1 \le \text{ length of any string } \le 20
$
"""
number_of_strings = int(input())
all_strings = [input() for i in range(number_of_strings)]
number_of_queries = int(input())
while number_of_queries:
search_string = input()
search_string_occurrence = filter(lambda x: x == search_string, all_strings)
print(len(list(search_string_occurrence)))
if __name__ == "__main__":
sparse_array()
|
def mostFrequentDigitSum(n):
'''
A step(x) operation works like this: it changes a number x into x - s(x), where s(x) is the sum of x's digits. You like applying functions to numbers, so given the number n, you decide to build a decreasing sequence of numbers: n, step(n), step(step(n)), etc., with 0 as the last element.
Building a single sequence isn't enough for you, so you replace all elements of the sequence with the sums of their digits (s(x)). Now you're curious as to which number appears in the new sequence most often. If there are several answers, return the maximal one.
Example
For n = 88, the output should be
mostFrequentDigitSum(n) = 9.
Here is the first sequence you built: 88, 72, 63, 54, 45, 36, 27, 18, 9, 0;
And here is s(x) for each of its elements: 16, 9, 9, 9, 9, 9, 9, 9, 9, 0.
As you can see, the most frequent number in the second sequence is 9.
For n = 8, the output should be
mostFrequentDigitSum(n) = 8.
At first you built the following sequence: 8, 0
s(x) for each of its elements is: 8, 0
As you can see, the answer is 8 (it appears as often as 0, but is greater than it).
'''
firstSequence = [n]
while n > 0:
n = n - sumDigits(n)
firstSequence.append(n)
secondSequence = [sumDigits(i) for i in firstSequence]
d = dict()
for i in firstSequence + secondSequence:
if i in d:
d[i] += 1
else:
d[i] = 1
currentMax = n
currentCounter = 1
for k in d.keys():
if d[k] == currentCounter:
if k > currentMax:
currentMax = k
elif d[k] > currentCounter:
currentCounter = d[k]
currentMax = k
return currentMax
def sumDigits(n):
s = 0
while n:
s += n % 10
n //= 10
return s
|
"""DTE Energy Bridge Exceptions."""
class DteEnergyBridgeError(Exception):
"""Base class for all DTE Energy Bridge exceptions"""
class InvalidResponseError(DteEnergyBridgeError):
"""Response from DTE Energy Bridge was invalid"""
class InvalidArgumentError(DteEnergyBridgeError):
"""Invalid argument"""
|
# x=int(input("enter the number"))
# print("factors of ",x,"is:")
# for i in range (1,x+1):
# if X%i==0:
# print(i)
n=int(input("enter factors number="))
i=1
while i<=n:
if n%i==0:
print(i)
i+=1
|
'''
Created on Feb 20, 2013
@author: gorgolewski, steele
'''
#import os
#subjects = os.listdir("/scr/namibia1/baird/MPI_Project/Neuroimaging_Data/")
working_dir = "/scr/alaska1/steele/BSL_IHI/processing/cmt"
results_dir = "/scr/alaska1/steele/BSL_IHI/processing/cmt/results"
freesurfer_dir = '/scr/alaska1/steele/BSL_IHI/processing/freesurfer/'
subjects_M = ['KCDT100819_T1.TRIO',
'JA7T100824_T1.TRIO',
'17230.95_20111026_T1.TRIO',
'SJAT_100416_T1.TRIO',
'DM6T100909_T1.TRIO',
'NS5T090217_T1.TRIO',
'11530.56_090910_T1.TRIO',
'15205.bb_20110818_T1.TRIO',
'BSLT100916__T1.TRIO',
'SF8T100916_T1.TRIO',
'SAST_100421_T1.TRIO',
'SMXT100805_T1.TRIO',
'MN3T090909_T1.TRIO',
'ED2T101126_T1.TRIO',
'LP4T091026_T1.TRIO',
'DS9T101110_T1.TRIO',
'GD4T100909_T1.TRIO',
'AS3T100715_T1.TRIO',
'SL6T101119_T1.TRIO',
'UF1T100824_T1.TRIO',
'12522.80_20110818_T1.TRIO',
'GC6T100805_T1.TRIO',
'15832.a8_20110616_T1.TRIO',
'KAHT101103_T1.TRIO',
'16833.de_20111025_T1.TRIO',
'SCMT101110_T1.TRIO',
'KE5T100909_T1.TRIO',
'14841.b6_20111026_T1.TRIO']
subjects_NM= ['MMJT100420_T1.TRIO',
'RMFT100708_T1.TRIO',
'KG6T100708_T1.TRIO',
'GMOT100628_T1.TRIO',
'STCT090817_T1.TRIO',
'DH2T100420_T1.TRIO',
'12612.9b_20090318_T1_TRIO',
'RSET090817_T1.TRIO',
'LC7T100629_T1.TRIO',
'14102.d1_20111024_T1.TRIO',
'DA5T110620_T1.TRIO',
'16687.41_20111025_T1.TRIO',
'01212.43_20090617_T1.TRIO',
'BC9T100831_T1.TRIO',
'NC3T090721_T1.TRIO',
'WMCT090817_T1.TRIO',
'WSFT100322_T1.TRIO',
'BSGT081016_T1.TRIO',
'10060.70_20111025_T1.TRIO',
'HCBT060321_T1.DTI',
'11401.38_111025_T1.TRIO',
'10576.44_20091217_T1.TRIO',
'15510.c9_20111110_T1.TRIO',
'JR1T090216_T1.TRIO',
'WF5T091110_T1.TRIO',
'WT6T090807_T1.TRIO',
'HN3T090610_T1.TRIO',
'SU3T090819_T1.TRIO']
|
# (C) Datadog, Inc. 2020-present
# All rights reserved
# Licensed under a 3-clause BSD style license (see LICENSE)
def get_counter(check, metric_name, modifiers, global_options):
"""
https://prometheus.io/docs/concepts/metric_types/#counter
https://github.com/OpenObservability/OpenMetrics/blob/master/specification/OpenMetrics.md#counter-1
"""
monotonic_count_method = check.monotonic_count
metric_name = f'{metric_name}.count'
def counter(metric, sample_data, runtime_data):
flush_first_value = runtime_data['flush_first_value']
for sample, tags, hostname in sample_data:
if sample.name.endswith('_total'):
monotonic_count_method(
metric_name,
sample.value,
tags=tags,
hostname=hostname,
flush_first_value=flush_first_value,
)
del check
del modifiers
del global_options
return counter
|
class ShortCodeError(Exception):
"""Base exception raised when some unexpected event occurs in the shortcode
OAuth flow."""
pass
class UnknownShortCodeError(ShortCodeError):
"""Exception raised when an unknown error happens while running shortcode
OAuth.
"""
pass
class ShortCodeAccessDeniedError(ShortCodeError):
"""Exception raised when the user denies access to the client in shortcode
OAuth."""
pass
class ShortCodeTimeoutError(ShortCodeError):
"""Exception raised when the shortcode expires without being accepted."""
pass
|
class Empty(Exception):
"""Use this class to raise exception if a container is empty."""
pass
class CircularQueue:
"""Queue implemented using cicrcularly linked list for storage."""
class _Node:
"""Lightweight, nonpublic class for storing a singly linked node."""
__slots__ = ["_element", "_next"] # streamline menory usage
def __init__(self, element, next):
self._element = element
self._next = next
def __str__(self):
"""Represents the node elemnt."""
return "{}".format(self._element)
# CircularQueue methods
def __init__(self):
"""Create an empty queue."""
self._tail = None # will represent tail of queue
self._size = 0
def __len__(self):
"""Return the no. of elements in the queue."""
return self._size
def is_empty(self):
"""Return True if queue is empty; False otherwise."""
return self._size == 0
def first(self):
"""Return (but don't remove) the element at the head of the queue.
Raise Empty Exception if queue is empty."""
if self.is_empty():
raise Empty("Queue is empty")
head = self._tail._next
return head._element
def deque(self):
"""Remove and return the first element of the queue.
Raise Empty exception if queue is empty."""
if self.is_empty():
raise Empty("Queue is empty")
old_head = self._tail._next
if self._size == 1: # removing only element which existed
self._tail = None # queue becomes empty
else: # head exists
self._tail._next = old_head._next # bpass oldhead head and point to the next node
self._size -=1
return old_head._element
def enque(self, e):
"""Add element e to the end of queue(tail of linked list)."""
newest = self._Node(e, None) # create a new tail node
if self.is_empty(): # queue is empty
newest._next = newest # initialize circularly
else: # tail element exists
newest._next = self._tail._next # new node points to head
self._tail._next = newest # old tail points to the new node
self._tail = newest # new node becomes the new node
self._size += 1 # increase size
def __str__(self):
"""Return the Circular Queue data as string"""
result = ""
# we will traverse from tail node to head node(if any)
# as it is circularly linked list, we will stop traversal if we arrive back to the same tail node
tail_node = self._tail # store tail node
if self._size == 0: # queue is enmpty
result += str(tail_node) + "->" # no need to traverse furthur
else:
next_node = tail_node._next # get the next node of tail node
while next_node != tail_node: # traverse untill we arrive back to the tail node
result += str(next_node) + " -> " # add next node information
next_node = next_node._next # chnge next_node to the subsequent next node
result += str(tail_node) + " -> " # add the tail node information finally
return "< CircularQueue: [{}] >".format(result)
if __name__ == "__main__":
circular_queue = CircularQueue()
print(circular_queue)
circular_queue.enque(1)
print(circular_queue)
print("Element at the front of queue:", circular_queue.first())
print("Queue size:", len(circular_queue))
circular_queue.deque()
for i in range(1, 11):
circular_queue.enque(i)
print(circular_queue)
print("Element at the front of queue:", circular_queue.first())
print("Queue size:", len(circular_queue))
for i in range(1, 11):
circular_queue.deque()
print(circular_queue)
if not circular_queue.is_empty():
print("Element at the front of queue:", circular_queue.first())
print("Queue size:", len(circular_queue))
|
def szyfr(ciag, k):
nowy_ciag = ""
for lit in ciag:
nowy_ord = 65+(ord(lit)-65+k) % 26
nowy_ciag += chr(nowy_ord)
return nowy_ciag
def odszyfr(ciag, k):
nowy_ciag = ""
for lit in ciag:
nowy_ord = 65+(ord(lit)-65-k) % 26
nowy_ciag += chr(nowy_ord)
return nowy_ciag
def szukaj(ciag, ciag2):
def zdobadz_klucz(znak, znak2):
if ord(znak2) < ord(znak):
return 26-(ord(znak)-ord(znak2))
else:
return abs(ord(znak2)-ord(znak))
roz = zdobadz_klucz(ciag[0], ciag2[0])
if ciag2 != szyfr(ciag, roz):
return False
return True
with open("wyniki_6_1.txt", "w") as wyjscie:
with open("DANE_PR2/dane_6_1.txt") as wejscie:
for linia in wejscie:
if not linia:
continue
linia = linia.strip()
wyjscie.write(szyfr(linia, 107)+"\n")
with open("wyniki_6_2.txt", "w") as wyjscie:
with open("DANE_PR2/dane_6_2.txt") as wejscie:
for linia in wejscie:
if not linia:
continue
linia = linia.strip()
try:
ciag, k = linia.split()
except:
k = 0
wyjscie.write(odszyfr(ciag, int(k))+"\n")
with open("wyniki_6_3.txt", "w") as wyjscie:
with open("DANE_PR2/dane_6_3.txt") as wejscie:
for linia in wejscie:
linia = linia.strip()
ciag1, ciag2 = linia.split()
if not szukaj(ciag1, ciag2):
wyjscie.write(ciag1+"\n")
|
#! python3
# __author__ = "YangJiaHao"
# date: 2018/2/3
class Solution:
def myAtoi(self, str):
"""
:type str: str
:rtype: int
"""
str = str.strip()
if str == "":
return 0
num = ''
symbol = 1
if str[0] == '-':
symbol = -1
str = str[1:]
elif str[0] == '+':
symbol = 1
str = str[1:]
for i in str:
if i < '0' or i > '9':
break
else:
num += i
if num == "":
return 0
num = int(num) * symbol
if num > 2147483647:
num = 2147483647
elif num < -2147483648:
num = -2147483648
return num
if __name__ == '__main__':
so = Solution()
i = so.myAtoi("+-45")
print(i)
|
__doc__ = '网上常用的python实现示例'
# 图算法 -- 深度优先搜搜 -- DFS -- 栈（先进后出）
# 1.利用栈实现
# 2.从源节点开始把节点按照深度放入栈，然后弹出
# 3.每弹出一个点，把该节点下一个没有进过栈的邻接点放入栈
# 4.直到栈变空
def DFS(graph, start):
stack = [start]
visited = set()
step = 0 # 记录扩散的步数
while stack:
vertex = stack.pop()
if vertex not in visited:
visited.add(vertex)
for w in graph[vertex]:
if w not in visited:
stack.append(w)
step += 1
print(vertex)
print(step)
# 图算法 -- 广度优先搜搜 -- BFS -- 队列（先进先出）
# 1.利用队列实现
# 2.从源节点开始依次按照宽度进队列，然后弹出
# 3.每弹出一个节点，就把该节点所有没有进过队列的邻接点放入队列
# 4.直到队列变空
def BFS(graph, start):
queue = [] # 核心数据结构,模拟队列
queue.append(start) # 将起点加入队列
visited = set() # 避免走回头路
visited.add(start)
step = 0 # 记录扩散的步数
while len(queue) > 0:
vertex = queue.pop(0)
nodes = graph[vertex]
for w in nodes:
if w not in visited:
queue.append(w)
visited.add(w)
step += 1
print(vertex)
print(step)
graph = {
"A": ["B", "C"],
"B": ["A", "C", "D"],
"C": ["A", "B", "D", "E"],
"D": ["B", "C", "E", "F"],
"E": ["C", "D"],
"F": ["D"]
}
print("-----DFS-----")
DFS(graph, "A")
print("-----BFS-----")
BFS(graph, "A")
|
#! coding:utf-8
# Definition for singly-linked list.
# class ListNode(object):
# def __init__(self, x):
# self.val = x
# self.next = None
def addTwoNumbers(l1, l2):
"""
:type l1: ListNode
:type l2: ListNode
:rtype: ListNode
"""
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, x):
# self.val = x
# self.next = None
head = ListNode(0)
jin_wei = 0 # 进位和
cur = head
while l1 or l2:
#判断当前节点是否为None，而不是下一个节点，不然第一步进入不了
x = l1.val if l1 else 0
y = l2.val if l2 else 0
he = jin_wei + x + y
jin_wei = he // 10
cur.next = ListNode(he % 10)
cur = cur.next
if l1 != None: l1 = l1.next
if l2 != None: l2 = l2.next
if jin_wei > 0:
cur.next = ListNode(1)
return head.next
#
# if __name__ == '__main__':
# addTwoNumbers()
|
#!/usr/bin/python
patch_size = [11, 15, 21]
detector = ["FeatureDetectorHarrisCV", "FeatureDetectorUniform"]
filter_size = [1, 3]
max_disparity = [140, 160, 180, 200]
fp_runscript = open("/mnt/ssd/kivan/cv-stereo/scripts/eval_batch/run_batch_grid_search_stage2.sh", 'w')
fp_runscript.write("#!/bin/bash\n\n")
cnt = 0
for i in range(len(patch_size)):
for j in range(len(detector)):
for k in range(len(filter_size)):
for l in range(len(max_disparity)):
cnt += 1
filepath = "/home/kivan/Projects/cv-stereo/config_files/experiments/kitti/validation_stage2/param_validation_stage2_" + str(cnt) + ".txt"
print(filepath)
fp = open(filepath, 'w')
fp.write("odometry_method = VisualOdometryRansac\n")
fp.write("ransac_iters = 1000\n\n")
fp.write("tracker = StereoTracker\n")
fp.write("max_disparity = " + str(max_disparity[l]) + "\n")
fp.write("stereo_wsz = " + str(patch_size[i]) + "\n")
fp.write("ncc_threshold_s = 0.7\n\n")
fp.write("tracker_mono = TrackerBFM\n")
fp.write("max_features = 5000\n")
fp.write("ncc_threshold_m = 0.8\n")
fp.write("ncc_patch_size = " + str(patch_size[i]) + "\n")
fp.write("search_wsz = 230\n\n")
fp.write("detector = " + detector[j] + "\n")
fp.write("harris_block_sz = 3\n")
fp.write("harris_filter_sz = " + str(filter_size[k]) + "\n")
fp.write("harris_k = 0.04\n")
fp.write("harris_thr = 1e-05\n")
fp.write("harris_margin = " + str(patch_size[i]) + "\n\n")
fp.write("use_bundle_adjustment = false")
fp.close()
fp_runscript.write('./run_kitti_evaluation_dinodas.sh "' + filepath + '"\n')
fp_runscript.close()
|
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, val=0, left=None, right=None):
# self.val = val
# self.left = left
# self.right = right
class Solution:
def isMirror(self, r1: TreeNode, r2: TreeNode) -> bool:
if r1 == None and r2 == None:
return True
if r1 == None or r2 == None:
return False
return (r1.val == r2.val) and self.isMirror(r1.left, r2.right) and self.isMirror(r1.right, r2.left)
def isSymmetric(self, root: TreeNode) -> bool:
return self.isMirror(root, root)
|
class Passenger:
def __init__(self, name):
self.name = name
def selectTrip(self, tripOptions):
'''
Given a list of trip options, a passenger may select a trip
This trip is then added to the trip queue, which allows for later return pricing
tripOptions: the queue of given trips available to the passenger
This should come from TripPlanner.offerReturnPrices()
returns the index of the desired trip
'''
for idx, trip in enumerate(tripOptions):
print(f'Trip Number: {idx}\n{repr(trip)}')
trip_num = 100
while trip_num < 0 and trip_num > len(tripOptions):
trip_num = int(input('enter desired trip number: '))
return trip_num
def stateSource(self):
return input('enter desired source: ')
def stateDestination(self):
return input('enter desired destination: ')
def stateHour(self):
return int(input('enter desired hour to leave: '))
|
# -*- coding: utf-8 -*-
"""
--------------------------------------
@File : stats.py
@Author : maixiaochai
@Email : maixiaochai@outlook.com
@CreatedOn : 2020/6/8 23:29
--------------------------------------
一些统计信息
1）任务数量, 总数、成功、失败、运行中、运行完
2）任务数量分布统计
3）历史成功率统计
4）硬件信息统计，磁盘、cpu、内存、文件数量
5）日志数量
6) 运行时间长度排名，日、周、月、年
7）业务运行时间排名、业务分布
8）任务更改次数排名、业务分布
10)接口访问统计，总数，成功，失败
11）用户访问统计，总数，成功、失败、top
...
一些运行状态
1）某个任务在运行[中|完|成功|失败]
"""
|
# A file containing mappings of CC -> MC file names
# Pack version 3
VER3 = {
'char.png': 'minecraft/textures/entity/steve.png',
'chicken.png': 'minecraft/textures/entity/chicken.png',
'creeper.png': 'minecraft/textures/entity/creeper/creeper.png',
'pig.png': 'minecraft/textures/entity/pig/pig.png',
'sheep.png': 'minecraft/textures/entity/sheep/sheep.png',
'sheep_fur.png': 'minecraft/textures/entity/sheep/sheep_fur.png',
'skeleton.png': 'minecraft/textures/entity/skeleton/skeleton.png',
'spider.png': 'minecraft/textures/entity/spider/spider.png',
'zombie.png': 'minecraft/textures/entity/zombie/zombie.png',
'default.png': 'minecraft/textures/font/ascii.png',
'icons.png': 'minecraft/textures/gui/icons.png',
'gui.png': 'minecraft/textures/gui/widgets.png',
'gui_classic.png': 'minecraft/textures/gui/widgets.png'
}
# Blocks
BLOCKS3 = [
# glass_pane_top_brown is substitute for rope
'grass_top', 'stone', 'dirt', 'grass_side',
'planks_oak', 'stone_slab_side', 'stone_slab_top', 'brick',
'tnt_side', 'tnt_top', 'tnt_bottom', ('glass_pane_top_brown', 'glass_pane_top'),
'flower_rose', 'flower_dandelion', 'water_still', 'sapling_oak',
'cobblestone', 'bedrock', 'sand', 'gravel',
'log_oak', 'log_oak_top', 'leaves_oak', 'iron_block',
'gold_block', 'sandstone_top', 'quartz_block_lines_top', None,
'mushroom_red', 'mushroom_brown', 'lava_still', 'grass_top',
# TODO: fire_layer_0 is an animation sheet, only get first frame for terrain.png
'gold_ore', 'iron_ore', 'coal_ore', 'bookshelf',
'cobblestone_mossy', 'obsidian', 'fire_layer_0', 'iron_block',
'gold_block', 'sandstone_normal', 'quartz_block_lines', None,
None, None, None, None,
# shulker_top_brown is crate
'sponge', 'glass', 'snow', 'ice',
'stonebrick', 'shulker_top_brown', 'quartz_block_side', 'iron_block',
'gold_block', 'sandstone_bottom', 'quartz_block_lines_top', None,
None, None, None, None,
# TODO: Some colours don't exist in modern minecraft, get them from hex colours instead
'wool_colored_red', 'wool_colored_orange', 'wool_colored_yellow', 'wool_colored_lime',
'wool_colored_green', 'TEAL', 'wool_colored_light_blue', 'wool_colored_cyan',
'BLUE', 'wool_colored_purple', 'VIOLET', 'wool_colored_magenta',
'PINK', 'wool_colored_black', 'wool_colored_gray', 'wool_colored_white',
'wool_colored_pink', 'FOREST GREEN', 'wool_colored_brown', 'wool_colored_blue',
'TURQUOISE', None, 'magma'
# TODO: Are the breaking state textures at the bottom ever used by anyone? Don't transfer them over for now.
]
|
# output: ok
assert(max(1, 2, 3) == 3)
assert(max(1, 3, 2) == 3)
assert(max(3, 2, 1) == 3)
assert(min([1]) == 1)
assert(min([1, 2, 3]) == 1)
assert(min([1, 3, 2]) == 1)
assert(min([3, 2, 1]) == 1)
exception = False
try:
min()
except TypeError:
exception = True
assert(exception)
exception = False
try:
max()
except TypeError:
exception = True
assert(exception)
def testIter(iterable):
i = iter(iterable)
assert(next(i) == 1)
assert(next(i) == 2)
assert(next(i) == 3)
caught = False
try:
next(i)
except StopIteration:
caught = True
assert(caught)
class OwnSequence:
def __init__(self, wrapped):
self.wrapped = wrapped
def __getitem__(self, index):
return self.wrapped[index]
testIter([1, 2, 3])
testIter(OwnSequence([1, 2, 3]))
def inc(x):
return x + 1
assert(list(map(inc, [])) == [])
assert(list(map(inc, [1, 2, 3])) == [2, 3, 4])
assert(list(zip()) == [])
assert(list(zip([1], [2])) == [(1, 2)])
assert(list(zip([1, 2], [2, 3])) == [(1, 2), (2, 3)])
assert(sum([]) == 0)
assert(sum([1, 2, 3]) == 6)
assert(sum((1, 2, 3), 4) == 10)
# todo: these tests are probably not sufficient
assert(divmod(5, 2) == (2, 1))
assert(divmod(4.5, 1.5) == (3.0, 0.0))
assert(divmod(5, 1.5) == (3.0, 0.5))
assert(divmod(1, -1) == (-1, 0))
assert(divmod(-1, 1) == (-1, 0))
# Builtin classes are not modifiable
builtinClasses = [ bool, dict, tuple, list, int, float, object ]
def checkException(thunk, exceptionType, message):
try:
thunk()
except Exception as e:
if isinstance(e, exceptionType) and message in str(e):
return True
return False
def addAttr(c):
c.foo = 1
for c in builtinClasses:
assert checkException(lambda: addAttr(c), TypeError, "can't set attributes")
# Can't add attributes to instances of builtin classes
for c in builtinClasses:
assert checkException(lambda: addAttr(c()), AttributeError,
"object has no attribute")
# locals
def locals1():
return locals()
#assert locals1() == {}
assert len(locals1().keys()) == 0
def locals2():
a = 1
b = 2
return locals()
x = locals2()
assert x['a'] == 1
assert x['b'] == 2
def locals3(z):
a = 1
b = 2
return locals()
x = locals3(3)
assert x['a'] == 1
assert x['b'] == 2
assert x['z'] == 3
def locals4():
a = 1
b = 2
def x():
return a
return locals()
x = locals4()
assert x['a'] == 1
assert x['b'] == 2
assert 'x' in x
# globals
foo = 1
g = globals()
assert g['foo'] == 1
g['foo'] = 2
assert g['foo'] == 2
assert foo == 2
#assert 'foo' in g.keys()
assert 2 in g.values()
assert len(g.values()) == len(g.keys())
print('ok')
|
# Hack 1: InfoDB lists. Build your own/personalized InfoDb with a list length > 3, create list within a list as illustrated with Owns_Cars
blue = "\033[34m"
white = "\033[37m"
InfoDb = []
# List with dictionary records placed in a list
InfoDb.append({
"FirstName": "Michael",
"LastName": "Chen",
"DOB": "December 1",
"Residence": "San Diego",
"Email": "michaelc57247@stu.powayusd.com",
"Owns_Cars":["2016 Ford Focus EV", "2019 Honda Pilot"]
})
InfoDb.append({
"FirstName": "Ethan",
"LastName": "Vo",
"DOB": "Not Born",
"Residence": "The Moon",
"Email": "ethanv696969@stu.powayusd.com",
"Owns_Cars":["Broken Down Golf Cart"]
})
InfoDb.append({
"FirstName": "Anirudh",
"LastName": "Ramachandran",
"DOB": "August 18",
"Residence": "Uranus",
"Email": "anirudhr42069@stu.powayusd.com",
"Owns_Cars":["Can't Even Drive"]
})
# given an index this will print InfoDb content
def print_data(n):
print(InfoDb[n]["FirstName"], InfoDb[n]["LastName"]) # using comma puts space between values
print("\t", "Cars: ", end="") # \t is a tab indent, end="" make sure no return occurs
print(", ".join(InfoDb[n]["Owns_Cars"])) # join allows printing a string list with separator
print()
# Hack 2: InfoDB loops. Print values from the lists using three different ways: for, while, recursion
## hack 2a: def for_loop()
## hack 2b: def while_loop(0)
## hack 2c : def recursive_loop(0)
def for_loop():
for x in range(len(InfoDb)):
# print(InfoDb[x])
print_data(x)
def while_loop(x):
while x < len(InfoDb):
# print(InfoDb[x])
print_data(x)
x += 1
def recursive_loop(x):
if x < len(InfoDb):
# print(InfoDb[x])
print_data(x)
recursive_loop(x + 1)
# hack 3: fibonnaci
def fibonacci(n):
if n == 0:
return 0 # for 0
elif n == 1:
return 1 # for 1
else:
return fibonacci(n-1) + fibonacci(n-2) # recursion
def tester2():
try:
num = int(input("Term of Fibonacci Sequence: ")) # user input
# check if the number is negative
if num < 0:
print("You tested negative for COVID-19! Unfortunately, we only accept postive values at this Wendy's") # negative input
else:
print(num, "terms of the Fibonacci Sequence:")
for i in range(num):
print(fibonacci(i), end=" ")# list 0-n
print()
except:
print("INTEGER INTEGER INTEGER WHAT ARE YOU EVEN DOING") # non-integer input
# tester2()
def tester():
print(blue + "For loop" + white)
for_loop()
print(blue + "While loop" + white)
while_loop(0) # requires initial index to start while
print(blue + "Recursive loop" + white)
recursive_loop(0) # requires initial index to start recursion
# tester2()
# exit()
# hack3()
# tester()
|
x,y,z = map(int,input().split(' '))
a,b,c = map(int,input().split(' '))
if (x, y, z) == (a, b, c):
print("0")
elif (y, z) == (b, c):
print(15 * (x - a))
elif z==c:
if y<=b and x<=a:
print("0")
else:
print(500 * (y - b))
elif z>c:
print("10000")
else:
print("0")
|
def get_sum(arr,i,j):
sum = 0
sum += arr[i-1][j-1]
sum += arr[i-1][j]
sum += arr[i - 1][j+1]
sum += arr[i][j]
sum += arr[i+1][j-1]
sum += arr[i+1][j]
sum += arr[i+1][j+1]
return sum
if __name__ == '__main__':
arr = []
for _ in range(6):
arr.append(list(map(int, input().rstrip().split())))
max_sum = -63
for i in range(1,5):
for j in range(1,5):
current = get_sum(arr,i,j)
if current > max_sum:
max_sum = current
print(max_sum)
|
"""
The exceptions here tries to follow PEP249 (https://www.python.org/dev/peps/pep-0249/#exceptions)
"""
class Warning(Exception):
"""Exception raised for important warnings like data truncations while inserting, etc."""
pass
class Error(Exception):
"""Exception that is the base class of all other error exceptions.
You can use this to catch all errors with one single except statement.
Warnings are not considered errors and thus should not use this class as base.
"""
pass
class InterfaceError(Error):
"""Exception raised for errors that are related to the database interface rather than
the database itself.
"""
pass
class DatabaseError(Error):
"""Exception raised for errors that are related to the database."""
pass
class DataError(DatabaseError):
"""Exception raised for errors that are due to problems with the processed
data like division by zero, numeric value out of range, etc
"""
pass
class OperationalError(DatabaseError):
"""Exception raised for errors that are related to the database's operation
and not necessarily under the control of the programmer, e.g. an unexpected
disconnect occurs, the data source name is not found, a transaction could
not be processed, a memory allocation error occurred during processing, etc
"""
pass
class IntegrityError(DatabaseError):
"""Exception raised when the relational integrity of the database is affected,
e.g. a foreign key check fails.
"""
pass
class InternalError(DatabaseError):
"""Exception raised when the database encounters an internal error, e.g. the
cursor is not valid anymore, the transaction is out of sync, etc.
"""
pass
class ProgrammingError(DatabaseError):
"""Exception raised for programming errors, e.g. table not found or already exists,
syntax error in the SQL statement, wrong number of parameters specified, etc
"""
pass
|
BROKER_URL = "redis://localhost:6379/0"
CELERY_RESULT_BACKEND = "redis://localhost:6379/0"
CELERY_TASK_SERIALIZER = 'json'
CELERY_RESULT_SERIALIZER = 'json'
CELERY_ACCEPT_CONTENT=['json']
CELERY_ENABLE_UTC = True
CELERY_TRACK_STARTED=True
|
def substring (Str,n):
for i in range(n):
print(i) #0 #1
for j in range(i ,n): #0 to 3 #1 to 3
for k in range(i, (j + 1)): #0 to 1 => 0 #1 to 2 => 1
print(Str[k], end="") #print 0th element of the string. #print 0th and 1st element side by side.
print()
Str = "abc"
n = len(Str)
substring(Str,n)
|
class MockPresenterFactory:
def __init__(self):
self.__presented_logs = []
def register_presenter(self, presenter):
pass
def present(self, obj):
text = ""
if isinstance(obj, str):
text = obj
elif isinstance(obj, list):
if len(obj) > 0:
text = "A list of %s" % (type(obj[0]).__name__)
else:
text = "A list"
else:
text = type(obj).__name__
self.__presented_logs.append(text)
def clear(self):
self.__presented_logs.clear()
@property
def presented_logs(self):
return self.__presented_logs
|
def is_growth(numbers):
for i in range(1, len(numbers)):
if numbers[i] <= numbers[i - 1]:
return False
return True
def main():
numbers = list(map(int, input().split()))
if is_growth(numbers):
print('YES')
else:
print('NO')
if __name__ == '__main__':
main()
|
"""
https://leetcode-cn.com/explore/interview/card/top-interview-questions-easy/1/array/31/
题目：旋转图像
给定一个 n × n 的二维矩阵表示一个图像。
将图像顺时针旋转 90 度。
说明：
你必须在原地旋转图像，这意味着你需要直接修改输入的二维矩阵。请不要使用另一个矩阵来旋转图像。
示例 1:
给定 matrix =
[
[1,2,3],
[4,5,6],
[7,8,9]
],
原地旋转输入矩阵，使其变为:
[
[7,4,1],
[8,5,2],
[9,6,3]
]
@author Niefy
@date 2018-09-12
"""
class RotateImage:
def rotate(self, matrix):#解答来自 https://blog.csdn.net/shawpan/article/details/69663710
"""
:type matrix: List[List[int]]
:rtype: void Do not return anything, modify matrix in-place instead.
"""
matrix[:]=map(list,zip(*matrix[::-1]))
# 测试代码
t=RotateImage()
matrix=[
[1,2,3],
[4,5,6],
[7,8,9]
]
t.rotate(matrix)
print(matrix)
|
# -*- coding: utf-8 -*-
# this file is released under public domain and you can use without limitations
#########################################################################
## This is a sample controller
## - index is the default action of any application
## - user is required for authentication and authorization
## - download is for downloading files uploaded in the db (does streaming)
## - call exposes all registered services (none by default)
#########################################################################
def index():
"""
example action using the internationalization operator T and flash
rendered by views/default/index.html or views/generic.html
if you need a simple wiki simply replace the two lines below with:
return auth.wiki()
"""
response.flash = T("Welcome to web2py!")
return dict(message=T('Hello World'))
return dict(table=SQLFORM.grid(db.factura,
create=False, editable=False, deletable=False))
@auth.requires_login()
def status():
""" This is command action to update the invoice status.
It is triggered by the other menu actions.
commands:
- clear: resets the invoice selection
(allows to create a new one)
- lock: close the invoice avoiding further modifications
(for supporting billing)
- cancel: abort the current invoice
"""
if not request.args[3] == "limpiar":
factura = db.factura[request.args[1]]
if factura:
factura.update_record(status=request.args[3])
session.flash = \
T("Factura %(factura_id)s is %(status)s") % \
dict(status=request.args[3],
factura_id=request.args[1])
session.factura_id = None
redirect(URL(f="index"))
@auth.requires_login()
def factura():
""" The invoice header action
It allows to create or modify an invoice header.
Locked or cancelled operations are not editable.
"""
factura = cliente = readonly = None
# INVOICE_ID stores the currently selected invoice
if FACTURA_ID:
if request.args(1):
session.factura_id = request.args(1)
# get the invoice db record
factura = db.factura[session.factura_id]
# compute/update totals for each item and
# the invoice's total amount
if factura: factura_total(factura)
# was this invoice closed? then disable editing
readonly = factura.status in ("bloqueada", "cancelada")
form = SQLFORM(db.factura, session.factura_id,
readonly=readonly)
# on invoice update disable editing too (you can keep
# updating by accessing the invoice header trough the menu)
if form.process().accepted:
response.flash = T("Done!")
form = SQLFORM(db.factura, session.factura_id,
readonly=True)
else:
# here we add the cancel and close (lock) actions to
# the menu.
if not readonly:
response.menu += [
(T("Close"), True, URL(f="status",
args=["factura", session.factura_id,
"status", "bloqueada"])),
(T("Cancel"), True, URL(f="status",
args=["factura", session.factura_id,
"status", "cancelada"]))]
else:
# when there's no invoice informed (by session variable or
# action argument) we expose a create form
form = SQLFORM(db.factura)
if form.process().accepted:
session.factura_id = form.vars.id
session.flash = T("New invoice created")
# on sucess, self-redirect to allow editing
redirect(URL(f="factura"))
return dict(form=form)
@auth.requires_login()
def detalle():
"""
The invoice details grid.
It exposes an invoice item CRUD interface and updates totals for
each submission. It requires a session invoice variable which
is set by user input (via the menu), so you cannot edit details
unless you selected an invoice previously.
"""
if not session.factura_id:
# return an empty page if there's no invoice selected
response.flash = T("No invoice selected!")
return dict(header=None, details=None)
else:
# get the invoice database record
factura = db.factura[session.factura_id]
# update item and invoice totals (only open invoices)
factura_total(factura)
# is the invoice editable? then allow item CRUD.
editable = not factura.status in ("bloqueada", "cancelada")
detalle = SQLFORM.grid(db.item.factura_id==session.factura_id,
create=editable, editable=editable, deletable=editable)
# we add the invoice header to the action data for reference
header = SQLFORM(db.factura, session.factura_id, readonly=True)
return dict(header=header, detalle=detalle)
def user():
"""
exposes:
http://..../[app]/default/user/login
http://..../[app]/default/user/logout
http://..../[app]/default/user/register
http://..../[app]/default/user/profile
http://..../[app]/default/user/retrieve_password
http://..../[app]/default/user/change_password
http://..../[app]/default/user/manage_users (requires membership in
use @auth.requires_login()
@auth.requires_membership('group name')
@auth.requires_permission('read','table name',record_id)
to decorate functions that need access control
"""
return dict(form=auth())
@cache.action()
def download():
"""
allows downloading of uploaded files
http://..../[app]/default/download/[filename]
"""
return response.download(request, db)
def call():
"""
exposes services. for example:
http://..../[app]/default/call/jsonrpc
decorate with @services.jsonrpc the functions to expose
supports xml, json, xmlrpc, jsonrpc, amfrpc, rss, csv
"""
return service()
@auth.requires_signature()
def data():
"""
http://..../[app]/default/data/tables
http://..../[app]/default/data/create/[table]
http://..../[app]/default/data/read/[table]/[id]
http://..../[app]/default/data/update/[table]/[id]
http://..../[app]/default/data/delete/[table]/[id]
http://..../[app]/default/data/select/[table]
http://..../[app]/default/data/search/[table]
but URLs must be signed, i.e. linked with
A('table',_href=URL('data/tables',user_signature=True))
or with the signed load operator
LOAD('default','data.load',args='tables',ajax=True,user_signature=True)
"""
return dict(form=crud())
#def person():
# person = person = readonly = None
#
# if not readonly:
# response.menu += (T('Home'), False, URL('default', 'report'), [])
#
# else:
# form = SQLFORM(db.factura)
# redirect(URL(f="person","persons"))
# return dict(form=form)
#implementacion de appreport plugin
def report():
form = plugin_appreport.REPORTFORM(person)
if form.accepts(request.vars, session):
return plugin_appreport.REPORTPISA(table = person, title = 'List of persons', filter = dict(form.vars))
return dict(form = form)
|
a="#"
b="@"
c=1
d=int(input("Enter Number:"))
if d%2==0:
f=d/2
else:
f=d//2+1
h=f-3
e=1
g=2
while c<=d:
if c<=2 or c==f:
print (a*c)
c+=1
elif c>2 and c<f:
print (a+(b*e)+a)
c+=1
e+=1
elif c>f and c<d-1:
print (a+(b*h)+a)
c+=1
h=h-1
else:
print (a*g)
c+=1
g=g-1
|
# substitution ciphers
# or, how to transform data from one thing to another
encode_table = {
'A': 'H',
'B': 'Z',
'C': 'Y',
'D': 'W',
'E': 'O',
'F': 'R',
'G': 'J',
'H': 'D',
'I': 'P',
'J': 'T',
'K': 'I',
'L': 'G',
'M': 'L',
'N': 'C',
'O': 'E',
'P': 'X',
'Q': 'K',
'R': 'U',
'S': 'N',
'T': 'F',
'U': 'A',
'V': 'M',
'W': 'B',
'X': 'Q',
'Y': 'V',
'Z': 'S'
}
# decode_table = {}
# for key, value in encode_table.items():
# decode_table[value] = key
decode_table = {value: key for key, value in encode_table.items()}
def encode(plain_text):
cipher = ""
for char in plain_text:
if char.isspace():
cipher += ' '
else:
cipher += encode_table[char.upper()]
return cipher
def decode(cipher_text):
plain_text = ""
for char in cipher_text:
if char.isspace():
plain_text += ' '
else:
plain_text += decode_table[char.upper()]
return plain_text
cipher = encode("Super secret message just for you")
print(cipher)
reversed_plain_text = decode(cipher)
print(reversed_plain_text)
|
class Color:
pass
class rgb(Color):
"A representation of an RGBA color"
def __init__(self, r, g, b, a=1.0):
self.r = r
self.g = g
self.b = b
self.a = a
def __repr__(self):
return "rgba({}, {}, {}, {})".format(self.r, self.g, self.b, self.a)
@property
def rgb(self):
return self
class hsl(Color):
"A representation of an HSLA color"
def __init__(self, h, s, l, a=1.0): # noqa: E741
self.h = h
self.s = s
self.l = l # noqa
self.a = a
def __repr__(self):
return "hsla({}, {}, {}, {})".format(self.h, self.s, self.l, self.a)
@property
def rgb(self):
c = (1.0 - abs(2.0 * self.l - 1.0)) * self.s
h = self.h / 60.0
x = c * (1.0 - abs(h % 2 - 1.0))
m = self.l - 0.5 * c
if h < 1.0:
r, g, b = c + m, x + m, m
elif h < 2.0:
r, g, b = x + m, c + m, m
elif h < 3.0:
r, g, b = m, c + m, x + m
elif h < 4.0:
r, g, b = m, x + m, c + m
elif h < 5.0:
r, g, b = m, x + m, c + m
else:
r, g, b = c + m, m, x + m
return rgb(
round(r * 0xff),
round(g * 0xff),
round(b * 0xff),
self.a
)
ALICEBLUE = 'aliceblue'
ANTIQUEWHITE = 'antiquewhite'
AQUA = 'aqua'
AQUAMARINE = 'aquamarine'
AZURE = 'azure'
BEIGE = 'beige'
BISQUE = 'bisque'
BLACK = 'black'
BLANCHEDALMOND = 'blanchedalmond'
BLUE = 'blue'
BLUEVIOLET = 'blueviolet'
BROWN = 'brown'
BURLYWOOD = 'burlywood'
CADETBLUE = 'cadetblue'
CHARTREUSE = 'chartreuse'
CHOCOLATE = 'chocolate'
CORAL = 'coral'
CORNFLOWERBLUE = 'cornflowerblue'
CORNSILK = 'cornsilk'
CRIMSON = 'crimson'
CYAN = 'cyan'
DARKBLUE = 'darkblue'
DARKCYAN = 'darkcyan'
DARKGOLDENROD = 'darkgoldenrod'
DARKGRAY = 'darkgray'
DARKGREY = 'darkgrey'
DARKGREEN = 'darkgreen'
DARKKHAKI = 'darkkhaki'
DARKMAGENTA = 'darkmagenta'
DARKOLIVEGREEN = 'darkolivegreen'
DARKORANGE = 'darkorange'
DARKORCHID = 'darkorchid'
DARKRED = 'darkred'
DARKSALMON = 'darksalmon'
DARKSEAGREEN = 'darkseagreen'
DARKSLATEBLUE = 'darkslateblue'
DARKSLATEGRAY = 'darkslategray'
DARKSLATEGREY = 'darkslategrey'
DARKTURQUOISE = 'darkturquoise'
DARKVIOLET = 'darkviolet'
DEEPPINK = 'deeppink'
DEEPSKYBLUE = 'deepskyblue'
DIMGRAY = 'dimgray'
DIMGREY = 'dimgrey'
DODGERBLUE = 'dodgerblue'
FIREBRICK = 'firebrick'
FLORALWHITE = 'floralwhite'
FORESTGREEN = 'forestgreen'
FUCHSIA = 'fuchsia'
GAINSBORO = 'gainsboro'
GHOSTWHITE = 'ghostwhite'
GOLD = 'gold'
GOLDENROD = 'goldenrod'
GRAY = 'gray'
GREY = 'grey'
GREEN = 'green'
GREENYELLOW = 'greenyellow'
HONEYDEW = 'honeydew'
HOTPINK = 'hotpink'
INDIANRED = 'indianred'
INDIGO = 'indigo'
IVORY = 'ivory'
KHAKI = 'khaki'
LAVENDER = 'lavender'
LAVENDERBLUSH = 'lavenderblush'
LAWNGREEN = 'lawngreen'
LEMONCHIFFON = 'lemonchiffon'
LIGHTBLUE = 'lightblue'
LIGHTCORAL = 'lightcoral'
LIGHTCYAN = 'lightcyan'
LIGHTGOLDENRODYELLOW = 'lightgoldenrodyellow'
LIGHTGRAY = 'lightgray'
LIGHTGREY = 'lightgrey'
LIGHTGREEN = 'lightgreen'
LIGHTPINK = 'lightpink'
LIGHTSALMON = 'lightsalmon'
LIGHTSEAGREEN = 'lightseagreen'
LIGHTSKYBLUE = 'lightskyblue'
LIGHTSLATEGRAY = 'lightslategray'
LIGHTSLATEGREY = 'lightslategrey'
LIGHTSTEELBLUE = 'lightsteelblue'
LIGHTYELLOW = 'lightyellow'
LIME = 'lime'
LIMEGREEN = 'limegreen'
LINEN = 'linen'
MAGENTA = 'magenta'
MAROON = 'maroon'
MEDIUMAQUAMARINE = 'mediumaquamarine'
MEDIUMBLUE = 'mediumblue'
MEDIUMORCHID = 'mediumorchid'
MEDIUMPURPLE = 'mediumpurple'
MEDIUMSEAGREEN = 'mediumseagreen'
MEDIUMSLATEBLUE = 'mediumslateblue'
MEDIUMSPRINGGREEN = 'mediumspringgreen'
MEDIUMTURQUOISE = 'mediumturquoise'
MEDIUMVIOLETRED = 'mediumvioletred'
MIDNIGHTBLUE = 'midnightblue'
MINTCREAM = 'mintcream'
MISTYROSE = 'mistyrose'
MOCCASIN = 'moccasin'
NAVAJOWHITE = 'navajowhite'
NAVY = 'navy'
OLDLACE = 'oldlace'
OLIVE = 'olive'
OLIVEDRAB = 'olivedrab'
ORANGE = 'orange'
ORANGERED = 'orangered'
ORCHID = 'orchid'
PALEGOLDENROD = 'palegoldenrod'
PALEGREEN = 'palegreen'
PALETURQUOISE = 'paleturquoise'
PALEVIOLETRED = 'palevioletred'
PAPAYAWHIP = 'papayawhip'
PEACHPUFF = 'peachpuff'
PERU = 'peru'
PINK = 'pink'
PLUM = 'plum'
POWDERBLUE = 'powderblue'
PURPLE = 'purple'
REBECCAPURPLE = 'rebeccapurple'
RED = 'red'
ROSYBROWN = 'rosybrown'
ROYALBLUE = 'royalblue'
SADDLEBROWN = 'saddlebrown'
SALMON = 'salmon'
SANDYBROWN = 'sandybrown'
SEAGREEN = 'seagreen'
SEASHELL = 'seashell'
SIENNA = 'sienna'
SILVER = 'silver'
SKYBLUE = 'skyblue'
SLATEBLUE = 'slateblue'
SLATEGRAY = 'slategray'
SLATEGREY = 'slategrey'
SNOW = 'snow'
SPRINGGREEN = 'springgreen'
STEELBLUE = 'steelblue'
TAN = 'tan'
TEAL = 'teal'
THISTLE = 'thistle'
TOMATO = 'tomato'
TURQUOISE = 'turquoise'
VIOLET = 'violet'
WHEAT = 'wheat'
WHITE = 'white'
WHITESMOKE = 'whitesmoke'
YELLOW = 'yellow'
YELLOWGREEN = 'yellowgreen'
NAMED_COLOR = {
ALICEBLUE: rgb(0xF0, 0xF8, 0xFF),
ANTIQUEWHITE: rgb(0xFA, 0xEB, 0xD7),
AQUA: rgb(0x00, 0xFF, 0xFF),
AQUAMARINE: rgb(0x7F, 0xFF, 0xD4),
AZURE: rgb(0xF0, 0xFF, 0xFF),
BEIGE: rgb(0xF5, 0xF5, 0xDC),
BISQUE: rgb(0xFF, 0xE4, 0xC4),
BLACK: rgb(0x00, 0x00, 0x00),
BLANCHEDALMOND: rgb(0xFF, 0xEB, 0xCD),
BLUE: rgb(0x00, 0x00, 0xFF),
BLUEVIOLET: rgb(0x8A, 0x2B, 0xE2),
BROWN: rgb(0xA5, 0x2A, 0x2A),
BURLYWOOD: rgb(0xDE, 0xB8, 0x87),
CADETBLUE: rgb(0x5F, 0x9E, 0xA0),
CHARTREUSE: rgb(0x7F, 0xFF, 0x00),
CHOCOLATE: rgb(0xD2, 0x69, 0x1E),
CORAL: rgb(0xFF, 0x7F, 0x50),
CORNFLOWERBLUE: rgb(0x64, 0x95, 0xED),
CORNSILK: rgb(0xFF, 0xF8, 0xDC),
CRIMSON: rgb(0xDC, 0x14, 0x3C),
CYAN: rgb(0x00, 0xFF, 0xFF),
DARKBLUE: rgb(0x00, 0x00, 0x8B),
DARKCYAN: rgb(0x00, 0x8B, 0x8B),
DARKGOLDENROD: rgb(0xB8, 0x86, 0x0B),
DARKGRAY: rgb(0xA9, 0xA9, 0xA9),
DARKGREY: rgb(0xA9, 0xA9, 0xA9),
DARKGREEN: rgb(0x00, 0x64, 0x00),
DARKKHAKI: rgb(0xBD, 0xB7, 0x6B),
DARKMAGENTA: rgb(0x8B, 0x00, 0x8B),
DARKOLIVEGREEN: rgb(0x55, 0x6B, 0x2F),
DARKORANGE: rgb(0xFF, 0x8C, 0x00),
DARKORCHID: rgb(0x99, 0x32, 0xCC),
DARKRED: rgb(0x8B, 0x00, 0x00),
DARKSALMON: rgb(0xE9, 0x96, 0x7A),
DARKSEAGREEN: rgb(0x8F, 0xBC, 0x8F),
DARKSLATEBLUE: rgb(0x48, 0x3D, 0x8B),
DARKSLATEGRAY: rgb(0x2F, 0x4F, 0x4F),
DARKSLATEGREY: rgb(0x2F, 0x4F, 0x4F),
DARKTURQUOISE: rgb(0x00, 0xCE, 0xD1),
DARKVIOLET: rgb(0x94, 0x00, 0xD3),
DEEPPINK: rgb(0xFF, 0x14, 0x93),
DEEPSKYBLUE: rgb(0x00, 0xBF, 0xFF),
DIMGRAY: rgb(0x69, 0x69, 0x69),
DIMGREY: rgb(0x69, 0x69, 0x69),
DODGERBLUE: rgb(0x1E, 0x90, 0xFF),
FIREBRICK: rgb(0xB2, 0x22, 0x22),
FLORALWHITE: rgb(0xFF, 0xFA, 0xF0),
FORESTGREEN: rgb(0x22, 0x8B, 0x22),
FUCHSIA: rgb(0xFF, 0x00, 0xFF),
GAINSBORO: rgb(0xDC, 0xDC, 0xDC),
GHOSTWHITE: rgb(0xF8, 0xF8, 0xFF),
GOLD: rgb(0xFF, 0xD7, 0x00),
GOLDENROD: rgb(0xDA, 0xA5, 0x20),
GRAY: rgb(0x80, 0x80, 0x80),
GREY: rgb(0x80, 0x80, 0x80),
GREEN: rgb(0x00, 0x80, 0x00),
GREENYELLOW: rgb(0xAD, 0xFF, 0x2F),
HONEYDEW: rgb(0xF0, 0xFF, 0xF0),
HOTPINK: rgb(0xFF, 0x69, 0xB4),
INDIANRED: rgb(0xCD, 0x5C, 0x5C),
INDIGO: rgb(0x4B, 0x00, 0x82),
IVORY: rgb(0xFF, 0xFF, 0xF0),
KHAKI: rgb(0xF0, 0xE6, 0x8C),
LAVENDER: rgb(0xE6, 0xE6, 0xFA),
LAVENDERBLUSH: rgb(0xFF, 0xF0, 0xF5),
LAWNGREEN: rgb(0x7C, 0xFC, 0x00),
LEMONCHIFFON: rgb(0xFF, 0xFA, 0xCD),
LIGHTBLUE: rgb(0xAD, 0xD8, 0xE6),
LIGHTCORAL: rgb(0xF0, 0x80, 0x80),
LIGHTCYAN: rgb(0xE0, 0xFF, 0xFF),
LIGHTGOLDENRODYELLOW: rgb(0xFA, 0xFA, 0xD2),
LIGHTGRAY: rgb(0xD3, 0xD3, 0xD3),
LIGHTGREY: rgb(0xD3, 0xD3, 0xD3),
LIGHTGREEN: rgb(0x90, 0xEE, 0x90),
LIGHTPINK: rgb(0xFF, 0xB6, 0xC1),
LIGHTSALMON: rgb(0xFF, 0xA0, 0x7A),
LIGHTSEAGREEN: rgb(0x20, 0xB2, 0xAA),
LIGHTSKYBLUE: rgb(0x87, 0xCE, 0xFA),
LIGHTSLATEGRAY: rgb(0x77, 0x88, 0x99),
LIGHTSLATEGREY: rgb(0x77, 0x88, 0x99),
LIGHTSTEELBLUE: rgb(0xB0, 0xC4, 0xDE),
LIGHTYELLOW: rgb(0xFF, 0xFF, 0xE0),
LIME: rgb(0x00, 0xFF, 0x00),
LIMEGREEN: rgb(0x32, 0xCD, 0x32),
LINEN: rgb(0xFA, 0xF0, 0xE6),
MAGENTA: rgb(0xFF, 0x00, 0xFF),
MAROON: rgb(0x80, 0x00, 0x00),
MEDIUMAQUAMARINE: rgb(0x66, 0xCD, 0xAA),
MEDIUMBLUE: rgb(0x00, 0x00, 0xCD),
MEDIUMORCHID: rgb(0xBA, 0x55, 0xD3),
MEDIUMPURPLE: rgb(0x93, 0x70, 0xDB),
MEDIUMSEAGREEN: rgb(0x3C, 0xB3, 0x71),
MEDIUMSLATEBLUE: rgb(0x7B, 0x68, 0xEE),
MEDIUMSPRINGGREEN: rgb(0x00, 0xFA, 0x9A),
MEDIUMTURQUOISE: rgb(0x48, 0xD1, 0xCC),
MEDIUMVIOLETRED: rgb(0xC7, 0x15, 0x85),
MIDNIGHTBLUE: rgb(0x19, 0x19, 0x70),
MINTCREAM: rgb(0xF5, 0xFF, 0xFA),
MISTYROSE: rgb(0xFF, 0xE4, 0xE1),
MOCCASIN: rgb(0xFF, 0xE4, 0xB5),
NAVAJOWHITE: rgb(0xFF, 0xDE, 0xAD),
NAVY: rgb(0x00, 0x00, 0x80),
OLDLACE: rgb(0xFD, 0xF5, 0xE6),
OLIVE: rgb(0x80, 0x80, 0x00),
OLIVEDRAB: rgb(0x6B, 0x8E, 0x23),
ORANGE: rgb(0xFF, 0xA5, 0x00),
ORANGERED: rgb(0xFF, 0x45, 0x00),
ORCHID: rgb(0xDA, 0x70, 0xD6),
PALEGOLDENROD: rgb(0xEE, 0xE8, 0xAA),
PALEGREEN: rgb(0x98, 0xFB, 0x98),
PALETURQUOISE: rgb(0xAF, 0xEE, 0xEE),
PALEVIOLETRED: rgb(0xDB, 0x70, 0x93),
PAPAYAWHIP: rgb(0xFF, 0xEF, 0xD5),
PEACHPUFF: rgb(0xFF, 0xDA, 0xB9),
PERU: rgb(0xCD, 0x85, 0x3F),
PINK: rgb(0xFF, 0xC0, 0xCB),
PLUM: rgb(0xDD, 0xA0, 0xDD),
POWDERBLUE: rgb(0xB0, 0xE0, 0xE6),
PURPLE: rgb(0x80, 0x00, 0x80),
REBECCAPURPLE: rgb(0x66, 0x33, 0x99),
RED: rgb(0xFF, 0x00, 0x00),
ROSYBROWN: rgb(0xBC, 0x8F, 0x8F),
ROYALBLUE: rgb(0x41, 0x69, 0xE1),
SADDLEBROWN: rgb(0x8B, 0x45, 0x13),
SALMON: rgb(0xFA, 0x80, 0x72),
SANDYBROWN: rgb(0xF4, 0xA4, 0x60),
SEAGREEN: rgb(0x2E, 0x8B, 0x57),
SEASHELL: rgb(0xFF, 0xF5, 0xEE),
SIENNA: rgb(0xA0, 0x52, 0x2D),
SILVER: rgb(0xC0, 0xC0, 0xC0),
SKYBLUE: rgb(0x87, 0xCE, 0xEB),
SLATEBLUE: rgb(0x6A, 0x5A, 0xCD),
SLATEGRAY: rgb(0x70, 0x80, 0x90),
SLATEGREY: rgb(0x70, 0x80, 0x90),
SNOW: rgb(0xFF, 0xFA, 0xFA),
SPRINGGREEN: rgb(0x00, 0xFF, 0x7F),
STEELBLUE: rgb(0x46, 0x82, 0xB4),
TAN: rgb(0xD2, 0xB4, 0x8C),
TEAL: rgb(0x00, 0x80, 0x80),
THISTLE: rgb(0xD8, 0xBF, 0xD8),
TOMATO: rgb(0xFF, 0x63, 0x47),
TURQUOISE: rgb(0x40, 0xE0, 0xD0),
VIOLET: rgb(0xEE, 0x82, 0xEE),
WHEAT: rgb(0xF5, 0xDE, 0xB3),
WHITE: rgb(0xFF, 0xFF, 0xFF),
WHITESMOKE: rgb(0xF5, 0xF5, 0xF5),
YELLOW: rgb(0xFF, 0xFF, 0x00),
YELLOWGREEN: rgb(0x9A, 0xCD, 0x32),
}
|
aggregate_genres = [{"rock": ["symphonic rock", "jazz-rock", "heartland rock", "rap rock", "garage rock", "folk-rock", "roots rock", "adult alternative pop rock", "rock roll", "punk rock", "arena rock", "pop-rock", "glam rock", "southern rock", "indie rock", "funk rock", "country rock", "piano rock", "art rock", "rockabilly", "acoustic rock", "progressive rock", "folk rock", "psychedelic rock", "rock & roll", "blues rock", "alternative rock", "rock and roll", "soft rock", "rock and indie", "hard rock", "pop/rock", "pop rock", "rock", "classic pop and rock", "psychedelic", "british psychedelia", "punk", "metal", "heavy metal"]},
{"alternative/indie": ["adult alternative pop rock", "alternative rock", "alternative metal", "alternative", "lo-fi indie", "indie", "indie folk", "indietronica", "indie pop", "indie rock", "rock and indie"]},
{"electronic/dance": ["dance and electronica", "electro house", "electronic", "electropop", "progressive house", "hip house", "house", "eurodance", "dancehall", "dance", "trap"]},
{"soul": ["psychedelic soul", "deep soul", "neo-soul", "neo soul", "southern soul", "smooth soul", "blue-eyed soul", "soul and reggae", "soul"]},
{"classical/soundtrack": ["classical", "orchestral", "film soundtrack", "composer"]},
{"pop": ["country-pop", "latin pop", "classical pop", "pop-metal", "orchestral pop", "instrumental pop", "indie pop", "sophisti-pop", "pop punk", "pop reggae", "britpop", "traditional pop", "power pop", "sunshine pop", "baroque pop", "synthpop", "art pop", "teen pop", "psychedelic pop", "folk pop", "country pop", "pop rap", "pop soul", "pop and chart", "dance-pop", "pop", "top 40"]},
{"hip-hop/rnb": ["conscious hip hop", "east coast hip hop", "hardcore hip hop", "west coast hip hop", "hiphop", "southern hip hop", "hip-hop", "hip hop", "hip hop rnb and dance hall", "contemporary r b", "gangsta rap", "rapper", "rap", "rhythm and blues", "contemporary rnb", "contemporary r&b", "rnb", "rhythm & blues","r&b", "blues"]},
{"disco": ["disco"]},
{"swing": ["swing"]},
{"folk": ["contemporary folk", "folk"]},
{"country": ["country rock", "country-pop", "country pop", "contemporary country", "country"]},
{"jazz": ["vocal jazz", "jazz", "jazz-rock"]},
{"religious": ["christian", "christmas music", "gospel"]},
{"blues": ["delta blues", "rock blues", "urban blues", "electric blues", "acoustic blues", "soul blues", "country blues", "jump blues", "classic rock. blues rock", "jazz and blues", "piano blues", "british blues", "british rhythm & blues", "rhythm and blues", "blues", "blues rock", "rhythm & blues"]},
{"reggae": ["reggae fusion", "roots reggae", "reggaeton", "pop reggae", "reggae", "soul and reggae"]}]
|
"""
Mock module for _luastack C++ extension.
Behaves like true _luastack module, but operates an imaginary Lua stack
represented by a list.
"""
class StackPad:
"""Stub for padding the stack to make indexing start at 1."""
def __repr__(self):
return "<StackPad>"
stack = [StackPad()] # Imaginary Lua stack
references = {} # Lua reference registry
def top():
return len(stack) - 1
def pop(n=1):
for _ in range(n):
stack.pop()
def push(n):
stack.append(stack[n])
def push_nil():
stack.append(None)
def push_globals():
create_table()
def convert_py_to_lua(o):
stack.append(o)
def convert_lua_to_py(i=-1):
return stack[i]
def get_field(i, name):
assert isinstance(i, int)
assert isinstance(name, str)
print("get_field", i, name, "\nBefore operation")
stack_dump()
val = stack[i][name]
stack.append(val)
print("After operation")
stack_dump()
print()
def set_field(i, name):
assert isinstance(i, int)
assert isinstance(name, str)
print("set_field", i, name, "\nBefore operation")
stack_dump()
stack[i][name] = stack[-1]
stack.pop()
print("After operation")
stack_dump()
print()
def get_table(i):
assert isinstance(i, int)
print("get_table", i, "\nBefore operation")
stack_dump()
key = stack[-1]
value = stack[i][key]
stack[-1] = value # Replacing key with value
print("After operation")
stack_dump()
print()
def set_table(i):
assert isinstance(i, int)
print("set_table", i, "\nBefore operation")
stack_dump()
key, value = stack[-2], stack[-1]
stack[i][key] = value
del stack[-1] # Deleting value
del stack[-1] # Deleting key
print("After operation")
stack_dump()
print()
def call(n_args, n_returns):
"""Stub. Always replaced with a mock by mocker.patch()."""
raise NotImplementedError("call() should always be mocked")
python_next = next
def next(table_index):
pop()
try:
key, value = python_next(table_index)
stack.append(key)
stack.append(value)
return 1
except StopIteration:
return 0
def reference_create():
referent = stack.pop()
references[id(referent)] = referent
return id(referent)
def reference_push(ref):
stack.append(references[ref])
def reference_free(ref):
del references[ref]
def create_table():
stack.append({})
def stack_dump():
print("Stack:", stack)
|
# Number of images used for training (rest goes for validation)
train_size = 55000
# Image width and height of mnist
width = 28
height = 28
# The total number of labels
num_labels = 10
# The number of batches to prefetch when training on GPU
num_prefetch = 5
# Number of neurons the weight matrices as specified in the document about the challenge
num_neurons = [1000, 1000, 500, 200]
# Testing with prunning for
prune_k = [0.0, 0.25, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 0.97, 0.99]
# Prune types
prune_types = [None, "weight_pruning", "unit_pruning"]
|
#recursive solution
def fib(n):
if (n<=2):
return 1
return fib(n-1)+fib(n-2)
#print(fib(6)) #should be 8
#dp solution
def fib_dp(n):
a = [0]*n
a[0] = a[1] = 1
for i in range(2, n):
a[i] = a[i-1] + a[i-2]
#print(a)
return a
fib_dp(6)
|
preco = float(input('Digite o preço do produto: '))
pagamento = int(input('Digite a forma de pagamento (0 (avista), 1 (cartão avista) ou + número de prestações: '))
if pagamento == 0:
preco = preco * 0.9
elif pagamento == 1:
preco = preco * 0.95
elif pagamento == 2:
preco = preco / 2
else:
preco = preco * 1.2 / pagamento
print('Você irá pagar: R$ {:.2f}'.format(preco))
print('{:=^20}'.format('bolsonaro'))
|
## configuration settings
c = get_config()
## Configure SSL -----------------------------------------------
c.JupyterHub.ssl_key = "/srv/jupyterhub/ssl/jhub.privkey.pem"
c.JupyterHub.ssl_cert = "/srv/jupyterhub/ssl/jhub.fullchain.pem"
c.JupyterHub.ip = '128.59.232.200'
c.JupyterHub.port = 443
## Configure OAuth ----------------------------------------------
c.JupyterHub.authenticator_class = 'oauthenticator.GitHubOAuthenticator'
c.Authenticator.oauth_callback_url = 'https://jhub.eaton-lab.org/hub/oauth_callback'
c.Authenticator.client_id = 'fee71ad7b23fe4daa861'
c.Authenticator.client_secret = '...'
## any members of these GH organization are whitelisted
c.Authenticator.admin_users = {"eaton-lab", "isaacovercast"}
c.Authenticator.whitelist = {
"dereneaton",
"eaton-lab",
"isaacovercast",
"pdsb-test-student",
"pmckenz1",
}
# Mount the real user's Docker volume on the host to the notebook user's
c.JupyterHub.spawner_class = 'dockerspawner.DockerSpawner'
c.DockerSpawner.notebook_dir = '/home/jovyan/'
c.DockerSpawner.image = 'dereneaton/jhub'
c.DockerSpawner.volumes = {
# user's persistent volume
'jhub-user-{username}': '/home/jovyan/work',
# admin's r/o pre-made data dir
'data': {
'bind': '/home/jovyan/data',
'mode': 'ro',
},
}
c.DockerSpawner.remove_containers = True
c.DockerSpawner.mem_limit = '16G'
# set docker containers need to find the hub IP
c.JupyterHub.hub_ip = c.JupyterHub.ip
# max days to stay connected
c.JupyterHub.cookie_max_age_days = 5
# max number of users
c.JupyterHub.active_server_limit = 40
|
class Config(object):
DEBUG = True
DEVELOPMENT = True
class ProductionConfig(Config):
DEBUG = False
DEVELOPMENT = False
|
N, M = map(int, input().split())
G = [[] for _ in range(N)]
for _ in range(M):
A, B = map(int, input().split())
G[A].append(B)
G[B].append(A)
dist = [-1] * N
nodes = [[] for _ in range(N)]
dist[0] = 0
nodes[0] = [0]
for k in range(1, N):
for v in nodes[k-1]:
for next_v in G[v]:
if dist[next_v] != -1:
continue
dist[next_v] = dist[v] + 1
nodes[k].append(next_v)
print(max(dist))
|
# -*- coding: UTF-8 -*-
class Global:
G_TEXT_LOGO = '''
____ _
/ __ )(_)___ ____ _____
/ __ / / __ \/ __ `/ __ \\
/ /_/ / / / / / /_/ / /_/ /
/_____/_/_/ /_/\__, /\____/
/____/
'''
G_AUTHOR_NAME = 'LiBin (Bingo)'
G_CONTACT_ME = 'linux_bingo@163.com'
G_COPYRIGHT_INFO = 'Copyright©2019-2021 Bingo. All Rights Reserved.'
G_REQUIRED_DIR = '.\\Required'
G_DEPENDENCE_FILE = '.\\Required\\dependence.json'
G_SETTINGS_FILE = '.\\Required\\settings.json'
G_RESOURCE_DIR = '.\\Required\\Resource'
G_INTERFACE_DIR = '.\\Interface'
G_SCRIPTS_DIR = '.\\Interface\\Scripts'
G_DOWNLOAD_DIR = '.\\Download'
G_PID_DIR = ''
G_RUN_DIR = '.\\Run'
G_LOG_PATH = '.\\Run\\tool.log'
G_PACK_ZIP = 'package.zip'
# 内部分隔符,与common_function.sh脚本中对应
G_INNER_SPLIT = '____BINGO_FILTER____'
# cache 数据分隔符,与common_function.sh脚本中对应
G_CACHE_SPLIT = '____BINGO_CACHE____'
G_SERVER_UPLOAD = '%s/__UPLOAD__'
G_SERVER_DOWNLOAD = '%s/__DOWNLOAD__'
|
n = [1, 2, 3, 4, 5]
new = []
k = int(input('Сдвиг: '))
for _ in range(5):
new.append(n[-k])
k -= 1
print(n)
print(new)
|
def store_value(redis_client,key_name,value):
redis_client.setnx(key_name,value)
return True
def get_key_value(redis_client,key_name):
return redis_client.get(key_name)
|
class HTTPException(Exception):
def __init__(self, status: int, reason: str):
self.status = status
self.reason = reason
def __str__(self):
return "HTTPException: {}: {}".format(self.status, self.reason)
|
#!/usr/bin/env python3
def find_root(n, m):
r = int(pow(m, 1 / n))
if r**n == m:
return r
if (r + 1)**n == m:
return r + 1
return -1
for t in range(int(input())):
print(find_root(*map(int, input().split())))
|
class QuantumProcessor:
"""A class for defining a quantum processor"""
def __init__(self, qubit_num=1, execution_time=0.1):
"""Define a quantum processor
Args:
qubit_num (int, optional): The number of qubits. Defaults to 1.
execution_time (float, optional): The execution time of each quantum gate. Defaults to 0.1.
"""
self.id = 0
self.qubit_num = qubit_num
self.execution_time = execution_time
def set_id(self, id_):
"""Set a processor id to this quantum processor
Args:
id_ (int): A processor id
"""
self.id = id_
def get_id(self):
"""Return the id of this quantum processor
Returns:
int: The id of this quantum processor
"""
return self.id
def get_info(self):
"""Return an details about properties of this quantum processor
Returns:
dict: A dict that contains details of this quantum processor
"""
info = {
"id": self.id,
"qubit_num": self.qubit_num,
"execution_time": self.execution_time
}
return info
|
hooked_function = None
def set_hook(hook):
global hooked_function
hooked_function = hook
hooked_function
def do_it():
if hooked_function != None:
hooked_function()
else:
print("Did not get hooked")
|
# assign first item to dictionary, give value of 1
# go through items
# if item name isn't equal to any dictionary, set it to a new dictionary
# if item name equals existing dictionary, set that dictionary's value to +=1
# after everything, print dictionaries
people = {}
with open('tweeters.txt') as file:
for line in file:
person = line.strip()
people[person] = people.get(person, 0) + 1
with open('tweets.txt', 'a') as file:
for i in people:
file.write(str(i) + ': ' + str(people[i]) + '\n')
|
#! /usr/bin/env python
"""
Some type definitions for metadata extraction
"""
class MetadataError(RuntimeError):
pass
|
USER_INFORMATION ={
"object": "user",
"url": "https://api.wanikani.com/v2/user",
"data_updated_at": "2020-05-01T05:20:41.769053Z",
"data": {
"id": "7a18daeb-4067-4e77-b0ea-230c7c347ea8",
"username": "Tadgh11",
"level": 12,
"profile_url": "https://www.wanikani.com/users/Tadgh11",
"started_at": "2013-07-09T12:02:54.952786Z",
"subscription": {
"active": True,
"type": "lifetime",
"max_level_granted": 60,
"period_ends_at": None
},
"current_vacation_started_at": None,
"preferences": {
"lessons_batch_size": 5,
"lessons_autoplay_audio": True,
"reviews_autoplay_audio": False,
"lessons_presentation_order": "ascending_level_then_subject",
"reviews_display_srs_indicator": True
}
}
}
SUBJECT = {
"id": 2467,
"object": "vocabulary",
"url": "https://api.wanikani.com/v2/subjects/2467",
"data_updated_at": "2018-05-21T21:52:43.041390Z",
"data": {
"created_at": "2012-02-28T08:04:47.000000Z",
"level": 1,
"slug": "一",
"hidden_at": None,
"document_url": "https://www.wanikani.com/vocabulary/%E4%B8%80",
"characters": "一",
"meanings": [{"meaning": "One", "primary": True, "accepted_answer": True}],
"readings": [{"primary": True, "reading": "いち", "accepted_answer": True}],
"parts_of_speech": ["numeral"],
"component_subject_ids": [440],
"auxiliary_meanings": [],
},
}
SINGLE_SUBJECT = {
"id": 1,
"object": "radical",
"url": "https://api.wanikani.com/v2/subjects/1",
"data_updated_at": "2018-12-05T20:47:15.603277Z",
"data": {
"created_at": "2012-02-27T18:08:16.000000Z",
"level": 1,
"slug": "ground",
"hidden_at": None,
"document_url": "https://www.wanikani.com/radicals/ground",
"characters": "一",
"character_images": [
{
"url": "https://cdn.wanikani.com/images/legacy/1054-subject-1-normal-weight-black-original.png?1520987606",
"metadata": {
"color": "#000000",
"dimensions": "1024x1024",
"style_name": "original",
},
"content_type": "image/png",
}
],
"meanings": [{"meaning": "Ground", "primary": True, "accepted_answer": True}],
"auxiliary_meanings": [],
"amalgamation_subject_ids": [2],
},
}
EMPTY_SUBJECTS_PAGE = {
"object": "collection",
"url": "https://api.wanikani.com/v2/subjects?ids=1%2C2%2C3&slugs=abc%2C123&types=vocabulary",
"pages": {"per_page": 1000, "next_url": None, "previous_url": None},
"total_count": 0,
"data_updated_at": None,
"data": [],
}
SUBJECTS_PAGE = {
"object": "collection",
"url": "https://api.wanikani.com/v2/subjects",
"pages": {"per_page": 1000, "next_url": None, "previous_url": None},
"total_count": 3,
"data_updated_at": "2018-07-05T22:22:07.129381Z",
"data": [
{
"id": 3,
"object": "radical",
"url": "https://api.wanikani.com/v2/subjects/1",
"data_updated_at": "2018-05-21T21:51:35.051365Z",
"data": {
"created_at": "2012-02-27T18:08:16.000000Z",
"level": 1,
"slug": "ground",
"hidden_at": None,
"document_url": "https://www.wanikani.com/radicals/ground",
"characters": "一",
"auxiliary_meanings": [],
"character_images": [
{
"url": "https://cdn.wanikani.com/images/legacy/1054-subject-1-normal-weight-black-original.png?1520987606",
"metadata": {
"color": "#000000",
"dimensions": "1024x1024",
"style_name": "original",
},
"content_type": "image/png",
},
{
"url": "https://cdn.wanikani.com/images/legacy/1054-subject-1-normal-weight-black-1024px.png?1520987606",
"metadata": {
"color": "#000000",
"dimensions": "1024x1024",
"style_name": "1024px",
},
"content_type": "image/png",
},
{
"url": "https://cdn.wanikani.com/images/legacy/1054-subject-1-normal-weight-black-512px.png?1520987606",
"metadata": {
"color": "#000000",
"dimensions": "512x512",
"style_name": "512px",
},
"content_type": "image/png",
},
{
"url": "https://cdn.wanikani.com/images/legacy/1054-subject-1-normal-weight-black-256px.png?1520987606",
"metadata": {
"color": "#000000",
"dimensions": "256x256",
"style_name": "256px",
},
"content_type": "image/png",
},
{
"url": "https://cdn.wanikani.com/images/legacy/1054-subject-1-normal-weight-black-128px.png?1520987606",
"metadata": {
"color": "#000000",
"dimensions": "128x128",
"style_name": "128px",
},
"content_type": "image/png",
},
{
"url": "https://cdn.wanikani.com/images/legacy/1054-subject-1-normal-weight-black-64px.png?1520987606",
"metadata": {
"color": "#000000",
"dimensions": "64x64",
"style_name": "64px",
},
"content_type": "image/png",
},
{
"url": "https://cdn.wanikani.com/images/legacy/1054-subject-1-normal-weight-black-32px.png?1520987606",
"metadata": {
"color": "#000000",
"dimensions": "32x32",
"style_name": "32px",
},
"content_type": "image/png",
},
{
"url": "https://cdn.wanikani.com/images/legacy/576-subject-1-without-css-original.svg?1520987227",
"metadata": {"inline_styles": False},
"content_type": "image/svg+xml",
},
{
"url": "https://cdn.wanikani.com/images/legacy/98-subject-1-with-css-original.svg?1520987072",
"metadata": {"inline_styles": True},
"content_type": "image/svg+xml",
},
],
"meanings": [
{"meaning": "Ground", "primary": True, "accepted_answer": True}
],
"amalgamation_subject_ids": [
440,
449,
450,
451,
488,
531,
533,
568,
590,
609,
633,
635,
709,
710,
724,
783,
808,
913,
932,
965,
971,
1000,
1020,
1085,
1113,
1126,
1137,
1178,
1198,
1240,
1241,
1249,
1340,
1367,
1372,
1376,
1379,
1428,
1431,
1463,
1491,
1506,
1521,
1547,
1559,
1591,
1655,
1674,
1706,
1769,
1851,
1852,
1855,
1868,
1869,
1888,
1970,
2091,
2104,
2128,
2138,
2148,
2171,
2182,
2263,
2277,
2334,
2375,
2419,
2437,
],
},
},
{
"id": 1,
"object": "kanji",
"url": "https://api.wanikani.com/v2/subjects/534",
"data_updated_at": "2018-05-21T21:51:48.658813Z",
"data": {
"created_at": "2012-03-02T02:11:55.000000Z",
"level": 4,
"slug": "央",
"hidden_at": None,
"document_url": "https://www.wanikani.com/kanji/%E5%A4%AE",
"characters": "央",
"meanings": [
{"meaning": "Center", "primary": True, "accepted_answer": True},
{"meaning": "Central", "primary": False, "accepted_answer": True},
{"meaning": "Centre", "primary": False, "accepted_answer": True},
],
"readings": [
{
"type": "onyomi",
"primary": True,
"reading": "おう",
"accepted_answer": True,
}
],
"auxiliary_meanings": [],
"component_subject_ids": [29, 18],
"amalgamation_subject_ids": [2726],
},
},
{
"id": 2,
"object": "vocabulary",
"url": "https://api.wanikani.com/v2/subjects/2467",
"data_updated_at": "2018-05-21T21:52:43.041390Z",
"data": {
"created_at": "2012-02-28T08:04:47.000000Z",
"level": 1,
"slug": "一",
"hidden_at": None,
"document_url": "https://www.wanikani.com/vocabulary/%E4%B8%80",
"characters": "一",
"meanings": [
{"meaning": "One", "primary": True, "accepted_answer": True}
],
"readings": [
{"primary": True, "reading": "いち", "accepted_answer": True}
],
"parts_of_speech": ["numeral"],
"auxiliary_meanings": [],
"component_subject_ids": [440],
},
},
],
}
ASSIGNMENTS_PAGE = {
"object": "collection",
"url": "https://api.wanikani.com/v2/assignments",
"pages": {
"per_page": 500,
"next_url": "https://api.wanikani.com/v2/assignments?page_after_id=62308815",
"previous_url": None,
},
"total_count": 3,
"data_updated_at": "2018-06-30T16:40:52.513654Z",
"data": [
{
"id": 85899,
"object": "assignment",
"url": "https://api.wanikani.com/v2/assignments/85899",
"data_updated_at": "2018-05-09T21:17:31.000000Z",
"data": {
"created_at": "2017-04-15T14:53:56.818837Z",
"subject_id": 2,
"subject_type": "vocabulary",
"level": 5,
"srs_stage": 9,
"unlocked_at": "2017-04-15T14:53:56.818837Z",
"started_at": "2017-04-15T14:53:56.818837Z",
"passed_at": None,
"burned_at": "2018-01-03T00:08:22.451866Z",
"available_at": None,
"resurrected_at": None,
"passed": True,
"hidden": False,
},
},
{
"id": 86555,
"object": "assignment",
"url": "https://api.wanikani.com/v2/assignments/86555",
"data_updated_at": "2018-05-09T21:17:31.000000Z",
"data": {
"created_at": "2017-04-15T14:50:51.503084Z",
"subject_id": 3,
"subject_type": "vocabulary",
"level": 5,
"srs_stage": 9,
"unlocked_at": "2017-04-15T14:50:51.503084Z",
"started_at": "2017-04-15T14:50:51.503084Z",
"passed_at": None,
"burned_at": "2018-02-19T23:02:25.053105Z",
"available_at": None,
"resurrected_at": None,
"passed": True,
"hidden": False,
},
},
{
"id": 86606,
"object": "assignment",
"url": "https://api.wanikani.com/v2/assignments/86606",
"data_updated_at": "2018-05-09T21:17:31.000000Z",
"data": {
"created_at": "2017-04-24T15:17:28.712677Z",
"subject_id": 1,
"subject_type": "vocabulary",
"level": 6,
"srs_stage": 9,
"unlocked_at": "2017-04-24T15:17:28.712677Z",
"started_at": "2017-04-24T15:17:28.712677Z",
"passed_at": "2017-05-10T13:52:56.699204Z",
"burned_at": "2018-02-19T22:46:09.144931Z",
"available_at": None,
"resurrected_at": None,
"passed": True,
"hidden": False,
},
},
],
}
REVIEW_STATISTICS_PAGE = {
"object": "collection",
"url": "https://api.wanikani.com/v2/review_statistics",
"pages": {
"per_page": 500,
"next_url": "https://api.wanikani.com/v2/review_statistics?page_after_id=62308745",
"previous_url": None,
},
"total_count": 5,
"data_updated_at": "2018-05-24T22:02:41.393482Z",
"data": [
{
"id": 85899,
"object": "review_statistic",
"url": "https://api.wanikani.com/v2/review_statistics/85899",
"data_updated_at": "2018-01-03T00:08:22.469272Z",
"data": {
"created_at": "2017-04-15T14:53:56.818837Z",
"subject_id": 1,
"subject_type": "vocabulary",
"meaning_correct": 13,
"meaning_incorrect": 2,
"meaning_max_streak": 7,
"meaning_current_streak": 7,
"reading_correct": 13,
"reading_incorrect": 0,
"reading_max_streak": 13,
"reading_current_streak": 13,
"percentage_correct": 93,
"hidden": False,
},
},
{
"id": 86555,
"object": "review_statistic",
"url": "https://api.wanikani.com/v2/review_statistics/86555",
"data_updated_at": "2018-02-19T23:02:25.114612Z",
"data": {
"created_at": "2017-04-15T14:50:51.503084Z",
"subject_id": 2,
"subject_type": "vocabulary",
"meaning_correct": 11,
"meaning_incorrect": 0,
"meaning_max_streak": 11,
"meaning_current_streak": 11,
"reading_correct": 11,
"reading_incorrect": 1,
"reading_max_streak": 7,
"reading_current_streak": 7,
"percentage_correct": 96,
"hidden": False,
},
},
{
"id": 86606,
"object": "review_statistic",
"url": "https://api.wanikani.com/v2/review_statistics/86606",
"data_updated_at": "2018-02-19T22:46:09.166397Z",
"data": {
"created_at": "2017-04-24T15:17:28.712677Z",
"subject_id": 3,
"subject_type": "vocabulary",
"meaning_correct": 8,
"meaning_incorrect": 0,
"meaning_max_streak": 8,
"meaning_current_streak": 8,
"reading_correct": 8,
"reading_incorrect": 0,
"reading_max_streak": 8,
"reading_current_streak": 8,
"percentage_correct": 100,
"hidden": False,
},
},
{
"id": 86625,
"object": "review_statistic",
"url": "https://api.wanikani.com/v2/review_statistics/86625",
"data_updated_at": "2018-02-19T23:54:40.912486Z",
"data": {
"created_at": "2017-04-24T15:17:29.061457Z",
"subject_id": 1,
"subject_type": "radical",
"meaning_correct": 8,
"meaning_incorrect": 0,
"meaning_max_streak": 8,
"meaning_current_streak": 8,
"reading_correct": 1,
"reading_incorrect": 0,
"reading_max_streak": 1,
"reading_current_streak": 1,
"percentage_correct": 100,
"hidden": False,
},
},
{
"id": 86891,
"object": "review_statistic",
"url": "https://api.wanikani.com/v2/review_statistics/86891",
"data_updated_at": "2018-05-24T21:35:18.556752Z",
"data": {
"created_at": "2017-04-24T15:17:38.685804Z",
"subject_id": 3,
"subject_type": "vocabulary",
"meaning_correct": 12,
"meaning_incorrect": 1,
"meaning_max_streak": 11,
"meaning_current_streak": 11,
"reading_correct": 12,
"reading_incorrect": 1,
"reading_max_streak": 9,
"reading_current_streak": 3,
"percentage_correct": 92,
"hidden": False,
},
},
],
}
STUDY_MATERIALS_PAGE = {
"object": "collection",
"url": "https://api.wanikani.com/v2/study_materials",
"pages": {"per_page": 500, "next_url": None, "previous_url": None},
"total_count": 3,
"data_updated_at": "2018-02-20T21:23:31.246408Z",
"data": [
{
"id": 1539170,
"object": "study_material",
"url": "https://api.wanikani.com/v2/study_materials/1539170",
"data_updated_at": "2017-06-01T19:01:36.573350Z",
"data": {
"created_at": "2017-02-01T15:55:42.058583Z",
"subject_id": 7518,
"subject_type": "vocabulary",
"meaning_note": None,
"reading_note": None,
"meaning_synonyms": ["young girl"],
"hidden": False,
},
},
{
"id": 1661853,
"object": "study_material",
"url": "https://api.wanikani.com/v2/study_materials/1661853",
"data_updated_at": "2017-06-07T00:23:41.431508Z",
"data": {
"created_at": "2017-04-08T14:02:50.758641Z",
"subject_id": 2798,
"subject_type": "vocabulary",
"meaning_note": None,
"reading_note": None,
"meaning_synonyms": ["balls"],
"hidden": False,
},
},
{
"id": 1678472,
"object": "study_material",
"url": "https://api.wanikani.com/v2/study_materials/1678472",
"data_updated_at": "2017-06-12T15:22:15.753065Z",
"data": {
"created_at": "2017-02-23T14:51:21.526934Z",
"subject_id": 3416,
"subject_type": "vocabulary",
"meaning_note": None,
"reading_note": None,
"meaning_synonyms": ["wool"],
"hidden": False,
},
},
],
}
SUMMARY = {
"object": "report",
"url": "https://api.wanikani.com/v2/summary",
"data_updated_at": "2018-07-02T07:00:00.000000Z",
"data": {
"lessons": [{"available_at": "2018-07-02T07:00:00.000000Z", "subject_ids": []}],
"next_reviews_at": "2018-07-02T09:00:00.000000Z",
"reviews": [
{"available_at": "2018-07-02T07:00:00.000000Z", "subject_ids": [1, 2, 3]},
{"available_at": "2018-07-02T08:00:00.000000Z", "subject_ids": [4, 5, 6]},
{"available_at": "2018-07-02T09:00:00.000000Z", "subject_ids": [647]},
{"available_at": "2018-07-02T10:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-02T11:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-02T12:00:00.000000Z", "subject_ids": []},
{
"available_at": "2018-07-02T13:00:00.000000Z",
"subject_ids": [8800, 2944, 2943],
},
{"available_at": "2018-07-02T14:00:00.000000Z", "subject_ids": []},
{
"available_at": "2018-07-02T15:00:00.000000Z",
"subject_ids": [
658,
8738,
3447,
6237,
3449,
3451,
7676,
7528,
7621,
7679,
2822,
3420,
657,
5717,
3436,
7677,
7678,
3452,
7529,
3450,
3438,
7568,
7675,
3437,
3422,
3448,
4877,
7734,
7735,
666,
646,
648,
],
},
{"available_at": "2018-07-02T16:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-02T17:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-02T18:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-02T19:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-02T20:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-02T21:00:00.000000Z", "subject_ids": [2841]},
{"available_at": "2018-07-02T22:00:00.000000Z", "subject_ids": []},
{
"available_at": "2018-07-02T23:00:00.000000Z",
"subject_ids": [2945, 672, 2956, 2932, 2981, 2953, 674, 2936, 654],
},
{"available_at": "2018-07-03T00:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-03T01:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-03T02:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-03T03:00:00.000000Z", "subject_ids": []},
{
"available_at": "2018-07-03T04:00:00.000000Z",
"subject_ids": [
671,
853,
3709,
2959,
4849,
2970,
2960,
2966,
2967,
2952,
2946,
8663,
2962,
2961,
2973,
2938,
2935,
2940,
7461,
2969,
2958,
2937,
7736,
2957,
8801,
2974,
677,
2939,
675,
663,
668,
650,
664,
670,
660,
676,
],
},
{"available_at": "2018-07-03T05:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-03T06:00:00.000000Z", "subject_ids": []},
{"available_at": "2018-07-03T07:00:00.000000Z", "subject_ids": []},
],
},
}
REVIEWS_PAGE = {
"object": "collection",
"url": "https://api.wanikani.com/v2/reviews",
"pages": {
"per_page": 1000,
"next_url": "https://api.wanikani.com/v2/reviews?page_after_id=168707639",
"previous_url": None,
},
"total_count": 3,
"data_updated_at": "2018-07-06T19:30:19.657822Z",
"data": [
{
"id": 6418820,
"object": "review",
"url": "https://api.wanikani.com/v2/reviews/6418820",
"data_updated_at": "2017-08-13T14:32:50.580980Z",
"data": {
"created_at": "2017-08-13T14:32:50.580980Z",
"assignment_id": 69392456,
"subject_id": 2514,
"starting_srs_stage": 8,
"ending_srs_stage": 9,
"incorrect_meaning_answers": 0,
"incorrect_reading_answers": 0,
},
},
{
"id": 6418839,
"object": "review",
"url": "https://api.wanikani.com/v2/reviews/6418839",
"data_updated_at": "2017-08-13T14:32:52.693772Z",
"data": {
"created_at": "2017-08-13T14:32:52.693772Z",
"assignment_id": 30950170,
"subject_id": 69,
"starting_srs_stage": 8,
"ending_srs_stage": 9,
"incorrect_meaning_answers": 0,
"incorrect_reading_answers": 0,
},
},
{
"id": 6418872,
"object": "review",
"url": "https://api.wanikani.com/v2/reviews/6418872",
"data_updated_at": "2017-08-13T14:32:56.587244Z",
"data": {
"created_at": "2017-08-13T14:32:56.587244Z",
"assignment_id": 30950168,
"subject_id": 60,
"starting_srs_stage": 8,
"ending_srs_stage": 9,
"incorrect_meaning_answers": 0,
"incorrect_reading_answers": 0,
},
},
],
}
LEVEL_PROGRESSIONS_PAGE = {
"object": "collection",
"url": "https://api.wanikani.com/v2/level_progressions",
"pages": {"per_page": 500, "next_url": None, "previous_url": None},
"total_count": 2,
"data_updated_at": "2018-07-05T18:03:21.967992Z",
"data": [
{
"id": 15446,
"object": "level_progression",
"url": "https://api.wanikani.com/v2/level_progressions/15446",
"data_updated_at": "2018-07-05T15:04:04.222661Z",
"data": {
"created_at": "2017-09-28T01:24:11.715238Z",
"level": 7,
"unlocked_at": "2017-06-12T15:24:48.181971Z",
"started_at": "2017-09-28T01:24:11.707880Z",
"passed_at": "2018-07-05T15:04:04.210181Z",
"completed_at": None,
"abandoned_at": None,
},
},
{
"id": 365549,
"object": "level_progression",
"url": "https://api.wanikani.com/v2/level_progressions/365549",
"data_updated_at": "2018-07-05T18:03:21.967992Z",
"data": {
"created_at": "2018-07-05T15:04:04.365184Z",
"level": 8,
"unlocked_at": "2018-07-05T15:04:04.338492Z",
"started_at": "2018-07-05T18:03:21.957917Z",
"passed_at": None,
"completed_at": None,
"abandoned_at": None,
},
},
],
}
RESETS_PAGE = {
"object": "collection",
"url": "https://api.wanikani.com/v2/resets",
"pages": {"per_page": 500, "next_url": None, "previous_url": None},
"total_count": 1,
"data_updated_at": "2018-03-21T22:07:39.261116Z",
"data": [
{
"id": 6529,
"object": "reset",
"url": "https://api.wanikani.com/v2/resets/6529",
"data_updated_at": "2018-03-21T22:07:39.261116Z",
"data": {
"created_at": "2018-03-21T22:04:13.313903Z",
"original_level": 13,
"target_level": 1,
"confirmed_at": "2018-03-21T22:05:44.454026Z",
},
}
],
}
|
# -*- coding: utf-8 -*-
""" KVSキャッシュモジュール
get/set/deleteメソッドを実装すること
"""
class Cache(object):
""" キャッシュモジュールのベースクラス """
def get(self, key, default = None):
""" 値の取得
@param key: キー
@param default: 取得できない場合のデフォルト値
@return: 取得した値
"""
raise NotImplementedError("Cache::get")
def set(self, key, value, lifetime = None):
""" 値の設定
@param key: キー
@param value: 値
@param lifetime: 有効期間[sec] （キャッシュシステムへの提案情報として渡しているが、値がこの期間中保持されていること及びこの期間を経過したら削除されることは保証されない）
@return: キャッシュオブジェクト
"""
raise NotImplementedError("Cache::set")
def delete(self, key):
""" キーの削除
@param key: キー
@return: キャッシュオブジェクト
"""
raise NotImplementedError("Cache::delete")
class DictCache(Cache):
""" 辞書によるインメモリキャッシュ
辞書オブジェクトに保存するのでオブジェクトが破棄されると内容も消えるが、インメモリでプロセス間通信等も行わないので極めて高速
"""
def __init__(self):
self.__cache = {}
def get(self, key, default = None):
return self.__cache.get(key, default)
def set(self, key, value, lifetime = None):
self.__cache[key] = value
return self
def delete(self, key):
if key in self.__cache:
del self.__cache[key]
return self
class ChainCache(Cache):
""" 複数のキャッシュオブジェクトのチェイン
メモリ/ディスク/ネットワーク等、速度が異なる複数の保存先の中から高速なものを優先的に使いたい場合に有用
"""
def __init__(self, *cache_list):
""" コンストラクタ
@param cache_list: キャッシュオブジェクト一覧（先に指定したものがgetで優先的に使われる）
"""
self.__cache_list = cache_list
def get(self, key, default = None, lifetime = None):
""" 値の取得
最初に見つかった値を返し、見つからなかったオブジェクトにはその値を入れる
@param key: キー
@param default: 取得できない場合のデフォルト値
@param lifetime: 高優先度のキャッシュオブジェクトに値を設定する際の有効期間[sec]
@return: 取得した値
"""
cache_not_found = []
for cache in self.__cache_list:
value = cache.get(key, default)
if value != default:
# 見つかったらそれまでのオブジェクトに値を設定
self.__set(cache_not_found, key, value, lifetime)
return value
cache_not_found.append(cache)
return default
def set(self, key, value, lifetime = None):
self.__set(self.__cache_list, key, value, lifetime)
return self
def delete(self, key):
""" キーの削除
全てのキャッシュオブジェクトから値を削除
@param key: キー
@return: キャッシュオブジェクト
"""
self.__delete(self.__cache_list, key)
return self
@staticmethod
def __set(cache_list, key, value, lifetime):
""" 指定のキャッシュオブジェクトに値を設定
@param cache_list: キャッシュオブジェクト一覧
@param key: キー
@param value: 値
"""
for cache in cache_list:
cache.set(key, value, lifetime)
@staticmethod
def __delete(cache_list, key):
""" 指定のキャッシュオブジェクトから値を削除
@param cache_list: キャッシュオブジェクト一覧
@param key: キー
"""
for cache in cache_list:
cache.delete(key)
def _test():
""" テスト """
########################################
# 辞書キャッシュのテスト
dict_cache1 = DictCache()
dict_cache1.set("a", 1)
assert dict_cache1.get("a") == 1
assert dict_cache1.get("b") == None
########################################
# チェインキャッシュのテスト
dict_cache2 = DictCache()
dict_cache2.set("b", 2)
chain_cache = ChainCache(dict_cache1, dict_cache2)
# dict_cacheになくてglobal_dict_cache1にあるものを取り出したら、取り出した後でdict_cacheにもコピーされる
assert dict_cache1.get("b") == None
assert chain_cache.get("b") == 2
assert dict_cache1.get("b") == 2
# global_dict_cache1になくてdict_cacheにあるものを取り出しても、global_dict_cache1にはコピーされない
assert dict_cache2.get("a") == None
assert chain_cache.get("a") == 1
assert dict_cache2.get("a") == None
# チェインキャッシュのキーを削除すると全てのキャッシュから削除される
chain_cache.delete("b")
assert dict_cache1.get("b") == None
assert dict_cache2.get("b") == None
print("OK")
if __name__ == "__main__":
_test()
|
class PyginationError(Exception):
pass
class PaginationError(Exception):
pass
|
soma = 0
cont = 0
for imp in range(1, 501, 2):
if imp % 3 == 0:
cont = cont + 1
soma = soma + imp
print('A soma de todos os {} valores solicitados é : {} '.format(cont, soma))
|
## CLASSES
class NamedThing(object):
"""
a databased entity or concept/class
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class NamedThing(object):
"""
a databased entity or concept/class
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class BiologicalEntity(NamedThing):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class BiologicalEntity(NamedThing):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class OrganismalEntity(BiologicalEntity):
"""
A named entity that is either a part of an organism, a whole organism, population or clade of organisms, excluding molecular entities
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class OrganismalEntity(BiologicalEntity):
"""
A named entity that is either a part of an organism, a whole organism, population or clade of organisms, excluding molecular entities
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class PopulationOfIndividualOrganisms(OrganismalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class PopulationOfIndividualOrganisms(OrganismalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Cohort(PopulationOfIndividualOrganisms):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class ExtensionsAndEvidenceAssociationMixin(object):
"""
An injected mixing that adds additional fields to association objects. This is a mixture of (a) closures for denormalization (b) evidence fields specific to the monarch model.
"""
def __init__(self,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class TaxonClosureMixin(object):
"""
An association that includes flattened inlined objects, such as subject_taxon_closure
"""
def __init__(self,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class RelationshipType(object):
"""
An OWL property used as an edge label
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Attribute(object):
"""
A property or characteristic of an entity
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Attribute(object):
"""
A property or characteristic of an entity
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class BiologicalSex(Attribute):
"""
None
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class BiologicalSex(Attribute):
"""
None
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class PhenotypicSex(BiologicalSex):
"""
An attribute corresponding to the phenotypic sex of the individual, based upon the reproductive organs present.
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class GenotypicSex(BiologicalSex):
"""
An attribute corresponding to the genotypic sex of the individual, based upon genotypic composition of sex chromosomes.
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class SeverityValue(Attribute):
"""
describes the severity of a phenotypic feature or disease
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class FrequencyValue(Attribute):
"""
describes the frequency of occurrence of an event or condition
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class ClinicalModifier(Attribute):
"""
Used to characterize and specify the phenotypic abnormalities defined in the Phenotypic abnormality subontology, with respect to severity, laterality, age of onset, and other aspects
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Onset(Attribute):
"""
The age group in which manifestations appear
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class OntologyClass(object):
"""
a concept or class in an ontology, vocabulary or thesaurus
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class OntologyClass(object):
"""
a concept or class in an ontology, vocabulary or thesaurus
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class GeneOntologyClass(OntologyClass):
"""
an ontology class that describes a functional aspect of a gene, gene prodoct or complex
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class ThingWithTaxon(object):
"""
A mixin that can be used on any entity with a taxon
"""
def __init__(self,
in_taxon=None):
self.in_taxon=in_taxon
def __str__(self):
return "in_taxon={} ".format(self.in_taxon)
def __repr__(self):
return self.__str__()
class OrganismTaxon(OrganismalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class IndividualOrganism(OrganismalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class IndividualOrganism(OrganismalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Case(IndividualOrganism):
"""
An individual organism that has a patient role in some clinical context.
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Biosample(OrganismalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class DiseaseOrPhenotypicFeature(BiologicalEntity):
"""
Either one of a disease or an individual phenotypic feature. Some knowledge resources such as Monarch treat these as distinct, others such as MESH conflate.
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class DiseaseOrPhenotypicFeature(BiologicalEntity):
"""
Either one of a disease or an individual phenotypic feature. Some knowledge resources such as Monarch treat these as distinct, others such as MESH conflate.
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Disease(DiseaseOrPhenotypicFeature):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class PhenotypicFeature(DiseaseOrPhenotypicFeature):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Environment(BiologicalEntity):
"""
A feature of the environment of an organism that influences one or more phenotypic features of that organism, potentially mediated by genes
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class InformationContentEntity(NamedThing):
"""
a piece of information that typically describes some piece of biology or is used as support.
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class InformationContentEntity(NamedThing):
"""
a piece of information that typically describes some piece of biology or is used as support.
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class ConfidenceLevel(InformationContentEntity):
"""
Level of confidence in a statement
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class EvidenceType(InformationContentEntity):
"""
Class of evidence that supports an association
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class Publication(InformationContentEntity):
"""
Any published piece of information. Can refer to a whole publication, or to a part of it (e.g. a figure, figure legend, or section highlighted by NLP). The scope is intended to be general and include information published on the web as well as journals.
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class AdministrativeEntity(object):
"""
None
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class AdministrativeEntity(object):
"""
None
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Provider(AdministrativeEntity):
"""
person, group, organization or project that provides a piece of information
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class MolecularEntity(BiologicalEntity):
"""
A gene, gene product, small molecule or macromolecule (including protein complex)
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class MolecularEntity(BiologicalEntity):
"""
A gene, gene product, small molecule or macromolecule (including protein complex)
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class ChemicalSubstance(MolecularEntity):
"""
may be a chemical entity or a formulation with a chemical entity as active ingredient, or a complex material with multiple chemical entities as part
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class AnatomicalEntity(OrganismalEntity):
"""
A subcellular location, cell type or gross anatomical part
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class LifeStage(OrganismalEntity):
"""
A stage of development or growth of an organism, including post-natal adult stages
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class PlanetaryEntity(NamedThing):
"""
Any entity or process that exists at the level of the whole planet
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class PlanetaryEntity(NamedThing):
"""
Any entity or process that exists at the level of the whole planet
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class EnvironmentalProcess(PlanetaryEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class EnvironmentalFeature(PlanetaryEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class ClinicalEntity(NamedThing):
"""
Any entity or process that exists in the clinical domain and outside the biological realm. Diseases are placed under biological entities
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class ClinicalEntity(NamedThing):
"""
Any entity or process that exists in the clinical domain and outside the biological realm. Diseases are placed under biological entities
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class ClinicalTrial(ClinicalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class ClinicalIntervention(ClinicalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class GenomicEntity(MolecularEntity):
"""
an entity that can either be directly located on a genome (gene, transcript, exon, regulatory region) or is encoded in a genome (protein)
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GenomicEntity(MolecularEntity):
"""
an entity that can either be directly located on a genome (gene, transcript, exon, regulatory region) or is encoded in a genome (protein)
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Genome(GenomicEntity):
"""
A genome is the sum of genetic material within a cell or virion.
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Transcript(GenomicEntity):
"""
An RNA synthesized on a DNA or RNA template by an RNA polymerase
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Exon(GenomicEntity):
"""
A region of the transcript sequence within a gene which is not removed from the primary RNA transcript by RNA splicing
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class CodingSequence(GenomicEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GeneOrGeneProduct(GenomicEntity):
"""
a union of genes or gene products. Frequently an identifier for one will be used as proxy for another
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GeneOrGeneProduct(GenomicEntity):
"""
a union of genes or gene products. Frequently an identifier for one will be used as proxy for another
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Gene(GeneOrGeneProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GeneProduct(GeneOrGeneProduct):
"""
The functional molecular product of a single gene. Gene products are either proteins or functional RNA molecules
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GeneProduct(GeneOrGeneProduct):
"""
The functional molecular product of a single gene. Gene products are either proteins or functional RNA molecules
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Protein(GeneProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class RnaProduct(GeneProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class RnaProduct(GeneProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class NoncodingRnaProduct(RnaProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class NoncodingRnaProduct(RnaProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Microrna(NoncodingRnaProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class MacromolecularComplex(MolecularEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GeneGrouping(object):
"""
any grouping of multiple genes or gene products
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class GeneFamily(MolecularEntity):
"""
any grouping of multiple genes or gene products related by common descent
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Zygosity(Attribute):
"""
None
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Genotype(GenomicEntity):
"""
An information content entity that describes a genome by specifying the total variation in genomic sequence and/or gene expression, relative to some extablished background
"""
def __init__(self,
has_zygosity=None,
id=None,
label=None,
in_taxon=None):
self.has_zygosity=has_zygosity
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "has_zygosity={} id={} label={} in_taxon={} ".format(self.has_zygosity,self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Genotype(GenomicEntity):
"""
An information content entity that describes a genome by specifying the total variation in genomic sequence and/or gene expression, relative to some extablished background
"""
def __init__(self,
has_zygosity=None,
id=None,
label=None,
in_taxon=None):
self.has_zygosity=has_zygosity
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "has_zygosity={} id={} label={} in_taxon={} ".format(self.has_zygosity,self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Allele(Genotype):
"""
A genomic feature representing one of a set of coexisting sequence variants at a particular genomic locus
"""
def __init__(self,
has_gene=None,
has_zygosity=None,
id=None,
label=None,
in_taxon=None):
self.has_gene=has_gene
self.has_zygosity=has_zygosity
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "has_gene={} has_zygosity={} id={} label={} in_taxon={} ".format(self.has_gene,self.has_zygosity,self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class SequenceVariant(GenomicEntity):
"""
A genomic feature representing one of a set of coexisting sequence variants at a particular genomic locus.
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Environment(BiologicalEntity):
"""
A feature of the environment of an organism that influences one or more phenotypic features of that organism, potentially mediated by genes
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class DrugExposure(Environment):
"""
A drug exposure is an intake of a particular chemical substance
"""
def __init__(self,
drug=None,
id=None,
label=None):
self.drug=drug
self.id=id
self.label=label
def __str__(self):
return "drug={} id={} label={} ".format(self.drug,self.id,self.label)
def __repr__(self):
return self.__str__()
class Treatment(Environment):
"""
A treatment is targeted at a disease or phenotype and may involve multiple drug 'exposures'
"""
def __init__(self,
treats=None,
has_exposure_parts=None,
id=None,
label=None):
self.treats=treats
self.has_exposure_parts=has_exposure_parts
self.id=id
self.label=label
def __str__(self):
return "treats={} has_exposure_parts={} id={} label={} ".format(self.treats,self.has_exposure_parts,self.id,self.label)
def __repr__(self):
return self.__str__()
class GeographicLocation(PlanetaryEntity):
"""
a location that can be described in lat/long coordinates
"""
def __init__(self,
latitude=None,
longitude=None,
id=None,
label=None):
self.latitude=latitude
self.longitude=longitude
self.id=id
self.label=label
def __str__(self):
return "latitude={} longitude={} id={} label={} ".format(self.latitude,self.longitude,self.id,self.label)
def __repr__(self):
return self.__str__()
class GeographicLocationAtTime(PlanetaryEntity):
"""
a location that can be described in lat/long coordinates, for a particular time
"""
def __init__(self,
latitude=None,
longitude=None,
timepoint=None,
id=None,
label=None):
self.latitude=latitude
self.longitude=longitude
self.timepoint=timepoint
self.id=id
self.label=label
def __str__(self):
return "latitude={} longitude={} timepoint={} id={} label={} ".format(self.latitude,self.longitude,self.timepoint,self.id,self.label)
def __repr__(self):
return self.__str__()
class Association(InformationContentEntity):
"""
A typed association between two entities, supported by evidence
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class Association(InformationContentEntity):
"""
A typed association between two entities, supported by evidence
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GenotypeToGenotypePartAssociation(Association):
"""
Any association between one genotype and a genotypic entity that is a sub-component of it
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GenotypeToGeneAssociation(Association):
"""
Any association between a genotype and a gene. The genotype have have multiple variants in that gene or a single one. There is no assumption of cardinality
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GenotypeToVariantAssociation(Association):
"""
Any association between a genotype and a sequence variant.
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToGeneAssociation(Association):
"""
abstract parent class for different kinds of gene-gene or gene product to gene product relationships. Includes homology and interaction.
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToGeneAssociation(Association):
"""
abstract parent class for different kinds of gene-gene or gene product to gene product relationships. Includes homology and interaction.
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToGeneHomologyAssociation(GeneToGeneAssociation):
"""
A homology association between two genes. May be orthology (in which case the species of subject and object should differ) or paralogy (in which case the species may be the same)
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class MolecularInteraction(Association):
"""
An interaction at the molecular level between two physical entities
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class PairwiseGeneOrProteinInteractionAssociation(GeneToGeneAssociation):
"""
An interaction between two genes or two gene products. May be physical (e.g. protein binding) or genetic (between genes). May be symmetric (e.g. protein interaction) or directed (e.g. phosphorylation)
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToThingAssociation(Association):
"""
An interaction between a chemical entity and another entity
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class CaseToThingAssociation(Association):
"""
An abstract association for use where the case is the subject
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToGeneAssociation(Association):
"""
An interaction between a chemical entity or substance and a gene or gene product. The chemical substance may be a drug with the gene being a target of the drug.
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToDiseaseOrPhenotypicFeatureAssociation(Association):
"""
An interaction between a chemical entity and a phenotype or disease, where the presence of the chemical gives rise to or exacerbates the phenotype
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToPathwayAssociation(Association):
"""
An interaction between a chemical entity and a biological process or pathway
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToGeneAssociation(Association):
"""
An interaction between a chemical entity or substance and a gene or gene product. The chemical substance may be a drug with the gene being a target of the drug.
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class BiosampleToThingAssociation(Association):
"""
An association between a biosample and something
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class BiosampleToDiseaseOrPhenotypicFeatureAssociation(Association):
"""
An association between a biosample and a disease or phenotype
definitional: true
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class EntityToPhenotypicFeatureAssociation(Association):
"""
None
"""
def __init__(self,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier,self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class EntityToDiseaseAssociation(object):
"""
None
"""
def __init__(self,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None):
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
def __str__(self):
return "frequency_qualifier={} severity_qualifier={} onset_qualifier={} ".format(self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier)
def __repr__(self):
return self.__str__()
class ThingToDiseaseOrPhenotypicFeatureAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class DiseaseToThingAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GenotypeToPhenotypicFeatureAssociation(Association):
"""
Any association between one genotype and a phenotypic feature, where having the genotype confers the phenotype, either in isolation or through environment
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class EnvironmentToPhenotypicFeatureAssociation(Association):
"""
Any association between an environment and a phenotypic feature, where being in the environment influences the phenotype
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class DiseaseToPhenotypicFeatureAssociation(Association):
"""
An association between a disease and a phenotypic feature in which the phenotypic feature is associated with the disease in some way
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class CaseToPhenotypicFeatureAssociation(Association):
"""
An association between a case (e.g. individual patient) and a phenotypic feature in which the individual has or has had the phenotype
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class GeneToThingAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToPhenotypicFeatureAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class GeneToDiseaseAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier)
def __repr__(self):
return self.__str__()
class ModelToDiseaseMixin(object):
"""
This mixin is used for any association class for which the subject plays the role of a 'model'
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class GeneToDiseaseAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier)
def __repr__(self):
return self.__str__()
class GeneAsAModelOfDiseaseAssociation(GeneToDiseaseAssociation):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier)
def __repr__(self):
return self.__str__()
class GeneHasVariantThatContributesToDiseaseAssociation(GeneToDiseaseAssociation):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier)
def __repr__(self):
return self.__str__()
class GenotypeToThingAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToExpressionSiteAssociation(Association):
"""
An association between a gene and an expression site, possibly qualified by stage/timing info.
"""
def __init__(self,
stage_qualifier=None,
quantifier_qualifier=None,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.stage_qualifier=stage_qualifier
self.quantifier_qualifier=quantifier_qualifier
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "stage_qualifier={} quantifier_qualifier={} association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.stage_qualifier,self.quantifier_qualifier,self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class SequenceVariantModulatesTreatmentAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToGoTermAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class AssociationResultSet(InformationContentEntity):
"""
None
"""
def __init__(self,
associations=None,
id=None,
label=None):
self.associations=associations
self.id=id
self.label=label
def __str__(self):
return "associations={} id={} label={} ".format(self.associations,self.id,self.label)
def __repr__(self):
return self.__str__()
class GenomicSequenceLocalization(Association):
"""
A relationship between a sequence feature and an entity it is localized to. The reference entity may be a chromosome, chromosome region or information entity such as a contig
"""
def __init__(self,
start_interbase_coordinate=None,
end_interbase_coordinate=None,
genome_build=None,
phase=None,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.start_interbase_coordinate=start_interbase_coordinate
self.end_interbase_coordinate=end_interbase_coordinate
self.genome_build=genome_build
self.phase=phase
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "start_interbase_coordinate={} end_interbase_coordinate={} genome_build={} phase={} association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.start_interbase_coordinate,self.end_interbase_coordinate,self.genome_build,self.phase,self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class SequenceFeatureRelationship(Association):
"""
For example, a particular exon is part of a particular transcript or gene
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class SequenceFeatureRelationship(Association):
"""
For example, a particular exon is part of a particular transcript or gene
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class TranscriptToGeneRelationship(SequenceFeatureRelationship):
"""
A gene is a collection of transcripts
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToGeneProductRelationship(SequenceFeatureRelationship):
"""
A gene is transcribed and potentially translated to a gene product
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ExonToTranscriptRelationship(SequenceFeatureRelationship):
"""
A transcript is formed from multiple exons
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class SequenceFeatureToSequenceRelationship(Association):
"""
Relates a sequence feature such as a gene to its sequence
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneRegulatoryRelationship(Association):
"""
A regulatory relationship between two genes
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class AnatomicalEntityToAnatomicalEntityAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class AnatomicalEntityToAnatomicalEntityAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class AnatomicalEntityPartOfAnatomicalEntityAssociation(AnatomicalEntityToAnatomicalEntityAssociation):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class Occurrent(object):
"""
A processual entity
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Occurrent(object):
"""
A processual entity
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class MolecularActivity(Occurrent):
"""
An execution of a molecular function
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class BiologicalProcess(BiologicalEntity):
"""
One or more causally connected executions of molecular functions
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class BiologicalProcess(BiologicalEntity):
"""
One or more causally connected executions of molecular functions
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class Pathway(BiologicalProcess):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class AnatomicalEntity(OrganismalEntity):
"""
A subcellular location, cell type or gross anatomical part
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class CellularComponent(AnatomicalEntity):
"""
A location in or around a cell
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Cell(AnatomicalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GrossAnatomicalStructure(AnatomicalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class NamedGraph(InformationContentEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class PropertyValuePair(object):
"""
None
"""
def __init__(self,
relation=None,
filler=None):
self.relation=relation
self.filler=filler
def __str__(self):
return "relation={} filler={} ".format(self.relation,self.filler)
def __repr__(self):
return self.__str__()
class RelationshipType(object):
"""
An OWL property used as an edge label
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class PhenotypicSex(BiologicalSex):
"""
An attribute corresponding to the phenotypic sex of the individual, based upon the reproductive organs present.
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class GenotypicSex(BiologicalSex):
"""
An attribute corresponding to the genotypic sex of the individual, based upon genotypic composition of sex chromosomes.
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class SeverityValue(Attribute):
"""
describes the severity of a phenotypic feature or disease
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class FrequencyValue(Attribute):
"""
describes the frequency of occurrence of an event or condition
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class ClinicalModifier(Attribute):
"""
Used to characterize and specify the phenotypic abnormalities defined in the Phenotypic abnormality subontology, with respect to severity, laterality, age of onset, and other aspects
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Onset(Attribute):
"""
The age group in which manifestations appear
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class GeneOntologyClass(OntologyClass):
"""
an ontology class that describes a functional aspect of a gene, gene prodoct or complex
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class ThingWithTaxon(object):
"""
A mixin that can be used on any entity with a taxon
"""
def __init__(self,
in_taxon=None):
self.in_taxon=in_taxon
def __str__(self):
return "in_taxon={} ".format(self.in_taxon)
def __repr__(self):
return self.__str__()
class OrganismTaxon(OrganismalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class Case(IndividualOrganism):
"""
An individual organism that has a patient role in some clinical context.
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Biosample(OrganismalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Disease(DiseaseOrPhenotypicFeature):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class PhenotypicFeature(DiseaseOrPhenotypicFeature):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class ConfidenceLevel(InformationContentEntity):
"""
Level of confidence in a statement
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class EvidenceType(InformationContentEntity):
"""
Class of evidence that supports an association
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class Publication(InformationContentEntity):
"""
Any published piece of information. Can refer to a whole publication, or to a part of it (e.g. a figure, figure legend, or section highlighted by NLP). The scope is intended to be general and include information published on the web as well as journals.
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class Provider(AdministrativeEntity):
"""
person, group, organization or project that provides a piece of information
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class ChemicalSubstance(MolecularEntity):
"""
may be a chemical entity or a formulation with a chemical entity as active ingredient, or a complex material with multiple chemical entities as part
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class LifeStage(OrganismalEntity):
"""
A stage of development or growth of an organism, including post-natal adult stages
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class EnvironmentalProcess(PlanetaryEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class EnvironmentalFeature(PlanetaryEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class ClinicalTrial(ClinicalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class ClinicalIntervention(ClinicalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class Genome(GenomicEntity):
"""
A genome is the sum of genetic material within a cell or virion.
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Transcript(GenomicEntity):
"""
An RNA synthesized on a DNA or RNA template by an RNA polymerase
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Exon(GenomicEntity):
"""
A region of the transcript sequence within a gene which is not removed from the primary RNA transcript by RNA splicing
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class CodingSequence(GenomicEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Gene(GeneOrGeneProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Protein(GeneProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Microrna(NoncodingRnaProduct):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class MacromolecularComplex(MolecularEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GeneGrouping(object):
"""
any grouping of multiple genes or gene products
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class GeneFamily(MolecularEntity):
"""
any grouping of multiple genes or gene products related by common descent
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Zygosity(Attribute):
"""
None
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Allele(Genotype):
"""
A genomic feature representing one of a set of coexisting sequence variants at a particular genomic locus
"""
def __init__(self,
has_gene=None,
has_zygosity=None,
id=None,
label=None,
in_taxon=None):
self.has_gene=has_gene
self.has_zygosity=has_zygosity
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "has_gene={} has_zygosity={} id={} label={} in_taxon={} ".format(self.has_gene,self.has_zygosity,self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class SequenceVariant(GenomicEntity):
"""
A genomic feature representing one of a set of coexisting sequence variants at a particular genomic locus.
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class DrugExposure(Environment):
"""
A drug exposure is an intake of a particular chemical substance
"""
def __init__(self,
drug=None,
id=None,
label=None):
self.drug=drug
self.id=id
self.label=label
def __str__(self):
return "drug={} id={} label={} ".format(self.drug,self.id,self.label)
def __repr__(self):
return self.__str__()
class Treatment(Environment):
"""
A treatment is targeted at a disease or phenotype and may involve multiple drug 'exposures'
"""
def __init__(self,
treats=None,
has_exposure_parts=None,
id=None,
label=None):
self.treats=treats
self.has_exposure_parts=has_exposure_parts
self.id=id
self.label=label
def __str__(self):
return "treats={} has_exposure_parts={} id={} label={} ".format(self.treats,self.has_exposure_parts,self.id,self.label)
def __repr__(self):
return self.__str__()
class GeographicLocation(PlanetaryEntity):
"""
a location that can be described in lat/long coordinates
"""
def __init__(self,
latitude=None,
longitude=None,
id=None,
label=None):
self.latitude=latitude
self.longitude=longitude
self.id=id
self.label=label
def __str__(self):
return "latitude={} longitude={} id={} label={} ".format(self.latitude,self.longitude,self.id,self.label)
def __repr__(self):
return self.__str__()
class GeographicLocationAtTime(PlanetaryEntity):
"""
a location that can be described in lat/long coordinates, for a particular time
"""
def __init__(self,
latitude=None,
longitude=None,
timepoint=None,
id=None,
label=None):
self.latitude=latitude
self.longitude=longitude
self.timepoint=timepoint
self.id=id
self.label=label
def __str__(self):
return "latitude={} longitude={} timepoint={} id={} label={} ".format(self.latitude,self.longitude,self.timepoint,self.id,self.label)
def __repr__(self):
return self.__str__()
class GenotypeToGenotypePartAssociation(Association):
"""
Any association between one genotype and a genotypic entity that is a sub-component of it
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GenotypeToGeneAssociation(Association):
"""
Any association between a genotype and a gene. The genotype have have multiple variants in that gene or a single one. There is no assumption of cardinality
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GenotypeToVariantAssociation(Association):
"""
Any association between a genotype and a sequence variant.
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToGeneHomologyAssociation(GeneToGeneAssociation):
"""
A homology association between two genes. May be orthology (in which case the species of subject and object should differ) or paralogy (in which case the species may be the same)
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class MolecularInteraction(Association):
"""
An interaction at the molecular level between two physical entities
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class PairwiseGeneOrProteinInteractionAssociation(GeneToGeneAssociation):
"""
An interaction between two genes or two gene products. May be physical (e.g. protein binding) or genetic (between genes). May be symmetric (e.g. protein interaction) or directed (e.g. phosphorylation)
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToThingAssociation(Association):
"""
An interaction between a chemical entity and another entity
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class CaseToThingAssociation(Association):
"""
An abstract association for use where the case is the subject
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToGeneAssociation(Association):
"""
An interaction between a chemical entity or substance and a gene or gene product. The chemical substance may be a drug with the gene being a target of the drug.
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToDiseaseOrPhenotypicFeatureAssociation(Association):
"""
An interaction between a chemical entity and a phenotype or disease, where the presence of the chemical gives rise to or exacerbates the phenotype
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToPathwayAssociation(Association):
"""
An interaction between a chemical entity and a biological process or pathway
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ChemicalToGeneAssociation(Association):
"""
An interaction between a chemical entity or substance and a gene or gene product. The chemical substance may be a drug with the gene being a target of the drug.
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class BiosampleToThingAssociation(Association):
"""
An association between a biosample and something
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class BiosampleToDiseaseOrPhenotypicFeatureAssociation(Association):
"""
An association between a biosample and a disease or phenotype
definitional: true
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class EntityToPhenotypicFeatureAssociation(Association):
"""
None
"""
def __init__(self,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier,self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class EntityToDiseaseAssociation(object):
"""
None
"""
def __init__(self,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None):
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
def __str__(self):
return "frequency_qualifier={} severity_qualifier={} onset_qualifier={} ".format(self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier)
def __repr__(self):
return self.__str__()
class ThingToDiseaseOrPhenotypicFeatureAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class DiseaseToThingAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GenotypeToPhenotypicFeatureAssociation(Association):
"""
Any association between one genotype and a phenotypic feature, where having the genotype confers the phenotype, either in isolation or through environment
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class EnvironmentToPhenotypicFeatureAssociation(Association):
"""
Any association between an environment and a phenotypic feature, where being in the environment influences the phenotype
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class DiseaseToPhenotypicFeatureAssociation(Association):
"""
An association between a disease and a phenotypic feature in which the phenotypic feature is associated with the disease in some way
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class CaseToPhenotypicFeatureAssociation(Association):
"""
An association between a case (e.g. individual patient) and a phenotypic feature in which the individual has or has had the phenotype
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class GeneToThingAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToPhenotypicFeatureAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None,
sex_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
self.sex_qualifier=sex_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} sex_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier,self.sex_qualifier)
def __repr__(self):
return self.__str__()
class ModelToDiseaseMixin(object):
"""
This mixin is used for any association class for which the subject plays the role of a 'model'
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class GeneAsAModelOfDiseaseAssociation(GeneToDiseaseAssociation):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier)
def __repr__(self):
return self.__str__()
class GeneHasVariantThatContributesToDiseaseAssociation(GeneToDiseaseAssociation):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None,
frequency_qualifier=None,
severity_qualifier=None,
onset_qualifier=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
self.frequency_qualifier=frequency_qualifier
self.severity_qualifier=severity_qualifier
self.onset_qualifier=onset_qualifier
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} frequency_qualifier={} severity_qualifier={} onset_qualifier={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label,self.frequency_qualifier,self.severity_qualifier,self.onset_qualifier)
def __repr__(self):
return self.__str__()
class GenotypeToThingAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToExpressionSiteAssociation(Association):
"""
An association between a gene and an expression site, possibly qualified by stage/timing info.
"""
def __init__(self,
stage_qualifier=None,
quantifier_qualifier=None,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.stage_qualifier=stage_qualifier
self.quantifier_qualifier=quantifier_qualifier
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "stage_qualifier={} quantifier_qualifier={} association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.stage_qualifier,self.quantifier_qualifier,self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class SequenceVariantModulatesTreatmentAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToGoTermAssociation(Association):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class AssociationResultSet(InformationContentEntity):
"""
None
"""
def __init__(self,
associations=None,
id=None,
label=None):
self.associations=associations
self.id=id
self.label=label
def __str__(self):
return "associations={} id={} label={} ".format(self.associations,self.id,self.label)
def __repr__(self):
return self.__str__()
class GenomicSequenceLocalization(Association):
"""
A relationship between a sequence feature and an entity it is localized to. The reference entity may be a chromosome, chromosome region or information entity such as a contig
"""
def __init__(self,
start_interbase_coordinate=None,
end_interbase_coordinate=None,
genome_build=None,
phase=None,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.start_interbase_coordinate=start_interbase_coordinate
self.end_interbase_coordinate=end_interbase_coordinate
self.genome_build=genome_build
self.phase=phase
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "start_interbase_coordinate={} end_interbase_coordinate={} genome_build={} phase={} association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.start_interbase_coordinate,self.end_interbase_coordinate,self.genome_build,self.phase,self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class TranscriptToGeneRelationship(SequenceFeatureRelationship):
"""
A gene is a collection of transcripts
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneToGeneProductRelationship(SequenceFeatureRelationship):
"""
A gene is transcribed and potentially translated to a gene product
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class ExonToTranscriptRelationship(SequenceFeatureRelationship):
"""
A transcript is formed from multiple exons
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class SequenceFeatureToSequenceRelationship(Association):
"""
Relates a sequence feature such as a gene to its sequence
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class GeneRegulatoryRelationship(Association):
"""
A regulatory relationship between two genes
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class AnatomicalEntityPartOfAnatomicalEntityAssociation(AnatomicalEntityToAnatomicalEntityAssociation):
"""
None
"""
def __init__(self,
association_type=None,
subject=None,
negated=None,
relation=None,
object=None,
qualifiers=None,
publications=None,
provided_by=None,
id=None,
label=None,
subject_extensions=None,
object_extensions=None,
has_evidence_graph=None,
has_evidence_type=None,
has_evidence=None,
subject_taxon=None,
subject_taxon_label=None,
subject_taxon_closure=None,
subject_taxon_closure_label=None,
object_taxon=None,
object_taxon_label=None,
object_taxon_closure=None,
object_taxon_closure_label=None):
self.association_type=association_type
self.subject=subject
self.negated=negated
self.relation=relation
self.object=object
self.qualifiers=qualifiers
self.publications=publications
self.provided_by=provided_by
self.id=id
self.label=label
self.subject_extensions=subject_extensions
self.object_extensions=object_extensions
self.has_evidence_graph=has_evidence_graph
self.has_evidence_type=has_evidence_type
self.has_evidence=has_evidence
self.subject_taxon=subject_taxon
self.subject_taxon_label=subject_taxon_label
self.subject_taxon_closure=subject_taxon_closure
self.subject_taxon_closure_label=subject_taxon_closure_label
self.object_taxon=object_taxon
self.object_taxon_label=object_taxon_label
self.object_taxon_closure=object_taxon_closure
self.object_taxon_closure_label=object_taxon_closure_label
def __str__(self):
return "association_type={} subject={} negated={} relation={} object={} qualifiers={} publications={} provided_by={} id={} label={} subject_extensions={} object_extensions={} has_evidence_graph={} has_evidence_type={} has_evidence={} subject_taxon={} subject_taxon_label={} subject_taxon_closure={} subject_taxon_closure_label={} object_taxon={} object_taxon_label={} object_taxon_closure={} object_taxon_closure_label={} ".format(self.association_type,self.subject,self.negated,self.relation,self.object,self.qualifiers,self.publications,self.provided_by,self.id,self.label,self.subject_extensions,self.object_extensions,self.has_evidence_graph,self.has_evidence_type,self.has_evidence,self.subject_taxon,self.subject_taxon_label,self.subject_taxon_closure,self.subject_taxon_closure_label,self.object_taxon,self.object_taxon_label,self.object_taxon_closure,self.object_taxon_closure_label)
def __repr__(self):
return self.__str__()
class MolecularActivity(Occurrent):
"""
An execution of a molecular function
"""
def __init__(self):
pass
def __str__(self):
return "".format()
def __repr__(self):
return self.__str__()
class Pathway(BiologicalProcess):
"""
None
"""
def __init__(self,
id=None,
label=None):
self.id=id
self.label=label
def __str__(self):
return "id={} label={} ".format(self.id,self.label)
def __repr__(self):
return self.__str__()
class CellularComponent(AnatomicalEntity):
"""
A location in or around a cell
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class Cell(AnatomicalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
class GrossAnatomicalStructure(AnatomicalEntity):
"""
None
"""
def __init__(self,
id=None,
label=None,
in_taxon=None):
self.id=id
self.label=label
self.in_taxon=in_taxon
def __str__(self):
return "id={} label={} in_taxon={} ".format(self.id,self.label,self.in_taxon)
def __repr__(self):
return self.__str__()
|
#!/usr/bin/env python3
def part_one(file):
return(min(main(file)))
def part_two(file):
return(max(main(file)))
def main(file):
distances = dict()
cities = set([s.strip().split(" ")[0] for s in open(file)])
cities.update([s.strip().split(" ")[2] for s in open(file)])
for city in cities:
distances[city] = dict()
for line in open(file):
args = line.strip().split(" ")
distances[args[0]][args[2]] = int(args[4])
distances[args[2]][args[0]] = int(args[4])
record = []
for city in distances:
travel_to_next_city(record, distances, [city], 0)
return record
def travel_to_next_city(record, distances, cities_travelled, distance_travelled):
if len(distances) == len(cities_travelled):
record.append(distance_travelled)
else:
for city in distances:
if city not in cities_travelled:
distance_to_next_city = distances[cities_travelled[-1]][city]
new_cities_travelled = cities_travelled.copy()
new_cities_travelled.append(city)
travel_to_next_city(record, distances, new_cities_travelled, distance_travelled + distance_to_next_city)
if __name__ == "__main__":
# import doctest
# doctest.testmod()
print(part_one(r"2015\2015_09_distances.txt"))
print(part_two(r"2015\2015_09_distances.txt"))
|
#Handling Exceptions
try:
age = int(input("Enter your age:"))
except ValueError as ex:
print(ex)
print(type(ex))
print("Please enter valid age!")
else:
print("else part executed")
|
def uncycle(list):
if len(list) <= 3:
return max(list)
m = int(len(list) / 2)
if list[0] < list[m]:
return uncycle(list[m:])
else:
return uncycle(list[:m])
|
def _build_csv_path(target:str, directory:str, cell_line:str):
return "{target}/{directory}/{cell_line}.csv".format(
target=target,
directory=directory,
cell_line=cell_line
)
def get_raw_epigenomic_data_path(target:str, cell_line:str):
return _build_csv_path(target, "epigenomic_data", cell_line)
def get_raw_nucleotides_sequences_path(target:str, cell_line:str):
return _build_csv_path(target, "one_hot_encoded_expanded_regions", cell_line)
def get_raw_classes_path(target:str, cell_line:str):
return _build_csv_path(target, "one_hot_encoded_classes", cell_line)
|
# -*- coding: utf-8 -*-
# Copyright: (c) 2017, Wayne Witzel III <wayne@riotousliving.com>
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
class ModuleDocFragment(object):
# Ansible Tower documentation fragment
DOCUMENTATION = r'''
options:
tower_host:
description:
- URL to your Tower instance.
type: str
tower_username:
description:
- Username for your Tower instance.
type: str
tower_password:
description:
- Password for your Tower instance.
type: str
validate_certs:
description:
- Whether to allow insecure connections to Tower.
- If C(no), SSL certificates will not be validated.
- This should only be used on personally controlled sites using self-signed certificates.
type: bool
aliases: [ tower_verify_ssl ]
tower_config_file:
description:
- Path to the Tower config file.
type: path
requirements:
- ansible-tower-cli >= 3.0.2
notes:
- If no I(config_file) is provided we will attempt to use the tower-cli library
defaults to find your Tower host information.
- I(config_file) should contain Tower configuration in the following format
host=hostname
username=username
password=password
'''
|
def main():
question = input("Please what type of variation is it ... |> ")
if question == "direct":
question = input("Please what is the value of the initial 1st variable => ").isdigit()
if question:
int(question)
another_question = input("Please what is the value of the initial 2nd variable => ").isdigit()
if another_question:
int(another_question)
direct_variation(question, another_question)
elif question == "inverse":
pass
elif question == "joint":
pass
elif question == "partial":
pass
else:
print("Sorry can't find the type of variation mentioned ...")
exit()
def direct_variation(initial_var, another_initial_var):
def find_constant(value_1st_var, value_2nd_var):
side = value_1st_var / value_2nd_var
another_side = value_2nd_var / value_2nd_var
k = side
return k
k = find_constant(initial_var, another_initial_var)
print(k)
main()
|
def Values_Sum_Greater(Test_Dict):
return sum(list(Test_Dict.keys())) < sum(list(Test_Dict.values()))
Test_Dict = {5: 3, 1: 3, 10: 4, 7: 3, 8: 1, 9: 5}
print(Values_Sum_Greater(Test_Dict))
|
class Concept:
ID = None
descriptions = None
definition = None
def __init__(self, ID=None, descriptions=None, definition = None):
self.ID = ID
self.descriptions = [] if descriptions is None else descriptions
self.definition = None
class Description:
ID = None
concept_ID = None
term = None
def __init__(self, ID=None, concept_ID=None, term=None):
self.ID = ID
self.concept_ID = concept_ID
self.term = term
class Definition:
ID = None
concept_ID = None
text = None
def __init__(self, ID=None, concept_ID=None, text=None):
self.ID = ID
self.concept_ID = concept_ID
self.text = text
|
expected_output = {
'pvst': {
'a': {
'pvst_id': 'a',
'vlans': {
2: {
'vlan_id': 2,
'designated_root_priority': 32768,
'designated_root_address': '0021.1bff.d973',
'designated_root_max_age': 20,
'designated_root_forward_delay': 15,
'bridge_priority': 32768,
'sys_id_ext': 0,
'bridge_address': '8cb6.4fff.6588',
'bridge_max_age': 20,
'bridge_forward_delay': 15,
'bridge_transmit_hold_count': 6,
'interface': {
'GigabitEthernet0/7/0/0': {
'name': 'GigabitEthernet0/7/0/0',
'cost': 20000,
'role': 'DSGN',
'port_priority': 128,
'port_num': 1,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '8cb6.4fff.6588',
'designated_port_priority': 128,
'designated_port_num': 1,
},
'GigabitEthernet0/7/0/1': {
'name': 'GigabitEthernet0/7/0/1',
'cost': 20000,
'role': 'DSGN',
'port_priority': 128,
'port_num': 2,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '8cb6.4fff.6588',
'designated_port_priority': 128,
'designated_port_num': 2,
},
'GigabitEthernet0/7/0/10': {
'name': 'GigabitEthernet0/7/0/10',
'cost': 20000,
'role': 'ROOT',
'port_priority': 128,
'port_num': 3,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '0021.1bff.d973',
'designated_port_priority': 128,
'designated_port_num': 3,
},
'GigabitEthernet0/7/0/11': {
'name': 'GigabitEthernet0/7/0/11',
'cost': 20000,
'role': 'ALT',
'port_priority': 128,
'port_num': 4,
'port_state': 'BLK',
'designated_bridge_priority': 32768,
'designated_bridge_address': '0021.1bff.d973',
'designated_port_priority': 128,
'designated_port_num': 4,
},
},
},
3: {
'vlan_id': 3,
'designated_root_priority': 32768,
'designated_root_address': '0021.1bff.d973',
'designated_root_max_age': 20,
'designated_root_forward_delay': 15,
'bridge_priority': 32768,
'sys_id_ext': 0,
'bridge_address': '8cb6.4fff.6588',
'bridge_max_age': 20,
'bridge_forward_delay': 15,
'bridge_transmit_hold_count': 6,
'interface': {
'GigabitEthernet0/7/0/0': {
'name': 'GigabitEthernet0/7/0/0',
'cost': 20000,
'role': 'DSGN',
'port_priority': 128,
'port_num': 1,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '8cb6.4fff.6588',
'designated_port_priority': 128,
'designated_port_num': 1,
},
'GigabitEthernet0/7/0/1': {
'name': 'GigabitEthernet0/7/0/1',
'cost': 20000,
'role': 'DSGN',
'port_priority': 128,
'port_num': 2,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '8cb6.4fff.6588',
'designated_port_priority': 128,
'designated_port_num': 2,
},
'GigabitEthernet0/7/0/10': {
'name': 'GigabitEthernet0/7/0/10',
'cost': 20000,
'role': 'ROOT',
'port_priority': 128,
'port_num': 3,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '0021.1bff.d973',
'designated_port_priority': 128,
'designated_port_num': 3,
},
'GigabitEthernet0/7/0/11': {
'name': 'GigabitEthernet0/7/0/11',
'cost': 20000,
'role': 'ALT',
'port_priority': 128,
'port_num': 4,
'port_state': 'BLK',
'designated_bridge_priority': 32768,
'designated_bridge_address': '0021.1bff.d973',
'designated_port_priority': 128,
'designated_port_num': 4,
},
},
},
4: {
'vlan_id': 4,
'designated_root_priority': 32768,
'designated_root_address': '0021.1bff.d973',
'designated_root_max_age': 20,
'designated_root_forward_delay': 15,
'bridge_priority': 32768,
'sys_id_ext': 0,
'bridge_address': '8cb6.4fff.6588',
'bridge_max_age': 20,
'bridge_forward_delay': 15,
'bridge_transmit_hold_count': 6,
'interface': {
'GigabitEthernet0/7/0/0': {
'name': 'GigabitEthernet0/7/0/0',
'cost': 20000,
'role': 'DSGN',
'port_priority': 128,
'port_num': 1,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '8cb6.4fff.6588',
'designated_port_priority': 128,
'designated_port_num': 1,
},
'GigabitEthernet0/7/0/1': {
'name': 'GigabitEthernet0/7/0/1',
'cost': 20000,
'role': 'DSGN',
'port_priority': 128,
'port_num': 2,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '8cb6.4fff.6588',
'designated_port_priority': 128,
'designated_port_num': 2,
},
'GigabitEthernet0/7/0/10': {
'name': 'GigabitEthernet0/7/0/10',
'cost': 20000,
'role': 'ROOT',
'port_priority': 128,
'port_num': 3,
'port_state': 'FWD',
'designated_bridge_priority': 32768,
'designated_bridge_address': '0021.1bff.d973',
'designated_port_priority': 128,
'designated_port_num': 3,
},
'GigabitEthernet0/7/0/11': {
'name': 'GigabitEthernet0/7/0/11',
'cost': 20000,
'role': 'ALT',
'port_priority': 128,
'port_num': 4,
'port_state': 'BLK',
'designated_bridge_priority': 32768,
'designated_bridge_address': '0021.1bff.d973',
'designated_port_priority': 128,
'designated_port_num': 4,
},
},
},
},
},
},
}
|
t1 = (1, 2, 3, 'a')
t2 = 4, 5, 6, 'b'
t3 = 1,
# print(t1[3])
# for v in t1:
# print(v)
# print(t1 + t2)
n1, n2, *n = t1
print(n1)
# Processo para mudar valor de uma tupla
t1 = list(t1)
t1[1] = 3000
t1 = tuple(t1)
print(t1)
|
#! /root/anaconda3/bin/python
# 例子一
g = 18
def f1():
g = 19
print(g)
f1()
print(g)
# 例子二
def f2():
global g
g = 20
print(g)
f2()
print(g)
# 例子三
def f3():
g += 1
print(g)
try:
f3()
except Exception as err:
print(type(err))
print(err)
|
# Medium
# for loop with twoSum
class Solution:
def threeSum(self, nums: List[int]) -> List[List[int]]:
nums.sort()
result = []
for i in range(len(nums)):
if i>0 and nums[i] == nums[i-1]:
continue
tmp = self.twoSum(nums,i+1,0-nums[i])
for t in tmp:
merge = [nums[i]] + [*t]
result.append([*merge])
return result
def twoSum(self,nums,index,tar):
check = set([])
appear = set([])
result = []
for i in range(index,len(nums)):
if tar - nums[i] in check:
if (tar-nums[i],nums[i]) not in appear:
result.append( [tar-nums[i],nums[i]] )
appear.add((tar-nums[i],nums[i]))
check.add(nums[i])
#print('2sum',result)
return result
|
# You work at Len’s Slice, a new pizza joint in the neighborhood. You are going to use your knowledge of Python lists to organize some of your sales data.
# Your code below:
# Create a list called "toppings" to keep track of the kinds of pizzas you sell
toppings = [["Pepperoni"], ["Pineapple"], ["Cheese"], ["Sausage"], ["Olives"], ["Anchovies"], ["Mushrooms"]]
print(toppings)
# result: [['Pepperoni'], ['Pineapple'], ['Cheese'], ['Sausage'], ['Olives'], ['Anchovies'], ['Mushrooms']]
# Keep track of how much the pizza costs, create a list called prices, with the provided integer values
prices = [2, 6, 1, 3, 2, 7, 2]
print(prices)
# result: [2, 6, 1, 3, 2, 7, 2]
# Count the number of occurences of "2" in the "prices" list and store the result in a variable called "num_two_dollar_slices". Print.
num_two_dollar_slices = prices.count(2)
print(num_two_dollar_slices)
# result: 3
# Find the length of the toppings list and store in a variable called "num_pizzas"
num_pizzas = len(toppings)
print(num_pizzas)
# result: 7
# Print the string We sell [num_pizzas] different kinds of pizza!, where [num_pizzas] represents the value of our variable num_pizzas.
print("We sell", num_pizzas, "different kinds of pizza!")
# result: We sell 7 different kinds of pizza!
# Use the existing data about the pizza toppings and prices to create a new two-dimensional list called pizza_and_prices.
# Each sublist in pizza_and_prices should have one pizza topping and an associated price.
#For this new list make sure the prices come before the topping name
pizza_and_prices = [[2, "Pepperoni"], [6, "Pineapple"], [1, "Cheese"], [3, "Sausage"], [2, "Olives"], [7, "Anchovies"], [2, "Mushrooms"]]
print(pizza_and_prices)
#result: [[2, 'Pepperoni'], [6, 'Pineapple'], [1, 'Cheese'], [3, 'Sausage'], [2, 'Olives'], [7, 'Anchovies'], [2, 'Mushrooms']]
# Sort pizza_and_prices so that the pizzas are in the order of increasing price (ascending).
pizza_and_prices.sort()
print(pizza_and_prices)
# result: [[1, 'Cheese'], [2, 'Mushrooms'], [2, 'Olives'], [2, 'Pepperoni'], [3, 'Sausage'], [6, 'Pineapple'], [7, 'Anchovies']]
# Store the first element of pizza_and_prices in a variable called cheapest_pizza.
cheapest_pizza = pizza_and_prices[0]
print(cheapest_pizza)
# result : [1, 'Cheese']
# A man walks into the pizza store and shouts “I will have your MOST EXPENSIVE pizza!”
# Get the last item of the pizza_and_prices list and store it in a variable called priciest_pizza.
priciest_pizza = pizza_and_prices[-1]
print(priciest_pizza)
# result: [7, 'Anchovies']
# It looks like the most expensive pizza from the previous step was our very last "anchovies" slice. Remove it from our pizza_and_prices list since the man bought the last slice.
pizza_and_prices.pop()
print(pizza_and_prices)
# result: [[1, 'Cheese'], [2, 'Mushrooms'], [2, 'Olives'], [2, 'Pepperoni'], [3, 'Sausage'], [6, 'Pineapple']]
# Since there is no longer an "anchovies" pizza, you want to add a new topping called "peppers" to keep your customers excited about new toppings.
# Add the new peppers pizza topping to our list pizza_and_prices.
# Note: Make sure to position it relative to the rest of the sorted data in pizza_and_prices, otherwise our data will not be correctly sorted anymore!
pizza_and_prices.insert(4, [2.5, "Peppers"])
print(pizza_and_prices)
# result: [[1, 'Cheese'], [2, 'Mushrooms'], [2, 'Olives'], [2, 'Pepperoni'], [2.5, 'Peppers'], [3, 'Sausage'], [6, 'Pineapple']]
# Three mice walk into the store. They don’t have much money (they’re mice), but they do each want different pizzas.
# Slice the pizza_and_prices list and store the 3 lowest cost pizzas in a list called three_cheapest.
three_cheapest = pizza_and_prices[:-3]
print(three_cheapest)
# result: [[1, 'Cheese'], [2, 'Mushrooms'], [2, 'Olives'], [2, 'Pepperoni']]
|
def minion_game(string):
string = string.lower()
scoreStuart = 0
scoreKevin = 0
vowels = 'aeiou'
for j, i in enumerate(string):
if i not in vowels:
scoreStuart += len(string) - j
if i in vowels:
scoreKevin += len(string) - j
if scoreStuart > scoreKevin:
print('Stuart', scoreStuart)
elif scoreKevin > scoreStuart:
print('Kevin', scoreKevin)
else:
print('Draw')
if __name__ == '__main__':
s = input()
minion_game(s)
|
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