Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

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from django.conf import settings from rest_framework_jwt.authentication import JSONWebTokenAuthentication from rest_framework_jwt.settings import api_settings from .user_utils import get_or_create_user def patch_jwt_settings(): """Patch rest_framework_jwt authentication settings from allauth""" defaults = api_settings.defaults defaults['JWT_PAYLOAD_GET_USER_ID_HANDLER'] = ( __name__ + '.get_user_id_from_payload_handler') if 'allauth.socialaccount' not in settings.INSTALLED_APPS: return from allauth.socialaccount.models import SocialApp try: app = SocialApp.objects.get(provider='helsinki') except SocialApp.DoesNotExist: return defaults['JWT_SECRET_KEY'] = app.secret defaults['JWT_AUDIENCE'] = app.client_id # Disable automatic settings patching for now because it breaks Travis. # patch_jwt_settings() class JWTAuthentication(JSONWebTokenAuthentication): def authenticate_credentials(self, payload): return get_or_create_user(payload) def get_user_id_from_payload_handler(payload): return payload.get('sub')

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from collections import namedtuple Apple = namedtuple("Apple", ["species_name", "size", "price"]) def run(): apple = Apple("Gala", "M", 2.5) print(apple.species_name) print(apple.size) print(apple.price) print(apple[0]) print(apple[1]) print(apple[2]) for data in apple: print(data) if __name__ == '__main__': run()

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# (C) Datadog, Inc. 2019 # All rights reserved # Licensed under a 3-clause BSD style license (see LICENSE) import pytest from datadog_checks.ibm_db2.utils import scrub_connection_string pytestmark = pytest.mark.unit class TestPasswordScrubber: def test_start(self): s = 'pwd=password;...' assert scrub_connection_string(s) == 'pwd=********;...' def test_end(self): s = '...;pwd=password' assert scrub_connection_string(s) == '...;pwd=********' def test_no_match_within_value(self): s = '...pwd=password;...' assert scrub_connection_string(s) == s

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import _surface import chimera try: import chimera.runCommand except: pass from VolumePath import markerset as ms try: from VolumePath import Marker_Set, Link new_marker_set=Marker_Set except: from VolumePath import volume_path_dialog d= volume_path_dialog(True) new_marker_set= d.new_marker_set marker_sets={} surf_sets={} if "Cog1_Anch" not in marker_sets: s=new_marker_set('Cog1_Anch') marker_sets["Cog1_Anch"]=s s= marker_sets["Cog1_Anch"] mark=s.place_marker((440, 791, 782), (0, 0, 1), 21.9005) if "Cog2_GFPN" not in marker_sets: s=new_marker_set('Cog2_GFPN') marker_sets["Cog2_GFPN"]=s s= marker_sets["Cog2_GFPN"] mark=s.place_marker((225, 173, 486), (1, 0.5, 0), 21.9005) if "Cog2_GFPC" not in marker_sets: s=new_marker_set('Cog2_GFPC') marker_sets["Cog2_GFPC"]=s s= marker_sets["Cog2_GFPC"] mark=s.place_marker((189, 410, 398), (1, 0.5, 0), 21.9005) if "Cog2_Anch" not in marker_sets: s=new_marker_set('Cog2_Anch') marker_sets["Cog2_Anch"]=s s= marker_sets["Cog2_Anch"] mark=s.place_marker((223, 777, 905), (1, 0.5, 0), 21.9005) if "Cog3_GFPN" not in marker_sets: s=new_marker_set('Cog3_GFPN') marker_sets["Cog3_GFPN"]=s s= marker_sets["Cog3_GFPN"] mark=s.place_marker((478, 789, 82), (1, 0.87, 0), 21.9005) if "Cog3_GFPC" not in marker_sets: s=new_marker_set('Cog3_GFPC') marker_sets["Cog3_GFPC"]=s s= marker_sets["Cog3_GFPC"] mark=s.place_marker((333, 343, 863), (1, 0.87, 0), 21.9005) if "Cog3_Anch" not in marker_sets: s=new_marker_set('Cog3_Anch') marker_sets["Cog3_Anch"]=s s= marker_sets["Cog3_Anch"] mark=s.place_marker((31, 931, 648), (1, 0.87, 0), 21.9005) if "Cog4_GFPN" not in marker_sets: s=new_marker_set('Cog4_GFPN') marker_sets["Cog4_GFPN"]=s s= marker_sets["Cog4_GFPN"] mark=s.place_marker((870, 666, 358), (0.97, 0.51, 0.75), 21.9005) if "Cog4_GFPC" not in marker_sets: s=new_marker_set('Cog4_GFPC') marker_sets["Cog4_GFPC"]=s s= marker_sets["Cog4_GFPC"] mark=s.place_marker((808, 521, 926), (0.97, 0.51, 0.75), 21.9005) if "Cog4_Anch" not in marker_sets: s=new_marker_set('Cog4_Anch') marker_sets["Cog4_Anch"]=s s= marker_sets["Cog4_Anch"] mark=s.place_marker((930, 997, 266), (0.97, 0.51, 0.75), 21.9005) if "Cog5_GFPN" not in marker_sets: s=new_marker_set('Cog5_GFPN') marker_sets["Cog5_GFPN"]=s s= marker_sets["Cog5_GFPN"] mark=s.place_marker((361, 198, 927), (0.39, 0.31, 0.14), 21.9005) if "Cog5_GFPC" not in marker_sets: s=new_marker_set('Cog5_GFPC') marker_sets["Cog5_GFPC"]=s s= marker_sets["Cog5_GFPC"] mark=s.place_marker((324, 359, 244), (0.39, 0.31, 0.14), 21.9005) if "Cog5_Anch" not in marker_sets: s=new_marker_set('Cog5_Anch') marker_sets["Cog5_Anch"]=s s= marker_sets["Cog5_Anch"] mark=s.place_marker((138, 760, 307), (0.39, 0.31, 0.14), 21.9005) if "Cog6_GFPN" not in marker_sets: s=new_marker_set('Cog6_GFPN') marker_sets["Cog6_GFPN"]=s s= marker_sets["Cog6_GFPN"] mark=s.place_marker((105, 308, 227), (0.6, 0.31, 0.64), 21.9005) if "Cog6_GFPC" not in marker_sets: s=new_marker_set('Cog6_GFPC') marker_sets["Cog6_GFPC"]=s s= marker_sets["Cog6_GFPC"] mark=s.place_marker((981, 431, 237), (0.6, 0.31, 0.64), 21.9005) if "Cog6_Anch" not in marker_sets: s=new_marker_set('Cog6_Anch') marker_sets["Cog6_Anch"]=s s= marker_sets["Cog6_Anch"] mark=s.place_marker((90, 179, 506), (0.6, 0.31, 0.64), 21.9005) if "Cog7_GFPN" not in marker_sets: s=new_marker_set('Cog7_GFPN') marker_sets["Cog7_GFPN"]=s s= marker_sets["Cog7_GFPN"] mark=s.place_marker((62, 80, 966), (0.89, 0.1, 0.1), 21.9005) if "Cog7_GFPC" not in marker_sets: s=new_marker_set('Cog7_GFPC') marker_sets["Cog7_GFPC"]=s s= marker_sets["Cog7_GFPC"] mark=s.place_marker((941, 518, 40), (0.89, 0.1, 0.1), 21.9005) if "Cog7_Anch" not in marker_sets: s=new_marker_set('Cog7_Anch') marker_sets["Cog7_Anch"]=s s= marker_sets["Cog7_Anch"] mark=s.place_marker((148, 603, 718), (0.89, 0.1, 0.1), 21.9005) if "Cog8_GFPC" not in marker_sets: s=new_marker_set('Cog8_GFPC') marker_sets["Cog8_GFPC"]=s s= marker_sets["Cog8_GFPC"] mark=s.place_marker((755, 407, 323), (0.3, 0.69, 0.29), 21.9005) if "Cog8_Anch" not in marker_sets: s=new_marker_set('Cog8_Anch') marker_sets["Cog8_Anch"]=s s= marker_sets["Cog8_Anch"] mark=s.place_marker((819, 809, 563), (0.3, 0.69, 0.29), 21.9005) for k in surf_sets.keys(): chimera.openModels.add([surf_sets[k]])

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batxes@gmail.com

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import math def calcula_gaussiana(x, mi, sigma): form = (1/ (sigma((2*math.pi)**(1/2))))* (e**(((-0.5((z-mi)/sigma))**2)) return form

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class Solution: def minWindow(self, s: str, t: str) -> str: ans = float('inf') minstr = '' sourcehash = [0] * 256 targethash = [0] * 256 self.init_target_hash(targethash, t) j = 0 for i in range(len(s)): while not self.valid(sourcehash, targethash) and j < len(s): sourcehash[ord[j]] += 1 j += 1 if self.valid(sourcehash, targethash): if ans > j - i: ans = j - i minstr = s[i:j] sourcehash[ord[i]] -= 1 return minstr def init_target_hash(self, targethash, t): for ch in t: targethash[ord[ch]] = targethash.get(ord[ch], 0) + 1 def valid(self, sourcehash, targethash): # to check whether it is includes in targethash for i in range(256): if targethash[i] > sourcehash[i]: return False return True ## time, space - O(N) from collections import Counter, defaultdict class Solution: def minWindow(self, s: str, t: str) -> str: t_cnts = Counter(t) s_cnts = defaultdict(int) start, end = 0, 0 match = 0 minstr = '' minLen = float('inf') while end < len(s): s_cnts[s[end]] += 1 if s[end] in t_cnts and s_cnts[s[end]] == t_cnts[s[end]]: match += 1 end += 1 while match == len(t_cnts): if end - start < minLen: minLen = end - start minstr = s[start:end] s_cnts[s[start]] -= 1 if s[start] in t_cnts and s_cnts[s[start]] < t_cnts[s[start]]: match -= 1 start += 1 return minstr

[ "xucaizhi@gmail.com" ]

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from django.shortcuts import render,redirect from .models import * from .forms import * from Profile.models import * from django.http import JsonResponse from django.contrib.auth.decorators import login_required import json import datetime from .utils import * # Create your views here. def show_all_product(request): all_brand=brand.objects.all() all_category=category.objects.all() all_products=index.objects.all().order_by('-id')[:6] if request.user.is_authenticated: cookieContent=cookieCart(request) item=cookieContent['items'] net_total=cookieContent['net'] total=cookieContent['total'] else: cookieContent=cookieCart(request) item=cookieContent['items'] net_total=0 total=cookieContent['total'] return render(request,'main/index.html',{'all_brand':all_brand ,'all_category':all_category,'products':all_products,'total':total}) def product_detail(request,slug): all_products=index.objects.get(slug=slug) all_brand=brand.objects.all() all_category=category.objects.all() all_reviews=review.objects.all() if request.method=='POST': form=reviewForm(request.POST,request.FILES) if form.is_valid(): form.save() else: form=reviewForm() return render(request,'main/product_details.html',{'products':all_products,'all_brand':all_brand ,'all_category':all_category,'form':form,'revi':all_reviews}) def wish_list(request,slug): product=index.objects.get(slug=slug) if request.user in product.add_to_wishlist.all(): product.add_to_wishlist.remove(request.user) else: product.add_to_wishlist.add(request.user) return redirect('main:show') def wishlist_page(request): product_wished=index.objects.filter(add_to_wishlist=request.user) return render(request,'main/wish_page.html',{'wished':product_wished}) def search_by_category(request): cat=request.GET['category'] print (cat) all_brand=brand.objects.all() all_category=category.objects.all() name_of_category=category.objects.get(category_name=cat) categore_selected_result=index.objects.filter(product_category=name_of_category.id) return render(request,'main/search_category.html',{'category':categore_selected_result,'all_brand':all_brand ,'all_category':all_category}) def search_by_brand(request): brand_=request.GET['brand'] print(brand_) all_brand=brand.objects.all() all_category=category.objects.all() brand_name=brand.objects.get(brand_name = brand_) brand_selected_result=index.objects.filter(product_brand=brand_name.id) return render(request,'main/search_brand.html',{'brand':brand_selected_result,'all_brand':all_brand ,'all_category':all_category}) def cart(request): if request.user.is_authenticated: cartData=dataCart(request) item=cartData['items'] net_total=cartData['net'] total=cartData['total'] else: cookieContent=cookieCart(request) item=cookieContent['items'] net_total=cookieContent['net'] total=cookieContent['total'] return render(request,'main/cart.html',{'items':item ,'net':net_total,'total':total}) def checkout(request): if request.user.is_authenticated: cartData=dataCart(request) item=cartData['items'] net_total=cartData['net'] total=cartData['total'] coutries=cartData['countries'] states=cartData['state'] shipping_info=shippinginfo.objects.all() shiped=False for i in item: if i.item_order.order_completed ==False: shiped = True else: cookieContent=cookieCart(request) item=cookieContent['items'] net_total=cookieContent['net'] total=cookieContent['total'] shipping_info=shippinginfo.objects.all() coutries=country.objects.all() shiped=False states=state.objects.filter(state_country__in=coutries) return render(request,'main/checkout.html',{'items':item , 'net':net_total,'total':total,'countries':coutries,'state':states,'shiped':shiped,'info':shipping_info}) def update_cart(request): additon=json.loads(request.body) product=additon['produactId'] product_action=additon['action'] print(product_action,product) selected_product=index.objects.get(id=product) order_owner=request.user requested_user=userprofile.objects.get(usrename=order_owner) Order , create=order.objects.get_or_create(order_customer=requested_user,order_completed=False) item , create=orderItem.objects.get_or_create(item_name=selected_product,item_order=Order) if product_action == 'add': item.item_quantity = item.item_quantity elif product_action == 'add2': item.item_quantity = item.item_quantity + 1 else: item.item_quantity = item.item_quantity- 1 print('-') item.save() print(item.item_quantity) if item.item_quantity == 0: item.delete() if product_action == 'delete': item.delete() return JsonResponse('added',safe=False) def country_name_from_json(request,*args,**kwargs): selected_country=kwargs.get('country') states_according_to_country=list(state.objects.filter(state_country__country_name=selected_country).values()) return JsonResponse({'data':states_according_to_country}) from django.views.decorators.csrf import csrf_exempt @csrf_exempt def process_order(request): transaction_id2=datetime.datetime.now().timestamp() data=json.loads(request.body) print(data) print(transaction_id2) userc=request.user print(userc) if userc.is_authenticated: user=request.user print(user) customer=userprofile.objects.get(username=user) print(customer) Order=order.objects.get(order_customer=customer,order_compcleted=False) total=float(data['shippingData']['total']) print(total) order.transaction_id=transaction_id2 item=orderItem.objects.filter(item_order=Order) net_total=sum([items.total_selected_item for items in item]) if total == net_total: Order.order_completed=True Order.save() shiiping=shippinginfo.objects.create( shipping_user=customer,shipping_order=Order,shipping_mail=data['shippingData']['email'], title=data['shippingData']['title'],shipping_firstname=data['shippingData']['firstname'],shiping_middlename=data['shippingData']['middlename'], shipping_lastname=data['shippingData']['lastname'],shiping_adress1=data['shippingData']['adress1'],shipping_adress2=data['shippingData']['adress2'], shipping_zipcode=data['shippingData']['zipcode'],shipping_country=data['shippingData']['country'],shipping_state=data['shippingData']['state'], shipping_phone=data['shippingData']['phone'],shipping_mobile_number=data['shippingData']['mobile_number'],shipping_fax=data['shippingData']['fax'] ) shiiping.save() else: print('user not logged in') return JsonResponse('payment submitted.........',safe=False)

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''' Created on Apr 8, 2016 @author: Thomas ''' import re import sys def flip_stack(s): '''flip the provided stack/substack of pancakes''' # replace with temporary character s = s.replace('+', 't') # switch - for + s = s.replace('-', '+') # switch + for - s = s.replace('t', '-') return s def flip(stack, k): start = stack.find("-") end = (start + k) past_end = end - (len(stack) - 1) if past_end > 0: start -= past_end end -= past_end s_sub = stack[start:end] stack = stack[:start] + flip_stack(s_sub) + stack[end:] return stack def flip_decision(stack, k, num_flips=0): '''decide what to flip, do the flip, and continue until all happy faces''' print stack if "-" in stack: # Not all Happy Face Pancakes if ('-' * k) in stack: num_occ = stack.count('-' * k) stack = stack.replace(('-' * k), ('+' * k)) num_flips += num_occ elif stack.find("-") >= 0: print "pre" + stack stack = flip(stack, k) num_flips += 1 print "pos" + stack if num_flips > len(stack): return "IMPOSSIBLE" return flip_decision(stack, k, num_flips) else: return num_flips if __name__ == '__main__': out = {} with open("A-small-attempt2.in", 'rb') as f: lines = f.readlines()[1:] for idx,line in enumerate(lines): line = line.rstrip() pancakes = re.search("[+-]+", line).group(0) k = int(re.search("[0-9]+", line).group(0)) print line + str("||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||") num_flips = flip_decision(pancakes, k) out[idx+1] = num_flips with open("output.out", 'w') as f: f.write("") for key, val in out.iteritems(): line = "Case #" + str(key) + ": " + str(val) + "\n" f.write(line)

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#B q=input() count3=0 for j1 in q: if (j1.isdigit() or j1.isalpha()): count3+=1 if count3!=0: print("Yes") else: print("No")

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from board import board from human import humanInput from decentAI import decentAI from randomAI import randomAI from inorderAI import inorderAI from minimaxAI100 import minimaxAI100 from miniAIb100 import miniAIb100 from uctAI import uctAI import random class play: p1 = 1 p2 = -1 current = p1 win = 0 userInput = humanInput() b = board(7, 6) def __init__(self): self.current = self.p1 self.win = 0 def begin(self, whoGoesFirst): #print "Would you like to go first? Enter: [y/n]" #note that if user enters anything other than "n", user goes first if (whoGoesFirst == 1): valid = True self.current = self.p2 ai = True if (ai == True): opp = minimaxAI100() #1 opp2 = miniAIb100() #-1 depth = 4 depth2 = 5 while(self.win == 0): self.b.update() if self.b.boardFull() == True: break if (ai == True): if (self.current < 0): #print "--------AI 2's Move-------" # 1 self.b.move(self.current, opp2.chooseMove(self.b, self.current, depth2)) elif (self.current > 0): self.b.move(self.current, opp.chooseMove(self.b, self.current, depth)) valid = True #print "------AI 1's Move------" # -1 elif not ai: valid = True self.win = self.b.winner(self.current) if (valid == False): continue else: self.current = self.current * -1 self.b.update() # update print statement to print ai/user won #print opp.uctTree #opp.writeTree() #print"The winner is " print self.win # playAgain = True # count = 0 # while(playAgain == True): # count = count + 1 p = play() # if (count <=50): p.begin(0) # else: # p.begin(1) # #print "Would you like to play again? Enter: [y/n]" # #note that if user enters anything other than "n", user plays again # #if (raw_input() == "n"): # #playAgain = False # if (count > 100): # playAgain = False # else: p.b.setUp()

[ "szl5@cornell.edu" ]

szl5@cornell.edu

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/google/ads/google_ads/v2/proto/services/ad_group_ad_asset_view_service_pb2_grpc.py

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juanmacugat/google-ads-python

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refs/heads/master

2021-02-18T17:00:22.067673

2020-03-05T16:13:57

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# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! import grpc from google.ads.google_ads.v2.proto.resources import ad_group_ad_asset_view_pb2 as google_dot_ads_dot_googleads__v2_dot_proto_dot_resources_dot_ad__group__ad__asset__view__pb2 from google.ads.google_ads.v2.proto.services import ad_group_ad_asset_view_service_pb2 as google_dot_ads_dot_googleads__v2_dot_proto_dot_services_dot_ad__group__ad__asset__view__service__pb2 class AdGroupAdAssetViewServiceStub(object): """Proto file describing the ad group ad asset view service. Service to fetch ad group ad asset views. """ def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.GetAdGroupAdAssetView = channel.unary_unary( '/google.ads.googleads.v2.services.AdGroupAdAssetViewService/GetAdGroupAdAssetView', request_serializer=google_dot_ads_dot_googleads__v2_dot_proto_dot_services_dot_ad__group__ad__asset__view__service__pb2.GetAdGroupAdAssetViewRequest.SerializeToString, response_deserializer=google_dot_ads_dot_googleads__v2_dot_proto_dot_resources_dot_ad__group__ad__asset__view__pb2.AdGroupAdAssetView.FromString, ) class AdGroupAdAssetViewServiceServicer(object): """Proto file describing the ad group ad asset view service. Service to fetch ad group ad asset views. """ def GetAdGroupAdAssetView(self, request, context): """Returns the requested ad group ad asset view in full detail. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_AdGroupAdAssetViewServiceServicer_to_server(servicer, server): rpc_method_handlers = { 'GetAdGroupAdAssetView': grpc.unary_unary_rpc_method_handler( servicer.GetAdGroupAdAssetView, request_deserializer=google_dot_ads_dot_googleads__v2_dot_proto_dot_services_dot_ad__group__ad__asset__view__service__pb2.GetAdGroupAdAssetViewRequest.FromString, response_serializer=google_dot_ads_dot_googleads__v2_dot_proto_dot_resources_dot_ad__group__ad__asset__view__pb2.AdGroupAdAssetView.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'google.ads.googleads.v2.services.AdGroupAdAssetViewService', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,))

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/githubapi.py

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cclauss/repo-tools

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refs/heads/master

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"""Access to information using the GitHub API.""" from __future__ import print_function import operator import pprint import dateutil.parser from urlobject import URLObject from helpers import paginated_get, requests from models import PullRequestBase class JsonAttributeHelper(object): @classmethod def from_json(cls, issues_data): for issue_data in issues_data: if not cls.want_this_json_object(issue_data): continue yield cls(issue_data) @classmethod def want_this_json_object(cls, obj): return True def attribute_lookup(self, name, field_map, mapped_fields=None): obj = None for field_names, value in field_map: if name in field_names: obj = value break if obj is not None: if mapped_fields: name = mapped_fields.get(name, name) val = self.deep_getitem(obj, name) if name.endswith('_at') and val is not None: val = dateutil.parser.parse(val) return val raise AttributeError("Nope: don't have {!r} attribute on {}".format(name, self.__class__.__name__)) def deep_getitem(self, val, key): for k in key.split("."): if val is None: break val = val[k] return val class PullRequest(JsonAttributeHelper, PullRequestBase): def __init__(self, issue_data): self._issue = issue_data if 0: print("---< Issue >---------------------------------") pprint.pprint(issue_data) self._pull = None self.labels = [self.short_label(l['name']) for l in self.labels] @classmethod def want_this_json_object(cls, obj): pr_url = obj.get('pull_request', {}).get('url') return bool(pr_url) ISSUE_FIELDS = { 'assignee_login', 'closed_at', 'comments', 'comments_url', 'created_at', 'labels', 'number', 'pull_request_url', 'pull_request_html_url', 'state', 'title', 'updated_at', 'user_html_url', 'user_login', } PULL_FIELDS = { 'additions', 'base_ref', 'changed_files', 'commits', 'deletions', 'merged_at', } MAPPED_FIELDS = { 'assignee_login': 'assignee.login', 'base_ref': 'base.ref', 'pull_request_url': 'pull_request.url', 'pull_request_html_url': 'pull_request.html_url', 'user_login': 'user.login', 'user_html_url': 'user.html_url', } def __getattr__(self, name): return self.attribute_lookup( name, [(self.ISSUE_FIELDS, self._issue), (self.PULL_FIELDS, self._pull)], self.MAPPED_FIELDS ) def load_pull_details(self, pulls=None): """Get pull request details also. `pulls` is a dictionary of pull requests, to perhaps avoid making another request. """ if pulls: self._pull = pulls.get(self.number) if not self._pull: self._pull = requests.get(self.pull_request_url).json() if 0: print("---< Pull Request >--------------------------") pprint.pprint(self._pull) class Comment(JsonAttributeHelper): def __init__(self, obj): self._comment = obj FIELDS = { 'body', 'created_at', 'user_login', } def __getattr__(self, name): return self.attribute_lookup( name, [(self.FIELDS, self._comment)], {'user_login': 'user.login'}, ) def get_pulls(owner_repo, labels=None, state="open", since=None, org=False, pull_details=None): """ Get a bunch of pull requests (actually issues). `pull_details` indicates how much information you want from the associated pull request document. None means just issue information is enough. "list" means the information available when listing pull requests is enough. "all" means you need all the details. See the GitHub API docs for the difference: https://developer.github.com/v3/pulls/ """ url = URLObject("https://api.github.com/repos/{}/issues".format(owner_repo)) if labels: url = url.set_query_param('labels', ",".join(labels)) if since: url = url.set_query_param('since', since.isoformat()) if state: url = url.set_query_param('state', state) url = url.set_query_param('sort', 'updated') issues = PullRequest.from_json(paginated_get(url)) if org: issues = sorted(issues, key=operator.attrgetter("org")) pulls = None if pull_details == "list": issues = list(issues) if issues: # Request a bunch of pull details up front, for joining to. We can't # ask for exactly the ones we need, so make a guess. limit = int(len(issues) * 1.5) pull_url = URLObject("https://api.github.com/repos/{}/pulls".format(owner_repo)) if state: pull_url = pull_url.set_query_param('state', state) pulls = { pr['number']: pr for pr in paginated_get(pull_url, limit=limit) } for issue in issues: if pull_details: issue.load_pull_details(pulls=pulls) issue.id = "{}.{}".format(owner_repo, issue.number) yield issue def get_comments(pull): url = URLObject(pull.comments_url).set_query_param("sort", "created").set_query_param("direction", "desc") comments = Comment.from_json(paginated_get(url)) return comments

[ "ned@nedbatchelder.com" ]

ned@nedbatchelder.com

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/examples/data/Assignment_9/jnrkhy001/question2.py

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[]

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MrHamdulay/csc3-capstone

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refs/heads/master

2021-03-12T21:55:57.781339

2014-09-22T02:22:22

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py

# Khyati Jinerdeb # Assignment 9 # Date: 17.05.2014 # to program a text file to make them of same length def readF(filename): newLines = [] #To create a list file = open(filename,"r") #To open the file lines = file.readlines() #To read lines into a string file.close() #To close the file for line in lines: newLines.append(line.replace('\n','')) #To replace all the command for empty lines by an empty string(to remove all \n) return newLines #To add it to the list also def setLines(l,w): s = '' tmpL = [''] i = 0 for line in l: if len(line) > 1: words = line.split(' ') for word in words: if (len(tmpL[i])+len(word)) <= w : tmpL[i] += word+" " elif word == 'a': tmpL[i] += word else: tmpL.append(word+" ") i += 1 else: tmpL.append('\n') i += 1 return tmpL def writeF(filename,lines): #write contents of outList to output file f = open(filename,'w') for line in lines: print(line,file=f) f.close() def main(): inputF = input("Enter the input filename:\n") outputF = input("Enter the output filename:\n") wid = eval(input("Enter the line width:\n")) lines = readF(inputF) lines = setLines(lines,wid) writeF(outputF,lines) main()

[ "jarr2000@gmail.com" ]

jarr2000@gmail.com

4fae9ac1bbf6df3f073e7624c668d4427c7807a7

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/testRNN.py

16627f8f32b001e61b9a87911e6d7579e7942cfb

[]

no_license

sumitparw/NLP_Sentiment-Analysis-using-lstm

4a90dd842e24592b432ef47113fa1f17a2c0f2cf

6c1cc7717999cb16089376fe27a1e48e5b8ce2c7

refs/heads/master

2020-12-26T22:44:08.935738

2020-02-01T20:21:53

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UTF-8

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py

import nltk import random import pandas as pd from nltk.tokenize import word_tokenize import string import re import numpy as np import keras from keras.preprocessing.text import Tokenizer from keras.preprocessing.sequence import pad_sequences import matplotlib.pyplot as plt import seaborn as sns from sklearn.metrics import accuracy_score,f1_score from keras.models import Sequential from keras.layers import Dense,Embedding,LSTM,Dropout from keras.optimizers import Adam class rnn(): word_dict=dict() max_cap=80 def assign_label(self,x): if x[2] < 3.0 : return "negative" elif x[2] > 3.0 : return "positive" else: return "neutral" def clean_document(self,doco): punctuation = string.punctuation + '\n\n'; punc_replace = ''.join([' ' for s in punctuation]); doco_clean = doco.replace('-', ' '); doco_alphas = re.sub(r'\W +', '', doco_clean) trans_table = str.maketrans(punctuation, punc_replace); doco_clean = ' '.join([word.translate(trans_table) for word in doco_alphas.split(' ')]); doco_clean = doco_clean.split(' '); doco_clean = [word.lower() for word in doco_clean if len(word) > 0]; return doco_clean; def return_train_test_data_rnn(self,file_path): df = pd.read_csv(file_path,header=None) df = df[df.columns[2:4]] df[2] = df.apply(self.assign_label, axis=1) inx = df[df[2]=='neutral'].index df.drop(inx,inplace=True) df[2] = df[2].map({'negative': 0, 'positive': 1}) reviews = np.array(df[3].to_list()) labels = np.array(df[2].to_list()) review_cleans = [self.clean_document(doc) for doc in reviews]; sentences = [' '.join(r) for r in review_cleans] tokenizer = Tokenizer(); tokenizer.fit_on_texts(sentences); text_sequences = np.array(tokenizer.texts_to_sequences(sentences)); sequence_dict = tokenizer.word_index; self.word_dict = dict((num, val) for (val, num) in sequence_dict.items()); reviews_encoded = []; for i, review in enumerate(review_cleans): reviews_encoded.append([sequence_dict[x] for x in review]); lengths = [len(x) for x in reviews_encoded]; with plt.xkcd(): plt.hist(lengths, bins=range(100)) max_cap = 80; X = pad_sequences(reviews_encoded, maxlen=max_cap, truncating='post') Y = np.array([[0,1] if label == 0 else [1,0] for label in labels]) np.random.seed(1024); random_posits = np.arange(len(X)) np.random.shuffle(random_posits); # Shuffle X and Y X = X[random_posits]; Y = Y[random_posits]; # Divide the reviews into Training, Dev, and Test data. train_cap = int(0.70 * len(X)); dev_cap = int(0.85 * len(X)); X_train, Y_train = X[:train_cap], Y[:train_cap]; X_dev, Y_dev = X[train_cap:dev_cap], Y[train_cap:dev_cap]; X_test, Y_test = X[dev_cap:], Y[dev_cap:] return X_train,Y_train,X_dev,Y_dev,X_test,Y_test def build_model(self): model = Sequential(); model.add(Embedding(len(self.word_dict), self.max_cap, input_length=self.max_cap)); model.add(LSTM(80, return_sequences=True, recurrent_dropout=0.2)); model.add(Dropout(0.2)) model.add(LSTM(80, recurrent_dropout=0.2)); model.add(Dense(80, activation='relu')); model.add(Dense(2, activation='softmax')); print(model.summary()); return model def train_model(self,X_train,Y_train,X_dev,Y_dev): model= self.build_model() optimizer = Adam(lr=0.01, decay=0.001); model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy']) # fit model model.fit(X_train, Y_train, batch_size=600, epochs=1, validation_data=(X_dev, Y_dev)) return model def predict(self,X_test,model): predictions = model.predict_classes(X_test) return predictions def accuracy(self,predictions,X_test,Y_test,model): # Convert Y_test to the same format as predictions actuals = [0 if y[0] == 1 else 1 for y in Y_test] print("f1_score:"+f1_score) # Use SkLearn's Metrics module return accuracy_score(predictions, actuals)

[ "46736751+sumitparw@users.noreply.github.com" ]

46736751+sumitparw@users.noreply.github.com

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/setup.py

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pombredanne/google-resumable-media-python

076ec91e0b81999c0571009d30eb4649f4be3e39

c158f0f2e43d2730350bd1fbcce4ddde35c4aa96

refs/heads/master

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0

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# Copyright 2017 Google Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import setuptools PACKAGE_ROOT = os.path.abspath(os.path.dirname(__file__)) with open(os.path.join(PACKAGE_ROOT, 'README.rst')) as file_obj: README = file_obj.read() REQUIREMENTS = [ 'six', ] EXTRAS_REQUIRE = { 'requests': [ 'requests >= 2.18.0, < 3.0.0dev', ], } setuptools.setup( name='google-resumable-media', version='0.3.0', description='Utilities for Google Media Downloads and Resumable Uploads', author='Google Cloud Platform', author_email='googleapis-publisher@google.com', long_description=README, namespace_packages=['google'], scripts=[], url='https://github.com/GoogleCloudPlatform/google-resumable-media-python', packages=setuptools.find_packages(exclude=('tests*',)), license='Apache 2.0', platforms='Posix; MacOS X; Windows', include_package_data=True, zip_safe=False, install_requires=REQUIREMENTS, extras_require=EXTRAS_REQUIRE, classifiers=[ 'Development Status :: 3 - Alpha', 'Intended Audience :: Developers', 'License :: OSI Approved :: Apache Software License', 'Operating System :: OS Independent', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Topic :: Internet', ], )

[ "daniel.j.hermes@gmail.com" ]

daniel.j.hermes@gmail.com

1009696b09ebe1c6c83517db0ed3e096f49cd272

697c7514abc80e53dab70f22177c649d499500ce

/0015/A0015.py

e5f4ea89406e03fafc27a45f034c554f39ce471a

[]

no_license

aliceqin12/ShowMeTheCode

c2fbcf82090c7ccea47936f73c35efbfe927fc28

4d52e5b331912a6cc0f2dd842939067d0d2507d9

refs/heads/master

2021-07-01T19:24:04.602407

2017-09-20T02:09:59

null

0

null

UTF-8

Python

false

505

py

import json import xlrd import xlwt def writeCityDataToExcel(city_data): wb = xlwt.Workbook() table = wb.add_sheet('city') i = 0 for number in city_data: city_name = city_data.get(number) table.write(i, 0, number) table.write(i, 1, city_name) i += 1 wb.save('city.xls') if __name__ == '__main__': filename = 'city.txt' with open(filename, 'r', encoding='utf-8') as f: city_data = json.load(f) writeCityDataToExcel(city_data)

[ "geekworldzhang@163.com" ]

geekworldzhang@163.com

fc78ea23f77df88d8c88ccf06ee7ba2efa3455b1

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/Programs/Oops/destuctor2.py

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[]

no_license

Susama91/Project

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refs/heads/master

2020-05-15T01:56:11.035480

2019-04-19T07:13:43

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class x: def __init__(self): print("in constructor of x") def m1(self): print("in m1 of x") def __del__(self): print("in destructor of x") x1=x() print(x1) x2=x1 print(x2) x3=x2 print(x3) x1=x() print(x1) x2=x() print(x2) x3=x() print(x3)

[ "susama00@gmail.com" ]

susama00@gmail.com

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/userauth/migrations/0004_auto_20191205_2057.py

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[]

no_license

Aksa123/ecommerce

4b73571eb92ec3b36a3321cd368fbe40874b68bc

5de73daa318ab90cdf864600de6644266dc56ed5

refs/heads/master

2020-09-28T13:20:45.848574

2019-12-09T05:04:02

226,787,003

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# Generated by Django 2.2.7 on 2019-12-05 13:57 import datetime from django.db import migrations, models from django.utils.timezone import utc class Migration(migrations.Migration): dependencies = [ ('userauth', '0003_auto_20191205_2051'), ] operations = [ migrations.AlterField( model_name='userprofile', name='birthday', field=models.DateField(default=datetime.datetime(2019, 12, 5, 13, 57, 55, 294801, tzinfo=utc)), ), ]

[ "=" ]

=

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[]

no_license

AhsonAslam/webapi

54cf7466aac4685da1105f9fb84c686e38f92121

1b2bfa4614e7afdc57c9210b0674506ea70b20b5

refs/heads/master

2020-07-27T06:05:36.057953

2019-09-17T06:35:33

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UTF-8

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version https://git-lfs.github.com/spec/v1 oid sha256:5fc4a23b6bf0c06ea81c0d7f377ba3b35b99e19b6f9f35c06bdc98df2ce6e102 size 1649

[ "github@cuba12345" ]

github@cuba12345

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/venv/Scripts/temboo/Library/Google/Directions/GetBicyclingDirections.py

cde366c29ff3ab8d08f58f44735e9d9e575eb3cd

[]

no_license

DevHyperCoder/News_Manager

45b05061db5be8bb32f1485ff5480d4aa6145b3f

88b54c3d1995b8f015dc03ac30657e6f9777f3aa

refs/heads/master

2020-08-21T14:22:57.248732

2019-10-19T09:14:45

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UTF-8

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false

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# -*- coding: utf-8 -*- ############################################################################### # # GetBicyclingDirections # Generate biking directions between two locations, denoted by address or latitude/longitude coordinates. # # Python versions 2.6, 2.7, 3.x # # Copyright 2014, Temboo Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, # either express or implied. See the License for the specific # language governing permissions and limitations under the License. # # ############################################################################### from temboo.core.choreography import Choreography from temboo.core.choreography import InputSet from temboo.core.choreography import ResultSet from temboo.core.choreography import ChoreographyExecution import json class GetBicyclingDirections(Choreography): def __init__(self, temboo_session): """ Create a new instance of the GetBicyclingDirections Choreo. A TembooSession object, containing a valid set of Temboo credentials, must be supplied. """ super(GetBicyclingDirections, self).__init__(temboo_session, '/Library/Google/Directions/GetBicyclingDirections') def new_input_set(self): return GetBicyclingDirectionsInputSet() def _make_result_set(self, result, path): return GetBicyclingDirectionsResultSet(result, path) def _make_execution(self, session, exec_id, path): return GetBicyclingDirectionsChoreographyExecution(session, exec_id, path) class GetBicyclingDirectionsInputSet(InputSet): """ An InputSet with methods appropriate for specifying the inputs to the GetBicyclingDirections Choreo. The InputSet object is used to specify input parameters when executing this Choreo. """ def set_APIKey(self, value): """ Set the value of the APIKey input for this Choreo. ((required, string) The API Key provided by Google.) """ super(GetBicyclingDirectionsInputSet, self)._set_input('APIKey', value) def set_Alternatives(self, value): """ Set the value of the Alternatives input for this Choreo. ((optional, string) If set to true, additional routes will be returned.) """ super(GetBicyclingDirectionsInputSet, self)._set_input('Alternatives', value) def set_Destination(self, value): """ Set the value of the Destination input for this Choreo. ((required, string) Enter the address or latitude/longitude coordinates from which directions will be generated (i.e."104 Franklin St, New York, NY" or "40.7160,-74.0037").) """ super(GetBicyclingDirectionsInputSet, self)._set_input('Destination', value) def set_Origin(self, value): """ Set the value of the Origin input for this Choreo. ((required, string) Enter the address or latitude/longitude coordinates from which directions will be computed (i.e."104 Franklin St, New York, NY" or "40.7160,-74.0037").) """ super(GetBicyclingDirectionsInputSet, self)._set_input('Origin', value) def set_Region(self, value): """ Set the value of the Region input for this Choreo. ((optional, string) Enter the region code for the directions, specified as a ccTLD two-character value.) """ super(GetBicyclingDirectionsInputSet, self)._set_input('Region', value) def set_Sensor(self, value): """ Set the value of the Sensor input for this Choreo. ((optional, boolean) Indicates whether or not the directions request is from a device with a location sensor. Value must be either 1 or 0. Defaults to 0 (false).) """ super(GetBicyclingDirectionsInputSet, self)._set_input('Sensor', value) def set_Units(self, value): """ Set the value of the Units input for this Choreo. ((optional, string) Specify the units to be used when displaying results. Options include, metric, or imperial.) """ super(GetBicyclingDirectionsInputSet, self)._set_input('Units', value) def set_Waypoints(self, value): """ Set the value of the Waypoints input for this Choreo. ((optional, string) Specify route waypoints, either by address, or latitude/longitude coordinates.) """ super(GetBicyclingDirectionsInputSet, self)._set_input('Waypoints', value) class GetBicyclingDirectionsResultSet(ResultSet): """ A ResultSet with methods tailored to the values returned by the GetBicyclingDirections Choreo. The ResultSet object is used to retrieve the results of a Choreo execution. """ def getJSONFromString(self, str): return json.loads(str) def get_Response(self): """ Retrieve the value for the "Response" output from this Choreo execution. ((json) The response from Google.) """ return self._output.get('Response', None) class GetBicyclingDirectionsChoreographyExecution(ChoreographyExecution): def _make_result_set(self, response, path): return GetBicyclingDirectionsResultSet(response, path)

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arduinoleo88@gmail.com

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/11_OOP/smartwatch.py

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class UsefulStuff: def __init__(self, name): print(name, 'is used to make life easier!') class Watch(UsefulStuff): def __init__(self, watch_name): print(watch_name, "is small and convenient") super().__init__(watch_name) class Phone(UsefulStuff): def __init__(self, phone_name): print(phone_name, "can make a call") super().__init__(phone_name) class SmartWatch(Watch, Phone): def __init__(self): print('Smartwatch is great!') super().__init__('Smartwatch') sw = SmartWatch()

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marta.kedzior@wp.pl

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/Code/Untested SarsaZero and SarsaLambda/ARL_package/CodeFramework/PlotAgent.py

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import numpy as np from numpy.linalg import norm import matplotlib.pyplot as plt from copy import deepcopy class PlotAgent(object): def __init__(self, dimension): """ Diagramm: Horizontal: Episoid Number Vertical: 1. Step Number 2. Total Reward 3. If reach center 4. Q function difference every 100 episoid Graph: Policy after 100 Episoid """ self.dimension = dimension def get_qFun_diff(self, qFuncHistory): qFunDiff = [] qFuncPre = [] qFuncCurrent = [] for i in qFuncHistory: qFuncPre = qFuncCurrent qFuncCurrent = i if len(list(qFuncPre)) == 0: continue temp = 0 for x, y in zip(qFuncPre.values(), qFuncCurrent.values()): temp += (np.array(x.values(), dtype=float) - np.array(y.values(), dtype=float)) ** 2 qFunDiff.append(np.sqrt(sum(temp))) qFuncPre = qFuncCurrent return qFunDiff def plot_policy_graph(self, policyHistory): for singlePolicy in reversed(policyHistory): soaList = [] for state in singlePolicy.keys(): if state == (0, 0): continue action = singlePolicy[state] x, y = state m, n = action soaList.append([x, y, m, n]) X,Y,U,V = zip(*soaList) plt.figure() ax = plt.gca() ax.quiver(X,Y,U,V,angles='xy',scale_units='xy',scale=1) ax.set_xlim([-list(self.dimension)[0] // 2, list(self.dimension)[0] // 2 + 1]) ax.set_ylim([-list(self.dimension)[1] // 2, list(self.dimension)[1] // 2 + 1]) break plt.draw() plt.show() def plot_diag(self, diagInfo, qFuncDiff): stepNumTrue = [] totalReward = [] ifReachCenter = [] for i in diagInfo: stepNumTrue.append(list(i)[0]) totalReward.append(list(i)[1]) ifReachCenter.append(list(i)[2]) stepNumFalse = deepcopy(stepNumTrue) for i in xrange(len(ifReachCenter)): if ifReachCenter[i]: stepNumFalse[i] = 0 else: stepNumTrue[i] = 0 length = np.arange(1, len(diagInfo) + 1) plt.subplot(3, 1, 1) plt.plot(length, stepNumFalse, 'r') plt.plot(length, stepNumTrue, 'b') plt.title('How many steps does learning algorithm need to reach Terminal or failed') plt.ylabel('Step Number') # plt.subplot(4, 1, 2) # plt.plot(length, ifReachCenter, 'r.-') # plt.title('If the agent reach the goal state') # plt.ylabel('1 for Reaching') # plt.xlabel('Episoid') # # ifReachCenter = np.array(ifReachCenter, dtype=bool) * 1 # # ifReachCenter = np.array(ifReachCenter, dtype=int) plt.subplot(3, 1, 2) plt.plot(length, totalReward, 'k') plt.title('How much is the total reward in one episoid') plt.ylabel('Reward') length = np.arange(1, len(qFuncDiff) + 1) plt.subplot(3, 1, 3) plt.plot(length, qFuncDiff, 'g-') plt.title('How big is the difference of Q function in every 10 episoids') plt.ylabel('Difference') plt.show() def plot(self, diagInfo, qFuncHistory, policyHistory): qFuncDiff = self.get_qFun_diff(qFuncHistory) self.plot_diag(diagInfo, qFuncDiff) self.plot_policy_graph(policyHistory) if __name__ == '__main__': import numpy as np import matplotlib.pyplot as plt soa =np.array( [ [0,0,3,2], [0,0,1,1],[0,0,9,9]]) X,Y,U,V = zip(*soa) plt.figure() ax = plt.gca() ax.quiver(X,Y,U,V,angles='xy',scale_units='xy',scale=1) ax.set_xlim([-1,10]) ax.set_ylim([-1,10]) plt.draw() plt.show()

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# Generated by Django 3.0.8 on 2020-09-09 11:15 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('FirstApp', '0001_initial'), ] operations = [ migrations.AlterField( model_name='emailuser', name='email', field=models.EmailField(max_length=50, unique=True), ), migrations.AlterField( model_name='emailuser', name='username', field=models.CharField(max_length=50, unique=True), ), ]

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import demistomock as demisto # noqa: F401 from CommonServerPython import * # noqa: F401 import gzip import re import shutil from os.path import isfile ESCAPE_CHARACTERS = r'[/\<>"|?*]' def escape_illegal_characters_in_file_name(file_name: str) -> str: if file_name: file_name = re.sub(ESCAPE_CHARACTERS, '-', file_name) file_name = re.sub(r'-+', '-', file_name) # prevent more than one consecutive dash in the file name return file_name def gzip_file(fileEntryID: str): entry_ids = argToList(fileEntryID) file_names = list() for entry_id in entry_ids: res = demisto.executeCommand('getFilePath', {'id': entry_id}) if is_error(res): raise DemistoException( 'Failed to get the file path for entry: ' + entry_id + ' the error message was ' + get_error(res)) filePath = res[0]['Contents']['path'] fileCurrentName = escape_illegal_characters_in_file_name(res[0]['Contents']['name']) if not isfile(filePath): # in case that the user will send a directory raise DemistoException(entry_id + ' is not a file. Please recheck your input.') # Handling duplicate names. if fileCurrentName in file_names: name, ext = os.path.splitext(fileCurrentName) i = 0 while fileCurrentName in file_names: i += 1 fileCurrentName = f'{name} {i}{ext}' # copying the file to current location shutil.copy(filePath, fileCurrentName) file_names.append(fileCurrentName) unzippedgzFileNames = [] for file_name in file_names: with gzip.open(file_name, 'r') as f_in, open(file_name[:-3], 'wb') as f_out: shutil.copyfileobj(f_in, f_out) with open(file_name[:-3], 'rb') as f: file_data = f.read() demisto.results(fileResult(file_name[:-3], file_data)) unzippedgzFileNames.append(file_name[:-3]) readable_output = tableToMarkdown(name="Unzipped GZ Files", t=[{'Unzipped GZ File Names': unzippedgzFileNames, 'Original File Names': file_names}], removeNull=True) return CommandResults( outputs_prefix="UnzipGZFile.UnzippedGZFiles", outputs_key_field="UnzippedGZFiles", outputs=unzippedgzFileNames, readable_output=readable_output, raw_response={'UnzippedGZFiles': unzippedgzFileNames}, ) def main(): try: args = demisto.args() entryID = args.get('entryID') if not entryID: raise DemistoException('You must set an entryID when using the unzip GZ script') result = gzip_file(fileEntryID=entryID) return_results(result) except Exception as exc: return_error(exc) if __name__ in ('__main__', '__builtin__', 'builtins'): main()

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import os import dataset class Database: """The wrapper class for database operations. """ def __init__(self, connection_uri=None): self.connection = dataset.connect( connection_uri or os.getenv("MIKE_DB")) @property def subscriptions(self): """Returns the dataset table object.""" return self.connection["subscriptions"] def subscribe(self, player_account, discord_account, discord_backend_id): """Subscribe to a player account from a discord account. :param player_account: Account name in STEEM blockchain :param discord_account: Discord ID. (foo#N) :return: None """ self.subscriptions.insert(dict( player_account=player_account, discord_account=discord_account, discord_backend_id=discord_backend_id, )) def unsubscribe(self, player_account, discord_account): """Unsubscribe from a discord account to a discord account. :param player_account: Account name in STEEM blockchain :param discord_account: Discord ID. (foo#N) :return: None """ self.subscriptions.delete( player_account=player_account, discord_account=discord_account, ) def subscription_exists(self, player_account, discord_account): """Check if a subscription is already exists. :param player_account: Account name in STEEM blockchain :param discord_account: Discord ID. (foo#N) :return (boolean): True or False based on the existence """ if self.subscriptions.find_one( player_account=player_account, discord_account=discord_account): return True return False def active_subscription_count(self, discord_account): """Return the active subscription count for a discord account. :param discord_account: Discord ID. (foo#N) :return (boolean): True or False based on the existence """ return len(list( self.subscriptions.find(discord_account=discord_account))) def all_subscriptions(self): """Returns all subscriptions globally.""" return list(self.subscriptions.find()) def subscriptions_by_user(self, discord_account): """Return all subscriptions of a particular user. :param discord_account: Discord ID. (foo#N) """ return list(self.subscriptions.find(discord_account=discord_account)) def subscriptions_by_player_account(self, player_account): """Return all subscriptions of a player account. :param player_account: Account name """ return list(self.subscriptions.find(player_account=player_account)) def registered_targets(self): targets = list(self.subscriptions.find()) return [t["player_account"] for t in targets]

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mail@emreyilmaz.me

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/education/timetable/report/__init__.py

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adahra/addons

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c5a5678379649ccdf57a9d55b09b30436428b430

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2022-06-17T21:22:22.306787

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# -*- encoding: utf-8 -*- ############################################################################## # # OpenERP, Open Source Management Solution # Copyright (C) 2004-2009 Tiny SPRL (<http://tiny.be>). # Copyright (C) 2011-2012 Serpent Consulting Services (<http://www.serpentcs.com>) # Copyright (C) 2013-2014 Serpent Consulting Services (<http://www.serpentcs.com>) # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Affero General Public License as # published by the Free Software Foundation, either version 3 of the # License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Affero General Public License for more details. # # You should have received a copy of the GNU Affero General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # ############################################################################## import timetable_info # vim:expandtab:smartindent:tabstop=4:softtabstop=4:shiftwidth=4:

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"""Platform for binary sensor integration.""" from __future__ import annotations from smarttub import SpaError, SpaReminder import voluptuous as vol from homeassistant.components.binary_sensor import ( BinarySensorDeviceClass, BinarySensorEntity, ) from homeassistant.helpers import entity_platform from .const import ATTR_ERRORS, ATTR_REMINDERS, DOMAIN, SMARTTUB_CONTROLLER from .entity import SmartTubEntity, SmartTubSensorBase # whether the reminder has been snoozed (bool) ATTR_REMINDER_SNOOZED = "snoozed" ATTR_ERROR_CODE = "error_code" ATTR_ERROR_TITLE = "error_title" ATTR_ERROR_DESCRIPTION = "error_description" ATTR_ERROR_TYPE = "error_type" ATTR_CREATED_AT = "created_at" ATTR_UPDATED_AT = "updated_at" # how many days to snooze the reminder for ATTR_REMINDER_DAYS = "days" RESET_REMINDER_SCHEMA = { vol.Required(ATTR_REMINDER_DAYS): vol.All( vol.Coerce(int), vol.Range(min=30, max=365) ) } SNOOZE_REMINDER_SCHEMA = { vol.Required(ATTR_REMINDER_DAYS): vol.All( vol.Coerce(int), vol.Range(min=10, max=120) ) } async def async_setup_entry(hass, entry, async_add_entities): """Set up binary sensor entities for the binary sensors in the tub.""" controller = hass.data[DOMAIN][entry.entry_id][SMARTTUB_CONTROLLER] entities = [] for spa in controller.spas: entities.append(SmartTubOnline(controller.coordinator, spa)) entities.append(SmartTubError(controller.coordinator, spa)) entities.extend( SmartTubReminder(controller.coordinator, spa, reminder) for reminder in controller.coordinator.data[spa.id][ATTR_REMINDERS].values() ) async_add_entities(entities) platform = entity_platform.current_platform.get() platform.async_register_entity_service( "snooze_reminder", SNOOZE_REMINDER_SCHEMA, "async_snooze", ) platform.async_register_entity_service( "reset_reminder", RESET_REMINDER_SCHEMA, "async_reset", ) class SmartTubOnline(SmartTubSensorBase, BinarySensorEntity): """A binary sensor indicating whether the spa is currently online (connected to the cloud).""" _attr_device_class = BinarySensorDeviceClass.CONNECTIVITY def __init__(self, coordinator, spa): """Initialize the entity.""" super().__init__(coordinator, spa, "Online", "online") @property def entity_registry_enabled_default(self) -> bool: """Return if the entity should be enabled when first added to the entity registry. This seems to be very noisy and not generally useful, so disable by default. """ return False @property def is_on(self) -> bool: """Return true if the binary sensor is on.""" return self._state is True class SmartTubReminder(SmartTubEntity, BinarySensorEntity): """Reminders for maintenance actions.""" _attr_device_class = BinarySensorDeviceClass.PROBLEM def __init__(self, coordinator, spa, reminder): """Initialize the entity.""" super().__init__( coordinator, spa, f"{reminder.name.title()} Reminder", ) self.reminder_id = reminder.id @property def unique_id(self): """Return a unique id for this sensor.""" return f"{self.spa.id}-reminder-{self.reminder_id}" @property def reminder(self) -> SpaReminder: """Return the underlying SpaReminder object for this entity.""" return self.coordinator.data[self.spa.id][ATTR_REMINDERS][self.reminder_id] @property def is_on(self) -> bool: """Return whether the specified maintenance action needs to be taken.""" return self.reminder.remaining_days == 0 @property def extra_state_attributes(self): """Return the state attributes.""" return { ATTR_REMINDER_SNOOZED: self.reminder.snoozed, ATTR_REMINDER_DAYS: self.reminder.remaining_days, } async def async_snooze(self, days): """Snooze this reminder for the specified number of days.""" await self.reminder.snooze(days) await self.coordinator.async_request_refresh() async def async_reset(self, days): """Dismiss this reminder, and reset it to the specified number of days.""" await self.reminder.reset(days) await self.coordinator.async_request_refresh() class SmartTubError(SmartTubEntity, BinarySensorEntity): """Indicates whether an error code is present. There may be 0 or more errors. If there are >0, we show the first one. """ _attr_device_class = BinarySensorDeviceClass.PROBLEM def __init__(self, coordinator, spa): """Initialize the entity.""" super().__init__( coordinator, spa, "Error", ) @property def error(self) -> SpaError | None: """Return the underlying SpaError object for this entity.""" errors = self.coordinator.data[self.spa.id][ATTR_ERRORS] if len(errors) == 0: return None return errors[0] @property def is_on(self) -> bool: """Return true if an error is signaled.""" return self.error is not None @property def extra_state_attributes(self): """Return the state attributes.""" if (error := self.error) is None: return {} return { ATTR_ERROR_CODE: error.code, ATTR_ERROR_TITLE: error.title, ATTR_ERROR_DESCRIPTION: error.description, ATTR_ERROR_TYPE: error.error_type, ATTR_CREATED_AT: error.created_at.isoformat(), ATTR_UPDATED_AT: error.updated_at.isoformat(), }

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import sys N = int(sys.stdin.readline().strip()) S = [] for _ in range(N): s_i = sys.stdin.readline().strip() S.append(s_i) # left bracket - right bracketを高さとした、最小の高さと最終的な高さの座標列 # ex) # ")": (-1, -1) # "(": (1, 1) # "()": (1, 0) # ")()(": (-1, 0) # "))))(((((: (-4, 1) plus_seqs = [] minus_seqs = [] for s_i in S: h = 0 min_h = float("inf") for bracket in s_i: if bracket == "(": h += 1 else: h -= 1 min_h = min(min_h, h) if h >= 0: plus_seqs.append((min_h, h)) else: # minus_seqs.append((-1 * min_h, -1 * h)) minus_seqs.append((min_h - h, -1 * h)) # print(plus_seqs) # print(minus_seqs) hight = 0 for (min_h, h) in sorted(plus_seqs, reverse=True): if hight + min_h < 0: print("No") sys.exit() hight += h hight2 = 0 for (min_h, h) in sorted(minus_seqs, reverse=True): if hight2 + min_h < 0: print("No") sys.exit() hight2 += h # print(hight, hight2) if hight == hight2: print("Yes") else: print("No")

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/Interview_Preperation_Kit/WarmUpChallenges/CountingValleys.py

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no_license

ktyagi12/HackerRank

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2020-09-06T19:33:27.422287

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#Problem available at: https://www.hackerrank.com/challenges/counting-valleys/problem?h_l=interview&playlist_slugs%5B%5D=interview-preparation-kit&playlist_slugs%5B%5D=warmup #!/bin/python3 import math import os import random import re import sys # Complete the countingValleys function below. def countingValleys(n, s): sea_level = 0 valley = 0 step = 0 while(step<n): if(s[step] == 'U'): sea_level= sea_level+1 if(s[step] == 'D'): sea_level = sea_level -1 if(sea_level==0 and s[step]=='U'): valley = valley+1 step+= 1 return valley if __name__ == '__main__': fptr = open(os.environ['OUTPUT_PATH'], 'w') n = int(input()) s = input() result = countingValleys(n, s) fptr.write(str(result) + '\n') fptr.close()

[ "karishmatyagi12@gmail.com" ]

karishmatyagi12@gmail.com

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/aula05/exercicio 8.py

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[]

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Elvis-Lopes/Ci-ncias-de-Dados-Uni9

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2021-02-11T12:54:56.248564

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listaNumerica = [] n = float(input('Digite um numero: ')) listaNumerica.append(n) while n != 0: n = float(input('Digite um numero: ')) listaNumerica.append(n) print(listaNumerica)

[ "elvislopes1996@hotmail.com" ]

elvislopes1996@hotmail.com

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/travello/views.py

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[]

no_license

tamanna090903/travello

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2020-06-24T17:32:37.622240

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from django.shortcuts import render from .models import Destination # Create your views here. def index(request): dests = Destination.objects.all() return render(request ,"index.html", {'dests': dests})

[ "hizbul.ku@gmail.com" ]

hizbul.ku@gmail.com

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/gevent/thread.py

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[ "MIT" ]

permissive

easel/gevent

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"""Implementation of the standard :mod:`thread` module that spawns greenlets. .. note:: This module is a helper for :mod:`gevent.monkey` and is not intended to be used directly. For spawning greenlets in your applications, prefer :class:`Greenlet` class. """ import sys __implements__ = ['allocate_lock', 'get_ident', 'exit', 'LockType', 'stack_size', 'start_new_thread', '_local'] __imports__ = ['error'] if sys.version_info[0] <= 2: __target__ = 'thread' else: __target__ = '_thread' __thread__ = __import__(__target__) error = __thread__.error from gevent.hub import getcurrent, GreenletExit from gevent.greenlet import Greenlet from gevent.lock import Semaphore as LockType from gevent.local import local as _local def get_ident(gr=None): if gr is None: return id(getcurrent()) else: return id(gr) def start_new_thread(function, args=(), kwargs={}): greenlet = Greenlet.spawn(function, *args, **kwargs) return get_ident(greenlet) def allocate_lock(): return LockType(1) def exit(): raise GreenletExit if hasattr(__thread__, 'stack_size'): _original_stack_size = __thread__.stack_size def stack_size(size=None): if size is None: return _original_stack_size() if size > _original_stack_size(): return _original_stack_size(size) else: pass # not going to decrease stack_size, because otherwise other greenlets in this thread will suffer else: __implements__.remove('stack_size') __all__ = __implements__ + __imports__ __all__.remove('_local') # XXX interrupt_main

[ "denis.bilenko@gmail.com" ]

denis.bilenko@gmail.com

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/Hash table/MaxNumberofK-SumPairs.py

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[]

no_license

prashant97sikarwar/leetcode

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2023-08-23T05:06:23.181869

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#Problem Link:- https://leetcode.com/problems/max-number-of-k-sum-pairs/ """You are given an integer array nums and an integer k. In one operation, you can pick two numbers from the array whose sum equals k and remove them from the array.Return the maximum number of operations you can perform on the array.""" class Solution(object): def maxOperations(self, nums, k): d = dict() res = 0 for i in range(len(nums)): if k-nums[i] not in d: if nums[i] not in d: d[nums[i]] = 1 else: d[nums[i]] += 1 else: res += 1 d[k-nums[i]] -= 1 if d[k-nums[i]] == 0: del d[k-nums[i]] return res

[ "prashant97sikarwar@gmail.com" ]

prashant97sikarwar@gmail.com

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/Proper/proper/examples/simple_prescription.py

cf7b181641c3e6576ad699572b6fa0f84fe0d83c

[ "MIT" ]

permissive

RupertDodkins/MEDIS

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refs/heads/master

2021-07-05T20:06:44.162517

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# Copyright 2016, 2017 California Institute of Technology # Users must agree to abide by the restrictions listed in the # file "LegalStuff.txt" in the PROPER library directory. # # PROPER developed at Jet Propulsion Laboratory/California Inst. Technology # Original IDL version by John Krist # Python translation by Navtej Saini, with Luis Marchen and Nikta Amiri import proper def simple_prescription(wavelength, gridsize): # Define entrance aperture diameter and other quantities diam = 1.0 focal_ratio = 15.0 focal_length = diam * focal_ratio beam_ratio = 0.5 # Define the wavefront wfo = proper.prop_begin(diam, wavelength, gridsize, beam_ratio) # Define a circular aperture proper.prop_circular_aperture(wfo, diam/2) # Define entrance proper.prop_define_entrance(wfo) # Define a lens proper.prop_lens(wfo, focal_length) # Propagate the wavefront proper.prop_propagate(wfo, focal_length) # End (wfo, sampling) = proper.prop_end(wfo) return (wfo, sampling)

[ "rupertdodkins@gmail.com" ]

rupertdodkins@gmail.com

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/xlsxwriter/test/comparison/test_chart_errorbars10.py

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[ "BSD-2-Clause-Views", "BSD-3-Clause", "MIT" ]

permissive

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refs/heads/master

2021-09-07T14:00:40.759486

2018-02-23T23:21:13

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############################################################################### # # Tests for XlsxWriter. # # Copyright (c), 2013-2017, John McNamara, jmcnamara@cpan.org # from ..excel_comparsion_test import ExcelComparisonTest from ...workbook import Workbook class TestCompareXLSXFiles(ExcelComparisonTest): """ Test file created by XlsxWriter against a file created by Excel. """ def setUp(self): self.maxDiff = None filename = 'chart_errorbars10.xlsx' test_dir = 'xlsxwriter/test/comparison/' self.got_filename = test_dir + '_test_' + filename self.exp_filename = test_dir + 'xlsx_files/' + filename self.ignore_files = [] self.ignore_elements = {} def test_create_file(self): """Test the creation of an XlsxWriter file with error bars.""" workbook = Workbook(self.got_filename) worksheet = workbook.add_worksheet() chart = workbook.add_chart({'type': 'line'}) chart.axis_ids = [69198976, 69200896] data = [ [1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [3, 6, 9, 12, 15], ] worksheet.write_column('A1', data[0]) worksheet.write_column('B1', data[1]) worksheet.write_column('C1', data[2]) chart.add_series({ 'categories': '=Sheet1!$A$1:$A$5', 'values': '=Sheet1!$B$1:$B$5', 'y_error_bars': { 'type': 'custom', 'plus_values': '=Sheet1!$A$1', 'minus_values': '=Sheet1!$B$1:$B$3', 'plus_data': [1], 'minus_data': [2, 4, 6], }, }) chart.add_series({ 'categories': '=Sheet1!$A$1:$A$5', 'values': '=Sheet1!$C$1:$C$5', }) worksheet.insert_chart('E9', chart) workbook.close() self.assertExcelEqual()

[ "mwrb7d@mst.edu" ]

mwrb7d@mst.edu

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/getdeal/apps/profiles/permissions.py

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[]

no_license

PankeshGupta/getdeal

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2020-03-18T14:15:37.874570

2015-02-23T00:12:58

2015-02-23T00:20:11

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# -*- coding: utf-8 -*- """ Created on Sep 22, 2013 """ from rest_framework import permissions class IsUserOwnerOrReadOnly(permissions.BasePermission): """ Custom permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): # Read permissions are allowed to any request if request.method in permissions.SAFE_METHODS: return True # Write permissions are only allowed to the owner of the profile return obj == request.user class IsProfileOwnerOrReadOnly(permissions.BasePermission): """ Custom permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): # Read permissions are allowed to any request if request.method in permissions.SAFE_METHODS: return True # Write permissions are only allowed to the owner of the profile return obj.user == request.user

[ "mouradmourafiq@gmail.com" ]

mouradmourafiq@gmail.com

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/karbor-1.3.0/karbor/services/protection/protectable_plugins/share.py

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[ "Apache-2.0" ]

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2021-03-22T16:07:19.561504

2020-03-15T01:31:10

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Apache-2.0

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# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import six from karbor.common import constants from karbor import exception from karbor import resource from karbor.services.protection.client_factory import ClientFactory from karbor.services.protection import protectable_plugin from oslo_log import log as logging LOG = logging.getLogger(__name__) INVALID_SHARE_STATUS = ['deleting', 'deleted', 'error', 'error_deleting', 'manage_error', 'unmanage_error', 'extending_error', 'shrinking_error', 'reverting_error'] class ShareProtectablePlugin(protectable_plugin.ProtectablePlugin): """Manila share protectable plugin""" _SUPPORT_RESOURCE_TYPE = constants.SHARE_RESOURCE_TYPE def _client(self, context): self._client_instance = ClientFactory.create_client( "manila", context) return self._client_instance def get_resource_type(self): return self._SUPPORT_RESOURCE_TYPE def get_parent_resource_types(self): return (constants.PROJECT_RESOURCE_TYPE, ) def list_resources(self, context, parameters=None): try: shares = self._client(context).shares.list(detailed=True) except Exception as e: LOG.exception("List all summary shares from manila failed.") raise exception.ListProtectableResourceFailed( type=self._SUPPORT_RESOURCE_TYPE, reason=six.text_type(e)) else: return [resource.Resource(type=self._SUPPORT_RESOURCE_TYPE, id=share.id, name=share.name) for share in shares if share.status not in INVALID_SHARE_STATUS] def show_resource(self, context, resource_id, parameters=None): try: share = self._client(context).shares.get(resource_id) except Exception as e: LOG.exception("Show a summary share from manila failed.") raise exception.ProtectableResourceNotFound( id=resource_id, type=self._SUPPORT_RESOURCE_TYPE, reason=six.text_type(e)) else: if share.status in INVALID_SHARE_STATUS: raise exception.ProtectableResourceInvalidStatus( id=resource_id, type=self._SUPPORT_RESOURCE_TYPE, status=share.status) return resource.Resource(type=self._SUPPORT_RESOURCE_TYPE, id=share.id, name=share.name) def get_dependent_resources(self, context, parent_resource): try: shares = self._client(context).shares.list() except Exception as e: LOG.exception("List all shares from manila failed.") raise exception.ListProtectableResourceFailed( type=self._SUPPORT_RESOURCE_TYPE, reason=six.text_type(e)) else: return [resource.Resource(type=self._SUPPORT_RESOURCE_TYPE, id=share.id, name=share.name) for share in shares if share.project_id == parent_resource.id and share.status not in INVALID_SHARE_STATUS]

[ "Wayne Gong@minbgong-winvm.cisco.com" ]

Wayne Gong@minbgong-winvm.cisco.com

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/2021_하반기 코테연습/leet_451.py

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[]

no_license

holim0/Algo_Study

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from collections import defaultdict class Solution: def frequencySort(self, s: str) -> str: fre_cnt = defaultdict(int) for cur in s: fre_cnt[cur]+=1 sorted_fre = sorted(fre_cnt.items(), key=lambda x: -x[1]) answer ="" for cur in sorted_fre: letter, cnt = cur for _ in range(cnt): answer+=letter return answer

[ "holim1226@gmail.com" ]

holim1226@gmail.com

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/bigmler/retrain/dispatcher.py

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refs/heads/master

2021-03-01T02:08:29.730986

2020-01-25T10:43:01

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# -*- coding: utf-8 -*- # # Copyright 2017-2020 BigML # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """BigMLer retrain main processing Functions to retrain a modeling resource """ from __future__ import absolute_import import sys import os import shutil import bigmler.processing.args as a import bigmler.utils as u from bigmler.defaults import DEFAULTS_FILE from bigmler.retrain.retrain import retrain_model from bigmler.dispatcher import (SESSIONS_LOG, clear_log_files) from bigmler.command import get_context COMMAND_LOG = u".bigmler_retrain" DIRS_LOG = u".bigmler_retrain_dir_stack" LOG_FILES = [COMMAND_LOG, DIRS_LOG, u.NEW_DIRS_LOG] DEFAULT_OUTPUT = "retrain_script" SETTINGS = { "command_log": COMMAND_LOG, "sessions_log": SESSIONS_LOG, "dirs_log": DIRS_LOG, "default_output": DEFAULT_OUTPUT, "defaults_file": DEFAULTS_FILE} def check_compulsory_options(flags, args): """Checks whether the id or a unique tag are provided """ return args.resource_id is not None or \ len([flag for flag in flags if flag.endswith("-tag")]) > 0 def retrain_dispatcher(args=sys.argv[1:]): """Main processing of the parsed options for BigMLer retrain """ # If --clear-logs the log files are cleared if "--clear-logs" in args: clear_log_files(LOG_FILES) # parses the command line to get the context args and the log files to use command_args, command, api, session_file, resume = get_context(args, SETTINGS) # --id or --model-tag, --ensemble-tag, etc. is compulsory if check_compulsory_options(command.flags, command_args): retrain_model(command_args, api, command, session_file=session_file) u.log_message("_" * 80 + "\n", log_file=session_file) else: sys.exit("You must provide the ID of the resource to be" " retrained in the --id option or a unique tag" " to retrieve such ID." " Type bigmler retrain --help\n" " to see all the available options.")

[ "merce@bigml.com" ]

merce@bigml.com

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/python/ray/tests/aws/test_autoscaler_aws.py

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[ "Apache-2.0", "MIT" ]

permissive

mehrdadn/ray

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refs/heads/master

2020-09-03T15:33:35.578248

2020-07-31T21:33:27

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import pytest import ray.tests.aws.utils.stubs as stubs import ray.tests.aws.utils.helpers as helpers from ray.tests.aws.utils.constants import AUX_SUBNET, DEFAULT_SUBNET, \ DEFAULT_SG_AUX_SUBNET, DEFAULT_SG, DEFAULT_SG_DUAL_GROUP_RULES, \ DEFAULT_SG_WITH_RULES_AUX_SUBNET, DEFAULT_SG_WITH_RULES, AUX_SG def test_create_sg_different_vpc_same_rules(iam_client_stub, ec2_client_stub): # use default stubs to skip ahead to security group configuration stubs.skip_to_configure_sg(ec2_client_stub, iam_client_stub) # given head and worker nodes with custom subnets defined... # expect to first describe the worker subnet ID stubs.describe_subnets_echo(ec2_client_stub, AUX_SUBNET) # expect to second describe the head subnet ID stubs.describe_subnets_echo(ec2_client_stub, DEFAULT_SUBNET) # given no existing security groups within the VPC... stubs.describe_no_security_groups(ec2_client_stub) # expect to first create a security group on the worker node VPC stubs.create_sg_echo(ec2_client_stub, DEFAULT_SG_AUX_SUBNET) # expect new worker security group details to be retrieved after creation stubs.describe_sgs_on_vpc( ec2_client_stub, [AUX_SUBNET["VpcId"]], [DEFAULT_SG_AUX_SUBNET], ) # expect to second create a security group on the head node VPC stubs.create_sg_echo(ec2_client_stub, DEFAULT_SG) # expect new head security group details to be retrieved after creation stubs.describe_sgs_on_vpc( ec2_client_stub, [DEFAULT_SUBNET["VpcId"]], [DEFAULT_SG], ) # given no existing default head security group inbound rules... # expect to authorize all default head inbound rules stubs.authorize_sg_ingress( ec2_client_stub, DEFAULT_SG_DUAL_GROUP_RULES, ) # given no existing default worker security group inbound rules... # expect to authorize all default worker inbound rules stubs.authorize_sg_ingress( ec2_client_stub, DEFAULT_SG_WITH_RULES_AUX_SUBNET, ) # given the prior modification to the head security group... # expect the next read of a head security group property to reload it stubs.describe_sg_echo(ec2_client_stub, DEFAULT_SG_WITH_RULES) # given the prior modification to the worker security group... # expect the next read of a worker security group property to reload it stubs.describe_sg_echo(ec2_client_stub, DEFAULT_SG_WITH_RULES_AUX_SUBNET) # given our mocks and an example config file as input... # expect the config to be loaded, validated, and bootstrapped successfully config = helpers.bootstrap_aws_example_config_file("example-subnets.yaml") # expect the bootstrapped config to show different head and worker security # groups residing on different subnets assert config["head_node"]["SecurityGroupIds"] == [DEFAULT_SG["GroupId"]] assert config["head_node"]["SubnetIds"] == [DEFAULT_SUBNET["SubnetId"]] assert config["worker_nodes"]["SecurityGroupIds"] == [AUX_SG["GroupId"]] assert config["worker_nodes"]["SubnetIds"] == [AUX_SUBNET["SubnetId"]] # expect no pending responses left in IAM or EC2 client stub queues iam_client_stub.assert_no_pending_responses() ec2_client_stub.assert_no_pending_responses() if __name__ == "__main__": import sys sys.exit(pytest.main(["-v", __file__]))

[ "noreply@github.com" ]

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# -*- coding: utf-8 -*- #COMECE AQUI ABAIXO investimento = float (input('Digite o valor do investimento inicial: ')) taxa = float (input('Digite o valor da taxa anual (em decimais): ')) renda = (investimento+(investimento*taxa)) for i in range (1,10+1,1): print('%.2f'%renda) investimento=renda

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import flask import scipy.misc import sys import uuid from flask import Flask, request app = Flask(__name__) import re import os import json from skimage import io import numpy as np from io import BytesIO import cv2 import PyOpenPose as OP from concurrent.futures import ThreadPoolExecutor, wait def init_pose(): op = OP.OpenPose((656, 368), (368, 368), (1280, 720), "COCO", "/home/sean/openpose/models/", 0, False, OP.OpenPose.ScaleMode.ZeroToOne, True, True) return op # GPU conflict somehow goes away when using threads pose_executor = ThreadPoolExecutor(1) future = pose_executor.submit(init_pose) wait([future]) op = future.result() import detection_nn from i3dnn import I3DNN i3d = I3DNN("2") datafiles_root = "../main_server/sumica/datafiles" def format_image(image): if len(image.shape) == 2: # grayscale -> 3 channels image = np.expand_dims(image, 2) image = np.repeat(image, 3, 2) elif image.shape[2] > 3: # 4-channel -> 3-channels image = image[:, :, :3] elif image.shape[2] == 1: # single-channel -> 3-channelS image = np.repeat(image, 3, 2) return image clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8)) def preprocess(imgmat): img_yuv = cv2.cvtColor(imgmat, cv2.COLOR_RGB2YUV) img_yuv[:, :, 0] = clahe.apply(img_yuv[:, :, 0]) img_output = cv2.cvtColor(img_yuv, cv2.COLOR_YUV2RGB) return img_output def nms(dets, iou_threshold=0.5): sorted_list = sorted(dets, key=lambda k: k['confidence']) filtered_list = [] for det in dets: skip = False for b in filtered_list: if b["label"] == det["label"] and iou(b["box"], det["box"]) > iou_threshold: skip = True break if not skip: filtered_list.append(det) return filtered_list def iou(boxA, boxB): xA = max(boxA[0], boxB[0]) yA = max(boxA[1], boxB[1]) xB = min(boxA[2], boxB[2]) yB = min(boxA[3], boxB[3]) # compute the area of intersection rectangle interArea = (xB - xA + 1) * (yB - yA + 1) # compute the area of both the prediction and ground-truth # rectangles boxAArea = (boxA[2] - boxA[0] + 1) * (boxA[3] - boxA[1] + 1) boxBArea = (boxB[2] - boxB[0] + 1) * (boxB[3] - boxB[1] + 1) # compute the intersection over union by taking the intersection # area and dividing it by the sum of prediction + ground-truth # areas - the interesection area iou = interArea / float(boxAArea + boxBArea - interArea) # return the intersection over union value return iou def pose_estimation(img): op.detectPose(img) op.detectFace(img) op.detectHands(img) body = op.getKeypoints(op.KeypointType.POSE)[0] hand = op.getKeypoints(op.KeypointType.HAND)[0] face = op.getKeypoints(op.KeypointType.FACE)[0] new_data = {'body': [], 'hand': [], 'face': []} if body is not None: new_data['body'] = body.tolist() if hand is not None: new_data['hand'] = hand.tolist() if face is not None: new_data['face'] = face.tolist() return new_data def object_detection(imgmat, query): # default settings conf_thresh = 0.3 get_img_feats = False get_obj_feats = False get_obj_dets = True if "detection_threshold" in query: conf_thresh = float(query["detection_threshold"]) if "get_image_features" in query: get_img_feats = query["get_image_features"] == "true" if "get_object_detections" in query: get_obj_dets = query["get_object_detections"] == "true" if "get_object_features" in query: get_obj_feats = query["get_object_features"] == "true" only_img_feats = get_img_feats and not get_obj_feats and not get_obj_dets # if only_img_feats, RCNN will only do region proposal step out = detection_nn.detect(imgmat, conf_thresh, only_img_feats) out_data = {} img_feats, obj_dets, obj_feats = out if get_img_feats: fn = str(uuid.uuid4()) + ".npy" feats = np.max(img_feats, axis=(0, 1)) # collapse feature maps into vector np.save(datafiles_root + "/image_features/" + fn, feats) out_data["image_features_filename"] = fn if get_obj_feats: fn = str(uuid.uuid4()) + ".npy" obj_feats = np.array(obj_feats) np.save(datafiles_root + "/object_features/" + fn, obj_feats) out_data["object_features_filename"] = fn if get_obj_dets: if "nms_threshold" in query: out_data["detections"] = nms(obj_dets, float(query["nms_threshold"])) else: out_data["detections"] = obj_dets return out_data def action_recognition(whole_img, data): for i in range(len(data["detections"])): if data["detections"][i]["label"] == "person": box = data["detections"][i]["box"] im_w, im_h = whole_img.shape[1], whole_img.shape[0] box_w, box_h = (box[2] - box[0]), (box[3] - box[1]) # expand cx, cy = (box[0] + box[2]) // 2, (box[1] + box[3]) // 2 longer_side = max(box_w, box_h) * 2.0 constrained_side = min(min(im_w, im_h), longer_side) a = constrained_side / 2.0 x1, y1, x2, y2 = cx - a, cy - a, cx + a, cy + a if x1 < 0: x2 -= x1 x1 = 0 if y1 < 0: y2 -= y1 y1 = 0 if x2 >= im_w: x1 -= x2 - im_w x2 = im_w if y2 >= im_h: y1 -= y2 - im_h y2 = im_h x1, y1, x2, y2 = map(int, [x1, y1, x2, y2]) crop = whole_img[y1:y2, x1:x2, :] crop = cv2.resize(crop, (224, 224)) img = np.repeat(crop[None, None, :], 10, axis=1) prob, logits, label, feats = i3d.process_image(img) det = data["detections"][i] updates = {} updates["action_label"] = label updates["action_confidence"] = float(prob) updates["action_crop"] = [x1, y1, x2, y2] updates["action_vector"] = feats det.update(updates) # a = persons.index(i) # if pose_indices[a] is not None: # updates["detections.{}.pose_body_index".format(i)] = pose_indices[a] return data @app.route('/extract_features', methods=["POST"]) def extract_features(): query = request.form.to_dict() imgmat = format_image(io.imread(query["path"])) out_data = object_detection(imgmat, query) future = pose_executor.submit(pose_estimation, (imgmat)) wait([future]) pose_data = future.result() out_data["pose"] = pose_data out_data = action_recognition(imgmat, out_data) return json.dumps(out_data) if __name__ == "__main__": app.run(host='0.0.0.0', threaded=False, use_reloader=False, debug=False, port=5002)

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from review.models import * def run(): n1= node_user(fb_id="34",user_name="joe") n1.save() n2= node_user(fb_id="35",user_name="sam") n2.save() n3= node_user(fb_id="36",user_name="john") n3.save() n4= node_user(fb_id="37",user_name="jeff") n4.save() n5= node_user(fb_id="38",user_name="tom") n5.save() n6= node_user(fb_id="39",user_name="ravi") n6.save() n7= node_user(fb_id="40",user_name="lucky") n7.save() edge_friend(node_user_1=n1,node_user_2= n2).save() edge_friend(node_user_1=n2,node_user_2= n1).save() edge_friend(node_user_1=n1,node_user_2=n3).save() edge_friend(node_user_1=n3,node_user_2=n1).save() edge_friend(node_user_1=n4,node_user_2=n1).save() edge_friend(node_user_1=n1,node_user_2=n4).save() edge_friend(node_user_1=n2,node_user_2=n5).save() edge_friend(node_user_1=n5,node_user_2=n2).save() reviews(product_id=1234,user_id=n2,comment="ABC",rating=2).save() reviews(product_id=1234,user_id=n3,comment="DEF",rating=3).save() reviews(product_id=1234,user_id=n4,comment="GHI",rating=4).save() reviews(product_id=1234,user_id=n5,comment="JKL",rating=8).save() reviews(product_id=1234,user_id=n6,comment="MNO",rating=6).save() reviews(product_id=1234,user_id=n7,comment="PQR",rating=9).save()

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aliostad+github@gmail.com

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# -*- coding:utf-8 -*- # @Author : 江湖一笑 # @Time : 2020/9/11 8:40 # @Software : Python_study # @Python_verison : 3.7 ''' 命令提示符登录系统后，第一眼看到的内容是： [root@localhost ~]# 这就是 Linux 系统的命令提示符。那么，这个提示符的含义是什么呢？ []：这是提示符的分隔符号，没有特殊含义。 root：显示的是当前的登录用户，笔者现在使用的是 root 用户登录。 @：分隔符号，没有特殊含义。 localhost：当前系统的简写主机名（完整主机名是 localhost.localdomain）。 ~：代表用户当前所在的目录，此例中用户当前所在的目录是家目录。 #：命令提示符，Linux 用这个符号标识登录的用户权限等级。如果是超级用户，提示符就是 #；如果是普通用户，提示符就是 $。家目录（又称主目录）是什么？ Linux 系统是纯字符界面，用户登录后，要有一个初始登录的位置，这个初始登录位置就称为用户的家：超级用户的家目录：/root。普通用户的家目录：/home/用户名。用户在自己的家目录中拥有完整权限，所以我们也建议操作实验可以放在家目录中进行。我们切换一下用户所在目录，看看有什么效果。 [root@localhost ~]# cd /usr/local [root@localhost local]# 仔细看，如果切换用户所在目录，那么命令提示符中的会变成用户当前所在目录的最后一个目录（不显示完整的所在目录 /usr/ local，只显示最后一个目录 local)。命令的基本格式接下来看看 Linux 命令的基本格式: [root@localhost ~]# 命令[选项][参数] 命令格式中的 [] 代表可选项，也就是有些命令可以不写选项或参数，也能执行。那么，我们就用 Linux 中最常见的 ls 命令来解释一下命令的格式（有关 ls 命令的具体用法，后续章节会详细介绍）。如果按照命令的分类，那么 ls 命令应该属于目录操作命令。 [root@localhost ~]# ls anaconda-ks.cfg install.log install.log.syslog 1) 选项的作用 ls 命令之后不加选项和参数也能执行，不过只能执行最基本的功能，即显示当前目录下的文件名。那么加入一个选项，会出现什么结果？ [root@localhost ~]# Is -l 总用量44 -rw-------.1 root root 1207 1 月 14 18:18 anaconda-ks.cfg -rw-r--r--.1 root root 24772 1 月 14 18:17 install.log -rw-r--r--.1 root root 7690 1 月 14 18:17 install.log.syslog 如果加一个"-l"选项，则可以看到显示的内容明显增多了。"-l"是长格式（long list）的意思，也就是显示文件的详细信息。至于 "-l" 选项的具体含义，我们稍后再详细讲解。可以看到选项的作用是调整命令功能。如果没有选项，那么命令只能执行最基本的功能；而一旦有选项，则可以显示更加丰富的数据。 Linux 的选项又分为短格式选项（-l）和长格式选项（--all）。短格式选项是英文的简写，用一个减号调用，例如： [root@localhost ~]# ls -l 而长格式选项是英文完整单词，一般用两个减号调用，例如： [root@localhost ~]# ls --all 一般情况下，短格式选项是长格式选项的缩写，也就是一个短格式选项会有对应的长格式选项。当然也有例外，比如 ls 命令的短格式选项 -l 就没有对应的长格式选项。所以具体的命令选项可以通过后面我们要学习的帮助命令来进行査询。 2) 参数的作用参数是命令的操作对象，一般文件、目录、用户和进程等可以作为参数被命令操作。例如： [root@localhost ~]# ls -l anaconda-ks.cfg -rw-------.1 root root 1207 1 月 14 18:18 anaconda-ks.cfg 但是为什么一开始 ls 命令可以省略参数？那是因为有默认参数。命令一般都需要加入参数，用于指定命令操作的对象是谁。如果可以省略参数，则一般都有默认参数。例如： [root@localhost ~]# ls anaconda-ks.cfg install.log install.log.syslog 这个 ls 命令后面没有指定参数，默认参数是当前所在位置，所以会显示当前目录下的文件名。 '''

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import json from suggestion.models import Study from suggestion.models import TrialMetric from suggestion.early_stop_algorithm.abstract_early_stop import AbstractEarlyStopAlgorithm class EarlyStopDescendingAlgorithm(AbstractEarlyStopAlgorithm): def get_early_stop_trials(self, trials): result = [] for trial in trials: study = Study.objects.get(name=trial.study_name) study_configuration_json = json.loads(study.study_configuration) study_goal = study_configuration_json["goal"] metrics = TrialMetric.objects.filter( trial_id=trial.id).order_by("-training_step") metrics = [metric for metric in metrics] if len(metrics) >= 2: if study_goal == "MAXIMIZE": if metrics[0].objective_value < metrics[1].objective_value: result.append(trial) elif study_goal == "MINIMIZE": if metrics[0].objective_value > metrics[1].objective_value: result.append(trial) return result

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import yaml from pathlib import Path __all__ = ('load_config',) def load_config(config_file=None): default_file = Path(__file__).parent / 'config.yaml' with open(default_file, 'r') as f: config = yaml.safe_load(f) cf_dict = {} if config_file: cf_dict = yaml.safe_load(config_file) config.update(**cf_dict) return config

[ "stognienkovv@gmail.com" ]

stognienkovv@gmail.com

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Eulerianial/premise-selection-deepmath-style

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import xgboost as xgb import argparse import sys import os from saving_loading import * ##################################### p = { "max_depth":int(5.0), "eta":0.07, "gamma":0.0, "num_boost_round":int(10.0), "early_stopping_rounds":int(10.0) } ##################################### if __name__ == "__main__": parser = argparse.ArgumentParser(description='Run CV for xgboost with particular combination of parameters') parser.add_argument("X", help = "path to CSR matrix with features of pairs (theorem, premise)") parser.add_argument("y", help = "path to CSV file with labels reflecting relevances of pairs (theorem, premise)") parser.add_argument("output_directory", help = "path to directory where performance of tested model should be saved") args = parser.parse_args() y = read_csv(os.path.abspath(args.y), type_of_records = "int") X = load_obj(os.path.abspath(args.X)) output_directory = os.path.abspath(args.output_directory) dtrain = xgb.DMatrix(X, label = y) params = { "max_depth":p["max_depth"], "eta":p["eta"], "gamma":p["gamma"], "objective":"binary:logistic" } x = xgb.cv( params = params, dtrain = dtrain, num_boost_round = p["num_boost_round"], early_stopping_rounds = p["early_stopping_rounds"], nfold = 4, metrics = {"error","auc","logloss"} ) output_name = os.path.join(output_directory, "_".join(map(str, list(p.values())))+".pkl") save_obj({"params":p, "stats":x}, output_name)

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# This file is part of the pyMOR project (https://www.pymor.org). # Copyright pyMOR developers and contributors. All rights reserved. # License: BSD 2-Clause License (https://opensource.org/licenses/BSD-2-Clause) from pymor.core.config import config config.require('FENICS') import dolfin as df from pymor.algorithms.preassemble import preassemble as preassemble_ from pymor.analyticalproblems.elliptic import StationaryProblem from pymor.analyticalproblems.functions import LincombFunction from pymor.bindings.fenics import FenicsVectorSpace, FenicsMatrixBasedOperator, FenicsVisualizer from pymor.discretizers.fenics.domaindiscretizer import discretize_domain from pymor.models.basic import StationaryModel from pymor.operators.constructions import LincombOperator, NumpyConversionOperator from pymor.operators.block import BlockColumnOperator def discretize_stationary_cg(analytical_problem, diameter=None, degree=1, preassemble=True): """Discretizes a |StationaryProblem| with finite elements using FEniCS. Parameters ---------- analytical_problem The |StationaryProblem| to discretize. diameter If not `None`, `diameter` is passed as an argument to the `domain_discretizer`. degree polynomial degree of the finite element. preassemble If `True`, preassemble all operators in the resulting |Model|. Returns ------- m The |Model| that has been generated. data Dictionary with the following entries: :mesh: The generated dolfin mesh object. :boundary_mask: Codim-1 `MeshFunctionSizet` indicating which boundary type a bundary facet belongs to. :boundary_ids: Dict mapping boundary types to ids used in `boundary_mask`. :unassembled_m: In case `preassemble` is `True`, the generated |Model| before preassembling operators. """ assert isinstance(analytical_problem, StationaryProblem) p = analytical_problem if p.diffusion is not None and not p.diffusion.shape_range == (): raise NotImplementedError if p.nonlinear_advection is not None: raise NotImplementedError if p.nonlinear_advection_derivative is not None: raise NotImplementedError if p.nonlinear_reaction is not None: raise NotImplementedError if p.nonlinear_reaction_derivative is not None: raise NotImplementedError if not p.domain.boundary_types <= {'dirichlet', 'neumann'}: raise NotImplementedError if p.dirichlet_data is not None and p.dirichlet_data.parametric: raise NotImplementedError mesh, (boundary_mask, boundary_ids) = discretize_domain(p.domain, diameter=diameter) V = df.FunctionSpace(mesh, 'Lagrange', degree) bc = df.DirichletBC(V, 0. if p.dirichlet_data is None else p.dirichlet_data.to_fenics(mesh)[0].item(), boundary_mask, boundary_ids['dirichlet']) u = df.TrialFunction(V) v = df.TestFunction(V) dx, ds = df.dx, df.ds Li = [FenicsMatrixBasedOperator(df.Constant(0.)*u*v*dx, {}, bc, bc_zero=False, name='boundary_part')] coefficients = [1.] _assemble_operator(p.diffusion, lambda c: df.inner(c.item() * df.grad(u), df.grad(v)) * dx, mesh, bc, True, 'diffusion', Li, coefficients) _assemble_operator( p.advection, lambda c: u * sum(ci * gi for ci, gi in zip(c, df.grad(v))) * dx, mesh, bc, True, 'advection', Li, coefficients ) _assemble_operator( p.reaction, lambda c: c * u * v * dx, mesh, bc, True, 'reaction', Li, coefficients, ) L = LincombOperator(operators=Li, coefficients=coefficients, name='ellipticOperator') # right-hand side Fi = [] coefficients_F = [] _assemble_operator(p.rhs, lambda c: c.item() * v * dx, mesh, bc, False, 'rhs', Fi, coefficients_F) if p.neumann_data is not None and p.domain.has_neumann: _assemble_operator( p.neumann_data, lambda c: c.item() * v * ds, mesh, bc, False, 'neumann', Fi, coefficients_F, negative=True ) F = LincombOperator(operators=Fi, coefficients=coefficients_F, name='rhsOperator') h1_0_semi_product = FenicsMatrixBasedOperator(df.inner(df.grad(u), df.grad(v))*dx, {}, bc, bc_zero=False, name='h1_0_semi') l2_product = FenicsMatrixBasedOperator(u*v*dx, {}, name='l2') h1_semi_product = FenicsMatrixBasedOperator(df.inner(df.grad(u), df.grad(v))*dx, {}, bc, bc_zero=False, name='h1_0_semi') h1_product = l2_product + h1_semi_product products = { 'l2': l2_product, 'h1_semi': h1_0_semi_product, 'h1': h1_product, 'h1_0_semi': h1_0_semi_product, } if p.outputs: if any(o[0] not in ('l2', 'l2_boundary') for o in p.outputs): raise NotImplementedError outputs = [] for o in p.outputs: if o[0] == 'l2': outputs.append( _assemble_operator(o[1], lambda c: c * v * dx, mesh, functional=True, name='l2_output') ) else: outputs.append( _assemble_operator(o[1], lambda c: c * v * ds, mesh, functional=True, name='l2_boundary_output') ) if len(outputs) > 1: output_functional = BlockColumnOperator(outputs) output_functional = NumpyConversionOperator(output_functional.range) @ output_functional else: output_functional = outputs[0] else: output_functional = None m = StationaryModel(L, F, output_functional=output_functional, products=products, visualizer=FenicsVisualizer(FenicsVectorSpace(V)), name=f'{p.name}_CG') data = { 'mesh': mesh, 'boundary_mask': boundary_mask, 'boundary_ids': boundary_ids, 'bc': bc, } if preassemble: data['unassembled_m'] = m m = preassemble_(m) return m, data def _assemble_operator(function, factory, mesh, bc=None, bc_zero=None, name=None, ops=None, coeffs=None, negative=False, functional=False): def assemble_op(f, name): coeff, params = f.to_fenics(mesh) return FenicsMatrixBasedOperator(factory(coeff), params, bc=bc, bc_zero=bc_zero, functional=functional, name=name) if isinstance(function, LincombFunction): operators = [assemble_op(f, f'{name}_{i}') for i, f in enumerate(function.functions)] cfs = [-c if negative else c for c in function.coefficients] if ops is not None: ops.extend(operators) coeffs.extend(cfs) else: return LincombOperator(operators, cfs, name=name) elif function is not None: operator = assemble_op(function, name) if ops is not None: ops.append(operator) coeffs.append(-1 if negative else 1.) else: return -operator if negative else operator

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# python3 import sys import argparse from pyfaidx import Fasta import pandas as pd import warnings # input parameters ap = argparse.ArgumentParser() ap.add_argument("-bed", "--bed", required=True, help="input bed file(made with bedops, every feature in the \'.gff\' or \'.gff3\' file should have an \'ID\' tag in the \'attributes\' column)") ap.add_argument("-in", "--input", required=True, help="input fasta file") ap.add_argument("-out", "--output", required=True, help="output fasta file") ap.add_argument("-fea", "--feature", required=False, default='gene', type=str, help="specify the pattern to select the lines that have it. Default is \'gene\'") ap.add_argument("-pro", "--program", required=False, default=1, type=int, help="program to choose: 1) filter the bed file before retrieving sequences, 2) do not filter. Default is 1") args = vars(ap.parse_args()) # main # create function to split the input sequence based on a specific number of characters(60) def split_every_60(s): return [str(s)[i:i+60] for i in range(0,len(str(s)),60)] # ignore warnings warnings.filterwarnings('ignore') # import bed with no headers specified df = pd.read_csv(args['bed'], sep= "\t", header=None) # choose program if args['program'] == 1: # select the rows containing the feature bool2 = df.iloc[:, 7].str.contains(args['feature']) df = df[bool2] else: pass # convert each column to list chrom = df.iloc[:,0].values.tolist() start = df.iloc[:,1].values.tolist() end = df.iloc[:,2].values.tolist() ids = df.iloc[:,3].values.tolist() strand = df.iloc[:,5].values.tolist() # import fasta file features = Fasta(args['input']) # iterate all below lists in pairs sys.stdout = open(args['output'], 'a') for (a, b, c, d, e) in zip(ids, chrom, start, end, strand): if str(e) == "+": print(''.join([">",str(a)," ",str(b),":",str(int(c) + 1),"-",str(d)]).replace('\r', '')) print('\n'.join(split_every_60(features[str(b)][int(c):int(d)].seq))) else: print(''.join([">",str(a)," ",str(b),":",str(int(c) + 1),"-",str(d)," ","reverse complement"]).replace('\r', '')) print('\n'.join(split_every_60(features[str(b)][int(c):int(d)].reverse.complement.seq))) sys.stdout.close()

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olgatsiouri@outlook.com

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""" The core's core. """ from sympy.core.compatibility import cmp # used for canonical ordering of symbolic sequences # via __cmp__ method: # FIXME this is *so* irrelevant and outdated! ordering_of_classes = [ # singleton numbers 'Zero', 'One','Half','Infinity','NaN','NegativeOne','NegativeInfinity', # numbers 'Integer','Rational','Float', # singleton symbols 'Exp1','Pi','ImaginaryUnit', # symbols 'Symbol','Wild','Temporary', # arithmetic operations 'Pow', 'Mul', 'Add', # function values 'Derivative','Integral', # defined singleton functions 'Abs','Sign','Sqrt', 'Floor', 'Ceiling', 'Re', 'Im', 'Arg', 'Conjugate', 'Exp','Log', 'Sin','Cos','Tan','Cot','ASin','ACos','ATan','ACot', 'Sinh','Cosh','Tanh','Coth','ASinh','ACosh','ATanh','ACoth', 'RisingFactorial','FallingFactorial', 'factorial','binomial', 'Gamma','LowerGamma','UpperGamma','PolyGamma', 'Erf', # special polynomials 'Chebyshev','Chebyshev2', # undefined functions 'Function','WildFunction', # anonymous functions 'Lambda', # Landau O symbol 'Order', # relational operations 'Equality', 'Unequality', 'StrictGreaterThan', 'StrictLessThan', 'GreaterThan', 'LessThan', ] class BasicType(type): pass class Registry(object): """ Base class for registry objects. Registries map a name to an object using attribute notation. Registry classes behave singletonically: all their instances share the same state, which is stored in the class object. All subclasses should set `__slots__ = []`. """ __slots__ = [] def __setattr__(self, name, obj): setattr(self.__class__, name, obj) def __delattr__(self, name): delattr(self.__class__, name) #A set containing all sympy class objects, kept in sync with C all_classes = set() class ClassRegistry(Registry): """ Namespace for SymPy classes This is needed to avoid problems with cyclic imports. To get a SymPy class, use `C.<class_name>` e.g. `C.Rational`, `C.Add`. For performance reasons, this is coupled with a set `all_classes` holding the classes, which should not be modified directly. """ __slots__ = [] def __setattr__(self, name, cls): Registry.__setattr__(self, name, cls) all_classes.add(cls) def __delattr__(self, name): cls = getattr(self, name) Registry.__delattr__(self, name) # The same class could have different names, so make sure # it's really gone from C before removing it from all_classes. if cls not in self.__class__.__dict__.itervalues(): all_classes.remove(cls) C = ClassRegistry() class BasicMeta(BasicType): def __init__(cls, *args, **kws): setattr(C, cls.__name__, cls) def __cmp__(cls, other): # If the other object is not a Basic subclass, then we are not equal to # it. if not isinstance(other, BasicType): return -1 n1 = cls.__name__ n2 = other.__name__ c = cmp(n1, n2) if not c: return 0 UNKNOWN = len(ordering_of_classes) + 1 try: i1 = ordering_of_classes.index(n1) except ValueError: i1 = UNKNOWN try: i2 = ordering_of_classes.index(n2) except ValueError: i2 = UNKNOWN if i1 == UNKNOWN and i2 == UNKNOWN: return c return cmp(i1, i2) def __lt__(cls, other): if cls.__cmp__(other) == -1: return True return False def __gt__(cls, other): if cls.__cmp__(other) == 1: return True return False C.BasicMeta = BasicMeta

[ "kevin.m.smyth@gmail.com" ]

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# coding=utf-8 """Unit tests for source.py. """ __author__ = ['Ryan Barrett <activitystreams@ryanb.org>'] import copy import json import mox from source import Source from oauth_dropins.webutil import testutil from oauth_dropins.webutil import util LIKES = [{ 'verb': 'like', 'author': {'id': 'tag:fake.com:person', 'numeric_id': '5'}, 'object': {'url': 'http://foo/like/5'}, }, { 'verb': 'like', 'author': {'id': 'tag:fake.com:6'}, 'object': {'url': 'http://bar/like/6'}, }, ] ACTIVITY = { 'id': '1', 'object': { 'id': '1', 'tags': LIKES, } } RSVPS = [{ 'id': 'tag:fake.com:246_rsvp_11500', 'objectType': 'activity', 'verb': 'rsvp-yes', 'actor': {'displayName': 'Aaron P', 'id': 'tag:fake.com,2013:11500'}, }, { 'objectType': 'activity', 'verb': 'rsvp-no', 'actor': {'displayName': 'Ryan B'}, }, { 'id': 'tag:fake.com:246_rsvp_987', 'objectType': 'activity', 'verb': 'rsvp-maybe', 'actor': {'displayName': 'Foo', 'id': 'tag:fake.com,2013:987'}, }] EVENT = { 'id': 'tag:fake.com:246', 'objectType': 'event', 'displayName': 'Homebrew Website Club', } EVENT_WITH_RSVPS = copy.deepcopy(EVENT) EVENT_WITH_RSVPS.update({ 'attending': [RSVPS[0]['actor']], 'notAttending': [RSVPS[1]['actor']], 'maybeAttending': [RSVPS[2]['actor']], }) class FakeSource(Source): DOMAIN = 'fake.com' def __init__(self, **kwargs): pass class SourceTest(testutil.HandlerTest): def setUp(self): super(SourceTest, self).setUp() self.source = FakeSource() self.mox.StubOutWithMock(self.source, 'get_activities') def test_original_post_discovery(self): activity = {'object': { 'objectType': 'article', 'displayName': 'article abc', 'url': 'http://example.com/article-abc', 'tags': [], }} self.assert_equals(activity, Source.original_post_discovery( copy.deepcopy(activity))) # missing objectType activity['object']['attachments'] = [{'url': 'http://x.com/y'}] Source.original_post_discovery(activity) self.assert_equals([], activity['object']['tags']) activity['object']['content'] = 'x (not.at end) y (at.the end)' Source.original_post_discovery(activity) self.assert_equals(['http://at.the/end'], activity['object']['upstreamDuplicates']) self.assert_equals([], activity['object']['tags']) activity['object'].update({ 'content': 'x http://baz/3 y', 'attachments': [{'objectType': 'article', 'url': 'http://foo/1'}], 'tags': [{'objectType': 'article', 'url': 'http://bar/2'}], }) Source.original_post_discovery(activity) self.assert_equals([ {'objectType': 'article', 'url': 'http://foo/1'}, {'objectType': 'article', 'url': 'http://bar/2'}, {'objectType': 'article', 'url': 'http://baz/3'}, ], activity['object']['tags']) # leading parens used to cause us trouble activity = {'object': {'content' : 'Foo (http://snarfed.org/xyz)'}} Source.original_post_discovery(activity) self.assert_equals( [{'objectType': 'article', 'url': 'http://snarfed.org/xyz'}], activity['object']['tags']) # don't duplicate PSCs and PSLs with http and https for field in 'tags', 'attachments': for scheme in 'http', 'https': url = scheme + '://foo.com/1' activity = {'object': { 'content': 'x (foo.com/1)', field: [{'objectType': 'article', 'url': url}], }} Source.original_post_discovery(activity) self.assert_equals([{'objectType': 'article', 'url': url}], activity['object']['tags']) # exclude ellipsized URLs for ellipsis in '...', u'…': url = 'foo.com/1' + ellipsis activity = {'object': { 'content': 'x (%s)' % url, 'attachments': [{'objectType': 'article', 'url': 'http://' + url}], }} Source.original_post_discovery(activity) self.assert_equals([], activity['object']['tags']) def test_get_like(self): self.source.get_activities(user_id='author', activity_id='activity', fetch_likes=True).AndReturn([ACTIVITY]) self.mox.ReplayAll() self.assert_equals(LIKES[1], self.source.get_like('author', 'activity', '6')) def test_get_like_numeric_id(self): self.source.get_activities(user_id='author', activity_id='activity', fetch_likes=True).AndReturn([ACTIVITY]) self.mox.ReplayAll() self.assert_equals(LIKES[0], self.source.get_like('author', 'activity', '5')) def test_get_like_not_found(self): activity = copy.deepcopy(ACTIVITY) del activity['object']['tags'] self.source.get_activities(user_id='author', activity_id='activity', fetch_likes=True).AndReturn([activity]) self.mox.ReplayAll() self.assert_equals(None, self.source.get_like('author', 'activity', '6')) def test_get_like_no_activity(self): self.source.get_activities(user_id='author', activity_id='activity', fetch_likes=True).AndReturn([]) self.mox.ReplayAll() self.assert_equals(None, self.source.get_like('author', 'activity', '6')) def test_get_share(self): activity = copy.deepcopy(ACTIVITY) share = activity['object']['tags'][1] share['verb'] = 'share' self.source.get_activities(user_id='author', activity_id='activity', fetch_shares=True).AndReturn([activity]) self.mox.ReplayAll() self.assert_equals(share, self.source.get_share('author', 'activity', '6')) def test_get_share_not_found(self): self.source.get_activities(user_id='author', activity_id='activity', fetch_shares=True).AndReturn([ACTIVITY]) self.mox.ReplayAll() self.assert_equals(None, self.source.get_share('author', 'activity', '6')) def test_add_rsvps_to_event(self): event = copy.deepcopy(EVENT) Source.add_rsvps_to_event(event, []) self.assert_equals(EVENT, event) Source.add_rsvps_to_event(event, RSVPS) self.assert_equals(EVENT_WITH_RSVPS, event) def test_get_rsvps_from_event(self): self.assert_equals([], Source.get_rsvps_from_event(EVENT)) self.assert_equals(RSVPS, Source.get_rsvps_from_event(EVENT_WITH_RSVPS)) def test_get_rsvps_from_event_bad_id(self): event = copy.deepcopy(EVENT) for id in None, 'not_a_tag_uri': event['id'] = id self.assert_equals([], Source.get_rsvps_from_event(event)) def test_base_object_multiple_objects(self): like = copy.deepcopy(LIKES[0]) like['object'] = [like['object'], {'url': 'http://fake.com/second'}] self.assert_equals(('second', 'http://fake.com/second'), self.source.base_object(like)) def test_content_for_create(self): def cfc(base, extra): obj = base.copy() obj.update(extra) return self.source._content_for_create(obj) self.assertEqual(None, cfc({}, {})) for base in ({'objectType': 'article'}, {'inReplyTo': {'url': 'http://not/fake'}}, {'objectType': 'comment', 'object': {'url': 'http://not/fake'}}): self.assertEqual(None, cfc(base, {})) self.assertEqual('c', cfc(base, {'content': ' c '})) self.assertEqual('n', cfc(base, {'content': 'c', 'displayName': 'n'})) self.assertEqual('s', cfc(base, {'content': 'c', 'displayName': 'n', 'summary': 's'})) for base in ({'objectType': 'note'}, {'inReplyTo': {'url': 'http://fake.com/post'}}, {'objectType': 'comment', 'object': {'url': 'http://fake.com/post'}}): self.assertEqual(None, cfc(base, {})) self.assertEqual('n', cfc(base, {'displayName': 'n'})) self.assertEqual('c', cfc(base, {'displayName': 'n', 'content': 'c'})) self.assertEqual('s', cfc(base, {'displayName': 'n', 'content': 'c', 'summary': ' s '}))

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import threading import sys class ThreadHandler(object): def __init__(self, name, callable, *args, **kwargs): # Set up exception handling self.exception = None def wrapper(*args, **kwargs): try: callable(*args, **kwargs) except BaseException: self.exception = sys.exc_info() # Kick off thread thread = threading.Thread(None, wrapper, name, args, kwargs) thread.setDaemon(True) thread.start() # Make thread available to instantiator self.thread = thread

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PeterTao666/learnpython2

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# 访问一个网址 # 更改自己的UserAgent进行伪装 from urllib import request, error if __name__ == '__main__': url = 'http://www.baidu.com' try: #　使用ｈｅａｄ方法伪装ＵＡ # 方法一： #headers = {} #headers['User-Agent'] = 'Mozilla/5.0 (ipad;CPU OS 5_0 like Mac OS X) AppleWibKit/534.46(KHTML, like Gecko) Version/5.1 Mobile/9A334 Safari/7534.48.3' #req = request.Request(url, headers=headers) # 方法二:使用add_header方法 req = request.Request(url) req.add_header("User-Agent", "Mozilla/5.0 (ipad;CPU OS 5_0 like Mac OS X) AppleWibKit/534.46(KHTML, like Gecko) Version/5.1 Mobile/9A334 Safari/7534.48.3'") # 正常访问 rsp = request.urlopen(req) html = rsp.read().decode() print(html) except error.HTTPError as e: print(e) except error.URLError as e: print(e) except Exception as e: print(e) print("Done...")

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# file openpyxl/tests/test_write.py # Copyright (c) 2010-2011 openpyxl # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # 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. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. # # @license: http://www.opensource.org/licenses/mit-license.php # @author: see AUTHORS file # Python stdlib imports from StringIO import StringIO import os.path # 3rd party imports from nose.tools import eq_, with_setup, raises # package imports from openpyxl.tests.helper import TMPDIR, DATADIR, \ assert_equals_file_content, clean_tmpdir, make_tmpdir from openpyxl.workbook import Workbook from openpyxl.reader.excel import load_workbook from openpyxl.writer.excel import save_workbook, save_virtual_workbook, \ ExcelWriter from openpyxl.writer.workbook import write_workbook, write_workbook_rels from openpyxl.writer.worksheet import write_worksheet, write_worksheet_rels from openpyxl.writer.strings import write_string_table from openpyxl.writer.styles import StyleWriter @with_setup(setup = make_tmpdir, teardown = clean_tmpdir) def test_write_empty_workbook(): wb = Workbook() dest_filename = os.path.join(TMPDIR, 'empty_book.xlsx') save_workbook(wb, dest_filename) assert os.path.isfile(dest_filename) def test_write_virtual_workbook(): old_wb = Workbook() saved_wb = save_virtual_workbook(old_wb) new_wb = load_workbook(StringIO(saved_wb)) assert new_wb def test_write_workbook_rels(): wb = Workbook() content = write_workbook_rels(wb) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'workbook.xml.rels'), content) def test_write_workbook(): wb = Workbook() content = write_workbook(wb) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'workbook.xml'), content) def test_write_string_table(): table = {'hello': 1, 'world': 2, 'nice': 3} content = write_string_table(table) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sharedStrings.xml'), content) def test_write_worksheet(): wb = Workbook() ws = wb.create_sheet() ws.cell('F42').value = 'hello' content = write_worksheet(ws, {'hello': 0}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1.xml'), content) def test_write_hidden_worksheet(): wb = Workbook() ws = wb.create_sheet() ws.sheet_state = ws.SHEETSTATE_HIDDEN ws.cell('F42').value = 'hello' content = write_worksheet(ws, {'hello': 0}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1.xml'), content) def test_write_bool(): wb = Workbook() ws = wb.create_sheet() ws.cell('F42').value = False ws.cell('F43').value = True content = write_worksheet(ws, {}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_bool.xml'), content) def test_write_formula(): wb = Workbook() ws = wb.create_sheet() ws.cell('F1').value = 10 ws.cell('F2').value = 32 ws.cell('F3').value = '=F1+F2' content = write_worksheet(ws, {}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_formula.xml'), content) def test_write_style(): wb = Workbook() ws = wb.create_sheet() ws.cell('F1').value = '13%' style_id_by_hash = StyleWriter(wb).get_style_by_hash() content = write_worksheet(ws, {}, style_id_by_hash) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_style.xml'), content) def test_write_height(): wb = Workbook() ws = wb.create_sheet() ws.cell('F1').value = 10 ws.row_dimensions[ws.cell('F1').row].height = 30 content = write_worksheet(ws, {}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_height.xml'), content) def test_write_hyperlink(): wb = Workbook() ws = wb.create_sheet() ws.cell('A1').value = "test" ws.cell('A1').hyperlink = "http://test.com" content = write_worksheet(ws, {'test': 0}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_hyperlink.xml'), content) def test_write_hyperlink_rels(): wb = Workbook() ws = wb.create_sheet() eq_(0, len(ws.relationships)) ws.cell('A1').value = "test" ws.cell('A1').hyperlink = "http://test.com/" eq_(1, len(ws.relationships)) ws.cell('A2').value = "test" ws.cell('A2').hyperlink = "http://test2.com/" eq_(2, len(ws.relationships)) content = write_worksheet_rels(ws, 1) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_hyperlink.xml.rels'), content) def test_hyperlink_value(): wb = Workbook() ws = wb.create_sheet() ws.cell('A1').hyperlink = "http://test.com" eq_("http://test.com", ws.cell('A1').value) ws.cell('A1').value = "test" eq_("test", ws.cell('A1').value) def test_write_auto_filter(): wb = Workbook() ws = wb.worksheets[0] ws.cell('F42').value = 'hello' ws.auto_filter = 'A1:F1' content = write_worksheet(ws, {'hello': 0}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_auto_filter.xml'), content) content = write_workbook(wb) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'workbook_auto_filter.xml'), content) def test_freeze_panes_horiz(): wb = Workbook() ws = wb.create_sheet() ws.cell('F42').value = 'hello' ws.freeze_panes = 'A4' content = write_worksheet(ws, {'hello': 0}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_freeze_panes_horiz.xml'), content) def test_freeze_panes_vert(): wb = Workbook() ws = wb.create_sheet() ws.cell('F42').value = 'hello' ws.freeze_panes = 'D1' content = write_worksheet(ws, {'hello': 0}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_freeze_panes_vert.xml'), content) pass def test_freeze_panes_both(): wb = Workbook() ws = wb.create_sheet() ws.cell('F42').value = 'hello' ws.freeze_panes = 'D4' content = write_worksheet(ws, {'hello': 0}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'sheet1_freeze_panes_both.xml'), content) def test_long_number(): wb = Workbook() ws = wb.create_sheet() ws.cell('A1').value = 9781231231230 content = write_worksheet(ws, {}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'long_number.xml'), content) def test_short_number(): wb = Workbook() ws = wb.create_sheet() ws.cell('A1').value = 1234567890 content = write_worksheet(ws, {}, {}) assert_equals_file_content(os.path.join(DATADIR, 'writer', 'expected', \ 'short_number.xml'), content)

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#!/usr/bin/env python # -*- coding: utf-8 -*- # Created by weihang huang on 17-12-23 from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import sys import os import tensorflow as tf import numpy as np def colormap(n): cmap = np.zeros([n, 3]).astype(np.uint8) for i in np.arange(n): r, g, b = np.zeros(3) for j in np.arange(8): r = r + (1 << (7 - j)) * ((i & (1 << (3 * j))) >> (3 * j)) g = g + (1 << (7 - j)) * ((i & (1 << (3 * j + 1))) >> (3 * j + 1)) b = b + (1 << (7 - j)) * ((i & (1 << (3 * j + 2))) >> (3 * j + 2)) cmap[i, :] = np.array([r, g, b]) return cmap class Colorize(object): def __init__(self): self.cmap = colormap(256) def __call__(self, gray_image): size = gray_image.shape color_image = np.zeros((size[0], size[1], 3)) for i in range(color_image.shape[0]): for j in range(color_image.shape[1]): color_image[i, j, :] = self.cmap[gray_image[i, j]] return color_image def colorize(ori_img): color_fcn = Colorize() img = color_fcn(ori_img.astype(np.uint8)) return img

[ "614047311@qq.com" ]

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# -*- coding: utf-8 -*- # Copyright 2014 Spanish National Research Council (CSIC) # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import logging import warnings from oslo_config import cfg from oslo_log import log import caso logging.captureWarnings(True) warnings.simplefilter("default", DeprecationWarning) log.register_options(cfg.CONF) def parse_args(argv, default_config_files=None): cfg.CONF(argv[1:], project='caso', version=caso.__version__, default_config_files=default_config_files)

[ "aloga@ifca.unican.es" ]

aloga@ifca.unican.es

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yuhuofei/TensorFlow-1

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# Lint as: python3 # Copyright 2018 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Init module for TensorFlow Model Analysis extractors.""" from tensorflow_model_analysis.extractors import legacy_meta_feature_extractor as meta_feature_extractor from tensorflow_model_analysis.extractors.batched_input_extractor import BatchedInputExtractor from tensorflow_model_analysis.extractors.extractor import Extractor from tensorflow_model_analysis.extractors.extractor import Filter from tensorflow_model_analysis.extractors.legacy_feature_extractor import FeatureExtractor from tensorflow_model_analysis.extractors.legacy_input_extractor import InputExtractor from tensorflow_model_analysis.extractors.legacy_predict_extractor import PredictExtractor from tensorflow_model_analysis.extractors.slice_key_extractor import SLICE_KEY_EXTRACTOR_STAGE_NAME from tensorflow_model_analysis.extractors.slice_key_extractor import SliceKeyExtractor

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import sys sys.stdin = open("장기_input.txt") def bfs(): que = [] que.append((R, C, 0)) data[R][C] = 1 dr = [-2, -2, -1, 1, 2, 2, 1, -1] dc = [-1, 1, 2, 2, 1, -1, -2, -2] while que: r, c, turn = que.pop(0) if r == S and c == K: return turn for i in range(8): nr = r + dr[i] nc = c + dc[i] if nr < 0 or nr >= N or nc < 0 or nc >= M: continue if data[nr][nc] == 1: continue data[nr][nc] = 1 que.append((nr, nc, turn+1)) N, M = map(int, input().split()) R, C, S, K = map(int, input().split()) R -= 1 C -= 1 S -= 1 K -= 1 data = [[0 for _ in range(M)] for _ in range(N)] print(bfs())

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#!/usr/bin/python ''' Defines the general behavior that can be used by all cgi search modules. ''' import unicodedata import cgi import cgitb cgitb.enable() def receive_data(): ''' Receive and return the cgi data from web-page. @return: the cgi form data from the corresponding web-page ''' print 'Content-Type: text/html\n\n' data = cgi.FieldStorage() return data def find_search_result(rst_list, process_each_search_result): ''' According to the search results list, and search result processing method, return a search results html string. @param rst_list: the search results list @param process_each_search_result: the method of processing each search result @return: the search result html string ''' # If search miss if len(rst_list) == 0: return 'Search miss!<br>\n' rst_string = 'Total search hits number: ' + str(len(rst_list)) + '<br><br>\n' # Print out top 10 search hits for i in range(0, 10): if i >= len(rst): break if i % 2 == 0: rst_string += '<div class="blog-top">\n' search_result += process_each_search_result(rst_list[i], i + 1) if i % 2 == 1: search_result += ''' <div class="clear"></div> </div> ''' return rst_string def html_file_top(): ''' Return a html string that corresponds to the search result page's header. @return: a html string that corresponds to the search result page's header ''' return ''' <html> <head> <title>Search Result</title> <meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1"> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <link href="css/style.css" rel="stylesheet" type="text/css" media="all" /> <link href='http://fonts.googleapis.com/css?family=Raleway' rel='stylesheet' type='text/css'> <script src="js/jquery.min.js"></script> </head> <body> <div class="index-banner1"> <div class="header-top"> <div class="wrap"> <div class="logo"> <a href="home.html"><img src="images/another_search.png" alt=""/></a> </div> <div class="clear"></div> </div> </div> </div> <div class="main"> <div class="wrap"> <div class="abstract"> ''' def html_file_bottom(): ''' Return a html string that corresponds to the search result page's footer. @return: a html string that corresponds to the search result page's footer ''' return ''' </body> </html> ''' def write_and_jump(rst_html_str): ''' Write the search result html string into ./soccer_search/result.html file, then jump current web-page into the result page (http://localhost:8000/soccer_search/result.html) @param rst_html_str: the search result html string ''' # Write the processed search result html string into ./soccer_search/result.html file with open('./soccer_search/result.html', 'w') as html_file: html_file.write(html_file_top()) html_file.write(rst_html_str) html_file.write(html_file_bottom()) # Jump current web-page into the result page print ''' <html> <meta http-equiv="refresh" content="0.1;url=http://localhost:8000/soccer_search/result.html"> </html> '''

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apple@Junchao.local

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/horizon/horizon/dashboards/nova/images_and_snapshots/snapshots/forms.py

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# vim: tabstop=4 shiftwidth=4 softtabstop=4 # Copyright 2011 United States Government as represented by the # Administrator of the National Aeronautics and Space Administration. # All Rights Reserved. # # Copyright 2011 Nebula, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import logging from django import shortcuts from django.contrib import messages from django.utils.translation import ugettext as _ from openstackx.api import exceptions as api_exceptions from horizon import api from horizon import forms LOG = logging.getLogger(__name__) class CreateSnapshot(forms.SelfHandlingForm): tenant_id = forms.CharField(widget=forms.HiddenInput()) instance_id = forms.CharField(widget=forms.TextInput( attrs={'readonly': 'readonly'})) name = forms.CharField(max_length="20", label=_("Snapshot Name")) def handle(self, request, data): try: LOG.info('Creating snapshot "%s"' % data['name']) snapshot = api.snapshot_create(request, data['instance_id'], data['name']) instance = api.server_get(request, data['instance_id']) messages.info(request, _('Snapshot "%(name)s" created for instance "%(inst)s"') % {"name": data['name'], "inst": instance.name}) return shortcuts.redirect('horizon:nova:images_and_snapshots' ':snapshots:index') except api_exceptions.ApiException, e: msg = _('Error Creating Snapshot: %s') % e.message LOG.exception(msg) messages.error(request, msg) return shortcuts.redirect(request.build_absolute_uri())

[ "gabriel@strikeawe.com" ]

gabriel@strikeawe.com

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import unittest from streamlink.plugins.googledrive import GoogleDocs class TestPluginGoogleDocs(unittest.TestCase): def test_can_handle_url(self): should_match = [ 'https://drive.google.com/file/d/123123/preview?start=1', ] for url in should_match: self.assertTrue(GoogleDocs.can_handle_url(url)) def test_can_handle_url_negative(self): should_not_match = [ 'https://example.com/index.html', ] for url in should_not_match: self.assertFalse(GoogleDocs.can_handle_url(url))

[ "gravyboat@users.noreply.github.com" ]

gravyboat@users.noreply.github.com

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# encoding=utf-8 import pdb import os import torch.utils.data.dataset as dataset import misc_utils as utils import random import numpy as np import cv2 from dataloader.transforms.custom_transform import read_image class ListTrainValDataset(dataset.Dataset): """ImageDataset for training. Args: file_list(str): dataset list, input and label should be split by ',' aug(bool): data argument (×8) norm(bool): normalization Example: train_dataset = ImageDataset('train.txt', aug=False) for i, data in enumerate(train_dataset): input, label = data['input']. data['label'] """ def __init__(self, file_list, transforms, max_size=None): self.im_names = [] self.labels = [] with open(file_list, 'r') as f: lines = f.readlines() for line in lines: line = line.rstrip('\n') img, label = line.split() img, label = img.strip(), label.strip() self.im_names.append(img) self.labels.append(label) self.transforms = transforms self.max_size = max_size def __getitem__(self, index): """Get indexs by index Args: index(int): index Returns: { 'input': input, 'label': label, 'path': path, } """ input = read_image(self.im_names[index]) gt = read_image(self.labels[index]) sample = self.transforms(**{ 'image': input, 'gt': gt, }) sample = { 'input': sample['image'], 'label': sample['gt'], 'path': self.im_names[index], } return sample def __len__(self): if self.max_size is not None: return min(self.max_size, len(self.im_names)) return len(self.im_names) class ListTestDataset(dataset.Dataset): """ImageDataset for test. Args: file_list(str): dataset path' norm(bool): normalization Example: test_dataset = ImageDataset('test', crop=256) for i, data in enumerate(test_dataset): input, file_name = data """ def __init__(self, file_list, transforms, max_size=None): self.im_names = [] with open(file_list, 'r') as f: lines = f.readlines() for line in lines: line = line.rstrip('\n') img = line self.im_names.append(img) self.transforms = transforms self.max_size = max_size def __getitem__(self, index): input = Image.open(self.im_names[index]).convert("RGB") sample = self.transforms(**{ 'image': input, 'gt': input, }) sample = { 'input': sample['image'], 'path': self.im_names[index], } return sample def __len__(self): if self.max_size is not None: return min(self.max_size, len(self.im_names)) return len(self.im_names)

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serihiro/blueoil

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refs/heads/master

2020-07-25T11:53:48.940466

2019-09-12T06:38:12

208,280,175

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2019-09-13T14:22:36

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# -*- coding: utf-8 -*- # Copyright 2018 The Blueoil Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================= import ctypes as ct import numpy as np from numpy.ctypeslib import ndpointer class NNLib(object): def __init__(self): self.lib = None self.nnlib = None def load(self, libpath): self.lib = ct.cdll.LoadLibrary(libpath) self.lib.network_create.argtypes = [] self.lib.network_create.restype = ct.c_void_p self.lib.network_init.argtypes = [ct.c_void_p] self.lib.network_init.restype = ct.c_bool self.lib.network_delete.argtypes = [ct.c_void_p] self.lib.network_delete.restype = None self.lib.network_get_input_rank.argtypes = [ct.c_void_p] self.lib.network_get_input_rank.restype = ct.c_int self.lib.network_get_output_rank.argtypes = [ct.c_void_p] self.lib.network_get_output_rank.restype = ct.c_int self.lib.network_get_input_shape.argtypes = [ct.c_void_p, ndpointer(ct.c_int32, flags="C_CONTIGUOUS")] self.lib.network_get_input_shape.restype = None self.lib.network_get_output_shape.argtypes = [ct.c_void_p, ndpointer(ct.c_int32, flags="C_CONTIGUOUS")] self.lib.network_get_output_shape.restype = None self.lib.network_run.argtypes = [ ct.c_void_p, ndpointer( ct.c_float, flags="C_CONTIGUOUS"), ndpointer( ct.c_float, flags="C_CONTIGUOUS"), ] self.lib.network_run.restype = None self.nnlib = self.lib.network_create() return True def init(self): return self.lib.network_init(self.nnlib) def delete(self): if self.nnlib: self.lib.network_delete(self.nnlib) self.nnlib = None self.lib = None def __del__(self): self.delete() def get_input_rank(self): return self.lib.network_get_input_rank(self.nnlib) def get_output_rank(self): return self.lib.network_get_output_rank(self.nnlib) def get_input_shape(self): r = self.get_input_rank() s = np.zeros(r, np.int32) self.lib.network_get_input_shape(self.nnlib, s) return tuple(s) def get_output_shape(self): r = self.get_output_rank() s = np.zeros(r, np.int32) self.lib.network_get_output_shape(self.nnlib, s) return tuple(s) def run(self, tensor): input = tensor.flatten().astype(np.float32) output = np.zeros((self.get_output_shape()), np.float32) self.lib.network_run( self.nnlib, input, output) return output

[ "matsuda@leapmind.io" ]

matsuda@leapmind.io

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hugovk/coveragepy

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2023-06-27T08:39:02.120975

2023-06-07T10:28:18

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# Licensed under the Apache License: http://www.apache.org/licenses/LICENSE-2.0 # For details: https://github.com/nedbat/coveragepy/blob/master/NOTICE.txt """A file tracer plugin for test_plugins.py to import.""" from __future__ import annotations import os.path from types import FrameType from typing import Any, Optional, Set, Tuple from coverage import CoveragePlugin, FileReporter, FileTracer from coverage.plugin_support import Plugins from coverage.types import TLineNo try: import third.render # pylint: disable=unused-import except ImportError: # This plugin is used in a few tests. One of them has the third.render # module, but most don't. We need to import it but not use it, so just # try importing it and it's OK if the module doesn't exist. pass class Plugin(CoveragePlugin): """A file tracer plugin for testing.""" def file_tracer(self, filename: str) -> Optional[FileTracer]: if "render.py" in filename: return RenderFileTracer() return None def file_reporter(self, filename: str) -> FileReporter: return MyFileReporter(filename) class RenderFileTracer(FileTracer): """A FileTracer using information from the caller.""" def has_dynamic_source_filename(self) -> bool: return True def dynamic_source_filename( self, filename: str, frame: FrameType, ) -> Optional[str]: if frame.f_code.co_name != "render": return None source_filename: str = os.path.abspath(frame.f_locals['filename']) return source_filename def line_number_range(self, frame: FrameType) -> Tuple[TLineNo, TLineNo]: lineno = frame.f_locals['linenum'] return lineno, lineno+1 class MyFileReporter(FileReporter): """A goofy file reporter.""" def lines(self) -> Set[TLineNo]: # Goofy test arrangement: claim that the file has as many lines as the # number in its name. num = os.path.basename(self.filename).split(".")[0].split("_")[1] return set(range(1, int(num)+1)) def coverage_init( reg: Plugins, options: Any, # pylint: disable=unused-argument ) -> None: """Called by coverage to initialize the plugins here.""" reg.add_file_tracer(Plugin())

[ "ned@nedbatchelder.com" ]

ned@nedbatchelder.com

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/graph/migrations/0001_initial.py

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belal-bh/django-mptt-example

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2023-03-15T21:44:52.678226

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# Generated by Django 3.1.4 on 2020-12-04 18:52 from django.db import migrations, models import django.db.models.deletion import mptt.fields class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Node', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('username', models.CharField(max_length=30, unique=True)), ('name', models.CharField(max_length=255)), ('is_verified', models.BooleanField(default=False)), ('is_active', models.BooleanField(default=False)), ('updated', models.DateTimeField(auto_now=True)), ('timestamp', models.DateTimeField(auto_now_add=True)), ('lft', models.PositiveIntegerField(editable=False)), ('rght', models.PositiveIntegerField(editable=False)), ('tree_id', models.PositiveIntegerField(db_index=True, editable=False)), ('level', models.PositiveIntegerField(editable=False)), ('connection', models.ManyToManyField(related_name='_node_connection_+', to='graph.Node')), ('parent', mptt.fields.TreeForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='children', to='graph.node')), ], options={ 'abstract': False, }, ), ]

[ "bh.pro.pust@gmail.com" ]

bh.pro.pust@gmail.com

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/OpenCV预处理/局部自适应阈值处理inv.py

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[]

no_license

HotView/PycharmProjects

215ab9edd341e3293daebcf86d97537f8cd28d75

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refs/heads/master

2020-06-02T07:41:53.608742

2019-11-13T08:31:57

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# 目标区域为偏暗色，即灰度值最小的地方为感兴趣区 import cv2 import numpy as np def Nothing(val): size = cv2.getTrackbarPos("size","gray") param = cv2.getTrackbarPos("param","gray") thresh = cv2.adaptiveThreshold(gray,255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV,2*size+1, param) cv2.imshow("thresh", thresh) img = cv2.imread("image/hand01.jpg") img = cv2.GaussianBlur(img,(5,5),1) gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) #cv2.namedWindow("thresh") cv2.namedWindow("gray") cv2.createTrackbar("size","gray",0,300,Nothing) cv2.createTrackbar("param","gray",0,100,Nothing) cv2.imshow("gray",gray) cv2.waitKey(0)

[ "864773190@qq.com" ]

864773190@qq.com

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/src/allennlp_plugins/__init__.py

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permissive

j6mes/eacl2021-debias-finetuning

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2023-03-26T01:39:11.674216

2021-03-27T21:35:52

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from debias_finetuning.commands.finetune_l2 import * from debias_finetuning.commands.finetune_ewc import * from debias_finetuning.commands.evaluate_with_overwrite import *

[ "james@jthorne.co.uk" ]

james@jthorne.co.uk

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/learn/FileIO.py

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pranjalparmar/Learn-Python

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refs/heads/main

2023-02-28T17:42:53.271860

2021-02-06T11:18:45

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f = open("pranjal.txt","rt") print(f.readlines()) # print(f.readline()) # print(f.readline()) # content = (f.readline()) # content = (f.readline()) # print("1",content) # for line in f: # print(line,end="") f.close()

[ "noreply@github.com" ]

pranjalparmar.noreply@github.com

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/Code/CodeRecords/2690/60678/248819.py

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no_license

AdamZhouSE/pythonHomework

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refs/heads/master

2022-11-24T08:05:22.122011

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times = int(input()) for loopTimes in range(0, times): input() stringList = input().split() stringM = stringList[0] stringS = stringList[1] stringTest = stringM + ' ' + stringS listM = list(stringM) listS = list(stringS) for i in range(0, len(stringS)): while stringM.find(stringS[i]) != -1: listM[stringM.find(stringS[i])] = '1' stringM = ''.join(listM) for i in range(0, len(listM)): if listM[i] != '1': listM[i] = '0' stringM = ''.join(listM) stringM = stringM.split('0') index = 0 while index < len(stringM): if stringM[index] == '': del stringM[index] index -= 1 index += 1 # print(len(stringM)) if len(stringM) == 4: print(len(stringM)) else: print(stringTest)

[ "1069583789@qq.com" ]

1069583789@qq.com

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/LintCode/6-Linked List/2.covertSortedListToBalancedBST.py

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[]

no_license

armsky/OnlineJudge

f4159326c92a794695cca8a162280fef32f95a2a

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refs/heads/master

2020-04-15T01:21:18.158217

2015-12-11T03:05:28

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""" Given a singly linked list where elements are sorted in ascending order, convert it to a height balanced BST. Example 2 1->2->3 => / \ 1 3 """ class ListNode(object): def __init__(self, val, next=None): self.val = val self.next = next class TreeNode: def __init__(self, val): self.val = val self.left, self.right = None, None class Solution: """ @param head: The first node of linked list. @return: a tree node """ cur = None def sortedListToBST(self, head): global cur if not head: return None size = self.getLen(head) cur = head return self.build(size) def getLen(self, a): n = 0 while a: a = a.next n += 1 return n def build(self, size): global cur if size <= 0: return None left = self.build(size/2) root = TreeNode(cur.val) cur = cur.next right = self.build(size -1 -size/2) root.left = left root.right = right return root # O(n log n) time # No need to keep a global variable current_node def sortedListToBST2(self, head): if not head: return head size = self.getLen(head) return self.construct(head, size) def construct(self, head, size): if not head or size==0: return None root = self.getNode(size/2, head) root.left = self.construct(head, size/2) root.right = self.construct(self.getNode(size/2 + 1, head), size - size/2 -1) return root def getNode(self, n, head): for i in range(n): head = head.next return head so = Solution() a = ListNode(1) a.next = ListNode(2) a.next.next = ListNode(3) print so.sortedListToBST(a).val

[ "armsky1988@gmail.com" ]

armsky1988@gmail.com

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/loqusdb/commands/cli.py

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[]

no_license

robinandeer/loqusdb

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refs/heads/master

2021-01-18T10:47:44.870986

2016-03-02T13:10:34

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null

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import click from loqusdb.log import LEVELS, init_log from loqusdb import logger, __version__ from loqusdb.plugins import MongoAdapter @click.group() @click.option('-db', '--database', default='loqusdb', show_default=True, ) @click.option('-u', '--username', type=str ) @click.option('-p', '--password', type=str ) @click.option('-port', '--port', default=27017, show_default=True, help='Specify the port where to look for the mongo database.' ) @click.option('-h', '--host', default='localhost', show_default=True, help='Specify the host where to look for the mongo database.' ) @click.option('-b', '--backend', default='mongo', show_default=True, type=click.Choice(['mongo',]), help='Specify what backend to use.' ) @click.option('-c', '--conn_host', default='mongodb://', show_default=True, help='Used for testing.' ) @click.option('-l', '--logfile', type=click.Path(exists=False), help=u"Path to log file. If none logging is "\ "printed to stderr." ) @click.option('-v', '--verbose', count=True, default=1) @click.version_option(__version__) @click.pass_context def cli(ctx, conn_host, database, username, password, port, host, verbose, logfile, backend): """loqusdb: manage a local variant count database.""" # configure root logger to print to STDERR loglevel = LEVELS.get(min(verbose,1), "INFO") init_log( logger = logger, filename = logfile, loglevel = loglevel ) # mongo uri looks like: #mongodb://[username:password@]host1[:port1][,host2[:port2],...[,hostN[:portN]]][/[database][?options]] uri = None if username and password: uri = "{0}{1}:{2}@{3}:{4}/{5}".format( conn_host, username, password, host, port, database ) logger.info('uri={0}'.format(uri)) adapter = MongoAdapter() adapter.connect( host=host, port=port, database=database, uri=uri ) ctx.obj = {} ctx.obj['db'] = database ctx.obj['user'] = username ctx.obj['password'] = password ctx.obj['port'] = port ctx.obj['host'] = host ctx.obj['adapter'] = adapter

[ "monsunas@gmail.com" ]

monsunas@gmail.com

0f70d2f0a0efc9c22f33694d5afcb0cfafa6536a

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/leetcode/1541. Minimum Insertions to Balance a Parentheses String.py

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[]

no_license

cuiy0006/Algorithms

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00fd1397b65c68a303fcf963db3e28cd35c1c003

refs/heads/master

2023-03-31T13:55:59.191857

2023-03-31T03:39:42

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class Solution: def minInsertions(self, s: str) -> int: left = 0 cnt = 0 i = 0 while i < len(s): if s[i] == '(': left += 1 i += 1 else: if i == len(s) - 1 or s[i+1] != ')': cnt += 1 i += 1 else: i += 2 if left == 0: cnt += 1 else: left -= 1 return cnt + left * 2

[ "noreply@github.com" ]

cuiy0006.noreply@github.com

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/src/config/device-manager/device_manager/ansible_base.py

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[ "Apache-2.0", "LicenseRef-scancode-warranty-disclaimer" ]

permissive

tungstenfabric/tf-controller

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refs/heads/master

2023-08-28T02:56:27.329584

2023-08-20T12:15:38

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2023-07-23T01:38:17

2019-12-31T10:24:38

C++

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# # Copyright (c) 2017 Juniper Networks, Inc. All rights reserved. # """ This file contains implementation plugin base class for device config module. The specific plugins should inherit from this class. """ import abc from builtins import object from builtins import str from .imports import import_ansible_plugins # # Base Class for all plugins. pluigns must implement all abstract methods # class AnsibleBase(object): _plugins = {} class PluginError(Exception): """Exception class to indicate plugin error.""" def __init__(self, plugin_info): """Initialize the exception with plugin info.""" self.plugin_info = plugin_info # end __init__ def __str__(self): """Provide plugin info in exception details.""" return "Ansible Plugin Error, Configuration = %s" % \ str(self.plugin_info) # end __str__ # end PluginError class PluginsRegistrationFailed(Exception): """Exception class to indicate plugin registration error.""" def __init__(self, exceptions): """Initialize the exception with nested exceptions.""" self.exceptions = exceptions # end __init__ def __str__(self): """Provide details of nested exception in exception message.""" ex_mesg = "Plugin Registrations Failed:\n" for ex in self.exceptions or []: ex_mesg += ex + "\n" return ex_mesg # end __str__ # end PluginsRegistrationFailed def __init__(self, logger): """Initialize the plugin.""" self._logger = logger self.commit_stats = { 'last_commit_time': '', 'last_commit_duration': '', 'commit_status_message': '', 'total_commits_sent_since_up': 0, } self.initialize() self.device_connect() # end __init__ # instantiate a plugin dynamically @classmethod def plugin(cls, vendor, product, params, logger): pr = params.get("physical_router") name = str(pr.physical_router_role) + ":" + \ str(vendor) + ":" + str(product) if pr.physical_router_role and vendor and product: pconf = AnsibleBase._plugins.get(pr.physical_router_role) if pconf: logger.info( "Found ansible plugin pr=%s, role/vendor/product=%s" % (pr.uuid, name)) pconf = pconf[0] # for now one only inst_cls = pconf.get('class') return inst_cls(logger, params) logger.warning( "No ansible plugin pr=%s, role/vendor/product=%s" % (pr.uuid, name)) return None # end plugin # validate plugin name def verify_plugin(self, vendor, product, role): return self.is_role_supported(role) # end verify_plugin # register all plugins with device manager @classmethod def register_plugins(cls): # make sure modules are loaded import_ansible_plugins() # register plugins, find all leaf implementation classes derived from # this class subclasses = set() work = [cls] while work: parent = work.pop() if not parent.__subclasses__(): subclasses.add(parent) continue for child in parent.__subclasses__(): if child not in subclasses: work.append(child) # register all plugins, # if there is any exception, continue to register all other plugins, # finally throw one single exception to the caller exceptions = [] for scls in subclasses or []: try: scls.register() except AnsibleBase.PluginError as e: exceptions.append(str(e)) if exceptions: raise cls.PluginsRegistrationFailed(exceptions) # end register_plugins @classmethod def register(cls, plugin_info): if not plugin_info or not plugin_info.get("roles"): raise AnsibleBase.PluginError(plugin_info) for role in plugin_info.get("roles"): AnsibleBase._plugins.setdefault( role.lower(), []).append(plugin_info) # end register @classmethod def is_role_supported(cls, role): """Check if plugin is capable of supporting role.""" return False # end is_role_supported @abc.abstractmethod def plugin_init(self, is_delete=False): """Initialize plugin.""" # end plugin_init @abc.abstractmethod def initialize(self): """Initialize local data structures.""" # end initialize def validate_device(self): return True # def validate_device @abc.abstractmethod def update(self, params): """Update plugin intialization params.""" # end update def clear(self): """Clear connections and data structures.""" self.initialize() self.device_disconnect() # end clear @abc.abstractmethod def device_connect(self): """Initialize the device connection and get the handle.""" pass # end device_connect @abc.abstractmethod def device_disconnect(self): """Delete the device connection and and reset the handle.""" pass # end device_disconnect @abc.abstractmethod def retry(self): """Retry send conf or not.""" return False # end retry @abc.abstractmethod def device_get(self, filters={}): """Retrieve configuration from device for given filter parameters.""" return {} # end device_get def device_get_config(self, filters={}): """Retrieve entire device current configuration.""" return {} # end device_get_config @abc.abstractmethod def get_commit_stats(self): """Return Commit Statistics if any.""" return self.commit_stats # end device_get @abc.abstractmethod def push_conf(self, feature_configs=None, is_delete=False): """Push config to device.""" return 0 # end push_conf @abc.abstractmethod def get_service_status(self, service_params={}): """Get service status for a given service.""" return {} # end get_service_status # end AnsibleBase

[ "andrey-mp@yandex.ru" ]

andrey-mp@yandex.ru

958e29edf8b1e663aabc6944aef2aae04ecbf3d5

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/PE/pe0493.py

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[]

no_license

196884/Python

edd0234fd72a40d7a0b3310776edcaa8bda74478

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refs/heads/master

2016-09-06T19:26:19.860746

2015-11-09T00:09:23

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from mpmath import * mp.dps = 30 def sortFn((a, b)): return a def evolvePos(c, i): # c is the configuration # i is the index chosen r = list(c) (ni, ki) = c[i] f = ni * ki if ki > 1: r[i] = (ni, ki-1) else: r.pop(i) if ni > 1: n = len(r) found = False for i in range(0, n): if r[i][0] == ni - 1: r[i] = (r[i][0], r[i][1]+1) found = True if not found: r.append((ni-1, 1)) r.sort(key = sortFn) return (f, tuple(r)) def handlePick(d, total): r = dict() for c, proba in d.iteritems(): nc = len(c) for i in range(0, nc): (f, cb) = evolvePos(c, i) thisProba = proba * mpf(f) / mpf(total) prevProba = r.get(cb, mpf(0)) r[cb] = prevProba + thisProba return r def nbColors(c): l = list(c) (n, k) = l[-1] if n == 10: return 7 - k else: return 7 def solve(): # Bruteforcing it... d = dict() d[((9,1),(10,6))] = mpf(1) total = 69 for k in range(0, 19): d = handlePick(d, total) total -= 1 r = mpf(0) for c, p in d.iteritems(): n = nbColors(c) r = r + mpf(n) * p return r if __name__ == "__main__": result = solve() print "Result: %s" % result

[ "regis.dupont+git@m4x.org" ]

regis.dupont+git@m4x.org

9ad0fc7bf19e3d9004fa97afe0d0cfd173119ba0

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[]

no_license

kussy-tessy/atcoder

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# print('input >>') N = int(input()) P = list(map(int,(input().split()))) ans = 0 now = P[0] for p in P: if now >= p: ans += 1 now = p # print('-----output-----') print(ans)

[ "teppei04285000@gmail.com" ]

teppei04285000@gmail.com

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/vega/common/dag.py

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permissive

huawei-noah/vega

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2023-09-01T20:16:28.746745

2023-02-15T09:36:59

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2023-02-15T09:37:01

2020-06-20T08:20:06

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py

"""DAG class.""" from collections import deque from collections import OrderedDict class DAG: """DAG.""" def __init__(self): """Init DAG.""" self.nodes = OrderedDict() def add_node(self, node): """Add node.""" if node not in self.nodes: self.nodes[node] = set() def remove_node(self, node): """Remove node.""" if node in self.nodes: self.nodes.pop(node) for pre_node, nodes in iter(self.nodes.items()): if node in nodes: nodes.remove(node) def add_edge(self, pre_node, node): """Add edge.""" if pre_node not in self.nodes or node not in self.nodes: return self.nodes[pre_node].add(node) def remove_edge(self, pre_node, node): """Remove edge.""" if pre_node in self.nodes and node in self.nodes[pre_node]: self.nodes[pre_node].remove(node) def from_dict(self, dict_value): """Construct DAG from dict.""" self.nodes = OrderedDict() for node in iter(dict_value.keys()): self.add_node(node) for pre_node, nodes in iter(dict_value.items()): if not isinstance(nodes, list): raise TypeError('dict values must be lists') for node in nodes: self.add_edge(pre_node, node) def next_nodes(self, node): """Get all successor of the node.""" return list(self.nodes[node]) def pre_nodes(self, node): """Get all predecessor of the node.""" return [item for item in self.nodes if node in self.nodes[item]] def topological_sort(self): """Topological sort.""" in_degree = {node: 0 for node in self.nodes} out_degree = {node: 0 for node in self.nodes} for node in self.nodes: out_degree[node] = len(node) for next_node in self.nodes[node]: in_degree[next_node] += 1 ret = [] stack = deque() for node in in_degree: if in_degree[node] == 0: stack.append(node) while len(stack) > 0: node = stack.pop() for item in self.nodes[node]: in_degree[item] -= 1 if in_degree[item] == 0: stack.append(item) ret.append(node) if len(ret) != len(self.nodes): raise ValueError("Not a directed acyclic graph") return ret def ind_nodes(self): """Independent nodes.""" in_degree = {node: 0 for node in self.nodes} for node in self.nodes: for next_node in self.nodes[node]: in_degree[next_node] += 1 ret = set(node for node in self.nodes if in_degree[node] == 0) return ret def size(self): """Return the size of graph.""" return len(self.nodes)

[ "zhangjiajin@huawei.com" ]

zhangjiajin@huawei.com

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/sdk/python/lib/test/langhost/resource_thens/test_resource_thens.py

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permissive

orionstudt/pulumi

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refs/heads/master

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# Copyright 2016-2021, Pulumi Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from os import path from ..util import LanghostTest class ResourceThensTest(LanghostTest): """ Test that tests Pulumi's ability to track dependencies between resources. ResourceA has an (unknown during preview) output property that ResourceB depends on. In all cases, the SDK must inform the engine that ResourceB depends on ResourceA. When not doing previews, ResourceB has a partial view of ResourceA's properties. """ def test_resource_thens(self): self.run_test( program=path.join(self.base_path(), "resource_thens"), expected_resource_count=2) def register_resource(self, _ctx, _dry_run, ty, name, _resource, _dependencies, _parent, _custom, protect, _provider, _property_deps, _delete_before_replace, _ignore_changes, _version, _import, _replace_on_changes): if ty == "test:index:ResourceA": self.assertEqual(name, "resourceA") self.assertDictEqual(_resource, {"inprop": 777, "inprop_2": 42}) urn = self.make_urn(ty, name) res_id = "" props = {} if not _dry_run: res_id = name props["outprop"] = "output yeah" return { "urn": urn, "id": res_id, "object": props } if ty == "test:index:ResourceB": self.assertEqual(name, "resourceB") self.assertListEqual(_dependencies, ["test:index:ResourceA::resourceA"]) if _dry_run: self.assertDictEqual(_resource, { # other_in is unknown, so it is not in the dictionary. # other_out is unknown, so it is not in the dictionary. # other_id is also unknown so it is not in the dictionary }) else: self.assertDictEqual(_resource, { "other_in": 777, "other_out": "output yeah", "other_id": "resourceA", }) res_id = "" if not _dry_run: res_id = name return { "urn": self.make_urn(ty, name), "id": res_id, "object": {} } self.fail(f"unknown resource type: {ty}")

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orionstudt.noreply@github.com

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/python/problems/array/remove_duplicates_in_place_sorted_array.py

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[]

no_license

santhosh-kumar/AlgorithmsAndDataStructures

edc1a296746e2d2b0e1d4c748d050fe12af7b65f

11f4d25cb211740514c119a60962d075a0817abd

refs/heads/master

2022-11-15T00:22:53.930170

2020-07-10T03:31:30

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""" Remove Duplicates In-Place For a Sorted Array Given a sorted array, the task is to remove the duplicate elements from the array. Examples: Input : arr[] = {2, 2, 2, 2, 2} Output : arr[] = {2} new size = 1 Input : arr[] = {1, 2, 2, 3, 4, 4, 4, 5, 5} Output : arr[] = {1, 2, 3, 4, 5} new size = 5 """ from common.problem import Problem class RemoveDuplicatesInPlaceSortedArray(Problem): """ RemoveDuplicatesInPlaceSortedArray """ PROBLEM_NAME = "RemoveDuplicatesInPlaceSortedArray" def __init__(self, input_list): """RemoveDuplicatesInPlaceSortedArray Args: input_list: Contains a list of integers Returns: None Raises: None """ assert (len(input_list) > 0) super().__init__(self.PROBLEM_NAME) self.input_list = input_list def solve(self): """Solve the problem Note: The O(n) runtime and O(1) (space). Args: Returns: integer Raises: None """ print("Solving {} problem ...".format(self.PROBLEM_NAME)) i = 0 while i < len(self.input_list): j = i + 1 # iterate till we find the next non-duplicate and an increasing value while j < len(self.input_list) and ( self.input_list[i] == self.input_list[j] or self.input_list[i] > self.input_list[j]): j = j + 1 # swap with the next position if within the allowed size if (i + 1) < len(self.input_list) and j < len(self.input_list): self.input_list[i + 1], self.input_list[j] = self.input_list[j], self.input_list[i + 1] else: # we have reached the end w.r.t. j and hence return now return i i = i + 1 return i

[ "santhoshkumar.sunderrajan@gmail.com" ]

santhoshkumar.sunderrajan@gmail.com

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no_license

qyguo/makegridpacks

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refs/heads/master

2020-03-31T22:08:16.978758

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#!/usr/bin/env python import argparse from makegridpacks import * if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--dry-run", "-n", action="store_true", help="don't send anything to McM") parser.add_argument("--times", "-t", action="store_true", help="get the times from McM for all requests") args = parser.parse_args() with RequestQueue() as queue: for productionmode in "ggH", "VBF", "WplusH", "WminusH", "ZH", "ttH": for decaymode in "4l", "2l2nu", "2l2q": for mass in getmasses(productionmode, decaymode): sample = POWHEGJHUGenMassScanMCSample(productionmode, decaymode, mass) if (sample.needsupdate or args.times) and sample.prepid and os.path.exists(sample.cvmfstarball): sample.gettimepereventfromMcM() print sample if sample.needsupdate and not args.dry_run: queue.addrequest(sample, useprepid=True)

[ "jroskes1@jhu.edu" ]

jroskes1@jhu.edu

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/packages/pyright-internal/src/tests/samples/expressions8.py

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[ "LicenseRef-scancode-generic-cla", "MIT" ]

permissive

isabella232/pyright

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refs/heads/master

2023-03-13T05:04:51.852745

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py

# This sample verifies that binary expressions like "less than" # work if the operands are constrained TypeVars. from abc import abstractmethod from typing import Protocol, TypeVar _T = TypeVar("_T") class ComparableTo(Protocol[_T]): @abstractmethod def __lt__(self, x: _T) -> bool: pass def custom_compare(a: ComparableTo[_T], b: _T) -> bool: return a < b custom_compare("first", "second") custom_compare(3, 2) # This should generate an error. custom_compare(3, "hi")

[ "erictr@microsoft.com" ]

erictr@microsoft.com

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/backend/api/errors.py

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[]

no_license

toyscript/toyscript

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2021-06-19T08:40:39

2021-04-21T03:32:40

JavaScript

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py

class MovieDoesNotExist(Exception): def __init__(self, message="해당 영화를 찾을 수 없습니다.", status=404): self.message = message self.status = status

[ "swamys@naver.com" ]

swamys@naver.com

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/ghidra9.2.1_pyi/ghidra/program/database/data/CategoryDBAdapter.pyi

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permissive

kohnakagawa/ghidra_scripts

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2023-03-25T08:25:16.842142

2021-03-18T13:31:40

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import java.lang class CategoryDBAdapter(object): def __init__(self): ... def equals(self, __a0: object) -> bool: ... def getClass(self) -> java.lang.Class: ... def hashCode(self) -> int: ... def notify(self) -> None: ... def notifyAll(self) -> None: ... def toString(self) -> unicode: ... @overload def wait(self) -> None: ... @overload def wait(self, __a0: long) -> None: ... @overload def wait(self, __a0: long, __a1: int) -> None: ...

[ "tsunekou1019@gmail.com" ]

tsunekou1019@gmail.com

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/5 - Notebooks e Data/1 - Análises numéricas/Arquivos David/Atualizados/logDicas-master/data/2019-1/226/users/4137/codes/1575_1334.py

4a02531f8dd05fe3a3c2859b82ad6825f61ec54d

[]

no_license

JosephLevinthal/Research-projects

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refs/heads/master

2022-07-31T06:43:02.686109

2020-05-23T00:24:26

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py

print("Adicao: ", 5 + 3) print("Subtracao: ", 10 - 2) print("Multiplicacao: ", 2*4) print("Divisao: ", 16/2) print("Resto: ", 16//2 ) print("Potenciacao: ", 2 ** 3)

[ "jvlo@icomp.ufam.edu.br" ]

jvlo@icomp.ufam.edu.br

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/pyrolite/mineral/transform.py

051b6d30d068c1f55e1c32d90c780845f6c5592b

[ "BSD-3-Clause", "MIT" ]

permissive

JustinGOSSES/pyrolite

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refs/heads/master

2020-12-23T11:26:55.078871

2020-01-10T09:03:22

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2020-01-30T04:08:52

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py

import pandas as pd import numpy as np import periodictable as pt from ..util.pd import to_frame import logging logging.getLogger(__name__).addHandler(logging.NullHandler()) logger = logging.getLogger(__name__) def formula_to_elemental(formula, weight=True): """Convert a periodictable.formulas.Formula to elemental composition.""" formula = pt.formula(formula) fmass = formula.mass composition = {} if weight: for a, c in formula.atoms.items(): composition[str(a)] = (c * a.mass) / fmass else: atoms = sum([c for a, c in formula.atoms.items()]) for a, c in formula.atoms.items(): composition[str(a)] = c / atoms return composition def merge_formulae(formulas): """ Combine multiple formulae into one. Particularly useful for defining oxide mineral formulae. Parameters ----------- formulas: iterable Iterable of multiple formulae to merge into a single larger molecular formulae. """ molecule = pt.formula("") for f in formulas: molecule += pt.formula(f) return molecule def parse_composition(composition): """ Parse a composition to provide an ionic elemental version in the form of a pandas.Series. Currently accepts pandas.Series, periodictable.formulas.Formula and structures which will directly convert to pandas.Series (list of tuples, dict). Parameters ----------- composition : :class:`pandas.Series` | :class:`periodictable.formulas.Formula` Formulation of composition to parse. """ if composition is not None: if isinstance(composition, pd.Series): # convert to molecular oxides, then to formula, then to wt% elemental components = [pt.formula(c) for c in composition.index] values = composition.values formula = merge_formulae( [v / c.mass * c for v, c in zip(values, components)] ) return pd.Series(formula_to_elemental(formula)) elif isinstance(composition, pt.formulas.Formula): return pd.Series(formula_to_elemental(composition)) else: return parse_composition(pd.Series(composition)) def recalc_cations( df, ideal_cations=4, ideal_oxygens=6, Fe_species=["FeO", "Fe", "Fe2O3"], oxygen_constrained=False, ): """ Recalculate a composition to a.p.f.u. """ assert ideal_cations is not None or ideal_oxygens is not None # if Fe2O3 and FeO are specified, calculate based on oxygen moles = to_frame(df) moles = moles.div([pt.formula(c).mass for c in moles.columns]) moles = moles.where(~np.isclose(moles, 0.0), np.nan) # determine whether oxygen is an open or closed system count_iron_species = np.array([i in moles.columns for i in Fe_species]).sum() oxygen_constrained = oxygen_constrained if not oxygen_constrained: if count_iron_species > 1: # check that only one is defined oxygen_constrained = ( count_iron_species - pd.isnull(moles.loc[:, Fe_species]).all(axis=1).sum() ) > 1 if oxygen_constrained: logger.info("Multiple iron species defined. Calculating using oxygen.") else: logger.info("Single iron species defined. Calculating using cations.") components = moles.columns as_oxides = len(list(pt.formula(components[0]).atoms)) > 1 schema = [] # if oxygen_constrained: # need to specifically separate Fe2 and Fe3 if as_oxides: parts = [pt.formula(c).atoms for c in components] for p in parts: oxygens = p[pt.O] other_components = [i for i in list(p) if not i == pt.O] assert len(other_components) == 1 # need to be simple oxides other = other_components[0] charge = oxygens * 2 / p[other] ion = other.ion[charge] schema.append({str(ion): p[other], "O": oxygens}) else: # elemental composition parts = components for part in parts: p = list(pt.formula(part).atoms)[0] if p.charge != 0: charge = p.charge else: charge = p.default_charge schema.append({p.ion[charge]: 1}) ref = pd.DataFrame(data=schema) ref.columns = ref.columns.map(str) ref.index = components cation_masses = {c: pt.formula(c).mass for c in ref.columns} oxygen_index = [i for i in ref.columns if "O" in i][0] ref = ref.loc[:, [i for i in ref.columns if not i == oxygen_index] + [oxygen_index]] moles_ref = ref.copy(deep=True) moles_ref.loc[:, :] = ( ref.values * moles.T.values ) # this works for series, not for frame moles_O = moles_ref[oxygen_index].sum() moles_cations = ( moles_ref.loc[:, [i for i in moles_ref.columns if not i == oxygen_index]] .sum() .sum() ) if not oxygen_constrained: # oxygen unquantified, try to calculate using cations scale = ideal_cations / moles_cations else: # oxygen quantified, try to calculate using oxygen scale = ideal_oxygens / moles_O moles_ref *= scale return moles_ref.sum(axis=0)

[ "morgan.j.williams@hotmail.com" ]

morgan.j.williams@hotmail.com

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/term-1/AIND-Recognizer/asl_utils.py

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[]

no_license

SteadBytes/ai-nanodegree

01d7c707456585fdf39a83f07ac4def90264324d

ba260106dacaaba675a41558e96b2a0998685482

refs/heads/master

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2018-04-04T15:39:57

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from asl_data import SinglesData, WordsData import numpy as np from IPython.core.display import display, HTML RAW_FEATURES = ['left-x', 'left-y', 'right-x', 'right-y'] GROUND_FEATURES = ['grnd-rx', 'grnd-ry', 'grnd-lx', 'grnd-ly'] def show_errors(guesses: list, test_set: SinglesData): """ Print WER and sentence differences in tabular form :param guesses: list of test item answers, ordered :param test_set: SinglesData object :return: nothing returned, prints error report WER = (S+I+D)/N but we have no insertions or deletions for isolated words so WER = S/N """ S = 0 N = len(test_set.wordlist) num_test_words = len(test_set.wordlist) if len(guesses) != num_test_words: print("Size of guesses must equal number of test words ({})!".format( num_test_words)) for word_id in range(num_test_words): if guesses[word_id] != test_set.wordlist[word_id]: S += 1 print("\n**** WER = {}".format(float(S) / float(N))) print("Total correct: {} out of {}".format(N - S, N)) print('Video Recognized Correct') print('=====================================================================================================') for video_num in test_set.sentences_index: correct_sentence = [test_set.wordlist[i] for i in test_set.sentences_index[video_num]] recognized_sentence = [guesses[i] for i in test_set.sentences_index[video_num]] for i in range(len(recognized_sentence)): if recognized_sentence[i] != correct_sentence[i]: recognized_sentence[i] = '*' + recognized_sentence[i] print('{:5}: {:60} {}'.format(video_num, ' '.join( recognized_sentence), ' '.join(correct_sentence))) def getKey(item): return item[1] def train_all_words(training: WordsData, model_selector): """ train all words given a training set and selector :param training: WordsData object (training set) :param model_selector: class (subclassed from ModelSelector) :return: dict of models keyed by word """ sequences = training.get_all_sequences() Xlengths = training.get_all_Xlengths() model_dict = {} for word in training.words: model = model_selector(sequences, Xlengths, word, n_constant=3).select() model_dict[word] = model return model_dict def combine_sequences(split_index_list, sequences): ''' concatenate sequences referenced in an index list and returns tuple of the new X,lengths useful when recombining sequences split using KFold for hmmlearn :param split_index_list: a list of indices as created by KFold splitting :param sequences: list of feature sequences :return: tuple of list, list in format of X,lengths use in hmmlearn ''' sequences_fold = [sequences[idx] for idx in split_index_list] X = [item for sublist in sequences_fold for item in sublist] lengths = [len(sublist) for sublist in sequences_fold] return X, lengths def putHTML(color, msg): source = """<font color={}>{}</font><br/>""".format(color, msg) return HTML(source) def feedback(passed, failmsg='', passmsg='Correct!'): if passed: return putHTML('green', passmsg) else: return putHTML('red', failmsg) def test_features_tryit(asl): print('asl.df sample') display(asl.df.head()) sample = asl.df.ix[98, 1][GROUND_FEATURES].tolist() correct = [9, 113, -12, 119] failmsg = 'The values returned were not correct. Expected: {} Found: {}'.format( correct, sample) return feedback(sample == correct, failmsg) def test_std_tryit(df_std): print('df_std') display(df_std) sample = df_std.ix['man-1'][RAW_FEATURES] correct = [15.154425, 36.328485, 18.901917, 54.902340] failmsg = 'The raw man-1 values returned were not correct.\nExpected: {} for {}'.format( correct, RAW_FEATURES) return feedback(np.allclose(sample, correct, .001), failmsg)

[ "=" ]

=

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/scripts/bandplot

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[]

no_license

materialsvirtuallab/phonopy

62117e757f98447de2b247e4b6aa186b0b141aab

97888bac864f8d8e5eee799b2eeef232e627f018

refs/heads/master

2020-12-01T03:09:31.707376

2014-09-08T15:42:54

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#!/usr/bin/env python # Copyright (C) 2011 Atsushi Togo # All rights reserved. # # This file is part of phonopy. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions # are met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in # the documentation and/or other materials provided with the # distribution. # # * Neither the name of the phonopy project nor the names of its # contributors may be used to endorse or promote products derived # from this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS # FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE # COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, # INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, # BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT # LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN # ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. import sys import numpy as np try: import yaml except ImportError: print "You need to install python-yaml." exit(1) try: from yaml import CLoader as Loader from yaml import CDumper as Dumper except ImportError: from yaml import Loader, Dumper from phonopy.units import VaspToTHz def get_plot_data(data): segment_positions = [] frequencies = [] distances = [] npoints = data['nqpoint'] / data['npath'] for j, v in enumerate(data['phonon']): frequencies.append([f['frequency'] for f in v['band']]) distances.append(v['distance']) if j % npoints == 0: segment_positions.append(v['distance']) return distances, frequencies, segment_positions # Parse options from optparse import OptionParser parser = OptionParser() parser.set_defaults(factor=1.0, f_max=None, f_min=None, is_gnuplot=False, is_points=False, is_vertial_line=False, output_filename=None, labels=None, show_legend=False, title=None) parser.add_option("--factor", dest="factor", type="float", help="Conversion factor to favorite frequency unit") parser.add_option("--fmax", dest="f_max", type="float", help="Maximum frequency plotted") parser.add_option("--fmin", dest="f_min", type="float", help="Minimum frequency plotted") parser.add_option("--gnuplot", dest="is_gnuplot", action="store_true", help="Output in gnuplot data style") parser.add_option("--legend", dest="show_legend", action="store_true", help="Show legend") parser.add_option("--line", "-l", dest="is_vertial_line", action="store_true", help="Vertial line is drawn at between paths") parser.add_option("-o", "--output", dest="output_filename", action="store", type="string", help="Output filename of PDF plot") parser.add_option("--labels", dest="labels", action="store", type="string", help="Show labels at band segments") parser.add_option("--points", dest="is_points", action="store_true", help="Draw points") parser.add_option("-t", "--title", dest="title", action="store", type="string", help="Title of plot") (options, args) = parser.parse_args() if options.output_filename: import matplotlib matplotlib.use('Agg') if not options.is_gnuplot: import matplotlib.pyplot as plt if options.labels: from matplotlib import rc rc('text', usetex=True) colors = ['b-', 'g-', 'r-', 'c-', 'm-', 'y-', 'k-', 'b--', 'g--', 'r--', 'c--', 'm--', 'y--', 'k--'] if options.is_points: colors = [x + 'o' for x in colors] count = 0 if len(args) == 0: filenames = ['band.yaml'] else: filenames = args if options.is_gnuplot: print "# distance frequency (bands are separated by blank lines)" for i, filename in enumerate(filenames): string = open(filename).read() data = yaml.load(string, Loader=Loader) distances, frequencies, segment_positions = get_plot_data(data) if options.is_gnuplot: print "# segments:", for v in segment_positions: print "%10.8f" % v, print "%10.8f" % distances[-1] elif options.is_vertial_line and len(filenames) == 1: for v in segment_positions[1:]: plt.axvline(x=v, linewidth=0.5, color='b') for j, freqs in enumerate(np.array(frequencies).T): if options.is_gnuplot: for d, f in zip(distances, freqs * options.factor): print d,f print else: if j==0: plt.plot(distances, freqs * options.factor, colors[i], label=filename) else: plt.plot(distances, freqs * options.factor, colors[i]) if options.is_gnuplot: print if not options.is_gnuplot: plt.ylabel('Frequency') plt.xlabel('Wave vector') plt.xlim(distances[0], distances[-1]) if not options.f_max == None: plt.ylim(ymax = options.f_max) if not options.f_min == None: plt.ylim(ymin = options.f_min) plt.axhline(y=0, linestyle=':', linewidth=0.5, color='b') if len(filenames) == 1: xticks = segment_positions + [distances[-1]] if options.labels: labels = [x for x in options.labels.split()] if len(labels)==len(xticks): plt.xticks(xticks, labels) else: print "Numbers of labels and band segments don't match." sys.exit(1) else: plt.xticks(xticks, [''] * len(xticks)) else: plt.xticks([]) if not options.title == None: plt.title(options.title) if options.show_legend: plt.legend() if not options.output_filename == None: plt.rcParams['pdf.fonttype'] = 42 plt.rcParams['font.family'] = 'serif' plt.savefig(options.output_filename) else: plt.show()

[ "atz.togo@gmail.com" ]

atz.togo@gmail.com

08c4ff249af2ede845061c68aa550a412a32f068

b3586235dc1e1acbd49fab996f581269a808480b

/sistema/producao/migrations/0090_auto_20200419_1946.py

05ec1f4442faf22924833cefc45f46cace20c101

[]

no_license

gonfersilva/Sistema

37ad1cd03dfbb7889fa0b0367c6ebd9044712ae3

4c6d9ade22040972efbe892eae0130939d7b5c46

refs/heads/master

2021-10-23T23:21:51.262723

2021-10-13T19:45:49

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py

# Generated by Django 2.2.7 on 2020-04-19 18:46 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('producao', '0089_reciclado_timestamp_edit'), ] operations = [ migrations.AlterField( model_name='reciclado', name='timestamp_edit', field=models.DateTimeField(), ), ]

[ "goncalo.silva@elastictek.com" ]

goncalo.silva@elastictek.com

3eec27e2dd17dd5a63596c4c056f129c7fd1b671

6e4f493329341661d869d9c5a8dd21c1baa6a621

/science/Optics/mirrorformula_cnc/mirrorformula_cnc.py

7b65c4ba9fd8bfe303a01feb13b81077b5ec018f

[]

no_license

yujinee/scimat2

8dd03e1ba003715dd910d7e6a086b6f596a7f23b

98712c061b9ce5337b3da5b421926de4aaefbe67

refs/heads/main

2023-08-28T01:57:53.482632

2021-10-22T17:30:10

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null

UTF-8

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py

import random # An object is placed at u cm in front of a concave mirror of focal length f cm. Find at what distance image is formed and its nature. # An image is formed by a concave mirror of focal length f cm at a distance of v cm in front of it. Find at what distance object is placed in front of mirror. # An image is formed by a concave mirror of focal length f cm at a distance of v cm behind it. Find at what distance object is placed in front of mirror. # An object is placed at u cm in front of a concave mirror. Image is formed at a distance of v cm in front of it. Find the focal length of the mirror. # An object is placed at u cm in front of a concave mirror. Image is formed at a distance of v cm behind it. Find the focal length of the mirror. # All variants of 1/f = 1/v + 1/u for concave mirror qns = open('./questions.txt', 'w') ans = open('./answers.txt','w') no_of_samples = 3000000 def calculation_1(u, f) : return round((u*f)/(u-f),1) def calculation_2(u, f) : return round((u*f)/(f-u),1) def calculation_3(v, f) : return round((v*f)/(v-f),1) def calculation_4(v, f) : return round((v*f)/(v+f),1) def calculation_5(u, v) : return round((u*v)/(u+v),1) def calculation_6(u, v) : return round((u*v)/(v-u),1) def type1() : f = random.randint(1,800) u = random.randint(f+1,f+1200) q = "An object is placed at " + str(u) + " cm in front of a concave mirror of focal length " + str(f) + " cm. Find at what distance image is formed and its nature.\n" v = str(calculation_1(u,f)) + "cm and real\n" return q,v def type2() : u = random.randint(1,1000) f = random.randint(u+1,u+1000) q = "An object is placed at " + str(u) + " cm in front of a concave mirror of focal length " + str(f) + " cm. Find at what distance image is formed and its nature.\n" v = str(calculation_2(u,f)) + "cm and virtual\n" return q,v def type3() : f = random.randint(1,800) v = random.randint(f+1,f+1200) q = "An image is formed by a concave mirror of focal length " + str(f) + " cm at a distance of " + str(v) + " cm in front of it. Find at what distance object is placed in front of mirror.\n" u = str(calculation_3(v,f)) + "cm\n" return q,u def type4() : f = random.randint(1,1000) v = random.randint(1,1000) q = "An image is formed by a concave mirror of focal length " + str(f) + " cm at a distance of " + str(v) + " cm behind it. Find at what distance object is placed in front of mirror.\n" u = str(calculation_4(v,f)) + "cm\n" return q,u def type5() : u = random.randint(1,1000) v = random.randint(1,1000) q = "An object is placed at " + str(u) + " cm in front of a concave mirror. Image is formed at a distance of " + str(v) + " cm in front of it. Find the focal length of the mirror.\n" f = str(calculation_5(u,v)) + "cm\n" return q,f def type6() : u = random.randint(1,1000) v = random.randint(u+1,u+1000) q = "An object is placed at " + str(u) + " cm in front of a concave mirror. Image is formed at a distance of " + str(v) + " cm behind it. Find the focal length of the mirror.\n" f = str(calculation_6(u,v)) + "cm\n" return q,f for i in range(no_of_samples): types = random.randint(1,6) if types == 1: ques,answer = type1() elif types == 2: ques,answer = type2() elif types == 3: ques,answer = type3() elif types == 4: ques,answer = type4() elif types == 5: ques,answer = type5() elif types == 6: ques,answer = type6() qns.write(ques) ans.write(answer) qns.close() ans.close()

[ "snehith.chatakonda@plivo.com" ]

snehith.chatakonda@plivo.com

2c904b54db472eb9fcd58830d3373a19f91eec34

252d023b55575f3d25fb9ab8faa92084479244b3

/indexpy/http/middleware.py

4d296400f4c12251c08bdfc25b053ada44efdb7b

[ "Apache-2.0" ]

permissive

sangensong/index.py

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4b4cfd0aeef67986f484e3f5f06544b8a2cb7699

refs/heads/master

2023-03-03T12:24:00.468335

2021-02-13T14:46:33

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py

from __future__ import annotations import typing from indexpy.concurrency import keepasync if typing.TYPE_CHECKING: from .request import Request from .responses import Response, convert_response MiddlewareMeta = keepasync("process_request", "process_response", "process_exception") class MiddlewareMixin(metaclass=MiddlewareMeta): # type: ignore mounts: typing.Sequence[typing.Callable] = () def __init__(self, get_response: typing.Callable) -> None: self.get_response = self.mount_middleware(get_response) def mount_middleware(self, get_response: typing.Callable) -> typing.Callable: for middleware in reversed(self.mounts): get_response = middleware(get_response) return get_response async def __call__(self, request: Request) -> Response: response = await self.process_request(request) if response is None: try: response = await self.get_response(request) except Exception as exc: response = await self.process_exception(request, exc) if response is None: raise exc response = convert_response(response) response = await self.process_response(request, response) return response async def process_request(self, request: Request) -> typing.Optional[typing.Any]: """ Must return None, otherwise return the value as the result of this request. """ async def process_response(self, request: Request, response: Response) -> Response: return response async def process_exception( self, request: Request, exception: Exception ) -> typing.Optional[typing.Any]: """ If return None, will raise exception. Otherwise return the value as the result of this request. """

[ "me@abersheeran.com" ]

me@abersheeran.com

8a5b454d7307b0ef888c3ccc7dbcc2a78b49ce39

53fab060fa262e5d5026e0807d93c75fb81e67b9

/backup/user_136/ch25_2020_10_04_03_54_44_850472.py

7687d7e86cce8171d9932c23f11bbf1f7f0be68e

[]

no_license

gabriellaec/desoft-analise-exercicios

b77c6999424c5ce7e44086a12589a0ad43d6adca

01940ab0897aa6005764fc220b900e4d6161d36b

refs/heads/main

2023-01-31T17:19:42.050628

2020-12-16T05:21:31

306,735,108

0

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UTF-8

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py

import math g= 9.8 def distancia(v, o): k= math.sin h= (180/math.pi)*o d= ((v**2)*k(2*h))/g if d>=99 and d<=101: print ('Acertou!') elif d>101: print ('Muito longe') elif d<99: print ('Muito perto')

[ "you@example.com" ]

you@example.com

14bc887b39a0ef1763ad3da22c7d9239cd101b13

3803b6364290e21061e8c0c97d3e9c0b204c50fc

/gae_main.py

7533cd5125638887f7837401aa16cc45aa1c6a9d

[]

no_license

t0ster/django-gae-buildout-skeleton

5a146b94d35ff466b9ee5e981c0ecdfb31eb28b5

71c3553b661fbd58937797d352f1a337c1641b0a

refs/heads/master

2020-05-27T06:28:21.745403

2011-06-27T19:24:21

1,962,053

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null

UTF-8

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py

import sys from os.path import dirname, abspath, join PROJECT_DIR = join(abspath(dirname(__file__)), "testapp") if PROJECT_DIR not in sys.path or sys.path.index(PROJECT_DIR) > 0: while PROJECT_DIR in sys.path: sys.path.remove(PROJECT_DIR) sys.path.insert(0, PROJECT_DIR) import djangoappengine.main.main djangoappengine.main.main.main()

[ "roman@bravetstudio.com" ]

roman@bravetstudio.com

39b77ac51e19c5f33bf7b51871b0966c27a13121

141b42d9d72636c869ff2ce7a2a9f7b9b24f508b

/myvenv/Lib/site-packages/phonenumbers/data/region_SC.py

b0e98d3e74585ab661b7fde30f9021a9aaefbf4c

[ "BSD-3-Clause" ]

permissive

Fa67/saleor-shop

105e1147e60396ddab6f006337436dcbf18e8fe1

76110349162c54c8bfcae61983bb59ba8fb0f778

refs/heads/master

2021-06-08T23:51:12.251457

2018-07-24T08:14:33

168,561,915

1

0

BSD-3-Clause

2021-04-18T07:59:12

2019-01-31T17:00:39

Python

UTF-8

Python

false

971

py

"""Auto-generated file, do not edit by hand. SC metadata""" from ..phonemetadata import NumberFormat, PhoneNumberDesc, PhoneMetadata PHONE_METADATA_SC = PhoneMetadata(id='SC', country_code=248, international_prefix='0(?:[02]|10?)', general_desc=PhoneNumberDesc(national_number_pattern='[24689]\\d{5,6}', possible_length=(7,)), fixed_line=PhoneNumberDesc(national_number_pattern='4[2-46]\\d{5}', example_number='4217123', possible_length=(7,)), mobile=PhoneNumberDesc(national_number_pattern='2[5-8]\\d{5}', example_number='2510123', possible_length=(7,)), toll_free=PhoneNumberDesc(national_number_pattern='8000\\d{3}', example_number='8000000', possible_length=(7,)), voip=PhoneNumberDesc(national_number_pattern='(?:64\\d|971)\\d{4}', example_number='6412345', possible_length=(7,)), preferred_international_prefix='00', number_format=[NumberFormat(pattern='(\\d)(\\d{3})(\\d{3})', format='\\1 \\2 \\3', leading_digits_pattern=['[246]'])])

[ "gruzdevasch@gmail.com" ]

gruzdevasch@gmail.com

410c72545e00ff4b20fa2686e2cb0a81edbfd253

0cea2eef085a16792b0722b5ea1ccecf22ebf56a

/emu/tests/test_wps_wordcounter.py

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[ "Apache-2.0" ]

permissive

Ouranosinc/emu

6931657412c2a3412e9548b2ad80a91c7362e79b

f3b92f44555b9e85f8c62e8e34a8a59d420a1c67

refs/heads/master

2021-05-04T02:00:59.517729

2016-11-18T17:48:31

71,271,528

0

Apache-2.0

2020-11-11T03:21:22

2016-10-18T17:03:47

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UTF-8

Python

false

550

py

import pytest from pywps import Service from emu.tests.common import client_for, assert_response_success from emu.processes.wps_wordcounter import WordCounter @pytest.mark.online def test_wps_wordcount(): client = client_for(Service(processes=[WordCounter()])) datainputs = "text={0}".format( "https://en.wikipedia.org/wiki/Web_Processing_Service") resp = client.get( service='wps', request='execute', version='1.0.0', identifier='wordcounter', datainputs=datainputs) assert_response_success(resp)

[ "ehbrecht@dkrz.de" ]

ehbrecht@dkrz.de

ddc2256caa53e5da02d9ef82936e44811ede8002

71e50200ed8fec2bd567b060d52b6ab5c216dc08

/app/auth/forms.py

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[ "MIT" ]

permissive

ThiraTheNerd/the_blog

5361d7b92be857e4576d3d96e64c176539ff7cba

3edd51b2507726b4339f3b59b95133f9e2005700

refs/heads/master

2023-06-10T15:16:06.112694

2021-06-27T07:59:02

379,469,459

0

null

UTF-8

Python

false

1,210

py

from flask_wtf import FlaskForm from wtforms import StringField,PasswordField,SubmitField,ValidationError,BooleanField from wtforms.validators import Required,Email,EqualTo from ..models import User class RegistrationForm(FlaskForm): email = StringField('Your Email Address',validators=[Required(),Email()]) username = StringField('Enter your username',validators = [Required()]) password = PasswordField('Password',validators = [Required(), EqualTo('password_confirm',message = 'Passwords must match')]) password_confirm = PasswordField('Confirm Passwords',validators = [Required()]) submit = SubmitField('Sign Up') def validate_email(self,data_field): if User.query.filter_by(email =data_field.data).first(): raise ValidationError('There is an account with that email') def validate_username(self,data_field): if User.query.filter_by(username = data_field.data).first(): raise ValidationError('That username is taken') class LoginForm(FlaskForm): email = StringField('Your Email Address',validators=[Required(),Email()]) password = PasswordField('Password',validators =[Required()]) remember = BooleanField('Remember me') submit = SubmitField('Sign In')

[ "thiragithinji@gmail.com" ]

thiragithinji@gmail.com

264ea3af5cb07d50065bcd17d8510014c65e8225

65b4522c04c2be071c2d42095956fe950fe1cebe

/agu-paper/near_field_co_disp/verticals/plot_co_obs_pred.py

1c81afdcebed862eb9e1599a073dafd28848637f

[]

no_license

geodesy/viscojapan

ac0cd93f7a2134cd2651623b94879dcc21c0c46a

03e70265b56eb5994e73bcb6066f0be338e42f27

refs/heads/master

2021-03-03T18:19:07.779601

2015-07-16T03:50:49

null

0

null

UTF-8

Python

false

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from os.path import join import numpy as np import tempfile import pGMT import viscojapan as vj gmt = pGMT.GMT() gmt.gmtset('ANNOT_FONT_SIZE_PRIMARY','9', 'LABEL_FONT_SIZE','9', 'BASEMAP_TYPE','PLAIN', ) gplt = gmt.gplt lon1 = 139 lon2 = 145 lat1 = 34.7 lat2 = 41 gplt.psbasemap( R = '{lon1}/{lon2}/{lat1}/{lat2}'.format(lon1=lon1, lon2=lon2, lat1 = lat1, lat2 = lat2 ), # region J = 'B{lon0}/{lat0}/{lat1}/{lat2}/14c'.format( lon0=(lon1+lon2)/2., lat0 = (lat1+lat2)/2., lat1 = lat1, lat2 = lat2), # projection B = '2', U='20/0/22/Yang', K='', P='' ) # plot coseismic slip splt = vj.gmt.GMTSlipPlotter( gplt = gplt, slip_file_txt = '../share/co_slip' ) splt.init( # original_cpt_file = 'bath_112.cpt', original_cpt_file = '../Blues_09.cpt', #if_cpt_reverse = True ) splt.plot_slip() splt.plot_scale( xpos = 12, ypos = 5) vj.gmt.plot_plate_boundary(gplt, color=100) scale = 5 ########################### # onshore # plot prediction plt_vec = vj.gmt.VecFieldPlotter(gmt, 'share/co_ver_pred',scale) plt_vec.plot_vectors(arrow_width='.2', head_length='.1', head_width='.1', pen_width='1.2') plt_vec.plot_vec_legend( lon=142.5, lat=40.5, leg_len = 0.2, leg_txt = '20 cm pred.', text_offset_lon = -0.4, text_offset_lat = -0.15, if_vertical = True ) # plot observation plt_vec = vj.gmt.VecFieldPlotter(gmt, 'share/co_ver_obs',scale,'red') plt_vec.plot_vectors(arrow_width='.2', head_length='.1', head_width='.1', pen_width='1.2') plt_vec.plot_vec_legend( lon=143.2, lat=40.5, leg_len = .2, leg_txt = '20 cm obs. ONSHORE', text_offset_lon = -0.2, text_offset_lat = -0.15, if_vertical = True, ) #######################3 # plot seafloor: scale = 1.5 # plot prediction plt_vec = vj.gmt.VecFieldPlotter(gmt, 'share/co_ver_pred_seafloor',scale) plt_vec.plot_empty_vectors() plt_vec.plot_vec_legend( lon=143, lat=35.2, leg_len = 1, leg_txt = '1 m pred.', text_offset_lon = -0.2, text_offset_lat = -0.25, if_vertical = True ) # plot observation plt_vec = vj.gmt.VecFieldPlotter(gmt, 'share/co_ver_obs_seafloor',scale,'red') plt_vec.plot_empty_vectors() plt_vec.plot_vec_legend( lon=143.7, lat=35.2, leg_len = 1, leg_txt = '1 m obs. SEAFLOOR', text_offset_lon = -0.2, text_offset_lat = -0.25, if_vertical = True ) gplt.pscoast( R = '', J = '', D = 'h', N = 'a/faint,50,--', A='500', W = 'faint,100', L='f139.5/39.5/38/50+lkm+jt', O = '', K='') vj.gmt.plot_seafloor_stations(gplt, marker_size=0, network='SEAFLOOR_POST', justification='MB', text_offset_Y=0.03, fontsize='8') gplt.finish() gmt.save('seafloor_co_ver_obs_pred.pdf')

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# -*- coding: utf-8 -*- from django.conf.urls import url, include from rest_framework.routers import DefaultRouter from score.views import stats, mystats, ScoreView, CurrentScoreView router = DefaultRouter() router.register(r'scores', ScoreView) router.register(r'currentscores', CurrentScoreView) urlpatterns = [ url(r'^', include(router.urls)), url(r'^stats/$', stats), url(r'^mystats/$', mystats), ]

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# Title: 행렬 제곱 # Link: https://www.acmicpc.net/problem/10830 import sys import copy sys.setrecursionlimit(10 ** 6) read_list_int = lambda: list(map(int, sys.stdin.readline().strip().split(' '))) def multiple_matrix(n: int, a: list, b: list): res = [] for row in a: t_row = [] for i in range(n): s = 0 for x, v in enumerate(row): s = (s + (v * (b[x][i] % 1000)) % 1000)%1000 t_row.append(s) res.append(t_row) return res def solution(n: int, b: int, matrix: list): bin_b = list('{0:b}'.format(b)) acc = [[1 if x==y else 0 for x in range(n)] for y in range(n)] temp = copy.deepcopy(matrix) if bin_b.pop() == '1': acc = multiple_matrix(n, acc, matrix) while bin_b: temp = multiple_matrix(n, temp, temp) if bin_b.pop() == '1': acc = multiple_matrix(n, acc, temp) temp = [[1 if x==y else 0 for x in range(n)] for y in range(n)] ans = [] for row in acc: ans.append(' '.join(map(str, row))) return '\n'.join(ans) def main(): n, b = read_list_int() matrix = [] for _ in range(n): matrix.append(read_list_int()) print(solution(n, b, matrix)) if __name__ == '__main__': main()

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dep = float(input('Qual o depósito inicial?')) i = float(input('Qual a taxa de juros?')) total=0 t=1 while i<=24: mes = (dep*(1+i)**t) total = total + mes print ('{0}:.2f'.format(mes)) i=i+1 print ('{0}:.2f'.format(total))

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#!/usr/bin/env python import sys def copyall(*files): target = files[-1] with open(target, 'w') as fw: for filename in files[:-1]: with open(filename) as fp: fw.write(fp.name.center(60, '-') + "\n") for line in fp: fw.write(line) print "%s : file copied " % fp.name fw.write('-'.center(60, '-')+"\n") fw.write("\n") def usage(): if len(sys.argv) < 3: print "Usage : " print "%s source [source ....] target" % sys.argv[0] exit(1) usage() copyall(*sys.argv[1:])

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#!/usr/bin/env python # encoding: utf-8 """ @author: Wayne @contact: wangye.hope@gmail.com @software: PyCharm @file: Max Value of Equation @time: 2020/06/28 15:53 """ import heapq import sys class Solution: def findMaxValueOfEquation(self, points: list(list()), k: int) -> int: h = [] ret = -sys.maxsize for px, py in points: while h and px - h[0][1] > k: heapq.heappop(h) if h: ret = max(ret, px + py - h[0][0]) heapq.heappush(h, (px - py, px)) return ret

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