diff --git "a/1228.jsonl" "b/1228.jsonl" new file mode 100644--- /dev/null +++ "b/1228.jsonl" @@ -0,0 +1,613 @@ +{"seq_id":"87464227","text":"'''\nfinished in last second\n'''\nclass Solution:\n def cutOffTree(self, forest):\n m = len(forest)\n n = len(forest[0])\n if not self.can_cut(forest, m, n):\n # print('cant cut')\n return -1\n\n heights_with_location = []\n for x, row in enumerate(forest):\n for y, height in enumerate(row):\n if height > 1:\n heights_with_location.append((height, x, y))\n heights_with_location = sorted(heights_with_location, key=lambda x:x[0])\n print(heights_with_location)\n\n res = 0\n prev_x = 0 \n prev_y = 0\n for _, x, y in heights_with_location:\n res += self.find_route(prev_x, prev_y, x, y, forest)\n print(res)\n prev_x = x\n prev_y = y\n return res\n \n def find_route(self, x, y, n_x, n_y, forest):\n directions = [(0,-1), (0,1), (-1,0),(1,0)]\n \n m = len(forest)\n n = len(forest[0])\n visited = [[0 for _ in range(n)] for __ in range(m)]\n visited[x][y] = 1\n q = [(x, y, 0)]\n while len(q) > 0:\n x, y, time = q[0]\n if x == n_x and y == n_y:\n return time\n for x_step, y_step in directions:\n x_next = x + x_step\n y_next = y + y_step\n if 0 <= x_next < m and 0 <= y_next < n:\n if forest[x_next][y_next] > 0 and visited[x_next][y_next] == 0:\n q.append((x_next, y_next, time+1))\n visited[x_next][y_next] = 1\n q = q[1:]\n\n\n def all_cut(self, forest):\n for row in forest:\n for height in row:\n if height > 1:\n return False\n return True\n\n def can_cut(self, forest, m, n):\n directions = [(0,-1), (0,1), (-1,0),(1,0)]\n visited = [[0 for _ in range(n)] for __ in range(m)]\n visited[0][0] = 1\n q = [(0,0)]\n while len(q) > 0:\n x, y = q[0]\n for x_step, y_step in directions:\n x_next = x + x_step\n y_next = y + y_step\n if 0 <= x_next < m and 0 <= y_next < n:\n if forest[x_next][y_next] > 0 and visited[x_next][y_next] == 0:\n q.append((x_next, y_next))\n visited[x_next][y_next] = 1\n q = q[1:]\n\n for row_v, row_f in zip(visited, forest):\n for vis, height in zip(row_v, row_f):\n if vis == 0 and height > 0:\n return False\n return True\n\nif __name__ == '__main__':\n sol = Solution()\n forest = [\n [4557,6199,7461,2554,6132,7471,7103,4290],\n [2034,2301,6733,6040,2603,5697,9541,6678],\n [7308,7368,9618,4386,6944,3923,4754,4294],\n [0,3016,7242,5284,6631,1897,1767,7603],\n [2228,0,3625,7713,2956,3264,3371,6124],\n [9195,7804,2787,0,4919,9304,5161,502]\n ]\n print(sol.cutOffTree(forest))\n ","sub_path":"Mock Interview/11/Cut Off Trees for Golf Event.py","file_name":"Cut Off Trees for Golf Event.py","file_ext":"py","file_size_in_byte":3028,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"70671310","text":"import tkinter as tk\r\nfrom tkinter import filedialog\r\nimport csv\r\n#from mpl_toolkits.mplot3d import axes3d\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nfrom matplotlib.animation import FuncAnimation\r\nfrom numpy import genfromtxt\r\n\r\n###############################################################\r\n# open file\r\n###############################################################\r\nroot = tk.Tk()\r\nroot.withdraw()\r\nfile_path = filedialog.askopenfilename()\r\n\r\nif file_path is None:\r\n print('File not chosen.')\r\n quit()\r\nelse:\r\n dadostranspostos = genfromtxt(file_path, delimiter='\\t')\r\n #with open(file_path, newline='') as csvfile:\r\n # dados = csv.DictReader(csvfile)\r\n #data = list(csv.reader(csvfile))\r\n # for row in dados:\r\n # print(row)\r\n # print(row['time'], row['Va'], row['Vb'], row['Vc'])\r\n dados = np.transpose(dadostranspostos)\r\n\r\n#print(dados[0])\r\n\r\n##################################################\r\n# Constants and figures\r\n##################################################\r\nfig = plt.figure(figsize=plt.figaspect(0.45))\r\nabcscalars1 = fig.add_subplot(1,2,1)\r\nabcspace = fig.add_subplot(1,2,2, projection='3d')\r\n\r\n##################################################\r\n# Plotting mains voltages\r\n##################################################\r\nabcscalars1.plot(dados[0], dados[1], color='red', label='a')\r\nabcscalars1.plot(dados[0], dados[2], color='darkgreen', label='b')\r\nabcscalars1.plot(dados[0], dados[3], color='blue', label='c')\r\n\r\n##################################################\r\n# Settings of abc scalars chart\r\n##################################################\r\n#abcscalars1.set_xlim([0.00, 2*np.pi])\r\nabcscalars1.set_xlim([0.00, 0.04])\r\nabcscalars1.set_ylim([-1.2, 1.2])\r\n#abcscalars1.set_xlabel('angle')\r\n#abcscalars1.set_xlabel('time (rad)')\r\nabcscalars1.set_xlabel('time (s)')\r\nabcscalars1.set_ylabel('mains')\r\nabcscalars1.grid(False)\r\n#abcscalars1.set_xticks([])\r\n#abcscalars1.set_yticks([])\r\n#abcscalars1.set_zticks([])\r\n\r\n##################################################\r\n# Settings of abc space chart\r\n##################################################\r\n#abcspace.view_init(azim=-45, elev=20)\r\nabcspace.view_init(azim=45, elev=35.26) #top view from zero sequence line\r\nabcspace.set_proj_type('ortho')\r\nabcspace.set_xlim([-1,1])\r\nabcspace.set_ylim([-1,1])\r\nabcspace.set_zlim([-1,1])\r\n#abcspace.set_xlabel('a')\r\n#abcspace.set_ylabel('b')\r\n#abcspace.set_zlabel('c')\r\nabcspace.set_xticks([])\r\nabcspace.set_yticks([])\r\nabcspace.set_zticks([])\r\nabcspace.set_axis_off()\r\n#abcspace.xaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))#use if only the background is to be white\r\n#abcspace.yaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))\r\n#abcspace.zaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))\r\n##################################################\r\n# Plotting Balanced Plane\r\n##################################################\r\nbalancedplaneamplitude = 0\r\nnsampbalplane = 361\r\nanglesoneturn = np.linspace(start=0, stop=2*np.pi, num=nsampbalplane, endpoint=True)\r\nif balancedplaneamplitude > 0:\r\n balancedplanecircle = np.zeros((3, nsampbalplane))\r\n balancedplanecirclephaseshift = np.array([0, -2 * np.pi / 3, 2 * np.pi / 3])\r\n for numphase in range (0, 3):\r\n balancedplanecircle[numphase, :] = (balancedplaneamplitude\r\n * np.cos(anglesoneturn + balancedplanecirclephaseshift[numphase]))\r\n abcspace.plot(balancedplanecircle[0, :],\r\n balancedplanecircle[1, :],\r\n balancedplanecircle[2, :],\r\n color='blue',\r\n linewidth=0.5)\r\n\r\n balancedplanelines = np.ones((3, 50))\r\n anglestep = 10\r\n for i in range(0,10,1):\r\n for numphase in range(0, 3, 1):\r\n balancedplanelines[numphase, i * 5] = balancedplanecircle[numphase, anglestep * i]\r\n for numphase in range(0, 3, 1):\r\n balancedplanelines[numphase, i * 5 + 1] = balancedplanecircle[numphase, 180 - anglestep * i]\r\n for numphase in range(0, 3, 1):\r\n balancedplanelines[numphase, i * 5 + 2] = balancedplanecircle[numphase, 180 + anglestep * i]\r\n for numphase in range(0, 3, 1):\r\n balancedplanelines[numphase, i * 5 + 3] = balancedplanecircle[numphase, 360 - anglestep * i]\r\n for numphase in range(0, 3, 1):\r\n balancedplanelines[numphase, i * 5 + 4] = balancedplanecircle[numphase, anglestep * i]\r\n abcspace.plot(balancedplanelines[0, :],\r\n balancedplanelines[1, :],\r\n balancedplanelines[2, :],\r\n color='blue', label='a+b+c=0 plane',\r\n linewidth=0.5)\r\n\r\n##################################################\r\n# Plotting a b c base vectors\r\n##################################################\r\nshowabcbases = True\r\nbaselength = 1\r\n#quiverpivot = 'middle'\r\nquiverpivot = 'tail'\r\nif showabcbases:\r\n abcspace.quiver(0, 0, 0, 1, 0, 0, length=baselength,\r\n pivot=quiverpivot, arrow_length_ratio=0.025,\r\n linewidth=1, linestyle='dotted',\r\n color='black')\r\n abcspace.quiver(0, 0, 0, 0, 1, 0, length=baselength,\r\n pivot=quiverpivot, arrow_length_ratio=0.025,\r\n linewidth=1, linestyle='dotted',\r\n color='black')\r\n abcspace.quiver(0, 0, 0, 0, 0, 1, length=baselength,\r\n pivot=quiverpivot, arrow_length_ratio=0.025,\r\n linewidth=1, linestyle='dotted',\r\n color='black')\r\n abcspace.text(baselength/2, 0, 0, 'a', (0, 1, 0))\r\n abcspace.text(0, baselength/2, 0, 'b', (0, 1, 0))\r\n abcspace.text(0, 0, baselength/2, 'c', (0, 1, 0))\r\n\r\n##################################################\r\n# Plotting a b c in scalargraph + abcspace + timeslide\r\n##################################################\r\nmainsquiver = abcspace.quiver([0], [0], [0], dados[1, 100], dados[2, 100], dados[3, 100], arrow_length_ratio=0.1,\r\n color='black', label='mains')\r\n\r\naquiver = abcspace.quiver(0, 0, 0, 1, 0, 0, length=1,\r\n pivot='tail', arrow_length_ratio=0.2, color='red')\r\nbquiver = abcspace.quiver(0, 0, 0, 0, 1, 0, length=-0.5,\r\n pivot='tail', arrow_length_ratio=0.2, color='green')\r\ncquiver = abcspace.quiver(0, 0, 0, 0, 0, 1, length=-0.5,\r\n pivot='tail', arrow_length_ratio=0.2,\r\n color='blue')\r\n\r\ntimeslide, = abcscalars1.plot([0,0], [-2,2], color='brown', linestyle='dashed')\r\n\r\n##################################################\r\n# Plotting a b c path\r\n##################################################\r\n#pathquiver = abcspace.plot(dados[1, 0:10], dados[2, 0:10], dados[3, 0:10],\r\n# color='black', linestyle='dotted', linewidth=0.5)\r\npathquiver = abcspace.plot(dados[1,:], dados[2,:], dados[3,:],\r\n color='black', linestyle='dashed', linewidth=1)\r\n\r\n\r\n##################################################\r\n# Plotting a b c legends\r\n##################################################\r\nabcspace.legend()\r\nabcscalars1.legend()\r\n\r\nrotate3dspace = False\r\ncadaumporsi = 2\r\nshowmainsquiver = True\r\n\r\ndef update(i):\r\n global mainsquiver\r\n global timeslide\r\n global pathquiver\r\n global aquiver, bquiver, cquiver\r\n\r\n timeslide.remove()\r\n\r\n if showmainsquiver:\r\n mainsquiver.remove()\r\n mainsquiver = abcspace.quiver([0], [0], [0], dados[1, i], dados[2, i], dados[3, i], arrow_length_ratio=0.1,\r\n color='black')\r\n\r\n if cadaumporsi == 1:\r\n aquiver.remove()\r\n bquiver.remove()\r\n cquiver.remove()\r\n aquiver = abcspace.quiver(0, 0, 0, 1, 0, 0, length=dados[1, i],\r\n pivot='tail', arrow_length_ratio=0.2, color='red')\r\n bquiver = abcspace.quiver(0, 0, 0, 0, 1, 0, length=dados[2, i],\r\n pivot='tail', arrow_length_ratio=0.2, color='green')\r\n cquiver = abcspace.quiver(0, 0, 0, 0, 0, 1, length=dados[3, i],\r\n pivot='tail', arrow_length_ratio=0.2,\r\n color='blue')\r\n if cadaumporsi == 2:\r\n aquiver.remove()\r\n bquiver.remove()\r\n cquiver.remove()\r\n aquiver = abcspace.quiver(0, 0, 0, 1, 0, 0, length=dados[1, i],\r\n pivot='tail', arrow_length_ratio=0.2, color='red')\r\n bquiver = abcspace.quiver(dados[1, i], 0, 0, 0, 1, 0, length=dados[2, i],\r\n pivot='tail', arrow_length_ratio=0.2, color='green')\r\n cquiver = abcspace.quiver(dados[1, i], dados[2, i], 0, 0, 0, 1, length=dados[3, i],\r\n pivot='tail', arrow_length_ratio=0.2,\r\n color='blue')\r\n\r\n timeslide, = abcscalars1.plot([dados[0, i], dados[0, i]],\r\n [-2, 2],\r\n color='black', linestyle='dashed')\r\n #if i>2:\r\n # pathquiver = abcspace.plot(dados[1, 0:i], dados[2, 0:i], dados[3, 0:i],\r\n # color='black', linewidth=1)\r\n\r\n if rotate3dspace:\r\n deltaelevconstant = -45\r\n deltaelevdangle = -2*deltaelevconstant/180\r\n if i < 180:\r\n abcspace.view_init(azim=45, elev=deltaelevdangle * i + deltaelevconstant)\r\n else:\r\n abcspace.view_init(azim=45, elev=-deltaelevdangle * (i - 180) - deltaelevconstant)\r\n\r\nanimacao = FuncAnimation(fig, update, frames=len(dados[0]), interval=10)\r\nplt.show()","sub_path":"csv_one3phase.py","file_name":"csv_one3phase.py","file_ext":"py","file_size_in_byte":9640,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"575609837","text":"from random import randint\r\n\r\n\r\ndef is_prime(number):\r\n divider = 2\r\n prime = 'no'\r\n nummber_sqrt = number**0.5\r\n while divider <= nummber_sqrt and number % divider != 0:\r\n divider += 1\r\n if divider > nummber_sqrt:\r\n prime = 'yes'\r\n return prime\r\n\r\n\r\ndef recieve_data_for_round():\r\n number_to_check = randint(1, 100)\r\n prime = is_prime(number_to_check)\r\n return prime, number_to_check\r\n\r\n\r\nGREETING = '''Answer \"yes\" if given number is prime.\r\n \\rOtherwise answer \"no\".'''\r\n","sub_path":"brain_games/games/prime.py","file_name":"prime.py","file_ext":"py","file_size_in_byte":527,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"441185566","text":"#找出1~9999之间的所有完美数\n# 完美数是除自身外其他所有因子的和正好等于这个数本身的数\n# 例如: 6 = 1 + 2 + 3, 28 = 1 + 2 + 4 + 7 + 14\n\nimport math\n\nfor num in range(1,10000):\n result = 0\n for factor in range(1,int(math.sqrt(num))+1):\n if num % factor == 0:\n result += factor\n if factor > 1 and num // factor != factor:\n result += num // factor\n if result == num:\n print(num)","sub_path":"100Days/Day05/perfect.py","file_name":"perfect.py","file_ext":"py","file_size_in_byte":471,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"496830517","text":"# Copyright 2021 Huawei Technologies Co., Ltd\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n# ============================================================================\n\n\"\"\"post process for 310 inference\"\"\"\nimport os\nimport argparse\nimport pickle\nimport numpy as np\n\nparser = argparse.ArgumentParser(description=\"ecolite inference\")\nparser.add_argument(\"--result_path\", type=str, required=True, help=\"result files path.\")\nparser.add_argument(\"--label_path\", type=str, required=True, help=\"image file path.\")\nparser.add_argument('--batch_size', default=256, type=int,\n metavar='N', help='mini-batch size (default: 256)')\nargs = parser.parse_args()\nbatch_size = args.batch_size\nnum_classes = 101\n\n\ndef get_result(result_path, label_path):\n \"\"\"Get final accuracy result\"\"\"\n files = os.listdir(result_path)\n top1 = 0\n top5 = 0\n total_data = batch_size * len(files)\n for i in range(len(files)):\n video_label_id = i\n file = 'eval_predict_' + str(video_label_id) + '_.bin'\n data_path = os.path.join(result_path, file)\n result = np.fromfile(data_path, dtype=np.float32).reshape(batch_size, num_classes)\n predict = np.argsort(result, axis=-1)[:, -5:]\n\n label_file_path = label_path + 'eval_label_'\n label_file_path += str(video_label_id)\n label_file_path += '.pkl'\n pkllabelfile = open(label_file_path, 'rb')\n label = pickle.load(pkllabelfile)\n for batch in range(batch_size):\n if predict[batch][-1] == label[batch]:\n top1 += 1\n top5 += 1\n elif label[batch] in predict[batch][-5:]:\n top5 += 1\n print(f\"Total data: {total_data}, top1 accuracy: {top1 / total_data}, top5 accuracy: {top5 / total_data}.\")\n\n\nif __name__ == '__main__':\n get_result(args.result_path, args.label_path)\n","sub_path":"research/cv/ecolite/postprocess.py","file_name":"postprocess.py","file_ext":"py","file_size_in_byte":2354,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"191353790","text":"# coding=UTF-8\nimport requests\nfrom prices_us import PricesUS\nfrom prices_eu import PricesEU\nfrom geopy.geocoders import Nominatim\n\n\nclass GeoData:\n def __init__(self, address):\n self.address = address\n geolocator = Nominatim()\n location = geolocator.geocode(address)\n self.lat = location.latitude\n self.lon = location.longitude\n\n payload = {'key': '6TMPLBB3OFXI', 'format': 'json', 'by': 'position', 'lat': self.lat, 'lng': self.lon}\n self._country_detail = requests.get('http://api.timezonedb.com/v2/get-time-zone', params=payload).json()\n\n self.set_timezone()\n self.set_price()\n\n @property\n def country_name(self):\n return self._country_detail['countryName']\n\n @property\n def country_code(self):\n return self._country_detail['countryCode']\n\n\n def set_timezone(self):\n self.timezone_name = self._country_detail['abbreviation']\n self.timezone_time = self._country_detail['formatted']\n self.timezone_region = self._country_detail['zoneName']\n self.timezone_gmt_offset = self._country_detail['gmtOffset']\n\n\n def set_price(self):\n # responsible for determining the price per kwh of electricity in the country that the given address is within\n if self.country_code == 'GB':\n self.price = 0.12\n self.currency = \"£\"\n elif self.country_code == 'US':\n self.price = PricesUS.get_latest_elec_cost(self.lat, self.lon)\n self.currency = PricesUS.currency_str\n else:\n self.price = PricesEU.get_latest_elec_cost(self.country_code)\n self.currency = PricesEU.currency_str\n","sub_path":"geo_calc/geo_data.py","file_name":"geo_data.py","file_ext":"py","file_size_in_byte":1677,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"102406868","text":"from copy import copy\nimport numpy as np\nimport re\n\n# ======================\n# Padding Utils\n# ======================\n\ndef padd_nested(vecs, end_char, pad_char):\n _vecs = copy(vecs)\n max_ls = np.max([[len(v) for v in vec] for vec in _vecs], axis=0)\n for i in range(len(_vecs)):\n _vecs[i] = [padd_vec(vec, end_char, pad_char, l) for l, vec in zip(max_ls, _vecs[i])]\n return _vecs\n\ndef padd_vecs(vecs, end_char, pad_char, max_l=None):\n _vecs = copy(vecs)\n if max_l == None:\n max_l = max([len(v) for v in vecs])\n for i in range(len(_vecs)):\n _vecs[i] = padd_vec(_vecs[i], end_char, pad_char, max_l)\n return _vecs\n\ndef padd_vec(vec, end_char, pad_char, l):\n _vec = copy(vec)\n if not end_char is None:\n _vec.append(end_char)\n while True:\n if len(_vec) == l + 1:\n break\n _vec.append(pad_char)\n return _vec\n\n# ======================\n# Vector Utils\n# ======================\n\ndef flatten(l):\n seed = copy(l)\n while True:\n new = []\n for s in seed:\n if hasattr(s, '__iter__') and not type(s) is str:\n for x in s:\n new.append(x)\n else:\n new.append(s)\n seed = copy(new)\n if all([not hasattr(s, '__iter__') or type(s) is str for s in seed]):\n break\n return seed\n\ndef choose(total_size, group_sizes: list, rel_sizes=False, add_fill_group=False, random_seed=None):\n \"\"\"Method to choose indecis from a list of length total_size.\n ARGS:\n - total size (int): length of the list\n - group_sizes (list): sizes of the different groups we want to choose\n - rel_sizes (bool): group sizes are in relative units. default=False\n - add_fill_group (bool): weather to add an extra group with the rest of the indicis. default=False\n - random_seed (int): (optional) set random seed. default=None\n RETURNS:\n list of lists of indicis for the different groups\"\"\"\n if not random_seed is None:\n np.random.seed(random_seed)\n if rel_sizes:\n group_sizes = [int(np.floor(size * total_size)) for size in group_sizes]\n chosen_idxs = set()\n final_idxs = []\n for size in group_sizes:\n idxs = []\n while True:\n idx = np.random.randint(0, total_size - 1)\n if not idx in chosen_idxs:\n idxs.append(idx)\n chosen_idxs.add(idx)\n if len(idxs) == size:\n break\n final_idxs.append(idxs)\n if add_fill_group:\n idxs = [i for i in range(total_size) if not i in chosen_idxs]\n final_idxs.append(idxs)\n return final_idxs\n\n# ======================\n# Text Utils\n# ======================\n\ndef split_text(string, sep):\n if sep == 'chars':\n return [s for s in string]\n elif sep == 'words':\n return string.split()\n elif sep == None:\n return string\n else:\n return re.split(sep, string)\n\n# =======================\n# Normalization Utils\n# =======================\n\ndef unit_normalization(vecs: np.array, axis=None, batch_size=128):\n min_v = np.min(vecs, axis=axis)\n max_v = np.max(np.abs(vecs), axis=axis)\n return costume_linear_transform(vecs, 1 / max_v, - min_v / max_v + 1e-6, batch_size), (min_v, max_v)\n\ndef inverse_unit_normalization(vecs, min_v, max_v, batch_size=128):\n raise costume_linear_transform(vecs, max_v, min_v)\n\ndef zscore_normalization(vecs, axis=None, batch_size=128, return_params=True):\n mean = np.mean(vecs, axis=axis)\n std = np.std(vecs, axis=axis)\n if return_params:\n return costume_linear_transform(vecs, 1 / std, - mean / std, batch_size), (mean, std)\n else:\n return costume_linear_transform(vecs, 1 / std, - mean / std, batch_size)\n\ndef inverse_zscore_normalization(vecs, mean, std, batch_size=128):\n return costume_linear_transform(vecs, std, mean, batch_size)\n\ndef positive_zscore_normalization(vecs, axis=None, batch_size=128):\n vecs = zscore_normalization(vecs, axis, batch_size)\n min_v = np.min(vecs, axis=axis)\n return np.minimum(costume_linear_transform(vecs, 1, min_v, batch_size), 1e-12)\n\ndef costume_linear_transform(vecs, a, b, batch_size=128):\n '''function to apply a linear transformation in batches'''\n vecs = np.array(vecs, dtype=np.float32)\n batch_num = int(np.floor(len(vecs) / batch_size))\n # transforming vecs in batches\n for batch in range(batch_num):\n vecs[(batch * batch_size):((batch + 1) * batch_size)] = a * vecs[(batch * batch_size):((batch + 1) * batch_size)] + b\n # transforming last batch\n vecs[(batch_num * batch_size):] = a * vecs[(batch_num * batch_size):] + b\n return vecs\n\n\n","sub_path":"Data/commons.py","file_name":"commons.py","file_ext":"py","file_size_in_byte":4705,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"323384936","text":"# from elasticsearch_dsl import analyzer\nfrom django_elasticsearch_dsl.documents import DocType\nfrom django_elasticsearch_dsl import fields\nfrom django_elasticsearch_dsl import Index\n\nfrom .models.notes import NoteInfo\n\n# define index\nnotes = Index('notes')\n\n\n@notes.doc_type\nclass NoteDocument(DocType):\n \"\"\"\n This method defines a document for note search\n and models and fields given to that document\n \"\"\"\n # class Index:\n # name = 'notes'\n # settings = {\n # 'number_of_shards': 1,\n # 'number_of_replicas': 0\n # }\n # user = fields.ObjectField(properties={\n # 'name': fields.IntegerField()\n # })\n class Django:\n model = NoteInfo\n fields = [\n 'id',\n 'title',\n 'content',\n 'created_at',\n 'image',\n 'url',\n # 'user',\n # 'labels',\n # 'collaborator',\n 'is_pin',\n 'is_archive',\n 'is_trash'\n ]\n\n\n\n\n\n\n#\n# notes_index = Index('notes')\n# notes_index.settings(\n# number_of_shards=1,\n# number_of_replicas=0\n# )\n#\n# html_strip = analyzer(\n# 'html_strip',\n# tokenizer=\"standard\",\n# filter=[\"standard\", \"lowercase\", \"stop\", \"snowball\"],\n# char_filter=[\"html_strip\"]\n# )\n#\n#\n# @notes_index.doc_type\n# class NoteDocument(DocType):\n#\n# id = fields.IntegerField(attr='id')\n# title = fields.StringField(\n# analyzer='html_strip',\n# fields={\n# 'raw': fields.StringField(analyzer='keyword'),\n# }\n# )\n# content = fields.StringField(\n# analyzer='html_strip',\n# fields={\n# 'raw': fields.StringField(analyzer='keyword'),\n# }\n# )\n#\n# class Django:\n# model = Notes\n","sub_path":"notes/documents.py","file_name":"documents.py","file_ext":"py","file_size_in_byte":1793,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"473970139","text":"import json\nimport mock\n\nfrom django.test import TestCase\n\nfrom billing_proxy.api.middleware.bssapi_middleware import \\\n AdminAuthenticationMiddleware\n\nfrom billing_proxy.client import cloud_guard_client\nfrom billing_proxy.client import common_req_client\nfrom billing_proxy import models\n\nfrom django.conf import settings\n\n\nclass ResourceStatisticTestcase(TestCase):\n def setUp(self):\n super(ResourceStatisticTestcase, self).setUp()\n self.httpclient = common_req_client.construct_http_client(\n username=settings.BILLING_PROXY_USER,\n password=settings.BILLING_PROXY_PASSWORD,\n tenant_name=settings.BILLING_PROXY_TENANT,\n auth_url=settings.IDENTITY_URI + 'v2.0')\n self.cg_client = cloud_guard_client.Client(\n username=settings.BILLING_PROXY_USER,\n password=settings.BILLING_PROXY_PASSWORD,\n tenant_name=settings.BILLING_PROXY_TENANT,\n auth_url=settings.IDENTITY_URI + 'v2.0')\n\n def test_client_authenticate(self):\n self.assertEqual(\"keystone\", self.httpclient.auth_strategy)\n self.httpclient.authenticate_and_fetch_endpoint_url()\n auth_info = self.httpclient.get_auth_info()\n self.assertIn(\"auth_token\", auth_info)\n self.assertIn(\"auth_tenant_id\", auth_info)\n self.assertIn(\"auth_user_id\", auth_info)\n self.assertIn(\"endpoint_url\", auth_info)\n\n def test_client_get_antiddos_data(self):\n AdminAuthenticationMiddleware.process_request = mock.Mock()\n\n models.get_order_by_resource_id = mock.Mock(\n return_value=\"a4cc02f6-bb23-4aac-be47-96d9133edb9f\")\n body = {\n \"startTime\": \"2017-02-01\",\n \"endTime\": \"2017-02-11\",\n \"usage\": [\n {\"resourceType\": \"Anti-DDoS\",\n \"resourceId\": \"ac5bf3d3-421c-4e89-b161-4c5f2bdb1f05\"}\n ]\n }\n body = json.dumps(body)\n resp = self.client.post('/bss_api/ResourceUsage', data=body,\n content_type=\"json\")\n self.assertIn(\"data\", resp)\n self.assertIn(\"bill\", resp[\"data\"])\n self.assertIn(\"DomainNameCount\", resp[\"data\"][\"bill\"])\n self.assertIn(\"NormalFixedBandwidth\", resp[\"data\"][\"bill\"])\n self.assertIn(\"CCPeakRequest\", resp[\"data\"][\"bill\"])\n self.assertIn(\"DDosPeakFlow\", resp[\"data\"][\"bill\"])\n","sub_path":"billing_proxy/tests/units/test_cloudguard_interface.py","file_name":"test_cloudguard_interface.py","file_ext":"py","file_size_in_byte":2384,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"423106259","text":"import matplotlib.pyplot as plt\nimport socket\n\nimport h5_storage\nimport analysis\n\nplt.close('all')\n\nhostname = socket.gethostname()\nif 'psi' in hostname or 'lc6a' in hostname or 'lc7a' in hostname:\n default_dir = '/sf/data/measurements/2021/04/25/'\n archiver_dir = '/afs/psi.ch/intranet/SF/Beamdynamics/Philipp/data/archiver_api_data/'\nelif hostname == 'desktop':\n default_dir = '/storage/data_2021-04-25/'\n archiver_dir = '/storage/Philipp_data_folder/archiver_api_data/'\nelif hostname == 'pubuntu':\n default_dir = '/home/work/data_2021-04-25/'\n archiver_dir = '/home/work/archiver_api_data/'\n\nstreaker_calib_file = default_dir + '2021_04_25-16_55_25_Calibration_SARUN18-UDCP020.h5'\ndata_dict = h5_storage.loadH5Recursive(streaker_calib_file)\nanalysis.analyze_streaker_calibration(data_dict['raw_data'])\n\n\n\nplt.show()\n","sub_path":"050_improve_offset_scan.py","file_name":"050_improve_offset_scan.py","file_ext":"py","file_size_in_byte":837,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"246823459","text":"#!/usr/bin/env python3\r\n# -*- coding: utf-8 -*-\r\n\r\nfrom random import getrandbits\r\nfrom base64 import urlsafe_b64encode\r\nfrom datetime import date, datetime, timedelta\r\n\r\nimport psycopg2\r\nfrom psycopg2.extras import DictCursor\r\n\r\nimport pygments\r\nfrom pygments import highlight\r\nfrom pygments.lexers import get_lexer_by_name, guess_lexer, get_all_lexers\r\nfrom pygments.formatters import HtmlFormatter\r\n\r\nfrom flask import Flask, \\\r\n\t\trender_template, url_for, flash, \\\r\n\t\trequest, redirect, Response, abort\r\n\r\nfrom stats import pasteview, pastecount, getstats\r\nimport config\r\n\r\napp = Flask(__name__)\r\napp.secret_key = config.secret_key\r\napp.config['MAX_CONTENT_LENGTH'] = config.max_content_length\r\n\r\n\r\nlexers_all = get_all_lexers()\r\nyear = date.today().year\r\n\r\n\r\n\r\ndef base_encode(num):\r\n\tif not num:\r\n\t\treturn config.url_alph[0]\r\n\tresult = ''\r\n\twhile num:\r\n\t\tnum, rem = divmod(num, config.base)\r\n\t\tresult = result.join(config.url_alph[rem])\r\n\treturn result\r\n\r\ndef plain(text):\r\n\tresp = Response(text)\r\n\tresp.headers['Content-Type'] = 'text/plain; charset=utf-8'\r\n\treturn resp\r\n\r\ndef paste_stats(text):\r\n\tstats = {}\r\n\tstats['lines'] = len(text.split('\\n'))\r\n\tstats['sloc'] = stats['lines'] - len(text.split('\\n\\n'))\r\n\tstats['size'] = len(text.encode('utf-8'))\r\n\treturn stats\r\n\r\ndef url_collision(db, route):\r\n\tfor rule in app.url_map.iter_rules():\r\n\t\tif rule.rule == '/' + route:\r\n\t\t\treturn True\r\n\twith db.cursor() as cur: \r\n\t\tcur.execute(\"SELECT pasteid FROM pastes WHERE pasteid = %s;\", (route,))\r\n\t\tif cur.fetchone():\r\n\t\t\treturn True\r\n\treturn False\r\n\r\ndef db_newpaste(db, opt, stats):\r\n\tdate = datetime.utcnow()\r\n\tdate += timedelta(hours=float(opt['ttl']))\r\n\twith db.cursor() as cur:\r\n\t\tcur.execute(\"\"\"INSERT INTO \r\n\t\t\tpastes (pasteid, token, lexer, expiration, burn, \r\n\t\t\tpaste, size, lines, sloc)\r\n\t\t\tVALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s);\"\"\", \\\r\n\t\t\t(opt['pasteid'], opt['token'], opt['lexer'], \\\r\n\t\t\tdate, opt['burn'], opt['paste'], \\\r\n\t\t\tstats['size'], stats['lines'], stats['sloc']))\r\n\r\ndef db_getpaste(db, pasteid):\r\n\twith db.cursor(cursor_factory = DictCursor) as cur:\r\n\t\tcur.execute((\"\"\"SELECT * FROM pastes WHERE pasteid=%s;\"\"\"), (pasteid,))\r\n\t\tr = cur.fetchone()\r\n\treturn r\r\n\r\n\r\ndef db_deletepaste(db, pasteid):\r\n\twith db.cursor() as cur:\r\n\t\tcur.execute((\"\"\"DELETE FROM pastes WHERE pasteid=%s;\"\"\"), (pasteid,))\r\n\r\ndef db_burn(db, pasteid):\r\n\twith db.cursor() as cur:\r\n\t\tcur.execute((\"\"\"UPDATE pastes SET burn = burn - 1 WHERE pasteid=%s;\"\"\"), (pasteid,))\r\n\r\n@app.route('/', methods=['GET', 'POST'])\r\n@app.route('/newpaste', methods=['POST']) #only used via html form\r\ndef newpaste():\r\n\tif request.method == 'POST':\r\n\t\tpaste_opt = {}\r\n\t\tfor param in config.defaults: #init form parameters with defaults\r\n\t\t\t\tpaste_opt[param] = config.defaults[param]\r\n\t\tfor param in request.form:\r\n\t\t\tif param in paste_opt:\r\n\t\t\t\tpaste_opt[param] = request.form[param]\r\n\t\tif paste_opt['paste'] == '':\r\n\t\t\treturn config.empty_paste\r\n\t\ttry:\r\n\t\t\tif not config.paste_limits['ttl_min'] < \\\r\n\t\t\t\t\t\tfloat(paste_opt['ttl']) < \\\r\n\t\t\t\t\t\tconfig.paste_limits['ttl_max']:\r\n\t\t\t\treturn config.invalid_ttl\r\n\t\texcept ValueError:\r\n\t\t\treturn config.invalid_ttl\r\n\t\ttry:\r\n\t\t\tif paste_opt['lexer'] == 'auto':\r\n\t\t\t\tpaste_opt['lexer'] = guess_lexer(paste_opt['paste']).aliases[0]\r\n\t\texcept pygments.util.ClassNotFound:\r\n\t\t\tpaste_opt['lexer'] = 'text'\r\n\t\ttry:\r\n\t\t\tif paste_opt['burn'] == '' or paste_opt['burn'] == 0 or paste_opt['burn'] == config.defaults['burn']:\r\n\t\t\t\tpaste_opt['burn'] = config.defaults['burn']\r\n\t\t\telif not config.paste_limits['burn_min'] <= int(paste_opt['burn']) <= config.paste_limits['burn_max']:\r\n\t\t\t\treturn config.invalid_burn\r\n\t\texcept ValueError:\r\n\t\t\treturn config.invalid_burn\r\n\r\n\t\twith psycopg2.connect(config.dsn) as db:\r\n\t\t\turl_len = config.url_len\r\n\t\t\tpaste_opt['pasteid'] = ''\r\n\t\t\twhile url_collision(db, paste_opt['pasteid']):\r\n\t\t\t\tfor i in range(url_len):\r\n\t\t\t\t\tpaste_opt['pasteid'] += base_encode(getrandbits(6))\t\r\n\t\t\t\turl_len += 1\r\n\t\t\t\r\n\t\t\tpaste_opt['token'] = \\\r\n\t\t\t\turlsafe_b64encode(getrandbits(48).to_bytes(config.token_len, 'little')).decode('utf-8')\r\n\t\t\t\r\n\t\t\tstats = paste_stats(paste_opt['paste']) #generate text stats\r\n\t\t\t\r\n\t\t\tdb_newpaste(db, paste_opt, stats)\r\n\t\t\t\r\n\t\t\tpastecount(db) #increment total pastes\r\n\r\n\t\t\tif request.path != '/newpaste': #plaintext reply \r\n\t\t\t\treturn \"token: \" + paste_opt['token'] + \" | \" + config.domain + url_for('viewraw', pasteid = paste_opt['pasteid']) + \"\\n\"\r\n\t\t\t\r\n\t\t\tflash(paste_opt['token'])\r\n\t\treturn redirect(paste_opt['pasteid'])\r\n\telif request.method == 'GET':\r\n\t\treturn render_template('newpaste.html', \\\r\n\t\t\t\tlexers_all = lexers_all, lexers_common = config.lexers_common, \\\r\n\t\t\t\tttl = config.ttl_options, paste_limits = config.paste_limits, year = year)\r\n\telse:\r\n\t\tabort(405)\r\n\r\n\r\n@app.route('/', methods=['GET', 'DELETE'])\r\ndef viewpaste(pasteid):\r\n\tif request.method == 'GET':\r\n\t\tdirection = 'ltr'\r\n\t\twith psycopg2.connect(config.dsn) as db:\r\n\t\t\tresult = db_getpaste(db, pasteid)\r\n\t\t\tif not result:\r\n\t\t\t\tabort(404)\r\n\t\t\tif result['burn'] == 0 or result['expiration'] < datetime.utcnow():\r\n\t\t\t\tdb_deletepaste(db, pasteid)\r\n\t\t\t\tabort(404)\r\n\t\t\telif result['burn'] > 0:\r\n\t\t\t\tdb_burn(db, pasteid)\r\n\t\t\t\r\n\t\t\tpasteview(db) #count towards total paste views\r\n\r\n\t\t\tif request.args.get('raw') is not None:\r\n\t\t\t\treturn plain(result['paste'])\r\n\t\t\t\r\n\t\t\tif request.args.get('d') is not None:\r\n\t\t\t\tdirection = 'rtl'\r\n\t\t\t\r\n\t\t\tlexer = get_lexer_by_name(result['lexer'])\r\n\t\t\tformatter = HtmlFormatter(nowrap=True, cssclass='paste')\r\n\t\t\tpaste = highlight(result['paste'], lexer, formatter)\r\n\r\n\t\t\tstats = {'lines': result['lines'],\r\n\t\t\t\t\t'sloc': result['sloc'],\r\n\t\t\t\t\t'size': result['size'],\r\n\t\t\t\t\t'lexer': lexer.name\r\n\t\t\t}\r\n\t\t\tdel_url = url_for('deletepaste', pasteid=pasteid, token=result['token'])\r\n\t\t\treturn render_template('viewpaste.html', \\\r\n\t\t\t\tstats=stats, paste=paste.split(\"\\n\"), direction=direction, delete=del_url, year=year)\r\n\t\tabort(500)\r\n\telif request.method == 'DELETE':\r\n\t\twith psycopg2.connect(config.dsn) as db:\r\n\t\t\tresult = db_getpaste(db, pasteid)\r\n\t\t\tif not result:\r\n\t\t\t\treturn config.msg_err_404, 404\r\n\t\t\telif 'token' in request.form and result['token'] == request.form['token']:\r\n\t\t\t\tdb_deletepaste(db, pasteid)\r\n\t\t\t\treturn config.msg_paste_deleted, 200\r\n\t\t\telif 'token' in request.headers and result['token'] == request.headers.get('token'):\r\n\t\t\t\tdb_deletepaste(db, pasteid)\r\n\t\t\t\treturn config.msg_paste_deleted, 200\r\n\t\t\telse:\r\n\t\t\t\treturn config.msg_err_401, 401\t\r\n\telse:\r\n\t\tabort(405)\r\n\r\n@app.route('/plain/', methods=['GET', 'DELETE'])\r\n@app.route('/raw/', methods=['GET', 'DELETE'])\r\ndef viewraw(pasteid):\r\n\tif request.method == 'GET':\r\n\t\twith psycopg2.connect(config.dsn) as db:\r\n\t\t\tresult = db_getpaste(db, pasteid)\r\n\t\t\tif not result:\r\n\t\t\t\treturn config.msg_err_404, 404\r\n\t\t\tif result['burn'] == 0 or result['expiration'] < datetime.utcnow():\r\n\t\t\t\tdb_deletepaste(db, pasteid)\r\n\t\t\t\treturn config.msg_err_404, 404\r\n\t\t\telif result['burn'] > 0:\r\n\t\t\t\tdb_burn(db, pasteid)\r\n\t\r\n\t\t\tpasteview(db) #count towards total paste views\r\n\t\t\t\r\n\t\t\treturn result['paste']\r\n\r\n\telif request.method == 'DELETE':\r\n\t\twith psycopg2.connect(config.dsn) as db:\r\n\t\t\tresult = db_getpaste(db, pasteid)\r\n\t\t\tif not result:\r\n\t\t\t\treturn config.msg_err_404, 404\r\n\t\t\telif 'token' in request.form and result['token'] == request.form['token']:\r\n\t\t\t\tdb_deletepaste(db, pasteid)\r\n\t\t\t\treturn config.msg_paste_deleted, 200\r\n\t\t\telif 'token' in request.headers and result['token'] == request.headers.get('token'):\r\n\t\t\t\tdb_deletepaste(db, pasteid)\r\n\t\t\t\treturn config.msg_paste_deleted, 200\r\n\t\t\telse:\r\n\t\t\t\treturn config.msg_err_401, 401\r\n\telse:\r\n\t\treturn \"invalid http method\\n\"\r\n\r\n@app.route('//', methods=['GET'])\r\ndef\tdeletepaste(pasteid, token):\r\n\twith psycopg2.connect(config.dsn) as db:\r\n\t\tresult = db_getpaste(db, pasteid)\r\n\t\tif not result:\r\n\t\t\tabort(404)\r\n\t\telif result['token'] == token:\r\n\t\t db_deletepaste(db, pasteid)\r\n\t\t return render_template('deleted.html')\r\n\t\telse:\r\n\t\t\tabort(401)\r\n\t\t\t\r\n@app.route('/about/api')\r\ndef aboutapi():\r\n\treturn render_template('api.html', year=year)\r\n\r\n@app.route('/about')\r\ndef aboutpage():\r\n\treturn render_template('about.html', year=year)\r\n\r\n@app.route('/stats')\r\ndef statspage():\r\n\twith psycopg2.connect(config.dsn) as db:\r\n\t\tstats = getstats(db)\r\n\t\treturn render_template('stats.html', year=year, stats = stats)\r\n\r\n\r\n@app.errorhandler(404)\r\ndef page_not_found(e):\r\n\treturn render_template('404.html'), 404\r\n\r\n@app.errorhandler(500)\r\ndef internal_server_error():\r\n\treturn render_template('500.html'), 500\r\n\r\nif __name__ == '__main__':\r\n\tapp.debug = False\r\n\tapp.run()\r\n","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":8592,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"150995686","text":"import detectron2\nfrom detectron2 import model_zoo\nfrom detectron2.config import get_cfg\n\ndef get_default_cfg(model_id: str = \"COCO-Detection/faster_rcnn_R_101_FPN_3x.yaml\"):\n cfg = get_cfg()\n cfg.merge_from_file(model_zoo.get_config_file(model_id))\n cfg.MODEL.MODEL_ID = model_id\n cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5 # set threshold for this model\n cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url(model_id)\n \n return cfg\n","sub_path":"srl_handler/utils/cfg.py","file_name":"cfg.py","file_ext":"py","file_size_in_byte":453,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"344263715","text":"#!/usr/bin/env python\nimport tornado.httpserver\nimport tornado.ioloop\nimport tornado.web\nimport tornado.auth\nimport tornado.httpclient\nimport auth9\nimport json\n\n# this base handler defines how you get your user info, cookie or session\nclass BaseHandler(tornado.web.RequestHandler):\n def get_current_user(self):\n user = self.get_secure_cookie(\"user\")\n if user:\n return json.loads(user)\n return None\n\n# this handler handles login and saves user info\nclass LoginHandler(auth9.LoginHandler):\n def on_login(self, user, redirect_url):\n if not user:\n raise tornado.web.HTTPError(500, \"net9 auth failed\")\n self.set_secure_cookie(\"user\", json.dumps(user))\n self.redirect(redirect_url)\n\n# normal handler\nclass MainHandler(BaseHandler):\n @tornado.web.authenticated\n def get(self):\n self.write(\"Hello\" + json.dumps(self.current_user))\n\nsettings = {\n \"cookie_secret\": \"just a test\",\n \"login_url\": \"/login\",\n \"client_id\": \"WlNIuDqhEIKIxEZd-Rjj8QycscQ\",\n \"client_secret\": \"asd\"\n}\n\napplication = tornado.web.Application([\n (r\"/\", MainHandler),\n (r\"/login\", LoginHandler)\n], **settings)\n\nif __name__ == \"__main__\":\n http_server = tornado.httpserver.HTTPServer(application)\n http_server.listen(8888)\n tornado.ioloop.IOLoop.instance().start()\n\n","sub_path":"server.py","file_name":"server.py","file_ext":"py","file_size_in_byte":1351,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"57"} +{"seq_id":"505965872","text":"\"\"\"\nshow system internal processes memory\n\"\"\"\n\n# Python\nimport re\n\n# Metaparser\nfrom genie.metaparser import MetaParser\nfrom genie.metaparser.util.schemaengine import (Schema, Any, Optional,\n Or, And, Default, Use)\n# Parser Utils\nfrom genie.libs.parser.utils.common import Common\n\n\nclass ShowSystemInternalProcessesMemorySchema(MetaParser):\n \"\"\"\n Schema for show system internal processes memory\n \"\"\"\n\n schema = {\n 'pid':\n {\n Any():\n {\n 'stat': str,\n 'time': str,\n 'majflt': int,\n 'trs': int,\n 'rss': int,\n 'vsz': int,\n 'mem_percent': float,\n 'command': str,\n 'tty': str\n }\n }\n }\n\n\nclass ShowSystemInternalProcessesMemory(ShowSystemInternalProcessesMemorySchema):\n \"\"\"\n Parser for show system internal processes memory\n \"\"\"\n cli_command = \"show system internal processes memory\"\n\n def cli(self, output=None):\n if not output:\n out = self.device.execute(self.cli_command)\n else:\n out = output\n\n # 7482 ? Ssl 00:05:05 158 0 219576 1053628 3.7 /opt/mtx/bin/grpc -i 2626 -I\n # 27344 pts/0 Sl+ 00:00:20 0 63 117180 709928 1.9 /isan/bin/vsh.bin\n p1 = re.compile(\n r'^(?P\\d+)\\s+(?P\\S+)\\s+(?P\\S+)\\s+(?P