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

a12f73648f46854614cd7f814a32252da0ca2ac6

ae6f85863eb6ebecca2950b4fbff394a4edcfca6

/chataggregator.py

79fa3b314e31448072f444fc877169aab9c6829d

[ "MIT" ]

permissive

m-henderson/ChatAggregator

79ee32ae7a851b0ae5136184d55f5ea596eaab85

2692e9e5dfd5d78bbf5d658731b57630099ec3e4

refs/heads/master

2020-09-12T04:13:47.784589

2019-11-17T19:20:39

null

0

null

UTF-8

Python

false

132

py

import tklib import tkinter as tk root = tk.Tk() root.title("Chatbox") gui = tklib.main.MainWindow(root) gui.grid() root.mainloop()

[ "Dogeek@users.noreply.github.com" ]

Dogeek@users.noreply.github.com

0b9f8c69a516049fee15317748749ab9d00bb152

e17966d3831e9f99527fb44c50c77c90e08694de

/cmasher/colormaps/cosmic/cosmic.py

22748307b61c1a4f48607bd8bc7069e7557c2c79

[ "BSD-3-Clause" ]

permissive

ajdittmann/CMasher

85e4f94e45f962c247d2f8e04a1e966b01b77248

1ad6a5eaa3b473ef5eb3d56dfd3ecb8e887f16cd

refs/heads/master

2023-03-27T12:46:30.052679

2021-03-22T23:56:47

277,986,917

0

BSD-3-Clause

2020-07-08T04:10:55

2020-07-08T04:10:54

null

UTF-8

Python

false

13,150

py

# %% IMPORTS # Package imports from matplotlib.cm import register_cmap from matplotlib.colors import ListedColormap # All declaration __all__ = ['cmap'] # Author declaration __author__ = "Ellert van der Velden (@1313e)" # Package declaration __package__ = 'cmasher' # %% GLOBALS AND DEFINITIONS # Type of this colormap cm_type = 'sequential' # RGB-values of this colormap cm_data = [[0.00000000, 0.00000000, 0.00000000], [0.00022254, 0.00017671, 0.00025009], [0.00078387, 0.00060500, 0.00090179], [0.00164763, 0.00123817, 0.00193717], [0.00280144, 0.00205342, 0.00336061], [0.00423939, 0.00303533, 0.00518202], [0.00595880, 0.00417200, 0.00741444], [0.00795875, 0.00545370, 0.01007259], [0.01023937, 0.00687218, 0.01317220], [0.01280170, 0.00842008, 0.01673051], [0.01564747, 0.01009067, 0.02076595], [0.01877857, 0.01187795, 0.02529699], [0.02219739, 0.01377623, 0.03034346], [0.02590682, 0.01577996, 0.03592673], [0.02990978, 0.01788399, 0.04202298], [0.03420930, 0.02008340, 0.04820472], [0.03880874, 0.02237336, 0.05439934], [0.04358445, 0.02474908, 0.06061196], [0.04832042, 0.02720564, 0.06684805], [0.05302794, 0.02973858, 0.07311083], [0.05771012, 0.03234333, 0.07940403], [0.06236976, 0.03501524, 0.08573111], [0.06700933, 0.03774971, 0.09209532], [0.07163105, 0.04054044, 0.09849968], [0.07623693, 0.04327934, 0.10494709], [0.08082877, 0.04595941, 0.11144026], [0.08540827, 0.04858162, 0.11798198], [0.08997690, 0.05114686, 0.12457468], [0.09453596, 0.05365588, 0.13122062], [0.09908671, 0.05610920, 0.13792216], [0.10363029, 0.05850720, 0.14468161], [0.10816775, 0.06085010, 0.15150121], [0.11270017, 0.06313785, 0.15838356], [0.11722839, 0.06537049, 0.16533065], [0.12175321, 0.06754789, 0.17234460], [0.12627538, 0.06966979, 0.17942753], [0.13079560, 0.07173582, 0.18658154], [0.13531450, 0.07374552, 0.19380872], [0.13983264, 0.07569829, 0.20111112], [0.14435069, 0.07759327, 0.20849123], [0.14886940, 0.07942918, 0.21595220], [0.15338885, 0.08120569, 0.22349476], [0.15790940, 0.08292181, 0.23112093], [0.16243170, 0.08457592, 0.23883387], [0.16695619, 0.08616646, 0.24663627], [0.17148270, 0.08769287, 0.25452854], [0.17601191, 0.08915275, 0.26251464], [0.18054395, 0.09054460, 0.27059648], [0.18507865, 0.09186716, 0.27877510], [0.18961684, 0.09311710, 0.28705556], [0.19415775, 0.09429396, 0.29543682], [0.19870231, 0.09539359, 0.30392490], [0.20324973, 0.09641511, 0.31251899], [0.20780042, 0.09735485, 0.32122351], [0.21235420, 0.09821004, 0.33004063], [0.21691053, 0.09897843, 0.33897132], [0.22146970, 0.09965550, 0.34802028], [0.22603124, 0.10023806, 0.35718935], [0.23059455, 0.10072284, 0.36648009], [0.23515923, 0.10110562, 0.37589528], [0.23972479, 0.10138193, 0.38543762], [0.24429061, 0.10154697, 0.39510979], [0.24885596, 0.10159568, 0.40491433], [0.25341998, 0.10152262, 0.41485371], [0.25798164, 0.10132206, 0.42493024], [0.26253975, 0.10098790, 0.43514603], [0.26709296, 0.10051368, 0.44550301], [0.27163969, 0.09989258, 0.45600280], [0.27617812, 0.09911739, 0.46664673], [0.28070701, 0.09817741, 0.47743992], [0.28522342, 0.09706670, 0.48837993], [0.28972520, 0.09577455, 0.49946960], [0.29420947, 0.09429133, 0.51070913], [0.29867327, 0.09260527, 0.52210001], [0.30311267, 0.09070667, 0.53363982], [0.30752387, 0.08858214, 0.54532909], [0.31190255, 0.08621737, 0.55716750], [0.31624329, 0.08360013, 0.56915082], [0.32054033, 0.08071586, 0.58127560], [0.32478720, 0.07754942, 0.59353712], [0.32897683, 0.07408316, 0.60593109], [0.33310058, 0.07030445, 0.61844686], [0.33714920, 0.06619871, 0.63107428], [0.34111255, 0.06174960, 0.64380328], [0.34497874, 0.05694953, 0.65661652], [0.34873478, 0.05179404, 0.66949545], [0.35236629, 0.04628711, 0.68241857], [0.35585736, 0.04044955, 0.69535960], [0.35919048, 0.03450248, 0.70828712], [0.36234671, 0.02894281, 0.72116432], [0.36530584, 0.02392884, 0.73395112], [0.36804648, 0.01964477, 0.74659946], [0.37054659, 0.01629018, 0.75905887], [0.37278395, 0.01408742, 0.77127140], [0.37473691, 0.01326930, 0.78317727], [0.37638521, 0.01407636, 0.79471435], [0.37771093, 0.01674823, 0.80582046], [0.37869941, 0.02151387, 0.81643596], [0.37934000, 0.02858112, 0.82650669], [0.37962694, 0.03812858, 0.83598519], [0.37955939, 0.04951968, 0.84483436], [0.37914154, 0.06144082, 0.85302802], [0.37838226, 0.07366794, 0.86055174], [0.37729438, 0.08604353, 0.86740266], [0.37589428, 0.09845369, 0.87358820], [0.37420030, 0.11081496, 0.87912536], [0.37223249, 0.12306544, 0.88403831], [0.37001170, 0.13515937, 0.88835682], [0.36755886, 0.14706339, 0.89211456], [0.36489450, 0.15875385, 0.89534754], [0.36203830, 0.17021480, 0.89809281], [0.35900949, 0.18143572, 0.90038753], [0.35582553, 0.19241145, 0.90226812], [0.35250263, 0.20314042, 0.90376962], [0.34905654, 0.21362321, 0.90492566], [0.34550110, 0.22386312, 0.90576779], [0.34184894, 0.23386511, 0.90632553], [0.33811203, 0.24363489, 0.90662650], [0.33430129, 0.25317905, 0.90669631], [0.33042661, 0.26250480, 0.90655861], [0.32649697, 0.27161973, 0.90623512], [0.32252050, 0.28053167, 0.90574576], [0.31850454, 0.28924853, 0.90510876], [0.31445576, 0.29777822, 0.90434077], [0.31038061, 0.30612826, 0.90345722], [0.30628532, 0.31430588, 0.90247243], [0.30217392, 0.32231916, 0.90139844], [0.29805278, 0.33017428, 0.90024789], [0.29392464, 0.33787908, 0.89903036], [0.28979522, 0.34543927, 0.89775663], [0.28566704, 0.35286192, 0.89643473], [0.28154364, 0.36015310, 0.89507278], [0.27742935, 0.36731812, 0.89367887], [0.27332615, 0.37436312, 0.89225902], [0.26923690, 0.38129344, 0.89081940], [0.26516428, 0.38811418, 0.88936560], [0.26111077, 0.39483025, 0.88790274], [0.25707865, 0.40144635, 0.88643542], [0.25307008, 0.40796697, 0.88496784], [0.24908704, 0.41439642, 0.88350381], [0.24513141, 0.42073882, 0.88204676], [0.24120493, 0.42699810, 0.88059982], [0.23730925, 0.43317804, 0.87916579], [0.23344590, 0.43928225, 0.87774724], [0.22961633, 0.44531416, 0.87634645], [0.22582190, 0.45127709, 0.87496549], [0.22206389, 0.45717419, 0.87360621], [0.21834349, 0.46300848, 0.87227029], [0.21466236, 0.46878272, 0.87095954], [0.21102119, 0.47449978, 0.86967506], [0.20742080, 0.48016236, 0.86841794], [0.20386210, 0.48577303, 0.86718919], [0.20034666, 0.49133403, 0.86599021], [0.19687454, 0.49684789, 0.86482134], [0.19344637, 0.50231688, 0.86368323], [0.19006344, 0.50774301, 0.86257688], [0.18672570, 0.51312849, 0.86150244], [0.18343350, 0.51847533, 0.86046025], [0.18018787, 0.52378532, 0.85945104], [0.17698826, 0.52906048, 0.85847458], [0.17383532, 0.53430249, 0.85753132], [0.17072887, 0.53951311, 0.85662124], [0.16766875, 0.54469402, 0.85574432], [0.16465509, 0.54984675, 0.85490071], [0.16168705, 0.55497296, 0.85409003], [0.15876483, 0.56007400, 0.85331248], [0.15588710, 0.56515145, 0.85256749], [0.15305387, 0.57020657, 0.85185517], [0.15026358, 0.57524082, 0.85117488], [0.14751579, 0.58025541, 0.85052658], [0.14480878, 0.58525167, 0.84990960], [0.14214173, 0.59023075, 0.84932376], [0.13951263, 0.59519388, 0.84876836], [0.13692028, 0.60014214, 0.84824310], [0.13436243, 0.60507669, 0.84774724], [0.13183741, 0.60999854, 0.84728036], [0.12934276, 0.61490877, 0.84684171], [0.12687634, 0.61980834, 0.84643072], [0.12443548, 0.62469823, 0.84604664], [0.12201756, 0.62957937, 0.84568878], [0.11961967, 0.63445266, 0.84535639], [0.11723878, 0.63931897, 0.84504866], [0.11487170, 0.64417916, 0.84476479], [0.11251507, 0.64903403, 0.84450394], [0.11016531, 0.65388437, 0.84426522], [0.10781885, 0.65873094, 0.84404775], [0.10547170, 0.66357448, 0.84385054], [0.10312014, 0.66841567, 0.84367273], [0.10075970, 0.67325523, 0.84351320], [0.09838664, 0.67809378, 0.84337110], [0.09599597, 0.68293198, 0.84324519], [0.09358395, 0.68777038, 0.84313463], [0.09114522, 0.69260963, 0.84303810], [0.08867599, 0.69745020, 0.84295474], [0.08617051, 0.70229269, 0.84288313], [0.08362511, 0.70713753, 0.84282243], [0.08103357, 0.71198527, 0.84277110], [0.07839237, 0.71683626, 0.84272829], [0.07569525, 0.72169103, 0.84269246], [0.07293844, 0.72654989, 0.84266263], [0.07011617, 0.73141325, 0.84263735], [0.06722404, 0.73628145, 0.84261542], [0.06425764, 0.74115477, 0.84259561], [0.06121130, 0.74603356, 0.84257635], [0.05808247, 0.75091799, 0.84255664], [0.05486570, 0.75580838, 0.84253483], [0.05155846, 0.76070488, 0.84250968], [0.04815913, 0.76560763, 0.84247998], [0.04466405, 0.77051685, 0.84244395], [0.04107468, 0.77543259, 0.84240043], [0.03741096, 0.78035490, 0.84234809], [0.03385282, 0.78528385, 0.84228537], [0.03043137, 0.79021949, 0.84221065], [0.02716948, 0.79516171, 0.84212275], [0.02409051, 0.80011044, 0.84202021], [0.02122047, 0.80506559, 0.84190153], [0.01858815, 0.81002699, 0.84176524], [0.01622412, 0.81499451, 0.84160961], [0.01416537, 0.81996783, 0.84143342], [0.01245080, 0.82494667, 0.84123518], [0.01112317, 0.82993067, 0.84101341], [0.01022949, 0.83491944, 0.84076663], [0.00982139, 0.83991250, 0.84049339], [0.00995551, 0.84490931, 0.84019224], [0.01069215, 0.84990934, 0.83986145], [0.01210010, 0.85491187, 0.83949971], [0.01425466, 0.85991610, 0.83910577], [0.01723795, 0.86492117, 0.83867832], [0.02113724, 0.86992620, 0.83821555], [0.02605147, 0.87493010, 0.83771618], [0.03209157, 0.87993158, 0.83717944], [0.03937186, 0.88492950, 0.83660298], [0.04753062, 0.88992218, 0.83598667], [0.05607917, 0.89490805, 0.83532877], [0.06500234, 0.89988525, 0.83462804], [0.07428800, 0.90485162, 0.83388399], [0.08393083, 0.90980477, 0.83309565], [0.09393285, 0.91474203, 0.83226231], [0.10430211, 0.91966031, 0.83138359], [0.11505191, 0.92455607, 0.83045962], [0.12619999, 0.92942531, 0.82949010], [0.13776962, 0.93426332, 0.82847628], [0.14978894, 0.93906464, 0.82741934], [0.16229169, 0.94382285, 0.82632213], [0.17531808, 0.94853039, 0.82518803], [0.18891548, 0.95317821, 0.82402273], [0.20313976, 0.95775546, 0.82283421], [0.21805616, 0.96224898, 0.82163430], [0.23374218, 0.96664270, 0.82043899], [0.25028497, 0.97091692, 0.81927329], [0.26778032, 0.97504765, 0.81817391], [0.28632927, 0.97900591, 0.81719338], [0.30601898, 0.98275811, 0.81640936], [0.32689118, 0.98626848, 0.81593233], [0.34888332, 0.98950593, 0.81591102], [0.37176267, 0.99245625, 0.81652140]] # Create ListedColormap object for this colormap cmap = ListedColormap(cm_data, name='cmr.cosmic', N=len(cm_data)) cmap_r = cmap.reversed() # Register (reversed) cmap in MPL register_cmap(cmap=cmap) register_cmap(cmap=cmap_r)

[ "ellert_vandervelden@outlook.com" ]

ellert_vandervelden@outlook.com

e459a8bed2ebf847119b43f03585274b9d6d301d

d8ce486989fe13074365a20b77743dc333b37b65

/python/paradrop/backend/exc/runtime.py

ff7817cab128621782d10a037dca7d526d2ffdfc

[]

no_license

damouse/AnotherParadrop

a1ae8e8d91d54b091a1b8f4d564e4e6339e2c60f

7c3ca7a149b8e30ba11f6d6b6e4d953374bf8708

refs/heads/master

2021-01-17T06:52:55.933794

2016-07-11T01:10:00

62,856,876

0

null

UTF-8

Python

false

1,561

py

################################################################### # Copyright 2013-2015 All Rights Reserved # Authors: The Paradrop Team ################################################################### from pdtools.lib.output import out from paradrop.backend.exc import plangraph from paradrop.lib import config def generatePlans(update): """ This function looks at a diff of the current Chute (in @chuteStor) and the @newChute, then adds Plan() calls to make the Chute match the @newChute. Returns: True: abort the plan generation process """ out.verbose("%r\n" % (update)) # Generate virt start script, stored in cache (key: 'virtPreamble') update.plans.addPlans(plangraph.RUNTIME_GET_VIRT_PREAMBLE, (config.dockerconfig.getVirtPreamble, )) # If the user specifies DHCP then we need to generate the config and store it to disk update.plans.addPlans(plangraph.RUNTIME_GET_VIRT_DHCP, (config.dhcp.getVirtDHCPSettings, )) update.plans.addPlans(plangraph.RUNTIME_SET_VIRT_DHCP, (config.dhcp.setVirtDHCPSettings, )) # Reload configuration files todoPlan = (config.configservice.reloadAll, ) abtPlan = [(config.osconfig.revertConfig, "dhcp"), (config.osconfig.revertConfig, "firewall"), (config.osconfig.revertConfig, "network"), (config.osconfig.revertConfig, "wireless"), (config.configservice.reloadAll, )] update.plans.addPlans(plangraph.RUNTIME_RELOAD_CONFIG, todoPlan, abtPlan) return None

[ "damouse007@gmail.com" ]

damouse007@gmail.com

69e938ae8597f11320f9ad83b8e276f8401c8d4a

074dcf2274f2864710264db115b840c838b64ffd

/leet_0985_sum_of_even_numbers_after_queries.py

32e67b96e33cb9081f2f1c235692f83e8e231335

[]

no_license

kkaixiao/pythonalgo2

212da2dac8d3a38fd06b0d1f5895cb9a768da43e

92b4b7c6b69d39bf79a9e20a9fc947304c2a1de5

refs/heads/master

2021-06-23T07:20:13.659422

2021-05-10T05:16:30

224,455,645

2

1

null

UTF-8

Python

false

1,614

py

""" e have an array A of integers, and an array queries of queries. For the i-th query val = queries[i][0], index = queries[i][1], we add val to A[index]. Then, the answer to the i-th query is the sum of the even values of A. (Here, the given index = queries[i][1] is a 0-based index, and each query permanently modifies the array A.) Return the answer to all queries. Your answer array should have answer[i] as the answer to the i-th query. Example 1: Input: A = [1,2,3,4], queries = [[1,0],[-3,1],[-4,0],[2,3]] Output: [8,6,2,4] Explanation: At the beginning, the array is [1,2,3,4]. After adding 1 to A[0], the array is [2,2,3,4], and the sum of even values is 2 + 2 + 4 = 8. After adding -3 to A[1], the array is [2,-1,3,4], and the sum of even values is 2 + 4 = 6. After adding -4 to A[0], the array is [-2,-1,3,4], and the sum of even values is -2 + 4 = 2. After adding 2 to A[3], the array is [-2,-1,3,6], and the sum of even values is -2 + 6 = 4. Note: 1 <= A.length <= 10000 -10000 <= A[i] <= 10000 1 <= queries.length <= 10000 -10000 <= queries[i][0] <= 10000 0 <= queries[i][1] < A.length """ class Solution: def sumEvenAfterQueries(self, A: List[int], queries: List[List[int]]) -> List[int]: res = [] isEven = lambda x: x % 2 == 0 evenSum = sum(filter(isEven, A)) for query in queries: numToAdd, idx = query[0], query[1] if isEven(A[idx]): evenSum -= A[idx] A[idx] += numToAdd if isEven(A[idx]): evenSum += A[idx] res.append(evenSum) return res

[ "show-key@qq.com" ]

show-key@qq.com

8a69e7b744e52b3f84dd74831ee475bb703574fe

baacad8007b78f105b41030fd48d643820142ba1

/hw-pca.py

22172f834d3d4ddc3c6bcb97c164458cb32c3d54

[]

no_license

baoaya/point-cloud

b31ef7ca19eb3f2255876a0ed08fc0ccd67e5e6a

6c35cf38bfcfafbf25b5725ce2b13d0e8f0153c6

refs/heads/master

2023-03-21T03:21:56.844632

2021-03-07T11:42:07

344,090,961

0

null

UTF-8

Python

false

2,462

py

import numpy as np import open3d as o3d from matplotlib import pyplot as plt # PCA # x是点云矩阵，返回排序好的特征向量 def pca(x): x_mean = np.mean(x, axis=0) normalize_x = x - x_mean normalize_x = normalize_x.T h = normalize_x.dot(normalize_x.T) eigen_values, eigen_vectors = np.linalg.eig(h) return eigen_vectors def hw_pca(x): u = pca(x) # 投影2维坐标 projection_matrix = (u.T[:][:2]).T x_pca = x.dot(projection_matrix) return x_pca # 计算法向量 # x为点云矩阵，n为临近点个数 def hw_surface_normal(x, n): point_cloud_o3d = o3d.geometry.PointCloud() point_cloud_o3d.points = o3d.utility.Vector3dVector(point_cloud_o3d) pcd_tree = o3d.geometry.KDTreeFlann(point_cloud_o3d) # 对点云建立kd树方便搜索 normals = [] print(x.shape[0]) # 10000 for i in range(x.shape[0]): # search_knn_vector_3d函数，输入值[每一点，x] 返回值 [int, open3d.utility.IntVector, open3d.utility.DoubleVector] [_, idx, _] = pcd_tree.search_knn_vector_3d(point_cloud_o3d.points[i], n) # asarray和array 一样但是array会copy出一个副本，asarray不会，节省内存 k_nearest_point = np.asarray(point_cloud_o3d.points)[idx, :] # 找出每一点的10个临近点，类似于拟合成曲面，然后进行PCA找到特征向量最小的值，作为法向量 eigen_vectors = pca(k_nearest_point) # 取最后的那个 normals.append(eigen_vectors[:, 2]) return normals # 下采样 # x为点云矩阵 # r为Voxel Grid的大小 # take为取点方式，默认为random随机取点，centroid取中心点 def hw_downsampling(x, r, take="random"): max = np.max(axis=0) min = np.min(axis=0) # x_min, y_min, z_min = min[0], min[1], min[2] # x_max, y_max, z_max = max[0], max[1], max[2] d = (max - min)/r # dx, dy, dz = (x_max - x_min) / r, (y_max - y_min) / r, (z_max - z_min) / r hash = {} X return def main(): # 加载文件 x = np.loadtxt('/Users/jimmy/Desktop/DeepLearning/homework/1/data/airplane_0027.txt', delimiter=',')[:, 0:3] x_pca = hw_pca(x) # 显示 plt.scatter(x_pca[:, 0], x_pca[:, 1]) plt.show() normals = hw_surface_normal(x, 10) # 10个临近点 ds_random = hw_downsampling(x, take="random") ds_centroid = hw_downsampling(x, take="centroid") return if __name__ == "__main__": main()

[ "wuhaojie@gmail.com" ]

wuhaojie@gmail.com

1a8f7f2c0353ac2b624f1e8636896917b3309abb

d62e60b26fdb5373f72c2cf5ddcd7ad99b835f23

/eee/koans/about_control_statements.py

40b5444ef520f4ae763da2e1a9980d390e85d91f

[]

no_license

glambertation/Paper

4cf6e605235eb0bbe7e6ebe24a916e5a34935e3d

7a4945490a53cc409641720621c7710b7ab9f2ae

refs/heads/master

2021-09-04T13:23:06.385324

2018-01-19T04:45:25

105,601,966

0

null

UTF-8

Python

false

2,258

py

#!/usr/bin/env python # -*- coding: utf-8 -*- from runner.koan import * class AboutControlStatements(Koan): def test_if_then_else_statements(self): if True: result = 'true value' else: result = 'false value' self.assertEqual('true value', result) def test_if_then_statements(self): result = 'default value' if True: result = 'true value' self.assertEqual('true value', result) def test_if_then_elif_else_statements(self): if False: result = 'first value' elif True: result = 'true value' else: result = 'default value' self.assertEqual('true value', result) def test_while_statement(self): i = 1 result = 1 while i <= 10: result = result * i i += 1 self.assertEqual(3628800, result) def test_break_statement(self): i = 1 result = 1 while True: if i > 10: break result = result * i i += 1 self.assertEqual(3628800, result) def test_continue_statement(self): i = 0 result = [] while i < 10: i += 1 if (i % 2) == 0: continue result.append(i) self.assertEqual([1,3,5,7,9], result) def test_for_statement(self): phrase = ["fish", "and", "chips"] result = [] for item in phrase: result.append(item.upper()) self.assertEqual(['FISH','AND','CHIPS'], result) def test_for_statement_with_tuples(self): round_table = [ ("Lancelot", "Blue"), ("Galahad", "I don't know!"), ("Robin", "Blue! I mean Green!"), ("Arthur", "Is that an African Swallow or European Swallow?") ] result = [] for knight, answer in round_table: result.append("Contestant: '" + knight + \ "' Answer: '" + answer + "'") text = __ self.assertMatch("Contestant: 'Robin' Answer: 'Blue! I mean Green!'", result[2]) self.assertNoMatch(text, result[0]) self.assertNoMatch(text, result[1]) self.assertNoMatch(text, result[3])

[ "songhaiyun@bytedance.com" ]

songhaiyun@bytedance.com

33d4076089c5e19b3838fc02d813cc695a5951d3

9c8ab08d961dcc8087c34f90561f4e3d304f6bf8

/Exotag_SW_uploader/sw_uploader.py

a5a9a92cf05de66925c9fde56a7d175082c0d5ea

[]

no_license

kdubovenko/eclipseRepo

230e249749175a7fb4e3e30308aca2ba378ff2d4

081eb845dc5e8328ed2b7454003506bcb0b79c16

refs/heads/master

2021-01-16T21:14:19.890046

2020-05-13T22:57:39

100,223,402

1

0

null

UTF-8

Python

false

3,865

py

#!/usr/bin/python from __future__ import print_function import sys, binascii, serial, time, getopt, io, struct from intelhex import IntelHex def main(argv): inputfile = '' port = '' split = 1024 usage_string = 'huzzah_exotag_firmware.py -i <inputfile> -p <comm port:/dev/ttyUSB or \\\.\COM12>' try: opts, args = getopt.getopt(argv,"hi:p:s:",["file=","port=","split="]) except getopt.GetoptError: print () sys.exit(2) if not opts: print ("no arguments provided ") print (usage_string) sys.exit(2) for opt, arg in opts: if opt == '-h': print (usage_string) sys.exit() elif opt in ("-i", "--file"): inputfile = arg elif opt in ("-p", "--port"): port = arg elif opt in ("-s", "--split"): split = int(arg) else: print ("wrong arguments: " + opt) print (usage_string) print('input file: '+inputfile) print('output port: '+port) print('split in bytes: %d' % split) if inputfile.endswith('.hex'): ih = IntelHex() # create empty object ih.padding=0xFF ih.fromfile(inputfile,format='hex') # also load from hex ascii_bin = binascii.hexlify(ih.tobinstr()) #sys.exit() elif inputfile.endswith('.bin'): #reconsider the extension here, the routine actually handles ascii with open(inputfile, 'r') as f: read_data = f.read() f.closed read_data = read_data.rstrip('\r\n') print (read_data) print ([n for n in read_data]) ascii_bin = read_data #binascii.unhexlify(read_data) #sys.exit() #print(ascii_bin) crc_result=binascii.crc32(ascii_bin) & 0xffffffff print("CRC = %08x" % crc_result) #sys.exit() exotag_uart = serial.Serial(port, 115200, timeout=1) exotag_uart_io = io.TextIOWrapper(io.BufferedRWPair(exotag_uart, exotag_uart)) print('send start update: ' + unicode('exotag=update\r')) exotag_uart_io.write(unicode('exotag=update'.rstrip()+'\r')) exotag_uart_io.flush() time.sleep(1) #print (exotag_uart.readline()) print('write') for i in range(0, len(ascii_bin), split): print((ascii_bin[i:i + split])) exotag_uart.write((ascii_bin[i:i + split])) exotag_uart_io.flush() time.sleep(1) print( binascii.hexlify(struct.pack("<I", crc_result)) ) exotag_uart.write('!'.encode()+struct.pack("<I", crc_result)) exotag_uart_io.flush() #time.sleep(1) print('send end of firmware update') exotag_uart_io.write(unicode('~')) exotag_uart_io.flush() print('read exotag messages') exotag_string = exotag_uart_io.read() print("***********************\r\n"+exotag_string+"\r\n***********************") if (-1 != exotag_string.find('firmware update: SUCCESS')): print('tell huzzah to push update to exotag') exotag_uart_io.write(unicode('exotag=program'.rstrip()+'\r')) exotag_uart_io.flush() #time.sleep(10) print('read exotag messages') time.sleep(5) exotag_string = exotag_uart_io.read() print("***********************\r\n"+exotag_string+"\r\n***********************") if (-1 != exotag_string.find('EFM8 flash write read-back verify success')): print('EFM8 flash write read-back verify success - indicates SUCCESS') print('reset exotag') exotag_uart_io.write(unicode('exotag=reset'.rstrip()+'\r')) exotag_uart_io.flush() time.sleep(5) exotag_string = exotag_uart_io.read() print("***********************\r\n"+exotag_string+"\r\n***********************") exotag_uart.close() if __name__ == "__main__": main(sys.argv[1:])

[ "kdubovenko@gmail.com" ]

kdubovenko@gmail.com

058c007c891929098cb59e8d6ed13d88a8135a36

668188a66168ae01a84efa03a3a08d0618885e86

/classify/utils/d_process.py

353563784d96da27f4457ed499cd6518332d8600

[]

no_license

Xie-JunWei/lstm-network

c59c939765c9362750922374083a827cf32a8671

3f4cc841e41e3b48a4cef427a5fe373355f38d1b

refs/heads/main

2023-02-26T02:20:53.668018

2021-02-07T14:13:55

336,803,296

1

0

null

UTF-8

Python

false

1,621

py

# 预处理加随机噪声，归一化 import numpy as np def dp(traj_,max_len_): x, x_v, y, y_v ,z ,z_v= [],[],[],[],[],[] ini = 0 # count = 1201 for line in traj_: if ini==0: x_0=line[0] y_0=line[1] z_0=line[2] ini+=1 else: rand_r = np.random.normal(0, 145, 3) rand_v = np.random.normal(0, 23.2, 3) np.random.shuffle(rand_r) np.random.shuffle(rand_v) # 添加随机噪声 # x.append((line[0]-x_0+rand_r[0])/10e3) # y.append((line[1]-y_0+rand_r[1])/10e3) # z.append((line[2]-z_0+rand_r[2])/10e3) # x_v.append(line[3]+rand_v[0]) # y_v.append(line[4]+rand_v[1]) # z_v.append(line[5]+rand_v[2]) x.append((line[0] - x_0) / 10e5) y.append((line[1] - y_0) / 10e5) z.append((line[2] - z_0) / 10e5) x_v.append(line[3] / 10e2) y_v.append(line[4] / 10e2) z_v.append(line[5] / 10e2) max_len_=max_len_-1 if max_len_<0: break xnew, ynew, znew, x_vnew, y_vnew ,z_vnew=np.array(x), np.array(y),np.array(z),\ np.array(x_v),np.array(y_v),np.array(z_v) new = np.transpose(np.vstack((xnew,ynew,znew,x_vnew,y_vnew,z_vnew))) return new class data_process(object): def __init__(self, max_len): self.max_len = max_len def __call__(self, traj): traj=dp(traj,self.max_len) return traj

[ "noreply@github.com" ]

Xie-JunWei.noreply@github.com

2aad664b1d1fb518045bd6f2279ab4277a41eb31

f2e3b1181c13bded5baaedda0813129838118971

/IOT-Web-Services/src/config.py

99f9f24404dd4126034502428ed1b7477644670f

[]

no_license

zubairshakoorarbisoft/iot-api-usama

bf1627131c58a106139755d75e26a48de8a38219

d623745e35b24cf00f5d95389193045b16ef4f5a

refs/heads/main

2023-08-31T10:09:29.785934

2021-09-26T20:36:29

410,654,734

0

null

UTF-8

Python

false

289

py

from pydantic import BaseSettings class Settings(BaseSettings): pgsql_host: str pgsql_dns: str pgsql_port: int pgsql_user: str pgsql_password: str pgsql_db_name: str class Config: env_prefix = '' env_file = '../.env' settings = Settings()

[ "noreply@github.com" ]

zubairshakoorarbisoft.noreply@github.com

2b17eb37f580aae31898a48853bef496335a74aa

bfe3c294db999eb46af04f1c3c6451c974a4a7eb

/PyPoll/main.py

16d95d67b9b898a4e524d21261092d068e2c12c5

[]

no_license

diazdez/Python-Challenge

5fb06331a4edae06254169e3396496ab09e19d93

1a753dd82a91ca52563fb0d4fd9422dd68865e15

refs/heads/master

2022-12-22T10:16:40.641322

2020-09-22T21:51:54

296,190,241

0

null

UTF-8

Python

false

3,740

py

# PYPOLL: Homework # PyPoll CSV File: election_data.csv # CSV has a header with 3 categories: "Voter ID", "County" & “Candidate” # The total number of votes cast # A complete list of candidates who received votes # The percentage of votes each candidate won # The total number of votes each candidate won # The winner of the election based on popular vote. # Put together final script should both print the analysis to the terminal # Export a text file with the analysis/results. # Identify Variables vote_count = 0 candidates_with_votes = [] candidate_vote_num = [0,0,0,0] pct_of_votes = [] # create file path across Operating Systems (os) # module for reading the csv file import os import csv # file path csvpath = os.path.join('Resources', 'election_data.csv') # open/read file with open(csvpath) as csvfile: csvreader= csv.reader(csvfile, delimiter=',') csvheader = next(csvreader) for row in csvreader: # number of rows equals the number of votes: vote_count = vote_count + 1 # Candidates are listed in Column 3 (Index = 2) listed_candidate = (row[2]) # Need to find the different candidates in the Column 3 # Need to find the vote count for each candidate if listed_candidate not in candidates_with_votes: #index the candidate to the list candidates_with_votes.append(listed_candidate) else: pass # print(candidates_with_votes) = found a total of 4 different types of candidates #increase vote count by 1 with open(csvpath) as csvfile: csvreader= csv.reader(csvfile, delimiter=',') csvheader = next(csvreader) for row in csvreader: if row[2] == candidates_with_votes[0]: candidate_vote_num[0] = candidate_vote_num[0] +1 elif row[2] == candidates_with_votes[1]: candidate_vote_num[1] = candidate_vote_num[1] +1 elif row[2] == candidates_with_votes[2]: candidate_vote_num[2] = candidate_vote_num[2] +1 elif row[2] == candidates_with_votes[3]: candidate_vote_num[3] = candidate_vote_num[3] +1 #print(candidate_vote_num) high_vote_count = 0 votecount_index = 0 for x in range(len(candidates_with_votes)): #calculate the percentage of votes received per candidate: (CandidateVote#/TotalVote#)*100 pct = round(candidate_vote_num[x]/vote_count*100, 3) pct_of_votes.append(pct) if candidate_vote_num[x] > high_vote_count: high_vote_count = candidate_vote_num[x] votecount_index = x winner = candidates_with_votes[votecount_index] # print(winner) # RESULTS print() print("Election Results") print("-------------------------") print("Total Votes: " + str(vote_count)) print("-------------------------") for x in range(len(candidates_with_votes)): print(str(candidates_with_votes[x]) + ": " +str(pct_of_votes[x])+"%" + " "+ "(" +str(candidate_vote_num[x]) +")") print("-------------------------") print("Winner: " + (winner)) print("-------------------------") # # save output file path as text pypoll_output_file = os.path.join("..", "pypoll_output.txt") # # open the output file with write mode with open(pypoll_output_file,"w") as text: text.write(("Election Results")+ '\n') text.write(("-------------------------")+ '\n') text.write(("Total Votes: " + str(vote_count))+ '\n') text.write(("-------------------------")+ '\n') for x in range(len(candidates_with_votes)): text.write((str(candidates_with_votes[x]) + ": " +str(pct_of_votes[x])+"%" + " "+ "(" +str(candidate_vote_num[x]) +")") + '\n') text.write((" ")+ '\n') text.write(("-------------------------")+ '\n') text.write(("Winner: " + (winner)) + '\n') text.write(("-------------------------")+ '\n')

[ "69435783+diazdez@users.noreply.github.com" ]

69435783+diazdez@users.noreply.github.com

0b9ad678fafff5f6858e34778dcf49f9e2da81f1

dcf1478d7a3c2338f5daa04240ac6e90f6e6cce2

/application/routes.py

5af5ae553545eb5cbaa1778edd19170c79cf9e0c

[]

no_license

LeoKnox/flask_py

555968ad90cb092e6ba383cb76c47931f8d49c98

68e8cc9159584bab33220177dc2003c699489095

refs/heads/master

2023-03-25T08:21:37.124324

2020-05-25T05:50:58

260,389,671

0

null

2021-03-20T03:40:42

2020-05-01T05:53:14

HTML

UTF-8

Python

false

1,653

py

from application import app, db, mycol from application.models import Room from application.forms import CreateRoomForm from flask import render_template, request @app.route("/") @app.route("/index") def index(): return render_template("index.html", index="active") @app.route("/dungeon") def dungeon(): info = Room.objects.all() return render_template("dungeon.html", dungeon="active", info=info) @app.route("/room/", methods=["GET", "POST"]) @app.route("/room/<room_name>", methods=["GET", "POST"]) def room(room_name="Entry"): if not room_name: room_name="Entry" room_data = Room.objects.get(room_name=room_name) form = CreateRoomForm() if form.validate_on_submit(): room_name = form.room_name.data length = form.length.data width = form.width.data pos_x = form.pos_x.data pos_y = form.pos_y.data room = Room(room_name=room_name,length=length,width=width,pos_x=pos_x,pos_y=pos_y) Room.objects(room_name=room_name).update(pos_y=6) return render_template("room.html", room="active", info=room_data, form=form) @app.route("/map") def map(): x = 'Entry' y = {'room_name':x} newvalues = {"$set": {"pos_x":5,"pos_y":5,"doors":{"wall":1,"position":3}}} z = mycol.update_many(y,newvalues) return render_template("map.html", map="active") @app.route("/monsters") def monsters(): return render_template("monsters.html", monsters="active") @app.route("/treasure") def treasure(): return render_template("treasure.html", treasure="active")

[ "noreply@github.com" ]

LeoKnox.noreply@github.com

a6db7fdd687e1c3b4a48e8e4f97344c121c8d0c1

3eb0d7197bbbb5f4677ce30620eda571decedf12

/pygbif/registry/__init__.py

00e3d4ea2ee4eabc0c402754a4534355c57f24d9

[ "LicenseRef-scancode-unknown-license-reference", "MIT" ]

permissive

faroit/pygbif

f38e34571639f8135b15c749da51778ff36c0d01

4bfdb7bc87c372c59f1f0e81843a18585a3056f4

refs/heads/master

2023-01-22T11:10:40.686527

2020-09-29T23:41:18

297,910,320

0

MIT

2020-09-23T08:53:46

2020-09-23T08:53:45

null

UTF-8

Python

false

637

py

""" GBIF registry APIs methods * `organizations`: Organizations metadata * `nodes`: Nodes metadata * `networks`: Networks metadata * `installations`: Installations metadata * `datasets`: Search for datasets and dataset metadata * `dataset_metrics`: Get details/metrics on a GBIF dataset * `dataset_suggest`: Search that returns up to 20 matching datasets * `dataset_search`: Full text search across all datasets """ from .nodes import nodes from .networks import networks from .installations import installations from .datasets import datasets, dataset_metrics, dataset_suggest, dataset_search from .organizations import organizations

[ "myrmecocystus@gmail.com" ]

myrmecocystus@gmail.com

afdb85dbdce3a8016eb733c7a9673913e4f8feb2

a6c12a2790c7fb7b032f43eeafb12a79138376c2

/app2/views.py

6aeedd991680e7f96036e4e6272d08673b6bd703

[]

no_license

karthi-chala/pro22

12fbb735b23acfea1bc017c86a7f91dad9d4cb00

52b913c8f865cee63a73910910983f18c22b53f8

refs/heads/main

2023-03-31T11:56:13.018840

2021-04-03T12:24:28

354,331,623

0

null

UTF-8

Python

false

248

py

from django.shortcuts import render from django.http import HttpResponse # Create your views here. def index(request): return HttpResponse('<h1>welcome to index of app2</h1>') def sample(request): return render(request,'app2/sample.html')

[ "karthi.sacred27@gmail.com" ]

karthi.sacred27@gmail.com

6dd5ad61bfdc032115e548d265370f29b51aac01

6e51ff71f150ff964caaaba3af6550f8258e975a

/news_scraper/spiders/inside.py

9ea59a93668ebb232a848afc399fa679186f243b

[ "MIT" ]

permissive

yungjr/news-scraper

289fbab2f2c37f515016f346ece8953c669b0fc3

f10c7a7f4c456ec950cd5f8c12ee202e2d0be793

refs/heads/main

2023-03-16T01:03:24.146905

2021-02-28T09:01:31

null

0

null

UTF-8

Python

false

1,435

py

import scrapy class InsideSpider(scrapy.Spider): name = 'inside' allowed_domains = ['www.inside.com.tw'] start_urls = ['https://www.inside.com.tw/tag/ai'] count = 1 # 執行次數 def parse(self, response): yield from self.scrape(response) # 爬取網頁內容 # 定位「下一頁」按鈕元素 next_page_url = response.xpath( "//a[@class='pagination_item pagination_item-next']/@href") if next_page_url: url = next_page_url.get() # 取得下一頁的網址 InsideSpider.count += 1 if InsideSpider.count <= 3: yield scrapy.Request(url, callback=self.parse) # 發送請求 def scrape(self, response): # 爬取文章標題 post_titles = response.xpath( "//h3[@class='post_title']/a[@class='js-auto_break_title']/text()" ).getall() # 爬取發佈日期 post_dates = response.xpath( "//li[@class='post_date']/span/text()" ).getall() # 爬取作者 post_authors = response.xpath( "//span[@class='post_author']/a/text()" ).getall() for data in zip(post_titles, post_dates, post_authors): NewsScraperItem = { "post_title": data[0], "post_date": data[1], "post_author": data[2] } yield NewsScraperItem

[ "mikekuforgit@gmail.com" ]

mikekuforgit@gmail.com

3b01306425299986ae69ee9a5f0da7376a8f7ff7

a920c8dfcbf789c37b0207987070b81512217136

/graph.py

6c7db432592baa9a3e3d1c4c20cc6ee7650e83da

[]

no_license

carter-yagemann/BeijingAir

affc7cdfbaf53fc5d1ea3dcf42758219a97821df

c08061382f968569fad7d77090012be85f7d7deb

refs/heads/master

2021-01-11T21:51:35.778990

2015-03-10T04:05:34

78,866,395

0

null

UTF-8

Python

false

2,393

py

#!/usr/bin/python ''' BeijingAir graph.py Copyright Carter Yagemann 2015 This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>. ''' import sys import matplotlib.pyplot as plt #-----------------------------------------------------# # Helper Functions # #-----------------------------------------------------# def usage(): print 'Usage: python graph.py <csv_input_data>' ############################################ ## Main ## ############################################ if len(sys.argv) != 2: usage() sys.exit() filename = sys.argv[1] try: file = open(filename, 'r') y_array = [] x_array = [] # Generate array while True: nextline = file.readline(); # Have we hit EOF? if nextline == '': break # Convert csv to array parsedline = nextline.split(', ') # Exclude averages, No Data, or unexpected lines if len(parsedline) < 3: continue if 'No Data' in parsedline[2]: continue if '24hr avg' in parsedline[1]: continue # Passed validation, store data point y_array.append(parsedline[2]) x_array.append(parsedline[0]) file.close() # Display graph plt.title('Beijing Air Quality\n' + x_array[0] + ' to ' + x_array[-1]) plt.plot(y_array) plt.ylabel('PM2.5') frame = plt.gca() frame.axes.get_xaxis().set_visible(False) fig = plt.gcf() fig.canvas.set_window_title('BeijingAir') plt.show() except KeyboardInterrupt: print "\nCaught keyboard interrupt, exiting." sys.exit() except: print "\nUnexpected Exception:", str(sys.exc_info()[1]) sys.exit()

[ "yager.code@gmail.com" ]

yager.code@gmail.com

a9d30b879ccaabca5abc2e5f1cbc6ca98d86d3c3

9d39f6ec24ea355ee82adfd4487453172953dd37

/tao_detection_release/configs/baselines/untitled.py

8638d6ce39fea718525ea919f636993395a6144e

[ "Apache-2.0" ]

permissive

feiaxyt/Winner_ECCV20_TAO

d69c0efdb1b09708c5d95c3f0a38460dedd0e65f

dc36c2cd589b096d27f60ed6f8c56941b750a0f9

refs/heads/main

2023-03-19T14:17:36.867803

2021-03-16T14:04:31

334,864,331

82

6

null

UTF-8

Python

false

9,591

py

_base_ = '../detectors/detectors_htc_r101_64x4d_1x_coco.py' model = dict( pretrained='open-mmlab://resnext101_64x4d', backbone=dict( type='DetectoRS_ResNeXt', depth=101, groups=64, base_width=4, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=1, norm_cfg=dict(type='BN', requires_grad=True), norm_eval=True, style='pytorch', conv_cfg=dict(type='ConvAWS'), sac=dict(type='SAC', use_deform=True), stage_with_sac=(False, True, True, True), output_img=True), neck=dict( type='RFP', rfp_steps=2, aspp_out_channels=64, aspp_dilations=(1, 3, 6, 1), rfp_backbone=dict( rfp_inplanes=256, type='DetectoRS_ResNeXt', depth=101, groups=64, base_width=4, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=1, norm_cfg=dict(type='BN', requires_grad=True), norm_eval=True, conv_cfg=dict(type='ConvAWS'), sac=dict(type='SAC', use_deform=True), stage_with_sac=(False, True, True, True), pretrained='open-mmlab://resnext101_64x4d', style='pytorch')), roi_head=dict( bbox_head=[ dict( type='Shared2FCBBoxHead', in_channels=256, fc_out_channels=1024, roi_feat_size=7, num_classes=1230, bbox_coder=dict( type='DeltaXYWHBBoxCoder', target_means=[0., 0., 0., 0.], target_stds=[0.1, 0.1, 0.2, 0.2]), reg_class_agnostic=True, loss_cls=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0), loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0)), dict( type='Shared2FCBBoxHead', in_channels=256, fc_out_channels=1024, roi_feat_size=7, num_classes=1230, bbox_coder=dict( type='DeltaXYWHBBoxCoder', target_means=[0., 0., 0., 0.], target_stds=[0.05, 0.05, 0.1, 0.1]), reg_class_agnostic=True, loss_cls=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0), loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0)), dict( type='Shared2FCBBoxHead', in_channels=256, fc_out_channels=1024, roi_feat_size=7, num_classes=1230, bbox_coder=dict( type='DeltaXYWHBBoxCoder', target_means=[0., 0., 0., 0.], target_stds=[0.033, 0.033, 0.067, 0.067]), reg_class_agnostic=True, loss_cls=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0), loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0)) ], mask_head=[ dict( type='HTCMaskHead', with_conv_res=False, num_convs=4, in_channels=256, conv_out_channels=256, num_classes=1230, loss_mask=dict( type='CrossEntropyLoss', use_mask=True, loss_weight=1.0)), dict( type='HTCMaskHead', num_convs=4, in_channels=256, conv_out_channels=256, num_classes=1230, loss_mask=dict( type='CrossEntropyLoss', use_mask=True, loss_weight=1.0)), dict( type='HTCMaskHead', num_convs=4, in_channels=256, conv_out_channels=256, num_classes=1230, loss_mask=dict( type='CrossEntropyLoss', use_mask=True, loss_weight=1.0)) ])) # model training and testing settings train_cfg = dict( rpn=dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.7, neg_iou_thr=0.3, min_pos_iou=0.3, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=256, pos_fraction=0.5, neg_pos_ub=-1, add_gt_as_proposals=False), allowed_border=0, pos_weight=-1, debug=False), rpn_proposal=dict( nms_across_levels=False, nms_pre=2000, nms_post=2000, max_num=2000, nms_thr=0.7, min_bbox_size=0), rcnn=[ dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.5, neg_iou_thr=0.5, min_pos_iou=0.5, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=512, pos_fraction=0.25, neg_pos_ub=-1, add_gt_as_proposals=True), mask_size=28, pos_weight=-1, debug=False), dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.6, neg_iou_thr=0.6, min_pos_iou=0.6, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=512, pos_fraction=0.25, neg_pos_ub=-1, add_gt_as_proposals=True), mask_size=28, pos_weight=-1, debug=False), dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.7, neg_iou_thr=0.7, min_pos_iou=0.7, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=512, pos_fraction=0.25, neg_pos_ub=-1, add_gt_as_proposals=True), mask_size=28, pos_weight=-1, debug=False) ], stage_loss_weights=[1, 0.5, 0.25]) test_cfg = dict( rpn=dict( nms_across_levels=False, nms_pre=1000, nms_post=1000, max_num=1000, nms_thr=0.7, min_bbox_size=0), rcnn=dict( score_thr=0.0001, nms=dict(type='nms', iou_thr=0.5), # LVIS allows up to 300 max_per_img=300, mask_thr_binary=0.5) ) # dataset settings dataset_type = 'LVISDataset' data_root = 'data/lvis/' img_norm_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) train_pipeline = [ dict(type='LoadImageFromFile'), dict( type='LoadAnnotations', with_bbox=True, with_mask=True, with_seg=True, poly2mask=False), dict( type='Resize', img_scale=[(1600, 400), (1600, 1400)], multiscale_mode='range', keep_ratio=True), dict(type='RandomFlip', flip_ratio=0.5), dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size_divisor=32), dict(type='SegRescale', scale_factor=1 / 8), dict(type='DefaultFormatBundle'), dict( type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks', 'gt_semantic_seg']), ] test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(1333, 800), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip', flip_ratio=0.5), dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size_divisor=32), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']), ]) ] data = dict( samples_per_gpu=1, workers_per_gpu=1, train=dict( type='ClassBalancedDataset', oversample_thr=1e-3, dataset=dict( type=dataset_type, ann_file=data_root + 'lvis_v0.5_train.json', seg_prefix=data_root + 'stuffthingmaps/train2017/', img_prefix=data_root + 'train2017/', pipeline=train_pipeline)), val=dict( type=dataset_type, ann_file=data_root + 'lvis_v0.5_val.json', img_prefix=data_root + 'val2017/', pipeline=test_pipeline), test=dict( type=dataset_type, ann_file=data_root + 'lvis_v0.5_val.json', img_prefix=data_root + 'val2017/', pipeline=test_pipeline)) evaluation = dict(metric=['bbox', 'segm']) # optimizer optimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001) optimizer_config = dict(grad_clip=None) # learning policy lr_config = dict( policy='step', warmup='linear', warmup_iters=500, warmup_ratio=0.001, step=[16, 19]) total_epochs = 20 checkpoint_config = dict(interval=1) # yapf:disable log_config = dict( interval=50, hooks=[ dict(type='TextLoggerHook'), # dict(type='TensorboardLoggerHook') ]) # yapf:enable dist_params = dict(backend='nccl') log_level = 'INFO' load_from = None resume_from = None workflow = [('train', 1)]

[ "feiaxyt@163.com" ]

feiaxyt@163.com

701944f9a0da6fa0588f63bf6e177d303b98160d

ded10c2f2f5f91c44ec950237a59225e8486abd8

/.history/2/matrix_squaring_20200420170220.py

c2d708f28a6dde0df64200c0ef45ffffb76e08f1

[]

no_license

jearistiz/Statistical-Physics-Projects

276a86407b32ded4e06b32efb2fadbd8eff8daed

d9c5b16a50856e148dc8604d92b6de3ea21fc552

refs/heads/master

2022-11-05T03:41:23.623050

2020-06-28T06:36:05

254,909,897

1

0

null

UTF-8

Python

false

17,545

py

# -*- coding: utf-8 -*- from __future__ import division import os import numpy as np import matplotlib.pyplot as plt from time import time import pandas as pd # Author: Juan Esteban Aristizabal-Zuluaga # date: 20200414 def rho_free(x,xp,beta): """Uso: devuelve elemento de matriz dsnsidad para el caso de una partícula libre en un toro infinito.""" return (2.*np.pi*beta)**(-0.5) * np.exp(-(x-xp)**2 / (2 * beta) ) def harmonic_potential(x): """Devuelve valor del potencial armónico para una posición x dada""" return 0.5*x**2 def anharmonic_potential(x): """Devuelve valor de potencial anarmónico para una posición x dada""" # return np.abs(x)*(1+np.cos(x)) #el resultado de este potencial es interesante return 0.5*x**2 - x**3 + x**4 def QHO_canonical_ensemble(x,beta): """ Uso: calcula probabilidad teórica cuántica de encontrar al oscilador armónico (inmerso en un baño térmico a temperatura inversa beta) en la posición x. Recibe: x: float -> posición beta: float -> inverso de temperatura en unidades reducidas beta = 1/T. Devuelve: probabilidad teórica cuántica en posición x para temperatura inversa beta. """ return (np.tanh(beta/2.)/np.pi)**0.5 * np.exp(- x**2 * np.tanh(beta/2.)) def rho_trotter(x_max = 5., nx = 101, beta=1, potential=harmonic_potential): """ Uso: devuelve matriz densidad en aproximación de Trotter para altas temperaturas y bajo influencia del potencial "potential". Recibe: x_max: float -> los valores de x estarán en el intervalo (-x_max,x_max). nx: int -> número de valores de x considerados (igualmente espaciados). beta: float -> inverso de temperatura en unidades reducidas. potential: func -> potencial de interacción. Debe ser función de x. Devuelve: rho: numpy array, shape=(nx,nx) -> matriz densidad en aproximación de Trotter para altas temperaturas y potencial dado. grid_x: numpy array, shape=(nx,) -> valores de x en los que está evaluada rho. dx: float -> separación entre valores contiguos de grid_x """ # Valor de la discretización de posiciones según x_max y nx dados como input dx = 2. * x_max / (nx - 1) # Lista de valores de x teniendo en cuenta discretización y x_max grid_x = np.array([i*dx for i in range(-int((nx-1)/2), int(nx/2 + 1))]) # Construcción de matriz densidad dada por aproximación de Trotter rho = np.array([ [ rho_free(x , xp, beta) * np.exp(-0.5*beta*(potential(x)+potential(xp))) for x in grid_x] for xp in grid_x]) return rho, grid_x, dx def density_matrix_squaring(rho, grid_x, N_iter = 1, beta_ini = 1, print_steps=True): """ Uso: devuelve matriz densidad luego de aplicarle algoritmo matrix squaring N_iter veces. En la primera iteración se usa matriz de densidad dada por el input rho (a temperatura inversa beta_ini); en las siguientes iteraciones se usa matriz densidad generada por la iteración inmediatamente anterior. El sistema asociado a la matriz densidad obtenida (al final de aplicar el algoritmo) está a temperatura inversa beta_fin = beta_ini * 2**(N_iter). Recibe: rho: numpy array, shape=(nx,nx) -> matriz densidad discretizada en valores dados por x_grid. grid_x: numpy array, shape=(nx,) -> valores de x en los que está evaluada rho. N_iter: int -> número de iteraciones del algoritmo. beta_ini: float -> valor de inverso de temperatura asociado a la matriz densidad rho dada como input. print_steps: bool -> decide si muestra valores de beta en cada iteración. Devuelve: rho: numpy array, shape=(nx,nx) -> matriz densidad de estado rho a temperatura inversa igual a beta_fin. trace_rho: float -> traza de la matriz densidad a temperatura inversa igual a beta_fin. Por la definición que tomamos de rho, ésta es equivalente a la función partición a dicha temperatura. beta_fin: float -> temperatura inversa del sistema asociado a rho. """ # Valor de discretixación de las posiciones dx = grid_x[1] - grid_x[0] # Cálculo del valor de beta_fin según valores beta_ini y N_iter dados como input beta_fin = beta_ini * 2 ** N_iter # Imprime infromación relevante if print_steps: print('\nbeta_ini = %.3f'%beta_ini, '\n----------------------------------------------------------------') # Itera algoritmo matrix squaring for i in range(N_iter): rho = dx * np.dot(rho,rho) # Imprime información relevante if print_steps: print(u'Iteración %d) 2^%d * beta_ini --> 2^%d * beta_ini'%(i, i, i+1)) if print_steps: print('----------------------------------------------------------------\n' + u'beta_fin = %.3f'%beta_fin) # Calcula traza de rho trace_rho = np.trace(rho)*dx return rho, trace_rho, beta_fin def save_csv(data, data_headers=None, file_name='file.csv', relevant_info=None, print_data=True): """ Uso: data debe contener listas que serán las columnas de un archivo CSV que se guardará con nombre file_name. Recibe: data: array of arrays, shape=(nx,ny) -> cada lista es una columna del archivo. data_headers: numpy array, shape=(nx,) -> nombres de las columnas file_name: str -> nombre del archivo en el que se guardarán datos. relevant_info: list of str -> información que se agrega como comentario en primeras líneas. Cada elemento de esta lista se agrega como una nueva línea. print_data: bool -> decide si imprime datos guardados, en pantalla. Devuelve: data_pdDF: pd.DataFrame -> archivo con datos formato "pandas data frame". guarda archivo con datos e inforamación relevante en primera línea. """ # Almacena datos de probabilifad en diccionario: grid_x para posiciones y x_weights para # valores de densidad de probabilidad. if file_name=='file.csv': script_dir = os.path.dirname(os.path.abspath(__file__)) #path completa para este script file_name = script_dir + '/' + 'file_name' if len(data_headers)!=len(data) or data_headers is None: data_headers = range(len(data)) print( 'Nota: no hay suficientes headers en data_headers para función save_csv().\n'+ 'Los headers usados en el archivo serán los números 0, 1, 2,...') data_dict = {} for i,column in enumerate(data): data_dict[data_headers[i]] = column # Pasamos datos a formato DataFrame de pandas. data_pdDF = pd.DataFrame(data=data_dict) # Crea archivo .csv y agrega comentarios relevantes dados como input if relevant_info is not None: with open(file_name,mode='w') as file_csv: for info in list(relevant_info): file_csv.write('# '+info+'\n') file_csv.close() # Usamos pandas para escribir en archivo en formato csv. with open(file_name,mode='a') as file_csv: data_pdDF.to_csv(file_csv) file_csv.close() else: with open(file_name,mode='w') as file_csv: data_pdDF.to_csv(file_csv) file_csv.close() # Imprime datos en pantalla. if print_data==True: print(data_pdDF) return data_pdDF def run_pi_x_sq_trotter(x_max=5., nx=201, N_iter=7, beta_fin=4, potential=harmonic_potential, potential_string = 'harmonic_potential', print_steps=True, save_data=True, file_name=None, relevant_info=None, plot=True, save_plot=True, show_plot=True): """ Uso: corre algoritmo matrix squaring iterativamente (N_iter veces). En la primera iteración se usa una matriz densidad en aproximación de Trotter a temperatura inversa beta_ini = beta_fin * 2**(-N_iter) para potencial dado por potential; en las siguientes iteraciones se usa matriz densidad generada por la iteración inmediatamente anterior. Además ésta función guarda datos de pi(x;beta) vs. x en archivo de texto y grafica pi(x;beta) comparándolo con teoría para el oscilador armónico cuántico. Recibe: x_max: float -> los valores de x estarán en el intervalo (-x_max,x_max). nx: int -> número de valores de x considerados. N_iter: int -> número de iteraciones del algoritmo matrix squaring. beta_ini: float -> valor de inverso de temperatura que queremos tener al final de aplicar el algoritmo matrix squaring iterativamente. potential: func -> potencial de interacción usado en aproximación de trotter. Debe ser función de x. potential_string: str -> nombre del potencial (con éste nombramos los archivos que se generan). print_steps: bool -> decide si imprime los pasos del algoritmo matrix squaring. save_data: bool -> decide si guarda los datos en archivo .csv. plot: bool -> decide si grafica. save_plot: bool -> decide si guarda la figura. show_plot: bool -> decide si muestra la figura en pantalla. Devuelve: rho: numpy array, shape=(nx,nx) -> matriz densidad de estado rho a temperatura inversa igual a beta_fin. trace_rho: float -> traza de la matriz densidad a temperatura inversa igual a beta_fin. Por la definición que tomamos de "rho", ésta es equivalente a la función partición en dicha temperatura. grid_x: numpy array, shape=(nx,) -> valores de x en los que está evaluada rho. """ # Cálculo del valor de beta_ini según valores beta_fin y N_iter dados como input beta_ini = beta_fin * 2**(-N_iter) # Cálculo de rho con aproximación de Trotter rho, grid_x, dx = rho_trotter(x_max, nx, beta_ini, potential) # Aproximación de rho con matrix squaring iterado N_iter veces. rho, trace_rho, beta_fin_2 = density_matrix_squaring( rho, grid_x, N_iter, beta_ini, print_steps ) print( '----------------------------------------------------------------\n' + u'Matrix squaring: beta_ini = %.3f --> beta_fin = %.3f'%(beta_ini, beta_fin_2) + u' N_iter = %d Z(beta_fin) = Tr(rho(beta_fin)) = %.3E \n'%(N_iter,trace_rho)) # Normalización de rho a 1 y cálculo de densidades de probabilidad para valores en grid_x. rho_normalized = np.copy(rho)/trace_rho x_weights = np.diag(rho_normalized) # Guarda datos en archivo .csv. script_dir = os.path.dirname(os.path.abspath(__file__)) #path completa para este script if save_data==True: # Nombre del archivo .csv en el que guardamos valores de pi(x;beta_fin). if file_name is None: file_name = script_dir+u'/pi_x-ms-%s-x_max_%.3f-nx_%d-N_iter_%d-beta_fin_%.3f.csv'\ %(potential_string,x_max,nx,N_iter,beta_fin) else: file_name = script_dir + u'/pi_x-ms-' + file_name +'.csv' # Información relevante para agregar como comentario al archivo csv. if relevant_info is None: relevant_info = [ 'pi(x;beta_fin) computed using matrix squaring algorithm and' + \ ' Trotter approximation. Parameters:', u'%s x_max = %.3f nx = %d '%(potential_string,x_max,nx) + \ u'N_iter = %d beta_ini = %.3f '%(N_iter,beta_ini,) + \ u'beta_fin = %.3f'%beta_fin ] # Guardamos valores de pi(x;beta_fin) en archivo csv. pi_x_data = [grid_x.copy(),x_weights.copy()] pi_x_data_headers = ['position_x','prob_density'] pi_x_data = save_csv(pi_x_data,pi_x_data_headers,file_name,relevant_info,print_data=0) # Gráfica y comparación con teoría if plot == True: plt.figure(figsize=(8,5)) plt.plot(grid_x, x_weights, label = 'Matrix squaring +\nfórmula de Trotter.\n$N=%d$ iteraciones\n$dx=%.3E$'%(N_iter,dx)) plt.plot(grid_x, QHO_canonical_ensemble(grid_x,beta_fin), label=u'Valor teórico QHO') plt.xlabel(u'x') plt.ylabel(u'$\pi^{(Q)}(x;\\beta)$') plt.legend(loc='best',title=u'$\\beta=%.2f$'%beta_fin) plt.tight_layout() if save_plot==True: if file_name is None: plot_name = script_dir+u'/pi_x-ms-plot-%s-x_max_%.3f-nx_%d-N_iter_%d-beta_fin_%.3f.eps'%(potential_string,x_max,nx,N_iter,beta_fin) else: plot_name = script_dir+u'/pi_x-ms-plot-'+file_name+'.eps' plt.savefig(plot_name) if show_plot==True: plt.show() plt.close() return rho, trace_rho, grid_x def Z_several_values( temp_min=1./10, temp_max=1/2., N_temp=10, save_Z_csv=True, Z_file_name = 'Z.csv', relevant_info = None, print_Z_data = True, x_max=7., nx=201, N_iter=7, potential = harmonic_potential, potential_string = 'harmonic_potential', print_steps=False, save_pi_x_data=False, plot=False, save_plot=False, show_plot=False ): """ """ beta_max = 1./temp_min beta_min = 1./temp_max N_temp = int(N_temp) beta_array = np.linspace(beta_max,beta_min,N_temp) Z = [] for beta_fin in beta_array: rho, trace_rho, grid_x = \ run_pi_x_sq_trotter(x_max=x_max, nx=nx, N_iter=N_iter, beta_fin=beta_fin, potential=potential, potential_string=potential_string, print_steps=print_steps, save_data=save_pi_x_data, plot=plot, save_plot=save_plot, show_plot=show_plot) Z.append(trace_rho) Z_data = [beta_array.copy(),1./beta_array.copy(),Z.copy()] if Z_file_name == 'Z.csv': script_dir = os.path.dirname(os.path.abspath(__file__)) #path completa para este script Z_file_name = script_dir + '/' + Z_file_name if save_Z_csv == True: Z_data_headers = ['beta','temperature','Z'] Z_data = save_csv( Z_data, Z_data_headers, relevant_info=relevant_info, file_name = Z_file_name, print_data = False ) if print_Z_data == True: print(Z_data) return Z_data # Agranda letra en texto de figuras generadas plt.rcParams.update({'font.size':15}) # Corre algoritmo matrix squaring run_algorithm = True # Parámetros físicos del algoritmo x_max=5. nx=201 N_iter=7 beta_fin=4 potential, potential_string = harmonic_potential, 'harmonic_potential' # Parámetros técnicos print_steps=True save_data=True file_name=None relevant_info=None plot=True save_plot=True show_plot=True if run_algorithm: rho, trace_rho, grid_x = \ run_pi_x_sq_trotter( x_max, nx, N_iter, beta_fin, potential, potential_string, print_steps, save_data, file_name, relevant_info, plot, save_plot, show_plot) # Borrador: cálculo de energía interna calculate_avg_energy = False script_dir = os.path.dirname(os.path.abspath(__file__)) #path completa para este script Z_file_name = script_dir+'/'+'partition-function-test-2.csv' temp_min = 1./10 temp_max = 1./2 N_temp = 10 if calculate_avg_energy: t_0 = time() Z_data = Z_several_values() t_1= time() print('<E(beta)> --> %.3f sec.'%(t_1-t_0)) # READ DATA IS OK Z_file_name = script_dir+'/'+'partition-function-test-2.csv' Z_file_read = pd.read_csv(Z_file_name, index_col=0, comment='#') beta_read = Z_file_read['beta'] beta_read = beta_read.to_numpy() temp_read = Z_file_read['temperature'] temp_read = temp_read.to_numpy() Z_read = Z_file_read['Z'] Z_read = Z_read.to_numpy() E_avg = np.gradient(-np.log(Z_read),beta_read) def Z_QHO(beta): return 0.5/np.sinh(beta/2) def E_QHO_avg_theo(beta): return 0.5/np.tanh(0.5*beta) plt.figure() plt.plot(temp_read,E_avg,label=u'$< E > Path Integral$') plt.plot(temp_read,E_QHO_avg_theo(beta_read),label=u'$< E > theory$') plt.plot(temp_read,Z_read,'v-',label=u'$ Z(T) $') plt.legend(loc='best') plt.xlabel(u'$T$') plt.ylabel(u'$< E >$ or $Z(T)$') plt.show() plt.close()

[ "jeaz.git@gmail.com" ]

jeaz.git@gmail.com

11f52d314437ea29e602494b2f3a7ab5684aebbd

9681736f96d9fd8e402600272f8a8b58fce20694

/melspec.py

aaac9b56fe678e438c386c2a1d8d106199c354de

[]

no_license

akio-kobayashi/audio_processing_pt2

b988b7d4e553cc84eb83627d101781f5742d7ad3

7eaa2d2e1b4d1f33dbbb280c4f89546f300a61a7

refs/heads/master

2022-11-22T09:22:18.411992

2020-07-17T03:35:45

276,017,834

0

null

UTF-8

Python

false

2,237

py

#!/usr/bin/python3 import os import numpy as np import scipy import h5py import re import csv import librosa import argparse def compute_melspec(signal): melspec=librosa.feature.melspectrogram(signal, sr=16000, S=None, n_fft=512, hop_length=200, win_length=400, window='hamming', center=True, pad_mode='reflect', power=2.0, n_mels=40) melspec = np.log(melspec+1.0e-8) return melspec def main(): parser = argparse.ArgumentParser() parser.add_argument('--csv', type=str, required=True) parser.add_argument('--train', type=str, required=True) parser.add_argument('--valid', type=str, required=True) args = parser.parse_args() data={} keys=[] with open(args.csv) as fp: csv_file = open(args.csv, "r") df = csv.DictReader(csv_file) for row in df: keys.append(row['filename']) data[row['filename']] = row counts={} for n in range(5): counts[n]=0 with h5py.File(args.valid, 'w') as valid: with h5py.File(args.train, 'w') as train: for key in keys: if data[key]['category'] == 'cat': label=0 elif data[key]['category'] == 'cow': label=1 elif data[key]['category'] == 'dog': label=2 elif data[key]['category'] == 'frog': label=3 elif data[key]['category'] == 'pig': label=4 else: continue counts[label] += 1 path=os.path.join('./ESC-50-master/audio',data[key]['filename']) wav,sr=librosa.load(path) mels=compute_melspec(wav) if counts[label] > 30: valid.create_group(key) valid.create_dataset(key+'/feature', data=mels) valid.create_dataset(key+'/label', data=label) else: train.create_group(key) train.create_dataset(key+'/feature', data=mels) train.create_dataset(key+'/label', data=label) if __name__ == "__main__": main()

[ "a-kobayashi@a.tsukuba-tech.ac.jp" ]

a-kobayashi@a.tsukuba-tech.ac.jp

72e0e6a314371822134735a4588f6f9f0bd8ebb6

dabc28b01defdec0dd1978f39486df000ebc8c23

/iptFilter-range.py

9fc74add06d32ce20e61a00915655cbb7a21b224

[]

no_license

jaberansariali/my-iptables-python

db10e92be3298cdb4df67f6d84ce4d892a1db0a8

0ff34f8c535e280f555ff9e3949e0937e2f0a1a5

refs/heads/master

2020-12-06T19:50:23.019142

2020-01-11T11:34:07

232,537,775

0

null

UTF-8

Python

false

2,907

py

#!/usr/bin/python3.6 ############################################################################################################################## ######### WRITE BY A.ANSARI ## ######### ## ############################################################################################################################## ##########Do not change any thing ########################### import iptc import sys ############################################Discription################################### # This the input parameter 1#Ch:input/output 2#Po:tcp/udp/all 3#: interface/all 4#S:ip/subnet or all 5#D:ip/subnet or all 6# source range ip 7# destination range ip 6#SP:portnumber/all 7#DP:portnumber/all 8#ACCEPT/DROP if len(sys.argv) > 11: print('You have specified too many arguments') sys.exit() if len(sys.argv) < 11: print('You need to specify the path to be listed') sys.exit() Chain = sys.argv[1] protocol = sys.argv[2] interface = sys.argv[3] source = sys.argv[4] destination = sys.argv[5] source_Range = sys.argv[6] destination_Range = sys.argv[7] source_port = sys.argv[8] destination_port = sys.argv[9] targets = sys.argv[10] #print(len(sys.argv)) def drop(): # chain = iptc.Chain(iptc.Table(iptc.Table.FILTER), Chain) # rule = iptc.Rule() # rule.protocol = protocol # rule.in_interface = interface # rule.add_match(match) # match = iptc.Match(rule, "iprange") # match.src_range = "192.168.1.100-192.168.1.200" # match.dst_range = "172.22.33.106" # rule.add_match(match) # target = iptc.Target(rule, targets) # rule.target = target # chain.insert_rule(rule) rule = iptc.Rule() rule.protocol = protocol match = iptc.Match(rule, protocol) match.sport = source_port match.dport = destination_port rule.add_match(match) match = iptc.Match(rule, "iprange") match.src_range = source_Range match.dst_range = destination_Range rule.src = source rule.dst = destination rule.add_match(match) rule.target = iptc.Target(rule, targets) chain = iptc.Chain(iptc.Table(iptc.Table.FILTER), Chain) chain.insert_rule(rule) def allowLoopback(): chain = iptc.Chain(iptc.Table(iptc.Table.FILTER), "INPUT") rule = iptc.Rule() rule.in_interface = "lo" target = iptc.Target(rule, "ACCEPT") rule.target = target chain.insert_rule(rule) def allowEstablished(): chain = iptc.Chain(iptc.Table(iptc.Table.FILTER), 'INPUT') rule = iptc.Rule() match = rule.create_match('state') match.state = "RELATED,ESTABLISHED" rule.target = iptc.Target(rule, 'ACCEPT') chain.insert_rule(rule) drop() #allowLoopback() #allowEstablished() #print (sys.argv[1]) #print (sys.argv[2])

[ "a.ansari@fwutech.com" ]

a.ansari@fwutech.com

3c4f13f5bdab54fff953eb3c1894c035d1da94a8

958769d6794a840643c1d7a016d811118edfe494

/Test/event.py

c8cace4645560d3ecb691d0b257ee902313c48bd

[]

no_license

d-schmitt/Rostersimulation

9a3ccd1d2ec0b4e63b9058a8985b6a1ec770bcaa

cb58c4be25403b9c41b0c55bcaf83138b1402f17

refs/heads/master

2021-09-04T00:58:01.610131

2018-01-13T17:35:24

109,983,162

0

null

2018-01-03T12:25:07

2017-11-08T14:01:01

Python

UTF-8

Python

false

10,012

py

from datetime import datetime, timedelta from random import randint #-------------------------------------------------------------------------------------------------------------------------------- # Erklaerung zu den verschiedenen Stati # working: der MA ist gerade im Dienst # none: der MA hat frei und steht - wenn keine Restriktionen dadurch verletzt werden - fuer das Rescheduling bereit # vacation: der MA hat Urlaub, damit steht er nicht fuer das Rescheduling bereit # sick: der MA ist krank und steht nicht fuer das Rescheduling bereit, waehrend er den Status sick hat, kann er die vorher # festgelegten Schichten nicht antreten und es muss ein Rescheduling stattfinden. #-------------------------------------------------------------------------------------------------------------------------------- # Ereignisklasse fuer die Simulation class Event(object): # Konstruktor def __init__(self, eDate): self.date = eDate # Datum, wann das Ereignis terminiert ist #--------------------------------------------------------------------------------------------------------------------------------- # Abschnitt: Schichtbeginn & -Ende #--------------------------------------------------------------------------------------------------------------------------------- # Spezialereignis Schichtbeginn class shiftBegin(Event): # Konstruktor def __init__(self, r, currentTime): eTime = self.terminateEvent(r, currentTime)[0] self.type = self.terminateEvent(r, currentTime)[1] Event.__init__(self, eTime) # Attribut an Superklasse weiterreichen self.sType = self.setShiftType(eTime, r) # Schichtart bestimmen # Funktion zur Bestimmung der Schichtart def setShiftType(self, dt, r): for st in r.shiftTypes: if datetime.strptime(st["startTime"], '%H:%M').hour == dt.hour: return st["name"] # Funktion zur Terminierung des naechsten Schichtbeginns def terminateEvent(self, r, currentTime): nextShift = r.getNextStartTime(currentTime.hour) nextShiftTime = nextShift[0] # Startzeit der naechsten Schicht currentDay0 = currentTime - timedelta(hours=currentTime.hour, minutes=currentTime.minute) # Zeit auf 0 Uhr setzen nextShiftDateTime = currentDay0 + timedelta(days=nextShift[2], hours=int(nextShiftTime[0:2]), minutes=int(nextShiftTime[3:5])) # Startzeit addieren return(nextShiftDateTime, nextShift[1]) # Aenderung der Zustandsvariablen der einzelnen MItarbeiter, die durch den Schichtbeginn ausgeloest wird def changeState(self, r, log_file): #print("Zustandsaenderungen Schichtbeginn " + self.sType + ":") workingList = r.getWorkingEmployees(self.date, self.sType) # Liste der Mitarbeiter alertMA = 999 for e in workingList: if e.state != "sick": r.changeEmployeeState(e.fName + " " + e.lName, "working") else: alertMA = e.eID r.printStates(log_file, alertMA) return(r) # Spezialereignis: Schichtende class shiftEnd(Event): # Konstruktor def __init__(self, sType, beginnTime, r): self.type = sType self.beginnTime = str(beginnTime) eTime = self.terminateEvent(r) Event.__init__(self, eTime) # Attribut an Superklasse weiterreichen self.sType = self.setShiftType(eTime, r) # Schichtart bestimmen # Funktion zur Bestimmung der Schichtart def setShiftType(self, dt, r): for st in r.shiftTypes: if datetime.strptime(st["endTime"], '%H:%M').hour == dt.hour: return st["name"] def terminateEvent(self, r): endTime = r.getEndByStart(self.type) beginTimeForm = datetime.strptime(self.beginnTime, '%Y-%m-%d %H:%M:%S') currentDay0 = beginTimeForm - timedelta(hours=int(beginTimeForm.hour), minutes=int(beginTimeForm.minute)) # Zeit auf 0 Uhr setzen nextEndDateTime = currentDay0 + timedelta(hours=int(endTime[0:2]), minutes=int(endTime[3:5])) # Startzeit addieren return(nextEndDateTime) # Aenderung der Zustandsvariablen der einzelnen Mitarbeiter, die durch das Schichtende ausgeloest wird def changeState(self, r, log_file): alertMA = 999 #print("Zustandsaenderungen Schichtende " + self.sType + ":") beginTimeForm = datetime.strptime(self.beginnTime, '%Y-%m-%d %H:%M:%S') workingList = r.getWorkingEmployees(beginTimeForm, self.sType) # Liste der Mitarbeiter # TODO: Arbeitsstundenberechnung anpassen for e in workingList: if e.state != "sick": r.changeEmployeeState(e.fName + " " + e.lName, "none") for st in r.shiftTypes: if st["name"] == self.sType: e.hoursWorked = e.hoursWorked + st["workingHours"] log_file.write(str(e.fName) + ": +" + str(st["workingHours"]) + " Arbeitsstunden\n") r.printStates(log_file, alertMA) return(r) #--------------------------------------------------------------------------------------------------------------------------------- # Abschnitt: Urlaubsbeginn & -Ende #--------------------------------------------------------------------------------------------------------------------------------- # Spezialereignis: Urlaubsbeginn class vacationBegin(Event): # Konstruktor def __init__(self, r, currentTime): eTime, employees = self.terminateEvent(r, currentTime) Event.__init__(self, eTime) self.employees = employees # Zeitpunkt des Eregnisses terminieren def terminateEvent(self, r, currentTime): for key, value in r.vacationBegin.items(): if key >= currentTime: return(key + timedelta(minutes=30), value) return("none","none") # Aenderung der Zustandsvariablen der, die durch den Urlaubsbeginn ausgeloest werden def changeState(self, r, log_file): alertMA = 999 for e in self.employees: r.changeEmployeeState(e, "vacation") r.printStates(log_file, alertMA) return(r) # Spezialereignis: Urlaubsende class vacationEnd(Event): # Konstruktor def __init__(self, r, currentTime): eTime, employees = self.terminateEvent(r, currentTime) Event.__init__(self, eTime) self.employees = employees # Zeitpunkt des Eregnisses terminieren def terminateEvent(self, r, currentTime): for key, value in r.vacationEnd.items(): if key >= currentTime: return(key + timedelta(hours=1), value) return("none","none") # Aenderung der Zustandsvariablen der, die durch den Urlaubsbeginn ausgeloest werden def changeState(self, r, log_file): alertMA = 999 for e in self.employees: r.changeEmployeeState(e, "none") r.printStates(log_file, alertMA) return(r) #--------------------------------------------------------------------------------------------------------------------------------- # Abschnitt: Krankheitsbeginn, Re-Scheduling & Krankheitsende #--------------------------------------------------------------------------------------------------------------------------------- # Spezialereignis: Krankheitsbeginn class illnessBegin(Event): # Konstruktor def __init__(self, r, currentTime, lastSick): eTime, eEmployee = self.terminateEvent(r, currentTime, lastSick) Event.__init__(self, eTime) self. employee = eEmployee self.duration = self.terminateDuration() # Dauer der Krankheit festlegen # TODO: besseren Algorithmus def terminateDuration(self): iTime = timedelta(days=randint(1,5)) return(iTime) # Zeitpunkt des Ereignisses terminieren def terminateEvent(self, r, currentTime, lastSick): # durch lastSick wird sichergestellt, dass kein MA krank wird, der schon krank ist iEmployee = r.determineIllness(lastSick) iTime = r.determineIllnessTime(currentTime) return(iTime, iEmployee) # Zustandaenderung durchfuehren def changeState(self, r, log_file, currentTime): alertMA = 999 # Fehlermeldung drin lassen, bis die Ergebnisse der Simulation 100% passen # Zu diesem Fall sollte es nie kommen if self.employee.state == "sick": print(self.employee.fName + " ist Waehrend der Krankheit nochmal krank geworden") r.changeEmployeeState(self.employee.fName + " " + self.employee.lName, "sick") r.printStates(log_file, alertMA) r.addSickHours(self.employee.eID, currentTime, self.duration, log_file, currentTime) return(r) # Spezialereignis: Krankheitsende class illnessEnd(Event): # Konstruktor def __init__(self, r, currentTime, employee, duration): eTime = self.terminateEvent(r, currentTime, duration) Event.__init__(self, eTime) self. employee = employee # Zeitpunkt des Ereignisses terminieren def terminateEvent(self, r, currentTime, duration): iTime = currentTime+duration-timedelta(hours=currentTime.hour, minutes=currentTime.minute)+timedelta(hours=23, minutes=30) return(iTime) # Zustandsaenderung durchfuehren def changeState(self, r, log_file): alertMA = 999 r.changeEmployeeState(self.employee.fName + " " + self.employee.lName, "none") r.printStates(log_file, alertMA) return(r)

[ "noreply@github.com" ]

d-schmitt.noreply@github.com

3ccde3ab4eb46be77a8bb20983463e9784ae1ba4

6b98d916935f03ac8f75e52a174de73040602336

/chapter 7 python/Second2.py

625609071021a156550f36b666ffba245ee78c3b

[]

no_license

AungKyawZaww9/python

61e014d4b2c5bd8fd675a59b50ca210dd410a384

627afbec42f358dfcd5909bc787029e3fb30391c

refs/heads/master

2023-06-22T00:28:48.825211

2021-07-25T19:16:15

389,271,686

0

null

UTF-8

Python

false

523

py

from Second1 import Time time1 = Time() print("The initial military time is :",time1.printMilitary()) print("\nThe initial standard time is :",time1.printstandard()) time1.setTime( 7, 37, 40) print("\n\nMilitary time after setime is :", time1.printMilitary()) print("\nStandard time after settime is :", time1.printstandard()) time1.setHour(4) time1.setMinute(3) time1.setSecond(6) print("\nMilitary time after Set.Hour,Minute,Second :",time1.printMilitary()) print("\n\nStandard tme after :", time1.printMilitary())

[ "www.aungkyawzaww1999@gmail.com" ]

www.aungkyawzaww1999@gmail.com

52c9c49a2314745c804a0f7e444d3616000acd05

479f1d9530cd7a969063957d1ef55768f4b060dc

/modules/Server.py

5aee92a2ab1073e662eb70ba8bcaff2d0b081a69

[]

no_license

kenanismayilov335/FavePorn

4b1e1287a429a844dcd772e72229f1fbccdf9872

fc8ca60f86b48a3c2211d95b6d7c168b49548f36

refs/heads/main

2023-08-29T07:25:25.021818

2021-10-16T12:39:48

null

0

null

UTF-8

Python

false

1,066

py

import datetime #SERVER STATUS ATTRIBUTES isTesting= False sessions= {} whiteList= [ 'KarmaKunh' ] blackList= [ ] #SERVER STATISTICS ATTRIBUTES pics_sent= 0 video_sent= 0 user_count= 0 all_video_research= {} all_users= [] session_reset_time= datetime.datetime.now() user_count_resetDate= datetime.datetime.now() video_sent_resetDate = datetime.datetime.now() pics_sent_resetDate = datetime.datetime.now() all_video_research_resetDate = datetime.datetime.now() all_users_resetDate = datetime.datetime.now() #SERVER STATISTICS METHODS def session_count(): return len( sessions) def add_to_whiteList( username): whiteList.append( username) def remove_from_whiteList( username): try: whiteList.remove( username) except: print("error") pass def add_to_blackList( username): blackList.append( username) def remove_from_blackList( username): try: blackList.remove( username) except: print("error") pass

[ "noreply@github.com" ]

kenanismayilov335.noreply@github.com

40298913bb95315380f176d6bd947da284ffad40

c101831acd67a49a91259bf44a508520ffd72b06

/Assignment3/domain.py

5420824c6c7ececfbfb0bc2312f8b321be18f075

[]

no_license

MihaiSilinc/Artificial-intelligence

6744989f01c2fe44d3dea5429ac88ea38ac47bdc

7576fd6aa9eff1d75da61efa2aabb5dbf76d6f56

refs/heads/master

2023-05-30T10:05:48.715575

2021-06-18T13:49:46

378,163,999

0

null

UTF-8

Python

false

15,813

py

# -*- coding: utf-8 -*- from random import * from utils import * import numpy as np from heapq import nlargest import itertools # the glass gene can be replaced with int or float, or other types # depending on your problem's representation class gene: def __init__(self): # random initialise the gene according to the representation self.__gene = choice([UP, DOWN, LEFT, RIGHT]) def get_direction(self): return self.__gene def set_direction(self, otherDirection): if otherDirection not in [UP, DOWN, LEFT, RIGHT]: raise Exception("Invalid direction!") self.__gene= otherDirection class Individual: def __init__(self, size = 0): self.__size = size #chromosome self.__chromozome = [gene() for i in range(self.__size)] self.__fitness = None def get_size(self): return self.__size def get_gene(self, genePosition): if genePosition >= self.__size: raise Exception("No gene!") return self.__chromozome[genePosition] def set_gene(self, genePosition, newGene): if genePosition >= self.__size: raise Exception("No gene!") self.__chromozome[genePosition] = newGene def get_chromosome(self): return self.__chromozome def set_chromosome(self, chromosome): self.__chromozome = chromosome def fitness(self, map, x, y): # x, y represents the starting position of the drone. posx, posy = x, y copy_map = map.copy() score = 0 score += copy_map.markVisible(x, y) for gene in self.__chromozome: direction = gene.get_direction() if direction == UP: posx = posx - 1 if not (0 <= posx <= 19) or not (0 <= posy <= 19) or (copy_map[posx][posy] == 1): posx = posx + 1 continue #score += copy_map.markVisible(posx, posy) if direction == DOWN: posx = posx + 1 if not (0 <= posx <= 19) or not (0 <= posy <= 19) or (copy_map[posx][posy] == 1): posx = posx - 1 continue #score += copy_map.markVisible(posx, posy) if direction == LEFT: posy = posy - 1 if not (0 <= posx <= 19) or not (0 <= posy <= 19) or (copy_map[posx][posy] == 1): posy = posy + 1 continue #score += copy_map.markVisible(posx, posy) if direction == RIGHT: posy = posy + 1 if not (0 <= posx <= 19) or not (0 <= posy <= 19) or (copy_map[posx][posy] == 1): posy = posy - 1 continue #score += copy_map.markVisible(posx, posy) score += copy_map.markVisible(posx, posy) self.__fitness = score return self.__fitness def mutate(self, mutateProbability = 0.04): if random() < mutateProbability: mutated_gene = randrange(self.__size) self.__chromozome[mutated_gene].set_direction(choice([UP, DOWN, LEFT, RIGHT])) # perform a mutation with respect to the representation def crossover(self, otherParent, crossoverProbability = 0.7): offspring1, offspring2 = Individual(self.__size), Individual(self.__size) if random() < crossoverProbability: border = randrange(0, self.__size) for i in range(border): offspring1.set_gene(i, self.get_gene(i)) offspring2.set_gene(i, otherParent.get_gene(i)) for j in range(border, self.__size): offspring1.set_gene(j, otherParent.get_gene(j)) offspring2.set_gene(j, self.get_gene(j)) else: offspring1.set_chromosome(self.get_chromosome()) offspring2.set_chromosome(otherParent.get_chromosome()) return offspring1, offspring2 class Population(): def __init__(self, chromozomeSize = 0, initialX=0, initialY=0, map = None): self.__chromozomeSize = chromozomeSize # chromozome size self.__individuals = [] self.__x = initialX self.__y = initialY self.map = map self.__individuals_scores = {} # for ind in self.__individuals: # self.__individuals_scores[ind] = 0 self.__total = 0 self.__best = 0 self.__bestIndividual = None def clear_individuals(self): self.__individuals.clear() self.__individuals_scores = {} def evaluate(self): # evaluates the population self.__total = 0 self.__best = 0 self.__bestIndividual = None for x in self.__individuals: individual_score = x.fitness(self.map, self.__x, self.__y) self.__individuals_scores[x] = individual_score self.__total += individual_score if individual_score > self.__best: self.__best = individual_score self.__bestIndividual = x return self.__total, self.__best def add_individuals_scores(self, individuals_scores): # individuals_scores - dict with individuals and scores for i in individuals_scores: self.__individuals.append(i) self.__individuals_scores[i] = individuals_scores[i] if individuals_scores[i] >= self.__best: self.__best = individuals_scores[i] self.__bestIndividual = i self.__total += individuals_scores[i] def __len__(self): return len(self.__individuals) @property def populationSize(self): return len(self.__individuals) @property def average(self): return self.__total / len(self.__individuals) @property def total(self): return self.__total @property def best(self): return self.__best @property def individuals(self): return self.__individuals @property def individuals_with_scores(self): return self.__individuals_scores @property def bestIndividual(self): return self.__bestIndividual def getStartingPosition(self): return self.__x, self.__y def get_chromozome_size(self): return self.__chromozomeSize def random_individuals(self, size): # generate a population with given size self.__individuals_scores = {} self.__individuals = [Individual(self.__chromozomeSize) for i in range(size)] self.evaluate() def set_individuals(self, individuals): # generate a population from list of individuals self.__individuals_scores = {} self.__individuals.clear() for i in individuals: if len(i.get_chromosome()) != self.__chromozomeSize: raise Exception('Incompatible individuals!') self.__individuals.append(i) self.evaluate() def selection(self, k = 0): selected = set() while(len(selected) != k): individual = np.random.choice(self.__individuals, 1, False, [(self.__individuals_scores[y] / self.__total) for y in self.__individuals]) selected.add(individual[0]) return selected def bestK(self, k = 2): a = nlargest(k, self.__individuals_scores, key=self.__individuals_scores.get) x1 = [] x2 = [] for i in self.__individuals: x1.append(self.__individuals_scores[i]) for i in a: x2.append(self.__individuals_scores[i]) x1.sort(reverse=True) print(x1) print(x2) print(len(self.__individuals)) print(len(self.__individuals_scores)) print('---------------') return a def filter(self, k): # filter , keep the best individuals filtered = self.bestK(k) survivors = {} for ind in filtered: survivors[ind] = self.__individuals_scores[ind] self.clear_individuals() self.__best = 0 self.__total = 0 self.__bestIndividual = None self.add_individuals_scores(survivors) def find_optimal_solution(self): genes = [gene(), gene(), gene(), gene()] genes[0].set_direction(UP) genes[1].set_direction(DOWN) genes[2].set_direction(LEFT) genes[3].set_direction(RIGHT) ALL_CHROMOSOMES = itertools.product(genes, repeat=self.__chromozomeSize) best_score = 0 best_individual = None i = 0 for c in ALL_CHROMOSOMES: i += 1 print(i) chromosome = list(c) print(chromosome) ind = Individual(self.__chromozomeSize) ind.set_chromosome(chromosome) score = ind.fitness(self.map, self.__x, self.__y) if score > best_score: best_individual = ind best_score = score return best_individual.get_chromosome(), best_score # a = [LEFT, RIGHT, UP, DOWN] # x = itertools.product(a, repeat=10) # i = 0 # for e in x: # print(e) # i += 1 # print(i) class Map(): def __init__(self, n = 20, m = 20): self.n = n self.m = m self.surface = np.zeros((self.n, self.m)) # creates a random map of given size def randomMap(self, fill = 0.2, n = 20, m = 20): self.n = n self.m = m self.surface = np.zeros((self.n, self.m)) for i in range(self.n): for j in range(self.m): if random() <= fill: self.surface[i][j] = 1 else: self.surface[i][j] = 0 def __getitem__(self, key): return self.surface[key] def get_size(self): return self.n, self.m def __str__(self): string="" for i in range(self.n): for j in range(self.m): string = string + str(int(self.surface[i][j])) string = string + "\n" return string def copy(self): copy = Map(self.n, self.m) copy.surface = np.array(self.surface, copy=True) return copy def readUDMSensors(self, x,y): readings=[0,0,0,0] # UP xf = x - 1 while ((xf >= 0) and (self.surface[xf][y] == 0)): xf = xf - 1 readings[UP] = readings[UP] + 1 # DOWN xf = x + 1 while ((xf < self.n) and (self.surface[xf][y] == 0)): xf = xf + 1 readings[DOWN] = readings[DOWN] + 1 # LEFT yf = y + 1 while ((yf < self.m) and (self.surface[x][yf] == 0)): yf = yf + 1 readings[LEFT] = readings[LEFT] + 1 # RIGHT yf = y - 1 while ((yf >= 0) and (self.surface[x][yf] == 0)): yf = yf - 1 readings[RIGHT] = readings[RIGHT] + 1 return readings def markVisible(self, x, y): marked = 0 if self.surface[x][y] == 0: marked += 1 self.surface[x][y] = 2 # UP xf = x - 1 while ((xf >= 0) and (self.surface[xf][y] != 1)): # add to the count if it wasn't marked previously if self.surface[xf][y] == 0: marked += 1 self.surface[xf][y] = 2 xf = xf - 1 # DOWN xf = x + 1 while ((xf < self.n) and (self.surface[xf][y] != 1)): # add to the count if it wasn't marked previously if self.surface[xf][y] == 0: marked += 1 self.surface[xf][y] = 2 xf = xf + 1 # LEFT yf = y + 1 while ((yf < self.m) and (self.surface[x][yf] != 1)): # add to the count if it wasn't marked previously if self.surface[x][yf] == 0: marked += 1 self.surface[x][yf] = 2 yf = yf + 1 # RIGHT yf = y - 1 while ((yf >= 0) and (self.surface[x][yf] != 1)): # add to the count if it wasn't marked previously if self.surface[x][yf] == 0: marked += 1 self.surface[x][yf] = 2 yf = yf - 1 return marked # def image(self, colour=BLUE, background=WHITE): # imagine = pygame.Surface((400, 400)) # brick = pygame.Surface((20, 20)) # destination = pygame.Surface((20, 20)) # roadGreedy = pygame.Surface((20, 20)) # roadAStar = pygame.Surface((20, 20)) # common_road = pygame.Surface((20, 20)) # brick.fill(BLUE) # imagine.fill(WHITE) # destination.fill(RED) # # for i in range(self.n): # for j in range(self.m): # if (self.surface[i][j] == 1): # imagine.blit(brick, (j * 20, i * 20)) # if (self.surface[i][j] == 2): # imagine.blit(destination, (j * 20, i * 20)) # if (self.surface[i][j] == 3): # imagine.blit(roadGreedy, (j * 20, i * 20)) # if (self.surface[i][j] == 4): # imagine.blit(roadAStar, (j * 20, i * 20)) # if (self.surface[i][j] == 5): # imagine.blit(common_road, (j * 20, i * 20)) # # return imagine def get_neighbours(self, xi, yi): possibilities = [(xi + 1, yi), (xi - 1, yi), (xi, yi + 1), (xi, yi - 1)] # squares have coordinates between 0 and 19 first_cut = list(filter(lambda t: (0 <= t[0] <= 19 and 0 <= t[1] <= 19), possibilities)) return list(filter(lambda t: (self.surface[t[0]][t[1]] == 0 or self.surface[t[0]][t[1]] >= 2), first_cut)) def convertChromozomeToPath(self, chromozome, x, y): path = [] path.append([x,y]) posx = x posy = y for gene in chromozome: direction = gene.get_direction() if direction == UP: posx = posx - 1 if not (0 <= posx <= 19) or not (0 <= posy <= 19) or (self.surface[posx][posy] == 1): posx = posx + 1 continue # score += copy_map.markVisible(posx, posy) elif direction == DOWN: posx = posx + 1 if not (0 <= posx <= 19) or not (0 <= posy <= 19) or (self.surface[posx][posy] == 1): posx = posx - 1 continue # score += copy_map.markVisible(posx, posy) elif direction == LEFT: posy = posy - 1 if not (0 <= posx <= 19) or not (0 <= posy <= 19) or (self.surface[posx][posy] == 1): posy = posy + 1 continue # score += copy_map.markVisible(posx, posy) elif direction == RIGHT: posy = posy + 1 if not (0 <= posx <= 19) or not (0 <= posy <= 19) or (self.surface[posx][posy] == 1): posy = posy - 1 continue # score += copy_map.markVisible(posx, posy) print('added') path.append([posx, posy]) return path class Statistics: def __init__(self): self.runs = [] self.best = [] self.std = [] def add_generation_score(self, score): self.runs.append(score) def add_best_score(self, score): self.best.append(score) def add_standard_deviation(self, std): self.std.append(std) def get_scores(self): return self.runs, self.best, self.std

[ "mihaisilinc@yahoo.com" ]

mihaisilinc@yahoo.com

262a5197dd5ba8597678e06daaf76597fdf97d15

a4c9b7353a31d9aac6919fbac601cf365eee9cb7

/social_example_project/project_specific.py

19ff00b4d651ff7ae129143a36e8945577b6f673

[]

no_license

crass/django-social

b885e788dd4ace57335141e7fef4106474b70c37

cce7516dbf16509ba1e6e4bb55c6c0b7c8b9c7d9

refs/heads/master

2020-04-01T18:43:31.889103

2012-03-05T07:44:28

3,245,104

0

null

UTF-8

Python

false

1,234

py

from django import shortcuts from django.db.models import signals from django.contrib.auth.models import User from social.notification import Notification # deploy contrib for a quick try from social.contrib import comments # auto subscribe users to objects they comment comments.signals.comment_was_posted.connect(comments.comments_subscription) # auto notify subscribers of an object when it receives a comment # full blown, reusable: # comments.signals.comment_was_posted.connect(comments.comment_notification) # quickstart example: def comment_notification(sender, comment=None, **kwargs): Notification(comment=comment, template='comment_quickstart', subscribers_of=comment.content_object).emit() comments.signals.comment_was_posted.connect(comment_notification) from social.contrib import auth auth.signals.post_save.connect(auth.subscribe_user_to_himself, sender=User) auth.subscribe_existing_users_to_themselves(None) def user_detail(request, username, template_name='auth/user_detail.html', extra_context=None): context = { 'user': shortcuts.get_object_or_404(User, username=username) } context.update(extra_context or {}) return shortcuts.render(request, template_name, context)

[ "jamespic@gmail.com" ]

jamespic@gmail.com

2968955f3edef66592f8efcbb0a5fc9bdd9b1e10

1bdbf12e6fa1091beeb4ce0d923664e779cda509

/tuples.py

7962b449b5c5faf5de4dbe4080c489c970d8225c

[]

no_license

balajisaikumar2000/Python-Snippets

d61176f3a3752861c5a355c09b27c418727b90fd

b36a642b99cb2517438f773d21654ae4fef2cc05

refs/heads/master

2023-01-24T05:57:03.654796

2020-12-05T13:38:58

null

0

null

UTF-8

Python

false

357

py

#immutable x = tuple(("apple","banana","cherry")) y = list(x) y[0] = "mango" x = tuple(y) print(x) #creating single tuple a = ("balaji") #this will cause an error print(type(a)) b= ("balaji",) #correct process print(type(b)) #count(): z = (1,2,4,1,2,6,7,8,4,6) print(z.count(2)) #index(): m = (1,2,3,6,3,5,6,3,9,6,1) print(m.index(6))

[ "balajisaikumar3@gmail.com" ]

balajisaikumar3@gmail.com

8739c3d861b4a52332c4d5679e34725d6ed4d01e

bee554d289d8f18fb04dea4adaaccb03b28e5efb

/Re/Demo1.py

0b8c80a8a1a0dea001c3476e416326b17a91ca1f

[]

no_license

loveCanopy/Python

f24e1fce68850e895dcf24b4da6b65928ba43caf

4bf8838b7b73596f502349b1450c7c48767e3a57

refs/heads/master

2021-01-10T08:17:05.101714

2017-03-14T08:59:42

54,179,629

0

null

UTF-8

Python

false

431

py

#compile match split sub import re pattern=re.compile(r'hello') match=pattern.match("hello world") m=re.match(r"hell",'hellworld') n=re.match(r"world$","hellworld") p=re.compile(r'\d+') r=p.split("one1two2three3four4") f=p.findall("one1two2three3four4") l=re.search(r'he','worhell') print(l) p2=re.compile(r'[abc]') k=p2.sub('O','Markmarkmarkmark',count=2) print(k) print(f) print(r) print(n) print(m.group()) print(match.group())

[ "1039431583@qq.com" ]

1039431583@qq.com

d63652dbb64052fd613ea28b3451203c2542516c

9fc4767cb81fa96c920ac2a59a74448c9875c574

/ABC/ABC067/a.py

b61046b2b452f1aff06aff4dacc332975578ee39

[]

no_license

temp176/AtCoder

ce6a2070d8d3931256fae29303f6efc8d50902c8

70c5489cfdff95cb400791b63ff4a8fc3e9c3b9b

refs/heads/master

2021-06-08T17:45:59.475097

2020-05-17T05:32:46

132,405,875

0

null

UTF-8

Python

false

139

py

A,B=[int(i) for i in input().split()] if A % 3 == 0 or B % 3 == 0 or (A + B) % 3 == 0: print('Possible') else: print('Impossible')

[ "teheodks@gmail.com" ]

teheodks@gmail.com

0aab8557c40a843eb79d544ec0964ebe1827f7b2

8902f2f30a35f0a87b3d40196fda7c74a883a535

/core/tests/conftest.py

95fc6217fe80f533e8cf88898e4482ae83bb9759

[]

no_license

sleonardoaugusto/scanpy

e970e89c74818b438689586cd181141cb37b9e9e

14d61d06f62a9840ad94b887512ab6da4b6744e9

refs/heads/main

2023-08-05T12:24:16.318014

2021-09-06T07:16:42

2021-09-07T21:55:16

398,474,051

0

null

UTF-8

Python

false

1,172

py

from pathlib import Path import pytest from core.pages.pages import Login, Home, Settings from core.webdriver import Driver from scrapper.scrapper import BASE_URL @pytest.fixture(scope='session') def fix_user(): class User: username = 'bobbybackupy' password = 'Argyleawesome123!' secret_key = 'J6PMJ5GNXMGVU47A' return User() @pytest.fixture(scope='session') def fix_login_page(): with Driver(path='webdrivers/chromedriver') as driver: login_page = Login(webdriver=driver, url=BASE_URL) login_page.open() yield login_page @pytest.fixture(scope='session') def fix_home_page(fix_login_page, fix_user): webdriver = fix_login_page.webdriver fix_login_page.login(username=fix_user.username, password=fix_user.password) home = Home(webdriver) yield home @pytest.fixture(scope='session') def fix_settings_page(fix_home_page, fix_user): webdriver = fix_home_page.webdriver fix_home_page.navbar.open_settings(fix_user.secret_key) settings = Settings(webdriver) yield settings @pytest.fixture(autouse=True, scope='session') def delete_logs(): Path.unlink(Path('log.log'))

[ "sleonardoaugusto@gmail.com" ]

sleonardoaugusto@gmail.com

34cca73a90032fba4534e5ecaff98d67950e3f3b

3fef5ea4a88bc42a0acdb7ae581639ebbb3dd962

/tb_store/tb_store/apps/users/urls.py

417f3eb0393e93d10a2fd7acd9b0985ab7c96cbc

[]

no_license

ducgt/Django-Store

96476597811c6db772e196d9cd56ef9516e1e287

f68b7dd657b2a9c5769a3a657be083dad5b2ff11

refs/heads/master

2021-04-21T20:54:54.811437

2019-07-22T08:16:44

2019-07-22T08:17:15

null

0

null

UTF-8

Python

false

1,203

py

from django.conf.urls import url from rest_framework import routers from . import views from rest_framework_jwt.views import obtain_jwt_token urlpatterns = [ url(r'^usernames/(?P<username>\w{5,20})/count/$', views.UsernameCountView.as_view()), url(r'^mobiles/(?P<mobile>1[3-9]\d{9})/count/$', views.MobileCountView.as_view()), url(r'^usernames/$', views.UserView.as_view()), # url(r'^authorizations/$', obtain_jwt_token), url(r"^user/$", views.UserDetailView.as_view()), url(r"^email/$", views.EmailView.as_view()), url(r'^emails/verification/$', views.VerifyEmailView.as_view()), url(r'^browse_histories/$', views.UserBrowsingHistoryView.as_view()), url(r'^password/$', views.PassWord2.as_view()), url(r'^authorizations/$', views.UserAuthorizeView.as_view()), ] router = routers.DefaultRouter() router.register(r'addresses', views.AddressViewSet, base_name='addresses') urlpatterns += router.urls # POST /addresses/ 新建 -> create # PUT /addresses/<pk>/ 修改 -> update # GET /addresses/ 查询 -> list # DELETE /addresses/<pk>/ 删除 -> destroy # PUT /addresses/<pk>/status/ 设置默认 -> status # PUT /addresses/<pk>/title/ 设置标题 -> title

[ "15670339118@qq.com" ]

15670339118@qq.com

34e8b079677924bf95cde928c5a71e25e99cf66d

0e294ec96263fafc3f39aa2f4bb2fff49569582e

/bach_resize.py

370475c1ad81d44b6ac4d5448775c00103b339ee

[]

no_license

dailing/mask_rcnn

6988f529b57fc2bfe3f79f060b3b6eeaec79330f

f499c8f98c5e9a9a23d7cbe8c1036ada81e16655

refs/heads/master

2020-05-25T10:37:22.463188

2020-04-19T10:32:04

187,763,422

0

null

UTF-8

Python

false

753

py

import os.path import cv2 from tqdm import tqdm from random import shuffle from util.augment import Compose, FundusAOICrop, Resize, ResizeKeepAspectRatio input_dir = '../dataset/' out_dir = '../dataset/small_pic' os.makedirs(out_dir, exist_ok=True) files = os.listdir(input_dir) shuffle(files) for i in tqdm(files): ofile = f'{out_dir}/{i}' if os.path.exists(ofile): continue transform = Compose( (, ResizeKeepAspectRatio(299)) ) img = cv2.imread(f'{input_dir}/{i}', cv2.IMREAD_COLOR) img = transform(img) ok, content = cv2.imencode('.png', img) assert ok is True with open(ofile, 'wb') as f: f.write(content) # cv2.imwrite(ofile, img, dict(ext='png'))

[ "qzyz_dailing@163.com" ]

qzyz_dailing@163.com

98d55bb8d3c2863135d11c2f7e2e4a05ccf5512e

95e42bbdd441f70bd5647668de0b609eb46d5edf

/Part 3 - Classification/Section 15 - K-Nearest Neighbors (K-NN)/my_knn.py

a2ee7ecebce220b0ade5b9dacd34cc208ee76e31

[]

no_license

varunnaagaraj/ML-A-Z_Course

1b4f90e8ab4e00a670ea1d3fe3d0bd2575bf876f

ad36d9ebcae7d04e9a8015508b9dc87f26146283

refs/heads/master

2020-05-02T23:59:53.165017

2019-03-28T23:16:47

178,296,170

0

null

UTF-8

Python

false

2,568

py

# K Nearest Neighbors # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv('Social_Network_Ads.csv') X = dataset.iloc[:, [2,3]].values y = dataset.iloc[:, 4].values # Splitting the dataset into the Training set and Test set from sklearn.cross_validation import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0) # Feature scaling from sklearn.preprocessing import StandardScaler sc_X = StandardScaler() X_train = sc_X.fit_transform(X_train) X_test = sc_X.transform(X_test) # Fitting the logistic regression model from sklearn.neighbors import KNeighborsClassifier classifier = KNeighborsClassifier(n_neighbors=5, metric="minkowski", p=2) classifier.fit(X_train, y_train) #Prediction y_pred = classifier.predict(X_test) #Confusion Matrix from sklearn.metrics import confusion_matrix cm = confusion_matrix(y_test, y_pred) #Visualization from matplotlib.colors import ListedColormap X_set, y_set = X_train, y_train X1, X2 = np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.01), np.arange(start = X_set[:, 1].min() - 1, stop = X_set[:, 1].max() + 1, step = 0.01)) plt.contourf(X1, X2, classifier.predict(np.array([X1.ravel(), X2.ravel()]).T).reshape(X1.shape), alpha = 0.75, cmap = ListedColormap(('red', 'green'))) plt.xlim(X1.min(), X1.max()) plt.ylim(X2.min(), X2.max()) for i, j in enumerate(np.unique(y_set)): plt.scatter(X_set[y_set == j, 0], X_set[y_set == j, 1], c = ListedColormap(('red', 'green'))(i), label = j) plt.title('K-NN (Training set)') plt.xlabel('Age') plt.ylabel('Estimated Salary') plt.legend() plt.show() from matplotlib.colors import ListedColormap X_set, y_set = X_test, y_test X1, X2 = np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.01), np.arange(start = X_set[:, 1].min() - 1, stop = X_set[:, 1].max() + 1, step = 0.01)) plt.contourf(X1, X2, classifier.predict(np.array([X1.ravel(), X2.ravel()]).T).reshape(X1.shape), alpha = 0.75, cmap = ListedColormap(('red', 'green'))) plt.xlim(X1.min(), X1.max()) plt.ylim(X2.min(), X2.max()) for i, j in enumerate(np.unique(y_set)): plt.scatter(X_set[y_set == j, 0], X_set[y_set == j, 1], c = ListedColormap(('red', 'green'))(i), label = j) plt.title('K-NN (Training set)') plt.xlabel('Age') plt.ylabel('Estimated Salary') plt.legend() plt.show()

[ "varun.naagaraj@gmail.com" ]

varun.naagaraj@gmail.com

8dfc8d52199cc913852b7553e3552f508e77e2ca

b9bd670454d308c49f80156d6f493be97d2ce696

/Zhihu/Zhihu/settings.py

2e5c9b9216d2481b14236bdc2e976664a2b6391d

[]

no_license

CP-0/py_spider_codes

2cf3ee2dd8143891c0e28c5298a3e902b9a35fc4

d7875b33c21d06b3a9af952248bf9f3acd50db93

refs/heads/master

2021-09-20T01:13:38.914499

2018-08-02T05:54:30

112,149,605

83

1

null

UTF-8

Python

false

3,372

py

# -*- coding: utf-8 -*- # Scrapy settings for Zhihu project # # For simplicity, this file contains only settings considered important or # commonly used. You can find more settings consulting the documentation: # # http://doc.scrapy.org/en/latest/topics/settings.html # http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html # http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html BOT_NAME = 'Zhihu' SPIDER_MODULES = ['Zhihu.spiders'] NEWSPIDER_MODULE = 'Zhihu.spiders' # Crawl responsibly by identifying yourself (and your website) on the user-agent # USER_AGENT = 'Zhihu (+http://www.yourdomain.com)' # Obey robots.txt rules ROBOTSTXT_OBEY = False # Configure maximum concurrent requests performed by Scrapy (default: 16) # CONCURRENT_REQUESTS = 32 # Configure a delay for requests for the same website (default: 0) # See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs # DOWNLOAD_DELAY = 3 # The download delay setting will honor only one of: # CONCURRENT_REQUESTS_PER_DOMAIN = 16 # CONCURRENT_REQUESTS_PER_IP = 16 # Disable cookies (enabled by default) # COOKIES_ENABLED = False # Disable Telnet Console (enabled by default) # TELNETCONSOLE_ENABLED = False # Override the default request headers: DEFAULT_REQUEST_HEADERS = { 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Language': 'en', 'authorization': 'oauth c3cef7c66a1843f8b3a9e6a1e3160e20', 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.94 Safari/537.36' } # Enable or disable spider middlewares # See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html # SPIDER_MIDDLEWARES = { # 'Zhihu.middlewares.ZhihuSpiderMiddleware': 543, # } # Enable or disable downloader middlewares # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html # DOWNLOADER_MIDDLEWARES = { # 'Zhihu.middlewares.MyCustomDownloaderMiddleware': 543, # } # Enable or disable extensions # See http://scrapy.readthedocs.org/en/latest/topics/extensions.html # EXTENSIONS = { # 'scrapy.extensions.telnet.TelnetConsole': None, # } # Configure item pipelines # See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html ITEM_PIPELINES = { 'Zhihu.pipelines.MongoPipeline': 300, } # Enable and configure the AutoThrottle extension (disabled by default) # See http://doc.scrapy.org/en/latest/topics/autothrottle.html # AUTOTHROTTLE_ENABLED = True # The initial download delay # AUTOTHROTTLE_START_DELAY = 5 # The maximum download delay to be set in case of high latencies # AUTOTHROTTLE_MAX_DELAY = 60 # The average number of requests Scrapy should be sending in parallel to # each remote server # AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 # Enable showing throttling stats for every response received: # AUTOTHROTTLE_DEBUG = False # Enable and configure HTTP caching (disabled by default) # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings # HTTPCACHE_ENABLED = True # HTTPCACHE_EXPIRATION_SECS = 0 # HTTPCACHE_DIR = 'httpcache' # HTTPCACHE_IGNORE_HTTP_CODES = [] # HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage' MONGO_URI = 'localhost' MONGO_DATABASE = 'zhihu'

[ "cyj001@cyj721001.uu.me" ]

cyj001@cyj721001.uu.me

aa39e1ee08966f77ab522c5c903530e0749a334e

4114590f97ca3734862c9255f1a4bbc730ded8d7

/manage.py

968edc33bd4ccde3e25d2a75a4000a4e62c18250

[]

no_license

filipe027/probex2018

dea369f784f3c3ab82787736a79d3ee0a09d79f8

37c5bb12987cb39c0fe682d5b912f25b8dcd92c7

refs/heads/master

2020-03-23T05:53:22.024489

2019-11-10T22:10:38

141,173,565

0

null

UTF-8

Python

false

553

py

#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "Chuvas.settings") try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv)

[ "filipe.freitas@cear.ufpb.br" ]

filipe.freitas@cear.ufpb.br

24b38a0832ea721afae965b47d43a1cd21e4b07a

d4b67c170af87fb407d8088e1fbb8e3600231533

/optimize_cage.py

abff3ee09cd1c2afe80a318c3456a2f3bcdd6245

[ "MIT" ]

permissive

qingmeizhujiu/deep_cage

404708d1c6b1659ab9b7bab6c0c9cc32f051740d

da4c07dcc5c10d44c1b040fbbd0d897ea5ab1f98

refs/heads/master

2022-12-07T04:26:51.625134

2020-09-08T08:25:11

null

0

null

UTF-8

Python

false

20,963

py

""" Optimize the initial cage for a new source shape """ from __future__ import print_function from pprint import pprint import traceback import sys import datetime import shutil import torch import os import numpy as np import pymesh from pytorch_points.misc import logger from pytorch_points.network.operations import faiss_knn from pytorch_points.network.geo_operations import mean_value_coordinates_3D, edge_vertex_indices from pytorch_points.utils.pc_utils import load, save_ply, save_ply_with_face, center_bounding_box from pytorch_points.utils.geometry_utils import get_edge_points from pytorch_points.utils.pytorch_utils import weights_init, check_values, save_network, load_network, \ clamp_gradient_norm, tolerating_collate, clamp_gradient, fix_network_parameters from pytorch_points.network.model_loss import MeshLaplacianLoss import network2 as networks from common import loadInitCage, build_dataset, deform_with_MVC, read_trimesh from losses import MVCRegularizer from option import DeformationOptions from matplotlib.colors import Normalize from matplotlib import cm import openmesh as om import pandas as pd class MyOptions(DeformationOptions): def initialize(self, parser): parser.add_argument( "--model", type=str, default="/home/mnt/points/data/MPI-FAUST/training/registrations/tr_reg_010.ply") parser.add_argument("--use_cage", type=str, help="path to optimized cage") parser.add_argument("--opt_lap", action="store_true", help="optimize deformed shape using laplacian") return super().initialize(parser) def parse(self): super().parse() assert(self.opt.source_model is not None), "source model is required for optimize_cage" if not isinstance(self.opt.source_model, str): self.opt.source_model = self.opt.source_model[0] return self.opt def visualize_correspondence(opt, source_shape, source_face, target_shape, target_face, corres_1, corres_2): """ source_shape (1,N,3) source_face (1,F,3) target_shape (1,N2,3) target_face (1,F2,3) corres_face_1 (P) corres_face_2 (P) """ # save these points with color codes P = corres_2.shape[0] assert(corres_1.shape[0] == corres_2.shape[0]) corres_1 = corres_1.cpu().numpy().reshape(-1) corres_2 = corres_2.cpu().numpy().reshape(-1) normalize = Normalize(vmin=0, vmax=corres_1.shape[0]) cmap = cm.get_cmap("jet") colors_picked = cmap(normalize(np.arange(P, dtype=np.float32)))[:, :3] colors_source = np.ones((source_face.shape[1], 3), dtype=np.float32) colors_source[corres_1, :] = colors_picked save_ply_with_face(source_shape[0].cpu().detach().numpy(), source_face[0].cpu().detach().numpy(), os.path.join(opt.log_dir, opt.subdir, "source_corr.ply"), colors_source) colors_target = np.ones((target_face.shape[1], 3), dtype=np.float32) colors_target[corres_2, :] = colors_picked save_ply_with_face(target_shape[0].cpu().detach().numpy(), target_face[0].cpu().detach().numpy(), os.path.join(opt.log_dir, opt.subdir, "target_corr.ply"), colors_target) def optimize(opt): """ weights are the same with the original source mesh target=net(old_source) """ # load new target if opt.is_poly: target_mesh = om.read_polymesh(opt.model) else: target_mesh = om.read_trimesh(opt.model) target_shape_arr = target_mesh.points() target_shape = target_shape_arr.copy() target_shape = torch.from_numpy( target_shape[:, :3].astype(np.float32)).cuda() target_shape.unsqueeze_(0) target_faces_arr = target_mesh.face_vertex_indices() target_faces = target_faces_arr.copy() target_faces = torch.from_numpy( target_faces[:, :3].astype(np.int64)).cuda() target_faces.unsqueeze_(0) states = torch.load(opt.ckpt) if "states" in states: states = states["states"] cage_v = states["template_vertices"].transpose(1, 2).cuda() cage_f = states["template_faces"].cuda() shape_v = states["source_vertices"].transpose(1, 2).cuda() shape_f = states["source_faces"].cuda() if os.path.isfile(opt.model.replace(os.path.splitext(opt.model)[1], ".picked")) and os.path.isfile(opt.source_model.replace(os.path.splitext(opt.source_model)[1], ".picked")): new_label_path = opt.model.replace(os.path.splitext(opt.model)[1], ".picked") orig_label_path = opt.source_model.replace(os.path.splitext(opt.source_model)[1], ".picked") logger.info("Loading picked labels {} and {}".format(orig_label_path, new_label_path)) new_label = pd.read_csv(new_label_path, delimiter=" ",skiprows=1, header=None) orig_label = pd.read_csv(orig_label_path, delimiter=" ",skiprows=1, header=None) orig_label_name = orig_label.iloc[:,5] new_label_name = new_label.iloc[:,5].tolist() new_to_orig_idx = [] for i, name in enumerate(new_label_name): matched_idx = orig_label_name[orig_label_name==name].index if matched_idx.size == 1: new_to_orig_idx.append((i, matched_idx[0])) new_to_orig_idx = np.array(new_to_orig_idx) if new_label.shape[1] == 10: new_vidx = new_label.iloc[:,9].to_numpy()[new_to_orig_idx[:,0]] target_points = target_shape[:, new_vidx, :] else: new_label_points = torch.from_numpy(new_label.iloc[:,6:9].to_numpy().astype(np.float32)) target_points = new_label_points.unsqueeze(0).cuda() target_points, new_vidx, _ = faiss_knn(1, target_points, target_shape, NCHW=False) target_points = target_points.squeeze(2) # B,N,3 new_label[9] = new_vidx.squeeze(0).squeeze(-1).cpu().numpy() new_label.to_csv(new_label_path, sep=" ", header=[str(new_label.shape[0])]+[""]*(new_label.shape[1]-1), index=False) target_points = target_points[:, new_to_orig_idx[:,0], :] target_points = target_points.cuda() source_shape, _ = read_trimesh(opt.source_model) source_shape = torch.from_numpy(source_shape[None, :,:3]).float() if orig_label.shape[1] == 10: orig_vidx = orig_label.iloc[:,9].to_numpy()[new_to_orig_idx[:,1]] source_points = source_shape[:, orig_vidx, :] else: orig_label_points = torch.from_numpy(orig_label.iloc[:,6:9].to_numpy().astype(np.float32)) source_points = orig_label_points.unsqueeze(0) # find the closest point on the original meshes source_points, new_vidx, _ = faiss_knn(1, source_points, source_shape, NCHW=False) source_points = source_points.squeeze(2) # B,N,3 orig_label[9] = new_vidx.squeeze(0).squeeze(-1).cpu().numpy() orig_label.to_csv(orig_label_path, sep=" ", header=[str(orig_label.shape[0])]+[""]*(orig_label.shape[1]-1), index=False) source_points = source_points[:,new_to_orig_idx[:,1],:] _, source_center, _ = center_bounding_box(source_shape[0]) source_points -= source_center source_points = source_points.cuda() # # shift target so that the belly match # try: # orig_bellyUp_idx = orig_label_name[orig_label_name=="bellUp"].index[0] # orig_bellyUp = orig_label_points[orig_bellyUp_idx, :] # new_bellyUp_idx = [i for i, i2 in new_to_orig_idx if i2==orig_bellyUp_idx][0] # new_bellyUp = new_label_points[new_bellyUp_idx,:] # target_points += (orig_bellyUp - new_bellyUp) # except Exception as e: # logger.warn("Couldn\'t match belly to belly") # traceback.print_exc(file=sys.stdout) # source_points[0] = center_bounding_box(source_points[0])[0] elif not os.path.isfile(opt.model.replace(os.path.splitext(opt.model)[1], ".picked")) and \ os.path.isfile(opt.source_model.replace(os.path.splitext(opt.source_model)[1], ".picked")): logger.info("Could not find {}. Assuming SMPL model".format(opt.model.replace(os.path.splitext(opt.model)[1], ".picked"))) source_shape, source_faces = read_trimesh(opt.source_model) assert(source_faces.shape[0] == target_faces.shape[1]), \ "opt.model must be a SMPL model with {} faces and {} vertices. Otherwise a correspondence file {} must be present.".format( source_faces.shape[0], source_shape.shape[0], opt.model.replace(os.path.splitext(opt.model)[1], ".picked")) # align faces not vertices orig_label_path = opt.source_model.replace(os.path.splitext(opt.source_model)[1], ".picked") logger.info("Loading picked labels {}".format(orig_label_path)) orig_label = pd.read_csv(orig_label_path, delimiter=" ",skiprows=1, header=None) source_shape = torch.from_numpy(source_shape[None, :, :3]).cuda().float() source_faces = torch.from_numpy(source_faces[None, :, :3]).cuda().long() idx = torch.from_numpy(orig_label.iloc[:,1].to_numpy()).long() source_points = torch.gather(source_shape.unsqueeze(1).expand(-1, idx.numel(), -1, -1), 2, source_faces[:, idx, :, None].expand(-1, -1, -1, 3)) source_points = source_points.mean(dim=-2) target_points = torch.gather(target_shape.unsqueeze(1).expand(-1, idx.numel(), -1, -1), 2, target_faces[:, idx, :, None].expand(-1, -1, -1, 3)) target_points = target_points.mean(dim=-2) _, source_center, _ = center_bounding_box(source_shape[0]) source_points -= source_center elif not os.path.isfile(opt.model.replace(os.path.splitext(opt.model)[1], ".picked")): logger.info("Could not find {}. Assuming SMPL model".format(opt.model.replace(os.path.splitext(opt.model)[1], ".picked"))) source_shape, source_faces = read_trimesh(opt.source_model) assert(source_faces.shape[0] == target_faces.shape[1]), \ "opt.model must be a SMPL model with {} faces and {} vertices. Otherwise a correspondence file {} must be present.".format( source_faces.shape[0], source_shape.shape[0], opt.model.replace(os.path.splitext(opt.model)[1], ".picked")) source_shape, source_faces = read_trimesh(opt.source_model) _, source_center, _ = center_bounding_box(source_shape[0]) source_points -= source_center source_shape = torch.from_numpy(source_shape[None, :, :3]).cuda().float() source_faces = torch.from_numpy(source_faces[None, :, :3]).cuda().long() # select a subset of faces, otherwise optimization is too slow idx = torch.from_numpy(np.random.permutation(2048)).cuda().long() source_points = torch.gather(source_shape.unsqueeze(1).expand(-1, source_faces.shape[1], -1, -1), 2, source_faces[:, idx,:, None].expand(-1, -1, -1, 3)) source_points = source_points.mean(dim=-2) target_points = torch.gather(target_shape.unsqueeze(1).expand(-1, source_faces.shape[1], -1, -1), 2, target_faces[:,idx,: None].expand(-1, -1, -1, 3)) target_points = target_points.mean(dim=-2) target_points = target_points[:, idx] source_points = source_points[:, idx] target_shape[0], target_center, target_scale = center_bounding_box(target_shape[0]) _, _, source_scale = center_bounding_box(shape_v[0]) # scale according y axis (body height) target_scale_factor = (source_scale/target_scale)[0,1] target_shape *= target_scale_factor target_points -= target_center target_points = (target_points*target_scale_factor).detach() # make sure test use the normalized target_shape_arr[:] = target_shape[0].cpu().numpy() om.write_mesh(os.path.join(opt.log_dir, opt.subdir, os.path.splitext( os.path.basename(opt.model))[0]+"_normalized.obj"), target_mesh) opt.model = os.path.join(opt.log_dir, opt.subdir, os.path.splitext( os.path.basename(opt.model))[0]+"_normalized.obj") pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-initial.obj"), shape_v[0].cpu().numpy(), shape_f[0].cpu().numpy()) pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "cage-initial.obj"), cage_v[0].cpu().numpy(), cage_f[0].cpu().numpy()) save_ply(target_points[0].cpu().numpy(), os.path.join( opt.log_dir, opt.subdir, "target_points.ply")) save_ply(source_points[0].cpu().numpy(), os.path.join( opt.log_dir, opt.subdir, "source_points.ply")) logger.info("Optimizing for {} corresponding vertices".format( target_points.shape[1])) cage_init = cage_v.clone().detach() lap_loss = MeshLaplacianLoss(torch.nn.MSELoss(reduction="none"), use_cot=True, use_norm=True, consistent_topology=True, precompute_L=True) mvc_reg_loss = MVCRegularizer(threshold=50, beta=1.0, alpha=0.0) cage_v.requires_grad_(True) optimizer = torch.optim.Adam([cage_v], lr=opt.lr, betas=(0.5, 0.9)) scheduler = torch.optim.lr_scheduler.StepLR(optimizer, int(opt.nepochs*0.4), gamma=0.5, last_epoch=-1) if opt.dim == 3: weights_ref = mean_value_coordinates_3D( source_points, cage_init, cage_f, verbose=False) else: raise NotImplementedError for t in range(opt.nepochs): optimizer.zero_grad() weights = mean_value_coordinates_3D( target_points, cage_v, cage_f, verbose=False) loss_mvc = torch.mean((weights-weights_ref)**2) # reg = torch.sum((cage_init-cage_v)**2, dim=-1)*1e-4 reg = torch.tensor(0.0).cuda() if opt.clap_weight > 0: reg = lap_loss(cage_init, cage_v, face=cage_f)*opt.clap_weight reg = reg.mean() if opt.mvc_weight > 0: reg += mvc_reg_loss(weights)*opt.mvc_weight loss = loss_mvc + reg if (t+1) % 50 == 0: print("t {}/{} mvc_loss: {} reg: {}".format(t, opt.nepochs, loss_mvc.item(), reg.item())) if loss_mvc.item() < 5e-6: break loss.backward() optimizer.step() scheduler.step() return cage_v, cage_f def test_one(opt, cage_shape, new_source, new_source_face, new_target, new_target_face): states = torch.load(opt.ckpt) if "states" in states: states = states["states"] pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-initial.ply"), states["source_vertices"][0].transpose( 0, 1).detach().cpu(), states["source_faces"][0].detach().cpu()) # states["template_vertices"] = cage_shape.transpose(1, 2) # states["source_vertices"] = new_source.transpose(1, 2) # states["source_faces"] = new_source_face pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-Sa.ply"), new_source[0].detach().cpu(), new_source_face[0].detach().cpu()) pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-Sb.ply"), new_target[0].detach().cpu(), new_target_face[0].detach().cpu()) net = networks.FixedSourceDeformer(opt, 3, opt.num_point, bottleneck_size=512, template_vertices=cage_shape.transpose(1, 2), template_faces=states["template_faces"].cuda(), source_vertices=new_source.transpose(1, 2), source_faces=new_source_face).cuda() net.eval() load_network(net, states) outputs = net(new_target.transpose(1, 2).contiguous()) deformed = outputs["deformed"] pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-Sab.ply"), deformed[0].detach().cpu(), new_target_face[0].detach().cpu()) def test_all(opt, new_cage_shape): opt.phase = "test" opt.target_model = None print(opt.model) if opt.is_poly: source_mesh = om.read_polymesh(opt.model) else: source_mesh = om.read_trimesh(opt.model) dataset = build_dataset(opt) dataloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False, drop_last=False, collate_fn=tolerating_collate, num_workers=0, worker_init_fn=lambda id: np.random.seed(np.random.get_state()[1][0] + id)) states = torch.load(opt.ckpt) if "states" in states: states = states["states"] # states["template_vertices"] = new_cage_shape.transpose(1, 2) # states["source_vertices"] = new_source.transpose(1,2) # states["source_faces"] = new_source_face # new_source_face = states["source_faces"] om.write_mesh(os.path.join(opt.log_dir, opt.subdir, "template-Sa.ply"), source_mesh) net = networks.FixedSourceDeformer(opt, 3, opt.num_point, bottleneck_size=opt.bottleneck_size, template_vertices=states["template_vertices"], template_faces=states["template_faces"].cuda(), source_vertices=states["source_vertices"], source_faces=states["source_faces"]).cuda() print(net) load_network(net, states) source_points = torch.from_numpy( source_mesh.points().copy()).float().cuda().unsqueeze(0) with torch.no_grad(): # source_face = net.source_faces.detach() for i, data in enumerate(dataloader): data = dataset.uncollate(data) target_shape, target_filename = data["target_shape"], data["target_file"] logger.info("", data["target_file"][0]) sample_idx = None if "sample_idx" in data: sample_idx = data["sample_idx"] outputs = net(target_shape.transpose(1, 2), cage_only=True) if opt.d_residual: cage_offset = outputs["new_cage"]-outputs["cage"] outputs["cage"] = new_cage_shape outputs["new_cage"] = new_cage_shape+cage_offset deformed = deform_with_MVC(outputs["cage"], outputs["new_cage"], outputs["cage_face"].expand( outputs["cage"].shape[0], -1, -1), source_points) for b in range(deformed.shape[0]): t_filename = os.path.splitext(target_filename[b])[0] source_mesh_arr = source_mesh.points() source_mesh_arr[:] = deformed[0].cpu().detach().numpy() om.write_mesh(os.path.join( opt.log_dir, opt.subdir, "template-{}-Sab.obj".format(t_filename)), source_mesh) pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-{}-Sb.ply".format(t_filename)), data["target_mesh"][b].detach().cpu(), data["target_face"][b].detach().cpu()) pymesh.save_mesh_raw( os.path.join(opt.log_dir, opt.subdir, "template-{}-cage1.ply".format(t_filename)), outputs["cage"][b].detach().cpu(), outputs["cage_face"][b].detach().cpu(), ) pymesh.save_mesh_raw( os.path.join(opt.log_dir, opt.subdir, "template-{}-cage2.ply".format(t_filename)), outputs["new_cage"][b].detach().cpu(), outputs["cage_face"][b].detach().cpu(), ) if i % 20 == 0: logger.success("[{}/{}] Done".format(i, len(dataloader))) dataset.render_result(os.path.join(opt.log_dir, opt.subdir)) if __name__ == "__main__": parser = MyOptions() opt = parser.parse() opt.log_dir = os.path.dirname(opt.ckpt) os.makedirs(os.path.join(opt.log_dir, opt.subdir), exist_ok=True) if opt.use_cage is None: # optimize initial cage for the new target cage_v, cage_f = optimize(opt) pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "optimized_template_cage.ply"), cage_v[0].detach().cpu(), cage_f[0].detach().cpu()) else: cage_v, cage_f = read_trimesh(opt.use_cage) cage_v = torch.from_numpy(cage_v[:, :3].astype(np.float32)).cuda() cage_f = torch.from_numpy(cage_f[:, :3].astype(np.int64)).cuda() cage_v.unsqueeze_(0) cage_f.unsqueeze_(0) # # test using the new source and initial cage # target_shape_pose, target_face_pose, _ = read_trimesh("/home/mnt/points/data/MPI-FAUST/training/registrations/tr_reg_002.ply") # target_shape_pose = torch.from_numpy(target_shape_pose[:,:3].astype(np.float32)).cuda() # target_face_pose = torch.from_numpy(target_face_pose[:,:3].astype(np.int64)).cuda() # target_shape_pose, _, _ = center_bounding_box(target_shape_pose) # target_shape_pose.unsqueeze_(0) # target_face_pose.unsqueeze_(0) # test_one(opt, cage_v, target_shape, target_face, target_shape_pose, target_face_pose) test_all(opt, cage_v)

[ "yifan.wang@inf.ethz.ch" ]

yifan.wang@inf.ethz.ch

ca84b1277c35cd6489cbf442d0400faa19000fa6

25d5b4790c94949bc4ac4e5575ef3b5e7e16c2ec

/api/models.py

f6df86e8908f2ab50fd7dea8e88700d379c6faa4

[]

no_license

andre0shazam/DjangoRest

c5d8535ab159d7c225c817eb6c8a8399fdbbc0a5

421632c31538e14c6afffa0f214bf78e2f3f77f5

refs/heads/main

2023-06-16T06:28:04.931136

2021-07-09T03:36:36

384,311,418

0

null

UTF-8

Python

false

264

py

from django.db import models class Client(models.Model): nome = models.CharField(max_length=30) sobrenome = models.CharField(max_length=30) idade = models.CharField(max_length=30) sexo = models.CharField(max_length=30) # Create your models here.

[ "andredog058@gmail.com" ]

andredog058@gmail.com

5f6fd827837ea66d8f74cc7cefddea9c8c314cc1

9a75cddf9eb2684dfd43cd38cd76878a0c4ff7db

/api/models.py

94473f53a9fe498eb19214bbe8eaaf0c8803848e

[]

no_license

redcrix/amazon-scraper

9cf178b42815b664aec9d3a604c4227d4f3ef594

17145d1c7d362799d2500b463f438b090dd5d09e

refs/heads/master

2020-06-24T17:04:10.347983

2019-08-28T06:34:57

199,024,434

0

null

UTF-8

Python

false

805

py

from django.db import models class Input(models.Model): url=models.CharField(max_length=1000) page_no=models.IntegerField() def __str__(self): return self.url class Api(models.Model): Product_name=models.CharField(max_length=50) by_info = models.CharField(max_length=15) Product_url = models.CharField(max_length=1000) Product_img = models.CharField(max_length=1000) Product_price = models.CharField(max_length=10) rating = models.CharField(max_length=15) total_review = models.CharField(max_length=15) ans_ask = models.CharField(max_length=15) prod_des = models.CharField(max_length=800) feature = models.CharField(max_length=1000) cust_review = models.CharField(max_length=5000) def __str__(self): return self.Product_name

[ "contact@redcrix.com" ]

contact@redcrix.com

2a08c1264727f25d9e966fcfe5077a7a6a878d3c

12b6e1a471614339c6def409d374fa886823c829

/mne_nirs/statistics/tests/test_statsmodels.py

832f294e1f052fe1abacb380f927baf94980c38a

[]

no_license

PiranitaGomez/mne-nirs

687913a2dbc9855987123c06ba9a58b6d815fbbb

cbf6bdcf61cccf35983006d53e3a9aff1e6fbd51

refs/heads/master

2023-03-11T05:38:05.913691

2021-02-26T02:43:54

null

0

null

UTF-8

Python

false

2,047

py

# Authors: Robert Luke <mail@robertluke.net> # # License: BSD (3-clause) import numpy as np from numpy.testing import assert_allclose import pytest import pandas as pd import statsmodels.formula.api as smf from ...simulation import simulate_nirs_raw from ...experimental_design import make_first_level_design_matrix from ...statistics import run_GLM, statsmodels_to_results from ...utils._io import glm_to_tidy @pytest.mark.parametrize('func', ('mixedlm', 'ols', 'rlm')) @pytest.mark.filterwarnings('ignore:.*optimization.*:') @pytest.mark.filterwarnings('ignore:.*on the boundary.*:') @pytest.mark.filterwarnings('ignore:.*The Hessian matrix at the estimated.*:') def test_statsmodel_to_df(func): func = getattr(smf, func) np.random.seed(0) amplitude = 1.432 df_cha = pd.DataFrame() for n in range(5): raw = simulate_nirs_raw(sfreq=3., amplitude=amplitude, sig_dur=300., stim_dur=5., isi_min=15., isi_max=45.) design_matrix = make_first_level_design_matrix(raw, stim_dur=5.0) glm_est = run_GLM(raw, design_matrix) with pytest.warns(RuntimeWarning, match='Non standard source detect'): cha = glm_to_tidy(raw, glm_est, design_matrix) cha["ID"] = '%02d' % n df_cha = df_cha.append(cha) df_cha["theta"] = df_cha["theta"] * 1.0e6 roi_model = func("theta ~ -1 + Condition", df_cha, groups=df_cha["ID"]).fit() df = statsmodels_to_results(roi_model) assert type(df) == pd.DataFrame assert_allclose(df["Coef."]["Condition[A]"], amplitude, rtol=1e-12) assert df["Significant"]["Condition[A]"] assert df.shape == (8, 8) roi_model = smf.rlm("theta ~ -1 + Condition", df_cha, groups=df_cha["ID"]).fit() df = statsmodels_to_results(roi_model) assert type(df) == pd.DataFrame assert_allclose(df["Coef."]["Condition[A]"], amplitude, rtol=1e-12) assert df["Significant"]["Condition[A]"] assert df.shape == (8, 8)

[ "noreply@github.com" ]

PiranitaGomez.noreply@github.com

0df692a6adbec35cf1c008fd20438bfd4e45212a

6123fe5a8c0b1d7b890558c662a16450696363f4

/training/compare.py

10ab58c6a28b6a28506c055d8f89c322498f052e

[]

no_license

RandallBalestriero/EMDGN

06023b6c5b09d3badc489b543e9d57d690948488

ce164e227e55b78b640f99d525367709a07abaed

refs/heads/master

2022-12-31T16:47:41.591652

2020-10-22T02:30:43

249,811,056

1

0

null

UTF-8

Python

false

2,547

py

import sys sys.path.insert(0, "../../SymJAX") sys.path.insert(0, "../") import numpy as np import symjax as sj import symjax.tensor as T import matplotlib.pyplot as plt import utils import networks from tqdm import tqdm import matplotlib import argparse parser = argparse.ArgumentParser() parser.add_argument('--std', type=float, default=0.55)#0.15 parser.add_argument('--seed', type=int, default=0) parser.add_argument('--dataset', type=str) parser.add_argument('--model', type=str) parser.add_argument('--network', type=str) parser.add_argument('--epochs', type=int, default=100) parser.add_argument('--leakiness', type=float, default=0.1) parser.add_argument('--noise', type=float, default=0.1) args = parser.parse_args() np.random.seed(args.seed) BS = 1000 DATA = networks.create_dataset(args.dataset, BS, noise_std=args.std) if args.network == 'small': Ds = [1, 8, DATA.shape[1]] R = 16 elif args.network == 'large': Ds = [1, 16, 16, DATA.shape[1]] R = 64 graph = sj.Graph('test') with graph: if args.model != 'EM': lr = sj.tensor.Variable(1., name='lr', trainable=False) emt = networks.create_fns(BS, R, Ds, 1, var_x = np.ones(Ds[-1]), lr=0.005, leakiness=args.leakiness) model = networks.create_vae(50, Ds, args.seed, lr=lr, leakiness=args.leakiness, scaler=1) else: model = networks.create_fns(BS, R, Ds, 1, lr=0.001, leakiness=args.leakiness, var_x=args.std**2) for RUN in range(20): graph.reset() # do the VAE case if args.model != 'EM': filename = 'nnsaving_likelihood_{}_{}_{}_{}_{}_{}.npz' for lr_ in [0.005, 0.001, 0.0001]: lr.assign(lr_) out = networks.EM(model, DATA, epochs=args.epochs, n_iter=500, extra=emt) np.savez(filename.format(args.dataset, args.epochs, args.model, lr_, args.network, RUN), L=out[0], LL=out[1], samples=model['sample'](4*BS), noise=np.random.randn(4*BS,2) * np.sqrt(model['varx']()), data=DATA) else: filename = 'nnsaving_likelihood_{}_{}_{}_{}_{}.npz' out = networks.EM(model, DATA, epochs=args.epochs, n_iter=100, update_var=4) np.savez(filename.format(args.dataset, args.epochs, args.model, args.network, RUN), L=out, samples=model['sample'](4*BS), noise=np.random.randn(4*BS,Ds[-1]) * np.sqrt(model['varx']()), data=DATA)

[ "randallbalestriero@gmail.com" ]

randallbalestriero@gmail.com

93e9bc9a42dc775c374e0bc17ac9f423f8fe1b71

a69d8dd2a2f0ba514dc4137bec9e9a279af8cc2a

/links/migrations/0003_vote.py

01ad26a235fa08d23e59be0cc918049867743f3a

[]

no_license

JosePedroZarate/API-react-apollo

db05e86d3fc3ed0aa74875a796e5a9f222326940

02dc6db4619135f9f9dbedd636612a5798905f3c

refs/heads/master

2023-05-17T21:28:43.285670

2021-06-14T19:07:49

376,927,757

0

null

UTF-8

Python

false

827

py

# Generated by Django 3.1.3 on 2021-06-10 02:27 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('links', '0002_link_posted_by'), ] operations = [ migrations.CreateModel( name='Vote', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('link', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='votes', to='links.link')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]

[ "jzaratespinosa2@gmail.com" ]

jzaratespinosa2@gmail.com

59a949fbb8a08da9f8d058fcbe6e2e7aa3d462e6

e38913d34f512b2840c22e9cb46e20863d5ec991

/skills_kindregan.py

f008e5236f97c8a5d4a1f0b94953a7a6fef0b6d1

[]

no_license

ultramarine7/self_assessment_4_10

fdfd631592ef5747f929fb1af8b50763b1661e88

b3ef7b44eca249249a4b58644ee11884e6da914f

refs/heads/master

2021-01-10T02:01:46.857975

2016-04-11T16:46:52

55,943,382

0

null

UTF-8

Python

false

9,416

py

"""Skills Assessment: Lists Edit the function bodies until all of the doctests pass when you run this file. """ number_list = [1, 2, 7, -5] odd_list = [] # Originally overthought this and was trying to write a code that reproduced a list. But assumed later # the list is 1, 2, 7, -5. # number_list = [] # i = 1 # while i < 3: # number_list.append(i) # i += 1 # i = -1 # while i > -3: # number_list.append(i) # i -= 1 def all_odd(number_list): """Return a list of only the odd numbers in the input list. >>> all_odd([1, 2, 7, -5]) [1, 7, -5] >>> all_odd([2, -6, 8]) [] """ for num in number_list: if num % 2 != 0: odd_list.append(num) # print odd_list return [] number_list = [2, -6, 8] odd_list = [] def all_odd(number_list): for num in number_list: if num % 2 == 0: odd_list.append(num) return [] all_odd(number_list) ################################################################################## number_list = [2, 3, 5, 6, -1, -2] even_list = [] def all_even(number_list): """Return a list of only the even numbers in the input list. >>> all_even([2, 6, -1, -2]) [2, 6, -2] >>> all_even([-1, 3, 5]) [] """ for num in number_list: if num % 2 == 0: even_list.append(num) return [] number_list = [-1, 3, 5] even_list = [] def all_even(number_list): for num in number_list: if num % 2 != 0: even_list.append(num) # print even_list return [] all_even(number_list) ################################################################### my_list = ["Toyota", "Jeep", "Volovo"] def print_indexes(my_list): """Print the index of each item in the input_list, followed by the item itself. Do this without using a counting variable---that is, don't do something like this: count = 0 for item in list: print count count = count + 1 Output should look like this: >>> print_indexes(["Toyota", "Jeep", "Volvo"]) 0 Toyota 1 Jeep 2 Volvo """ for item, index in enumerate(my_list): print item, index ######################################################## word_list = ["all", "are", "tiny"] long_word_list = [] def long_words(word_list): """Return all words in input list that are longer than 4 characters. >>> long_words(["hello", "hey", "spam", "spam", "bacon", "bacon"]) ['hello', 'bacon', 'bacon'] >>> long_words(["all", "are", "tiny"]) [] """ word_length = 4 for word in word_list: if len(word) > word_length: long_word_list.append(word) # print long_word_list return [] word_list = ["all", "are", "tiny"] long_word_list = [] def long_words(word_list): word_length = 4 for word in word_list: if len(word) > word_length: long_word_list.append(word) return [] ######################################################### number_list = [-5, 2, -5, 7] def smallest_int(number_list): """Find the smallest integer in a list of integers and return it. DO NOT USE the built-in function `min`! >>> smallest_int([-5, 2, -5, 7]) -5 >>> smallest_int([3, 7, 2, 8, 4]) 2 If the input list is empty, return None: >>> smallest_int([]) is None True """ for number in number_list: number = int(number) number_list.sort() minimum = number_list[0] small_list = minimum return small_list number_list = [3, 7, 2, 8, 4] def smallest_int(number_list): for number in number_list: number = int(number) number_list.sort() minimum = number_list[0] small_list = minimum return small_list smallest_int(number_list) ######################################################## number_list = [-5, 2, -5, 7] def largest_int(number_list): """Find the largest integer in a list of integers and return it. DO NOT USE the built-in function `max`! >>> largest_int([-5, 2, -5, 7]) 7 >>> largest_int([3, 7, 2, 8, 4]) 8 If the input list is empty, return None: >>> largest_int([]) is None True """ for num in number_list: num = int(num) number_list.sort() maximum = number_list[-1] return number_list = [3, 7, 2, 8, 4] def largest_int(number_list): for num in number_list: num = int(num) number_list.sort() maximum = number_list[-1] return largest_int(number_list) ########################################################################## number_list = [2, 6, -2] division_list = [] def halvesies(number_list): """Return list of numbers from input list, each divided by two. >>> halvesies([2, 6, -2]) [1.0, 3.0, -1.0] If any of the numbers are odd, make sure you don't round off the half: >>> halvesies([1, 5]) [0.5, 2.5] """ for num in number_list: division = float(num) / 2 division_list.append(division) return number_list = [1, 5] division_list = [] def halvesies(number_list): for num in number_list: division = float(num) / 2 division_list.append(division) return halvesies(number_list) ################################################################################### word_list = ["hello", "hey", "hello", "spam"] length_list = [] def word_lengths(word_list): """Return the length of words in the input list. >>> word_lengths(["hello", "hey", "hello", "spam"]) [5, 3, 5, 4] """ for word in word_list: length = len(word) length_list.append(length) return length_list ############################################################################## sum_numbers = [1, 2, 3, 10] def sum_numbers(number_list): # I had no idea there is sum() lol """Return the sum of all of the numbers in the list. Python has a built-in function, `sum()`, which already does this -- but for this exercise, you should not use it. >>> sum_numbers([1, 2, 3, 10]) 16 Any empty list should return the sum of zero: >>> sum_numbers([]) 0 """ total = 0 for num in number_list: total = total + num return total ############################################################################################# number_list = [1, 2, 3] def mult_numbers(number_list): """Return product (result of multiplication) of the numbers in the list. >>> mult_numbers([1, 2, 3]) 6 Obviously, if there is a zero in the input, the product will be zero: >>> mult_numbers([10, 20, 0, 50]) 0 As explained at http://en.wikipedia.org/wiki/Empty_product, if the list is empty, the product should be 1: >>> mult_numbers([]) 1 """ total = 1 for num in range(0, len(number_list)): total = total * number_list[num] return total ############################################################################################ word_list = ["spam", "spam", "bacon", "balloonicorn"] def join_strings(word_list): """Return a string of all input strings joined together. Python has a built-in method on lists, `join`---but for this exercise, you should not use it. >>> join_strings(["spam", "spam", "bacon", "balloonicorn"]) 'spamspambaconballoonicorn' For an empty list, you should return an empty string: >>> join_strings([]) '' """ joined_list = "" for word in range(0, len(word_list)): joined_list = joined_list + word_list[word] return joined_list join_strings(word_list) ############################################################################### number_list = [2, 12, 3] def average(number_list): """Return the average (mean) of the list of numbers given. >>> average([2, 12, 3]) 5.666666666666667 There is no defined answer if the list given is empty. It's fine if this raises an error when given an empty list. """ average = 0 sum = 0 for num in number_list: sum = sum + num average = float(sum) / len(number_list) return average average(number_list) ########################################################################### list_of_words = ["Labrador", "Poodle", "French Bulldog"] def join_strings_with_comma(list_of_words): """Return ['list', 'of', 'words'] like "list, of, words". >>> join_strings_with_comma(["Labrador", "Poodle", "French Bulldog"]) 'Labrador, Poodle, French Bulldog' If there's only one thing in the list, it should return just that thing, of course: >>> join_strings_with_comma(["Pretzel"]) 'Pretzel' """ for words in list_of_words: joined_words = ", ".join(list_of_words) return list_of_words join_strings_with_comma(list_of_words) ############################################################################## # END OF ASSIGNMENT: You can ignore everything below. if __name__ == "__main__": import doctest print result = doctest.testmod() if not result.failed: print "*** %s TESTS PASSED. GOOD WORK!" % result.attempted print

[ "kindc005@riveter03-ml.swna.wdpr.disney.com" ]

kindc005@riveter03-ml.swna.wdpr.disney.com

5e1b614ea755b33c5ce4f98f3cfb783b2e3a24c5

51dcd31096526bfa6aeae4baea9f0f45657c6623

/ocean/datasets/datasets.py

81bb5f5316ed602de9d5b6f81d5883b0d3b2b7a4

[]

no_license

sopac/ocean-portal-docker

eba5de774e5a2b3e9b019440c39e7f0041715dd9

159aeba7143e66fdd9ed253de935407f898b4873

refs/heads/master

2021-01-20T08:07:58.698449

2017-09-10T09:24:04

90,103,531

1

5

null

2017-12-13T03:30:45

2017-05-03T03:19:57

Python

UTF-8

Python

false

3,164

py

# # (c) 2012 Commonwealth of Australia # Australian Bureau of Meteorology, COSPPac COMP # All Rights Reserved # # Authors: Danielle Madeley <d.madeley@bom.gov.au> import cgi import datetime from ocean.config import regionConfig from ocean.core import ReportableException class MissingParameter(ReportableException): pass class ValidationError(ReportableException): pass class Dataset(object): # these are the possible paramaters that can be passed to a dataset # and their types __form_params__ = { 'dataset': str, 'variable': str, 'plot': str, 'date': datetime.date, 'period': str, 'area': str, 'step': str, } # these parameters are required, failure to include them is an exception __required_params__ = [ 'dataset', 'variable', 'plot', 'period', ] __periods__ = [ ] __variables__ = [ ] __plots__ = [ ] @classmethod def parse(self, validate=True): form = cgi.FieldStorage() output = {} for k, t in self.__form_params__.items(): if k not in form: continue v = form[k].value # coerce the form values into the right types if hasattr(self, 'parse_%s' % k): v = getattr(self, 'parse_%s' % k)(v) if not isinstance(v, t): raise TypeError("Form parameter '%s' is of type %s, expected %s" % (k, type(v), t)) else: v = t(v) # run validation # FIXME: should this be done afterwards with the entire param set? if validate and hasattr(self, 'validate_%s' % k): try: getattr(self, 'validate_%s' % k)(v) except AssertionError, e: raise ValidationError(e) output[k] = v # check for required if validate: for k in self.__required_params__: if k not in output: raise MissingParameter("Expected parameter '%s'" % k) return output @classmethod def parse_date(self, p): if len(p) == 8: day = int(p[6:8]) elif len(p) == 6: day = 1 else: raise TypeError("Length of date must be 6 or 8, not %i" % len(p)) return datetime.date(int(p[0:4]), int(p[4:6]), day) @classmethod def validate_variable(self, p): if not p in self.__variables__: raise ValidationError("Unknown variable '%s'" % p) @classmethod def validate_plot(self, p): if not p in self.__plots__: raise ValidationError("Unknown plot type '%s'" % p) @classmethod def validate_period(self, p): if not p in self.__periods__: raise ValidationError("Unknown period '%s'" % p) @classmethod def validate_area(self, p): if p not in regionConfig.regions: raise ValidationError("Unknown area '%s'" % p) def process(self, params): raise NotImplemented

[ "sachindras@spc.int" ]

sachindras@spc.int

3258e737d5e764ba89d735a746e74cee2d3960b6

c27f94e58f3b2cc6e3ae313d9860d24bebd55515

/src/training/dataprep/convert_to_parquet.py

b8699b0fbf8b1534457cd6f74be7f2865144f5b1

[ "Apache-2.0" ]

permissive

mengdong/merlin-on-vertex

5cea099db676c932d776c0ca61b8bcbb1dbfbc66

0d8ac410f6afb01ff1b2ec70b51cb5caa28a66ad

refs/heads/main

2023-08-19T13:27:03.053988

2021-10-09T05:01:16

415,205,910

0

Apache-2.0

2021-10-09T04:55:34

2021-10-09T04:55:33

null

UTF-8

Python

false

4,008

py

# Copyright 2021 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and import argparse import glob import logging import nvtabular as nvt import numpy as np import os import shutil import time import utils CRITEO_FILE_RE = 'day_*' def convert(args): """Converts Criteo TSV files to Parquet.""" # Create Dask cluster client = utils.create_dask_cluster( gpus=args.devices.split(','), device_memory_fraction=args.device_limit_frac, device_pool_fraction=args.device_pool_frac, local_directory=args.dask_path, protocol=args.protocol ) # Specify column names cont_names = ["I" + str(x) for x in range(1, 14)] cat_names = ["C" + str(x) for x in range(1, 27)] cols = ["label"] + cont_names + cat_names # Specify column dtypes. dtypes = {} dtypes["label"] = np.int32 for x in cont_names: dtypes[x] = np.int32 for x in cat_names: dtypes[x] = "hex" # Create an NVTabular Dataset from Criteo TSV files file_list = glob.glob(os.path.join(args.input_path, CRITEO_FILE_RE)) dataset = nvt.Dataset( file_list, engine="csv", names=cols, part_mem_fraction=args.part_mem_frac, sep="\t", dtypes=dtypes, client=client, ) # Convert to Parquet dataset.to_parquet( output_path=args.output_path, preserve_files=True, ) def parse_args(): parser = argparse.ArgumentParser(description=("Multi-GPU Criteo Preprocessing")) parser.add_argument( "--input_path", type=str, help="A path to Criteo TSV files") parser.add_argument( "--output_path", type=str, help="A path to Criteo Parquet files") parser.add_argument( "--dask_path", type=str, help="A path to Dask working directory") parser.add_argument( "-d", "--devices", type=str, help='Comma-separated list of visible devices (e.g. "0,1,2,3"). ' ) parser.add_argument( "-p", "--protocol", choices=["tcp", "ucx"], default="tcp", type=str, help="Communication protocol to use (Default 'tcp')", ) parser.add_argument( "--device_limit_frac", default=0.7, type=float, help="Worker device-memory limit as a fraction of GPU capacity (Default 0.8). " ) parser.add_argument( "--device_pool_frac", default=0.9, type=float, help="RMM pool size for each worker as a fraction of GPU capacity (Default 0.9). " "The RMM pool frac is the same for all GPUs, make sure each one has enough memory size", ) parser.add_argument( "--num_io_threads", default=0, type=int, help="Number of threads to use when writing output data (Default 0). " "If 0 is specified, multi-threading will not be used for IO.", ) parser.add_argument( "--part_mem_frac", default=0.125, type=float, help="Maximum size desired for dataset partitions as a fraction " "of GPU capacity (Default 0.125)", ) args = parser.parse_args() return args if __name__ == '__main__': logging.basicConfig(format='%(asctime)s %(message)s') logging.root.setLevel(logging.NOTSET) logging.getLogger('numba').setLevel(logging.WARNING) logging.getLogger('asyncio').setLevel(logging.WARNING) args = parse_args() convert(args)

[ "jarokaz@no-reply.com" ]

jarokaz@no-reply.com

eb4e148f1f3df6fa2869bba533a6a3eea067e17f

fcc8102e3649ade30449e4ddb91536251b9896be

/code-1mwtt/ex12_bin_search.py

3a14fbc0aecb2f3208b9a905cdc67ca3a830f351

[ "MIT" ]

permissive

shilpasayura/algohack

b8373da344acd5b78e92c34b748cabf3ab036463

74e88e558244464771a18d8ed5f466a0e2acec78

refs/heads/master

2023-04-10T07:17:31.626591

2023-03-17T15:50:58

136,417,023

6

null

2018-09-15T16:27:54

2018-06-07T03:28:47

Python

UTF-8

Python

false

1,075

py

def bin_search(xs, x): # return the least index of an element equal to x sorted x low = 0 high = len(xs) while low + 1 < high: guess = (low + high) // 2 if x < xs[guess]: high = guess else: low = guess return low def test(test_case_xs, test_case_x, expected): actual = bin_search(test_case_xs, test_case_x) if actual == expected: print("Passed test for " + test_case_x) else: print("Didn't pass test for " + test_case_x) print("The result was " + str(actual) + " but it should have been " + str(expected)) test([], "x", 0) test(["code", "learn", "to"], "code", 0) test(["code", "learn", "to"], "learn", 1) test(["code", "learn", "to"], "to", 2) sentence = "A brownish cloud descends every Friday, growing, hovering impressively, jeopardously keeping low, moving nimbly over populated quarters, returning silently to unknown, violently wild xylogenic yttriferous zones." words = sentence.lower().split(" ") for i in range(0, len(words)): test(words, words[i], i)

[ "shilpasayura@gmail.com" ]

shilpasayura@gmail.com

8ae9c07b59c89ec6ed4ff6ddaa00edd00dcc9bfe

e96ed9d92cea007f98b03b7213b5daab2e3f33ea

/World.py

06873071bd363a15c3efbe4a7c574d1187f9ce1f

[]

no_license

SterlingPeet/PyBioSim

70a4add7fda16db1427bfbdde169c512199beb0c

b86fdff97f42cde661bb5bef584cb7e9eeaee067

refs/heads/master

2021-01-15T19:13:55.579793

2015-03-05T22:17:34

30,716,717

1

0

null

UTF-8

Python

false

820

py

''' Created on Jan 16, 2015 @author: Arindam ''' from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import numpy as np from pylab import * import os class World(object): def __init__(self, width, height): self.agents=[] self.obstacles=[] self.balls=[] self.width = width self.height = height def draw(self, ax): ax.set_xlim3d(-self.width,self.width) ax.set_ylim3d(-self.width,self.width) ax.set_zlim3d(-self.height,self.height) for agent in self.agents: agent.draw(ax) for obstacle in self.obstacles: obstacle.draw(ax) for ball in self.balls: ball.draw(ax) return ax

[ "arindam.b@gatech.edu" ]

arindam.b@gatech.edu

c383feae171c9937de1ed0b92f573b81edbc2d96

eb69eff59cfee055cdb831c886a98b27fc2c03df

/count_words_in_books/without_asyncio.py

49e47f2f0c75dec7861d944c1d9556c8bf4bd7ee

[]

no_license

overfl0/depcon_asyncio

eb1f1600a727828f3b04b7d14184c3cf4381df5c

09ba2318bdc866a83550530ecba5f81d2a411370

refs/heads/master

2021-07-01T14:53:34.508406

2019-12-06T10:04:49

226,342,907

0

null

2021-02-26T02:42:29

2019-12-06T14:07:07

Python

UTF-8

Python

false

373

py

from count_words_in_books.common import links_wl from urllib.request import urlopen def count_words(text): wordcount = {} for word in text.split(): if word not in wordcount: wordcount[word] = 1 else: wordcount[word] += 1 def main(): for link in links_wl: data = urlopen(link).read() count_words(data)

[ "lukaszchojnacki2@gmail.com" ]

lukaszchojnacki2@gmail.com

d67673100f1b976c27b6772711072121e573ee42

0ff58efd704400dd8ed21b1ce5781b93be7ddc80

/wiki_split_3.py

a7f55758bb2c5badc8ed28ab64d237b19b1bdecf

[ "MIT" ]

permissive

danieleandreatta/wiki_page_stats

452ff39b747a18c008e8ed989ea1f064e295513f

02f342f4bf73497ffc3ca1fc2c163eb1627e72b0

refs/heads/master

2021-01-19T21:28:22.494149

2015-02-28T10:44:53

29,706,263

0

null

UTF-8

Python

false

437

py

#!/usr/bin/python3.4 import time import sys t0 = time.clock() pages = [] with open(sys.argv[1], 'rb') as f: for line in f: ws = line.split() if ws[0] == b'en' and int(ws[2]) > 500: pages.append((ws[1].decode('ascii'), int(ws[2]))) pages.sort(reverse=True, key=lambda x:x[1]) t1 = time.clock() print('Query took %.2f seconds' % (t1-t0)) for i in range(min(10, len(pages))): print('%s (%d)' % pages[i])

[ "d_andreatta@hotmail.com" ]

d_andreatta@hotmail.com

361dcd2a8a5f84b0725ec737cdeb87b13b46a64e

1207c58fa92dad30050b9f3bcc1173d7e7034c73

/mnist_tools.py

127a5ccc739ea8502a23197d9b85c1bbf5fe0bd9

[]

no_license

chagge/rethinking-generalization

b49cf59c8d4d2c3607fa2074a80f86d8e682150c

317c1ae29ae119d7399e8e04e95eb903f4d1c045

refs/heads/master

2021-01-22T09:04:55.449746

2017-02-12T16:41:09

null

0

null

UTF-8

Python

false

2,871

py

# -*- coding: utf-8 -*- import gzip, os, six, sys from six.moves.urllib import request from PIL import Image import numpy as np parent = "http://yann.lecun.com/exdb/mnist" train_images_filename = "train-images-idx3-ubyte.gz" train_labels_filename = "train-labels-idx1-ubyte.gz" test_images_filename = "t10k-images-idx3-ubyte.gz" test_labels_filename = "t10k-labels-idx1-ubyte.gz" n_train = 60000 n_test = 10000 dim = 28 * 28 def load_mnist(data_filename, label_filename, num): images = np.zeros(num * dim, dtype=np.uint8).reshape((num, dim)) label = np.zeros(num, dtype=np.uint8).reshape((num, )) with gzip.open(data_filename, "rb") as f_images, gzip.open(label_filename, "rb") as f_labels: f_images.read(16) f_labels.read(8) for i in six.moves.range(num): label[i] = ord(f_labels.read(1)) for j in six.moves.range(dim): images[i, j] = ord(f_images.read(1)) if i % 100 == 0 or i == num - 1: sys.stdout.write("\rloading images ... ({} / {})".format(i + 1, num)) sys.stdout.flush() sys.stdout.write("\n") return images, label def load_train_images(): if not os.path.exists("../" + train_images_filename): download_mnist_data() images, labels = load_mnist("../" + train_images_filename, "../" + train_labels_filename, n_train) return images, labels def load_test_images(): if not os.path.exists("../" + test_images_filename): download_mnist_data() images, labels = load_mnist("../" + test_images_filename, "../" + test_labels_filename, n_test) return images, labels def download_mnist_data(): print("Downloading {} ...".format(train_images_filename)) request.urlretrieve("{}/{}".format(parent, train_images_filename), "../" + train_images_filename) print("Downloading {} ...".format(train_labels_filename)) request.urlretrieve("{}/{}".format(parent, train_labels_filename), "../" + train_labels_filename) print("Downloading {} ...".format(test_images_filename)) request.urlretrieve("{}/{}".format(parent, test_images_filename), "../" + test_images_filename) print("Downloading {} ...".format(test_labels_filename)) request.urlretrieve("{}/{}".format(parent, test_labels_filename), "../" + test_labels_filename) print("Done") def extract_bitmaps(): train_dir = "train_images" test_dir = "test_images" try: os.mkdir(train_dir) os.mkdir(test_dir) except: pass data_train, label_train = load_test_images() data_test, label_test = load_test_images() print "Saving training images ..." for i in xrange(data_train.shape[0]): image = Image.fromarray(data_train[i].reshape(28, 28)) image.save("{}/{}_{}.bmp".format(train_dir, label_train[i], i)) print "Saving test images ..." for i in xrange(data_test.shape[0]): image = Image.fromarray(data_test[i].reshape(28, 28)) image.save("{}/{}_{}.bmp".format(test_dir, label_test[i], i))

[ "musyoku@users.noreply.github.com" ]

musyoku@users.noreply.github.com

eefab490fac85d434563527a62d7c61c21cdedd4

501615c82801733e69c7447ab9fd68d3883ed947

/hotfix/mz_platform/services/functions/career_course_service.py

a590aa114a064a4fa0554f9cf3c981374b55dd5d

[]

no_license

az0ne/python

b2e1cc1e925d1fcdb269e7dd4c48e24665deeeee

aec5d23bb412f7dfca374fb5c5b9988c1b817347

refs/heads/master

2021-07-18T02:08:46.314972

2017-10-27T06:23:36

null

0

null

UTF-8

Python

false

3,828

py

# -*- coding: utf-8 -*- __author__ = 'changfu' from mz_platform.services.functions.mz_service import MZService, Orm2Str from mz_platform.orms.course_models import CareerCourse from mz_platform.orms.mz_common import CareerObjRelation from mz_platform.orms.course_models import Course from mz_platform.orms.mz_user import UserProfile from mz_platform.orms.mz_article import Article from mz_platform.orms.mz_common import CareerAd from mz_platform.orms.course_models import Lesson class CareerCourseService(MZService): """ 职业课程service """ factory_functions = dict(career_course=CareerCourse) def __init__(self): """ @brief @return: """ super(CareerCourseService, self).__init__() def get_related_objects(self, career_course_id, obj_type='COURSE', ad_type='COURSE', is_active=True, what='*', conditions=None, limit=None, order_by=None): """ @brief 获取职业课程所相关的objects, 如课程，文章，老师，视频, 广告 @param career_course_id: 职业课程的id @param obj_type: objects的类型，可选为'COURSE', 'ARTICLE', 'TEACHER', 'LESSON', 'CAREERAD', 默认为'COURSE' @param ad_type: 广告的类型，指明广告的位置．当ob_type='CAREERAD'时，该参数有效．可选值为'COURSE', 'ARTICLE', 默认为'COURSE' @param is_active: True or False, 如果为True,则返回激活的课程，如果为False, 返回全部课程，默认为True @param what: @param conditions: @param limit: @param order_by: @return: 课程信息字典的列表 @note example1: get_related_objects(career_course_id=5, obj_type='COURSE', is_activate=False, order_by='-id', what='id', conditions=['id>10'], limit='9, 14') 　获取id为5的职业课程的全部相关小课程(is_active=False)的id字段，条件为小课程的id大于10.从结果的第9条开始取，取14条，并按id字段降序排列 example2: get_related_objects(career_course_id=5, obj_type='CAREERAD', ad_type='ARTICLE', is_activate=False, order_by='-id', what='id', limit='9, 14') 　获取id为5的职业课程的文章详情页的广告的(is_active=False)的id字段。从结果的第9条开始取，取14条，并按id字段降序排列 """ relation_map = dict(CAREERAD=([(CareerAd, ('career_id', 'type', 'is_actived'), (career_course_id, ad_type, 1 if is_active else 0))], CareerAd, None), COURSE=([(CareerObjRelation, ('career_id', 'is_actived', 'obj_type'), (career_course_id, 1 if is_active else 0, 'COURSE'))], Course, [('inner', (CareerObjRelation, Course), ('obj_id', 'id'))]), ARTICLE=([(CareerObjRelation, ('career_id', 'is_actived', 'obj_type'), (career_course_id, 1 if is_active else 0, 'ARTICLE'))], Article, [('inner', (CareerObjRelation, Article), ('obj_id', 'id'))]), TEACHER=(), LESSON=()) more_conditions, where, join = relation_map[obj_type.upper()] data = Orm2Str.orm2str(what=what, where=where, join=join, conditions=conditions, more_conditions=more_conditions, limit=limit, order_by=order_by) return self.db.select(**data)

[ "1461847795@qq.com" ]

1461847795@qq.com

14f82a34f2211b09f1441103c7218d080c5601e0

5226b3ed1ecbafae65859049289447a1681215bd

/split_every_page.py

eaa611af6948c4df9a0837ff62ba9536961a793a

[ "Apache-2.0" ]

permissive

ClemensBasler/python-pdf-test

35dfca34cabe3a674e092003d0bae43c05a16622

02a5e397c5bca05a80cb7de2250ebacd6e889ae8

refs/heads/master

2020-04-29T17:44:43.224042

2019-03-18T14:38:22

176,305,192

0

null

UTF-8

Python

false

611

py

# pdf_splitter.py import os from PyPDF2 import PdfFileReader, PdfFileWriter def pdf_splitter(path): fname = os.path.splitext(os.path.basename(path))[0] pdf = PdfFileReader(path) for page in range(pdf.getNumPages()): pdf_writer = PdfFileWriter() pdf_writer.addPage(pdf.getPage(page)) output_filename = '{}_page_{}.pdf'.format( fname, page+1) with open(output_filename, 'wb') as out: pdf_writer.write(out) print('Created: {}'.format(output_filename)) if __name__ == '__main__': path = 'input/test.pdf' pdf_splitter(path)

[ "clemens-basler@t-online.de" ]

clemens-basler@t-online.de

7178f8ac1e0922e8cfe3a8096f3a33236d592e8a

6be1cdfea8c3b2fe73f9ba28da0f70c906a22ed3

/algorithm/_abc/iterable/genetic.py

f946a449dd8e4377406af25a855bbb1dc50c3297

[]

no_license

chivdan/evoguess

63b52c7a376cf374994c87253726ee303ec0a2e7

2294dfe29369998786dd0b79b311c3efc385c895

refs/heads/master

2023-08-02T16:43:49.153184

2021-10-08T13:21:46

null

0

null

UTF-8

Python

false

612

py

from .evolution import * class Genetic(Evolution): tweak_chunk_size = 2 name = 'Algorithm(Iterable): Genetic' def __init__(self, crossover, *args, **kwargs): self.crossover = crossover super().__init__(*args, **kwargs) def tweak(self, selected: Population): raise NotImplementedError def join(self, parents: Population, children: Population): raise NotImplementedError def __info__(self): return { **super().__info__(), 'crossover': self.crossover.__info__() } __all__ = [ 'Genetic', 'Population', ]

[ "art-pavlenko@mail.ru" ]

art-pavlenko@mail.ru

8ddf2cf2991093f5f0b31aa38198e71470511241

54a73236923028a91d0427daeacfa44a82ae7e68

/pytests/blob1.py

581e83ca9370be5ad8af01615aebe2a449af84cf

[]

no_license

pbxrshd/transfer

85dd3de93be73ad75ea17c52facf57a5fa47c04f

15aed0f5087e77e048eb97af1be464a637e5eabc

refs/heads/master

2016-09-05T15:45:48.175922

2015-07-09T13:46:20

27,556,084

0

null

UTF-8

Python

false

25,810

py

#!/usr/bin/python import cv import time import serial from scipy import * from scipy.cluster import vq import numpy import sys, os, random, hashlib from math import * top = 0 bottom = 1 left = 0 right = 1 def merge_collided_bboxes( bbox_list ): for this_bbox in bbox_list: # Collision detect every other bbox: for other_bbox in bbox_list: if this_bbox is other_bbox: continue # Skip self # Assume a collision to start out with: has_collision = True if (this_bbox[bottom][0]*1.1 < other_bbox[top][0]*0.9): has_collision = False if (this_bbox[top][0]*.9 > other_bbox[bottom][0]*1.1): has_collision = False if (this_bbox[right][1]*1.1 < other_bbox[left][1]*0.9): has_collision = False if (this_bbox[left][1]*0.9 > other_bbox[right][1]*1.1): has_collision = False if has_collision: # merge these two bboxes into one, then start over: top_left_x = min( this_bbox[left][0], other_bbox[left][0] ) top_left_y = min( this_bbox[left][1], other_bbox[left][1] ) bottom_right_x = max( this_bbox[right][0], other_bbox[right][0] ) bottom_right_y = max( this_bbox[right][1], other_bbox[right][1] ) new_bbox = ( (top_left_x, top_left_y), (bottom_right_x, bottom_right_y) ) bbox_list.remove( this_bbox ) bbox_list.remove( other_bbox ) bbox_list.append( new_bbox ) # Start over with the new list: return merge_collided_bboxes( bbox_list ) # When there are no collions between boxes, return that list: return bbox_list def detect_faces( image, haar_cascade, mem_storage ): faces = [] image_size = cv.GetSize( image ) faces = cv.HaarDetectObjects(image, haar_cascade, mem_storage, 1.2, 2, cv.CV_HAAR_DO_CANNY_PRUNING, ( image_size[0]/10, image_size[1]/10) ) for face in faces: box = face[0] cv.Rectangle(image, ( box[0], box[1] ), ( box[0] + box[2], box[1] + box[3]), cv.RGB(255, 0, 0), 1, 8, 0) class Target: def __init__(self): try: self.ser = serial.Serial('/dev/ttyUSB0', 9600, timeout=1) self.have_eye = 1 except: print " may want to plug something into /dev/ttyUSB0" self.have_eye = 0 self.joymap = [1,2,3,4] # link between joystick and the servo to move self.joyreverse = [0,0,0,0,0] fps=6 is_color = True self.capture = cv.CaptureFromCAM(0) cv.SetCaptureProperty( self.capture, cv.CV_CAP_PROP_FRAME_WIDTH, 320 ); cv.SetCaptureProperty( self.capture, cv.CV_CAP_PROP_FRAME_HEIGHT, 240 ); frame = cv.QueryFrame(self.capture) frame_size = cv.GetSize(frame) self.writer = None frame = cv.QueryFrame(self.capture) cv.NamedWindow("Target", 1) def ServoMove(self, servo, angle): servo = self.joymap[servo] if self.joyreverse[servo]: angle = 180 - angle if (0 <= angle <= 180): self.ser.write(chr(255)) self.ser.write(chr(servo)) self.ser.write(chr(angle)) else: print "Servo angle must be an integer between 0 and 180.\n" def run(self): frame = cv.QueryFrame( self.capture ) frame_size = cv.GetSize( frame ) # Capture the first frame from webcam for image properties display_image = cv.QueryFrame( self.capture ) # Greyscale image, thresholded to create the motion mask: grey_image = cv.CreateImage( cv.GetSize(frame), cv.IPL_DEPTH_8U, 1 ) # The RunningAvg() function requires a 32-bit or 64-bit image... running_average_image = cv.CreateImage( cv.GetSize(frame), cv.IPL_DEPTH_32F, 3 ) # ...but the AbsDiff() function requires matching image depths: running_average_in_display_color_depth = cv.CloneImage( display_image ) # RAM used by FindContours(): mem_storage = cv.CreateMemStorage(0) # The difference between the running average and the current frame: difference = cv.CloneImage( display_image ) target_count = 1 last_target_count = 1 last_target_change_t = 0.0 k_or_guess = 1 codebook=[] frame_count=0 last_frame_entity_list = [] t0 = time.time() # For toggling display: image_list = [ "display", "difference", "threshold", "camera", "faces"] image_index = 0 # Index into image_list # Prep for text drawing: text_font = cv.InitFont(cv.CV_FONT_HERSHEY_COMPLEX, .5, .5, 0.0, 1, cv.CV_AA ) text_coord = ( 5, 15 ) text_color = cv.CV_RGB(255,255,255) haar_cascade = cv.Load( 'haarcascades/haarcascade_frontalface_alt.xml' ) max_targets = 3 while True: camera_image = cv.QueryFrame( self.capture ) frame_count += 1 frame_t0 = time.time() # Create an image with interactive feedback: display_image = cv.CloneImage( camera_image ) # Create a working "color image" to modify / blur color_image = cv.CloneImage( display_image ) # Smooth to get rid of false positives cv.Smooth( color_image, color_image, cv.CV_GAUSSIAN, 19, 0 ) # Use the Running Average as the static background # a = 0.020 leaves artifacts lingering way too long. # a = 0.320 works well at 320x240, 15fps. (1/a is roughly num frames.) cv.RunningAvg( color_image, running_average_image, 0.420, None ) # Convert the scale of the moving average. cv.ConvertScale( running_average_image, running_average_in_display_color_depth, 1.0, 0.0 ) # Subtract the current frame from the moving average. cv.AbsDiff( color_image, running_average_in_display_color_depth, difference ) # Convert the image to greyscale. cv.CvtColor( difference, grey_image, cv.CV_RGB2GRAY ) # Threshold the image to a black and white motion mask: cv.Threshold( grey_image, grey_image, 2, 255, cv.CV_THRESH_BINARY ) # Smooth and threshold again to eliminate "sparkles" cv.Smooth( grey_image, grey_image, cv.CV_GAUSSIAN, 19, 0 ) cv.Threshold( grey_image, grey_image, 240, 255, cv.CV_THRESH_BINARY ) cv.Dilate(grey_image, grey_image, None, 18) cv.Erode(grey_image, grey_image, None, 20) grey_image_as_array = numpy.asarray( cv.GetMat( grey_image ) ) non_black_coords_array = numpy.where( grey_image_as_array > 3 ) # Convert from numpy.where()'s two separate lists to one list of (x, y) tuples: non_black_coords_array = zip( non_black_coords_array[1], non_black_coords_array[0] ) points = [] # Was using this to hold either pixel coords or polygon coords. bounding_box_list = [] # Now calculate movements using the white pixels as "motion" data contour = cv.FindContours( grey_image, mem_storage, cv.CV_RETR_CCOMP, cv.CV_CHAIN_APPROX_SIMPLE ) while contour: bounding_rect = cv.BoundingRect( list(contour) ) point1 = ( bounding_rect[0], bounding_rect[1] ) point2 = ( bounding_rect[0] + bounding_rect[2], bounding_rect[1] + bounding_rect[3] ) bounding_box_list.append( ( point1, point2 ) ) polygon_points = cv.ApproxPoly( list(contour), mem_storage, cv.CV_POLY_APPROX_DP ) # To track polygon points only (instead of every pixel): #points += list(polygon_points) # Draw the contours: levels = 0 cv.DrawContours(color_image, contour, cv.CV_RGB(255,0,0), cv.CV_RGB(0,255,0), levels, 3, 0, (0,0) ) cv.FillPoly( grey_image, [ list(polygon_points), ], cv.CV_RGB(255,255,255), 0, 0 ) cv.PolyLine( display_image, [ polygon_points, ], 0, cv.CV_RGB(255,255,255), 1, 0, 0 ) #cv.Rectangle( display_image, point1, point2, cv.CV_RGB(120,120,120), 1) contour = contour.h_next() # Find the average size of the bbox (targets), then # remove any tiny bboxes (which are prolly just noise). # "Tiny" is defined as any box with 1/10th the area of the average box. # This reduces false positives on tiny "sparkles" noise. box_areas = [] for box in bounding_box_list: box_width = box[right][0] - box[left][0] box_height = box[bottom][0] - box[top][0] box_areas.append( box_width * box_height ) #cv.Rectangle( display_image, box[0], box[1], cv.CV_RGB(255,0,0), 1) average_box_area = 0.0 if len(box_areas): average_box_area = float( sum(box_areas) ) / len(box_areas) trimmed_box_list = [] for box in bounding_box_list: box_width = box[right][0] - box[left][0] box_height = box[bottom][0] - box[top][0] # Only keep the box if it's not a tiny noise box: if (box_width * box_height) > average_box_area*0.1: trimmed_box_list.append( box ) # Draw the trimmed box list: #for box in trimmed_box_list: # cv.Rectangle( display_image, box[0], box[1], cv.CV_RGB(0,255,0), 2 ) bounding_box_list = merge_collided_bboxes( trimmed_box_list ) # Draw the merged box list: for box in bounding_box_list: cv.Rectangle( display_image, box[0], box[1], cv.CV_RGB(0,255,0), 1 ) # Here are our estimate points to track, based on merged & trimmed boxes: estimated_target_count = len( bounding_box_list ) if frame_t0 - last_target_change_t < .650: # 1 change per 0.35 secs estimated_target_count = last_target_count else: if last_target_count - estimated_target_count > 1: estimated_target_count = last_target_count - 1 if estimated_target_count - last_target_count > 1: estimated_target_count = last_target_count + 1 last_target_change_t = frame_t0 # Clip to the user-supplied maximum: estimated_target_count = min( estimated_target_count, max_targets ) points = non_black_coords_array center_points = [] if len(points): k_or_guess = max( estimated_target_count, 1 ) # Need at least one target to look for. if len(codebook) == estimated_target_count: k_or_guess = codebook #points = vq.whiten(array( points )) # Don't do this! Ruins everything. codebook, distortion = vq.kmeans( array( points ), k_or_guess ) # Convert to tuples (and draw it to screen) for center_point in codebook: center_point = ( int(center_point[0]), int(center_point[1]) ) center_points.append( center_point ) trimmed_center_points = [] removed_center_points = [] for box in bounding_box_list: # Find the centers within this box: center_points_in_box = [] for center_point in center_points: if center_point[0] < box[right][0] and center_point[0] > box[left][0] and \ center_point[1] < box[bottom][1] and center_point[1] > box[top][1] : # This point is within the box. center_points_in_box.append( center_point ) # Now see if there are more than one. If so, merge them. if len( center_points_in_box ) > 1: # Merge them: x_list = y_list = [] for point in center_points_in_box: x_list.append(point[0]) y_list.append(point[1]) average_x = int( float(sum( x_list )) / len( x_list ) ) average_y = int( float(sum( y_list )) / len( y_list ) ) trimmed_center_points.append( (average_x, average_y) ) # Record that they were removed: removed_center_points += center_points_in_box if len( center_points_in_box ) == 1: trimmed_center_points.append( center_points_in_box[0] ) # Just use it. # If there are any center_points not within a bbox, just use them. # (It's probably a cluster comprised of a bunch of small bboxes.) for center_point in center_points: if (not center_point in trimmed_center_points) and (not center_point in removed_center_points): trimmed_center_points.append( center_point ) # Determine if there are any new (or lost) targets: actual_target_count = len( trimmed_center_points ) last_target_count = actual_target_count # Now build the list of physical entities (objects) this_frame_entity_list = [] # An entity is list: [ name, color, last_time_seen, last_known_coords ] for target in trimmed_center_points: # Is this a target near a prior entity (same physical entity)? entity_found = False entity_distance_dict = {} for entity in last_frame_entity_list: entity_coords= entity[3] delta_x = entity_coords[0] - target[0] delta_y = entity_coords[1] - target[1] distance = sqrt( pow(delta_x,2) + pow( delta_y,2) ) entity_distance_dict[ distance ] = entity # Did we find any non-claimed entities (nearest to furthest): distance_list = entity_distance_dict.keys() distance_list.sort() for distance in distance_list: # Yes; see if we can claim the nearest one: nearest_possible_entity = entity_distance_dict[ distance ] if nearest_possible_entity in this_frame_entity_list: continue # Found the nearest entity to claim: entity_found = True nearest_possible_entity[2] = frame_t0 # Update last_time_seen nearest_possible_entity[3] = target # Update the new location this_frame_entity_list.append( nearest_possible_entity ) break if entity_found == False: # It's a new entity. color = ( random.randint(0,255), random.randint(0,255), random.randint(0,255) ) name = hashlib.md5( str(frame_t0) + str(color) ).hexdigest()[:6] last_time_seen = frame_t0 new_entity = [ name, color, last_time_seen, target ] this_frame_entity_list.append( new_entity ) # Now "delete" any not-found entities which have expired: entity_ttl = 1.0 # 1 sec. ent_count = 0 for entity in last_frame_entity_list: last_time_seen = entity[2] if frame_t0 - last_time_seen > entity_ttl: pass else: # Save it for next time... not expired yet: this_frame_entity_list.append( entity ) ent_count += 1 # For next frame: last_frame_entity_list = this_frame_entity_list # Draw the found entities to screen: count = 0 if ent_count != 0: entity = this_frame_entity_list[0] center_point = entity[3] c = entity[1] # RGB color tuple # print '%s %d %d %d' % (entity[0], count, center_point[0], center_point[1]) cv.Circle(display_image, center_point, 20, cv.CV_RGB(c[0], c[1], c[2]), 1) cv.Circle(display_image, center_point, 15, cv.CV_RGB(c[0], c[1], c[2]), 1) cv.Circle(display_image, center_point, 10, cv.CV_RGB(c[0], c[1], c[2]), 2) cv.Circle(display_image, center_point, 5, cv.CV_RGB(c[0], c[1], c[2]), 3) text_font = cv.InitFont(cv.CV_FONT_HERSHEY_COMPLEX, .5, .5, 0.0, 1, cv.CV_AA ) text_coord = ( 5, 15 ) text_color = cv.CV_RGB(255,255,255) x = 50 + (center_point[0] * 80 / 320) y = 20 + (center_point[1] * 80 / 240) if self.have_eye: self.ServoMove(0, int(x)) self.ServoMove(1, int(y)) s = '%3.0d %3.0d' % (x, y) cv.PutText(display_image, str(s), text_coord, text_font, text_color ) #print "min_size is: " + str(min_size) # Listen for ESC or ENTER key c = cv.WaitKey(7) % 0x100 if c == 27 or c == 10: break # Toggle which image to show if chr(c) == 'd': image_index = ( image_index + 1 ) % len( image_list ) image_name = image_list[ image_index ] # Display frame to user if image_name == "display": image = display_image # cv.PutText( image, "AABBs and contours", text_coord, text_font, text_color ) elif image_name == "camera": image = camera_image cv.PutText( image, "No overlay", text_coord, text_font, text_color ) elif image_name == "difference": image = difference cv.PutText( image, "Difference Image", text_coord, text_font, text_color ) elif image_name == "faces": # Do face detection detect_faces( camera_image, haar_cascade, mem_storage ) image = camera_image # Re-use camera image here cv.PutText( image, "Face Detection", text_coord, text_font, text_color ) elif image_name == "threshold": # Convert the image to color. cv.CvtColor( grey_image, display_image, cv.CV_GRAY2RGB ) image = display_image # Re-use display image here cv.PutText( image, "Motion Mask", text_coord, text_font, text_color ) cv.ShowImage( "Target", image ) if self.writer: cv.WriteFrame( self.writer, image ); frame_t1 = time.time() t1 = time.time() time_delta = t1 - t0 processed_fps = float( frame_count ) / time_delta print "Got %d frames. %.1f s. %f fps." % ( frame_count, time_delta, processed_fps ) if __name__=="__main__": t = Target() t.run()

[ "rshdpbx@gmail.com" ]

rshdpbx@gmail.com

b57452e38a1139dde3005b8cd198b2ac97024466

ca19d3793ac651292a04351aa5328fc6035afe6a

/함수버튼연습01.py

24076841df4dd2123ba5c7121e2282cef6a58441

[]

no_license

lyricalzy/python

fd490ab068d290bf94812927ae92aa50ab56f50f

cb0e2d712f2a14e34fbe654ba68981623af544dc

refs/heads/master

2021-01-02T02:10:39.128811

2020-02-18T07:29:09

239,447,495

0

null

UTF-8

Python

false

1,103

py

from tkinter import * def file_write(): print("저장") fruit = ["사과", "바나나", "배"] # 파일에 저장 fruit_file = open("fruit.txt", "w") for x in fruit: fruit_file.write(x + "\n") fruit_file.close() def file_write2(): print("저장2") fruit2 = [] for i in range(0, 5): fruit2.append(input("과일 입력: ")) print(fruit2) # 파일에 저장 # fruit_file = open("fruit.txt", "w") # for x in fruit: # fruit_file.write(x + "\n") # fruit_file.close() def file_read(): print("읽기") file = open("fruit.txt", "r") for j in range(0,3): temp = file.readline() data = temp.strip() print(data) file.close() w = Tk() # 프레임을 만들어 주는 함수 w.geometry("200x150") button1 = Button(w, text="저장", bg="green", font=("새 굴림", 30), fg="white", command=file_write) button1.pack() button2 = Button(w, text="읽기", bg="green", font=("새 굴림", 30), fg="white", command=file_read) button2.pack() w.mainloop()

[ "noreply@github.com" ]

lyricalzy.noreply@github.com

fe4f0bb60158fead685319319500402ec7300cde

9719df2dc131aa1189acef7273bee090290becd6

/Chapter 12/E2.py

498cf9b3da0bb1ac95ec433c8cbb8d026b8b1f4e

[ "MIT" ]

permissive

hanzhi713/thinkcs-python3-solutions

df72e9d76779a5ffb9a8f9a9316c672a021feece

290b34df7d9c7f45daebd1af6017a03828ec8eb4

refs/heads/master

2020-03-31T10:03:03.301775

2018-10-08T17:41:10

152,120,690

13

7

null

UTF-8

Python

false

475

py

import math help(math) # (a) # 44 # (b) # math.ceil(x) ''' Return the ceiling of x as an Integral This is the smallest integer >= x.''' # math.floor(x) '''Return the floor of x as an Integral This is the largest integer <=x ''' # (c) By using Newton's algorithm '''def sqrt(n): approx = n/2.0 while True: better = (approx + n/approx)/2.0 if abs(approx - better) < 0.001: return better approx = better''' # (d) math.pi math.e

[ "hanzhi713@163.com" ]

hanzhi713@163.com

f3dd6f0fa00130a093838604fbcd31efa45166f1

d5e4953aae14a27fed713bc2fe21ee41df9c2f92

/current_omega.py

89af93f5344a07989d76afd9a04a72185dd7fbf3

[ "BSD-2-Clause" ]

permissive

j-silver/quantum_dots

c7714822741f0b0807ec254a475ddcbf7d2322d4

54132a3c7dd0e83e27375f6c5f6ec154065a9695

refs/heads/master

2021-01-22T12:12:05.048203

2017-02-13T17:29:14

26,187,902

0

null

UTF-8

Python

false

693

py

#!/usr/bin/env python import matplotlib.pyplot as plt import numpy as np fig = plt.figure() #fig.suptitle('Asymptotic current as a function of the frequency $\Omega$') plt.xlabel('$\Omega/\\Delta$') plt.ylabel('$I/I_0$') plt.xscale('log') plt.grid('on') #plt.text(0.005, 0.15, '$\\frac{\kappa_B T}{\hbar\Delta}=1$\n$\\alpha=0.005$', bbox={'facecolor':'white','alpha':0.8}) R_CURRT = (np.loadtxt('RED-STAT-CURR-O.dat')).T C_CURRT = (np.loadtxt('CP-STAT-CURR-O.dat')).T rfig = plt.plot(R_CURRT[0], R_CURRT[1], color='red', label='Redfield dynamics') cfig = plt.plot(C_CURRT[0], C_CURRT[1], color='blue', label='CP dynamics') plt.legend(('Redfield dynamics', 'CP dynamics')) plt.show()

[ "giuseppe.argentieri@ts.infn.it" ]

giuseppe.argentieri@ts.infn.it

0f253f10f1a06bb12051b106aaf606e8818c0a2f

ad11d4b949d480054c3d6259acca0aed6aa809c7

/07-string-manipulation.py

c157469dfa0010c72f7f45d77b6f771e016c4bd6

[]

no_license

kamranajabbar/python3_practice

08263e3a0a49131b38f813c6e79593f8b26bb108

312b3225d11cb22b1358185d9b91d971ecdf865d

refs/heads/master

2023-03-06T07:33:55.471101

2021-02-03T13:40:51

276,912,414

0

null

UTF-8

Python

false

1,516

py

#Chapter # 24 String changing case name = "Kamran" print("String in Upper Case : ", name.upper()) print("String in Lower Case : ", name.lower()) print("String in Capitale Case : ", name.capitalize()) print("String in Title Case : ", name.title()) str = "hello" print(str[:2]) string = "my name is x" for i in string.split(): print(i, end=", ") print("\n") x=1 y=2 z=x x=y y=z print(x,y) A = 16 B = 15 print(A % B // A) print("-------- Q14 -----") for i in range(10): if i == 5: break else: print(i) else: print("Here") print("-------- Q15 -----") list1 = [1, 3, 2] print(list1 * 2) print("-------- Q16 -----") a = {} a[1] = 1 a['1'] = 2 a[1] = a[1]+1 count = 0 for i in a: count += a[i] print(count) print("-------- Q17 -----") numbers = [1,2,3,4] numbers.append([5,6,7,8]) print(len(numbers)) print("-------- Q18 -----") names = ['Amir','Bear','Chariton','Daman'] print(names[-1][-1]) print("-------- Q19 -----") names = [1,2,3,4] print(names[-3:-2]) print("-------- Q20 -----") abc = {"KJ":78} xyz = {"AJ":156} print(abc == xyz) print("-------- Q22 -----") x = 1 / 2.0 + 3//3 + 4 ** 1 print(x) print("-------- Q23 -----") a = [11,2,23] b = [11,2,2] print(a < b) print("-------- Q24 -----") a = {1:5,2:3,3:4} a.pop(3) print(a) print("-------- Q27 -----") abc = {"KJ":40, "AJ":45} print("KJ" in abc) print("-------- Q29 -----") s1 = [3,4] s2 = [1,2] s3 = list() i=0 j=0 for i in s1: for j in s2: s3.append((i,j)) i +=1 j +=1 print(s3)

[ "kamranajabbar@gmail.com" ]

kamranajabbar@gmail.com

0528d2db08b2589fe1bc93ac70b28626a3b8a954

a6d1b9bccdf8b06c7623c786c67d04ca15d3a69b

/CCNP1.py

72b524e619673b03e67cb555737ddc556b56fbd8

[]

no_license

amrkhailr/cbtnuggets

f6a584aa4f05dc53af213acfc202fc5caf51bac8

d43a52ae72e3725e2eb6b8776ba609b161dca34a

refs/heads/master

2022-09-16T02:45:34.564816

2020-05-30T04:38:48

267,768,503

0

null

UTF-8

Python

false

387

py

#my_list = [1,2,3,4] #my_list[2] = 45 #A = my_list *3 #print(A) #my_list = [1024, 3, True, 6.5] #my_list.append(False) #print(my_list) import datetime def greet(): dt = datetime.datetime.now() if dt.hour <= 11 : greeting = 'morning' elif dt.hour <= 17: greeting = 'afternoon' else: greeting = 'night' print("Hello, good",greeting) greet()

[ "romal.amarkhail@gmail.com" ]

romal.amarkhail@gmail.com

67a6acbe758dcaaf23938c3fc0d98b472cb4158a

bbc972524d9f0ccf95fbac30de2f7a7c0a1badf2

/tests/unit2/test_physics_engine2.py

3471b8c35fa6908f0a23c110a0d89d792ff38987

[ "MIT" ]

permissive

JFincher42/arcade

e0049b84b0317a0fd9eee3702e4e6e843cc2ebac

f9eebfc4c6989e0e99d7b6dfe0409f248bfd5a44

refs/heads/master

2021-06-29T20:41:31.850895

2021-03-18T14:43:01

226,012,595

0

NOASSERTION

2021-03-18T14:45:09

2019-12-05T04:00:26

Python

UTF-8

Python

false

10,576

py

""" Physics engine tests. """ import arcade OUT_OF_THE_WAY = (250, 250) def basic_tests(moving_sprite, wall_list, physics_engine): """ Run basic tests that can be done by both engines. """ wall_sprite_1 = wall_list[0] wall_sprite_2 = wall_list[1] wall_sprite_2.position = OUT_OF_THE_WAY # --- Collisions between a moving sprite and one wall block # Two non-moving sprites side-by-side wall_sprite_1.position = (10, 0) wall_sprite_1.angle = 0 moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 0 collisions = physics_engine.update() assert moving_sprite.position == (0, 0) assert len(collisions) == 0 # Move up to wall wall_sprite_1.position = (11, 0) moving_sprite.position = (0, 0) moving_sprite.change_x = 1 moving_sprite.change_y = 0 collisions = physics_engine.update() assert moving_sprite.position == (1, 0) assert len(collisions) == 0 # Move into wall going left to right for speed in range(2, 10): wall_sprite_1.position = (11, 0) moving_sprite.position = (0, 0) moving_sprite.change_x = speed moving_sprite.change_y = 0 collisions = physics_engine.update() assert(moving_sprite.position == (1, 0)) assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 # Move into wall going right to left for speed in range(2, 10): wall_sprite_1.position = (-11, 0) moving_sprite.position = (0, 0) moving_sprite.change_x = -speed moving_sprite.change_y = 0 collisions = physics_engine.update() assert(moving_sprite.position == (-1, 0)) assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 # Move into wall going downwards for speed in range(2, 10): wall_sprite_1.position = (0, -11) moving_sprite.position = (0, 0) moving_sprite.change_x = 0 moving_sprite.change_y = -speed collisions = physics_engine.update() assert(moving_sprite.position == (0, -1)) assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 # Move into wall going up for speed in range(2, 10, 1): wall_sprite_1.position = (0, 11) moving_sprite.position = (0, 0) moving_sprite.change_x = 0 moving_sprite.change_y = speed collisions = physics_engine.update() assert(moving_sprite.position == (0, 1)) assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 # --- Check rotating collision # - Rotate, with block to the right # Check rotation one degree wall_sprite_1.position = (10, 0) moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 1 collisions = physics_engine.update() assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 assert moving_sprite.position == (-1, 0) # Check rotation 45 degrees wall_sprite_1.position = (10, 0) moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 45 collisions = physics_engine.update() assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 assert moving_sprite.position == (-4, 0) # - Rotate, with block to the left # Check rotation one degree wall_sprite_1.position = (-10, 0) moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 1 collisions = physics_engine.update() assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 assert moving_sprite.position == (1, 0) # Check rotation 45 degrees wall_sprite_1.position = (-10, 0) moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 45 collisions = physics_engine.update() assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 assert moving_sprite.position == (4, 0) # - Rotate, with block above # Check rotation one degree wall_sprite_1.position = (0, 10) moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 1 collisions = physics_engine.update() assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 assert moving_sprite.position == (0, -1) # Check rotation 45 degrees wall_sprite_1.position = (0, 10) moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 45 collisions = physics_engine.update() assert len(collisions) == 1 assert collisions[0] == wall_sprite_1 assert moving_sprite.position == (0, -4) # - Rotate, between two blocks # Check rotation one degree wall_sprite_1.position = (10, 0) wall_sprite_2.position = (-10, 0) moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 1 collisions = physics_engine.update() assert len(collisions) == 2 assert wall_sprite_1 in collisions assert wall_sprite_2 in collisions assert moving_sprite.position == (0, 0) # --- Check pre-existing collision wall_sprite_1.position = (9, 0) wall_sprite_2.position = OUT_OF_THE_WAY moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = 0 moving_sprite.change_y = 0 moving_sprite.change_angle = 0 collisions = physics_engine.update() assert moving_sprite.position == (-1, 0) assert len(collisions) == 0 def simple_engine_tests(moving_sprite, wall_list, physics_engine): wall_sprite_1 = wall_list[0] wall_sprite_2 = wall_list[1] wall_sprite_2.position = OUT_OF_THE_WAY # --- Collide on angle wall_sprite_1.position = (15, -5) wall_sprite_1.angle = 45 for speed in range(2, 10): moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = speed moving_sprite.change_y = 0 moving_sprite.change_angle = 0 collisions = physics_engine.update() assert moving_sprite.position == (2, 0) if speed == 2: assert len(collisions) == 0 else: assert len(collisions) == 1 wall_sprite_1.position = (-15, -5) wall_sprite_1.angle = 45 for speed in range(2, 10): moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = -speed moving_sprite.change_y = 0 moving_sprite.change_angle = 0 collisions = physics_engine.update() assert moving_sprite.position == (-2, 0) if speed == 2: assert len(collisions) == 0 else: assert len(collisions) == 1 def platformer_tests(moving_sprite, wall_list, physics_engine): wall_sprite_1 = wall_list[0] wall_sprite_2 = wall_list[1] wall_sprite_2.position = OUT_OF_THE_WAY wall_sprite_1.position = (15, -5) wall_sprite_1.angle = 45 moving_sprite.position = (3, 1) moving_sprite.angle = 0 collisions = arcade.check_for_collision_with_list(moving_sprite, wall_list) print(f"\n **** {len(collisions)}") print("") # --- Collide on angle wall_sprite_1.position = (15, -5) wall_sprite_1.angle = 45 for speed in range(2, 7): moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = speed moving_sprite.change_y = 0 moving_sprite.change_angle = 0 collisions = physics_engine.update() if speed == 2: assert moving_sprite.position == (2, 0) elif speed == 3: assert moving_sprite.position == (3, 1) elif speed == 4: assert moving_sprite.position == (4, 2) elif speed == 5: assert moving_sprite.position == (5, 3) elif speed == 6: assert moving_sprite.position == (6, 4) wall_sprite_1.position = (-15, -5) wall_sprite_1.angle = 45 for speed in range(2, 7): moving_sprite.position = (0, 0) moving_sprite.angle = 0 moving_sprite.change_x = -speed moving_sprite.change_y = 0 moving_sprite.change_angle = 0 collisions = physics_engine.update() if speed == 2: assert moving_sprite.position == (-2, 0) elif speed == 3: assert moving_sprite.position == (-3, 1) elif speed == 4: assert moving_sprite.position == (-4, 2) elif speed == 5: assert moving_sprite.position == (-5, 3) elif speed == 6: assert moving_sprite.position == (-6, 4) # Move up to wall wall_sprite_1.position = OUT_OF_THE_WAY physics_engine.gravity_constant = 1 moving_sprite.position = (0, 0) moving_sprite.change_x = 1 moving_sprite.change_y = 0 collisions = physics_engine.update() assert moving_sprite.position == (1, -1) collisions = physics_engine.update() assert moving_sprite.position == (2, -3) collisions = physics_engine.update() assert moving_sprite.position == (3, -6) def test_main(twm): if twm: assert True else: character_list = arcade.SpriteList() wall_list = arcade.SpriteList() moving_sprite = arcade.SpriteSolidColor(10, 10, arcade.color.RED) character_list.append(moving_sprite) wall_sprite = arcade.SpriteSolidColor(10, 10, arcade.color.BLUE) wall_list.append(wall_sprite) wall_sprite = arcade.SpriteSolidColor(10, 10, arcade.color.BLUE) wall_sprite.position = OUT_OF_THE_WAY wall_list.append(wall_sprite) physics_engine = arcade.PhysicsEngineSimple(moving_sprite, wall_list) basic_tests(moving_sprite, wall_list, physics_engine) simple_engine_tests(moving_sprite, wall_list, physics_engine) physics_engine = arcade.PhysicsEnginePlatformer(moving_sprite, wall_list, gravity_constant=0.0) basic_tests(moving_sprite, wall_list, physics_engine) platformer_tests(moving_sprite, wall_list, physics_engine)

[ "jfincher42@gmail.com" ]

jfincher42@gmail.com

0410e802c2b0556f2ca3888c0be9ecdc86e6ebad

bb64ff9d2a6f65afaa44f3be70c42c897f635552

/lingtools/util/__init__.py

e062e4b70aba09208003b4352fa6809bd430629b

[ "Apache-2.0" ]

permissive

lingtools/lingtools

c173bfcfa1bcf1c92c94eb424f89754e9e9388aa

cd5b44a5552fdc79ec99c61dfe526face8df522b

refs/heads/master

2021-01-21T04:25:07.160936

2015-01-17T19:44:21

16,148,868

7

2

null

2016-09-20T14:50:05

2014-01-22T18:52:49

Python

UTF-8

Python

false

26

py

""" Utility modules. """

[ "lignos@seas.upenn.edu" ]

lignos@seas.upenn.edu

dc28c4cec7ece6aebe88802c998a185fdf40a5c3

28c971e96bc3236bf6988feab8d7f0b41b9d031e

/2018_Informatik_l/Ex_03/task_1.py

e844534f63ddf8195c7fc33e6ceb49518b6ecf61

[]

no_license

Olstra/UZH

98cc2ba3e9db0dbe4fafc0b6ac7266f2b4bf7722

038d6a2b0b97a7ee22988fd47f4025a70473929c

refs/heads/master

2020-04-23T12:35:15.064379

2019-08-27T20:26:49

171,174,293

0

null

UTF-8

Python

false

442

py

# Please do not modify this part of the code! grade = '-' # Your code goes here score = int(input("Type in your achieved score: ")) if score in range(0, 101): score = int(score) if score >= 90: grade = 'A' elif score >= 80: grade = 'B' elif score >= 70: grade = 'C' elif score >= 60: grade = 'D' else: grade = 'F' else: print("\nERROR: Please enter a number from 0-100.")

[ "noreply@github.com" ]

Olstra.noreply@github.com

c6c4755f951b1c39f607d3b3cc37c99b18d92b88

425b8bb7ea01bfd9e59706f461e9fb7a2550a5fb

/manage.py

c5f42ea6e4c995c1c2f89f39910985906fd057aa

[]

no_license

pwbryant/superno3

c8798b9f5caeca47ab1d9ab888832704fe7c5a8e

96c2a14ce219b9360e38d98851d907abbd073b28

refs/heads/master

2021-01-01T03:47:51.129801

2016-04-28T21:26:17

57,334,855

0

null

UTF-8

Python

false

251

py

#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "superno3.settings") from django.core.management import execute_from_command_line execute_from_command_line(sys.argv)

[ "paulwilliambryant@gmail.com" ]

paulwilliambryant@gmail.com

a6252bfecc3583b46f38cb2e68d103cb8493e682

f6fd11d996bee6455e8e6cf35a2ad0b615c51665

/saengsorn-6230403955-lab2/dict_strings.py.py

2d75c075690291ab2e1ced056c49dddc24a1b72a

[]

no_license

Saengsorn-Wongpriew/6230403955-oop-labs

f4c80679542b44fb36cca62ebbd68038c10fbdb5

735dbe1c57e826bce5617884a4ada529025b112b

refs/heads/master

2023-01-16T02:38:10.830465

2020-11-20T09:51:30

284,725,036

1

0

null

UTF-8

Python

false

387

py

dictionary = { "manee": "1234", "mana": "4567", "chujai": "6789" } t = list(dictionary.items()) print(t) v = list(dictionary.values()) print(v) k = list(dictionary.keys()) print(k) word = "antidisestablishmentarianism" word = sorted(word) print(''.join(word)) sentence = "the quick brown fox jumped over the lazy dog" w = sentence.split() print(w)

[ "noreply@github.com" ]

Saengsorn-Wongpriew.noreply@github.com

85267b1060a3e2d33902bc2af850b6da6644a4ed

09c96fa897f9a9818c656548d1e234c40648a350

/ls/joyous/tests/test_recurrence.py

8150de7c95c398674e2384bad33e08d7a7727cf2

[ "BSD-3-Clause" ]

permissive

linuxsoftware/ls.joyous

45bfbe376c154cdbfea6ae1fa6d5e6cf9a7222b1

7c408d52ab935140c69f6c12379655e39e8b5ca5

refs/heads/master

2023-08-30T02:14:33.518824

2022-07-01T03:11:34

120,979,220

85

38

BSD-3-Clause

2023-08-07T10:43:25

2018-02-10T03:02:51

Python

UTF-8

Python

false

11,790

py

# ------------------------------------------------------------------------------ import sys import datetime as dt from dateutil.rrule import rrule from django.test import TestCase from ls.joyous.utils.recurrence import Recurrence, Weekday from ls.joyous.utils.recurrence import MO, TU, WE, TH, FR, SA, SU from ls.joyous.utils.recurrence import YEARLY, MONTHLY, WEEKLY, DAILY from .testutils import datetimetz # ------------------------------------------------------------------------------ class TestWeekday(TestCase): def testStr(self): self.assertEqual(str(Weekday(0)), "Monday") self.assertEqual(str(Weekday(4,1)), "first Friday") self.assertEqual(str(Weekday(4,-1)), "last Friday") self.assertEqual(str(SA), "Saturday") self.assertEqual(str(FR(3)), "third Friday") def testGetWhen(self): self.assertEqual(Weekday(0)._getWhen(0), "Monday") self.assertEqual(FR(1)._getWhen(0), "first Friday") self.assertEqual(SU._getWhen(1), "Monday") self.assertEqual(WE._getWhen(-2), "Monday") self.assertEqual(FR(1)._getWhen(-1), "Thursday before the first Friday") self.assertEqual(SU(1)._getWhen(2), "Tuesday after the first Sunday") def testRepr(self): self.assertEqual(repr(Weekday(0)), "MO") self.assertEqual(repr(Weekday(4,2)), "+2FR") self.assertEqual(repr(SA), "SA") self.assertEqual(repr(FR(3)), "+3FR") self.assertEqual(repr(WE(-2)), "-2WE") # ------------------------------------------------------------------------------ class TestRecurrence(TestCase): def testInitStr(self): with self.assertRaises(ValueError): Recurrence("DTSTART:19970902T090000\n" "RRULE:FREQ=DAILY;INTERVAL=3\n" "RRULE:FREQ=DAILY;INTERVAL=4") def testInitRecurrence(self): rr1 = Recurrence(dtstart=dt.date(2009, 1, 1), freq=WEEKLY, byweekday=[MO,TU,WE,TH,FR]) rr2 = Recurrence(rr1) self.assertEqual(rr2.freq, WEEKLY) def testInitRrule(self): rr1 = rrule(dtstart=dt.date(2009, 1, 1), freq=WEEKLY, byweekday=[MO,TU,WE,TH,FR]) rr2 = Recurrence(rr1) self.assertEqual(rr2.freq, WEEKLY) def testEq(self): rr1 = rrule(dtstart=dt.datetime(2009, 1, 1, 0, 0, 1), freq=WEEKLY, byweekday=[MO,TU,WE,TH,FR]) rr2 = Recurrence(dtstart=dt.date(2009, 1, 1), freq=WEEKLY, byweekday=[MO,TU,WE,TH,FR]) rr3 = Recurrence("DTSTART:20090101\n" "RRULE:FREQ=WEEKLY;WKST=SU;BYDAY=MO,TU,WE,TH,FR") rr4 = rrule(dtstart=dt.date(2009, 1, 1), freq=WEEKLY, byweekday=[MO,TU,WE,TH,FR], until=dt.date(2009, 1, 10)) self.assertEqual(Recurrence(rr1), rr2) self.assertEqual(rr2, rr1) self.assertEqual(rr1, rr2) self.assertEqual(rr2, rr2) self.assertEqual(rr2, rr3) self.assertNotEqual(rr2, 99) self.assertNotEqual(rr2, rr4) def testRepr(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=WEEKLY, count=9, byweekday=[MO,TU,WE,TH,FR]) self.assertEqual(repr(rr), "DTSTART:20090101\n" "RRULE:FREQ=WEEKLY;WKST=SU;COUNT=9;BYDAY=MO,TU,WE,TH,FR") self.assertEqual(rr.count, rr.getCount()) rr = Recurrence(dtstart=dt.date(2011, 1, 1), freq=DAILY, interval=2, until=dt.date(2011,1,11)) self.assertEqual(repr(rr), "DTSTART:20110101\n" "RRULE:FREQ=DAILY;INTERVAL=2;WKST=SU;UNTIL=20110111") rr = Recurrence(dtstart=dt.date(2012, 1, 1), freq=YEARLY, bymonth=[1,2], byweekday=range(7), until=dt.date(2012,1,31)) self.assertEqual(repr(rr), "DTSTART:20120101\n" "RRULE:FREQ=YEARLY;WKST=SU;UNTIL=20120131;" "BYDAY=MO,TU,WE,TH,FR,SA,SU;BYMONTH=1,2") rr = Recurrence(dtstart=dt.date(2015, 10, 1), freq=MONTHLY, bymonth=range(1,12), byweekday=[(SU(-1))]) self.assertEqual(repr(rr), "DTSTART:20151001\n" "RRULE:FREQ=MONTHLY;WKST=SU;BYDAY=-1SU;BYMONTH=1,2,3,4,5,6,7,8,9,10,11") def testParse(self): rr = Recurrence("DTSTART:20090101\n" "RRULE:FREQ=WEEKLY;WKST=SU;BYDAY=MO,TU,WE,TH,FR;COUNT=9") self.assertEqual(rr.dtstart, dt.date(2009, 1, 1)) self.assertEqual(rr.count, 9) self.assertCountEqual(rr.byweekday, [MO,TU,WE,TH,FR]) def testParseNoDtstart(self): rr = Recurrence("RRULE:FREQ=DAILY;WKST=SU") self.assertEqual(rr.freq, DAILY) def testRoundtrip(self): rrStr = "DTSTART:20151001\n" \ "RRULE:FREQ=MONTHLY;WKST=SU;BYDAY=-1SU;BYMONTH=1,2,3,4,5,6,7,8,9,10,11" self.assertEqual(repr(Recurrence(rrStr)), rrStr) rrStr = "DTSTART:20141001\n" \ "RRULE:FREQ=MONTHLY;WKST=SU;UNTIL=20141001;BYMONTHDAY=1,-1" # first&last self.assertEqual(repr(Recurrence(rrStr)), rrStr) def testFrequency(self): rr = Recurrence(freq=10) self.assertEqual(rr.frequency, "unsupported_frequency_10") def testGetRrule(self): rr = Recurrence(dtstart=dt.date(2011, 1, 1), freq=DAILY, interval=2, until=dt.date(2011,1,11)) self.assertEqual(rr._getRrule(), "FREQ=DAILY;INTERVAL=2;WKST=SU;UNTIL=20110111") with self.assertRaises(TypeError): rr._getRrule(untilDt=dt.datetime(2011,1,11)) self.assertEqual(rr._getRrule(untilDt=dt.datetime(2011,1,11,23,59,59, tzinfo=dt.timezone.utc)), "FREQ=DAILY;INTERVAL=2;WKST=SU;UNTIL=20110111T235959Z") # ------------------------------------------------------------------------------ class TestGetWhen(TestCase): def testDaily(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=DAILY) self.assertEqual(rr._getWhen(2), "Daily") def testEvery2Days(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), interval=2, freq=DAILY) self.assertEqual(rr._getWhen(3), "Every 2 days") def testMonEveryFortnight(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), interval=2, freq=WEEKLY, byweekday=MO) self.assertEqual(rr._getWhen(0), "Fortnightly on Mondays") def testMonEvery6Weeks(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), interval=6, freq=WEEKLY, byweekday=MO) self.assertEqual(rr._getWhen(0), "Every 6 weeks on Mondays") def testEveryday(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, byweekday=[MO,TU,WE,TH,FR,SA,SU]) self.assertEqual(rr._getWhen(0), "Everyday") def testFirstMonMonthly(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, byweekday=MO(1)) self.assertEqual(rr._getWhen(0), "The first Monday of the month") def testMonEvery2Months(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), interval=2, freq=MONTHLY, byweekday=MO) self.assertEqual(rr._getWhen(0), "Every Monday, every 2 months") def testLastSatSeptEvery2Years(self): rr = Recurrence(dtstart=dt.date(2018, 9, 29), interval=2, freq=YEARLY, byweekday=SA(-1), bymonth=9) self.assertEqual(rr._getWhen(0, numDays=5), "The last Saturday of September, every 2 years for 5 days") def test1st(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, bymonthday=1) self.assertEqual(rr._getWhen(0), "The first day of the month") def test22ndOffsetNeg1(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=YEARLY, bymonthday=22, bymonth=5) self.assertEqual(rr._getWhen(-1), "The 21st day of May") def test30thOffset1(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, bymonthday=30) self.assertEqual(rr._getWhen(1), "The day after the 30th day of the month") def testMonWedFriOffset1(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=WEEKLY, count=9, byweekday=[MO,WE,FR]) self.assertEqual(rr._getWhen(1), "Tuesdays, Thursdays and Saturdays") def test2ndAnd4thFriOffsetNeg1(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, byweekday=[FR(2),FR(4)]) self.assertEqual(rr._getWhen(-1), "The Thursday before the second Friday and " "Thursday before the fourth Friday of the month") def test1stOffsetNeg1(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, bymonthday=1, until=dt.date(2010,5,1)) self.assertEqual(rr._getWhen(-1), "The last day of the month (until 30 April 2010)") def test3rdOffset2(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, bymonthday=3) self.assertEqual(rr._getWhen(2), "The fifth day of the month") def test1stJanAprMayOffsetNeg1(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=YEARLY, bymonthday=1, bymonth=[1,4,5]) self.assertEqual(rr._getWhen(-1), "The last day of December, March and April") def testLastJulAugSepDecOffset1(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=YEARLY, bymonthday=-1, bymonth=[7,8,9,12]) self.assertEqual(rr._getWhen(1), "The first day of August, September, October and January") def test1stAndLast(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, bymonthday=[1,-1]) self.assertEqual(rr._getWhen(0), "The first and the last day of the month") def test1stAndLastOffsetNeg1(self): rr = Recurrence(dtstart=dt.date(2009, 1, 1), freq=MONTHLY, bymonthday=[1,-1]) self.assertEqual(rr._getWhen(-1), "The day before the first and the last day of the month") # ------------------------------------------------------------------------------ # ------------------------------------------------------------------------------ # ------------------------------------------------------------------------------

[ "david@linuxsoftware.co.nz" ]

david@linuxsoftware.co.nz

a80034d2228bbfe9990d1fb8127411bc8c05716d

709724e7afcd3fb3247e62bcd3542f50a4addbbc

/DataDisplay/migrations/0011_auto_20180328_1054.py

703262fe4757f91a1547243beade1c1d54f1f3f8

[]

no_license

fuckgitb/Design-and-Implementation-of-Multi-source-and-Multi-category-Graphic-Data-Monitoring-Platform

16a4e9de61d5f00cba88cc6b46c12416599457ca

1af69f652f79cde986d241572f94eb0c2945445c

refs/heads/master

2021-09-17T18:34:28.947608

2018-07-04T12:22:57

null

0

null

UTF-8

Python

false

453

py

# Generated by Django 2.0.2 on 2018-03-28 02:54 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('DataDisplay', '0010_auto_20180328_1043'), ] operations = [ migrations.AlterField( model_name='headline_images', name='id', field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), ), ]

[ "781137149@qq.com" ]

781137149@qq.com

e9a5e3f9fdecab88a9a87cac35f2bb503c83b4a9

fd696d4ee723adf8a6ff2ab8cfdd4491bdb6cb9e

/usuarios/views.py

3fe47cc28a75849bb8b73512783b4f0c7253b0a4

[]

no_license

gonzalinismo/wertu

b2fb9752c4995ad330c6df7448f2d34adecacb43

dfcdafd489a02cdaf3bfad048064e282055c17d3

refs/heads/master

2020-05-31T13:27:53.403210

2019-06-05T14:00:56

190,304,668

0

null

2019-06-05T14:00:57

2019-06-05T01:25:29

Python

UTF-8

Python

false

1,881

py

from django.shortcuts import render from .forms import UserForm from django.contrib.auth import authenticate, login, logout from django.http import HttpResponseRedirect, HttpResponse from django.urls import reverse from django.contrib.auth.decorators import login_required @login_required def special(request): return HttpResponse("You are logged in !") @login_required def user_logout(request): logout(request) return HttpResponseRedirect(reverse('index')) def register(request): registered = False if request.method == 'POST': user_form = UserForm(data=request.POST) if user_form.is_valid(): user = user_form.save() user.set_password(user.password) user.save() registered = True else: print(user_form.errors) else: user_form = UserForm() return render(request,'registration.html', {'user_form':user_form, 'registered':registered}) def user_login(request): if request.method == 'POST': username = request.POST.get('username') password = request.POST.get('password') user = authenticate(username=username, password=password) if user: if user.is_active: login(request,user) return HttpResponseRedirect('../../misTiendas') else: return HttpResponse("Your account was inactive.") print("salame") else: print("Someone tried to login and failed.") print("They used username: {} and password: {}".format(username,password)) return HttpResponse("Invalid login details given") else: return render(request, 'login.html', {})

[ "noreply@github.com" ]

gonzalinismo.noreply@github.com

23134786c8fbf5948cdc7ff5c1655121e2bc1b2a

292d6c07588d14385f6875d75adea517f0df4f23

/Centralized_Learning/Centralized_Learning.py

d5633144153179b671209e3a47d8815afaaa53a4

[]

no_license

wangyingwwyy/Privacy-Preserving-Federated-Learning-I

17c236fcdda3632beb31a703893e6ff5741e1b93

c2f22f3310eaa8dc78492b836e4cf30956eca61a

refs/heads/master

2023-04-19T13:29:46.580799

2021-05-10T13:18:21

352,018,276

1

0

null

UTF-8

Python

false

5,738

py

import pandas as pd import numpy as np import tensorflow as tf import tensorflow.keras as keras from tensorflow.keras import layers from tensorflow.keras import models from tensorflow.keras import regularizers from tensorflow.keras.callbacks import ModelCheckpoint from sklearn.metrics import confusion_matrix import os from os import path from datetime import datetime import csv def build_model(): input_dim = 115 model = tf.keras.Sequential() model.add(layers.Input(shape=(input_dim,))) model.add(layers.Dense(int(0.75 * input_dim), activation='relu')) model.add(layers.Dense(int(0.5 * input_dim), activation='relu')) model.add(layers.Dense(int(0.33 * input_dim), activation='relu')) model.add(layers.Dense(int(0.25 * input_dim), activation='relu')) model.add(layers.Dense(int(0.33 * input_dim), activation='relu')) model.add(layers.Dense(int(0.5 * input_dim), activation='relu')) model.add(layers.Dense(int(0.75 * input_dim), activation='relu')) model.add(layers.Dense(input_dim)) return model def train_model(epochs): train_data = pd.read_csv('../train_validation_test_minmax/train_centralized.csv') train_data = train_data.sample(frac = 1) print('reading train_data') print(train_data) validation_data = pd.read_csv('../train_validation_test_minmax/validation_centralized.csv') validation_data = validation_data.sample(frac=1) print('reading validation_data') print(validation_data) model = build_model() model.load_weights('../initial_weight/weight.h5') print('initial weight') print(model.get_weights()) Optimizer = keras.optimizers.SGD() model.compile(optimizer=Optimizer, loss="mean_squared_error", metrics=['accuracy']) print('data for training') print(train_data.iloc[:, :-2]) print('data for validation') print(validation_data.iloc[:, :-2]) #os.mkdir('centralized_model') checkpoint = ModelCheckpoint(filepath='centralized_model/model_{epoch:04d}.h5', period = 1) history = model.fit(train_data.iloc[:, :-2], train_data.iloc[:, :-2], batch_size=1024, epochs=epochs, validation_data=(validation_data.iloc[:, :-2], validation_data.iloc[:, :-2]), callbacks=[checkpoint] ) np.save('history_epoch_{}_batchsize_1024_minmax.npy'.format(epochs), history.history) def threshold_calculation(Path): validation_data = pd.read_csv('../train_validation_test_minmax/validation_centralized.csv') validation_x = validation_data.iloc[:, :-2] model = keras.models.load_model(Path) X_predict = model.predict(validation_x) mse = np.mean(np.power(validation_x - X_predict, 2), axis=1) print('power of np') print(np.power(validation_x - X_predict, 2)) # calculate threshold tr = mse.mean() + mse.std() print('threshold = ' + str(tr)) def evaluate_model(virus, Path, threshold): model = keras.models.load_model(Path) #tr = 0.019348176634629 tr = threshold if not path.exists('logbook_centralized.csv'): with open('logbook_centralized.csv', 'w', newline='') as logbook: writer = csv.writer(logbook) writer.writerow(['Device Name', 'TN', 'FP', 'FN', 'TP', 'Accuracy', 'Precision', 'Recall']) logbook.close() if virus == 'BASHLITE': devices = ['Ecobee_Thermostat', 'Provision_PT_737E_Security_Camera', 'Philips_B120N10_Baby_Monitor', 'Provision_PT_838_Security_Camera', 'SimpleHome_XCS7_1002_WHT_Security_Camera', 'Danmini_Doorbell', 'SimpleHome_XCS7_1003_WHT_Security_Camera', 'Samsung_SNH_1011_N_Webcam', 'Ennio_Doorbell'] test_data = pd.read_csv('../train_validation_test_minmax/test_BASHLITE.csv') elif virus == 'mirai': devices = ['Ecobee_Thermostat', 'Provision_PT_737E_Security_Camera', 'Philips_B120N10_Baby_Monitor', 'Provision_PT_838_Security_Camera', 'SimpleHome_XCS7_1002_WHT_Security_Camera', 'Danmini_Doorbell', 'SimpleHome_XCS7_1003_WHT_Security_Camera'] test_data = pd.read_csv('../train_validation_test_minmax/test_mirai.csv') test_data = test_data.sample(frac = 1) test_result = pd.DataFrame() mse_store = pd.DataFrame() log = [] for device in devices: test_data_single_device = test_data[test_data['device'] == device] mse_store['label'] = test_data_single_device['label'] mse_store['device'] = test_data_single_device['device'] test_predict = model.predict(test_data_single_device.iloc[:, :-2]) mse_test = np.mean(np.power(test_data_single_device.iloc[:, :-2] - test_predict, 2), axis=1) mse_store['mse'] = mse_test predictions = (mse_test > tr).astype(int) print('predicion results: ') print(predictions) tn, fp, fn, tp = confusion_matrix(test_data_single_device['label'], predictions, labels=[0, 1]).ravel() accuracy = (tp + tn) / (tn + fp + fn + tp) precision = tp / (tp + fp) recall = tp / (tp + fn) temp = [device, tn, fp, fn, tp, accuracy, precision, recall,tr] test_result = pd.concat([test_result, mse_store]) mse_store= pd.DataFrame() log.append(temp) with open('logbook_centralized.csv', 'a', newline='') as logbook: writer = csv.writer(logbook) writer.writerow(['[' + str(datetime.now()) + ']' + 'testing result of ' + virus]) for i in range(len(log)): writer.writerow(log[i]) logbook.close() train_model(100)

[ "wangyingwwyy96@hotmail.com" ]

wangyingwwyy96@hotmail.com

bc6205660bf6d926fd613856f972bfe2f182e762

8dde10652d0f30f94f5991f2949511bd22085d7d

/social_media_project/groups/templates/groups/blog_project/blog/blogapp/models.py

7f6e8d0b6590753a83151cd754120b70b4003739

[]

no_license

Tambiebarango/social-media-clone

43346563bb420888c8f9b84939f6edeafdbed6b7

dafc07798fd1fd4da9918df57f5df93097675378

refs/heads/master

2020-05-18T10:17:03.203980

2019-05-01T00:40:04

184,349,163

0

null

UTF-8

Python

false

1,586

py

from django.db import models from django.contrib.auth.models import User from django.utils import timezone from django.core.urlresolvers import reverse # Create your models here. class UserProfileInfo(models.Model): user = models.OneToOneField(User) #to add more attributes to the user #additional attributes # portfolio_site = models.URLField(blank=True) # profile_pic = models.ImageField(upload_to='profile_pics', blank=True) def __str__(self): return self.user.username class Post(models.Model): author = models.ForeignKey('auth.User') title = models.CharField(max_length=200) text = models.TextField() create_date = models.DateTimeField(default=timezone.now) published_date = models.DateTimeField(blank=True, null=True) def publish(self): self.published_date = timezone.now() self.save() def approved_comments(self): return self.comments.filter(approved_comment=True) def get_absolute_url(self): return reverse("post_detail",kwargs={'pk':self.pk}) def __str__(self): return self.title class Comment(models.Model): post = models.ForeignKey(Post, related_name='comments') author = models.CharField(max_length=200) text = models.TextField() create_date = models.DateTimeField(default=timezone.now) approved_comment = models.BooleanField(default=False) def approve(self): self.approved_comment = True self.save() def get_absolute_url(self): return reverse('post_list') def __str__(self): return self.text

[ "theodorebarango@Theodores-MacBook-Pro.local" ]

theodorebarango@Theodores-MacBook-Pro.local

d88fce8f8224563faf71fb2b52c67a0816d81051

98f96f3efb2a585805756f27483d9e91a75eecf3

/GitHub_test_2.py

9697ecdbcd25d73e5bf07355117d5f737bada294

[]

no_license

Aiden-yang-qq/GitHub_test

795f042e295da532c6295f06ba44255aeb2a59be

d2cf3a6a900c033ff79e7ef2987f733355d6da46

refs/heads/master

2022-04-28T07:41:02.633326

2020-04-30T07:42:11

260,118,390

0

null

UTF-8

Python

false

134

py

# 试验使用Pycharm上传文件到GitHub def main(): print('github_2试验成功！') if __name__ == '__main__': main()

[ "jayskateboy@outlook.com" ]

jayskateboy@outlook.com

ab8c1ccb0b80f94e1bbe462ae249c17cde0ff235

ea6004b96cb045d0174e037bbf2be6261f26eff3

/qubit/io/celery/config.py

347d5e123d08e0cbb6104dc4abd008fccc74f9e6

[]

no_license

RyanKung/qubit

5dfd63eaf8874b00dfc00f004f2f54374b4f3622

e16efece0753b693868a17cccf0633844d5d1ee0

refs/heads/master

2020-12-24T06:39:03.559675

2017-04-19T09:56:53

73,465,795

1

0

null

UTF-8

Python

false

933

py

from qubit.config import MQ_BROKER, REDIS_BACKEND TIMEZONE = 'Europe/London' ENABLE_UTC = True BROKER_URL = MQ_BROKER CELERY_RESULT_BACKEND = REDIS_BACKEND CELERY_ACCEPT_CONTENT = ['application/json', 'application/x-python-serialize'] CELERY_TASK_RESULT_EXPIRES = 18000 # 5 hours. CELERY_ALWAYS_EAGER = False CELERY_DEFAULT_QUEUE = 'qubit.tasks.default' CELERY_DEFAULT_EXCHANGE = 'qubit.tasks.default' CELERY_DEFAULT_ROUTING_KEY = 'default' # These settings is used for fix `celeryev.xxx queue huge length` problem: # http://stackoverflow.com/questions/30227266/what-is-the-celeryev-queue-for # http://stackoverflow.com/questions/17778715/celeryev-queue-in-rabbitmq-becomes-very-large # DOC: # http://celery.readthedocs.io/en/latest/configuration.html#celery-event-queue-ttl CELERY_SEND_EVENTS = True CELERY_EVENT_QUEUE_TTL = 60 CELERY_EVENT_QUEUE_EXPIRES = 60 # Will delete all celeryev. queues without consumers after 1 minute.

[ "ryankung@ieee.org" ]

ryankung@ieee.org

5cc99ebec398364037bbd43f6cbea2dbcaec88f0

76795255ca4395c0868ad29443c1afe289061acb

/colonizer/wish/scripts/run_test.py

5b103ebe359d94d5af93c3b00b2e59bfa70e8608

[ "LicenseRef-scancode-warranty-disclaimer" ]

no_license

vmenajr/mongo

337f3c779f2e2469711b051c0063feca76b2500c

77cfdb1dfc658c592430d86b1359c6c45e031cf9

refs/heads/master

2021-04-03T10:04:54.571211

2021-03-24T15:15:00

125,252,199

7

null

2019-11-22T22:59:20

2018-03-14T17:50:53

JavaScript

UTF-8

Python

false

38,406

py

import json from bson.json_util import dumps import paramiko import argparse import yaml import pymongo import concurrent.futures import os import datetime from pymongo import MongoClient import time import subprocess import multiprocessing from datetime import timedelta os_user = 'colonizer' # for testing #os_user = 'ubuntu' home_dir = '/home/' + os_user + '/' ssh_dir = home_dir + '.ssh/' ycsb_dir = home_dir + 'ycsb-0.12.0/' #ycsb_dir = home_dir + 'YCSB-master/ycsb-mongodb/' test_result_dir = 'test_results/' dbpath = '/data' servers = {} servers_list = [] servers_file = 'cluster.json' test_file = 'hosts_sharded_cluster.json' workload_template = 'workload_template' hosts_per_shard = 3 device_shard = '/dev/nvme0n1' device_other = '/dev/xvdg' all_mongodb_roles = ['configs', 'shards', 'mongos', 'replica_set', 'standalone'] all_mongodb_roles_reverse = ['standalone', 'replica_set', 'mongos', 'shards', 'configs'] all_roles = all_mongodb_roles + ['clients'] logpath = '/data/logs/' other_client = 'false' num_of_clients = ["4", "8", "16", "32"] #num_of_clients = ["2", "4"] def get_hosts(): servers_list = [] mongos_list = [] with open(servers_file) as data_file: servers = json.load(data_file) with open(test_file) as tests: hosts = json.load(tests) if 'client' in servers['inventory']['value']: hosts['clients'] = [] for index, mv in enumerate(servers['inventory']['value']['client'][0]['private']): hosts['clients'].append({'hostname' : mv}) if 'configs' in servers['inventory']['value']: hosts['configs'] = [] for index, mv in enumerate(servers['inventory']['value']['configs'][0]['private']): if mv not in servers_list: servers_list.append(mv) config = { 'hostname' : mv, 'port': '27017', 'dbpath': '/data', 'logpath': '/data/mongo.log', 'role': 'config' } hosts['configs'].append(config) if 'mongos' in servers['inventory']['value']: hosts['mongos'] = [] for index, mv in enumerate(servers['inventory']['value']['mongos'][0]['private']): if mv not in servers_list: servers_list.append(mv) mongos = { 'hostname' : mv, 'port': '27017', 'dbpath': '/data', 'logpath': '/data/mongo.log', 'role': 'mongos' } hosts['mongos'].append(mongos) mongos_list.append(mv + ':' + '27017') #hosts['mongodbUrl' + str(index+1)] = 'mongodb://' + ','.join(mongos_list) + hosts['url_options']; # Adjust the test to run with 6 mongos in the connection string #if index == 5: # hosts['mongodbUrl' + str(index+1)] = 'mongodb://' + ','.join(mongos_list) + hosts['url_options']; conn_str = 'mongodb://' + ','.join(mongos_list) hosts['mongodbUrl'] = conn_str + hosts['url_options']; if 'shards' in servers['inventory']['value']: hosts['shards'] = [] shards = [] for index, mv in enumerate(servers['inventory']['value']['shards'][0]['private']): shard_number = index / hosts_per_shard i = index - shard_number * hosts_per_shard shard = { 'hostname' : mv, 'port': '27017', 'dbpath': '/data', 'logpath': '/data/mongo.log', 'role': 'secondary', 'priority': 1 } if (index % hosts_per_shard == 0): shard['priority'] = 5 shard['role'] = 'primary' hosts['shards'].append(shards) shards = [] hosts['shards'][shard_number].append(shard) if mv not in servers_list: servers_list.append(mv) hosts['servers_list'] = servers_list with open(args.test_file, 'w') as data_file: json.dump(hosts, data_file, indent=4, sort_keys=True) def setup_mongodb(hosts): config_list = [] shards = [] config_str = "" if 'configs' in hosts: repl_name = hosts['cluster_name'] + '_Cfg' for index, mv in enumerate(hosts['configs']): dbpath = hosts['dbpath'] + '/' +repl_name + '_' + str(index) + '/' mv['dbpath'] = dbpath if (hosts['config_server_type'] == 'CSRS'): update_mongod_config(mv, dbpath, repl_name, 'configsvr', 'wiredTiger') ssh_exe(mv['hostname'], 'sudo blockdev --setra 0 ' + device_other) else: update_mongod_config(mv, dbpath, '', 'configsvr', hosts['storage_engine']) if hosts['storage_engine'].lower() == 'wiredtiger': ssh_exe(mv['hostname'], 'sudo blockdev --setra 0 ' + device_other) else: ssh_exe(mv['hostname'], 'sudo blockdev --setra 32 ' + device_other) config_file_no_auth = dbpath + mv['hostname'] + '.' + mv['port'] + '.no_auth.mongod.conf' config_file_auth = dbpath + mv['hostname'] + '.' + mv['port'] + '.auth.mongod.conf' if 'user' in hosts: mv['config_file'] = config_file_auth else: mv['config_file'] = config_file_no_auth ssh_exe(mv['hostname'], 'mongod -f ' + config_file_no_auth) config_list.append(mv['hostname'] + ':' + mv['port']) if (hosts['config_server_type'] == 'CSRS'): print('Wait for 10 seconds before initialing CSRS') time.sleep(10) init_repl(repl_name, hosts['configs']) config_str = repl_name + '/' + ','.join(config_list) else: config_str = ','.join(config_list) if 'shards' in hosts: for num, mv in enumerate(hosts['shards']): repl_name = hosts['cluster_name'] + '_Shard_' + str(num) shard_list = [] for index, nv in enumerate(hosts['shards'][num]): dbpath = hosts['dbpath'] + '/' + repl_name + '_' + str(index) + '/' nv['dbpath'] = dbpath update_mongod_config(nv, dbpath, repl_name, 'shardsvr', hosts['storage_engine']) if hosts['storage_engine'].lower() == 'wiredtiger': ssh_exe(nv['hostname'], 'sudo blockdev --setra 0 ' + device_shard) else: ssh_exe(nv['hostname'], 'sudo blockdev --setra 32 ' + device_shard) config_file_no_auth = dbpath + nv['hostname'] + '.' + nv['port'] + '.no_auth.mongod.conf' config_file_auth = dbpath + nv['hostname'] + '.' + nv['port'] + '.auth.mongod.conf' if 'user' in hosts: nv['config_file'] = config_file_auth else: nv['config_file'] = config_file_no_auth ssh_exe(nv['hostname'], 'mongod -f ' + config_file_no_auth) shard_list.append(nv['hostname'] + ':' + nv['port']) print('Wait for 10 seconds before initialing shards') time.sleep(10) init_repl(repl_name, mv) shard = repl_name + '/' + ','.join(shard_list) shards.append(shard) if 'user' in hosts: conn_str = 'mongodb://' + ','.join(shard_list) + '/replicaSet=' + repl_name add_user_mongo(conn_str, hosts['user'], hosts['password']) if 'mongos' in hosts: mongos_list = [] for index, mv in enumerate(hosts['mongos']): dbpath = hosts['dbpath'] + '/' + hosts['cluster_name'] + '_' + str(index) + '/' mv['dbpath'] = dbpath update_mongos_config(mv, dbpath, config_str) config_file_no_auth = dbpath + mv['hostname'] + '.' + mv['port'] + '.no_auth.mongos.conf' config_file_auth = dbpath + mv['hostname'] + '.' + mv['port'] + '.auth.mongos.conf' if 'user' in hosts: mv['config_file'] = config_file_auth else: mv['config_file'] = config_file_no_auth ssh_exe(mv['hostname'], 'mongos -f ' + config_file_no_auth) if index == 0: print('Wait for 10 seconds before adding shards') time.sleep(10) init_cluster(mv['hostname'], mv['port'], shards) mongos_list.append(mv['hostname'] + ':' + mv['port']) #hosts['mongodbUrl' + str(index+1)] = 'mongodb://' + ','.join(mongos_list) + hosts['url_options']; #if 'user' in hosts: # hosts['mongodbUrl' + str(index+1)] = 'mongodb://' + hosts['user'] + ':' + hosts['password'] + '@' + ','.join(mongos_list) + hosts['url_options']; conn_str = 'mongodb://' + ','.join(mongos_list) + hosts['url_options']; if 'user' in hosts: add_user_mongo(conn_str, hosts['user'], hosts['password']) conn_str = 'mongodb://' + hosts['user'] + ':' + hosts['password'] + '@' + ','.join(mongos_list) + hosts['url_options']; hosts['mongodbUrl'] = conn_str if 'replica_set' in hosts: member_list = [] for index, mv in enumerate(hosts['replica_set']): dbpath = hosts['dbpath'] + '/' + hosts['replica_set_name'] + '_' + str(index) + '/' mv['dbpath'] = dbpath update_mongod_config(mv, dbpath, hosts['replica_set_name'], '', hosts['storage_engine']) config_file_no_auth = dbpath + mv['hostname'] + '.' + mv['port'] + '.no_auth.mongod.conf' config_file_auth = dbpath + mv['hostname'] + '.' + mv['port'] + '.auth.mongod.conf' if 'user' in hosts: mv['config_file'] = config_file_auth else: mv['config_file'] = config_file_no_auth ssh_exe(mv['hostname'], 'mongod -f ' + config_file_no_auth) member_list.append(mv['hostname'] + ':' + mv['port']) init_repl(hosts['replica_set_name'], hosts['replica_set']) conn_str = 'mongodb://' + ','.join(member_list) + '/replicaSet=' + hosts['replica_set_name'] if 'user' in hosts: add_user_mongo(conn_str, hosts['user'], hosts['password']) conn_str = 'mongodb://' + hosts['user'] + ':' + hosts['password'] + '@' + ','.join(member_list) + '/replicaSet=' + hosts['replica_set_name'] hosts['mongodbUrl'] = conn_str if 'standalone' in hosts: dbpath = hosts['dbpath'] + '/' hosts['standalone']['dbpath'] = dbpath update_mongod_config(hosts['standalone'], dbpath, '', '', hosts['storage_engine']) config_file_no_auth = dbpath + hosts['standalone']['hostname'] + '.' + hosts['standalone']['port'] + '.no_auth.mongod.conf' config_file_auth = dbpath + hosts['standalone']['hostname'] + '.' + hosts['standalone']['port'] + '.auth.mongod.conf' if 'user' in hosts: hosts['standalone']['config_file'] = config_file_auth else: hosts['standalone']['config_file'] = config_file_no_auth ssh_exe(hosts['standalone']['hostname'], 'mongod -f ' + config_file_no_auth) conn_str = 'mongodb://' + hosts['standalone']['hostname'] + ':' + hosts['standalone']['port'] if 'user' in hosts: add_user_mongo(conn_str, hosts['user'], hosts['password']) conn_str = 'mongodb://' + hosts['user'] + ':' + hosts['password'] + '@' + hosts['standalone']['hostname'] + ':' + hosts['standalone']['port'] hosts['mongodbUrl'] = conn_str with open(test_file, 'w') as data_file: json.dump(hosts, data_file, indent=4, sort_keys=True) if 'user' in hosts: populate_keyFile(hosts) shutdown_mongodb_all(hosts) start_mongodb_all(hosts) geneate_test_file(hosts, test_file) def geneate_test_file(hosts, test_file): cluster_name = hosts['cluster_name'] for index, mv in enumerate(hosts['clients']): hosts['mongodbUrl1'] = 'mongodb://' + hosts['mongos'][index]['hostname'] + ':' + hosts['mongos'][index]['port'] + hosts['url_options']; if 'user' in hosts: hosts['mongodbUrl1'] = 'mongodb://' + hosts['user'] + ':' + hosts['password'] + '@' + hosts['mongos'][index]['hostname'] + ':' + hosts['mongos'][index]['port'] + hosts['url_options']; with open('/tmp/'+ test_file, 'w') as data_file: json.dump(hosts, data_file, indent=4, sort_keys=True) scp_file(mv['hostname'], '/tmp/' + test_file, home_dir + test_file) for index2, nv in enumerate(num_of_clients): hosts['cluster_name'] = nv + 'clients_' + cluster_name filename = nv + 'clients_' + test_file with open('/tmp/'+ filename, 'w') as data_file: json.dump(hosts, data_file, indent=4, sort_keys=True) scp_file(mv['hostname'], '/tmp/' + filename, home_dir + filename) def populate_keyFile(hosts): os.system('openssl rand -base64 756 > ' + 'keyFile') os.system('chmod 400 ' + 'keyFile') for index, mv in enumerate(hosts['servers_list']): scp_file(mv, 'keyFile', home_dir + 'keyFile') run_cmd_all(hosts, 'chmod 400 ' + home_dir + 'keyFile', False) def clean_dbpath(host): ssh_exe(host['hostname'], 'rm -rf ' + host['dbpath']) def clean_dbpath_all(hosts): func_by_roles(hosts, all_mongodb_roles, clean_dbpath) def shutdown_mongodb(host, user, password): if user == "": cmd = 'mongo --port ' + host['port'] + ' admin --eval "db.shutdownServer({force: true});"' else: cmd = 'mongo --port ' + host['port'] + ' --username ' + user + ' --password ' + password + ' admin --eval "db.shutdownServer({force: true});"' ssh_exe(host['hostname'], cmd) def shutdown_mongodb_all(hosts): user = password = '' if 'user' in hosts: user = hosts['user'] password = hosts['password'] func_by_roles(hosts, all_mongodb_roles_reverse, shutdown_mongodb, user, password) def start_mongodb(host, options): if host['role'] == 'mongos': ssh_exe(host['hostname'], 'mongos -f ' + host['config_file'] + ' ' + options) else: ssh_exe(host['hostname'], 'mongod -f ' + host['config_file'] + ' ' + options) def start_mongodb_all(hosts): func_by_roles(hosts, all_mongodb_roles, start_mongodb, '') def scp_file(hostname, source, target): ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname, username=os_user) sftp = ssh.open_sftp() try: sftp.put(source, target, callback=None) except IOError: pass ssh.close() def ssh_exe(hostname, command): ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) print('host: ' + hostname) print('command: ' + command) ssh.connect(hostname, username=os_user) stdin, stdout, stderr = ssh.exec_command(command) print stdout.readlines() ssh.close() def update_mongod_config(host, dbpath, repl_name, role, engine): with open("mongod.conf", 'r') as conf_file: data = yaml.load(conf_file) try: data['net']['port'] = host['port'] if (repl_name != ''): data['replication'] = {} data['replication']['replSetName'] = repl_name if (role != ''): data['sharding'] = {} data['sharding']['clusterRole'] = role data['storage']['dbPath'] = dbpath if (engine == "mmapv1"): data['storage']['engine'] = "mmapv1" else: data['storage']['engine'] = "wiredTiger" # set the cache size for testing #data['storage']['wiredTiger'] = { 'engineConfig' : { 'cacheSizeGB' : 1 } } cmd = 'mkdir -p ' + dbpath ssh_exe(host['hostname'], cmd) cmd = 'mkdir -p ' + logpath ssh_exe(host['hostname'], cmd) data['systemLog']['path'] = logpath + 'mongodb.log' except yaml.YAMLError as exc: print(exc) mongod_conf_file_no_auth = host['hostname'] + '.' + host['port'] + '.no_auth.mongod.conf' with open('/tmp/' + mongod_conf_file_no_auth, 'w') as yaml_file: yaml_file.write( yaml.safe_dump(data, default_flow_style=False)) target = dbpath + mongod_conf_file_no_auth scp_file(host['hostname'], '/tmp/' + mongod_conf_file_no_auth, target) data['security'] = {'authorization': 'enabled', 'keyFile': home_dir + 'keyFile' } mongod_conf_file_auth = host['hostname'] + '.' + host['port'] + '.auth.mongod.conf' with open('/tmp/' + mongod_conf_file_auth, 'w') as yaml_file: yaml_file.write( yaml.safe_dump(data, default_flow_style=False)) target = dbpath + mongod_conf_file_auth scp_file(host['hostname'], '/tmp/' + mongod_conf_file_auth, target) def init_repl(repl_name, repl_hosts): print ('initialize replica set') client = MongoClient(repl_hosts[0]['hostname'], int(repl_hosts[0]['port'])) config = {'_id': repl_name, 'members': [] } for index, mv in enumerate(repl_hosts): member = {'_id': index, 'host': mv['hostname'] + ':' + mv['port']} if 'priority' in mv: member['priority'] = mv['priority'] config['members'].append(member) try: client.admin.command("replSetInitiate", config) except Exception, e: print(e) client.close() def update_mongos_config(host, dbpath, config_str): with open("mongos.conf", 'r') as conf_file: data = yaml.load(conf_file) try: cmd = 'mkdir -p ' + dbpath ssh_exe(host['hostname'], cmd) cmd = 'mkdir -p ' + logpath ssh_exe(host['hostname'], cmd) data['net']['port'] = host['port'] data['systemLog']['path'] = logpath + 'mongodb.log' data['sharding']['configDB'] = config_str except yaml.YAMLError as exc: print(exc) mongos_conf_file_no_auth = host['hostname'] + '.' + host['port'] + '.no_auth.mongos.conf' with open('/tmp/' + mongos_conf_file_no_auth, 'w') as yaml_file: yaml_file.write( yaml.safe_dump(data, default_flow_style=False)) target = dbpath + mongos_conf_file_no_auth scp_file(host['hostname'], '/tmp/' + mongos_conf_file_no_auth, target) data['security'] = {'keyFile': home_dir + 'keyFile' } mongos_conf_file_auth = host['hostname'] + '.' + host['port'] + '.auth.mongos.conf' with open('/tmp/' + mongos_conf_file_auth, 'w') as yaml_file: yaml_file.write( yaml.safe_dump(data, default_flow_style=False)) target = dbpath + mongos_conf_file_auth scp_file(host['hostname'], '/tmp/' + mongos_conf_file_auth, target) def init_cluster(hostname, port, shards): client = MongoClient(hostname, int(port)) for index, mv in enumerate(shards): client.admin.command("addShard", mv) print ('adding shard: ' + mv) client.close() def add_user_mongo(conn_str, user, password): client = MongoClient(conn_str) client.admin.add_user(user, password, roles=['root']) client.close() def parse_workload_file(workload_file): workloads = {} with open(workload_file) as data_file: for line in data_file: key, value = line.partition("=")[::2] if key.strip() != '': workloads[key.strip()] = value.strip() return workloads def write_workload_file(file_name, workloads): with open(file_name, 'w') as workload_file: for key, value in sorted(workloads.iteritems()): if key != '': workload_file.write(key + '=' + str(value) + '\n') def load_data(hosts): workloads = parse_workload_file(workload_template) del workloads['maxexecutiontime'] # for testing #workloads['recordcount'] = '10000' now = datetime.datetime.utcnow().isoformat() test_run_dir = test_result_dir + hosts['cluster_name'] + '_' + now + '/' print(test_run_dir) os.system('mkdir -p ' + test_run_dir + '/workloads') write_workload_file(test_run_dir + '/workloads/workload_load', workloads) client = MongoClient(hosts['mongodbUrl']) try: client.admin.command({ 'enableSharding' : 'ycsb' }) except Exception, e: print(e) try: client.admin.command({ 'shardCollection' : 'ycsb.usertable', 'key': {'_id':'hashed'}}) except Exception, e: print(e) client.config.settings.update( { '_id': 'balancer' }, { '$set' : { 'stopped': 'true' } }, upsert=True ) client.close() cmd = ycsb_dir + '/bin/ycsb load mongodb -P ' + test_run_dir + 'workloads/workload_load -p mongodb.url=' + hosts['mongodbUrl1'] process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) out, err = process. communicate() with open (test_run_dir + '/load.ycsb.stdout', 'w') as stdout: stdout.write(out) with open (test_run_dir + '/load.ycsb.stderr', 'w') as stderr: stderr.write(err) print("data load completed") def run_cmd_all(hosts, cmd, client): if 'servers_list' not in hosts: servers_list = {} if 'mongos' in hosts: for index, mv in enumerate(hosts['mongos']): if mv['hostname'] not in servers_list: servers_list.append(mv['hostname']) if 'configs' in hosts: for index, mv in enumerate(hosts['configs']): if mv['hostname'] not in servers_list: servers_list.append(mv['hostname']) if 'shards' in hosts: for num, mv in enumerate(hosts['shards']): for index, nv in enumerate(hosts['shards'][num]): if nv['hostname'] not in servers_list: servers_list.append(nv['hostname']) if 'replica_set' in hosts: for index, mv in enumerate(hosts['replica_set']): if mv['hostname'] not in servers_list: servers_list.append(mv['hostname']) if 'standalone' in hosts: if hosts['standalone']['hostname'] not in servers_list: servers_list.append(hosts['standalone']['hostname']) for index, mv in enumerate(hosts['servers_list']): ssh_cmd = 'ssh -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -f ' + mv + ' ' + cmd print(ssh_cmd) process = subprocess.Popen(ssh_cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) if (client == True): for index, mv in enumerate(hosts['clients']): ssh_cmd = 'ssh -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -f ' + mv['hostname'] + ' ' + cmd print(ssh_cmd) process = subprocess.Popen(ssh_cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) def rotate_mongodb_logs(host, user, password): host_port = host['hostname'] + ':' + host['port'] conn_str = 'mongodb://' + host_port if 'user' != '': conn_str = 'mongodb://' + hosts['user'] + ':' + hosts['password'] + '@' + host_port client = MongoClient(conn_str) client.admin.command("logRotate") client.close() def rotate_mongodb_logs_all(hosts): user = password = '' if 'user' in hosts: user = hosts['user'] password = hosts['password'] func_by_roles(hosts, all_mongodb_roles, rotate_mongodb_logs, user, password) def clean_mongodb_logs(host): ssh_exe(host['hostname'], 'rm -rf ' + logpath + '/mongodb.log.*') def clean_mongodb_logs_all(hosts): func_by_roles(hosts, all_mongodb_roles, clean_mongodb_logs) def set_slowms(host, user, password): host_port = host['hostname'] + ':' + host['port'] conn_str = 'mongodb://' + host_port if 'user' != '': conn_str = 'mongodb://' + hosts['user'] + ':' + hosts['password'] + '@' + host_port client = MongoClient(conn_str) client.admin.command('profile', 0, slowms=-1) client.close() def launchRemoteSadc(hosts, maxSeconds): run_cmd_all(hosts, '/usr/bin/pkill -u ' + os_user + ' sadc', True) run_cmd_all(hosts, '/bin/rm -f /tmp/sadc.out', True) run_cmd_all(hosts, '/usr/lib/sysstat/sadc -S XDISK 1 ' + str(maxSeconds) + ' /tmp/sadc.out', True) def killCaptureRemoteSadc(hosts, test_run_dir): run_cmd_all(hosts, '/usr/bin/pkill -u ' + os_user + ' sadc', True) for index, mv in enumerate(hosts['servers_list']): os.system('mkdir -p ' + test_run_dir + '/' + mv) scp_get_file(mv, '/tmp/sadc.out', test_run_dir + '/' + mv + '/sadc.out') for index, mv in enumerate(hosts['clients']): os.system('mkdir -p ' + test_run_dir + '/' + mv['hostname']) scp_get_file(mv['hostname'], '/tmp/sadc.out', test_run_dir + '/' + mv['hostname'] + '/sadc.out') #run_cmd_all(hosts, '/bin/rm -f /tmp/sadc.out', True) def scp_get_file(hostname, remotepath, localpath): ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname, username=os_user) sftp = ssh.open_sftp() try: sftp.get(remotepath, localpath, callback=None) except IOError: pass ssh.close() def scp_mongodb_logs(host, test_run_dir): local_log_dir = test_run_dir + '/' + host['role'] + '_' + host['hostname'] + '_' + host['port'] os.system('mkdir -p ' + local_log_dir) ssh_exe(host['hostname'], 'tar -cvzf ' + '/tmp/mongodblogs.tar.gz ' + logpath) os.system('scp -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -q ' + host['hostname'] + ':/tmp/mongodblogs.tar.gz ' + local_log_dir) #os.system('scp -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -q ' + host['hostname'] + ':' + logpath + '/mongodb.log* ' + local_log_dir) if host['role'] != 'mongos': os.system('mkdir -p ' + local_log_dir + '/diagnostic.data') os.system('scp -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -q ' + host['hostname'] + ':' + host['dbpath'] + '/diagnostic.data/* ' + local_log_dir + '/diagnostic.data/') def scp_mongodb_logs_all(hosts, test_run_dir): func_by_roles(hosts, all_mongodb_roles, scp_mongodb_logs, test_run_dir) def check_replication_lags(hosts): if 'shards' in hosts: while True: max_lag = 0 max_lag_host = '' for num, mv in enumerate(hosts['shards']): hosts_ports = mv[0]['hostname'] + ':' + mv[0]['port'] + ',' + mv[1]['hostname'] + ':' + mv[1]['port'] conn_str = 'mongodb://' + hosts_ports if 'user' in hosts: conn_str = 'mongodb://' + hosts['user'] + ':' + hosts['password'] + '@' + hosts_ports client = MongoClient(conn_str) rsStatus = client.admin.command("replSetGetStatus") client.close() secondary_optimes = []; primary_optime = 0; for index, nv in enumerate(rsStatus['members']): if (nv['stateStr'] == "PRIMARY"): primary_optime = nv['optimeDate'] elif ( nv['stateStr'] == "SECONDARY" ): secondaryStat = {} secondaryStat['name'] = nv['name'] secondaryStat['optime'] = nv['optimeDate'] secondary_optimes.append(secondaryStat) for index, nv in enumerate(secondary_optimes): lag = timedelta.total_seconds(primary_optime - nv['optime']) if (lag > max_lag): max_lag = lag max_lag_host = nv['name'] if (max_lag > 1): print( max_lag_host + " is lagging " + str(max_lag) + " seconds, waiting for 5 seconds") time.sleep(5) else: break def collect_conn_pool_stats(host, test_run_dir, testx, user, password): local_log_dir = test_run_dir + '/' + host['role'] + '_' + host['hostname'] + '_' + host['port'] host_port = host['hostname'] + ':' + host['port'] conn_str = 'mongodb://' + host_port if 'user' != '': conn_str = 'mongodb://' + user + ':' + password + '@' + host_port client = MongoClient(conn_str) conn_pool_stats = client.admin.command('connPoolStats') with open (local_log_dir + '/' + testx + '_conn_pool_stats.json', 'a') as stats: stats.write('\n=== ' + datetime.datetime.utcnow().isoformat() + '\n') stats.write(dumps(conn_pool_stats, indent=4)) shard_conn_pool_stats = client.admin.command('shardConnPoolStats') with open (local_log_dir + '/' + testx + '_shard_conn_pool_stats.json', 'a') as shard_stats: shard_stats.write('\n=== ' + datetime.datetime.utcnow().isoformat() + '\n') shard_stats.write(dumps(shard_conn_pool_stats, indent=4)) client.close() def collect_conn_pool_stats_all(hosts, test_run_dir, testx): user = password = '' if 'user' in hosts: user = hosts['user'] password = hosts['password'] while True: func_by_roles(hosts, ['mongos', 'shards'], collect_conn_pool_stats, test_run_dir, testx, user, password) time.sleep(30) def func_by_roles(hosts, roles, func, *args): for role in roles: if role in hosts: if role == 'shards': for num, mv in enumerate(hosts[role]): for index, nv in enumerate(hosts[role][num]): func(nv, *args) else: for index, mv in enumerate(hosts[role]): func(mv, *args) def create_log_dir(host, test_run_dir): print(host) local_log_dir = test_run_dir + '/' + host['role'] + '_' + host['hostname'] + '_' + host['port'] os.system('mkdir -p ' + local_log_dir) def create_log_dir_all(hosts, test_run_dir): func_by_roles(hosts, all_mongodb_roles, create_log_dir, test_run_dir) def run_workloads(hosts, test_run_dir): num_shard = 1 workload_dir = test_run_dir + 'workloads/' os.system('mkdir -p ' + workload_dir) stats_dir = test_run_dir + 'stats/' os.system('mkdir -p ' + stats_dir) if 'shards' in hosts: num_shard = len(hosts['shards']) i = 1 # Adjust this number to run the tests with 6 mongos in the connection string #i = 6 while True: if 'mongodbUrl' + str(i) in hosts: if i != 1: # Adjust this number to run the tests with 6 mongos in the connection string #if i != 6: time.sleep(120) print('mongodbUrl: ' + hosts['mongodbUrl' + str(i)]) for index1, mv in enumerate(hosts['workloads']): workloads = parse_workload_file(workload_template) for key, value in mv.iteritems(): workloads[key] = value for index2, nv in enumerate(hosts['threads']): check_replication_lags(hosts) time.sleep(30) if other_client != "true": rotate_mongodb_logs_all(hosts) workloads['threadcount'] = nv * num_shard workload_file = 'workload_' + str(index1) + '_' + str(index2) + '_' + str(nv) write_workload_file(workload_dir + workload_file, workloads) with open (stats_dir + '/' + str(i) + '_mongos_' + workload_file + '.ycsb.stats', 'a') as stats: stats.write('Test started at: ' + datetime.datetime.utcnow().isoformat() + '\n') print('Running workload:' + str(index1) + ' threads: ' + str(nv)) if other_client != "true": p = multiprocessing.Process(target=collect_conn_pool_stats_all, args=(hosts, test_run_dir, str(i) + '_mongos_' + workload_file)) p.start() cmd = ycsb_dir + '/bin/ycsb run mongodb -P ' + workload_dir + workload_file + ' -p mongodb.url="' + hosts['mongodbUrl' + str(i)] + '"' process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) out, err = process. communicate() with open (stats_dir + '/' + str(i) + '_mongos_' + workload_file + '.ycsb.stdout', 'w') as stdout: stdout.write(out) with open (stats_dir + '/' + str(i) + '_mongos_' + workload_file + '.ycsb.stderr', 'w') as stderr: stderr.write(err) with open (stats_dir + '/' + str(i) + '_mongos_' + workload_file + '.ycsb.stats', 'a') as stats: stats.write('Test completed at: ' + datetime.datetime.utcnow().isoformat() + '\n') if other_client != "true": p.terminate() time.sleep(30) i += 1 else: break def scp_ycsb_stats(hosts, test_run_dir): all_ycsb_stats_dir = test_run_dir + '/all_ycsb_stats/' os.system('mkdir -p ' + all_ycsb_stats_dir) for index, mv in enumerate(hosts['clients']): stats_dir = all_ycsb_stats_dir + mv['hostname'] os.system('mkdir -p ' + stats_dir) os.system('scp -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -q ' + mv['hostname'] + ':' + test_run_dir + '/stats/* ' + stats_dir) def run_tests(hosts): now = datetime.datetime.utcnow().strftime("%Y-%m-%dT%H-%M-%S-%f") test_run_dir = test_result_dir + hosts['cluster_name'] + '/' os.system('mkdir -p ' + test_run_dir) if other_client != "true": rotate_mongodb_logs_all(hosts) clean_mongodb_logs_all(hosts) launchRemoteSadc(hosts, 600000) create_log_dir_all(hosts, test_run_dir) try: check = raw_input('Press Enter to start the tests') except EOFError: print ("Error: EOF or empty input!") check = "" print check run_workloads(hosts, test_run_dir) if other_client != "true": killCaptureRemoteSadc(hosts, test_run_dir); scp_mongodb_logs_all(hosts, test_run_dir) if (len(hosts['clients']) > 1): scp_ycsb_stats(hosts, test_run_dir) print('!!!!!!!!!!!!!!!!!!!!!') print('Test results are in ' + hosts['clients'][0]['hostname'] + ':' + home_dir + test_run_dir + ', please copy them to a safe place otherwise they will be lost when the client machine is destroy.') print('!!!!!!!!!!!!!!!!!!!!!') def get_logs(hosts, test_run_dir): os.system('mkdir -p ' + test_run_dir) killCaptureRemoteSadc(hosts, test_run_dir); scp_mongodb_logs_all(hosts, test_run_dir) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('-s', '--servers_file', help='servers json file, generated by "terraform output -json"') parser.add_argument('-t', '--test_file', help='test json file. It includes the information for the MongoDB deployment, like storage engine, authentication, config server type, and the information related to YCSB testing, like workloads, threads') parser.add_argument('-a', '--actions', help='the actions: it can be get_hosts, clean, start, stop, setup_mongodb, load, run') parser.add_argument('-e', '--storage_engine', help='storage engine. It can be mmapv1 or wiredTiger') parser.add_argument('-u', '--user', help='user name for the MongoDB deployment. If specified, it will create the deployment with authentication enabled') parser.add_argument('-p', '--password', help='password for the MongoDB deployment. If user name is specified, but password is not specified, it will use the user name as the password') parser.add_argument('-c', '--config_server_type', help='the type of the config server. It can be SCCC or CSRS') parser.add_argument('-n', '--cluster_name', help='name for the cluster. It will be used as part of the dbpath, test result path') parser.add_argument('-w', '--workload_template', help='workload file') parser.add_argument('-o', '--other_client', help='the flag to set whether this is not the main client. If so, we will not collect stats from mongod') args = parser.parse_args() if args.servers_file: servers_file = args.servers_file if args.test_file: test_file = args.test_file with open(test_file) as tests: hosts = json.load(tests) if args.storage_engine: if args.storage_engine.lower() == "mmap" or args.storage_engine.lower() == "mmapv1": hosts['storage_engine'] = 'mmapv1' if args.storage_engine.lower() == "wt" or args.storage_engine.lower() == "wiredtiger": hosts['storage_engine'] = 'wiredTiger' if args.user: hosts['user'] = args.user if args.password: hosts['password'] = args.password else: hosts['password'] = args.user if args.cluster_name: hosts['cluster_name'] = args.cluster_name if args.config_server_type: if args.config_server_type.lower() == 'sccc': hosts['config_server_type'] = 'SCCC' if args.config_server_type.lower() == 'csrs': hosts['config_server_type'] = 'CSRS' if args.workload_template: workload_template = args.workload_template if args.other_client: other_client = args.other_client if args.actions: actions = args.actions.split(',') for index, mv in enumerate(actions): if mv == "all": get_hosts(hosts) setup_mongodb(hosts) load_data(hosts) run_tests(hosts) if mv == "get_hosts": get_hosts() if mv == "setup_mongodb": setup_mongodb(hosts) if mv == "start": start_mongodb_all(hosts) if mv == "shutdown": shutdown_mongodb_all(hosts) if mv == "clean": shutdown_mongodb_all(hosts) clean_dbpath_all(hosts) if mv == "load": load_data(hosts) if mv == "run": run_tests(hosts) if mv == "restart_mongos_no_auto_split": user = password = '' if 'user' in hosts: user = hosts['user'] password = hosts['password'] func_by_roles(hosts, ['mongos'], shutdown_mongodb, user, password) func_by_roles(hosts, ['mongos'], start_mongodb, '--noAutoSplit') if mv == "get_logs": get_logs(hosts) if mv == "set_slowms": user = password = '' if 'user' in hosts: user = hosts['user'] password = hosts['password'] func_by_roles(hosts, ['shards'], set_slowms, user, password)

[ "vickmena@gmail.com" ]

vickmena@gmail.com

509df8769c60d81ad8721b75fff1f40f28ba7b29

c78614f196777624efb0663342ec1de7ebd44655

/grundlaggande_programvareutveckling/Week1Exercises/Week1Exercises/week1/src/samples/ClassObjects.py

066722a1d04109070750f8e44a36684e6b7105f0

[]

no_license

Dunkaburk/gruprog_1

4cb99b07bd2ba4b96d5f819f02906a9f9982dd8b

088e918843c0c3e14690169eb09034a2f3d818c6

refs/heads/main

2023-08-31T20:50:01.540508

2021-10-13T13:35:55

407,120,189

0

null

UTF-8

Python

false

2,060

py

# package samples # To package data of different types we use class objects (remember: arrays may only # use same type of data). The data should in some sense "belong together". # I.e. an objects is a package of variables of possibly different types # describing some concept (a car, a dog, a hero, ... any noun ...) # # To create class objects we first must declare a class describing the variables packaged (the # instance variables). I.e. a class is a blue print of the objects to be created. # # When the class is declared we may create objects, using the new-operator. # # When declaring a class we also automatically define a new type (so we can declare a variable # for a class object, remember, must specify type at variable declaration). # # def class_objects_program(): # A class also introduces a new typ (Dog). Use type to declare variable d1: Dog = Dog() # Must instantiate, i.e. create a dog object named d1 (using class initializer/constructor) print(d1.age) # Get value of contained variable using '.' "dot"-notation and variable name. print(f"{d1.name} is {d1.age} years old") # prints default values d1.name = "Fido" # Assign values to variables in dog object, use "dot"-notation d1.age = 3 d1.age += 1 # Getting older ... print(f"{d1.name} is {d1.age} years old") d2: Dog = Dog() # Create another dog. Same class used (class is a blue print)! d2.name = "Lassie" d2.age = 14 if d1.age > d2.age: print(f"{d1.name} is older") else: print(f"{d2.name} is older") # // --- A class ----- # // Class declaration specifies a name and instance variables. # // This class captures the concept of a dog class Dog: # Two instance variables, with default values # NOTE: This is not how you normally do it - instead you # use class initializers / constructors. More on this later. name = "Sprocket" # A Dog has a name and... (default value null) age = 0 # ... and age (default value 0) if __name__ == "__main__": class_objects_program()

[ "jonte8000@hotmail.com" ]

jonte8000@hotmail.com

8cc063e3aace2a9b498abba1696ccf45d3457f7e

d01b06289196407adb2eebd37310b3e307965e77

/tworaymodel.py

d8bba479234fdf8bb696b227b9b200be5b778d67

[ "MIT" ]

permissive

Dhanesh-raj/Two-ray-ground-reflection-model

fceb2a9d042df9ebb84e34acee827f8ed13efef2

7465a100822950d4fdd62fdcf2f50e2b6a1f60b0

refs/heads/master

2023-03-17T11:12:36.811484

2020-03-08T08:00:16

null

0

null

UTF-8

Python

false

3,007

py

import numpy as np import matplotlib.pyplot as plt import os # 4 set of bands to simulate (4 subplots) b1 = ['900'] b2 = ['800', '900', '2100'] b3 = ['800', '900', '1800', '2100'] b4 = ['800', '900', '1800', '2100', '2600'] # u value used to simplified two-ray model, assuming that two rays are always combined coherently, with a reflection # factor |Γ|, so the sum is multiplied by u=1+Γ. (FSPL is when u=1 (only 1 ray)). u = 1.6 R = -0.9 # R (or Γ) reflection factor used in two-ray ground-reflection model (in general is # dependent on the angle of incidence) ht = 6 # transmitter height hr = 4 # receiver height maxd = 25 # Maximum distance from transmitter (m) d = np.linspace(1, maxd, 2000) d_ref = np.sqrt((ht + hr) ** 2 + d ** 2) d_los = np.sqrt((ht - hr) ** 2 + d ** 2) G_los = 1 G_gr = 1 bandslist = [b1, b2, b3, b4] fig, ax = plt.subplots(2, 2, figsize=(20,15)) fig.suptitle(f'Models comparison for: ht={ht}m, hr={hr}m, Γ={R} and u={u} simplified model') ax = ax.ravel() for i, bands in enumerate(bandslist): tworayloss = 0 freespaceloss = 0 freq = np.asarray(bands).astype(int) lam = 3 * 10 ** 2 / freq for lam in lam: phi = 2 * np.pi * (d_ref - d_los) / lam loscoef = np.sqrt(G_los) / d_los reflcoef = R * np.sqrt(G_gr) * np.exp(-1j * phi) / d_ref rs = lam * (loscoef + reflcoef) / (4 * np.pi) tworayloss += 10*np.log10((abs(rs))**2) freespaceloss += 20*np.log10(lam / (4 * np.pi * d_los)) freespace_u = 10*len(freq)*np.log10(u**2) + freespaceloss norm = max(tworayloss[0], freespace_u[0]) tworayloss = tworayloss - norm freespaceloss = freespaceloss - norm freespace_u = freespace_u-norm ax[i].semilogx(d, tworayloss, d, freespace_u, d, freespaceloss) p = (1 - np.sum(tworayloss>freespace_u)/len(d))*100 ax[i].text(1, 0.90*min(tworayloss), f'{p:0.2f}% of values (u={u} model)\ngreater than analytical model') ax[i].text(1, min(tworayloss), f'Mean diff. [(u={u}), analytical two-ray]:=' f'{np.mean(freespace_u-tworayloss):+.1f}dB\n' f'Mean diff. [FSPL, analytical two-ray]:=' f'{np.mean(freespaceloss-tworayloss):+.1f}dB)') ax[i].legend((f'Two-Ray ground-reflection\n analytical model (Γ={R})', f'u={u}', 'Free Space (FSPL)'), loc=6) bandsstring = ', '.join(freq.astype(str)) bandsstring = '(' + bandsstring + ')' fname = f'ht = {ht}m, hr={hr}m, Γ={R}, u={u}' title = f'Bands={bandsstring}MHz' ax[i].set_title(title) ax[i].set_xlabel('Distance (m)') ax[i].set_ylabel('Normalized Path Loss (dB)') xticks = np.append(1, np.linspace(5, maxd, int(maxd/5)).astype(int)) ax[i].set_xticks(xticks) ax[i].set_xticklabels(xticks.astype(str)) plt.savefig(os.getcwd()+'\\Figures\\'+fname+'.png') # plt.show()

[ "noreply@github.com" ]

Dhanesh-raj.noreply@github.com

e283276355eca71bd1e71714aca213139b8934d2

7b11794013b6c186dad756f5682d038e4eb527d4

/fuber/models/taxi.py

e234ef47bdbd170d6a9e90b6bda04ef5ebe90fab

[]

no_license

himani93/Fuber-Taxi

6e9af17d2ecb3877307504fad187d530ba9b8ac8

ba3a0e80e17f830a83ae1df51c483250788d471a

refs/heads/master

2020-03-09T21:59:34.509058

2018-04-09T06:42:51

129,024,128

0

null

UTF-8

Python

false

1,942

py

import helper from exceptions import ( InvalidTaxiLicenseNumberException, InvalidTaxiColorException, InvalidLocationException, ) from location import Location class Taxi(object): def __init__(self, license_no, color="yellow", location=None): if not license_no: raise InvalidTaxiLicenseNumberException("{} is not valid".format(license_no)) self._license_no = license_no if not color: raise InvalidTaxiColorException("{} is not valid".format(color)) self._color = color if color == "pink": self._category = "pink" else: self._category = "default" self.available = True self.location = location self._id = helper.get_id() def __repr__(self): return "Taxi({} - {} - {})".format(self.license_no, self.color, self.available) def __str__(self): return "Taxi({} - {} - {})".format(self.license_no, self.color, self.available) def to_dict(self): return { "id": self.id, "license_no": self.license_no, "color": self.color, "available": self.available, "category": self.category, "location": self.location.to_dict() if self.location else self.location, } @property def license_no(self): return self._license_no @property def color(self): return self._color @property def category(self): return self._category @property def id(self): return self._id @property def location(self): return self._location @location.setter def location(self, loc): if loc is not None and type(loc) is not Location: raise InvalidLocationException("{} is not of Location type".format(loc)) self._location = loc def is_pink(self): return True if self.category == "pink" else False

[ "himani93@gmail.com" ]

himani93@gmail.com

965ff358445f18342fd71501800fa948bcb92a9c

f7f0df40f586014cc17961cb3f12cdfa8f87df56

/src/Test1/test6.py

e723e5e445c659e7cf90e6dc3f64cffbf1570fa9

[]

no_license

muxuehen/pythonStuty

5274a1a8c97bf67de19f07e07357d9710dc4967b

c99f8722218c4a08aefdcbe1987fa567e07cf10c

refs/heads/master

2020-03-29T17:17:42.790847

2014-12-09T09:09:57

null

0

null

UTF-8

Python

false

74

py

#coding=utf-8 ''' Created on 2014年12月4日 @author: ''' i = 9 print i

[ "zhangxuli@boco.com" ]

zhangxuli@boco.com

93e15d15e8a81c03ff3105f917050a361ae6a3d9

1bd53b731c7b2fce066204ab6e545020c6213468

/code/neural_network.py

9a4390e19fe96e6f4b9d8f6b7abbd250c4ae0cfa

[]

no_license

dougbrion/machine_learning_cw

2624fd794a415323e4d9391653738e2230f83245

d1e24df477c66c1b78416bf96c17d77e873abdee

refs/heads/master

2020-04-19T14:03:22.503598

2019-01-29T22:00:55

168,232,155

0

null

UTF-8

Python

false

4,186

py

import tensorflow as tf import helpers as hp import numpy as np def softmax_fn(_X, _inputs, _units): W = tf.Variable(tf.random_normal([_inputs, _units]), name='weight') b = tf.Variable(tf.random_normal([_units]), name='bias') y = tf.nn.softmax(tf.matmul(_X, W) + b) return y, W, b def selu_fn(_X, _inputs, _units): W = tf.Variable(tf.random_normal([_inputs, _units]), name='weight') b = tf.Variable(tf.random_normal([_units]), name='bias') y = tf.nn.selu(tf.add(tf.matmul(_X, W) , b)) return y, W, b def relu_fn(_X, _inputs, _units): W = tf.Variable(tf.random_normal([_inputs, _units]), name='weight') b = tf.Variable(tf.random_normal([_units]), name='bias') y = tf.nn.relu(tf.add(tf.matmul(_X, W) , b)) return y, W, b def sigmoid_fn(_X, _inputs, _units): W = tf.Variable(tf.random_normal([_inputs, _units]), name='weight') b = tf.Variable(tf.random_normal([_units]), name='bias') y = tf.nn.sigmoid(tf.add(tf.matmul(_X, W) , b)) return y, W, b def tanh_fn(_X, _inputs, _units): W = tf.Variable(tf.random_normal([_inputs, _units]), name='weight') b = tf.Variable(tf.random_normal([_units]), name='bias') y = tf.nn.tanh(tf.add(tf.matmul(_X, W) , b)) return y, W, b def calc_error_L1(_y, _pred): print("Loss Function L1") cost = tf.reduce_mean(tf.abs(_y - _pred)) return cost def huber_error(_y, _pred, _delta=1.0): residual = tf.abs(_y - _pred) cond = tf.less(residual, _delta) small_res = 0.5 * tf.square(residual) large_res = _delta * residual - 0.5 * tf.square(_delta) cost = tf.reduce_mean(tf.where(cond, small_res, large_res)) return cost def cost_function(_y, _pred): cost = tf.reduce_mean(tf.square(_y - _pred)) return cost def layers(_X, _y, _output_layer=0): inputs = int(hp.num_features(_X)) hidden_layer_nodes = int((inputs + 1) / 2) hidden_layer, hidden_weight, hidden_bias = relu_fn(_X, inputs, hidden_layer_nodes) if _output_layer == 0: print("Ouput Layer is ReLU") pred, weight, bias = relu_fn(hidden_layer, hidden_layer_nodes, 1) elif _output_layer == 1: print("Ouput Layer is SeLU") pred, weight, bias = selu_fn(hidden_layer, hidden_layer_nodes, 1) elif _output_layer == 2: print("Ouput Layer is Softmax") pred, weight, bias = softmax_fn(hidden_layer, hidden_layer_nodes, 1) elif _output_layer == 3: print("Ouput Layer is TanH") pred, weight, bias = tanh_fn(hidden_layer, hidden_layer_nodes, 1) elif _output_layer == 4: print("Ouput Layer is Sigmoid") pred, weight, bias = sigmoid_fn(hidden_layer, hidden_layer_nodes, 1) else: print("Ouput Layer is ReLU") pred, weight, bias = relu_fn(hidden_layer, hidden_layer_nodes, 1) cost = cost_function(_y, pred) W = [hidden_weight, weight] b = [hidden_bias, bias] return pred, cost, W, b def neural_network(_train_X, _train_y, _test_X, _test_y, _epochs, _rate, _regularisation, _cross_val, _output_layer=0): reg_type, reg_scale = _regularisation X = tf.placeholder(tf.float32, [None, hp.num_features(_train_X)], name="input") y = tf.placeholder(tf.float32, name="output") pred, cost, W, b = layers(X, y, _output_layer) lad = calc_error_L1(y, pred) huber_loss = huber_error(y, pred) print("Regularisation: ", _regularisation) if reg_type == 1: L1 = tf.contrib.layers.l1_regularizer(scale=reg_scale) reg_cost = tf.contrib.layers.apply_regularization(L1, W) elif reg_type == 2: L2 = tf.contrib.layers.l2_regularizer(scale=reg_scale) reg_cost = tf.contrib.layers.apply_regularization(L2, W) else: reg_cost = 0 cost += reg_cost optimizer = tf.train.GradientDescentOptimizer(_rate).minimize(cost) XyWb = [X, y, W, b] with tf.Session() as sess: if _cross_val == True: return hp.cross_validation(sess, XyWb, _train_X, _train_y, _test_X, _test_y, optimizer, cost, huber_loss, _epochs, "nn") else: return hp.run(sess, XyWb, _train_X, _train_y, _test_X, _test_y, optimizer, cost, huber_loss, _epochs, "nn")

[ "db1415@ic.ac.uk" ]

db1415@ic.ac.uk

84e879737e214d539d0b8ef455b15232c549954d

bdd738e4190ec53532a7278a7896a8053706d713

/Contents/Code/siteLubed.py

c48ec08070a44ca4cfd13ad450d1ea658dcdc7b1

[]

no_license

mutluerol/PhoenixAdult.bundle

c7709a2572631bb4033634a3cb21f1960f1e3929

6305158702d6e14fd5fe85e5bac9d8d3a96ba604

refs/heads/master

2020-04-15T07:49:09.118583

2019-01-07T23:02:01

164,502,693

0

1

null

2019-01-07T21:55:18

null

UTF-8

Python

false

3,529

py

import PAsearchSites import PAgenres def search(results,encodedTitle,title,searchTitle,siteNum,lang,searchByDateActor,searchDate,searchAll,searchSiteID): url = 'http://lubed.com/video/' + searchTitle.lower().replace(" ","-") searchResults = HTML.ElementFromURL(url) searchResult = searchResults.xpath('//div[@class="details col-sm-6 col-md-3 order-md-2 mb-2"]')[0] titleNoFormatting = searchResult.xpath('.//div[@class="row"]//div[@class="col-6 col-md-12"]//h1')[0].text_content() Log("Result Title: " + titleNoFormatting) cur = "/video/" + searchTitle.lower().replace(" ","-") curID = cur.replace('/','_') Log("ID: " + curID) releasedDate = searchResult.xpath('.//div[@class="row"]//div[@class="col-6 col-md-12"]//p')[0].text_content() girlName = searchResult.xpath('.//div[@class="row"]//div[@class="col-6 col-md-12"]//a')[0].text_content() Log("CurID" + str(curID)) lowerResultTitle = str(titleNoFormatting).lower() titleNoFormatting = girlName + " - " + titleNoFormatting + " [Lubed, " + releasedDate +"]" score = 100 results.Append(MetadataSearchResult(id = curID + "|" + str(siteNum), name = titleNoFormatting, score = score, lang = lang)) return results def update(metadata,siteID,movieGenres,movieActors): temp = str(metadata.id).split("|")[0].replace('_', '/') url = PAsearchSites.getSearchBaseURL(siteID) + temp Log('url :' + url) detailsPageElements = HTML.ElementFromURL(url) metadata.studio = "Lubed" # Summary # paragraph = detailsPageElements.xpath('//p[@class="desc"]')[0].text_content() # paragraph = paragraph.replace('&13;', '').strip(' \t\n\r"').replace('\n', '').replace(' ', '') + "\n\n" # metadata.summary = paragraph[:-10] tagline = "Lubed" metadata.collections.clear() metadata.tagline = tagline metadata.collections.add(tagline) metadata.title = detailsPageElements.xpath('//div[@class="details col-sm-6 col-md-3 order-md-2 mb-2"]//div[@class="row"]//div[@class="col-6 col-md-12"]//h1')[0].text_content() # Genres movieGenres.clearGenres() for genreName in ['60FPS', 'Lube', 'Raw', 'Wet', 'Sex', 'Ass', 'Pussy', 'Sex', 'Cumshot']: movieGenres.addGenre(genreName) # Actors movieActors.clearActors() titleActors = "" actors = detailsPageElements.xpath('//div[@class="details col-sm-6 col-md-3 order-md-2 mb-2"]//div[@class="row"]//div[@class="col-6 col-md-12"]//a') if len(actors) > 0: for actorLink in actors: actorPageURL = 'http://lubed.com' + actorLink.get("href") actorPage = HTML.ElementFromURL(actorPageURL) actorName = actorPage.xpath('//div[@class="col-md-3 order-md-2 mb-2 details"]//h1')[0].text_content() titleActors = titleActors + actorName + " & " actorPhotoURL = "http:" + actorPage.xpath('//div[@class="col-md-6 order-md-1 mb-4 image"]//a//img')[0].get("src") movieActors.addActor(actorName,actorPhotoURL) titleActors = titleActors[:-3] metadata.title = metadata.title # Posters background = "http:" + detailsPageElements.xpath('//video[@id="player"]')[0].get('poster') Log("BG DL: " + background) metadata.art[background] = Proxy.Preview(HTTP.Request(background, headers={'Referer': 'http://www.google.com'}).content, sort_order = 1) metadata.posters[background] = Proxy.Preview(HTTP.Request(background, headers={'Referer': 'http://www.google.com'}).content, sort_order = 1) return metadata

[ "pahelper@sahasrahla.com" ]

pahelper@sahasrahla.com

92988e5abacf6500ac71f7c3cc407f34fa9882ab

3b5f28ed1505c68f94ec1df496fe061d110294ce

/lixian.py

cd8a2380685cb4b548c5c15174ac20dd5d8358d0

[ "MIT" ]

permissive

yuanlizbyy/xunlei-lixian

089d388fbf4023bfae217906268c19dde43528e1

fe96ee19c1af8a268dc39818a5e8d33ff71e50ee

refs/heads/master

2021-01-17T21:48:13.932068

2012-12-10T05:35:43

7,854,959

1

0

null

UTF-8

Python

false

25,808

py

__all__ = ['XunleiClient'] import urllib import urllib2 import cookielib import re import time import os.path import json from ast import literal_eval def retry(f): #retry_sleeps = [1, 1, 1] retry_sleeps = [1, 2, 3, 5, 10, 20, 30, 60] + [60] * 60 def withretry(*args, **kwargs): for second in retry_sleeps: try: return f(*args, **kwargs) except: import traceback import sys print "Exception in user code:" traceback.print_exc(file=sys.stdout) time.sleep(second) raise return withretry class XunleiClient: page_size = 100 bt_page_size = 9999 def __init__(self, username=None, password=None, cookie_path=None, login=True): self.cookie_path = cookie_path if cookie_path: self.cookiejar = cookielib.LWPCookieJar() if os.path.exists(cookie_path): self.load_cookies() else: self.cookiejar = cookielib.CookieJar() self.set_page_size(self.page_size) self.opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(self.cookiejar)) if login: if not self.has_logged_in(): if not username and self.has_cookie('.xunlei.com', 'usernewno'): username = self.get_username() if not username: import lixian_config username = lixian_config.get_config('username') # if not username: # raise NotImplementedError('user is not logged in') if not password: raise NotImplementedError('user is not logged in') self.login(username, password) else: self.id = self.get_userid() @retry def urlopen(self, url, **args): #print url if 'data' in args and type(args['data']) == dict: args['data'] = urlencode(args['data']) return self.opener.open(urllib2.Request(url, **args), timeout=60) def urlread(self, url, **args): args.setdefault('headers', {}) headers = args['headers'] headers.setdefault('Accept-Encoding', 'gzip, deflate') # headers.setdefault('Referer', 'http://lixian.vip.xunlei.com/task.html') # headers.setdefault('User-Agent', 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:11.0) Gecko/20100101 Firefox/11.0') # headers.setdefault('Accept', 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8') # headers.setdefault('Accept-Language', 'zh-cn,zh;q=0.7,en-us;q=0.3') response = self.urlopen(url, **args) data = response.read() if response.info().get('Content-Encoding') == 'gzip': data = ungzip(data) elif response.info().get('Content-Encoding') == 'deflate': data = undeflate(data) return data def load_cookies(self): self.cookiejar.load(self.cookie_path, ignore_discard=True, ignore_expires=True) def save_cookies(self): if self.cookie_path: self.cookiejar.save(self.cookie_path, ignore_discard=True) def get_cookie(self, domain, k): if self.has_cookie(domain, k): return self.cookiejar._cookies[domain]['/'][k].value def has_cookie(self, domain, k): return domain in self.cookiejar._cookies and k in self.cookiejar._cookies[domain]['/'] def get_userid(self): if self.has_cookie('.xunlei.com', 'userid'): return self.get_cookie('.xunlei.com', 'userid') else: raise Exception('Probably login failed') def get_userid_or_none(self): return self.get_cookie('.xunlei.com', 'userid') def get_username(self): return self.get_cookie('.xunlei.com', 'usernewno') def get_gdriveid(self): return self.get_cookie('.vip.xunlei.com', 'gdriveid') def has_gdriveid(self): return self.has_cookie('.vip.xunlei.com', 'gdriveid') def get_referer(self): return 'http://dynamic.cloud.vip.xunlei.com/user_task?userid=%s' % self.id def set_cookie(self, domain, k, v): c = cookielib.Cookie(version=0, name=k, value=v, port=None, port_specified=False, domain=domain, domain_specified=True, domain_initial_dot=False, path='/', path_specified=True, secure=False, expires=None, discard=True, comment=None, comment_url=None, rest={}, rfc2109=False) self.cookiejar.set_cookie(c) def set_gdriveid(self, id): self.set_cookie('.vip.xunlei.com', 'gdriveid', id) def set_page_size(self, n): self.set_cookie('.vip.xunlei.com', 'pagenum', str(n)) def get_cookie_header(self): def domain_header(domain): root = self.cookiejar._cookies[domain]['/'] return '; '.join(k+'='+root[k].value for k in root) return domain_header('.xunlei.com') + '; ' + domain_header('.vip.xunlei.com') def is_login_ok(self, html): return len(html) > 512 def has_logged_in(self): id = self.get_userid_or_none() if not id: return False #print self.urlopen('http://dynamic.cloud.vip.xunlei.com/user_task?userid=%s&st=0' % id).read().decode('utf-8') self.set_page_size(1) url = 'http://dynamic.cloud.vip.xunlei.com/user_task?userid=%s&st=0' % id #url = 'http://dynamic.lixian.vip.xunlei.com/login?cachetime=%d' % current_timestamp() r = self.is_login_ok(self.urlread(url)) self.set_page_size(self.page_size) return r def login(self, username, password): cachetime = current_timestamp() check_url = 'http://login.xunlei.com/check?u=%s&cachetime=%d' % (username, cachetime) login_page = self.urlopen(check_url).read() verifycode = self.get_cookie('.xunlei.com', 'check_result')[2:].upper() password = encypt_password(password) password = md5(password+verifycode) login_page = self.urlopen('http://login.xunlei.com/sec2login/', data={'u': username, 'p': password, 'verifycode': verifycode}) self.id = self.get_userid() self.set_page_size(1) login_page = self.urlopen('http://dynamic.lixian.vip.xunlei.com/login?cachetime=%d&from=0'%current_timestamp()).read() self.set_page_size(self.page_size) assert self.is_login_ok(login_page), 'login failed' self.save_cookies() def logout(self): #session_id = self.get_cookie('.xunlei.com', 'sessionid') #timestamp = current_timestamp() #url = 'http://login.xunlei.com/unregister?sessionid=%s&cachetime=%s&noCacheIE=%s' % (session_id, timestamp, timestamp) #self.urlopen(url).read() #self.urlopen('http://dynamic.vip.xunlei.com/login/indexlogin_contr/logout/').read() ckeys = ["vip_isvip","lx_sessionid","vip_level","lx_login","dl_enable","in_xl","ucid","lixian_section"] ckeys1 = ["sessionid","usrname","nickname","usernewno","userid"] for k in ckeys: self.set_cookie('.vip.xunlei.com', k, '') for k in ckeys1: self.set_cookie('.xunlei.com', k, '') self.save_cookies() def read_task_page_url(self, url): page = self.urlread(url).decode('utf-8', 'ignore') if not self.has_gdriveid(): gdriveid = re.search(r'id="cok" value="([^"]+)"', page).group(1) self.set_gdriveid(gdriveid) self.save_cookies() tasks = parse_tasks(page) for t in tasks: t['client'] = self pginfo = re.search(r'<div class="pginfo">.*?</div>', page) match_next_page = re.search(r'<li class="next"><a href="([^"]+)">[^<>]*</a></li>', page) return tasks, match_next_page and 'http://dynamic.cloud.vip.xunlei.com'+match_next_page.group(1) def read_task_page(self, st, pg=None): if pg is None: url = 'http://dynamic.cloud.vip.xunlei.com/user_task?userid=%s&st=%d' % (self.id, st) else: url = 'http://dynamic.cloud.vip.xunlei.com/user_task?userid=%s&st=%d&p=%d' % (self.id, st, pg) return self.read_task_page_url(url) def read_tasks(self, st=0): '''read one page''' tasks = self.read_task_page(st)[0] for i, task in enumerate(tasks): task['#'] = i return tasks def read_all_tasks(self, st=0): '''read all pages''' all_tasks = [] tasks, next_link = self.read_task_page(st) all_tasks.extend(tasks) while next_link: tasks, next_link = self.read_task_page_url(next_link) all_tasks.extend(tasks) for i, task in enumerate(all_tasks): task['#'] = i return all_tasks def read_completed(self): '''read first page of completed tasks''' return self.read_tasks(2) def read_all_completed(self): '''read all pages of completed tasks''' return self.read_all_tasks(2) def read_history_page_url(self, url): self.set_cookie('.vip.xunlei.com', 'lx_nf_all', urllib.quote('page_check_all=history&fltask_all_guoqi=1&class_check=0&page_check=task&fl_page_id=0&class_check_new=0&set_tab_status=11')) page = self.urlread(url).decode('utf-8', 'ignore') if not self.has_gdriveid(): gdriveid = re.search(r'id="cok" value="([^"]+)"', page).group(1) self.set_gdriveid(gdriveid) self.save_cookies() tasks = parse_history(page) for t in tasks: t['client'] = self pginfo = re.search(r'<div class="pginfo">.*?</div>', page) match_next_page = re.search(r'<li class="next"><a href="([^"]+)">[^<>]*</a></li>', page) return tasks, match_next_page and 'http://dynamic.cloud.vip.xunlei.com'+match_next_page.group(1) def read_history_page(self, type=0, pg=None): if pg is None: url = 'http://dynamic.cloud.vip.xunlei.com/user_history?userid=%s&type=%d' % (self.id, type) else: url = 'http://dynamic.cloud.vip.xunlei.com/user_history?userid=%s&p=%d&type=%d' % (self.id, pg, type) return self.read_history_page_url(url) def read_history(self, type=0): '''read one page''' tasks = self.read_history_page(type)[0] for i, task in enumerate(tasks): task['#'] = i return tasks def read_all_history(self, type=0): '''read all pages of deleted/expired tasks''' all_tasks = [] tasks, next_link = self.read_history_page(type) all_tasks.extend(tasks) while next_link: tasks, next_link = self.read_history_page_url(next_link) all_tasks.extend(tasks) for i, task in enumerate(all_tasks): task['#'] = i return all_tasks def read_deleted(self): return self.read_history() def read_all_deleted(self): return self.read_all_history() def read_expired(self): return self.read_history(1) def read_all_expired(self): return self.read_all_history(1) def list_bt(self, task): assert task['type'] == 'bt' url = 'http://dynamic.cloud.vip.xunlei.com/interface/fill_bt_list?callback=fill_bt_list&tid=%s&infoid=%s&g_net=1&p=1&uid=%s&noCacheIE=%s' % (task['id'], task['bt_hash'], self.id, current_timestamp()) self.set_page_size(self.bt_page_size) html = remove_bom(self.urlread(url)).decode('utf-8') self.set_page_size(self.page_size) sub_tasks = parse_bt_list(html) for t in sub_tasks: t['date'] = task['date'] return sub_tasks def get_torrent_file_by_info_hash(self, info_hash): url = 'http://dynamic.cloud.vip.xunlei.com/interface/get_torrent?userid=%s&infoid=%s' % (self.id, info_hash.upper()) response = self.urlopen(url) torrent = response.read() if torrent == "<meta http-equiv='Content-Type' content='text/html; charset=utf-8' /><script>alert('\xe5\xaf\xb9\xe4\xb8\x8d\xe8\xb5\xb7\xef\xbc\x8c\xe6\xb2\xa1\xe6\x9c\x89\xe6\x89\xbe\xe5\x88\xb0\xe5\xaf\xb9\xe5\xba\x94\xe7\x9a\x84\xe7\xa7\x8d\xe5\xad\x90\xe6\x96\x87\xe4\xbb\xb6!');</script>": raise Exception('Torrent file not found on xunlei cloud: '+info_hash) assert response.headers['content-type'] == 'application/octet-stream' return torrent def get_torrent_file(self, task): return self.get_torrent_file_by_info_hash(task['bt_hash']) def add_task(self, url): protocol = parse_url_protocol(url) assert protocol in ('ed2k', 'http', 'ftp', 'thunder', 'Flashget', 'qqdl', 'bt', 'magnet'), 'protocol "%s" is not suppoted' % protocol from lixian_url import url_unmask url = url_unmask(url) protocol = parse_url_protocol(url) assert protocol in ('ed2k', 'http', 'ftp', 'bt', 'magnet'), 'protocol "%s" is not suppoted' % protocol if protocol == 'bt': return self.add_torrent_task_by_info_hash(url[5:]) elif protocol == 'magnet': return self.add_magnet_task(url) random = current_random() check_url = 'http://dynamic.cloud.vip.xunlei.com/interface/task_check?callback=queryCid&url=%s&random=%s&tcache=%s' % (urllib.quote(url), random, current_timestamp()) js = self.urlopen(check_url).read().decode('utf-8') qcid = re.match(r'^queryCid($.+$)\s*$', js).group(1) qcid = literal_eval(qcid) if len(qcid) == 8: cid, gcid, size_required, filename, goldbean_need, silverbean_need, is_full, random = qcid elif len(qcid) == 9: cid, gcid, size_required, filename, goldbean_need, silverbean_need, is_full, random, ext = qcid elif len(qcid) == 10: cid, gcid, size_required, some_key, filename, goldbean_need, silverbean_need, is_full, random, ext = qcid else: raise NotImplementedError(qcid) assert goldbean_need == 0 assert silverbean_need == 0 if url.startswith('http://') or url.startswith('ftp://'): task_type = 0 elif url.startswith('ed2k://'): task_type = 2 else: raise NotImplementedError() task_url = 'http://dynamic.cloud.vip.xunlei.com/interface/task_commit?'+urlencode( {'callback': 'ret_task', 'uid': self.id, 'cid': cid, 'gcid': gcid, 'size': size_required, 'goldbean': goldbean_need, 'silverbean': silverbean_need, 't': filename, 'url': url, 'type': task_type, 'o_page': 'task', 'o_taskid': '0', }) response = self.urlopen(task_url).read() assert response == 'ret_task(Array)', response def add_batch_tasks(self, urls, old_task_ids=None): assert urls urls = list(urls) for url in urls: if parse_url_protocol(url) not in ('http', 'ftp', 'ed2k', 'bt', 'thunder', 'magnet'): raise NotImplementedError('Unsupported: '+url) urls = filter(lambda u: parse_url_protocol(u) in ('http', 'ftp', 'ed2k', 'thunder'), urls) if not urls: return #self.urlopen('http://dynamic.cloud.vip.xunlei.com/interface/batch_task_check', data={'url':'\r\n'.join(urls), 'random':current_random()}) jsonp = 'jsonp%s' % current_timestamp() url = 'http://dynamic.cloud.vip.xunlei.com/interface/batch_task_commit?callback=%s' % jsonp if old_task_ids: batch_old_taskid = ','.join(old_task_ids) else: batch_old_taskid = '0' + ',' * (len(urls) - 1) # XXX: what is it? data = {} for i in range(len(urls)): data['cid[%d]' % i] = '' data['url[%d]' % i] = urllib.quote(to_utf_8(urls[i])) # fix per request #98 data['batch_old_taskid'] = batch_old_taskid response = self.urlopen(url, data=data).read() assert_response(response, jsonp, len(urls)) def add_torrent_task_by_content(self, content, path='attachment.torrent'): assert re.match(r'd\d+:', content), 'Probably not a valid content file [%s...]' % repr(content[:17]) upload_url = 'http://dynamic.cloud.vip.xunlei.com/interface/torrent_upload' jsonp = 'jsonp%s' % current_timestamp() commit_url = 'http://dynamic.cloud.vip.xunlei.com/interface/bt_task_commit?callback=%s' % jsonp content_type, body = encode_multipart_formdata([], [('filepath', path, content)]) response = self.urlopen(upload_url, data=body, headers={'Content-Type': content_type}).read().decode('utf-8') upload_success = re.search(r'<script>document\.domain="xunlei\.com";var btResult =(\{.*\});</script>', response, flags=re.S) if upload_success: bt = json.loads(upload_success.group(1)) bt_hash = bt['infoid'] bt_name = bt['ftitle'] bt_size = bt['btsize'] data = {'uid':self.id, 'btname':bt_name, 'cid':bt_hash, 'tsize':bt_size, 'findex':''.join(f['id']+'_' for f in bt['filelist']), 'size':''.join(f['subsize']+'_' for f in bt['filelist']), 'from':'0'} response = self.urlopen(commit_url, data=data).read() #assert_response(response, jsonp) assert re.match(r'%s${"id":"\d+","progress":1}$' % jsonp, response), repr(response) return bt_hash already_exists = re.search(r"parent\.edit_bt_list$(\{.*\}),''$", response, flags=re.S) if already_exists: bt = json.loads(already_exists.group(1)) bt_hash = bt['infoid'] return bt_hash raise NotImplementedError() def add_torrent_task_by_info_hash(self, sha1): return self.add_torrent_task_by_content(self.get_torrent_file_by_info_hash(sha1), sha1.upper()+'.torrent') def add_torrent_task(self, path): with open(path, 'rb') as x: return self.add_torrent_task_by_content(x.read(), os.path.basename(path)) def add_torrent_task_by_info_hash2(self, sha1, old_task_id=None): '''similar to add_torrent_task_by_info_hash, but faster. I may delete current add_torrent_task_by_info_hash completely in future''' link = 'http://dynamic.cloud.vip.xunlei.com/interface/get_torrent?userid=%s&infoid=%s' % (self.id, sha1) return self.add_torrent_task_by_link(link, old_task_id=old_task_id) def add_magnet_task(self, link): return self.add_torrent_task_by_link(link) def add_torrent_task_by_link(self, link, old_task_id=None): url = 'http://dynamic.cloud.vip.xunlei.com/interface/url_query?callback=queryUrl&u=%s&random=%s' % (urllib.quote(link), current_timestamp()) response = self.urlopen(url).read() success = re.search(r'queryUrl($1,.*$)\s*$', response, flags=re.S) if not success: already_exists = re.search(r"queryUrl$-1,'([^']{40})", response, flags=re.S) if already_exists: return already_exists.group(1) raise NotImplementedError(repr(response)) args = success.group(1).decode('utf-8') args = literal_eval(args.replace('new Array', '')) _, cid, tsize, btname, _, names, sizes_, sizes, _, types, findexes, timestamp = args def toList(x): if type(x) in (list, tuple): return x else: return [x] data = {'uid':self.id, 'btname':btname, 'cid':cid, 'tsize':tsize, 'findex':''.join(x+'_' for x in toList(findexes)), 'size':''.join(x+'_' for x in toList(sizes)), 'from':'0'} if old_task_id: data['o_taskid'] = old_task_id data['o_page'] = 'history' jsonp = 'jsonp%s' % current_timestamp() commit_url = 'http://dynamic.cloud.vip.xunlei.com/interface/bt_task_commit?callback=%s' % jsonp response = self.urlopen(commit_url, data=data).read() #assert_response(response, jsonp) assert re.match(r'%s\({"id":"\d+","progress":1}$' % jsonp, response), repr(response) return cid def readd_all_expired_tasks(self): url = 'http://dynamic.cloud.vip.xunlei.com/interface/delay_once?callback=anything' response = self.urlopen(url).read() def delete_tasks_by_id(self, ids): jsonp = 'jsonp%s' % current_timestamp() data = {'taskids': ','.join(ids)+',', 'databases': '0,'} url = 'http://dynamic.cloud.vip.xunlei.com/interface/task_delete?callback=%s&type=%s&noCacheIE=%s' % (jsonp, 2, current_timestamp()) # XXX: what is 'type'? response = self.urlopen(url, data=data).read() response = remove_bom(response) assert_response(response, jsonp, '{"result":1,"type":2}') def delete_task_by_id(self, id): self.delete_tasks_by_id([id]) def delete_task(self, task): self.delete_task_by_id(task['id']) def delete_tasks(self, tasks): self.delete_tasks_by_id([t['id'] for t in tasks]) def pause_tasks_by_id(self, ids): url = 'http://dynamic.cloud.vip.xunlei.com/interface/task_pause?tid=%s&uid=%s&noCacheIE=%s' % (','.join(ids)+',', self.id, current_timestamp()) assert self.urlopen(url).read() == 'pause_task_resp()' def pause_task_by_id(self, id): self.pause_tasks_by_id([id]) def pause_task(self, task): self.pause_task_by_id(task['id']) def pause_tasks(self, tasks): self.pause_tasks_by_id(t['id'] for t in tasks) def restart_tasks(self, tasks): jsonp = 'jsonp%s' % current_timestamp() url = 'http://dynamic.cloud.vip.xunlei.com/interface/redownload?callback=%s' % jsonp form = [] for task in tasks: assert task['type'] in ('ed2k', 'http', 'ftp', 'https', 'bt'), "'%s' is not tested" % task['type'] data = {'id[]': task['id'], 'cid[]': '', # XXX: should I set this? 'url[]': task['original_url'], 'download_status[]': task['status']} if task['type'] == 'ed2k': data['taskname[]'] = task['name'].encode('utf-8') # XXX: shouldn't I set this for other task types? form.append(urlencode(data)) form.append(urlencode({'type':1})) data = '&'.join(form) response = self.urlopen(url, data=data).read() assert_response(response, jsonp) def rename_task(self, task, new_name): assert type(new_name) == unicode url = 'http://dynamic.cloud.vip.xunlei.com/interface/rename' taskid = task['id'] bt = '1' if task['type'] == 'bt' else '0' url = url+'?'+urlencode({'taskid':taskid, 'bt':bt, 'filename':new_name.encode('utf-8')}) response = self.urlopen(url).read() assert '"result":0' in response, response def restart_task(self, task): self.restart_tasks([task]) def get_task_by_id(self, id): tasks = self.read_all_tasks(0) for x in tasks: if x['id'] == id: return x raise Exception('Not task found for id '+id) def current_timestamp(): return int(time.time()*1000) def current_random(): from random import randint return '%s%06d.%s' % (current_timestamp(), randint(0, 999999), randint(100000000, 9999999999)) def parse_task(html): inputs = re.findall(r'<input[^<>]+/>', html) def parse_attrs(html): return dict((k, v1 or v2) for k, v1, v2 in re.findall(r'''\b(\w+)=(?:'([^']*)'|"([^"]*)")''', html)) info = dict((x['id'], unescape_html(x['value'])) for x in map(parse_attrs, inputs)) mini_info = {} mini_map = {} #mini_info = dict((re.sub(r'\d+$', '', k), info[k]) for k in info) for k in info: mini_key = re.sub(r'\d+$', '', k) mini_info[mini_key] = info[k] mini_map[mini_key] = k taskid = mini_map['taskname'][8:] url = mini_info['f_url'] task_type = re.match(r'[^:]+', url).group() task = {'id': taskid, 'type': task_type, 'name': mini_info['taskname'], 'status': int(mini_info['d_status']), 'status_text': {'0':'waiting', '1':'downloading', '2':'completed', '3':'failed', '5':'pending'}[mini_info['d_status']], 'size': int(mini_info.get('ysfilesize', 0)), 'original_url': mini_info['f_url'], 'xunlei_url': mini_info.get('dl_url', None), 'bt_hash': mini_info['dcid'], 'dcid': mini_info['dcid'], 'gcid': parse_gcid(mini_info.get('dl_url', None)), } m = re.search(r'<em class="loadnum"[^<>]*>([^<>]*)</em>', html) task['progress'] = m and m.group(1) or '' m = re.search(r'<em [^<>]*id="speed\d+">([^<>]*)</em>', html) task['speed'] = m and m.group(1).replace(' ', '') or '' m = re.search(r'<span class="c_addtime">([^<>]*)</span>', html) task['date'] = m and m.group(1) or '' return task def parse_tasks(html): rwbox = re.search(r'<div class="rwbox".*', html, re.S).group() rw_lists = re.findall(r'<div class="rw_list".*?', rwbox, re.S) return map(parse_task, rw_lists) def parse_history(html): rwbox = re.search(r'<div class="rwbox" id="rowbox_list".*?', html, re.S).group() rw_lists = re.findall(r'<div class="rw_list".*?<input id="d_tasktype\d+"[^<>]*/>', rwbox, re.S) return map(parse_task, rw_lists) def parse_bt_list(js): result = json.loads(re.match(r'^fill_bt_list$(.+)$\s*$', js).group(1))['Result'] files = [] for record in result['Record']: files.append({ 'id': int(record['taskid']), 'index': record['id'], 'type': 'bt', 'name': record['title'], # TODO: support folder 'status': int(record['download_status']), 'status_text': {'0':'waiting', '1':'downloading', '2':'completed', '3':'failed'}[record['download_status']], 'size': int(record['filesize']), 'original_url': record['url'], 'xunlei_url': record['downurl'], 'dcid': record['cid'], 'gcid': parse_gcid(record['downurl']), 'speed': '', 'progress': '%s%%' % record['percent'], 'date': '', }) return files def parse_gcid(url): if not url: return m = re.search(r'&g=([A-F0-9]{40})&', url) if not m: return return m.group(1) def urlencode(x): def unif8(u): if type(u) == unicode: u = u.encode('utf-8') return u return urllib.urlencode([(unif8(k), unif8(v)) for k, v in x.items()]) def encode_multipart_formdata(fields, files): #http://code.activestate.com/recipes/146306/ """ fields is a sequence of (name, value) elements for regular form fields. files is a sequence of (name, filename, value) elements for data to be uploaded as files Return (content_type, body) ready for httplib.HTTP instance """ BOUNDARY = '----------ThIs_Is_tHe_bouNdaRY_$' CRLF = '\r\n' L = [] for (key, value) in fields: L.append('--' + BOUNDARY) L.append('Content-Disposition: form-data; name="%s"' % key) L.append('') L.append(value) for (key, filename, value) in files: L.append('--' + BOUNDARY) L.append('Content-Disposition: form-data; name="%s"; filename="%s"' % (key, filename)) L.append('Content-Type: %s' % get_content_type(filename)) L.append('') L.append(value) L.append('--' + BOUNDARY + '--') L.append('') body = CRLF.join(L) content_type = 'multipart/form-data; boundary=%s' % BOUNDARY return content_type, body def get_content_type(filename): import mimetypes return mimetypes.guess_type(filename)[0] or 'application/octet-stream' def assert_default_page(response, id): #assert response == "<script>top.location='http://dynamic.cloud.vip.xunlei.com/user_task?userid=%s&st=0'</script>" % id assert re.match(r"^<script>top\.location='http://dynamic\.cloud\.vip\.xunlei\.com/user_task\?userid=%s&st=0(&cache=\d+)?'</script>$" % id, response), response def remove_bom(response): if response.startswith('\xef\xbb\xbf'): response = response[3:] return response def assert_response(response, jsonp, value=1): response = remove_bom(response) assert response == '%s(%s)' % (jsonp, value), repr(response) def parse_url_protocol(url): m = re.match(r'([^:]+)://', url) if m: return m.group(1) elif url.startswith('magnet:'): return 'magnet' else: return url def unescape_html(html): import xml.sax.saxutils return xml.sax.saxutils.unescape(html) def to_utf_8(s): if type(s) == unicode: return s.encode('utf-8') else: return s def md5(s): import hashlib return hashlib.md5(s).hexdigest().lower() def encypt_password(password): if not re.match(r'^[0-9a-f]{32}$', password): password = md5(md5(password)) return password def ungzip(s): from StringIO import StringIO import gzip buffer = StringIO(s) f = gzip.GzipFile(fileobj=buffer) return f.read() def undeflate(s): import zlib return zlib.decompress(s, -zlib.MAX_WBITS)

[ "iambus@gmail.com" ]

iambus@gmail.com

a034cf49cfa642beaac238623dc1c694bb4c2ef7

e94c3050f391380848b3ab82992e9b1bb3803b49

/node_modules/node-sass/build/config.gypi

d2df84ecde9a71790827afc1e98440e4362ba0ba

[ "MIT", "LicenseRef-scancode-unknown-license-reference" ]

permissive

JaneGav/Template_email

cf6a8e0dd490697a763d28ee1067c8280ead0fe4

5b4880eabe822ca40a704d18ffcc79dc567c8b70

refs/heads/master

2020-04-19T17:05:38.243447

2019-01-30T10:33:57

168,323,958

0

null

UTF-8

Python

false

5,614

gypi

# Do not edit. File was generated by node-gyp's "configure" step { "target_defaults": { "cflags": [], "default_configuration": "Release", "defines": [], "include_dirs": [], "libraries": [] }, "variables": { "asan": 0, "build_v8_with_gn": "false", "coverage": "false", "debug_nghttp2": "false", "enable_lto": "false", "enable_pgo_generate": "false", "enable_pgo_use": "false", "force_dynamic_crt": 0, "host_arch": "x64", "icu_data_in": "../../deps/icu-small/source/data/in/icudt62l.dat", "icu_endianness": "l", "icu_gyp_path": "tools/icu/icu-generic.gyp", "icu_locales": "en,root", "icu_path": "deps/icu-small", "icu_small": "true", "icu_ver_major": "62", "llvm_version": "0", "node_byteorder": "little", "node_debug_lib": "false", "node_enable_d8": "false", "node_enable_v8_vtunejit": "false", "node_install_npm": "true", "node_module_version": 64, "node_no_browser_globals": "false", "node_prefix": "/usr/local", "node_release_urlbase": "https://nodejs.org/download/release/", "node_shared": "false", "node_shared_cares": "false", "node_shared_http_parser": "false", "node_shared_libuv": "false", "node_shared_nghttp2": "false", "node_shared_openssl": "false", "node_shared_zlib": "false", "node_tag": "", "node_target_type": "executable", "node_use_bundled_v8": "true", "node_use_dtrace": "true", "node_use_etw": "false", "node_use_large_pages": "false", "node_use_openssl": "true", "node_use_pch": "false", "node_use_perfctr": "false", "node_use_v8_platform": "true", "node_with_ltcg": "false", "node_without_node_options": "false", "openssl_fips": "", "openssl_no_asm": 0, "shlib_suffix": "64.dylib", "target_arch": "x64", "v8_enable_gdbjit": 0, "v8_enable_i18n_support": 1, "v8_enable_inspector": 1, "v8_no_strict_aliasing": 1, "v8_optimized_debug": 0, "v8_promise_internal_field_count": 1, "v8_random_seed": 0, "v8_trace_maps": 0, "v8_typed_array_max_size_in_heap": 0, "v8_use_snapshot": "true", "want_separate_host_toolset": 0, "xcode_version": "7.0", "nodedir": "/Users/dzhein/.node-gyp/10.14.2", "standalone_static_library": 1, "libsass_ext": "", "libsass_cflags": "", "libsass_ldflags": "", "libsass_library": "", "save_dev": "", "legacy_bundling": "", "dry_run": "", "viewer": "man", "only": "", "commit_hooks": "true", "browser": "", "also": "", "sign_git_commit": "", "rollback": "true", "usage": "", "audit": "true", "globalignorefile": "/Users/dzhein/.npm-global/etc/npmignore", "shell": "/bin/bash", "maxsockets": "50", "init_author_url": "", "shrinkwrap": "true", "parseable": "", "metrics_registry": "https://registry.npmjs.org/", "timing": "", "init_license": "ISC", "if_present": "", "sign_git_tag": "", "init_author_email": "", "cache_max": "Infinity", "preid": "", "long": "", "local_address": "", "git_tag_version": "true", "cert": "", "registry": "https://registry.npmjs.org/", "noproxy": "", "fetch_retries": "2", "versions": "", "message": "%s", "key": "", "globalconfig": "/Users/dzhein/.npm-global/etc/npmrc", "prefer_online": "", "logs_max": "10", "always_auth": "", "global_style": "", "cache_lock_retries": "10", "update_notifier": "true", "heading": "npm", "audit_level": "low", "searchlimit": "20", "read_only": "", "offline": "", "fetch_retry_mintimeout": "10000", "json": "", "access": "", "allow_same_version": "", "https_proxy": "", "engine_strict": "", "description": "true", "userconfig": "/Users/dzhein/.npmrc", "init_module": "/Users/dzhein/.npm-init.js", "cidr": "", "user": "501", "node_version": "10.14.2", "save": "true", "ignore_prepublish": "", "editor": "vi", "auth_type": "legacy", "tag": "latest", "script_shell": "", "progress": "true", "global": "", "searchstaleness": "900", "optional": "true", "ham_it_up": "", "save_prod": "", "force": "", "bin_links": "true", "searchopts": "", "node_gyp": "/Users/dzhein/.npm-global/lib/node_modules/npm/node_modules/node-gyp/bin/node-gyp.js", "depth": "Infinity", "sso_poll_frequency": "500", "rebuild_bundle": "true", "unicode": "true", "fetch_retry_maxtimeout": "60000", "tag_version_prefix": "v", "strict_ssl": "true", "sso_type": "oauth", "scripts_prepend_node_path": "warn-only", "save_prefix": "^", "ca": "", "save_exact": "", "group": "20", "fetch_retry_factor": "10", "dev": "", "version": "", "prefer_offline": "", "cache_lock_stale": "60000", "otp": "", "cache_min": "10", "searchexclude": "", "cache": "/Users/dzhein/.npm", "color": "true", "package_lock": "true", "package_lock_only": "", "save_optional": "", "ignore_scripts": "", "user_agent": "npm/6.7.0 node/v10.14.2 darwin x64", "cache_lock_wait": "10000", "production": "", "send_metrics": "", "save_bundle": "", "umask": "0022", "node_options": "", "init_version": "1.0.0", "init_author_name": "", "git": "git", "scope": "", "unsafe_perm": "true", "tmp": "/var/folders/s1/h9zjrylj1_b1bpwfrv8brhjr0000gn/T", "onload_script": "", "link": "", "prefix": "/Users/dzhein/.npm-global" } }

[ "eugeniavad@gmail.com" ]

eugeniavad@gmail.com

d57d6288a18c44ff8f681c65beb55e60255251a6

73868ce5fe6fd1e0c7c88f0779f2dfacab22d6e3

/skiplist.py

51d525fe284669e71824695a6dee9dab2531d58f

[ "CC0-1.0", "LicenseRef-scancode-public-domain" ]

permissive

vincentvbh/pqm3

f73185b878e6a6c5bb40d39a1031fda4ea201058

138ea1b3fee78814fac680da596ecb31ea11fdc3

refs/heads/master

2023-08-29T20:15:14.497159

2021-10-22T02:12:57

395,266,784

0

null

2021-08-12T09:35:06

2021-08-12T09:35:05

null

UTF-8

Python

false

9,968

py

skip_list = [ {'scheme': 'kyber1024', 'implementation': 'm3', 'estmemory': 12288}, {'scheme': 'kyber512', 'implementation': 'm3', 'estmemory': 7168}, {'scheme': 'kyber768', 'implementation': 'm3', 'estmemory': 9216}, {'scheme': 'saber', 'implementation': 'm3', 'estmemory': 22528}, {'scheme': 'sikep434', 'implementation': 'opt', 'estmemory': 10240}, {'scheme': 'sikep503', 'implementation': 'opt', 'estmemory': 10240}, {'scheme': 'sikep610', 'implementation': 'opt', 'estmemory': 14336}, {'scheme': 'sikep751', 'implementation': 'opt', 'estmemory': 16384}, {'scheme': 'bikel1', 'implementation': 'opt', 'estmemory': 90112}, {'scheme': 'bikel3', 'implementation': 'opt', 'estmemory': 175104}, {'scheme': 'firesaber', 'implementation': 'clean', 'estmemory': 28672}, {'scheme': 'frodokem1344aes', 'implementation': 'clean', 'estmemory': 3853312}, {'scheme': 'frodokem1344aes', 'implementation': 'opt', 'estmemory': 305152}, {'scheme': 'frodokem1344shake', 'implementation': 'clean', 'estmemory': 3852288}, {'scheme': 'frodokem1344shake', 'implementation': 'opt', 'estmemory': 252928}, {'scheme': 'frodokem640aes', 'implementation': 'clean', 'estmemory': 932864}, {'scheme': 'frodokem640aes', 'implementation': 'opt', 'estmemory': 144384}, {'scheme': 'frodokem640shake', 'implementation': 'clean', 'estmemory': 932864}, {'scheme': 'frodokem640shake', 'implementation': 'opt', 'estmemory': 119808}, {'scheme': 'frodokem976aes', 'implementation': 'clean', 'estmemory': 2080768}, {'scheme': 'frodokem976aes', 'implementation': 'opt', 'estmemory': 222208}, {'scheme': 'frodokem976shake', 'implementation': 'clean', 'estmemory': 2079744}, {'scheme': 'frodokem976shake', 'implementation': 'opt', 'estmemory': 185344}, {'scheme': 'kyber1024-90s', 'implementation': 'clean', 'estmemory': 28672}, {'scheme': 'kyber1024', 'implementation': 'clean', 'estmemory': 28672}, {'scheme': 'kyber512-90s', 'implementation': 'clean', 'estmemory': 15360}, {'scheme': 'kyber512', 'implementation': 'clean', 'estmemory': 14336}, {'scheme': 'kyber768', 'implementation': 'clean', 'estmemory': 21504}, {'scheme': 'lightsaber', 'implementation': 'clean', 'estmemory': 15360}, {'scheme': 'kyber768-90s', 'implementation': 'clean', 'estmemory': 21504}, {'scheme': 'mceliece348864', 'implementation': 'clean', 'estmemory': 833536}, {'scheme': 'mceliece348864f', 'implementation': 'clean', 'estmemory': 833536}, {'scheme': 'mceliece460896', 'implementation': 'clean', 'estmemory': 4733952}, {'scheme': 'mceliece460896f', 'implementation': 'clean', 'estmemory': 4733952}, {'scheme': 'mceliece6688128', 'implementation': 'clean', 'estmemory': 5255168}, {'scheme': 'mceliece6688128f', 'implementation': 'clean', 'estmemory': 5255168}, {'scheme': 'mceliece6960119', 'implementation': 'clean', 'estmemory': 5257216}, {'scheme': 'mceliece6960119f', 'implementation': 'clean', 'estmemory': 5257216}, {'scheme': 'mceliece8192128', 'implementation': 'clean', 'estmemory': 5568512}, {'scheme': 'mceliece8192128f', 'implementation': 'clean', 'estmemory': 5568512}, {'scheme': 'ntruhps2048509', 'implementation': 'clean', 'estmemory': 29696}, {'scheme': 'ntruhps2048677', 'implementation': 'clean', 'estmemory': 38912}, {'scheme': 'ntruhps4096821', 'implementation': 'clean', 'estmemory': 47104}, {'scheme': 'ntruhrss701', 'implementation': 'clean', 'estmemory': 38912}, {'scheme': 'saber', 'implementation': 'clean', 'estmemory': 20480}, {'scheme': 'hqc-rmrs-128', 'implementation': 'clean', 'estmemory': 81920}, {'scheme': 'hqc-rmrs-192', 'implementation': 'clean', 'estmemory': 161792}, {'scheme': 'hqc-rmrs-256', 'implementation': 'clean', 'estmemory': 257024}, {'scheme': 'ntrulpr653', 'implementation': 'clean', 'estmemory': 18432}, {'scheme': 'ntrulpr761', 'implementation': 'clean', 'estmemory': 19456}, {'scheme': 'ntrulpr857', 'implementation': 'clean', 'estmemory': 23552}, {'scheme': 'sntrup653', 'implementation': 'clean', 'estmemory': 15360}, {'scheme': 'sntrup761', 'implementation': 'clean', 'estmemory': 18432}, {'scheme': 'sntrup857', 'implementation': 'clean', 'estmemory': 20480}, {'scheme': 'dilithium2', 'implementation': 'clean', 'estmemory': 60416}, {'scheme': 'dilithium3', 'implementation': 'clean', 'estmemory': 91136}, {'scheme': 'falcon-1024', 'implementation': 'clean', 'estmemory': 90112}, {'scheme': 'falcon-512', 'implementation': 'clean', 'estmemory': 47104}, {'scheme': 'sphincs-haraka-128f-robust', 'implementation': 'clean', 'estmemory': 23552}, {'scheme': 'sphincs-haraka-128f-simple', 'implementation': 'clean', 'estmemory': 23552}, {'scheme': 'sphincs-haraka-128s-robust', 'implementation': 'clean', 'estmemory': 13312}, {'scheme': 'sphincs-haraka-128s-simple', 'implementation': 'clean', 'estmemory': 13312}, {'scheme': 'sphincs-haraka-192f-robust', 'implementation': 'clean', 'estmemory': 43008}, {'scheme': 'sphincs-haraka-192f-simple', 'implementation': 'clean', 'estmemory': 43008}, {'scheme': 'sphincs-haraka-192s-robust', 'implementation': 'clean', 'estmemory': 23552}, {'scheme': 'sphincs-haraka-192s-simple', 'implementation': 'clean', 'estmemory': 23552}, {'scheme': 'sphincs-haraka-256f-robust', 'implementation': 'clean', 'estmemory': 59392}, {'scheme': 'sphincs-haraka-256f-simple', 'implementation': 'clean', 'estmemory': 59392}, {'scheme': 'sphincs-haraka-256s-robust', 'implementation': 'clean', 'estmemory': 38912}, {'scheme': 'sphincs-haraka-256s-simple', 'implementation': 'clean', 'estmemory': 38912}, {'scheme': 'sphincs-sha256-128f-robust', 'implementation': 'clean', 'estmemory': 21504}, {'scheme': 'sphincs-sha256-128f-simple', 'implementation': 'clean', 'estmemory': 21504}, {'scheme': 'sphincs-sha256-128s-robust', 'implementation': 'clean', 'estmemory': 12288}, {'scheme': 'sphincs-sha256-128s-simple', 'implementation': 'clean', 'estmemory': 12288}, {'scheme': 'sphincs-sha256-192f-robust', 'implementation': 'clean', 'estmemory': 41984}, {'scheme': 'sphincs-sha256-192f-simple', 'implementation': 'clean', 'estmemory': 41984}, {'scheme': 'sphincs-sha256-192s-robust', 'implementation': 'clean', 'estmemory': 22528}, {'scheme': 'sphincs-sha256-192s-simple', 'implementation': 'clean', 'estmemory': 22528}, {'scheme': 'sphincs-sha256-256f-robust', 'implementation': 'clean', 'estmemory': 57344}, {'scheme': 'sphincs-sha256-256f-simple', 'implementation': 'clean', 'estmemory': 57344}, {'scheme': 'sphincs-sha256-256s-robust', 'implementation': 'clean', 'estmemory': 37888}, {'scheme': 'sphincs-sha256-256s-simple', 'implementation': 'clean', 'estmemory': 37888}, {'scheme': 'sphincs-shake256-128f-robust', 'implementation': 'clean', 'estmemory': 21504}, {'scheme': 'sphincs-shake256-128f-simple', 'implementation': 'clean', 'estmemory': 21504}, {'scheme': 'sphincs-shake256-128s-robust', 'implementation': 'clean', 'estmemory': 12288}, {'scheme': 'sphincs-shake256-128s-simple', 'implementation': 'clean', 'estmemory': 12288}, {'scheme': 'sphincs-shake256-192f-robust', 'implementation': 'clean', 'estmemory': 41984}, {'scheme': 'sphincs-shake256-192f-simple', 'implementation': 'clean', 'estmemory': 41984}, {'scheme': 'sphincs-shake256-192s-robust', 'implementation': 'clean', 'estmemory': 22528}, {'scheme': 'sphincs-shake256-192s-simple', 'implementation': 'clean', 'estmemory': 22528}, {'scheme': 'sphincs-shake256-256f-robust', 'implementation': 'clean', 'estmemory': 57344}, {'scheme': 'sphincs-shake256-256f-simple', 'implementation': 'clean', 'estmemory': 57344}, {'scheme': 'sphincs-shake256-256s-robust', 'implementation': 'clean', 'estmemory': 37888}, {'scheme': 'sphincs-shake256-256s-simple', 'implementation': 'clean', 'estmemory': 37888}, {'scheme': 'dilithium2aes', 'implementation': 'clean', 'estmemory': 61440}, {'scheme': 'dilithium3aes', 'implementation': 'clean', 'estmemory': 92160}, {'scheme': 'dilithium5', 'implementation': 'clean', 'estmemory': 136192}, {'scheme': 'dilithium5aes', 'implementation': 'clean', 'estmemory': 138240}, {'scheme': 'rainbowI-circumzenithal', 'implementation': 'clean', 'estmemory': 490496}, {'scheme': 'rainbowI-classic', 'implementation': 'clean', 'estmemory': 445440}, {'scheme': 'rainbowI-compressed', 'implementation': 'clean', 'estmemory': 387072}, {'scheme': 'rainbowIII-circumzenithal', 'implementation': 'clean', 'estmemory': 5087232}, {'scheme': 'rainbowIII-classic', 'implementation': 'clean', 'estmemory': 5704704}, {'scheme': 'rainbowIII-compressed', 'implementation': 'clean', 'estmemory': 4460544}, {'scheme': 'rainbowV-circumzenithal', 'implementation': 'clean', 'estmemory': 6140928}, {'scheme': 'rainbowV-classic', 'implementation': 'clean', 'estmemory': 7535616}, {'scheme': 'rainbowV-compressed', 'implementation': 'clean', 'estmemory': 4732928}, {'scheme': 'falcon-1024-tree', 'implementation': 'opt-ct', 'estmemory': 186368}, {'scheme': 'falcon-1024-tree', 'implementation': 'opt-leaktime', 'estmemory': 186368}, {'scheme': 'falcon-1024', 'implementation': 'opt-ct', 'estmemory': 90112}, {'scheme': 'falcon-1024', 'implementation': 'opt-leaktime', 'estmemory': 90112}, {'scheme': 'falcon-512-tree', 'implementation': 'opt-ct', 'estmemory': 91136}, {'scheme': 'falcon-512-tree', 'implementation': 'opt-leaktime', 'estmemory': 91136}, {'scheme': 'falcon-512', 'implementation': 'opt-ct', 'estmemory': 47104}, {'scheme': 'falcon-512', 'implementation': 'opt-leaktime', 'estmemory': 47104}, {'scheme': 'dilithium2', 'implementation': 'm3', 'estmemory': 46080}, {'scheme': 'dilithium3', 'implementation': 'm3', 'estmemory': 62464}, {'scheme': 'dilithium4', 'implementation': 'm3', 'estmemory': 79872}, ]

[ "git@rpls.de" ]

git@rpls.de

7e106c21d729df1b192289fad2ebdb0b3a916922

d49d0428835d9def6a6eb8f255b4f352b2f913bd

/GF_company.py

ed6ab043da835db4e393c1c6326fd8fd4253bddd

[]

no_license

UCanCallMeJia/wechat_GF

2e6b88dc1e4cb8c3c0ad7a94349666af27e46940

831c6f85c37b82e39b4ff23301d201a12978cc5c

refs/heads/master

2020-08-30T03:30:21.878953

2020-07-01T02:08:49

218,248,883

1

0

null

UTF-8

Python

false

11,721

py

from __future__ import unicode_literals from wxpy import * from requests import get from requests import post from platform import system from os import chdir from random import choice from threading import Thread import configparser import time import sys # 获取每日励志精句 def get_message(): r = get("http://open.iciba.com/dsapi/") note = r.json()['note'] content = r.json()['content'] return note,content # 发送消息给她 def send_message(your_message): try: # 对方的微信名称 my_friend = bot.friends().search('咸鱼不会翻身吗')[0] # 发送消息给对方 my_friend.send(your_message) except: # 出问题时，发送信息到文件传输助手 bot.file_helper.send(u"守护女友出问题了，赶紧去看看咋回事~") # 在规定时间内进行关心她操作 def start_care(): # 待发送的内容，先置为空 message = "" # 来个死循环，24小时关心她 while(True): # 提示 print("守护中，时间:%s"% time.ctime()) # 每天定时问候，早上起床，中午吃饭，晚上吃饭，晚上睡觉 # 获取时间，只获取时和分，对应的位置为倒数第13位到倒数第8位 now_time = time.ctime()[-13:-8] if (now_time == say_good_morning): # 随机取一句问候语 message = choice(str_list_good_morning) # 是否加上随机表情 if(flag_wx_emoj): message = message + choice(str_list_emoj) send_message(message) print("提醒女友早上起床:%s" % time.ctime()) elif (now_time == say_good_lunch): message = choice(str_list_good_lunch) # 是否加上随机表情 if(flag_wx_emoj): message = message + choice(str_list_emoj) send_message('智能男友用法：消息以‘_’开始，例如：‘_在吗’') send_message(message) print("提醒女友中午吃饭:%s" % time.ctime()) elif (now_time == say_good_dinner): message = choice(str_list_good_dinner) # 是否加上随机表情 if(flag_wx_emoj): message = message + choice(str_list_emoj) send_message(message) print("提醒女友晚上吃饭:%s" % time.ctime()) elif (now_time == say_good_dream): # 是否在结尾加上每日学英语 if(flag_learn_english): note, content = get_message() message = choice(str_list_good_dream) + "\n\n" + "顺便一起来学英语哦：\n" + "原文: " + content + "\n\n翻译: " + note else: message = choice(str_list_good_dream) # 是否加上随机表情 if(flag_wx_emoj): message = message + choice(str_list_emoj) send_message(message) print("提醒女友晚上睡觉:%s" % time.ctime()) # 节日问候语 festival_month = time.strftime('%m', time.localtime()) festival_day = time.strftime('%d', time.localtime()) if(festival_month == '02' and festival_day == '14' and now_time == "08:00"): send_message(str_Valentine) print("发送情人节祝福:%s" % time.ctime()) elif(festival_month == '03' and festival_day == '08' and now_time == "08:00"): send_message(str_Women) print("发送三八妇女节祝福:%s" % time.ctime()) elif(festival_month == '12' and festival_day == '24' and now_time == "00:00"): send_message(str_Christmas_Eve) print("发送平安夜祝福:%s" % time.ctime()) elif(festival_month == '12' and festival_day == '25' and now_time == "00:00"): send_message(str_Christmas) print("发送圣诞节祝福:%s" % time.ctime()) # 生日问候语 if(festival_month == birthday_month and festival_day == birthday_day and now_time == "00:00"): send_message(str_birthday) print("发送生日祝福:%s" % time.ctime()) # 每60秒检测一次 time.sleep(60) if __name__ == "__main__": # 若发现读取取配置文件出错，可以取消注释下面这行，一般在pycharm环境下才需要增加 # 设置当前文件所在的目录为当前工作路径 # chdir(sys.path[0]) # 启动微信机器人，自动根据操作系统执行不同的指令 # windows系统或macOS Sierra系统使用bot = Bot() # linux系统或macOS Terminal系统使用bot = Bot(console_qr=2) if('Windows' in system()): # Windows bot = Bot() elif('Darwin' in system()): # MacOSX bot = Bot() elif('Linux' in system()): # Linux bot = Bot(console_qr=2,cache_path=True) else: # 自行确定 print("无法识别你的操作系统类型，请自己设置") # 读取配置文件 cf = configparser.ConfigParser() cf.read(r"D:\python_ws\GirlFriend\config.ini",encoding='UTF-8') # 设置女友的微信名称，记住，不是微信ID也不是微信备注 # 你女友的微信名称，记住，不是微信ID也不是微信备注 my_lady_wechat_name = cf.get("configuration", "my_lady_wechat_name") # 设置早上起床时间，中午吃饭时间，下午吃饭时间，晚上睡觉时间 say_good_morning = cf.get("configuration", "say_good_morning") say_good_lunch = cf.get("configuration", "say_good_lunch") say_good_dinner = cf.get("configuration", "say_good_dinner") say_good_dream = cf.get("configuration", "say_good_dream") # 设置女友生日信息 # 几月，注意补全数字，为两位数，比如6月必须写成06 birthday_month = cf.get("configuration", "birthday_month") # 几号，注意补全数字，为两位数，比如6号必须写成08 birthday_day = cf.get("configuration", "birthday_day") # 读取早上起床时间，中午吃饭时间，下午吃饭时间，晚上睡觉时间的随机提示语 # 一般这里的代码不要改动，需要增加提示语可以自己打开对应的文件修改 #早上起床问候语列表，数据来源于新浪微博 str_list_good_morning = '' with open(r"D:\python_ws\GirlFriend\sentence_good_morning.txt", "r",encoding='UTF-8') as f: str_list_good_morning = f.readlines() print(str_list_good_morning) #中午吃饭问候语列表，数据来源于新浪微博 str_list_good_lunch = '' with open(r"D:\python_ws\GirlFriend\sentence_good_lunch.txt", "r",encoding='UTF-8') as f: str_list_good_lunch = f.readlines() print(str_list_good_lunch) #晚上吃饭问候语列表，数据来源于新浪微博 str_list_good_dinner = '' with open(r"D:\python_ws\GirlFriend\sentence_good_dinner.txt", "r",encoding='UTF-8') as f: str_list_good_dinner = f.readlines() print(str_list_good_dinner) #晚上睡觉问候语列表，数据来源于新浪微博 str_list_good_dream = '' with open(r"D:\python_ws\GirlFriend\sentence_good_dream.txt", "r",encoding='UTF-8') as f: str_list_good_dream = f.readlines() print(str_list_good_dream) # 设置晚上睡觉问候语是否在原来的基础上再加上每日学英语精句 # False表示否 True表示是 if((cf.get("configuration", "flag_learn_english")) == '1'): flag_learn_english = True else: flag_learn_english = False print(flag_learn_english) # 设置所有问候语结束是否加上表情符号 # False表示否 True表示是 str_emoj = "(•‾̑⌣‾̑•)✧˖°----(๑´ڡ`๑)----(๑¯ิε ¯ิ๑)----(๑•́ ₃ •̀๑)----( ∙̆ .̯ ∙̆ )----(๑˘ ˘๑)----(●′ω`●)----(●･̆⍛･̆●)----ಥ_ಥ----_(:qゝ∠)----(´；ω；`)----( `)3')----Σ((( つ•̀ω•́)つ----╰(*´︶`*)╯----( ´´ิ∀´ิ` )----(´∩｀。)----( ื▿ ื)----(｡ŏ_ŏ)----( •ิ _ •ิ )----ヽ(*΄◞ิ౪◟ิ‵ *)----( ˘ ³˘)----(; ´_ゝ`)----(*ˉ﹃ˉ)----(◍'౪`◍)ﾉﾞ----(｡◝‿◜｡)----(ಠ .̫.̫ ಠ)----(´◞⊖◟`)----(。≖ˇェˇ≖｡)----(◕ܫ◕)----(｀◕‸◕´+)----(▼ _ ▼)----( ◉ืൠ◉ื)----ㄟ(◑‿◐ )ㄏ----(●'◡'●)ﾉ♥----(｡◕ˇ∀ˇ◕）----( ◔ ڼ ◔ )----( ´◔ ‸◔`)----(☍﹏⁰)----(♥◠‿◠)----ლ(╹◡╹ლ )----(๑꒪◞౪◟꒪๑)" str_list_emoj = str_emoj.split('----') if ((cf.get("configuration", "flag_wx_emoj")) == '1'): flag_wx_emoj = True else: flag_wx_emoj = False print(str_list_emoj) # 设置节日祝福语 # 情人节祝福语 str_Valentine = cf.get("configuration", "str_Valentine") print(str_Valentine) # 三八妇女节祝福语 str_Women = cf.get("configuration", "str_Women") print(str_Women) # 平安夜祝福语 str_Christmas_Eve = cf.get("configuration", "str_Christmas_Eve") print(str_Christmas_Eve) # 圣诞节祝福语 str_Christmas = cf.get("configuration", "str_Christmas") print(str_Christmas) # 她生日的时候的祝福语 str_birthday = cf.get("configuration", "str_birthday") print(str_birthday) # 开始守护女友 t = Thread(target=start_care, name='start_care') t.start() # 接收女友消息监听器 # 女友微信名 my_girl_friend = bot.friends().search(my_lady_wechat_name)[0] @bot.register(chats=my_girl_friend, except_self=False) def print_others(msg): # 输出聊天内容 print(msg.text) # 可采用snownlp或者jieba等进行分词、情感分析，由于打包后文件体积太大，故暂时不采用这种方式 # 仅仅是直接调用网络接口 # 做极其简单的情感分析 # 结果仅供参考，请勿完全相信 postData = {'data':msg.text} response = post('https://bosonnlp.com/analysis/sentiment?analysisType=',data=postData) data = response.text # 情感评分指数(越接近1表示心情越好，越接近0表示心情越差) now_mod_rank = (data.split(',')[0]).replace('[[','') print("来自女友的消息:%s\n当前情感得分:%s\n越接近1表示心情越好，越接近0表示心情越差，情感结果仅供参考，请勿完全相信！\n\n" % (msg.text, now_mod_rank)) # 发送信息到文件传输助手 mood_message = u"来自女友的消息:" + msg.text + "\n当前情感得分:" + now_mod_rank + "\n越接近1表示心情越好，越接近0表示心情越差，情感结果仅供参考，请勿完全相信！\n\n" bot.file_helper.send(mood_message) text = msg.text[1:] if msg.text[0] == '_': print(text) api_url = 'http://www.tuling123.com/openapi/api' # 图灵机器人网址 data = { 'key': '453b2da4ec4f4bec947fda36f6e1eedf', # 如果这个 apiKey 如不能用，那就注册一次 'info': text, # 这是我们从好友接收到的消息然后转发给图灵机器人 'userid': 'wechat-robot', # 这里你想改什么都可以 } r = post(api_url, data=data).json() # 把data数据发 print(r.get('text')) # 机器人回复给好友的消息 return r['text']

[ "noreply@github.com" ]

UCanCallMeJia.noreply@github.com

d8e4ec2df7ef5c4033d1ea233f4c92691b53493b

d6235a8215b0b57105336039c49ccb78400d5376

/src/utils/inference.py

4f9182b0b8879b2fa3e8c8abcb5910b063501c3a

[]

no_license

Ibrahimkhawaja/Facial_Emotion_Recognision

61d40da83e9015af805ac6479f647caea9f33219

9fab1117b9e95a40a50813bcc28cc6778238f423

refs/heads/master

2022-12-01T11:43:26.440616

2020-02-05T17:09:31

238,501,241

0

null

2022-11-21T21:16:18

2020-02-05T16:52:43

Python

UTF-8

Python

false

1,398

py

import cv2 import matplotlib.pyplot as plt import numpy as np from keras.preprocessing import image def load_image(image_path, grayscale=False, color_mode="rgb", target_size=None): pil_image = image.load_img(image_path, grayscale, color_mode, target_size) return image.img_to_array(pil_image) def load_detection_model(model_path): detection_model = cv2.CascadeClassifier(model_path) return detection_model def detect_faces(detection_model, gray_image_array): return detection_model.detectMultiScale(gray_image_array, 1.3, 5) def draw_bounding_box(face_coordinates, image_array, color): x, y, w, h = face_coordinates cv2.rectangle(image_array, (x, y), (x + w, y + h), color, 2) def apply_offsets(face_coordinates, offsets): x, y, width, height = face_coordinates x_off, y_off = offsets return (x - x_off, x + width + x_off, y - y_off, y + height + y_off) def draw_text(coordinates, image_array, text, color, x_offset=0, y_offset=0, font_scale=2, thickness=2): x, y = coordinates[:2] cv2.putText(image_array, text, (x + x_offset, y + y_offset), cv2.FONT_HERSHEY_SIMPLEX, font_scale, color, thickness, cv2.LINE_AA) def get_colors(num_classes): colors = plt.cm.hsv(np.linspace(0, 1, num_classes)).tolist() colors = np.asarray(colors) * 255 return colors

[ "khawajaibrahim2011@hotmail.com" ]

khawajaibrahim2011@hotmail.com

339e40ac12cbd66cb7e200816179b447721ff4d6

2af6a5c2d33e2046a1d25ae9dd66d349d3833940

/res_bw/scripts/common/lib/curses/has_key.py

7260fcff66f2171899806164e7f08e769cb9a4e2

[]

no_license

webiumsk/WOT-0.9.12-CT

e6c8b5bb106fad71b5c3056ada59fb1aebc5f2b2

2506e34bd6634ad500b6501f4ed4f04af3f43fa0

refs/heads/master

2021-01-10T01:38:38.080814

2015-11-11T00:08:04

45,803,240

0

null

WINDOWS-1250

Python

false

5,057

py

# 2015.11.10 21:35:00 Střední Evropa (běžný čas) # Embedded file name: scripts/common/Lib/curses/has_key.py import _curses _capability_names = {_curses.KEY_A1: 'ka1', _curses.KEY_A3: 'ka3', _curses.KEY_B2: 'kb2', _curses.KEY_BACKSPACE: 'kbs', _curses.KEY_BEG: 'kbeg', _curses.KEY_BTAB: 'kcbt', _curses.KEY_C1: 'kc1', _curses.KEY_C3: 'kc3', _curses.KEY_CANCEL: 'kcan', _curses.KEY_CATAB: 'ktbc', _curses.KEY_CLEAR: 'kclr', _curses.KEY_CLOSE: 'kclo', _curses.KEY_COMMAND: 'kcmd', _curses.KEY_COPY: 'kcpy', _curses.KEY_CREATE: 'kcrt', _curses.KEY_CTAB: 'kctab', _curses.KEY_DC: 'kdch1', _curses.KEY_DL: 'kdl1', _curses.KEY_DOWN: 'kcud1', _curses.KEY_EIC: 'krmir', _curses.KEY_END: 'kend', _curses.KEY_ENTER: 'kent', _curses.KEY_EOL: 'kel', _curses.KEY_EOS: 'ked', _curses.KEY_EXIT: 'kext', _curses.KEY_F0: 'kf0', _curses.KEY_F1: 'kf1', _curses.KEY_F10: 'kf10', _curses.KEY_F11: 'kf11', _curses.KEY_F12: 'kf12', _curses.KEY_F13: 'kf13', _curses.KEY_F14: 'kf14', _curses.KEY_F15: 'kf15', _curses.KEY_F16: 'kf16', _curses.KEY_F17: 'kf17', _curses.KEY_F18: 'kf18', _curses.KEY_F19: 'kf19', _curses.KEY_F2: 'kf2', _curses.KEY_F20: 'kf20', _curses.KEY_F21: 'kf21', _curses.KEY_F22: 'kf22', _curses.KEY_F23: 'kf23', _curses.KEY_F24: 'kf24', _curses.KEY_F25: 'kf25', _curses.KEY_F26: 'kf26', _curses.KEY_F27: 'kf27', _curses.KEY_F28: 'kf28', _curses.KEY_F29: 'kf29', _curses.KEY_F3: 'kf3', _curses.KEY_F30: 'kf30', _curses.KEY_F31: 'kf31', _curses.KEY_F32: 'kf32', _curses.KEY_F33: 'kf33', _curses.KEY_F34: 'kf34', _curses.KEY_F35: 'kf35', _curses.KEY_F36: 'kf36', _curses.KEY_F37: 'kf37', _curses.KEY_F38: 'kf38', _curses.KEY_F39: 'kf39', _curses.KEY_F4: 'kf4', _curses.KEY_F40: 'kf40', _curses.KEY_F41: 'kf41', _curses.KEY_F42: 'kf42', _curses.KEY_F43: 'kf43', _curses.KEY_F44: 'kf44', _curses.KEY_F45: 'kf45', _curses.KEY_F46: 'kf46', _curses.KEY_F47: 'kf47', _curses.KEY_F48: 'kf48', _curses.KEY_F49: 'kf49', _curses.KEY_F5: 'kf5', _curses.KEY_F50: 'kf50', _curses.KEY_F51: 'kf51', _curses.KEY_F52: 'kf52', _curses.KEY_F53: 'kf53', _curses.KEY_F54: 'kf54', _curses.KEY_F55: 'kf55', _curses.KEY_F56: 'kf56', _curses.KEY_F57: 'kf57', _curses.KEY_F58: 'kf58', _curses.KEY_F59: 'kf59', _curses.KEY_F6: 'kf6', _curses.KEY_F60: 'kf60', _curses.KEY_F61: 'kf61', _curses.KEY_F62: 'kf62', _curses.KEY_F63: 'kf63', _curses.KEY_F7: 'kf7', _curses.KEY_F8: 'kf8', _curses.KEY_F9: 'kf9', _curses.KEY_FIND: 'kfnd', _curses.KEY_HELP: 'khlp', _curses.KEY_HOME: 'khome', _curses.KEY_IC: 'kich1', _curses.KEY_IL: 'kil1', _curses.KEY_LEFT: 'kcub1', _curses.KEY_LL: 'kll', _curses.KEY_MARK: 'kmrk', _curses.KEY_MESSAGE: 'kmsg', _curses.KEY_MOVE: 'kmov', _curses.KEY_NEXT: 'knxt', _curses.KEY_NPAGE: 'knp', _curses.KEY_OPEN: 'kopn', _curses.KEY_OPTIONS: 'kopt', _curses.KEY_PPAGE: 'kpp', _curses.KEY_PREVIOUS: 'kprv', _curses.KEY_PRINT: 'kprt', _curses.KEY_REDO: 'krdo', _curses.KEY_REFERENCE: 'kref', _curses.KEY_REFRESH: 'krfr', _curses.KEY_REPLACE: 'krpl', _curses.KEY_RESTART: 'krst', _curses.KEY_RESUME: 'kres', _curses.KEY_RIGHT: 'kcuf1', _curses.KEY_SAVE: 'ksav', _curses.KEY_SBEG: 'kBEG', _curses.KEY_SCANCEL: 'kCAN', _curses.KEY_SCOMMAND: 'kCMD', _curses.KEY_SCOPY: 'kCPY', _curses.KEY_SCREATE: 'kCRT', _curses.KEY_SDC: 'kDC', _curses.KEY_SDL: 'kDL', _curses.KEY_SELECT: 'kslt', _curses.KEY_SEND: 'kEND', _curses.KEY_SEOL: 'kEOL', _curses.KEY_SEXIT: 'kEXT', _curses.KEY_SF: 'kind', _curses.KEY_SFIND: 'kFND', _curses.KEY_SHELP: 'kHLP', _curses.KEY_SHOME: 'kHOM', _curses.KEY_SIC: 'kIC', _curses.KEY_SLEFT: 'kLFT', _curses.KEY_SMESSAGE: 'kMSG', _curses.KEY_SMOVE: 'kMOV', _curses.KEY_SNEXT: 'kNXT', _curses.KEY_SOPTIONS: 'kOPT', _curses.KEY_SPREVIOUS: 'kPRV', _curses.KEY_SPRINT: 'kPRT', _curses.KEY_SR: 'kri', _curses.KEY_SREDO: 'kRDO', _curses.KEY_SREPLACE: 'kRPL', _curses.KEY_SRIGHT: 'kRIT', _curses.KEY_SRSUME: 'kRES', _curses.KEY_SSAVE: 'kSAV', _curses.KEY_SSUSPEND: 'kSPD', _curses.KEY_STAB: 'khts', _curses.KEY_SUNDO: 'kUND', _curses.KEY_SUSPEND: 'kspd', _curses.KEY_UNDO: 'kund', _curses.KEY_UP: 'kcuu1'} def has_key(ch): if isinstance(ch, str): ch = ord(ch) capability_name = _capability_names.get(ch) if capability_name is None: return False elif _curses.tigetstr(capability_name): return True else: return False return if __name__ == '__main__': try: L = [] _curses.initscr() for key in _capability_names.keys(): system = key in _curses python = has_key(key) if system != python: L.append('Mismatch for key %s, system=%i, Python=%i' % (_curses.keyname(key), system, python)) finally: _curses.endwin() for i in L: print i # okay decompyling c:\Users\PC\wotsources\files\originals\res_bw\scripts\common\lib\curses\has_key.pyc # decompiled 1 files: 1 okay, 0 failed, 0 verify failed # 2015.11.10 21:35:00 Střední Evropa (běžný čas)

[ "info@webium.sk" ]

info@webium.sk

93758cce46271f9984e7c318b94f42934b31a49c

6c412b6f6c112b40e80587a17db537c4683d9dd0

/angle/predict.py

9a57c713468df723c5f4a5de33866fba64bfc78d

[]

no_license

laugha/Chinese-OCR-3

50df8904e654413b8816c78866e554579de85678

5bc9f201bacf95af38b4eadf471a231f6c93aa1b

refs/heads/master

2021-01-26T11:03:11.677400

2020-02-11T04:28:15

null

0

null

UTF-8

Python

false

2,066

py

#!/usr/bin/env python # -*- coding: utf-8 -*- # _Author_: xiaofeng # Date: 2018-04-22 18:13:46 # Last Modified by: xiaofeng # Last Modified time: 2018-04-22 18:13:46 ''' 根据给定的图形，分析文字的朝向 ''' # from keras.models import load_model import numpy as np from PIL import Image from keras.applications.vgg16 import preprocess_input, VGG16 from keras.layers import Dense from keras.models import Model # 编译模型，以较小的学习参数进行训练 from keras.optimizers import SGD def load(): vgg = VGG16(weights=None, input_shape=(224, 224, 3)) # 修改输出层 3个输出 x = vgg.layers[-2].output predictions_class = Dense( 4, activation='softmax', name='predictions_class')(x) prediction = [predictions_class] model = Model(inputs=vgg.input, outputs=prediction) sgd = SGD(lr=0.00001, momentum=0.9) model.compile( optimizer=sgd, loss='categorical_crossentropy', metrics=['accuracy']) model.load_weights( r'/home/rayjue/MyWayOnOCR/frist/chinese_ocr/angle/modelAngle.h5') return model # 加载模型 model = None def predict(path=None, img=None): global model if model is None: model = load() """ 图片文字方向预测 """ ROTATE = [0, 90, 180, 270] if path is not None: im = Image.open(path).convert('RGB') elif img is not None: im = Image.fromarray(img).convert('RGB') w, h = im.size # 对图像进行剪裁 # 左上角(int(0.1 * w), int(0.1 * h)) # 右下角(w - int(0.1 * w), h - int(0.1 * h)) xmin, ymin, xmax, ymax = int(0.1 * w), int( 0.1 * h), w - int(0.1 * w), h - int(0.1 * h) im = im.crop((xmin, ymin, xmax, ymax)) # 剪切图片边缘，清除边缘噪声 # 对图片进行剪裁之后进行resize成(224,224) im = im.resize((224, 224)) # 将图像转化成数组形式 img = np.array(im) img = preprocess_input(img.astype(np.float32)) pred = model.predict(np.array([img])) index = np.argmax(pred, axis=1)[0] return ROTATE[index]

[ "noreply@github.com" ]

laugha.noreply@github.com

0b6a1ba7dbe457aa088b69afbd6d89460cdb29b7

fbc756ec0ee27e0a262f3bcb30954c1f7e10b6cd

/eb-cli/lib/python2.7/site-packages/ebcli/controllers/console.py

581f8ecc714ad6aac1919cc8f32bb97f28a16f14

[ "Apache-2.0", "LicenseRef-scancode-unknown-license-reference" ]

permissive

workivate/step-elastic-beanstalk-deploy

a541e2521a77f049c7a03e6e391a73cc1c45c06f

5b0bcfac4e8557ce1dc84c0254e2264708da396c

refs/heads/master

2020-02-26T17:18:00.125354

2015-09-17T10:26:25

24,529,988

0

1

null

UTF-8

Python

false

1,138

py

# Copyright 2014 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). You # may not use this file except in compliance with the License. A copy of # the License is located at # # http://aws.amazon.com/apache2.0/ # # or in the "license" file accompanying this file. This file is # distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF # ANY KIND, either express or implied. See the License for the specific # language governing permissions and limitations under the License. from ..core.abstractcontroller import AbstractBaseController from ..resources.strings import strings from ..core import fileoperations, operations, io class ConsoleController(AbstractBaseController): class Meta: label = 'console' description = strings['console.info'] usage = AbstractBaseController.Meta.usage.replace('{cmd}', label) def do_command(self): app_name = self.get_app_name() region = self.get_region() env_name = self.get_env_name(noerror=True) operations.open_console(app_name, env_name, region)

[ "teengenerate@gmail.com" ]

teengenerate@gmail.com

32d77a5dfc12bcdd2213bbf1a7edc386cfbd04fa

3b74ecbc020ba5d5db436e248200cab14a0d13f4

/spider/spiders/OLD/spiderGenerico.py

3ddccf28cd18f83a6247f7b8f5c3c51e3ffbad06

[]

no_license

paologastaldi/spider

ec37577435c6138f60c2514ee36429bfcf6b4bae

eae624dd7ad56646d51458b274aada91dd537390

refs/heads/master

2021-01-21T13:34:03.270087

2016-05-14T08:43:48

55,077,930

1

null

2016-05-14T08:43:49

2016-03-30T16:12:46

HTML

UTF-8

Python

false

788

py

import scrapy from scrapy.selector import Selector from spider.items import ElementoDaEsaminare class DmozSpider(scrapy.Spider): name = "" allowed_domains = [] start_urls = [] def __init__(self, name, allowed_domains, start_urls): self.name = name self.allowed_domains = allowed_domains self.start_urls = start_urls def parse(self, response): analizzatorePagina = Selector(response) elencoPagineSito = analizzatorePagina.xpath('//body') elencoElementiDaEsaminare = [] for paginaSito in elencoPagineSito elementoDaEsaminare = ElementoDaEsaminare() pagineSito = site.xpath('text()').extract() elencoElementiDaEsaminare.append(elementoDaEsaminare) return elencoElementiDaEsaminare

[ "paolo97.g@gmail.com" ]

paolo97.g@gmail.com

f2fdb6bcb053fac10b934794a703af5abc5ba306

30acccad28c4e353ab6e38eef209c1752c18719f

/lambda_functions.py

de83ae4d75cc08575013cae4b816330fb8652eec

[]

no_license

phumidea/dropbox_app_mockup

ede58674f176b635a873641c08b54edadba1bdda

1395a33032926df0cb95a80f79831cd0f3ec41d8

refs/heads/main

2023-04-06T13:35:34.748967

2021-04-02T10:32:09

353,984,692

0

null

UTF-8

Python

false

6,029

py

import json import boto3 from datetime import datetime, timedelta BUCKET_NAME = "phum2021" # Bucket name keep user data s3 = boto3.client('s3') # Connect with S3 dynamodb = boto3.resource('dynamodb') # Connect with DynamoDB table = dynamodb.Table('myDropboxUsers') # Connect table def lambda_handler(event, context): command = str(event["queryStringParameters"]["command"]) # Classify what request want from command parameter ############################################################################################# if command == "newuser": # Create new user username = str(event["queryStringParameters"]["username"]) # Get username from request password = str(event["queryStringParameters"]["password"]) # Get password from request try: response = table.get_item(Key={'username': username})["Item"] return { 'statusCode': 200, 'body': json.dumps("This username alredy existing.") } except: response = table.put_item(Item = {'username':username,'password':password}) return { 'statusCode': 200, 'body': json.dumps("Create newuser finish.") } ############################################################################################# elif command == "login": # Login to the application username = str(event["queryStringParameters"]["username"]) # Get username from request password = str(event["queryStringParameters"]["password"]) # Get password from request try: response = table.get_item(Key={'username': username})["Item"] if (response["username"] == username) and (response["password"] == password): return { 'statusCode': 200, 'body': json.dumps("Login successfull") } else: return { 'statusCode': 200, 'body': json.dumps("Wrong password! Please try again") } except: return { 'statusCode': 200, 'body': json.dumps("No username in database.") } ############################################################################################# elif command == "put": # Upload file to S3 fileName = str(event["queryStringParameters"]["fileName"]) # Get filename from request content = str(event["queryStringParameters"]["content"]) # Get file content from request path = "/tmp/" + fileName # Prepare path to save new file with open(path, 'w+') as file: # Write content in new file file.write(content) s3.upload_file(path, BUCKET_NAME, fileName) # Upload file to S3 return { 'statusCode': 200, 'body': json.dumps("Put finish") } ############################################################################################# elif command == "view": # List all file in bucket username = str(event["queryStringParameters"]["username"]) all_file = [] # Create empty list for containing object information for obj in s3.list_objects(Bucket=BUCKET_NAME)["Contents"]: # Check loop for each object in bucket key = str(obj["Key"]) key_list = key.split("+") if username in key_list[1:]: file = dict() file["Key"] = key_list[0] file["LastModified"] = (obj["LastModified"] + timedelta(hours=7)).strftime("%Y-%m-%d %H:%M:%S") file["Size"] = obj["Size"] all_file.append(file) return { 'statusCode': 200, 'body': json.dumps(all_file) } ############################################################################################# elif command == "get": # Download file from S3 fileName = str(event["queryStringParameters"]["fileName"]) # get file name from request username = str(event["queryStringParameters"]["username"]) for obj in s3.list_objects(Bucket=BUCKET_NAME)["Contents"]: # check each object key_str = str(obj["Key"]) key_list = key_str.split("+") if (key_list[0] == fileName) and (username in key_list[1:]): # Match obj with file name path = "/tmp/"+key_str # create tmp path s3.download_file(BUCKET_NAME, key_str, path) # dwonload file from s3 file = open(path,"r") # open and read content inside content = file.read() return { 'statusCode': 200, 'body': content } return { 'statusCode': 200, 'body': json.dumps("Type wrong filename") } ############################################################################################# elif command == "share": fileName = str(event["queryStringParameters"]["fileName"]) # get file name from request username = str(event["queryStringParameters"]["username"]) share_user = str(event["queryStringParameters"]["share_user"]) for obj in s3.list_objects(Bucket=BUCKET_NAME)["Contents"]: key = str(obj["Key"]) key_list = key.split("+") if (key_list[0] == fileName) and (key_list[1] == username): copy_source = {"Bucket":BUCKET_NAME, "Key":key} s3.copy(copy_source,BUCKET_NAME,key+"+"+share_user) s3.delete_object(Bucket=BUCKET_NAME, Key=key) return { 'statusCode': 200, 'body': "Finish" } ############################################################################################# else: return { 'statusCode': 500, 'body': json.dumps("AWS Service broken") }

[ "noreply@github.com" ]

phumidea.noreply@github.com

26a12bd802e8a93364e938b58d788e87da974974

5d095521eb9a4e3a58c98938775da390b988098e

/Python/BatterUp.py

54369fef4c202b26c5a31429b0750a7430bf7421

[]

no_license

houstonwalley/Kattis

c50932ccba12f7a7777c01caff1383d11d90d698

c825e5f612f2c9f11de1fad610f6b830a4be45af

refs/heads/master

2021-07-21T10:38:11.580292

2020-09-01T19:37:38

210,641,358

0

null

2020-04-28T03:34:39

2019-09-24T15:51:00

Python

UTF-8

Python

false

115

py

n = int(input()) s = map(int, input().split()) v = [] for m in s: if m >= 0: v.append(m) print(sum(v)/len(v))

[ "noreply@github.com" ]

houstonwalley.noreply@github.com

6861c429f30b05eaab663c0de04d4e13e8a6785c

a7bf172fc3ece3fd103a4d295c0c68636a99236f

/vDictEspn.py

670d05a708a30373c64bc4a0487d3366efe8aeb7

[]

no_license

thedaynos/fantasyDraftHighlights

e781e098bf63bed31f28a2ce911bb0208c82b3d8

3cf0b3e63896183bbf03ea7cbcaff16ccf161024

refs/heads/master

2023-06-07T11:52:06.066918

2021-07-20T22:25:45

197,640,436

21

7

null

2023-05-30T18:58:19

2019-07-18T18:49:11

Python

UTF-8

Python

false

17,396

py

vDictEspn={ "RBNYGSaquonBarkley":"", "RBDalEzekielElliott":"", "RBCarChristianMcCaffrey":"", "RBNOAlvinKamara":"", "RBNYJLeVeonBell":"", "WRHouDeAndreHopkins":"", "RBLARToddGurleyII":"", "WRGBDavanteAdams":"", "RBLACMelvinGordon":"", "WRNOMichaelThomas":"", "WRAtlJulioJones":"", "RBAriDavidJohnson":"", "TEKCTravisKelce":"", "WRKCTyreekHill":"", "WRCleOdellBeckhamJr":"", "RBPitJamesConner":"", "WROakAntonioBrown":"", "QBKCPatrickMahomes":"", "WRPitJuJuSmithSchuster":"", "RBCinJoeMixon":"", "WRLACKeenanAllen":"", "RBMinDalvinCook":"", "WRTBMikeEvans":"", "RBJaxLeonardFournette":"", "TEPhiZachErtz":"", "TESFGeorgeKittle":"", "WRIndTYHilton":"", "WRDalAmariCooper":"", "RBCleNickChubb":"", "WRMinAdamThielen":"", "RBAtlDevontaFreeman":"", "WRNEJulianEdelman":"", "RBTenDerrickHenry":"", "WRLARBrandinCooks":"", "RBOakJoshJacobs":"", "WRMinStefonDiggs":"", "WRCinAJGreen":"", "QBHouDeshaunWatson":"", "RBIndMarlonMack":"", "RBDetKerryonJohnson":"", "QBGBAaronRodgers":"", "RBGBAaronJones":"", "RBKCDamienWilliams":"", "WRLARRobertWoods":"", "TENYGEvanEngram":"", "RBNESonyMichel":"", "RBDenPhillipLindsay":"", "WRLARCooperKupp":"", "WRPhiAlshonJeffery":"", "RBNEJamesWhite":"", "WRDetKennyGolladay":"", "RBBalMarkIngramII":"", "QBIndAndrewLuck":"", "RBSeaChrisCarson":"", "DSTChiBearsDST":"M3_q67ABSSw", "QBAtlMattRyan":"", "WRSeaTylerLockett":"", "TETBOJHoward":"", "QBCleBakerMayfield":"", "WRCleJarvisLandry":"", "TELACHunterHenry":"", "WRTBChrisGodwin":"", "WRAtlCalvinRidley":"", "WRCinTylerBoyd":"", "WRKCSammyWatkins":"", "TENOJaredCook":"", "QBNODrewBrees":"", "WRCarDJMoore":"", "RBMiaKenyanDrake":"", "RBChiTarikCohen":"", "RBChiDavidMontgomery":"", "WRLACMikeWilliams":"", "RBWshDerriusGuice":"", "WRChiAllenRobinson":"", "QBCarCamNewton":"", "DSTLARRamsDST":"2QujiGePXUk", "RBHouLamarMiller":"", "KLARGregZuerlein":"", "WRNYJRobbyAnderson":"", "RBSFTevinColeman":"", "TEIndEricEbron":"", "RBPhiMilesSanders":"", "QBPhiCarsonWentz":"", "WRHouWillFullerV":"", "WRNYGSterlingShepard":"", "TECleDavidNjoku":"", "RBBufLeSeanMcCoy":"", "WRDetMarvinJonesJr":"", "DSTJaxJaguarsDST":"ozYX_neURXs", "KBalJustinTucker":"", "WRJaxDedeWestbrook":"", "WRAriChristianKirk":"", "TETenDelanieWalker":"", "TEPitVanceMcDonald":"", "DSTBufBillsDST":"yIarX0CYrec", "RBLACAustinEkeler":"", "WRSFDantePettis":"", "WRAriLarryFitzgerald":"", "QBSeaRussellWilson":"", "QBNETomBrady":"", "RBPhiJordanHoward":"", "QBPitBenRoethlisberger":"", "RBNOLataviusMurray":"", "WRTenCoreyDavis":"", "RBLARDarrellHenderson":"", "QBDalDakPrescott":"", "KKCHarrisonButker":"", "WRNYGGoldenTate":"", "QBAriKylerMurray":"", "RBSeaRashaadPenny":"", "DSTMinVikingsDST":"CeT1zNWs5k", "QBLARJaredGoff":"", "KNEStephenGostkowski":"", "DSTNOSaintsDST":"DMz24zixNMQ", "WRNENKealHarry":"", "KNOWilLutz":"", "RBTBPeytonBarber":"", "RBIndNyheimHines":"", "WRDenEmmanuelSanders":"", "WRPhiDeSeanJackson":"", "DSTLACChargersDST":"jmhi-gUoRwI", "WRDenCourtlandSutton":"", "KHouKaimiFairbairn":"", "RBTBRonaldJones":"", "RBSFJerickMcKinnon":"", "WRHouKekeCoutee":"", "TEChiTreyBurton":"", "RBCleKareemHunt":"", "WRCarCurtisSamuel":"", "DSTNEPatriotsDST":"Mj7AfBA6VZQ", "TECarGregOlsen":"", "WRDalMichaelGallup":"", "KSFRobbieGould":"", "WRPitDonteMoncrief":"", "WRGBGeronimoAllison":"", "TEAtlAustinHooper":"", "RBHouDOntaForeman":"", "RBDenRoyceFreeman":"", "WRSeaDKMetcalf":"", "RBKCCarlosHyde":"", "DSTIndColtsDST":"k3-H03xkRX4", "QBLACPhilipRivers":"", "QBChiMitchellTrubisky":"", "RBSFMattBreida":"", "TEMinKyleRudolph":"", "DSTDenBroncosDST":"YmOKim16x4s", "KLACMikeBadgley":"", "KIndAdamVinatieri":"", "TEGBJimmyGraham":"", "WRPitJamesWashington":"", "DSTHouTexansDST":"mWWB8Y1gDx8", "DSTPhiEaglesDST":"4PRndm6u38M", "WROakTyrellWilliams":"", "DSTCleBrownsDST":"W2pGqDeNYu4", "WRGBMarquezValdesScantling":"", "QBBalLamarJackson":"", "WRIndDevinFunchess":"", "RBNEDamienHarris":"", "TEIndJackDoyle":"", "KDalBrettMaher":"", "DSTBalRavensDST":"hb6EV_FnFwE", "TEWshJordanReed":"", "WRBalMarquiseBrown":"", "WRDenDaeSeanHamilton":"", "QBTBJameisWinston":"", "DSTDalCowboysDST":"OnOTXPmaFl8", "RBTenDionLewis":"", "WRNYJJamisonCrowder":"", "RBMiaKalenBallage":"", "QBMinKirkCousins":"", "TEDetTJHockenson":"", "RBWshAdrianPeterson":"", "WRTenAdamHumphries":"", "WRIndParrisCampbell":"", "KPhiJakeElliott":"", "QBSFJimmyGaroppolo":"", "WRChiAnthonyMiller":"", "DSTPitSteelersDST":"s2MJWK5zxv4", "WRAtlMohamedSanu":"", "KDetMattPrater":"", "TEDenNoahFant":"", "DSTKCChiefsDST":"NotMr7-z6tQ", "WRMiaKennyStills":"", "TEDalJasonWitten":"", "KGBMasonCrosby":"", "DSTTenTitansDST":"57cjzFe9qhM", "RBDetCJAnderson":"", "RBPitJaylenSamuels":"", "QBOakDerekCarr":"", "QBBufJoshAllen":"", "KNYGAldrickRosas":"", "WRDalRandallCobb":"", "RBOakJalenRichard":"", "TEBalMarkAndrews":"", "QBNYJSamDarnold":"", "DSTCarPanthersDST":"tfAA7MJvXYU", "QBDetMatthewStafford":"", "RBGBJamaalWilliams":"", "WRKCMecoleHardman":"", "QBJaxNickFoles":"", "RBAtlItoSmith":"", "RBCleDukeJohnsonJr":"", "QBWshDwayneHaskins":"", "TECinTylerEifert":"", "DSTNYJJetsDST":"1PdNL8Br3uM", "DSTGBPackersDST":"BJ-7mCLfZBQ", "TENERobGronkowski":"", "RBCinGiovaniBernard":"", "DSTSeaSeahawksDST":"BfwnvukHwBM", "RBBufDevinSingletary":"", "WRNOTedGinnJr":"", "WRMiaAlbertWilson":"", "RBWshChrisThompson":"", "DSTSFersDST":"Glh2C1nUkP0", "KCarGrahamGano":"", "KMinDanBailey":"", "KSeaJasonMyers":"", "RBLACJustinJackson":"", "DSTDetLionsDST":"L35Exibkvfg", "KPitChrisBoswell":"", "TEPhiDallasGoedert":"", "TENYJChrisHerndon":"", "DSTAtlFalconsDST":"Fr7PdwOzgn8", "RBMinAlexanderMattison":"", "QBTenMarcusMariota":"", "DSTOakRaidersDST":"jnsv58g-lRQ", "WRSFDeeboSamuel":"", "WRNEDemaryiusThomas":"", "TENEBenjaminWatson":"", "DSTWshRedskinsDST":"AjtdTXK8_EA", "WRTenAJBrown":"", "WRBufColeBeasley":"", "RBPitBennySnellJr":"", "TEMiaMikeGesicki":"", "QBNYGEliManning":"", "WRAriAndyIsabella":"", "QBOakNathanPeterman":"", "WRNEJoshGordon":"", "WRSFMarquiseGoodwin":"", "KTenRyanSuccop":"", "DSTNYGGiantsDST":"axSSb-HoT8Y", "WRBufJohnBrown":"", "KCleAustinSeibert":"", "KAtlGiorgioTavecchio":"", "WRPhiNelsonAgholor":"", "KDenBrandonMcManus":"", "QBDenJoeFlacco":"", "RBDalTonyPollard":"", "RBKCDarwinThompson":"", "WRNOTreQuanSmith":"", "KWshDustinHopkins":"", "WRCleAntonioCallaway":"", "KBufStephenHauschka":"", "WRTBAnthonyJohnson":"", "QBNYGDanielJones":"", "KTBMattGay":"", "RBPhiDarrenSproles":"", "DSTAriCardinalsDST":"cY4Os6h2p1k", "TEMinIrvSmithJr":"", "KLACNickNovak":"", "RBBufFrankGore":"", "DSTTBBuccaneersDST":"6Qvo_yVtIE8", "KSeaSebastianJanikowski":"", "RBOakMarshawnLynch":"", "KAtlMattBryant":"", "KChiCodyParkey":"", "RBDalAlfredMorris":"", "RBNERexBurkhead":"", "DSTMiaDolphinsDST":"59y91tJ-XfA", "KJaxJoshLambo":"", "QBWshMarkSanchez":"", "QBFAJayCutler":"", "QBNOTaysomHill":"", "TESeaWillDissly":"", "KLACYounghoeKoo":"", "QBAriSamBradford":"", "RBBalGusEdwards":"", "WRChiTaylorGabriel":"", "TEOakDarrenWaller":"", "WRNOLilJordanHumphrey":"", "KChiEddyPineiro":"", "RBPhiJayAjayi":"", "WRNODezBryant":"", "KOakMikeNugent":"", "WRNOBrandonMarshall":"", "TENYGCJConrad":"", "TELACAntonioGates":"", "RBBalJusticeHill":"", "RBKCCJSpiller":"", "WRChiRileyRidley":"", "KAriZaneGonzalez":"", "WRDetDannyAmendola":"", "KOakDanielCarlson":"", "QBCinAndyDalton":"", "WROakJordyNelson":"", "WRMiaDeVanteParker":"", "TEDenJakeButt":"", "KSeaBlairWalsh":"", "WRSeaDougBaldwin":"", "KMiaJasonSanders":"", "WRCleRashardHiggins":"", "WRCinJohnRoss":"", "QBBalRobertGriffinIII":"", "WRDalTavonAustin":"", "WRBalMichaelCrabtree":"", "RBNEGlennGronkowski":"", "RBBufTJYeldon":"", "RBOakIsaiahCrowell":"", "DSTCinBengalsDST":"aSpB5PkgcyQ", "WRCarChrisHogan":"", "QBLACKellenClemens":"", "RBKCAkeemHunt":"", "WRAriHakeemButler":"", "KChiConnorBarth":"", "WRChiCordarrellePatterson":"", "TEMiaAnthonyFasano":"", "QBFACarsonPalmer":"", "TENOJoshHill":"", "TECleDemetriusHarris":"", "TEFAMartellusBennett":"", "RBDetLeGarretteBlount":"", "RBChiMikeDavis":"", "KNYJChandlerCatanzaro":"", "RBKCDarrelWilliams":"", "QBMiaRyanFitzpatrick":"", "TEChiZachMiller":"", "RBNOJohnKuhn":"", "KCinRandyBullock":"", "WRNOBrandonTate":"", "TENEMattLaCosse":"", "WRPitRyanSwitzer":"", "RBMinCJHam":"", "TEDetJesseJames":"", "RBNEJamesDevelin":"", "KTBNickFolk":"", "WRPhiJJArcegaWhiteside":"", "WRMinChadBeebe":"", "RBKCTremonSmith":"", "TEKCBlakeBell":"", "RBDetTyJohnson":"", "WRBufZayJones":"", "WROakJJNelson":"", "TEDalBlakeJarwin":"", "RBDalMikeWeber":"", "TENOMichaelHoomanawanui":"", "KClePhilDawson":"", "RBFAMattForte":"", "RBKCAnthonySherman":"", "WRKCKelvinBenjamin":"", "RBDetZachZenner":"", "KLACTravisCoons":"", "KCleGregJoseph":"", "KTBCairoSantos":"", "TELARGeraldEverett":"", "QBPitJoshuaDobbs":"", "WROakHunterRenfrow":"", "RBDalDariusJackson":"", "QBNEJarrettStidham":"", "TEKCNealSterling":"", "WRJaxTyreBrady":"", "TENODanArnold":"", "WRSFLouisMurphy":"", "WRKCDemarcusRobinson":"", "RBLACDerekWatt":"", "WRPhiMikeWallace":"", "TENELanceKendricks":"", "WRNEBraxtonBerrios":"", "KGBSamFicken":"", "WROakBrandonLaFell":"", "WRDalNoahBrown":"", "WRPitDiontaeJohnson":"", "WRLARMikeThomas":"", "QBLACTyrodTaylor":"", "WRNOKeithKirkwood":"", "KLACRobertoAguayo":"", "RBPhiWendellSmallwood":"", "WRFAKennyBritt":"", "QBLARBlakeBortles":"", "TEAriRickySealsJones":"", "WRKCGehrigDieter":"", "QBChiChaseDaniel":"", "WRGBJakeKumerow":"", "RBTenAkrumWadley":"", "RBKCAlgernonBrown":"", "QBJaxGardnerMinshew":"", "RBAtlRickyOrtiz":"", "QBGBTimBoyle":"", "TEPitXavierGrimble":"", "RBCleDontrellHilliard":"", "RBTenChrisJohnson":"", "QBHouBrandonWeeden":"", "WRSFMaxMcCaffrey":"", "TEFACobyFleener":"", "RBFADeMarcoMurray":"", "WRIndMarcusJohnson":"", "TEGBJaceSternberger":"", "WRNYGRussellShepard":"", "WRPhiCarltonAgudosi":"", "TELACVirgilGreen":"", "WRNOAustinCarr":"", "WRHouDeAndreCarter":"", "RBMinAmeerAbdullah":"", "WRMinLaquonTreadwell":"", "WRNEDontrelleInman":"", "RBHouJoshFerguson":"", "WRAriKevinWhite":"", "WRCinJoshMalone":"", "WRBalMilesBoykin":"", "WRAtlJustinHardy":"", "TELARTylerHigbee":"", "WRAtlRussellGage":"", "QBMiaBrockOsweiler":"", "QBFATJYates":"", "QBTBRyanGriffin":"", "RBPitRooseveltNix":"", "RBBufSamRogers":"", "TEAtlLoganPaulsen":"", "RBSFJoeWilliams":"", "RBFAEddieLacy":"", "WRChiMarvinHall":"", "WRTenHarryDouglas":"", "QBKCChadHenne":"", "RBJaxTommyBohanon":"", "TENYGRhettEllison":"", "KTBPatrickMurray":"", "RBAriTJLogan":"", "KJaxKaiForbath":"", "TETenJonnuSmith":"", "WRDenRiverCracraft":"", "WRBufAndreRoberts":"", "TEHouJordanAkins":"", "QBLACCardaleJones":"", "TESeaEdDickson":"", "WRCleDamionRatley":"", "RBNYGPaulPerkins":"", "WRDenAaronBurbridge":"", "WRKCMarcusKemp":"", "WRTenJalenTolliver":"", "RBBufMikeTolbert":"", "KLACNickRose":"", "RBCarElijahHood":"", "WRNORishardMatthews":"", "TESeaTyroneSwoopes":"", "RBNODevineOzigbo":"", "RBNYGRodSmith":"", "QBPhiCodyKessler":"", "RBNYGJonathanStewart":"", "WRBufRayRayMcCloudIII":"", "RBChiFreddieStevenson":"", "RBPhiMattJones":"", "TEChiAdamShaheen":"", "RBGBDonJackson":"", "QBPitMasonRudolph":"", "WRWshRobertDavis":"", "RBSFKyleJuszczyk":"", "RBHouBuddyHowell":"", "WRFAEricDecker":"", "RBPitStevanRidley":"", "QBDetTomSavage":"", "RBDenKhalfaniMuhammad":"", "WRMinBrandonZylstra":"", "RBJaxJamaalCharles":"", "WRCarTorreySmith":"", "TECinCJUzomah":"", "KMiaAndrewFranks":"", "QBSeaPaxtonLynch":"", "QBDalMikeWhite":"", "TENOAlizeMack":"", "WRKCByronPringle":"", "WRNEMatthewSlater":"", "QBCleGarrettGilbert":"", "QBNYJTrevorSiemian":"", "WRWshCamSims":"", "WRPitDarriusHeywardBey":"", "TEJaxJamesOShaughnessy":"", "QBWshJoshJohnson":"", "QBNYJJoshMcCown":"", "QBSeaGenoSmith":"", "QBBufMattBarkley":"", "QBWshAlexSmith":"", "RBFADannyWoodhead":"", "WRDetChrisLacy":"", "RBCinTrayveonWilliams":"", "WRWshJehuChesson":"", "TEMiaNickOLeary":"", "RBHouTaiwanJones":"", "KLACCalebSturgis":"", "RBFAOrleansDarkwa":"", "WRMinJordanTaylor":"", "TEPhiBrentCelek":"", "RBNOZachLine":"", "QBSFCJBeathard":"", "WRMiaIsaiahFord":"", "RBNYGShaneSmith":"", "RBAriDJFoster":"", "TEDalDaltonSchultz":"", "TEMiaDwayneAllen":"", "TEWshVernonDavis":"", "TENEStephenAnderson":"", "TEPitZachGentry":"", "WRFAJeremyMaclin":"", "WRSeaAmaraDarboh":"", "WRDetJaceBillingsley":"", "QBSeaTrevoneBoykin":"", "QBAtlMattSchaub":"", "WRHouVyncintSmith":"", "QBCinJeffDriskel":"", "TEBufTylerKroft":"", "WRLACDylanCantrell":"", "QBChiTylerBray":"", "TEBufLeeSmith":"", "WRLARJoJoNatson":"", "TESeaNickVannett":"", "QBMiaJakeRudock":"", "WRPhiCharlesJohnson":"", "RBPhiJoshAdams":"", "WRSeaMalikTurner":"", "WRSFPierreGarcon":"", "WRMiaAllenHurns":"", "WRHouJoeWebbIII":"", "WRTenCameronBatson":"", "RBCarAlexArmah":"", "QBHouAJMcCarron":"", "RBNEBrandonBolden":"", "QBCleDrewStanton":"", "TEMinColeHikutini":"", "WRNEMauriceHarris":"", "WRChiJavonWims":"", "WRDalDevinSmith":"", "WRAriKeeSeanJohnson":"", "WRBalQuincyAdeboyejo":"", "WRDalCedrickWilson":"", "RBDenAndyJanovich":"", "QBLARBrandonAllen":"", "QBMiaJoshRosen":"", "TEMinDavidMorgan":"", "WRKCSammieCoatesJr":"", "RBSeaBoScarbrough":"", "RBCarDevonJohnson":"", "WRNYJQuadreeHenderson":"", "TENYJTrevonWesco":"", "RBJaxThomasRawls":"", "QBNOTeddyBridgewater":"", "WRDenBrendanLangley":"", "TESFLevineToilolo":"", "RBKCAaronRipkowski":"", "TENYGGarrettDickerson":"", "WRNYJQuincyEnunwa":"", "RBNYJTyMontgomery":"", "WRCinAudenTate":"", "QBSFNickMullens":"", "TENERyanIzzo":"", "QBTBNickFitzgerald":"", "WRNEDannyEtling":"", "WRLARMarquezNorth":"", "TETenPhillipSupernaw":"", "TELACJeffCumberland":"", "WRSeaDamoreeaStringfellow":"", "RBPhiDonnelPumphrey":"", "TEMinTylerConklin":"", "TEGBMarcedesLewis":"", "WRNECameronMeredith":"", "TELARHenryKriegerCoble":"", "WRCinAlexErickson":"", "WROakDwayneHarris":"", "RBDenDavidWilliams":"", "TEWshJeremySprinkle":"", "TEDenJeffHeuerman":"", "TELACBraedonBowman":"", "WRNYJLuckyWhitehead":"", "RBSeaCJProsise":"", "TEKCAlexEllis":"", "TENYGScottSimonson":"", "RBAtlJeremyLangford":"", "KChiChrisBlewitt":"", "RBGBDannyVitale":"", "WRPitJohnnyHolton":"", "RBChiKerrithWhyteJr":"", "WRPhiMackHollins":"", "WRIndDauriceFountain":"", "TECleSethDeValve":"", "RBCleKelvinTaylor":"", "WRCarKeyarrisGarrett":"", "WRChiTannerGentry":"", "WRTBBoboWilson":"", "WRSFJalenHurd":"", "WRAriDamiereByrd":"", "TELACAustinRoberts":"", "QBPhiChristianHackenberg":"", "QBLACEastonStick":"", "QBFAMattMoore":"", "TEAriIfeanyiMomah":"", "WRIndZachPascal":"", "WRGBJawillDavis":"", "TENYJEricTomlinson":"", "TEJaxDonnieErnsberger":"", "RBCinQuintonFlowers":"", "TEOakDerekCarrier":"", "TEAtlEricSaubert":"", "TECinDrewSample":"", }

[ "noreply@github.com" ]

thedaynos.noreply@github.com

8939b092b0f7a5321485af541808b9e5b0c6e4e9

30f88ef95fc374335574835342f84b75a722d0b5

/tools/vcoco/train_net_pd.py

dbc8fffa66de8933c3229e661372dd1bb971c82e

[]

no_license

MuchHair/PD-Net-Extended-Version

8f4c1a69d97e1d95167555dcf1af638aad3f8c14

84814817efdd0700570ddcdbbddbb25cdefbb8c6

refs/heads/master

2023-04-22T05:30:48.832382

2021-04-25T12:27:48

292,491,878

10

0

null

UTF-8

Python

false

7,131

py

import sys sys.path.insert(0, "lib") from dataset.dataset import Features_PD_VCOCO from net.model import PD_Net import os import itertools import numpy as np import torch import torch.nn as nn from tqdm import tqdm tqdm.monitor_interval = 0 import torch.optim as optim from torch.autograd import Variable from tensorboard_logger import configure, log_value from torch.utils.data.sampler import RandomSampler import utils.io as io def train_model(model, dataset_train, dataset_val, lr, num_epochs, model_dir, exp_name, parm_need_train=None): if parm_need_train is None: params = itertools.chain( model.parameters()) optimizer = optim.Adam(params, lr=lr) else: optimizer = optim.Adam(parm_need_train, lr=lr) criterion = nn.BCELoss() model.train() step = 0 optimizer.zero_grad() for epoch in range(0, num_epochs): sampler = RandomSampler(dataset_train) for i, sample_id in enumerate(sampler): data = dataset_train[sample_id] feats = { 'human_feats': Variable(torch.cuda.FloatTensor(data['human_feat'])), 'object_feats': Variable(torch.cuda.FloatTensor(data['object_feat'])), 'union_feats': Variable(torch.cuda.FloatTensor(data['union_features'])), 'box': Variable(torch.cuda.FloatTensor(data['box_feat'])), 'absolute_pose': Variable(torch.cuda.FloatTensor(data['absolute_pose'])), 'relative_pose': Variable(torch.cuda.FloatTensor(data['relative_pose'])), 'human_prob_vec': Variable(torch.cuda.FloatTensor(data['human_prob_vec'])), 'object_prob_vec': Variable(torch.cuda.FloatTensor(data['object_prob_vec'])), 'object_one_hot': Variable(torch.cuda.FloatTensor(data['object_one_hot'])), 'prob_mask': Variable(torch.cuda.FloatTensor(data['prob_mask'])), "human_prob": Variable(torch.cuda.FloatTensor(data['human_prob'])), "object_prob": Variable(torch.cuda.FloatTensor(data['object_prob'])), "verb_object_vec": Variable(torch.cuda.FloatTensor(data["verb_obj_vec"])), "hoi_label": Variable(torch.cuda.FloatTensor(data['hoi_label'])) } verb_scores, hoi_scores = model(feats) hoi_labels = Variable(torch.cuda.FloatTensor(data['hoi_label_vec'])) loss1 = criterion(verb_scores, hoi_labels) loss2 = criterion(hoi_scores, hoi_labels) loss = loss1 + loss2 loss.backward() if step % 1 == 0: optimizer.step() optimizer.zero_grad() max_prob = hoi_scores.max().data[0] max_prob_tp = torch.max(hoi_scores * hoi_labels).data[0] if step % 20 == 0 and step != 0: num_tp = np.sum(data['hoi_label']) num_fp = data['hoi_label'].shape[0] - num_tp log_str = \ 'Epoch: {} | Iter: {} | Step: {} | ' + \ 'Train Loss: {:.8f} | TPs: {} | FPs: {} | ' + \ 'Max TP Prob: {:.8f} | Max Prob: {:.8f} | lr:{}' log_str = log_str.format( epoch, i, step, loss.data[0], num_tp, num_fp, max_prob_tp, max_prob, optimizer.param_groups[0]["lr"]) print(log_str) if step % 100 == 0: log_value('train_loss', loss.data[0], step) log_value('max_prob', max_prob, step) log_value('max_prob_tp', max_prob_tp, step) print(exp_name) if step % 1000 == 0 and step > 9000: val_loss, val_loss_1, val_loss_2 = eval_model(model, dataset_val) log_value('val_loss', val_loss, step) log_value('val_loss_1', val_loss_1, step) log_value('val_loss_2', val_loss_2, step) print(exp_name) if step == 10 or (step % 1000 == 0 and step > 9000): hoi_classifier_pth = os.path.join( model_dir, "model", f'hoi_classifier_{step}') torch.save( model.state_dict(), hoi_classifier_pth) step += 1 def eval_model(model, dataset): model.eval() criterion = nn.BCELoss() step = 0 val_loss = 0 val_loss1 = 0 val_loss2 = 0 count = 0 sampler = RandomSampler(dataset) torch.manual_seed(0) for sample_id in tqdm(sampler): data = dataset[sample_id] feats = { 'human_feats': Variable(torch.cuda.FloatTensor(data['human_feat'])), 'union_feats': Variable(torch.cuda.FloatTensor(data['union_features'])), 'object_feats': Variable(torch.cuda.FloatTensor(data['object_feat'])), 'box': Variable(torch.cuda.FloatTensor(data['box_feat'])), 'absolute_pose': Variable(torch.cuda.FloatTensor(data['absolute_pose'])), 'relative_pose': Variable(torch.cuda.FloatTensor(data['relative_pose'])), 'human_prob_vec': Variable(torch.cuda.FloatTensor(data['human_prob_vec'])), 'object_prob_vec': Variable(torch.cuda.FloatTensor(data['object_prob_vec'])), 'object_one_hot': Variable(torch.cuda.FloatTensor(data['object_one_hot'])), 'prob_mask': Variable(torch.cuda.FloatTensor(data['prob_mask'])), "human_prob": Variable(torch.cuda.FloatTensor(data['human_prob'])), "object_prob": Variable(torch.cuda.FloatTensor(data['object_prob'])), "verb_object_vec": Variable(torch.cuda.FloatTensor(data["verb_obj_vec"])), } verb_scores, hoi_scores = model(feats) hoi_labels = Variable(torch.cuda.FloatTensor(data['hoi_label_vec'])) loss1 = criterion(verb_scores, hoi_labels) loss2 = criterion(hoi_scores, hoi_labels) loss = loss1 + loss2 batch_size = verb_scores.size(0) val_loss1 += (batch_size * loss1.data[0]) val_loss2 += (batch_size * loss2.data[0]) val_loss += (batch_size * loss.data[0]) count += batch_size step += 1 val_loss = val_loss / float(count) val_loss1 = val_loss1 / float(count) val_loss2 = val_loss2 / float(count) return val_loss, val_loss1, val_loss2 def main_PD_net(): model = PD_Net(True, 4).cuda() lr = 1e-4 num_epochs = 10 model_dir = "output/vcoco/PD" io.mkdir_if_not_exists(model_dir, recursive=True) io.mkdir_if_not_exists(os.path.join(model_dir, "log")) io.mkdir_if_not_exists(os.path.join(model_dir, "model")) configure(os.path.join(model_dir, "log")) dataset_train = Features_PD_VCOCO(subset="trainval", fp_to_tp_ratio=1000) dataset_val = Features_PD_VCOCO(subset="test") print(model) train_model(model, dataset_train, dataset_val, lr, num_epochs, model_dir, model_dir) if __name__ == "__main__": main_PD_net()

[ "eexubin@mail.scut.edu.cn" ]

eexubin@mail.scut.edu.cn

69ad3dd86512c379e348acbd6e38a601c72bb95e

3da29484b8d6d598c75dc5446be89c96c8209e3e

/data/BK_MC_2012_27163003_Beam4000GeV-2012-MagDown-Nu2.5-Pythia8_Sim08a_Digi13_Trig0x409f0045_Reco14a_Stripping20NoPrescalingFlagged_ALLSTREAMS.DST.py

f2e099a204b7805f9a7737402bc9f7313e7a5e16

[]

no_license

betatim/glowing-wookie

71560dd14cd23466e629dadc6de270c04d848016

fb327714cd066c7c58864d6aec8424271d147f06

refs/heads/master

2016-09-05T19:39:30.174535

2014-08-08T16:25:21

null

0

null

UTF-8

Python

false

20,844

py

#-- GAUDI jobOptions generated on Thu Jul 18 16:26:43 2013 #-- Contains event types : #-- 27163003 - 206 files - 3513735 events - 736.90 GBytes #-- Extra information about the data processing phases: #-- Processing Pass Step-124620 #-- StepId : 124620 #-- StepName : Digi13 with G4 dE/dx #-- ApplicationName : Boole #-- ApplicationVersion : v26r3 #-- OptionFiles : $APPCONFIGOPTS/Boole/Default.py;$APPCONFIGOPTS/Boole/DataType-2012.py;$APPCONFIGOPTS/Boole/Boole-SiG4EnergyDeposit.py;$APPCONFIGOPTS/Persistency/Compression-ZLIB-1.py #-- DDDB : fromPreviousStep #-- CONDDB : fromPreviousStep #-- ExtraPackages : AppConfig.v3r164 #-- Visible : Y #-- Processing Pass Step-124632 #-- StepId : 124632 #-- StepName : TCK-0x409f0045 Flagged for Sim08 2012 #-- ApplicationName : Moore #-- ApplicationVersion : v14r8p1 #-- OptionFiles : $APPCONFIGOPTS/Moore/MooreSimProductionWithL0Emulation.py;$APPCONFIGOPTS/Conditions/TCK-0x409f0045.py;$APPCONFIGOPTS/Moore/DataType-2012.py;$APPCONFIGOPTS/L0/L0TCK-0x0045.py #-- DDDB : fromPreviousStep #-- CONDDB : fromPreviousStep #-- ExtraPackages : AppConfig.v3r164 #-- Visible : Y #-- Processing Pass Step-124630 #-- StepId : 124630 #-- StepName : Stripping20-NoPrescalingFlagged for Sim08 #-- ApplicationName : DaVinci #-- ApplicationVersion : v32r2p1 #-- OptionFiles : $APPCONFIGOPTS/DaVinci/DV-Stripping20-Stripping-MC-NoPrescaling.py;$APPCONFIGOPTS/DaVinci/DataType-2012.py;$APPCONFIGOPTS/DaVinci/InputType-DST.py;$APPCONFIGOPTS/Persistency/Compression-ZLIB-1.py #-- DDDB : fromPreviousStep #-- CONDDB : fromPreviousStep #-- ExtraPackages : AppConfig.v3r164 #-- Visible : Y #-- Processing Pass Step-124834 #-- StepId : 124834 #-- StepName : Reco14a for MC #-- ApplicationName : Brunel #-- ApplicationVersion : v43r2p7 #-- OptionFiles : $APPCONFIGOPTS/Brunel/DataType-2012.py;$APPCONFIGOPTS/Brunel/MC-WithTruth.py;$APPCONFIGOPTS/Persistency/Compression-ZLIB-1.py #-- DDDB : fromPreviousStep #-- CONDDB : fromPreviousStep #-- ExtraPackages : AppConfig.v3r164 #-- Visible : Y #-- Processing Pass Step-125079 #-- StepId : 125079 #-- StepName : Sim08a - 2012 - MD - Pythia8 #-- ApplicationName : Gauss #-- ApplicationVersion : v45r3 #-- OptionFiles : $APPCONFIGOPTS/Gauss/Sim08-Beam4000GeV-md100-2012-nu2.5.py;$DECFILESROOT/options/@{eventType}.py;$LBPYTHIA8ROOT/options/Pythia8.py;$APPCONFIGOPTS/Gauss/G4PL_FTFP_BERT_EmNoCuts.py;$APPCONFIGOPTS/Persistency/Compression-ZLIB-1.py #-- DDDB : Sim08-20130503-1 #-- CONDDB : Sim08-20130503-1-vc-md100 #-- ExtraPackages : AppConfig.v3r171;DecFiles.v27r6 #-- Visible : Y #-- Processing Pass Step-125336 #-- StepId : 125336 #-- StepName : Sim08a - 2012 - MD - Pythia8 #-- ApplicationName : Gauss #-- ApplicationVersion : v45r3 #-- OptionFiles : $APPCONFIGOPTS/Gauss/Sim08-Beam4000GeV-md100-2012-nu2.5.py;$DECFILESROOT/options/@{eventType}.py;$LBPYTHIA8ROOT/options/Pythia8.py;$APPCONFIGOPTS/Gauss/G4PL_FTFP_BERT_EmNoCuts.py;$APPCONFIGOPTS/Persistency/Compression-ZLIB-1.py #-- DDDB : Sim08-20130503-1 #-- CONDDB : Sim08-20130503-1-vc-md100 #-- ExtraPackages : AppConfig.v3r171;DecFiles.v27r8 #-- Visible : Y from Gaudi.Configuration import * from GaudiConf import IOHelper IOHelper('ROOT').inputFiles(['LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000001_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000002_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000003_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000004_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000005_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000006_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000007_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000008_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000009_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000010_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000011_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000012_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000013_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000014_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000015_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000016_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000017_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000018_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000019_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000020_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000021_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000022_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000023_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000024_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000025_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000026_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000027_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000029_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000030_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000031_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000032_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000033_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000034_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000035_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000036_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000037_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000038_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000039_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000040_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000041_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000042_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000043_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000044_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000045_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000046_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000047_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000048_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000049_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000050_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000051_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000052_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000053_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000054_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000056_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000057_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000058_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000059_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000060_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000061_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000062_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000063_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000064_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000065_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000066_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000067_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000068_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000069_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000070_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000071_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000072_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000073_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000074_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000075_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000076_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000077_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000078_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000079_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000080_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000081_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000082_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000083_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000084_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000085_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000086_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000087_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000088_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000089_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000090_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000091_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000092_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000093_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000094_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000095_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000096_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000097_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000098_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000099_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000100_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000101_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000102_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000103_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000104_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000105_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000106_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000107_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000108_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000109_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000110_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000111_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000112_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000113_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000114_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000115_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000116_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000117_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000118_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000119_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000120_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000121_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000122_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000123_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000124_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000125_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000126_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000127_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000128_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000129_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000130_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000131_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000132_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000133_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000134_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000135_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000136_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000137_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000138_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000139_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000140_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000141_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000142_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000143_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000144_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000147_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000148_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000149_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000150_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025316/0000/00025316_00000151_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000001_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000002_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000003_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000004_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000005_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000006_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000007_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000008_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000009_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000010_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000011_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000012_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000013_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000014_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000015_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000016_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000017_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000018_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000019_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000020_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000021_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000022_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000023_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000024_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000025_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000027_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000028_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000029_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000030_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000031_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000032_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000033_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000034_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000035_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000036_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000037_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000038_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000040_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000041_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000042_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000043_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000044_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000045_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000046_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000048_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000050_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000051_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000052_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000054_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000055_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000056_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000057_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000058_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000059_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000060_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000061_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000063_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000064_1.allstreams.dst', 'LFN:/lhcb/MC/2012/ALLSTREAMS.DST/00025931/0000/00025931_00000065_1.allstreams.dst' ], clear=True)

[ "thomas.bird@cern.ch" ]

thomas.bird@cern.ch

f88bc082dba510ad310965033149a2cd4b5b9749

c3d0011d7842db09a57d185fb38a54e7da2db698

/app/tests/conftest.py

07bfbf51f34fc971d201b0291afd1a69596004fc

[]

no_license

ChiaYinChen/fastapi-practice

eebc988cd59ffa37e8c54f0cdf39094bfc4ead8f

61d07502945d6a3b71c842b9fd47062ee4a412cd

refs/heads/master

2023-09-02T03:30:39.634621

2021-11-10T03:25:56

410,732,538

0

null

UTF-8

Python

false

1,597

py

"""Pytest's conftest.py.""" import logging from typing import Dict, Generator import pytest from fastapi.testclient import TestClient from sqlalchemy.orm import Session from app import color_formatter from app.core.config import settings from app.db.session import SessionLocal from app.main import app from .utils.user import (authentication_token_from_username, user_authentication_headers) @pytest.fixture(scope="session") def db() -> Generator: """Postgres test session.""" yield SessionLocal() @pytest.fixture(scope="module") def client() -> Generator: """Mock client.""" with TestClient(app) as c: yield c @pytest.fixture(scope="module") def superuser_token_headers( client: TestClient, db: Session ) -> Dict[str, str]: """Token headers for superuser.""" return user_authentication_headers( client=client, username=settings.FIRST_SUPERUSER, password=settings.FIRST_SUPERUSER_PASSWORD ) @pytest.fixture(scope="module") def normal_user_token_headers( client: TestClient, db: Session ) -> Dict[str, str]: """Token headers for normal user.""" return authentication_token_from_username( client=client, username=settings.TEST_USER_USERNAME, db=db ) @pytest.fixture(scope='session', autouse=True) def setup_logging(): """Set custom logging handler for pytest.""" logger = logging.getLogger() logger.setLevel(logging.DEBUG) _handler = logging.StreamHandler() _handler.setFormatter(color_formatter) logger.addHandler(_handler)

[ "awdrg1210@gmail.com" ]

awdrg1210@gmail.com

39998b9a9178ac4d0bdf68c6631a1fd94392ee68

517756b136e1a2f7fb1929adab09cd6db900f9bf

/web/pages/migrations/0003_wikipage_wikipagerelatedlink_delete_freeformpage.py

c698b953c06790f4e36ad180d61f7f98939e0f5e

[]

no_license

andreiavram/scoutfile

6b67d07693a9b5d5f4d78247f2ec88eacc52dcc5

999ee76d82590af4b7c9f067eb949a48ffda5500

refs/heads/develop

2023-07-22T21:16:17.099526

2023-03-01T09:24:38

21,454,635

0

null

2019-02-18T00:51:20

2014-07-03T08:07:07

Python

UTF-8

Python

false

2,280

py

# Generated by Django 4.1.7 on 2023-02-24 17:05 from django.db import migrations, models import django.db.models.deletion import modelcluster.fields import wagtail.blocks import wagtail.contrib.table_block.blocks import wagtail.documents.blocks import wagtail.fields import wagtail.images.blocks class Migration(migrations.Migration): dependencies = [ ('wagtailcore', '0083_workflowcontenttype'), ('wagtailimages', '0025_alter_image_file_alter_rendition_file'), ('pages', '0002_freeformpage'), ] operations = [ migrations.CreateModel( name='WikiPage', fields=[ ('page_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='wagtailcore.page')), ('body', wagtail.fields.StreamField([('heading', wagtail.blocks.CharBlock(form_classname='title')), ('paragraph', wagtail.blocks.RichTextBlock()), ('image', wagtail.images.blocks.ImageChooserBlock()), ('document', wagtail.documents.blocks.DocumentChooserBlock()), ('table', wagtail.contrib.table_block.blocks.TableBlock())], use_json_field=True)), ('cover_image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.image')), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), migrations.CreateModel( name='WikiPageRelatedLink', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('name', models.CharField(max_length=255)), ('url', models.URLField()), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='pages.wikipage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.DeleteModel( name='FreeFormPage', ), ]

[ "andrei.avram@gmail.com" ]

andrei.avram@gmail.com

2746759beec23a93c8483f12f67e4e24dfdbd05c

2a256bce43ae0dcdd0699cb89744d7dfefda53e7

/genres.py

1e0de8859bf36a1d096c3f79047544cdfcb88c23

[]

no_license

mainul123/Project-for-Compsci

addb0534d9ff17d19f31ae7450b7c4a3296cf54c

137fb65da794bb1ac762627f065b8d619d9778ef

refs/heads/master

2021-08-30T19:25:01.428367

2017-12-19T05:41:31

110,990,830

0

null

UTF-8

Python

false

2,655

py

genres = [{"rock": ["symphonic rock", "jazz-rock", "heartland rock", "rap rock", "garage rock", "folk-rock", "roots rock", "adult alternative pop rock", "rock roll", "punk rock", "arena rock", "pop-rock", "glam rock", "southern rock", "indie rock", "funk rock", "country rock", "piano rock", "art rock", "rockabilly", "acoustic rock", "progressive rock", "folk rock", "psychedelic rock", "rock & roll", "blues rock", "alternative rock", "rock and roll", "soft rock", "rock and indie", "hard rock", "pop/rock", "pop rock", "rock", "classic pop and rock", "psychedelic", "british psychedelia", "punk", "metal", "heavy metal"]}, {"alternative/indie": ["adult alternative pop rock", "alternative rock", "alternative metal", "alternative", "lo-fi indie", "indie", "indie folk", "indietronica", "indie pop", "indie rock", "rock and indie"]}, {"electronic/dance": ["dance and electronica", "electro house", "electronic", "electropop", "progressive house", "hip house", "house", "eurodance", "dancehall", "dance", "trap"]}, {"soul": ["psychedelic soul", "deep soul", "neo-soul", "neo soul", "southern soul", "smooth soul", "blue-eyed soul", "soul and reggae", "soul"]}, {"classical": ["classical", "orchestral", "film soundtrack", "composer"]}, {"pop": ["country-pop", "latin pop", "classical pop", "pop-metal", "orchestral pop", "instrumental pop", "indie pop", "sophisti-pop", "pop punk", "pop reggae", "britpop", "traditional pop", "power pop", "sunshine pop", "baroque pop", "synthpop", "art pop", "teen pop", "psychedelic pop", "folk pop", "country pop", "pop rap", "pop soul", "pop and chart", "dance-pop", "pop", "top 40"]}, {"hip-hop/rnb": ["conscious hip hop", "east coast hip hop", "hardcore hip hop", "west coast hip hop", "hiphop", "southern hip hop", "hip-hop", "hip hop", "hip hop rnb and dance hall", "contemporary r b", "gangsta rap", "rapper", "rap", "rhythm and blues", "contemporary rnb", "contemporary r&b", "rnb", "rhythm & blues","r&b", "blues"]}, {"disco": ["disco"]}, {"swing": ["swing"]}, {"folk": ["contemporary folk", "folk"]}, {"country": ["country rock", "country-pop", "country pop", "contemporary country", "country"]}, {"jazz": ["vocal jazz", "jazz", "jazz-rock"]}, {"religious": ["christian", "christmas music", "gospel"]}, {"blues": ["delta blues", "rock blues", "urban blues", "electric blues", "acoustic blues", "soul blues", "country blues", "jump blues", "classic rock. blues rock", "jazz and blues", "piano blues", "british blues", "british rhythm & blues", "rhythm and blues", "blues", "blues rock", "rhythm & blues"]}, {"reggae": ["reggae fusion", "roots reggae", "reggaeton", "pop reggae", "reggae", "soul and reggae"]}]

[ "you@example.com" ]

you@example.com

db77a8b668dc1cbb0fb88e903388300504290f7c

41c1417ff294878ab3b46d5d3db1cc9d63ba07e5

/UI_data_Alert.py

264a0798b5936c11506ff806ed669889c9f8d34f

[]

no_license

eong93/QGIS_DataAlertPlugin

006404b14d174f3d552d32cd17ca1b2d8af82c95

5aec2a5ad44e95f8fcf177c8cc7825ffa64d1258

refs/heads/master

2021-01-10T12:37:40.688394

2015-10-01T19:09:42

43,501,913

0

null

UTF-8

Python

false

2,890

py

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'data_Alert_dockwidget_base.ui' # # Created: Tue Sep 29 12:29:50 2015 # by: PyQt4 UI code generator 4.10.2 # # WARNING! All changes made in this file will be lost! from PyQt4 import QtCore, QtGui try: _fromUtf8 = QtCore.QString.fromUtf8 except AttributeError: def _fromUtf8(s): return s try: _encoding = QtGui.QApplication.UnicodeUTF8 def _translate(context, text, disambig): return QtGui.QApplication.translate(context, text, disambig, _encoding) except AttributeError: def _translate(context, text, disambig): return QtGui.QApplication.translate(context, text, disambig) class Ui_dataAlertDockWidgetBase(object): def setupUi(self, dataAlertDockWidgetBase): dataAlertDockWidgetBase.setObjectName(_fromUtf8("dataAlertDockWidgetBase")) dataAlertDockWidgetBase.resize(350, 548) self.dockWidgetContents = QtGui.QWidget() self.dockWidgetContents.setObjectName(_fromUtf8("dockWidgetContents")) self.endButton = QtGui.QPushButton(self.dockWidgetContents) self.endButton.setGeometry(QtCore.QRect(240, 480, 75, 23)) self.endButton.setObjectName(_fromUtf8("endButton")) self.startButton = QtGui.QPushButton(self.dockWidgetContents) self.startButton.setGeometry(QtCore.QRect(30, 480, 75, 23)) self.startButton.setObjectName(_fromUtf8("startButton")) self.textBrowser = QtGui.QTextBrowser(self.dockWidgetContents) self.textBrowser.setGeometry(QtCore.QRect(15, 110, 321, 351)) self.textBrowser.setObjectName(_fromUtf8("textBrowser")) self.upper = QtGui.QLineEdit(self.dockWidgetContents) self.upper.setGeometry(QtCore.QRect(120, 10, 113, 20)) self.upper.setObjectName(_fromUtf8("upper")) self.left = QtGui.QLineEdit(self.dockWidgetContents) self.left.setGeometry(QtCore.QRect(20, 40, 113, 20)) self.left.setObjectName(_fromUtf8("left")) self.right = QtGui.QLineEdit(self.dockWidgetContents) self.right.setGeometry(QtCore.QRect(220, 40, 113, 20)) self.right.setObjectName(_fromUtf8("right")) self.lower = QtGui.QLineEdit(self.dockWidgetContents) self.lower.setGeometry(QtCore.QRect(120, 70, 113, 20)) self.lower.setObjectName(_fromUtf8("lower")) dataAlertDockWidgetBase.setWidget(self.dockWidgetContents) self.retranslateUi(dataAlertDockWidgetBase) QtCore.QMetaObject.connectSlotsByName(dataAlertDockWidgetBase) def retranslateUi(self, dataAlertDockWidgetBase): dataAlertDockWidgetBase.setWindowTitle(_translate("dataAlertDockWidgetBase", "UVI Alert", None)) self.endButton.setText(_translate("dataAlertDockWidgetBase", "End", None)) self.startButton.setText(_translate("dataAlertDockWidgetBase", "Start", None))

[ "eric.ong@digitalglobe.com" ]

eric.ong@digitalglobe.com

c9135529a7f8dec9f1c3f1914cd91e165f7eab43

b252d1f8ec5f68bf5f935c000e0bb011718ea691

/virtualenvs/ninetyseven/src/savoy/core/template_pages/middleware.py

117c03647f31b1ef61820c131b21d2f9d5190506

[]

no_license

syncopated/97bottles

2ceace7ed6a852bef61796733a08eb878b045152

08f4210e3de77c4564fcc8c1a2e9b47a0088249f

refs/heads/master

2016-08-05T07:48:51.109089

2012-12-02T17:38:35

null

0

null

UTF-8

Python

false

719

py

from django.http import Http404 from django.conf import settings from savoy.core.template_pages.views import templatepage class TemplatepageFallbackMiddleware(object): def process_response(self, request, response): if response.status_code != 404: return response # No need to check for a flatpage for non-404 responses. try: return templatepage(request, request.path) # Return the original response if any errors happened. Because this # is a middleware, we can't assume the errors will be caught elsewhere. except Http404: return response except: if settings.DEBUG: raise return response

[ "keith@dkeithrobinson.com" ]

keith@dkeithrobinson.com

e634b0b58082403c727066d3ea4845f10e9599f7

ad31c7890508030c41699f4d98a47aa4b2cd1765

/models/ndpm/priors.py

473d31285df93dd7ffb72100aa3e08b3526c3111

[]

no_license

Chandan-IITI/online-continual-learning

cd821f7f189251b5b183b75c2db50087930f731a

1050d1b716c51edc83799e2ecee38da66a169931

refs/heads/main

2023-03-05T18:10:08.085657

2021-02-10T19:42:27

340,447,633

2

1

null

2021-02-19T17:52:42

null

UTF-8

Python

false

1,610

py

from abc import ABC, abstractmethod import torch from utils.utils import maybe_cuda class Prior(ABC): def __init__(self, params): self.params = params @abstractmethod def add_expert(self): pass @abstractmethod def record_usage(self, usage, index=None): pass @abstractmethod def nl_prior(self, normalize=False): pass class CumulativePrior(Prior): def __init__(self, params): super().__init__(params) self.log_counts = maybe_cuda(torch.tensor( params.log_alpha )).float().unsqueeze(0) def add_expert(self): self.log_counts = torch.cat( [self.log_counts, maybe_cuda(torch.zeros(1))], dim=0 ) def record_usage(self, usage, index=None): """Record expert usage Args: usage: Tensor of shape [K+1] if index is None else scalar index: expert index """ if index is None: self.log_counts = torch.logsumexp(torch.stack([ self.log_counts, usage.log() ], dim=1), dim=1) else: self.log_counts[index] = torch.logsumexp(torch.stack([ self.log_counts[index], maybe_cuda(torch.tensor(usage)).float().log() ], dim=0), dim=0) def nl_prior(self, normalize=False): nl_prior = -self.log_counts if normalize: nl_prior += torch.logsumexp(self.log_counts, dim=0) return nl_prior @property def counts(self): return self.log_counts.exp()

[ "zhedamai0126@gmail.com" ]

zhedamai0126@gmail.com

0bfb21e8e2ff9add1ccd3f4e5d69776fe7878c58

712a7acca58d9f4b5dc2a107f92354aaa5caec65

/app/new_feature.py

3e10145111e40f254ebe8966e05ba5cb4286bc34

[]

no_license

myd10/testing-123-2.0

2332ad5f529765be30509f4b35cb60371569a892

59de9dbee3e506b9769dd7c94d2e5f179ecd2fc0

refs/heads/master

2022-04-23T07:02:31.742780

2020-04-19T21:21:06

255,473,162

0

null

2020-04-19T21:21:08

2020-04-14T00:39:04

Python

UTF-8

Python

false

79

py

#new feature on my-new-feature branch def announce(): return "Hello World"

[ "myd10@georgetown.edu" ]

myd10@georgetown.edu

dd37637d40b6aa1f04a8fc1d4cec182d38ff2386

f9ac779ee4de9f66da3c9d9585785fa95ca0e7a2

/h5pyd/_apps/hscopy.py

022cf90d09e0337cf4bb865de2f851d3b82c043a

[ "LicenseRef-scancode-warranty-disclaimer" ]

no_license

t-sommer/h5pyd

e4cb145e7b523972062de7ce86d500fe3473003a

a99860928f5845079800f761480e51ca9be0d759

refs/heads/master

2020-04-20T06:09:58.717543

2019-01-31T07:15:09

null

0

null

UTF-8

Python

false

7,691

py

############################################################################## # Copyright by The HDF Group. # # All rights reserved. # # # # This file is part of HSDS (HDF5 Scalable Data Service), Libraries and # # Utilities. The full HSDS copyright notice, including # # terms governing use, modification, and redistribution, is contained in # # the file COPYING, which can be found at the root of the source code # # distribution tree. If you do not have access to this file, you may # # request a copy from help@hdfgroup.org. # ############################################################################## import sys import logging try: import h5pyd except ImportError as e: sys.stderr.write("ERROR : %s : install it to use this utility...\n" % str(e)) sys.exit(1) try: import pycurl as PYCRUL except ImportError as e: PYCRUL = None if __name__ == "__main__": from config import Config from utillib import load_file else: from .config import Config from .utillib import load_file cfg = Config() #---------------------------------------------------------------------------------- def usage(): print("Usage:\n") print((" {} [ OPTIONS ] source destination".format(cfg["cmd"]))) print("") print("Description:") print(" Copy domain") print(" source: domain to be copied ") print(" destination: target domain") print("") print("Options:") print(" -v | --verbose :: verbose output") print(" -e | --endpoint <domain> :: The HDF Server endpoint, e.g. http://hsdshdflab.hdfgroup.org") print(" -u | --user <username> :: User name credential") print(" -p | --password <password> :: Password credential") print(" -c | --conf <file.cnf> :: A credential and config file") print(" -z[n] :: apply compression filter to any non-compressed datasets, n: [0-9]") print(" --cnf-eg :: Print a config file and then exit") print(" --logfile <logfile> :: logfile path") print(" --loglevel debug|info|warning|error :: Change log level") print(" --nodata :: Do not upload dataset data") print(" -h | --help :: This message.") print("") #end print_usage #---------------------------------------------------------------------------------- def print_config_example(): print("# default") print("hs_username = <username>") print("hs_password = <passwd>") print("hs_endpoint = http://hsdshdflab.hdfgroup.org") #print_config_example #---------------------------------------------------------------------------------- def main(): loglevel = logging.ERROR verbose = False nodata = False deflate = None cfg["cmd"] = sys.argv[0].split('/')[-1] if cfg["cmd"].endswith(".py"): cfg["cmd"] = "python " + cfg["cmd"] cfg["logfname"] = None logfname=None src_files = [] argn = 1 while argn < len(sys.argv): arg = sys.argv[argn] val = None if arg[0] == '-' and len(src_files) > 0: # options must be placed before filenames print("options must precead source files") usage() sys.exit(-1) if len(sys.argv) > argn + 1: val = sys.argv[argn+1] if arg in ("-v", "--verbose"): verbose = True argn += 1 elif arg == "--nodata": nodata = True argn += 1 elif arg == "--loglevel": if val == "debug": loglevel = logging.DEBUG elif val == "info": loglevel = logging.INFO elif val == "warning": loglevel = logging.WARNING elif val == "error": loglevel = logging.ERROR else: print("unknown loglevel") usage() sys.exit(-1) argn += 2 elif arg == '--logfile': logfname = val argn += 2 elif arg in ("-h", "--help"): usage() sys.exit(0) elif arg in ("-e", "--endpoint"): cfg["hs_endpoint"] = val argn += 2 elif arg in ("-u", "--username"): cfg["hs_username"] = val argn += 2 elif arg in ("-p", "--password"): cfg["hs_password"] = val argn += 2 elif arg == '--cnf-eg': print_config_example() sys.exit(0) elif arg.startswith("-z"): compressLevel = 4 if len(arg) > 2: try: compressLevel = int(arg[2:]) except ValueError: print("Compression Level must be int between 0 and 9") sys.exit(-1) deflate = compressLevel argn += 1 elif arg[0] == '-': usage() sys.exit(-1) else: src_files.append(arg) argn += 1 # setup logging logging.basicConfig(filename=logfname, format='%(asctime)s %(filename)s:%(lineno)d %(message)s', level=loglevel) logging.debug("set log_level to {}".format(loglevel)) # end arg parsing logging.info("username: {}".format(cfg["hs_username"])) logging.info("password: {}".format(cfg["hs_password"])) logging.info("endpoint: {}".format(cfg["hs_password"])) logging.info("verbose: {}".format(verbose)) if len(src_files) < 2: # need at least a src and destination usage() sys.exit(-1) src_domain = src_files[0] des_domain = src_files[1] logging.info("source domain: {}".format(src_domain)) logging.info("target domain: {}".format(des_domain)) if src_domain[0] != '/' or src_domain[-1] == '/': print("source domain must be an absolute path, non-folder domain") usage() sys.exit(-1) if des_domain[0] != '/' or des_domain[-1] == '/': print("source domain must be an absolute path, non-folder domain") usage() sys.exit(-1) if cfg["hs_endpoint"] is None: logging.error('No endpoint given, try -h for help\n') sys.exit(1) logging.info("endpoint: {}".format(cfg["hs_endpoint"])) try: # get a handle to input file try: fin = h5pyd.File(src_domain, mode='r') except IOError as ioe: logging.error("Error opening file {}: {}".format(src_domain, ioe)) sys.exit(1) # create the output domain try: username = cfg["hs_username"] password = cfg["hs_password"] endpoint = cfg["hs_endpoint"] fout = h5pyd.File(des_domain, 'x', endpoint=endpoint, username=username, password=password) except IOError as ioe: if ioe.errno == 403: logging.error("No write access to domain: {}".format(des_domain)) else: logging.error("Error creating file {}: {}".format(des_domain, ioe)) sys.exit(1) # do the actual load load_file(fin, fout, verbose=verbose, nodata=nodata, deflate=deflate) msg = "File {} uploaded to domain: {}".format(src_domain, des_domain) logging.info(msg) if verbose: print(msg) except KeyboardInterrupt: logging.error('Aborted by user via keyboard interrupt.') sys.exit(1) # __main__ if __name__ == "__main__": main()

[ "jreadey@hdfgroup.org" ]

jreadey@hdfgroup.org

1dca4c5c4032b6d7106218048591403bb413149b

2cafc4981f85e9a25cceb18af1e936e19268e0ee

/scapy_tcp_ACK_discovery.py

ffc67cf055318e0203ce98a8c94e2e35b256b78e

[]

no_license

lapinrepository/ethicalhacking

fdd0647bffeb87544ede182eb62544ee922579fd

14fac0bee8ca5f58c5499e4e91323e005a5e6c25

refs/heads/master

2021-10-09T15:14:29.976534

2018-12-30T09:30:19

null

0

null

UTF-8

Python

false

1,287

py

#!/usr/bin/python from scapy.all import * import logging import subprocess logging.getLogger("scapy.runtime").setLevel(logging.ERROR) import threading screenlock = threading.Semaphore(value=1) def tcpackscan(prefix, addr): try: answer = sr1(IP(dst=prefix+str(addr))/TCP(dport=80, flags = 'A'), timeout=1, verbose=0) screenlock.acquire() if int(answer[TCP].flags) == 4: print("[+] Host " + prefix + str(addr) + " is alive") else: pass except: pass finally: screenlock.release() if len(sys.argv) != 2: print("Usage scapy_tcp_ACK_discovery.py [interface]") print("Example: scapy_tcp_ACK_discovery.py eth0") sys.exit() interface = str(sys.argv[1]) ip = subprocess.check_output("ifconfig " + interface + " | grep 'inet' | cut -d ' ' -f 1 | cut -d 'n' -f 2 | cut -d ' ' -f 2", shell=True).strip() prefix = ip.split('.')[0] + '.' + ip.split('.')[1] + '.' + ip.split('.')[2] + '.' reply_ip = list() for addr in range(100,254): t = threading.Thread(target=tcpackscan, args=(prefix, addr)) t.start() #for addr in range(100,110): # answer = sr1(IP(dst=prefix + str(addr)) / TCP(dport=80, flags = 'A'), timeout=1, verbose=0) # try: # if int(answer[TCP].flags) == 4: # reply_ip.append(prefix + str(addr)) # except: # pass #for elt in reply_ip: # print(elt)

[ "root@localhost.localdomain" ]

root@localhost.localdomain

b8e40021cad5f7464ecf970db88946677e9f121d

3bf1480a1a00209bc8ef8a66e1995549987ae70e

/utils/scripts/OOOlevelGen/src/levels/level_2_1.py

b1a083b100c10f780210b20af5f57d1be6d5f578

[ "MIT" ]

permissive

fullscreennl/bullettime

284a8ea320fb4adabc07c3639731a80fc4db5634

8967449cdf926aaed6bb7ec217d92e0689fb0c3c

refs/heads/master

2020-03-29T01:56:26.627283

2018-10-11T19:09:48

149,414,264

0

null

UTF-8

Python

false

5,698

py

import LevelBuilder from sprites import * def render(name,bg): lb = LevelBuilder.LevelBuilder(name+".plist",background=bg) lb.addObject(Bullet.BulletSprite(x=0, y=0,width=10,height=10,angle='0',restitution=0.5,static='false',friction=0.5,density=3,spawnEvent='onShoot')) lb.addObject(Hero.HeroSprite(x=34, y=48,width=42,height=74)) lb.addObject(Teleporter.TeleporterSprite( level_id='leveldata/level_2_2')) lb.addObject(ZoomTrigger.ZoomTriggerSprite(x=20,y=250,width=100,height=500,zoom_fact=1.0)) lb.addObject(ZoomTrigger.ZoomTriggerSprite(x=185,y=320-60,width=128,height=100,zoom_fact=0.1666)) lb.addObject(ZoomTrigger.ZoomTriggerSprite(x=350,y=250,width=100,height=500,zoom_fact=1.0)) lb.addObject(WatchtowerVisual.WatchtowerVisualSprite(x=185, y=92,width=128,height=235-50,angle='0',restitution=0.2,static='true',friction=0.5,density=20,firstframe='watchtower.png' )) lb.addObject(Crate.CrateSprite(x=2343,y=53,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=2305,y=53,width=32, height=32, static='false',angle=0)) lb.addObject(Beam.BeamSprite(x=1642, y=103,width=160,height=36,angle='0' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Beam.BeamSprite(x=1156, y=220,width=160,height=36,angle='0' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Beam.BeamSprite(x=2180, y=220,width=160,height=36,angle='0' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Pickup.PickupSprite(x=2224,y=257,width=32, height=32, static='false',angle=0)) lb.addObject(Pickup.PickupSprite(x=2140,y=257,width=32, height=32, static='false',angle=0)) lb.addObject(Pickup.PickupSprite(x=1685,y=140,width=32, height=32, static='false',angle=0)) lb.addObject(Pickup.PickupSprite(x=1607,y=140,width=32, height=32, static='false',angle=0)) lb.addObject(Pickup.PickupSprite(x=1201,y=257,width=32, height=32, static='false',angle=0)) lb.addObject(Pickup.PickupSprite(x=1117,y=257,width=32, height=32, static='false',angle=0)) lb.addObject(Enemy.EnemySprite(x=1395, y=19,width=33,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=5 , classname='BlobSprite',firstframe='monsterblob.png')) lb.addObject(Enemy.EnemySprite(x=1353, y=19,width=33,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=5 , classname='BlobSprite',firstframe='monsterblob.png')) lb.addObject(Enemy.EnemySprite(x=736, y=19,width=33,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=5 , classname='BlobSprite',firstframe='monsterblob.png')) lb.addObject(Enemy.EnemySprite(x=1261, y=19,width=33,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=5 , classname='BlobSprite',firstframe='monsterblob.png')) lb.addObject(Enemy.EnemySprite(x=1219, y=19,width=33,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=5 , classname='BlobSprite',firstframe='monsterblob.png')) lb.addObject(Enemy.EnemySprite(x=1158, y=255,width=33,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=5 , classname='BlobSprite',firstframe='monsterblob.png')) lb.addObject(Crate.CrateSprite(x=2343,y=15,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=2305,y=15,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=1645,y=176,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=1607,y=176,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=2343,y=89,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=2305,y=89,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=2383,y=53,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=2383,y=15,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=1685,y=176,width=32, height=32, static='false',angle=0)) lb.addObject(Crate.CrateSprite(x=2383,y=89,width=32, height=32, static='false',angle=0)) lb.addObject(Beam.BeamSprite(x=406, y=38,width=72,height=76,angle='90' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Beam.BeamSprite(x=406, y=108,width=72,height=76,angle='90' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Beam.BeamSprite(x=406, y=179,width=72,height=76,angle='90' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Beam.BeamSprite(x=406, y=249,width=72,height=76,angle='90' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Beam.BeamSprite(x=406, y=320,width=72,height=76,angle='90' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Beam.BeamSprite(x=406, y=390,width=72,height=76,angle='90' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Beam.BeamSprite(x=406, y=461,width=72,height=76,angle='90' ,restitution=0.2,static='true',friction=0.5,density=20 ,classname='Destructable').setName('dBeam')) lb.addObject(Enemy.EnemySprite(x=1983, y=116,width=225,height=225,angle='0',restitution=0.2,static='false',friction=0.5,density=5 , classname='BlobSprite',firstframe='monsterblob.png')) lb.render()

[ "github@fotoboer.nl" ]

github@fotoboer.nl

a2ef8e111e897f9bbacafce69f64708f2fef7967

e41d21d3f2db1e3f3bf3f34da357a6fa70670e9f

/03/2.py

535fd215c07861bc21932f1998f88a3e52566918

[]

no_license

reynoldscem/aoc2016

98536a220461365e004ce370db41e540277c513a

432415d1c72f7eac6b386627a3f235e2233964cb

refs/heads/master

2020-06-13T22:07:48.734760

2016-12-21T09:11:30

75,547,582

0

null

UTF-8

Python

false

915

py

from itertools import permutations import numpy as np import argparse import os def build_parser(): parser = argparse.ArgumentParser() parser.add_argument('filename') return parser def is_valid(triangle): for permutation in permutations(triangle): if np.sum(permutation[0:2]) <= permutation[2]: return False return True def main(args): with open(args.filename) as fd: data = fd.read().split() data = np.array( list(map(int, data)) ).reshape(-1, 3).transpose().reshape(-1, 3) triangles = [ tuple(entry) for entry in data ] valid_count = 0 for triangle in triangles: if is_valid(triangle): valid_count += 1 print(valid_count) if __name__ == '__main__': args = build_parser().parse_args() assert os.path.isfile(args.filename), 'Must provide a valid filename' main(args)

[ "reynoldscem@gmail.com" ]

reynoldscem@gmail.com