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/gender.py
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pankajdahilkar/python_codes
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refs/heads/master
2021-05-25T17:16:55.765443
2020-04-13T07:21:02
2020-04-13T07:21:02
253,838,761
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null
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UTF-8
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py
import csv name = input("Enter your name ") with open("Female.csv",'r', encoding='utf-8') as f: reader = csv.reader(f) for row in reader : for field in row : if field == name: print(name,"is girl") break else : print("not found")
[ "pankajmdahilkar@gmail.com" ]
pankajmdahilkar@gmail.com
fbad71338ab509e1dfd81e377efb259dc9287a74
4e092f6a59c0aad5cfe4235baac06f4f9823c62a
/0026. Remove Duplicates from Sorted Array.py
3628990533211b662c2e9da54cc9ee0e44197a56
[]
no_license
xinmiaoo/leetcode_Aug_3
72091fd7d23f98fb646ffb6f0b1a3068c930ea3f
732d8aa126dd5149013a4ce084f37ee8bc123ac7
refs/heads/master
2020-07-12T04:34:24.506629
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2019-08-10T21:54:50
null
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UTF-8
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411
py
class Solution(object): def removeDuplicates(self, nums): """ :type nums: List[int] :rtype: int """ if len(nums)<1: return if len(nums)==1: return i=1 while i<len(nums): if nums[i]==nums[i-1]: del nums[i] else: i+=1 return
[ "noreply@github.com" ]
xinmiaoo.noreply@github.com
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/Day4/answer_day4_question2.py
93ae2c3f566d420feb9820a96e4d196c55632b24
[]
no_license
nama-aman/Qiskit-Challenge-India-2020
88e56982012221b4153dc9d73e4f09508c3d7807
038956e5b241868637c06cbbf81928f3f9a1d796
refs/heads/master
2022-12-16T00:11:15.135572
2020-09-06T12:58:47
2020-09-06T12:58:47
293,277,220
0
0
null
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py
### WRITE YOUR CODE BETWEEN THESE LINES - START # import libraries that are used in the functions below. from qiskit import QuantumCircuit import numpy as np ### WRITE YOUR CODE BETWEEN THESE LINES - END def init_circuit(): # create a quantum circuit on two qubits qc = QuantumCircuit(2) # initializing the circuit qc.h(0) qc.x(1) return qc # The initial state has been defined above. # You'll now have to apply necessary gates in the build_state() function to convert the state as asked in the question. def build_state(): ### WRITE YOUR CODE BETWEEN THESE LINES - START # the initialized circuit circuit = init_circuit() circuit.cu3(0,-np.pi/2,0,1,0) # apply a single cu3 gate ### WRITE YOUR CODE BETWEEN THESE LINES - END return circuit
[ "noreply@github.com" ]
nama-aman.noreply@github.com
1080efe864c0987d212ee7dc9f93c2eb3b2aac02
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/tranx/datasets/django/dataset.py
6e4e64b95bf293feb1a5c1198b55baed0eb6137f
[]
no_license
gaoliujie2016/tranx-1
0a9727d9f5bf96ea0874b2c723045d734fa824d6
f9e4de91f678284f2935e2f9c4cdf71a32d8deca
refs/heads/master
2022-03-08T14:49:42.148163
2019-08-27T18:15:21
2019-08-27T18:15:21
null
0
0
null
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UTF-8
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# coding=utf-8 from __future__ import print_function import torch import re import pickle import ast import astor import nltk import sys import numpy as np from asdl.lang.py.py_asdl_helper import python_ast_to_asdl_ast, asdl_ast_to_python_ast from asdl.lang.py.py_transition_system import PythonTransitionSystem from asdl.hypothesis import * from asdl.lang.py.py_utils import tokenize_code from components.action_info import ActionInfo, get_action_infos p_elif = re.compile(r'^elif\s?') p_else = re.compile(r'^else\s?') p_try = re.compile(r'^try\s?') p_except = re.compile(r'^except\s?') p_finally = re.compile(r'^finally\s?') p_decorator = re.compile(r'^@.*') QUOTED_STRING_RE = re.compile(r"(?P<quote>['\"])(?P<string>.*?)(?<!\\)(?P=quote)") def replace_string_ast_nodes(py_ast, str_map): for node in ast.walk(py_ast): if isinstance(node, ast.Str): str_val = node.s if str_val in str_map: node.s = str_map[str_val] else: # handle cases like `\n\t` in string literals for key, val in str_map.items(): str_literal_decoded = key.decode('string_escape') if str_literal_decoded == str_val: node.s = val class Django(object): @staticmethod def canonicalize_code(code): if p_elif.match(code): code = 'if True: pass\n' + code if p_else.match(code): code = 'if True: pass\n' + code if p_try.match(code): code = code + 'pass\nexcept: pass' elif p_except.match(code): code = 'try: pass\n' + code elif p_finally.match(code): code = 'try: pass\n' + code if p_decorator.match(code): code = code + '\ndef dummy(): pass' if code[-1] == ':': code = code + 'pass' return code @staticmethod def canonicalize_str_nodes(py_ast, str_map): for node in ast.walk(py_ast): if isinstance(node, ast.Str): str_val = node.s if str_val in str_map: node.s = str_map[str_val] else: # handle cases like `\n\t` in string literals for str_literal, slot_id in str_map.items(): str_literal_decoded = str_literal.decode('string_escape') if str_literal_decoded == str_val: node.s = slot_id @staticmethod def canonicalize_query(query): """ canonicalize the query, replace strings to a special place holder """ str_count = 0 str_map = dict() matches = QUOTED_STRING_RE.findall(query) # de-duplicate cur_replaced_strs = set() for match in matches: # If one or more groups are present in the pattern, # it returns a list of groups quote = match[0] str_literal = match[1] quoted_str_literal = quote + str_literal + quote if str_literal in cur_replaced_strs: # replace the string with new quote with slot id query = query.replace(quoted_str_literal, str_map[str_literal]) continue # FIXME: substitute the ' % s ' with if str_literal in ['%s']: continue str_repr = '_STR:%d_' % str_count str_map[str_literal] = str_repr query = query.replace(quoted_str_literal, str_repr) str_count += 1 cur_replaced_strs.add(str_literal) # tokenize query_tokens = nltk.word_tokenize(query) new_query_tokens = [] # break up function calls like foo.bar.func for token in query_tokens: new_query_tokens.append(token) i = token.find('.') if 0 < i < len(token) - 1: new_tokens = ['['] + token.replace('.', ' . ').split(' ') + [']'] new_query_tokens.extend(new_tokens) query = ' '.join(new_query_tokens) query = query.replace('\' % s \'', '%s').replace('\" %s \"', '%s') return query, str_map @staticmethod def canonicalize_example(query, code): canonical_query, str_map = Django.canonicalize_query(query) query_tokens = canonical_query.split(' ') canonical_code = Django.canonicalize_code(code) ast_tree = ast.parse(canonical_code) Django.canonicalize_str_nodes(ast_tree, str_map) canonical_code = astor.to_source(ast_tree) # sanity check # decanonical_code = Django.decanonicalize_code(canonical_code, str_map) # decanonical_code_tokens = tokenize_code(decanonical_code) # raw_code_tokens = tokenize_code(code) # if decanonical_code_tokens != raw_code_tokens: # pass # try: # ast_tree = ast.parse(canonical_code).body[0] # except: # print('error!') # canonical_code = Django.canonicalize_code(code) # gold_ast_tree = ast.parse(canonical_code).body[0] # str_map = {} # parse_tree = python_ast_to_asdl_ast(gold_ast_tree, grammar) # gold_source = astor.to_source(gold_ast_tree) # ast_tree = asdl_ast_to_python_ast(parse_tree, grammar) # source = astor.to_source(ast_tree) # assert gold_source == source, 'sanity check fails: gold=[%s], actual=[%s]' % (gold_source, source) # # # action check # parser = PythonTransitionSystem(grammar) # actions = parser.get_actions(parse_tree) # # hyp = Hypothesis() # for action in actions: # assert action.__class__ in parser.get_valid_continuation_types(hyp) # if isinstance(action, ApplyRuleAction): # assert action in parser.get_valid_continuations(hyp) # hyp.apply_action(action) # # src_from_hyp = astor.to_source(asdl_ast_to_python_ast(hyp.tree, grammar)) # assert src_from_hyp == gold_source return query_tokens, canonical_code, str_map @staticmethod def parse_django_dataset(annot_file, code_file, asdl_file_path, max_query_len=70, vocab_freq_cutoff=10): asdl_text = open(asdl_file_path).read() grammar = ASDLGrammar.from_text(asdl_text) transition_system = PythonTransitionSystem(grammar) loaded_examples = [] from components.vocab import Vocab, VocabEntry from components.dataset import Example for idx, (src_query, tgt_code) in enumerate(zip(open(annot_file), open(code_file))): src_query = src_query.strip() tgt_code = tgt_code.strip() src_query_tokens, tgt_canonical_code, str_map = Django.canonicalize_example(src_query, tgt_code) python_ast = ast.parse(tgt_canonical_code).body[0] gold_source = astor.to_source(python_ast).strip() tgt_ast = python_ast_to_asdl_ast(python_ast, grammar) tgt_actions = transition_system.get_actions(tgt_ast) # print('+' * 60) # print('Example: %d' % idx) # print('Source: %s' % ' '.join(src_query_tokens)) # if str_map: # print('Original String Map:') # for str_literal, str_repr in str_map.items(): # print('\t%s: %s' % (str_literal, str_repr)) # print('Code:\n%s' % gold_source) # print('Actions:') # sanity check hyp = Hypothesis() for t, action in enumerate(tgt_actions): assert action.__class__ in transition_system.get_valid_continuation_types(hyp) if isinstance(action, ApplyRuleAction): assert action.production in transition_system.get_valid_continuating_productions(hyp) p_t = -1 f_t = None if hyp.frontier_node: p_t = hyp.frontier_node.created_time f_t = hyp.frontier_field.field.__repr__(plain=True) print('\t[%d] %s, frontier field: %s, parent: %d' % (t, action, f_t, p_t)) hyp = hyp.clone_and_apply_action(action) assert hyp.frontier_node is None and hyp.frontier_field is None src_from_hyp = astor.to_source(asdl_ast_to_python_ast(hyp.tree, grammar)).strip() assert src_from_hyp == gold_source print('+' * 60) loaded_examples.append({'src_query_tokens' : src_query_tokens, 'tgt_canonical_code': gold_source, 'tgt_ast' : tgt_ast, 'tgt_actions' : tgt_actions, 'raw_code' : tgt_code, 'str_map': str_map}) # print('first pass, processed %d' % idx, file=sys.stderr) train_examples = [] dev_examples = [] test_examples = [] action_len = [] for idx, e in enumerate(loaded_examples): src_query_tokens = e['src_query_tokens'][:max_query_len] tgt_actions = e['tgt_actions'] tgt_action_infos = get_action_infos(src_query_tokens, tgt_actions) example = Example(idx=idx, src_sent=src_query_tokens, tgt_actions=tgt_action_infos, tgt_code=e['tgt_canonical_code'], tgt_ast=e['tgt_ast'], meta={'raw_code': e['raw_code'], 'str_map': e['str_map']}) # print('second pass, processed %d' % idx, file=sys.stderr) action_len.append(len(tgt_action_infos)) # train, valid, test split if 0 <= idx < 16000: train_examples.append(example) elif 16000 <= idx < 17000: dev_examples.append(example) else: test_examples.append(example) print('Max action len: %d' % max(action_len), file=sys.stderr) print('Avg action len: %d' % np.average(action_len), file=sys.stderr) print('Actions larger than 100: %d' % len(list(filter(lambda x: x > 100, action_len))), file=sys.stderr) src_vocab = VocabEntry.from_corpus([e.src_sent for e in train_examples], size=5000, freq_cutoff=vocab_freq_cutoff) primitive_tokens = [map(lambda a: a.action.token, filter(lambda a: isinstance(a.action, GenTokenAction), e.tgt_actions)) for e in train_examples] primitive_vocab = VocabEntry.from_corpus(primitive_tokens, size=5000, freq_cutoff=vocab_freq_cutoff) assert '_STR:0_' in primitive_vocab # generate vocabulary for the code tokens! code_tokens = [tokenize_code(e.tgt_code, mode='decoder') for e in train_examples] code_vocab = VocabEntry.from_corpus(code_tokens, size=5000, freq_cutoff=vocab_freq_cutoff) vocab = Vocab(source=src_vocab, primitive=primitive_vocab, code=code_vocab) print('generated vocabulary %s' % repr(vocab), file=sys.stderr) return (train_examples, dev_examples, test_examples), vocab @staticmethod def process_django_dataset(): vocab_freq_cutoff = 15 # TODO: found the best cutoff threshold annot_file = 'data/django/all.anno' code_file = 'data/django/all.code' (train, dev, test), vocab = Django.parse_django_dataset(annot_file, code_file, 'asdl/lang/py/py_asdl.txt', vocab_freq_cutoff=vocab_freq_cutoff) pickle.dump(train, open('data/django/train.bin', 'w')) pickle.dump(dev, open('data/django/dev.bin', 'w')) pickle.dump(test, open('data/django/test.bin', 'w')) pickle.dump(vocab, open('data/django/vocab.freq%d.bin' % vocab_freq_cutoff, 'w')) @staticmethod def run(): asdl_text = open('asdl/lang/py/py_asdl.txt').read() grammar = ASDLGrammar.from_text(asdl_text) annot_file = 'data/django/all.anno' code_file = 'data/django/all.code' transition_system = PythonTransitionSystem(grammar) for idx, (src_query, tgt_code) in enumerate(zip(open(annot_file), open(code_file))): src_query = src_query.strip() tgt_code = tgt_code.strip() query_tokens, tgt_canonical_code, str_map = Django.canonicalize_example(src_query, tgt_code) python_ast = ast.parse(tgt_canonical_code).body[0] gold_source = astor.to_source(python_ast) tgt_ast = python_ast_to_asdl_ast(python_ast, grammar) tgt_actions = transition_system.get_actions(tgt_ast) # sanity check hyp = Hypothesis() hyp2 = Hypothesis() for action in tgt_actions: assert action.__class__ in transition_system.get_valid_continuation_types(hyp) if isinstance(action, ApplyRuleAction): assert action.production in transition_system.get_valid_continuating_productions(hyp) hyp = hyp.clone_and_apply_action(action) hyp2.apply_action(action) src_from_hyp = astor.to_source(asdl_ast_to_python_ast(hyp.tree, grammar)) assert src_from_hyp == gold_source assert hyp.tree == hyp2.tree and hyp.tree is not hyp2.tree print(idx) @staticmethod def canonicalize_raw_django_oneliner(code): # use the astor-style code code = Django.canonicalize_code(code) py_ast = ast.parse(code).body[0] code = astor.to_source(py_ast).strip() return code def generate_vocab_for_paraphrase_model(vocab_path, save_path): from components.vocab import VocabEntry, Vocab vocab = pickle.load(open(vocab_path)) para_vocab = VocabEntry() for i in range(0, 10): para_vocab.add('<unk_%d>' % i) for word in vocab.source.word2id: para_vocab.add(word) for word in vocab.code.word2id: para_vocab.add(word) pickle.dump(para_vocab, open(save_path, 'w')) if __name__ == '__main__': # Django.run() # f1 = Field('hahah', ASDLPrimitiveType('123'), 'single') # rf1 = RealizedField(f1, value=123) # # # print(f1 == rf1) # a = {f1: 1} # print(a[rf1]) Django.process_django_dataset() # generate_vocab_for_paraphrase_model('data/django/vocab.freq10.bin', 'data/django/vocab.para.freq10.bin') # py_ast = ast.parse("""sorted(asf, reverse='k' 'k', k='re' % sdf)""") # canonicalize_py_ast(py_ast) # for node in ast.walk(py_ast): # if isinstance(node, ast.Str): # print(node.s) # print(astor.to_source(py_ast))
[ "alex.dinu07@gmail.com" ]
alex.dinu07@gmail.com
45a17b83e5063af268f032dd425b660dcf74ebf6
ae67cd669cb733f0ed7b4b02c1320757c91ebd9f
/lut/__init__.py
ff33cffbf0d228820ebf83cb62a25232e9a5b6ea
[]
no_license
anguelos/lut
bef878485a6ce31195593a504f0a819032e878be
6898fefc748cbbc323415e96e22c1711dfcce1e1
refs/heads/master
2016-09-14T01:29:15.626110
2016-05-06T16:50:22
2016-05-06T16:50:22
58,217,071
0
0
null
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UTF-8
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py
import core import train import models import view import loss import layers import metric import ds core=reload(core) models=reload(models) view=reload(view) loss=reload(loss) layers=reload(layers) metric=reload(metric) ds=reload(ds) train=reload(train) from core import * from train import * from models import * from view import * from ds import * from loss import * from layers import * from metric import *
[ "anguelos.nicolaou@gmail.com" ]
anguelos.nicolaou@gmail.com
1afefbe7797fabd4b8f9a7ab4164ea1bf07b73e6
b13c95cb06434a985f9da51575f1eb3fa484cb0c
/helloworld/main.py
9320a568b423d22b5eaab013607325ea89c83177
[]
no_license
shandre-github/minikube
aa34294d6355ade16e0155bd5caef6a946840e69
94cfe856bf202e90464c2d85ccabe1ce673dbeb2
refs/heads/master
2023-03-13T15:11:39.785525
2021-02-25T04:53:19
2021-02-25T04:53:19
341,305,244
0
0
null
null
null
null
UTF-8
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false
false
219
py
import os from flask import Flask app = Flask(__name__) @app.route('/') def index(): name = os.environ.get('MY_POD_NAME') return 'Hello World from {name}'.format(name=name) app.run(host='0.0.0.0', port=8080)
[ "shpnaruto@gmail.com" ]
shpnaruto@gmail.com
6ecde04930e4c4d2d909383a6d9ae3c2c8476230
c089d51e00ace0e2d2c1c08cc7278ea4a43ff8f9
/classifiers/keras.py
4ac55c4f41d6fadb0db78e8d3ac6e6246d879ec9
[]
no_license
salman-kha3/ActiveLearning
84f088aac802c59edba94c205b4666bfa8e7b15f
3d6c6c120788ea2fd338cff5d3f5b88b5b8901ec
refs/heads/master
2021-01-11T20:35:46.977142
2017-04-02T12:58:01
2017-04-02T12:58:01
79,150,978
1
1
null
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UTF-8
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py
import keras from libact.base.interfaces import ContinuousModel import numpy as np class KerasClassifier(ContinuousModel): def __init__(self, *args, **kwargs): self.model = keras.models.Sequential(*args, **kwargs) def train(self, dataset, *args, **kwargs): return self.model.fit(*(dataset.format_sklearn()+args), **kwargs) def predict(self, feature, *args, **kwargs): return self.model.predict(feature, *args, **kwargs) def score(self, *args, **kwargs): return self.model.evaluate(*args, **kwargs) def predict_real(self, feature, *args, **kwargs): if hasattr(self.model, "decision_function"): dvalue = self.model.decision_function(feature, *args, **kwargs) else: dvalue = self.model.predict_proba(feature, *args, **kwargs) # [:, 1] if len(np.shape(dvalue)) == 1: # n_classes == 2 return np.vstack((-dvalue, dvalue)).T else: return dvalue def add(self, *args, **kwargs): self.model.add(*args, **kwargs) def compile(self, *args, **kwargs): self.model.compile(*args, **kwargs)
[ "salman.khatri3@gmail.com" ]
salman.khatri3@gmail.com
77f78c54499c89158741dcfdec3c99815d78fd7f
48399403b64b9d8e52ea573c0cbefb941f33e540
/server.py
62775f3592e3fea539d03b16d9b96c25a5d4ac78
[]
no_license
Henry-Aybar/counter
97c54c9a3060fb0249ee432ec89163ae796c014e
8bb089134d502bd334d785751352086340561862
refs/heads/master
2023-08-03T09:41:43.420948
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406,517,407
0
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py
from flask import Flask, render_template, request, redirect, session app = Flask(__name__) app.secret_key = 'Im just Super Sayin!' @app.route('/') def index(): if 'visit' in session: session['visit'] += 1 else: session['visit'] = 1 if 'count' in session: session['count'] += 1 else: session['count'] = 0 return render_template("index.html") @app.route('/clear') def clear_session(): session.clear() return redirect('/') if __name__=="__main__": app.run(debug=True)
[ "aybar.henry.usmc@gmail.com" ]
aybar.henry.usmc@gmail.com
f4dbe6287f26b3505bbd41c6c3a493e894db9f0e
43e36f639e69bb3c0ace7b89eee8571d946da1c8
/scripts/ball_gripping_test.py
28d81f812fe81d24a1a294c322afcb8d91a80c66
[]
no_license
mikolak/test_package
309a07e78b322a0fe378ac595200b473cba0a391
c9978a440bcdeed54839aeeb1e80795060cc1b5e
refs/heads/master
2016-09-03T07:24:23.361858
2014-09-08T13:36:32
2014-09-08T13:36:32
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UTF-8
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#!/usr/bin/env python import rospy import tf import actionlib import math from controller_manager_msgs.srv import * from std_msgs.msg import * from diagnostic_msgs.msg import * from geometry_msgs.msg import * from trajectory_msgs.msg import * from control_msgs.msg import * from cartesian_trajectory_msgs.msg import * from force_control_msgs.msg import * from tf.transformations import * import PyKDL import tf_conversions.posemath as pm def getDownOrientedQuaternion(): real_angle = math.pi * 1 #180 stopni to pionowo w dol v_x = 0.0 v_y = -1 v_z = 0 angle = 0.5 * real_angle _sin = math.sin(angle) x = _sin * v_x y = _sin * v_y z = _sin * v_z w = math.cos(angle) return Quaternion(x, y, z, w) if __name__ == '__main__': rospy.init_node('simple_trajectory_test') rospy.wait_for_service('/controller_manager/switch_controller') conManSwitch = rospy.ServiceProxy('/controller_manager/switch_controller', SwitchController) #------------------------------------------------ # Stawy #------------------------------------------------ conManSwitch(['Irp6pmSplineTrajectoryGeneratorJoint'], [], True) client = actionlib.SimpleActionClient('/irp6p_arm/spline_trajectory_action_joint', FollowJointTrajectoryAction) client.wait_for_server() print 'Inicjacja postawy' goal = FollowJointTrajectoryGoal() goal.trajectory.joint_names = ['joint1', 'joint2', 'joint3', 'joint4', 'joint5', 'joint6'] goal.trajectory.points.append(JointTrajectoryPoint([0, -0.5 * math.pi, 0, 0, 1.45 * math.pi, -0.5 * math.pi], [], [], [], rospy.Duration(6.0))) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) client.send_goal(goal) client.wait_for_result() command_result = client.get_result() #===================================================== conManSwitch(['Irp6pmPoseInt'], ['Irp6pmSplineTrajectoryGeneratorJoint'], True) pose_client = actionlib.SimpleActionClient('/irp6p_arm/pose_trajectory', CartesianTrajectoryAction) pose_client.wait_for_server() print 'Ustawienie pozycji poczatkowej' goal = CartesianTrajectoryGoal() quaternion = getDownOrientedQuaternion() point = Point(0.85, 0, 1.20) goal.trajectory.points.append(CartesianTrajectoryPoint(rospy.Duration(10.0), Pose(point, quaternion), Twist())) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) pose_client.send_goal(goal) pose_client.wait_for_result() command_result = pose_client.get_result() #==================================================== conManSwitch(['Irp6pmPoseInt'], [], True) pose_client = actionlib.SimpleActionClient('/irp6p_arm/pose_trajectory', CartesianTrajectoryAction) pose_client.wait_for_server() print 'Podejscie do podjecia' goal = CartesianTrajectoryGoal() quaternion = getDownOrientedQuaternion() point = Point(0.9, 0, 0.95) goal.trajectory.points.append(CartesianTrajectoryPoint(rospy.Duration(10.0), Pose(point, quaternion), Twist())) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) pose_client.send_goal(goal) pose_client.wait_for_result() command_result = pose_client.get_result() rospy.sleep(5.0) #======================================================== conManSwitch(['Irp6ptfgSplineTrajectoryGeneratorMotor'], ['Irp6pmPoseInt'], True) motor_client = actionlib.SimpleActionClient('/irp6p_tfg/spline_trajectory_action_motor', FollowJointTrajectoryAction) motor_client.wait_for_server() print 'Chwyt' goal = FollowJointTrajectoryGoal() goal.trajectory.joint_names = ['joint1'] goal.trajectory.points.append(JointTrajectoryPoint([1000.0], [0.0], [], [], rospy.Duration(3.0))) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) motor_client.send_goal(goal) motor_client.wait_for_result() command_result = motor_client.get_result() #======================================================= conManSwitch(['Irp6pmPoseInt'], ['Irp6ptfgSplineTrajectoryGeneratorMotor'], True) pose_client = actionlib.SimpleActionClient('/irp6p_arm/pose_trajectory', CartesianTrajectoryAction) pose_client.wait_for_server() print 'Powrot do pozycji poczatkowej' goal = CartesianTrajectoryGoal() quaternion = getDownOrientedQuaternion() point = Point(0.85, 0, 1.20) goal.trajectory.points.append(CartesianTrajectoryPoint(rospy.Duration(15.0), Pose(point, quaternion), Twist())) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) pose_client.send_goal(goal) pose_client.wait_for_result() command_result = pose_client.get_result() #======================================================== conManSwitch(['Irp6pmPoseInt'], [], True) pose_client = actionlib.SimpleActionClient('/irp6p_arm/pose_trajectory', CartesianTrajectoryAction) pose_client.wait_for_server() print 'Podejscie do odlozenia' goal = CartesianTrajectoryGoal() quaternion = getDownOrientedQuaternion() point = Point(0.9, 0.3, 0.95) goal.trajectory.points.append(CartesianTrajectoryPoint(rospy.Duration(10.0), Pose(point, quaternion), Twist())) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) pose_client.send_goal(goal) pose_client.wait_for_result() command_result = pose_client.get_result() #=========================================== conManSwitch(['Irp6ptfgSplineTrajectoryGeneratorMotor'], ['Irp6pmPoseInt'], True) motor_client = actionlib.SimpleActionClient('/irp6p_tfg/spline_trajectory_action_motor', FollowJointTrajectoryAction) motor_client.wait_for_server() print 'Wypuszczenie' goal = FollowJointTrajectoryGoal() goal.trajectory.joint_names = ['joint1'] goal.trajectory.points.append(JointTrajectoryPoint([-1000.0], [0.0], [], [], rospy.Duration(3.0))) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) motor_client.send_goal(goal) motor_client.wait_for_result() command_result = motor_client.get_result() #============================================ conManSwitch(['Irp6pmPoseInt'], ['Irp6ptfgSplineTrajectoryGeneratorMotor'], True) pose_client = actionlib.SimpleActionClient('/irp6p_arm/pose_trajectory', CartesianTrajectoryAction) pose_client.wait_for_server() print 'Powrot do pozycji poczatkowej' goal = CartesianTrajectoryGoal() quaternion = getDownOrientedQuaternion() point1 = Point(0.9, 0.3, 1.20) point2 = Point(0.85, 0, 1.20) goal.trajectory.points.append(CartesianTrajectoryPoint(rospy.Duration(8.0), Pose(point1, quaternion), Twist())) goal.trajectory.points.append(CartesianTrajectoryPoint(rospy.Duration(16.0), Pose(point2, quaternion), Twist())) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) pose_client.send_goal(goal) pose_client.wait_for_result() command_result = pose_client.get_result() #================================================ conManSwitch(['Irp6pmSplineTrajectoryGeneratorJoint'], ['Irp6pmPoseInt'], True) client = actionlib.SimpleActionClient('/irp6p_arm/spline_trajectory_action_joint', FollowJointTrajectoryAction) client.wait_for_server() print 'Powrot do pozycji synchronizacji' goal = FollowJointTrajectoryGoal() goal.trajectory.joint_names = ['joint1', 'joint2', 'joint3', 'joint4', 'joint5', 'joint6'] goal.trajectory.points.append(JointTrajectoryPoint([-0.10087151336609543, -1.5417429815634993, 0.019743230015841898, 1.1331041783656084, 3.658011557435151, -2.7351279214366393], [], [], [], rospy.Duration(10.0))) goal.trajectory.header.stamp = rospy.get_rostime() + rospy.Duration(0.2) client.send_goal(goal) client.wait_for_result() command_result = client.get_result() conManSwitch([], ['Irp6pmSplineTrajectoryGeneratorJoint'], True) print 'Skonczylem!'
[ "mikolak.k@gmail.com" ]
mikolak.k@gmail.com
c72344f39a2b47d401f7e46eee77380b114764d6
32a3a7522546df5f18effcaec43b66115c1cd2c1
/alpha/migrations/0001_initial.py
deee8f56a15d69afa30df48f53d2484a0ee593bc
[]
no_license
seian/youask
4b90804a289d3b7d21c9fb9b7b7736279845b95b
490c8f730e32462eae6a7f69af25fed10c92aba9
refs/heads/master
2016-08-09T08:17:19.168489
2016-02-17T05:58:46
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# -*- coding: utf-8 -*- # Generated by Django 1.9.1 on 2016-02-17 04:40 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Celeb_info', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('owner', models.IntegerField()), ('name', models.CharField(max_length=100)), ('birth', models.DateTimeField()), ('group', models.CharField(max_length=500)), ('job', models.CharField(max_length=500)), ('school', models.CharField(max_length=500)), ], ), migrations.CreateModel( name='Celeb_info_career', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('owner', models.IntegerField()), ('_from', models.DateTimeField()), ('_to', models.DateTimeField()), ('award', models.CharField(max_length=500)), ], ), migrations.CreateModel( name='Members', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('email', models.CharField(max_length=200)), ('nick_name', models.CharField(max_length=50)), ('password', models.CharField(max_length=512)), ('signup_date', models.DateTimeField(auto_now=True)), ('contents', models.TextField(max_length=300)), ], ), migrations.CreateModel( name='Replies', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('owner', models.IntegerField()), ('thread', models.IntegerField()), ('content', models.CharField(max_length=500)), ('preference', models.IntegerField()), ('post_date', models.DateTimeField(auto_now=True)), ('parent_id', models.IntegerField()), ], ), migrations.CreateModel( name='Thread', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('owner', models.IntegerField()), ('topic', models.CharField(max_length=500)), ('title', models.CharField(max_length=500)), ('post_date', models.DateTimeField(auto_now=True)), ], ), ]
[ "wnsdud1861@gmail.com" ]
wnsdud1861@gmail.com
0795e38e200dc99858a29c73d98fbc5eada52473
9d8314bcb2cdabb62e6ce97cf61fc79e559e1c4f
/python-ds-practice/fs_5_read_file_list/read_file_list.py
74b36e94617c01f212c124ad2b7d30a53cadb857
[]
no_license
hannahsylee/18_Python
110ac6bfcda571bfafa0a737723616ba0ac87957
165465755fd3707b20fa5f7a094826ee2374cbe8
refs/heads/main
2023-08-27T02:22:53.879605
2021-10-18T04:05:22
2021-10-18T04:05:22
417,318,259
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def read_file_list(filename): """Read file and print out each line separately with a "-" before it. For example, if we have a file, `dogs`, containing: Fido Whiskey Dr. Sniffle This should work: >>> read_file_list("dogs") - Fido - Whiskey - Dr. Sniffle It will raise an error if the file cannot be found. """ with open(filename) as f: for line in f: # remove newline at end of line! line = line.strip() print(f"- {line}") # hint: when you read lines of files, there will be a "newline" # (end-of-line character) at the end of each line, and you want to # strip that off before you print it. Do some research on that!
[ "hannahsylee@gmail.com" ]
hannahsylee@gmail.com
595a9e74a588b9a31577ba1c84a3e2bd2e99a3bc
e4c798246339e765f04424d727106e80e810f47c
/Medium/iNo008.py
7c70fbb6da2f54341b2bef3bbcc9b1e6fae85c2f
[]
no_license
kikihiter/LeetCode
3a61dc4ee3223d634632e30b97c30a73e5bbe253
62b5ae50e3b42ae7a5a002efa98af5ed0740a37f
refs/heads/master
2021-05-26T08:05:00.126775
2019-05-21T09:18:37
2019-05-21T09:18:37
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class Solution(object): def myAtoi(self, str): """ :type str: str :rtype: int """ str = str.lstrip() posNum = True if str == "": return 0 if str[0]=='-': posNum = False str = str[1:] elif str[0]=='+': str = str[1:] try: int(str[0]) except: return 0 rStr = "" for i in str: try: int(i) except: break rStr = rStr + i rStr = rStr.lstrip('0') if rStr == "": return 0 if posNum == False: return max(-int(rStr),-2147483648) print rStr return min(int(rStr),2147483647)
[ "noreply@github.com" ]
kikihiter.noreply@github.com
78196c0216eb2c3169434d91e959b6edf1d91d1a
44d9cdc0ca026036c314b8530a7eeda1fb3ee21c
/src/JZ/JZ14-II.py
ea9dde6589c4ad917732d8c88169b2ff6c251334
[]
no_license
Sibyl233/LeetCode
525a2104a4f96e0e701fa175dfad6d02d6cf40f3
3e20e54bb11f7a56d8fa8189a0a1a1461f81eb8a
refs/heads/master
2021-09-06T14:52:31.718922
2021-08-20T15:51:37
2021-08-20T15:51:37
234,050,203
0
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"""่งฃๆณ•๏ผšๆ‰พ่ง„ๅพ‹ - ๆ—ถ้—ดๅคๆ‚ๅบฆ๏ผšO(logN)ใ€‚ไธบไบŒๅˆ†ๆฑ‚ไฝ™ๆณ•ๅคๆ‚ๅบฆใ€‚ - ็ฉบ้—ดๅคๆ‚ๅบฆ๏ผšO(1) """ class Solution: def cuttingRope(self, n: int) -> int: if n <= 3: return n - 1 # ไธๅŒไบŽJZ14-I๏ผŒๆ นๆฎ้ข˜ๆ„ๆญคๅค„ๆฑ‚ไฝ™้‡‡็”จไบŒๅˆ†ๆฑ‚ไฝ™ๆณ• a, b, p, x, rem = n // 3 - 1, n % 3, 1000000007, 3 , 1 while a > 0: if a % 2: rem = (rem * x) % p x = x ** 2 % p a //= 2 if b == 0: return (rem * 3) % p # = 3^(a+1) % p if b == 1: return (rem * 4) % p # = 3^a * 4 % p return (rem * 6) % p # = 3^(a+1) * 2 % p if __name__=="__main__": n = 10 print(Solution().cuttingRope(n)) # 36
[ "780598113@qq.com" ]
780598113@qq.com
5d5fd3a0fc2112964ec1c90c48196dcdc7468bd7
d93b337a73a9bc6f6c104cc6eea9ca8d60ef3577
/stripeAPI/cargo.py
407cca194cdbced169d8ec5a77e78e9b275ed8e4
[]
no_license
erivera23/market
0532c5aefe32bd0102fa18fe6b224af289c4388f
73bead776f233bd1a79d34122daeff74b2b3ce18
refs/heads/master
2022-12-13T00:21:38.163936
2020-01-18T22:52:34
2020-01-18T22:52:34
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from . import stripe def create_cargo(orden): if orden.billing_profile and orden.user and orden.user.customer_id: cargo = stripe.Charge.create( amount = int(orden.total) * 100, currency = 'USD', description = orden.descripcion, customer=orden.user.customer_id, source=orden.billing_profile.card_id, metadata= { 'orden_id': orden.id } ) return cargo
[ "riveraefrain5@gmail.com" ]
riveraefrain5@gmail.com
b4fde878db7746ff13c0a3dedbfbca0736d7249c
34c91527966ecf29d8adf46becbf3af5032dc3a6
/basic/armstrongnumber.py
9552f47dc63cdff9b0b8cf0745e63ea4f047d5bf
[]
no_license
mjohnkennykumar/csipythonprograms
0a23040a484812b3176b614bf0e18f685c74a375
750cdaeda15fe73328902c3de567d6083dfa7a77
refs/heads/master
2021-01-21T14:32:37.913617
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2017-06-24T12:54:03
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py
# -*- coding: utf-8 -*- # Python program to check if the number provided by the user is an Armstrong number or not # take input from the user # num = int(input("Enter a number: ")) # initialize sum sum = 0 num = int(input("Enter a number: ")) # find the sum of the cube of each digit temp = num while temp > 0: digit = temp % 10 sum += digit ** 3 temp //= 10 # display the result if num == sum: print(num,"is an Armstrong number"); else: print(num,"is not an Armstrong number");
[ "Samuel Henry" ]
Samuel Henry
acc0e879ddff0fddff0f1c17854d03eba9823789
be8fe594fae8a4fb66c0cbc1f0e8462891eabb1b
/examsystemapp/api/external.py
ff92d1a6411c523b029c830ee33dfb926c6e41f2
[]
no_license
ITfyMe/ExamSytemPython
a30cccc1ba4ef832666b23109a772209fcbcea8c
da7506ae9607d69c97744bdc08ac1113fc86237a
refs/heads/master
2023-06-12T11:48:20.514142
2021-07-12T13:16:06
2021-07-12T13:16:06
369,427,947
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py
""" Created By : Nikesh Created On : Reviewed By : Reviewed On : Version : """ from django.http import HttpRequest from examsystemapp.api.base_controller import BaseController from examsystemapp.utils.helpers.request_helper import RequestHelper from django.conf import settings class External(BaseController): def __init__(self, request: HttpRequest): BaseController.__init__(self, request) def check_session(self, request): pass def masters(self, request: HttpRequest): json_data = RequestHelper().call_ext_api(request, settings.MASTER_BASE_URL) return self.send_response_raw_json(json_data)
[ "nikesh.kedlaya@gmail.com" ]
nikesh.kedlaya@gmail.com
3bf09fa4f79c4ab4f60f4fdf8d3c23e04214b598
6fa7f99d3d3d9b177ef01ebf9a9da4982813b7d4
/F5ycABGyZtghMpYjr_16.py
ce3767d6e7a4448df5ed169a0465448836b9b5c5
[]
no_license
daniel-reich/ubiquitous-fiesta
26e80f0082f8589e51d359ce7953117a3da7d38c
9af2700dbe59284f5697e612491499841a6c126f
refs/heads/master
2023-04-05T06:40:37.328213
2021-04-06T20:17:44
2021-04-06T20:17:44
355,318,759
0
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UTF-8
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py
def max_num(n1, n2): if n1 > n2: return n1 else: return n2
[ "daniel.reich@danielreichs-MacBook-Pro.local" ]
daniel.reich@danielreichs-MacBook-Pro.local
50157256f9b323f313890c0165fa4fe159337357
8cce087dfd5c623c2f763f073c1f390a21838f0e
/projects/the/test.py
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[ "Unlicense" ]
permissive
quinn-dougherty/python-on-nix
b2ae42761bccf7b3766999b27a4674310e276fd8
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refs/heads/main
2023-08-23T11:57:55.988175
2021-09-24T05:55:00
2021-09-24T05:55:00
414,799,752
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py
import the
[ "kamadorueda@gmail.com" ]
kamadorueda@gmail.com
d0e5a0905a4356ef92ac7aaf23d6954bde4d27c3
6a2d708c290d5fc8b4eb6d2b6d52186d6ae57406
/Chef Race (SRTF) Final/srtf.py
5bbf4bbf634474a5b9be024dfb09b3ce1e213ed3
[]
no_license
ac-marlon/ChefRaceUD
64080c1e575234f03113c16d9c017c4f42f55010
b3c8312af7b6b8e3e6fc0a457169358e4bd1d62b
refs/heads/master
2021-08-26T01:09:25.324512
2021-08-18T15:01:24
2021-08-18T15:01:24
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import cola import time from procesos import * import recursos as rs import queue import threading import numpy as np import pygame from pygame.sprite import Sprite from pygame.locals import * import util import sys, pygame, util from receta import Receta from recursos import CuchillosIma from recursos import LicuadoraIma from recursos import HornoIma from pizarra import Pizarra size = width, height = 900, 712 screen = pygame.display.set_mode(size) class Procesador(threading.Thread): def __init__(self,idProcesador,*args): threading.Thread.__init__(self) self.idProcesador=idProcesador self.proceso=None self.lis=cola.Cola() self.ter=cola.Cola() self.blo=cola.Cola() self.sus=cola.Cola() self._args=args self.uso=True self.minIter=50 def __str__(self): return str(self.idProcesador) def run(self): while self.uso: self.usarProcesador(*self._args) def usarProcesador(self,q): while not self.proceso==None or not q.empty() or not self.lis.es_vacia() or not self.sus.es_vacia() or not self.blo.es_vacia() or self.minIter>0: time.sleep(2) self.minIter-=1 if not q.empty(): self.asignar(q.get()) self.lis.ordenar() if not self.lis.es_vacia() and self.proceso==None: posible=self.lis.desencolar() if posible.recurso.libre: self.ocupado=True self.proceso=posible self.proceso.recurso.utilizar() self.proceso.estado=3 else: posible.bloquear() self.blo.encolar(posible) elif not self.lis.es_vacia() and not self.proceso==None: posible=self.lis.desencolar() if self.proceso.t>posible.t and posible.recurso.libre: self.proceso.suspender() self.sus.encolar(self.proceso) self.proceso=posible self.proceso.recurso.utilizar() else: self.lis.encolar(posible) self.contarColaBlo() self.contarColaLis() self.revisarColaSus() self.revisarColaBlo() if not self.proceso==None: self.proceso.procesar() if self.proceso.t==0: self.proceso.recurso.liberar() print("\nterminando proceso",self.proceso,"en el procesador",self,",sus",self.proceso.sus,",lis",self.proceso.lis,",blo",self.proceso.blo,",zona critica",self.proceso.zc) self.proceso.estado=4 self.ter.encolar(self.proceso) self.proceso=None q.task_done() print("termino el procesador",self,"lista de tareas completadas en este procesador:") for i in range(self.ter.tam): print(self.ter.desencolar()) self.uso=False def revisarColaSus(self): tam = self.sus.tam for i in range(tam): n=self.sus.desencolar() n.tr-=1 n.sus+=1 if n.tr==0: self.asignar(n) print("\nse saco el proceso",n,"de la cola de suspendidos y entro a la cola de listo") else: self.sus.encolar(n) def revisarColaBlo(self): for i in range(self.blo.tam): posible=self.blo.desencolar() if posible.recurso.libre: self.asignar(posible) print("\nse saco el proceso",posible," de la cola de bloqueados y entro en la cola de listos") else: self.blo.encolar(posible) def contarColaLis(self): tam = self.lis.tam for i in range(tam): n=self.lis.desencolar() n.lis+=1 self.lis.encolar(n) def contarColaBlo(self): tam = self.blo.tam for i in range(self.blo.tam): n=self.blo.desencolar() n.blo+=1 self.blo.encolar(n) def asignar(self,proceso): proceso.estado=0 self.lis.encolar(proceso) class cliente: def __init__(self): self.numPo=0 self.numMa=0 self.numEn=0 self.recursos=[rs.Horno(),rs.Cuchillos(),rs.Licuadora()] self.cola1=queue.Queue() self.cola2=queue.Queue() self.cola3=queue.Queue() self.colaProcesadores=queue.Queue() self.procesador1=Chef((width-900,height),1,self.cola1) self.procesador2=Chef((width-700,height),2,self.cola2) self.procesador3=Chef((width-500,height),3,self.cola3) pygame.init() pygame.mixer.init() self.fondo = pygame.image.load("imagenes/cocina.png") self.intro = pygame.image.load("imagenes/intro.png") self.fondorect = self.fondo.get_rect() self.introrect = self.intro.get_rect() pygame.display.set_caption( "Chef Race (Universidad Distrital)" ) self.pizarra = pygame.image.load("imagenes/pizarra.png") self.sInicio = util.cargar_sonido('sonidos/inicio.wav') self.sHorno = util.cargar_sonido('sonidos/horno.wav') self.sCuchillo = util.cargar_sonido('sonidos/cuchillo.wav') self.sLicuadora = util.cargar_sonido('sonidos/licuadora.wav') self.sPrincipal = util.cargar_sonido('sonidos/principal.wav') self.pizarra1 = Pizarra((width-900,height)) self.pizarra2 = Pizarra((width-700,height)) self.pizarra3 = Pizarra((width-500,height)) self.receta1 = Receta((width,height)) self.receta2 = Receta((width+200,height)) self.receta3 = Receta((width+400,height)) self.comida1 = PolloConPapas(000,self.recursos[0],size) self.comida2 = Ensalada(111,self.recursos[1],size) self.comida3 = Malteada(222,self.recursos[2],size) self.listaChefs = [self.procesador1, self.procesador2, self.procesador3] self.listaPizarras = [self.pizarra1, self.pizarra2, self.pizarra3] self.listaRecetas = [self.receta1, self.receta2, self.receta3] self.listaComida = [self.comida1, self.comida2, self.comida3] self.cuchillos = CuchillosIma(size) self.licuadora = LicuadoraIma(size) self.horno = HornoIma(size) self.reloj = pygame.time.Clock() self.fuente1 = pygame.font.Font(None,70) self.fuente2 = pygame.font.Font(None,25) self.textoBienvenida = self.fuente1.render("Bienvenido a Chef Race UD", 1, (255,255,255)) self.textoAutor1 = self.fuente2.render("Marlon Arias", 1, (0,0,0)) self.textoAutor2 = self.fuente2.render("David Amado", 1, (0,0,0)) self.textoAutor3 = self.fuente2.render("Realizado por:", 1, (0,0,0)) def iniciar(self): self.sInicio.play() aux = 3 while aux > 0: screen.blit(self.intro, self.introrect) screen.blit(self.textoAutor1,(width-170,height-680)) screen.blit(self.textoAutor2,(width-170,height-660)) screen.blit(self.textoAutor3,(width-170,height-700)) screen.blit(self.textoBienvenida,((width-880, (height/2)+30))) pygame.display.update() time.sleep(1) aux=aux-1 self.sPrincipal.play(1) self.procesador1.start() self.procesador2.start() self.procesador3.start() self.hiloAnimacion = threading.Thread(name='Animacion', target = self.pintar) self.hiloEventos = threading.Thread(name='Animacion', target = self.capturarEventos) #self.hiloEventos.daemon=True self.hiloEventos.start() self.hiloAnimacion.daemon=True self.hiloAnimacion.start() self.cola1.join() self.cola2.join() self.cola3.join() self.hiloAnimacion.join() self.hiloEventos.join() def capturarEventos(self): while self.procesador1.uso or self.procesador2.uso or self.procesador3.uso: for event in pygame.event.get(): if event.type == pygame.QUIT: sys.exit() if event.type == pygame.MOUSEBUTTONDOWN: print("Evento ratonBtn capturado") for x in range(700, 760): for y in range(282, 342): proceso = Malteada(self.numMa,self.recursos[2],size) self.numMa+=1 estado="trabajandoLicuadora1" if event.button == 1 and event.pos == (x, y): self.cola1.put(proceso) self.procesador1.estado=estado self.pizarra1.arregloRecetas.append(proceso) print("pico el click izq") elif event.button == 2 and event.pos == (x, y): self.cola2.put(proceso) self.procesador2.estado=estado self.pizarra2.arregloRecetas.append(proceso) print("pico el click cent") elif event.button == 3 and event.pos == (x, y): self.cola3.put(proceso) self.procesador3.estado=estado self.pizarra3.arregloRecetas.append(proceso) print("pico el click der") for x in range(700, 760): for y in range(27, 87): proceso=PolloConPapas(self.numPo,self.recursos[0],size) self.numPo+=1 estado="trabajandoHorno1" if event.button == 1 and event.pos == (x, y): self.cola1.put(proceso) self.procesador1.estado=estado self.pizarra1.arregloRecetas.append(proceso) print("pico el click izq") elif event.button == 2 and event.pos == (x, y): self.cola2.put(proceso) self.procesador2.estado=estado self.pizarra2.arregloRecetas.append(proceso) print("pico el click cent") elif event.button == 3 and event.pos == (x, y): self.cola3.put(proceso) self.procesador3.estado=estado self.pizarra3.arregloRecetas.append(proceso) print("pico el click der") for x in range(700, 750): for y in range(137, 197): proceso=Ensalada(self.numEn,self.recursos[1],size) self.numEn+=1 estado="trabajandoCuchillo1" if event.button == 1 and event.pos == (x, y): self.cola1.put(proceso) self.procesador1.estado=estado self.pizarra1.arregloRecetas.append(proceso) print("pico el click izq") elif event.button == 2 and event.pos == (x, y): self.cola2.put(proceso) self.procesador2.estado=estado self.pizarra2.arregloRecetas.append(proceso) print("pico el click cent") elif event.button == 3 and event.pos == (x, y): self.cola3.put(proceso) self.procesador3.estado=estado self.pizarra3.arregloRecetas.append(proceso) print("pico el click der") def pintar(self): while self.procesador1.uso or self.procesador2.uso or self.procesador3.uso: self.reloj.tick(3) for elemento in self.listaChefs: elemento.update() time.sleep(0.5) screen.blit(self.fondo, self.fondorect) for elemento in self.listaChefs: screen.blit(elemento.image, elemento.rect) for elemento in self.listaPizarras: screen.blit(elemento.image, elemento.rect) for i in elemento.arregloRecetas: if elemento.arregloRecetas[elemento.arregloRecetas.index(i)].estado==0: screen.blit(i.iml, (elemento.rect[0]+30,elemento.rect[1]+elemento.arregloRecetas.index(i)*60+10)) elif elemento.arregloRecetas[elemento.arregloRecetas.index(i)].estado==1: screen.blit(i.imb, (elemento.rect[0]+30,elemento.rect[1]+elemento.arregloRecetas.index(i)*60+10)) elif elemento.arregloRecetas[elemento.arregloRecetas.index(i)].estado==2: screen.blit(i.ims, (elemento.rect[0]+30,elemento.rect[1]+elemento.arregloRecetas.index(i)*60+10)) elif elemento.arregloRecetas[elemento.arregloRecetas.index(i)].estado==3: screen.blit(i.ime, (elemento.rect[0]+30,elemento.rect[1]+elemento.arregloRecetas.index(i)*60+10)) elif elemento.arregloRecetas[elemento.arregloRecetas.index(i)].estado==4: elemento.arregloRecetas.remove(i) for elemento in self.listaRecetas: screen.blit(elemento.image, elemento.rect) for elemento in self.listaComida: screen.blit(elemento.iml, elemento.rect) screen.blit(self.cuchillos.image, self.cuchillos.rect) screen.blit(self.licuadora.image, self.licuadora.rect) screen.blit(self.horno.image, self.horno.rect) pygame.display.update() def crearProceso(self,nProcesos): for i in range(nProcesos): self.asignar_pedido_aleatorio() def asignar_pedido_aleatorio(self): aleatorio1=np.random.randint(3) aleatorio2=np.random.randint(3) if aleatorio1==0: proceso=PolloConPapas(self.numPo,self.recursos[0],size) self.numPo+=1 estado="trabajandoHorno1" elif aleatorio1==1: proceso=Ensalada(self.numEn,self.recursos[1],size) self.numEn+=1 estado="trabajandoCuchillo1" else: proceso= Malteada(self.numMa,self.recursos[2],size) self.numMa+=1 estado="trabajandoLicuadora1" if aleatorio2==0: self.cola1.put(proceso) self.procesador1.estado=estado elif aleatorio2==1: self.cola2.put(proceso) self.procesador2.estado=estado else: self.cola3.put(proceso) self.procesador3.estado=estado class Chef(Sprite, Procesador): def __init__(self, cont_size,idProcesador,*args): Sprite.__init__(self) Procesador.__init__(self,idProcesador,*args) self.cont_size = cont_size self.estados = ["espera", "trabajandoCuchillo1", "trabajandoCuchillo2", "trabajandoHorno1", "trabajandoHorno2", "trabajandoLicuadora1", "trabajandoLicuadora2"] self.estado = self.estados[0] self.imagenes = [util.cargar_imagen('imagenes/chef.png'), util.cargar_imagen('imagenes/chefCuchi.png'), util.cargar_imagen('imagenes/chefCuchi2.png'), util.cargar_imagen('imagenes/chefHorno.png'), util.cargar_imagen('imagenes/chefHorno2.png'), util.cargar_imagen('imagenes/chefLicu.png'), util.cargar_imagen('imagenes/chefLicu2.png')] self.image = self.imagenes[0] self.rect = self.image.get_rect() self.rect.move_ip(cont_size[0], cont_size[1]-250) def update(self): #animacion sprite if self.proceso==None: self.image = self.imagenes[0] print("el procesador",self,"no tiene proceso") else: if self.proceso.recurso.nombre=="Cuchillos": if self.estado == self.estados[1]: self.image = self.imagenes[1] self.estado = self.estados[2] else: self.image = self.imagenes[2] self.estado = self.estados[1] elif self.proceso.recurso.nombre=="Horno": if self.estado == self.estados[3]: self.image = self.imagenes[3] self.estado = self.estados[4] else: self.image = self.imagenes[4] self.estado = self.estados[3] else: if self.estado == self.estados[5]: self.image = self.imagenes[5] self.estado = self.estados[6] else: self.image = self.imagenes[6] self.estado = self.estados[5] cliente = cliente() cliente.iniciar()
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from django.urls import include, path from .apis import (UserEmailChange, UserGetApi, UserLoginApi, UserLogoutApi, UserPasswordChange, UserPasswordReset, UserPasswordResetCheck, UserRegisterApi, UserRegisterVerifyApi, UserRegisterVerifyCheckApi, UserUpdateApi) authentication_urls = [ path('register/', UserRegisterApi.as_view(), name='register'), path('register/verify/<int:user_id>/', UserRegisterVerifyApi.as_view(), name='register_verify'), path('register/verify_check/<int:user_id>/', UserRegisterVerifyCheckApi.as_view(), name='register_verify_check'), path('login/', UserLoginApi.as_view(), name='login'), path('logout/', UserLogoutApi.as_view(), name='logout'), path('password_reset/', UserPasswordReset.as_view()), path('password_reset_check/', UserPasswordResetCheck.as_view()), path('password_change/<int:user_id>/', UserPasswordChange.as_view(), name='password_change'), path('email_change/<int:user_id>/', UserEmailChange.as_view(), name='email_change'), path('get/<int:user_id>/', UserGetApi.as_view(), name='get'), ] drivers_urls =[ path('update/<int:user_id>/', UserUpdateApi.as_view(), name='update') ] urlpatterns =[ path('auth/', include((authentication_urls, 'auth'))), path('driver/', include((drivers_urls, 'driver'))) ]
[ "italobarzola18@gmail.com" ]
italobarzola18@gmail.com
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/BK_Scripts/shapes.py
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permissive
bkvignesh/manim
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from manimlib.imports import * from math import cos, sin, pi import numpy as np class Shapes(Scene): def construct(self): circle = Circle(color = YELLOW) square = Square(color = DARK_BLUE) square.surround(circle) rectangle = Rectangle(height=2, width=3, color=RED) ring = Annulus(inner_radius=.2, outer_radius=1, color=BLUE) ring2 = Annulus(inner_radius=.6, outer_radius=1, color=BLUE) ring3 = Annulus(inner_radius=.2, outer_radius=1, color=BLUE) ellipse = Ellipse(width=5, height=3, color=DARK_BLUE) pointers = [] for i in range(8): pointers.append(Line(ORIGIN, np.array([cos(pi/180*360/8*i),sin(pi/180*360/8*i), 0]), color = YELLOW)) self.add(circle) self.play(FadeIn(square)) self.play(Transform(square, rectangle)) self.play(FadeOut(circle), FadeIn(ring)) self.play(Transform(ring, ring2)) self.play(Transform(ring2, ring3)) self.play(FadeOut(square), GrowFromCenter(ellipse), Transform(ring2, ring)) self.add(*pointers) self.wait(2)
[ "vigneshbk42@gmail.com" ]
vigneshbk42@gmail.com
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/tpfa/boundary_conditions.py
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import numpy as np from scipy.sparse import csr_matrix, lil_matrix class BoundaryConditions(): def __init__(self, num_elements, nx, ny, coef): self.coef = coef self.num_elements = num_elements self.nx = nx self.ny = ny self.coef, self.q = self.pressao_prescrita() def pressao_prescrita(self): self.q = lil_matrix((self.num_elements, 1), dtype=np.float_) self.coef[0:self.nx*self.ny] = 0 self.q [0:self.nx*self.ny] = 500 self.coef[self.num_elements-(self.nx*self.ny):self.num_elements] = 0 for r in range(self.nx*self.ny): self.coef[r,r] = 1 self.coef[r+self.num_elements-(self.nx*self.ny),r+self.num_elements-(self.nx*self.ny)] = 1 return self.coef, self.q
[ "renatattavares@hotmail.com" ]
renatattavares@hotmail.com
9b0b34eb1b3a8edde6ec56f298ac3c0a5bbe79f7
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/eurito_daps/flaskblog.py
74bf352313b346746653461bbfeb148f1c63290a
[]
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porter22/porter22.github.io
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refs/heads/master
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from flask import Flask, render_template, url_for from flask_sqlalchemy import SQLAlchemy from datetime import datetime app = Flask(__name__) #instantiated flask variable app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///site.db' #/// relative path from the current dir db = SQLAlchemy(app) #create database instance class User(db.Model): id = db.Column(db.Integer, primary_key=True) username = db.Column(db.String(20), unique=True) email = db.Column(db.String(120), unique=True, nullable=False) image_file = db.Column(db.String(20), nullable=False, default='default.jpg') password = db.Column(db.String(60), nullable=False) posts = db.relationship('Post', backref='author', lazy=True) # one author can have multiple posts, but a post can have only one author: one to many relationship def __repr__(self): #how object is printed return f"User('{self.username}', '{self.email}', '{self.image_file}')" class Post(db.Model): id = db.Column(db.Integer, primary_key=True) title = db.Column(db.String(100), nullable=False) data_posted = db.Column(db.DateTime, nullable=False, default = datetime.utcnow ) content = db.Column(db.Text, nullable=False) user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False) def __repr__(self): #how object is printed return f"Post('{self.title}', '{self.data_posted}')" posts = [ { 'author': 'Corey Schafer', 'title': 'Blog Post 1', 'content': 'First post content', 'date_posted': 'April 20, 2018' }, { 'author': 'Jane Doe', 'title': 'Blog Post 2', 'content': 'Second post content', 'date_posted': 'April 21, 2018' } ] @app.route("/") @app.route("/home") def home(): return render_template('home.html', posts = posts) @app.route("/about") def about(): return render_template('about.html', title = 'About') #this is so that we will not have to restart the server whenever new changes are introduced if __name__ == '__main__': app.run(debug=True)
[ "idrissov22@gmail.com" ]
idrissov22@gmail.com
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428dd6e4ab9ee4916664f13a25f04ae424769d47
/pwd.py
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[]
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licmnn/pwd
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#password = 'a123456' #x = 3 #while x > 0: # pw = input('่ฏท่พ“ๅ…ฅๅฏ†็ ๏ผš ') # if pw == password: # print('็™ปๅ…ฅๆˆๅŠŸ') # quit # break # elif x != 0: # x = x - 1 # print('ๅฏ†็ ้”™่ฏฏ๏ผ ่ฟ˜ๆœ‰%dๆฌกๆœบไผš๏ผ' % x) # else: # pirnt('') ''' pw = input('่ฏท่พ“ๅ…ฅๆ‚จ็š„ๅฏ†็ ๏ผš ') x = 2 print('ๅฏ†็ ้”™่ฏฏ๏ผ ่ฟ˜ๆœ‰%dๆฌกๆœบไผš ' % x) while x > 0 : if pw != 'a123456' and x > 0: pw = input('่ฏท่พ“ๅ…ฅๆ‚จ็š„ๅฏ†็ ๏ผš ') x = x - 1 print('ๅฏ†็ ้”™่ฏฏ๏ผ ่ฟ˜ๆœ‰%dๆฌกๆœบไผš ' % x) elif x == 0: print('ๅฏ†็ ้”™่ฏฏ๏ผ็ญๆœ‰ๆœบไผšไบ†') elif pw == 'a123456': print('็™ปๅ…ฅๆˆๅŠŸ') ''' password = 'a123456' x = 3 while x > 0: x = x -1 pw = input('่ฏท่พ“ๅ…ฅๅฏ†็ ๏ผš ') if pw == password: print('็™ปๅ…ฅๆˆๅŠŸ') # quit break else: # x = x -1 print('ๅฏ†็ ้”™่ฏฏ๏ผ') if x > 0: print('่ฟ˜ๆœ‰%dๆฌกๆœบไผš๏ผ' % x) else: print('ๆฒกๆœ‰ๆœบไผšไบ†๏ผŒ่ดฆๅท้”ๅฎš๏ผ')
[ "licmn@live.com" ]
licmn@live.com
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/srezy.py
eb59c4eaa583d3111c0c3b1040beb6c6948da6cd
[]
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NosevichOleksandr/firstrepository
ced760563a039af88dd1a5588ba0553e5e0cdef6
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refs/heads/master
2023-04-02T02:46:50.723173
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print('hello world') a = input('write your ... something: ') if len(a) % 2 == 0: b = a[:len(a)//2] c = a[len(a)//2:][::-1] print(b + c) else: print('ั‚ั‹ ะฝะตะฟั€ะฐะฒะธะปัŒะฝะพ ะฒะฒะตะป')
[ "bpxnastalgia@gmail.com" ]
bpxnastalgia@gmail.com
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/main.py
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ahaggart/image-shatter
db00662c85c6f8b698008757fc38e9b42d733d91
cca1a392bc3445b117e413bcdb8fd473de82ebfe
refs/heads/master
2020-05-26T21:55:49.783242
2019-05-24T11:03:48
2019-05-24T11:03:48
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import argparse import cv2 as cv from blobs import caluculate_colorspace_distances, grow_blobs from polygons import find_edges, order_edges from colorize import color_blobs, color_edges, color_ordered def main(config): image = cv.imread('img/' + config.file) width, height = image.shape[:2] print("Calculating colorspace distances...") xdist, ydist = caluculate_colorspace_distances(image) print("Growing blobs...") blobs = grow_blobs(width, height, xdist, ydist) print("> Num blobs: {}".format(blobs.index)) edges = find_edges(blobs) ordered = order_edges(edges) print("Coloring blobs...") # colors = color_blobs(image, blobs) # colors = color_edges(edges, width, height) colors = color_ordered(ordered, width, height) print("Writing image...") cv.imwrite('out/' + config.file, colors) if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument( "file", help="the path to the file within the img/ directory", ) main(parser.parse_args())
[ "alex.haggart@gmail.com" ]
alex.haggart@gmail.com
f1b79ea5db5f487fdf2cfc2259c01ffb58418ed7
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/tsne-test.py
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[]
no_license
briantimar/nn-test1
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980b29b3909c6b9539a06e771f3fafbc413a2a14
refs/heads/master
2020-03-19T15:20:28.541618
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Jun 14 00:13:18 2018 @author: btimar Visualizing ground states? """ import sys import numpy as np import tensorflow as tf sys.path.append("/Users/btimar/Documents/ryd-theory-code/python_code") from ryd_base import make_1d_TFI_spin from tools import get_sent from quspin.operators import hamiltonian from tsne import tsne def z(i, basis): static = [['z', [[1.0, i]]]] return hamiltonian(static, [], basis=basis) def zz(i, j, basis): static = [['zz', [[1.0, i, j]]]] return hamiltonian(static, [], basis=basis, dtype=np.float64) def make_labels(gvals): return (gvals <1).astype(int) def get_features(gvals, basis): N=len(gvals) s = np.empty((N, basis.Ns)) for i in range(N): h = make_1d_TFI_spin(1, gvals[i], basis, dtype=np.float64) _, psi0 = h.eigsh(k=1, which='SA') s[i, :] = psi0.reshape(basis.Ns) return s from quspin.basis import spin_basis_1d L=8 basis = spin_basis_1d(L, kblock=0, pblock=1) basis_full = spin_basis_1d(L) proj=basis.get_proj(np.float64) N=500 gvals = np.linspace(0, 2.0, N) states = get_features(gvals, basis) labels = make_labels(gvals) psi_full = np.asarray(proj.todense().dot( features.transpose())) zzops = [zz(0, i, basis_full) for i in range(1,L//2)] features = np.empty((N, len(zzops))) for i in range(len(zzops)): features[:, i] = zzops[i].expt_value(psi_full) from tools import overlap overlaps = [np.abs(overlap(features[i, :], features[-1, :]))**2 for i in range(N-1)] zz1 = zz1op.expt_value(psi_full) #tSNE params no_dims = 2 #dimensionality of raw data d = features.shape[1] initial_dims = d perplexity = 30.0 print("Passing to tsne") y = tsne(features, no_dims=no_dims, initial_dims=initial_dims, perplexity=perplexity) import matplotlib.pyplot as plt from EDIO import save fig, ax=plt.subplots() plt.scatter(y[:, 0], y[:, 1], c=labels) #save(fig, "20180613/tsne-tfi-symm-wfs-L={0}".format(L),which='mac') blockA = (y[:, 1]>0)*(y[:, 0]<15) blockB = np.logical_not(blockA) plt.plot(gvals[blockA], zz1[blockA], label='A') plt.plot(gvals[blockB], zz1[blockB], 'rx',label='B')
[ "timarbrian@gmail.com" ]
timarbrian@gmail.com
a6d1b05a1ca185859368e58727850feec6b840f5
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/.venv/bin/chardetect
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[]
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obiorbitalstar/chess-board
f65e5706405e4a420dfc843b5f18c39a1f16cc7d
0bb61022fd49a6361813d894f28bcd99c07766aa
refs/heads/Master
2022-12-18T01:56:50.652476
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2020-08-30T13:43:38
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2020-08-30T13:43:39
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#!/home/orphues/codefellows/401/chess-board/.venv/bin/python3 # -*- coding: utf-8 -*- import re import sys from chardet.cli.chardetect import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0]) sys.exit(main())
[ "obiorbitalstar@gmail.com" ]
obiorbitalstar@gmail.com
ab6f49788e9c9b703b8119182f349d2b181ec92c
f907f8ce3b8c3b203e5bb9d3be012bea51efd85f
/kaki.py
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[]
no_license
KohsukeKubota/Atcoder-practice
3b4b986395551443f957d1818d6f9a0bf6132e90
52554a2649445c2760fc3982e722854fed5b8ab1
refs/heads/master
2020-08-26T15:17:29.344402
2019-10-26T11:14:24
2019-10-26T11:14:24
217,052,829
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py
S = [input() for _ in range(12)] cnt = 0 for s in S: set_ = set(s) if 'r' in set_: cnt += 1 print(cnt)
[ "kohsuke@KohsukeKubotas-MacBook-Air.local" ]
kohsuke@KohsukeKubotas-MacBook-Air.local
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/opentcweb/settings/prod.py
fd788fb20c554254729032aeabf64156243e772a
[ "MIT" ]
permissive
cahya-wirawan/opentc-web
c8e758835d129cf7edb6f9dbf640632c2aa9ff2f
fa74c49f3f2b1a74624deca912f7da87afdc7e1b
refs/heads/master
2021-01-19T19:13:44.629858
2018-01-21T13:21:32
2018-01-21T13:21:32
88,406,223
1
0
null
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null
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UTF-8
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py
from __future__ import absolute_import from .base import * # Production overrides DEBUG = False #...
[ "cahya.wirawan@gmail.com" ]
cahya.wirawan@gmail.com
46b52fe8e5c60205d2161d38dc9193d19d105f9e
cba90cdd06eced813be6ad80e6295587223c4600
/betfairlightweight/endpoints/navigation.py
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[ "MIT" ]
permissive
mberk/betfair
1a22528b881e02567626dbe7e8c4f0197809c38e
6b064a68c8d2afceda81b70d74b6a0ee9601f228
refs/heads/master
2023-03-07T02:33:06.443407
2022-08-16T08:06:10
2022-08-16T08:06:10
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MIT
2023-03-01T12:03:37
2019-06-20T19:28:23
Python
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import requests from ..exceptions import APIError, InvalidResponse from ..utils import check_status_code from .baseendpoint import BaseEndpoint from ..compat import json class Navigation(BaseEndpoint): """ Navigation operations. """ def list_navigation(self, session: requests.Session = None) -> dict: """ This Navigation Data for Applications service allows the retrieval of the full Betfair market navigation menu from a compressed file. :param requests.session session: Requests session object :rtype: json """ return self.request(session=session) def request( self, method: str = None, params: dict = None, session: requests.Session = None ) -> (dict, float): session = session or self.client.session try: response = session.get( self.url, headers=self.client.request_headers, timeout=(self.connect_timeout, self.read_timeout), ) except requests.ConnectionError as e: raise APIError(None, method, params, e) except Exception as e: raise APIError(None, method, params, e) check_status_code(response) try: response_json = json.loads(response.content.decode("utf-8")) except ValueError: raise InvalidResponse(response.text) return response_json @property def url(self) -> str: return self.client.navigation_uri
[ "paulingliam@gmail.com" ]
paulingliam@gmail.com
42cd98f60f8637e2f8b57280dee6eeb14f3eac98
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/src/modules/customised/payroll/hra/__init__.py
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[]
no_license
kakamble-aiims/work
ba6cbaf4c525ff7bc28d0a407f16c829d0c35983
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refs/heads/master
2022-04-02T14:45:58.515014
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false
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py
from trytond.pool import Pool from .hra import * def register(): Pool.register( HRA_Allowance, module='hra', type_='model')
[ "kakamble.aiims@gmail.com" ]
kakamble.aiims@gmail.com
fb12aa0f0a717a88fe55aac5ace8b0cda17fdc54
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/club/app/migrations/0026_paquete_inscrito_horas_consumidas.py
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[]
no_license
Rob866/club
eb26c3085bb37908226bfed306d98538eed64dff
f2e58ca773a4e461a9905c0898c1f11bd5e94099
refs/heads/master
2022-12-16T00:07:32.423945
2020-01-09T04:38:09
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0
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# Generated by Django 2.2.6 on 2019-10-15 20:29 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('app', '0025_auto_20191015_1240'), ] operations = [ migrations.AddField( model_name='paquete_inscrito', name='horas_consumidas', field=models.DurationField(default=datetime.timedelta(0)), ), ]
[ "juanrob_10@hotmail.com" ]
juanrob_10@hotmail.com
6722bcef452c085f75a486160d1e49a88934b6c6
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/urls.py
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[]
no_license
Engaginglab/scoreit
91a7cc4b610556b45355bdd32c4c608dc2993edd
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refs/heads/master
2021-01-10T19:58:05.162232
2012-09-22T14:34:48
2012-09-22T14:34:48
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0
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UTF-8
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py
from django.contrib import admin from django.conf.urls.defaults import * admin.autodiscover() urlpatterns = patterns('', (r'^auth/', include('auth.urls')), (r'^handball/', include('handball.urls')), (r'^admin/', include(admin.site.urls)) )
[ "martin@maklesoft.com" ]
martin@maklesoft.com
dd8ff876cdff51683095b93c5c1e9985b5a29584
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/superhero/ability_and_armor.py
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[]
no_license
makhmudislamov/fun_python_exercises
f3c7557fa6ed400ee196252a84ad7b6b23b913f1
21ab89540fb5f4f04dbdb80f361bf4febd694c11
refs/heads/master
2020-05-26T05:42:20.115833
2019-10-17T03:28:57
2019-10-17T03:28:57
188,125,045
0
0
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py
from random import randint class Ability: def __init__(self, name, max_damage): ''' Initialize the values passed into this method as instance variables. ''' self.name = name self.max_damage = max_damage def __str__(self): return f'This ability is {self.name}' def ability_attack(self): ''' Use randint(a, b) to select a random attack value. Return an attack value between 0 and the full attack. ''' attack_value = randint(0, self.max_damage) # print(f"attack value in ability: {attack_value}") self.max_damage -= attack_value return attack_value class Weapon(Ability): def ability_attack(self): """ This method returns a random value between one half to the full attack power of the weapon. """ return randint(self.max_damage // 2, self.max_damage) class Armor(): def __init__(self, name, max_block): ''' Initialize the values passed into this method as instance variables. ''' self.name = name self.max_block = max_block def block(self): ''' Return a random value between 0 and the initialized max_block strength. ''' block_value = randint(0, self.max_block) return block_value # if __name__ == "__main__": # pass
[ "sunnatovichvv@gmail.com" ]
sunnatovichvv@gmail.com
0cd44d57984873ff2dd3d1e25064b5bc50b880c1
23fdc97552b7e55b8c5e5eca3046ee95eb29d43c
/leetcode/leetcode_111.py
db8f1ff94b73fffc72e5a91a64d84064cc74e9ef
[]
no_license
qiqimaochiyu/tutorial-python
b999ef63026d05045a33225b1fbe2a5919422961
a0d50946859798a642aaacdc31fa97cc015ae615
refs/heads/master
2018-10-04T18:12:18.017065
2018-06-26T09:23:50
2018-06-26T09:23:50
90,226,235
2
1
null
null
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UTF-8
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532
py
# Definition for a binary tree node. # class TreeNode: # def __init__(self, x): # self.val = x # self.left = None # self.right = None class Solution: def minDepth(self, root): """ :type root: TreeNode :rtype: int """ if not root: return 0 if not (root.left) or not (root.right): return self.minDepth(root.left) + self.minDepth(root.right) + 1 return min(self.minDepth(root.left), self.minDepth(root.right)) + 1
[ "noreply@github.com" ]
qiqimaochiyu.noreply@github.com
90208cdc6c60917016382d39760b8a3bb14ff4d3
8d34c0d29b69028fb1da01499fdac19f9762a8e1
/lib/python2.7/sunlight/service.py
cf069d357b54bd46632e3a1b8417e69f90c7f8b1
[]
no_license
politicrowd/politicrowd
87a98689724c288b5400acd0de6fb7fae7e058d4
e62c89d234a59f6c7d56fae2c8af6074f426c265
refs/heads/master
2021-01-20T00:55:48.083054
2013-07-30T00:14:08
2013-07-30T00:14:08
null
0
0
null
null
null
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UTF-8
Python
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py
# Copyright (c) Sunlight Labs, 2012 under the terms and conditions # of the LICENSE file. """ .. module:: sunlight.service :synopsis: Sunlight API Superclass Base service class. All API classes (such as say - :class:`sunlight.services.openstates.OpenStates`) inherit from this. """ import sys import sunlight.config import sunlight.errors if sys.version_info[0] >= 3: from urllib.parse import urlencode from urllib.request import urlopen from urllib.error import HTTPError else: from urllib import urlencode from urllib2 import urlopen from urllib2 import HTTPError class Service: """ Base class for all the API implementations, as well as a bunch of common code on how to actually fetch text over the network. """ def get(self, top_level_object, **kwargs): """ Get some data from the network - this is where we actually fetch something and make a request. .. warning:: Be sure that API_KEY was set before calling this method. This will throw a :class:`sunlight.errors.NoAPIKeyException` if the API_KEY is not set. args: ``top_level_object`` (str): Thing to query for (such as say, "bills" for OpenStates ) kwargs: These arguments will be passed to the underlying API implementation to help create a query. Validation will happen down below, and on a per-API level. """ if not sunlight.config.API_KEY: raise sunlight.errors.NoAPIKeyException( "Warning: Missing API Key. please visit " + sunlight.config.API_SIGNUP_PAGE + " to register for a key.") url = self._get_url(top_level_object, sunlight.config.API_KEY, **kwargs) try: r = urlopen(url) return_data = r.read().decode('utf8') return self._decode_response(return_data) except HTTPError as e: message = e.read() code = e.getcode() ex = sunlight.errors.BadRequestException("Error (%s) -- %s" % ( code, message )) ex.url = e.geturl() ex.message = message ex.code = code raise ex
[ "paul@politicrowd.com" ]
paul@politicrowd.com
7be265dac32863a3cb746a50679f132f3cfc6705
7d17375998378125fa63b1cf8673b8387d99324f
/core/migrations/0006_auto_20200517_0929.py
07187c5d3c0bad2459578712f836c9dcc72447db
[]
no_license
priyanka1698/Late-checker
c2f96993340f09c55bd9eac2261cc760c409eae9
ff1c4615b3abefd65fa789fcd1e684322ddfc9de
refs/heads/master
2022-08-19T15:22:00.692770
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2020-05-20T11:45:35
null
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Python
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# Generated by Django 3.0.5 on 2020-05-17 09:29 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('core', '0005_delete_image'), ] operations = [ migrations.CreateModel( name='Timing', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('start', models.TimeField()), ('end', models.TimeField()), ], ), migrations.RenameModel( old_name='Station', new_name='Gate', ), migrations.RenameField( model_name='gate', old_name='station_no', new_name='no', ), migrations.RenameField( model_name='log', old_name='entry_station', new_name='entry_gate', ), migrations.RenameField( model_name='log', old_name='exit_station', new_name='exit_gate', ), migrations.RemoveField( model_name='log', name='entry_image', ), migrations.RemoveField( model_name='log', name='exit_image', ), migrations.RemoveField( model_name='log', name='fare', ), migrations.AddField( model_name='log', name='entry_status', field=models.CharField(choices=[('late', 'late'), ('early', 'early'), ('on time', 'on time'), ('in office', 'in office')], default='on time', max_length=100), ), migrations.AddField( model_name='log', name='exit_status', field=models.CharField(choices=[('late', 'late'), ('early', 'early'), ('on time', 'on time'), ('in office', 'in office')], default='on time', max_length=100), ), ]
[ "sanyam19092000@gmail.com" ]
sanyam19092000@gmail.com
eaed7c034ea788beec33f6c9b31938383407cb09
7c98bee73fdd64a8fa08dc3a94e520b175ac190e
/bin/rst2latex.py
311af3f8a994b04f7ad5f9f586bc0e1fc7cd2fcd
[]
no_license
Barry-Chen-Intersective/Proj-Api-Test
97015eccb4b6d1652ca8809cbb8ddbe1132008c0
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#!/Library/Frameworks/Python.framework/Versions/2.7/Resources/Python.app/Contents/MacOS/Python # $Id: rst2latex.py 5905 2009-04-16 12:04:49Z milde $ # Author: David Goodger <goodger@python.org> # Copyright: This module has been placed in the public domain. """ A minimal front end to the Docutils Publisher, producing LaTeX. """ try: import locale locale.setlocale(locale.LC_ALL, '') except: pass from docutils.core import publish_cmdline description = ('Generates LaTeX documents from standalone reStructuredText ' 'sources. ' 'Reads from <source> (default is stdin) and writes to ' '<destination> (default is stdout). See ' '<http://docutils.sourceforge.net/docs/user/latex.html> for ' 'the full reference.') publish_cmdline(writer_name='latex', description=description)
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# Generated by Django 3.1.5 on 2021-06-18 00:48 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='TaskList', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('task', models.CharField(max_length=300)), ('done', models.BooleanField(default=False)), ], ), ]
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# coding: utf-8 """ Quickpac API Here you will find all public interfaces to the Quickpac system. # noqa: E501 OpenAPI spec version: v1.00 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import quickpac from quickpac.models.mode_type import ModeType # noqa: E501 from quickpac.rest import ApiException class TestModeType(unittest.TestCase): """ModeType unit test stubs""" def setUp(self): pass def tearDown(self): pass def testModeType(self): """Test ModeType""" # FIXME: construct object with mandatory attributes with example values # model = quickpac.models.mode_type.ModeType() # noqa: E501 pass if __name__ == '__main__': unittest.main()
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import random, time from datetime import datetime from django.shortcuts import render from rest_framework import viewsets from rest_framework import status from rest_framework import permissions from rest_framework import authentication from rest_framework import mixins from rest_framework.response import Response from rest_framework.views import APIView from rest_framework_jwt.authentication import JSONWebTokenAuthentication from utils.permissions import IsOwnerOrReadOnly from utils.alipay import AliPay from .serializers import ShopCartSerializer,ShopCartDetailSerializer, OrderSerializer, OrderDetailSerializer from .models import ShoppingCart, OrderInfo, OrderGoods from mxshop.settings import appid, private_key_path, alipay_pub_key_path, alipay_notify_url, alipay_return_url # Create your views here. class ShoppingCartViewset(viewsets.ModelViewSet): """ ่ดญ็‰ฉ่ฝฆๅŠŸ่ƒฝ list: ่Žทๅ–่ดญ็‰ฉ่ฝฆ็‰ฉๅ“ๅˆ—่กจ create: ๅŠ ๅ…ฅ่ดญ็‰ฉ่ฝฆ็‰ฉๅ“ delete: ๅˆ ้™ค่ดญ็‰ฉ่ฝฆ็‰ฉๅ“ update: ๆ›ดๆ–ฐ่ดญ็‰ฉ่ฝฆ็‰ฉๅ“ """ authentication_classes = (JSONWebTokenAuthentication, authentication.SessionAuthentication) permission_classes = (permissions.IsAuthenticated, IsOwnerOrReadOnly) lookup_field = "goods_id" # override get_serializer_class method, if list return DetailSerializer def get_serializer_class(self, *args, **kwargs): if self.action == 'list': return ShopCartDetailSerializer else: return ShopCartSerializer def get_queryset(self): return ShoppingCart.objects.filter(user=self.request.user) class OrderViewset(mixins.ListModelMixin, mixins.CreateModelMixin, mixins.RetrieveModelMixin, mixins.DestroyModelMixin, viewsets.GenericViewSet): """ ่ฎขๅ•็ฎก็† List: ่Žทๅ–่ฎขๅ• Delete: ๅˆ ้™ค่ฎขๅ• Create: ๆ–ฐๅขž่ฎขๅ• Retrieve: ่Žทๅ–่ฎขๅ•่ฏฆๆƒ… """ authentication_classes = (JSONWebTokenAuthentication, authentication.SessionAuthentication) permission_classes = (permissions.IsAuthenticated, IsOwnerOrReadOnly) serializer_class = OrderSerializer def get_queryset(self): return OrderInfo.objects.filter(user=self.request.user) def get_serializer_class(self): if self.action == 'retrieve': return OrderDetailSerializer else: return OrderSerializer # ็”Ÿๆˆ่ฎขๅ•ๅท ๅฝ“ๅ‰ๆ—ถ้—ด+userid+random def generate_order_sn(self): random_int = random.Random() order_sn = "{time_str}{userid}{random_str}".format(time_str=time.strftime('%Y%m%d%H%M%S'), userid=self.request.user.id, random_str=random_int.randint(10, 99)) return order_sn # ๅœจๅˆ›ๅปบ่ฎขๅ•ๆ—ถ๏ผŒ้‡่ฝฝ perform_create ๆ–นๆณ•, set order_sn in serializer.data def perform_create(self, serializer): """ ๅœจๅˆ›ๅปบ่ฎขๅ•ๆ—ถ๏ผŒๅ…ณ่”่ฎขๅ•ไธญ็š„ๅ•†ๅ“๏ผŒๆถˆๅ‡ๅ•†ๅ“ๅบ“ๅญ˜๏ผŒๆธ…็ฉบ่ดญ็‰ฉ่ฝฆ """ # ไฟๅญ˜ๅฝ“ๅ‰็”จๆˆท็š„่ฎขๅ• order = serializer.save(order_sn=self.generate_order_sn()) # ่Žทๅ–ๅฝ“ๅ‰็”จๆˆท่ดญ็‰ฉ่ฝฆๅ†…ๆ‰€ๆœ‰ๅ•†ๅ“ๆก็›ฎ shop_carts = ShoppingCart.objects.filter(user=self.request.user) # ๆŠŠๅ•†ๅ“ใ€ๅ•†ๅ“ๆ•ฐ้‡ๆ”พๅ…ฅๅฎšๅ•๏ผŒๅบ“ๅญ˜็›ธๅบ”ๆถˆๅ‡๏ผŒๅนถๆธ…็ฉบ่ดญ็‰ฉ่ฝฆ for shop_cart in shop_carts: # ็”Ÿๆˆ่ฎขๅ•ๅ•†ๅ“ๅฏน่ฑก order_goods = OrderGoods() # ๆŠŠๅ•†ๅ“ใ€ๅ•†ๅ“ๆ•ฐ้‡ๆ”พๅ…ฅ่ฎขๅ•ๅ•†ๅ“ๅฏน่ฑก order_goods.goods = shop_cart.goods order_goods.goods_num = shop_cart.nums # ๅฏนๅ•†ๅ“็š„ๅบ“ๅญ˜็›ธๅบ”ๆถˆๅ‡ order_goods.goods.goods_num -= order_goods.goods_num order_goods.goods.save() # ๆ”พๅ…ฅ่ฎขๅ•ๅฏน่ฑกๅนถไฟๅญ˜ order_goods.order = order order_goods.save() # ๆธ…็ฉบ่ดญ็‰ฉ่ฝฆ shop_cart.delete() return order # ๅœจๅˆ ้™ค่ฎขๅ•ๆ—ถ๏ผŒ้‡่ฝฝ perform_destroy ๆ–นๆณ•๏ผŒๅฎž็Žฐ่ฎขๅ•ๅ•†ๅ“ๅบ“ๅญ˜ๅขžๅŠ  def perform_destroy(self, instance): if instance.pay_status != "TRADE_SUCCESS": # ๅœจๅˆ ้™ค่ฎขๅ•ๅ‰๏ผŒๅฆ‚ๆžœ่ฎขๅ•ๆฒกๆœ‰ๆ”ฏไป˜ๆˆๅŠŸ๏ผŒๅขžๅŠ ่ฟ™ไธช่ฎขๅ•ไธญ็š„ๆ‰€ๆœ‰ๅ•†ๅ“ๅฏนๅบ”ๆ•ฐ้‡็š„ๅบ“ๅญ˜ order_goods = OrderGoods.objects.filter(order=instance.id) for order_good in order_goods: order_good.goods.goods_num += order_good.goods_num order_good.goods.save() instance.delete() class AliPayViewset(APIView): def get(self, request): """ ๅค„็†ๆ”ฏไป˜ๅฎreturn_url ่ฟ”ๅ›ž :param request: :return: """ processed_dict = {} for key, value in request.GET.items(): processed_dict[key] = value sign = processed_dict.pop("sign", None) alipay = AliPay( appid=appid, app_notify_url=alipay_notify_url, app_private_key_path=private_key_path, alipay_public_key_path=alipay_pub_key_path, # ๆ”ฏไป˜ๅฎ็š„ๅ…ฌ้’ฅ๏ผŒ้ชŒ่ฏๆ”ฏไป˜ๅฎๅ›žไผ ๆถˆๆฏไฝฟ็”จ๏ผŒไธๆ˜ฏไฝ ่‡ชๅทฑ็š„ๅ…ฌ้’ฅ, debug=True, # ้ป˜่ฎคFalse, return_url=alipay_return_url, ) verify_re = alipay.verify(processed_dict, sign) if verify_re is True: # order_sn = processed_dict.get('out_trade_no', None) # trade_no = processed_dict.get('trade_no', None) # trade_status = processed_dict.get('trade_status', None) # existed_orders = OrderInfo.objects.filter(order_sn=order_sn) # for existed_order in existed_orders: # existed_order.pay_status = trade_status # existed_order.trade_no = trade_no # existed_order.pay_time = datetime.now() # existed_order.save() return Response("success") def post(self, request): """ ๅค„็†ๆ”ฏไป˜ๅฎnotify_url ่ฟ”ๅ›ž :param request: :return: """ processed_dict = {} for key, value in request.POST.items(): processed_dict[key] = value print(key, value) sign = processed_dict.pop("sign", None) alipay = AliPay( appid=appid, app_notify_url=alipay_notify_url, app_private_key_path=private_key_path, alipay_public_key_path=alipay_pub_key_path, # ๆ”ฏไป˜ๅฎ็š„ๅ…ฌ้’ฅ๏ผŒ้ชŒ่ฏๆ”ฏไป˜ๅฎๅ›žไผ ๆถˆๆฏไฝฟ็”จ๏ผŒไธๆ˜ฏไฝ ่‡ชๅทฑ็š„ๅ…ฌ้’ฅ, debug=True, # ้ป˜่ฎคFalse, return_url=alipay_return_url, ) verify_re = alipay.verify(processed_dict, sign) if verify_re is True: order_sn = processed_dict.get('out_trade_no', None) trade_no = processed_dict.get('trade_no', None) trade_status = processed_dict.get('trade_status', None) existed_orders = OrderInfo.objects.filter(order_sn=order_sn) for existed_order in existed_orders: existed_order.pay_status = trade_status # ๅฆ‚ๆžœๆ”ฏไป˜ๆˆๅŠŸ๏ผŒๆŠŠ่ฎขๅ•ไธญๆ‰€ๆœ‰ๅ•†ๅ“ๅ”ฎๅ‡บๆ•ฐ้‡ๅš็›ธๅบ”ๅขžๅŠ (ๆณจ๏ผš่ฟ™ไธชๆ“ไฝœไธ่ฆๆฑ‚ๅฎžๆ—ถ๏ผŒๅปบ่ฎฎ็”จๅŽๅฐ็จ‹ๅบๆฅๅฎŒๆˆไผšๆ›ดๅฅฝ) if existed_order.pay_status == "TRADE_SUCCESS": order_goods = existed_order.goods.all() for order_good in order_goods: order_good.goods.sold_num += order_good.goods_num order_good.goods.save() existed_order.trade_no = trade_no existed_order.pay_time = datetime.now() existed_order.save() return Response("success")
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""" Django settings for site02 project. For more information on this file, see https://docs.djangoproject.com/en/1.6/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.6/ref/settings/ """ # Build paths inside the project like this: os.path.join(BASE_DIR, ...) import os BASE_DIR = os.path.dirname(os.path.dirname(__file__)) TEMPLATE_DIRS = ( os.path.join(BASE_DIR, 'templates'), ) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.6/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'y97upk5xk__c@j95sw4v-pf&#i45ir$cm6-ya)byzikor7+2sv' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True TEMPLATE_DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = ( 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'approver', 'poster' ) MIDDLEWARE_CLASSES = ( 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ) ROOT_URLCONF = 'site02.urls' WSGI_APPLICATION = 'site02.wsgi.application' # Database # https://docs.djangoproject.com/en/1.6/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'TweetApprover.db'), } } # Internationalization # https://docs.djangoproject.com/en/1.6/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.6/howto/static-files/ STATIC_URL = '/static/' # from this point on MY consts TWEET_APPROVER_EMAIL = 'georstef@gmail.com' EMAIL_HOST = 'smtp.mydomain.com' EMAIL_HOST_USER = 'username' EMAIL_HOST_PASSWORD = 'password' DEFAULT_FROM_EMAIL = 'username@mydomain.com' SERVER_EMAIL = 'username@mydomain.com' TWITTER_CONSUMER_KEY = 'DeH9TfrfeV7UeRgK3OSGA' TWITTER_CONSUMER_SECRET = 'sZGBB28VZcrRfcZvexYydj2Pc2uWW307kP8l7T7yiQo' TWITTER_OAUTH_TOKEN = '2334856880-zYwvSu8kS7cGfH67lQ64vulTUbY7zxhc39bpnlG' TWITTER_OAUTH_TOKEN_SECRET = 'RTQ7pzSytCIPsASCkA0Z5rubpHSWbvjvYR3c3hb9QhC3M'
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import os import main import unittest import tempfile class JJblogTestCase(unittest.TestCase): def setUp(self): self.db_fd, main.app.config['DATABASE'] = tempfile.mkstemp() self.app = main.app.test_client() main.database.init_db() def tearDown(self): os.close(self.db_fd) os.unlink(main.app.config['DATABASE']) def login(self, username, password): return self.app.post('/admin', data=dict( username=username, password=password), follow_redirects=True) def logout(self): return self.app.get('/admin/logout', follow_redirects=True) def test_login_logout(self): rv = self.login('aadmin', 'admin') # assert 'Failed' in rv.data print(rv.data) rv = self.logout() if __name__ == '__main__': unittest.main()
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""" File: complement.py Name: Roger(Yu-Ming) Chang ---------------------------- This program uses string manipulation to tackle a real world problem - finding the complement strand of a DNA sequence. The program asks users for a DNA sequence as a python string that is case-insensitive. Your job is to output the complement of it. """ def main(): """ The program will output the complement of a DNA sequence users input. """ dna = input_dna() complement = build_complement(dna) print('The complement of ' + str(dna) + ' is ' + str(complement)) def input_dna(): """ The function will ask users input a DNA sequence and check whether the input format is correct. :return: str, the correct input format. """ while True: dna = input('Please give me a DNA strand and I\'ll find the complement: ') dna = dna.upper() wrong = 0 for i in range(len(dna)): ch = dna[i] if ch == 'A' or ch == 'T' or ch == 'C' or ch == 'G': wrong += 0 else: wrong += 1 if wrong > 0: print('The input format is not correct.') if wrong == 0: return dna def build_complement(base): """ :param base: str, the DNA sequence users input. :return: str, the complement of the entered DNA sequence. """ strand = '' for i in range(len(base)): ch = base[i] if ch == 'A': strand += 'T' if ch == 'T': strand += 'A' if ch == 'C': strand += 'G' if ch == 'G': strand += 'C' return strand if __name__ == '__main__': main()
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"""gestao URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.2/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path, include from django.conf.urls import url urlpatterns = [ path('admin/', admin.site.urls), path('', include('comparador.urls')), path('', include('teste.urls')), path('pousada/', include('pousada.urls')), path('cotacao/', include('cotacao.urls')), path('chat2/', include('chatbot.urls'), name='chatbot'), ]
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# Copyright 2020 The TensorFlow Probability Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Targets package.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from tensorflow_probability.python.experimental.inference_gym.targets.banana import Banana from tensorflow_probability.python.experimental.inference_gym.targets.bayesian_model import BayesianModel from tensorflow_probability.python.experimental.inference_gym.targets.ill_conditioned_gaussian import IllConditionedGaussian from tensorflow_probability.python.experimental.inference_gym.targets.item_response_theory import ItemResponseTheory from tensorflow_probability.python.experimental.inference_gym.targets.item_response_theory import SyntheticItemResponseTheory from tensorflow_probability.python.experimental.inference_gym.targets.logistic_regression import GermanCreditNumericLogisticRegression from tensorflow_probability.python.experimental.inference_gym.targets.logistic_regression import LogisticRegression from tensorflow_probability.python.experimental.inference_gym.targets.model import Model from tensorflow_probability.python.experimental.inference_gym.targets.sparse_logistic_regression import GermanCreditNumericSparseLogisticRegression from tensorflow_probability.python.experimental.inference_gym.targets.sparse_logistic_regression import SparseLogisticRegression __all__ = [ 'Banana', 'BayesianModel', 'GermanCreditNumericLogisticRegression', 'GermanCreditNumericSparseLogisticRegression', 'IllConditionedGaussian', 'ItemResponseTheory', 'LogisticRegression', 'Model', 'SparseLogisticRegression', 'SyntheticItemResponseTheory', ]
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#!/usr/bin/env python # -*- coding: utf-8 -*- # # Copyright ยฉ 2016 Matthew Stone <mstone5@mgh.harvard.edu> # Distributed under terms of the MIT license. """ Modification of Michael Waskom's JointGrid implementation in Seaborn. Supports multiple JointGrids in single figure """ import numpy as np import pandas as pd import matplotlib.gridspec as gridspec import matplotlib.pyplot as plt import seaborn as sns class JointGrid(sns.JointGrid): """Grid for drawing a bivariate plot with marginal univariate plots.""" def __init__(self, x, y, data=None, gs=None, ratio=5, space=.2, dropna=True, xlim=None, ylim=None): """Set up the grid of subplots. Parameters ---------- x, y : strings or vectors Data or names of variables in ``data``. data : DataFrame, optional DataFrame when ``x`` and ``y`` are variable names. size : numeric Size of each side of the figure in inches (it will be square). ratio : numeric Ratio of joint axes size to marginal axes height. space : numeric, optional Space between the joint and marginal axes dropna : bool, optional If True, remove observations that are missing from `x` and `y`. {x, y}lim : two-tuples, optional Axis limits to set before plotting. See Also -------- jointplot : High-level interface for drawing bivariate plots with several different default plot kinds. """ # Set up the subplot grid if gs is None: gs = gridspec.GridSpec(ratio + 1, ratio + 1, hspace=space, wspace=space) ax_joint = plt.subplot(gs[1:, :-1]) ax_marg_x = plt.subplot(gs[0, :-1], sharex=ax_joint) ax_marg_y = plt.subplot(gs[1:, -1], sharey=ax_joint) self.ax_joint = ax_joint self.ax_marg_x = ax_marg_x self.ax_marg_y = ax_marg_y # Turn off tick visibility for the measure axis on the marginal plots plt.setp(ax_marg_x.get_xticklabels(), visible=False) plt.setp(ax_marg_y.get_yticklabels(), visible=False) # Turn off the ticks on the density axis for the marginal plots plt.setp(ax_marg_x.yaxis.get_majorticklines(), visible=False) plt.setp(ax_marg_x.yaxis.get_minorticklines(), visible=False) plt.setp(ax_marg_y.xaxis.get_majorticklines(), visible=False) plt.setp(ax_marg_y.xaxis.get_minorticklines(), visible=False) plt.setp(ax_marg_x.get_yticklabels(), visible=False) plt.setp(ax_marg_y.get_xticklabels(), visible=False) ax_marg_x.yaxis.grid(False) ax_marg_y.xaxis.grid(False) # Possibly extract the variables from a DataFrame if data is not None: if x in data: x = data[x] if y in data: y = data[y] # Possibly drop NA if dropna: not_na = pd.notnull(x) & pd.notnull(y) x = x[not_na] y = y[not_na] # Find the names of the variables if hasattr(x, "name"): xlabel = x.name ax_joint.set_xlabel(xlabel) if hasattr(y, "name"): ylabel = y.name ax_joint.set_ylabel(ylabel) # Convert the x and y data to arrays for plotting self.x = np.asarray(x) self.y = np.asarray(y) if xlim is not None: ax_joint.set_xlim(xlim) if ylim is not None: ax_joint.set_ylim(ylim) class JointGrids: def __init__(self, data, x, y, col=None, col_order=None, row=None, row_order=None, panel_size=8, ratio=5): # row=None, row_order=None, # col=None, col_order=None, # hue=None, hue_order=None): """ Borrowed heavily from seaborn FacetGrid Arguments --------- panel_size : int, optional Height/width of each constituent JointGrid ratio : int, optional Ratio of joint to marginal axis size """ if row is None: row_names = [] else: row_names = sns.utils.categorical_order(data[row], row_order) if col is None: col_names = [] else: col_names = sns.utils.categorical_order(data[col], col_order) # if col is not None and col_order is None: # col_order = data[col].drop_duplicates().sort_values() # n_cols = len(col_order) n_cols = 1 if col is None else len(col_names) n_rows = 1 if row is None else len(row_names) self.fig = plt.figure(figsize=(n_cols * panel_size, n_rows * panel_size)) self.gs = gridspec.GridSpec(n_rows, n_cols) self.grids = np.empty((n_rows, n_cols), dtype=object) if len(row_names) > 0 and len(col_names) > 0: for i, row_val in enumerate(row_names): for j, col_val in enumerate(col_names): subdata = data.loc[(data[col] == col_val) & (data[row] == row_val)] ss = self.gs[i, j] gs = gridspec.GridSpecFromSubplotSpec(ratio + 1, ratio + 1, subplot_spec=ss) grid = JointGrid(x, y, data=subdata, gs=gs) self.grids[i, j] = grid else: if len(row_names) > 0: facets = row_names facet = row grids = self.grids[:, 0] else: facets = col_names facet = col grids = self.grids[0] for i, val in enumerate(facets): subdata = data.loc[data[facet] == val] gs = gridspec.GridSpecFromSubplotSpec(ratio + 1, ratio + 1, subplot_spec=self.gs[i]) grid = JointGrid(x, y, data=subdata, gs=gs) grids[i] = grid def set_xlims(self, xmin, xmax): for grid in self.grids.flat: grid.ax_joint.set_xlim(xmin, xmax) def set_ylims(self, ymin, ymax): for grid in self.grids.flat: grid.ax_joint.set_ylim(ymin, ymax) def set_lims(self, xmin, xmax): for grid in self.grids.flat: grid.ax_joint.set_xlim(xmin, xmax) grid.ax_joint.set_ylim(xmin, xmax) def plot_joint(self, func, **kwargs): for grid in self.grids.flat: grid.plot_joint(func, **kwargs) def plot_marginals(self, func, **kwargs): for grid in self.grids.flat: grid.plot_marginals(func, **kwargs)
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from datetime import datetime import flask import urllib import hashlib import re from linebot.models import TextSendMessage from linebot import LineBotApi from smart_schedule.settings import ( line_env, web_env, hash_env ) line_bot_api = LineBotApi(line_env['channel_access_token']) # TODO ไปฅ้™ใฎ้–ขๆ•ฐใŸใกใฏใฉใ“ใซใ‚ใ‚‹ในใใ‹ใ€ใƒชใƒ•ใ‚กใ‚ฏใ‚ฟใƒชใƒณใ‚ฐใฎไฝ™ๅœฐใŒ็„กใ„ใ‹่€ƒใˆใ‚‹ def reply_google_auth_message(event): auth_url = flask.url_for('oauth2') if event.source.type == 'user': talk_id = event.source.user_id elif event.source.type == 'group': talk_id = event.source.group_id elif event.source.type == 'room': talk_id = event.source.room_id else: raise Exception('invalid `event.source`') m = hashlib.md5() m.update(talk_id.encode('utf-8')) m.update(hash_env['seed'].encode('utf-8')) params = urllib.parse.urlencode({'talk_id': talk_id, 'hash': m.hexdigest()}) url = '{}{}?{}'.format(web_env['host'], auth_url, params) line_bot_api.reply_message( event.reply_token, TextSendMessage(text='ใ“ใฎใƒชใƒณใ‚ฏใ‹ใ‚‰่ช่จผใ‚’่กŒใฃใฆใใ ใ•ใ„\n{}'.format(url)) ) def reply_refresh_error_message(event): reply_text = '''่ช่จผๆƒ…ๅ ฑใฎๆ›ดๆ–ฐใ‚จใƒฉใƒผใŒ็™บ็”Ÿใ—ใพใ—ใŸใ€‚ๅŒใ˜Googleใ‚ขใ‚ซใ‚ฆใƒณใƒˆใง่ค‡ๆ•ฐใฎ\ ่ช่จผใ‚’่กŒใฃใฆใ„ใ‚‹ๅ ดๅˆใซใ“ใฎไธๅ…ทๅˆใŒ็™บ็”Ÿใ—ใพใ™ใ€‚ใ“ใฎใƒˆใƒผใ‚ฏใงSmart Scheduleใ‚’ไฝฟ็”จใ—ใŸใ„ๅ ดๅˆ\ ใฏไปฅไธ‹ใฎใ„ใšใ‚Œใ‹ใ‚’่กŒใฃใŸๅพŒใง่ช่จผใ—ใชใŠใ—ใฆใใ ใ•ใ„ใ€‚ 1. ๅŒใ˜ใ‚ขใ‚ซใ‚ฆใƒณใƒˆใง่ช่จผใ—ใฆใ„ใ‚‹ใƒˆใƒผใ‚ฏใงlogoutใ‚ณใƒžใƒณใƒ‰ใ‚’่กŒใ†(ใ‚ชใ‚นใ‚นใƒก) 2. ไธ‹่จ˜URLใ‹ใ‚‰ๆ‰‹ๅ‹•ใงSmart Scheduleใฎ่ช่จผใ‚’่งฃ้™คใ™ใ‚‹\ https://myaccount.google.com/u/1/permissions''' line_bot_api.reply_message( event.reply_token, TextSendMessage(text=reply_text) ) def reply_invalid_credential_error_message(event): reply_text = '''็„กๅŠนใช่ช่จผๆƒ…ๅ ฑใงใ™ใ€‚ๅŒใ˜Googleใ‚ขใ‚ซใ‚ฆใƒณใƒˆใง่ค‡ๆ•ฐใฎ่ช่จผใ‚’่กŒใฃใฆใ„ใ‚‹\ ๅ ดๅˆใซใ“ใฎไธๅ…ทๅˆใŒ็™บ็”Ÿใ—ใพใ™ใ€‚่ช่จผใ‚’ใ‚„ใ‚ŠใชใŠใ—ใฆใใ ใ•ใ„ใ€‚''' line_bot_api.reply_message( event.reply_token, TextSendMessage(text=reply_text) ) def generate_message_from_events(events, reply_text): day_of_week_strs = ["ๆœˆ", "็ซ", "ๆฐด", "ๆœจ", "้‡‘", "ๅœŸ", "ๆ—ฅ"] for e in events: summary = e['summary'] start = e['start'].get('dateTime', e['start'].get('date')) if re.match('\d+[-]\d+[-]\d+[T]\d+[:]\d+[:]\d+[+]\d+[:]\d+', start): start_datetime = datetime.strptime(start, '%Y-%m-%dT%H:%M:%S+09:00') day_of_week = day_of_week_strs[start_datetime.weekday()] start = start_datetime.strftime( '%Yๅนด%mๆœˆ%dๆ—ฅ({}) %Hๆ™‚%Sๅˆ†'.format(day_of_week) ) end = e['end'].get('dateTime', e['end'].get('date')) end_datetime = datetime.strptime(end, '%Y-%m-%dT%H:%M:%S+09:00') day_of_week = day_of_week_strs[end_datetime.weekday()] end = end_datetime.strftime( '%Yๅนด%mๆœˆ%dๆ—ฅ({}) %Hๆ™‚%Sๅˆ†'.format(day_of_week) ) reply_text += '\n\n{}\n{}\n |\n{}\n\n---------------------------'.format(summary, start, end) else: start_datetime = datetime.strptime(start, '%Y-%m-%d') start = start_datetime.strftime('%Yๅนด%mๆœˆ%dๆ—ฅ') end = '็ต‚ๆ—ฅ' reply_text += '\n\n{}\n{} {}\n\n---------------------------'.format(summary, start, end) return reply_text from .join_event_handler import JoinEventHandler from .leave_event_handler import LeaveEventHandler from .message_event_handler import MessageEventHandler from .postback_event_handler import PostBackEventHandler from .unfollow_event_handler import UnfollowEventHandler
[ "shunji.makino@gmail.com" ]
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""" Measure the lengths of random games. """ import random from uno_ai.game import Game def main(): while True: g = Game(4) num_moves = 0 while g.winner() is None: action = random.choice(g.options()) g.act(action) num_moves += 1 print(num_moves) if __name__ == '__main__': main()
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#!/usr/bin/python # -*- coding: utf-8 -*- # # Copyright (c) 2017 F5 Networks Inc. # GNU General Public License v3.0 (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) from __future__ import absolute_import, division, print_function __metaclass__ = type ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ['stableinterface'], 'supported_by': 'certified'} DOCUMENTATION = r''' --- module: bigip_iapp_template short_description: Manages TCL iApp templates on a BIG-IP description: - Manages TCL iApp templates on a BIG-IP. This module will allow you to deploy iApp templates to the BIG-IP and manage their lifecycle. The conventional way to use this module is to import new iApps as needed or by extracting the contents of the iApp archive that is provided at downloads.f5.com and then importing all the iApps with this module. This module can also update existing iApps provided that the source of the iApp changed while the name stayed the same. Note however that this module will not reconfigure any services that may have been created using the C(bigip_iapp_service) module. iApps are normally not updated in production. Instead, new versions are deployed and then existing services are changed to consume that new template. As such, the ability to update templates in-place requires the C(force) option to be used. version_added: 2.4 options: force: description: - Specifies whether or not to force the uploading of an iApp. When C(yes), will force update the iApp even if there are iApp services using it. This will not update the running service though. Use C(bigip_iapp_service) to do that. When C(no), will update the iApp only if there are no iApp services using the template. type: bool name: description: - The name of the iApp template that you want to delete. This option is only available when specifying a C(state) of C(absent) and is provided as a way to delete templates that you may no longer have the source of. content: description: - Sets the contents of an iApp template directly to the specified value. This is for simple values, but can be used with lookup plugins for anything complex or with formatting. C(content) must be provided when creating new templates. state: description: - Whether the iApp template should exist or not. default: present choices: - present - absent partition: description: - Device partition to manage resources on. default: Common extends_documentation_fragment: f5 author: - Tim Rupp (@caphrim007) ''' EXAMPLES = r''' - name: Add the iApp contained in template iapp.tmpl bigip_iapp_template: content: "{{ lookup('template', 'iapp.tmpl') }}" password: secret server: lb.mydomain.com state: present user: admin delegate_to: localhost - name: Update a template in place bigip_iapp_template: content: "{{ lookup('template', 'iapp-new.tmpl') }}" password: secret server: lb.mydomain.com state: present user: admin delegate_to: localhost - name: Update a template in place that has existing services created from it. bigip_iapp_template: content: "{{ lookup('template', 'iapp-new.tmpl') }}" force: yes password: secret server: lb.mydomain.com state: present user: admin delegate_to: localhost ''' RETURN = r''' # only common fields returned ''' import re import uuid from ansible.module_utils.basic import AnsibleModule from ansible.module_utils.basic import env_fallback try: from library.module_utils.network.f5.bigip import HAS_F5SDK from library.module_utils.network.f5.bigip import F5Client from library.module_utils.network.f5.common import F5ModuleError from library.module_utils.network.f5.common import AnsibleF5Parameters from library.module_utils.network.f5.common import cleanup_tokens from library.module_utils.network.f5.common import f5_argument_spec from library.module_utils.network.f5.common import fq_name try: from library.module_utils.network.f5.common import iControlUnexpectedHTTPError from f5.utils.iapp_parser import NonextantTemplateNameException except ImportError: HAS_F5SDK = False except ImportError: from ansible.module_utils.network.f5.bigip import HAS_F5SDK from ansible.module_utils.network.f5.bigip import F5Client from ansible.module_utils.network.f5.common import F5ModuleError from ansible.module_utils.network.f5.common import AnsibleF5Parameters from ansible.module_utils.network.f5.common import cleanup_tokens from ansible.module_utils.network.f5.common import f5_argument_spec from ansible.module_utils.network.f5.common import fq_name try: from ansible.module_utils.network.f5.common import iControlUnexpectedHTTPError from f5.utils.iapp_parser import NonextantTemplateNameException except ImportError: HAS_F5SDK = False try: from StringIO import StringIO except ImportError: from io import StringIO class Parameters(AnsibleF5Parameters): api_attributes = [] returnables = [] @property def name(self): if self._values['name']: return self._values['name'] if self._values['content']: try: name = self._get_template_name() return name except NonextantTemplateNameException: raise F5ModuleError( "No template name was found in the template" ) return None @property def content(self): if self._values['content'] is None: return None result = self._squash_template_name_prefix() result = self._replace_template_name(result) return result @property def checksum(self): return self._values['tmplChecksum'] def to_return(self): result = {} try: for returnable in self.returnables: result[returnable] = getattr(self, returnable) result = self._filter_params(result) except Exception: pass return result def _squash_template_name_prefix(self): """Removes the template name prefix The IappParser in the SDK treats the partition prefix as part of the iApp's name. This method removes that partition from the name in the iApp so that comparisons can be done properly and entries can be created properly when using REST. :return string """ pattern = r'sys\s+application\s+template\s+/Common/' replace = 'sys application template ' return re.sub(pattern, replace, self._values['content']) def _replace_template_name(self, template): """Replaces template name at runtime To allow us to do the switch-a-roo with temporary templates and checksum comparisons, we need to take the template provided to us and change its name to a temporary value so that BIG-IP will create a clone for us. :return string """ pattern = r'sys\s+application\s+template\s+[^ ]+' if self._values['name']: name = self._values['name'] else: name = self._get_template_name() replace = 'sys application template {0}'.format(fq_name(self.partition, name)) return re.sub(pattern, replace, template) def _get_template_name(self): # There is a bug in the iApp parser in the F5 SDK that prevents us from # using it in all cases to get the name of an iApp. So we'll use this # pattern for now and file a bug with the F5 SDK pattern = r'sys\s+application\s+template\s+(?P<path>\/[^\{}"\'*?|#]+\/)?(?P<name>[^\{}"\'*?|#]+)' matches = re.search(pattern, self._values['content']) try: result = matches.group('name').strip() except IndexError: result = None if result: return result raise NonextantTemplateNameException class ModuleManager(object): def __init__(self, *args, **kwargs): self.module = kwargs.get('module', None) self.client = kwargs.get('client', None) self.have = None self.want = Parameters(params=self.module.params) self.changes = Parameters() def exec_module(self): result = dict() changed = False state = self.want.state try: if state == "present": changed = self.present() elif state == "absent": changed = self.absent() except iControlUnexpectedHTTPError as e: raise F5ModuleError(str(e)) changes = self.changes.to_return() result.update(**changes) result.update(dict(changed=changed)) return result def present(self): if self.exists(): return self.update() else: return self.create() def update(self): self.have = self.read_current_from_device() if not self.templates_differ(): return False if not self.want.force and self.template_in_use(): return False if self.module.check_mode: return True self._remove_iapp_checksum() # The same process used for creating (load) can be used for updating self.create_on_device() self._generate_template_checksum_on_device() return True def template_in_use(self): collection = self.client.api.tm.sys.application.services.get_collection() fullname = '/{0}/{1}'.format(self.want.partition, self.want.name) for resource in collection: if resource.template == fullname: return True return False def read_current_from_device(self): self._generate_template_checksum_on_device() resource = self.client.api.tm.sys.application.templates.template.load( name=self.want.name, partition=self.want.partition ) result = resource.attrs return Parameters(params=result) def absent(self): changed = False if self.exists(): changed = self.remove() return changed def exists(self): result = self.client.api.tm.sys.application.templates.template.exists( name=self.want.name, partition=self.want.partition ) return result def _remove_iapp_checksum(self): """Removes the iApp tmplChecksum This is required for updating in place or else the load command will fail with a "AppTemplate ... content does not match the checksum" error. :return: """ resource = self.client.api.tm.sys.application.templates.template.load( name=self.want.name, partition=self.want.partition ) resource.modify(tmplChecksum=None) def templates_differ(self): # BIG-IP can generate checksums of iApps, but the iApp needs to be # on the box to do this. Additionally, the checksum is MD5, but it # is not an MD5 of the entire content of the template. Instead, it # is a hash of some portion of the template that is unknown to me. # # The code below is responsible for uploading the provided template # under a unique name and creating a checksum for it so that that # checksum can be compared to the one of the existing template. # # Using this method we can compare the checksums of the existing # iApp and the iApp that the user is providing to the module. backup = self.want.name # Override whatever name may have been provided so that we can # temporarily create a new template to test checksums with self.want.update({ 'name': 'ansible-{0}'.format(str(uuid.uuid4())) }) # Create and remove temporary template temp = self._get_temporary_template() # Set the template name back to what it was originally so that # any future operations only happen on the real template. self.want.update({ 'name': backup }) if temp.checksum != self.have.checksum: return True return False def _get_temporary_template(self): self.create_on_device() temp = self.read_current_from_device() self.remove_from_device() return temp def _generate_template_checksum_on_device(self): generate = 'tmsh generate sys application template {0} checksum'.format( self.want.name ) self.client.api.tm.util.bash.exec_cmd( 'run', utilCmdArgs='-c "{0}"'.format(generate) ) def create(self): if self.module.check_mode: return True self.create_on_device() if self.exists(): return True else: raise F5ModuleError("Failed to create the iApp template") def create_on_device(self): remote_path = "/var/config/rest/downloads/{0}".format(self.want.name) load_command = 'tmsh load sys application template {0}'.format(remote_path) template = StringIO(self.want.content) upload = self.client.api.shared.file_transfer.uploads upload.upload_stringio(template, self.want.name) output = self.client.api.tm.util.bash.exec_cmd( 'run', utilCmdArgs='-c "{0}"'.format(load_command) ) if hasattr(output, 'commandResult'): result = output.commandResult if 'Syntax Error' in result: raise F5ModuleError(output.commandResult) if 'ERROR' in result: raise F5ModuleError(output.commandResult) def remove(self): if self.module.check_mode: return True self.remove_from_device() if self.exists(): raise F5ModuleError("Failed to delete the iApp template") return True def remove_from_device(self): resource = self.client.api.tm.sys.application.templates.template.load( name=self.want.name, partition=self.want.partition ) resource.delete() class ArgumentSpec(object): def __init__(self): self.supports_check_mode = True argument_spec = dict( name=dict(), state=dict( default='present', choices=['present', 'absent'] ), force=dict( type='bool' ), content=dict(), partition=dict( default='Common', fallback=(env_fallback, ['F5_PARTITION']) ) ) self.argument_spec = {} self.argument_spec.update(f5_argument_spec) self.argument_spec.update(argument_spec) def main(): spec = ArgumentSpec() module = AnsibleModule( argument_spec=spec.argument_spec, supports_check_mode=spec.supports_check_mode ) if not HAS_F5SDK: module.fail_json(msg="The python f5-sdk module is required") try: client = F5Client(**module.params) mm = ModuleManager(module=module, client=client) results = mm.exec_module() cleanup_tokens(client) module.exit_json(**results) except F5ModuleError as e: cleanup_tokens(client) module.fail_json(msg=str(e)) if __name__ == '__main__': main()
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def factorial(n): """ return the recursive factorial of n """ if n == 1: return 1 else: return n*factorial(n-1) if __name__ == "__main__": print """Welcome to the FACTORIAL CALCULATOR\n \nTo use the calculator, enter the number for which you want the factorial of, then press enter. In order to quit, type 'q' or 'quit'""" while True: x = raw_input("==> ") if x.lower() == "q" or x.lower() == "quit": print "Thank you for using this program" break else: try: print factorial(int(x)) except: print "Please enter input again"
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from user_auth.vendors.top.api.rest.TopIpoutGetRequest import TopIpoutGetRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcFlowChargeProvinceRequest import AlibabaAliqinFcFlowChargeProvinceRequest from user_auth.vendors.top.api.rest.HttpdnsGetRequest import HttpdnsGetRequest from user_auth.vendors.top.api.rest.TopSecretGetRequest import TopSecretGetRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcFlowQueryRequest import AlibabaAliqinFcFlowQueryRequest from user_auth.vendors.top.api.rest.KfcKeywordSearchRequest import KfcKeywordSearchRequest from user_auth.vendors.top.api.rest.TopatsTaskDeleteRequest import TopatsTaskDeleteRequest from user_auth.vendors.top.api.rest.TimeGetRequest import TimeGetRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcSmsNumSendRequest import AlibabaAliqinFcSmsNumSendRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcTtsNumSinglecallRequest import AlibabaAliqinFcTtsNumSinglecallRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcSmsNumQueryRequest import AlibabaAliqinFcSmsNumQueryRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcFlowChargeRequest import AlibabaAliqinFcFlowChargeRequest from user_auth.vendors.top.api.rest.TopatsResultGetRequest import TopatsResultGetRequest from user_auth.vendors.top.api.rest.AreasGetRequest import AreasGetRequest from user_auth.vendors.top.api.rest.TopAuthTokenCreateRequest import TopAuthTokenCreateRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcFlowGradeRequest import AlibabaAliqinFcFlowGradeRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcVoiceNumDoublecallRequest import AlibabaAliqinFcVoiceNumDoublecallRequest from user_auth.vendors.top.api.rest.AlibabaAliqinFcVoiceNumSinglecallRequest import AlibabaAliqinFcVoiceNumSinglecallRequest from user_auth.vendors.top.api.rest.TopAuthTokenRefreshRequest import TopAuthTokenRefreshRequest from user_auth.vendors.top.api.rest.AppipGetRequest import AppipGetRequest
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/2020-01-python/api.py
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suzuki-hoge/warikan
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from bottle import route, get, post, put, request, response, hook, run import json import db, party def handle(f): def wrapper(*args, **kwargs): try: result = f(*args, **kwargs) return {'status': 'ok', 'result': result} if result is not None else {'status': 'ok'} except BaseException as e: return {'status': 'ng', 'error': e.message} return wrapper @hook('after_request') def allow_cors(): response.headers['Access-Control-Allow-Origin'] = '*' response.headers['Access-Control-Allow-Headers'] = 'Content-Type' response.headers['Access-Control-Allow-Methods'] = 'GET, POST, PUT, OPTIONS' @route('<any:path>', method = 'OPTIONS') def options(**kwargs): return {} @get('/party/<partyName>') @handle def find(partyName): def party_dict(p): return {'partyName': p.partyName, 'partyHoldAt': p.partyHoldAt, 'participants': map(participant_dict, p.participants), 'billingAmount': p.billingAmount, 'adjustingUnitAmount': p.adjustingUnitAmount} def participant_dict(p): return {'participantName': p.participantName, 'participantType': p.participantType, 'paymentSection': p.paymentSection} return party_dict(db.read(partyName)) @post('/party/plan') @handle def plan(): p = request.json new = party.Party.plan(p.get('partyName'), p.get('partyHoldAt'), p.get('secretaryName'), p.get('paymentSection'), p.get('billingAmount'), p.get('adjustingUnitAmount')) db.write(new) @put('/party/<partyName>/add') @handle def add(partyName): p = request.json found = db.read(partyName) updated = found.add(party.Participant(p.get('participantName'), 'NotSec', p.get('paymentSection'))) db.write(updated) @put('/party/<partyName>/remove') @handle def remove(partyName): p = request.params found = db.read(partyName) updated = found.remove(p.participantName) db.write(updated) @put('/party/<partyName>/change') @handle def change(partyName): p = request.json found = db.read(partyName) updated = found.change(p.get('adjustingUnitAmount')) db.write(updated) @get('/party/<partyName>/demand') @handle def demand(partyName): found = db.read(partyName) return map(lambda (participantName, paymentAmount): {'participantName': participantName, 'paymentAmount': str(paymentAmount)}, found.demand()) run(host = 'localhost', port = 9000)
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# -*- mode: python; coding: utf-8 -*- # Copyright 2019-2020 the .NET Foundation # Licensed under the MIT License. from __future__ import absolute_import, division, print_function import os.path from .. import cli from . import tempdir def test_cli(tempdir): "Simple smoke test to see if it runs at all." prev_dir = os.getcwd() try: os.chdir(tempdir) cli.entrypoint( [ "tree", "fetch", "https://web.wwtassets.org/engine/assets/builtin-image-sets.wtml", ] ) cli.entrypoint(["tree", "summarize"]) cli.entrypoint(["tree", "print-image-urls"]) cli.entrypoint(["tree", "print-dem-urls"]) finally: # Windows can't remove the temp tree unless we chdir out of it. os.chdir(prev_dir)
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# -*- coding: utf-8 -*- """ Created on Wed Mar 1 17:37:44 2017 @author: yangshiyu89 """ import numpy as np import pandas as pd import tensorflow as tf import matplotlib.pyplot as plt # Define dl net def Neural_Net(train_features, train_targets, val_features, val_targets, test_features): features = tf.placeholder(tf.float32, shape=[None, train_features.shape[1]]) targets = tf.placeholder(tf.float32, shape=[None, train_targets.shape[1]]) W_1 = tf.Variable(tf.truncated_normal(shape=[train_features.shape[1], 25], dtype=tf.float32, stddev=0.001)) b_1 = tf.Variable(tf.zeros(shape=[25], dtype=tf.float32)) W_2 = tf.Variable(tf.truncated_normal(shape=[25, train_targets.shape[1]], dtype=tf.float32, stddev=0.001)) b_2 = tf.Variable(tf.zeros(shape=[train_targets.shape[1]], dtype=tf.float32)) layer = tf.add(tf.matmul(features, W_1), b_1) layer = tf.nn.relu(layer) predict = tf.add(tf.matmul(layer, W_2), b_2) loss = tf.reduce_mean(tf.pow(targets - predict, 2)) optimizer = tf.train.AdamOptimizer(learning_rate = 0.1).minimize(loss) with tf.Session() as sess: sess.run(tf.global_variables_initializer()) for epoch in range(1001): sess.run(optimizer, feed_dict={features:train_features, targets:train_targets}) if epoch%10 == 0: cost_test = sess.run(loss, feed_dict={features:train_features, targets:train_targets}) cost_val = sess.run(loss, feed_dict={features:val_features, targets:val_targets}) print("epoch {:4d}; cost_test: {:.4f}; cost_val: {:.4f}".format(epoch, cost_test, cost_val)) predict_targets = sess.run(predict, feed_dict={features:test_features}) return predict_targets if __name__ == "__main__": # Load and prepare the data data_path = "Bike-Sharing-Dataset/hour.csv" rides = pd.read_csv(data_path) # Dummy variables dummy_fields = ['season', 'weathersit', 'mnth', 'hr', 'weekday'] for each in dummy_fields: dummies = pd.get_dummies(rides[each], prefix=each, drop_first=False) rides = pd.concat([rides, dummies], axis=1) fields_to_drop = ['instant', 'dteday', 'season', 'weathersit', 'weekday', 'atemp', 'mnth', 'workingday', 'hr'] data = rides.drop(fields_to_drop, axis=1) # Scaling target variables quant_features = ['casual', 'registered', 'cnt', 'temp', 'hum', 'windspeed'] # Store scalings in a dictionary so we can convert back later scaled_features = {} for each in quant_features: mean, std = data[each].mean(), data[each].std() scaled_features[each] = [mean, std] data.loc[:, each] = (data[each] - mean)/std # Splitting the data into training, testing, and validation sets # Save the last 21 days test_data = data[-21*24:] data = data[:-21*24] # Separate the data into features and targets target_fields = ['cnt', 'casual', 'registered'] features, targets = data.drop(target_fields, axis=1), data[target_fields] test_features, test_targets = test_data.drop(target_fields, axis=1), test_data[target_fields] # Hold out the last 60 days of the remaining data as a validation set train_features, train_targets = features[:-60*24], targets[:-60*24] val_features, val_targets = features[-60*24:], targets[-60*24:] predict_targets = Neural_Net(train_features, train_targets['cnt'][:, np.newaxis], val_features, val_targets['cnt'][:, np.newaxis], test_features) # Check the prediction fig, ax = plt.subplots(figsize=(8,4)) mean, std = scaled_features['cnt'] predictions = predict_targets*std + mean ax.plot(predictions[:], label='Prediction') ax.plot((test_targets['cnt']*std + mean).values, label='Data') ax.set_xlim(right=len(predictions)) ax.legend() dates = pd.to_datetime(rides.ix[test_data.index]['dteday']) dates = dates.apply(lambda d: d.strftime('%b %d')) ax.set_xticks(np.arange(len(dates))[12::24]) _ = ax.set_xticklabels(dates[12::24], rotation=45)
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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables from . import outputs __all__ = [ 'GetVirtualNetworkGatewayBgpPeerStatusResult', 'AwaitableGetVirtualNetworkGatewayBgpPeerStatusResult', 'get_virtual_network_gateway_bgp_peer_status', ] @pulumi.output_type class GetVirtualNetworkGatewayBgpPeerStatusResult: """ Response for list BGP peer status API service call """ def __init__(__self__, value=None): if value and not isinstance(value, list): raise TypeError("Expected argument 'value' to be a list") pulumi.set(__self__, "value", value) @property @pulumi.getter def value(self) -> Optional[Sequence['outputs.BgpPeerStatusResponseResult']]: """ List of BGP peers """ return pulumi.get(self, "value") class AwaitableGetVirtualNetworkGatewayBgpPeerStatusResult(GetVirtualNetworkGatewayBgpPeerStatusResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetVirtualNetworkGatewayBgpPeerStatusResult( value=self.value) def get_virtual_network_gateway_bgp_peer_status(peer: Optional[str] = None, resource_group_name: Optional[str] = None, virtual_network_gateway_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetVirtualNetworkGatewayBgpPeerStatusResult: """ Response for list BGP peer status API service call :param str peer: The IP address of the peer to retrieve the status of. :param str resource_group_name: The name of the resource group. :param str virtual_network_gateway_name: The name of the virtual network gateway. """ __args__ = dict() __args__['peer'] = peer __args__['resourceGroupName'] = resource_group_name __args__['virtualNetworkGatewayName'] = virtual_network_gateway_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:network/v20171001:getVirtualNetworkGatewayBgpPeerStatus', __args__, opts=opts, typ=GetVirtualNetworkGatewayBgpPeerStatusResult).value return AwaitableGetVirtualNetworkGatewayBgpPeerStatusResult( value=__ret__.value)
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vubon/django-graphql
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from django.apps import AppConfig class IngrdientsConfig(AppConfig): name = 'ingredients'
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""" Manifest handling of a repository. https://hacs.xyz/docs/publish/start#hacsjson """ from typing import List import attr from custom_components.hacs.exceptions import HacsException @attr.s(auto_attribs=True) class HacsManifest: """HacsManifest class.""" name: str = None content_in_root: bool = False zip_release: bool = False filename: str = None manifest: dict = {} hacs: str = None hide_default_branch: bool = False domains: List[str] = [] country: List[str] = [] homeassistant: str = None persistent_directory: str = None iot_class: str = None render_readme: bool = False @staticmethod def from_dict(manifest: dict): """Set attributes from dicts.""" if manifest is None: raise HacsException("Missing manifest data") manifest_data = HacsManifest() manifest_data.manifest = manifest if country := manifest.get("country"): if isinstance(country, str): manifest["country"] = [country] for key in manifest: setattr(manifest_data, key, manifest[key]) return manifest_data
[ "dimitri.steiner.gl@gmail.com" ]
dimitri.steiner.gl@gmail.com
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#personal spam message #nolwazi dlamini #3 march 2014 name =input("Enter first name: \n") surname=input("Enter last name: \n") money=eval(input("Enter sum of money in USD: \n")) country=input("Enter country name: \n") print("\nDearest" ,name) print("It is with a heavy heart that I inform you of the death of my father,") print("General Fayk ",surname,", your long lost relative from Mapsfostol.",sep="") print("My father left the sum of ", money,"USD for us, your distant cousins. ",sep="") print("Unfortunately, we cannot access the money as it is in a bank in ",country,".",sep="") print("I desperately need your assistance to access this money.") print("I will even pay you generously, 30% of the amount - ",(money*0.3),"USD,",sep="") print("for your help. Please get in touch with me at this email address asap.") print("Yours sincerely") print("Frank" ,surname)
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import json import os import stat import sys import binascii def make(vfs_name, prefix=None): """Called by python -m brython --make_file_system <vfs_name> <prefix> Creates a Virtual File System : a Javascript file with the files in current directory and its children. The file is stored in current directory as "<vfs_name>.vfs.js". A dictionary "files" is created. Keys are the file names, relative to the current directory (ie a file "data.txt" in current directory has the key "data.txt", and a file "names.txt" in the subdirectory "address" has key "address/names.txt"). If <prefix> was specified, it is prepended to the keys, followed by a /. For instance, if prefix is "info", the files above will have keys "info/data.txt" and "info/adress/names.txt" Python files can be included in such files, but *programs will not be able to import them*; for this, use --modules instead. """ files = {} this_dir = os.getcwd() dest_file = f"{vfs_name}.vfs.js" virtual_dir = prefix.split("/") if prefix else [] print("virtual dir", virtual_dir) for dirpath, dirnames, filenames in os.walk(this_dir): if dirpath == this_dir: path = [] else: path = dirpath[len(this_dir) + len(os.sep):].split(os.sep) for filename in filenames: if filename.endswith(".vfs.js"): continue rel_path = "/".join(virtual_dir + path + [filename]) with open(os.path.join(dirpath, filename), "rb") as f: # File content is base64-encoded content = binascii.b2a_base64(f.read()).decode('ascii') file_stat = os.fstat(f.fileno()) files[rel_path] = { "content": content, "ctime": file_stat.st_ctime, "mtime": file_stat.st_mtime } print(list(files)) with open(dest_file, "w", encoding="utf-8") as out: out.write("__BRYTHON__.add_files(") json.dump(files, out, indent=4) out.write(")")
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quentel.pierre@orange.fr
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inigokintana/automating-AWS-python
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#!/usr/bin/python # -*- coding: utf-8 -*- """Webotron: Deploy websites with aws. Webotron automates the process of deploying static websites to AWS. - Configure AWS S3 buckets - Create them - Set them up for static website hosting - Deploy local files to them - Configure DNS with AWS Route 53 - Configure a Content Delivery Network and SSL with AWS CloudFront """ import boto3 import click from bucket import BucketManager session = boto3.Session(profile_name='pythonAutomation') bucket_manager = BucketManager(session) @click.group() def cli(): """Webotron deploys websites to AWS.""" pass @cli.command('list-buckets') def list_buckets(): """List all s3 buckets.""" for bucket in bucket_manager.all_buckets(): print(bucket) @cli.command('list-bucket-objects') @click.argument('bucket') def list_bucket_objects(bucket): """List objects in an s3 bucket.""" for obj in bucket_manager.all_objects(bucket): print(obj) @cli.command('setup-bucket') @click.argument('bucket') def setup_bucket(bucket): """Create and configure S3 bucket.""" s3_bucket = bucket_manager.init_bucket(bucket) bucket_manager.set_policy(s3_bucket) bucket_manager.configure_website(s3_bucket) return @cli.command('sync') @click.argument('pathname', type=click.Path(exists=True)) @click.argument('bucket') def sync(pathname, bucket): """Sync contents of PATHNAME to BUCKET.""" bucket_manager.sync(pathname, bucket) if __name__ == '__main__': cli()
[ "inigokintana@gmail.com" ]
inigokintana@gmail.com
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kelly4strength/hmchallenge
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"""helper functions""" # from model import word, user_guess, partial_word # import unnecessary # def show_correct_guess_letter(word, user_guess, partial_word): # """function to show current guess letter if it is in the word""" # for i in range(len(word)): # if user_guess != word[i]: # partial_word = partial_word + "_ " # else: # partial_word = partial_word + word[i] # return partial_word def generate_partial_word(word, correct_guess_list): """generates the word with all correctly chosen letters""" temp_partial_word = "" # for each letter either put a dash or a letter for i in range(len(word)): matches = False for letter in correct_guess_list: if letter == word[i]: temp_partial_word = temp_partial_word + letter matches = True if matches == False: temp_partial_word = temp_partial_word + "_" return temp_partial_word #if there is no match to word[i] then add a underscore for that index # only append underscore after all matches are determined
[ "kellyhoffer@Kellys-MacBook-Pro-2.local" ]
kellyhoffer@Kellys-MacBook-Pro-2.local
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/src/software/simulated_tests/er_force_simulator.py
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LiCody/Software
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from subprocess import Popen from proto.import_all_protos import * from software.networking.threaded_unix_listener import ThreadedUnixListener from software.networking.threaded_unix_sender import ThreadedUnixSender from software.py_constants import * class ErForceSimulator(object): def __init__(self, runtime_dir="/tmp/tbots"): """Runs our standalone er-force simulator binary and sets up the unix sockets to communicate with it :param runtime_dir: The unix path to run everything """ # inputs to er_force_simulator_main self.sim_tick_sender = ThreadedUnixSender(runtime_dir + SIMULATION_TICK_PATH) self.world_state_sender = ThreadedUnixSender(runtime_dir + WORLD_STATE_PATH) self.blue_world_sender = ThreadedUnixSender(runtime_dir + BLUE_WORLD_PATH) self.yellow_world_sender = ThreadedUnixSender(runtime_dir + YELLOW_WORLD_PATH) self.blue_primitive_set_sender = ThreadedUnixSender( runtime_dir + BLUE_PRIMITIVE_SET ) self.yellow_primitive_set_sender = ThreadedUnixSender( runtime_dir + YELLOW_PRIMITIVE_SET ) # outputs from er_force_sim_main self.ssl_wrapper_listener = ThreadedUnixListener( runtime_dir + SSL_WRAPPER_PACKET_PATH, SSL_WrapperPacket ) self.blue_robot_status_listener = ThreadedUnixListener( runtime_dir + BLUE_ROBOT_STATUS_PATH, RobotStatus ) self.yellow_robot_status_listener = ThreadedUnixListener( runtime_dir + YELLOW_ROBOT_STATUS_PATH, RobotStatus, ) self.world_state = WorldState() self.simulator_process = Popen(["software/er_force_simulator_main"]) def __setup_robots(self, robot_locations, team_colour): """Initializes the world from a list of robot locations :param robot_locations: A list of robot locations (index is robot id) :param team_colour: The color (either "blue" or "yellow") """ if "blue" in team_colour: robot_map = self.world_state.blue_robots else: robot_map = self.world_state.yellow_robots for robot_id, robot_location in enumerate(robot_locations): robot_map[robot_id].CopyFrom( RobotState( global_position=Point( x_meters=robot_location.x(), y_meters=robot_location.y() ), global_orientation=Angle(radians=0), global_velocity=Vector(x_component_meters=0, y_component_meters=0), global_angular_velocity=AngularVelocity(radians_per_second=0), ) ) self.setup_world(self.world_state) def setup_blue_robots(self, robot_locations): """Initializes the world from a list of robot locations :param robot_locations: A list of robot locations (index is robot id) """ self.__setup_robots(robot_locations, "blue") def setup_yellow_robots(self, robot_locations): """Initializes the world from a list of robot locations :param robot_locations: A list of robot locations (index is robot id) """ self.__setup_robots(robot_locations, "yellow") def setup_ball(self, ball_position, ball_velocity, distance_from_ground=0): """Setup the ball with the x, y coordinates in meters :param ball_position: A tuple with the x,y coordinates :param ball_velocity: A tuple with the x,y velocity components :param distance_from_ground: How high up to start the ball """ self.world_state.ball_state.CopyFrom( BallState( global_position=Point( x_meters=ball_position.x(), y_meters=ball_position.y(), ), global_velocity=Vector( x_component_meters=ball_velocity.x(), y_component_meters=ball_velocity.y(), ), distance_from_ground=distance_from_ground, ) ) self.setup_world(self.world_state) def setup_world(self, world_state): """Pass in a world_state proto directly to setup the simulator :param world_state: The world state to initialize with """ self.world_state_sender.send(world_state) def __get_sensor_proto(self, ssl_wrapper, robot_status_listener): """Helper function to create a sensor proto :param ssl_wrapper: The ssl_wrapper packet to put in the sensor proto :param robot_status_listener: The robot status listener (blue or yellow) :returns: A sensor proto with the robot status from the listener """ sensor_proto = SensorProto() if ssl_wrapper: sensor_proto.ssl_vision_msg.CopyFrom(ssl_wrapper) robot_status = robot_status_listener.get_most_recent_message() packets = [] while robot_status is not None: packets.append(robot_status) robot_status = robot_status_listener.get_most_recent_message() sensor_proto.robot_status_msgs.extend(packets) return sensor_proto def get_blue_sensor_proto(self, ssl_wrapper): """Returns the blue sensor proto :param ssl_wrapper: The wrapper to pack in the sensor proto """ return self.__get_sensor_proto(ssl_wrapper, self.blue_robot_status_listener) def get_yellow_sensor_proto(self, ssl_wrapper): """Returns the yellow sensor proto :param ssl_wrapper: The wrapper to pack in the sensor proto """ return self.__get_sensor_proto(ssl_wrapper, self.yellow_robot_status_listener) def get_ssl_wrapper_packet(self, block=False): """Get wrapper packet :param block: If true, block until we receive a packet :return: SSL_WrapperPacket """ return self.ssl_wrapper_listener.get_most_recent_message(block) def tick(self, duration_ms): """Tick the simulator with the given duration :param duration_ms: The duration to step the sim """ tick = SimulatorTick() tick.milliseconds = duration_ms self.sim_tick_sender.send(tick) def send_blue_primitive_set_and_world(self, world, primitive_set): """Blue primitive set and world :param world: The world msg to send :param primitive_set: The primitive set to send """ self.blue_world_sender.send(world) self.blue_primitive_set_sender.send(primitive_set) def send_yellow_primitive_set_and_world(self, world, primitive_set): """Yellow primitive set and world :param world: The world msg to send :param primitive_set: The primitive set to send """ self.yellow_world_sender.send(world) self.yellow_primitive_set_sender.send(primitive_set) def stop(): """Stop all listeners and senders. """ for unix_socket in [ self.sim_tick_sender, self.world_state_sender, self.blue_world_sender, self.yellow_world_sender, self.blue_primitive_set_sender, self.yellow_primitive_set_sender, self.ssl_wrapper_listener, self.blue_robot_status_listener, self.yellow_robot_status_listener, ]: unix_socket.force_stop()
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# ไธ€ไธช้ป‘ๆฟไธŠๅ†™็€ไธ€ไธช้ž่ดŸๆ•ดๆ•ฐๆ•ฐ็ป„ nums[i] ใ€‚ # ๅฐ็บขๅ’Œๅฐๆ˜Ž่ฝฎๆตไปŽ้ป‘ๆฟไธŠๆ“ฆๆމไธ€ไธชๆ•ฐๅญ—๏ผŒๅฐ็บขๅ…ˆๆ‰‹ใ€‚ # ๅฆ‚ๆžœๆ“ฆ้™คไธ€ไธชๆ•ฐๅญ—ๅŽ๏ผŒๅ‰ฉไฝ™็š„ๆ‰€ๆœ‰ๆ•ฐๅญ—ๆŒ‰ไฝๅผ‚ๆˆ–่ฟ็ฎ—ๅพ—ๅ‡บ็š„็ป“ๆžœ็ญ‰ไบŽ 0 ็š„่ฏ๏ผŒๅฝ“ๅ‰็Žฉๅฎถๆธธๆˆๅคฑ่ดฅใ€‚ย  # (ๅฆๅค–๏ผŒๅฆ‚ๆžœๅชๅ‰ฉไธ€ไธชๆ•ฐๅญ—๏ผŒๆŒ‰ไฝๅผ‚ๆˆ–่ฟ็ฎ—ๅพ—ๅˆฐๅฎƒๆœฌ่บซ๏ผ›ๅฆ‚ๆžœๆ— ๆ•ฐๅญ—ๅ‰ฉไฝ™๏ผŒๆŒ‰ไฝๅผ‚ๆˆ–่ฟ็ฎ—็ป“ๆžœไธบ0ใ€‚๏ผ‰ # ๆข็ง่ฏดๆณ•ๅฐฑๆ˜ฏ๏ผŒ่ฝฎๅˆฐๆŸไธช็Žฉๅฎถๆ—ถ๏ผŒๅฆ‚ๆžœๅฝ“ๅ‰้ป‘ๆฟไธŠๆ‰€ๆœ‰ๆ•ฐๅญ—ๆŒ‰ไฝๅผ‚ๆˆ–่ฟ็ฎ—็ป“ๆžœ็ญ‰ไบŽ 0๏ผŒ่ฟ™ไธช็Žฉๅฎถ่Žท่ƒœใ€‚ # ๅ‡่ฎพไธคไธช็Žฉๅฎถๆฏๆญฅ้ƒฝไฝฟ็”จๆœ€ไผ˜่งฃ๏ผŒๅฝ“ไธ”ไป…ๅฝ“ๅฐ็บข่Žท่ƒœๆ—ถ่ฟ”ๅ›ž trueใ€‚ ###################################################################### def xorGame(nums): re = 0 for i in nums: re = re ^ i if re == 0: return True else: if len(nums) % 2 == 0: return True else: return False pass ###################################################################### # ๅฐ็บขๅฟ…่ƒœ็š„ๅฏ่ƒฝๆ€งไธบ๏ผŒๅ…ˆๆ‰‹ๅผ‚ๆˆ–ไธบ0๏ผŒๆˆ–numsไธญ็š„ๅ…ƒ็ด ไธบๅถๆ•ฐ๏ผŒๅ…ถไป–ๆ‰ๆœ‰ๅฏ่ƒฝๅฐๆ˜Ž่ƒœๅˆฉใ€‚ nums = [1,1,2,3] result = xorGame(nums)
[ "735159373@qq.com" ]
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import psycopg2 import psycopg2.extras import faker import random def add_order(connection): try: cursor = connection.cursor(cursor_factory = psycopg2.extras.DictCursor) # Choose random user cursor.execute(''' SELECT user_pid FROM users ORDER BY random() DESC LIMIT 1; ''') user = dict(cursor.fetchone()) user_pid = user['user_pid'] # Choose random item cursor.execute(''' SELECT item_pid, item_price FROM items ORDER BY random() DESC LIMIT 1; ''') item = dict(cursor.fetchone()) item_pid = item['item_pid'] item_price = item['item_price'] cursor.execute(''' INSERT INTO orders(user_pid, item_pid, order_price) VALUES(%s, %s, %s) RETURNING order_pid ''', (user_pid, item_pid, item_price)) order = dict(cursor.fetchone()) order_pid = order['order_pid'] cursor.execute(''' UPDATE users SET user_balance = user_balance - %s WHERE user_pid = %s ''', (item_price, user_pid)) except (Exception, psycopg2.DatabaseError) as error: connection.rollback() cursor.close() print("[ ERROR ] User: %s failed to order item %s for price: %s" % ( user_pid, item_pid, item_price )) print(str(error)) return connection.commit() cursor.close() print("[ ORDER ] User: %s ordered item %s for price: %s, order number: %s" % ( user_pid, item_pid, item_price, order_pid )) def connect(): print('Connecting to the PostgreSQL database...') connection = psycopg2.connect( host = "192.168.122.51", database = "unixway1", user = "unixway1user", password = "password1" ) for index in range(0, 100000): add_order( connection = connection ) if __name__ == '__main__': connect()
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import cv2 import numpy as np img = cv2.imread('Covid1.png') print("Image Properties") print("- Number of Pixels: " + str(img.size)) print("- Shape/Dimensions: " + str(img.shape)) cv2.imshow('org',img) cv2.waitKey(0) blue, green, red = cv2.split(img) # Split the image into its channels resized_image = cv2.resize(img, (200, 200)) print("Image Properties") print("- Number of Pixels: " + str(resized_image.size)) print("- Shape/Dimensions: " + str(resized_image.shape)) cv2.imshow('res',resized_image) # Display the grayscale version of image cv2.waitKey(0) img_gray = cv2.cvtColor(resized_image, cv2.COLOR_BGR2GRAY) cv2.imshow('grayscale',img_gray) # Display the grayscale version of image cv2.waitKey(0) r, threshold = cv2.threshold(img_gray, 125, 255, cv2.THRESH_BINARY) cv2.imshow('threshold',threshold) cv2.waitKey(0) edged = cv2.Canny(img_gray, 100,200) cv2.imshow('Edge',edged) cv2.waitKey(0) contours, hierarchy = cv2.findContours(edged,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) print("Number of Contours found = " + str(len(contours))) cv2.drawContours(resized_image, contours, -1, (0, 255, 0), 3) cv2.imshow('Contours', resized_image) cv2.waitKey(0)
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from abc import ABCMeta, abstractmethod class AbstractStrategy(object): """ AbstractStrategy is an abstract base class providing an interface for all subsequent (inherited) strategy handling objects. The goal of a (derived) Strategy object is to generate Signal objects for particular symbols based on the inputs of ticks generated from a PriceHandler (derived) object. This is designed to work both with historic and live data as the Strategy object is agnostic to data location. """ __metaclass__ = ABCMeta @abstractmethod def calculate_signals(self, event): """ Provides the mechanisms to calculate the list of signals. """ raise NotImplementedError("Should implement calculate_signals()") def set_portfolio(self, portfolio_handler): self.portfolio_handler = portfolio_handler def get_symbol_position(self, symbol): key = ["symbol", "quantity", "unavailable_quantity", "available_quantity", "price", "total_commission", "avg_price", "market_value"] position_dict = {k:0 for k in key} position_dict["symbol"] = symbol try: position = self.portfolio_handler.portfolio.positions[symbol] except: pass else: position_dict["quantity"] = position.quantity position_dict["unavailable_quantity"] = position.unavailable_quantity position_dict["available_quantity"] = position.available_quantity position_dict["price"] = position.price position_dict["total_commission"] = position.total_commission position_dict["avg_price"] = position.avg_price position_dict["market_value"] = position.market_value return position_dict class Strategies(AbstractStrategy): """ Strategies is a collection of strategy """ def __init__(self, *strategies): self._lst_strategies = strategies def calculate_signals(self, event): for strategy in self._lst_strategies: strategy.calculate_signals(event)
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# Author: Gael Varoquaux # Copyright: INRIA import pylab as pl import numpy as np from scipy import linalg from covariance.generate_data import generate_standard_sparse_mvn from covariance.cov_estimator_l1 import CovEstimatorL1CV ################################################################################ N_SAMPLES = 30 DIM = 20 prng = np.random.RandomState(10) x, true_prec = generate_standard_sparse_mvn(N_SAMPLES, DIM, prng=prng) emp_cov = np.dot(x.T, x)/N_SAMPLES true_cov = linalg.inv(true_prec) model = CovEstimatorL1CV() model.fit(x) l1 = model.best_model.l1 if 1: prec_ = model.precision cov_ = linalg.inv(prec_) #gap, pobj, dobj = model.dual_gap(emp_cov, with_obj=True) #print "Dual gap : %s" % gap #print "Criterion : %s" % pobj #print "Dual criterion : %s" % dobj ############################################################################### # Visualize vmin = min(true_cov.min(), emp_cov.min(), cov_.min()) vmax = max(true_cov.max(), emp_cov.max(), cov_.max()) vmax = max(-vmin, vmax) pl.figure() pl.subplot(2, 3, 1) pl.imshow(true_cov, interpolation='nearest', vmin=-vmax, vmax=vmax, cmap=pl.cm.RdBu_r) pl.axis('off') pl.title('True (simulated) covariance', fontsize=10) pl.subplot(2, 3, 2) pl.imshow(emp_cov, interpolation='nearest', vmin=-vmax, vmax=vmax, cmap=pl.cm.RdBu_r) pl.axis('off') pl.title('sample covariance', fontsize=10) pl.subplot(2, 3, 3) pl.imshow(cov_, interpolation='nearest', vmin=-vmax, vmax=vmax, cmap=pl.cm.RdBu_r) pl.axis('off') pl.title('L1 covariance estimate \n for lambda=%s' % l1, fontsize=10) vmin = min(true_prec.min(), prec_.min()) vmax = max(true_prec.max(), prec_.max()) vmax = max(-vmin, vmax) pl.subplot(2, 3, 4) pl.imshow(true_prec, interpolation='nearest', vmin=-vmax, vmax=vmax, cmap=pl.cm.RdBu_r) pl.imshow(np.ma.masked_array(np.ones_like(true_prec), true_prec!=0), cmap=pl.cm.gray, interpolation='nearest', vmin=0, vmax=2) pl.axis('off') pl.title('True (simulated) precision', fontsize=10) pl.subplot(2, 3, 5) pl.imshow(linalg.inv(emp_cov), interpolation='nearest', vmin=-vmax, vmax=vmax, cmap=pl.cm.RdBu_r) pl.axis('off') pl.title('Empirical precision', fontsize=10) pl.subplot(2, 3, 6) pl.imshow(prec_, interpolation='nearest', vmin=-vmax, vmax=vmax, cmap=pl.cm.RdBu_r) pl.imshow(np.ma.masked_array(np.ones_like(true_prec), np.abs(prec_)>1e-2), cmap=pl.cm.gray, interpolation='nearest', vmin=0, vmax=2) pl.axis('off') pl.title('L1 precision estimate \n for lambda=%s' % l1, fontsize=10) pl.show()
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# Licensed under MIT License. # See LICENSE in the project root for license information. """Several graph algorithms.""" # With DFS, we can classify the edges in a directed or undirected graph: # # 1. A tree edge is (u,v) if v was first discovered by exploring edge (u,v). All the edges in the depth-first forest G(parent) (aka the predecessor subgraph) are tree edges (but the reverse does not always hold - not all tree edges are in G(pa)). # 2. A back edge is (u,v) connecting u to an ancestor v in a depth-first tree. For # directed graphs, we consider self-loops to be back edges. # 3. A forward edge is a non-tree edge (u,v) connecting u to a descendant v. # 4. All other edges that is not any of the above kind are called cross edges. # 5. For undirected graphs, we classify the edge as the first type in the list # above; and we classify the edge according to whichever of (u,v) or (v,u) the DFS # encounters first. # # When we first explore an edge (u,v), if: # a) v.color = WHITE: then this is a tree edge. # b) v.color = GRAY: then this is a back edge, since the gray vertices always form # a linear chain of descendants corresponding to the stack of active _dfs_visit() # invocations. Exploration always proceeds from the deepest (latest) gray vertex, # so an edge that reaches another gray vertex must have reached an ancestor. # c) v.color = BLACK (only possible for a directed graph): then this is a forward # or cross edge. When u.grayed_time < v.grayed_time, it is a forward edge; if >, # it is a cross edge. # # According to CLRS Theorem 22.10, for an undirected graph, every edge is either a # tree edge or a back edge (ie there are no forward or cross edges). # Hence, for an undirected graph, it has a cycle if and only if DFS finds a back # edge. from typing import Sequence, Tuple import enum class Color(enum.Enum): """Color definition for Graph.""" WHITE = enum.auto() GRAY = enum.auto() BLACK = enum.auto() class Graph: """Graph represented using adjacency lists. The default is undirected graph.""" def __init__( self, num_vertices: int, edges: Sequence[Tuple], is_directed: bool = False ) -> None: # Adjacency list (ie list of all neighbors) for all vertices self.adjlist = [[] for _ in range(num_vertices)] for v1, v2 in edges: # `edges` is a list of tuples of vertex values like (v1, v2). # We want to store the edge info as neighbors for each vertex, so that # we will have an adjacency list self.adjlist[v1].append(v2) if not is_directed: self.adjlist[v2].append(v1) self.color: Color = [Color.WHITE] * num_vertices # For source vertex and all undiscovered vertices, their parents are None self.parent = [None] * num_vertices # Distance (ie total num of edges) from source to the vertex self.distance = [None] * num_vertices # The next attrs are for DFS to store the time when a vertex turns gray/black self.timestamp = 0 self.grayed_time = [None] * num_vertices self.blackened_time = [None] * num_vertices # Mark the cycle index number of a vertex; `None` if it belongs to no cycle self.cycle_mark = [None] * max(num_vertices, len(edges)) # Total number of cycles in the graph self.num_cycles = 0 def __repr__(self) -> str: """Representation showing neighbors of each vertex.""" return "\n".join([f"{i}: {neighbors}" for (i, neighbors) in enumerate(self.adjlist)]) def __str__(self) -> str: """Representation.""" return self.__repr__() def adjacency_matrix(self) -> list: """Get the adjacency matrix.""" adjmat = [[0] * len(self.adjlist) for _ in range(len(self.adjlist))] for i, neighbors in enumerate(self.adjlist): for j in neighbors: adjmat[i][j] = 1 return adjmat def breadth_first_search(self, source: int) -> list: """Breadth-first search (BFS) of a graph from vertex `source`, cf CLRS 22.2.""" # Time complexity: O(num_vertices + num_edges), aka O(V+E) # Note: This initialization is a must, since other methods may change defaults self.color = [Color.WHITE] * len(self.adjlist) # For source vertex and all undiscovered vertices, their parents are None self.parent = [None] * len(self.adjlist) # Distance (ie total num of edges) from source to the vertex self.distance = [None] * len(self.adjlist) # Source is discovered, but not all its neighbors are discovered, so gray self.color[source] = Color.GRAY self.distance[source] = 0 queue = [] # Use-and-discard FIFO queue traversal = [] # Record the BFS traversal route queue.append(source) traversal.append(source) while queue: # We use queue as FIFO here u = queue.pop(0) for v in self.adjlist[u]: if self.color[v] == Color.WHITE: # White means undiscovered, so discover it self.color[v] = Color.GRAY self.distance[v] = self.distance[u] + 1 self.parent[v] = u queue.append(v) traversal.append(v) # When u's adjlist is exhausted, turn u to black self.color[u] = Color.BLACK return traversal def shortest_path(self, source: int, vertex: int) -> list: """Return the shortest path from vertex `source` to `vertex`. Note ---- The length of the shortest path (when one exists) is trivial: `len(returning list)-1`. """ # Time complexity: O(num of vertices in the path) # First, we need to compute all vertices' parents using b_f_s() _ = self.breadth_first_search(source) if vertex == source: return [source] elif self.parent[vertex] is None: print(f"No path from {source} to {vertex} exists.") return [] else: return self.shortest_path(source, self.parent[vertex]) + [vertex] def breadth_first_search_jovian(self, source: int) -> list: """Breadth-first search (BFS) traversal of a graph from vertex `source`.""" # Time complexity: O(num_vertices + num_edges), aka O(V+E) visited = [False] * len(self.adjlist) queue = [] # same as `traversal` in the above breadth_first_search() # Label root (ie source) as visited visited[source] = True queue.append(source) i = 0 while i < len(queue): for v in self.adjlist[queue[i]]: # v is a neighbor of queue[i] (starting from queue[0]=source) if not visited[v]: visited[v] = True queue.append(v) i += 1 return queue def depth_first_search(self) -> list: """Depth-first search (DFS) of a graph, cf CLRS 22.3.""" # Time complexity: Theta(V + E) # Note: This initialization is a must, since other methods may change defaults self.color = [Color.WHITE] * len(self.adjlist) # For source vertex and all undiscovered vertices, their parents are None self.parent = [None] * len(self.adjlist) self.timestamp = 0 # `predsubg` is the predecessor subgraph: G(parent) = (V, E(parent)), where # E(parent) = {(v.pa, v): v in G.V and v.pa is not None}. # Note: Depending on the tree structure, predsubg may not include ALL edges of # the original graph. But we are sure that predsubg does not include duplicate # edges, and does not have any edges that are not present in the original graph. predsubg = [None] * len(self.adjlist) for vertex in range(len(self.adjlist)): if self.color[vertex] == Color.WHITE: # Every time _dfs_visit(vertex) is called, `vertex` becomes the root of # a new tree in the depth-first forest predsubg[vertex] = self._dfs_visit(vertex) return predsubg, self.grayed_time, self.blackened_time def _dfs_visit(self, vertex: int) -> list: # Visit all neighbors of `vertex` using DFS approach. traversal = [] # White `vertex` is discovered, so it turns gray self.timestamp += 1 self.grayed_time[vertex] = self.timestamp self.color[vertex] = Color.GRAY for v in self.adjlist[vertex]: # Edge (vertex, v) is being explored by the DFS if self.color[v] == Color.WHITE: self.parent[v] = vertex traversal += [(vertex, v)] + self._dfs_visit(v) elif self.color[v] == Color.GRAY: # TODO: For an undirected graph, this means (u,v) is a back edge, which means there is a cycle # print('cyc', traversal + [(v, self.parent[v])]) pass # When all neighbors of `vertex` have been exhausted, it turns black self.color[vertex] = Color.BLACK self.timestamp += 1 self.blackened_time[vertex] = self.timestamp return traversal def depth_first_search_jovian(self, source: int) -> list: """Depth-first search (DFS) traversal of a graph from vertex `source`.""" # DFS is more memory efficient than BFS, since you can backtrack sooner. visited = [False] * len(self.adjlist) queue = [] stack = [source] while stack: v = stack.pop() if not visited[v]: visited[v] = True queue.append(v) for neighbor in self.adjlist[v]: # Push (ie append) all neighbors of v into stack for next loop stack.append(neighbor) return queue def is_cyclic(self) -> bool: """Check if the graph has any cycles.""" visited = [False] * len(self.adjlist) for vertex in range(len(self.adjlist)): if not visited[vertex] and self._is_subgraph_cyclic(vertex, visited, -1): return True return False def _is_subgraph_cyclic(self, v: int, visited: Sequence, parent: int) -> bool: # Detect cycles in the subgraph reachable from vertex `v`. visited[v] = True for neighbor in self.adjlist[v]: if not visited[neighbor]: # If neighbor is not visited, then recurse on it if self._is_subgraph_cyclic(neighbor, visited, v): return True elif parent != neighbor: # If neighbor has been visited and is not the parent of v, # then there is a cycle return True return False def dfs_cycle(self, u: int, p: int) -> None: """Mark the vertices with different numbers for different cycles.""" if p is None: # This initialization is a must, since other methods may change defaults self.color = [Color.WHITE] * len(self.adjlist) # For source vertex and all undiscovered vertices, their parents are None self.parent = [None] * len(self.adjlist) # Store total number of cycles found; also used as current cycle's index num self.num_cycles = 0 if self.color[u] == Color.GRAY: # A vertex that is discovered but not finished. # For an undirected graph, this means we have discovered a back edge, which # means there is a cycle. So we backtrack based on parents to find whole cyc self.num_cycles += 1 current = p self.cycle_mark[current] = self.num_cycles while current != u: # Backtrack the parent of current, until the cycle is exhausted current = self.parent[current] self.cycle_mark[current] = self.num_cycles elif self.color[u] == Color.WHITE: # Set p to be u's parent, and mark u as (first) discovered self.parent[u] = p self.color[u] = Color.GRAY for v in self.adjlist[u]: # Edge (u, v) is being explored by the DFS if v != self.parent[u]: self.dfs_cycle(v, u) # Now u is finished self.color[u] = Color.BLACK def print_cycles(self, edges: Sequence[Tuple]) -> None: """Print and return the cycles in the graph.""" self.dfs_cycle(0, None) cycles = [[] for _ in range(self.num_cycles + 1)] for i in range(len(self.adjlist)): if self.cycle_mark[i] is not None: print(i, self.cycle_mark, cycles) cycles[self.cycle_mark[i]].append(i) for i in range(1, self.num_cycles + 1): print(f"Cycle #{i}:", *cycles[i]) print() return cycles[1:] ########################################## ### Driver code edges = [(0, 1), (1, 2), (2, 3), (3, 4), (4, 0), (1, 4), (1, 3)] g1 = Graph(5, edges) print(g1) print('Adjacent matrix:', g1.adjacency_matrix()) print('BFS:', g1.breadth_first_search(3)) print('BFS jovian:', g1.breadth_first_search_jovian(3)) print('Shortest path:', g1.shortest_path(2, 4)) print('DFS:', g1.depth_first_search()) print('DFS jovian:', g1.depth_first_search_jovian(0)) print('Has cycles:', g1.is_cyclic()) print(g1.print_cycles(edges)) # Has a small cycle edges = [(0, 1), (0, 3), (1, 2), (2, 0), (3, 4)] g = Graph(5, edges) print(g) print(g.depth_first_search()) print(g.is_cyclic()) print("Cycles: ", g.print_cycles(edges)) # Has a big cycle edges = [(0, 1), (1, 2), (2, 3), (3, 4), (4, 0)] g = Graph(5, edges) print(g) print(g.depth_first_search()) print(g.is_cyclic()) print("Cycles: ", g.print_cycles(edges)) edges = [(0, 1), (0, 3), (3, 1), (1, 4), (4, 3), (2, 4), (2, 5), (5, 5)] g = Graph(6, edges, is_directed=True) print(g) print(g.depth_first_search()) print("Cycles: ", g.print_cycles(edges)) edges = [(0, 1), (1, 2), (2, 3), (1, 4), (5, 6), (5, 7)] g = Graph(8, edges, is_directed=True) print(g) print(g.depth_first_search())
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# waopp to add students and their rno in class class student: def __init__(self, rno, name): self.rno = rno self.name = name def show(self): print("rno = ", self.rno) print("name = ",self.name) data = [] while True: op = int(input(" 1 add, 2 view and 3 exit")) if op == 1: rno = int(input("enter rno ")) name = input("enter name ") s = student(rno, name) data.append(s) elif op == 2: for d in data: d.show() elif op == 3: break else: print("invalid option ")
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a = str.split(raw_input()) N = int(a[0]) K = int(a[1]) ret = 0; for i in range(0,N): if(int(raw_input())%K==0): ret = ret + 1 print ret
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from pyspark.sql import Row from pyspark.ml.feature import OneHotEncoder, StringIndexer from pyspark.ml.feature import VectorAssembler from pyspark import SparkConf, SparkContext from pyspark.sql import SQLContext from pyspark.ml import Pipeline from pyspark.mllib.classification import LogisticRegressionWithSGD, LogisticRegressionModel from pyspark.mllib.regression import LabeledPoint from pyspark.mllib.linalg import Vectors from pyspark.mllib.evaluation import BinaryClassificationMetrics import os, tempfile path = tempfile.mkdtemp() #sc = spark.sparkContext conf = SparkConf().setAppName("Assignment 3") sc = SparkContext(conf=conf) sqlCtx = SQLContext(sc) ###### Part 1- Preparing the data ####### #To count the number of distinct values in each column distnct_values = {} # Load a text file and convert each line to a Row. lines = sc.textFile("test_2.csv") #extract header header = lines.first() lines = lines.filter(lambda row : row != header) parts = lines.map(lambda l: l.split(",")) data_T = parts.map(lambda p: Row(click=(p[1]), C1=p[3], banner_pos = p[4], site_id=p[5], site_domain=p[6], site_category=p[7], app_id=p[8], app_domain=p[9], app_category=p[10], device_id=p[11], device_ip=p[12], device_model=p[13], device_type=p[14], device_conn_type=p[15], C14=p[16], C15=p[17], C16=p[18], C17=p[19], C18=p[20], C19=p[21], C20=p[22], C21=p[23] )) #create the dataframe df = sqlCtx.createDataFrame(data_T) #selecting all the categorical columns and checking the distinct values in each col_names= ['C1','site_category','app_category','device_type','C14','C15','C16','C17','C18','C19','C20','C21'] for i in col_names: ##col_names contains names of cols that contains categorical data distinctValues = df.select(i).distinct().rdd.map(lambda r: r[0]).count() distnct_values[i] = distinctValues #delete columns which have more than 100 distinct values in them for key, value in distnct_values.iteritems() : if int(value) >100: df = df.drop(str(key)) #drop the columns which have NA values in it. df = df.na.replace('', 'NA', 'C1') df = df.dropna() #stringIndexer on all the categorical columns c1I = StringIndexer(inputCol="C1", outputCol="iC1", handleInvalid="skip") c15I = StringIndexer(inputCol="C15", outputCol="iC15", handleInvalid="skip") c16I = StringIndexer(inputCol="C16", outputCol="iC16", handleInvalid="skip") c18I = StringIndexer(inputCol="C18", outputCol="iC18", handleInvalid="skip") c19I = StringIndexer(inputCol="C19", outputCol="iC19", handleInvalid="skip") c21I = StringIndexer(inputCol="C21", outputCol="iC21", handleInvalid="skip") appcatI = StringIndexer(inputCol="app_category", outputCol="i_app_category", handleInvalid="skip") devtypeI = StringIndexer(inputCol="device_type", outputCol="i_device_type", handleInvalid="skip") sitecatI = StringIndexer(inputCol="site_category", outputCol="i_site_category", handleInvalid="skip") #OneHotEncoder applied after the stringIndexer to form binary vector for each column c1E = OneHotEncoder(inputCol="iC1", outputCol="C1Vector") c15E = OneHotEncoder(inputCol="iC15", outputCol="C15Vector") c16E = OneHotEncoder(inputCol="iC16", outputCol="C16Vector") c18E = OneHotEncoder(inputCol="iC18", outputCol="C18Vector") c19E = OneHotEncoder(inputCol="iC19", outputCol="C19Vector") c21E = OneHotEncoder(inputCol="iC21", outputCol="C21Vector") appcatE = OneHotEncoder(inputCol="i_app_category", outputCol="i_app_category_Vector") devtypeE = OneHotEncoder(inputCol="i_device_type", outputCol="i_device_type_Vector") sitecatE = OneHotEncoder(inputCol="i_site_category", outputCol="i_site_category_Vector") #Vector assembler fAssembler = VectorAssembler( inputCols=["C1Vector", "C15Vector", "C16Vector", "C18Vector", "C19Vector", "C21Vector", "i_app_category_Vector", "i_device_type_Vector", "i_site_category_Vector"], outputCol="features") #pipeline to sum up all the stringIndexers and OneHotEncoders and VectorAssemebler data_P = Pipeline(stages=[c1I, c15I, c16I, c18I, c19I, c21I, appcatI, devtypeI, sitecatI, c1E, c15E, c16E, c18E, c19E, c21E, appcatE, devtypeE, sitecatE, fAssembler]) model = data_P.fit(df) data_t = model.transform(df) ###### Part 1 ends here ##### # Making the labelpoints to train the data with LR parsedData=data_t.select('click', 'features').rdd.map(lambda row: LabeledPoint(float(row.click),Vectors.dense((row.features).toArray()))) # split the dataset training,test = parsedData.randomSplit([0.6, 0.4], seed=11L) training.cache() ##### PART 4 ###### # Retrain your model using an L2 Regularization method. # Tune the cost parameter by dividing your training set into a training and a validation set. # Output the value of the best choice. Test the new model with the provided test set. Output the accuracy, FPR, and AUC training_l2, validation_l2 = training.randomSplit([0.8, 0.2], seed=11L) training_l2.cache() model1 = LogisticRegressionWithSGD.train(training_l2, step=0.1, miniBatchFraction=0.1, regType='l2', regParam=0.01) model2 = LogisticRegressionWithSGD.train(training_l2, step=0.1, miniBatchFraction=0.1, regType='l2', regParam=1.0) model3 = LogisticRegressionWithSGD.train(training_l2, step=0.1, miniBatchFraction=0.1, regType='l2', regParam=0.9) model3.save(sc, path) # 1- Testing the Accuracy by changing the regParam(cost Parameter) print("Model 1:") labelsAndPreds1 = validation_l2.map(lambda p: (float(model1.predict(p.features)), p.label)) Accuracy = labelsAndPreds1.filter(lambda (v, p): v == p).count() / float(validation_l2.count()) print("Accuracy 1 = " + str(Accuracy)) print("Model 2:") labelsAndPreds2 = validation_l2.map(lambda p: (float(model2.predict(p.features)), p.label)) Accuracy = labelsAndPreds2.filter(lambda (v, p): v == p).count() / float(validation_l2.count()) print("Accuracy 2 = " + str(Accuracy)) print("Model 3:") labelsAndPreds3 = validation_l2.map(lambda p: (float(model3.predict(p.features)), p.label)) Accuracy = labelsAndPreds3.filter(lambda (v, p): v == p).count() / float(validation_l2.count()) print("Accuracy 3 = " + str(Accuracy)) # After running all the three models, the accuracy was slightly higher in the 3rd model - Accuracy = 0.831453634085 # So using the 3rd model to evaluate the test set: print("Test Data Metrics on Best model:") model_best = LogisticRegressionModel.load(sc,path) # 1- Accuracy labelsAndPredsT = test.map(lambda p: (float(model_best.predict(p.features)), p.label)) Accuracy = labelsAndPredsT.filter(lambda (v, p): v == p).count() / float(test.count()) print("Accuracy = " + str(Accuracy)) # 2- To Find the FPR fpr_of_data= labelsAndPredsT.filter(lambda (v, p): v==1 and p==0).count() fpr= fpr_of_data/(fpr_of_data+labelsAndPredsT.filter(lambda (v, p): v==0 and p==0).count()) print("FPR = " + str(fpr)) #Clears the threshold so that predict will output raw prediction scores, which will be used for AU -ROC model_best.clearThreshold() # Instantiate metrics object metrics = BinaryClassificationMetrics(labelsAndPredsT) # Area under ROC curve print("Area under ROC = %s" % metrics.areaUnderROC)
[ "amogh.gk@gmail.com" ]
amogh.gk@gmail.com
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/KMP.py
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leesen934/leetcode_practices
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def getNext(p): j = 0 k = -1 # next[j]็š„ๅ€ผ๏ผˆไนŸๅฐฑๆ˜ฏk๏ผ‰่กจ็คบ๏ผŒๅฝ“P[j] != T[i]ๆ—ถ๏ผŒjๆŒ‡้’ˆ็š„ไธ‹ไธ€ๆญฅ็งปๅŠจไฝ็ฝฎใ€‚ next_p = [-1] * len(p) while j < len(p) - 1: print("p[k]: " + p[k] + ", p[j]: " + p[j]) if k == -1 or p[k] == p[j]: j += 1 k += 1 if p[j] == p[k]: # ๅฝ“ไธคไธชๅญ—็ฌฆ็›ธ็ญ‰ๆ—ถ่ฆ่ทณ่ฟ‡ next_p[j] = next_p[k] else: next_p[j] = k else: k = next_p[k] print(next_p) return next_p def KMP(s, p): i = 0 # ไธปไธฒไฝ็ฝฎ j = 0 # ๆจกๅผไธฒไฝ็ฝฎ next_p =getNext(p) while i < len(s) and j < len(p): if j == -1 or s[i] == p[j]: # ๅฝ“jไธบ-1ๆ—ถ๏ผŒ่ฆ็งปๅŠจ็š„ๆ˜ฏi๏ผŒๅฝ“็„ถjไนŸ่ฆๅฝ’0 i += 1 j += 1 else: j = next_p[j] if j == len(p): return i - j else: return -1 if __name__ == "__main__": s = "abcabcabcabcabxabc" p = "abcabx" p = "abbcabcaabbcaa" print(KMP(s, p))
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lichunchn0516@gmail.com
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#!/usr/bin/python3.6 from xml.dom.minidom import parse import xml.dom.minidom import os import sys,json json_str=sys.argv[1] #print(json_str) #print(type(json_str)) json_dict=json.loads(json_str) xmlstr = "" for key in json_dict: if(key == 'data'): break; xmlstr +="<Param ErrorCode=\"0\">" xmlstr += "<camera>" xmlstr += "<" + key + ">" for i in json_dict[key]: xmlstr += "<" + i + " " for j in json_dict[key][i]: xmlstr +=" " + j + "=\"" +json_dict[key][i][j] + "\"" xmlstr += "/>" xmlstr += "</" + key + ">" xmlstr += "</camera>" xmlstr += "</Param>" f=open('/tmp/temp.xml', 'w') f.write(xmlstr); f.close(); os.system("/home/root/bin/XmlDevice set /tmp/temp.xml > /dev/null") os.system("/home/root/bin/XiXmlDevice get /home/root/config/camera.xml > /dev/null") DOMTree = xml.dom.minidom.parse("/home/root/config/camera.xml") root=DOMTree.documentElement cameraNodes=root.getElementsByTagName('camera') def getAttrbute(node): tempstr="{" j=1 for key in node.attributes.keys(): tempstr += "\""+ key+"\":\""+node.attributes[key].value+"\"" if j < (node.attributes.length): tempstr +="," j=j+1 tempstr+="}" return tempstr def metaNode(cells, str): str +="\""+cells.nodeName+"\"" + ":" str+='{' i=0 for cell in cells.childNodes: i=i+1 if cell.nodeType == 3: continue str += "\""+cell.nodeName+"\"" + ":" str += getAttrbute(cell) if i < (cells.childNodes.length-1): str +="," str += "}" return str str="{" for camerchild in cameraNodes: k=0 for cell in camerchild.childNodes: k=k+1 if cell.nodeType == 3: continue str = metaNode(cell,str) if k < (camerchild.childNodes.length-1): str += "," str+="}" print (str)
[ "zestroly@126.com" ]
zestroly@126.com
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/nash_test.py
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ryanpig/MultiagentSystem-FindNE
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refs/heads/master
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import nash import numpy as np import datetime import matplotlib.pyplot as plt import matplotlib.mlab as mlab from scipy.stats import norm # Algorithms def non_duplicate_print(eqs): tmp1 = [] tmp2 = [] for eq in eqs: #print("eq:",eq,"tmp:",tmp) #print(np.any(eq in tmp)) #print(eq in tmp) # print(tmp1,tmp2) if len(tmp1) == 0 and len(tmp2) == 0: tmp1.append(eq[0]) tmp2.append(eq[1]) print(eq) flag = False for i in range(len(tmp1)): if np.all(eq[0] == tmp1[i]): if np.all(eq[1] == tmp2[i]): flag = True if flag is False: tmp1.append(eq[0]) tmp2.append(eq[1]) print(eq) def find_nash_support_enum(utilA , utilB): random_game = nash.Game(utilA, utilB) eqs = random_game.support_enumeration() non_duplicate_print(eqs) def find_nash_lemke_howson(utilA , utilB): random_game = nash.Game(utilA, utilB) a = random_game.lemke_howson(initial_dropped_label=0) print("NE", a[0],a[1]) #print("row", a[3]) #print("col", a[4]) return a[2] #for eq in random_game.lemke_howson_enumeration(): # print(eq) #eqs = random_game.lemke_howson_enumeration() #non_duplicate_print(eqs) def find_nash_vertex_enum(utilA , utilB): random_game = nash.Game(utilA, utilB) for eq in random_game.vertex_enumeration(): print(eq) # generate m x n 2-player game def generate_game(m = 2, n = 2, utility_max = 10, utility_min = -10): # two player game, multiple actions (m x n) # m = 6 # n = 4 # utility_max = 10 # utility_min = -10 print("Rows:", m, "Cols:", n, "Max:", utility_max, "Min:", utility_min) utilA = np.random.uniform(utility_min, utility_max, size=(m, n)) utilB = np.random.uniform(utility_min, utility_max, size=(m, n)) utilA = np.asarray(utilA, dtype=np.int8) utilB = np.asarray(utilB, dtype=np.int8) print("utility of row player") print(utilA) print("utility of col player") print(utilB) return utilA, utilB # generate a single m x n game def gen_single_game(m, n): # Configuration flag_steps_distribusion = False flag_single_game = True flag_use_customized_game = True flag_save_game = False #outfileA = 'game_A_prison.npy' #outfileB = 'game_B_prison.npy' #outfileA = 'game_A_rock.npy' #outfileB = 'game_B_rock.npy' #outfileA = 'game_A.npy' #outfileB = 'game_B.npy' outfileA = 'game_A_53.npy' outfileB = 'game_B_53.npy' # outfileA = 'game_A_12.npy' # outfileB = 'game_B_12.npy' if flag_single_game == True: # Generate a new game or use customized game. if flag_use_customized_game == True: a = np.load(outfileA) b = np.load(outfileB) print(a) print(b) else: a, b = generate_game(m=m, n=n) if flag_save_game == True: # Save np.save(outfileA, a) np.save(outfileB, b) a = [[3,1,5],[2,2,4]] b = [[2,1,0],[2,3,1]] t1 = datetime.datetime.now() print("Support Enumeration") find_nash_support_enum(a, b) print("Lemke Howson") find_nash_lemke_howson(a, b) print("Vertex Enumeration") find_nash_vertex_enum(a, b) t2 = datetime.datetime.now() diff = t1 - t2 tdiff_sec = abs(diff.total_seconds()) print("Time cost for finding NE:", tdiff_sec) # Cal steps distribution if flag_steps_distribusion == True: count = 0 arrs = [] counts = [] for k in range(5, 9, 1): counts.clear() for i in range(300): a, b = generate_game(m=k, n=k) # Using customized game # a = [[0,-1,1],[1,0,-1],[-1,1,0]] # b = [[0,1,-1],[-1,0,1],[1,-1,0]] # a = [[3,0],[0,2]] # b = [[2,0],[0,3]] # Loading existing game # outfileA = 'game_A.npy' # outfileB = 'game_B.npy' # a = np.load(outfileA) # b = np.load(outfileB) # Run count = find_nash_lemke_howson(a, b) # Save # np.save(outfileA, a) # np.save(outfileB, b) print(count) if count <= 40: counts.append(count) arrs.append(counts.copy()) title = "Random size:" + str(k) + " x " + str(k) # plot_histogram(counts,title) plot_four_hist(arrs[0], arrs[1], arrs[2], arrs[3]) def plot_histogram(arrs,title): #x = np.random.normal(size=1000) #plt.hist(x, normed=True, bins=30) plt.ylabel('Steps to find a NE'); plt.xlabel('counts'); plt.title(title) plt.hist(arrs, bins=20) plt.show() #l = plt.plot(bins, y, 'r--', linewidth=1) def plot_four_hist(arr1,arr2,arr3,arr4): f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharex='col', sharey='row') (mu1, sigma1) = norm.fit(arr1) (mu2, sigma2) = norm.fit(arr2) (mu3, sigma3) = norm.fit(arr3) (mu4, sigma4) = norm.fit(arr4) mu1 = format(mu1, '.2f') mu2 = format(mu2, '.2f') mu3 = format(mu3, '.2f') mu4 = format(mu4, '.2f') sigma1 = format(sigma1, '.2f') sigma2 = format(sigma2, '.2f') sigma3 = format(sigma3, '.2f') sigma4 = format(sigma4, '.2f') ax1.hist(arr1, rwidth=0.8, color='sandybrown') ax2.hist(arr2, rwidth=0.8, color='sandybrown') ax3.hist(arr3, rwidth=0.8, color='sandybrown') ax4.hist(arr4, rwidth=0.8, color='sandybrown') plt.title("Find a NE in different Size in 300 rounds") ax1.set_ylabel("Counts") ax2.set_ylabel("Counts") ax3.set_ylabel("Counts") ax4.set_ylabel("Counts") str1 = "Game Size 5 x 5 " + ", u:" + str(mu1) + ", s:" + str(sigma1) str2 = "Game Size 6 x 6 " + ", u:" + str(mu2) + ", s:" + str(sigma2) str3 = "Game Size 7 x 7 " + ", u:" + str(mu3) + ", s:" + str(sigma3) str4 = "Game Size 8 x 8 " + ", u:" + str(mu4) + ", s:" + str(sigma4) ax1.set_title(str1) ax2.set_title(str2) ax3.set_title(str3) ax4.set_title(str4) plt.show() def plot_cal_time(arrs): # debug print(arrs[0]) print(arrs[1]) print(arrs[2]) # len1 = len(arrs[0]) x = range(2, len1+2) plt.title('Finding NE in a symmetric game') plt.xlabel('The number of actions') plt.ylabel('Running Time in second') #plt.xlim(xmin=2) a0, = plt.plot(x, arrs[0], 'r') a1, = plt.plot(x, arrs[1], 'g') a2, = plt.plot(x, arrs[2], 'b') plt.legend((a0, a1, a2), ('Support Enum','LH','Vertex Enum')) plt.tight_layout() def gen_multi_games(m, n): max1 = max(m, n) len_algorithms = 3 arr_tdiffs = [] # Loop all algorithm for ind in range(len_algorithms): arr_tdiff = [] for i in range(2, max1+1, 1): a, b = generate_game(m=i, n=i) # time start for the various algorithms t1 = datetime.datetime.now() # pick up one algorithm if ind == 0: find_nash_support_enum(a, b) elif ind == 1: find_nash_lemke_howson(a, b) elif ind == 2: find_nash_vertex_enum(a, b) t2 = datetime.datetime.now() # time end diff = t1 - t2 tdiff_sec = abs(diff.total_seconds()) arr_tdiff.append(tdiff_sec) print("Time cost for finding NE:", tdiff_sec) arr_tdiffs.append(arr_tdiff) # plotting plot_cal_time(arr_tdiffs) # main -> find_nash -> random_game.support_enumeration() # loop symmetric games from (2,2) to (10,10) actions #gen_multi_games(12, 12) # single game test gen_single_game(5, 3)
[ "ryanpig@gmail.com" ]
ryanpig@gmail.com
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danielrhunt/python
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'''COMPARING TUPLES''' '''comparison operators work on tuples, just like other sequences Python starts by comparing the first element in each sequence if they are equal, it goes on to the next element, and then on again, and again, until it finds elements that differ subsequent elements are not considered (even if they are really big)''' '''the SORT FUNCTION works the same way: it sorts primarily by first element, but in case of a tie, it moves onto the next element until the tie is broken this feature lends itself to a pattern called DSU: DECORATE, SORT, and UNDECORATE''' example = "but soft what light in yonder window breaks" print(example) print(type(example)) words = example.split() #this doesn't appear to do anything on its own tt = list() #create empty list for word in words: #build list of tuples, where each tuple is preceded by it's length tt.append((len(word), word)) #add length of word, and then the word print(tt) #prints list in original order, preceded by count print(type(tt)) #the sort compares the first element (length) first, and only considers the second element to break ties #reverse = True tells sort method to go in decreasing order tt.sort(reverse = True) #reverse number sort (i.e. starts at highest) print(tt) #prints list in number sorted order (highest to lowest) print(type(tt)) #this loop traverses the list of tuples, and builds a list of words in descending order of length #the four character words are sorted in reverse alphabetical order res = list() #create another empty list for length, word in tt: #use two mnemonically named iteration variables res.append(word) #append the words to res list print(res) #should just print the words print(type(res))
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from itertools import groupby w = list(input()) k = [(len(list(cgen)), int(c)) for c,cgen in groupby(w)] print(" ".join(str(item) for item in k))
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Snoblomma.noreply@github.com
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/prepare_submission_20180430.py
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#!/usr/bin/python3 from argparse import ArgumentParser import os import collections from lxml.html import fromstring import json import re import requests import glob import pandas from urllib.parse import urljoin from rdflib import Graph, Literal, URIRef from generate_combined_transcript_C1 import ( paper_433_experiment_files, ASOF_RUN17_experiment_files ) from woldrnaseq.models import load_experiments from htsworkflow.util.opener import autoopen from htsworkflow.util.rdfns import ( libraryOntology, RDF, RDFS, ) from htsworkflow.util.rdfhelp import ( dump_model, ) # 20031-20038 are good on flowcell HF7NTBCX2 # 20026-20030 are mixed on flowcell HF7NTBCX2 def main(cmdline=None): parser = ArgumentParser() parser.add_argument('--first-tranche', default=False, action='store_true', help='Use just the first tranche as experiment list') parser.add_argument('--name', required=True, help='submission name') parser.add_argument('-s', '--sheet', default=0, help='Sheet to use') parser.add_argument('--header', default=None, help="header row") parser.add_argument('filename', nargs=1, help='driver spreadsheet') args = parser.parse_args(cmdline) root_fastq_url = 'http://jumpgate.caltech.edu/runfolders/volvox02/' desplit = os.path.expanduser('~/proj/htsworkflow/htsworkflow/pipelines/desplit_fastq.py') header = int(args.header) if args.header is not None else None data = read_spreadsheet(args.filename[0], args.sheet, header) print(data.shape) if args.first_tranche: experiment_file_list = paper_433_experiment_files.split('\n') else: experiment_file_list = ASOF_RUN17_experiment_files.split('\n') experiment_files = [ os.path.expanduser(x.strip()) for x in experiment_file_list] experiments = load_experiments(experiment_files) experiments['replicates'] = experiments['replicates'].apply(lambda l: [x.replace('_mm10', '').replace('_clean', '') for x in l]) current_experiments = find_experiments_to_submit(experiments, data) aliases_tsv = '{}-aliases.tsv'.format(args.name) make_library_aliases(current_experiments, aliases_tsv) submission_fastqs_tsv = '{}-fastqs.tsv'.format(args.name) if not os.path.exists(submission_fastqs_tsv): fastq_urls = find_all_fastqs(root_fastq_url, current_experiments, submission_fastqs_tsv) fastq_urls = pandas.read_csv(submission_fastqs_tsv, sep='\t') barcodes_tsv = '{}-barcodes.tsv'.format(args.name) make_library_barcodes(fastq_urls, barcodes_tsv) metadata_tsv = '{}-flowcell-details.tsv'.format(args.name) metadata = make_metadata(fastq_urls, root_fastq_url, metadata_tsv) merge_file = '{}-merge-fastqs.condor'.format(args.name) make_desplit_condor(fastq_urls, metadata, desplit, root_fastq_url, merge_file) def read_spreadsheet(filename, sheet, header=None): if filename.endswith('xlsx'): data = pandas.read_excel( 'Second_set_of_limb_single_cell_data_for_Diane_almost_complete_April13_2018.xlsx', sheet=sheet, header=header ) elif filename.endswith('ods'): from pandasodf import ODFReader book = ODFReader(filename) data = book.parse(sheet, header=header) return data def find_all_fastqs(root_fastq_url, experiments, output_file): """Get urls to the raw fastq files for all our replicates """ runfolder = Runfolder(root_fastq_url) records = [] multi = [] for record in find_replicate_flowcells(experiments): fastqs = [] for flowcell in record['flowcells']: fastqs.extend(list(runfolder.find_fastqs(flowcell, record['library_id']))) record['fastq_urls'] = fastqs fluidigm_fields = parse_fluidigm(urljoin(root_fastq_url, fastqs[0])) record['barcode'] = fluidigm_fields['barcode'] record['location'] = fluidigm_fields['location'] records.append(record) if len(record['flowcells']) > 1: multi.append(record) df = pandas.DataFrame(records) df.to_csv(output_file, sep='\t', index=False) if len(multi) > 0: print('Warning, runs on multiple flowcells check multiple_flowcells.tsv') pandas.DataFrame(multi).to_csv('multiple_flowcells.tsv', sep='\t') return df def find_replicate_flowcells(experiments): model = Graph() for i, row in experiments.iterrows(): for extended_id in row.replicates: library_id, location, *_ = extended_id.split('_') extended_id = library_id + '_' + location uri = URIRef('https://felcat.caltech.edu/library/{}/'.format(library_id)) s = (uri, RDF['type'], libraryOntology['Library']) if s not in model: model.parse(source=uri, format='rdfa') flowcells = model.query("""PREFIX libns: <http://jumpgate.caltech.edu/wiki/LibraryOntology#> select distinct ?flowcell_id where { ?library a libns:Library ; libns:has_lane ?lane . ?lane libns:flowcell ?flowcell . ?flowcell libns:flowcell_id ?flowcell_id . } """, initBindings={'library': uri}) yield {'experiment': row.name, 'library_id': extended_id, 'flowcells': sorted([x[0].value for x in flowcells]) } def find_experiments_to_submit(experiments, submission_table): to_upload = set(submission_table[submission_table.columns[0]]) missing = set(submission_table[submission_table.columns[0]]) tosubmit = [] for i, row in experiments.iterrows(): current = to_upload.intersection(set(row.replicates)) missing = missing.difference(set(row.replicates)) if len(current) > 0: tosubmit.append({ 'name': row.name, 'analysis_dir': row.analysis_dir, 'replicates': list(current) }) print('Not found:', len(missing), sorted(missing)) df = pandas.DataFrame(tosubmit) df.set_index('name', inplace=True) return df def find_seans_fastqs(experiments): for i, row in experiments.iterrows(): for library_id in row.replicates: pattern = os.path.join(row.analysis_dir, library_id + '*.fastq.gz') files = glob.glob(pattern) assert len(files) > 0 filesets.setdefault(i, []).extend(files) #make_desplit_condor(filesets) def make_library_aliases(experiments, aliases_tsv): aliases = {} for i, row in experiments.iterrows(): for library_id in row.replicates: aliases.setdefault(row.name, []).append('barbara-wold:{}'.format(library_id)) with open(aliases_tsv, 'wt') as outstream: for key in sorted(aliases): outstream.write(key) outstream.write('\t') outstream.write(','.join(sorted(aliases[key]))) outstream.write(os.linesep) def make_library_barcodes(experiments, barcode_tsv): def sorted_plate_key(row): return row['plate_id'] + '_' + row['plate_location'] barcodes = {} for i, row in experiments.iterrows(): plate_id, location, *_ = row.library_id.split('_') record = {'barcode': row.barcode, 'plate_id': plate_id, 'plate_location': location} barcodes.setdefault(row.experiment, []).append(record) with open(barcode_tsv, 'wt') as outstream: for key in sorted(barcodes): outstream.write(key) outstream.write('\t') outstream.write(json.dumps(sorted(barcodes[key], key=sorted_plate_key))) outstream.write(os.linesep) def make_desplit_condor(experiments, metadata, desplit_cmd, root_url, condor_file): """Make condor file to build merged fastqs :Parameters: - experiments: (pandas.DataFrame) Experiments and their fastq urls from find_all_fastqs() - metadata: (pandas.DataFrame) metadata details about each fastq - desplit_cmd: (filename) Path to the desplit_fastq.py file from htsworkflow - condor_file: (filename) target to write condor file :Returns: True if all the merged fastqs exists, otherwise False """ header = """universe=vanilla executable=/usr/bin/python3 error=log/desplit_fastq.$(process).out output=log/desplit_fastq.$(process).out log=log/desplit_fastq.log environment="PYTHONPATH=/woldlab/loxcyc/home/diane/proj/htsworkflow" requirements=(MACHINE != "wold-clst-3.woldlab") && (MACHINE != "wold-clst-4.woldlab") """ experiment_fastqs = {} for i, row in metadata.iterrows(): output_name = row.experiment + '.fastq.gz' experiment_fastqs.setdefault(output_name, []).append(row.fastq_url) # chunk all fastqs by experiment body = [] for output_name in experiment_fastqs: print(output_name) fastq_urls = experiment_fastqs[output_name] body.extend(['arguments="{} --gzip -o {} -s 0:50 {}"'.format(desplit_cmd, output_name, ' '.join(sorted(fastq_urls))), 'queue', '']) if len(body) > 0: with open(condor_file, 'wt') as outstream: outstream.write(header) outstream.write(os.linesep.join(body)) return False else: return True def make_metadata(experiments, root_fastq_url, filename): model = Graph() metadata = [] for i, row in experiments.iterrows(): fastq_urls = [ urljoin(root_fastq_url, x[1:-1]) for x in row.fastq_urls[1:-1].split(', ')] for fastq_url in fastq_urls: fastq_data = parse_fluidigm(fastq_url) metadata.append({ 'experiment': row.experiment, 'fastq_url': fastq_url, 'machine': 'http://jumpgate.caltech.edu/sequencer/8', 'flowcell': fastq_data['flowcell_id'], 'lane': fastq_data['lane_number'], 'barcode': fastq_data['barcode'], 'read_length': fastq_data['read_length'] }) metadata = sorted(metadata, key=lambda row: (row['experiment'], row['flowcell'], row['barcode'])) df = pandas.DataFrame(metadata, columns=['experiment', 'fastq_url', 'machine', 'flowcell', 'lane', 'barcode', 'read_length']) print(df.head()) df.to_csv(filename, sep='\t', index=False) return df fluidigm_fields = ['library_id', 'location', 'barcode', 'lane_number', 'read'] def parse_fluidigm(pathname): path, name = os.path.split(pathname) p = r'(?P<library_id>[0-9]{5})_'\ '(?P<location>[A-H][0-9]{1,2})_'\ '(?P<barcode>[AGCT-]+)_'\ 'L00(?P<lane_number>[1-8])_'\ 'R(?P<read>[1-3])' match = re.match(p, name) if match is not None: fields = { k: match.group(k) for k in fluidigm_fields } with autoopen(pathname, 'rt') as stream: fields.update(parse_fastq_header(stream.readline())) seq = stream.readline() fields['read_length'] = len(seq) return fields def parse_fastq_header(header): header = header.strip() read_id, extra = header.split(' ') fields = read_id.split(':') extra_fields = extra.split(':') return { 'flowcell_id': fields[2], #'lane_number': fields[3], #'read': fields[4], 'barcode': extra_fields[3], } class Runfolder: def __init__(self, root_url): self.root_url = root_url self.pages = {} def load_index(self, url=''): absolute_url = urljoin(self.root_url, url) response = requests.get(absolute_url) if response.status_code != 200: raise RuntimeError('Unable to access {}. Status {}'.format(absolute_url, response.status_code)) tree = fromstring(response.content) rows = tree.xpath('*/table/tr/td/a') if len(rows) == 0: raise RuntimeError('{} is not a directory'.format(absolute_url)) if rows[0].text == 'Parent Directory': rows.pop(0) self.pages[url] = [ x.text for x in rows ] def find_flowcell(self, flowcell): root = '' if root not in self.pages: self.load_index(root) for name in self.pages[root]: if flowcell in name: return name def _find_unaligned(self, url): if url not in self.pages: self.load_index(url) for name in self.pages[url]: for unaligned in ['Unaligned.dualIndex/', 'Unaligned/']: if unaligned == name: return url + name raise RuntimeError('Unable to find index in {}'.format(url)) def _find_extended_id(self, url, extended_id): if url not in self.pages: self.load_index(url) for name in self.pages[url]: if extended_id in name: return url + name def find_fastqs(self, flowcell, extended_id): runfolder = self.find_flowcell(flowcell) assert runfolder is not None unaligned = self._find_unaligned(runfolder) assert unaligned is not None project = self._find_extended_id(unaligned, extended_id) sample = self._find_extended_id(project, extended_id) if sample not in self.pages: self.load_index(sample) for name in self.pages[sample]: if 'fastq.gz' in name: yield sample + name if __name__ == '__main__': main()
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diane@ghic.org
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/02_QUICKVIEW_hand_made_quick_view_classification/02_1_classification_basic_perceptron.py
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jerrychen44/python_machine_learning_sr
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import os import numpy as np import pandas as pd import matplotlib.pyplot as plt filepath=os.path.dirname(os.path.realpath(__file__))#root, where the apk_integration_test.py file is. source_folder='source' print(filepath) data_csv_path=filepath+'/'+source_folder+'/iris.csv' ################################ #implement the perceptron class ############################### class Perceptron(object): """Perceptron classifier. Parameters ------------ eta : float Learning rate (between 0.0 and 1.0) n_iter : int Passes over the training dataset. Attributes ----------- w_ : 1d-array Weights after fitting. errors_ : list Number of misclassifications in every epoch. """ def __init__(self, eta=0.01, n_iter=10): self.eta = eta self.n_iter = n_iter def fit(self, X, y): """Fit training data. Parameters ---------- X : {array-like}, shape = [n_samples, n_features] Training vectors, where n_samples is the number of samples and n_features is the number of features. y : array-like, shape = [n_samples] Target values. Returns ------- self : object """ self.w_ = np.zeros(1 + X.shape[1]) self.errors_ = [] for _ in range(self.n_iter): errors = 0 for xi, target in zip(X, y): update = self.eta * (target - self.predict(xi)) self.w_[1:] += update * xi self.w_[0] += update errors += int(update != 0.0) self.errors_.append(errors) return self def net_input(self, X): """Calculate net input""" return np.dot(X, self.w_[1:]) + self.w_[0] def predict(self, X): """Return class label after unit step""" return np.where(self.net_input(X) >= 0.0, 1, -1) ##################### #loading data set # ref: https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data # Attribute Information: # 1. sepal length in cm # 2. sepal width in cm # 3. petal length in cm # 4. petal width in cm # 5. class: # -- Iris Setosa # -- Iris Versicolour # -- Iris Virginica ########################## def read_csv_pd(): #df = pd.read_csv('https://archive.ics.uci.edu/ml/' # 'machine-learning-databases/iris/iris.data', header=None) df = pd.read_csv(data_csv_path, header=None) #df.to_csv(filepath+'/'+source_folder+'/iris.csv',index=0,header=False) print(df.tail()) print(df.shape) return df def plot_2d_data(df): ###################### # plot to take a look,Plotting the Iris data #################### # select setosa and versicolor y = df.iloc[0:100, 4].values y = np.where(y == 'Iris-setosa', -1, 1) # extract sepal length and petal length X = df.iloc[0:100, [0, 2]].values # plot data plt.scatter(X[:50, 0], X[:50, 1], color='red', marker='o', label='setosa') plt.scatter(X[50:100, 0], X[50:100, 1], color='blue', marker='x', label='versicolor') plt.xlabel('petal length [cm]') plt.ylabel('sepal length [cm]') plt.legend(loc='upper left') plt.tight_layout() # plt.savefig('./iris_1.png', dpi=300) plt.show() return X,y ############## #Training the perceptron model ############ def train_perceptron_model(X,y): #new a object ppn = Perceptron(eta=0.1, n_iter=10) ppn.fit(X, y) #show the error history #it shows the model converge at 6th round. plt.plot(range(1, len(ppn.errors_) + 1), ppn.errors_, marker='o') plt.xlabel('Epochs') plt.ylabel('Number of misclassifications') plt.tight_layout() # plt.savefig('./perceptron_1.png', dpi=300) plt.show() #return the model object return ppn #A function for plotting decision regions def plot_decision_regions(X, y, classifier, resolution=0.02): from matplotlib.colors import ListedColormap # setup marker generator and color map markers = ('s', 'x', 'o', '^', 'v') colors = ('red', 'blue', 'lightgreen', 'gray', 'cyan') cmap = ListedColormap(colors[:len(np.unique(y))]) # plot the decision surface x1_min, x1_max = X[:, 0].min() - 1, X[:, 0].max() + 1 x2_min, x2_max = X[:, 1].min() - 1, X[:, 1].max() + 1 xx1, xx2 = np.meshgrid(np.arange(x1_min, x1_max, resolution), np.arange(x2_min, x2_max, resolution)) Z = classifier.predict(np.array([xx1.ravel(), xx2.ravel()]).T) Z = Z.reshape(xx1.shape) plt.contourf(xx1, xx2, Z, alpha=0.4, cmap=cmap) plt.xlim(xx1.min(), xx1.max()) plt.ylim(xx2.min(), xx2.max()) # plot class samples for idx, cl in enumerate(np.unique(y)): plt.scatter(x=X[y == cl, 0], y=X[y == cl, 1], alpha=0.8, c=cmap(idx), marker=markers[idx], label=cl) def plot_decision_plan(ppn,X,y): plot_decision_regions(X, y, classifier=ppn) plt.xlabel('sepal length [cm]') plt.ylabel('petal length [cm]') plt.legend(loc='upper left') plt.tight_layout() # plt.savefig('./perceptron_2.png', dpi=300) plt.show() return 0 def main(): data_df=read_csv_pd() X,y=plot_2d_data(data_df) ppn=train_perceptron_model(X,y) plot_decision_plan(ppn,X,y) return 0 main()
[ "jerrychen040@gmail.com" ]
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GeoffRiley/AdventOfCode
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from collections import deque def an_elephant_named_joseph(inp, part1=True): elves = deque(range(1, inp + 1)) elves2 = deque() if part1: while len(elves) > 1: elves.rotate(-1) elves.popleft() else: elf_c = inp while len(elves) > len(elves2): elves2.append(elves.pop()) while elf_c > 1: elves2.pop() elves2.appendleft(elves.popleft()) if len(elves2) - len(elves) > 1: elves.append(elves2.pop()) elf_c -= 1 return elves[0] if part1 else elves2[0] if __name__ == '__main__': elf_count = 3_004_953 print(f'Day 19, part 1: {an_elephant_named_joseph(elf_count)}') print(f'Day 19, part 2: {an_elephant_named_joseph(elf_count, False)}') # Day 19, part 1: 1815603 # Day 19, part 2: 1410630
[ "geoffr@adaso.com" ]
geoffr@adaso.com
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# Set up the paths. import os import sys sys.path.append(os.path.abspath('.')) import themodule def test_hallo(): assert themodule.hallo() == "hallo" def test_nohallo(): assert themodule.hallo() != "blaat"
[ "jeroen.van.nieuwenhuizen@jeroen.se" ]
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/partyDataDownload.py
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Shan-Herald-Agency-for-News/MMElection2020_Scripting
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import json import requests import os import shutil partyInfoFile = "shanRegionParties.json" def flag_imageDownload(): image_url = "" filename = "" filepath = "" with open(partyInfoFile) as jFile: data = json.load(jFile) for d in data['data']: attr = d['attributes'] image_url = attr['flag_image'] filename = filename.join( [attr['name_english'], "_", d['id'], ".jpg"]) filepath = os.path.join("party/flag", filename) r = requests.get(image_url, stream=True) if r.status_code == 200: r.raw.decode_content = True with open(filepath, 'wb') as f: shutil.copyfileobj(r.raw, f) print("Image successfully Downloaded: ", filename) image_url = "" filename = "" filepath = "" else: print("Image Couldn\'t be retreived") def policy_download(): file_url = "" filename = "" filepath = "" with open(partyInfoFile) as jFile: data = json.load(jFile) for d in data['data']: attr = d['attributes'] file_url = attr['policy'] filename = filename.join( [attr['name_english'], "_", d['id'], ".pdf"]) filepath = os.path.join("party/policy", filename) r = requests.get(file_url, stream=True) if r.status_code == 200: r.raw.decode_content = True with open(filepath, 'wb') as f: shutil.copyfileobj(r.raw, f) print("Image successfully Downloaded: ", filename) file_url = "" filename = "" filepath = "" else: print("Image Couldn\'t be retreived") partyInfoFile = "shanRegionParties.json" def seal_imageDownload(): image_url = "" filename = "" filepath = "" with open(partyInfoFile) as jFile: data = json.load(jFile) for d in data['data']: attr = d['attributes'] image_url = attr['seal_image'] filename = filename.join( [attr['name_english'], "_", d['id'], ".jpg"]) filepath = os.path.join("party/seal", filename) r = requests.get(image_url, stream=True) if r.status_code == 200: r.raw.decode_content = True with open(filepath, 'wb') as f: shutil.copyfileobj(r.raw, f) print("Image successfully Downloaded: ", filename) image_url = "" filename = "" filepath = "" else: print("Image Couldn\'t be retreived") # seal_imageDownload() # flag_imageDownload() # policy_download()
[ "noernova666@gmail.com" ]
noernova666@gmail.com
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/migrations/versions/061243403ebc_.py
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"""empty message Revision ID: 061243403ebc Revises: Create Date: 2020-02-28 20:57:43.760065 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = '061243403ebc' down_revision = None branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('user_profiles', sa.Column('id', sa.Integer(), nullable=False), sa.Column('first_name', sa.String(length=80), nullable=True), sa.Column('last_name', sa.String(length=80), nullable=True), sa.Column('username', sa.String(length=80), nullable=True), sa.PrimaryKeyConstraint('id'), sa.UniqueConstraint('username') ) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_table('user_profiles') # ### end Alembic commands ###
[ "noreply@github.com" ]
tam876.noreply@github.com
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/Sample.py
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print ("This is the sample GIT code")
[ "jamunamec@gmail.com" ]
jamunamec@gmail.com
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/JTTest/SL7/CMSSW_10_2_15/src/dataRunA/nano200.py
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# Auto generated configuration file # using: # Revision: 1.19 # Source: /local/reps/CMSSW/CMSSW/Configuration/Applications/python/ConfigBuilder.py,v # with command line options: nanoAOD_jetToolbox_cff -s NANO --data --eventcontent NANOAOD --datatier NANOAOD --no_exec --conditions 102X_dataRun2_Sep2018Rereco_v1 --era Run2_2018,run2_nanoAOD_102Xv1 --customise_commands=process.add_(cms.Service('InitRootHandlers', EnableIMT = cms.untracked.bool(False))) --customise JMEAnalysis/JetToolbox/nanoAOD_jetToolbox_cff.nanoJTB_customizeMC --filein /users/h2/rsk146/JTTest/SL7/CMSSW_10_6_12/src/ttbarCutTest/dataReprocessing/0004A5E9-9F18-6B42-B31D-4206406CE423.root --fileout file:jetToolbox_nano_datatest.root import FWCore.ParameterSet.Config as cms from Configuration.StandardSequences.Eras import eras process = cms.Process('NANO',eras.Run2_2018,eras.run2_nanoAOD_102Xv1) # import of standard configurations process.load('Configuration.StandardSequences.Services_cff') process.load('SimGeneral.HepPDTESSource.pythiapdt_cfi') process.load('FWCore.MessageService.MessageLogger_cfi') process.load('Configuration.EventContent.EventContent_cff') process.load('Configuration.StandardSequences.GeometryRecoDB_cff') process.load('Configuration.StandardSequences.MagneticField_AutoFromDBCurrent_cff') process.load('PhysicsTools.NanoAOD.nano_cff') process.load('Configuration.StandardSequences.EndOfProcess_cff') process.load('Configuration.StandardSequences.FrontierConditions_GlobalTag_cff') process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32(-1) ) # Input source process.source = cms.Source("PoolSource", fileNames = cms.untracked.vstring('file:root://cms-xrd-global.cern.ch//store/data/Run2018A/EGamma/MINIAOD/17Sep2018-v2/270000/A2A03ED2-C2C7-D446-B850-478F84233086.root'), secondaryFileNames = cms.untracked.vstring() ) process.options = cms.untracked.PSet( ) # Production Info process.configurationMetadata = cms.untracked.PSet( annotation = cms.untracked.string('nanoAOD_jetToolbox_cff nevts:1'), name = cms.untracked.string('Applications'), version = cms.untracked.string('$Revision: 1.19 $') ) # Output definition process.NANOAODoutput = cms.OutputModule("NanoAODOutputModule", compressionAlgorithm = cms.untracked.string('LZMA'), compressionLevel = cms.untracked.int32(9), dataset = cms.untracked.PSet( dataTier = cms.untracked.string('NANOAOD'), filterName = cms.untracked.string('') ), fileName = cms.untracked.string('file:jetToolbox_nano_datatest200.root'), outputCommands = process.NANOAODEventContent.outputCommands ) # Additional output definition # Other statements from Configuration.AlCa.GlobalTag import GlobalTag process.GlobalTag = GlobalTag(process.GlobalTag, '102X_dataRun2_Sep2018Rereco_v1', '') # Path and EndPath definitions process.nanoAOD_step = cms.Path(process.nanoSequence) process.endjob_step = cms.EndPath(process.endOfProcess) process.NANOAODoutput_step = cms.EndPath(process.NANOAODoutput) # Schedule definition process.schedule = cms.Schedule(process.nanoAOD_step,process.endjob_step,process.NANOAODoutput_step) from PhysicsTools.PatAlgos.tools.helpers import associatePatAlgosToolsTask associatePatAlgosToolsTask(process) # customisation of the process. # Automatic addition of the customisation function from PhysicsTools.NanoAOD.nano_cff from PhysicsTools.NanoAOD.nano_cff import nanoAOD_customizeData #call to customisation function nanoAOD_customizeData imported from PhysicsTools.NanoAOD.nano_cff process = nanoAOD_customizeData(process) # Automatic addition of the customisation function from JMEAnalysis.JetToolbox.nanoAOD_jetToolbox_cff from JMEAnalysis.JetToolbox.nanoAOD_jetToolbox_cff import nanoJTB_customizeMC #call to customisation function nanoJTB_customizeMC imported from JMEAnalysis.JetToolbox.nanoAOD_jetToolbox_cff process = nanoJTB_customizeMC(process) # End of customisation functions # Customisation from command line process.add_(cms.Service('InitRootHandlers', EnableIMT = cms.untracked.bool(False))) # Add early deletion of temporary data products to reduce peak memory need from Configuration.StandardSequences.earlyDeleteSettings_cff import customiseEarlyDelete process = customiseEarlyDelete(process) # End adding early deletion
[ "rsk146@scarletmail.rutgers.edu" ]
rsk146@scarletmail.rutgers.edu
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/verletPygame.py
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Kelloggs/verletPygame
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""" Verlet integration scheme for a deformable object using a mesh-based Mass Spring System. This has just been written to test pygame. Require: numpy, pygame TODO: - add less naive collision handling and response between objects Author: Jens Cornelis """ from numpy import array, linalg, cross, dot import math import pygame import sys import time #globalsb world_size = 1000,700 world_rect = pygame.Rect(0,0, world_size[0], world_size[1]) num_iterations = 10 #iteration for constraint relaxation pickedParticle = None mousePosition = 0,0 frames = 25 drawVelocities = True paused = False class Material: def __init__(self, stiffness=0.3, friction=0.1): self.stiffness = stiffness self.friction = friction class MSSObject: def __init__(self, vertices, indexedSprings, screen, material): self.screen = screen self.particles = [] self.material = material #set up particles for vertex in vertices: self.particles.append(Particle(vertex, screen, self)) self.mass = len(self.particles) #set up springs/constraints self.constraints = [] for spring in indexedSprings: self.constraints.append(Constraint(self.particles[spring[0]], self.particles[spring[1]])) #initial draw self.draw() def setMass(self, mass): self.mass = mass partialMass = mass / float(len(self.particles)) for particle in self.particles: particle.mass = partialMass def get_rect(self): x_min, y_min = world_size[0], world_size[1] x_max, y_max = 0, 0 for particle in self.particles: if particle.x[0] > x_max: x_max = particle.x[0] if particle.x[0] < x_min: x_min = particle.x[0] if particle.x[1] > y_max: y_max = particle.x[1] if particle.x[1] < y_min: y_min = particle.x[1] return pygame.Rect(x_min, y_min, x_max - x_min, y_max - y_min) def update(self): for particle in self.particles: particle.update() def draw(self): for constraint in self.constraints: pos1 = (constraint.p1.x[0], constraint.p1.x[1]) pos2 = (constraint.p2.x[0], constraint.p2.x[1]) pygame.draw.aaline(self.screen, (0,0,255), pos1, pos2) for particle in self.particles: particle.draw() class DeformableSphere(MSSObject): def __init__(self, center, radius, vertices, indexedSprings, screen, material=Material()): MSSObject.__init__(self, vertices, indexedSprings, screen, material) self.radius = radius self.center = center def movePointOut(self, point): direction = point - self.center directionLength = linalg.norm(direction) normalizedDirection = direction/directionLength distMax = 0 for particle in self.particles: tmp = dot(normalizedDirection, particle.x - self.center) if tmp > distMax: distMax = tmp if linalg.norm(direction) < distMax: diff = (self.radius - directionLength)/directionLength return direction*diff else: return (0,0) class DeformableCube(MSSObject): def __init__(self, vertices, indexedSprings, screen, material=Material()): MSSObject.__init__(self, vertices, indexedSprings, screen, material) raise Error("Not yet implemented") def movePointOut(self, point): return (0,0) class Constraint: def __init__(self, p1, p2): self.p1 = p1 self.p2 = p2 self.restlength = linalg.norm(p1.x - p2.x) class Particle: def __init__(self, x, screen, parentObject, mass = 1.0): #set up physical quantities self.x = x self.oldx = x self.force = array([0., 0.]) self.mass = mass self.image = pygame.image.load("sphere.png") self.picked = False self.parentObject = parentObject self.velocity = array([0,0]) #set bounding volume and position self.bv = self.image.get_rect() self.radius = self.bv[2]/2.0 self.bv[0] = self.x[0] - self.radius self.bv[1] = self.x[1] - self.radius #initial drawing self.screen = screen self.draw() def draw(self): self.screen.blit(self.image, self.bv) if drawVelocities: pygame.draw.aaline(self.screen, (255,0,0), self.x, self.x + 0.1*self.velocity) def update(self): self.bv[0] = self.x[0] - self.radius self.bv[1] = self.x[1] - self.radius def computeForces(objects): #add gravitational forces and friction for obj in objects: for particle in obj.particles: particle.force = array([0.0, particle.mass * 9.81 * 100.0]) def computeFriction(objects): for obj in objects: for particle in obj.particles: friction = particle.parentObject.material.friction if not particle.x[0] < (world_size[0] - particle.radius): delta = particle.x[1] - particle.oldx[1] depth = math.fabs(world_size[0] - particle.radius - particle.x[0]) particle.oldx[1] = particle.x[1] - depth*friction*delta if not (particle.x[0] > particle.radius): delta = particle.x[1] - particle.oldx[1] depth = math.fabs(particle.radius - particle.x[0]) particle.oldx[1] = particle.x[1] - depth*friction*delta if not particle.x[1] < (world_size[1] - particle.radius): delta = particle.x[0] - particle.oldx[0] depth = math.fabs(world_size[1] - particle.radius - particle.x[1]) particle.oldx[0] = particle.x[0] - depth*friction*delta if not (particle.x[1] > particle.radius): delta = particle.x[0] - particle.oldx[0] depth = math.fabs(particle.radius - particle.x[1]) particle.oldx[0] = particle.x[0] - depth*friction*delta def verlet(h, objects): for obj in objects: for particle in obj.particles: x = array([particle.x[0], particle.x[1]]) tmp = array([particle.x[0], particle.x[1]]) oldx = particle.oldx a = particle.force / particle.mass particle.x += x - oldx + a*h*h #compute velocity as central difference of positions particle.velocity = (particle.x - particle.oldx)/(2.0*h) particle.oldx = tmp def satisfyConstraints(objects): for val in range(num_iterations): for obj in objects: #check and solve world collisions for particle in obj.particles: particle.x[0] = min(max(particle.x[0], particle.radius), world_size[0] - particle.radius) particle.x[1] = min(max(particle.x[1], particle.radius), world_size[1] - particle.radius) #solve constraints deformable object for constraint in obj.constraints: p1 = constraint.p1 p2 = constraint.p2 delta = p2.x - p1.x deltalength = linalg.norm(delta) diff = (deltalength - constraint.restlength)/deltalength #make material stiffness linear to solver iterations and apply to #particle positions k = 1 - (1 - obj.material.stiffness)**(1.0/float(num_iterations)) p1.x += delta*0.5*diff*k p2.x -= delta*0.5*diff*k #constraint for picked particle to act on mouse action if pickedParticle: delta = pickedParticle.x - mousePosition deltalength = linalg.norm(delta) if deltalength > 0: diff = (0 - deltalength)/deltalength pickedParticle.x += delta*diff for particle in obj.particles: for obj2 in objects: if obj == obj2: continue else: if obj2.get_rect().collidepoint(particle.x): particle.x += obj2.movePointOut(particle.x) def create2DBall(screen, center, radius, particles, material): '''Convenience method to generate a ball mesh''' p = [] p.append(center) for val in range(particles): angle = val * 360./particles tmp_x = center[0] + radius*math.cos((angle*math.pi)/180.) tmp_y = center[1] + radius*math.sin((angle*math.pi)/180.) p.append(array([tmp_x, tmp_y])) c = [] for val in range(1, len(p) - 1): c.append((val, val + 1)) c.append((0, val)) c.append((1, len(p) - 1)) c.append((0, len(p) - 1)) return DeformableSphere(center, radius, p, c, screen, material) def create2DCube(screen, rect, material): p = [] p.append(array([rect[0], rect[1]])) p.append(array([rect[0], rect[1] + rect[3]])) p.append(array([rect[0] + rect[2], rect[1]])) p.append(array([rect[0] + rect[2], rect[1] + rect[3]])) c = (0,1), (1,2), (2,3), (3, 0), (0,2), (1,3) return DeformableCube(p, c, screen, material) def main(): global pickedParticle, mousePosition, mouseClickPosition, paused #initialization of pygame and window pygame.init() screen = pygame.display.set_mode(world_size) #setting up objects objects = [] mat1 = Material(0.9) mat2 = Material(0.6) sphere = create2DBall(screen, array([300., 300.]), 100., 8, mat2) objects.append(sphere) # sphere2 = create2DBall(screen, array([100., 100.]), 80., 7, mat1) # objects.append(sphere2) clock = pygame.time.Clock() #main simulation loop while True: #set clock of pygame to predefined frames for equal timesteps clock.tick(frames) for event in pygame.event.get(): #stop the program if user wants us to if event.type == pygame.QUIT: sys.exit() #flag particle as picked if user clicked on it if event.type == pygame.MOUSEBUTTONDOWN: for obj in objects: for particle in obj.particles: if particle.bv.collidepoint(event.pos): particle.picked = True pickedParticle = particle if event.type == pygame.MOUSEMOTION: mousePosition = event.pos if event.type == pygame.MOUSEBUTTONUP: if pickedParticle: pickedParticle.picked = False pickedParticle = None if event.type == pygame.KEYDOWN: if event.key == pygame.K_p: paused = not paused if event.key == pygame.K_s: pygame.image.save(screen, "screenshot" + str(time.time()) + ".jpg") if paused: continue #clear screen with background color screen.fill((255,255,255)) #compute external forces computeForces(objects) computeFriction(objects) #compute timestep according to frame set py pygame.clock h=frames/1000. #do integration step and satisfy constraints verlet(h, objects) satisfyConstraints(objects) #update and draw particles for obj in objects: obj.update() obj.draw() #make everything visible pygame.display.flip() ######################################### if __name__ == '__main__': main() #########################################
[ "mail@jenscornelis.de" ]
mail@jenscornelis.de
161c51566a4e0d910527636a2197e923a1518102
84239d0809dca1c88a33d42e1cda225ae5512f0f
/models/models_3_2.py
dbb8dd0b87933e755fa9ddfed094e529d0f03ca4
[]
no_license
siebeniris/Understanding-NN
92e2e9662d9d56e2946dec151d9d8f13bb3ae776
a6d1553aea8e137827a7b909461664c87f1db238
refs/heads/master
2021-05-10T22:43:29.609052
2018-01-20T06:05:20
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from tensorflow.python.ops import nn_ops, gen_nn_ops import tensorflow as tf class MNIST_CNN: def __init__(self, name): self.name = name def __call__(self, X, reuse=False): with tf.variable_scope(self.name) as scope: if reuse: scope.reuse_variables() with tf.variable_scope('layer0'): X_img = tf.reshape(X, [-1, 28, 28, 1]) # Convolutional Layer #1 and Pooling Layer #1 with tf.variable_scope('layer1'): conv1 = tf.layers.conv2d(inputs=X_img, filters=32, kernel_size=[3, 3], padding="SAME", activation=tf.nn.relu, use_bias=False) pool1 = tf.layers.max_pooling2d(inputs=conv1, pool_size=[2, 2], padding="SAME", strides=2) # Convolutional Layer #2 and Pooling Layer #2 with tf.variable_scope('layer2'): conv2 = tf.layers.conv2d(inputs=pool1, filters=64, kernel_size=[3, 3], padding="SAME", activation=tf.nn.relu, use_bias=False) pool2 = tf.layers.max_pooling2d(inputs=conv2, pool_size=[2, 2], padding="SAME", strides=2) # Convolutional Layer #3 and Pooling Layer #3 with tf.variable_scope('layer3'): conv3 = tf.layers.conv2d(inputs=pool2, filters=128, kernel_size=[3, 3], padding="SAME", activation=tf.nn.relu, use_bias=False) pool3 = tf.layers.max_pooling2d(inputs=conv3, pool_size=[2, 2], padding="SAME", strides=2) # Dense Layer with Relu with tf.variable_scope('layer4'): flat = tf.reshape(pool3, [-1, 128 * 4 * 4]) dense4 = tf.layers.dense(inputs=flat, units=625, activation=tf.nn.relu, use_bias=False) # Logits (no activation) Layer: L5 Final FC 625 inputs -> 10 outputs with tf.variable_scope('layer5'): logits = tf.layers.dense(inputs=dense4, units=10, use_bias=False) prediction = tf.nn.softmax(logits) return [X_img, conv1, pool1, conv2, pool2, conv3, pool3, flat, dense4, prediction], logits @property def vars(self): return tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=self.name) class Taylor: def __init__(self, activations, weights, conv_ksize, pool_ksize, conv_strides, pool_strides, name): self.last_ind = len(activations) for op in activations: self.last_ind -= 1 if any([word in op.name for word in ['conv', 'pooling', 'dense']]): break self.activations = activations self.activations.reverse() self.weights = weights self.weights.reverse() self.conv_ksize = conv_ksize self.pool_ksize = pool_ksize self.conv_strides = conv_strides self.pool_strides = pool_strides self.name = name def __call__(self, logit): with tf.name_scope(self.name): Rs = [] j = 0 for i in range(len(self.activations) - 1): if i is self.last_ind: if 'conv' in self.activations[i].name.lower(): Rs.append(self.backprop_conv_input(self.activations[i + 1], self.weights[j], Rs[-1], self.conv_strides)) else: Rs.append(self.backprop_dense_input(self.activations[i + 1], self.weights[j], Rs[-1])) continue if i is 0: Rs.append(self.activations[i][:,logit,None]) Rs.append(self.backprop_dense(self.activations[i + 1], self.weights[j][:,logit,None], Rs[-1])) j += 1 continue elif 'dense' in self.activations[i].name.lower(): Rs.append(self.backprop_dense(self.activations[i + 1], self.weights[j], Rs[-1])) j += 1 elif 'reshape' in self.activations[i].name.lower(): shape = self.activations[i + 1].get_shape().as_list() shape[0] = -1 Rs.append(tf.reshape(Rs[-1], shape)) elif 'conv' in self.activations[i].name.lower(): Rs.append(self.backprop_conv(self.activations[i + 1], self.weights[j], Rs[-1], self.conv_strides)) j += 1 elif 'pooling' in self.activations[i].name.lower(): # Apply average pooling backprop regardless of type of pooling layer used, following recommendations by Montavon et al. # Uncomment code below if you want to apply the winner-take-all redistribution policy suggested by Bach et al. # # if 'max' in self.activations[i].name.lower(): # pooling_type = 'max' # else: # pooling_type = 'avg' # Rs.append(self.backprop_pool(self.activations[i + 1], Rs[-1], self.pool_ksize, self.pool_strides, pooling_type)) Rs.append(self.backprop_pool(self.activations[i + 1], Rs[-1], self.pool_ksize, self.pool_strides, 'avg')) else: raise Error('Unknown operation.') return Rs[-1] def backprop_conv(self, activation, kernel, relevance, strides, padding='SAME'): W_p = tf.maximum(0., kernel) z = nn_ops.conv2d(activation, W_p, strides, padding) + 1e-10 s = relevance / z c = nn_ops.conv2d_backprop_input(tf.shape(activation), W_p, s, strides, padding) return activation * c def backprop_pool(self, activation, relevance, ksize, strides, pooling_type, padding='SAME'): if pooling_type.lower() in 'avg': z = nn_ops.avg_pool(activation, ksize, strides, padding) + 1e-10 s = relevance / z c = gen_nn_ops._avg_pool_grad(tf.shape(activation), s, ksize, strides, padding) return activation * c else: z = nn_ops.max_pool(activation, ksize, strides, padding) + 1e-10 s = relevance / z c = gen_nn_ops._max_pool_grad(activation, z, s, ksize, strides, padding) return activation * c def backprop_dense(self, activation, kernel, relevance): W_p = tf.maximum(0., kernel) z = tf.matmul(activation, W_p) + 1e-10 s = relevance / z c = tf.matmul(s, tf.transpose(W_p)) return activation * c def backprop_conv_input(self, X, kernel, relevance, strides, padding='SAME', lowest=0., highest=1.): W_p = tf.maximum(0., kernel) W_n = tf.minimum(0., kernel) L = tf.ones_like(X, tf.float32) * lowest H = tf.ones_like(X, tf.float32) * highest z_o = nn_ops.conv2d(X, kernel, strides, padding) z_p = nn_ops.conv2d(L, W_p, strides, padding) z_n = nn_ops.conv2d(H, W_n, strides, padding) z = z_o - z_p - z_n + 1e-10 s = relevance / z c_o = nn_ops.conv2d_backprop_input(tf.shape(X), kernel, s, strides, padding) c_p = nn_ops.conv2d_backprop_input(tf.shape(X), W_p, s, strides, padding) c_n = nn_ops.conv2d_backprop_input(tf.shape(X), W_n, s, strides, padding) return X * c_o - L * c_p - H * c_n def backprop_dense_input(self, X, kernel, relevance, lowest=0., highest=1.): W_p = tf.maximum(0., kernel) W_n = tf.minimum(0., kernel) L = tf.ones_like(X, tf.float32) * lowest H = tf.ones_like(X, tf.float32) * highest z_o = tf.matmul(X, kernel) z_p = tf.matmul(L, W_p) z_n = tf.matmul(H, W_n) z = z_o - z_p - z_n + 1e-10 s = relevance / z c_o = tf.matmul(s, tf.transpose(kernel)) c_p = tf.matmul(s, tf.transpose(W_p)) c_n = tf.matmul(s, tf.transpose(W_n)) return X * c_o - L * c_p - H * c_n
[ "1202kbs@gmail.com" ]
1202kbs@gmail.com
1d13b98d948da4230d205362cbabd0696af80cf6
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/argparse/5_conflicting_options.py
55541fc040e8ba860bdcc2e766342e231fbcbf87
[]
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51802bf354c36049f41f539778f576d7e9560305
4a1bb17c08204edf6954196c29f6e40a88274ef6
refs/heads/master
2023-05-31T21:15:37.770161
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""" Letโ€™s introduce a third one, add_mutually_exclusive_group(). It allows for us to specify options that conflict with each other. Letโ€™s also change the rest of the program so that the new functionality makes more sense: weโ€™ll introduce the --quiet option, which will be the opposite of the --verbose one: """ import argparse parser = argparse.ArgumentParser(description="calculate X to the power of Y") group = parser.add_mutually_exclusive_group() group.add_argument("-v", "--verbose", action="store_true") group.add_argument("-q", "--quiet", action="store_true") parser.add_argument("x", type=int, help="the base") parser.add_argument("y", type=int, help="the exponent") args = parser.parse_args() answer = args.x ** args.y print("Running '{}'".format(__file__)) if args.quiet: print(answer) elif args.verbose: print("{} to the power {} equals {}".format(args.x, args.y, answer)) else: print("{}^{} == {}".format(args.x, args.y, answer))
[ "junseok.kim@greenventory.de" ]
junseok.kim@greenventory.de
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Sravanthi-Gogadi/PythonDeeplearningCourse
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from bs4 import BeautifulSoup import urllib.request import pandas as pd import csv # using tabulate to display the pandas dataframe from tabulate import tabulate # Read the web url into a variable url = "https://en.wikipedia.org/wiki/List_of_state_and_union_territory_capitals_in_India" # use urllib to open the url res = urllib.request.urlopen(url) plain_text = res # Use beautiful soup to get the content of webpage soup = BeautifulSoup(plain_text, "html.parser") # Print the title of the web page print(soup.find('title').string) # Print all the anchor tags in the webpage result_list = soup.findAll('a') # Print the text of href for i in result_list: link = i.get('href') print(link) # Read the table from webpage result_table = soup.findAll('table', {'class': 'wikitable sortable plainrowheaders'}) for tr in result_table: table_data = tr.findAll('td') table_head = tr.findAll('th') # Print td and th print(table_data, table_head) # To display the list of union territories table = soup.find_all('table')[1] # using pandas object read the table and assign header df = pd.read_html(str(table),header=0) # display the output print( tabulate(df[0], headers='keys', tablefmt='psql') )
[ "sravanthigogadi@gmail.com" ]
sravanthigogadi@gmail.com
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/solutions_python/Problem_155/791.py
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dr-dos-ok/Code_Jam_Webscraper
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__author__ = 'rrampage' t = int(input()) def input_format(): s = input().split()[1] return [int(i) for i in s] def ovation(aud): extras = 0 tot_standing = 0 for i, a in enumerate(aud): if a == 0: continue if tot_standing >= i: tot_standing += a else: extras += (i - tot_standing) tot_standing += (i - tot_standing) tot_standing += a return extras for x in range(t): print("Case #%d: %d" % (x+1, ovation(input_format())))
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miliar1732@gmail.com
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/Scrapy/DouyuPicture/DouyuPicture/settings.py
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haochen95/python_tutorial
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2020-04-18T03:26:19.331623
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# -*- coding: utf-8 -*- # Scrapy settings for DouyuPicture project # # For simplicity, this file contains only settings considered important or # commonly used. You can find more settings consulting the documentation: # # https://doc.scrapy.org/en/latest/topics/settings.html # https://doc.scrapy.org/en/latest/topics/downloader-middleware.html # https://doc.scrapy.org/en/latest/topics/spider-middleware.html BOT_NAME = 'DouyuPicture' SPIDER_MODULES = ['DouyuPicture.spiders'] NEWSPIDER_MODULE = 'DouyuPicture.spiders' # Crawl responsibly by identifying yourself (and your website) on the user-agent #USER_AGENT = 'DouyuPicture (+http://www.yourdomain.com)' # Obey robots.txt rules ROBOTSTXT_OBEY = True # Configure maximum concurrent requests performed by Scrapy (default: 16) #CONCURRENT_REQUESTS = 32 # Configure a delay for requests for the same website (default: 0) # See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs #DOWNLOAD_DELAY = 3 # The download delay setting will honor only one of: #CONCURRENT_REQUESTS_PER_DOMAIN = 16 #CONCURRENT_REQUESTS_PER_IP = 16 # Disable cookies (enabled by default) #COOKIES_ENABLED = False # Disable Telnet Console (enabled by default) #TELNETCONSOLE_ENABLED = False # Override the default request headers: DEFAULT_REQUEST_HEADERS = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98', # 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', # 'Accept-Language': 'en', } # Enable or disable spider middlewares # See https://doc.scrapy.org/en/latest/topics/spider-middleware.html # SPIDER_MIDDLEWARES = { # 'DouyuPicture.middlewares.DouyupictureSpiderMiddleware': 543, # } IMAGE_STORE = "C:/Users/haoch/Desktop/Programming/Python/Scrapy_project01/Image/" # Enable or disable downloader middlewares # See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html #DOWNLOADER_MIDDLEWARES = { # 'DouyuPicture.middlewares.DouyupictureDownloaderMiddleware': 543, #} # Enable or disable extensions # See https://doc.scrapy.org/en/latest/topics/extensions.html #EXTENSIONS = { # 'scrapy.extensions.telnet.TelnetConsole': None, #} # Configure item pipelines # See https://doc.scrapy.org/en/latest/topics/item-pipeline.html ITEM_PIPELINES = { 'DouyuPicture.pipelines.DouyupicturePipeline': 300, } # Enable and configure the AutoThrottle extension (disabled by default) # See https://doc.scrapy.org/en/latest/topics/autothrottle.html #AUTOTHROTTLE_ENABLED = True # The initial download delay #AUTOTHROTTLE_START_DELAY = 5 # The maximum download delay to be set in case of high latencies #AUTOTHROTTLE_MAX_DELAY = 60 # The average number of requests Scrapy should be sending in parallel to # each remote server #AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 # Enable showing throttling stats for every response received: #AUTOTHROTTLE_DEBUG = False # Enable and configure HTTP caching (disabled by default) # See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings #HTTPCACHE_ENABLED = True #HTTPCACHE_EXPIRATION_SECS = 0 #HTTPCACHE_DIR = 'httpcache' #HTTPCACHE_IGNORE_HTTP_CODES = [] #HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
[ "haochen273@gmail.com" ]
haochen273@gmail.com
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import numpy as np ''' In mathematics, Chebyshev distance (or Tchebychev distance), maximum metric, or Lโˆž metric is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.[2] It is named after Pafnuty Chebyshev. It is also known as chessboard distance, since in the game of chess the minimum number of moves needed by a king to go from one square on a chessboard to another equals the Chebyshev distance between the centers of the squares, if the squares have side length one, as represented in 2-D spatial coordinates with axes aligned to the edges of the board. ''' objA = [22, 1, 42, 10] objB = [20, 0, 36, 8] npA = np.array(objA) npB = np.array(objB) chebyshev = np.abs(npA - npB).max() # chebyshev = np.linalg.norm(npA -npB, ord=np.inf) print(chebyshev)
[ "mangelladen@gmail.com" ]
mangelladen@gmail.com
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import math import re #Define exceptions class RomanError(Exception): pass class OutOfRangeError(RomanError): pass class NotIntegerError(RomanError): pass class InvalidRomanNumeralError(RomanError): pass #Define digit mapping romanNumeralMap = (('M', 1000), ('CM', 900), ('D', 500), ('CD', 400), ('C', 100), ('XC', 90), ('L', 50), ('XL', 40), ('X', 10), ('IX', 9), ('V', 5), ('IV', 4), ('I', 1)) def toRoman(n): """convert integer to Roman numeral""" if not (0 < n < 5000): raise OutOfRangeError, "number out of range (must be 1..4999)" if int(n) != n: raise NotIntegerError, "decimals can not be converted" result = "" for numeral, integer in romanNumeralMap: while n >= integer: result += numeral n -= integer return result #Define pattern to detect valid Roman numerals romanNumeralPattern = re.compile(""" ^ # beginning of string M{0,4} # thousands - 0 to 4 M's (CM|CD|D?C{0,3}) # hundreds - 900 (CM), 400 (CD), 0-300 (0 to 3 C's), # or 500-800 (D, followed by 0 to 3 C's) (XC|XL|L?X{0,3}) # tens - 90 (XC), 40 (XL), 0-30 (0 to 3 X's), # or 50-80 (L, followed by 0 to 3 X's) (IX|IV|V?I{0,3}) # ones - 9 (IX), 4 (IV), 0-3 (0 to 3 I's), # or 5-8 (V, followed by 0 to 3 I's) $ # end of string """ ,re.VERBOSE) def fromRoman(s): """convert Roman numeral to integer""" if not s: raise InvalidRomanNumeralError, 'Input can not be blank' if not romanNumeralPattern.search(s): raise InvalidRomanNumeralError, 'Invalid Roman numeral: %s' % s result = 0 index = 0 for numeral, integer in romanNumeralMap: while s[index:index+len(numeral)] == numeral: result += integer index += len(numeral) return result def int_to_roman(input): """ Convert an integer to Roman numerals. Examples: >>> int_to_roman(0) Traceback (most recent call last): ValueError: Argument must be between 1 and 3999 >>> int_to_roman(-1) Traceback (most recent call last): ValueError: Argument must be between 1 and 3999 >>> int_to_roman(1.5) Traceback (most recent call last): TypeError: expected integer, got <type 'float'> >>> for i in range(1, 21): print int_to_roman(i) ... I II III IV V VI VII VIII IX X XI XII XIII XIV XV XVI XVII XVIII XIX XX >>> print int_to_roman(2000) MM >>> print int_to_roman(1999) MCMXCIX """ if type(input) != type(1): raise TypeError, "expected integer, got %s" % type(input) ints = (1000, 900, 500, 400, 100, 90, 50, 40, 10, 9, 5, 4, 1) nums = ('M', 'CM', 'D', 'CD','C', 'XC','L','XL','X','IX','V','IV','I') result = "" for i in range(len(ints)): count = int(input / ints[i]) result += nums[i] * count input -= ints[i] * count return result def number(char): if char=='M': return 1000 elif char=='D': return 500 elif char=='C': return 100 elif char=='L': return 50 elif char=='X': return 10 elif char=='V': return 5 elif char=='I': return 1 else: return 'error' def romanToNumber(s): sum=0 previous=10**7 for char in s: if previous<number(char): sum+=number(char)-2*previous previous=number(char) else: sum+=number(char) previous=number(char) return sum print romanToNumber('MMMMCCCXIV') print romanToNumber('MMDCCLXIX') print romanToNumber('CMLXXXVII') print toRoman(romanToNumber('MMMMCCCLXXXXVII')) lines = [line.strip() for line in open('roman.txt')] print lines sum=0 for s in lines: sum+=len(s)-len(toRoman(romanToNumber(s))) print sum
[ "spirosrap@gmail.com" ]
spirosrap@gmail.com
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/Python/String/266. ๅ›žๆ–‡ๆŽ’ๅˆ—.py
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[]
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Leahxuliu/Data-Structure-And-Algorithm
04e0fc80cd3bb742348fd521a62bc2126879a70e
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''' ๅฅ‡ๆ•ฐไธช็š„charๆœ€ๅคšๅช่ƒฝๆœ‰ไธ€ไธช ''' from collections import defaultdict class Solution: def canPermutePalindrome(self, s: str) -> bool: if s == '': return True info = defaultdict(int) for i in s: info[i] += 1 count = 0 for v in info.values(): if v % 2 == 1: count += 1 if count >= 2: return False return True
[ "leahxuliu@gmail.com" ]
leahxuliu@gmail.com
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/examples/ex_pyside.py
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from idaapi import PluginForm from PySide import QtGui, QtCore class MyPluginFormClass(PluginForm): def OnCreate(self, form): """ Called when the plugin form is created """ # Get parent widget self.parent = self.FormToPySideWidget(form) self.PopulateForm() def PopulateForm(self): # Create layout layout = QtGui.QVBoxLayout() layout.addWidget( QtGui.QLabel("Hello from <font color=red>PySide</font>")) layout.addWidget( QtGui.QLabel("Hello from <font color=blue>IDAPython</font>")) self.parent.setLayout(layout) def OnClose(self, form): """ Called when the plugin form is closed """ pass plg = MyPluginFormClass() plg.Show("PySide hello world")
[ "elias.bachaalany@fccdda4b-c33c-0410-84de-61e1e3e5f415" ]
elias.bachaalany@fccdda4b-c33c-0410-84de-61e1e3e5f415
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/Porthole_Detection/Data_to_Image.py
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[]
no_license
MLJejuCamp2017/Pothole_Detection_using_CNN
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# ํŒŒ์ผ ํ•˜๋‚˜๋งŒ ๋ฐ”๊ฟ”์คŒ ''' import numpy as np from scipy.misc import toimage x = np.loadtxt("/Users/User/PycharmProjects/network/ML_Camp/Porthole_Detection/all.csv", delimiter=',') # toimage(x).show() toimage(x).save('all(grayscale).jpg') ''' ''' # ๋””๋ ‰ํ† ๋ฆฌ ๋‚ด์˜ ํŒŒ์ผ๋“ค์„ ํ•œ๋ฒˆ์— ์ผ๊ด„ ๋ณ€ํ™˜ ์™€ ๊ฐœ์ฉ๋‹ค ๋‚œ ๋…ธ๊ฐ€๋‹คํ–ˆ๋Š”๋ฐ ใ……ใ…‚ ์ง„์ž‘์— ํ• ๊ฑธ import os import numpy as np from scipy.misc import toimage path = "/Users/User/OneDrive/์„ผ์„œ๋กœ๊ทธ/์ž์ „๊ฑฐ/ํฌํŠธํ™€/csv/๋‹ค๋“ฌ๋‹ค๋“ฌ/" dirs = os.listdir(path) def convert(): for item in dirs: if os.path.isfile(path+item): print(path+item) x = np.loadtxt(path+item, delimiter=',') f, e = os.path.splitext(path+item) toimage(x).save(f + '.jpg') convert() ''' # ์ŠคํŽ™ํŠธ๋Ÿผ ์ด๋ฏธ์ง€๋กœ ์ผ๊ด„ ๋ณ€ํ™˜ # ''' import matplotlib.pyplot as plt import stft import os import numpy as np path = "/Users/User/OneDrive/์„ผ์„œ๋กœ๊ทธ/์ž์ „๊ฑฐ/ํฌํŠธํ™€/csv/๋‹ค๋“ฌ๋‹ค๋“ฌ/" dirs = os.listdir(path) def convert(): for item in dirs: if os.path.isfile(path+item): print(path+item) x = np.loadtxt(path+item, delimiter=',', unpack=True, dtype='float32') f, e = os.path.splitext(path+item) z_data = np.transpose(x[2]) # specgram_z = stft.spectrogram(z_data) specgram_z = stft.spectrogram(z_data, window=0.4) plt._imsave(f + '.jpg', abs(specgram_z), vmin=-40, vmax=40, cmap=plt.get_cmap('coolwarm'), format='jpg') # gray Wistia convert() # ''' # ํŒŒ์ผ ํ•˜๋‚˜๋งŒ ์ŠคํŽ™ํŠธ๋Ÿผ ์ด๋ฏธ์ง€๋กœ ๋ฐ”๊ฟ”์คŒ ''' import matplotlib.pyplot as plt import stft import numpy as np x = np.loadtxt("/Users/User/PycharmProjects/network/ML_Camp/Porthole_Detection/all.csv", delimiter=',', unpack=True) # toimage(x).show() z_data = np.transpose(x[2]) specgram_z = stft.spectrogram(z_data, window=0.4) plt._imsave('all(test).jpg', abs(specgram_z), vmin=-40, vmax=40, cmap=plt.get_cmap('coolwarm'), format='jpg') # '''
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chzhqk1994@gmail.com
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/likes/templatetags/likes_tags.py
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dyr201500800475/web_novels
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from django import template from django.contrib.contenttypes.models import ContentType from ..models import LikeCount, LikeRecord register = template.Library() # ่Žทๅ–็‚น่ตžๆ•ฐ @register.simple_tag def get_like_count(obj): content_type = ContentType.objects.get_for_model(obj) like_count, created = LikeCount.objects.get_or_create(content_type=content_type, object_id=obj.pk) return like_count.liked_num # ่Žทๅ–็‚น่ตž็Šถๆ€ @register.simple_tag(takes_context=True) def get_like_status(context, obj): content_type = ContentType.objects.get_for_model(obj) user=context['user'] if not user.is_authenticated: return '' if LikeRecord.objects.filter(content_type=content_type, object_id=obj.pk, user=user).exists(): return 'active' else: return '' # ่Žทๅ–็‚น่ตžๅฏน่ฑก็š„็ฑปๅž‹ @register.simple_tag def get_content_type(obj): content_type = ContentType.objects.get_for_model(obj) return content_type.model
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/src/python/codechef/JAN19B/DPAIRS.py
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N, M = input().split(" ") N = int(N) M = int(M) A = input().split(" ") A = [int(elem) for elem in A] B = input().split(" ") B = [int(elem) for elem in B] A_sorted = [i[0] for i in sorted(enumerate(A), key=lambda x: x[1])] B_sorted = [i[0] for i in sorted(enumerate(B), key=lambda x: x[1])] A_i = 0 B_i = 0 As_turn = True # print(A_sorted) # print(B_sorted) while len(A_sorted) > A_i and len(B_sorted) > B_i: print("%s %s" % (A_sorted[A_i], B_sorted[B_i])) if As_turn: # print("As_turn") As_turn = False A_i += 1 else: # print("Bs_turn") As_turn = True B_i += 1
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pulkitsingh01@gmail.com