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

e54416140692cc6de81bef6a7723085a7570ffe0

9b29c9fffd33489a35225b256d148f1a6146137b

/Server/StartAppium.py

1d03d6ae9dfaadb81966adff4b31f36bdb966eba

[]

no_license

fghad1991/companion

748bb9fa0753d4bdcc1cd9f53ec21a56b7ef2aa3

8a836531f15400eb392f12c85d5cdfaad02f1db9

refs/heads/master

2020-12-30T14:20:40.653720

2017-05-15T08:30:53

91,313,711

0

null

UTF-8

Python

false

610

py

__author__ = 'JJLanMo' class appium(): def start(self,host,port,bootstrap_port,session_override): errormsg = "" appium_server_url = "" appium_log_path = "" # appium - a 127.0.0.1 - p4726 - -bootstrap - port 4780 - -session - override - -log "E:/appium" - -command - timeout 600 if self.port_is_free(host,port): cmd = 'start /b appium -a ' + host + ' -p ' + str(port) + ' --bootstrap-port ' + str( bootstrap_port) + ' --session-override --log ' + '"' + appium_log_path + '" --command-timeout 600' else: print ("a")(port)

[ "13564733570@163.com" ]

13564733570@163.com

61c54a8826e2a96a5e82ca3db7fd51286bf2f868

2222fa632138465c237e0d501a17e78bd41c4fca

/predict.py

6158b5f1f965669746d8b42bfa9fd8b2aff23e9a

[]

no_license

minji9583/ai_chatbot_project

e3d1936091650150090c642fcda335c4a5583e3a

dafdf565bddb0841d5dc38dfb85a1b41310b87c8

refs/heads/master

2023-01-06T17:32:54.982468

2019-10-15T02:20:37

207,702,203

4

1

null

2023-01-01T13:24:51

2019-09-11T02:08:05

Python

UTF-8

Python

false

5,403

py

import tensorflow as tf import data import sys import model as ml from configs import DEFINES def eval(): char2idx, idx2char, vocabulary_length = data.load_voc() train_input, train_label, eval_input, eval_label = data.load_data() # 평가셋 인코딩 만드는 부분이다. eval_input_enc, eval_input_enc_length = data.enc_processing(eval_input, char2idx) # 평가셋 디코딩 출력 부분 만드는 부분이다. eval_target_dec, _ = data.dec_target_processing(eval_label, char2idx) classifier = tf.estimator.Estimator( model_fn=ml.Model, # 모델 등록한다. model_dir=DEFINES.check_point_path, # 체크포인트 위치 등록한다. params={ # 모델 쪽으로 파라메터 전달한다. 'hidden_size': DEFINES.hidden_size, # 가중치 크기 설정한다. 'layer_size': DEFINES.layer_size, # 멀티 레이어 층 개수를 설정한다. 'learning_rate': DEFINES.learning_rate, # 학습율 설정한다. 'teacher_forcing_rate': DEFINES.teacher_forcing_rate, # 학습시 디코더 인풋 정답 지원율 설정 'vocabulary_length': vocabulary_length, # 딕셔너리 크기를 설정한다. 'embedding_size': DEFINES.embedding_size, # 임베딩 크기를 설정한다. 'embedding': DEFINES.embedding, # 임베딩 사용 유무를 설정한다. 'multilayer': DEFINES.multilayer, # 멀티 레이어 사용 유무를 설정한다. 'attention': DEFINES.attention, # 어텐션 지원 유무를 설정한다. 'teacher_forcing': DEFINES.teacher_forcing, # 학습시 디코더 인풋 정답 지원 유무 설정한다. 'loss_mask': DEFINES.loss_mask, # PAD에 대한 마스크를 통한 loss를 제한 한다. 'serving': DEFINES.serving # 모델 저장 및 serving 유무를 설정한다. }) eval_result = classifier.evaluate(input_fn=lambda: data.eval_input_fn( eval_input_enc, eval_target_dec, DEFINES.batch_size)) print('\ntest set 정확도: {accuracy:0.3f}\n'.format(**eval_result)) def predict(input_data): # 데이터를 통한 사전 구성 한다. char2idx, idx2char, vocabulary_length = data.load_voc() # 테스트용 데이터 만드는 부분이다. # 인코딩 부분 만든다. input = input_data predic_input_enc, predic_input_enc_length = data.enc_processing([input], char2idx) # 학습 과정이 아니므로 디코딩 입력은 # 존재하지 않는다.(구조를 맞추기 위해 넣는다.) # 학습 과정이 아니므로 디코딩 출력 부분도 # 존재하지 않는다.(구조를 맞추기 위해 넣는다.) predic_target_dec, _ = data.dec_target_processing([""], char2idx) if DEFINES.serving == True: # 모델이 저장된 위치를 넣어 준다. export_dir predictor_fn = tf.contrib.predictor.from_saved_model( export_dir="/home/evo_mind/DeepLearning/NLP/Work/ChatBot2_Final/data_out/model/1541575161" ) else: # 에스티메이터 구성한다. classifier = tf.estimator.Estimator( model_fn=ml.Model, # 모델 등록한다. model_dir=DEFINES.check_point_path, # 체크포인트 위치 등록한다. params={ # 모델 쪽으로 파라메터 전달한다. 'hidden_size': DEFINES.hidden_size, # 가중치 크기 설정한다. 'layer_size': DEFINES.layer_size, # 멀티 레이어 층 개수를 설정한다. 'learning_rate': DEFINES.learning_rate, # 학습율 설정한다. 'teacher_forcing_rate': DEFINES.teacher_forcing_rate, # 학습시 디코더 인풋 정답 지원율 설정 'vocabulary_length': vocabulary_length, # 딕셔너리 크기를 설정한다. 'embedding_size': DEFINES.embedding_size, # 임베딩 크기를 설정한다. 'embedding': DEFINES.embedding, # 임베딩 사용 유무를 설정한다. 'multilayer': DEFINES.multilayer, # 멀티 레이어 사용 유무를 설정한다. 'attention': DEFINES.attention, # 어텐션 지원 유무를 설정한다. 'teacher_forcing': DEFINES.teacher_forcing, # 학습시 디코더 인풋 정답 지원 유무 설정한다. 'loss_mask': DEFINES.loss_mask, # PAD에 대한 마스크를 통한 loss를 제한 한다. 'serving': DEFINES.serving # 모델 저장 및 serving 유무를 설정한다. }) if DEFINES.serving == True: predictions = predictor_fn({'input': predic_input_enc, 'output': predic_target_dec}) # data.pred2string(predictions, idx2char) else: # 예측을 하는 부분이다. predictions = classifier.predict( input_fn=lambda: data.eval_input_fn(predic_input_enc, predic_target_dec, DEFINES.batch_size)) # 예측한 값을 인지 할 수 있도록 # 텍스트로 변경하는 부분이다. # data.pred2string(predictions, idx2char) return data.pred_next_string(predictions, idx2char) def main(self): char2idx, idx2char, vocabulary_length = data.load_voc() print(predict("졸려")) eval() if __name__ == '__main__': tf.logging.set_verbosity(tf.logging.INFO) tf.app.run(main) tf.logging.set_verbosity

[ "gpfhddl09@gmail.com" ]

gpfhddl09@gmail.com

d4c173c2e18b79464f26d50aed0cb587a711543d

20e7921251e81518fccb87a583d0a0c8c284d539

/orayeb/asgi.py

db1930dd39872542af7b6425ca6c5dbba490fe2b

[]

no_license

ysawiris/orayeb

fd2c88c39807d378178f2db7ac0626e3ed38b9d5

ba24bfc74f34edf0f9d7d553d39723ab32a6b21f

refs/heads/main

2023-02-23T14:41:29.949013

2021-01-12T23:24:57

329,027,461

0

null

UTF-8

Python

false

389

py

""" ASGI config for orayeb project. It exposes the ASGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/asgi/ """ import os from django.core.asgi import get_asgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'orayeb.settings') application = get_asgi_application()

[ "youssef.sawiris@students.dominican.edu" ]

youssef.sawiris@students.dominican.edu

1f4c69f1e02e3cd6bc5a0a58287d130163386f84

ad1e55b9a67c798cf4b4ce41c76b26977f8b4e8d

/vendor-local/celery/tests/test_events/test_events_state.py

b8817f5a83f3398df59f2048f1e18115062a33b1

[ "BSD-3-Clause" ]

permissive

kumar303/rockit

7a6ac84bb8c37e5f3b65d7dcecf9b9c549902cf5

fc347b5b143835ddd77fd0c1ea4e6f2007a21972

refs/heads/master

2021-01-10T19:51:30.638073

2020-07-26T19:00:37

4,219,328

0

2

BSD-3-Clause

2020-07-26T19:00:38

2012-05-03T22:03:24

Python

UTF-8

Python

false

10,736

py

from __future__ import absolute_import from time import time from itertools import count from celery import states from celery.events import Event from celery.events.state import State, Worker, Task, HEARTBEAT_EXPIRE from celery.utils import uuid from celery.tests.utils import Case class replay(object): def __init__(self, state): self.state = state self.rewind() self.setup() def setup(self): pass def __iter__(self): return self def __next__(self): try: self.state.event(self.events[self.position()]) except IndexError: raise StopIteration() next = __next__ def rewind(self): self.position = count(0).next return self def play(self): for _ in self: pass class ev_worker_online_offline(replay): def setup(self): self.events = [ Event("worker-online", hostname="utest1"), Event("worker-offline", hostname="utest1"), ] class ev_worker_heartbeats(replay): def setup(self): self.events = [ Event("worker-heartbeat", hostname="utest1", timestamp=time() - HEARTBEAT_EXPIRE * 2), Event("worker-heartbeat", hostname="utest1"), ] class ev_task_states(replay): def setup(self): tid = self.tid = uuid() self.events = [ Event("task-received", uuid=tid, name="task1", args="(2, 2)", kwargs="{'foo': 'bar'}", retries=0, eta=None, hostname="utest1"), Event("task-started", uuid=tid, hostname="utest1"), Event("task-revoked", uuid=tid, hostname="utest1"), Event("task-retried", uuid=tid, exception="KeyError('bar')", traceback="line 2 at main", hostname="utest1"), Event("task-failed", uuid=tid, exception="KeyError('foo')", traceback="line 1 at main", hostname="utest1"), Event("task-succeeded", uuid=tid, result="4", runtime=0.1234, hostname="utest1"), ] class ev_snapshot(replay): def setup(self): self.events = [ Event("worker-online", hostname="utest1"), Event("worker-online", hostname="utest2"), Event("worker-online", hostname="utest3"), ] for i in range(20): worker = not i % 2 and "utest2" or "utest1" type = not i % 2 and "task2" or "task1" self.events.append(Event("task-received", name=type, uuid=uuid(), hostname=worker)) class test_Worker(Case): def test_survives_missing_timestamp(self): worker = Worker(hostname="foo") worker.on_heartbeat(timestamp=None) self.assertEqual(worker.heartbeats, []) def test_repr(self): self.assertTrue(repr(Worker(hostname="foo"))) class test_Task(Case): def test_info(self): task = Task(uuid="abcdefg", name="tasks.add", args="(2, 2)", kwargs="{}", retries=2, result=42, eta=1, runtime=0.0001, expires=1, exception=1, received=time() - 10, started=time() - 8, succeeded=time()) self.assertEqual(sorted(list(task._info_fields)), sorted(task.info().keys())) self.assertEqual(sorted(list(task._info_fields + ("received", ))), sorted(task.info(extra=("received", )))) self.assertEqual(sorted(["args", "kwargs"]), sorted(task.info(["args", "kwargs"]).keys())) def test_ready(self): task = Task(uuid="abcdefg", name="tasks.add") task.on_received(timestamp=time()) self.assertFalse(task.ready) task.on_succeeded(timestamp=time()) self.assertTrue(task.ready) def test_sent(self): task = Task(uuid="abcdefg", name="tasks.add") task.on_sent(timestamp=time()) self.assertEqual(task.state, states.PENDING) def test_merge(self): task = Task() task.on_failed(timestamp=time()) task.on_started(timestamp=time()) task.on_received(timestamp=time(), name="tasks.add", args=(2, 2)) self.assertEqual(task.state, states.FAILURE) self.assertEqual(task.name, "tasks.add") self.assertTupleEqual(task.args, (2, 2)) task.on_retried(timestamp=time()) self.assertEqual(task.state, states.RETRY) def test_repr(self): self.assertTrue(repr(Task(uuid="xxx", name="tasks.add"))) class test_State(Case): def test_repr(self): self.assertTrue(repr(State())) def test_worker_online_offline(self): r = ev_worker_online_offline(State()) r.next() self.assertTrue(r.state.alive_workers()) self.assertTrue(r.state.workers["utest1"].alive) r.play() self.assertFalse(r.state.alive_workers()) self.assertFalse(r.state.workers["utest1"].alive) def test_worker_heartbeat_expire(self): r = ev_worker_heartbeats(State()) r.next() self.assertFalse(r.state.alive_workers()) self.assertFalse(r.state.workers["utest1"].alive) r.play() self.assertTrue(r.state.alive_workers()) self.assertTrue(r.state.workers["utest1"].alive) def test_task_states(self): r = ev_task_states(State()) # RECEIVED r.next() self.assertTrue(r.tid in r.state.tasks) task = r.state.tasks[r.tid] self.assertEqual(task.state, states.RECEIVED) self.assertTrue(task.received) self.assertEqual(task.timestamp, task.received) self.assertEqual(task.worker.hostname, "utest1") # STARTED r.next() self.assertTrue(r.state.workers["utest1"].alive, "any task event adds worker heartbeat") self.assertEqual(task.state, states.STARTED) self.assertTrue(task.started) self.assertEqual(task.timestamp, task.started) self.assertEqual(task.worker.hostname, "utest1") # REVOKED r.next() self.assertEqual(task.state, states.REVOKED) self.assertTrue(task.revoked) self.assertEqual(task.timestamp, task.revoked) self.assertEqual(task.worker.hostname, "utest1") # RETRY r.next() self.assertEqual(task.state, states.RETRY) self.assertTrue(task.retried) self.assertEqual(task.timestamp, task.retried) self.assertEqual(task.worker.hostname, "utest1") self.assertEqual(task.exception, "KeyError('bar')") self.assertEqual(task.traceback, "line 2 at main") # FAILURE r.next() self.assertEqual(task.state, states.FAILURE) self.assertTrue(task.failed) self.assertEqual(task.timestamp, task.failed) self.assertEqual(task.worker.hostname, "utest1") self.assertEqual(task.exception, "KeyError('foo')") self.assertEqual(task.traceback, "line 1 at main") # SUCCESS r.next() self.assertEqual(task.state, states.SUCCESS) self.assertTrue(task.succeeded) self.assertEqual(task.timestamp, task.succeeded) self.assertEqual(task.worker.hostname, "utest1") self.assertEqual(task.result, "4") self.assertEqual(task.runtime, 0.1234) def assertStateEmpty(self, state): self.assertFalse(state.tasks) self.assertFalse(state.workers) self.assertFalse(state.event_count) self.assertFalse(state.task_count) def assertState(self, state): self.assertTrue(state.tasks) self.assertTrue(state.workers) self.assertTrue(state.event_count) self.assertTrue(state.task_count) def test_freeze_while(self): s = State() r = ev_snapshot(s) r.play() def work(): pass s.freeze_while(work, clear_after=True) self.assertFalse(s.event_count) s2 = State() r = ev_snapshot(s2) r.play() s2.freeze_while(work, clear_after=False) self.assertTrue(s2.event_count) def test_clear_tasks(self): s = State() r = ev_snapshot(s) r.play() self.assertTrue(s.tasks) s.clear_tasks(ready=False) self.assertFalse(s.tasks) def test_clear(self): r = ev_snapshot(State()) r.play() self.assertTrue(r.state.event_count) self.assertTrue(r.state.workers) self.assertTrue(r.state.tasks) self.assertTrue(r.state.task_count) r.state.clear() self.assertFalse(r.state.event_count) self.assertFalse(r.state.workers) self.assertTrue(r.state.tasks) self.assertFalse(r.state.task_count) r.state.clear(False) self.assertFalse(r.state.tasks) def test_task_types(self): r = ev_snapshot(State()) r.play() self.assertEqual(sorted(r.state.task_types()), ["task1", "task2"]) def test_tasks_by_timestamp(self): r = ev_snapshot(State()) r.play() self.assertEqual(len(r.state.tasks_by_timestamp()), 20) def test_tasks_by_type(self): r = ev_snapshot(State()) r.play() self.assertEqual(len(r.state.tasks_by_type("task1")), 10) self.assertEqual(len(r.state.tasks_by_type("task2")), 10) def test_alive_workers(self): r = ev_snapshot(State()) r.play() self.assertEqual(len(r.state.alive_workers()), 3) def test_tasks_by_worker(self): r = ev_snapshot(State()) r.play() self.assertEqual(len(r.state.tasks_by_worker("utest1")), 10) self.assertEqual(len(r.state.tasks_by_worker("utest2")), 10) def test_survives_unknown_worker_event(self): s = State() s.worker_event("worker-unknown-event-xxx", {"foo": "bar"}) s.worker_event("worker-unknown-event-xxx", {"hostname": "xxx", "foo": "bar"}) def test_survives_unknown_task_event(self): s = State() s.task_event("task-unknown-event-xxx", {"foo": "bar", "uuid": "x", "hostname": "y"}) def test_callback(self): scratch = {} def callback(state, event): scratch["recv"] = True s = State(callback=callback) s.event({"type": "worker-online"}) self.assertTrue(scratch.get("recv"))

[ "kumar.mcmillan@gmail.com" ]

kumar.mcmillan@gmail.com

8b93e8f95d8ebe73848675dccb06fce575530545

994ae8f8dec8e4484ea490b3874991fd6f788b7e

/ARTools/ARUtils.py

08633d2b1a1e494907237337e3c97e0fd3b57b4f

[]

no_license

Leslie-zh/autoRig_Tools

c249f6b942d3a065e5aba203a5172ed9e689c856

9aa833ce674095fb24e91a7f9c9b5cb6435b4655

refs/heads/master

2022-03-15T04:26:47.502259

2019-04-22T18:59:07

null

0

null

UTF-8

Python

false

16,732

py

from maya import cmds from maya import OpenMaya from maya import OpenMayaAnim from maya import mel import re import pymel.core as pm import math import logging logging.basicConfig() logger = logging.getLogger('RigUtils:') logger.setLevel(logging.DEBUG) def snapIkFk(controller): """ snap ik fk or fk ik :param controller(str or pm): Controller with ikFk shape attribute :return: """ # check type if isinstance(controller, str): ikCtr = pm.PyNode(controller) ######################################## ## Find all controls and main objects ## ######################################## # get locator shape, it is common in all ik and fk controllers. # also it has the ikFk info locatorS = ikCtr.listRelatives(s=True, type=pm.nodetypes.Locator)[0] logger.debug('locatorS: %s' % locatorS) if not locatorS: logger.info('is not a ik fk chain') return # ikFk attribute value ikFkAttr = locatorS.ikFk instances = locatorS.getInstances() logger.debug('locator instances: %s' % instances) ikCtrList = [] # system ik controllers fkCtrList = [] # # system Fk controllers # get controllers from instances of locator for i in instances: controller = i.split('|')[-2] controller = pm.PyNode(controller) if 'ik' in str(controller): ikCtrList.append(controller) elif 'fk' in str(controller): fkCtrList.append(controller) # reverse lists, from nearest to world to last child ikCtrList = list(reversed(ikCtrList)) fkCtrList = list(reversed(fkCtrList)) # ik Stretch node with stretch value ikStretchNode = None try: # use top fk controller, because it has the correct base name of the system. ikStretchNode = str(fkCtrList[0]).split('_')[0:3] # base name of the system ikStretchNode = pm.PyNode('_'.join(ikStretchNode+['ikStretch','stretchValue','condition'])) # name of the stretch ik node except: pass # get system main joints mainJointList = [pm.PyNode(str(fk).replace('fk', 'main').replace('ctr', 'joint')) for fk in fkCtrList] # get pole controller ikHandle = ikCtrList[0].listRelatives(ad=True, type='ikHandle')[0] poleConstraint = ikHandle.poleVectorX.inputs(type='constraint')[0] pole = poleConstraint.target[0].targetTranslate.inputs(type='transform')[0] ## find child controllers, fingers, foot controllers, etc ## ikChildList = [ctr.getTransform() for ctr in ikCtrList[0].listRelatives(ad=True, type='nurbsCurve') if ctr.getTransform() not in ikCtrList] fkChildList = [ctr.getTransform() for ctr in fkCtrList[0].listRelatives(ad=True, type='nurbsCurve') if ctr.getTransform() not in fkCtrList] mainChildList = [ctr for ctr in mainJointList[0].listRelatives(ad=True, type='joint') if ctr not in mainJointList] ikChildCommonCtr = [] fkChildCommonCtr = [] ikFkChildCommonCtr = [] # [ikCtrA, fkCtrA, ikCtrB, fkctrB,...] controllers only appear in ik and fk chains mainChildCommonJnt = [] # get common controllers between lists # copy of the fkChils list, because we are going to delete members for i, fkCtr in enumerate(list(fkChildList)): # ask if the given sttr is in the list try: # it is possible some ctr in ik and fk, but not in main, like generaToe ctr ikCtr = pm.PyNode(str(fkCtr).replace('fk', 'ik')) try: # try if it exists in main too mainJnt = pm.PyNode(str(fkCtr).replace('fk', 'main').replace('ctr', 'joint')) mainChildCommonJnt.append(mainJnt) mainChildList.remove(mainJnt) except: # if controller is not in main, it is a special controller, only for ik and fk chains ikFkChildCommonCtr.append(ikCtr) ikFkChildCommonCtr.append(fkCtr) fkChildList.remove(fkCtr) ikChildList.remove(ikCtr) # continue next loop continue # append to common lists fkChildCommonCtr.append(fkCtr) ikChildCommonCtr.append(ikCtr) # remove from child lists fkChildList.remove(fkCtr) ikChildList.remove(ikCtr) except: pass # find possible parents of the system, p.e clavicle # use the skin skeleton, because it has a more clean hierarchy and it is easiest skinJoint = pm.PyNode(str(fkCtrList[0]).replace('fk', 'skin').replace('ctr', 'joint')) parentJoint = skinJoint.firstParent() # first parent for the test parentFkCtrList = [] # iterate over the parents to find valid system parents, like clavicle # valid parents only can have 1 joint child while True: childCount = parentJoint.getChildren(type='joint') if len(childCount) > 1: # more than 1 child joint, isn't valid logger.debug('No parent ctr found') break else: try: parentCtr = pm.PyNode(str(parentJoint).replace('skin', 'fk').replace('joint','ctr')) except: # do not exists a valid ctr, break the iteration logger.debug('No parent ctr found') break # save the control and try another joint parentFkCtrList.append(parentCtr) parentJoint = parentJoint.firstParent() ########## #ik -> fk# ########## if ikFkAttr.get(): # parent ctr, like clavicles if parentFkCtrList: parentRotation = parentFkCtrList[0].getRotation('world') zoneName = str(parentFkCtrList[0]).split('_')[1] # zone str name try: # try if it has an auto attribute, if system does not has an auto attribute, # it is not necessary apply rotation locatorS.attr('auto%s' % zoneName.capitalize()).set(0) parentFkCtrList[0].setRotation(parentRotation, 'world') except: pass # copy stretch factor, if the system has stretch option if ikStretchNode: locatorS.fkStretch.set(ikStretchNode.outColorR.get()) # copy rotation from main joints for i, mainj in enumerate(mainJointList): fkCtrList[i].setRotation(mainj.getRotation()) # cmds.xform(fkControllers[i], a=True, eu=True, ro=cmds.xform(mainj, a=True, eu=True, q=True, ro=True)) # last system ctr, foot or hand # if we have ikChilds, we have a foot system, so we snap to 'ball' controller (the last) if ikChildList: #print 'ballCtr', ikChildList[-1] fkCtrList[-1].setRotation(ikChildList[-1].getRotation('world'), 'world') # ikFk exclusive controllers #for i in range(0, len(ikFkChildCommonCtr), 2): #ikFkChildCommonCtr[i+1].setRotation(ikFkChildCommonCtr[i].getRotation('world'), 'world') # ik Fk main common ctrllers, general first for i, fkCtr in enumerate(fkChildCommonCtr): fkCtr.setRotation(mainChildCommonJnt[i].getRotation('world'), 'world') ikFkAttr.set(0) ########## #fk -> ik# ########## elif not ikFkAttr.get(): # reset walk values if ikChildList: # ikControllers only just like walk controllers ikCtrAttributes = pm.listAttr(ikCtrList[0], ud=True, k=True) for attr in ikCtrAttributes: ikCtrList[0].attr('%s' % attr).set(0) # set ikChildCtr to 0 for ikCtr in ikChildList: ikCtr.setRotation((0,0,0)) pm.xform(ikCtrList[0], ws=True, m=pm.xform(fkCtrList[-1], q=True, ws=True, m=True)) # ikFk exclusive controllers for i in range(0, len(ikFkChildCommonCtr), 2): ikFkChildCommonCtr[i+1].setRotation(ikFkChildCommonCtr[i].getRotation('world'), 'world') # ikFk exclusive controllers for i in range(0, len(ikFkChildCommonCtr), 2): ikFkChildCommonCtr[i].setRotation(ikFkChildCommonCtr[i+1].getRotation('world'), 'world') # ik Fk main common ctrllers, general first for i, ikCtr in enumerate(ikChildCommonCtr): ikCtr.setRotation(mainChildCommonJnt[i].getRotation('world'), 'world') if pole: # poleVector, use vector additive propriety upperLegPos = mainJointList[0].getTranslation('world') lowerLegPos = mainJointList[1].getTranslation('world') footPos = mainJointList[2].getTranslation('world') vector1 = pm.datatypes.Vector(lowerLegPos-upperLegPos) vector1.normalize() vector2 = pm.datatypes.Vector(lowerLegPos - footPos) vector2.normalize() poleVectorPos = vector1 + vector2 poleVectorPos.normalize() # multiply the resultant vector by the value we want, this way we can control the distance poleVectorPos = poleVectorPos * 20 # set pole vector position pole.setTranslation(poleVectorPos+lowerLegPos, 'world') ikFkAttr.set(1) def neckHeadIsolateSnap(name, zone, controller, point, orient): """ TODO: valid with only 1 argument isolate to 0 or 1 and snap controllers args: name(str): character name zone(str): zone of controller controller(str): controller type point (bool): if true, snap translation orient (bool): if true, snap rotation """ headControl = '%s_IK_%s_%s_1_ctr' % (name, zone, controller) # check if exist if not cmds.objExists(headControl): print ('%s do not exists' % headControl) return # save transforms headControlTranslate = cmds.xform(headControl, q=True, ws=True, m=True) if orient: # set orient print ('set orient') isolate = not cmds.getAttr('%s.isolateOrient' % headControl) cmds.setAttr('%s.isolateOrient' % headControl, isolate) if point: # set position print ('set point') isolate = not cmds.getAttr('%s.isolatePoint' % headControl) cmds.setAttr('%s.isolatePoint' % headControl, isolate) # Transform head control cmds.xform(headControl, ws=True, m=headControlTranslate) ## Proxies ## # TODO: make class, include in the picker #UI def proxyShowUI(name): """ Activate proxies UI Args: name(str): name of the character """ windowName = '%sShowProxiesUI' % name.capitalize() # check if window exists if cmds.window(windowName, q=True, exists=True): cmds.deleteUI(windowName) cmds.window(windowName) # proxy str proxyStr = 'proxy' # def window column = cmds.columnLayout(adj=True, co=('both', 10)) cmds.text(label='%s Proxies' % name.capitalize()) cmds.separator(visible=True, h=20) # row layout to store chBox and button cmds.rowLayout(nc=2, adjustableColumn=2) # check state parent, state = checkState(name, proxyStr) # ui widgets chBox = cmds.checkBox(label='Parent', value=parent, enable=not state) buttonName = 'Model' if state else 'Proxies' button = cmds.button(buttonName, command=lambda x: proxyShowUIButton(name, chBox, button, proxyStr)) # show window cmds.showWindow() def proxyShowUIButton(name, chBox, button, proxyStr, *args): """ UI proxies button, turn on or off proxies. Args: name(str): name of the character chBox(str): UI checkBox button(str): UI button proxyStr(str): common word for all the proxies *args: """ chBoxValue = cmds.checkBox(chBox, q=True, v=True) # list proxies proxyList = cmds.ls('*%s' % proxyStr, type='transform') # connect proxies by parenting if chBoxValue: value = proxyModelParent(name, proxyList, proxyStr) # connect proxies by constraint else: value = proxyModelConstraints(name, proxyList, proxyStr) # change button name and disable chBox if value: cmds.button(button, e=True, label='Model') cmds.checkBox(chBox, e=True, enable=False) # change button name and enable chBox else: cmds.button(button, e=True, label='Proxies') cmds.checkBox(chBox, e=True, enable=True) def checkState(name, proxyStr): """ check the state of the proxies return: (bool): True, parent. False, constraint (bool): True, proxies active. False, model active """ proxyGrp = '%s_%s_grp' % (name, proxyStr) proxyConstraints = cmds.listRelatives(proxyGrp, ad=True, type='constraint') proxyTransforms = [proxy for proxy in cmds.listRelatives('%s_rig_grp' % name, ad=True, type='transform') if proxyStr in proxy] if proxyConstraints: return False, True elif proxyTransforms: return True, True else: return False, False # proxy scripts def proxyModelConstraints(name, proxies, proxyStr): """ Connect proxy models to deform joints by constraints Args: name(str): name of the character proxies(list(str)): list with proxies proxyStr(str): common word for all the proxies """ proxyGrp = '%s_%s_grp' % (name, proxyStr) proxyConstraints = cmds.listRelatives(proxyGrp, ad=True, type='constraint') # disconnect proxies if proxyConstraints: ProxyDisconnectConstraints(name, 0) cmds.delete(proxyConstraints) cmds.setAttr('%s.visibility' % proxyGrp, 0) return False # useful to change elements of the ui # connect proxies else: ProxyDisconnectConstraints(name, 1) cmds.setAttr('%s.visibility' % proxyGrp, 1) for proxy in proxies: try: mainName = proxy.replace(proxyStr, 'main') cmds.parentConstraint(mainName, proxy, maintainOffset=False) cmds.scaleConstraint(mainName, proxy, maintainOffset=False) except: ctrName = proxy.replace(proxyStr, 'ctr') cmds.parentConstraint(ctrName, proxy, maintainOffset=False) cmds.scaleConstraint(ctrName, proxy, maintainOffset=False) return True # useful to change elements of the ui def proxyModelParent(name, proxies, proxyStr): """ Connect proxy models to deform joints by parenting them Args: name(str): name of the character proxies(list(str)): list with proxies proxyStr(str): common word for all the proxies """ proxyTransforms = [proxy for proxy in cmds.listRelatives('%s_rig_grp' % name, ad=True, type='transform') if proxyStr in proxy] proxyGrp = '%s_%s_grp' % (name, proxyStr) # unparent proxies if proxyTransforms: ProxyDisconnectConstraints(name, 0) # 1 connect cmds.parent(proxyTransforms, '%s_%s_grp' % (name, proxyStr)) cmds.setAttr('%s.visibility' % proxyGrp, 0) return False # useful to change elements of the ui # parent proxies else: ProxyDisconnectConstraints(name, 1) # 1 disconnect for proxy in proxies: try: mainName = proxy.replace(proxyStr, 'main') cmds.parent(proxy, mainName) cmds.xform(proxy, os=True, t=(0, 0, 0), ro=(0, 0, 0), s=(1, 1, 1)) except: ctrName = proxy.replace(proxyStr, 'ctr') cmds.parent(proxy, ctrName) cmds.xform(proxy, os=True, t=(0, 0, 0), ro=(0, 0, 0), s=(1, 1, 1)) return True # useful to change elements of the ui def ProxyDisconnectConstraints(name, value): """ Turn off all deformable joint constraints, and skinClusters Args: name(str): Character name value(int): 1->disconnect, 0->connect """ jointsGrp = '%s_joints_grp' % name modelGrp = '%s_model_grp' % name constraints = cmds.ls(jointsGrp, dag=True, type='constraint') meshList = cmds.ls(modelGrp, dag=True, type='mesh') # groups visibility cmds.setAttr('%s.visibility' % jointsGrp, not value) cmds.setAttr('%s.visibility' % modelGrp, not value) for constraint in constraints: cmds.setAttr('%s.nodeState' % constraint, value) # disconnect cmds.setAttr('%s.frozen' % constraint, value) for mesh in meshList: skinNode = cmds.listConnections(mesh, d=True, type='skinCluster') if skinNode: cmds.setAttr('%s.nodeState' % skinNode[0], value) # disconnect cmds.setAttr('%s.frozen' % skinNode[0], value) """ if __name__ == '__main__': proxyShowUI('akona') """

[ "Jap3dWorks@gmail.com" ]

Jap3dWorks@gmail.com

0894168cf481341050dd22efc8f324aea99c393d

040a735434f94168c34543c69291a6860d83ad01

/exel/xl_snake.py

87e8da4d19991f9450eba8e30d5ca4365132e651

[]

no_license

ngphatpython190/tren-mang

a1fb5d9f01e68ac40f4bc9f8e12b5744fc5d7d87

9276e53f38218e97c5bcdecb74442fe01b87af4d

refs/heads/main

2023-09-03T11:19:12.657557

2021-11-06T11:35:11

418,477,353

0

null

UTF-8

Python

false

4,012

py

import xlwings as xw from string import ascii_uppercase from random import randint from time import sleep from sys import exit class Snake: def __init__(self,speed,width,height): # Book setup self.book = xw.Book() self.sheet = self.book.sheets[0] self.sheet.name = 'snake' # board setup self.speed = 1 / speed self.width = width self.height = height self.board_setup() # snake setup self.body = [(int(height / 2),5),(int(height / 2),4),(int(height / 2),3)] self.direction = (0,1) self.eaten = False self.create_apple() def board_setup(self): # background colors game_cells = f'B2:{ascii_uppercase[self.width]}{self.height + 1}' self.sheet[game_cells].color = board_color control_cells = f'B{self.height + 2}:{ascii_uppercase[self.width]}{self.height + 6}' self.sheet[control_cells].color = control_color # buttons self.exit_cell = f'{ascii_uppercase[self.width]}{self.height + 6}' self.sheet[self.exit_cell].value = 'quit' self.left_cell = f'C{self.height + 4}' self.sheet[self.left_cell].value = 'left' self.right_cell = f'E{self.height + 4}' self.sheet[self.right_cell].value = 'right' self.up_cell = f'D{self.height + 3}' self.sheet[self.up_cell].value = 'up' self.down_cell = f'D{self.height + 5}' self.sheet[self.down_cell].value = 'down' # button styling for button in [self.exit_cell,self.left_cell,self.right_cell,self.up_cell,self.down_cell]: self.sheet[button].color = button_color self.sheet[button].font.color = text_color # cell dimensions self.sheet[f'B2:B{self.height + 6}'].row_height = 40 def display_game_elements(self): # apple display self.sheet[self.apple_pos].color = apple_color # snake display for index,cell in enumerate(self.body): if index == 0: self.sheet[cell].color = head_color else: self.sheet[cell].color = body_color def create_apple(self): # get a random cell (row,col) row = randint(1,self.height) col = randint(1,self.width) # check if apple is below snake while (row,col) in self.body: row = randint(1,self.height) col = randint(1,self.width) self.apple_pos = (row,col) def input(self): selected_cell = self.book.selection.address.replace('$','') if selected_cell == self.right_cell: self.direction = (0,1) elif selected_cell == self.left_cell: self.direction = (0,-1) elif selected_cell == self.up_cell: self.direction = (-1,0) elif selected_cell == self.down_cell: self.direction = (1,0) def exit_game(self): selected_cell = self.book.selection.address.replace('$','') if selected_cell == self.exit_cell: self.book.close() exit() def move_snake(self): if self.eaten: new_body = self.body[:] self.eaten = False else: lost_cell = self.body[-1] new_body = self.body[:-1] self.sheet[lost_cell].color = board_color new_head = self.add_direction(new_body[0],self.direction) new_body.insert(0,new_head) self.body = new_body def add_direction(self,cell,direction): row = cell[0] + direction[0] col = cell[1] + direction[1] return(row,col) def check_apple_collision(self): if self.body[0] == self.apple_pos: self.eaten = True self.create_apple() def check_fail(self): head = self.body[0] body = self.body[1:] if head in body or head[1] <= 0 or head[1] >= self.width + 1 or head[0] <= 0 or head[0] >= self.height + 1: self.book.close() exit() def run(self): while True: self.exit_game() sleep(self.speed) self.input() self.move_snake() self.check_apple_collision() self.check_fail() self.display_game_elements() # COLORS board_color = (226,227,223) control_color = (46,50,51) button_color = (81,91,94) text_color = (255, 255, 255) apple_color = (0,255,100) head_color = (255,0,0) body_color = (200,0,0) snake = Snake(3,12,8) snake.run()

[ "noreply@github.com" ]

ngphatpython190.noreply@github.com

bb88c6ede9da6acfa26ee404324f10121a2c33c1

9695228629e72a9074882211603d12dae51abf3e

/show/views.py

8c9a14b21b2aa359624f1980e18db48375fab06f

[]

no_license

ken890728/maze

b875880adc08800f03adbb4a0ce3a6c6adbe8786

a30cca47121a238df0a84b10b00e5b245abf0bac

refs/heads/master

2021-01-15T22:08:51.058562

2017-08-10T07:17:04

99,888,238

0

null

UTF-8

Python

false

509

py

from django.shortcuts import render_to_response, redirect from django.http import HttpResponse from django.template import RequestContext from models import Record def index(request): return render_to_response('index.html') def add(request, seconds): record = Record(seconds=seconds) record.save() return redirect("/show") def show(request): records = Record.objects.all().order_by("-id") return render_to_response('show.html',{'records':records}, context_instance=RequestContext(request))

[ "ken22436653@gmail.com" ]

ken22436653@gmail.com

88fc2053e80bc58ae209cdfe9ed49b6a4bcafc2c

c3082eb2adc43b311dd3c9ff16fd3ed9df85f266

/python/examples/gravatar.py

02ce05805f996cdb851c9e6a8fb3a644257d5e44

[]

no_license

szabgab/slides

78818c7138331b3ba9e221c81da3678a46efe9b3

63bba06678554db737602f2fbcd6510c36037e8a

refs/heads/main

2023-08-31T07:13:51.536711

2023-08-29T13:17:59

122,212,527

87

69

null

2023-05-19T06:55:11

2018-02-20T14:57:03

Python

UTF-8

Python

false

294

py

import hashlib import sys def gravatar(email): return hashlib.md5(email.strip().lower().encode('utf8')).hexdigest() if len(sys.argv) != 2: exit(f"Usage: {sys.argv[0]} EMAIL") email = sys.argv[1] code = gravatar(email) print(f"https://www.gravatar.com/avatar/{code}?s=100&d=blank")

[ "gabor@szabgab.com" ]

gabor@szabgab.com

feee5c1b995b9b8d43dd9bb95364532994f3bf72

ff469ac1982a55d0ac209b5c42ee20c54f9fd5e5

/app/app.py

ebc61f9ce7ef40933a9b579bb6924a70aebf00e2

[]

no_license

carlosrv999/demo-gcp

7667618e98751f95d25f6d70c885ee0dd208ae44

2c13e48a915acf908fa048e26b6d1d754a750df7

refs/heads/master

2023-05-13T17:21:17.470582

2020-05-05T23:46:04

261,557,229

0

null

2023-05-01T21:39:47

2020-05-05T18:51:37

Shell

UTF-8

Python

false

584

py

from flask import request, Flask import socket app = Flask(__name__) @app.route("/healthz") def healthz(): return "Healthy" @app.route("/") def rootpage(): return "root page" @app.route("/greetings") def hello(): return "Hello World from " + socket.gethostname() + "." @app.route("/square") def square(): x = request.args.get('x') try: x = int(x) return str(x ** 2) except: return "Ingrese un numero entero con el parametro x en la url (/square?x=1 por ejemplo)" if __name__ == '__main__': app.run(debug=True, host='0.0.0.0')

[ "carlosrv125@icloud.com" ]

carlosrv125@icloud.com

db5043627d2d557ddbf8f268af315b97bae02f34

17c280ade4159d4d8d5a48d16ba3989470eb3f46

/18/mc/ExoDiBosonResonances/EDBRTreeMaker/test/crab3_analysisM2500_R_0-1.py

0f7c4e4db7ada38e47e4cb679cfa85d072b43dce

[]

no_license

chengchen1993/run2_ntuple

798ff18489ff5185dadf3d1456a4462e1dbff429

c16c2b203c05a3eb77c769f63a0bcdf8b583708d

refs/heads/master

2021-06-25T18:27:08.534795

2021-03-15T06:08:01

212,079,804

0

2

null

UTF-8

Python

false

2,201

py

from WMCore.Configuration import Configuration name = 'WWW' steam_dir = 'xulyu' config = Configuration() config.section_("General") config.General.requestName = 'M2500_R0-1_off' config.General.transferLogs = True config.section_("JobType") config.JobType.pluginName = 'Analysis' config.JobType.inputFiles = ['Autumn18_V19_MC_L1FastJet_AK4PFchs.txt','Autumn18_V19_MC_L2Relative_AK4PFchs.txt','Autumn18_V19_MC_L3Absolute_AK4PFchs.txt','Autumn18_V19_MC_L1FastJet_AK8PFchs.txt','Autumn18_V19_MC_L2Relative_AK8PFchs.txt','Autumn18_V19_MC_L3Absolute_AK8PFchs.txt','Autumn18_V19_MC_L1FastJet_AK8PFPuppi.txt','Autumn18_V19_MC_L2Relative_AK8PFPuppi.txt','Autumn18_V19_MC_L3Absolute_AK8PFPuppi.txt','Autumn18_V19_MC_L1FastJet_AK4PFPuppi.txt','Autumn18_V19_MC_L2Relative_AK4PFPuppi.txt','Autumn18_V19_MC_L3Absolute_AK4PFPuppi.txt' ] #config.JobType.inputFiles = ['PHYS14_25_V2_All_L1FastJet_AK4PFchs.txt','PHYS14_25_V2_All_L2Relative_AK4PFchs.txt','PHYS14_25_V2_All_L3Absolute_AK4PFchs.txt','PHYS14_25_V2_All_L1FastJet_AK8PFchs.txt','PHYS14_25_V2_All_L2Relative_AK8PFchs.txt','PHYS14_25_V2_All_L3Absolute_AK8PFchs.txt'] # Name of the CMSSW configuration file #config.JobType.psetName = 'bkg_ana.py' config.JobType.psetName = 'analysis.py' #config.JobType.allowUndistributedCMSSW = True config.JobType.allowUndistributedCMSSW = True config.section_("Data") #config.Data.inputDataset = '/WJetsToLNu_13TeV-madgraph-pythia8-tauola/Phys14DR-PU20bx25_PHYS14_25_V1-v1/MINIAODSIM' config.Data.inputDataset = '/WkkToWRadionToWWW_M2500-R0-1_TuneCP5_13TeV-madgraph/RunIIAutumn18MiniAOD-102X_upgrade2018_realistic_v15-v1/MINIAODSIM' #config.Data.inputDBS = 'global' config.Data.inputDBS = 'global' config.Data.splitting = 'LumiBased' config.Data.unitsPerJob =5 config.Data.totalUnits = -1 config.Data.publication = False config.Data.outLFNDirBase='/store/group/phys_b2g/chench/cc/'#chench/'# = '/store/group/dpg_trigger/comm_trigger/TriggerStudiesGroup/STEAM/' + steam_dir + '/' + name + '/' # This string is used to construct the output dataset name config.Data.outputDatasetTag = 'M2500_R0-1_off' config.section_("Site") # Where the output files will be transmitted to config.Site.storageSite = 'T2_CH_CERN'

[ "c.chen@cern.ch" ]

c.chen@cern.ch

97bb186f1525825173d22a5a7c27d401e39fa997

29619c1b1ee216fd40f6c13b1cb4612cc6ef79e5

/merge_two_sorted_list.py

6379cb54ca6829eb7ed3674e29982c7b323e4810

[]

no_license

sacsachin/programing

9527c4340522159423120d203152c37dcf9f8931

377b25c317e3972d63ead7a34397458702f8accf

refs/heads/master

2022-12-14T00:20:35.232816

2020-09-26T12:36:32

298,810,542

0

null

UTF-8

Python

false

1,424

py

# !/usr/bin/python3 """ https://www.interviewbit.com/problems/remove-duplicates-from-sorted-list/ Remove dyplicate from sorted list. """ class Node: def __init__(self, val=0, nxt=None): self.val = val self.next = nxt class LinkList: def __init__(self, nodes=None): self.head = None if nodes is not None: node = Node(val=nodes.pop(0)) self.head = node for elem in nodes: node.next = Node(val=elem) node = node.next def solve(first, second): ans = [] head = tail = None while first and second: if first.val <= second.val: node = first first = first.next else: node = second second = second.next if head == None: head = tail = node else: tail.next = node tail = node while first: tail.next = first tail = first first = first.next while second: tail.next = second tail = second second = second.next current = head while current: ans.append(current.val) current = current.next return ans if __name__ == "__main__": first = LinkList([(lambda x: int(x))(x) for x in input().split()]) second = LinkList([(lambda x: int(x))(x) for x in input().split()]) print(solve(first.head, second.head))

[ "psachin@zeomega.com" ]

psachin@zeomega.com

5fb84372f582c5ae87a1b79178eaa1d6403251aa

3f3044255b8430a9c73e02177e94c0fadc88ca9a

/archive/bullshitalign.py

654a0985d689389ac04f9e3e9689e2cfff95ae38

[]

no_license

msgordon/optipol-reduc

263d95b5d0b1c7009d40c03a79d7038d3d26438e

37a0e778ea357ad1cb679a0364a31fe5d6dd6ff9

refs/heads/master

2020-05-17T13:26:07.974020

2017-10-11T00:31:24

20,042,490

0

null

UTF-8

Python

false

1,631

py

#! /usr/bin/env python import numpy as np import argparse import pyfits from scipy.ndimage.interpolation import shift as sc_shift #from shift import shift as fft_shift import os from pyds9 import pydisplay def shift(filename, xs, ys, refFile,noShift=False): f = pyfits.open(filename) header = f[0].header header['REF_FILE'] = (os.path.basename(refFile),'Reference file') header['PRE_FILE'] = (os.path.basename(filename),'Filename before shift') header['XSHIFT'] = (xs,'X shift from ref_file') header['YSHIFT'] = (ys,'Y shift from ref_file') newName = os.path.splitext(filename) newName = ''.join([newName[0],'_s',newName[1]]) #return newName if noShift: newDat = f[0].data else: #newDat = fft_shift(f[0].data,xs,ys) newDat = sc_shift(f[0].data,[ys,xs]) print 'Writing to %s' % newName pyfits.writeto(newName,newDat,header=header,clobber=True) return newName def main(): parser = argparse.ArgumentParser(description='Shift images to align objects in input file') parser.add_argument('file',help='Input file with coordinates') args = parser.parse_args() data = np.genfromtxt(args.file,names=['fname','x','y'],dtype=['a100','f8','f8'],autostrip=True) # Copy reference file checkMe = [] ref = data[0] checkMe.append(shift(ref['fname'],0,0,ref['fname'],noShift=False)) for dat in data[1:]: xs = ref['x'] - dat['x'] ys = ref['y'] - dat['y'] checkMe.append(shift(dat['fname'],xs,ys,ref['fname'])) #pydisplay(checkMe) if __name__ == '__main__': main()

[ "msgordon.astro@gmail.com" ]

msgordon.astro@gmail.com

9a34a1120fe9546f1836735b1d5af632a15b354f

2642ea15cb26372c616458233d3b94e3700e3eb7

/Module02/radixStable.py

a5a12db587c8984d1b4f16c1064dd12bf18ad12b

[]

no_license

hdmcspadden/CS5012

96be4c1d09007fb365a1f2f3d4afb70f22d4ad7a

b856c5e780229dddd909691c2ddb4e454d377826

refs/heads/master

2023-04-18T08:12:07.733808

2021-05-02T21:48:29

333,499,252

1

0

null

UTF-8

Python

false

1,823

py

# Python program for implementation of Radix Sort # A function to do counting sort of arr[] according to # the digit represented by exp. def countingSort(arr, exp1): n = len(arr) # The output array elements that will have sorted arr output = [0] * (n) # initialize count array as 0 # this is hard-coded for base 10. count = [0] * (10) # Store count of occurrences in count[] for i in range(0, n): index = (arr[i] / exp1) count[int(index % 10)] += 1 # increase the count of the number of elements at that place # Change count[i] so that count[i] now contains actual # position of this digit in output array for i in range(1, 10): count[i] += count[i - 1] # Build the output array i = n - 1 while i >= 0: index = (arr[i] / exp1) output[count[int(index % 10)] - 1] = arr[i] count[int(index % 10)] -= 1 i -= 1 # Copying the output array to arr[], # so that arr now contains sorted numbers i = 0 for i in range(0, len(arr)): arr[i] = output[i] # Method to do Radix Sort def radixSort(arr): # Find the maximum number to know number of digits # knowing the max seems a cheat. max1 = max(arr) # Do counting sort for every digit. Note that instead # of passing digit number, exp is passed. exp is 10^i # where i is current digit number exp = 1 while max1 / exp > 0: countingSort(arr, exp) exp *= 10 arr = [36,1,12,25,44,11,25] print("Input array: {}".format(arr)) # Function Call radixSort(arr) print("Resulting array: {}".format(arr)) #for i in range(len(arr)): # print(arr[i]) # This code is contributed by Mohit Kumra # Edited by Patrick Gallagher

[ "hdmcspadden@gmail.com" ]

hdmcspadden@gmail.com

84804ddd9a4668077b8d84017577df31b6b0775b

2d1dcf1d13e5aa5cbc60fd2730f39bbace5556e4

/quiz/settings/base.py

0f4da07aedf0f56b1eea9814e7b1505b448efd98

[]

no_license

amalu-m/world-trivia

2c66c0f84c6cb87a459590cdd778c14cc0e575b7

ffb837231b40b0d357aef27edd45ff4e2f2a8e3a

refs/heads/master

2023-01-10T12:20:30.844418

2020-11-13T03:01:41

305,027,675

0

null

2020-11-09T05:53:26

2020-10-18T05:14:51

Python

UTF-8

Python

false

197

py

import os from dotenv import load_dotenv load_dotenv() SECRET_KEY = os.getenv("SECRET_KEY") ENV_NAME = os.getenv("ENV_NAME") DB_USER = os.getenv("DB_USER") DB_PASSWORD = os.getenv("DB_PASSWORD")

[ "amalulmathew@gmail.com" ]

amalulmathew@gmail.com

8108385351aac8c2bdb972161149bfb87e009ee6

e50edc6f4b4bececb13ec4f8b3249418a1b36fb1

/知识可视化/urls.py

cd08ec2a6e27c62e174bd5a3a0f06ec0ed71885f

[]

no_license

Fanyunjie/ML-Project

e9b0efb378deaa4bf1d96cad199835f3bbe0d8ee

fba6248f6c978e3add20eaa904107009cadf44cc

refs/heads/master

2022-11-30T08:51:12.319983

2020-08-14T04:35:44

287,442,250

0

null

UTF-8

Python

false

1,546

py

"""知识可视化 URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.0/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path, include from app01.views import * from django.views.generic.base import TemplateView from django.conf.urls import url urlpatterns = [ path('admin/', admin.site.urls), path('knowledge', find_all_data.as_view()), path('title_find_data', title_find_data.as_view()), path('find_similar_title',find_similar_title.as_view()), url('', TemplateView.as_view(template_name='index.html')), # path('title_find_paper_data', title_find_paper_data.as_view()), # path('title_find_news_data', title_find_news_data.as_view()), # path('title_find_rumor_data', title_find_rumor_data.as_view()), # path('find_similar_paper_titles', find_similar_paper_titles.as_view()), # path('find_similar_news_titles', find_similar_news_titles.as_view()), # path('find_similar_rumors_titles', find_similar_rumors_titles.as_view()) ]

[ "843179781@qq.com" ]

843179781@qq.com

eff067dc97f33395ef1ff5db167fdf8df5d64cba

ec1d4ce3fcbb8057281bee180a936be1767c3fae

/04.py

05d48ecfd651ccdb567cfb3a56625bbab081df0c

[]

no_license

majatrepsic/advent-of-code-2017

fda71a48aee28ffb2e4e4b277655b4f9c4de0d77

c36eb3a7e82b282f39607988f622e4c67fafbd75

refs/heads/master

2021-08-24T11:03:22.033849

2017-12-09T11:51:25

112,757,282

2

0

null

UTF-8

Python

false

1,027

py

import csv # Part one valid_inputs = 0 with open('inputs/04.txt', 'rb') as csvfile: input_reader = csv.reader(csvfile, delimiter=' ') for row in input_reader: # print len(row) # print len(set(row)) if len(row) == len(set(row)): valid_inputs += 1 print valid_inputs # Part two def check_permutations(row): for i in range(0, len(row)): for j in range(i + 1, len(row)): # print row[i] + ',' + row[j] # print str(sorted(row[i])) + ',' + str(sorted(row[j])) if (len(row[i]) == len(row[j])) \ and (sorted(row[i]) == sorted(row[j])): return False return True valid_inputs_permutation = 0 with open('inputs/04.txt', 'rb') as csvfile: input_reader = csv.reader(csvfile, delimiter=' ') for row in input_reader: if len(row) == len(set(row)): # print row if check_permutations(row): valid_inputs_permutation += 1 print valid_inputs_permutation

[ "maja.trepsic@amphinicy.com" ]

maja.trepsic@amphinicy.com

50530eb0a7d5d0fe82c48791eaa79b4cc8fa29dd

759dd1e7aef4e54fe07c89d4e7289758b6fe18f3

/core/models.py

dc32b9b8dd74e7b56339ed6f083c12ee06c00190

[]

no_license

igoo-Y/iemu11

059e8bcd51764bad6f5adeaca174b013defe35a4

0ed68ec8932ece7e4537d5cee601f5b86fae656d

refs/heads/main

2023-08-18T23:09:55.233882

2021-10-04T11:09:40

351,639,014

0

null

UTF-8

Python

false

247

py

from django.db import models class TimeStampedModel(models.Model): """Time Stamed Model Definition""" created = models.DateField(auto_now_add=True) updated = models.DateField(auto_now=True) class Meta: abstract = True

[ "79055280+igoo-Y@users.noreply.github.com" ]

79055280+igoo-Y@users.noreply.github.com

67be5ae559d9805937ef23598331da812d5621e8

f41409cd5bff8ad9dbd2b96f49ff27a733472da5

/agentpool/agentcraw/xiciagent/xiciCraw.py

a19528f4ade6c4ab890d48dcd09f4e58e7333117

[]

no_license

LittleStone8/SBagentpool

3f5229c1dde2d9d6f9ac29e428371b90dcc18c57

0a0302c3763069c11d0b3bf729d6460162bb51d5

refs/heads/master

2020-06-24T02:57:54.795022

2019-07-26T05:47:53

198,829,367

6

0

null

UTF-8

Python

false

1,535

py

from agentpool.agentcraw.xiciagent import xicicommon from agentpool.agentcraw.xiciagent.xiciUrlmanager import xiciUrlmanager from agentpool.agentcraw.xiciagent.xicidownloader import xicidownloader from agentpool.agentcraw.xiciagent.xicioutputer import xicioutputer from agentpool.agentcraw.xiciagent.xiciparser import xiciparser from common import agentsrc from framemodule.Craw import Craw class xiciCraw(Craw): def __init__(self,Scheduler): self.urlmanager = xiciUrlmanager() self.downloader = xicidownloader() self.parser = xiciparser() self.outputer = xicioutputer() self.job_interval= xicicommon.xici_craw_interval self.scheduler=Scheduler pass def docraw(self): self.start_craw() if self.job_interval!=0: self.scheduler.timer.addtask(self.start_craw,self.job_interval) pass def start_craw(self): print('启动开始抓取xici代理任务:') for url in self.urlmanager.new_urls: self.scheduler.run_in_main_threadpool(func=self.craw, args=(url,)) pass def craw(self,url): print('开始抓取:'+url) html = self.downloader.download_by_myself_useagent(url) data = self.parser.parse(url, html) returndata = 0 if data != None: returndata = str(len(data)) print(url + "返回数据:" + str(returndata)) storagesum=self.outputer.collect_data(data,url,agentsrc.xici) print(url + "抓取完毕,入库:"+str(storagesum))

[ "262627160@qq.com" ]

262627160@qq.com

7368fbf5331c7acbeec9c4c90da997d2e4fa59e8

d7d27f05de357cfa68f85c3529364409e488622c

/repo/repo

65fb2cde1f75f764db026cd4fcf4d29482857b21

[]

no_license

yuanjianye/software_config

c82949d06f118690911f93bb46d9fee7def82161

a7314c8cef49fa83ede033df2b07b8766567be55

HEAD

2016-09-05T12:28:28.247501

2015-05-14T06:02:01

35,592,603

1

0

null

UTF-8

Python

false

24,140

#! /usr/bin/python ## repo default configuration ## #REPO_URL = 'https://gerrit.googlesource.com/git-repo' REPO_URL = 'root@home.yuanjianye.com:/.storage/git/git-repo' REPO_REV = 'stable' # Copyright (C) 2008 Google Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # increment this whenever we make important changes to this script VERSION = (1, 21) # increment this if the MAINTAINER_KEYS block is modified KEYRING_VERSION = (1, 2) MAINTAINER_KEYS = """ Repo Maintainer <repo@android.kernel.org> -----BEGIN PGP PUBLIC KEY BLOCK----- Version: GnuPG v1.4.2.2 (GNU/Linux) mQGiBEj3ugERBACrLJh/ZPyVSKeClMuznFIrsQ+hpNnmJGw1a9GXKYKk8qHPhAZf WKtrBqAVMNRLhL85oSlekRz98u41H5si5zcuv+IXJDF5MJYcB8f22wAy15lUqPWi VCkk1l8qqLiuW0fo+ZkPY5qOgrvc0HW1SmdH649uNwqCbcKb6CxaTxzhOwCgj3AP xI1WfzLqdJjsm1Nq98L0cLcD/iNsILCuw44PRds3J75YP0pze7YF/6WFMB6QSFGu aUX1FsTTztKNXGms8i5b2l1B8JaLRWq/jOnZzyl1zrUJhkc0JgyZW5oNLGyWGhKD Fxp5YpHuIuMImopWEMFIRQNrvlg+YVK8t3FpdI1RY0LYqha8pPzANhEYgSfoVzOb fbfbA/4ioOrxy8ifSoga7ITyZMA+XbW8bx33WXutO9N7SPKS/AK2JpasSEVLZcON ae5hvAEGVXKxVPDjJBmIc2cOe7kOKSi3OxLzBqrjS2rnjiP4o0ekhZIe4+ocwVOg e0PLlH5avCqihGRhpoqDRsmpzSHzJIxtoeb+GgGEX8KkUsVAhbQpUmVwbyBNYWlu dGFpbmVyIDxyZXBvQGFuZHJvaWQua2VybmVsLm9yZz6IYAQTEQIAIAUCSPe6AQIb AwYLCQgHAwIEFQIIAwQWAgMBAh4BAheAAAoJEBZTDV6SD1xl1GEAn0x/OKQpy7qI 6G73NJviU0IUMtftAKCFMUhGb/0bZvQ8Rm3QCUpWHyEIu7kEDQRI97ogEBAA2wI6 5fs9y/rMwD6dkD/vK9v4C9mOn1IL5JCPYMJBVSci+9ED4ChzYvfq7wOcj9qIvaE0 GwCt2ar7Q56me5J+byhSb32Rqsw/r3Vo5cZMH80N4cjesGuSXOGyEWTe4HYoxnHv gF4EKI2LK7xfTUcxMtlyn52sUpkfKsCpUhFvdmbAiJE+jCkQZr1Z8u2KphV79Ou+ P1N5IXY/XWOlq48Qf4MWCYlJFrB07xjUjLKMPDNDnm58L5byDrP/eHysKexpbakL xCmYyfT6DV1SWLblpd2hie0sL3YejdtuBMYMS2rI7Yxb8kGuqkz+9l1qhwJtei94 5MaretDy/d/JH/pRYkRf7L+ke7dpzrP+aJmcz9P1e6gq4NJsWejaALVASBiioqNf QmtqSVzF1wkR5avZkFHuYvj6V/t1RrOZTXxkSk18KFMJRBZrdHFCWbc5qrVxUB6e N5pja0NFIUCigLBV1c6I2DwiuboMNh18VtJJh+nwWeez/RueN4ig59gRTtkcc0PR 35tX2DR8+xCCFVW/NcJ4PSePYzCuuLvp1vEDHnj41R52Fz51hgddT4rBsp0nL+5I socSOIIezw8T9vVzMY4ArCKFAVu2IVyBcahTfBS8q5EM63mONU6UVJEozfGljiMw xuQ7JwKcw0AUEKTKG7aBgBaTAgT8TOevpvlw91cAAwUP/jRkyVi/0WAb0qlEaq/S ouWxX1faR+vU3b+Y2/DGjtXQMzG0qpetaTHC/AxxHpgt/dCkWI6ljYDnxgPLwG0a Oasm94BjZc6vZwf1opFZUKsjOAAxRxNZyjUJKe4UZVuMTk6zo27Nt3LMnc0FO47v FcOjRyquvgNOS818irVHUf12waDx8gszKxQTTtFxU5/ePB2jZmhP6oXSe4K/LG5T +WBRPDrHiGPhCzJRzm9BP0lTnGCAj3o9W90STZa65RK7IaYpC8TB35JTBEbrrNCp w6lzd74LnNEp5eMlKDnXzUAgAH0yzCQeMl7t33QCdYx2hRs2wtTQSjGfAiNmj/WW Vl5Jn+2jCDnRLenKHwVRFsBX2e0BiRWt/i9Y8fjorLCXVj4z+7yW6DawdLkJorEo p3v5ILwfC7hVx4jHSnOgZ65L9s8EQdVr1ckN9243yta7rNgwfcqb60ILMFF1BRk/ 0V7wCL+68UwwiQDvyMOQuqkysKLSDCLb7BFcyA7j6KG+5hpsREstFX2wK1yKeraz 5xGrFy8tfAaeBMIQ17gvFSp/suc9DYO0ICK2BISzq+F+ZiAKsjMYOBNdH/h0zobQ HTHs37+/QLMomGEGKZMWi0dShU2J5mNRQu3Hhxl3hHDVbt5CeJBb26aQcQrFz69W zE3GNvmJosh6leayjtI9P2A6iEkEGBECAAkFAkj3uiACGwwACgkQFlMNXpIPXGWp TACbBS+Up3RpfYVfd63c1cDdlru13pQAn3NQy/SN858MkxN+zym86UBgOad2 =CMiZ -----END PGP PUBLIC KEY BLOCK----- Conley Owens <cco3@android.com> -----BEGIN PGP PUBLIC KEY BLOCK----- Version: GnuPG v1.4.11 (GNU/Linux) mQENBFHRvc8BCADFg45Xx/y6QDC+T7Y/gGc7vx0ww7qfOwIKlAZ9xG3qKunMxo+S hPCnzEl3cq+6I1Ww/ndop/HB3N3toPXRCoN8Vs4/Hc7by+SnaLFnacrm+tV5/OgT V37Lzt8lhay1Kl+YfpFwHYYpIEBLFV9knyfRXS/428W2qhdzYfvB15/AasRmwmor py4NIzSs8UD/SPr1ihqNCdZM76+MQyN5HMYXW/ALZXUFG0pwluHFA7hrfPG74i8C zMiP7qvMWIl/r/jtzHioH1dRKgbod+LZsrDJ8mBaqsZaDmNJMhss9g76XvfMyLra 9DI9/iFuBpGzeqBv0hwOGQspLRrEoyTeR6n1ABEBAAG0H0NvbmxleSBPd2VucyA8 Y2NvM0BhbmRyb2lkLmNvbT6JATgEEwECACIFAlHRvc8CGwMGCwkIBwMCBhUIAgkK CwQWAgMBAh4BAheAAAoJEGe35EhpKzgsP6AIAJKJmNtn4l7hkYHKHFSo3egb6RjQ zEIP3MFTcu8HFX1kF1ZFbrp7xqurLaE53kEkKuAAvjJDAgI8mcZHP1JyplubqjQA xvv84gK+OGP3Xk+QK1ZjUQSbjOpjEiSZpRhWcHci3dgOUH4blJfByHw25hlgHowd a/2PrNKZVcJ92YienaxxGjcXEUcd0uYEG2+rwllQigFcnMFDhr9B71MfalRHjFKE fmdoypqLrri61YBc59P88Rw2/WUpTQjgNubSqa3A2+CKdaRyaRw+2fdF4TdR0h8W zbg+lbaPtJHsV+3mJC7fq26MiJDRJa5ZztpMn8su20gbLgi2ShBOaHAYDDi5AQ0E UdG9zwEIAMoOBq+QLNozAhxOOl5GL3StTStGRgPRXINfmViTsihrqGCWBBUfXlUE OytC0mYcrDUQev/8ToVoyqw+iGSwDkcSXkrEUCKFtHV/GECWtk1keyHgR10YKI1R mquSXoubWGqPeG1PAI74XWaRx8UrL8uCXUtmD8Q5J7mDjKR5NpxaXrwlA0bKsf2E Gp9tu1kKauuToZhWHMRMqYSOGikQJwWSFYKT1KdNcOXLQF6+bfoJ6sjVYdwfmNQL Ixn8QVhoTDedcqClSWB17VDEFDFa7MmqXZz2qtM3X1R/MUMHqPtegQzBGNhRdnI2 V45+1Nnx/uuCxDbeI4RbHzujnxDiq70AEQEAAYkBHwQYAQIACQUCUdG9zwIbDAAK CRBnt+RIaSs4LNVeB/0Y2pZ8I7gAAcEM0Xw8drr4omg2fUoK1J33ozlA/RxeA/lJ I3KnyCDTpXuIeBKPGkdL8uMATC9Z8DnBBajRlftNDVZS3Hz4G09G9QpMojvJkFJV By+01Flw/X+eeN8NpqSuLV4W+AjEO8at/VvgKr1AFvBRdZ7GkpI1o6DgPe7ZqX+1 dzQZt3e13W0rVBb/bUgx9iSLoeWP3aq/k+/GRGOR+S6F6BBSl0SQ2EF2+dIywb1x JuinEP+AwLAUZ1Bsx9ISC0Agpk2VeHXPL3FGhroEmoMvBzO0kTFGyoeT7PR/BfKv +H/g3HsL2LOB9uoIm8/5p2TTU5ttYCXMHhQZ81AY =AUp4 -----END PGP PUBLIC KEY BLOCK----- """ GIT = 'git' # our git command MIN_GIT_VERSION = (1, 7, 2) # minimum supported git version repodir = '.repo' # name of repo's private directory S_repo = 'repo' # special repo repository S_manifests = 'manifests' # special manifest repository REPO_MAIN = S_repo + '/main.py' # main script MIN_PYTHON_VERSION = (2, 6) # minimum supported python version import errno import optparse import os import re import stat import subprocess import sys if sys.version_info[0] == 3: import urllib.request import urllib.error else: import imp import urllib2 urllib = imp.new_module('urllib') urllib.request = urllib2 urllib.error = urllib2 def _print(*objects, **kwargs): sep = kwargs.get('sep', ' ') end = kwargs.get('end', '\n') out = kwargs.get('file', sys.stdout) out.write(sep.join(objects) + end) # Python version check ver = sys.version_info if ver[0] == 3: _print('warning: Python 3 support is currently experimental. YMMV.\n' 'Please use Python 2.6 - 2.7 instead.', file=sys.stderr) if (ver[0], ver[1]) < MIN_PYTHON_VERSION: _print('error: Python version %s unsupported.\n' 'Please use Python 2.6 - 2.7 instead.' % sys.version.split(' ')[0], file=sys.stderr) sys.exit(1) home_dot_repo = os.path.expanduser('~/.repoconfig') gpg_dir = os.path.join(home_dot_repo, 'gnupg') extra_args = [] init_optparse = optparse.OptionParser(usage="repo init -u url [options]") # Logging group = init_optparse.add_option_group('Logging options') group.add_option('-q', '--quiet', dest="quiet", action="store_true", default=False, help="be quiet") # Manifest group = init_optparse.add_option_group('Manifest options') group.add_option('-u', '--manifest-url', dest='manifest_url', help='manifest repository location', metavar='URL') group.add_option('-b', '--manifest-branch', dest='manifest_branch', help='manifest branch or revision', metavar='REVISION') group.add_option('-m', '--manifest-name', dest='manifest_name', help='initial manifest file', metavar='NAME.xml') group.add_option('--mirror', dest='mirror', action='store_true', help='create a replica of the remote repositories ' 'rather than a client working directory') group.add_option('--reference', dest='reference', help='location of mirror directory', metavar='DIR') group.add_option('--depth', type='int', default=None, dest='depth', help='create a shallow clone with given depth; see git clone') group.add_option('--archive', dest='archive', action='store_true', help='checkout an archive instead of a git repository for ' 'each project. See git archive.') group.add_option('-g', '--groups', dest='groups', default='default', help='restrict manifest projects to ones with specified ' 'group(s) [default|all|G1,G2,G3|G4,-G5,-G6]', metavar='GROUP') group.add_option('-p', '--platform', dest='platform', default="auto", help='restrict manifest projects to ones with a specified ' 'platform group [auto|all|none|linux|darwin|...]', metavar='PLATFORM') # Tool group = init_optparse.add_option_group('repo Version options') group.add_option('--repo-url', dest='repo_url', help='repo repository location', metavar='URL') group.add_option('--repo-branch', dest='repo_branch', help='repo branch or revision', metavar='REVISION') group.add_option('--no-repo-verify', dest='no_repo_verify', action='store_true', help='do not verify repo source code') # Other group = init_optparse.add_option_group('Other options') group.add_option('--config-name', dest='config_name', action="store_true", default=False, help='Always prompt for name/e-mail') class CloneFailure(Exception): """Indicate the remote clone of repo itself failed. """ def _Init(args): """Installs repo by cloning it over the network. """ opt, args = init_optparse.parse_args(args) if args: init_optparse.print_usage() sys.exit(1) url = opt.repo_url if not url: url = REPO_URL extra_args.append('--repo-url=%s' % url) branch = opt.repo_branch if not branch: branch = REPO_REV extra_args.append('--repo-branch=%s' % branch) if branch.startswith('refs/heads/'): branch = branch[len('refs/heads/'):] if branch.startswith('refs/'): _print("fatal: invalid branch name '%s'" % branch, file=sys.stderr) raise CloneFailure() try: os.mkdir(repodir) except OSError as e: if e.errno != errno.EEXIST: _print('fatal: cannot make %s directory: %s' % (repodir, e.strerror), file=sys.stderr) # Don't raise CloneFailure; that would delete the # name. Instead exit immediately. # sys.exit(1) _CheckGitVersion() try: if NeedSetupGnuPG(): can_verify = SetupGnuPG(opt.quiet) else: can_verify = True dst = os.path.abspath(os.path.join(repodir, S_repo)) _Clone(url, dst, opt.quiet) if can_verify and not opt.no_repo_verify: rev = _Verify(dst, branch, opt.quiet) else: rev = 'refs/remotes/origin/%s^0' % branch _Checkout(dst, branch, rev, opt.quiet) except CloneFailure: if opt.quiet: _print('fatal: repo init failed; run without --quiet to see why', file=sys.stderr) raise def ParseGitVersion(ver_str): if not ver_str.startswith('git version '): return None num_ver_str = ver_str[len('git version '):].strip().split('-')[0] to_tuple = [] for num_str in num_ver_str.split('.')[:3]: if num_str.isdigit(): to_tuple.append(int(num_str)) else: to_tuple.append(0) return tuple(to_tuple) def _CheckGitVersion(): cmd = [GIT, '--version'] try: proc = subprocess.Popen(cmd, stdout=subprocess.PIPE) except OSError as e: _print(file=sys.stderr) _print("fatal: '%s' is not available" % GIT, file=sys.stderr) _print('fatal: %s' % e, file=sys.stderr) _print(file=sys.stderr) _print('Please make sure %s is installed and in your path.' % GIT, file=sys.stderr) raise CloneFailure() ver_str = proc.stdout.read().strip() proc.stdout.close() proc.wait() ver_act = ParseGitVersion(ver_str) if ver_act is None: _print('error: "%s" unsupported' % ver_str, file=sys.stderr) raise CloneFailure() if ver_act < MIN_GIT_VERSION: need = '.'.join(map(str, MIN_GIT_VERSION)) _print('fatal: git %s or later required' % need, file=sys.stderr) raise CloneFailure() def NeedSetupGnuPG(): if not os.path.isdir(home_dot_repo): return True kv = os.path.join(home_dot_repo, 'keyring-version') if not os.path.exists(kv): return True kv = open(kv).read() if not kv: return True kv = tuple(map(int, kv.split('.'))) if kv < KEYRING_VERSION: return True return False def SetupGnuPG(quiet): try: os.mkdir(home_dot_repo) except OSError as e: if e.errno != errno.EEXIST: _print('fatal: cannot make %s directory: %s' % (home_dot_repo, e.strerror), file=sys.stderr) sys.exit(1) try: os.mkdir(gpg_dir, stat.S_IRWXU) except OSError as e: if e.errno != errno.EEXIST: _print('fatal: cannot make %s directory: %s' % (gpg_dir, e.strerror), file=sys.stderr) sys.exit(1) env = os.environ.copy() env['GNUPGHOME'] = gpg_dir.encode() cmd = ['gpg', '--import'] try: proc = subprocess.Popen(cmd, env = env, stdin = subprocess.PIPE) except OSError as e: if not quiet: _print('warning: gpg (GnuPG) is not available.', file=sys.stderr) _print('warning: Installing it is strongly encouraged.', file=sys.stderr) _print(file=sys.stderr) return False proc.stdin.write(MAINTAINER_KEYS) proc.stdin.close() if proc.wait() != 0: _print('fatal: registering repo maintainer keys failed', file=sys.stderr) sys.exit(1) _print() fd = open(os.path.join(home_dot_repo, 'keyring-version'), 'w') fd.write('.'.join(map(str, KEYRING_VERSION)) + '\n') fd.close() return True def _SetConfig(local, name, value): """Set a git configuration option to the specified value. """ cmd = [GIT, 'config', name, value] if subprocess.Popen(cmd, cwd = local).wait() != 0: raise CloneFailure() def _InitHttp(): handlers = [] mgr = urllib.request.HTTPPasswordMgrWithDefaultRealm() try: import netrc n = netrc.netrc() for host in n.hosts: p = n.hosts[host] mgr.add_password(p[1], 'http://%s/' % host, p[0], p[2]) mgr.add_password(p[1], 'https://%s/' % host, p[0], p[2]) except: pass handlers.append(urllib.request.HTTPBasicAuthHandler(mgr)) handlers.append(urllib.request.HTTPDigestAuthHandler(mgr)) if 'http_proxy' in os.environ: url = os.environ['http_proxy'] handlers.append(urllib.request.ProxyHandler({'http': url, 'https': url})) if 'REPO_CURL_VERBOSE' in os.environ: handlers.append(urllib.request.HTTPHandler(debuglevel=1)) handlers.append(urllib.request.HTTPSHandler(debuglevel=1)) urllib.request.install_opener(urllib.request.build_opener(*handlers)) def _Fetch(url, local, src, quiet): if not quiet: _print('Get %s' % url, file=sys.stderr) cmd = [GIT, 'fetch'] if quiet: cmd.append('--quiet') err = subprocess.PIPE else: err = None cmd.append(src) cmd.append('+refs/heads/*:refs/remotes/origin/*') cmd.append('refs/tags/*:refs/tags/*') proc = subprocess.Popen(cmd, cwd = local, stderr = err) if err: proc.stderr.read() proc.stderr.close() if proc.wait() != 0: raise CloneFailure() def _DownloadBundle(url, local, quiet): if not url.endswith('/'): url += '/' url += 'clone.bundle' proc = subprocess.Popen( [GIT, 'config', '--get-regexp', 'url.*.insteadof'], cwd = local, stdout = subprocess.PIPE) for line in proc.stdout: m = re.compile(r'^url\.(.*)\.insteadof (.*)$').match(line) if m: new_url = m.group(1) old_url = m.group(2) if url.startswith(old_url): url = new_url + url[len(old_url):] break proc.stdout.close() proc.wait() if not url.startswith('http:') and not url.startswith('https:'): return False dest = open(os.path.join(local, '.git', 'clone.bundle'), 'w+b') try: try: r = urllib.request.urlopen(url) except urllib.error.HTTPError as e: if e.code in [403, 404]: return False _print('fatal: Cannot get %s' % url, file=sys.stderr) _print('fatal: HTTP error %s' % e.code, file=sys.stderr) raise CloneFailure() except urllib.error.URLError as e: _print('fatal: Cannot get %s' % url, file=sys.stderr) _print('fatal: error %s' % e.reason, file=sys.stderr) raise CloneFailure() try: if not quiet: _print('Get %s' % url, file=sys.stderr) while True: buf = r.read(8192) if buf == '': return True dest.write(buf) finally: r.close() finally: dest.close() def _ImportBundle(local): path = os.path.join(local, '.git', 'clone.bundle') try: _Fetch(local, local, path, True) finally: os.remove(path) def _Clone(url, local, quiet): """Clones a git repository to a new subdirectory of repodir """ try: os.mkdir(local) except OSError as e: _print('fatal: cannot make %s directory: %s' % (local, e.strerror), file=sys.stderr) raise CloneFailure() cmd = [GIT, 'init', '--quiet'] try: proc = subprocess.Popen(cmd, cwd = local) except OSError as e: _print(file=sys.stderr) _print("fatal: '%s' is not available" % GIT, file=sys.stderr) _print('fatal: %s' % e, file=sys.stderr) _print(file=sys.stderr) _print('Please make sure %s is installed and in your path.' % GIT, file=sys.stderr) raise CloneFailure() if proc.wait() != 0: _print('fatal: could not create %s' % local, file=sys.stderr) raise CloneFailure() _InitHttp() _SetConfig(local, 'remote.origin.url', url) _SetConfig(local, 'remote.origin.fetch', '+refs/heads/*:refs/remotes/origin/*') if _DownloadBundle(url, local, quiet): _ImportBundle(local) else: _Fetch(url, local, 'origin', quiet) def _Verify(cwd, branch, quiet): """Verify the branch has been signed by a tag. """ cmd = [GIT, 'describe', 'origin/%s' % branch] proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd = cwd) cur = proc.stdout.read().strip() proc.stdout.close() proc.stderr.read() proc.stderr.close() if proc.wait() != 0 or not cur: _print(file=sys.stderr) _print("fatal: branch '%s' has not been signed" % branch, file=sys.stderr) raise CloneFailure() m = re.compile(r'^(.*)-[0-9]{1,}-g[0-9a-f]{1,}$').match(cur) if m: cur = m.group(1) if not quiet: _print(file=sys.stderr) _print("info: Ignoring branch '%s'; using tagged release '%s'" % (branch, cur), file=sys.stderr) _print(file=sys.stderr) env = os.environ.copy() env['GNUPGHOME'] = gpg_dir.encode() cmd = [GIT, 'tag', '-v', cur] proc = subprocess.Popen(cmd, stdout = subprocess.PIPE, stderr = subprocess.PIPE, cwd = cwd, env = env) out = proc.stdout.read() proc.stdout.close() err = proc.stderr.read() proc.stderr.close() if proc.wait() != 0: _print(file=sys.stderr) _print(out, file=sys.stderr) _print(err, file=sys.stderr) _print(file=sys.stderr) raise CloneFailure() return '%s^0' % cur def _Checkout(cwd, branch, rev, quiet): """Checkout an upstream branch into the repository and track it. """ cmd = [GIT, 'update-ref', 'refs/heads/default', rev] if subprocess.Popen(cmd, cwd = cwd).wait() != 0: raise CloneFailure() _SetConfig(cwd, 'branch.default.remote', 'origin') _SetConfig(cwd, 'branch.default.merge', 'refs/heads/%s' % branch) cmd = [GIT, 'symbolic-ref', 'HEAD', 'refs/heads/default'] if subprocess.Popen(cmd, cwd = cwd).wait() != 0: raise CloneFailure() cmd = [GIT, 'read-tree', '--reset', '-u'] if not quiet: cmd.append('-v') cmd.append('HEAD') if subprocess.Popen(cmd, cwd = cwd).wait() != 0: raise CloneFailure() def _FindRepo(): """Look for a repo installation, starting at the current directory. """ curdir = os.getcwd() repo = None olddir = None while curdir != '/' \ and curdir != olddir \ and not repo: repo = os.path.join(curdir, repodir, REPO_MAIN) if not os.path.isfile(repo): repo = None olddir = curdir curdir = os.path.dirname(curdir) return (repo, os.path.join(curdir, repodir)) class _Options: help = False def _ParseArguments(args): cmd = None opt = _Options() arg = [] for i in range(len(args)): a = args[i] if a == '-h' or a == '--help': opt.help = True elif not a.startswith('-'): cmd = a arg = args[i + 1:] break return cmd, opt, arg def _Usage(): _print( """usage: repo COMMAND [ARGS] repo is not yet installed. Use "repo init" to install it here. The most commonly used repo commands are: init Install repo in the current working directory help Display detailed help on a command For access to the full online help, install repo ("repo init"). """, file=sys.stderr) sys.exit(1) def _Help(args): if args: if args[0] == 'init': init_optparse.print_help() sys.exit(0) else: _print("error: '%s' is not a bootstrap command.\n" ' For access to online help, install repo ("repo init").' % args[0], file=sys.stderr) else: _Usage() sys.exit(1) def _NotInstalled(): _print('error: repo is not installed. Use "repo init" to install it here.', file=sys.stderr) sys.exit(1) def _NoCommands(cmd): _print("""error: command '%s' requires repo to be installed first. Use "repo init" to install it here.""" % cmd, file=sys.stderr) sys.exit(1) def _RunSelf(wrapper_path): my_dir = os.path.dirname(wrapper_path) my_main = os.path.join(my_dir, 'main.py') my_git = os.path.join(my_dir, '.git') if os.path.isfile(my_main) and os.path.isdir(my_git): for name in ['git_config.py', 'project.py', 'subcmds']: if not os.path.exists(os.path.join(my_dir, name)): return None, None return my_main, my_git return None, None def _SetDefaultsTo(gitdir): global REPO_URL global REPO_REV REPO_URL = gitdir proc = subprocess.Popen([GIT, '--git-dir=%s' % gitdir, 'symbolic-ref', 'HEAD'], stdout = subprocess.PIPE, stderr = subprocess.PIPE) REPO_REV = proc.stdout.read().strip() proc.stdout.close() proc.stderr.read() proc.stderr.close() if proc.wait() != 0: _print('fatal: %s has no current branch' % gitdir, file=sys.stderr) sys.exit(1) def main(orig_args): repo_main, rel_repo_dir = _FindRepo() cmd, opt, args = _ParseArguments(orig_args) wrapper_path = os.path.abspath(__file__) my_main, my_git = _RunSelf(wrapper_path) if not repo_main: if opt.help: _Usage() if cmd == 'help': _Help(args) if not cmd: _NotInstalled() if cmd == 'init': if my_git: _SetDefaultsTo(my_git) try: _Init(args) except CloneFailure: for root, dirs, files in os.walk(repodir, topdown=False): for name in files: os.remove(os.path.join(root, name)) for name in dirs: os.rmdir(os.path.join(root, name)) os.rmdir(repodir) sys.exit(1) repo_main, rel_repo_dir = _FindRepo() else: _NoCommands(cmd) if my_main: repo_main = my_main ver_str = '.'.join(map(str, VERSION)) me = [sys.executable, repo_main, '--repo-dir=%s' % rel_repo_dir, '--wrapper-version=%s' % ver_str, '--wrapper-path=%s' % wrapper_path, '--'] me.extend(orig_args) me.extend(extra_args) try: os.execv(sys.executable, me) except OSError as e: _print("fatal: unable to start %s" % repo_main, file=sys.stderr) _print("fatal: %s" % e, file=sys.stderr) sys.exit(148) if __name__ == '__main__': main(sys.argv[1:])

[ "yuanjianye@126.com" ]

yuanjianye@126.com

399f348277fb3b7163ca3a4c76f76af5f25d109d

3366e2c70dd863951a3386aa41bf0a00c8b79178

/process_iemocap.py

d2f454b9a90b4d90a42fcc1713a1da822ba48c98

[]

no_license

mia2mia/emotionrecognition

5ec5d9e220dbfe42f2ab926be035c40553f32951

d1915b00f316a2b516050e772e57436c27325e53

refs/heads/master

2022-07-16T16:38:17.816397

2018-08-16T20:02:07

263,222,665

0

null

UTF-8

Python

false

5,659

py

import argparse import os from sklearn.utils import shuffle import numpy as np #TODO: import the correct feature extraction function from audio_features import extract_logmel as extract_feat def parse_args(): """Returns dictionary containing CLI arguments""" ap = argparse.ArgumentParser() ap.add_argument("-p", "--data-path", required=True, help="Path to the IEMOCAP processed dataset") ap.add_argument("-o", "--out-path", required=True, help="Path to the output directory") args = vars(ap.parse_args()) return args def parse_dialog_file(dialog_file_path, x, y): """Function to parse the Evaluation file per dialog Evaluation file structure: % [START_TIME - END_TIME] TURN_NAME EMOTION [V, A, D] [6.2901 - 8.2357] Ses01F_impro01_F000 neu [2.5000, 2.5000, 2.5000] C-E2: Neutral; () C-E3: Neutral; () C-E4: Neutral; () C-F1: Neutral; (curious) A-E3: val 3; act 2; dom 2; () A-E4: val 2; act 3; dom 3; (mildly aggravated but staying polite, attitude) A-F1: val 3; act 2; dom 1; () [10.0100 - 11.3925] Ses01F_impro01_F001 neu [2.5000, 2.5000, 2.5000] ... """ global target_emotions dialog_wav_base_path = os.path.splitext(dialog_file_path)[0] with open(dialog_file_path, 'r') as dialog_file: # skip the headers _ = dialog_file.readline() _ = dialog_file.readline() # read the line containing frame and emotion and skip till the next line = dialog_file.readline().strip() while line: wavfile, emotion = line.split('\t')[1:3] if emotion in target_emotions: wav_path = os.path.join(dialog_wav_base_path, wavfile+'.wav') print (wav_path, emotion) # extract features and append it to the list features = extract_feat(wav_path) # shape (M, 40) if features is not None: x.append(features) y.append(target_emotions[emotion]) # skip all lines till the blank line while line != '\n': line = dialog_file.readline() # read in the next line containing frame and emotion line = dialog_file.readline().strip() def walk_through_sessions(x, y, data_path, out_path, sessions): """Function to iterate recursively over all session annotations, extract features, and append the features/labels to the x,y lists. """ for session in sessions: session_path = os.path.join(data_path, session) for dirpath, dnames, fnames in os.walk(session_path): for f in fnames: if f.endswith(".txt"): dialog_file_path = os.path.join(dirpath, f) parse_dialog_file(dialog_file_path, x, y) def compute_mean_std(x_train, y_train): """Function to compute mean and std of feature vectors from neutral emotions""" # warning: not used global mean, std, target_emotions neutral_examples = np.vstack(x_train[np.where(y_train==target_emotions['neu'])]) mean = np.mean(neutral_examples, axis=0) std = np.std(neutral_examples, axis=0) print (mean.shape) print (mean) print (std.shape) print (std) def normalize_data(x, mean, std): """function to normalize X by subtracting mean and dividing by std""" for i in range(len(x)): x[i] = (x[i] - mean) / std def create_training_set(data_path, out_path, sessions): """wrapper function to create training set""" global mean, std print ("Processing training set...") x_train = [] y_train = [] walk_through_sessions(x_train, y_train, data_path, out_path, sessions) print (len(x_train), len(y_train)) """Lines to perform external normalization. Not used. x_train = np.array(x_train) y_train = np.array(y_train) compute_mean_std(x_train, y_train) print ("sample before normalization", x_train[0][0]) normalize_data(x_train, mean, std) print ("sample after normalization", x_train[0][0]) """ np.save(os.path.join(out_path,'x_train.npy'), x_train) np.save(os.path.join(out_path,'y_train.npy'), y_train) def create_testval_set(data_path, out_path, sessions): global mean, std print ("Processing test/val set...") x = [] y = [] walk_through_sessions(x, y, data_path, out_path, sessions) # normalize_data(x, mean, std) n_val = int(len(y)/2) x,y = shuffle(x,y) x_val = x[:n_val] y_val = y[:n_val] x_test = x[n_val:] y_test = y[n_val:] print (len(x_val), len(y_val), len(x_test), len(y_test)) np.save(os.path.join(out_path,'x_val.npy'), x_val) np.save(os.path.join(out_path,'y_val.npy'), y_val) np.save(os.path.join(out_path,'x_test.npy'), x_test) np.save(os.path.join(out_path,'y_test.npy'), y_test) if __name__ == '__main__': args = parse_args() data_path = args["data_path"] out_path = args["out_path"] if not os.path.exists(data_path): raise("Path to Dataset is incorrect or doesn't exist") if not os.path.exists(out_path): os.makedirs(out_path) # sessions used for training and testing sessions_train = ['Session1', 'Session2', 'Session3', 'Session4'] sessions_val = ['Session5'] target_emotions = { 'ang':0, 'hap':1, 'sad':2, 'neu':3, } # target_emotions = {'ang':0, 'hap':1, 'exc':2, 'sad':3, 'fru':4, 'neu':5,} mean = None std = None create_training_set(data_path, out_path, sessions_train) create_testval_set(data_path, out_path, sessions_val)

[ "deepc94@gmail.com" ]

deepc94@gmail.com

bacc0ed50288fc9e1318a109db7351883c306837

f07a42f652f46106dee4749277d41c302e2b7406

/Data Set/bug-fixing-5/388510f379bf268c9fa7e135007fcf1295a5e82f-<read_sysctl_file>-fix.py

5944de126f95a653371ecd488b692d83c9600aee

[]

no_license

wsgan001/PyFPattern

e0fe06341cc5d51b3ad0fe29b84098d140ed54d1

cc347e32745f99c0cd95e79a18ddacc4574d7faa

refs/heads/main

2023-08-25T23:48:26.112133

2021-10-23T14:11:22

null

0

null

UTF-8

Python

false

624

py

def read_sysctl_file(self): lines = [] if os.path.isfile(self.sysctl_file): try: f = open(self.sysctl_file, 'r') lines = f.readlines() f.close() except IOError: e = get_exception() self.module.fail_json(msg=('Failed to open %s: %s' % (self.sysctl_file, str(e)))) for line in lines: line = line.strip() self.file_lines.append(line) if ((not line) or line.startswith('#')): continue (k, v) = line.split('=', 1) k = k.strip() v = v.strip() self.file_values[k] = v.strip()

[ "dg1732004@smail.nju.edu.cn" ]

dg1732004@smail.nju.edu.cn

603b373c5b40981b400793fb84c38b2fe0e80722

53fab060fa262e5d5026e0807d93c75fb81e67b9

/backup/user_321/ch87_2020_05_06_17_53_40_771914.py

9e76ed669a24108340ce5d59e9ea300a2bd1138d

[]

no_license

gabriellaec/desoft-analise-exercicios

b77c6999424c5ce7e44086a12589a0ad43d6adca

01940ab0897aa6005764fc220b900e4d6161d36b

refs/heads/main

2023-01-31T17:19:42.050628

2020-12-16T05:21:31

306,735,108

0

null

UTF-8

Python

false

199

py

with open('churras.txt','r') as texto: conteudo = texto.read n = conteudo.split(',') print (n) del n[0,:,3] valor = 0 i = 0 while i <= len(n): valor += n[i]*n[i+1] i += 2 print(valor)

[ "you@example.com" ]

you@example.com

1c7c47ec1ae65cc25478853c5ec03cb378ba9ce6

3a17482f2229325dda7dfdf74f51b18a69faeb17

/setup.py

5f3688acdef48ff07d79ffb7decf00b496f6cf1d

[]

no_license

Albertomanas/ApiRest_gildedRose

067b4031d455d40053488f713048147dec5edf14

430000567500fed4b6e7e745cf08caccf25c1c2b

refs/heads/master

2022-04-10T10:25:34.205277

2020-03-27T04:12:18

247,736,498

0

null

UTF-8

Python

false

1,440

py

import setuptools with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name="API REST GildedRose", version="0.0.1", author="dfleta", author_email="gelpiorama@gmail.com", description="API REST Flask example", long_description=long_description, long_description_content_type="text/markdown", url="https://github.com/dfleta/api-rest-gildedrose.git", packages=setuptools.find_packages(), include_package_data=True, classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ], python_requires='>=3.6', install_requires=[ 'aniso8601==8.0.0', 'astroid==2.3.3', 'Click==7.0', 'dnspython==1.16.0', 'Flask==1.1.1', 'Flask-Cors==3.0.8', 'flask-mongoengine==0.9.5', 'Flask-PyMongo==2.3.0', 'Flask-RESTful==0.3.7', 'Flask-WTF==0.14.2', 'isort==4.3.21', 'itsdangerous==1.1.0', 'Jinja2==2.11.1', 'lazy-object-proxy==1.4.3', 'MarkupSafe==1.1.1', 'mccabe==0.6.1', 'mongoengine==0.19.1', 'pycodestyle==2.5.0', 'pylint==2.4.4', 'pymongo==3.10.1', 'pytz==2019.3', 'six==1.14.0', 'typed-ast==1.4.0', 'Werkzeug==1.0.0', 'wrapt==1.11.2', 'WTForms==2.2.1', ], )

[ "amanas@cifpfbmoll.eu" ]

amanas@cifpfbmoll.eu

259d2cd92a32309fc550fed0d26e1561a84b8007

e6cd7bc1214ae7a44c3cb789a360e9a840eb8034

/week2/practical3_approximate_matching.py

fb11fdab32e9342cf35b834f063f2b84c27f9179

[]

no_license

MariaTroj/DNA_sequencing_algo

3e93546645c9e96966aeeecacd36c5c06e9541bd

11a45bcdd4d5df3e96ab2ef245b613dca0aa0acf

refs/heads/master

2023-09-03T15:13:44.292655

2021-10-19T11:30:20

null

0

null

UTF-8

Python

false

1,254

py

from practical1_boyer_moore import * def approximate_match(pattern: str, text: str, n: int): segment_length = int(round(len(pattern) / (n + 1))) all_matches = set() for i in range(n+1): start = i*segment_length end = min((i+1) * segment_length, len(pattern)) p_bm = BoyerMoore(pattern[start:end], alphabet='ACGT') matches = boyer_moore(pattern[start:end], p_bm, text) # Extend matching segments to see if whole p matches for m in matches: if m < start or m-start+len(pattern) > len(text): continue mismatches = 0 for j in range(0, start): if not pattern[j] == text[m - start + j]: mismatches += 1 if mismatches > n: break for j in range(end, len(pattern)): if not pattern[j] == text[m - start + j]: mismatches += 1 if mismatches > n: break if mismatches <= n: all_matches.add(m - start) return list(all_matches) if __name__ == '__main__': pattern = 'AACTTG' text = 'CACTTAATTTG' print(approximate_match(pattern, text, 2))

[ "maria.a.mierzwa@gmail.com" ]

maria.a.mierzwa@gmail.com

5dbf5f0adba3a36a978555d503f078233ec24a42

ec7359f3c1739d68ee4d18351ee048d7c42d9e5c

/regression/samples/overfitting.py

0c616ec001e19f84937dd3d00b0c0a63f52ef596

[]

no_license

guilhermevarela/machinelearning

381e4db33f6500f07e3886754e94befed9610b84

3af1514c6f6916f51c242648ee185b417736a023

refs/heads/master

2020-12-02T19:33:52.426149

2019-04-02T21:45:12

96,360,194

0

null

UTF-8

Python

false

3,670

py

''' Created on May 11, 2017 @author: Varela ''' # notes for this course can be found at: # https://deeplearningcourses.com/c/data-science-linear-regression-in-python # https://www.udemy.com/data-science-linear-regression-in-python import numpy as np import matplotlib.pyplot as plt import aux as ax from regress import lin, r2 #make up some data and plot it N = 100 X = np.linspace(0, 6*np.pi, N) Y = np.sin(X) plt.plot(X,Y) plt.show() # def fit(X,Y): # return np.linalg.solve(X.T.dot(X), X.T.dot(Y)) def fit_and_display(X,Y, sample, deg): N = len(X) trainidx = np.random.choice(N, sample) Xtrain = X[trainidx] Ytrain = Y[trainidx] plt.scatter(Xtrain, Ytrain) plt.show() #fit polynomial # Xtrain_poly = ax.polyfy(Xtrain, deg) X_poly = ax.polyfy(X, deg) Xtrain_poly = X_poly[trainidx] # w = fit(Xtrain_poly, Ytrain) #Compute redisiduals w, resid0 = lin(Xtrain_poly, Ytrain) resid1 = r2(w, X_poly, Y) print ("degree %d .: in-sample %.4f out sample %.4f" % (deg ,resid0, resid1)) #display the polynomial # X_poly = ax.polyfy(X, deg) Y_hat = X_poly.dot(w) plt.plot(X,Y) plt.plot(X,Y_hat) plt.scatter(Xtrain, Ytrain) plt.title("deg= %d" % deg) plt.show() for deg in (2,3,4,5,6,7,8,9): fit_and_display(X, Y, 10, deg) #LAZY programmers's # import numpy as np # import matplotlib.pyplot as plt # # # def make_poly(X, deg): # n = len(X) # data = [np.ones(n)] # for d in xrange(deg): # data.append(X**(d+1)) # return np.vstack(data).T # # # def fit(X, Y): # return np.linalg.solve(X.T.dot(X), X.T.dot(Y)) # # # def fit_and_display(X, Y, sample, deg): # N = len(X) # train_idx = np.random.choice(N, sample) # Xtrain = X[train_idx] # Ytrain = Y[train_idx] # # plt.scatter(Xtrain, Ytrain) # plt.show() # # # fit polynomial # Xtrain_poly = make_poly(Xtrain, deg) # w = fit(Xtrain_poly, Ytrain) # # # display the polynomial # X_poly = make_poly(X, deg) # Y_hat = X_poly.dot(w) # plt.plot(X, Y) # plt.plot(X, Y_hat) # plt.scatter(Xtrain, Ytrain) # plt.title("deg = %d" % deg) # plt.show() # # # def get_mse(Y, Yhat): # d = Y - Yhat # return d.dot(d) / len(d) # # # def plot_train_vs_test_curves(X, Y, sample=20, max_deg=20): # N = len(X) # train_idx = np.random.choice(N, sample) # Xtrain = X[train_idx] # Ytrain = Y[train_idx] # # test_idx = [idx for idx in xrange(N) if idx not in train_idx] # # test_idx = np.random.choice(N, sample) # Xtest = X[test_idx] # Ytest = Y[test_idx] # # mse_trains = [] # mse_tests = [] # for deg in xrange(max_deg+1): # Xtrain_poly = make_poly(Xtrain, deg) # w = fit(Xtrain_poly, Ytrain) # Yhat_train = Xtrain_poly.dot(w) # mse_train = get_mse(Ytrain, Yhat_train) # # Xtest_poly = make_poly(Xtest, deg) # Yhat_test = Xtest_poly.dot(w) # mse_test = get_mse(Ytest, Yhat_test) # # mse_trains.append(mse_train) # mse_tests.append(mse_test) # # plt.plot(mse_trains, label="train mse") # plt.plot(mse_tests, label="test mse") # plt.legend() # plt.show() # # plt.plot(mse_trains, label="train mse") # plt.legend() # plt.show() # # if __name__ == "__main__": # # make up some data and plot it # N = 100 # X = np.linspace(0, 6*np.pi, N) # Y = np.sin(X) # # plt.plot(X, Y) # plt.show() # # for deg in (5, 6, 7, 8, 9): # fit_and_display(X, Y, 10, deg) # plot_train_vs_test_curves(X, Y) # '

[ "guilhermevarela@hotmail.com" ]

guilhermevarela@hotmail.com

f75e0ea9b0d03abe0bb91340f6a38c7ef5450902

02f565644b729c496bb4d802dfc6cb3a5db68ff1

/problems/sum_of_root_to_leaf_binary_numbers.py

bf25156100ee3f75041e482b2c02950d01d394ed

[]

no_license

saubhik/leetcode

99a854ad87272eb82b16f22408ee7314ba0db099

221f0cb3105e4ccaec40cd1d37b9d7d5e218c731

refs/heads/master

2023-04-27T03:11:03.565056

2021-05-17T07:55:22

275,324,914

3

1

null

2020-10-03T07:06:17

2020-06-27T07:48:37

Python

UTF-8

Python

false

949

py

# Definition for a binary tree node. class TreeNode: def __init__(self, val=0, left=None, right=None): self.val = val self.left = left self.right = right class Solution: # Normal DFS. # Time: O(H) = O(N) in worst case of degenerate tree. # Space: O(H) = O(N) in worst case of degenerate tree, due to recursion call stack. def sumRootToLeaf(self, root: TreeNode, running_sum: int = 0) -> int: if root is None: return 0 running_sum = running_sum * 2 + root.val left_sum, right_sum = 0, 0 if root.left is not None: left_sum = self.sumRootToLeaf(root=root.left, running_sum=running_sum) if root.right is not None: right_sum = self.sumRootToLeaf(root=root.right, running_sum=running_sum) if root.left is None and root.right is None: # leaf return running_sum return left_sum + right_sum

[ "saubhik.mukherjee@gmail.com" ]

saubhik.mukherjee@gmail.com

d76eac3ec6e96bc0e958803f72c4ec807b4ce5fb

9afbf779eb64a925e379bcd005798ec04c1b7232

/WebScraper/WebScraper.py

4df72dea9228643b671e7dc2c2cfcd61782770ce

[]

no_license

hoomanvhd/Broken_link_finder_in_a_page

1a1124f86163a66231b44bfa055ef6e0115dad68

d7a885021f33e2039057f7cd9d7c6267d3b1a87f

refs/heads/master

2021-05-17T04:14:16.126600

2020-03-27T18:49:49

250,616,917

1

0

null

UTF-8

Python

false

2,087

py

from bs4 import BeautifulSoup import requests from urllib.parse import urlparse, urljoin import urllib.request import colorama colorama.init() green = colorama.Fore.GREEN yellow = colorama.Fore.YELLOW gray = colorama.Fore.LIGHTBLACK_EX red = colorama.Fore.RED reset = colorama.Fore.RESET internal_urls = set() external_urls = set() def Check(url): try: request = urllib.request.Request(url) response = urllib.request.urlopen(request) if response.status in [204, 301, 308, 400, 401, 404, 408, 410, 500, 501, 502]: print(red + response.status + " - " + response.reason + " --> " + url) else: print(green + " no problem in --> " + url) except Exception as exception: print(yellow + " {}-{} ".format(exception, url)) pass def is_valid(url): parsed= urlparse(url) return bool(parsed.netloc) and bool(parsed.scheme) def get_links(url): urls = set() domain = urlparse(url).netloc soup = BeautifulSoup(requests.get(url).content, "html.parser") for a_tag in soup.findAll("a"): href = a_tag.attrs.get("href") if href == "" or href is None: continue href = urljoin(url, href) parsed_href = urlparse(href) href = parsed_href.scheme + ("://") + parsed_href.netloc + parsed_href.path if not is_valid(href): continue if href in internal_urls: continue if domain not in href: if href not in external_urls: Check(href) external_urls.add(href) continue Check(href) urls.add(href) internal_urls.add(href) return urls total_urls = 0 def crawl(url, max_urls=30): global total_urls total_urls += 1 links = get_links(url) for link in links: if total_urls > max_urls: break crawl(link, max_urls=max_urls) if __name__ == "__main__": URL = input("please enter a url: ") crawl(URL) print("Total links: ", len(external_urls) + len(internal_urls))

[ "mahmood.vahedi.94@gmail.com" ]

mahmood.vahedi.94@gmail.com

010571ff13652a4024b55546fc0ae60db508f76c

f781030f19b59d59817e4020b68f2bb1a293e629

/find_best_smoothing_value.py

99c7d5ce7dad4f0516cb4665822e306fcd245b6d

[]

no_license

xchenlp/simplified-lp-nlu-v2

9885e7d32184d6a1910931f59abaf1c2785146ac

e0b00c13f4b08ec9bbd632e58fb4d7fd6f68f4ab

refs/heads/master

2023-01-31T20:27:53.087258

2020-12-09T01:04:31

318,620,268

0

null

UTF-8

Python

false

2,963

py

from model import Model import os import pandas from sklearn.metrics import classification_report, f1_score, accuracy_score import argparse os.environ["CUDA_VISIBLE_DEVICES"] = '-1' # disable gpu. This is because on ca-gpu2, the cuDNN version is wrong for tensorflow def main(): f1s, accs = [], [] es = [0.01, 0.02, 0.03, 0.04, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5] for e in es: model = Model(word2vec_pkl_path='/data/cb_nlu_v2/vectors/wiki-news-300d-1M.pkl', config_path='config.yml', label_smoothing=e) test_model_path = f'/data/cb_nlu_test_model_early_stopping_with_label_smoothing' if not os.path.exists(test_model_path): os.makedirs(test_model_path) tr_set_path = f'/data/starter_pack_datasets/telco/tr_100_per_class.json' te_set_path = f'/data/starter_pack_datasets/telco/te.json' print("start training") ######################### training ######################### model.train(tr_set_path, test_model_path) ######################### training ends ######################### print("start testing") ######################### loading ######################### model.load(test_model_path) ######################### loading ends ######################### ######################### predicting ######################### df_te = pandas.read_json(te_set_path, lines=True) output = model.predict(list(df_te.text)) ######################### predicting ends ######################### ######################### evaluating the prediction ######################### ground_truths = list(df_te.intent) predictions = [x['label'] for x in output] threshold_predictions = [x['label'] if x['highestProb'] >= 0.6 else 'undefined' for x in output] df_te.loc[:, 'pred_intent'] = threshold_predictions df_te.loc[:, 'pred_score'] = [x['highestProb'] for x in output] df_te.loc[:, 'prob'] = [x['prob'] for x in output] #df_te.to_json(f'/data/cb_nlu_results/telco/te_preds_xentroy_smoothing_{e}.json', orient='records', lines=True) print(classification_report(y_true=ground_truths, y_pred=threshold_predictions)) f1s.append(f1_score(y_true=ground_truths, y_pred=threshold_predictions, average='macro')) accs.append(accuracy_score(y_true=ground_truths, y_pred=threshold_predictions)) ######################### evaluating the prediction ends ######################### max_f1 = max(f1s) max_acc = max(accs) max_f1_e = f1s.index(max_f1) max_acc_e = accs.index(max_acc) print(f'best macro f1 score {max_f1} is obtained at e={es[max_f1_e]}') print(f'best accuracy score {max_acc} is obtained at e={es[max_acc_e]}') if __name__ == '__main__': #parser = argparse.ArgumentParser() #parser.add_argument('--vertical', required=True, type=str) #args = parser.parse_args() # main(args) main()

[ "xchen@liveperson.com" ]

xchen@liveperson.com

6309417daf524ad0787d2defa32fb75f0a8a4672

3335d3c7b8eccaeb3a212a9247aa320de9306896

/arboretum/auditree/evidences/repo_metadata.py

f434980da977e6cbc785a2b2ba22413c0dc16ca8

[ "Apache-2.0" ]

permissive

syllogy/auditree-arboretum

6dc3f3e254bc2124b9a1e7860f29040241afb3ce

ed3cdfc7eca3c44591e606178aff00744d3e4e1e

refs/heads/main

2023-03-01T19:34:55.819952

2021-02-15T17:53:31

null

0

null

UTF-8

Python

false

2,202

py

# -*- mode:python; coding:utf-8 -*- # Copyright (c) 2020 IBM Corp. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Repository metadata evidence.""" import json from arboretum.common.constants import IGNORE_REPO_METADATA from compliance.evidence import RawEvidence from compliance.utils.data_parse import format_json class RepoMetadataEvidence(RawEvidence): """Repository metadata raw evidence class.""" @property def repo_size(self): """Provide the repo size.""" if self.content: rs_factory = { 'gh': self._get_gh_repo_size, 'gl': self._get_gl_repo_size, 'bb': self._get_bb_repo_size } if not hasattr(self, '_size'): self._size = rs_factory[self.name[:2]]() return self._size @property def filtered_content(self): """Provide evidence content minus the ignored fields as JSON.""" if self.content: if not hasattr(self, '_filtered_content'): metadata = json.loads(self.content) for field in IGNORE_REPO_METADATA[self.name[:2]]: try: metadata.pop(field) except KeyError: pass self._filtered_content = str(format_json(metadata)) return self._filtered_content def _get_gh_repo_size(self): return json.loads(self.content)['size'] def _get_gl_repo_size(self): raise NotImplementedError('Support for Gitlab coming soon...') def _get_bb_repo_size(self): raise NotImplementedError('Support for Bitbucket coming soon...')

[ "noreply@github.com" ]

syllogy.noreply@github.com

bfeef4f3238d108628c91eff7054ab03319a3c5d

d21f40ea0014950437e06c0ffb688b407e359a56

/utilities/config.py

7215bbcd7d43042448206ed0294f51985588258f

[]

no_license

slimanihajar/flights-delta-lake

7b8d54544ba7ab77457deb26a01715c74750dd8a

2d2bc36bc508d6dd4dd76ac16cf47ab9008e66c9

refs/heads/main

2023-08-13T19:47:40.949018

2021-09-29T12:35:41

null

0

null

UTF-8

Python

false

5,051

py

#!/c/Users/aghar/anaconda3/envs/ds/python # -*- coding: utf-8 -*- # # PROGRAMMER: Ahmed Gharib # DATE CREATED: 20/06/2021 # REVISED DATE: # PURPOSE: Configuration file to hold all the variables and import needed for DEND project # ## # Imports python modules import os import pandas as pd import logging from IPython.core.display import HTML from utilities.flights_raw import FlightsRaw print('importing libraries ....') print( """ Libraries ( os, pandas as pd, logging, HTML, FlightsRaw ) Are available now """ ) # Set pandas maximum column width to 400 pd.options.display.max_colwidth = 400 # Setting pandas to display all columns pd.options.display.max_columns = None print('pandas maximum column width is set to 400 and maximum number of columns to None') logging.info('pandas maximum column width is set to 400 and maximum number of columns to None') print('Setting up variables ....') logging.info('Setting up variables ....') # Setting the path for data source and delta lake working_dir = os.getcwd() data_source = os.path.join(working_dir, 'data_source', '') delta_lake = os.path.join(working_dir, 'delta_lake', '') flight_raw_path = os.path.join(delta_lake, 'flights_raw', '') # Creating the flight raw directory if not exists if not os.path.isdir(flight_raw_path): os.mkdir(flight_raw_path) flight_bronz_path = os.path.join(delta_lake, 'flight_bronz') flight_silver_path = os.path.join(delta_lake, 'flight_silver') flight_gold_path = os.path.join(delta_lake, 'flight_gold') date_gold_path = os.path.join(delta_lake, 'date_gold') checkpoints_path = os.path.join(working_dir, 'checkpoints') flight_raw_checkpoint = os.path.join(checkpoints_path, "flight_raw", "") flight_bronz_checkpoint = os.path.join(checkpoints_path, "flight_bronz") flight_silver_checkpoint = os.path.join(checkpoints_path, "flight_silver") flight_gold_checkpoint = os.path.join(checkpoints_path, "flight_gold") flight_raw_data_path = os.path.join(data_source, 'flights_raw', '') lookup_tables_path = os.path.join(data_source, 'LookupTables', '') l_plane_path = os.path.join(lookup_tables_path, 'L_PLANE.csv') l_airport_path = os.path.join(lookup_tables_path, 'L_AIRPORT.csv') l_cancelation_path = os.path.join(lookup_tables_path, 'L_CANCELLATION.csv') l_unique_carrier_path = os.path.join(lookup_tables_path, 'L_UNIQUE_CARRIERS.csv') # Vriables list of dictionaries to organize and print the variables when loading the configurations vars = [ {'Name': 'working_dir', 'Value': working_dir, 'Description': 'string path for current working directory'}, {'Name': 'data_source', 'Value': data_source, 'Description': 'string path for data source location'}, {'Name': 'delta_lake', 'Value': delta_lake, 'Description': 'string path for delta lake location'}, {'Name': 'flight_raw_path', 'Value': flight_raw_path, 'Description': 'string path for flight raw data'}, {'Name': 'flight_bronz_path', 'Value': flight_bronz_path, 'Description': 'string path for flight bronz data'}, {'Name': 'flight_silver_path', 'Value': flight_silver_path, 'Description': 'string path for flight silver data'}, {'Name': 'flight_gold_path', 'Value': flight_gold_path, 'Description': 'string path for flight gold data'}, {'Name': 'date_gold_path', 'Value': date_gold_path, 'Description': 'string path for date gold data'}, {'Name': 'checkpoints_path', 'Value': checkpoints_path, 'Description': 'string path for checkpoints directory'}, {'Name': 'flight_raw_checkpoint', 'Value': flight_raw_checkpoint, 'Description': 'string path for flight raw checkpoint'}, {'Name': 'flight_bronz_checkpoint', 'Value': flight_bronz_checkpoint, 'Description': 'string path for flight bronz checkpoint'}, {'Name': 'flight_silver_checkpoint', 'Value': flight_silver_checkpoint, 'Description': 'string path for flight silver checkpoint'}, {'Name': 'flight_gold_checkpoint', 'Value': flight_gold_checkpoint, 'Description': 'string path for flight gold checkpoint'}, {'Name': 'flight_raw_data_path', 'Value': flight_raw_data_path, 'Description': 'string path for flight raw data source'}, {'Name': 'lookup_tables_path', 'Value': lookup_tables_path, 'Description': 'string path for lookup tables directory'}, {'Name': 'l_plane_path', 'Value': l_plane_path, 'Description': 'string path for plane data csv file'}, {'Name': 'l_airport_path', 'Value': l_airport_path, 'Description': 'string path for airport data csv file'}, {'Name': 'l_cancelation_path', 'Value': l_cancelation_path, 'Description': 'string path for cancelation data csv file'}, {'Name': 'l_unique_carrier_path', 'Value': l_unique_carrier_path, 'Description': 'string path for unique carrier csv file'} ] vars_df = pd.DataFrame(vars).to_html() print('vars_df is available as HTML content to display simply run HTML(vars_df)') logging.info('vars_df is available as HTML content to display simply run HTML(vars_df)')

[ "a.gharib89@yahoo.com" ]

a.gharib89@yahoo.com

7de2176332b55861a0bb08f58d2b7caa91fa5460

77b3923245bd7b4a215471067548d1aeb9c8d8c0

/fboss/system_tests/test_server.py

09fd3e7fcf0fdec66bad1a6a34595c791128fe76

[ "BSD-3-Clause" ]

permissive

nanokinetics/fboss

95682f29aa77bd465ee64f54cad9f41789c9f66b

2e4799aefaddd5ef5f82002c6d31538257b90460

refs/heads/master

2021-04-14T04:41:36.688789

2018-03-22T23:02:18

2018-03-22T23:17:48

null

0

null

UTF-8

Python

false

12,250

py

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals """ A service to run on testing hosts, so that we can source traffic, sync traffic, etc. Modeled after pyserver example in open source https://github.com/facebook/fbthrift/blob/master/thrift/tutorial/\ py/PythonServer.py """ from thrift.transport import TSocket from thrift.transport import TTransport from thrift.protocol import THeaderProtocol from thrift.server import TServer from neteng.fboss.ttypes import FbossBaseError from fboss.system_tests.test import TestService from fboss.system_tests.test.ttypes import DeviceType from fboss.system_tests.test.constants import DEFAULT_PORT from os.path import isfile import json import logging import pcapy # this library currently only supports python 2.x :-( import signal import socket import subprocess import time import traceback class TestServer(TestService.Iface): SERVICE = TestService PCAP_READ_BATCHING = 100 # in miliseconds DEVICE_TYPE_ENUM_TO_STRING = { DeviceType.LOOPBACK: "dummy" } def __init__(self): self.log = logging.getLogger(self.__class__.__name__) self.log.addHandler(logging.StreamHandler()) self.log.setLevel(logging.INFO) self.pcap_captures = {} self.pkt_captures = {} self.log.debug("Log: debug enabled") # Keep track of added_interfaces so users can't remove interfaces # they didn't add self.added_interfaces = set() signal.signal(signal.SIGINT, self._cleanUpAddedInterfaces) self.log.info("Log: info enabled") self.log.warn("Log: warnings enabled") def __enter__(self): return self def __exit__(self, type, value, traceback): self._cleanUpAddedInterfaces() def ping(self, ip, options=None): """ @param ip : a string, e.g., "128.8.128.118" """ # Ping default options is to capture 1 packet if not options: options = ['-c', '1'] if ":" in ip: options.append('-6') # Using subprocess.call with shell=False should prevent # any security concerns because this just calls exec() natively # (assuming there are no commandline buffer overflows in ping) command = ["ping"] + options + [ip] self.log.debug("Ping: running `%s`" % " ".join(command)) with open("/dev/null") as devnull: response = subprocess.call(command, stdout=devnull) return response == 0 def get_interface_mtu(self, intf): command = ["cat", "/sys/class/net/%s/mtu" % intf] response = subprocess.check_output(command) return int(response) def get_v4_ip(self, intf): command = ["ip", "-4", "addr", "show", intf] response = subprocess.check_output(command) return response def get_v6_ip(self, intf): command = ["ip", "-6", "addr", "show", intf] response = subprocess.check_output(command) return response def status(self): return True def startPktCapture(self, interface_name, pcap_filter_str): self.log.debug("startPktCapture(%s,filter=%s)" % ( interface_name, pcap_filter_str)) if interface_name in self.pcap_captures: # close out any old captures del self.pcap_captures[interface_name] reader = pcapy.open_live(interface_name, 1500, 1, self.PCAP_READ_BATCHING) reader.setnonblock(1) reader.setfilter(pcap_filter_str) self.pcap_captures[interface_name] = reader self.pkt_captures[interface_name] = [] def _pkt_callback(self, interface_name, pkt_hdr, pkt_data): pkts = self.pkt_captures[interface_name] self.log.debug("_pkt_callback(%s): %d pkts captured" % (interface_name, len(pkts))) pkts.append((pkt_hdr, pkt_data)) def getPktCapture(self, interface_name, ms_timeout, maxPackets): """ All documentation for this call is in thrift definition """ if interface_name not in self.pcap_captures: raise FbossBaseError("No startPktCapture() for Interface " + interface_name) reader = self.pcap_captures[interface_name] start = time.time() intf = interface_name # horrible hack to fit in 80 chars below self.log.debug("getPktCapture(%s,ms_timeout=%d,maxPackets=%d)" % (interface_name, ms_timeout, maxPackets)) while time.time() < (start + (ms_timeout / 1000)): # this reader is set to not block, so this will busy wait until # packets show up or the timeout occurs. Given the note # about the readtimeout param in open_live() not being widely # supported, this is the best we can do try: reader.dispatch( maxPackets, lambda phdr, pdata: self._pkt_callback(intf, phdr, pdata)) except Exception as e: traceback.print_exc() print(str(e)) raise pkts = self.pkt_captures[interface_name] self.log.debug(" got %d packets" % len(pkts)) if len(pkts) >= maxPackets: break return_pkts = [] for _phdr, pdata in pkts: capture = TestService.CapturedPacket() capture.packet_data = pdata capture.packet_length = _phdr.getlen() return_pkts.append(capture) return return_pkts def stopPktCapture(self, interface_name): if interface_name not in self.pcap_captures: raise FbossBaseError("Calling stopPktCapture() without " + " startPktCapture()?") del self.pcap_captures[interface_name] def sendPkt(self, interface_name, pkt): """ To send a packet, we need an open_live call. If one's already open, use that, if not, start and stop one quickly """ self.log.warning("Doing sendPkt(%s,len(%s))" % (interface_name, len(pkt))) ## NOTE: pcapy.reader.sendpacket() is not implemented! use python raw = socket.socket(socket.AF_PACKET, socket.SOCK_RAW) raw.bind((interface_name, 0)) raw.send(pkt) @staticmethod def check_output(cmd, **kwargs): return subprocess.check_output(cmd.split(' '), **kwargs) def kill_iperf3(self): try: self.check_output('pkill -9 iperf3') except Exception: pass def iperf3_server(self, timeout, options): ''' initialize iperf3 server, with timeout to expire server if no client request comes in ''' def timeout_handler(signum, frame): raise FbossBaseError("IPERF3 SERVER TIMEOUT") self.kill_iperf3() # kill lingering iperf3 processes (server or client) signal.signal(signal.SIGALRM, timeout_handler) signal.alarm(timeout) iperf3_pid_fn = '/tmp/iperf3_thrift.pid' server_options = '-I {fn} -J -1 -s '.format(fn=iperf3_pid_fn) if options: server_options += ' '.join(options) command = "iperf3 {options}".format(options=server_options) try: response = self.check_output(command) except Exception as e: response = json.dumps({'error': repr(e)}) finally: signal.alarm(0) if isfile(iperf3_pid_fn): with open(iperf3_pid_fn, 'r') as f: pid = f.read().strip('\0') self.check_output('kill -9 {pid}'.format(pid=pid)) return response def iperf3_client(self, server_ip, client_retries=3): ''' @param ip : a string, e.g., "128.8.128.118" @param client_retries: int, how many retries client attempts ''' self.kill_iperf3() # kill lingering iperf3 processes (server or client) is_ipv6 = '-6' if ':' in server_ip else '' command = "iperf3 {} -J -t 1 -c {}".format(is_ipv6, server_ip) client_loop_cnt = 0 while client_loop_cnt < client_retries: try: response = self.check_output(command) break except Exception: client_loop_cnt += 1 error_msg = '{} retries to reach iperf3 server {}' \ .format(client_loop_cnt, server_ip) response = json.dumps({'error': error_msg}) time.sleep(1) return response def flap_server_port(self, interface, numberOfFlaps, sleepDuration): ''' System test to verify port flap handling works and doesn't hang the system. ''' command_for_interface_down = 'ifconfig ' + interface + " down" command_for_interface_up = 'ifup ' + interface for _iteration in range(1, numberOfFlaps + 1): # Ignore the SIGHUP signal to maintain session when the server port # is turned down. old_handler = signal.signal(signal.SIGHUP, signal.SIG_IGN) self.log.debug("Flap iteration {}".format(_iteration)) self.check_output(command_for_interface_down) time.sleep(sleepDuration) self.check_output(command_for_interface_up) # Change the SIGHUP settings back to original value. signal.signal(signal.SIGHUP, old_handler) def add_interface(self, ifName, deviceType): if ifName in self.added_interfaces: raise FbossBaseError( "Device {} already exists".format(ifName)) strDeviceType = self.DEVICE_TYPE_ENUM_TO_STRING.get(deviceType) if not strDeviceType: raise FbossBaseError( "DeviceType {} not found/supported (are you sure you used the enum?)" .format(deviceType)) command = "ip link add name {} type {}".format(ifName, strDeviceType) try: self.check_output(command) except Exception as e: # Ignoring "File exists" error if "exit status 2" not in str(e): raise FbossBaseError("Error adding interface: {}".format(str(e))) self.added_interfaces.add(ifName) return True def remove_interface(self, ifName): if ifName not in self.added_interfaces: raise FbossBaseError( "User attempted to remove an interface they did not add. Ignoring.") command = "ip link del dev {}".format(ifName) try: self.check_output(command) except Exception as e: raise FbossBaseError("Error deleting interface: {}".format(str(e))) self.added_interfaces.remove(ifName) return True def add_address(self, address, ifName): command = "ip addr add {} dev {}".format(address, ifName) try: self.check_output(command) except Exception as e: # Ignoring "File exists" error if "exit status 2" not in str(e): raise FbossBaseError("Error adding address: {}".format(str(e))) return True def _cleanUpAddedInterfaces(self): for ifName in self.added_interfaces: command = "ip link del dev {}".format(ifName) try: self.check_output(command) except Exception as e: self.log.info("Error deleting interface: {}".format(str(e))) if __name__ == '__main__': with TestServer() as handler: transport = TSocket.TServerSocket(DEFAULT_PORT) tfactory = TTransport.TBufferedTransportFactory() pfactory = THeaderProtocol.THeaderProtocolFactory() server = TServer.TSimpleServer(handler, transport, tfactory, pfactory) # You could do one of these for a multithreaded server # server = TServer.TThreadedServer(handler, transport, tfactory, pfactory) print('Starting the server...') server.serve() print('Done.')

[ "facebook-github-bot@users.noreply.github.com" ]

facebook-github-bot@users.noreply.github.com

9b94651beea06eff8912c9e6c4fa33218dddd01b

0bfb0c59bdaf3a8999f22abc9a177ba0560817cc

/fgiggle/manage.py

e58288544eb6dfd6b05827602c2a0384d52d93e5

[]

no_license

CristiBalu/furry-giggle

0b51bf7d61ac4beb9d8ed7725c932dc09841418c

81521cc52f3b8fddcc2527dfb34867a21323a4b7

refs/heads/master

2020-04-19T04:05:32.567934

2016-09-07T22:05:44

67,527,854

0

null

UTF-8

Python

false

250

py

#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "fgiggle.settings") from django.core.management import execute_from_command_line execute_from_command_line(sys.argv)

[ "sb720@exeter.ac.uk" ]

sb720@exeter.ac.uk

991297ff8bc64fc31dcaf0117b5a96ea34df9c31

2579392850ca0534d98b391bae670b578792ff3f

/historical/tests/test_commons.py

37802929ba4e1335a852fe4644105623bbf7fce8

[ "Apache-2.0" ]

permissive

shdobxr/historical

7bf4b6db357d78065b7ed31d77b7b237ee61d031

05a8473fb5fc00233fdbb0974c515110dc64ffbc

refs/heads/master

2020-03-24T09:10:19.330468

2018-07-26T20:31:18

null

0

null

UTF-8

Python

false

9,057

py

""" .. module: historical.tests.test_commons :platform: Unix :copyright: (c) 2017 by Netflix Inc., see AUTHORS for more :license: Apache, see LICENSE for more details. .. author:: Mike Grima <mgrima@netflix.com> """ import json from datetime import datetime import pytest from historical.common.exceptions import DurableItemIsMissingException from historical.s3.collector import process_update_records from historical.tests.factories import CloudwatchEventFactory, DetailFactory, serialize, DynamoDBRecordFactory, \ DynamoDBDataFactory S3_BUCKET = { "arn": "arn:aws:s3:::testbucket1", "principalId": "joe@example.com", "userIdentity": { "sessionContext": { "userName": "oUEKDvMsBwpk", "type": "Role", "arn": "arn:aws:iam::123456789012:role/historical_poller", "principalId": "AROAIKELBS2RNWG7KASDF", "accountId": "123456789012" }, "principalId": "AROAIKELBS2RNWG7KASDF:joe@example.com" }, "accountId": "123456789012", "eventTime": "2017-09-08T00:34:34Z", "eventSource": "aws.s3", "BucketName": "testbucket1", "Region": "us-east-1", "Tags": {}, "configuration": { "Grants": { "75aa57f09aa0c8caeab4f8c24e99d10f8e7faeebf76c078efc7c6caea54ba06a": [ "FULL_CONTROL" ] }, "Owner": { "ID": "75aa57f09aa0c8caeab4f8c24e99d10f8e7faeebf76c078efc7c6caea54ba06a" }, "LifecycleRules": [ { "Status": "Enabled", "Prefix": None, "Expiration": { "Days": 7 }, "ID": "Some cleanup" } ], "Logging": {}, "Policy": None, "Versioning": {}, "Website": None, "Cors": [], "Notifications": {}, "Acceleration": None, "Replication": {}, "CreationDate": "2006-02-03T16:45:09Z", "AnalyticsConfigurations": [], "MetricsConfigurations": [], "InventoryConfigurations": [], "Name": "testbucket1", "_version": 8 } } def test_deserialize_current_record_to_current_model(historical_role, current_s3_table, buckets): from historical.common.dynamodb import deserialize_current_record_to_current_model from historical.s3.models import CurrentS3Model # Create the event to fetch the Current data from: bucket = S3_BUCKET.copy() bucket['eventTime'] = datetime(year=2017, month=5, day=12, hour=10, minute=30, second=0).isoformat() + 'Z' ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': bucket['arn'] }), eventName='INSERT'), default=serialize)) result = deserialize_current_record_to_current_model(ddb_record, CurrentS3Model) assert result.configuration.attribute_values['Name'] == "testbucket1" assert isinstance(result, CurrentS3Model) # And for sns_too_big: # Create the bucket in the current table: now = datetime.utcnow().replace(tzinfo=None, microsecond=0) create_event = json.loads(json.dumps(CloudwatchEventFactory( detail=DetailFactory( requestParameters={ "bucketName": "testbucket1" }, eventSource="aws.s3", eventName="CreateBucket", eventTime=now ) ), default=serialize)) process_update_records([create_event]) del bucket['configuration'] ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': bucket['arn'] }), eventName='INSERT'), default=serialize)) ddb_record['sns_too_big'] = True result = deserialize_current_record_to_current_model(ddb_record, CurrentS3Model) assert result.configuration.attribute_values['Name'] == "testbucket1" assert isinstance(result, CurrentS3Model) # And if the object isn't in the current table: ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': 'arn:aws:s3:::notarealbucket' }), eventName='INSERT'), default=serialize)) ddb_record['sns_too_big'] = True result = deserialize_current_record_to_current_model(ddb_record, CurrentS3Model) assert not result def test_deserialize_durable_record_to_durable_model(historical_role, durable_s3_table, buckets): from historical.common.dynamodb import deserialize_durable_record_to_durable_model, \ deserialize_current_record_to_durable_model from historical.s3.models import CurrentS3Model, DurableS3Model # Create the event to fetch the Durable data from: bucket = S3_BUCKET.copy() del bucket['eventSource'] bucket['eventTime'] = datetime(year=2017, month=5, day=12, hour=10, minute=30, second=0).isoformat() + 'Z' ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': bucket['arn'] }), eventName='INSERT'), default=serialize)) result = deserialize_durable_record_to_durable_model(ddb_record, DurableS3Model) assert result assert result.configuration.attribute_values['Name'] == "testbucket1" assert result.eventTime == bucket['eventTime'] assert isinstance(result, DurableS3Model) # And for sns_too_big: # Create the bucket in the durable table: ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': bucket['arn'] }), eventName='INSERT'), default=serialize)) revision = deserialize_current_record_to_durable_model(ddb_record, CurrentS3Model, DurableS3Model) revision.save() ddb_record['sns_too_big'] = True del bucket['configuration'] result = deserialize_durable_record_to_durable_model(ddb_record, DurableS3Model) assert result assert result.configuration.attribute_values['Name'] == "testbucket1" assert result.eventTime == bucket['eventTime'] assert isinstance(result, DurableS3Model) # And if the object isn't in the durable table: ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': 'arn:aws:s3:::notarealbucket' }), eventName='INSERT'), default=serialize)) ddb_record['sns_too_big'] = True # Raises an exception: with pytest.raises(DurableItemIsMissingException): deserialize_durable_record_to_durable_model(ddb_record, DurableS3Model) def test_deserialize_durable_record_to_current_model(historical_role, current_s3_table, buckets): from historical.common.dynamodb import deserialize_durable_record_to_current_model from historical.s3.models import CurrentS3Model # Create the event to fetch the Current data from: bucket = S3_BUCKET.copy() del bucket['eventSource'] bucket['eventTime'] = datetime(year=2017, month=5, day=12, hour=10, minute=30, second=0).isoformat() + 'Z' ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': bucket['arn'] }), eventName='INSERT'), default=serialize)) result = deserialize_durable_record_to_current_model(ddb_record, CurrentS3Model) assert result.configuration.attribute_values['Name'] == "testbucket1" assert isinstance(result, CurrentS3Model) # And for sns_too_big: # Create the bucket in the Current table: now = datetime.utcnow().replace(tzinfo=None, microsecond=0) create_event = json.loads(json.dumps(CloudwatchEventFactory( detail=DetailFactory( requestParameters={ "bucketName": "testbucket1" }, eventSource="aws.s3", eventName="CreateBucket", eventTime=now ) ), default=serialize)) process_update_records([create_event]) del bucket['configuration'] ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': bucket['arn'] }), eventName='INSERT'), default=serialize)) ddb_record['sns_too_big'] = True result = deserialize_durable_record_to_current_model(ddb_record, CurrentS3Model) assert result assert result.configuration.attribute_values['Name'] == "testbucket1" assert isinstance(result, CurrentS3Model) # And if the object isn't in the durable table: ddb_record = json.loads(json.dumps(DynamoDBRecordFactory(dynamodb=DynamoDBDataFactory( NewImage=bucket, Keys={ 'arn': 'arn:aws:s3:::notarealbucket' }), eventName='INSERT'), default=serialize)) ddb_record['sns_too_big'] = True result = deserialize_durable_record_to_current_model(ddb_record, CurrentS3Model) assert not result

[ "mgrima@netflix.com" ]

mgrima@netflix.com

9459684b423408f0e0e297ebd428202457793f54

bfd523ae160a49e24c9529dbbf6eb151c1790b2c

/localizacao/migrations/0001_initial.py

c406ff375662ebd56882ed26ca894e8712b6c5e7

[]

no_license

FilipeBP/DjangoAPI

bad1d5b273fa0795e2ad1abf9c206998b46c0504

b05d9f46901597d95b1f2dd39bfd429bbdfbd0cc

refs/heads/master

2020-09-08T09:11:56.469188

2019-11-16T19:13:07

221,089,038

0

null

UTF-8

Python

false

834

py

# Generated by Django 2.2.7 on 2019-11-13 20:46 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Localization', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('country', models.CharField(max_length=70)), ('state', models.CharField(max_length=70)), ('city', models.CharField(max_length=70)), ('row1', models.CharField(max_length=150)), ('row2', models.CharField(blank=True, max_length=150, null=True)), ('lat', models.DecimalField(decimal_places=6, max_digits=9)), ], ), ]

[ "filipebritoperez@hotmail.com" ]

filipebritoperez@hotmail.com

a23aa3dc313e6e4ce01499017354a5d938c4d720

4c15467527b2526cb24e543868b4b4249949b4d4

/main.py

c606b82bbe05f5c085945c4adaf02f820f2365b9

[]

no_license

reergymerej/chords

9cd3f4170a5361d715a9c04b2d0f62feb222f05a

878113d95823431b0a4217e386d8aa3f8c11ab5c

refs/heads/master

2021-09-03T11:56:11.743040

2018-01-08T21:56:22

115,677,340

0

null

UTF-8

Python

false

1,930

py

#!/usr/bin/env python3 print("Give me a root note.") NOTES = [ 'A', 'B♭', 'B', 'C', 'C♯', 'D', 'E♭', 'E', 'F', 'F♯', 'G', 'G♯', ] def validate_note(note): return note.upper() in NOTES def interpret_note_variant(note): """Convert shorthand and weird names to our NOTES.""" note = note.replace('+', '♯') note = note.replace('-', '♭') note = note.upper() weird_variations = { 'A♭': 'G♯', 'A♯': 'B♭', 'D♭': 'C♯', 'D♯': 'E♭', 'G♭': 'F♯', } if (note in weird_variations): return weird_variations[note] return note def ask_for_note(): while True: note = interpret_note_variant(input("root note: ")) if (validate_note(note)): return note else: print("I don't understand that note.") def shift_list(the_list, item): """Reorganize list so item is at 0 index.""" index = the_list.index(item) before = the_list[:index] the_list = the_list[index:] the_list.extend(before) return the_list def get_major_chord(root_note): shifted_notes = shift_list(NOTES, root_note) third = shifted_notes[4] fifth = shifted_notes[7] chord = '{:s}-{:s}-{:s}'.format(root_note, third, fifth) return 'major', chord def get_minor_chord(root_note): shifted_notes = shift_list(NOTES, root_note) third = shifted_notes[3] fifth = shifted_notes[7] chord = '{:s}-{:s}-{:s}'.format(root_note, third, fifth) return 'minor', chord note = ask_for_note() chord_types = [ get_major_chord, get_minor_chord, ] for chord_type in chord_types: chord_type_name, chord = chord_type(note) print('The {:s} chord for the root {:s} is {:s}.'.format(chord_type_name, note, chord))

[ "jeremy.greer.atl@gmail.com" ]

jeremy.greer.atl@gmail.com

2ae0490a8033275531c9922d8b3dbeb36687774c

2ed1b17c2bd710a1cb31d5e6e7956297a374a8f6

/04-Evr_List_Comprehensions/Solved/comprehensions.py

c45261007e8c2e6730273eefa277f6e2845eb86f

[]

no_license

jzcapets/09PythonActivities2

cf5910dc1212dcb6195936f0cb0b36b08d7b30f0

7f2998cda57fa7f43a6ac6c610eb35f68abd8983

refs/heads/master

2020-11-27T12:41:40.663968

2019-12-21T15:11:43

229,444,337

0

null

UTF-8

Python

false

968

py

fish = "halibut" # Loop through each letter in the string # and push to an array letters = [] for letter in fish: letters.append(letter) print(letters) # List comprehensions provide concise syntax for creating lists letters = [letter for letter in fish] print(letters) # We can manipulate each element as we go capital_letters = [] for letter in fish: capital_letters.append(letter.upper()) print(capital_letters) # List Comprehension for the above capital_letters = [letter.upper() for letter in fish] print(capital_letters) # We can also add conditional logic (if statements) to a list comprehension july_temperatures = [87, 85, 92, 79, 106] hot_days = [] for temperature in july_temperatures: if temperature > 90: hot_days.append(temperature) print(hot_days) # List Comprehension with conditional hot_days = [temperature for temperature in july_temperatures if temperature > 90] print(hot_days)

[ "noreply@github.com" ]

jzcapets.noreply@github.com

bc3244f2e25658027cd449260e5ba51108e15589

2d56818b961354d1aed1f4884eeacfa5390a236f

/Day 9/day9_starting_code.py

aa4be2b5d8b2470e223af316bae473703566dbf3

[]

no_license

bayramhayri/100DaysOfPython

675a6ece8cbb45b47af7d95e8f881b623877dd25

f3dae0882055f11f65f02ac3b86702ecd154d5d6

refs/heads/main

2023-01-23T16:30:34.561243

2020-12-05T14:23:08

312,025,224

0

null

UTF-8

Python

false

740

py

programming_dictionary = { "Bug": "An error in a program that prevents the program from running as expected.", "Function": "A piece of code that you can easily call over and over again." } print(programming_dictionary["Bug"]) # Adding new items to dictionary. programming_dictionary["Loop"] = "The action of doing something over and over again." print(programming_dictionary) # Create an empty dictionary. empty_dictionary = {} # Wipe an existing dictionary. #programming_dictionary = {} # Edit an item in a dictionary. programming_dictionary["Bug"] = "A moth in your computer." print(programming_dictionary) # Loop through a dictionary for key in programming_dictionary: print(key) print(programming_dictionary[key])

[ "bayramhayri@gmail.com" ]

bayramhayri@gmail.com

ec916814fa9524bc04235e34b57fdd9c3a848dc7

678864ef6b96ca59c5de29dab0047f6b7cc7463a

/libs/SmartMeshSDK/ApiDefinition/IpMgrDefinition.py

9dd1768799bb4cc3d972f6237ea4bfa323ccba15

[]

no_license

ddidiy/smartmeshsdk

c880f894a7f45a38af15d2f427a742115d1b744d

947224c945e560854ff3e80d142a79077c267671

refs/heads/master

2021-01-12T19:24:18.464870

2016-08-04T19:05:02

null

0

null

UTF-8

Python

false

77,802

py

#!/usr/bin/python import ApiDefinition import ByteArraySerializer class IpMgrDefinition(ApiDefinition.ApiDefinition): ''' \ingroup ApiDefinition \brief API definition for the IP manager. \note This class inherits from ApiDefinition. It redefines the attributes of its parents class, but inherits the methods. ''' STRING = ApiDefinition.FieldFormats.STRING BOOL = ApiDefinition.FieldFormats.BOOL INT = ApiDefinition.FieldFormats.INT INTS = ApiDefinition.FieldFormats.INTS HEXDATA = ApiDefinition.FieldFormats.HEXDATA RC = ApiDefinition.ApiDefinition.RC SUBID1 = ApiDefinition.ApiDefinition.SUBID1 SUBID2 = ApiDefinition.ApiDefinition.SUBID2 RC_OK = ApiDefinition.ApiDefinition.RC_OK OPTIONAL = [ 'pkLen_1', 'delay_1', 'pkLen_2', 'delay_2', 'pkLen_3', 'delay_3', 'pkLen_4', 'delay_4', 'pkLen_5', 'delay_5', 'pkLen_6', 'delay_6', 'pkLen_7', 'delay_7', 'pkLen_8', 'delay_8', 'pkLen_9', 'delay_9', 'pkLen_10', 'delay_10', 'stationId', ] def __init__(self): self.serializer = ByteArraySerializer.ByteArraySerializer(self) def default_serializer(self,commandArray,fieldsToFill): ''' \brief IpMgrDefinition-specific implementation of default serializer \param commandArray An array of the form [commandName, subCommandname] The array can be of any length, and is of length 1 if no subcommands are used. \param fieldsToFill The list of fields to send, organized as a dictionary of the form <tt>fieldname:fieldvalue</tt>. \returns id,byteString where id is the command ID and byteArray an array of bytes ''' return self.serializer.serialize(commandArray,fieldsToFill) def deserialize(self,type,cmdId,byteArray): ''' \brief IpMgrDefinition-specific implementation of deserializer ''' return self.serializer.deserialize(type,cmdId,byteArray) # We redefine this attribute inherited from ApiDefinition. See # ApiDefinition for a full description of the structure of this field. fieldOptions = { # 'notificationTypes' : [ # [ 1, 'event', 'Event notification'], # [ 2, 'log', 'Log notification'], # [ 4, 'data', 'Data payload notification'], # [ 5, 'ipData', '6LoWPAN packet notification'], # [ 6, 'healthReport', 'Health report notification'], # ], # 'eventTypes' : [ # [ 0, 'moteReset', 'A mote reset'], # [ 1, 'networkReset', 'The network was reset'], # [ 2, 'commandFinish ', 'A command has completed execution'], # [ 3, 'moteJoin', 'A mote joined the network'], # [ 4, 'moteOperational', 'A new mote was configured and is now operational'], # [ 5, 'moteLost', 'A mote is no longer communicating in the network'], # [ 6, 'netTime', 'Contains the network uptime (in response to a getTime command)'], # [ 7, 'pingResponse', 'A reply was received from a mote ping'], # [10, 'pathCreate', 'A path was created'], # [11, 'pathDelete', 'A path was deleted'], # [12, 'packetSent', 'A packet was sent'], # [13, 'moteCreate', 'A mote was created'], # [14, 'moteDelete', 'A mote was deleted'], # ], RC : [ [ 0, 'RC_OK', 'The application layer has processed the command correctly'], [ 1, 'RC_INVALID_COMMAND', 'Invalid command'], [ 2, 'RC_INVALID_ARGUMENT', 'Invalid argument'], [11, 'RC_END_OF_LIST', 'End of list is returned when an iteration reaches the end of the list of objects'], [12, 'RC_NO_RESOURCES', 'Reached maximum number of items'], [13, 'RC_IN_PROGRESS', 'Operation is in progress'], [14, 'RC_NACK', 'Negative acknowledgment'], [15, 'RC_WRITE_FAIL', 'Flash write failed'], [16, 'RC_VALIDATION_ERROR', 'Parameter validation error'], [17, 'RC_INV_STATE', 'Object has inappropriate state'], [18, 'RC_NOT_FOUND', 'Object is not found'], ], 'frameProfile' : [ [ 1, 'Profile_01', 'Fast network build, medium speed network operation'], ], 'advertisementState' : [ [ 0, 'on', 'Advertisement is on'], [ 1, 'off', 'Advertisement is off'], ], 'downstreamFrameMode' : [ [ 0, 'normal', 'Normal downstream bandwidth'], [ 1, 'fast', 'Fast downstream bandwidth'], ], 'networkState' : [ [ 0, 'operational', 'Network is operating normally'], [ 1, 'radiotest', 'Manager is in radiotest mode'], [ 2, 'notStarted', 'Waiting for startNetwork API command'], [ 3, 'errorStartup', 'Unexpected error occurred at startup'], [ 4, 'errorConfig', 'Invalid or not licensed configuration found at startup'], [ 5, 'errorLicense', 'Invalid license file found at startup'], ], 'moteState' : [ [ 0, 'lost', 'Mote is not currently part of the network'], [ 1, 'negotiating', 'Mote is in the process of joining the network'], [ 4, 'operational', 'Mote is operational'], ], 'resetType' : [ [ 0, 'resetSystem', 'Reset the system'], [ 2, 'resetMote', 'Reset the mote'], ], 'backboneFrameMode' : [ [ 0, 'off', 'Backbone frame is off'], [ 1, 'upstream', 'Backbone frame is activated for upstream frames'], [ 2, 'bidirectional', 'Backbone frame is activated for both upstream and downstream frames'], ], 'pathFilter' : [ [ 0, 'all', 'All paths'], [ 1, 'upstream', 'Upstream paths'], ], 'pathDirection' : [ [ 0, 'none', 'No path'], [ 1, 'unused', 'Path is not used'], [ 2, 'upstream', 'Upstream path'], [ 3, 'downstream', 'Downstream path'], ], 'packetPriority': [ [0, 'Low', 'Default packet priority'], [1, 'Medium', 'Higher packet priority'], [2, 'High', 'Highest packet priority'], ], 'commandFinishedResult': [ [0, 'OK', 'Command completed successfully'], [1, 'nack', 'Command not acknowledged'], [2, 'commandTimeout', 'Command timed out'], ], 'ccaMode': [ [0, 'off', 'CCA disabled'], [1, 'energy', 'Energy detect'], [2, 'carrier', 'Carrier detect'], [3, 'both', 'Energy detect and Carrier detect'], ], 'radiotestType': [ [0, 'packet', 'Transmit packets'], [1, 'cm', 'Continuous modulation'], [2, 'cw', 'Continuous wave'], [3, 'pkcca', 'Packet test with clear channel assessment (CCA) enabled'], ], 'seqSize': [ [0, '0', ''], [1, '1', ''], [2, '2', ''], [3, '3', ''], [4, '4', ''], [5, '5', ''], [6, '6', ''], [7, '7', ''], [8, '8', ''], [9, '9', ''], [10, '10', ''], ], #==================== misc ============================================ 'successCode' : [ [ 0, 'success', ''], [ 1, 'unsupported_version', ''], [ 2, 'invalid_mode', ''], ], 'mode' : [ [ 0, 'legacy', ''], ], 'userRole' : [ [ 0, 'viewer', 'Viewer-role user has read-only access to non-sensitive network information'], [ 1, 'user', 'User-role user has read-write privileges'], ], } # We redefine this attribute inherited from ApiDefinition. See # ApiDefinition for a full description of the structure of this field. commands = [ # command 'hello' (commandID 1) is handled by the Hdlc module # command 'hello_response' (commandID 2) is handled by the Hdlc module { 'id' : 1, 'name' : 'mux_hello', 'description': 'Sent by the manager to initiate a new session with a client.', 'request' : [ ['version', INT, 1, None], ['secret', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['version', INT, 1, None], ], }, }, { 'id' : 1, 'name' : 'hello', 'description': '', 'request' : [ ['version', INT, 1, None], ['cliSeqNo', INT, 1, None], ['mode', INT, 1, True], ], }, { 'id' : 2, 'name' : 'hello_response', 'description': '', 'request' : [], # there is no request 'response' : { 'FIELDS': [ ['successCode', INT, 1, True], ['version', INT, 1, None], ['mgrSeqNo', INT, 1, None], ['cliSeqNo', INT, 1, None], ['mode', INT, 1, True], ], }, }, { 'id' : 21, 'name' : 'reset', 'description': 'The reset command is used to reset various objects. The command argument is an object type, and if the object is a mote the MAC address must be specified (otherwise that argument is ignored).', 'request' : [ ['type', INT, 1, 'resetType'], ['macAddress', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['macAddress', HEXDATA, 8, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'Mote with specified MAC address is not found', 'RC_INV_STATE' : 'Mote is not in operational state', 'RC_NACK' : 'User commands queue is full (applies to mote reset)', 'RC_INVALID_ARGUMENT' : 'Invalid reset type value', }, }, { 'id' : 22, 'name' : 'subscribe', 'description': "The subscribe command indicates that the manager should send the external application the specified notifications. It contains two filter fields:\n\n- filter is a bitmask of flags indicating the types of notifications that the client wants to receive\n- unackFilter allows the client to select which of the notifications selected in filter should be sent acknowledged. If a notification is sent as 'acknowledged', thesubsequent notification packets will be queued while waiting for response.\n\nEach subscription request overwrites the previous one. If an application is subscribed to data and then decides he also wants events he should send a subscribe command with both the data and event flags set. To clear all subscriptions, the client should send a subscribe command with the filter set to zero. When a session is initiated between the manager and a client, the subscription filter is initialized to zero.\n\nThe subscribe bitmap uses the values of the notification type enumeration. Some values are unused to provide backwards compatibility with earlier APIs.", 'request' : [ ['filter', HEXDATA, 4, None], ['unackFilter', HEXDATA, 4, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_INVALID_ARGUMENT' : 'Invalid subscription filter value', }, }, { 'id' : 23, 'name' : 'getTime', 'description': 'The getTime command returns the current manager UTC time and current absolute slot number (ASN). The time values returned by this command are delayed by queuing and transfer time over the serial connection. For additional precision, an external application should trigger the networkTime notification using the Time Pin.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['uptime', INT, 4, None], ['utcSecs', INT, 8, None], ['utcUsecs', INT, 4, None], ['asn', HEXDATA, 5, None], ['asnOffset', INT, 2, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 26, 'name' : 'setNetworkConfig', 'description': 'The setNetworkConfig command changes network configuration parameters. The response code indicates whether the changes were successfully applied. This change is persistent.\n\nGenerally, changes to network configuration will take effect when the manager reboots. Exceptions are detailed below:\n\n- Max Motes: The new maxMotes value is used as soon as new motes try to join the network, but motes are not removed from the network if the value is set to a number lower than numMotes.\n- Base Bandwidth: Changing baseBandwidth while the network is running does not reallocate bandwidth to Operational motes.', 'request' : [ ['networkId', INT, 2, None], ['apTxPower', INTS, 1, None], ['frameProfile', INT, 1, True], ['maxMotes', INT, 2, None], ['baseBandwidth', INT, 2, None], ['downFrameMultVal', INT, 1, None], ['numParents', INT, 1, None], ['ccaMode', INT, 1, True], ['channelList', INT, 2, None], ['autoStartNetwork', BOOL, 1, None], ['locMode', INT, 1, None], ['bbMode', INT, 1, 'backboneFrameMode'], ['bbSize', INT, 1, None], ['isRadioTest', INT, 1, None], ['bwMult', INT, 2, None], ['oneChannel', INT, 1, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_INVALID_ARGUMENT' : 'Validation of the network parameters failed', 'RC_WRITE_FAIL' : 'Flash write error, cannot save new settings', }, }, { 'id' : 31, 'name' : 'clearStatistics', 'description': 'The clearStatistics command clears the accumulated network statistics. The command does not clear path quality or mote statistics.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 33, 'name' : 'exchangeMoteJoinKey', 'description': 'The exchangeMoteJoinKey command triggers the manager to send a new join key to the specified mote and update the manager\'s ACL entry for the mote. The response contains a callbackId. A commandFinished event notification with this callbackId will be sent when the operation is complete. This change is persistent.', 'request' : [ ['macAddress', HEXDATA, 8, None], ['key', HEXDATA, 16, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['callbackId', INT, 4, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'Mote with specified MAC address is not found', 'RC_INV_STATE' : 'Mote is not in operational state', 'RC_NACK' : 'User commands queue is full', 'RC_WRITE_FAIL' : 'Flash write error, can\'t save new settings', }, }, { 'id' : 34, 'name' : 'exchangeNetworkId', 'description': 'The exchangeNetworkId command triggers the manager to distribute a new network ID to all the motes in the network. A callbackId is returned in the response. A commandFinished notification with this callbackId will be sent when the operation is complete.This change is persistent.', 'request' : [ ['id', INT, 2, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['callbackId', INT, 4, None], ], }, 'responseCodes': { 'RC_OK' : 'Command received', 'RC_IN_PROGRESS' : 'A command is still pending. Wait until acommandFinishednotification is received for the previous command before retrying.', 'RC_NACK' : 'User commands queue is full', 'RC_WRITE_FAIL' : 'Flash write error; cannot save new settings', }, }, { 'id' : 35, 'name' : 'radiotestTx', 'description': 'The radiotestTx command allows the user to initiate a radio transmission test. It may only be executed if the manager has been booted up in radiotest mode (see setNetworkConfig command). Three types of transmission tests are supported:\n\n- Packet transmission\n- Continuous modulation (CM)\n- Continuous wave, i.e unmodulated signal (CW)\n\nIn a packet transmission test, the device generates a repeatCnt number of packet sequences. Each sequence consists of up to 10 packets with configurable size and delays. Each packet starts with a PHY preamble (5 bytes), followed by a PHY length field (1 byte), followed by data payload of up to 125 bytes, and finally a 2-byte 802.15.4 CRC at the end. Byte 0 of the payload contains stationId of the sender. Bytes 1 and 2 contain the packet number (in big-endian format) that increments with every packet transmitted. Bytes 3..N contain a counter (from 0..N-2) that increments with every byte inside payload. Transmissions occur on the set of channels defined by chanMask , selected inpseudo-randomorder.\n\nIn a continuous modulation test, the device generates continuous pseudo-random modulated signal, centered at the specified channel. The test is stopped by resetting the device.\n\nIn a continuous wave test, the device generates an unmodulated tone, centered at the specified channel. The test tone is stopped by resetting the device.\n\n\n\nChannel numbering is 0-15, corresponding to IEEE 2.4 GHz channels 11-26.\n\nThe station ID is a user selectable value. It is used in packet tests so that a receiver (see radiotestRx) can identify packets from this device in cases where there may be multiple tests running in the same radio space. This field is not used for CM or CW tests.', 'request' : [ ['testType', INT, 1, 'radiotestType'], ['chanMask', HEXDATA, 2, None], ['repeatCnt', INT, 2, None], ['txPower', INTS, 1, None], ['seqSize', INT, 1, 'seqSize'], ['pkLen_1', INT, 1, None], ['delay_1', INT, 2, None], ['pkLen_2', INT, 1, None], ['delay_2', INT, 2, None], ['pkLen_3', INT, 1, None], ['delay_3', INT, 2, None], ['pkLen_4', INT, 1, None], ['delay_4', INT, 2, None], ['pkLen_5', INT, 1, None], ['delay_5', INT, 2, None], ['pkLen_6', INT, 1, None], ['delay_6', INT, 2, None], ['pkLen_7', INT, 1, None], ['delay_7', INT, 2, None], ['pkLen_8', INT, 1, None], ['delay_8', INT, 2, None], ['pkLen_9', INT, 1, None], ['delay_9', INT, 2, None], ['pkLen_10', INT, 1, None], ['delay_10', INT, 2, None], ['stationId', INT, 1, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_IN_PROGRESS' : 'Radiotest is in progress', 'RC_INVALID_ARGUMENT' : 'Invalid "channel" or "txPower" value', }, 'serializer' : 'serialize_radiotestTx', }, { 'id' : 37, 'name' : 'radiotestRx', 'description': 'The radiotestRx command clears all previously collected statistics and initiates radio reception on the specified channel. It may only be executed if the manager has been booted up in radiotest mode (see setNetworkConfig command). During the test, the device keeps statistics about the number of packets received (with and without error). The test results may be retrieved using the getRadiotestStatistics command.\n\nThe station ID is a user selectable value. It must be set to match the station ID used by the transmitter. Station ID is used to isolate traffic if multiple tests are running in the same radio space.\n\n\n\nChannel numbering is 0-15, corresponding to IEEE 2.4 GHz channels 11-26.', 'request' : [ ['mask', HEXDATA, 2, None], ['duration', INT, 2, None], ['stationId', INT, 1, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_IN_PROGRESS' : 'Radiotest is in progress', 'RC_INVALID_ARGUMENT' : 'Invalid mask value', }, }, { 'id' : 38, 'name' : 'getRadiotestStatistics', 'description': 'This command retrieves statistics from a previously run radiotestRx command.It may only be executed if the manager has been booted up in radiotest mode (see setNetworkConfig command).', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['rxOk', INT, 2, None], ['rxFail', INT, 2, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_IN_PROGRESS' : 'Radiotest is in progress', 'RC_INVALID_COMMAND' : 'No radiotest was started', }, }, { 'id' : 39, 'name' : 'setACLEntry', 'description': 'The setACLEntry command adds a new entry or updates an existing entry in the Access Control List (ACL).This change is persistent.', 'request' : [ ['macAddress', HEXDATA, 8, None], ['joinKey', HEXDATA, 16, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NO_RESOURCES' : 'ACL is full (when adding a new entry)', 'RC_WRITE_FAIL' : 'Flash write error, can\'t save new settings', }, }, { 'id' : 40, 'name' : 'getNextACLEntry', 'description': 'The getNextACLEntry command returns information about next mote entry in the access control list (ACL). To begin a search (find the first mote in ACL), a zero MAC address (0000000000000000) should be sent. There is no mechanism for reading the ACL entry of a specific mote. This call is an iterator. If you call getNextACLEntry with mote A as the argument, your response is the ACL entry for mote B, where B is the next mote in the ACL.', 'request' : [ ['macAddress', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['macAddress', HEXDATA, 8, None], ['joinKey', HEXDATA, 16, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_END_OF_LIST' : 'End of ACL is reached', 'RC_NOT_FOUND' : 'No such mote in the ACL', }, }, { 'id' : 41, 'name' : 'deleteACLEntry', 'description': 'The deleteACLEntry command deletes the specified mote from the access control list (ACL). If the macAddress parameter is set to all 0xFFs or all 0x00s, the entire ACL is cleared. This change is persistent.', 'request' : [ ['macAddress', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'Specified mote is not found in ACL', 'RC_WRITE_FAIL' : 'Flash write error, can\'t save new settings', }, }, { 'id' : 42, 'name' : 'pingMote', 'description': 'The pingMote command sends a ping (echo request) to the mote specified by MAC address. A unique callbackId is generated and returned with the response. When the response is received from the mote, the manager generates a pingResponse notification with the measured round trip delay and several other parameters. The request is sent using unacknowledged transport, so the mote is not guaranteed to receive the request.', 'request' : [ ['macAddress', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['callbackId', INT, 4, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'Specified mote not found', 'RC_INV_STATE' : 'Mote is not in operational state', 'RC_NO_RESOURCES' : 'User commands queue is full', 'RC_IN_PROGRESS' : 'Previous echo request command is still pending for specified mote', }, }, { 'id' : 43, 'name' : 'getLog', 'description': 'The getLog command retrieves diagnostic logs from the manager or a mote specified by MAC address.', 'request' : [ ['macAddress', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'Specified mote not found', 'RC_INV_STATE' : 'Mote is not in operational state', }, }, { 'id' : 44, 'name' : 'sendData', 'description': "The sendData command sends a packet to a mote in the network. The response contains a callbackId. When the manager injects the packet into the network, it will generate a packetSent notification. It is the responsibility of the customer'sapplication layer at the mote to send a response. It is also the responsibility of thecustomer's application layer to timeout if no response is received at the manager if one is expected.\n\nThe sendData command should be used by applications that communicate directly with the manager. If end-to-end (application to mote) IP connectivity is required, the application should use the sendIP command. For a more comprehensive discussion of the distinction, see the SmartMesh IPNetwork User Guide.", 'request' : [ ['macAddress', HEXDATA, 8, None], ['priority', INT, 1, 'packetPriority'], ['srcPort', INT, 2, None], ['dstPort', INT, 2, None], ['options', INT, 1, None], ['data', HEXDATA, None,None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['callbackId', INT, 4, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'Specified mote is not found', 'RC_INV_STATE' : 'Mote is not in operational state', 'RC_NACK' : 'User commands queue is full or couldn\'t allocate memory buffer for payload', 'RC_INVALID_ARGUMENT' : 'Payload size exceeds maximum allowed value', }, }, { 'id' : 45, 'name' : 'startNetwork', 'description': 'The startNetwork command tells the manager to allow the network to start forming (begin accepting join requests from devices). The external application must issue the startNetwork command if the autoStartNetwork flag is not set (see setNetworkConfig).\n\nThis command has been deprecated and should not be used in new designs.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_IN_PROGRESS' : 'The network is already started', }, }, { 'id' : 46, 'name' : 'getSystemInfo', 'description': 'The getSystemInfo command returns system-level information about the hardware and software versions.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['macAddress', HEXDATA, 8, None], ['hwModel', INT, 1, None], ['hwRev', INT, 1, None], ['swMajor', INT, 1, None], ['swMinor', INT, 1, None], ['swPatch', INT, 1, None], ['swBuild', INT, 2, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 47, 'name' : 'getMoteConfig', 'description': 'The getMoteConfig command returns a single mote description as the response. The command takes two arguments, a MAC Address and a flag indicating whether the MAC Address refers to the requested mote or to the next mote in managers memory. This command may be used to iterate through all motes known by the manager by starting with the macAddress parameter set to 0 and next set to true, and then using the MAC Address of that response as the input to the next call.\n\nThe mote MAC address is used in all query commands, but space constraints require the neighbor health reports to use the Mote ID for identification. Therefore, both identifiers are present in the mote structure.', 'request' : [ ['macAddress', HEXDATA, 8, None], ['next', BOOL, 1, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['macAddress', HEXDATA, 8, None], ['moteId', INT, 2, None], ['isAP', BOOL, 1, None], ['state', INT, 1, 'moteState'], ['reserved', INT, 1, None], ['isRouting', BOOL, 1, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'The specified mote doesn\'t exist', 'RC_END_OF_LIST' : 'Last mote in the list has been reached (next = true)', }, }, { 'id' : 48, 'name' : 'getPathInfo', 'description': 'The getPathInfo command returns parameters of requested path.', 'request' : [ ['source', HEXDATA, 8, None], ['dest', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['source', HEXDATA, 8, None], ['dest', HEXDATA, 8, None], ['direction', INT, 1, 'pathDirection'], ['numLinks', INT, 1, None], ['quality', INT, 1, None], ['rssiSrcDest', INTS, 1, None], ['rssiDestSrc', INTS, 1, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'A path between the specified motes doesn\'t exist', }, }, { 'id' : 49, 'name' : 'getNextPathInfo', 'description': 'The getNextPathInfo command allows iteration across paths connected to a particular mote. The pathId parameter indicates the previous value in the iteration. Setting pathId to 0 returns the first path. A pathId can not be used as a unique identifier for a path. It is only valid when associated with a particular mote.', 'request' : [ ['macAddress', HEXDATA, 8, None], ['filter', INT, 1, 'pathFilter'], ['pathId', INT, 2, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['pathId', INT, 2, None], ['source', HEXDATA, 8, None], ['dest', HEXDATA, 8, None], ['direction', INT, 1, 'pathDirection'], ['numLinks', INT, 1, None], ['quality', INT, 1, None], ['rssiSrcDest', INTS, 1, None], ['rssiDestSrc', INTS, 1, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'The specified path ID does not exist', 'RC_END_OF_LIST' : 'The specified pathId in the request is the end of the list', }, }, { 'id' : 50, 'name' : 'setAdvertising', 'description': 'The setAdvertising command tells the manager to activate or deactivate advertising. The response is a callbackId. A commandFinished notification with the callbackId is generated when the command propagation is complete.', 'request' : [ ['activate', INT, 1, 'advertisementState'], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['callbackId', INT, 4, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_IN_PROGRESS' : 'A command is still pending. Wait until acommandFinishednotification is received for the previous command before retrying.', }, }, { 'id' : 51, 'name' : 'setDownstreamFrameMode', 'description': 'The setDownstreamFrameMode command tells the manager to shorten or extend the downstream slotframe. The base slotframe length will be multiplied by the downFrameMultVal for "normal" speed. For "fast" speed the downstream slotframe is the base length.Once this command is executed, the manager switches to manual mode and no longer changes slotframesize automatically. The response is a callbackId. A commandFinished notification with the callbackId is generated when the command propagation is complete.', 'request' : [ ['frameMode', INT, 1, 'downstreamFrameMode'], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['callbackId', INT, 4, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_IN_PROGRESS' : 'A command is still pending. Wait until acommandFinishednotification is received for the previous command before retrying.', 'RC_INVALID_ARGUMENT' : 'The downFrameMultVal (as set by setNetworkConfig) is equal to 1, so changing the downstream frame mode would have no effect.', }, }, { 'id' : 53, 'name' : 'getManagerStatistics', 'description': 'The getManagerStatistics command returns dynamic information and statistics about the manager API. The statistics counts are cleared together with all current statistics using clearStatistics.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['serTxCnt', INT, 2, None], ['serRxCnt', INT, 2, None], ['serRxCRCErr', INT, 2, None], ['serRxOverruns', INT, 2, None], ['apiEstabConn', INT, 2, None], ['apiDroppedConn', INT, 2, None], ['apiTxOk', INT, 2, None], ['apiTxErr', INT, 2, None], ['apiTxFail', INT, 2, None], ['apiRxOk', INT, 2, None], ['apiRxProtErr', INT, 2, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 54, 'name' : 'setTime', 'description': 'This command has been deprecated, and should not be used in new designs. When the Manager restarts, it will start counting from 20:00:00 UTC July 2, 2002.\n\nThe setTime command sets the UTC time on the manager. This command may only be executed when the network is not running. If the trigger flag is false, the manager sets the specified time as soon as it receives the setTime command. When the manager receives a Time Pin trigger, it temporarily stores the current time. If a setTime request is received within a short period of time following the trigger, the manager calculates the delay since the trigger and adjust the time such that the trigger was received at the specified time value.', 'request' : [ ['trigger', INT, 1, None], ['utcSecs', INT, 8, None], ['utcUsecs', INT, 4, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed. The manager is ready to set the time.', 'RC_INVALID_ARGUMENT' : 'One of the parameters was invalid', 'RC_VALIDATION_ERROR' : 'Network is running, setTime command is disabled.', }, }, { 'id' : 55, 'name' : 'getLicense', 'description': 'The getLicense command has been deprecated in Manager >= 1.3.0.There is no need to use a license to enable > 32 mote networks.\n\nThe getLicense command returns the current license key.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['license', HEXDATA, 13, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 56, 'name' : 'setLicense', 'description': 'The setLicense command has been deprecated in Manager >= 1.3.0. There is no longer a need to use a license to enable > 32 mote networks.\n\nThe setLicense command validates and updates the software license key stored in flash. Features enabled or disabled by the license key change will take effect after the device is restarted.If the license parameter is set to all 0x0s, the manager restores the default license. This change is persistent.', 'request' : [ ['license', HEXDATA, 13, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_VALIDATION_ERROR' : 'The license key is not valid', 'RC_WRITE_FAIL' : 'Flash write error, cannot save new settings', }, }, { 'id' : 58, 'name' : 'setCLIUser', 'description': 'The setCLIUser command sets the password that must be used to log into the command line for a particular user role. The user roles are:\n\n- Viewer - read-only access to non-sensitive information\n- User - read-write access This change is persistent.', 'request' : [ ['role', INT, 1, 'userRole'], ['password', HEXDATA, 16, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_WRITE_FAIL' : 'Flash write error, can\'t save new settings', }, }, { 'id' : 59, 'name' : 'sendIP', 'description': 'The sendIP command sends a 6LoWPAN packet to a mote in the network. The response contains a callback Id. When the manager injects the packet into the network, it will generate a packetSent notification with the calllbackId. The application is responsible for constructing a valid 6LoWPAN packet. The packet is sent to the mote best-effort, so the application should deal with responses and timeouts, if any.\n\nThe sendIP command should be used by applications that require end-to-end IP connectivity. For applications that do not require end-to-end IP connectivity, the sendData command provides a simpler interface without requiring the application to understand 6LoWPAN encapsulation. For a more comprehensive discussion of the distinction, see the SmartMesh IP Network User Guide.', 'request' : [ ['macAddress', HEXDATA, 8, None], ['priority', INT, 1, 'packetPriority'], ['options', INT, 1, None], ['encryptedOffset', INT, 1, None], ['data', HEXDATA, None,None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['callbackId', INT, 4, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'Specified mote is not found', 'RC_INV_STATE' : 'Mote is not in operational state', 'RC_NACK' : 'User commands queue is full or could not allocate memory buffer for payload', 'RC_INVALID_ARGUMENT' : 'Payload size exceeds maximum allowed value or the 6LoWPAN packet is invalid', }, }, { 'id' : 61, 'name' : 'restoreFactoryDefaults', 'description': 'The restoreFactoryDefaults command restores the default configuration and clears the ACL. This change is persistent.\n\nFor Manager versions <1.3.0 that required a license, the license used to enable optional features is preserved during a restore.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_WRITE_FAIL' : 'Flash write error; cannot save new settings', }, }, { 'id' : 62, 'name' : 'getMoteInfo', 'description': 'The getMoteInfo command returns dynamic information for the specified mote.', 'request' : [ ['macAddress', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['macAddress', HEXDATA, 8, None], ['state', INT, 1, 'moteState'], ['numNbrs', INT, 1, None], ['numGoodNbrs', INT, 1, None], ['requestedBw', INT, 4, None], ['totalNeededBw', INT, 4, None], ['assignedBw', INT, 4, None], ['packetsReceived', INT, 4, None], ['packetsLost', INT, 4, None], ['avgLatency', INT, 4, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'No such mote', }, }, { 'id' : 63, 'name' : 'getNetworkConfig', 'description': 'The getNetworkConfig command returns general network configuration parameters, including the Network ID, bandwidth parameters and number of motes.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['networkId', INT, 2, None], ['apTxPower', INTS, 1, None], ['frameProfile', INT, 1, True], ['maxMotes', INT, 2, None], ['baseBandwidth', INT, 2, None], ['downFrameMultVal', INT, 1, None], ['numParents', INT, 1, None], ['ccaMode', INT, 1, True], ['channelList', INT, 2, None], ['autoStartNetwork', BOOL, 1, None], ['locMode', INT, 1, None], ['bbMode', INT, 1, 'backboneFrameMode'], ['bbSize', INT, 1, None], ['isRadioTest', INT, 1, None], ['bwMult', INT, 2, None], ['oneChannel', INT, 1, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 64, 'name' : 'getNetworkInfo', 'description': 'The getNetworkInfo command returns dynamic network information and statistics.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['numMotes', INT, 2, None], ['asnSize', INT, 2, None], ['advertisementState', INT, 1, True], ['downFrameState', INT, 1, 'downstreamFrameMode'], ['netReliability', INT, 1, None], ['netPathStability', INT, 1, None], ['netLatency', INT, 4, None], ['netState', INT, 1, 'networkState'], ['ipv6Address', HEXDATA, 16, None], ['numLostPackets', INT, 4, None], ['numArrivedPackets', INT, 8, None], ['maxNumbHops', INT, 1, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 65, 'name' : 'getMoteConfigById', 'description': 'The getMoteConfigById command returns a single mote description as the response. The command takes one argument, the short address of a mote (Mote ID). The command returns the same response structure as the getMoteConfig command.', 'request' : [ ['moteId', INT, 2, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['macAddress', HEXDATA, 8, None], ['moteId', INT, 2, None], ['isAP', BOOL, 1, None], ['state', INT, 1, 'moteState'], ['reserved', INT, 1, None], ['isRouting', BOOL, 1, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'No such mote', }, }, { 'id' : 66, 'name' : 'setCommonJoinKey', 'description': 'The setCommonJoinKey command will set a new value for the common join key. The common join key is used to decrypt join messages only if the ACL is empty.', 'request' : [ ['key', HEXDATA, 16, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 67, 'name' : 'getIPConfig', 'description': 'The getIPConfig command returns the manager\'s IP configuration parameters, including the IPv6 address and mask.', 'request' : [ ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['ipv6Address', HEXDATA, 16, None], ['mask', HEXDATA, 16, None], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', }, }, { 'id' : 68, 'name' : 'setIPConfig', 'description': 'The setIPConfig command sets the IPv6 prefix of the mesh network. Only the upper 8 bytes of the IPv6 address are relevant: the lower 8 bytes of the IPv6 address are ignored, and lower 8 bytes of the mask field are reserved and should be set to 0.This change is persistent.', 'request' : [ ['ipv6Address', HEXDATA, 16, None], ['mask', HEXDATA, 16, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_WRITE_FAIL' : 'Flash write error, can\'t save new settings', }, }, { 'id' : 69, 'name' : 'deleteMote', 'description': 'The deleteMote command deletes a mote from the manager\'s list. A mote can only be deleted if it in the Lost or Unknown states. This change is persistent.', 'request' : [ ['macAddress', HEXDATA, 8, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ], }, 'responseCodes': { 'RC_OK' : 'Command successfully completed', 'RC_NOT_FOUND' : 'Specified mote is not found', 'RC_INV_STATE' : 'Mote state is not Lost or mote is access point', 'RC_WRITE_FAIL' : 'Flash write error, can\'t save new settings', }, }, { 'id' : 70, 'name' : 'getMoteLinks', 'description': 'The getMoteLinks command returns information about links assigned to the mote. The response contains a list of links starting with Nth link on the mote, where N is supplied as the idx parameter in the request. To retrieve all links on the device the user can call this command with idx that increments by number of links returned with priorresponse, until the command returns RC_END_OF_LIST response code. Note that links assigned to a mote may change between API calls.', 'request' : [ ['macAddress', HEXDATA, 8, None], ['idx', INT, 2, None], ], 'response' : { 'FIELDS': [ [RC, INT, 1, True], ['idx', INT, 2, None], ['utilization', INT, 1, None], ['numLinks', INT, 1, None], ['frameId_1', INT, 1, None], # 1 ['slot_1', INT, 4, None], ['channelOffset_1', INT, 1, None], ['moteId_1', INT, 2, None], ['flags_1', INT, 1, None], ['frameId_2', INT, 1, None], # 2 ['slot_2', INT, 4, None], ['channelOffset_2', INT, 1, None], ['moteId_2', INT, 2, None], ['flags_2', INT, 1, None], ['frameId_3', INT, 1, None], # 3 ['slot_3', INT, 4, None], ['channelOffset_3', INT, 1, None], ['moteId_3', INT, 2, None], ['flags_3', INT, 1, None], ['frameId_4', INT, 1, None], # 4 ['slot_4', INT, 4, None], ['channelOffset_4', INT, 1, None], ['moteId_4', INT, 2, None], ['flags_4', INT, 1, None], ['frameId_5', INT, 1, None], # 5 ['slot_5', INT, 4, None], ['channelOffset_5', INT, 1, None], ['moteId_5', INT, 2, None], ['flags_5', INT, 1, None], ['frameId_6', INT, 1, None], # 6 ['slot_6', INT, 4, None], ['channelOffset_6', INT, 1, None], ['moteId_6', INT, 2, None], ['flags_6', INT, 1, None], ['frameId_7', INT, 1, None], # 7 ['slot_7', INT, 4, None], ['channelOffset_7', INT, 1, None], ['moteId_7', INT, 2, None], ['flags_7', INT, 1, None], ['frameId_8', INT, 1, None], # 8 ['slot_8', INT, 4, None], ['channelOffset_8', INT, 1, None], ['moteId_8', INT, 2, None], ['flags_8', INT, 1, None], ['frameId_9', INT, 1, None], # 9 ['slot_9', INT, 4, None], ['channelOffset_9', INT, 1, None], ['moteId_9', INT, 2, None], ['flags_9', INT, 1, None], ['frameId_10', INT, 1, None], # 10 ['slot_10', INT, 4, None], ['channelOffset_10', INT, 1, None], ['moteId_10', INT, 2, None], ['flags_10', INT, 1, None], ], }, 'responseCodes': { 'RC_NOT_FOUND' : 'No such mote.', 'RC_INV_STATE' : 'Mote is not in operational state', 'RC_END_OF_LIST' : 'The index requested is greater than number of links.', }, }, ] subCommandsEvents = [ { 'id' : 0, 'name' : 'eventMoteReset', 'description': 'This notification is sent when a user-initiated reset is executed by the manager.', 'response' : { 'FIELDS': [ ['macAddress', HEXDATA, 8, None], ], }, }, { 'id' : 1, 'name' : 'eventNetworkReset', 'description': 'This notification is sent when the manager starts the network. This event has no eventData fields.', 'response' : { 'FIELDS': [ ], }, }, { 'id' : 2, 'name' : 'eventCommandFinished', 'description': 'The commandFinished notification is sent when a command associated with the provided callback id finishes executing.', 'response' : { 'FIELDS': [ ['callbackId', HEXDATA, 4, None], ['rc', INT, 1, 'commandFinishedResult'], ], }, }, { 'id' : 3, 'name' : 'eventMoteJoin', 'description': 'This notification is sent when a mote joins the network.', 'response' : { 'FIELDS': [ ['macAddress', HEXDATA, 8, None], ], }, }, { 'id' : 4, 'name' : 'eventMoteOperational', 'description': 'This notification is sent when a mote that joins the network becomes operational.', 'response' : { 'FIELDS': [ ['macAddress', HEXDATA, 8, None], ], }, }, { 'id' : 5, 'name' : 'eventMoteLost', 'description': "This notification is sent when a mote's state changes to Lost , which indicates that the mote is not responding to downstream messages.", 'response' : { 'FIELDS': [ ['macAddress', HEXDATA, 8, None], ], }, }, { 'id' : 6, 'name' : 'eventNetworkTime', 'description': 'The time notification is triggered by the client asserting the TIME pin or by calling the getTime command. This notification contains the time when the TIME pin was asserted (or the getTime command was processed) expressed as:\n\n- ASN The absolute slot number (the number of timeslots since " 7/2/2002 8:00:00 PM PST" if UTC is set on manager, otherwise since Jan 1, 1970)\n\n\n- Uptime The number of seconds since the device was booted\n- Unixtime The number of seconds and microseconds since Jan 1, 1970 in UTC', 'response' : { 'FIELDS': [ ['uptime', INT, 4, None], ['utcSecs', INT, 8, None], ['utcUsecs', INT, 4, None], ['asn', HEXDATA, 5, None], ['asnOffset', INT, 2, None], ], }, }, { 'id' : 7, 'name' : 'eventPingResponse', 'description': 'This notification is sent when a reply is received from a mote ping.', 'response' : { 'FIELDS': [ ['callbackId', INT, 4, None], ['macAddress', HEXDATA, 8, None], ['delay', INT, 4, None], ['voltage', INT, 2, None], ['temperature', INTS, 1, None], ], }, }, { 'id' : 10, 'name' : 'eventPathCreate', 'description': 'This notification is sent when the manager creates a connection (path) between two motes.', 'response' : { 'FIELDS': [ ['source', HEXDATA, 8, None], ['dest', HEXDATA, 8, None], ['direction', INT, 1, 'pathDirection'], ], }, }, { 'id' : 11, 'name' : 'eventPathDelete', 'description': 'This notification is sent when the manager removes a connection (path) between two motes.', 'response' : { 'FIELDS': [ ['source', HEXDATA, 8, None], ['dest', HEXDATA, 8, None], ['direction', INT, 1, 'pathDirection'], ], }, }, { 'id' : 12, 'name' : 'eventPacketSent', 'description': 'The packetSent notification is generated when client\'s packet is removed from manager\'s queue and sent into the wireless network.', 'response' : { 'FIELDS': [ ['callbackId', INT, 4, None], ['rc', INT, 1, None], ], }, }, { 'id' : 13, 'name' : 'eventMoteCreate', 'description': 'This event is sent when a mote joins the manager for the first time.', 'response' : { 'FIELDS': [ ['macAddress', HEXDATA, 8, None], ['moteId', INT, 2, None], ], }, }, { 'id' : 14, 'name' : 'eventMoteDelete', 'description': 'This notification is sent when a mote is deleted as a result of moteDelete command.', 'response' : { 'FIELDS': [ ['macAddress', HEXDATA, 8, None], ['moteId', INT, 2, None], ], }, }, ] subCommandsNotification = [ { 'id' : 1, 'name' : 'notifEvent', 'description': 'Event notification', 'response' : { 'FIELDS': [ ['eventId', INT, 4, None], [SUBID2, INT, 1, None], ], }, 'subCommands': subCommandsEvents, }, { 'id' : 2, 'name' : 'notifLog', 'description': 'A log notifications is generated in response to the getLog command. Each log notification contains a message from the mote\'s log.', 'response' : { 'FIELDS': [ ['macAddress', HEXDATA, 8, None], ['logMsg', HEXDATA, None,None], ], }, }, { 'id' : 4, 'name' : 'notifData', 'description': 'The data notification contains a header and a variable length array of binary data. The length of the data is determined based on the length of the notification.\n\nThe manager forwards all packets received on its IP address and non-manager ports as data notifications.', 'response' : { 'FIELDS': [ ['utcSecs', INT, 8, None], ['utcUsecs', INT, 4, None], ['macAddress', HEXDATA, 8, None], ['srcPort', INT, 2, None], ['dstPort', INT, 2, None], ['data', HEXDATA, None,None], ], }, }, { 'id' : 5, 'name' : 'notifIpData', 'description': "The ipData notification contains full IP packet sent by the mote, including 6LoWPAN header, UDP header, and the UDP payload. Manager generates this notification when it receives packet from a mote with destination other than manager's own IP address. The size of the data field can be calculated by subtracting the fixed header size (up to macAddress) from the size of overall notification packet.", 'response' : { 'System': [ ['utcSecs', INT, 8, None], ['utcUsecs', INT, 4, None], ['macAddress', HEXDATA, 8, None], ['data', HEXDATA, None,None], ], }, }, { 'id' : 6, 'name' : 'notifHealthReport', 'description': 'The healthReport notifications include the raw payload of health reports received from devices. The payload contains one or more specific health report messages. Each message contains an identifier, length and variable-sized data. The individual healthReport message structures are defined below.', 'response' : { 'System': [ ['macAddress', HEXDATA, 8, None], ['payload', HEXDATA, None,None], ], }, }, ] # We redefine this attribute inherited from ApiDefinition. See # ApiDefinition for a full description of the structure of this field. notifications = [ { 'id' : 3, 'name' : 'manager_hello', 'description': 'Sent by the manager to a initiate new session with a client.', 'response' : { 'FIELDS': [ ['version', INT, 1, None], ['mode', INT, 1, None], ], }, }, { 'id' : 20, 'name' : 'notification', 'description': '', 'response' : { 'FIELDS': [ [SUBID1, INT, 1, None], ] }, 'subCommands': subCommandsNotification, }, ] def serialize_radiotestTx(self, commandArray, cmd_params): # start by serializing with complete API definition returnVal = self.default_serializer(commandArray, cmd_params) # remove the unused sequence definitions startIndex = 7+cmd_params['seqSize']*3 numVals = 10-cmd_params['seqSize'] returnVal[1][startIndex:startIndex+numVals*3] = [] return returnVal

[ "twatteyne@linear.com" ]

twatteyne@linear.com

361d332a36051cf2846855e434f8291687e94b7a

0c6332a4ab51a2b762d74c6a73b321838637fa06

/Haystome2/wsgi.py

b04a2d7141c334fa57e2376e242c5508d348ce4a

[]

no_license

bopopescu/Haystome

58d097125506a35b4ded60f52d8ab9ff28060c25

9242f96a17fdd63696179e9015f54f7b1e000d9b

refs/heads/master

2022-11-20T01:33:20.999462

2019-12-05T01:31:41

280,994,289

0

null

2020-07-20T02:33:35

2020-07-20T02:33:34

null

UTF-8

Python

false

395

py

""" WSGI config for Haystome2 project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/2.2/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'Haystome2.settings') application = get_wsgi_application()

[ "tan.rathanah@gmail.com" ]

tan.rathanah@gmail.com

fb86da0ccb95eb27bef39c4322166f68a0ee5aaa

4acab9fb77c551ee58b00df025431376f11106be

/1. PythonChallenges/reverse.py

b7621e2809df5f1ec1bf36231f485545e94ccaab

[]

no_license

MakeSchool-17/twitter-bot-python-samlee405

e7404f278eeb07097577eefbe5f549e450087089

09a14af858af89292d4d636d91f7be2d35118cfe

refs/heads/master

2021-01-18T23:07:09.913608

2016-11-28T21:24:44

72,684,235

1

0

null

UTF-8

Python

false

344

py

import sys def main(): argumentList = sys.argv del argumentList[0] inputString = " ".join(argumentList) newString = "" index = len(inputString) for _ in range(0, index): newString = newString + inputString[index - 1] index = index - 1 print("The reverse of your string is: " + newString) main()

[ "samlee405@yahoo.com" ]

samlee405@yahoo.com

2c7925a442418e9717b78845dced5ee0d39b26da

d7775fa094ce48785c4a9abbc00ed1e3cd3a8ba8

/api/tests/test_hotel.py

7907bba8fd4281d2ecac2e1bec6f9efdce4c25b3

[]

no_license

fabricioadenir/tourismAPI

75580ef45ef51f9123dc6879ef9ed9c1e9b956f1

8e65dcde7c03fc2fbf8d015b6db2ebc96fbcefdb

refs/heads/main

2023-02-17T19:16:01.613525

2021-01-19T16:50:31

321,408,077

0

null

2021-01-19T16:50:32

2020-12-14T16:31:38

Python

UTF-8

Python

false

2,009

py

from django.test import TestCase from rest_framework.test import APIRequestFactory from rest_framework.test import force_authenticate from django.contrib.auth.models import User from api.models import Hotel, Category, City, Country from api.views import HotelViewSet class HotelViewSetTestClass(TestCase): """ Responsible for testing the data structure. """ def setUp(self): Category.objects.create(name="Hospedagem de Verão") City.objects.create( name="Florianópolis", state="SC" ) Country.objects.create( name="Brasil" ) category = Category.objects.get(id=1) city = City.objects.get(id=1) country = Country.objects.get(id=1) self.hotel = Hotel.objects.create( hotel_name="Alameda Alegra", image="http://tourism.com/images/alameda-alegra.jpg", city=city, country=country, category=category, price=3000 ) self.username = 'tourism' self.password = 'tourism_pwd' self.user = User.objects.create_superuser( self.username, 'test@example.com', self.password) def test_without_authentication(self): """ Test without authentication """ api_request = APIRequestFactory().get("") detail_view = HotelViewSet.as_view({'get': 'retrieve'}) response = detail_view(api_request, pk=self.hotel.pk) self.assertEqual(response.status_code, 403) def test_with_authentication(self): """ Auth using force_authenticate """ factory = APIRequestFactory() user = User.objects.get(username=self.username) detail_view = HotelViewSet.as_view({'get': 'retrieve'}) api_request = factory.get('') force_authenticate(api_request, user=user) response = detail_view(api_request, pk=self.hotel.pk) self.assertEqual(response.status_code, 200)

[ "fabricio.adenir@softplan.com.br" ]

fabricio.adenir@softplan.com.br

a5cd54ab133af5c5678d2b51970ce91d246f1b8b

c4c63c0ee30b655ef335afa6bce361746be27d9f

/app/User/models.py

221e561bd86cb7f0a2713eea845b34d931fc93a4

[]

no_license

neofit77/food-recipes-web-service

6227bec14627cf9c52af6203b40794c57eedfd52

e16faaf13b9dff933e0c0655f47ec00fafe256f1

refs/heads/main

2023-07-14T19:43:02.850531

2021-08-20T08:50:13

396,765,256

0

null

UTF-8

Python

false

2,055

py

from django.db import models from django.contrib.auth.models import AbstractBaseUser, BaseUserManager, PermissionsMixin from django.db import models from rest_framework_simplejwt.tokens import RefreshToken from django.contrib.auth.hashers import make_password class UserManager(BaseUserManager): """Overide default methods for django User model""" def create_user(self, username, email, password=None): """Overide create_user method""" if username is None: raise TypeError('Users should have a username') user = self.model(username=username, email=self.normalize_email(email)) user.set_password(make_password(password)) user.save() return user def create_superuser(self, username, email, password): """Overide method that create superuser""" if password is None: raise TypeError('Password should not be none') user = self.create_user(username, email, password) user.is_superuser = True user.is_staff = True user.save() return user class User(AbstractBaseUser, PermissionsMixin): """Overide built django class User""" username = models.CharField(max_length=40, unique=True) email = models.EmailField(max_length=40, unique=True) first_name = models.CharField(max_length=40) last_name = models.CharField(max_length=40) company_name = models.CharField(max_length=100, default='') company_domain = models.CharField(max_length=50, default='') city = models.CharField(max_length=60, default='') is_staff = models.BooleanField(default=False) created_at = models.DateTimeField(auto_now=True) updated_at = models.DateTimeField(auto_now=True) USERNAME_FIELD = 'username' REQUIRED_FIELDS = ['email'] objects = UserManager() def __str__(self): return self.username def tokens(self): refresh = RefreshToken.for_user(self) return { 'refresh': str(refresh), 'access': str(refresh.access_token) }

[ "aleksandar.petrovicvr@gmail.com" ]

aleksandar.petrovicvr@gmail.com

97beaeedfc15447c373d82819beeb0e8631738aa

d4a891ea1d8fd87068daee7a8dfa2f0968add0e7

/MyDProject/album/migrations/0002_belongs.py

5bdc046e16da380927217a08d90683406b4505de

[]

no_license

pravinkmrp/MyProjectRepo

f5a320ba0604b37ae69ee932444e283697910dfe

68ce63aed02cd7cbef7a07b01ba0553b256e8700

refs/heads/master

2021-01-22T02:34:22.026108

2020-09-17T11:48:43

30,541,674

0

null

UTF-8

Python

false

685

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('album', '0001_initial'), ] operations = [ migrations.CreateModel( name='Belongs', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('folder', models.ForeignKey(to='album.Folder')), ('parent', models.ForeignKey(related_name='parent', to='album.Folder')), ], options={ }, bases=(models.Model,), ), ]

[ "pravinkmrp@gmail.com" ]

pravinkmrp@gmail.com

950f014ebeca729c8a7fc11225d996b5ce09836c

ead3782e2d3cd07bf0b513ce5bf4b0a9f443e8e0

/classes_play.py

66933044fd66f5bfccf0c4e0f14a7e740a4f74a8

[]

no_license

racinmat/kralupy_coding

013fa6209ef6de9c633563f5609fc6ef018c61b2

c61646c3fbe38c95d46900c398b4d34143d063d0

refs/heads/master

2020-07-06T03:27:54.614442

2019-08-25T09:52:32

202,874,065

0

null

UTF-8

Python

false

2,869

py

class Inventory: my_items = [] def __init__(self, items) -> None: super().__init__() self.items = items print('já jsem konstruktor') def filled_size(self): return len(self.items) def __repr__(self) -> str: return f'Inventory(items={self._items})' def __contains__(self, item): return item in self._items def loot_inventory(self, another: 'Inventory'): self.items += another.items another.items = [] def __iter__(self): return iter(self._items) @property def items(self): return self._items.copy() @items.setter def items(self, other_items): self._items = other_items class LimitedInventory(Inventory): def __init__(self, items, max_capacity) -> None: self.max_capacity = max_capacity super().__init__(items) def loot_inventory(self, another: 'Inventory'): free_space = self.max_capacity - self.filled_size() if another.filled_size() > free_space: self.items += another.items[:free_space] another.items = another.items[free_space:] else: self.items += another.items another.items = [] @property def items(self): return self._items.copy() @items.setter def items(self, other_items): if len(other_items) > self.max_capacity: raise Exception('inventory is too small') self._items = other_items def create_inventories(): inventory_1 = Inventory([ 'malá věc', 'velká věc']) inventory_2 = LimitedInventory([ 'malá věc', 'střední věc', 'veká věc'], 4) return [inventory_1, inventory_2] def main(): inventory_1 = Inventory([ 'vařečka', 'meč osudu']) inventory_2 = LimitedInventory([ 'vařečka', 'meč osudu', '30 zlatek'], 4) print(create_inventories()) # print(inventory_1.filled_size(), inventory_1.items) # print(inventory_2.filled_size(), inventory_2.items) # print(inventory_1) # print('přidávám louč') # inventory_1.items.append('louč') # print('přidávám louč hackem') # inventory_1._items.append('louč') # # print(inventory_1) # # inventory_1.items = [] # # print(inventory_1) # # print('louč' in inventory_1) # inventory_1.loot_inventory(inventory_2) # print(inventory_1) # print(inventory_2) # inventory_2.loot_inventory(inventory_1) # print(inventory_1) # print(inventory_2) item = 'můj velký item' print('item', item) for item in inventory_1: print(item) print('item', item) print(inventory_1.my_items) print(inventory_2.my_items) inventory_1.my_items.append('tvoje itemy') print(inventory_1.my_items) print(inventory_2.my_items) if __name__ == '__main__': main()

[ "racinmat@fel.cvut.cz" ]

racinmat@fel.cvut.cz

4803c21ff84494043745787f4b9e8fcf6ed4cefc

54ba419e5bad49858f6a861472c98ef307cf25d3

/pages/views.py

0e93366dc22b857ae6c8bc64f812d9eb06f630d5

[]

no_license

shuvo14051/real-estate51

84ccbd777e29598f50fd55efc2adc4ceebe51119

13987bcad3395cfe1a78decdda809ddf11a891da

refs/heads/master

2022-11-30T22:36:55.300239

2020-08-16T10:08:22

287,917,958

0

null

UTF-8

Python

false

807

py

from django.shortcuts import render from listings.choice import price_choices, bedroom_choices, state_choices from listings.models import Listing from realtors.models import Realtor def index(request): listings = Listing.objects.order_by('-list_date').filter(is_published = True)[:3] context = { 'listings':listings, 'state_choices':state_choices, 'bedroom_choices':bedroom_choices, 'price_choices':price_choices, } return render(request, 'pages/index.html', context) def about(request): realtors = Realtor.objects.order_by('-hire_date') mvp_realtors = Realtor.objects.all().filter(is_mvp = True) context = { 'realtors':realtors, 'mvp_realtors': mvp_realtors, } return render(request, 'pages/about.html', context)

[ "shuvo1137017@gmail.com" ]

shuvo1137017@gmail.com

e4436c2940f82a4b464c4040bf76269a52189500

286b6dc56323f982092ffafbfac8a32dbbaeb7ef

/training_assignments/Day_05/logging_1.py

ab38671c36e6f080f41b3a6e1bf5506b890b451a

[]

no_license

learndevops19/pythonTraining-CalsoftInc

ccee0d90aadc00bfdb17f9578620f6bf92f80a4c

c5f61516b835339b394876edd1c6f62e7cc6f0c3

refs/heads/master

2021-02-05T04:27:17.590913

2019-11-20T17:27:06

null

0

null

UTF-8

Python

false

502

py

import logging logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) def Add(a ,b): logger.info("in Add function") return a+b def Sub(a ,b): logger.info("in sub function") return a-b def Mul(a ,b): logger.info("in mul function") return a*b def Div(a ,b): logger.info("in divide function") try: c=a/b return c except ZeroDivisionError: logger.error("0 as a second argument") Add(1,2) Mul(1,2) Sub(1,2) Div(1,0)

[ "rajpratik71@gmail.com" ]

rajpratik71@gmail.com

393532f42e7a054d841d2b238db0d1525894c730

3a298c93b67386392d3dee243671f2c101decf01

/leetcode/patterns/08-tree-dfs/15_delete_nodes_and_return_forest.py

004f1730162a62940d860e9aa5c02e17c05792eb

[]

no_license

Zahidsqldba07/coding-problems-2

ffbc8408e4408fc846c828af2ec50a9d72e799bc

020bffbd14ca9993f1e678181ee7df761f1533de

refs/heads/master

2023-06-26T11:05:34.089697

2021-07-21T15:16:10

null

0

null

UTF-8

Python

false

722

py

class Solution: def delNodes(self, root, to_delete): self.nodes = [] self.toDelete = set(to_delete) self.delNodesRec(root) if not root.val in self.toDelete: self.nodes.append(root) return self.nodes def delNodesRec(self, node): if node is None: return None node.left = self.delNodesRec(node.left) node.right = self.delNodesRec(node.right) if node.val in self.toDelete: if node.left is not None: self.nodes.append(node.left) if node.right is not None: self.nodes.append(node.right) return None return node

[ "alvee.akand@outlook.com" ]

alvee.akand@outlook.com

ae60e70aebbd79c68c1790edc4625e528d4ed8a9

6e8b920ddc4ac45c80796e4db08c12ce65058429

/Python/Black-Hat-Python/chapter 2/tcpsclient-gui.py

8c6526db1341042d08f8e14f1ae20088ae7a15df

[]

no_license

arpbadger/Library

d4a892c77917b593a457ebda5ca40dacf1ec99ce

a078fe30f62160a82d798d86e1fa6224116da018

refs/heads/master

2020-06-07T20:45:36.143018

2019-07-23T00:46:44

193,090,914

0

null

2019-07-23T00:46:45

2019-06-21T12:03:02

C

UTF-8

Python

false

2,063

py

# tcpclient-badger-gui # developed by arpbadger with assistance from Justic Seitz, "Black Hat Python" # The GUI version of tcpclient-badger from Tkinter import * import socket target_host = "" target_port = 0 # Pring title page def title_sequence(): print (''' __ _ _ ___ _ /\ \ \___| |___ _____ _ __| | __ / __\ __ _ __| | __ _ ___ _ __ / \/ / _ \ __\ \ /\ / / _ \| '__| |/ / /__\/// _` |/ _` |/ _` |/ _ \ '__| / /\ / __/ |_ \ V V / (_) | | | < / \/ \ (_| | (_| | (_| | __/ | \_\ \/ \___|\__| \_/\_/ \___/|_| |_|\_\ \_____/\__,_|\__,_|\__, |\___|_| |___/ ''') return # get domain or targer IP and port from the user def add_target(): global target_host target_host = e.get() def add_port(): global target_port target_port = e1.get() target_port = int(target_port) def get_target(): return target_host,target_port # Request http connection def connect(target_host,target_port): #edit target_host variable. I.E cut of www ftarget_host = target_host[2:] #create a socket object client = socket.socket(socket.AF_INET, socket.SOCK_STREAM) #connect the client client.connect((target_host,target_port)) #send some data client.send("GET / HTTP/1.1\r\nHost: "+ftarget_host+"\r\n\r\n") #receive some data response = client.recv(4096) print(response) # Main sequence def main(): title_sequence() get_target() connect(target_host,target_port) # Create GUI Interface root = Tk() root.title('TCPClient Badger') # Create target entry feild e = Entry(root) e.pack() e.focus_set() # Create 'add target' button b = Button(root,text='Add target',command = add_target) b.pack() # Create port entry feild e1 = Entry(root) e1.pack() e1.focus_set() # Create 'add port' button c = Button(root,text='Add Port', command = add_port) c.pack() d = Button(root,text='Run Badger', command = main) d.pack(side='bottom') # run gui interface root.mainloop()

[ "arpbadger@protonmail.com" ]

arpbadger@protonmail.com

c546a6a6e6f1bac8f1c5d07cc5d4459195450daa

85c4417294b234ba3e3ef652d1cd5724706d77e1

/main.py

1b28738b21267e9c7370c316182d6fb723630add

[]

no_license

iamabdil/workout-tracker

e9df8e0df4d7f9bdf3442f1056f8dcdb19d78b2d

e552de4246c14c3df9377015b6f4deea91d63bd2

refs/heads/master

2023-04-25T22:37:07.870057

2021-05-21T19:10:47

369,631,270

0

null

UTF-8

Python

false

1,761

py

import requests from datetime import datetime import os GENDER = "Male" WEIGHT_KG = 81 HEIGHT_CM = 179 AGE = 22 # APP_ID = "63c48190" APP_ID = os.environ['APP_ID'] # API_KEY = "36924c0dc3e1dea5ddc559a75ad334e0" API_KEY = os.environ['API_KEY'] USERNAME = "" USERNAME = os.environ['USERNAME'] PROJECT_NAME = "Workout Tracking" SHEET_NAME = "" exercise_endpoint = "https://trackapi.nutritionix.com/v2/natural/exercise" sheety_endpoint = "https://api.sheety.co/dca6ac72c87dc84251d90fc67ef39e87/workoutTracking/workouts" exercise_text = input("Tell me which exercise you did!") headers = { "x-app-id": APP_ID, "x-app-key": API_KEY, } params = { "query": exercise_text, "gender": GENDER, "weight_kg": WEIGHT_KG, "height_cm": HEIGHT_CM, "age": AGE, } response = requests.post(exercise_endpoint, json=params, headers=headers) response.raise_for_status() result = response.json() today_date = datetime.now().strftime("%d/%m/%Y") now_time = datetime.now().strftime("%X") for exercise in result["exercises"]: sheet_inputs = { "workout": { "date": today_date, "time": now_time, "exercise": exercise["name"].title(), "duration": exercise["duration_min"], "calories": exercise["nf_calories"], } } sheety_response = requests.post(sheety_endpoint, json=sheet_inputs) # Basic Authentication sheety_response = requests.post( sheety_endpoint, json=sheet_inputs, auth=( USERNAME, "abc123" ) ) # Bearer Token Authentication bearer_headers = { "Authorization": "Bearer bnVsbDpudWxa" } sheety_response = requests.post( sheety_endpoint, json=sheet_inputs, headers=bearer_headers, ) print(sheety_response.text)

[ "51669829+iamabdil@users.noreply.github.com" ]

51669829+iamabdil@users.noreply.github.com

c47940f8d078b632487c905152a5da7ba9ea90a7

98731548daa91f8f7c10e0bd41e6f5dc59f8cdf7

/zArchive/datastore-2014/intro_datastore.py

f576a6cec34cc6df1de48cf18b0411a18a3e1c77

[ "MIT" ]

permissive

topquark28/CSSI-2016

3ae52686abfc208684cdfb9843e4e8bf51f6e493

42b82462fc58fd3f454e2529e860d5edc0548e7f

refs/heads/master

2020-12-25T10:59:12.837422

2016-07-20T05:58:47

63,488,363

0

null

UTF-8

Python

false

203

py

from google.appengine.ext import ndb class Student(ndb.Model): name = ndb.StringProperty(required=True) university = ndb.StringProperty(required=True) birthday = ndb.DateProperty(required=False)

[ "reimerc@gmail.com" ]

reimerc@gmail.com

ce175b4964ee84d489102bcbf273165ae4966f89

1023fbd328d001782fdc42a9f2b81d2ac715704a

/01-Neural_Networks_and_Deep_Learning/week4/py-project2/dnn_app_utils_v2.py

057ed658f1d64bf98464b00feb95597d3cc2b5ae

[]

no_license

Qu-rixin/deeplearning.ai-notes

a7868ce6b4fc87f266a41bccf3887fa95705bc67

fb217a0fd4be79846be1e069c9baea2221689fa5

refs/heads/master

2020-09-02T14:56:16.851256

2019-11-03T12:01:02

209,943,381

0

null

UTF-8

Python

false

17,199

py

import numpy as np import matplotlib.pyplot as plt import h5py def sigmoid(Z): """ Implements the sigmoid activation in numpy Arguments: Z -- numpy array of any shape Returns: A -- output of sigmoid(z), same shape as Z cache -- returns Z as well, useful during backpropagation """ A = 1/(1+np.exp(-Z)) cache = Z return A, cache def relu(Z): """ Implement the RELU function. Arguments: Z -- Output of the linear layer, of any shape Returns: A -- Post-activation parameter, of the same shape as Z cache -- a python dictionary containing "A" ; stored for computing the backward pass efficiently """ A = np.maximum(0,Z) assert(A.shape == Z.shape) cache = Z return A, cache def relu_backward(dA, cache): """ Implement the backward propagation for a single RELU unit. Arguments: dA -- post-activation gradient, of any shape cache -- 'Z' where we store for computing backward propagation efficiently Returns: dZ -- Gradient of the cost with respect to Z """ Z = cache dZ = np.array(dA, copy=True) # just converting dz to a correct object. # When z <= 0, you should set dz to 0 as well. dZ[Z <= 0] = 0 assert (dZ.shape == Z.shape) return dZ def sigmoid_backward(dA, cache): """ Implement the backward propagation for a single SIGMOID unit. Arguments: dA -- post-activation gradient, of any shape cache -- 'Z' where we store for computing backward propagation efficiently Returns: dZ -- Gradient of the cost with respect to Z """ Z = cache s = 1/(1+np.exp(-Z)) dZ = dA * s * (1-s) assert (dZ.shape == Z.shape) return dZ def load_data(): train_dataset = h5py.File('datasets/train_catvnoncat.h5', "r") train_set_x_orig = np.array(train_dataset["train_set_x"][:]) # your train set features train_set_y_orig = np.array(train_dataset["train_set_y"][:]) # your train set labels test_dataset = h5py.File('datasets/test_catvnoncat.h5', "r") test_set_x_orig = np.array(test_dataset["test_set_x"][:]) # your test set features test_set_y_orig = np.array(test_dataset["test_set_y"][:]) # your test set labels classes = np.array(test_dataset["list_classes"][:]) # the list of classes train_set_y_orig = train_set_y_orig.reshape((1, train_set_y_orig.shape[0])) test_set_y_orig = test_set_y_orig.reshape((1, test_set_y_orig.shape[0])) return train_set_x_orig, train_set_y_orig, test_set_x_orig, test_set_y_orig, classes def initialize_parameters(n_x, n_h, n_y): """ Argument: n_x -- size of the input layer n_h -- size of the hidden layer n_y -- size of the output layer Returns: parameters -- python dictionary containing your parameters: W1 -- weight matrix of shape (n_h, n_x) b1 -- bias vector of shape (n_h, 1) W2 -- weight matrix of shape (n_y, n_h) b2 -- bias vector of shape (n_y, 1) """ np.random.seed(1) W1 = np.random.randn(n_h, n_x)*0.01 b1 = np.zeros((n_h, 1)) W2 = np.random.randn(n_y, n_h)*0.01 b2 = np.zeros((n_y, 1)) assert(W1.shape == (n_h, n_x)) assert(b1.shape == (n_h, 1)) assert(W2.shape == (n_y, n_h)) assert(b2.shape == (n_y, 1)) parameters = {"W1": W1, "b1": b1, "W2": W2, "b2": b2} return parameters def initialize_parameters_deep(layer_dims): """ Arguments: layer_dims -- python array (list) containing the dimensions of each layer in our network Returns: parameters -- python dictionary containing your parameters "W1", "b1", ..., "WL", "bL": Wl -- weight matrix of shape (layer_dims[l], layer_dims[l-1]) bl -- bias vector of shape (layer_dims[l], 1) """ np.random.seed(1) parameters = {} L = len(layer_dims) # number of layers in the network for l in range(1, L): parameters['W' + str(l)] = np.random.randn(layer_dims[l], layer_dims[l-1]) / np.sqrt(layer_dims[l-1]) #*0.01 parameters['b' + str(l)] = np.zeros((layer_dims[l], 1)) assert(parameters['W' + str(l)].shape == (layer_dims[l], layer_dims[l-1])) assert(parameters['b' + str(l)].shape == (layer_dims[l], 1)) return parameters def linear_forward(A, W, b): """ Implement the linear part of a layer's forward propagation. Arguments: A -- activations from previous layer (or input data): (size of previous layer, number of examples) W -- weights matrix: numpy array of shape (size of current layer, size of previous layer) b -- bias vector, numpy array of shape (size of the current layer, 1) Returns: Z -- the input of the activation function, also called pre-activation parameter cache -- a python dictionary containing "A", "W" and "b" ; stored for computing the backward pass efficiently """ Z = W.dot(A) + b assert(Z.shape == (W.shape[0], A.shape[1])) cache = (A, W, b) return Z, cache def linear_activation_forward(A_prev, W, b, activation): """ Implement the forward propagation for the LINEAR->ACTIVATION layer Arguments: A_prev -- activations from previous layer (or input data): (size of previous layer, number of examples) W -- weights matrix: numpy array of shape (size of current layer, size of previous layer) b -- bias vector, numpy array of shape (size of the current layer, 1) activation -- the activation to be used in this layer, stored as a text string: "sigmoid" or "relu" Returns: A -- the output of the activation function, also called the post-activation value cache -- a python dictionary containing "linear_cache" and "activation_cache"; stored for computing the backward pass efficiently """ if activation == "sigmoid": # Inputs: "A_prev, W, b". Outputs: "A, activation_cache". Z, linear_cache = linear_forward(A_prev, W, b) A, activation_cache = sigmoid(Z) elif activation == "relu": # Inputs: "A_prev, W, b". Outputs: "A, activation_cache". Z, linear_cache = linear_forward(A_prev, W, b) A, activation_cache = relu(Z) assert (A.shape == (W.shape[0], A_prev.shape[1])) cache = (linear_cache, activation_cache) return A, cache def L_model_forward(X, parameters): """ Implement forward propagation for the [LINEAR->RELU]*(L-1)->LINEAR->SIGMOID computation Arguments: X -- data, numpy array of shape (input size, number of examples) parameters -- output of initialize_parameters_deep() Returns: AL -- last post-activation value caches -- list of caches containing: every cache of linear_relu_forward() (there are L-1 of them, indexed from 0 to L-2) the cache of linear_sigmoid_forward() (there is one, indexed L-1) """ caches = [] A = X L = len(parameters) // 2 # number of layers in the neural network # Implement [LINEAR -> RELU]*(L-1). Add "cache" to the "caches" list. for l in range(1, L): A_prev = A A, cache = linear_activation_forward(A_prev, parameters['W' + str(l)], parameters['b' + str(l)], activation = "relu") caches.append(cache) # Implement LINEAR -> SIGMOID. Add "cache" to the "caches" list. AL, cache = linear_activation_forward(A, parameters['W' + str(L)], parameters['b' + str(L)], activation = "sigmoid") caches.append(cache) assert(AL.shape == (1,X.shape[1])) return AL, caches def compute_cost(AL, Y): """ Implement the cost function defined by equation (7). Arguments: AL -- probability vector corresponding to your label predictions, shape (1, number of examples) Y -- true "label" vector (for example: containing 0 if non-cat, 1 if cat), shape (1, number of examples) Returns: cost -- cross-entropy cost """ m = Y.shape[1] # Compute loss from aL and y. cost = (1./m) * (-np.dot(Y,np.log(AL).T) - np.dot(1-Y, np.log(1-AL).T)) cost = np.squeeze(cost) # To make sure your cost's shape is what we expect (e.g. this turns [[17]] into 17). assert(cost.shape == ()) return cost def linear_backward(dZ, cache): """ Implement the linear portion of backward propagation for a single layer (layer l) Arguments: dZ -- Gradient of the cost with respect to the linear output (of current layer l) cache -- tuple of values (A_prev, W, b) coming from the forward propagation in the current layer Returns: dA_prev -- Gradient of the cost with respect to the activation (of the previous layer l-1), same shape as A_prev dW -- Gradient of the cost with respect to W (current layer l), same shape as W db -- Gradient of the cost with respect to b (current layer l), same shape as b """ A_prev, W, b = cache m = A_prev.shape[1] dW = 1./m * np.dot(dZ,A_prev.T) db = 1./m * np.sum(dZ, axis = 1, keepdims = True) dA_prev = np.dot(W.T,dZ) assert (dA_prev.shape == A_prev.shape) assert (dW.shape == W.shape) assert (db.shape == b.shape) return dA_prev, dW, db def linear_activation_backward(dA, cache, activation): """ Implement the backward propagation for the LINEAR->ACTIVATION layer. Arguments: dA -- post-activation gradient for current layer l cache -- tuple of values (linear_cache, activation_cache) we store for computing backward propagation efficiently activation -- the activation to be used in this layer, stored as a text string: "sigmoid" or "relu" Returns: dA_prev -- Gradient of the cost with respect to the activation (of the previous layer l-1), same shape as A_prev dW -- Gradient of the cost with respect to W (current layer l), same shape as W db -- Gradient of the cost with respect to b (current layer l), same shape as b """ linear_cache, activation_cache = cache if activation == "relu": dZ = relu_backward(dA, activation_cache) dA_prev, dW, db = linear_backward(dZ, linear_cache) elif activation == "sigmoid": dZ = sigmoid_backward(dA, activation_cache) dA_prev, dW, db = linear_backward(dZ, linear_cache) return dA_prev, dW, db def L_model_backward(AL, Y, caches): """ Implement the backward propagation for the [LINEAR->RELU] * (L-1) -> LINEAR -> SIGMOID group Arguments: AL -- probability vector, output of the forward propagation (L_model_forward()) Y -- true "label" vector (containing 0 if non-cat, 1 if cat) caches -- list of caches containing: every cache of linear_activation_forward() with "relu" (there are (L-1) or them, indexes from 0 to L-2) the cache of linear_activation_forward() with "sigmoid" (there is one, index L-1) Returns: grads -- A dictionary with the gradients grads["dA" + str(l)] = ... grads["dW" + str(l)] = ... grads["db" + str(l)] = ... """ grads = {} L = len(caches) # the number of layers m = AL.shape[1] Y = Y.reshape(AL.shape) # after this line, Y is the same shape as AL # Initializing the backpropagation dAL = - (np.divide(Y, AL) - np.divide(1 - Y, 1 - AL)) # Lth layer (SIGMOID -> LINEAR) gradients. Inputs: "AL, Y, caches". Outputs: "grads["dAL"], grads["dWL"], grads["dbL"] current_cache = caches[L-1] grads["dA" + str(L)], grads["dW" + str(L)], grads["db" + str(L)] = linear_activation_backward(dAL, current_cache, activation = "sigmoid") for l in reversed(range(L-1)): # lth layer: (RELU -> LINEAR) gradients. current_cache = caches[l] dA_prev_temp, dW_temp, db_temp = linear_activation_backward(grads["dA" + str(l + 2)], current_cache, activation = "relu") grads["dA" + str(l + 1)] = dA_prev_temp grads["dW" + str(l + 1)] = dW_temp grads["db" + str(l + 1)] = db_temp return grads def update_parameters(parameters, grads, learning_rate): """ Update parameters using gradient descent Arguments: parameters -- python dictionary containing your parameters grads -- python dictionary containing your gradients, output of L_model_backward Returns: parameters -- python dictionary containing your updated parameters parameters["W" + str(l)] = ... parameters["b" + str(l)] = ... """ L = len(parameters) // 2 # number of layers in the neural network # Update rule for each parameter. Use a for loop. for l in range(L): parameters["W" + str(l+1)] = parameters["W" + str(l+1)] - learning_rate * grads["dW" + str(l+1)] parameters["b" + str(l+1)] = parameters["b" + str(l+1)] - learning_rate * grads["db" + str(l+1)] return parameters def predict(X, y, parameters): """ This function is used to predict the results of a L-layer neural network. Arguments: X -- data set of examples you would like to label parameters -- parameters of the trained model Returns: p -- predictions for the given dataset X """ m = X.shape[1] n = len(parameters) // 2 # number of layers in the neural network p = np.zeros((1,m)) # Forward propagation probas, caches = L_model_forward(X, parameters) # convert probas to 0/1 predictions for i in range(0, probas.shape[1]): if probas[0,i] > 0.5: p[0,i] = 1 else: p[0,i] = 0 #print results #print ("predictions: " + str(p)) #print ("true labels: " + str(y)) print("Accuracy: " + str(np.sum((p == y)/m))) return p def print_mislabeled_images(classes, X, y, p): """ Plots images where predictions and truth were different. X -- dataset y -- true labels p -- predictions """ a = p + y mislabeled_indices = np.asarray(np.where(a == 1)) plt.rcParams['figure.figsize'] = (40.0, 40.0) # set default size of plots num_images = len(mislabeled_indices[0]) for i in range(num_images): index = mislabeled_indices[1][i] plt.subplot(2, num_images, i + 1) plt.imshow(X[:,index].reshape(64,64,3), interpolation='nearest') plt.axis('off') plt.title("Prediction: " + classes[int(p[0,index])].decode("utf-8") + " \n Class: " + classes[y[0,index]].decode("utf-8")) def L_layer_model(X, Y, layers_dims, learning_rate = 0.0075, num_iterations = 3000, print_cost=False):#lr was 0.009 """ Implements a L-layer neural network: [LINEAR->RELU]*(L-1)->LINEAR->SIGMOID. Arguments: X -- data, numpy array of shape (number of examples, num_px * num_px * 3) Y -- true "label" vector (containing 0 if cat, 1 if non-cat), of shape (1, number of examples) layers_dims -- list containing the input size and each layer size, of length (number of layers + 1). learning_rate -- learning rate of the gradient descent update rule num_iterations -- number of iterations of the optimization loop print_cost -- if True, it prints the cost every 100 steps Returns: parameters -- parameters learnt by the model. They can then be used to predict. """ np.random.seed(1) costs = [] # keep track of cost # Parameters initialization. parameters = initialize_parameters_deep(layers_dims) # Loop (gradient descent) for i in range(0, num_iterations): # Forward propagation: [LINEAR -> RELU]*(L-1) -> LINEAR -> SIGMOID. AL, caches = L_model_forward(X, parameters) # Compute cost. cost = compute_cost(AL, Y) # Backward propagation. grads = L_model_backward(AL, Y, caches) # Update parameters. parameters = update_parameters(parameters, grads, learning_rate=learning_rate) # Print the cost every 100 training example if print_cost and i % 100 == 0: print ("Cost after iteration %i: %f" %(i, cost)) if print_cost and i % 100 == 0: costs.append(cost) # plot the cost plt.plot(np.squeeze(costs)) plt.ylabel('cost') plt.xlabel('iterations (per tens)') plt.title("Learning rate =" + str(learning_rate)) plt.show() return parameters

[ "noreply@github.com" ]

Qu-rixin.noreply@github.com

1641dbf439c23db22eef588cd46047788da9152a

6968d37d97727685af9e413d34fd8cd9004c836e

/blog/migrations/0002_auto_20200630_2248.py

74544862a11349c0d0a8d5191e6e5a1e8eef507e

[]

no_license

eunjungleo/0715lecnote

6ef8c7992c6c82fd49a2f8059c1a78f7e9ade3e9

a6b93279c1ad806e1a9297cc3be325b8a237bc3e

refs/heads/master

2022-11-17T12:55:08.289124

2020-07-15T11:26:35

279,613,525

0

null

UTF-8

Python

false

731

py

# Generated by Django 3.0.7 on 2020-06-30 13:48 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('blog', '0001_initial'), ] operations = [ migrations.AlterField( model_name='comment', name='post', field=models.ForeignKey(default='', on_delete=django.db.models.deletion.CASCADE, related_name='post_id', to='blog.Post'), ), migrations.AlterField( model_name='post', name='comment', field=models.ForeignKey(default='', on_delete=django.db.models.deletion.DO_NOTHING, related_name='comment_id', to='blog.Comment'), ), ]

[ "asaprocky123@likelion.org" ]

asaprocky123@likelion.org

d000a16a23df4f4f7a6039f2585d22f6f582f620

d829c090d178a1bca976a4299014c46e0fbac24b

/push/push.py

10c6881e00019cf8d126cece53945f586d4bbf33

[ "MIT" ]

permissive

quannv108/redis_fifo_clients

9bdab30daad86caff8b5b37f8e77d8282f7bb175

880c2ea1c7e49f39dc74e16d3b2dd96e9ff1c9e4

refs/heads/master

2022-02-24T04:16:01.095022

2019-10-04T07:17:14

212,522,124

2

0

null

UTF-8

Python

false

411

py

import redis import os import time from datetime import datetime if __name__ == '__main__': print('push starting...') redis_conn = redis.Redis(host=os.getenv('HOST'), port=6379, db=0) count = 0 while True: time.sleep(3) now = datetime.now() print('will push value {}'.format(now)) redis_conn.lpush('abc', now.strftime('%Y-%m-%d %H:%M:%S.%f')) count += 1

[ "quannv@d-soft.com.vn" ]

quannv@d-soft.com.vn

fc347e03429f8460b8f3300c15f04c370a519892

c61a28aba19f7cdf9a5127e8a782bf115c265e70

/env/bin/pygmentize

71647a426bbc992d8f9a844ab9330a2cd73d7788

[]

no_license

sharmilaviji/RecruitPRO-NEW

fa72c8fc00f469a41798b1047c11dcc470fbc495

dcfaedebe56b45acd6ddcab7e24c939b853a2c8c

refs/heads/master

2021-05-26T12:14:12.611154

2020-04-27T04:40:50

254,125,640

1

0

null

UTF-8

Python

false

242

#!/home/sharmila/frappe-bench/env/bin/python3 # -*- coding: utf-8 -*- import re import sys from pygments.cmdline import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0]) sys.exit(main())

[ "sharmiviji1997@gmail.com" ]

sharmiviji1997@gmail.com

23c3506556a0d679d371d7221560b44fc26c5655

6514c3c286e8637e9d73fe140df61e260394e655

/vault/forms.py

84d2c5d438d66e6290da87d0f7aff7f2afef02c7

[]

no_license

Duncan-Stout/your_vault

3b8ceb785388c6c5f7b783d072dc137907b5ee85

4cf079dbef98a04d28498c7ec4fa7556e561f638

refs/heads/main

2023-02-12T05:50:43.776694

2020-11-28T09:39:11

312,155,154

0

null

UTF-8

Python

false

131

py

from django import forms class UploadfileForm(forms.Form): title = forms.CharField(max_length=50) file = forms.FileField()

[ "destout1983@yahoo.com" ]

destout1983@yahoo.com

7a8e55bc4d5539029e8c24e20c1d25272b887f74

62f271853955906d3c2898f357c65945a0b38998

/py_dj_blog/wsgi.py

6d936bdf523dcd65ba59226562454833795d077a

[]

no_license

shootie007/py_dj_blog

46bd9cc65cf98a4e9065223c9132ee9930a95245

9e018201e8550dd92bd1c0d275f46c4498de55a0

refs/heads/master

2022-12-04T11:10:57.086828

2020-08-28T07:50:07

285,501,370

0

null

UTF-8

Python

false

397

py

""" WSGI config for py_dj_blog project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'py_dj_blog.settings') application = get_wsgi_application()

[ "shoot@Shootie-MacBook.local" ]

shoot@Shootie-MacBook.local

2dbb562e94ee2bfe30d7a41946ff1b5bca578a55

11fc58b24edc43f00cba7bf029fe498b7beb493d

/lab project/mysite/mysite/urls.py

12dfe9c0586bc409f5b73c24bf7f18b563bd452b

[]

no_license

AndrewZhou924/Bootstrap_Django_website

ab460a2f45b75d0bf3cce9167def5571cf872d87

7f565ef56a5859092535b953f90f3a4b6169233b

refs/heads/master

2022-12-04T18:14:31.799855

2019-07-01T07:12:24

193,053,240

0

null

2022-11-22T03:15:07

2019-06-21T07:35:19

JavaScript

UTF-8

Python

false

1,029

py

"""mysite URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.0/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.conf.urls import url from django.conf.urls import include from django.contrib import admin from login import views from login import views urlpatterns = [ url(r'^admin/', admin.site.urls), url(r'^index/', views.index), url(r'^login/', views.login), url(r'^register/', views.register), url(r'^logout/', views.logout), url(r'^captcha', include('captcha.urls')) ]

[ "andrewzhou924@gmail.com" ]

andrewzhou924@gmail.com

a545ac2c798829459b6312574645abf1a5576465

94d065f032359c0c7f18f5c8cba933dde14d3f95

/train.py

1616e35044629e87e7b0b512a1a8a8bf23415f2f

[]

no_license

smartprobe/HGNN

d57350e19274a9364ec50093af1d1c2e402f2153

6c68c42fff55057ec5e14185e51b7449293a4583

refs/heads/main

2023-01-25T05:21:46.183436

2020-12-10T12:15:05

320,261,591

3

2

null

UTF-8

Python

false

22,421

py

from torchtools import * from data import MiniImagenetLoader,TieredImagenetLoader from model import EmbeddingImagenet, Unet,Unet2 import shutil import os import random import time class ModelTrainer(object): def __init__(self, enc_module, unet_module, data_loader): # set encoder and unet self.enc_module = enc_module.to(tt.arg.device) self.unet_module = unet_module.to(tt.arg.device) if tt.arg.num_gpus > 1: print('Construct multi-gpu model ...') self.enc_module = nn.DataParallel(self.enc_module, device_ids=[2, 3], dim=0) self.unet_module = nn.DataParallel(self.unet_module, device_ids=[2, 3], dim=0) print('done!\n') # get data loader self.data_loader = data_loader # set module parameters self.module_params = list(self.enc_module.parameters()) + list(self.unet_module.parameters()) # set optimizer self.optimizer = optim.Adam(params=self.module_params, lr=tt.arg.lr, weight_decay=tt.arg.weight_decay) # set loss self.node_loss = nn.NLLLoss() self.global_step = 0 self.val_acc = 0 self.test_acc = 0 def train(self): val_acc = self.val_acc # set edge mask (to distinguish support and query edges) num_supports = tt.arg.num_ways * tt.arg.num_shots num_queries = tt.arg.num_queries num_samples = num_supports + num_queries time_start=time.time() # for each iteration for iter in range(self.global_step + 1, tt.arg.train_iteration + 1): # init grad self.optimizer.zero_grad() # set current step self.global_step = iter # load task data list [support_data, support_label, query_data, query_label] = self.data_loader['train'].get_task_batch(num_tasks=tt.arg.meta_batch_size, num_ways=tt.arg.num_ways, num_shots=tt.arg.num_shots, num_queries=int(tt.arg.num_queries /tt.arg.num_ways), seed=iter + tt.arg.seed) # set as single data full_data = torch.cat([support_data, query_data], 1) full_label = torch.cat([support_label, query_label], 1) full_edge = self.label2edge(full_label) # set init edge init_edge = full_edge.clone() # batch_size x 2 x num_samples x num_samples init_edge[:, num_supports:, :] = 0.5 init_edge[:, :, num_supports:] = 0.5 for i in range(num_queries): init_edge[:, num_supports + i, num_supports + i] = 1.0 # set as train mode self.enc_module.train() self.unet_module.train() # (1) encode data full_data = [self.enc_module(data.squeeze(1)) for data in full_data.chunk(full_data.size(1), dim=1)] full_data = torch.stack(full_data, dim=1) # batch_size x num_samples x featdim one_hot_label = self.one_hot_encode(tt.arg.num_ways, support_label.long()) query_padding = (1 / tt.arg.num_ways) * torch.ones([full_data.shape[0]] + [num_queries] + [tt.arg.num_ways], device=one_hot_label.device) one_hot_label = torch.cat([one_hot_label, query_padding], dim=1) full_data = torch.cat([full_data, one_hot_label], dim=-1) if tt.arg.transductive == True: # transduction full_node_out = self.unet_module(init_edge, full_data) else: # non-transduction support_data = full_data[:, :num_supports] # batch_size x num_support x featdim query_data = full_data[:, num_supports:] # batch_size x num_query x featdim support_data_tiled = support_data.unsqueeze(1).repeat(1, num_queries, 1, 1) # batch_size x num_queries x num_support x featdim support_data_tiled = support_data_tiled.view(tt.arg.meta_batch_size * num_queries, num_supports, -1) # (batch_size x num_queries) x num_support x featdim query_data_reshaped = query_data.contiguous().view(tt.arg.meta_batch_size * num_queries, -1).unsqueeze( 1) # (batch_size x num_queries) x 1 x featdim input_node_feat = torch.cat([support_data_tiled, query_data_reshaped], 1) # (batch_size x num_queries) x (num_support + 1) x featdim input_edge_feat = 0.5 * torch.ones(tt.arg.meta_batch_size, num_supports + 1, num_supports + 1).to( tt.arg.device) # batch_size x (num_support + 1) x (num_support + 1) input_edge_feat[:, :num_supports, :num_supports] = init_edge[:, :num_supports, :num_supports] # batch_size x (num_support + 1) x (num_support + 1) input_edge_feat = input_edge_feat.repeat(num_queries, 1, 1) # (batch_size x num_queries) x (num_support + 1) x (num_support + 1) # 2. unet node_out = self.unet_module(input_edge_feat, input_node_feat) # (batch_size x num_queries) x (num_support + 1) x num_classes node_out = node_out.view(tt.arg.meta_batch_size, num_queries, num_supports + 1, tt.arg.num_ways) # batch_size x num_queries x (num_support + 1) x num_classes full_node_out = torch.zeros(tt.arg.meta_batch_size, num_samples, tt.arg.num_ways).to(tt.arg.device) full_node_out[:, :num_supports, :] = node_out[:, :, :num_supports, :].mean(1) full_node_out[:, num_supports:, :] = node_out[:, :, num_supports:, :].squeeze(2) # 3. compute loss query_node_out = full_node_out[:,num_supports:] node_pred = torch.argmax(query_node_out, dim=-1) node_accr = torch.sum(torch.eq(node_pred, full_label[:, num_supports:].long())).float() \ / node_pred.size(0) / num_queries node_loss = [self.node_loss(data.squeeze(1), label.squeeze(1).long()) for (data, label) in zip(query_node_out.chunk(query_node_out.size(1), dim=1), full_label[:, num_supports:].chunk(full_label[:, num_supports:].size(1), dim=1))] node_loss = torch.stack(node_loss, dim=0) node_loss = torch.mean(node_loss) node_loss.backward() self.optimizer.step() # adjust learning rate self.adjust_learning_rate(optimizers=[self.optimizer], lr=tt.arg.lr, iter=self.global_step) # logging tt.log_scalar('train/loss', node_loss, self.global_step) tt.log_scalar('train/node_accr', node_accr, self.global_step) tt.log_scalar('train/time', time.time()-time_start, self.global_step) # evaluation if self.global_step % tt.arg.test_interval == 0: val_acc = self.eval(partition='val') is_best = 0 if val_acc >= self.val_acc: self.val_acc = val_acc is_best = 1 tt.log_scalar('val/best_accr', self.val_acc, self.global_step) self.save_checkpoint({ 'iteration': self.global_step, 'enc_module_state_dict': self.enc_module.state_dict(), 'unet_module_state_dict': self.unet_module.state_dict(), 'val_acc': val_acc, 'optimizer': self.optimizer.state_dict(), }, is_best) tt.log_step(global_step=self.global_step) def eval(self,partition='test', log_flag=True): best_acc = 0 # set edge mask (to distinguish support and query edges) num_supports = tt.arg.num_ways * tt.arg.num_shots num_queries = tt.arg.num_queries num_samples = num_supports + num_queries query_node_accrs = [] time_start_eval=time.time() # for each iteration for iter in range(tt.arg.test_iteration // tt.arg.test_batch_size): # load task data list [support_data, support_label, query_data, query_label] = self.data_loader[partition].get_task_batch(num_tasks=tt.arg.test_batch_size, num_ways=tt.arg.num_ways, num_shots=tt.arg.num_shots, num_queries=int(tt.arg.num_queries /tt.arg.num_ways), seed=iter) ''' q0 = query_data[:,0,:].clone() q1 = query_data[:,1,:].clone() query_data[:, 1, :] = q0 query_data[:, 0, :] = q1 ql0 = query_label[:,0].clone() ql1 = query_label[:,1].clone() query_label[:, 1] = ql0 query_label[:, 0] = ql1 ''' # set as single data full_data = torch.cat([support_data, query_data], 1) full_label = torch.cat([support_label, query_label], 1) full_edge = self.label2edge(full_label) # set init edge init_edge = full_edge.clone() init_edge[:, num_supports:, :] = 0.5 init_edge[:, :, num_supports:] = 0.5 for i in range(num_queries): init_edge[:, num_supports + i, num_supports + i] = 1.0 # set as eval mode self.enc_module.eval() self.unet_module.eval() # (1) encode data full_data = [self.enc_module(data.squeeze(1)) for data in full_data.chunk(full_data.size(1), dim=1)] full_data = torch.stack(full_data, dim=1) # batch_size x num_samples x featdim one_hot_label = self.one_hot_encode(tt.arg.num_ways, support_label.long()) query_padding = (1 / tt.arg.num_ways) * torch.ones([full_data.shape[0]] + [num_queries] + [tt.arg.num_ways], device=one_hot_label.device) one_hot_label = torch.cat([one_hot_label, query_padding], dim=1) full_data = torch.cat([full_data, one_hot_label], dim=-1) if tt.arg.transductive == True: # transduction full_node_out = self.unet_module(init_edge, full_data) else: # non-transduction support_data = full_data[:, :num_supports] # batch_size x num_support x featdim query_data = full_data[:, num_supports:] # batch_size x num_query x featdim support_data_tiled = support_data.unsqueeze(1).repeat(1, num_queries, 1, 1) # batch_size x num_queries x num_support x featdim support_data_tiled = support_data_tiled.view(tt.arg.test_batch_size * num_queries, num_supports, -1) # (batch_size x num_queries) x num_support x featdim query_data_reshaped = query_data.contiguous().view(tt.arg.test_batch_size * num_queries, -1).unsqueeze( 1) # (batch_size x num_queries) x 1 x featdim input_node_feat = torch.cat([support_data_tiled, query_data_reshaped], 1) # (batch_size x num_queries) x (num_support + 1) x featdim input_edge_feat = 0.5 * torch.ones(tt.arg.test_batch_size, num_supports + 1, num_supports + 1).to( tt.arg.device) # batch_size x (num_support + 1) x (num_support + 1) input_edge_feat[:, :num_supports, :num_supports] = init_edge[:, :num_supports, :num_supports] # batch_size x (num_support + 1) x (num_support + 1) input_edge_feat = input_edge_feat.repeat(num_queries, 1, 1) # (batch_size x num_queries) x (num_support + 1) x (num_support + 1) # 2. unet node_out = self.unet_module(input_edge_feat, input_node_feat) # (batch_size x num_queries) x (num_support + 1) x num_classes node_out = node_out.view(tt.arg.test_batch_size, num_queries, num_supports + 1, tt.arg.num_ways) # batch_size x num_queries x (num_support + 1) x num_classes full_node_out = torch.zeros(tt.arg.test_batch_size, num_samples, tt.arg.num_ways).to(tt.arg.device) full_node_out[:, :num_supports, :] = node_out[:, :, :num_supports, :].mean(1) full_node_out[:, num_supports:, :] = node_out[:, :, num_supports:, :].squeeze(2) # 3. compute loss query_node_out = full_node_out[:, num_supports:] node_pred = torch.argmax(query_node_out, dim=-1) node_accr = torch.sum(torch.eq(node_pred, full_label[:, num_supports:].long())).float() \ / node_pred.size(0) / num_queries query_node_accrs += [node_accr.item()] print('time cost',time.time()-time_start_eval,'s') # logging if log_flag: tt.log('---------------------------') tt.log_scalar('{}/node_accr'.format(partition), np.array(query_node_accrs).mean(), self.global_step) tt.log('evaluation: total_count=%d, accuracy: mean=%.2f%%, std=%.2f%%, ci95=%.2f%%' % (iter, np.array(query_node_accrs).mean() * 100, np.array(query_node_accrs).std() * 100, 1.96 * np.array(query_node_accrs).std() / np.sqrt( float(len(np.array(query_node_accrs)))) * 100)) tt.log('---------------------------') return np.array(query_node_accrs).mean() def adjust_learning_rate(self, optimizers, lr, iter): new_lr = lr * (0.5 ** (int(iter / tt.arg.dec_lr))) for optimizer in optimizers: for param_group in optimizer.param_groups: param_group['lr'] = new_lr def label2edge(self, label): # get size num_samples = label.size(1) # reshape label_i = label.unsqueeze(-1).repeat(1, 1, num_samples) label_j = label_i.transpose(1, 2) # compute edge edge = torch.eq(label_i, label_j).float().to(tt.arg.device) return edge def one_hot_encode(self, num_classes, class_idx): return torch.eye(num_classes)[class_idx].to(tt.arg.device) def save_checkpoint(self, state, is_best): torch.save(state, 'asset/checkpoints/{}/'.format(tt.arg.experiment) + 'checkpoint.pth.tar') if is_best: shutil.copyfile('asset/checkpoints/{}/'.format(tt.arg.experiment) + 'checkpoint.pth.tar', 'asset/checkpoints/{}/'.format(tt.arg.experiment) + 'model_best.pth.tar') def set_exp_name(): exp_name = 'D-{}'.format(tt.arg.dataset) exp_name += '_N-{}_K-{}_Q-{}'.format(tt.arg.num_ways, tt.arg.num_shots,tt.arg.num_queries) exp_name += '_B-{}_T-{}'.format(tt.arg.meta_batch_size,tt.arg.transductive) exp_name += '_P-{}_Un-{}'.format(tt.arg.pool_mode,tt.arg.unet_mode) exp_name += '_SEED-{}_2'.format(tt.arg.seed) return exp_name if __name__ == '__main__': tt.arg.device = 'cuda:0' if tt.arg.device is None else tt.arg.device tt.arg.dataset_root = 'dataset' tt.arg.dataset = 'mini' if tt.arg.dataset is None else tt.arg.dataset tt.arg.num_ways = 5 if tt.arg.num_ways is None else tt.arg.num_ways tt.arg.num_shots = 5 if tt.arg.num_shots is None else tt.arg.num_shots tt.arg.num_queries = tt.arg.num_ways*1 tt.arg.num_supports = tt.arg.num_ways*tt.arg.num_shots tt.arg.transductive = True if tt.arg.transductive is None else tt.arg.transductive if tt.arg.transductive == False: tt.arg.meta_batch_size = 20 else: tt.arg.meta_batch_size = 40 tt.arg.seed = 222 if tt.arg.seed is None else tt.arg.seed tt.arg.num_gpus = 1 # model parameter related tt.arg.emb_size = 128 tt.arg.in_dim = tt.arg.emb_size + tt.arg.num_ways tt.arg.pool_mode = 'kn' if tt.arg.pool_mode is None else tt.arg.pool_mode # 'way'/'support'/'kn' tt.arg.unet_mode = 'addold' if tt.arg.unet_mode is None else tt.arg.unet_mode # 'addold'/'noold' unet2_flag = False # the label of using unet2 # confirm ks if tt.arg.num_shots == 1 and tt.arg.transductive == False: if tt.arg.pool_mode == 'support': # 'support': pooling on support tt.arg.ks = [0.6, 0.5] # 5->3->1 elif tt.arg.pool_mode == 'kn': # left close support node tt.arg.ks = [0.6, 0.5] # 5->3->1 else: print('wrong mode setting!!!') raise NameError('wrong mode setting!!!') elif tt.arg.num_shots == 5 and tt.arg.transductive == False: if tt.arg.pool_mode == 'way': # 'way' pooling on support by way tt.arg.ks_1 = [0.6, 0.5] # 5->3->1 mode_1 = 'way' tt.arg.ks_2 = [0.6, 0.5] # 5->3->1 # supplementary pooling for fair comparing mode_2 = 'support' unet2_flag = True elif tt.arg.pool_mode == 'kn': tt.arg.ks_1 = [0.6, 0.5] # 5->3->1 mode_1 = 'way&kn' tt.arg.ks_2 = [0.6, 0.5] # 5->3->1 # supplementary pooling for fair comparing mode_2 = 'kn' unet2_flag = True else: print('wrong mode setting!!!') raise NameError('wrong mode setting!!!') elif tt.arg.num_shots == 1 and tt.arg.transductive == True: if tt.arg.pool_mode == 'support': # 'support': pooling on support tt.arg.ks = [0.6, 0.5] # 5->3->1 elif tt.arg.pool_mode == 'kn': # left close support node tt.arg.ks = [0.6, 0.5] # 5->3->1 else: print('wrong mode setting!!!') raise NameError('wrong mode setting!!!') elif tt.arg.num_shots == 5 and tt.arg.transductive == True: if tt.arg.pool_mode == 'way': # 'way' pooling on support by way tt.arg.ks_1 = [0.6, 0.5] # 5->3->1 mode_1 = 'way' tt.arg.ks_2 = [0.6, 0.5] # 5->3->1 # supplementary pooling for fair comparing mode_2 = 'support' unet2_flag = True elif tt.arg.pool_mode == 'kn': tt.arg.ks_1 = [0.2] # 5->1 mode_1 = 'way&kn' tt.arg.ks_2 = [0.2] # 5->1 # supplementary pooling for fair comparing mode_2 = 'kn' unet2_flag = True else: print('wrong mode setting!!!') raise NameError('wrong mode setting!!!') else: print('wrong shot and T settings!!!') raise NameError('wrong shot and T settings!!!') # train, test parameters tt.arg.train_iteration = 100000 if tt.arg.dataset == 'mini' else 200000 tt.arg.test_iteration = 10000 tt.arg.test_interval = 20 # 5000 tt.arg.test_batch_size = 10 tt.arg.log_step = 10 tt.arg.lr = 1e-3 tt.arg.grad_clip = 5 tt.arg.weight_decay = 1e-6 tt.arg.dec_lr = 10000 if tt.arg.dataset == 'mini' else 20000 tt.arg.dropout = 0.1 if tt.arg.dataset == 'mini' else 0.0 tt.arg.experiment = set_exp_name() if tt.arg.experiment is None else tt.arg.experiment print(set_exp_name()) # set random seed np.random.seed(tt.arg.seed) torch.manual_seed(tt.arg.seed) torch.cuda.manual_seed_all(tt.arg.seed) random.seed(tt.arg.seed) torch.backends.cudnn.deterministic = True torch.backends.cudnn.benchmark = False tt.arg.log_dir_user = tt.arg.log_dir if tt.arg.log_dir_user is None else tt.arg.log_dir_user tt.arg.log_dir = tt.arg.log_dir_user if not os.path.exists('asset/checkpoints'): os.makedirs('asset/checkpoints') if not os.path.exists('asset/checkpoints/' + tt.arg.experiment): os.makedirs('asset/checkpoints/' + tt.arg.experiment) enc_module = EmbeddingImagenet(emb_size=tt.arg.emb_size) if tt.arg.transductive == False: if unet2_flag == False: unet_module = Unet(tt.arg.ks, tt.arg.in_dim, tt.arg.num_ways, 1) else: unet_module = Unet2(tt.arg.ks_1, tt.arg.ks_2, mode_1, mode_2, tt.arg.in_dim, tt.arg.num_ways, 1) else: if unet2_flag == False: unet_module = Unet(tt.arg.ks, tt.arg.in_dim, tt.arg.num_ways, tt.arg.num_queries) else: unet_module = Unet2(tt.arg.ks_1, tt.arg.ks_2, mode_1, mode_2, tt.arg.in_dim, tt.arg.num_ways, tt.arg.num_queries) if tt.arg.dataset == 'mini': train_loader = MiniImagenetLoader(root=tt.arg.dataset_root, partition='train') valid_loader = MiniImagenetLoader(root=tt.arg.dataset_root, partition='val') elif tt.arg.dataset == 'tiered': train_loader = TieredImagenetLoader(root=tt.arg.dataset_root, partition='train') valid_loader = TieredImagenetLoader(root=tt.arg.dataset_root, partition='val') else: print('Unknown dataset!') raise NameError('Unknown dataset!!!') data_loader = {'train': train_loader, 'val': valid_loader } # create trainer trainer = ModelTrainer(enc_module=enc_module, unet_module=unet_module, data_loader=data_loader) trainer.train()

[ "noreply@github.com" ]

smartprobe.noreply@github.com

fbec8e03c0fe27c466c4d49ca9f37570fa8f45b3

d28df0e0ec46aa47d75273e55dad5bba34162919

/InitUser/wsgi.py

8c8f8275895d5ab3237d295335142d525a115d9e

[]

no_license

sarudalf3/Django_register

0a85e7215f809a3d0bdc4392b3c576018b08c87f

f5d2c61e15949ce22337f992a8c17769991299c5

refs/heads/master

2023-07-17T13:44:30.502860

2021-09-02T00:52:28

402,244,068

0

null

UTF-8

Python

false

393

py

""" WSGI config for InitUser project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.2/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'InitUser.settings') application = get_wsgi_application()

[ "ruben.miranda.f@gmail.com" ]

ruben.miranda.f@gmail.com

059f8ab0f37b5e7f40886a1a96270d144121d038

f320256bf4cd65db7a8bc0cd6fe61131cd1903d7

/pondpi/ui/views/index.py

3ae374badc357aabeea3e6a4ad96712ca9a488a8

[ "MIT" ]

permissive

meinjens/pondpi

6bc1a9648a42bc25135b7a99058cdb6ddb0b5c46

f6830d0d834b685bff2729943188171096f31c93

refs/heads/main

2023-05-13T22:28:49.098092

2023-01-28T14:19:50

354,050,540

0

MIT

2023-05-01T22:44:37

2021-04-02T14:56:55

Jinja

UTF-8

Python

false

373

py

import flask from pondpi.ui import ui @ui.route('/', methods=["GET"]) def index(): return flask.render_template('start.html') @ui.route('/dashboard', methods=["GET"]) def dashboard(): return flask.render_template('dashboard.html') @ui.route('/control-station', methods=["GET"]) def control_station(): return flask.render_template('control-station.html')

[ "1739138+meinjens@users.noreply.github.com" ]

1739138+meinjens@users.noreply.github.com

c09fbb5af4bd07204b3f6165d002d80a474d3891

9fb8ba88d50ffba4e9ad4f3fb4cfd7c5d13f3591

/new/read_xml.py

93b34d9bb50bfb872bb4f5b66487d06f7f93449b

[]

no_license

joshsomma/python_webdata

b35e4903ca63b8f17493de32e8d24222107f6401

017673bd89ca2ec7af52a3dc214f06f1464d2831

refs/heads/master

2016-08-10T15:31:13.071254

2016-02-07T00:26:18

45,772,812

0

null

UTF-8

Python

false

420

py

# import libs import urllib import xml.etree.ElementTree as ET # prompt to enter data location address = raw_input('Enter location: ') print 'Retrieving', address # open and store data from location uh = urllib.urlopen(address) data = uh.read() # parse data in object tree = ET.fromstring(data) total = 0 for num in tree.iter('count'): #print num.text total += int(num.text) print "The total is: ", total

[ "jsomma@squiz.com" ]

jsomma@squiz.com

db876c2995e00f27fc4d14a58b98efde7091f4a1

3b5f7fe204a3f2f8d0534e7f02bc4aa517e12d70

/wargaming/games/wot/__init__.py

7a957b218e13abcfe313079ae9bc77ed6c89ccba

[ "MIT" ]

permissive

cstrutton/python-wargaming

1916d45cad1ca5a490342253a2f6f41427afeb50

8a446b5c34a55025dd961438d6b67a3a0a186791

refs/heads/master

2020-12-29T18:52:23.411208

2014-11-26T15:12:01

null

0

null

UTF-8

Python

false

1,308

py

# -*- coding: utf-8 -*- import six from wargaming import settings from wargaming.api import BaseAPI, MetaAPI from wargaming.games.wot.accounts import Accounts from wargaming.games.wot.auth import Auth from wargaming.games.wot.clans import Clans from wargaming.games.wot.globalwar import GlobalWar from wargaming.games.wot.encyclopedia import Encyclopedia from wargaming.games.wot.ratings import Ratings from wargaming.games.wot.clan_ratings import ClanRatings from wargaming.games.wot.tanks import Tanks __all__ = ('API', ) @six.add_metaclass(MetaAPI) class API(BaseAPI): """World of Tanks API client""" def __init__(self, application_id, language=settings.DEFAULT_LANGUAGE): """ :param application_id: Your application ID from the https://wargaming.net/developers/applications/ :type application_id: str :param language: Language for the requests (defaults to English) :type language: str """ super(API, self).__init__(application_id, language, base_url='https://api.worldoftanks.com/wot/') accounts = Accounts() auth = Auth() clans = Clans() globalwar = GlobalWar() encyclopedia = Encyclopedia() ratings = Ratings() clan_ratings = ClanRatings() tanks = Tanks()

[ "self@svartalf.info" ]

self@svartalf.info

4b4a3d00e0c59dfe5920fc6020a70ade72ea8065

0e26592078429d8b0b3da25e797128f72938b311

/数字信号处理实验/2.2.py

c0aa3bac0692a05600e274f97181bdfcc0d8f226

[]

no_license

wrh2048470785/2

e67c144243c9a64cc3dc5935e46ebd820ddfdc62

de15509e3d32bcbdd79a2d8a2a7c75eb3bf09240

refs/heads/main

2023-06-08T03:48:25.054502

2021-06-30T07:51:15

366,720,162

0

null

UTF-8

Python

false

1,667

py

from thinkdsp import Sinusoid from thinkdsp import normalize, unbias import numpy as np import matplotlib.pyplot as plt from thinkdsp import SquareSignal from thinkdsp import TriangleSignal class SawtoothSignal(Sinusoid): '''锯齿波的类''' def evaluate(self, ts): #cycle是自起始时间的周期数 cycles = self.freq * ts + self.offset / np.pi / 2 frac, _ = np.modf(cycles) #np.modf()能将一个数分为小数部分和整数部分 ys = normalize(unbias(frac), self.amp) #frac的序列介于0到1 #unbias将波形下移使其中心位于0 #normalize将波形归一化到给定的振幅（amp） return ys plt.rcParams['font.sans-serif']=['SimHei'] #加上这一句就能在图表中显示中文 plt.rcParams['axes.unicode_minus']=False #用来正常显示负号 #plt.subplot(511)#产生5行1列的第一个图 #plt.title(u"锯齿波的频谱") sawtooth = SawtoothSignal().make_wave(duration=0.5, framerate=40000) #制作波形长度为0.5s，每秒40000帧 #sawtooth.make_spectrum().plot() #plt.subplot(513) #plt.title(u"锯齿波（灰）&方波的频谱") #sawtooth.make_spectrum().plot(color='gray')#将原锯齿波显示为灰色便于观察 #square = SquareSignal(amp=0.5).make_wave(duration=0.5, framerate=40000) #将方波的振幅调整为0.5便于比较 #square.make_spectrum().plot() #plt.subplot(515) plt.title(u"锯齿波（灰）&三角波的频谱") sawtooth.make_spectrum().plot(color='gray') triangle = TriangleSignal(amp=0.79).make_wave(duration=0.5, framerate=40000) triangle.make_spectrum().plot() plt.show()

[ "noreply@github.com" ]

wrh2048470785.noreply@github.com

37e661602813c679895aa41f210f591c32611488

d4ea1f4955863aa2a013c6f3ae206675cf437f51

/code-examples/mapreduce/wc_mapper.py

dc4fac9cfe07f66eda851d2ff279f984a56f6f1e

[]

no_license

SolGirouard/css

b20cec0df4c011603ec717512bbcd00016442cf1

fcf6fde063f290cb6a2fa7eedb288da810046dc9

refs/heads/master

2021-01-19T13:22:49.670095

2017-05-05T22:50:31

null

0

null

UTF-8

Python

false

611

py

#!/usr/bin/env python2 """Example mapper module for counting words via map-reduce. This file is saved as wc_mapper.py with execute permission (chmod +x wc_mapper.py)""" import sys def main(): """Take lines from stdin and emit each word with count 1. This is for illustration purposes, treating any string separated by whitespace as a 'word'. Additional cleaning (e.g., removing punctuation) could be added if necessary.""" for line in sys.stdin: words = line.strip().split() for word in words: print word + '\t' + '1' if __name__ == "__main__": main()

[ "jongbin@stanford.edu" ]

jongbin@stanford.edu

7dc97045f49c5a4732e198885b55b6eca8057611

b92adbd59161b701be466b3dbeab34e2b2aaf488

/.c9/metadata/environment/fb_post_learning/fb_post/utils/__init__.py

da90613ab5a9ef0bd8b13998516cf28468ee3e78

[]

no_license

R151865/cloud_9_files

7486fede7af4db4572f1b8033990a0f07f8749e8

a468c44e9aee4a37dea3c8c9188c6c06e91cc0c4

refs/heads/master

2022-11-22T10:45:39.439033

2020-07-23T09:31:52

281,904,416

0

1

null

2022-11-20T00:47:10

2020-07-23T09:08:48

Python

UTF-8

Python

false

24,199

py

{"filter":false,"title":"__init__.py","tooltip":"/fb_post_learning/fb_post/utils/__init__.py","undoManager":{"mark":93,"position":93,"stack":[[{"start":{"row":0,"column":0},"end":{"row":30,"column":12},"action":"insert","lines":["from .create_comment import create_comment","from .create_post import create_post","from .get_post import get_post","from .get_replies_for_comment import get_replies_for_comment","from .get_user_posts import get_user_posts","\"\"\"","from .other_functions import get_total_reaction_count, get_reaction_metrics","from .other_functions import delete_post, get_posts_with_more_positive_reactions","from .other_functions import get_posts_reacted_by_user, get_reactions_to_post","\"\"\"","from .react_to_comment import react_to_comment","from .react_to_post import react_to_post","from .reply_to_comment import reply_to_comment","","__all__ = ['create_comment',"," 'create_post',"," 'get_post',"," 'get_replies_for_comment',"," 'get_user_posts',"," 'react_to_comment',"," 'react_to_post',"," 'reply_to_comment'"," ]","","sb=['get_total_reaction_count',"," 'get_reaction_metrics',"," 'delete_post',"," 'get_posts_with_more_positive_reactions',"," 'get_posts_reacted_by_user',"," 'get_reactions_to_post',"," ]"],"id":1}],[{"start":{"row":21,"column":29},"end":{"row":21,"column":30},"action":"insert","lines":[","],"id":2}],[{"start":{"row":21,"column":30},"end":{"row":22,"column":0},"action":"insert","lines":["",""],"id":3},{"start":{"row":22,"column":0},"end":{"row":22,"column":11},"action":"insert","lines":[" "]}],[{"start":{"row":22,"column":11},"end":{"row":22,"column":35},"action":"insert","lines":["get_total_reaction_count"],"id":4}],[{"start":{"row":5,"column":0},"end":{"row":10,"column":0},"action":"remove","lines":["\"\"\"","from .other_functions import get_total_reaction_count, get_reaction_metrics","from .other_functions import delete_post, get_posts_with_more_positive_reactions","from .other_functions import get_posts_reacted_by_user, get_reactions_to_post","\"\"\"",""],"id":5}],[{"start":{"row":5,"column":0},"end":{"row":6,"column":0},"action":"insert","lines":["",""],"id":6}],[{"start":{"row":18,"column":35},"end":{"row":18,"column":36},"action":"insert","lines":["\""],"id":7}],[{"start":{"row":18,"column":11},"end":{"row":18,"column":12},"action":"insert","lines":["'"],"id":8}],[{"start":{"row":18,"column":36},"end":{"row":18,"column":37},"action":"remove","lines":["\""],"id":9}],[{"start":{"row":18,"column":36},"end":{"row":18,"column":37},"action":"insert","lines":["'"],"id":10},{"start":{"row":18,"column":37},"end":{"row":18,"column":38},"action":"insert","lines":[","]}],[{"start":{"row":9,"column":0},"end":{"row":10,"column":0},"action":"insert","lines":["",""],"id":11}],[{"start":{"row":10,"column":0},"end":{"row":10,"column":1},"action":"insert","lines":["F"],"id":12},{"start":{"row":10,"column":1},"end":{"row":10,"column":2},"action":"insert","lines":["R"]},{"start":{"row":10,"column":2},"end":{"row":10,"column":3},"action":"insert","lines":["O"]},{"start":{"row":10,"column":3},"end":{"row":10,"column":4},"action":"insert","lines":["M"]}],[{"start":{"row":10,"column":3},"end":{"row":10,"column":4},"action":"remove","lines":["M"],"id":13},{"start":{"row":10,"column":2},"end":{"row":10,"column":3},"action":"remove","lines":["O"]},{"start":{"row":10,"column":1},"end":{"row":10,"column":2},"action":"remove","lines":["R"]},{"start":{"row":10,"column":0},"end":{"row":10,"column":1},"action":"remove","lines":["F"]}],[{"start":{"row":10,"column":0},"end":{"row":10,"column":1},"action":"insert","lines":["f"],"id":14},{"start":{"row":10,"column":1},"end":{"row":10,"column":2},"action":"insert","lines":["r"]},{"start":{"row":10,"column":2},"end":{"row":10,"column":3},"action":"insert","lines":["o"]},{"start":{"row":10,"column":3},"end":{"row":10,"column":4},"action":"insert","lines":["m"]}],[{"start":{"row":10,"column":4},"end":{"row":10,"column":5},"action":"insert","lines":[" "],"id":15},{"start":{"row":10,"column":5},"end":{"row":10,"column":6},"action":"insert","lines":["."]}],[{"start":{"row":10,"column":6},"end":{"row":10,"column":7},"action":"insert","lines":["g"],"id":16},{"start":{"row":10,"column":7},"end":{"row":10,"column":8},"action":"insert","lines":["e"]},{"start":{"row":10,"column":8},"end":{"row":10,"column":9},"action":"insert","lines":["t"]},{"start":{"row":10,"column":9},"end":{"row":10,"column":10},"action":"insert","lines":["_"]},{"start":{"row":10,"column":10},"end":{"row":10,"column":11},"action":"insert","lines":["t"]},{"start":{"row":10,"column":11},"end":{"row":10,"column":12},"action":"insert","lines":["o"]}],[{"start":{"row":10,"column":6},"end":{"row":10,"column":12},"action":"remove","lines":["get_to"],"id":17},{"start":{"row":10,"column":6},"end":{"row":10,"column":30},"action":"insert","lines":["get_total_reaction_count"]}],[{"start":{"row":10,"column":30},"end":{"row":10,"column":31},"action":"insert","lines":[" "],"id":18},{"start":{"row":10,"column":31},"end":{"row":10,"column":32},"action":"insert","lines":["i"]},{"start":{"row":10,"column":32},"end":{"row":10,"column":33},"action":"insert","lines":["m"]},{"start":{"row":10,"column":33},"end":{"row":10,"column":34},"action":"insert","lines":["p"]},{"start":{"row":10,"column":34},"end":{"row":10,"column":35},"action":"insert","lines":["o"]},{"start":{"row":10,"column":35},"end":{"row":10,"column":36},"action":"insert","lines":["r"]},{"start":{"row":10,"column":36},"end":{"row":10,"column":37},"action":"insert","lines":["t"]}],[{"start":{"row":10,"column":37},"end":{"row":10,"column":38},"action":"insert","lines":[" "],"id":19},{"start":{"row":10,"column":38},"end":{"row":10,"column":39},"action":"insert","lines":["g"]},{"start":{"row":10,"column":39},"end":{"row":10,"column":40},"action":"insert","lines":["e"]},{"start":{"row":10,"column":40},"end":{"row":10,"column":41},"action":"insert","lines":["t"]}],[{"start":{"row":10,"column":38},"end":{"row":10,"column":41},"action":"remove","lines":["get"],"id":20},{"start":{"row":10,"column":38},"end":{"row":10,"column":62},"action":"insert","lines":["get_total_reaction_count"]}],[{"start":{"row":10,"column":62},"end":{"row":11,"column":0},"action":"insert","lines":["",""],"id":21},{"start":{"row":11,"column":0},"end":{"row":11,"column":1},"action":"insert","lines":["f"]},{"start":{"row":11,"column":1},"end":{"row":11,"column":2},"action":"insert","lines":["r"]},{"start":{"row":11,"column":2},"end":{"row":11,"column":3},"action":"insert","lines":["o"]},{"start":{"row":11,"column":3},"end":{"row":11,"column":4},"action":"insert","lines":["m"]}],[{"start":{"row":11,"column":3},"end":{"row":11,"column":4},"action":"remove","lines":["m"],"id":22},{"start":{"row":11,"column":2},"end":{"row":11,"column":3},"action":"remove","lines":["o"]},{"start":{"row":11,"column":1},"end":{"row":11,"column":2},"action":"remove","lines":["r"]},{"start":{"row":11,"column":0},"end":{"row":11,"column":1},"action":"remove","lines":["f"]}],[{"start":{"row":11,"column":0},"end":{"row":11,"column":1},"action":"insert","lines":["f"],"id":23},{"start":{"row":11,"column":1},"end":{"row":11,"column":2},"action":"insert","lines":["r"]},{"start":{"row":11,"column":2},"end":{"row":11,"column":3},"action":"insert","lines":["o"]},{"start":{"row":11,"column":3},"end":{"row":11,"column":4},"action":"insert","lines":["m"]}],[{"start":{"row":11,"column":4},"end":{"row":11,"column":5},"action":"insert","lines":[" "],"id":24},{"start":{"row":11,"column":5},"end":{"row":11,"column":6},"action":"insert","lines":["."]},{"start":{"row":11,"column":6},"end":{"row":11,"column":7},"action":"insert","lines":["e"]}],[{"start":{"row":11,"column":6},"end":{"row":11,"column":7},"action":"remove","lines":["e"],"id":25}],[{"start":{"row":11,"column":6},"end":{"row":11,"column":7},"action":"insert","lines":["g"],"id":26},{"start":{"row":11,"column":7},"end":{"row":11,"column":8},"action":"insert","lines":["e"]}],[{"start":{"row":11,"column":8},"end":{"row":11,"column":9},"action":"insert","lines":["t"],"id":27}],[{"start":{"row":11,"column":9},"end":{"row":11,"column":10},"action":"insert","lines":["r"],"id":28},{"start":{"row":11,"column":10},"end":{"row":11,"column":11},"action":"insert","lines":["e"]},{"start":{"row":11,"column":11},"end":{"row":11,"column":12},"action":"insert","lines":["a"]}],[{"start":{"row":11,"column":11},"end":{"row":11,"column":12},"action":"remove","lines":["a"],"id":29},{"start":{"row":11,"column":10},"end":{"row":11,"column":11},"action":"remove","lines":["e"]},{"start":{"row":11,"column":9},"end":{"row":11,"column":10},"action":"remove","lines":["r"]}],[{"start":{"row":11,"column":9},"end":{"row":11,"column":10},"action":"insert","lines":["_"],"id":30},{"start":{"row":11,"column":10},"end":{"row":11,"column":11},"action":"insert","lines":["r"]},{"start":{"row":11,"column":11},"end":{"row":11,"column":12},"action":"insert","lines":["e"]},{"start":{"row":11,"column":12},"end":{"row":11,"column":13},"action":"insert","lines":["a"]}],[{"start":{"row":11,"column":6},"end":{"row":11,"column":13},"action":"remove","lines":["get_rea"],"id":31},{"start":{"row":11,"column":6},"end":{"row":11,"column":26},"action":"insert","lines":["get_reaction_metrics"]}],[{"start":{"row":11,"column":26},"end":{"row":11,"column":27},"action":"insert","lines":[" "],"id":32},{"start":{"row":11,"column":27},"end":{"row":11,"column":28},"action":"insert","lines":["i"]},{"start":{"row":11,"column":28},"end":{"row":11,"column":29},"action":"insert","lines":["m"]},{"start":{"row":11,"column":29},"end":{"row":11,"column":30},"action":"insert","lines":["p"]},{"start":{"row":11,"column":30},"end":{"row":11,"column":31},"action":"insert","lines":["o"]},{"start":{"row":11,"column":31},"end":{"row":11,"column":32},"action":"insert","lines":["r"]},{"start":{"row":11,"column":32},"end":{"row":11,"column":33},"action":"insert","lines":["t"]}],[{"start":{"row":11,"column":33},"end":{"row":11,"column":34},"action":"insert","lines":[" "],"id":33},{"start":{"row":11,"column":34},"end":{"row":11,"column":35},"action":"insert","lines":["r"]},{"start":{"row":11,"column":35},"end":{"row":11,"column":36},"action":"insert","lines":["e"]},{"start":{"row":11,"column":36},"end":{"row":11,"column":37},"action":"insert","lines":["a"]}],[{"start":{"row":11,"column":36},"end":{"row":11,"column":37},"action":"remove","lines":["a"],"id":34},{"start":{"row":11,"column":35},"end":{"row":11,"column":36},"action":"remove","lines":["e"]},{"start":{"row":11,"column":34},"end":{"row":11,"column":35},"action":"remove","lines":["r"]}],[{"start":{"row":11,"column":34},"end":{"row":11,"column":35},"action":"insert","lines":["g"],"id":35},{"start":{"row":11,"column":35},"end":{"row":11,"column":36},"action":"insert","lines":["e"]},{"start":{"row":11,"column":36},"end":{"row":11,"column":37},"action":"insert","lines":["t"]},{"start":{"row":11,"column":37},"end":{"row":11,"column":38},"action":"insert","lines":["_"]}],[{"start":{"row":11,"column":38},"end":{"row":11,"column":39},"action":"insert","lines":["r"],"id":36},{"start":{"row":11,"column":39},"end":{"row":11,"column":40},"action":"insert","lines":["e"]},{"start":{"row":11,"column":40},"end":{"row":11,"column":41},"action":"insert","lines":["a"]}],[{"start":{"row":11,"column":34},"end":{"row":11,"column":41},"action":"remove","lines":["get_rea"],"id":37},{"start":{"row":11,"column":34},"end":{"row":11,"column":54},"action":"insert","lines":["get_reaction_metrics"]}],[{"start":{"row":20,"column":38},"end":{"row":21,"column":0},"action":"insert","lines":["",""],"id":38},{"start":{"row":21,"column":0},"end":{"row":21,"column":11},"action":"insert","lines":[" "]}],[{"start":{"row":21,"column":11},"end":{"row":21,"column":13},"action":"insert","lines":["''"],"id":39}],[{"start":{"row":21,"column":12},"end":{"row":21,"column":32},"action":"insert","lines":["get_reaction_metrics"],"id":40}],[{"start":{"row":21,"column":33},"end":{"row":21,"column":34},"action":"insert","lines":[","],"id":41}],[{"start":{"row":21,"column":34},"end":{"row":22,"column":0},"action":"insert","lines":["",""],"id":42},{"start":{"row":22,"column":0},"end":{"row":22,"column":11},"action":"insert","lines":[" "]}],[{"start":{"row":11,"column":54},"end":{"row":12,"column":0},"action":"insert","lines":["",""],"id":43},{"start":{"row":12,"column":0},"end":{"row":12,"column":1},"action":"insert","lines":["f"]},{"start":{"row":12,"column":1},"end":{"row":12,"column":2},"action":"insert","lines":["r"]},{"start":{"row":12,"column":2},"end":{"row":12,"column":3},"action":"insert","lines":["o"]},{"start":{"row":12,"column":3},"end":{"row":12,"column":4},"action":"insert","lines":["m"]}],[{"start":{"row":12,"column":4},"end":{"row":12,"column":5},"action":"insert","lines":[" "],"id":44},{"start":{"row":12,"column":5},"end":{"row":12,"column":6},"action":"insert","lines":["."]},{"start":{"row":12,"column":6},"end":{"row":12,"column":7},"action":"insert","lines":["d"]},{"start":{"row":12,"column":7},"end":{"row":12,"column":8},"action":"insert","lines":["e"]},{"start":{"row":12,"column":8},"end":{"row":12,"column":9},"action":"insert","lines":["l"]}],[{"start":{"row":12,"column":6},"end":{"row":12,"column":9},"action":"remove","lines":["del"],"id":45},{"start":{"row":12,"column":6},"end":{"row":12,"column":17},"action":"insert","lines":["delete_post"]}],[{"start":{"row":12,"column":17},"end":{"row":12,"column":18},"action":"insert","lines":[" "],"id":46},{"start":{"row":12,"column":18},"end":{"row":12,"column":19},"action":"insert","lines":["i"]},{"start":{"row":12,"column":19},"end":{"row":12,"column":20},"action":"insert","lines":["m"]},{"start":{"row":12,"column":20},"end":{"row":12,"column":21},"action":"insert","lines":["p"]},{"start":{"row":12,"column":21},"end":{"row":12,"column":22},"action":"insert","lines":["o"]},{"start":{"row":12,"column":22},"end":{"row":12,"column":23},"action":"insert","lines":["r"]},{"start":{"row":12,"column":23},"end":{"row":12,"column":24},"action":"insert","lines":["t"]}],[{"start":{"row":12,"column":24},"end":{"row":12,"column":25},"action":"insert","lines":[" "],"id":47},{"start":{"row":12,"column":25},"end":{"row":12,"column":26},"action":"insert","lines":["d"]},{"start":{"row":12,"column":26},"end":{"row":12,"column":27},"action":"insert","lines":["e"]}],[{"start":{"row":12,"column":25},"end":{"row":12,"column":27},"action":"remove","lines":["de"],"id":48},{"start":{"row":12,"column":25},"end":{"row":12,"column":36},"action":"insert","lines":["delete_post"]}],[{"start":{"row":22,"column":34},"end":{"row":23,"column":0},"action":"insert","lines":["",""],"id":49},{"start":{"row":23,"column":0},"end":{"row":23,"column":11},"action":"insert","lines":[" "]}],[{"start":{"row":23,"column":11},"end":{"row":23,"column":13},"action":"insert","lines":["\"\""],"id":50}],[{"start":{"row":23,"column":12},"end":{"row":23,"column":23},"action":"insert","lines":["delete_post"],"id":51}],[{"start":{"row":23,"column":23},"end":{"row":23,"column":24},"action":"remove","lines":["\""],"id":52}],[{"start":{"row":23,"column":11},"end":{"row":23,"column":12},"action":"remove","lines":["\""],"id":53}],[{"start":{"row":23,"column":11},"end":{"row":23,"column":12},"action":"insert","lines":["'"],"id":54}],[{"start":{"row":23,"column":23},"end":{"row":23,"column":24},"action":"insert","lines":["'"],"id":55},{"start":{"row":23,"column":24},"end":{"row":23,"column":25},"action":"insert","lines":[","]}],[{"start":{"row":23,"column":25},"end":{"row":24,"column":0},"action":"insert","lines":["",""],"id":56},{"start":{"row":24,"column":0},"end":{"row":24,"column":11},"action":"insert","lines":[" "]}],[{"start":{"row":24,"column":11},"end":{"row":24,"column":13},"action":"insert","lines":["''"],"id":57}],[{"start":{"row":12,"column":36},"end":{"row":13,"column":0},"action":"insert","lines":["",""],"id":58}],[{"start":{"row":13,"column":0},"end":{"row":14,"column":0},"action":"insert","lines":["",""],"id":59}],[{"start":{"row":14,"column":0},"end":{"row":15,"column":0},"action":"insert","lines":["from .delete_post import delete_post",""],"id":60}],[{"start":{"row":27,"column":12},"end":{"row":27,"column":50},"action":"insert","lines":["get_posts_with_more_positive_reactions"],"id":61}],[{"start":{"row":27,"column":51},"end":{"row":27,"column":52},"action":"insert","lines":[","],"id":62}],[{"start":{"row":27,"column":52},"end":{"row":28,"column":0},"action":"insert","lines":["",""],"id":63},{"start":{"row":28,"column":0},"end":{"row":28,"column":11},"action":"insert","lines":[" "]}],[{"start":{"row":14,"column":6},"end":{"row":14,"column":17},"action":"remove","lines":["delete_post"],"id":64},{"start":{"row":14,"column":6},"end":{"row":14,"column":44},"action":"insert","lines":["get_posts_with_more_positive_reactions"]}],[{"start":{"row":14,"column":52},"end":{"row":14,"column":63},"action":"remove","lines":["delete_post"],"id":65},{"start":{"row":14,"column":52},"end":{"row":14,"column":90},"action":"insert","lines":["get_posts_with_more_positive_reactions"]}],[{"start":{"row":28,"column":11},"end":{"row":28,"column":13},"action":"insert","lines":["''"],"id":66}],[{"start":{"row":28,"column":12},"end":{"row":28,"column":37},"action":"insert","lines":["get_posts_reacted_by_user"],"id":67}],[{"start":{"row":28,"column":38},"end":{"row":28,"column":39},"action":"insert","lines":[","],"id":68}],[{"start":{"row":28,"column":39},"end":{"row":29,"column":0},"action":"insert","lines":["",""],"id":69},{"start":{"row":29,"column":0},"end":{"row":29,"column":11},"action":"insert","lines":[" "]}],[{"start":{"row":15,"column":0},"end":{"row":15,"column":1},"action":"insert","lines":["f"],"id":70},{"start":{"row":15,"column":1},"end":{"row":15,"column":2},"action":"insert","lines":["r"]},{"start":{"row":15,"column":2},"end":{"row":15,"column":3},"action":"insert","lines":["o"]},{"start":{"row":15,"column":3},"end":{"row":15,"column":4},"action":"insert","lines":["m"]}],[{"start":{"row":15,"column":4},"end":{"row":15,"column":5},"action":"insert","lines":[" "],"id":71},{"start":{"row":15,"column":5},"end":{"row":15,"column":6},"action":"insert","lines":["."]}],[{"start":{"row":15,"column":6},"end":{"row":15,"column":31},"action":"insert","lines":["get_posts_reacted_by_user"],"id":72}],[{"start":{"row":15,"column":31},"end":{"row":15,"column":32},"action":"insert","lines":[" "],"id":73},{"start":{"row":15,"column":32},"end":{"row":15,"column":33},"action":"insert","lines":["i"]},{"start":{"row":15,"column":33},"end":{"row":15,"column":34},"action":"insert","lines":["m"]},{"start":{"row":15,"column":34},"end":{"row":15,"column":35},"action":"insert","lines":["p"]},{"start":{"row":15,"column":35},"end":{"row":15,"column":36},"action":"insert","lines":["r"]},{"start":{"row":15,"column":36},"end":{"row":15,"column":37},"action":"insert","lines":["t"]}],[{"start":{"row":15,"column":36},"end":{"row":15,"column":37},"action":"remove","lines":["t"],"id":74},{"start":{"row":15,"column":35},"end":{"row":15,"column":36},"action":"remove","lines":["r"]}],[{"start":{"row":15,"column":35},"end":{"row":15,"column":36},"action":"insert","lines":["o"],"id":75},{"start":{"row":15,"column":36},"end":{"row":15,"column":37},"action":"insert","lines":["r"]},{"start":{"row":15,"column":37},"end":{"row":15,"column":38},"action":"insert","lines":["t"]}],[{"start":{"row":15,"column":38},"end":{"row":15,"column":39},"action":"insert","lines":[" "],"id":76}],[{"start":{"row":15,"column":39},"end":{"row":15,"column":64},"action":"insert","lines":["get_posts_reacted_by_user"],"id":77}],[{"start":{"row":15,"column":64},"end":{"row":16,"column":0},"action":"insert","lines":["",""],"id":80},{"start":{"row":16,"column":0},"end":{"row":16,"column":1},"action":"insert","lines":["f"]},{"start":{"row":16,"column":1},"end":{"row":16,"column":2},"action":"insert","lines":["o"]},{"start":{"row":16,"column":2},"end":{"row":16,"column":3},"action":"insert","lines":["m"]}],[{"start":{"row":16,"column":2},"end":{"row":16,"column":3},"action":"remove","lines":["m"],"id":81},{"start":{"row":16,"column":1},"end":{"row":16,"column":2},"action":"remove","lines":["o"]}],[{"start":{"row":16,"column":1},"end":{"row":16,"column":2},"action":"insert","lines":["r"],"id":82},{"start":{"row":16,"column":2},"end":{"row":16,"column":3},"action":"insert","lines":["o"]},{"start":{"row":16,"column":3},"end":{"row":16,"column":4},"action":"insert","lines":["m"]}],[{"start":{"row":16,"column":4},"end":{"row":16,"column":5},"action":"insert","lines":[" "],"id":83},{"start":{"row":16,"column":5},"end":{"row":16,"column":6},"action":"insert","lines":["."]}],[{"start":{"row":30,"column":11},"end":{"row":30,"column":13},"action":"insert","lines":["''"],"id":84}],[{"start":{"row":30,"column":12},"end":{"row":30,"column":33},"action":"insert","lines":["get_reactions_to_post"],"id":85}],[{"start":{"row":16,"column":6},"end":{"row":16,"column":27},"action":"insert","lines":["get_reactions_to_post"],"id":86}],[{"start":{"row":16,"column":27},"end":{"row":16,"column":28},"action":"insert","lines":[" "],"id":87},{"start":{"row":16,"column":28},"end":{"row":16,"column":29},"action":"insert","lines":["i"]},{"start":{"row":16,"column":29},"end":{"row":16,"column":30},"action":"insert","lines":["m"]},{"start":{"row":16,"column":30},"end":{"row":16,"column":31},"action":"insert","lines":["p"]},{"start":{"row":16,"column":31},"end":{"row":16,"column":32},"action":"insert","lines":["o"]},{"start":{"row":16,"column":32},"end":{"row":16,"column":33},"action":"insert","lines":["r"]},{"start":{"row":16,"column":33},"end":{"row":16,"column":34},"action":"insert","lines":["t"]}],[{"start":{"row":16,"column":34},"end":{"row":16,"column":35},"action":"insert","lines":[" "],"id":88}],[{"start":{"row":16,"column":35},"end":{"row":16,"column":56},"action":"insert","lines":["get_reactions_to_post"],"id":89}],[{"start":{"row":16,"column":56},"end":{"row":17,"column":0},"action":"insert","lines":["",""],"id":90},{"start":{"row":17,"column":0},"end":{"row":18,"column":0},"action":"insert","lines":["",""]}],[{"start":{"row":36,"column":0},"end":{"row":42,"column":12},"action":"remove","lines":["sb=['get_total_reaction_count',"," 'get_reaction_metrics',"," 'delete_post',"," 'get_posts_with_more_positive_reactions',"," 'get_posts_reacted_by_user',"," 'get_reactions_to_post',"," ]"],"id":91},{"start":{"row":35,"column":0},"end":{"row":36,"column":0},"action":"remove","lines":["",""]},{"start":{"row":34,"column":12},"end":{"row":35,"column":0},"action":"remove","lines":["",""]}],[{"start":{"row":33,"column":10},"end":{"row":33,"column":11},"action":"remove","lines":[" "],"id":92},{"start":{"row":33,"column":9},"end":{"row":33,"column":10},"action":"remove","lines":[" "]},{"start":{"row":33,"column":8},"end":{"row":33,"column":9},"action":"remove","lines":[" "]},{"start":{"row":33,"column":4},"end":{"row":33,"column":8},"action":"remove","lines":[" "]},{"start":{"row":33,"column":0},"end":{"row":33,"column":4},"action":"remove","lines":[" "]},{"start":{"row":32,"column":34},"end":{"row":33,"column":0},"action":"remove","lines":["",""]}],[{"start":{"row":14,"column":51},"end":{"row":14,"column":52},"action":"remove","lines":[" "],"id":93}],[{"start":{"row":14,"column":51},"end":{"row":14,"column":52},"action":"insert","lines":["\\"],"id":94}],[{"start":{"row":14,"column":52},"end":{"row":15,"column":0},"action":"insert","lines":["",""],"id":95}],[{"start":{"row":15,"column":0},"end":{"row":15,"column":11},"action":"insert","lines":[" "],"id":96}]]},"ace":{"folds":[],"scrolltop":80.6879657657598,"scrollleft":0,"selection":{"start":{"row":15,"column":11},"end":{"row":15,"column":11},"isBackwards":false},"options":{"guessTabSize":true,"useWrapMode":false,"wrapToView":true},"firstLineState":{"row":3,"state":"start","mode":"ace/mode/python"}},"timestamp":1588912940229,"hash":"aebebb4973aa457238f537967f37636bcaf98c26"}

[ "r151865@rguktrkv.ac.in" ]

r151865@rguktrkv.ac.in

0a2ef5825e62d7df2aea484feabf55d8d106bc18

225a5b040c0fdb758b5077fe779315339c46d828

/detect/lib/prepare_training_data/txt2voc.py

a9d2a5dc0bc735793aa56d09e83c83c2b6458e7c

[]

no_license

RobotWithCV/ocrui

b9b37cf238f97cddd70024bc27946754f476bbd2

459c82e8e31831533c4b60ac3e90b90ce68b9a9e

refs/heads/master

2020-05-19T18:31:33.281564

2018-08-15T12:34:18

null

0

null

UTF-8

Python

false

2,584

py

import os import numpy as np import math import cv2 as cv root = '/home/deeple/project/ctpn/text-detection-ctpn/data/0730/' path = root + 'errdata' gt_path = root + 'errlabel_txt' out_path = 're_image' if not os.path.exists(out_path): os.makedirs(out_path) files = os.listdir(path) files.sort() #files=files[:100] for file in files: _, basename = os.path.split(file) if basename.lower().split('.')[-1] not in ['jpg', 'png']: continue stem, ext = os.path.splitext(basename) gt_file = os.path.join(gt_path, '' + stem + '.txt') img_path = os.path.join(path, file) print(img_path) img = cv.imread(img_path) img_size = img.shape im_size_min = np.min(img_size[0:2]) im_size_max = np.max(img_size[0:2]) # im_scale = float(600) / float(im_size_min) # if np.round(im_scale * im_size_max) > 1200: # im_scale = float(1200) / float(im_size_max) # re_im = cv.resize(img, None, None, fx=im_scale, fy=im_scale, interpolation=cv.INTER_LINEAR) # re_size = re_im.shape cv.imwrite(os.path.join(out_path, stem) + '.jpg', img) with open(gt_file, 'r') as f: lines = f.readlines() for line in lines: tmp = line.strip('\n').split(',') xmin, ymin, xmax, ymax = [int(i) for i in tmp] width = xmax - xmin height = ymax - ymin # reimplement step = 16.0 x_left = [] x_right = [] x_left.append(xmin) x_left_start = int(math.ceil(xmin / 16.0) * 16.0) if x_left_start == xmin: x_left_start = xmin + 16 for i in np.arange(x_left_start, xmax, 16): x_left.append(i) x_left = np.array(x_left) x_right.append(x_left_start - 1) for i in range(1, len(x_left) - 1): x_right.append(x_left[i] + 15) x_right.append(xmax) x_right = np.array(x_right) idx = np.where(x_left == x_right) x_left = np.delete(x_left, idx, axis=0) x_right = np.delete(x_right, idx, axis=0) if not os.path.exists('label_tmp'): os.makedirs('label_tmp') with open(os.path.join('label_tmp', stem) + '.txt', 'a') as f: for i in range(len(x_left)): f.writelines("text\t") f.writelines(str(int(x_left[i]))) f.writelines("\t") f.writelines(str(int(ymin))) f.writelines("\t") f.writelines(str(int(x_right[i]))) f.writelines("\t") f.writelines(str(int(ymax))) f.writelines("\n")

[ "651238355@qq.com" ]

651238355@qq.com

67e65c9303e2f35244f9a50b2a85e1d3d3956dbb

82b69271d5473d538fb9230c0cc316d5cd5bd5f3

/tests/settings.py

b123d7fec0420117c939a67c94b21990a38fb8a7

[ "MIT" ]

permissive

aaloy/django-simple-options

3ade7369eaebd15bc4d0af7f1d1ba458b15b7c22

3199faf5da34e6cb05fc7dab4890a6f32b1f5217

refs/heads/master

2020-06-12T02:33:45.489231

2019-06-28T15:43:43

194,169,633

0

MIT

2019-06-27T22:12:48

null

UTF-8

Python

false

487

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals, absolute_import import django DEBUG = True USE_TZ = True SECRET_KEY = "dummy" DATABASES = { "default": { "ENGINE": "django.db.backends.sqlite3", "NAME": ":memory:", } } INSTALLED_APPS = [ "django.contrib.auth", "django.contrib.contenttypes", "django.contrib.sites", "options", ] SITE_ID = 1 if django.VERSION >= (1, 10): MIDDLEWARE = () else: MIDDLEWARE_CLASSES = ()

[ "marcosgabarda@gmail.com" ]

marcosgabarda@gmail.com

814fba12e0e1c92414fe77f4e1ff2cfc2fc371a4

5f2103b1083b088aed3f3be145d01a770465c762

/187. Repeated DNA Sequences.py

6a64da5e4c341cebe26e62b83c60533052f79460

[]

no_license

supersj/LeetCode

5605c9bcb5ddcaa83625de2ad9e06c3485220019

690adf05774a1c500d6c9160223dab7bcc38ccc1

refs/heads/master

2021-01-17T17:23:39.585738

2017-02-27T15:08:42

65,526,089

2

0

null

UTF-8

Python

false

854

py

# All DNA is composed of a series of nucleotides abbreviated as A, C, G, and T, for example: "ACGAATTCCG". When studying DNA, it is sometimes useful to identify repeated sequences within the DNA. # # Write a function to find all the 10-letter-long sequences (substrings) that occur more than once in a DNA molecule. # # For example, class Solution(object): def findRepeatedDnaSequences(self, s): """ :type s: str :rtype: List[str] """ result = {} hashmap = {} slen = len(s) if slen < 10: return [] for i in range(slen-10+1): tmp = s[i:i+10] if tmp in hashmap.keys() and tmp not in result.keys() : result[s[i:i+10]] = 1 else: hashmap[s[i:i+10]] = 1 return result.keys()

[ "ml@ml.ml" ]

ml@ml.ml

df205bbcb23d0a5a2204480913e333ac31bcc619

e9dda48b620484a50d5685c8f7f17284bb42a086

/rig/zbw_shapeClash.py

9c63afcc20a48886d47eccaf4884bf3e2965d2a2

[]

no_license

zethwillie/zTools

5b7b1903c18e4e619b07f1eb92c4c3f24c0f1a54

04bc49af814561264f08b2af2b2a503a0d63440c

refs/heads/master

2022-08-26T19:47:32.844348

2022-07-18T15:12:48

53,161,975

5

4

null

UTF-8

Python

false

334

py

"""zbw_shapeClash""" import maya.cmds as cmds import zTools.resources.zbw_clash as clash reload(clash) # get all shape node clashes def shapeClash(): clashes = clash.detectShapeClashes(fixClashes = False) print("in Shape Clashes:", clashes) # put them all into a list # button to fix the shape nodes for each clash incident

[ "zethwillie@gmail.com" ]

zethwillie@gmail.com

c39c950b162896d3455479b623469d98e24be1df

830e2b774c2884252fed369ba38f11636890d33d

/www/cgi-bin/register.py

a9d93da51e56045f272bb4ec7324c26c9d624201

[]

no_license

AckerStewie/todo

419fddc9bedc6bf9a268ce7f28b69e24aa5882e7

7d0582bd8d02e5a3b633bad7b109448310ffa544

refs/heads/master

2020-06-28T03:56:18.175884

2019-08-02T00:32:27

197,731,153

0

null

UTF-8

Python

false

980

py

import psycopg2 #データベース接続 conn = psycopg2.connect("dbname=postgres user=postgres password=password") #カーソル取得 cur = conn.cursor() #select文の実行 cur.execute("SELECT * FROM priorites;") ERA = [] #for row in cur: # ERA.append((row[1].***,row[0)) print(""" <!DOCTYPE html> <html lang="ja"> <head> <meta charset="UTF-8" /> <title>新規登録</title> <link rel="stylesheet" href="../css/register.css" /> </head> <body> <form action="login.py" method="post"> <h1>新規登録</h1> <p>ユーザーID</p> <input type="text" placeholder="ユーザーIDを入力してください。" name="user_id"/> <p>パスワード</p> <input type="text" placeholder="パスワードを入力してください。" name="password"/> <p>パスワード再入力</p> <input type="text" placeholder="再度パスワードを入力してください。" name="re_password"/> <button>決定</button> </form> </body> </html> """) #try: #except:

[ "fkiseexz5@i.softbank.jp" ]

fkiseexz5@i.softbank.jp

330b4fce52616fc3aeac0ed2bbdef3bd4b5793c4

d725745f5c6b4ad99399aa50f368db39f5046f81

/angr_platforms/tricore/bo_instr.py

9402711fd0eabc663d5ad0d234880096523d9d7f

[ "BSD-2-Clause" ]

permissive

angr/angr-platforms

6816d777ea4696af05290613a490e91b8daa79ea

06db4e6a594af47aaeb0a5071f2cdb9a8c30f7f5

refs/heads/master

2023-03-05T10:15:20.783462

2023-02-20T18:38:12

86,003,468

60

28

BSD-2-Clause

2023-08-31T19:50:46

2017-03-23T22:28:04

Python

UTF-8

Python

false

57,764

py

#!/usr/bin/env python3 """ bo_instr.py Implementation of tricore BO format instructions. """ import sys from pyvex.lifting.util import Type, Instruction import bitstring from .rtl import reverse16, extend_to_32_bits from .logger import log_this class BO_LD_09_Instructions(Instruction): """ A class for LOAD instruction with OP=09 """ name = 'BO_LD_09_Instructions ...' op = "{0}{1}".format(bin(0)[2:].zfill(4), bin(9)[2:].zfill(4)) bin_format = op + 'a'*4 + 'b'*4 + 'c'*4 + 'd'*4 + 'e'*4 + 'f'*4 def parse(self, bitstrm): data = Instruction.parse(self, bitstrm) tmp = bitstring.BitArray(bin="{0}{1}{2}{3}{4}{5}".format(data['e'], data['f'], data['c'], data['d'], data['a'], data['b'])) off10 = bitstring.BitArray(bin="{0}{1}".format(tmp[0:4].bin, tmp[10:16].bin).zfill(12)) op2 = bitstring.BitArray(bin="{0}".format(tmp[4:10])) op2 = int(op2.bin, 2) b = tmp[16:20] a = tmp[20:] if op2 == 0x0: self.name = 'BO_LD.B_PostInc' elif op2 == 0x1: self.name = 'BO_LD.BU_PostInc' elif op2 == 0x2: self.name = 'BO_LD.H_PostInc' elif op2 == 0x3: self.name = 'BO_LD.HU_PostInc' elif op2 == 0x4: self.name = 'BO_LD.W_PostInc' elif op2 == 0x5: self.name = 'BO_LD.D_PostInc' elif op2 == 0x6: self.name = 'BO_LD.A_PostInc' elif op2 == 0x7: self.name = 'BO_LD.DA_PostInc' elif op2 == 0x8: self.name = 'BO_LD.Q_PostInc' elif op2 == 0x10: self.name = 'BO_LD.B_PreInc' elif op2 == 0x11: self.name = 'BO_LD.BU_PreInc' elif op2 == 0x12: self.name = 'BO_LD.H_PreInc' elif op2 == 0x13: self.name = 'BO_LD.HU_PreInc' elif op2 == 0x14: self.name = 'BO_LD.W_PreInc' elif op2 == 0x15: self.name = 'BO_LD.D_PreInc' elif op2 == 0x16: self.name = 'BO_LD.A_PreInc' elif op2 == 0x17: self.name = 'BO_LD.DA_PreInc' elif op2 == 0x18: self.name = 'BO_LD.Q_PreInc' elif op2 == 0x20: self.name = 'BO_LD.B_BaseShortOffset' elif op2 == 0x21: self.name = 'BO_LD.BU_BaseShortOffset' elif op2 == 0x22: self.name = 'BO_LD.H_BaseShortOffset' elif op2 == 0x23: self.name = 'BO_LD.HU_BaseShortOffset' elif op2 == 0x24: self.name = 'BO_LD.W_BaseShortOffset' elif op2 == 0x25: self.name = 'BO_LD.D_BaseShortOffset' elif op2 == 0x26: self.name = 'BO_LD.A_BaseShortOffset' elif op2 == 0x27: self.name = 'BO_LD.DA_BaseShortOffset' elif op2 == 0x28: self.name = 'BO_LD.Q_BaseShortOffset' else: self.name = "UNKNOWN" data = {"a": int(a.hex, 16), "b": int(b.hex, 16), "off10": int(off10.hex, 16), "op2": op2} log_this(self.name, data, hex(self.addr)) return data def get_sign_ext_offset(self): return self.constant(self.data['off10'], Type.int_10).cast_to(Type.int_32, signed=True) def get_a_b(self): return self.get("a{0}".format(self.data['b']), Type.int_32) def fetch_operands(self): return [self.get_a_b(), self.get_sign_ext_offset()] def compute_result(self, *args): a_b = args[0] sign_ext_offset = args[1] result = "" op2 = self.data['op2'] if op2 == 0x0: # BO_LD.B_PostInc ea = a_b result = self.load(ea, Type.int_8).cast_to(Type.int_32, signed=True) self.put(result, "d{0}".format(self.data['a'])) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x1: # BO_LD.BU_PostInc ea = a_b result = self.load(ea, Type.int_8).cast_to(Type.int_32) self.put(result, "d{0}".format(self.data['a'])) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x2: # BO_LD.H_PostInc ea = a_b result = self.load(ea, Type.int_16).cast_to(Type.int_32, signed=True) self.put(result, "d{0}".format(self.data['a'])) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x3: # BO_LD.HU_PostInc ea = a_b result = self.load(ea, Type.int_16).cast_to(Type.int_32) self.put(result, "d{0}".format(self.data['a'])) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x4: # BO_LD.W_PostInc ea = a_b result = self.load(ea, Type.int_32) self.put(result, "d{0}".format(self.data['a'])) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x5: # BO_LD.D_PostInc ea = a_b result_0 = self.load(ea, Type.int_32) result_1 = self.load(ea+4, Type.int_32) self.put(result_0, "d{0}".format(self.data['a'])) self.put(result_1, "d{0}".format(self.data['a']+1)) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x6: # BO_LD.A_PostInc ea = a_b result = self.load(ea, Type.int_32) self.put(result, "a{0}".format(self.data['a'])) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x7: # BO_LD.DA_PostInc ea = a_b result_0 = self.load(ea, Type.int_32) result_1 = self.load(ea+4, Type.int_32) self.put(result_0, "a{0}".format(self.data['a'])) self.put(result_1, "a{0}".format(self.data['a']+1)) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x8: # BO_LD.Q_PostInc ea = a_b result = self.load(ea, Type.int_16).cast_to(Type.int_32) << 16 self.put(result, "d{0}".format(self.data['a'])) result_2 = ea + sign_ext_offset # increment self.put(result_2, "a{0}".format(self.data['b'])) elif op2 == 0x10: # BO_LD.B_PreInc ea = a_b + sign_ext_offset result = self.load(ea, Type.int_8).cast_to(Type.int_32, signed=True) self.put(result, "d{0}".format(self.data['a'])) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x11: # BO_LD.BU_PreInc ea = a_b + sign_ext_offset result = self.load(ea, Type.int_8).cast_to(Type.int_32) self.put(result, "d{0}".format(self.data['a'])) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x12: # BO_LD.H_PreInc ea = a_b + sign_ext_offset result = self.load(ea, Type.int_16).cast_to(Type.int_32, signed=True) self.put(result, "d{0}".format(self.data['a'])) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x13: # BO_LD.HU_PreInc ea = a_b + sign_ext_offset result = self.load(ea, Type.int_16).cast_to(Type.int_32) self.put(result, "d{0}".format(self.data['a'])) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x14: # BO_LD.W_PreInc ea = a_b + sign_ext_offset result = self.load(ea, Type.int_32) self.put(result, "d{0}".format(self.data['a'])) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x15: # BO_LD.D_PreInc ea = a_b + sign_ext_offset result_0 = self.load(ea, Type.int_32) result_1 = self.load(ea+4, Type.int_32) self.put(result_0, "d{0}".format(self.data['a'])) self.put(result_1, "d{0}".format(self.data['a']+1)) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x16: # BO_LD.A_PreInc ea = a_b + sign_ext_offset result = self.load(ea, Type.int_32) self.put(result, "a{0}".format(self.data['a'])) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x17: # BO_LD.DA_PreInc ea = a_b + sign_ext_offset result_0 = self.load(ea, Type.int_32) result_1 = self.load(ea+4, Type.int_32) self.put(result_0, "a{0}".format(self.data['a'])) self.put(result_1, "a{0}".format(self.data['a']+1)) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x18: # BO_LD.Q_PreInc ea = a_b + sign_ext_offset result = self.load(ea, Type.int_16).cast_to(Type.int_32) << 16 self.put(result, "d{0}".format(self.data['a'])) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x20: # BO_LD.B_BaseShortOffset ea = a_b + sign_ext_offset result = self.load(ea, Type.int_8).cast_to(Type.int_32, signed=True) self.put(result, "d{0}".format(self.data['a'])) elif op2 == 0x21: # BO_LD.BU_BaseShortOffset ea = a_b + sign_ext_offset result = self.load(ea, Type.int_8).cast_to(Type.int_32) self.put(result, "d{0}".format(self.data['a'])) elif op2 == 0x22: # BO_LD.H_BaseShortOffset ea = a_b + sign_ext_offset result = self.load(ea, Type.int_16).cast_to(Type.int_32, signed=True) self.put(result, "d{0}".format(self.data['a'])) elif op2 == 0x23: # BO_LD.HU_BaseShortOffset ea = a_b + sign_ext_offset result = self.load(ea, Type.int_16).cast_to(Type.int_32) self.put(result, "d{0}".format(self.data['a'])) elif op2 == 0x24: # BO_LD.W_BaseShortOffset ea = a_b + sign_ext_offset result = self.load(ea, Type.int_32) self.put(result, "d{0}".format(self.data['a'])) elif op2 == 0x25: # BO_LD.D_BaseShortOffset ea = a_b + sign_ext_offset result_0 = self.load(ea, Type.int_32) result_1 = self.load(ea+4, Type.int_32) self.put(result_0, "d{0}".format(self.data['a'])) self.put(result_1, "d{0}".format(self.data['a']+1)) elif op2 == 0x26: # BO_LD.A_BaseShortOffset ea = a_b + sign_ext_offset result = self.load(ea, Type.int_32) self.put(result, "a{0}".format(self.data['a'])) elif op2 == 0x27: # BO_LD.DA_BaseShortOffset ea = a_b + sign_ext_offset result_0 = self.load(ea, Type.int_32) result_1 = self.load(ea+4, Type.int_32) self.put(result_0, "a{0}".format(self.data['a'])) self.put(result_1, "a{0}".format(self.data['a']+1)) elif op2 == 0x28: # BO_LD.Q_BaseShortOffset ea = a_b + sign_ext_offset result = self.load(ea, Type.int_16).cast_to(Type.int_32) << 16 self.put(result, "d{0}".format(self.data['a'])) class BO_LD_29_Instructions(Instruction): """ A class for LOAD instructions with OP=29 """ name = 'BO_LD_29_Instructions ...' op = "{0}{1}".format(bin(2)[2:].zfill(4), bin(9)[2:].zfill(4)) bin_format = op + 'a'*4 + 'b'*4 + 'c'*4 + 'd'*4 + 'e'*4 + 'f'*4 def parse(self, bitstrm): data = Instruction.parse(self, bitstrm) tmp = bitstring.BitArray(bin="{0}{1}{2}{3}{4}{5}".format(data['e'], data['f'], data['c'], data['d'], data['a'], data['b'])) off10 = bitstring.BitArray(bin="{0}{1}".format(tmp[0:4].bin, tmp[10:16].bin)) op2 = bitstring.BitArray(bin="{0}".format(tmp[4:10])) op2 = int(op2.bin, 2) b = tmp[16:20] a = tmp[20:] if op2 == 0x0: self.name = 'BO_LD.B_BitRev' elif op2 == 0x1: self.name = 'BO_LD.BU_BitRev' elif op2 == 0x2: self.name = 'BO_LD.H_BitRev' elif op2 == 0x3: self.name = 'BO_LD.HU_BitRev' elif op2 == 0x4: self.name = 'BO_LD.W_BitRev' elif op2 == 0x5: self.name = 'BO_LD.D_BitRev' elif op2 == 0x6: self.name = 'BO_LD.A_BitRev' elif op2 == 0x7: self.name = 'BO_LD.DA_BitRev' elif op2 == 0x8: self.name = 'BO_LD.Q_BitRev' elif op2 == 0x10: self.name = 'BO_LD.B_Circ' elif op2 == 0x11: self.name = 'BO_LD.BU_Circ' elif op2 == 0x12: self.name = 'BO_LD.H_Circ' elif op2 == 0x13: self.name = 'BO_LD.HU_Circ' elif op2 == 0x14: self.name = 'BO_LD.W_Circ' elif op2 == 0x15: self.name = 'BO_LD.D_Circ' elif op2 == 0x16: self.name = 'BO_LD.A_Circ' elif op2 == 0x17: self.name = 'BO_LD.DA_Circ' elif op2 == 0x18: self.name = 'BO_LD.Q_Circ' else: self.name = "UNKNOWN" data = {"a": int(a.hex, 16), "b": int(b.hex, 16), "off10": int(off10.bin, 2), "op2": op2} log_this(self.name, data, hex(self.addr)) return data def get_dst_reg(self): if self.data['op2'] in ["0x6", "0x16"]: return "a{0}".format(self.data['a']) return "d{0}".format(self.data['a']) def get_sign_ext_offset(self): return self.constant(self.data['off10'], Type.int_10).cast_to(Type.int_32, signed=True) def get_a_b_1(self): return self.get("a{0}".format(self.data['b']+1), Type.int_32) def get_a_b(self): return self.get("a{0}".format(self.data['b']), Type.int_32) def fetch_operands(self): return self.get_a_b(), self.get_a_b_1(), self.get_sign_ext_offset() def compute_result(self, *args): a_b = args[0] a_b_1 = args[1] sign_ext_offset = args[2] result = "" op2 = self.data['op2'] if op2 == 0x0: # BO_LD.B_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_8).cast_to(Type.int_32, signed=True) new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) if op2 == 0x1: # BO_LD.BU_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_8) new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x2: # BO_LD.H_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_16).cast_to(Type.int_32, signed=True) new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x3: # BO_LD.HU_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_16) new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x4: # BO_LD.W_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_32) new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x5: # BO_LD.D_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result_0 = self.load(ea, Type.int_32) result_1 = self.load(ea+4, Type.int_32) self.put(result_0, "d{0}".format(self.data['a'])) self.put(result_1, "d{0}".format(self.data['a']+1)) new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x6: # BO_LD.A_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_32) new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x7: # BO_LD.DA_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result_0 = self.load(ea, Type.int_32) result_1 = self.load(ea+4, Type.int_32) self.put(result_0, "a{0}".format(self.data['a'])) self.put(result_1, "a{0}".format(self.data['a']+1)) new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x8: # BO_LD.Q_BitRev index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_16).cast_to(Type.int_32) << 16 new_index = reverse16(reverse16(index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x10: # BO_LD.B_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_8).cast_to(Type.int_32, signed=True) new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x11: # BO_LD.BU_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_8) new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x12: # BO_LD.H_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_16).cast_to(Type.int_32, signed=True) new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x13: # BO_LD.HU_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_16) new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x14: # BO_LD.W_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea_0 = a_b + index ea_2 = a_b + index + (2 % length) result = self.load(ea_2, Type.int_16).cast_to(Type.int_32) << 16 | \ self.load(ea_0, Type.int_16).cast_to(Type.int_32) new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x15: # BO_LD.D_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea_0 = a_b + index ea_2 = a_b + (index + 2) % length ea_4 = a_b + (index + 4) % length ea_6 = a_b + (index + 6) % length result_hw0 = self.load(ea_0, Type.int_16).cast_to(Type.int_32) result_hw1 = self.load(ea_2, Type.int_16).cast_to(Type.int_32) result_hw2 = self.load(ea_4, Type.int_16).cast_to(Type.int_32) result_hw3 = self.load(ea_6, Type.int_16).cast_to(Type.int_32) result_0 = (result_hw1 << 16) | result_hw0 result_1 = (result_hw3 << 16) | result_hw2 self.put(result_0, "d{0}".format(self.data['a'])) self.put(result_1, "d{0}".format(self.data['a']+1)) new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x16: # BO_LD.A_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_32) new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x17: # BO_LD.DA_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea_0 = a_b + index ea_4 = a_b + (index + 4) % length result_0 = self.load(ea_0, Type.int_32) result_1 = self.load(ea_4, Type.int_32) self.put(result_0, "a{0}".format(self.data['a'])) self.put(result_1, "a{0}".format(self.data['a']+1)) new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x18: # BO_LD.Q_Circ index = a_b_1 & 0xffff length = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_16).cast_to(Type.int_32) << 16 new_index = index + sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + length) & cond_new_index_neg) | \ ((new_index % length) & (cond_new_index_neg^0xffffffff)) result_2 = ((length & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) return result def commit_result(self, res): self.put(res, self.get_dst_reg()) class BO_49_Instructions(Instruction): """ A class for instructions with OP=49 """ name = 'BO_49_Instructions ...' op = "{0}{1}".format(bin(4)[2:].zfill(4), bin(9)[2:].zfill(4)) bin_format = op + 'a'*4 + 'b'*4 + 'c'*4 + 'd'*4 + 'e'*4 + 'f'*4 def parse(self, bitstrm): data = Instruction.parse(self, bitstrm) tmp = bitstring.BitArray(bin="{0}{1}{2}{3}{4}{5}".format(data['e'], data['f'], data['c'], data['d'], data['a'], data['b'])) off10 = bitstring.BitArray(bin="{0}{1}".format(tmp[0:4].bin, tmp[10:16].bin).zfill(12)) op2 = bitstring.BitArray(bin="{0}".format(tmp[4:10])) op2 = int(op2.bin, 2) b = tmp[16:20] a = tmp[20:] if op2 == 0x0: self.name = 'BO_SWAP.W (Post-increment Addressing Mode)' elif op2 == 0x1: self.name = 'BO_LDMST (Post-increment Addressing Mode)' elif op2 == 0x10: self.name = 'BO_SWAP.W (Pre-increment Addressing Mode)' elif op2 == 0x11: self.name = 'BO_LDMST (Pre-increment Addressing Mode)' elif op2 == 0x20: self.name = 'BO_SWAP.W (Base + Short Offset Addressing Mode)' elif op2 == 0x21: self.name = 'BO_LDMST (Base + Short Offset Addressing Mode)' elif op2 == 0x24: self.name = 'BO_LDLCX' elif op2 == 0x25: self.name = 'BO_LDUCX' elif op2 == 0x26: self.name = 'BO_STLCX' elif op2 == 0x27: self.name = 'BO_STUCX' elif op2 == 0x28: self.name = 'BO_LEA' else: self.name = "UNKNOWN" data = {"a": int(a.hex, 16), "b": int(b.hex, 16), "off10": int(off10.hex, 16), "op2": op2} log_this(self.name, data, hex(self.addr)) return data def get_sign_ext_offset(self): return self.constant(self.data['off10'], Type.int_10).cast_to(Type.int_32, signed=True) def get_a_b(self): return self.get("a{0}".format(self.data['b']), Type.int_32) def fetch_operands(self): return [self.get_a_b(), self.get_sign_ext_offset()] def compute_result(self, *args): a_b = args[0] sign_ext_offset = args[1] result = "" op2 = self.data['op2'] if op2 == 0x0: # SWAP.W (Post-increment Addressing Mode) ea = a_b tmp = self.load(ea, Type.int_32) self.store(self.get("d{0}".format(self.data['a']), Type.int_32), ea) self.put(tmp, "d{0}".format(self.data['a'])) self.put(ea + sign_ext_offset, "a{0}".format(self.data['b'])) elif op2 == 0x1: # LDMST (Post-increment Addressing Mode) ea = a_b result = self.load(ea, Type.int_32) e_a_1 = self.get("d{0}".format(self.data['a']), Type.int_32) # E[a][31:0] e_a_2 = self.get("d{0}".format(self.data['a']+1), Type.int_32) # E[a][63:32] result = (result & ~e_a_2) | (e_a_1 & e_a_2) self.store(result, ea) self.put(ea + sign_ext_offset, "a{0}".format(self.data['b'])) elif op2 == 0x10: # SWAP.W (Pre-increment Addressing Mode) tmp = self.load(ea, Type.int_32) self.store(self.get("d{0}".format(self.data['a']), Type.int_32), ea) self.put(tmp, "d{0}".format(self.data['a'])) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x11: # LDMST (Pre-increment Addressing Mode) result = self.load(ea, Type.int_32) e_a_1 = self.get("d{0}".format(self.data['a']), Type.int_32) # E[a][31:0] e_a_2 = self.get("d{0}".format(self.data['a']+1), Type.int_32) # E[a][63:32] result = (result & ~e_a_2) | (e_a_1 & e_a_2) self.store(result, ea) self.put(ea, "a{0}".format(self.data['b'])) elif op2 == 0x20: # SWAP.W (Base + Short Offset Addressing Mode) tmp = self.load(ea, Type.int_32) self.store(self.get("d{0}".format(self.data['a']), Type.int_32), ea) self.put(self.load(ea, Type.int_32), "a{0}".format(self.data['a'])) self.put(tmp, "d{0}".format(self.data['a'])) elif op2 == 0x21: # LDMST (Base + Short Offset Addressing Mode) ea = a_b + sign_ext_offset result = self.load(ea, Type.int_32) e_a_1 = self.get("d{0}".format(self.data['a']), Type.int_32) # E[a][31:0] e_a_2 = self.get("d{0}".format(self.data['a']+1), Type.int_32) # E[a][63:32] result = (result & ~e_a_2) | (e_a_1 & e_a_2) self.store(result, ea) elif op2 == 0x24: # LDLCX #dummy = self.load(ea, Type.int_32) #dummy = self.load(ea+4, Type.int_32) self.put(self.load(ea+8, Type.int_32), "a2") self.put(self.load(ea+12, Type.int_32), "a3") self.put(self.load(ea+16, Type.int_32), "d0") self.put(self.load(ea+20, Type.int_32), "d1") self.put(self.load(ea+24, Type.int_32), "d2") self.put(self.load(ea+28, Type.int_32), "d3") self.put(self.load(ea+32, Type.int_32), "a4") self.put(self.load(ea+36, Type.int_32), "a5") self.put(self.load(ea+40, Type.int_32), "a6") self.put(self.load(ea+44, Type.int_32), "a7") self.put(self.load(ea+48, Type.int_32), "d4") self.put(self.load(ea+52, Type.int_32), "d5") self.put(self.load(ea+56, Type.int_32), "d6") self.put(self.load(ea+60, Type.int_32), "d7") elif op2 == 0x25: # LDUCX #dummy = self.load(ea, Type.int_32) #dummy = self.load(ea+4, Type.int_32) self.put(self.load(ea+8, Type.int_32), "a10") self.put(self.load(ea+12, Type.int_32), "a11") self.put(self.load(ea+16, Type.int_32), "d8") self.put(self.load(ea+20, Type.int_32), "d9") self.put(self.load(ea+24, Type.int_32), "d10") self.put(self.load(ea+28, Type.int_32), "d11") self.put(self.load(ea+32, Type.int_32), "a12") self.put(self.load(ea+36, Type.int_32), "a13") self.put(self.load(ea+40, Type.int_32), "a14") self.put(self.load(ea+44, Type.int_32), "a15") self.put(self.load(ea+48, Type.int_32), "d12") self.put(self.load(ea+52, Type.int_32), "d13") self.put(self.load(ea+56, Type.int_32), "d14") self.put(self.load(ea+60, Type.int_32), "d15") elif op2 == 0x26: # STLCX self.store(self.get("pcxi", Type.int_32), ea) self.store(self.get("a11", Type.int_32), ea+4) self.store(self.get("a2", Type.int_32), ea+8) self.store(self.get("a3", Type.int_32), ea+12) self.store(self.get("d0", Type.int_32), ea+16) self.store(self.get("d1", Type.int_32), ea+20) self.store(self.get("d2", Type.int_32), ea+24) self.store(self.get("d3", Type.int_32), ea+28) self.store(self.get("a4", Type.int_32), ea+32) self.store(self.get("a5", Type.int_32), ea+36) self.store(self.get("a6", Type.int_32), ea+40) self.store(self.get("a7", Type.int_32), ea+44) self.store(self.get("d4", Type.int_32), ea+48) self.store(self.get("d5", Type.int_32), ea+52) self.store(self.get("d6", Type.int_32), ea+56) self.store(self.get("d7", Type.int_32), ea+60) elif op2 == 0x27: # STUCX self.store(self.get("pcxi", Type.int_32), ea) self.store(self.get("psw", Type.int_32), ea+4) self.store(self.get("a10", Type.int_32), ea+8) self.store(self.get("a11", Type.int_32), ea+12) self.store(self.get("d8", Type.int_32), ea+16) self.store(self.get("d9", Type.int_32), ea+20) self.store(self.get("d10", Type.int_32), ea+24) self.store(self.get("d11", Type.int_32), ea+28) self.store(self.get("a12", Type.int_32), ea+32) self.store(self.get("a13", Type.int_32), ea+36) self.store(self.get("a14", Type.int_32), ea+40) self.store(self.get("a15", Type.int_32), ea+44) self.store(self.get("d12", Type.int_32), ea+48) self.store(self.get("d13", Type.int_32), ea+52) self.store(self.get("d14", Type.int_32), ea+56) self.store(self.get("d15", Type.int_32), ea+60) elif op2 == 0x28: # LEA ea = a_b + sign_ext_offset self.put(ea, "a{0}".format(self.data["a"])) else: print("Error: Unknown OP2 '{0}'!".format(self.data['op2'])) print("BO instruction OP=49, OP2=Unknown") sys.exit(1) class BO_69_Instructions(Instruction): """ A class for instructions with OP=69 """ name = 'BO_69_Instructions ...' op = "{0}{1}".format(bin(4)[2:].zfill(4), bin(9)[2:].zfill(4)) bin_format = op + 'a'*4 + 'b'*4 + 'c'*4 + 'd'*4 + 'e'*4 + 'f'*4 def parse(self, bitstrm): data = Instruction.parse(self, bitstrm) tmp = bitstring.BitArray(bin="{0}{1}{2}{3}{4}{5}".format(data['e'], data['f'], data['c'], data['d'], data['a'], data['b'])) off10 = bitstring.BitArray(bin="{0}{1}".format(tmp[0:4].bin, tmp[10:16].bin).zfill(12)) op2 = bitstring.BitArray(bin="{0}".format(tmp[4:10])) op2 = int(op2.bin, 2) b = tmp[16:20] a = tmp[20:] if op2 == 0x0: self.name = 'BO_SWAP.W (Bit-reverse Addressing Mode)' elif op2 == 0x1: self.name = 'BO_LDMST (Bit-reverse Addressing Mode)' elif op2 == 0x10: self.name = 'BO_SWAP.W (Circular Addressing Mode)' elif op2 == 0x11: self.name = 'BO_LDMST (Circular Addressing Mode)' else: self.name = "UNKNOWN" data = {"a": int(a.hex, 16), "b": int(b.hex, 16), "off10": int(off10.hex, 16), "op2": op2} log_this(self.name, data, hex(self.addr)) return data def get_sign_ext_offset(self): return self.constant(self.data['off10'], Type.int_10).cast_to(Type.int_32, signed=True) def get_a_b(self): return self.get("a{0}".format(self.data['b']), Type.int_32) def get_a_b_1(self): return self.get("a{0}".format(self.data['b']+1), Type.int_32) def fetch_operands(self): return [self.get_a_b(), self.get_a_b_1(), self.get_sign_ext_offset()] def compute_result(self, *args): a_b = args[0] a_b_1 = args[1] sign_ext_offset = args[2] result = "" op2 = self.data['op2'] if op2 == 0x0: # SWAP.W (Bit-reverse Addressing Mode) index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index tmp = self.load(ea, Type.int_32) self.store("d{0}".format(self.data['a']), ea) self.put(tmp, "d{0}".format(self.data['a'])) new_index = reverse16(reverse16(index) + reverse16(incr)) self.put(((incr & 0xffff) << 16) | (new_index & 0xffff), "a{0}".format(self.data['b']+1)) elif op2 == 0x1: # LDMST (Bit-reverse Addressing Mode) index = a_b_1 & 0xffff incr = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_32) e_a_1 = self.get("d{0}".format(self.data['a']), Type.int_32) # E[a][31:0] e_a_2 = self.get("d{0}".format(self.data['a']+1), Type.int_32) # E[a][63:32] result = (result & ~e_a_2) | (e_a_1 & e_a_2) self.store(result, ea) new_index = reverse16(reverse16(index) + reverse16(incr)) self.put(((incr & 0xffff) << 16) | (new_index & 0xffff), "a{0}".format(self.data['b']+1)) elif op2 == 0x10: # SWAP.W (Circular Addressing Mode) index = a_b_1 & 0xffff length = a_b_1 >> 16 ea = a_b + index tmp = self.load(ea, Type.int_32) self.store("d{0}".format(self.data['a']), ea) self.put(tmp, "d{0}".format(self.data['a'])) new_index = index + sign_ext_offset new_index = (new_index < 0).ite( new_index + length, new_index % length ) self.put(((length & 0xffff) << 16) | (new_index & 0xffff), "a{0}".format(self.data['b']+1)) elif op2 == 0x11: # LDMST (Circular Addressing Mode) index = a_b_1 & 0xffff length = a_b_1 >> 16 ea = a_b + index result = self.load(ea, Type.int_32) e_a_1 = self.get("d{0}".format(self.data['a']), Type.int_32) # E[a][31:0] e_a_2 = self.get("d{0}".format(self.data['a']+1), Type.int_32) # E[a][63:32] result = (result & ~e_a_2) | (e_a_1 & e_a_2) self.store(result, ea) new_index = index + sign_ext_offset new_index = (new_index < 0).ite( new_index + length, new_index % length ) self.put(((length & 0xffff) << 16) | (new_index & 0xffff), "a{0}".format(self.data['b']+1)) else: print("Error: Unknown OP2 '{0}'!".format(self.data['op2'])) print("BO instruction OP=69, OP2=Unknown") sys.exit(1) class BO_ST_89_Instructions(Instruction): """ A class for STORE instructions with OP=89 """ name = 'BO_ST_89_Instructions ...' op = "{0}{1}".format(bin(8)[2:].zfill(4), bin(9)[2:].zfill(4)) bin_format = op + 'a'*4 + 'b'*4 + 'c'*4 + 'd'*4 + 'e'*4 + 'f'*4 def parse(self, bitstrm): data = Instruction.parse(self, bitstrm) tmp = bitstring.BitArray(bin="{0}{1}{2}{3}{4}{5}".format(data['e'], data['f'], data['c'], data['d'], data['a'], data['b'])) off10 = bitstring.BitArray(bin="{0}{1}".format(tmp[0:4].bin, tmp[10:16].bin)) op2 = bitstring.BitArray(bin="{0}".format(tmp[4:10])) op2 = int(op2.bin, 2) b = tmp[16:20] a = tmp[20:] if op2 == 0x6: self.name = 'BO_ST.A_PostInc' elif op2 == 0x16: self.name = 'BO_ST.A_PreInc' elif op2 == 0x26: self.name = 'BO_ST.A_BaseShortOffset' elif op2 == 0x0: self.name = 'BO_ST.B_PostInc' elif op2 == 0x10: self.name = 'BO_ST.B_PreInc' elif op2 == 0x20: self.name = 'BO_ST.B_BaseShortOffset' elif op2 == 0x2: self.name = 'BO_ST.H_PostInc' elif op2 == 0x12: self.name = 'BO_ST.H_PreInc' elif op2 == 0x22: self.name = 'BO_ST.H_BaseShortOffset' elif op2 == 0x4: self.name = 'BO_ST.W_PostInc' elif op2 == 0x14: self.name = 'BO_ST.W_PreInc' elif op2 == 0x24: self.name = 'BO_ST.W_BaseShortOffset' elif op2 == 0x5: self.name = 'BO_ST.D_PostInc' elif op2 == 0x15: self.name = 'BO_ST.D_PreInc' elif op2 == 0x25: self.name = 'BO_ST.D_BaseShortOffset' elif op2 == 0x7: self.name = 'BO_ST.DA_PostInc' elif op2 == 0x17: self.name = 'BO_ST.DA_PreInc' elif op2 == 0x27: self.name = 'BO_ST.DA_BaseShortOffset' elif op2 == 0x8: self.name = 'BO_ST.Q_PostInc' elif op2 == 0x18: self.name = 'BO_ST.Q_PreInc' elif op2 == 0x28: self.name = 'BO_ST.Q_BaseShortOffset' else: self.name = "UNKNOWN" data = {"a": int(a.bin, 2), "b": int(b.bin, 2), "off10": int(off10.bin, 2), "op2": op2} log_this(self.name, data, hex(self.addr)) return data @property def ea(self): """ Return A[b]+ off10. """ return self.a_b + self.sign_ext_offset @property def sign_ext_offset(self): return self.constant(self.data['off10'], Type.int_10).cast_to(Type.int_32, signed=True) @property def a_b(self): """ Return A[b] register. """ return self.get("a{0}".format(self.data['b']), Type.int_32) @property def a_a_1(self): """ Return A[a]+1 register. """ return self.get("a{0}".format(self.data['a']+1), Type.int_32) @property def a_a(self): """ Return A[a] register. """ return self.get("a{0}".format(self.data['a']), Type.int_32) @property def d_a_1(self): """ Return D[a]+1 register. """ return self.get("d{0}".format(self.data['a']+1), Type.int_32) @property def d_a(self): """ Return D[a] register """ return self.get("d{0}".format(self.data['a']), Type.int_32) def compute_result(self, *args): op2 = self.data['op2'] if op2 == 0x6: # BO_ST.A_PostInc self.store(self.a_a, self.a_b) inc = self.a_b + self.sign_ext_offset self.put(inc, "a{0}".format(self.data['b'])) elif op2 == 0x16: # BO_ST.A_PreInc self.store(self.a_a, self.ea) self.put(self.ea, "a{0}".format(self.data['b'])) elif op2 == 0x26: # BO_ST.A_BaseShortOffset self.store(self.a_a, self.ea) elif op2 == 0x0: # BO_ST.B_PostInc val = self.d_a & 0xff self.store(val, self.a_b) inc = self.a_b + self.sign_ext_offset self.put(inc, "a{0}".format(self.data['b'])) elif op2 == 0x10: # BO_ST.B_PreInc val = self.d_a & 0xff self.store(val, self.ea) self.put(self.ea, "a{0}".format(self.data['b'])) elif op2 == 0x20: # BO_ST.B_BaseShortOffset val = self.d_a & 0xff self.store(val, self.ea) elif op2 == 0x2: # BO_ST.H_PostInc val = self.d_a & 0xffff self.store(val, self.a_b) inc = self.a_b + self.sign_ext_offset self.put(inc, "a{0}".format(self.data['b'])) elif op2 == 0x12: # BO_ST.H_PreInc val = self.d_a & 0xffff self.store(val, self.ea) self.put(self.ea, "a{0}".format(self.data['b'])) elif op2 == 0x22: # BO_ST.H_BaseShortOffset val = self.d_a & 0xffff self.store(val, self.ea) elif op2 == 0x4: # BO_ST.W_PostInc val = self.d_a self.store(val, self.a_b) inc = self.a_b + self.sign_ext_offset self.put(inc, "a{0}".format(self.data['b'])) elif op2 == 0x14: # BO_ST.W_PreInc self.store(self.d_a, self.ea) self.put(self.ea, "a{0}".format(self.data['b'])) elif op2 == 0x24: # BO_ST.W_BaseShortOffset self.store(self.d_a, self.ea) elif op2 == 0x5: # BO_ST.D_PostInc self.store(self.d_a, self.a_b) self.store(self.d_a_1, self.a_b+4) inc = self.a_b + self.sign_ext_offset self.put(inc, "a{0}".format(self.data['b'])) elif op2 == 0x15: # BO_ST.D_PreInc self.store(self.d_a, self.ea) self.store(self.d_a_1, self.ea+4) self.put(self.ea, "a{0}".format(self.data['b'])) elif op2 == 0x25: # BO_ST.D_BaseShortOffset self.store(self.d_a, self.ea) self.store(self.d_a_1, self.ea+4) elif op2 == 0x7: # BO_ST.DA_PostInc self.store(self.a_a, self.a_b) self.store(self.a_a_1, self.a_b+4) inc = self.a_b + self.sign_ext_offset self.put(inc, "a{0}".format(self.data['b'])) elif op2 == 0x17: # BO_ST.DA_PreInc self.store(self.a_a, self.ea) self.store(self.a_a_1, self.ea+4) self.put(self.ea, "a{0}".format(self.data['b'])) elif op2 == 0x27: # BO_ST.DA_BaseShortOffset self.store(self.a_a, self.ea) self.store(self.a_a_1, self.ea+4) elif op2 == 0x8: # BO_ST.Q_PostInc val = self.d_a >> 16 self.store(val, self.a_b) inc = self.a_b + self.sign_ext_offset self.put(inc, "a{0}".format(self.data['b'])) elif op2 == 0x18: # BO_ST.Q_PreInc val = self.d_a >> 16 self.store(val, self.ea) self.put(self.ea, "a{0}".format(self.data['b'])) elif op2 == 0x28: # BO_ST.Q_BaseShortOffset val = self.d_a >> 16 self.store(val, self.ea) else: print("Error: Unknown OP2 '{0}'!".format(op2)) print("BO instruction OP=89, OP2=Unknown") sys.exit(1) class BO_ST_A9_Instructions(Instruction): """ A class for STORE instructions with OP=A9 """ name = 'BO_ST_A9_Instructions ...' op = "{0}{1}".format(bin(0xa)[2:].zfill(4), bin(9)[2:].zfill(4)) bin_format = op + 'a'*4 + 'b'*4 + 'c'*4 + 'd'*4 + 'e'*4 + 'f'*4 def parse(self, bitstrm): data = Instruction.parse(self, bitstrm) tmp = bitstring.BitArray(bin="{0}{1}{2}{3}{4}{5}".format(data['e'], data['f'], data['c'], data['d'], data['a'], data['b'])) off10 = bitstring.BitArray(bin="{0}{1}".format(tmp[0:4].bin, tmp[10:16].bin)) op2 = bitstring.BitArray(bin="{0}".format(tmp[4:10])) op2 = int(op2.bin, 2) b = tmp[16:20] a = tmp[20:] if op2 == 0x0: self.name = 'BO_ST.B_BitRev' elif op2 == 0x10: self.name = 'BO_ST.B_Circ' elif op2 == 0x5: self.name = 'BO_ST.D_BitRev' elif op2 == 0x15: self.name = 'BO_ST.D_Circ' elif op2 == 0x6: self.name = 'BO_ST.A_BitRev' elif op2 == 0x16: self.name = 'BO_ST.A_Circ' elif op2 == 0x7: self.name = 'BO_ST.DA_BitRev' elif op2 == 0x17: self.name = 'BO_ST.DA_Circ' elif op2 == 0x2: self.name = 'BO_ST.H_BitRev' elif op2 == 0x12: self.name = 'BO_ST.H_Circ' elif op2 == 0x8: self.name = 'BO_ST.Q_BitRev' elif op2 == 0x18: self.name = 'BO_ST.Q_Circ' elif op2 == 0x4: self.name = 'BO_ST.W_BitRev' elif op2 == 0x14: self.name = 'BO_ST.W_Circ' else: self.name = "UNKNOWN" data = {"a": int(a.hex, 16), "b": int(b.hex, 16), "off10": int(off10.bin, 2), "op2": op2} log_this(self.name, data, hex(self.addr)) return data @property def index(self): return self.a_b_1 & 0xffff @property def length(self): return self.a_b_1 >> 16 @property def ea_6(self): return self.a_b + ((self.index+6) % self.length) @property def ea_4(self): return self.a_b + ((self.index+4) % self.length) @property def ea_2(self): return self.a_b + ((self.index+2) % self.length) @property def ea_0(self): return self.a_b + self.index @property def sign_ext_offset(self): return self.constant(self.data['off10'], Type.int_10).cast_to(Type.int_32, signed=True) @property def a_b_1(self): return self.get("a{0}".format(self.data['b']+1), Type.int_32) @property def a_b(self): return self.get("a{0}".format(self.data['b']), Type.int_32) @property def a_a_1(self): return self.get("a{0}".format(self.data['a']+1), Type.int_32) @property def a_a(self): return self.get("a{0}".format(self.data['a']), Type.int_32) @property def d_a_1(self): return self.get("d{0}".format(self.data['a']+1), Type.int_32) @property def d_a(self): return self.get("d{0}".format(self.data['a']), Type.int_32) def compute_result(self, *args): op2 = self.data['op2'] if op2 == 0x0: # BO_ST.B_BitRev incr = self.a_b_1 >> 16 self.store(self.d_a & 0xff, self.ea_0) new_index = reverse16(reverse16(self.index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x10: # BO_ST.B_Circ self.store(self.d_a & 0xff, self.ea_0) new_index = self.index + self.sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + self.length) & cond_new_index_neg) | \ ((new_index % self.length) & (cond_new_index_neg^0xffffffff)) result = ((self.length & 0xffff) << 16) | (new_index & 0xffff) self.put(result, "a{0}".format(self.data['b']+1)) elif op2 == 0x5: # BO_ST.D_BitRev incr = self.a_b_1 >> 16 self.store(self.d_a, self.ea_0) self.store(self.d_a_1, self.ea_0+4) new_index = reverse16(reverse16(self.index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x15: # BO_ST.D_Circ self.store(self.d_a & 0xffff, self.ea_0) self.store(self.d_a >> 16, self.ea_2) self.store(self.d_a_1 & 0xffff, self.ea_4) self.store(self.d_a_1 >> 16, self.ea_6) new_index = self.index + self.sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + self.length) & cond_new_index_neg) | \ ((new_index % self.length) & (cond_new_index_neg^0xffffffff)) result = ((self.length & 0xffff) << 16) | (new_index & 0xffff) self.put(result, "a{0}".format(self.data['b']+1)) elif op2 == 0x6: # BO_ST.A_BitRev incr = self.a_b_1 >> 16 self.store(self.a_a, self.ea_0) new_index = reverse16(reverse16(self.index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x16: # BO_ST.A_Circ self.store(self.a_a, self.ea_0) new_index = self.index + self.sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + self.length) & cond_new_index_neg) | \ ((new_index % self.length) & (cond_new_index_neg^0xffffffff)) result = ((self.length & 0xffff) << 16) | (new_index & 0xffff) self.put(result, "a{0}".format(self.data['b']+1)) elif op2 == 0x7: # BO_ST.DA_BitRev incr = self.a_b_1 >> 16 self.store(self.a_a, self.ea_0) self.store(self.a_a_1, self.ea_0+4) new_index = reverse16(reverse16(self.index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x17: # BO_ST.DA_Circ self.store(self.a_a, self.ea_0) self.store(self.a_a_1, self.ea_4) new_index = self.index + self.sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + self.length) & cond_new_index_neg) | \ ((new_index % self.length) & (cond_new_index_neg^0xffffffff)) result = ((self.length & 0xffff) << 16) | (new_index & 0xffff) self.put(result, "a{0}".format(self.data['b']+1)) elif op2 == 0x2: # BO_ST.H_BitRev incr = self.a_b_1 >> 16 self.store(self.d_a & 0xffff, self.ea_0) new_index = reverse16(reverse16(self.index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x12: # BO_ST.H_Circ self.store(self.d_a & 0xffff, self.ea_0) new_index = self.index + self.sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + self.length) & cond_new_index_neg) | \ ((new_index % self.length) & (cond_new_index_neg^0xffffffff)) result = ((self.length & 0xffff) << 16) | (new_index & 0xffff) self.put(result, "a{0}".format(self.data['b']+1)) elif op2 == 0x8: # BO_ST.Q_BitRev incr = self.a_b_1 >> 16 self.store(self.d_a >> 16, self.ea_0) new_index = reverse16(reverse16(self.index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x18: # BO_ST.Q_Circ self.store(self.d_a >> 16, self.ea_0) new_index = self.index + self.sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + self.length) & cond_new_index_neg) | \ ((new_index % self.length) & (cond_new_index_neg^0xffffffff)) result = ((self.length & 0xffff) << 16) | (new_index & 0xffff) self.put(result, "a{0}".format(self.data['b']+1)) elif op2 == 0x4: # BO_ST.W_BitRev incr = self.a_b_1 >> 16 self.store(self.d_a, self.ea_0) new_index = reverse16(reverse16(self.index) + reverse16(incr)) result_2 = ((incr & 0xffff) << 16) | (new_index & 0xffff) self.put(result_2, "a{0}".format(self.data['b']+1)) elif op2 == 0x14: # BO_ST.W_Circ self.store(self.d_a, self.ea_0) new_index = self.index + self.sign_ext_offset cond_new_index_neg = extend_to_32_bits(new_index & 0x80000000 == 0x80000000) new_index = ((new_index + self.length) & cond_new_index_neg) | \ ((new_index % self.length) & (cond_new_index_neg^0xffffffff)) result = ((self.length & 0xffff) << 16) | (new_index & 0xffff) self.put(result, "a{0}".format(self.data['b']+1)) else: print("Error: Unknown OP2 '{0}'!".format(op2)) print("BO instruction OP=A9, OP2=Unknown") sys.exit(1)

[ "noreply@github.com" ]

angr.noreply@github.com

9d2eb5e7101f25c69133388b5298f21e6c156b36

2aace9bb170363e181eb7520e93def25f38dbe5c

/build/idea-sandbox/system/python_stubs/cache/3edeb844795ba685a7cb6811051e176c0111319ceb300f8bdfc98281d9d62383/win32inet.py

f6bb75423847caf8b877cb3111a35d2eae311d40

[]

no_license

qkpqkp/PlagCheck

13cb66fd2b2caa2451690bb72a2634bdaa07f1e6

d229904674a5a6e46738179c7494488ca930045e

refs/heads/master

2023-05-28T15:06:08.723143

2021-06-09T05:36:34

375,235,940

1

0

null

UTF-8

Python

false

3,530

py

# encoding: utf-8 # module win32inet # from C:\Users\Doly\Anaconda3\lib\site-packages\win32\win32inet.pyd # by generator 1.147 # no doc # imports from pywintypes import error # Variables with simple values UNICODE = 1 # functions def CommitUrlCacheEntry(*args, **kwargs): # real signature unknown pass def CreateUrlCacheEntry(*args, **kwargs): # real signature unknown pass def CreateUrlCacheGroup(*args, **kwargs): # real signature unknown pass def DeleteUrlCacheEntry(*args, **kwargs): # real signature unknown pass def DeleteUrlCacheGroup(*args, **kwargs): # real signature unknown pass def FindCloseUrlCache(*args, **kwargs): # real signature unknown pass def FindFirstUrlCacheEntry(*args, **kwargs): # real signature unknown pass def FindFirstUrlCacheEntryEx(*args, **kwargs): # real signature unknown pass def FindFirstUrlCacheGroup(*args, **kwargs): # real signature unknown pass def FindNextUrlCacheEntry(*args, **kwargs): # real signature unknown pass def FindNextUrlCacheEntryEx(*args, **kwargs): # real signature unknown pass def FindNextUrlCacheGroup(*args, **kwargs): # real signature unknown pass def FtpCommand(*args, **kwargs): # real signature unknown pass def FtpOpenFile(*args, **kwargs): # real signature unknown pass def GetUrlCacheEntryInfo(*args, **kwargs): # real signature unknown pass def GetUrlCacheGroupAttribute(*args, **kwargs): # real signature unknown pass def InternetAttemptConnect(*args, **kwargs): # real signature unknown pass def InternetCanonicalizeUrl(*args, **kwargs): # real signature unknown pass def InternetCheckConnection(*args, **kwargs): # real signature unknown pass def InternetCloseHandle(*args, **kwargs): # real signature unknown pass def InternetConnect(*args, **kwargs): # real signature unknown pass def InternetGetCookie(*args, **kwargs): # real signature unknown pass def InternetGetLastResponseInfo(*args, **kwargs): # real signature unknown pass def InternetGoOnline(*args, **kwargs): # real signature unknown pass def InternetOpen(*args, **kwargs): # real signature unknown pass def InternetOpenUrl(*args, **kwargs): # real signature unknown pass def InternetQueryOption(*args, **kwargs): # real signature unknown pass def InternetReadFile(*args, **kwargs): # real signature unknown pass def InternetSetCookie(*args, **kwargs): # real signature unknown pass def InternetSetOption(*args, **kwargs): # real signature unknown pass def InternetWriteFile(*args, **kwargs): # real signature unknown pass def SetUrlCacheEntryGroup(*args, **kwargs): # real signature unknown pass def SetUrlCacheGroupAttribute(*args, **kwargs): # real signature unknown pass def WinHttpGetDefaultProxyConfiguration(*args, **kwargs): # real signature unknown pass def WinHttpGetIEProxyConfigForCurrentUser(*args, **kwargs): # real signature unknown pass def WinHttpGetProxyForUrl(*args, **kwargs): # real signature unknown pass def WinHttpOpen(*args, **kwargs): # real signature unknown pass # no classes # variables with complex values __loader__ = None # (!) real value is '<_frozen_importlib_external.ExtensionFileLoader object at 0x00000214F80354A8>' __spec__ = None # (!) real value is "ModuleSpec(name='win32inet', loader=<_frozen_importlib_external.ExtensionFileLoader object at 0x00000214F80354A8>, origin='C:\\\\Users\\\\Doly\\\\Anaconda3\\\\lib\\\\site-packages\\\\win32\\\\win32inet.pyd')"

[ "qinkunpeng2015@163.com" ]

qinkunpeng2015@163.com

5599fddb1996441c6feec6e05de8788be34929d3

ff811849b246e78df4a4054594e4ff31dc52532a

/interception_efficiency.py

8a0076cb2cc7cdd80d8238778bd85651166a6c95

[]

no_license

zhan3870/git_filtration

8e4bee8f00a435c55ec3d0389c3d8d989433b0a5

4fffcc9b4290955444c42bea9c813b20d595e06c

refs/heads/master

2021-07-23T08:29:00.489477

2017-10-31T06:26:40

null

0

null

UTF-8

Python

false

211

py

# coding: utf-8 # In[ ]: def interception_efficiency(alpha,Ku,N_R): import numpy as np eta_R = (1+N_R)/(2*Ku)*(2*np.log(1+N_R)-1+alpha+(1/(1+N_R))**2*(1-alpha/2)-alpha/2*(1+N_R)**2) return eta_R

[ "zhan3870@umn.edu" ]

zhan3870@umn.edu

92bd2b77c3e3fe6df3bc537ad30e4e44ab32392e

91e23b6db1d756ea0fdfd3d7c77350c839226dbf

/home/migrations/0019_auto_20200524_0053.py

46d7ed3782447d84ef5d43a884c0b92314dbf712

[]

no_license

hasretbicak/Python-Django-Havaliman-TransferSistemi

c02103f0ea9b611351e0f704e922b83b7d43cd1b

7700e5383c62394c1b6b4ab98aa4f2d16faea7b7

refs/heads/master

2022-10-09T13:13:13.047622

2020-05-23T23:12:54

252,548,623

0

null

UTF-8

Python

false

428

py

# Generated by Django 3.0.5 on 2020-05-23 21:53 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('home', '0018_auto_20200524_0035'), ] operations = [ migrations.AlterField( model_name='faq', name='status', field=models.CharField(choices=[('False', 'False'), ('True', 'True')], max_length=10), ), ]

[ "hsrt.bck002@gmail.com" ]

hsrt.bck002@gmail.com

12b427b03bb9491d4cf68afa4d66488fac655eb4

3d1aacb0ce641a1d96cb4a4b1363b0d03bc3f87c

/netbox/virtualization/constants.py

307921e0ea6176e2d2a5e69b705dfdff8fbf7863

[ "Apache-2.0" ]

permissive

MarcelRaschke/netbox

242e30909c8cdcc6cbfb1e5beb7fc29752d5025e

8206e46991498616bd9fdc5f40b57e66067b674a

refs/heads/develop

2023-09-05T18:59:32.540609

2022-08-12T02:26:58

160,838,955

1

Apache-2.0

2023-04-30T00:40:43

2018-12-07T15:08:25

Python

UTF-8

Python

false

466

py

from __future__ import unicode_literals from dcim.constants import DEVICE_STATUS_ACTIVE, DEVICE_STATUS_OFFLINE, DEVICE_STATUS_STAGED # VirtualMachine statuses (replicated from Device statuses) VM_STATUS_CHOICES = [ [DEVICE_STATUS_ACTIVE, 'Active'], [DEVICE_STATUS_OFFLINE, 'Offline'], [DEVICE_STATUS_STAGED, 'Staged'], ] # Bootstrap CSS classes for VirtualMachine statuses VM_STATUS_CLASSES = { 0: 'warning', 1: 'success', 3: 'primary', }

[ "jstretch@digitalocean.com" ]

jstretch@digitalocean.com

d5011dbad6c73ea2ce5cdc2afc4b6923897018b1

2dbccf2272e391c9c177478881a474ba84f80eac

/example/data_pb2_grpc.py

3677703a5790f6104a1bf68c86207ad8dc6baeb9

[]

no_license

killer933/grpc_python

703725b212f5ffccabf77d9e2ec87eec9b55f196

27d91b6b358ca0d3ad760d09aa77688632d849eb

refs/heads/master

2020-06-17T12:39:58.542032

2019-07-09T03:44:36

195,927,231

0

null

UTF-8

Python

false

1,466

py

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! import grpc import sys sys.path.append('C:/Users/Administrator/PycharmProjects/testkeras') from example import data_pb2 as data__pb2 class GreeterStub(object): # missing associated documentation comment in .proto file pass def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.SayHello = channel.unary_unary( '/example.Greeter/SayHello', request_serializer=data__pb2.HelloRequest.SerializeToString, response_deserializer=data__pb2.HelloReply.FromString, ) class GreeterServicer(object): # missing associated documentation comment in .proto file pass def SayHello(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_GreeterServicer_to_server(servicer, server): rpc_method_handlers = { 'SayHello': grpc.unary_unary_rpc_method_handler( servicer.SayHello, request_deserializer=data__pb2.HelloRequest.FromString, response_serializer=data__pb2.HelloReply.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'example.Greeter', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,))

[ "china.sunzhi@gmail.com" ]

china.sunzhi@gmail.com

8e78c55ebf8c6ff4d594d23acba62782228ce564

b8cb10a3c99961f44ac758b3683523627d032680

/runoschool/runo/migrations/0016_auto_20201022_2208.py

7895a86854c2633520c818682c2444f93ede56d4

[]

no_license

samuelatuma1/runoschool

4a2183be4a7e856723fc5368c90edcb79d6ed29e

ed75fb4077cf5ff86b7d546d3346fc4625bee97e

refs/heads/master

2023-01-29T20:22:25.160805

2020-12-14T08:33:13

312,167,155

1

0

null

UTF-8

Python

false

783

py

# Generated by Django 3.1.1 on 2020-10-22 21:08 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('runo', '0015_auto_20201022_1707'), ] operations = [ migrations.AddField( model_name='welcometab', name='img1L', field=models.OneToOneField(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='welcLead', to='runo.welcleaders'), ), migrations.AddField( model_name='welcometab2', name='img2L', field=models.OneToOneField(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='welcLead2', to='runo.welcleaders'), ), ]

[ "atumasaake@gmail.com" ]

atumasaake@gmail.com

0e7053df72c502c35c80129ff5ba7ca61f4884f4

ea0bcd33f1bb1fa9fde281508c5446fa07cf0c27

/real_estate/migrations/0010_auto_20201228_1250.py

6cd099028d08a5ba450258e9c8bb1fad84fc64f2

[]

no_license

Pranali2510/Real_Estate

1acf0d56dc7a0e7b3cc11f3a54d909a8f51f28c5

65b3167abf14243a75bb5bc306bd290a65d5f558

refs/heads/master

2023-04-07T16:35:47.141109

2021-04-08T12:10:04

355,891,277

0

null

UTF-8

Python

false

431

py

# Generated by Django 3.0.7 on 2020-12-28 07:20 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('real_estate', '0009_auto_20201227_1814'), ] operations = [ migrations.AlterField( model_name='agent', name='a_image', field=models.FileField(blank=True, default='', null=True, upload_to='images/'), ), ]

[ "pranalimahajan2510@gmail.com" ]

pranalimahajan2510@gmail.com

91d6a853e70ce8e64013e96c27438efa6310f2a0

88ae8695987ada722184307301e221e1ba3cc2fa

/third_party/grpc/src/tools/codegen/core/gen_stats_data.py

85e22146f76ff03b993c5760ec1a582e6e86e0c8

[ "BSD-3-Clause", "MPL-2.0", "Apache-2.0", "LGPL-2.0-or-later", "MIT", "GPL-1.0-or-later" ]

permissive

iridium-browser/iridium-browser

71d9c5ff76e014e6900b825f67389ab0ccd01329

5ee297f53dc7f8e70183031cff62f37b0f19d25f

refs/heads/master

2023-08-03T16:44:16.844552

2023-07-20T15:17:00

2023-07-23T16:09:30

220,016,632

341

40

BSD-3-Clause

2021-08-13T13:54:45

2019-11-06T14:32:31

null

UTF-8

Python

false

18,146

py

#!/usr/bin/env python3 # Copyright 2017 gRPC 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. from __future__ import print_function import collections import ctypes import json import math import sys import yaml with open('src/core/lib/debug/stats_data.yaml') as f: attrs = yaml.load(f.read(), Loader=yaml.Loader) REQUIRED_FIELDS = ['name', 'doc'] def make_type(name, fields): return (collections.namedtuple( name, ' '.join(list(set(REQUIRED_FIELDS + fields)))), []) def c_str(s, encoding='ascii'): if isinstance(s, str): s = s.encode(encoding) result = '' for c in s: c = chr(c) if isinstance(c, int) else c if not (32 <= ord(c) < 127) or c in ('\\', '"'): result += '\\%03o' % ord(c) else: result += c return '"' + result + '"' types = ( make_type('Counter', []), make_type('Histogram', ['max', 'buckets']), ) Shape = collections.namedtuple('Shape', 'max buckets') inst_map = dict((t[0].__name__, t[1]) for t in types) stats = [] for attr in attrs: found = False for t, lst in types: t_name = t.__name__.lower() if t_name in attr: name = attr[t_name] del attr[t_name] lst.append(t(name=name, **attr)) found = True break assert found, "Bad decl: %s" % attr def dbl2u64(d): return ctypes.c_ulonglong.from_buffer(ctypes.c_double(d)).value def u642dbl(d): return ctypes.c_double.from_buffer(ctypes.c_ulonglong(d)).value def shift_works_until(mapped_bounds, shift_bits): for i, ab in enumerate(zip(mapped_bounds, mapped_bounds[1:])): a, b = ab if (a >> shift_bits) == (b >> shift_bits): return i return len(mapped_bounds) def find_ideal_shift(mapped_bounds, max_size): best = None for shift_bits in reversed(list(range(0, 64))): n = shift_works_until(mapped_bounds, shift_bits) if n == 0: continue table_size = mapped_bounds[n - 1] >> shift_bits if table_size > max_size: continue if best is None: best = (shift_bits, n, table_size) elif best[1] < n: best = (shift_bits, n, table_size) return best def gen_map_table(mapped_bounds, shift_data): #print("gen_map_table(%s, %s)" % (mapped_bounds, shift_data)) tbl = [] cur = 0 mapped_bounds = [x >> shift_data[0] for x in mapped_bounds] for i in range(0, mapped_bounds[shift_data[1] - 1]): while i > mapped_bounds[cur]: cur += 1 tbl.append(cur) return tbl static_tables = [] def decl_static_table(values, type): global static_tables v = (type, values) for i, vp in enumerate(static_tables): if v == vp: return i r = len(static_tables) static_tables.append(v) return r def type_for_uint_table(table): mv = max(table) if mv < 2**8: return 'uint8_t' elif mv < 2**16: return 'uint16_t' elif mv < 2**32: return 'uint32_t' else: return 'uint64_t' def merge_cases(cases): l = len(cases) if l == 1: return cases[0][1] left_len = l // 2 left = cases[0:left_len] right = cases[left_len:] return 'if (value < %d) {\n%s\n} else {\n%s\n}' % ( left[-1][0], merge_cases(left), merge_cases(right)) def gen_bucket_code(shape): bounds = [0, 1] done_trivial = False done_unmapped = False first_nontrivial = None first_unmapped = None while len(bounds) < shape.buckets + 1: if len(bounds) == shape.buckets: nextb = int(shape.max) else: mul = math.pow( float(shape.max) / bounds[-1], 1.0 / (shape.buckets + 1 - len(bounds))) nextb = int(math.ceil(bounds[-1] * mul)) if nextb <= bounds[-1] + 1: nextb = bounds[-1] + 1 elif not done_trivial: done_trivial = True first_nontrivial = len(bounds) bounds.append(nextb) bounds_idx = decl_static_table(bounds, 'int') #print first_nontrivial, shift_data, bounds #if shift_data is not None: print [hex(x >> shift_data[0]) for x in code_bounds[first_nontrivial:]] if first_nontrivial is None: return ('return grpc_core::Clamp(value, 0, %d);\n' % shape.max, bounds_idx) cases = [(0, 'return 0;'), (first_nontrivial, 'return value;')] if done_trivial: first_nontrivial_code = dbl2u64(first_nontrivial) last_code = first_nontrivial_code while True: code = '' first_nontrivial = u642dbl(first_nontrivial_code) code_bounds_index = None for i, b in enumerate(bounds): if b > first_nontrivial: code_bounds_index = i break code_bounds = [dbl2u64(x) - first_nontrivial_code for x in bounds] shift_data = find_ideal_shift(code_bounds[code_bounds_index:], 65536) if not shift_data: break map_table = gen_map_table(code_bounds[code_bounds_index:], shift_data) if not map_table: break if map_table[-1] < 5: break map_table_idx = decl_static_table( [x + code_bounds_index for x in map_table], type_for_uint_table(map_table)) last_code = ( (len(map_table) - 1) << shift_data[0]) + first_nontrivial_code code += 'DblUint val;\n' code += 'val.dbl = value;\n' code += 'const int bucket = ' code += 'kStatsTable%d[((val.uint - %dull) >> %d)];\n' % ( map_table_idx, first_nontrivial_code, shift_data[0]) code += 'return bucket - (value < kStatsTable%d[bucket]);' % bounds_idx cases.append((int(u642dbl(last_code)) + 1, code)) first_nontrivial_code = last_code last = u642dbl(last_code) + 1 for i, b in enumerate(bounds[:-2]): if bounds[i + 1] < last: continue cases.append((bounds[i + 1], 'return %d;' % i)) cases.append((None, 'return %d;' % (len(bounds) - 2))) return (merge_cases(cases), bounds_idx) # utility: print a big comment block into a set of files def put_banner(files, banner): for f in files: for line in banner: print('// %s' % line, file=f) print(file=f) shapes = set() for histogram in inst_map['Histogram']: shapes.add(Shape(max=histogram.max, buckets=histogram.buckets)) def snake_to_pascal(name): return ''.join([x.capitalize() for x in name.split('_')]) with open('src/core/lib/debug/stats_data.h', 'w') as H: # copy-paste copyright notice from this file with open(sys.argv[0]) as my_source: copyright = [] for line in my_source: if line[0] != '#': break for line in my_source: if line[0] == '#': copyright.append(line) break for line in my_source: if line[0] != '#': break copyright.append(line) put_banner([H], [line[2:].rstrip() for line in copyright]) put_banner( [H], ["Automatically generated by tools/codegen/core/gen_stats_data.py"]) print("#ifndef GRPC_SRC_CORE_LIB_DEBUG_STATS_DATA_H", file=H) print("#define GRPC_SRC_CORE_LIB_DEBUG_STATS_DATA_H", file=H) print(file=H) print("#include <grpc/support/port_platform.h>", file=H) print("#include <atomic>", file=H) print("#include <memory>", file=H) print("#include <stdint.h>", file=H) print("#include \"src/core/lib/debug/histogram_view.h\"", file=H) print("#include \"absl/strings/string_view.h\"", file=H) print("#include \"src/core/lib/gprpp/per_cpu.h\"", file=H) print(file=H) print("namespace grpc_core {", file=H) for shape in shapes: print("class HistogramCollector_%d_%d;" % (shape.max, shape.buckets), file=H) print("class Histogram_%d_%d {" % (shape.max, shape.buckets), file=H) print(" public:", file=H) print(" static int BucketFor(int value);", file=H) print(" const uint64_t* buckets() const { return buckets_; }", file=H) print( " friend Histogram_%d_%d operator-(const Histogram_%d_%d& left, const Histogram_%d_%d& right);" % (shape.max, shape.buckets, shape.max, shape.buckets, shape.max, shape.buckets), file=H) print(" private:", file=H) print(" friend class HistogramCollector_%d_%d;" % (shape.max, shape.buckets), file=H) print(" uint64_t buckets_[%d]{};" % shape.buckets, file=H) print("};", file=H) print("class HistogramCollector_%d_%d {" % (shape.max, shape.buckets), file=H) print(" public:", file=H) print(" void Increment(int value) {", file=H) print(" buckets_[Histogram_%d_%d::BucketFor(value)]" % (shape.max, shape.buckets), file=H) print(" .fetch_add(1, std::memory_order_relaxed);", file=H) print(" }", file=H) print(" void Collect(Histogram_%d_%d* result) const;" % (shape.max, shape.buckets), file=H) print(" private:", file=H) print(" std::atomic<uint64_t> buckets_[%d]{};" % shape.buckets, file=H) print("};", file=H) print("struct GlobalStats {", file=H) print(" enum class Counter {", file=H) for ctr in inst_map['Counter']: print(" k%s," % snake_to_pascal(ctr.name), file=H) print(" COUNT", file=H) print(" };", file=H) print(" enum class Histogram {", file=H) for ctr in inst_map['Histogram']: print(" k%s," % snake_to_pascal(ctr.name), file=H) print(" COUNT", file=H) print(" };", file=H) print(" GlobalStats();", file=H) print( " static const absl::string_view counter_name[static_cast<int>(Counter::COUNT)];", file=H) print( " static const absl::string_view histogram_name[static_cast<int>(Histogram::COUNT)];", file=H) print( " static const absl::string_view counter_doc[static_cast<int>(Counter::COUNT)];", file=H) print( " static const absl::string_view histogram_doc[static_cast<int>(Histogram::COUNT)];", file=H) print(" union {", file=H) print(" struct {", file=H) for ctr in inst_map['Counter']: print(" uint64_t %s;" % ctr.name, file=H) print(" };", file=H) print(" uint64_t counters[static_cast<int>(Counter::COUNT)];", file=H) print(" };", file=H) for ctr in inst_map['Histogram']: print(" Histogram_%d_%d %s;" % (ctr.max, ctr.buckets, ctr.name), file=H) print(" HistogramView histogram(Histogram which) const;", file=H) print( " std::unique_ptr<GlobalStats> Diff(const GlobalStats& other) const;", file=H) print("};", file=H) print("class GlobalStatsCollector {", file=H) print(" public:", file=H) print(" std::unique_ptr<GlobalStats> Collect() const;", file=H) for ctr in inst_map['Counter']: print( " void Increment%s() { data_.this_cpu().%s.fetch_add(1, std::memory_order_relaxed); }" % (snake_to_pascal(ctr.name), ctr.name), file=H) for ctr in inst_map['Histogram']: print( " void Increment%s(int value) { data_.this_cpu().%s.Increment(value); }" % (snake_to_pascal(ctr.name), ctr.name), file=H) print(" private:", file=H) print(" struct Data {", file=H) for ctr in inst_map['Counter']: print(" std::atomic<uint64_t> %s{0};" % ctr.name, file=H) for ctr in inst_map['Histogram']: print(" HistogramCollector_%d_%d %s;" % (ctr.max, ctr.buckets, ctr.name), file=H) print(" };", file=H) print(" PerCpu<Data> data_;", file=H) print("};", file=H) print("}", file=H) print(file=H) print("#endif // GRPC_SRC_CORE_LIB_DEBUG_STATS_DATA_H", file=H) with open('src/core/lib/debug/stats_data.cc', 'w') as C: # copy-paste copyright notice from this file with open(sys.argv[0]) as my_source: copyright = [] for line in my_source: if line[0] != '#': break for line in my_source: if line[0] == '#': copyright.append(line) break for line in my_source: if line[0] != '#': break copyright.append(line) put_banner([C], [line[2:].rstrip() for line in copyright]) put_banner( [C], ["Automatically generated by tools/codegen/core/gen_stats_data.py"]) print("#include <grpc/support/port_platform.h>", file=C) print(file=C) print("#include \"src/core/lib/debug/stats_data.h\"", file=C) print("#include <stdint.h>", file=C) print(file=C) histo_code = [] histo_bucket_boundaries = {} for shape in shapes: code, bounds_idx = gen_bucket_code(shape) histo_bucket_boundaries[shape] = bounds_idx histo_code.append(code) print("namespace grpc_core {", file=C) print("namespace { union DblUint { double dbl; uint64_t uint; }; }", file=C) for shape in shapes: print( "void HistogramCollector_%d_%d::Collect(Histogram_%d_%d* result) const {" % (shape.max, shape.buckets, shape.max, shape.buckets), file=C) print(" for (int i=0; i<%d; i++) {" % shape.buckets, file=C) print( " result->buckets_[i] += buckets_[i].load(std::memory_order_relaxed);", file=C) print(" }", file=C) print("}", file=C) print( "Histogram_%d_%d operator-(const Histogram_%d_%d& left, const Histogram_%d_%d& right) {" % (shape.max, shape.buckets, shape.max, shape.buckets, shape.max, shape.buckets), file=C) print(" Histogram_%d_%d result;" % (shape.max, shape.buckets), file=C) print(" for (int i=0; i<%d; i++) {" % shape.buckets, file=C) print(" result.buckets_[i] = left.buckets_[i] - right.buckets_[i];", file=C) print(" }", file=C) print(" return result;", file=C) print("}", file=C) for typename, instances in sorted(inst_map.items()): print( "const absl::string_view GlobalStats::%s_name[static_cast<int>(%s::COUNT)] = {" % (typename.lower(), typename), file=C) for inst in instances: print(" %s," % c_str(inst.name), file=C) print("};", file=C) print( "const absl::string_view GlobalStats::%s_doc[static_cast<int>(%s::COUNT)] = {" % (typename.lower(), typename), file=C) for inst in instances: print(" %s," % c_str(inst.doc), file=C) print("};", file=C) print("namespace {", file=C) for i, tbl in enumerate(static_tables): print("const %s kStatsTable%d[%d] = {%s};" % (tbl[0], i, len(tbl[1]), ','.join('%s' % x for x in tbl[1])), file=C) print("} // namespace", file=C) for shape, code in zip(shapes, histo_code): print(("int Histogram_%d_%d::BucketFor(int value) {%s}") % (shape.max, shape.buckets, code), file=C) print("GlobalStats::GlobalStats() : %s {}" % ",".join("%s{0}" % ctr.name for ctr in inst_map['Counter']), file=C) print("HistogramView GlobalStats::histogram(Histogram which) const {", file=C) print(" switch (which) {", file=C) print(" default: GPR_UNREACHABLE_CODE(return HistogramView());", file=C) for inst in inst_map['Histogram']: print(" case Histogram::k%s:" % snake_to_pascal(inst.name), file=C) print( " return HistogramView{&Histogram_%d_%d::BucketFor, kStatsTable%d, %d, %s.buckets()};" % (inst.max, inst.buckets, histo_bucket_boundaries[Shape( inst.max, inst.buckets)], inst.buckets, inst.name), file=C) print(" }", file=C) print("}", file=C) print( "std::unique_ptr<GlobalStats> GlobalStatsCollector::Collect() const {", file=C) print(" auto result = std::make_unique<GlobalStats>();", file=C) print(" for (const auto& data : data_) {", file=C) for ctr in inst_map['Counter']: print(" result->%s += data.%s.load(std::memory_order_relaxed);" % (ctr.name, ctr.name), file=C) for h in inst_map['Histogram']: print(" data.%s.Collect(&result->%s);" % (h.name, h.name), file=C) print(" }", file=C) print(" return result;", file=C) print("}", file=C) print( "std::unique_ptr<GlobalStats> GlobalStats::Diff(const GlobalStats& other) const {", file=C) print(" auto result = std::make_unique<GlobalStats>();", file=C) for ctr in inst_map['Counter']: print(" result->%s = %s - other.%s;" % (ctr.name, ctr.name, ctr.name), file=C) for h in inst_map['Histogram']: print(" result->%s = %s - other.%s;" % (h.name, h.name, h.name), file=C) print(" return result;", file=C) print("}", file=C) print("}", file=C)

[ "jengelh@inai.de" ]

jengelh@inai.de

75c9694b5b9779f317f22559caee48de01e93160

501ceb6d503b749fa6cb86961fdc825a516a7c22

/heroes4Hire/urls.py

c46411081e0ef7e7f1e3a39c2c9cb74c466b552e

[]

no_license

prasanthkp89/Heroes4Hire

07de9d7542e9aa18f3a8fe06d8ade2414d0f3a9b

689128ccb8328c08e113466cf7b2a5ce18f4d08b

refs/heads/master

2021-06-11T14:20:32.081560

2017-02-14T07:52:28

null

0

null

UTF-8

Python

false

1,309

py

"""heroes4Hire URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.10/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.conf.urls import url, include 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls')) """ from django.conf.urls import url, include from django.contrib import admin from django.conf.urls.static import static from django.conf import settings from heroes import views as heroes_views urlpatterns = [ url('^accounts/profile/$', heroes_views.profile, name='profile'), url('^accounts/', include('django.contrib.auth.urls')), url(r'^admin/', admin.site.urls), url(r'^heroes/', include('heroes.urls', namespace='heroes')), url(r'^training/', include('training.urls', namespace='trainings')), url(r'^missions/', include('missions.urls', namespace='missions')), ] + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

[ "wmmufunde@yahoocom" ]

wmmufunde@yahoocom

420c886aade9e0be50a6e79d828ce906825b4ff5

549188abd5cf84ab4ec24445184ac76b2e54eec4

/circle_magic.py

91f5c26dced00a4073b14d8159f05bed1a72455f

[]

no_license

BuakawRed/Circles_Are_Magical

970bfa1eadb6bb94ddd2935a98eb9fcc82b7e40c

084bbe71278241cb19ef4910664d3ff0ca1b3de3

refs/heads/master

2020-04-21T18:32:38.143237

2019-04-03T05:54:30

169,773,648

0

null

UTF-8

Python

false

293

py

import numpy as np import math def Pi_tester(N): x=np.random.uniform(-1,1, N) y=np.random.uniform(-1,1, N) sum_sqr=x*x+y*y a=[] for val in sum_sqr: if math.sqrt(val)<=1: a.append(val) M=len(a) return (M/N)*4 print(Pi_tester(999))

[ "noreply@github.com" ]

BuakawRed.noreply@github.com

ef8cfc42b48088eae6cdd117fce499e597517b00

7e12fef37575c7a3bfc352a30c8937b7dcdf590a

/mysite/myapp/migrations/0008_auto_20190215_1306.py

a0cd0f8ff402432709d6edbfe722d5074efb0dcc

[]

no_license

shree7796/webapp

37945a29a41d03a3c406635fc60bb484423d3a0d

42a8294f5448ff41fe47810b6593a215a27a7786

refs/heads/master

2021-06-11T22:47:48.287237

2021-04-18T14:19:15

179,231,439

1

0

null

2021-04-16T16:14:53

2019-04-03T07:09:46

JavaScript

UTF-8

Python

false

2,813

py

# Generated by Django 2.0.10 on 2019-02-15 07:36 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('myapp', '0007_auto_20190215_1302'), ] operations = [ migrations.AlterField( model_name='personaleducationdetails', name='year_of_graduation', field=models.DateField(choices=[(1970, 1970), (1971, 1971), (1972, 1972), (1973, 1973), (1974, 1974), (1975, 1975), (1976, 1976), (1977, 1977), (1978, 1978), (1979, 1979), (1980, 1980), (1981, 1981), (1982, 1982), (1983, 1983), (1984, 1984), (1985, 1985), (1986, 1986), (1987, 1987), (1988, 1988), (1989, 1989), (1990, 1990), (1991, 1991), (1992, 1992), (1993, 1993), (1994, 1994), (1995, 1995), (1996, 1996), (1997, 1997), (1998, 1998), (1999, 1999), (2000, 2000), (2001, 2001), (2002, 2002), (2003, 2003), (2004, 2004), (2005, 2005), (2006, 2006), (2007, 2007), (2008, 2008), (2009, 2009), (2010, 2010), (2011, 2011), (2012, 2012), (2013, 2013), (2014, 2014), (2015, 2015), (2016, 2016), (2017, 2017)], null=True), ), migrations.AlterField( model_name='personaleducationdetails', name='year_passing_10th', field=models.DateField(choices=[(1970, 1970), (1971, 1971), (1972, 1972), (1973, 1973), (1974, 1974), (1975, 1975), (1976, 1976), (1977, 1977), (1978, 1978), (1979, 1979), (1980, 1980), (1981, 1981), (1982, 1982), (1983, 1983), (1984, 1984), (1985, 1985), (1986, 1986), (1987, 1987), (1988, 1988), (1989, 1989), (1990, 1990), (1991, 1991), (1992, 1992), (1993, 1993), (1994, 1994), (1995, 1995), (1996, 1996), (1997, 1997), (1998, 1998), (1999, 1999), (2000, 2000), (2001, 2001), (2002, 2002), (2003, 2003), (2004, 2004), (2005, 2005), (2006, 2006), (2007, 2007), (2008, 2008), (2009, 2009), (2010, 2010), (2011, 2011), (2012, 2012), (2013, 2013), (2014, 2014), (2015, 2015), (2016, 2016), (2017, 2017)], null=True), ), migrations.AlterField( model_name='personaleducationdetails', name='year_passing_12th', field=models.DateField(choices=[(1970, 1970), (1971, 1971), (1972, 1972), (1973, 1973), (1974, 1974), (1975, 1975), (1976, 1976), (1977, 1977), (1978, 1978), (1979, 1979), (1980, 1980), (1981, 1981), (1982, 1982), (1983, 1983), (1984, 1984), (1985, 1985), (1986, 1986), (1987, 1987), (1988, 1988), (1989, 1989), (1990, 1990), (1991, 1991), (1992, 1992), (1993, 1993), (1994, 1994), (1995, 1995), (1996, 1996), (1997, 1997), (1998, 1998), (1999, 1999), (2000, 2000), (2001, 2001), (2002, 2002), (2003, 2003), (2004, 2004), (2005, 2005), (2006, 2006), (2007, 2007), (2008, 2008), (2009, 2009), (2010, 2010), (2011, 2011), (2012, 2012), (2013, 2013), (2014, 2014), (2015, 2015), (2016, 2016), (2017, 2017)], null=True), ), ]

[ "shivamshrivastava470@gmail.com" ]

shivamshrivastava470@gmail.com

01659e7f6238a105a77b183b7982dfceadda8e86

761c39ed62047c0f2fc6675b17e7477cc635741e

/com/test/ConnectSqlite.py

b8d948587bf090cc6e7d29766fd7d7c45c299458

[]

no_license

open-pythons/lottedfs

e48d9a121a9a1158067c6351fcf35d98575f3574

a17422231802503527ee4f31a90da0ae3878718e

refs/heads/master

2022-03-16T20:54:10.205219

2019-11-08T15:53:56

220,019,179

1

0

null

UTF-8

Python

false

5,839

py

#!/usr/bin/env python # encoding: utf-8 """ @version: v1.0 @author: W_H_J @license: Apache Licence @contact: 415900617@qq.com @software: PyCharm @file: SQLite3Config.py @time: 2019/5/17 14:22 @describe: sqllit3 操作助手 """ import sys import os import sqlite3 sys.path.append(os.path.abspath(os.path.dirname(__file__) + '/' + '..')) sys.path.append("..") class ConnectSqlite: def __init__(self, dbName="./sqlite3Test.db"): """ 初始化连接--使用完记得关闭连接 :param dbName: 连接库名字，注意，以'.db'结尾 """ self._conn = sqlite3.connect(dbName) self._cur = self._conn.cursor() self._time_now = "[" + sqlite3.datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S') + "]" def close_con(self): """ 关闭连接对象--主动调用 :return: """ self._cur.close() self._conn.close() def create_tabel(self, sql): """ 创建表初始化 :param sql: 建表语句 :return: True is ok """ try: self._cur.execute(sql) self._conn.commit() return True except Exception as e: print(self._time_now, "[CREATE TABLE ERROR]", e) return False def drop_table(self, table_name): """ 删除表 :param table_name: 表名 :return: """ try: self._cur.execute('DROP TABLE {0}'.format(table_name)) self._conn.commit() return True except Exception as e: print(self._time_now, "[DROP TABLE ERROR]", e) return False def delete_table(self, sql): """ 删除表记录 :param sql: :return: True or False """ try: if 'DELETE' in sql.upper(): self._cur.execute(sql) self._conn.commit() return True else: print(self._time_now, "[EXECUTE SQL IS NOT DELETE]") return False except Exception as e: print(self._time_now, "[DELETE TABLE ERROR]", e) return False def fetchall_table(self, sql, limit_flag=True): """ 查询所有数据 :param sql: :param limit_flag: 查询条数选择，False 查询一条，True 全部查询 :return: """ try: self._cur.execute(sql) war_msg = self._time_now + ' The [{}] is empty or equal None!'.format(sql) if limit_flag is True: r = self._cur.fetchall() return r if len(r) > 0 else war_msg elif limit_flag is False: r = self._cur.fetchone() return r if len(r) > 0 else war_msg except Exception as e: print(self._time_now, "[SELECT TABLE ERROR]", e) def insert_update_table(self, sql): """ 插入/更新表记录 :param sql: :return: """ try: self._cur.execute(sql) self._conn.commit() return True except Exception as e: print(self._time_now, "[INSERT/UPDATE TABLE ERROR]", e) return False def insert_table_many(self, sql, value): """ 插入多条记录 :param sql: :param value: list:[(),()] :return: """ try: self._cur.executemany(sql, value) self._conn.commit() return True except Exception as e: print(self._time_now, "[INSERT MANY TABLE ERROR]", e) return False class conTest: """测试类""" def __init__(self): self.con = ConnectSqlite("./sqlite3Test.db") def create_table_test(self): sql = '''CREATE TABLE `mytest` ( `id` DATETIME DEFAULT NULL, `user` VARCHAR(12) DEFAULT NULL, `name` VARCHAR(12) DEFAULT NULL, `number` VARCHAR(12) DEFAULT NULL )''' print(self.con.create_tabel(sql)) def drop_table_test(self): print(self.con.drop_table("mytest")) def fetchall_table_test(self): sql = "SELECT * from mytest WHERE user='1003';" sql_all = "SELECT * from mytest;" print("全部记录", self.con.fetchall_table(sql_all)) print("单条记录", self.con.fetchall_table(sql_all, False)) print("条件查询", self.con.fetchall_table(sql)) def delete_table_test(self): sql = "DELETE FROM mytest WHERE user='1003';" print(self.con.delete_table(sql)) def update_table_test(self): sql_update = "UPDATE mytest SET id={0},user={1},name={2},number={3} WHERE number={4}".format(1, 1002, "'王五'", 1002, 1002) print(self.con.insert_update_table(sql_update)) def insert_table_test_one(self): sql = """INSERT INTO mytest VALUES (3, 1003, "王五", 1003);""" print(self.con.insert_update_table(sql)) def insert_table_test_many(self): sql = """INSERT INTO mytest VALUES (?, ?, ?, ?)""" value = [(2, 1004, "赵六", 1004), (4, 1005, "吴七", 1005)] print(self.con.insert_table_many(sql, value)) def close_con(self): self.con.close_con() if __name__ == '__main__': contest = conTest() contest.create_table_test() contest.insert_table_test_many() contest.fetchall_table_test() contest.insert_table_test_one() contest.fetchall_table_test() contest.update_table_test() contest.drop_table_test() contest.close_con()

[ "longzinziyan@gmail.com" ]

longzinziyan@gmail.com

4dc67dc8f16d162464e5fa5448a7a507a8d151ba

e4b39086d0dd1cda8f97582b263377587aa7383b

/Connect4/connect4/strategy/strategy.py

58bbe980ef1d587229a0289575b0c447e16d2450

[]

no_license

jercanioana/Fundamentals-of-Programming

f88207027e86bf1f1c088fc63992b47e34a50524

2da42da4029401705c6bfa832898266f25c9e41e

refs/heads/master

2022-07-04T09:57:14.903444

2020-05-05T12:22:48

261,451,383

0

null

UTF-8

Python

false

155

py

from abc import abstractmethod from connect4.board.cell import Cell class Strategy: @abstractmethod def move(self, *args) -> Cell: pass

[ "ioana.jercan02@gmail.com" ]

ioana.jercan02@gmail.com

3b2a70bdb3ab23a408a21d4cc1d8bc2d9154cca2

c1125e2835829c6ed0f06d641142fb7b4e179132

/project/simpleLogisticRegression.py

888686ad40bb890089e46f6c67cdc2f0281d5c97

[]

no_license

chien-lung/DataScience_2018

b3b41e9cd9a5deaadd17e8507fcb0b80dd576022

dbb2a6ac9b695aafe6e2b9ba5a892387574b2514

refs/heads/master

2020-04-16T19:55:20.242523

2019-01-17T10:08:44

165,879,051

0

null

UTF-8

Python

false

3,880

py

# -*- coding: utf-8 -*- """ Created on Tue Jan 8 00:03:35 2019 @author: Lung """ import numpy as np import pandas as pd from sklearn.preprocessing import LabelEncoder, OneHotEncoder from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression def deleteWC(wc_data, normal_not_exist_teams): wc_not_data = wc_data.loc[wc_data['team'].isin(normal_not_exist_teams)] wc_use_data = wc_data.loc[~wc_data['gameid'].isin(np.unique(wc_not_data['gameid']))] return wc_use_data filename = '2016 complete match data OraclesElixir 2018-12-18.xlsx' stat_list = ['player','side','team','champion','position'] data = pd.read_excel(filename) normal_data = data.loc[~data['league'].isin(['WC'])] wc_data = data.loc[data['league'].isin(['WC'])] normal_not_exist_teams = set(wc_data['team']).difference(set(normal_data['team']))#['Albus NoX Luna','EDward Gaming','Royal Never Give Up','I MAY'] wc_use_data = deleteWC(wc_data, normal_not_exist_teams) b = np.array(normal_data.loc[normal_data['playerid'].isin([100])]['team']) b_r = np.array(normal_data.loc[normal_data['playerid'].isin([100])]['result']) r = np.array(normal_data.loc[normal_data['playerid'].isin([200])]['team']) r_r = np.array(normal_data.loc[normal_data['playerid'].isin([200])]['result']) team_stat = pd.DataFrame({'B_team':b,'R_team':r}) team_X = pd.get_dummies(team_stat, columns=['B_team','R_team']) team_y = b_r wc_b = np.array(wc_use_data.loc[wc_use_data['playerid'].isin([100])]['team']) wc_b_r = np.array(wc_use_data.loc[wc_use_data['playerid'].isin([100])]['result']) wc_r = np.array(wc_use_data.loc[wc_use_data['playerid'].isin([200])]['team']) wc_r_r = np.array(wc_use_data.loc[wc_use_data['playerid'].isin([200])]['result']) wc_stat = pd.DataFrame({'B_team':wc_b,'R_team':wc_r}) X_test = pd.get_dummies(wc_stat, columns=['B_team','R_team']) y_test = wc_b_r X_train, X_val, y_train, y_val = train_test_split(team_X, team_y, test_size=0.3, random_state=36) logreg = LogisticRegression() logreg.fit(X_train, y_train) score = logreg.score(X_train, y_train) print("Training set accuracy: ", '%.3f'%(score)) score = logreg.score(X_val, y_val) print("Validation set accuracy: ", '%.3f'%(score)) score = logreg.score(X_test, y_test) print("WC set accuracy: ", '%.3f'%(score)) ''' team_stat = pd.DataFrame({'B_team':np.concatenate((b,r)), 'R_team':np.concatenate((r,b))}) team_X = pd.get_dummies(team_stat, columns=['B_team','R_team']) team_y = np.concatenate((b_r,r_r)) X_train, X_val, y_train, y_val = train_test_split(team_X, team_y, test_size=0.3, random_state=36) logreg = LogisticRegression() logreg.fit(X_train, y_train) print("Training set accuracy: ", '%.3f'%(score)) score = logreg.score(X_val, y_val) print("Validation set accuracy: ", '%.3f'%(score)) #score = logreg.score(X_test, y_test) #print("WC set accuracy: ", '%.3f'%(score)) ''' ''' for plrid in range(1,6): plr = data.loc[data['playerid'].isin([plrid, plrid+5])]['player'] plr_arr = np.array(plr) team_stat['player{}'.format(plrid)] = pd.Series(plr_arr, index=team_stat.index) #Team team_X = pd.get_dummies(team_stat) X_train, X_test, y_train, y_test = train_test_split(team_X, team_result, test_size=0.25, random_state=36) logreg = LogisticRegression() logreg.fit(X_train, y_train) score = logreg.score(X_train, y_train) score2 = logreg.score(X_test, y_test) print("Training set accuracy: ", '%.3f'%(score)) print("Test set accuracy: ", '%.3f'%(score2)) #Players plr_X = pd.get_dummies(plr_stat, prefix=stat_list, columns=stat_list) X_train, X_test, y_train, y_test = train_test_split(plr_X, plr_result, test_size=0.3, random_state=1) logreg = LogisticRegression() logreg.fit(X_train, y_train) score = logreg.score(X_train, y_train) score2 = logreg.score(X_test, y_test) print("Training set accuracy: ", '%.3f'%(score)) print("Test set accuracy: ", '%.3f'%(score2)) '''

[ "e125313530@gmail.com" ]

e125313530@gmail.com

0280e212179474e2cef2943f05464f14fa6fb089

e2cb1cc3ebf462300b519bfec5841c326dccb095

/pyscandl/modules/Pyscandl.py

b3e204b69561604583a039eadc9b607c6042296d

[ "BSD-3-Clause" ]

permissive

Annwan/pyscandl

eb9fcd60bca49f277d96ec9968f1e9b57e69b72a

afec7b410699f1bb6289a8653fc7cfa5b0d03406

refs/heads/master

2023-03-14T09:05:36.478222

2021-02-23T18:24:33

344,026,261

0

BSD-3-Clause

2021-03-03T06:32:19

null

UTF-8

Python

false

12,594

py

import contextlib from .excepts import DryNoSauceHere, TooManySauce, EmptyChapter, DelayedRelease from .fetchers.fetcher import StandaloneFetcher from PIL import Image import requests import os from re import sub as re_sub from sys import stderr from wand.image import Image class Pyscandl: """ The main object of the program. It is responsible of the downloads and controls the fetchers for you. """ def __init__(self, fetcher, chapstart=1, output:str=".", pdf:bool=True, keep:bool=False, image:bool=False, all:bool=False, link:str=None, manga:str=None, download_number:int=1, chapend=0, quiet:bool=False, skip:int=0, tiny:bool=False): """ Initialize this instance of the pyscandl downloader, it needs either manga or link to work. :param fetcher: fetcher object related to the download :param chapstart: first chapter to be downloaded :type chapstart: int/float/str :param output: output folder :type output: str :param pdf: tell if the result should be kept as a pdf :type pdf: bool :param keep: tell if the result should be kept as a pdf and as a collection of images :type keep: bool :param image: tell if the result should be kept as a collection of images :type image: bool :param all: download all the chapters that are available after chapstart :type all: bool :param link: link of the manga to download :type link: str :param manga: identification tag of the manga *(see every fetcher for their different variations)* :type manga: str :param download_number: number of chapters to download :type download_number: int :param chapend: chapter to end the download on, if non exstant the download will stop once the next to download chapter number is greater than it :type chapend: int/float/str :param quiet: should the program not output any information about what it is doing in the console :type quiet: bool :param skip: number of images to skip on the first chapter being downloaded *(useful if running in image mode)* :type skip: int :param tiny: should the name of every downloaded scan be minified and only include the chapter number and the chapter title :type tiny: bool :raises DryNoSauceHere: neither link or manga was specified :raises TooManySauce: both link and manga were specified """ if link is not None and manga is None or link is None and manga is not None: if issubclass(fetcher, StandaloneFetcher): self.fetcher = fetcher(link=link, manga=manga) else: self.fetcher = fetcher(link=link, manga=manga, chapstart=chapstart) elif link is None and manga is None: raise DryNoSauceHere else: raise TooManySauce # in case windows is the os, remove the banned characters if os.name == "nt": manga_name = re_sub(r'[\\/*?:"<>|]', u"█", self.fetcher.manga_name) else: manga_name = self.fetcher.manga_name # creating output folder self._output = (output[-1] == "/" and output or output + "/") + manga_name + "/" if not os.path.exists(self._output): os.makedirs(self._output) self._header = {"User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.36", "Set-Cookie": f"domain={self.fetcher.domain}"} self._header.update(self.fetcher.headers) self._nskip = skip self._quiet = quiet # select download mode self._pdf = pdf self._keep = keep self._image = image self._all = all self._download_number = download_number self._chapend = float(chapend) if "." in str(chapend) else int(chapend) self._path = f"{self._output}ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}/" # save path for images self._img_bin_list = [] self._tiny = tiny # in case windows is the os, remove the banned characters if os.name == "nt": chapter_name = re_sub(r'[\\/*?:"<>|]', u"█", self.fetcher.chapter_name) else: chapter_name = self.fetcher.chapter_name if self._tiny: if isinstance(self.fetcher, StandaloneFetcher): self._pdf_path = f"{self._output}{chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.chapter_name}" else: self._pdf_path = f"{self._output}ch.{self.fetcher.chapter_number} {chapter_name}.pdf" self._name_metadata_pdf = f"ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}" else: if isinstance(self.fetcher, StandaloneFetcher): self._pdf_path = f"{self._output}{manga_name} - {chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.manga_name} - {self.fetcher.chapter_name}" else: self._pdf_path = f"{self._output}{manga_name} - ch.{self.fetcher.chapter_number} {chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.manga_name} - ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}" self._banlist = [] ban_path = f"{os.path.dirname(os.path.abspath(__file__))}/../banlist" for img in os.listdir(ban_path): with open(f"{ban_path}/{img}", "rb") as img_bin: self._banlist.append(img_bin.read()) def _dl_image(self): """ Downloads the currently selected image. """ if not os.path.exists(self._path): os.makedirs(self._path) with open(f"{self._path}{self.fetcher.npage}.{self.fetcher.ext}", "wb") as img: img.write(requests.get(self.fetcher.image, headers=self._header).content) if not self._quiet: print(".", end="", flush=True) def full_chapter(self): """ Fetching all the images of the chapter and storing them in RAM. """ if not self._quiet: if isinstance(self.fetcher, StandaloneFetcher): print(f"fetching: {self.fetcher.chapter_name}") else: print(f"fetching: ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}") while not self.fetcher.is_last_image(): self._img_bin_list.append(requests.get(self.fetcher.image, headers=self._header).content) if not self._quiet: print(".", end="", flush=True) self.fetcher.next_image() self._img_bin_list.append(requests.get(self.fetcher.image, headers=self._header).content) if not self._quiet: print(".", end="", flush=True) def keep_full_chapter(self): """ Downloading all the images of the chapters and storing them where the output was specified. """ if not self._quiet: if isinstance(self.fetcher, StandaloneFetcher): print(f"downloading: {self.fetcher.chapter_name}") else: print(f"downloading: ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}") while not self.fetcher.is_last_image(): if self._keep: self._img_bin_list.append(requests.get(self.fetcher.image, headers=self._header).content) self._dl_image() self.fetcher.next_image() if self._keep: self._img_bin_list.append(requests.get(self.fetcher.image, headers=self._header).content) self._dl_image() if not self._quiet and self._image: print("") def _skip(self): """ Skips the images as asked with the skip parameter. """ for loop in range(self._nskip): self.fetcher.next_image() def create_pdf(self): """ Creates the pdf at the output location with the fetched or the downloaded images of the current chapter. :raises EmptyChapter: the images of the current chapter were all blacklisted images and the pdf was empty """ print("Warning: the pdf creation engine will be changed for Wand in the next major release (3.0.0). Please do not forget to install imagemagick at that time", file=stderr) if not self._quiet: print("\nconverting...", end=" ") # loading the downloaded images if keep mode # removing the images found in the banlist self._img_bin_list = [img for img in self._img_bin_list if img not in self._banlist] if len(self._img_bin_list) > 0: # creating the pdf with Image() as pdf: for img_bin in self._img_bin_list: with contextlib.redirect_stderr(None): # to mute alpha channel and ICC warnings as wand processes the image well anyway with Image(blob=img_bin) as img: pdf.sequence.append(img) pdf.save(filename=self._pdf_path) with open(self._pdf_path, "rb") as file: pdf = file.read() with open(self._pdf_path, "wb") as file: file.write(pdf.replace(b"/Producer (https://imagemagick.org)", b"/Producer (https://pypi.org/project/pyscandl/)") .replace( b"/CreationDate", b"/Author <feff"+self.fetcher.author.encode("utf-16_be").hex().encode()+ b">\n/Keywords <feff"+self.fetcher.manga_name.encode("utf-16_be").hex().encode()+b">\n/CreationDate") ) # manually adding the missing metadate from the pdf creation if not self._quiet: print("converted") else: raise EmptyChapter(self.fetcher.manga_name, self.fetcher.chapter_number) def go_to_chapter(self, chap_num): """ Make Pyscandl go to the asked chapter. :param chap_num: chapter number that was asked for :type chap_num: int/str/float """ # in case windows is the os, remove the banned characters if os.name == "nt": chapter_name = re_sub(r'[\\/*?:"<>|]', u"█", self.fetcher.chapter_name) else: chapter_name = self.fetcher.chapter_name self.fetcher.go_to_chapter(chap_num) self._path = f"{self._output}ch.{self.fetcher.chapter_number} {chapter_name}/" self._img_bin_list = [] # prepares the next pdf path and name if self._tiny: if isinstance(self.fetcher, StandaloneFetcher): self._pdf_path = f"{self._output}{chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.chapter_name}" else: self._pdf_path = f"{self._output}ch.{self.fetcher.chapter_number} {chapter_name}.pdf" self._name_metadata_pdf = f"ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}" else: if isinstance(self.fetcher, StandaloneFetcher): self._pdf_path = f"{self._output}{self.fetcher.manga_name} - {chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.manga_name} - {self.fetcher.chapter_name}" else: self._pdf_path = f"{self._output}{self.fetcher.manga_name} - ch.{self.fetcher.chapter_number} {chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.manga_name} - ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}" def next_chapter(self): """ Goes to the next chapter """ self.fetcher.next_chapter() # in case windows is the os, remove the banned characters if os.name == "nt": chapter_name = re_sub(r'[\\/*?:"<>|]', u"█", self.fetcher.chapter_name) else: chapter_name = self.fetcher.chapter_name self._path = f"{self._output}ch.{self.fetcher.chapter_number} {chapter_name}/" self._img_bin_list = [] # prepares the next pdf path and name if self._tiny: if isinstance(self.fetcher, StandaloneFetcher): self._pdf_path = f"{self._output}{chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.chapter_name}" else: self._pdf_path = f"{self._output}ch.{self.fetcher.chapter_number} {chapter_name}.pdf" self._name_metadata_pdf = f"ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}" else: if isinstance(self.fetcher, StandaloneFetcher): self._pdf_path = f"{self._output}{self.fetcher.manga_name} - {chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.manga_name} - {self.fetcher.chapter_name}" else: self._pdf_path = f"{self._output}{self.fetcher.manga_name} - ch.{self.fetcher.chapter_number} {chapter_name}.pdf" self._name_metadata_pdf = f"{self.fetcher.manga_name} - ch.{self.fetcher.chapter_number} {self.fetcher.chapter_name}" def full_download(self): """ Does the full download process with what is specified when initializing the Pyscandl object """ try: # emulating a do while self._skip() counter = 1 try: if self._keep or self._image: self.keep_full_chapter() else: self.full_chapter() if not self._image: try: self.create_pdf() except EmptyChapter: if not self._quiet: print("empty") except DelayedRelease as e: if not self._quiet: print(e) while not isinstance(self.fetcher, StandaloneFetcher) and not self.fetcher.is_last_chapter() and (self._all or counter < self._download_number or float(self.fetcher.chapter_number) < self._chapend): self.next_chapter() try: if self._keep or self._image: self.keep_full_chapter() else: self.full_chapter() if not self._image: try: self.create_pdf() except EmptyChapter: if not self._quiet: print("empty") except DelayedRelease as e: if not self._quiet: print(e) counter += 1 except KeyboardInterrupt: if not self._quiet: print("\nmanual interruption") finally: self.fetcher.quit() if not self._quiet: print("end of the download")

[ "thomas99.montero@gmail.com" ]

thomas99.montero@gmail.com

de75a9910004d2d0ddb1e10339b6493c821b0881

ce814bdc76513d1a03245a292a9b1194a287b152

/CEM/frozen_lake/preprocessing.py

9de50b6eb619024de295666c81a2f5673ddb58ef

[]

no_license

gowtham1997/Reinforcement-Learning-Algorithms

b34678bbdcfee2634beef2a687758337b4fd09d2

44f52d5d6ffbf684c790752966dcf9b1bd4514cf

refs/heads/master

2022-08-14T18:12:51.835771

2019-09-28T14:40:31

160,662,125

0

null

2022-06-21T21:36:16

2018-12-06T11:00:57

Python

UTF-8

Python

false

2,512

py

import torch import numpy as np from collections import namedtuple import gym import torch.nn as nn class DiscrteOneHotWrapper(gym.ObservationWrapper): def __init__(self, env): super().__init__(env) # converting discrete to Box space self.observation_space = gym.spaces.Box(0.0, 1.0, (env.observation_space.n, ), np.float32) def observation(self, obs): # one hot conversion of discrete obs new_obs = np.copy(self.observation_space.low) new_obs[obs] = 1.0 return new_obs def iterate_batches(env, net, batch_size): np.random.seed(12345) obs = env.reset() Episode_Step = namedtuple('Episode_Step', field_names=[ 'observation', 'action']) Episode = namedtuple('Episode', field_names=['reward', 'steps']) episode_steps = [] batch = [] episode_reward = 0.0 softmax = nn.Softmax(dim=1) while True: obs_tensor = torch.FloatTensor([obs]) logits = net(obs_tensor) action_prob_tensor = softmax(logits) action_probs = action_prob_tensor.data.numpy()[0] action = np.random.choice(len(action_probs), p=action_probs) new_obs, reward, is_done, _ = env.step(action) episode_reward += reward episode_steps.append(Episode_Step(obs, action)) if is_done: batch.append(Episode(episode_reward, episode_steps)) new_obs = env.reset() episode_reward = 0.0 episode_steps = [] if len(batch) == batch_size: yield batch batch = [] obs = new_obs # print(action_probs) def filter_batches(batch, percentile, gamma): # discound reward and value episodes which take less steps to win. disc_rewards = list( map(lambda s: s.reward * (gamma ** len(s.steps)), batch)) reward_boundary = np.percentile(disc_rewards, percentile) # store elite examples and pass them on in the next iteration. elite_batch = [] train_obs = [] train_actions = [] for element, disc_reward in zip(batch, disc_rewards): if disc_reward > reward_boundary: train_actions.extend(map(lambda s: s.action, element.steps)) train_obs.extend(map(lambda s: s.observation, element.steps)) elite_batch.append(element) return elite_batch, train_obs, train_actions, reward_boundary

[ "gowtham.ramesh1@gmail.com" ]

gowtham.ramesh1@gmail.com

4e7f38e9a24f9b722097e1408a4fbf5462cce724

9fb581010facc08374cd636b98951dae0f2c0a2d

/kineticmodels/views.py

1abddc074f8e12b5ce97cb79e6db90ce5bcf6090

[]

no_license

bslakman/kineticmodelssite

e4f74378ca3663647b9de9eeeb88af8035279780

0bb3aa9dff2795442d1c451b2b2d2e27742e90c5

refs/heads/master

2020-12-25T13:23:46.677652

2015-10-30T14:00:02

null

0

null

UTF-8

Python

false

269

py

from django.shortcuts import render from django.http import HttpResponse from django.template import RequestContext, loader def index(request): # template=loader.get_template('kineticmodels/index.html') return HttpResponse("This is the kinetic models index!")

[ "david.ma.green@gmail.com" ]

david.ma.green@gmail.com

16a6a02aabedb0b303922512e57ad926b4e9f14d

0bc81c8742e6b7cd4bd3a804ac41cedee637c921

/portalweb/tests/__init__.py

c16c21fb2eadf9f4ff591414edaa544253c1dcfe

[]

no_license

TPAC-MARVL/portal

c7ff9445ea340774aaa1890e2b847001e6564379

b9660d7b771f105360c814e1a861fb16dc036c2b

refs/heads/master

2016-09-16T11:25:25.742221

2014-11-07T04:44:19

null

0

null

UTF-8

Python

false

168

py

from openstackmoduletest import * #from usermanagertest import * #from instancemanagertest import * #from configmanagertest import * #from instanceservicetest import *

[ "fxmzb123@gmail.com" ]

fxmzb123@gmail.com

c53395dc36f9d60f7b1508497f163495d634a4fb

d1667b512038e21045ec35d85e307d85a396dd46

/news/views.py

ba4c7aedbb6e094b83f10e6ab53a8868e1181c5f

[]

no_license

yashmoda/CodeUtsava_HackStrangely_AgricultureServer

556ff334d52cffa87d330b106a0640380e763f11

03b73ce4c8d9cb712ed2e061746768d4df0991e5

refs/heads/master

2021-05-16T16:46:30.949722

2018-02-21T09:45:47

120,063,987

1

0

null

UTF-8

Python

false

1,693

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.http.response import JsonResponse from django.shortcuts import render import urllib2 # Create your views here. import keys def show_news(request): response_json = {keys.NEWS: []} try: if request.method == 'GET': news_url = 'http://eventregistry.org/json/article?query=%7B%22%24query%22%3A%7B%22%24and%22%3A%5B%7B%22conceptUri%22%3A%7B%22%24and%22%3A%5B%22http%3A%2F%2Fen.wikipedia.org%2Fwiki%2FAgriculture%22%5D%7D%7D%2C%7B%22categoryUri%22%3A%7B%22%24and%22%3A%5B%22dmoz%2FBusiness%2FAgriculture_and_Forestry%2FField_Crops%22%2C%22dmoz%2FScience%2FAgriculture%22%5D%7D%7D%2C%7B%22%24or%22%3A%5B%7B%22sourceUri%22%3A%22timesofindia.indiatimes.com%22%7D%2C%7B%22sourceUri%22%3A%22thehindu.com%22%7D%2C%7B%22sourceUri%22%3A%22bhaskar.com%22%7D%2C%7B%22sourceUri%22%3A%22economictimes.indiatimes.com%22%7D%2C%7B%22sourceUri%22%3A%22indianexpress.com%22%7D%2C%7B%22sourceUri%22%3A%22in.reuters.com%22%7D%2C%7B%22sourceUri%22%3A%22dnaindia.com%22%7D%5D%7D%2C%7B%22lang%22%3A%22eng%22%7D%5D%7D%7D&action=getArticles&resultType=articles&articlesSortBy=rel&articlesCount=10&articlesArticleBodyLen=-1&apiKey=1d149793-9d64-4ebe-bd70-9d82cc8126aa&callback=JSON_CALLBACK' response_json[keys.NEWS] = urllib2.urlopen(news_url).read() response_json[keys.SUCCESS] = True response_json[keys.MESSAGE] = "All news shown." return JsonResponse(response_json) except Exception as e: print(str(e)) response_json[keys.SUCCESS] = False response_json[keys.MESSAGE] = "Please try again later." return JsonResponse(response_json)

[ "yashmoda07@gmail.com" ]

yashmoda07@gmail.com

9ea39910d1888a5c1b4e29019173a17c18c082ce

19f96fdd86f1a29f4eec3d18d9e513865f1f512f

/webWork_backup/webflask/test_py3/lib/python3.5/weakref.py

318c642b1c2955967e39c3fcdbb4b83861e7c44a

[]

no_license

Cattmonkey/openWork

e133376eeea3bbf5279f9199b18aa8cf44f21637

3e1f21f0c6bce7ec114cc8d6311746c4a2cc426b

refs/heads/master

2020-03-14T00:58:41.610424

2018-05-04T09:59:03

131,368,011

0

null

UTF-8

Python

false

40

py

/root/anaconda3/lib/python3.5/weakref.py

[ "yyxdyx01@163.com" ]

yyxdyx01@163.com

0358b4f0bbab7000ade46e616a5d61fd12016333

823e659ad9aad1a0717cecfdd6f8c3eab4310fd1

/to_do_list/todo_router.py

0aaa26e31be6b99be20c84ad6d54243d5cf0ba48

[]

no_license

gaoqingloon/best_wishes

e3d708264d58da52239fc3ebd18c4678a7a1e253

cc0ffd49b96b98edfd706ddcaf1f6529a7afb443

refs/heads/main

2023-03-22T04:25:50.496289

2021-03-13T04:33:59

332,776,305

0

1

null

UTF-8

Python

false

1,429

py

from utils.valid_util import module_select def todo_return_button(): print("任意键返回\n", end="") input("Please input: ") todo_router() def todo_router(): function_select_parse = \ "+" + "-" * 58 + "+\n" \ "| <1> Our plan\t\t\t\t\t\t |\n" + \ "| <2> Secret\t\t\t\t\t\t |\n" + \ "| <3> First time for us\t\t\t\t\t |\n" + \ "| <0> Return\t\t\t\t\t\t |\n" + \ "+" + "-" * 58 + "+\n" + \ "Please select: " print() select_num = input(function_select_parse) if select_num != "0829" and select_num != "papapa": select_num = module_select(select_num, function_select_parse, 0, 3) if select_num == "papapa": from to_do_list.papapa import our_papapa our_papapa() todo_return_button() elif select_num == "0829": from to_do_list.todo_list import first_time first_time() todo_return_button() elif int(select_num) == 1: from to_do_list.todo_list import todo_list todo_list() todo_return_button() elif int(select_num) == 2: print(":) 嘿嘿，暗号不对哦~\n") todo_return_button() elif int(select_num) == 3: print(":) qinglong.gao record, secret...\n") todo_return_button() else: from best_wishes import select_route select_route() if __name__ == '__main__': todo_router()

[ "gordon_ml@163.com" ]

gordon_ml@163.com

20f5aa7402083c520f00ed6fee80516b0dce609b

d8adb204f43471bf868b44d4cd552103ab9b114f

/Lab3.py

5ffa9f575a491ef1c29be6d5be9a1794235886b7

[]

no_license

ytwog/tchmkProject3

bfbadcb09ed2df657948cd59aa186188bc808713

d91a5a95ae4ebc75a9d8c02f5d76ccdec6bf2a80

refs/heads/master

2022-09-15T16:50:18.911887

2020-05-30T07:08:20

268,026,644

0

null

UTF-8

Python

false

303

py

import math import random N = 10 ** 100 M = 10 ** 4 res = 2 - (2 * math.log(2)) def func(M): num = 0 for x in range(M): b = random.randint(1, N) r = N % b if r < b / 2: num += 1 print('Probability: ', num / M) print('Teoreth: ', res) print(func(M))

[ "ytwog@mail.ru" ]

ytwog@mail.ru

73585b7971de472d714d021bd438be989c8d4e19

86ea59142d252b1f11421a9771e7ec66d4b374d7

/project/script/LR_model.py

ac09d0be0c71f0c334df669bffb37f0c3ecb0c4f

[]

no_license

Loielaine/NLP

145c6883852d0fdd5713830fbeba3030ecc860c3

7c45ee6f98045cb22af6fede48ae61bc76c89802

refs/heads/master

2020-12-29T10:18:19.850359

2020-04-28T18:25:46

238,570,520

1

null

UTF-8

Python

false

714

py

from torch import nn import torch.nn.functional as F class LogisticRegression(nn.Module): def __init__(self, input_size, num_classes): super(LogisticRegression, self).__init__() self.linear = nn.Linear(input_size, 200) self.output = nn.Linear(200, num_classes) # Initialize the weights of both layers self.init_weights() def init_weights(self): initrange = 0.1 self.linear.weight.data.uniform_(-1 * initrange, initrange) self.linear.bias.data.zero_() self.output.weight.data.uniform_(-1 * initrange, initrange) self.output.bias.data.zero_() def forward(self, x): x = x.view(x.size()[0], -1) input = self.linear(x) output = self.output(input) out = F.softmax(output) return out

[ "noreply@github.com" ]

Loielaine.noreply@github.com

cb6db7eb37364ebd18c2e62d7b3e88d6bad7b233

719c658585b2e585ee16d7a9421d0ca28b30158e

/code/sulheim2020/consensusModel/fix_SBO_terms.py

a373c47ee1e6302f60ac5d9e6f3403665fea746a

[ "CC-BY-4.0" ]

permissive

matinnuhamunada/Sco-GEM

896046f0ef2b4a15f408eab75959dd1cf0c1a5a3

418c1a5942cd22b89a9d118c01f72506f2c80e16

refs/heads/master

2023-05-04T16:22:27.119213

2021-04-04T19:57:58

null

0

null

UTF-8

Python

false

3,452

py

# -*- coding: utf-8 -*- #!/usr/bin/env python """ Author: Snorre Sulheim / Eduard Kerkhoven # Description This file adds SBO terms to reactions and metabolites. This is kind of a copy of a matlab-script Eduard used to to the same """ import cobra import logging """ Reactions SBO terms =================== SBO term | name ------------------------------------ SBO:0000627 | exchange reaction SBO:0000628 | demand reaction SBO:0000629 | biomass production SBO:0000630 | ATP maintenance SBO:0000395 | encapsulating process SBO:0000655 | transport reaction SBO:0000176 | biochemical reaction SBO:0000632 | sink reaction SBO:0000631 | pseudoreaction Metabolite SBO terms ==================== SBO term | name ------------------------------ SBO:0000649 | biomass SBO:0000247 | simple chemical Genes ====== All genes SBO:0000243 """ METABOLITE_SBO_TERMS = { "biomass": "SBO:0000649", "simple chemical": "SBO:0000247", } REACTION_SBO_TERMS = { "exchange reaction": "SBO:0000627", "demand reaction": "SBO:0000628", "biomass production": "SBO:0000629", "ATP mainteinance": "SBO:0000630", "encapsulating process": "SBO:0000395", "transport reaction": "SBO:0000655", "biochemical reaction": "SBO:0000176", "sink reaction": "SBO:0000632", "pseudoreaction": "SBO:0000631", } GENE_SBO_TERM = "SBO:0000243" def add_SBO(scoGEM): # Metabolites for m in scoGEM.metabolites: if m.name in ["biomass", "DNA", "RNA", "protein", "carbohydrate", "cell wall", "lipid"]: m.annotation["SBO"] = METABOLITE_SBO_TERMS["biomass"] else: m.annotation["SBO"] = METABOLITE_SBO_TERMS["simple chemical"] # Reactions all_reactions = [r.id for r in scoGEM.reactions] for r in scoGEM.exchanges: r.annotation["SBO"] = REACTION_SBO_TERMS["exchange reaction"] all_reactions.remove(r.id) for r in scoGEM.demands: r.annotation["SBO"] = REACTION_SBO_TERMS["demand reaction"] all_reactions.remove(r.id) for r in scoGEM.sinks: r.annotation["SBO"] = REACTION_SBO_TERMS["sink reaction"] all_reactions.remove(r.id) scoGEM.reactions.ATPM.annotation["SBO"] = REACTION_SBO_TERMS["ATP mainteinance"] all_reactions.remove("ATPM") for r_id in all_reactions: r = scoGEM.reactions.get_by_id(r_id) if "BIOMASS_SCO" in r.id: r.annotation["SBO"] = REACTION_SBO_TERMS["biomass production"] elif r.id in ["PSEUDO_DONOR_NADH", "PSEUDO_DONOR_NADPH", "PSEUDO_ACCEPTOR_NAD", "PSEUDO_ACCEPTOR_NADP"]: r.annotation["SBO"] = REACTION_SBO_TERMS["pseudoreaction"] elif "pseudoreaction" in r.name.lower(): r.annotation["SBO"] = REACTION_SBO_TERMS["encapsulating process"] else: if len(r.compartments) == 2: r.annotation["SBO"] = REACTION_SBO_TERMS["transport reaction"] else: r.annotation["SBO"] = REACTION_SBO_TERMS["biochemical reaction"] # Genes for g in scoGEM.genes: g.annotation["SBO"] = GENE_SBO_TERM logging.info("Added SBO terms to genes, reactions and metabolites") print("Added SBO terms") if __name__ == '__main__': scoGEM_FN = "../../ModelFiles/xml/scoGEM.xml" scoGEM = cobra.io.read_sbml_model(scoGEM_FN) add_SBO(scoGEM)

[ "ssulheim@gmail.com" ]

ssulheim@gmail.com

95e284a91a19a3a14eaf0b3cdecba1fa3bbdd1e9

6c4a0877fd924ccb2ef276a6214e9dc0440e1a65

/PairwiseCorrelation_3.py

4de4a2fc068319ded1f9921fcf146a600ee064ee

[]

no_license

GboladeAI/hipppocampal-Neuro-modelling

907ccbde3a7fe541aabfb25b04fc906bfdd3a764

a9061830d0e6267813b40193a67586b379e67fa9

refs/heads/master

2021-06-29T15:20:56.170384

2017-09-14T14:24:28

103,421,748

0

null

UTF-8

Python

false

7,640

py

import math import numpy as numpy from pandas import * import pylab as pltlab from matplotlib.pyplot import * import matplotlib.pyplot as plt import matplotlib.mlab as mlab import bisect import pandas as pdb import numpy as np import pandas as pd import scipy.io as spio import matplotlib.pyplot as plt from matplotlib import cm import sys from math import exp, factorial, pow, log from decimal import Decimal import mysql.connector import os import sys #orig_stdout = sys.stdout #f = open('outputPairwiseCorrelation.txt', 'w') #sys.stdout = f cwd = os.getcwd() import datetime print (datetime.datetime.now()) def getSpikeDatPoint(NueronID): conn = mysql.connector.connect(user='root', password='AnuIfe2014$', database='NueroSCi') curr = conn.cursor() selectstmt = " SELECT " selectstmt = selectstmt + " d.id, d.AnimalName, d.time_at_location, a.TimeSpike, d.x_axis, d.y_axis, d.mesh, a.CrossValidation " selectstmt = selectstmt + " from NueroSCi.tblNeuronspikeI a, NueroSci.tblMAP " selectstmt = selectstmt + " b, NueroSCi.tblLOCATIONDATAI d " selectstmt = selectstmt + " where " selectstmt = selectstmt + " a.id = b.id_tblNEURONSPIKE and b.distance < 1 " selectstmt = selectstmt + " and b.id_tblLOCATIONDATA = d.id and a.TimeSpike >= 5285 and a.TimeSpike<=7353 " selectstmt = selectstmt + " and a.NeuronID = " + str(NueronID) + " " selectstmt = selectstmt + " order by " selectstmt = selectstmt + " 3 asc " #print selectstmt curr.execute(selectstmt) data = curr.fetchall() varTimeSpike = [] varTimeSpikeDiff = [] Neuron =[] k = 0 summ = 0.00 for row in data: varTimeSpike.append(float(row[2])) Neuron.append(float(row[2]) * 1000) if k == 0: varTimeSpikeDiff.append(float("0.00")) else: if abs((float(varTimeSpike[k]) - float(varTimeSpike[k - 1]))) < 6.00: varTimeSpike.append(float(row[2])) Neuron.append(float(row[2])* 1000) k = k + 1 curr.close() conn.close() return Neuron def getDistinctNueron(): conn = mysql.connector.connect(user='root', password='AnuIfe2014$', database='NueroSCi') curr = conn.cursor() curr = conn.cursor() selectstmt = " SELECT " selectstmt = selectstmt + " distinct a.NeuronID as NeuronID " selectstmt = selectstmt + " from NueroSCi.tblNeuronspikeI a, NueroSci.tblMAP " selectstmt = selectstmt + " b, NueroSCi.tblLOCATIONDATAI d " selectstmt = selectstmt + " where " selectstmt = selectstmt + " a.id = b.id_tblNEURONSPIKE and b.distance < 1 " selectstmt = selectstmt + " and b.id_tblLOCATIONDATA = d.id and a.TimeSpike >= 5285 and a.TimeSpike<=7353 " selectstmt = selectstmt + " order by 1 asc " #print selectstmt curr.execute(selectstmt) data = curr.fetchall() NeuronIDs = [] for row in data: NeuronIDs.append(row[0]) curr.close() conn.close() return NeuronIDs N=getDistinctNueron() sizeN = len(N) positivecorrcoef = [] positivepairnueron = [] negativecorrcoef = [] negativepairnueron = [] zeropairnueron =[] zerocorrcoef = [] lp=0 ln=0 lz=0 ticksp=[] ticksn=[] ticksz=[] np=0 nn=0 nz=0 DtTAB=10 Dt=(DtTAB/10.0) * 1000 # 0.1 seconds for k in range(0, sizeN ): nuerona=N[k] Nueron_A =getSpikeDatPoint(nuerona) # get the spike count for Nueron A based on Dt time bin spikecountNoise_A, binsA, patchesA = plt.hist(Nueron_A, bins=int(Dt), histtype='bar', color='blue') #plt.savefig(str(cwd) + '/test.png') print " nuerona : " + str(nuerona) for j in range(k+1, sizeN ): nueronb = N[j] Nueron_B = getSpikeDatPoint(nueronb) # get the spike count for Nueron B based on Dt time bin spikecountNoise_B, binsB, patchesB = plt.hist(Nueron_B, bins=int(Dt), histtype='bar', color='blue') #plt.savefig(str(cwd)+'/test.png') ### COmpute the Spearman correlation a, b = numpy.corrcoef(spikecountNoise_A, spikecountNoise_B)[0] cc = str(nuerona) +'_'+ str(nueronb) if b>0.00: positivecorrcoef.append(float(b)) positivepairnueron.append(str(cc)) ticksp.append(np) np=np+1 if b < 0.00: negativecorrcoef.append(float(b)) negativepairnueron.append(str(cc)) ticksn.append(nn) nn=nn+1 if b==0.00: zerocorrcoef.append(float(b)) zeropairnueron.append(str(cc)) ticksn.append(nz) nz = nz + 1 dfpositive = DataFrame({'PairNueron':positivepairnueron, 'CorrCoef': positivecorrcoef}) #df=df.sort([ 'CorrCoef'], ascending=[ False]) dfpositive.sort_values('CorrCoef', axis=0, ascending=False, inplace=True, kind='quicksort', na_position='last') dfnegative = DataFrame({'PairNueron':negativepairnueron, 'CorrCoef': negativecorrcoef}) #df=df.sort([ 'CorrCoef'], ascending=[ False]) dfnegative.sort_values('CorrCoef', axis=0, ascending=False, inplace=True, kind='quicksort', na_position='last') dfzero = DataFrame({'PairNueron':zeropairnueron, 'CorrCoef': zerocorrcoef}) print("Positive Pairwise Correlation") print("**************************************************") conn = mysql.connector.connect(user='root', password='AnuIfe2014$', database='NueroSCi') curr = conn.cursor() for row in dfpositive.iterrows(): index, data = row print (data['PairNueron']), (data['CorrCoef']) INSERTstmt = " Insert into PairwiseCorrelation"+str(DtTAB)+"00 VALUES( 'Positive','I', "+str(data['PairNueron']).split("_")[0] +", " INSERTstmt=INSERTstmt +str(data['PairNueron']).split("_")[1]+", "+ str(data['CorrCoef']) +" ) " try: curr.execute(INSERTstmt) curr.execute("commit") except mysql.connector.ProgrammingError: print( "The following query failed:") print (INSERTstmt) conn.close() curr.close() print("Negative Pairwise Correlation") print("**************************************************") conn = mysql.connector.connect(user='root', password='AnuIfe2014$', database='NueroSCi') curr = conn.cursor() for row in dfnegative.iterrows(): index, data = row #print (data['PairNueron']), (data['CorrCoef']) INSERTstmt = " Insert into PairwiseCorrelation"+str(DtTAB)+"00 VALUES( 'Negative','I', "+str(data['PairNueron']).split("_")[0] +", " INSERTstmt=INSERTstmt +str(data['PairNueron']).split("_")[1]+", "+ str(data['CorrCoef']) +" ) " try: curr.execute(INSERTstmt) curr.execute("commit") except mysql.connector.ProgrammingError: print( "The following query failed:") print (INSERTstmt) conn.close() curr.close() print("") print("") print("") print("Zero Pairwise Correlation") print("**************************************************") conn = mysql.connector.connect(user='root', password='AnuIfe2014$', database='NueroSCi') curr = conn.cursor() for row in dfzero.iterrows(): index, data = row #print (data['PairNueron']), (data['CorrCoef']) INSERTstmt = " Insert into PairwiseCorrelation"+str(DtTAB)+"00 VALUES( 'Zero','I', "+str(data['PairNueron']).split("_")[0] +", " INSERTstmt=INSERTstmt +str(data['PairNueron']).split("_")[1]+", "+ str(data['CorrCoef']) +" ) " try: curr.execute(INSERTstmt) curr.execute("commit") except mysql.connector.ProgrammingError: print( "The following query failed:") print (INSERTstmt) conn.close() curr.close() print("") print("") print("") #sys.stdout = orig_stdout #f.close() print (datetime.datetime.now())

[ "noreply@github.com" ]

GboladeAI.noreply@github.com

3612f1f79bd273655750d177b8935d7343cae48a

3b66632458e2463db62a800f9a0cf9e13c71a47e

/tests/test_iterators/test_tf_batches.py

a458cf5d88bfb93a210c6d1e36e2c94cdc9f33ff

[ "MIT" ]

permissive

pesser/edflow

eddb6d9341b861670946c157363933e9add52288

317cb1b61bf810a68004788d08418a5352653264

refs/heads/dev

2022-12-09T05:19:35.850173

2020-07-21T16:29:15

146,750,121

27

15

MIT

2022-12-07T20:55:50

2018-08-30T12:59:11

Python

UTF-8

Python

false

1,075

py

import pytest import numpy as np from edflow.iterators import tf_batches as batches def test_tf_batch_to_canvas(): import tensorflow as tf tf.enable_eager_execution() x = np.ones((9, 100, 100, 3)) x = tf.convert_to_tensor(x) canvas = batches.tf_batch_to_canvas(x) assert canvas.shape == (1, 300, 300, 3) canvas = batches.tf_batch_to_canvas(x, cols=5) assert canvas.shape == (1, 200, 500, 3) canvas = batches.tf_batch_to_canvas(x, cols=1) assert canvas.shape == (1, 900, 100, 3) canvas = batches.tf_batch_to_canvas(x, cols=0) assert canvas.shape == (1, 900, 100, 3) canvas = batches.tf_batch_to_canvas(x, cols=None) assert canvas.shape == (1, 300, 300, 3) x = np.ones((9, 100, 100, 1)) x = tf.convert_to_tensor(x) canvas = batches.tf_batch_to_canvas(x) assert canvas.shape == (1, 300, 300, 1) x = np.ones((9, 100, 100, 1, 1)) x = tf.convert_to_tensor(x) with pytest.raises(ValueError, match="input tensor has more than 4 dimensions."): canvas = batches.tf_batch_to_canvas(x)

[ "supermario94123@gmail.com" ]

supermario94123@gmail.com

a3612f2f4a46e893399fd2040db726e8602be19d

f203c94b9bc0e65dff7d955fc96e581cbed3edff

/desafio 20.py

046a0c1bbcce6376cd43b3e8872fca758a61a199

[]

no_license

Woimarina/mundo-1---python-curso-em-video

45521012613c69a045d341855b619e8d59dd7811

09e2b127d2ee85e70807a83a7bd9880992748bee

refs/heads/main

2023-09-05T15:57:28.274525

2021-11-01T18:50:24

null

0

null

UTF-8

Python

false

358

py

import random aluno1 = input('digite o nome do primeiro aluno: ') aluno2 = input('digite o nome do segundo aluno: ') aluno3 = input('digite o nome do terceiro aluno: ') aluno4 = input('digite o nome do quarto aluno: ') lista = [aluno1, aluno2, aluno3, aluno4] random.shuffle(lista) print(' a sequencia de apresentação será: {}'.format(lista))

[ "noreply@github.com" ]

Woimarina.noreply@github.com

c50bc8addf50e1d761c36d106a08f8f01960d815

040e29f30d17743a67562867640b73ae19834524

/incentive.py

8de5910986cb9d0c8b94d72df90e7303903b2e26

[ "Apache-2.0" ]

permissive

AIandSocialGoodLab/securitygamewithinformants

0f7ee58471ac9ccd542b73e2c60290796447b6e9

6244e8891d1244fd6162aea79ff259a34d0f3c66

refs/heads/master

2023-04-03T00:33:51.256758

2023-03-19T20:52:27

260,015,755

0

3

null

2020-04-29T19:01:13

2020-04-29T18:54:54

null

UTF-8

Python

false

5,113

py

# This is the code used to generate the data for Figure 4(b) in the paper. import gurobipy as gp from gurobipy import GRB import numpy as np import pandas # from scipy.special import softmaxscipy import matplotlib.pyplot as plt import seaborn as sns import datetime def printGraph(X, Y, Y1, name): plt.figure('Draw') plt.plot(X, Y) plt.plot(X, Y1) legend = [] legend.append('defense utility gain') legend.append('expected additional payoff') plt.legend(legend, loc='lower right') # plt.scatter(X, Y, color = 'r', marker='.') plt.xlabel('addtional reward') plt.draw() plt.savefig(name + ".pdf") plt.close() print("print figure finish: " + name) def lp_calc(pw, pa, ra, pd, rd, uc, uu, p, r, t): ilp_model = gp.Model('utility_optimization') x = ilp_model.addVars(len(pa), len(pa) + 2, name='x') m = np.zeros((len(pa), len(p))) for i in range(len(p)): for j in range(len(pa)): if uc[j, i] < uu[j, i]: m[j, i] = len(pa) + 1 else: m[j, i] = j + 1 ilp_model.setObjective(gp.quicksum( (p[i] * ((1 - pw) * (x[t, 0] * rd[t] + (1 - x[t, 0]) * pd[t]) + pw * (x[t, m[t, i]] * rd[t] + (1 - x[t, m[t, i]]) * pd[t]))) for i in range(len(p))), GRB.MAXIMIZE) ilp_model.addConstrs(gp.quicksum( (p[i] * ((1 - pw) * (x[t, 0] * pa[t] + (1 - x[t, 0]) * ra[t]) + pw * (x[t, m[t, i]] * pa[t] + (1 - x[t, m[t, i]]) * ra[t]))) for i in range(len(p))) >= gp.quicksum( (p[i] * ((1 - pw) * (x[j, 0] * pa[j] + (1 - x[j, 0]) * ra[j]) + pw * (x[j, m[j, i]] * pa[j] + (1 - x[j, m[j, i]]) * ra[j]))) for i in range(len(p))) for j in range(len(pa))) ilp_model.addConstrs(x[t1, i] >= x[t1, len(pa) + 1] for i in range(len(pa) + 2) for t1 in range(len(pa))) ilp_model.addConstrs(x[t1, i] <= x[t1, t1 + 1] for i in range(len(pa) + 2) for t1 in range(len(pa))) ilp_model.addConstrs(x[t1, i] >= 0 for t1 in range(len(pa)) for i in range(len(pa) + 2)) ilp_model.addConstrs(x[t1, i] <= 1 for t1 in range(len(pa)) for i in range(len(pa) + 2)) ilp_model.addConstrs(gp.quicksum(x[t, i] for t in range(len(pa))) <= r for i in range(len(pa) + 2)) ilp_model.optimize() try: print(ilp_model.objVal) except Exception as e: print(e) return -np.inf, -np.inf, 0 x1 = ilp_model.getAttr('X', x) attacker_val = sum((p[i] * ((1 - pw) * (x1[t, 0] * pa[t] + (1 - x1[t, 0]) * ra[t]) + pw * ( x1[t, m[t, i]] * pa[t] + (1 - x1[t, m[t, i]]) * ra[t]))) for i in range(len(p))) print(attacker_val) return ilp_model.objVal, attacker_val, sum(p[i] * x1[t, m[t, i]] * pw for i in range(len(p))) def softmax(x): return np.exp(x) / sum(np.exp(x)) import pickle def save(obj, path): with open(path, 'wb') as f: pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL) if __name__ == '__main__': type_number = 2 target_numbers = [10, 30, 100, 200, 300, 400, 500, 600] target_number = 10 alpha = 0.3 eps = 1e-8 res = [] payoff_res = [] target_us = [] for num_instances in range(50): # print(p.shape) r = 1 pw = 0.3 maxv = -np.inf list_a = [] list_result = [] list_pay = [] scale = 0.1 pa = -np.random.rand(target_number) ra = np.random.rand(target_number) uc = np.random.rand(target_number, type_number) pd = -np.random.rand(target_number) rd = np.random.rand(target_number) uu = np.random.rand(target_number, type_number) uc *= scale uu *= scale p = np.random.rand(type_number) p = p / np.sum(p) r = 1 target_u = -np.inf for i in range(0, target_number): cur_utility, _, _ = lp_calc(pw, pa, ra, pd, rd, uc, uu, p, r, i) target_u = max(target_u, cur_utility) target_us.append(target_u) for up in np.arange(0, 0.1, 0.001): uc = uc + up maxv = -np.inf payoff = 0 for i in range(0, target_number): cur_utility, _ , xt= lp_calc(pw, pa, ra, pd, rd, uc, uu, p, r, i) if cur_utility > maxv: maxv = cur_utility payoff = xt * up list_result.append(maxv) list_pay.append(payoff) res.append(list_result) payoff_res.append(list_pay) print(res) print_x = np.arange(0, 0.1, 0.001) res = np.array(res) payoff_res = np.array(payoff_res) print(res) save(res, 'tmp/incentive_n.pickle') save(payoff_res, 'tmp/incentive_payoff.pickle') # The following part is to draw a draft with the data, not exactly painting the figure in the paper mean_res = np.mean(res, axis=0) print(mean_res.shape) mean_res = mean_res.reshape(-1) mean_payoff = np.mean(payoff_res, axis=0) mean_payoff = mean_payoff.reshape(-1) printGraph(print_x, mean_res, mean_payoff, 'incentive')

[ "chenweizhe1999@126.com" ]

chenweizhe1999@126.com

93fc5ec316577bd629f8918a2d20178df6b74d41

f15e1bf95382348c8ed758bf136bf86d2435b9b4

/apputils/stock_analysis.py

55a5308e20168c7e45544acfc69a4046e49ddb20

[ "Apache-2.0" ]

permissive

VaidherviKansal/Delta-lake_demo

40e56913e631b3b22bda963bd1a240307c29cf96

fca694b1b89959fb29932c90a0f1784a779dd22c

refs/heads/master

2021-05-17T21:47:49.874987

2020-03-31T07:14:29

250,966,078

0

null

UTF-8

Python

false

2,181

py

import datetime from pyspark.sql import SparkSession # read from local system spark = SparkSession.builder.appName('abc').getOrCreate() dfBasePrice = spark.read.format("csv").option("header", "true").load("/home/vaidhervi/Downloads/stocksDailyPrices.csv") dfBaseFund = spark.read.format("csv").option("header", "true").load("/home/vaidhervi/Downloads/stocksFundamentals.csv") dfBaseFund.show() dfBasePrice.show() # write # Create Fundamental Data (Databricks Delta table) print("delta table") dfBaseFund.write.mode('overwrite').format("delta").save("file:///home/vaidhervi/delta/stockF") # Create Price Data (Databricks Delta table) dfBasePrice.write.mode('overwrite').format("delta").save("file:///home/vaidhervi/delta/stockP") print("transformations") row = dfBasePrice.aggregate((dfBasePrice.price_date.max()).alias("maxDate"), (dfBasePrice.price_date.min()).alias("minDate")).collect()[0] startDate = row["minDate"] endDate = row["maxDate"] # Define our date range function def daterange(start_date, end_date): for n in range(int((end_date - start_date).days)): yield start_date + datetime.timedelta(n) # Define combinePriceAndFund information by date def combinePriceAndFund(theDate): dfFund = dfBaseFund.where( dfBaseFund.price_date == theDate) dfPrice = dfBasePrice.where( dfBasePrice.price_date == theDate).drop('price_date').collect() # Drop the updated column dfPriceWFund = dfPrice.join(dfFund, on=["ticker"], how='inner').drop("updated") # Save data to DBFS dfPriceWFund.write.format("delta").mode("append").save("file:///home/vaidhervi/delta/stocksDailyPricesWFund") # Loop through dates to complete fundamentals # + price ETL process for single_date in daterange(startDate, (endDate + datetime.timedelta(days=1))): start = datetime.datetime.now() combinePriceAndFund(single_date) end = datetime.datetime.now() dfPriceWithFundamentals = spark.read.format("delta").load("file:///home/vaidhervi/delta/stocksDailyPricesWFund") dfPriceWithFundamentals.show() # Create temporary view of the data dfPriceWithFundamentals.createOrReplaceTempView("priceWithFundamentals")

[ "vaidhervi.kansal@teamcomputers.com" ]

vaidhervi.kansal@teamcomputers.com