content stringlengths 7 1.05M |
|---|
info = {
"%%and-small": {
"(0, 99)": "og =%spellout-cardinal-common=;",
"(100, 'inf')": "=%spellout-cardinal-common=;"
},
"%%and-small-n": {
"(0, 99)": "og =%spellout-cardinal-neuter=;",
"(100, 'inf')": "=%spellout-cardinal-neuter=;"
},
"%%ord-de-c": {
"0": "de;",
"(1, 'inf')": "' og =%spellout-ordinal-common=;"
},
"%%ord-de-n": {
"0": "de;",
"(1, 'inf')": "' og =%spellout-ordinal-neuter=;"
},
"%%ord-e-c": {
"0": "e;",
"(1, 99)": "' og =%spellout-ordinal-common=;",
"(100, 'inf')": "' =%spellout-ordinal-common=;"
},
"%%ord-e-n": {
"0": "e;",
"(1, 99)": "' og =%spellout-ordinal-neuter=;",
"(100, 'inf')": "' =%spellout-ordinal-neuter=;"
},
"%%ord-te-c": {
"0": "te;",
"(1, 'inf')": "' =%spellout-ordinal-common=;"
},
"%%ord-te-n": {
"0": "te;",
"(1, 'inf')": "' =%spellout-ordinal-neuter=;"
},
"%%ord-teer-c": {
"0": "te;",
"(1, 'inf')": "er =%spellout-ordinal-common=;"
},
"%%ord-teer-n": {
"0": "te;",
"(1, 'inf')": "er =%spellout-ordinal-neuter=;"
},
"%spellout-cardinal-common": {
"0": "nul;",
"1": "en;",
"2": "to;",
"3": "tre;",
"4": "fire;",
"5": "fem;",
"6": "seks;",
"7": "syv;",
"8": "otte;",
"9": "ni;",
"10": "ti;",
"11": "elleve;",
"12": "tolv;",
"13": "tretten;",
"14": "fjorten;",
"15": "femten;",
"16": "seksten;",
"17": "sytten;",
"18": "atten;",
"19": "nitten;",
"(20, 29)": "[>>og]tyve;",
"(30, 39)": "[>>og]tredive;",
"(40, 49)": "[>>og]fyrre;",
"(50, 59)": "[>>og]halvtreds;",
"(60, 69)": "[>>og]tres;",
"(70, 79)": "[>>og]halvfjerds;",
"(80, 89)": "[>>og]firs;",
"(90, 99)": "[>>og]halvfems;",
"(100, 199)": "hundrede[ og >>];",
"(200, 999)": "<%spellout-cardinal-neuter<hundrede[ og >>];",
"(1000, 1999)": "tusinde[ >%%and-small>];",
"(2000, 999999)": "<%spellout-cardinal-neuter< tusinde[ >%%and-small>];",
"(1000000, 1999999)": "million[ >>];",
"(2000000, 999999999)": "<< millioner[ >>];",
"(1000000000, 1999999999)": "milliard[ >>];",
"(2000000000, 999999999999)": "<< milliarder[ >>];",
"(1000000000000, 1999999999999)": "billion[ >>];",
"(2000000000000, 999999999999999)": "<< billioner[ >>];",
"(1000000000000000, 1999999999999999)": "billiard[ >>];",
"(2000000000000000, 999999999999999999)": "<< billiarder[ >>];",
"(1000000000000000000, 'inf')": "=#,##0=;"
},
"%spellout-cardinal-neuter": {
"0": "nul;",
"1": "et;",
"(2, 99)": "=%spellout-cardinal-common=;",
"(100, 199)": "hundrede[ og >>];",
"(200, 999)": "<%spellout-cardinal-neuter<hundrede[ og >>];",
"(1000, 1999)": "tusind[ >%%and-small-n>];",
"(2000, 999999)": "<%spellout-cardinal-neuter< tusind[ >%%and-small-n>];",
"(1000000, 1999999)": "en million[ >>];",
"(2000000, 999999999)": "<%spellout-cardinal-common< millioner[ >>];",
"(1000000000, 1999999999)": "en milliard[ >>];",
"(2000000000, 999999999999)": "<%spellout-cardinal-common< milliarder[ >>];",
"(1000000000000, 1999999999999)": "en billion[ >>];",
"(2000000000000, 999999999999999)": "<%spellout-cardinal-common< billioner[ >>];",
"(1000000000000000, 1999999999999999)": "en billiard[ >>];",
"(2000000000000000, 999999999999999999)": "<%spellout-cardinal-common< billiarder[ >>];",
"(1000000000000000000, 'inf')": "=#,##0=;"
},
"%spellout-numbering": {
"(0, 'inf')": "=%spellout-cardinal-common=;"
},
"%spellout-numbering-year": {
"(0, 9999)": "=%spellout-numbering=;",
"(10000, 'inf')": "=%spellout-numbering=;"
},
"%spellout-ordinal-common": {
"0": "nulte;",
"1": "første;",
"2": "anden;",
"3": "tredje;",
"4": "fjerde;",
"5": "femte;",
"6": "sjette;",
"7": "syvende;",
"8": "ottende;",
"9": "niende;",
"10": "tiende;",
"11": "ellevte;",
"12": "tolvte;",
"(13, 19)": "=%spellout-numbering=de;",
"(20, 29)": "[>%spellout-numbering>og]tyvende;",
"(30, 39)": "[>%spellout-numbering>og]tredivte;",
"(40, 49)": "[>%spellout-numbering>og]fyrrende;",
"(50, 99)": "=%spellout-numbering=indstyvende;",
"(100, 199)": "hundrede>%%ord-de-c>;",
"(200, 999)": "<%spellout-numbering< hundrede>%%ord-de-c>;",
"(1000, 1999)": "tusind>%%ord-e-c>;",
"(2000, 999999)": "<%spellout-numbering< tusind>%%ord-e-c>;",
"(1000000, 1999999)": "million>%%ord-te-c>;",
"(2000000, 999999999)": "<%spellout-numbering< million>%%ord-teer-c>;",
"(1000000000, 1999999999)": "milliard>%%ord-te-c>;",
"(2000000000, 999999999999)": "<%spellout-numbering< milliard>%%ord-teer-c>;",
"(1000000000000, 1999999999999)": "billion>%%ord-te-c>;",
"(2000000000000, 999999999999999)": "<%spellout-numbering< billion>%%ord-teer-c>;",
"(1000000000000000, 1999999999999999)": "billiard>%%ord-te-c>;",
"(2000000000000000, 999999999999999999)": "<%spellout-numbering< billiard>%%ord-teer-c>;",
"(1000000000000000000, 'inf')": "=#,##0=.;"
},
"%spellout-ordinal-neuter": {
"0": "nulte;",
"1": "første;",
"2": "andet;",
"(3, 19)": "=%spellout-ordinal-common=;",
"(20, 29)": "[>%spellout-cardinal-neuter>og]tyvende;",
"(30, 39)": "[>%spellout-cardinal-neuter>og]tredivte;",
"(40, 49)": "[>%spellout-cardinal-neuter>og]fyrrende;",
"(50, 99)": "=%spellout-cardinal-neuter=indstyvende;",
"(100, 199)": "hundrede>%%ord-de-n>;",
"(200, 999)": "<%spellout-cardinal-neuter< hundrede>%%ord-de-n>;",
"(1000, 1999)": "tusinde>%%ord-e-n>;",
"(2000, 999999)": "<%spellout-cardinal-neuter< tusind>%%ord-e-n>;",
"(1000000, 1999999)": "million>%%ord-teer-n>;",
"(2000000, 999999999)": "<%spellout-cardinal-neuter< million>%%ord-teer-n>;",
"(1000000000, 1999999999)": "milliard>%%ord-te-n>;",
"(2000000000, 999999999999)": "<%spellout-cardinal-neuter< milliard>%%ord-teer-n>;",
"(1000000000000, 1999999999999)": "billion>%%ord-te-n>;",
"(2000000000000, 999999999999999)": "<%spellout-cardinal-neuter< billion>%%ord-teer-n>;",
"(1000000000000000, 1999999999999999)": "billiard>%%ord-te-n>;",
"(2000000000000000, 999999999999999999)": "<%spellout-cardinal-neuter< billiard>%%ord-teer-n>;",
"(1000000000000000000, 'inf')": "=#,##0=.;"
}
}
|
def happy_birthday(name):
print("Happy Birthday, dear " + name + "!")
happy_birthday("Trey")
|
class Questions:
"""A class to access the Questions PDI API endpoint."""
def __init__(self):
questions_endpoint = "/questions"
self.url_questions = self.base_url + questions_endpoint
super().__init__()
def get_questions(self, limit=None):
"""Get a list of Questions.
`Args:`
limit: int
Specify limit to return.
`Returns:`
parsons.Table
A Parsons table of all the data.
"""
return self._request(self.url_questions, limit=limit)
|
fname = input('Enter the file name: ')
try:
fhand = open(fname)
except:
print('File cannot be opened:', fname)
exit()
count = 0
total = 0
for line in fhand:
if line.startswith('X-DSPAM-Confidence: '):
count = count + 1 #counts number of lines with X-DSPAM
colpos = line.find(':') #finds colon
num = line[colpos+1:].strip() #removes all text except number
spam = float(num)
total = total + spam
average = total / count
print('Average spam confidence: ', average)
|
#
# The Python Imaging Library.
# $Id$
#
# sequence support classes
#
# history:
# 1997-02-20 fl Created
#
# Copyright (c) 1997 by Secret Labs AB.
# Copyright (c) 1997 by Fredrik Lundh.
#
# See the README file for information on usage and redistribution.
#
##
class Iterator:
"""
This class implements an iterator object that can be used to loop
over an image sequence.
You can use the ``[]`` operator to access elements by index. This operator
will raise an :py:exc:`IndexError` if you try to access a nonexistent
frame.
:param im: An image object.
"""
def __init__(self, im):
if not hasattr(im, "seek"):
raise AttributeError("im must have seek method")
self.im = im
self.position = getattr(self.im, "_min_frame", 0)
def __getitem__(self, ix):
try:
self.im.seek(ix)
return self.im
except EOFError:
raise IndexError # end of sequence
def __iter__(self):
return self
def __next__(self):
try:
self.im.seek(self.position)
self.position += 1
return self.im
except EOFError:
raise StopIteration
def all_frames(im, func=None):
"""
Applies a given function to all frames in an image or a list of videos.
The frames are returned as a list of separate videos.
:param im: An image, or a list of videos.
:param func: The function to apply to all of the image frames.
:returns: A list of videos.
"""
if not isinstance(im, list):
im = [im]
ims = []
for imSequence in im:
current = imSequence.tell()
ims += [im_frame.copy() for im_frame in Iterator(imSequence)]
imSequence.seek(current)
return [func(im) for im in ims] if func else ims
|
def resolve():
s = input()
ret = ""
for c in s:
ret += c.swapcase() # lower() <-> upper()
print(ret)
|
# imc if elif
print(' ')
pe = float(input('Qual é o seu peso? (Kg) '))
al = float(input('Qual sua altura? (m) '))
imc = pe/(al ** 2)
print(' ')
print(' O IMC dessa pessoa é de {:.1f}'.format(imc))
if imc < 18.5:
print(' Você está ABAIXO do peso normal.')
elif 18.5 <= imc < 25:
print(' PARABÉNS!!! Você está na faixa de peso ADEQUADO.')
elif 25 <= imc < 30:
print(' Você está em SOBREPESO.')
elif 30 <= imc < 40:
print(' Você está em OBESIDADE.')
elif imc >= 40:
print(' Você está em OBESIDADE MORBIDA, cuidado!!!')
|
class Oven(object):
def __init__(self, iterable, size: int = None):
self.iterable = iterable
self.size = size if size else len(iterable) // 100
def __iter__(self):
batch = []
for x in self.iterable:
batch.append(x)
if len(batch) >= self.size:
yield batch
batch = []
if batch:
yield batch
|
# https://qiita.com/knhr__/items/cb3ce311508337128714
def dijkstra(nodes):
start_node = nodes[0]
routes_from_start = {n: math.inf for n in nodes}
routes_from_start[start_node] = 0
minHeap = []
# 最初の頂点を追加
heappush(minHeap, (0, start_node))
path = collections.defaultdict(Node)
# ヒープがなくなるまで探索
while minHeap:
(cost, current_node) = heappop(minHeap)
# priority keyは重複するのでここでチェックする
if cost > routes_from_start[current_node]:
continue
for node in current_node.routes:
price_info = current_node.routes[node]
if routes_from_start[node] > price_info + routes_from_start[current_node]:
routes_from_start[node] = price_info + routes_from_start[current_node]
# 最短距離を更新するノードを記録する
path[node.id] = current_node.id
# 更新されたらpriorityに値を追加
heappush(minHeap, (price_info + routes_from_start[current_node], node))
current_node = nodes[-1].id
path_array = []
#最短距離を記録したノードをゴールからたどる
while current_node:
path_array.append(current_node)
if current_node not in path:
break
current_node = path[current_node]
return routes_from_start[nodes[-1]], path_array[::-1]
def read_file(file_path):
file = open(file_path, 'r')
lines = [x.strip() for x in file.readlines()]
return lines
def get_nodes(data):
nodes = []
v, e = data[0].split()
for i in range(1,len(data)):
nodes.append(list(map(int,data[i].split())))
return v, e, nodes
data_path = "sample-data/g1.txt"
data = read_file(data_path)
v, e, nodes = get_nodes(data)
print(v, e)
print(nodes[0])
|
def getIEX_API_KEY():
return readAPI(0)
def getIEX_API_KEY_TEST():
return readAPI(1)
def getNYT_API_KEY():
return readAPI(2)
def readAPI(x):
f = open("api_list.txt", "r")
lines = f.readlines()
return lines[x].translate({ord('\n'): None})
|
class SuperManager:
def __init__(self, entity, db):
self.entity = entity
self.errors = list()
self.db = db
def get_page(self, page_nr=0, max_entries=0, like_search=None, order_by=None, ascendant=True, query=None):
"""Lista los objetos de la base de datos de la entitad asignada en la clase hija.
Parameters
----------
page_nr : int
Page number to display.
max_entries : int
max records per page.
like_search : string, None
Criteria de búsqueda.
order_by : string, None
Nombre de la columna a ordenar.
ascendant : bool
Criteria de sentido de orden.
query:
Returns
-------
dict
Retorna un diccionario en donde la clave objects contiene el reultado del listado.
"""
if not query:
query = self.db.query(self.entity)
if like_search and len(like_search) > 0:
query = query.filter(self.colums_like(self.entity, like_search))
total = query.count()
max_pages = (total - 1) // max_entries + 1
if page_nr < 1:
page_nr = 1
elif page_nr > max_pages:
page_nr = max_pages
if order_by and len(order_by) > 0:
query = self.order_by(query, self.entity, order_by, ascendant)
if total > 0:
query = query.offset((page_nr - 1) * max_entries).limit(max_entries)
return {"max_pages": max_pages, "objects": query}
def colums_like(self, entity, like_search):
"""Retorna una colección de consultas "likes" de cada columna de la entidad asignada.
Parameters
----------
entity : class
Clase entidad mapeada o modelo de sqlalchemy.
like_search : string
Criteria de búsqueda.
Returns
-------
arguments : sqlalchemy.sql.elements.BooleanClauseList
Tipo de dato propio de sqlalchemy, este resultado debe ser pasado como parametro
al metodo filter.
error
"""
i = True
for column in entity.__table__.columns:
if i:
arguments = column.like("%" + like_search + "%")
i = False
else:
arguments = arguments | column.like("%" + like_search + "%")
return arguments
def order_by(self, query, entity, column_name, ascendant):
"""Concatena un order by a consulta dada.
Parameters
----------
query
Consulta sqlalchemy.
entity : class
Clase entidad mapeada o modelo de sqlalchemy.
column_name : string
Nombre de la columna.
ascendant : bool
Sentido de orden establecido.
Returns
-------
query
Consulta sqlalchemy.
"""
column = getattr(entity, column_name, None)
if column is not None:
if ascendant:
return query.order_by(column)
return query.order_by(column.desc())
def obtain(self, key):
return self.db.query(self.entity).get(key)
def list_all(self):
return self.db.query(self.entity)
def many_to_many(self, object):
if hasattr(object, 'secondary_classes'):
for item in object.secondary_classes:
obj_attr = getattr(object, item[0])
keys = obj_attr[:]
obj_attr.clear()
for key in keys:
obj_attr.append(self.db.query(item[1]).
get(key))
return object
def insert(self, object):
object = self.many_to_many(object)
self.db.add(object)
self.db.commit()
return object
def update(self, object):
object = self.many_to_many(object)
self.db.merge(object)
self.db.commit()
return object
def change_state(self, key, state):
obj = self.db.query(self.entity).get(key)
obj.enabled = state
self.db.commit()
return obj
class Error:
def __init__(self, message, detail):
self.message = message
self.detail = detail
|
Dal = int(input('Quantos dias o carro foi alugado? - '))
Kal = int(input('Quantos Kilometros andou?'))
VDal = float(Dal*60)
VKal = float(Kal * 0.15)
print('A viatuta foi alugada por {} dias tendo custado {:.2f}€.'.format(Dal, VDal))
print('A viatura andou {}Km tendo custado {:.2f}€.'.format(Kal, VKal))
print('O valor final do aluguer é de {:.2f}€.'.format(VDal + VKal))
|
#!/usr/bin/env python3
"""The Whole Barn module"""
def check_shapes(mat1, mat2):
"""Check if the two matrices has the same shape
if not return None"""
shape = []
while (isinstance(mat1, list) and isinstance(mat2, list)):
lenMat1 = len(mat1)
lenMat2 = len(mat2)
if lenMat1 != lenMat2:
return None
shape.append(lenMat1)
mat1 = mat1[0]
mat2 = mat2[0]
return shape
def helper(mat1, mat2):
"""Recursion method to sum the matrices"""
# Base case
if not isinstance(mat1, list) and not isinstance(mat2, list):
return mat1 + mat2
ans = []
for m in zip(mat1, mat2):
ans.append(helper(m[0], m[1]))
return ans
def add_matrices(mat1, mat2):
"""Main function"""
if check_shapes(mat1, mat2) is None:
return None
return helper(mat1, mat2)
|
# -*- coding: utf-8 -*-
"""Refresher activity.
This script will use variables, conditionals, lists, dicts, and functions
to print out different greetings for customers based on their
business tier (determined by revenue).
"""
# List of dicts
customers = [
{ "first_name": "Tom", "last_name": "Bell", "revenue": 0 },
{ "first_name": "Maggie", "last_name": "Johnson", "revenue": 1032 },
{ "first_name": "John", "last_name": "Spectre", "revenue": 2543 },
{ "first_name": "Susy", "last_name": "Simmons", "revenue": 5322 }
]
# @TODO Define a function that accepts a customer first_name, last_name, and
# revenue and returns a custom greeting with the full name.
# Use these ranges to determine the business tier (and corresponding message)
# for each customer.
# Platinum = 3001+
# Gold = 2001-3000
# Silver = 1001-2000
# Bronze = 0-1000
def create_greeting(first_name, last_name, revenue):
# @TODO: YOUR CODE HERE!
greeting = ""
return greeting
# @TODO: Loop through the list of customers and use your function to print
# custom greetings for each customer.
# @TODO: YOUR CODE HERE!
|
with open('/home/steven/advent-of-code-2021/day7/input') as input:
lines = input.readlines()
positions = lines[0].split(',')
positions = [int(i) for i in positions]
max_pos = max(positions)
fuel_sums = {}
for i in range(0, max_pos+1):
fuel_sum = 0
for pos in positions:
fuel = abs(i - pos)
fuel_sum += fuel
fuel_sums[i] = fuel_sum
minimum_fuel = min(fuel_sums.values())
for i, fuel_val in enumerate(fuel_sums.values()):
if fuel_val == minimum_fuel:
print(f"OPTIMAL POSITION: {i}")
print(f"FUEL REQUIRED = {minimum_fuel}") |
class Solution:
def simplifyPath(self, path):
tokens = path.split('/') # some of them could be empty == '//'
stack = []
for item in tokens:
if item in ['','.']:
continue
elif item == '..':
if len(stack) > 0:
stack.pop()
else:
stack.append(item)
return "/"+"/".join(stack)
|
#!/usr/bin/python3
def dict_is_equal(dict1, dict2):
"""
"""
assert set(dict1.keys()) == set(dict2.keys())
assert set(dict1.values()) == set(dict2.values())
for k1, v1 in dict1.items():
assert v1 == dict2[k1] |
# -*- coding: utf-8 -*-
# Copyright 2021 Cohesity Inc.
class AlertCategoryEnum(object):
"""Implementation of the 'AlertCategory' enum.
Specifies the category of an Alert.
kDisk - Alert associated with the disk.
kNode - Alert associated with general hardware on a specific node.
kCluster - Alert associated with general hardware in cluster level.
kChassis - Alert associated with the Chassis.
kPowerSupply - Alert associated with the power supply.
kCPU - Alert associated with the CPU usage.
kMemory - Alert associated with the RAM/Memory.
kTemperature - Alert associated with the temperature.
kFan - Alert associated with the fan.
kNIC - Alert associated with network chips and interfaces.
kFirmware - Alert associated with the firmware.
kNodeHealth - Alert associated with node health status.
kOperatingSystem - Alert associated with operating systems.
kDataPath - Alert associated with data management in the cluster.
kMetadata - Alert associated with metadata management.
kIndexing - Alert associated with indexing services.
kHelios - Alert associated with Helios.
kAppMarketPlace - Alert associated with App MarketPlace.
kLicense - Alert associated with licensing.
kSecurity - Alert associated with security.
kUpgrade - Alert associated with upgrade activities.
kClusterManagement - Alert associated with cluster management activities.
kAuditLog - Alert associated with audit log events.
kNetworking - Alert associated with networking issue.
kConfiguration - Alert associated with cluster or system configurations.
kStorageUsage - Alert associated with the disk/domain/cluster storage usage.
kFaultTolerance - Alert associated with the fault tolerance in different levels.
kBackupRestore - Alert associated with Backup-Restore job.
kArchivalRestore - Alert associated with Archival-Restore job.
kRemoteReplication - Alert associated with Replication job.
kQuota - Alert associated with Quotas.
Attributes:
KDISK: TODO: type description here.
KNODE: TODO: type description here.
KCLUSTER: TODO: type description here.
KCHASSIS: TODO: type description here.
KPOWERSUPPLY: TODO: type description here.
KCPU: TODO: type description here.
KMEMORY: TODO: type description here.
KTEMPERATURE: TODO: type description here.
KFAN: TODO: type description here.
KNIC: TODO: type description here.
KFIRMWARE: TODO: type description here.
KNODEHEALTH: TODO: type description here.
KOPERATINGSYSTEM: TODO: type description here.
KDATAPATH: TODO: type description here.
KMETADATA: TODO: type description here.
KINDEXING: TODO: type description here.
KHELIOS: TODO: type description here.
KAPPMARKETPLACE: TODO: type description here.
KLICENSE: TODO: type description here.
KSECURITY: TODO: type description here.
KUPGRADE: TODO: type description here.
KCLUSTERMANAGEMENT: TODO: type description here.
KAUDITLOG: TODO: type description here.
KNETWORKING: TODO: type description here.
KCONFIGURATION: TODO: type description here.
KSTORAGEUSAGE: TODO: type description here.
KFAULTTOLERANCE: TODO: type description here.
KBACKUPRESTORE: TODO: type description here.
KARCHIVALRESTORE: TODO: type description here.
KREMOTEREPLICATION: TODO: type description here.
KQUOTA: TODO: type description here.
"""
KDISK = 'kDisk'
KNODE = 'kNode'
KCLUSTER = 'kCluster'
KCHASSIS = 'kChassis'
KPOWERSUPPLY = 'kPowerSupply'
KCPU = 'kCPU'
KMEMORY = 'kMemory'
KTEMPERATURE = 'kTemperature'
KFAN = 'kFan'
KNIC = 'kNIC'
KFIRMWARE = 'kFirmware'
KNODEHEALTH = 'kNodeHealth'
KOPERATINGSYSTEM = 'kOperatingSystem'
KDATAPATH = 'kDataPath'
KMETADATA = 'kMetadata'
KINDEXING = 'kIndexing'
KHELIOS = 'kHelios'
KAPPMARKETPLACE = 'kAppMarketPlace'
KLICENSE = 'kLicense'
KSECURITY = 'kSecurity'
KUPGRADE = 'kUpgrade'
KCLUSTERMANAGEMENT = 'kClusterManagement'
KAUDITLOG = 'kAuditLog'
KNETWORKING = 'kNetworking'
KCONFIGURATION = 'kConfiguration'
KSTORAGEUSAGE = 'kStorageUsage'
KFAULTTOLERANCE = 'kFaultTolerance'
KBACKUPRESTORE = 'kBackupRestore'
KARCHIVALRESTORE = 'kArchivalRestore'
KREMOTEREPLICATION = 'kRemoteReplication'
KQUOTA = 'kQuota'
|
a=5
b=0
try:
print(a/b)
except ZeroDivisionError:
print("the divisor can't be 0")
m=3
n="1"
try:
print(m+n)
except TypeError:
print("numbers can't calculated with strings") |
expected_output = {
"total_peers":4,
"vrf":{
"default":{
"peer":{
"8":{
"mode":"unsynchronized",
"remote":"8",
"local":"16",
"stratum":8,
"poll":16,
"reach":377,
"delay":0.01311,
"vrf":"default"
}
}
}
},
"clock_state":{
"system_status":{
"clock_state":"unsynchronized"
}
}
}
|
'''
Замена подстроки
'''
inp_str = input()
inp_str = inp_str.replace('1', 'one')
print(inp_str)
|
class Solution(object):
def hasPathSum(self, root, S):
if not root: return False
stack = []
stack.append((root, 0))
while stack:
node, s = stack.pop()
s += node.val
if not node.left and not node.right and s==S: return True
if node.left: stack.append((node.left, s))
if node.right: stack.append((node.right, s))
return False
"""
Time: O(N)
Space: O(N)
DFS
"""
class Solution(object):
def hasPathSum(self, root, targetSum):
if not root: return False
stack = [(root, root.val)]
while stack:
node, total = stack.pop()
if not node.left and not node.right and total==targetSum: return True
if node.left: stack.append((node.left, total+node.left.val))
if node.right: stack.append((node.right, total+node.right.val))
return False
|
"""
Test cases for the worker thread class.
"""
|
# We will register here processors for the message types by name
VERIFIER_REGISTER = dict()
INCOMING_HANDLER = dict()
GARBAGE_COLLECTORS = dict()
def register_verifier(message_type, handler):
""" Verifies a message is valid before forwarding it,
handling it (should it be different?).
"""
VERIFIER_REGISTER[message_type] = handler
def register_incoming_handler(message_type, handler):
""" Registers a function as an incoming message handler for a specific type.
"""
INCOMING_HANDLER[message_type] = handler
def register_garbage_collector(message_type, handler):
""" Registers a function as a periodical garbage collector
for a specific type.
"""
GARBAGE_COLLECTORS[message_type] = handler
async def handle_incoming_message(message, content):
if message['type'] in INCOMING_HANDLER:
return await INCOMING_HANDLER[message['type']](message, content)
else:
return True |
input = """
a:-b.
b:-a.
a v b.
:- not a.
:- not b.
"""
output = """
{a, b}
"""
|
"""01/09/2017
Temperature Calculator
Celsius
Kelvin
Fahrenheit
Rankine
"""
#Define initial unit
initial_unit = input("Enter initial temperature unit " + "c, k, f, r:")
while initial_unit != "c" and initial_unit != "k" and initial_unit != "f" and initial_unit != "r":
initial_unit = input("incorrect unit, try again:")
if initial_unit == "c":
cel = float(input("Degree celsius:"))
kel = cel + 273.15
fah = cel * 9/5 + 32
ran = kel * 9/5
elif initial_unit == "k":
kel = float(input("Kelvin:"))
cel = kel - 273.15
fah = kel * 9/5 - 459.67
ran = kel * 9/5
elif initial_unit == "f":
fah = float(input("Degree fahrenheit:"))
cel = (fah - 32) * 5/9
kel = (fah + 459.67) * 5/9
ran = fah + 459.67
elif initial_unit == "r":
ran = float(input("Degree Rankine:"))
cel = (ran - 491.67) * 5/9
kel = ran * 5/9
fah = ran - 459.67
print(" ")
print("Celsius " + str(cel))
print("Kelvin " + str(kel))
print("Fahrenheit " + str(fah))
print("Rankine " + str(ran)) |
mode = 'image_caption' # caption|image|image_caption|
max_seq_length = 170
model ='uniter-base' # lxmert, uniter-base, visualbert-base, uniter-large
pretrained_weights = '../artifacts/MM/uniter-base.pt'
frcnn_path = '../data/BUTD_features/'
hidden_size = 768
#Data
img_col = 'g5'
img_sep = ','
separator = ' . '
train_batch_size = 32 # Recomended 16 or 32
dev_batch_size = 32
#max_len_tokenized_sentence = -1 # -1 to calculate
#Training
epochs = 12 # Recomended 8 - 12
optimizer = 'AdamW'
lr = 2e-5 # Recomended 5e-5
eps = 1e-8 # Recomended
weight_decay = 0.01
scheduler = 'None' #linear
warmup_steps = int(8000/train_batch_size)
swa_start = 5
swa_scheduler = 'linear' # linear or cosine
gradient_accumulation_steps = 8
clipping_grad_norm = 2
|
# -*- coding: utf-8 -*-
"""Check entry requirements according to a reference format."""
YEAR_OR_DATE = frozenset(['year', 'date'])
AUTHOR_OR_EDITOR = frozenset(['author', 'editor'])
# Requirements for each entry type. Values are 2-tuples of the required fields
# and a list of fields where only one needs to be present
bibtex_requirements = {
'article': (
frozenset([
'author',
'title',
'journal',
'year'
]),
[]
), 'book': (
frozenset([
'title',
'publisher',
'year'
]),
[AUTHOR_OR_EDITOR]
), 'booklet': (
frozenset(['title']),
[]
), 'inbook': (
frozenset([
'title',
'publisher',
'year'
]), [
AUTHOR_OR_EDITOR,
frozenset(['chapter', 'pages'])
]
), 'incollection': (
frozenset([
'author',
'title',
'booktitle',
'publisher',
'year'
]),
[]
), 'inproceedings': (
frozenset([
'author',
'title',
'booktitle',
'year'
]),
[]
), 'manual': (
frozenset(['title']),
[]
), 'masterthesis': (
frozenset([
'author',
'title',
'school',
'year'
]),
[]
), 'misc': (
frozenset(),
[]
), 'phdthesis': (
frozenset([
'author',
'title',
'school',
'year'
]),
[]
), 'proceedings': (
frozenset([
'title',
'year'
]),
[]
), 'techreport': (
frozenset([
'author',
'title',
'institution',
'year'
]),
[]
), 'unpublished': (
frozenset([
'author',
'title',
'note'
]),
[]
)
}
bibtex_requirements['conference'] = bibtex_requirements['inproceedings']
biblatex_requirements = {
'article': (
frozenset(['author', 'title', 'journaltitle']),
[YEAR_OR_DATE]
), 'book': (
frozenset(['author', 'title']),
[YEAR_OR_DATE]
), 'mvbook': (
frozenset(['author', 'title']),
[YEAR_OR_DATE]
), 'booklet': (
frozenset(['title']),
[AUTHOR_OR_EDITOR, YEAR_OR_DATE]
), 'mvcollection': (
frozenset(['editor', 'title']),
[YEAR_OR_DATE]
), 'collection': (
frozenset(['editor', 'title']),
[YEAR_OR_DATE]
), 'incollection': (
frozenset(['author', 'title', 'booktitle']),
[YEAR_OR_DATE]
), 'manual': (
frozenset(['title']),
[AUTHOR_OR_EDITOR, YEAR_OR_DATE]
), 'misc': (
frozenset(),
[]
), 'online': (
frozenset(['title', 'url']),
[AUTHOR_OR_EDITOR, YEAR_OR_DATE]
), 'patent': (
frozenset(['author', 'title', 'number']),
[YEAR_OR_DATE]
), 'periodical': (
frozenset(['editor', 'title']),
[YEAR_OR_DATE]
), 'proceedings': (
frozenset(['title']),
[YEAR_OR_DATE]
), 'inproceedings': (
frozenset(['author', 'title', 'booktitle']),
[YEAR_OR_DATE]
), 'report': (
frozenset(['author', 'title', 'type', 'institution']),
[YEAR_OR_DATE]
), 'set': (
frozenset(['entryset']),
[]
), 'thesis': (
frozenset(['author', 'title', 'type', 'institution']),
[YEAR_OR_DATE]
), 'unpublished': (
frozenset(['author', 'title']),
[YEAR_OR_DATE]
), 'xdata': (
frozenset(),
[]
)
}
mixed_requirements = {} # Possible?
# Set aliases for requirements
biblatex_requirements['report'] = biblatex_requirements['collection']
# Convenience dictionary for selecting reference formats
formats = {
'bibtex': bibtex_requirements,
'biblatex': biblatex_requirements,
'mixed': mixed_requirements
}
def check(entry, format):
"""Check that an entry abides by the format's requirements.
Note that these requirements are not strictly enforced in bibtex or
biblatex. They are more guidelines for achieving well-formatted entries in
your bibliography.
"""
if format in ('relaxed', 'mixed'):
return (frozenset(), [])
if format not in formats:
raise ValueError("Unknown reference format '{0}'".format(format))
requirements = formats[format]
fields = frozenset(entry.fields)
required, either = requirements.get(entry.bibtype, (frozenset(), []))
# We return sets to enable easy comparison between requirements since
# set([1, 2]) == set([2, 1]), but [1, 2] != [2, 1]
return set(required - fields), [set(e) for e in either
if fields.isdisjoint(e)]
def collect(entries, format):
"""Collect all missing requirements for a set of entries."""
result = []
for entry in entries:
required, optional = check(entry, format)
if required or optional:
result.append((entry, (required, optional)))
return result
|
a = list(map(int, input().split()))
b = sorted(list(map(int, input().split())))
p = a[1]
i = 1
while i < a[0]:
if (b[i] + b[i - 1] > p):
break
i += 1
print(i)
|
#!/usr/bin/env python
#
# Copyright 2015 riteme
#
# Fibonacci series:
a, b = 0, 1
bMax = int(input('Enter the max value of number: '))
while b < bMax:
print(b, end = ', ')
a, b = b, a + b
|
class Solution:
def XXX(self, nums: List[int]) -> None:
pre = [0,0,0] # 定义一个三元素的数组A
for num in nums:
pre[num] += 1 # 把原始数组的值当做A的下标，统计每个数字出现的次数
i = 0 # 根据每个数字出现的次数，从0开始重置原始数组
for n in range(len(pre)):
for b in range(pre[n]):
nums[i] = n
i += 1
return nums
|
class Student(object):
def __init__(self, name, score):
self.__name = name
self._score = score
def print_score(self):
print('%s: %s' % (self.__name, self.__score))
bart = Student("Zero", 32)
print(bart)
if __name__ == "__main__":
jump = True
number = 1
while jump:
if number < 4:
number += 1
else:
pass
print("结束") |
"""
Desenvolva um programa que leia o primeiro termo e a razão de uma PA.
No final, mostre os 10 primeiros termos dessa progressão.
"""
print('=-=' * 20)
print(' Progressão Aritmética')
print('=-=' * 20)
priTermo = int(input('Escolha o primeiro termo: '))
razao = int(input('Escolha a razão da PA: '))
decTermo = priTermo + (11 - 1) * razao # an = a1 + (n-1) x r
for pa in range(priTermo, decTermo, razao):
print(pa, end=' -> ')
print('END')
|
# define all the configurations here---
MAXLEN = 128
NUM_WORKERS = 4
TRAIN_BATCH_SIZE = 16
VALID_BATCH_SIZE = 16
EPOCHS = 10 |
class Solution:
def gcd(self, x: int, y: int) -> int:
while (y): x, y = y, x % y
return x
def isGoodArray(self, nums: List[int]) -> bool:
x = nums[0]
for y in nums: x = self.gcd(x, y)
return x == 1
|
# class Person:
# def __init__(self, fn, ln):
# self.fn = fn
# self.ln = ln
# def fullname(self):
# return self.fn + ' ' + self.ln
def constructor(self, fn, ln):
self.fn = fn
self.ln = ln
def fullname(self):
return self.fn + ' ' + self.ln
Person = type("Person", (object,), {
"__init__": constructor,
"fullname": fullname
})
p = Person('Bob', 'Smith')
print(p.fullname())
|
"""
Version module.
This module defines the package version for use in __init__.py and setup.py.
"""
__version__ = '0.2.1alpha'
|
allbases = {
'866_8_4_16' : ['0234','1234','0345','1345','0246','1246','0456','1456','0237','1237','0357','1357','0267','1267','0567','1567'] ,
'867_8_4_12' : ['0234','1234','0345','1345','0246','1246','0456','1456','2347','3457','2467','4567'] ,
'868_8_4_9' : ['0234','1234','0345','1345','2346','3456','0347','1347','3467'] ,
'869_8_4_8' : ['0234','1234','0345','1345','2346','3456','2347','3457'] ,
'870_8_4_5' : ['0234','1234','2345','2346','2347'] ,
'871_8_4_8' : ['0234','1234','0345','1345','0246','1246','0456','1456'] ,
'872_8_4_6' : ['0234','1234','0345','1345','2346','3456'] ,
'873_8_4_4' : ['0234','1234','2345','2346'] ,
'874_8_4_4' : ['0234','1234','0345','1345'] ,
'875_8_4_3' : ['0234','1234','2345'] ,
'876_8_4_2' : ['0234','1234'] ,
'878_8_4_20' : ['0234','1234','0345','1345','0246','1246','0456','1456','0237','1237','0347','1347','0357','1357','0267','1267','0467','1467','0567','1567'] ,
'879_8_4_16' : ['0234','1234','0345','1345','0246','1246','0456','1456','0247','1247','2347','0457','1457','3457','2467','4567'] ,
'880_8_4_18' : ['0234','1234','0345','1345','2346','3456','0237','1237','0247','1247','0357','1357','0457','1457','2367','2467','3567','4567'] ,
'881_8_4_15' : ['0234','1234','0345','1345','2346','3456','0247','1247','0347','1347','0457','1457','2467','3467','4567'] ,
'882_8_4_14' : ['0234','1234','0345','1345','2346','3456','0247','1247','2347','0457','1457','3457','2467','4567'] ,
'883_8_4_11' : ['0234','1234','0345','1345','2346','3456','0347','1347','2347','3457','3467'] ,
'884_8_4_12' : ['0234','1234','0345','1345','0346','1346','2346','3456','0347','1347','2347','3457'] ,
'885_8_4_12' : ['0234','1234','0245','1245','0345','1345','2346','2456','3456','2347','2457','3457'] ,
'886_8_4_9' : ['0234','1234','2345','2346','0347','1347','2347','3457','3467'] ,
'887_8_4_12' : ['0234','1234','0345','1345','0236','1236','0246','1246','0356','1356','0456','1456'] ,
'888_8_4_10' : ['0234','1234','0345','1345','0246','1246','2346','0456','1456','3456'] ,
'889_8_4_8' : ['0234','1234','0345','1345','0346','1346','2346','3456'] ,
'890_8_4_9' : ['0234','1234','0245','1245','0345','1345','2346','2456','3456'] ,
'891_8_4_7' : ['0234','1234','2345','0346','1346','2346','3456'] ,
'892_8_4_6' : ['0234','1234','0245','1245','0345','1345'] ,
'893_8_4_5' : ['0234','1234','0235','1235','2345'] ,
'894_8_4_3' : ['0123','0134','1234'] ,
'895_8_4_24' : ['0234','1234','0345','1345','0246','1246','0456','1456','0237','1237','0247','1247','2347','0357','1357','0457','1457','3457','0267','1267','2467','0567','1567','4567'] ,
'896_8_4_20' : ['0234','1234','0345','1345','0246','1246','0456','1456','0247','1247','0347','1347','2347','0457','1457','3457','0467','1467','2467','4567'] ,
'897_8_4_21' : ['0234','1234','0345','1345','2346','3456','0237','1237','0247','1247','0347','1347','0357','1357','0457','1457','2367','2467','3467','3567','4567'] ,
'898_8_4_20' : ['0234','1234','0345','1345','2346','3456','0237','1237','0247','1247','2347','0357','1357','0457','1457','3457','2367','2467','3567','4567'] ,
'899_8_4_17' : ['0234','1234','0345','1345','2346','3456','0247','1247','0347','1347','2347','0457','1457','3457','2467','3467','4567'] ,
'900_8_4_16' : ['0234','1234','2345','0236','1236','0246','1246','0346','1346','2356','2456','3456','2347','2367','2467','3467'] ,
'901_8_4_13' : ['0234','1234','2345','2346','0247','1247','0347','1347','2347','2457','3457','2467','3467'] ,
'902_8_4_14' : ['0234','1234','0345','1345','0236','1236','0246','1246','2346','0356','1356','0456','1456','3456'] ,
'903_8_4_12' : ['0234','1234','0345','1345','0236','1236','0346','1346','2346','0356','1356','3456'] ,
'904_8_4_12' : ['0234','1234','2345','0236','1236','0246','1246','0346','1346','2356','2456','3456'] ,
'905_8_4_10' : ['0234','1234','2345','0246','1246','0346','1346','2346','2456','3456'] ,
'906_8_4_8' : ['0234','1234','0235','1235','0245','1245','0345','1345'] ,
'907_8_4_7' : ['0234','1234','0245','1245','0345','1345','2345'] ,
'908_8_4_4' : ['0123','0124','0234','1234'] ,
'909_8_4_28' : ['0234','1234','0345','1345','0246','1246','0456','1456','0237','1237','0247','1247','0347','1347','2347','0357','1357','0457','1457','3457','0267','1267','0467','1467','2467','0567','1567','4567'] ,
'910_8_4_23' : ['0234','1234','0345','1345','2346','3456','0237','1237','0247','1247','0347','1347','2347','0357','1357','0457','1457','3457','2367','2467','3467','3567','4567'] ,
'911_8_4_17' : ['0234','1234','2345','2346','0237','1237','0247','1247','0347','1347','2347','2357','2457','3457','2367','2467','3467'] ,
'912_8_4_16' : ['0234','1234','0345','1345','0236','1236','0246','1246','0346','1346','2346','0356','1356','0456','1456','3456'] ,
'913_8_4_13' : ['0234','1234','2345','0236','1236','0246','1246','0346','1346','2346','2356','2456','3456'] ,
'914_8_4_9' : ['0234','1234','0235','1235','0245','1245','0345','1345','2345'] ,
'915_8_4_5' : ['0123','0124','0134','0234','1234'] ,
'916_8_4_24' : ['0234','1234','0345','1345','0236','1236','0246','1246','0356','1356','0456','1456','0237','1237','0247','1247','0357','1357','0457','1457','0267','1267','0567','1567'] ,
'917_8_4_18' : ['0234','1234','0345','1345','0246','1246','2346','0456','1456','3456','0247','1247','2347','0457','1457','3457','2467','4567'] ,
'918_8_4_13' : ['0234','1234','0345','1345','0346','1346','2346','3456','0347','1347','2347','3457','3467'] ,
'919_8_4_18' : ['0234','1234','0245','1245','0345','1345','2346','2456','3456','0247','1247','0347','1347','0457','1457','2467','3467','4567'] ,
'920_8_4_12' : ['0234','1234','2345','0346','1346','2346','3456','0347','1347','2347','3457','3467'] ,
'921_8_4_12' : ['0234','1234','0245','1245','0345','1345','0246','1246','0346','1346','0456','1456'] ,
'922_8_4_9' : ['0234','1234','0235','1235','2345','0236','1236','2346','2356'] ,
'923_8_4_6' : ['0123','0134','1234','0135','1235','1345'] ,
'924_8_4_24' : ['0234','1234','0345','1345','0236','1236','0246','1246','0356','1356','0456','1456','0347','1347','2347','3457','0367','1367','2367','0467','1467','2467','3567','4567'] ,
'925_8_4_25' : ['0234','1234','0345','1345','0246','1246','2346','0456','1456','3456','0237','1237','0347','1347','0357','1357','0267','1267','2367','0467','1467','3467','0567','1567','3567'] ,
'926_8_4_21' : ['0234','1234','0245','1245','0345','1345','2346','2456','3456','0237','1237','2347','0257','1257','0357','1357','2457','3457','2367','2567','3567'] ,
'927_8_4_15' : ['0234','1234','0245','1245','0345','1345','0236','1236','2346','0256','1256','0356','1356','2456','3456'] ,
'928_8_4_9' : ['0123','0134','1234','0125','0235','0145','1245','0345','2345'] ,
'929_8_4_26' : ['0234','1234','0345','1345','0236','1236','0246','1246','0356','1356','0456','1456','0247','1247','2347','0457','1457','3457','0267','1267','2367','2467','0567','1567','3567','4567'] ,
'930_8_4_24' : ['0234','1234','0345','1345','0246','1246','2346','0456','1456','3456','0237','1237','2347','0357','1357','3457','0267','1267','2367','2467','0567','1567','3567','4567'] ,
'931_8_4_21' : ['0234','1234','0345','1345','0246','1246','2346','0456','1456','3456','0247','1247','0347','1347','0457','1457','0467','1467','2467','3467','4567'] ,
'932_8_4_19' : ['0234','1234','0345','1345','0246','1246','2346','0456','1456','3456','0347','1347','2347','3457','0467','1467','2467','3467','4567'] ,
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'1790_8_4_66' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','2367','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1791_8_4_66' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','1467','2467','3467','0567','1567','3567','4567'] ,
'1792_8_4_64' : ['0123','0124','0234','1234','0125','0235','1235','0245','1245','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1793_8_4_67' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1794_8_4_67' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1795_8_4_67' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1796_8_4_67' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1797_8_4_67' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1798_8_4_67' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1799_8_4_67' : ['0123','0124','0234','1234','0125','0135','0235','0145','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1800_8_4_65' : ['0123','0124','0234','1234','0125','0235','1235','0245','1245','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1801_8_4_68' : ['0123','0124','0234','1234','0125','0135','0235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1802_8_4_68' : ['0123','0124','0234','1234','0125','0135','0235','1235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1803_8_4_68' : ['0123','0124','0234','1234','0125','0135','0235','1235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','3567','4567'] ,
'1804_8_4_69' : ['0123','0124','0234','1234','0125','0135','0235','1235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
'1805_8_4_70' : ['0123','0124','0134','0234','1234','0125','0135','0235','1235','0145','0245','1245','0345','1345','2345','0126','0136','0236','1236','0146','0246','1246','0346','1346','2346','0156','0256','1256','0356','1356','2356','0456','1456','2456','3456','0127','0137','0237','1237','0147','0247','1247','0347','1347','2347','0157','0257','1257','0357','1357','2357','0457','1457','2457','3457','0167','0267','1267','0367','1367','2367','0467','1467','2467','3467','0567','1567','2567','3567','4567'] ,
}
|
# max_contiguous_sum([-2, -3, 4, -1, -2, 1, 5, -3]) -> 7
def max_contiguous_sum(numbers: list) -> int:
highest = numbers[0]
local_highest = highest
for index, x in enumerate(numbers[1:]):
local_highest += x
if x > local_highest:
local_highest = x
if local_highest > highest:
highest = local_highest
return highest
def max_contiguous_sub_array(numbers: list) -> list:
i, f = 0, 1
highest = numbers[0]
local_highest = highest
for index, x in enumerate(numbers[1:]):
index += 1
local_highest += x
if x > local_highest:
local_highest = x
i = index
if local_highest > highest:
highest = local_highest
f = index + 1
return numbers[i:f]
|
CANONICAL_FORMS = {
"no_relation": ["NR"],
"org:founded_by": ["{obj}, founder of {subj}.",
"{obj}, who established {subj}.",
"{subj}, founded by {obj}.",
"{obj} was the founder of {subj}.",
"{subj} founder {obj}."],
"per:employee_of": ["{subj} is an employee of {obj}.",
"{subj}, member of {obj}.",
"{subj} is a member of {obj}.",
"{subj} joined {obj}.",
"{subj}, spokeman of {obj}."],
"org:alternate_names": ["{subj} known as {obj}.",
"{subj}, formally known as {obj}.",
"{subj}, then called {obj}.",
"Called {subj} or {obj}."],
"per:cities_of_residence": ["{subj} lived in {obj}.",
"{subj} moved to {obj}.",
"{subj}'s home in {obj}.",
"{subj} grew up in {obj}.",
"{subj} who lived in {obj}."],
"per:children": ["{subj}'s child is {obj}.",
"{subj}'s daughter is {obj}.",
"{subj} has given birth to a son, {obj}."],
"per:title": ["{subj} is a {obj}."],
"per:siblings": ["{subj}'s sibling is {obj}.",
"{subj}'s sister, {obj}.",
"{obj}, {subj}'s brother."],
"per:religion": ["{subj}, a {obj}.",
"{subj}, a {obj} minister.",
"{subj} minister {obj}."],
"per:age": ["{subj} is {obj} years old.",
"{subj} dies at age {obj}.",
"{subj}, aged {obj}.",
"{subj} reached the age of {obj}."],
"org:website": ["Find {subj} online in {obj}."],
"per:stateorprovinces_of_residence": ["{subj} lived in {obj}.",
"{subj} moved to {obj}.",
"{subj}'s home in {obj}.",
"{subj} grew up in {obj}.",
"{subj} who lived in {obj}."],
"org:member_of": ["{subj} is part of {obj}.",
"{subj} has join the {obj}.",
"{subj} is a member of {obj}.",
"{obj} is composed of {subj}."],
"org:top_members/employees": ["{obj} is the head of {subj}.",
"{subj} CEO {obj}.",
"{obj}, the CEO of {subj}.",
"{obj}, {subj}'s president.",
"{obj}, president of {subj}.",
"{obj} heads {subj}."],
"per:countries_of_residence": ["{subj} lived in {obj}.",
"{subj} moved to {obj}.",
"{subj}'s home in {obj}.",
"{subj} grew up in {obj}.",
"{subj} who lived in {obj}."],
"org:city_of_headquarters": ["{subj}, based in {obj}.",
"{subj} is headquartered in {obj}.",
"{subj}, an organization based in {obj}.",
"{subj}, which is based in {obj}."],
"org:members": ["{obj} is part of {subj}.",
"{obj} has join the {subj}.",
"{obj} is a member of {subj}.",
"{subj} is composed of {obj}."],
"org:country_of_headquarters": ["{subj}, based in {obj}.",
"{subj}, based in Dublin, {obj}.",
"{subj} is headquartered in {obj}.",
"{subj}, an organization based in {obj}.",
"{subj}, which is based in {obj}."],
"per:spouse": ["{subj} is married to {obj}.",
"{subj} married {obj}.",
"{subj}'s wife {obj}.",
"{subj} and her husband {obj}."],
"org:stateorprovince_of_headquarters": ["{subj}, based in {obj}.",
"{subj}, based in Seattle, {obj}.",
"{subj} is headquartered in {obj}.",
"{subj}, an organization based in {obj}.",
"{subj}, which is based in {obj}."],
"org:number_of_employees/members": ["{subj} employes {obj} workers.",
"{subj} is an organization with {obj} employees.",
"{subj} has {obj} employees."],
"org:parents": ["{subj}, a unit of {obj}.",
"{subj} at {obj}.",
"{subj} is a division of {obj}.",
"{subj} was sold to {obj}."],
"org:subsidiaries": ["{obj}, a unit of {subj}.",
"{obj} at {subj}.",
"{obj} is a division of {subj}.",
"{obj} was sold to {subj}."],
"per:origin": ["{subj} is a {obj} native.",
"{obj} {subj}.",
"{subj} is a {obj}."],
"org:political/religious_affiliation": ["{obj} group {subj}."],
"per:other_family": ["{subj} and {obj} are family members.",
"{subj}'s uncle {obj}.",
"{subj}'s aunt {obj}.",
"{subj}'s grandmother {obj}.",
"{subj}'s grandfather {obj}.",
"{subj}'s niece {obj}."],
"per:stateorprovince_of_birth": ["{subj} was born in {obj}.",
"{subj} was born on January 1st in {obj}.",
"{subj} was born in London, {obj}."],
"org:dissolved": ["{subj} was dissolved in {obj}.",
"{subj} announced bankrupcy in {obj}."],
"per:date_of_death": ["{subj} died in {obj}.",
"{subj} died at his home in {obj}."],
"org:shareholders": ["{obj} acquired some of {subj}.",
"{obj} invested in {subj}.",
"{subj}'s shareholder {obj}."],
"per:alternate_names": ["{subj}, who was known as {obj}.",
"{subj}, whose real name is {obj}.",
"{subj}, then known as {obj}."],
"per:parents": ["{obj} is {subj}'s parent.",
"{subj}'s father, {obj}.",
"{obj}, {subj}'s father.",
"{obj}, mother of {subj}."],
"per:schools_attended": ["{subj} graduated from {obj}.",
"{subj} received a degree from {obj}.",
"{subj} attended {obj}."],
"per:cause_of_death": ["{subj} died of {obj}.",
"{subj} died from {obj}."],
"per:city_of_death": ["{subj} died in {obj}.",
"{subj} died at his home in {obj}.",
"{subj} died at Sunday in {obj}."],
"per:stateorprovince_of_death": ["{subj} died in {obj}.",
"{subj} died at his home in {obj}.",
"{subj} died in London, {obj}.",
"{subj} died at Sunday in {obj}."],
"org:founded": ["{subj} was established in {obj}.",
"Founded {subj} in {obj}.",
"{subj}, established in {obj}.",
"The founder founded {subj} in {obj}."],
"per:country_of_birth": ["{subj} was born in {obj}.",
"{subj} was born on January 1st in {obj}.",
"{subj} was born in Berlin, {obj}."],
"per:date_of_birth": ["{subj} was born in {obj}.",
"{subj} was born on {obj}."],
"per:city_of_birth": ["{subj} was born in {obj}.",
"{subj} was born on January 1st in {obj}."],
"per:charges": ["{subj} was convicted of {obj}.",
"{subj} face {obj} among other charges."],
"per:country_of_death": ["{subj} died in {obj}.",
"{subj} died at his home in {obj}.",
"{subj} died in London, {obj}.",
"{subj} died at Sunday in {obj}."]
}
|
n = int(input())
if n%5 == 0:
print(int(n/5))
else:
print(int(n/5)+1) |
""""""
"""5. Busque e imprima el pais de Venezuela y su capital"""
archivo = open("paises.txt", "r")
lista = []
for i in archivo:
lista.append(i)
pc = " ".join(lista)
if(pc == "Venezuela: Caracas\n"):
break
lista = []
print(pc)
archivo.close() |
class Solution(object):
def intersection(self, nums1, nums2):
"""
:type nums1: List[int]
:type nums2: List[int]
:rtype: List[int]
"""
s = set(nums1)
ans = set()
for num in nums2:
if num in s:
ans.add(num)
return list(ans) |
# pytest --reruns n n是重新测试的次数
def test_1():
print('test 1')
assert False, '故意失败'
|
""" Package specific exceptions. """
class Ai1wmError(Exception):
""" Exceptions raised from this package. """
pass
|
"""
Defines the possible rewards for rollout.
Can be augmented for more complex policies using simialr scheme as Rollout or UCT policies.
Is defined through CLI in the Tree script.
"""
class RolloutRewards(object):
"""
Defines penalty and rewards for the rollout if it's in the chasis.
"""
def __init__(self, penalty, full_state_reward):
self.penalty = penalty
self.full_state_reward = full_state_reward
def __repr__(self):
"""Reward representation is its values"""
return("Penalty is {} and full state reward is {}".format(self.penalty, self.full_state_reward))
Basic_Rollout_Reward = RolloutRewards(penalty = -1, full_state_reward = 2)
|
alph = 'abcdefghijklmnopqrstuvwxyz'[::-1]
def getWinner(s1, s2):
if ("no" in s1 or "no" in s2):
return 0
if (not s1.isalpha() or not s2.isalpha()):
return 0
for c in alph:
c1 = s1.count(c)
c2 = s2.count(c)
if (c1 > c2):
return 1
elif (c2 > c1):
return 2
return 0
firstWordCount = 0
firstWord68th = ""
with open("D:\\Work\\Repositories\\programmingContest\\programmingContest2Input1.txt") as file:
for line in file:
words = line.split()
winner = getWinner(words[0], words[1])
if (winner == 1):
firstWordCount = firstWordCount + 1
if (firstWordCount == 68):
firstWord68th = words[0]
print(firstWord68th)
print(firstWordCount) |
# Let's clean the paragraph up a bit. We don't want to
# consider "It" and "it" two different words, so let's make
# everything lowercase
myParagraph = "In the year 1878 I took my degree of Doctor of Medicine of the University of London, and proceeded to Netley to go through the course prescribed for surgeons in the army. Having completed my studies there, I was duly attached to the Fifth Northumberland Fusiliers as Assistant Surgeon. The regiment was stationed in India at the time, and before I could join it, the second Afghan war had broken out. On landing at Bombay, I learned that my corps had advanced through the passes, and was already deep in the enemy’s country. I followed, however, with many other officers who were in the same situation as myself, and succeeded in reaching Candahar in safety, where I found my regiment, and at once entered upon my new duties."
myParagraph = myParagraph.lower()
# Let's also delete the punctuation, so "London." and "London"
# aren't two different words. (there are better ways to do
# this that we will see later)
myParagraph = myParagraph.replace(",", "")
myParagraph = myParagraph.replace(".", "")
# Otherwise, the code is the same:
words = myParagraph.split(" ")
uniqueWords = set(words)
mostCommonWord = []
mCWFreq = 0
for word in uniqueWords:
if word != " ":
freq = words.count(word)
if freq > mCWFreq:
mCWFreq = freq
mostCommonWord = [word]
elif freq == mCWFreq and word not in mostCommonWord:
mostCommonWord.append(word)
# Print the final results
print(f"The most common word(s) is/are {mostCommonWord}, which occur(s) {mCWFreq} time(s)!") |
class ChartTypes:
METER_TIME = 0
METER_TIME_DAY_AGG = 1
METER_INSTALLATION = 2
class UploadFileTypes:
BUILDING_DATA = 0
HALF_HOURLY_DATA = 1
METER_DATA = 2
|
list1 = [12,-7,5,64,-14]
for num1 in list1 :
if num1 >= 0:
print(num1, end = " ")
list2 = [12,14,-95,3]
for num2 in list2 :
if num2 >= 0:
print(num2, end = " ")
|
directions = [
(1, 0), # east
(0, 1), # south
(-1, 0), # west
(0, -1) # north
]
def rotate(x, y, code, value):
rotations = value // 90
if code == 'R':
for i in range(rotations):
x, y = -y, x
elif code == 'L':
for i in range(rotations):
x, y = y, -x
return x, y
with open('day12.txt') as f:
instr = [line.strip() for line in f]
def move():
px, py = 0, 0 # position
dx, dy = 1, 0 # direction
for inst in instr:
code = inst[0]
value = int(inst[1:])
if code == 'N':
py -= value
elif code == 'S':
py += value
elif code == 'E':
px += value
elif code == 'W':
px -= value
elif code == 'F':
px += dx * value
py += dy * value
elif code == 'L' or code == 'R':
dx, dy = rotate(dx, dy, code, value)
else:
raise Exception(f'unexpected code: {code}')
return px, py
px, py = move()
print(abs(px) + abs(py))
def wmove():
px, py = 0, 0
wx, wy = 10, -1
for inst in instr:
code = inst[0]
value = int(inst[1:])
if code == 'N':
wy -= value
elif code == 'S':
wy += value
elif code == 'E':
wx += value
elif code == 'W':
wx -= value
elif code == 'F':
px += wx * value
py += wy * value
elif code == 'L' or code == 'R':
wx, wy = rotate(wx, wy, code, value)
else:
raise Exception(f'unexpected code: {code}')
return px, py
px, py = wmove()
print(abs(px) + abs(py))
|
#!/usr/bin/env python
# encoding: utf-8
"""
minimal_window_string.py
Created by Shengwei on 2014-07-06.
"""
# https://oj.leetcode.com/problems/minimum-window-substring/
# tags: hard, string, hashtable, minimal, edge cases, clarification (dups)
"""
Given a string S and a string T, find the minimum window in S which will contain all the characters in T in complexity O(n).
For example,
S = "ADOBECODEBANC"
T = "ABC"
Minimum window is "BANC".
Note:
If there is no such window in S that covers all characters in T, return the emtpy string "".
If there are multiple such windows, you are guaranteed that there will always be only one unique minimum window in S.
"""
"""
Notes for 3 bugs while implementing:
1. should move left pointer when substring is set other than left > 0;
alternatively, set left to -1 in the beginning and later check if it's > -1
2. should check counter == char_count only when counter just changed
3. should decrease counter only when lookup_dict entry is -1, which means
it just dissatisfies the minimum requirements
The last two are mainly due to the change of concept -- there can be dups in T.
"""
# TODO:
# 1. refactor it using a queue
# 2. do not need to store both index and the char
class Solution:
# @return a string
def minWindow(self, S, T):
"""Think about a windown sliding through S."""
window, counter, char_count = [], 0, len(set(T))
left = right = 0
min_substring = ''
# initialize lookup dictionary, with negative count of
# each char in T; they are expected to be supplimented
# by sliding the window on S
lookup_dict = collections.defaultdict(int)
for char in T:
lookup_dict[char] -= 1
while right < len(S):
if window and left > window[0][1]:
# drop off the left most one from the window;
# the count of such item in the window decreases
to_be_removed = window.pop(0)[0]
lookup_dict[to_be_removed] -= 1
# IMPORTANT! should check if it's -1 other than < 0
if lookup_dict[to_be_removed] == -1:
# no such char is in the window now, decrease count
counter -= 1
if S[right] in lookup_dict:
# include S[right] in the window
window.append((S[right], right))
lookup_dict[S[right]] += 1
if lookup_dict[S[right]] == 0:
# requirement for S[right] has been just satisfied;
# if there were more than enough S[right], no change
counter += 1
# only check this when counter increases
if counter == char_count:
# all requirements for T have been satisfied;
# shrink the window for mimimum substring
while lookup_dict[window[0][0]] > 0:
# the left most item in the window is
# superfluous, drop it
lookup_dict[window.pop(0)[0]] -= 1
# shrink the window to the tighter boundary
left = window[0][1]
# update minimum substring; after all chars in T have
# been in the window, the window only shrinks or
# at least has no change, so do not need comparison
min_substring = S[left:right+1]
# slide the window to the right
right += 1
# move the left of the window after we've found a substring
if min_substring:
left += 1
return min_substring
|
# Twitter Credentials
# Later used in utils.py
consumer_key = 'consumer key'
consumer_secret = 'consumer_secret'
access_token = 'access_token'
access_token_secret = 'access_token_secret'
|
cores = {'limpa': '\033[m',
'vermelho': '\033[0;31m',
'verde': '\033[0;32m',
'amarelo': '\033[0;33m',
'azul': '\033[0;34m',
'anil': '\033[0;35m',
'ciano': '\033[0;36m'}
alg = (input('{}Digite algo na tela: '.format(cores['azul'])))
print('Foi digitado "{}"::'.format(alg))
print('')
print(type(alg))
print('{}É alfabetico: {}'.format(cores['vermelho'], cores['limpa']))
print(alg.isalpha())
print('{}É numerico:{}'.format(cores['anil'], cores['limpa']))
print(alg.isnumeric())
print('{}É alfanumerico:{}'.format(cores['verde'], cores['limpa']))
print(alg.isalnum())
print('{}É escrito em maiusculas:{}'.format(cores['amarelo'], cores['limpa']))
print(alg.isupper())
print('{}É escrito em minusculas:{}'.format(cores['ciano'], cores['limpa']))
print(alg.islower()) |
def truncate(a, b):
n = min(len(a), len(b))
return a[:n], b[:n]
def truncate3(a, b, c):
n = min(len(a), len(b), len(c))
return a[:n], b[:n], c[:n]
def xor(x, y):
# assert len(x) == len(y)
a = int.from_bytes(x, "big")
b = int.from_bytes(y, "big")
return (a ^ b).to_bytes(len(x), "big")
# Expects a textfile containing
# ciphertexts separated by new lines
# Returns a tuple
# - a list of strings (each cipher)
# - a string (the first cipher)
def parse_text(filepath):
texts = []
with open(filepath) as f:
for line in f:
s = line.strip(' \t\n\r')
if s != '': texts.append(s)
return texts
# Expects a list of strings representing
# byte in hex representation
# Returns the corresponding list the actual bytes
# represented by each string
def byteslist_fromhex(hexlist):
byteslist = []
for h in hexlist:
byteslist.append(bytes.fromhex(h))
return byteslist
|
X1_COORDINATE_IMAGE_CROPPED = 2000
X2_COORDINATE_IMAGE_CROPPED = 3000
Y1_COORDINATE_IMAGE_CROPPED = 0
Y2_COORDINATE_IMAGE_CROPPED = 3880
HSV_MIN = (100,80,150) #min for red - normal - generelalized
HSV_MAX = (150,255,255) #max for red - normal - generelalized
HSV_INVERTED_MIN = (50,230,240) #min for green - inverted
HSV_INVERTED_MAX = (70,250,255) #max for green - inverted
MIN_DIST_BETWEEN_LASERS = 40
MAX_DIST_BETWEEN_LASERS = 200
ESTIMATED_LASER_AREA = 5000 |
ivan = {'пушене', 'пиене', 'тия три неща', 'коли', 'facebook', 'игри', 'разходки по плажа', 'скандинавска поезия'}
maria = {'пиене', 'мода', 'facebook', 'игри', 'лов със соколи', 'шопинг', 'кино'}
#print(set(ivan) & set(maria))
print(ivan & maria) |
# -*- coding: utf-8 -*-
# @Project : curve_fit
# @Time : 2019-05-27 14:28
# @Author : Samuel Chan
# @Email : samuelchan1205@gmail.com
# @File : __init__.py
name = "curve_fit"
|
"""Classes for containing morphological objects."""
class Affix:
"""A class representing a single affix."""
def __init__(self, string_in, tag):
self.s = string_in
self.tag = tag
def __hash__(self):
return hash((self.s, self.tag))
def __eq__(self, other):
return (self.s, self.tag) == (other.s, other.tag)
def __str__(self):
return self.s
def to_tag(self):
return self.tag
class ParseList:
"""A class representing a single set of possible affix combinations."""
def __init__(self):
self.affixes = []
def __hash__(self):
return hash(self.affixes)
def __eq__(self, other):
return self.affixes == other.affixes
def __str__(self):
tags = map(lambda x: x.to_tag(), self.affixes)
return ' - '.join(tags)
def append(self, a):
"""No validation is done at this step, do it before"""
self.affixes.append(a) |
__author__ = 'srio'
NAME = "XOPPY: Tools"
ID = "orangecontrib.xoppy.widgets.tools"
DESCRIPTION = """Widgets for x-ray oriented programs under python (xoppy)"""
LONG_DESRIPTION = """
Miscellanea Tools
"""
ICON = "icons/xoppy_2.png"
BACKGROUND = "#FFD39F"
PRIORITY = 2003
|
#問題の指定だとC or C++だけど，ここはPythonで
def reverse(str):
list_str = list(str)
j = -1
for i in range(len(list_str) // 2):
list_str[i], list_str[j] = list_str[j], list_str[i]
j -= 1
print(list_str)
reverse("abxcd")
reverse("mahiru")
reverse("abcd") |
def SimIRStmt_WrTmp(engine, state, stmt):
# get data and track data reads
with state.history.subscribe_actions() as data_deps:
data = engine.handle_expression(state, stmt.data)
state.scratch.store_tmp(stmt.tmp, data, deps=data_deps)
#actual_size = len(data)
#expected_size = stmt.data.result_size(state.scratch.tyenv)
#if actual_size != expected_size:
# raise SimStatementError("WrTmp expected length %d but got %d" % (actual_size, expected_size))
|
__author__ = "M. Jastad"
__copyright__ = "Copyright 2017, CSRA Hackathon"
__credits__ = ["M.Jastad", "M.Lavi"]
__license__ = "N/A"
__version__ = "1.0.1"
__maintainer__ = "M. Jastad"
__email__ = "michael.jastad@nutanix.com"
__status__ = "Reference"
class User:
def __init__(self, uname, pwd):
self.uname = uname
self.passwd = pwd
@property
def name(self):
return self.uname
@property
def password(self):
return self.passwd
|
class Solution:
def fizzBuzz(self, n):
list = []
for i in range(1,n+1):
buff_string = ""
if i % 3 == 0:
buff_string += "Fizz"
if i % 5 == 0:
buff_string += "Buzz"
if buff_string == '':
buff_string = str(i)
list.append(buff_string)
return list |
##############################################################################
# Copyright (c) 2020 China Mobile Co.,Ltd and others.
#
# All rights reserved. This program and the accompanying materials
# are made available under the terms of the Apache License, Version 2.0
# which accompanies this distribution, and is available at
# http://www.apache.org/licenses/LICENSE-2.0
##############################################################################
"""
ERROR CODE instruction
"""
ERROR_CODE = {
# E100XXX: Connection
"E100001": "E100001:fail to get response from the url",
"E100002": "E100002:unexpected request url",
"E100003": "E100003:failed to setup connection",
# E200XXX: options - tools arguments.
"E200001": "E200001:unsupported input file_mode, \
should be one of [yaml,excel]",
# E300XXX: resource issue - depended resource is not existing...
"E300001": "E300001:invalid token",
"E300002": "E300002:fail to get dependency parent id, Action: check if the \
resource support by server",
"E300003": "E300003:fail to get expected id list for component_id, \
Action: check if the resource support by server",
# E400XXX: configuration error
"E400001": "E400001:fail to find configure file",
"E400002": "E400002:parse config.yaml exception",
"E400003": "E400003: key_list is null for key_flags",
"E400004": "E400004: unexpected response body type",
"E400005": "E400005: customized expected value format error, \
Action:check input expected value type with actual returned value type",
"E400006": "E400006: unexpected expected value type, \
expected[str,list,dict]",
"E400007": "E400007: unexpected expected value type while comparing",
# E500XXX: application - find no value from cache
"E500001": "E500001: fail find key from actual value, \
Action: check if the attribute support by server",
# E600XXX: restful interface
"E600001": "E600001: unsupported redfish api?",
}
WARN_CODE = {
"W100001": "W100001: fail to the response from a request",
"W100002": "W100002: unexpected type of return_value type",
"W100003": "W100003: NoneType value",
}
|
'''
Now You Code 4: Find a character in text
Description
Write a program to input a character, and then some text. It should then output
the number of times the character was found in the text.
Requirements:
#1 Write a function char_in_text which returns an int value as to
the count of that character in the text
Function: char_in_text
Arguments: char, text
Returns: count of char in text
#2 You're going to need a deterministic loop to iterate over each character in
the text.
Example Run #1:
Enter Character: e
Enter Text: Mike Fudge
The character 'e' appears 2 times in the text.
Example Run #2:
Enter Character: x
Enter Text: oakland
The character 'x' appears 0 times in the text.
Start out your program by writing your TODO list of steps
you'll need to solve the problem!
'''
# TODO: Write Todo list then beneath write your code
# Write code here
|
class Database:
mysql = {
"host": "localhost",
"user": "root",
"pass": "pass",
"port": 3306,
"name": "db"
} |
friends = ['ali', 'ahmad', 'jali']
for friend in friends:
print('Selamat',friend)
print('selesai')
|
"""
Flags specified here must not impact ABI. Code compiled with and without these
opts will be linked together, and in some cases headers compiled with and
without these options will be part of the same program.
We use the same flags as absl.
"""
load(
"@com_google_absl//absl:copts/GENERATED_copts.bzl",
"ABSL_GCC_FLAGS",
"ABSL_GCC_TEST_FLAGS",
"ABSL_LLVM_FLAGS",
"ABSL_LLVM_TEST_FLAGS",
"ABSL_MSVC_FLAGS",
"ABSL_MSVC_TEST_FLAGS",
)
WERROR = ["-Werror=return-type", "-Werror=switch", "-Werror=sign-compare", "-Werror=type-limits", "-Werror=old-style-cast", "-Werror=unused-parameter"]
DEFAULT_COPTS = select({
"//:windows": ABSL_MSVC_FLAGS,
"//:llvm_compiler": ABSL_LLVM_FLAGS,
"//conditions:default": ABSL_GCC_FLAGS + WERROR,
})
TEST_COPTS = DEFAULT_COPTS + select({
"//:windows": ABSL_MSVC_TEST_FLAGS,
"//:llvm_compiler": ABSL_LLVM_TEST_FLAGS,
"//conditions:default": ABSL_GCC_TEST_FLAGS + WERROR,
})
|
"""Message type identifiers for Feature Discovery."""
PROTOCOL_URI = "did:sov:BzCbsNYhMrjHiqZDTUASHg;spec/discover-features/1.0"
DISCLOSE = f"{PROTOCOL_URI}/disclose"
QUERY = f"{PROTOCOL_URI}/query"
PROTOCOL_PACKAGE = "aries_cloudagent.protocols.discovery"
MESSAGE_TYPES = {
DISCLOSE: f"{PROTOCOL_PACKAGE}.messages.disclose.Disclose",
QUERY: f"{PROTOCOL_PACKAGE}.messages.query.Query",
}
|
# Задача 4. Вариант 22.
# Напишите программу, которая выводит имя, под которым скрывается Самюэл Ленгхорн Клеменс. Дополнительно необходимо вывести область интересов указанной личности, место рождения, годы рождения и смерти (если человек умер), вычислить возраст на данный момент (или момент смерти). Для хранения всех необходимых данных требуется использовать переменные. После вывода информации программа должна дожидаться пока пользователь нажмет Enter для выхода.
# Nikishin P. S.
# 12.05.2016
name = "Самюэл Ленгхорн Клеменс"
mestoro = "Флорида, Миссури, США)"
dataro = int(1835)
datasm = int(1910)
years = int(datasm - dataro)
interesi = "Литература"
print(name+" более известен как писатель Марк Твен")
print("Место рождения: "+mestoro)
print("Год рождения: "+str(dataro))
print("Год смерти: "+str(datasm))
print("Возраст: "+str(years))
print("Область интересов: "+interesi)
input("\nДля выхода нажмите Enter")
|
global where
global who
global what
global cook
global food
global shumoku
where = ['日本','ブルンジ','アメリカ','ドイツ','地獄','アマゾン','砂漠','海','赤羽','ボウリング場','武道館','劇場','映画館','サバンナ',\
'競馬場','桜の木の下','五反田','インターネット','学校裏サイト','2ch','温泉地','風呂','タイ料理屋','ラーメン屋','寿司屋','美容院','病院',\
'カラオケ','自宅','海岸','断崖絶壁','ぐるナイ収録現場','結婚式会場','葬儀会場','火葬場','会社','東京証券取引所','ジム']
who = ['ヒンギス','ウルトラ','しめさば','nonko','おつマス','メッシ','ドログバ','ひろゆき','安倍晋三','安倍満蔵','上原亜衣','椎名へきる',\
'奈緒','獅子舞','悟空','カツドン','谷岡','ミタ','四角君','ナタリー・ポートマン','ブルンジ人','鬼','猫','食パンマン','踏み焼き',\
'梅林ボーイ','寿司職人','ホリエモン','仮面ライダー','江戸川コナン','東京都知事','プペル','100日後に死ぬワニ','証拠','五味','ナポレオン'\
'マリオ','ドラえもん','ベッカムえもん','北島康介','ガッキー','アイドル']
what = ['走った','笑った','泣いた','うんこした','ニッコニコした','木っ端微塵になった','干からびた','キレ散らかした','生ゴミを食べた',\
'謝罪した','ガラスを割った','ぎっくり腰になった','相撲した','スベった','穴を掘った','魔法を使った','毒を吐き出した','嘔吐した',\
'眠った','錯乱した','歌った','気持ちよくなった','泥酔した','異臭を発した','喧嘩した','絵を描いた','マウントを取った']
cook = ['焼く','茹でる','炒める','揚げる','煮る','和える','蒸す']
cook2 = ['かきまぜる','すり潰す','加熱する','どよめく','泡立てる','ぐちゃぐちゃに混ぜる']
food = ['うんこ','たくあん','マグロ','ションベン','たくあん','醤油','ラーメン','寿司','ステーキ','スイカ','カレー','マンゴー','はちみつ',\
'サンマ','ブロッコリー','チョコ','マシュマロ','玄米','味噌汁','大根','お酢','ニトログリセリン','鰹節','カツオドリ','ウミウシ','グミ','砂糖',\
'生ゴミ','パスタ','にんにく','アイス','ジビエ','チャーハン','餃子','ホヤ','イクラ','ウニ','キャビア','トリュフ','アボカド','フォアグラ'\
'ソース','ムッキムキの鯛','トマト','きゅうり','じゃがいも','レタス','タン塩','ピーマン','柿ピー','ブタメン','ラー油','ミネラルウォーター',\
'新聞紙','寒天ゼリー','鶴','イワナ','パッションフルーツ','パイナップル','岩塩','グラタン','台湾まぜそば','魚粉','コオロギ','カブトムシ']
shumoku = ['レスバトル','柔道','空手','剣道','フルマラソン','手コキ耐久','100メートル走','将棋','囲碁','大声対決','うんこ早漏らし',\
'エベレスト登山','フリースロー','MCバトル','ダンスバトル','早着替え','演技','飛び込み','ファッション対決','学力テスト','クイズ対決',\
'料理対決','スイカ早食い','FPS','スマブラ','カヌー','フィギュアスケート','スキージャンプ','カブトムシ捕獲対決']
|
#%%
"""
- Maximum Subarray
- https://leetcode.com/problems/maximum-subarray/
- Easy
Given an integer array nums, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum.
Example:
Input: [-2,1,-3,4,-1,2,1,-5,4],
Output: 6
Explanation: [4,-1,2,1] has the largest sum = 6.
Follow up:
If you have figured out the O(n) solution, try coding another solution using the divide and conquer approach, which is more subtle.
"""
#%%
# from i , calculate i to n
# O(n^2)
class S1:
def maxSubArray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
n = len(nums)
m = float('-inf')
for i in range(n):
s = 0
for j in range(i, n):
s += nums[j]
m = max(m, s)
return m
#%%
# DP
# ms(i) = max(ms[i]+a[i], a[i])
# at index i , the max range may be in either adding a[i] or start from a[i]
class S2:
def maxSubArray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
n = len(nums)
maxSum = [nums[0] for i in range(n)]
for i in range(1,n):
maxSum[i] = max(maxSum[i-1] + nums[i], nums[i])
return max(maxSum)
#%%
class S3:
def maxSubArray(self, nums):
n = len(nums)
maxSum, maxEnd = nums[0], nums[0]
for i in range(1, n):
maxEnd = max(nums[i], maxEnd + nums[i])
maxSum = max(maxEnd, maxSum)
return maxSum
#%%
# Divide and Conquer
# The max subarray sum has three options: left part, right part or across left and right part
# O(nlogn)
class S4:
def maxSubArray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
def find_max_crossing_subarray(nums, low, mid, high):
left_sum = float('-inf')
sum = 0
for i in range(mid, low-1, -1):
sum = sum + nums[i]
if sum > left_sum:
left_sum = sum
right_sum = float('-inf')
sum = 0
for j in range(mid+1, high+1):
sum = sum + nums[j]
if sum > right_sum:
right_sum = sum
return left_sum + right_sum
def find_max_subarray(nums, low, high):
if low == high:
return nums[low]
else:
mid = (low+high) // 2
left_sum = find_max_subarray(nums, low, mid)
right_sum = find_max_subarry(nums, mid+1, high)
cross_sum = find_max_crossing_subarray(nums, low, mid, high)
return max(left_sum, right_sum, cross_sum)
return find_max_subarray(nums, 0, len(nums)-1)
#%%
|
allSum = 10000
last = 10150
percentAllSum = 100
percentLast = ((last - allSum) / allSum) * percentAllSum
print (percentLast) |
class ReporteOptimizacion():
def __init__(self, regla, original, optimizado, fila, columna):
self.regla = regla
self.original = original
self.optimizado = optimizado
self.fila = fila
self.columna = columna
|
HAND_ID_LIMITS = (200000000000, 999999999999)
# Offsets for PokerStars 7 (Build: 46014)
OFFSETS = { 'client' : { 'num_tables' : 0x133CAB0 },
'table' : { 'base' : ((0x01344248, 0x20, 0x04, 0x00, 0xDF8),
(0x01344248, 0x14, 0x00, 0xDF8)),
'interval' : ((0x00, 0x00, 0x10, 0x00, 0x00),
(0x00, 0x00, 0x04, 0x00)),
'button_position' : 0x00,
'turn_counter' : 0x04,
'is_post_flop' : 0x08,
'pot' : 0x18,
'hand_id' : 0x40,
'num_cards' : 0x58,
'card_values' : 0x64,
'card_suits' : 0x68,
'self_position' : 0x10B0,
'time_remaining' : 0x11C4 },
'seat' : { 'base' : 0x0218,
'interval' : 0x0160,
'name' : 0x00,
'stack' : 0x58,
'bet' : 0x68,
'is_empty' : 0x80,
'is_in_play' : 0x88,
'does_exist' : 0x8C,
'card_values' : 0x9C,
'card_suits' : 0xA0 } }
|
while True:
print("========================================")
print("계산할 수식(+,-,*,/,%) <Ctrl + C로 중단>")
result = 0.0;
num1 = int(input("num1:"))
sel = input("연산자:")
num2 = int(input("num2:"))
if(sel == "+"):
result = (num1 + num2)
elif(sel == "-"):
result = (num1 - num2)
elif(sel == "*"):
result = (num1 * num2)
elif(sel == "/"):
result = (num1 / num2)
elif(sel == "%"):
result = (num1 % num2)
else:
print("Wrong input, please input again")
continue
print("결과: ", result) |
# AUTOGENERATED! DO NOT EDIT! File to edit: 00_core.ipynb (unless otherwise specified).
__all__ = ['learn']
# Cell
def learn(model, data):
'''
Model learns using the
''' |
mes = input("Enter message >>")
demes = []
dmes = []
lengh = input("Enter lengh >>")
letters = ['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z']
letters += letters
for i in range(0,int(lengh)):
for n in range(0,26):
if (mes[i] == letters[n]):
demes.append(letters[n+int(lengh)])
dmes.append(letters[n-int(lengh)])
print(str(demes))
print(dmes)
|
# _*_coding:utf-8_*_
class Solution:
def NumberOf1Between1AndN_Solution(self, n):
pass |
def merge(arr, left, mid, right):
n1 = mid - left + 1
n2 = right - mid
# Creating temporary arrays and copying the elements to it
L = [0] * n1
R = [0] * n2
for i in range(0, n1):
L[i] = arr[left + i]
for j in range(0, n2):
R[j] = arr[mid + 1 + j]
# Merging the temporary arrays
i = 0
j = 0
k = left
while i < n1 and j < n2:
if L[i] <= R[j]:
arr[k] = L[i]
i += 1
else:
arr[k] = R[j]
j += 1
k += 1
# Copying the remaining elements, if there are any left out
while i < n1:
arr[k] = L[i]
i += 1
k += 1
while j < n2:
arr[k] = R[j]
j += 1
k += 1
def merge_sort(arr, left, right):
if left < right:
mid = (left + (right - 1)) // 2
merge_sort(arr, left, mid)
merge_sort(arr, mid + 1, right)
merge(arr, left, mid, right)
array = list(map(int, input('Enter the array of integers to be sorted(separated by spaces):').split()))
n = len(array)
print("Given array is")
print(*array)
merge_sort(array, 0, n - 1)
print("Sorted array is")
print(*array)
|
# Exercício 60
# Faça um programa que leia um número qualquer e mostre o seu fatorial.
# Exemplo: 5! = 5 x 4 x 3 x 2 x 1 = 120
fatorial = 1
num = int(input("Digite um número: "))
contador = num
print(f"{num}! = ", end="")
while contador != 0:
print(f"{contador} x " if contador !=1 else f"{contador} = ", end = "")
fatorial = contador * fatorial
contador -= 1
print(f'{fatorial}')
|
# Small alphabet j using function
def for_j():
""" *'s printed in the Shape of small j """
for row in range(9):
for col in range(4):
if col == 2 and row not in (1,8) or col ==1 and row in (2,8) or col ==0 and row ==7:
print('*',end=' ')
else:
print(' ',end=' ')
print()
def while_j():
""" *'s printed in the Shape of Small j """
row =0
while row <9:
col =0
while col <4:
if col == 2 and row not in (1,8) or col ==1 and row in (2,8) or col ==0 and row ==7:
print('*',end=' ')
else:
print(' ',end=' ')
col+=1
print()
row +=1
|
dados = list()
pessoa = list()
# [PESSOA] [NOME/NOTAS] [NOTA1/NOTA2]
while True:
pessoa.append(str(input('Nome: ')))
notas = [int(input('Nota 1: ')),
int(input('Nota 2: '))]
pessoa.append(notas[:])
dados.append(pessoa[:])
notas.clear()
pessoa.clear()
continuar = str(input('Deseja continuar? [S/N]')).upper().strip()[0]
if continuar in 'N': break
print(dados)
print(pessoa)
print('-='*50)
print('N° Nome Média')
print('-'*30)
for contador_dados in range(0,len(dados)):
print(f'{contador_dados}', end=' ')
print(f'{dados[contador_dados][0]:<5}', end='')
print(f'{(dados[contador_dados][1][0] +dados[contador_dados][1][1])/2:>30}')
while True:
print('-'*30)
aluno = int(input('Mostrar nota de qual aluno? [999 interrompe]'))
if aluno == 999: break
print(f'Notas de {dados[aluno][0]} são {dados[aluno][1]}')
# Nota:{(dados[contador_pessoa][1][0] + dados[contador_pessoa][1][1])/2}
# Nome: {dados[contador_pessoa][0]} |
s = input()
length = len(s)
word_len = int(length / 3)
t = ""
if s[0:word_len] == s[word_len:word_len*2]:
t = s[0:word_len]
elif s[word_len:word_len*2] == s[word_len*2:word_len*3]:
t = s[word_len:word_len*2]
else:
t = s[0:word_len]
print(t) |
# Use cmd --
# use python .\87exeTest.txt
# pyinstaller .\87exeTest.txt
# .\87exeTest.exe
# For one file :
# Use cmd --
# pyinstaller --onefile .\87exeTest.py
# .\87exeTest.exe
print('Welcome to Adder')
print(int(input())+int(input()))
|
# Faça um programa que faça 5 perguntas para uma pessoa sobre um crime. As perguntas são:
#
# "Telefonou para a vítima?"
# "Esteve no local do crime?"
# "Mora perto da vítima?"
# "Devia para a vítima?"
# "Já trabalhou com a vítima?"
#
# O programa deve no final emitir uma classificação sobre a participação da pessoa no crime.
# Se a pessoa responder positivamente a 2 questões ela deve ser classificada como "Suspeita", entre 3 e 4 como "Cúmplice" e 5 como "Assassino".
# Caso contrário, ele será classificado como "Inocente".
print("-"*30)
print(" INTERROGATÓRIO SOBRE O CRIME ")
print("-"*30)
count = 0
pergunta = input("Telefonou para a vítima? [SIM ou NÃO]: ")
pergunta.lower()
if pergunta == "sim":
count += 1
pergunta = input("Esteve no local do crime? [SIM ou NÃO]: ")
pergunta.upper()
if pergunta == "sim":
count += 1
pergunta = input("Mora perto da vítima? [SIM ou NÃO]: ")
pergunta.upper()
if pergunta == "sim":
count += 1
pergunta = input("Devia para a vítima? [SIM ou NÃO]: ")
pergunta.upper()
if pergunta == "sim":
count += 1
pergunta = input("Já trabalhou com a vítima? [SIM ou NÃO]: ")
pergunta.upper()
if pergunta == "sim":
count += 1
if count == 2:
print("Suspeito.")
elif count == 3 or count == 4:
print("Cúmplice.")
elif count == 5:
print("Assassino!")
else:
print("Inocente.")
|
"""Helper function for _load_compcor."""
prefix_compcor = {"temporal_anat": ["t", "a"],
"temporal": ["t"],
"anat": ["a"]}
anat_masker = {"combined": ["combined"],
"separated": ["WM", "CSF"],
None: None}
def _find_compcor(confounds_json, compcor, n_compcor):
"""Build list for the number of compcor components."""
prefix_set, anat_mask = _check_compcor_method(compcor)
collector = []
for prefix in prefix_set:
# all possible compcor confounds in order, mixing different
# types of mask
all_compcor_name = [
comp
for comp in confounds_json.keys()
if f"{prefix}_comp_cor" in comp
]
# filter by prefix first (anat vs temporal)
compcor_cols_filt = _prefix_confound_filter(prefix, all_compcor_name)
if prefix == "a":
# apply acompor mask option if relevant, and select top components
compcor_cols_filt = _acompcor_mask(
confounds_json, anat_mask, compcor_cols_filt, n_compcor
)
else:
# select top components
compcor_cols_filt = _select_compcor(compcor_cols_filt, n_compcor)
# Aggregate components across all masks
collector += compcor_cols_filt
return collector
def _select_compcor(compcor_cols, n_compcor):
"""Retain a specified number of compcor components."""
# only select if not "all", or less components are requested than there
# actually is
if (n_compcor != "all") and (n_compcor < len(compcor_cols)):
compcor_cols = compcor_cols[0:n_compcor]
return compcor_cols
def _check_compcor_method(compcor):
"""Load compcor options and check if method is acceptable."""
compcor_type = compcor.split("_")
if len(compcor_type) > 1:
compcor_type = "_".join(compcor_type[:-1])
anat_mask_type = compcor.split("_")[-1:][0]
else:
compcor_type = compcor_type[0]
anat_mask_type = None
# get relevant prefix from compcor strategy
prefix_set = prefix_compcor[compcor_type]
# get relevant compcor mask
anat_mask = anat_masker[anat_mask_type]
return prefix_set, anat_mask
def _acompcor_mask(confounds_json, anat_mask, compcor_cols_filt, n_compcor):
"""Filter according to acompcor mask(s) and select top components."""
collector = []
for mask in anat_mask:
cols = _json_mask(compcor_cols_filt, confounds_json, mask)
cols = _select_compcor(cols, n_compcor)
collector += cols
return collector
def _json_mask(compcor_cols_filt, confounds_json, mask):
"""Extract anat compcor components from a given mask."""
return [
compcor_col
for compcor_col in compcor_cols_filt
if confounds_json[compcor_col]["Mask"] in mask
]
def _prefix_confound_filter(prefix, all_compcor_name):
"""Get confound columns by prefix and acompcor mask."""
compcor_cols_filt = []
for nn in range(len(all_compcor_name)):
nn_str = str(nn).zfill(2)
compcor_col = f"{prefix}_comp_cor_{nn_str}"
compcor_cols_filt.append(compcor_col)
return compcor_cols_filt
|
class Solution(object):
def wordBreak(self, s, wordDict):
def helper(s_left):
if not s_left: return True
if s_left in history: return history[s_left]
for word in wordDict:
if len(s_left)<len(word): continue
if s_left[:len(word)]==word and helper(s_left[len(word):]):
history[s_left] = True
return history[s_left]
history[s_left] = False
return history[s_left]
history = {}
return helper(s) |
#############################################
## Load masterBedroom controlCommands
#############################################
print('Load masterBedroom controlCommands')
longPress = .5 #seconds
commands = {
"Home": [
{"controlWord": "Home", "hidCode": 0x223, "hidReport": 2, "options": "reload"}
],
"Menu": [
{"controlWord": "Menu", "hidCode": 0x40, "hidReport": 2}
],
"Back": [
{"controlWord": "Back", "hidCode": 0x46, "hidReport": 2}
],
"Up": [
{"controlWord": "Up", "hidCode": 0x42, "hidReport": 2}
],
"Down": [
{"controlWord": "Down", "hidCode": 0x43, "hidReport": 2}
],
"Left": [
{"controlWord": "Left", "hidCode": 0x44, "hidReport": 2}
],
"Right": [
{"controlWord": "Right", "hidCode": 0x45, "hidReport": 2}
],
"Ok": [
{"controlWord": "Ok", "hidCode": 0x41, "hidReport": 2}
],
"Softer": [
{"controlWord": "Softer", "hidCode": 0xEA, "hidReport": 2}
],
"Louder": [
{"controlWord": "Louder", "hidCode": 0xE9, "hidReport": 2}
],
"Silence": [
{"controlWord": "Menu", "hidCode": 0xE2, "hidReport": 2}
],
"Sound": [
{"controlWord": "Menu", "hidCode": 0xE2, "hidReport": 2}
],
"SoundToggle": [
{"controlWord": "SoundToggle", "hidCode": 0xE2, "hidReport": 2}
],
"Forward": [
{"controlWord": "Forward", "hidCode": 0xB3, "hidReport": 2, "hidWait": longPress, "hidRepeat": 1}
],
"Backward": [
{"controlWord": "Backward", "hidCode": 0xB4, "hidReport": 2, "hidWait": longPress, "hidRepeat": 1}
],
"PlayToggle": [
{"controlWord": "PlayToggle", "hidCode": 0xCD, "hidReport": 2}
],
"On": [
{"controlWord": "Home", "hidCode": 0x223, "hidReport": 2},
],
"OnToggle": [
{"controlWord": "OnToggle", "hidCode": 0x30, "hidReport": 2},
]
}
|
"""
@author Victor I. Afolabi
A.I. Engineer & Software developer
javafolabi@gmail.com
Created on 22 December, 2017 @ 9:57 PM.
Copyright © 2017. Victor. All rights reserved.
"""
|
class Matrix: # Class that creates adjacency matrix for displaying graph.
def __init__(self):
self.graph = {} # graph to be displayed
self.matrix = [] # list that will contain the adjacency matrix
def create_matrix(self):
keys = sorted(self.graph.keys()) # ordering of keys in graph for use in matrix table
self.matrix.append(['-'] + keys) # column headers
for node in keys:
row = [node] # create a row[list] for each key in the graph
for neighbours in keys: # for every node in the graph
if node == neighbours: # check if the nodes are same
row.append('-') # if same then insert blank
elif neighbours in self.graph[node]: # if neighbour node is actually a neighbour of the current node
row.append(self.graph[node][neighbours]) # insert the distance from the node to the neighbour
else:
row.append('-') # the neighbour node is not in the neighbours of source so blank is inserted
self.matrix.append(row) # Add completed row to matrix
return self.display_matrix() # call method for display graph formatting
def display_matrix(self): # function to display graph as formatted string string
display_matrix = [map("{:^7}".format, line) for line in self.matrix] # map applies formatting every list in -
# matrix
# ^7 is spacing between elements
start = "([" # opening part of string
end = "])" # last part of string
lines = ["[{}]".format(" ".join(array)) for array in display_matrix] # joins the formatted graph
line_prefix = ",\n" + " " * len(start)
data = line_prefix.join(lines)
return start + data + end # return the matrix
|
"""
PERIODS
"""
numPeriods = 180
"""
STOPS
"""
numStations = 13
station_names = (
"Hamburg Hbf", # 0
"Landwehr", # 1
"Hasselbrook", # 2
"Wansbeker Chaussee*", # 3
"Friedrichsberg*", # 4
"Barmbek*", # 5
"Alte Woehr (Stadtpark)", # 6
"Ruebenkamp (City Nord)", # 7
"Ohlsdorf*", # 8
"Kornweg", # 9
"Hoheneichen", # 10
"Wellingsbuettel", # 11
"Poppenbuettel*", # 12
)
numStops = 26
stops_position = (
(0, 0), # Stop 0
(2, 0), # Stop 1
(3, 0), # Stop 2
(4, 0), # Stop 3
(5, 0), # Stop 4
(6, 0), # Stop 5
(7, 0), # Stop 6
(8, 0), # Stop 7
(9, 0), # Stop 8
(11, 0), # Stop 9
(13, 0), # Stop 10
(14, 0), # Stop 11
(15, 0), # Stop 12
(15, 1), # Stop 13
(15, 1), # Stop 14
(13, 1), # Stop 15
(12, 1), # Stop 16
(11, 1), # Stop 17
(10, 1), # Stop 18
(9, 1), # Stop 19
(8, 1), # Stop 20
(7, 1), # Stop 21
(6, 1), # Stop 22
(4, 1), # Stop 23
(2, 1), # Stop 24
(1, 1), # Stop 25
)
stops_distance = (
(0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 0
(0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 1
(0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 2
(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 3
(0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 4
(0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 5
(0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 6
(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 7
(0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 8
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 9
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 10
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 11
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 12
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 13
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 14
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 15
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 16
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0), # Stop 17
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0), # Stop 18
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0), # Stop 19
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0), # Stop 20
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), # Stop 21
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0), # Stop 22
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0), # Stop 23
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2), # Stop 24
(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # Stop 25
)
station_start = 0
"""
TRAMS
"""
numTrams = 18
tram_capacity = 514
tram_capacity_cargo = 304
tram_capacity_min_passenger = 208
tram_capacity_min_cargo = 0
tram_speed = 1
tram_headway = 1
tram_min_service = 1
tram_max_service = 10
min_time_next_tram = 0.333
tram_travel_deviation = 0.167
"""
PASSENGERS
"""
passenger_set = "pas-20210422-1717-int1"
passenger_service_time_board = 0.0145
passenger_service_time_alight = 0.0145
"""
CARGO
"""
numCargo = 90
cargo_size = 4
cargo_station_destination = (
8, # 0
8, # 1
4, # 2
5, # 3
3, # 4
8, # 5
4, # 6
3, # 7
5, # 8
12, # 9
12, # 10
5, # 11
5, # 12
3, # 13
8, # 14
3, # 15
12, # 16
4, # 17
5, # 18
5, # 19
8, # 20
5, # 21
5, # 22
5, # 23
8, # 24
5, # 25
12, # 26
8, # 27
4, # 28
8, # 29
5, # 30
8, # 31
3, # 32
5, # 33
12, # 34
4, # 35
3, # 36
12, # 37
12, # 38
8, # 39
3, # 40
5, # 41
4, # 42
4, # 43
12, # 44
3, # 45
12, # 46
12, # 47
5, # 48
3, # 49
12, # 50
5, # 51
12, # 52
5, # 53
12, # 54
4, # 55
5, # 56
3, # 57
4, # 58
12, # 59
5, # 60
3, # 61
8, # 62
5, # 63
4, # 64
5, # 65
3, # 66
8, # 67
5, # 68
12, # 69
4, # 70
8, # 71
8, # 72
3, # 73
5, # 74
12, # 75
3, # 76
8, # 77
3, # 78
8, # 79
3, # 80
4, # 81
12, # 82
3, # 83
12, # 84
5, # 85
3, # 86
3, # 87
5, # 88
4, # 89
)
cargo_release = (
2, # 0
3, # 1
3, # 2
5, # 3
6, # 4
6, # 5
7, # 6
8, # 7
8, # 8
9, # 9
9, # 10
10, # 11
12, # 12
12, # 13
12, # 14
13, # 15
14, # 16
14, # 17
15, # 18
16, # 19
17, # 20
18, # 21
19, # 22
21, # 23
22, # 24
24, # 25
25, # 26
26, # 27
27, # 28
28, # 29
28, # 30
29, # 31
30, # 32
30, # 33
32, # 34
33, # 35
33, # 36
34, # 37
35, # 38
36, # 39
37, # 40
37, # 41
37, # 42
37, # 43
37, # 44
37, # 45
38, # 46
38, # 47
39, # 48
41, # 49
41, # 50
43, # 51
44, # 52
44, # 53
45, # 54
45, # 55
46, # 56
46, # 57
46, # 58
47, # 59
48, # 60
49, # 61
49, # 62
51, # 63
52, # 64
52, # 65
55, # 66
56, # 67
57, # 68
57, # 69
61, # 70
61, # 71
61, # 72
62, # 73
63, # 74
64, # 75
64, # 76
65, # 77
65, # 78
66, # 79
66, # 80
67, # 81
70, # 82
70, # 83
70, # 84
71, # 85
71, # 86
71, # 87
71, # 88
72, # 89
)
cargo_station_deadline = (
33, # 0
119, # 1
119, # 2
176, # 3
59, # 4
123, # 5
72, # 6
18, # 7
171, # 8
90, # 9
175, # 10
142, # 11
88, # 12
32, # 13
157, # 14
84, # 15
131, # 16
105, # 17
170, # 18
155, # 19
156, # 20
140, # 21
38, # 22
173, # 23
123, # 24
126, # 25
91, # 26
36, # 27
87, # 28
144, # 29
127, # 30
108, # 31
40, # 32
134, # 33
141, # 34
101, # 35
163, # 36
108, # 37
144, # 38
85, # 39
98, # 40
47, # 41
47, # 42
76, # 43
175, # 44
162, # 45
48, # 46
97, # 47
87, # 48
114, # 49
164, # 50
143, # 51
54, # 52
142, # 53
55, # 54
55, # 55
56, # 56
56, # 57
56, # 58
57, # 59
118, # 60
59, # 61
160, # 62
112, # 63
95, # 64
141, # 65
168, # 66
170, # 67
105, # 68
139, # 69
71, # 70
71, # 71
71, # 72
82, # 73
73, # 74
90, # 75
135, # 76
109, # 77
161, # 78
128, # 79
151, # 80
77, # 81
80, # 82
98, # 83
169, # 84
81, # 85
129, # 86
104, # 87
97, # 88
99, # 89
)
cargo_max_delay = 3
cargo_service_time_load = 0.3333333333333333
cargo_service_time_unload = 0.25
"""
parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html
"""
#initial entropy
entropy = 8991598675325360468762009371570610170
#index for seed sequence child
child_seed_index = (
0, # 0
)
|
##############################################################################
#
# Copyright (c) 2003 Zope Corporation and Contributors.
# All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED
# WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS
# FOR A PARTICULAR PURPOSE.
#
##############################################################################
"""Compute a resolution order for an object and it's bases
$Id: ro.py 25177 2004-06-02 13:17:31Z jim $
"""
def ro(object):
"""Compute a "resolution order" for an object
"""
return mergeOrderings([_flatten(object, [])])
def mergeOrderings(orderings, seen=None):
"""Merge multiple orderings so that within-ordering order is preserved
Orderings are constrained in such a way that if an object appears
in two or more orderings, then the suffix that begins with the
object must be in both orderings.
For example:
>>> _mergeOrderings([
... ['x', 'y', 'z'],
... ['q', 'z'],
... [1, 3, 5],
... ['z']
... ])
['x', 'y', 'q', 1, 3, 5, 'z']
"""
if seen is None:
seen = {}
result = []
orderings.reverse()
for ordering in orderings:
ordering = list(ordering)
ordering.reverse()
for o in ordering:
if o not in seen:
seen[o] = 1
result.append(o)
result.reverse()
return result
def _flatten(ob, result):
result.append(ob)
for base in ob.__bases__:
_flatten(base, result)
return result
|
#############################################################################
#
# Copyright (c) 2008 by Casey Duncan and contributors
# All Rights Reserved.
#
# This software is subject to the provisions of the MIT License
# A copy of the license should accompany this distribution.
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
#
#############################################################################
"""Particle system classes"""
__version__ = '$Id$'
class ParticleSystem(object):
def __init__(self, global_controllers=()):
"""Initialize the particle system, adding the specified global
controllers, if any
"""
# Tuples are used for global controllers to prevent
# unpleasant side-affects if they are added during update or draw
self.controllers = tuple(global_controllers)
self.groups = []
def add_global_controller(self, *controllers):
"""Add a global controller applied to all groups on update"""
self.controllers += controllers
def add_group(self, group):
"""Add a particle group to the system"""
self.groups.append(group)
def remove_group(self, group):
"""Remove a particle group from the system, raise ValueError
if the group is not in the system
"""
self.groups.remove(group)
def __len__(self):
"""Return the number of particle groups in the system"""
return len(self.groups)
def __iter__(self):
"""Iterate the system's particle groups"""
# Iterate a copy of the group list to so that the groups
# can be safely changed during iteration
return iter(list(self.groups))
def __contains__(self, group):
"""Return True if the specified group is in the system"""
return group in self.groups
def update(self, time_delta):
"""Update all particle groups in the system. time_delta is the
time since the last update (in arbitrary time units).
When updating, first the global controllers are applied to
all groups. Then update(time_delta) is called for all groups.
This method can be conveniently scheduled using the Pyglet
scheduler method: pyglet.clock.schedule_interval
"""
for group in self:
group.update(time_delta)
def run_ahead(self, time, framerate):
"""Run the particle system for the specified time frame at the
specified framerate to move time forward as quickly as possible.
Useful for "warming up" the particle system to reach a steady-state
before anything is drawn or to simply "skip ahead" in time.
time -- The amount of simulation time to skip over.
framerate -- The framerate of the simulation in updates per unit
time. Higher values will increase simulation accuracy,
but will take longer to compute.
"""
if time:
td = 1.0 / framerate
update = self.update
for i in xrange(int(time / td)):
update(td)
def draw(self):
"""Draw all particle groups in the system using their renderers.
This method is convenient to call from your Pyglet window's
on_draw handler to redraw particles when needed.
"""
for group in self:
group.draw()
|
class World():
def __init__(self, size):
# World Size
self.x_range = size[0]
self.y_range = size[1]
if(len(size) == 3):
self.z_range = size[2]
# World Information
self.environment = None
self.agents = []
self.comm_messages = []
def add_agent(self, agent):
self.agents.append(agent)
def set_environment(self, environment):
self.environment = environment
# Agents behaviour:
# - Observe Environment
# - Send out Communication
# - Receive Communication and Perform Action
def update(self, delta):
if(self.environment):
self.environment.update(delta)
# First let the agent observe the current world.
# - While observing, agent should create a plan on what it wants to do
for agent in self.agents:
agent.observe(self)
# Collect all communication messages
# - A comm_message can contain information on what the agent is planning to do.
self.comm_messages = []
for agent in self.agents:
comm_message = agent.communicate()
if(comm_message):
self.comm_messages.append( comm_message )
# Perform the (planned) action
# - Action can be influenced based comm_message (e.g. planned action might cause collision)
for agent in self.agents:
agent.update(self, delta) |
alt = float(input('Altura da parede em metros: '))
larg = float(input('Largura da parede em metros: '))
area = alt * larg
tinta = area / 2
print(f'Sua parede tem dimensão de {alt}x{larg} e sua área é {area:.3f}m²')
print(f'Para pintar essa parede, você precisará de {tinta}l de tinta')
|
#
# PySNMP MIB module NNCEXTVPTTP-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/NNCEXTVPTTP-MIB
# Produced by pysmi-0.3.4 at Mon Apr 29 20:13:17 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)
#
OctetString, ObjectIdentifier, Integer = mibBuilder.importSymbols("ASN1", "OctetString", "ObjectIdentifier", "Integer")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ConstraintsIntersection, ValueSizeConstraint, ConstraintsUnion, SingleValueConstraint, ValueRangeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsIntersection", "ValueSizeConstraint", "ConstraintsUnion", "SingleValueConstraint", "ValueRangeConstraint")
atmVclVpi, = mibBuilder.importSymbols("ATM-MIB", "atmVclVpi")
ifIndex, = mibBuilder.importSymbols("IF-MIB", "ifIndex")
nncExtensions, = mibBuilder.importSymbols("NNCGNI0001-SMI", "nncExtensions")
NotificationGroup, ObjectGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ObjectGroup", "ModuleCompliance")
Counter64, IpAddress, iso, Counter32, Gauge32, MibIdentifier, Unsigned32, ObjectIdentity, TimeTicks, NotificationType, Integer32, MibScalar, MibTable, MibTableRow, MibTableColumn, ModuleIdentity, Bits = mibBuilder.importSymbols("SNMPv2-SMI", "Counter64", "IpAddress", "iso", "Counter32", "Gauge32", "MibIdentifier", "Unsigned32", "ObjectIdentity", "TimeTicks", "NotificationType", "Integer32", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "ModuleIdentity", "Bits")
DisplayString, TextualConvention = mibBuilder.importSymbols("SNMPv2-TC", "DisplayString", "TextualConvention")
nncExtVpttp = ModuleIdentity((1, 3, 6, 1, 4, 1, 123, 3, 80))
if mibBuilder.loadTexts: nncExtVpttp.setLastUpdated('200007211126Z')
if mibBuilder.loadTexts: nncExtVpttp.setOrganization('Alcatel Networks Corporation')
nncExtVpttpObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 123, 3, 80, 1))
nncExtVpttpGroups = MibIdentifier((1, 3, 6, 1, 4, 1, 123, 3, 80, 3))
nncExtVpttpCompliances = MibIdentifier((1, 3, 6, 1, 4, 1, 123, 3, 80, 4))
nncCrVpTrailTerminationPointTable = MibTable((1, 3, 6, 1, 4, 1, 123, 3, 80, 1, 1), )
if mibBuilder.loadTexts: nncCrVpTrailTerminationPointTable.setStatus('current')
nncCrVpTrailTerminationPointEntry = MibTableRow((1, 3, 6, 1, 4, 1, 123, 3, 80, 1, 1, 1), ).setIndexNames((0, "IF-MIB", "ifIndex"), (0, "ATM-MIB", "atmVclVpi"))
if mibBuilder.loadTexts: nncCrVpTrailTerminationPointEntry.setStatus('current')
nncCrVpTrailTerminationPoint = MibTableColumn((1, 3, 6, 1, 4, 1, 123, 3, 80, 1, 1, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2))).clone(namedValues=NamedValues(("disabled", 0), ("enabledWithNoAlarms", 1), ("enabledWithAlarms", 2)))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: nncCrVpTrailTerminationPoint.setStatus('current')
nncCrVpTrailTerminationPointGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 123, 3, 80, 3, 1)).setObjects(("NNCEXTVPTTP-MIB", "nncCrVpTrailTerminationPoint"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
nncCrVpTrailTerminationPointGroup = nncCrVpTrailTerminationPointGroup.setStatus('current')
nncVpttpCompliance = ModuleCompliance((1, 3, 6, 1, 4, 1, 123, 3, 80, 4, 1)).setObjects(("NNCEXTVPTTP-MIB", "nncCrVpTrailTerminationPointGroup"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
nncVpttpCompliance = nncVpttpCompliance.setStatus('current')
mibBuilder.exportSymbols("NNCEXTVPTTP-MIB", nncExtVpttpObjects=nncExtVpttpObjects, nncCrVpTrailTerminationPointTable=nncCrVpTrailTerminationPointTable, nncExtVpttpGroups=nncExtVpttpGroups, PYSNMP_MODULE_ID=nncExtVpttp, nncVpttpCompliance=nncVpttpCompliance, nncCrVpTrailTerminationPointGroup=nncCrVpTrailTerminationPointGroup, nncExtVpttp=nncExtVpttp, nncCrVpTrailTerminationPointEntry=nncCrVpTrailTerminationPointEntry, nncCrVpTrailTerminationPoint=nncCrVpTrailTerminationPoint, nncExtVpttpCompliances=nncExtVpttpCompliances)
|
# -*- coding: utf-8 -*-
"""This package contains code related to all authorization calls.
The main and currently only supported authorization method is OAuth2.
"""
|
"""
https://www.codewars.com/kata/5412509bd436bd33920011bc/train/python
Given a string consisting of a cc number,
return a string in which all but the last four characters are changed into #
maskify("4556364607935616") == "############5616"
maskify( "64607935616") == "#######5616"
maskify( "1") == "1"
maskify( "") == ""
"""
def maskify(cc: str) -> str:
if len(cc) < 4:
return cc
return '#' * (len(cc)-4) + cc[-4:]
print(maskify("4556364607935616"))
print(maskify("64607935616"))
print(maskify("1"))
print(maskify(""))
|
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