`\n\n\"\"\"\n\nfrom setuptools import find_packages\nfrom setuptools import setup\n\ntry:\n readme = open('readme.md').read()\nexcept:\n readme = __doc__\n\nsetup(\n name='pip_services3_prometheus',\n version='3.1.2',\n url='http://github.com/pip-services3-python/pip-services3-prometheus-python',\n license='MIT',\n description='Prometheus components for Pip.Services in Python',\n author='Conceptual Vision Consulting LLC',\n author_email='seroukhov@gmail.com',\n long_description=readme,\n long_description_content_type=\"text/markdown\",\n packages=find_packages(exclude=['config', 'data', 'test']),\n include_package_data=True,\n zip_safe=True,\n platforms='any',\n install_requires=[\n 'pytest',\n\n 'pip-services3-commons >= 3.3.9, < 4.0',\n 'pip-services3-components >= 3.5.0, < 4.0',\n 'pip-services3-rpc >= 3.2.12, < 4.0'\n ],\n classifiers=[\n 'Development Status :: 4 - Beta',\n 'Intended Audience :: Developers',\n 'License :: OSI Approved :: MIT License',\n 'Operating System :: OS Independent',\n 'Programming Language :: Python',\n 'Programming Language :: Python :: 3.5',\n 'Programming Language :: Python :: 3.6',\n 'Programming Language :: Python :: 3.7',\n 'Programming Language :: Python :: 3.8',\n 'Topic :: Software Development :: Libraries :: Python Modules'\n ]\n)\n","sub_path":"setup.py","file_name":"setup.py","file_ext":"py","file_size_in_byte":1769,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"40027280","text":"\"\"\"singular value decomposition\"\"\"\nimport numpy as np\n\ndef singular_values(dataset):\n \"\"\"applies svd to the dataset to obtain singular values\n\n :type dataset: numpy.array (mxn) | numpy.matrix (mxn)\n :return: singular values obtained from applying svd on the dataset\n \"\"\"\n U, sigma, Vt = np.linalg.svd(dataset)\n return sigma\n\ndef compress_dataset(dataset):\n \"\"\"uses svd to compress the dataset into a new one with fewer feature but that still conserves 90% of the energy\n\n :type dataset: numpy.matrix (mxn)\n :return: compressed dataset\n \"\"\"\n U, sigma, Vt = np.linalg.svd(dataset)\n energy_threshold = sum(sigma ** 2) * 0.9\n\n # find minimum number of features that contain 90% of the energy\n num_single_values = 0\n for i in range(1, len(sigma)):\n energy = sum(sigma[:i] ** 2)\n if energy >= energy_threshold:\n num_single_values = i\n\n # reconstruct the dataset with less features\n sigma_matrix = np.mat(np.eye(num_single_values) * sigma[:num_single_values])\n # transform dataset into lower dimensional space\n compressed_dataset = dataset.T * U[:, :num_single_values] * sigma_matrix.I\n return compressed_dataset\n","sub_path":"dimensionality_reduction/singular_value_decomposition/svd.py","file_name":"svd.py","file_ext":"py","file_size_in_byte":1191,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"335339467","text":"import numpy\r\n\r\nclass Solution(object):\r\n def matrixReshape(self, nums, r, c):\r\n \"\"\"\r\n :type nums: List[List[int]]\r\n :type r: int\r\n :type c: int\r\n :rtype: List[List[int]]\r\n \"\"\"\r\n shape = numpy.array(nums).shape\r\n \r\n if r*c != shape[0]*shape[1]:\r\n return nums\r\n \r\n else:\r\n return numpy.reshape(nums, (r, c)).tolist()\r\n\r\nif __name__ =='__main__':\r\n test = Solution()\r\n print(test.matrixReshape([[1,2],[3,4]],r=1,c=4))\r\n","sub_path":"No566_reshape_the_matrix.py","file_name":"No566_reshape_the_matrix.py","file_ext":"py","file_size_in_byte":529,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"287566111","text":"#!usr/bin/env python\n# -*- coding:utf-8 _*-\n\"\"\"\n@author:jerry\n@file: student_insecure_server.py\n@time: 2019/06/18\n\"\"\"\nimport time\nimport logging\nimport grpc\nimport student_pb2_grpc\nfrom concurrent.futures import ThreadPoolExecutor\nfrom student_servicer_imp import StudentServiceImp\n\n_ONE_DAY_IN_SECONDS = 60 * 60 * 24\n\n\ndef serve():\n logging.info(\"rpc服务启动\")\n server = grpc.server(ThreadPoolExecutor(max_workers=3))\n student_pb2_grpc.add_StudentServiceServicer_to_server(servicer=StudentServiceImp(), server=server)\n server.add_insecure_port(\"localhost:8080\")\n server.start()\n try:\n while True:\n time.sleep(_ONE_DAY_IN_SECONDS)\n except KeyboardInterrupt:\n server.stop(0)\n logging.info(\"rpc服务停止\")\n\n\nif __name__ == '__main__':\n logging.basicConfig(filename='./server.log', level=10)\n serve()\n","sub_path":"insecure-demo/student_insecure_server.py","file_name":"student_insecure_server.py","file_ext":"py","file_size_in_byte":864,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"565937649","text":"import tensorflow as tf\nimport numpy as np\nimport random\nimport os\nimport cv2\nfrom tensorflow.examples.tutorials.mnist import input_data\n\nmnist = input_data.read_data_sets(os.path.dirname(os.path.realpath(__file__))+\"/../data/MNIST_data/\", one_hot=True)\n\nx = tf.placeholder(\"float\", [None, 784])\ny = tf.placeholder(\"float\", [None, 10])\n\nW = tf.Variable(tf.zeros([784, 10]))\nb = tf.Variable(tf.zeros([10]))\n\nlearning_rate = 0.01\ntraining_epochs = 1\nbatch_size = 100\ndisplay_step = 1\n\n### modeling ###\n\nactivation = tf.nn.softmax(tf.matmul(x, W) + b)\n\ncross_entropy = tf.reduce_mean(-tf.reduce_sum(y * tf.log(activation), reduction_indices=1))\n\noptimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cross_entropy)\n\ninit = tf.global_variables_initializer()\n\nsess = tf.Session()\nsess.run(init)\n\n### training ###\n\nfor epoch in range(training_epochs) :\n\n avg_cost = 0\n total_batch = int(mnist.train.num_examples/batch_size)\n\n for i in range(total_batch) :\n\n batch_xs, batch_ys =mnist.train.next_batch(batch_size)\n sess.run(optimizer, feed_dict={x: batch_xs, y: batch_ys})\n avg_cost += sess.run(cross_entropy, feed_dict = {x: batch_xs, y: batch_ys}) / total_batch\n\n if epoch % display_step == 0 :\n print(\"Epoch : \", \"%04d\" % (epoch+1), \"cost=\", \"{:.9f}\".format(avg_cost))\n\nprint(\"Optimization Finished\")\n\n### predict number ###\n\nr = random.randint(0, mnist.test.num_examples - 1)\nprint(\"Prediction: \", sess.run(tf.argmax(activation,1), {x: mnist.test.images[r:r+1]}))\nprint(\"Correct Answer: \", sess.run(tf.argmax(mnist.test.labels[r:r+1], 1)))\n\nimage = np.zeros((1,784))\nsess.run(tf.argmax(activation,1), {x: image})","sub_path":"SFData/ICSE2020/s39032277_ground_truth.py","file_name":"s39032277_ground_truth.py","file_ext":"py","file_size_in_byte":1665,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"405289957","text":"# Copyright 2017 IBM Corp.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n# License for the specific language governing permissions and limitations\n# under the License.\n\n\nfrom zvmsdk import config\nfrom zvmsdk import constants as const\nfrom zvmsdk import exception\nfrom zvmsdk import log\nfrom zvmsdk import smtclient\nfrom zvmsdk import utils as zvmutils\n\n\n_HOSTOPS = None\nCONF = config.CONF\nLOG = log.LOG\n\n\ndef get_hostops():\n global _HOSTOPS\n if _HOSTOPS is None:\n _HOSTOPS = HOSTOps()\n return _HOSTOPS\n\n\nclass HOSTOps(object):\n\n def __init__(self):\n self._smtclient = smtclient.get_smtclient()\n\n def get_info(self):\n inv_info = self._smtclient.get_host_info()\n host_info = {}\n\n with zvmutils.expect_invalid_resp_data(inv_info):\n host_info['zcc_userid'] = inv_info['zcc_userid']\n host_info['zvm_host'] = inv_info['zvm_host']\n host_info['vcpus'] = int(inv_info['lpar_cpu_total'])\n host_info['vcpus_used'] = int(inv_info['lpar_cpu_used'])\n host_info['cpu_info'] = {}\n host_info['cpu_info'] = {'architecture': const.ARCHITECTURE,\n 'cec_model': inv_info['cec_model'], }\n mem_mb = zvmutils.convert_to_mb(inv_info['lpar_memory_total'])\n host_info['memory_mb'] = mem_mb\n mem_mb_used = zvmutils.convert_to_mb(inv_info['lpar_memory_used'])\n host_info['memory_mb_used'] = mem_mb_used\n host_info['hypervisor_type'] = const.HYPERVISOR_TYPE\n verl = inv_info['hypervisor_os'].split()[1].split('.')\n version = int(''.join(verl))\n host_info['hypervisor_version'] = version\n host_info['hypervisor_hostname'] = inv_info['hypervisor_name']\n host_info['ipl_time'] = inv_info['ipl_time']\n diskpool_name = CONF.zvm.disk_pool.split(':')[1]\n dp_info = self.diskpool_get_info(diskpool_name)\n host_info.update(dp_info)\n\n return host_info\n\n def guest_list(self):\n guest_list = self._smtclient.get_all_user_direct()\n with zvmutils.expect_invalid_resp_data(guest_list):\n return guest_list\n\n def diskpool_get_info(self, pool):\n dp_info = self._smtclient.get_diskpool_info(pool)\n with zvmutils.expect_invalid_resp_data(dp_info):\n for k in list(dp_info.keys()):\n s = dp_info[k].strip().upper()\n if s.endswith('G'):\n sl = s[:-1].split('.')\n n1, n2 = int(sl[0]), int(sl[1])\n if n2 >= 5:\n n1 += 1\n dp_info[k] = n1\n elif s.endswith('M'):\n n_mb = int(s[:-3])\n n_gb, n_ad = n_mb // 1024, n_mb % 1024\n if n_ad >= 512:\n n_gb += 1\n dp_info[k] = n_gb\n else:\n exp = \"ending with a 'G' or 'M'\"\n errmsg = (\"Invalid diskpool size format: %(invalid)s; \"\n \"Expected: %(exp)s\") % {'invalid': s, 'exp': exp}\n LOG.error(errmsg)\n raise exception.SDKInternalError(msg=errmsg)\n\n return dp_info\n","sub_path":"zvmsdk/hostops.py","file_name":"hostops.py","file_ext":"py","file_size_in_byte":3682,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"465593849","text":"import pandas as pd\nimport numpy as np\nfrom sklearn.preprocessing import StandardScaler\nimport matplotlib.pyplot as plt\nfrom sklearn.decomposition import PCA\nfrom sklearn.feature_selection import VarianceThreshold\ndef dataDesc(data): #数据的基础信息展示\n var_types= pd.DataFrame(data.dtypes,columns=['v_types'])\n var_types['flag']=var_types['v_types'].apply(lambda x:('float' in str(x)) or ('int' in str(x)) or ('ouble' in str(x))) \n obj_features=data[var_types[var_types['flag']==False].index]\n num_desc=data.describe().T\n num_features=list(var_types[var_types['flag']==True].index)\n for num in num_features:\n st=data[num].value_counts()\n num_desc.at[num,'unique']=st.shape[0]\n if st.shape[0]>0:\n num_desc.at[num,'top']=st.index[0]\n num_desc.at[num,'freq']=st.values[0] \n if obj_features.shape[1]>0 : \n obj_desc=obj_features.describe().T\n rs=pd.concat([obj_desc,num_desc])\n else:\n rs=num_desc\n rs=rs[['min','25%','50%','75%','max','mean','std','count','unique','top','freq' ]] \n rs['missing']=1-rs['count']/data.shape[0]\n print(\"===================各个变量的基本情况==================\")\n print(rs.round())\n #cov = np.corrcoef(data[num_features].T)\n cov=data[num_features].corr().round(2)\n print(\"===================各数量变量的相关系数矩阵==================\")\n print(cov)\n plt.figure(figsize=(8,8))\n img = plt.matshow(cov,cmap=plt.cm.winter,fignum=0)# plt.cm.winter\n plt.title('corr of variable')\n plt.colorbar(img, ticks=[-1,0,1])\n plt.show()\n plt.close()\n print(\"===================变量分布统计图==================\")\n data.hist(figsize=(13,4*(data.shape[1]//3+1)),bins=30) #各个变量分布\n plt.show()\n plt.close()\n if len(num_features)<11:\n print(\"===================各数值变量间的散点关系图==================\")\n pd.scatter_matrix(data[num_features],figsize=(18,12))\n plt.show()\n plt.close()\n else:\n print(\"数值变量超过10个，不统计各个变量间的散点关系图\")\n num_features.remove('Target')\n rows=len(num_features)//3+1\n plt.figure(figsize=(13,4*rows))\n i=1\n for v in num_features:\n plt.subplot(rows,3,i)\n plt.plot( data['Target'],data[v],'or')\n plt.title(v+\" vs Target scatter\")\n i=i+1\n print(\"===================自变量与目标变量的散点图==================\")\n plt.show()\n plt.close()\n return rs,cov\nif __name__ == '__main__':\n# data=loadDataSet()\n data=pd.read_table('D:\\model_data\\diabetes.txt')\n data.rename(columns={'Y':'Target'}, inplace = True)#设立目标变量 因变量\n #desc=dataDesc(std_data) #数据初步探索\n y=np.array(data['Target'])\n x_df=data.drop(['Target'],axis=1)\n feature_names=list(x_df.columns)\n X=StandardScaler().fit_transform(X=x_df,y=y) # 标准化 也可以归一化，但是标准化多\n st=VarianceThreshold(threshold=3).fit_transform(X=data,y=y)\n #pca = PCA(n_components='mle') \n #pca.fit(data[['AGE', 'SEX', 'BMI', 'BP', 'S1', 'S2', 'S3', 'S4', 'S5', 'S6']])\n #gui_data=(data - data.min()) / (data.max() - data.min()) #归一化\n \n #data.hist(figsize=(15,15),bins=30) #各个变量分布\n #pd.scatter_matrix(data,figsize=(18,12))","sub_path":"model/diabetes.py","file_name":"diabetes.py","file_ext":"py","file_size_in_byte":3373,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"56649721","text":"\nimport os\nimport re\nimport math\nimport os.path as op\n\nfrom pyrocko import config, util\nfrom pyrocko.topo import srtmgl3, etopo1, dataset, tile\n\npositive_region = tile.positive_region\n\nearthradius = 6371000.0\nr2d = 180./math.pi\nd2r = 1./r2d\nkm = 1000.\nd2m = d2r*earthradius\nm2d = 1./d2m\n\ntopo_data_dir = config.config().topo_dir\n\nsrtmgl3 = srtmgl3.SRTMGL3(\n name='SRTMGL3',\n data_dir=op.join(topo_data_dir, 'SRTMGL3'))\n\nsrtmgl3_d2 = dataset.DecimatedTiledGlobalDataset(\n name='SRTMGL3_D2',\n base=srtmgl3,\n ndeci=2,\n data_dir=op.join(topo_data_dir, 'SRTMGL3_D2'))\n\nsrtmgl3_d4 = dataset.DecimatedTiledGlobalDataset(\n name='SRTMGL3_D4',\n base=srtmgl3_d2,\n ndeci=2,\n data_dir=op.join(topo_data_dir, 'SRTMGL3_D4'))\n\nsrtmgl3_d8 = dataset.DecimatedTiledGlobalDataset(\n name='SRTMGL3_D8',\n base=srtmgl3_d4,\n ndeci=2,\n ntx=1001,\n nty=1001,\n data_dir=op.join(topo_data_dir, 'SRTMGL3_D8'))\n\netopo1 = etopo1.ETOPO1(\n name='ETOPO1',\n data_dir=op.join(topo_data_dir, 'ETOPO1'))\n\netopo1_d2 = dataset.DecimatedTiledGlobalDataset(\n name='ETOPO1_D2',\n base=etopo1,\n ndeci=2,\n data_dir=op.join(topo_data_dir, 'ETOPO1_D2'))\n\netopo1_d4 = dataset.DecimatedTiledGlobalDataset(\n name='ETOPO1_D4',\n base=etopo1_d2,\n ndeci=2,\n data_dir=op.join(topo_data_dir, 'ETOPO1_D4'))\n\netopo1_d8 = dataset.DecimatedTiledGlobalDataset(\n name='ETOPO1_D8',\n base=etopo1_d4,\n ndeci=2,\n data_dir=op.join(topo_data_dir, 'ETOPO1_D8'))\n\nsrtmgl3_all = [\n srtmgl3,\n srtmgl3_d2,\n srtmgl3_d4,\n srtmgl3_d8]\n\netopo1_all = [\n etopo1,\n etopo1_d2,\n etopo1_d4,\n etopo1_d8]\n\ndems = srtmgl3_all + etopo1_all\n\n\ndef make_all_missing_decimated():\n for dem in dems:\n if isinstance(dem, dataset.DecimatedTiledGlobalDataset):\n dem.make_all_missing()\n\n\ndef cpt(name):\n if os.path.exists(name):\n return name\n\n if not re.match(r'[A-Za-z0-9_]+', name):\n raise Exception('invalid cpt name')\n\n fn = util.data_file(os.path.join('colortables', '%s.cpt' % name))\n if not os.path.exists(fn):\n raise Exception('cpt file does not exist: %s' % fn)\n\n return fn\n\n\ndef comparison(region, dems=dems):\n import matplotlib.pyplot as plt\n\n east, west, south, north = tile.positive_region(region)\n\n fig = plt.gcf()\n\n for idem, dem_ in enumerate(dems):\n fig.add_subplot(len(dems), 1, idem+1)\n t = dem_.get(region)\n if t:\n plt.pcolormesh(t.x(), t.y(), t.data)\n plt.title(dem_.name)\n plt.xlim(east, west)\n plt.ylim(south, north)\n\n plt.show()\n\n\nclass UnknownDEM(Exception):\n pass\n\n\ndef dem_names():\n return [dem.name for dem in dems]\n\n\ndef dem(dem_name):\n for dem in dems:\n if dem.name == dem_name:\n return dem\n\n raise UnknownDEM(dem_name)\n\n\ndef get(dem_name, region):\n return dem(dem_name).get(region)\n\n\ndef select_dem_names(kind, dmin, dmax, region):\n assert kind in ('land', 'ocean')\n ok = []\n if kind == 'land':\n for dem in srtmgl3_all:\n if dem.is_suitable(region, dmin, dmax):\n ok.append(dem.name)\n break\n\n for dem in etopo1_all:\n if dem.is_suitable(region, dmin, dmax):\n ok.append(dem.name)\n break\n\n return ok\n\nif __name__ == '__main__':\n #comparison((-180., 180., -90, 90), dems=[etopo1_d8])\n util.setup_logging('topo', 'info')\n comparison((30, 31, 30, 31), dems=[srtmgl3, srtmgl3_d2])\n","sub_path":"src/topo/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":3488,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"223345506","text":"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n\nimport codecs\nimport os\nimport io\nimport glob\nimport random\n\ndef feed(reduceby):\n #Parent.SendStreamMessage(\"Beginning Overheat\")\n global timerActive\n voteDir = 'D:/Program Files/Streamlabs Chatbot/Services/Twitch/Votes/'\n campfireDir = 'D:/Program Files/Streamlabs Chatbot/Services/Twitch/flame.txt'\n retVal = ''\n threshold = 800\n interval = 100 # for every 100 past 1000, increase the multiplier by 1\n payoutBase = 2\n payoutInterval = 1000\n \n timerActive = False\n choices = os.listdir(voteDir)\n \n # add multiple copies of choices with higher values\n for file in os.listdir(voteDir):\n \n with io.open(voteDir + file, 'r', encoding = 'utf-8-sig') as f:\n campfire = int(f.read().decode('utf-8-sig'))\n \n if campfire >= (threshold+interval):\n multiplier = (campfire-1000)/100\n \n for i in range(multiplier):\n choices.append(file)\n \n choice = random.choice(choices)\n name = choice # choose a random file from within the directory\n \n #for each in choices:\n # Parent.SendStreamMessage(each)\n \n with open(voteDir + name, 'r') as file: # open the random file\n filedata = int(file.read().decode('utf-8-sig'))\n \n #Parent.SendStreamMessage('Opened name: ' + name)\n\n if reduceby > filedata: # make sure it has enough logs to reduce by that much\n retVal += 'The questing tendrils of salamander flame pass up ' + name.split('.')[0] + '; It is too small to sate it\\'s appetite.'\n \n #Parent.SendStreamMessage('Too small')\n else: # feed\n filedata = filedata - reduceby\n retVal += 'The salamander flame gorges itself on '+ name.split('.')[0] + '\\'s log pile, consuming ' + str(reduceby) + ' logs. It is sated for now.'\n \n #Parent.SendStreamMessage('The right size.')\n \n # Write the reduced log count to the file.\n with open(voteDir + name, 'w+') as file:\n file.write(str(filedata))\n \n print('The right size, but smaller')\n \n # read in the campfire\n with open(campfireDir, 'r') as file:\n campfire = int(file.read().decode('utf-8-sig'))\n print(str(campfire))\n campfire = campfire + reduceby\n \n #Parent.SendStreamMessage('Payout interval: ' + payoutInterval)\n #payout = int(payoutBase) + int(campfire / payoutInterval)\n #Parent.SendStreamMessage(payout)\n payout = 2\n print(\"The growing forest rewards users with \" + str(payout))\n \n # write the new campfire value in\n with open(campfireDir, 'w+') as file:\n file.write(str(campfire))\n \n myDict = {}\n #for viewers in Parent.GetViewerList():\n # this controls how much chatters get payed\n # myDict[viewers] = payout\n\n #Parent.AddPointsAll(myDict)\n #Parent.SendStreamMessage(\"The growing forest rewards users with \" + payout)\n \n print(retVal)\n \nfeed(10)","sub_path":"Overheat/test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":3115,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"182022103","text":"import requests\nimport pandas as pd\nimport numpy as np\nimport datetime\nimport json\n\nurl = \"https://bloomberg-market-and-financial-news.p.rapidapi.com/market/get-full\"\n\nquerystring = {\"id\":\"adsmi:ind,aex:ind,co1:com,gc1:com\"}\n\nheaders = {\n 'x-rapidapi-key': \"a9164563cbmshbb0d9669c26e1e6p1c432bjsn477e1068516e\",\n 'x-rapidapi-host': \"bloomberg-market-and-financial-news.p.rapidapi.com\"\n }\n\nresponse = requests.request(\"GET\", url, headers=headers, params=querystring)\n\nprint(response.text)\n\nrow_data = response.text\n\nwith open (\"data_log_original_version.txt\", \"w\") as plik:\n\tprint(row_data, file=plik)\n\nd = json.loads(row_data)\n\nwith open (\"data_log_original_version_json.json\", \"w\") as plik:\n\tprint(d, file=plik)\n\ndf = pd.json_normalize(d['result'])\ndf_t = df.T\n\ndf_t.to_excel(\"structured_data_original_version.xlsx\")","sub_path":"data_download/data_download_BLOOMBERG/MARKET/get-full/data_fetch.py","file_name":"data_fetch.py","file_ext":"py","file_size_in_byte":825,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"203749767","text":"import numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.gridspec import GridSpec\nimport random\n\n# 이 코드는 agent의 수와 target의 수가 고정된 상황에서 움직이는 target을 찾는 문제를 위해 만든 코드임\nclass Drones(object):\n def __init__(self, pos, view_range):\n self.pos = pos\n self.view_range = view_range\n\nclass Human(object): \n #사람 위치도 random하게 설정할 수 있음. 나중에 constant velocity 모델을 고려한다고 하면 더 다양한 움직임을 가지는 target을 생성 가능함\n def __init__(self, pos):\n self.pos = pos\n\nclass EnvDrones(object):\n def __init__(self, map_size, drone_num, view_range, tree_num, human_num):\n self.map_size = map_size\n self.drone_num = drone_num\n self.tree_num = tree_num # tree가 사람의 움직임을 방해하는가?\n self.human_num = human_num\n self.view_range = view_range\n \n # initialize blocks \n self.land_mark_map = np.zeros((self.map_size, self.map_size))\n for i in range(self.map_size):\n for j in range(self.map_size):\n if random.random() < 0.000001:\n # self.land_mark_map[i, j] = 0.0 # Block을 random하게 생성하는 코드\n self.land_mark_map[i, j] = 1 # Block을 random하게 생성하는 코드\n\n # intialize tree\n for i in range(self.tree_num):\n temp_pos = [random.randint(0, self.map_size-1), random.randint(0, self.map_size-1)]\n while self.land_mark_map[temp_pos[0], temp_pos[1]] != 0:\n temp_pos = [random.randint(0, self.map_size-1), random.randint(0, self.map_size-1)]\n self.land_mark_map[temp_pos[0], temp_pos[1]] = 2\n\n # initialize humans\n self.human_list = []\n for i in range(self.human_num): \n temp_pos = [random.randint(0, self.map_size-1), random.randint(0, self.map_size-1)]\n while self.land_mark_map[temp_pos[0], temp_pos[1]] != 0:\n temp_pos = [random.randint(0, self.map_size-1), random.randint(0, self.map_size-1)]\n temp_human = Human(temp_pos)\n self.human_list.append(temp_human)\n\n \"\"\"\n 블록과 나무 그리고 사람을 초기화 할 때는 서로 겹치지 않도록 0이 아닌 부분을 제외하는 방식으로 위치 할당\n \"\"\"\n # initialize drones\n self.start_pos = [self.map_size-1, self.map_size-1] # 드론의 초기 위치를 동일하게 할당하고 아래쪽에 random 한 위치로 할당 시켜버린다.\n self.drone_list = []\n for i in range(drone_num):\n temp_drone = Drones(self.start_pos, view_range)\n self.drone_list.append(temp_drone) \n\n def get_full_obs(self):\n obs = np.ones((self.map_size, self.map_size, 3))\n for i in range(self.map_size):\n for j in range(self.map_size):\n if self.land_mark_map[i, j] == 1: # block\n obs[i, j, 0] = 0\n obs[i, j, 1] = 0\n obs[i, j, 2] = 0\n if self.land_mark_map[i, j] == 2: # tree\n obs[i, j, 0] = 0\n obs[i, j, 1] = 1\n obs[i, j, 2] = 0\n\n for i in range(self.human_num):\n obs[self.human_list[i].pos[0], self.human_list[i].pos[1], 0] = 1\n obs[self.human_list[i].pos[0], self.human_list[i].pos[1], 1] = 0\n obs[self.human_list[i].pos[0], self.human_list[i].pos[1], 2] = 0\n return obs\n\n def get_drone_obs(self, drone):\n obs_size = 2 * drone.view_range - 1\n # obs = np.ones((self.map_size, self.map_size, 3)) # global observation size 와 local observation size 를 모두 통일\n obs = np.ones((obs_size, obs_size, 3))\n\n for i in range(obs_size):\n for j in range(obs_size):\n x = i + drone.pos[0] - drone.view_range + 1\n y = j + drone.pos[1] - drone.view_range + 1\n\n for k in range(self.human_num):\n if self.human_list[k].pos[0] == x and self.human_list[k].pos[1] == y:\n obs[i, j, 0] = 1\n obs[i, j, 1] = 0\n obs[i, j, 2] = 0\n\n if x>=0 and x<=self.map_size-1 and y>=0 and y<=self.map_size-1:\n if self.land_mark_map[x, y] == 1:\n obs[i, j, 0] = 0\n obs[i, j, 1] = 0\n obs[i, j, 2] = 0\n if self.land_mark_map[x, y] == 2:\n obs[i, j, 0] = 0\n obs[i, j, 1] = 1\n obs[i, j, 2] = 0\n else:\n obs[i, j, 0] = 0.5\n obs[i, j, 1] = 0.5\n obs[i, j, 2] = 0.5\n\n if (drone.view_range - 1 - i)*(drone.view_range - 1 - i)+(drone.view_range - 1 - j)*(drone.view_range - 1 - j) > drone.view_range*drone.view_range:\n obs[i, j, 0] = 0.5\n obs[i, j, 1] = 0.5\n obs[i, j, 2] = 0.5\n return obs\n\n def get_joint_obs(self):\n obs = np.ones((self.map_size, self.map_size, 3))\n for i in range(self.map_size):\n for j in range(self.map_size):\n obs[i, j, 0] = 0.5\n obs[i, j, 1] = 0.5\n obs[i, j, 2] = 0.5\n for k in range(self.drone_num):\n temp = self.get_drone_obs(self.drone_list[k])\n size = temp.shape[0] \n for i in range(size):\n for j in range(size):\n x = i + self.drone_list[k].pos[0] - self.drone_list[k].view_range + 1\n y = j + self.drone_list[k].pos[1] - self.drone_list[k].view_range + 1\n if_obs = True\n if temp[i, j, 0] == 0.5 and temp[i, j, 1] == 0.5 and temp[i, j, 2] == 0.5:\n if_obs = False\n if if_obs == True: \n obs[x, y, 0] = temp[i, j, 0]\n obs[x, y, 1] = temp[i, j, 1]\n obs[x, y, 2] = temp[i, j, 2]\n return obs\n\n def get_local_obs(self, drone_index):\n obs = np.ones((self.map_size, self.map_size, 3))\n for i in range(self.map_size):\n for j in range(self.map_size):\n obs[i, j, 0] = 0.5\n obs[i, j, 1] = 0.5\n obs[i, j, 2] = 0.5\n temp = self.get_drone_obs(self.drone_list[drone_index])\n size = temp.shape[0]\n for i in range(size):\n for j in range(size):\n x = i + self.drone_list[drone_index].pos[0] - self.drone_list[drone_index].view_range + 1\n y = j + self.drone_list[drone_index].pos[1] - self.drone_list[drone_index].view_range + 1\n if_obs = True\n if temp[i, j, 0] == 0.5 and temp[i, j, 1] == 0.5 and temp[i, j, 2] == 0.5:\n if_obs = False\n if if_obs == True: \n obs[x, y, 0] = temp[i, j, 0]\n obs[x, y, 1] = temp[i, j, 1]\n obs[x, y, 2] = temp[i, j, 2]\n return obs\n \n def rand_reset_drone_pos(self): \n for k in range(self.drone_num): \n self.drone_list[k].pos = [random.randint(0, self.map_size-1), random.randint(0, self.map_size-1)] \n\n def drone_step(self, drone_act_list):\n # Action에 맞춰서 drone의 position을 grid 상에서 옮겨버림\n if len(drone_act_list) != self.drone_num:\n print(\"Not enough number of actions for the agents\")\n return 0\n bad_actions = []\n self.bad_action = False \n for k in range(self.drone_num):\n if drone_act_list[k] == 0: # go up\n if self.drone_list[k].pos[0] > 0:\n self.drone_list[k].pos[0] = self.drone_list[k].pos[0] - 1\n if self.drone_list[k].pos[0] == 0:\n self.bad_action = True\n elif drone_act_list[k] == 1: # go down\n if self.drone_list[k].pos[0] < self.map_size - 1:\n self.drone_list[k].pos[0] = self.drone_list[k].pos[0] + 1\n if self.drone_list[k].pos[0] == self.map_size:\n self.bad_action = True\n elif drone_act_list[k] == 2: # go left\n if self.drone_list[k].pos[1] > 0:\n self.drone_list[k].pos[1] = self.drone_list[k].pos[1] - 1\n if self.drone_list[k].pos[1] == 0:\n self.bad_action = True\n elif drone_act_list[k] == 3: # go right\n if self.drone_list[k].pos[1] < self.map_size - 1:\n self.drone_list[k].pos[1] = self.drone_list[k].pos[1] + 1\n if self.drone_list[k].pos[1] == self.map_size:\n self.bad_action = True\n elif drone_act_list[k] == 4: # stop\n self.drone_list[k].pos[0] = self.drone_list[k].pos[0]\n self.drone_list[k].pos[1] = self.drone_list[k].pos[1]\n \n if self.drone_list[k].pos[0] == self.map_size or self.drone_list[k].pos[1] == self.map_size:\n self.bad_action = True\n bad_actions.append(self.bad_action)\n\n return bad_actions\n \"\"\"\n ㅡㅡㅡㅡㅡㅡㅡㅡㅡㅡㅡ> y\n |\n |\n | x축, y축을 잘 보고 판단!\n |\n |\n |\n x\n \"\"\"\n def human_step(self, human_act_list):\n if len(human_act_list) != self.human_num:\n return\n for k in range(self.human_num):\n if human_act_list[k] == 0:\n if self.human_list[k].pos[0] > 0:\n free_space = self.land_mark_map[self.human_list[k].pos[0] - 1, self.human_list[k].pos[1]]\n if free_space == 0:\n self.human_list[k].pos[0] = self.human_list[k].pos[0] - 1\n elif human_act_list[k] == 1:\n if self.human_list[k].pos[0] < self.map_size - 1:\n free_space = self.land_mark_map[self.human_list[k].pos[0] + 1, self.human_list[k].pos[1]]\n if free_space == 0:\n self.human_list[k].pos[0] = self.human_list[k].pos[0] + 1\n elif human_act_list[k] == 2:\n if self.human_list[k].pos[1] > 0:\n free_space = self.land_mark_map[self.human_list[k].pos[0], self.human_list[k].pos[1] - 1]\n if free_space == 0:\n self.human_list[k].pos[1] = self.human_list[k].pos[1] - 1\n elif human_act_list[k] == 3:\n if self.human_list[k].pos[1] < self.map_size - 1:\n free_space = self.land_mark_map[self.human_list[k].pos[0], self.human_list[k].pos[1] + 1]\n if free_space == 0:\n self.human_list[k].pos[1] = self.human_list[k].pos[1] + 1\n elif human_act_list[k] == 4:\n self.human_list[k].pos[0] = self.human_list[k].pos[0]\n self.human_list[k].pos[1] = self.human_list[k].pos[1]\n\n def step(self, human_act_list, drone_act_list): \n self.drone_step(drone_act_list)\n self.human_step(human_act_list) \n\n def cal_distance(self, ref_x, ref_y, target_x, target_y):\n return np.sqrt(pow(ref_x -target_x, 2) + pow(ref_y - target_y, 2))\n\n def get_reward(self, observations, min_distance):\n obs_size = 2 * self.view_range - 1\n communication_bound = 2*obs_size\n total_reward = []\n distance_matrix = []\n # calculate the center position of the drone\n self.x_center = int(obs_size / 2)\n self.y_center = int(obs_size / 2)\n self.ref_x = self.drone_list[0].pos[0]\n self.ref_y = self.drone_list[0].pos[1]\n\n for k in range(self.drone_num): \n current_x = self.drone_list[k].pos[0]\n current_y = self.drone_list[k].pos[1]\n r = 0.1\n target_count = 0 \n temp_count = 0\n # target이 local observation 내부에 있는지 여부를 파악하여 reward를 줌\n for i in range(obs_size):\n for j in range(obs_size):\n if observations[k][i,j,0]==1 and observations[k][i,j,1] == 0 and observations[k][i,j,2] == 0:\n temp_count += 1\n target_count +=1\n \n if temp_count != 0: \n distance = self.cal_distance(self.x_center, self.y_center, i, j) \n r = (self.view_range*2 - distance + 1) * 0.1 \n temp_count = 0\n\n # # commnuication bound\n if min_distance[k] >= communication_bound:\n r = r + 0.3 \n\n # if target_count == 0 and (current_x <= 0 or current_y <=0 or current_x >= self.map_size - 1 or current_y >= self.map_size -1): \n # r = r - 1 \n\n total_reward.append(r) \n \n return total_reward\n\n def communication(self, agent_index):\n # get current drone position\n current_x = self.drone_list[agent_index].pos[0]\n current_y = self.drone_list[agent_index].pos[1]\n \n # calculate the distance between agents\n distance = np.zeros([self.drone_num,1])\n index = 0 \n for k in range(self.drone_num):\n if k is not agent_index:\n target_x = self.drone_list[k].pos[0]\n target_y = self.drone_list[k].pos[1]\n distance[k] = self.cal_distance(current_x, current_y, target_x, target_y)\n elif k == agent_index:\n distance[k] = 1000\n \n # get the closest agent index and position\n min_distance = np.min(distance)\n closest_agent_index = np.argmin(distance) \n closest_position = [self.drone_list[closest_agent_index].pos[0], self.drone_list[closest_agent_index].pos[0]] \n \n vector_pos = [current_x / self.map_size, \n current_y / self.map_size, \n self.drone_list[closest_agent_index].pos[0] / self.map_size, \n self.drone_list[closest_agent_index].pos[0]/ self.map_size] \n closest_info = vector_pos \n \n return [closest_info, min_distance]\n","sub_path":"VDN/env_Drones.py","file_name":"env_Drones.py","file_ext":"py","file_size_in_byte":14833,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"488769921","text":"from typing import List\nfrom Leetcode.utils import perf\n\n\nclass Solution:\n\n serialize = {\n None: 'null',\n True: 'true',\n False: 'false'\n }\n\n @perf\n def run(self, actions, inputs, word_dictionary):\n ans = [None]\n wd = word_dictionary\n\n for j, action in enumerate(actions[1:], 1):\n if action == 'addWord':\n word = inputs[j][0]\n wd.addWord(word)\n ans.append(None)\n elif action == 'search':\n word = inputs[j][0]\n res = wd.search(word)\n ans.append(res)\n\n ans = [ self.serialize[entry] for entry in ans ]\n ans = '[' + ','.join(ans) + ']'\n return ans\n","sub_path":"Leetcode/add_and_search_word/run_solution.py","file_name":"run_solution.py","file_ext":"py","file_size_in_byte":731,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"402936997","text":"#coding: utf-8\n\nimport datetime\nfrom django.contrib.auth import logout, authenticate, login\nfrom django.contrib.auth.decorators import login_required\nfrom django.contrib.auth.models import User\nfrom django.core.paginator import Paginator, EmptyPage, PageNotAnInteger\nfrom django.core.urlresolvers import reverse\nfrom django.http import HttpResponseRedirect, HttpResponse\nfrom django.template import RequestContext\nfrom django.shortcuts import render_to_response\nfrom django.core.validators import validate_email\nfrom django.contrib import messages\nfrom django.shortcuts import redirect\nfrom django.utils.safestring import mark_safe\nfrom .models import Perfil, TipoUsuario, Organizacion, Rol, Agenda\nfrom multimodelo.settings import LOGIN_URL\nfrom userdj.calendario import CalendarioAgenda\nfrom .forms import OrganizacionForm\nfrom django.core.mail import EmailMultiAlternatives\nfrom django.http import HttpResponseForbidden\n\n\ndef login_user(request):\n logout(request)\n username = password = ''\n error = False\n if request.POST:\n username = request.POST['username']\n password = request.POST['password']\n next = request.GET.get('next', '/')\n user = authenticate(username=username, password=password)\n\n if user is not None:\n if user.is_active:\n login(request, user)\n return HttpResponseRedirect(next)\n else:\n error = True\n\n return render_to_response('userdj/login.html', {'error': error}, context_instance=RequestContext(request))\n\n\ndef salir(request):\n logout(request)\n return HttpResponseRedirect('/acceder/')\n\n\ndef asignar_cuestionario(request):\n idUsuario = request.GET['idUsuario']\n cuestionario = request.GET['cuestionario']\n valor = int(request.GET['valor'])\n \n usuario = User.objects.get(id=idUsuario)\n perfil = Perfil.objects.get(usuario=usuario)\n \n if cuestionario == 'entorno':\n perfil.cuestionario_entorno = valor\n else: \n perfil.cuestionario_extraccion = valor\n \n perfil.save()\n return HttpResponse(\"OK\")\n\n\ndef modificar_usuario(request, id_usuario):\n user = User.objects.get(id=id_usuario)\n perfil = Perfil.objects.get(usuario=user)\n\n tipos_usuarios = TipoUsuario.objects.all()\n organizaciones = Organizacion.objects.all()\n roles = Rol.objects.all()\n\n username = user.username\n nombre = user.first_name\n apellidos = user.last_name\n correo = user.email\n\n representante = perfil.principal\n tipo_usuario = perfil.tipo_usuario\n organizacion = perfil.organizacion\n rol = perfil.rol\n\n if request.method == 'POST':\n\n username = request.POST.get('username')\n nombre = request.POST.get('nombre')\n apellidos = request.POST.get('apellidos')\n correo = request.POST.get('correo')\n password = User.objects.make_random_password()\n\n representante = request.POST.get('representante', None)\n tipo_usuario = request.POST.get('tipo_usuario')\n organizacion = request.POST.get('organizacion', None)\n rol = request.POST.get('rol')\n\n try:\n validate_email(correo)\n try:\n from django.contrib.auth import authenticate\n\n user = User.objects.get(id=id_usuario)\n user.first_name = nombre\n user.last_name = apellidos\n\n if int(tipo_usuario) == 7:\n if request.user.is_superuser:\n user.is_staff = True\n user.is_superuser = True\n else:\n tipo_usuario = 1\n\n user.save()\n\n perfil = Perfil.objects.get(usuario=user)\n\n if organizacion:\n perfil.organizacion = Organizacion.objects.get(id=organizacion)\n else:\n perfil.organizacion = request.user.perfil.all()[:1].get().organizacion\n\n perfil.tipo_usuario = TipoUsuario.objects.get(id=tipo_usuario)\n perfil.rol = Rol.objects.get(id=rol)\n perfil.principal = False\n\n if representante:\n perfil.principal = True\n\n perfil.save()\n\n #email = EmailMultiAlternatives('Nueva cuenta', u\"Nombre de usuario: \" + username + u\"\\nContraseña: \" + password + u\"Agregar cita: http://mm.edgaruribe.mx/citas/agregar/\\n\", \"administrador@edgaruribe.mx\", [correo])\n #email.attach_alternative(u\"Nombre de usuario: \" + username + u\"
Contraseña: \" + password + u'
Agregar cita: http://mm.edgaruribe.mx/citas/agregar/
', \"text/html\")\n #email.send()\n\n # authenticate(username, password=password)\n\n messages.success(request, 'Usuario modificado correctamente.' + tipo_usuario)\n\n return redirect('usuarios')\n except Exception as e:\n messages.error(request, 'El nombre de usuario ya existe. ' + str(e) + ' - ' + tipo_usuario)\n except:\n messages.error(request, 'El correo es invalido.')\n\n return render_to_response('userdj/registro.html',\n {'username': username,\n 'nombre': nombre,\n 'apellidos': apellidos,\n 'correo': correo,\n 't_u': tipo_usuario,\n 'o': organizacion,\n 'r': rol,\n 'tipos_usuarios': tipos_usuarios,\n 'organizaciones': organizaciones,\n 'roles': roles,\n 'accion': \"Modificar\"},\n context_instance=RequestContext(request))\n\n\ndef agregar_usuario(request):\n tipos_usuarios = TipoUsuario.objects.all()\n organizaciones = Organizacion.objects.all()\n roles = Rol.objects.all()\n\n if request.method == 'POST':\n\n username = request.POST.get('username')\n nombre = request.POST.get('nombre')\n apellidos = request.POST.get('apellidos')\n correo = request.POST.get('correo')\n password = User.objects.make_random_password()\n\n representante = request.POST.get('representante', None)\n tipo_usuario = request.POST.get('tipo_usuario')\n organizacion = request.POST.get('organizacion', None)\n rol = request.POST.get('rol')\n\n existe = User.objects.filter(email=correo).exists()\n\n if not existe:\n try:\n validate_email(correo)\n try:\n from django.contrib.auth import authenticate\n\n user = User.objects.create_user(username, correo, password)\n user.first_name = nombre\n user.last_name = apellidos\n\n if int(tipo_usuario) == 7:\n if request.user.is_superuser:\n user.is_staff = True\n user.is_superuser = True\n else:\n tipo_usuario = 1\n\n user.save()\n\n perfil = Perfil()\n\n if organizacion:\n perfil.organizacion = Organizacion.objects.get(id=organizacion)\n else:\n perfil.organizacion = request.user.perfil.all()[:1].get().organizacion\n\n perfil.usuario = user\n perfil.tipo_usuario = TipoUsuario.objects.get(id=tipo_usuario)\n perfil.rol = Rol.objects.get(id=rol)\n perfil.principal = False\n\n if representante:\n perfil.principal = True\n\n perfil.save()\n\n if perfil.principal:\n asunto = u\"Registro como representante de organización\"\n mensaje = u\"Qué tal, el motivo del presente es que has sido registrado como representante de tu organización en el sistema para la extracción del conocimiento tácito de la organización para realizar el proyecto de formalización del conocimiento sobre los procesos para desarrolo de software que se llevan a cabo en tu organización, adjunto en este mensaje se envían el usuario y contraseña para acceso al sistema así como el link para acceder al sistema.\"\n mensaje_fin = u\"El siguiente paso es que entres al sistema, revises los datos de tu organización y agregues a los entrevistados de tu organización gracias.\"\n else:\n asunto = u\"Registro como entrevistado de organización\"\n mensaje = u\"Qué tal, el motivo del presente es que has sido registrado como entrevistado de tu organización, en el sistema para la extracción del conocimiento tácito de la organización para realizar el proyecto de formalización del conocimiento sobre los procesos para desarrolo de software que se llevan a cabo en tu organización, adjunto en este mensaje se envían el usuario y contraseña para acceso al sistema así como el link para acceder al sistema.\"\n mensaje_fin = u\"El siguiente paso es que accedas al sistema y selecciones el día y hora de tu entrevista gracias.\"\n\n email = EmailMultiAlternatives(asunto,\n mensaje + u\"\\n\\nNombre de usuario: \" + username + u\"\\nContraseña: \" + password + u\"Agregar cita: http://mm.edgaruribe.mx/citas/agregar/\\n\\n\" + mensaje_fin + u\"\\n\",\n \"administrador@edgaruribe.mx\", [correo])\n email.attach_alternative(\n \"\" + mensaje + u\"
Nombre de usuario: \" + username + u\"
Contraseña: \" + password + u'
Agregar cita: http://mm.edgaruribe.mx/citas/agregar/
' + mensaje_fin + u\"
\",\n \"text/html\")\n email.send()\n\n # authenticate(username, password=password)\n\n messages.success(request, 'Usuario agregado correctamente.' + tipo_usuario)\n\n return redirect('usuarios')\n except Exception as e:\n messages.error(request, 'El nombre de usuario ya existe. ' + str(e) + ' - ' + tipo_usuario)\n except:\n messages.error(request, 'El correo es invalido.')\n else:\n messages.error(request, 'El correo ya existe.')\n\n return render_to_response('userdj/registro.html',\n {'username': username,\n 'nombre': nombre,\n 'apellidos': apellidos,\n 'correo': correo,\n 't_u': tipo_usuario,\n 'o': organizacion,\n 'r': rol,\n 'tipos_usuarios': tipos_usuarios,\n 'organizaciones': organizaciones,\n 'roles': roles},\n context_instance=RequestContext(request))\n else:\n return render_to_response('userdj/registro.html',\n {'tipos_usuarios': tipos_usuarios,\n 'organizaciones': organizaciones,\n 'roles': roles},\n context_instance=RequestContext(request))\n\n\ndef usuarios(request):\n organizacion = int(request.GET.get(\"organizacion\", 0))\n organizaciones = Organizacion.objects.all()\n tipos_usuarios = TipoUsuario.objects.all()\n roles = Rol.objects.all()\n\n page = request.GET.get('page')\n\n if request.user.is_superuser:\n if not organizacion == 0:\n usuarios = User.objects.filter(perfil__organizacion_id=organizacion)\n else:\n usuarios = User.objects.all().order_by(\"-id\")\n else:\n usuarios = User.objects.filter(perfil__organizacion=request.user.perfil.all()[:1].get().organizacion).order_by(\n \"-id\")\n\n paginator = Paginator(usuarios, 10)\n\n try:\n usuarios = paginator.page(page)\n except PageNotAnInteger:\n # If page is not an integer, deliver first page.\n usuarios = paginator.page(1)\n except EmptyPage:\n # If page is out of range (e.g. 9999), deliver last page of results.\n usuarios = paginator.page(paginator.num_pages)\n\n return render_to_response('userdj/usuarios.html',\n {'usuarios': usuarios,\n 'organizacion': organizacion,\n 'organizaciones': organizaciones,\n 'tipos_usuarios': tipos_usuarios,\n 'roles': roles},\n context_instance=RequestContext(request))\n\n\ndef agenda(request, mes, ano):\n organizacion = int(request.GET.get('organizacion', 0))\n citas = Agenda.objects.filter(fecha__year=ano, fecha__month=int(mes)).order_by('fecha')\n\n if not organizacion == 0:\n citas = Agenda.objects.filter(usuario__perfil__organizacion_id=organizacion, fecha__year=ano,\n fecha__month=int(mes)).order_by('fecha')\n\n calendario = CalendarioAgenda(citas).formatmonth(int(ano), int(mes))\n\n organizaciones = Organizacion.objects.all()\n return render_to_response('userdj/calendario.html', {'calendario': mark_safe(calendario),\n 'citas': citas,\n 'mes': mes,\n 'ano': ano,\n 'organizaciones': organizaciones,\n 'organizacion': organizacion},\n context_instance=RequestContext(request))\n\n\ndef organizaciones(request):\n if request.user.is_superuser:\n organizaciones = Organizacion.objects.all().order_by(\"-id\")\n else:\n organizaciones = Organizacion.objects.filter(perfil__usuario=request.user)\n\n paginator = Paginator(organizaciones, 10)\n page = request.GET.get('page')\n\n try:\n organizaciones = paginator.page(page)\n except PageNotAnInteger:\n # If page is not an integer, deliver first page.\n organizaciones = paginator.page(1)\n except EmptyPage:\n # If page is out of range (e.g. 9999), deliver last page of results.\n organizaciones = paginator.page(paginator.num_pages)\n\n form = OrganizacionForm()\n\n return render_to_response('userdj/organizaciones.html', {'organizaciones': organizaciones,\n 'form': form},\n context_instance=RequestContext(request))\n\n\ndef agregar_organizacion(request):\n if request.method == 'POST':\n form = OrganizacionForm(request.POST)\n\n if form.is_valid():\n form.save()\n messages.success(request, 'Organización agregada correctamente.')\n return redirect('organizaciones')\n else:\n messages.error(request, 'Error al agregar el formulario.')\n\n else:\n form = OrganizacionForm()\n return render_to_response('userdj/agregar_organizacion.html', {'form': form},\n context_instance=RequestContext(request))\n\n\ndef modificar_organizacion(request, id_organizacion):\n organizacion = Organizacion.objects.get(id=id_organizacion)\n\n if request.method == 'POST':\n form = OrganizacionForm(request.POST, instance=organizacion)\n\n if form.is_valid():\n form.save()\n messages.success(request, 'Organización modificada correctamente.')\n return redirect('organizaciones')\n else:\n messages.error(request, 'Error al modificar el formulario.')\n\n else:\n form = OrganizacionForm(instance=organizacion)\n return render_to_response('userdj/agregar_organizacion.html', {'form': form, 'modificar': True},\n context_instance=RequestContext(request))\n\n\n@login_required(login_url=LOGIN_URL)\ndef agregar_cita(request):\n cita = None\n\n if request.method == 'POST':\n fecha = request.POST.get('fecha')\n hora = request.POST.get('hora') + \":00\"\n fecha_hora = datetime.datetime.strptime(fecha + \" \" + hora, '%d/%m/%Y %H:%M:%S')\n\n try:\n cita = Agenda.objects.get(usuario=request.user, fecha=fecha_hora)\n messages.error(request, 'La cita ya existe, para camibiarla selecciona otra fecha y/u hora.')\n except Agenda.DoesNotExist:\n try:\n cita = Agenda.objects.get(usuario=request.user)\n cita.cancelada = True\n cita.save()\n\n agenda = Agenda()\n agenda.fecha = fecha_hora\n agenda.usuario = request.user\n agenda.modificada = True\n agenda.save()\n messages.success(request, 'Cita modificada correctamente.')\n\n except:\n agenda = Agenda()\n agenda.fecha = fecha_hora\n agenda.usuario = request.user\n agenda.save()\n messages.success(request, 'Cita agregada correctamente.')\n else:\n try:\n cita = Agenda.objects.filter(usuario=request.user)[:1].get()\n except Agenda.DoesNotExist:\n cita = None\n\n return render_to_response('userdj/agregar_cita.html', {'cita': cita},\n context_instance=RequestContext(request))\n\n\ndef enviar_recordatorio(request):\n today = datetime.date.today()\n citas = Agenda.objects.filter(fecha__year=today.year, fecha__month=today.month, fecha__day=today.day)\n correos = \"\"\n for cita in citas:\n correos += cita.usuario.email + \"
\"\n email = EmailMultiAlternatives('Recordatorio cita',\n \"Recuerda que tu cita es hoy a las \" + str(cita.fecha.hour) + \":\" + str(\n cita.fecha.minute) + \".\", \"administrador@edgaruribe.mx\",\n [cita.usuario.email])\n email.attach_alternative(\n \"Recuerda que tu cita es hoy a las \" + str(cita.fecha.hour) + \":\" + str(cita.fecha.minute) + \".\",\n \"text/html\")\n try:\n email.send()\n except:\n pass\n\n return HttpResponse(\"Ok!
\" + correos)\n\n\ndef eliminar_usuario(request, id_usuario):\n borrar = bool(request.POST.get('borrar', False))\n usuario = User.objects.get(id=id_usuario)\n\n if borrar:\n usuario.delete()\n messages.success(request, 'Usuario eliminado correctamente.')\n return redirect(\"usuarios\")\n\n return render_to_response('userdj/borrar.html',\n {'mensaje': u\" al usuario %s %s\" % (usuario.first_name, usuario.last_name ),\n 'link': reverse('usuarios')},\n context_instance=RequestContext(request))\n\n\ndef eliminar_organizacion(request, id_organizacion):\n borrar = bool(request.POST.get('borrar', False))\n\n organizacion = Organizacion.objects.get(id=id_organizacion)\n\n if borrar:\n organizacion.delete()\n messages.success(request, 'Organización eliminado correctamente.')\n return redirect(\"organizaciones\")\n\n return render_to_response('userdj/borrar.html', {'mensaje': u\" la organización %s \" % organizacion.nombre,\n 'link': reverse('organizaciones')},\n context_instance=RequestContext(request))\n","sub_path":"multimodelo/userdj/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":19990,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"536367475","text":"# Copyright 2010 New Relic, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport pytest\nimport threading\n\nfrom newrelic.core.config import global_settings\nfrom testing_support.fixtures import override_generic_settings\n\nfrom newrelic.core.application import Application\nfrom newrelic.core.agent_streaming import StreamingRpc\nfrom newrelic.core.infinite_tracing_pb2 import Span, AttributeValue\nfrom testing_support.validators.validate_metric_payload import (\n validate_metric_payload)\n\nsettings = global_settings()\n\nCONDITION_CLS = type(threading.Condition())\n\n\n@pytest.fixture()\ndef app():\n app = Application('Python Agent Test (Infinite Tracing)')\n yield app\n # Calling internal_agent_shutdown on an application that is already closed\n # will raise an exception.\n active_session = app._active_session\n try:\n app.internal_agent_shutdown(restart=False)\n except:\n pass\n if active_session:\n assert not active_session._rpc.response_processing_thread.is_alive()\n assert not active_session._rpc.channel\n\n\n@pytest.mark.parametrize(\n 'status_code, metrics', (\n ('UNIMPLEMENTED', [\n ('Supportability/InfiniteTracing/Span/gRPC/UNIMPLEMENTED', 1),\n ('Supportability/InfiniteTracing/Span/Response/Error', 1)]),\n ('INTERNAL', [\n ('Supportability/InfiniteTracing/Span/gRPC/INTERNAL', 1),\n ('Supportability/InfiniteTracing/Span/Response/Error', 1)]),\n ))\ndef test_infinite_tracing_span_streaming(mock_grpc_server,\n status_code, metrics, monkeypatch, app):\n event = threading.Event()\n\n class TerminateOnWait(CONDITION_CLS):\n def notify_all(self, *args, **kwargs):\n event.set()\n return super(TerminateOnWait, self).notify_all(*args, **kwargs)\n\n def wait(self, *args, **kwargs):\n event.set()\n return super(TerminateOnWait, self).wait(*args, **kwargs)\n\n @staticmethod\n def condition(*args, **kwargs):\n return TerminateOnWait(*args, **kwargs)\n\n monkeypatch.setattr(StreamingRpc, 'condition', condition)\n\n span = Span(\n intrinsics={'status_code': AttributeValue(string_value=status_code)},\n agent_attributes={},\n user_attributes={})\n\n @override_generic_settings(settings, {\n 'distributed_tracing.enabled': True,\n 'span_events.enabled': True,\n 'infinite_tracing.trace_observer_host': 'localhost',\n 'infinite_tracing.trace_observer_port': mock_grpc_server,\n 'infinite_tracing.ssl': False,\n })\n @validate_metric_payload(metrics=metrics)\n def _test():\n app.connect_to_data_collector(None)\n\n app._stats_engine.span_stream.put(span)\n\n assert event.wait(timeout=5)\n\n app.harvest(shutdown=True)\n\n _test()\n\n\ndef test_reconnect_on_failure(monkeypatch, mock_grpc_server,\n buffer_empty_event, app):\n\n status_code = \"INTERNAL\"\n wait_event = threading.Event()\n continue_event = threading.Event()\n\n class WaitOnWait(CONDITION_CLS):\n def wait(self, *args, **kwargs):\n wait_event.set()\n continue_event.wait()\n return True\n\n @staticmethod\n def condition(*args, **kwargs):\n return WaitOnWait(*args, **kwargs)\n\n monkeypatch.setattr(StreamingRpc, 'condition', condition)\n\n terminating_span = Span(\n intrinsics={'status_code': AttributeValue(string_value=status_code)},\n agent_attributes={},\n user_attributes={})\n\n span = Span(\n intrinsics={},\n agent_attributes={},\n user_attributes={})\n\n @override_generic_settings(settings, {\n 'distributed_tracing.enabled': True,\n 'span_events.enabled': True,\n 'infinite_tracing.trace_observer_host': 'localhost',\n 'infinite_tracing.trace_observer_port': mock_grpc_server,\n 'infinite_tracing.ssl': False,\n })\n def _test():\n app.connect_to_data_collector(None)\n\n # Send a span that will trigger a failure\n app._stats_engine.span_stream.put(terminating_span)\n\n assert wait_event.wait(timeout=5)\n\n # Send a normal span afterwards\n app._stats_engine.span_stream.put(span)\n\n buffer_empty_event.clear()\n\n # Trigger the event so that a reconnect will occur\n continue_event.set()\n\n # Wait for the stream buffer to empty meaning all spans have been sent.\n assert buffer_empty_event.wait(10)\n app.internal_agent_shutdown(restart=False)\n\n _test()\n\n\ndef test_agent_restart(app):\n # Get the application connected to the actual 8T endpoint\n app.connect_to_data_collector(None)\n rpc = app._active_session._rpc\n\n # Store references to the original rpc and threads\n original_rpc = rpc.rpc\n original_thread = rpc.response_processing_thread\n original_span_stream = app._stats_engine.span_stream\n assert original_rpc\n assert rpc.response_processing_thread.is_alive()\n\n # Force an agent restart\n app.internal_agent_shutdown(restart=True)\n\n # Wait for connect to complete\n app._connected_event.wait()\n rpc = app._active_session._rpc\n\n assert not original_thread.is_alive()\n assert rpc.rpc is not original_rpc\n assert app._stats_engine.span_stream is not original_span_stream\n assert rpc.response_processing_thread.is_alive()\n\n\ndef test_disconnect_on_UNIMPLEMENTED(mock_grpc_server, monkeypatch, app):\n event = threading.Event()\n\n class WaitOnNotify(CONDITION_CLS):\n def notify_all(self, *args, **kwargs):\n event.set()\n return super(WaitOnNotify, self).notify_all(*args, **kwargs)\n\n @staticmethod\n def condition(*args, **kwargs):\n return WaitOnNotify(*args, **kwargs)\n\n monkeypatch.setattr(StreamingRpc, 'condition', condition)\n\n terminating_span = Span(\n intrinsics={'status_code': AttributeValue(\n string_value='UNIMPLEMENTED')},\n agent_attributes={},\n user_attributes={})\n\n @override_generic_settings(settings, {\n 'distributed_tracing.enabled': True,\n 'span_events.enabled': True,\n 'infinite_tracing.trace_observer_host': 'localhost',\n 'infinite_tracing.trace_observer_port': mock_grpc_server,\n 'infinite_tracing.ssl': False,\n })\n def _test():\n app.connect_to_data_collector(None)\n\n # Send a span that will trigger disconnect\n app._stats_engine.span_stream.put(terminating_span)\n\n # Wait for the notify event in close to be called\n assert event.wait(timeout=5)\n\n # Verify the rpc management thread is killed\n rpc_thread = app._active_session._rpc.response_processing_thread\n rpc_thread.join(timeout=5)\n assert not rpc_thread.is_alive()\n\n _test()\n\n\ndef test_agent_shutdown():\n # Get the application connected to the actual 8T endpoint\n app = Application('Python Agent Test (Infinite Tracing)')\n app.connect_to_data_collector(None)\n rpc = app._active_session._rpc\n # Store references to the original rpc and threads\n assert rpc.response_processing_thread.is_alive()\n app.internal_agent_shutdown(restart=False)\n assert not rpc.response_processing_thread.is_alive()\n assert not rpc.channel\n\n\n@pytest.mark.xfail(reason=\"This test is flaky\", strict=False)\ndef test_no_delay_on_ok(mock_grpc_server, monkeypatch, app):\n wait_event = threading.Event()\n connect_event = threading.Event()\n\n metrics = [('Supportability/InfiniteTracing/Span/gRPC/OK', 1),\n ('Supportability/InfiniteTracing/Span/Response/Error', None)]\n\n class SetFlagOnWait(CONDITION_CLS):\n def wait(self, *args, **kwargs):\n wait_event.set()\n return super(SetFlagOnWait, self).wait(*args, **kwargs)\n\n @staticmethod\n def condition(*args, **kwargs):\n return SetFlagOnWait(*args, **kwargs)\n\n monkeypatch.setattr(StreamingRpc, 'condition', condition)\n span = Span(\n intrinsics={\"status_code\": AttributeValue(string_value=\"OK\")},\n agent_attributes={},\n user_attributes={},\n )\n\n @override_generic_settings(settings, {\n 'distributed_tracing.enabled': True,\n 'span_events.enabled': True,\n 'infinite_tracing.trace_observer_host': 'localhost',\n 'infinite_tracing.trace_observer_port': mock_grpc_server,\n 'infinite_tracing.ssl': False,\n })\n @validate_metric_payload(metrics=metrics)\n def _test():\n\n def connect_complete():\n connect_event.set()\n\n app.connect_to_data_collector(connect_complete)\n\n assert connect_event.wait(timeout=5)\n connect_event.clear()\n\n # Send a span that will trigger disconnect\n stream_buffer = app._stats_engine.span_stream\n rpc = app._active_session._rpc\n\n _rpc = rpc.rpc\n\n def patched_rpc(*args, **kwargs):\n connect_event.set()\n return _rpc(*args, **kwargs)\n\n rpc.rpc = patched_rpc\n\n\n # Put a span that will trigger an OK status code and wait for an attempted\n # reconnect.\n stream_buffer.put(span)\n assert connect_event.wait(timeout=5)\n rpc.close()\n assert not wait_event.is_set()\n app.harvest()\n\n _test()\n","sub_path":"tests/agent_streaming/test_infinite_tracing.py","file_name":"test_infinite_tracing.py","file_ext":"py","file_size_in_byte":9683,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"60394880","text":"#-*-coding:utf8 -*-\n'''\n 缓存配置，缓存服务挂掉时，程序里的数据，以及elasticsearch的搜索点\n'''\nimport ConfigParser\nimport os\nimport pdb\nimport json\nfrom Clogdata import Clogdata\nfrom EShelplog import getlogInst\nimport os\ng_loginst=getlogInst()\ncf = ConfigParser.ConfigParser()\ncf.read('config/ess.conf')\nclass ESconfig:\n def __init__(self):\n global cf\n secs = cf.sections()\n self.Scalesize=0\n def setsize(self,size):\n self.Scalesize=size\n ret=cf.set(\"elasticsearchpara\",\"scalsize\",size)\n with open(\"config/ess.conf\", \"w+\") as f:\n cf.write(f)\n\n def getsize(self):\n temp = cf.get(\"elasticsearchpara\", \"scalsize\")\n self.Scalesize =cf.get(\"elasticsearchpara\", \"scalsize\")\n return self.Scalesize\n\nclass Dictcache:\n def __init__(self):\n self.dict={}\n def Getdict(self):\n global cf\n secs = cf.sections()\n str = cf.get(\"dictdata\", \"g_dict\")\n self.dict = self.deserialize(str)\n return self.dict\n def Setdict(self,tempdict):\n self.dict = tempdict\n ret = cf.set(\"dictdata\", \"g_dict\", self.serialize())\n with open(\"config/ess.conf\", \"w+\") as f:\n cf.write(f)\n def serialize(self):\n strdict=\"\"\n for (key,value) in self.dict.items():\n strdict+=key\n strdict+=\"@@@\"\n valuedata=json.dumps(value.Data2Json())\n strdict+=str(valuedata)\n strdict+=\"&&\"\n strdict=strdict[:-2] #去掉最后一个”&&“\n return strdict\n\n def deserialize(self,strdata):\n tempdict={}\n strdata=strdata.encode('utf-8')\n filedlist = strdata.split('&&')\n for item in filedlist:\n keyvalue=item.split(\"@@@\",1)\n strobj=keyvalue[1]\n jsonobj=json.loads(strobj.encode('utf-8'))\n logobj=Clogdata()\n logobj.copyAttr(jsonobj)\n tempdict[keyvalue[0]]=logobj\n self.dict=tempdict\n return self.dict\n pass\n def Createconf(self):# 不存在就创建一个\n global g_loginst\n flag=os.path.exists('config/ess.conf')\n if flag==True:\n pass\n g_loginst.logger.info(\"配置文件存在，不需要创建\")\n else:\n g_loginst.logger.info(\"配置文件不存在，创建文件\")\n cf.add_section('elasticsearchpara')\n cf.set('elasticsearchpara','scalsize',0)\n cf.add_section('dictdata')\n cf.set('dictdata','g_dict',{})\n pdb.set_trace()\n with open('config/ess.conf', 'w') as configfile:\n cf.write(configfile)\nif __name__ =='__main__':\n pass\n t=Dictcache()\n pdb.set_trace()\n t.Createconf()\n","sub_path":"ESconfig.py","file_name":"ESconfig.py","file_ext":"py","file_size_in_byte":2772,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"66909575","text":"import xml.etree.ElementTree as ET \r\nimport json\r\n\r\ndatasource= open('FindBugsCompileTime.xml')\r\ntree = ET.parse('FindBugsCompileTime.xml') \r\nroot = tree.getroot()\r\nprint (root.get('version'))\r\n# one specific item attribute\r\nprint(root[1].attrib)\r\nvulnTag= \"BugInstance\"\r\nappName=\"\"\r\n#Count total number of vulnerabilities\r\nfor element in root:\r\n if (element.tag=='FindBugsSummary'):\r\n total_vuln= element.get('total_bugs')\r\nprint (total_vuln)\r\nif (root[1].get('projectName')!=None):\r\n appName = root[1].get('projectName')\r\nelse:\r\n appName = \"ProjectNameNotDefined\"\r\nprint (appName)\r\nmydict= {}\r\nmydict [vulnTag]=[]\r\nfor element in root:\r\n if (element.tag==vulnTag):\r\n mydict[vulnTag].append({ \r\n 'findingName': element.get('category'),\r\n 'severity': element.get('priority'),\r\n 'description': element[0][0].get('sourcepath')\r\n })\r\nwith open('findbugs-json-output.json', 'w') as outfile: \r\n json.dump(mydict, outfile)\r\n\r\n\r\n\r\n","sub_path":"findbugs-python.py","file_name":"findbugs-python.py","file_ext":"py","file_size_in_byte":985,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"46636818","text":"from rest_framework import serializers\nfrom authentication.models import User\nfrom social.models import Followers, Request, Tags, TagContains\nfrom utils import paginator\n\nclass TagSearchSerializer(serializers.ModelSerializer):\n count = serializers.SerializerMethodField()\n results = serializers.SerializerMethodField()\n total_pages = serializers.SerializerMethodField()\n\n class Meta:\n model = User\n fields = ('count', 'total_pages', 'results')\n\n def get_count(self, obj):\n count = len(self.context.get(\"data\"))\n return count\n\n def get_total_pages(self, obj):\n all = self.context.get(\"data\")\n p = paginator(all, limit=15)\n return p.get('total_page')\n\n def get_results(self, obj):\n\n page = self.context.get(\"page\")\n url = self.context.get(\"url\")\n all = self.context.get(\"data\")\n requset_user = self.context.get('request_user')\n p = paginator(all, page=page, limit=15)\n\n result = p.get('result')\n result_list = []\n for tag in result:\n\n all_pic = TagContains.objects.filter(tag=tag).order_by('-id')\n if len(all_pic) == 0:\n continue\n picture = url + str(all_pic[0].post.picture)\n\n item = {\n 'tag_id': tag.id,\n 'tag_name': tag.name,\n 'picture': picture\n }\n result_list.append(item)\n\n return result_list\n\n\n\n","sub_path":"social/serializers/tag_search_serializer.py","file_name":"tag_search_serializer.py","file_ext":"py","file_size_in_byte":1459,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"264894079","text":"import numpy as np\r\nimport torch\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\nimport torchvision.models as models\r\nimport math\r\n\r\nimport os,inspect,sys\r\ncurrentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))\r\nsys.path.insert(0,currentdir)\r\n\r\n\"\"\"\r\nImplementation of CNN+LSTM.\r\n\"\"\"\r\n\"\"\"\r\nImplementation of Resnet+LSTM\r\n\"\"\"\r\nclass ResCRNN(nn.Module):\r\n def __init__(self, sample_size=256, sample_duration=16, num_classes=100,\r\n lstm_hidden_size=512, lstm_num_layers=1, arch=\"resnet18\",\r\n attention=False):\r\n super(ResCRNN, self).__init__()\r\n self.sample_size = sample_size\r\n self.sample_duration = sample_duration\r\n self.num_classes = num_classes\r\n\r\n # network params\r\n self.lstm_hidden_size = lstm_hidden_size\r\n self.lstm_num_layers = lstm_num_layers\r\n self.attention = attention\r\n\r\n # network architecture\r\n if arch == \"resnet18\":\r\n resnet = models.resnet18(pretrained=False)\r\n elif arch == \"resnet34\":\r\n resnet = models.resnet34(pretrained=False)\r\n elif arch == \"resnet50\":\r\n resnet = models.resnet50(pretrained=False)\r\n elif arch == \"resnet101\":\r\n resnet = models.resnet101(pretrained=False)\r\n elif arch == \"resnet152\":\r\n resnet = models.resnet152(pretrained=False)\r\n # delete the last fc layer\r\n modules = list(resnet.children())[:-1]\r\n self.resnet = nn.Sequential(*modules)\r\n self.lstm = nn.LSTM(\r\n input_size=resnet.fc.in_features,\r\n hidden_size=self.lstm_hidden_size,\r\n num_layers=self.lstm_num_layers,\r\n batch_first=True,\r\n )\r\n self.fc1 = nn.Linear(self.lstm_hidden_size, self.num_classes)\r\n\r\n def forward(self, x):\r\n # CNN\r\n cnn_embed_seq = []\r\n # x: (batch_size, channel, t, h, w)\r\n for t in range(x.size(2)):\r\n # with torch.no_grad():\r\n out = self.resnet(x[:, :, t, :, :])\r\n # print(out.shape)\r\n out = out.view(out.size(0), -1)\r\n cnn_embed_seq.append(out)\r\n\r\n cnn_embed_seq = torch.stack(cnn_embed_seq, dim=0)\r\n # print(cnn_embed_seq.shape)\r\n # batch first\r\n cnn_embed_seq = cnn_embed_seq.transpose_(0, 1)\r\n\r\n # LSTM\r\n # use faster code paths\r\n self.lstm.flatten_parameters()\r\n out, (h_n, c_n) = self.lstm(cnn_embed_seq, None)\r\n # MLP\r\n if self.attention:\r\n out = self.fc1(self.attn_block(out))\r\n else:\r\n # out: (batch, seq, feature), choose the last time step\r\n out = self.fc1(out[:, -1, :])\r\n\r\n return out\r\n\r\n\r\n# Test\r\nif __name__ == '__main__':\r\n import sys\r\n sys.path.append(\"..\")\r\n import torchvision.transforms as transforms\r\n sample_size = 128\r\n sample_duration = 16\r\n num_classes = 100\r\n # crnn = CRNN()\r\n data=torch.randn(1,3,16,128,128).cuda()\r\n crnn = ResCRNN(sample_size=sample_size, sample_duration=sample_duration, num_classes=num_classes, arch=\"resnet18\").cuda()\r\n print(crnn(data).size())","sub_path":"models/resnet2dlstm.py","file_name":"resnet2dlstm.py","file_ext":"py","file_size_in_byte":3162,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"241236709","text":"import numpy as np\nimport tensorflow as tf\nfrom tqdm import tqdm\n\nimport os\nimport matplotlib.pyplot as plt\n\npath_upwards = '../../'\nimport sys\nsys.path.extend([path_upwards + '../TailingDamDetection/'])\n\nimport config\nfrom nn_architecture.aka_lenet import cnn_adjust_lr\nfrom utils.ml_functions import softmax\n\nrseed = 1000\nnp.random.seed(rseed)\ntf.random.set_random_seed(rseed)\n\nexperiment_name = 'two_classes_images_v3'\n\npath_to_data = path_upwards + config.data_path + config.experiment_data + experiment_name + '/'\npath_to_results = path_upwards + config.result_path + config.experiment_data + experiment_name + '/'\nif not os.path.exists(path_to_results):\n os.makedirs(path_to_results)\n\nn_epoch = 40\nbatch_size = 32\n\ndata = np.load(path_to_data + 'train_test_data.npz')\n\ntrain_images = data['train_images']\ntrain_labels = data['train_labels']\n\ncnn = cnn_adjust_lr(n_classes=train_labels.shape[1], input_shape=train_images[0].shape, lr=1e-4)\n\ntrain_accuracy = np.zeros((n_epoch,), dtype=np.float64)\n\nfor epoch in range(n_epoch):\n print('\\tepoch %d...' % epoch)\n\n cnn.fit(train_images, train_labels, epochs=1, shuffle=True, batch_size=batch_size, verbose=0)\n\n train_prediction = cnn.predict(train_images)\n train_accuracy[epoch] = np.mean(np.argmax(train_prediction, axis=1) == np.argmax(train_labels, axis=1))\n print('\\ttrain accuracy {}'.format(train_accuracy[epoch]))\n\n\ntrain_predicted_probs = softmax(train_prediction, axis=1)\n\nplt.plot(range(n_epoch), train_accuracy, 'r--', label='train')\nplt.title('Accuracy')\n#plt.savefig(path_to_results + 'accuracy_results_{}.pdf'.format(cv_run))\nplt.show()\n\nif not os.path.exists(path_to_results + 'trained_model/'):\n os.makedirs(path_to_results + 'trained_model/')\ncnn.save(path_to_results + 'trained_model/weights.ckpt')\n\nnp.savez(path_to_results + 'results',\n train_accuracy=train_accuracy,\n train_predicted_probs=train_predicted_probs)\n","sub_path":"dam_recognition/two_classes_images_v3/train_cnn_from_scratch.py","file_name":"train_cnn_from_scratch.py","file_ext":"py","file_size_in_byte":1922,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"615581078","text":"# -*- coding: utf-8 -*-\nfrom main.Database.base import Base\nfrom sqlalchemy import Column, String, Integer, Table, ForeignKey\nfrom sqlalchemy.orm import relationship, backref\n\nroles_users = Table(\n 'roles_users',\n Base.metadata,\n Column('user_id', Integer(), ForeignKey('user.id')),\n Column('role_id', Integer(), ForeignKey('permission.id'))\n)\n\nclass User(Base):\n __tablename__ = 'user'\n id = Column(Integer, primary_key=True)\n username = Column(String(32))\n psk = Column(String)\n permission = relationship(\n 'Permission',\n secondary=roles_users,\n backref=backref('user', lazy='dynamic')\n )\n\n\n def __init__(self, username, psk, permission):\n self.username = username\n self.psk = psk\n self.permission = permission\n\n def __str__(self):\n return \"id: {}, username: {}, psk: {}, permission: {}\".format(self.id, self.username, self.psk, self.permission)\n","sub_path":"software/django project/main/Database/User.py","file_name":"User.py","file_ext":"py","file_size_in_byte":933,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"309597654","text":"from company import CompanyManager\nfrom IO import IO\n\n\ndef main():\n io = IO()\n io.options['test']()\n \"\"\" OLD SCHOOL\n manager = CompanyManager('database.db')\n manager.create_tables()\n\n while True:\n command = input(\"command>\")\n if command == \"add_employee\":\n name = input(\"name\")\n monthly_salary = input(\"monthly_salary\")\n yearly_bonus = input(\"yearly_bonus\")\n position = input(\"position\")\n manager.add_employee(name, monthly_salary, yearly_bonus, position)\n\n if command == \"list_employess\":\n return manager.cursor.execute(\"SELECT name FROM users\")\n \"\"\"\nif __name__ == '__main__':\n main()\n","sub_path":"week6/2-nd/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":699,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"296521761","text":"# -*- coding: utf-8 -*-\nimport re\n\ndef fixed_width(input_str, fixed_w=0, input_str_codec='utf-8'):\n\t\"\"\"\n\t把一个字符串裁剪为不长于fixed_w的版本，考虑“中文字符在屏幕中占两个显示位”的因素。\n\t\"\"\"\n\tif not isinstance(input_str, basestring):\n\t\treturn input_str\n\telif isinstance(input_str, basestring) and not isinstance(input_str, unicode):\n\t\tinput_str = unicode(input_str, input_str_codec)\n\n\tpat = re.compile(r'[\\x00-\\xFF]')\n\n\twidth_got = 0\n\tshorted_str = ''\n\tori_len = len(input_str)\n\tstop_poz = ori_len if ori_len > fixed_w else fixed_w\t#取长的，循环到取够长度为止\n\n\tc_list = list(input_str)\n\n\tfor i in range(0, stop_poz):\n\t\tif i < ori_len:\n\t\t\tnew_c = c_list[i]\n\t\telse:\n\t\t\tnew_c = ' '\n\n\t\tif pat.match(new_c):\n\t\t\twidth_got += 1\n\t\telse:\n\t\t\twidth_got += 2\n\n\t\tshorted_str += new_c\n\n\t\tif width_got == fixed_w:\n\t\t\treturn shorted_str\n\t\telif width_got == fixed_w + 1:\n\t\t\treturn shorted_str[0:i] + ' '\n\n","sub_path":"haotuWeixinEnterprise/haotu/utils/string.py","file_name":"string.py","file_ext":"py","file_size_in_byte":943,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"138609440","text":"resource = [400, 540, 120, 9, 550]\nespresso = [250, 0, 16, 1, 4]\nlatte = [350, 75, 20, 1, 7]\ncappuccino = [200, 100, 12, 1, 6]\nnew_resource = [[], [], [], [], []]\n\n\ndef result(resource):\n print('The coffee machine has:')\n print(str(resource[0]) + ' of water')\n print(str(resource[1]) + ' of milk')\n print(str(resource[2]) + ' of coffee beans')\n print(str(resource[3]) + ' of disposable cups')\n if resource[4] == 0:\n print(str(resource[4]) + ' of money')\n else:\n print('$' + str(resource[4]) + ' of money')\n\n\ndef write_action():\n action = str(input('\\n' + 'Write action (buy, fill, take, remaining, exit):' + '\\n'))\n if action == 'exit':\n quit()\n elif action == 'remaining':\n print()\n result(resource)\n write_action()\n elif action == 'take':\n action_take()\n elif action == 'fill':\n action_fill()\n elif action == 'buy':\n action_buy()\n\n\ndef action_take():\n print()\n print('I gave you $' + str(resource[4]))\n resource[4] = 0\n write_action()\n\n\ndef action_fill():\n print()\n resource[0] += int(input('Write how many ml of water do you want to add:' + '\\n'))\n resource[1] += int(input('Write how many ml of milk do you want to add:' + '\\n'))\n resource[2] += int(input('Write how many grams of coffee beans do you want to add:' + '\\n'))\n resource[3] += int(input('Write how many disposable cups of coffee do you want to add:' + '\\n'))\n write_action()\n\n\ndef check_resource(coffee):\n for i in range(len(resource) - 1):\n if resource[i] - coffee[i] < 0:\n print('Sorry, not enough resource!')\n write_action()\n else:\n print('I have enough resources, making you a coffee!')\n resource_calculation(coffee)\n\n\ndef resource_calculation(coffee):\n global resource\n for i in range(len(resource) - 1):\n new_resource[i] = resource[i] - coffee[i]\n new_resource[4] = resource[4] + coffee[4]\n resource = new_resource\n write_action()\n\n\ndef action_buy():\n print()\n coffee = str(input('What do you want to buy? 1 - espresso, 2 - latte, 3 - cappuccino, back - to main menu:' + '\\n'))\n if coffee == 'back':\n write_action()\n elif coffee == '1':\n check_resource(espresso)\n elif coffee == '2':\n check_resource(latte)\n elif coffee == '3':\n check_resource(cappuccino)\n\n\nwrite_action()\n","sub_path":"Coffee Machine/task/machine/coffee_machine.py","file_name":"coffee_machine.py","file_ext":"py","file_size_in_byte":2407,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"49730651","text":"# Copyright 2020 Sonatype Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\nimport json\nfrom fpdf import FPDF\nimport datetime\nimport time\nimport plotly.graph_objects as go\nimport argparse\nimport statistics\n\nparser = argparse.ArgumentParser(description='generate insights report')\nparser.add_argument('-all','--insightsAll', help='generates insights report for all violations', action='store_true', required=False)\nparser.add_argument('-s','--insightsSec', help='generates insights report only for Security violations', action='store_true', required=False)\nparser.add_argument('-l','--insightsLic', help='generates insights report only for Licensing violations', action='store_true', required=False)\nparser.add_argument('-before','--beforeFile', help='enter the path to the earlier json file to compare',dest='jsonBefore', action='store', required=True)\nparser.add_argument('-after','--afterFile', help='enter the path to the later json file to compare',dest='jsonAfter', action='store', required=True)\n\nargs = vars(parser.parse_args())\n\nxtitle = [\"Date\", \"Applications\", \"Organisations\"]\nfilenameBefore = args['jsonBefore']\nfilenameAfter = args['jsonAfter']\nsonatype_colours = ['rgb(0,106,197)','rgb(253,198,22)','rgb(246,128,4)','rgb(205,0,40)']\ndisfixwai_colours = ['rgb(245,69,44)','rgb(0,209,146)','rgb(101,104,255)']\nfrom datetime import date\ntoday = datetime.datetime.today()\ntoday = today.strftime(\"%Y-%m-%d %H:%M:%S\")\n\n\nwith open(filenameBefore, 'r') as f1:\n report1 = json.load(f1)\n summary1 = report1[\"summary\"]\n apps1 = report1[\"apps\"]\n licences1 = report1[\"licences\"]\n Security1 = report1[\"security\"]\n appCount1 = len(apps1)\n\nwith open(filenameAfter, 'r') as f2:\n report2 = json.load(f2)\n summary2 = report2[\"summary\"]\n apps2 = report2[\"apps\"]\n licences2 = report2[\"licences\"]\n Security2 = report2[\"security\"]\n appCount2 = len(apps2)\n\n#print(str(appCount1)+\" , \"+str(appCount2))\n\n# Print iterations progress\ndef printProgressBar (\n iteration, \n total, \n prefix = 'Progress:', \n suffix = 'Complete', \n decimals = 1, \n length = 50, \n fill = '█'):\n\n time.sleep(0.1)\n percent = (\"{0:.\" + str(decimals) + \"f}\").format(100 * (iteration / float(total)))\n filledLength = int(length * iteration // total)\n bar = fill * filledLength + '-' * (length - filledLength)\n print('\\r%s |%s| %s%% %s' % (prefix, bar, percent, suffix), end = '\\r')\n # Print New Line on Complete\n if iteration == total: \n print()\n\n#---------------------------------\n# Chart/pdf functions\n\ndef make_chart(period, data, filename, title, xtitle):\n fig = go.Figure(\n data=[ go.Bar(x=period, y=data, textposition='auto') ], \n layout_title_text=title\n )\n\n fig.update_layout(autosize=False, width=864, height=528, xaxis=go.layout.XAxis(title_text=xtitle))\n fig.update_xaxes(tickvals=period,automargin=True)\n\n fig.write_image(filename)\n\ndef make_stacked_chart(period, data, legend, filename, title, xtitle,colours):\n traces = []\n for i in range(0, len(data)):\n trace = go.Bar(\n name = legend[i],\n x = period,\n y = data[i],\n textposition = 'auto',\n marker = dict(color=colours[i])\n )\n traces.append(trace)\n\n fig = go.Figure(data=traces, layout_title_text=title)\n fig.update_layout(\n barmode='stack',\n autosize=False,\n width=840,\n height=528,\n xaxis=go.layout.XAxis(\n title_text=xtitle\n )\n )\n fig.update_xaxes(tickvals=period,automargin=True)\n fig.write_image(filename)\n\ndef make_group_chart(period, data, legend, filename, title, xtitle,colours):\n traces = []\n for i in range(0, len(data)):\n trace = go.Bar(\n name = legend[i],\n x = period,\n y = data[i],\n textposition = 'auto',\n marker = dict(color=colours[i])\n )\n traces.append(trace)\n\n fig = go.Figure(data=traces, layout_title_text=title)\n fig.update_layout(\n barmode='group',\n autosize=False,\n width=840,\n height=528,\n xaxis=go.layout.XAxis(\n title_text=xtitle\n )\n )\n fig.update_xaxes(tickvals=period,automargin=True)\n fig.write_image(filename)\n\n\n\n#---------------------------------\n\nclass PDF(FPDF):\n def header(self):\n # Logo\n self.image('sonatype_logo.png', 10, 8, 33)\n # Times bold 15\n self.set_font('Times', 'B', 15)\n # Move to the right\n self.cell(80)\n # Title\n self.cell(100, 10, 'Success Metrics report', 1, 0, 'C')\n # Line break\n self.ln(20)\n\n # Page footer\n def footer(self):\n # Position at 1.5 cm from bottom\n self.set_y(-15)\n # Arial italic 8\n self.set_font('Times', 'I', 8)\n # Page number\n self.cell(0, 10, 'Page ' + str(self.page_no()) + '/{nb}', 0, 0, 'C')\n\n #Chapter title\n def chapter_title(self, title):\n # Arial 12\n self.set_font('Times', 'B', 12)\n # Background color\n self.set_fill_color(200, 220, 255)\n # Title\n self.cell(0, 6, '%s' % (title), 0, 1, 'L', 1)\n # Line break\n self.ln(0)\n\n #Chapter body\n def chapter_body(self, content_dict):\n # Times 12\n self.set_font('Times', '', 12)\n # Output justified text\n #self.multi_cell(0, 5, content)\n for field in content_dict:\n self.cell(0, 5, field+\": \"+content_dict[field], 1, 1)\n # Line break\n self.ln()\n\n #Print chapter\n def print_chapter(self, title, content):\n self.add_page('L')\n self.chapter_title(title)\n self.chapter_body(content)\n\n def print_list(self,data):\n self.cell()\n\n def fancy_table(this,header,data):\n #Colors, line width and bold font\n this.set_fill_color(255,0,0)\n this.set_text_color(255)\n this.set_draw_color(128,0,0)\n this.set_line_width(.3)\n this.set_font('Times','B')\n #Header\n w=[]\n column_no = len(header)\n page_width = 277 #magic number for A4 in mm\n column_width = page_width/column_no\n for i in range(0,column_no):\n w.append(column_width)\n for i in range(0,column_no):\n this.cell(w[i],7,header[i],1,0,'C',1)\n this.ln()\n #Color and font restoration\n this.set_fill_color(224,235,255)\n this.set_text_color(0)\n this.set_font('Times')\n #Data\n fill=0\n #print(\"This data: \")\n #print(len(data))\n #print(len(w))\n #print(column_no)\n for row in data:\n for i in range(0,column_no):\n this.cell(w[i],6,row[i],'LR',0,'C',fill)\n #print(row[i])\n this.ln()\n fill=not fill\n this.cell(sum(w),0,'','T')\n\n\n#---------------------------------\n\ndef output_pdf(pages, filename):\n\tpdf = FPDF()\n\tpdf.set_font('Times','B',12)\n\tfor image in pages:\n\t\tpdf.add_page('L')\n\t\tpdf.set_xy(0,0)\n\t\tpdf.image(image, x = None, y = None, w = 0, h = 0, type = '', link = '')\n\tpdf.output(filename, 'F')\n\n\n#---------------------------------\n\ndef nonzeroAvg(metric,percentage,integer):\n nonzero = 0\n aux = 0\n for i in range(0,len(metric)):\n if metric[i] != 0:\n aux += metric[i]\n nonzero += 1\n if nonzero == 0:\n nonzero = 1\n if percentage == True:\n output = round((aux / nonzero) * 100,1)\n elif integer == True:\n output = int(aux / nonzero)\n else:\n output = round(aux / nonzero,1)\n return(output)\n\n#---------------------------------\n\ndef average(numerator,denominator,percentage,integer):\n if denominator == 0:\n denominator = 1\n if percentage == True:\n output = round((numerator / denominator) * 100,1)\n elif integer == True:\n output = int(numerator / denominator)\n else:\n output = round(numerator / denominator,1)\n return(output)\n#---------------------------------\n\ndef weeksWithData(scope):\n aux = 0\n stop = 0\n for week in range(0,len(scope)):\n if scope[week] == 0 and stop == 0:\n aux += 1\n elif scope[week] != 0:\n stop = 1\n output = len(scope) - aux \n return(output)\n\n#---------------------------------\n\ndef getScope(scope1,scope2):\n S1 = set(scope1)\n S2 = set(scope2)\n inter = S1.intersection(S2)\n #print(inter)\n if inter != {}:\n if scope2[-1] >= scope1[-1]:\n index = scope2.index(scope1[-1])\n scope = scope2[index+1:]\n elif scope1[-1] > scope2[-1]:\n print(\"The date ranges for before and after json files are swapped. Please, run the command again but swapping the files for before and after. \\nExiting...\")\n raise SystemExit\n if scope == []:\n print(\"The date ranges for before and after json files are identical. There is no delta to analyse. \\nExiting...\")\n raise SystemExit\n #print(\"scope1: \"+str(scope1))\n #print(\"scope2: \"+str(scope2))\n #print(\"index: \"+str(index))\n #print(\"scope1[-1]: \"+str(scope1[-1]))\n #print(\"length of scope1: \"+str(len(scope1)))\n #print(\"length of scope2: \"+str(len(scope2)))\n #print(\"scope: \"+str(scope))\n else:\n print(\"The date ranges for before and after json files do not intersect. There is a gap in the data. \\nPlease generate new json files extending the date ranges so that both json files intersect. \\nExiting...\")\n raise SystemExit\n return(scope)\n\n#---------------------------------\n\n#INSIGHTS: Insights report (comparison between two different json files)\ndef insights(apps1,apps2,summary1,summary2,report):\n\n pages, t, graphNo = [], 0, 2\n appName, orgName, OpeLow, OpeMod, OpeSev, OpeCri, mttrLow, mttrMod, mttrSev, mttrCri = [],[],[],[],[],[],[],[],[],[]\n printProgressBar(t,graphNo)\n \n pdf = PDF()\n pdf.alias_nb_pages()\n\n if report == 'summary':\n selector = 'TOTAL'\n if report == 'security':\n selector = 'SECURITY'\n if report == 'licences':\n selector = 'LICENSE'\n\n ################################\n #Loading data for json1 (before)\n ################################\n header_Open_App1 = ['Application', 'Critical','Severe','Moderate','Low']\n data_Open_App1= []\n for app in apps1:\n critical1 = app[report]['openCountsAtTimePeriodEnd'][selector]['CRITICAL']['rng'][-1]\n severe1 = app[report]['openCountsAtTimePeriodEnd'][selector]['SEVERE']['rng'][-1]\n moderate1 = app[report]['openCountsAtTimePeriodEnd'][selector]['MODERATE']['rng'][-1]\n low1 = app[report]['openCountsAtTimePeriodEnd'][selector]['LOW']['rng'][-1]\n aux1 = [critical1,severe1,moderate1,low1]\n data_Open_App1.append([app['applicationName']] + aux1)\n data_Open_App1.sort(key = lambda data_Open_App1: data_Open_App1[1], reverse = True)\n aux1=[]\n if len(data_Open_App1) <= 100:\n for i in range(0,len(data_Open_App1)):\n aux1.append([data_Open_App1[i][0],str(data_Open_App1[i][1]),str(data_Open_App1[i][2]),str(data_Open_App1[i][3]),str(data_Open_App1[i][4])])\n else:\n for i in range(0,100):\n aux1.append([data_Open_App1[i][0],str(data_Open_App1[i][1]),str(data_Open_App1[i][2]),str(data_Open_App1[i][3]),str(data_Open_App1[i][4])])\n data_Open_App1 = aux1\n ###########################\n\n ################################\n #Loading data for json2 (after)\n ################################\n header_Open_App2 = ['Application', 'Critical','Severe','Moderate','Low']\n data_Open_App2= []\n for app in apps2:\n critical2 = app[report]['openCountsAtTimePeriodEnd'][selector]['CRITICAL']['rng'][-1]\n severe2 = app[report]['openCountsAtTimePeriodEnd'][selector]['SEVERE']['rng'][-1]\n moderate2 = app[report]['openCountsAtTimePeriodEnd'][selector]['MODERATE']['rng'][-1]\n low2 = app[report]['openCountsAtTimePeriodEnd'][selector]['LOW']['rng'][-1]\n aux2 = [critical2,severe2,moderate2,low2]\n data_Open_App2.append([app['applicationName']] + aux2)\n data_Open_App2.sort(key = lambda data_Open_App2: data_Open_App2[1], reverse = True)\n aux2=[]\n if len(data_Open_App2) <= 100:\n for i in range(0,len(data_Open_App2)):\n aux2.append([data_Open_App2[i][0],str(data_Open_App2[i][1]),str(data_Open_App2[i][2]),str(data_Open_App2[i][3]),str(data_Open_App2[i][4])])\n else:\n for i in range(0,100):\n aux2.append([data_Open_App2[i][0],str(data_Open_App2[i][1]),str(data_Open_App2[i][2]),str(data_Open_App2[i][3]),str(data_Open_App2[i][4])])\n data_Open_App2 = aux2\n ###########################\n\n scope = getScope(summary1[\"dates\"],summary2[\"dates\"]) \n weeks = len(scope)\n weeks1 = weeksWithData(summary1[\"weeks\"])\n weeks2 = weeksWithData(summary2[\"weeks\"])\n\n onboarded = summary2[\"appOnboard\"][-1] - summary1[\"appOnboard\"][-1]\n onboarded1 = summary1[\"appOnboard\"][-1]\n onboarded2 = summary2[\"appOnboard\"][-1]\n weeklyOnboard = average(onboarded,weeks,0,0)\n weeklyOnboard1 = average(onboarded1,weeks1,0,0)\n weeklyOnboard2 = average(onboarded2,weeks2,0,0)\n\n scanned1 = sum(summary1[\"appNumberScan\"])\n scanned2 = sum(summary2[\"appNumberScan\"])\n scanned = summary2[\"appNumberScan\"][-weeks:]\n #print(\"scanned: \"+str(scanned))\n weeklyScanned = average(sum(scanned),weeks,0,0)\n weeklyScanned1 = average(scanned1,weeks1,0,0)\n\n scans = sum(summary2[\"weeklyScans\"]) - sum(summary1[\"weeklyScans\"])\n scans1 = sum(summary1[\"weeklyScans\"])\n scans2 = sum(summary2[\"weeklyScans\"])\n if scans < 0:\n scans = scans2\n weeklyScans = average(scans,weeks,0,0)\n weeklyScans1 = average(scans1,weeks1,0,0)\n weeklyScans2 = average(scans2,weeks2,0,0)\n\n discovered = sum(summary2[\"discoveredCounts\"][\"TOTAL\"]) - sum(summary1[\"discoveredCounts\"][\"TOTAL\"])\n discovered1 = sum(summary1[\"discoveredCounts\"][\"TOTAL\"])\n discovered2 = sum(summary2[\"discoveredCounts\"][\"TOTAL\"])\n if discovered < 0:\n discovered = discovered2\n weeklyDiscovered = average(discovered,weeks,0,0)\n weeklyDiscovered1 = average(discovered1,weeks1,0,0)\n weeklyDiscovered2 = average(discovered2,weeks2,0,0)\n \n disCri = sum(summary2[\"discoveredCounts\"][\"CRITICAL\"]) - sum(summary1[\"discoveredCounts\"][\"CRITICAL\"])\n disCri1 = sum(summary1[\"discoveredCounts\"][\"CRITICAL\"])\n disCri2 = sum(summary2[\"discoveredCounts\"][\"CRITICAL\"])\n\n if disCri < 0:\n disCri = disCri2\n weeklyDisCri = average(disCri,weeks,0,0)\n weeklyDisCri1 = average(disCri1,weeks1,0,0)\n weeklyDisCri2 = average(disCri2,weeks2,0,0)\n\n \n if len(data_Open_App1) > 0:\n mostCri = data_Open_App2[0][0]\n mostCriVal = data_Open_App2[0][1]\n else:\n mostCri = \"Error: No applications found!\"\n mostCriVal = 0\n if len(data_Open_App2) > 0:\n leastCri = data_Open_App2[-1][0]\n leastCriVal = data_Open_App2[-1][1]\n else:\n leastCri = \"Error: No applications found!\"\n leastCriVal = 0\n\n fixed = sum(summary2[\"fixedCounts\"][\"TOTAL\"]) - sum(summary1[\"fixedCounts\"][\"TOTAL\"])\n fixed1 = sum(summary1[\"fixedCounts\"][\"TOTAL\"])\n fixed2 = sum(summary2[\"fixedCounts\"][\"TOTAL\"])\n if fixed < 0:\n fixed = fixed2\n weeklyFixed = average(fixed,weeks,0,0)\n weeklyFixed1 = average(fixed1,weeks1,0,0)\n weeklyFixed2 = average(fixed2,weeks2,0,0)\n \n fixedCri = sum(summary2[\"fixedCounts\"][\"CRITICAL\"]) - sum(summary1[\"fixedCounts\"][\"CRITICAL\"])\n fixedCri1 = sum(summary1[\"fixedCounts\"][\"CRITICAL\"])\n fixedCri2 = sum(summary2[\"fixedCounts\"][\"CRITICAL\"])\n\n if fixedCri < 0:\n fixedCri = fixedCri2\n weeklyFixedCri = average(fixedCri,weeks,0,0)\n weeklyFixedCri1 = average(fixedCri1,weeks1,0,0)\n weeklyFixedCri2 = average(fixedCri2,weeks2,0,0)\n\n\n waived = sum(summary2[\"waivedCounts\"][\"TOTAL\"]) - sum(summary1[\"waivedCounts\"][\"TOTAL\"])\n waived1 = sum(summary1[\"waivedCounts\"][\"TOTAL\"])\n waived2 = sum(summary2[\"waivedCounts\"][\"TOTAL\"])\n if waived < 0:\n waived = waived2\n weeklyWaived = average(waived,weeks,0,0)\n weeklyWaived1 = average(waived1,weeks1,0,0)\n weeklyWaived2 = average(waived2,weeks2,0,0)\n waivedCri = sum(summary2[\"waivedCounts\"][\"CRITICAL\"]) - sum(summary1[\"waivedCounts\"][\"CRITICAL\"])\n waivedCri1 = sum(summary1[\"waivedCounts\"][\"CRITICAL\"])\n waivedCri2 = sum(summary2[\"waivedCounts\"][\"CRITICAL\"])\n\n if waivedCri < 0:\n waivedCri = waivedCri2\n weeklyWaivedCri = average(waivedCri,weeks,0,0)\n weeklyWaivedCri1 = average(waivedCri1,weeks1,0,0)\n weeklyWaivedCri2 = average(waivedCri2,weeks2,0,0)\n\n\n opened1 = summary1[\"openCountsAtTimePeriodEnd\"][\"TOTAL\"][-1]\n opened2 = summary2[\"openCountsAtTimePeriodEnd\"][\"TOTAL\"][-1]\n openedCri1 = summary1[\"openCountsAtTimePeriodEnd\"][\"CRITICAL\"][-1]\n openedCri2 = summary2[\"openCountsAtTimePeriodEnd\"][\"CRITICAL\"][-1]\n \n dealt = fixed + waived\n if discovered > 0:\n dealtRate = round((dealt / discovered) * 100,1)\n else:\n dealtRate = 0\n dealt1 = fixed1 + waived1\n if discovered1 > 0:\n dealtRate1 = round((dealt1 / discovered1) * 100,1)\n else:\n dealtRate1 = 0\n \n riskRatio = [float(i) for i in summary2[\"riskRatioCritical\"]]\n riskRatio = riskRatio[-weeks:]\n riskRatioAvg = average(sum(riskRatio),weeks,0,0)\n riskRatio1 = [float(i) for i in summary1[\"riskRatioCritical\"]]\n riskRatioAvg1 = average(sum(riskRatio1),weeks1,0,0)\n\n sigma = round(statistics.stdev(riskRatio),1)\n sigma1 = round(statistics.stdev(riskRatio1),1)\n \n mttr = summary2[\"mttrCriticalThreat\"][-weeks:]\n mttrAvg = nonzeroAvg(mttr,0,0)\n mttr1 = summary1[\"mttrCriticalThreat\"]\n mttrAvg1 = nonzeroAvg(mttr1,0,0)\n\n\n if report == 'summary':\n pdf.print_chapter('Insights Summary (all violations)',\"\")\n elif report == 'security':\n pdf.print_chapter('Insights Summary (only security violations)',\"\")\n elif report =='licences':\n pdf.print_chapter('Insights Summary (only licensing violations)',\"\")\n \n content0 = \"Report run on: \"+str(today)+\" comparing \"+str(filenameBefore)+\" with \"+str(filenameAfter)+\" from w/c \"+str(scope[0])+\" to w/c \"+str(scope[-1])\n pdf.multi_cell(0,5,content0,0)\n pdf.ln(10)\n \n content1 = \"During the \"+str(weeks)+\" weeks in scope, your organisation:\"\n pdf.set_font('Times', 'B', 24)\n pdf.cell(0,0,content1,0)\n pdf.ln(10)\n pdf.set_font('Times', 'B', 18)\n \n content2 = \"Onboarded \"+str(onboarded)+\" applications (going from \"+str(onboarded1)+\" to \"+str(onboarded2)+\" apps), at an average of \"+str(weeklyOnboard)+\" per week (previously \"+str(weeklyOnboard1)+\" apps onboarded per week).\"\n pdf.multi_cell(0,7,content2,0)\n pdf.ln(1)\n if weeklyOnboard > weeklyOnboard1:\n content21 = \"This represents a \"+str(round(average(weeklyOnboard,weeklyOnboard1,1,0) - 100,1))+\"% increase in the onboarding rate.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content21,0)\n elif weeklyOnboard < weeklyOnboard1:\n content21 = \"This represents a \"+str(round(100 - average(weeklyOnboard,weeklyOnboard1,1,0),1))+\"% reduction in the onboarding rate. Have all apps been onboarded yet?\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content21,0)\n elif onboarded1 == onboarded2:\n content21 = \"No new applications have been onboarded during this time period. Have all apps been onboarded yet?\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content21,0)\n else:\n content21 = \"This represents a stable onboarding pattern.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content21,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n\n content3 = \"Scanned applications at an average of \"+str(weeklyScanned)+\" apps scanned per week (previously \"+str(weeklyScanned1)+\" apps scanned per week). Scanning coverage is \"+str(round(average(weeklyScanned,onboarded2,1,0),1))+\"% (percentage of total apps scanned).\"\n pdf.multi_cell(0,7,content3,0)\n pdf.ln(1)\n if weeklyScanned > weeklyScanned1:\n content31 = \"This represents a \"+str(round(average(weeklyScanned,weeklyScanned1,1,0) - 100,1))+\"% increase in the scanning coverage rate.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content31,0)\n elif weeklyScanned < weeklyScanned1:\n content31 = \"This represents a \"+str(round(100 - average(weeklyScanned,weeklyScanned1,1,0),1))+\"% reduction in the scanning coverage rate.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content31,0)\n elif scanned == 0:\n content31 = \"No applications have been scanned during this time period. Is there a problem with the CI integration or with the uptake of IQ within the development teams?\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content31,0)\n else:\n content31 = \"This represents a stable app scanning pattern.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content31,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n \n content4 = \"Performed \"+str(scans)+\" scans (previously \"+str(scans1)+\" scans) at an average of \"+str(weeklyScans)+\" scans per week (previously \"+str(weeklyScans1)+\" scans per week).\"\n pdf.multi_cell(0,7,content4,0)\n pdf.ln(1)\n if weeklyScans > weeklyScans1:\n content41 = \"This represents a \"+str(round(average(weeklyScans,weeklyScans1,1,0) - 100,1))+\"% increase in the scanning rate.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content41,0)\n elif weeklyScans < weeklyScans1:\n content41 = \"This represents a \"+str(round(100 - average(weeklyScans,weeklyScans1,1,0),1))+\"% reduction in the scanning rate.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content41,0)\n elif scans == 0:\n content41 = \"No scans have been performed during this time period. Is there a problem with the CI integration or with the uptake of IQ within the development teams?\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content41,0)\n else:\n content41 = \"This represents a stable scanning pattern.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content41,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n\n\n content5 = \"Discovered \"+str(discovered)+\" new violations at an average of \"+str(weeklyDiscovered)+\" discovered per week (previously \"+str(weeklyDiscovered1)+\" discovered per week). \\nOf these, \"+str(disCri)+\" were Critical at an average of \"+str(weeklyDisCri)+\" discovered Criticals per week (previously \"+str(weeklyDisCri1)+\" discovered Criticals per week).\"\n\n pdf.multi_cell(0,7,content5,0)\n pdf.ln(1)\n if weeklyDiscovered > weeklyDiscovered1:\n content51 = \"This represents a \"+str(round(average(weeklyDiscovered,weeklyDiscovered1,1,0) - 100,1))+\"% increase in the discovery rate. This could indicate that development teams are not selecting safer OSS components. Have you integrated the IDE plugins and Chrome extension?\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content51,0)\n elif weeklyDiscovered < weeklyDiscovered1:\n content51 = \"This represents a \"+str(round(100 - average(weeklyDiscovered,weeklyDiscovered1,1,0),1))+\"% reduction in the discovery rate. This could indicate that development teams are selecting safer OSS components, hence shifting left.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content51,0)\n elif discovered == 0 and scans != 0:\n content51 = \"No new discovered violations during this time period. This could indicate that development teams are selecting safer OSS components, hence shifting left.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content51,0)\n else:\n content51 = \"This represents a stable discovery rate.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content51,0)\n pdf.ln(1)\n pdf.set_text_color(0, 0, 0)\n if (weeklyDisCri > weeklyDisCri1) and (weeklyDiscovered >= weeklyDiscovered1):\n content52 = \"This also represents a \"+str(round(average(weeklyDisCri,weeklyDisCri1,1,0) - 100,1))+\"% increase in the discovery rate for Critical violations.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content52,0)\n elif (weeklyDisCri > weeklyDisCri1) and (weeklyDiscovered < weeklyDiscovered1):\n content52 = \"However, there is a \"+str(round(average(weeklyDisCri,weeklyDisCri1,1,0) - 100,1))+\"% increase in the discovery rate for Critical violations.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content52,0)\n elif (weeklyDisCri < weeklyDisCri1) and (weeklyDiscovered >= weeklyDiscovered1):\n content52 = \"However, there is a \"+str(round(100 - average(weeklyDisCri,weeklyDisCri1,1,0),1))+\"% reduction in the discovery rate for Critical violations.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content52,0)\n\n elif (weeklyDisCri < weeklyDisCri1) and (weeklyDiscovered < weeklyDiscovered1):\n content52 = \"This also represents a \"+str(round(100 - average(weeklyDisCri,weeklyDisCri1,1,0),1))+\"% reduction in the discovery rate for Critical violations.\"\n\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content52,0) \n else:\n content52 = \"This represents a stable discovery rate for Critical violations.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content52,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n\n\n content6 = \"Fixed \"+str(fixed)+\" violations from your open backlog at an average of \"+str(weeklyFixed)+\" fixed per week (previously \"+str(weeklyFixed1)+\" fixed per week). \\nOf these, \"+str(fixedCri)+\" were Critical at an average of \"+str(weeklyFixedCri)+\" fixed Criticals per week (previously \"+str(weeklyFixedCri1)+\" fixed Criticals per week).\"\n\n pdf.multi_cell(0,7,content6,0)\n pdf.ln(1)\n if weeklyFixed > weeklyFixed1:\n content61 = \"This represents a \"+str(round(average(weeklyFixed,weeklyFixed1,1,0) - 100,1))+\"% increase in the fixing rate.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content61,0)\n elif weeklyFixed < weeklyFixed1:\n content61 = \"This represents a \"+str(round(100 - average(weeklyFixed,weeklyFixed1,1,0),1))+\"% reduction in the fixing rate.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content61,0)\n else:\n content61 = \"This represents a stable fixing rate.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content61,0)\n pdf.ln(1)\n pdf.set_text_color(0, 0, 0)\n if (weeklyFixedCri > weeklyFixedCri1) and (weeklyFixed >= weeklyFixed1):\n content62 = \"This also represents a \"+str(round(average(weeklyFixedCri,weeklyFixedCri1,1,0) - 100,1))+\"% increase in the fixing rate for Critical violations.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content62,0)\n elif (weeklyFixedCri > weeklyFixedCri1) and (weeklyFixed < weeklyFixed1):\n content62 = \"However, there is a \"+str(round(average(weeklyFixedCri,weeklyFixedCri1,1,0) - 100,1))+\"% increase in the fixing rate for Critical violations.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content62,0)\n elif (weeklyFixedCri < weeklyFixedCri1) and (weeklyFixed >= weeklyFixed1):\n content62 = \"However, there is a \"+str(round(100 - average(weeklyFixedCri,weeklyFixedCri1,1,0),1))+\"% reduction in the fixing rate for Critical violations.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content62,0)\n\n elif (weeklyFixedCri < weeklyFixedCri1) and (weeklyFixed < weeklyFixed1):\n content62 = \"This also represents a \"+str(round(100 - average(weeklyFixedCri,weeklyFixedCri1,1,0),1))+\"% reduction in the fixing rate for Critical violations.\"\n\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content62,0) \n else:\n content62 = \"This represents a stable fixing rate for Critical violations.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content62,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n\n content7 = \"Waived \"+str(waived)+\" violations at an average of \"+str(weeklyWaived)+\" waived per week (previously \"+str(weeklyWaived1)+\" waived per week).\\nOf these, \"+str(waivedCri)+\" were Critical at an average of \"+str(weeklyWaivedCri)+\" waived Criticals per week (previously \"+str(weeklyWaivedCri1)+\" waived Criticals per week).\"\n pdf.multi_cell(0,7,content7,0)\n pdf.ln(1)\n if weeklyWaived > weeklyWaived1:\n content71 = \"This represents a \"+str(round(average(weeklyWaived,weeklyWaived1,1,0) - 100,1))+\"% increase in the waiving rate.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content71,0)\n elif weeklyWaived < weeklyWaived1:\n content71 = \"This represents a \"+str(round(100 - average(weeklyWaived,weeklyWaived1,1,0),1))+\"% reduction in the waiving rate.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content71,0)\n elif waived == 0:\n content71 = \"This means that waivers are not being used.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content71,0)\n else:\n content71 = \"This represents a stable waiving rate.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content71,0)\n pdf.ln(1)\n pdf.set_text_color(0, 0, 0)\n if (weeklyWaivedCri > weeklyWaivedCri1) and (weeklyWaived >= weeklyWaived1):\n content72 = \"This also represents a \"+str(round(average(weeklyWaivedCri,weeklyWaivedCri1,1,0) - 100,1))+\"% increase in the waiving rate for Critical violations.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content72,0)\n elif (weeklyWaivedCri > weeklyWaivedCri1) and (weeklyWaived < weeklyWaived1):\n content72 = \"However, there is a \"+str(round(average(weeklyWaivedCri,weeklyWaivedCri1,1,0) - 100,1))+\"% increase in the waiving rate for Critical violations.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content72,0)\n elif (weeklyWaivedCri < weeklyWaivedCri1) and (weeklyWaived >= weeklyWaived1):\n content72 = \"However, there is a \"+str(round(100 - average(weeklyWaivedCri,weeklyWaivedCri1,1,0),1))+\"% reduction in the waiving rate for Critical violations.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content72,0)\n\n elif (weeklyWaivedCri < weeklyWaivedCri1) and (weeklyWaived < weeklyWaived1):\n content72 = \"This also represents a \"+str(round(100 - average(weeklyWaivedCri,weeklyWaivedCri1,1,0),1))+\"% reduction in the waiving rate for Critical violations.\"\n\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content72,0) \n elif waivedCri == 0:\n content72 = \"This means that waivers are not used for Critical violations.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content72,0)\n else:\n content72 = \"This represents a stable waiving rate for Critical violations.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content72,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n \n content8 = \"Your organisation currently has \"+str(opened2)+\" open violations in their backlog (previously \"+str(opened1)+\" violations). Of these, \"+str(openedCri2)+\" were Critical (previously \"+str(openedCri1)+\" were Critical).\"\n pdf.multi_cell(0,7,content8,0)\n pdf.ln(1)\n if opened2 > opened1:\n content81 = \"This represents a \"+str(round(average(opened2,opened1,1,0) - 100,1))+\"% increase in violations in the backlog.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content81,0)\n elif opened2 < opened1:\n content81 = \"This represents a \"+str(round(100 - average(opened2,opened1,1,0),1))+\"% reduction in violations in the backlog.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content81,0)\n else:\n content81 = \"There were the same number of violations in the open backlog at the beginning and at the end of the period in scope.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content81,0)\n pdf.ln(1)\n pdf.set_text_color(0, 0, 0)\n if (openedCri2 > openedCri1) and (opened2 >= opened1):\n content82 = \"This also represents a \"+str(round(average(openedCri2,openedCri1,1,0) - 100,1))+\"% increase in Critical violations in the backlog.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content82,0)\n elif (openedCri2 > openedCri1) and (opened2 < opened1):\n content82 = \"However, there is a \"+str(round(average(openedCri2,openedCri1,1,0) - 100,1))+\"% increase in Critical violations in the backlog.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content82,0)\n elif (openedCri2 < openedCri1) and (opened2 >= opened1):\n content82 = \"However, there is a \"+str(round(100 - average(openedCri2,openedCri1,1,0),1))+\"% reduction in Critical violations in the backlog.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content82,0)\n elif (openedCri2 < openedCri1) and (opened2 < opened1):\n content82 = \"This also represents a \"+str(round(100 - average(openedCri2,openedCri1,1,0),1))+\"% reduction in Critical violations in the backlog.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content82,0) \n else:\n content82 = \"There were the same number of Critical violations in the open backlog at the beginning and at the end of the period in scope.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content82,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n \n content9 = \"Your organisation currently has a Backlog Dealing rate ((Fixed + Waived) / Discovered) of \"+str(dealtRate)+\"% (previously it was \"+str(dealtRate1)+\"%).\"\n pdf.multi_cell(0,7,content9,0)\n pdf.ln(1)\n if dealtRate > dealtRate1:\n content91 = \"This represents a \"+str(round(average(dealtRate,dealtRate1,1,0) - 100,1))+\"% increase in the Backlog Dealing rate, which means that the backlog is reducing.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content91,0)\n elif dealtRate < dealtRate1:\n content91 = \"This represents a \"+str(round(100 - average(dealtRate,dealtRate1,1,0),1))+\"% reduction in the Backlog Dealing rate, which means that the backlog is increasing.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content91,0)\n else:\n content91 = \"The Backlog Dealing rate was the same at the beginning and at the end of the period in scope.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content91,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n \n content10 = \"On average, each application had \"+str(round(riskRatioAvg,1))+\" open Critical violations (previously \"+str(round(riskRatioAvg1,1))+\" open Critical violations).\"\n pdf.multi_cell(0,7,content10,0)\n pdf.ln(1)\n if riskRatioAvg > riskRatioAvg1:\n content101 = \"This represents a \"+str(round(average(riskRatioAvg,riskRatioAvg1,1,0) - 100,1))+\"% increase in the risk ratio.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content101,0)\n elif riskRatioAvg < riskRatioAvg1:\n content101 = \"This represents a \"+str(round(100 - average(riskRatioAvg,riskRatioAvg1,1,0),1))+\"% reduction in the risk ratio.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content101,0)\n else:\n content101 = \"The risk ratio was the same at the beginning and at the end of the period in scope.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content101,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n\n content11 = \"The standard deviation was \"+str(sigma)+\" open Critical violations (previously \"+str(sigma1)+\" open Critical violations).\"\n pdf.multi_cell(0,7,content11,0)\n pdf.ln(1)\n if sigma > sigma1:\n content111 = \"This represents a \"+str(round(average(sigma,sigma1,1,0) - 100,1))+\"% increase in the spread of Critical violations.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content111,0)\n elif sigma < sigma1:\n content111 = \"This represents a \"+str(round(100 - average(sigma,sigma1,1,0),1))+\"% reduction in the spread of Critical violations.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content111,0)\n else:\n content111 = \"The standard deviation was the same at the beginning and at the end of the period in scope.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content111,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n\n #-------------------------------------------------------------------------\n ################################\n #Loading data for json2 (after)\n ################################\n header_Open_App = ['Application', 'Critical','Severe','Moderate','Low']\n data_Open_App= []\n for app in apps2:\n critical2 = app[report]['openCountsAtTimePeriodEnd'][selector]['CRITICAL']['rng'][-1]\n severe2 = app[report]['openCountsAtTimePeriodEnd'][selector]['SEVERE']['rng'][-1]\n moderate2 = app[report]['openCountsAtTimePeriodEnd'][selector]['MODERATE']['rng'][-1]\n low2 = app[report]['openCountsAtTimePeriodEnd'][selector]['LOW']['rng'][-1]\n aux2 = [critical2,severe2,moderate2,low2]\n data_Open_App.append([app['applicationName']] + aux2)\n data_Open_App.sort(key = lambda data_Open_App: data_Open_App[1], reverse = True)\n aux2=[]\n if len(data_Open_App) <= 100:\n for i in range(0,len(data_Open_App)):\n aux2.append([data_Open_App[i][0],str(data_Open_App[i][1]),str(data_Open_App[i][2]),str(data_Open_App[i][3]),str(data_Open_App[i][4])])\n else:\n for i in range(0,100):\n aux2.append([data_Open_App[i][0],str(data_Open_App[i][1]),str(data_Open_App[i][2]),str(data_Open_App[i][3]),str(data_Open_App[i][4])])\n \n for app in range(0,len(aux2)):\n if float(aux2[app][1]) >= riskRatioAvg+sigma:\n low_index = app\n data_Open_App = aux2[:low_index+1]\n\n if low_index > 0: \n content12 = \"Based on the current average and standard deviation, below is a table with the applications to be prioritised for remediation (all apps with more than \"+str(round(riskRatioAvg+sigma,1))+\" open Critical violations):\"\n pdf.multi_cell(0,7,content12,0)\n pdf.ln(5)\n\n pdf.fancy_table(header_Open_App, data_Open_App)\n pdf.ln(15)\n t +=1\n printProgressBar(t,graphNo)\n\n #---------------------------------------------------------------------\n\n pdf.set_font('Times', 'B', 18)\n content13 = \"It took an average of \"+str(mttrAvg)+\" days to fix Critical violations (previously \"+str(mttrAvg1)+\" days to fix Critical violations).\"\n\n pdf.cell(0,0,content13,0)\n pdf.ln(5)\n if mttrAvg > mttrAvg1:\n content131 = \"This represents a \"+str(round(average(mttrAvg,mttrAvg1,1,0) - 100,1))+\"% increase in the MTTR for Critical violations.\"\n pdf.set_text_color(255, 0, 0)\n pdf.multi_cell(0,7,content131,0)\n elif mttrAvg < mttrAvg1:\n content131 = \"This represents a \"+str(round(100 - average(mttrAvg,mttrAvg1,1,0),1))+\"% reduction in the MTTR for Critical violations.\"\n pdf.set_text_color(0, 153, 0)\n pdf.multi_cell(0,7,content131,0)\n else:\n content131 = \"The MTTR for Critical violations was the same at the beginning and at the end of the period in scope.\"\n pdf.set_text_color(0, 0, 255)\n pdf.multi_cell(0,7,content131,0)\n pdf.ln(10)\n pdf.set_text_color(0, 0, 0)\n\n\n t +=1\n printProgressBar(t,graphNo)\n\n ###########################\n\n \n #-------------------------------------------------------------------------\n return pdf\n\n\n#-------------------------------------------------------------------------\ndef insightsAll():\n pdf = insights(apps1,apps2,summary1,summary2,'summary')\n pdf.output('./output/insights_report_all.pdf', 'F')\n\n\n#-------------------------------------------------------------------------\ndef insightsSec():\n pdf = insights(apps1,apps2,Security1,Security2,'security')\n pdf.output('./output/insights_report_security.pdf', 'F')\n #print(\"Report not yet implemented\")\n#-------------------------------------------------------------------------\ndef insightsLic():\n pdf = insights(apps1,apps2,licences1,licences2,'licences')\n pdf.output('./output/insights_report_licences.pdf', 'F')\n #print(\"Report not yet implemented\")\n#-------------------------------------------------------------------------\n#-------------------------------------------------------------------------\n\n\ndef main():\n \n for report in args:\n if args[report] == True:\n exec(report+\"()\")\n \n\nif __name__ == \"__main__\":\n main()\n#raise SystemExit\n\n","sub_path":"insights.py","file_name":"insights.py","file_ext":"py","file_size_in_byte":41425,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"645025453","text":"# Created byMartin.cz\n# Copyright (c) Martin Strohalm. All rights reserved.\n\nimport weakref\n\n\nclass Proxy(object):\n \"\"\"\n This class encapsulates given callback function to enable weak references\n to instance methods as well as functions.\n \"\"\"\n \n \n def __init__(self, callback):\n \"\"\"\n Initializes a new instance of Proxy.\n \n Args:\n callback: callable\n Callback function or method to be encapsulated.\n \"\"\"\n \n # instance methods\n if hasattr(callback, '__self__'):\n self.obj = weakref.ref(callback.__self__)\n self.func = weakref.ref(callback.__func__)\n \n # direct function\n else:\n self.obj = None\n self.func = weakref.ref(callback)\n \n \n def __repr__(self):\n \"\"\"Gets debug string representation.\"\"\"\n \n return \"Proxy(%s)\" % self.callback\n \n \n def __call__(self, *args, **kwargs):\n \"\"\"Calls defined callback.\"\"\"\n \n self.callback(*args, **kwargs)\n \n \n def __eq__(self, other):\n \"\"\"Compares two proxies for equality.\"\"\"\n \n if not isinstance(other, Proxy):\n other = Proxy(other)\n \n if self.obj is other.obj:\n return self.func is other.func\n \n if self.obj is None or other.obj is None:\n return False\n \n return self.obj() is other.obj() and self.func() is other.func()\n \n \n def __ne__(self, other):\n \"\"\"Compares two proxies for non-equality.\"\"\"\n \n return not self.__eq__(other)\n \n \n @property\n def callback(self):\n \"\"\"Gets the callback.\"\"\"\n \n # direct function\n if self.obj is None:\n return self.func()\n \n # instance method\n obj = self.obj()\n if obj is not None:\n return getattr(obj, self.func().__name__)\n","sub_path":"pero/events/proxy.py","file_name":"proxy.py","file_ext":"py","file_size_in_byte":1949,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"101593518","text":"#\n# LSST Data Management System\n# Copyright 2014 LSST Corporation.\n#\n# This product includes software developed by the\n# LSST Project (http://www.lsst.org/).\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the LSST License Statement and\n# the GNU General Public License along with this program. If not,\n# see .\n#\n\"\"\"\nTests for lsst.afw.geom.XYTransform and xyTransformRegistry\n\"\"\"\nfrom __future__ import absolute_import, division, print_function\nimport math\nimport unittest\n\nfrom builtins import range\nfrom builtins import object\n\nimport lsst.utils.tests\nimport lsst.pex.exceptions\nfrom lsst.afw.geom import Extent2D, Point2D, xyTransformRegistry, OneXYTransformConfig, \\\n IdentityXYTransform, AffineXYTransform, RadialXYTransform\n\n\nclass RefMultiAffineTransform(object):\n\n def __init__(self, affineTransformList):\n self.affineTransformList = affineTransformList\n\n def __call__(self, point):\n for tr in self.affineTransformList:\n point = tr(point)\n return point\n\n\nclass RefMultiXYTransform(object):\n\n def __init__(self, transformList):\n self.transformList = transformList\n\n def forwardTransform(self, point):\n for tr in self.transformList:\n point = tr.forwardTransform(point)\n return point\n\n def reverseTransform(self, point):\n for tr in reversed(self.transformList):\n point = tr.reverseTransform(point)\n return point\n\n def linearizeForwardTransform(self, point):\n affineTransformList = [tr.linearizeForwardTransform(point) for\n tr in self.transformList]\n return RefMultiAffineTransform(affineTransformList)\n\n def linearizeReverseTransform(self, point):\n affineTransformList = [tr.linearizeReverseTransform(point) for\n tr in reversed(self.transformList)]\n return RefMultiAffineTransform(affineTransformList)\n\n\nclass XYTransformTestCase(unittest.TestCase):\n\n def fromIter(self):\n for x in (-1.1, 0, 2.2):\n for y in (3.1, 0, 2.1):\n yield Point2D(x, y)\n\n def checkBasics(self, transform):\n \"\"\"Check round trip and linearization of transform\n \"\"\"\n for fromPoint in self.fromIter():\n toPoint = transform.forwardTransform(fromPoint)\n roundTripPoint = transform.reverseTransform(toPoint)\n for i in range(2):\n self.assertAlmostEqual(fromPoint[i], roundTripPoint[i])\n\n for deltaFrom in (\n Extent2D(0),\n Extent2D(0.1, -0.1),\n Extent2D(-0.15, 0.1),\n ):\n tweakedFromPoint = fromPoint + deltaFrom\n tweakedToPoint = transform.forwardTransform(tweakedFromPoint)\n linToPoint = transform.linearizeForwardTransform(\n fromPoint)(tweakedFromPoint)\n linRoundTripPoint = transform.linearizeReverseTransform(\n toPoint)(tweakedToPoint)\n for i in range(2):\n self.assertAlmostEqual(\n tweakedToPoint[i], linToPoint[i], places=2)\n self.assertAlmostEqual(\n tweakedFromPoint[i], linRoundTripPoint[i], places=2)\n\n def checkConfig(self, tClass, tConfig, filePath):\n \"\"\"Check round trip of config\n \"\"\"\n tConfig.save(filePath)\n loadConfig = tConfig.__class__()\n loadConfig.load(filePath)\n transform = tClass(loadConfig)\n self.checkBasics(transform)\n\n def testIdentity(self):\n \"\"\"Test identity = IdentityXYTransform\n \"\"\"\n identClass = xyTransformRegistry[\"identity\"]\n with lsst.utils.tests.getTempFilePath(\".py\") as filePath:\n self.checkConfig(identClass, identClass.ConfigClass(), filePath)\n ident = identClass(identClass.ConfigClass())\n self.assertEqual(type(ident), IdentityXYTransform)\n self.checkBasics(ident)\n for fromPoint in self.fromIter():\n toPoint = ident.forwardTransform(fromPoint)\n for i in range(2):\n self.assertAlmostEqual(fromPoint[i], toPoint[i])\n\n def testInverted(self):\n \"\"\"Test inverted = InvertedXYTransform\n \"\"\"\n invertedClass = xyTransformRegistry[\"inverted\"]\n invertedConfig = invertedClass.ConfigClass()\n affineClass = xyTransformRegistry[\"affine\"]\n invertedConfig.transform.retarget(affineClass)\n affineConfig = invertedConfig.transform\n affineConfig.translation = (1.2, -3.4)\n with lsst.utils.tests.getTempFilePath(\".py\") as filePath:\n self.checkConfig(invertedClass, invertedConfig, filePath)\n inverted = invertedClass(invertedConfig)\n self.checkBasics(inverted)\n for fromPoint in self.fromIter():\n toPoint = inverted.forwardTransform(fromPoint)\n predToPoint = fromPoint - \\\n Extent2D(*invertedConfig.transform.translation)\n for i in range(2):\n self.assertAlmostEqual(toPoint[i], predToPoint[i])\n\n def testDefaultAffine(self):\n \"\"\"Test affine = AffineXYTransform with default coeffs (identity transform)\n \"\"\"\n affineClass = xyTransformRegistry[\"affine\"]\n affineConfig = affineClass.ConfigClass()\n with lsst.utils.tests.getTempFilePath(\".py\") as filePath:\n self.checkConfig(affineClass, affineConfig, filePath)\n affine = affineClass(affineConfig)\n self.assertEqual(type(affine), AffineXYTransform)\n self.checkBasics(affine)\n for fromPoint in self.fromIter():\n toPoint = affine.forwardTransform(fromPoint)\n for i in range(2):\n self.assertAlmostEqual(fromPoint[i], toPoint[i])\n\n def testTranslateAffine(self):\n \"\"\"Test affine = AffineXYTransform with just translation coefficients\n \"\"\"\n affineClass = xyTransformRegistry[\"affine\"]\n affineConfig = affineClass.ConfigClass()\n affineConfig.translation = (1.2, -3.4)\n with lsst.utils.tests.getTempFilePath(\".py\") as filePath:\n self.checkConfig(affineClass, affineConfig, filePath)\n affine = affineClass(affineConfig)\n for fromPoint in self.fromIter():\n toPoint = affine.forwardTransform(fromPoint)\n predToPoint = fromPoint + Extent2D(*affineConfig.translation)\n for i in range(2):\n self.assertAlmostEqual(toPoint[i], predToPoint[i])\n\n def testLinearAffine(self):\n \"\"\"Test affine = AffineXYTransform with just linear coefficients\n \"\"\"\n affineClass = xyTransformRegistry[\"affine\"]\n affineConfig = affineClass.ConfigClass()\n rotAng = 0.25 # radians\n xScale = 1.2\n yScale = 0.8\n affineConfig.linear = (\n math.cos(rotAng) * xScale, math.sin(rotAng) * yScale,\n -math.sin(rotAng) * xScale, math.cos(rotAng) * yScale,\n )\n with lsst.utils.tests.getTempFilePath(\".py\") as filePath:\n self.checkConfig(affineClass, affineConfig, filePath)\n affine = affineClass(affineConfig)\n for fromPoint in self.fromIter():\n toPoint = affine.forwardTransform(fromPoint)\n predToPoint = Point2D(\n affineConfig.linear[0] * fromPoint[0] +\n affineConfig.linear[1] * fromPoint[1],\n affineConfig.linear[2] * fromPoint[0] +\n affineConfig.linear[3] * fromPoint[1],\n )\n for i in range(2):\n self.assertAlmostEqual(toPoint[i], predToPoint[i])\n\n def testFullAffine(self):\n \"\"\"Test affine = AffineXYTransform with just linear coefficients\n \"\"\"\n affineClass = xyTransformRegistry[\"affine\"]\n affineConfig = affineClass.ConfigClass()\n affineConfig.translation = (-2.1, 3.4)\n rotAng = 0.832 # radians\n xScale = 3.7\n yScale = 45.3\n affineConfig.linear = (\n math.cos(rotAng) * xScale, math.sin(rotAng) * yScale,\n -math.sin(rotAng) * xScale, math.cos(rotAng) * yScale,\n )\n with lsst.utils.tests.getTempFilePath(\".py\") as filePath:\n self.checkConfig(affineClass, affineConfig, filePath)\n affine = affineClass(affineConfig)\n for fromPoint in self.fromIter():\n toPoint = affine.forwardTransform(fromPoint)\n predToPoint = Point2D(\n affineConfig.linear[0] * fromPoint[0] +\n affineConfig.linear[1] * fromPoint[1],\n affineConfig.linear[2] * fromPoint[0] +\n affineConfig.linear[3] * fromPoint[1],\n )\n predToPoint = predToPoint + Extent2D(*affineConfig.translation)\n for i in range(2):\n self.assertAlmostEqual(toPoint[i], predToPoint[i])\n\n def testRadial(self):\n \"\"\"Test radial = RadialXYTransform\n \"\"\"\n radialClass = xyTransformRegistry[\"radial\"]\n radialConfig = radialClass.ConfigClass()\n radialConfig.coeffs = (0, 1.05, 0.1)\n with lsst.utils.tests.getTempFilePath(\".py\") as filePath:\n self.checkConfig(radialClass, radialConfig, filePath)\n radial = radialClass(radialConfig)\n self.assertEqual(type(radial), RadialXYTransform)\n self.assertEqual(len(radial.getCoeffs()), len(radialConfig.coeffs))\n for coeff, predCoeff in zip(radial.getCoeffs(), radialConfig.coeffs):\n self.assertAlmostEqual(coeff, predCoeff)\n self.checkBasics(radial)\n for fromPoint in self.fromIter():\n fromRadius = math.hypot(fromPoint[0], fromPoint[1])\n fromAngle = math.atan2(fromPoint[1], fromPoint[0])\n predToRadius = fromRadius * \\\n (radialConfig.coeffs[2] *\n fromRadius + radialConfig.coeffs[1])\n predToPoint = Point2D(\n predToRadius * math.cos(fromAngle),\n predToRadius * math.sin(fromAngle))\n toPoint = radial.forwardTransform(fromPoint)\n for i in range(2):\n self.assertAlmostEqual(toPoint[i], predToPoint[i])\n\n def testBadRadial(self):\n \"\"\"Test radial with invalid coefficients\n \"\"\"\n for badCoeffs in (\n (0.1,), # len(coeffs) must be > 1\n (0.1, 1.0), # coeffs[0] must be zero\n (0.0, 0.0), # coeffs[1] must be nonzero\n (0.0, 0.0, 0.1), # coeffs[1] must be nonzero\n ):\n with self.assertRaises(lsst.pex.exceptions.Exception):\n RadialXYTransform(badCoeffs)\n\n radialClass = xyTransformRegistry[\"radial\"]\n radialConfig = radialClass.ConfigClass()\n radialConfig.coeffs = badCoeffs\n with self.assertRaises(Exception):\n radialConfig.validate()\n\n def testMulti(self):\n \"\"\"Test multi = MultiXYTransform\n \"\"\"\n affineClass = xyTransformRegistry[\"affine\"]\n wrapper0 = OneXYTransformConfig()\n wrapper0.transform.retarget(affineClass)\n affineConfig0 = wrapper0.transform\n affineConfig0.translation = (-2.1, 3.4)\n rotAng = 0.832 # radians\n xScale = 3.7\n yScale = 45.3\n affineConfig0.linear = (\n math.cos(rotAng) * xScale, math.sin(rotAng) * yScale,\n -math.sin(rotAng) * xScale, math.cos(rotAng) * yScale,\n )\n\n wrapper1 = OneXYTransformConfig()\n wrapper1.transform.retarget(affineClass)\n affineConfig1 = wrapper1.transform\n affineConfig1.translation = (26.5, -35.1)\n rotAng = -0.25 # radians\n xScale = 1.45\n yScale = 0.9\n affineConfig1.linear = (\n math.cos(rotAng) * xScale, math.sin(rotAng) * yScale,\n -math.sin(rotAng) * xScale, math.cos(rotAng) * yScale,\n )\n\n multiClass = xyTransformRegistry[\"multi\"]\n multiConfig = multiClass.ConfigClass()\n multiConfig.transformDict = {\n 0: wrapper0,\n 1: wrapper1,\n }\n with lsst.utils.tests.getTempFilePath(\".py\") as filePath:\n self.checkConfig(multiClass, multiConfig, filePath)\n multiXYTransform = multiClass(multiConfig)\n\n affine0 = affineClass(affineConfig0)\n affine1 = affineClass(affineConfig1)\n transformList = (affine0, affine1)\n refMultiXYTransform = RefMultiXYTransform(transformList)\n\n self.checkBasics(refMultiXYTransform)\n\n for fromPoint in self.fromIter():\n toPoint = multiXYTransform.forwardTransform(fromPoint)\n predToPoint = refMultiXYTransform.forwardTransform(fromPoint)\n for i in range(2):\n self.assertAlmostEqual(toPoint[i], predToPoint[i])\n\n\nclass MemoryTester(lsst.utils.tests.MemoryTestCase):\n pass\n\n\ndef setup_module(module):\n lsst.utils.tests.init()\n\n\nif __name__ == \"__main__\":\n lsst.utils.tests.init()\n unittest.main()\n","sub_path":"tests/test_xyTransform.py","file_name":"test_xyTransform.py","file_ext":"py","file_size_in_byte":13789,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"135507915","text":"import math\n\n\nclass SimpleDistanceCalculation:\n\n def __init__(self, known_cone_width, known_cone_height, focal_length, image_width, image_height):\n self.known_cone_width = known_cone_width\n self.known_cone_height = known_cone_height\n self.focal_length = focal_length\n self.image_width = image_width\n self.image_width_half = image_width / 2.\n self.image_height = image_height\n\n def calculate_focal_length(self, known_distance, cone_w, cone_h):\n focal_width = (cone_w * known_distance) / self.known_cone_width\n focal_height = (cone_h * known_distance) / self.known_cone_height\n return (focal_width + focal_height) / 2\n\n def calculate_distance(self, cone_w, cone_h):\n distance_width = (self.known_cone_width * self.focal_length) / cone_w\n distance_height = (self.known_cone_height * self.focal_length) / cone_h\n return (distance_width + distance_height) / 2\n\n def calculate_relative_angle(self, cone_x, cone_y):\n if cone_x >= self.image_width_half:\n opposite = cone_x - self.image_width / 2.\n else:\n opposite = self.image_width / 2. - cone_x\n adjacent = self.image_height - cone_y\n return math.tan(opposite / adjacent)\n","sub_path":"SimpleDistanceCalculation.py","file_name":"SimpleDistanceCalculation.py","file_ext":"py","file_size_in_byte":1262,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"389798077","text":"import os\nfrom datetime import datetime\nfrom flask import (\n render_template,\n url_for,\n flash,\n redirect,\n request,\n Blueprint,\n current_app,\n send_file,\n)\nfrom P2MT_App.fetTools.forms import UploadFetDataForm\nfrom P2MT_App.fetTools.generateFetOutputFiles import ripFetFiles\nfrom P2MT_App.main.utilityfunctions import printLogEntry\n\nfetTools_bp = Blueprint(\"fetTools_bp\", __name__)\n\n\ndef save_csvFile(form_csvFetFile, filename):\n output_file_path = \"/tmp\"\n file_path = os.path.join(output_file_path, filename)\n # file_path = os.path.join(current_app.root_path, \"static/fet_data_files\", filename)\n form_csvFetFile.save(file_path)\n # file1 = open(file_path, \"w\")\n # file1.write(form_csvFetFile.data)\n # file1.close()\n return file_path\n\n\n@fetTools_bp.route(\"/fettools\", methods=[\"GET\", \"POST\"])\ndef displayFetTools():\n form = UploadFetDataForm()\n if form.validate_on_submit():\n if form.csvFetStudentInputFile.data:\n FetStudentInputFile = save_csvFile(\n form.csvFetStudentInputFile.data, \"FET_Student_Input_File.csv\"\n )\n if form.csvFetClassTeacherInputFile.data:\n FetClassTeacherInputFile = save_csvFile(\n form.csvFetClassTeacherInputFile.data,\n \"FET_Class_Teacher_Input_File.csv\",\n )\n if form.csvFetTimetableInputFile.data:\n FetTimeTableFile = save_csvFile(\n form.csvFetTimetableInputFile.data, \"FET_Timetable_File.csv\"\n )\n flash(\"Your account has been updated!\", \"success\")\n # output_file_path = os.path.join(current_app.root_path, \"static/fet_data_files\")\n output_file_path = \"/tmp\"\n ripFetFiles(\n form.yearOfGraduation.data,\n form.schoolYear.data,\n form.semester.data,\n FetStudentInputFile,\n FetClassTeacherInputFile,\n FetTimeTableFile,\n output_file_path,\n )\n print(\n \"=== Completed ripFetFiles. Redirecting to fetOutputFiles ===\",\n datetime.now(),\n \" ===\",\n )\n return redirect(url_for(\"fetTools_bp.fetOutputFiles\"))\n elif request.method == \"GET\":\n return render_template(\n \"fettools.html\", title=\"FET Tools\", UploadFetDataForm=form\n )\n print(form.errors)\n\n\n@fetTools_bp.route(\"/fetoutputfiles\", methods=[\"GET\"])\ndef fetOutputFiles():\n print(\"=== Arriving at fetOutputFiles ===\", datetime.now(), \" ===\")\n return render_template(\"fetoutputfiles.html\", title=\"FET Output Files\")\n\n\n@fetTools_bp.route(\"/fetoutputfiles/downloadcsv\")\ndef download_FetCsvFile():\n printLogEntry(\"download_FetCsvFile() function called\")\n csvFilename = \"/tmp/FetOutputFile.csv\"\n return send_file(csvFilename, as_attachment=True, cache_timeout=0)\n\n\n@fetTools_bp.route(\"/fetoutputfiles/downloadjson\")\ndef download_FetJsonFile():\n printLogEntry(\"download_FetJsonFile() function called\")\n csvFilename = \"/tmp/FetOutputFile.json\"\n return send_file(csvFilename, as_attachment=True, cache_timeout=0)\n","sub_path":"P2MT_App/fetTools/routes.py","file_name":"routes.py","file_ext":"py","file_size_in_byte":3102,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"333622935","text":"# uncompyle6 version 3.7.4\n# Python bytecode 3.7 (3394)\n# Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04) \n# [GCC 8.4.0]\n# Embedded file name: /users/garrigaf/Documents/git/darfix/build/lib/darfix/__init__.py\n# Compiled at: 2020-03-03 08:28:12\n# Size of source mod 2**32: 1824 bytes\n\"\"\"The darfix package contains the following main sub-packages:\n\n- silx.core: Core classes and functions\n- silx.gui: Qt widgets for data visualization and data file browsing\n- silx.image: Some processing functions for 2D images\n- silx.io: Functions for input/output operations\n- silx.utils: Miscellaneous convenient functions\n\"\"\"\n__authors__ = [\n 'J. Garriga']\n__license__ = 'MIT'\n__date__ = '16/12/2019'\nfrom ._config import Config as _Config\nconfig = _Config()","sub_path":"pycfiles/darfix-0.3.0-py3-none-any/__init__.cpython-37.py","file_name":"__init__.cpython-37.py","file_ext":"py","file_size_in_byte":760,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"70729248","text":"# !/usr/bin/env python\n# coding: utf-8\n\"\"\"\n# file : WSGIServer.py\n# author : shao\n# date: 2017/10/30 0030\n\"\"\"\nimport socket\nimport sys\n\n\nclass WSGIServer(object):\n\taddress_family=socket.AF_INET\n\tsocket_type=socket.SOCK_STREAM\n\trequest_queue_size=1\n\t\n\tdef __init__(self,server_address):\n\t\tself.listen_socket=listen_socket=socket.socket(\n\t\t\tself.address_family,\n\t\t\tself.socket_type\n\t\t)\n\t\t\n\t\tlisten_socket.setsockopt(socket.SOL_SOCKET,socket.SO_REUSEADDR,1)\n\t\t# 绑定服务器地址\n\t\tlisten_socket.bind(server_address)\n\t\t# 监听\n\t\tlisten_socket.listen(self.request_queue_size)\n\t\t# 得到服务器的主机名和端口\n\t\thost,port=self.listen_socket.getsockname()[:2]\n\t\tself.server_name=socket.getfqdn(host)\n\t\tself.server_port=port\n\t\t\n\t\t# 返回网络应用的头部信息\n\t\tself.headers_set=[]\n\t\n\tdef set_app(self,application):\n\t\tself.application=application\n\t\n\tdef server_forever(self):\n\t\tlisten_socket=self.listen_socket\n\t\twhile True:\n\t\t\t# 监听客户端连接\n\t\t\tself.client_connection,client_address=listen_socket.accept()\n\t\t\t# 处理请求,关闭连接,循环等待\n\t\t\tself.handle_one_request()\n\t\n\tdef handle_one_request(self):\n\t\tself.request_data=request_data=self.client_connection.recv(2048)\n\t\t# 输出格式化的请求数据\n\t\tprint(''.join(\n\t\t\t'< {line}\\n'.format(line=line)\n\t\t\tfor line in request_data.splitlines()\n\t\t))\n\t\t\n\t\tself.parse_request(request_data)\n\t\t\n\t\t# 使用请求数据构建环境目录\n\t\tenv=self.get_environ()\n\t\t\n\t\tresult=self.application(env,self.start_response)\n\t\t\n\t\tself.finish_response(result)\n\t\n\tdef parse_request(self,text):\n\t\trequest_line=str(text.splitlines()[0])\n\t\t# print(request_line)\n\t\t# request_line=bytes(request_line,encoding='UTF-8')\n\t\trequest_line=request_line.rstrip('\\r\\n')\n\t\t(self.request_method,# GET\n\t\t self.path,# /hello\n\t\t self.request_version, # HTTP /1.1\n\t\t )=request_line.split()\n\t\n\tdef get_environ(self):\n\t\tenv={}\n\t\tenv['wsgi.version']=(1,0)\n\t\tenv['wsgi.url_scheme']='http'\n\t\tenv['wsgi.input']=str(self.request_data)\n\t\tenv['wsgi.errors']=sys.stderr\n\t\tenv['wsgi.mutithread']=True\n\t\tenv['wsgi.mutiprocess']=True\n\t\tenv['wsgi.run_once']=False\n\t\t\n\t\tenv['REQUEST_METHOD']=self.request_method\n\t\tenv['PATH_INFO']=self.path\n\t\tenv['SERVER_NAME']=self.server_name\n\t\tenv['SERVER_PORT']=str(self.server_port)\n\t\treturn env\n\t\n\tdef start_response(self,status,response_headers,exc_info=None):\n\t\tserver_headers=[\n\t\t\t('Data','Tue, 31 Mar 2015 12:54:46 GMT'),\n\t\t\t('Server','WSGIServer 0.2'),\n\t\t]\n\t\tself.headers_set=[status,response_headers+server_headers]\n\t\n\t# return self.finish_response\n\t\n\tdef finish_response(self,result):\n\t\ttry:\n\t\t\tstatus,response_headers=self.headers_set\n\t\t\tresponse='HTTP/1.1 {status}\\r\\n'.format(status=status)\n\t\t\tfor header in response_headers:\n\t\t\t\tresponse+='{0}: {1}\\r\\n'.format(*header)\n\t\t\tresponse+='\\r\\n'\n\t\t\tresponse=str(response)\n\t\t\t\n\t\t\tfor data in result:\n\t\t\t\tresponse+=str(data)\n\t\t\t\n\t\t\tprint(''.join(\n\t\t\t\t'> {line}\\n'.format(line=line)\n\t\t\t\tfor line in response.splitlines()\n\t\t\t))\n\t\t\tresponse=bytes(response,encoding='UTF-8')\n\t\t\tself.client_connection.sendall(response)\n\t\t\n\t\tfinally:\n\t\t\tself.client_connection.close()\n\n\nSERVER_ADDRESS=(HOST,PORT)='',8888\n\n\ndef make_server(server_address,application):\n\tserver=WSGIServer(server_address)\n\tserver.set_app(application)\n\treturn server\n\n\nif __name__=='__main__':\n\tif len(sys.argv)<2:\n\t\tsys.exit('Provide a WSGI application object as module:callable')\n\tapp_path=sys.argv[1]\n\tmodule,application=app_path.split(':')\n\tmodule=__import__(module)\n\tapplication=getattr(module,application)\n\thttpd=make_server(SERVER_ADDRESS,application)\n\tprint('WSGIServer:Server HTTP on port {port}...\\n'.format(port=PORT))\n\thttpd.server_forever()\n","sub_path":"server/serverproject/WSGIServer.py","file_name":"WSGIServer.py","file_ext":"py","file_size_in_byte":3641,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"579197186","text":"from bs4 import BeautifulSoup\nimport requests\nimport html5lib\nmy_url=\"https://www.vocabulary.com/lists/141245\"\nraw_cont=requests.get(my_url)\nsoup= BeautifulSoup(raw_cont.text, 'html5lib')\nword_list={}\nword_list_unfil=soup.find('ol', attrs = {'id':'wordlist'})\nfor obj in word_list_unfil.findAll('li',attrs={'class':'entry learnable'}):\n word=(obj.find('a',attrs={'class':'word dynamictext'})).text\n word_def=(obj.find('div',attrs={'class':'definition'})).text\n word_list[word]=word_def\nwith open('WordList.txt','w') as f:\n for w,w_d in word_list.items():\n f.write(w+\" : \"+w_d+\"\\n\")\n\n \n","sub_path":"C++/Hangman Project/scripts/scrapper_script.py","file_name":"scrapper_script.py","file_ext":"py","file_size_in_byte":611,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"97147101","text":"def merge_attached_event(mpack_event, data):\n '\\n Merges an event payload attached in the ``__sentry-event`` attachment.\\n '\n size = mpack_event.size\n if ((size == 0) or (size > MAX_MSGPACK_EVENT_SIZE_BYTES)):\n return\n try:\n event = unpack(mpack_event)\n except (ValueError, UnpackException, ExtraData) as e:\n minidumps_logger.exception(e)\n return\n for key in event:\n value = event.get(key)\n if (value is not None):\n data[key] = value","sub_path":"Data Set/bug-fixing-5/00f97172d2c459ee2f3e2cd37d5035d17749e393--bug.py","file_name":"00f97172d2c459ee2f3e2cd37d5035d17749e393--bug.py","file_ext":"py","file_size_in_byte":510,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"591094646","text":"import sys\nsys.setrecursionlimit(10000)\n\ninput = sys.stdin.readline\n\n\nt = int(input())\n\n\ndx = [0, 0, 1, -1]\ndy = [-1, 1, 0, 0]\n\ndef dfs(y, x):\n visited[y][x] = 1\n for i in range(4):\n nx = x + dx[i]\n ny = y + dy[i]\n if 0 <= nx < m and 0 <= ny < n:\n if visited[ny][nx] == 0 and matrix[ny][nx] == 1:\n dfs(ny, nx)\n\nfor _ in range(t):\n m, n, k = map(int, input().split())\n matrix = [[0]*m for _ in range(n)]\n for _ in range(k):\n a, b = map(int, input().split())\n matrix[b][a] = 1\n visited = [[0]*m for _ in range(n)]\n inum = 0\n for i in range(n):\n for j in range(m):\n if visited[i][j] == 0 and matrix[i][j] == 1:\n dfs(i, j)\n inum += 1\n print(inum)","sub_path":"boj/boj_1012.py","file_name":"boj_1012.py","file_ext":"py","file_size_in_byte":778,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"638098553","text":"import json\nimport boto3\nfrom botocore.exceptions import ClientError\nimport sys\n\ndef pp(obj):\n print(json.dumps(obj, sort_keys=True,indent=3, separators=(',', ': ')))\n\ndef lambda_handler(event, context):\n pp(event)\n region_map = {\n \"tokyo\": \"ap-northeast-1\",\n \"singapore\": \"ap-southeast-1\",\n \"frankfurt\": \"eu-central-1\",\n \"ireland\": \"eu-west-1\",\n \"london\": \"eu-west-2\",\n \"sydney\": \"ap-southeast-2\",\n \"oregon\": \"us-west-2\",\n \"ohio\": \"us-east-2\",\n \"canada\": \"ca-central-1\"\n }\n resp = {}\n resp[\"sessionAttributes\"] = { \"foo\": \"bar\" }\n resp[\"dialogAction\"] = {\n \"type\" : \"Close\",\n \"fulfillmentState\": \"Fulfilled\",\n \"message\": {\n \"contentType\": \"PlainText\",\n \"content\": \"Awesome! Your stack is launching now!\"\n }\n }\n # validate the fulfillment\n if event[\"bot\"][\"name\"] != \"BookTrip\" or event[\"currentIntent\"][\"name\"] != \"LaunchStack\" or event[\"currentIntent\"][\"confirmationStatus\"] != \"Confirmed\":\n # invalid \n print(\"ERROR - invalid event\")\n return \"\"\n instance_number = event[\"currentIntent\"][\"slots\"][\"slotNumber\"]\n instance_os = event[\"currentIntent\"][\"slots\"][\"slotOS\"]\n instance_region = event[\"currentIntent\"][\"slots\"][\"slotRegion\"]\n if int(instance_number) not in range(1,11):\n resp[\"dialogAction\"][\"message\"][\"content\"] = \"invalid instance count\"\n return resp\n elif instance_os.lower() not in ['linux', 'windows']:\n resp[\"dialogAction\"][\"message\"][\"content\"] = \"invalid OS\"\n return resp\n elif instance_region.lower() not in region_map.keys():\n resp[\"dialogAction\"][\"message\"][\"content\"] = \"invalid region\"\n return resp\n \n region_code = region_map[instance_region.lower()]\n instance_os = instance_os.lower()\n instance_number = int(instance_number)\n #cfn_stack_url = 'https://s3-us-west-2.amazonaws.com/pahud-cfn-us-west-2/ecs-cfn-refarch/cloudformation/codepipeline.yml'\n cfn_stack_url = {\n 'linux': 'https://s3-us-west-2.amazonaws.com/pahud-cfn-us-west-2/ecs-cfn-refarch/cloudformation/service.yml',\n 'windows': 'https://s3-us-west-2.amazonaws.com/pahud-cfn-us-west-2/ecs-cfn-refarch/cloudformation/service-windows.yml'\n }\n\n session = boto3.session.Session()\n cfn = boto3.client('cloudformation', region_name=region_code)\n try:\n print('creating stack now')\n cfn_resp = cfn.create_stack(\n StackName='summit-lex-{0}'.format(instance_os),\n TemplateURL=cfn_stack_url[instance_os],\n Parameters=[\n {\n 'ParameterKey': 'ASGDesiredCapacity',\n 'ParameterValue': str(instance_number),\n 'UsePreviousValue': True\n },\n {\n 'ParameterKey': 'ASGMaxSize',\n 'ParameterValue': str(int(instance_number) + 5),\n 'UsePreviousValue': True\n },\n {\n 'ParameterKey': 'ASGMinSize',\n 'ParameterValue': '0',\n 'UsePreviousValue': True\n },\n {\n 'ParameterKey': 'Repository',\n 'ParameterValue': '',\n 'UsePreviousValue': True\n }\n ],\n Capabilities=['CAPABILITY_IAM']\n\n )\n print(cfn_resp)\n resp[\"dialogAction\"][\"message\"][\"content\"] = \"Awesome! Your stack is launching in {0} now!\".format(instance_region)\n except ClientError as ex:\n print(ex)\n resp[\"dialogAction\"][\"message\"][\"content\"] = 'failed to create - resource already exists'\n \n \n return resp\n","sub_path":"Lambda/LexLaunchStack/venv/index.py","file_name":"index.py","file_ext":"py","file_size_in_byte":3755,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"289317164","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom pathlib import Path\nimport warnings\nimport covid19dh\nimport pandas as pd\nfrom covsirphy.util.term import Term\nfrom covsirphy.cleaning.cbase import CleaningBase\nfrom covsirphy.cleaning.jhu_data import JHUData\nfrom covsirphy.cleaning.oxcgrt import OxCGRTData\nfrom covsirphy.cleaning.population import PopulationData\nfrom covsirphy.cleaning.pcr_data import PCRData\n\n\nclass COVID19DataHub(Term):\n \"\"\"\n Load datasets retrieved from COVID-19 Data Hub.\n https://covid19datahub.io/\n\n Args:\n filename (str): CSV filename to save records\n \"\"\"\n # Citation\n CITATION = '(Secondary source)' \\\n ' Guidotti, E., Ardia, D., (2020), \"COVID-19 Data Hub\",' \\\n ' Journal of Open Source Software 5(51):2376, doi: 10.21105/joss.02376.'\n # Name conversion list of columns\n _OXCGRT_COLS_RAW = [\n \"school_closing\",\n \"workplace_closing\",\n \"cancel_events\",\n \"gatherings_restrictions\",\n \"transport_closing\",\n \"stay_home_restrictions\",\n \"internal_movement_restrictions\",\n \"international_movement_restrictions\",\n \"information_campaigns\",\n \"testing_policy\",\n \"contact_tracing\",\n \"stringency_index\"\n ]\n _COL_DICT = {\n \"date\": Term.DATE,\n \"administrative_area_level_1\": Term.COUNTRY,\n \"administrative_area_level_2\": Term.PROVINCE,\n \"tests\": Term.TESTS,\n \"confirmed\": Term.C,\n \"deaths\": Term.F,\n \"recovered\": Term.R,\n \"population\": Term.N,\n \"iso_alpha_3\": Term.ISO3,\n **{v: v.capitalize() for v in _OXCGRT_COLS_RAW}\n }\n # Class objects of datasets\n OBJ_DICT = {\n \"jhu\": JHUData,\n \"population\": PopulationData,\n \"oxcgrt\": OxCGRTData,\n \"pcr\": PCRData,\n }\n\n def __init__(self, filename):\n try:\n self.filepath = Path(filename)\n except TypeError:\n raise TypeError(f\"@filename should be a path-like object, but {filename} was applied.\")\n self.filepath.parent.mkdir(exist_ok=True, parents=True)\n self.primary_list = None\n self._loaded_df = None\n\n def load(self, name=\"jhu\", force=True, verbose=1):\n \"\"\"\n Load the datasets of COVID-19 Data Hub and create dataset object.\n\n Args:\n name (str): name of dataset, \"jhu\", \"population\", \"oxcgrt\" or \"pcr\"\n force (bool): if True, always download the dataset from the server\n verbose (int): level of verbosity\n\n Returns:\n covsirphy.CleaningBase: the dataset\n\n Note:\n If @verbose is 2, detailed citation list will be shown when downloading.\n If @verbose is 1, how to show the list will be explained.\n Citation of COVID-19 Data Hub will be set as JHUData.citation etc.\n \"\"\"\n if name not in self.OBJ_DICT:\n raise KeyError(\n f\"@name must be {', '.join(list(self.OBJ_DICT.keys()))}, but {name} was applied.\")\n # Get all data\n if self._loaded_df is None:\n self._loaded_df = self._load(force=force, verbose=verbose)\n return self.OBJ_DICT[name](data=self._loaded_df, citation=self.CITATION)\n\n def _load(self, force, verbose):\n \"\"\"\n Load the datasets of COVID-19 Data Hub.\n\n Args:\n force (bool): if True, always download the dataset from the server\n verbose (int): level of verbosity\n\n Returns:\n pandas.DataFrame: as the same as COVID19DataHub._preprocessing()\n\n Note:\n If @verbose is 2, detailed citation list will be shown when downloading.\n If @verbose is 1, how to show the list will be explained.\n \"\"\"\n # Use local CSV file\n if not force and self.filepath.exists():\n df = CleaningBase.load(\n self.filepath,\n dtype={\n self.PROVINCE: \"object\", \"Province/State\": \"object\",\n \"key\": \"object\", \"key_alpha_2\": \"object\",\n })\n if set(self._COL_DICT.values()).issubset(df.columns):\n return df\n # Download dataset from server\n raw_df = self._retrieve(verbose=verbose)\n raw_df.to_csv(self.filepath, index=False)\n return raw_df\n\n def _retrieve(self, verbose=1):\n \"\"\"\n Retrieve datasets from COVID-19 Data Hub.\n Level 1 (country) and level2 (province) will be used and combined to a dataframe.\n\n Args:\n verbose (int): level of verbosity\n\n Note:\n If @verbose is 2, detailed citation list will be shown when downloading.\n If @verbose is 1, how to show the list will be explained.\n \"\"\"\n # Download datasets\n if verbose:\n print(\"Retrieving datasets from COVID-19 Data Hub https://covid19datahub.io/\")\n c_df, p_df, self.primary_list = self._download()\n # Merge the datasets\n df = pd.concat([c_df, p_df], axis=0, ignore_index=True)\n # Perform pre-processing\n df = self._preprocessing(df)\n # Show citation list\n if verbose:\n if isinstance(verbose, int) and verbose >= 2:\n print(\"\\nDetailed citaition list:\")\n print(self.primary_list)\n else:\n print(\"\\tPlease set verbose=2 to see the detailed citation list.\")\n return df\n\n def _download(self):\n \"\"\"\n Retrieve dataset and citation list from COVID-19 Data Hub.\n\n Returns:\n tuple:\n pandas.DataFrame: dataset at country level\n pandas.DataFrame: dataset at province level\n str: the list of primary sources\n\n Note:\n For some countries, province-level data is included.\n \"\"\"\n warnings.simplefilter(\"ignore\", ResourceWarning)\n levels = [f\"administrative_area_level_{i}\" for i in range(1, 4)]\n # Level 1 (country/region)\n c_raw, c_cite = covid19dh.covid19(country=None, level=1, verbose=False, raw=True)\n c_df = c_raw.groupby(levels[0]).ffill().fillna(0)\n for num in range(3):\n c_df.loc[:, levels[num]] = c_raw[levels[num]]\n # Level 2 (province/state)\n p_raw, p_cite = covid19dh.covid19(country=None, level=2, verbose=False, raw=True)\n p_df = p_raw.groupby(levels[:2]).ffill().fillna(0)\n for num in range(3):\n p_df.loc[:, levels[num]] = p_raw[levels[num]]\n # Citation\n cite = pd.concat([c_cite, p_cite], axis=0, ignore_index=True)\n cite = cite.loc[:, [\"title\", \"year\", \"url\"]]\n cite = cite.sort_values([\"year\", \"url\"], ascending=[False, True])\n cite.drop_duplicates(subset=\"title\", inplace=True)\n series = cite.apply(lambda x: f\"{x[0]} ({x[1]}), {x[2]}\", axis=1)\n return (c_df, p_df, \"\\n\".join(series.tolist()))\n\n def _preprocessing(self, raw):\n \"\"\"\n Perform pre-processing with the raw dataset.\n\n Args:\n raw (pandas.DataFrame):\n Index\n reset index\n Columns\n Refer to COVID-19 Data Hub homepage.\n https://covid19datahub.io/articles/doc/data.html\n\n Returns:\n pandas.DataFrame:\n Index\n reset index\n Columns\n - Date: observation date\n - Country: country/region name\n - Province: province/prefecture/state name\n - Confirmed: the number of confirmed cases\n - Infected: the number of currently infected cases\n - Fatal: the number of fatal cases\n - Recovered: the number of recovered cases\n - School_closing\n - Workplace_closing\n - Cancel_events\n - Gatherings_restrictions\n - Transport_closing\n - Stay_home_restrictions\n - Internal_movement_restrictions\n - International_movement_restrictions\n - Information_campaigns\n - Testing_policy\n - Contact_tracing\n - Stringency_index\n\n Note:\n Data types are not confirmed.\n \"\"\"\n df = raw.copy()\n # Replace column names\n df = df.rename(columns=self._COL_DICT)\n self._ensure_dataframe(df, columns=list(self._COL_DICT.values()))\n # Country\n df[self.COUNTRY] = df[self.COUNTRY].replace(\n {\n # COD\n \"Congo, the Democratic Republic of the\": \"Democratic Republic of the Congo\",\n # COG\n \"Congo\": \"Republic of the Congo\",\n # KOR\n \"Korea, South\": \"South Korea\",\n }\n )\n # Set 'Others' as the country name of cruise ships\n ships = [\"Diamond Princess\", \"Costa Atlantica\", \"Grand Princess\", \"MS Zaandam\"]\n for ship in ships:\n df.loc[df[self.COUNTRY] == ship, [self.COUNTRY, self.PROVINCE]] = [self.OTHERS, ship]\n return df\n\n @property\n def primary(self):\n \"\"\"\n str: the list of primary sources.\n \"\"\"\n return self.primary_list or self._download()[-1]\n","sub_path":"covsirphy/cleaning/covid19datahub.py","file_name":"covid19datahub.py","file_ext":"py","file_size_in_byte":9374,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"99672373","text":"from django.db import models\n\nfrom api.managers.ComplianceReportStatusManager import \\\n ComplianceReportStatusManager\nfrom api.managers.TheTypeManager import TheTypeManager\nfrom api.models.CompliancePeriod import CompliancePeriod\nfrom api.models.ComplianceReportSchedules import ScheduleC, ScheduleB, ScheduleA\nfrom api.models.Organization import Organization\nfrom api.models.mixins.DisplayOrder import DisplayOrder\nfrom api.models.mixins.EffectiveDates import EffectiveDates\nfrom auditable.models import Auditable\n\n\nclass ComplianceReportStatus(Auditable, DisplayOrder, EffectiveDates):\n \"\"\"\n List of Possible statuses for compliance reports.\n \"\"\"\n status = models.CharField(\n max_length=25,\n blank=True,\n null=True,\n unique=True,\n db_comment=\"Contains an enumerated value to describe the compliance \"\n \"report status. This is a unique natural key.\"\n )\n\n objects = ComplianceReportStatusManager()\n\n def natural_key(self):\n \"\"\"\n Allows type 'status' to be used to identify\n a row in the table\n \"\"\"\n return (self.status,)\n\n class Meta:\n db_table = 'compliance_report_status'\n\n db_table_comment = \"List of possible statuses.\" \\\n \"(Draft, Submitted, Received, etc.)\"\n\n\nclass ComplianceReportType(DisplayOrder):\n \"\"\"\n List of Possible statuses for compliance reports.\n \"\"\"\n the_type = models.CharField(\n max_length=100,\n blank=False,\n null=False,\n unique=True,\n db_comment=\"Short descriptive name of the compliance report type.\"\n )\n\n description = models.CharField(\n max_length=1000, blank=True, null=False,\n db_comment=\"Description of the compliance report type. This is the \"\n \"displayed name.\"\n )\n\n objects = TheTypeManager()\n\n def natural_key(self):\n \"\"\"\n Allows type 'status' to be used to identify\n a row in the table\n \"\"\"\n return (self.the_type,)\n\n class Meta:\n db_table = 'compliance_report_type'\n\n db_table_comment = \"List of possible compliance report types.\"\n\n\nclass ComplianceReport(Auditable):\n \"\"\"\n List of Possible statuses for compliance reports.\n \"\"\"\n status = models.ForeignKey(\n ComplianceReportStatus,\n on_delete=models.PROTECT,\n null=False\n )\n\n type = models.ForeignKey(\n ComplianceReportType,\n on_delete=models.PROTECT,\n null=False\n )\n\n organization = models.ForeignKey(\n Organization,\n on_delete=models.CASCADE,\n null=False\n )\n\n compliance_period = models.ForeignKey(\n CompliancePeriod,\n on_delete=models.DO_NOTHING,\n null=False\n )\n\n schedule_a = models.OneToOneField(\n ScheduleA,\n related_name='compliance_report',\n on_delete=models.CASCADE,\n null=True\n )\n\n schedule_b = models.OneToOneField(\n ScheduleB,\n related_name='compliance_report',\n on_delete=models.CASCADE,\n null=True\n )\n\n schedule_c = models.OneToOneField(\n ScheduleC,\n related_name='compliance_report',\n on_delete=models.CASCADE,\n null=True\n )\n\n class Meta:\n db_table = 'compliance_report'\n\n db_table_comment = \"Contains annual compliance report records\"\n","sub_path":"backend/api/models/ComplianceReport.py","file_name":"ComplianceReport.py","file_ext":"py","file_size_in_byte":3358,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"120369538","text":"#!/usr/bin/python3\n# -*- coding:utf-8 -*-\nfrom typing import List, Optional\n\n\nclass ListNode:\n def __init__(self, val=0, next=None):\n self.val = val\n self.next = next\n\n\nclass Solution:\n def mergeKLists(self, lists: List[Optional[ListNode]]) -> Optional[ListNode]:\n # 全部取出，再拼接\n import heapq\n dummy = ListNode(0)\n p = dummy\n h = []\n for i in range(len(lists)):\n if lists[i]:\n heapq.heappush(h, (lists[i].val, i))\n lists[i] = lists[i].next\n\n while h:\n val, idx = heapq.heappop(h)\n p.next = ListNode(val)\n p = p.next\n if lists[idx]:\n heapq.heappush(h, (lists[idx].val, idx))\n lists[idx] = lists[idx].next\n return dummy.next\n\n\nif __name__ == '__main__':\n sn = Solution()\n\n from gen_node import gen_node\n\n lists = [gen_node([1, 4, 5]), gen_node([1, 3, 4]), gen_node([2, 6])]\n\n print(sn.mergeKLists(lists))\n","sub_path":"字节/23.py","file_name":"23.py","file_ext":"py","file_size_in_byte":1019,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"581659518","text":"# import hashlib\nimport base58\nfrom urllib.parse import urlparse\n\nimport dateutil.parser\nimport multihash\nfrom goose import Goose\n# from lxml import etree\nfrom scrapy.linkextractors import LinkExtractor\n\n\nclass WebsiteParser(object):\n \"\"\"\n Receive response from scrapy\n Return the list of items to save:\n * HTML content to save to S3\n * parsed dict with information to send to SQS\n \"\"\"\n\n def __init__(self, response, allowed_domains=[]):\n self.response = response\n self.allowed_domains = allowed_domains\n self.my_le = LinkExtractor(allow=('', ))\n\n def get_body(self):\n return self.response.body\n\n def get_content_multihash(self):\n return base58.b58encode(\n bytes(multihash.encode(self.response.body, multihash.SHA1))\n )\n\n def get_s3_filename(self):\n # return hashlib.sha256(self.response.url.encode('utf-8')).hexdigest()\n return self.get_content_multihash()\n\n def get_result(self):\n \"\"\"\n Return parse results\n https://github.com/difchain/rmaas/blob/master/docs/WebCrawler_Client.md\n \"\"\"\n gs = Goose()\n parsed_article = gs.extract(raw_html=self.get_body())\n\n owner = urlparse(self.response.url).netloc\n identifier = self.response.url # .replace('https://', '').replace('http://', '')\n result = {\n # RecordName area\n 'identifier': identifier,\n 'owner': owner,\n # RecordVersion area\n 'Hash': self.get_content_multihash(),\n 'RecordsAuthority': 'naa.gov.au:gda21',\n 'Title': parsed_article.title,\n 'Description': parsed_article.cleaned_text[:300],\n 'Author': self._get_version_author(),\n 'DateCreated': self._get_date_created(),\n 'Classification': 'UNCLASSIFIED',\n 'Language': self._get_language(),\n # object\n 'size': len(self.response.body),\n 'MIMEType': self._get_mimetype(),\n # etc\n 's3_filename': self.get_s3_filename(),\n 'external_domains': self._get_external_domains(),\n 'links': self._get_links(),\n }\n return result\n\n # def _get_version_title(self):\n # return self.response.selector.xpath('//title/text()').extract_first() or '?'\n\n # def _get_version_description(self):\n # tree = etree.HTML(self.response.body)\n # etree.strip_tags(tree)\n # text_spaced = etree.tounicode(tree, method='text').replace('\\n', ' ').strip()\n # text = ' '.join(x for x in text_spaced.split() if x)\n # return text[:300] if text else '?'\n\n def _get_version_author(self):\n return 'John the Dropbear'\n\n def _get_mimetype(self):\n result = self.response.headers.get('Content-Type')\n if result:\n result = result.decode('utf-8')\n return result or 'text/html'\n\n def _get_date_created(self):\n lm = self.response.headers.get('Last-Modified')\n if lm:\n lm = dateutil.parser.parse(lm)\n if lm:\n lm = lm.isoformat()\n return lm\n\n def _get_language(self):\n return 'en-us'\n\n def _get_external_domains(self):\n # get the list of external domain names linked from this page\n external_domains = set()\n for link in self.my_le.extract_links(self.response):\n parsed_link = urlparse(link.url)\n if parsed_link.netloc not in self.allowed_domains:\n external_domains.add(parsed_link.netloc)\n return sorted(list(external_domains))\n\n def _get_links(self):\n links = set()\n for link in self.my_le.extract_links(self.response):\n links.add(link.url)\n return sorted(list(links))\n","sub_path":"crawler-node/src/my_parser.py","file_name":"my_parser.py","file_ext":"py","file_size_in_byte":3775,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"514100670","text":"import requests \nimport numpy as np\nimport csv\nimport os\nimport pandas as pd\nfrom textblob import TextBlob\nfrom sklearn.naive_bayes import MultinomialNB\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom api_cred import Credentials\n\n\n\nfrom google.cloud import language\nfrom google.cloud.language import enums\nfrom google.cloud.language import types\n\nos.environ[\"GOOGLE_APPLICATION_CREDENTIALS\"] = \"/path/to/credientials.json\"\n\ndef run_azure(input_array):\n creds = Credentials().get('azure')\n headers = { 'Ocp-Apim-Subscription-Key' : creds['subscription_key'] }\n sentiment_api_url = creds['endpoint'] + \"sentiment\"\n docs = []\n assert(len(input_array.flatten()) <= 1000)\n for i, input_text in enumerate(input_array.flatten()):\n docs.append({'id' : str(i+1), 'language' : 'en', 'text' : input_text})\n documents = { 'documents' : docs }\n response = requests.post(sentiment_api_url, headers=headers, json=documents)\n sentiments = response.json()\n print(sentiments)\n scores = [x['score'] for x in sentiments['documents']]\n scores = np.array(scores)\n return scores.reshape(input_array.shape[0], 1)\n\n\ndef run_textblob(input_array): \n result_arr = []\n for r in input_array: \n blob = TextBlob(r)\n result_arr.append([blob.sentiment.polarity, blob.sentiment.subjectivity])\n return result_arr\n\ndef api_chunks(twt_list, n=1000):\n for i in range(0, len(twt_list), n): \n yield twt_list[i:i+n]\n\ndef write_results(tweet_list, label_list, sensitive_attr, api_func, save_file, score_label): \n with open(save_file, 'w') as f: \n csv_writer = csv.writer(f)\n if len(score_label) == 1: \n csv_writer.writerow([\"text X\", \"Z\", \"label Y\", score_label])\n else: \n print([\"text X\", \"Z\", \"label Y\"] + score_label)\n csv_writer.writerow([\"text X\", \"Z\", \"label Y\"] + score_label)\n sentiment = [] \n review_iter = api_chunks(tweet_list, 50)\n for sub_list in review_iter: \n sentiment += list(api_func(np.array(sub_list)))\n\n for i, twt in enumerate(tweet_list): \n if len(sentiment[i]) == 1: \n csv_writer.writerow([twt, sensitive_attr[i], label_list[i], sentiment[i][0]])\n else: \n csv_writer.writerow([twt, sensitive_attr[i], label_list[i]] + sentiment[i])\n\ndef run_google_sentiment(input_array): \n # Instantiates a client\n client = language.LanguageServiceClient()\n\n result_arr = [] \n # The text to analyze\n for twt in input_array: \n document = types.Document(\n content=twt,\n type=enums.Document.Type.PLAIN_TEXT)\n\n # Detects the sentiment of the text\n try: \n sentiment = client.analyze_sentiment(document=document).document_sentiment\n print('Text: {}'.format(twt))\n print('Sentiment: {}, {}'.format(sentiment.score, sentiment.magnitude))\n result_arr.append([sentiment.score, sentiment.magnitude])\n except: \n print(twt)\n result_arr.append([0, 0])\n\n return result_arr\n\n\ndef run_custom_sentiment(input_array): \n df = pd.read_csv('datasets/amazon_sentiment.csv')\n texts = df['text'].tolist() \n labels = df['label'].tolist()\n vectorizer = CountVectorizer(stop_words='english', max_features=10000)\n train_features = vectorizer.fit_transform(texts[1000:9000])\n nb_model = MultinomialNB()\n nb_model.fit(train_features, labels[1000:9000])\n\n vocab = vectorizer.vocabulary_\n\n vectorizer = CountVectorizer(stop_words='english', vocabulary=vocab)\n test_features = vectorizer.fit_transform(input_array)\n predictions = nb_model.predict(test_features)\n prob = nb_model.predict_proba(test_features)\n predictions = nb_model.predict(test_features)\n\n class_prob = [[p[1]] for p in prob]\n return class_prob\n\n\n\n\nif __name__ == \"__main__\": \n\n reviews = [] \n sensitive_attr = [] \n labels = [] \n dataset_str = 'movies'\n with open('datasets/' + dataset_str + '1000.csv', 'r') as f: \n csv_reader = csv.reader(f)\n row = next(csv_reader)\n for row in csv_reader: \n reviews.append(row[0])\n sensitive_attr.append(row[1])\n labels.append(row[2])\n\n #write_results(reviews, labels, sensitive_attr, run_azure, 'results/'+ dataset_str + '_azure_results.csv', ['sentiment'])\n \n #write_results(reviews, labels, sensitive_attr, run_textblob, 'results/'+ dataset_str + '_tb_results.csv', ['sentiment'])\n\n #write_results(reviews, labels, sensitive_attr, run_google_sentiment, 'results/'+ dataset_str + '_google_results.csv', ['sentiment', 'magnitude'])\n","sub_path":"tasks/nlp/get_sentiment.py","file_name":"get_sentiment.py","file_ext":"py","file_size_in_byte":4729,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"374907688","text":"import cv2\nimport matplotlib.pylab as plt\nimport numpy as np\nimport math\nimport pylab as pl\nimport scipy.signal as signal\n\nCAMERA={\n 'FX_C':1081.3720703125,\n 'FY_C':-1081.3720703125,\n 'CX_C':960.5,\n 'CY_C':539.5,\n 'FX_D':366.864685058594,\n 'FY_D':-366.864685058594,\n 'CX_D':263.148010253906, \n 'CY_D':200.292007446289}\n\ndef RGBtoD(p, frame):\n if frame<=30:\n c=3.5\n elif frame>=130:\n c=4.5\n else:\n c=4\n x_c=p[0]\n y_c=p[1]\n x_d=round((x_c-CAMERA['CX_C'])/CAMERA['FX_C']*CAMERA['FX_D']+CAMERA['CX_D']+c)\n y_d=round((y_c-CAMERA['CY_C'])/CAMERA['FY_C']*CAMERA['FY_D']+CAMERA['CY_D'])\n #print(x_d)\n #print(y_d)\n #print(type(im[y_d][x_d][0]))\n #print(im[y_d+424][x_d][0])\n \n return (x_d, y_d)\n\ndef filter(p, im, size):\n s=(size-1)/2\n (x_d, y_d)=RGBtoD(p)\n win=[im[i,j] for i in range(y_d-s, y_d+s+1) for j in range(x_d-s, x_d+s+1)]\n for k in win:\n if (k>=0 and k<=23) or k>175:\n win.remove(k)\n win=np.array(win)\n return np.median(win)\n\ndef RGBto3D(p, im, frame, filter=False, size=0):\n \n x_c=p[0]\n y_c=p[1]\n if frame<=30:\n c=3.5\n elif frame>=130:\n c=4.5\n else:\n c=4\n x_d=round((x_c-CAMERA['CX_C'])/CAMERA['FX_C']*CAMERA['FX_D']+CAMERA['CX_D']+c)\n y_d=round((y_c-CAMERA['CY_C'])/CAMERA['FY_C']*CAMERA['FY_D']+CAMERA['CY_D'])\n #print(x_d)\n #print(y_d)\n #print(type(im[y_d][x_d][0]))\n #print(im[y_d+424][x_d][0])\n if len(p)==2:\n if filter:\n z=his_image(im, size, p, frame)[0]\n else:\n #print(im[round(y_d)][round(x_d)][0])\n z=im[round(y_d)][round(x_d)][0]*256/6+im[round(y_d+424)][round(x_d)][0]\n '''\n if(z==0):\n z1=max([im[y_d+i][x_d+j][0] for i in range(-2,3) for j in range(-2,3)])\n z0=min([im[y_d+i][x_d+j][0] for i in range(-2,3) for j in range(-2,3)])\n \n z=z1*256+z0 \n '''\n x=(x_d-CAMERA['CX_D'])*z/CAMERA['FX_D']\n y=(y_d-CAMERA['CY_D'])*(z)/CAMERA['FY_D']\n else:\n z=p[2]\n x=(x_d-CAMERA['CX_D'])*z/CAMERA['FX_D']\n y=(y_d-CAMERA['CY_D'])*(z)/CAMERA['FY_D']\n \n return (x, y, z)\n\ndef angle(p1,p2,p3,alwaysPositive=True):\n n=len(p1)\n # vectors\n v1=[(p1[i]-p2[i]) for i in range(n)]\n v2=[(p3[i]-p2[i]) for i in range(n)]\n # angle = acos( dot(v1,v2) / (len(v1)*len(v2)) )\n dot=sum([(v1[i]*v2[i]) for i in range(n)])\n len_v1=math.sqrt(sum([(v1[i]**2) for i in range(n)]))\n len_v2=math.sqrt(sum([(v2[i]**2) for i in range(n)]))\n if(len_v1!=0 and len_v2!=0):\n if not alwaysPositive and n==3 and (v1[2]<0 and v2[2]<=0):\n return 360-math.degrees(math.acos(dot/(len_v1*len_v2)))\n else:\n return math.degrees(math.acos(dot/(len_v1*len_v2)))\n else:\n return 180\n\ndef v2i(cap, frame, save=False): \n cap.set(cv2.CAP_PROP_POS_FRAMES, frame) # 设置帧数标记\n ret, im = cap.read() # read方法返回一个布尔值和一个视频帧\n if ret: \n if save:\n cv2.imwrite(\"test1/img/\" + str(frame) + \"C.jpg\", im)\n return im\n else:\n return 'No image!!'\n \ndef his_image(im, size, p, frame):\n\n # médian\n #img_m=cv2.medianBlur(im,5)\n #font=cv2.FONT_HERSHEY_SIMPLEX\n img_m=im[0:828, 0:512]\n '''\n img_m_h=img_m[0:424, 0:512]\n img_m_b=img_m[424:828, 0:512]\n for i in range(424):\n for j in range(512):\n img_m[i,j]=img_m_h[i,j]*256/6+img_m_b[i,j]\n '''\n \n x=p[0]\n y=p[1]\n (x_d, y_d)=RGBtoD((x, y),frame)\n ndg_h1=img_m[y_d, x_d][0]# Original Depth_high\n ndg_b1=img_m[y_d+424, x_d][0]# Depth Original_low\n print(ndg_h1, ndg_b1)\n #print(img_m[(y_d-int((size-1)/2)):(y_d+int((size-1)/2)),(x_d-int((size-1)/2)):(x_d+int((size-1)/2))] )\n ng=[]\n #print(img_m[(y_d-int((size-1)/2)):(y_d+int((size-1)/2)),(x_d-int((size-1)/2)):(x_d+int((size-1)/2))] )\n for i in range(y_d-int((size-1)/2), y_d+int((size-1)/2)+1):\n for j in range(x_d-int((size-1)/2), x_d+int((size-1)/2)+1):\n z0=(img_m[i,j]*256/6+img_m[i+424,j])[0]/10\n if z0>120 and z0<850:\n ng.append(int(round(z0)))\n \n print(len(ng))\n ngh=[0]*851\n for h in set(ng):\n ngh[h]=ng.count(h)\n\n zm=ngh.index(max(ngh))*10\n print(zm)\n\n return (zm, ndg_h1*256/6+ndg_b1)\n\ndef compt(t1, vd, t2, gt, dt, show=False):\n gt_r=[]\n t=[]\n t1=[j-dt for j in t1]\n for i in t1:\n \n if i<=0:\n continue\n elif i\n \n \n \n Форма добавления\n \n \n \n \n \n \n \n \n \"\"\")\nelif 'exportExcelButton' in form: # Если нажата кнопка \"Экспортировать таблицу в Excel\"\n tablePeoples = {\"Surname\": [], # Собирается таблица для записи в файл (пока есть только шапка)\n \"Name\": [],\n \"Patronymic\": [],\n \"Region\": [],\n \"City\": [],\n \"Telephone\": [],\n \"E-mail\": []}\n cursor = db.cursor()\n cursor.execute('''\n SELECT p.surname, p.name, p.patronymic, r.region, c.city, p.telephone, p.email FROM peoples p\n JOIN regions r ON p.regionId = r.id\n JOIN cities c ON (p.cityId=c.id AND p.regionId = c.regionId) \n ''')\n peoples = cursor.fetchall() # Из таблицы peoples забираются все строки и постепенно наполняют tablePeoples\n for surname, name, patronymic, region, city, telephone, email in peoples:\n tablePeoples[\"Surname\"].append(surname)\n tablePeoples[\"Name\"].append(name)\n tablePeoples[\"Patronymic\"].append(patronymic)\n tablePeoples[\"Region\"].append(region)\n tablePeoples[\"City\"].append(city)\n tablePeoples[\"Telephone\"].append(telephone)\n tablePeoples[\"E-mail\"].append(email)\n dataFrame = pd.DataFrame(tablePeoples)\n dataFrame.to_excel(\"Peoples.xlsx\") # Записываем таблицу в файл с именем Peoples.xlsx в директорию проекта\n print('''\n \n \n \n \n ''') # Уведомляем пользователя о том, что таблица peoples была экспортрована\nelif 'importPdfButton' in form: # Если нажата кнопка \"Импорт данных из PDF\"\n pdf = workPDF.openPDF() # Открываем PDF\n text = workPDF.getText(pdf) # Получаем текст из файла (с сохранененной структурой)\n text = text.split('\\n') # Получаем список строк из файла\n data = {} # Данные из резюме (пока пустой)\n\n fio = text[0].split(' ') # Первой строчкой в резюме является ФИО, которое разделено пробелами. Считываем его.\n data[\"Surname\"] = fio[0]\n data[\"Name\"] = fio[1]\n data[\"Patronymic\"] = '-'\n if len(fio) > 2:\n data[\"Patronymic\"] = ' '.join(fio[1:]) # В случае, если в резюме есть и отчество, получаем и его (иначе, значение по умолчанию = \"-\")\n\n city = text[4].split(' ') # Получаем строку про место проживания (известен только город)\n city = city[len(city) - 1]\n cursor = db.cursor()\n cursor.execute(\"SELECT id, regionId FROM cities WHERE city='{}'\".format(city))\n location = cursor.fetchall()\n data[\"City\"] = location[0][0] # Получаем ИД города и региона из таблицы, исходя из названия города\n data[\"Region\"] = location[0][1]\n\n telephone = text[2] # Получаем строку с телефоном\n data[\"Telephone\"] = re.sub(\n '[- ]*',\n '',\n re.findall(r'[(][0-9]{3,}[)]\\s*[0-9]+[-\\s]*[0-9]+[-\\s]*[0-9]', telephone)[0]\n ) # Получаем сам номер телефона поиском в строке по шаблону номера телефона\n\n email = text[3] # Получаем строку с почтой\n data[\"E-mail\"] = re.findall(r'\\w+@[A-Z0-9]+\\.[A-Z]{2,4}', email, flags=re.IGNORECASE)[0] # Получаем саму почту поиском в строке по шаблону почты\n cursor = db.cursor()\n request = \"INSERT INTO peoples VALUES({},{},{},{},{},{},{})\".format(\n \"\\'{}\\'\".format(data[\"Surname\"]),\n \"\\'{}\\'\".format(data[\"Name\"]),\n \"\\'{}\\'\".format(data[\"Patronymic\"]),\n int(data[\"Region\"]),\n int(data[\"City\"]),\n \"\\'{}\\'\".format(data[\"Telephone\"]),\n \"\\'{}\\'\".format(data[\"E-mail\"])\n ) # Вставляем в таблицу полученные с резюме данные\n cursor.execute(request)\n db.commit() # Фиксируем изменения\n print('''\n \n \n \n \n \n ''') # Уведомляем пользователя о том, что данные уже добавлены и возвращаемя обратно к таблице\nelif 'exportPdfButton' in form: # Если нажата кнопка \"Экспортировать таблицу в PDF\"\n newPdf = FPDF() # Создаем pdf и добавляем шрифт для записи русских символов\n newPdf.add_font('Athena', '', 'font/new_athena_unicode.ttf', uni=True)\n cursor = db.cursor() # Создаем курсор перед выполением запроса\n cursor.execute('''\n SELECT p.surname, p.name, p.patronymic, r.region, c.city, p.telephone, p.email FROM peoples p\n JOIN regions r ON p.regionId = r.id\n JOIN cities c ON (p.cityId=c.id AND p.regionId = c.regionId)\n ''') # Получаем все данные с таблицы\n peoples = cursor.fetchall() # Забираем все найденные данные\n for i, person in enumerate(peoples): # Постепенно заполняем файл\n newPdf.add_page() # Создаем новую страницу в файле (для резюме следующего человека из списка)\n newPdf.set_font(family=\"Athena\", size=30) # Устанавливаем шрифт\n newPdf.cell(0, 10, txt=\"Резюме {}\".format(i+1), ln=1, align=\"C\") # Заголовок\n newPdf.cell(0, 10, txt=\"\", ln=1, align=\"C\") # Новая строчка\n fio = ' '.join([person[0], person[1]]) # Имя и Фамилия соединятются через пробел\n if person[2] != '-':\n fio = ' '.join([fio, person[2]]) # Если указано и отчество, то присоединяем и отчество\n newPdf.cell(0, 10, txt=fio, ln=1, align=\"C\") # Вставляем строчку с ФИО\n newPdf.set_font(family=\"Athena\", size=20) # Устанавливаем шрифт (уменьшаем размер)\n location = ''\n if person[3] != '-' and person[4] == '-':\n location = person[3]\n elif person[3] == '-' and person[4] != '-':\n location = person[4]\n else:\n location = ', '.join([person[3], person[4]])\n newPdf.cell(0, 10, txt=\"Проживает в {}\".format(location), ln=1, align=\"C\") # Вставляем строку с местом проживанием (если что-то не указано, то пропускаем его)\n if person[5] != '-':\n newPdf.cell(0, 10, txt=\"Телефон +7{}\".format(person[5]), ln=1, align=\"C\") # Если указан телефон, то добавляем в резюме\n if person[6] != '-':\n newPdf.cell(0, 10, txt=\"Почта {}\".format(person[6]), ln=1, align=\"C\") # Если указана почта, то добавляем в резюме\n newPdf.output(\"Peoples.pdf\") # Сохраняем все сформированные данные в файле pdf\n print('''\n \n \n \n \n \n ''') # Уведомляем пользователя о том, что данные уже экспортированы в Peoples.pdf и возвращаемя обратно к таблице\n","sub_path":"cgi-bin/formTableListener.py","file_name":"formTableListener.py","file_ext":"py","file_size_in_byte":12851,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"340787037","text":"import logging\nimport time\nimport sys\n\nimport smpplib.gsm\nimport smpplib.client\nimport smpplib.consts\nimport config\n\n# if you want to know what's happening\nlogging.basicConfig(level='DEBUG')\n\nclient = smpplib.client.Client(config.host, config.port, allow_unknown_opt_params=True)\n\ndef handle_receive_sms(pdu):\n logging.debug('Sample dict log: %s', pdu)\n return 0 # cmd status for deliver_sm_resp\n\ndef send_message(part):\n pdu = client.send_message(\n source_addr_ton=smpplib.consts.SMPP_TON_INTL,\n source_addr=config.source_addr,\n dest_addr_ton=smpplib.consts.SMPP_TON_INTL,\n destination_addr=config.default_receiver,\n short_message=part,\n data_coding=encoding_flag,\n esm_class=msg_type_flag,\n registered_delivery=True,\n )\n\ndef listen(client):\n client.listen()\n\n# Print when obtain message_id\nclient.set_message_sent_handler(\n lambda pdu: sys.stdout.write('sent {} {}\\n'.format(pdu.sequence, pdu.message_id)))\nclient.set_message_received_handler(lambda pdu: handle_receive_sms(pdu))\n\nclient.connect()\nclient.bind_transceiver(system_id=config.system_id, password=config.password)\n\ntry:\n\tlisten(client)\nexcept:\n\ttime.sleep(600)\n\tlisten(client)\n","sub_path":"client.py","file_name":"client.py","file_ext":"py","file_size_in_byte":1215,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"557091029","text":"from django.contrib.contenttypes.fields import GenericForeignKey\nfrom django.contrib.contenttypes.models import ContentType\nfrom django.db import models\nfrom django.contrib.auth.models import User\nfrom main.models import Place\n\n\nclass CommentManager(models.Manager):\n def filter_by_instance(self, instance):\n content_type = ContentType.objects.get_for_model(instance)\n obj_id = instance.id\n qs = super(CommentManager, self).filter(content_type=content_type, object_id=obj_id)\n return qs\n\n\nclass Comment(models.Model):\n user = models.ForeignKey(User, on_delete=models.CASCADE, default=1)\n content_type = models.ForeignKey(ContentType, on_delete=models.CASCADE, null=True)\n object_id = models.PositiveIntegerField(null=True)\n content_object = GenericForeignKey('content_type', 'object_id')\n content = models.TextField()\n timestamp = models.DateTimeField(auto_now_add=True)\n\n def __str__(self):\n return str(self.user.username)\n\n objects = CommentManager()\n","sub_path":"mainproject/comments/models.py","file_name":"models.py","file_ext":"py","file_size_in_byte":1015,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"652282885","text":"import psycopg2\nimport base64\nimport os\nfrom python.Utils import get_images_label\nfrom psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT\nfrom psycopg2.sql import Identifier, SQL\n\ncursor = \"\"\n\n\ndef create_filled_tables():\n for image_label in get_images_label():\n cursor.execute(SQL(\"CREATE TABLE {} (id SERIAL, data BYTEA)\").format(Identifier(image_label)))\n files = next(os.walk(os.getcwd() + \"\\\\assets\\\\img\\\\\" + image_label))[2]\n location = \"assets/img/\" + image_label + \"/\"\n for file in files:\n with open(location + file, \"rb\") as img:\n data = base64.b64encode(img.read())\n cursor.execute(SQL(\"INSERT INTO {} (data) VALUES (%s)\").format(Identifier(image_label)), [data])\n\n\ndef get_data_from_db(label):\n cursor.execute(SQL(\"SELECT data FROM {} ORDER BY random() limit 30\").format(Identifier(label)))\n return cursor.fetchall()\n\n\ndef connect():\n global cursor\n con = psycopg2.connect(database=\"\", user=\"\",\n password=\"\",\n host=\"\", port=\"5432\")\n con.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)\n cursor = con.cursor()\n","sub_path":"python/Database.py","file_name":"Database.py","file_ext":"py","file_size_in_byte":1165,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"38613604","text":"# Copyright (c) 2013, 2018 National Technology and Engineering Solutions of Sandia, LLC . Under the terms of Contract\n# DE-NA0003525 with National Technology and Engineering Solutions of Sandia, LLC, the U.S. Government\n# retains certain rights in this software.\n\n#!/usr/bin/env python\n\nimport os\nimport subprocess\n\nenabled_plugins = \"/etc/munin/plugins\"\nplugin_storage = \"/usr/share/munin/plugins\"\nconf_storage = \"/etc/munin/plugin-conf.d\"\ncontext = \"system_u:object_r:munin_unconfined_plugin_exec_t:s0\"\n\nfor plugin in [\"couchdb-availability\", \"couchdb-request-times\", \"slycat-availability\", \"slycat-files\", \"slycat-memory\", \"slycat-threads\", \"slycat-requests\"]:\n subprocess.check_call([\"cp\", plugin, plugin_storage])\n subprocess.check_call([\"chown\", \"root:root\", os.path.join(plugin_storage, plugin)])\n subprocess.check_call([\"chmod\", \"755\", os.path.join(plugin_storage, plugin)])\n subprocess.check_call([\"chcon\", context, os.path.join(plugin_storage, plugin)])\n subprocess.check_call([\"ln\", \"-sf\", os.path.join(plugin_storage, plugin), os.path.join(enabled_plugins, plugin)])\n\nfor conf in [\"slycat.conf\", \"slycat-files.conf\", \"slycat-requests.conf\"]:\n subprocess.check_call([\"cp\", conf, conf_storage])\n\nsubprocess.check_call([\"/etc/init.d/munin-node\", \"restart\"])\n","sub_path":"munin-plugins/install.py","file_name":"install.py","file_ext":"py","file_size_in_byte":1273,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"525260055","text":"# Copyright CERFACS (http://cerfacs.fr/)\n# Apache License, Version 2.0 (http://www.apache.org/licenses/LICENSE-2.0)\n#\n# Author: Natalia Tatarinova\n\nfrom datetime import datetime\n\n\n# set the global attributs \"title\", \"history\", \"reference\", \"institution\" and \"comment\" in output meta data\n# (the minimum set of global attributes recomended by CF: http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.4/cf-conventions.html)\n\n\ndef title(out_nc, indice_name):\n '''\n Set the global attribute \"title\" in output meta data\n \n :param out_nc: out NetCDF dataset\n :type out_nc: netCDF4.Dataset\n :param indice_name: name of indice \n :type indice_name: str\n \n '''\n \n if indice_name in ['TG', 'TX', 'TN', 'DTR', 'ETR', 'vDTR']:\n indice_group = 'temperature'\n elif indice_name in ['SU', 'TR', 'CSU', 'TXx', 'TNx', 'TG90p', 'TX90p', 'TN90p', 'WSDI']:\n indice_group = 'heat'\n elif indice_name in ['GD4', 'GSL', 'FD', 'CFD', 'HD17','ID', 'TXn', 'TNn', 'TG10p', 'TX10p', 'TN10p', 'CSDI']:\n indice_group = 'cold'\n elif indice_name in ['CDD']:\n indice_group = 'drought' \n elif indice_name in ['PRCPTOT', 'RR1', 'SDII', 'CWD', 'R10mm', 'R20mm', 'RX1day', 'RX5day', 'R75p', 'R95p', 'R99p', 'R75pTOT', 'R95pTOT', 'R99pTOT']:\n indice_group = 'rain'\n elif indice_name in ['SD','SD1', 'SD5cm', 'SD50cm']:\n indice_group = 'snow'\n elif indice_name in ['CD','CW', 'WD', 'WW']:\n indice_group = 'compound'\n \n # example: title: ECA heat indice SU\n title_str = 'ECA {0} indice {1}'.format(indice_group, indice_name)\n\n out_nc.setncattr('title', title_str)\n \ndef history(out_nc, calc_grouping, indice_name, time_range):\n '''\n Set the global attribute \"title\" in output meta data\n \n :param out_nc: out NetCDF dataset\n :type out_nc: netCDF4.Dataset\n :param calc_grouping: temporal grouping to apply for calculations\n :type calc_grouping: list of str or int\n :param indice_name: name of indice \n :type indice_name: str\n :param time_range: upper and lower bounds for time dimension subsetting\n :type time_range:[datetime.datetime, datetime.datetime]\n \n \n '''\n\n current_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\n dt1 = time_range[0]\n dt2 = time_range[1]\n \n dt1_str = '{0}-{1}-{2}'.format(dt1.year, dt1.month, dt1.day)\n dt2_str = '{0}-{1}-{2}'.format(dt2.year, dt2.month, dt2.day)\n\n # make an attempt to select the mode from a seasonal grouping object\n try:\n mode = calc_grouping.icclim_mode\n # if this attribute does not exist, attempt to identify the grouping through other comparisons methods\n except AttributeError:\n ## use sets to allow different orderings\n if set(calc_grouping) == set(['year','month']):\n mode = 'monthly time series'\n ## always convert to list before comparison in case a tuple is passed\n elif list(calc_grouping) == ['year']:\n mode = 'annual'\n elif list(calc_grouping) == ['month']:\n mode = 'monthly climatology'\n else:\n mode = str(calc_grouping)\n # etc ...\n \n # example of history_str: 2012-10-02 15:30:20 Calculation of SU indice (monthly) from 1960-01-01 to 1990-12-31.\n history_str = '{0} Calculation of {1} indice ({2}) from {3} to {4}.'.format(current_time, indice_name, mode, dt1_str, dt2_str)\n\n out_nc.setncattr('history', getattr(out_nc,'history') + ' \\n' + history_str)\n \ndef history2(out_nc, calc_grouping, indice_name, time_range):\n '''\n Set the global attribute \"title\" in output meta data\n \n :param out_nc: out NetCDF dataset\n :type out_nc: netCDF4.Dataset\n :param calc_grouping: temporal grouping to apply for calculations\n :type calc_grouping: list of str or int\n :param indice_name: name of indice \n :type indice_name: str\n :param time_range: upper and lower bounds for time dimension subsetting\n :type time_range:[datetime.datetime, datetime.datetime]\n \n \n '''\n\n current_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\n dt1 = time_range[0]\n dt2 = time_range[1]\n \n dt1_str = '{0}-{1}-{2}'.format(dt1.year, dt1.month, dt1.day)\n dt2_str = '{0}-{1}-{2}'.format(dt2.year, dt2.month, dt2.day)\n \n if calc_grouping == 'year':\n mode = 'annual time series'\n elif calc_grouping == 'month':\n mode = 'monthly time series'\n elif calc_grouping == 'DJF':\n mode = 'winter time series'\n elif calc_grouping == 'MAM':\n mode = 'spring time series'\n elif calc_grouping == 'JJA':\n mode = 'summer time series'\n elif calc_grouping == 'SON':\n mode = 'autumn time series'\n elif calc_grouping == 'ONDJFM':\n mode = 'winter half-year time series'\n elif calc_grouping == 'AMJJAS':\n mode = 'summer half-year time series'\n elif type(calc_grouping) is list:\n if calc_grouping[0]=='month':\n months = calc_grouping[1]\n mode = 'monthly time series (months: ' + str(months) + ')' \n elif calc_grouping[0]=='season':\n months_season = calc_grouping[1]\n if type(months_season) is list: \n season = months_season\n elif type(months_season) is tuple:\n season = months_season[0]+months_season[1]\n mode = 'seasonal time series (season: ' + str(season) + ')' \n \n else:\n raise(NotImplementedError(calc_grouping))\n # etc ...\n \n # example of history_str: 2012-10-02 15:30:20 Calculation of SU indice (monthly) from 1960-01-01 to 1990-12-31.\n history_str = '{0} Calculation of {1} indice ({2}) from {3} to {4}.'.format(current_time, indice_name, mode, dt1_str, dt2_str)\n\n out_nc.setncattr('history', getattr(out_nc,'history') + ' \\n' + history_str) # ? \n\n\ndef references(out_nc):\n '''\n Set the global attribute \"references\" in output meta data\n \n :param out_nc: out NetCDF dataset\n :type out_nc: netCDF4.Dataset\n \n '''\n \n references_str = 'ATBD of the ECA indices calculation (http://eca.knmi.nl/documents/atbd.pdf)'\n out_nc.setncattr('references', references_str)\n\n\ndef institution(out_nc, institution_str):\n '''\n Set the global attribute \"institution\" in output meta data\n \n :param out_nc: out NetCDF dataset\n :type out_nc: netCDF4.Dataset\n :param institution_str: institution which uses this library\n :type institution_str: str\n \n '''\n \n #institution_str = 'Climate impact portal (http://climate4impact.eu)'\n \n out_nc.setncattr('institution', institution_str)\n \n \ndef comment(out_nc, indice_name):\n '''\n Set the global attribute \"comment\" in output meta data\n \n :param out_nc: out NetCDF dataset\n :type out_nc: netCDF4.Dataset\n \n Note: will be defined for several indices, else will be empty\n \n '''\n \n if indice_name == 'GSL':\n comment_str = 'This indice is defined only for the northern hemisphere'\n \n # elif ...\n \n # elif ...\n \n # etc\n \n else:\n comment_str = ' '\n \n out_nc.setncattr('comment', comment_str)\n","sub_path":"icclim/set_globattr.py","file_name":"set_globattr.py","file_ext":"py","file_size_in_byte":7137,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"459074431","text":"# Pyrogram - Telegram MTProto API Client Library for Python\n# Copyright (C) 2017-2018 Dan Tès \n#\n# This file is part of Pyrogram.\n#\n# Pyrogram is free software: you can redistribute it and/or modify\n# it under the terms of the GNU Lesser General Public License as published\n# by the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# Pyrogram is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU Lesser General Public License for more details.\n#\n# You should have received a copy of the GNU Lesser General Public License\n# along with Pyrogram. If not, see .\n\nfrom pyrogram.api.core import Object\n\n\nclass PhotoSize(Object):\n \"\"\"This object represents one size of a photo or a file / sticker thumbnail.\n\n Args:\n file_id (``str``):\n Unique identifier for this file.\n\n width (``int``):\n Photo width.\n\n height (``int``):\n Photo height.\n\n file_size (``int``, *optional*):\n File size.\n\n date (``int``, *optional*):\n Date the photo was sent in Unix time\n \"\"\"\n\n ID = 0xb0700005\n\n def __init__(self, file_id, width, height, file_size=None, date=None):\n self.file_id = file_id # string\n self.width = width # int\n self.height = height # int\n self.file_size = file_size # flags.0?int\n self.date = date\n","sub_path":"ENV/lib/python3.5/site-packages/pyrogram/client/types/photo_size.py","file_name":"photo_size.py","file_ext":"py","file_size_in_byte":1582,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"325179916","text":"from django.http import HttpResponseForbidden\nfrom django.shortcuts import get_object_or_404\nfrom django.urls import resolve\n\nimport waffle\nfrom project.models import ProjectTeam, Issue, Project\nfrom re import compile\n\nPROJECT_URLS = [compile(r'^project/.+')]\nISSUE_ORDER = compile(r'^project/issue_order/$')\n\n\nclass CheckProjectRelation(object):\n def __init__(self, get_response):\n self.get_response = get_response\n\n def is_user_attached_to_project(self, user_id, project_id):\n user_project_team = ProjectTeam.objects.filter(project_id=project_id, employees=user_id)\n if user_project_team:\n return True\n else:\n get_object_or_404(Project, pk=project_id)\n return False\n\n def __call__(self, request):\n path = request.path_info.lstrip('/')\n if request.user.is_staff or \\\n not any(m.match(path) for m in PROJECT_URLS):\n response = self.get_response(request)\n return response\n\n if waffle.flag_is_active(request, 'create_team') and path == 'project/create/':\n return self.get_response(request)\n\n resolved = resolve(request.path)\n if resolved.kwargs.get('project_id', False):\n if self.is_user_attached_to_project(request.user.id,\n resolved.kwargs['project_id']):\n response = self.get_response(request)\n return response\n\n if request.method == 'POST':\n response = self.get_response(request)\n return response\n\n return HttpResponseForbidden()\n","sub_path":"Jiller/middleware/CheckProjectRelationMiddleware.py","file_name":"CheckProjectRelationMiddleware.py","file_ext":"py","file_size_in_byte":1609,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"438134608","text":"from selenium import webdriver\nfrom selenium.webdriver.common.keys import Keys\nfrom selenium.webdriver.common.action_chains import ActionChains\nimport time\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom selenium.webdriver.support import expected_conditions as EC\n\nfrom openpyxl import Workbook, load_workbook\nfrom os.path import exists\nfrom datetime import datetime\nimport re\nimport string\nfrom openpyxl.styles import PatternFill, Color\n\ndef is_digit(str):\n try:\n tmp = float(str)\n return True\n except ValueError:\n return False\n\ntoday = datetime.now()\ntodayDate = today.strftime('%Y-%m-%d')\nMonthDate = today.strftime('%Y-%m')\ntodayCnt = int(today.strftime('%d'))\n\n#work_path = 'C:/study/python/chubb/'\nwork_path = 'D:/dev/python/chubb/'\n\ntoday_file_name = 'TaskToClose_' + MonthDate + '.xlsx'\nfile_path = work_path + today_file_name\n\nif exists(file_path):\n result_xlsx = load_workbook(file_path)\n worksheet = result_xlsx.active\n\nelse:\n result_xlsx = Workbook()\n worksheet = result_xlsx.active\n worksheet.append(['중분류', '소분류', 'ServiceNow', '등록일', '예상작업기간', '상태', '실제작업기간', '진행율', 'MM', '담당팀', '담당자', '요청자','datetime'])\n\n\n\nchg_file_name = 'ChangeToClose_' + MonthDate + '.xlsx'\nchg_file_path = work_path + chg_file_name\n\nif exists(chg_file_path):\n chg_xlsx = load_workbook(chg_file_path)\n chg_sheet = chg_xlsx.active\n\nelse:\n chg_xlsx = Workbook()\n chg_sheet = chg_xlsx.active\n chg_sheet.append(['중분류', '소분류', 'ServiceNow', '등록일', '예상작업기간', '상태', '실제작업기간', '진행율', 'MM', '담당팀', '담당자', '요청자','datetime'])\n\n# driver = webdriver.Chrome('D:\\dev\\python\\chromedriver')\ndriver = webdriver.Chrome(work_path + 'chromedriver')\n\ninput_sdesc = '' # 제목\ncno_text = '' # 콜번호\nopened_t = '' # 요청일시\ncaller_t = '' # 요청자\nworkguy = '' # 담당자\nrequestNo = '' # Request번호\nisApproved = ''\ndoneYN = ''\ntransferDate = ''\netc = '' # 오류 내용\noriDesc = '' # 요청내용\nCALL_URL = ''\nREQ_URL = ''\nIT_worker = ''\ntitleM = '' #중분류\ndoneDate = '' # 처리일\nclickLabel = 'ChangeToClose'\n#clickLabel = 'TaskToCloseAll'\n\ntry:\n driver.get('https://chubb.service-now.com')\n\n elem = driver.find_element_by_id('username')\n elem.send_keys('jsmoon')\n\n elem = driver.find_element_by_id('password')\n elem.send_keys('Niceday77')\n # elem.send_keys(open('password').read().strip())\n elem.send_keys(Keys.RETURN)\n\n elem = driver.find_element_by_name('securityCode')\n inputKey = input()\n elem.send_keys(inputKey)\n elem.send_keys(Keys.RETURN)\n\n # 아이프레임이 로딩 끝나기를 ��다린다.\n iframe = driver.find_element_by_id('gsft_main')\n driver.switch_to.frame(iframe)\n\n WebDriverWait(driver, 60).until(\n # By.ID 는 ID로 검색, By.CSS_SELECTOR 는 CSS Selector 로 검색\n EC.presence_of_element_located((By.ID, \"sysparm_page_num\"))\n )\n\n waitingTime = 0\n\n # 여기서 부터 반복~~~\n while 1:\n time.sleep(waitingTime)\n\n # favorites tab 클릭\n driver.switch_to.default_content()\n WebDriverWait(driver, 60).until(\n EC.element_to_be_clickable((By.ID, \"favorites_tab\"))\n )\n\n driver.find_element_by_xpath('//a[@id=\"favorites_tab\"]').click()\n\n wait = WebDriverWait(driver, 60)\n cond = EC.element_to_be_clickable((By.LINK_TEXT, clickLabel))\n btn = wait.until(cond)\n btn.click()\n\n iframe = driver.find_element_by_id('gsft_main')\n driver.switch_to.frame(iframe)\n\n list_body = driver.find_element_by_class_name('list2_body')\n elems = list_body.find_elements_by_xpath('//tr[contains(@id,\"row_\")]')\n\n # 처리할 대상\n cno_t = ''\n cno_text = ''\n tag_t = ''\n caller_t = ''\n desc_t = ''\n doneYN = 'N'\n workguy = ''\n doneDate = ''\n taskType = ''\n isDB = ''\n isApp = ''\n isClose = ''\n state = ''\n\n for elem in elems:\n\n taskType = ''\n isDB = ''\n isApp = ''\n isClose = ''\n titleM = ''\n cno_text = ''\n state = ''\n cno_t = ''\n\n cno = elem.find_element_by_xpath('.//a[@class=\"linked formlink\"]')\n\n clink = cno.get_attribute('href')\n desc = elem.find_element_by_xpath('./td[4]')\n desc_chk = desc.text\n desc_chk = desc_chk.lower()\n cno_text = cno.text\n\n workguy = elem.find_element_by_xpath('./td[5]/a').text # 담당자\n caller_t = elem.find_element_by_xpath('./td[6]/a').text # 요청자\n state = elem.find_element_by_xpath('./td[7]').text # 상태\n #print('workguy:'+workguy)\n #print('caller_t:' + caller_t)\n #print('desc_chk:' + desc_chk)\n\n if cno_text.startswith('SCTASK'):\n taskType = 'SCTASK'\n if cno_text.startswith('CTASK'):\n taskType = 'CTASK'\n if cno_text.startswith('CHG'):\n taskType = 'CHG'\n if cno_text.startswith('INC'):\n taskType = 'INC'\n\n # 반영건 종료 대상 판단\n if (taskType == 'CTASK' and state == 'In Progress' and 'app완' in desc_chk and workguy in ['In-Moo Lee', 'Jin-Sung Moon']):\n print(\"111 taskNo:\" + cno_text)\n isClose = 'Y'\n isApp = 'Y'\n titleM = '소스반영'\n elif (taskType == 'CTASK' and state == 'In Progress' and 'db완' in desc_chk and 'app완' in desc_chk and workguy in ['Yong-Keum Kim']):\n print(\"222 taskNo:\" + cno_text)\n isClose = 'Y'\n isDB = 'Y'\n titleM = 'DB반영'\n elif '(선처리)' in desc_chk or '(완료)' in desc_chk or '[완료]' in desc_chk or '[완]' in desc_chk or '(완)' in desc_chk or '[처리완료]' in desc_chk:\n print(\"333 taskNo:\" + cno_text)\n isClose = 'Y'\n elif taskType == 'CHG' and (state == 'Review' or state == 'Scheduled') :\n print(\"CHG 처리대상:\" + cno_text)\n isClose = 'Y'\n\n # 중분류\n if taskType == 'CTASK' and 'app완' in desc_chk :\n isApp = 'Y'\n titleM = '소스반영'\n if taskType == 'CTASK' and 'db완' in desc_chk:\n isDB = 'Y'\n titleM = 'DB반영'\n\n\n\n if isClose:\n cno_t = cno\n # caller_t = caller.text\n desc_t = desc.text\n CALL_URL = clink\n # opened_t = opened.text\n print(\"taskNo:\" + cno.text)\n #print(CALL_URL)\n break\n\n\n # 담당자 지정건 없으면 종료\n if not isClose:\n #waitingTime = 60\n\n if clickLabel == 'ChangeToClose':\n\n clickLabel = 'TaskToCloseAll'\n else:\n clickLabel = 'ChangeToClose'\n\n print('------ 대상없음 '+clickLabel+'로 전환!! ------')\n\n continue\n\n\n waitingTime = 0\n\n # 하단 페이지 타이밍 로딩 기다리기\n WebDriverWait(driver, 60).until(\n EC.element_to_be_clickable((By.ID, \"page_timing_div\"))\n )\n\n # 요청서 번호 클릭\n cno_t.click()\n\n # Work notes 입력란 표시까지 대기\n WebDriverWait(driver, 60).until(\n EC.presence_of_element_located((By.ID, \"activity-stream-textarea\"))\n )\n\n if taskType == 'SCTASK':\n print('-------------SCTASK--------------')\n\n RequestedFor = driver.find_element_by_xpath(\"//input[@id='sys_display.sc_task.request_item.request.requested_for']\")\n AssignedTo = driver.find_element_by_xpath(\"//*[@id='sys_display.sc_task.assigned_to']\")\n ExpectedStart = driver.find_element_by_xpath(\"//*[@id='sc_task.expected_start']\")\n ChangedDate = driver.find_element_by_xpath(\"//*[@id='sn_form_inline_stream_entries']/ul/li[1]/div[2]/span/div[1]\")\n ShortDesc = driver.find_element_by_xpath(\"//input[@id='sc_task.short_description']\")\n Description = driver.find_element_by_xpath(\"//*[@id='sc_task.description']\")\n\n input_sdesc = ShortDesc.get_attribute('value')\n #opened_t = ExpectedStart.get_attribute('value')\n changedDate_t = ChangedDate.text\n IT_worker = AssignedTo.get_attribute('value')\n caller_t = RequestedFor.get_attribute('value')\n oriDesc = Description.get_attribute('value')\n\n #print(input_sdesc)\n #print(opened_t)\n #print(changedDate_t)\n #print(IT_worker)\n #print(caller_t)\n #print(oriDesc)\n\n tmpDesc = oriDesc.lower()\n\n for s_word in ['이용건수','수급권','한도초과','한도 초과','배서불가','담보삭제','강제배서', '강제 배서', '계약상태', '계약 상태','피보험자 오류','피보험자 수','고객번호','고객 번호','pos','cpc','보험시작일 변경','피보험자업로드','계좌 변경','webfax','피보험자 수정','단체 피보험자','출력물','피보험자 이름변경']:\n if s_word in tmpDesc:\n titleM = '계속계약'\n break\n for s_word in ['dc code', 'producer code', '머리디안', 'meridian','pacpl']:\n if s_word in tmpDesc:\n titleM = '머리디안'\n break\n for s_word in ['지연일수','보험금','응급실','지급일','claim','보상','출재']:\n if s_word in tmpDesc:\n titleM = '보상'\n break\n for s_word in ['상품복사','상품개정','개정상품','판매제한','판매플랜','마케팅플랜','상품복사','상품 복사','plan 복사','plan복사','pve','플랜코드','담보 명칭 변경']:\n if s_word in tmpDesc:\n titleM = '상품'\n break\n for s_word in ['수당']:\n if s_word in tmpDesc:\n titleM = '수당'\n break\n for s_word in ['즉시이체','환급목록','거래자료','거래 자료','가상계좌','캠페인 소급','시책','수수료','결제','입출금','환급금','가마감']:\n if s_word in tmpDesc:\n titleM = '입출금'\n break\n for s_word in ['입사자','수수료 정산 종료일','권한 부여','권한부여','id등록','id 등록','발령','전배','사용자명','맥 추가','mac 추가','수신인','겸직','개명','권한삭제','권한 삭제','권한','해촉','퇴사','조직']:\n if s_word in tmpDesc:\n titleM = '조직'\n break\n for s_word in ['청약','갱신','단체','포괄번호']:\n if s_word in tmpDesc:\n titleM = '청약'\n break\n\n if not titleM:\n titleM = '기타'\n\n if opened_t:\n opened_t = opened_t[:10]\n\n if not opened_t:\n opened_t = changedDate_t[:10]\n\n opened_t = opened_t.replace(\"-\", \".\")\n # 완료일자\n items = re.findall('처리일자\\s\\s:\\s([^\\n]+)', tmpDesc)\n if len(items) > 0:\n doneDate = items[0]\n #work_period = datetime.now().strftime('%m.%d') + '~' + datetime.now().strftime('%m.%d')\n\n print('titleM:'+titleM)\n print('doneDate:(' + doneDate+')')\n\n if doneDate:\n work_period = doneDate + '~' + doneDate\n\n # 처리일자를 기재하지 않으면 요청일자를 처리일로 셋팅\n if not doneDate:\n work_period = opened_t[5:] + '~' + opened_t[5:]\n\n print(work_period)\n\n # 요청일자\n reqDate = ''\n items = re.findall('요청일자\\s\\s:\\s([^\\n]+)', tmpDesc)\n if len(items) > 0:\n reqDate = items[0]\n reqDate = reqDate.replace('-','.')\n\n print('reqDate:(' + reqDate + ')')\n\n if reqDate:\n opened_t = reqDate\n\n # 엑셀쓰기\n worksheet.append([titleM, input_sdesc, cno_text, opened_t, work_period, '완료', work_period, '100', '-', 'OPR', IT_worker, caller_t, datetime.now()])\n #worksheet.cell(5, (12 + todayCnt), '○')\n #ca2 = worksheet['R6']\n #ca2.fill = PatternFill(patternType='solid', fgColor=Color('00B0F0'))\n result_xlsx.save(file_path)\n\n # Work notes 입력란 표시까지 대기\n WebDriverWait(driver, 60).until(\n EC.visibility_of_element_located((By.ID, \"activity-stream-textarea\"))\n )\n # Work notes 입력\n driver.find_element_by_xpath(\"//textarea[@id='activity-stream-textarea']\").send_keys('Completed')\n\n # Close 버튼 클릭\n driver.find_element_by_xpath(\"//*[@id='close_sc_task']\").click()\n\n if taskType == 'CTASK':\n print('-------반영건-------CTASK----------------')\n\n AssignedTo = driver.find_element_by_xpath(\"//*[@id='sys_display.change_task.assigned_to']\")\n IT_worker = AssignedTo.get_attribute('value')\n ShortDesc = driver.find_element_by_xpath(\"//input[@id='change_task.short_description']\")\n input_sdesc = ShortDesc.get_attribute('value')\n\n planned_start_date = driver.find_element_by_xpath(\"//input[@id='change_task.planned_start_date']\")\n planned_end_date = driver.find_element_by_xpath(\"//input[@id='change_task.planned_end_date']\")\n planStartDate = planned_start_date.get_attribute('value')\n planEndDate = planned_end_date.get_attribute('value')\n print('planStartDate:'+planStartDate)\n print('planEndDate:' + planEndDate)\n\n ori_start_date = driver.find_element_by_xpath(\"//input[@id='sys_original.change_task.change_request.start_date']\")\n ori_end_date = driver.find_element_by_xpath(\"//input[@id='sys_original.change_task.change_request.end_date']\")\n oriStartDate = ori_start_date.get_attribute('value')\n oriEndDate = ori_end_date.get_attribute('value')\n print('oriStartDate:'+oriStartDate)\n print('oriEndDate:' + oriEndDate)\n\n if not planStartDate:\n planned_start_date.send_keys(oriStartDate)\n if not planEndDate:\n planned_end_date.send_keys(oriEndDate)\n\n if not titleM:\n titleM = 'DB작업'\n\n\n elems = driver.find_elements_by_xpath('//*[@class=\"h-card h-card_md h-card_comments\"]')\n i = 1\n max_e = len(elems)\n print('elems len: ' + str(max_e))\n for elem in elems:\n\n e_createdby = elem.find_element_by_xpath('.//*[@class=\"sn-card-component-createdby\"]')\n print('e_createdby:'+e_createdby.text)\n e_date = elem.find_element_by_xpath('.//*[@class=\"date-calendar\"]')\n print('e_date:'+e_date.text)\n '''\n if i == 1: # 완료일도 그냥 최초 작성일로 설정.\n doneDate = e_date.text\n doneDate = doneDate[5:10]\n doneDate = doneDate.replace(\"-\", \".\")\n '''\n if i == max_e: #최초작성일\n opened_t = e_date.text\n opened_t = opened_t[:10]\n opened_t = opened_t.replace(\"-\", \".\")\n\n doneDate = e_date.text\n doneDate = doneDate[5:10]\n doneDate = doneDate.replace(\"-\", \".\")\n\n caller_t = e_createdby.text\n i = i + 1\n\n\n # short desc에 종료일자 있으면 검사 ex) [완료][6.17]\n if input_sdesc:\n print('shortDesc:' + input_sdesc)\n\n # 완료일자\n items = re.findall('\\[([^]]+)', input_sdesc)\n\n for itm in items:\n itm = itm.replace('/', '.')\n\n if is_digit(itm) and len(itm) <= 5:\n doneDate = itm\n print('doneDate:' + doneDate)\n break\n\n\n print('opened_t:' + opened_t)\n print('doneDate:' + doneDate)\n work_period = doneDate + '~' + doneDate\n\n print('work_period:' + work_period)\n print('input_sdesc:' + input_sdesc)\n print('IT_worker:' + IT_worker)\n print('caller_t:' + caller_t)\n\n # 엑셀쓰기\n if isApp and isDB:\n worksheet.append(\n ['소스반영', input_sdesc, cno_text, opened_t, work_period, '완료', work_period, '100', '-', 'OPR',\n IT_worker, caller_t, datetime.now()])\n worksheet.append(\n ['DB반영', desc_t, cno_text, opened_t, work_period, '완료', work_period, '100', '-', 'OPR',\n 'Yong-Keum Kim',\n caller_t, datetime.now()])\n result_xlsx.save(file_path)\n else:\n worksheet.append(\n [titleM, input_sdesc, cno_text, opened_t, work_period, '완료', work_period, '100', '-', 'OPR',\n IT_worker,\n caller_t, datetime.now()])\n result_xlsx.save(file_path)\n\n\n # Close notes 입력란 표시까지 대기\n WebDriverWait(driver, 60).until(\n EC.visibility_of_element_located((By.ID, \"change_task.close_notes\"))\n )\n # Close code 선택\n driver.find_element_by_xpath(\"//option[@value='successful']\").click()\n # Close notes 입력\n close_notes = driver.find_element_by_xpath(\"//textarea[@id='change_task.close_notes']\")\n if not close_notes.text:\n close_notes.send_keys('Completed')\n\n # Close 버튼 클릭\n butts = driver.find_elements_by_xpath(\"//button[@id='change_task_to_closed']\")\n butt = butts[1]\n # print(butt.text)\n butt.click()\n #input()\n if taskType == 'CHG':\n # Close notes 입력란 표시까지 대기\n WebDriverWait(driver, 60).until(\n EC.visibility_of_element_located((By.ID, \"change_request.close_notes\"))\n )\n\n print('state:'+state)\n\n # 종료처리\n if state == 'Review':\n # Actual start end 입력\n planned_start_date = driver.find_element_by_xpath(\"//input[@id='change_request.work_start']\")\n planned_end_date = driver.find_element_by_xpath(\"//input[@id='change_request.work_end']\")\n planStartDate = planned_start_date.get_attribute('value')\n planEndDate = planned_end_date.get_attribute('value')\n print('Actual start date:' + planStartDate)\n print('Actual end date:' + planEndDate)\n\n ori_start_date = driver.find_element_by_xpath(\"//input[@id='change_request.start_date']\")\n ori_end_date = driver.find_element_by_xpath(\"//input[@id='change_request.end_date']\")\n oriStartDate = ori_start_date.get_attribute('value')\n oriEndDate = ori_end_date.get_attribute('value')\n print('oriStartDate:' + oriStartDate)\n print('oriEndDate:' + oriEndDate)\n\n if not planStartDate:\n planned_start_date.send_keys(oriStartDate)\n if not planEndDate:\n planned_end_date.send_keys(oriEndDate)\n\n AssignedTo = driver.find_element_by_xpath(\"//*[@id='sys_display.change_request.assigned_to']\")\n IT_worker = AssignedTo.get_attribute('value')\n ShortDesc = driver.find_element_by_xpath(\"//input[@id='change_request.short_description']\")\n input_sdesc = ShortDesc.get_attribute('value')\n RequestedBy = driver.find_element_by_xpath(\"//input[@id='sys_display.change_request.requested_by']\")\n caller_t = RequestedBy.get_attribute('value')\n\n # 활동이력\n elems = driver.find_elements_by_xpath('//*[@class=\"h-card h-card_md h-card_comments\"]')\n i = 1\n max_e = len(elems)\n print('elems len: ' + str(max_e))\n for elem in elems:\n\n e_createdby = elem.find_element_by_xpath('.//*[@class=\"sn-card-component-createdby\"]')\n #print('e_createdby:' + e_createdby.text)\n e_date = elem.find_element_by_xpath('.//*[@class=\"date-calendar\"]')\n #print('e_date:' + e_date.text)\n\n if i == 1: # 완료일\n doneDate = e_date.text\n doneDate = doneDate[5:10]\n doneDate = doneDate.replace(\"-\", \".\")\n\n if i == max_e: # 최초작성일\n opened_t = e_date.text\n opened_t = opened_t[:10]\n opened_t = opened_t.replace(\"-\", \".\")\n #caller_t = e_createdby.text\n i = i + 1\n work_period = doneDate + '~' + doneDate\n\n if not titleM:\n titleM = '종료처리'\n\n chg_sheet.append(\n [titleM, input_sdesc, cno_text, opened_t, work_period, '완료', work_period, '100', '-', 'OPR',\n IT_worker,\n caller_t, datetime.now()])\n chg_xlsx.save(chg_file_path)\n\n # Close code 선택\n driver.find_element_by_xpath(\"//option[@value='successful']\").click()\n # Close notes 입력\n driver.find_element_by_xpath(\"//textarea[@id='change_request.close_notes']\").send_keys('Completed')\n # Close 버튼 클릭\n butts = driver.find_elements_by_xpath(\"//button[@id='state_model_move_to_closed']\")\n butt = butts[1]\n # print(butt.text)\n\n #input() #################### test\n\n\n butt.click()\n # close 버튼이 사라질때까지 기다린다.\n WebDriverWait(driver, 60).until(\n EC.invisibility_of_element_located((By.XPATH, \"//button[@id='state_model_move_to_closed']\"))\n )\n # implement 처리\n if state == 'Scheduled':\n # implement 버튼 클릭\n butts = driver.find_elements_by_xpath(\"//button[@id='state_model_move_to_implement']\")\n butt = butts[1]\n butt.click()\n # close 버튼이 사라질때까지 기다린다.\n WebDriverWait(driver, 60).until(\n EC.invisibility_of_element_located((By.XPATH, \"//button[@id='state_model_move_to_implement']\"))\n )\n\n\nexcept Exception as e:\n print('----------- Main Error -------------')\n print(e)\n etc = str(e)\n worksheet.append(\n [input_sdesc, cno_text, oriDesc, opened_t, caller_t, workguy, requestNo, datetime.now(), etc, CALL_URL,\n REQ_URL])\n result_xlsx.save(file_path)\nfinally:\n print('~~~~~~~~~~ Main END ~~~~~~~~~~~~!')\n input()\n driver.quit()\n","sub_path":"TaskToClose.py","file_name":"TaskToClose.py","file_ext":"py","file_size_in_byte":23863,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"78080622","text":"from typing import List\nimport collections\n\nclass Solution:\n def canCross(self, stones: List[int]) -> bool:\n pastJumps = {x: set() for x in stones}\n pastJumps[0].add(0)\n \n for i in stones:\n for k in pastJumps[i]:\n for s in [k - 1, k, k + 1]:\n if s > 0 and i + s in pastJumps:\n pastJumps[i + s].add(s)\n \n return bool(pastJumps[stones[-1]])\n \n def canCross1(self, stones: List[int]) -> bool:\n pastJumps = collections.defaultdict(set)\n pastJumps[0] = {0}\n \n for i in range(1, len(stones)):\n newJumps = collections.defaultdict(set)\n for last, jumps in pastJumps.items():\n j = stones[i] - last\n \n if j in jumps or j + 1 in jumps or j - 1 in jumps:\n newJumps[stones[i]].add(j)\n \n pastJumps.update(newJumps)\n \n return len(pastJumps[stones[-1]]) != 0","sub_path":"leetcode/403-Frog-Jump.py","file_name":"403-Frog-Jump.py","file_ext":"py","file_size_in_byte":1023,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"351296938","text":"import re\nimport string\nimport collections as cll\nfrom scipy.stats import kendalltau\nimport math\nimport subprocess\n\n\nclass Bcolors:\n HEADER = '\\033[95m'\n OKBLUE = '\\033[94m'\n OKGREEN = '\\033[92m'\n WARNING = '\\033[93m'\n FAIL = '\\033[91m'\n ENDC = '\\033[0m'\n BOLD = '\\033[1m'\n UNDERLINE = '\\033[4m'\n\n @classmethod\n def postprocess(cls, input_str):\n input_str = input_str.replace(\"\", cls.HEADER)\n input_str = input_str.replace(\"\", cls.OKBLUE)\n input_str = input_str.replace(\"\", cls.OKGREEN)\n input_str = input_str.replace(\"\", cls.WARNING)\n input_str = input_str.replace(\"\", cls.FAIL)\n input_str = input_str.replace(\"\", cls.ENDC)\n input_str = input_str.replace(\"\", cls.BOLD)\n input_str = input_str.replace(\"\", cls.UNDERLINE)\n return input_str\n\n\ndef print_counter(counts, prefix=\"\"):\n keys = list(counts.keys())\n keys.sort()\n for key in keys:\n print(\"{}{} = {:d} / {:d} ({:.2f}%)\".format(prefix, key, counts[key], sum(counts.values()), counts[key] * 100 / sum(counts.values())))\n\ndef get_bucket(x, thresholds):\n bucket = -1\n for flt in thresholds:\n if x >= flt:\n bucket += 1\n else:\n break\n return bucket\n\n\ndef get_kendall_tau(x1, x2):\n x1 = normalize_answer(x1)\n x2 = normalize_answer(x2)\n\n x1_tokens = x1.split()\n x2_tokens = x2.split()\n\n for x1_index, tok in enumerate(x1_tokens):\n try:\n x2_index = x2_tokens.index(tok)\n x1_tokens[x1_index] = \"-{:d}\".format(x1_index + 1)\n x2_tokens[x2_index] = \"-{:d}\".format(x1_index + 1)\n except ValueError:\n pass\n\n common_seq_x1 = [int(x1_tok_flag.split(\"-\")[-1]) for x1_tok_flag in x1_tokens if x1_tok_flag.startswith(\"\")]\n common_seq_x2 = [int(x2_tok_flag.split(\"-\")[-1]) for x2_tok_flag in x2_tokens if x2_tok_flag.startswith(\"\")]\n\n assert len(common_seq_x1) == len(common_seq_x2)\n\n ktd = kendalltau(common_seq_x1, common_seq_x2).correlation\n anomaly = False\n\n if math.isnan(ktd):\n ktd = -1.0\n anomaly = True\n\n return ktd, anomaly\n\n\ndef normalize_answer(s):\n \"\"\"Lower text and remove punctuation, articles and extra whitespace.\"\"\"\n\n def remove_articles(text):\n return re.sub(r'\\b(a|an|the)\\b', ' ', text)\n\n def white_space_fix(text):\n return ' '.join(text.split())\n\n def remove_punc(text):\n exclude = set(string.punctuation)\n return ''.join(ch for ch in text if ch not in exclude)\n\n def lower(text):\n return text.lower()\n\n return white_space_fix(remove_articles(remove_punc(lower(s))))\n\n\ndef f1_score(prediction, ground_truth):\n \"\"\"Calculate word level F1 score.\"\"\"\n prediction_tokens = normalize_answer(prediction).split()\n ground_truth_tokens = normalize_answer(ground_truth).split()\n if not prediction_tokens and not ground_truth_tokens:\n return 1.0, 1.0, 1.0\n common = cll.Counter(prediction_tokens) & cll.Counter(ground_truth_tokens)\n num_same = sum(common.values())\n if num_same == 0:\n return 0, 0, 0\n precision = 1.0 * num_same / len(prediction_tokens)\n recall = 1.0 * num_same / len(ground_truth_tokens)\n f1 = (2 * precision * recall) / (precision + recall)\n return precision, recall, f1\n\n\ndef export_server(output, filename, server_folder, server=\"azkaban\"):\n with open(\"{}.txt\".format(filename), \"w\") as f:\n f.write(Bcolors.postprocess(output) + \"\\n\")\n print(\"Exporting {} to {}...\".format(filename, server))\n subprocess.check_output(\"cat {0}.txt | ansi2html.sh --palette=linux --bg=dark > {0}.html\".format(filename), shell=True)\n subprocess.check_output(\"scp {}.html {}:/scratch/kalpesh/style_transfer_overlap/data_logs/{}\".format(filename, server, server_folder), shell=True)\n\n\nhp_feature_sets = [\n (\"original\", \"input0\", \"save_62\", \"author_data/authors_1M_tokens_37_classes_srl_arg0_arg1\"),\n (\"punctuation\", \"punctuation_input0\", \"save_98\", \"author_data/authors_1M_tokens_37_classes_srl_arg0_arg1_punctuation\"),\n (\"pos_tags\", \"pos_tags_input0\", \"save_45\", \"author_data/authors_1M_tokens_37_classes_srl_arg0_arg1_pos_tag\"),\n (\"shuffle\", \"shuffle_input0\", \"save_60\", \"author_data/authors_1M_tokens_37_classes_srl_arg0_arg1_shuffle\"),\n (\"top_100\", \"top_100_input0\", \"save_89\", \"author_data/authors_1M_tokens_37_classes_srl_arg0_arg1_top_100\"),\n (\"top_10\", \"top_10_input0\", \"save_88\", \"author_data/authors_1M_tokens_37_classes_srl_arg0_arg1_top_10\"),\n]\nshakespeare_feature_sets = [\n (\"original\", \"input0\", \"save_110\", \"shakespeare/unsupervised_filtered\"),\n]\nshakespeare_prior_feature_sets = [\n (\"original\", \"input0\", \"save_151\", \"shakespeare/unsupervised_prior\")\n]\nshakespeare_prior_detokenized_feature_sets = [\n (\"original\", \"input0\", \"save_149\", \"shakespeare/unsupervised_prior_detokenize\")\n]\nformality_prior_feature_sets = [\n (\"original\", \"input0\", \"save_159\", \"formality/formality_prior\")\n]\nformality_prior_detokenized_feature_sets = [\n (\"original\", \"input0\", \"save_157\", \"formality/formality_prior_detokenize\")\n]\nshakespeare_aae_tweets_feature_sets = [\n (\"original\", \"input0\", \"save_112\", \"dataset_pools/shakespeare_aae_tweets\"),\n]\nseven_styles_feature_sets = [\n (\"original\", \"input0\", \"save_116\", \"dataset_pools/shakespeare_aae_tweets_bible_romantic-poetry_joyce_congress-bills\"),\n]\nsix_styles_feature_sets = [\n (\"original\", \"input0\", \"save_123\", \"dataset_pools/shakespeare_aae_tweets_bible_romantic-poetry_switchboard\"),\n]\npoliteness_feature_sets = [\n (\"original\", \"input0\", \"save_147\", \"politeness/politeness\"),\n]\ngender_feature_sets = [\n (\"original\", \"input0\", \"save_139\", \"gender/gender\"),\n]\nformality_feature_sets = [\n (\"original\", \"input0\", \"save_143\", \"formality/formality\"),\n]\npolitical_feature_sets = [\n (\"original\", \"input0\", \"save_145\", \"political-slant/political-slant\"),\n]\nten_styles_feature_sets = [\n (\"original\", \"input0\", \"save_133\", \"dataset_pools/shakespeare_aae_tweets_bible_romantic-poetry_switchboard_coha_3_bins_lyrics_full\"),\n]\ntwelve_styles_feature_sets = [\n (\"original\", \"input0\", \"save_161\", \"dataset_pools/shakespeare_aae_tweets_bible_romantic-poetry_congress-bills_joyce_switchboard_coha_3_bins_lyrics_full\"),\n]\neleven_styles_feature_sets = [\n (\"original\", \"input0\", \"save_170\", \"dataset_pools/shakespeare_aae_tweets_bible_romantic-poetry_joyce_switchboard_coha_3_bins_lyrics_full\"),\n]\n\nall_ft_sets = [\n hp_feature_sets, shakespeare_feature_sets, shakespeare_aae_tweets_feature_sets, seven_styles_feature_sets,\n six_styles_feature_sets, politeness_feature_sets, gender_feature_sets, formality_feature_sets,\n political_feature_sets, ten_styles_feature_sets, shakespeare_prior_detokenized_feature_sets, shakespeare_prior_feature_sets,\n formality_prior_feature_sets, formality_prior_detokenized_feature_sets, twelve_styles_feature_sets, eleven_styles_feature_sets\n]\n\n\ndef choose_classifier_feat_sets_from_dir(data_dir):\n stripped_data_dir = data_dir.replace(\"/mnt/nfs/work1/miyyer/kalpesh/projects/style-embeddings\", \"\").strip(\"/\")\n for ft_set in all_ft_sets:\n if ft_set[0][-1] == stripped_data_dir:\n return ft_set\n raise ValueError(\"ft_set not found\")\n\ndef choose_classifier_feat_sets(ft_set):\n if ft_set == \"shakespeare\":\n feature_sets = shakespeare_feature_sets\n elif ft_set == \"shakespeare_aae_tweets\":\n feature_sets = shakespeare_aae_tweets_feature_sets\n elif ft_set == \"seven_styles_feature_sets\":\n feature_sets = seven_styles_feature_sets\n elif ft_set == \"six_styles_feature_sets\":\n feature_sets = six_styles_feature_sets\n elif ft_set == \"politeness_feature_sets\":\n feature_sets = politeness_feature_sets\n elif ft_set == \"ten_styles_feature_sets\":\n feature_sets = ten_styles_feature_sets\n elif ft_set == \"twelve_styles_feature_sets\":\n feature_sets = twelve_styles_feature_sets\n elif ft_set == \"eleven_styles_feature_sets\":\n feature_sets = eleven_styles_feature_sets\n elif ft_set == \"formality_feature_sets\":\n feature_sets = formality_feature_sets\n elif ft_set == \"gender_feature_sets\":\n feature_sets = gender_feature_sets\n elif ft_set == \"political_feature_sets\":\n feature_sets = political_feature_sets\n elif ft_set == \"harry_potter\":\n feature_sets = hp_feature_sets\n elif ft_set == \"shakespeare_prior\":\n feature_sets = shakespeare_prior_feature_sets\n elif ft_set == \"shakespeare_prior_detokenize\":\n feature_sets = shakespeare_prior_detokenized_feature_sets\n elif ft_set == \"formality_prior\":\n feature_sets = formality_prior_feature_sets\n elif ft_set == \"formality_prior_detokenize\":\n feature_sets = formality_prior_detokenized_feature_sets\n else:\n raise ValueError(\"Invalid value for --ft_set\")\n\n return feature_sets\n","sub_path":"datasets/preprocess_utils.py","file_name":"preprocess_utils.py","file_ext":"py","file_size_in_byte":8947,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"190651205","text":"#!/usr/bin/env python\n#coding:utf-8\n\"\"\"\n Author: iJasonLee (kingmax_res@163.com | 184327932@qq.com)\n Purpose: \n Created: 2017/8/13\n\"\"\"\n\nimport sys\nfrom PyQt5.QtWidgets import *\nfrom PyQt5.QtGui import *\nfrom PyQt5.QtCore import *\n\n########################################################################\nclass Communicate(QObject):\n \"\"\"\"\"\"\n updateBW = pyqtSignal(int)\n \n########################################################################\nclass BurningWidget(QWidget):\n \"\"\"\"\"\"\n\n #----------------------------------------------------------------------\n def __init__(self):\n \"\"\"Constructor\"\"\"\n \n super(BurningWidget, self).__init__()\n self.initUI()\n \n #----------------------------------------------------------------------\n def initUI(self):\n \"\"\"\"\"\"\n self.setMinimumSize(1, 30)\n self.value = 75\n self.num = [75, 150, 225, 300, 375, 450, 525, 600, 675]\n \n #----------------------------------------------------------------------\n def setValue(self, val):\n \"\"\"\"\"\"\n self.value = val\n \n #----------------------------------------------------------------------\n def paintEvent(self, e):\n \"\"\"\"\"\"\n pt = QPainter()\n pt.begin(self)\n self.drawWidget(pt)\n pt.end()\n \n #----------------------------------------------------------------------\n def drawWidget(self, pt):\n \"\"\"\"\"\"\n MAX_CAPACITY = 700\n OVER_CAPACITY = 750\n \n font = QFont('Serif', 7, QFont.Light)\n pt.setFont(font)\n \n size = self.size()\n w = size.width()\n h = size.height()\n step = int(round(w/10))\n till = int((w / OVER_CAPACITY) * self.value)\n full = int((w / OVER_CAPACITY) * MAX_CAPACITY)\n \n pt.setPen(Qt.white)\n pt.setBrush(QColor(255, 255, 184)) \n if self.value >= MAX_CAPACITY:\n pt.drawRect(0, 0, full, h)\n c = QColor(255, 175, 175)\n pt.setPen(c)\n pt.setBrush(c)\n pt.drawRect(full, 0, till-full, h)\n else:\n pt.drawRect(0, 0, till, h)\n \n pen = QPen(QColor(20, 20, 20), 1, Qt.SolidLine)\n pt.setPen(pen)\n pt.setBrush(Qt.NoBrush)\n pt.drawRect(0, 0, w-1, h-1)\n \n j = 0\n for i in range(step, 10*step, step):\n pt.drawLine(i, 0, i, 5)\n metrics = pt.fontMetrics()\n txt = str(self.num[j])\n fw = metrics.width(txt)\n pt.drawText(i-fw/2, h/2, txt)\n j += 1\n \n\n########################################################################\nclass Window(QWidget):\n \"\"\"\"\"\"\n \n #----------------------------------------------------------------------\n def __init__(self):\n \"\"\"Constructor\"\"\"\n super(Window, self).__init__()\n self.initUI()\n\n #----------------------------------------------------------------------\n def initUI(self):\n \"\"\"\"\"\"\n OVER_CAPACITY = 750\n \n sld = QSlider(Qt.Horizontal, self)\n sld.setFocusPolicy(Qt.NoFocus)\n sld.setRange(1, OVER_CAPACITY)\n sld.setValue(75)\n sld.setGeometry(30, 40, 300, 30)\n \n self.c = Communicate()\n self.bwWidget = BurningWidget()\n self.c.updateBW[int].connect(self.bwWidget.setValue)\n \n sld.valueChanged[int].connect(self.changeValue)\n \n hbox = QHBoxLayout()\n hbox.addWidget(self.bwWidget)\n vbox = QVBoxLayout()\n vbox.addStretch(1)\n vbox.addLayout(hbox)\n self.setLayout(vbox)\n\n self.setGeometry(300, 300, 390, 210)\n self.setWindowTitle('Customize Burning Widget')\n self.show()\n \n #----------------------------------------------------------------------\n def changeValue(self, val):\n \"\"\"\"\"\"\n self.c.updateBW.emit(val)\n self.bwWidget.repaint()\n\n\nif __name__ == '__main__':\n app = QApplication(sys.argv)\n win = Window()\n sys.exit(app.exec_())","sub_path":"customWidget/customWidget.py","file_name":"customWidget.py","file_ext":"py","file_size_in_byte":4064,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"39539781","text":"import numpy\nfrom scipy.special import gammaln\n\ndef _gammaln(x):\n \"\"\"Vectorized calculation of ln(abs(gamma(array))) across a Numpy array.\n\n Numpy does not have a native implementation of gammaln.\n U{Scipy does },\n but that would introduce a dependency.\n \"\"\"\n \n array = numpy.asarray(x)\n gammaln_cof = [76.18009173, -86.50532033, 24.01409822, -1.231739516e0, 0.120858003e-2, -0.536382e-5]\n gammaln_stp = 2.50662827465\n x = numpy.array(array - 1.0)\n tmp = x + 5.5\n tmp = ((x + 0.5)*numpy.log(tmp)) - tmp\n ser = numpy.ones(array.shape[0], dtype=numpy.dtype(float))\n for cof in gammaln_cof:\n x += 1.0\n ser += cof/x\n return (tmp + numpy.log(gammaln_stp*ser))\n\ndef logfactorial(n):\n \n return gammaln( n + 1)\n","sub_path":"threeML/plugins/gammaln.py","file_name":"gammaln.py","file_ext":"py","file_size_in_byte":854,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"226739881","text":"\"\"\"\nExtract Edges\n~~~~~~~~~~~~~~~~~\n\nExtracts edges from a surface.\n\"\"\"\n\n# sphinx_gallery_thumbnail_number = 2\nimport pyvista as pv\nfrom pyvista import examples\n\n###############################################################################\n# From vtk documentation, the edges are one of the following:\n#\n# 1. boundary (used by one polygon) or a line cell\n# 2. non-manifold (used by three or more polygons)\n# 3. feature edges (edges used by two triangles and whose dihedral angle > feature_angle)\n# 4. manifold edges (edges used by exactly two polygons).\n#\n# This filter will extract those edges given a feature angle and return a datset\n# with lines that represent the edges of the original mesh.\n# To demonstrate, we will first extract the edges around Queen Nefertiti's eyes:\n\n# Load Queen Nefertiti mesh\nmesh = examples.download_nefertiti()\n\n# Extract the edges above a 12 degree feature angle\nedges = mesh.extract_edges(12)\n\n# Render the edge lines ontop of the original mesh\np = pv.Plotter()\np.add_mesh(mesh, color=True)\np.add_mesh(edges, color=\"red\", line_width=5)\n# Define a camera position that will zoom to her eye\np.camera_position = [(96.0, -197.0, 45.0), (7.0, -109.0, 22.0), (0, 0, 1)]\np.show()\n\n###############################################################################\n# We can do this anaylsis for any :class:`pyvista.PolyData` object. Let's try\n# the cow mesh example:\n\nmesh = examples.download_cow()\n\nedges = mesh.extract_edges(20)\n\np = pv.Plotter()\np.add_mesh(mesh, color=True)\np.add_mesh(edges, color=\"red\", line_width=5)\np.camera_position = [(9.5, 3.0, 5.5), (2.5, 1, 0), (0, 1, 0)]\np.show()\n","sub_path":"examples/01-filter/extract-edges.py","file_name":"extract-edges.py","file_ext":"py","file_size_in_byte":1620,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"411814415","text":"#Write a function writeNumbers() that takes a file name as parameter, write to the file each on a different line,\n# the numbers from 100 to 1000 (inclusive) incremented by 100.\n#so the file will contain 100 200 300 .... 1000 each on a separate line.\n\n\ndef writeNumbers(filename):\n with open(filename,'a') as harun:\n for i in range(100,10001,100):\n k=str(i)\n k+=\" \\n\"\n harun.writelines(k)\n k=\"\"\n\n\n\n\n\nwriteNumbers(\"harun.text\")\n\n\n","sub_path":"FinalExercises/files/writeNumbers.py","file_name":"writeNumbers.py","file_ext":"py","file_size_in_byte":482,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"373382044","text":"\nimport math\nimport operator\n\nimport cadquery as cq\n\nimport paramak\n\n\nclass BallReactor(paramak.Reactor):\n \"\"\"Creates geometry for a simple ball reactor including a plasma,\n cylindical center column shielding, square toroidal field coils.\n There is no inboard breeder blanket on this ball reactor like\n most spherical reactors.\n\n :param inner_bore_radial_thickness: the radial thickness of \n the inner bore (cm)\n :type inner_bore_radial_thickness: float\n :inboard_tf_leg_radial_thickness: the radial thickness of the\n inner leg of the toroidal field coils (cm)\n :type inboard_tf_leg_radial_thickness: float\n :center_column_shield_radial_thickness: the radial thickness\n of the center column shield (cm)\n :type center_column_shield_radial_thickness: float\n :divertor_radial_thickness: the radial thickness of the divertor\n (cm), this fills the gap between the center column shield and blanket\n :type divertor_radial_thickness: float\n :inner_plasma_gap_radial_thickness: the radial thickness of the\n inboard gap between the plasma and the center column shield (cm)\n :type inner_plasma_gap_radial_thickness: float\n :plasma_radial_thickness: the radial thickness of the plasma (cm),\n this is double the minor radius\n :type plasma_radial_thickness: float\n :outer_plasma_gap_radial_thickness: the radial thickness of the\n outboard gap between the plasma and the firstwall (cm)\n :type outer_plasma_gap_radial_thickness: float\n :firstwall_radial_thickness: the radial thickness of the first wall (cm)\n :type firstwall_radial_thickness: float\n :blanket_radial_thickness: the radial thickness of the blanket (cm)\n :type blanket_radial_thickness: float\n :blanket_rear_wall_radial_thickness: the radial thickness of the rear wall\n of the blanket (cm)\n :type blanket_rear_wall_radial_thickness: float\n :elongation: the elongation of the plasma\n :type elongation: float\n :triangularity: the triangularity of the plasma\n :type triangularity: float\n :number_of_tf_coils: the number of tf coils\n :type number_of_tf_coils: int\n :pf_coil_to_rear_blanket_radial_gap: the radial distance between the rear\n blanket and the closest poloidal field coil (optional)\n :type pf_coil_to_rear_blanket_radial_gap: float\n :pf_coil_radial_thicknesses: the radial thickness of each poloidal field\n coil (optional)\n :type pf_coil_radial_thicknesses: list of floats\n :pf_coil_vertical_thicknesses: the vertical thickness of each poloidal\n field coil (optional)\n :type pf_coil_vertical_thicknesses: list of floats\n :pf_coil_to_tf_coil_radial_gap: the radial distance between the rear of\n the poloidal field coil and the toroidal field coil (optional)\n :type pf_coil_to_tf_coil_radial_gap: float\n :tf_coil_radial_thickness: the radial thickness of the toroidal field\n coil (optional)\n :type tf_coil_radial_thickness: float\n :tf_coil_poloidal_thickness: the poloidal thickness of the toroidal field\n coil (optional)\n :type tf_coil_poloidal_thickness: float\n :rotation_angle: the angle of the sector that is desired\n :type rotation_angle: int\n\n :return: a Reactor object that has generic functionality\n :rtype: paramak shape object\n \"\"\"\n\n def __init__(\n self,\n inner_bore_radial_thickness,\n inboard_tf_leg_radial_thickness,\n center_column_shield_radial_thickness,\n divertor_radial_thickness,\n inner_plasma_gap_radial_thickness,\n plasma_radial_thickness,\n outer_plasma_gap_radial_thickness,\n firstwall_radial_thickness,\n blanket_radial_thickness,\n blanket_rear_wall_radial_thickness,\n elongation,\n triangularity,\n number_of_tf_coils,\n pf_coil_to_rear_blanket_radial_gap = None,\n pf_coil_radial_thicknesses = None,\n pf_coil_vertical_thicknesses = None,\n pf_coil_to_tf_coil_radial_gap = None,\n tf_coil_radial_thickness = None,\n tf_coil_poloidal_thickness = None,\n rotation_angle = 360,\n ):\n\n super().__init__([])\n\n self.inner_bore_radial_thickness = inner_bore_radial_thickness\n self.inboard_tf_leg_radial_thickness = inboard_tf_leg_radial_thickness\n self.center_column_shield_radial_thickness = center_column_shield_radial_thickness\n self.divertor_radial_thickness = divertor_radial_thickness\n self.inner_plasma_gap_radial_thickness = inner_plasma_gap_radial_thickness\n self.plasma_radial_thickness = plasma_radial_thickness\n self.outer_plasma_gap_radial_thickness = outer_plasma_gap_radial_thickness\n self.firstwall_radial_thickness = firstwall_radial_thickness\n self.blanket_radial_thickness = blanket_radial_thickness\n self.blanket_rear_wall_radial_thickness = blanket_rear_wall_radial_thickness\n self.pf_coil_to_rear_blanket_radial_gap = pf_coil_to_rear_blanket_radial_gap\n self.pf_coil_radial_thicknesses = pf_coil_radial_thicknesses\n self.pf_coil_vertical_thicknesses = pf_coil_vertical_thicknesses\n self.pf_coil_to_tf_coil_radial_gap = pf_coil_to_tf_coil_radial_gap\n self.tf_coil_radial_thickness = tf_coil_radial_thickness\n self.tf_coil_poloidal_thickness = tf_coil_poloidal_thickness\n\n # sets major raduis and minor radius from equatorial_points to allow a radial build\n # this helps avoid the plasma overlapping the center column and such things\n inner_equatorial_point = inner_bore_radial_thickness + inboard_tf_leg_radial_thickness + center_column_shield_radial_thickness + inner_plasma_gap_radial_thickness\n outer_equatorial_point = inner_equatorial_point + plasma_radial_thickness\n self.major_radius = (inner_equatorial_point + plasma_radial_thickness + inner_equatorial_point) /2\n self.minor_radius = ((outer_equatorial_point + inner_equatorial_point) /2 )-inner_equatorial_point\n\n self.elongation = elongation\n self.triangularity = triangularity\n\n self.number_of_tf_coils = number_of_tf_coils\n self.rotation_angle = rotation_angle\n\n self.create_components()\n\n\n def create_components(self):\n\n shapes_or_components = []\n\n plasma = paramak.Plasma(major_radius=self.major_radius,\n minor_radius=self.minor_radius,\n elongation=self.elongation,\n triangularity=self.triangularity,\n rotation_angle=self.rotation_angle)\n plasma.create_solid()\n\n shapes_or_components.append(plasma)\n\n\n # this is the radial build sequence, where one componet stops and another starts\n inner_bore_start_radius = 0\n inner_bore_end_radius = inner_bore_start_radius + self.inner_bore_radial_thickness\n\n inboard_tf_coils_start_radius = inner_bore_end_radius\n inboard_tf_coils_end_radius = inboard_tf_coils_start_radius + self.inboard_tf_leg_radial_thickness\n\n center_column_shield_start_radius = inboard_tf_coils_end_radius\n center_column_shield_end_radius = center_column_shield_start_radius + self.center_column_shield_radial_thickness\n\n divertor_start_radius = center_column_shield_end_radius\n divertor_end_radius = center_column_shield_end_radius + self.divertor_radial_thickness\n\n firstwall_start_radius = center_column_shield_end_radius \\\n + self.inner_plasma_gap_radial_thickness \\\n + self.plasma_radial_thickness \\\n + self.outer_plasma_gap_radial_thickness \n firstwall_end_radius = firstwall_start_radius + self.firstwall_radial_thickness\n\n blanket_start_radius = firstwall_end_radius\n blanket_end_radius = blanket_start_radius + self.blanket_radial_thickness\n\n blanket_read_wall_start_radius = blanket_end_radius \n blanket_read_wall_end_radius = blanket_read_wall_start_radius + self.blanket_rear_wall_radial_thickness \n\n #this is the vertical build sequence, componets build on each other in a similar manner to the radial build\n\n divertor_start_height = plasma.high_point[1]+ self.outer_plasma_gap_radial_thickness\n # make it the same hight as fw, blanket, rw\n divertor_end_height = divertor_start_height + self.firstwall_radial_thickness + self.blanket_radial_thickness + self.blanket_rear_wall_radial_thickness\n\n firstwall_start_height = divertor_start_height\n firstwall_end_height = firstwall_start_height + self.firstwall_radial_thickness\n\n blanket_start_height = firstwall_end_height\n blanket_end_height = blanket_start_height + self.blanket_radial_thickness\n\n blanket_rear_wall_start_height = blanket_end_height\n blanket_rear_wall_end_height = blanket_rear_wall_start_height + self.blanket_rear_wall_radial_thickness\n\n tf_coil_height = blanket_rear_wall_end_height\n center_column_shield_height = blanket_rear_wall_end_height * 2\n\n if self.pf_coil_vertical_thicknesses!=None and self.pf_coil_radial_thicknesses !=None and self.pf_coil_to_rear_blanket_radial_gap !=None:\n number_of_pf_coils = len(self.pf_coil_vertical_thicknesses)\n\n y_position_step = (2*(blanket_rear_wall_end_height + self.pf_coil_to_rear_blanket_radial_gap))/(number_of_pf_coils+1)\n\n pf_coils_y_values = []\n pf_coils_x_values = []\n # adds in coils with equal spacing strategy, should be updated to allow user positions\n for i in range(number_of_pf_coils):\n y_value =blanket_rear_wall_end_height + self.pf_coil_to_rear_blanket_radial_gap - y_position_step*(i+1)\n x_value = blanket_read_wall_end_radius + self.pf_coil_to_rear_blanket_radial_gap + \\\n 0.5*self.pf_coil_radial_thicknesses[i]\n pf_coils_y_values.append(y_value)\n pf_coils_x_values.append(x_value)\n\n pf_coil_start_radius = blanket_read_wall_end_radius + self.pf_coil_to_rear_blanket_radial_gap\n pf_coil_end_radius = pf_coil_start_radius + max(self.pf_coil_radial_thicknesses)\n \n if self.pf_coil_to_tf_coil_radial_gap !=None and self.tf_coil_radial_thickness !=None:\n tf_coil_start_radius = pf_coil_end_radius + self.pf_coil_to_rear_blanket_radial_gap \n tf_coil_end_radius = tf_coil_start_radius + self.tf_coil_radial_thickness\n\n\n if self.rotation_angle < 360:\n max_high = 3 * center_column_shield_height\n max_width = 3 * blanket_read_wall_end_radius\n cutting_slice = paramak.RotateStraightShape(points=[\n (0,max_high),\n (max_width, max_high),\n (max_width, -max_high),\n (0, -max_high),\n ],\n rotation_angle=360-self.rotation_angle,\n azimuth_placement_angle=360-self.rotation_angle\n )\n else:\n cutting_slice=None\n\n # shapes_or_components.append(inboard_tf_coils)\n inboard_tf_coils = paramak.CenterColumnShieldCylinder(\n height=tf_coil_height * 2,\n inner_radius=inboard_tf_coils_start_radius,\n outer_radius=inboard_tf_coils_end_radius,\n rotation_angle=self.rotation_angle,\n # color=centre_column_color,\n stp_filename=\"inboard_tf_coils.stp\",\n name=\"inboard_tf_coils\",\n material_tag=\"inboard_tf_coils_mat\",\n )\n shapes_or_components.append(inboard_tf_coils)\n\n center_column_shield = paramak.CenterColumnShieldCylinder(\n height=center_column_shield_height,\n inner_radius=center_column_shield_start_radius,\n outer_radius=center_column_shield_end_radius,\n rotation_angle=self.rotation_angle,\n # color=centre_column_color,\n stp_filename=\"center_column_shield.stp\",\n name=\"center_column_shield\",\n material_tag=\"center_column_shield_mat\",\n )\n shapes_or_components.append(center_column_shield)\n\n space_for_divertor = plasma.high_point[0] - center_column_shield_end_radius\n\n #add blanket if the divertor doesn't take up all the space\n if space_for_divertor > self.divertor_radial_thickness:\n print('making extra blanket as there is space between the divertor and existing blanket')\n extra_blanket_upper = paramak.RotateStraightShape(points=[\n (divertor_end_radius, blanket_start_height),\n (divertor_end_radius, blanket_end_height),\n (plasma.high_point[0], blanket_end_height),\n (plasma.high_point[0], blanket_start_height),\n ],\n rotation_angle=self.rotation_angle,\n stp_filename='extra_blanket_upper.stp',\n name='extra_blanket_upper',\n material_tag='blanket_mat')\n shapes_or_components.append(extra_blanket_upper)\n\n extra_firstwall_upper = paramak.RotateStraightShape(points=[\n (divertor_end_radius, firstwall_start_height),\n (divertor_end_radius, firstwall_end_height),\n (plasma.high_point[0], firstwall_end_height),\n (plasma.high_point[0], firstwall_start_height),\n ],\n rotation_angle=self.rotation_angle,\n stp_filename='extra_firstwall_upper.stp',\n name='extra_firstwall_upper',\n material_tag='firstwall_mat')\n shapes_or_components.append(extra_firstwall_upper)\n\n extra_blanket_rear_wall_upper = paramak.RotateStraightShape(points=[\n (divertor_end_radius, blanket_rear_wall_start_height),\n (divertor_end_radius, blanket_rear_wall_end_height),\n (plasma.high_point[0], blanket_rear_wall_end_height),\n (plasma.high_point[0], blanket_rear_wall_start_height),\n ],\n rotation_angle=self.rotation_angle,\n stp_filename='extra_blanket_rear_wall_upper.stp',\n name='extra_blanket_rear_wall_upper',\n material_tag='blanket_rear_wall_mat')\n shapes_or_components.append(extra_blanket_rear_wall_upper)\n\n extra_blanket_lower = paramak.RotateStraightShape(points=[\n (divertor_end_radius, -blanket_start_height),\n (divertor_end_radius, -blanket_end_height),\n (plasma.high_point[0], -blanket_end_height),\n (plasma.high_point[0], -blanket_start_height),\n ],\n rotation_angle=self.rotation_angle,\n stp_filename='extra_blanket_lower.stp',\n name='extra_blanket_lower',\n material_tag='blanket_mat')\n shapes_or_components.append(extra_blanket_lower)\n\n extra_firstwall_lower = paramak.RotateStraightShape(points=[\n (divertor_end_radius, -firstwall_start_height),\n (divertor_end_radius, -firstwall_end_height),\n (plasma.high_point[0], -firstwall_end_height),\n (plasma.high_point[0], -firstwall_start_height),\n ],\n rotation_angle=self.rotation_angle,\n stp_filename='extra_firstwall_lower.stp',\n name='extra_firstwall_lower',\n material_tag='firstwall_mat')\n shapes_or_components.append(extra_firstwall_lower)\n\n extra_blanket_rear_wall_lower = paramak.RotateStraightShape(points=[\n (divertor_end_radius, -blanket_rear_wall_start_height),\n (divertor_end_radius, -blanket_rear_wall_end_height),\n (plasma.high_point[0], -blanket_rear_wall_end_height),\n (plasma.high_point[0], -blanket_rear_wall_start_height),\n ],\n rotation_angle=self.rotation_angle,\n stp_filename='extra_blanket_rear_wall_lower.stp',\n name='extra_blanket_rear_wall_lower',\n material_tag='blanket_rear_wall_mat')\n shapes_or_components.append(extra_blanket_rear_wall_lower)\n\n divertor_upper_part = paramak.RotateStraightShape(points=[\n (divertor_start_radius, divertor_end_height),\n (divertor_start_radius, divertor_start_height),\n (divertor_end_radius, divertor_start_height),\n (divertor_end_radius, divertor_end_height),\n ],\n stp_filename='divertor_upper.stp',\n name='divertor_upper',\n rotation_angle=self.rotation_angle,\n material_tag='divertor_mat'\n )\n shapes_or_components.append(divertor_upper_part)\n\n # negative signs used as this is in the negative side of the Z axis \n divertor_lower_part = paramak.RotateStraightShape(points=[\n (divertor_start_radius, -divertor_end_height),\n (divertor_start_radius, -divertor_start_height),\n (divertor_end_radius, -divertor_start_height),\n (divertor_end_radius, -divertor_end_height),\n ],\n stp_filename='divertor_lower.stp',\n name='divertor_lower',\n rotation_angle=self.rotation_angle,\n material_tag='divertor_mat'\n )\n shapes_or_components.append(divertor_lower_part)\n\n # curve divertor arround if it is larger than the horitonal space provided\n elif self.divertor_radial_thickness > space_for_divertor:\n\n length_of_curved_section = self.divertor_radial_thickness - space_for_divertor\n\n center_point, radius = paramak.utils.find_center_point_of_circle(point1=(firstwall_start_radius, 0),\n point2=(plasma.high_point[0], firstwall_start_height),\n point3=(plasma.low_point[0], -firstwall_start_height))\n\n circumference = 2.*math.pi*radius\n\n rotation_angle = (length_of_curved_section * 2 * math.pi) / circumference\n\n new_point_x1, new_point_y1 = paramak.utils.rotate(center_point, (plasma.high_point[0], firstwall_start_height), -rotation_angle/2.)\n new_point_x2, new_point_y2 = paramak.utils.rotate(center_point, (plasma.high_point[0], firstwall_start_height), -rotation_angle)\n new_point_x3, new_point_y3 = paramak.utils.rotate(center_point, (plasma.high_point[0], blanket_rear_wall_end_height), -rotation_angle)\n new_point_x4, new_point_y4 = paramak.utils.rotate(center_point, (plasma.high_point[0], blanket_rear_wall_end_height), -rotation_angle/2.)\n\n divertor_upper_part = paramak.RotateMixedShape(points=[\n (divertor_start_radius, divertor_end_height, 'straight'),\n (divertor_start_radius, divertor_start_height, 'straight'),\n (divertor_start_radius+space_for_divertor, divertor_start_height, 'circle'),\n (new_point_x1, new_point_y1, 'circle'),\n (new_point_x2, new_point_y2, 'straight'),\n (new_point_x3, new_point_y3, 'circle'),\n (new_point_x4, new_point_y4, 'circle'),\n (divertor_start_radius+space_for_divertor, divertor_end_height, 'straight'),\n ],\n stp_filename='divertor_upper.stp',\n name='divertor_upper',\n rotation_angle=self.rotation_angle,\n material_tag='divertor_mat'\n )\n shapes_or_components.append(divertor_upper_part)\n\n # negative signs used as this is in the negative side of the Z axis \n divertor_lower_part = paramak.RotateMixedShape(points=[\n (divertor_start_radius, -divertor_end_height, 'straight'),\n (divertor_start_radius, -divertor_start_height, 'straight'),\n (divertor_start_radius+space_for_divertor, -divertor_start_height, 'circle'),\n (new_point_x1, -new_point_y1, 'circle'),\n (new_point_x2, -new_point_y2, 'straight'),\n (new_point_x3, -new_point_y3, 'circle'),\n (new_point_x4, -new_point_y4, 'circle'),\n (divertor_start_radius+space_for_divertor, -divertor_end_height, 'straight'),\n ],\n stp_filename='divertor_lower.stp',\n name='divertor_lower',\n rotation_angle=self.rotation_angle,\n material_tag='divertor_mat'\n )\n shapes_or_components.append(divertor_lower_part)\n\n elif self.divertor_radial_thickness == space_for_divertor:\n\n divertor_upper_part = paramak.RotateMixedShape(points=[\n (divertor_start_radius, divertor_end_height, 'straight'),\n (divertor_start_radius, divertor_start_height, 'straight'),\n (divertor_start_radius+space_for_divertor, divertor_start_height, 'straight'),\n (divertor_start_radius+space_for_divertor, divertor_end_height, 'straight'),\n ],\n stp_filename='divertor_upper.stp',\n name='divertor_upper',\n rotation_angle=self.rotation_angle,\n material_tag='divertor_mat'\n )\n shapes_or_components.append(divertor_upper_part)\n\n # negative signs used as this is in the negative side of the Z axis \n divertor_lower_part = paramak.RotateMixedShape(points=[\n (divertor_start_radius, -divertor_end_height, 'straight'),\n (divertor_start_radius, -divertor_start_height, 'straight'),\n (divertor_start_radius+space_for_divertor, -divertor_start_height, 'straight'),\n (divertor_start_radius+space_for_divertor, -divertor_end_height, 'straight'),\n ],\n stp_filename='divertor_lower.stp',\n name='divertor_lower',\n rotation_angle=self.rotation_angle,\n material_tag='divertor_mat'\n )\n shapes_or_components.append(divertor_lower_part)\n\n firstwall = paramak.BlanketConstantThicknessArcV(\n inner_mid_point=(firstwall_start_radius, 0),\n inner_upper_point=(plasma.high_point[0], firstwall_start_height),\n inner_lower_point=(plasma.low_point[0], -firstwall_start_height),\n thickness=self.firstwall_radial_thickness,\n rotation_angle=self.rotation_angle,\n stp_filename='firstwall.stp',\n name='firstwall',\n material_tag='firstwall_mat',\n cut=[divertor_lower_part, divertor_upper_part]\n )\n shapes_or_components.append(firstwall)\n\n blanket = paramak.BlanketConstantThicknessArcV(\n inner_mid_point=(blanket_start_radius, 0),\n inner_upper_point=(plasma.high_point[0], blanket_start_height),\n inner_lower_point=(plasma.low_point[0], -blanket_start_height),\n thickness=self.blanket_radial_thickness,\n rotation_angle=self.rotation_angle,\n stp_filename='blanket.stp',\n name='blanket',\n material_tag='blanket_mat',\n cut=[divertor_lower_part, divertor_upper_part]\n )\n shapes_or_components.append(blanket)\n\n blanket_rear_casing = paramak.BlanketConstantThicknessArcV(\n inner_mid_point=(blanket_read_wall_start_radius, 0),\n inner_upper_point=(plasma.high_point[0], blanket_rear_wall_start_height),\n inner_lower_point=(plasma.low_point[0], -blanket_rear_wall_start_height),\n thickness=self.blanket_rear_wall_radial_thickness,\n rotation_angle=self.rotation_angle,\n stp_filename='blanket_rear_wall.stp',\n name='blanket_rear_wall',\n material_tag='blanket_rear_wall_mat',\n cut=[divertor_lower_part, divertor_upper_part]\n )\n shapes_or_components.append(blanket_rear_casing)\n\n if self.pf_coil_vertical_thicknesses!=None and self.pf_coil_radial_thicknesses !=None and self.pf_coil_to_rear_blanket_radial_gap !=None:\n \n for i, (rt, vt, y_value, x_value) in enumerate(zip(self.pf_coil_radial_thicknesses,\n self.pf_coil_vertical_thicknesses,\n pf_coils_y_values,\n pf_coils_x_values,\n )\n ):\n\n\n pf_coil = paramak.PoloidalFieldCoil(width=rt, \n height=vt,\n center_point=(x_value,y_value),\n rotation_angle=self.rotation_angle,\n stp_filename='pf_coil_'+str(i)+'.stp',\n name='pf_coil',\n material_tag='pf_coil_mat')\n shapes_or_components.append(pf_coil)\n \n if self.pf_coil_to_tf_coil_radial_gap !=None and self.tf_coil_radial_thickness !=None:\n tf_coil = paramak.ToroidalFieldCoilRectangle(inner_upper_point=(inboard_tf_coils_start_radius, tf_coil_height),\n inner_lower_point=(inboard_tf_coils_start_radius, -tf_coil_height),\n inner_mid_point=(tf_coil_start_radius, 0),\n thickness= self.tf_coil_radial_thickness,\n number_of_coils=self.number_of_tf_coils,\n distance=self.tf_coil_poloidal_thickness,\n cut=cutting_slice)\n\n shapes_or_components.append(tf_coil)\n \n self.shapes_and_components = shapes_or_components","sub_path":"paramak/parametric_reactors/ball_reactor.py","file_name":"ball_reactor.py","file_ext":"py","file_size_in_byte":26301,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"429600621","text":"# Databricks notebook source\nfrom tweepy import OAuthHandler\nfrom tweepy import API\nfrom tweepy import Cursor\nfrom textblob import TextBlob\nfrom wordcloud import WordCloud\nimport matplotlib.pyplot as plt\nimport tweepy as tw\nimport pandas as pd\nimport re\nimport numpy as np\nimport csv\n\nconsumer_key = '' #twitter app’s API Key\nconsumer_secret = '' #twitter app’s API secret Key\naccess_token = '' #twitter app’s Access token\naccess_token_secret = '' #twitter app’s access token secret\n\nauth = OAuthHandler(consumer_key, consumer_secret)\nauth.set_access_token(access_token, access_token_secret)\nauth_api = API(auth)\n\nIBMacess_tweets = auth_api.user_timeline(screen_name = \"IBMAccess\", q=\"#a11y\",count = 1000, include_rts = False, tweet_mode = \"extended\", lang=\"en\", since=\"2018-11-16\")\nfinal_tweets = [each_tweet.full_text for each_tweet in IBMacess_tweets]\n\ndef cleanTxt(text):\n text = re.sub('@[A-Za-z0–9]+', '', text) # Removing @mentions\n text = re.sub('https?:\\/\\/\\S+', '', text) # Removing hyperlink\n\n return text\n\n\ndf = pd.DataFrame([tweet.full_text for tweet in IBMacess_tweets], columns=['Tweets'])\ndf['Tweets']= df['Tweets'].apply(cleanTxt)\n\n\ndef getSubjectivity(text):\n return TextBlob(text).sentiment.subjectivity\n\n\n# Create a function to get the polarity\ndef getPolarity(text):\n return TextBlob(text).sentiment.polarity\n\n\n# Create two new columns 'Subjectivity' & 'Polarity'\ndf['Subjectivity'] = df['Tweets'].apply(getSubjectivity)\ndf['Polarity'] = df['Tweets'].apply(getPolarity)\n\n\n#Creating a worldcloud to check what words appear the most\nallWords = ' '.join([twts for twts in df['Tweets']])\nwordCloud = WordCloud(width=500, height=300, random_state=21, max_font_size=110).generate(allWords)\n\n\nplt.imshow(wordCloud, interpolation=\"bilinear\")\nplt.axis('off')\n\n#Analysis of sentiment score\ndef getAnalysis(score):\n if score < 0:\n return 'Negative'\n elif score == 0:\n return 'Neutral'\n else:\n return 'Positive'\n\n\ndf['Analysis'] = df['Polarity'].apply(getAnalysis)\n\n\n# Printing positive tweets\nprint('Printing positive tweets:\\n')\nj=1\nsortedDF = df.sort_values(by=['Polarity']) #Sort the tweets\nfor i in range(0, sortedDF.shape[0] ):\n if( sortedDF['Analysis'][i] == 'Positive'):\n print(str(j) + ') '+ sortedDF['Tweets'][i])\n print()\n j= j+1\n\n\n# Printing negative tweets\nprint('Printing negative tweets:\\n')\nj=1\nsortedDF = df.sort_values(by=['Polarity'],ascending=False)\nfor i in range(0, sortedDF.shape[0] ):\n if( sortedDF['Analysis'][i] == 'Negative'):\n print(str(j) + ') '+sortedDF['Tweets'][i])\n print()\n j=j+1\n\n#plot polarity and subjectivity\nplt.figure(figsize=(8, 6))\nfor i in range(0, df.shape[0]):\n plt.scatter(df[\"Polarity\"][i], df[\"Subjectivity\"][i], color='Blue')\n\nplt.title('Sentiment Analysis')\nplt.xlabel('Polarity')\nplt.ylabel('Subjectivity')\nplt.show()","sub_path":"tweet_analysis.py","file_name":"tweet_analysis.py","file_ext":"py","file_size_in_byte":2820,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"469978834","text":"import cv2\nimport numpy as np\nimport common\nimport global_values\n\nclass Box:\n def __init__(self, robot):\n self.robot = robot\n self.color = None\n self.points = None\n self.center_x = 0\n self.center_y = 0\n self.image_half_width = 500 ##### TO EDIT: get the width from a global variable #####\n self.center_accuracy = 100 # is used when checking the box is in the center or not\n self.variance = global_values.square_variance# Variance for right-square\n self.thresh_frame = None\n def is_box_totally_visible(self):\n self.points = None\n if self.color is None:\n masked = common.apply_mask(self.robot.current_frame)\n else:\n masked = common.apply_mask(self.robot.current_frame,self.color)\n gray_img = cv2.cvtColor(masked,cv2.COLOR_BGR2GRAY)\n thresh = common.get_otsu_gaussian_threshold(gray_img)\n self.thresh_frame = cv2.cvtColor(thresh,cv2.COLOR_GRAY2BGR)\n contours = common.get_contours(thresh)\n return self.look_for_box(contours,self.variance)\n\n\n\n def look_for_box(self,contours,var):\n for c in contours:\n moments = cv2.moments(c)\n if moments[\"m00\"] > 10000: #make 1000 if it didnt work\n r = cv2.minAreaRect(c)\n r = ((r[0][0], r[0][1]), (r[1][0], r[1][1]), r[2])\n (width,height)=(r[1][0], r[1][1])\n box = cv2.boxPoints(r)\n\n box = np.int0(box)\n if (height > (1 - var) * width and height < (1 + var) * width):\n self.points = box\n #print box\n #self.center_x = int(box[:, 0].mean())\n self.center_x = int((min(box[:,0]) + max(box[:,0]))/2)\n self.center_y = int((min(box[:,1]) + max(box[:,1]))/2)\n\n return True\n return False\n\n def is_box_seen(self):\n ########### is box partially visible code goes here ###############\n\n\n\n pass\n\n\n\n\n##############3 debugging code ##############################\n def show(self): # For testing\n frame = self.thresh_frame\n\n if self.is_box_totally_visible():\n cv2.drawContours(frame, [self.points], -1, (0, 0, 255), 2)\n cv2.circle(frame, (self.center_x, self.center_y), 7, (0, 0, 255), 2)\n\n ls = self.left_shifting()\n rs = self.right_shifting()\n if ls > 0:\n cv2.putText(frame, \"LEFT SHIFT \" + str(ls), (self.image_half_width - 200, 100), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.8, (0, 255, 255))\n elif rs > 0:\n cv2.putText(frame, \"RIGHT SHIFT \" + str(rs), (self.image_half_width + 200, 100), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.8, (0, 255, 255))\n else:\n cv2.putText(frame, \"CENTERED\", (self.image_half_width, 100), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.8, (0, 255, 0))\n\n return frame\n\n def is_centered(self): # Check wheather the box is centered or not\n return abs(self.image_half_width - self.center_x) <= self.center_accuracy\n\n def left_shifting(self): # Distance to the left from the center\n shifting = (self.image_half_width - self.center_accuracy) - self.center_x\n return shifting if shifting > 0 else 0\n\n def right_shifting(self): # Distance to the right from the center\n shifting = self.center_x - (self.image_half_width + self.center_accuracy)\n return shifting if shifting > 0 else 0\n","sub_path":"SLIIT Robofest 2016/robofest_pi/v1/box_logic.py","file_name":"box_logic.py","file_ext":"py","file_size_in_byte":3498,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"322253976","text":"from django.conf.urls import url\nfrom . import views\n\nurlpatterns = [\n\t#/code/\n url(r'^$', views.codebeta, name='codebeta'),\n url(r'^ot/$', views.ot, name='ot'),\n #/code/projects\n url(r'^projects/$', views.projects, name='projects'),\n #/code/share\n url(r'^share/$', views.share, name='share'),\n #/code/projects/new\n url(r'^newproject/$', views.newproject, name='newproject'),\n #/code/projects/projectname\n\turl(r'^projects/(?P[0-9]+)/$', views.whichproject, name='whichproject'),\n\t#/code/projects/projectname/filename\n\turl(r'^projects/(?P[0-9]+)/(?P[a-zA-Z0-9]+)/$', views.file, name='code'),\n\t#/code/share/sharehash\n\turl(r'^share/(?P[0-9a-zA-Z]+)/$', views.share, name='share'),\n#test email thing\n\turl(r'^testemail/$', views.notifyUser2, name='notifyUser2'),\n\n# AJAX FUNCTIONS\n # PROJECT\n #ajax call /code/newProjectAjax/\n url(r'^newProjectAjax/$', views.newProjectAjax, name='newProjectAjax'),\n #ajax call /code/ajax_check_addmember_username/\n url(r'^ajax_check_addmember_username/$', views.ajax_check_addmember_username, name='ajax_check_addmember_username'),\n #ajax call /code/ajax_addNewTeamMember/\n url(r'^ajax_addNewTeamMember/$', views.ajax_addNewTeamMember, name='ajax_addNewTeamMember'),\n # FILE\n #ajax call /code/newFileAjax/\n url(r'^newFileAjax/$', views.newFileAjax, name='newFileAjax'),\n #ajax call /code/newFileAjax/\n url(r'^newDirAjax/$', views.newDirAjax, name='newDirAjax'),\n #ajax call /code/newFileAjax/\n url(r'^saveCodeContent/$', views.saveCodeContent, name='saveCodeContent'),\n url(r'^saveCodeContentFromNode/$', views.saveCodeContentFromNode, name='saveCodeContentFromNode'),\n #ajax call /code/loadInitialFile/\n url(r'^loadInitialFile/$', views.loadInitialFile, name='loadInitialFile'),\n #ajax call /code/loadSharedFile/\n url(r'^loadSharedFile/$', views.loadSharedFile, name='loadSharedFile'),\n #ajax call /code/deleteFileAjax/\n url(r'^deleteFileAjax/$', views.deleteFileAjax, name='deleteFileAjax'),\n #ajax call /code/deleteFideleteProjectleAjax/\n url(r'^deleteProject/$', views.deleteProject, name='deleteProject'),\n\n]\n\n\n\n'''\nsamples\n'''\n # url(r'^createStory/$', views.createStory, name='createStory'),\n # url(r'^editStory/$', views.editStory, name='editStory'),\n # url(r'^deleteStory/$', views.deleteStory, name='deleteStory'),\n # # /projectname/\n\t# url(r'^(?P[0-9]+)/$', views.project, name='project'),\n\t# # url(r'^(?P[0-9]+)/iteration/$', views.iteration, name='iteration'),\n\t# # url(r'^(?P[0-9]+)/iteration/new/$', views.newIteration, name='newIteration'),\n\t# # url(r'^(?P[0-9]+)/iteration/(?P[0-9]+)/$', views.iteration, name='iteration'),\n\t# url(r'^(?P[a-zA-Z]+)/iteration/new/$', views.newIteration, name='newIteration'),\n\t# url(r'^(?P[a-zA-Z]+)/iteration/(?P[0-9]+)/$', views.iteration, name='iteration'),\n\n","sub_path":"codeapp/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":3004,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"173749810","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Aug 1 15:31:47 2021\n\n@author: Daniel Souza - PC\n\"\"\"\nimport numpy as np\nfrom matplotlib import pyplot as plt\nimport seaborn as sns\nimport pandas as pd\nfrom pandas.api.types import is_numeric_dtype\n\ndef plot_histograms(df, title, n_columns = 4):\n fig_columns = n_columns\n fig_rows = int(np.ceil(len(df.columns) / fig_columns))\n \n fig, axes = plt.subplots(fig_rows, fig_columns, figsize=(18, 4 * fig_rows))\n fig.suptitle(title, size='xx-large')\n\n for i, column in enumerate(df.columns):\n ax = axes[i//fig_columns][i%fig_columns]\n \n sns.histplot(data = df, x = column, ax=ax, kde = True)\n \n if(is_numeric_dtype(df[column])):\n ax.axvline(x=np.mean(df[column]), linestyle='dashed', label='Mean')\n ax.legend()\n \n\n ax.set_title(column.title().replace(\"_\", \" \"))\n \n\n plt.tight_layout()\n \n return fig\n\ndef plot_high_correlation_variables(df, correlation, correl_threshold, title, n_columns = 4):\n fig_columns = 4\n\n high_corr_pair_list = []\n \n # Add high correlation variables pairs to list\n for i, line in enumerate(correlation.columns):\n for column in correlation.columns[i+1:]:\n cor_abs_val = np.abs(correlation.loc[line, column])\n \n if cor_abs_val >= correl_threshold:\n high_corr_pair_list.append([line, column, cor_abs_val])\n \n # Sort list according to absolute correlation\n high_corr_pair_list.sort(reverse = True, key = lambda x: x[2])\n # Set amount of rows \n fig_rows = int(np.ceil(len(high_corr_pair_list) / fig_columns))\n \n # Plot charts\n fig, axes = plt.subplots(fig_rows, fig_columns, figsize=(18, 4*fig_rows))\n fig.suptitle(title, size='xx-large')\n \n for i, pair in enumerate(high_corr_pair_list):\n if fig_rows > 1:\n ax = axes[i//fig_columns][i%fig_columns]\n else:\n ax = axes[i]\n \n cor_i = correlation.loc[pair[0], pair[1]]\n \n sns.scatterplot(data = df, x = pair[1], y = pair[0], ax = ax, alpha = 0.8)\n ax.set_title(str(pair[0]).title().replace(\"_\", \" \") + \" x \" + str(pair[1]).title().replace(\"_\", \" \") \\\n + \", corr = {:.2f}\".format(cor_i) )\n \n plt.tight_layout()\n plt.subplots_adjust(top=0.95)\n return fig","sub_path":"exploratory_analysis.py","file_name":"exploratory_analysis.py","file_ext":"py","file_size_in_byte":2383,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"329985263","text":"__author__ = 'Guillaume'\n# from https://www.interviewbit.com/courses/programming/topics/math/problems/factors/\n\nimport math\n\n\nclass Solution:\n # @param A : integer\n # @return a list of integers\n def allFactors(self, A):\n res1 = []\n res2 = []\n for i in range(1, int(math.ceil(math.sqrt(A)) + 1)):\n if A % i == 0:\n res1.append(i)\n if i != math.sqrt(A):\n res2.append(int(A/i))\n return res1 + res2[::-1]\n\n\nsl = Solution()\nprint(sl.allFactors(12))\n","sub_path":"Python/IB_all_factors.py","file_name":"IB_all_factors.py","file_ext":"py","file_size_in_byte":540,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"402069404","text":"# {@tested@}\nfrom sys import version_info\n\nis_string = None; is_string\ndef _define_is_string_by_version(v):\n global is_string\n if v == 2:\n is_string = eval('''lambda o: isinstance(o, basestring)''')\n elif 3 <= v:\n is_string = lambda o: isinstance(o, (bytes, str))\n else:\n raise AssertionError(v)\n_define_is_string_by_version(version_info[0])\n\ndef is_regex(o):\n if not atom(o):\n return False\n if is_string(o):\n return True\n try:\n o.match\n except AttributeError:\n return False\n return True\n\ndef atom(o):\n return is_string(o) or not _is_iterable(o)\n\ndef is_iterable(o):\n return not is_string(o) and _is_iterable(o)\n\ndef _is_iterable(o):\n try:\n o.__iter__\n except AttributeError:\n return False\n return True\n","sub_path":"gnuinst/lib/atom.py","file_name":"atom.py","file_ext":"py","file_size_in_byte":808,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"84068326","text":"from PyQt5.QtCore import *\r\nfrom InStkForm_handler import *\r\nfrom GlobalAPI_handler import *\r\nfrom Chart_handler import *\r\nfrom RcvSckt_handler import *\r\nfrom SndSckt_handler import *\r\nfrom TFQttn_handler import *\r\nfrom TestQttn_Sender import *\r\nfrom PyQt5 import uic\r\nfrom matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas\r\n\r\nui_path = os.path.dirname(os.path.abspath(__file__))\r\nMainFormClass = uic.loadUiType(os.path.join(ui_path, \"MainForm.ui\"))[0]\r\n\r\n# 메인 폼 핸들러\r\nclass MainForm_handler(QMainWindow, MainFormClass):\r\n\r\n def __init__(self, isUnite=\"None\"):\r\n super().__init__()\r\n\r\n # 폼 설정\r\n self.setupUi(self)\r\n\r\n # 객체변수 설정\r\n self.DBH = None # DB 핸들러\r\n self.APIH = None # API 핸들러\r\n self.CrtH = None # 차트 핸들러\r\n self.QttnSctkT = None # 시세수신소켓쓰레드\r\n self.TfRcvSctkT = None # 딥러닝수신소켓쓰레드\r\n self.TfSndSctkT = None # 딥러닝송신소켓\r\n self.ProcStkList = [] # 처리대상 종목리스트\r\n self.TestQttnSnd = None # 테스트 시세 전송 쓰레드\r\n\r\n # 수신소켓 동작여부\r\n self.NowRcvIdxQttn = False\r\n self.NowRcvGlobalQttn = False\r\n self.NowTensorFlow = False\r\n self.NowRcvGlobalSavedQttn = False\r\n\r\n # 버튼이벤트 핸들러 설정\r\n self.btnInStkCd.clicked.connect (self.ClickInStkCd ) # 처리종목 입력\r\n self.btnDelStkCd.clicked.connect (self.ClickDelStkCd ) # 처리종목 삭제\r\n self.btnInitMnQttn.clicked.connect (self.ClickInitMnQttn ) # 처리종목 분봉시세 초기화\r\n self.btnRcvIdxQttn.clicked.connect (self.ClickRcvIdxQttn ) # 지수 실시간 시세 받기/종료\r\n self.btnRcvGlobalQttn.clicked.connect (self.ClickRcvGlobalQttn ) # 글로벌 실시간 시세 받기/종료\r\n self.btnTensorFlow.clicked.connect (self.ClickTensorFlow ) # 딥러닝 송수신 동작/중지\r\n self.btnRcvGlobalSavedQttn.clicked.connect(self.ClickRcvGlobalSavedQttn) # 저장된 글로벌 시세 받기/종료\r\n\r\n self.btnMnQttnOrd.clicked.connect (self.ClickMnQttnOrd ) # 빈분봉처리\r\n self.btnSetFstQttn.clicked.connect (self.ClickSetFstQttn ) # 첫시세 설정\r\n self.btnMnQttnOrd.setVisible(False)\r\n self.btnSetFstQttn.setVisible(False)\r\n\r\n # DB 핸들러 초기화\r\n try:\r\n self.DBH = DB_handler() # DB 핸들러\r\n except Exception as e:\r\n print(\"DB 핸들러 오류:\",e)\r\n\r\n # API 핸들러 초기화\r\n try:\r\n self.APIH = GlobalAPI_handler()\r\n self.APIH.initAPI(False, self) # 전송모드일 경우 True, 메인폼 수신 False\r\n print(\"GLOBAL end \")\r\n except Exception as e:\r\n print(\"API초기화오류:\",e)\r\n\r\n # 차트 초기화\r\n self.fig = plt.Figure()\r\n self.canvas = FigureCanvas(self.fig)\r\n self.vbChart.addWidget(self.canvas)\r\n self.CrtH = Chart_handler()\r\n self.CrtH.SetHandler(self.fig, self.canvas)\r\n\r\n # 처리대상 종목 초기화\r\n self.ShowProcStkList()\r\n\r\n # 딥러닝 시세 핸들러 초기화\r\n self.TFH = TFQttn_handler(self)\r\n\r\n # 통합실행의 경우 수신준비\r\n if (isUnite == \"TRUE\"):\r\n #3초 딜레이후 실행\r\n time.sleep(3)\r\n # 지수시세 실시간\r\n self.ClickRcvIdxQttn()\r\n # 텐서플로 실시간\r\n self.ClickTensorFlow()\r\n\r\n return None\r\n\r\n def __del__(self):\r\n self.APIH.CloseAPI()\r\n return None\r\n\r\n # 처리대상종목 입력\r\n def ClickInStkCd(self):\r\n if (self.NowRcvGlobalQttn):\r\n ctypes.windll.user32.MessageBoxW(0, \"글로번 시세 수신중으로 추가 불가\", \"알림\", 0)\r\n return None\r\n inStkForm = InStkForm_handler()\r\n inStkForm.exec_()\r\n self.ShowProcStkList()\r\n return None\r\n\r\n # 처리대상종목 삭제\r\n def ClickDelStkCd(self):\r\n if (self.NowRcvGlobalQttn):\r\n ctypes.windll.user32.MessageBoxW(0, \"글로번 시세 수신중으로 추가 불가\", \"알림\", 0)\r\n return None\r\n sItem = self.tblProcStkList.selectedItems()\r\n sMktTpCd = sItem[CodeDef.PROC_STK_COL_MKT_TP_CD].text() # 시장구분코드\r\n sStkCd = sItem[CodeDef.PROC_STK_COL_STK_CD].text() # 종목코드\r\n self.DBH.deleteProcStk(sMktTpCd, sStkCd)\r\n self.ShowProcStkList()\r\n return None\r\n\r\n # 처리대상 종목 표시\r\n def ShowProcStkList(self):\r\n StkList = self.DBH.queryProcStkList()\r\n RowCnt = len(StkList.index)\r\n ColCnt = len(StkList.columns)\r\n self.tblProcStkList.setRowCount(RowCnt)\r\n self.tblProcStkList.setColumnCount(ColCnt)\r\n self.tblProcStkList.setHorizontalHeaderLabels(list(StkList))\r\n # 처리대상 종목리스트\r\n self.ProcStkList.clear()\r\n self.ProcStkList = list(StkList[\"STK_CD\"])\r\n\r\n for iRow in range(RowCnt):\r\n for iCol in range(ColCnt):\r\n item = QTableWidgetItem(StkList.iat[iRow,iCol])\r\n item.setTextAlignment(Qt.AlignVCenter | Qt.AlignCenter)\r\n self.tblProcStkList.setItem(iRow, iCol, item)\r\n\r\n self.tblProcStkList.resizeColumnsToContents()\r\n self.tblProcStkList.resizeRowsToContents()\r\n return None\r\n\r\n # 처리대상 종목 리스트 가져오기\r\n def GetProcStkList(self):\r\n return self.ProcStkList[:]\r\n\r\n # 처리종목 분봉시세 초기화\r\n def ClickInitMnQttn(self):\r\n Chk = ctypes.windll.user32.MessageBoxW(0, \"초기화 시작합니다.\", \"알림\", 1)\r\n if(Chk == 2):\r\n return None\r\n # 초기화 대상 종목 리스트 조회\r\n StkList = self.DBH.queryProcStkList()\r\n RowCnt = len(StkList.index)\r\n for iRow in range(RowCnt):\r\n\r\n # 티레이더 글로벌 초기화 확인\r\n if(StkList.iat[iRow, CodeDef.PROC_STK_COL_RCV_TP] != \"GLOBAL\"):\r\n continue\r\n\r\n MktTpCd = StkList.iat[iRow, CodeDef.PROC_STK_COL_MKT_TP_CD]\r\n StkCd = StkList.iat[iRow, CodeDef.PROC_STK_COL_STK_CD]\r\n LastDtMn = StkList.iat[iRow, CodeDef.PROC_STK_COL_LAST_DT_MN]\r\n LastDt = LastDtMn[:8]\r\n LastMn = LastDtMn[-4:]\r\n # 데이터가 없는 경우는 기본값 이용\r\n if (LastDt is None or len(LastDt.strip()) == 0):\r\n LastDt = CodeDef.INIT_STR_DT_DEFAULT\r\n if (LastMn is None or len(LastMn.strip()) == 0):\r\n LastMn = CodeDef.INIT_STR_MN_DEFAULT\r\n\r\n inEndDt = CodeDef.INIT_END_DT_DEFAULT\r\n inEndMn = CodeDef.INIT_END_MN_DEFAULT\r\n\r\n # 동기화보다 뒤면 패스\r\n if(int(LastDt + LastMn) >= int(CodeDef.INIT_END_DT_DEFAULT + CodeDef.INIT_END_MN_DEFAULT)):\r\n continue\r\n\r\n print(\"초기화 시작:\",StkCd,(LastDt + LastMn) ,(inEndDt + inEndMn))\r\n try:\r\n # 기존 시세삭제\r\n self.DBH.deleteMnQttn(MktTpCd, StkCd, LastDt, LastMn, inEndDt, inEndMn)\r\n\r\n # 시세 분봉 초기입력\r\n self.APIH.InitMnQttn(MktTpCd, StkCd, LastDt, LastMn, inEndDt, inEndMn)\r\n print(\"초기 분송 수신입력 종료:\", StkCd)\r\n\r\n # 빈분봉 처리시작\r\n print(\"빈분봉처리 시작!!:\", StkCd)\r\n\r\n # 빈분봉처리 대상 구간 조회\r\n print(\"조회:\", MktTpCd, StkCd, LastDt, LastMn, CodeDef.INIT_END_DT_DEFAULT, CodeDef.INIT_END_MN_DEFAULT)\r\n Qttn = self.DBH.queryMnQttn(MktTpCd,StkCd,LastDt,LastMn,CodeDef.INIT_END_DT_DEFAULT, CodeDef.INIT_END_MN_DEFAULT)\r\n\r\n ProcDt = datetime(year=int(LastDt[:4]), month=int(LastDt[4:6]), day=int(LastDt[6:]),hour=int(LastMn[:2]), minute=int(LastMn[2:]))\r\n if (CodeDef.isQttnBlnk(self, ProcDt)):\r\n ProcDt = CodeDef.getMon07AM(self,ProcDt)\r\n\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n QttnCnt = len(Qttn.index)\r\n FtPrc = 0.0\r\n HgPrc = 0.0\r\n LoPrc = 0.0\r\n ClPrc = 0.0\r\n UpdnPrc = 0.0\r\n Vlum = 0.0\r\n PreQttn = []\r\n Dt = None\r\n Mn = None\r\n for qIdx in range(QttnCnt):\r\n Dt = Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_DT]\r\n Mn = Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_MN]\r\n FtPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_FTPRC])\r\n HgPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_HGPRC])\r\n LoPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_LOPRC])\r\n ClPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_CLPRC])\r\n UpdnPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_UPDN_PRC])\r\n Vlum = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_VLUM])\r\n\r\n if((Dt+Mn) == (ProcDt.strftime(\"%Y%m%d%H%M\"))):\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n # 이전시세 백업\r\n PreQttn = [FtPrc, HgPrc, LoPrc, ClPrc, UpdnPrc, Vlum]\r\n continue\r\n else:\r\n # 이전시세가 없으면 넘긴다\r\n if(len(PreQttn)==0):\r\n ProcDt = datetime(year=int(Dt[:4]), month=int(Dt[4:6]), day=int(Dt[6:]),\r\n hour=int(Mn[:2]), minute=int(Mn[2:4]))\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n PreQttn = [FtPrc, HgPrc, LoPrc, ClPrc, UpdnPrc, Vlum]\r\n continue\r\n\r\n EndDt = datetime(year=int(Dt[:4]), month=int(Dt[4:6]), day=int(Dt[6:]),hour=int(Mn[:2]), minute=int(Mn[2:4]))\r\n MnCnt = (EndDt - ProcDt).total_seconds()/60.0\r\n\r\n for eIdx in range(int(MnCnt)):\r\n # 비는 시세 확인\r\n if(CodeDef.isQttnBlnk(self, ProcDt)):\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n continue\r\n if(ProcDt == EndDt):\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n break\r\n\r\n self.DBH.insertMnQttn(MktTpCd, StkCd, ProcDt.strftime(\"%Y%m%d\"), ProcDt.strftime(\"%H%M\"), PreQttn[0], PreQttn[1], PreQttn[2], PreQttn[3], PreQttn[4], PreQttn[5])\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n\r\n # 이전시세 백업\r\n PreQttn = [FtPrc, HgPrc, LoPrc, ClPrc, UpdnPrc, Vlum]\r\n \r\n # 빈분봉 채우기 if 끝\r\n # 종목 시세 정리 for qIdx in range(QttnCnt): 끝\r\n\r\n # 마지막 시세가 초기화 종료일까지 못갔을 경우 마지막을 채운다.\r\n if(int(ProcDt.strftime(\"%Y%m%d%H%M\")) < int(CodeDef.INIT_END_DT_DEFAULT+CodeDef.INIT_END_MN_DEFAULT)):\r\n\r\n EndDt = datetime(year=int(CodeDef.INIT_END_DT_DEFAULT[:4]), month=int(CodeDef.INIT_END_DT_DEFAULT[4:6]), day=int(CodeDef.INIT_END_DT_DEFAULT[6:]), hour=int(CodeDef.INIT_END_MN_DEFAULT[:2]),minute=int(CodeDef.INIT_END_MN_DEFAULT[2:4]))\r\n MnCnt = (EndDt - ProcDt).total_seconds() / 60.0\r\n\r\n for eIdx in range(int(MnCnt)+1):\r\n # 비는 시세 확인\r\n if (CodeDef.isQttnBlnk(self, ProcDt)):\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n continue\r\n if (int(ProcDt.strftime(\"%H%M\")) > int(EndDt.strftime(\"%H%M\"))):\r\n #print(\"ProcDt:\",ProcDt,\"EndDt:\",EndDt)\r\n break\r\n\r\n self.DBH.insertMnQttn(MktTpCd, StkCd, ProcDt.strftime(\"%Y%m%d\"), ProcDt.strftime(\"%H%M\"),\r\n PreQttn[0], PreQttn[1], PreQttn[2], PreQttn[3], PreQttn[4], PreQttn[5])\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n\r\n except Exception as e:\r\n print(\"빈분봉처리에러:\",e,StkCd)\r\n return None\r\n\r\n # 최종 초기화 일자시각 입력\r\n self.DBH.updateProcStkLastDtMn(MktTpCd, StkCd, (inEndDt+inEndMn))\r\n\r\n # 처리종목별 처리 for iRow in range(RowCnt): 끝\r\n\r\n ctypes.windll.user32.MessageBoxW(0, \"초기화 완료되었습니다.\", \"알림\", 0)\r\n self.ShowProcStkList()\r\n return None\r\n\r\n # 지수시세 실시간 받기/종료\r\n def ClickRcvIdxQttn(self):\r\n # 중지실행\r\n if(self.NowRcvIdxQttn):\r\n if (self.QttnSctkT is not None):\r\n print(\"지수시세 쓰레드 중지 시작\")\r\n try:\r\n self.QttnSctkT.DoStop()\r\n self.QttnSctkT.join()\r\n except Exception as e:\r\n print(\"지수시세 받기 쓰레드 중지 에러:\", e)\r\n return None\r\n print(\"지수시세 Loop 종료됨.\")\r\n self.btnRcvIdxQttn.setText(\"지수시세수신\")\r\n self.NowRcvIdxQttn = False\r\n self.btnRcvIdxQttn.setStyleSheet(\"background-color:None\")\r\n # 받기시작\r\n else:\r\n try:\r\n self.QttnSctkT = RcvSckt_handler(self,CodeDef.PORT_INDEX_QTTN)\r\n self.QttnSctkT.start()\r\n except Exception as e:\r\n print(\"지수시세 받기 쓰레드 시작 에러:\", e)\r\n return None\r\n print(\"지수시세 Loop 시작됨.\")\r\n self.btnRcvIdxQttn.setText(\"지수시세중지\")\r\n self.NowRcvIdxQttn = True\r\n self.btnRcvIdxQttn.setStyleSheet(\"background-color:rgb(255,020,147)\")\r\n return None\r\n\r\n # 글로벌 실시간 시세 받기/종료\r\n def ClickRcvGlobalQttn(self):\r\n # 중지실행\r\n if (self.NowRcvGlobalQttn):\r\n #for idx in range(len(self.ProcStkList)):\r\n # self.APIH.StopRealRcv(None, self.ProcStkList[idx])\r\n self.APIH.StopAllRealRcv()\r\n self.btnRcvGlobalQttn.setText(\"글로벌시세수신\")\r\n self.NowRcvGlobalQttn = False\r\n self.btnRcvGlobalQttn.setStyleSheet(\"background-color:None\")\r\n print(\"Global 시세받기 종료됨.\")\r\n # 받기시작\r\n else:\r\n self.btnRcvGlobalQttn.setText(\"글로벌시세중지\")\r\n self.NowRcvGlobalQttn = True\r\n self.btnRcvGlobalQttn.setStyleSheet(\"background-color:rgb(255,020,147)\")\r\n print(\"Global 시세받기 시작됨.\")\r\n for idx in range(len(self.ProcStkList)):\r\n self.APIH.OnRequest(\"REAL_QTTN\", \"61\", self.ProcStkList[idx])\r\n #self.APIH.waitSrvrRspn()\r\n return None\r\n\r\n # 글로벌 저장된 시세 받기/종료\r\n def ClickRcvGlobalSavedQttn(self):\r\n # 중지실행\r\n if (self.NowRcvGlobalSavedQttn):\r\n try:\r\n self.TestQttnSnd.DoStop()\r\n #self.TestQttnSnd.join()\r\n except Exception as e:\r\n print(\"저장된 글로벌 시세받기 쓰레드 중지 에러:\", e)\r\n return None\r\n self.btnRcvGlobalSavedQttn.setText(\"저장된시세수신\")\r\n self.NowRcvGlobalSavedQttn = False\r\n self.btnRcvGlobalSavedQttn.setStyleSheet(\"background-color:None\")\r\n print(\"저장된 Global 시세받기 종료됨.\")\r\n # 받기시작\r\n else:\r\n try:\r\n if(self.TestQttnSnd is None):\r\n # 차트 X축 변경(0900에 시작으로 변경)\r\n self.CrtH.SetTestQttnXList()\r\n\r\n self.TestQttnSnd = TestQttn_Sender(self)\r\n self.TestQttnSnd.start()\r\n else:\r\n self.TestQttnSnd.DoRestart()\r\n except Exception as e:\r\n print(\"저장된 글로벌 시세받기 쓰레드 시작 에러:\", e)\r\n return None\r\n self.btnRcvGlobalSavedQttn.setText(\"저장된시세수신중지\")\r\n self.NowRcvGlobalSavedQttn = True\r\n self.btnRcvGlobalSavedQttn.setStyleSheet(\"background-color:rgb(255,020,147)\")\r\n print(\"저장된 Global 시세받기 시작됨.\")\r\n\r\n return None\r\n\r\n # 실시간 수신시세 처리\r\n # inProcTp : 처리구분\r\n # inQttn : 시세문자열\r\n def ProcRcvRealQttn(self,inProcTp,inRcvQttn):\r\n # 다중수신여부 확인\r\n inQttn = inRcvQttn.split(\"|\")\r\n InfoCnt = len(inQttn)\r\n QttnList = [] # 시세열\r\n Tmplist = [] # 임시 시세열\r\n # 시세 파싱\r\n for i in range(InfoCnt):\r\n if(len(inQttn[i]) == 0):\r\n continue\r\n # 시세넣기\r\n if (inQttn[i] == \"E\"):\r\n QttnList.append(Tmplist)\r\n Tmplist = []\r\n else:\r\n Tmplist.append(inQttn[i])\r\n\r\n # 시세차트설정\r\n if(inProcTp == \"KOSPI_INDEX\"):\r\n self.CrtH.UpdateRealQttn(QttnList, \"CurrentPrice\")\r\n #print(\"QttnList:\",QttnList)\r\n self.TFH.UpdateQttn(QttnList)\r\n elif(inProcTp == \"GLOBAL_QTTN\"):\r\n #self.CrtH.UpdateRealQttn(QttnList, \"Prediction\") # 테스트용\r\n # 딥러닝 시세 업데이트 및 시세 저장\r\n self.TFH.UpdateQttn(QttnList)\r\n elif (inProcTp == \"TF_RSLT\"):\r\n self.dispText(\"결과수신!!:\" + inRcvQttn)\r\n self.CrtH.UpdateRealQttn(QttnList, \"Prediction\") # 테스트용\r\n else:\r\n print(\"inProcTp 확인\")\r\n\r\n return None\r\n\r\n # 딥러닝 동작/중지\r\n def ClickTensorFlow(self):\r\n # 실행중지\r\n if (self.NowTensorFlow):\r\n # 송신 소켓은 따로 처리하지 않는다.\r\n # 수신 쓰레드 중지\r\n if (self.TfRcvSctkT is not None):\r\n print(\"딥러닝 쓰레드 중지 시작\")\r\n try:\r\n self.TfRcvSctkT.DoStop()\r\n self.TfRcvSctkT.join()\r\n except Exception as e:\r\n print(\"딥러닝 쓰레드 중지에러\")\r\n print(\"에러:\",e)\r\n return None\r\n print(\"딥러닝 Loop 종료됨.\")\r\n self.btnTensorFlow.setText(\"딥러닝연결\")\r\n self.btnTensorFlow.setStyleSheet(\"background-color:None\")\r\n self.NowTensorFlow = False\r\n # 동작실행\r\n else:\r\n # 수신소켓 쓰레드 시작\r\n try:\r\n self.TfRcvSctkT = RcvSckt_handler(self, CodeDef.PORT_TF_RCV_RSLT)\r\n self.TfRcvSctkT.start()\r\n except Exception as e:\r\n print(\"딥러닝 쓰레드 시작에러:\", e)\r\n return None\r\n\r\n # 송신소켓 접속\r\n try:\r\n if(self.TfSndSctkT is None):\r\n self.TfSndSctkT = SndSckt_handler()\r\n if (self.TfSndSctkT.GetOnSock() == False):\r\n self.TfSndSctkT.CnntSckt(CodeDef.PORT_TF_DATA)\r\n except Exception as e:\r\n print(\"송신소켓 접속 시작에러:\", e)\r\n return None\r\n print(\"딥러닝 Loop 시작됨.\")\r\n self.btnTensorFlow.setStyleSheet(\"background-color:rgb(255,020,147)\")\r\n self.btnTensorFlow.setText(\"딥러닝중지\")\r\n self.NowTensorFlow = True\r\n\r\n return None\r\n\r\n\r\n # 딥러닝 프로그램에 데이터 전송\r\n # TFQttn_handler에서 사용\r\n # inSndData : 전송데이터\r\n def SendTensorFlow(self,inSndData):\r\n #self.dispText(\"시세전송!!:\"+inSndData)\r\n # 데이터 전송\r\n try:\r\n if (self.TfSndSctkT is not None and self.TfSndSctkT.GetOnSock()):\r\n self.TfSndSctkT.SendData(inSndData)\r\n except Exception as e:\r\n print(\"딥러닝 데이터 전송 에러:\", e)\r\n\r\n return None\r\n\r\n\r\n # 비어있는 분봉시세 초기화만 처리\r\n def ClickMnQttnOrd(self):\r\n # 처리대상\r\n #StkList = ['NQU18','HGU18','ADU18']\r\n #StkList = ['ADU18']\r\n StkList = [\"USDCNH\"]\r\n RowCnt = len(StkList)\r\n for iRow in range(RowCnt):\r\n StkCd = StkList[iRow]\r\n print(\"처리시작:\",StkCd)\r\n try:\r\n # 분봉조회\r\n #Qttn = self.DBH.queryMnQttn(\"DERV\",StkCd,CodeDef.INIT_STR_DT_DEFAULT, CodeDef.INIT_STR_MN_DEFAULT, CodeDef.INIT_END_DT_DEFAULT, CodeDef.INIT_END_MN_DEFAULT)\r\n Qttn = self.DBH.queryMnQttn(\"DERV\", StkCd, \"20180604\", \"0900\",\"20181102\", \"0859\")\r\n\r\n ProcDt = datetime(year=int(CodeDef.INIT_STR_DT_DEFAULT[:4]), month=int(CodeDef.INIT_STR_DT_DEFAULT[4:6]), day=int(CodeDef.INIT_STR_DT_DEFAULT[6:]),hour=int(CodeDef.INIT_STR_MN_DEFAULT[:2]), minute=int(CodeDef.INIT_STR_MN_DEFAULT[2:]))\r\n if (CodeDef.isQttnBlnk(self, ProcDt)):\r\n ProcDt = CodeDef.getMon07AM(self,ProcDt)\r\n\r\n QttnCnt = len(Qttn.index)\r\n FtPrc = 0.0\r\n HgPrc = 0.0\r\n LoPrc = 0.0\r\n ClPrc = 0.0\r\n UpdnPrc = 0.0\r\n Vlum = 0.0\r\n PreQttn = []\r\n for qIdx in range(QttnCnt):\r\n Dt = Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_DT]\r\n Mn = Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_MN]\r\n FtPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_FTPRC])\r\n HgPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_HGPRC])\r\n LoPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_LOPRC])\r\n ClPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_CLPRC])\r\n UpdnPrc = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_UPDN_PRC])\r\n Vlum = float(Qttn.iat[qIdx, CodeDef.QTTN_MN_DATA_COL_VLUM])\r\n\r\n if( qIdx in [0,1,2,3,4]):\r\n print(\"(Dt+Mn) == (ProcDt.strftime(%Y%m%d%H%M)):\", (Dt + Mn), (ProcDt.strftime(\"%Y%m%d%H%M\")))\r\n\r\n if((Dt+Mn) == (ProcDt.strftime(\"%Y%m%d%H%M\"))):\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n # 이전시세 백업\r\n PreQttn = [FtPrc, HgPrc, LoPrc, ClPrc, UpdnPrc, Vlum]\r\n continue\r\n else:\r\n # 이전시세가 없으면 조회 첫번째로 세팅후 넘긴다\r\n if(len(PreQttn)==0):\r\n ProcDt = datetime(year=int(Dt[:4]), month=int(Dt[4:6]), day=int(Dt[6:]), hour=int(Mn[:2]),minute=int(Mn[2:4]))\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n PreQttn = [FtPrc, HgPrc, LoPrc, ClPrc, UpdnPrc, Vlum]\r\n continue\r\n\r\n #print(\"(Dt+Mn) == (ProcDt.strftime(%Y%m%d%H%M)):\", (Dt + Mn), (ProcDt.strftime(\"%Y%m%d%H%M\")))\r\n\r\n EndDt = datetime(year=int(Dt[:4]), month=int(Dt[4:6]), day=int(Dt[6:]),hour=int(Mn[:2]), minute=int(Mn[2:4]))\r\n MnCnt = (EndDt - ProcDt).total_seconds()/60.0\r\n\r\n for eIdx in range(int(MnCnt)):\r\n # 비는 시세 확인\r\n if(CodeDef.isQttnBlnk(self, ProcDt)):\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n continue\r\n if(ProcDt == EndDt):\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n break\r\n\r\n self.DBH.insertMnQttn(\"DERV\"\r\n , StkCd, ProcDt.strftime(\"%Y%m%d\"), ProcDt.strftime(\"%H%M\"), PreQttn[0], PreQttn[1], PreQttn[2], PreQttn[3], PreQttn[4], PreQttn[5])\r\n ProcDt = ProcDt + CodeDef.ONE_MINUTE\r\n\r\n # 이전시세 백업\r\n PreQttn = [FtPrc, HgPrc, LoPrc, ClPrc, UpdnPrc, Vlum]\r\n\r\n # -- 빈분봉 채워넣기 for문 종료 -----\r\n\r\n # ------- 조회된 시세 main for문 종료 ------\r\n except Exception as e:\r\n print(e)\r\n print(\"처리끝:\",StkCd)\r\n # --------- 빈분봉처리 종료 ---------\r\n ctypes.windll.user32.MessageBoxW(0, \"초기화 완료되었습니다.\", \"알림\", 0)\r\n return None\r\n\r\n # 출력 표시\r\n def dispText(self,inText):\r\n self.edtChk.append(inText) ## 임시확인\r\n return None\r\n\r\n # 첫시세 설정\r\n # 장중 마지막 시세를 가져와 설정함.\r\n def ClickSetFstQttn(self):\r\n\r\n print(\"첫시세 설정!!\")\r\n\r\n mn = int(datetime.today().strftime(\"%H%M\"))\r\n\r\n if(mn > 1500 or mn < 900):\r\n ctypes.windll.user32.MessageBoxW(0, \"장중에만 사용가능\", \"알림\", 0)\r\n return None\r\n\r\n FstQttn = self.DBH.queryFstTFQttn()\r\n\r\n RowCnt = len(FstQttn)\r\n for idx in range(RowCnt):\r\n FstQttn[idx] = str(FstQttn[idx])\r\n\r\n print(\"FstQttn:\", FstQttn)\r\n\r\n self.TFH.SetFstQttn(FstQttn)\r\n\r\n return None\r\n\r\n # 분봉 시세 저장\r\n # inProcTp : 처리구분\r\n # inStkCd : 종목코드\r\n # inDt : 일자\r\n # inTime : 시간(HHMM)\r\n # inFtPrc : 시가\r\n # inHgPrc : 고가\r\n # inLoPrc : 저가\r\n # inClPrc : 종가\r\n # inUpDnPrc : 등락가\r\n # inVlum : 거래량\r\n def insertMnQttn(self, inProcTp, inStkCd, inDt, inMn, inFtPrc, inHgPrc, inLoPrc, inClPrc, inUpDnPrc, inVlum):\r\n\r\n self.DBH.insertMnQttn(inProcTp, inStkCd, inDt,inMn, inFtPrc, inHgPrc, inLoPrc, inClPrc, inUpDnPrc, inVlum)\r\n\r\n return None","sub_path":"YT_Prediction/MainForm_handler.py","file_name":"MainForm_handler.py","file_ext":"py","file_size_in_byte":26752,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"406594986","text":"import cv2\nimport os\nimport glob\nimport tf_calib\nimport numpy as np\n\ntry:\n import python.modules.tf_calib\nexcept ImportError:\n pass\n\n\ndef calibrate(path: str, filter: str, nrows: int, ncols: int):\n calibrator = tf_calib.TFCalib()\n objp = np.zeros((nrows * ncols, 3), np.float32)\n objp[:, :2] = np.mgrid[0:nrows, 0:ncols].T.reshape(-1, 2)\n for imname in glob.glob(os.path.join(path, filter)):\n image = cv2.imread(imname, cv2.IMREAD_GRAYSCALE)\n f, corners = cv2.findChessboardCorners(image, (nrows, ncols), None)\n cv2.cornerSubPix(image, corners, (11, 11), (-1, -1),\n (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001))\n calibrator.train(np.squeeze(corners.astype(np.float64)), objp)\n\n\ndef test_solve():\n def f1(x, y):\n return x ** 2 + x * y\n\n def f2(x, y):\n return y ** 2 + 2 * y\n\n x_sol = 2\n y_sol = 3\n\n constants = [f1(x_sol, y_sol), f2(x_sol, y_sol)]\n X = np.ndarray((2,), dtype=np.float32)\n tf_calib.solve([f1, f2], constants, np.array([[0., 3.], [2., 4.]]), X, 100)\n\n\nif __name__ == '__main__':\n # test_solve()\n calibrate('/data/stereo_images/left', 'left*.png', 8, 13)\n","sub_path":"python/modules/test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":1198,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"486115885","text":"from abc import ABCMeta, abstractmethod\n\nclass CourseException(Exception):\n\tdef __init__(self, message):\n\t\tsuper().__init__(message)\n\nclass Course():\n\tdef __init__(self, name):\n\t\tself.name = name\n\t\tself.teachers = set()\n\t\tself.students = set()\n\t\n\tdef __repr__(self):\n\t\treturn self.name\n\t\n\tdef add_teacher(self, teacher):\n\t\tif not isinstance(teacher, Teacher):\n\t\t\traise CourseException(\n\t\t\t\t'Class \"{}\" is not Teacher!'.format(teacher)\n\t\t\t)\n\t\t\t\n\t\tif teacher not in self.teachers:\n\t\t\tself.teachers.add(teacher)\n\t\tif not teacher.hasCource(self):\n\t\t\tteacher.add_cource(self)\n\t\t\n\tdef remove_teacher(self, teacher):\n\t\tif not isinstance(teacher, Teacher):\n\t\t\traise CourseException(\n\t\t\t\t'Class \"{}\" is not Teacher!'.format(teacher)\n\t\t\t)\n\t\t\n\t\tif teacher in self.teachers:\n\t\t\tself.teachers.remove(teacher)\n\t\tif teacher.hasCource(self):\n\t\t\tteacher.remove_cource(self)\n\t\t\t\n\tdef hasTeacher(self, teacher):\n\t\tif not isinstance(teacher, Teacher):\n\t\t\traise CourseException(\n\t\t\t\t'Class \"{}\" is not Teacher!'.format(teacher)\n\t\t\t)\n\t\t\t\n\t\treturn teacher in self.teachers\n\t\t\n\tdef get_list_all_teachers(self):\n\t\treturn list(self.teachers)\n\t\t\n\tdef add_student(self, student):\n\t\tif not isinstance(student, Student):\n\t\t\traise CourseException(\n\t\t\t\t'Class \"{}\" is not Student!'.format(student)\n\t\t\t)\n\t\t\t\n\t\tif student not in self.students:\n\t\t\tself.students.add(student)\n\t\tif not student.hasCource(self):\n\t\t\tstudent.add_cource(self)\n\t\t\n\tdef remove_student(self, student):\n\t\tif not isinstance(student, Student):\n\t\t\traise CourseException(\n\t\t\t\t'Class \"{}\" is not Student!'.format(student)\n\t\t\t)\n\t\t\n\t\tif student in self.students:\n\t\t\tself.students.remove(student)\n\t\tif student.hasCource(self):\n\t\t\tstudent.remove_cource(self)\n\t\n\tdef hasStudent(self, student):\n\t\tif not isinstance(student, Student):\n\t\t\traise CourseException(\n\t\t\t\t'Class \"{}\" is not Student!'.format(student)\n\t\t\t)\n\t\t\t\n\t\treturn student in self.students\n\t\t\n\tdef get_list_all_students(self):\n\t\treturn list(self.students)\n\t\n\tdef getInfoAboutCources(self):\n\t\treturn 'Курс \"{}\". \\nПреподаватели: {} \\nСтуденты: {}\\n'.format(self.name, \\\n\t\t\t\"\".join(str(i) for i in list(self.teachers)), \"\".join(str(i) for i in list(self.students)))\n\t\n\t\t\n\t\t\nclass RoleInItmoCourceException(Exception):\n\tdef __init__(self, message):\n\t\tsuper().__init__(message)\n\t\t\t\nclass RoleInItmoCource(metaclass=ABCMeta):\n\tdef __init__(self, firstname, lastname):\n\t\tself.firstname = firstname\n\t\tself.lastname = lastname\n\t\tself.cources = set()\n\t\n\t@abstractmethod\n\tdef __repr__(self):\n\t\tpass\n\t\n\tdef add_cource(self, cource):\n\t\tif not isinstance(cource, Course):\n\t\t\traise RoleInItmoCourceException(\n\t\t\t\t'Class \"{}\" is not Course!'.format(cource)\n\t\t\t)\n\t\tself.cources.add(cource)\n\t\t\n\tdef remove_cource(self, cource):\n\t\tif not isinstance(cource, Course):\n\t\t\traise RoleInItmoCourceException(\n\t\t\t\t'Class \"{}\" is not Course!'.format(cource)\n\t\t\t)\n\t\tif cource in self.cources:\n\t\t\tself.cources.remove(cource)\n\t\t\n\tdef getInfoAboutCources(self):\n\t\treturn ''.join(str(i) for i in list(self.cources))\n\t\t\n\tdef hasCource(self, cource):\n\t\tif not isinstance(cource, Course):\n\t\t\traise RoleInItmoCourceException(\n\t\t\t\t'Class \"{}\" is not Course!'.format(cource)\n\t\t\t)\n\t\treturn cource in self.cources\n\t\t\n\tdef get_list_all_cources(self):\n\t\treturn list(self.cources)\n\nclass Student(RoleInItmoCource):\n\tdef __init__(self, firstname, lastname):\n\t\tsuper().__init__(firstname, lastname)\n\t\n\tdef __repr__(self):\n\t\treturn '\"{} {}\"'.format(self.firstname, self.lastname)\n\t\n\tdef getInfoAboutCources(self):\n\t\treturn 'Я учусь на следующих курсах: \"{}\"'.format(super().getInfoAboutCources())\n\t\t\n\tdef remove_cource(self, cource):\n\t\tsuper().remove_cource(cource)\n\t\tif cource.hasStudent(self):\n\t\t\tcource.remove_student(self)\n\t\t\t\n\tdef add_cource(self, cource):\n\t\tsuper().add_cource(cource)\n\t\tif not cource.hasStudent(self):\n\t\t\tcource.add_student(self)\n\t\t\nclass Teacher(RoleInItmoCource):\n\tdef __init__(self, firstname, lastname, skills):\n\t\tsuper().__init__(firstname, lastname)\n\t\tself.skills = skills\n\t\n\tdef __repr__(self):\n\t\treturn '\"{} {}\" Умения: \"{}\".'.format(self.firstname, self.lastname, \\\n\t\t\t\", \".join(self.skills))\n\t\n\tdef getInfoAboutCources(self):\n\t\treturn 'Я преподаю на следующих курсах: \"{}\"'.format(super().getInfoAboutCources())\n\t\t\n\tdef remove_cource(self, cource):\n\t\tsuper().remove_cource(cource)\n\t\tif cource.hasTeacher(self):\n\t\t\tcource.remove_teacher(self)\n\t\t\t\n\tdef add_cource(self, cource):\n\t\tsuper().add_cource(cource)\n\t\tif not cource.hasTeacher(self):\n\t\t\tcource.add_teacher(self)\n\t\t\t\npython_cource = Course(\"Python\")\nteacher = Teacher(\"Кирилл\", \"Версетти\", ['Python', 'PHP', 'JS', 'HTML', 'CSS', 'Docker'])\nstudent = Student(\"Александр\", \"Разыграев\")\npython_cource.add_teacher(teacher)\npython_cource.add_student(student)\n\nprint(student.getInfoAboutCources())\nprint(teacher.getInfoAboutCources())\nprint(python_cource.getInfoAboutCources())\n\npython_cource.remove_teacher(teacher)\npython_cource.remove_student(student)\n\nprint(student.getInfoAboutCources())\nprint(teacher.getInfoAboutCources())\nprint(python_cource.getInfoAboutCources())\n\npython_cource.add_teacher(teacher)\npython_cource.add_student(student)\nstudent2 = Student(\"Иванов\", \"Иван\")\npython_cource.add_student(student2)\n\nprint(student.getInfoAboutCources())\nprint(teacher.getInfoAboutCources())\nprint(python_cource.getInfoAboutCources())\n\nteacher.remove_cource(python_cource)\nstudent2.remove_cource(python_cource)\n\nprint(student.getInfoAboutCources())\nprint(teacher.getInfoAboutCources())\nprint(python_cource.getInfoAboutCources())\n\nstudent2.add_cource(python_cource)\n\nprint(student.getInfoAboutCources())\nprint(teacher.getInfoAboutCources())\nprint(python_cource.getInfoAboutCources())\n\nprint(python_cource.get_list_all_students())\nprint(python_cource.get_list_all_teachers())\nprint(student2.get_list_all_cources())","sub_path":"task_training_center.py","file_name":"task_training_center.py","file_ext":"py","file_size_in_byte":5859,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"380658606","text":"import math\nfrom display import *\n\ndef magnitude(vector):\n return math.sqrt(math.pow(vector[0],2)+math.pow(vector[1],2)+math.pow(vector[2],2))\n\n#vector functions\n#normalize vector, should modify the parameter\ndef normalize(vector):\n print(vector)\n length = magnitude(vector)\n if length==0:\n return vector\n else:\n vector[0]/=length\n vector[1]/=length\n vector[2]/=length\n return vector\n#Return the dot porduct of a . b\ndef dot_product(a, b):\n return a[0]*b[0]+a[1]*b[1]+a[2]*b[2]\n\n#Calculate the surface normal for the triangle whose first\n#point is located at index i in polygons\ndef calculate_normal(polygons, i):\n p0=polygons[i]\n p1=polygons[i+1]\n p2=polygons[i+2]\n a=[p1[0]-p0[0],p1[1]-p0[1],p1[2]-p0[2]]\n b=[p2[0]-p0[0],p2[1]-p0[1],p2[2]-p0[2]]\n n=[a[1]*b[2]-a[2]*b[1],a[2]*b[0]-a[0]*b[2],a[0]*b[1]-a[1]*b[0]]\n return n\n","sub_path":"gmath.py","file_name":"gmath.py","file_ext":"py","file_size_in_byte":897,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"575735525","text":"#encoding=utf-8\r\nimport os\r\nimport json\r\nfrom apyori import apriori # Frequent Pattern 分析用\r\nimport jieba # 中文斷詞用\r\nfrom langconv import* # 繁體轉簡體用，為了讓 結巴 的中文斷詞表現更好\r\nfrom wordcloud import WordCloud\r\n\r\n# 有些字我們不在乎，只要一碰到就可以去掉它...\r\nstop_word_list = [', ', ',', '...', '的', '\\xa0', ' ', '「', '」', '。', '，', '、', '（', '）', '：', '.', '...', '】', '【', '....', '”',\r\n 'a', 'is', 'of', 'the', 'an', 'to', 'as', 'at', 'by', 'in', 'on', 'with', 'for', 'and', 'are', 'that', 'have', 'has', 'had', 'we',\r\n '-', '—', 'your', 'its', '', '“', '／', '；', '》', '《', '“', 'he', 'they', 'was', 'or', 'be', 'this', 'how', 'his', 'per',\r\n 'it\\'s', 'so', 'who', 'were', 'their', 'it', 'what', 'you', 'our', 'she', 'my', 'say', 10, 20]\r\n\r\n# 讀取 英文 版本JSON檔，並將所有檔案整合成一份 txt 檔並輸出，接著再做資料處理 (老實說，模組化寫得不好... 較無彈性...)\r\n# 因為中文版處理方式較麻煩 (需斷詞)，故分成兩種版本\r\ndef read_json_en(keywords_of_title_en, keywords_of_text_en):\r\n # 將所有爬到的 English新聞 們整合成一份 txt 檔案，以便將來討論某個特定關鍵字的成因\r\n def aggregate_news_en(json_file):\r\n with open('aggregated_news_en.txt', 'w') as f:\r\n for data in json_file:\r\n f.write('news_title: ')\r\n f.write(str(data['news_title'].encode(encoding=\"utf-8\")))\r\n f.write('\\n')\r\n f.write('news_text: ')\r\n f.write(str(data['news_text'].encode(encoding=\"utf-8\")))\r\n f.write('\\n')\r\n f.write('news_link: ')\r\n f.write(str(data['news_link'].encode(encoding=\"utf-8\")))\r\n f.write('\\n\\n')\r\n\r\n\r\n # 我們要一次處理多個 json 檔案，這邊要 ***手動*** 設定資料夾名稱，並放在project的同一個資料夾內 (或者用絕對路徑)\r\n file_name = ['Anti+Extradition+Law_0622', 'Hong+Kong_0622', 'Tiananmen_0622']\r\n # 把所有讀進來的JSON檔案存進一個list內\r\n json_data_list = list()\r\n for name in file_name:\r\n if os.path.exists(name):\r\n print(name + '/' + name[:-5] + '.json')\r\n with open(name + '/' + name[:-5] + '.json', 'r') as input_file:\r\n tmp_json_data = json.load(input_file)\r\n json_data_list.extend(tmp_json_data)\r\n else:\r\n print('資料夾名稱: %s 應該有誤，請檢查' % (name))\r\n # print(json_data_list)\r\n # print(len(json_data_list)) # 看一下讀進了幾條新聞\r\n aggregate_news_en(json_data_list) # 將所有讀進來的 英文 新聞整合成一份txt檔\r\n\r\n # 開始把句子中的單字拆出來，順便去除stop_word，未來要做資料分析用\r\n for news in json_data_list:\r\n # 處理標題\r\n tmp = []\r\n for char in news['news_title'].lower().split(): # 記得要一律轉成小寫，不然之後會分析不出frequent pattern\r\n if char not in stop_word_list:\r\n tmp.append(char)\r\n keywords_of_title_en.append(tmp)\r\n\r\n # 處理內文\r\n tmp = []\r\n for char in news['news_text'].lower().split(): # 記得要一律轉成小寫，不然之後會分析不出frequent pattern\r\n if char not in stop_word_list:\r\n tmp.append(char)\r\n keywords_of_text_en.append(tmp)\r\n\r\n\r\n# 讀取 中文 版本JSON檔，並將所有檔案整合成一份 txt 檔並輸出，接著再做資料處理 (老實說，模組化寫得不好... 較無彈性...)\r\n# 因為中文版處理方式較麻煩 (需斷詞)，故分成兩種版本\r\ndef read_json_ch(keywords_of_title_ch, keywords_of_text_ch):\r\n # 將所有爬到的新聞們整合成一份 txt 檔案，中文版需處理編碼問題，比較麻煩\r\n def aggregate_news_ch(json_file):\r\n with open('aggregated_news_ch.txt', 'wb') as f: # 這邊要記得用wb\r\n for data in json_file:\r\n f.write('news_title: '.encode('utf8'))\r\n f.write(data['news_title'].encode('utf8'))\r\n f.write('\\n'.encode('utf8'))\r\n f.write('news_text: '.encode('utf8'))\r\n f.write(data['news_text'].encode(encoding=\"utf-8\"))\r\n f.write('\\n'.encode('utf8'))\r\n f.write('news_link: '.encode('utf8'))\r\n f.write(data['news_link'].encode(encoding=\"utf-8\"))\r\n f.write('\\n\\n'.encode('utf8'))\r\n\r\n\r\n # 我們要一次處理多個 json 檔案，這邊要 ***手動*** 設定資料夾名稱，並放在project的同一個資料夾內 (或者用絕對路徑)\r\n file_name = ['六四_0622', '香港_0622', '反送中_0622']\r\n json_data_list = list()\r\n for name in file_name:\r\n if os.path.exists(name):\r\n with open(name + '/' + name[:-5] + '.json', 'r') as input_file:\r\n tmp_json_data = json.load(input_file)\r\n json_data_list.extend(tmp_json_data)\r\n else:\r\n print('檔案名稱: %s 應該有誤，請檢查' % (name))\r\n # print(json_data_list)\r\n # print(len(json_data_list)) # 看一下讀進了幾條新聞\r\n aggregate_news_ch(json_data_list) # 將所有讀進來的 中文 新聞整合成一份txt檔\r\n\r\n # 開始把句子中的字拆出來 (中文斷詞)，順便去除stop_word，未來要做資料分析用\r\n for news in json_data_list:\r\n # 處理標題\r\n title = news['news_title'] # 中文比較麻煩，沒辦法用split來切。 需使用 結巴 函式庫\r\n title = Converter('zh-hans').convert(title) # 繁體中文轉換成簡體中文，這樣斷詞的效果比較好\r\n # print(title)\r\n seg_list = jieba.cut(title, cut_all=False, HMM=True) # 預設精準模式\r\n # seg_list = jieba.cut_for_search(title, HMM=True) # 搜尋引擎模式，好像沒有比較厲害?\r\n split_word = \"/\".join(seg_list)\r\n # print(split_word)\r\n keywords_of_title_ch.append(split_word)\r\n\r\n # 處理內文\r\n text = news['news_text'] # 中文比較麻煩，沒辦法用split來切。 需使用 結巴 函式庫\r\n text = Converter('zh-hans').convert(text) # 繁體中文轉換成簡體中文，這樣斷詞的效果比較好\r\n # print(text)\r\n seg_list = jieba.cut(text, cut_all=False, HMM=True) # 預設精準模式\r\n # seg_list = jieba.cut_for_search(text, HMM=True) # 搜尋引擎模式，不知道有沒有比較厲害?\r\n split_word = \"/\".join(seg_list)\r\n # print(split_word)\r\n keywords_of_text_ch.append(split_word)\r\n\r\n # 將斷詞過後的中文 標題 弄成適合作Apriori的資料格式 (list)，故使用到tmp, tmp2 (外層list包一堆內層list)\r\n tmp = []\r\n for sentence in keywords_of_title_ch:\r\n words = sentence.split('/')\r\n tmp2 = []\r\n for word in words:\r\n if word not in stop_word_list:\r\n word = Converter('zh-hant').convert(word) # 最後轉換回繁體中文\r\n tmp2.append(word)\r\n tmp.append(tmp2)\r\n keywords_of_title_ch[:] = tmp # 這麼做超級重要!! 因為 keywords_of_text_ch[] = tmp 只是改變local的指標，當函數結束就被回收了 (所以不會真的變動到...)\r\n\r\n # 將斷詞過後的中文 內文 弄成適合作Apriori的資料格式 (list)，故使用到tmp, tmp2 (外層list包一堆內層list)\r\n tmp = []\r\n for sentence in keywords_of_text_ch:\r\n words = sentence.split('/')\r\n tmp2 = []\r\n for word in words:\r\n if word not in stop_word_list:\r\n word = Converter('zh-hant').convert(word) # 最後轉換回繁體中文\r\n tmp2.append(word)\r\n tmp.append(tmp2)\r\n keywords_of_text_ch[:] = tmp # 這麼做超級重要!! 因為 keywords_of_text_ch[] = tmp 只是改變local的指標，當函數結束就被回收了 (所以不會真的變動到...)\r\n\r\n\r\n# 回傳frequent pattern分析後的結果 (frozen set)\r\ndef frequent_pattern_analyze(data):\r\n print('----- 開始Frequent Pattern分析... (Apriori) -----')\r\n # print(data)\r\n association_rules = apriori(data)\r\n association_results = list(association_rules)\r\n frequent_pattern_result = []\r\n for i in association_results:\r\n frequent_pattern_result.append(i)\r\n print('----- Frequent Pattern分析完成! -----')\r\n return frequent_pattern_result\r\n\r\n\r\n# 由於Frequent Pattern效果不好，故嘗試關鍵字頻率分析\r\ndef frequency_statistics(data):\r\n frequency_count = {}\r\n for news_title in data:\r\n for word in news_title:\r\n if word not in frequency_count and word not in stop_word_list:\r\n frequency_count[word] = 1\r\n elif word in frequency_count and word not in stop_word_list:\r\n frequency_count[word] += 1\r\n\r\n # 依照出現頻率由大到小排序\r\n sorted_frequency_count = sorted(frequency_count.items(), key=lambda x: x[1], reverse=True)\r\n # 這邊再進一步處理，把一些 單一字 或 頻率太低的字過濾掉 (e.g., '我': 14)\r\n freq_count_result = []\r\n for i in sorted_frequency_count:\r\n if len(i[0]) >= 2 and i[1] >= 15: # len(i[0]) 是中文詞長度、len(i[1]) 是出現頻率 (原則上我們對單一中文字沒興趣，故過濾)\r\n freq_count_result.append( (i[0], i[1]) )\r\n return freq_count_result\r\n\r\n\r\n# 方便 print list用的\r\ndef print_data(data):\r\n print(' --- print data... ---')\r\n for i in data:\r\n print(i)\r\n print(' --- print finished! ---')\r\n\r\n# 將分析出來的 頻率統計 輸出成4個txt檔案，以供將來做成文字雲\r\ndef output_frequency_count(word_count_title_en, word_count_text_en,\r\n word_count_title_ch, word_count_text_ch):\r\n with open('word_count_title_en.txt', 'w') as f:\r\n for tuple in word_count_title_en:\r\n for i in range(tuple[1]):\r\n f.write(tuple[0] + ' ')\r\n f.write('\\n')\r\n with open('word_count_text_en.txt', 'w') as f:\r\n for tuple in word_count_text_en:\r\n for i in range(tuple[1]):\r\n f.write(tuple[0] + ' ')\r\n f.write('\\n')\r\n with open('word_count_title_ch.txt', 'w') as f:\r\n for tuple in word_count_title_ch:\r\n for i in range(tuple[1]):\r\n f.write(tuple[0] + ' ')\r\n f.write('\\n')\r\n with open('word_count_text_ch.txt', 'w') as f:\r\n for tuple in word_count_text_ch:\r\n for i in range(tuple[1]):\r\n f.write(tuple[0] + ' ')\r\n f.write('\\n')\r\n\r\n\r\n# 將統計出來的資料視覺化成文字雲 共4張圖片，不輸出frequent pattern (沒有找到明顯的pattern, 且格式比較難處理)\r\ndef output_word_cloud():\r\n # 這邊要 ***手動*** 設定txt檔案名稱，並放在project的同一個資料夾內 (或者用絕對路徑)\r\n for file_name in ['word_count_title_en', 'word_count_text_en', 'word_count_title_ch', 'word_count_text_ch']:\r\n text = open( file_name + \".txt\", 'r').read()\r\n wc = WordCloud(background_color=\"white\",\r\n width=1000,\r\n height=860,\r\n margin=2,\r\n font_path='msyh.ttf', # 引入一個支援中文的字型，建議字型放在同一個資料夾內\r\n collocations=False, # 這行超重要!!!，不然字體會重複出現多次\r\n max_words=100,\r\n max_font_size=150,\r\n min_font_size=32)\r\n wc.generate(text)\r\n wc.to_file(file_name + '.png')\r\n\r\n\r\nif __name__ == '__main__':\r\n # 首先宣告list，未來要存新聞 標題&內文 關鍵詞用的\r\n keywords_of_title_en, keywords_of_text_en = list(), list()\r\n keywords_of_title_ch, keywords_of_text_ch = list(), list()\r\n\r\n # 讀取 English JSON檔案，並存進 keywords_of_title_en, keywords_of_text_en 兩個list\r\n read_json_en(keywords_of_title_en, keywords_of_text_en)\r\n print_data(keywords_of_title_en)\r\n print_data(keywords_of_text_en)\r\n\r\n # 讀取 中文 JSON檔案，並存進 keywords_of_title_ch, keywords_of_text_ch 兩個list\r\n read_json_ch(keywords_of_title_ch, keywords_of_text_ch)\r\n print_data(keywords_of_title_ch)\r\n print_data(keywords_of_text_ch)\r\n\r\n # 開始做 英文版 Frequent Pattern 分析\r\n frequent_pattern_of_title_en = frequent_pattern_analyze(keywords_of_title_en)\r\n print_data(frequent_pattern_of_title_en)\r\n frequent_pattern_of_text_en = frequent_pattern_analyze(keywords_of_text_en)\r\n print_data(frequent_pattern_of_text_en)\r\n\r\n # 開始做 中文版 Frequent Pattern 分析\r\n frequent_pattern_of_title_ch = frequent_pattern_analyze(keywords_of_title_ch)\r\n print_data(frequent_pattern_of_title_ch)\r\n frequent_pattern_of_text_ch = frequent_pattern_analyze(keywords_of_text_ch)\r\n print_data(frequent_pattern_of_text_ch)\r\n\r\n # 開始做 English版 字彙頻率 分析\r\n frequency_count_of_title_en = frequency_statistics(keywords_of_title_en)\r\n print_data(frequency_count_of_title_en)\r\n frequency_count_of_text_en = frequency_statistics(keywords_of_text_en)\r\n print_data(frequency_count_of_text_en)\r\n\r\n # 開始做 中文版 字彙頻率 分析\r\n frequency_count_of_title_ch = frequency_statistics(keywords_of_title_ch)\r\n print_data(frequency_count_of_title_ch)\r\n frequency_count_of_text_ch = frequency_statistics(keywords_of_text_ch)\r\n print_data(frequency_count_of_text_ch)\r\n\r\n # 開始輸出 字母頻率 統計，共4個txt檔案\r\n output_frequency_count(frequency_count_of_title_en, frequency_count_of_text_en, frequency_count_of_title_ch, frequency_count_of_text_ch)\r\n # 開始輸出 文字雲 ，會讀取上一步驟之4個txt檔案 (或者你自己準備其他txt檔案也可以啦...)\r\n output_word_cloud()","sub_path":"DataScience_Final/show_data.py","file_name":"show_data.py","file_ext":"py","file_size_in_byte":14112,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"3869032","text":"# -*- coding: utf-8 -*-\nimport os\nimport sys\n\n\ndef write_helpfile(obj):\n \"\"\"\n Function to write help(obj) to file in current working directory.\n \"\"\"\n filename = obj.__class__.__name__ + '_help.txt'\n try:\n with open(filename, 'w') as f:\n t = sys.stdout\n sys.stdout = f\n help(obj)\n sys.stdout = t\n if not os.path.isfile(filename):\n raise Exception('No file written')\n except Exception as e:\n print('Error in helpfilewriter: ', e)\n else:\n print(f'Class {obj.__class__.__name__} help file {filename} saved to working directory.')\n","sub_path":"OpenSeries/helpfilewriter.py","file_name":"helpfilewriter.py","file_ext":"py","file_size_in_byte":630,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"165899912","text":"#coding=utf-8\n\n\"\"\"\nCreated on 2020/11/18\n@author: lianxiujuan\n@desc: 标签-托盘\n\"\"\"\n\nimport pytest\nimport sys\nfrom DataApp.LabelmgData import *\nfrom src.public.common.Close_current_tab import Close_current_tab\nfrom src.public.common.Login import *\nfrom src.pageobjectAPP.pageLabel import *\nfrom src.public.common.Select_Item import *\nfrom src.public.common.Search_Item import *\nimport random,string\n\nlabeldata = ''.join(random.sample(string.ascii_letters + string.digits, 4))\n\n\nclass Test_palletlabel:\n def test_palletlabel_login(self):\n login_label()\n new_click(pallet)\n time.sleep(2)\n label_add(labeldata, labeldata, labeldata, labeldata)\n time.sleep(2)\n assert new_page_source(labeldata)\n\n # 新增 标签-托盘\n def test_add_palletlabel(self):\n log.info(\"开始执行用例%s\" % sys._getframe().f_code.co_name)\n label_add(palletcode, palletname, palletdesc, palletzpl)\n time.sleep(2)\n assert new_page_source(palletcode)\n\n # 搜索 标签-托盘\n def test_search_palletlabel(self):\n log.info(\"开始执行用例%s\" % sys._getframe().f_code.co_name)\n search_item(\"编码\", palletcode)\n time.sleep(2)\n ele = new_find_elements(searchresult)\n text = new_get_text_ele(ele[0])\n time.sleep(2)\n assert palletcode in text\n search_item(\"编码\", ' ')\n time.sleep(2)\n\n # 编辑 标签-托盘\n def test_edit_palletlabel(self):\n log.info(\"开始执行用例%s\" % sys._getframe().f_code.co_name)\n select_item(palletcode)\n label_edit(editname, editdesc, editzpl)\n time.sleep(2)\n assert new_page_source(editname)\n\n # 设置标准模板\n def test_setdefault_palletlabel(self):\n log.info(\"开始执行用例%s\" % sys._getframe().f_code.co_name)\n label_setdefault()\n time.sleep(2)\n select_item(labeldata)\n label_setdefault()\n time.sleep(2)\n\n # 删除 标签-托盘\n def test_delete_palletlabel(self):\n log.info(\"开始执行用例%s\" % sys._getframe().f_code.co_name)\n select_item(palletcode)\n label_delete()\n time.sleep(2)\n assert new_page_source(palletcode) == False\n sleep(1)\n Close_current_tab()\n\n\nif __name__ == '__main__':\n pytest.main(['-s','test_palletlabelcase.py'])\n","sub_path":"TestcaseApp/Label/test_palletlabel.py","file_name":"test_palletlabel.py","file_ext":"py","file_size_in_byte":2359,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"19755451","text":"import datetime\n\nimport pymysql\n\nconnection = pymysql.connect(user='root', db='data', unix_socket='/var/lib/mysql/mysql.sock')\n\nfor table in ['detail_user_reg']:\n total = 0\n day = datetime.date(2017, 1, 1)\n\n start_time = datetime.datetime.now()\n while day < datetime.date(2017, 12, 31):\n print(table, day)\n for batch_commit in range(1):\n for execute in range(100):\n with connection.cursor() as cursor:\n values_str = '(%s,\"%s\")' % (total, day.strftime('%Y-%m-%d'))\n total += 1\n for i in range(999):\n values_str += ',(%s,\"%s\")' % (total, day.strftime('%Y-%m-%d'))\n total += 1\n sql = \"INSERT INTO `\" + table + \"` (`uid`, `date`) VALUES \" + values_str\n cursor.execute(sql)\n connection.commit()\n day += datetime.timedelta(days=1)\n print('Insert complete! Time used: ', datetime.datetime.now() - start_time)\n","sub_path":"insert_huge_data.py","file_name":"insert_huge_data.py","file_ext":"py","file_size_in_byte":1016,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"171700375","text":"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n\nimport pronouncing as pr\nfrom collections import Counter\nimport re\nimport json\n\ndef nl_split(text, char):\n\n # split the given text into a list of its sentences, split by every newline\n sentences_nl_split = [sentence.split() for sentence in text.split(char)]\n\n # for each word in every sentence, remove any special characters from it and lowercase it\n words = [[re.sub('[^A-Za-z0-9]+', '', word).lower() for word in sentence] for sentence in sentences_nl_split]\n\n # create one single list of all the words separated by a space\n word_list = []\n for line in words:\n if len(line) == 0:\n continue\n else:\n for word in line:\n word_list.append(word)\n word_list.append(' ')\n\n return word_list\n\ndef sounds(words):\n\n # for each word in a sentence, find its arpabet translation, append them into a single list, assume first phone\n sound_list = []\n for word in words:\n if word == ' ':\n sound_list.append(word)\n continue\n else:\n sound = pr.phones_for_word(word)\n # if len of sound == 0, it was not recognized as a word in the cmu dictionary\n if len(sound) == 0:\n sound_list.append('*')\n else:\n sound_list.append(sound[0])\n return sound_list\n\ndef stresses(sounds):\n # for each sound of every word, find the syllable stress pattern\n stress_list = []\n for sound in sounds:\n if sound == ' ':\n stress_list.append(sound)\n elif sound == '*':\n stress_list.append(sound)\n else:\n stress_list.append(pr.stresses(sound))\n return stress_list\n\n\ndef word_count(words):\n c = dict(Counter(words))\n del c[\" \"]\n counts = [{\"word\":key, \"count\":value} for key, value in c.items()]\n return counts\n\ndef phones_count(sounds):\n # count individual sounds in it arpabet word\n individual_sounds = []\n for word in sounds:\n phone = str(word).split()\n for sound in phone:\n individual_sounds.append(sound)\n c = dict(Counter(individual_sounds))\n #convert counter object c into a Json object with a key, value\n sound_json = [{\"phone\":key, \"count\":value} for key, value in c.items()]\n\n\n return sound_json\n\ndef stress_csv(stresses):\n\n # create csv of stresses\n f = open(\"stresses.csv\", \"w\")\n for stress in stresses:\n if stress == ' ':\n f.write('\\n')\n else:\n f.write(stress + ' ')\n f.close()\n\ndef create_json(dict, filename):\n\n #create a json file of the phones counter\n f = open(filename, \"w\")\n json.dump(dict, f, sort_keys = True, indent = 4)\n f.close()\n\n\n\n","sub_path":"poetryparser.py","file_name":"poetryparser.py","file_ext":"py","file_size_in_byte":2748,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"55007732","text":"# Sacado de https://scipy.github.io/old-wiki/pages/Cookbook/Matplotlib/LaTeX_Examples.html\n\nimport matplotlib.pyplot as plt\nimport pylab\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport math\n#import numarray\nfrom pylab import arange,pi,sin,cos,sqrt,savefig\n\n\ngolden_mean = (math.sqrt(5)-1.0)/2.0 # Aesthetic ratio\nfig_width = 3+3/8 \t\t\t # width in inches\nfig_height = fig_width*golden_mean # height in inches\nfig_size = [fig_width,fig_height]\n\nparams = {'backend': 'ps',\n 'axes.titlesize': 8,\n 'axes.labelsize': 9,\n 'axes.linewidth': 0.5, \n 'axes.grid': True,\n 'axes.labelweight': 'normal', \n 'font.family': 'serif',\n 'font.size': 8.0,\n 'font.weight': 'normal',\n 'text.color': 'black',\n 'xtick.labelsize': 8,\n 'ytick.labelsize': 8,\n 'text.usetex': True,\n 'legend.fontsize': 8,\n 'figure.dpi': 300,\n 'figure.figsize': fig_size,\n 'savefig.dpi': 300,\n }\n\npylab.rcParams.update(params)\n\n### DATA\n\ndata = np.genfromtxt('out_distbc_225p_1.2m.txt', delimiter = ' ')\n\nvd = data[:,0]\ndistance = data[:,1]\nerror = data[:,2]\n\n### PLOT\n\npylab.figure(1)\npylab.clf()\n\n\nplt.plot(vd,distance,'wo',zorder=3) \nplt.plot(vd,distance,'k',lw=1.0,zorder=2) \nplt.errorbar(vd,distance,error,linestyle='-',fmt='.',color='w',ecolor='k',label='N=225',zorder=1) \n\n\n#pylab.xticks(np.arange(0,8,2))\n#pylab.yticks(np.arange(20,100,20))\npylab.xlabel('$v_d$~(m/s)')\npylab.ylabel('Distance~(m)')\npylab.legend()\n#pylab.ylim(20, 80)\n#pylab.xlim(0, 6)\nlgd=plt.legend() \nlgd.set_visible(False)\n \npylab.savefig('distancebc_225p_1.2m.eps', format='eps', dpi=300, bbox_inches='tight')\n\n\n\n'''\n\n####################OLD STUFF#########################\n\n#plt.legend(loc=4)\n#pylab.grid(True)\n\n#plt.scatter(gap1,te1,marker='o',s=50, color='w', zorder=0)\n#plt.axhline(y=31, xmin=0, xmax=8, linewidth=1, color = 'black',ls='dashed')\n\nplt.figure(1)\nplt.errorbar(gap1,te1,yerr1,linestyle='',marker='o',color='red',label='vd= 4 m/s ')\nplt.errorbar(gap2,te2,yerr2,linestyle='',marker='o',label='vd= 8 m/s')\nplt.errorbar(gap3,te3,yerr3,linestyle='',marker='o',color='green',label='N= 961')\n#plt.axhline(y=40, xmin=0, xmax=21, linewidth=2, color = 'green') #linea horizontal\n#plt.axvline(1.2,linewidth=2, color='k', linestyle='-')\nplt.legend(loc=4)\nplt.xlabel('Gap size (m)',fontsize=22)\nplt.ylabel('Evacuation Time (s)', fontsize=22)\n'''\n\n","sub_path":"bc2/d_medio/plot_dmed.py","file_name":"plot_dmed.py","file_ext":"py","file_size_in_byte":2468,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"157007732","text":"import numpy as np\nimport pandas as pd\nfrom scipy.spatial import distance\nimport scipy, argparse, os, sys, csv, io, time\n\nimport torch\nimport torch.nn as nn\nimport torch.functional as F\nimport torch.nn.functional as F\nimport torch.backends.cudnn as cudnn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\n\nclass log_manager_heracles():\n def __init__(self, args):\n self.G = np.zeros((2,))\n self.D = np.zeros((2,))\n self.total_tp = np.zeros((2,))\n self.total_len = np.zeros((2,))\n self.Dx = np.zeros((2,))\n self.Dx_score = np.zeros((2,))\n self.D_Gz1 = np.zeros((2,))\n self.D_Gz1_score = np.zeros((2,))\n self.D_Gz2 = np.zeros((2,))\n self.D_Gz2_score = np.zeros((2,))\n self.loss_Dx = np.zeros((2,))\n self.loss_D_Gz1 = np.zeros((2,))\n self.loss_D_Gz2 = np.zeros((2,))\n self.recall = np.zeros((2,))\n self.tr_total_loss_Dx = []\n self.tr_total_loss_D_Gz1 = []\n self.tr_total_loss_D_Gz2 = []\n self.te_total_loss_Dx = []\n self.te_total_loss_D_Gz1 = []\n self.te_total_loss_D_Gz2 = []\n self.tr_recall = []\n self.te_recall = []\n def accumlate_D(self, Dx, Dx_score, D_Gz1, D_Gz1_score, train=True):\n mode = 0 if train else 1\n self.D[mode] += 1\n self.Dx[mode] += Dx\n self.Dx_score[mode] += Dx_score\n self.D_Gz1[mode] += D_Gz1\n self.D_Gz1_score[mode] += D_Gz1_score\n self.loss_Dx[mode] += (2 * self.Dx[mode] + 3 * self.Dx_score[mode])\n self.loss_D_Gz1[mode] += (2 * self.D_Gz1[mode] + 3 * self.D_Gz1_score[mode])\n def accumlate_G(self, D_Gz2, D_Gz2_score, train=True):\n mode = 0 if train else 1\n self.G[mode] += 1\n self.D_Gz2[mode] += D_Gz2\n self.D_Gz2_score[mode] += D_Gz2_score\n self.loss_D_Gz2[mode] += (2 * self.D_Gz2[mode] + 3 * self.D_Gz2_score[mode])\n def accumlate_R(self, tp, total_l, train=True):\n mode = 0 if train else 1\n self.total_tp[mode] += tp\n self.total_len[mode] += total_l\n self.recall[mode] = self.total_tp[mode] / self.total_len[mode] *100\n def display(self, train=True):\n mode = 0 if train else 1\n return (self.Dx[mode]/self.D[mode], self.D_Gz1[mode]/self.D[mode],\n self.D_Gz2[mode]/self.G[mode], self.recall[mode])\n def record_log(self):\n self.tr_total_loss_Dx.append(self.Dx[0]/self.D[0])\n self.tr_total_loss_D_Gz1.append(self.D_Gz1[0]/self.D[0])\n self.tr_total_loss_D_Gz2.append(self.D_Gz2[0]/self.G[0])\n self.te_total_loss_Dx.append(self.Dx[1]/self.D[1])\n self.te_total_loss_D_Gz1.append(self.D_Gz1[1]/self.D[1])\n self.te_total_loss_D_Gz2.append(self.D_Gz2[1]/self.G[1])\n self.tr_recall.append(self.recall[0])\n self.te_recall.append(self.recall[1])\n np.savez(os.path.join('log', 'log_{}.npz'.format('heracles')),\n train_Dx= self.tr_total_loss_Dx,\n train_D_Gz1 = self.tr_total_loss_D_Gz1,\n train_D_Gz2 = self.tr_total_loss_D_Gz2,\n train_recall = self.tr_recall,\n test_Dx = self.te_total_loss_Dx,\n test_D_Gz1 = self.te_total_loss_D_Gz1,\n test_D_Gz2 = self.te_total_loss_D_Gz2,\n test_recall = self.te_recall)\n self.clean_record()\n def clean_record(self):\n self.G = np.zeros((2,))\n self.D = np.zeros((2,))\n self.total_tp = np.zeros((2,))\n self.total_len = np.zeros((2,))\n self.Dx = np.zeros((2,))\n self.Dx_score = np.zeros((2,))\n self.D_Gz1 = np.zeros((2,))\n self.D_Gz1_score = np.zeros((2,))\n self.D_Gz2 = np.zeros((2,))\n self.D_Gz2_score = np.zeros((2,))\n self.loss_Dx = np.zeros((2,))\n self.loss_D_Gz1 = np.zeros((2,))\n self.loss_D_Gz2 = np.zeros((2,))\n self.recall = np.zeros((2,))\n def plot_log(self):\n import matplotlib\n import matplotlib.pyplot as plt\n matplotlib.use('Agg')\n plt.figure(figsize=(16,12))\n plt.clf()\n plt.subplot(2, 1, 1)\n l1 = np.array(self.tr_recall).flatten()\n l2 = np.array(self.te_recall).flatten()\n plt.xlabel('Epochs')\n plt.plot(l1, label='train')\n plt.plot(l2, label='test')\n plt.legend(loc='lower right')\n plt.title('{}_recall'.format('heracles'))\n plt.subplot(2, 3, 4)\n l1 = np.array(self.tr_total_loss_Dx).flatten()\n l2 = np.array(self.te_total_loss_Dx).flatten()\n plt.xlabel('Epochs')\n plt.plot(l1, label='train')\n plt.plot(l2, label='test')\n plt.legend(loc='upper right')\n plt.title('{}_D(x)'.format('heracles'))\n plt.subplot(2, 3, 5)\n l1 = np.array(self.tr_total_loss_D_Gz1).flatten()\n l2 = np.array(self.te_total_loss_D_Gz1).flatten()\n plt.xlabel('Epochs')\n plt.plot(l1, label='train')\n plt.plot(l2, label='test')\n plt.legend(loc='upper right')\n plt.title('{}_D(G(z1))'.format('heracles'))\n plt.subplot(2, 3, 6)\n l1 = np.array(self.tr_total_loss_D_Gz2).flatten()\n l2 = np.array(self.te_total_loss_D_Gz2).flatten()\n plt.xlabel('Epochs')\n plt.plot(l1, label='train')\n plt.plot(l2, label='test')\n plt.legend(loc='upper right')\n plt.title('{}_D(G(z2))'.format('heracles'))\n plt.tight_layout()\n plt.savefig(os.path.join('plot', 'heracles'))\n plt.close()\n\nclass log_manager():\n def __init__(self, args):\n self.model = args.mt\n self.end2end = \"End-to-End\" if args.end2end == \"True\" else \"Non-End-to-End\"\n self.count = np.zeros((2,))\n self.total_loss = np.zeros((2,))\n self.total_tp = np.zeros((2,))\n self.total_len = np.zeros((2,))\n self.recall = np.zeros((2,))\n self.loss = np.zeros((2,))\n\n self.tr_loss = []\n self.te_loss = []\n self.tr_recall = []\n self.te_recall = []\n def accumulate(self, loss, tp, total, train=True):\n mode = 0 if train else 1\n self.count[mode] += 1\n self.total_loss[mode] += loss\n self.total_tp[mode] += tp\n self.total_len[mode] += total\n self.recall[mode] = self.total_tp[mode] / self.total_len[mode] *100\n self.loss[mode] = self.total_loss[mode]/ self.count[mode]\n def record_log(self):\n self.tr_loss.append(self.loss[0])\n self.tr_recall.append(self.recall[0])\n self.te_loss.append(self.loss[1])\n self.te_recall.append(self.recall[1])\n np.savez(os.path.join('log', 'log_{}_{}.npz'.format(self.model, self.end2end)),\n train_loss= self.tr_loss,\n train_recall = self.tr_recall,\n test_loss = self.te_loss,\n test_recall = self.te_recall)\n self.clean_record()\n def clean_record(self):\n self.count = np.zeros((2,))\n self.total_loss = np.zeros((2,))\n self.total_tp = np.zeros((2,))\n self.total_len = np.zeros((2,))\n self.recall = np.zeros((2,))\n self.loss = np.zeros((2,))\n def plot_log(self):\n import matplotlib\n import matplotlib.pyplot as plt\n matplotlib.use('Agg')\n plt.figure(figsize=(16,12))\n plt.clf()\n plt.subplot(2, 1, 1)\n l1 = np.array(self.tr_loss).flatten()\n l2 = np.array(self.te_loss).flatten()\n plt.xlabel('Epochs')\n plt.plot(l1, label='train')\n plt.plot(l2, label='test')\n plt.legend(loc='upper right')\n plt.title('{}_{}_loss'.format(self.end2end, self.model))\n plt.subplot(2,1,2)\n l1 = np.array(self.tr_recall).flatten()\n l2 = np.array(self.te_recall).flatten()\n plt.xlabel('Epochs')\n plt.plot(l1, label='train')\n plt.plot(l2, label='test')\n plt.legend(loc='lower right')\n plt.title('{}_{}_recall'.format(self.end2end, self.model))\n plt.tight_layout()\n plt.savefig(os.path.join('plot', self.end2end+'_'+self.model))\n plt.close()\n\ndef cos_cdist(y_pred, vec_matrix):\n return scipy.spatial.distance.cdist(y_pred, vec_matrix, 'euclidean')\n\ndef top_k(y_pred, vec_matrix, k):\n tmp = cos_cdist(y_pred, vec_matrix)\n total_top_k = np.argsort(tmp)[:, :k]\n return total_top_k\n\ndef f1_score(top_k_result, hashtag_y, idx2word):\n # string compare to string\n gt_hashtag, to_word = [], []\n tp, total_l = 0, 0\n for ele in hashtag_y:\n ele = ele.strip().split()\n gt_hashtag.append(ele)\n for row in range(len(top_k_result)):\n tmp = []\n for ele in top_k_result[row]:\n tmp += [idx2word[ele]]\n to_word.append(tmp)\n for row_idx in range(len(to_word)):\n tp += len(set(to_word[row_idx])&set(gt_hashtag[row_idx]))\n total_l += len(gt_hashtag[row_idx])\n return tp, total_l\n\n\nif __name__ == \"__main__\":\n a = np.array([[1,0,0], [0,1,0]])\n b = np.array([[1,0,0],[0,1,1]])\n c = np.array([[0,1,0]])\n print(a, b, c)\n print(cos_cdist(a,b))\n print(cos_cdist(a,c))\n print(np.argsort(cos_cdist(a,b)))\n print(\"this is evalution pyfile\")\n","sub_path":"hades_model/utils/evalution.py","file_name":"evalution.py","file_ext":"py","file_size_in_byte":9179,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"625722639","text":"#!/usr/bin/python\n# This file is part of Ansible\n#\n# Ansible is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# Ansible is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with Ansible. If not, see .\n\nANSIBLE_METADATA = {'metadata_version': '1.1',\n 'status': ['preview'],\n 'supported_by': 'community'}\n\n\nDOCUMENTATION = \"\"\"\n---\nmodule: elasticache_parameter_group\nshort_description: Manage cache security groups in Amazon Elasticache.\ndescription:\n - Manage cache security groups in Amazon Elasticache.\n - Returns information about the specified cache cluster.\nversion_added: \"2.3\"\nauthor: \"Sloane Hertel (@s-hertel)\"\nextends_documentation_fragment:\n - aws\n - ec2\nrequirements: [ boto3, botocore ]\noptions:\n group_family:\n description:\n - The name of the cache parameter group family that the cache parameter group can be used with.\n Required when creating a cache parameter group.\n choices: ['memcached1.4', 'memcached1.5', 'redis2.6', 'redis2.8', 'redis3.2', 'redis4.0', 'redis5.0']\n name:\n description:\n - A user-specified name for the cache parameter group.\n required: yes\n description:\n description:\n - A user-specified description for the cache parameter group.\n state:\n description:\n - Idempotent actions that will create/modify, destroy, or reset a cache parameter group as needed.\n choices: ['present', 'absent', 'reset']\n required: true\n values:\n description:\n - A user-specified dictionary of parameters to reset or modify for the cache parameter group.\n\"\"\"\n\nEXAMPLES = \"\"\"\n# Note: None of these examples set aws_access_key, aws_secret_key, or region.\n# It is assumed that their matching environment variables are set.\n---\n- hosts: localhost\n connection: local\n tasks:\n - name: 'Create a test parameter group'\n elasticache_parameter_group:\n name: 'test-param-group'\n group_family: 'redis3.2'\n description: 'This is a cache parameter group'\n state: 'present'\n - name: 'Modify a test parameter group'\n elasticache_parameter_group:\n name: 'test-param-group'\n values:\n activerehashing: yes\n client-output-buffer-limit-normal-hard-limit: 4\n state: 'present'\n - name: 'Reset all modifiable parameters for the test parameter group'\n elasticache_parameter_group:\n name: 'test-param-group'\n state: reset\n - name: 'Delete a test parameter group'\n elasticache_parameter_group:\n name: 'test-param-group'\n state: 'absent'\n\"\"\"\n\nRETURN = \"\"\"\nelasticache:\n description: cache parameter group information and response metadata\n returned: always\n type: dict\n sample:\n cache_parameter_group:\n cache_parameter_group_family: redis3.2\n cache_parameter_group_name: test-please-delete\n description: \"initial description\"\n response_metadata:\n http_headers:\n content-length: \"562\"\n content-type: text/xml\n date: \"Mon, 06 Feb 2017 22:14:08 GMT\"\n x-amzn-requestid: 947291f9-ecb9-11e6-85bd-3baa4eca2cc1\n http_status_code: 200\n request_id: 947291f9-ecb9-11e6-85bd-3baa4eca2cc1\n retry_attempts: 0\nchanged:\n description: if the cache parameter group has changed\n returned: always\n type: bool\n sample:\n changed: true\n\"\"\"\n\n# import module snippets\nfrom ansible.module_utils.basic import AnsibleModule\nfrom ansible.module_utils.ec2 import boto3_conn, get_aws_connection_info, ec2_argument_spec, camel_dict_to_snake_dict\nfrom ansible.module_utils._text import to_text\nfrom ansible.module_utils.six import string_types\nimport traceback\n\ntry:\n import boto3\n import botocore\n HAS_BOTO3 = True\nexcept ImportError:\n HAS_BOTO3 = False\n\n\ndef create(module, conn, name, group_family, description):\n \"\"\" Create ElastiCache parameter group. \"\"\"\n try:\n response = conn.create_cache_parameter_group(CacheParameterGroupName=name, CacheParameterGroupFamily=group_family, Description=description)\n changed = True\n except botocore.exceptions.ClientError as e:\n module.fail_json(msg=\"Unable to create cache parameter group.\", exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))\n return response, changed\n\n\ndef delete(module, conn, name):\n \"\"\" Delete ElastiCache parameter group. \"\"\"\n try:\n conn.delete_cache_parameter_group(CacheParameterGroupName=name)\n response = {}\n changed = True\n except botocore.exceptions.ClientError as e:\n module.fail_json(msg=\"Unable to delete cache parameter group.\", exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))\n return response, changed\n\n\ndef make_current_modifiable_param_dict(module, conn, name):\n \"\"\" Gets the current state of the cache parameter group and creates a dict with the format: {ParameterName: [Allowed_Values, DataType, ParameterValue]}\"\"\"\n current_info = get_info(conn, name)\n if current_info is False:\n module.fail_json(msg=\"Could not connect to the cache parameter group %s.\" % name)\n\n parameters = current_info[\"Parameters\"]\n modifiable_params = {}\n\n for param in parameters:\n if param[\"IsModifiable\"]:\n modifiable_params[param[\"ParameterName\"]] = [param.get(\"AllowedValues\")]\n modifiable_params[param[\"ParameterName\"]].append(param[\"DataType\"])\n modifiable_params[param[\"ParameterName\"]].append(param.get(\"ParameterValue\"))\n return modifiable_params\n\n\ndef check_valid_modification(module, values, modifiable_params):\n \"\"\" Check if the parameters and values in values are valid. \"\"\"\n changed_with_update = False\n\n for parameter in values:\n new_value = values[parameter]\n\n # check valid modifiable parameters\n if parameter not in modifiable_params:\n module.fail_json(msg=\"%s is not a modifiable parameter. Valid parameters to modify are: %s.\" % (parameter, modifiable_params.keys()))\n\n # check allowed datatype for modified parameters\n str_to_type = {\"integer\": int, \"string\": string_types}\n expected_type = str_to_type[modifiable_params[parameter][1]]\n if not isinstance(new_value, expected_type):\n if expected_type == str:\n if isinstance(new_value, bool):\n values[parameter] = \"yes\" if new_value else \"no\"\n else:\n values[parameter] = to_text(new_value)\n elif expected_type == int:\n if isinstance(new_value, bool):\n values[parameter] = 1 if new_value else 0\n else:\n module.fail_json(msg=\"%s (type %s) is not an allowed value for the parameter %s. Expected a type %s.\" %\n (new_value, type(new_value), parameter, modifiable_params[parameter][1]))\n else:\n module.fail_json(msg=\"%s (type %s) is not an allowed value for the parameter %s. Expected a type %s.\" %\n (new_value, type(new_value), parameter, modifiable_params[parameter][1]))\n\n # check allowed values for modifiable parameters\n choices = modifiable_params[parameter][0]\n if choices:\n if not (to_text(new_value) in choices or isinstance(new_value, int)):\n module.fail_json(msg=\"%s is not an allowed value for the parameter %s. Valid parameters are: %s.\" %\n (new_value, parameter, choices))\n\n # check if a new value is different from current value\n if to_text(values[parameter]) != modifiable_params[parameter][2]:\n changed_with_update = True\n\n return changed_with_update, values\n\n\ndef check_changed_parameter_values(values, old_parameters, new_parameters):\n \"\"\" Checking if the new values are different than the old values. \"\"\"\n changed_with_update = False\n\n # if the user specified parameters to reset, only check those for change\n if values:\n for parameter in values:\n if old_parameters[parameter] != new_parameters[parameter]:\n changed_with_update = True\n break\n # otherwise check all to find a change\n else:\n for parameter in old_parameters:\n if old_parameters[parameter] != new_parameters[parameter]:\n changed_with_update = True\n break\n\n return changed_with_update\n\n\ndef modify(module, conn, name, values):\n \"\"\" Modify ElastiCache parameter group to reflect the new information if it differs from the current. \"\"\"\n # compares current group parameters with the parameters we've specified to to a value to see if this will change the group\n format_parameters = []\n for key in values:\n value = to_text(values[key])\n format_parameters.append({'ParameterName': key, 'ParameterValue': value})\n try:\n response = conn.modify_cache_parameter_group(CacheParameterGroupName=name, ParameterNameValues=format_parameters)\n except botocore.exceptions.ClientError as e:\n module.fail_json(msg=\"Unable to modify cache parameter group.\", exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))\n return response\n\n\ndef reset(module, conn, name, values):\n \"\"\" Reset ElastiCache parameter group if the current information is different from the new information. \"\"\"\n # used to compare with the reset parameters' dict to see if there have been changes\n old_parameters_dict = make_current_modifiable_param_dict(module, conn, name)\n\n format_parameters = []\n\n # determine whether to reset all or specific parameters\n if values:\n all_parameters = False\n format_parameters = []\n for key in values:\n value = to_text(values[key])\n format_parameters.append({'ParameterName': key, 'ParameterValue': value})\n else:\n all_parameters = True\n\n try:\n response = conn.reset_cache_parameter_group(CacheParameterGroupName=name, ParameterNameValues=format_parameters, ResetAllParameters=all_parameters)\n except botocore.exceptions.ClientError as e:\n module.fail_json(msg=\"Unable to reset cache parameter group.\", exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))\n\n # determine changed\n new_parameters_dict = make_current_modifiable_param_dict(module, conn, name)\n changed = check_changed_parameter_values(values, old_parameters_dict, new_parameters_dict)\n\n return response, changed\n\n\ndef get_info(conn, name):\n \"\"\" Gets info about the ElastiCache parameter group. Returns false if it doesn't exist or we don't have access. \"\"\"\n try:\n data = conn.describe_cache_parameters(CacheParameterGroupName=name)\n return data\n except botocore.exceptions.ClientError as e:\n return False\n\n\ndef main():\n argument_spec = ec2_argument_spec()\n argument_spec.update(\n dict(\n group_family=dict(type='str', choices=['memcached1.4', 'memcached1.5', 'redis2.6', 'redis2.8', 'redis3.2', 'redis4.0', 'redis5.0']),\n name=dict(required=True, type='str'),\n description=dict(default='', type='str'),\n state=dict(required=True),\n values=dict(type='dict'),\n )\n )\n module = AnsibleModule(argument_spec=argument_spec)\n\n if not HAS_BOTO3:\n module.fail_json(msg='boto required for this module')\n\n parameter_group_family = module.params.get('group_family')\n parameter_group_name = module.params.get('name')\n group_description = module.params.get('description')\n state = module.params.get('state')\n values = module.params.get('values')\n\n # Retrieve any AWS settings from the environment.\n region, ec2_url, aws_connect_kwargs = get_aws_connection_info(module, boto3=True)\n if not region:\n module.fail_json(msg=\"Either region or AWS_REGION or EC2_REGION environment variable or boto config aws_region or ec2_region must be set.\")\n\n connection = boto3_conn(module, conn_type='client',\n resource='elasticache', region=region,\n endpoint=ec2_url, **aws_connect_kwargs)\n\n exists = get_info(connection, parameter_group_name)\n\n # check that the needed requirements are available\n if state == 'present' and not (exists or parameter_group_family):\n module.fail_json(msg=\"Creating a group requires a family group.\")\n elif state == 'reset' and not exists:\n module.fail_json(msg=\"No group %s to reset. Please create the group before using the state 'reset'.\" % parameter_group_name)\n\n # Taking action\n changed = False\n if state == 'present':\n if exists:\n # confirm that the group exists without any actions\n if not values:\n response = exists\n changed = False\n # modify existing group\n else:\n modifiable_params = make_current_modifiable_param_dict(module, connection, parameter_group_name)\n changed, values = check_valid_modification(module, values, modifiable_params)\n response = modify(module, connection, parameter_group_name, values)\n # create group\n else:\n response, changed = create(module, connection, parameter_group_name, parameter_group_family, group_description)\n if values:\n modifiable_params = make_current_modifiable_param_dict(module, connection, parameter_group_name)\n changed, values = check_valid_modification(module, values, modifiable_params)\n response = modify(module, connection, parameter_group_name, values)\n elif state == 'absent':\n if exists:\n # delete group\n response, changed = delete(module, connection, parameter_group_name)\n else:\n response = {}\n changed = False\n elif state == 'reset':\n response, changed = reset(module, connection, parameter_group_name, values)\n\n facts_result = dict(changed=changed, elasticache=camel_dict_to_snake_dict(response))\n\n module.exit_json(**facts_result)\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"env/lib/python3.9/site-packages/ansible/modules/cloud/amazon/elasticache_parameter_group.py","file_name":"elasticache_parameter_group.py","file_ext":"py","file_size_in_byte":14590,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"239034193","text":"# Copyright 2018 Spotify AB. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n\"\"\"Utilities and Mocked Data for tests\"\"\"\n\nfrom comet_core.app import EventContainer\n\n\ndef get_all_test_messages(parsed=False):\n \"\"\"Get all test messages and their filenames as an iterator.\n\n Args:\n parsed (bool): returns Event objects if true otherwise strings\n Yields:\n EventContainer: some test event\n \"\"\"\n event = EventContainer('test', {})\n event.set_owner('test@acme.org')\n event.set_fingerprint('test')\n return [event]\n","sub_path":"tests/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":1060,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"223931895","text":"import sys\nimport logging\nimport sqlite3\nimport hashlib\nimport csv\nfrom pathlib import Path\n\nlogger = logging.getLogger(\"sqlitedb\")\n\n\nclass LocalDB():\n def __init__(self, dbLoc=None):\n \"\"\"init the sqlite database class\n\n Args:\n dbLoc ([string], optional): database filename. Defaults to :memory:\n \"\"\"\n self.conn = None\n if dbLoc == None:\n dbLoc = \":memory:\"\n\n logger.debug(f\"attempt open db {dbLoc}\")\n try:\n self.conn = sqlite3.connect(\n dbLoc, detect_types=sqlite3.PARSE_DECLTYPES | sqlite3.PARSE_COLNAMES)\n except sqlite3.Error as errID:\n logger.critical(\n f\"Database connection failure. \", exc_info=True)\n sys.exit(1)\n except Exception as err:\n logger.critical(f\"Error: {err}\", exc_info=True)\n sys.exit(1)\n\n logger.debug(f\"successful connection to {dbLoc}\")\n\n c = self.conn.cursor()\n c.execute(\"PRAGMA foreign_keys = ON\")\n c.execute(\"PRAGMA database_list;\")\n xtmp = c.fetchall()\n logger.debug(f\"PRAGMA database_list: {xtmp}\")\n\n def _exeScriptFile(self, scriptFileName):\n \"\"\"Executes a Script file. (internal use only)\n\n Args:\n scriptFileName (string): SQL script file to run\n \"\"\"\n\n logger.debug(f\"loading script: {scriptFileName} to memory\")\n scriptFile = open(scriptFileName, 'r')\n script = scriptFile.read()\n scriptFile.close()\n logger.debug(f\"executing script: {scriptFileName}\")\n try:\n c = self.conn.cursor()\n c.executescript(script)\n except Exception as e:\n logger.critical(\n f\"Unexpected Error running script: {scriptFileName}. Exception {e}\", exc_info=True)\n sys.exit(1)\n\n self.conn.commit()\n logger.debug(f\"script: {scriptFileName} commited successfully\")\n\n def _exeSQLInsert(self, sql, theVals):\n \"\"\"Submit insert type sql. (internal use only)\n\n Args:\n sql (string): The insert Sql, this will include INSERT\n theVals : The value parms passed into the sql.\n theVals type depends on the sql, i.e. list or dict.\n\n Returns:\n [list]: [int,string]\n Samples:\n [0, \"Commit successful\"]\n [2, f\"sqlite integrity error: {e.args[0]}\"]\n Unexpected error will exit app\n \"\"\"\n logger.debug(f\"Sql: {sql}\")\n logger.debug(f\"Values: {theVals}\")\n try:\n c = self.conn.cursor()\n c.execute(sql, theVals)\n self.conn.commit()\n\n except sqlite3.IntegrityError as e:\n logger.warning(f\"sqlite integrity error: {e.args[0]}\")\n return [2, f\"sqlite integrity error: {e.args[0]}\"]\n except Exception as e:\n logger.critical(\n f\"Unexpected error executing sql: {sql}. Values are {theVals} Exception: {e}\", exc_info=True)\n sys.exit(1)\n\n logger.debug(\"successful commit of sql\")\n return [0, \"Commit successful\"]\n\n def initDB(self, scriptPath):\n \"\"\"Create tables, views, indexes for the database\n\n ASSUMPTION database is new, and tables do not exist.\n Args:\n scriptPath (string): Path to script(s). Defaults to None.\n \"\"\"\n logger.info(f\"scriptPath={scriptPath}\")\n gtScripts = Path(scriptPath)\n logger.info(f\"Executing scripts to create database\")\n\n scriptFile = gtScripts / \"createtables.sql\"\n logger.debug(f\"Executing {scriptFile}\")\n self._exeScriptFile(scriptFileName=f'{scriptFile}')\n\n def addLibKeyRec(self, srcRec):\n \"\"\"Add a record to the Library Key table\n\n Args:\n srcRec ([class srcRec]): Source record to add\n\n Returns:\n [int]: The primary key id for the added source record\n \"\"\"\n sql = \"INSERT INTO t_libkeys (server, library, filePath, skey, uKey) VALUES (:server, :libName, :uFilePath, :sKey, :uKey)\"\n theVals = {'server': srcRec.svrName,\n 'libName': srcRec.libName, 'uFilePath': srcRec.uFilePath, 'sKey': srcRec.sKey, 'uKey': srcRec.uKey}\n r = self._exeSQLInsert(sql, theVals)\n\n # Getting the rowID for the record just added.\n try:\n c = self.conn.cursor()\n c.execute(\"select last_insert_rowid()\")\n row = c.fetchone()\n except Exception as e:\n logger.critical(\n f\"Unexpected error executing sql: {sql}. Exception: {e}\", exc_info=True)\n sys.exit(1)\n\n return row[0]\n\n def addLibValRec(self, keyRec):\n sql = \"INSERT INTO t_libvals (srcKey_id, s_value) VALUES (:srcKey, :sValue)\"\n theVals = {'srcKey': keyRec.srckey_id, 'sValue': keyRec.sValue}\n logger.debug(f\"adding movie library value record\")\n return self._exeSQLInsert(sql, theVals)\n\n def exportLibDiff(self, oFile):\n \"\"\"Export the Library diff query to a csv file\n\n Args:\n oFile (string): File name for the csv file\n \"\"\"\n logger.debug(f\"oFile={oFile}\")\n\n sql = \"SELECT library, filePath, skey, server1_val, server2_val, isDiff FROM v_lib_DiffResults\"\n\n try:\n logger.debug(f\"executing sql: {sql}\")\n localc = self.conn.cursor()\n localc.execute(sql)\n\n except Exception as e:\n logger.critical(\n f\"Unexpected error executing sql: {sql}. Values are {theVals} Exception: {e}\", exc_info=True)\n sys.exit(1)\n\n logger.debug(f\"Writing sql results to: {oFile}\")\n with open(oFile, \"w\", newline='') as csv_file:\n csv_writer = csv.writer(csv_file, dialect='excel')\n csv_writer.writerow([i[0] for i in localc.description])\n csv_writer.writerows(localc)\n\n def exportColDiff(self, oFile):\n logger.debug(f\"oFile={oFile}\")\n sql = \"select libname as library, colname, skey, server1_val, server2_val, isdiff FROM v_col_DiffResults\"\n try:\n logger.debug(f\"executing sql: {sql}\")\n localc = self.conn.cursor()\n localc.execute(sql)\n except Exception as e:\n logger.critical(\n f\"Unexpected error executing sql: {sql}. Values are {theVals} Exception: {e}\", exc_info=True)\n sys.exit(1)\n\n logger.debug(f\"Writing sql results to: {oFile}\")\n with open(oFile, \"w\", newline='') as csv_file:\n csv_writer = csv.writer(csv_file, dialect='excel')\n csv_writer.writerow([i[0] for i in localc.description])\n csv_writer.writerows(localc)\n\n def addColKeyRec(self, keyRec):\n \"\"\"Add a record to the Collection keys table\n\n Args:\n keyRec (Class ColKey): Collection Key's object with values to write\n\n Returns:\n [int]: The primary key id for the added key record\n \"\"\"\n pass\n sql = \"INSERT INTO t_colkeys (svrName, libName, colName, sKey, uKey) VALUES (:svrName, :libName, :colName, :sKey, :uKey)\"\n theVals = {'svrName': keyRec.svrName, 'libName': keyRec.libName,\n 'colName': keyRec.colName, \"sKey\": keyRec.sKey, \"uKey\": keyRec.uKey}\n\n logger.debug(f\"adding collection key record : {theVals}, \")\n r = self._exeSQLInsert(sql, theVals)\n # Getting the rowID for the record just added.\n try:\n xcursor = self.conn.cursor()\n xcursor.execute(\"select last_insert_rowid()\")\n row = xcursor.fetchone()\n except Exception as e:\n logger.critical(\n f\"Unexpected error executing sql: {sql}. Exception: {e}\", exc_info=True)\n sys.exit(1)\n\n return row[0]\n\n def addColValRec(self, valRec):\n sql = \"INSERT INTO t_colvals (colkey_id, s_value) VALUES (:ColKey, :sValue)\"\n theVals = {'ColKey': valRec.srckey_id, 'sValue': valRec.sValue}\n\n logger.debug(f\"adding collection value record {valRec.srckey_id}\")\n\n return self._exeSQLInsert(sql, theVals)\n\n\nclass LibSrcKey():\n def __init__(self):\n self.svrName = \"\"\n self.libName = \"\"\n self.uFilePath = \"\"\n self.sKey = \"\"\n\n @property\n def uKey(self):\n # Returns unique key created by\n # returning md5 hexdigest of the combined:\n # - Library Name (libname)\n # - Universal File Path (uFilePath)\n # - Key (sKey)\n str2hash = self.libName + self.uFilePath + self.sKey\n return hashlib.md5(str2hash.encode()).hexdigest()\n\n\nclass LibKeyVal():\n def __init__(self):\n self.srckey_id = \"\"\n self.sValue = \"\"\n\n def __repr__(self):\n return f\"srckey_id={self.srckey_id}, svalue={self.sValue}\"\n\n\nclass ColKey():\n def __init__(self):\n self.svrName = \"\"\n self.libName = \"\"\n self.colName = \"\"\n self.sKey = \"\"\n\n @property\n def uKey(self):\n # Returns unique key created by\n # returning md5 hexdigest of the combined:\n # - Library Name (libname)\n # - Collection Name (colName)\n # - Key (sKey)\n str2hash = self.libName + self.colName + self.sKey\n return hashlib.md5(str2hash.encode()).hexdigest()\n\n\nclass ColKeyVal():\n def __init__(self):\n self.srckey_id = \"\"\n self.sValue = \"\"\n\n def __repr__(self):\n return f\"srckey_id={self.srckey_id}, svalue={self.sValue}\"\n","sub_path":"plexinfo/sqlitedb.py","file_name":"sqlitedb.py","file_ext":"py","file_size_in_byte":9488,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"291973120","text":"# -*- coding: utf-8 -*-\n# This file is a personal adaptation the SPORCO package. Details of the\n# copyright for the toolbox and user license can be found in the 'LICENSE.txt'\n# file distributed with the package.\n\n\"\"\"Classes for ADMM algorithm for the Convolutional BPDN problem specific to the\"\n Object project. Adaptation from SPORCO.\"\"\"\n\nfrom __future__ import division\nfrom __future__ import absolute_import\nfrom __future__ import print_function\nfrom builtins import range\nfrom builtins import object\n\nimport copy\nfrom types import MethodType\nimport collections\n\nimport numpy as np\nimport scipy\nfrom scipy import linalg\nimport tensorly as tl\n\nfrom sporco import cdict\nfrom sporco import util\nfrom sporco import common\nfrom sporco.admm import admm\nfrom sporco.admm import cbpdn\n\nimport sporco.cnvrep as cr\nimport sporco.linalg as sl\nimport sporco.prox as sp\nfrom sporco.util import u\n\n\n__author__ = \"\"\"David Reixach \"\"\"\n\nclass IterStatsConfig(object):\n \"\"\"Configuration object for Alternated Kruscal ConvBPDN learning algorithm\n iteration statistics.\n\n Adaptation from Sporco ditclearn::IterStatsConfig\n\n \"\"\"\n\n fwiter = 4\n \"\"\"Field width for iteration count display column\"\"\"\n fpothr = 2\n \"\"\"Field precision for other display columns\"\"\"\n\n\n def __init__(self, isfld, isxmap, evlmap, hdrtxt, hdrmap,\n fmtmap=None):\n \"\"\"\n Parameters\n ----------\n isfld : list\n List of field names for iteration statistics namedtuple\n isxmap : dict\n Dictionary mapping iteration statistics namedtuple field names\n to field names in corresponding X step object iteration\n statistics namedtuple\n evlmap : dict\n Dictionary mapping iteration statistics namedtuple field names\n to labels in the dict returned by :meth:`DictLearn.evaluate`\n hdrtxt : list\n List of column header titles for verbose iteration statistics\n display\n hdrmap : dict\n Dictionary mapping column header titles to IterationStats entries\n fmtmap : dict, optional (default None)\n A dict providing a mapping from field header strings to print\n format strings, providing a mechanism for fields with print\n formats that depart from the standard format\n \"\"\"\n\n self.IterationStats = collections.namedtuple('IterationStats', isfld)\n self.isxmap = isxmap\n self.evlmap = evlmap\n self.hdrtxt = hdrtxt\n self.hdrmap = hdrmap\n\n # Call utility function to construct status display formatting\n self.hdrstr, self.fmtstr, self.nsep = common.solve_status_str(\n hdrtxt, fmtmap=fmtmap, fwdth0=type(self).fwiter,\n fprec=type(self).fpothr)\n\n\n\n def iterstats(self, j, t, isx, evl):\n \"\"\"Construct IterationStats namedtuple from X step list\n IterationStats namedtuples.\n\n Parameters\n ----------\n j : int\n Iteration number\n t : float\n Iteration time\n isx : namedtuple\n IterationStats namedtuple from X step object\n evl : dict\n Dict associating result labels with values computed by\n :meth:`DictLearn.evaluate`\n \"\"\"\n\n vlst = []\n # Iterate over the fields of the IterationStats namedtuple\n # to be populated with values. If a field name occurs as a\n # key in the isxmap dictionary, use the corresponding key\n # value as a field name in the isx namedtuple for the X\n # step object and append the value of that field as the\n # next value in the IterationStats namedtuple under\n # construction. There are also two reserved field\n # names, 'Iter' and 'Time', referring respectively to the\n # iteration number and run time of the dictionary learning\n # algorithm.\n for fnm in self.IterationStats._fields:\n if fnm in self.isxmap:\n vlst.append(getattr(isx, self.isxmap[fnm]))\n elif fnm in self.evlmap:\n vlst.append(evl[fnm])\n elif fnm == 'Iter':\n vlst.append(j)\n elif fnm == 'Time':\n vlst.append(t)\n else:\n vlst.append(None)\n\n return self.IterationStats._make(vlst)\n\n\n\n def printheader(self):\n \"\"\"Print status display header and separator strings.\"\"\"\n\n print(self.hdrstr)\n self.printseparator()\n\n\n\n def printseparator(self):\n \"Print status display separator string.\"\"\"\n\n print(\"-\" * self.nsep)\n\n\n\n def printiterstats(self, itst):\n \"\"\"Print iteration statistics.\n\n Parameters\n ----------\n itst : namedtuple\n IterationStats namedtuple as returned by :meth:`iterstats`\n \"\"\"\n\n itdsp = tuple([getattr(itst, self.hdrmap[col]) for col in self.hdrtxt])\n print(self.fmtstr % itdsp)\n\n\nclass KCSC_ConvRepIndexing(object):\n \"\"\"Array dimensions and indexing for Kruskal CSC problems.\n\n Manage the inference of problem dimensions and the roles of\n :class:`numpy.ndarray` indices for convolutional representations in\n convolutional sparse coding problems (e.g.\n :class:`.admm.cbpdn.ConvBPDN` and related classes).\n \"\"\"\n\n def __init__(self, cri_AK, Rank, l):\n \"\"\"Initialise a ConvRepIndexing object.\n\n Initialise a ConvRepIndexing object representing dimensions\n of S (input signal), D (dictionary), and X (coefficient array)\n in a convolutional representation. These dimensions are\n inferred from the input `D` and `S` as well as from parameters\n `dimN` and `dimK`. Management and inferrence of these problem\n dimensions is not entirely straightforward because\n :class:`.admm.cbpdn.ConvBPDN` and related classes make use\n *internally* of S, D, and X arrays with a standard layout\n (described below), but *input* `S` and `D` are allowed to\n deviate from this layout for the convenience of the user.\n\n The most fundamental parameter is `dimN`, which specifies the\n dimensionality of the spatial/temporal samples being\n represented (e.g. `dimN` = 2 for representations of 2D\n images). This should be common to *input* S and D, and is\n also common to *internal* S, D, and X. The remaining\n dimensions of input `S` can correspond to multiple channels\n (e.g. for RGB images) and/or multiple signals (e.g. the array\n contains multiple independent images). If input `S` contains\n two additional dimensions (in addition to the `dimN` spatial\n dimensions), then those are considered to correspond, in\n order, to channel and signal indices. If there is only a\n single additional dimension, then determination whether it\n represents a channel or signal index is more complicated. The\n rule for making this determination is as follows:\n\n * if `dimK` is set to 0 or 1 instead of the default ``None``,\n then that value is taken as the number of signal indices in\n input `S` and any remaining indices are taken as channel\n indices (i.e. if `dimK` = 0 then dimC = 1 and if `dimK` = 1\n then dimC = 0).\n * if `dimK` is ``None`` then the number of channel dimensions is\n determined from the number of dimensions in the input\n dictionary `D`. Input `D` should have at least `dimN` + 1\n dimensions, with the final dimension indexing dictionary\n filters. If it has exactly `dimN` + 1 dimensions then it is a\n single-channel dictionary, and input `S` is also assumed to be\n single-channel, with the additional index in `S` assigned as a\n signal index (i.e. dimK = 1). Conversely, if input `D` has\n `dimN` + 2 dimensions it is a multi-channel dictionary, and\n the additional index in `S` is assigned as a channel index\n (i.e. dimC = 1).\n\n Note that it is an error to specify `dimK` = 1 if input `S`\n has `dimN` + 1 dimensions and input `D` has `dimN` + 2\n dimensions since a multi-channel dictionary requires a\n multi-channel signal. (The converse is not true: a\n multi-channel signal can be decomposed using a single-channel\n dictionary.)\n\n The *internal* data layout for S (signal), D (dictionary), and\n X (coefficient array) is (multi-channel dictionary)\n ::\n\n sptl. chn sig flt\n S(N0, N1, ..., C, K, 1)\n D(N0, N1, ..., C, 1, M)\n X(N0, N1, ..., 1, K, M)\n\n or (single-channel dictionary)\n\n ::\n\n sptl. chn sig flt\n S(N0, N1, ..., C, K, 1)\n D(N0, N1, ..., 1, 1, M)\n X(N0, N1, ..., C, K, M)\n\n where\n\n * Nv = [N0, N1, ...] and N = N0 x N1 x ... are the vector of sizes\n of the spatial/temporal indices and the total number of\n spatial/temporal samples respectively\n * C is the number of channels in S\n * K is the number of signals in S\n * M is the number of filters in D\n\n It should be emphasised that dimC and `dimK` may take on values\n 0 or 1, and represent the number of channel and signal\n dimensions respectively *in input S*. In the internal layout\n of S there is always a dimension allocated for channels and\n signals. The number of channel dimensions in input `D` and the\n corresponding size of that index are represented by dimCd\n and Cd respectively.\n\n Parameters\n ----------\n D : array_like\n Input dictionary\n S : array_like\n Input signal\n dimK : 0, 1, or None, optional (default None)\n Number of dimensions in input signal corresponding to multiple\n independent signals\n dimN : int, optional (default 2)\n Number of spatial/temporal dimensions of signal samples\n \"\"\"\n\n # # Determine whether dictionary is single- or multi-channel\n # self.dimCd = D.ndim - (dimN + 2)\n # if self.dimCd == 0:\n # self.Cd = 1\n # else:\n # self.Cd = D.shape[-2]\n #\n # # Numbers of spatial, channel, and signal dimensions in\n # # external S are dimN, dimC, and dimK respectively. These need\n # # to be calculated since inputs D and S do not already have\n # # the standard data layout above, i.e. singleton dimensions\n # # will not be present\n # if dimK is None:\n # rdim = S.ndim - dimN\n # if rdim == 0:\n # (dimC, dimK) = (0, 0)\n # elif rdim == 1:\n # dimC = self.dimCd # Assume S has same number of channels as D\n # dimK = S.ndim - dimN - dimC # Assign remaining channels to K\n # else:\n # (dimC, dimK) = (1, 1)\n # else:\n # dimC = S.ndim - dimN - dimK # Assign remaining channels to C\n #\n # self.dimN = dimN # Number of spatial dimensions\n # self.dimC = dimC # Number of channel dimensions in S\n # self.dimK = dimK # Number of signal dimensions in S\n #\n # # Number of channels in S\n # if self.dimC == 1:\n # self.C = S.shape[dimN]\n # else:\n # self.C = 1\n # Cx = self.C - self.Cd + 1\n #\n # # Ensure that multi-channel dictionaries used with a signal with a\n # # matching number of channels\n # if self.Cd > 1 and self.C != self.Cd:\n # raise ValueError(\"Multi-channel dictionary with signal with \"\n # \"mismatched number of channels (Cd=%d, C=%d)\" %\n # (self.Cd, self.C))\n #\n # # Number of signals in S\n # if self.dimK == 1:\n # self.K = S.shape[self.dimN + self.dimC]\n # else:\n # self.K = 1\n #\n # # Number of filters\n # self.M = D.shape[1] # KCSC std layout D(n',M,n,C)\n #\n # # Shape of spatial indices and number of spatial samples\n # self.Nv = S.shape[0:dimN]\n # self.N = np.prod(np.array(self.Nv))\n #\n # self.N_ = D.shape[0]\n #\n # self.nv = tuple(np.array(np.array(self.Nv)/self.N_,dtype=int))\n #\n # # Axis indices for each component of X and internal S and D\n # self.axisN = tuple(range(2, dimN+2))\n # self.axisC = dimN + 2\n # self.axisK = dimN + 3\n # self.axisM = 1\n #\n # # Shapes of internal S, D, and X (TO BE DONE, maybe not needed)\n # self.shpD = (self.N_,) + (self.M,) + self.nv + (self.Cd,) + (1,)\n # self.shpS = (1,) + (1,) + self.Nv + (self.C,) + (self.K,)\n # self.shpX = (1,) + (self.M,) + self.nv + (Cx,) + (self.K,)\n #\n # # Number of independent Linear systems\n # self.dimL = np.prod(self.nv)*self.Cd\n\n # Shape of spatial indices and number of spatial samples\n self.n = cri_AK.Nv[l]\n self.NC = int(cri_AK.N*cri_AK.Cd/self.n)\n self.MR = int(np.sum(Rank))\n\n # Axis indices for each component of X and internal S and D\n self.axisNC = [0]\n self.axisMR = [1]\n self.axisn = [2]\n\n # Shapes of internal S, D, and X\n self.shpD = (self.NC,self.MR,self.n)\n self.shpS = (self.NC,1,self.n)\n self.shpX = (self.MR,1,self.n)\n\n\n\n def __str__(self):\n \"\"\"Return string representation of object.\"\"\"\n\n return pprint.pformat(vars(self))\n\n\n\ndef Kl1Wshape(W, cri):\n r\"\"\"Get internal shape for an :math:`\\ell_1` norm weight array.\n\n Get appropriate internal shape (see\n :class:`CSC_ConvRepIndexing`) for an :math:`\\ell_1` norm weight\n array `W`, as in option ``L1Weight`` in\n :class:`.admm.cbpdn.ConvBPDN.Options` and related options classes.\n The external shape of `W` depends on the external shape of input\n data array `S` and the size of the final axis (i.e. the number of\n filters) in dictionary array `D`. The internal shape of the\n weight array `W` is required to be compatible for multiplication\n with the internal sparse representation array `X`. The simplest\n criterion for ensuring that the external `W` is compatible with\n `S` is to ensure that `W` has shape ``S.shape + D.shape[-1:]``,\n except that non-singleton dimensions may be replaced with\n singleton dimensions. If `W` has a single additional axis that is\n neither a spatial axis nor a filter axis, it is assigned as a\n channel or multi-signal axis depending on the corresponding\n assignement in `S`.\n\n Parameters\n ----------\n W : array_like\n Weight array\n cri : :class:`CSC_ConvRepIndexing` object\n Object specifying convolutional representation dimensions\n\n Returns\n -------\n shp : tuple\n Appropriate internal weight array shape\n \"\"\"\n\n # Number of dimensions in input array `S`\n sdim = len(cri.shpX) # + cri.dimC + cri.dimK\n\n if W.ndim < sdim:\n if W.size == 1:\n # Weight array is a scalar\n shpW = (1,) * 3\n else:\n # Invalid weight array shape\n raise ValueError('weight array must be scalar or have at least '\n 'the same number of dimensions as input array')\n elif W.ndim == sdim:\n # Weight array has the same number of dimensions as the input array\n shpW = W.shape\n else:\n # # Weight array has more dimensions than the input array\n # if W.ndim == cri.dimN + 4:\n # # Weight array is already of the appropriate shape\n # shpW = W.shape\n # else:\n # # # Assume that the final axis in the input array is the filter\n # # # index\n # # shpW = (1,) + W.shape[-1:] + W.shape[0:-1] + (1,) * (2 - cri.dimC - \\\n # # cri.dimK)\n\n # Invalid weight array shape\n raise ValueError('Internal shape of weight array should match shpX'\n 'w(MR, 1, n)')\n\n return shpW\n\n\n\nclass KConvBPDN(cbpdn.GenericConvBPDN):\n r\"\"\"\n ADMM algorithm for the Convolutional BPDN (CBPDN)\n :cite:`wohlberg-2014-efficient` :cite:`wohlberg-2016-efficient`\n :cite:`wohlberg-2016-convolutional` problem.\n\n |\n\n .. inheritance-diagram:: ConvBPDN\n :parts: 2\n\n |\n\n Solve the optimisation problem\n\n .. math::\n \\mathrm{argmin}_\\mathbf{x} \\;\n (1/2) \\left\\| \\sum_m \\mathbf{d}_m * \\mathbf{x}_m -\n \\mathbf{s} \\right\\|_2^2 + \\lambda \\sum_m \\| \\mathbf{x}_m \\|_1\n\n for input image :math:`\\mathbf{s}`, dictionary filters\n :math:`\\mathbf{d}_m`, and coefficient maps :math:`\\mathbf{x}_m`,\n via the ADMM problem\n\n .. math::\n \\mathrm{argmin}_{\\mathbf{x}, \\mathbf{y}} \\;\n (1/2) \\left\\| \\sum_m \\mathbf{d}_m * \\mathbf{x}_m -\n \\mathbf{s} \\right\\|_2^2 + \\lambda \\sum_m \\| \\mathbf{y}_m \\|_1\n \\quad \\text{such that} \\quad \\mathbf{x}_m = \\mathbf{y}_m \\;\\;.\n\n Multi-image and multi-channel problems are also supported. The\n multi-image problem is\n\n .. math::\n \\mathrm{argmin}_\\mathbf{x} \\;\n (1/2) \\sum_k \\left\\| \\sum_m \\mathbf{d}_m * \\mathbf{x}_{k,m} -\n \\mathbf{s}_k \\right\\|_2^2 + \\lambda \\sum_k \\sum_m\n \\| \\mathbf{x}_{k,m} \\|_1\n\n with input images :math:`\\mathbf{s}_k` and coefficient maps\n :math:`\\mathbf{x}_{k,m}`, and the multi-channel problem with input\n image channels :math:`\\mathbf{s}_c` is either\n\n .. math::\n \\mathrm{argmin}_\\mathbf{x} \\;\n (1/2) \\sum_c \\left\\| \\sum_m \\mathbf{d}_m * \\mathbf{x}_{c,m} -\n \\mathbf{s}_c \\right\\|_2^2 +\n \\lambda \\sum_c \\sum_m \\| \\mathbf{x}_{c,m} \\|_1\n\n with single-channel dictionary filters :math:`\\mathbf{d}_m` and\n multi-channel coefficient maps :math:`\\mathbf{x}_{c,m}`, or\n\n .. math::\n \\mathrm{argmin}_\\mathbf{x} \\;\n (1/2) \\sum_c \\left\\| \\sum_m \\mathbf{d}_{c,m} * \\mathbf{x}_m -\n \\mathbf{s}_c \\right\\|_2^2 + \\lambda \\sum_m \\| \\mathbf{x}_m \\|_1\n\n with multi-channel dictionary filters :math:`\\mathbf{d}_{c,m}` and\n single-channel coefficient maps :math:`\\mathbf{x}_m`.\n\n After termination of the :meth:`solve` method, attribute :attr:`itstat`\n is a list of tuples representing statistics of each iteration. The\n fields of the named tuple ``IterationStats`` are:\n\n ``Iter`` : Iteration number\n\n ``ObjFun`` : Objective function value\n\n ``DFid`` : Value of data fidelity term :math:`(1/2) \\| \\sum_m\n \\mathbf{d}_m * \\mathbf{x}_m - \\mathbf{s} \\|_2^2`\n\n ``RegL1`` : Value of regularisation term :math:`\\sum_m \\|\n \\mathbf{x}_m \\|_1`\n\n ``PrimalRsdl`` : Norm of primal residual\n\n ``DualRsdl`` : Norm of dual residual\n\n ``EpsPrimal`` : Primal residual stopping tolerance\n :math:`\\epsilon_{\\mathrm{pri}}`\n\n ``EpsDual`` : Dual residual stopping tolerance\n :math:`\\epsilon_{\\mathrm{dua}}`\n\n ``Rho`` : Penalty parameter\n\n ``XSlvRelRes`` : Relative residual of X step solver\n\n ``Time`` : Cumulative run time\n \"\"\"\n\n\n class Options(cbpdn.GenericConvBPDN.Options):\n r\"\"\"ConvBPDN algorithm options\n\n Options include all of those defined in\n :class:`.admm.ADMMEqual.Options`, together with additional options:\n\n ``L1Weight`` : An array of weights for the :math:`\\ell_1`\n norm. The array shape must be such that the array is\n compatible for multiplication with the `X`/`Y` variables (see\n :func:`.cnvrep.l1Wshape` for more details). If this\n option is defined, the regularization term is :math:`\\lambda\n \\sum_m \\| \\mathbf{w}_m \\odot \\mathbf{x}_m \\|_1` where\n :math:`\\mathbf{w}_m` denotes slices of the weighting array on\n the filter index axis.\n \"\"\"\n\n defaults = copy.deepcopy(cbpdn.GenericConvBPDN.Options.defaults)\n defaults.update({'L1Weight': 1.0})\n\n\n def __init__(self, opt=None):\n \"\"\"\n Parameters\n ----------\n opt : dict or None, optional (default None)\n ConvBPDN algorithm options\n \"\"\"\n\n if opt is None:\n opt = {}\n cbpdn.GenericConvBPDN.Options.__init__(self, opt)\n\n\n\n itstat_fields_objfn = ('ObjFun', 'DFid', 'RegL1', 'RegL2')\n hdrtxt_objfn = ('Fnc', 'DFid', u('Regℓ1'), u('Regℓ2'))\n hdrval_objfun = {'Fnc': 'ObjFun', 'DFid': 'DFid',\n u('Regℓ1'): 'RegL1', u('Regℓ2'): 'RegL2'}\n\n\n def __init__(self, Wf, Sf, cri_K, dtype, lmbda=None, mu=0.0, opt=None):\n \"\"\"\n This class supports an arbitrary number of spatial dimensions,\n `dimN`, with a default of 2. The input dictionary `D` is either\n `dimN` + 1 dimensional, in which case each spatial component\n (image in the default case) is assumed to consist of a single\n channel, or `dimN` + 2 dimensional, in which case the final\n dimension is assumed to contain the channels (e.g. colour\n channels in the case of images). The input signal set `S` is\n either `dimN` dimensional (no channels, only one signal), `dimN`\n + 1 dimensional (either multiple channels or multiple signals),\n or `dimN` + 2 dimensional (multiple channels and multiple\n signals). Determination of problem dimensions is handled by\n :class:`.cnvrep.CSC_ConvRepIndexing`.\n\n\n |\n\n **Call graph**\n\n .. image:: ../_static/jonga/cbpdn_init.svg\n :width: 20%\n :target: ../_static/jonga/cbpdn_init.svg\n\n |\n\n\n Parameters\n ----------\n D : array_like\n Dictionary array\n S : array_like\n Signal array\n lmbda : float\n Regularisation parameter\n opt : :class:`ConvBPDN.Options` object\n Algorithm options\n dimK : 0, 1, or None, optional (default None)\n Number of dimensions in input signal corresponding to multiple\n independent signals\n dimN : int, optional (default 2)\n Number of spatial/temporal dimensions\n \"\"\"\n\n # Set default options if none specified\n if opt is None:\n opt = KConvBPDN.Options()\n\n # Set dtype attribute based on S.dtype and opt['DataType']\n self.set_dtype(opt, dtype)\n\n # problem dimensions\n self.cri = cri_K\n\n # Reshape D and S to standard layout (NOT NEEDED in AKConvBPDN)\n self.Wf = np.asarray(Wf.reshape(self.cri.shpD), dtype=self.dtype)\n self.Sf = np.asarray(Sf.reshape(self.cri.shpS), dtype=self.dtype)\n # self.Sf_ = np.moveaxis(Sf.reshape([self.cri.nv[0],self.cri.N_,1]),[0,1,2],[2,0,1])\n\n # Set default lambda value if not specified\n if lmbda is None:\n b = np.conj(Df) * Sf\n lmbda = 0.1 * abs(b).max()\n\n # Set l1 term scaling\n self.lmbda = self.dtype.type(lmbda)\n\n # Set l2 term scaling\n self.mu = self.dtype.type(mu)\n\n # Set penalty parameter\n self.set_attr('rho', opt['rho'], dval=(50.0 * self.lmbda + 1.0),\n dtype=self.dtype)\n\n # Set rho_xi attribute (see Sec. VI.C of wohlberg-2015-adaptive)\n if self.lmbda != 0.0:\n rho_xi = float((1.0 + (18.3)**(np.log10(self.lmbda) + 1.0)))\n else:\n rho_xi = 1.0\n self.set_attr('rho_xi', opt['AutoRho', 'RsdlTarget'], dval=rho_xi,\n dtype=self.dtype)\n\n # Call parent class __init__ (not ConvBPDN bc FFT domain data)\n super(cbpdn.GenericConvBPDN, self).__init__(self.cri.shpX, Sf.dtype, opt)\n\n # Initialise byte-aligned arrays for pyfftw\n self.YU = sl.pyfftw_empty_aligned(self.Y.shape, dtype=self.dtype)\n self.Xf = sl.pyfftw_empty_aligned(self.Y.shape, self.dtype)\n\n\n self.c = [None] * self.cri.n # to be filled with cho_factor\n\n self.setdictf()\n\n\n # Set l1 term weight array\n self.wl1 = np.asarray(opt['L1Weight'], dtype=self.dtype)\n self.wl1 = self.wl1.reshape(Kl1Wshape(self.wl1, self.cri))\n\n print('L1Weight %s \\n' % (self.wl1,))\n\n\n def setdictf(self, Wf=None):\n \"\"\"Set dictionary array.\"\"\"\n\n if Wf is not None:\n self.Wf = Wf;\n # Compute D^H S\n print('Df shape %s \\n' % (self.Wf.shape,))\n print('Sf shape %s \\n' % (self.Sf.shape,))\n\n self.WSf = (np.sum(np.conj(self.Wf) * self.Sf, axis=0)).squeeze()\n # if self.cri.Cd > 1:\n # self.WSf = np.sum(self.WSf, axis=self.cri.axisC, keepdims=True)\n\n # Df_full = self.Wf.reshape([self.cri.shpD[0],self.cri.shpD[1],self.cri.n])\n for s in range(self.cri.n):\n Df_ = self.Wf[:,:,s]\n Df_H = np.conj(Df_.transpose())\n self.c[s] = linalg.cho_factor(np.dot(Df_H,Df_) + (self.mu + self.rho) * \\\n np.identity(self.cri.MR,dtype=self.dtype),lower=False,check_finite=True)\n\n\n def uinit(self, ushape):\n \"\"\"Return initialiser for working variable U\"\"\"\n\n if self.opt['Y0'] is None:\n return np.zeros(ushape, dtype=self.dtype)\n else:\n # If initial Y is non-zero, initial U is chosen so that\n # the relevant dual optimality criterion (see (3.10) in\n # boyd-2010-distributed) is satisfied.\n return (self.lmbda/self.rho)*np.sign(self.Y)\n\n\n def xstep(self):\n r\"\"\"Minimise Augmented Lagrangian with respect to\n :math:`\\mathbf{x}`.\n \"\"\"\n\n self.YU[:] = self.Y - self.U\n\n print('YU dtype %s \\n' % (self.YU.dtype,))\n\n b = (self.WSf + self.rho*sl.fftn(self.YU, None, self.cri.axisn).squeeze())\n\n # print('b shape %s \\n' % (b.shape,))\n\n # if self.cri.Cd == 1:\n for s in range(self.cri.n):\n self.Xf[:,0,s] = linalg.cho_solve(self.c[s],b[:,s],check_finite=True)\n # else:\n # raise ValueError(\"Multi-channel dictionary not implemented\")\n # self.Xf[:] = sl.solvemdbi_ism(self.Wf, self.mu + self.rho, b,\n # self.cri.axisM, self.cri.axisC)\n\n self.X = sl.irfftn(self.Xf, [self.cri.n], self.cri.axisn)\n\n # if self.opt['LinSolveCheck']:\n # Dop = lambda x: sl.inner(self.Wf, x, axis=self.cri.axisM)\n # if self.cri.Cd == 1:\n # DHop = lambda x: np.conj(self.Wf) * x\n # else:\n # DHop = lambda x: sl.inner(np.conj(self.Wf), x,\n # axis=self.cri.axisC)\n # ax = DHop(Dop(self.Xf)) + (self.mu + self.rho)*self.Xf\n # self.xrrs = sl.rrs(ax, b)\n # else:\n # self.xrrs = None\n\n\n def ystep(self):\n r\"\"\"Minimise Augmented Lagrangian with respect to\n :math:`\\mathbf{y}`.\"\"\"\n\n scalar_factor = (self.lmbda / self.rho) * self.wl1\n print('AX dtype %s \\n' % (self.AX.dtype,))\n print('U dtype %s \\n' % (self.U.dtype,))\n print('sc_factor shape %s \\n' % (scalar_factor.shape,))\n\n self.Y = sp.prox_l1(self.AX + self.U,(self.lmbda / self.rho) * self.wl1)\n super(KConvBPDN, self).ystep()\n\n\n def obfn_reg(self):\n \"\"\"Compute regularisation term and contribution to objective\n function. (ConvElasticNet)\n \"\"\"\n\n rl1 = np.linalg.norm((self.wl1 * self.obfn_gvar()).ravel(), 1)\n rl2 = 0.5*np.linalg.norm(self.obfn_gvar())**2\n return (self.lmbda*rl1 + self.mu*rl2, rl1, rl2)\n\n\n def setdict(self):\n \"\"\"Set dictionary array.\n\n Overriding this method is required.\n \"\"\"\n\n raise NotImplementedError()\n\n\n def reconstruct(self):\n \"\"\"Reconstruct representation.\n\n Overriding this method is required.\n \"\"\"\n\n raise NotImplementedError()\n\n\nclass AKConvBPDN(object):\n \"\"\"Boundary masking for convolutional representations using the\n Alternated Kruscal ConvBPDN technique described in\n :cite:`humbert-2019`. Implemented as a wrapper about a\n ConvBPDN or derived object (or any other object with\n sufficiently similar interface and internals). The wrapper is largely\n transparent, but must be taken into account when setting some of the\n options for the inner object, e.g. the shape of the ``L1Weight``\n option array must take into account the extra dictionary atom appended\n by the wrapper.\n \"\"\"\n\n class Options(cdict.ConstrainedDict):\n \"\"\"AKConvBPDN options.\n\n Options:\n\n ``Verbose`` : Flag determining whether iteration status is\n displayed.\n\n ``StatusHeader`` : Flag determining whether status header and\n separator are displayed.\n\n ``IterTimer`` : Label of the timer to use for iteration times.\n\n ``MaxMainIter`` : Maximum main iterations.\n\n ``Callback`` : Callback function to be called at the end of\n every iteration.\n \"\"\"\n\n defaults = {'Verbose': False, 'StatusHeader': True,\n 'IterTimer': 'solve', 'MaxMainIter': 50,\n 'Callback': None}\n\n\n def __init__(self, opt=None):\n \"\"\"\n Parameters\n ----------\n opt : dict or None, optional (default None)\n DictLearn algorithm options\n \"\"\"\n\n if opt is None:\n opt = {}\n cdict.ConstrainedDict.__init__(self, opt)\n\n\n def __new__(cls, *args, **kwargs):\n \"\"\"Create an AKConvBPDN object and start its\n initialisation timer.\"\"\"\n\n instance = super(AKConvBPDN, cls).__new__(cls)\n instance.timer = util.Timer(['init', 'solve', 'solve_wo_eval'])\n instance.timer.start('init')\n return instance\n\n\n def __init__(self, D, S, R, opt=None, lmbda=None, optx=None,\n dimK=None, dimN=2,*args, **kwargs):\n \"\"\"\n Parameters\n ----------\n xstep : internal xstep object (e.g. xstep.ConvBPDN)\n D : array_like\n Dictionary array\n S : array_like\n Signal array\n R : array_like\n Rank array\n lmbda : list of float\n Regularisation parameter\n opt : list containing :class:`ConvBPDN.Options` object\n Algorithm options for each individual solver\n dimK : 0, 1, or None, optional (default None)\n Number of dimensions in input signal corresponding to multiple\n independent signals\n dimN : int, optional (default 2)\n Number of spatial/temporal dimensions\n *args\n Variable length list of arguments for constructor of internal\n xstep object (e.g. mu)\n **kwargs\n Keyword arguments for constructor of internal xstep object\n \"\"\"\n\n if opt is None:\n opt = AKConvBPDN.Options()\n self.opt = opt\n\n # Infer outer problem dimensions\n self.cri = cr.CSC_ConvRepIndexing(D, S, dimK=dimK, dimN=dimN)\n\n # Parse mu\n if 'mu' in kwargs:\n mu = kwargs['mu']\n else:\n mu = [0] * self.cri.dimN\n\n # Parse lmbda and optx\n if lmbda is None: lmbda = [None] * self.cri.dimN\n if optx is None: optx = [None] * self.cri.dimN\n\n # Parse isc\n if 'isc' in kwargs:\n isc = kwargs['isc']\n else:\n isc = None\n\n # Store parameters\n self.lmbda = lmbda\n self.optx = optx\n self.mu = mu\n self.R = R\n\n # Reshape D and S to standard layout\n self.D = np.asarray(D.reshape(self.cri.shpD), dtype=S.dtype)\n self.S = np.asarray(S.reshape(self.cri.shpS), dtype=S.dtype)\n\n # Compute signal in DFT domain\n self.Sf = sl.fftn(self.S, None, self.cri.axisN)\n # print('Sf shape %s \\n' % (self.Sf.shape,))\n # print('S shape %s \\n' % (self.S.shape,))\n # print('shpS %s \\n' % (self.cri.shpS,))\n\n # Signal uni-dim (kruskal)\n # self.Skf = np.reshape(self.Sf,[np.prod(np.array(self.Sf.shape)),1],order='F')\n\n # Decomposed Kruskal Initialization\n self.K = []\n self.Kf = []\n Nvf = []\n for i,Nvi in enumerate(self.cri.Nv): # Ui\n Ki = np.random.randn(Nvi,np.sum(self.R))\n Kfi = sl.pyfftw_empty_aligned(Ki.shape, self.Sf.dtype)\n Kfi[:] = sl.fftn(Ki,None,[0])\n self.K.append(Ki)\n self.Kf.append(Kfi)\n Nvf.append(Kfi.shape[0])\n\n self.Nvf = tuple(Nvf)\n\n # Fourier dimensions\n self.NC = int(np.prod(self.Nvf)*self.cri.Cd)\n\n # dict FFT\n self.setdict()\n\n # Init KCSC solver (Needs to be initiated inside AKConvBPDN because requires convolvedict() and reshapesignal())\n self.xstep = []\n for l in range(self.cri.dimN):\n\n Wl = self.convolvedict(l) # convolvedict\n cri_l = KCSC_ConvRepIndexing(self.cri,self.R,l) # cri KCSC\n\n self.xstep.append(KConvBPDN(Wl, np.reshape(self.Sf,cri_l.shpS,order='C'), cri_l,\\\n self.S.dtype, self.lmbda[l], self.mu[l], self.optx[l]))\n\n # Init isc\n if isc is None:\n\n isc_lst = [] # itStats from block-solver\n isc_fields = []\n for i in range(self.cri.dimN):\n str_i = '_{0!s}'.format(i)\n\n isc_i = IterStatsConfig(\n isfld=['ObjFun'+str_i, 'PrimalRsdl'+str_i,'DualRsdl'+str_i,\n 'Rho'+str_i],\n isxmap={'ObjFun'+str_i: 'ObjFun', 'PrimalRsdl'+str_i: 'PrimalRsdl',\n 'DualRsdl'+str_i: 'DualRsdl', 'Rho'+str_i: 'Rho'},\n evlmap={},\n hdrtxt=['Fnc'+str_i, 'r'+str_i, 's'+str_i, u('ρ'+str_i)],\n hdrmap={'Fnc'+str_i: 'ObjFun'+str_i, 'r'+str_i: 'PrimalRsdl'+str_i,\n 's'+str_i: 'DualRsdl'+str_i, u('ρ'+str_i): 'Rho'+str_i}\n )\n isc_fields += isc_i.IterationStats._fields\n\n isc_lst.append(isc_i)\n\n # isc_it = IterStatsConfig( # global itStats -> No, to be managed in dictlearn\n # isfld=['Iter','Time'],\n # isxmap={},\n # evlmap={},\n # hdrtxt=['Itn'],\n # hdrmap={'Itn': 'Iter'}\n # )\n #\n # isc_fields += isc_it._fields\n\n self.isc_lst = isc_lst\n # self.isc_it = isc_it\n self.isc = collections.namedtuple('IterationStats', isc_fields)\n\n # Required because dictlrn.DictLearn assumes that all valid\n # xstep objects have an IterationStats attribute\n # self.IterationStats = self.xstep.IterationStats\n\n self.itstat = []\n self.j = 0\n\n\n def solve(self):\n \"\"\"Call the solve method of the inner KConvBPDN object and return the\n result.\n \"\"\"\n\n itst = []\n\n # Main optimisation iterations\n for self.j in range(self.j, self.j + self.opt['MaxMainIter']):\n\n for l in range(self.cri.dimN):\n\n # Pre x-step\n Wl = self.convolvedict(l) # convolvedict\n self.xstep[l].setdictf(Wl) # setdictf\n\n # Solve KCSC\n self.xstep[l].solve()\n\n # Post x-step\n Kl = np.moveaxis(self.xstep[l].getcoef().squeeze(),[0,1],[1,0])\n self.Kf[l] = sl.fftn(Kl, None, [0]) # Update Kruskal\n\n # IterationStats\n xitstat = self.xstep.itstat[-1] if self.xstep.itstat else \\\n self.xstep.IterationStats(\n *([0.0,] * len(self.xstep.IterationStats._fields)))\n\n itst += self.isc_lst[l].iterstats(self.j, 0, xitstat, 0) # Accumulate\n\n self.itstat.append(self.isc(*itst)) # Cast to global itstats and store\n\n # Decomposed ifftn\n for l in range(self.cri.dimN):\n self.K[l] = sl.irfftn(self.Kf[l], self.cri.Nv[l], [0]) # ifft transform\n\n self.j += 1\n\n\n def setdict(self, D=None):\n \"\"\"Set dictionary array.\"\"\"\n\n if D is not None:\n self.D = np.asarray(D, dtype=self.dtype)\n # self.Df = sl.fftn(self.D, self.cri.Nv, self.cri.axisN)\n\n print('D shape %s \\n' % (self.D.shape,))\n print('axisN %s \\n' % (self.cri.axisN,))\n print('dimN %s \\n' % (self.cri.dimN,))\n\n # Df = self.D\n # for l in range(self.cri.dimN):\n # Df = sl.fftn(Df, [self.cri.Nv[l]], [self.cri.axisN[l]])\n # self.Df = Df\n\n self.Df = sl.fftn(self.D, self.Nvf, self.cri.axisN)\n\n print('Df shape %s \\n' % (self.Df.shape,))\n print('self.cri.Cd %s \\n' % (self.cri.Cd,))\n print('self.NC %s \\n' % (self.NC,))\n print('self.Nvf %s \\n' % (self.Nvf,))\n\n # if not hasattr(self, 'cri_f'):\n # # At first call: Infer outer problem dimensions for fourier domain\n # self.cri_f = cr.CSC_ConvRepIndexing(self.Df, self.Sf, dimK=self.cri.dimK, dimN=self.cri.dimN)\n\n NC = self.NC\n M = self.cri.M\n\n self.Df_mat = np.dot(np.reshape(self.Df,[NC,M],order='F'),self.getweights().transpose()) # Df_mat(NC,R*M)\n\n\n def convolvedict(self,l=None):\n \"\"\"W: Convolve D w/.\"\"\"\n\n Df_mat = self.Df_mat\n Kf = self.Kf\n\n NC = self.NC\n\n Nl = self.Nvf[l] if l is not None else 1\n\n print('Kf shape %s \\n' % (Kf[l].shape,))\n print('Nl %s \\n' % (Nl,))\n\n Df_ = np.moveaxis(np.reshape(Df_mat,[Nl,int(NC/Nl),sum(self.R)],order='F'),\\\n [0,1,2],[2,0,1]).squeeze()\n Q = np.reshape(tl.tenalg.khatri_rao(Kf,skip_matrix=l,reverse=True),\\\n [int(NC/Nl),sum(self.R),1])\n return Df_*Q\n\n\n def getweights(self):\n \"\"\"Linear map from [NxR*K] to [NxK] array.\"\"\"\n\n weightsArray = []\n for k,Rk in enumerate(self.R):\n weightsArray.append(np.ones([Rk,1]))\n\n return linalg.block_diag(*weightsArray) # map from R*M to M\n\n\n def getcoef(self):\n \"\"\"Get result of inner xstep object and expand Kruskal.\"\"\"\n\n Nz = self.cri.Nv\n Nz.append(self.cri.M)\n\n Z = np.dot(tl.tenalg.khatri_rao(self.K,reverse=True),self.getweights())\n\n return tl.base.vec_to_tensor(Z,Nz) # as array Z(N0,N1,...,M)\n\n\n def getKruskal(self):\n \"\"\"Get decomposed Krukal Z.\"\"\"\n\n return self.K()\n\n\n def reconstruct(self, X=None):\n \"\"\"Reconstruct representation.\"\"\"\n\n Df = self.Df\n Nz = self.Nvf\n Nz.append(self.cri.M)\n\n # # Stupid Option\n # Tz = self.getcoef()\n # Xf = sl.rfftn(Tz,None,self.cri.axisN)\n\n #Smart Option\n Zf = np.dot(tl.tenalg.khatri_rao(self.Kf,reverse=True),self.getweights())\n Xf = tl.base.vec_to_tensor(Z,Nz)\n\n Sf = np.sum(Df*Xf, axis=self.cri.axisM)\n\n return sl.ifftn(Sf, self.cri.Nv, self.cri.axisN)\n\n\n def getitstat(self):\n \"\"\"Get iteration stats.\"\"\"\n\n return self.itstat\n","sub_path":"sporco/admm/object.py","file_name":"object.py","file_ext":"py","file_size_in_byte":39170,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"63632675","text":"#!/usr/bin/env python\nimport torch\nimport numpy as np\nfrom numpy import random\nimport socket\n\nfrom models.experimental import attempt_load\nfrom utils.general import non_max_suppression\n\nimport cv2\nimport sys\nimport time\n\nfrom socket_funcs import *\n\ndef letterbox(\n img,\n new_shape=(640, 640),\n color=(114, 114, 114),\n auto=True,\n scaleFill=False,\n scaleup=True,\n):\n # Resize image to a 32-pixel-multiple rectangle https://github.com/ultralytics/yolov3/issues/232\n shape = img.shape[:2] # current shape [height, width]\n if isinstance(new_shape, int):\n new_shape = (new_shape, new_shape)\n # Scale ratio (new / old)\n r = min(new_shape[0] / shape[0], new_shape[1] / shape[1])\n if not scaleup: # only scale down, do not scale up (for better test mAP)\n r = min(r, 1.0)\n # Compute padding\n ratio = r, r # width, height ratios\n new_unpad = int(round(shape[1] * r)), int(round(shape[0] * r))\n dw, dh = new_shape[1] - new_unpad[0], new_shape[0] - new_unpad[1] # wh padding\n if auto: # minimum rectangle\n dw, dh = np.mod(dw, 32), np.mod(dh, 32) # wh padding\n elif scaleFill: # stretch\n dw, dh = 0.0, 0.0\n new_unpad = (new_shape[1], new_shape[0])\n ratio = new_shape[1] / shape[1], new_shape[0] / shape[0] # width, height ratios\n dw /= 2 # divide padding into 2 sides\n dh /= 2\n if shape[::-1] != new_unpad: # resize\n img = cv2.resize(img, new_unpad, interpolation=cv2.INTER_LINEAR)\n top, bottom = int(round(dh - 0.1)), int(round(dh + 0.1))\n left, right = int(round(dw - 0.1)), int(round(dw + 0.1))\n img = cv2.copyMakeBorder(\n img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color\n ) # add border\n return img, ratio, (dw, dh)\n\ndef preprocessing(img):\n img = letterbox(img, new_shape=(640, 640))[0]\n # Convert\n img = img[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB, to 3x416x416\n img = np.ascontiguousarray(img)\n img = torch.from_numpy(img).to(\"cuda:0\")\n img = img.half() # if half else img.float() # uint8 to fp16/32\n img /= 255.0 # 0 - 255 to 0.0 - 1.0\n img = img.unsqueeze(0)\n return img\n\n\nmodel_path = \"./weights/churo.pt\"\n\n\nwith open('AWS_IP.txt', 'r') as f:\n TCP_IP = f.readline()\nTCP_PORT = 6666\ns = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\ns.bind((TCP_IP, TCP_PORT))\ns.listen(True)\n \nTCP_PORT = 5555\nss = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nss.bind((TCP_IP, TCP_PORT))\nss.listen(True)\n\nprint('listening...')\ncam_client, addr = s.accept()\nprint('image node connected')\nmsg_client, addr = ss.accept()\nprint('message node connected')\nprint(\"start\")\n\nif __name__ == \"__main__\":\n model = attempt_load(model_path, map_location=\"cuda\")\n model = model.autoshape() # for autoshaping of PIL/cv2/np inputs and NMS\n model.half()\n names = model.module.names if hasattr(model, \"module\") else model.names\n print(\"classes : \",names)\n colors = [[random.randint(0, 255) for _ in range(3)] for _ in range(len(names))]\n while True:\n t = time.time()\n im0 = recv_img_from(cam_client)\n h,w=im0.shape[:2]\n \n img = preprocessing(im0)\n h_,w_=640,640\n \n # Inference\n prediction = model(img)[0]\n prediction = non_max_suppression(prediction)\n prediction = prediction[0].cpu().numpy()\n bboxes = []\n for pred in prediction:\n if pred is not None:\n x1 = min(1,max(0,float(pred[0]/w_)))\n y1 = min(1,max(0,float(pred[1]/h_)))\n x2 = min(1,max(0,float(pred[2]/w_)))\n y2 = min(1,max(0,float(pred[3]/h_)))\n cls = int(pred[-1])\n bboxes.append([x1, y1, x2, y2, cls])\n\n msgs=''\n if len(bboxes) != 0:\n for box in bboxes:\n msg=\"{0:0.4f},{1:0.4f},{2:0.4f},{3:0.4f},{4}\".format(box[0],box[1],box[2],box[3],box[4])\n msgs=msgs+msg+'!'\n # print(\"bboxes :\",bboxes)\n # print(\"msgs :\",msgs)\n # print(\"msgs length:\",len(msgs))\n # send_image_to(im0,cam_client,dsize=(480, 320))\n send_msg_to(msgs,msg_client)\n dt = time.time()-t\n print(\"fps :{0:0.3f}\".format(1/dt))","sub_path":"yolov5_simple.py","file_name":"yolov5_simple.py","file_ext":"py","file_size_in_byte":4236,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"388167043","text":"\n\n#calss header\nclass _DETRITUS():\n\tdef __init__(self,): \n\t\tself.name = \"DETRITUS\"\n\t\tself.definitions = [u'waste material or rubbish, especially left after a particular event: ', u'a loose mass of decaying material']\n\n\t\tself.parents = []\n\t\tself.childen = []\n\t\tself.properties = []\n\t\tself.jsondata = {}\n\n\n\t\tself.specie = 'nouns'\n\n\n\tdef run(self, obj1 = [], obj2 = []):\n\t\treturn self.jsondata\n","sub_path":"xai/brain/wordbase/nouns/_detritus.py","file_name":"_detritus.py","file_ext":"py","file_size_in_byte":391,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"101767818","text":"def get_answers_tree(project, snapshot=None):\n\n values = {}\n valuesets = {}\n\n # first we loop over all values of this snapshot\n # the values are gathered in one nested dict {attribute_id: set_index: collection_index: value}\n # additionally all values with an attribute labeled 'id' are collected in a dict {attribute.parent.id: value.text}\n\n for value in project.values.filter(snapshot=snapshot):\n if value.attribute:\n # put values in a dict labled by the values attibute id, the set_index and the collection_index\n if value.attribute.id not in values:\n values[value.attribute.id] = {}\n if value.set_index not in values[value.attribute.id]:\n values[value.attribute.id][value.set_index] = {}\n if value.collection_index not in values[value.attribute.id][value.set_index]:\n values[value.attribute.id][value.set_index][value.collection_index] = {}\n\n values[value.attribute.id][value.set_index][value.collection_index] = value\n\n # put all values with an attribute labeled 'id' in a valuesets dict labeled by the parent attribute entities id\n if value.attribute.key == 'id':\n if value.attribute.parent.id not in valuesets:\n valuesets[value.attribute.parent.id] = {}\n\n valuesets[value.attribute.parent.id][value.set_index] = value.text\n\n # then we loop over sections, subsections and entities to collect questions and answers\n\n sections = []\n for catalog_section in project.catalog.sections.order_by('order'):\n subsections = []\n for catalog_subsection in catalog_section.subsections.order_by('order'):\n entities = []\n for catalog_entity in catalog_subsection.entities.filter(question__parent=None).order_by('order'):\n\n if catalog_entity.attribute_entity:\n\n if catalog_entity.is_set:\n\n attribute_entity = catalog_entity.attribute_entity\n\n if attribute_entity.parent_collection or attribute_entity.is_collection:\n\n if attribute_entity.parent_collection:\n collection = attribute_entity.parent_collection\n else:\n collection = attribute_entity\n\n questions = []\n for catalog_question in catalog_entity.questions.order_by('order'):\n\n # for a questionset collection loop over valuesets\n if collection.id in valuesets:\n\n sets = []\n for set_index in valuesets[collection.id]:\n valueset = valuesets[collection.id][set_index]\n\n # try to get the values for this question's attribute_entity and set_index\n answers = get_answers(values, catalog_question.attribute_entity.id, set_index)\n\n if answers:\n sets.append({\n 'id': valueset,\n 'answers': answers\n })\n\n if sets:\n questions.append({\n 'sets': sets,\n 'text': catalog_question.text,\n 'attribute': catalog_question.attribute_entity.attribute,\n 'is_collection': catalog_question.attribute_entity.is_collection or catalog_question.widget_type == 'checkbox'\n })\n\n if questions:\n entities.append({\n 'questions': questions,\n 'attribute': catalog_entity.attribute_entity,\n 'is_set': True,\n 'is_collection': True,\n })\n\n else:\n # # for a questionset loop over questions\n questions = []\n for catalog_question in catalog_entity.questions.order_by('order'):\n\n # try to get the values for this question's attribute_entity\n answers = get_answers(values, catalog_question.attribute_entity.id)\n\n if answers:\n questions.append({\n 'text': catalog_question.text,\n 'attribute': catalog_question.attribute_entity.attribute,\n 'answers': answers,\n 'is_collection': catalog_question.attribute_entity.is_collection or catalog_question.widget_type == 'checkbox'\n })\n\n if questions:\n entities.append({\n 'questions': questions,\n 'attribute': catalog_entity.attribute_entity,\n 'is_set': True,\n 'is_collection': False\n })\n\n else:\n # for a question just collect the answer\n\n # try to get the values for this question's attribute_entity\n answers = get_answers(values, catalog_entity.attribute_entity.id)\n\n if answers:\n entities.append({\n 'text': catalog_entity.question.text,\n 'attribute': catalog_entity.attribute_entity.attribute,\n 'answers': answers,\n 'is_set': False,\n 'is_collection': catalog_entity.attribute_entity.is_collection or catalog_entity.question.widget_type == 'checkbox'\n })\n\n if entities:\n subsections.append({\n 'title': catalog_subsection.title,\n 'entities': entities\n })\n\n if subsections:\n sections.append({\n 'title': catalog_section.title,\n 'subsections': subsections\n })\n\n return {'sections': sections}\n\n\ndef get_answers(values, attribute_id, set_index=0):\n answers = []\n\n try:\n for collection_index, value in sorted(values[attribute_id][set_index].items()):\n answers.append(value.value_and_unit)\n except KeyError:\n pass\n\n return answers\n","sub_path":"rdmo/projects/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":7081,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"142758141","text":"import cv2\n\nimage = cv2.imread('image.jpg')\ngrayscale = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)\ncv2.imshow('grayscale', grayscale)\ncv2.waitKey(0)\n# aplicar limiarização\nret, threshhold = cv2.threshold(grayscale, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)\ncv2.imshow('threshhold', threshhold)\ncv2.waitKey(0)\nkernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, 10))\nfor i in range(10):\n erosao = cv2.erode(threshhold, kernel, iterations=i)\n cv2.imshow('erosao', erosao)\n cv2.waitKey(1000)\n","sub_path":"40/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":507,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"467991258","text":"from django.conf.urls import url, include\nfrom django.contrib import admin\n\n\"\"\"\n一级级路由\n\n\"\"\"\n# alt + 回车\nurlpatterns = [\n url('admin/', admin.site.urls),\n url('1/', include('model01.urls')),\n url('2/', include('model02.urls')),\n]\n","sub_path":"Django02/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":250,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"622348550","text":"from django.http import HttpResponse, HttpResponseRedirect, HttpResponseBadRequest\nfrom django.shortcuts import render, get_object_or_404\nfrom django.core.urlresolvers import reverse\nfrom turnos.models import Person, Department, Role, Calendar, Event\nfrom .forms import DepartmentForm, RoleForm, FormRole, FormPersonNew, CalendarForm\nfrom django.template import RequestContext, loader\nfrom django.shortcuts import redirect\nfrom django.forms.formsets import formset_factory\nfrom django.contrib.auth.decorators import login_required\nfrom django.contrib.auth.models import User\nfrom django.views.generic import TemplateView\nimport json\nfrom django.views.decorators.csrf import csrf_exempt\n\n\"\"\"\n\nclass NewTurn(TemplateView):\n template_name = 'admin/department_turn.html'\n form = CalendarForm()\n\n def get_context_data(self, *args, **kwargs):\n context = super(NewTurn, self).get_context_data(**kwargs)\n\n pk = self.kwargs.get('pk', None)\n new_month = self.kwargs.get('month', None)\n\n persons = Person.objects.filter(department__id=pk).values('name', 'first_surname').order_by('name')\n calendars = Calendar.objects.filter(department__id=pk).order_by('month')\n department = Department.objects.get(pk=pk)\n context.update(form=CalendarForm())\n\n extra_context = {'person_list': persons,\n 'group':department,\n 'calendars': calendars}\n\n for key, value in extra_context.items():\n if callable(value):\n context[key] = value()\n else:\n context[key] = value\n\n return context\n\n @csrf_exempt\n def dispatch(self, *args, **kwargs):\n return super(NewTurn, self).dispatch(*args, **kwargs)\n\n\n def post(self, request, *args, **kwargs):\n if not request.is_ajax():\n return HttpResponseBadRequest('Expected an XMLHttpRequest')\n\n in_data = json.loads(request.body)\n form = CheckoutForm(data={'subject': in_data.get('subject')})\n\n if form.is_valid():\n new_calendar = form.save(commit=False)\n department = Department.objects.get(pk=pk)\n new_calendar.department = department\n new_calendar.save()\n\n return HttpResponseRedirect(reverse('audiovisual.views.DepartmentTurn',\n args=(pk, new_calendar.id)))\n\n\"\"\"\n\n@login_required(login_url='/admin/login')\ndef controls(request):\n users = User.objects.all()\n context = {'user_list':users}\n return render(request, 'admin/panel_de_control.html', context)\n\n@login_required(login_url='/admin/login')\ndef DepartmentIndex(request):\n department_list = Department.objects.order_by('title')\n RoleFormset = formset_factory(RoleForm, extra=3)\n form = DepartmentForm()\n formset = RoleFormset()\n\n if request.method == \"POST\":\n # save button pressed\n if 'save' in request.POST:\n print('save button pressed')\n form = DepartmentForm(request.POST)\n formset = RoleFormset(request.POST, request.FILES)\n\n if form.is_valid() and formset.is_valid():\n title = form.cleaned_data['title']\n\n # create a new department\n new_department = Department.objects.create(title = title)\n\n for form in formset:\n data = form.cleaned_data\n title = data.get('title')\n\n # if not empty\n if title:\n Role.objects.create(department=new_department, title=title)\n\n\n form = DepartmentForm()\n formset = RoleFormset()\n pass\n\n # Cancel button pressed\n elif 'cancel' in request.POST:\n form = DepartmentForm()\n formset = RoleFormset()\n print('cancel button pressed')\n\n # method = GET\n else:\n form = DepartmentForm()\n formset = RoleFormset()\n\n context= {'department_list' : department_list, 'form':form, 'formset':formset}\n return render(request, 'admin/department_index.html', context)\n\n# Page for roles in a particular department with id = pk\n@login_required(login_url='/admin/login')\ndef DepartmentRole(request, pk):\n department = get_object_or_404(Department, pk=pk)\n\n if request.method == \"POST\":\n # save button pressed\n if 'save' in request.POST:\n print('save button pressed')\n form = FormRole(request.POST)\n\n if form.is_valid():\n title = form.cleaned_data['title']\n\n # create a new Role\n Role.objects.create(department=department, title=title)\n\n # generate a new form for redirection\n form = FormRole()\n\n # Get all Roles belonging to the Department with id = pk\n roles = Role.objects.filter(department = department)\n\n # Cancel button pressed\n elif 'cancel' in request.POST:\n form = FormRole()\n\n # Get all Roles belonging to the Department with id = pk\n roles = department.role_set.all()\n print('cancel button pressed')\n\n # method = GET\n else:\n form = FormRole()\n\n # Get all Roles belonging to the Department with id = pk\n roles = Role.objects.filter(department = department)\n\n # Display the roles page with empty role\n context= {'role_list':roles, 'department':department, 'form':form}\n return render(request, 'admin/department_rol.html', context)\n\n@login_required(login_url='/admin/login')\ndef DepartmentPerson(request, pk):\n person_list = Person.objects.filter(department__id=pk)\n department = get_object_or_404(Department, pk=pk)\n context= {'person_list' : person_list, 'department':department}\n return render(request, 'admin/department_members.html', context)\n\n@login_required(login_url='/admin/login')\ndef DepartmentTurn(request, pk, month=0, new_month=True, new_event=False):\n persons = Person.objects.filter(department__id=pk).values('name', 'first_surname').order_by('name')\n calendars = Calendar.objects.filter(department__id=pk).order_by('month')\n department = Department.objects.get(pk=pk)\n #events = Event.objects.filter(calendar__month=month).order_by('date')\n form = CalendarForm()\n\n if request.method == \"POST\":\n # save button pressed\n if 'save' in request.POST:\n print('save button pressed')\n form = CalendarForm(request.POST)\n\n if form.is_valid():\n new_calendar = form.save(commit=False)\n department = Department.objects.get(pk=pk)\n new_calendar.department = department\n new_calendar.save()\n\n return HttpResponseRedirect(reverse('audiovisual.views.DepartmentTurn',\n args=(pk, new_calendar.id)))\n elif 'cancel' in request.POST:\n new_month = False\n\n context= { 'person_list': persons,\n 'form':form,\n 'group':department,\n 'calendars': calendars,\n 'new_month': new_month,\n 'new_event': new_event}\n return render(request, 'admin/department_turn.html', context)\n\n\n# Page for all persons\n@login_required(login_url='/admin/login')\ndef PersonIndex(request):\n person_list = Person.objects.all()[:15]\n context= {'person_list' : person_list}\n return render(request, 'admin/personas.html', context)\n\n# Page for a particular person\n@login_required(login_url='/admin/login')\ndef PersonDetail(request, pk):\n person = get_object_or_404(Person, pk=pk)\n context = {'person':person}\n return render(request, 'admin/person_detail.html', context)\n\n# Page to edit a person\n@login_required(login_url='/admin/login')\ndef PersonEdit(request, pk):\n person = get_object_or_404(Person, pk=pk)\n form = FormPersonNew(instance=person)\n\n if request.method == \"POST\":\n # save button pressed\n if 'save' in request.POST:\n form = FormPersonNew(request.POST, instance=person)\n\n if form.is_valid():\n form.save()\n\n\n return HttpResponseRedirect(reverse('audiovisual.views.PersonDetail', args=(pk,)))\n\n # Display the edit person page\n context= {'form':form}\n return render(request, 'admin/person_edit.html', context)\n\n\n# Page to edit a person\n@login_required(login_url='/admin/login')\ndef PersonClear(request, pk):\n return render(request, 'admin/detalle.html')\n\n\n\n@login_required(login_url='/admin/login')\ndef PersonNew(request):\n form = FormPersonNew()\n\n if request.method == \"POST\":\n # save button pressed\n if 'save' in request.POST or 'save_new' in request.POST:\n print('save button pressed')\n form = FormPersonNew(request.POST)\n\n if form.is_valid():\n form.save()\n\n # generate a new form for redirection\n form = FormPersonNew()\n\n if 'save_new' in request.POST:\n # return to the create page\n return HttpResponseRedirect(reverse('audiovisual.views.PersonNew'))\n\n elif 'cancel' in request.POST:\n # return to the list of persons\n return HttpResponseRedirect(reverse('audiovisual.views.PersonIndex'))\n\n # Display the roles page with empty or error filled form\n context= {'form':form}\n return render(request, 'admin/person_create.html', context)\n\n\n@login_required(login_url='/admin/login')\ndef details(request):\n return render(request, 'admin/detalle.html')\n\n@login_required(login_url='/admin/login')\ndef turns(request):\n return render(request, 'admin/detalle.html')\n\n# Page for all roles in all department\n@login_required(login_url='/admin/login')\ndef RoleIndex(request):\n role_list = Role.objects.all()[:15]\n context= {'role_list' : role_list}\n return render(request, 'admin/roles_index.html', context)\n","sub_path":"audiovisual/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":9205,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"460891638","text":"#!/bin/python3\n\nimport math\nimport os\nimport random\nimport re\nimport sys\n\n\n#\n# Complete the 'birthdayCakeCandles' function below.\n#\n# The function is expected to return an INTEGER.\n# The function accepts INTEGER_ARRAY candles as parameter.\n#\n\ndef birthdayCakeCandles(candles):\n count1 = {}\n count2 = 0\n candles.sort()\n for num in candles:\n if num in count1:\n count1[num] += 1\n else:\n count1[num] = 1\n\n k = list(count1.keys())[-1]\n print(count1[k])\n\n # Write your code here\n\n\nif __name__ == '__main__':\n\n\n candles_count = int(input().strip())\n\n candles = list(map(int, input().rstrip().split()))\n n = len(candles)\n\n result = birthdayCakeCandles(candles)\n\n\n\n\n","sub_path":"Mix Questions/candle_plm.py","file_name":"candle_plm.py","file_ext":"py","file_size_in_byte":726,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"82"}
+{"seq_id":"32191822","text":"# -*- coding: utf-8 -*-\nfrom odoo import models, api, _\n\n\nclass SaleAdvancePaymentInv(models.TransientModel):\n _inherit = \"sale.advance.payment.inv\"\n\n @api.multi\n def _create_invoice(self, order, so_line, amount):\n invoice = super(SaleAdvancePaymentInv, self)._create_invoice(order, so_line, amount)\n if invoice:\n invoice.action_invoice_open()\n","sub_path":"bi_automatic_invoice_validate/models/sale_advance_payment_inv.py","file_name":"sale_advance_payment_inv.py","file_ext":"py","file_size_in_byte":378,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"623041082","text":"import json\nfrom selenium import webdriver\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.support import expected_conditions as EC\nfrom selenium.common.exceptions import NoSuchElementException\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom selenium.webdriver.common.keys import Keys\nfrom time import sleep\nfrom modules.caps_client import CapsClient\n\nfrom credentials import cookies\nfrom config import Config\n\n\nclass EmailChecker:\n\n def __init__(self):\n\n self.cap = CapsClient()\n self.cred = self._get_cookies()\n options = webdriver.ChromeOptions()\n options.add_argument(\"--start-maximized\")\n options.add_argument(\"--disable-infobars\")\n # options.add_argument(\"--incognito\")\n # options.add_argument('--proxy-server=socks://' + self.cred['proxy_host'] + ':' + self.cred['proxy_port'])\n options.add_argument(\"--proxy-server={}\".format(self._get_proxy()))\n\n print(\"proxy: {}\".format(self._get_proxy()))\n\n self.Cookies = json.loads(self.cred['cookies'])\n\n # chrome webdriver\n # self.driver = webdriver.Chrome(options=options)\n\n # remote webdriver\n self.driver = webdriver.Remote(\n command_executor=Config.SELENIUM_URI,\n desired_capabilities=options.to_capabilities(),\n )\n\n # self.EMAILFIELD = (By.ID, \"identifierId\")\n # self.PASSWORDFIELD = (By.NAME, \"password\")\n # self.NEXTBUTTON = (By.ID, \"identifierNext\")\n # self.PNEXTBUTTON = (By.ID, \"passwordNext\")\n self.SEARCHFIELD = (By.NAME, \"q\")\n self.SUBMIT = (By.CLASS_NAME, \"gbqfb\")\n\n # random proxy based on chosen filters\n def _get_proxy(self):\n\n try:\n random_proxy = self.cap.get_proxy_random(type='socks5')\n return \"socks5://{}:{}\".format(random_proxy['host'], random_proxy['port'])\n\n except:\n return 'socks5://5.39.20.153:25567'\n\n def _get_cookies(self):\n credential = self.cap.get_credential_random('google')\n return {'cookies': cookies['cookies']}\n\n def checker(self, emailId):\n\n url = \"https://gmail.com/\"\n self.driver.get(\"https://google.com\")\n\n for cookie in self.Cookies:\n cookie_dict = {'domain': cookie['domain'], 'secure': cookie['secure'], 'value': cookie['value'],\n 'name': cookie['name'], 'httpOnly': cookie['httpOnly'], 'storeId': cookie['storeId'],\n 'path': cookie['path'], 'session': cookie['session'], 'hostOnly': cookie['hostOnly'],\n 'sameSite': cookie['sameSite'], 'id': cookie['id']}\n try:\n if cookie['expirationDate']:\n cookie_dict['expirationDate'] = cookie['expirationDate']\n # print(cookie['expirationDate'])\n except:\n pass\n # print(cookie_dict)\n self.driver.add_cookie(cookie_dict)\n sleep(0.5)\n self.driver.get('https://gmail.com')\n\n # print(emailId)\n #\n WebDriverWait(self.driver, 10).until(EC.element_to_be_clickable(self.SEARCHFIELD)).send_keys(emailId)\n # WebDriverWait(self.driver, 10).until(EC.element_to_be_clickable(self.SUBMIT)).click()\n self.driver.find_element_by_name('q').send_keys(Keys.ENTER)\n # WebDriverWait(self.driver, 10).until(EC.element_to_be_clickable(self.PASSWORDFIELD)).send_keys(passd)\n # WebDriverWait(self.driver, 10).until(EC.element_to_be_clickable(self.PNEXTBUTTON)).click()\n # # print(\"%s seconds\" % (time.time() - start_time))\n sleep(3)\n try:\n\n # # googleplusid\n try:\n mailid1 = self.driver.find_element_by_xpath('//*[@id=\":2\"]/div/div[2]/div[4]/div[1]/div[2]/div[1]/div[1]')\n except NoSuchElementException:\n mailid1 = self.driver.find_element_by_xpath('//*[@id=\":1\"]/div/div[2]/div[4]/div[1]/div[2]/div[1]/div[1]')\n # # sleep(0.5)\n # print(mailid1)\n # e = mailid1.get_attribute('href')\n # image on google account\n try:\n image = self.driver.find_element_by_xpath('//*[@id=\":2\"]/div/div[2]/div[4]/div[1]/div[1]/img')\n except NoSuchElementException:\n image = self.driver.find_element_by_xpath('//*[@id=\":1\"]/div/div[2]/div[4]/div[1]/div[1]/img')\n img = image.get_attribute('src')\n # print(e)\n # name of the user\n name = mailid1.text\n self.driver.quit()\n\n return {'email': True,\n 'email_id': emailId,\n # 'googlePlusId': e[24:],\n 'name': name,\n 'image': img}\n except:\n self.driver.quit()\n return {'email': False}\n\n # # try:\n # mailid1 = self.driver.find_element_by_xpath('//*[@id=\"app__container\"]/div[2]/header')\n # sleep(0.5)\n # print(mailid1.text)\n # self.driver.quit()\n #\n # return {'mailid': False}\n # except:\n # mailid = self.driver.find_element_by_xpath('//*[@id=\"signup_magiclink\"]/div[1]/div/h1/p')\n # sleep(2)\n # print(mailid.text)\n # self.driver.quit()\n #\n # return {'mailid': True}\n\n\nif __name__ == '__main__':\n obj = EmailChecker()\n # print(obj.checker('veronikascott27@gmail.com'))\n print(obj.checker('justinmat1994@gmail.com'))\n # print(obj.checker('justinmat199@gmail.com'))\n\n","sub_path":"google-api/modules/emailChecker.py","file_name":"emailChecker.py","file_ext":"py","file_size_in_byte":5560,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"589459548","text":"import cv2, time\n\nvideo=cv2.VideoCapture(0)\n\na=0\n\n#while loop -> ctr c to stop (or z if ctr c doesn't work)\n#while loop bc you want to have string of pics.\nwhile True:\n a=a+1\n check, frame = video.read()\n\n print(check)\n print(frame)\n\n gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)\n #time.sleep(3) -> if you use cv2.waitKey for a specific time (not 0 to stop with the button as before) you don't need this command anymore\n cv2.imshow(\"Capturing\", gray)\n\n key=cv2.waitKey(1)\n\n if key==ord('q'):\n break\nprint(a)\n#it's to check how many iterations you have \n\nvideo.release()\ncv2.destroyAllWindows()\n","sub_path":"MotionDetector/video_creation.py","file_name":"video_creation.py","file_ext":"py","file_size_in_byte":627,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"160432691","text":"from datetime import datetime\nfrom ftw.testing import freeze\nfrom opengever.testing import IntegrationTestCase\nfrom opengever.testing.helpers import index_data_for\nfrom opengever.trash.trash import ITrasher\nfrom plone import api\n\n\nclass TestCatalog(IntegrationTestCase):\n\n def test_trashed_index_registered(self):\n self.assertIn('trashed', api.portal.get_tool('portal_catalog').indexes())\n\n def test_modified_index_gets_updated_when_trashing(self):\n self.login(self.regular_user)\n\n with freeze(datetime(2014, 5, 7, 12, 30)) as clock:\n ITrasher(self.subsubdocument).trash()\n clock.forward(minutes=5)\n\n ITrasher(self.taskdocument).trash()\n clock.forward(minutes=5)\n\n ITrasher(self.document).trash()\n clock.forward(minutes=5)\n\n ITrasher(self.subdocument).trash()\n\n catalog = api.portal.get_tool('portal_catalog')\n modified_idx = catalog._catalog.indexes['modified']\n\n def modified_idx_value(obj):\n return index_data_for(obj)['modified']\n\n def to_idx_value(value):\n return modified_idx._convert(value)\n\n self.assertEqual(\n to_idx_value(datetime(2014, 5, 7, 12, 30)),\n modified_idx_value(self.subsubdocument))\n\n self.assertEqual(\n to_idx_value(datetime(2014, 5, 7, 12, 35)),\n modified_idx_value(self.taskdocument))\n\n self.assertEqual(\n to_idx_value(datetime(2014, 5, 7, 12, 40)),\n modified_idx_value(self.document))\n\n self.assertEqual(\n to_idx_value(datetime(2014, 5, 7, 12, 45)),\n modified_idx_value(self.subdocument))\n","sub_path":"opengever/trash/tests/test_catalog.py","file_name":"test_catalog.py","file_ext":"py","file_size_in_byte":1685,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"240340995","text":"# Singly-linked lists are already defined with this interface:\n# class ListNode(object):\n# def __init__(self, x):\n# self.value = x\n# self.next = None\n#\ndef isListPalindrome(l):\n a = []\n while l != None:\n a.append(l.value)\n l = l.next\n return a == a[::-1]","sub_path":"Interview_Practice/LinkedList/isListPalindrome.py","file_name":"isListPalindrome.py","file_ext":"py","file_size_in_byte":287,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"115129685","text":"# List Comprehension\n# ls = [i for i in range(100) if i%3 == 0]\n# print(ls)\n#\n# ls = [i for i in range(0,100,3) ]\n# print(ls)\n#\n# # Print dictionary 0:item0, 1:item1..\n# dict = { i:f\"item{i}\" for i in range(5) }\n# print(dict)\n#\n# # Reverse of above dict\n# dict1 = {value:key for key,value in dict.items()}\n# print(dict1)\n\n# Generator Comprehension\n# evens = (i for i in range(40) if i%2==0)\n# print(evens)\n# print(type(evens))\n# print(evens.__next__())\n# print(evens.__next__())\n# print(evens.__next__())\n\n#Q Take numbers in input as a list, ask for which type of comprehension want ??\n# ..convert them to that comprehension.\n\nlst = input(\"Enter the number\")\nlst = lst.split(' ')\n# print(type(lst))\n# print(lst)\n# lst=[i for i in input(\"enter element\").split(' ')]\n\nchoice = int(input(\"Enter -\\n 1 for List comprehension \\n 2 for Set comprehension \\n 3 for Dictionary comprehension\"))\nif choice ==1:\n lst1 = [i for i in lst]\n print(lst1)\nelif choice == 2:\n sett = { i for i in lst}\n print(sett)\nelse:\n dict_user = {l: f\"You are awesome programmer\" for l in lst}\n print(dict_user)\n\n","sub_path":"Comprehension-file.py","file_name":"Comprehension-file.py","file_ext":"py","file_size_in_byte":1099,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"474824280","text":"import copy\n\nfrom game.player import Player\nimport game.constants as const\n\n\nclass MisterX(Player):\n def __init__(self, game, name, blackCards=2, doubleMoveCards=2):\n super().__init__(game, name, busCard=3, taxiCard=4, undergroundCard=3)\n\n # Black cards hide used transportation method from the detectives\n # 2x cards can be used to move twice in one turn\n self.cards.update({\n 'black': blackCards,\n 'double': doubleMoveCards,\n })\n self.originalCards = copy.deepcopy(self.cards)\n\n self.doubleMoves = []\n \n @property\n def lastKnownPosition(self):\n try:\n idx = max([i - 1 for i in const.MRX_OPEN_TURNS if i - 1 < len(self.history)])\n except ValueError:\n # max from an empty sequence\n return None\n return self.history[idx][-1]\n\n def __str__(self):\n \"Overwite the string method of base class Player for consistency\"\n return \"Mr. X\"\n\n def cloneFrom(self, old):\n super().cloneFrom(old)\n self.doubleMoves = [m for m in old.doubleMoves]\n\n def clone(self, game=None):\n if game is None:\n game = self.game\n new = type(self)(game, self.name)\n new.cloneFrom(self)\n return new\n\n def reset(self):\n super().reset()\n self.doubleMoves = []\n","sub_path":"game/misterx.py","file_name":"misterx.py","file_ext":"py","file_size_in_byte":1352,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"313041048","text":"import sys\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport glob\r\n\r\ntimeout = 600\r\nlength = 500\r\nmin_points = 1\r\nnpop = 25\r\ndef getData(files):\r\n\tavg = []\r\n\tdata = []\r\n\tN = 0\r\n\tfor i in range(0,len(files)):\r\n\t\ttry:\r\n\t\t\tfiledata = np.loadtxt(files[i])\r\n\t\t\tif isinstance(filedata,np.ndarray) and len(filedata.shape) == 1 and filedata.shape[0] >= min_points:\r\n\t\t\t\tdata.append(filedata)\r\n\t\t\telse:\r\n\t\t\t\tprint(\"Warning - Bad input: \" + files[i])\r\n\t\texcept ValueError:\r\n\t\t\tprint(\"Bad data in \" + str(files[i]))\r\n\t\t\r\n\t\tif len(data) > 0:\r\n\t\t\tN = max(N,len(data[-1]))\r\n\tN =min(N,npop)\r\n\tfor i in range(N):\r\n\t\tfor j in range(len(data)):\r\n\t\t\tif i < len(data[j]):\r\n\t\t\t\tif data[j][i] >= timeout and data[j][i] < timeout + 30:\r\n\t\t\t\t\tdata[j][i] = timeout\r\n\t\t\t\t\t#assert len(data[j]) == i + 1 , \"wtf\"\r\n\t\t\t\t\twhile len(data[j]) < npop:\r\n\t\t\t\t\t\t#data[j].append(timeout)\r\n\t\t\t\t\t\tdata[j] = np.append(data[j],timeout)\r\n\t\t\t\t\tbreak\r\n\t\t\telif i == len(data[j]):\r\n\t\t\t\tdata[j] = np.append(data[j],data[j][-1])\r\n\t\tx = 0.0\r\n\t\tm=0.0\r\n\t\tfor j in range(len(data)):\r\n\t\t\tif i < len(data[j]):\r\n\t\t\t\tx += data[j][i]\r\n\t\t\t\tm += 1.0\r\n\t\t\t\tif data[j][i] > 605:\r\n\t\t\t\t\tprint(x,files[j])\r\n\t\t\t\t\tprint(data[j])\r\n\t\t\t\t\tsys.exit(1)\r\n\t\tavg.append(x/m)\r\n\treturn avg\r\n\r\ndir = \"../data/7_28_test_mathvz3/\"\t\r\n\t\r\nscores = []\r\nscores.append(getData(glob.glob(dir + \"run*random*.txt\")))\r\nscores.append(getData(glob.glob(dir + \"run*Eps*.txt\")))\t\t\r\nscores.append(getData(glob.glob(dir + \"run*Thomp*.txt\")))\r\nscores.append(getData(glob.glob(dir + \"run*UCB*.txt\")))\r\nplt.plot(scores[0],label = \"Random\")\r\nplt.plot(scores[1],label = \"Epsilon\")\r\nplt.plot(scores[2],label = \"Thompson\")\r\nplt.plot(scores[3],label = \"UCB\")\r\nplt.legend()\r\nplt.show()\r\n","sub_path":"plots/parse_dump_exp2.py","file_name":"parse_dump_exp2.py","file_ext":"py","file_size_in_byte":1690,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"512530820","text":"import threading\r\n\r\n\r\nclass HeadPhone(threading.Thread):\r\n def run(self):\r\n for _ in xrange(10):\r\n print(threading.current_thread().getName())\r\n\r\nx = HeadPhone(name='send')\r\ny = HeadPhone(name='recv')\r\nx.start()\r\ny.start()\r\n","sub_path":"HeadPhone/sandbox.py","file_name":"sandbox.py","file_ext":"py","file_size_in_byte":245,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"386387866","text":"import dill\n\nname = 'cart69'\n\nwith open('./'+name+'.dill', 'rb') as f:\n out = dill.load(f)\n\n\n# for set in range(0, 10):\ndata = out['problem_data']\nsol = out['solution'][-1][-1]\n\nsol.prepare(data)\n\nwriteList = []\n\nfor state in data['state_list']:\n x = sol.evaluate(state)\n writeList.append(x)\n # print(x)\n\n# print(sol.evaluate('xb'))\n# print(sol.evaluate('yb'))\n\nu = sol.evaluate('w')\nwriteList.append(u)\n\nt = sol.evaluate('t')\nwriteList.append(t)\n# print(t)\n\n# print(writeList)\n\nwith open(name+\".txt\", \"w\") as my_file:\n for set in writeList:\n for element in set:\n my_file.write(str(element) + ' ')\n my_file.write('\\n\\n')\n","sub_path":"examples/Nolan/AFRL/Carts/export.py","file_name":"export.py","file_ext":"py","file_size_in_byte":663,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"555559367","text":"from kivy.app import App\nfrom kivy.properties import ObjectProperty, StringProperty, BooleanProperty\nfrom kivy.uix.gridlayout import GridLayout\n\nfrom generalcommands import to_bool\nfrom generalconstants import containers_friendly, video_codecs_friendly, audio_codecs_friendly\nfrom generalElements.buttons.MenuButton import MenuButton\nfrom generalElements.dropDowns.NormalDropDown import NormalDropDown\n\nfrom kivy.lang.builder import Builder\n\nBuilder.load_string(\"\"\"\n:\n padding: 0, 0, int(app.button_scale / 2), 0\n cols: 1\n size_hint: 1, None\n height: self.minimum_height\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n WideButton:\n text: 'Convert'\n on_release: root.encode()\n WideButton:\n text: 'Cancel Edit'\n warn: True\n on_release: root.owner.set_edit_panel('main')\n MediumBufferY:\n NormalLabel:\n text: 'Convert Video:'\n MenuStarterButtonWide:\n text: 'Presets'\n size_hint_x: 1\n on_release: root.preset_drop.open(self)\n GridLayout:\n canvas.before:\n Color:\n rgba: app.theme.area_background\n BorderImage:\n pos: self.pos\n size: self.size\n source: 'data/buttonflat.png'\n padding: app.padding\n cols: 1\n size_hint: 1, None\n height: self.minimum_height\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: 'Container:'\n MenuStarterButtonWide:\n size_hint_x: 1\n text: root.file_format\n on_release: root.container_drop.open(self)\n SmallBufferY:\n NormalToggle:\n id: resize\n size_hint_x: 1\n state: 'down' if root.resize else 'normal'\n text: 'Resize' if self.state == 'down' else 'No Resize'\n on_release: root.update_resize(self.state)\n BoxLayout:\n disabled: not root.resize\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n ShortLabel:\n text: 'Size:'\n NormalInput:\n id: widthInput\n hint_text: '1920'\n multiline: False\n text: root.resize_width\n on_text: root.set_resize_width(self)\n ShortLabel:\n text: 'x'\n NormalInput:\n id: heightInput\n hint_text: '1080'\n multiline: False\n text: root.resize_height\n on_text: root.set_resize_height(self)\n SmallBufferY:\n NormalToggle:\n id: deinterlace\n size_hint_x: 1\n state: 'down' if root.deinterlace else 'normal'\n text: 'Deinterlace' if self.state == 'down' else 'No Deinterlace'\n on_release: root.update_deinterlace(self.state)\n SmallBufferY:\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: 'Video Codec:'\n MenuStarterButtonWide:\n size_hint_x: 1\n text: root.video_codec\n on_release: root.video_codec_drop.open(self)\n id: videoCodecDrop\n #BoxLayout:\n # orientation: 'horizontal'\n # size_hint_y: None\n # height: app.button_scale\n # LeftNormalLabel:\n # text: 'Video Quality:'\n # MenuStarterButtonWide:\n # size_hint_x: 1\n # text: root.video_quality\n # on_release: root.video_quality_drop.open(self)\n # id: videoQualityDrop\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: 'Encoding Speed:'\n MenuStarterButtonWide:\n size_hint_x: 1\n text: root.encoding_speed\n on_release: root.encoding_speed_drop.open(self)\n id: encodingSpeedDrop\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: 'Video Bitrate:'\n FloatInput:\n id: videoBitrateInput\n text: root.video_bitrate\n\n SmallBufferY:\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: 'Audio Codec:'\n MenuStarterButtonWide:\n size_hint_x: 1\n text: root.audio_codec\n on_release: root.audio_codec_drop.open(self)\n id: audioCodecDrop\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: 'Audio Bitrate:'\n FloatInput:\n id: audioBitrateInput\n text: root.audio_bitrate\n SmallBufferY:\n GridLayout:\n canvas.before:\n Color:\n rgba: app.theme.area_background\n BorderImage:\n pos: self.pos\n size: self.size\n source: 'data/buttonflat.png'\n padding: app.padding\n cols: 1\n size_hint: 1, None\n height: self.minimum_height\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: \"Manual command line:\"\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: \"This will override all other settings.\"\n SmallBufferY:\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n ShortLabel:\n text: 'ffmpeg.exe '\n NormalInput:\n id: commandInput\n hint_text: '-sn %c %v %a %f %p %b %d'\n multiline: False\n text: root.command_line\n on_text: root.set_command_line(self)\n BoxLayout:\n orientation: 'horizontal'\n size_hint_y: None\n height: app.button_scale\n LeftNormalLabel:\n text: \"String Replacements:\"\n GridLayout:\n cols: 3\n size_hint: 1, None\n height: int(app.button_scale * 9)\n\n ShortLabel:\n text: '%i'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Input File (Required)'\n\n ShortLabel:\n text: '%c'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Container Setting'\n\n ShortLabel:\n text: '%v'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Video Codec Setting'\n\n ShortLabel:\n text: '%a'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Audio Codec Setting'\n\n ShortLabel:\n text: '%f'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Framerate (From Original File)'\n\n ShortLabel:\n text: '%p'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Pixel Format (From Original File)'\n\n ShortLabel:\n text: '%b'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Video Bitrate Setting'\n\n ShortLabel:\n text: '%d'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Audio Bitrate Setting'\n\n ShortLabel:\n text: '%%'\n ShortLabel:\n text: ' - '\n LeftNormalLabel:\n text: 'Single Percent Sign (%)'\n\"\"\")\n\nclass EditConvertVideo(GridLayout):\n \"\"\"Convert a video file to another format using ffmpeg.\"\"\"\n\n owner = ObjectProperty()\n\n #Encoding settings\n video_codec = StringProperty()\n audio_codec = StringProperty()\n video_quality = StringProperty()\n encoding_speed = StringProperty()\n file_format = StringProperty()\n input_file = StringProperty()\n video_bitrate = StringProperty('8000')\n audio_bitrate = StringProperty('192')\n command_line = StringProperty()\n deinterlace = BooleanProperty(False)\n resize = BooleanProperty(False)\n resize_width = StringProperty('1920')\n resize_height = StringProperty('1080')\n\n #Dropdown menus\n preset_drop = ObjectProperty()\n container_drop = ObjectProperty()\n video_codec_drop = ObjectProperty()\n video_quality_drop = ObjectProperty()\n encoding_speed_drop = ObjectProperty()\n audio_codec_drop = ObjectProperty()\n\n def __init__(self, **kwargs):\n self.setup_dropdowns()\n app = App.get_running_app()\n encoding_preset = app.config.get('Presets', 'encoding')\n if encoding_preset:\n encoding_settings = encoding_preset.split(',', 10)\n if len(encoding_settings) == 11:\n self.file_format = encoding_settings[0]\n self.video_codec = encoding_settings[1]\n self.audio_codec = encoding_settings[2]\n self.resize = to_bool(encoding_settings[3])\n self.resize_width = encoding_settings[4]\n self.resize_height = encoding_settings[5]\n self.video_bitrate = encoding_settings[6]\n self.audio_bitrate = encoding_settings[7]\n self.encoding_speed = encoding_settings[8]\n self.deinterlace = to_bool(encoding_settings[9])\n self.command_line = encoding_settings[10]\n super(EditConvertVideo, self).__init__(**kwargs)\n\n def refresh_buttons(self):\n pass\n\n def save_last(self):\n pass\n\n def load_last(self):\n pass\n\n def store_settings(self):\n encoding_preset = self.file_format+','+self.video_codec+','+self.audio_codec+','+str(self.resize)+','+self.resize_width+','+self.resize_height+','+self.video_bitrate+','+self.audio_bitrate+','+self.encoding_speed+','+str(self.deinterlace)+','+self.command_line\n app = App.get_running_app()\n app.config.set('Presets', 'encoding', encoding_preset)\n\n def setup_dropdowns(self):\n \"\"\"Creates and populates the various drop-down menus used by this dialog.\"\"\"\n\n self.preset_drop = NormalDropDown()\n app = App.get_running_app()\n for index, preset in enumerate(app.encoding_presets):\n menu_button = MenuButton(text=preset['name'])\n menu_button.bind(on_release=self.set_preset)\n self.preset_drop.add_widget(menu_button)\n\n self.file_format = containers_friendly[0]\n self.container_drop = NormalDropDown()\n for container in containers_friendly:\n menu_button = MenuButton(text=container)\n menu_button.bind(on_release=self.change_container_to)\n self.container_drop.add_widget(menu_button)\n\n self.video_codec = video_codecs_friendly[0]\n self.video_codec_drop = NormalDropDown()\n for codec in video_codecs_friendly:\n menu_button = MenuButton(text=codec)\n menu_button.bind(on_release=self.change_video_codec_to)\n self.video_codec_drop.add_widget(menu_button)\n\n #self.video_quality = 'Constant Bitrate'\n #video_qualities = ['Constant Bitrate', 'High', 'Medium', 'Low', 'Very Low']\n #self.video_quality_drop = NormalDropDown()\n #for quality in video_qualities:\n # menu_button = MenuButton(text=quality)\n # menu_button.bind(on_release=self.change_video_quality_to)\n # self.video_quality_drop.add_widget(menu_button)\n\n self.encoding_speed = 'Fast'\n encoding_speeds = ['Very Fast', 'Fast', 'Medium', 'Slow', 'Very Slow']\n self.encoding_speed_drop = NormalDropDown()\n for speed in encoding_speeds:\n menu_button = MenuButton(text=speed)\n menu_button.bind(on_release=self.change_encoding_speed_to)\n self.encoding_speed_drop.add_widget(menu_button)\n\n self.audio_codec = audio_codecs_friendly[0]\n self.audio_codec_drop = NormalDropDown()\n for codec in audio_codecs_friendly:\n menu_button = MenuButton(text=codec)\n menu_button.bind(on_release=self.change_audio_codec_to)\n self.audio_codec_drop.add_widget(menu_button)\n\n def update_deinterlace(self, state):\n if state == 'down':\n self.deinterlace = True\n else:\n self.deinterlace = False\n\n def update_resize(self, state):\n if state == 'down':\n self.resize = True\n else:\n self.resize = False\n\n def set_resize_width(self, instance):\n self.resize_width = instance.text\n self.store_settings()\n\n def set_resize_height(self, instance):\n self.resize_height = instance.text\n self.store_settings()\n\n def set_preset(self, instance):\n \"\"\"Sets the current dialog preset settings to one of the presets stored in the app.\n Argument:\n index: Integer, the index of the preset to set.\n \"\"\"\n\n self.preset_drop.dismiss()\n app = App.get_running_app()\n for preset in app.encoding_presets:\n if preset['name'] == instance.text:\n if preset['file_format'] in containers_friendly:\n self.file_format = preset['file_format']\n else:\n self.file_format = containers_friendly[0]\n if preset['video_codec'] in video_codecs_friendly:\n self.video_codec = preset['video_codec']\n else:\n self.video_codec = video_codecs_friendly[0]\n if preset['audio_codec'] in audio_codecs_friendly:\n self.audio_codec = preset['audio_codec']\n else:\n self.audio_codec = audio_codecs_friendly[0]\n self.resize = preset['resize']\n self.resize_width = preset['width']\n self.resize_height = preset['height']\n self.video_bitrate = preset['video_bitrate']\n self.audio_bitrate = preset['audio_bitrate']\n self.encoding_speed = preset['encoding_speed']\n self.deinterlace = preset['deinterlace']\n self.command_line = preset['command_line']\n self.store_settings()\n return\n\n def on_video_bitrate(self, *_):\n self.store_settings()\n\n def on_audio_bitrate(self, *_):\n self.store_settings()\n\n def set_command_line(self, instance):\n self.command_line = instance.text\n self.store_settings()\n\n def change_video_quality_to(self, instance):\n \"\"\"Sets the self.video_quality value.\"\"\"\n\n self.video_quality_drop.dismiss()\n self.video_quality = instance.text\n self.store_settings()\n\n def change_encoding_speed_to(self, instance):\n \"\"\"Sets the self.encoding_speed value.\"\"\"\n\n self.encoding_speed_drop.dismiss()\n self.encoding_speed = instance.text\n self.store_settings()\n\n def change_audio_codec_to(self, instance):\n \"\"\"Sets the self.audio_codec value.\"\"\"\n\n self.audio_codec_drop.dismiss()\n self.audio_codec = instance.text\n self.store_settings()\n\n def change_video_codec_to(self, instance):\n \"\"\"Sets the self.video_codec value.\"\"\"\n\n self.video_codec_drop.dismiss()\n self.video_codec = instance.text\n self.store_settings()\n\n def change_container_to(self, instance):\n \"\"\"Sets the self.file_format value.\"\"\"\n\n self.container_drop.dismiss()\n self.file_format = instance.text\n self.store_settings()\n\n def encode(self):\n \"\"\"Pass encoding settings to owner album screen and tell it to begin encoding process.\"\"\"\n\n #file_format = containers[containers_friendly.index(self.file_format)]\n #video_codec = video_codecs[video_codecs_friendly.index(self.video_codec)]\n #audio_codec = audio_codecs[audio_codecs_friendly.index(self.audio_codec)]\n encoding_settings = {'file_format': self.file_format,\n 'video_codec': self.video_codec,\n 'audio_codec': self.audio_codec,\n 'resize': self.resize,\n 'width': self.resize_width,\n 'height': self.resize_height,\n 'video_bitrate': self.video_bitrate,\n 'audio_bitrate': self.audio_bitrate,\n 'encoding_speed': self.encoding_speed,\n 'deinterlace': self.deinterlace,\n 'command_line': self.command_line}\n self.owner.encoding_settings = encoding_settings\n print(encoding_settings)\n self.store_settings()\n self.owner.begin_encode()","sub_path":"screenAlbum/EditConvertVideo.py","file_name":"EditConvertVideo.py","file_ext":"py","file_size_in_byte":17673,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"272067233","text":"import logging\nimport logging.handlers\nimport os\nimport traceback\nimport json\nimport time\nfrom enum import Enum\nfrom pathlib import Path\nfrom time import sleep\n\n\nfrom typing import Callable, Sequence\n\nimport pika\nimport re\nfrom pika.adapters.blocking_connection import BlockingChannel\n\nfrom innovapos.shared.data import utils\nfrom innovapos.shared.data.abstractions import AbstractDataAdapter, BaseDataAdapterParameters\nfrom innovapos.shared.data.adapters import TCPDataAdapterParameters, TCPDataAdapter, SerialDataAdapterParameters#,SerialDataAdapter\nfrom innovapos.shared.data.exceptions import NotUnderstoodException\nfrom innovapos.shared.data.utils import Singleton\nfrom innovapos.worker.clients import HardwareClient, BlockingAMQPClient\nimport datetime\nimport os\n\nclass HardwareWorkerSettings:\n def __init__(self):\n \"\"\"\n Reflects the configuration file that is read from the drive.\n By default targets the simulator and a local RabbitMQ instance\n \"\"\"\n self.machine_id = None\n self.restart_on_fail_seconds: str = None\n self.include_stacktrace: bool = False\n self.rabbitmq_incoming_connection_string: str = None\n self.rabbitmq_incoming_queue_name: str = None\n self.rabbitmq_outgoing_connection_string: str = None\n self.rabbitmq_outgoing_queue_name: str = None\n self.rabbitmq_app_gate_connection_string: str = None\n self.rabbitmq_app_gate_queue_name: str = None\n self.logging_logger_name: str = None\n self.logging_level: int = None\n self.logging_filename: str = None\n self.logging_format: str = None\n self.ccm_adapter_type: str = None\n self.ccm_connection_string: str = None\n self.mon_adapter_type: str = None\n self.mon_connection_string: str = None\n self.general_adapter = BaseDataAdapterParameters()\n self.general_adapter.send_msg_end = \"\\n\"\n self.general_adapter.recv_msg_end = \"\\n\"\n self.general_adapter.timeout = 1\n self.general_adapter.answer_delay = 1\n\n\n @staticmethod\n def parse_config_to_settings(path: str):\n \"\"\"\n Parses a settings file with its configuration. \n\n :param path: path to load configuration from\n :type path: str\n :return: loaded settings object\n :rtype: HardwareWorkerSettings\n \"\"\"\n # check that file exists. if it does not - raise\n if not path:\n raise ValueError(\"Path to config file is None\")\n else:\n from pathlib import Path\n print(f'Path {path}')\n my_file = Path(path)\n if not my_file.is_file():\n raise FileNotFoundError(\"Could not find config file at provided path\")\n from configparser import ConfigParser\n parser = ConfigParser()\n parser.read(path)\n config = HardwareWorkerSettings()\n\n # uuid from getnode is the mac address of the current machine in the case that we don't have one defined\n import uuid\n config.machine_id = utils.get_with_default(parser, \"worker\", \"machine_id\", uuid.getnode())\n config.include_stacktrace = utils.get_with_default(parser, \"worker\", \"include_stacktrace\", False)\n config.restart_on_fail_seconds = int(utils.get_with_default(parser, \"worker\", \"restart_on_fail_seconds\", 3))\n\n config.logging_level = utils.get_with_default(parser, \"logging\", \"level\", \"DEBUG\")\n config.logging_filename = utils.get_with_default(parser, \"logging\", \"filename\", 'innovapos_no_config.log')\n config.logging_format = utils.get_with_default(parser, \"logging\", \"format\",\n \"%%(asctime)s %%(name)s %%(levelname)s %%(message)s\")\n config.ccm_adapter_type = utils.get_with_default(parser, \"ccm_adapter\", \"type\", None)\n config.ccm_connection_string = utils.get_with_default(parser, \"ccm_adapter\", \"connection_string\", None)\n config.mon_adapter_type = utils.get_with_default(parser, \"mon_adapter\", \"type\", None)\n config.mon_connection_string = utils.get_with_default(parser, \"mon_adapter\", \"connection_string\", None)\n # config.general_adapter.send_msg_end = utils.get_with_default(parser, \"general_adapters\", \"send_end_char\",\n # config.general_adapter.send_msg_end)\n # config.general_adapter.recv_msg_end = utils.get_with_default(parser, \"general_adapters\", \"receive_end_char\",\n # config.general_adapter.recv_msg_end)\n # TODO: fix ini file \\n auto escape\n config.general_adapter.send_msg_end = '\\n'\n config.general_adapter.recv_msg_end = '\\n'\n\n timeout_int = int(utils.get_with_default(parser, \"general_adapters\", \"timeout\", \"2\"))\n config.general_adapter.timeout = timeout_int\n answer_delay_int = int(utils.get_with_default(parser, \"general_adapters\", \"answer_delay\", \"2\"))\n config.general_adapter.answer_delay = answer_delay_int\n conn = parser.get(\"rabbitmq_incoming\", \"connection_string\")\n print(f'conexcion: {conn}')\n config.rabbitmq_incoming_connection_string = parser.get(\"rabbitmq_incoming\", \"connection_string\")\n config.rabbitmq_incoming_queue_name = f'{parser.get(\"rabbitmq_incoming\", \"queue_name\")}{config.machine_id}'\n config.rabbitmq_outgoing_connection_string = parser.get(\"rabbitmq_outgoing\", \"connection_string\")\n config.rabbitmq_outgoing_queue_name = f'{parser.get(\"rabbitmq_outgoing\", \"queue_name\")}{config.machine_id}'\n #gateway\n config.rabbitmq_app_gate_connection_string = parser.get(\"rabbitmq_local\", \"connection_string\")\n config.rabbitmq_app_gate_queue_name = f'{parser.get(\"rabbitmq_local\", \"queue_name\")}-{config.machine_id}'\n\n\n\n return config\n\n\n\nclass WorkerStates(Enum):\n NONE = \"NONE\" # --si\n DEBUGGING = \"DEBUGGING\"\n ANY = \"ANY\" # --si\n BOOTING = \"BOOTING\"\n IDLE = \"IDLE\"\n BUYING_CASH = \"BUYING_CASH\"\n BUYING_CASH_NO_APP = \"BUYING_CASH_NO_APP\"\n WAITING_CASH = \"WAITING_CASH\"\n RETURN_CASH = \"RETURN_CASH\"\n DISPENSING = \"DISPENSING\"\n WAIT_COLLECTION = \"WAIT_COLLECTION\"\n MANUAL = \"MANUAL\" # --si\n APP = \"APP\" # --si\n WAIT_PRODUCT_OUT=\"WAIT_PRODUCT_OUT\" #--si\n WAIT_PRODUCT_OUT_LOCAL=\"WAIT_PRODUCT_OUT_LOCAL\"\n LOCAL=\"LOCAL\"\n\nclass MessageJson():\n Accion=''\n Phone=''\n Success='true'\n Status=''\n Mensaje=''\n TimeBloq=''\n\nclass ErrorProcess():\n DESCONOCIDO = \"ERR-1000: ERROR DESCONOCIDO\" # --si\n CONEXION_USO= \"ERR-1001: La conexion esta en uso\"\n USO_APP = \"ERR-1002: Maquina usada por APP\"\n CCM_STATUS = \"ERR-2001: Maquina No disponible\"\n CCM_SELECT = \"ERR-2002: No se puede Seleccionar el producto\"\n CCM_OUT_PRODUC=\"ERR-2003: Existe un Producto en el Dispensador, Retirelo para continuar\"\n CCM_WRITE = \"ERR-2004: No se puede Despachar el producto\"\n TIME_OUT=\"ERR-2004: Su compra ha exedido el tiempo Establecido.\"\n PRICE_LACK=\"ERR-3001: Precio Insuficente \"\n\n SET_STOCK=\"ERR-3002: no se puede Actualizar el Stock\"\n SET_STOCK_FULL=\"ERR-3003: No se puede actualizar el Stock Full\"\n GET_STOCK=\"ERR-3004: No se puede obtener el Stock\"\n GET_STOCK_FULL=\"ERR-3005: No se puede obtener el Stock Full\"\n SET_PRICE=\"ERR-3006: Error Actualizando el Precio\"\n\nclass SussesProcess():\n START='Proceso Iniciado con Exito'\n PREPARE='Equipo Preparado Para Compra'\n CANCEL='Operaciones Canceladas'\n CCM_STATUS = \"Maquina disponible\"\n CCM_SELECT = \"Producto Seleccionado\"\n CCM_WRITE = \"Producto Despachado\"\n\n SET_STOCK = \"Stock Agregado con Exito\"\n SET_STOCK_FULL = \"Stock Agregado con Exito\"\n SET_PRICE = \"Actiualizacion de Precio Correcto\"\n ADD_TIME = \"Tiempo extra Asignado\"\n\nclass ConstantesProcess():\n TimeMessageExpire:str='60000'\n QueueServer:str='SERVER'\n TimeMessageExpireMovil:str='120000'\n QueueServerCompra:str='OUT_ServerREAD'\n\n\n\n\n@Singleton\nclass HardwareWorker:\n _instance_ = None\n\n def __init__(self):\n \"\"\"\n Main coordinator of the interaction with the dispenser\n Uses innovapos.dispenser.adapters.HardwareClient in order to interact with the data; \\\n the pika library is used in order to be able to read and write from RabbitMQ\n\n \"\"\"\n self._ws_handlers_ = {}\n self._gateway_handlers_ = {}\n self._app_handlers_ = {}\n self.settings: HardwareWorkerSettings = None\n self.hardware_client: HardwareClient = None\n self.ws_client: BlockingAMQPClient = None\n self.gateway_client: BlockingAMQPClient = None\n self.cur_app_user_client: BlockingAMQPClient = None\n self.machine_id = None\n self.current_state = WorkerStates.BOOTING\n # TODO: Variables de Uso local\n self.importeIngresado = 0\n self.precioProducto = 0\n self.KeyApi:str=None\n self.KeyTime:int=0\n self.new_inc_queue:str=None\n self.new_out_queue:str=None\n self.Fecha:datetime=None\n self.isFinish:bool=False\n\n def restart(self):\n self.current_state = WorkerStates.IDLE\n self.KeyApi: str = None\n self.KeyTime: int = 0\n self.new_inc_queue: str = None\n self.new_out_queue: str = None\n self.Fecha: datetime = None\n self.current_state=WorkerStates.IDLE\n\n @staticmethod\n def _shared_decorator_(fn, handlers_dict, rule, valid_states):\n if valid_states is None or len(valid_states) == 0:\n raise RuntimeError(\"Valid states for a handler cannot be None or empty. Use WorkerStates.NONE if needed\")\n if rule in handlers_dict:\n raise RuntimeError(f\"rule {rule} is being set twice, existing handler is {handlers_dict[rule]}\")\n handlers_dict[rule] = {\"valid_states\": valid_states, \"function\": fn}\n return fn\n\n def ws_message_handler(self, rule, valid_states: Sequence[WorkerStates]) -> \\\n Callable[[BlockingAMQPClient, pika.BasicProperties, str], None]:\n \"\"\"\n Message handler decorator. Registers a function in the handlers dictionary so that when a new message arrives\n from the SERVER message queue it gets handled.\n :param rule: \n :type rule: \n :param valid_states: \n :type valid_states: \n :return: \n :rtype: \n \"\"\"\n\n def decorator(fn):\n self._shared_decorator_(fn, self._ws_handlers_, rule, valid_states)\n return fn\n\n return decorator\n\n def gateway_message_handler(self, rule, valid_states: Sequence[WorkerStates] = None) -> \\\n Callable[[BlockingAMQPClient, pika.BasicProperties, str], None]:\n \"\"\"\n Message handler decorator. Registers a function in the handlers dictionary so that when a new message arrives\n from the GATEWAY message queue it gets handled.\n :param rule: \n :type rule: \n :return: \n :rtype: \n \"\"\"\n\n def decorator(fn):\n self._shared_decorator_(fn, self._gateway_handlers_, rule, valid_states)\n return fn\n\n return decorator\n\n def app_message_handler(self, rule, valid_states: Sequence[WorkerStates] = None) -> \\\n Callable[[BlockingAMQPClient, pika.BasicProperties, str], None]:\n \"\"\"\n Message handler decorator. Registers a function in the handlers dictionary so that when a new message arrives\n from the APP message queue it gets handled.\n :param rule: \n :type rule: \n :return: \n :rtype: \n \"\"\"\n\n def decorator(fn):\n self._shared_decorator_(fn, self._app_handlers_, rule, valid_states)\n return fn\n\n return decorator\n\n def _setup_logging_(self) -> None:\n self.logger = logging.getLogger(self.settings.logging_logger_name)\n self.logger.setLevel(self.settings.logging_level)\n log_stream_handler = logging.StreamHandler()\n log_stream_handler.setLevel(self.settings.logging_level)\n log_stream_formatter = logging.Formatter(self.settings.logging_format)\n log_stream_handler.setFormatter(log_stream_formatter)\n\n if self.settings.logging_filename.startswith(\"~\"):\n self.settings.logging_filename = self.settings.logging_filename.replace(\"~\", os.path.expanduser(\"~\"))\n dir_path = Path(self.settings.logging_filename).parent\n os.makedirs(dir_path, exist_ok=True)\n log_file_handler = logging.handlers.TimedRotatingFileHandler(filename=self.settings.logging_filename,\n when='D', interval=1, backupCount=0)\n log_file_formatter = logging.Formatter(self.settings.logging_format)\n log_file_handler.setFormatter(log_file_formatter)\n self.logger.addHandler(log_stream_handler)\n self.logger.addHandler(log_file_handler)\n self.logger.info(\" = = = = = = Bootstrapper logging setup = = = = = = \")\n self.logger.debug(\"Bootstrapper config complete\")\n\n def configure_from_config_file(self, config_path: str):\n self.settings = HardwareWorkerSettings.parse_config_to_settings(config_path)\n self._setup_logging_()\n self.machine_id = self.settings.machine_id\n self.logger.info(f\"Machine configured as {self.machine_id} from config file {config_path}\")\n\n def _create_and_configure_adapter_(self, adapter_type: str, connection_string: str) -> AbstractDataAdapter:\n \"\"\"\n Configures a data adapter based on the the configuration loaded\n\n :param connection_string: configuration string for the needed adapter\n :type connection_string: configuration\n :return: \n :rtype: \n \"\"\"\n adapter: AbstractDataAdapter = None\n if adapter_type == \"tcp\":\n con_str_split = connection_string.split(\":\")\n hostname = con_str_split[0]\n port = int(con_str_split[1])\n adapter_params = TCPDataAdapterParameters(hostname=hostname, port=port,\n send_end_char=self.settings.general_adapter.send_msg_end,\n recv_end_char=self.settings.general_adapter.recv_msg_end,\n timeout=self.settings.general_adapter.timeout,\n answer_delay=self.settings.general_adapter.answer_delay)\n adapter = TCPDataAdapter(adapter_params)\n elif adapter_type == \"serial\":\n adapter_params = SerialDataAdapterParameters(serial_port=connection_string,\n send_end_char=self.settings.general_adapter.send_msg_end,\n recv_end_char=self.settings.general_adapter.recv_msg_end,\n timeout=self.settings.general_adapter.timeout,\n answer_delay=self.settings.general_adapter.answer_delay)\n adapter = SerialDataAdapter(adapter_params)\n return adapter\n\n def _setup_hw_client_(self):\n ccm_adapter = self._create_and_configure_adapter_(self.settings.ccm_adapter_type,\n self.settings.ccm_connection_string)\n mon_adapter = self._create_and_configure_adapter_(self.settings.mon_adapter_type,\n self.settings.mon_connection_string)\n self.hardware_client: HardwareClient = HardwareClient(ccm_adapter=ccm_adapter, mon_adapter=mon_adapter)\n\n self.hardware_client.set_monedero_callback(self._monedero_message_received_callback_)\n self.hardware_client.open_connections()\n\n\n def _setup_ws_amqp_client_(self):\n #TODO: agregado para phone\n self.ws_client = BlockingAMQPClient(\n incoming_mq_params=pika.URLParameters(self.settings.rabbitmq_incoming_connection_string),\n incoming_queue_name=self.settings.rabbitmq_incoming_queue_name,\n outgoing_mq_params=pika.URLParameters(self.settings.rabbitmq_outgoing_connection_string),\n outgoing_queue_name=self.settings.rabbitmq_outgoing_queue_name,\n message_handler=self._ws_message_received_callback_)\n self.ws_client.begin_consuming()\n self.logger.info(\"WS AMQP setup done\")\n\n def _setup_app_gateway_amqp_client_(self):\n #todo Agregado para phone\n print(f'innova: {self.settings.rabbitmq_app_gate_connection_string}')\n self.gateway_client = BlockingAMQPClient(\n incoming_mq_params=pika.URLParameters(self.settings.rabbitmq_app_gate_connection_string),\n incoming_queue_name=self.settings.rabbitmq_app_gate_queue_name,\n outgoing_mq_params=pika.URLParameters(self.settings.rabbitmq_app_gate_connection_string),\n outgoing_queue_name=self.settings.rabbitmq_app_gate_queue_name + \"-default\",\n message_handler=self._gateway_message_received_callback_)\n self.gateway_client.begin_consuming()\n self.logger.debug(\"App Gate AMQP setup done\")\n\n def _setup_cur_app_user_client_(self, incoming_queue_name: str, outgoing_queue_name: str,\n message_handler: Callable[[BlockingChannel, pika.spec.Basic.Deliver,\n pika.spec.BasicProperties, bytes], None]):\n self.cur_app_user_client = BlockingAMQPClient(\n incoming_mq_params=pika.URLParameters(self.settings.rabbitmq_app_gate_connection_string),\n incoming_queue_name=incoming_queue_name,\n outgoing_mq_params=pika.URLParameters(self.settings.rabbitmq_app_gate_connection_string),\n outgoing_queue_name=outgoing_queue_name,\n message_handler=message_handler)\n self.cur_app_user_client.begin_consuming()\n\n def _shared_message_handler_(self, client: BlockingAMQPClient, handlers_dict: dict,\n channel: BlockingChannel, method: pika.spec.Basic.Deliver,\n props: pika.spec.BasicProperties, body: bytes):\n try:\n self.logger.info(f\"Reciviendo mensaje de AMQP. MSG ID: {props.message_id}\")\n _props = pika.spec.BasicProperties()\n _props.expiration = '20000'\n\n if props.type not in handlers_dict: # no existe handler para este tipo\n print('no existe handler para este tipo')\n self.logger.error('no existe handler para este tipo')\n raise NotUnderstoodException(f\"Tipo de Mensaje '{props.type}' No es Soportado por el handler\")\n handler_info = handlers_dict[props.type] # handler existe, lo sacamos\n valid_states = handler_info['valid_states']\n if self.current_state not in valid_states and WorkerStates.ANY not in valid_states:\n # si el estado no es valido o si el comando no soporta \"ANY\" -> mandamos error\n # TODO: definir como controlar errores de este tipo\n if WorkerStates.NONE in valid_states:\n self.logger.warning(f\"Handler function {handler_info['function']} has a NONE identifier. \" +\n f\"Is this intentional?\")\n self.logger.debug(f\"Could not handle command {props.message_id}. \" +\n f\"Estado Actual {self.current_state}, Enviado: {valid_states}\")\n\n\n client.send_message(f\"Estado Actual {self.current_state}, Esperado: {valid_states}\",props=_props)\n return\n handler = handler_info[\"function\"]\n self.logger.info(f\"Handling msg #{props.message_id}, type '{props.type}' with {handler}\")\n message = body.decode()\n handler(client, props, message)\n\n except Exception as exc:\n stack_trace = traceback.format_exc()\n self.logger.error(f\"An exception occured while handling MQ message #{props.message_id}\\n{stack_trace}\")\n client.send_message(stack_trace,props=_props)\n self.logger.debug(f\"Error from message #{props.message_id} sent to queue.\")\n\n def _monedero_message_received_callback_(self, message: str) -> str:\n\n #TODO: hugo monedero callback\n '''\n print('')\n print('')\n print('>>>>>>>>>>>>>< LECTURA MONEDERO >>>>>>>>>>>>>>>>>>>>><')\n print('')\n print('')\n print('')\n '''\n # self.logger.debug(f\" Message from Monedero {message}\")\n '''\n 1.- Verificcamos el comando del monedero\n :param message: \n :return: \n '''\n\n #fecha=str(time.strftime(\"%H:%M:%S\"))\n if 'PING' in message:\n return ''\n self.logger.info(f\"Monedero message received: {message}\")\n\n #print(f'Precio Producto:>>>>>>> {self.precioProducto}')\n print(f'====================================')\n print(f'Mensaje monedero: {message}')\n print(f'Status: {self.current_state}')\n print(f'====================================')\n if('CCM_Valor_Introducido' in message and (self.current_state==WorkerStates.APP or self.current_state==WorkerStates.LOCAL)):\n matches = re.search(\"CCM_Valor_Introducido_(\\d+\\.\\d+)CCM_Valor_Restante_(\\d+\\.\\d+)\", message)\n self.importeIngresado = self.importeIngresado + float(matches.groups()[0])\n print('**************************************')\n print('Lectura comandos ')\n print(f'Importe Introducido: {self.importeIngresado}')\n print(f'Mensaje Machine: {message}')\n print('**************************************')\n return 'Status: APP'\n if((self.current_state==WorkerStates.WAIT_PRODUCT_OUT or self.current_state==WorkerStates.WAIT_PRODUCT_OUT_LOCAL) and (('CCM_Producto_OUT' in message)or ('CCM_Producto_Out' in message ))):\n print('Producto retirado OK')\n print('Valida CCM_Producto_OUT Y WAIT_PRODUCT_OUT_LOCAL')\n print(f'Estado Machine:{self.current_state}')\n print(f'isFinish:{self.isFinish}')\n\n if(self.current_state==WorkerStates.WAIT_PRODUCT_OUT):\n if (self.isFinish==True):\n self.current_state==WorkerStates.IDLE\n else:\n self.current_state=WorkerStates.APP\n print(f'Cambiado Estado:{self.current_state}')\n else:\n if (self.isFinish == True):\n self.current_state == WorkerStates.IDLE\n else:\n self.current_state = WorkerStates.LOCAL\n\n\n self.importeIngresado=0\n self.precioProducto=0\n\n return 'OK'\n\n if ('CCM_OK_DEVOLUCION' in message and (self.current_state==WorkerStates.APP or self.current_state==WorkerStates.LOCAL)):\n self.importeIngresado = 0\n return 'Status: APP'\n\n print(f'Estatus machine: {self.current_state}')\n #elif ('CCM_DESPEDIDA_OK' in message or 'CCM_OK_DEVOLUCION' in message or 'CCM_Producto_Out' in message or 'CCM_COMMAND_PRODUCTOTAMBOR' in message or 'CCM_Recarga_Stop' in message):\n #\n # self.current_state=WorkerStates.IDLE\n # self.importeIngresado=0\n # self.precioProducto=0\n #else:\n # print(f'Mensaje: {message}')\n # self.importeIngresado = 0\n # self.precioProducto = 0\n\n return 'Operando'\n\n def changeStatus(self, Estatus):\n if Estatus.upper() == 'NOR':\n self.current_state = WorkerStates.MANUAL\n elif Estatus.upper() == 'APP':\n self.current_state = WorkerStates.APP\n else:\n self.current_state = WorkerStates.IDLE\n\n def messageJsonOutput(self, Mensaje: MessageJson,MultiDat:str=None):\n return self.messageJsonOutput_Encoding(Mensaje.Accion, Mensaje.Phone, Mensaje.Success, Mensaje.Status, Mensaje.Mensaje,Mensaje.TimeBloq,MultiDat)\n\n ''\n def messageJsonOutput_Encoding(self, Accion, Phone, Success, Status, Mensaje,TimeBloq,MultiDat):\n\n jsonData = '{\"Accion\":\"'+str(Accion)+'\",\"Phone\":\"'+str(Phone)+'\",\"Success\":'+str(Success)+',\"Status\":\"'+str(Status)+'\",\"Mensaje\":\"'+str(Mensaje)+'\",\"TimeBloq\":\"'+str(TimeBloq)+'\"}'\n if MultiDat!=None:\n jsonData = '{\"Accion\":\"' + str(Accion) + '\",\"Phone\":\"' + str(Phone) + '\",\"Success\":' + str(\n Success) + ',\"Status\":\"' + str(Status) + '\",\"Mensaje\":' + str(Mensaje) + '}'\n jsonToPython =jsonData# json.loads(jsonData)\n print(f'Mensaje >>>> : {jsonToPython}')\n return jsonToPython\n\n def _ws_message_received_callback_(self, channel: BlockingChannel, method: pika.spec.Basic.Deliver,\n props: pika.spec.BasicProperties, body: bytes):\n self._shared_message_handler_(self.ws_client, self._ws_handlers_, channel, method, props, body)\n\n def _gateway_message_received_callback_(self, channel: BlockingChannel, method: pika.spec.Basic.Deliver,\n props: pika.spec.BasicProperties, body: bytes):\n self._shared_message_handler_(self.gateway_client, self._gateway_handlers_, channel, method, props, body)\n\n def _app_message_received_callback_(self, channel: BlockingChannel, method: pika.spec.Basic.Deliver,\n props: pika.spec.BasicProperties, body: bytes):\n self._shared_message_handler_(self.cur_app_user_client, self._app_handlers_, channel, method, props, body)\n\n def run_with_autorecover(self):\n \"\"\"\n Runs the worker\n \"\"\"\n self.logger.info(\"Starting up dispenser main loop\")\n self.logger.info(f\"Following command handlers were registered:\\n {', '.join(self._ws_handlers_.keys())}\")\n TimeReboot=0\n while True:\n try:\n self.logger.info(f\"Ejecutando Autorecover.Inicio el worker de conexiones\")\n print('HMS: configurando hw_client_')\n #TODO: TV\n self.logger.info(f\"Configurando conexiones con los Soket\")\n self._setup_hw_client_()\n print('HMS: configurando amqp_client_')\n self._setup_ws_amqp_client_()\n #TODO: desactivamos la parte del gateway\n print('HMS: configurando gateway')\n # HMS: gateway\n #self._setup_app_gateway_amqp_client_()\n self.logger.info(f\"Conexion Iniciada con Exito. Inicio de Loop de eventos.\")\n self.current_state = WorkerStates.IDLE\n\n #import threading\n #import sys\n #from innovapos.worker.tasks.Api import API\n #Service=API()\n #Service.Run()\n\n #t=threading.Thread(target=Service.Run())\n #t.start()\n #t.join()\n #Service.Run()\n\n while True:\n self.ws_client.process_data_events()\n #HMS: gateway\n #self.gateway_client.process_data_events()\n if self.cur_app_user_client is not None:\n self.cur_app_user_client.process_data_events()\n sleep(0.1)\n except Exception as e:\n TimeReboot = TimeReboot + 1\n # TODO: LINUX\n print(f'HMS Reboot: {TimeReboot}')\n if (TimeReboot == 3):\n os.system('sudo reboot now')\n\n\n self.logger.exception(f\"An error has occurred during worker execution.\")\n self.logger.info(\"Recovering from error. Restarting in \" +\n f\"{self.settings.restart_on_fail_seconds} seconds...\")\n sleep(self.settings.restart_on_fail_seconds)\n\n\n","sub_path":"src/innovapos/worker/worker.py","file_name":"worker.py","file_ext":"py","file_size_in_byte":27987,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"107077104","text":"import data\nfrom menu import await_input\ndef search_tool(will_print=False):\n \"\"\"If will_print is true will search for and print entries in the phonebook. If false it will return a list with those entries instead.\"\"\"\n search_term = input(\"Search for: \").lower()\n is_item_found = False\n list_out = []\n\n for entry in data.container_phonebook: #Search for each dictionary in the list.\n for key in entry: #Search for each key in the dictionary.\n if entry[key].lower() == search_term: #Search each value in the dictionary.\n if will_print == True:\n print(\"{first_name} {last_name}: {number}\".format(**entry)) #** is an operator that unpacks a dictionary.\n is_item_found = True\n else:\n list_out.append(entry) \n if (\"{first_name} {last_name}\".format(**entry)).lower() == search_term:\n print(\"{first_name} {last_name}: {number}\".format(**entry)) #** is an operator that unpacks a dictionary.\n is_item_found = True\n\n if is_item_found == False:\n print(\"No Entries Found\")\n await_input()\n return list_out\n \n \n\n","sub_path":"02-week/2-wednesday/labs/henderson-ephriam/project-phone-book/search.py","file_name":"search.py","file_ext":"py","file_size_in_byte":1176,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"538431967","text":"import unittest\nimport numpy as np\nimport numpy.testing as npt\nimport lbm_bgk as lbm\n\n\ndims, q = 2, 9\ne = np.array([(0, 0), (1, 0), (0, 1), (-1, 0), (0, -1), (1, 1), (-1, 1),\n (-1, -1), (1, -1)])\nw = np.array([4./9., 1./9., 1./9., 1./9., 1./9., 1./36., 1./36., 1./36.,\n 1./36.])\nc = 1./np.sqrt(3) # Speed of sound\n\n\nclass TestFunctions(unittest.TestCase):\n\n def test_viscosity(self):\n self.assertEqual(lbm.viscosity(10, 10, 100), 1)\n\n def test_RelaxationTime(self):\n self.assertAlmostEqual(lbm.RelaxationTime(c, 10, 10, 300), 1.5)\n\n def test_density(self):\n self.assertEqual(lbm.density(np.array([1, 2, 3])), 6)\n\n def test_geometry(self):\n self.assertTrue(lbm.geometry(1, 0, 4, 1, 4).all())\n self.assertFalse(lbm.geometry(0, 0, 3, 1, 4).all())\n npt.assert_array_equal(lbm.geometry(1, 1, 1, 3, 3)[1],\n [False, True, False])\n\n def test_vel_init(self):\n self.assertAlmostEqual(lbm.vel_init(0.1, 1, 1, 2)[0], 0.1)\n self.assertAlmostEqual(lbm.vel_init(0.1, 1, 1, 2)[1], 0.0)\n\n def test_solve(self):\n self.assertAlmostEqual(lbm.solve(Nx=2, Ny=4, max_v=0.1, x_c=0, y_c=3,\n side=0, iterations=10)[1][1,0,3], 0.0)\n\n self.assertAlmostEqual(lbm.solve(Nx=2, Ny=4, max_v=0.1, x_c=0, y_c=3,\n side=0, iterations=10)[1][1,1,3], 0.0)\n\n self.assertAlmostEqual(lbm.solve(Nx=2, Ny=4, max_v=0.1, x_c=0, y_c=3,\n side=0, iterations=10)[1][1, 1, 3], 0)\n\nif __name__ == '__main__':\n unittest.main()\n","sub_path":"test_lbm.py","file_name":"test_lbm.py","file_ext":"py","file_size_in_byte":1649,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"565729443","text":"# Definition for singly-linked list.\n# class ListNode(object):\n# def __init__(self, x):\n# self.val = x\n# self.next = None\n\nclass Solution(object):\n def reverseList(self, head):\n \"\"\"\n :type head: ListNode\n :rtype: ListNode\n \"\"\"\n if head is None:\n return None\n\n if head.next is None:\n return head\n\n # divide and conquer\n # 1. find the last node of current iteration\n # 2. put the last node in the first place\n # 3. recursively reverse the rest of nodes, \n # and connect the first (last previously) node to the reversed nodes\n head_copy = head\n \n while head.next.next:\n head = head.next\n \n last_node = head.next\n head.next = None\n\n last_node.next = self.reverseList(head_copy)\n\n return last_node\n\n def reverseBetween(self, head, m, n):\n \"\"\"\n :type head: ListNode\n :type m: int\n :type n: int\n :rtype: ListNode\n \"\"\"\n\n if head is None:\n return None\n \n # add a header before any non-trivial node\n header = ListNode(-999)\n header.next = head\n head = header\n\n index = 0\n while head:\n if index == m - 1:\n before_reverse = head\n start = head.next\n if index == n:\n end = head\n after_reverse = head.next\n break\n \n index += 1\n head = head.next\n\n end.next = None\n reversed_linked_list = self.reverseList(start)\n before_reverse.next = reversed_linked_list\n\n head = header\n while head.next:\n head = head.next\n \n head.next = after_reverse\n\n return header.next\n","sub_path":"codes/MartinMa28/python3/0092_reverse_linked_list_2.py","file_name":"0092_reverse_linked_list_2.py","file_ext":"py","file_size_in_byte":1843,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"617198204","text":"from collections import deque\nimport sys\nN = int(sys.stdin.readline())\nqueue = deque()\nfor _ in range(N):\n cmd = list(sys.stdin.readline().split())\n if cmd[0] == 'push_back':\n queue.append(cmd[1])\n\n elif cmd[0] == 'push_front':\n queue.appendleft(cmd[1])\n\n elif cmd[0] == 'pop_front':\n if len(queue) == 0:\n print('-1')\n else:\n print(queue.popleft())\n\n elif cmd[0] == 'pop_back':\n if len(queue) == 0:\n print('-1')\n else:\n print(queue.pop())\n\n elif cmd[0] == 'size':\n print(str(len(queue)))\n\n elif cmd[0] == 'empty':\n if len(queue) == 0:\n print('1')\n else:\n print('0')\n\n elif cmd[0] == 'front':\n if len(queue) == 0:\n print('-1')\n else:\n print(queue[0])\n\n elif cmd[0] == 'back':\n if len(queue) == 0:\n print('-1')\n else:\n print(queue[-1])","sub_path":"알고리즘 기초/10866.py","file_name":"10866.py","file_ext":"py","file_size_in_byte":961,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"326614446","text":"import sys\nsys.stdin = open(\"파리퇴치.txt\", 'r')\n\nT = int(input())\nfor tc in range(T):\n N, M = map(int, input().split()) #N 영역크기, M 파리채크기\n arr = [list(map(int,input().split())) for _ in range(N)]\n maxi = 0\n\n\n for i in range(N-M+1):\n for j in range(N-M+1):\n dye = 0\n for k in range(M):\n for l in range(M):\n\n dye += arr[i+k][j+l]\n\n if maxi < dye:\n maxi = dye\n print(maxi)\n\n\n\n\n\n","sub_path":"08_algorithm/05_algorithm2019.08.19/파리퇴치.py","file_name":"파리퇴치.py","file_ext":"py","file_size_in_byte":501,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"173999370","text":"nums = [3,4,5,1,2] \n\n# binary search - o(logn) runtime, o(1) space\nif not nums:\n return -1\n\nl = 0\nr = len(nums) - 1\nwhile l < r:\n mid = l + (r-l)//2\n if nums[mid] > nums[r]:\n l = mid + 1\n else:\n r = mid\n\nreturn nums[l]","sub_path":"medium/153.py","file_name":"153.py","file_ext":"py","file_size_in_byte":244,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"89"}
+{"seq_id":"31184401","text":"import os\nfrom flask import Flask, flash, render_template, request, redirect, \\\n url_for, send_from_directory\nfrom werkzeug import secure_filename\nimport cloudinary\nfrom cloudinary.uploader import upload\nfrom cloudinary.utils import cloudinary_url\nimport requests\n\nfrom label import label_leaf\n\nALLOWED_EXTENSIONS = set(['jpg', 'jpeg'])\nUPLOAD_FOLDER = './pictures'\n\napp = Flask(__name__)\napp.secret_key = '@3xffxbex9b5x06:x8f=xc0x04x15Bxe6xc2'\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\ncloudinary.config( \n cloud_name = \"toni-not-oak\",\n api_key = \"866339269462168\",\n api_secret = \"TwmBPqSIbsuwWcG2w3-SrkokM2Q\"\n)\n\n\n@app.route('/', methods=['GET', 'POST'])\ndef index():\n if request.method == 'POST':\n # Check if the post request has the file part\n if 'file' not in request.files:\n flash('No file part')\n return redirect(request.url)\n file_to_upload = request.files['file']\n # If user does not select file, browser also\n # submit an empty part without filename\n if file_to_upload.filename == '':\n flash('No selected file')\n return redirect(request.url)\n # Check if filetype is okay\n if not allowed_file(file_to_upload.filename):\n flash('File-type not allowed. Use .png, .jpg or .jpeg.')\n print('File-type not allowed. Use .png, .jpg or .jpeg.')\n return redirect(request.url)\n # Upload file\n upload_result = upload(file_to_upload, folder = 'uploads')\n thumbnail_for_model, options = cloudinary_url(\n upload_result['public_id'], format=\"jpg\", crop=\"scale\", width=299,\n height=299)\n thumbnail_for_user, options = cloudinary_url(\n upload_result['public_id'], format=\"jpg\", crop=\"fit\", width=600,\n height=600, secure=True)\n # Analysis\n image = requests.get(thumbnail_for_model, allow_redirects=True)\n open('image/image.jpg', 'wb').write(image.content)\n leaf_result = label_leaf('image/image.jpg')\n return render_template('analysis.html',\n leaf=leaf_result['labels'][0],\n certainty=leaf_result['results'][0], time=leaf_result['time'],\n thumbnail_for_user=thumbnail_for_user)\n\n # Upload form via GET request\n return render_template('index.html')\n\n\n@app.route('/about')\ndef about():\n return render_template('about.html')\n\n\n@app.route('/analysis_example', methods=['GET', 'POST'])\ndef examples():\n if request.method == 'POST':\n thumbnail_for_user = request.form.get('postImage')\n # Resize for model via Cloudinary URL\n thumbnail_for_model = thumbnail_for_user.replace(\"w_600\",\"w_299,h_299\")\n # Analysis\n image = requests.get(thumbnail_for_model, allow_redirects=True)\n open('image/image.jpg', 'wb').write(image.content)\n leaf_result = label_leaf('image/image.jpg')\n return render_template('analysis.html',\n leaf=leaf_result['labels'][0],\n certainty=leaf_result['results'][0], time=leaf_result['time'],\n thumbnail_for_user=thumbnail_for_user)\n\n return render_template('index.html')\n\n\ndef allowed_file(filename):\n return '.' in filename and \\\n filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":3306,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"121512003","text":"#!/usr/bin/env python\n\nimport sys\nimport yaml\nimport subprocess\n\nignore_attribs = ['CameraName',\n 'DeviceEthAddress',\n 'HostEthAddress',\n 'HostIPAddress',\n 'SerialNumber',\n 'UniqueId',\n 'WhitebalMode',\n 'ExposureMode',\n 'GainMode',\n 'FrameStartTriggerMode',\n 'StreamBytesPerSecond',\n 'Height',\n 'Width',\n 'ExposureValue',\n 'GainValue',\n 'WhitebalValueRed',\n 'WhitebalValueBlue',\n 'RegionX',\n 'RegionY',\n 'PacketSize',\n 'FrameRate',\n 'SyncInLevels',\n 'StatFrameRate',\n 'StatFramesCompleted',\n 'StatFramesDropped',\n 'StatPacketsErroneous',\n 'StatPacketsMissed',\n 'StatPacketsReceived',\n 'StatPacketsRequested',\n 'StatPacketsResent']\n\n\ndef write_attributes(output):\n attribs = {}\n for ln in output.split('\\n'):\n vals = ln.split()\n \n if len(vals) < 3:\n continue\n\n if vals[-2] != '=':\n continue\n\n if ignore_attribs.count(vals[0]) == 0:\n attribs[vals[0]] = vals[-1]\n \n stream = file('prosilica_attribs.yaml', 'w')\n yaml.dump(attribs, stream)\n \n\n\nif __name__ == '__main__':\n IP = '10.68.0.20'\n \n cmd = 'rosrun prosilica_gige_sdk ListAttributes %s' % IP\n \n p = subprocess.Popen(cmd, stdout=subprocess.PIPE,\n stderr = subprocess.PIPE, shell=True)\n o, e = p.communicate()\n \n if p.returncode != 0:\n print >> sys.stderr, \"Unable to get Attributes from prosilica\"\n\n write_attributes(o)\n","sub_path":"root/usr/share/checkprosilica/get_prosilica_attribs.py","file_name":"get_prosilica_attribs.py","file_ext":"py","file_size_in_byte":1910,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"521898303","text":"\"\"\"\nGiven a sorted array, convert it into a height-balanced binary search tree.\n--\nstart from the middle,\nrecurse on the left and right\n\"\"\"\n\n\nclass Node:\n def __init__(self, val):\n self.val = val\n self.left = None\n self.right = None\n\n\ndef high_balanced_bst(arr):\n def helper(start, end, arr):\n if start > end:\n return None\n elif start == end:\n return Node(arr[start])\n else:\n mid = start + (end - start) // 2\n n = Node(arr[mid])\n n.left = helper(start, mid - 1, arr)\n n.right = helper(mid + 1, end, arr)\n return n\n\n return helper(0, len(arr) - 1, arr)\n\n\nif __name__ == \"__main__\":\n res = high_balanced_bst([1, 2, 3, 4, 5])\n","sub_path":"old/dcp_series/dcp_296.py","file_name":"dcp_296.py","file_ext":"py","file_size_in_byte":754,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"424089698","text":"import spacy\n\n# Matcherをインポート\nfrom spacy.matcher import Matcher\n\nnlp = spacy.load(\"en_core_web_sm\")\ndoc = nlp(\"Upcoming iPhone X release date leaked as Apple reveals pre-orders\")\n\n# 共有語彙データを用いてMatcherを初期化\nmatcher = Matcher(nlp.vocab)\n\n# 「iPhone」と「X」にマッチするパターンを作成\npattern = [{\"TEXT\": \"iPhone\"}, {\"TEXT\": \"X\"}]\n\n# matcherにパターンを追加\nmatcher.add(\"IPHONE_X_PATTERN\", None, pattern)\n\n# docに対してmatcherを用いる\nmatches = matcher(doc)\nprint(\"Matches:\", [doc[start:end].text for match_id, start, end in matches])\n","sub_path":"exercises/ja/solution_01_11.py","file_name":"solution_01_11.py","file_ext":"py","file_size_in_byte":607,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"278171338","text":"def ChkPrime(no):\n\tif no > 1:\n\t\tfor i in range(2, no):\n\t\t\tif no % i == 0:\n\t\t\t\tbreak\n\t\t\t\treturn False\n\t\telse:\n\t\t\treturn True\n\telse:\n\t\treturn False\n\ndef main():\n\tno = int(input(\"Enter a number: \"))\n\tif no > 0:\n\t\tArr = list()\n\t\tfor i in range(0, no):\n\t\t\tprint(\"Enter no {}: \".format(i+1), end=\"\")\n\t\t\tArr.append(int(input()))\n\t\tprint(\"Accepted List: {}\".format(Arr))\n\t\tFilteredList = list(filter(ChkPrime, Arr))\n\t\tif len(FilteredList) > 0:\n\t\t\tprint(\"Filtered List: {}\".format(FilteredList))\n\t\t\tMappedList = list(map(lambda no : no * 2, FilteredList))\n\t\t\tprint(\"Mapped list: {}\".format(MappedList))\n\t\t\tprint(\"Maximum number from mapped list is: {}\".format(max(MappedList)))\n\t\telse:\n\t\t\tprint(\"There is no filtered data for further operations\")\n\telse:\n\t\tprint(\"Please enter a valid number\")\nif __name__ == \"__main__\":\n\tmain()","sub_path":"Assignment4/Assignment4_5.py","file_name":"Assignment4_5.py","file_ext":"py","file_size_in_byte":818,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"636600036","text":"import torch\nfrom eod.utils.general.registry_factory import RUNNER_REGISTRY\nfrom eod.utils.general.global_flag import FP16_FLAG\n\nfrom .base_runner import BaseRunner\n\n\n__all__ = ['FP16Runner']\n\n\n@RUNNER_REGISTRY.register('fp16')\nclass FP16Runner(BaseRunner):\n def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n self.scaler = torch.cuda.amp.GradScaler(enabled=True)\n self.fp16 = True\n FP16_FLAG.fp16 = True\n\n def forward(self, batch, return_output=False):\n with torch.cuda.amp.autocast(enabled=True):\n output = self.forward_model(batch)\n self._temporaries['last_output'] = output\n losses = [val for name, val in output.items() if name.find('loss') >= 0]\n loss = sum(losses)\n if return_output:\n return loss, output\n else:\n return loss\n\n def backward(self, loss):\n self.model.zero_grad()\n self.scaler.scale(loss).backward()\n self._hooks('after_backward', self.cur_iter, loss)\n return loss\n\n def update(self):\n self.scaler.step(self.optimizer)\n self.scaler.update()\n self._hooks('after_update', self.cur_iter)\n\n def resume_fp16(self, ckpt):\n self.scaler.load_state_dict(ckpt['scaler'])\n\n def get_fp16_dump_dict(self):\n return {'scaler': self.scaler.state_dict()}\n","sub_path":"eod/runner/fp16_runner.py","file_name":"fp16_runner.py","file_ext":"py","file_size_in_byte":1364,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"389144211","text":"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.db import models, migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('database', '0005_kviz_uganka'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='user',\n name='tocke',\n field=models.IntegerField(verbose_name='tocke', default=0),\n ),\n ]\n","sub_path":"database/migrations/0006_user_tocke.py","file_name":"0006_user_tocke.py","file_ext":"py","file_size_in_byte":412,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"572201869","text":"import os\nimport json\nfrom flask import Flask, render_template, request\nfrom flask_bootstrap import Bootstrap\nfrom steamapi import core, user\nimport requests as reqGet\n\napp = Flask(\"whatcanweplay\")\nBootstrap(app)\nSTEAM_KEY = os.environ.get('STEAM_KEY')\ncore.APIConnection(api_key=STEAM_KEY)\n\n\ndef getUserID(nickname):\n session = reqGet.Session()\n session.mount(\"http://\", reqGet.adapters.HTTPAdapter(max_retries=10))\n print(\"Retrieving user and game data for \" + nickname + \"...\")\n id_response_json = json.loads(session.get(\n url='http://api.steampowered.com/ISteamUser/ResolveVanityURL/v0001/?key=' + STEAM_KEY + '&vanityurl=' + nickname).text)\n # If user is found\n if id_response_json and id_response_json['response']['success'] == 1:\n return str(id_response_json['response']['steamid'])\n else:\n print(\"cry\")\n\n\ndef make_string_of_games(games):\n all_games = \"\"\n for game in games:\n all_games += game.name + \"\\n\"\n return all_games\n\n\n@app.route('/')\ndef home():\n return render_template('index.html')\n\n\ndef make_list_of_shared_games(friends):\n games = []\n for friend in friends:\n games.append(friend.games)\n result = set(games[0])\n for game in games[1:]:\n result.intersection_update(game)\n return sorted(result, key=lambda x: x.name)\n\n\n# Friend.state\n# 0 - Offline\n# 1 - Online\n# 3 - Away\n\n\ndef sort_friends_by_status(steam_user):\n friends = sorted(steam_user.friends, key=lambda x: x.name)\n online_friends = []\n for friend in friends:\n if friend.state != 0:\n online_friends.append(friend)\n friends.remove(friend)\n return online_friends + friends\n\n\n@app.route('/user')\ndef page_with_loaded_user():\n name = request.args.get('search')\n if \" \" in name:\n names = name.split(\" \")\n friends = []\n for name in names:\n try:\n friends.append(user.SteamUser(userid=int(name)))\n except ValueError:\n friends.append(user.SteamUser(userurl=name))\n return render_template('index.html', main_user=friends[0], friends=sort_friends_by_status(friends[0]),\n games=make_list_of_shared_games(friends))\n\n try:\n try:\n steam_user = user.SteamUser(userid=int(name))\n except ValueError: # Not an ID, but a vanity URL.\n steam_user = user.SteamUser(userurl=name)\n name = steam_user.name\n img = steam_user.avatar\n friends = sort_friends_by_status(steam_user)\n return render_template('index.html', main_user=steam_user, friends=friends)\n # return render_template('hello.html', name=name, content=content, img=img, games=make_string_of_games(steam_user.games))\n except Exception as ex:\n # We might not have permission to the user's friends list or games, so just carry on with a blank message.\n return render_template('index.html', user=name)\n # return render_template('hello.html', name=name)\n\n\nif __name__ == '__main__':\n port = int(os.environ.get('PORT', 5000))\n app.run(host='0.0.0.0', port=port)\n","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":3117,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"224599461","text":"from typing import Optional, Union, Sequence\n\nfrom webdnn.graph.operator import Operator\nfrom webdnn.graph.operators.attributes.inplace import Inplace\nfrom webdnn.graph.order import Order\nfrom webdnn.graph.placeholder import Placeholder\nfrom webdnn.graph.variable import Variable\nfrom webdnn.graph.variables.constant_variable import ConstantVariable\nfrom webdnn.util.misc import mul\n\n\nclass Reshape(Operator):\n \"\"\"Reshape(name, in_order, out_order, out_shape)\n\n Reshape array assuming it is C-order.\n Removing / inserting axis with length 1\n\n When in_order: NHWC, out_order: NTC, out_shape: (2, 6, 10) and input variable is (2, 3, 4, 5), the semantic procedure is as follows.\n 1. Interpret input variable as NTHWC (2, 1, 3, 4, 5) with inserting axis with length 1\n 2. Reshape it with assuming C-order and length of axis being removed is 1; NTHWC (2, 6, 1, 1, 10)\n 3. Remove axes; NTC (2, 6, 10)\n\n Swapping axes is prohibited because it is ambiguous.\n If in_order and out_order match the actual input / output variable order, kernel does not have to do anything.\n\n Args:\n name (str): Operator name.\n in_order (:class:`~webdnn.graph.order.Order`): input order\n out_order (:class:`~webdnn.graph.order.Order`): output order\n out_shape (list of int or :class:`~webdnn.graph.placeholder.Placeholder`): output shape\n\n Signature\n .. code::\n\n y, = op(x)\n\n - **x** - Input variable.\n - **y** - Output variable.\n \"\"\"\n\n def __init__(self, name: Optional[str], in_order: Order, out_order: Order, out_shape: Sequence[Union[int, Placeholder]]):\n super().__init__(name)\n\n assert -1 not in out_shape, \"-1 (wildcard) in reshape output shape is currently not supported\"\n\n self.parameters[\"in_order\"] = in_order\n self.parameters[\"out_order\"] = out_order\n self.parameters[\"out_shape\"] = out_shape\n\n self.attributes.add(Inplace(self, \"x\", \"y\"))\n\n def __call__(self, x: Variable):\n in_shape = x.shape\n in_order = self.parameters[\"in_order\"]\n out_shape = self.parameters[\"out_shape\"]\n out_order = self.parameters[\"out_order\"]\n assert x.order == in_order\n assert x.size == mul(out_shape), f\"Reshape operator must not change variable size: \" \\\n f\"(x.shape)={in_shape}, (x.size)={mul(in_shape)}, \" \\\n f\"(y.shape)={out_shape}, (y.size)={mul(out_shape)}\"\n\n y = Variable(out_shape, out_order)\n self.append_input(\"x\", x)\n self.append_output(\"y\", y)\n\n return y,\n\n def fold_constance(self):\n in_order = self.parameters[\"in_order\"]\n out_shape = self.parameters[\"out_shape\"]\n out_order = self.parameters[\"out_order\"]\n\n x = self.inputs[\"x\"]\n y = self.outputs[\"y\"]\n y.replace(ConstantVariable(x.copy().change_order(in_order).data.reshape(out_shape), out_order))\n self.remove_all()\n","sub_path":"src/graph_transpiler/webdnn/graph/operators/reshape.py","file_name":"reshape.py","file_ext":"py","file_size_in_byte":2990,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"501336549","text":"contents = [line.rstrip('\\n') for line in open('input')]\n\nseen = set()\ntotal = 0\nindex = 0\n\nwhile True:\n total += int(contents[index])\n if total in seen:\n print(total)\n break\n seen.add(total)\n index += 1\n if index >= len(contents):\n index = 0\n","sub_path":"python/1/2.py","file_name":"2.py","file_ext":"py","file_size_in_byte":279,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"275901812","text":"#!/usr/bin/env python\n# -*- coding: utf8 -*-\n\nimport os, sys, subprocess, math\nfrom time import sleep\nimport scipy.stats as stats\n\n#\n# Tiempo de simulacion (en segundos)\n#\nTS=7200\n\n#\n# Lee cuáles son las paradas existentes\n#\nPARADAS=[]\nf=open(\"paradas.txt\",\"r\")\nfor l in f:\n p=int(l)\n PARADAS.append(p)\nf.close()\n\n#\n# Lee cuáles son las líneas existentes\n#\nLINEAS=[]\nf=open(\"lineas.txt\",\"r\")\nfor l in f:\n li=int(l)\n LINEAS.append(li)\nf.close()\n\n#\n# Lee para cada parada cuál es el lambda de arribo de personas\n#\nLAMBDAS_PARADAS={}\ns=subprocess.Popen([ 'bash','./calcula_lambdas_paradas' ], stdout=subprocess.PIPE)\nfor l in s.stdout:\n s=l.split(',')\n p=int(s[0]) # parada\n l=float(s[1]) # lambda\n LAMBDAS_PARADAS[p]=l\n \n#\n# Lee para cada linea cuál es el lambda de arribo a su primer parada\n#\nLAMBDAS_LINEAS={}\ns=subprocess.Popen([ 'bash','./calcula_lambdas_lineas' ], stdout=subprocess.PIPE)\nfor l in s.stdout:\n s=l.split(',')\n li=int(s[0]) # linea\n la=float(s[1]) # lambda\n LAMBDAS_LINEAS[li]=la\n\n#\n# Lee para cada combinación de parada y linea el lambda de gente que sube\n#\nLAMBDAS_PARADAS_LINEAS={}\ns=subprocess.Popen([ 'bash','./calcula_lambdas_paradas_lineas' ], stdout=subprocess.PIPE)\nfor l in s.stdout:\n s=l.split(',')\n pa=int(s[0]) # parada\n li=int(s[1]) # linea\n la=float(s[2]) # lambda\n LAMBDAS_PARADAS_LINEAS[pa,li]=la\n \n#\n# Lee lambda de tiempo que demora una persona en subir\n#\ns=subprocess.Popen( ['bash','./lambda_tiempo_subir'],stdout=subprocess.PIPE)\nfor l in s.stdout:\n LAMBDA_TIEMPO_SUBIR=float(l)\n\n#\n# Lee cuáles son las primeras paradas de cada linea\n#\nPRIMER_PARADA={}\ns=subprocess.Popen( ['bash','./calcula_primeras_paradas'],stdout=subprocess.PIPE)\nfor l in s.stdout:\n s=l.split(',')\n l=int(s[0]) # linea\n p=int(s[1]) # primer parada\n PRIMER_PARADA[l]=p\n\n#\n# Lee valores para la distribución normal que se usará para\n# calcular la cantidad inicial de personas en cada parada\n#\nMU={}\nS2={}\nMAX={}\ns=subprocess.Popen( ['bash','./calcula_s2'],stdout=subprocess.PIPE)\nfor l in s.stdout:\n s=l.split(',')\n p=int(s[0]) # parada\n mu=float(s[1]) # mu\n s2=float(s[2]) # s^2\n mx=int(s[3]) # cantidad máxima de personas observada\n MU[p]=mu\n S2[p]=s2\n MAX[p]=mx\n\n#\n# Calcula array AP\n#\nAP={}\nfor p in PARADAS:\n remanente=0\n for seg in range (1,TS):\n va=stats.expon.rvs(scale=LAMBDAS_PARADAS[p])\n llegan,r=divmod(va+remanente,1)\n remanente=va+remanente-llegan\n AP[p,seg]=llegan\n\n#\n# Ciclo principal\n#\n\nPP={}\nTANT={}\nTULT={}\nDELTA=[]\nTPANT={}\nTPULT={}\nDELTAP=[]\nPROXIMO={}\n\nfor p in PARADAS:\n PP[p]=int(round(stats.norm.rvs()*math.sqrt(S2[p])+MU[p],0))\n if PP[p] < 0:\n PP[p]=0\n if PP[p] > MAX[p]:\n PP[p]=MAX[p]\n\nfor l in LINEAS:\n va=stats.expon.rvs(scale=LAMBDAS_LINEAS[l])\n PROXIMO[l]=int(va)\n\nfor seg in range (1,TS):\n for p in PARADAS:\n PP[p]+=AP[p,seg]\n \n # Ve si hay que inyectar un nuevo colectivo\n # -----------------------------------------\n for l in LINEAS:\n\n # Partida de un colectivo\n # -----------------------\n if seg==PROXIMO[l]:\n # 1) inyecta colectivo\n # 2) calcula el próximo\n va=stats.expon.rvs(scale=LAMBDAS_LINEAS[l])\n PROXIMO[l]=int(va)+seg\n # 3) cálculos para determinar factor de contracción\n if l not in TANT:\n TANT[l]=seg\n else:\n DELTA.append(seg-TANT[l])\n TANT[l]=seg\n\n # Llegada de colectivos a parada\n # ------------------------------\n if True==True:\n p=1 # OJO, acá hay que ver a qué parada llegó el colectivo\n l=17 # OJO, acá hay que ver a qué linea corresponde el colectivo\n\n if (p,l) not in TULT: # Es la primer llegada de la linea a la parada\n TULT[p,l]=0\n\n # tt significa tiempo transcurrido\n tt=seg-TULT[p,l]\n\n suben=round(stats.expon.rvs(scale=LAMBDAS_PARADAS_LINEAS[p,l]*tt),0)\n tdet=round(stats.expon.rvs(scale=LAMBDA_TIEMPO_SUBIR*tt),0)\n\n # Cálculos para determinar factor de contracción\n if p==PRIMER_PARADA[l]:\n if l not in TPANT:\n TPANT[l]=seg\n else:\n DELTAP.append(seg-TPANT[l])\n TPANT[l]=seg\n\n # Establecer detención\n\n if PP[p] < suben:\n PP[p]=0\n else:\n PP[p]-=suben\n","sub_path":"mediciones/simulacion.py","file_name":"simulacion.py","file_ext":"py","file_size_in_byte":4174,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"460564042","text":"#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n\ndic = {\n \"植物\":\n {\"草本植物\":\n [\"牵牛花\",\"瓜叶草\",\"葫芦\",\"翠菊\",\"冬小麦\"],\n \"木本植物\":\n [\"乔木\",\"灌木\",\"如松\",\"杉\",\"樟\"],\n \"水生植物\":\n [\"菊花\",\"干厨菜\",\"菖蒲\",\"水葱\",\"再力花\",\"梭鱼草\"]},\n \"动物\":\n {\"两栖动物\":\n [\"山龟\",\"山鳌\",\"石蛙\",\"娃娃鱼\",\"蟾蜍\",\"龟\",\"鳄鱼\",\"蜥蜴\",\"蛇\"],\n \"禽类\":\n [\"雏鸡\",\"原鸡\",\"长鸣鸡\",\"昌国鸡\",\"斗鸡\",\"长尾鸡\",\"乌骨鸡\"],\n \"哺乳类动物\":\n [\"虎\",\"狼\",\"鼠\",\"貂\",\"猴\",\"树懒\",\"斑马\",\"狗\"]}}\nli = []\ngo = True\nwhile go:\n for i,v in enumerate(dic,1):\n print(i,v)\n li.append(v)\n u_c = input(\">>>\")\n if u_c == \"b\":\n li.clear()\n break\n elif u_c == \"q\":\n go = False\n break\n else:\n u_c = int(u_c)\n u_c = int(u_c)\n li1 = []\n while go:\n for i,v in enumerate(dic[li[u_c-1]],1):\n print(i,v)\n li1.append(v)\n u_c1 = input(\">>>>\")\n if u_c1 == \"b\":\n li1.clear()\n break\n elif u_c1 == \"q\":\n go = False\n break\n else:\n u_c1 = int(u_c1)\n\n while go:\n for i in dic[li[u_c-1]][li1[u_c1-1]]:\n print(i)\n u_c2 = str(input(\">>>>>\"))\n u_c2 = u_c2.lower()\n if u_c2 == \"b\":\n li1.clear()\n break\n elif u_c2 == \"q\":\n go = False\n break\n","sub_path":"python_scripts/Three_mem.py","file_name":"Three_mem.py","file_ext":"py","file_size_in_byte":1614,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"131566735","text":"import logging\n\ndef logger(module, level='info'):\n \"\"\"\n\n :param module: module name\n :param level: logging level , check LEVELS variable for available options\n :return: logger object\n \"\"\"\n formatter = \"%(asctime)s - %(name)s - %(levelname)s - %(message)s\"\n\n LEVELS = {'debug': logging.DEBUG,\n 'info': logging.INFO,\n 'warning': logging.WARNING,\n 'error': logging.ERROR,\n 'critical': logging.CRITICAL}\n level_name = LEVELS.get(level, logging.NOTSET)\n logging.basicConfig(format=formatter, level=level_name)\n log = logging.getLogger(module)\n return log","sub_path":"logger.py","file_name":"logger.py","file_ext":"py","file_size_in_byte":635,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"100022954","text":"from __future__ import print_function\nimport csv\nimport sys\nimport re\nfrom utils import Utils\nfrom filereader import FileReader\n\nclass Join:\n def __init__(self):\n self.utils = Utils()\n self.filereader = FileReader()\n\n def join(self, dictionary, tableNames, const_conditions, join_conditions):\n database = {}\n visited = {}\n for t in tableNames:\n visited[t] = False\n database[t] = []\n self.filereader.readFile(t + \".csv\", database[t])\n # print database\n Jc = self.get_join_conditions(dictionary, join_conditions)\n remove_attribs = []\n i = 1\n for t in tableNames:\n self.utils.spaces_rem(t)\n if i == 1:\n resultant_data = database[t]\n visited[t] = True\n schema = dictionary[t]\n i = 0\n else:\n for key, value in visited.items():\n if visited[key]:\n try:\n join_attribs = Jc[(t, key)]\n except:\n join_attribs = None\n if join_attribs:\n remove_attribs.append(t + '.' + join_attribs[0])\n resultant_data, schema = self.join_tables(resultant_data, database[t], key, t, schema,\n join_attribs[1], join_attribs[0], dictionary)\n else:\n resultant_data, schema = self.join_tables(resultant_data, database[t], key, t, schema, None,\n None,\n dictionary)\n\n if const_conditions:\n if \"=\" in const_conditions:\n if len(const_conditions):\n resultant_data, schema = self.utils.rem_via_constants(resultant_data, const_conditions, schema,\n dictionary,\n tableNames)\n\n for r in remove_attribs:\n try:\n schema.remove(r)\n except:\n print(\"No such attribute present\")\n\n return resultant_data, schema\n\n def get_join_conditions(self, dictionary, join_conditions):\n Jc = {}\n if join_conditions:\n for j in join_conditions:\n j = self.utils.spaces_rem(j)\n c = self.utils.parse_condition(j)\n if c:\n Jc[(c[0], c[1])] = (c[2], c[3])\n Jc[(c[1], c[0])] = (c[3], c[2])\n return Jc\n\n def join_tables(self, resultant_data, table_data, table1, table2, schema, r_att, t_att, dictionary):\n if schema:\n if r_att and t_att:\n h = {}\n new = []\n old = []\n i = schema.index(table1 + \".\" + r_att)\n\n for idx, row in enumerate(resultant_data):\n h[row[i]] = idx\n if t_att:\n i = dictionary[table2].index(table2 + \".\" + t_att)\n if resultant_data:\n for row in table_data:\n if h.has_key(row[i]):\n new.append(resultant_data[h[row[i]]] + row)\n resultant_data = new\n\n else:\n new = []\n if resultant_data:\n for r in resultant_data:\n for t in table_data:\n new.append(r + t)\n resultant_data = new\n schema += dictionary[table2]\n\n return (resultant_data, schema)\n","sub_path":"join.py","file_name":"join.py","file_ext":"py","file_size_in_byte":3824,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"9289567","text":"\n# -*- coding: utf-8 -*-\n\"\"\"\n@author: David Bestue\n\"\"\"\n\nimport numpy as np\nimport random\nimport pandas as pd\n\n\n### rgb in psychopy goes from -1 (0) to 1 (255)\n\nno_stim = [0,0,0] # grey\nc1=[-1,-1,1] ### dark blue\nc2=[-1,1,-1] ### green\nc3=[-1,1,1] ####cyan\nc4=[1,-1,-1] #red\nc5=[1,-1,1] #pink\nc6=[1,1,-1] #yellow\nc7=[1,1,1] #white\n\n\npos_colors = [c1,c2,c3,c4,c5,c6,c7]\npos_locs = np.arange(1,9,1)\n\ndelay_short=1\ndelay_inter=4\ndelay_long=7\n\nlow_load = 3\nhigh_load = 7\n\ntrials_each = 8# 6-7min aprox 16 ##12-15 min aprox\n\n\n##file 1: short version\n# outputs_short=[]\n\n# for delay in [delay_short, delay_long]:\n# outputs_ = []\n# for loads in [low_load, high_load]:\n# for t in range(trials_each):\n# number_grey_pos = 8-loads\n# list_grey = [no_stim for i in range(number_grey_pos)]\n# list_colors = random.sample(pos_colors,loads) \n# list_trial = list_grey + list_colors \n# #\n# random.shuffle(list_trial) \n# #\n# pos_locs = np.arange(0,8,1)\n# candidate_targets = pos_locs[np.array([list_trial[i] !=[0,0,0] for i in range(8)]) ] ##locations with color\n# target_ = random.choice(list(candidate_targets))\n# response_cue = list_trial[target_]\n# #\n# target_angle = np.arange(0,360,45)[target_]\n# #\n# output = list_trial + [response_cue] + [target_angle] + [loads] + [delay] + [t]\n# outputs_.append(output)\n# ###\n# trials = pd.DataFrame(outputs_)\n# trials.columns=['Color0', 'Color45', 'Color90', 'Color135', 'Color180', 'Color225', 'Color270', 'Color315', 'Cueresp', 'target_angle', 'load', 'delay', 'trial']\n# if delay==delay_short:\n# trials.to_excel('trials_short_delay.xlsx')\n# else:\n# trials.to_excel('trials_long_delay.xlsx')\n\n\n\n\n##file 2: long version\noutputs_short=[]\n\nfor delay in [delay_short, delay_inter, delay_long]:\n outputs_ = []\n for loads in [low_load, high_load]:\n for t in range(trials_each):\n number_grey_pos = 8-loads\n list_grey = [no_stim for i in range(number_grey_pos)]\n list_colors = random.sample(pos_colors,loads) \n list_trial = list_grey + list_colors \n #\n random.shuffle(list_trial) \n #\n pos_locs = np.arange(0,8,1)\n candidate_targets = pos_locs[np.array([list_trial[i] !=[0,0,0] for i in range(8)]) ] ##locations with color\n target_ = random.choice(list(candidate_targets))\n response_cue = list_trial[target_]\n #\n target_angle = np.arange(0,360,45)[target_]\n #\n indiv_colors = list(np.concatenate(list_trial))\n output = indiv_colors + [response_cue[0]] + [response_cue[1]] + [response_cue[2]] + [target_angle] + [loads] + [delay] + [t]\n outputs_.append(output)\n ###\n trials = pd.DataFrame(outputs_)\n colors_columns = [['Color'+a+'_r', 'Color'+a+'_g', 'Color'+a+'_b'] for a in ['0', '45', '90', '135', '180', '225', '270', '315'] ]\n colors_columns = list(np.concatenate(colors_columns)) \n Column_names = colors_columns + ['Cueresp_r', 'Cueresp_g', 'Cueresp_b', 'target_angle', 'load', 'delay', 'trial']\n trials.columns=Column_names\n if delay==delay_short:\n trials.to_excel('trials_short_delay3.xlsx')\n elif delay==delay_inter:\n trials.to_excel('trials_inter_delay3.xlsx')\n else:\n trials.to_excel('trials_long_delay3.xlsx')\n\n\n\n","sub_path":"task/stims_generator2.py","file_name":"stims_generator2.py","file_ext":"py","file_size_in_byte":3545,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"417114282","text":"import random\n\n# 점수 알고리즘을 위한 random 모듈 import\n\n\nclass bowling_board(): # OOP 5대 원칙중 단일 책임 원칙(SRP)에 따라 board 만 분리\n def __init__(self):\n self.history = []\n\n def add_score(self, name, score):\n self.history.append(name + \" : \" + score)\n\n def get_history(self):\n return self.history\n\n\nclass bowling_game(): # OOP 5대 원칙중 단일 책임 원칙(SRP)에 따라 game 코드만 분리\n def __init__(self, num_of_players, names_of_players):\n self.num_of_players = num_of_players\n self.names = names_of_players\n self.board = bowling_board() # 점수판\n\n # bowling 클래스의 num_of_players 초기화 될 때 각각 인자로 받은 값으로 정의\n def __make_score(self, user_input):\n rand = random.randrange(0, 10)\n user_input += rand # 입력 받은 값의 1부터 10까지의 임의의 수를 더함\n if user_input > 10:\n user_input -= 10\n return str(user_input) # 문자열 연산에 필요한 값이기 때문에 str로 형 변환을 해주어야 함\n\n def shoot(self, user_input):\n score = self.__make_score(user_input)\n self.board.add_score(self.names[len(self.board.get_history()) - 1],\n score)\n\n def get_board(self):\n return self.board\n\n\nclass bowling_informations():\n @staticmethod\n def print_rules():\n print(\"\"\"\n 반갑습니다.\\n\n 이 볼링 게임에 대해서 설명 드리도록 하겠습니다.\\n\n 1부터 10 사이의 수를 입력해주세요.\\n\n 저는 여기에 1부터 10까지의 임의의 수를 더하겠습니다.\\n\n 이 값이 10보다 작다면 여러분의 점수이고,\\n\n 그렇지 않다면 그 값에 10을 뺀 값이 여러분의 점수입니다.\n \"\"\")\n\n @staticmethod\n def print_greeting(num_of_players):\n if (num_of_players is 1): # 플레이어\n print(\"안녕하세요. 혼자 플레이 하시는군요!\")\n else:\n print(\"%d분 안녕하세요!\" % num_of_players)\n\n\ndef main():\n bowling_informations.print_rules()\n\n num_of_players = int(input(\"플레이어 수를 입력해주세요: \")) # 정수형 값으로 플레이어수를 입력 받음\n names = []\n\n if num_of_players is 0:\n print(\"게임을 종료합니다.\")\n exit()\n\n bowling_informations.print_greeting(num_of_players)\n\n for i in range(0, num_of_players):\n name = input(\"%d번째 플레이어의 이름을 입력해주세요: \" %\n (i + 1)) # 사용자에게는 1부터 시작하는 셈이 익숙함으로 1부터 시작\n names.append(name)\n\n game = bowling_game(num_of_players, names)\n\n print(\"\\n\")\n\n for i in range(0, num_of_players):\n user_input = -1\n while user_input < 0 or user_input > 10:\n user_input = int(\n input(\"숫자를 입력해주세요: \")) # 숫자를 입력받아야 함으로 정수 int로 형 변환\n game.shoot(user_input)\n\n print(\"\\n\\n-----게임종료-----\\n\\n\")\n\n for history in game.get_board().get_history():\n print(history)\n\n\nmain()\n","sub_path":"OOP/bowling.py","file_name":"bowling.py","file_ext":"py","file_size_in_byte":3211,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"567724206","text":"import csv\nimport statistics\n\n#Abrir arquivo base para calcular as medianas\nf = open('C:/Users/marco.junior/Desktop/TabelaDelphi.csv', encoding='UTF-8')\n\n#Criar lists a partir do arquivo aberto.\nSkuMedian = []\nPriceToMedian = []\n\nreader = csv.reader(f, delimiter = ',')\nfor row in reader:\n SkuMedian.append(row[0])\n PriceToMedian.append(row[4])\nf.close()\n\n#Excluir Cabeçalho das listas criadas e remover as duplicatas\ndel SkuMedian[0]\ndel PriceToMedian[0]\n\nPriceToMedian = [float(x) for x in PriceToMedian]\nSkuClean = list(set(SkuMedian))\n\n#Calcular a Mediana da Base\nMedian = []\ni = 0\nk = 0\nwhile k in range(len(SkuClean)):\n c = []\n c.append(SkuClean[k])\n PriceListToMedian = []\n for index, item in enumerate(SkuMedian):\n if item == c[0]:\n j = index\n PriceListToMedian.append(float(PriceToMedian[j]))\n PriceListToMedian = [x for x in PriceListToMedian if x != 0]\n if PriceListToMedian == []:\n Median.append(0)\n else:\n MedianToappend = statistics.median(PriceListToMedian)\n Median.append(MedianToappend)\n k += 1\nMedian = [int(x) for x in Median]\n\n#Abrir CSV Lojista e criar lists com as informações\nseller = open('C:/Users/marco.junior/Desktop/PricePartner53.csv', encoding='UTF-8')\n\nSellersSKU = []\nSellersPrice = []\nreader = csv.reader(seller, delimiter = ',')\nfor row in reader:\n SellersSKU.append(row[0])\n SellersPrice.append(row[1])\nseller.close()\ndel SellersSKU[0]\ndel SellersPrice[0]\nSellersPrice = [float(x) for x in SellersPrice]\n\n#Escrever o Cabeçalho no arquivo gerado no Output\nheader = [\"SKU\", \"Preço enviado\", \"Mediana\", \"Porcentagem\"]\nwith open('DelphiPrecos2.csv', 'w',newline='') as csvfile:\n spamwriter = csv.writer(csvfile, delimiter=',',\n quotechar='|', quoting=csv.QUOTE_MINIMAL)\n spamwriter.writerow(header)\n\n#Comparar CSV Lojista com Mediana Calculada e printar no arquivo gerado caso o preço seja desproporcional à mediana\ni = 0\nwhile i in range(len(SellersSKU)):\n for index, item in enumerate(SkuClean):\n if item == SellersSKU[i]:\n j = index\n if(SellersPrice[i] != 0):\n if (SellersPrice[i] <= Median[j]* 0.6) or (SellersPrice[i] >= Median[j]* 3.0):\n Percentage = int((SellersPrice[i] * 100)/Median[j])\n print(SellersSKU[i], SellersPrice[i], Median[j], Percentage)\n Row = [SellersSKU[i],SellersPrice[i],Median[j], Percentage]\n with open('DelphiPrecos2.csv', 'a', newline='') as csvfile:\n spamwriter = csv.writer(csvfile, delimiter=',',\n quoting=csv.QUOTE_MINIMAL)\n spamwriter.writerow(Row)\n\n i += 1","sub_path":"untitled/venv/LendoCSV/CódigoCompleto.py","file_name":"CódigoCompleto.py","file_ext":"py","file_size_in_byte":2766,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"308371482","text":"\"\"\"\nThis spider is a SalesStaff spider created on top of the ATSSpider\nscrapy crawl salesstaff -a mining_job_id=9999 -a iteration=1 -a extract=1 -a url=\"http://www.sales-staff.de/kandidaten/#stellenangebote\"\n\nsample url:\nhttp://www.sales-staff.de/kandidaten/#stellenangebote\n\"\"\"\n\nfrom re import compile\nfrom scrapy.http import Request\nfrom scrapy.selector import Selector\nfrom urlparse import urljoin\n\nfrom brightcorp.base.atsspiders import ATSSpider\nfrom brightcorp.items import BrightcorpItemLoader\nfrom brightcorp.processors import Prefix\n\n\nclass SalesStaff(ATSSpider):\n\n name = \"salesstaff\"\n ref_re = compile(r\"(\\d+)$\")\n\n def parse(self, response):\n sel = Selector(response)\n if not hasattr(self, \"logo_url\"):\n logo_url = sel.xpath('//img[@class=\"logo\"]/@src').extract()\n if logo_url:\n self.logo_url = logo_url\n\n iframe_url = sel.xpath(\n '//iframe[@name=\"Stellenangebote\"]/@src').extract()\n if iframe_url:\n yield Request(iframe_url[0], callback=self.parse_jobs_list)\n\n def parse_jobs_list(self, response):\n sel = Selector(response)\n if not self.expected_job_count_set:\n job_count = sel.xpath('//div[@class=\"left\"]/text()').extract()\n if job_count:\n self.expected_job_count = job_count\n\n jobs = sel.xpath('//table[@class=\"recordList\"]//tr')\n for job in jobs:\n job_url = job.xpath('./td/a/@href').extract()\n if job_url:\n job_url = urljoin(response.url, job_url[0])\n meta = {\n 'title': job.xpath('./td/a/text()').extract(),\n 'cat': job.xpath(\n './td[@class=\"category\"]/text()').extract(),\n 'loc': job.xpath('./td[@class=\"region\"]/text()').extract(),\n }\n yield Request(\n job_url, callback=self.parse_job_callback(), meta=meta\n )\n\n next_url = sel.xpath('//a[@class=\"button next\"]/@href').extract()\n if next_url:\n next_url = urljoin(response.url, next_url[0])\n yield Request(next_url, callback=self.parse_jobs_list)\n\n def parse_job(self, response):\n loader = BrightcorpItemLoader(response=response)\n\n loader.add_value('url', response.url)\n loader.add_value('logo_url', self.logo_url)\n loader.add_value('title', response.meta.get('title'))\n loader.add_value('location', response.meta.get('loc'))\n loader.add_value('jobcategory', response.meta.get('cat'))\n loader.add_value(\n 'referencenumber', response.url,\n Prefix('%s-' % self.name), re=self.ref_re\n )\n\n loader.add_xpath(\n 'description',\n '//div[@id=\"jobBody\"]/following-sibling::node()'\n )\n\n yield loader.load_item()\n","sub_path":"brightcorp/brightcorp/spiders/salesstaff.py","file_name":"salesstaff.py","file_ext":"py","file_size_in_byte":2887,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"172794886","text":"import numpy as np\nimport matplotlib.pyplot as plt\nfrom camparing_epsilon import run_experiment as eps_exp\n\n\nclass Bandit:\n def __init__(self,m,upper_limit):\n self.m = m\n self.mean = upper_limit\n self.N = 1\n\n def pull(self):\n return np.random.randn() + self.m\n\n def update(self,x):\n self.N += 1\n self.mean = (1 - 1.0/self.N)*self.mean + 1.0/self.N*x\n\n\ndef run_experiment(m1,m2,m3,upper_limit,N):\n bandits = [Bandit(m1,upper_limit), Bandit(m2,upper_limit), Bandit(m3,upper_limit)]\n\n data = np.empty(N)\n for i in range(N):\n #optimistic initial\n j = np.argmax([b.mean for b in bandits])\n x = bandits[j].pull()\n bandits[j].update(x)\n\n #for the plot\n data[i] = x\n cumulative_average =np.cumsum(data)/(np.arange(N)+1)\n\n #plot moving average ctr\n\n plt.plot(cumulative_average)\n plt.plot(np.ones(N)*m1)\n plt.plot(np.ones(N)*m2)\n plt.plot(np.ones(N)*m3)\n plt.xscale('log')\n plt.show()\n\n for bandit in bandits:\n print(bandit.mean)\n\n return cumulative_average\n\n\nif __name__ == '__main__':\n c_1 = run_experiment(1.0,2.0,3.0,10,100000)\n c_05 = run_experiment(1.0,2.0,3.0,0.05,100000)\n c_e= eps_exp(1.0,2.0,3.0,0.1,100000)\n\n\n #log scale plot\n plt.title(label=\"log_scale\")\n plt.plot(c_1,label= 'optimistic = 10')\n plt.plot(c_e,label= 'eps = 0.1')\n plt.legend()\n plt.xscale('log')\n plt.show()\n\n # linear plot\n plt.title(label=\"linear plot\")\n plt.plot(c_1,label= 'optimistic = 10')\n plt.plot(c_e, label='eps = 0.1')\n\n plt.legend()\n plt.show()","sub_path":"Machine Learning/optimistic_initial_values.py","file_name":"optimistic_initial_values.py","file_ext":"py","file_size_in_byte":1615,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"328561059","text":"class Solution(object):\r\n def numberOfArithmeticSlices(self, A):\r\n \"\"\"\r\n :type A: List[int]\r\n :rtype: int\r\n \"\"\"\r\n count = sum = 0\r\n \r\n for i in range(1,len(A)-1):\r\n if A[i]-A[i-1] == A[i+1]-A[i]:\r\n \r\n count += 1 # every time move forward one means a new array itself, and one new combine with previous one\r\n sum += count\r\n else:\r\n count = 0\r\n \r\n return sum\r\n\r\nif __name__ == '__main__':\r\n\r\n test = Solution()\r\n print(test.numberOfArithmeticSlices([1,3,5,6,7,9,11,13]))\r\n","sub_path":"numberOfArithmeticSlices.py","file_name":"numberOfArithmeticSlices.py","file_ext":"py","file_size_in_byte":632,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"134107191","text":"#!/usr/bin/python\n\nimport os, sys, shutil\nimport numpy as np\nimport pyrap.tables as tb\n\nimport logging\nlogger = logging.getLogger('PiLL')\n\ndef merge_parmdb(parmdb_p, parmdb_a, parmdb_out, clobber=False):\n \"\"\"\n Merges facet selfcal parmdbs into a parmdb for a single band\n\n Parameters\n ----------\n parmdb_p : str\n Filename of CommonScalarPhase and TEC parmdb\n parmdb_a : str\n Filename of Gain parmdb. The nearset match in frequency to that of the\n input band will be used\n parmdb_out : str\n Filename of output file\n clobber : bool, optional\n If True, overwrite existing output file\n\n \"\"\"\n import lofar.parmdb as parmdb\n if type(clobber) is str:\n if clobber.lower() == 'true':\n clobber = True\n else:\n clobber = False\n\n if os.path.exists(parmdb_out):\n if clobber:\n shutil.rmtree(parmdb_out)\n else:\n return\n pdb_out = parmdb.parmdb(parmdb_out, create=True)\n\n # Copy over the CommonScalar phases and TEC\n pdb_p = parmdb.parmdb(parmdb_p)\n for parmname in pdb_p.getNames():\n parms = pdb_p.getValuesGrid(parmname)\n pdb_out.addValues(parms)\n\n # Copy over the Gains\n pdb_a = parmdb.parmdb(parmdb_a)\n for parmname in pdb_a.getNames():\n parms = pdb_a.getValuesGrid(parmname)\n pdb_out.addValues(parms)\n\n # Write values\n pdb_out.flush()\n \n\ndef find_nchan(ms):\n \"\"\"\n Find number of channel in this ms\n \"\"\"\n with tb.table(ms+'/SPECTRAL_WINDOW', ack=False) as t:\n nchan = t.getcol('NUM_CHAN')\n assert (nchan[0] == nchan).all() # all spw have same channels?\n logger.debug('Channel in '+ms+': '+str(nchan[0]))\n return nchan[0]\n\n\ndef find_chanband(ms):\n \"\"\"\n Find bandwidth of a channel\n \"\"\"\n with tb.table(ms+'/SPECTRAL_WINDOW', ack=False) as t:\n chan_w = t.getcol('CHAN_WIDTH')[0]\n assert all(x==chan_w[0] for x in chan_w) # all chans have same width\n logger.debug('Channel width in '+ms+': '+str(chan_w[0]/1e6)+' MHz')\n return chan_w[0]\n\n\ndef find_timeint(ms):\n \"\"\"\n Get time interval in seconds\n \"\"\"\n with tb.table(ms, ack=False) as t:\n Ntimes = len(set(t.getcol('TIME')))\n with tb.table(ms+'/OBSERVATION', ack=False) as t:\n deltat = (t.getcol('TIME_RANGE')[0][1]-t.getcol('TIME_RANGE')[0][0])/Ntimes\n logger.debug('Time interval for '+ms+': '+str(deltat))\n return deltat\n\n\ndef get_phase_centre(ms):\n \"\"\"\n Get the phase centre of the first source (is it a problem?) of an MS\n \"\"\"\n field_no = 0\n ant_no = 0\n with tb.table(ms + '/FIELD', ack=False) as field_table:\n direction = field_table.getcol('PHASE_DIR')\n ra = direction[ ant_no, field_no, 0 ]\n dec = direction[ ant_no, field_no, 1 ]\n return (ra*180/np.pi, dec*180/np.pi)\n\n","sub_path":"autocal/lib_pipeline_ms.py","file_name":"lib_pipeline_ms.py","file_ext":"py","file_size_in_byte":2844,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"384567388","text":"from django.shortcuts import render\nfrom rest_framework import generics, status # generic.ListAPIVIEW allowed us to create a class inherits from a generic API view # status for access to http status code when we use Response\nfrom .serializers import RoomSerializer, CreateRoomSerializer\nfrom api.models import Room\nfrom rest_framework.views import APIView\nfrom rest_framework.response import Response # get response from our view\n\n# Create your views here.\n\n\nclass RoomView(generics.ListAPIView): # Is a already set up to return to us all of difference room \n queryset = Room.objects.all() \n serializer_class = RoomSerializer\n\n\nclass CreateRoomView(APIView): # APIView allowed us to overwrite default ( get and post )method \n serializer_class = CreateRoomSerializer\n\n def post(self, request, format=None): \n if not self.request.session.exists(self.request.session.session_key): # For at identify host we should use session-key.# Session is a temporary connection between to computer or devices\n self.request.session.create() # if there is no session so makes a session\n\n serializer = self.serializer_class(data=request.data)\n if serializer.is_valid(): # if there are those data, that should to be like 'guest_can_pause', 'votes_to_skip'\n guest_can_pause = serializer.data.get('guest_can_pause') # get they data\n votes_to_skip = serializer.data.get('votes_to_skip')\n host = self.request.session.session_key\n queryset = Room.objects.filter(host=host) \n if queryset.exists(): # If there is any room with the same host code\n room = queryset[0] # get det first room\n room.guest_can_pause = guest_can_pause\n room.votes_to_skip = votes_to_skip\n room.save(update_fields=['guest_can_pause', 'votes_to_skip'])\n return Response(RoomSerializer(room).data, status=status.HTTP_200_OK)\n else: # If there is any room so makes a room \n room = Room(host=host, guest_can_pause=guest_can_pause,\n votes_to_skip=votes_to_skip)\n room.save()\n return Response(RoomSerializer(room).data, status=status.HTTP_201_CREATED) # serilize the room\n\n return Response({'Bad Request': 'Invalid data...'}, status=status.HTTP_400_BAD_REQUEST)","sub_path":"music_controller/api/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2369,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"182132811","text":"import networkx as nx\nimport xlsxwriter\nimport operator\nimport os\n\n\n\n\ntime_index = 0\ndataset_percentage = 0\n\n\n\n# Start from the first cell below the headers.\nmanifest = 15\n\n# Candidate tested functions\nfunction_lists = [nx.resource_allocation_index,\n nx.jaccard_coefficient,\n nx.adamic_adar_index,\n nx.preferential_attachment]\n\nprecentage_conatainer = [0.1, 0.3, 0.5, 0.7, 0.9]\n\ndef test_predictions(datasetPath, threshold, percentage, prediction_function, worksheet, row, col):\n # Creating a graph\n Ga = nx.Graph()\n Gb = nx.Graph()\n\n\n total_lines = 0\n currentIndex = 0\n bList = []\n\n\n # Loop the Dataset to calculate the total lines, and put all the data into graph A\n with open(datasetPath) as f:\n for line in f:\n total_lines = total_lines + 1\n inner_list = [int(elt.strip()) for elt in line.split()]\n Ga.add_node(inner_list[0])\n Ga.add_node(inner_list[1])\n\n\n\n # Populate the graph with half data\n with open(datasetPath) as f:\n\n for line in f:\n currentIndex += 1\n inner_list = [int(elt.strip()) for elt in line.split()]\n\n if currentIndex <= total_lines * percentage:\n Ga.add_edge(inner_list[0], inner_list[1])\n else:\n if currentIndex >= total_lines:\n break\n bList.append((inner_list[0], inner_list[1]))\n\n\n no_edge_pairs = nx.non_edges(Ga)\n\n preds = prediction_function(Ga, list(no_edge_pairs))\n mylist = (list(preds))\n mylist.sort(key=operator.itemgetter(2), reverse=True)\n\n number_of_top_percent = int(threshold * (len(mylist) / 100))\n\n cList = []\n topPercentList = mylist[0:number_of_top_percent]\n for item in topPercentList:\n cList.append((item[0], item[1]))\n\n dList = list(set(bList + cList))\n repeatedNumber = len(bList) + len(cList) - len(dList)\n\n worksheet.write(row, col, round(repeatedNumber / len(bList),3) )\n worksheet.write(row, col + manifest, round(repeatedNumber / len(topPercentList), 3) )\n\n\n\ndef start_test():\n\n for current_dataset_percentage in precentage_conatainer:\n print('%f ' % (current_dataset_percentage))\n\n result_output_path = \"Results/results\" + str(current_dataset_percentage*10) + \".xlsx\"\n # Create a workbook and add a worksheet.\n workbook = xlsxwriter.Workbook(result_output_path)\n\n # Add a bold format to use to highlight cells.\n bold = workbook.add_format({'bold': True})\n\n for current_function in function_lists:\n print(current_function.__name__)\n worksheet = workbook.add_worksheet(current_function.__name__)\n row = 1\n col = 1\n\n for current_threshold in range(10, 91, 20):\n print(' %d ' %(current_threshold))\n # AUC y-axis\n worksheet.write(row, 0, current_threshold, bold)\n worksheet.write(row+1, 0, \"Average\", bold)\n\n # precision y-axis\n worksheet.write(row, manifest, current_threshold, bold)\n\n col = 1\n datasetfiles = os.listdir(\"NewDatasets/\")\n for current_dataset in datasetfiles:\n print(\" {}\" + (current_dataset))\n # AUC x-axis\n worksheet.write(0, col, current_dataset, bold)\n\n # precision x-axis\n worksheet.write(0, col + manifest, current_dataset, bold)\n\n current_dataset_name = \"NewDatasets/\" + current_dataset\n\n\n test_predictions(current_dataset_name, current_threshold, current_dataset_percentage, current_function, worksheet, row, col)\n\n col += 1\n\n row += 1\n # average\n worksheet.write(row, 1, '=AVERAGE(B2:B6)')\n\n\n workbook.close()\n\ndef main():\n start_test()\n\n print(\"end\")\n\n\nif __name__ == \"__main__\":\n main()\n","sub_path":"Week10xls.py","file_name":"Week10xls.py","file_ext":"py","file_size_in_byte":4010,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"54034017","text":"from django.shortcuts import render, redirect\nfrom .models import Article, Comment\nfrom .forms import ArticleForm, CommentForm\n\n# Create your views here.\ndef index(request):\n articles = Article.objects.all()\n context = {\n 'articles': articles,\n }\n return render(request, 'articles/index.html', context)\n\ndef new(request):\n if request.method == \"POST\":\n form = ArticleForm(request.POST)\n form.save()\n return redirect('articles:index')\n else:\n form = ArticleForm()\n context = {\n 'form': form,\n }\n print(form)\n return render(request, 'articles/new.html', context)\n\ndef detail(request, article_pk):\n article = Article.objects.get(pk=article_pk)\n comments = article.comment_set.all()\n commentform = CommentForm()\n context = {\n 'article': article,\n 'commentform': commentform,\n 'comments': comments,\n }\n return render(request, 'articles/detail.html', context)\n\ndef edit(request, article_pk):\n article = Article.objects.get(pk=article_pk) \n if request.method == \"POST\":\n form = ArticleForm(request.POST, instance=article)\n form.save()\n return redirect('articles:detail', article_pk)\n else:\n form = ArticleForm(instance=article)\n context = {\n 'form': form,\n }\n return render(request, 'articles/new.html', context)\n\ndef delete(request, article_pk):\n article = Article.objects.get(pk=article_pk)\n article.delete()\n return redirect('articles:index')\n\ndef comment_create(request, article_pk):\n if request.method == \"POST\":\n comment_form = CommentForm(request.POST)\n comment = comment_form.save(commit=False)\n comment.article_id = article_pk\n comment.save()\n\n return redirect('articles:detail', article_pk)\n\ndef comment_delete(request, article_pk, comment_pk):\n comment = Comment.objects.get(pk=comment_pk)\n comment.delete()\n return redirect('articles:detail', article_pk)\n \n \n\n \n","sub_path":"03_Django/pair-programmig2/articles/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2011,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"48063272","text":"from django.db import models\nfrom django.urls import reverse\nfrom django.core import validators\nfrom django.utils.translation import ugettext_lazy as _\n\nfrom ticketflix.spectacle.models import Spectacle\nfrom ticketflix.room.models import Room\n\nclass Session(models.Model):\n\n date = models.DateField(\n auto_now=False,\n auto_now_add=False\n )\n\n time = models.TimeField(\n auto_now=False,\n auto_now_add=False\n )\n\n place = models.CharField(\n max_length=50\n )\n\n available_ticket_number = models.IntegerField()\n\n total_ticket_number = models.IntegerField()\n\n spectacle = models.ForeignKey(\n Spectacle,\n related_name='sessions',\n related_query_name='session',\n on_delete=models.CASCADE,\n null=True\n )\n\n price = models.FloatField(\n verbose_name=_(\"Preço\"),\n help_text=_(\"Preço\"),\n validators=[validators.MinValueValidator(0)],\n blank=False,\n default=0\n )\n\n room = models.ForeignKey(\n Room,\n related_name='sessions',\n related_query_name='sessions',\n on_delete=models.CASCADE,\n blank=False,\n default=None\n )\n\n def __str__(self):\n return ('Session ' + str(self.id))\n\n class Meta:\n verbose_name = (\"Sessão\")\n verbose_name_plural = (\"Sessões\")\n","sub_path":"ticketflix/session/models.py","file_name":"models.py","file_ext":"py","file_size_in_byte":1349,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"426122712","text":"from collections import OrderedDict\nfrom urllib.parse import urljoin\n\nfrom django.template.loader import render_to_string\nfrom rest_framework import exceptions\nfrom rest_framework.compat import coreapi\nfrom rest_framework.schemas import SchemaGenerator\n\n\ndef make_plain_schema(nested_schema) -> OrderedDict:\n \"\"\"Makes plain ordered schema from nested schema recursively.\"\"\"\n plain_schema = OrderedDict()\n\n def _unpack(schema, path=''):\n if hasattr(schema, 'data') and schema.data:\n for name, node in schema.data.items():\n new_path = '{} {}'.format(path, name) if path else name\n if hasattr(node, 'links') and node.links:\n plain_schema[new_path] = node\n else:\n _unpack(node, path=new_path)\n\n _unpack(nested_schema)\n return plain_schema\n\n\nclass CustomSchemaGenerator(SchemaGenerator):\n def get_link(self, path, method, view):\n methods = [\n 'get_path_fields',\n 'get_serializer_fields',\n 'get_pagination_fields',\n 'get_filter_fields'\n ]\n\n fields = []\n for method_name in methods:\n try:\n fields += getattr(self, method_name)(path, method, view)\n except (AttributeError, AssertionError):\n # it suppresses any exceptions caused by some custom serializers, methods etc.\n pass\n\n if fields and any([field.location in ('form', 'body') for field in fields]):\n encoding = self.get_encoding(path, method, view)\n else:\n encoding = None\n\n description = self.get_description(path, method, view)\n\n if self.url and path.startswith('/'):\n path = path[1:]\n\n return coreapi.Link(\n url=urljoin(self.url, path),\n action=method.lower(),\n encoding=encoding,\n fields=fields,\n description=description\n )\n\n\nclass ApiDocsHandler(object):\n template = 'api_docs/template.md'\n\n def __init__(self, project_name: [str, None]=None, template: [str, None]=None):\n self.project_name = project_name or ''\n self.template = template or self.template\n\n def render(self) -> str:\n generator = CustomSchemaGenerator(\n title=self.project_name,\n )\n schema = generator.get_schema()\n\n if not schema:\n raise exceptions.ValidationError(\n 'The schema generator did not return a schema Document'\n )\n\n return render_to_string(self.template, {\n 'project_name': self.project_name,\n 'api': make_plain_schema(schema)\n })\n","sub_path":"drf_api_docs/handlers.py","file_name":"handlers.py","file_ext":"py","file_size_in_byte":2685,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"576883745","text":"from discord.ext import commands, tasks\r\nfrom contextlib import redirect_stdout\r\r\nimport os\r\nimport subprocess\r\nimport traceback\r\nimport discord\r\nimport traceback\r\nimport io\r\nimport textwrap\r\n\r\n\r\n\r\nclass Admin(commands.Cog, command_attrs=dict(hidden=True)):\r\n def __init__(self, bot):\r\n self.bot = bot\r\n self._last_result = None\r\n\r\n\r\n def cleanup_code(self, content):\r\n \"\"\"Automatically removes code blocks from the code.\"\"\"\r\n # remove ```py\\n```\r\n if content.startswith('```') and content.endswith('```'):\r\n return '\\n'.join(content.split('\\n')[1:-1])\r\n\r\n # remove `foo`\r\n return content.strip('` \\n')\r\n\r\n async def cog_check(self, ctx):\r\n return await self.bot.is_owner(ctx.author)\r\n\r\n\r\n @commands.command()\r\n async def discord_py(self, ctx):\r\n await ctx.send(discord.__version__)\r\n\r\n @commands.command()\r\n async def load(self, ctx, module:str, opt:str = None):\r\n module = f'cogs.{module}'\r\n if opt is None:\r\n self.bot.load_extension(module)\r\n\r\n elif opt == 'un':\r\n self.bot.unload_extension(module)\r\n\r\n elif opt == 're':\r\n self.bot.reload_extension(module)\r\n\r\n else:\r\n return await ctx.message.add_reaction('\\N{BLACK QUESTION MARK ORNAMENT}')\r\n \r\n await ctx.message.add_reaction('\\N{WHITE HEAVY CHECK MARK}')\r\n\r\n \r\n @commands.command()\r\n async def restart(self, ctx):\r\n os.system('cals')\r\n subprocess.run(\"launc.py\", shell=True)\n \n @commands.command()\n async def shutdown(self, ctx):\n await bot.logout()\n \r\n\r\n \r\n \r\n\r\n async def say_permissions(self, ctx, member):\r\n permissions = member.guild_permissions\r\n e = discord.Embed(colour=member.colour)\r\n avatar = member.avatar_url_as(static_format='png')\r\n e.set_author(name=str(member), url=avatar)\r\n allowed, denied = [], []\r\n for name, value in permissions:\r\n name = name.replace('_', ' ').replace('guild', 'server').title()\r\n if value:\r\n allowed.append(name)\r\n else:\r\n denied.append(name)\r\n\r\n e.add_field(name='Allowed', value='\\n'.join(allowed))\r\n e.add_field(name='Denied', value='\\n'.join(denied))\r\n await ctx.send(embed=e)\r\n\r\n @commands.command()\r\n async def cp(self, ctx):\r\n \"\"\"Shows a member's permissions in a specific channel.\r\n If no channel is given then it uses the current one.\r\n You cannot use this in private messages. If no member is given then\r\n the info returned will be yours.\r\n \"\"\"\r\n guild = self.bot.get_guild(619926767821652000)\r\n channel = self.bot.get_channel(650399901284565023)\r\n member = ctx.guild.me\r\n\r\n await self.say_permissions(ctx, member)\r\n\r\n @cp.error\r\n async def load_error(self, ctx, error):\r\n await ctx.send(f'```py\\n{traceback.format_exc()}\\n```')\r\n\r\n @commands.command(aliases = ['role_list'])\r\n async def _list(self, ctx):\r\n guild = self.bot.get_guild(619926767821652000)\r\n desc = '\\n'.join(f'{role.name} - {role.id}' for role in reversed(guild.roles))\r\n embed = discord.Embed(title = '役職一覧', colour = ctx.author.colour, description = desc)\r\n await ctx.send(embed = embed)\r\n\r\n \r\n @commands.command(name='eval')\r\n async def _eval(self, ctx, *, body: str = None):\r\n \"\"\"Evaluates a code\"\"\"\r\n if body is None:\r\n return await ctx.send('w')\r\n\r\n env = {\r\n 'bot': self.bot,\r\n 'ctx': ctx,\r\n 'channel': ctx.channel,\r\n 'author': ctx.author,\r\n 'guild': ctx.guild,\r\n 'message': ctx.message,\r\n '_': self._last_result\r\n }\r\n\r\n env.update(globals())\r\n \r\n body = self.cleanup_code(body)\r\n stdout = io.StringIO()\r\n try:\r\n to_compile = f'async def func():\\n{textwrap.indent(body, \" \")}'\r\n exec(to_compile, env)\r\n except Exception as e:\r\n return await ctx.send(f'```py\\n{e.__class__.__name__}: {e}\\n```')\r\n func = env['func']\r\n \r\n try:\r\n with redirect_stdout(stdout):\r\n ret = await func()\r\n except Exception as e:\r\n value = stdout.getvalue()\r\n await ctx.send(f'```py\\n{value}{traceback.format_exc()}\\n```')\r\n else:\r\n value = stdout.getvalue()\r\n if ret is None:\r\n if value:\r\n await ctx.send(f'```py\\n{value}\\n```')\r\n else:\r\n self._last_result = ret\r\n await ctx.send(f'```py\\n{value}{ret}\\n```')\r\n\r\n @commands.command()\r\n async def tes_(self, ctx, member):\r\n await ctx.send(type(member))\r\ndef setup(bot):\r\n bot.add_cog(Admin(bot))","sub_path":"cogs/admin.py","file_name":"admin.py","file_ext":"py","file_size_in_byte":4895,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"358463805","text":"import csv\nfrom re import sub\nfrom decimal import Decimal\nimport glob, os\n\nGREEN = '\\033[32m'\nRED = '\\033[31m'\nBLUE = '\\033[36m'\nENDC = '\\033[0m'\n\ndef moneyToFloat( money_string ):\n\t\n\tif money_string[0] != '-':\n\t\tmoney_float = Decimal( sub(r'[^\\d.]', '', money_string) ) \n\telse:\n\t\tmoney_float = Decimal( sub(r'[^\\d.]', '', money_string) )\n\t\tmoney_float = 0 - money_float\n\n\treturn money_float\n\ndef moneyToString( money_float ):\n\t\n\tif money_float >= 0:\n\t\treturn \"$\" + str(money_float)\n\telif money_float < 0:\n\t\treturn \"-$\" + str(money_float * -1)\n\ndef compare( date, reg_or_adtnl ):\n\n\tfilename1 = 'Payment' + '/' + date + '.csv'\n\twith open(filename1, 'r') as csvfile:\n\n\t\tpayment_activity = csv.DictReader(csvfile)\n\t\tresult = {}\n\n\t\tfor row_a in payment_activity:\n\t\n\t\t\tamount_paid \t\t= moneyToFloat( row_a['Amount'] )\n\t\t\tamount_discrepency \t= moneyToFloat( row_a['Amount'] )\n\n\t\t\tfilename2 = reg_or_adtnl + '/' + date + '.csv'\n\t\t\twith open(filename2, 'r') as csvfile2:\n\t\t\t\tactivity_2 = csv.DictReader(csvfile2)\n\n\t\t\t\tfor row_b in activity_2:\n\t\t\t\t\tif row_a['Order Number'] == row_b['Order Number']:\n\t\t\t\t\t\tamount_discrepency = amount_discrepency - moneyToFloat( row_b['Purchase amount'] )\n\n\t\t\tresult[row_a['Order Number']] = amount_discrepency\n\n\t\treturn result\n\ndef dict_reconcile( payment_dict, date, style ):\n\n\tresult = {}\n\n\tfor key in payment_dict:\n\n\t\tamount_paid \t\t= payment_dict[key]\n\t\tamount_discrepency \t= payment_dict[key]\t\n\n\t\tfilename1 = style + '/' + date + '.csv'\n\t\twith open(filename1, 'r') as csvfile:\n\n\t\t\tadditional_activity = csv.DictReader(csvfile)\n\t\t\t\n\t\t\tfor row_a in additional_activity:\n\n\t\t\t\tif row_a['Order Number'] == key:\n\t\t\t\t\tif style != 'Payment':\n\t\t\t\t\t\tamount_discrepency = amount_discrepency - moneyToFloat( row_a['Purchase amount'] )\n\t\t\t\t\telif style == 'Payment':\n\t\t\t\t\t\tamount_discrepency = amount_discrepency - moneyToFloat( row_a['Amount'] )\n\n\t\tresult[key] = amount_discrepency\n\n\treturn result\n\ndef getDates( directory ):\n\t\n\tdates = []\n\tos.chdir( directory )\n\tfor file in glob.glob( \"*.csv\" ):\n\t\tdates.append( file.split('.')[0] )\n\n\tos.chdir( '../' )\n\n\treturn dates\n\ndef class_breakdown( date ):\n\n\tnumbers = {}\n\tmoney \t= {}\n\n\tfilename1 = 'Registration' + '/' + date + '.csv'\n\tfilename2 = 'Additional' + '/' + date + '.csv'\n\twith open(filename1, 'r') as csvfile:\n\t\treg_activity = csv.DictReader(csvfile)\n\t\tfor row_a in reg_activity:\n\t\t\tsession_name = row_a['Session']\n\t\t\tprint()\n\t\t\tprint( \"Session : \" + session_name )\n\t\t\tsession_name = session_name[:session_name.find(\"(\")]\n\t\t\tprint( \"Session : \" + session_name )\n\t\t\t\n\t\t\tnumbers.setdefault(session_name, 0)\n\t\t\tmoney.setdefault(session_name, 0)\n\t\t\t\n\t\t\tprint( \"for \" + str(row_a['Participant']) + \" on \" + str(date) );\n\t\t\tnumbers[session_name] = numbers[session_name] + 1\n\t\t\tmoney[session_name] = money[session_name] + moneyToFloat(row_a['Purchase amount'])\n\t\t\tprint( \"adding \" + str(moneyToFloat(row_a['Purchase amount'])) + \" to \" + str(money[session_name]) )\n\n\twith open(filename2, 'r') as csvfile:\n\t\tadditional_activity = csv.DictReader(csvfile)\n\t\tfor row_b in additional_activity:\n\t\t\tearly_drop_off = 'Early Drop Off'\n\t\t\tlate_pick_up = 'Late Pick Up'\n\n\t\t\tsession_name = row_b['Session']\n\t\t\tsession_name = session_name[:session_name.find(\"(\")]\n\n\t\t\tmoney.setdefault( early_drop_off, 0)\n\t\t\tmoney.setdefault( late_pick_up, 0)\n\t\t\tif \"Early\" in row_b['Item Name']:\n\t\t\t\tmoney[early_drop_off] = money[early_drop_off] + moneyToFloat(row_b['Purchase amount'])\n\t\t\tif \"Late\" in row_b['Item Name']:\n\t\t\t\tmoney[late_pick_up] = money[late_pick_up] + moneyToFloat(row_b['Purchase amount'])\n\t\t\tmoney[session_name] = money[session_name] + moneyToFloat(row_b['Purchase amount'])\n\n\n\treturn_tuple = (numbers, money)\n\treturn return_tuple\n\n\n","sub_path":"ActRecon.py","file_name":"ActRecon.py","file_ext":"py","file_size_in_byte":3689,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"134898519","text":"# Visualize the topics\nimport pyLDAvis\nimport pyLDAvis.gensim\nimport gensim\nimport pickle\n\nwith open('./pickle/bow_corpus.pkl', 'rb') as f:\n bow_corpus = pickle.load(f)\n\nwith open('./pickle/corpus_tfidf.pkl', 'rb') as f:\n corpus_tfidf = pickle.load(f)\n\nwith open('./pickle/dictionary.pkl', 'rb') as f:\n dictionary = pickle.load(f)\n\nlda_model = gensim.models.LdaModel.load('./pickle/lda_model')\nvis_10topics = pyLDAvis.gensim.prepare(lda_model, bow_corpus, dictionary)\npyLDAvis.save_html(vis_10topics, './DataViz/Viz10Topics.html')\n\nlda_model_tfidf = gensim.models.LdaModel.load('./pickle/lda_model_tfidf')\nvis_10topics_tfidf = pyLDAvis.gensim.prepare(lda_model_tfidf, corpus_tfidf, dictionary)\npyLDAvis.save_html(vis_10topics_tfidf, './DataViz/Viz10TopicsTFIDF.html')\n\nlda_model_mallet_tfidf = gensim.models.wrappers.LdaMallet.load('./pickle/lda_model_mallet_tfidf')\nlda_mallet2gensim = gensim.models.wrappers.ldamallet.malletmodel2ldamodel(lda_model_mallet_tfidf, iterations=1000)\nvis_mallet_tfidf = pyLDAvis.gensim.prepare(lda_mallet2gensim, corpus_tfidf, dictionary)\npyLDAvis.save_html(vis_mallet_tfidf, './DataViz/Viz10TopicsMalletTFIDF.html')","sub_path":"15-Visualize10TopicsModels.py","file_name":"15-Visualize10TopicsModels.py","file_ext":"py","file_size_in_byte":1156,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"414543389","text":"class tool(object):#tool成为类对象\n num=0#类属性\n def __init__(self,name):#\n self.name=name#实例属性\n tool.num+=1#调用类属性的方法，类名.类属性。即可\n #类属性每个实例的对象都可以在类中的方法中调用\n #类的属性，但是方法与方法之间的之间的属性不可以直接调用\n #类属性是可以被更改的，再次创建对象的时候类属性会被改变\n print(tool.num)\ntool1=tool('铁铲')#tool1为实例对象\ntool2=tool('铁铲1')\ntool3=tool('铁铲2')\n\n","sub_path":"01-python基础/62-类属性和实例属性，类对象和实例对象.py","file_name":"62-类属性和实例属性，类对象和实例对象.py","file_ext":"py","file_size_in_byte":603,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"589785819","text":"import csv\nfrom django.core.management.base import BaseCommand\nfrom project_app.models import Station, Route\n\n\nclass Command(BaseCommand):\n help = 'importing stations from file to DB'\n\n def add_arguments(self, parser):\n pass\n\n # def handle(self, *args, **options):\n # with open('moscow_bus_stations.csv', 'rt', encoding='cp1251') as csv_file:\n # table_reader = csv.reader(csv_file, delimiter=';')\n # next(table_reader)\n # for line in table_reader:\n # # for obj in list(Station.objects.all()):\n # # print(obj.routes.all())\n # # break\n # # print(line)\n # routes_obj = []\n # routes_list = line[7].split('; ')\n # for route in routes_list:\n # if Route.objects.filter(name=route):\n # route_obj = Route.objects.get(name=route)\n # # print(route_obj)\n # print(f'маршрут {route} уже есть')\n # routes_obj.append(route_obj)\n # else:\n # Route.objects.create(name=route)\n # route_obj = Route.objects.get(name=route)\n # print(f'создание маршрута {route}')\n # routes_obj.append(route_obj)\n # print(routes_obj)\n # station = Station.objects.create(latitude=line[3], longitude=line[2], name=line[1])\n # station.save()\n # print(station.routes.set(routes_obj))\n # station.save()\n # print(station.routes.all())\n # print(route_obj.stations.last())\n # # if len(Station.objects.all()) == 10:\n # # break\n #\n # routes_obj.clear()\n\n def handle(self, *args, **options):\n with open('moscow_bus_stations.csv', newline='', encoding='cp1251') as csv_file:\n reader = csv.DictReader(csv_file, delimiter=';')\n for row in reader:\n station = Station()\n station.id = row['ID']\n station.name = row['Name']\n station.latitude = row['Latitude_WGS84']\n station.longitude = row['Longitude_WGS84']\n station.save()\n for route in row['RouteNumbers'].split('; '):\n obj, routes = Route.objects.get_or_create(name=route)\n station.routes.add(obj)\n print('Строка обработана - {}'.format(row))\n print('Загрузка завершена')\n\n\n\n # print(Station.routes.first())\n\n\n","sub_path":"project_app/management/commands/import_stations.py","file_name":"import_stations.py","file_ext":"py","file_size_in_byte":2722,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"29878788","text":"#!/usr/bin/env python\n\"\"\"\n This is a script for finding all json parameter files located in a directiory tree. This script is most powerful\n when used in the cluster experiments. It allows me to make changes to branches of the experiment directory structure.\n \n The script will then attempt to open these json files, make an edit before saving the changes.\n \n BE AWARE: USE WITH CAUTION\n\"\"\"\n\nimport os\nimport sys\n\nfrom Directory_tree_searching import load_json_data, save_json_data, find_file_paths_in_sub_directories\n\n\ndef print_help():\n print(\"\\nThis script can sensitive so handle with care.\\n\\n\"\n \"The parameter inputs for this script are:\\n\"\n \" - sys.arg[1] = Base directory path (preferably from root) that we will be finding parameter files from.\\n\"\n \" - sys.arg[2] = The filename of the parameter files.\\n\"\n \" - sys.arg[3] = The file path filters to be applied, separated by (,). \\n\"\n \" - sys.arg[4] = the Key of the variable you wish to alter.\\n\"\n \" - sys.arg[5] = The value (i.e. int, str, or bool) that you wish to replace.\\n\"\n \" - sys.arg[6] = *OPTIONAL* Override all user inputs in the script (enter True/False)\\n\\n\"\n \"To print the locations of all parameter files to be altered - do NOT provide a key or value\\n\")\n\n\ndef make_backup_json(file_path, parameter_file_data):\n # make backup\n if file_path.endswith('.json'):\n backup_file_path = file_path[:-5]\n backup_file_path = backup_file_path + \"_backup.json\"\n save_json_data(parameter_file_data, backup_file_path)\n else:\n raise Exception(\"Cannot figure out backup because parameter file does not end with .json\")\n\n\ndef convert_string_to_logical_type_var(arg):\n # Check for int\n\n if arg == \"del\":\n return \"del\"\n\n for var_type in [int, float]:\n try:\n test_type = var_type(arg)\n if str(test_type) == arg:\n print(\"\\nValue '{0}' has been found to cleanly convert to an {1}.\".format(arg, var_type))\n return test_type\n except:\n pass\n\n if arg == \"True\" or arg == \"true\":\n print(\"\\nValue '{0}' has been found to cleanly convert to an {1}.\".format(arg, type(True)))\n return True\n elif arg == \"False\" or arg == \"false\":\n print(\"\\nValue '{0}' has been found to cleanly convert to an {1}.\".format(arg, type(True)))\n return False\n elif arg == \"none\" or arg == \"None\":\n return None\n\n print(\"Cannot convert the string '{0}' to int, float, or bool. Will treat as a string\".format(arg))\n return arg\n\n\ndef check_recognised_key(parameter_file_data, key):\n if key in parameter_file_data.keys():\n return True\n else:\n return False\n\n\ndef user_check_add_key(file_path, key, user_approve_add_key_all, overide_user_inputs, value):\n approved = False\n if user_approve_add_key_all or overide_user_inputs:\n approved = True\n else:\n print(\"{0} was not found in {1}.\".format(key, file_path))\n user_approve_add_key = input(\n \"Would you like me to add '{0}' with value {1} to this data? y/n: \".format(key, value))\n if user_approve_add_key == \"y\":\n approved = True\n if user_approve_add_key_all != \"n\":\n user_approve_add_key_all = input(\"Would you like me to add this key to all files found? y/n: \")\n if user_approve_add_key_all == \"y\":\n user_approve_add_key_all = True\n else:\n user_approve_add_key_all = False\n\n return approved, user_approve_add_key_all\n\n\ndef update_parameter_files(parameter_file_paths, key, value, overide_user_inputs):\n print(\"\\nATTEMPTING TO UPDATE PARAMETERS!\\n\")\n\n user_approve_add_key_all = None\n\n for file_path in parameter_file_paths:\n parameter_file_data = load_json_data(file_path)\n\n # Check approve criteria\n update_approved = False\n if overide_user_inputs:\n update_approved = True\n elif user_approve_add_key_all:\n update_approved = True\n elif check_recognised_key(parameter_file_data, key):\n update_approved = True\n else:\n update_approved, user_approve_add_key_all = user_check_add_key(file_path, key, user_approve_add_key_all,\n overide_user_inputs, value)\n\n if update_approved or overide_user_inputs:\n print(\"Modifying {0}\".format(file_path))\n make_backup_json(file_path, parameter_file_data)\n parameter_file_data[key] = value\n save_json_data(parameter_file_data, file_path)\n\n\ndef delete_key_from_files(parameter_file_paths, key, value, overide_user_inputs):\n print(\"\\nATTEMPTING TO UPDATE PARAMETERS!\\n\")\n\n user_approve_add_key_all = None\n\n for file_path in parameter_file_paths:\n parameter_file_data = load_json_data(file_path)\n\n # Check approve criteria\n update_approved = False\n if overide_user_inputs:\n update_approved = True\n elif user_approve_add_key_all:\n update_approved = True\n elif check_recognised_key(parameter_file_data, key):\n update_approved = True\n else:\n print(\"{0} not found in {1}\".format(key, file_path))\n continue\n\n if update_approved or overide_user_inputs:\n print(\"Deleting {0} from {1}\".format(key, file_path))\n make_backup_json(file_path, parameter_file_data)\n parameter_file_data.pop(key)\n save_json_data(parameter_file_data, file_path)\n\n\ndef unpack_sys_arguments(args):\n base_dir_path = None\n filename = None\n key = None\n value = None\n override_user_inputs = False\n filters = None\n\n if len(args) >= 3:\n base_dir_path = sys.argv[1]\n if base_dir_path == \".\":\n base_dir_path = os.getcwd()\n filename = sys.argv[2]\n\n if len(sys.argv) >= 4:\n filters = sys.argv[3].split(\",\")\n\n if len(args) >= 5:\n key = args[4]\n\n if len(args) >= 6:\n value = args[5]\n\n if len(sys.argv) >= 7:\n if sys.argv[6] == \"1\" or sys.argv[6] == \"True\":\n override_user_inputs = True\n print(\"\\n OVERRIDE USER INPUTS = {0}\".format(override_user_inputs))\n\n return base_dir_path, filename, key, value, filters, override_user_inputs\n\n\ndef display_file_path_list(parameter_file_paths, base_dir_path, key):\n string = \"\\nI found [{0}] files with that name in [ {1} ] \\n\\n\".format(len(parameter_file_paths), base_dir_path)\n print(\"=\" * len(string))\n print(string)\n print(\"=\" * len(string))\n if key is None:\n for file_path in parameter_file_paths:\n print(file_path[len(base_dir_path):])\n else:\n # Open each file\n for file_path in parameter_file_paths:\n parameter_file_data = load_json_data(file_path)\n if key in parameter_file_data.keys():\n print(file_path[len(base_dir_path):], \"*** with VALUE:\", parameter_file_data[key],\n type(parameter_file_data[key]), \"***\")\n else:\n print(file_path[len(base_dir_path):], \"*** Key NOT present. ***\")\n print(string)\n print(\"=\" * len(string))\n print(\"\\n\")\n\n\ndef user_check(key, value, overide_user_inputs):\n if value != \"del\":\n print(\"\\n=================================================\"\n \"\\nBased upon the script args, you would like the key:\\n-- {0} \\nto have value: \\n-- {1} {2}\"\n \"\\n\\nVERY CAREFULLY CHECK: ARE THESE DETAILS CORRECT?\"\n \"\\n=================================================\".format(key, value, type(value)))\n elif value == \"del\":\n print(\"\\n===========================================================\"\n \"\\nBased upon the script args, you would like to *DELETE* key\\n-- {0}\"\n \"\\nVERY CAREFULLY CHECK: ARE THESE DETAILS CORRECT?\"\n \"\\n===========================================================\".format(key, value, type(value)))\n\n if not overide_user_inputs:\n y = \"y\"\n user_checked = input(\"Input 'y' to continue:\")\n if user_checked == \"n\":\n raise Exception(\"ABORTING because user input {0}\".format(user_checked))\n elif user_checked != \"y\":\n raise Exception(\"Unrecognised input '{0}'. Exiting\".format(user_checked))\n elif user_checked == \"y\":\n return True\n else:\n raise Exception(\"UNRECOGNISED ERROR IN USER CHECK!\")\n else:\n print(\"OVERRIDE USER INPUTS APPLIED!\")\n return True\n\n\ndef filtered_file_paths(parameter_file_paths, filters):\n if filters is None:\n return parameter_file_paths\n filtered_file_paths = []\n for path in parameter_file_paths:\n my_bool = True\n for f in filters:\n if f not in path:\n my_bool = False\n\n if my_bool:\n filtered_file_paths.append(path)\n\n if len(filtered_file_paths) == 0:\n print(\"ERROR - Filtering paths lead to no acceptable paths.\")\n exit()\n\n return filtered_file_paths\n\n\ndef main():\n print(\"\\n\\nWelcome to the change parameter file detail script.\\n\")\n\n if len(sys.argv) == 1:\n print_help()\n exit()\n print(\"\\nYour system arguments are:\")\n for arg in sys.argv[1:]:\n print(arg)\n\n base_dir_path, filename, key, value, filters, override_user_inputs = unpack_sys_arguments(sys.argv)\n\n parameter_file_paths = None\n if base_dir_path is not None and filename is not None:\n parameter_file_paths = find_file_paths_in_sub_directories(base_dir_path, filename)\n parameter_file_paths = filtered_file_paths(parameter_file_paths, filters)\n display_file_path_list(parameter_file_paths, base_dir_path, key)\n else:\n exit()\n\n if key is not None and value is not None:\n value = convert_string_to_logical_type_var(value)\n if user_check(key, value, override_user_inputs):\n if value == \"del\":\n delete_key_from_files(parameter_file_paths, key, value, override_user_inputs)\n else:\n update_parameter_files(parameter_file_paths, key, value, override_user_inputs)\n print(\"\\nScript complete! All files have been updated.\")\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"bin/change_directory_tree_par_detail.py","file_name":"change_directory_tree_par_detail.py","file_ext":"py","file_size_in_byte":10400,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"402439623","text":"# ##### BEGIN GPL LICENSE BLOCK #####\n#\n# This program is free software; you can redistribute it and/or\n# modify it under the terms of the GNU General Public License\n# as published by the Free Software Foundation; either version 2\n# of the License, or (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program; if not, write to the Free Software Foundation,\n# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.\n#\n# ##### END GPL LICENSE BLOCK #####\n\nbl_info = {\n \"name\": \"Useless Tools\",\n \"description\": \"Just a little collection of scripts and tools I use daily\",\n \"author\": \"Greg Zaal\",\n \"version\": (1, 2),\n \"blender\": (2, 75, 0),\n \"location\": \"Mostly 3D view toolshelf\",\n \"warning\": \"\",\n \"wiki_url\": \"\",\n \"tracker_url\": \"\",\n \"category\": \"Tools\"}\n\n\nimport bpy\nimport os\n\nglobal obtypes\nobtypes = ['MESH', 'CURVE', 'SURFACE', 'META', 'FONT', 'ARMATURE', 'LATTICE', 'EMPTY', 'CAMERA', 'LAMP']\n\n\nclass UTSetSelectable(bpy.types.Operator):\n\n 'Sets selectability for the selected objects'\n bl_idname = 'ut.set_selectable'\n bl_label = 'set selectable'\n selectable = bpy.props.BoolProperty()\n\n def execute(self, context,):\n for obj in bpy.context.selected_objects:\n if self.selectable == True:\n obj.hide_select = False\n else:\n obj.hide_select = True\n return {'FINISHED'}\n\n\nclass UTSetRenderable(bpy.types.Operator):\n\n 'Sets renderability for the selected objects'\n bl_idname = 'ut.set_renderable'\n bl_label = 'set renderable'\n renderable = bpy.props.BoolProperty()\n\n def execute(self, context,):\n for obj in bpy.context.selected_objects:\n if self.renderable == True:\n obj.hide_render = False\n else:\n obj.hide_render = True\n return {'FINISHED'}\n\n\nclass UTAllSelectable(bpy.types.Operator):\n\n 'Allows all objects to be selected'\n bl_idname = 'ut.all_selectable'\n bl_label = 'all selectable'\n\n def execute(self, context,):\n for obj in bpy.data.objects:\n obj.hide_select = False\n return {'FINISHED'}\n\n\nclass UTAllRenderable(bpy.types.Operator):\n\n 'Allows all objects to be rendered'\n bl_idname = 'ut.all_renderable'\n bl_label = 'all renderable'\n\n def execute(self, context,):\n for obj in bpy.data.objects:\n obj.hide_render = False\n return {'FINISHED'}\n\n\nclass UTSelNGon(bpy.types.Operator):\n\n 'Selects faces with more than 4 vertices'\n bl_idname = 'ut.select_ngons'\n bl_label = 'Select NGons'\n\n @classmethod\n def poll(cls, context):\n if not context.active_object or context.mode != 'EDIT_MESH':\n return False\n else:\n return True\n\n def execute(self, context):\n context.tool_settings.mesh_select_mode = (False, False, True)\n bpy.ops.mesh.select_face_by_sides(number=4, type='GREATER', extend=True)\n return {'FINISHED'}\n\n\nclass UTWireHideSel(bpy.types.Operator):\n\n 'Hides the wire overlay of all objects in the selection'\n bl_idname = 'ut.wirehidesel'\n bl_label = 'Hide Wire'\n show = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n for e in bpy.context.selected_objects:\n try:\n e.show_wire = self.show\n except KeyError:\n print(\"Error on \" + e.name)\n return {'FINISHED'}\n\n\nclass UTWireHideAll(bpy.types.Operator):\n\n 'Hides the wire overlay of all objects'\n bl_idname = 'ut.wirehideall'\n bl_label = 'Hide Wire (All)'\n show = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n for e in bpy.data.objects:\n try:\n e.show_wire = self.show\n except KeyError:\n print(\"Error on \" + e.name)\n return {'FINISHED'}\n\n\nclass UTSubsurfHideSel(bpy.types.Operator):\n\n 'Sets the Subsurf modifier of all objects in selection to be invisible in the viewport'\n bl_idname = 'ut.subsurfhidesel'\n bl_label = 'Subsurf Hide'\n show = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n for e in bpy.context.selected_objects:\n try:\n e.modifiers['Subsurf'].show_viewport = self.show\n except KeyError:\n print(\"No subsurf on \" + e.name + \" or it is not named Subsurf\")\n return {'FINISHED'}\n\n\nclass UTSubsurfHideAll(bpy.types.Operator):\n\n 'Sets the Subsurf modifier of all objects to be invisible in the viewport'\n bl_idname = 'ut.subsurfhideall'\n bl_label = 'Subsurf Hide (All)'\n show = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n for e in bpy.data.objects:\n try:\n e.modifiers['Subsurf'].show_viewport = self.show\n except KeyError:\n print(\"No subsurf on \" + e.name + \" or it is not named Subsurf\")\n return {'FINISHED'}\n\n\nclass UTOptimalDisplaySel(bpy.types.Operator):\n\n 'Disables Optimal Display for all Subsurf modifiers on selected objects'\n bl_idname = 'ut.optimaldisplaysel'\n bl_label = 'Optimal Display'\n on = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n for e in bpy.context.selected_objects:\n try:\n e.modifiers['Subsurf'].show_only_control_edges = self.on\n except KeyError:\n print(\"No subsurf on \" + e.name + \" or it is not named Subsurf\")\n return {'FINISHED'}\n\n\nclass UTOptimalDisplayAll(bpy.types.Operator):\n\n 'Disables Optimal Display for all Subsurf modifiers'\n bl_idname = 'ut.optimaldisplayall'\n bl_label = 'Optimal Display Off (All)'\n on = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n for e in bpy.data.objects:\n try:\n e.modifiers['Subsurf'].show_only_control_edges = self.on\n except KeyError:\n print(\"No subsurf on \" + e.name + \" or it is not named Subsurf\")\n return {'FINISHED'}\n\n\nclass UTAllEdges(bpy.types.Operator):\n\n 'Enables All Edges for all objects'\n bl_idname = 'ut.all_edges'\n bl_label = 'All Edges'\n on = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n for e in bpy.data.objects:\n e.show_all_edges = self.on\n return {'FINISHED'}\n\n\nclass UTDoubleSided(bpy.types.Operator):\n\n 'Disables Double Sided Normals for all objects'\n bl_idname = 'ut.double_sided'\n bl_label = 'Double Sided Normals'\n on = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n for e in bpy.data.meshes:\n try:\n e.show_double_sided = self.on\n except KeyError:\n print(\"Error setting double sided on \" + e.name)\n return {'FINISHED'}\n\n\nclass UTClearAnim(bpy.types.Operator):\n\n 'Deletes animation for the selected objects'\n bl_idname = 'ut.clearanim'\n bl_label = 'Delete Animation'\n selected_only = bpy.props.BoolProperty(default=False)\n\n def execute(self, context):\n if self.selected_only:\n objs = bpy.context.selected_objects\n else:\n objs = bpy.data.objects\n\n for obj in objs:\n obj.animation_data_clear()\n\n self.report({'INFO'}, \"Animation deleted\")\n return {'FINISHED'}\n\n\nclass UTKillSubsurfs(bpy.types.Operator):\n\n 'Deletes all Subsurf modifiers in the scene'\n bl_idname = 'ut.remove_all_subsurfs'\n bl_label = 'Kill All Subsurfs'\n\n def execute(self, context,):\n counter = 0\n for obj in bpy.data.objects:\n bpy.context.scene.objects.active = obj\n for mod in bpy.context.object.modifiers:\n if mod.type == 'SUBSURF':\n if context.mode == \"EDIT_MESH\":\n bpy.ops.object.editmode_toggle()\n bpy.ops.object.modifier_remove(modifier=mod.name)\n bpy.ops.object.editmode_toggle()\n else:\n bpy.ops.object.modifier_remove(modifier=mod.name)\n counter = counter + 1\n self.report({'INFO'}, str(counter) + \" subsurfs removed!\")\n return {'FINISHED'}\n\n\nclass UTDrawTypeOp(bpy.types.Operator):\n\n 'Sets draw type for the selected objects'\n bl_idname = 'ut.set_draw_type'\n bl_label = 'Draw Type'\n prop = bpy.props.StringProperty()\n\n def execute(self, context,):\n for obj in bpy.context.selected_objects:\n obj.draw_type = self.prop\n return {'FINISHED'}\n\n\nclass UTDrawTypeMenu(bpy.types.Menu):\n bl_idname = 'OBJECT_MT_DrawTypeMenu'\n bl_label = \"Draw Type\"\n\n def draw(self, context):\n layout = self.layout\n layout.operator(\"ut.set_draw_type\", text=\"Textured\").prop = \"TEXTURED\"\n layout.operator(\"ut.set_draw_type\", text=\"Solid\").prop = \"SOLID\"\n layout.operator(\"ut.set_draw_type\", text=\"Wire\").prop = \"WIRE\"\n layout.operator(\"ut.set_draw_type\", text=\"Bounds\").prop = \"BOUNDS\"\n\n\nclass UTSetLens(bpy.types.Operator):\n\n 'Sets viewport lense to 100mm'\n bl_idname = 'ut.set_lens'\n bl_label = 'Set Lens'\n prop = bpy.props.IntProperty(default=35)\n\n def execute(self, context,):\n bpy.context.space_data.lens = self.prop\n return {'FINISHED'}\n\n\nclass UTOriginToSel(bpy.types.Operator):\n\n 'Moves object origin to selection (Edit mode only, cannot undo)'\n bl_idname = 'ut.origin_to_selected'\n bl_label = 'Origin to Selected'\n\n @classmethod\n def poll(cls, context):\n return context.active_object and (bpy.context.mode == 'EDIT_MESH' or bpy.context.mode == 'EDIT_CURVE')\n\n def execute(self, context,):\n curloc = bpy.context.scene.cursor_location\n curx = curloc.x\n cury = curloc.y\n curz = curloc.z\n\n bpy.ops.view3d.snap_cursor_to_selected()\n bpy.ops.object.editmode_toggle()\n bpy.ops.object.origin_set(type='ORIGIN_CURSOR', center='MEDIAN')\n bpy.ops.object.editmode_toggle()\n bpy.context.scene.cursor_location.x = curx\n bpy.context.scene.cursor_location.y = cury\n bpy.context.scene.cursor_location.z = curz\n return {'FINISHED'}\n\n\nclass UTRecalcNormalsObjects(bpy.types.Operator):\n\n 'Recalculate normals of all selected objects'\n bl_idname = 'ut.recalculate_normals'\n bl_label = 'Recalculate Normals'\n\n @classmethod\n def poll(cls, context):\n return bpy.context.mode == 'OBJECT' and bpy.context.selected_objects\n\n def execute(self, context,):\n objs = context.selected_objects\n oldactive = context.active_object\n\n for obj in objs:\n context.scene.objects.active = obj\n bpy.ops.object.editmode_toggle()\n bpy.ops.mesh.select_all(action='SELECT')\n bpy.ops.mesh.normals_make_consistent(inside=False)\n bpy.ops.object.editmode_toggle()\n self.report({'INFO'}, \"Recalculated normals of \" + obj.name)\n return {'FINISHED'}\n\n\nclass UTSaveFile(bpy.types.Operator):\n\n 'Saves the File, or Save As if not saved already'\n bl_idname = 'ut.save_file'\n bl_label = 'Save File'\n\n @classmethod\n def poll(cls, context):\n return bpy.data.filepath != \"\" and not bpy.data.filepath.endswith(\"untitled.blend\")\n\n def execute(self, context,):\n if bpy.data.filepath != \"\":\n bpy.ops.wm.save_mainfile(filepath=bpy.data.filepath)\n else:\n bpy.ops.wm.save_as_mainfile()\n return {'FINISHED'}\n\n\nclass UTSaveFileIncrement(bpy.types.Operator):\n\n 'Increments the file name and then saves it'\n bl_idname = 'ut.save_file_increment'\n bl_label = 'Save File Increment'\n\n @classmethod\n def poll(cls, context):\n return bpy.data.filepath[-7:-6].isnumeric()\n\n def execute(self, context,):\n if bpy.data.filepath != \"\":\n fp = bpy.data.filepath\n enddigit = fp[-7:-6]\n end2digit = fp[-8:-7]\n end3digit = fp[-9:-8]\n if enddigit.isnumeric():\n if int(enddigit) == 9 and not end2digit.isnumeric():\n endint = int(enddigit) + 1\n fp = fp[:-7] + str(endint) + fp[-6:]\n if int(enddigit) != 9:\n endint = int(enddigit) + 1\n fp = fp[:-7] + str(endint) + fp[-6:]\n if end2digit.isnumeric() and int(enddigit) == 9:\n endint = 0\n end2int = int(end2digit) + 1\n fp = fp[:-8] + str(end2int) + str(endint) + fp[-6:]\n if end3digit.isnumeric() and int(end2digit) == 9 and int(enddigit) == 9:\n endint = 0\n end2int = 0\n end3int = int(end3digit) + 1\n fp = fp[:-10] + str(end3int) + str(end2int) + str(endint) + fp[-6:]\n splitsep = fp.split(os.sep)\n self.report({'INFO'}, \"Saved as \" + splitsep[len(splitsep) - 1])\n bpy.ops.wm.save_as_mainfile(filepath=fp)\n else:\n print(\"saving as...\")\n bpy.ops.wm.save_as_mainfile()\n return {'FINISHED'}\n\n\nclass UTClippingToggle(bpy.types.Operator):\n\n 'Toggles mirror modifiers clipping property'\n bl_idname = 'ut.mirror_clipping'\n bl_label = 'Toggle Clipping'\n\n @classmethod\n def poll(cls, context):\n hasmirror = False\n for obj in bpy.context.selected_objects:\n for mod in obj.modifiers:\n if mod.type == 'MIRROR':\n hasmirror = True\n return hasmirror\n\n def execute(self, context):\n for e in bpy.context.selected_objects:\n try:\n if e.modifiers['Mirror'].use_clip == True:\n e.modifiers['Mirror'].use_clip = False\n elif e.modifiers['Mirror'].use_clip == False:\n e.modifiers['Mirror'].use_clip = True\n except KeyError:\n print(\"No mirror modifier on \" + e.name + \" or it is not named Mirror\")\n return {'FINISHED'}\n\n\nclass UTEmptyAlign(bpy.types.Operator):\n\n 'Sets the offset of the image'\n bl_idname = 'ut.align_empty'\n bl_label = 'Align'\n pos = bpy.props.StringProperty()\n\n @classmethod\n def poll(cls, context):\n isimage = False\n if context.active_object.empty_draw_type == 'IMAGE':\n isimage = True\n return isimage\n\n def execute(self, context,):\n pos = self.pos\n px = 0\n py = 0\n\n if pos == \"U_L\":\n px = 0\n py = -1\n if pos == \"U_M\":\n px = -0.5\n py = -1\n if pos == \"U_R\":\n px = -1\n py = -1\n if pos == \"M_L\":\n px = 0\n py = -0.5\n if pos == \"M_M\":\n px = -0.5\n py = -0.5\n if pos == \"M_R\":\n px = -1\n py = -0.5\n if pos == \"D_L\":\n px = 0\n py = 0\n if pos == \"D_M\":\n px = -0.5\n py = 0\n if pos == \"D_R\":\n px = -1\n py = 0\n\n obj = bpy.context.active_object\n if not context.scene.UTEmptySlide:\n obj.empty_image_offset[0] = px\n obj.empty_image_offset[1] = py\n else:\n dx = obj.empty_image_offset[0] - px\n dy = obj.empty_image_offset[1] - py\n obj.empty_image_offset[0] = px\n obj.empty_image_offset[1] = py\n obj.location.x = obj.location.x + (dx * obj.empty_draw_size * obj.scale.x)\n obj.location.y = obj.location.y + (dy * obj.empty_draw_size * obj.scale.y)\n\n goodrot = True\n if obj.rotation_euler.x != 0 or obj.rotation_euler.y != 0 or obj.rotation_euler.z != 0 or obj.rotation_quaternion.w != 1 or obj.rotation_quaternion.x != 0 or obj.rotation_quaternion.y != 0 or obj.rotation_quaternion.z != 0 or obj.rotation_axis_angle[0] != 0 or obj.rotation_axis_angle[1] != 0 or obj.rotation_axis_angle[2] != 1 or obj.rotation_axis_angle[3] != 0:\n goodrot = False\n if goodrot == False and context.scene.UTEmptySlide == True:\n self.report({'WARNING'}, \"CAUTION! Aligning images with 'Slide Origin' on and a non-default rotation may have unexpected results\")\n return {'FINISHED'}\n\n\nclass UTAddPositionedSuzanne(bpy.types.Operator):\n\n 'Add a monkey that sits on the ground'\n bl_idname = 'ut.positioned_suz'\n bl_label = 'Positioned Suzanne'\n\n @classmethod\n def poll(cls, context):\n return (context.mode == 'OBJECT')\n\n def execute(self, context):\n cloc = context.scene.cursor_location\n bpy.ops.mesh.primitive_monkey_add(radius=1, view_align=False, enter_editmode=False, location=(cloc.x, cloc.y, cloc.z + 0.4955), layers=(True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False))\n bpy.ops.object.shade_smooth()\n bpy.ops.object.subdivision_set(level=3)\n bpy.context.object.modifiers[\"Subsurf\"].render_levels = 3\n bpy.context.object.rotation_euler.x = -0.6254132986068726\n\n return {'FINISHED'}\n\n\nclass UTDeleteNodeGroups(bpy.types.Operator):\n\n 'Disables Fake User and reloads the file. Click this several times until there are no unused groups left'\n bl_idname = 'ut.delete_node_groups'\n bl_label = 'Delete Unused Node Groups'\n\n @classmethod\n def poll(cls, context):\n return bpy.data.filepath != \"\" and not bpy.data.filepath.endswith(\"untitled.blend\")\n\n def execute(self, context):\n groups = bpy.data.node_groups\n\n num_groups = len(groups)\n num_affected = 0\n for g in groups:\n if g.use_fake_user:\n g.use_fake_user = False\n num_affected += 1\n\n bpy.ops.wm.save_reload()\n\n self.report({'INFO'}, (\"Affected \" + str(num_affected) + \" of \" + str(num_groups)))\n\n return {'FINISHED'}\n\n\n","sub_path":"scripts/addons_extern/AF_display_tools/useless_tools.py","file_name":"useless_tools.py","file_ext":"py","file_size_in_byte":18285,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"451214890","text":"from itertools import chain\nfrom operator import attrgetter\n\nfrom django.contrib.auth.decorators import login_required\nfrom django.contrib.auth.models import User\nfrom django.http import HttpResponse\nfrom django.http import HttpResponseRedirect\nfrom django.shortcuts import render\nfrom django.urls import reverse\n\nfrom feed.models import Tweet, Retweet, DummyUser\n\n\n@login_required\ndef home(request):\n if request.method == \"POST\":\n t = Tweet(text=request.POST[\"text\"])\n t.user = request.user\n t.save()\n return HttpResponseRedirect(reverse(\"feed:home\"))\n\n tweets = Tweet.objects.all()\n retweets = Retweet.objects.all()\n tweets_n_retweets = sorted(chain(tweets, retweets), key=attrgetter('pub_date'), reverse=True)\n\n return render(request, \"feed/home.html\", {\"items\": tweets_n_retweets,\n \"s\": \"1234\"})\n\n\ndef list_tweets(request, username):\n # tweets = Tweet.objects.filter(user__username=username).order_by(\"-pub_date\")\n\n tweets = User.objects.get(username=username).tweet_set.order_by(\"-pub_date\")\n return render(request, \"feed/list_tweets.html\", {\"tweets\": tweets})\n\n\n@login_required\ndef cite(request):\n if request.method != \"POST\":\n return HttpResponse(\"Not supported\")\n t = Tweet(user=request.user)\n origin = Tweet.objects.get(id=request.POST[\"tweet_id\"])\n t.text = 'RT @%s: \"%s\" on %s' % (origin.user.username,\n origin.text,\n origin.pub_date)\n t.save()\n return HttpResponseRedirect(reverse(\"feed:home\"))\n\n\ndef retweet(request):\n if request.method != \"POST\":\n return HttpResponse(\"Not supported\")\n rt = Retweet(\n user=request.user,\n tweet_id=request.POST[\"tweet_id\"]\n )\n rt.save()\n return HttpResponseRedirect(reverse(\"feed:home\"))\n\n\ndef dummy(request):\n return render(request, \"feed/dummy01.html\")\n","sub_path":"07 app with tags&filters and static/feed/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":1950,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"519709212","text":"arr1 = [9, 20, 28, 18, 11]\narr2 = [30, 1, 21, 17, 28]\ndef solution(n, arr1, arr2):\n answer = []\n for a1, a2 in zip(arr1, arr2):\n a12 = str(bin(a1 | a2))[2:]\n print(a12)\n a12 = '0' * (n-len(a12)) +a12\n a12.replace('1','#')\n a12.replace('0',' ')\n return answer\n\n\nresult = solution(5,arr1,arr2)\n\nprint(result)\n","sub_path":"python/kakao2018/map.py","file_name":"map.py","file_ext":"py","file_size_in_byte":351,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"617846074","text":"import time\n\nimport firebase_admin\nfrom firebase_admin import credentials\nfrom firebase_admin import firestore\nimport flask\nfrom flask import request, jsonify\n\n# initialize firebase application\nfirebase_admin.initialize_app()\n\n# connect to db\ndb = firestore.client()\n\nrecdata = {\n \"type_of_followup\": \"val\",\n \"details\": \"val\",\n \"doc_id\": \"val\",\n \"doer_docid\": \"val\",\n \"follow_up_id\": \"val\",\n \"edate\": \"val\"\n}\n\n\ndef hello_world(request):\n recdata = flask.request.json\n\n type_of_followup = recdata['type_of_followup']\n details = recdata['details']\n doc_id = recdata['doc_id']\n doer_docid = recdata['doer_docid']\n follow_up_id = recdata['follow_up_id']\n edate = int(time.time())\n\n docs = db.collection(\"Profile\").document(doc_id).collection(\"FollowUps\").document(follow_up_id)\n\n flag = 0\n\n for doc in docs:\n flag = 1\n\n if flag == 0:\n response = {\n \"status\": \"False\",\n \"message\": \"FollowUp does not exists!\"\n }\n return jsonify(response)\n\n ref = db.collection(\"Profile\").document(doc_id).collection(\"FollowUps\").document(follow_up_id).collection(\"FollowUpDetails\").document()\n\n data = {\n \"type_of_followup\": type_of_followup,\n \"details\": details,\n \"doer_docid\": doer_docid,\n \"doc_id\": doc_id,\n \"follow_up_id\": follow_up_id,\n \"edate\": edate\n }\n\n ref.set(data)\n\n response = {\n \"status\": \"True\",\n \"message\": \"FollowUpDetails added successfully!\"\n }\n\n return jsonify(response)\n","sub_path":"testing/addFollowUpDetails.py","file_name":"addFollowUpDetails.py","file_ext":"py","file_size_in_byte":1528,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"12179640","text":"#!/usr/bin/python3\n\n# traj2moments.py\n# calculates moments of segment length distribution from state populations (loaded from trajectory file)\n\nfrom matplotlib import rc\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport numpy.matlib as npm\nimport sys\n\nrc('font', **{'family': 'serif', 'serif': ['Computer Modern']})\nrc('text', usetex=True)\n\ntry:\n data = np.loadtxt(sys.argv[1])\nexcept:\n print('Syntax: traj2moments.py input_filename')\n sys.exit()\n\nvtx_loc = data[0:2,1:] # vertex locations on graph\ntraj = data[2:,1:] # trajectory (i.e. p(vertex) over time)\nt = data[2:,0] # time\nntstep = np.size(t) # number of timesteps\n\nL = np.max(vtx_loc) # number of monomer units in the system\n\nvtx_nbound = vtx_loc[0,] # number of bound monomers in config at each vertex\nvtx_nbonds = vtx_loc[1,] # number of bonds in config at each vertex\nvtx_nmon = L - vtx_nbound # number of monomers in config at each vertex\nvtx_nseg = L - vtx_nbonds # number of segments in config at each vertex\nvtx_lbar = np.divide(L, vtx_nseg) # average segment length in config at each vertex\n\nmoments = np.empty([ntstep,0])\nmoment0 = np.transpose(np.sum(np.multiply(traj,npm.repmat(np.ones(np.size(vtx_lbar)),ntstep,1)),axis=1))\nmoment1 = np.sum(np.multiply(traj,npm.repmat(np.power(vtx_lbar,1.0),ntstep,1)),axis=1)\nmoment2 = np.sum(np.multiply(traj,npm.repmat(np.power(vtx_lbar,2.0),ntstep,1)),axis=1)\nmoment3 = np.sum(np.multiply(traj,npm.repmat(np.power(vtx_lbar,3.0),ntstep,1)),axis=1)\nmoments = np.concatenate((t[:,None],moment0[:,None],moment1[:,None],moment2[:,None],moment3[:,None]),axis=1)\nprint('\\n'.join(' '.join(str(cell) for cell in row) for row in moments))\n","sub_path":"analytic/full/traj2moments.py","file_name":"traj2moments.py","file_ext":"py","file_size_in_byte":1904,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"214459063","text":"#-*- coding: utf-8 -*-\nfrom socket import *\nfrom time import ctime\nfrom time import localtime\nimport time\n\nHOST=''\nPORT=2222 #设置侦听端口\nBUFSIZ=1024\nADDR=(HOST, PORT)\nsock=socket(AF_INET, SOCK_STREAM)\n\nsock.bind(ADDR)\n\nsock.listen(5)\n#设置退出条件\nSTOP_CHAT=False\nwhile not STOP_CHAT:\n print('Waiting for connection, on port:%d' % (PORT))\n tcpClientSock, addr=sock.accept()\n print('Connected by address:',addr)\n while True:\n try:\n data=tcpClientSock.recv(BUFSIZ)\n except:\n #print(e)\n tcpClientSock.close()\n break\n if not data:\n break\n #python3使用bytes，所以要进行编码\n #s='%s发送给我的信息是:[%s] %s' %(addr[0],ctime(), data.decode('utf8'))\n #对日期进行一下格式化\n ISOTIMEFORMAT='%Y-%m-%d %X'\n stime=time.strftime(ISOTIMEFORMAT, localtime())\n #s='%sReceived message:%s' %(addr[0],data)\n #tcpClientSock.send(s.encode('utf8'))\n print([stime],':',data.decode('utf8'))\n #如果输入quit(忽略大小写),则程序退出\n STOP_CHAT=(data.upper()==\"QUIT\")\n if STOP_CHAT:\n break\ntcpClientSock.close()\nsock.close()\n","sub_path":"Demo/s2.py","file_name":"s2.py","file_ext":"py","file_size_in_byte":1228,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"353640479","text":"#\n# @lc app=leetcode id=156 lang=python3\n#\n# [156] Binary Tree Upside Down\n#\n# https://leetcode.com/problems/binary-tree-upside-down/description/\n#\n# algorithms\n# Medium (56.19%)\n# Likes: 330\n# Dislikes: 1024\n# Total Accepted: 66.1K\n# Total Submissions: 117.5K\n# Testcase Example: '[1,2,3,4,5]'\n#\n# Given the root of a binary tree, turn the tree upside down and return the new\n# root.\n# \n# You can turn a binary tree upside down with the following steps:\n# \n# \n# The original left child becomes the new root.\n# The original root becomes the new right child.\n# The original right child becomes the new left child.\n# \n# \n# \n# \n# The mentioned steps are done level by level, it is guaranteed that every node\n# in the given tree has either 0 or 2 children.\n# \n# \n# Example 1:\n# \n# \n# Input: root = [1,2,3,4,5]\n# Output: [4,5,2,null,null,3,1]\n# \n# \n# Example 2:\n# \n# \n# Input: root = []\n# Output: []\n# \n# \n# Example 3:\n# \n# \n# Input: root = [1]\n# Output: [1]\n# \n# \n# \n# Constraints:\n# \n# \n# The number of nodes in the tree will be in the range [0, 10].\n# 1 <= Node.val <= 10\n# Every node has either 0 or 2 children.\n# \n# \n#\n\n# @lc code=start\n# Definition for a binary tree node.\n# class TreeNode:\n# def __init__(self, val=0, left=None, right=None):\n# self.val = val\n# self.left = left\n# self.right = right\nclass Solution:\n '''\n 145/145 cases passed (36 ms)\n Your runtime beats 45.14 % of python3 submissions\n Your memory usage beats 52.78 % of python3 submissions (14.3 MB)\n '''\n def upsideDownBinaryTree(self, root: TreeNode) -> TreeNode:\n if not root:\n return root\n \n return self.helper(root, None)\n \n def helper(self, node, parent):\n if not node:\n return parent\n \n newRoot = self.helper(node.left, node)\n node.left = parent.right if parent else None\n node.right = parent\n\n return newRoot\n\n\n \n# @lc code=end\n\n","sub_path":"Python/156.binary-tree-upside-down.py","file_name":"156.binary-tree-upside-down.py","file_ext":"py","file_size_in_byte":1958,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"114909685","text":"#首先创建一个list\nL = [x * x for x in range(10)]\n#然后 把这个list写成generator\ng = (x * x for x in range(10))\n#打印出每一个元素\nfor n in g:\n print(n)\n\n#斐波拉契数列\ndef fib(max):\n a,b,c=0,0,1\n while a 0:\n model_lst = []\n for i in range(10):\n model = models.resnet18()\n model_lst.append(model)\n model = EnsembleModel(model_lst, 5)\n # model = models.resnet18(pretrained=False)\n # model.conv1 = nn.Conv2d(4, 64, kernel_size=7, stride=2, padding=3, bias=False)\n # model.fc = nn.Linear(512, 5, bias=True)\n if model_ckpt:\n state_dict = torch.load(model_ckpt)\n state_dict = {m.replace('module.', '') : i for m, i in state_dict.items()}\n model.load_state_dict(state_dict)\n\n transform = transforms.Compose([ToTensor()])\n\n \n with torch.no_grad():\n model.eval()\n model = model.cuda()\n num_input = len(input_fnames)\n dataset_val = CustomDataset(input_images, output_labels, transform=transform)\n loader_val = DataLoader(dataset_val, batch_size=num_input, shuffle=False, collate_fn=dataset_val.custom_collate_fn, num_workers=8)\n\n for batch, data in enumerate(loader_val, 1):\n val_label = data['label'].to(device)\n val_input = data['input'].to(device)\n pred_label = model(val_input)\n \n result_y = (max_values - min_values) * pred_label.cpu().numpy() + min_values\n result_x = (max_values - min_values) * val_label.cpu().numpy() + min_values\n\n for y in result_y:\n for a in range(len(y)):\n if y[a] < 0:\n y[a] = 0\n if answer:\n final_output = np.concatenate([result_x, result_y], axis=1)\n final_output = pd.DataFrame(final_output, index=img_idx, columns=[f'label_{_}' for _ in target_df.columns] + [f'pred_{_}' for _ in target_df.columns])\n\n squared_error = np.zeros(5)\n squared_target = np.zeros(5)\n\n for n, cname in enumerate(target_df.columns):\n squared_error[n] += np.sum(np.power(final_output['label_{}'.format(cname)] - final_output['pred_{}'.format(cname)], 2))\n squared_target[n] += np.sum(np.power(final_output['label_{}'.format(cname)], 2))\n\n nmse = squared_error / squared_target\n\n # print(nmse)\n # print(\"NMSE: {:.4f}\".format(np.sum(nmse)))\n\n final_output.to_csv(result_path)\n \n if write_json:\n columns = [\"FreshWeightShoot\", \"DryWeightShoot\", \"Height\", \"Diameter\", \"LeafArea\"]\n columns_output = [\"RGBImage\", \"DebthInformation\"]\n columns_output.extend(columns)\n final_output = pd.DataFrame(result_y, index=img_idx, columns=[f'{_}' for _ in columns])\n final_output['RGBImage'] = input_fnames\n depth_input_fnames = [fname.replace('RGB', 'Debth') for fname in input_fnames]\n final_output['DebthInformation'] = depth_input_fnames\n final_output = final_output[columns_output]\n result = final_output.to_json(orient=\"index\")\n parsed = json.loads(result)\n parsed = {'Measurements': parsed}\n json.dumps(parsed, indent='\\t')\n file_path = os.path.join('./evaluation', (model_name + '.json'))\n with open(file_path, 'w') as outfile:\n json.dump(parsed, outfile, indent=4)\n\n return np.sum(nmse)\n\ndef parse_args():\n parser = argparse.ArgumentParser(description=\"AGIC-PART A\", formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n parser.add_argument(\"--model_name\", default='best', type=str, dest=\"model_name\") \n parser.add_argument(\"--answer\", default=1, type=int, dest=\"answer\")\n parser.add_argument(\"--verbose\", default=1, type=int, dest='verbose')\n parser.add_argument(\"--write_json\", default=1, type=int, dest='write_json')\n\n return parser.parse_args()\n\ndef main():\n args = parse_args()\n evaluate(args)\n\nif __name__ == '__main__':\n main()","sub_path":"evaluate_ensemble.py","file_name":"evaluate_ensemble.py","file_ext":"py","file_size_in_byte":5429,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"564980175","text":"# Copyright (c) 2011 OpenStack Foundation\n# All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n# License for the specific language governing permissions and limitations\n# under the License.\n\nimport datetime\n\nfrom iso8601 import iso8601\nfrom oslo_utils import timeutils\nimport webob.exc\n\nfrom cinder.api.contrib import hosts as os_hosts\nfrom cinder import context\nfrom cinder import exception\nfrom cinder import test\n\n\ncreated_time = datetime.datetime(2012, 11, 14, 1, 20, 41, 95099)\ncurr_time = datetime.datetime(2013, 7, 3, 0, 0, 1)\n\nSERVICE_LIST = [\n {'created_at': created_time, 'updated_at': curr_time,\n 'host': 'test.host.1', 'topic': 'cinder-volume', 'disabled': 0,\n 'availability_zone': 'cinder'},\n {'created_at': created_time, 'updated_at': curr_time,\n 'host': 'test.host.1', 'topic': 'cinder-volume', 'disabled': 0,\n 'availability_zone': 'cinder'},\n {'created_at': created_time, 'updated_at': curr_time,\n 'host': 'test.host.1', 'topic': 'cinder-volume', 'disabled': 0,\n 'availability_zone': 'cinder'},\n {'created_at': created_time, 'updated_at': curr_time,\n 'host': 'test.host.1', 'topic': 'cinder-volume', 'disabled': 0,\n 'availability_zone': 'cinder'},\n {'created_at': created_time, 'updated_at': None,\n 'host': 'test.host.1', 'topic': 'cinder-volume', 'disabled': 0,\n 'availability_zone': 'cinder'},\n]\n\nLIST_RESPONSE = [{'service-status': 'available', 'service': 'cinder-volume',\n 'zone': 'cinder', 'service-state': 'enabled',\n 'host_name': 'test.host.1', 'last-update': curr_time},\n {'service-status': 'available', 'service': 'cinder-volume',\n 'zone': 'cinder', 'service-state': 'enabled',\n 'host_name': 'test.host.1', 'last-update': curr_time},\n {'service-status': 'available', 'service': 'cinder-volume',\n 'zone': 'cinder', 'service-state': 'enabled',\n 'host_name': 'test.host.1', 'last-update': curr_time},\n {'service-status': 'available', 'service': 'cinder-volume',\n 'zone': 'cinder', 'service-state': 'enabled',\n 'host_name': 'test.host.1', 'last-update': curr_time},\n {'service-status': 'unavailable', 'service': 'cinder-volume',\n 'zone': 'cinder', 'service-state': 'enabled',\n 'host_name': 'test.host.1', 'last-update': None},\n ]\n\n\ndef stub_utcnow(with_timezone=False):\n tzinfo = iso8601.Utc() if with_timezone else None\n return datetime.datetime(2013, 7, 3, 0, 0, 2, tzinfo=tzinfo)\n\n\nclass FakeRequest(object):\n environ = {'cinder.context': context.get_admin_context()}\n GET = {}\n\n\nclass FakeRequestWithcinderZone(object):\n environ = {'cinder.context': context.get_admin_context()}\n GET = {'zone': 'cinder'}\n\n\nclass HostTestCase(test.TestCase):\n \"\"\"Test Case for hosts.\"\"\"\n\n def setUp(self):\n super(HostTestCase, self).setUp()\n self.controller = os_hosts.HostController()\n self.req = FakeRequest()\n self.patch('cinder.db.service_get_all', autospec=True,\n return_value=SERVICE_LIST)\n self.mock_object(timeutils, 'utcnow', stub_utcnow)\n\n def _test_host_update(self, host, key, val, expected_value):\n body = {key: val}\n result = self.controller.update(self.req, host, body=body)\n self.assertEqual(expected_value, result[key])\n\n def test_list_hosts(self):\n \"\"\"Verify that the volume hosts are returned.\"\"\"\n hosts = os_hosts._list_hosts(self.req)\n self.assertEqual(LIST_RESPONSE, hosts)\n\n cinder_hosts = os_hosts._list_hosts(self.req, 'cinder-volume')\n expected = [host for host in LIST_RESPONSE\n if host['service'] == 'cinder-volume']\n self.assertEqual(expected, cinder_hosts)\n\n def test_list_hosts_with_zone(self):\n req = FakeRequestWithcinderZone()\n hosts = os_hosts._list_hosts(req)\n self.assertEqual(LIST_RESPONSE, hosts)\n\n def test_bad_status_value(self):\n self.assertRaises(webob.exc.HTTPBadRequest, self.controller.update,\n self.req, 'test.host.1', body={'status': 'bad'})\n self.assertRaises(webob.exc.HTTPBadRequest,\n self.controller.update,\n self.req,\n 'test.host.1',\n body={'status': 'disablabc'})\n\n def test_bad_update_key(self):\n bad_body = {'crazy': 'bad'}\n self.assertRaises(webob.exc.HTTPBadRequest, self.controller.update,\n self.req, 'test.host.1', body=bad_body)\n\n def test_bad_update_key_and_correct_udpate_key(self):\n bad_body = {'status': 'disable', 'crazy': 'bad'}\n self.assertRaises(webob.exc.HTTPBadRequest, self.controller.update,\n self.req, 'test.host.1', body=bad_body)\n\n def test_good_udpate_keys(self):\n body = {'status': 'disable'}\n self.assertRaises(NotImplementedError, self.controller.update,\n self.req, 'test.host.1', body=body)\n\n def test_bad_host(self):\n self.assertRaises(exception.HostNotFound,\n self.controller.update,\n self.req,\n 'bogus_host_name',\n body={'disabled': 0})\n\n def test_show_forbidden(self):\n self.req.environ['cinder.context'].is_admin = False\n dest = 'dummydest'\n self.assertRaises(webob.exc.HTTPForbidden,\n self.controller.show,\n self.req, dest)\n self.req.environ['cinder.context'].is_admin = True\n\n def test_show_host_not_exist(self):\n \"\"\"A host given as an argument does not exists.\"\"\"\n self.req.environ['cinder.context'].is_admin = True\n dest = 'dummydest'\n self.assertRaises(exception.ServiceNotFound,\n self.controller.show,\n self.req, dest)\n","sub_path":"cinder/tests/unit/api/contrib/test_hosts.py","file_name":"test_hosts.py","file_ext":"py","file_size_in_byte":6502,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"534503521","text":"\n# 参数\n# multiprocessing.Process(group=None, target=None, name=None, args=(), kwargs={})\n\n# - group: 分组，实际上很少使用，\n# - target: 表示调用对象，你可以传入方法的名字，或者函数名称\n# - name: 别名，相当于给这个进程取一个名字\n# - args: 表示调用对象的位置参数元祖，比如target是函数a，他有两个参数m，n，那么args就传入（m，n）即可\n# - kwargs：表示调用对象的字典\n\nfrom multiprocessing import Process\n\n\ndef f(name):\n print(f'hello {name}')\n\nif __name__ == '__main__':\n p = Process(target=f, args=('john',))\n p.start()\n p.join() # 等待子进程结束，父进程才能结束\n\n# join(timeout) # 超过多少秒 子进程不结束，则父进程也会立即结束\n# 如果可选参数 timeout 是None（默认值），则该方法将阻塞\n# 知道调用join() 方法的进程终止。如果timeout是一个正数，它最多会阻塞 timeout 秒。\n# 请注意，如果进程终止或方法超时，则该方法返回 None。\n# 检查进程的exitcode以确定它是否终止\n# 一个进程可以合并多次\n# 进程无法并入自身，因为这会导致死锁。\n# 尝试在启动进程之前合并进程是错误的","sub_path":"week03/p_multiprocessing.py","file_name":"p_multiprocessing.py","file_ext":"py","file_size_in_byte":1230,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"461048079","text":"# coding=utf-8\n# --------------------------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License. See License.txt in the project root for\n# license information.\n#\n# Code generated by Microsoft (R) AutoRest Code Generator.\n# Changes may cause incorrect behavior and will be lost if the code is\n# regenerated.\n# --------------------------------------------------------------------------\n\nfrom .store_read_settings_py3 import StoreReadSettings\n\n\nclass HttpReadSettings(StoreReadSettings):\n \"\"\"Sftp read settings.\n\n All required parameters must be populated in order to send to Azure.\n\n :param additional_properties: Unmatched properties from the message are\n deserialized this collection\n :type additional_properties: dict[str, object]\n :param type: Required. The read setting type.\n :type type: str\n :param max_concurrent_connections: The maximum concurrent connection count\n for the source data store. Type: integer (or Expression with resultType\n integer).\n :type max_concurrent_connections: object\n :param request_method: The HTTP method used to call the RESTful API. The\n default is GET. Type: string (or Expression with resultType string).\n :type request_method: object\n :param request_body: The HTTP request body to the RESTful API if\n requestMethod is POST. Type: string (or Expression with resultType\n string).\n :type request_body: object\n :param additional_headers: The additional HTTP headers in the request to\n the RESTful API. Type: string (or Expression with resultType string).\n :type additional_headers: object\n :param request_timeout: Specifies the timeout for a HTTP client to get\n HTTP response from HTTP server.\n :type request_timeout: object\n \"\"\"\n\n _validation = {\n 'type': {'required': True},\n }\n\n _attribute_map = {\n 'additional_properties': {'key': '', 'type': '{object}'},\n 'type': {'key': 'type', 'type': 'str'},\n 'max_concurrent_connections': {'key': 'maxConcurrentConnections', 'type': 'object'},\n 'request_method': {'key': 'requestMethod', 'type': 'object'},\n 'request_body': {'key': 'requestBody', 'type': 'object'},\n 'additional_headers': {'key': 'additionalHeaders', 'type': 'object'},\n 'request_timeout': {'key': 'requestTimeout', 'type': 'object'},\n }\n\n def __init__(self, *, type: str, additional_properties=None, max_concurrent_connections=None, request_method=None, request_body=None, additional_headers=None, request_timeout=None, **kwargs) -> None:\n super(HttpReadSettings, self).__init__(additional_properties=additional_properties, type=type, max_concurrent_connections=max_concurrent_connections, **kwargs)\n self.request_method = request_method\n self.request_body = request_body\n self.additional_headers = additional_headers\n self.request_timeout = request_timeout\n","sub_path":"sdk/datafactory/azure-mgmt-datafactory/azure/mgmt/datafactory/models/http_read_settings_py3.py","file_name":"http_read_settings_py3.py","file_ext":"py","file_size_in_byte":2981,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"178878147","text":"from django.db import models\nfrom django.core.exceptions import ObjectDoesNotExist\n\n\"\"\"This file is used to assign a oitive value for each Course\nThis takes that if not positive Integer is already associated to the model \nThen it allots one to it bu uing uery Set\n\"\"\"\n\n\nclass OrderField(models.PositiveIntegerField):\n\n\tdef __init__(self,for_fields=None,*args,**kwargs):\n\t\tself.for_fields=for_fields\n\t\tsuper (OrderField,self).__init__(*args,**kwargs)\n\n\tdef pre_save(self, model_instance,add):\n\t\tif getattr(model_instance,self.attname) is None:\n\t\t\ttry:\n\t\t\t\tqs=self.model.objects.all()\n\n\t\t\t\tif self.for_fields:\n\t\t\t\t\t# filter by objects with the same field values\n\t\t\t\t\t# for the fields in \"for_fields\"\n\t\t\t\t\tquery={fields:getattr(model_instance,fields) for fields in self.for_fields}\n\t\t\t\t\tqs=qs.filter(**query)\n\t\t\t\t# get the order of the last item\n\t\t\t\tlast_value=qs.latest(self.attname)\n\t\t\t\tvalue=last_value.order+1\n\t\t\texcept ObjectDoesNotExist:\n\t\t\t\tvalue=0\n\n\t\t\tsetattr(model_instance,self.attname,value)\n\t\t\treturn value\n\n\t\telse:\n\t\t\treturn super(OrderField,self).pre_save(model_instance,add)","sub_path":"elearn/courses/fields.py","file_name":"fields.py","file_ext":"py","file_size_in_byte":1086,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"475988397","text":"#使用range（）使for循环执行相应次数，同时创建相对应的外星人\n#罗旭阳，2019/01/29\n#创建一个存储外星人的空列表\naliens = []\n\n# 创建30个外星人\nfor alien_num in range(30):\n\tnew_alien = {\"color\" : \"green\", \"point\" : 5, \"speed\" : \"slow\"}\n\taliens.append(new_alien)\n\n#显示前五个外星人\nfor alien in aliens[:5]:\n\tprint(alien)\n\nprint(\"... ...\")\n\n#显示到底创建多少个外星人\nprint(\"Total number of aliens : \" + str(len(aliens)))\n","sub_path":"auto_create_aliens.py","file_name":"auto_create_aliens.py","file_ext":"py","file_size_in_byte":481,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"228478861","text":"from app.global_data.global_data import g\nfrom app.domain.message import Message\nfrom app.utils.pageable import gen_pageable\n\n\ndef create_message(message):\n sql = '''\n INSERT INTO message (\n sender,\n receiver,\n subject,\n content,\n url,\n urgent,\n viewed,\n deleted,\n created_date,\n modified_date\n ) VALUES (\"{}\", \"{}\", \"{}\", \"{}\", \"{}\", {}, {}, {}, \"{}\", \"{}\")\n '''.format(\n message.sender,\n message.receiver,\n message.subject,\n message.content,\n message.url if hasattr(message, 'url') else '',\n 1 if hasattr(message, 'urgent') and message.urgent else 0,\n 1 if message.viewed else 0,\n 1 if message.deleted else 0,\n message.createdDate,\n message.modifiedDate\n )\n\n conn = g.db.pool.connection()\n with conn.cursor() as cursor:\n cursor.execute(sql)\n conn.commit()\n cursor.execute('SELECT last_insert_id() FROM message limit 1')\n id = cursor.fetchone()[0]\n conn.close()\n\n return id\n\n\ndef get_messages(where, pageable):\n pageable = gen_pageable(pageable)\n sql = 'SELECT * FROM message {} {}'.format(where, pageable)\n sql_total_count = 'SELECT COUNT(*) FROM message {}'.format(where)\n\n conn = g.db.pool.connection()\n with conn.cursor() as cursor:\n cursor.execute(sql)\n records = cursor.fetchall()\n message_list = []\n for record in records:\n message = Message()\n message.from_record(record)\n message_list.append(message.__dict__)\n\n cursor.execute(sql_total_count)\n total_count = cursor.fetchone()\n conn.close()\n\n return total_count[0], message_list\n\n\ndef find_one_by_id(id):\n sql = 'SELECT * FROM message WHERE id = \"{}\" limit 1'.format(id)\n\n conn = g.db.pool.connection()\n with conn.cursor() as cursor:\n cursor.execute(sql)\n records = cursor.fetchall()\n conn.close()\n\n message_list = []\n for record in records:\n message = Message()\n message.from_record(record)\n message_list.append(message)\n\n return message_list[0] if len(message_list) > 0 else None\n\n\ndef delete_message(id):\n sql = 'DELETE FROM message WHERE id = \"{}\"'.format(id)\n\n conn = g.db.pool.connection()\n with conn.cursor() as cursor:\n cursor.execute(sql)\n conn.commit()\n conn.close()\n\n\ndef update_message_viewed(id, viewed):\n sql = '''\n UPDATE message SET \n viewed = {}\n WHERE id = {}\n '''.format(\n 1 if viewed else 0,\n id\n )\n\n conn = g.db.pool.connection()\n with conn.cursor() as cursor:\n cursor.execute(sql)\n conn.commit()\n conn.close()\n\n\ndef update_message_deleted(id, deleted):\n sql = '''\n UPDATE message SET \n deleted = {}\n WHERE id = {}\n '''.format(\n 1 if deleted else 0,\n id\n )\n\n conn = g.db.pool.connection()\n with conn.cursor() as cursor:\n cursor.execute(sql)\n conn.commit()\n conn.close()\n\n\ndef get_unread_count(receiver, deleted):\n sql = 'SELECT COUNT(*) FROM message WHERE receiver = \"{}\" and deleted = {} and viewed = 0'.format(\n receiver,\n 1 if deleted else 0\n )\n\n conn = g.db.pool.connection()\n with conn.cursor() as cursor:\n cursor.execute(sql)\n count = cursor.fetchone()\n conn.close()\n\n return count[0]\n","sub_path":"uaa-python/app/database/message_db.py","file_name":"message_db.py","file_ext":"py","file_size_in_byte":3527,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"392930895","text":"from abc import ABC, abstractmethod\nimport torch, torchtext\nimport gensim\nimport os\nimport numpy as np\n\n\nclass KeyedVectors:\n\n def __init__(self, word2index, weights):\n assert len(word2index)==weights.shape[0], 'wrong number of dimensions'\n index2word = {i:w for w,i in word2index.items()}\n assert len([i for i in range(len(index2word)) if i not in index2word])==0, 'gaps in indexing not allowed'\n self.word2index = word2index\n self.index2word = index2word\n self.weights = weights\n\n def extract(self, words):\n dim = self.weights.shape[1]\n v_size = len(words)\n\n source_idx, target_idx = [], []\n for i,word in enumerate(words):\n if word not in self.word2index: continue\n j = self.word2index[word]\n source_idx.append(i)\n target_idx.append(j)\n\n extraction = np.zeros((v_size, dim))\n extraction[np.asarray(source_idx)] = self.weights[np.asarray(target_idx)]\n\n return extraction\n\n\n\nclass PretrainedEmbeddings(ABC):\n\n def __init__(self):\n super().__init__()\n\n @abstractmethod\n def vocabulary(self): pass\n\n @abstractmethod\n def dim(self): pass\n\n @classmethod\n def reindex(cls, words, word2index):\n source_idx, target_idx = [], []\n for i, word in enumerate(words):\n if word not in word2index: continue\n j = word2index[word]\n source_idx.append(i)\n target_idx.append(j)\n source_idx = np.asarray(source_idx)\n target_idx = np.asarray(target_idx)\n return source_idx, target_idx\n\n\nclass GloVe(PretrainedEmbeddings):\n\n def __init__(self, setname='840B'):\n super().__init__()\n print(f'Loading GloVe pretrained vectors from torchtext')\n self.embed = torchtext.vocab.GloVe(setname)\n print('Done')\n\n def vocabulary(self):\n return set(self.embed.stoi.keys())\n\n def dim(self):\n return self.embed.dim\n\n def extract(self, words):\n source_idx, target_idx = PretrainedEmbeddings.reindex(words, self.embed.stoi)\n extraction = torch.zeros((len(words), self.dim()))\n extraction[source_idx] = self.embed.vectors[target_idx]\n return extraction\n\n\nclass Word2Vec(PretrainedEmbeddings):\n\n def __init__(self, path, limit=None):\n super().__init__()\n print(f'Loading word2vec pretrained vectors from {path}')\n assert os.path.exists(path), print(f'pre-trained keyed vectors not found in {path}')\n self.embed = gensim.models.KeyedVectors.load_word2vec_format(path, binary=True, limit=limit)\n self.word2index={w:i for i,w in enumerate(self.embed.index2word)}\n print('Done')\n\n def vocabulary(self):\n return set(self.word2index.keys())\n\n def dim(self):\n return self.embed.vector_size\n\n def extract(self, words):\n source_idx, target_idx = PretrainedEmbeddings.reindex(words, self.word2index)\n extraction = np.zeros((len(words), self.dim()))\n extraction[source_idx] = self.embed.vectors[target_idx]\n extraction = torch.from_numpy(extraction).float()\n return extraction\n\n","sub_path":"src/embedding/pretrained.py","file_name":"pretrained.py","file_ext":"py","file_size_in_byte":3159,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"414764284","text":"##############\n# Exercise 2.5\n##############\n\n# You can use the supplied test cases for your own testing. Good luck!\n\nimport re\n\nstart = \"ATG\"\nstop = [\"TAA\", \"TAG\", \"TGA\"]\n\n\ncodon_dict = dict()\n\ndef complementary(input):\n m = dict({\n 'A': 'T',\n 'T': 'A',\n 'G': 'C',\n 'C': 'G'\n })\n\n return \"\".join([m[letter] for letter in input.upper()])\n\n\n\ndef initDict():\n all = ['G', 'T', 'A', 'C']\n\n # G\n codon_dict.update({'GG'+c: 'G' for c in all})\n codon_dict.update({'GC'+c: 'A' for c in all})\n codon_dict.update({'GT'+c: 'V' for c in all})\n codon_dict.update({'GA'+c: 'E' for c in ['G', 'A']})\n codon_dict.update({'GA'+c: 'D' for c in ['C', 'T']})\n\n # C\n codon_dict.update({'CT'+c: 'L' for c in all})\n codon_dict.update({'CC'+c: 'P' for c in all})\n codon_dict.update({'CG'+c: 'R' for c in all})\n codon_dict.update({'CA'+c: 'Q' for c in ['G', 'A']})\n codon_dict.update({'CA'+c: 'H' for c in ['C', 'T']})\n\n # A\n codon_dict.update({'AC'+c: 'T' for c in all})\n codon_dict.update({'AT'+c: 'I' for c in ['A', 'C', 'T']})\n codon_dict.update({'ATG': 'M'})\n codon_dict.update({'AA'+c: 'K' for c in ['G', 'A']})\n codon_dict.update({'AA'+c: 'N' for c in ['C', 'T']})\n codon_dict.update({'AG'+c: 'R' for c in ['G', 'A']})\n codon_dict.update({'AG'+c: 'S' for c in ['C', 'T']})\n\n # T\n codon_dict.update({'TC'+c: 'S' for c in all})\n codon_dict.update({'TT'+c: 'L' for c in ['G', 'A']})\n codon_dict.update({'TT'+c: 'F' for c in ['C', 'T']})\n codon_dict.update({'TA'+c: 'Y' for c in ['C', 'T']})\n codon_dict.update({'TA'+c: 'STOP' for c in ['G', 'A']})\n codon_dict.update({'TG'+c: 'C' for c in ['C', 'T']})\n codon_dict.update({'TGA': 'STOP'})\n codon_dict.update({'TGG': 'W'})\n\ndef triplet_to_aa(t):\n if len(t) != 3:\n return None\n\n return codon_dict.get(t)\n\n\ndef validate(genome):\n if len(re.sub(\"[^TAGC]+\", '', genome)) < len(genome):\n raise TypeError\n\ndef get_next(genome, start_index):\n if start_index + 3 < len(genome):\n return (genome[start_index:start_index+3], start_index+3)\n elif start_index + 3 == len(genome):\n return (genome[start_index:start_index+3], 0)\n elif start_index + 3 > len(genome) and start_index + 3 < len(genome) + 3:\n res = genome[start_index:len(genome)]\n next_index = start_index - len(genome) + 3\n res = res + genome[0:next_index]\n return (res, next_index)\n else:\n raise RuntimeError\n\ndef read(genome, start_index, reversed):\n validate(genome)\n current_index = start_index\n first_sequence_index = None\n reading_sequence = False\n done = False\n\n first_stop = None\n\n sequences = dict()\n\n aa_sequence = \"\"\n while not done:\n triplet, next_index = get_next(genome, current_index)\n if not reading_sequence and triplet == start:\n first_sequence_index = current_index\n reading_sequence = True\n\n if reading_sequence and triplet in stop:\n reading_sequence = False\n\n if first_stop is None:\n first_stop = current_index\n else:\n if current_index == first_stop:\n done = True\n\n if len(aa_sequence) > 33:\n from_index = first_sequence_index\n to_index = next_index - 1 if next_index > 0 else len(genome)-1\n\n if reversed:\n from_index = len(genome) - from_index - 1\n to_index = len(genome) - to_index - 1\n\n new = (from_index, to_index, aa_sequence, reversed)\n old = sequences.get(to_index)\n\n if old is None:\n sequences[to_index] = new\n else:\n _, _, seq, _ = sequences[to_index]\n if len(seq) > len(aa_sequence):\n sequences[to_index] = new\n\n aa_sequence = \"\"\n\n if reading_sequence:\n aa_sequence += (triplet_to_aa(triplet))\n\n current_index = next_index\n\n return sequences\n\ndef get_orfs(genome):\n initDict()\n l = []\n\n res = read(genome, 0, False)\n for last_index, orf in read(genome, 1, False).items():\n if res.get(last_index) is not None:\n _, _, old_seq, _ = res.get(last_index)\n _, _, new_seq, _ = orf\n if len(new_seq) > len(old_seq):\n res[last_index] = orf\n for last_index, orf in read(genome, 2, False).items():\n if res.get(last_index) is not None:\n _, _, old_seq, _ = res.get(last_index)\n _, _, new_seq, _ = orf\n if len(new_seq) > len(old_seq):\n res[last_index] = orf\n\n l = list(res.values())\n\n res = read(complementary(genome)[::-1], 0, True)\n for last_index, orf in read(complementary(genome)[::-1], 1, True).items():\n if res.get(last_index) is not None:\n _, _, old_seq, _ = res.get(last_index)\n _, _, new_seq, _ = orf\n if len(new_seq) > len(old_seq):\n res[last_index] = orf\n for last_index, orf in read(complementary(genome)[::-1], 2, True).items():\n if res.get(last_index) is not None:\n _, _, old_seq, _ = res.get(last_index)\n _, _, new_seq, _ = orf\n if len(new_seq) > len(old_seq):\n res[last_index] = orf\n\n l += list(res.values())\n\n return l","sub_path":"codechecker/repos/1/collected_files/orffinder/ga58luw.py","file_name":"ga58luw.py","file_ext":"py","file_size_in_byte":5420,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"287493651","text":"from datetime import datetime\nfrom textwrap import dedent\nfrom os.path import join, dirname\n\nfrom django.db import connection, reset_queries\nfrom django.contrib.contenttypes.models import ContentType\nfrom django.contrib.sites.models import Site\nfrom django.conf import settings\nfrom django.test import TestCase as DjangoTestCase, override_settings\n\nfrom django_comments_tree.models import (TreeComment, CommentAssociation,\n MaxThreadLevelExceededException)\nfrom django_comments_tree.tests.models import Article, Diary\n\nfrom django_comments_tree.models import (LIKEDIT_FLAG, DISLIKEDIT_FLAG,\n TreeCommentFlag)\nfrom django_comments_tree.tests.factories import (ArticleFactory,\n UserFactory,\n TreeCommentFactory,\n TreeCommentFlagFactory)\n\n\nclass ManagerTestBase(DjangoTestCase):\n\n @classmethod\n def setUpTestData(cls):\n cls.article_1 = ArticleFactory.create()\n cls.article_2 = ArticleFactory.create()\n cls.user1 = UserFactory.create()\n cls.user2 = UserFactory.create()\n cls.site = Site.objects.get(pk=1)\n cls.root_1 = TreeComment.objects.get_or_create_root(cls.article_1)\n cls.root_2 = TreeComment.objects.get_or_create_root(cls.article_2)\n\n cls.c1list = []\n cls.c2list = []\n for x in range(10):\n cls.c1list.append(cls.root_1.add_child(comment=f\"Comment Root1 {x}\"))\n cls.c2list.append(cls.root_2.add_child(comment=f\"Comment Root2 {x}\"))\n\n TreeCommentFlagFactory.create(user=cls.user1,\n comment=cls.c1list[0],\n flag=LIKEDIT_FLAG)\n TreeCommentFlagFactory.create(user=cls.user1,\n comment=cls.c1list[1],\n flag=DISLIKEDIT_FLAG)\n TreeCommentFlagFactory.create(user=cls.user1,\n comment=cls.c1list[2],\n flag=LIKEDIT_FLAG)\n TreeCommentFlagFactory.create(user=cls.user1,\n comment=cls.c1list[3],\n flag=DISLIKEDIT_FLAG)\n TreeCommentFlagFactory.create(user=cls.user1,\n comment=cls.c1list[7],\n flag=LIKEDIT_FLAG)\n TreeCommentFlagFactory.create(user=cls.user1,\n comment=cls.c1list[7],\n flag=TreeCommentFlag.SUGGEST_REMOVAL)\n\n\n\nclass TestModelManager(ManagerTestBase):\n\n def test_user_likes(self):\n\n result = TreeComment.objects.user_flags_for_model(self.user1,\n self.article_1)\n\n self.assertIsNotNone(result)\n\n self.assertIn('user', result)\n likes = result['liked']\n dislikes = result['disliked']\n reported = result['reported']\n self.assertEqual(len(likes), 3)\n self.assertEqual(len(dislikes), 2)\n self.assertEqual(len(reported), 1)\n self.assertEqual(likes, [self.c1list[0].id, self.c1list[2].id, self.c1list[7].id])\n","sub_path":"django_comments_tree/tests/test_model_manager.py","file_name":"test_model_manager.py","file_ext":"py","file_size_in_byte":3341,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"194936174","text":"# -*- coding: utf-8 -*-\nfrom django.shortcuts import render, redirect\nfrom django.contrib.auth.decorators import login_required\nfrom django.utils.decorators import method_decorator\nfrom django.core.paginator import Paginator, EmptyPage, PageNotAnInteger\nfrom django.views.generic import ListView\nfrom django.views.generic.edit import UpdateView, CreateView, FormView\nfrom django.core.urlresolvers import reverse\nfrom django.template import RequestContext\nfrom django.db.models import Q\n\n#from haystack.views import SearchView\n#from haystack.forms import SearchForm\n#from haystack.query import SearchQuerySet\n\nfrom profiles.models import Profile\nfrom geonames.models import Locality\nfrom models import Cartera, Practica, Ubicacion, Registro, Borrador, Definitiva, Otro_agente, Informacion_financiera\n\nfrom django import forms\nfrom gmapi import maps\nfrom gmapi.forms.widgets import GoogleMap\n\nfrom django.conf import settings\nimport elasticsearch\n\nes_host = settings.ELASTICSEARCH_HOST\n\nclass MapForm(forms.Form):\n \"\"\"Widget con google map grande\"\"\"\n map = forms.Field(widget=GoogleMap(attrs={'width':750, 'height':400}))\n\nclass MMapForm(forms.Form):\n \"\"\"Widget con google map chico\"\"\"\n map = forms.Field(widget=GoogleMap(attrs={'width':500, 'height':270}))\n\ndef mapea_busquedas(geo_names=[], googles=[]):\n \"\"\"Inserta los marcadores de dos listas de las busquedas de geocodificacion\"\"\"\n color = {1 : 'ffdf00', 2 : '0005ff'}\n gmap = maps.Map(opts = {\n 'mapTypeId': maps.MapTypeId.ROADMAP,\n 'mapTypeControlOptions': {\n 'style': maps.MapTypeControlStyle.DROPDOWN_MENU }, })\n if geo_names == None : geo_names = [] \n for location in geo_names :\n marker = maps.Marker(opts = {\n 'map': gmap,\n 'position': maps.LatLng(location.latitude,location.longitude),\n 'icon': u'http://gmapsmarkergenerator.eu01.aws.af.cm/getmarker?scale=1&color=%s' %color[2] })\n #'icon' : u'/static/markers/2.png' })\n maps.event.addListener(marker, 'mouseover', 'myobj.markerOver')\n maps.event.addListener(marker, 'mouseout', 'myobj.markerOut')\n info = maps.InfoWindow({\n 'content': location.address ,\n 'disableAutoPan': True })\n info.open(gmap, marker)\n if googles == None : googles = [] \n for location in googles :\n marker = maps.Marker(opts = {\n 'map': gmap,\n 'position': maps.LatLng(location.latitude,location.longitude),\n 'icon': u'http://gmapsmarkergenerator.eu01.aws.af.cm/getmarker?scale=1&color=%s' %color[1] })\n #'icon' : u'/static/markers/1.png' })\n maps.event.addListener(marker, 'mouseover', 'myobj.markerOver')\n maps.event.addListener(marker, 'mouseout', 'myobj.markerOut')\n info = maps.InfoWindow({\n 'content': location.address ,\n 'disableAutoPan': True })\n info.open(gmap, marker)\n return gmap\n\ndef mapea_practicas(practicas):\n \"\"\"Inserta marcadores coloreados en base al numero de la cartera a que pertenecen las practicas\"\"\"\n color = {1 : 'ffcf00', 2 : '0030ff', 3 : '30ff00', 0 : 'ff00cf', 4: '00b099', 5 : '9940ff'} \n #color = {}\n #for n in range(1,15) :\n # color.update({n: '%d.png' %n})\n gmap = maps.Map(opts = {\n 'mapTypeId': maps.MapTypeId.ROADMAP,\n 'mapTypeControlOptions': {\n 'style': maps.MapTypeControlStyle.DROPDOWN_MENU }, })\n for practica in practicas: #[ubicacion for borradores in practica.borrador_set.all() for ubicacion in borradores.ubicaciones.all()]:\n for u in practica.ubicaciones.all() :\n if u.point :\n location = u.point\n marker = maps.Marker(opts = {\n 'map': gmap,\n 'position': maps.LatLng(location.y,location.x),\n 'icon': u'http://gmapsmarkergenerator.eu01.aws.af.cm/getmarker?scale=1&color=%s' %color[practica.registro.cartera.pk%6]\n #'icon' : u'/static/markers/%s' % color[practica.registro.cartera.pk%14]\n })\n maps.event.addListener(marker, 'mouseover', 'myobj.markerOver')\n maps.event.addListener(marker, 'mouseout', 'myobj.markerOut')\n info = maps.InfoWindow({\n 'content': practica.registro.cartera.name+'
'+practica.name+'
'+u.address ,\n 'disableAutoPan': True })\n info.open(gmap, marker)\n return gmap\n\ndef practicando(user) :\n \"\"\"Genera la lista de objetos a listar para cada grupo de usuarios\"\"\"\n if user.groups.filter(name__in=['Codificadores',]) or user.is_superuser :\n lista = user.borrador_set.filter(estado=1)\n elif user.groups.filter(name__in=['Arbitros',]) :\n lista = user.definitiva_set.order_by('estado') # .exclude(estado=4)\n elif user.groups.filter(name__in=['Gerentes',]) :\n lista = Cartera.objects.filter(gerente=user) # .exclude(practicas__definitiva__estado=4)\n else :\n lista = Cartera.objects.all()\n return lista\n\ndef display(obj, field):\n field_obj = obj._meta.get_field(field)\n if getattr(obj,field) : return dict(field_obj.choices)[getattr(obj,field)]\n else : return '----'\n\n@login_required\ndef home(request):\n \"\"\"Vista inicial con la lista de elementos a administrar\n\n **Context**\n\n ``practicas``\n Instancia de :model:`observatorio.Practica`.\n\n ``carteras``\n Instancia de :model:`observatorio.Cartera`.\n\n **Template:**\n\n :template:`admin/home.html`\n \"\"\"\n if 'observacoop' in request.get_host() :\n practicas = practicando(request.user)\n else :\n return redirect(reverse('profile_logout'))\n\n context = RequestContext(request) \n if request.user.groups.filter(name__in=['Gerentes','Administradores']) :\n context['title'] = \"Carteras\"\n context['carteras'] = practicas\n practicas = set([practica for cartera in practicas for practica in cartera.practicas.all()])\n\n else:\n context['title'] = \"Practicas\"\n\n context['objects'] = practicas\n \n return render(request, 'admin/home.html', context )\n\n@login_required\ndef map(request, opt, pk):\n \"\"\"Despliega en un mapa los marcadores segun las\n\n **opciones**\n\n ``apa`` restinge las ubicaciones geocodificadas a las de la cartera(pk)\n\n ``bus`` busca en Geonames y google el termino de busqueda\n\n ``pnt`` busqueda inversa del codigo de geonames\n\n ``---`` las ubicaciones de las practicas asociadas al usuario \n \"\"\"\n context = RequestContext(request) \n if request.user.groups.filter(name='Arbitros') :\n practicas = Borrador.objects.filter(registro__definitiva__arbitro=request.user)\n elif request.user.groups.filter(name='Gerentes') :\n practicas = Borrador.objects.filter(registro__cartera__gerente=request.user)\n elif request.user.groups.filter(name='Administradores') :\n practicas = Borrador.objects.all()\n else :\n practicas = practicando(request.user)\n context['is_popup'] = True\n context['pk'] = pk\n\n if 'apa' == opt :\n practicas = practicas.filter(registro__cartera__id=pk) # [practica for practica in practicas if practica.registro.cartera.id == pk ]\n context['title'] = 'Cartera: %s' %practicas[0].registro.cartera.name\n\n if 'pnt' == opt :\n import requests\n import json\n gmap = maps.Map(opts = {'mapTypeId': maps.MapTypeId.ROADMAP, 'zoom': 8,\n 'mapTypeControlOptions': {\n 'style': maps.MapTypeControlStyle.DROPDOWN_MENU }, })\n ubicacion = Ubicacion.objects.get(pk=pk)\n base_url = 'http://api.geonames.org/getJSON?geonameId=%s&username=observacoop' %ubicacion.geonameId\n url_info = requests.get(base_url)\n geoinfo = json.loads(url_info.text)\n conts=''\n for line in [''+key+': '+geoinfo[key].__repr__()+'
' for key in geoinfo.viewkeys() if geoinfo[key] and key not in ['timezone','bbox']]: #alternateNames\n conts += line\n marker = maps.Marker(opts = {\n 'map': gmap,\n 'position': maps.LatLng(ubicacion.point.y,ubicacion.point.x),\n 'icon': u'http://gmapsmarkergenerator.eu01.aws.af.cm/getmarker?scale=1&color=%s' %\"00FFFF\"\n #'icon' : u'/static/markers/%d.png' % 8\n })\n maps.event.addListener(marker, 'mouseover', 'myobj.markerOver')\n info = maps.InfoWindow({\n 'content': conts,\n 'disableAutoPan': True })\n info.open(gmap, marker)\n context['form'] = MMapForm(initial={'map': gmap})\n context['title'] = 'geonameId: %d' % ubicacion.geonameId\n\n elif len(request.GET) or 'bus' == opt :\n data = request.GET\n context['is_popup'] = False\n query = data.get('q')\n if query :\n from geopy.geocoders import GeoNames, GoogleV3\n GNlocator = GeoNames(country_bias='MX', username='observacoop', timeout=40, proxies=None)\n Golocator = GoogleV3(api_key='AIzaSyDsI5Yh2XdPIRkbF-_Z1AP17vcXF_tYp-I', domain='maps.googleapis.com', \n scheme='https', client_id=None, secret_key=None, timeout=40, proxies=None)\n geo_names = GNlocator.geocode(query,False)\n googles = Golocator.geocode(query,False)\n if geo_names != None or googles != None :\n gmap = mapea_busquedas(geo_names, googles)\n context['form'] = MapForm(initial={'map': gmap})\n context['geo_names'] = geo_names\n context['googles'] = googles\n context['title'] = 'encontradas'\n else:\n context['error'] = 'No hay respuesta, favor de hacer una nueva busqueda'\n\n else :\n gmap = mapea_practicas(practicas)\n context['form'] = MapForm(initial={'map': gmap})\n\n return render(request, 'admin/map.html', context )\n\nclass UpdateUbicacionView(FormView):\n \"\"\"Asigna a la ubicacion el codigo de GeoNames seleccionado del resultado de la busqueda\"\"\"\n model = Ubicacion\n\n def get(self, request, **kwargs):\n return redirect(reverse('admin:observatorio_ubicacion_change', args=(self.kwargs['pk'],)))\n\n def post(self, request, **kwargs):\n \"\"\"Asigna los atributos de la respuesta de GeoNames\"\"\"\n from django.contrib.gis.geos import Point\n ubicacion_id = int(self.kwargs['pk'])\n ubicacion = Ubicacion.objects.get(pk=ubicacion_id)\n ubicacion.adminName1 = request.POST.get('adminName1')\n ubicacion.address = request.POST.get('address')\n ubicacion.geonameId = int(request.POST.get('geonameId'))\n ubicacion.point = Point(float(request.POST.get('point_longitude')), float(request.POST.get('point_latitude')))\n ubicacion.save()\n\n return redirect(reverse('admin:observatorio_ubicacion_change', args=(self.kwargs['pk'],)))\n \n @method_decorator(login_required)\n def dispatch(self, *args, **kwargs):\n return super(UpdateUbicacionView, self).dispatch(*args, **kwargs)\n\n@login_required\ndef pendientes(request, pk):\n \"\"\"Genera la lista de las ubicaciones que no estan geocodificados al cambiar el estado del borrador\"\"\"\n practicas = practicando(request.user).filter(ubicaciones__estado=1).filter(pk=pk)\n ubicaciones = [ ubicacion for practica in practicas for ubicacion in practica.ubicaciones.all() ]\n context = RequestContext(request) \n context['title'] = \"Ubicaciones pendientes por geocodificar\"\n context['objects'] = set(ubicaciones)\n \n return render(request, 'admin/pendientes.html', context )\n\nclass UpdatePracticaView(FormView):\n \"\"\"Actualizacion de estados\n **Definitiva**\n\n ``Geocodificada`` Cuando ambos borradores estan geocodificados, se llena con los datos que tienen ambos en comun junto con los que tiene solo uno o el otro, mismos que se borran si alguno es rechazado.\n \n ``En proceso`` Cuando ambos borradores son rechazados.\n\n ``Indexada`` Cuando ambos borradores estan aceptados y se han rectificado los datos definitivos. \n \"\"\"\n model = Practica\n\n def get(self, request, **kwargs):\n context = RequestContext(request)\n template = 'admin/error.html'\n context['practica'] = Borrador.objects.get(pk=int(self.kwargs['pk']))\n return render(request, template, context) \n\n def post(self, request, **kwargs):\n practica_id = int(self.kwargs['pk'])\n if self.kwargs['opt'] == 'idx' :\n practica = Definitiva.objects.get(pk=practica_id)\n else :\n practica = Borrador.objects.get(pk=practica_id)\n if practica.ubicaciones.filter(estado=1) :\n return redirect(reverse('observatorio_pendientes', kwargs={'pk' : practica.pk}))\n if self.kwargs['opt'] == 'gcd' : \n practica.estado = 2\n practica.error = None\n practica.save()\n if not practica.registro.borrador_set.filter(estado=1) :\n definitiva = practica.registro.definitiva_set.all().first()\n borradores = practica.registro.borrador_set.all()\n for field in practica.practica_ptr._meta.fields :\n if getattr(borradores[0],field.name) == getattr(borradores[1],field.name) :\n setattr(definitiva,field.name,getattr(borradores[0],field.name))\n if not getattr(borradores[0],field.name) and getattr(borradores[1],field.name) :\n setattr(definitiva,field.name,getattr(borradores[1],field.name))\n if not getattr(borradores[1],field.name) and getattr(borradores[0],field.name) :\n setattr(definitiva,field.name,getattr(borradores[0],field.name))\n for ubicacion in borradores[0].practica_ptr.ubicaciones.filter(geonameId__in=[u.geonameId for u in borradores[1].practica_ptr.ubicaciones.all()]) :\n ub = Ubicacion.objects.create(practicas=definitiva.practica_ptr)\n otra = borradores[1].practica_ptr.ubicaciones.get(geonameId=ubicacion.geonameId)\n for field, val, display_val in ubicacion : \n if getattr(ubicacion,field.name) == getattr(otra,field.name) : setattr(ub, field.name, val)\n ub.save()\n for ubicacion in borradores[0].practica_ptr.ubicaciones.exclude(geonameId__in=[u.geonameId for u in borradores[1].practica_ptr.ubicaciones.all()]) :\n ub = Ubicacion.objects.create(practicas=definitiva.practica_ptr)\n for field, val, display_val in ubicacion : \n if field.name not in ('id', 'actividades', 'actividad', 'practicas') : setattr(ub, field.name, val)\n if field.name == 'actividad' : \n ub.actividad.add(val)\n ub.save()\n for ubicacion in borradores[1].practica_ptr.ubicaciones.exclude(geonameId__in=[u.geonameId for u in borradores[0].practica_ptr.ubicaciones.all()]) :\n ub = Ubicacion.objects.create(practicas=definitiva.practica_ptr)\n for field, val, display_val in ubicacion : \n if field.name not in ('id', 'actividades', 'actividad', 'practicas') : setattr(ub, field.name, val)\n if field.name == 'actividad' : \n ub.actividad.add(val)\n ub.save()\n for agente in borradores[0].practica_ptr.otros_agentes.filter(nombre__in=[a.nombre for a in borradores[1].practica_ptr.otros_agentes.all()]) :\n ag = Otro_agente.objects.create(practica=definitiva.practica_ptr)\n otra = borradores[1].practica_ptr.otros_agentes.get(nombre=ubicacion.geonameId)\n for field, val, display_val in agente : \n if getattr(agente,field.name) == getattr(otra,field.name) : setattr(ag, field.name, val)\n ag.save()\n for agente in borradores[0].practica_ptr.otros_agentes.exclude(nombre__in=[a.nombre for a in borradores[1].practica_ptr.otros_agentes.all()]) :\n ag = Otro_agente.objects.create(practica=definitiva.practica_ptr)\n for field, val, display_val in agente : \n if field.name not in ('id', 'otros_agentes', 'practica') : setattr(ag, field.name, val)\n ag.save()\n for agente in borradores[1].practica_ptr.otros_agentes.exclude(nombre__in=[a.nombre for a in borradores[0].practica_ptr.otros_agentes.all()]) :\n ag = Otro_agente.objects.create(practica=definitiva.practica_ptr)\n for field, val, display_val in agente : \n if field.name not in ('id', 'otros_agentes', 'practica') : setattr(ag, field.name, val)\n ag.save()\n for info in [ informacion for borrador in borradores for informacion in borrador.practica_ptr.financieros.all() ] :\n fi = Informacion_financiera.objects.create(practica=definitiva.practica_ptr)\n for field, val, display_val in info :\n if field.name not in ('id', 'practica', 'ministraciones') : setattr(fi, field.name, val)\n if field.name == 'ministraciones' :\n for ministracion in val.all(): fi.ministraciones.add(ministracion)\n fi.save()\n definitiva.estado = 2\n definitiva.save()\n if self.kwargs['opt'] == 'gdc' : \n if not request.POST.get('error') :\n context = RequestContext(request)\n template = 'admin/error.html'\n context['practica'] = Borrador.objects.get(pk=int(self.kwargs['pk']))\n context['error'] = 'Favor de dar un motivo'\n return render(request, template, context) \n else :\n practica.error = self.request.POST['error']\n practica.estado = 1\n practica.save()\n definitiva = practica.registro.definitiva_set.all().first()\n new=Definitiva.objects.create(arbitro_id=definitiva.arbitro_id,registro_id=definitiva.registro_id)\n definitiva.delete()\n if practica.registro.borrador_set.filter(estado=2) :\n new.estado = 2\n new.save()\n if self.kwargs['opt'] == 'fin' : \n practica.estado = 3\n practica.save()\n if not practica.registro.borrador_set.filter(estado__in=[1, 2]) :\n definitiva = practica.registro.definitiva_set.all().first()\n definitiva.estado = 3\n definitiva.save()\n if self.kwargs['opt'] == 'idx' : \n practica.estado = 4\n practica.save()\n return redirect(reverse('observatorio_home'))\n\n @method_decorator(login_required)\n def dispatch(self, *args, **kwargs):\n return super(UpdatePracticaView, self).dispatch(*args, **kwargs)\n\n@login_required\ndef arbitra(request, pk, opt):\n \"\"\"Despliegue y cambio de estado de borradores y edicion de definitiva para el arbitro\"\"\"\n context = RequestContext(request)\n if opt == 'b' :\n objeto = Borrador.objects.get(pk=pk)\n elif opt == 'd' :\n objeto = Definitiva.objects.get(pk=pk)\n if opt == 'r' :\n context['title'] = \"Revisión de practicas\"\n context['definitiva'] = Definitiva.objects.get(pk=pk)\n template = 'admin/arbitra.html'\n else :\n template = 'admin/skel_arbitra.html'\n fieldset = (\n ('Información General', {'d_fields': ('practica_tipo',), 'fields': ('pais_receptor', 'pais_oferente', 'pais_socio',),\n 'd_fields2': ('poblacion_objetivo',), 'fields2': ( 'agencia_implementadora',), 'd_fields3': ( 'tipo_agente_implementador',), \n 'fields3': ( 'agencia_financiadora',), 'd_fields4': ('tipo_agente_financiador', 'modalidad_de_cooperacion', \n 'tipo_de_cooperacion', 'estatus',), 'fields4': ( 'descripcion_corta',\n 'descripcion_larga',), 'l_fields': ('documento_extra', 'url_referencia',)}),)\n fieldsets = (\n ('Inicio de operaciones', {'fields': ('inicio_dia','inicio_mes','inicio_ano')}),\n ('Final de operaciones', {'fields': ('final_dia','final_mes','final_ano')}),\n ('Vigencia', {'fields': ('vigencia_meses','vigencia_anos',)}),\n )\n sections = []\n for section in fieldset :\n fields = []\n for field in section[1]['d_fields'] :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': display(objeto,field)})\n for field in section[1]['fields'] :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': getattr(objeto,field) })\n for field in section[1]['d_fields2'] :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': display(objeto,field)})\n for field in section[1]['fields2'] :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': getattr(objeto,field) })\n for field in section[1]['d_fields3'] :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': display(objeto,field)})\n for field in section[1]['fields3'] :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': getattr(objeto,field) })\n for field in section[1]['d_fields4'] :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': display(objeto,field)})\n for field in section[1]['fields4'] :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': getattr(objeto,field) })\n sections.append({'name': section[0], 'fields': fields})\n for section in fieldsets :\n fields = []\n for field in section[1]['fields'] :\n if getattr(objeto,field) :\n fields.append({'name': objeto._meta.get_field(field).verbose_name.capitalize() , 'value': getattr(objeto,field) })\n sections.append({'name': section[0], 'fields': fields})\n links = []\n fields = []\n if objeto.documento_extra :\n fields.append({'name': objeto._meta.get_field('documento_extra').verbose_name.capitalize() , 'url': objeto.documento_extra.url, 'value': objeto.documento_extra.name.strip('./') })\n fields.append({'name': objeto._meta.get_field('url_referencia').verbose_name.capitalize() , 'url': objeto.url_referencia, 'value': objeto.url_referencia })\n links.append({'name': 'Referencias', 'fields': fields})\n related = []\n fields = []\n for agente in objeto.otros_agentes.all() :\n subfields = []\n for field, val, display_val in agente :\n subfields.append({'name': field.verbose_name.capitalize(), 'value': display_val})\n fields.append({'name': agente.nombre, 'value': subfields })\n related.append({'name': 'Otros Agentes', 'fields': fields})\n fields = []\n for financiera in objeto.financieros.all() :\n subfields = []\n subfields.append({'name': 'Ministrado', 'value': financiera.ministrado()})\n for field, val, display_val in financiera :\n subfields.append({'name': field.name.capitalize(), 'value': display_val})\n fields.append({'name': financiera.id_financiadora, 'value': subfields }) \n related.append({'name': 'Información Fianciera', 'fields': fields})\n fields = []\n for ubicacion in objeto.ubicaciones.all() :\n subfields = []\n for field, val, display_val in ubicacion :\n subfields.append({'name': field.verbose_name.capitalize(), 'value': display_val})\n fields.append({'id': ubicacion.id, 'name': ubicacion.geo_codigo, 'value': subfields })\n related.append({'name': 'Ubicaciones', 'fields': fields})\n context['sections'] = sections\n context['related'] = related\n context['links'] = links\n context['objeto'] = objeto\n \n return render(request, template, context)\n\nclass CreateCarteraView(CreateView):\n model = Cartera\n template_name = 'observatorio/cartera_form.html'\n #class_form = CarteraForm\n\n @method_decorator(login_required)\n def dispatch(self, *args, **kwargs):\n return super(CreateCarteraView, self).dispatch(*args, **kwargs)\n","sub_path":"observatorio/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":24575,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"196073942","text":"#!/usr/bin/python3\n\"\"\"Function to print a square\n with the character #. size must be\n 0 or a positive integer, otherwise raise a\n ValueError or TypeError.\n\"\"\"\n\n\ndef print_square(size):\n \"\"\"Print a square with # character and size 0 or\n a positive integer, otherwise raise exceptions.\n \"\"\"\n if type(size) is not int:\n raise TypeError(\"size must be an integer\")\n if size < 0:\n raise ValueError(\"size must be >= 0\")\n for i in range(size):\n print(\"#\" * size)\n","sub_path":"0x07-python-test_driven_development/4-print_square.py","file_name":"4-print_square.py","file_ext":"py","file_size_in_byte":503,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"493744834","text":"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n\nfrom tornado.web import RequestHandler\n\nimport os\nimport codecs\nimport json\nimport hashlib\nimport functools\nimport urlparse # py2\nfrom urllib import urlencode # py2\n\nfrom libs_gl import xlog\nfrom libs_gl import xhttp\n\nimport base_handler\n\nimport dao\nimport config\nimport time\nimport datetime\nimport requests\nimport recharge_handler\n\nbrand_info = {\n\n\t\"uu\": {\n\t\t\"name\": u\"UU电话\",\n\t},\n\n\t\"efl\": {\n\t\t\"name\": u\"易聊电话\",\n\t},\n\t\"3g\": {\n\t\t\"name\": u\"3G电话\",\n\t},\n\n\t\"kc\": {\n\t\t\"name\": u\"KC电话\",\n\t},\n\n\t\"sky\": {\n\t\t\"name\": u\"Sky电话\",\n\t},\n\n\t\"feiin\": {\n\t\t\"name\": u\"免费Wifi电话\",\n\t},\n\t\"4g\": {\n\t\t\"name\": u\"4G电话\",\n\t},\n}\n\n\nclass IndexHandler(RequestHandler):\n\tdef get(self, bid):\n\t\tpc_flag = self.get_argument(\"pc_flag\", \"\")\n\t\tuid = self.get_argument(\"uid\", \"\")\n\t\tkeys = brand_info.keys()\n\t\tif bid not in keys:\n\t\t\tkwargs = {\n\t\t\t\t\"reason\": u\"非法请求，品牌不正确\",\n\t\t\t}\n\t\t\tself.render(\"activities/double_dan/error.html\", **kwargs)\n\t\t\treturn\n\n\t\tis_iphone = False\n\t\tuser_agent = self.request.headers[\"User-Agent\"]\n\t\t\"\"\":type :str\"\"\"\n\t\tif user_agent.lower().find('iphone') != -1:\n\t\t\tis_iphone = True\n\n\t\tis_act_start = recharge_handler.check_activity_time_range()\n\t\tif is_act_start < 0:\n\t\t\tis_act_start = False\n\t\telse:\n\t\t\tis_act_start = True\n\n\n\t\tkwargs = {\n\t\t\t\"bid\": bid,\n\t\t\t\"uid\": uid,\n\t\t\t\"is_iphone\": is_iphone,\n\t\t\t\"pc_flag\": pc_flag,\n\t\t\t\"is_act_start\":is_act_start,\n\t\t}\n\t\tself.render(\"activities/double_dan/index.html\", **kwargs)\n\n\nclass LotterHandler(RequestHandler):\n\tdef get(self, bid):\n\t\tuid = self.get_argument(\"uid\", \"\")\n\t\tdata = recharge_handler.startLottery(bid, uid)\n\t\tself.write(json.dumps(data))\n\n\nclass LotteryDemoHandler(RequestHandler):\n\tdef get(self, bid):\n\t\tpc_flag = self.get_argument(\"pc_flag\", \"\")\n\t\tuid = self.get_argument(\"uid\", \"\")\n\t\tis_iphone = False\n\t\tuser_agent = self.request.headers[\"User-Agent\"]\n\t\t\"\"\":type :str\"\"\"\n\t\tif user_agent.lower().find('iphone') != -1:\n\t\t\tis_iphone = True\n\n\t\tkwargs = {\n\t\t\t\"bid\": bid,\n\t\t\t\"uid\": uid,\n\t\t\t\"is_iphone\": is_iphone,\n\t\t\t\"pc_flag\": pc_flag,\n\t\t}\n\t\tself.render(\"activities/double_dan/demo.html\", **kwargs)\n\n\nclass LoginHandler(RequestHandler):\n\tdef get(self, bid):\n\t\tuid = self.get_argument(\"uid\", \"\")\n\t\tpwd = self.get_argument(\"password\", \"\")\n\t\tif (len(uid) > 10):\n\t\t\tdata = recharge_handler.checkUserInfo(bid, uid, \"mobile\", pwd)\n\t\t\tif data.get(\"result\") == -1:\n\t\t\t\tdata = recharge_handler.checkUserInfo(bid, uid, \"uid\", pwd)\n\t\telse:\n\t\t\tdata = recharge_handler.checkUserInfo(bid, uid, \"uid\", pwd)\n\t\tself.write(json.dumps(data))\n\n\nclass QueryLotteryHandler(RequestHandler):\n\tdef get(self, bid, **kwargs):\n\t\tuid = self.get_argument(\"uid\", \"\")\n\t\tdata = recharge_handler.queryLottery(bid, uid)\n\t\t\"\"\":type :dict\"\"\"\n\t\tkwargs = {\n\t\t\t'list': data\n\t\t}\n\t\tself.render(\"activities/double_dan/lottery_log.html\", **kwargs)\n","sub_path":"src/main/act_double_dan.py","file_name":"act_double_dan.py","file_ext":"py","file_size_in_byte":2831,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"88"}
+{"seq_id":"277246181","text":"from flask import abort, redirect, render_template, request, url_for,abort,flash\nfrom flask_login import current_user, login_required, login_user, logout_user, login_manager\n\nfrom app.request import get_quote\n\nfrom .. import db\nfrom ..user import Blog, Comment, User\nfrom . import main\nfrom .forms import BlogForm, CommentForm, UpdateProfile,UpForm\n\n\n\n\n@main.route('/', methods=['GET', 'POST'])\ndef index():\n '''\n View root page function that returns the index page and its data\n '''\n title = 'my blogquote'\n quote = get_quote()\n blogs = Blog.query.all()\n return render_template('index.html', title=title, quote=quote, blogs=blogs)\n\n\n@main.route('/blog/new', methods=['GET', 'POST'])\n@login_required\ndef blogs():\n \"\"\"\n view blog function to create a new blog\n \"\"\"\n blog_form = BlogForm()\n\n if blog_form.validate_on_submit():\n title = blog_form.title.data\n content = blog_form.content.data\n print(current_user._get_current_object().id)\n blog = Blog(user_id=current_user._get_current_object().id,\n title=title, content=content)\n\n db.session.add(blog)\n db.session.commit()\n\n return redirect(url_for('main.index'))\n\n return render_template('new_blog.html', blog_form=blog_form)\n\n@main.route(\"/post/\")\n@login_required\ndef mypost(post_id):\n comments = Comment.query.filter_by(post_id=post_id).all()\n print(comments)\n heading = 'comments'\n blog = blog.query.get_or_404(post_id)\n return render_template('posts.html', title=blog.title, blog=blog, comments=comments, heading=heading)\n\n@main.route('/delete/blog,', methods=['GET', 'POST'])\n@login_required\ndef delete_blog(id):\n blog = Blog.query.filter_by(id=id).first()\n if blog is not None:\n blog.delete_blog()\n \n return redirect(url_for('main.index',))\n\n@main.route(\"/blog/update/\", methods=['GET', 'POST'])\n@login_required\ndef update_blog(id):\n blog = Blog.query.filter_by(id = id).first()\n if blog is None:\n abort(404)\n form = UpForm()\n if form.validate_on_submit():\n title = form.title.data\n content = form.content.data\n print(current_user._get_current_object().id)\n blog = Blog(user_id=current_user._get_current_object().id,\n title=title, content=content)\n \n db.session.add(blog)\n db.session.commit()\n \n return redirect(url_for('main.index', blog_id=blog.id))\n elif request.method == 'GET':\n title = form.title.data\n content = form.content.data\n return render_template('blog.html',form=form)\n\n\n@main.route('/user/