xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

a76744312dd71b2361f14534d5618c09af6e2802

28,542

py

Python

calc_dens_rates.py

daniel-furman/ice-densification-research

89645275aace68ad1dbf897ac5de72696685bffc

[ "MIT" ]

null

calc_dens_rates.py

daniel-furman/ice-densification-research

89645275aace68ad1dbf897ac5de72696685bffc

[ "MIT" ]

null

calc_dens_rates.py

daniel-furman/ice-densification-research

89645275aace68ad1dbf897ac5de72696685bffc

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tues Aug 18 13:27:33 2020 @author: danielfurman """ # Sixteen densification rate calculations. The entire creep curve was # composed of a transient response followed by the steady-state regime, # with rates calculated by taking time slices during steady-state and # averaging many thus-approximated rates. Steady-state slices corresponded to # relatively small changes in density; therefore, the mean relative density # was considered representative per measurement, and the densification can be # taken as density invariant, albeit locally. # Required Libraries: import pandas as pd import numpy as np import glob import matplotlib.pylab as plt import warnings warnings.filterwarnings("ignore") # Load all experimental data filenames = sorted(glob.glob('data/compaction*.csv')) #grab filepath names print('\nThe compaction creep test files are:\n\n',filenames) # print names data_list1 = [] #intialize empty numpy stack for f in filenames: #f is index with string filenames data_list1.append(np.loadtxt(fname=f, delimiter=',')) #stack arrays print('\nThere are', len(data_list1), 'total experimental files.') num_experiments = len(data_list1) #variable for number of files # Also load experimental table paper_table = pd.read_csv('data/paper_data.csv', delimiter=',', header = 'infer') applied_pressure_raw = np.array([0.627, 0.753, 0.878,0.973,1.16,1.16, 0.47,0.59,0.72,1.16,0.251,0.377, 0.44, 0.5967,1.16,1.16]) #In MPa fig, axes = plt.subplots(1, 3, figsize=(20,4.5)) #inialize matrix of plots steadystate_slice = data_list1[0][(data_list1[0][:,1]/(60*60)>=10)& (data_list1[0][:,1]/(60*60)<=115)] axes[0].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) axes[0].set_ylim([.74,.744]) axes[0].set_title('Compaction Id 1, First Step') x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[0,'Densification rate'] = dens_rate paper_table.loc[0, 'Mean dens'] = mean_dens paper_table.loc[0, 'applied stress'] = applied_pressure_raw[0]/mean_dens axes[0].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[0].legend(loc = 'lower right', shadow = True) axes[0].set_ylabel('Density (g/cm^3)') axes[0].set_xlabel('Time (hours)') steadystate_slice = data_list1[1][(data_list1[1][:,1]/(60*60)>=0) &(data_list1[1][:,1]/(60*60)<=33.9)] axes[1].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) axes[1].set_ylim([.739,.743]) axes[1].set_title('Compaction Id 2, First Step') x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[3,'Densification rate'] = dens_rate paper_table.loc[3, 'Mean dens'] = mean_dens paper_table.loc[3, 'applied stress'] = applied_pressure_raw[3]/mean_dens axes[1].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[1].legend(loc = 'lower right', shadow = True) axes[1].set_ylabel('Density (g/cm^3)') axes[1].set_xlabel('Time (hours)') steadystate_slice = data_list1[2][(data_list1[2][:,1]/(60*60)>=5) &(data_list1[2][:,1]/(60*60)<=60)] axes[2].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) axes[2].set_title('Compaction Id 3, First Step') x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[11,'Densification rate'] = dens_rate paper_table.loc[11, 'Mean dens'] = mean_dens paper_table.loc[11, 'applied stress'] = applied_pressure_raw[11]/mean_dens axes[2].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[2].legend(loc = 'lower right', shadow = True) axes[2].set_ylabel('Density (g/cm^3)') axes[2].set_xlabel('Time (hours)') fig, axes = plt.subplots(1, 3, figsize=(20,4.5)) #inialize matrix of plots steadystate_slice = data_list1[3][(data_list1[3][:,1]/(60*60)<=38) &(data_list1[3][:,1]/(60*60)>=23)] axes[0].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) axes[0].set_title('Compaction Id 4, Single step') x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[13,'Densification rate'] = dens_rate paper_table.loc[13, 'Mean dens'] = mean_dens paper_table.loc[13, 'applied stress'] = applied_pressure_raw[13]/mean_dens axes[0].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[0].legend(loc = 'lower right', shadow = True) axes[0].set_ylabel('Density (g/cm^3)') axes[0].set_xlabel('Time (hours)') steadystate_slice = data_list1[2][(data_list1[2][:,1]/(60*60)>=140)] axes[1].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) axes[1].set_title('Compaction Id 3, Second Step') x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[10,'Densification rate'] = dens_rate paper_table.loc[10, 'Mean dens'] = mean_dens paper_table.loc[10, 'applied stress'] = applied_pressure_raw[10]/mean_dens axes[1].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[1].legend(loc = 'lower right', shadow = True) axes[1].set_ylabel('Density (g/cm^3)') axes[1].set_xlabel('Time (hours)') steadystate_slice = data_list1[4][(data_list1[4][:,1]/(60*60)>=82) &(data_list1[4][:,1]/(60*60)<=97)] axes[2].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) axes[2].set_title('Compaction Id 5, First Step') x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[14,'Densification rate'] = dens_rate paper_table.loc[14, 'Mean dens'] = mean_dens paper_table.loc[14, 'applied stress'] = applied_pressure_raw[14]/mean_dens axes[2].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[2].legend(loc = 'lower right', shadow = True) axes[2].set_ylabel('Density (g/cm^3)') axes[2].set_xlabel('Time (hours)') fig, axes = plt.subplots(1, 3, figsize=(20,4.5)) #inialize matrix of plots steadystate_slice = data_list1[4][(data_list1[4][:,1]/(60*60)>=128)] axes[0].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) axes[0].set_title('Compaction Id 5, Second Step ') x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[12,'Densification rate'] = dens_rate paper_table.loc[12, 'Mean dens'] = mean_dens paper_table.loc[12, 'applied stress'] = applied_pressure_raw[12]/mean_dens axes[0].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[0].legend(loc = 'lower right', shadow = True) axes[0].set_ylabel('Density (g/cm^3)') axes[0].set_xlabel('Time (hours)') axes[1].set_title('Compaction Id 6, First Step') steadystate_slice = data_list1[5][(data_list1[5][:,1]/(60*60)>=60) &(data_list1[5][:,1]/(60*60)<=90)] axes[1].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[9,'Densification rate'] = dens_rate paper_table.loc[9, 'Mean dens'] = mean_dens paper_table.loc[9, 'applied stress'] = applied_pressure_raw[9]/mean_dens axes[1].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[1].legend(loc = 'lower right', shadow = True) axes[1].set_ylabel('Density (g/cm^3)') axes[1].set_xlabel('Time (hours)') axes[2].set_title('Compaction Id 6, Second Step') steadystate_slice = data_list1[5][(data_list1[5][:,1]/(60*60)>=91) &(data_list1[5][:,1]/(60*60)<=113)] axes[2].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[6,'Densification rate'] = dens_rate paper_table.loc[6, 'Mean dens'] = mean_dens paper_table.loc[6, 'applied stress'] = applied_pressure_raw[6]/mean_dens axes[2].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[2].legend(loc = 'lower right', shadow = True) axes[2].set_ylabel('Density (g/cm^3)') axes[2].set_xlabel('Time (hours)') fig, axes = plt.subplots(1, 3, figsize=(20,4.5)) #inialize matrix of plots steadystate_slice = data_list1[5][(data_list1[5][:,1]/(60*60)>=115) &(data_list1[5][:,1]/(60*60)<=136)] axes[0].set_title('Compaction Id 6, Third Step') axes[0].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[8,'Densification rate'] = dens_rate paper_table.loc[8, 'Mean dens'] = mean_dens paper_table.loc[8, 'applied stress'] = applied_pressure_raw[8]/mean_dens axes[0].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[0].legend(loc = 'lower right', shadow = True) axes[0].set_ylabel('Density (g/cm^3)') axes[0].set_xlabel('Time (hours)') steadystate_slice = data_list1[5][(data_list1[5][:,1]/(60*60)>=140)] axes[1].set_title('Compaction Id 6, Fourth Step') axes[1].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[7,'Densification rate'] = dens_rate paper_table.loc[7, 'Mean dens'] = mean_dens paper_table.loc[7, 'applied stress'] = applied_pressure_raw[7]/mean_dens axes[1].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[1].legend(loc = 'lower right', shadow = True) axes[1].set_ylabel('Density (g/cm^3)') axes[1].set_xlabel('Time (hours)') steadystate_slice = data_list1[0][(data_list1[0][:,1]/(60*60)>=140)] axes[2].set_title('Compaction Id 1, Second Step') axes[2].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[5,'Densification rate'] = dens_rate paper_table.loc[5, 'Mean dens'] = mean_dens paper_table.loc[5, 'applied stress'] = applied_pressure_raw[5]/mean_dens axes[2].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[2].legend(loc = 'lower right', shadow = True) fig, axes = plt.subplots(1, 3, figsize=(20,4.5)) #inialize matrix of plots axes[2].set_ylabel('Density (g/cm^3)') axes[2].set_xlabel('Time (hours)') axes[0].set_title('Compaction Id 2, Second Step') steadystate_slice = data_list1[1][(data_list1[1][:,1]/(60*60)>=60) &(data_list1[1][:,1]/(60*60)<=79)] axes[0].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[4,'Densification rate'] = dens_rate paper_table.loc[4, 'Mean dens'] = mean_dens paper_table.loc[4, 'applied stress'] = applied_pressure_raw[4]/mean_dens axes[0].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[0].legend(loc = 'lower right', shadow = True) axes[0].set_ylabel('Density (g/cm^3)') axes[0].set_xlabel('Time (hours)') axes[1].set_title('Compaction Id 2, Third Step') steadystate_slice = data_list1[1][(data_list1[1][:,1]/(60*60)>=80) &(data_list1[1][:,1]/(60*60)<=100)] axes[1].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[1,'Densification rate'] = dens_rate paper_table.loc[1, 'Mean dens'] = mean_dens paper_table.loc[1, 'applied stress'] = applied_pressure_raw[1]/mean_dens axes[1].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[1].legend(loc = 'lower right', shadow = True) axes[1].set_ylabel('Density (g/cm^3)') axes[1].set_xlabel('Time (hours)') axes[2].set_title('Compaction Id 2, Fourth Step') steadystate_slice = data_list1[1][(data_list1[1][:,1]/(60*60)>=125)] axes[2].plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[2,'Densification rate'] = dens_rate paper_table.loc[2, 'Mean dens'] = mean_dens paper_table.loc[2, 'applied stress'] = applied_pressure_raw[2]/mean_dens axes[2].plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes[2].legend(loc = 'lower right', shadow = True) axes[2].set_ylabel('Density (g/cm^3)') axes[2].set_xlabel('Time (hours)') fig, axes = plt.subplots(1, 1, figsize=(4.8,4)) #inialize matrix of plots axes.set_title('Compaction Id 7, Single Step') steadystate_slice = data_list1[6][(data_list1[6][:,1]/(60*60)>=100) &(data_list1[6][:,1]/(60*60)<=170)] axes.plot(steadystate_slice [:,1]/(60*60), steadystate_slice [:,7]) x = int(len(steadystate_slice[:,1])/10) densrates = np.zeros(x) strainrates = np.zeros(x) time1 = np.zeros(x) dense1 = np.zeros(x) time2 = np.zeros(x) dense2 = np.zeros(x) for i in range(0,x): dtime = steadystate_slice[:,1][i] - steadystate_slice[:,1][ (len(steadystate_slice)-(i+1))] ddense = steadystate_slice[:,7][i] - steadystate_slice[:,7][ (len(steadystate_slice)-(i+1))] dstrain = steadystate_slice[:,5][i] - steadystate_slice[:,5][ (len(steadystate_slice)-(i+1))] densrates[i] = (ddense/dtime)/.917 strainrates[i] = dstrain/dtime dense1[i] = steadystate_slice[:,7][i] time1[i] = steadystate_slice[:,1][i] dense2[i] = steadystate_slice[:,7][(len(steadystate_slice)-(i+1))] time2[i] = steadystate_slice[:,1][(len(steadystate_slice)-(i+1))] dens_rate = np.mean(densrates) mean_dens = np.mean(np.array([np.mean(dense1),np.mean(dense2)]))/.917 paper_table.loc[15,'Densification rate'] = dens_rate paper_table.loc[15, 'Mean dens'] = mean_dens paper_table.loc[15, 'applied stress'] = applied_pressure_raw[15]/mean_dens axes.plot(np.array([np.mean(time1)/(60*60),np.mean(time2)/(60*60)]), np.array([np.mean(dense1),np.mean(dense2)]), label = 'Steady-state rate = ' + "{:.2e}".format(dens_rate)) axes.legend(loc = 'lower right', shadow = True) axes.set_ylabel('Density (g/cm^3)') axes.set_xlabel('Time (hours)') paper_table.to_csv('data/paper_table_full.csv', index = None, header=True)

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ac043cab1d05cb93a5d913adb8d24e76f7373000

10,243

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Python

alembic/versions/da0fe56f616b_create_models_for_experiment_objects.py

notconfusing/CivilServant

f9c7a2cf4de4f6506e37b7c33a7e512b893069c3

[ "MIT" ]

17

2017-03-13T15:14:57.000Z

2020-01-07T19:12:49.000Z

alembic/versions/da0fe56f616b_create_models_for_experiment_objects.py

notconfusing/CivilServant

f9c7a2cf4de4f6506e37b7c33a7e512b893069c3

[ "MIT" ]

32

2016-06-08T03:35:43.000Z

2016-11-30T18:50:49.000Z

alembic/versions/da0fe56f616b_create_models_for_experiment_objects.py

notconfusing/CivilServant

f9c7a2cf4de4f6506e37b7c33a7e512b893069c3

[ "MIT" ]

4

2018-07-11T23:36:28.000Z

2019-11-16T19:32:33.000Z

"""create models for experiment objects Revision ID: da0fe56f616b Revises: 022d8114fe2a Create Date: 2016-07-23 19:18:48.388073 """ # revision identifiers, used by Alembic. revision = 'da0fe56f616b' down_revision = '022d8114fe2a' branch_labels = None depends_on = None from alembic import op import sqlalchemy as sa from sqlalchemy.dialects import mysql def upgrade(engine_name): globals()["upgrade_%s" % engine_name]() def downgrade(engine_name): globals()["downgrade_%s" % engine_name]() def upgrade_development(): ### commands auto generated by Alembic - please adjust! ### op.create_table('experiment_actions', sa.Column('id', sa.Integer(), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('experiment_id', sa.Integer(), nullable=True), sa.Column('praw_key_id', sa.String(length=256), nullable=True), sa.Column('action_subject_type', sa.String(length=64), nullable=True), sa.Column('action_subject_id', sa.String(length=256), nullable=True), sa.Column('action_object_type', sa.String(length=64), nullable=True), sa.Column('action_object_id', sa.String(length=256), nullable=True), sa.Column('metadata_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiment_actions_action_object_id'), 'experiment_actions', ['action_object_id'], unique=False) op.create_index(op.f('ix_experiment_actions_action_subject_id'), 'experiment_actions', ['action_subject_id'], unique=False) op.create_index(op.f('ix_experiment_actions_experiment_id'), 'experiment_actions', ['experiment_id'], unique=False) op.create_index(op.f('ix_experiment_actions_praw_key_id'), 'experiment_actions', ['praw_key_id'], unique=False) op.create_table('experiment_things', sa.Column('id', sa.String(length=256), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('object_type', sa.Integer(), nullable=True), sa.Column('experiment_id', sa.Integer(), nullable=True), sa.Column('object_created', sa.DateTime(), nullable=True), sa.Column('metadata_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiment_things_experiment_id'), 'experiment_things', ['experiment_id'], unique=False) op.create_table('experiments', sa.Column('id', sa.Integer(), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('name', sa.String(length=256), nullable=False), sa.Column('controller', sa.String(length=256), nullable=False), sa.Column('start_time', sa.DateTime(), nullable=True), sa.Column('end_time', sa.DateTime(), nullable=True), sa.Column('settings_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiments_name'), 'experiments', ['name'], unique=False) ### end Alembic commands ### def downgrade_development(): ### commands auto generated by Alembic - please adjust! ### op.drop_index(op.f('ix_experiments_name'), table_name='experiments') op.drop_table('experiments') op.drop_index(op.f('ix_experiment_things_experiment_id'), table_name='experiment_things') op.drop_table('experiment_things') op.drop_index(op.f('ix_experiment_actions_praw_key_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_experiment_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_action_subject_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_action_object_id'), table_name='experiment_actions') op.drop_table('experiment_actions') ### end Alembic commands ### def upgrade_test(): ### commands auto generated by Alembic - please adjust! ### op.create_table('experiment_actions', sa.Column('id', sa.Integer(), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('experiment_id', sa.Integer(), nullable=True), sa.Column('praw_key_id', sa.String(length=256), nullable=True), sa.Column('action_subject_type', sa.String(length=64), nullable=True), sa.Column('action_subject_id', sa.String(length=256), nullable=True), sa.Column('action_object_type', sa.String(length=64), nullable=True), sa.Column('action_object_id', sa.String(length=256), nullable=True), sa.Column('metadata_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiment_actions_action_object_id'), 'experiment_actions', ['action_object_id'], unique=False) op.create_index(op.f('ix_experiment_actions_action_subject_id'), 'experiment_actions', ['action_subject_id'], unique=False) op.create_index(op.f('ix_experiment_actions_experiment_id'), 'experiment_actions', ['experiment_id'], unique=False) op.create_index(op.f('ix_experiment_actions_praw_key_id'), 'experiment_actions', ['praw_key_id'], unique=False) op.create_table('experiment_things', sa.Column('id', sa.String(length=256), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('object_type', sa.Integer(), nullable=True), sa.Column('experiment_id', sa.Integer(), nullable=True), sa.Column('object_created', sa.DateTime(), nullable=True), sa.Column('metadata_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiment_things_experiment_id'), 'experiment_things', ['experiment_id'], unique=False) op.create_table('experiments', sa.Column('id', sa.Integer(), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('name', sa.String(length=256), nullable=False), sa.Column('controller', sa.String(length=256), nullable=False), sa.Column('start_time', sa.DateTime(), nullable=True), sa.Column('end_time', sa.DateTime(), nullable=True), sa.Column('settings_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiments_name'), 'experiments', ['name'], unique=False) ### end Alembic commands ### def downgrade_test(): ### commands auto generated by Alembic - please adjust! ### op.drop_index(op.f('ix_experiments_name'), table_name='experiments') op.drop_table('experiments') op.drop_index(op.f('ix_experiment_things_experiment_id'), table_name='experiment_things') op.drop_table('experiment_things') op.drop_index(op.f('ix_experiment_actions_praw_key_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_experiment_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_action_subject_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_action_object_id'), table_name='experiment_actions') op.drop_table('experiment_actions') ### end Alembic commands ### def upgrade_production(): ### commands auto generated by Alembic - please adjust! ### op.create_table('experiment_actions', sa.Column('id', sa.Integer(), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('experiment_id', sa.Integer(), nullable=True), sa.Column('praw_key_id', sa.String(length=256), nullable=True), sa.Column('action_subject_type', sa.String(length=64), nullable=True), sa.Column('action_subject_id', sa.String(length=256), nullable=True), sa.Column('action_object_type', sa.String(length=64), nullable=True), sa.Column('action_object_id', sa.String(length=256), nullable=True), sa.Column('metadata_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiment_actions_action_object_id'), 'experiment_actions', ['action_object_id'], unique=False) op.create_index(op.f('ix_experiment_actions_action_subject_id'), 'experiment_actions', ['action_subject_id'], unique=False) op.create_index(op.f('ix_experiment_actions_experiment_id'), 'experiment_actions', ['experiment_id'], unique=False) op.create_index(op.f('ix_experiment_actions_praw_key_id'), 'experiment_actions', ['praw_key_id'], unique=False) op.create_table('experiment_things', sa.Column('id', sa.String(length=256), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('object_type', sa.Integer(), nullable=True), sa.Column('experiment_id', sa.Integer(), nullable=True), sa.Column('object_created', sa.DateTime(), nullable=True), sa.Column('metadata_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiment_things_experiment_id'), 'experiment_things', ['experiment_id'], unique=False) op.create_table('experiments', sa.Column('id', sa.Integer(), nullable=False), sa.Column('created_at', sa.DateTime(), nullable=True), sa.Column('name', sa.String(length=256), nullable=False), sa.Column('controller', sa.String(length=256), nullable=False), sa.Column('start_time', sa.DateTime(), nullable=True), sa.Column('end_time', sa.DateTime(), nullable=True), sa.Column('settings_json', mysql.MEDIUMTEXT(), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_index(op.f('ix_experiments_name'), 'experiments', ['name'], unique=False) ### end Alembic commands ### def downgrade_production(): ### commands auto generated by Alembic - please adjust! ### op.drop_index(op.f('ix_experiments_name'), table_name='experiments') op.drop_table('experiments') op.drop_index(op.f('ix_experiment_things_experiment_id'), table_name='experiment_things') op.drop_table('experiment_things') op.drop_index(op.f('ix_experiment_actions_praw_key_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_experiment_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_action_subject_id'), table_name='experiment_actions') op.drop_index(op.f('ix_experiment_actions_action_object_id'), table_name='experiment_actions') op.drop_table('experiment_actions') ### end Alembic commands ###

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null

0

1

0

1

0

null

0

7

ac37fa0e7b54f16872b8c3a76e823c12fe181827

168

py

Python

language-python-test/test/features/strings/raw_bytestring_v3.py

wbadart/language-python

6c048c215ff7fe4a5d5cc36ba3c17a666af74821

[ "BSD-3-Clause" ]

null

language-python-test/test/features/strings/raw_bytestring_v3.py

wbadart/language-python

6c048c215ff7fe4a5d5cc36ba3c17a666af74821

[ "BSD-3-Clause" ]

null

language-python-test/test/features/strings/raw_bytestring_v3.py

wbadart/language-python

6c048c215ff7fe4a5d5cc36ba3c17a666af74821

[ "BSD-3-Clause" ]

null

rb'hello \n world' rb"hello \n world" br'hello \n world' br"hello \n world" rb"""hello \n world""" br"""hello \n world""" rb'''hello \n world''' br'''hello \n world'''

18.666667

22

0.619048

32

168

3.25

0.15625

0.461538

0.846154

0.5

0.980769

0

0.142857

168

8

23

21

0.722222

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0.5

0

0.636364

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1

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true

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null

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1

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1

0

null

0

1

0

12

ac73ee6cf5e7e4f259b17d12c069fd5507386f56

20,817

py

Python

tests/test_xray.py

jfunez/packtools

3a5fe3fa5bcfb9dfdf57b7822e834d72bae28150

[ "BSD-2-Clause" ]

null

tests/test_xray.py

jfunez/packtools

3a5fe3fa5bcfb9dfdf57b7822e834d72bae28150

[ "BSD-2-Clause" ]

null

tests/test_xray.py

jfunez/packtools

3a5fe3fa5bcfb9dfdf57b7822e834d72bae28150

[ "BSD-2-Clause" ]

null

#coding: utf-8 import unittest import zipfile from tempfile import NamedTemporaryFile from lxml import etree import mocker from packtools import xray as x_ray def make_test_archive(arch_data): fp = NamedTemporaryFile() with zipfile.ZipFile(fp, 'w') as zipfp: for archive, data in arch_data: zipfp.writestr(archive, data) return fp class SPSMixinTests(mocker.MockerTestCase): def _makeOne(self, fname): class Foo(x_ray.SPSMixin, x_ray.Xray): pass return Foo(fname) def test_xmls_yields_etree_instances(self): data = [('bar.xml', b'<root><name>bar</name></root>')] arch = make_test_archive(data) pkg = self._makeOne(arch.name) xmls = pkg.xmls self.assertIsInstance(xmls.next(), etree._ElementTree) def test_xml_returns_etree_instance(self): data = [('bar.xml', b'<root><name>bar</name></root>')] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertIsInstance(pkg.xml, etree._ElementTree) def test_xml_raises_AttributeError_when_multiple_xmls(self): data = [ ('bar.xml', b'<root><name>bar</name></root>'), ('baz.xml', b'<root><name>baz</name></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertRaises(AttributeError, lambda: pkg.xml) def test_meta_journal_title_data_is_fetched(self): data = [ ('bar.xml', b'<root><journal-meta><journal-title-group><journal-title>foo</journal-title></journal-title-group></journal-meta></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertEqual(pkg.meta['journal_title'], 'foo') def test_meta_journal_title_is_None_if_not_present(self): data = [ ('bar.xml', b'<root></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertIsNone(pkg.meta['journal_title']) def test_meta_journal_eissn_data_is_fetched(self): data = [ ('bar.xml', b'<root><journal-meta><issn pub-type="epub">1234-1234</issn></journal-meta></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertEqual(pkg.meta['journal_eissn'], '1234-1234') def test_meta_journal_eissn_is_None_if_not_present(self): data = [ ('bar.xml', b'<root></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertIsNone(pkg.meta['journal_eissn']) def test_meta_journal_pissn_data_is_fetched(self): data = [ ('bar.xml', b'<root><journal-meta><issn pub-type="ppub">1234-1234</issn></journal-meta></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertEqual(pkg.meta['journal_pissn'], '1234-1234') def test_meta_journal_pissn_is_None_if_not_present(self): data = [ ('bar.xml', b'<root></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertIsNone(pkg.meta['journal_pissn']) def test_meta_article_title_data_is_fetched(self): data = [ ('bar.xml', b'<root><article-meta><title-group><article-title>bar</article-title></title-group></article-meta></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertEqual(pkg.meta['article_title'], 'bar') def test_meta_article_title_is_None_if_not_present(self): data = [ ('bar.xml', b'<root></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertIsNone(pkg.meta['article_title']) def test_meta_issue_year_data_is_fetched(self): data = [ ('bar.xml', b'<root><article-meta><pub-date><year>2013</year></pub-date></article-meta></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertEqual(pkg.meta['issue_year'], '2013') def test_meta_issue_year_is_None_if_not_present(self): data = [ ('bar.xml', b'<root></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertIsNone(pkg.meta['issue_year']) def test_meta_issue_volume_data_is_fetched(self): data = [ ('bar.xml', b'<root><article-meta><volume>2</volume></article-meta></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertEqual(pkg.meta['issue_volume'], '2') def test_meta_issue_volume_is_None_if_not_present(self): data = [ ('bar.xml', b'<root></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertIsNone(pkg.meta['issue_volume']) def test_meta_issue_number_data_is_fetched(self): data = [ ('bar.xml', b'<root><article-meta><issue>2</issue></article-meta></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertEqual(pkg.meta['issue_number'], '2') def test_meta_issue_number_is_None_if_not_present(self): data = [ ('bar.xml', b'<root></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertIsNone(pkg.meta['issue_number']) def test_meta_is_not_valid(self): data = [ ('bar.xml', b'<root></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertFalse(pkg.is_valid_meta()) def test_meta_is_valid(self): data = [ ('bar.xml', b'<root><journal-meta><issn pub-type="ppub">12-34</issn></journal-meta><article-meta><issue>3</issue><title-group><article-title>Titulo de artigo</article-title></title-group></article-meta></root>'), ] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertTrue(pkg.is_valid_meta()) def test_is_valid_schema_with_valid_xml(self): data = [('bar.xml', b'''<?xml version="1.0" encoding="utf-8"?> <article article-type="in-brief" dtd-version="1.0" xml:lang="en" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML"> <front> <journal-meta> <journal-id journal-id-type="nlm-ta">Bull World Health Organ</journal-id> <journal-title-group> <journal-title>Bulletin of the World Health Organization</journal-title> <abbrev-journal-title abbrev-type="pubmed">Bull. World Health Organ.</abbrev-journal-title> </journal-title-group> <issn pub-type="ppub">0042-9686</issn> <publisher> <publisher-name>World Health Organization</publisher-name> </publisher> </journal-meta> <article-meta> <article-id pub-id-type="publisher-id">BLT.13.000813</article-id> <article-id pub-id-type="doi">10.2471/BLT.13.000813</article-id> <article-categories> <subj-group subj-group-type="heading"> <subject> In This Month´s Bulletin</subject> </subj-group> </article-categories> <title-group> <article-title>In this month's <italic>Bulletin</italic> </article-title> </title-group> <pub-date pub-type="ppub"> <month>08</month> <year>2013</year> </pub-date> <volume>91</volume> <issue>8</issue> <fpage>545</fpage> <lpage>545</lpage> <permissions> <copyright-statement>(c) World Health Organization (WHO) 2013. All rights reserved.</copyright-statement> <copyright-year>2013</copyright-year> </permissions> </article-meta> </front> <body> <p>In the editorial section, David B Evans and colleagues (546) discuss the dimensions of universal health coverage. In the news, Gary Humphreys & Catherine Fiankan-Bokonga (549–550) report on the approach France is taking to counter trends in childhood obesity. Fiona Fleck (551–552) interviews Philip James on how the global obesity epidemic started and what should be done to reverse it.</p> <sec sec-type="other1"> <title>Nigeria</title> </sec> </body> </article> ''')] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertTrue(pkg.is_valid_schema()) def test_is_valid_schema_with_invalid_xml(self): data = [('bar.xml', b'''<?xml version="1.0" encoding="utf-8"?> <article article-type="in-brief" dtd-version="1.0" xml:lang="en" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML"> <front> <journal-meta> <journal-title-group> <journal-title>Bulletin of the World Health Organization</journal-title> <abbrev-journal-title abbrev-type="pubmed">Bull. World Health Organ.</abbrev-journal-title> </journal-title-group> <issn pub-type="ppub">0042-9686</issn> <publisher> <publisher-name>World Health Organization</publisher-name> </publisher> </journal-meta> <article-meta> <article-id pub-id-type="publisher-id">BLT.13.000813</article-id> <article-id pub-id-type="doi">10.2471/BLT.13.000813</article-id> <article-categories> <subj-group subj-group-type="heading"> <subject> In This Month´s Bulletin</subject> </subj-group> </article-categories> <title-group> <article-title>In this month's <italic>Bulletin</italic> </article-title> </title-group> <pub-date pub-type="ppub"> <month>08</month> <year>2013</year> </pub-date> <volume>91</volume> <issue>8</issue> <fpage>545</fpage> <lpage>545</lpage> <permissions> <copyright-statement>(c) World Health Organization (WHO) 2013. All rights reserved.</copyright-statement> <copyright-year>2013</copyright-year> </permissions> </article-meta> </front> <body> <p>In the editorial section, David B Evans and colleagues (546) discuss the dimensions of universal health coverage. In the news, Gary Humphreys & Catherine Fiankan-Bokonga (549–550) report on the approach France is taking to counter trends in childhood obesity. Fiona Fleck (551–552) interviews Philip James on how the global obesity epidemic started and what should be done to reverse it.</p> <sec sec-type="other1"> <title>Nigeria</title> </sec> </body> </article> ''')] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertFalse(pkg.is_valid_schema()) def test_is_valid_schema_with_wrong_tag(self): data = [('bar.xml', b'''<?xml version="1.0" encoding="utf-8"?> <article article-type="in-brief" dtd-version="1.0" xml:lang="en" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML"> <front> <a>wrong</a> <journal-meta> <journal-title-group> <journal-title>Bulletin of the World Health Organization</journal-title> <abbrev-journal-title abbrev-type="pubmed">Bull. World Health Organ.</abbrev-journal-title> </journal-title-group> <issn pub-type="ppub">0042-9686</issn> <publisher> <publisher-name>World Health Organization</publisher-name> </publisher> </journal-meta> <article-meta> <article-id pub-id-type="publisher-id">BLT.13.000813</article-id> <article-id pub-id-type="doi">10.2471/BLT.13.000813</article-id> <article-categories> <subj-group subj-group-type="heading"> <subject> In This Month´s Bulletin</subject> </subj-group> </article-categories> <title-group> <article-title>In this month's <italic>Bulletin</italic> </article-title> </title-group> <pub-date pub-type="ppub"> <month>08</month> <year>2013</year> </pub-date> <volume>91</volume> <issue>8</issue> <fpage>545</fpage> <lpage>545</lpage> <permissions> <copyright-statement>(c) World Health Organization (WHO) 2013. All rights reserved.</copyright-statement> <copyright-year>2013</copyright-year> </permissions> </article-meta> </front> <body> <p>In the editorial section, David B Evans and colleagues (546) discuss the dimensions of universal health coverage. In the news, Gary Humphreys & Catherine Fiankan-Bokonga (549–550) report on the approach France is taking to counter trends in childhood obesity. Fiona Fleck (551–552) interviews Philip James on how the global obesity epidemic started and what should be done to reverse it.</p> <sec sec-type="other1"> <title>Nigeria</title> </sec> </body> </article> ''')] arch = make_test_archive(data) pkg = self._makeOne(arch.name) self.assertFalse(pkg.is_valid_schema()) class XrayTests(mocker.MockerTestCase): def _make_test_archive(self, arch_data): fp = NamedTemporaryFile() with zipfile.ZipFile(fp, 'w') as zipfp: for archive, data in arch_data: zipfp.writestr(archive, data) return fp def test_non_zip_archive_raises_ValueError(self): fp = NamedTemporaryFile() self.assertRaises(ValueError, lambda: x_ray.Xray(fp.name)) def test_get_ext_returns_member_names(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertEquals(xray.get_ext('xml'), ['bar.xml']) def test_get_ext_returns_empty_when_ext_doesnot_exist(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertEquals(xray.get_ext('jpeg'), []) def test_get_fps_returns_an_iterable(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) fps = xray.get_fps('xml') self.assertTrue(hasattr(fps, 'next')) def test_get_fpd_yields_ZipExtFile_instances(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) fps = xray.get_fps('xml') self.assertIsInstance(fps.next(), zipfile.ZipExtFile) def test_get_fps_swallow_exceptions_when_ext_doesnot_exist(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) fps = xray.get_fps('jpeg') self.assertRaises(StopIteration, lambda: fps.next()) def test_package_checksum_is_calculated(self): data = [('bar.xml', b'<root><name>bar</name></root>')] arch1 = make_test_archive(data) arch2 = make_test_archive(data) self.assertEquals( x_ray.Xray(arch1.name).checksum, x_ray.Xray(arch2.name).checksum ) def test_get_members(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertEquals(xray.get_members(), ['bar.xml', 'jar.xml']) def test_get_members_returns_empty(self): arch = make_test_archive([]) xray = x_ray.Xray(arch.name) self.assertEquals(xray.get_members(), []) def test_get_fp(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertIsInstance(xray.get_fp('bar.xml'), zipfile.ZipExtFile) def test_get_fp_nonexisting_members(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertRaises(ValueError, lambda: xray.get_fp('foo.xml')) def test_get_classified_members(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.xml', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertEquals(xray.get_classified_members(), {'xml': ['bar.xml', 'jar.xml']}) def test_get_ext_is_caseinsensitive(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.XML', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertEquals(xray.get_ext('xml'), ['bar.xml', 'jar.XML']) def test_get_ext_arg_is_caseinsensitive(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.XML', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertEquals(xray.get_ext('XML'), ['bar.xml', 'jar.XML']) def test_get_classified_members_is_caseinsensitive(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.XML', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) self.assertEquals(xray.get_classified_members(), {'xml': ['bar.xml', 'jar.XML']}) def test_get_fps_is_caseinsensitive(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.XML', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) fps = xray.get_fps('xml') self.assertEqual([fp.name for fp in fps], ['bar.xml', 'jar.XML']) def test_get_fps_arg_is_caseinsensitive(self): arch = make_test_archive( [('bar.xml', b'<root><name>bar</name></root>'), ('jar.XML', b'<root><name>bar</name></root>')]) xray = x_ray.Xray(arch.name) fps = xray.get_fps('XML') self.assertEqual([fp.name for fp in fps], ['bar.xml', 'jar.XML'])

40.032692

433

0.543978

2,416

20,817

4.527318

0.104719

0.017188

0.032181

0.064271

0.869446

0.826019

0.814043

0.808466

0.807003

0.806455

0

0.023581

0.315511

20,817

519

434

40.109827

0.743842

0.000624

0

0.690244

0

0.060976

0.533724

0.158983

0

0.095122

0

null

0.002439

0.014634

null

0

null

0

1

0

null

0

1

0

7

ac76f98e25d85405ee60b2f84b3d915d5130838a

14,520

py

Python

p4v1_1/simple_router/send2.py

vibhaa/iw15

c2a316499dbd3e7459aed2cacf0612df0b7dcec2

[ "Apache-2.0" ]

14

2019-02-25T22:42:15.000Z

2021-12-22T06:29:20.000Z

p4v1_1/simple_router/send2.py

vibhaa/iw15

c2a316499dbd3e7459aed2cacf0612df0b7dcec2

[ "Apache-2.0" ]

null

p4v1_1/simple_router/send2.py

vibhaa/iw15

c2a316499dbd3e7459aed2cacf0612df0b7dcec2

[ "Apache-2.0" ]

8

2018-11-25T11:42:24.000Z

2021-03-11T07:23:21.000Z

#!/usr/bin/python # Copyright 2013-present Barefoot Networks, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from scapy.all import sniff, sendp from scapy.all import Packet from scapy.all import ShortField, IntField, LongField, BitField from scapy.all import Ether, IP, TCP import networkx as nx import sys def main(): if len(sys.argv) != 1: print "Usage: send2.py" sys.exit(1) srcmac = '00:aa:bb:00:00:00' dstmac = '00:aa:bb:00:00:01' port = 80 msg = 'hi' p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '111.37.250.218', dst = '3.248.234.184') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '142.54.3.18', dst = '35.240.203.247') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '112.119.163.206', dst = '1.102.89.68') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '111.37.250.218', dst = '3.248.234.184') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '205.38.229.41', dst = '66.216.25.163') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '6.172.207.28', dst = '208.89.117.253') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.139.101.173', dst = '1.0.3.222') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '148.92.117.249', dst = '1.102.127.50') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '194.253.242.112', dst = '153.193.46.216') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '111.37.250.218', dst = '3.248.234.184') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '111.37.250.218', dst = '3.248.234.184') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '113.169.241.172', dst = '1.96.222.132') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '30.187.70.176', dst = '1.96.166.240') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '129.201.147.168', dst = '43.239.238.254') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '15.83.232.209', dst = '153.193.117.43') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '117.91.221.69', dst = '1.96.228.67') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '112.65.110.243', dst = '1.96.222.237') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '122.138.7.7', dst = '3.151.114.131') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '197.78.57.215', dst = '66.216.25.163') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '207.137.47.98', dst = '1.96.223.52') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '116.209.201.217', dst = '66.216.25.163') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '111.37.250.218', dst = '3.248.234.184') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '205.38.229.188', dst = '66.216.25.163') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '207.157.173.33', dst = '1.96.167.17') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '39.183.184.70', dst = '1.96.167.9') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '194.253.242.112', dst = '153.193.46.216') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '173.162.174.71', dst = '102.14.133.117') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.139.101.102', dst = '1.34.248.21') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '102.1.84.90', dst = '43.206.171.27') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '128.25.115.194', dst = '1.96.167.56') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '111.229.0.142', dst = '5.252.90.214') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '128.29.115.116', dst = '1.96.223.248') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '111.37.250.218', dst = '3.248.234.184') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '207.137.52.25', dst = '1.96.166.173') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '102.6.32.157', dst = '221.46.220.102') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '102.6.32.157', dst = '221.46.220.102') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '100.159.187.56', dst = '208.89.121.171') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '183.190.174.107', dst = '1.150.209.83') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '111.209.150.229', dst = '210.108.56.240') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '109.147.8.232', dst = '1.2.38.184') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '128.37.184.30', dst = '1.96.223.239') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '116.209.201.171', dst = '66.216.25.163') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '102.0.115.0', dst = '111.205.228.129') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '205.38.229.94', dst = '66.216.25.163') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '197.78.57.35', dst = '66.216.25.163') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '112.111.179.170', dst = '1.96.223.36') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '184.21.123.130', dst = '211.106.242.60') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '117.92.23.134', dst = '1.45.68.235') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '112.111.179.170', dst = '1.96.223.36') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '194.253.242.112', dst = '153.193.46.216') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.139.101.123', dst = '1.81.56.123') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '13.1.149.6', dst = '1.96.164.152') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '128.37.184.30', dst = '1.96.223.239') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.139.101.102', dst = '1.13.5.138') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '119.10.57.179', dst = '43.233.106.124') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '204.103.13.219', dst = '221.46.221.163') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '128.61.59.69', dst = '1.96.223.133') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.139.101.170', dst = '1.0.227.102') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '113.181.185.162', dst = '1.39.174.181') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '73.149.65.226', dst = '210.108.49.161') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '43.255.233.20', dst = '221.46.220.203') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '119.238.4.231', dst = '1.96.167.6') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '130.77.108.26', dst = '1.146.59.107') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '153.193.150.99', dst = '221.46.220.227') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '207.157.173.33', dst = '1.96.167.17') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '119.236.185.197', dst = '1.96.223.248') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '130.77.108.26', dst = '1.146.59.107') / msg sendp(p, iface = "veth0", verbose = 0) p = Ether(src=srcmac, dst=dstmac, type=0x0800) / IP(src = '74.90.63.201', dst = '210.108.56.240') / msg sendp(p, iface = "veth0", verbose = 0) if __name__ == '__main__': main()

66.605505

110

0.598691

2,477

14,520

3.506258

0.119096

0.061485

0.092228

0.153713

0.832355

0.830052

0

0.21001

0.192287

14,520

217

111

66.912442

0.530525

0.040427

0

0.675258

0

0.204684

0

0.038365

0

null

0

0.030928

null

0.005155

0

null

0

1

0

1

0

null

0

1

0

8

3baba84140516ff4c6c30f4ef6a9d363d405a779

4,839

py

Python

day11/main.py

ogun/advent-of-code-2020

1dcf268f9f1f6cd7c46d442b6aaa9b19ec5b2cf1

[ "MIT" ]

4

2020-12-03T13:22:12.000Z

2020-12-22T21:51:49.000Z

day11/main.py

ogun/advent-of-code-2020

1dcf268f9f1f6cd7c46d442b6aaa9b19ec5b2cf1

[ "MIT" ]

null

day11/main.py

ogun/advent-of-code-2020

1dcf268f9f1f6cd7c46d442b6aaa9b19ec5b2cf1

[ "MIT" ]

1

2020-12-12T13:41:12.000Z

from copy import deepcopy import day11.data as data def part1(): value = data.INPUT def get_neigbours(col, row, col_length, row_length): neigbours = [] for col_idx in range(col - 1, col + 2): for row_idx in range(row - 1, row + 2): if ( -1 in [col_idx, row_idx] or col_idx == col_length or row_idx == row_length ): continue if (col, row) == (col_idx, row_idx): continue neigbours.append((col_idx, row_idx)) return neigbours def next_step(value): result = deepcopy(value) for row_idx, row in enumerate(value): for col_idx, col in enumerate(row): current = value[row_idx][col_idx] if current == ".": continue neigbours = get_neigbours(col_idx, row_idx, len(value[0]), len(value)) occupied_seats = sum(1 for n in neigbours if value[n[1]][n[0]] == "#") if current == "L" and occupied_seats == 0: result[row_idx][col_idx] = "#" continue if current == "#" and occupied_seats > 3: result[row_idx][col_idx] = "L" continue return result next_value = next_step(value) while value != next_value: value = deepcopy(next_value) next_value = next_step(value) return sum(1 for r in value for c in r if c == "#") def part2(): value = data.INPUT def get_neigbours(col, row, col_length, row_length): neigbours = [] seats = ["L", "#"] # Up for row_idx in range(row - 1, -1, -1): if value[row_idx][col] in seats: neigbours.append((col, row_idx)) break # Down for row_idx in range(row + 1, row_length): if value[row_idx][col] in seats: neigbours.append((col, row_idx)) break # Left for col_idx in range(col - 1, -1, -1): if value[row][col_idx] in seats: neigbours.append((col_idx, row)) break # Right for col_idx in range(col + 1, col_length): if value[row][col_idx] in seats: neigbours.append((col_idx, row)) break # Up-Left for step in range(1, max(col_length, row_length)): col_idx = col - step row_idx = row - step if not (col_idx > -1 and row_idx > -1): break if value[row_idx][col_idx] in seats: neigbours.append((col_idx, row_idx)) break # Up-Right for step in range(1, max(col_length, row_length)): col_idx = col + step row_idx = row - step if not (col_idx < col_length and row_idx > -1): break if value[row_idx][col_idx] in seats: neigbours.append((col_idx, row_idx)) break # Down-Left for step in range(1, max(col_length, row_length)): col_idx = col - step row_idx = row + step if not (col_idx > -1 and row_idx < row_length): break if value[row_idx][col_idx] in seats: neigbours.append((col_idx, row_idx)) break # Down-Right for step in range(1, max(col_length, row_length)): col_idx = col + step row_idx = row + step if not (col_idx < col_length and row_idx < row_length): break if value[row_idx][col_idx] in seats: neigbours.append((col_idx, row_idx)) break return neigbours def next_step(value): result = deepcopy(value) for row_idx, row in enumerate(value): for col_idx, col in enumerate(row): current = value[row_idx][col_idx] if current == ".": continue neigbours = get_neigbours(col_idx, row_idx, len(value[0]), len(value)) occupied_seats = sum(1 for n in neigbours if value[n[1]][n[0]] == "#") if current == "L" and occupied_seats == 0: result[row_idx][col_idx] = "#" continue if current == "#" and occupied_seats > 4: result[row_idx][col_idx] = "L" continue return result next_value = next_step(value) while value != next_value: value = deepcopy(next_value) next_value = next_step(value) return sum(1 for r in value for c in r if c == "#")

28.633136

86

0.49349

601

4,839

3.777038

0.088186

0.097797

0.047577

0.052863

0.917621

0.903965

0.886344

0.845815

0

0.013636

0.408969

4,839

168

87

28.803571

0.78007

0.011573

0

0.798246

0

0.003351

0

1

0.052632

false

0

0.017544

0

0.122807

0

null

0

1

0

1

0

null

0

7

3be419ebc9aa8f6d5afe92154cfdcde28af9526c

95

py

Python

DTMT/dtmt/layers/__init__.py

fandongmeng/StackedDTMT

f10062f98a443ad67cadec68fa5abdc8ab60815f

[ "BSD-3-Clause" ]

3

2020-09-22T07:33:29.000Z

2021-02-19T09:53:28.000Z

DTMT/dtmt/layers/__init__.py

fandongmeng/StackedDTMT

f10062f98a443ad67cadec68fa5abdc8ab60815f

[ "BSD-3-Clause" ]

null

DTMT/dtmt/layers/__init__.py

fandongmeng/StackedDTMT

f10062f98a443ad67cadec68fa5abdc8ab60815f

[ "BSD-3-Clause" ]

null

# coding=utf-8 import dtmt.layers.attention import dtmt.layers.nn import dtmt.layers.rnn_cell

15.833333

28

0.810526

16

95

4.75

0.625

0.394737

0.631579

0

0.011628

0.094737

95

5

29

19

0.872093

0.126316

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

020cabf3902fc7fd00975c8bf6c6b0d16e8eff81

85,205

py

Python

tests/providers/figshare/test_provider.py

west1636/RDM-waterbutler

6ed22cd52eda8a9665a29615f9b2e623dcae3b29

[ "Apache-2.0" ]

65

2015-01-23T03:22:04.000Z

2022-01-11T22:33:19.000Z

tests/providers/figshare/test_provider.py

cslzchen/waterbutler

e4e07727e06885a752c9251e5731f5627f646da3

[ "Apache-2.0" ]

300

2015-02-16T16:45:02.000Z

2022-01-31T14:49:07.000Z

tests/providers/figshare/test_provider.py

cslzchen/waterbutler

e4e07727e06885a752c9251e5731f5627f646da3

[ "Apache-2.0" ]

76

2015-01-20T20:45:17.000Z

2021-07-30T13:18:10.000Z

import io import json import pytest import aiohttpretty from waterbutler.core import streams from waterbutler.core import exceptions from waterbutler.providers.figshare import metadata from waterbutler.providers.figshare import provider from waterbutler.providers.figshare.path import FigsharePath from waterbutler.providers.figshare.settings import MAX_PAGE_SIZE from tests.providers.figshare.fixtures import (crud_fixtures, error_fixtures, project_list_articles, root_provider_fixtures, project_article_type_1_metadata, project_article_type_3_metadata, project_article_type_1_file_metadata, project_article_type_3_file_metadata) @pytest.fixture def auth(): return { 'name': 'cat', 'email': 'cat@cat.com', 'callback_url': 'http://sup.com/api/v1/project/v8s9q/waterbutler/logs/', 'id': 'fakey', } @pytest.fixture def credentials(): return { 'token': 'freddie', } @pytest.fixture def project_settings(): return { 'container_type': 'project', 'container_id': '13423', } @pytest.fixture def project_settings_2(): return { 'container_type': 'project', 'container_id': '64916', } @pytest.fixture def article_settings(): return { 'container_type': 'article', 'container_id': '4037952', } @pytest.fixture def project_provider(auth, credentials, project_settings): return provider.FigshareProvider(auth, credentials, project_settings) @pytest.fixture def project_provider_2(auth, credentials, project_settings_2): return provider.FigshareProvider(auth, credentials, project_settings_2) @pytest.fixture def article_provider(auth, credentials, article_settings): return provider.FigshareProvider(auth, credentials, article_settings) @pytest.fixture def file_content(): return b'sleepy' @pytest.fixture def file_like(file_content): return io.BytesIO(file_content) @pytest.fixture def file_stream(file_like): return streams.FileStreamReader(file_like) class TestPolymorphism: def test_project_provider(self, project_settings, project_provider): assert isinstance(project_provider, provider.FigshareProjectProvider) assert project_provider.container_id == project_settings['container_id'] def test_article_provider(self, article_settings, article_provider): assert isinstance(article_provider, provider.FigshareArticleProvider) assert article_provider.container_id == article_settings['container_id'] class TestProjectV1ValidatePath: @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v1_path_folder_article(self, project_provider, root_provider_fixtures): item = root_provider_fixtures['folder_article_metadata'] file_id = str(item['id']) path = '/{}/'.format(file_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(False, *article_segments) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=item) result = await project_provider.validate_v1_path(path) expected = FigsharePath('/{}/'.format(item['title']), _ids=(project_provider.container_id, file_id), folder=True, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v1_path_folder_article_bad_path(self, project_provider, root_provider_fixtures): item = root_provider_fixtures['folder_article_metadata'] file_id = str(item['id']) path = '/{}'.format(file_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(False, *article_segments) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=item) with pytest.raises(exceptions.NotFoundError) as e: await project_provider.validate_v1_path(path) assert e.value.code == 404 assert aiohttpretty.has_call(method='GET', uri=article_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v1_path_folder_article_bad_type(self, project_provider, root_provider_fixtures): item = root_provider_fixtures['folder_article_metadata'] file_id = str(item['id']) path = '/{}/'.format(file_id) item['defined_type'] = 5 article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(False, *article_segments) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=item) with pytest.raises(exceptions.NotFoundError) as e: await project_provider.validate_v1_path(path) assert e.value.code == 404 assert aiohttpretty.has_call(method='GET', uri=article_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_validate_v1_path_root(self, project_provider): path = '/' result = await project_provider.validate_v1_path(path) expected = FigsharePath(path, _ids=('', ), folder=True, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_validate_v1_path_invalid_path(self, article_provider): with pytest.raises(exceptions.InvalidPathError) as e: await article_provider.validate_v1_path('/this/is/an/invalid/path') assert e.value.code == 400 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v1_path_invalid_path(self, project_provider): path = 'whatever' with pytest.raises(exceptions.InvalidPathError) as e: await project_provider.validate_v1_path(path) assert e.value.code == 400 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v1_path_file_article(self, project_provider, root_provider_fixtures): file_item = root_provider_fixtures['file_metadata'] item = root_provider_fixtures['file_article_metadata'] file_id = str(item['files'][0]['id']) article_id = str(item['id']) path = '/{}/{}'.format(article_id, file_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(False, *article_segments, 'files', file_id) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=file_item) result = await project_provider.validate_v1_path(path) expected = FigsharePath('/{}/{}'.format(item['title'], file_item['name']), _ids=(project_provider.container_id, file_id), folder=False, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v1_path_file_article_public(self, project_provider, root_provider_fixtures): file_item = root_provider_fixtures['file_metadata_public'] item = root_provider_fixtures['file_article_metadata'] file_id = str(file_item['id']) article_id = str(item['id']) path = '/{}/{}'.format(article_id, file_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(True, *article_segments, 'files', file_id) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['public_list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=file_item) result = await project_provider.validate_v1_path(path) expected = FigsharePath('/{}/{}'.format(item['title'], file_item['name']), _ids=(project_provider.container_id, file_id), folder=False, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v1_path_file_article_bad_path(self, project_provider, root_provider_fixtures): file_item = root_provider_fixtures['file_metadata'] item = root_provider_fixtures['file_article_metadata'] file_id = str(item['files'][0]['id']) article_id = str(item['id']) path = '/{}/{}/'.format(article_id, file_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(False, *article_segments, 'files', file_id) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=file_item) with pytest.raises(exceptions.NotFoundError) as e: await project_provider.validate_v1_path(path) assert e.value.code == 404 class TestArticleV1ValidatePath: @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_validate_v1_path_root(self, article_provider): path = '/' result = await article_provider.validate_v1_path(path) expected = FigsharePath(path, _ids=('', ), folder=True, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_validate_v1_path(self, article_provider, root_provider_fixtures): item = root_provider_fixtures['file_metadata'] file_id = item['id'] path = '/' + str(file_id) url = article_provider.build_url(False, *article_provider.root_path_parts, 'files', str(file_id)) aiohttpretty.register_json_uri('GET', url, body=item) result = await article_provider.validate_v1_path(path) expected = FigsharePath('/' + item['name'], _ids=('', file_id), folder=False, is_public=False) assert result == expected class TestProjectV0ValidatePath: @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v0_path_folder_article(self, project_provider, root_provider_fixtures): item = root_provider_fixtures['folder_article_metadata'] file_id = str(item['id']) path = '/{}/'.format(file_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(False, *article_segments) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=item) result = await project_provider.validate_path(path) expected = FigsharePath('/{}/'.format(item['title']), _ids=(project_provider.container_id, file_id), folder=True, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v0_path_folder_article_bad_path(self, project_provider, root_provider_fixtures): bad_article_id = '000000000' path = '/{}'.format(bad_article_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', bad_article_id) article_url = project_provider.build_url(False, *article_segments) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, status=404) result = await project_provider.validate_path(path) expected = FigsharePath(path, _ids=('', ''), folder=True, is_public=False) assert result == expected assert aiohttpretty.has_call(method='GET', uri=article_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_validate_v0_path_root(self, project_provider): path = '/' result = await project_provider.validate_path(path) expected = FigsharePath(path, _ids=('', ), folder=True, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_validate_v0_path_invalid_path(self, article_provider): with pytest.raises(exceptions.InvalidPathError) as e: await article_provider.validate_path('/this/is/an/invalid/path') assert e.value.code == 400 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v0_path_invalid_path(self, project_provider): path = 'whatever' with pytest.raises(exceptions.InvalidPathError) as e: await project_provider.validate_path(path) assert e.value.code == 400 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v0_path_file_article(self, project_provider, root_provider_fixtures): file_item = root_provider_fixtures['file_metadata'] item = root_provider_fixtures['file_article_metadata'] file_id = str(item['files'][0]['id']) article_id = str(item['id']) path = '/{}/{}'.format(article_id, file_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(False, *article_segments, 'files', file_id) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=file_item) result = await project_provider.validate_path(path) expected = FigsharePath('/{}/{}'.format(item['title'], file_item['name']), _ids=(project_provider.container_id, file_id), folder=False, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_validate_v0_path_file_article_public(self, project_provider, root_provider_fixtures): file_item = root_provider_fixtures['file_metadata_public'] item = root_provider_fixtures['file_article_metadata'] file_id = str(file_item['id']) article_id = str(item['id']) path = '/{}/{}'.format(article_id, file_id) article_list_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') article_segments = (*project_provider.root_path_parts, 'articles', str(item['id'])) article_url = project_provider.build_url(True, *article_segments, 'files', file_id) aiohttpretty.register_json_uri('GET', article_list_url, body=root_provider_fixtures['public_list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_list_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', article_url, body=file_item) result = await project_provider.validate_path(path) expected = FigsharePath('/{}/{}'.format(item['title'], file_item['name']), _ids=(project_provider.container_id, file_id), folder=False, is_public=False) assert result == expected class TestArticleV0ValidatePath: @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_validate_v0_path_root(self, article_provider): path = '/' result = await article_provider.validate_path(path) expected = FigsharePath(path, _ids=('', ), folder=True, is_public=False) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_validate_v0_path(self, article_provider, root_provider_fixtures): item = root_provider_fixtures['file_metadata'] file_id = item['id'] path = '/' + str(file_id) url = article_provider.build_url(False, *article_provider.root_path_parts, 'files', str(file_id)) aiohttpretty.register_json_uri('GET', url, body=item) result = await article_provider.validate_path(path) expected = FigsharePath('/' + item['name'], _ids=('', file_id), folder=False, is_public=False) assert result == expected class TestProjectMetadata: @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_contents(self, project_provider_2, project_list_articles, project_article_type_1_metadata, project_article_type_3_metadata): """Test content listings for a project root. """ root_parts = project_provider_2.root_path_parts # Register the requests that retrieve the article list of a project. list_articles_url = project_provider_2.build_url(False, *root_parts, 'articles') aiohttpretty.register_json_uri('GET', list_articles_url, body=project_list_articles['page1'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', list_articles_url, body=project_list_articles['page2'], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', list_articles_url, body=[], params={'page': '3', 'page_size': str(MAX_PAGE_SIZE)}) # Register the requests that retrieve the metadata for each item in the article list. article_id_1 = str(project_list_articles['page1'][0]['id']) article_url_1 = project_provider_2.build_url(False, *root_parts, 'articles', article_id_1) article_meta_1 = project_article_type_1_metadata['private'] aiohttpretty.register_json_uri('GET', article_url_1, body=article_meta_1) article_id_2 = str(project_list_articles['page1'][1]['id']) article_url_2 = project_provider_2.build_url(False, *root_parts, 'articles', article_id_2) article_meta_2 = project_article_type_1_metadata['public'] aiohttpretty.register_json_uri('GET', article_url_2, body=article_meta_2) article_id_3 = str(project_list_articles['page2'][0]['id']) article_url_3 = project_provider_2.build_url(False, *root_parts, 'articles', article_id_3) article_meta_3 = project_article_type_3_metadata['private'] aiohttpretty.register_json_uri('GET', article_url_3, body=article_meta_3) article_id_4 = str(project_list_articles['page2'][1]['id']) article_url_4 = project_provider_2.build_url(False, *root_parts, 'articles', article_id_4) article_meta_4 = project_article_type_3_metadata['public'] aiohttpretty.register_json_uri('GET', article_url_4, body=article_meta_4) # The ``metadata()`` call to test path = FigsharePath('/', _ids=(''), folder=True) metadata_list = (await project_provider_2.metadata(path)).sort(key=lambda x: x.path) assert aiohttpretty.has_call(method='GET', uri=list_articles_url, params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) assert aiohttpretty.has_call(method='GET', uri=list_articles_url, params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) assert aiohttpretty.has_call(method='GET', uri=list_articles_url, params={'page': '3', 'page_size': str(MAX_PAGE_SIZE)}) assert aiohttpretty.has_call(method='GET', uri=article_url_1) assert aiohttpretty.has_call(method='GET', uri=article_url_2) assert aiohttpretty.has_call(method='GET', uri=article_url_3) assert aiohttpretty.has_call(method='GET', uri=article_url_4) expected = ([ metadata.FigshareFileMetadata( project_article_type_1_metadata['public'], raw_file=project_article_type_1_metadata['public']['files'][0] ), metadata.FigshareFileMetadata( project_article_type_1_metadata['private'], raw_file=project_article_type_1_metadata['private']['files'][0] ), metadata.FigshareFolderMetadata(project_article_type_3_metadata['public']), metadata.FigshareFolderMetadata(project_article_type_3_metadata['private']) ]).sort(key=lambda x: x.path) assert metadata_list == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_metadata_invalid_figshare_path(self, project_provider_2): """Test that figshare path can at most have three levels (including root itself). """ path = FigsharePath('/folder_lvl_1/folder_lvl_2/file_lvl_3.txt', _ids=('1', '2', '3', '4', ), folder=False, is_public=False) with pytest.raises(exceptions.NotFoundError) as e: await project_provider_2.metadata(path) assert e.value.code == 404 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_metadata_bad_article_response(self, project_provider_2): """Test handling 404 response for figshare article request. """ root_parts = project_provider_2.root_path_parts path = FigsharePath('/article_name/file_name', _ids=('1', '2', '3'), folder=False, is_public=False) article_url = project_provider_2.build_url(path.is_public, *root_parts, 'articles', path.parts[1].identifier) aiohttpretty.register_json_uri('GET', article_url, status=404) with pytest.raises(exceptions.NotFoundError) as e: await project_provider_2.metadata(path) assert aiohttpretty.has_call(method='GET', uri=article_url) assert e.value.code == 404 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_folder_article_file(self, project_provider_2, project_article_type_1_metadata, project_article_type_1_file_metadata): """Test metadata for a file that belongs to an article of file type. """ root_parts = project_provider_2.root_path_parts article_meta_json = project_article_type_1_metadata['private'] file_meta_json = project_article_type_1_file_metadata['private'] article_id = str(article_meta_json['id']) article_name = article_meta_json['title'] file_id = str(file_meta_json['id']) file_name = file_meta_json['name'] article_meta_url = project_provider_2.build_url(False, *root_parts, 'articles', article_id) aiohttpretty.register_json_uri('GET', article_meta_url, body=article_meta_json) path = FigsharePath('/{}/{}'.format(article_name, file_name), _ids=('', article_id, file_id), folder=False, is_public=False) result = await project_provider_2.metadata(path) expected = metadata.FigshareFileMetadata(article_meta_json, file_meta_json) assert aiohttpretty.has_call(method='GET', uri=article_meta_url) assert result == expected assert str(result.id) == file_id assert result.name == file_name assert result.path == '/{}/{}'.format(article_id, file_id) assert result.materialized_path == '/{}/{}'.format(article_name, file_name) assert str(result.article_id) == article_id assert result.article_name == article_name assert result.size == file_meta_json['size'] assert result.is_public == (article_meta_json['published_date'] is not None) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_folder_article_file_not_found(self, project_provider_2, project_article_type_3_metadata, project_article_type_3_file_metadata): """Test the error case where the file is not found in the article's file list. """ root_parts = project_provider_2.root_path_parts article_meta_json = project_article_type_3_metadata['private'] article_meta_json['files'] = [] article_id = str(article_meta_json['id']) article_name = article_meta_json['title'] file_id = str(project_article_type_3_file_metadata['private']['id']) file_name = project_article_type_3_file_metadata['private']['name'] article_meta_url = project_provider_2.build_url(False, *root_parts, 'articles', article_id) aiohttpretty.register_json_uri('GET', article_meta_url, body=article_meta_json) path = FigsharePath('/{}/{}'.format(article_name, file_name), _ids=('', article_id, file_id), folder=False, is_public=False) with pytest.raises(exceptions.NotFoundError) as e: await project_provider_2.metadata(path) assert aiohttpretty.has_call(method='GET', uri=article_meta_url) assert e.value.code == 404 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_folder_article_type_error(self, project_provider, project_article_type_3_metadata): """Test the error case where the folder article is of a wrong type. """ root_parts = project_provider.root_path_parts article_meta_json = project_article_type_3_metadata['private'] article_meta_json['defined_type'] = 15 article_id = str(article_meta_json['id']) article_name = article_meta_json['title'] article_meta_url = project_provider.build_url(False, *root_parts, 'articles', article_id) aiohttpretty.register_json_uri('GET', article_meta_url, body=article_meta_json) path = FigsharePath('/{}'.format(article_name), _ids=('', article_id), folder=True, is_public=False) with pytest.raises(exceptions.NotFoundError) as e: await project_provider.metadata(path) assert aiohttpretty.has_call(method='GET', uri=article_meta_url) assert e.value.code == 404 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_folder_article_contents(self, project_provider_2, project_article_type_3_metadata): """Test content listing for an article of folder type. """ root_parts = project_provider_2.root_path_parts article_meta_json = project_article_type_3_metadata['private'] article_id = str(article_meta_json['id']) article_name = article_meta_json['title'] article_meta_url = project_provider_2.build_url(False, *root_parts, 'articles', article_id) aiohttpretty.register_json_uri('GET', article_meta_url, body=article_meta_json) path = FigsharePath('/{}'.format(article_name), _ids=('', article_id), folder=True, is_public=False) result = (await project_provider_2.metadata(path)).sort(key=lambda x: x.path) expected = ([ metadata.FigshareFileMetadata(article_meta_json, raw_file=article_meta_json['files'][0]), metadata.FigshareFileMetadata(article_meta_json, raw_file=article_meta_json['files'][1]) ]).sort(key=lambda x: x.path) assert aiohttpretty.has_call(method='GET', uri=article_meta_url) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_folder_article_file(self, project_provider_2, project_article_type_3_metadata, project_article_type_3_file_metadata): """Test metadata for a file that belongs to an article of folder type. """ root_parts = project_provider_2.root_path_parts article_meta_json = project_article_type_3_metadata['private'] file_meta_json = project_article_type_3_file_metadata['private'] article_id = str(article_meta_json['id']) article_name = article_meta_json['title'] file_id = str(file_meta_json['id']) file_name = file_meta_json['name'] article_meta_url = project_provider_2.build_url(False, *root_parts, 'articles', article_id) aiohttpretty.register_json_uri('GET', article_meta_url, body=article_meta_json) path = FigsharePath('/{}/{}'.format(article_name, file_name), _ids=('', article_id, file_id), folder=False, is_public=False) result = await project_provider_2.metadata(path) assert aiohttpretty.has_call(method='GET', uri=article_meta_url) expected = metadata.FigshareFileMetadata(article_meta_json, file_meta_json) assert result == expected assert str(result.id) == file_id assert result.name == file_name assert result.path == '/{}/{}'.format(article_id, file_id) assert result.materialized_path == '/{}/{}'.format(article_name, file_name) assert str(result.article_id) == article_id assert result.article_name == article_name assert result.size == file_meta_json['size'] assert result.is_public == (article_meta_json['published_date'] is not None) assert result.extra['hashes']['md5'] == '68c3a15be1ddc27893c17eaab61f2d3d' class TestArticleMetadata: @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_file_contents(self, article_provider, root_provider_fixtures): article_metadata = root_provider_fixtures['folder_article_metadata'] file_metadata = root_provider_fixtures['folder_file_metadata'] root_parts = article_provider.root_path_parts article_id = str(article_metadata['id']) article_name = article_metadata['title'] file_id = str(file_metadata['id']) file_name = file_metadata['name'] folder_article_metadata_url = article_provider.build_url(False, *root_parts) aiohttpretty.register_json_uri('GET', folder_article_metadata_url, body=article_metadata) path = FigsharePath('/{}'.format(file_name), _ids=('', file_id), folder=False, is_public=False) result = await article_provider.metadata(path) assert aiohttpretty.has_call(method='GET', uri=folder_article_metadata_url) expected = metadata.FigshareFileMetadata(article_metadata, file_metadata) assert result == expected assert str(result.id) == file_id assert result.name == file_name assert result.path == '/{}/{}'.format(article_id, file_id) assert result.materialized_path == '/{}/{}'.format(article_name, file_name) assert result.article_name == article_name assert result.size == file_metadata['size'] assert result.is_public is False @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_root_contents(self, article_provider, root_provider_fixtures): article_metadata = root_provider_fixtures['folder_article_metadata'] file_metadata = root_provider_fixtures['folder_file_metadata'] root_parts = article_provider.root_path_parts file_id = str(file_metadata['id']) folder_article_metadata_url = article_provider.build_url(False, *root_parts) file_metadata_url = article_provider.build_url(False, *root_parts, 'files', file_id) aiohttpretty.register_json_uri('GET', folder_article_metadata_url, body=article_metadata) aiohttpretty.register_json_uri('GET', file_metadata_url, body=file_metadata) path = FigsharePath('/', _ids=(file_id, ), folder=True, is_public=False) result = await article_provider.metadata(path) expected = [metadata.FigshareFileMetadata(article_metadata, file_metadata)] assert result == expected class TestProjectCRUD: """Due to a bug in aiohttpretty, the file stream is not being read from on file upload for the Figshare provider. Because the file stream isn't read, the stream hash calculator never gets any data, and the computed md5sum is always that of the empty string. To work around this, the fixtures currently include the empty md5 in the metadata. Once aiohttpretty is fixed, the metadata can be reverted to deliver the actual content hash.""" @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_upload(self, file_stream, project_provider, root_provider_fixtures, crud_fixtures): file_name = 'barricade.gif' path = FigsharePath('/' + file_name, _ids=('', ''), folder=False, is_public=False) root_parts = project_provider.root_path_parts article_id = str(crud_fixtures['upload_article_metadata']['id']) file_metadata = root_provider_fixtures['get_file_metadata'] create_article_url = project_provider.build_url(False, *root_parts, 'articles') create_file_url = project_provider.build_url(False, 'articles', article_id, 'files') file_url = project_provider.build_url(False, 'articles', article_id, 'files', str(file_metadata['id'])) get_article_url = project_provider.build_url(False, *root_parts, 'articles', article_id) upload_url = file_metadata['upload_url'] aiohttpretty.register_json_uri('POST', create_article_url, body=crud_fixtures['create_article_metadata'], status=201) aiohttpretty.register_json_uri('POST', create_file_url, body=crud_fixtures['create_file_metadata'], status=201) aiohttpretty.register_json_uri('GET', file_url, body=file_metadata) aiohttpretty.register_json_uri('GET', upload_url, body=root_provider_fixtures['get_upload_metadata']) aiohttpretty.register_uri('PUT', '{}/1'.format(upload_url), status=200) aiohttpretty.register_uri('POST', file_url, status=202) aiohttpretty.register_json_uri('GET', get_article_url, body=crud_fixtures['upload_article_metadata']) # md5 hash calculation is being hacked around. see test class docstring result, created = await project_provider.upload(file_stream, path) expected = metadata.FigshareFileMetadata( crud_fixtures['upload_article_metadata'], crud_fixtures['upload_article_metadata']['files'][0], ) assert aiohttpretty.has_call( method='POST', uri=create_article_url, data=json.dumps({ 'title': 'barricade.gif', }) ) assert aiohttpretty.has_call(method='PUT', uri='{}/1'.format(upload_url)) assert aiohttpretty.has_call(method='POST', uri=create_file_url) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_upload_checksum_mismatch(self, project_provider, root_provider_fixtures, crud_fixtures, file_stream): file_name = 'barricade.gif' item = root_provider_fixtures['get_file_metadata'] root_parts = project_provider.root_path_parts path = FigsharePath('/' + file_name, _ids=('', ''), folder=False, is_public=False) article_id = str(crud_fixtures['checksum_mismatch_article_metadata']['id']) create_article_url = project_provider.build_url(False, *root_parts, 'articles') create_file_url = project_provider.build_url(False, 'articles', article_id, 'files') file_url = project_provider.build_url(False, 'articles', article_id, 'files', str(item['id'])) get_article_url = project_provider.build_url(False, *root_parts, 'articles', article_id) upload_url = item['upload_url'] aiohttpretty.register_json_uri('POST', create_article_url, body=crud_fixtures['create_article_metadata'], status=201) aiohttpretty.register_json_uri('POST', create_file_url, body=crud_fixtures['create_file_metadata'], status=201) aiohttpretty.register_json_uri('GET', file_url, body=item) aiohttpretty.register_json_uri('GET', upload_url, body=root_provider_fixtures['get_upload_metadata']) aiohttpretty.register_uri('PUT', '{}/1'.format(upload_url), status=200) aiohttpretty.register_uri('POST', file_url, status=202) aiohttpretty.register_json_uri('GET', get_article_url, body=crud_fixtures['checksum_mismatch_article_metadata']) with pytest.raises(exceptions.UploadChecksumMismatchError): await project_provider.upload(file_stream, path) assert aiohttpretty.has_call( method='POST', uri=create_article_url, data=json.dumps({ 'title': 'barricade.gif', }) ) assert aiohttpretty.has_call(method='POST', uri=create_file_url) assert aiohttpretty.has_call(method='GET', uri=file_url) assert aiohttpretty.has_call(method='GET', uri=upload_url) assert aiohttpretty.has_call(method='PUT', uri='{}/1'.format(upload_url)) assert aiohttpretty.has_call(method='POST', uri=file_url) assert aiohttpretty.has_call(method='GET', uri=get_article_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_folder_upload(self, file_stream, project_provider, root_provider_fixtures, crud_fixtures): file_name = 'barricade.gif' article_id = str(root_provider_fixtures['list_project_articles'][1]['id']) article_name = root_provider_fixtures['list_project_articles'][1]['title'] root_parts = project_provider.root_path_parts path = FigsharePath('/{}/{}'.format(article_name, file_name), _ids=('', article_id, ''), folder=False, is_public=False) file_metadata = root_provider_fixtures['get_file_metadata'] create_file_url = project_provider.build_url(False, 'articles', article_id, 'files') file_url = project_provider.build_url(False, 'articles', article_id, 'files', str(file_metadata['id'])) get_article_url = project_provider.build_url(False, *root_parts, 'articles', article_id) upload_url = file_metadata['upload_url'] aiohttpretty.register_json_uri('POST', create_file_url, body=crud_fixtures['create_file_metadata'], status=201) aiohttpretty.register_json_uri('GET', file_url, body=file_metadata) aiohttpretty.register_json_uri('GET', upload_url, body=root_provider_fixtures['get_upload_metadata']) aiohttpretty.register_uri('PUT', '{}/1'.format(upload_url), status=200) aiohttpretty.register_uri('POST', file_url, status=202) aiohttpretty.register_json_uri('GET', get_article_url, body=crud_fixtures['upload_folder_article_metadata']) # md5 hash calculation is being hacked around. see test class docstring result, created = await project_provider.upload(file_stream, path) expected = metadata.FigshareFileMetadata( crud_fixtures['upload_folder_article_metadata'], crud_fixtures['upload_folder_article_metadata']['files'][0], ) assert aiohttpretty.has_call(method='PUT', uri='{}/1'.format(upload_url)) assert aiohttpretty.has_call(method='POST', uri=create_file_url) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_folder_upload_undefined_type(self, file_stream, project_provider, root_provider_fixtures, crud_fixtures): file_name = 'barricade.gif' article_id = str(root_provider_fixtures['list_project_articles'][1]['id']) article_name = root_provider_fixtures['list_project_articles'][1]['title'] changed_metadata = crud_fixtures['upload_folder_article_metadata'] changed_metadata['defined_type'] = 5 root_parts = project_provider.root_path_parts list_articles_url = project_provider.build_url(False, *root_parts, 'articles') aiohttpretty.register_json_uri('POST', list_articles_url, status=201, body=crud_fixtures['create_upload_article_metadata']) path = FigsharePath('/{}/{}'.format(article_name, file_name), _ids=('', article_id, ''), folder=False, is_public=False) file_metadata = root_provider_fixtures['get_file_metadata'] create_file_url = project_provider.build_url(False, 'articles', article_id, 'files') file_url = project_provider.build_url(False, 'articles', article_id, 'files', str(file_metadata['id'])) get_article_url = project_provider.build_url(False, *root_parts, 'articles', article_id) upload_url = file_metadata['upload_url'] aiohttpretty.register_json_uri('POST', create_file_url, body=crud_fixtures['create_file_metadata'], status=201) aiohttpretty.register_json_uri('GET', file_url, body=file_metadata) aiohttpretty.register_json_uri('GET', upload_url, body=root_provider_fixtures['get_upload_metadata']) aiohttpretty.register_uri('PUT', '{}/1'.format(upload_url), status=200) aiohttpretty.register_uri('POST', file_url, status=202) aiohttpretty.register_json_uri('GET', get_article_url, body=changed_metadata) result, created = await project_provider.upload(file_stream, path) expected = metadata.FigshareFileMetadata( crud_fixtures['upload_folder_article_metadata'], crud_fixtures['upload_folder_article_metadata']['files'][0], ) assert aiohttpretty.has_call(method='PUT', uri='{}/1'.format(upload_url)) assert aiohttpretty.has_call(method='POST', uri=create_file_url) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_upload_update_error(self, file_stream, project_provider): path = FigsharePath('/testfolder/whatever.txt', _ids=('512415', '123325', '8890481'), folder=False, is_public=False) with pytest.raises(exceptions.UnsupportedOperationError) as e: await project_provider.upload(file_stream, path) assert e.value.code == 403 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_article_download(self, project_provider, root_provider_fixtures): article_id = str(root_provider_fixtures['list_project_articles'][0]['id']) file_id = str(root_provider_fixtures['file_article_metadata']['files'][0]['id']) article_name = str(root_provider_fixtures['list_project_articles'][0]['title']) file_name = str(root_provider_fixtures['file_article_metadata']['files'][0]['name']) body = b'castle on a cloud' root_parts = project_provider.root_path_parts file_metadata_url = project_provider.build_url(False, *root_parts, 'articles', article_id, 'files', file_id) article_metadata_url = project_provider.build_url(False, *root_parts, 'articles', article_id) download_url = root_provider_fixtures['file_metadata']['download_url'] aiohttpretty.register_json_uri('GET', file_metadata_url, body=root_provider_fixtures['file_metadata']) aiohttpretty.register_json_uri('GET', article_metadata_url, body=root_provider_fixtures['file_article_metadata']) aiohttpretty.register_uri('GET', download_url, params={'token': project_provider.token}, body=body, auto_length=True) path = FigsharePath('/{}/{}'.format(article_name, file_name), _ids=('', article_id, file_id), folder=False, is_public=False) result = await project_provider.download(path) content = await result.read() assert content == body @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_file_delete(self, project_provider, root_provider_fixtures): file_id = str(root_provider_fixtures['file_metadata']['id']) file_name = root_provider_fixtures['file_metadata']['name'] article_id = str(root_provider_fixtures['list_project_articles'][0]['id']) article_name = str(root_provider_fixtures['list_project_articles'][0]['title']) root_parts = project_provider.root_path_parts file_url = project_provider.build_url(False, *root_parts, 'articles', article_id, 'files', file_id) file_article_url = project_provider.build_url(False, *root_parts, 'articles', article_id) aiohttpretty.register_json_uri('GET', file_url, body=root_provider_fixtures['file_metadata']) aiohttpretty.register_json_uri('GET', file_article_url, body=root_provider_fixtures['file_article_metadata']) aiohttpretty.register_uri('DELETE', file_article_url, status=204) path = FigsharePath('/{}/{}'.format(article_name, file_name), _ids=('', article_id, file_id), folder=False, is_public=False) result = await project_provider.delete(path) assert result is None assert aiohttpretty.has_call(method='DELETE', uri=file_article_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_file_delete_folder_type(self, project_provider, root_provider_fixtures): item = root_provider_fixtures['file_article_metadata'] item['defined_type'] = 4 file_id = str(root_provider_fixtures['file_metadata']['id']) article_id = str(root_provider_fixtures['list_project_articles'][0]['id']) root_parts = project_provider.root_path_parts path = FigsharePath('/{}/{}'.format(article_id, file_id), _ids=('', article_id, file_id), folder=False) list_articles_url = project_provider.build_url(False, *root_parts, 'articles') file_article_url = project_provider.build_url(False, 'articles', path.parts[1]._id, 'files', path.parts[2]._id) get_file_article_url = project_provider.build_url(False, *root_parts, 'articles', article_id) aiohttpretty.register_json_uri('GET', list_articles_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', list_articles_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', get_file_article_url, body=item) aiohttpretty.register_uri('DELETE', file_article_url, status=204) result = await project_provider.delete(path) assert result is None assert aiohttpretty.has_call(method='DELETE', uri=file_article_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_file_delete_bad_path(self, project_provider, root_provider_fixtures): file_name = str(root_provider_fixtures['file_metadata']['name']) article_name = str(root_provider_fixtures['list_project_articles'][0]['title']) path = FigsharePath('/{}/{}'.format(article_name, file_name), _ids=('',), folder=False) with pytest.raises(exceptions.NotFoundError) as e: await project_provider.delete(path) assert e.value.code == 404 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_folder_delete(self, project_provider, root_provider_fixtures): article_id = str(root_provider_fixtures['list_project_articles'][1]['id']) root_parts = project_provider.root_path_parts list_articles_url = project_provider.build_url(False, *root_parts, 'articles') folder_article_url = project_provider.build_url(False, *root_parts, 'articles', article_id) aiohttpretty.register_json_uri('GET', list_articles_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', list_articles_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', folder_article_url, body=root_provider_fixtures['folder_article_metadata']) aiohttpretty.register_uri('DELETE', folder_article_url, status=204) path = FigsharePath('/{}'.format(article_id), _ids=('', article_id), folder=True) result = await project_provider.delete(path) assert result is None assert aiohttpretty.has_call(method='DELETE', uri=folder_article_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_delete_root_confirm_error(self, project_provider): path = FigsharePath('/', _ids=('11241213', ), folder=True, is_public=False) with pytest.raises(exceptions.DeleteError) as e: await project_provider.delete(path) assert e.value.code == 400 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_delete_root(self, project_provider, root_provider_fixtures): path = FigsharePath('/', _ids=('11241213', ), folder=True, is_public=False) item = root_provider_fixtures['list_project_articles'] list_articles_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') delete_url_1 = project_provider.build_url(False, *project_provider.root_path_parts, 'articles', str(item[0]['id'])) delete_url_2 = project_provider.build_url(False, *project_provider.root_path_parts, 'articles', str(item[1]['id'])) aiohttpretty.register_json_uri('DELETE', delete_url_1, status=204) aiohttpretty.register_json_uri('DELETE', delete_url_2, status=204) aiohttpretty.register_json_uri('GET', list_articles_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', list_articles_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) await project_provider.delete(path, 1) assert aiohttpretty.has_call(method='DELETE', uri=delete_url_2) assert aiohttpretty.has_call(method='DELETE', uri=delete_url_1) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_delete_errors(self, project_provider): path = FigsharePath('/test.txt', _ids=('11241213', '123123'), folder=False, is_public=False) with pytest.raises(exceptions.NotFoundError) as e: await project_provider.delete(path) assert e.value.code == 404 path = FigsharePath('/test/test.txt', _ids=('11241213', '123123', '123123'), folder=True, is_public=False) with pytest.raises(exceptions.NotFoundError) as e: await project_provider.delete(path) assert e.value.code == 404 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_create_folder(self, project_provider, root_provider_fixtures, crud_fixtures): item = root_provider_fixtures['file_metadata'] file_id = str(item['id']) path = FigsharePath('/folder2/', _ids=('', file_id), folder=True) create_url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles') metadata_url = crud_fixtures['create_article_metadata']['location'] aiohttpretty.register_json_uri('POST', create_url, body=crud_fixtures['create_article_metadata'], status=201) aiohttpretty.register_json_uri('GET', metadata_url, body=root_provider_fixtures['folder_article_metadata']) result = await project_provider.create_folder(path) assert result is not None @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_create_folder_invalid_path(self, project_provider, root_provider_fixtures): item = root_provider_fixtures['file_metadata'] file_id = str(item['id']) path = FigsharePath('/folder2/folder3/folder4/folder5', _ids=('', file_id, file_id, file_id), folder=True) with pytest.raises(exceptions.CreateFolderError) as e: await project_provider.create_folder(path) assert e.value.code == 400 class TestArticleCRUD: @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_upload(self, file_stream, article_provider, root_provider_fixtures, crud_fixtures): file_name = 'barricade.gif' file_id = str(root_provider_fixtures['get_file_metadata']['id']) root_parts = article_provider.root_path_parts path = FigsharePath('/' + file_name, _ids=('', ''), folder=False, is_public=False) create_file_url = article_provider.build_url(False, *root_parts, 'files') file_url = article_provider.build_url(False, *root_parts, 'files', file_id) get_article_url = article_provider.build_url(False, *root_parts) upload_url = root_provider_fixtures['get_file_metadata']['upload_url'] aiohttpretty.register_json_uri('POST', create_file_url, body=crud_fixtures['create_file_metadata'], status=201) aiohttpretty.register_json_uri('GET', file_url, body=root_provider_fixtures['get_file_metadata']) aiohttpretty.register_json_uri('GET', root_provider_fixtures['get_file_metadata']['upload_url'], body=root_provider_fixtures['get_upload_metadata']) aiohttpretty.register_uri('PUT', '{}/1'.format(upload_url), status=200) aiohttpretty.register_uri('POST', file_url, status=202) aiohttpretty.register_json_uri('GET', get_article_url, body=crud_fixtures['upload_folder_article_metadata']) # md5 hash calculation is being hacked around. see test class docstring result, created = await article_provider.upload(file_stream, path) expected = metadata.FigshareFileMetadata( crud_fixtures['upload_folder_article_metadata'], crud_fixtures['upload_folder_article_metadata']['files'][0], ) assert aiohttpretty.has_call(method='PUT', uri='{}/1'.format(upload_url)) assert aiohttpretty.has_call(method='POST', uri=create_file_url) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_download(self, article_provider, root_provider_fixtures): item = root_provider_fixtures['file_metadata'] file_id = str(item['id']) file_name = str(item['name']) body = b'castle on a cloud' root_parts = article_provider.root_path_parts article_metadata_url = article_provider.build_url(False, *root_parts) download_url = item['download_url'] aiohttpretty.register_json_uri('GET', article_metadata_url, body=root_provider_fixtures['file_article_metadata']) aiohttpretty.register_uri('GET', download_url, params={'token': article_provider.token}, body=body, auto_length=True) path = FigsharePath('/{}'.format(file_name), _ids=('', file_id), folder=False, is_public=False) result = await article_provider.download(path) content = await result.read() assert content == body @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_download_range(self, article_provider, root_provider_fixtures): item = root_provider_fixtures['file_metadata'] file_id = str(item['id']) file_name = str(item['name']) body = b'castle on a cloud' root_parts = article_provider.root_path_parts article_metadata_url = article_provider.build_url(False, *root_parts) download_url = item['download_url'] aiohttpretty.register_json_uri('GET', article_metadata_url, body=root_provider_fixtures['file_article_metadata']) aiohttpretty.register_uri('GET', download_url, params={'token': article_provider.token}, body=body[0:2], auto_length=True, status=206) path = FigsharePath('/{}'.format(file_name), _ids=('', file_id), folder=False, is_public=False) result = await article_provider.download(path, range=(0, 1)) assert result.partial content = await result.read() assert content == b'ca' assert aiohttpretty.has_call(method='GET', uri=download_url, headers={'Range': 'bytes=0-1', 'Authorization': 'token freddie'}, params={'token': 'freddie'}) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_download_path_not_file(self, article_provider, root_provider_fixtures): path = FigsharePath('/testfolder/', _ids=('', ), folder=True, is_public=False) with pytest.raises(exceptions.NotFoundError) as e: await article_provider.download(path) assert e.value.code == 404 assert e.value.message == 'Could not retrieve file or directory /{}'.format(path.path) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_download_no_downloadurl(self, article_provider, error_fixtures): item = error_fixtures['file_metadata_missing_download_url'] file_id = str(item['id']) path = FigsharePath('/{}'.format(file_id), _ids=('', file_id), folder=False) root_parts = article_provider.root_path_parts file_metadata_url = article_provider.build_url(False, *root_parts, 'files', file_id) article_metadata_url = article_provider.build_url(False, *root_parts) missing_download_url = error_fixtures['file_article_metadata_missing_download_url'] aiohttpretty.register_json_uri('GET', file_metadata_url, body=item) aiohttpretty.register_json_uri('GET', article_metadata_url, body=missing_download_url) with pytest.raises(exceptions.DownloadError) as e: await article_provider.download(path) assert e.value.code == 403 assert e.value.message == 'Download not available' @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_upload_checksum_mismatch(self, file_stream, article_provider, root_provider_fixtures, crud_fixtures): file_name = 'barricade.gif' item = root_provider_fixtures['get_file_metadata'] file_id = str(item['id']) root_parts = article_provider.root_path_parts validate_file_url = article_provider.build_url(False, *root_parts, 'files', file_name) aiohttpretty.register_uri('GET', validate_file_url, status=404) path = FigsharePath('/' + file_name, _ids=('', file_id), folder=False, is_public=False) create_file_url = article_provider.build_url(False, *root_parts, 'files') file_url = article_provider.build_url(False, *root_parts, 'files', file_id) get_article_url = article_provider.build_url(False, *root_parts) upload_url = item['upload_url'] aiohttpretty.register_json_uri('POST', create_file_url, body=crud_fixtures['create_file_metadata'], status=201) aiohttpretty.register_json_uri('GET', file_url, body=item) aiohttpretty.register_json_uri('GET', item['upload_url'], body=root_provider_fixtures['get_upload_metadata']) aiohttpretty.register_uri('PUT', '{}/1'.format(upload_url), status=200) aiohttpretty.register_uri('POST', file_url, status=202) aiohttpretty.register_json_uri('GET', get_article_url, body=crud_fixtures['checksum_mismatch_folder_article_metadata']) with pytest.raises(exceptions.UploadChecksumMismatchError): await article_provider.upload(file_stream, path) assert aiohttpretty.has_call(method='POST', uri=create_file_url) assert aiohttpretty.has_call(method='GET', uri=file_url) assert aiohttpretty.has_call(method='GET', uri=item['upload_url']) assert aiohttpretty.has_call(method='PUT', uri='{}/1'.format(upload_url)) assert aiohttpretty.has_call(method='POST', uri=file_url) assert aiohttpretty.has_call(method='GET', uri=get_article_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_file_delete_root_no_confirm(self, article_provider): path = FigsharePath('/', _ids=('11241213', ), folder=True, is_public=False) with pytest.raises(exceptions.DeleteError) as e: await article_provider.delete(path) assert e.value.code == 400 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_file_delete_root(self, article_provider, root_provider_fixtures): path = FigsharePath('/', _ids=('11241213', ), folder=True, is_public=False) item = root_provider_fixtures['file_article_metadata'] list_articles_url = article_provider.build_url(False, *article_provider.root_path_parts) delete_url = article_provider.build_url(False, *article_provider.root_path_parts, 'files', str(item['files'][0]['id'])) aiohttpretty.register_json_uri('DELETE', delete_url, status=204) aiohttpretty.register_json_uri('GET', list_articles_url, body=item) await article_provider.delete(path, 1) assert aiohttpretty.has_call(method='DELETE', uri=delete_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_create_folder(self, article_provider): path = '/' with pytest.raises(exceptions.CreateFolderError) as e: await article_provider.create_folder(path) assert e.value.code == 400 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_file_delete(self, article_provider, root_provider_fixtures): file_id = str(root_provider_fixtures['file_metadata']['id']) file_name = root_provider_fixtures['file_metadata']['name'] file_url = article_provider.build_url(False, *article_provider.root_path_parts, 'files', file_id) aiohttpretty.register_uri('DELETE', file_url, status=204) path = FigsharePath('/{}'.format(file_name), _ids=('', file_id), folder=False) result = await article_provider.delete(path) assert result is None assert aiohttpretty.has_call(method='DELETE', uri=file_url) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_download_404(self, article_provider, root_provider_fixtures): item = root_provider_fixtures['file_metadata'] file_id = str(item['id']) path = FigsharePath('/{}'.format(file_id), _ids=('', file_id), folder=False) root_parts = article_provider.root_path_parts file_metadata_url = article_provider.build_url(False, *root_parts, 'files', file_id) article_metadata_url = article_provider.build_url(False, *root_parts) download_url = item['download_url'] aiohttpretty.register_json_uri('GET', file_metadata_url, body=item) aiohttpretty.register_json_uri('GET', article_metadata_url, body=root_provider_fixtures['file_article_metadata']) aiohttpretty.register_uri('GET', download_url, params={'token': article_provider.token}, status=404, auto_length=True) with pytest.raises(exceptions.DownloadError) as e: await article_provider.download(path) assert e.value.code == 404 assert e.value.message == 'Download not available' @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_upload_root(self, file_stream, article_provider, root_provider_fixtures, crud_fixtures): file_name = 'barricade.gif' file_id = str(root_provider_fixtures['get_file_metadata']['id']) root_parts = article_provider.root_path_parts item = crud_fixtures["upload_folder_article_metadata"] item['defined_type'] = 5 validate_file_url = article_provider.build_url(False, *root_parts, 'files', file_name) aiohttpretty.register_uri('GET', validate_file_url, status=404) path = FigsharePath('/1234/94813', _ids=('1234', '94813'), folder=False, is_public=False) create_file_url = article_provider.build_url(False, *root_parts, 'files') file_url = article_provider.build_url(False, *root_parts, 'files', file_id) get_article_url = article_provider.build_url(False, *root_parts) upload_url = root_provider_fixtures['get_file_metadata']['upload_url'] parent_url = article_provider.build_url(False, *root_parts, 'articles', path.parent.identifier) aiohttpretty.register_json_uri('GET', parent_url, body=item) aiohttpretty.register_json_uri('POST', create_file_url, body=crud_fixtures['create_file_metadata'], status=201) aiohttpretty.register_json_uri('GET', file_url, body=root_provider_fixtures['get_file_metadata']) aiohttpretty.register_json_uri('GET', root_provider_fixtures['get_file_metadata']['upload_url'], body=root_provider_fixtures['get_upload_metadata']) aiohttpretty.register_uri('PUT', '{}/1'.format(upload_url), status=200) aiohttpretty.register_uri('POST', file_url, status=202) aiohttpretty.register_json_uri('GET', get_article_url, body=crud_fixtures['upload_folder_article_metadata']) result, created = await article_provider.upload(file_stream, path) expected = metadata.FigshareFileMetadata( crud_fixtures['upload_folder_article_metadata'], crud_fixtures['upload_folder_article_metadata']['files'][0], ) assert aiohttpretty.has_call(method='PUT', uri='{}/1'.format(upload_url)) assert aiohttpretty.has_call(method='POST', uri=create_file_url) assert result == expected class TestRevalidatePath: @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_revalidate_path(self, project_provider, root_provider_fixtures): file_article_id = str(root_provider_fixtures['list_project_articles'][0]['id']) folder_article_id = str(root_provider_fixtures['list_project_articles'][1]['id']) root_parts = project_provider.root_path_parts list_articles_url = project_provider.build_url(False, *root_parts, 'articles') file_article_url = project_provider.build_url(False, *root_parts, 'articles', file_article_id) folder_article_url = project_provider.build_url(False, *root_parts, 'articles', folder_article_id) aiohttpretty.register_json_uri('GET', list_articles_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', list_articles_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', file_article_url, body=root_provider_fixtures['file_article_metadata']) aiohttpretty.register_json_uri('GET', folder_article_url, body=root_provider_fixtures['folder_article_metadata']) path = FigsharePath('/', _ids=(''), folder=True) result = await project_provider.revalidate_path(path, '{}'.format('file'), folder=False) assert result.is_dir is False assert result.name == 'file' assert result.identifier == str( root_provider_fixtures['file_article_metadata']['files'][0]['id']) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_revalidate_path_duplicate_folder(self, project_provider, root_provider_fixtures): file_article_id = str(root_provider_fixtures['list_project_articles'][0]['id']) folder_article_id = str(root_provider_fixtures['list_project_articles'][1]['id']) folder_article_name = root_provider_fixtures['list_project_articles'][1]['title'] root_parts = project_provider.root_path_parts list_articles_url = project_provider.build_url(False, *root_parts, 'articles') file_article_url = project_provider.build_url(False, *root_parts, 'articles', file_article_id) folder_article_url = project_provider.build_url(False, *root_parts, 'articles', folder_article_id) aiohttpretty.register_json_uri('GET', list_articles_url, body=root_provider_fixtures['list_project_articles'], params={'page': '1', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', list_articles_url, body=[], params={'page': '2', 'page_size': str(MAX_PAGE_SIZE)}) aiohttpretty.register_json_uri('GET', file_article_url, body=root_provider_fixtures['file_article_metadata']) aiohttpretty.register_json_uri('GET', folder_article_url, body=root_provider_fixtures['folder_article_metadata']) path = FigsharePath('/', _ids=(''), folder=True) result = await project_provider.revalidate_path(path, folder_article_name, folder=True) assert result.is_dir is True assert result.name == 'folder_article' assert result.identifier == folder_article_id @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_project_revalidate_path_not_root(self, project_provider, root_provider_fixtures): file_article_id = str(root_provider_fixtures['list_project_articles'][0]['id']) path = FigsharePath('/folder1/', _ids=('', file_article_id), folder=True) root_parts = project_provider.root_path_parts file_article_url = project_provider.build_url(False, *root_parts, 'articles', file_article_id) aiohttpretty.register_json_uri('GET', file_article_url, body=root_provider_fixtures['file_article_metadata']) result = await project_provider.revalidate_path(path, '{}'.format('file'), folder=False) assert result.is_dir is False assert result.name == 'file' assert result.identifier == str( root_provider_fixtures['file_article_metadata']['files'][0]['id']) @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_revalidate_path_bad_path(self, article_provider, root_provider_fixtures): item = root_provider_fixtures['file_metadata'] file_id = str(item['id']) path = FigsharePath('/fodler1/folder2/', _ids=('', '', file_id), folder=True) with pytest.raises(exceptions.NotFoundError) as e: await article_provider.revalidate_path(path, 'childname', folder=True) assert e.value.code == 404 @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test_article_revalidate_path_file(self, article_provider, crud_fixtures): item = crud_fixtures["upload_folder_article_metadata"] file_id = str(item['files'][0]['id']) file_name = item['files'][0]['name'] path = FigsharePath('/' + str(file_name), _ids=('', file_id), folder=True) urn_parts = (*article_provider.root_path_parts, (path.identifier)) url = article_provider.build_url(False, *urn_parts) aiohttpretty.register_json_uri('GET', url, body=item) result = await article_provider.revalidate_path(path, item['files'][0]['name'], folder=False) expected = path.child(item['files'][0]['name'], _id=file_id, folder=False, parent_is_folder=False) assert result == expected class TestMisc: def test_path_from_metadata_file(self, project_provider, root_provider_fixtures): file_article_metadata = root_provider_fixtures['file_article_metadata'] fig_metadata = metadata.FigshareFileMetadata(file_article_metadata) path = FigsharePath('/', _ids=(''), folder=True) expected = FigsharePath('/file_article/file', _ids=('', '4037952', '6530715'), folder=False) result = project_provider.path_from_metadata(path, fig_metadata) assert result == expected def test_path_from_metadata_folder(self, project_provider, root_provider_fixtures): folder_article_metadata = root_provider_fixtures['folder_article_metadata'] fig_metadata = metadata.FigshareFolderMetadata(folder_article_metadata) path = FigsharePath('/', _ids=(''), folder=True) expected = FigsharePath('/folder_article/', _ids=('', '4040019'), folder=True) result = project_provider.path_from_metadata(path, fig_metadata) assert result == expected @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test__get_article_metadata_returns_none(self, project_provider, root_provider_fixtures): file_id = root_provider_fixtures['file_article_metadata']['id'] item = {'defined_type': 5, 'files': None, 'id': file_id} url = project_provider.build_url(False, *project_provider.root_path_parts, 'articles', str(file_id)) aiohttpretty.register_json_uri('GET', url, body=item) result = await project_provider._get_article_metadata(str(file_id), False) assert result is None @pytest.mark.asyncio @pytest.mark.aiohttpretty async def test__get_file_upload_url_error(self, project_provider): article_id = '12345' file_id = '871947' url = project_provider.build_url(False, 'articles', article_id, 'files', file_id) aiohttpretty.register_json_uri('GET', url, status=404) with pytest.raises(exceptions.ProviderError) as e: await project_provider._get_file_upload_url(article_id, file_id) assert e.value.code == 500 @pytest.mark.asyncio async def test_revisions(self, project_provider): result = await project_provider.revisions('/') expected = [metadata.FigshareFileRevisionMetadata()] assert result == expected def test_can_duplicate_names(self, project_provider): assert project_provider.can_duplicate_names() is False def test_base_figshare_provider_fileset(self, auth, credentials): settings = { 'container_type': 'fileset', 'container_id': '13423', } test_provider = provider.FigshareArticleProvider(auth, credentials, settings) assert test_provider.container_type == 'article' def test_base_figshare_provider_invalid_setting(self, auth, credentials): bad_settings = { 'container_type': 'not_a_project', 'container_id': '13423', } with pytest.raises(exceptions.ProviderError) as e: provider.FigshareProjectProvider(auth, credentials, bad_settings) assert e.value.message == '{} is not a valid container type.'.format( bad_settings['container_type']) def test_figshare_provider_invalid_setting(self, auth, credentials): bad_settings = { 'container_type': 'not_a_project', 'container_id': '13423', } with pytest.raises(exceptions.ProviderError) as e: provider.FigshareProvider(auth, credentials, bad_settings) assert e.value.message == 'Invalid "container_type" {0}'.format( bad_settings['container_type'])

48.99655

103

0.637345

9,470

85,205

5.375713

0.032418

0.063939

0.059716

0.061523

0.903237

0.877544

0.856879

0.832345

0.802703

0.777736

0

0.01063

0.260255

85,205

1,738

104

49.024741

0.797049

0.009741

0

0.723626

0

0.088354

0.028902

0

0.115156

1

0.014116

false

0

0.008172

0.038633

0

null

0

1

0

1

0

null

0

7

021ff06c29c567be077f516b6d440f0702099da9

14,561

py

Python

delpapa/avalanches/Fig5.py

delpapa/CritSORN

cdad55d55f39e04f568ca1bc0c6036bec8db08fb

[ "MIT" ]

null

delpapa/avalanches/Fig5.py

delpapa/CritSORN

cdad55d55f39e04f568ca1bc0c6036bec8db08fb

[ "MIT" ]

null

delpapa/avalanches/Fig5.py

delpapa/CritSORN

cdad55d55f39e04f568ca1bc0c6036bec8db08fb

[ "MIT" ]

null

#### # Script for the 5th paper figure (from PhaseTransitionNoise) # A,B: Gaussian noise 'phase transition' # C,D: random spike 'phase transition' # E,F,G: raster plot for every phase #### from pylab import * import matplotlib.gridspec as gridspec import tables import os from tempfile import TemporaryFile import scipy, scipy.stats # for the binomial distribution import data_analysis as analysis import powerlaw as pl transient_steps = 2e6 stable_steps = 3e6 number_of_files = 2 THETA = 'half' raster_steps = 800 ### figure parameters width = 6 height = 9 fig = figure(1, figsize=(width, height)) fig_5a = subplot(3, 2, 1) fig_5b = subplot(3, 2, 2) fig_5c = subplot(3, 2, 3) fig_5d = subplot(3, 2, 4) fig_5e = subplot(9, 1, 7) fig_5f = subplot(9, 1, 8) fig_5g = subplot(9, 1, 9) letter_size = 11 letter_size_panel = 13 line_width = 1.5 line_width_fit = 2.0 subplot_letter = (-0.18, 1.05) subplot_letter_long = (-0.08, 0.85) ######################################################################## # Fig. 5A,B: Gaussian noise (power-laws and activity) experiment_name = 'Gaussian' print experiment_name for sigma in ['0.005', '0.05', '5']: print sigma data_all = np.zeros((number_of_files, stable_steps)) act_density = zeros((number_of_files, 200)) for data_file in xrange(number_of_files): exper = 'result.h5' exper_path = '' h5 = tables.openFile(os.path.join(exper_path,exper),'r') data = h5.root data_all[data_file] = np.around(data.activity[0] \ [transient_steps:]*data.c.N_e) for i in xrange(int(stable_steps)): act_density[data_file, data_all[data_file, i]] += 1 act_density[data_file, :] /= act_density[data_file, :].sum() ### Save raster plots if data_file == 0: # 0 is a random file if sigma == '0.005': raster_low = data.Spikes[0][:, -raster_steps:] if sigma == '0.05': raster_inter = data.Spikes[0][:, -raster_steps:] if sigma == '5': raster_high = data.Spikes[0][:, -raster_steps:] h5.close() # activity distribution and std act_density_mean = act_density.mean(0) act_density_std = act_density.std(0) # calculates avalanches T_data, S_data = analysis.avalanches(data_all, \ 'N', '200', Threshold=THETA) a_dur1, a_area1 = analysis.avalanches(data_all, 'N', '200',\ Theta_percent = 5) a_dur2, a_area2 = analysis.avalanches(data_all, 'N', '200',\ Theta_percent = 25) subplot(321) if sigma == '0.05': a_area1_pdf = pl.pdf(a_area1, 10) a_area2_pdf = pl.pdf(a_area2, 10) BinCenters1 = (a_area1_pdf[0][:-1]+a_area1_pdf[0][1:])/2. BinCenters2 = (a_area2_pdf[0][:-1]+a_area2_pdf[0][1:])/2. x_max = a_area1_pdf[0].max() interp1 = np.interp(np.arange(x_max), BinCenters1, a_area1_pdf[1]) interp2 = np.interp(np.arange(x_max), BinCenters2, a_area2_pdf[1]) fill_between(np.linspace(0,x_max,len(interp2)), interp2, interp1, facecolor='k', alpha=0.2) pl.plot_pdf(S_data, color='k', linewidth=line_width_fit) elif sigma == '0.005': a_area1_pdf = pl.pdf(a_area1, 10) a_area2_pdf = pl.pdf(a_area2, 10) BinCenters1 = (a_area1_pdf[0][:-1]+a_area1_pdf[0][1:])/2. BinCenters2 = (a_area2_pdf[0][:-1]+a_area2_pdf[0][1:])/2. x_max = a_area1_pdf[0].max() interp1 = np.interp(np.arange(x_max), BinCenters1, a_area1_pdf[1]) interp2 = np.interp(np.arange(x_max), BinCenters2, a_area2_pdf[1]) fill_between(np.linspace(0,x_max,len(interp2)), interp2, interp1, facecolor='darkcyan', alpha=0.2) pl.plot_pdf(S_data, color='darkcyan', linewidth=line_width) elif sigma == '5': a_area1_pdf = pl.pdf(a_area1, 10) a_area2_pdf = pl.pdf(a_area2, 10) BinCenters1 = (a_area1_pdf[0][:-1]+a_area1_pdf[0][1:])/2. BinCenters2 = (a_area2_pdf[0][:-1]+a_area2_pdf[0][1:])/2. x_max = a_area1_pdf[0].max() interp1 = np.interp(np.arange(x_max), BinCenters1, a_area1_pdf[1]) interp2 = np.interp(np.arange(x_max), BinCenters2, a_area2_pdf[1]) fill_between(np.linspace(0,x_max,len(interp2)), interp2, interp1, facecolor='r', alpha=0.2) pl.plot_pdf(S_data, color='r', linewidth=line_width) xscale('log'); yscale('log') xlabel(r'$S$', fontsize=letter_size) ylabel(r'$f(S)$', fontsize=letter_size) # ticks name xlim([1, 3000]) ylim([0.00001, 0.1]) xticks([1, 10, 100, 1000], \ ['$10^0$', '$10^{1}$', '$10^{2}$', '$10^{3}$']) yticks([0.1, 0.001, 0.00001],\ ['$10^{-1}$', '$10^{-3}$', '$10^{-5}$']) fig_5a.spines['right'].set_visible(False) fig_5a.spines['top'].set_visible(False) fig_5a.xaxis.set_ticks_position('bottom') fig_5a.yaxis.set_ticks_position('left') tick_params(labelsize=letter_size) subplot(322) if sigma == '0.005': plot(act_density_mean, 'c', linewidth=line_width, label='low') if sigma == '0.05': plot(act_density_mean, 'k', linewidth=line_width_fit, label='intermediate') if sigma == '5': plot(act_density_mean, 'r', linewidth=line_width, label='high') ### Binomial distribution plot ### p = 0.1 (\mu_IP); n = 200 (N_E) bino_x = np.arange(0, 40) bino_y = scipy.stats.binom.pmf(bino_x, 200,0.1) subplot(322) plot(bino_x, bino_y, '--', color='gray', linewidth=line_width_fit) xlabel(r'$a(x)$ [# neurons]', fontsize=letter_size) ylabel(r'$p(a(x))$', fontsize=letter_size) xlim([0, 70]) ylim([0, 0.11]) xticks([0, 20, 40, 60], \ ['$0$', '$20$', '$40$', '$60$']) yticks([0, 0.1], \ ['$0$', '$0.1$']) fig_5b.spines['right'].set_visible(False) fig_5b.spines['top'].set_visible(False) fig_5b.xaxis.set_ticks_position('bottom') fig_5b.yaxis.set_ticks_position('left') tick_params(labelsize=letter_size) legend(loc=(0.5, 0.55), prop={'size':letter_size}, \ title=r'Noise level', frameon=False) fig_5b.get_legend().get_title().set_fontsize(letter_size) ######################################################################## ######################################################################## # Fig. 5C,D: Random Spikes (power-laws and activity) experiment_name = 'RandomSpikes' print experiment_name for p in ['000', '005', '010']: if p == '000': number_of_files = 65 else: number_of_files = 30 print p data_all = np.zeros((number_of_files, stable_steps)) act_density = zeros((number_of_files, 200)) for data_file in xrange(number_of_files): exper = 'result.h5' exper_path = '' h5 = tables.openFile(os.path.join(exper_path,exper),'r') data = h5.root data_all[data_file] = np.around(data.activity[0] \ [transient_steps:]*data.c.N_e) for i in xrange(int(stable_steps)): act_density[data_file, data_all[data_file, i]] += 1 act_density[data_file, :] /= act_density[data_file, :].sum() h5.close() # activity distribution and std act_density_mean = act_density.mean(0) act_density_std = act_density.std(0) # calculates avalanches T_data, S_data = analysis.avalanches(data_all, \ 'N', '200', Threshold=THETA) a_dur1, a_area1 = analysis.avalanches(data_all, 'N', '200',\ Theta_percent = 10) a_dur2, a_area2 = analysis.avalanches(data_all, 'N', '200',\ Theta_percent = 25) subplot(323) if p == '005': a_area1_pdf = pl.pdf(a_area1, 10) a_area2_pdf = pl.pdf(a_area2, 10) BinCenters1 = (a_area1_pdf[0][:-1]+a_area1_pdf[0][1:])/2. BinCenters2 = (a_area2_pdf[0][:-1]+a_area2_pdf[0][1:])/2. x_max = a_area1_pdf[0].max() interp1 = np.interp(np.arange(x_max), BinCenters1, a_area1_pdf[1]) interp2 = np.interp(np.arange(x_max), BinCenters2, a_area2_pdf[1]) fill_between(np.linspace(0,x_max,len(interp2)), interp2, interp1, facecolor='k', alpha=0.2) pl.plot_pdf(S_data, color='k', linewidth=line_width_fit) elif p == '000': a_area1_pdf = pl.pdf(a_area1, 10) a_area2_pdf = pl.pdf(a_area2, 10) BinCenters1 = (a_area1_pdf[0][:-1]+a_area1_pdf[0][1:])/2. BinCenters2 = (a_area2_pdf[0][:-1]+a_area2_pdf[0][1:])/2. x_max = a_area1_pdf[0].max() interp1 = np.interp(np.arange(x_max), BinCenters1, a_area1_pdf[1]) interp2 = np.interp(np.arange(x_max), BinCenters2, a_area2_pdf[1]) fill_between(np.linspace(0,x_max,len(interp2))[100:-100], interp2[100:-100], interp1[100:-100], facecolor='darkcyan', alpha=0.2) pl.plot_pdf(S_data, color='darkcyan', linewidth=line_width) elif p == '010': a_area1_pdf = pl.pdf(a_area1, 10) a_area2_pdf = pl.pdf(a_area2, 10) BinCenters1 = (a_area1_pdf[0][:-1]+a_area1_pdf[0][1:])/2. BinCenters2 = (a_area2_pdf[0][:-1]+a_area2_pdf[0][1:])/2. x_max = a_area1_pdf[0].max() interp1 = np.interp(np.arange(x_max), BinCenters1, a_area1_pdf[1]) interp2 = np.interp(np.arange(x_max), BinCenters2, a_area2_pdf[1]) fill_between(np.linspace(0,x_max,len(interp2)), interp2, interp1, facecolor='r', alpha=0.2) pl.plot_pdf(S_data, color='r', linewidth=line_width) xscale('log'); yscale('log') xlabel(r'$S$', fontsize=letter_size) ylabel(r'$f(S)$', fontsize=letter_size) # ticks name xlim([1, 3000]) ylim([0.00001, 0.1]) xticks([1, 10, 100, 1000], \ ['$10^0$', '$10^{1}$', '$10^{2}$', '$10^{3}$']) yticks([0.1, 0.001, 0.00001],\ ['$10^{-1}$', '$10^{-3}$', '$10^{-5}$']) fig_5c.spines['right'].set_visible(False) fig_5c.spines['top'].set_visible(False) fig_5c.xaxis.set_ticks_position('bottom') fig_5c.yaxis.set_ticks_position('left') tick_params(labelsize=letter_size) subplot(324) if p == '000': label_p = '$0\%$' plot(act_density_mean, 'c', linewidth=line_width, label=label_p) elif p == '005': label_p = '$5\%$' plot(act_density_mean, 'k', linewidth=line_width_fit, label=label_p) if p == '010': label_p = '$10\%$' plot(act_density_mean, 'r', linewidth=line_width, label=label_p) ### Binomial distribution plot ### p = 0.1 (\mu_IP); n = 200 (N_E) bino_x = np.arange(0, 40) bino_y = scipy.stats.binom.pmf(bino_x, 200,0.1) subplot(324) plot(bino_x, bino_y, '--', color='gray', linewidth=line_width_fit) xlabel(r'$a(x)$ [# neurons]', fontsize=letter_size) ylabel(r'$p(a(x))$', fontsize=letter_size) xlim([0, 70]) ylim([0, 0.11]) xticks([0, 20, 40, 60], \ ['$0$', '$20$', '$40$', '$60$']) yticks([0, 0.1], \ ['$0$', '$0.1$']) fig_5d.spines['right'].set_visible(False) fig_5d.spines['top'].set_visible(False) fig_5d.xaxis.set_ticks_position('bottom') fig_5d.yaxis.set_ticks_position('left') tick_params(labelsize=letter_size) # legend stuff legend(loc=(0.5, 0.55), prop={'size':letter_size}, \ title=r'$p_{\rm s}$', frameon=False) fig_5d.get_legend().get_title().set_fontsize(letter_size) ######################################################################## ######################################################################## # Fig. 5E, F, G: Raster plots subplot(917) for (i,sp) in enumerate(raster_low): s_train = where(sp == 1)[0] if s_train != []: vlines(s_train, i + 0.5, i + 1.5) hold('on') ylabel('Low', fontsize=letter_size) ylim([0, 200]) tick_params(axis='both', which='major', labelsize=letter_size) xticks([]) yticks([]) subplot(918) for (i,sp) in enumerate(raster_inter): s_train = where(sp == 1)[0] if s_train != []: vlines(s_train, i + 0.5, i + 1.5) hold('on') ylabel('Interm.', fontsize=letter_size) ylim([0, 200]) tick_params(axis='both', which='major', labelsize=letter_size) xticks([]) yticks([]) subplot(919) for (i,sp) in enumerate(raster_high): s_train = where(sp == 1)[0] if s_train != []: vlines(s_train, i + 0.5, i + 1.5) hold('on') xlabel('Time step', fontsize=letter_size) ylabel('High', fontsize=letter_size) ylim([0, 200]) tick_params(axis='both', which='major', labelsize=letter_size) yticks([]) xticks([0, 400, 800], \ ['$0$', '$400$', '$800$']) ######################################################################## fig_5a.annotate('A', xy=subplot_letter, xycoords='axes fraction', \ fontsize=letter_size_panel , fontweight='bold', \ horizontalalignment='right', verticalalignment='bottom') fig_5b.annotate('B', xy=subplot_letter, xycoords='axes fraction', \ fontsize=letter_size_panel , fontweight='bold', \ horizontalalignment='right', verticalalignment='bottom') fig_5c.annotate('C', xy=subplot_letter, xycoords='axes fraction', \ fontsize=letter_size_panel , fontweight='bold', \ horizontalalignment='right', verticalalignment='bottom') fig_5d.annotate('D', xy=subplot_letter, xycoords='axes fraction', \ fontsize=letter_size_panel , fontweight='bold', \ horizontalalignment='right', verticalalignment='bottom') fig_5e.annotate('E', xy=subplot_letter_long, xycoords='axes fraction', \ fontsize=letter_size_panel , fontweight='bold', \ horizontalalignment='right', verticalalignment='bottom') fig_5f.annotate('F', xy=subplot_letter_long, xycoords='axes fraction', \ fontsize=letter_size_panel , fontweight='bold', \ horizontalalignment='right', verticalalignment='bottom') fig_5g.annotate('G', xy=subplot_letter_long, xycoords='axes fraction', \ fontsize=letter_size_panel , fontweight='bold', \ horizontalalignment='right', verticalalignment='bottom') fig.subplots_adjust(wspace=.25) fig.subplots_adjust(hspace=.45) print 'Saving figures...', result_path = '../../plots/' result_name_png = 'Fig5_test.pdf' savefig(os.path.join(result_path, result_name_png), format = 'pdf') print 'done\n\n'

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2,058

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0.033329

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0.810888

0.80595

0.745093

0.737934

0.707073

0

0.066251

0.218392

14,561

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137

38.018277

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0

null

0

1

0

null

0

1

0

7

023aed51d466633ff9001a665242e2cae3ed7787

150

py

Python

QFin/tvm.py

RomanMichaelPaolucci/Q-Fin

570e7322518cb57187c77cf173f7e013123b88ab

[ "MIT" ]

94

2021-04-21T20:15:54.000Z

2022-03-31T02:39:13.000Z

QFin/tvm.py

RBBRONDANI/Q-Fin

49902da7eb013bda196c3b383c5736b008a61a17

[ "MIT" ]

null

QFin/tvm.py

RBBRONDANI/Q-Fin

49902da7eb013bda196c3b383c5736b008a61a17

[ "MIT" ]

16

2021-04-24T21:45:01.000Z

2022-03-29T20:32:07.000Z

class Annuity: def __init__(): pass class Perpetuity: def __init__(): pass class TVM: def __init__(): pass

8.823529

19

0.533333

15

150

4.533333

0.466667

0.308824

0.485294

0.470588

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150

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1

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null

1

0

null

0

1

0

7

02481bad8ed51852bad92d2f10f9ae9fc281f0fb

10,421

py

Python

google/ads/google_ads/v6/proto/services/offline_user_data_job_service_pb2_grpc.py

jphanwebstaurant/google-ads-python

600812b2afcc4d57f00b47dfe436620ce50bfe9b

[ "Apache-2.0" ]

1

2021-04-09T04:28:47.000Z

google/ads/google_ads/v6/proto/services/offline_user_data_job_service_pb2_grpc.py

jphanwebstaurant/google-ads-python

600812b2afcc4d57f00b47dfe436620ce50bfe9b

[ "Apache-2.0" ]

null

google/ads/google_ads/v6/proto/services/offline_user_data_job_service_pb2_grpc.py

jphanwebstaurant/google-ads-python

600812b2afcc4d57f00b47dfe436620ce50bfe9b

[ "Apache-2.0" ]

null

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! """Client and server classes corresponding to protobuf-defined services.""" import grpc from google.ads.google_ads.v6.proto.resources import offline_user_data_job_pb2 as google_dot_ads_dot_googleads__v6_dot_proto_dot_resources_dot_offline__user__data__job__pb2 from google.ads.google_ads.v6.proto.services import offline_user_data_job_service_pb2 as google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2 from google.longrunning import operations_pb2 as google_dot_longrunning_dot_operations__pb2 class OfflineUserDataJobServiceStub(object): """Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs. """ def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.CreateOfflineUserDataJob = channel.unary_unary( '/google.ads.googleads.v6.services.OfflineUserDataJobService/CreateOfflineUserDataJob', request_serializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.CreateOfflineUserDataJobRequest.SerializeToString, response_deserializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.CreateOfflineUserDataJobResponse.FromString, ) self.GetOfflineUserDataJob = channel.unary_unary( '/google.ads.googleads.v6.services.OfflineUserDataJobService/GetOfflineUserDataJob', request_serializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.GetOfflineUserDataJobRequest.SerializeToString, response_deserializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_resources_dot_offline__user__data__job__pb2.OfflineUserDataJob.FromString, ) self.AddOfflineUserDataJobOperations = channel.unary_unary( '/google.ads.googleads.v6.services.OfflineUserDataJobService/AddOfflineUserDataJobOperations', request_serializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.AddOfflineUserDataJobOperationsRequest.SerializeToString, response_deserializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.AddOfflineUserDataJobOperationsResponse.FromString, ) self.RunOfflineUserDataJob = channel.unary_unary( '/google.ads.googleads.v6.services.OfflineUserDataJobService/RunOfflineUserDataJob', request_serializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.RunOfflineUserDataJobRequest.SerializeToString, response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString, ) class OfflineUserDataJobServiceServicer(object): """Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs. """ def CreateOfflineUserDataJob(self, request, context): """Creates an offline user data job. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetOfflineUserDataJob(self, request, context): """Returns the offline user data job. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def AddOfflineUserDataJobOperations(self, request, context): """Adds operations to the offline user data job. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def RunOfflineUserDataJob(self, request, context): """Runs the offline user data job. When finished, the long running operation will contain the processing result or failure information, if any. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_OfflineUserDataJobServiceServicer_to_server(servicer, server): rpc_method_handlers = { 'CreateOfflineUserDataJob': grpc.unary_unary_rpc_method_handler( servicer.CreateOfflineUserDataJob, request_deserializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.CreateOfflineUserDataJobRequest.FromString, response_serializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.CreateOfflineUserDataJobResponse.SerializeToString, ), 'GetOfflineUserDataJob': grpc.unary_unary_rpc_method_handler( servicer.GetOfflineUserDataJob, request_deserializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.GetOfflineUserDataJobRequest.FromString, response_serializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_resources_dot_offline__user__data__job__pb2.OfflineUserDataJob.SerializeToString, ), 'AddOfflineUserDataJobOperations': grpc.unary_unary_rpc_method_handler( servicer.AddOfflineUserDataJobOperations, request_deserializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.AddOfflineUserDataJobOperationsRequest.FromString, response_serializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.AddOfflineUserDataJobOperationsResponse.SerializeToString, ), 'RunOfflineUserDataJob': grpc.unary_unary_rpc_method_handler( servicer.RunOfflineUserDataJob, request_deserializer=google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.RunOfflineUserDataJobRequest.FromString, response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'google.ads.googleads.v6.services.OfflineUserDataJobService', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,)) # This class is part of an EXPERIMENTAL API. class OfflineUserDataJobService(object): """Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs. """ @staticmethod def CreateOfflineUserDataJob(request, target, options=(), channel_credentials=None, call_credentials=None, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/google.ads.googleads.v6.services.OfflineUserDataJobService/CreateOfflineUserDataJob', google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.CreateOfflineUserDataJobRequest.SerializeToString, google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.CreateOfflineUserDataJobResponse.FromString, options, channel_credentials, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetOfflineUserDataJob(request, target, options=(), channel_credentials=None, call_credentials=None, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/google.ads.googleads.v6.services.OfflineUserDataJobService/GetOfflineUserDataJob', google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.GetOfflineUserDataJobRequest.SerializeToString, google_dot_ads_dot_googleads__v6_dot_proto_dot_resources_dot_offline__user__data__job__pb2.OfflineUserDataJob.FromString, options, channel_credentials, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def AddOfflineUserDataJobOperations(request, target, options=(), channel_credentials=None, call_credentials=None, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/google.ads.googleads.v6.services.OfflineUserDataJobService/AddOfflineUserDataJobOperations', google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.AddOfflineUserDataJobOperationsRequest.SerializeToString, google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.AddOfflineUserDataJobOperationsResponse.FromString, options, channel_credentials, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def RunOfflineUserDataJob(request, target, options=(), channel_credentials=None, call_credentials=None, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/google.ads.googleads.v6.services.OfflineUserDataJobService/RunOfflineUserDataJob', google_dot_ads_dot_googleads__v6_dot_proto_dot_services_dot_offline__user__data__job__service__pb2.RunOfflineUserDataJobRequest.SerializeToString, google_dot_longrunning_dot_operations__pb2.Operation.FromString, options, channel_credentials, call_credentials, compression, wait_for_ready, timeout, metadata)

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5a55007cc4ace720eed8291694ffc85671e23a5c

185

py

Python

src/pytezos/rpc/__init__.py

konchunas/pytezos

65576d18bdf1956fae8ea21241b6c43a38921b83

[ "MIT" ]

98

2019-02-07T16:33:38.000Z

2022-03-31T15:53:41.000Z

src/pytezos/rpc/__init__.py

konchunas/pytezos

65576d18bdf1956fae8ea21241b6c43a38921b83

[ "MIT" ]

152

2019-05-20T16:38:56.000Z

2022-03-30T14:24:38.000Z

src/pytezos/rpc/__init__.py

konchunas/pytezos

65576d18bdf1956fae8ea21241b6c43a38921b83

[ "MIT" ]

34

2019-07-25T12:03:51.000Z

2021-11-11T22:23:38.000Z

from pytezos.rpc.helpers import * from pytezos.rpc.node import RpcMultiNode, RpcNode from pytezos.rpc.protocol import * from pytezos.rpc.search import * from pytezos.rpc.shell import *

30.833333

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Python

src/core_utils/validation.py

MoveBigRocks/core-utils

c167f80059e87db45564bf5e78f10d7e4ce18f21

[ "MIT" ]

null

src/core_utils/validation.py

MoveBigRocks/core-utils

c167f80059e87db45564bf5e78f10d7e4ce18f21

[ "MIT" ]

null

src/core_utils/validation.py

MoveBigRocks/core-utils

c167f80059e87db45564bf5e78f10d7e4ce18f21

[ "MIT" ]

null

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10

5a83f56d991d35556e353df24ee7d82dce508461

54,099

py

Python

tests/sedml/test_sedml_exec.py

virtualcell/Biosimulators_utils

1b34e1e0a9ace706d245e9d515d0fae1e55a248d

[ "MIT" ]

null

tests/sedml/test_sedml_exec.py

virtualcell/Biosimulators_utils

1b34e1e0a9ace706d245e9d515d0fae1e55a248d

[ "MIT" ]

null

tests/sedml/test_sedml_exec.py

virtualcell/Biosimulators_utils

1b34e1e0a9ace706d245e9d515d0fae1e55a248d

[ "MIT" ]

null

from biosimulators_utils.config import get_config from biosimulators_utils.log.data_model import ( Status, CombineArchiveLog, SedDocumentLog, TaskLog, ReportLog) from biosimulators_utils.log.utils import init_sed_document_log from biosimulators_utils.plot.data_model import PlotFormat from biosimulators_utils.report.data_model import VariableResults, DataSetResults, ReportResults, ReportFormat from biosimulators_utils.report.io import ReportReader from biosimulators_utils.report.warnings import RepeatDataSetLabelsWarning from biosimulators_utils.sedml import data_model from biosimulators_utils.sedml import exec from biosimulators_utils.sedml import io from biosimulators_utils.sedml.exceptions import SedmlExecutionError from biosimulators_utils.sedml.warnings import NoTasksWarning, NoOutputsWarning, InconsistentVariableShapesWarning from lxml import etree from unittest import mock import numpy import numpy.testing import os import shutil import tempfile import unittest class ExecTaskCase(unittest.TestCase): def setUp(self): self.tmp_dir = tempfile.mkdtemp() def tearDown(self): shutil.rmtree(self.tmp_dir) def test_successful(self): doc = data_model.SedDocument() doc.models.append(data_model.Model( id='model1', source='model1.xml', language='urn:sedml:language:sbml', )) doc.models.append(data_model.Model( id='model2', source='https://models.edu/model1.xml', language='urn:sedml:language:cellml', )) doc.simulations.append(data_model.SteadyStateSimulation( id='ss_sim', )) doc.simulations.append(data_model.UniformTimeCourseSimulation( id='time_course_sim', initial_time=10., output_start_time=20., output_end_time=30., number_of_points=5, )) doc.tasks.append(data_model.Task( id='task_1_ss', model=doc.models[0], simulation=doc.simulations[0], )) doc.tasks.append(data_model.Task( id='task_2_time_course', model=doc.models[1], simulation=doc.simulations[1], )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), ], math='data_gen_1_var_1', )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_2', variables=[ data_model.Variable( id='data_gen_2_var_2', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_2']/@concentration", task=doc.tasks[0], ), ], math='data_gen_2_var_2', )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_3', variables=[ data_model.Variable( id='data_gen_3_var_3', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_3']/@concentration", task=doc.tasks[1], ), ], math='data_gen_3_var_3', )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_4', variables=[ data_model.Variable( id='data_gen_4_var_4', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_4']/@concentration", task=doc.tasks[1], ), ], math='data_gen_4_var_4', )) doc.outputs.append(data_model.Report( id='report_1', data_sets=[ data_model.DataSet( id='dataset_1', label='dataset_1', data_generator=doc.data_generators[0], ), data_model.DataSet( id='dataset_2', label='dataset_2', data_generator=doc.data_generators[2], ), ], )) doc.outputs.append(data_model.Report( id='report_2', data_sets=[ data_model.DataSet( id='dataset_3', label='dataset_3', data_generator=doc.data_generators[1], ), data_model.DataSet( id='dataset_4', label='dataset_4', data_generator=doc.data_generators[3], ), ], )) doc.outputs.append(data_model.Report( id='report_3', data_sets=[ data_model.DataSet( id='dataset_5', label='dataset_5', data_generator=doc.data_generators[0], ), ], )) doc.outputs.append(data_model.Report( id='report_4', data_sets=[ data_model.DataSet( id='dataset_6', label='dataset_6', data_generator=doc.data_generators[3], ), data_model.DataSet( id='dataset_7', label='dataset_7', data_generator=doc.data_generators[3], ), ], )) filename = os.path.join(self.tmp_dir, 'test.sedml') io.SedmlSimulationWriter().run(doc, filename) def execute_task(task, variables, log): results = VariableResults() if task.id == 'task_1_ss': results[doc.data_generators[0].variables[0].id] = numpy.array((1., 2.)) results[doc.data_generators[1].variables[0].id] = numpy.array((3., 4.)) else: results[doc.data_generators[2].variables[0].id] = numpy.array((5., 6.)) results[doc.data_generators[3].variables[0].id] = numpy.array((7., 8.)) return results, log working_dir = os.path.dirname(filename) with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir = os.path.join(self.tmp_dir, 'results') with mock.patch('requests.get', return_value=mock.Mock(raise_for_status=lambda: None, content=b'')): output_results, _ = exec.exec_sed_doc(execute_task, filename, working_dir, out_dir, report_formats=[ReportFormat.csv], plot_formats=[]) expected_output_results = ReportResults({ doc.outputs[0].id: DataSetResults({ 'dataset_1': numpy.array((1., 2.)), 'dataset_2': numpy.array((5., 6.)), }), doc.outputs[1].id: DataSetResults({ 'dataset_3': numpy.array((3., 4.)), 'dataset_4': numpy.array((7., 8.)), }), doc.outputs[2].id: DataSetResults({ 'dataset_5': numpy.array((1., 2.)), }), doc.outputs[3].id: DataSetResults({ 'dataset_6': numpy.array((7., 8.)), 'dataset_7': numpy.array((7., 8.)), }), }) self.assertEqual(sorted(output_results.keys()), sorted(expected_output_results.keys())) for report_id, data_set_results in output_results.items(): self.assertEqual(sorted(output_results[report_id].keys()), sorted(expected_output_results[report_id].keys())) for data_set_id in data_set_results.keys(): numpy.testing.assert_allclose( output_results[report_id][data_set_id], expected_output_results[report_id][data_set_id]) data_set_results = ReportReader().run(doc.outputs[0], out_dir, doc.outputs[0].id, format=ReportFormat.csv) for data_set in doc.outputs[0].data_sets: numpy.testing.assert_allclose( output_results[doc.outputs[0].id][data_set.id], data_set_results[data_set.id]) data_set_results = ReportReader().run(doc.outputs[1], out_dir, doc.outputs[1].id, format=ReportFormat.csv) for data_set in doc.outputs[1].data_sets: numpy.testing.assert_allclose( output_results[doc.outputs[1].id][data_set.id], data_set_results[data_set.id]) # save in HDF5 format doc.models[1].source = doc.models[0].source io.SedmlSimulationWriter().run(doc, filename) shutil.rmtree(out_dir) exec.exec_sed_doc(execute_task, filename, os.path.dirname(filename), out_dir, report_formats=[ReportFormat.h5], plot_formats=[]) data_set_results = ReportReader().run(doc.outputs[0], out_dir, doc.outputs[0].id, format=ReportFormat.h5) for data_set in doc.outputs[0].data_sets: numpy.testing.assert_allclose( output_results[doc.outputs[0].id][data_set.id], data_set_results[data_set.id]) data_set_results = ReportReader().run(doc.outputs[1], out_dir, doc.outputs[1].id, format=ReportFormat.h5) for data_set in doc.outputs[1].data_sets: numpy.testing.assert_allclose( output_results[doc.outputs[1].id][data_set.id], data_set_results[data_set.id]) # track execution status shutil.rmtree(out_dir) log = SedDocumentLog( tasks={ 'task_1_ss': TaskLog(id='task_1_ss', status=Status.QUEUED), 'task_2_time_course': TaskLog(id='task_2_time_course', status=Status.QUEUED), }, outputs={ 'report_1': ReportLog(id='report_1', status=Status.QUEUED, data_sets={ 'dataset_1': Status.QUEUED, 'dataset_2': Status.QUEUED, }), 'report_2': ReportLog(id='report_2', status=Status.QUEUED, data_sets={ 'dataset_3': Status.QUEUED, 'dataset_4': Status.QUEUED, }), 'report_3': ReportLog(id='report_3', status=Status.QUEUED, data_sets={ 'dataset_5': Status.QUEUED, }), 'report_4': ReportLog(id='report_4', status=Status.QUEUED, data_sets={ 'dataset_6': Status.QUEUED, 'dataset_7': Status.QUEUED, }) }, ) log.parent = CombineArchiveLog(out_dir=out_dir) log.tasks['task_1_ss'].parent = log log.tasks['task_2_time_course'].parent = log log.outputs['report_1'].parent = log log.outputs['report_2'].parent = log log.outputs['report_3'].parent = log log.outputs['report_4'].parent = log exec.exec_sed_doc(execute_task, filename, os.path.dirname(filename), out_dir, report_formats=[ReportFormat.h5], plot_formats=[], log=log) expected_log = { 'location': None, 'status': None, 'exception': None, 'skipReason': None, 'output': None, 'duration': None, 'tasks': [ { 'id': 'task_1_ss', 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.tasks['task_1_ss'].output, 'duration': log.tasks['task_1_ss'].duration, 'algorithm': None, 'simulatorDetails': None, }, { 'id': 'task_2_time_course', 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.tasks['task_2_time_course'].output, 'duration': log.tasks['task_2_time_course'].duration, 'algorithm': None, 'simulatorDetails': None, }, ], 'outputs': [ { 'id': 'report_1', 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.outputs['report_1'].output, 'duration': log.outputs['report_1'].duration, 'dataSets': [ {'id': 'dataset_1', 'status': 'SUCCEEDED'}, {'id': 'dataset_2', 'status': 'SUCCEEDED'}, ], }, { 'id': 'report_2', 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.outputs['report_2'].output, 'duration': log.outputs['report_2'].duration, 'dataSets': [ {'id': 'dataset_3', 'status': 'SUCCEEDED'}, {'id': 'dataset_4', 'status': 'SUCCEEDED'}, ], }, { 'id': 'report_3', 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.outputs['report_3'].output, 'duration': log.outputs['report_3'].duration, 'dataSets': [ {'id': 'dataset_5', 'status': 'SUCCEEDED'}, ], }, { 'id': 'report_4', 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.outputs['report_4'].output, 'duration': log.outputs['report_4'].duration, 'dataSets': [ {'id': 'dataset_6', 'status': 'SUCCEEDED'}, {'id': 'dataset_7', 'status': 'SUCCEEDED'}, ], }, ], } actual = log.to_json() actual['tasks'].sort(key=lambda task: task['id']) actual['outputs'].sort(key=lambda output: output['id']) for output in actual['outputs']: output['dataSets'].sort(key=lambda dat_set: dat_set['id']) self.assertEqual(actual, expected_log) self.assertTrue(os.path.isfile(os.path.join(out_dir, get_config().LOG_PATH))) def test_with_model_changes(self): doc = data_model.SedDocument() model1 = data_model.Model( id='model1', source='model1.xml', language='urn:sedml:language:sbml', ) doc.models.append(model1) model2 = data_model.Model( id='model2', source='model1.xml', language='urn:sedml:language:sbml', changes=[ data_model.ModelAttributeChange( target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Z']/@id", new_value="Z2", ) ] ) doc.models.append(model2) model3 = data_model.Model( id='model3', source='#model2', language='urn:sedml:language:sbml', changes=[ data_model.ModelAttributeChange( target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Z2']/@initialConcentration", new_value="4.0", ), data_model.ComputeModelChange( target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Z2']/@initialConcentration", parameters=[ data_model.Parameter( id='p', value=3.1, ), ], variables=[ data_model.Variable( id='var_Z2', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Z2']/@initialConcentration", ), ], math='p * var_Z2', ), ], ) model3.changes[1].variables[0].model = model3 doc.models.append(model3) model1.changes.append( data_model.ModelAttributeChange( target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='X']/@initialConcentration", new_value="2.5", ) ), model1.changes.append( data_model.ComputeModelChange( target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Y']/@initialConcentration", parameters=[ data_model.Parameter(id='a', value=0.2), data_model.Parameter(id='b', value=2.0), ], variables=[ data_model.Variable( id='y', model=model1, target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='X']/@initialConcentration", ), data_model.Variable( id='z', model=model3, target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Z2']/@initialConcentration", ), ], math='a * y + b * z', ), ) doc.simulations.append(data_model.SteadyStateSimulation( id='sim1', )) doc.tasks.append(data_model.Task( id='task1', model=doc.models[0], simulation=doc.simulations[0], )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='X']/@initialConcentration", task=doc.tasks[0], ), ], math='data_gen_1_var_1', )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_2', variables=[ data_model.Variable( id='data_gen_2_var_2', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Y']/@initialConcentration", task=doc.tasks[0], ), ], math='data_gen_2_var_2', )) doc.outputs.append(data_model.Report( id='report_1', data_sets=[ data_model.DataSet( id='dataset_1', label='dataset_1', data_generator=doc.data_generators[0], ), data_model.DataSet( id='dataset_2', label='dataset_2', data_generator=doc.data_generators[1], ), ], )) filename = os.path.join(self.tmp_dir, 'test.sedml') working_dir = os.path.dirname(filename) io.SedmlSimulationWriter().run(doc, filename) shutil.copyfile( os.path.join(os.path.dirname(__file__), '..', 'fixtures', 'sbml-three-species.xml'), os.path.join(working_dir, 'model1.xml')) def execute_task(task, variables, log): et = etree.parse(task.model.source) results = VariableResults() for variable in variables: obj_xpath, _, attr = variable.target.rpartition('/@') obj = et.xpath(obj_xpath, namespaces={'sbml': 'http://www.sbml.org/sbml/level3/version2'})[0] results[variable.id] = numpy.array((float(obj.get(attr)),)) return results, log out_dir = os.path.join(self.tmp_dir, 'results') report_results, _ = exec.exec_sed_doc(execute_task, filename, working_dir, out_dir, apply_xml_model_changes=False) numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[0].id], numpy.array((1., ))) numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[1].id], numpy.array((2., ))) report_results, _ = exec.exec_sed_doc(execute_task, filename, working_dir, out_dir, apply_xml_model_changes=True) numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[0].id], numpy.array((2.5, ))) expected_value = 0.2 * 2.5 + 2.0 * 3.1 * 4.0 numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[1].id], numpy.array((expected_value))) def test_warnings(self): # no tasks doc = data_model.SedDocument() filename = os.path.join(self.tmp_dir, 'test.sedml') io.SedmlSimulationWriter().run(doc, filename) def execute_task(task, variables, log): return VariableResults(), log out_dir = os.path.join(self.tmp_dir, 'results') with self.assertWarns(NoTasksWarning): exec.exec_sed_doc(execute_task, filename, os.path.dirname(filename), out_dir) # no outputs doc = data_model.SedDocument() doc.models.append(data_model.Model( id='model1', source='model1.xml', language='urn:sedml:language:sbml', changes=[ data_model.ModelAttributeChange( target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='X']/@initialConcentration", new_value="2.0", ), ], )) doc.simulations.append(data_model.SteadyStateSimulation( id='sim1', )) doc.tasks.append(data_model.Task( id='task1', model=doc.models[0], simulation=doc.simulations[0], )) doc.tasks.append(data_model.Task( id='task2', model=doc.models[0], simulation=doc.simulations[0], )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='X']/@initialConcentration", task=doc.tasks[0], ), ], math='data_gen_1_var_1', )) doc.outputs.append(data_model.Report(id='report_1', data_sets=[ data_model.DataSet(id='data_set_1', label='data_set_1', data_generator=doc.data_generators[0]), ])) filename = os.path.join(self.tmp_dir, 'test.sedml') io.SedmlSimulationWriter().run(doc, filename) def execute_task(task, variables, log): if task.id == 'task1': return VariableResults({'data_gen_1_var_1': numpy.array(1.)}), log else: return VariableResults(), log working_dir = os.path.dirname(filename) with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir = os.path.join(self.tmp_dir, 'results') with self.assertWarns(NoOutputsWarning): exec.exec_sed_doc(execute_task, filename, working_dir, out_dir) def test_errors(self): # error: variable not recorded doc = data_model.SedDocument() doc.models.append(data_model.Model( id='model1', source='model1.xml', language='urn:sedml:language:sbml', )) doc.simulations.append(data_model.SteadyStateSimulation( id='sim1', )) doc.tasks.append(data_model.Task( id='task1', model=doc.models[0], simulation=doc.simulations[0], )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), ], math='data_gen_1_var_1', )) doc.outputs.append(data_model.Report( id='report_1', data_sets=[ data_model.DataSet( id='dataset_1', label='dataset_1', data_generator=doc.data_generators[0], ), ], )) filename = os.path.join(self.tmp_dir, 'test.sedml') io.SedmlSimulationWriter().run(doc, filename) def execute_task(task, variables, log): return VariableResults(), log working_dir = os.path.dirname(filename) with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir = os.path.join(self.tmp_dir, 'results') with self.assertRaisesRegex(SedmlExecutionError, 'did not generate the following expected variables'): exec.exec_sed_doc(execute_task, filename, working_dir, out_dir) # error: unsupported type of task doc = data_model.SedDocument() doc.tasks.append(mock.Mock( id='task_1_ss', )) out_dir = os.path.join(self.tmp_dir, 'results') with self.assertRaisesRegex(SedmlExecutionError, 'not supported'): exec.exec_sed_doc(execute_task, doc, '.', out_dir) # error: unsupported data generators doc = data_model.SedDocument() doc.models.append(data_model.Model( id='model1', source='model1.xml', language='urn:sedml:language:sbml', )) doc.simulations.append(data_model.SteadyStateSimulation( id='sim1', )) doc.tasks.append(data_model.Task( id='task1', model=doc.models[0], simulation=doc.simulations[0], )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), data_model.Variable( id='data_gen_1_var_2', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), ], math='data_gen_1_var_1 * data_gen_1_var_2', )) doc.outputs.append(data_model.Report( id='report_1', data_sets=[ data_model.DataSet( id='dataset_1', label='dataset_1', data_generator=doc.data_generators[0], ), ], )) def execute_task(task, variables, log): results = VariableResults() results[doc.data_generators[0].variables[0].id] = numpy.array((1.,)) results[doc.data_generators[0].variables[1].id] = numpy.array((1.,)) return results, log working_dir = self.tmp_dir with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir = os.path.join(self.tmp_dir, 'results') exec.exec_sed_doc(execute_task, doc, working_dir, out_dir) # error: inconsistent math doc.data_generators = [ data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), ], math='xx', ), ] doc.outputs = [ data_model.Report( id='report_1', data_sets=[ data_model.DataSet( id='dataset_1', label='dataset_1', data_generator=doc.data_generators[0], ), ] ) ] def execute_task(task, variables, log): results = VariableResults() results[doc.data_generators[0].variables[0].id] = numpy.array((1.,)) return results, log working_dir = self.tmp_dir with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir = os.path.join(self.tmp_dir, 'results') with self.assertRaisesRegex(SedmlExecutionError, 'could not be evaluated'): exec.exec_sed_doc(execute_task, doc, working_dir, out_dir) # error: variables have inconsistent shapes doc.data_generators = [ data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), data_model.Variable( id='data_gen_1_var_2', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_2']/@concentration", task=doc.tasks[0], ), ], math='data_gen_1_var_1 * data_gen_1_var_2', ), ] doc.outputs = [ data_model.Report( id='report_1', data_sets=[ data_model.DataSet( id='dataset_1', label='dataset_1', data_generator=doc.data_generators[0], ), ], ), ] def execute_task(task, variables, log): results = VariableResults() results[doc.data_generators[0].variables[0].id] = numpy.array((1.,)) results[doc.data_generators[0].variables[1].id] = numpy.array((1., 2.)) return results, log working_dir = self.tmp_dir with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir = os.path.join(self.tmp_dir, 'results') with self.assertWarnsRegex(InconsistentVariableShapesWarning, 'do not have consistent shapes'): exec.exec_sed_doc(execute_task, doc, working_dir, out_dir) # error: data generators have inconsistent shapes doc.data_generators = [ data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), ], math='data_gen_1_var_1', ), data_model.DataGenerator( id='data_gen_2', variables=[ data_model.Variable( id='data_gen_2_var_2', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_2']/@concentration", task=doc.tasks[0], ), ], math='data_gen_2_var_2', ), data_model.DataGenerator( id='data_gen_3', variables=[ data_model.Variable( id='data_gen_3_var_3', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_3']/@concentration", task=doc.tasks[0], ), ], math='data_gen_3_var_3', ), ] doc.outputs = [ data_model.Report( id='report_1', data_sets=[ data_model.DataSet( id='dataset_1', label='dataset_1', data_generator=doc.data_generators[0], ), data_model.DataSet( id='dataset_2', label='dataset_2', data_generator=doc.data_generators[1], ), ], ), ] def execute_task(task, variables, log): results = VariableResults() results[doc.data_generators[0].variables[0].id] = numpy.array((1.,)) results[doc.data_generators[1].variables[0].id] = numpy.array((1., 2.)) results[doc.data_generators[2].variables[0].id] = numpy.array(((1., 2., 3.), (4., 5., 6.), (7., 8., 9.))) return results, log working_dir = self.tmp_dir with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir = os.path.join(self.tmp_dir, 'results') with self.assertWarnsRegex(UserWarning, 'do not have consistent shapes'): report_results, _ = exec.exec_sed_doc(execute_task, doc, working_dir, out_dir) numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[0].id], numpy.array((1.))) numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[1].id], numpy.array((1., 2.))) doc.outputs[0].data_sets.append( data_model.DataSet( id='dataset_3', label='dataset_3', data_generator=doc.data_generators[2], ), ) working_dir = self.tmp_dir with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir = os.path.join(self.tmp_dir, 'results2') with self.assertRaisesRegex(SedmlExecutionError, 'Multidimensional reports cannot be exported to CSV'): with self.assertWarnsRegex(UserWarning, 'do not have consistent shapes'): exec.exec_sed_doc(execute_task, doc, working_dir, out_dir) with self.assertWarnsRegex(UserWarning, 'do not have consistent shapes'): report_results, _ = exec.exec_sed_doc(execute_task, doc, working_dir, out_dir, report_formats=[ReportFormat.h5]) numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[0].id], numpy.array((1.,))) numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[1].id], numpy.array((1., 2.))) numpy.testing.assert_equal(report_results[doc.outputs[0].id][doc.outputs[0].data_sets[2].id], numpy.array(((1., 2., 3.), (4., 5., 6.), (7., 8., 9.)))) # warning: data set labels are not unique doc.data_generators=[ data_model.DataGenerator( id='data_gen_1', variables=[ data_model.Variable( id='data_gen_1_var_1', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), ], math='data_gen_1_var_1', ), data_model.DataGenerator( id='data_gen_2', variables=[ data_model.Variable( id='data_gen_2_var_2', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var_1']/@concentration", task=doc.tasks[0], ), ], math='data_gen_2_var_2', ), ] doc.outputs=[ data_model.Report( id='report_1', data_sets=[ data_model.DataSet( id='dataset_1', label='dataset_label', data_generator=doc.data_generators[0], ), data_model.DataSet( id='dataset_2', label='dataset_label', data_generator=doc.data_generators[1], ), ], ), ] def execute_task(task, variables, log): results=VariableResults() results[doc.data_generators[0].variables[0].id]=numpy.array((1., 2.)) results[doc.data_generators[1].variables[0].id]=numpy.array((2., 3.)) return results, log working_dir=self.tmp_dir with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir=os.path.join(self.tmp_dir, 'results') with self.assertWarnsRegex(RepeatDataSetLabelsWarning, 'should have unique labels'): exec.exec_sed_doc(execute_task, doc, working_dir, out_dir) # error: unsupported outputs doc.outputs=[ mock.Mock(id='unsupported') ] working_dir=self.tmp_dir with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass log=SedDocumentLog(tasks={}, outputs={}) for task in doc.tasks: log.tasks[task.id]=TaskLog(parent=log) for output in doc.outputs: log.outputs[output.id]=ReportLog(parent=log) with self.assertRaisesRegex(SedmlExecutionError, 'are not supported'): exec.exec_sed_doc(execute_task, doc, working_dir, out_dir, log=log) def test_2d_plot(self): doc=data_model.SedDocument() doc.models.append(data_model.Model( id='model', source='model1.xml', language='urn:sedml:language:sbml', )) doc.simulations.append(data_model.UniformTimeCourseSimulation( id='sim', initial_time=0., output_start_time=10., output_end_time=10., number_of_points=10, )) doc.tasks.append(data_model.Task( id='task1', model=doc.models[0], simulation=doc.simulations[0], )) doc.tasks.append(data_model.Task( id='task2', model=doc.models[0], simulation=doc.simulations[0], )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_time', variables=[ data_model.Variable( id='time', symbol=data_model.Symbol.time, task=doc.tasks[0], ), ], math='time', )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_var', variables=[ data_model.Variable( id='var', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var']/@concentration", task=doc.tasks[1], ), ], math='var', )) doc.outputs.append(data_model.Plot2D( id='plot_2d_1', curves=[ data_model.Curve( id='curve1', x_data_generator=doc.data_generators[0], y_data_generator=doc.data_generators[0], x_scale=data_model.AxisScale.linear, y_scale=data_model.AxisScale.linear, ), data_model.Curve( id='curve2', x_data_generator=doc.data_generators[1], y_data_generator=doc.data_generators[1], x_scale=data_model.AxisScale.linear, y_scale=data_model.AxisScale.linear, ), ], )) doc.outputs.append(data_model.Plot2D( id='plot_2d_2', curves=[ data_model.Curve( id='curve3', x_data_generator=doc.data_generators[1], y_data_generator=doc.data_generators[1], x_scale=data_model.AxisScale.linear, y_scale=data_model.AxisScale.linear, ), ], )) filename=os.path.join(self.tmp_dir, 'test.sedml') io.SedmlSimulationWriter().run(doc, filename) def execute_task(task, variables, log=None): results=VariableResults() results[doc.data_generators[0].variables[0].id]=numpy.linspace(0., 10., 10 + 1) results[doc.data_generators[1].variables[0].id]=2 * results[doc.data_generators[0].variables[0].id] return results, log working_dir=os.path.dirname(filename) with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir=os.path.join(self.tmp_dir, 'results') _, log=exec.exec_sed_doc(execute_task, filename, working_dir, out_dir, plot_formats=[PlotFormat.pdf]) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_2d_1.pdf'))) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_2d_2.pdf'))) self.assertEqual( log.to_json()['outputs'], [ { 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.to_json()['outputs'][0]['output'], 'duration': log.to_json()['outputs'][0]['duration'], 'id': 'plot_2d_1', 'curves': [ {'id': 'curve1', 'status': 'SUCCEEDED'}, {'id': 'curve2', 'status': 'SUCCEEDED'}, ], }, { 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.to_json()['outputs'][1]['output'], 'duration': log.to_json()['outputs'][1]['duration'], 'id': 'plot_2d_2', 'curves': [ {'id': 'curve3', 'status': 'SUCCEEDED'}, ], }, ] ) os.remove(os.path.join(out_dir, 'plot_2d_1.pdf')) os.remove(os.path.join(out_dir, 'plot_2d_2.pdf')) # error with a curve doc.data_generators[0].math='time * var' io.SedmlSimulationWriter().run(doc, filename) log=init_sed_document_log(doc) with self.assertRaisesRegex(SedmlExecutionError, "name 'var' is not defined"): exec.exec_sed_doc(execute_task, filename, working_dir, out_dir, log=log, plot_formats=[PlotFormat.pdf]) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_2d_1.pdf'))) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_2d_2.pdf'))) self.assertEqual( log.to_json()['outputs'], [ { 'status': 'FAILED', 'exception': log.to_json()['outputs'][0]['exception'], 'skipReason': None, 'output': log.to_json()['outputs'][0]['output'], 'duration': log.to_json()['outputs'][0]['duration'], 'id': 'plot_2d_1', 'curves': [ {'id': 'curve1', 'status': 'FAILED'}, {'id': 'curve2', 'status': 'SUCCEEDED'}, ], }, { 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.to_json()['outputs'][1]['output'], 'duration': log.to_json()['outputs'][1]['duration'], 'id': 'plot_2d_2', 'curves': [ {'id': 'curve3', 'status': 'SUCCEEDED'}, ], }, ] ) # error with a task def execute_task(task, variables, log=None): results=VariableResults() results[doc.data_generators[0].variables[0].id]=None results[doc.data_generators[1].variables[0].id]=2 * numpy.linspace(0., 10., 10 + 1) return results, log doc.data_generators[0].math='time' io.SedmlSimulationWriter().run(doc, filename) log=init_sed_document_log(doc) with self.assertRaisesRegex(SedmlExecutionError, "Some generators could not be produced:"): exec.exec_sed_doc(execute_task, filename, working_dir, out_dir, log=log, plot_formats=[PlotFormat.pdf]) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_2d_1.pdf'))) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_2d_2.pdf'))) self.assertEqual( log.to_json()['outputs'], [ { 'status': 'FAILED', 'exception': log.to_json()['outputs'][0]['exception'], 'skipReason': None, 'output': log.to_json()['outputs'][0]['output'], 'duration': log.to_json()['outputs'][0]['duration'], 'id': 'plot_2d_1', 'curves': [ {'id': 'curve1', 'status': 'FAILED'}, {'id': 'curve2', 'status': 'SUCCEEDED'}, ], }, { 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.to_json()['outputs'][1]['output'], 'duration': log.to_json()['outputs'][1]['duration'], 'id': 'plot_2d_2', 'curves': [ {'id': 'curve3', 'status': 'SUCCEEDED'}, ], }, ] ) def test_3d_plot(self): doc=data_model.SedDocument() doc.models.append(data_model.Model( id='model', source='model1.xml', language='urn:sedml:language:sbml', )) doc.simulations.append(data_model.UniformTimeCourseSimulation( id='sim', initial_time=0., output_start_time=10., output_end_time=10., number_of_points=10, )) doc.tasks.append(data_model.Task( id='task1', model=doc.models[0], simulation=doc.simulations[0], )) doc.tasks.append(data_model.Task( id='task2', model=doc.models[0], simulation=doc.simulations[0], )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_time', variables=[ data_model.Variable( id='time', symbol=data_model.Symbol.time, task=doc.tasks[0], ), ], math='time', )) doc.data_generators.append(data_model.DataGenerator( id='data_gen_var', variables=[ data_model.Variable( id='var', target="/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:speces[@id='var']/@concentration", task=doc.tasks[1], ), ], math='var', )) doc.outputs.append(data_model.Plot3D( id='plot_3d_1', surfaces=[ data_model.Surface( id='surface1', x_data_generator=doc.data_generators[0], y_data_generator=doc.data_generators[0], z_data_generator=doc.data_generators[0], x_scale=data_model.AxisScale.linear, y_scale=data_model.AxisScale.linear, z_scale=data_model.AxisScale.linear, ), data_model.Surface( id='surface2', x_data_generator=doc.data_generators[1], y_data_generator=doc.data_generators[1], z_data_generator=doc.data_generators[1], x_scale=data_model.AxisScale.linear, y_scale=data_model.AxisScale.linear, z_scale=data_model.AxisScale.linear, ), ], )) doc.outputs.append(data_model.Plot3D( id='plot_3d_2', surfaces=[ data_model.Surface( id='surface3', x_data_generator=doc.data_generators[1], y_data_generator=doc.data_generators[1], z_data_generator=doc.data_generators[1], x_scale=data_model.AxisScale.linear, y_scale=data_model.AxisScale.linear, z_scale=data_model.AxisScale.linear, ), ], )) filename=os.path.join(self.tmp_dir, 'test.sedml') io.SedmlSimulationWriter().run(doc, filename) def execute_task(task, variables, log=None): results=VariableResults() x=numpy.arange(-5, 5, 0.25) x, _=numpy.meshgrid(x, x) results[doc.data_generators[0].variables[0].id]=x results[doc.data_generators[1].variables[0].id]=x return results, log working_dir=os.path.dirname(filename) with open(os.path.join(working_dir, doc.models[0].source), 'w'): pass out_dir=os.path.join(self.tmp_dir, 'results') _, log=exec.exec_sed_doc(execute_task, filename, working_dir, out_dir, plot_formats=[PlotFormat.pdf]) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_3d_1.pdf'))) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_3d_2.pdf'))) self.assertEqual( log.to_json()['outputs'], [ { 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.to_json()['outputs'][0]['output'], 'duration': log.to_json()['outputs'][0]['duration'], 'id': 'plot_3d_1', 'surfaces': [ {'id': 'surface1', 'status': 'SUCCEEDED'}, {'id': 'surface2', 'status': 'SUCCEEDED'}, ], }, { 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.to_json()['outputs'][1]['output'], 'duration': log.to_json()['outputs'][1]['duration'], 'id': 'plot_3d_2', 'surfaces': [ {'id': 'surface3', 'status': 'SUCCEEDED'}, ], }, ] ) os.remove(os.path.join(out_dir, 'plot_3d_1.pdf')) os.remove(os.path.join(out_dir, 'plot_3d_2.pdf')) # error with a surface doc.data_generators[0].math='time * var' io.SedmlSimulationWriter().run(doc, filename) log=init_sed_document_log(doc) with self.assertRaisesRegex(SedmlExecutionError, "name 'var' is not defined"): exec.exec_sed_doc(execute_task, filename, working_dir, out_dir, log=log, plot_formats=[PlotFormat.pdf]) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_3d_1.pdf'))) self.assertTrue(os.path.isfile(os.path.join(out_dir, 'plot_3d_2.pdf'))) self.assertEqual( log.to_json()['outputs'], [ { 'status': 'FAILED', 'exception': log.to_json()['outputs'][0]['exception'], 'skipReason': None, 'output': log.to_json()['outputs'][0]['output'], 'duration': log.to_json()['outputs'][0]['duration'], 'id': 'plot_3d_1', 'surfaces': [ {'id': 'surface1', 'status': 'FAILED'}, {'id': 'surface2', 'status': 'SUCCEEDED'}, ], }, { 'status': 'SUCCEEDED', 'exception': None, 'skipReason': None, 'output': log.to_json()['outputs'][1]['output'], 'duration': log.to_json()['outputs'][1]['duration'], 'id': 'plot_3d_2', 'surfaces': [ {'id': 'surface3', 'status': 'SUCCEEDED'}, ], }, ] )

38.422585

136

0.500878

5,453

54,099

4.758115

0.052081

0.053419

0.049141

0.026208

0.838048

0.796809

0.765436

0.751407

0.738996

0.726933

0

0.020406

0.372243

54,099

1,407

137

38.449893

0.743588

0.007357

0

0.731511

0

0.023312

0.142721

0.048505

0

0.038585

1

0.016881

false

0.009646

0.016077

0.001608

0.045016

0

null

0

1

0

1

0

null

0

7

ce73ba83e383c924f4adc7f4435b7b66d09e37e2

184

py

Python

pypy/translator/jvm/test/test_extreme.py

camillobruni/pygirl

ddbd442d53061d6ff4af831c1eab153bcc771b5a

[ "MIT" ]

12

2016-01-06T07:10:28.000Z

2021-05-13T23:02:02.000Z

pypy/translator/jvm/test/test_extreme.py

woodrow/pyoac

b5dc59e6a38e7912db47f26fb23ffa4764a3c0e7

[ "MIT" ]

null

pypy/translator/jvm/test/test_extreme.py

woodrow/pyoac

b5dc59e6a38e7912db47f26fb23ffa4764a3c0e7

[ "MIT" ]

2

2016-07-29T07:09:50.000Z

2016-10-16T08:50:26.000Z

from pypy.translator.jvm.test.runtest import JvmTest from pypy.translator.oosupport.test_template.extreme import BaseTestExtreme class TestExtreme(BaseTestExtreme, JvmTest): pass

30.666667

75

0.842391

22

184

7

0.681818

0.103896

0.233766

0

0.092391

184

5

76

36.8

0.922156

0

1

0

true

0.25

0.5

0

0.75

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

7

ceb8f9b08dd0a48099aae6a96157fbc3fa8c4cbf

5,257

py

Python

Game.py

doublehelix91/Multi-Agent-Alternating-Turn-Board-and-Card-Games

294800019b608fd21c652645b6c6ce557d9e52a4

[ "MIT" ]

4

2019-11-11T15:16:06.000Z

2021-03-08T10:05:43.000Z

Game.py

doublehelix91/Multi-Agent-Alternating-Turn-Board-and-Card-Games

294800019b608fd21c652645b6c6ce557d9e52a4

[ "MIT" ]

null

Game.py

doublehelix91/Multi-Agent-Alternating-Turn-Board-and-Card-Games

294800019b608fd21c652645b6c6ce557d9e52a4

[ "MIT" ]

1

2020-01-15T23:41:53.000Z

""" @author: Nihal & Adi """ from sequence import simpleSequence from Qlearn import Qlearn from minimaxQ import miniMAX import random import time def M_M(player, player2): M1 = miniMAX(player) M2 = miniMAX(player2) s = simpleSequence() s.printTitle("Minimax Q vs Minimax Q") s.print_board() s.printHand() while not s.complete(): while True: if player == s.player: state = str(s.board_string()) + '-' + s.getHand(player) #print(state) card, location = M1.play(state) if not s.make_move(card,location): print("Invalid Move!! Try Again!!") else: break else: state = s.board_string() + '-' + s.getHand(player2) #print(state) card, location = M2.play(state) if not s.make_move(card, location): print("Invalid Move!! Try Again!!") else: break s.printHand() s.switch_player() def Q_Q(player, player2): Q1 = Qlearn(player) Q2 = Qlearn(player2) s = simpleSequence() s.printTitle("Q Learning vs Q Learning") s.print_board() s.printHand() while not s.complete(): while True: if player == s.player: state = str(s.board_string()) + '-' + s.getHand(player) #print(state) card, location = Q1.play(state) if not s.make_move(card,location): print("Invalid Move!! Try Again!!") else: break else: state = s.board_string() + '-' + s.getHand(player2) #print(state) card, location = Q2.play(state) if not s.make_move(card, location): print("Invalid Move!! Try Again!!") else: break s.printHand() s.switch_player() def Q_M(player, player2): Q1 = Qlearn(player) M2 = miniMAX(player2) s = simpleSequence() time.sleep(10) s.printTitle("Minimax Q vs Q Learning") s.print_board() s.printHand() while not s.complete(): while True: if player == s.player: state = str(s.board_string()) + '-' + s.getHand(player) #print(state) card, location = Q1.play(state) if not s.make_move(card,location): print("Invalid Move!! Try Again!!") else: break else: state = s.board_string() + '-' + s.getHand(player2) #print(state) card, location = M2.play(state) if not s.make_move(card, location): print("Invalid Move!! Try Again!!") else: break s.printHand() s.switch_player() def Q_R(player): Q1 = Qlearn(player) s = simpleSequence() s.printTitle("Q Learning vs Random") s.print_board() s.printHand() while not s.complete(): while True: if player == s.player: state = str(s.board_string()) + '-' + s.getHand(player) #print(state) card, location = Q1.play(state) if not s.make_move(card,location): print("Invalid Move!! Try Again!!") else: break else: #state = s.board_string() + '-' + s.getHand(player2) #print(state) card = random.choice(s.available_moves()) #print(card.suit) while (card.value=='Jack'): card = random.choice(s.available_moves()) location=s.find_card_location(card) if not s.make_move(card, location): print("Invalid Move!! Try Again!!") else: break s.printHand() s.switch_player() def M_R(player): M1 = miniMAX(player) s = simpleSequence() s.printTitle("Minimax Q vs Random") s.print_board() s.printHand() while not s.complete(): while True: if player == s.player: state = str(s.board_string()) + '-' + s.getHand(player) #print(state) card, location = M1.play(state) if not s.make_move(card,location): print("Invalid Move!! Try Again!!") else: break else: #state = s.board_string() + '-' + s.getHand(player2) #print(state) card = random.choice(s.available_moves()) #print(card.suit) while (card.value=='Jack'): card = random.choice(s.available_moves()) location=s.find_card_location(card) if not s.make_move(card, location): print("Invalid Move!! Try Again!!") else: break s.printHand() s.switch_player() Q_M('B','G') Q_Q('B','G') Q_R('B') M_R('B') M_M('B', 'G')

31.860606

71

0.475556

560

5,257

4.378571

0.107143

0.097879

0.04894

0.053018

0.909054

0.87398

0.849918

0.792822

0

0.00925

0.403652

5,257

164

72

32.054878

0.772887

0.052311

0

0.833333

0

0.079016

0

1

0.036232

false

0

0.036232

0

0.072464

0.217391

0

null

0

1

0

1

0

null

0

7

cebfd7aca8a6225c86e48f1d8298d94aeb554fb3

11,284

py

Python

python/ql/test/query-tests/UselessCode/DuplicateCode/duplicate_test.py

vadi2/codeql

a806a4f08696d241ab295a286999251b56a6860c

[ "MIT" ]

26

2020-06-30T03:07:19.000Z

2022-03-31T03:57:23.000Z

python/ql/test/query-tests/UselessCode/DuplicateCode/duplicate_test.py

vadi2/codeql

a806a4f08696d241ab295a286999251b56a6860c

[ "MIT" ]

2

2020-06-30T06:00:59.000Z

2021-04-21T19:53:33.000Z

python/ql/test/query-tests/UselessCode/DuplicateCode/duplicate_test.py

vadi2/codeql

a806a4f08696d241ab295a286999251b56a6860c

[ "MIT" ]

10

2021-03-24T13:09:08.000Z

2022-02-10T07:39:30.000Z

#Code Duplication #Exact duplication of function #Code copied from stdlib, copyright PSF. #See http://www.python.org/download/releases/2.7/license/ def dis(x=None): """Disassemble classes, methods, functions, or code. With no argument, disassemble the last traceback. """ if x is None: distb() return if isinstance(x, types.InstanceType): x = x.__class__ if hasattr(x, 'im_func'): x = x.im_func if hasattr(x, 'func_code'): x = x.func_code if hasattr(x, '__dict__'): items = x.__dict__.items() items.sort() for name, x1 in items: if isinstance(x1, _have_code): print("Disassembly of %s:" % name) try: dis(x1) except TypeError(msg): print("Sorry:", msg) print() elif hasattr(x, 'co_code'): disassemble(x) elif isinstance(x, str): disassemble_string(x) else: raise TypeError( "don't know how to disassemble %s objects" % type(x).__name__) #And duplicate version def dis2(x=None): """Disassemble classes, methods, functions, or code. With no argument, disassemble the last traceback. """ if x is None: distb() return if isinstance(x, types.InstanceType): x = x.__class__ if hasattr(x, 'im_func'): x = x.im_func if hasattr(x, 'func_code'): x = x.func_code if hasattr(x, '__dict__'): items = x.__dict__.items() items.sort() for name, x1 in items: if isinstance(x1, _have_code): print("Disassembly of %s:" % name) try: dis(x1) except TypeError(msg): print("Sorry:", msg) print() elif hasattr(x, 'co_code'): disassemble(x) elif isinstance(x, str): disassemble_string(x) else: raise TypeError( "don't know how to disassemble %s objects" % type(x).__name__) #Exactly duplicate class class Popen3: """Class representing a child process. Normally, instances are created internally by the functions popen2() and popen3().""" sts = -1 # Child not completed yet def __init__(self, cmd, capturestderr=False, bufsize=-1): """The parameter 'cmd' is the shell command to execute in a sub-process. On UNIX, 'cmd' may be a sequence, in which case arguments will be passed directly to the program without shell intervention (as with os.spawnv()). If 'cmd' is a string it will be passed to the shell (as with os.system()). The 'capturestderr' flag, if true, specifies that the object should capture standard error output of the child process. The default is false. If the 'bufsize' parameter is specified, it specifies the size of the I/O buffers to/from the child process.""" _cleanup() self.cmd = cmd p2cread, p2cwrite = os.pipe() c2pread, c2pwrite = os.pipe() if capturestderr: errout, errin = os.pipe() self.pid = os.fork() if self.pid == 0: # Child os.dup2(p2cread, 0) os.dup2(c2pwrite, 1) if capturestderr: os.dup2(errin, 2) self._run_child(cmd) os.close(p2cread) self.tochild = os.fdopen(p2cwrite, 'w', bufsize) os.close(c2pwrite) self.fromchild = os.fdopen(c2pread, 'r', bufsize) if capturestderr: os.close(errin) self.childerr = os.fdopen(errout, 'r', bufsize) else: self.childerr = None def __del__(self): # In case the child hasn't been waited on, check if it's done. self.poll(_deadstate=sys.maxint) if self.sts < 0: if _active is not None: # Child is still running, keep us alive until we can wait on it. _active.append(self) def _run_child(self, cmd): if isinstance(cmd, basestring): cmd = ['/bin/sh', '-c', cmd] os.closerange(3, MAXFD) try: os.execvp(cmd[0], cmd) finally: os._exit(1) def poll(self, _deadstate=None): """Return the exit status of the child process if it has finished, or -1 if it hasn't finished yet.""" if self.sts < 0: try: pid, sts = os.waitpid(self.pid, os.WNOHANG) # pid will be 0 if self.pid hasn't terminated if pid == self.pid: self.sts = sts except os.error: if _deadstate is not None: self.sts = _deadstate return self.sts def wait(self): """Wait for and return the exit status of the child process.""" if self.sts < 0: pid, sts = os.waitpid(self.pid, 0) # This used to be a test, but it is believed to be # always true, so I changed it to an assertion - mvl assert pid == self.pid self.sts = sts return self.sts class Popen3Again: """Class representing a child process. Normally, instances are created internally by the functions popen2() and popen3().""" sts = -1 # Child not completed yet def __init__(self, cmd, capturestderr=False, bufsize=-1): """The parameter 'cmd' is the shell command to execute in a sub-process. On UNIX, 'cmd' may be a sequence, in which case arguments will be passed directly to the program without shell intervention (as with os.spawnv()). If 'cmd' is a string it will be passed to the shell (as with os.system()). The 'capturestderr' flag, if true, specifies that the object should capture standard error output of the child process. The default is false. If the 'bufsize' parameter is specified, it specifies the size of the I/O buffers to/from the child process.""" _cleanup() self.cmd = cmd p2cread, p2cwrite = os.pipe() c2pread, c2pwrite = os.pipe() if capturestderr: errout, errin = os.pipe() self.pid = os.fork() if self.pid == 0: # Child os.dup2(p2cread, 0) os.dup2(c2pwrite, 1) if capturestderr: os.dup2(errin, 2) self._run_child(cmd) os.close(p2cread) self.tochild = os.fdopen(p2cwrite, 'w', bufsize) os.close(c2pwrite) self.fromchild = os.fdopen(c2pread, 'r', bufsize) if capturestderr: os.close(errin) self.childerr = os.fdopen(errout, 'r', bufsize) else: self.childerr = None def __del__(self): # In case the child hasn't been waited on, check if it's done. self.poll(_deadstate=sys.maxint) if self.sts < 0: if _active is not None: # Child is still running, keep us alive until we can wait on it. _active.append(self) def _run_child(self, cmd): if isinstance(cmd, basestring): cmd = ['/bin/sh', '-c', cmd] os.closerange(3, MAXFD) try: os.execvp(cmd[0], cmd) finally: os._exit(1) def poll(self, _deadstate=None): """Return the exit status of the child process if it has finished, or -1 if it hasn't finished yet.""" if self.sts < 0: try: pid, sts = os.waitpid(self.pid, os.WNOHANG) # pid will be 0 if self.pid hasn't terminated if pid == self.pid: self.sts = sts except os.error: if _deadstate is not None: self.sts = _deadstate return self.sts def wait(self): """Wait for and return the exit status of the child process.""" if self.sts < 0: pid, sts = os.waitpid(self.pid, 0) # This used to be a test, but it is believed to be # always true, so I changed it to an assertion - mvl assert pid == self.pid self.sts = sts return self.sts #Duplicate function with identifiers changed def dis3(y=None): """frobnicate classes, methods, functions, or code. With no argument, frobnicate the last traceback. """ if y is None: distb() return if isinstance(y, types.InstanceType): y = y.__class__ if hasattr(y, 'im_func'): y = y.im_func if hasattr(y, 'func_code'): y = y.func_code if hasattr(y, '__dict__'): items = y.__dict__.items() items.sort() for name, y1 in items: if isinstance(y1, _have_code): print("Disassembly of %s:" % name) try: dis(y1) except TypeError(msg): print("Sorry:", msg) print() elif hasattr(y, 'co_code'): frobnicate(y) elif isinstance(y, str): frobnicate_string(y) else: raise TypeError( "don't know how to frobnicate %s objects" % type(y).__name__) #Mostly similar function def dis4(x=None): """Disassemble classes, methods, functions, or code. With no argument, disassemble the last traceback. """ if x is None: distb() return if isinstance(x, types.InstanceType): x = x.__class__ if hasattr(x, 'im_func'): x = x.im_func if hasattr(x, '__dict__'): items = x.__dict__.items() items.sort() for name, x1 in items: if isinstance(x1, _have_code): print("Disassembly of %s:" % name) try: dis(x1) except TypeError(msg): print("Sorry:", msg) print() elif hasattr(x, 'co_code'): disassemble(x) elif isinstance(x, str): disassemble_string(x) else: raise TypeError( "don't know how to disassemble %s objects" % type(x).__name__) #Similar function with changed identifiers def dis5(z=None): """splat classes, methods, functions, or code. With no argument, splat the last traceback. """ if z is None: distb() return if isinstance(z, types.InstanceType): z = z.__class__ if hasattr(z, 'im_func'): z = z.im_func if hasattr(y, 'func_code'): y = y.func_code if hasattr(z, '__dict__'): items = z.__dict__.items() items.sort() for name, z1 in items: if isinstance(z1, _have_code): print("Disassembly of %s:" % name) try: dis(z1) except TypeError(msg): print("Sorry:", msg) print() elif hasattr(z, 'co_code'): splat(z) elif isinstance(z, str): splat_string(z) else: raise TypeError( "don't know how to splat %s objects" % type(z).__name__)

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null

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0cfd7b22c59db19007b93fef7ce4541472accb9d

81

py

Python

tests/test_version.py

amirasaad/fastapi-passwordless

fa907800a9b649ac1f601807fce180f322203acd

[ "MIT" ]

null

tests/test_version.py

amirasaad/fastapi-passwordless

fa907800a9b649ac1f601807fce180f322203acd

[ "MIT" ]

6

2021-01-20T14:54:12.000Z

2021-12-19T22:50:29.000Z

tests/test_version.py

amirasaad/fastapi-passwordless

fa907800a9b649ac1f601807fce180f322203acd

[ "MIT" ]

null

import fastapi_passwordless assert hasattr(fastapi_passwordless, "__version__")

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null

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7

0b3abab2e1331de3de7e2d51ade45042e2b6d794

2,956

py

Python

vendor/pip-1.2.1/tests/test_vcs_git.py

hmoody87/heroku-buildpack-python-ffmpeg-lame

ba7f092f0f341dfb274da311ebc8a1ff43ac2e0a

[ "MIT" ]

1

2015-11-05T20:27:06.000Z

vendor/pip-1.2.1/tests/test_vcs_git.py

hmoody87/heroku-buildpack-python-ffmpeg-lame

ba7f092f0f341dfb274da311ebc8a1ff43ac2e0a

[ "MIT" ]

null

vendor/pip-1.2.1/tests/test_vcs_git.py

hmoody87/heroku-buildpack-python-ffmpeg-lame

ba7f092f0f341dfb274da311ebc8a1ff43ac2e0a

[ "MIT" ]

3

2015-03-26T17:19:04.000Z

2020-11-11T13:50:47.000Z

from mock import patch from pip.vcs.git import Git from tests.test_pip import (reset_env, run_pip, _create_test_package) def test_get_tag_revs_should_return_tag_name_and_commit_pair(): env = reset_env() version_pkg_path = _create_test_package(env) env.run('git', 'tag', '0.1', cwd=version_pkg_path) env.run('git', 'tag', '0.2', cwd=version_pkg_path) commit = env.run('git', 'rev-parse', 'HEAD', cwd=version_pkg_path).stdout.strip() git = Git() result = git.get_tag_revs(version_pkg_path) assert result == {'0.1': commit, '0.2': commit}, result def test_get_branch_revs_should_return_branch_name_and_commit_pair(): env = reset_env() version_pkg_path = _create_test_package(env) env.run('git', 'branch', 'branch0.1', cwd=version_pkg_path) commit = env.run('git', 'rev-parse', 'HEAD', cwd=version_pkg_path).stdout.strip() git = Git() result = git.get_branch_revs(version_pkg_path) assert result == {'master': commit, 'branch0.1': commit} def test_get_branch_revs_should_ignore_no_branch(): env = reset_env() version_pkg_path = _create_test_package(env) env.run('git', 'branch', 'branch0.1', cwd=version_pkg_path) commit = env.run('git', 'rev-parse', 'HEAD', cwd=version_pkg_path).stdout.strip() # current branch here is "* (nobranch)" env.run('git', 'checkout', commit, cwd=version_pkg_path, expect_stderr=True) git = Git() result = git.get_branch_revs(version_pkg_path) assert result == {'master': commit, 'branch0.1': commit} @patch('pip.vcs.git.Git.get_tag_revs') @patch('pip.vcs.git.Git.get_branch_revs') def test_check_rev_options_should_handle_branch_name(branches_revs_mock, tags_revs_mock): branches_revs_mock.return_value = {'master': '123456'} tags_revs_mock.return_value = {'0.1': '123456'} git = Git() result = git.check_rev_options('master', '.', []) assert result == ['123456'] @patch('pip.vcs.git.Git.get_tag_revs') @patch('pip.vcs.git.Git.get_branch_revs') def test_check_rev_options_should_handle_tag_name(branches_revs_mock, tags_revs_mock): branches_revs_mock.return_value = {'master': '123456'} tags_revs_mock.return_value = {'0.1': '123456'} git = Git() result = git.check_rev_options('0.1', '.', []) assert result == ['123456'] @patch('pip.vcs.git.Git.get_tag_revs') @patch('pip.vcs.git.Git.get_branch_revs') def test_check_rev_options_should_handle_ambiguous_commit(branches_revs_mock, tags_revs_mock): branches_revs_mock.return_value = {'master': '123456'} tags_revs_mock.return_value = {'0.1': '123456'} git = Git() result = git.check_rev_options('0.1', '.', []) assert result == ['123456'], result

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2,956

77

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0

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0

null

0

1

0

1

0

null

0

7

0b5441134f11f18c99bbaaac755754154609d810

3,265

py

Python

tests/test_scorekeepers.py

questionlp/api.wwdt.me_v2

9e3705bba2668221740f5d28e94eec90998c3d00

[ "Apache-2.0" ]

null

tests/test_scorekeepers.py

questionlp/api.wwdt.me_v2

9e3705bba2668221740f5d28e94eec90998c3d00

[ "Apache-2.0" ]

null

tests/test_scorekeepers.py

questionlp/api.wwdt.me_v2

9e3705bba2668221740f5d28e94eec90998c3d00

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # vim: set noai syntax=python ts=4 sw=4: # # Copyright (c) 2018-2022 Linh Pham # api.wwdt.me is released under the terms of the Apache License 2.0 """Testing /v2.0/scorekeepers routes """ from fastapi.testclient import TestClient import pytest from app.main import app from app.config import API_VERSION client = TestClient(app) def test_scorekeepers(): """Test /v2.0/scorekeepers route""" response = client.get(f"/v{API_VERSION}/scorekeepers") scorekeepers = response.json() assert response.status_code == 200 assert "scorekeepers" in scorekeepers assert "id" in scorekeepers["scorekeepers"][0] assert "name" in scorekeepers["scorekeepers"][0] assert "slug" in scorekeepers["scorekeepers"][0] @pytest.mark.parametrize("scorekeeper_id", [11]) def test_scorekeepers_id(scorekeeper_id: int): """Test /v2.0/scorekeepers/id/{scorekeeper_id} route""" response = client.get(f"/v{API_VERSION}/scorekeepers/id/{scorekeeper_id}") scorekeeper = response.json() assert response.status_code == 200 assert "id" in scorekeeper assert scorekeeper["id"] == scorekeeper_id assert "name" in scorekeeper assert "slug" in scorekeeper @pytest.mark.parametrize("scorekeeper_slug", ["bill-kurtis"]) def test_scorekeepers_slug(scorekeeper_slug: str): """Test /v2.0/scorekeepers/slug/{scorekeeper_slug} route""" response = client.get(f"/v{API_VERSION}/scorekeepers/slug/{scorekeeper_slug}") scorekeeper = response.json() assert response.status_code == 200 assert "id" in scorekeeper assert "name" in scorekeeper assert "slug" in scorekeeper assert scorekeeper["slug"] == scorekeeper_slug def test_scorekeepers_details(): """Test /v2.0/scorekeepers/details route""" response = client.get(f"/v{API_VERSION}/scorekeepers/details") scorekeepers = response.json() assert response.status_code == 200 assert "scorekeepers" in scorekeepers assert "id" in scorekeepers["scorekeepers"][0] assert "name" in scorekeepers["scorekeepers"][0] assert "slug" in scorekeepers["scorekeepers"][0] assert "appearances" in scorekeepers["scorekeepers"][0] @pytest.mark.parametrize("scorekeeper_id", [11]) def test_scorekeepers_details_id(scorekeeper_id: int): """Test /v2.0/scorekeepers/details/id/{scorekeeper_id} route""" response = client.get(f"/v{API_VERSION}/scorekeepers/details/id/{scorekeeper_id}") scorekeeper = response.json() assert response.status_code == 200 assert "id" in scorekeeper assert scorekeeper["id"] == scorekeeper_id assert "name" in scorekeeper assert "slug" in scorekeeper assert "appearances" in scorekeeper @pytest.mark.parametrize("scorekeeper_slug", ["bill-kurtis"]) def test_scorekeepers_details_slug(scorekeeper_slug: str): """Test /v2.0/scorekeepers/details/slug/{scorekeeper_slug} route""" response = client.get( f"/v{API_VERSION}/scorekeepers/details/slug/{scorekeeper_slug}" ) scorekeeper = response.json() assert response.status_code == 200 assert "id" in scorekeeper assert "name" in scorekeeper assert "slug" in scorekeeper assert scorekeeper["slug"] == scorekeeper_slug assert "appearances" in scorekeeper

32.009804

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null

0

1

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null

0

1

0

7

0b8454ef807c7deb6d40fa9879b045c97d7c52ad

23,541

py

Python

Incident-Response/Tools/dfirtrack/dfirtrack_main/tests/system_importer/test_system_importer_file_csv_tag_removal.py

sn0b4ll/Incident-Playbook

cf519f58fcd4255674662b3620ea97c1091c1efb

[ "MIT" ]

1

2021-07-24T17:22:50.000Z

Incident-Response/Tools/dfirtrack/dfirtrack_main/tests/system_importer/test_system_importer_file_csv_tag_removal.py

sn0b4ll/Incident-Playbook

cf519f58fcd4255674662b3620ea97c1091c1efb

[ "MIT" ]

2

2022-02-28T03:40:31.000Z

2022-02-28T03:40:52.000Z

Incident-Response/Tools/dfirtrack/dfirtrack_main/tests/system_importer/test_system_importer_file_csv_tag_removal.py

sn0b4ll/Incident-Playbook

cf519f58fcd4255674662b3620ea97c1091c1efb

[ "MIT" ]

2

2022-02-25T08:34:51.000Z

2022-03-16T17:29:44.000Z

from datetime import datetime from django.contrib.auth.models import User from django.contrib.messages import get_messages from django.test import TestCase from django.utils import timezone from dfirtrack.settings import BASE_DIR from dfirtrack_config.models import SystemImporterFileCsvConfigModel from dfirtrack_main.importer.file.csv import system_cron from dfirtrack_main.models import Analysisstatus, System, Systemstatus, Tag, Tagcolor from dfirtrack_main.tests.system_importer.config_functions import set_config_tag_remove_all from dfirtrack_main.tests.system_importer.config_functions import set_config_tag_remove_none from dfirtrack_main.tests.system_importer.config_functions import set_config_tag_remove_prefix from dfirtrack_main.tests.system_importer.config_functions import set_csv_import_filename from dfirtrack_main.tests.system_importer.config_functions import set_csv_import_path from mock import patch import os import urllib.parse def compare_messages_csv(self, messages): """ compare messages """ # compare - messages self.assertEqual(messages[0].message, '3 systems were updated.') self.assertEqual(messages[0].level_tag, 'success') # return to test function return self def compare_tag_remove_all(self, file_number): """ compare tags """ # compare - old tags (all removed) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name='tag_97_1').exists()) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name='tag_97_1').exists()) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name='tag_97_1').exists()) # compare - existence of objects self.assertTrue(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertTrue(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertTrue(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) # compare - new tags self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) # return to test function return self def compare_tag_remove_prefix(self, file_number): """ compare tags """ # compare - old tags (with prefix removed) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertFalse(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name='tag_97_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name='tag_97_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name='tag_97_1').exists()) # compare - existence of objects self.assertTrue(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertTrue(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertTrue(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) # compare - new tags self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) # return to test function return self def compare_tag_remove_none(self, file_number): """ compare tags """ # compare - old tags (no tag removed) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name='AUTO_tag_96_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_001').tag.filter(tag_name='tag_97_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_002').tag.filter(tag_name='tag_97_1').exists()) self.assertTrue(System.objects.get(system_name=f'system_csv_{file_number}_003').tag.filter(tag_name='tag_97_1').exists()) # compare - new tags (no tag created) self.assertFalse(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_1').exists()) self.assertFalse(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_2').exists()) self.assertFalse(Tag.objects.filter(tag_name=f'AUTO_tag_{file_number}_3').exists()) # return to test function return self class SystemImporterFileCsvTagRemovalViewTestCase(TestCase): """ system importer file CSV view tests """ @classmethod def setUpTestData(cls): """ one-time setup """ # create user test_user = User.objects.create_user(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') User.objects.create_user(username='message_user', password='8vwuoDthBxFkMQUBG2DM') # create objects analysisstatus_1 = Analysisstatus.objects.create(analysisstatus_name='analysisstatus_1') analysisstatus_2 = Analysisstatus.objects.create(analysisstatus_name='analysisstatus_2') systemstatus_1 = Systemstatus.objects.create(systemstatus_name='systemstatus_1') systemstatus_2 = Systemstatus.objects.create(systemstatus_name='systemstatus_2') # create systems system_csv_56_001 = System.objects.create( system_name = 'system_csv_56_001', systemstatus = systemstatus_1, analysisstatus = analysisstatus_1, system_modify_time = timezone.now(), system_created_by_user_id = test_user, system_modified_by_user_id = test_user, ) system_csv_56_002 = System.objects.create( system_name = 'system_csv_56_002', systemstatus = systemstatus_1, analysisstatus = analysisstatus_1, system_modify_time = timezone.now(), system_created_by_user_id = test_user, system_modified_by_user_id = test_user, ) system_csv_56_003 = System.objects.create( system_name = 'system_csv_56_003', systemstatus = systemstatus_1, analysisstatus = analysisstatus_1, system_modify_time = timezone.now(), system_created_by_user_id = test_user, system_modified_by_user_id = test_user, ) tagcolor_1 = Tagcolor.objects.create(tagcolor_name='tagcolor_1') AUTO_tag_96_1 = Tag.objects.create( tag_name='AUTO_tag_96_1', tagcolor=tagcolor_1, ) tag_97_1 = Tag.objects.create( tag_name='tag_97_1', tagcolor=tagcolor_1, ) system_csv_56_001.tag.add(AUTO_tag_96_1) system_csv_56_002.tag.add(AUTO_tag_96_1) system_csv_56_003.tag.add(AUTO_tag_96_1) system_csv_56_001.tag.add(tag_97_1) system_csv_56_002.tag.add(tag_97_1) system_csv_56_003.tag.add(tag_97_1) # set config set_csv_import_path(os.path.join(BASE_DIR, 'dfirtrack_main/tests/system_importer/system_importer_file_csv_files/')) # set config set_csv_import_filename('system_importer_file_csv_testfile_56_tag_delimiter_space.csv') # set config system_importer_file_csv_config_model = SystemImporterFileCsvConfigModel.objects.get(system_importer_file_csv_config_name='SystemImporterFileCsvConfig') system_importer_file_csv_config_model.csv_column_system = 1 system_importer_file_csv_config_model.csv_skip_existing_system = False system_importer_file_csv_config_model.csv_headline = False system_importer_file_csv_config_model.csv_import_username = test_user system_importer_file_csv_config_model.csv_default_systemstatus = systemstatus_1 system_importer_file_csv_config_model.csv_default_analysisstatus = analysisstatus_1 system_importer_file_csv_config_model.csv_default_tagfree_systemstatus = systemstatus_2 system_importer_file_csv_config_model.csv_default_tagfree_analysisstatus = analysisstatus_2 system_importer_file_csv_config_model.csv_tag_lock_systemstatus = 'LOCK_SYSTEMSTATUS' system_importer_file_csv_config_model.csv_tag_lock_analysisstatus = 'LOCK_ANALYSISSTATUS' system_importer_file_csv_config_model.csv_field_delimiter = 'field_comma' system_importer_file_csv_config_model.csv_text_quote = 'text_double_quotation_marks' system_importer_file_csv_config_model.csv_ip_delimiter = 'ip_semicolon' system_importer_file_csv_config_model.csv_tag_delimiter = 'tag_space' system_importer_file_csv_config_model.csv_tag_prefix = 'AUTO' system_importer_file_csv_config_model.csv_tag_prefix_delimiter = 'tag_prefix_underscore' system_importer_file_csv_config_model.csv_choice_tag = True system_importer_file_csv_config_model.csv_column_tag = 2 system_importer_file_csv_config_model.save() """ remove all tags """ def test_system_importer_file_csv_cron_tag_remove_all(self): """ test importer view """ # change config set_config_tag_remove_all() # mock timezone.now() t_1 = datetime(2021, 3, 26, 18, 35, tzinfo=timezone.utc) with patch.object(timezone, 'now', return_value=t_1): # execute cron job / scheduled task system_cron() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # get response response = self.client.get('/system/') # get messages messages = list(get_messages(response.wsgi_request)) # compare - user 1 self.assertEqual(str(response.context['user']), 'testuser_system_importer_file_csv_tag_removal') self.assertEqual(messages[0].message, 'System CSV importer: created: 0 | updated: 3 | skipped: 0 | multiple: 0 [2021-03-26 18:35:00 - 2021-03-26 18:35:00]') self.assertEqual(messages[0].level_tag, 'success') # switch user context self.client.logout() self.client.login(username='message_user', password='8vwuoDthBxFkMQUBG2DM') # get response response = self.client.get('/system/') # get messages messages = list(get_messages(response.wsgi_request)) # compare - user 2 self.assertEqual(str(response.context['user']), 'message_user') self.assertEqual(messages[0].message, 'System CSV importer: created: 0 | updated: 3 | skipped: 0 | multiple: 0 [2021-03-26 18:35:00 - 2021-03-26 18:35:00]') self.assertEqual(messages[0].level_tag, 'success') # compare - tags compare_tag_remove_all(self, '56') def test_system_importer_file_csv_instant_tag_remove_all(self): """ test importer view """ # change config set_config_tag_remove_all() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # create url destination = urllib.parse.quote('/system/', safe='/') # get response response = self.client.get('/system/importer/file/csv/instant/', follow=True) # get messages messages = list(get_messages(response.wsgi_request)) # compare - meta self.assertRedirects(response, destination, status_code=302, target_status_code=200) # compare - messages compare_messages_csv(self, messages) # compare - tags compare_tag_remove_all(self, '56') def test_system_importer_file_csv_upload_post_tag_remove_all(self): """ test importer view """ # change config set_config_tag_remove_all() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # open upload file systemcsv = open(os.path.join(BASE_DIR, 'dfirtrack_main/tests/system_importer/system_importer_file_csv_files/system_importer_file_csv_testfile_56_tag_delimiter_space.csv'), 'r') # create post data data_dict = { 'systemcsv': systemcsv, } # create url destination = urllib.parse.quote('/system/', safe='/') # get response response = self.client.post('/system/importer/file/csv/upload/', data_dict) # get messages messages = list(get_messages(response.wsgi_request)) # close file systemcsv.close() # compare - meta self.assertRedirects(response, destination, status_code=302, target_status_code=200) # compare - messages compare_messages_csv(self, messages) # compare - tags compare_tag_remove_all(self, '56') """ remove prefix tags """ def test_system_importer_file_csv_cron_tag_remove_prefix(self): """ test importer view """ # change config set_config_tag_remove_prefix() # mock timezone.now() t_2 = datetime(2021, 3, 26, 18, 40, tzinfo=timezone.utc) with patch.object(timezone, 'now', return_value=t_2): # execute cron job / scheduled task system_cron() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # get response response = self.client.get('/system/') # get messages messages = list(get_messages(response.wsgi_request)) # compare - user 1 self.assertEqual(str(response.context['user']), 'testuser_system_importer_file_csv_tag_removal') self.assertEqual(messages[0].message, 'System CSV importer: created: 0 | updated: 3 | skipped: 0 | multiple: 0 [2021-03-26 18:40:00 - 2021-03-26 18:40:00]') self.assertEqual(messages[0].level_tag, 'success') # switch user context self.client.logout() self.client.login(username='message_user', password='8vwuoDthBxFkMQUBG2DM') # get response response = self.client.get('/system/') # get messages messages = list(get_messages(response.wsgi_request)) # compare - user 2 self.assertEqual(str(response.context['user']), 'message_user') self.assertEqual(messages[0].message, 'System CSV importer: created: 0 | updated: 3 | skipped: 0 | multiple: 0 [2021-03-26 18:40:00 - 2021-03-26 18:40:00]') self.assertEqual(messages[0].level_tag, 'success') # compare - tags compare_tag_remove_prefix(self, '56') def test_system_importer_file_csv_instant_tag_remove_prefix(self): """ test importer view """ # change config set_config_tag_remove_prefix() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # create url destination = urllib.parse.quote('/system/', safe='/') # get response response = self.client.get('/system/importer/file/csv/instant/', follow=True) # get messages messages = list(get_messages(response.wsgi_request)) # compare - meta self.assertRedirects(response, destination, status_code=302, target_status_code=200) # compare - messages compare_messages_csv(self, messages) # compare - tags compare_tag_remove_prefix(self, '56') def test_system_importer_file_csv_upload_post_tag_remove_prefix(self): """ test importer view """ # change config set_config_tag_remove_prefix() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # open upload file systemcsv = open(os.path.join(BASE_DIR, 'dfirtrack_main/tests/system_importer/system_importer_file_csv_files/system_importer_file_csv_testfile_56_tag_delimiter_space.csv'), 'r') # create post data data_dict = { 'systemcsv': systemcsv, } # create url destination = urllib.parse.quote('/system/', safe='/') # get response response = self.client.post('/system/importer/file/csv/upload/', data_dict) # get messages messages = list(get_messages(response.wsgi_request)) # close file systemcsv.close() # compare - meta self.assertRedirects(response, destination, status_code=302, target_status_code=200) # compare - messages compare_messages_csv(self, messages) # compare - tags compare_tag_remove_prefix(self, '56') """ remove no tags """ def test_system_importer_file_csv_cron_tag_remove_none(self): """ test importer view """ # change config set_config_tag_remove_none() # mock timezone.now() t_3 = datetime(2021, 3, 26, 18, 45, tzinfo=timezone.utc) with patch.object(timezone, 'now', return_value=t_3): # execute cron job / scheduled task system_cron() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # get response response = self.client.get('/system/') # get messages messages = list(get_messages(response.wsgi_request)) # compare - user 1 self.assertEqual(str(response.context['user']), 'testuser_system_importer_file_csv_tag_removal') self.assertEqual(messages[0].message, 'System CSV importer: created: 0 | updated: 3 | skipped: 0 | multiple: 0 [2021-03-26 18:45:00 - 2021-03-26 18:45:00]') self.assertEqual(messages[0].level_tag, 'success') # switch user context self.client.logout() self.client.login(username='message_user', password='8vwuoDthBxFkMQUBG2DM') # get response response = self.client.get('/system/') # get messages messages = list(get_messages(response.wsgi_request)) # compare - user 2 self.assertEqual(str(response.context['user']), 'message_user') self.assertEqual(messages[0].message, 'System CSV importer: created: 0 | updated: 3 | skipped: 0 | multiple: 0 [2021-03-26 18:45:00 - 2021-03-26 18:45:00]') self.assertEqual(messages[0].level_tag, 'success') # compare - tags compare_tag_remove_none(self, '56') def test_system_importer_file_csv_instant_tag_remove_none(self): """ test importer view """ # change config set_config_tag_remove_none() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # create url destination = urllib.parse.quote('/system/', safe='/') # get response response = self.client.get('/system/importer/file/csv/instant/', follow=True) # get messages messages = list(get_messages(response.wsgi_request)) # compare - meta self.assertRedirects(response, destination, status_code=302, target_status_code=200) # compare - messages compare_messages_csv(self, messages) # compare - tags compare_tag_remove_none(self, '56') def test_system_importer_file_csv_upload_post_tag_remove_none(self): """ test importer view """ # change config set_config_tag_remove_none() # login testuser self.client.login(username='testuser_system_importer_file_csv_tag_removal', password='XAavYL75MrC5eVVSuzoL') # open upload file systemcsv = open(os.path.join(BASE_DIR, 'dfirtrack_main/tests/system_importer/system_importer_file_csv_files/system_importer_file_csv_testfile_56_tag_delimiter_space.csv'), 'r') # create post data data_dict = { 'systemcsv': systemcsv, } # create url destination = urllib.parse.quote('/system/', safe='/') # get response response = self.client.post('/system/importer/file/csv/upload/', data_dict) # get messages messages = list(get_messages(response.wsgi_request)) # close file systemcsv.close() # compare - meta self.assertRedirects(response, destination, status_code=302, target_status_code=200) # compare - messages compare_messages_csv(self, messages) # compare - tags compare_tag_remove_none(self, '56')

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0b93d8a4f2d3d99f468fed01691f702cc699ee58

17,661

py

Python

tests/client_connectivity/test_bridge_mode.py

brennerm/wlan-testing

ea99d5ab74177198324f4d7eddcdcff2844bbbf3

[ "BSD-3-Clause" ]

null

tests/client_connectivity/test_bridge_mode.py

brennerm/wlan-testing

ea99d5ab74177198324f4d7eddcdcff2844bbbf3

[ "BSD-3-Clause" ]

null

tests/client_connectivity/test_bridge_mode.py

brennerm/wlan-testing

ea99d5ab74177198324f4d7eddcdcff2844bbbf3

[ "BSD-3-Clause" ]

null

import pytest import sys for folder in 'py-json', 'py-scripts': if folder not in sys.path: sys.path.append(f'../lanforge/lanforge-scripts/{folder}') sys.path.append(f"../lanforge/lanforge-scripts/py-scripts/tip-cicd-sanity") sys.path.append(f'../libs') sys.path.append(f'../libs/lanforge/') from LANforge.LFUtils import * from configuration_data import TEST_CASES if 'py-json' not in sys.path: sys.path.append('../py-scripts') import sta_connect2 from sta_connect2 import StaConnect2 import eap_connect from eap_connect import EAPConnect import time @pytest.mark.run(order=13) @pytest.mark.bridge class TestBridgeModeClientConnectivity(object): @pytest.mark.wpa @pytest.mark.twog def test_client_wpa_2g(self, request, get_lanforge_data, setup_profile_data, instantiate_testrail, instantiate_project): profile_data = setup_profile_data["BRIDGE"]["WPA"]["2G"] station_names = [] for i in range(0, int(request.config.getini("num_stations"))): station_names.append(get_lanforge_data["lanforge_2dot4g_prefix"] + "0" + str(i)) print(profile_data, get_lanforge_data) staConnect = StaConnect2(get_lanforge_data["lanforge_ip"], int(get_lanforge_data["lanforge-port-number"]), debug_=False) staConnect.sta_mode = 0 staConnect.upstream_resource = 1 staConnect.upstream_port = get_lanforge_data["lanforge_bridge_port"] staConnect.radio = get_lanforge_data["lanforge_2dot4g"] staConnect.resource = 1 staConnect.dut_ssid = profile_data["ssid_name"] staConnect.dut_passwd = profile_data["security_key"] staConnect.dut_security = "wpa" staConnect.station_names = station_names staConnect.sta_prefix = get_lanforge_data["lanforge_2dot4g_prefix"] staConnect.runtime_secs = 10 staConnect.bringup_time_sec = 60 staConnect.cleanup_on_exit = True # staConnect.cleanup() staConnect.setup() staConnect.start() print("napping %f sec" % staConnect.runtime_secs) time.sleep(staConnect.runtime_secs) staConnect.stop() staConnect.cleanup() run_results = staConnect.get_result_list() for result in run_results: print("test result: " + result) # result = 'pass' print("Single Client Connectivity :", staConnect.passes) if staConnect.passes(): instantiate_testrail.update_testrail(case_id=TEST_CASES["2g_wpa_bridge"], run_id=instantiate_project, status_id=1, msg='2G WPA Client Connectivity Passed successfully - bridge mode') else: instantiate_testrail.update_testrail(case_id=TEST_CASES["2g_wpa_bridge"], run_id=instantiate_project, status_id=5, msg='2G WPA Client Connectivity Failed - bridge mode') assert staConnect.passes() # C2420 @pytest.mark.wpa @pytest.mark.fiveg def test_client_wpa_5g(self, request, get_lanforge_data, setup_profile_data, instantiate_project, instantiate_testrail): profile_data = setup_profile_data["BRIDGE"]["WPA"]["5G"] station_names = [] for i in range(0, int(request.config.getini("num_stations"))): station_names.append(get_lanforge_data["lanforge_5g_prefix"] + "0" + str(i)) staConnect = StaConnect2(get_lanforge_data["lanforge_ip"], int(get_lanforge_data["lanforge-port-number"]), debug_=False) staConnect.sta_mode = 0 staConnect.upstream_resource = 1 staConnect.upstream_port = get_lanforge_data["lanforge_bridge_port"] staConnect.radio = get_lanforge_data["lanforge_5g"] staConnect.resource = 1 staConnect.dut_ssid = profile_data["ssid_name"] staConnect.dut_passwd = profile_data["security_key"] staConnect.dut_security = "wpa" staConnect.station_names = station_names staConnect.sta_prefix = get_lanforge_data["lanforge_5g_prefix"] staConnect.runtime_secs = 10 staConnect.bringup_time_sec = 60 staConnect.cleanup_on_exit = True # staConnect.cleanup() staConnect.setup() staConnect.start() print("napping %f sec" % staConnect.runtime_secs) time.sleep(staConnect.runtime_secs) staConnect.stop() staConnect.cleanup() run_results = staConnect.get_result_list() for result in run_results: print("test result: " + result) # result = 'pass' print("Single Client Connectivity :", staConnect.passes) if staConnect.passes(): instantiate_testrail.update_testrail(case_id=TEST_CASES["5g_wpa_bridge"], run_id=instantiate_project, status_id=1, msg='5G WPA Client Connectivity Passed successfully - bridge mode') else: instantiate_testrail.update_testrail(case_id=TEST_CASES["5g_wpa_bridge"], run_id=instantiate_project, status_id=5, msg='5G WPA Client Connectivity Failed - bridge mode') assert staConnect.passes() # C2419 @pytest.mark.wpa2_personal @pytest.mark.twog def test_client_wpa2_personal_2g(self, request, get_lanforge_data, setup_profile_data, instantiate_project, instantiate_testrail): profile_data = setup_profile_data["BRIDGE"]["WPA2_P"]["2G"] station_names = [] for i in range(0, int(request.config.getini("num_stations"))): station_names.append(get_lanforge_data["lanforge_2dot4g_prefix"] + "0" + str(i)) staConnect = StaConnect2(get_lanforge_data["lanforge_ip"], int(get_lanforge_data["lanforge-port-number"]), debug_=False) staConnect.sta_mode = 0 staConnect.upstream_resource = 1 staConnect.upstream_port = get_lanforge_data["lanforge_bridge_port"] staConnect.radio = get_lanforge_data["lanforge_2dot4g"] staConnect.resource = 1 staConnect.dut_ssid = profile_data["ssid_name"] staConnect.dut_passwd = profile_data["security_key"] staConnect.dut_security = "wpa2" staConnect.station_names = station_names staConnect.sta_prefix = get_lanforge_data["lanforge_2dot4g_prefix"] staConnect.runtime_secs = 10 staConnect.bringup_time_sec = 60 staConnect.cleanup_on_exit = True # staConnect.cleanup() staConnect.setup() staConnect.start() print("napping %f sec" % staConnect.runtime_secs) time.sleep(staConnect.runtime_secs) staConnect.stop() staConnect.cleanup() run_results = staConnect.get_result_list() for result in run_results: print("test result: " + result) # result = 'pass' print("Single Client Connectivity :", staConnect.passes) if staConnect.passes(): instantiate_testrail.update_testrail(case_id=TEST_CASES["2g_wpa2_bridge"], run_id=instantiate_project, status_id=1, msg='2G WPA2 Client Connectivity Passed successfully - bridge mode') else: instantiate_testrail.update_testrail(case_id=TEST_CASES["2g_wpa2_bridge"], run_id=instantiate_project, status_id=5, msg='2G WPA2 Client Connectivity Failed - bridge mode') assert staConnect.passes() # C2237 @pytest.mark.wpa2_personal @pytest.mark.fiveg def test_client_wpa2_personal_5g(self, request, get_lanforge_data, setup_profile_data, instantiate_project, instantiate_testrail): profile_data = setup_profile_data["BRIDGE"]["WPA2_P"]["5G"] station_names = [] for i in range(0, int(request.config.getini("num_stations"))): station_names.append(get_lanforge_data["lanforge_5g_prefix"] + "0" + str(i)) staConnect = StaConnect2(get_lanforge_data["lanforge_ip"], int(get_lanforge_data["lanforge-port-number"]), debug_=False) staConnect.sta_mode = 0 staConnect.upstream_resource = 1 staConnect.upstream_port = get_lanforge_data["lanforge_bridge_port"] staConnect.radio = get_lanforge_data["lanforge_5g"] staConnect.resource = 1 staConnect.dut_ssid = profile_data["ssid_name"] staConnect.dut_passwd = profile_data["security_key"] staConnect.dut_security = "wpa2" staConnect.station_names = station_names staConnect.sta_prefix = get_lanforge_data["lanforge_5g_prefix"] staConnect.runtime_secs = 10 staConnect.bringup_time_sec = 60 staConnect.cleanup_on_exit = True # staConnect.cleanup() staConnect.setup() staConnect.start() print("napping %f sec" % staConnect.runtime_secs) time.sleep(staConnect.runtime_secs) staConnect.stop() staConnect.cleanup() run_results = staConnect.get_result_list() for result in run_results: print("test result: " + result) # result = 'pass' print("Single Client Connectivity :", staConnect.passes) if staConnect.passes(): instantiate_testrail.update_testrail(case_id=TEST_CASES["5g_wpa2_bridge"], run_id=instantiate_project, status_id=1, msg='5G WPA2 Client Connectivity Passed successfully - bridge mode') else: instantiate_testrail.update_testrail(case_id=TEST_CASES["5g_wpa2_bridge"], run_id=instantiate_project, status_id=5, msg='5G WPA2 Client Connectivity Failed - bridge mode') assert staConnect.passes() # C2236 @pytest.mark.wpa2_enterprise @pytest.mark.twog def test_client_wpa2_enterprise_2g(self, request, get_lanforge_data, setup_profile_data, instantiate_project, instantiate_testrail): profile_data = setup_profile_data["BRIDGE"]["WPA2_E"]["2G"] station_names = [] for i in range(0, int(request.config.getini("num_stations"))): station_names.append(get_lanforge_data["lanforge_2dot4g_prefix"] + "0" + str(i)) eap_connect = EAPConnect(get_lanforge_data["lanforge_ip"], get_lanforge_data["lanforge-port-number"]) eap_connect.upstream_resource = 1 eap_connect.upstream_port = get_lanforge_data["lanforge_bridge_port"] eap_connect.security = "wpa2" eap_connect.sta_list = station_names eap_connect.station_names = station_names eap_connect.sta_prefix = get_lanforge_data["lanforge_2dot4g_prefix"] eap_connect.ssid = profile_data["ssid_name"] eap_connect.radio = get_lanforge_data["lanforge_2dot4g"] eap_connect.eap = "TTLS" eap_connect.identity = "nolaradius" eap_connect.ttls_passwd = "nolastart" eap_connect.runtime_secs = 10 eap_connect.setup() eap_connect.start() print("napping %f sec" % eap_connect.runtime_secs) time.sleep(eap_connect.runtime_secs) eap_connect.stop() try: eap_connect.cleanup() eap_connect.cleanup() except: pass run_results = eap_connect.get_result_list() for result in run_results: print("test result: " + result) # result = 'pass' print("Single Client Connectivity :", eap_connect.passes) if eap_connect.passes(): instantiate_testrail.update_testrail(case_id=TEST_CASES["2g_eap_bridge"], run_id=instantiate_project, status_id=1, msg='5G WPA2 ENTERPRISE Client Connectivity Passed successfully - ' 'bridge mode') else: instantiate_testrail.update_testrail(case_id=TEST_CASES["2g_eap_bridge"], run_id=instantiate_project, status_id=5, msg='5G WPA2 ENTERPRISE Client Connectivity Failed - bridge mode') assert eap_connect.passes() # C5214 @pytest.mark.wpa2_enterprise @pytest.mark.fiveg def test_client_wpa2_enterprise_5g(self, request, get_lanforge_data, setup_profile_data, instantiate_project, instantiate_testrail): profile_data = setup_profile_data["BRIDGE"]["WPA2_E"]["5G"] station_names = [] for i in range(0, int(request.config.getini("num_stations"))): station_names.append(get_lanforge_data["lanforge_5g_prefix"] + "0" + str(i)) eap_connect = EAPConnect(get_lanforge_data["lanforge_ip"], get_lanforge_data["lanforge-port-number"]) eap_connect.upstream_resource = 1 eap_connect.upstream_port = get_lanforge_data["lanforge_bridge_port"] eap_connect.security = "wpa2" eap_connect.sta_list = station_names eap_connect.station_names = station_names eap_connect.sta_prefix = get_lanforge_data["lanforge_5g_prefix"] eap_connect.ssid = profile_data["ssid_name"] eap_connect.radio = get_lanforge_data["lanforge_5g"] eap_connect.eap = "TTLS" eap_connect.identity = "nolaradius" eap_connect.ttls_passwd = "nolastart" eap_connect.runtime_secs = 10 eap_connect.setup() eap_connect.start() print("napping %f sec" % eap_connect.runtime_secs) time.sleep(eap_connect.runtime_secs) eap_connect.stop() try: eap_connect.cleanup() eap_connect.cleanup() except: pass run_results = eap_connect.get_result_list() for result in run_results: print("test result: " + result) # result = 'pass' print("Single Client Connectivity :", eap_connect.passes) if eap_connect.passes(): instantiate_testrail.update_testrail(case_id=TEST_CASES["5g_eap_bridge"], run_id=instantiate_project, status_id=1, msg='5G WPA2 ENTERPRISE Client Connectivity Passed successfully - ' 'bridge mode') else: instantiate_testrail.update_testrail(case_id=TEST_CASES["5g_eap_bridge"], run_id=instantiate_project, status_id=5, msg='5G WPA2 ENTERPRISE Client Connectivity Failed - bridge mode') assert eap_connect.passes() @pytest.mark.modify_ssid @pytest.mark.parametrize( 'update_ssid', (["BRIDGE, WPA, 5G, Sanity-updated-5G-WPA-BRIDGE"]), indirect=True ) def test_modify_ssid(self, request, update_ssid, get_lanforge_data, setup_profile_data, instantiate_testrail, instantiate_project): profile_data = setup_profile_data["BRIDGE"]["WPA"]["5G"] station_names = [] for i in range(0, int(request.config.getini("num_stations"))): station_names.append(get_lanforge_data["lanforge_5g_prefix"] + "0" + str(i)) staConnect = StaConnect2(get_lanforge_data["lanforge_ip"], int(get_lanforge_data["lanforge-port-number"]), debug_=False) staConnect.sta_mode = 0 staConnect.upstream_resource = 1 staConnect.upstream_port = get_lanforge_data["lanforge_bridge_port"] staConnect.radio = get_lanforge_data["lanforge_5g"] staConnect.resource = 1 staConnect.dut_ssid = profile_data["ssid_name"] staConnect.dut_passwd = profile_data["security_key"] staConnect.dut_security = "wpa" staConnect.station_names = station_names staConnect.sta_prefix = get_lanforge_data["lanforge_5g_prefix"] staConnect.runtime_secs = 10 staConnect.bringup_time_sec = 60 staConnect.cleanup_on_exit = True # staConnect.cleanup() staConnect.setup() staConnect.start() print("napping %f sec" % staConnect.runtime_secs) time.sleep(staConnect.runtime_secs) staConnect.stop() staConnect.cleanup() run_results = staConnect.get_result_list() for result in run_results: print("test result: " + result) # result = 'pass' print("Single Client Connectivity :", staConnect.passes) if staConnect.passes(): instantiate_testrail.update_testrail(case_id=TEST_CASES["bridge_ssid_update"], run_id=instantiate_project, status_id=1, msg='5G WPA Client Connectivity Passed successfully - 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modules/dbnd-airflow/test_dbnd_airflow/package/test_airflow_imports.py

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modules/dbnd-airflow/test_dbnd_airflow/package/test_airflow_imports.py

ipattarapong/dbnd

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modules/dbnd-airflow/test_dbnd_airflow/package/test_airflow_imports.py

ipattarapong/dbnd

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def test_import_databand(): print("Starting Import") import dbnd str(dbnd) def test_import_airflow_settings(): print("Starting Import") import airflow.settings str(airflow.settings)

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GenDataset/words.py

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2022-02-22T13:07:55.000Z

words= '啊阿埃挨哎唉哀皑癌蔼矮艾碍爱隘鞍氨安俺按暗岸胺案肮昂盎凹敖熬翱袄傲奥懊澳芭捌扒叭吧笆八疤巴拔跋靶把耙坝霸罢爸白柏百摆佰败拜稗斑班搬扳般颁板版扮拌伴瓣半办绊邦帮梆榜膀绑棒磅蚌镑傍谤苞胞包褒剥薄雹保堡饱宝抱报暴豹鲍爆杯碑悲卑北辈背贝钡倍狈备惫焙被奔苯本笨崩绷甭泵蹦迸逼鼻比鄙笔彼碧蓖蔽毕毙毖币庇痹闭敝弊必辟壁臂避陛鞭边编贬扁便变卞辨辩辫遍标彪膘表鳖憋别瘪彬斌濒滨宾摈兵冰柄丙秉饼炳病并玻菠播拨钵波博勃搏铂箔伯帛舶脖膊渤泊驳捕卜哺补埠不布步簿部怖擦猜裁材才财睬踩采彩菜蔡餐参蚕残惭惨灿苍舱仓沧藏操糙槽曹草厕策侧册测层蹭插叉茬茶查碴搽察岔差诧拆柴豺搀掺蝉馋谗缠铲产阐颤昌猖场尝常长偿肠厂敞畅唱倡超抄钞朝嘲潮巢吵炒车扯撤掣彻澈郴臣辰尘晨忱沉陈趁衬撑称城橙成呈乘程惩澄诚承逞骋秤吃痴持匙池迟弛驰耻齿侈尺赤翅斥炽充冲虫崇宠抽酬畴踌稠愁筹仇绸瞅丑臭初出橱厨躇锄雏滁除楚础储矗搐触处揣川穿椽传船喘串疮窗幢床闯创吹炊捶锤垂春椿醇唇淳纯蠢戳绰疵茨磁雌辞慈瓷词此刺赐次聪葱囱匆从丛凑粗醋簇促蹿篡窜摧崔催脆瘁粹淬翠村存寸磋撮搓措挫错搭达答瘩打大呆歹傣戴带殆代贷袋待逮怠耽担丹单郸掸胆旦氮但惮淡诞弹蛋当挡党荡档刀捣蹈倒岛祷导到稻悼道盗德得的蹬灯登等瞪凳邓堤低滴迪敌笛狄涤翟嫡抵底地蒂第帝弟递缔颠掂滇碘点典靛垫电佃甸店惦奠淀殿碉叼雕凋刁掉吊钓调跌爹碟蝶迭谍叠丁盯叮钉顶鼎锭定订丢东冬董懂动栋侗恫冻洞兜抖斗陡豆逗痘都督毒犊独读堵睹赌杜镀肚度渡妒端短锻段断缎堆兑队对墩吨蹲敦顿囤钝盾遁掇哆多夺垛躲朵跺舵剁惰堕蛾峨鹅俄额讹娥恶厄扼遏鄂饿恩而儿耳尔饵洱二贰发罚筏伐乏阀法珐藩帆番翻樊矾钒繁凡烦反返范贩犯饭泛坊芳方肪房防妨仿访纺放菲非啡飞肥匪诽吠肺废沸费芬酚吩氛分纷坟焚汾粉奋份忿愤粪丰封枫蜂峰锋风疯烽逢冯缝讽奉凤佛否夫敷肤孵扶拂辐幅氟符伏俘服浮涪福袱弗甫抚辅俯釜斧脯腑府腐赴副覆赋复傅付阜父腹负富讣附妇缚咐噶嘎该改概钙盖溉干甘杆柑竿肝赶感秆敢赣冈刚钢缸肛纲岗港杠篙皋高膏羔糕搞镐稿告哥歌搁戈鸽胳疙割革葛格蛤阁隔铬个各给根跟耕更庚羹埂耿梗工攻功恭龚供躬公宫弓巩汞拱贡共钩勾沟苟狗垢构购够辜菇咕箍估沽孤姑鼓古蛊骨谷股故顾固雇刮瓜剐寡挂褂乖拐怪棺关官冠观管馆罐惯灌贯光广逛瑰规圭硅归龟闺轨鬼诡癸桂柜跪贵刽辊滚棍锅郭国果裹过哈骸孩海氦亥害骇酣憨邯韩含涵寒函喊罕翰撼捍旱憾悍焊汗汉夯杭航壕嚎豪毫郝好耗号浩呵喝荷菏核禾和何合盒貉阂河涸赫褐鹤贺嘿黑痕很狠恨哼亨横衡恒轰哄烘虹鸿洪宏弘红喉侯猴吼厚候后呼乎忽瑚壶葫胡蝴狐糊湖弧虎唬护互沪户花哗华猾滑画划化话槐徊怀淮坏欢环桓还缓换患唤痪豢焕涣宦幻荒慌黄磺蝗簧皇凰惶煌晃幌恍谎灰挥辉徽恢蛔回毁悔慧卉惠晦贿秽会烩汇讳诲绘荤昏婚魂浑混豁活伙火获或惑霍货祸击圾基机畸稽积箕肌饥迹激讥鸡姬绩缉吉极棘辑籍集及急疾汲即嫉级挤几脊己蓟技冀季伎祭剂悸济寄寂计记既忌际妓继纪嘉枷夹佳家加荚颊贾甲钾假稼价架驾嫁歼监坚尖笺间煎兼肩艰奸缄茧检柬碱碱拣捡简俭剪减荐槛鉴践贱见键箭件健舰剑饯渐溅涧建僵姜将浆江疆蒋桨奖讲匠酱降蕉椒礁焦胶交郊浇骄娇嚼搅铰矫侥脚狡角饺缴绞剿教酵轿较叫窖揭接皆秸街阶截劫节桔杰捷睫竭洁结解姐戒藉芥界借介疥诫届巾筋斤金今津襟紧锦仅谨进靳晋禁近烬浸尽劲荆兢茎睛晶鲸京惊精粳经井警景颈静境敬镜径痉靖竟竞净炯窘揪究纠玖韭久灸九酒厩救旧臼舅咎就疚鞠拘狙疽居驹菊局咀矩举沮聚拒据巨具距踞锯俱句惧炬剧捐鹃娟倦眷卷绢撅攫抉掘倔爵觉决诀绝均菌钧军君峻俊竣浚郡骏喀咖卡咯开揩楷凯慨刊堪勘坎砍看康慷糠扛抗亢炕考拷烤靠坷苛柯棵磕颗科壳咳可渴克刻客课肯啃垦恳坑吭空恐孔控抠口扣寇枯哭窟苦酷库裤夸垮挎跨胯块筷侩快宽款匡筐狂框矿眶旷况亏盔岿窥葵奎魁傀馈愧溃坤昆捆困括扩廓阔垃拉喇蜡腊辣啦莱来赖蓝婪栏拦篮阑兰澜谰揽览懒缆烂滥琅榔狼廊郎朗浪捞劳牢老佬姥酪烙涝勒乐雷镭蕾磊累儡垒擂肋类泪棱楞冷厘梨犁黎篱狸离漓理李里鲤礼莉荔吏栗丽厉励砾历利僳例俐痢立粒沥隶力璃哩俩联莲连镰廉怜涟帘敛脸链恋炼练粮凉梁粱良两辆量晾亮谅撩聊僚疗燎寥辽潦了撂镣廖料列裂烈劣猎琳林磷霖临邻鳞淋凛赁吝拎玲菱零龄铃伶羚凌灵陵岭领另令溜琉榴硫馏留刘瘤流柳六龙聋咙笼窿隆垄拢陇楼娄搂篓漏陋芦卢颅庐炉掳卤虏鲁麓碌露路赂鹿潞禄录陆戮驴吕铝侣旅履屡缕虑氯律率滤绿峦挛孪滦卵乱掠略抡轮伦仑沦纶论萝螺罗逻锣箩骡裸落洛骆络妈麻玛码蚂马骂嘛吗埋买麦卖迈脉瞒馒蛮满蔓曼慢漫谩芒茫盲氓忙莽猫茅锚毛矛铆卯茂冒帽貌贸么玫枚梅酶霉煤没眉媒镁每美昧寐妹媚门闷们萌蒙檬盟锰猛梦孟眯醚靡糜迷谜弥米秘觅泌蜜密幂棉眠绵冕免勉娩缅面苗描瞄藐秒渺庙妙蔑灭民抿皿敏悯闽明螟鸣铭名命谬摸摹蘑模膜磨摩魔抹末莫墨默沫漠寞陌谋牟某拇牡亩姆母墓暮幕募慕木目睦牧穆拿哪呐钠那娜纳氖乃奶耐奈南男难囊挠脑恼闹淖呢馁内嫩能妮霓倪泥尼拟你匿腻逆溺蔫拈年碾撵捻念娘酿鸟尿捏聂孽啮镊镍涅您柠狞凝宁拧泞牛扭钮纽脓浓农弄奴努怒女暖虐疟挪懦糯诺哦欧鸥殴藕呕偶沤啪趴爬帕怕琶拍排牌徘湃派攀潘盘磐盼畔判叛乓庞旁耪胖抛咆刨炮袍跑泡呸胚培裴赔陪配佩沛喷盆砰抨烹澎彭蓬棚硼篷膨朋鹏捧碰坯砒霹批披劈琵毗啤脾疲皮匹痞僻屁譬篇偏片骗飘漂瓢票撇瞥拼频贫品聘乒坪苹萍平凭瓶评屏坡泼颇婆破魄迫粕剖扑铺仆莆葡菩蒲埔朴圃普浦谱曝瀑期欺栖戚妻七凄漆柒沏其棋奇歧畦崎脐齐旗祈祁骑起岂乞企启契砌器气迄弃汽泣讫掐洽牵扦钎铅千迁签仟谦乾黔钱钳前潜遣浅谴堑嵌欠歉枪呛腔羌墙蔷强抢橇锹敲悄桥瞧乔侨巧鞘撬翘峭俏窍切茄且怯窃钦侵亲秦琴勤芹擒禽寝沁青轻氢倾卿清擎晴氰情顷请庆琼穷秋丘邱球求囚酋泅趋区蛆曲躯屈驱渠取娶龋趣去圈颧权醛泉全痊拳犬券劝缺炔瘸却鹊榷确雀裙群然燃冉染瓤壤攘嚷让饶扰绕惹热壬仁人忍韧任认刃妊纫扔仍日戎茸蓉荣融熔溶容绒冗揉柔肉茹蠕儒孺如辱乳汝入褥软阮蕊瑞锐闰润若弱撒洒萨腮鳃塞赛三叁伞散桑嗓丧搔骚扫嫂瑟色涩森僧莎砂杀刹沙纱傻啥煞筛晒珊苫杉山删煽衫闪陕擅赡膳善汕扇缮墒伤商赏晌上尚裳梢捎稍烧芍勺韶少哨邵绍奢赊蛇舌舍赦摄射慑涉社设砷申呻伸身深娠绅神沈审婶甚肾慎渗声生甥牲升绳省盛剩胜圣师失狮施湿诗尸虱十石拾时什食蚀实识史矢使屎驶始式示士世柿事拭誓逝势是嗜噬适仕侍释饰氏市恃室视试收手首守寿授售受瘦兽蔬枢梳殊抒输叔舒淑疏书赎孰熟薯暑曙署蜀黍鼠属术述树束戍竖墅庶数漱恕刷耍摔衰甩帅栓拴霜双爽谁水睡税吮瞬顺舜说硕朔烁斯撕嘶思私司丝死肆寺嗣四伺似饲巳松耸怂颂送宋讼诵搜艘擞嗽苏酥俗素速粟僳塑溯宿诉肃酸蒜算虽隋随绥髓碎岁穗遂隧祟孙损笋蓑梭唆缩琐索锁所塌他它她塔獭挞蹋踏胎苔抬台泰酞太态汰坍摊贪瘫滩坛檀痰潭谭谈坦毯袒碳探叹炭汤塘搪堂棠膛唐糖倘躺淌趟烫掏涛滔绦萄桃逃淘陶讨套特藤腾疼誊梯剔踢锑提题蹄啼体替嚏惕涕剃屉天添填田甜恬舔腆挑条迢眺跳贴铁帖厅听烃汀廷停亭庭艇通桐酮瞳同铜彤童桶捅筒统痛偷投头透凸秃突图徒途涂屠土吐兔湍团推颓腿蜕褪退吞屯臀拖托脱鸵陀驮驼椭妥拓唾挖哇蛙洼娃瓦袜歪外豌弯湾玩顽丸烷完碗挽晚皖惋宛婉万腕汪王亡枉网往旺望忘妄威巍微危韦违桅围唯惟为潍维苇萎委伟伪尾纬未蔚味畏胃喂魏位渭谓尉慰卫瘟温蚊文闻纹吻稳紊问嗡翁瓮挝蜗涡窝我斡卧握沃巫呜钨乌污诬屋无芜梧吾吴毋武五捂午舞伍侮坞戊雾晤物勿务悟误昔熙析西硒矽晰嘻吸锡牺稀息希悉膝夕惜熄烯溪汐犀檄袭席习媳喜铣洗系隙戏细瞎虾匣霞辖暇峡侠狭下厦夏吓掀锨先仙鲜纤咸贤衔舷闲涎弦嫌显险现献县腺馅羡宪陷限线相厢镶香箱襄湘乡翔祥详想响享项巷橡像向象萧硝霄削哮嚣销消宵淆晓小孝校肖啸笑效楔些歇蝎鞋协挟携邪斜胁谐写械卸蟹懈泄泻谢屑薪芯锌欣辛新忻心信衅星腥猩惺兴刑型形邢行醒幸杏性姓兄凶胸匈汹雄熊休修羞朽嗅锈秀袖绣墟戌需虚嘘须徐许蓄酗叙旭序畜恤絮婿绪续轩喧宣悬旋玄选癣眩绚靴薛学穴雪血勋熏循旬询寻驯巡殉汛训讯逊迅压押鸦鸭呀丫芽牙蚜崖衙涯雅哑亚讶焉咽阉烟淹盐严研蜒岩延言颜阎炎沿奄掩眼衍演艳堰燕厌砚雁唁彦焰宴谚验殃央鸯秧杨扬佯疡羊洋阳氧仰痒养样漾邀腰妖瑶摇尧遥窑谣姚咬舀药要耀椰噎耶爷野冶也页掖业叶曳腋夜液一壹医揖铱依伊衣颐夷遗移仪胰疑沂宜姨彝椅蚁倚已乙矣以艺抑易邑屹亿役臆逸肄疫亦裔意毅忆义益溢诣议谊译异翼翌绎茵荫因殷音阴姻吟银淫寅饮尹引隐印英樱婴鹰应缨莹萤营荧蝇迎赢盈影颖硬映哟拥佣臃痈庸雍踊蛹咏泳涌永恿勇用幽优悠忧尤由邮铀犹油游酉有友右佑釉诱又幼迂淤于盂榆虞愚舆余俞逾鱼愉渝渔隅予娱雨与屿禹宇语羽玉域芋郁吁遇喻峪御愈欲狱育誉浴寓裕预豫驭鸳渊冤元垣袁原援辕园员圆猿源缘远苑愿怨院曰约越跃钥岳粤月悦阅耘云郧匀陨允运蕴酝晕韵孕匝砸杂栽哉灾宰载再在咱攒暂赞赃脏葬遭糟凿藻枣早澡蚤躁噪造皂灶燥责择则泽贼怎增憎曾赠扎喳渣札轧铡闸眨栅榨咋乍炸诈摘斋宅窄债寨瞻毡詹粘沾盏斩辗崭展蘸栈占战站湛绽樟章彰漳张掌涨杖丈帐账仗胀瘴障招昭找沼赵照罩兆肇召遮折哲蛰辙者锗蔗这浙珍斟真甄砧臻贞针侦枕疹诊震振镇阵蒸挣睁征狰争怔整拯正政帧症郑证芝枝支吱蜘知肢脂汁之织职直植殖执值侄址指止趾只旨纸志挚掷至致置帜峙制智秩稚质炙痔滞治窒中盅忠钟衷终种肿重仲众舟周州洲诌粥轴肘帚咒皱宙昼骤珠株蛛朱猪诸诛逐竹烛煮拄瞩嘱主著柱助蛀贮铸筑住注祝驻抓爪拽专砖转撰赚篆桩庄装妆撞壮状椎锥追赘坠缀谆准捉拙卓桌琢茁酌啄着灼浊兹咨资姿滋淄孜紫仔籽滓子自渍字鬃棕踪宗综总纵邹走奏揍租足卒族祖诅阻组钻纂嘴醉最罪尊遵昨左佐柞做作坐座'

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b2bb97a54cbab4786370c1b4aa765d4d617fb5a1

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py

Python

dearpypixl/appitems/values.py

Atlamillias/pixl-engine

c4217a3a65e01e49d05bf7f07946d65484f6e1da

[ "MIT" ]

6

2021-08-28T03:22:19.000Z

2021-10-14T22:04:04.000Z

dearpypixl/appitems/values.py

Atlamillias/pixl-engine

c4217a3a65e01e49d05bf7f07946d65484f6e1da

[ "MIT" ]

1

2021-07-29T16:51:28.000Z

2021-08-03T00:24:11.000Z

dearpypixl/appitems/values.py

Atlamillias/pixl-engine

c4217a3a65e01e49d05bf7f07946d65484f6e1da

[ "MIT" ]

null

from typing import ( Callable, Any, Union, Dict, Tuple, Set, List, ) from dearpygui import dearpygui from dearpypixl.components import * ################################################## ####### NOTE: This file is auto-generated. ####### ################################################## __all__ = [ "IntValue", "Int4Value", "BoolValue", "FloatValue", "Float4Value", "StringValue", "DoubleValue", "Double4Value", "ColorValue", "FloatVectValue", "SeriesValue", ] class IntValue(Widget): """Adds a int value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (int, optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : int = ItemAttribute('information', 'get_item_cached', None, None) value : int = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvIntValue',) _command : Callable = dearpygui.add_int_value def __init__( self , label : str = None, user_data : Any = None, use_internal_label: bool = True, source : Union[int, str] = 0 , default_value : int = 0 , parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class Int4Value(Widget): """Adds a int4 value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (Union[List[int], Tuple[int, ...]], optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : Union[List[int], Tuple[int, ...]] = ItemAttribute('information', 'get_item_cached', None, None) value : Union[List[int], Tuple[int, ...]] = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvInt4Value',) _command : Callable = dearpygui.add_int4_value def __init__( self , label : str = None , user_data : Any = None , use_internal_label: bool = True , source : Union[int, str] = 0 , default_value : Union[List[int], Tuple[int, ...]] = (0, 0, 0, 0), parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class BoolValue(Widget): """Adds a bool value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (bool, optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : bool = ItemAttribute('information', 'get_item_cached', None, None) value : bool = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvBoolValue',) _command : Callable = dearpygui.add_bool_value def __init__( self , label : str = None , user_data : Any = None , use_internal_label: bool = True , source : Union[int, str] = 0 , default_value : bool = False, parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class FloatValue(Widget): """Adds a float value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (float, optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : float = ItemAttribute('information', 'get_item_cached', None, None) value : float = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvFloatValue',) _command : Callable = dearpygui.add_float_value def __init__( self , label : str = None, user_data : Any = None, use_internal_label: bool = True, source : Union[int, str] = 0 , default_value : float = 0.0 , parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class Float4Value(Widget): """Adds a float4 value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (Union[List[float], Tuple[float, ...]], optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : Union[List[float], Tuple[float, ...]] = ItemAttribute('information', 'get_item_cached', None, None) value : Union[List[float], Tuple[float, ...]] = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvFloat4Value',) _command : Callable = dearpygui.add_float4_value def __init__( self , label : str = None , user_data : Any = None , use_internal_label: bool = True , source : Union[int, str] = 0 , default_value : Union[List[float], Tuple[float, ...]] = (0.0, 0.0, 0.0, 0.0), parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class StringValue(Widget): """Adds a string value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (str, optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : str = ItemAttribute('information', 'get_item_cached', None, None) value : str = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvStringValue',) _command : Callable = dearpygui.add_string_value def __init__( self , label : str = None, user_data : Any = None, use_internal_label: bool = True, source : Union[int, str] = 0 , default_value : str = '' , parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class DoubleValue(Widget): """Adds a double value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (float, optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : float = ItemAttribute('information', 'get_item_cached', None, None) value : float = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvDoubleValue',) _command : Callable = dearpygui.add_double_value def __init__( self , label : str = None, user_data : Any = None, use_internal_label: bool = True, source : Union[int, str] = 0 , default_value : float = 0.0 , parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class Double4Value(Widget): """Adds a double value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (Any, optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : Any = ItemAttribute('information', 'get_item_cached', None, None) value : Any = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvDouble4Value',) _command : Callable = dearpygui.add_double4_value def __init__( self , label : str = None , user_data : Any = None , use_internal_label: bool = True , source : Union[int, str] = 0 , default_value : Any = (0.0, 0.0, 0.0, 0.0), parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class ColorValue(Widget): """Adds a color value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (Union[List[float], Tuple[float, ...]], optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : Union[List[float], Tuple[float, ...]] = ItemAttribute('information', 'get_item_cached', None, None) value : Union[List[float], Tuple[float, ...]] = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvColorValue',) _command : Callable = dearpygui.add_color_value def __init__( self , label : str = None , user_data : Any = None , use_internal_label: bool = True , source : Union[int, str] = 0 , default_value : Union[List[float], Tuple[float, ...]] = (0.0, 0.0, 0.0, 0.0), parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class FloatVectValue(Widget): """Adds a float vect value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (Union[List[float], Tuple[float, ...]], optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : Union[List[float], Tuple[float, ...]] = ItemAttribute('information', 'get_item_cached', None, None) value : Union[List[float], Tuple[float, ...]] = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvFloatVectValue',) _command : Callable = dearpygui.add_float_vect_value def __init__( self , label : str = None, user_data : Any = None, use_internal_label: bool = True, source : Union[int, str] = 0 , default_value : Union[List[float], Tuple[float, ...]] = () , parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, ) class SeriesValue(Widget): """Adds a plot series value. Args: label (str, optional): Overrides 'name' as label. user_data (Any, optional): User data for callbacks use_internal_label (bool, optional): Use generated internal label instead of user specified (appends ### uuid). tag (Union[int, str], optional): Unique id used to programmatically refer to the item.If label is unused this will be the label. source (Union[int, str], optional): Overrides 'id' as value storage key. default_value (Any, optional): parent (Union[int, str], optional): Parent to add this item to. (runtime adding) id (Union[int, str], optional): (deprecated) Returns: Union[int, str] """ label : str = ItemAttribute("configuration", "get_item_config", "set_item_config", None) user_data : Any = ItemAttribute("configuration", "get_item_config", "set_item_config", None) use_internal_label: bool = ItemAttribute("configuration", "get_item_config", "set_item_config", None) source : Union[int, str] = ItemAttribute("configuration", "get_item_config", "set_item_config", None) default_value : Any = ItemAttribute('information', 'get_item_cached', None, None) value : Any = ItemAttribute("configuration", "get_item_value", "set_item_value", "default_value") _is_container : bool = False _is_root_item : bool = False _is_value_able : bool = True _unique_parents : tuple = ('ValueRegistry',) _unique_children : tuple = () _unique_commands : tuple = () _unique_constants : tuple = ('mvSeriesValue',) _command : Callable = dearpygui.add_series_value def __init__( self , label : str = None, user_data : Any = None, use_internal_label: bool = True, source : Union[int, str] = 0 , default_value : Any = () , parent : Union[int, str] = 13 , **kwargs , ) -> None: super().__init__( label=label, user_data=user_data, use_internal_label=use_internal_label, source=source, default_value=default_value, parent=parent, **kwargs, )

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0.045887

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0.931169

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38,361

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62.681373

0.79614

0.204922

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0.791457

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8

b2ce779efb8dbd435eb3f8f8315d1d91ec804a5b

46,629

py

Python

test/integration/clueweb09.py

eugene-yang/ir_datasets

2b5a42edfb9ab8c4ee8f11674ffe14d60f41ec1e

[ "Apache-2.0" ]

null

test/integration/clueweb09.py

eugene-yang/ir_datasets

2b5a42edfb9ab8c4ee8f11674ffe14d60f41ec1e

[ "Apache-2.0" ]

null

test/integration/clueweb09.py

eugene-yang/ir_datasets

2b5a42edfb9ab8c4ee8f11674ffe14d60f41ec1e

[ "Apache-2.0" ]

null

import re import unittest import ir_datasets from ir_datasets.datasets.clueweb09 import TrecWebTrackQuery, TrecPrel from ir_datasets.formats import TrecQrel, TrecSubtopic, GenericDoc, GenericQuery, WarcDoc from .base import DatasetIntegrationTest _logger = ir_datasets.log.easy() class TestClueWeb09(DatasetIntegrationTest): def test_clueweb09_docs(self): self._test_docs('clueweb09', items={ 0: WarcDoc('clueweb09-ar0000-00-00000', 'http://0098shop.com/product_"EH24_A\'1C3_Forex_(\'2\'131E\'�G.html', '2009-03-84T15:35:08-0700', re.compile(b'^HTTP/1\\.1 200 OK\nServer: Apache/2\\.2\\.11 \$Unix\$ mod_ssl/2\\.2\\.11 OpenSSL/0\\.9\\.8b DAV/2 mod_auth_passthroug.{92}\nConnection: close\nContent\\-Type: text/html\nDate: Fri, 27 Feb 2009 16:04:39 GMT\nContent\\-Length: 38889$', flags=16), re.compile(b'^<meta httpequiv=Content\\-Type content="text/html; charset=utf\\-8"><meta httpequiv=Content\\-Type content.{38691}m3d\'\\);\\\r\n</SCRIPT>\\\r\n</span>\n\\\t<span id=\'HAM3D_counter\' class=\'HAM3D_hidden\'></span>\n</body>\n</html>\n\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-ar0000-00-00009', 'http://00perdomain.com/kids_and_teens/international/arabic/', '2009-03-84T15:35:08-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Mon, 09 Feb 2009 12:41:10 GMT\nPragma: n.{145} sid=iorj3059uaka0isae61uh29494; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 28444$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{28246}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-ar0000-00-01000', 'http://213.136.192.26/311276/ln59d.htm', '2009-03-84T15:35:13-0700', re.compile(b'^HTTP/1\\.1 200 OK\nAccept\\-Ranges: bytes\nContent\\-Type: text/html\nDate: Wed, 28 Jan 2009 18:47:22 GMT\nHos.{85}: close\nLast\\-Modified: Thu, 08 Jan 2009 00:28:36 GMT\nETag: "548bbb2871c91:a76"\nContent\\-Length: 65536$', flags=16), re.compile(b'^<html>\\\r\n <head>\\\r\n <META http\\-equiv="Content\\-Type" content="text/html; charset=windows\\-1256">\\\r\n .{65338}\n <font face="Simplified Arabic" color="\\#4D5064">\\\r\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/ar', items={ 0: WarcDoc('clueweb09-ar0000-00-00000', 'http://0098shop.com/product_"EH24_A\'1C3_Forex_(\'2\'131E\'�G.html', '2009-03-84T15:35:08-0700', re.compile(b'^HTTP/1\\.1 200 OK\nServer: Apache/2\\.2\\.11 \$Unix\$ mod_ssl/2\\.2\\.11 OpenSSL/0\\.9\\.8b DAV/2 mod_auth_passthroug.{92}\nConnection: close\nContent\\-Type: text/html\nDate: Fri, 27 Feb 2009 16:04:39 GMT\nContent\\-Length: 38889$', flags=16), re.compile(b'^<meta httpequiv=Content\\-Type content="text/html; charset=utf\\-8"><meta httpequiv=Content\\-Type content.{38691}m3d\'\\);\\\r\n</SCRIPT>\\\r\n</span>\n\\\t<span id=\'HAM3D_counter\' class=\'HAM3D_hidden\'></span>\n</body>\n</html>\n\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-ar0000-00-00009', 'http://00perdomain.com/kids_and_teens/international/arabic/', '2009-03-84T15:35:08-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Mon, 09 Feb 2009 12:41:10 GMT\nPragma: n.{145} sid=iorj3059uaka0isae61uh29494; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 28444$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{28246}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-ar0000-00-01000', 'http://213.136.192.26/311276/ln59d.htm', '2009-03-84T15:35:13-0700', re.compile(b'^HTTP/1\\.1 200 OK\nAccept\\-Ranges: bytes\nContent\\-Type: text/html\nDate: Wed, 28 Jan 2009 18:47:22 GMT\nHos.{85}: close\nLast\\-Modified: Thu, 08 Jan 2009 00:28:36 GMT\nETag: "548bbb2871c91:a76"\nContent\\-Length: 65536$', flags=16), re.compile(b'^<html>\\\r\n <head>\\\r\n <META http\\-equiv="Content\\-Type" content="text/html; charset=windows\\-1256">\\\r\n .{65338}\n <font face="Simplified Arabic" color="\\#4D5064">\\\r\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/zh', items={ 0: WarcDoc('clueweb09-zh0000-00-00000', 'http://000027.istock.jrj.com.cn/', '2009-03-77T19:52:11-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=GBK\nContent\\-Encoding: gzip\nVary: Accept\\-Encoding\nDa.{63}ose\nSet\\-Cookie: JSESSIONID=aWnxiSnSp6rg; path=/\nContent\\-Language: zh\\-CN, zh\\-CN\nContent\\-Length: 65536$', flags=16), re.compile(b'^\\\r\n\\\r\n\\\r\n\\\r\n\\\r\n\\\r\n<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Transitional//EN" "http://www\\.w3\\.org/TR/xht.{65338}\\.com\\.cn/component/editor/imgs/B012\\.gif" height="30" width="30" onclick="oblog_InsertImg\$this\\.src\$"\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-zh0000-00-00009', 'http://000078.istock.jrj.com.cn/forum000078/topic1001345.html', '2009-03-77T19:52:11-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=GBK\nContent\\-Encoding: gzip\nVary: Accept\\-Encoding\nDa.{63}ose\nSet\\-Cookie: JSESSIONID=bbPnYVFWx8D6; path=/\nContent\\-Language: zh\\-CN, zh\\-CN\nContent\\-Length: 26075$', flags=16), re.compile(b'^\\\r\n\\\r\n\\\r\n\\\r\n\\\r\n<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Transitional//EN" "http://www\\.w3\\.org/TR/xhtml.{25877}lt="" />\\\r\n</body>\\\r\n<script src="http://istock\\.jrj\\.com\\.cn/includes/js/tongji\\.js"></script>\\\r\n</html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-zh0000-00-01000', 'http://119go.com/shop/index.htm', '2009-03-77T19:52:15-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html\nAccept\\-Ranges: bytes\nDate: Fri, 09 Jan 2009 21:54:09 GMT\nSer.{56} close\nLast\\-Modified: Fri, 19 Sep 2008 01:50:00 GMT\nETag: "054996fa19c91:337a"\nContent\\-Length: 18005$', flags=16), re.compile(b'^<!DOCTYPE HTML PUBLIC "\\-//W3C//DTD HTML 4\\.01 Transitional//EN"\\\r\n"http://www\\.w3\\.org/TR/html4/loose\\.dt.{17807}UA\\-105821\\-1";urchinTracker\$\$;</script><!\\-\\-\\#include virtual="/include/ads\\.asp"\\-\\-></body>\\\r\n</html>\\\r\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/en', items={ 0: WarcDoc('clueweb09-en0000-00-00000', 'http://00000-nrt-realestate.homepagestartup.com/', '2009-03-65T08:43:19-0800', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html\nDate: Tue, 13 Jan 2009 18:05:10 GMT\nPragma: no\\-cache\nCache\\-C.{100}Modified: Tue, 13 Jan 2009 18:05:10 GMT\nExpires: Mon, 20 Dec 1998 01:00:00 GMT\nContent\\-Length: 16254$', flags=16), re.compile(b'^<head> <meta http\\-equiv="Content\\-Language" content="en\\-gb"> <meta http\\-equiv="Content\\-Type" content=.{16056} 8pt">YouTube Videos</span></td> </tr> </table> </td> </tr> </table></div> </div> </body> </html> \n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-en0000-00-00009', 'http://00perdomain.com/computers/', '2009-03-65T08:43:20-0800', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Sat, 17 Jan 2009 23:40:59 GMT\nPragma: n.{145} sid=i35idajmde65hlem4m2jpmrc37; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 23500$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{23302}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-en0000-00-01000', 'http://2modern.com/designer/FLOS/Flos-Archimoon-Soft-Table-Lamp', '2009-03-65T08:44:07-0800', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nKeep\\-Alive: timeout=15, max=965\nContent\\-Encod.{359}4Pa38Ta38Nb350; path=/\nLast\\-Modified: Tue, 13 Jan 2009 21:10:47 GMT\nExpires: 0\nContent\\-Length: 52741$', flags=16), re.compile(b'^\n<html>\n<head>\n<meta http\\-equiv="Content\\-Type" content="text/html; charset=UTF\\-8">\n<title>FLOS \\- Arc.{52543}\\- \\[ 418126 \\] \\[ \\] \\[ /s\\.nl \\] \\[ Tue Jan 13 13:10:47 PST 2009 \\] \\-\\->\n<!\\-\\- Not logging slowest SQL \\-\\->\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/fr', items={ 0: WarcDoc('clueweb09-fr0000-00-00000', 'http://0-charmedgallery.skyrock.com/', '2009-03-85T01:34:33-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html\nContent\\-Encoding: gzip\nP3P: CP="NOI DSP COR CURa DEVa PSAa O.{328}xpires: Sun, 08 Feb 2009 15:13:41 GMT\nETag: "92c422f2ea325185cfadb9a9088b2b1f"\nContent\\-Length: 53898$', flags=16), re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Strict//EN" "http://www\\.w3\\.org/TR/xhtml1/DTD/xhtml1\\-str.{53700}ascript" src="http://pagead2\\.googlesyndication\\.com/pagead/show_ads\\.js"></script>\n\n\n</body>\n</html>\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-fr0000-00-00009', 'http://000221.skyrock.com/', '2009-03-85T01:34:33-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html\nContent\\-Encoding: gzip\nP3P: CP="NOI DSP COR CURa DEVa PSAa O.{329}xpires: Fri, 13 Feb 2009 21:03:18 GMT\nETag: "bc2011cb3798d5b21d8df1709d7270f1"\nContent\\-Length: 31594$', flags=16), re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Strict//EN" "http://www\\.w3\\.org/TR/xhtml1/DTD/xhtml1\\-str.{31396}ascript" src="http://pagead2\\.googlesyndication\\.com/pagead/show_ads\\.js"></script>\n\n\n</body>\n</html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-fr0000-00-01000', 'http://123maigrir.com.ivchost3.com/pratique/institut/institut2.htm', '2009-03-85T01:34:39-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html\nAccept\\-Ranges: bytes\nDate: Thu, 29 Jan 2009 16:25:21 GMT\nSer.{95}ose\nLast\\-Modified: Fri, 15 Jun 2007 23:09:10 GMT\nETag: "18441c9\\-adbe\\-46731c16"\nContent\\-Length: 44478$', flags=16), re.compile(b'^<html><!\\-\\- \\#BeginTemplate "/Templates/page_menu_complet\\.dwt" \\-\\-><!\\-\\- DW6 \\-\\->\\\r\n<head>\\\r\n<script langua.{44280}"279" align="center">\\ </td>\\\r\n </tr>\\\r\n</table>\\\r\n\\\r\n</body>\\\r\n\\\r\n<!\\-\\- \\#EndTemplate \\-\\-></html>\\\r\n\\\r\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/de', items={ 0: WarcDoc('clueweb09-de0000-00-00000', 'http://00perdomain.com/kids_and_teens/international/deutsch/', '2009-03-84T23:38:37-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Sun, 08 Feb 2009 06:17:05 GMT\nPragma: n.{144}: sid=g3njt512js43a04j8vekkt0627; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 9942$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{9744}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-de0000-00-00009', 'http://00perdomain.com/world/deutsch/computer/', '2009-03-84T23:38:37-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Tue, 03 Feb 2009 03:48:40 GMT\nCache\\-Con.{145} sid=fit0t220fh9vpsefik8l628866; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 21957$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{21759}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-de0000-00-01000', 'http://1689494.rc-welt.com/', '2009-03-84T23:38:43-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=iso\\-8859\\-1\nContent\\-Encoding: gzip\nDate: Mon, 26 Jan.{332}Modified: Mon, 26 Jan 2009 01:42:05 GMT\nExpires: Mon, 26 Jan 2009 01:42:05 GMT\nContent\\-Length: 38206$', flags=16), re.compile(b'^ <!DOCTYPE HTML PUBLIC "\\-//W3C//DTD HTML 4\\.01 Transitional//EN"> <html> <head> <meta http\\-equiv="Co.{38008}"0" height="0" scrolling="no" name="dynamicFrame" src="RCheartbeat\\.php" ></iframe> </body> </html>\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/it', items={ 0: WarcDoc('clueweb09-it0000-00-00000', 'http://00lucianoligabue00.giovani.it/', '2009-03-84T17:45:02-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html\nContent\\-Encoding: gzip\nVary: Host,Accept\\-Encoding,User\\-Agent.{248}ec0cfa05ca1; path=/; domain=\\.giovani\\.it\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 12895$', flags=16), re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Transitional//EN" "http://www\\.w3\\.org/TR/xhtml1/DTD/xhtm.{12697}avascript">\n_uacct = "UA\\-746038\\-2";\n_udn="giovani\\.it";\nurchinTracker\$\$;\n</script>\n</body>\n</html>\n\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-it0000-00-00009', 'http://00perdomain.com/world/furlan/sal%c3%bbt/', '2009-03-84T17:45:02-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Sun, 08 Feb 2009 06:13:46 GMT\nCache\\-Con.{144}: sid=bqreqd4mrjrm3fi30405ldfnq6; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 9794$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{9596}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-it0000-00-01000', 'http://aaronsummers.ifrance.com/new/socci/', '2009-03-84T17:45:07-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=ISO\\-8859\\-1\nAccept\\-Ranges: bytes\nDate: Tue, 10 Feb 2.{70}lose\nLast\\-Modified: Wed, 10 Oct 2007 19:43:32 GMT\nETag: "804131\\-3d59\\-b356a100"\nContent\\-Length: 16483$', flags=16), re.compile(b'^<script language="Javascript" type="text/javascript">\n<!\\-\\-\nvar d=new Date; rnd=d\\.getDay\$\$\\+\'\\-\'\\+d\\.getH.{16285}\'<sc\'\\+\'ript src="http://js\\-perso\\.ifrance\\.com/js2\\.php\\?\'\\+rnd\\+\'"><\'\\+\'/sc\'\\+\'ript>\'\\);\n// \\-\\->\n</script>\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/ja', items={ 0: WarcDoc('clueweb09-ja0000-00-00000', 'http://00077.web.fc2.com/', '2009-03-85T02:09:10-0700', re.compile(b'^HTTP/1\\.1 200 OK\nAccept\\-Ranges: bytes\nContent\\-Type: text/html\nDate: Tue, 13 Jan 2009 21:29:20 GMT\nSer.{98}ection: close\nLast\\-Modified: Tue, 18 Nov 2008 14:07:53 GMT\nContent\\-Language: en\nContent\\-Length: 9911$', flags=16), re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Transitional//EN"\n "http://www\\.w3\\.org/TR/xhtml1/DTD/xht.{9713}_cs \\+ \'\\&dm=\' \\+ fhp_dm \\+ \'"><\' \\+ \'/script>\';\ndocument\\.write\$fhp_wt\$;\n//\\-\\-></script></body>\n</html>\n\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-ja0000-00-00009', 'http://0095.jp/', '2009-03-85T02:09:10-0700', b'HTTP/1.1 200 OK\nContent-Type: text/html\nDate: Thu, 08 Jan 2009 04:28:30 GMT\nServer: Apache/1.3.39 (Unix)\nX-Powered-By: PHP/5.2.8\nConnection: close\nContent-Length: 20822', re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Transitional//EN" "http://www\\.w3\\.org/TR/xhtml1/DTD/xhtm.{20624}r>\n\xa1\xa1\xa1\xa1\xa1\xa1\xa1\xa1\\&copy2009\\ <a href="http://0095\\.jp/">\xa5\xad\xa5\xa6\xa5\xa4\xb6\xe6\xb3\xda\xc9\xf4</a></div>\n</div>\n</body>\n</html>\n\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-ja0000-00-01000', 'http://1bunting.info/sanc3/0066/020/', '2009-03-85T02:09:15-0700', re.compile(b'^HTTP/1\\.1 200 OK\nAccept\\-Ranges: bytes\nContent\\-Type: text/html\nDate: Wed, 07 Jan 2009 12:39:57 GMT\nSer.{145}ast\\-Modified: Sun, 04 Jan 2009 02:38:48 GMT\nETag: "64d86f0\\-2d98\\-45f9f12e0be00"\nContent\\-Length: 11672$', flags=16), re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Transitional//EN" "http://www\\.w3\\.org/TR/xhtml1/DTD/xhtm.{11474}en\\.height\\+"\\&"\\);\ndocument\\.write\$"color="\\+screen\\.colorDepth\\+"\'>"\$;\n// \\-\\->\n</SCRIPT>\n</body>\n</html>\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/ko', items={ 0: WarcDoc('clueweb09-ko0000-00-00000', 'http://00perdomain.com/kids_and_teens/international/korean/', '2009-03-84T16:00:51-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Wed, 11 Feb 2009 16:27:15 GMT\nPragma: n.{145} sid=6eoehtb6uqtbtc5i6j1ohsht55; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 10481$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{10283}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-ko0000-00-00009', 'http://00perdomain.com/world/korean/%ea%b1%b4%ea%b0%95,%ec%9d%98%ed%95%99/%ec%a7%88%eb%b3%91,%ec%a7%88%ed%99%98/', '2009-03-84T16:00:51-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Fri, 27 Feb 2009 20:07:39 GMT\nCache\\-Con.{145} sid=6s444g9ae4nv9uk4mfbb9e2dv3; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 18781$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{18583}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-ko0000-00-01000', 'http://208.70.77.133/9ea771f89c09d26fdd4f9309023b.html', '2009-03-84T16:00:55-0700', b'HTTP/1.1 200 OK\nContent-Type: text/html; charset=EUC-KR\nDate: Sat, 17 Jan 2009 08:48:54 GMT\nServer: Apache/2.0.52 (CentOS)\nX-Powered-By: PHP/5.1.6\nConnection: close\nContent-Length: 14595', re.compile(b'^<!DOCTYPE HTML PUBLIC "\\-//W3C//DTD HTML 4\\.0 Transitional//EN">\n<html>\n<head>\n<title>\xc1\xea\xbd\xc3\xc6\xae\xb7\xb9\xc0\xcc\xb4\xd7\xba\xb9 \xc1.{14397}:<a href="mailto:webmaster@208\\.70\\.77\\.133">\xc0\xa5\xb8\xb6\xbd\xba\xc5\xcd</a>\n</center>\n<body>\n</html>\n<!\\-\\- 0\\.110781 \\-\\->\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/pt', items={ 0: WarcDoc('clueweb09-pt0000-00-00000', 'http://005bom.ezdir.net/', '2009-03-84T20:11:48-0700', re.compile(b'^HTTP/1\\.1 200 OK\nServer: Apache/1\\.3\\.37 \$Unix\$ mod_auth_passthrough/1\\.8 mod_log_bytes/1\\.2 mod_bwlimite.{91}Content\\-Type: text/html; charset=iso\\-8859\\-1\nDate: Wed, 18 Feb 2009 23:32:21 GMT\nContent\\-Length: 1970$', flags=16), re.compile(b'^<HTML>\n<HEAD>\n<META NAME="Generator" CONTENT="ezDIR \\- www\\.ezdir\\.net">\n<META NAME="Description" CONTE.{1772}/ezdir\\.inweb\\.adm\\.br/ezdir/anuncie\\.php">Clique aqui</A></FONT>\n</TD></TR>\n</TABLE>\n</BODY>\n</HTML>\n\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-pt0000-00-00009', 'http://00perdomain.com/world/portugu%c3%aas/artes/artesanato/', '2009-03-84T20:11:48-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Thu, 12 Feb 2009 05:26:23 GMT\nCache\\-Con.{145} sid=8j75130i6a5iibrmaq85ji1753; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 18361$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{18163}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-pt0000-00-01000', 'http://1001gatos.org/john-wood-saiu-da-microsoft-para-mudar-o-mundo/', '2009-03-84T20:11:55-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=UTF\\-8\nDate: Sun, 08 Feb 2009 00:43:44 GMT\nServer: A.{223}, 08\\-Feb\\-2010 00:43:45 GMT; path=/\nX\\-Pingback: http://1001gatos\\.org/xmlrpc\\.php\nContent\\-Length: 40352$', flags=16), re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Strict//EN" "http://www\\.w3\\.org/TR/xhtml1/DTD/xhtml1\\-str.{40154}DynaboxConfig\\?div_nome=dynabox\\&site_origem=8662542\\&cor=cc0000"></script>\\\r\n</body>\\\r\n</html>\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/es', items={ 0: WarcDoc('clueweb09-es0000-00-00000', 'http://00001101.blogspot.com/', '2009-03-81T23:59:24-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=UTF\\-8\nDate: Sat, 24 Jan 2009 18:07:26 GMT\nCache\\-Con.{101}ed: Sat, 17 Jan 2009 18:35:52 GMT\nETag: "a341615f\\-6594\\-4524\\-ae74\\-53101f87cdba"\nContent\\-Length: 34361$', flags=16), re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Strict//EN" "http://www\\.w3\\.org/TR/xhtml1/DTD/xhtml1\\-str.{34163}\\.com/fb/images/pub/feed\\-icon16x16\\.png" alt="" style="border:0"/></a></p>\\\r\n</div>\\\r\n</body>\\\r\n</html>\n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-es0000-00-00009', 'http://00perdomain.com/world/espa%c3%b1ol/', '2009-03-81T23:59:24-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Thu, 29 Jan 2009 19:26:46 GMT\nCache\\-Con.{144}: sid=javrlcp0o652co0p1gvpttlqe6; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 9073$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{8875}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-es0000-00-01000', 'http://abrahamzabludovsky.radiotrece.com.mx/2008/11/27/deportes-del-27-de-noviembre-de-2008/', '2009-03-81T23:59:31-0700', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=UTF\\-8\nDate: Mon, 09 Feb 2009 08:53:49 GMT\nServer: A.{51}tion: close\nX\\-Pingback: http://abrahamzabludovsky\\.radiotrece\\.com\\.mx/xmlrpc\\.php\nContent\\-Length: 28172$', flags=16), re.compile(b'^<!DOCTYPE html PUBLIC "\\-//W3C//DTD XHTML 1\\.0 Strict//EN" "http://www\\.w3\\.org/TR/xhtml1/DTD/xhtml1\\-str.{27974}UA\\-1620189\\-24"\\);\npageTracker\\._initData\$\$;\npageTracker\\._trackPageview\$\$;\n</script>\n</body>\n</html>\n\n\n$', flags=16), 'text/html'), }) self._test_docs('clueweb09/catb', items={ 0: WarcDoc('clueweb09-en0000-00-00000', 'http://00000-nrt-realestate.homepagestartup.com/', '2009-03-65T08:43:19-0800', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html\nDate: Tue, 13 Jan 2009 18:05:10 GMT\nPragma: no\\-cache\nCache\\-C.{100}Modified: Tue, 13 Jan 2009 18:05:10 GMT\nExpires: Mon, 20 Dec 1998 01:00:00 GMT\nContent\\-Length: 16254$', flags=16), re.compile(b'^<head> <meta http\\-equiv="Content\\-Language" content="en\\-gb"> <meta http\\-equiv="Content\\-Type" content=.{16056} 8pt">YouTube Videos</span></td> </tr> </table> </td> </tr> </table></div> </div> </body> </html> \n\n$', flags=16), 'text/html'), 9: WarcDoc('clueweb09-en0000-00-00009', 'http://00perdomain.com/computers/', '2009-03-65T08:43:20-0800', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nDate: Sat, 17 Jan 2009 23:40:59 GMT\nPragma: n.{145} sid=i35idajmde65hlem4m2jpmrc37; path=/\nExpires: Thu, 19 Nov 1981 08:52:00 GMT\nContent\\-Length: 23500$', flags=16), re.compile(b'^\n\n\n<!\\-\\- Site by Zaz Corporation, 1 \\- 8 8 8 \\- 2 \\- Z A Z C O R http://www\\.zazcorp\\.us \\-\\->\n\n\n\n<html><he.{23302}<script type="text/javascript">\n_uacct = "UA\\-488717\\-2";\nurchinTracker\$\$;\n</script>\n\n</body></html>\n\n$', flags=16), 'text/html'), 1000: WarcDoc('clueweb09-en0000-00-01000', 'http://2modern.com/designer/FLOS/Flos-Archimoon-Soft-Table-Lamp', '2009-03-65T08:44:07-0800', re.compile(b'^HTTP/1\\.1 200 OK\nContent\\-Type: text/html; charset=utf\\-8\nKeep\\-Alive: timeout=15, max=965\nContent\\-Encod.{359}4Pa38Ta38Nb350; path=/\nLast\\-Modified: Tue, 13 Jan 2009 21:10:47 GMT\nExpires: 0\nContent\\-Length: 52741$', flags=16), re.compile(b'^\n<html>\n<head>\n<meta http\\-equiv="Content\\-Type" content="text/html; charset=UTF\\-8">\n<title>FLOS \\- Arc.{52543}\\- \\[ 418126 \\] \\[ \\] \\[ /s\\.nl \\] \\[ Tue Jan 13 13:10:47 PST 2009 \\] \\-\\->\n<!\\-\\- Not logging slowest SQL \\-\\->\n\n\n$', flags=16), 'text/html'), }) self._assert_namedtuple(ir_datasets.load('clueweb09').docs.lookup('clueweb09-en0007-01-40637'), WarcDoc('clueweb09-en0007-01-40637', 'http://www.job-hunt.org/marketing.shtml', '2009-03-65T12:44:49-0800', re.compile(b'HTTP/1.1 200 OK.*44437', flags=16), body=re.compile(b'<!DOCTYPE HTML .*</script> \n\n</BODY>\n\n</HTML>\n\n\n', flags=16), body_content_type='text/html')) def test_clueweb09_docstore(self): docstore = ir_datasets.load('clueweb09').docs_store() docstore.clear_cache() with _logger.duration('cold fetch'): result = docstore.get_many(['clueweb09-en0000-00-00003', 'clueweb09-en0000-00-35154', 'clueweb09-ar0000-48-02342']) self.assertEqual(len(result), 3) with _logger.duration('warm fetch'): result = docstore.get_many(['clueweb09-en0000-00-00003', 'clueweb09-en0000-00-35154', 'clueweb09-ar0000-48-02342']) self.assertEqual(len(result), 3) docstore = ir_datasets.load('clueweb09').docs_store() with _logger.duration('warm fetch (new docstore)'): result = docstore.get_many(['clueweb09-en0000-00-00003', 'clueweb09-en0000-00-35154', 'clueweb09-ar0000-48-02342']) self.assertEqual(len(result), 3) with _logger.duration('cold fetch (nearby)'): result = docstore.get_many(['clueweb09-en0000-00-00023', 'clueweb09-en0000-00-35167', 'clueweb09-ar0000-48-02348']) self.assertEqual(len(result), 3) with _logger.duration('cold fetch (earlier)'): result = docstore.get_many(['clueweb09-en0000-00-00001', 'clueweb09-ar0000-48-00009']) self.assertEqual(len(result), 2) def test_clueweb09_queries(self): self._test_queries('clueweb09/en/trec-web-2009', count=50, items={ 0: TrecWebTrackQuery('1', 'obama family tree', "Find information on President Barack Obama's family\n history, including genealogy, national origins, places and dates of\n birth, etc.\n ", 'faceted', (TrecSubtopic(number='1', text='\n Find the TIME magazine photo essay "Barack Obama\'s Family Tree".\n ', type='nav'), TrecSubtopic(number='2', text="\n Where did Barack Obama's parents and grandparents come from?\n ", type='inf'), TrecSubtopic(number='3', text="\n Find biographical information on Barack Obama's mother.\n ", type='inf'))), 9: TrecWebTrackQuery('10', 'cheap internet', "I'm looking for cheap (i.e. low-cost) internet service.\n ", 'faceted', (TrecSubtopic(number='1', text='\n What are some low-cost broadband internet providers?\n ', type='inf'), TrecSubtopic(number='2', text='\n Do any internet providers still sell dial-up?\n ', type='inf'), TrecSubtopic(number='3', text='\n Who can provide inexpensive digital cable television bundled with\n internet service?\n ', type='inf'), TrecSubtopic(number='4', text="\n I'm looking for the Vonage homepage.\n ", type='nav'), TrecSubtopic(number='5', text='\n Find me some providers of free wireless internet access.\n ', type='inf'), TrecSubtopic(number='6', text='\n I want to find cheap DSL providers.\n ', type='inf'), TrecSubtopic(number='7', text='\n Is there a way to get internet access without phone service?\n ', type='inf'), TrecSubtopic(number='8', text="\n Take me to Comcast's homepage.\n ", type='nav'))), 49: TrecWebTrackQuery('50', 'dog heat', 'What is the effect of excessive heat on dogs?\n ', 'ambiguous', (TrecSubtopic(number='1', text='\n What is the effect of excessive heat on dogs?\n ', type='inf'), TrecSubtopic(number='2', text='\n What are symptoms of heat stroke and other heat-related illnesses\n in dogs?\n ', type='inf'), TrecSubtopic(number='3', text='\n Find information on dogs\' reproductive cycle. What does it mean\n when a dog is "in heat"?\n ', type='inf'))), }) self._test_queries('clueweb09/en/trec-web-2010', count=50, items={ 0: TrecWebTrackQuery('51', 'horse hooves', '\n Find information about horse hooves, their care, and diseases of hooves.\n ', 'faceted', (TrecSubtopic(number='1', text="\n Find information about horses' hooves and how to care for them.\n ", type='inf'), TrecSubtopic(number='2', text='\n Find pictures of horse hooves.\n ', type='nav'), TrecSubtopic(number='3', text='\n What are some injuries or diseases of hooves in horses, and how\n are they treated?\n ', type='inf'), TrecSubtopic(number='4', text="\n Describe the anatomy of horses' feet and hooves.\n ", type='inf'), TrecSubtopic(number='5', text='\n Find information on shoeing horses and horseshoe problems.\n ', type='inf'))), 9: TrecWebTrackQuery('60', 'bellevue', '\n Find information about Bellevue, Washington.\n ', 'ambiguous', (TrecSubtopic(number='1', text='\n Find information about Bellevue, Washington.\n ', type='inf'), TrecSubtopic(number='2', text='\n Find information about Bellevue, Nebraska.\n ', type='inf'), TrecSubtopic(number='3', text='\n Find information about Bellevue Hospital Center in New York, NY.\n ', type='inf'), TrecSubtopic(number='4', text='\n Find the homepage of Bellevue University.\n ', type='nav'), TrecSubtopic(number='5', text='\n Find the homepage of Bellevue College, Washington.\n ', type='nav'), TrecSubtopic(number='6', text='\n Find the homepage of Bellevue Hospital Center in New York, NY.\n ', type='nav'))), 49: TrecWebTrackQuery('100', 'rincon puerto rico', '\n Find information about Rincon, Puerto Rico.\n ', 'faceted', (TrecSubtopic(number='1', text='\n Find hotels and beach resorts in Rincon, Puerto Rico.\n ', type='inf'), TrecSubtopic(number='2', text='\n Find information on the history of Rincon, Puerto Rico.\n ', type='inf'), TrecSubtopic(number='3', text='\n Find surf forecasts for Rincon, Puerto Rico.\n ', type='inf'), TrecSubtopic(number='4', text='\n Find pictures of Rincon, Puerto Rico.\n ', type='nav'), TrecSubtopic(number='5', text='\n Find information about real estate and rental properties in\n Rincon, Puerto Rico.\n ', type='inf'))), }) self._test_queries('clueweb09/en/trec-web-2011', count=50, items={ 0: TrecWebTrackQuery('101', 'ritz carlton lake las vegas', '\n Find information about the Ritz Carlton resort at Lake Las Vegas.\n ', 'faceted', (TrecSubtopic(number='1', text='\n Find information about the Ritz Carlton resort at Lake Las Vegas.\n ', type='inf'), TrecSubtopic(number='2', text='\n Find a site where I can determine room price and availability.\n ', type='nav'), TrecSubtopic(number='3', text='\n Find directions to the Ritz Carlton Lake Las Vegas.\n ', type='nav'), TrecSubtopic(number='4', text='\n Find reviews of the Ritz Carlton Lake Las Vegas.\n ', type='inf'))), 9: TrecWebTrackQuery('110', 'map of brazil', '\n What are the boundaries of the political jurisdictions in Brazil?\n ', 'ambiguous', (TrecSubtopic(number='1', text='\n What are the boundaries of the political jurisdictions in Brazil?\n ', type='inf'), TrecSubtopic(number='2', text='\n I am looking for information about taking a vacation trip to Brazil.\n ', type='inf'), TrecSubtopic(number='3', text='\n I want to buy a road map of Brazil.\n ', type='nav'))), 49: TrecWebTrackQuery('150', 'tn highway patrol', '\n What are the requirements to become a Tennessee Highway Patrol State Trooper?\n ', 'faceted', (TrecSubtopic(number='1', text='\n What are the requirements to become a Tennessee Highway Patrol State Trooper?\n ', type='inf'), TrecSubtopic(number='2', text='\n information about the responsibilities of the Tennessee Highway Patrol\n ', type='inf'), TrecSubtopic(number='3', text='\n home page of the Tennessee Highway Patrol\n ', type='nav'), TrecSubtopic(number='4', text='\n I want to fill in the customer satisfaction survey about my interaction with a Tennessee Highway Patrol State Trooper.\n ', type='nav'))), }) self._test_queries('clueweb09/en/trec-web-2012', count=50, items={ 0: TrecWebTrackQuery('151', '403b', '\n What is a 403b plan?\n ', 'faceted', (TrecSubtopic(number='1', text='\n What is a 403b plan?\n ', type='inf'), TrecSubtopic(number='2', text='\n Who is eligible for a 403b plan?\n ', type='inf'), TrecSubtopic(number='3', text='\n What are the rules for a 403b retirement plan?\n ', type='nav'), TrecSubtopic(number='4', text='\n What is the difference between 401k and 403b retirement plans?\n ', type='inf'), TrecSubtopic(number='5', text='\n What are the withdrawal limitations for a 403b retirement plan?\n ', type='nav'))), 9: TrecWebTrackQuery('160', 'grilling', '\n Find kabob recipes.\n ', 'ambiguous', (TrecSubtopic(number='1', text='\n Find kabob recipes.\n ', type='nav'), TrecSubtopic(number='2', text='\n Find tips on grilling vegetables.\n ', type='inf'), TrecSubtopic(number='3', text='\n Find tips on grilling fish.\n ', type='inf'), TrecSubtopic(number='4', text='\n Find instructions for grilling chicken.\n ', type='inf'), TrecSubtopic(number='5', text='\n Find the Grilling Magazine website.\n ', type='nav'), TrecSubtopic(number='6', text='\n Find information on gas barbecue grills and cooking on a gas grill.\n ', type='inf'))), 49: TrecWebTrackQuery('200', 'ontario california airport', '\n Find flight information for the Ontario, CA airport.\n ', 'faceted', (TrecSubtopic(number='1', text='\n Find flight information for the Ontario, CA airport.\n ', type='inf'), TrecSubtopic(number='2', text='\n What hotels are near the Ontario, CA airport?\n ', type='inf'), TrecSubtopic(number='3', text='\n What services/facilities does the Ontario, CA airport offer?\n ', type='inf'), TrecSubtopic(number='4', text='\n What is the address of the Ontario, CA airport?\n ', type='nav'))), }) self._test_queries('clueweb09/catb/trec-web-2009', count=50, items={ 0: TrecWebTrackQuery('1', 'obama family tree', "Find information on President Barack Obama's family\n history, including genealogy, national origins, places and dates of\n birth, etc.\n ", 'faceted', (TrecSubtopic(number='1', text='\n Find the TIME magazine photo essay "Barack Obama\'s Family Tree".\n ', type='nav'), TrecSubtopic(number='2', text="\n Where did Barack Obama's parents and grandparents come from?\n ", type='inf'), TrecSubtopic(number='3', text="\n Find biographical information on Barack Obama's mother.\n ", type='inf'))), 9: TrecWebTrackQuery('10', 'cheap internet', "I'm looking for cheap (i.e. low-cost) internet service.\n ", 'faceted', (TrecSubtopic(number='1', text='\n What are some low-cost broadband internet providers?\n ', type='inf'), TrecSubtopic(number='2', text='\n Do any internet providers still sell dial-up?\n ', type='inf'), TrecSubtopic(number='3', text='\n Who can provide inexpensive digital cable television bundled with\n internet service?\n ', type='inf'), TrecSubtopic(number='4', text="\n I'm looking for the Vonage homepage.\n ", type='nav'), TrecSubtopic(number='5', text='\n Find me some providers of free wireless internet access.\n ', type='inf'), TrecSubtopic(number='6', text='\n I want to find cheap DSL providers.\n ', type='inf'), TrecSubtopic(number='7', text='\n Is there a way to get internet access without phone service?\n ', type='inf'), TrecSubtopic(number='8', text="\n Take me to Comcast's homepage.\n ", type='nav'))), 49: TrecWebTrackQuery('50', 'dog heat', 'What is the effect of excessive heat on dogs?\n ', 'ambiguous', (TrecSubtopic(number='1', text='\n What is the effect of excessive heat on dogs?\n ', type='inf'), TrecSubtopic(number='2', text='\n What are symptoms of heat stroke and other heat-related illnesses\n in dogs?\n ', type='inf'), TrecSubtopic(number='3', text='\n Find information on dogs\' reproductive cycle. What does it mean\n when a dog is "in heat"?\n ', type='inf'))), }) self._test_queries('clueweb09/catb/trec-web-2010', count=50, items={ 0: TrecWebTrackQuery('51', 'horse hooves', '\n Find information about horse hooves, their care, and diseases of hooves.\n ', 'faceted', (TrecSubtopic(number='1', text="\n Find information about horses' hooves and how to care for them.\n ", type='inf'), TrecSubtopic(number='2', text='\n Find pictures of horse hooves.\n ', type='nav'), TrecSubtopic(number='3', text='\n What are some injuries or diseases of hooves in horses, and how\n are they treated?\n ', type='inf'), TrecSubtopic(number='4', text="\n Describe the anatomy of horses' feet and hooves.\n ", type='inf'), TrecSubtopic(number='5', text='\n Find information on shoeing horses and horseshoe problems.\n ', type='inf'))), 9: TrecWebTrackQuery('60', 'bellevue', '\n Find information about Bellevue, Washington.\n ', 'ambiguous', (TrecSubtopic(number='1', text='\n Find information about Bellevue, Washington.\n ', type='inf'), TrecSubtopic(number='2', text='\n Find information about Bellevue, Nebraska.\n ', type='inf'), TrecSubtopic(number='3', text='\n Find information about Bellevue Hospital Center in New York, NY.\n ', type='inf'), TrecSubtopic(number='4', text='\n Find the homepage of Bellevue University.\n ', type='nav'), TrecSubtopic(number='5', text='\n Find the homepage of Bellevue College, Washington.\n ', type='nav'), TrecSubtopic(number='6', text='\n Find the homepage of Bellevue Hospital Center in New York, NY.\n ', type='nav'))), 49: TrecWebTrackQuery('100', 'rincon puerto rico', '\n Find information about Rincon, Puerto Rico.\n ', 'faceted', (TrecSubtopic(number='1', text='\n Find hotels and beach resorts in Rincon, Puerto Rico.\n ', type='inf'), TrecSubtopic(number='2', text='\n Find information on the history of Rincon, Puerto Rico.\n ', type='inf'), TrecSubtopic(number='3', text='\n Find surf forecasts for Rincon, Puerto Rico.\n ', type='inf'), TrecSubtopic(number='4', text='\n Find pictures of Rincon, Puerto Rico.\n ', type='nav'), TrecSubtopic(number='5', text='\n Find information about real estate and rental properties in\n Rincon, Puerto Rico.\n ', type='inf'))), }) self._test_queries('clueweb09/catb/trec-web-2011', count=50, items={ 0: TrecWebTrackQuery('101', 'ritz carlton lake las vegas', '\n Find information about the Ritz Carlton resort at Lake Las Vegas.\n ', 'faceted', (TrecSubtopic(number='1', text='\n Find information about the Ritz Carlton resort at Lake Las Vegas.\n ', type='inf'), TrecSubtopic(number='2', text='\n Find a site where I can determine room price and availability.\n ', type='nav'), TrecSubtopic(number='3', text='\n Find directions to the Ritz Carlton Lake Las Vegas.\n ', type='nav'), TrecSubtopic(number='4', text='\n Find reviews of the Ritz Carlton Lake Las Vegas.\n ', type='inf'))), 9: TrecWebTrackQuery('110', 'map of brazil', '\n What are the boundaries of the political jurisdictions in Brazil?\n ', 'ambiguous', (TrecSubtopic(number='1', text='\n What are the boundaries of the political jurisdictions in Brazil?\n ', type='inf'), TrecSubtopic(number='2', text='\n I am looking for information about taking a vacation trip to Brazil.\n ', type='inf'), TrecSubtopic(number='3', text='\n I want to buy a road map of Brazil.\n ', type='nav'))), 49: TrecWebTrackQuery('150', 'tn highway patrol', '\n What are the requirements to become a Tennessee Highway Patrol State Trooper?\n ', 'faceted', (TrecSubtopic(number='1', text='\n What are the requirements to become a Tennessee Highway Patrol State Trooper?\n ', type='inf'), TrecSubtopic(number='2', text='\n information about the responsibilities of the Tennessee Highway Patrol\n ', type='inf'), TrecSubtopic(number='3', text='\n home page of the Tennessee Highway Patrol\n ', type='nav'), TrecSubtopic(number='4', text='\n I want to fill in the customer satisfaction survey about my interaction with a Tennessee Highway Patrol State Trooper.\n ', type='nav'))), }) self._test_queries('clueweb09/catb/trec-web-2012', count=50, items={ 0: TrecWebTrackQuery('151', '403b', '\n What is a 403b plan?\n ', 'faceted', (TrecSubtopic(number='1', text='\n What is a 403b plan?\n ', type='inf'), TrecSubtopic(number='2', text='\n Who is eligible for a 403b plan?\n ', type='inf'), TrecSubtopic(number='3', text='\n What are the rules for a 403b retirement plan?\n ', type='nav'), TrecSubtopic(number='4', text='\n What is the difference between 401k and 403b retirement plans?\n ', type='inf'), TrecSubtopic(number='5', text='\n What are the withdrawal limitations for a 403b retirement plan?\n ', type='nav'))), 9: TrecWebTrackQuery('160', 'grilling', '\n Find kabob recipes.\n ', 'ambiguous', (TrecSubtopic(number='1', text='\n Find kabob recipes.\n ', type='nav'), TrecSubtopic(number='2', text='\n Find tips on grilling vegetables.\n ', type='inf'), TrecSubtopic(number='3', text='\n Find tips on grilling fish.\n ', type='inf'), TrecSubtopic(number='4', text='\n Find instructions for grilling chicken.\n ', type='inf'), TrecSubtopic(number='5', text='\n Find the Grilling Magazine website.\n ', type='nav'), TrecSubtopic(number='6', text='\n Find information on gas barbecue grills and cooking on a gas grill.\n ', type='inf'))), 49: TrecWebTrackQuery('200', 'ontario california airport', '\n Find flight information for the Ontario, CA airport.\n ', 'faceted', (TrecSubtopic(number='1', text='\n Find flight information for the Ontario, CA airport.\n ', type='inf'), TrecSubtopic(number='2', text='\n What hotels are near the Ontario, CA airport?\n ', type='inf'), TrecSubtopic(number='3', text='\n What services/facilities does the Ontario, CA airport offer?\n ', type='inf'), TrecSubtopic(number='4', text='\n What is the address of the Ontario, CA airport?\n ', type='nav'))), }) self._test_queries('clueweb09/trec-mq-2009', count=40000, items={ 0: GenericQuery('20001', '1:obama family tree'), 9: GenericQuery('20010', '1:cheap internet'), 39999: GenericQuery('60000', '4:bird shingles'), }) def test_clueweb09_qrels(self): self._test_qrels('clueweb09/en/trec-web-2009', count=23601, items={ 0: TrecPrel('1', 'clueweb09-en0003-55-31884', 0, 0, 1.0), 9: TrecPrel('1', 'clueweb09-en0009-84-37392', 0, 1, 0.0136322534877696), 23600: TrecPrel('50', 'clueweb09-en0007-05-20194', 0, 1, 1.0), }) self._test_qrels('clueweb09/en/trec-web-2010', count=25329, items={ 0: TrecQrel('51', 'clueweb09-en0000-16-19379', 0, '0'), 9: TrecQrel('51', 'clueweb09-en0001-55-24197', 0, '0'), 25328: TrecQrel('99', 'clueweb09-enwp03-23-18429', 0, '0'), }) self._test_qrels('clueweb09/en/trec-web-2011', count=19381, items={ 0: TrecQrel('101', 'clueweb09-en0007-71-07471', 0, '0'), 9: TrecQrel('101', 'clueweb09-en0044-05-29808', 2, '0'), 19380: TrecQrel('150', 'clueweb09-en0003-86-25593', -2, '0'), }) self._test_qrels('clueweb09/en/trec-web-2012', count=16055, items={ 0: TrecQrel('151', 'clueweb09-en0000-00-03430', -2, '0'), 9: TrecQrel('151', 'clueweb09-en0000-00-04023', -2, '0'), 16054: TrecQrel('200', 'clueweb09-enwp03-49-00268', 0, '0'), }) self._test_qrels('clueweb09/catb/trec-web-2009', count=13118, items={ 0: TrecPrel('1', 'clueweb09-en0003-55-31884', 0, 0, 1.0), 9: TrecPrel('1', 'clueweb09-enwp01-17-09993', 2, 1, 1.0), 13117: TrecPrel('50', 'clueweb09-en0007-05-20194', 0, 1, 1.0), }) self._test_qrels('clueweb09/catb/trec-web-2010', count=15845, items={ 0: TrecQrel('51', 'clueweb09-en0000-16-19379', 0, '0'), 9: TrecQrel('51', 'clueweb09-en0001-55-24197', 0, '0'), 15844: TrecQrel('99', 'clueweb09-enwp03-23-18429', 0, '0'), }) self._test_qrels('clueweb09/catb/trec-web-2011', count=13081, items={ 0: TrecQrel('101', 'clueweb09-en0007-71-07471', 0, '0'), 9: TrecQrel('101', 'clueweb09-en0001-12-16652', 0, '0'), 13080: TrecQrel('150', 'clueweb09-en0003-86-25593', -2, '0'), }) self._test_qrels('clueweb09/catb/trec-web-2012', count=10022, items={ 0: TrecQrel('151', 'clueweb09-en0000-00-03430', -2, '0'), 9: TrecQrel('151', 'clueweb09-en0000-00-04023', -2, '0'), 10021: TrecQrel('200', 'clueweb09-enwp03-49-00268', 0, '0'), }) self._test_qrels('clueweb09/trec-mq-2009', count=34534, items={ 0: TrecPrel('20001', 'clueweb09-en0003-55-31884', 0, 0, 1.0), 9: TrecPrel('20001', 'clueweb09-enwp01-17-09993', 2, 1, 1.0), 34533: TrecPrel('57118', 'clueweb09-en0010-39-07801', 0, 1, 0.0612006151868131), }) if __name__ == '__main__': unittest.main()

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py

Python

tools/grammar-analysis/ANTLRv4ParserListener.py

sanyaade-teachings/spresensedroplet

8dffe6d07a744288870aa5f37a179aa5db22f8d2

[ "MIT" ]

3

2017-05-19T15:07:19.000Z

2018-10-25T12:29:27.000Z

tools/grammar-analysis/ANTLRv4ParserListener.py

sanyaade-teachings/spresensedroplet

8dffe6d07a744288870aa5f37a179aa5db22f8d2

[ "MIT" ]

1

2018-08-30T19:37:37.000Z

tools/grammar-analysis/ANTLRv4ParserListener.py

sanyaade-teachings/spresensedroplet

8dffe6d07a744288870aa5f37a179aa5db22f8d2

[ "MIT" ]

7

2017-04-07T14:11:01.000Z

2021-11-11T19:32:01.000Z

# Generated from java-escape by ANTLR 4.5 from antlr4 import * # This class defines a complete listener for a parse tree produced by ANTLRv4Parser. class ANTLRv4ParserListener(ParseTreeListener): # Enter a parse tree produced by ANTLRv4Parser#grammarSpec. def enterGrammarSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#grammarSpec. def exitGrammarSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#grammarType. def enterGrammarType(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#grammarType. def exitGrammarType(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#prequelConstruct. def enterPrequelConstruct(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#prequelConstruct. def exitPrequelConstruct(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#optionsSpec. def enterOptionsSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#optionsSpec. def exitOptionsSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#option. def enterOption(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#option. def exitOption(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#optionValue. def enterOptionValue(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#optionValue. def exitOptionValue(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#delegateGrammars. def enterDelegateGrammars(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#delegateGrammars. def exitDelegateGrammars(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#delegateGrammar. def enterDelegateGrammar(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#delegateGrammar. def exitDelegateGrammar(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#tokensSpec. def enterTokensSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#tokensSpec. def exitTokensSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#channelsSpec. def enterChannelsSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#channelsSpec. def exitChannelsSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#idList. def enterIdList(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#idList. def exitIdList(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#action. def enterAction(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#action. def exitAction(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#actionScopeName. def enterActionScopeName(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#actionScopeName. def exitActionScopeName(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#actionBlock. def enterActionBlock(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#actionBlock. def exitActionBlock(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#argActionBlock. def enterArgActionBlock(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#argActionBlock. def exitArgActionBlock(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#modeSpec. def enterModeSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#modeSpec. def exitModeSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#rules. def enterRules(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#rules. def exitRules(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ruleSpec. def enterRuleSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ruleSpec. def exitRuleSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#parserRuleSpec. def enterParserRuleSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#parserRuleSpec. def exitParserRuleSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#exceptionGroup. def enterExceptionGroup(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#exceptionGroup. def exitExceptionGroup(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#exceptionHandler. def enterExceptionHandler(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#exceptionHandler. def exitExceptionHandler(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#finallyClause. def enterFinallyClause(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#finallyClause. def exitFinallyClause(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#rulePrequel. def enterRulePrequel(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#rulePrequel. def exitRulePrequel(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ruleReturns. def enterRuleReturns(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ruleReturns. def exitRuleReturns(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#throwsSpec. def enterThrowsSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#throwsSpec. def exitThrowsSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#localsSpec. def enterLocalsSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#localsSpec. def exitLocalsSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ruleAction. def enterRuleAction(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ruleAction. def exitRuleAction(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ruleModifiers. def enterRuleModifiers(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ruleModifiers. def exitRuleModifiers(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ruleModifier. def enterRuleModifier(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ruleModifier. def exitRuleModifier(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ruleBlock. def enterRuleBlock(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ruleBlock. def exitRuleBlock(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ruleAltList. def enterRuleAltList(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ruleAltList. def exitRuleAltList(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#labeledAlt. def enterLabeledAlt(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#labeledAlt. def exitLabeledAlt(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerRuleSpec. def enterLexerRuleSpec(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerRuleSpec. def exitLexerRuleSpec(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerRuleBlock. def enterLexerRuleBlock(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerRuleBlock. def exitLexerRuleBlock(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerAltList. def enterLexerAltList(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerAltList. def exitLexerAltList(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerAlt. def enterLexerAlt(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerAlt. def exitLexerAlt(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerElements. def enterLexerElements(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerElements. def exitLexerElements(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerElement. def enterLexerElement(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerElement. def exitLexerElement(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#labeledLexerElement. def enterLabeledLexerElement(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#labeledLexerElement. def exitLabeledLexerElement(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerBlock. def enterLexerBlock(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerBlock. def exitLexerBlock(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerCommands. def enterLexerCommands(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerCommands. def exitLexerCommands(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerCommand. def enterLexerCommand(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerCommand. def exitLexerCommand(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerCommandName. def enterLexerCommandName(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerCommandName. def exitLexerCommandName(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerCommandExpr. def enterLexerCommandExpr(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerCommandExpr. def exitLexerCommandExpr(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#altList. def enterAltList(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#altList. def exitAltList(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#alternative. def enterAlternative(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#alternative. def exitAlternative(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#element. def enterElement(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#element. def exitElement(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#labeledElement. def enterLabeledElement(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#labeledElement. def exitLabeledElement(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ebnf. def enterEbnf(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ebnf. def exitEbnf(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#blockSuffix. def enterBlockSuffix(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#blockSuffix. def exitBlockSuffix(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ebnfSuffix. def enterEbnfSuffix(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ebnfSuffix. def exitEbnfSuffix(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#lexerAtom. def enterLexerAtom(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#lexerAtom. def exitLexerAtom(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#atom. def enterAtom(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#atom. def exitAtom(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#notSet. def enterNotSet(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#notSet. def exitNotSet(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#blockSet. def enterBlockSet(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#blockSet. def exitBlockSet(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#setElement. def enterSetElement(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#setElement. def exitSetElement(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#block. def enterBlock(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#block. def exitBlock(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#ruleref. def enterRuleref(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#ruleref. def exitRuleref(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#characterRange. def enterCharacterRange(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#characterRange. def exitCharacterRange(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#terminal. def enterTerminal(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#terminal. def exitTerminal(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#elementOptions. def enterElementOptions(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#elementOptions. def exitElementOptions(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#elementOption. def enterElementOption(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#elementOption. def exitElementOption(self, ctx): pass # Enter a parse tree produced by ANTLRv4Parser#identifier. def enterIdentifier(self, ctx): pass # Exit a parse tree produced by ANTLRv4Parser#identifier. def exitIdentifier(self, ctx): pass

25.430314

84

0.682332

1,665

14,597

5.981982

0.130931

0.076506

0.12751

0.229518

0.791466

0.788153

0.787651

0.608635

0

0.012073

0.256628

14,597

573

85

25.474695

0.905815

0.495102

0

0.496063

1

0

1

0.496063

false

0.496063

0.003937

0

0.503937

0

null

0

1

0

1

0

1

0

1

0

null

0

1

0

1

0

1

0

9

6528feece33b346f134e6548f2dfdcb52c7e65c1

96

py

Python

ven2/lib/python2.7/site-packages/zope/deferredimport/samples/sample6.py

manliu1225/Facebook_crawler

0f75a1c4382dd4effc3178d84b99b0cad97337cd

[ "Apache-2.0" ]

4

2021-02-20T06:00:01.000Z

2022-01-07T20:37:37.000Z

ven2/lib/python2.7/site-packages/zope/deferredimport/samples/sample6.py

manliu1225/Facebook_crawler

0f75a1c4382dd4effc3178d84b99b0cad97337cd

[ "Apache-2.0" ]

2

2020-04-30T13:03:09.000Z

2021-05-05T10:20:15.000Z

ven2/lib/python2.7/site-packages/zope/deferredimport/samples/sample6.py

manliu1225/Facebook_crawler

0f75a1c4382dd4effc3178d84b99b0cad97337cd

[ "Apache-2.0" ]

5

2020-05-07T08:14:36.000Z

2022-03-24T15:15:08.000Z

import zope.deferredimport.sample5 def getone(): return zope.deferredimport.sample5.one

12

42

0.770833

11

96

6.727273

0.727273

0.486486

0.675676

0

0.02439

0.145833

96

7

43

13.714286

0.878049

0

1

0.333333

true

0

0.666667

0.333333

1.333333

0

1

0

null

1

0

1

0

null

0

1

0

1

0

9

3345b0eac5cc00a5018ad53d35a6980e4d23e0dc

100

py

Python

Lab_6/Lab6_054/4.2.2.py

Saif-M-Dhrubo/Crypto-Lab

2807320d7ca389adee86f69f704b9f91f9cd8054

[ "MIT" ]

2

2019-04-28T16:34:15.000Z

2019-04-28T17:54:06.000Z

Lab_6/Lab6_054/4.2.2.py

saif-mahmud/Crypto-Lab

2807320d7ca389adee86f69f704b9f91f9cd8054

[ "MIT" ]

null

Lab_6/Lab6_054/4.2.2.py

saif-mahmud/Crypto-Lab

2807320d7ca389adee86f69f704b9f91f9cd8054

[ "MIT" ]

1

2020-01-08T06:48:08.000Z

from struct import pack print pack("<IIIII",0xaabbccdd,0x00000000,0x00000000,0xbffe9a98,0x08048efe)

33.333333

75

0.84

12

100

7

0.833333

0

0.308511

0.06

100

2

76

50

0.585106

0

0.06

0

0.5

0

null

0

0.5

null

0.5

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

1

0

7

6824e70dad17ca462b2d50be808db2eea796cf38

14,237

py

Python

opponents/hermione/make_hermione_images.py

screenusername/spni

50243958299483dd9fab3d5970ad219e367cb426

[ "MIT" ]

null

opponents/hermione/make_hermione_images.py

screenusername/spni

50243958299483dd9fab3d5970ad219e367cb426

[ "MIT" ]

null

opponents/hermione/make_hermione_images.py

screenusername/spni

50243958299483dd9fab3d5970ad219e367cb426

[ "MIT" ]

null

import sys #emotions: #happy #calm #sad #loss #interested - clasping hands together? #horny #shocked - maybe hands in front of face, with a gap in between her fingers to see through? #excited #stunned - eyes closed, I think. #angry #clothes = shoes, socks, jumper, tie, skirt, shirt, bra, panties #11 total stages #appearance:36**aa12.42.0.42.54.12.42.0.4.70_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.65.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha75.75_hb49.1.44.99_hc0.59.39.0.59.39_hd1.1.49.49_ia_if0.59.59.0.1.5.0.0.5.0.0.0.0.3_ib0.55.55.0.0.0.0.1.5.0.0.5.0.0.2_id_ic34.60.60.18191E.0_jc_ie_ja9.2C2E31.070809.55_jb9.2C2E31.070809.55_jd7.60.50.50_je7.60.50.50_jf_jg_ka6.55.55.E8E8E8.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of4.6.44.6.0_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj_ad0.0.0.0.0.0.0.0.0.0 version_str = "36**" def get_emotion_data(): emotions = dict() #happy em = dict() em["pose"] = "aa12.42.0.42.54.12.42.0.4.70_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.65.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha75.75_hb49.1.44.99_hc0.59.39.0.59.39_hd1.1.49.49" em["blush_mod"] = 0 emotions["happy"] = em #calm em = dict() em["pose"] = "aa11.98.0.42.54.11.98.0.4.70_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.65.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha70.70_hb49.1.44.99_hc0.65.39.0.65.39_hd0.1.49.49" em["blush_mod"] = 0 emotions["calm"] = em #sad em = dict() em["pose"] = "aa13.97.0.42.54.13.97.0.4.70_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa3.50.50.60.50.74.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha59.59_hb49.1.20.99_hc0.61.39.0.61.39_hd8.1.49.49" em["blush_mod"] = 0 emotions["sad"] = em #loss em = dict() em["pose"] = "aa11.89.1.42.54.11.89.1.4.70_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.86.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha61.61_hb49.1.3.99_hc0.65.39.0.65.39_hd21.1.49.49" em["blush_mod"] = 0 emotions["loss"] = em #interested em = dict() em["pose"] = "aa26.63.0.16.58.24.63.1.0.64_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa5.50.50.60.50.0.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha84.84_hb49.1.44.99_hc0.39.39.0.39.39_hd1.1.49.49" em["blush_mod"] = 1 emotions["interested"] = em #horny em = dict() em["pose"] = "aa10.58.0.42.75.10.58.0.4.75_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.65.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha87.87_hb49.1.44.99_hc0.59.39.0.59.39_hd27.1.49.49" em["blush_mod"] = 2 emotions["horny"] = em #shocked em = dict() em["pose"] = "aa65.38.1.27.41.75.36.1.4.60_ab_ac2.52.52.52_ba50_bb17.1_bc185.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.79.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha88.88_hb49.1.44.99_hc0.59.39.0.59.39_hd41.1.49.49" em["blush_mod"] = 1 emotions["shocked"] = em #excited em = dict() em["pose"] = "aa7.44.0.43.54.7.44.0.6.43_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.99.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha96.96_hb49.1.44.99_hc0.41.39.0.41.39_hd34.1.49.49" em["blush_mod"] = 2 emotions["excited"] = em #stunned em = dict() em["pose"] = "aa8.100.1.0.54.8.100.1.6.30_ab_ac2.52.52.52_ba50_bb17.1_bc185.500.8.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.59.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha73.73_hb49.1.44.45_hc0.0.39.0.0.39_hd40.1.49.49" em["blush_mod"] = 1 emotions["stunned"] = em #angry em = dict() em["pose"] = "aa22.83.1.16.42.22.83.1.4.52_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.8.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa6.50.50.60.50.31.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha77.77_hb49.1.44.99_hc0.0.39.0.0.39_hd38.1.49.49" em["blush_mod"] = 0 emotions["angry"] = em #smug em = dict() em["pose"] = "aa20.72.0.42.49.20.72.0.4.49_ab_ac2.52.52.52_ba50_bb18.1_bc150.500.0.0.1_bd18_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd9.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc0.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.38.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha63.63_hb49.1.44.99_hc0.35.39.0.35.39_hd2.1.49.49" em["blush_mod"] = 0 emotions["smug"] = em return emotions def get_image_data(): d = dict() d["appearance"] = "36**aa12.42.0.42.54.12.42.0.4.70_ab_ac2.52.52.52_ba50_bb17.1_bc150.500.0.0.1_bd17_be180_ca61.0.40.61.14.8.34.0.9_cb0_da1.0.0.100_db_dd0.0.34.50.45_dh1.30.50.50.0_di4_qa_qb_dc40.1.1.1.1_ea26.A27241.A27241.56.0.0_ec10.0.A27241.A27241.56_ed28.50.1.1.A27241.56_ef_eg_eh4.A27241_r0_fa2.50.50.60.50.65.56_fb10_fc0.9.55.0.9.55.50.61.61_fd1.0.19.A27241.56_fe58.61_ff0000000000_fg0.50_t0_pa0.0.0.0.40.50.85.85.0.0_pb_pc_pd_pe_ga0_gb1_gc0.0_ge0000000000_gh_gf_gg_gd10000000_ha75.75_hb49.1.44.99_hc0.59.39.0.59.39_hd1.1.49.49_ia_if0.59.59.0.1.5.0.0.5.0.0.0.0.3_ib0.55.55.0.0.0.0.1.5.0.0.5.0.0.2_id_ic34.60.60.18191E.0_jc_ie_ja9.2C2E31.070809.55_jb9.2C2E31.070809.55_jd7.60.50.50_je7.60.50.50_jf_jg_ka6.55.55.E8E8E8.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of4.6.44.6.0_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj_ad0.0.0.0.0.0.0.0.0.0" #these are separated out because parts of the descriptions change according to blush and love juice levels d["vagina"] = "dc40.1.1.1.1" #dc component d["face"] = "dd0.0.34.50.45" #dd component stages = list() #lj = love juices #fully clothed s = {} s["blush"] = 0 s["lj"] = 0 s["clothes"] = "ia_if0.59.59.0.1.5.0.0.5.0.0.0.0.3_ib0.55.55.0.0.0.0.1.5.0.0.5.0.0.2_id_ic34.60.60.18191E.0_jc_ie_ja9.2C2E31.070809.55_jb9.2C2E31.070809.55_jd7.60.50.50_je7.60.50.50_jf_jg_ka6.55.55.B71740.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of4.6.44.6.0_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj" s["other"] = "" stages.append(s) #lost shoes s = {} s["blush"] = 0 s["lj"] = 0 s["clothes"] = "ia_if0.59.59.0.1.5.0.0.5.0.0.0.0.3_ib0.55.55.0.0.0.0.1.5.0.0.5.0.0.2_id_ic34.60.60.18191E.0_jc_ie_ja9.2C2E31.070809.55_jb9.2C2E31.070809.55_jd_je_jf_jg_ka6.55.55.B71740.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of4.6.44.6.0_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj" s["other"] = "" stages.append(s) #lost socks s = {} s["blush"] = 0 s["lj"] = 0 s["clothes"] = "ia_if0.59.59.0.1.5.0.0.5.0.0.0.0.3_ib0.55.55.0.0.0.0.1.5.0.0.5.0.0.2_id_ic34.60.60.18191E.0_jc_ie_ja_jb_jd_je_jf_jg_ka6.55.55.B71740.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of4.6.44.6.0_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj" s["other"] = "" stages.append(s) #lost jumper s = {} s["blush"] = 0 s["lj"] = 0 s["clothes"] = "ia_if_ib0.55.55.0.0.0.0.1.5.0.0.5.0.0.2_id_ic34.60.60.18191E.0_jc_ie_ja_jb_jd_je_jf_jg_ka6.55.55.B71740.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of4.6.44.6.0_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj" s["other"] = "" stages.append(s) #lost tie s = {} s["blush"] = 0 s["lj"] = 0 s["clothes"] = "ia_if_ib0.55.55.0.0.0.0.1.5.0.0.5.0.0.2_id_ic34.60.60.18191E.0_jc_ie_ja_jb_jd_je_jf_jg_ka6.55.55.B71740.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj" s["other"] = "" stages.append(s) #lost skirt s = {} s["blush"] = 1 s["lj"] = 0 s["clothes"] = "ia_if_ib0.55.55.0.0.0.0.1.5.0.0.5.0.0.2_id_ic_jc_ie_ja_jb_jd_je_jf_jg_ka6.55.55.B71740.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj" s["other"] = "" stages.append(s) #lost blouse s = {} s["blush"] = 1 s["lj"] = 0 s["clothes"] = "ia_if_ib_id_ic_jc_ie_ja_jb_jd_je_jf_jg_ka6.55.55.B71740.0_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj" s["other"] = "" stages.append(s) #lost bra s = {} s["blush"] = 2 s["lj"] = 0 s["clothes"] = "ia_if_ib_id_ic_jc_ie_ja_jb_jd_je_jf_jg_ka_kb6.55.55.B71740_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj" s["other"] = "" stages.append(s) #lost panties/nude s = {} s["blush"] = 2 s["lj"] = 5 s["clothes"] = "ia_if_ib_id_ic_jc_ie_ja_jb_jd_je_jf_jg_ka_kb_kc_kd_ke_kf_la_lb_oa_os_ob_oc_od_oe_of_lc_m0_n0_s0_og_oh_oo_op_oq_or_om_on_ok_ol_oi_oj_ad0.0.0.0.0.0.0.0.0.0" s["other"] = "" stages.append(s) #masturbating s = {} s["blush"] = 4 s["lj"] = 80 s["clothes"] = stages[-1]["clothes"] s["other"] = "" stages.append(s) #finished s = {} s["blush"] = 3 s["lj"] = 140 s["clothes"] = stages[-1]["clothes"] s["other"] = "" stages.append(s) d["stages"] = stages blush = list() blush.append(( 0, 9)) #0 no blush blush.append((14, 9)) #1 lost dress blush.append((27, 0)) #2 lost bra blush.append((50, 1)) #3 nude & finished blush.append((60, 10)) #4 masturbating blush.append((70, 12)) #5 stage + emotion mod blush.append((80, 14)) #6 d["blush"] = blush return d def make_descriptions(pd, ems, out_filename): #pd = player data #ems = emotion data #get complete vagina description string def get_v_str(desc, lj): #desc = vagina description string, lj = love juice level a, b = desc.split(".", 1) return "dc" + ("%d." % lj) + b #get blush/blue face desciption string def get_b_str(blush, blue): return "gc%d.%d" % (blush, blue) #get complete face description string def get_face_str(desc, sticker_type): a, b = desc.split(".", 1) return "dd" + ("%d." % sticker_type) + b with open(out_filename, "w") as f: #put special setup code here for ind, stage in enumerate(pd["stages"]): if ind == len(pd["stages"]) - 2: #skip the masturbation stage, all of those are custom images #continue pass stage_desc = version_str + stage["clothes"] # + pd["appearance"] + "_" if "other" in stage and len(stage["other"]) > 0: stage_desc += "_" + stage["other"] for em_name, em in ems.iteritems(): blush_ind = stage["blush"] + em["blush_mod"] if blush_ind < 0: blush_ind = 0 if blush_ind >= len(pd["blush"]): blush_ind = len(pd["blush"]) - 1 blush = pd["blush"][blush_ind] em_desc = stage_desc + "_" + em["pose"] em_desc += "_" + get_b_str(blush[0], 0) #put in the strings that need to be replaced last, so that they don't get overwritten em_desc += "_" + get_face_str(pd["face"], blush[1]) em_desc += "_" + get_v_str(pd["vagina"], stage["lj"]) image_name = "%d-%s" % (ind, em_name) f.write("%s=%s\n\n" % (image_name, em_desc)) def write_descriptions(out_name): character_data = get_image_data() emotion_data = get_emotion_data() make_descriptions(character_data, emotion_data, out_name) if __name__ == "__main__": write_descriptions(sys.argv[1])

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Python

test/test_msa.py

davidhwyllie/findNeighbour4

d42e10711e59e93ebf0e798fbb1598929f662c9c

[ "MIT" ]

null

test/test_msa.py

davidhwyllie/findNeighbour4

d42e10711e59e93ebf0e798fbb1598929f662c9c

[ "MIT" ]

14

2021-11-26T14:43:25.000Z

2022-03-22T00:39:17.000Z

test/test_msa.py

davidhwyllie/findNeighbour4

d42e10711e59e93ebf0e798fbb1598929f662c9c

[ "MIT" ]

null

""" tests msa.py A component of the findNeighbour4 system for bacterial relatedness monitoring Copyright (C) 2021 David Wyllie david.wyllie@phe.gov.uk repo: https://github.com/davidhwyllie/findNeighbour4 This program is free software: you can redistribute it and/or modify it under the terms of the MIT License as published by the Free Software Foundation. See <https://opensource.org/licenses/MIT>, and the LICENSE file. """ import os import unittest import time import pandas as pd from findn.msa import MSAResult, MSAStore from findn.persistence import Persistence # unittests UNITTEST_MONGOCONN: str = "mongodb://localhost" UNITTEST_RDBMSCONN: str = "sqlite://" class Test_MSA(unittest.TestCase): """tests the MSAResult class""" def runTest(self): inputdict = { "fconst": {}, "variant_positions": [0, 1, 2, 3], "invalid_guids": [], "valid_guids": [ "AAACGY-1", "CCCCGY-2", "TTTCGY-3", "GGGGGY-4", "NNNCGY-5", "ACTCGY-6", "TCTQGY-7", "AAACGY-8", ], "expected_p1": 0.16666666666666666, "sample_size": 30, "df_dict": { "AAACGY-1": { "aligned_seq": "AAAC", "aligned_mseq": "AAAC", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 1, "alignM": 0, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, "CCCCGY-2": { "aligned_seq": "CCCC", "aligned_mseq": "CCCC", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 1, "alignM": 0, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, }, "what_tested": "M", "outgroup": None, "creation_time": "2019-11-17T23:46:00.098151", } m = MSAResult(**inputdict) self.assertEqual(type(m.msa_fasta()), str) self.assertEqual(type(m.msa_html()), str) self.assertEqual(type(m.msa_dict()), dict) self.assertEqual(type(m.serialise()), dict) self.assertEqual(type(m.msa_interactive_depiction()), str) self.assertEqual(type(m.df), pd.DataFrame) self.assertEqual( m.token, "msa|M|no_og|ddc4781ec984b66b0b5bf006a71b29cf1f523740" ) # skip these tests if the NO_MONGO_TESTS variable exists mongo_test = unittest.skipIf( os.environ.get("NO_MONGO_TESTS", False), "no mongo tests performed" ) @mongo_test class Test_MSAStore_mongodb(unittest.TestCase): """tests the MSAStore class""" def runTest(self): inputdict1 = { "fconst": {}, "variant_positions": [0, 1, 2, 3], "invalid_guids": [], "valid_guids": ["AAACGY-1", "CCCCGY-2"], "expected_p1": 0.16666666666666666, "sample_size": 30, "df_dict": { "AAACGY-1": { "aligned_seq": "AAMM", "aligned_mseq": "AAYR", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 3, "alignM": 2, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, "CCCCGY-2": { "aligned_seq": "CCCC", "aligned_mseq": "CCCC", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 1, "alignM": 0, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, }, "what_tested": "M", "outgroup": None, "creation_time": "2019-11-17T23:46:00.098151", } inputdict2 = { "fconst": {}, "variant_positions": [0, 1, 2, 3], "invalid_guids": [], "valid_guids": ["AAACGY-1", "CCCCGY-2"], "expected_p1": 0.16666666666666666, "sample_size": 30, "df_dict": { "AAACGY-1": { "aligned_seq": "AAAM", "aligned_mseq": "AAAR", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 1, "alignM": 1, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, "CCCCGY-2": { "aligned_seq": "CCCC", "aligned_mseq": "CCCC", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 1, "alignM": 0, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, }, "what_tested": "M", "outgroup": None, "creation_time": "2019-11-17T23:46:00.098151", } m1 = MSAResult(**inputdict1) m2 = MSAResult(**inputdict2) guids1 = m1.valid_guids guids2 = m2.valid_guids pm = Persistence() p = pm.get_storage_object(connString=UNITTEST_MONGOCONN, debug=2, verbose=True) ms = MSAStore(p, in_ram_persistence_time=1) t1 = ms.get_token("M", False, guids1) t2 = ms.get_token("M", False, guids2) self.assertFalse(ms.is_in_ram(t1)) self.assertFalse(ms.is_in_ram(t2)) ms.cache_in_ram(token=t1, msa_result=m1) ms.cache_in_ram(token=t2, msa_result=m2) self.assertTrue(ms.is_in_ram(t1)) self.assertTrue(ms.is_in_ram(t2)) # test purging of expired samples time.sleep(2) ms.purge_ram() self.assertFalse(ms.is_in_ram(t1)) self.assertFalse(ms.is_in_ram(t2)) # store on disc ms.persist(t1, m1) ms.persist(t2, m2) m1r = ms.load(t1) m2r = ms.load(t2) self.assertEqual(m1r.valid_guids, m1.valid_guids) self.assertEqual(m2r.valid_guids, m2.valid_guids) ms.unpersist([]) m1r = ms.load(t1) m2r = ms.load(t2) self.assertIsNone(m1r) self.assertIsNone(m2r) rdbms_test = unittest.skipIf(os.environ.get("NO_RDBMS_TESTS", False), "No rdbms tests") @rdbms_test class Test_MSAStore_rdbms(unittest.TestCase): """tests the MSAStore class""" def runTest(self): inputdict1 = { "fconst": {}, "variant_positions": [0, 1, 2, 3], "invalid_guids": [], "valid_guids": ["AAACGY-1", "CCCCGY-2"], "expected_p1": 0.16666666666666666, "sample_size": 30, "df_dict": { "AAACGY-1": { "aligned_seq": "AAMM", "aligned_mseq": "AAYR", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 3, "alignM": 2, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, "CCCCGY-2": { "aligned_seq": "CCCC", "aligned_mseq": "CCCC", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 1, "alignM": 0, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, }, "what_tested": "M", "outgroup": None, "creation_time": "2019-11-17T23:46:00.098151", } inputdict2 = { "fconst": {}, "variant_positions": [0, 1, 2, 3], "invalid_guids": [], "valid_guids": ["AAACGY-1", "CCCCGY-2"], "expected_p1": 0.16666666666666666, "sample_size": 30, "df_dict": { "AAACGY-1": { "aligned_seq": "AAAM", "aligned_mseq": "AAAR", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 1, "alignM": 1, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, "CCCCGY-2": { "aligned_seq": "CCCC", "aligned_mseq": "CCCC", "aligned_seq_len": 4, "allN": 0, "alignN": 0, "allM": 1, "alignM": 0, "allN_or_M": 1, "alignN_or_M": 0, "p_value1": 1.0, "p_value2": 1.0, "p_value3": 1.0, "p_value4": 1.0, "observed_proportion": 0.0, "expected_proportion1": 0.16666666666666666, "expected_proportion2": 0.5, "expected_proportion3": 0.5, "expected_proportion4": 0.0, "what_tested": "M", }, }, "what_tested": "M", "outgroup": None, "creation_time": "2019-11-17T23:46:00.098151", } m1 = MSAResult(**inputdict1) m2 = MSAResult(**inputdict2) guids1 = m1.valid_guids guids2 = m2.valid_guids pm = Persistence() p = pm.get_storage_object(connString=UNITTEST_RDBMSCONN, debug=2, verbose=True) ms = MSAStore(p, in_ram_persistence_time=1) t1 = ms.get_token("M", False, guids1) t2 = ms.get_token("M", False, guids2) self.assertFalse(ms.is_in_ram(t1)) self.assertFalse(ms.is_in_ram(t2)) ms.cache_in_ram(token=t1, msa_result=m1) ms.cache_in_ram(token=t2, msa_result=m2) self.assertTrue(ms.is_in_ram(t1)) self.assertTrue(ms.is_in_ram(t2)) # test purging of expired samples time.sleep(2) ms.purge_ram() self.assertFalse(ms.is_in_ram(t1)) self.assertFalse(ms.is_in_ram(t2)) # store on disc ms.persist(t1, m1) ms.persist(t2, m2) m1r = ms.load(t1) m2r = ms.load(t2) self.assertEqual(m1r.valid_guids, m1.valid_guids) self.assertEqual(m2r.valid_guids, m2.valid_guids) ms.unpersist([]) m1r = ms.load(t1) m2r = ms.load(t2) self.assertIsNone(m1r) self.assertIsNone(m2r)

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0

7

68b598e17f3073ae1e3a74adc7d1c10e5845f58c

152

py

Python

jekyllutils/helpers/messages.py

queirozfcom/jekyll-utils

461b90ac11ea313a5506841dd14c024d544769d1

[ "MIT" ]

3

2016-11-23T21:00:58.000Z

2019-11-10T20:01:49.000Z

jekyllutils/helpers/messages.py

queirozfcom/jekyll-utils

461b90ac11ea313a5506841dd14c024d544769d1

[ "MIT" ]

9

2016-02-16T17:20:06.000Z

2020-06-20T19:06:32.000Z

jekyllutils/helpers/messages.py

queirozfcom/jekyll-utils

461b90ac11ea313a5506841dd14c024d544769d1

[ "MIT" ]

null

def wrap_error(msg): return "\033[31mERROR: \033[00m{0}".format(msg) def wrap_success(msg): return "\033[32mSUCCESS: \033[00m{0}".format(msg)

21.714286

53

0.671053

24

152

4.166667

0.5

0.14

0.24

0.26

0.32

0

0.166667

0.131579

152

6

54

25.333333

0.590909

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0.355263

0

1

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false

0

0.5

1

0

1

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null

0

1

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1

0

null

0

1

0

1

0

7

d7ad1309d340529b0c9b2c4ab6ccf2906053d06e

9,239

py

Python

agents/callback.py

mmcenta/left-shift

e9b89b29accc5faa6e41ce604df5c70ddd631ed1

[ "MIT" ]

39

2020-03-26T17:46:02.000Z

2022-01-07T15:39:31.000Z

agents/callback.py

mmcenta/left-shift

e9b89b29accc5faa6e41ce604df5c70ddd631ed1

[ "MIT" ]

8

2020-03-25T19:40:03.000Z

2022-02-10T00:44:45.000Z

agents/callback.py

mmcenta/left-shift

e9b89b29accc5faa6e41ce604df5c70ddd631ed1

[ "MIT" ]

4

2020-03-26T18:14:34.000Z

2022-01-07T15:39:33.000Z

# unusable until we find how to access states within _on_step() from stable_baselines.common.callbacks import BaseCallback import numpy as np import os class CustomCallback(BaseCallback): """ A custom callback that derives from ``BaseCallback``. :param verbose: (int) Verbosity level 0: not output 1: info 2: debug """ def __init__(self, log_dir='logs', hist_freq:int=100, verbose=0, log_file='log', eval_episodes=100): super(CustomCallback, self).__init__(verbose) self.num_episodes = 1 self.max_val = 0 self.histogram = np.zeros(15, dtype = int) self.verbose = verbose self.hist_freq = int(hist_freq) self.log_dir = log_dir self.log_file = log_file self.eval_episodes = eval_episodes self.last_timestep = 1 self.episode_lengths= [] self.episode_maxtiles = [] # Those variables will be accessible in the callback # (they are defined in the base class) # The RL model # self.model = None # type: BaseRLModel # An alias for self.model.get_env(), the environment used for training # self.training_env = None # type: Union[gym.Env, VecEnv, None] # Number of time the callback was called # self.n_calls = 0 # type: int # self.num_timesteps = 0 # type: int # local and global variables # self.locals = None # type: Dict[str, Any] # self.globals = None # type: Dict[str, Any] # The logger object, used to report things in the terminal # self.logger = None # type: logger.Logger # # Sometimes, for event callback, it is useful # # to have access to the parent object # self.parent = None # type: Optional[BaseCallback] def _on_training_start(self) -> None: """ This method is called before the first rollout starts. """ # print(self.verbose, type(self.hist_freq)) pass def _on_rollout_start(self) -> None: """ A rollout is the collection of environment interaction using the current policy. This event is triggered before collecting new samples. """ pass def _on_step(self) -> bool: """ This method will be called by the model after each call to `env.step()`. For child callback (of an `EventCallback`), this will be called when the event is triggered. :return: (bool) If the callback returns False, training is aborted early. """ timestep = self.locals['self'].num_timesteps num_episodes = len(self.locals['episode_rewards']) if num_episodes > self.num_episodes: self.num_episodes = num_episodes self.histogram[self.max_val] += 1 self.episode_maxtiles.append(self.max_val) self.episode_lengths.append(timestep-self.last_timestep) self.last_timestep = timestep if self.hist_freq > 0 and num_episodes % self.hist_freq == 0 : self._dump_values() self.max_val = self.locals['self'].get_env().maximum_tile() return True def _on_rollout_end(self) -> None: """ This event is triggered before updating the policy. """ pass def _on_training_end(self) -> None: """ This event is triggered before exiting the `learn()` method. """ pass def _dump_values(self): timestep = self.locals['self'].num_timesteps num_episodes = self.num_episodes if self.log_dir and self.log_file: log_path = os.path.join(self.log_dir, self.log_file) log_file = log_path + '.npz' try: os.replace(log_file, log_file+'.bkp') except: pass np.savez(log_path, rewards=self.locals['episode_rewards'], lengths=self.episode_lengths, max_tiles=self.episode_maxtiles) if self.verbose: print() print(f'#episodes: {num_episodes}') print(f'#timesteps: {timestep}') print(f'Mean rewards: {np.mean(self.locals["episode_rewards"][-self.eval_episodes:])}') print(f'Mean episode length: {np.mean(self.episode_lengths[-self.eval_episodes:])}') print('Histogram of maximum tile achieved:') for i in range(1,15): if self.histogram[i] > 0: print(f'{2**i}: {self.histogram[i]}') print() class CustomCallbackPPO2(BaseCallback): """ A custom callback that derives from ``BaseCallback``. :param verbose: (int) Verbosity level 0: not output 1: info 2: debug """ def __init__(self, log_dir='logs', hist_freq:int=100, verbose=0, log_file='log', eval_episodes=100): super(CustomCallbackPPO2, self).__init__(verbose) self.num_episodes = 1 self.max_val = 0 self.histogram = np.zeros(15, dtype = int) self.verbose = verbose self.hist_freq = int(hist_freq) self.log_dir = log_dir self.log_file = log_file self.eval_episodes = eval_episodes self.last_timestep = 1 # self.episode_lengths= [] self.episode_maxtiles = [] # Those variables will be accessible in the callback # (they are defined in the base class) # The RL model # self.model = None # type: BaseRLModel # An alias for self.model.get_env(), the environment used for training # self.training_env = None # type: Union[gym.Env, VecEnv, None] # Number of time the callback was called # self.n_calls = 0 # type: int # self.num_timesteps = 0 # type: int # local and global variables # self.locals = None # type: Dict[str, Any] # self.globals = None # type: Dict[str, Any] # The logger object, used to report things in the terminal # self.logger = None # type: logger.Logger # # Sometimes, for event callback, it is useful # # to have access to the parent object # self.parent = None # type: Optional[BaseCallback] def _on_training_start(self) -> None: """ This method is called before the first rollout starts. """ # print(self.verbose, type(self.hist_freq)) pass def _on_rollout_start(self) -> None: """ A rollout is the collection of environment interaction using the current policy. This event is triggered before collecting new samples. """ pass def _on_step(self) -> bool: """ This method will be called by the model after each call to `env.step()`. For child callback (of an `EventCallback`), this will be called when the event is triggered. :return: (bool) If the callback returns False, training is aborted early. """ timestep = self.locals['self'].num_timesteps env = self.training_env episode_rewards = env.get_attr('episode_rewards') n_env = len(episode_rewards) num_episodes = 0 for l in episode_rewards: num_episodes += len(l) if num_episodes > self.num_episodes: self.num_episodes = num_episodes self.histogram[self.max_val] += 1 self.episode_maxtiles.append(self.max_val) # self.episode_lengths.append(timestep-self.last_timestep) self.last_timestep = timestep if self.hist_freq > 0 and num_episodes % self.hist_freq == 0 : self._dump_values() self.max_val = env.env_method('maximum_tile') return True def _on_rollout_end(self) -> None: """ This event is triggered before updating the policy. """ pass def _on_training_end(self) -> None: """ This event is triggered before exiting the `learn()` method. """ pass def _dump_values(self): timestep = self.locals['self'].num_timesteps num_episodes = self.num_episodes env = self.training_env episode_rewards = env.get_attr('episode_rewards') if self.log_dir and self.log_file: log_path = os.path.join(self.log_dir, self.log_file) log_file = log_path + '.npz' try: os.replace(log_file, log_file+'.bkp') except: pass np.savez(log_path, rewards=episode_rewards, max_tiles=self.episode_maxtiles) if self.verbose: n_env = len(episode_rewards) print() print(f'#episodes: {num_episodes}') print(f'#timesteps: {timestep}') mean_rewards = 0 for l in episode_rewards: mean_rewards += np.mean(l[-self.eval_episodes//n_env:])/n_env print(f'Mean rewards: {mean_rewards}') # print(f'Mean episode length: {np.mean(self.episode_lengths[-self.eval_episodes:])}') print('Histogram of maximum tile achieved:') for i in range(1,15): if self.histogram[i] > 0: print(f'{2**i}: {self.histogram[i]}') print()

38.3361

133

0.597467

1,156

9,239

4.603806

0.15917

0.043405

0.022548

0.015784

0.908117

0.900225

0.892334

0.875235

0

0.008403

0.30447

9,239

240

134

38.495833

0.819795

0.333694

0

0.832

0

0.090292

0.020181

0

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0.112

false

0.08

0.024

0

0.168

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null

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1

0

1

0

null

0

1

0

8

d7c64ab2303f43a8b9e9f3f82d8532deac05fc3a

7,933

py

Python

frameworks/get_framework.py

proteekroy/samoo

a3497d65e060c8713b5a2153952cc4d9c83ba60a

[ "MIT" ]

6

2019-02-11T20:12:00.000Z

2020-04-12T10:41:58.000Z

frameworks/get_framework.py

proteekroy/samoo

a3497d65e060c8713b5a2153952cc4d9c83ba60a

[ "MIT" ]

null

frameworks/get_framework.py

proteekroy/samoo

a3497d65e060c8713b5a2153952cc4d9c83ba60a

[ "MIT" ]

2

2019-06-20T11:16:51.000Z

2020-04-12T10:42:10.000Z

from frameworks.framework11 import Framework11 from frameworks.framework12 import Framework12 from frameworks.framework21 import Framework21 from frameworks.framework22 import Framework22 from frameworks.framework31 import Framework31 from frameworks.framework32 import Framework32 from frameworks.framework41 import Framework41 from frameworks.framework42 import Framework42 from frameworks.framework5 import Framework5 from frameworks.framework6 import Framework6 def get_framework(framework_id=None, problem=None, algorithm=None, model_list=None, ref_dirs=None, curr_ref_id=None, g_aggregate_func=None, f_aggregate_func=None, m5_fg_aggregate_func=None, m6_fg_aggregate_func=None, *args, **kwargs): frameworks = framework_id.split(',') if len(frameworks) == 1: if framework_id in ['11']: return Framework11(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['12']: return Framework12(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['21']: return Framework21(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['22']: return Framework22(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['31']: return Framework31(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['32']: return Framework32(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['41']: return Framework41(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['42']: return Framework42(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['5']: return Framework5(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) elif framework_id in ['6A', '6B']: return Framework6(framework_id=framework_id, problem=problem, algorithm=algorithm, model_list=model_list, ref_dirs=ref_dirs, curr_ref_id=curr_ref_id, g_aggregate_func=g_aggregate_func, f_aggregate_func=f_aggregate_func, m5_fg_aggregate_func=m5_fg_aggregate_func, m6_fg_aggregate_func=m6_fg_aggregate_func, *args, **kwargs) else: raise Exception("Framework definition not supported") else: raise Exception("Multiple Frameworks not supported")

52.536424

73

0.47876

703

7,933

4.937411

0.083926

0.314607

0.181504

0.102852

0.729761

0

0.027818

0.474348

7,933

150

74

52.886667

0.804556

0

0.689189

0

0.011219

0

1

0.006757

false

0

0.067568

0

0.141892

0

null

1

0

1

0

null

0

7

d7cefb9fc757c32265b856aa6168b644882fd07a

131

py

Python

src/gmj/depends.py

nikell28/good-morning-jarvis

8783be63f5a53bb47c40b5b40247a21d5f56bbb5

[ "MIT" ]

null

src/gmj/depends.py

nikell28/good-morning-jarvis

8783be63f5a53bb47c40b5b40247a21d5f56bbb5

[ "MIT" ]

null

src/gmj/depends.py

nikell28/good-morning-jarvis

8783be63f5a53bb47c40b5b40247a21d5f56bbb5

[ "MIT" ]

null

from gmj.service import GoodMorningService def get_good_morning_service() -> GoodMorningService: return GoodMorningService()

21.833333

53

0.816794

13

131

8

0.769231

0

0.122137

131

5

54

26.2

0.904348

0

1

0.333333

true

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

7

d7cfe4ad88d702f45128d71f9076ff80ecf391c5

15,428

py

Python

dot_vim/plugged/powerline/tests/test_python/test_logging.py

gabefgonc/san-francisco-rice-dotfiles

60ff3539f34ecfff6d7bce895497e2a3805910d4

[ "MIT" ]

11,435

2015-01-01T03:32:34.000Z

2022-03-31T20:39:05.000Z

dot_vim/plugged/powerline/tests/test_python/test_logging.py

gabefgonc/san-francisco-rice-dotfiles

60ff3539f34ecfff6d7bce895497e2a3805910d4

[ "MIT" ]

879

2015-01-02T11:59:30.000Z

2022-03-24T09:52:17.000Z

dot_vim/plugged/powerline/tests/test_python/test_logging.py

gabefgonc/san-francisco-rice-dotfiles

60ff3539f34ecfff6d7bce895497e2a3805910d4

[ "MIT" ]

1,044

2015-01-05T22:37:53.000Z

2022-03-17T19:43:16.000Z

# vim:fileencoding=utf-8:noet '''Tests for various logging features''' from __future__ import (unicode_literals, division, absolute_import, print_function) import sys import re import codecs import os from io import StringIO from shutil import rmtree from powerline import finish_common_config, create_logger from tests.modules import TestCase from tests.modules.lib import replace_attr TIMESTAMP_RE = r'\d{4}-\d\d-\d\d \d\d:\d\d:\d\d,\d{3}' class TestRE(TestCase): def assertMatches(self, text, regexp): self.assertTrue( re.match(regexp, text), '{0!r} did not match {1!r}'.format(text, regexp), ) def close_handlers(logger): for handler in logger.handlers: handler.close() class TestHandlers(TestRE): def test_stderr_handler_is_default(self): out = StringIO() err = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {}) logger, pl, get_module_attr = create_logger(common_config) pl.error('Foo') close_handlers(logger) self.assertMatches(err.getvalue(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') self.assertEqual(out.getvalue(), '') def test_stream_override(self): out = StringIO() err = StringIO() stream = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) self.assertMatches(stream.getvalue(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_explicit_none(self): out = StringIO() err = StringIO() stream = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [None]}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) self.assertMatches(stream.getvalue(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_explicit_stream_handler(self): out = StringIO() err = StringIO() stream = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [['logging.StreamHandler', [[]]]]}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) self.assertEqual(stream.getvalue(), '') self.assertMatches(err.getvalue(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') self.assertEqual(out.getvalue(), '') def test_explicit_stream_handler_implicit_stream(self): out = StringIO() err = StringIO() stream = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [['logging.StreamHandler', []]]}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) self.assertMatches(stream.getvalue(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_file_handler(self): out = StringIO() err = StringIO() stream = StringIO() file_name = 'test_logging-test_file_handler' with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': file_name}) try: logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) with codecs.open(file_name, encoding='utf-8') as fp: self.assertMatches(fp.read(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') finally: os.unlink(file_name) self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_file_handler_create_dir(self): out = StringIO() err = StringIO() stream = StringIO() file_name = 'test_logging-test_file_handler_create_dir/file' self.assertFalse(os.path.isdir(os.path.dirname(file_name))) with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': file_name}) try: logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) self.assertTrue(os.path.isdir(os.path.dirname(file_name))) with codecs.open(file_name, encoding='utf-8') as fp: self.assertMatches(fp.read(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') finally: rmtree(os.path.dirname(file_name)) self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_multiple_files(self): out = StringIO() err = StringIO() stream = StringIO() file_name_1 = 'test_logging-test_multiple_files-1' file_name_2 = file_name_1[:-1] + '2' with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [file_name_1, file_name_2]}) try: try: logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) for file_name in (file_name_1, file_name_2): with codecs.open(file_name, encoding='utf-8') as fp: self.assertMatches(fp.read(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') finally: os.unlink(file_name_1) finally: os.unlink(file_name_2) self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_multiple_files_and_stream(self): out = StringIO() err = StringIO() stream = StringIO() file_name_1 = 'test_logging-test_multiple_files_and_stream-1' file_name_2 = file_name_1[:-1] + '2' with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [file_name_1, file_name_2, None]}) try: try: logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) for file_name in (file_name_1, file_name_2): with codecs.open(file_name, encoding='utf-8') as fp: self.assertMatches(fp.read(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') finally: os.unlink(file_name_1) finally: os.unlink(file_name_2) self.assertMatches(stream.getvalue(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_handler_args(self): out = StringIO() err = StringIO() stream = StringIO() file_name = 'test_logging-test_handler_args' with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [ ['RotatingFileHandler', [[file_name]]] ]}) try: logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') close_handlers(logger) with codecs.open(file_name, encoding='utf-8') as fp: self.assertMatches(fp.read(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') finally: os.unlink(file_name) self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_handler_args_kwargs(self): out = StringIO() err = StringIO() stream = StringIO() file_name = 'test_logging-test_handler_args_kwargs' with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [ ['RotatingFileHandler', [[file_name], {'maxBytes': 1, 'backupCount': 1}]] ]}) try: try: logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.error('Foo') pl.error('Bar') close_handlers(logger) with codecs.open(file_name, encoding='utf-8') as fp: self.assertMatches(fp.read(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Bar\n$') with codecs.open(file_name + '.1', encoding='utf-8') as fp: self.assertMatches(fp.read(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Foo\n$') finally: os.unlink(file_name + '.1') finally: os.unlink(file_name) self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_logger_level(self): out = StringIO() err = StringIO() stream = StringIO() stream1 = StringIO() stream2 = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [ ['logging.StreamHandler', [[stream1]], 'WARNING'], ['logging.StreamHandler', [[stream2]], 'ERROR'], ]}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.warn('Foo') pl.error('Bar') close_handlers(logger) self.assertMatches(stream1.getvalue(), ( '^' + TIMESTAMP_RE + ':WARNING:__unknown__:Foo\n' + TIMESTAMP_RE + ':ERROR:__unknown__:Bar\n$' )) self.assertMatches(stream2.getvalue(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Bar\n$') self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_logger_level_not_overriding_default(self): out = StringIO() err = StringIO() stream = StringIO() stream1 = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [ ['logging.StreamHandler', [[stream1]], 'DEBUG'], ]}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.debug('Foo') pl.error('Bar') close_handlers(logger) self.assertMatches(stream1.getvalue(), '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Bar\n$') self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_top_log_level(self): out = StringIO() err = StringIO() stream = StringIO() stream1 = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [ ['logging.StreamHandler', [[stream1]], 'DEBUG'], ], 'log_level': 'DEBUG'}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.debug('Foo') pl.error('Bar') close_handlers(logger) self.assertMatches(stream1.getvalue(), ( '^' + TIMESTAMP_RE + ':DEBUG:__unknown__:Foo\n' + TIMESTAMP_RE + ':ERROR:__unknown__:Bar\n$' )) self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_logger_format(self): out = StringIO() err = StringIO() stream = StringIO() stream1 = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [ ['logging.StreamHandler', [[stream1]], 'WARNING', 'FOO'], ]}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.warn('Foo') pl.error('Bar') close_handlers(logger) self.assertEqual(stream1.getvalue(), 'FOO\nFOO\n') self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') def test_top_log_format(self): out = StringIO() err = StringIO() stream = StringIO() stream1 = StringIO() stream2 = StringIO() with replace_attr(sys, 'stdout', out, 'stderr', err): common_config = finish_common_config('utf-8', {'log_file': [ ['logging.StreamHandler', [[stream1]], 'WARNING', 'FOO'], ['logging.StreamHandler', [[stream2]], 'WARNING'], ], 'log_format': 'BAR'}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.warn('Foo') pl.error('Bar') close_handlers(logger) self.assertEqual(stream2.getvalue(), 'BAR\nBAR\n') self.assertEqual(stream1.getvalue(), 'FOO\nFOO\n') self.assertEqual(stream.getvalue(), '') self.assertEqual(err.getvalue(), '') self.assertEqual(out.getvalue(), '') class TestPowerlineLogger(TestRE): def test_args_formatting(self): stream = StringIO() common_config = finish_common_config('utf-8', {}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.warn('foo {0}', 'Test') pl.warn('bar {0!r}', 'Test') close_handlers(logger) self.assertMatches(stream.getvalue(), ( '^' + TIMESTAMP_RE + ':WARNING:__unknown__:foo Test\n' + TIMESTAMP_RE + ':WARNING:__unknown__:bar u?\'Test\'\n$' )) def test_prefix_formatting(self): stream = StringIO() common_config = finish_common_config('utf-8', {}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.prefix = '1' pl.warn('foo') pl.prefix = '2' pl.warn('bar') close_handlers(logger) self.assertMatches(stream.getvalue(), ( '^' + TIMESTAMP_RE + ':WARNING:__unknown__:1:foo\n' + TIMESTAMP_RE + ':WARNING:__unknown__:2:bar\n$' )) def test_kwargs_formatting(self): stream = StringIO() common_config = finish_common_config('utf-8', {}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.warn('foo {arg}', arg='Test') pl.warn('bar {arg!r}', arg='Test') close_handlers(logger) self.assertMatches(stream.getvalue(), ( '^' + TIMESTAMP_RE + ':WARNING:__unknown__:foo Test\n' + TIMESTAMP_RE + ':WARNING:__unknown__:bar u?\'Test\'\n$' )) def test_args_kwargs_formatting(self): stream = StringIO() common_config = finish_common_config('utf-8', {}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.warn('foo {0!r} {arg}', 'Test0', arg='Test') pl.warn('bar {0} {arg!r}', 'Test0', arg='Test') close_handlers(logger) self.assertMatches(stream.getvalue(), ( '^' + TIMESTAMP_RE + ':WARNING:__unknown__:foo u?\'Test0\' Test\n' + TIMESTAMP_RE + ':WARNING:__unknown__:bar Test0 u?\'Test\'\n$' )) def test_exception_formatting(self): stream = StringIO() common_config = finish_common_config('utf-8', {}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) try: raise ValueError('foo') except ValueError: pl.exception('Message') close_handlers(logger) self.assertMatches(stream.getvalue(), ( '^' + TIMESTAMP_RE + ':ERROR:__unknown__:Message\n' + 'Traceback \$most recent call last\$:\n' + '(?: File ".*?", line \\d+, in \\w+\n [^\n]*\n)+' + 'ValueError: foo\n$' )) def test_levels(self): stream = StringIO() common_config = finish_common_config('utf-8', {'log_level': 'DEBUG'}) logger, pl, get_module_attr = create_logger(common_config, stream=stream) pl.debug('1') pl.info('2') pl.warn('3') pl.error('4') pl.critical('5') close_handlers(logger) self.assertMatches(stream.getvalue(), ( '^' + TIMESTAMP_RE + ':DEBUG:__unknown__:1\n' + TIMESTAMP_RE + ':INFO:__unknown__:2\n' + TIMESTAMP_RE + ':WARNING:__unknown__:3\n' + TIMESTAMP_RE + ':ERROR:__unknown__:4\n' + TIMESTAMP_RE + ':CRITICAL:__unknown__:5\n$' )) old_cwd = None def setUpModule(): global old_cwd global __file__ old_cwd = os.getcwd() __file__ = os.path.abspath(__file__) os.chdir(os.path.dirname(os.path.dirname(__file__))) def tearDownModule(): global old_cwd os.chdir(old_cwd) if __name__ == '__main__': from tests.modules import main main()

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Python

tasks-deploy/blind-robot/check.py

chankruze/qctf-school-2018

1e732cf264ee0a94bc2fc1fd8cf3a20660d57605

[ "MIT" ]

null

tasks-deploy/blind-robot/check.py

chankruze/qctf-school-2018

1e732cf264ee0a94bc2fc1fd8cf3a20660d57605

[ "MIT" ]

null

tasks-deploy/blind-robot/check.py

chankruze/qctf-school-2018

1e732cf264ee0a94bc2fc1fd8cf3a20660d57605

[ "MIT" ]

null

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reskit/util/loss_factors.py

OfficialCodexplosive/RESKit

e006e8c9923ddb044dab6951c95a15fa43489398

[ "MIT" ]

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2022-03-24T15:56:02.000Z

reskit/util/loss_factors.py

OfficialCodexplosive/RESKit

e006e8c9923ddb044dab6951c95a15fa43489398

[ "MIT" ]

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reskit/util/loss_factors.py

OfficialCodexplosive/RESKit

e006e8c9923ddb044dab6951c95a15fa43489398

[ "MIT" ]

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2020-02-26T14:31:26.000Z

2021-04-28T10:34:51.000Z

import numpy as np def low_generation_loss(capacity_factor, base=0, sharpness=5): """Generate capacity-factor-dependent loss factors Follows the equation: (1-base) * ( 1 - exp[-sharpness * capacity_factor] ) """ return (1 - base) * np.exp(-sharpness * capacity_factor) # dampens lower wind speeds

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Patyrn/Divide-and-Learn

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2020-11-06T01:29:48.000Z

2022-01-02T12:49:40.000Z

IntOpt/NeurIPSIntopt-main/experiments/Building Knapsack/optimizer.py

Patyrn/Divide-and-Learn

ff03689c7ab6a7155ebd019babce8f79d0757a53

[ "MIT" ]

2

2021-01-19T16:59:04.000Z

2021-01-25T10:17:46.000Z

IntOpt/NeurIPSIntopt-main/experiments/Building Knapsack/optimizer.py

Patyrn/Divide-and-Learn

ff03689c7ab6a7155ebd019babce8f79d0757a53

[ "MIT" ]

5

2021-07-13T04:47:13.000Z

2022-01-17T14:05:06.000Z

import numpy as np import random import pandas as pd import math, time import itertools from sklearn import preprocessing from sklearn.preprocessing import MinMaxScaler import datetime import torch from torch import nn, optim from torch.autograd import Variable import torch.utils.data as data_utils from torch.utils.data.dataset import Dataset from sklearn.preprocessing import StandardScaler import gurobipy as gp import logging import copy from collections import defaultdict import joblib budget = 20 test_batchsize = 31 scaler = joblib.load( 'price_scaler.bin') def inv_scaler_transform(value): return scaler.inverse_transform([[ value]]).squeeze() def actual_obj(prop_data, n_items = 62): n = len(prop_data) price = prop_data['Actual sales prices'].values cst = prop_data[ 'Actual construction costs'].values n_instances = n//n_items obj_list = [] for i in range(n_instances): p = price[(n_items*i):((i+1)*n_items)] c = cst[(n_items*i):((i+1)*n_items)] # print("Total cost",sum(c), "Total Profit",sum(p)) model = gp.Model() model.setParam('OutputFlag', 0) x = model.addMVar(shape= n_items, lb=0.0, ub=1.0,vtype=gp.GRB.BINARY, name="x") model.addConstr(c @ x == n_items*budget, name="eq") model.setObjective(p@x, gp.GRB.MAXIMIZE) model.optimize() sol = x.X obj_list.append(inv_scaler_transform(np.dot(sol,p))) return np.array(obj_list) class PriceNet(nn.Module): def __init__(self,n_ts_features,n_cat,n_features,lookback, embedding_size,num_layers,hidden_size,target_size=1): super().__init__() self.n_ts_features = n_ts_features self.n_cat = n_cat self.n_features = n_features self.embedding_size = embedding_size self.num_layers = num_layers self.hidden_size = hidden_size self.target_size = target_size self.lookback = lookback self.embeddings = nn.Embedding(n_cat, embedding_size) self.lstm = nn.LSTM(n_ts_features, hidden_size, num_layers, batch_first=True) # print("Pricenet: embedding size {} n_features {}".format(embedding_size, n_features)) # print(n_features+ embedding_size) self.fc = nn.Linear(n_features+ embedding_size + self.lookback * self.hidden_size, target_size) def forward(self,x_features,x_cat,x_ts,h): x_emb = self.embeddings(x_cat) out, h = self.lstm(x_ts, h) out = torch.flatten(out,start_dim=1) x = torch.cat([x_emb, x_features, out], 1) # print(x.shape) pred = self.fc(x).squeeze() return pred, h class MyCustomDataset(): def __init__(self, economic_data,properties_data,lookback=5): self.x_features= properties_data.iloc[:,6:13].values.astype(np.float32) self.x_cat = properties_data.iloc[:,5].cat.codes.values.astype(np.int64) self.y = properties_data.iloc[:,13].values.astype(np.float32) self.cost = properties_data.iloc[:,14].values.astype(np.float32) self.ts_features = economic_data.iloc[:,2:].values.astype(np.float32) self.x_ts = np.zeros((len(self.ts_features), lookback,self.ts_features.shape[1])).astype(np.float32) for i in range(0,len(self.x_ts),lookback): self.x_ts[i] = self.ts_features[i:(i+lookback),:] self.x_ts = self.x_ts.reshape(-1,lookback,self.ts_features.shape[1]) def __len__(self): return len(self.y) def __getitem__(self, idx): return self.x_features[idx],self.x_cat[idx],self.x_ts[idx], self.y[idx],self.cost[idx] class two_stage: def __init__(self,n_ts_features=19,n_cat=20,n_features=7,lookback=5, embedding_size=5,num_layers=2,hidden_size=10,target_size=1, epochs=8,optimizer=optim.Adam,batch_size=32,**hyperparams): self.embedding_size = embedding_size self.num_layers = num_layers self.hidden_size = hidden_size self.target_size = target_size self.n_features = n_features self.n_ts_features = n_ts_features self.n_cat = n_cat self.lookback = lookback self.optimizer = optimizer self.batch_size = batch_size self.hyperparams = hyperparams self.epochs= epochs # print("embedding size {} n_features {}".format(embedding_size, n_features)) self.model = PriceNet(embedding_size=embedding_size,n_features=n_features, n_ts_features = n_ts_features,n_cat= n_cat,lookback = lookback, num_layers=num_layers,hidden_size=hidden_size,target_size=target_size) self.optimizer = optimizer(self.model.parameters(), **hyperparams) def fit(self,economic_data,properties_data): logging.info("2stage") train_df = MyCustomDataset(economic_data,properties_data) criterion = nn.L1Loss(reduction='mean') #nn.MSELoss(reduction='mean') for e in range(self.epochs): logging.info("EPOCH Starts") total_loss = 0 train_dl = data_utils.DataLoader(train_df, batch_size=self.batch_size,shuffle=True) for x_f,x_c,x_t,y,cst in train_dl: # print("training shape",x_t.shape) self.optimizer.zero_grad() h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states loss = criterion(op, y) total_loss += loss.item() loss.backward() self.optimizer.step() logging.info("EPOCH Ends") # print("Epoch{} ::loss {}".format(e,total_loss)) def val_loss(self,economic_data,properties_data): test_obj = actual_obj(properties_data,n_items = test_batchsize) self.model.eval() criterion = nn.L1Loss(reduction='sum')#nn.MSELoss(reduction='sum') valid_df = MyCustomDataset(economic_data,properties_data) valid_dl = data_utils.DataLoader(valid_df, batch_size= test_batchsize,shuffle=False) prediction_loss = 0 obj_list = [] for x_f,x_c,x_t,y,cst in valid_dl: h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states loss = criterion(op, y) prediction_loss += loss.item() model = gp.Model() model.setParam('OutputFlag', 0) x = model.addMVar(shape= x_t.shape[0], lb=0.0, ub=1.0,vtype=gp.GRB.BINARY, name="x") model.addConstr(cst.detach().numpy() @ x == x_t.shape[0]*budget, name="eq") model.setObjective((op.detach().numpy())@x, gp.GRB.MAXIMIZE) model.optimize() sol = x.X y_np = y.detach().numpy() obj_list.append(inv_scaler_transform(np.dot(sol,y_np))) self.model.train() return prediction_loss, test_obj- np.array(obj_list) def predict(self,economic_data,properties_data): self.model.eval() pred_df = MyCustomDataset(economic_data,properties_data) pred_dl = data_utils.DataLoader(pred_df, batch_size=self.batch_size,shuffle=False) target =[] pred = [] for x_f,x_c,x_t,y,cst in pred_dl: h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states target = target+y.tolist() pred= pred+op.squeeze().tolist() self.model.train() return {'prediction':pred,'groundtuth':target} class SPO: def __init__(self,n_ts_features=19,n_cat=20,n_features=7,lookback=5, embedding_size=5,num_layers=2,hidden_size=10,target_size=1, epochs=8,optimizer=optim.Adam,batch_size=32,budget= budget,**hyperparams): self.embedding_size = embedding_size self.num_layers = num_layers self.hidden_size = hidden_size self.target_size = target_size self.n_features = n_features self.n_ts_features = n_ts_features self.n_cat = n_cat self.lookback = lookback self.budget = budget self.optimizer = optimizer self.batch_size = batch_size self.hyperparams = hyperparams self.epochs= epochs # print("embedding size {} n_features {}".format(embedding_size, n_features)) self.model = PriceNet(embedding_size=embedding_size,n_features=n_features, n_ts_features = n_ts_features,n_cat= n_cat,lookback = lookback, num_layers=num_layers,hidden_size=hidden_size,target_size=target_size) self.optimizer = optimizer(self.model.parameters(), **hyperparams) def fit(self,economic_data,properties_data): logging.info("SPO") train_df = MyCustomDataset(economic_data,properties_data) criterion = nn.L1Loss(reduction='mean') #nn.MSELoss(reduction='mean') for e in range(self.epochs): logging.info("EPOCH Starts") # total_loss = 0 train_dl = data_utils.DataLoader(train_df, batch_size=self.batch_size,shuffle=True) for x_f,x_c,x_t,y ,cst in train_dl: # print("shape",x_t.shape) self.optimizer.zero_grad() h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states model = gp.Model() model.setParam('OutputFlag', 0) x = model.addMVar(shape= x_t.shape[0], lb=0.0, ub=1.0,vtype=gp.GRB.CONTINUOUS, name="x") model.addConstr(cst.detach().numpy() @ x == x_t.shape[0]*self.budget, name="eq") model.setObjective((y.detach().numpy())@x, gp.GRB.MAXIMIZE) model.optimize() x_actual = x.X c_spo = (2*op - y) # print("SHape",y.shape, c_spo.shape, op.shape) model = gp.Model() model.setParam('OutputFlag', 0) x = model.addMVar(shape= x_t.shape[0], lb=0.0, ub=1.0,vtype=gp.GRB.CONTINUOUS, name="x") model.addConstr(cst.detach().numpy() @ x == x_t.shape[0]*self.budget, name="eq") model.setObjective((c_spo.detach().numpy())@x, gp.GRB.MAXIMIZE) model.optimize() x_SPO = x.X grad = torch.from_numpy( x_SPO -x_actual).float() op.backward(gradient=grad) self.optimizer.step() logging.info("EPOCH Ends") # print("Epoch{} ::loss {}".format(e,total_loss)) def val_loss(self,economic_data,properties_data): test_obj = actual_obj(properties_data,n_items = test_batchsize) self.model.eval() criterion = nn.L1Loss(reduction='sum')#nn.MSELoss(reduction='sum') valid_df = MyCustomDataset(economic_data,properties_data) valid_dl = data_utils.DataLoader(valid_df, batch_size= test_batchsize,shuffle=False) prediction_loss = 0 obj_list = [] for x_f,x_c,x_t,y,cst in valid_dl: h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states loss = criterion(op, y) prediction_loss += loss.item() model = gp.Model() model.setParam('OutputFlag', 0) x = model.addMVar(shape= x_t.shape[0], lb=0.0, ub=1.0,vtype=gp.GRB.BINARY, name="x") model.addConstr(cst.detach().numpy() @ x == x_t.shape[0]*budget, name="eq") model.setObjective((op.detach().numpy())@x, gp.GRB.MAXIMIZE) model.optimize() sol = x.X y_np = y.detach().numpy() obj_list.append(inv_scaler_transform(np.dot(sol,y_np))) self.model.train() return prediction_loss, test_obj- np.array(obj_list) def predict(self,economic_data,properties_data): self.model.eval() pred_df = MyCustomDataset(economic_data,properties_data) pred_dl = data_utils.DataLoader(pred_df, batch_size=self.batch_size,shuffle=False) target =[] pred = [] for x_f,x_c,x_t,y,cst in pred_dl: h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states target = target+y.tolist() pred= pred+op.squeeze().tolist() self.model.train() return {'prediction':pred,'groundtuth':target} import sys sys.path.insert(0,"../../Interior") from ip_model_whole import IPOfunc class Intopt: def __init__(self,smoothing=False,thr = 0.1,max_iter=None,method=1,mu0=None, n_ts_features=19,n_cat=20,n_features=7,lookback=5,damping=0.5, embedding_size=5,num_layers=2,hidden_size=10,target_size=1, epochs=8,optimizer=optim.Adam,batch_size=32,budget=budget,**hyperparams): self.embedding_size = embedding_size self.num_layers = num_layers self.hidden_size = hidden_size self.target_size = target_size self.n_features = n_features self.n_ts_features = n_ts_features self.n_cat = n_cat self.lookback = lookback self.budget = budget self.damping = damping self.smoothing = smoothing self.thr = thr self.max_iter = max_iter self.method = method self.mu0= mu0 self.optimizer = optimizer self.batch_size = batch_size self.hyperparams = hyperparams self.epochs= epochs # print("embedding size {} n_features {}".format(embedding_size, n_features)) self.model = PriceNet(embedding_size=embedding_size,n_features=n_features, n_ts_features = n_ts_features,n_cat= n_cat,lookback = lookback, num_layers=num_layers,hidden_size=hidden_size,target_size=target_size) self.optimizer = optimizer(self.model.parameters(), **hyperparams) def fit(self,economic_data,properties_data): logging.info("Intopt") train_df = MyCustomDataset(economic_data,properties_data) criterion = nn.L1Loss(reduction='mean') #nn.MSELoss(reduction='mean') grad_list = [] for e in range(self.epochs): total_loss = 0 # for i in range(30): # logging.info("EPOCH Starts") # train_prop = properties_data.sample(n = 279,random_state =i) # valid_prop = properties_data.loc[~properties_data.index.isin(train_prop.index)] # train_sl = train_prop.Sl.unique().tolist() # valid_sl = valid_prop.Sl.unique().tolist() # train_prop = train_prop.sort_values(['Sl'],ascending=[True]) # valid_prop = valid_prop.sort_values(['Sl'],ascending=[True]) # train_econ = economic_data[economic_data.Sl.isin(train_sl)] # valid_econ = economic_data[economic_data.Sl.isin(valid_sl)] # train_econ = train_econ.sort_values(['Sl','Lag'],ascending=[True,False]) # valid_econ = valid_econ.sort_values(['Sl','Lag'],ascending=[True,False]) # train_df = MyCustomDataset(train_econ,train_prop) train_dl = data_utils.DataLoader(train_df, batch_size=self.batch_size,shuffle=False) for x_f,x_c,x_t,y ,cst in train_dl: self.optimizer.zero_grad() h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states G = cst.unsqueeze(0) h = torch.tensor([x_t.shape[0]*self.budget],dtype=torch.float) A = torch.Tensor() b = torch.Tensor() x = IPOfunc(G,h,A,b,bounds= [(0., 1.)],max_iter=self.max_iter, thr=self.thr,damping=self.damping, smoothing=self.smoothing)(-op) loss = -(x*y).mean() # op.retain_grad() loss.backward() self.optimizer.step() logging.info("EPOCH Ends") # print("Epoch{} ::loss {} ->".format(e,total_loss)) # print(self.val_loss(valid_econ, valid_prop)) # print("______________") def val_loss(self,economic_data,properties_data): test_obj = actual_obj(properties_data,n_items = test_batchsize) self.model.eval() criterion = nn.L1Loss(reduction='sum')#nn.MSELoss(reduction='sum') valid_df = MyCustomDataset(economic_data,properties_data) valid_dl = data_utils.DataLoader(valid_df, batch_size= test_batchsize,shuffle=False) prediction_loss = 0 obj_list = [] for x_f,x_c,x_t,y,cst in valid_dl: h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states loss = criterion(op, y) prediction_loss += loss.item() model = gp.Model() model.setParam('OutputFlag', 0) x = model.addMVar(shape= x_t.shape[0], lb=0.0, ub=1.0,vtype=gp.GRB.BINARY, name="x") model.addConstr(cst.detach().numpy() @ x == x_t.shape[0]*budget, name="eq") model.setObjective((op.detach().numpy())@x, gp.GRB.MAXIMIZE) model.optimize() sol = x.X y_np = y.detach().numpy() obj_list.append(inv_scaler_transform(np.dot(sol,y_np))) self.model.train() return prediction_loss, test_obj- np.array(obj_list) def predict(self,economic_data,properties_data): self.model.eval() pred_df = MyCustomDataset(economic_data,properties_data) pred_dl = data_utils.DataLoader(pred_df, batch_size=self.batch_size,shuffle=False) target =[] pred = [] for x_f,x_c,x_t,y,cst in pred_dl: h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states target = target+y.tolist() pred= pred+op.squeeze().tolist() self.model.train() return {'prediction':pred,'groundtuth':target} from qpthlocal.qp import QPFunction from qpthlocal.qp import QPSolvers from qpthlocal.qp import make_gurobi_model def make_matrix_qp(w,budget): n = len(w) A1 = np.eye(n) b1 = np.ones(n) A2 = -np.eye(n) b2 = np.zeros(n) A3 = np.expand_dims(w, axis=0) b3 = np.array([budget]) A = np.vstack([A1,A2]) b = np.concatenate([b1,b2]) return torch.from_numpy(A).float(), torch.from_numpy(b).float(),torch.from_numpy(A3).float(), torch.from_numpy(b3).float() class qptl: def __init__(self,tau=1e5,n_ts_features=19,n_cat=20,n_features=7,lookback=5, embedding_size=5,num_layers=2,hidden_size=10,target_size=1, epochs=8,optimizer=optim.Adam,batch_size=32,budget=budget,**hyperparams): self.embedding_size = embedding_size self.num_layers = num_layers self.hidden_size = hidden_size self.target_size = target_size self.n_features = n_features self.n_ts_features = n_ts_features self.n_cat = n_cat self.lookback = lookback self.budget = budget self.tau = tau self.optimizer = optimizer self.batch_size = batch_size self.hyperparams = hyperparams self.epochs= epochs # print("embedding size {} n_features {}".format(embedding_size, n_features)) self.model = PriceNet(embedding_size=embedding_size,n_features=n_features, n_ts_features = n_ts_features,n_cat= n_cat,lookback = lookback, num_layers=num_layers,hidden_size=hidden_size,target_size=target_size) self.optimizer = optimizer(self.model.parameters(), **hyperparams) def fit(self,economic_data,properties_data): logging.info("QPTL") train_df = MyCustomDataset(economic_data,properties_data) grad_list = [] for e in range(self.epochs): total_loss = 0 # for i in range(30): # logging.info("EPOCH Starts") # train_prop = properties_data.sample(n = 279,random_state =i) # valid_prop = properties_data.loc[~properties_data.index.isin(train_prop.index)] # train_sl = train_prop.Sl.unique().tolist() # valid_sl = valid_prop.Sl.unique().tolist() # train_prop = train_prop.sort_values(['Sl'],ascending=[True]) # valid_prop = valid_prop.sort_values(['Sl'],ascending=[True]) # train_econ = economic_data[economic_data.Sl.isin(train_sl)] # valid_econ = economic_data[economic_data.Sl.isin(valid_sl)] # train_econ = train_econ.sort_values(['Sl','Lag'],ascending=[True,False]) # valid_econ = valid_econ.sort_values(['Sl','Lag'],ascending=[True,False]) # train_df = MyCustomDataset(train_econ,train_prop) train_dl = data_utils.DataLoader(train_df, batch_size=self.batch_size,shuffle=False) for x_f,x_c,x_t,y ,cst in train_dl: self.optimizer.zero_grad() h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states G,h,A,b = make_matrix_qp(cst.detach().numpy(),x_t.shape[0]*self.budget) Q = torch.eye(x_t.shape[0])/self.tau model_params_quad = make_gurobi_model(G.detach().numpy(),h.detach().numpy(), A.detach().numpy(),b.detach().numpy(), self.tau*np.eye(x_t.shape[0])) x = QPFunction(verbose=False, solver=QPSolvers.GUROBI, model_params=model_params_quad)(Q.expand(1, *Q.shape), -op, G.expand(1, *G.shape), h.expand(1, *h.shape), A.expand(1, *A.shape), b.expand(1, *b.shape)) loss = -(x*y).mean() op.retain_grad() loss.backward() # op_grad = copy.deepcopy(op.grad) # grad_dict = {} # grad_dict['epoch'] = e # grad_dict['subepoch'] = i # for l in range(len(op_grad)): # grad_dict['qpt_cgrad'] = op_grad[l].item() # grad_dict['prediction'] = op[l].item() # grad_dict['true'] = y[l].item() # grad_list.append(copy.deepcopy(grad_dict)) self.optimizer.step() total_loss += loss.item() logging.info("EPOCH Ends") # print("Epoch{} ::loss {} ->".format(e,total_loss)) # print(self.val_loss(valid_econ, valid_prop)) # print("______________") def val_loss(self,economic_data,properties_data): test_obj = actual_obj(properties_data,n_items = test_batchsize) self.model.eval() criterion = nn.L1Loss(reduction='sum')#nn.MSELoss(reduction='sum') valid_df = MyCustomDataset(economic_data,properties_data) valid_dl = data_utils.DataLoader(valid_df, batch_size= test_batchsize,shuffle=False) prediction_loss = 0 obj_list = [] for x_f,x_c,x_t,y,cst in valid_dl: h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states loss = criterion(op, y) prediction_loss += loss.item() model = gp.Model() model.setParam('OutputFlag', 0) x = model.addMVar(shape= x_t.shape[0], lb=0.0, ub=1.0,vtype=gp.GRB.BINARY, name="x") model.addConstr(cst.detach().numpy() @ x == x_t.shape[0]*budget, name="eq") model.setObjective((op.detach().numpy())@x, gp.GRB.MAXIMIZE) model.optimize() sol = x.X y_np = y.detach().numpy() obj_list.append(inv_scaler_transform(np.dot(sol,y_np))) self.model.train() return prediction_loss, test_obj- np.array(obj_list) def predict(self,economic_data,properties_data): self.model.eval() pred_df = MyCustomDataset(economic_data,properties_data) pred_dl = data_utils.DataLoader(pred_df, batch_size=self.batch_size,shuffle=False) target =[] pred = [] for x_f,x_c,x_t,y,cst in pred_dl: h = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) c = torch.zeros((self.num_layers,x_t.shape[0],self.hidden_size),dtype=torch.float) op,states = self.model(x_f,x_c,x_t,(h,c)) h,c = states target = target+y.tolist() pred= pred+op.squeeze().tolist() self.model.train() return {'prediction':pred,'groundtuth':target}

42.54067

126

0.606081

3,636

26,673

4.213696

0.074532

0.008616

0.019189

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26,673

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42.54067

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null

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7

0b0776b058df62266be922f31d4d8e5674a6fa34

10,272

py

Python

insights/tests/datasources/test_candlepin_broker.py

maxamillion/insights-core

aa11e07e68077df97b6c85219911f8382be6e2fa

[ "Apache-2.0" ]

121

2017-05-30T20:23:25.000Z

2022-03-23T12:52:15.000Z

insights/tests/datasources/test_candlepin_broker.py

maxamillion/insights-core

aa11e07e68077df97b6c85219911f8382be6e2fa

[ "Apache-2.0" ]

1,977

2017-05-26T14:36:03.000Z

2022-03-31T10:38:53.000Z

insights/tests/datasources/test_candlepin_broker.py

maxamillion/insights-core

aa11e07e68077df97b6c85219911f8382be6e2fa

[ "Apache-2.0" ]

244

2017-05-30T20:22:57.000Z

2022-03-26T10:09:39.000Z

import pytest from mock.mock import Mock from insights.core import ET from insights.core.spec_factory import DatasourceProvider from insights.core.dr import SkipComponent from insights.specs.default import candlepin_broker CANDLEPIN_BROKER = """ <configuration xmlns="urn:activemq" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="urn:activemq /schema/artemis-configuration.xsd"> <core xmlns="urn:activemq:core" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="urn:activemq:core "> <acceptors> <acceptor name="in-vm">vm://0</acceptor> <acceptor name="stomp">tcp://localhost:61613?protocols=STOMP;useEpoll=false;sslEnabled=true;trustStorePath=/etc/candlepin/certs/truststore;trustStorePassword=CDX9i3K5uPPBzcNtzz5tcycVf5PuXA5w;keyStorePath=/etc/candlepin/certs/keystore;keyStorePassword=4iBpTS45VZjFmVdNzRhRKNXtxbsH5Dij;needClientAuth=true</acceptor> </acceptors> <security-enabled>true</security-enabled> <security-settings> <security-setting match="katello.candlepin.#"> <permission type="consume" roles="candlepinEventsConsumer"/> </security-setting> <security-setting match="#"> <permission type="createAddress" roles="invm-role"/> <permission type="deleteAddress" roles="invm-role"/> <permission type="createDurableQueue" roles="invm-role"/> <permission type="deleteDurableQueue" roles="invm-role"/> <permission type="createNonDurableQueue" roles="invm-role"/> <permission type="deleteNonDurableQueue" roles="invm-role"/> <permission type="send" roles="invm-role"/> <permission type="consume" roles="invm-role"/> <permission type="browse" roles="invm-role"/> <permission type="manage" roles="invm-role"/> </security-setting> </security-settings>  <cluster-user></cluster-user> <cluster-password></cluster-password> </core> </configuration> """.strip() CANDLEPIN_BROKER_NO_SENSITIVE_INFO = """ <configuration xmlns="urn:activemq" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="urn:activemq /schema/artemis-configuration.xsd"> <core xmlns="urn:activemq:core" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="urn:activemq:core "> <security-enabled>true</security-enabled> <security-settings> <security-setting match="katello.candlepin.#"> <permission type="consume" roles="candlepinEventsConsumer"/> </security-setting> <security-setting match="#"> <permission type="createAddress" roles="invm-role"/> <permission type="deleteAddress" roles="invm-role"/> <permission type="createDurableQueue" roles="invm-role"/> <permission type="deleteDurableQueue" roles="invm-role"/> <permission type="createNonDurableQueue" roles="invm-role"/> <permission type="deleteNonDurableQueue" roles="invm-role"/> <permission type="send" roles="invm-role"/> <permission type="consume" roles="invm-role"/> <permission type="browse" roles="invm-role"/> <permission type="manage" roles="invm-role"/> </security-setting> </security-settings>  <cluster-user></cluster-user> </core> </configuration> """.strip() CANDLEPIN_BROKER_BAD = """ <config> <core/> </configuration> """.strip() CANDLEPIN_BROKER_XML = """ <configuration xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="urn:activemq /schema/artemis-configuration.xsd"> <core xsi:schemaLocation="urn:activemq:core "> <security-enabled>true</security-enabled> <security-settings> <security-setting match="katello.candlepin.#"> <permission roles="candlepinEventsConsumer" type="consume" /> </security-setting> <security-setting match="#"> <permission roles="invm-role" type="createAddress" /> <permission roles="invm-role" type="deleteAddress" /> <permission roles="invm-role" type="createDurableQueue" /> <permission roles="invm-role" type="deleteDurableQueue" /> <permission roles="invm-role" type="createNonDurableQueue" /> <permission roles="invm-role" type="deleteNonDurableQueue" /> <permission roles="invm-role" type="send" /> <permission roles="invm-role" type="consume" /> <permission roles="invm-role" type="browse" /> <permission roles="invm-role" type="manage" /> </security-setting> </security-settings> <cluster-user /> </core> </configuration> """.strip() CANDLE_BROKER_NO_SENTISVE_INFO = """ <configuration xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="urn:activemq /schema/artemis-configuration.xsd"> <core xsi:schemaLocation="urn:activemq:core "> <security-enabled>true</security-enabled> <security-settings> <security-setting match="katello.candlepin.#"> <permission roles="candlepinEventsConsumer" type="consume" /> </security-setting> <security-setting match="#"> <permission roles="invm-role" type="createAddress" /> <permission roles="invm-role" type="deleteAddress" /> <permission roles="invm-role" type="createDurableQueue" /> <permission roles="invm-role" type="deleteDurableQueue" /> <permission roles="invm-role" type="createNonDurableQueue" /> <permission roles="invm-role" type="deleteNonDurableQueue" /> <permission roles="invm-role" type="send" /> <permission roles="invm-role" type="consume" /> <permission roles="invm-role" type="browse" /> <permission roles="invm-role" type="manage" /> </security-setting> </security-settings> <cluster-user /> </core> </configuration> """.strip() RELATIVE_PATH = '/etc/candlepin/broker.xml' def xml_check_removed(result): root = ET.fromstring('\n'.join(result)) assert root is not None core_ele = root.find('core') assert core_ele is not None search_tags = ['cluster-password', 'acceptors'] for tag in search_tags: found = core_ele.find(tag) assert found is None, 'Tag {} should not be in result'.format(tag) def xml_compare(result, expected): root_result = ET.fromstring('\n'.join(result)) root_expected = ET.fromstring('\n'.join(expected)) re_core_ele = root_result.find('core') assert re_core_ele is not None ex_core_ele = root_expected.find('core') assert ex_core_ele is not None search_tags = ['cluster-user', 'security-enabled'] for tag in search_tags: ex_found = ex_core_ele.find(tag) if ex_found is not None: re_found = re_core_ele.find(tag) assert re_found is not None, 'Tag {} is in expected but not in result'.format(tag) assert re_found.text == ex_found.text, 'Tag {} text is different in expected and result'.format(tag) ex_settings = ex_core_ele.find('security-settings') if ex_settings is not None: re_settings = re_core_ele.find('security-settings') assert re_found is not None, 'Tag security-settings is in expected but not in result' assert re_found.text == ex_found.text, 'Tag {} text is different in expected and result'.format(tag) ex_settings_dict = {} re_settings_dict = {} for setting in ex_settings.findall('security-setting'): ex_settings_dict[setting.get('match')] = [] for perm in setting.findall('permission'): ex_settings_dict[setting.get('match')].append((perm.get('roles'), perm.get('type'))) for setting in re_settings.findall('security-setting'): re_settings_dict[setting.get('match')] = [] for perm in setting.findall('permission'): re_settings_dict[setting.get('match')].append((perm.get('roles'), perm.get('type'))) assert ex_settings_dict == re_settings_dict def test_candlepin_broker(): candlepin_broker_file = Mock() candlepin_broker_file.content = CANDLEPIN_BROKER.splitlines() broker = {candlepin_broker.LocalSpecs.candlepin_broker_input: candlepin_broker_file} result = candlepin_broker.candlepin_broker(broker) assert result is not None assert isinstance(result, DatasourceProvider) expected = DatasourceProvider(content=CANDLEPIN_BROKER_XML.splitlines(), relative_path=RELATIVE_PATH) xml_check_removed(result.content) xml_compare(result.content, expected.content) assert result.relative_path == expected.relative_path def test_candlepin_broker_bad(): candlepin_broker_file = Mock() candlepin_broker_file.content = CANDLEPIN_BROKER_BAD.splitlines() broker = {candlepin_broker.LocalSpecs.candlepin_broker_input: candlepin_broker_file} with pytest.raises(SkipComponent) as e: candlepin_broker.candlepin_broker(broker) assert 'Unexpected exception' in str(e) def test_candlpin_broker_no_sensitive_info(): candlepin_broker_file = Mock() candlepin_broker_file.content = CANDLEPIN_BROKER_NO_SENSITIVE_INFO.splitlines() broker = {candlepin_broker.LocalSpecs.candlepin_broker_input: candlepin_broker_file} result = candlepin_broker.candlepin_broker(broker) assert result is not None assert isinstance(result, DatasourceProvider) expected = DatasourceProvider(content=CANDLE_BROKER_NO_SENTISVE_INFO.splitlines(), relative_path=RELATIVE_PATH) xml_check_removed(result.content) xml_compare(result.content, expected.content) assert result.relative_path == expected.relative_path

45.653333

326

0.657516

1,097

10,272

6.023701

0.136737

0.054479

0.078692

0.069613

0.80796

0.750605

0.736077

0.720642

0.710654

0

0.005702

0.214661

10,272

224

327

45.857143

0.813437

0

0.673575

0

0.025907

0.635125

0.170171

0

0.088083

1

0.025907

false

0.015544

0.031088

0

0.056995

0

null

0

1

0

1

0

null

0

7

0b12b9992d497676ad30c37b169031f1a79fee67

143

py

Python

01_fundamentals/02_operators/grouping_values.py

doanthanhnhan/learningPY

93c10c5225a306c791402095e1cf0b454f31d0c2

[ "MIT" ]

1

2021-04-04T02:39:05.000Z

01_fundamentals/02_operators/grouping_values.py

doanthanhnhan/learningPY

93c10c5225a306c791402095e1cf0b454f31d0c2

[ "MIT" ]

null

01_fundamentals/02_operators/grouping_values.py

doanthanhnhan/learningPY

93c10c5225a306c791402095e1cf0b454f31d0c2

[ "MIT" ]

null

# Making a List my_list = [1, 2.5, "A string", True] print(my_list) my_list = [1, 2.5, "A string", True] print(my_list[2]) print(len(my_list))

20.428571

36

0.65035

30

143

2.933333

0.366667

0.340909

0.227273

0.25

0.75

0

0.057377

0.146853

143

7

37

20.428571

0.663934

0.090909

0

0.4

0

0.124031

0

1

0

false

0

0.6

0

null

1

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1

0

1

0

null

0

1

0

10

0b155d9e8742ba6d91aca897a1f7f2eeaf77eacd

9,975

py

Python

src/enochecker/useragents.py

hnj2/enochecker

464d585500effb98f33e357df9a90337af52a770

[ "MIT" ]

null

src/enochecker/useragents.py

hnj2/enochecker

464d585500effb98f33e357df9a90337af52a770

[ "MIT" ]

null

src/enochecker/useragents.py

hnj2/enochecker

464d585500effb98f33e357df9a90337af52a770

[ "MIT" ]

null

from random import sample from typing import List # Useragent list from ructf github :) useragents = [ r'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Windows NT 10.0; WOW64; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12) AppleWebKit/602.1.50 (KHTML, like Gecko) Version/10.0 Safari/602.1.50', r'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; WOW64; Trident/7.0; rv:11.0) like Gecko', r'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_1) AppleWebKit/602.2.14 (KHTML, like Gecko) Version/10.0.1 Safari/602.2.14', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.11; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/602.1.50 (KHTML, like Gecko) Version/10.0 Safari/602.1.50', r'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/51.0.2704.79 Safari/537.36 Edge/14.14393', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.3; WOW64; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.12; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Windows NT 6.1; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36', r'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36', r'Mozilla/5.0 (Windows NT 10.0; WOW64; Trident/7.0; rv:11.0) like Gecko', r'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.59 Safari/537.36', r'Mozilla/5.0 (X11; Linux x86_64; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (X11; Linux x86_64; rv:45.0) Gecko/20100101 Firefox/45.0', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Ubuntu Chromium/53.0.2785.143 Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/601.7.7 (KHTML, like Gecko) Version/9.1.2 Safari/601.7.7', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/601.7.8 (KHTML, like Gecko) Version/9.1.3 Safari/601.7.8', r'Mozilla/5.0 (iPad; CPU OS 10_0_2 like Mac OS X) AppleWebKit/602.1.50 (KHTML, like Gecko) Version/10.0 Mobile/14A456 Safari/602.1', r'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.3; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/602.1.50 (KHTML, like Gecko) Version/10.0 Safari/602.1.50', r'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.59 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.10; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.0; Trident/5.0; Trident/5.0)', r'Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0; Trident/5.0)', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/602.2.14 (KHTML, like Gecko) Version/10.0.1 Safari/602.2.14', r'Mozilla/5.0 (Windows NT 6.1; Trident/7.0; rv:11.0) like Gecko', r'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:45.0) Gecko/20100101 Firefox/45.0', r'Mozilla/5.0 (Windows NT 5.1; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/46.0.2486.0 Safari/537.36 Edge/13.10586', r'Mozilla/5.0 (Windows NT 6.3; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.59 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.59 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/52.0.2743.116 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.59 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:47.0) Gecko/20100101 Firefox/47.0', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.3; WOW64; Trident/7.0; rv:11.0) like Gecko', r'Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36', r'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.59 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:48.0) Gecko/20100101 Firefox/48.0', r'Mozilla/5.0 (iPhone; CPU iPhone OS 10_0_2 like Mac OS X) AppleWebKit/601.1 (KHTML, like Gecko) CriOS/53.0.2785.109 Mobile/14A456 Safari/601.1.46', r'Mozilla/5.0 (iPhone; CPU iPhone OS 10_0_2 like Mac OS X) AppleWebKit/602.1.50 (KHTML, like Gecko) Version/10.0 Mobile/14A456 Safari/602.1', r'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:47.0) Gecko/20100101 Firefox/47.0', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/601.6.17 (KHTML, like Gecko) Version/9.1.1 Safari/601.6.17', r'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:48.0) Gecko/20100101 Firefox/48.0', r'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/52.0.2743.116 Safari/537.36', r'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Ubuntu Chromium/52.0.2743.116 Chrome/52.0.2743.116 Safari/537.36', r'Mozilla/5.0 (Windows NT 10.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36', r'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36', r'Mozilla/5.0 (X11; Fedora; Linux x86_64; rv:49.0) Gecko/20100101 Firefox/49.0', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36', r'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_4) AppleWebKit/601.5.17 (KHTML, like Gecko) Version/9.1 Safari/601.5.17', r'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36', r'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.59 Safari/537.36' ] # type: List[str] def random_useragent(): # type: ()-> str """ Returns a random useragent :return: A seemingly valid useragent. """ return sample(useragents, 1)[0]

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9bc4d70bcb1e5463436709553fd1c41b589acba2

17,451

py

Python

calvin/tests/test_queue.py

gabrielcercel/calvin-base

c0315f100643230d65aed1745e1c22df3e7a7c2c

[ "Apache-2.0" ]

334

2015-06-04T15:14:28.000Z

2022-02-09T11:14:17.000Z

calvin/tests/test_queue.py

gabrielcercel/calvin-base

c0315f100643230d65aed1745e1c22df3e7a7c2c

[ "Apache-2.0" ]

89

2015-06-13T19:15:35.000Z

2019-12-03T19:23:20.000Z

calvin/tests/test_queue.py

gabrielcercel/calvin-base

c0315f100643230d65aed1745e1c22df3e7a7c2c

[ "Apache-2.0" ]

112

2015-06-06T19:16:54.000Z

2020-10-19T01:27:55.000Z

# -*- coding: utf-8 -*- # Copyright (c) 2015 Ericsson AB # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import pytest import unittest from calvin.runtime.north.plugins.port import queue from calvin.runtime.north.calvin_token import Token pytestmark = pytest.mark.unittest class QueueTests(unittest.TestCase): def setUp(self): pass def tearDown(self): pass def verify_data(self, write_data, fifo_data): print write_data, fifo_data for a, b in zip(write_data, fifo_data): d = b.value self.assertEquals(a, d) def test1(self): """Adding reader again (reconnect)""" f = queue.fanout_fifo.FanoutFIFO({'queue_length': 4, 'direction': "in"}, {}) f.add_reader('p1.id', {}) data = ['1', '2', '3', '4'] for token in data: self.assertTrue(f.slots_available(1, None)) self.assertTrue(f.write(Token(token), None)) self.verify_data(['1', '2'], [f.peek('p1.id') for _ in range(2)]) f.commit('p1.id') f.add_reader('p1.id', {}) self.verify_data(['3', '4'], [f.peek('p1.id') for _ in range(2)]) self.assertRaises(queue.common.QueueEmpty, f.peek, 'p1.id') f.commit('p1.id') for token in ['5', '6', '7', '8']: self.assertTrue(f.slots_available(1, None)) self.assertTrue(f.write(Token(token), None)) self.assertFalse(f.slots_available(1, None)) self.verify_data(['5', '6', '7', '8'], [f.peek('p1.id') for _ in range(4)]) f.commit('p1.id') def test2(self): """Multiple readers""" f = queue.fanout_fifo.FanoutFIFO({'queue_length': 4, 'direction': "in"}, {}) f.add_reader("r1", {}) f.add_reader("r2", {}) # Ensure fifo is empty self.assertRaises(queue.common.QueueEmpty, f.peek, "r1") self.assertTrue(f.tokens_available(0, "r1")) self.assertTrue(f.tokens_available(0, "r2")) # Add something self.assertTrue(f.write(Token('1'), None)) self.assertTrue(f.tokens_available(1, "r1")) self.assertTrue(f.tokens_available(1, "r2")) # Reader r1 read something self.assertTrue(f.peek('r1')) f.commit('r1') self.assertEquals([True] * 3, [f.write(Token(t), None) for t in ['2', '3', '4']]) self.assertRaises(queue.common.QueueFull, f.write, Token('5'), None) self.verify_data(['2', '3', '4'], [f.peek('r1') for _ in range(3)]) f.commit("r1") # Reader r1 all done, ensure reader r2 can still read self.assertTrue(f.tokens_available(4, "r2")) self.assertFalse(f.slots_available(1, None)) self.assertFalse(f.tokens_available(1, "r1")) # Reader r2 reads something self.verify_data(['1', '2', '3'], [f.peek("r2") for _ in range(3)]) f.commit("r2") self.assertTrue(f.tokens_available(1, "r2")) self.assertTrue(f.write(Token('5'), None)) self.verify_data(['4', '5'], [f.peek("r2") for _ in range(2)]) self.assertFalse(f.tokens_available(1, "r2")) self.assertRaises(queue.common.QueueEmpty, f.peek, "r2") self.assertTrue(f.tokens_available(1, "r1")) self.verify_data(['5'], [f.peek("r1")]) f.commit("r2") f.commit("r1") self.assertTrue(f.write(Token('6'), None)) self.assertTrue(f.write(Token('7'), None)) self.assertTrue(f.write(Token('8'), None)) self.assertTrue([f.peek("r1") for _ in range(3)], [f.peek("r2") for _ in range(3)]) self.assertRaises(queue.common.QueueEmpty, f.peek, "r1") self.assertRaises(queue.common.QueueEmpty, f.peek, "r2") def test3(self): """Testing commit reads""" f = queue.fanout_fifo.FanoutFIFO({'queue_length': 4, 'direction': "in"}, {}) f.add_reader("r1", {}) for token in ['1', '2', '3', '4']: self.assertTrue(f.slots_available(1, None)) self.assertTrue(f.write(Token(token), None)) # Fails, fifo full self.assertFalse(f.slots_available(1, None)) self.assertRaises(queue.common.QueueFull, f.write, Token('5'), None) # Tentative, fifo still full self.verify_data(['1'], [f.peek("r1")]) self.assertFalse(f.slots_available(1, None)) self.assertRaises(queue.common.QueueFull, f.write, Token('5'), None) # commit previous reads, fifo 1 pos free f.commit('r1') self.assertTrue(f.slots_available(1, None)) self.assertTrue(f.write(Token('5'), None)) # fifo full again self.assertFalse(f.slots_available(1, None)) self.assertRaises(queue.common.QueueFull, f.write, Token('5'), None) def test4(self): """Testing rollback reads""" f = queue.fanout_fifo.FanoutFIFO({'queue_length': 4, 'direction': "in"}, {}) f.add_reader('r1', {}) for token in ['1', '2', '3', '4']: self.assertTrue(f.slots_available(1, None)) self.assertTrue(f.write(Token(token), None)) # fifo full self.assertFalse(f.slots_available(1, None)) self.assertRaises(queue.common.QueueFull, f.write, Token('5'), None) # tentative reads self.verify_data(['1', '2', '3', '4'], [f.peek("r1") for _ in range(4)]) # check still tentative self.assertTrue(f.tokens_available(0, "r1")) self.assertTrue(f.slots_available(0, None)) f.cancel("r1") self.assertFalse(f.slots_available(1, None)) self.assertRaises(queue.common.QueueFull, f.write, Token('5'), None) self.assertTrue(f.tokens_available(4, "r1")) # re-read self.verify_data(['1'], [f.peek("r1")]) f.commit("r1") self.assertTrue(f.tokens_available(3, "r1")) # one pos free in fifo self.assertTrue(f.slots_available(1, None)) self.assertTrue(f.write(Token('a'), None)) self.assertFalse(f.slots_available(1, None)) self.assertRaises(queue.common.QueueFull, f.write, Token('b'), None) def test_round_robin_queue_1(self): """Round-Robin scheduled queue test""" f = queue.fanout_round_robin_fifo.FanoutRoundRobinFIFO({'routing': 'round-robin', 'nbr_peers': 2}, {}) f.add_reader("r1", {}) f.add_reader("r2", {}) # Ensure fifo is empty self.assertRaises(queue.common.QueueEmpty, f.peek, "r1") self.assertRaises(queue.common.QueueEmpty, f.peek, "r2") self.assertFalse(f.tokens_available(1, "r1")) self.assertFalse(f.tokens_available(1, "r2")) # Add something self.assertTrue(f.write(Token('1'), None)) self.assertTrue(f.tokens_available(1, "r1")) self.assertFalse(f.tokens_available(1, "r2")) # Add something self.assertTrue(f.write(Token('2'), None)) self.assertTrue(f.tokens_available(1, "r1")) self.assertFalse(f.tokens_available(2, "r1")) self.assertTrue(f.tokens_available(1, "r2")) # Reader r2 read something self.verify_data(['2'], [f.peek('r2')]) self.assertTrue(f.tokens_available(1, "r1")) self.assertFalse(f.tokens_available(2, "r1")) self.assertFalse(f.tokens_available(1, "r2")) f.commit('r2') self.assertTrue(f.tokens_available(1, "r1")) self.assertFalse(f.tokens_available(2, "r1")) self.assertFalse(f.tokens_available(1, "r2")) self.assertEquals([True] * 2, [f.write(Token(t), None) for t in ['3', '4']]) self.verify_data(['1', '3'], [f.peek('r1') for _ in range(2)]) f.commit("r1") # Reader r1 all done, ensure reader r2 can still read self.assertTrue(f.tokens_available(1, "r2")) self.assertFalse(f.tokens_available(1, "r1")) # Reader r2 reads something self.verify_data(['4'], [f.peek("r2") for _ in range(1)]) f.commit("r2") self.assertFalse(f.tokens_available(1, "r2")) self.assertTrue(f.write(Token('5'), None)) self.verify_data(['5'], [f.peek("r1")]) self.assertTrue(f.write(Token('6'), None)) self.assertFalse(f.tokens_available(1, "r1")) self.assertRaises(queue.common.QueueEmpty, f.peek, "r1") self.assertTrue(f.tokens_available(1, "r2")) self.verify_data(['6'], [f.peek("r2")]) f.commit("r2") f.commit("r1") self.assertTrue(f.write(Token('7'), None)) self.assertTrue(f.write(Token('8'), None)) self.assertTrue(f.write(Token('9'), None)) self.assertTrue(f.write(Token('10'), None)) self.verify_data(['7', '9'], [f.peek("r1") for _ in range(2)]) self.verify_data(['8', '10'], [f.peek("r2") for _ in range(2)]) self.assertRaises(queue.common.QueueEmpty, f.peek, "r1") self.assertRaises(queue.common.QueueEmpty, f.peek, "r2") def test_round_robin_queue_2(self): """Round-Robin scheduled queue test""" f = queue.fanout_round_robin_fifo.FanoutRoundRobinFIFO({'routing': 'round-robin', 'nbr_peers': 2}, {}) f.add_reader("r1", {}) f.add_reader("r2", {}) # Ensure fifo is empty self.assertRaises(queue.common.QueueEmpty, f.peek, "r1") self.assertRaises(queue.common.QueueEmpty, f.peek, "r2") self.assertFalse(f.tokens_available(1, "r1")) self.assertFalse(f.tokens_available(1, "r2")) # Fill up self.assertEquals([True] * 4, [f.write(Token(t), None) for t in map(lambda x: str(x), range(1,5))]) self.assertTrue(f.tokens_available(2, "r1")) self.assertTrue(f.tokens_available(2, "r2")) # Reader r2 read something self.verify_data(['2'], [f.peek('r2')]) self.assertFalse(f.tokens_available(2, "r2")) self.assertTrue(f.tokens_available(1, "r2")) self.assertTrue(f.tokens_available(2, "r1")) f.cancel('r2') self.assertTrue(f.tokens_available(2, "r2")) self.assertTrue(f.tokens_available(2, "r1")) # Reader r2 read something again self.verify_data(['2'], [f.peek('r2')]) self.assertFalse(f.tokens_available(2, "r2")) self.assertTrue(f.tokens_available(1, "r2")) self.assertTrue(f.tokens_available(2, "r1")) f.cancel('r2') self.assertTrue(f.tokens_available(2, "r2")) self.assertTrue(f.tokens_available(2, "r1")) # Reader r2 read something again plus some self.verify_data(['2', '4'], [f.peek('r2') for _ in range(2)]) self.assertFalse(f.tokens_available(1, "r2")) self.assertTrue(f.tokens_available(2, "r1")) f.cancel('r2') self.assertTrue(f.tokens_available(2, "r2")) self.assertTrue(f.tokens_available(2, "r1")) # Reader r2 read something again self.verify_data(['2', '4'], [f.peek('r2') for _ in range(2)]) self.assertFalse(f.tokens_available(1, "r2")) self.assertTrue(f.tokens_available(2, "r1")) f.commit('r2') self.assertFalse(f.tokens_available(1, "r2")) self.assertTrue(f.tokens_available(2, "r1")) self.verify_data(['1', '3'], [f.peek('r1') for _ in range(2)]) self.assertFalse(f.tokens_available(1, "r1")) f.commit('r1') self.assertFalse(f.tokens_available(1, "r1")) def test_scheduled_queue_3(self): """Round-Robin scheduled queue test""" f = queue.fanout_round_robin_fifo.FanoutRoundRobinFIFO({'routing': 'round-robin', 'nbr_peers': 2}, {}) f.add_reader("r1", {}) f.add_reader("r2", {}) # Ensure fifo is empty self.assertRaises(queue.common.QueueEmpty, f.peek, "r1") self.assertRaises(queue.common.QueueEmpty, f.peek, "r2") self.assertFalse(f.tokens_available(1, "r1")) self.assertFalse(f.tokens_available(1, "r2")) count = {'r1': 0, 'r2': 0} values = {'r1': [], 'r2': []} for k in range(10): # Fill up self.assertEquals([True] * 4, [f.write(Token(t), None) for t in map(lambda x: str(x), range(k*4+1,k*4+5))]) # Empty for r in ['r1', 'r2']: while True: try: values[r].append(f.peek(r)) count[r] += 1 except queue.common.QueueEmpty: break f.commit(r) assert count['r1'] == 20 assert count['r2'] == 20 values['r1'] = [int(v.value) for v in values['r1']] values['r2'] = [int(v.value) for v in values['r2']] # No common tokens and always in order assert len(set(values['r1']).intersection(set(values['r2']))) == 0 assert sorted(values['r1']) == values['r1'] assert sorted(values['r2']) == values['r2'] def test_random_queue_4(self): """Random scheduled queue test""" f = queue.fanout_random_fifo.FanoutRandomFIFO({'routing': 'random', 'nbr_peers': 2}, {}) f.add_reader("r1", {}) f.add_reader("r2", {}) # Ensure fifo is empty self.assertRaises(queue.common.QueueEmpty, f.peek, "r1") self.assertRaises(queue.common.QueueEmpty, f.peek, "r2") self.assertFalse(f.tokens_available(1, "r1")) self.assertFalse(f.tokens_available(1, "r2")) count = {'r1': 0, 'r2': 0} values = {'r1': [], 'r2': []} for k in range(10): # Fill up self.assertEquals([True] * 4, [f.write(Token(t), None) for t in map(lambda x: str(x), range(k*4+1,k*4+5))]) # Empty for r in ['r1', 'r2']: while True: try: values[r].append(f.peek(r)) count[r] += 1 except queue.common.QueueEmpty: break f.commit(r) # Even if random assume that at least 5 tokens to each peer assert count['r1'] > 5 assert count['r2'] > 5 assert sum(count.values()) == 10 * 4 values['r1'] = [int(v.value) for v in values['r1']] values['r2'] = [int(v.value) for v in values['r2']] # No common tokens and always in order assert len(set(values['r1']).intersection(set(values['r2']))) == 0 assert sorted(values['r1']) == values['r1'] assert sorted(values['r2']) == values['r2'] def test_collect_unordered1(self): f = queue.collect_unordered.CollectUnordered({'routing': 'collect-unordered', 'nbr_peers': 10}, {}) for i in range(10): f.add_writer("w"+str(i), {}) # Fill queue try: for t in range(40): for i in range(10): f.write(Token(i), "w"+str(i)) except: pass tokens = [] try: for i in range(1000): tokens.append(f.peek(None)) f.commit(None) except: pass print [t.value for t in tokens] assert [t.value for t in tokens] == range(0,10) * 4 def test_collect_unordered2(self): f = queue.collect_unordered.CollectUnordered({'routing': 'collect-unordered', 'nbr_peers': 10}, {}) for i in range(10): f.add_writer("w"+str(i), {}) # Fill queue try: for t in range(40): for i in range(10): f.write(Token(i), "w"+str(i)) except: pass tokens = [] try: for i in range(1000): tokens.append(f.peek(None)) if i % 2 == 1: f.commit(None) else: f.cancel(None) except: pass print [t.value for t in tokens] assert [t.value for t in tokens] == [0,0,1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9] * 4 def test_collect_unordered3(self): f = queue.collect_unordered.CollectUnordered({'routing': 'collect-unordered', 'nbr_peers': 10}, {}) for i in range(10): f.add_writer("w"+str(i), {}) # Fill queue try: for t in range(40): for i in range(0,6): f.write(Token(i), "w"+str(i)) except: pass tokens = [] try: for i in range(1000): tokens.append(f.peek(None)) if i % 2 == 1: f.commit(None) else: f.cancel(None) try: f.write(Token(0), "w0") except: pass except: pass print [t.value for t in tokens] s = [0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5] * 4 + [0] * 12 assert [t.value for t in tokens][:len(s)] == s

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9

50465b1a4463b39b3d9891638fc95254bfa2a2b5

22,774

py

Python

App/apis/UserApi.py

TonyRays/flaskapi4.0

559b6cee8c75cee15a658f06730a9a3b97c1c988

[ "Apache-2.0" ]

null

App/apis/UserApi.py

TonyRays/flaskapi4.0

559b6cee8c75cee15a658f06730a9a3b97c1c988

[ "Apache-2.0" ]

null

App/apis/UserApi.py

TonyRays/flaskapi4.0

559b6cee8c75cee15a658f06730a9a3b97c1c988

[ "Apache-2.0" ]

null

# coding=utf-8 import uuid from flask import abort, request, g from flask_restful import Resource, reqparse, fields, marshal, marshal_with from werkzeug.security import generate_password_hash, check_password_hash from App.ext import cache from App.models.UserModel import * #from flask_login import login_user # 输出参数 parser = reqparse.RequestParser() #parser_user = reqparse.RequestParser() #parser.add_argument('user', required=True, help="请输入操作者身份mentors/students") # 比较常见的位置直接放在 ?action=login, register #parser.add_argument('action', required=True, help="请提供具体操作") # ———————————————————— Labs 注册 ———————————————————————————————— # # 内层参数格式化 labs_fields = { 'lab_id' : fields.Integer, 'lab_name': fields.String, 'lab_info': fields.String, 'lab_time': fields.DateTime # lab_permission': fields.Integer, } # 外层输出参数格式化 response_labs_fields = { 'status': fields.Integer, 'msg': fields.String, 'data': fields.Nested(labs_fields) } # /labs/register/ class LabsRegister(Resource): def post(self): parser = reqparse.RequestParser() parser.add_argument('l_name', required=True, help="请输入lab名称") parser.add_argument('l_info', required=True, help="请输入lab信息") #global user args = parser.parse_args() #users = args.get("user") #action = args.get("action") l_name = args.get("l_name") l_info = args.get("l_info") #global data data = { "status": 201, "msg": 'lab register ok, please register mentors then!' } user = Labs() # 防止重复注册 if user.query.filter(Labs.lab_name.__eq__(l_name)).one_or_none(): data['status'] = 403 data['msg'] = 'lab has already registered' return data else: user.lab_name = l_name user.lab_info = l_info user.lab_time = datetime.now() user.save() data['data'] = user return marshal(data, response_labs_fields) # eg. curl http://localhost:5000/mentors/register/ def get(self): return marshal(data, response_labs_fields) # /labs/modify/<int:id>/ class Labsmodify(Resource): # 根据 id 获取 @authm.login_required @marshal_with(response_labs_fields) def get(self, id): user = Labs.query.get(id) data = { "status": 200, "msg": 'ok', 'data': user, } return data # 根据 id 修改 @authm.login_required @marshal_with(response_labs_fields) def post(self, id): parser = reqparse.RequestParser() parser.add_argument('l_name', required=True, help="请输入lab名称") parser.add_argument('l_info', required=True, help="请输入lab信息") args = parser.parse_args() l_name = args.get("l_name") l_info = args.get("l_info") user = Labs.query.get(id) # 根据id获得labs if not user: abort(401, message="user not login or didnt find id") else: user.lab_name = l_name user.lab_info = l_info #user.lab_time = datetime.now() user.save() data = { "status": 200, "msg": 'labs change ok', 'data': user } return data ''' # /labs/<int:mentor_id>/<int:lab_id>/operation1 class operation1(Resource): # 操作labs operation1 @authm.login_required @marshal_with(response_mentors_fields) def POST(self, mentor_id): user = Mentors.query.get(mentor_id) if user.lab_id #data = { # "status": 200, # "msg": 'ok', # 'data': user, #} #return data return # 根据 id 修改用户信息 --> 密码修改 @authm.login_required @marshal_with(response_mentors_fields) def post(self, mentor_id): parser = reqparse.RequestParser() parser.add_argument('u_password', required=True, help="请输入修改后的密码") args = parser.parse_args() u_password = args.get("u_password") user = Mentors.query.get(id) # 根据id获得用户 user.mentor_password = user.men_password(u_password) user.save() data = { "status": 200, "msg": 'password change ok', 'data': user } return data # 根据 id 删除某个用户 Model中应该设计一个字段 is_delete 来判断是否已删除 @authm.login_required @marshal_with(response_mentors_fields) def delete(self, id): user = Mentors.query.get(id) user.is_delete = True # is_delete = 1 表示删除用户 user.save() data = { "status": 200, "msg": 'delete ok', "data": user } return data ''' # ———————————————————— Mentors 注册和登录———————————————————————————————— # mentors_fields = { 'mentor_id': fields.Integer, 'mentor_name': fields.String, 'lab_id': fields.Integer #'mentor_permission': fields.Integer, } # 外层输出参数格式化 response_mentors_fields = { 'status': fields.Integer, 'msg': fields.String, 'data': fields.Nested(mentors_fields) } # 外层输出参数格式化 + token response_mentors_token_fields = { 'status': fields.Integer, 'msg': fields.String, 'token': fields.String, 'data': fields.Nested(mentors_fields) } # /mentors/register/ class MentorsRegister(Resource): def post(self): #global user parser = reqparse.RequestParser() parser.add_argument('u_name', required=True, help="请输入用户名") parser.add_argument('u_password', required=True, help="请输入密码") parser.add_argument('l_id', required=True, help="请输入lab_id") args = parser.parse_args() #users = args.get("user") #action = args.get("action") u_name = args.get("u_name") u_password = args.get("u_password") l_id = args.get("l_id") #global data data = { "status": 201, "msg": 'mentor register ok' } user = Mentors() # 如果重复注册 if user.query.filter(Mentors.mentor_name.__eq__(u_name)).one_or_none(): data['status'] = 403 data['msg'] = 'mentor has already registered' return data else: # register_mentors(user, u_name, u_password) user.mentor_name = u_name # 最终方法密码做数据安全处理 user.mentor_password = user.men_password(u_password) user.lab_id = l_id user.save() data['data'] = user return marshal(data, response_mentors_token_fields) # eg. curl http://localhost:5000/mentors/register/ def get(self): return marshal(data, response_mentors_token_fields) # /mentors/login/ class MentorsLogin(Resource): def post(self): parser = reqparse.RequestParser() parser.add_argument('u_name', required=True, help="请输入用户名") parser.add_argument('u_password', required=True, help="请输入密码") global user args = parser.parse_args() #users = args.get("user") #action = args.get("action") u_name = args.get("u_name") u_password = args.get("u_password") global data data = { "status": 201, "msg": 'mentor login ok' } #token = request.args.get("token") #if token: #abort(401, message="User has already login.") #else: user = Mentors.query.filter(Mentors.mentor_name.__eq__(u_name)).one_or_none() #login_mentors(user, u_password) if user: # 如果用户存在 # 如果用户已经登录 if user.is_login: data['status'] = 403 data['msg'] = 'mentor is login' return data # 如果密码错误 if not user.verify_password(u_password): data['status'] = 406 data['msg'] = 'password fail' return data # 如果用户已被删除 elif user.is_delete: data['status'] = 900 data['msg'] = 'mentor is deleted' return data else: g.user = user # 赋给全局 data['data'] = user # 生成token token = user.generate_auth_token(600) # token = str(uuid.uuid4()) # token 需要转换为字符串 # 将用户token 存到缓存中可以根据token 找到用户id 也可以根据用户id 找到token # key: 使用token 值:用户id # 第一个参数是键，这个主要是用来获取这个缓存的值。第二个参数是值。第三个参数是秒 cache.set(token, user.mentor_id, timeout=60*60*24*7) if not cache.get(token): abort(403, message="fail to set token") data['token'] = token user.is_login = True user.save() return marshal(data, response_mentors_token_fields) else: data['status'] = 406 data['msg'] = 'mentor not exist' #return data data['data'] = user return marshal(data, response_mentors_token_fields) #eg. curl http://localhost:5000/mentors/register/ def get(self): return marshal(data, response_mentors_token_fields) # /mentors/<int:id>/ class MentorUser(Resource): # 根据 id 获取用户信息 @authm.login_required @marshal_with(response_mentors_fields) def get(self, id): user = Mentors.query.get(id) data = { "status": 200, "msg": 'ok', 'data': user, } return data # 根据 id 修改用户信息 --> 密码修改 @authm.login_required @marshal_with(response_mentors_fields) def post(self, id): parser = reqparse.RequestParser() #parser.add_argument('u_password', required=True, help="请输入原密码") #parser.add_argument('u_new_password', required=True, help="请输入修改后的密码") parser.add_argument('u_password', required=True, help="请输入密码") args = parser.parse_args() u_password = args.get("u_password") #u_new_password = args.get("u_new_password") user = Mentors.query.get(id) # 根据id获得用户 #if user.mentor_password is not u_password: # abort(401, message="user not login") user.mentor_password = user.men_password(u_password) user.save() data = { "status": 200, "msg": 'password change ok', 'data': user } return data # 根据 id 删除某个用户 Model中应该设计一个字段 is_delete 来判断是否已删除 @authm.login_required @marshal_with(response_mentors_fields) def delete(self, id): user = Mentors.query.get(id) user.is_delete = True # is_delete = 1 表示删除用户 user.save() data = { "status": 200, "msg": 'delete ok', "data": user } return data ''' # /mentors/<int:id>/givepermission/<int:lab_id>/<int:s_id>/ #验证： #检查Mentors已登录，检查拥有lab的权限，给予学生权限 class Mentorsgivepermission(Resource): @authm.login_required def get(self, id): data = { "status": 201, "msg": 'ok' } user = Mentors.query.get(id) # 如果id不存在 if not Mentors.query.filter(Mentors.mentor_id.__eq__(id)).one_or_none(): data['status'] = 900 data['msg'] = 'mentor is deleted' return data # 如果用户还没登录 elif user.is_login == 0: data['status'] = 403 data['msg'] = 'please login first' return data # 用户登录了可以正常logout else: user.is_login = 0 user.save() return data ''' # /mentors/<int:id>/logout/ class MentorsLogout(Resource): @authm.login_required def get(self, id): data = { "status": 201, "msg": 'mentor logout ok' } user = Mentors.query.get(id) # 如果id不存在 if not Mentors.query.filter(Mentors.mentor_id.__eq__(id)).one_or_none(): data['status'] = 900 data['msg'] = 'mentor is deleted' return data # 如果用户还没登录 elif user.is_login == 0: data['status'] = 403 data['msg'] = 'please login first' return data # 只能操作自己的账号 # 用户登录了可以正常logout else: user.is_login = 0 user.save() return data # —————————————————————————— Students 注册和登录—————————————————————————————— # students_fields = { 'student_id': fields.Integer, 'student_name': fields.String, 'lab_id': fields.Integer #'student_permission': fields.Integer, } # 外层输出参数格式化 response_students_fields = { 'status': fields.Integer, 'msg': fields.String, 'data': fields.Nested(students_fields) } # 外层输出参数格式化 + token response_students_token_fields = { 'status': fields.Integer, 'msg': fields.String, 'token': fields.String, 'data': fields.Nested(students_fields) } # /students/register/ class StudentsRegister(Resource): @authm.login_required def post(self): #global user parser = reqparse.RequestParser() parser.add_argument('u_name', required=True, help="请输入用户名") parser.add_argument('u_password', required=True, help="请输入密码") parser.add_argument('l_id', required=True, help="请输入lab_id") args = parser.parse_args() #users = args.get("user") #action = args.get("action") u_name = args.get("u_name") u_password = args.get("u_password") l_id = args.get("l_id") #global data data = { "status": 201, "msg": 'student register ok' } user = Students() # 防止重复注册 if user.query.filter(Students.student_name.__eq__(u_name)).one_or_none(): data['status'] = 403 data['msg'] = 'student has already registered' return data else: # register_students(user, u_name, u_password) user.student_name = u_name # 密码做数据安全处理 user.student_password = user.stu_password(u_password) user.lab_id = l_id user.save() data['data'] = user return marshal(data, response_students_token_fields) # eg. curl http://localhost:5000/students/register/ def get(self): return marshal(data, response_students_token_fields) # /students/login/ class StudentsLogin(Resource): def post(self): parser = reqparse.RequestParser() parser.add_argument('u_name', required=True, help="请输入用户名") parser.add_argument('u_password', required=True, help="请输入密码") global user args = parser.parse_args() #users = args.get("user") #action = args.get("action") u_name = args.get("u_name") u_password = args.get("u_password") global data data = { "status": 201, "msg": 'student login ok' } #token = request.args.get("token") #if token: #abort(401, message="User has already login.") #else: user = Students.query.filter(Students.student_name.__eq__(u_name)).one_or_none() #login_students(user, u_password) if user: # 如果用户存在 # 如果用户已经登录 if user.is_login: data['status'] = 403 data['msg'] = 'student is login' return data # 如果密码错误 if not user.verify_password(u_password): data['status'] = 406 data['msg'] = 'password fail' return data # 如果用户已被删除 elif user.is_delete: data['status'] = 900 data['msg'] = 'student is deleted' return data else: g.user = user # 赋给全局 data['data'] = user token = user.generate_auth_token(600) #生成token # token = str(uuid.uuid4()) # token 需要转换为字符串 # 将用户token 存到缓存中可以根据token 找到用户id 也可以根据用户id 找到token # key: 使用token 值:用户id # 第一个参数是键，这个主要是用来获取这个缓存的值。第二个参数是值。第三个参数是秒 #cache.set(token, user.student_id, timeout=60*60*24*7) #if not cache.get(token): # abort(403, message="fail to set token") data['token'] = token user.is_login = True user.save() return marshal(data, response_students_token_fields) # 如果用户不存在 else: data['status'] = 406 data['msg'] = 'student not exist' #return data data['data'] = user return marshal(data, response_students_token_fields) #eg. curl http://localhost:5000/students/register/ def get(self): return marshal(data, response_students_token_fields) # /students/<int:id>/ class StudentUser(Resource): # 根据 id 获取用户信息 @auths.login_required @marshal_with(response_students_fields) def get(self, id): user = Students.query.get(id) data = { "status": 200, "msg": 'ok', 'data': user, } return data # 根据 id 修改用户信息 --> 密码修改 @auths.login_required @marshal_with(response_students_fields) def post(self, id): parser = reqparse.RequestParser() parser.add_argument('u_password', required=True, help="请输入修改后的密码") args = parser.parse_args() u_password = args.get("u_password") user = Students.query.get(id) # 根据id获得用户 user.student_password = user.stu_password(u_password) user.save() data = { "status": 200, "msg": 'password change ok', 'data': user } return data # 根据 id 删除某个用户 Model中设计一个字段 is_delete 来判断是否已删除 @auths.login_required @marshal_with(response_students_fields) def delete(self, id): user = Students.query.get(id) user.is_delete = True # is_delete = 1 表示删除用户 user.save() data = { "status": 200, "msg": 'delete ok', "data": user } return data # /students/<int:id>/logout/ class StudentsLogout(Resource): @auths.login_required def get(self, id): data = { "status": 201, "msg": 'student logout ok' } user = Students.query.get(id) # 如果id不存在 if not Students.query.filter(Students.student_id.__eq__(id)).one_or_none(): data['status'] = 900 data['msg'] = 'student is deleted' return data # 如果用户还没登录 elif user.is_login == 0: data['status'] = 403 data['msg'] = 'please login first' return data # 用户登录了可以正常logout else: user.is_login = 0 user.save() return data """ def login_mentors(user, u_password): if user: if not user.verify_password(u_password): data['status'] = 406 data['msg'] = 'password fail' return data elif user.is_delete: data['status'] = 900 data['msg'] = 'user is deleted' return data else: data['data'] = user token = user.generate_auth_token(600) #token = str(uuid.uuid4()) # token 需要转换为字符串 # 将用户token 存到缓存中可以根据token 找到用户id 也可以根据用户id 找到token # key: 使用token 值:用户id # 第一个参数是键，这个主要是用来获取这个缓存的值。第二个参数是值。第三个参数是秒 #cache.set(token, user.mentor_id, timeout=60*60*24*7) #if not cache.get(token): # abort(403, message="fail to set token") data['token'] = token return marshal(data, response_mentors_token_fields) else: data['status'] = 406 data['msg'] = 'user not exist' return data def register_mentors(user, u_name, u_password): user.mentor_name = u_name # 密码做数据安全处理 # user.set_password(u_password) # 最终方法密码做数据安全处理 user.mentor_password = user.men_password(u_password) user.save() # 用户注册登录操作其中密码做了数据安全 class UsersResource(Resource): def post(self): global user args = parser.parse_args() users = args.get("user") action = args.get("action") u_name = args.get("u_name") u_password = args.get("u_password") global data data = { "status": 201, "msg": 'ok' } if users == "mentors": #def login(User, u_name, u_password, data) if action == "login": # 用户登录 token = request.args.get("token") if token: abort(401, message="User has already login.") else: user = Mentors.query.filter(Mentors.mentor_name.__eq__(u_name)).one_or_none() login_mentors(user, u_password) elif action == "register": # 用户注册 #def register(User, u_name, u_password) user = Mentors() register_mentors(user, u_name, u_password) # elif action == "logout": # 用户登出 # user = Mentors() # cache. else: pass data['data'] = user return marshal(data, response_mentors_token_fields) #return data def get(self): return marshal(data, response_mentors_token_fields) # 更新用户信息不更改用户名，只改密码 parser_user = reqparse.RequestParser() parser_user.add_argument('u_password', required=True, help='请输入新密码') # 单个用户数据操作查询修改删除 class UserResource(Resource): # 根据 id 获取用户信息 @marshal_with(response_user_fields) def get(self, id): user = User.query.get(id) data = { "status": 200, "msg": 'ok', 'data': user, } return data # 根据 id 修改用户信息 --> 密码修改 @marshal_with(response_user_fields) def post(self, id): args = parser_user.parse_args() u_password = args.get("u_password") user = User.query.get(id) user.u_password = u_password user.save() data = { "status": 200, "msg": 'password change ok', 'data': user, } return data # 根据 id 删除某个用户 Model中应该设计一个字段 is_delete 来判断是否已删除 @marshal_with(response_user_fields) def delete(self, id): user = User.query.get(id) user.is_delete = True # is_delete = 1 表示删除用户 user.save() data = { "status": 200, "msg": 'delete ok', "data": user, } return data """

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Python

bcselector/tests/no_cost_based_filter_methods_test.py

Kaketo/bc-selector

c7acd1033bee741530735fb601f9e464c3ccc26f

[ "MIT" ]

5

2020-03-30T17:36:11.000Z

2021-06-16T09:14:20.000Z

bcselector/tests/no_cost_based_filter_methods_test.py

Kaketo/bc-selector

c7acd1033bee741530735fb601f9e464c3ccc26f

[ "MIT" ]

6

2020-04-28T16:32:04.000Z

2020-12-18T13:35:28.000Z

bcselector/tests/no_cost_based_filter_methods_test.py

Kaketo/bc-selector

c7acd1033bee741530735fb601f9e464c3ccc26f

[ "MIT" ]

2

2020-04-28T15:59:51.000Z

2020-05-14T08:11:33.000Z

import unittest import numpy as np from bcselector.filter_methods.no_cost_based_filter_methods import no_cost_find_best_feature from bcselector.information_theory.j_criterion_approximations import mim, mifs, mrmr, jmi, cife class TestNoCostMethod(unittest.TestCase): def test_simple_input_mim(self): integer_matrix = np.random.randint(0,10,(100,10)) diverse_target = np.random.randint(0,10,(100)) candidates_index = [0,1,2,6,7,8,9] costs = [ 1.76, 0.19, -0.36, 0.96, 0.41, 0.17, -0.36, 0.75, 0.79, -1.38] selected_feature, criterion_value, cost = no_cost_find_best_feature( j_criterion_func=mim, data=integer_matrix, target_variable=diverse_target, possible_variables_index=candidates_index, costs=costs) self.assertIsInstance(selected_feature,int) self.assertIsInstance(criterion_value, float) self.assertIsInstance(cost, float) def test_simple_input_mifs(self): integer_matrix = np.random.randint(0,10,(100,10)) diverse_target = np.random.randint(0,10,(100)) prev_variables_index = [3,4,5] candidates_index = [0,1,2,6,7,8,9] costs = [ 1.76, 0.19, -0.36, 0.96, 0.41, 0.17, -0.36, 0.75, 0.79, -1.38] beta = 10 selected_feature, criterion_value, cost = no_cost_find_best_feature( j_criterion_func=mifs, data=integer_matrix, target_variable=diverse_target, possible_variables_index=candidates_index, costs=costs, prev_variables_index=prev_variables_index, beta=beta) self.assertIsInstance(selected_feature,int) self.assertIsInstance(criterion_value, float) self.assertIsInstance(cost, float) def test_simple_input_mifs_no_beta_provided(self): integer_matrix = np.random.randint(0,10,(100,10)) diverse_target = np.random.randint(0,10,(100)) prev_variables_index = [3,4,5] candidates_index = [0,1,2,6,7,8,9] costs = [ 1.76, 0.19, -0.36, 0.96, 0.41, 0.17, -0.36, 0.75, 0.79, -1.38] with self.assertWarns(Warning): no_cost_find_best_feature( j_criterion_func=mifs, data=integer_matrix, target_variable=diverse_target, possible_variables_index=candidates_index, costs=costs, prev_variables_index=prev_variables_index) def test_simple_input_mrmr(self): integer_matrix = np.random.randint(0,10,(100,10)) diverse_target = np.random.randint(0,10,(100)) prev_variable_index = [3,4,5] candidates_index = [0,1,2,6,7,8,9] costs = [ 1.76, 0.19, -0.36, 0.96, 0.41, 0.17, -0.36, 0.75, 0.79, -1.38] selected_feature, criterion_value, cost = no_cost_find_best_feature( j_criterion_func=mrmr, data=integer_matrix, target_variable=diverse_target, possible_variables_index=candidates_index, costs=costs, prev_variables_index=prev_variable_index) self.assertIsInstance(selected_feature,int) self.assertIsInstance(criterion_value, float) self.assertIsInstance(cost, float) def test_simple_input_jmi(self): integer_matrix = np.random.randint(0,10,(100,10)) diverse_target = np.random.randint(0,10,(100)) prev_variable_index = [3,4,5] candidates_index = [0,1,2,6,7,8,9] costs = [ 1.76, 0.19, -0.36, 0.96, 0.41, 0.17, -0.36, 0.75, 0.79, -1.38] selected_feature, criterion_value, cost = no_cost_find_best_feature( j_criterion_func=jmi, data=integer_matrix, target_variable=diverse_target, possible_variables_index=candidates_index, costs=costs, prev_variables_index=prev_variable_index) self.assertIsInstance(selected_feature,int) self.assertIsInstance(criterion_value, float) self.assertIsInstance(cost, float) def test_simple_input_cife(self): integer_matrix = np.random.randint(0,10,(100,10)) diverse_target = np.random.randint(0,10,(100)) prev_variable_index = [3,4,5] candidates_index = [0,1,2,6,7,8,9] costs = [ 1.76, 0.19, -0.36, 0.96, 0.41, 0.17, -0.36, 0.75, 0.79, -1.38] beta = 10 selected_feature, criterion_value, cost = no_cost_find_best_feature( j_criterion_func=cife, data=integer_matrix, target_variable=diverse_target, possible_variables_index=candidates_index, costs=costs, prev_variables_index=prev_variable_index, beta=beta) self.assertIsInstance(selected_feature,int) self.assertIsInstance(criterion_value, float) self.assertIsInstance(cost, float) def test_simple_input_cife_no_beta_provided(self): integer_matrix = np.random.randint(0,10,(100,10)) diverse_target = np.random.randint(0,10,(100)) prev_variables_index = [3,4,5] candidates_index = [0,1,2,6,7,8,9] costs = [ 1.76, 0.19, -0.36, 0.96, 0.41, 0.17, -0.36, 0.75, 0.79, -1.38] with self.assertWarns(Warning): no_cost_find_best_feature( j_criterion_func=cife, data=integer_matrix, target_variable=diverse_target, possible_variables_index=candidates_index, costs=costs, prev_variables_index=prev_variables_index) if __name__ == '__main__': unittest.main()

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c5af2a4ea139f56feadad760a33ca1a6cd5de562

47

py

Python

src/socialite/strategy/__init__.py

garzola/masonite-socialite

70cb80365e2096773e291f84b6e7af81a276ac1b

[ "MIT" ]

13

2020-02-02T01:27:51.000Z

2021-11-08T08:50:57.000Z

src/socialite/strategy/__init__.py

garzola/masonite-socialite

70cb80365e2096773e291f84b6e7af81a276ac1b

[ "MIT" ]

17

2020-02-05T16:52:45.000Z

2021-05-16T14:34:46.000Z

src/socialite/strategy/__init__.py

garzola/masonite-socialite

70cb80365e2096773e291f84b6e7af81a276ac1b

[ "MIT" ]

6

2020-02-03T14:20:30.000Z

2021-03-18T01:33:21.000Z

from .MasoniteStrategy import MasoniteStrategy

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a8667d764c57992453d915792f8fed96deae1798

203

py

Python

rulesets/models/__init__.py

jdr-tools/rulesets

2bbfb280c84da6ef359d47fa6c24d34b84814eeb

[ "MIT" ]

null

rulesets/models/__init__.py

jdr-tools/rulesets

2bbfb280c84da6ef359d47fa6c24d34b84814eeb

[ "MIT" ]

3

2018-12-19T08:16:15.000Z

2018-12-19T08:16:47.000Z

rulesets/models/__init__.py

jdr-tools/rulesets

2bbfb280c84da6ef359d47fa6c24d34b84814eeb

[ "MIT" ]

null

import pymodm, os from rulesets.models.account import Account from rulesets.models.ruleset import Ruleset from rulesets.models.session import Session pymodm.connection.connect(os.getenv('MONGODB_URL'))

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7

a876fc0a3fcf244833f7c61dc5bd2a3382710e65

18,131

py

Python

load_functions.py

adambrzosko/ml-htt-methods

5378b4a9747ea21702c7a48e5f3cbb4fc75a71fc

[ "MIT" ]

null

load_functions.py

adambrzosko/ml-htt-methods

5378b4a9747ea21702c7a48e5f3cbb4fc75a71fc

[ "MIT" ]

null

load_functions.py

adambrzosko/ml-htt-methods

5378b4a9747ea21702c7a48e5f3cbb4fc75a71fc

[ "MIT" ]

1

2022-01-31T14:54:33.000Z

import uproot import os import pandas as pd import numpy as np def load_mc_ntuple(data, tree, branch, mjj_training, channel, cut_feats, apply_cuts, split_by_sample, signal, embedding, ff): # LOAD MC NTUPLES AND APPLY BASELINE CUTS BY CHANNEL # need to do something for when df too large.. try: iterator = uproot.iterate(data, tree, branches=branch+cut_feats) except IOError: print 'Tree/Branches not found' df = [] try: for block in iterator: df_b = pd.DataFrame(block) if apply_cuts: if channel == 'tt': df_b = df_b[ (df_b['pt_1'] > 40) & (df_b['deepTauVsJets_medium_1'] > 0.5) & (df_b['deepTauVsJets_medium_2'] > 0.5) & (df_b['deepTauVsEle_vvvloose_1'] > 0.5) & (df_b['deepTauVsMu_vloose_1'] > 0.5) & (df_b['deepTauVsEle_vvvloose_2'] > 0.5) & (df_b['deepTauVsMu_vloose_2'] > 0.5) & (df_b['leptonveto'] == False) & (df_b['trg_doubletau'] == True) ] elif channel == 'mt': df_b = df_b[ (df_b['iso_1'] < 0.15) & (df_b['mt_1'] < 40) # was 70 but use 40 & (df_b['mva_olddm_tight_2'] > 0.5) & (df_b['antiele_2'] == True) & (df_b['antimu_2'] == True) & (df_b['leptonveto'] == False) & (df_b['pt_2'] > 20) & ((df_b['trg_singlemuon']*df_b['pt_1'] > 23) | (df_b['trg_mutaucross']*df_b['pt_1'] < 23)) ] elif channel == 'et': df_b = df_b[ (df_b['iso_1'] < 0.1) & (df_b['mt_1'] < 40) & (df_b['mva_olddm_tight_2'] > 0.5) & (df_b['antiele_2'] == True) & (df_b['antimu_2'] == True) & (df_b['leptonveto'] == False) & (df_b['pt_2'] > 20) & (df_b['trg_singleelectron'] == True) ] elif channel == 'em': df_b = df_b[ (df_b['iso_1'] < 0.15) & (df_b['iso_2'] < 0.2) & (df_b['pzeta'] > -50) & (df_b['leptonveto'] == False) & (df_b['trg_muonelectron'] == True) ] else: assert ValueError('Channel not in ["tt", "mt", "et", "em"]') # if not embedding and not signal: # if channel == 'tt': # df_b = df_b[ # ~((df_b['gen_match_1'] == 5) # & (df_b['gen_match_2'] == 5))] # elif channel == 'mt': # df_b = df_b[ # ~((df_b['gen_match_1'] == 4) # & (df_b['gen_match_2'] == 5))] # elif channel == 'et': # df_b = df_b[ # ~((df_b['gen_match_1'] == 3) # & (df_b['gen_match_2'] == 5))] # elif channel == 'em': # df_b = df_b[ # ~((df_b['gen_match_1'] == 3) # & (df_b['gen_match_2'] == 4))] if ff and not signal: if channel == 'tt': df_b = df_b[ ~((df_b['gen_match_1'] == 6) | (df_b['gen_match_2'] == 6))] elif channel in ['et','mt']: df_b = df_b[df_b['gen_match_2'] < 6] ## TO SELECT THE SIGNAL SAMPLE ACCORDING TO ## CUTS APPLIED RELATING TO n_jets AND mjj if not split_by_sample: df_b = df_b else: if mjj_training == 'low': df_b = df_b[ (df_b['n_jets'] < 2) | ((df_b['n_jets'] >= 2) & (df_b['mjj'] < 300)) ] elif mjj_training == 'high': df_b = df_b[ ((df_b['n_jets'] >= 2) & (df_b['mjj'] > 300)) ] else: assert ValueError('Mjj training not in ["low", "high"]') df_b = df_b[(df_b['m_sv'] > 0)] ## SOME m_sv ARE MISSING df_b = df_b.drop(cut_feats, axis=1) df.append(df_b) df = pd.concat(df, ignore_index=True) except IndexError: print 'zero events in ntuple' return df def load_data_ntuple(data, tree, branch, mjj_training, channel, cut_feats, apply_cuts, split_by_sample): ## THIS FUNCTION IS FOR READING IN SAME SIGN DATA (FOR mt, et, em CHANNELS) ## OR ANTIISOLATED (FOR tt CHANNEL) FOR THE QCD ESTIMATION try: iterator = uproot.iterate(data, tree, branches=branch+cut_feats) except IOError: print 'Tree/Branches not found' df = [] for block in iterator: df_b = pd.DataFrame(block) if apply_cuts: if channel == 'tt': df_b = df_b[ (df_b['pt_1'] > 40) & ((df_b['mva_olddm_loose_1'] > 0.5) & (df_b['mva_olddm_tight_1'] < 0.5) & (df_b['mva_olddm_medium_2'] > 0.5)) | ((df_b['mva_olddm_loose_2'] > 0.5) & (df_b['mva_olddm_tight_2'] < 0.5) & (df_b['mva_olddm_medium_1'] > 0.5)) & (df_b['antiele_1'] == True) & (df_b['antimu_1'] == True) & (df_b['antiele_2'] == True) & (df_b['antimu_2'] == True) & (df_b['leptonveto'] == False) & (df_b['trg_doubletau'] == True) ] elif channel == 'mt': df_b = df_b[ (df_b['iso_1'] < 0.15) & (df_b['mt_1'] < 40) & (df_b['mva_olddm_tight_2'] > 0.5) & (df_b['antiele_2'] == True) & (df_b['antimu_2'] == True) & (df_b['leptonveto'] == False) & (df_b['pt_2'] > 20) & ((df_b['trg_singlemuon']*df_b['pt_1'] > 23) | (df_b['trg_mutaucross']*df_b['pt_1'] < 23)) & (df_b['os'] == False) ] elif channel == 'et': df_b = df_b[ (df_b['iso_1'] < 0.1) & (df_b['mt_1'] < 40) & (df_b['mva_olddm_tight_2'] > 0.5) & (df_b['antiele_2'] == True) & (df_b['antimu_2'] == True) & (df_b['leptonveto'] == False) & (df_b['pt_2'] > 20) & (df_b['trg_singleelectron'] == True) & (df_b['os'] == False) ] elif channel == 'em': df_b = df_b[ (df_b['iso_1'] < 0.15) & (df_b['iso_2'] < 0.2) & (df_b['pzeta'] > -50) & (df_b['leptonveto'] == False) & (df_b['trg_muonelectron'] == True) & (df_b['os'] == False) ] else: assert ValueError('Channel not in ["tt", "mt", "et", "em"]') ## TO SELECT THE SIGNAL SAMPLE ACCORDING TO ## CUTS APPLIED RELATING TO n_jets AND mjj if not split_by_sample: df_b = df_b else: if mjj_training == 'low': df_b = df_b[ (df_b['n_jets'] < 2) | ((df_b['n_jets'] >= 2) & (df_b['mjj'] < 300)) ] elif mjj_training == 'high': df_b = df_b[ ((df_b['n_jets'] >= 2) & (df_b['mjj'] > 300)) ] else: assert ValueError('Mjj training not in ["low", "high"]') df_b = df_b[(df_b['m_sv'] > 0)] ## SOME m_sv ARE MISSING df_b = df_b.drop(cut_feats, axis=1) df.append(df_b) df = pd.concat(df, ignore_index=True) return df def load_ff_ntuple(data, tree, branch, mjj_training, channel, cut_feats, apply_cuts, split_by_sample): try: iterator = uproot.iterate(data, tree, branches=branch+cut_feats) except IOError: print 'Tree/Branches not found' df = [] for block in iterator: df_b = pd.DataFrame(block) if apply_cuts: if channel == 'tt': df_b_tt = [] # df_b_1 = df_b[ # (df_b['pt_1'] > 40) # & ((df_b['mva_olddm_tight_1'] < 0.5) # & (df_b['mva_olddm_vloose_1'] > 0.5) # & (df_b['mva_olddm_tight_2'] > 0.5)) # & (df_b['antiele_1'] == True) # & (df_b['antimu_1'] == True) # & (df_b['antiele_2'] == True) # & (df_b['antimu_2'] == True) # & (df_b['leptonveto'] == False) # & (df_b['trg_doubletau'] == True) # ] # df_b_1["wt"] = df_b_1["wt_ff_1"] # df_b_tt.append(df_b_1) # df_b_2 = df_b[ # (df_b['pt_1'] > 40) # & ((df_b['mva_olddm_tight_2'] < 0.5) # & (df_b['mva_olddm_vloose_2'] > 0.5) # & (df_b['mva_olddm_tight_1'] > 0.5)) # & (df_b['antiele_1'] == True) # & (df_b['antimu_1'] == True) # & (df_b['antiele_2'] == True) # & (df_b['antimu_2'] == True) # & (df_b['leptonveto'] == False) # & (df_b['trg_doubletau'] == True) # ] # df_b_2["wt"] = df_b_2["wt_ff_2"] # df_b_tt.append(df_b_2) # new ffs with deeptau df_b = df_b[ (df_b['pt_1'] > 40) & ((df_b['deepTauVsJets_medium_1'] < 0.5) & (df_b['deepTauVsJets_vvvloose_1'] > 0.5) & (df_b['deepTauVsJets_medium_2'] > 0.5)) & (df_b['deepTauVsEle_vvvloose_1'] > 0.5 ) & (df_b['deepTauVsMu_vloose_1'] > 0.5 ) & (df_b['deepTauVsEle_vvvloose_2'] > 0.5 ) & (df_b['deepTauVsMu_vloose_2'] > 0.5 ) & (df_b['leptonveto'] == False) & (df_b['trg_doubletau'] == True) ] df_b["wt"] = df_b["wt_ff_dmbins_1"] elif channel == 'mt': df_b = df_b[ (df_b['iso_1'] < 0.15) & (df_b['mt_1'] < 40) & (df_b['mva_olddm_tight_2'] < 0.5) & (df_b['mva_olddm_vloose_2'] > 0.5) & (df_b['antiele_2'] == True) & (df_b['antimu_2'] == True) & (df_b['leptonveto'] == False) & (df_b['pt_2'] > 20) & ((df_b['trg_singlemuon']*df_b['pt_1'] > 23) | (df_b['trg_mutaucross']*df_b['pt_1'] < 23)) ] df_b["wt"] = df_b["wt_ff_1"] elif channel == 'et': df_b = df_b[ (df_b['iso_1'] < 0.1) & (df_b['mt_1'] < 40) & (df_b['mva_olddm_tight_2'] < 0.5) & (df_b['mva_olddm_vloose_2'] > 0.5) & (df_b['antiele_2'] == True) & (df_b['antimu_2'] == True) & (df_b['leptonveto'] == False) & (df_b['pt_2'] > 20) & (df_b['trg_singleelectron'] == True) ] df_b["wt"] = df_b["wt_ff_1"] else: assert ValueError('Channel not in ["tt", "mt", "et"]') ## TO SELECT THE SIGNAL SAMPLE ACCORDING TO ## CUTS APPLIED RELATING TO n_jets AND mjj if not split_by_sample: df_b = df_b else: if mjj_training == 'low': df_b = df_b[ (df_b['n_jets'] < 2) | ((df_b['n_jets'] >= 2) & (df_b['mjj'] < 300)) ] elif mjj_training == 'high': df_b = df_b[ ((df_b['n_jets'] >= 2) & (df_b['mjj'] > 300)) ] else: assert ValueError('Mjj training not in ["low", "high"]') df_b = df_b[(df_b['m_sv'] > 0)] ## SOME m_sv ARE MISSING df_b = df_b.drop(cut_feats, axis=1) df.append(df_b) df = pd.concat(df, ignore_index=True) return df def load_rhoID_ntuple(data, tree, branch, channel, cut_feats, apply_cuts): # LOAD MC NTUPLES AND APPLY BASELINE CUTS BY CHANNEL # need to do something for when df too large.. try: iterator = uproot.iterate(data, tree, branches=branch+cut_feats) except IOError: print 'Tree/Branches not found' df1 = [] df2 = [] try: for block in iterator: df_b1 = pd.DataFrame(block) df_b2 = pd.DataFrame(block) if apply_cuts: if channel == 'tt': df_b1 = df_b1[ (df_b1['pt_1'] > 40) & (df_b1['mva_olddm_tight_1'] > 0.5) & (df_b1['antiele_1'] == True) & (df_b1['antimu_1'] == True) & (df_b1['leptonveto'] == False) & (df_b1['trg_doubletau'] == True) & (df_b1['tau_decay_mode_1'] == 1) ] df_b2 = df_b2[ (df_b2['pt_1'] > 40) & (df_b2['mva_olddm_tight_2'] > 0.5) & (df_b2['antiele_2'] == True) & (df_b2['antimu_2'] == True) & (df_b2['leptonveto'] == False) & (df_b2['trg_doubletau'] == True) & (df_b2['tau_decay_mode_2'] == 1) ] else: assert ValueError('Channel not "tt"') df_b1 = df_b1.drop(cut_feats, axis=1) df1.append(df_b1) df_b2 = df_b2.drop(cut_feats, axis=1) df2.append(df_b2) except IndexError: print 'zero events in ntuple' df1 = pd.concat(df1, ignore_index=True) df2 = pd.concat(df2, ignore_index=True) return df1, df2 def load_noisejets_ntuple(data, tree, branch, channel, cut_feats, apply_cuts): # LOAD MC NTUPLES AND APPLY BASELINE CUTS BY CHANNEL # need to do something for when df too large.. try: iterator = uproot.iterate(data, tree, branches=branch+cut_feats) except IOError: print 'Tree/Branches not found' df1 = [] try: for block in iterator: df_b1 = pd.DataFrame(block) df_b2 = pd.DataFrame(block) if apply_cuts: if channel == 'zmm': # only train on zmm df_b1 = df_b1[ (df_b1['pt_1'] > 25) & (df_b1['iso_1'] < 0.15) & (df_b1['iso_2'] < 0.15) & (df_b1['trg_singlemuon'] == True) & ((df_b1["jpt_1"]/df_b1["pt_vis"]) > 0.5) & ((df_b1["jpt_1"]/df_b1["pt_vis"]) < 1.5) & ((df_b1["jpt_1"]) < 100) & (np.abs(df_b1["jeta_1"]) > 2.65) & (np.abs(df_b1["jeta_1"]) < 3.139) # & (df_b1["n_jets"] == 1) ] else: assert ValueError('Channel not "zmm"') df_b1 = df_b1.drop(cut_feats, axis=1) df1.append(df_b1) except IndexError: print 'zero events in ntuple' df1 = pd.concat(df1, ignore_index=True) return df1 def load_files(filelist): with open(filelist) as f: files = f.read().splitlines() file_names = [os.path.splitext(os.path.basename(file))[0] for file in files] return file_names

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null

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1

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8

a8991ab5d7325e00ce2a7a52857ca1761e3c97c6

10,300

py

Python

scripts/move-prediction/plot.py

dsmic/oakfoam

f4093d57ea173d5dc00e0f6031ed16f169258456

[ "BSD-2-Clause" ]

2

2019-08-27T04:18:45.000Z

2021-04-20T23:14:24.000Z

scripts/move-prediction/plot.py

dsmic/oakfoam

f4093d57ea173d5dc00e0f6031ed16f169258456

[ "BSD-2-Clause" ]

null

scripts/move-prediction/plot.py

dsmic/oakfoam

f4093d57ea173d5dc00e0f6031ed16f169258456

[ "BSD-2-Clause" ]

null

#!/usr/bin/env python # Read in a list of move prediction results and plot the results. # The input file format is JSON (see plot_example.json). import sys import math import numpy as np import json import csv import matplotlib import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import axes3d from matplotlib import cm jd = json.loads("".join(sys.stdin.readlines())) plottype = jd['type'] if plottype == 'move-prediction': # 2d move prediction fig = plt.figure() fig.canvas.set_window_title(jd['title']) plt.title(jd['title']) plt.xlabel('Move Rank') plt.ylabel('Cumulative Probability') plt.grid(True) plt.ylim(0,1) xmin = 1 xmax = 50 if 'xmax' in jd.keys(): xmax = int(jd['xmax']) plt.xlim(xmin,xmax) plt.yticks(np.append(np.arange(0,1,0.05),1)) plt.xticks(np.append(np.arange(xmin,xmax),xmax)) errk = 0.0 if 'errk' in jd.keys(): errk = float(jd['errk']) table = [] table.append(range(xmin,xmax+1)) tablelabels = [] tablelabels.append('Move Rank') c = 0 for f in jd['data']: with open(f['file'], 'rb') as csvfile: x = [] y = [] z = [] reader = csv.reader(csvfile) for row in reader: x.append(float(row[0])) y.append(float(row[1])) z.append(float(row[2])) err = [] err1 = [] err2 = [] for i in range(len(x)): if errk>0: e = errk*math.sqrt(y[i]*(1-y[i])/z[i]) else: e = 0 err.append(e) err1.append(y[i]+e) err2.append(y[i]-e) lbl = f['label'] + ' (%.1f%%)' % (y[0]*100) if len(jd['data']) == 1: col = cm.spectral(0) else: col = cm.spectral(c*0.9/(len(jd['data'])-1),1) c+=1 # p = plt.plot(x, z, label = lbl) p = plt.plot(x, y, label = lbl, color = col) # col = p[0].get_color() if errk>0: plt.fill_between(x, err1, err2, alpha = 0.2, color = col) # plt.errorbar(x, z, yerr = err, fmt='.', color = col) td = [] xi = 0 for i in table[0]: while i > x[xi]: xi += 1 td.append(y[xi]) table.append(td) tablelabels.append(lbl) plt.legend(loc=4) sys.stdout.write('# ' + jd['title'] + '\n') tt = len(tablelabels) for i in range(tt): sys.stdout.write('# ' + (' | ')*i + ' '*5 + '+' + ('-'*7)*(tt-i-1) + '- %d: ' % i + tablelabels[i] +'\n') sys.stdout.write('#' + (' |----|')*tt + '\n') for i in range(len(table[0])): sys.stdout.write(' ') for j in range(len(table)): if j == 0: sys.stdout.write(' %6d' % table[j][i]) else: sys.stdout.write(' %6.3f' % table[j][i]) sys.stdout.write('\n') elif plottype == 'stages-mp': # stages of move prediction fig = plt.figure() fig.canvas.set_window_title(jd['title']) plt.title(jd['title']) plt.xlabel('Game Stage Center') plt.ylabel('Move Prediction Accuracy') plt.grid(True) # plt.ylim(0,1) xmin = 0 xmax = 300 stage = 30 if 'xmax' in jd.keys(): xmax = int(jd['xmax']) if 'stage' in jd.keys(): stage = int(jd['stage']) plt.xlim(xmin,xmax) # plt.yticks(np.append(np.arange(0,1,0.02),1)) plt.xticks(np.append(np.arange(xmin,xmax,stage),xmax)) errk = 0.0 if 'errk' in jd.keys(): errk = float(jd['errk']) table = [] # table.append(range(xmin,xmax+1)) table.append(range(xmin+stage/2,xmax+1,stage)) tablelabels = [] tablelabels.append('Center of game stage') c = 0 for f in jd['data']: with open(f['file'], 'rb') as csvfile: x = [] y = [] z = [] reader = csv.reader(csvfile) for row in reader: r0 = float(row[0]) r1 = float(row[1]) r2 = float(row[2]) r3 = float(row[3]) r4 = float(row[4]) r5 = float(row[5]) x.append((r0+r1)/2) y.append(r2) z.append(r4) err = [] err1 = [] err2 = [] for i in range(len(x)): if errk>0: e = errk*math.sqrt(y[i]*(1-y[i])/z[i]) else: e = 0 err.append(e) err1.append(y[i]+e) err2.append(y[i]-e) lbl = f['label'] if len(jd['data']) == 1: col = cm.spectral(0) else: col = cm.spectral(c*0.9/(len(jd['data'])-1),1) c+=1 # p = plt.plot(x, z, label = lbl) p = plt.plot(x, y, label = lbl, color = col) # col = p[0].get_color() if errk>0: plt.fill_between(x, err1, err2, alpha = 0.2, color = col) # plt.errorbar(x, z, yerr = err, fmt='.', color = col) td = [] xi = 0 for i in table[0]: while i > x[xi]: xi += 1 td.append(y[xi]) table.append(td) tablelabels.append(lbl) plt.legend(loc=4) sys.stdout.write('# ' + jd['title'] + '\n') tt = len(tablelabels) for i in range(tt): sys.stdout.write('# ' + (' | ')*i + ' '*5 + '+' + ('-'*7)*(tt-i-1) + '- %d: ' % i + tablelabels[i] +'\n') sys.stdout.write('#' + (' |----|')*tt + '\n') for i in range(len(table[0])): sys.stdout.write(' ') for j in range(len(table)): if j == 0: sys.stdout.write(' %6d' % table[j][i]) else: sys.stdout.write(' %6.3f' % table[j][i]) sys.stdout.write('\n') elif plottype == 'stages-le': # stages of mean log-evidence fig = plt.figure() fig.canvas.set_window_title(jd['title']) plt.title(jd['title']) plt.xlabel('Game Stage Center') plt.ylabel('Mean Log-evidence') plt.grid(True) # plt.ylim(0,1) xmin = 0 xmax = 300 stage = 30 if 'xmax' in jd.keys(): xmax = int(jd['xmax']) if 'stage' in jd.keys(): stage = int(jd['stage']) plt.xlim(xmin,xmax) # plt.yticks(np.append(np.arange(0,1,0.02),1)) plt.xticks(np.append(np.arange(xmin,xmax,stage),xmax)) errk = 0.0 if 'errk' in jd.keys(): errk = float(jd['errk']) c = 0 for f in jd['data']: with open(f['file'], 'rb') as csvfile: x = [] y = [] z = [] reader = csv.reader(csvfile) for row in reader: r0 = float(row[0]) r1 = float(row[1]) r2 = float(row[2]) r3 = float(row[3]) r4 = float(row[4]) r5 = float(row[5]) x.append((r0+r1)/2) y.append(r3) z.append(r5) err = [] err1 = [] err2 = [] for i in range(len(x)): if errk>0: e = errk*math.sqrt(z[i]) else: e = 0 err.append(e) err1.append(y[i]+e) err2.append(y[i]-e) lbl = f['label'] if len(jd['data']) == 1: col = cm.spectral(0) else: col = cm.spectral(c*0.9/(len(jd['data'])-1),1) c+=1 # p = plt.plot(x, z, label = lbl) p = plt.plot(x, y, label = lbl, color = col) # col = p[0].get_color() if errk>0: plt.fill_between(x, err1, err2, alpha = 0.2, color = col) # plt.errorbar(x, z, yerr = err, fmt='.', color = col) plt.legend(loc=4) elif plottype == '3d': # legacy 3d mp plot fig = plt.figure() ax = fig.add_subplot(111, projection='3d') fig.suptitle(jd['title']) ax.set_ylabel('Move Rank') ax.set_zlabel('Cumulative Probability') xmax = 200 if 'xmax' in jd.keys(): xmax = jd['xmax'] X = [] Y = [] Z = [] for f in jd['data']: with open(f['file'], 'rb') as csvfile: x = [] y = [] reader = csv.reader(csvfile) xi = 1 s = 0 for row in reader: rx = float(row[0]) ry = float(row[1]) if rx>xmax: s += ry else: while xi<rx: x.append(xi) y.append(0.0) xi += 1 x.append(rx) y.append(ry) xi += 1 s += sum(y) t = 0.0 z = [] zz = [] for yy in y: t += yy z.append(t/s) zz.append(f['z']) Y.append(x) Z.append(z) X.append(zz) # ax.plot_wireframe(X, Y, Z, color='b', cmap='jet') surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet) fig.colorbar(surf, shrink=0.5, aspect=5) ax.set_zlim(0,1) ax.set_ylim(0,xmax) else: # legacy 2d mp plot fig = plt.figure() fig.canvas.set_window_title(jd['title']) plt.title(jd['title']) plt.xlabel('Move Rank') plt.ylabel('Cumulative Probability') plt.grid(True) plt.ylim(0,1) xmin = 1 xmax = 50 if 'xmax' in jd.keys(): xmax = int(jd['xmax']) plt.xlim(xmin,xmax) plt.yticks(np.append(np.arange(0,1,0.05),1)) plt.xticks(np.append(np.arange(xmin,xmax),xmax)) errk = 0.0 if 'errk' in jd.keys(): errk = float(jd['errk']) table = [] table.append(range(xmin,xmax+1)) tablelabels = [] tablelabels.append('Move Rank') c = 0 for f in jd['data']: with open(f['file'], 'rb') as csvfile: x = [] y = [] reader = csv.reader(csvfile) for row in reader: x.append(float(row[0])) y.append(float(row[1])) s = sum(y) t = 0.0 z = [] err = [] err1 = [] err2 = [] for yy in y: t += yy v = t/s z.append(v) if errk>0: e = errk*math.sqrt(v*(1-v)/s) else: e = 0 err.append(e) err1.append(v+e) err2.append(v-e) lbl = f['label'] + ' (%.1f%%)' % (z[0]*100) col = cm.spectral(c*0.9/(len(jd['data'])-1),1) c+=1 # p = plt.plot(x, z, label = lbl) p = plt.plot(x, z, label = lbl, color = col) # col = p[0].get_color() if errk>0: plt.fill_between(x, err1, err2, alpha = 0.2, color = col) # plt.errorbar(x, z, yerr = err, fmt='.', color = col) td = [] xi = 0 for i in table[0]: while i > x[xi]: xi += 1 td.append(z[xi]) table.append(td) tablelabels.append(lbl) plt.legend(loc=4) sys.stdout.write('# ' + jd['title'] + '\n') tt = len(tablelabels) for i in range(tt): sys.stdout.write('# ' + (' | ')*i + ' '*5 + '+' + ('-'*7)*(tt-i-1) + '- %d: ' % i + tablelabels[i] +'\n') sys.stdout.write('#' + (' |----|')*tt + '\n') for i in range(len(table[0])): sys.stdout.write(' ') for j in range(len(table)): if j == 0: sys.stdout.write(' %6d' % table[j][i]) else: sys.stdout.write(' %6.3f' % table[j][i]) sys.stdout.write('\n') plt.show()

24.465558

113

0.50301

1,595

10,300

3.232602

0.116614

0.036656

0.057021

0.019201

0.801202

0.793832

0.786074

0.782002

0.773274

0

0.036351

0.297573

10,300

420

114

24.52381

0.676296

0.085534

0

0.808023

0

0.069953

0

1

0

false

0

0.025788

0

0.025788

0

null

0

1

0

1

0

null

0

7

7635d638410991a211ac25f018d8be5b4fa60974

393

py

Python

exercise_brokensongify_solution.py

annezola/gdi-python

a806f0eca2eb17e5a975cce8d0b1d90490dd455e

[ "MIT" ]

null

exercise_brokensongify_solution.py

annezola/gdi-python

a806f0eca2eb17e5a975cce8d0b1d90490dd455e

[ "MIT" ]

null

exercise_brokensongify_solution.py

annezola/gdi-python

a806f0eca2eb17e5a975cce8d0b1d90490dd455e

[ "MIT" ]

1

2022-01-04T15:26:40.000Z

# Broken #1 def songify(lyric): return "🎼" + lyric + "🎶" songify("siiiinnnging in the rain") # Broken #2 def songify(lyric): return "🎼" + lyric + "🎶" songify("siiiinnnging in the rain") # Broken #3 def songify(lyric): return "🎼" + lyric + "🎶" songify("siiiinnnging in the rain") # Broken #4 def songify(lyric): return "🎼" + lyric + "🎶" print(songify("siiiinnnging in the rain"))

17.086957

42

0.633588

57

393

4.508772

0.280702

0.155642

0.233463

0.326848

0.941634

0.832685

0.723735

0

0.012539

0.188295

393

23

42

17.086957

0.768025

0.089059

0

0.916667

0

0.297143

0

1

0.333333

false

0

0.333333

0.666667

0.083333

0

null

0

1

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1

0

null

0

1

0

1

0

12

7668e1e1e289a1d416a6b3bcc82b0701c68e312d

3,449

py

Python

Packs/Workday/Integrations/Workday_IAM/test_data/event_results.py

matan-xmcyber/content

7f02301c140b35956af3cd20cb8dfc64f34afb3e

[ "MIT" ]

null

Packs/Workday/Integrations/Workday_IAM/test_data/event_results.py

matan-xmcyber/content

7f02301c140b35956af3cd20cb8dfc64f34afb3e

[ "MIT" ]

null

Packs/Workday/Integrations/Workday_IAM/test_data/event_results.py

matan-xmcyber/content

7f02301c140b35956af3cd20cb8dfc64f34afb3e

[ "MIT" ]

null

events_result = [ { "name": None, "rawJSON": "{\"Employee_Type\": \"Regular\", \"Leadership\": \"Yes-HQ\", \"Work_Country_Code\": \"840\", \"Street_Address\": \"3000 Tannery Way\", \"Employment_Status\": \"Active\", \"VP_Flag\": \"N\", \"Mgr_ID\": \"115069\", \"Cost_Center_Description\": \"Channel Sales\", \"GDPR_Country_Flag\": \"0\", \"Director_Flag\": \"Y\", \"Email_-_Primary_Home\": \"test@test.com\", \"First_Name\": \"Ronny\", \"Last_Hire_Date\": \"10/05/2020\", \"People_Manager_Flag\": \"N\", \"Department\": \"Sales NAM:NAM Channel Sales\", \"Workday_ID\": \"5aa443c785ff10461ac83e5a6be32e1e\", \"Postal_Code\": \"95054\", \"Rehired_Employee\": \"Yes\", \"Org_Level_1\": \"Sales\", \"Org_Level_3\": \"NAM Channel Sales\", \"Country_Name\": \"United States Of America\", \"Org_Level_2\": \"Sales NAM\", \"Emp_ID\": \"100122\", \"Job_Family\": \"Product Management\", \"User_Name\": \"rrahardjo@paloaltonetworks.com\", \"Preferred_Name_-_First_Name\": \"Ronny\", \"Prehire_Flag\": \"False\", \"Management_Level_1\": \"Nikesh Arora\", \"Work_Country_Abbrev\": \"US\", \"Management_Level_2\": \"Timmy Turner\", \"Email_Address\": \"rrahardjo@paloaltonetworks.com\", \"Title\": \"Dir, Product Line Manager\", \"City\": \"Santa Clara\", \"Work_State_US_Only\": \"California\", \"Job_Code\": \"2245\", \"PAN_CF_Okta_Location_Region\": \"Americas\", \"Last_Name\": \"Rahardjo\", \"Job_Function\": \"Product Management Function\", \"State\": \"California\", \"Exec_Admin_Flag\": \"N\", \"Preferred_Name\": \"Ronny Rahardjo\", \"Regular_Employee_Flag\": \"Y\", \"Preferred_Name_-_Last_Name\": \"Rahardjo\", \"Cost_Center_Code\": \"120100\", \"Location\": \"Office - USA - CA - Headquarters\", \"UserProfile\": {\"employee_type\": \"Regular\", \"leadership\": \"Yes-HQ\", \"work_country_code\": \"840\", \"street_address\": \"3000 Tannery Way\", \"employment_status\": \"Active\", \"vp_flag\": \"N\", \"mgr_id\": \"115069\", \"cost_center_description\": \"Channel Sales\", \"gdpr_country_flag\": \"0\", \"director_flag\": \"Y\", \"email_-_primary_home\": \"test@test.com\", \"first_name\": \"Ronny\", \"last_hire_date\": \"10/05/2020\", \"people_manager_flag\": \"N\", \"department\": \"Sales NAM:NAM Channel Sales\", \"workday_id\": \"5aa443c785ff10461ac83e5a6be32e1e\", \"postal_code\": \"95054\", \"rehired_employee\": \"Yes\", \"org_level_1\": \"Sales\", \"org_level_3\": \"NAM Channel Sales\", \"country_name\": \"United States Of America\", \"org_level_2\": \"Sales NAM\", \"emp_id\": \"100122\", \"job_family\": \"Product Management\", \"user_name\": \"rrahardjo@paloaltonetworks.com\", \"preferred_name_-_first_name\": \"Ronny\", \"prehire_flag\": \"False\", \"management_level_1\": \"Nikesh Arora\", \"work_country_abbrev\": \"US\", \"management_level_2\": \"Timmy Turner\", \"email_address\": \"rrahardjo@paloaltonetworks.com\", \"title\": \"Dir, Product Line Manager\", \"city\": \"Santa Clara\", \"work_state_us_only\": \"California\", \"job_code\": \"2245\", \"pan_cf_okta_location_region\": \"Americas\", \"last_name\": \"Rahardjo\", \"job_function\": \"Product Management Function\", \"state\": \"California\", \"exec_admin_flag\": \"N\", \"preferred_name\": \"Ronny Rahardjo\", \"regular_employee_flag\": \"Y\", \"preferred_name_-_last_name\": \"Rahardjo\", \"cost_center_code\": \"120100\", \"location\": \"Office - USA - CA - Headquarters\"}}", "details": "Profile changed. Changed fields: []" } ]

431.125

3,337

0.637576

387

3,449

5.338501

0.302326

0.014521

0.027106

0.028074

0.96515

0

0.042338

0.082343

3,449

7

3,338

492.714286

0.610427

0

0.173384

0

1

0

false

0

null

0

1

0

1

0

null

0

9

769ba07cabedacdf51e14f831f888c4a624780a3

218

py

Python

mosaicme/web/mosaic/models.py

emccode/mosaicme

a6e133defb3404b6de6083c1414078338fba773a

[ "MIT" ]

14

2015-08-26T14:51:43.000Z

2016-09-13T20:04:50.000Z

mosaicme/web/mosaic/models.py

thecodeteam/mosaicme

a6e133defb3404b6de6083c1414078338fba773a

[ "MIT" ]

21

2016-04-07T13:56:43.000Z

2016-09-19T14:41:00.000Z

mosaicme/web/mosaic/models.py

emccode/mosaicme

a6e133defb3404b6de6083c1414078338fba773a

[ "MIT" ]

12

2015-06-08T13:54:18.000Z

2016-09-11T11:08:03.000Z

from django.conf import settings def init_redis(): """ Returns redis connection. """ import redis return redis.StrictRedis(host=settings.REDIS_HOST, port=settings.REDIS_PORT, db=settings.REDIS_DB)

24.222222

102

0.724771

28

218

5.5

0.535714

0.253247

0

0.174312

218

9

102

24.222222

0.855556

0.114679

0

1

0.25

true

0

0.5

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

76b4933c0530989e5fd1033942f529d33c6f56a1

3,972

py

Python

examples/demo.py

diegoperezm/screencast-script

ac477c6f44a151cafa88ebfd981d2bbe34f792bd

[ "MIT" ]

null

examples/demo.py

diegoperezm/screencast-script

ac477c6f44a151cafa88ebfd981d2bbe34f792bd

[ "MIT" ]

null

examples/demo.py

diegoperezm/screencast-script

ac477c6f44a151cafa88ebfd981d2bbe34f792bd

[ "MIT" ]

null

import sys # for development sys.path.append('./src') sys.path.append('../src') from screencastscript import ScreencastScript # noqa: E402 screencast = ScreencastScript() ################################## # # # screencast-script: # # Demo # # # ################################## screencast.i3wm_ws_2() screencast.sleep(2) screencast.take_screenshots(8) screencast.i3wm_focus_right() screencast.send_input_take_screenshots("""import matplotlib.pyplot as plt """) screencast.sleep(4) screencast.take_screenshots(8) screencast.send_input_take_screenshots("""import numpy as np """) screencast.sleep(2) screencast.take_screenshots(8) screencast.send_input_take_screenshots( """x = np.linspace(-np.pi / 2, np.pi / 2, 31) y = np.cos(x)**3 """) screencast.sleep(2) screencast.take_screenshots(8) screencast.send_input_take_screenshots("""# 1) remove points where y > 0.7 x2 = x[y <= 0.7] y2 = y[y <= 0.7] """) screencast.sleep(2) screencast.take_screenshots(8) screencast.send_input_take_screenshots("""# 2) mask points where y > 0.7 y3 = np.ma.masked_where(y > 0.7, y) # 3) set to NaN where y > 0.7 y4 = y.copy() y4[y3 > 0.7] = np.nan """) screencast.sleep(2) screencast.take_screenshots(8) screencast.i3wm_toggle_fullscreen() screencast.take_screenshots(8) screencast.sleep(4) screencast.send_input_take_screenshots( """plt.plot(x * 0.1, y, 'o-', color='lightgrey', label='No mask') """) screencast.sleep(4) screencast.take_screenshots(8) screencast.send_input_take_screenshots("""plt.show() """) screencast.sleep(4) screencast.take_screenshots(12) screencast.send_input_take_screenshots( """plt.plot(x2 * 0.4, y2, 'o-', label='Points removed') """) screencast.sleep(4) screencast.take_screenshots(8) screencast.send_input_take_screenshots("""plt.show() """) screencast.sleep(4) screencast.take_screenshots(12) screencast.send_input_take_screenshots( """plt.plot(x * 0.7, y3, 'o-', label='Masked values') """) screencast.sleep(4) screencast.take_screenshots(8) screencast.send_input("""plt.show() """) screencast.sleep(4) screencast.take_screenshots(12) screencast.send_input("""plt.plot(x * 1.0, y4, 'o-', label='NaN values') """) screencast.sleep(4) screencast.take_screenshots(12) screencast.send_input("""plt.legend() """) screencast.sleep(4) screencast.send_input_take_screenshots("""plt.title('Masked and NaN data') """) screencast.sleep(4) screencast.take_screenshots(4) screencast.send_input_take_screenshots("""plt.show() """) screencast.sleep(4) screencast.take_screenshots(12) screencast.i3wm_toggle_fullscreen_take_screenshots() screencast.take_screenshots(4) screencast.i3wm_focus_left_take_screenshots() screencast.take_screenshots(4) screencast.sleep(2) screencast.i3wm_toggle_fullscreen_take_screenshots() screencast.take_screenshots(4) screencast.sleep(2) screencast.i3wm_zoom_in_take_screenshots() screencast.sleep(2) screencast.take_screenshots(8) screencast.i3wm_zoom_in_take_screenshots() screencast.sleep(2) screencast.take_screenshots(8) screencast.i3wm_zoom_in_take_screenshots() screencast.sleep(2) screencast.take_screenshots(8) screencast.vim_scroll_down_take_screenshots() screencast.sleep(2) screencast.take_screenshots(8) screencast.vim_scroll_down_take_screenshots() screencast.sleep(2) screencast.take_screenshots(8) screencast.vim_scroll_down_take_screenshots() screencast.sleep(2) screencast.take_screenshots(8) screencast.vim_scroll_down_take_screenshots() screencast.sleep(2) screencast.take_screenshots(8) screencast.vim_scroll_down_take_screenshots() screencast.sleep(2) screencast.take_screenshots(8) screencast.vim_scroll_down_take_screenshots() screencast.sleep(2) screencast.take_screenshots(24) screencast.make_video() # If you want to use this, you need an audio file (in the folder) # screencast.make_video_with_audio( # audio_file="./audio.mp3")

20.795812

74

0.739174

530

3,972

5.3

0.177358

0.277679

0.249199

0.166607

0.795657

0.776433

0.745461

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0.032741

0.108006

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190

75

20.905263

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false

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0.035398

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null

1

0

1

0

1

0

null

0

9

76c8ec8726c97f123104a8e3ed55ca0d3b92b623

4,032

py

Python

pycls/datasets/custom_datasets.py

acl21/deep-active-learning-pytorch

637fd507235632903bcf84ed841ff524d847b94e

[ "MIT" ]

42

2021-05-10T23:02:20.000Z

2022-03-26T02:21:40.000Z

pycls/datasets/custom_datasets.py

acl21/deep-active-learning-pytorch

637fd507235632903bcf84ed841ff524d847b94e

[ "MIT" ]

1

2021-06-24T06:43:11.000Z

2021-06-24T11:54:13.000Z

pycls/datasets/custom_datasets.py

acl21/deep-active-learning-pytorch

637fd507235632903bcf84ed841ff524d847b94e

[ "MIT" ]

3

2021-05-19T08:16:16.000Z

2022-02-03T10:58:51.000Z

import torch import torchvision from PIL import Image class CIFAR10(torchvision.datasets.CIFAR10): def __init__(self, root, train, transform, test_transform, download=True): super(CIFAR10, self).__init__(root, train, transform=transform, download=download) self.test_transform = test_transform self.no_aug = False def __getitem__(self, index: int): """ Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class. """ img, target = self.data[index], self.targets[index] # doing this so that it is consistent with all other datasets # to return a PIL Image img = Image.fromarray(img) if self.no_aug: if self.test_transform is not None: img = self.test_transform(img) else: if self.transform is not None: img = self.transform(img) return img, target class CIFAR100(torchvision.datasets.CIFAR100): def __init__(self, root, train, transform, test_transform, download=True): super(CIFAR100, self).__init__(root, train, transform=transform, download=download) self.test_transform = test_transform self.no_aug = False def __getitem__(self, index: int): """ Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class. """ img, target = self.data[index], self.targets[index] # doing this so that it is consistent with all other datasets # to return a PIL Image img = Image.fromarray(img) if self.no_aug: if self.test_transform is not None: img = self.test_transform(img) else: if self.transform is not None: img = self.transform(img) return img, target class MNIST(torchvision.datasets.MNIST): def __init__(self, root, train, transform, test_transform, download=True): super(MNIST, self).__init__(root, train, transform=transform, download=download) self.test_transform = test_transform self.no_aug = False def __getitem__(self, index: int): """ Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class. """ img, target = self.data[index], int(self.targets[index]) # doing this so that it is consistent with all other datasets # to return a PIL Image img = Image.fromarray(img.numpy(), mode='L') if self.no_aug: if self.test_transform is not None: img = self.test_transform(img) else: if self.transform is not None: img = self.transform(img) return img, target class SVHN(torchvision.datasets.SVHN): def __init__(self, root, train, transform, test_transform, download=True): super(SVHN, self).__init__(root, train, transform=transform, download=download) self.test_transform = test_transform self.no_aug = False def __getitem__(self, index: int): """ Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class. """ img, target = self.data[index], self.targets[index] # doing this so that it is consistent with all other datasets # to return a PIL Image img = Image.fromarray(img) if self.no_aug: if self.test_transform is not None: img = self.test_transform(img) else: if self.transform is not None: img = self.transform(img) return img, target

32

92

0.569196

464

4,032

4.782328

0.127155

0.11717

0.091933

0.064894

0.904461

0

0.005708

0.348214

4,032

126

93

32

0.838661

0.189484

0

0.793651

0

0.000339

0

1

0.126984

false

0

0.047619

0

0.301587

0

null

0

1

0

1

0

null

0

7

4f173ae3da752dfece60a87223ed5699969af000

12,040

py

Python

test/lba/util_tests.py

nervepoint/logonbox-authenticator-python

a91c94d4358c2ecf9779250fe55f0ec84c3fff07

[ "Apache-2.0" ]

null

test/lba/util_tests.py

nervepoint/logonbox-authenticator-python

a91c94d4358c2ecf9779250fe55f0ec84c3fff07

[ "Apache-2.0" ]

null

test/lba/util_tests.py

nervepoint/logonbox-authenticator-python

a91c94d4358c2ecf9779250fe55f0ec84c3fff07

[ "Apache-2.0" ]

null

import unittest import lba.util; class ByteArrayWriterTest(unittest.TestCase): def test_write_string(self): w = lba.util.ByteArrayWriter(); w.write_string("A Test String"); self.assertEqual(bytes([ 0, 0, 0, 13, 65, 32, 84, 101, 115, 116, 32, 83, 116, 114, 105, 110, 103 ]), w.get_bytes()); def test_integer(self): w = lba.util.ByteArrayWriter() w.write_int(4294967295) w.write_int(0) w.write_int(255) w.write_int(4294967040) self.assertEqual(bytes([ 0xff, 0xff, 0xff, 0xff, 0, 0, 0, 0, 0, 0, 0, 0xff, 0xff, 0xff, 0xff, 0 ]), w.get_bytes()) def test_big_integer(self): w = lba.util.ByteArrayWriter(); w.write_big_integer(329802389981797891243908975290812); self.assertEqual(bytes([ 0, 0, 0, 14, 16, 66, 176, 254, 247, 114, 215, 130, 240, 27, 237, 39, 233, 188 ]), w.get_bytes()); def test_binary_string(self): w = lba.util.ByteArrayWriter() w.write_binary_string("Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.".encode('UTF-8')) self.assertEqual(bytes([ 0, 0, 0, 123, 76, 111, 114, 101, 109, 32, 105, 112, 115, 117, 109, 32, 100, 111, 108, 111, 114, 32, 115, 105, 116, 32, 97, 109, 101, 116, 44, 32, 99, 111, 110, 115, 101, 99, 116, 101, 116, 117, 114, 32, 97, 100, 105, 112, 105, 115, 99, 105, 110, 103, 32, 101, 108, 105, 116, 44, 32, 115, 101, 100, 32, 100, 111, 32, 101, 105, 117, 115, 109, 111, 100, 32, 116, 101, 109, 112, 111, 114, 32, 105, 110, 99, 105, 100, 105, 100, 117, 110, 116, 32, 117, 116, 32, 108, 97, 98, 111, 114, 101, 32, 101, 116, 32, 100, 111, 108, 111, 114, 101, 32, 109, 97, 103, 110, 97, 32, 97, 108, 105, 113, 117, 97, 46 ]), w.get_bytes()) def test_massive_integer(self): w = lba.util.ByteArrayWriter() w.write_big_integer(4986580695048258251352289243969528543723799114324057371323608612564101467693190796478532220284311403189255873250803291602531019677110835331481798144386049284511688009328775687804730487000620487321119382781090544960120583643153599562724683545896843186364280959049341308629380720692043569110468202632021048673338887960542310457475382130231373634793736853819191982436405235215379401298185584213567077387840129057385674664071727417723315763120148348448625747824864998778650276874067046964948041454108472270884726573176720890632226924444526896411492224011080798782446878497167945815843132905198949069567082142592104355525279386692616234048604119115967592552701346081832583566701136596353331815241580453022478423878876764704414366376336598553049072822810090907768245535476110588270567353835663980833082822835527392197580869451516391575655964243632587493986489280683147080083155190055556030197814111481606633955453576346428985945179); self.assertEqual(bytes([ 0, 0, 1, 129, 0, 219, 187, 194, 33, 195, 140, 127, 7, 175, 149, 255, 85, 187, 33, 19, 91, 211, 199, 5, 237, 90, 0, 155, 254, 36, 119, 8, 188, 150, 217, 238, 237, 90, 223, 43, 21, 237, 235, 55, 138, 131, 252, 118, 236, 201, 9, 163, 47, 30, 139, 78, 117, 127, 191, 123, 137, 169, 168, 62, 179, 79, 118, 184, 119, 19, 169, 223, 68, 154, 25, 117, 175, 114, 110, 170, 14, 20, 92, 110, 158, 73, 57, 123, 52, 245, 87, 240, 34, 231, 184, 153, 186, 114, 242, 99, 25, 131, 37, 240, 29, 207, 117, 37, 242, 52, 219, 49, 88, 208, 186, 193, 85, 242, 176, 154, 112, 176, 81, 107, 219, 126, 133, 206, 92, 18, 178, 156, 177, 26, 152, 189, 81, 41, 30, 226, 88, 70, 123, 0, 164, 176, 105, 91, 166, 221, 169, 159, 163, 94, 40, 145, 123, 94, 202, 91, 246, 150, 171, 157, 244, 102, 86, 236, 54, 28, 141, 210, 49, 218, 149, 106, 78, 196, 232, 174, 20, 66, 213, 176, 239, 147, 80, 102, 232, 173, 142, 48, 122, 76, 161, 193, 238, 64, 90, 45, 189, 182, 162, 163, 218, 158, 187, 2, 145, 84, 14, 254, 177, 241, 142, 245, 165, 130, 241, 124, 94, 23, 172, 48, 252, 201, 209, 160, 21, 17, 18, 222, 198, 190, 34, 136, 26, 78, 163, 127, 61, 152, 31, 106, 98, 144, 251, 112, 205, 91, 244, 138, 167, 23, 92, 210, 60, 229, 6, 213, 244, 87, 225, 55, 171, 143, 90, 234, 223, 36, 247, 110, 251, 98, 121, 3, 145, 52, 133, 81, 128, 148, 122, 147, 215, 231, 226, 163, 179, 133, 244, 249, 209, 83, 56, 88, 78, 245, 243, 130, 155, 181, 131, 57, 235, 22, 233, 67, 205, 208, 210, 41, 157, 208, 212, 73, 142, 122, 231, 128, 124, 170, 172, 214, 231, 191, 205, 195, 176, 16, 57, 92, 51, 74, 250, 171, 132, 254, 178, 37, 46, 234, 47, 107, 153, 242, 179, 120, 82, 184, 195, 224, 134, 61, 79, 116, 34, 173, 153, 170, 221, 144, 64, 120, 43, 128, 117, 158, 62, 153, 195, 224, 114, 254, 30, 161, 112, 80, 168, 103, 2, 215, 130, 120, 171, 67, 25, 172, 91 ]), w.get_bytes()) def test_sig(self): w = lba.util.ByteArrayWriter() w.write_string("ssh-rsa") w.write_big_integer(65537) w.write_big_integer(4986580695048258251352289243969528543723799114324057371323608612564101467693190796478532220284311403189255873250803291602531019677110835331481798144386049284511688009328775687804730487000620487321119382781090544960120583643153599562724683545896843186364280959049341308629380720692043569110468202632021048673338887960542310457475382130231373634793736853819191982436405235215379401298185584213567077387840129057385674664071727417723315763120148348448625747824864998778650276874067046964948041454108472270884726573176720890632226924444526896411492224011080798782446878497167945815843132905198949069567082142592104355525279386692616234048604119115967592552701346081832583566701136596353331815241580453022478423878876764704414366376336598553049072822810090907768245535476110588270567353835663980833082822835527392197580869451516391575655964243632587493986489280683147080083155190055556030197814111481606633955453576346428985945179); self.assertEqual(bytes([ 0, 0, 0, 7, 115, 115, 104, 45, 114, 115, 97, 0, 0, 0, 3, 1, 0, 1, 0, 0, 1, 129, 0, 219, 187, 194, 33, 195, 140, 127, 7, 175, 149, 255, 85, 187, 33, 19, 91, 211, 199, 5, 237, 90, 0, 155, 254, 36, 119, 8, 188, 150, 217, 238, 237, 90, 223, 43, 21, 237, 235, 55, 138, 131, 252, 118, 236, 201, 9, 163, 47, 30, 139, 78, 117, 127, 191, 123, 137, 169, 168, 62, 179, 79, 118, 184, 119, 19, 169, 223, 68, 154, 25, 117, 175, 114, 110, 170, 14, 20, 92, 110, 158, 73, 57, 123, 52, 245, 87, 240, 34, 231, 184, 153, 186, 114, 242, 99, 25, 131, 37, 240, 29, 207, 117, 37, 242, 52, 219, 49, 88, 208, 186, 193, 85, 242, 176, 154, 112, 176, 81, 107, 219, 126, 133, 206, 92, 18, 178, 156, 177, 26, 152, 189, 81, 41, 30, 226, 88, 70, 123, 0, 164, 176, 105, 91, 166, 221, 169, 159, 163, 94, 40, 145, 123, 94, 202, 91, 246, 150, 171, 157, 244, 102, 86, 236, 54, 28, 141, 210, 49, 218, 149, 106, 78, 196, 232, 174, 20, 66, 213, 176, 239, 147, 80, 102, 232, 173, 142, 48, 122, 76, 161, 193, 238, 64, 90, 45, 189, 182, 162, 163, 218, 158, 187, 2, 145, 84, 14, 254, 177, 241, 142, 245, 165, 130, 241, 124, 94, 23, 172, 48, 252, 201, 209, 160, 21, 17, 18, 222, 198, 190, 34, 136, 26, 78, 163, 127, 61, 152, 31, 106, 98, 144, 251, 112, 205, 91, 244, 138, 167, 23, 92, 210, 60, 229, 6, 213, 244, 87, 225, 55, 171, 143, 90, 234, 223, 36, 247, 110, 251, 98, 121, 3, 145, 52, 133, 81, 128, 148, 122, 147, 215, 231, 226, 163, 179, 133, 244, 249, 209, 83, 56, 88, 78, 245, 243, 130, 155, 181, 131, 57, 235, 22, 233, 67, 205, 208, 210, 41, 157, 208, 212, 73, 142, 122, 231, 128, 124, 170, 172, 214, 231, 191, 205, 195, 176, 16, 57, 92, 51, 74, 250, 171, 132, 254, 178, 37, 46, 234, 47, 107, 153, 242, 179, 120, 82, 184, 195, 224, 134, 61, 79, 116, 34, 173, 153, 170, 221, 144, 64, 120, 43, 128, 117, 158, 62, 153, 195, 224, 114, 254, 30, 161, 112, 80, 168, 103, 2, 215, 130, 120, 171, 67, 25, 172, 91 ]), w.get_bytes()) class ByteArrayReaderTest(unittest.TestCase): def test_read_string(self): r = lba.util.ByteArrayReader(bytes([ 0, 0, 0, 13, 65, 32, 84, 101, 115, 116, 32, 83, 116, 114, 105, 110, 103])) self.assertEqual("A Test String", r.read_string()) def test_integer(self): r = lba.util.ByteArrayReader(bytes([ 0xff, 0xff, 0xff, 0xff, 0, 0, 0, 0, 0, 0, 0, 0xff, 0xff, 0xff, 0xff, 0 ])); self.assertEqual(4294967295, r.read_int()) self.assertEqual(0, r.read_int()) self.assertEqual(255, r.read_int()) self.assertEqual(4294967040, r.read_int()) def test_binary_string(self): r = lba.util.ByteArrayReader(bytes([ 0, 0, 0, 123, 76, 111, 114, 101, 109, 32, 105, 112, 115, 117, 109, 32, 100, 111, 108, 111, 114, 32, 115, 105, 116, 32, 97, 109, 101, 116, 44, 32, 99, 111, 110, 115, 101, 99, 116, 101, 116, 117, 114, 32, 97, 100, 105, 112, 105, 115, 99, 105, 110, 103, 32, 101, 108, 105, 116, 44, 32, 115, 101, 100, 32, 100, 111, 32, 101, 105, 117, 115, 109, 111, 100, 32, 116, 101, 109, 112, 111, 114, 32, 105, 110, 99, 105, 100, 105, 100, 117, 110, 116, 32, 117, 116, 32, 108, 97, 98, 111, 114, 101, 32, 101, 116, 32, 100, 111, 108, 111, 114, 101, 32, 109, 97, 103, 110, 97, 32, 97, 108, 105, 113, 117, 97, 46 ])) self.assertEqual( "Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.".encode("UTF-8"), r.read_binary_string()) def test_big_integer(self): r = lba.util.ByteArrayReader(bytes([ 0, 0, 0, 14, 16, 66, 176, 254, 247, 114, 215, 130, 240, 27, 237, 39, 233, 188 ])) self.assertEqual(329802389981797891243908975290812, r.read_big_integer()) def test_boolean(self): r = lba.util.ByteArrayReader(bytes([ 0, 1 ])) self.assertFalse(r.read_boolean()) self.assertTrue(r.read_boolean())

62.061856

955

0.534219

1,453

12,040

4.391604

0.188575

0.009403

0.008463

0.005015

0.910202

0.883247

0.876038

0.864441

0.838897

0.834665

0

0.624129

0.344601

12,040

193

956

62.38342

0.184514

0

0.440678

0

0.011299

0.024003

0

0.005316

0

0.084746

1

0.062147

false

0

0.011299

0

0.084746

0

null

0

1

0

1

0

1

0

null

0

8

4f3d8aeca4802004133b55244744bbf85575c3cc

100,487

py

Python

alibabacloud/clients/r_kvstore_20150101.py

wallisyan/alibabacloud-python-sdk-v2

6e024c97cded2403025a7dd8fea8261e41872156

[ "Apache-2.0" ]

21

2018-12-20T07:34:13.000Z

2020-03-05T14:32:08.000Z

alibabacloud/clients/r_kvstore_20150101.py

wallisyan/alibabacloud-python-sdk-v2

6e024c97cded2403025a7dd8fea8261e41872156

[ "Apache-2.0" ]

22

2018-12-21T13:22:33.000Z

2020-06-29T08:37:09.000Z

alibabacloud/clients/r_kvstore_20150101.py

wallisyan/alibabacloud-python-sdk-v2

6e024c97cded2403025a7dd8fea8261e41872156

[ "Apache-2.0" ]

12

2018-12-29T05:45:55.000Z

2022-01-05T09:59:30.000Z

# Copyright 2019 Alibaba Cloud 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 # limitations under the License. from alibabacloud.client import AlibabaCloudClient from alibabacloud.request import APIRequest from alibabacloud.utils.parameter_validation import verify_params class RkvstoreClient(AlibabaCloudClient): def __init__(self, client_config, credentials_provider=None, retry_policy=None, endpoint_resolver=None): AlibabaCloudClient.__init__(self, client_config, credentials_provider=credentials_provider, retry_policy=retry_policy, endpoint_resolver=endpoint_resolver) self.product_code = 'R-kvstore' self.api_version = '2015-01-01' self.location_service_code = 'redisa' self.location_endpoint_type = 'openAPI' def create_sharding_instance( self, shard_storage_quantity=None, resource_owner_id=None, node_type=None, coupon_no=None, network_type=None, engine_version=None, instance_class=None, capacity=None, password=None, shard_replica_class=None, security_token=None, incremental_backup_mode=None, instance_type=None, business_info=None, period=None, resource_owner_account=None, src_db_instance_id=None, owner_account=None, backup_id=None, owner_id=None, token=None, shard_quantity=None, vswitch_id=None, private_ip_address=None, security_ip_list=None, instance_name=None, shard_replica_quantity=None, architecture_type=None, vpc_id=None, redis_manager_class=None, zone_id=None, charge_type=None, proxy_quantity=None, config=None, proxy_mode=None): api_request = APIRequest('CreateShardingInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ShardStorageQuantity": shard_storage_quantity, "ResourceOwnerId": resource_owner_id, "NodeType": node_type, "CouponNo": coupon_no, "NetworkType": network_type, "EngineVersion": engine_version, "InstanceClass": instance_class, "Capacity": capacity, "Password": password, "ShardReplicaClass": shard_replica_class, "SecurityToken": security_token, "IncrementalBackupMode": incremental_backup_mode, "InstanceType": instance_type, "BusinessInfo": business_info, "Period": period, "ResourceOwnerAccount": resource_owner_account, "SrcDBInstanceId": src_db_instance_id, "OwnerAccount": owner_account, "BackupId": backup_id, "OwnerId": owner_id, "Token": token, "ShardQuantity": shard_quantity, "VSwitchId": vswitch_id, "PrivateIpAddress": private_ip_address, "SecurityIPList": security_ip_list, "InstanceName": instance_name, "ShardReplicaQuantity": shard_replica_quantity, "ArchitectureType": architecture_type, "VpcId": vpc_id, "RedisManagerClass": redis_manager_class, "ZoneId": zone_id, "ChargeType": charge_type, "ProxyQuantity": proxy_quantity, "Config": config, "ProxyMode": proxy_mode} return self._handle_request(api_request).result def describe_sharding_instances( self, resource_owner_id=None, security_token=None, resource_owner_account=None, instance_ids=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeShardingInstances', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "InstanceIds": instance_ids, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_tags( self, resource_owner_id=None, resource_owner_account=None, region_id=None, next_token=None, owner_account=None, owner_id=None, resource_type=None): api_request = APIRequest('DescribeTags', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "RegionId": region_id, "NextToken": next_token, "OwnerAccount": owner_account, "OwnerId": owner_id, "ResourceType": resource_type} return self._handle_request(api_request).result def describe_available_resource( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, zone_id=None, owner_id=None, instance_charge_type=None, order_type=None): api_request = APIRequest('DescribeAvailableResource', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ZoneId": zone_id, "OwnerId": owner_id, "InstanceChargeType": instance_charge_type, "OrderType": order_type} return self._handle_request(api_request).result def allocate_instance_public_connection( self, resource_owner_id=None, connection_string_prefix=None, instance_id=None, security_token=None, resource_owner_account=None, port=None, owner_account=None, owner_id=None): api_request = APIRequest('AllocateInstancePublicConnection', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ConnectionStringPrefix": connection_string_prefix, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "Port": port, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def release_instance_public_connection( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, current_connection_string=None): api_request = APIRequest('ReleaseInstancePublicConnection', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "CurrentConnectionString": current_connection_string} return self._handle_request(api_request).result def list_tag_resources( self, resource_owner_id=None, list_of_resource_id=None, resource_owner_account=None, region_id=None, next_token=None, owner_account=None, list_of_tag=None, owner_id=None, resource_type=None): api_request = APIRequest('ListTagResources', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceId": list_of_resource_id, "ResourceOwnerAccount": resource_owner_account, "RegionId": region_id, "NextToken": next_token, "OwnerAccount": owner_account, "Tag": list_of_tag, "OwnerId": owner_id, "ResourceType": resource_type} repeat_info = {"ResourceId": ('ResourceId', 'list', 'str', None), "Tag": ('Tag', 'list', 'dict', [('Value', 'str', None, None), ('Key', 'str', None, None), ]), } verify_params(api_request._params, repeat_info) return self._handle_request(api_request).result def tag_resources( self, resource_owner_id=None, list_of_resource_id=None, resource_owner_account=None, region_id=None, owner_account=None, list_of_tag=None, owner_id=None, resource_type=None): api_request = APIRequest('TagResources', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceId": list_of_resource_id, "ResourceOwnerAccount": resource_owner_account, "RegionId": region_id, "OwnerAccount": owner_account, "Tag": list_of_tag, "OwnerId": owner_id, "ResourceType": resource_type} repeat_info = {"ResourceId": ('ResourceId', 'list', 'str', None), "Tag": ('Tag', 'list', 'dict', [('Value', 'str', None, None), ('Key', 'str', None, None), ]), } verify_params(api_request._params, repeat_info) return self._handle_request(api_request).result def migrate_to_other_zone( self, vswitch_id=None, resource_owner_id=None, security_token=None, resource_owner_account=None, effective_time=None, owner_account=None, zone_id=None, db_instance_id=None, owner_id=None): api_request = APIRequest('MigrateToOtherZone', 'GET', 'http', 'RPC', 'query') api_request._params = { "VSwitchId": vswitch_id, "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "EffectiveTime": effective_time, "OwnerAccount": owner_account, "ZoneId": zone_id, "DBInstanceId": db_instance_id, "OwnerId": owner_id} return self._handle_request(api_request).result def untag_resources( self, all_=None, resource_owner_id=None, list_of_resource_id=None, resource_owner_account=None, region_id=None, owner_account=None, owner_id=None, list_of_tag_key=None, resource_type=None): api_request = APIRequest('UntagResources', 'GET', 'http', 'RPC', 'query') api_request._params = { "All": all_, "ResourceOwnerId": resource_owner_id, "ResourceId": list_of_resource_id, "ResourceOwnerAccount": resource_owner_account, "RegionId": region_id, "OwnerAccount": owner_account, "OwnerId": owner_id, "TagKey": list_of_tag_key, "ResourceType": resource_type} repeat_info = {"ResourceId": ('ResourceId', 'list', 'str', None), "TagKey": ('TagKey', 'list', 'str', None), } verify_params(api_request._params, repeat_info) return self._handle_request(api_request).result def modify_audit_log_config( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, audit_command=None, owner_account=None, owner_id=None, retention=None): api_request = APIRequest('ModifyAuditLogConfig', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "AuditCommand": audit_command, "OwnerAccount": owner_account, "OwnerId": owner_id, "Retention": retention} return self._handle_request(api_request).result def modify_db_instance_monitor( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, db_instance_id=None, interval=None, owner_id=None): api_request = APIRequest('ModifyDBInstanceMonitor', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "DBInstanceId": db_instance_id, "Interval": interval, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_db_instance_monitor( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, db_instance_id=None, owner_id=None): api_request = APIRequest('DescribeDBInstanceMonitor', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "DBInstanceId": db_instance_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_cache_analysis_report_list( self, date=None, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None, instance_id=None, security_token=None, page_size=None, page_numbers=None, days=None, node_id=None): api_request = APIRequest('DescribeCacheAnalysisReportList', 'GET', 'http', 'RPC', 'query') api_request._params = { "Date": date, "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "PageSize": page_size, "PageNumbers": page_numbers, "Days": days, "NodeId": node_id} return self._handle_request(api_request).result def describe_intranet_attribute( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeIntranetAttribute', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_intranet_attribute( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('ModifyIntranetAttribute', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_cache_analysis_report( self, date=None, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None, analysis_type=None, instance_id=None, security_token=None, page_size=None, page_numbers=None, node_id=None): api_request = APIRequest('DescribeCacheAnalysisReport', 'GET', 'http', 'RPC', 'query') api_request._params = { "Date": date, "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "AnalysisType": analysis_type, "InstanceId": instance_id, "SecurityToken": security_token, "PageSize": page_size, "PageNumbers": page_numbers, "NodeId": node_id} return self._handle_request(api_request).result def create_cache_analysis_task( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('CreateCacheAnalysisTask', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_audit_records( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, end_time=None, start_time=None, owner_id=None, query_keywords=None, page_number=None, host_address=None, instance_id=None, account_name=None, security_token=None, database_name=None, page_size=None, node_id=None): api_request = APIRequest('DescribeAuditRecords', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "QueryKeywords": query_keywords, "PageNumber": page_number, "HostAddress": host_address, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token, "DatabaseName": database_name, "PageSize": page_size, "NodeId": node_id} return self._handle_request(api_request).result def describe_slow_log_records( self, sql_id=None, resource_owner_id=None, resource_owner_account=None, owner_account=None, end_time=None, start_time=None, owner_id=None, page_number=None, slow_log_record_type=None, instance_id=None, db_name=None, security_token=None, page_size=None, node_id=None): api_request = APIRequest('DescribeSlowLogRecords', 'GET', 'http', 'RPC', 'query') api_request._params = { "SQLId": sql_id, "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "PageNumber": page_number, "SlowLogRecordType": slow_log_record_type, "InstanceId": instance_id, "DBName": db_name, "SecurityToken": security_token, "PageSize": page_size, "NodeId": node_id} return self._handle_request(api_request).result def describe_error_log_records( self, sql_id=None, resource_owner_id=None, resource_owner_account=None, owner_account=None, end_time=None, start_time=None, owner_id=None, page_number=None, instance_id=None, db_name=None, security_token=None, page_size=None, role_type=None, node_id=None): api_request = APIRequest('DescribeErrorLogRecords', 'GET', 'http', 'RPC', 'query') api_request._params = { "SQLId": sql_id, "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "PageNumber": page_number, "InstanceId": instance_id, "DBName": db_name, "SecurityToken": security_token, "PageSize": page_size, "RoleType": role_type, "NodeId": node_id} return self._handle_request(api_request).result def restart_instance( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, effective_time=None, owner_account=None, owner_id=None): api_request = APIRequest('RestartInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "EffectiveTime": effective_time, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_instance_auto_renewal_attribute( self, duration=None, resource_owner_id=None, auto_renew=None, security_token=None, resource_owner_account=None, owner_account=None, db_instance_id=None, owner_id=None): api_request = APIRequest('ModifyInstanceAutoRenewalAttribute', 'GET', 'http', 'RPC', 'query') api_request._params = { "Duration": duration, "ResourceOwnerId": resource_owner_id, "AutoRenew": auto_renew, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "DBInstanceId": db_instance_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_instance_auto_renewal_attribute( self, resource_owner_id=None, resource_owner_account=None, client_token=None, region_id=None, owner_account=None, page_size=None, db_instance_id=None, owner_id=None, page_number=None, proxy_id=None): api_request = APIRequest('DescribeInstanceAutoRenewalAttribute', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "ClientToken": client_token, "RegionId": region_id, "OwnerAccount": owner_account, "PageSize": page_size, "DBInstanceId": db_instance_id, "OwnerId": owner_id, "PageNumber": page_number, "proxyId": proxy_id} return self._handle_request(api_request).result def describe_running_log_records( self, sql_id=None, resource_owner_id=None, resource_owner_account=None, owner_account=None, end_time=None, start_time=None, owner_id=None, page_number=None, instance_id=None, db_name=None, security_token=None, page_size=None, role_type=None, node_id=None): api_request = APIRequest('DescribeRunningLogRecords', 'GET', 'http', 'RPC', 'query') api_request._params = { "SQLId": sql_id, "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "PageNumber": page_number, "InstanceId": instance_id, "DBName": db_name, "SecurityToken": security_token, "PageSize": page_size, "RoleType": role_type, "NodeId": node_id} return self._handle_request(api_request).result def unlink_replica_instance( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('UnlinkReplicaInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_active_operation_task( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, ids=None, switch_time=None, owner_id=None): api_request = APIRequest('ModifyActiveOperationTask', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "Ids": ids, "SwitchTime": switch_time, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_active_operation_task_type( self, resource_owner_id=None, is_history=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeActiveOperationTaskType', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "IsHistory": is_history, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_active_operation_task_region( self, resource_owner_id=None, is_history=None, task_type=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeActiveOperationTaskRegion', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "IsHistory": is_history, "TaskType": task_type, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_active_operation_task_count( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeActiveOperationTaskCount', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_active_operation_task( self, resource_owner_id=None, task_type=None, resource_owner_account=None, owner_account=None, owner_id=None, page_number=None, is_history=None, security_token=None, page_size=None, region=None): api_request = APIRequest('DescribeActiveOperationTask', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "TaskType": task_type, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "PageNumber": page_number, "IsHistory": is_history, "SecurityToken": security_token, "PageSize": page_size, "Region": region} return self._handle_request(api_request).result def modify_instance_major_version( self, resource_owner_id=None, instance_id=None, major_version=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, effect_time=None): api_request = APIRequest('ModifyInstanceMajorVersion', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "MajorVersion": major_version, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "EffectTime": effect_time} return self._handle_request(api_request).result def describe_parameter_templates( self, resource_owner_id=None, security_token=None, resource_owner_account=None, engine=None, owner_account=None, engine_version=None, owner_id=None, character_type=None): api_request = APIRequest('DescribeParameterTemplates', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "Engine": engine, "OwnerAccount": owner_account, "EngineVersion": engine_version, "OwnerId": owner_id, "CharacterType": character_type} return self._handle_request(api_request).result def revoke_account_privilege( self, resource_owner_id=None, instance_id=None, account_name=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('RevokeAccountPrivilege', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_parameters( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, db_instance_id=None, owner_id=None, node_id=None): api_request = APIRequest('DescribeParameters', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "DBInstanceId": db_instance_id, "OwnerId": owner_id, "NodeId": node_id} return self._handle_request(api_request).result def modify_account_description( self, resource_owner_id=None, instance_id=None, account_name=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, account_description=None): api_request = APIRequest('ModifyAccountDescription', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "AccountDescription": account_description} return self._handle_request(api_request).result def reset_account( self, resource_owner_id=None, account_password=None, instance_id=None, account_name=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('ResetAccount', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "AccountPassword": account_password, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def create_account( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, account_type=None, owner_id=None, account_description=None, account_privilege=None, account_password=None, instance_id=None, account_name=None, security_token=None): api_request = APIRequest('CreateAccount', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "AccountType": account_type, "OwnerId": owner_id, "AccountDescription": account_description, "AccountPrivilege": account_privilege, "AccountPassword": account_password, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token} return self._handle_request(api_request).result def delete_account( self, resource_owner_id=None, instance_id=None, account_name=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DeleteAccount', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_parameter_modification_history( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, end_time=None, db_instance_id=None, start_time=None, owner_id=None, node_id=None): api_request = APIRequest('DescribeParameterModificationHistory', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "DBInstanceId": db_instance_id, "StartTime": start_time, "OwnerId": owner_id, "NodeId": node_id} return self._handle_request(api_request).result def reset_account_password( self, resource_owner_id=None, account_password=None, instance_id=None, account_name=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('ResetAccountPassword', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "AccountPassword": account_password, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_accounts( self, resource_owner_id=None, instance_id=None, account_name=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeAccounts', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def grant_account_privilege( self, resource_owner_id=None, instance_id=None, account_name=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, account_privilege=None): api_request = APIRequest('GrantAccountPrivilege', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "AccountName": account_name, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "AccountPrivilege": account_privilege} return self._handle_request(api_request).result def evaluate_fail_over_switch( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('EvaluateFailOverSwitch', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def destroy_instance( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DestroyInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_instance_vpc_auth_mode( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, vpc_auth_mode=None, owner_id=None): api_request = APIRequest('ModifyInstanceVpcAuthMode', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "VpcAuthMode": vpc_auth_mode, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_db_instance_connection_string( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, new_connection_string=None, owner_id=None, ip_type=None, current_connection_string=None, security_token=None, port=None, db_instance_id=None): api_request = APIRequest('ModifyDBInstanceConnectionString', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "NewConnectionString": new_connection_string, "OwnerId": owner_id, "IPType": ip_type, "CurrentConnectionString": current_connection_string, "SecurityToken": security_token, "Port": port, "DBInstanceId": db_instance_id} return self._handle_request(api_request).result def describe_rds_vswitchs( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, vpc_id=None, zone_id=None, owner_id=None): api_request = APIRequest('DescribeRdsVSwitchs', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "VpcId": vpc_id, "ZoneId": zone_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_rds_vpcs( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, zone_id=None, owner_id=None): api_request = APIRequest('DescribeRdsVpcs', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ZoneId": zone_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_strategy( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('DescribeStrategy', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_replica_conflict_info( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, end_time=None, start_time=None, owner_id=None, page_number=None, security_token=None, replica_id=None, page_size=None): api_request = APIRequest('DescribeReplicaConflictInfo', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "PageNumber": page_number, "SecurityToken": security_token, "ReplicaId": replica_id, "PageSize": page_size} return self._handle_request(api_request).result def create_static_verification( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, destination_instance_id=None, source_instance_id=None, owner_id=None): api_request = APIRequest('CreateStaticVerification', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "DestinationInstanceId": destination_instance_id, "SourceInstanceId": source_instance_id, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_replica_recovery_mode( self, resource_owner_id=None, security_token=None, resource_owner_account=None, recovery_mode=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('ModifyReplicaRecoveryMode', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "RecoveryMode": recovery_mode, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_static_verification_list( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, destination_instance_id=None, source_instance_id=None, owner_id=None): api_request = APIRequest('DescribeStaticVerificationList', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "DestinationInstanceId": destination_instance_id, "SourceInstanceId": source_instance_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_verification_list( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, end_time=None, start_time=None, owner_id=None, page_number=None, security_token=None, replica_id=None, page_size=None): api_request = APIRequest('DescribeVerificationList', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "PageNumber": page_number, "SecurityToken": security_token, "ReplicaId": replica_id, "PageSize": page_size} return self._handle_request(api_request).result def modify_replica_verification_mode( self, resource_owner_id=None, verification_mode=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('ModifyReplicaVerificationMode', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "VerificationMode": verification_mode, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_instances_by_expire_time( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None, page_number=None, security_token=None, has_expired_res=None, page_size=None, instance_type=None, expire_period=None): api_request = APIRequest('DescribeInstancesByExpireTime', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "PageNumber": page_number, "SecurityToken": security_token, "HasExpiredRes": has_expired_res, "PageSize": page_size, "InstanceType": instance_type, "ExpirePeriod": expire_period} return self._handle_request(api_request).result def modify_replica_relation( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('ModifyReplicaRelation', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_replica_mode( self, domain_mode=None, resource_owner_id=None, primary_instance_id=None, replica_mode=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('ModifyReplicaMode', 'GET', 'http', 'RPC', 'query') api_request._params = { "DomainMode": domain_mode, "ResourceOwnerId": resource_owner_id, "PrimaryInstanceId": primary_instance_id, "ReplicaMode": replica_mode, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_guard_domain_mode( self, domain_mode=None, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('ModifyGuardDomainMode', 'GET', 'http', 'RPC', 'query') api_request._params = { "DomainMode": domain_mode, "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_instance_ssl( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, ssl_enabled=None): api_request = APIRequest('ModifyInstanceSSL', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "SSLEnabled": ssl_enabled} return self._handle_request(api_request).result def describe_instance_ssl( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeInstanceSSL', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_logic_instance_topology( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeLogicInstanceTopology', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_instance_spec( self, resource_owner_id=None, auto_pay=None, from_app=None, resource_owner_account=None, owner_account=None, coupon_no=None, owner_id=None, instance_class=None, instance_id=None, security_token=None, effective_time=None, force_upgrade=None, business_info=None): api_request = APIRequest('ModifyInstanceSpec', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "AutoPay": auto_pay, "FromApp": from_app, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "CouponNo": coupon_no, "OwnerId": owner_id, "InstanceClass": instance_class, "InstanceId": instance_id, "SecurityToken": security_token, "EffectiveTime": effective_time, "ForceUpgrade": force_upgrade, "BusinessInfo": business_info} return self._handle_request(api_request).result def modify_instance_spec_pre_check( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, target_instance_class=None): api_request = APIRequest('ModifyInstanceSpecPreCheck', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "TargetInstanceClass": target_instance_class} return self._handle_request(api_request).result def modify_instance_net_expire_time( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, connection_string=None, classic_expired_days=None, owner_account=None, owner_id=None): api_request = APIRequest('ModifyInstanceNetExpireTime', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "ConnectionString": connection_string, "ClassicExpiredDays": classic_expired_days, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def release_replica( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('ReleaseReplica', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_replica_description( self, replica_description=None, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('ModifyReplicaDescription', 'GET', 'http', 'RPC', 'query') api_request._params = { "ReplicaDescription": replica_description, "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_replica_usage( self, resource_owner_id=None, source_db_instance_id=None, destination_db_instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('DescribeReplicaUsage', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SourceDBInstanceId": source_db_instance_id, "DestinationDBInstanceId": destination_db_instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_replicas( self, resource_owner_id=None, security_token=None, resource_owner_account=None, attach_db_instance_data=None, owner_account=None, replica_id=None, page_size=None, owner_id=None, page_number=None): api_request = APIRequest('DescribeReplicas', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "AttachDbInstanceData": attach_db_instance_data, "OwnerAccount": owner_account, "ReplicaId": replica_id, "PageSize": page_size, "OwnerId": owner_id, "PageNumber": page_number} return self._handle_request(api_request).result def describe_replica_performance( self, resource_owner_id=None, destination_db_instance_id=None, resource_owner_account=None, owner_account=None, end_time=None, start_time=None, owner_id=None, source_db_instance_id=None, security_token=None, replica_id=None, key=None): api_request = APIRequest('DescribeReplicaPerformance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "DestinationDBInstanceId": destination_db_instance_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "SourceDBInstanceId": source_db_instance_id, "SecurityToken": security_token, "ReplicaId": replica_id, "Key": key} return self._handle_request(api_request).result def describe_replica_initialize_progress( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, replica_id=None, owner_id=None): api_request = APIRequest('DescribeReplicaInitializeProgress', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "ReplicaId": replica_id, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_instance_minor_version( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, minorversion=None, owner_account=None, owner_id=None, effect_time=None): api_request = APIRequest('ModifyInstanceMinorVersion', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "Minorversion": minorversion, "OwnerAccount": owner_account, "OwnerId": owner_id, "EffectTime": effect_time} return self._handle_request(api_request).result def modify_certification( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, no_certification=None): api_request = APIRequest('ModifyCertification', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "NoCertification": no_certification} return self._handle_request(api_request).result def describe_certification( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, parameters=None): api_request = APIRequest('DescribeCertification', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "Parameters": parameters} return self._handle_request(api_request).result def describe_db_instance_net_info( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeDBInstanceNetInfo', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_monthly_service_status_detail( self, resource_owner_id=None, instance_id=None, month=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeMonthlyServiceStatusDetail', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "Month": month, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_monthly_service_status( self, resource_owner_id=None, month=None, security_token=None, resource_owner_account=None, instance_ids=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeMonthlyServiceStatus', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "Month": month, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "InstanceIds": instance_ids, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_security_ips( self, resource_owner_id=None, modify_mode=None, resource_owner_account=None, owner_account=None, security_ips=None, owner_id=None, security_ip_group_name=None, instance_id=None, security_token=None, security_ip_group_attribute=None): api_request = APIRequest('ModifySecurityIps', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ModifyMode": modify_mode, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "SecurityIps": security_ips, "OwnerId": owner_id, "SecurityIpGroupName": security_ip_group_name, "InstanceId": instance_id, "SecurityToken": security_token, "SecurityIpGroupAttribute": security_ip_group_attribute} return self._handle_request(api_request).result def describe_security_ips( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeSecurityIps', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_instance_maintain_time( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, maintain_start_time=None, owner_account=None, owner_id=None, maintain_end_time=None): api_request = APIRequest('ModifyInstanceMaintainTime', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "MaintainStartTime": maintain_start_time, "OwnerAccount": owner_account, "OwnerId": owner_id, "MaintainEndTime": maintain_end_time} return self._handle_request(api_request).result def describe_instance_attribute( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeInstanceAttribute', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def restore_instance( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, backup_id=None, owner_id=None): api_request = APIRequest('RestoreInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "BackupId": backup_id, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_backup_policy( self, preferred_backup_time=None, preferred_backup_period=None, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('ModifyBackupPolicy', 'GET', 'http', 'RPC', 'query') api_request._params = { "PreferredBackupTime": preferred_backup_time, "PreferredBackupPeriod": preferred_backup_period, "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_backups( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, backup_id=None, end_time=None, start_time=None, owner_id=None, page_number=None, instance_id=None, security_token=None, page_size=None): api_request = APIRequest('DescribeBackups', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "BackupId": backup_id, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "PageNumber": page_number, "InstanceId": instance_id, "SecurityToken": security_token, "PageSize": page_size} return self._handle_request(api_request).result def describe_backup_policy( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeBackupPolicy', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def create_backup( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('CreateBackup', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def switch_network( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None, vswitch_id=None, instance_id=None, security_token=None, target_network_type=None, retain_classic=None, classic_expired_days=None, vpc_id=None): api_request = APIRequest('SwitchNetwork', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "VSwitchId": vswitch_id, "InstanceId": instance_id, "SecurityToken": security_token, "TargetNetworkType": target_network_type, "RetainClassic": retain_classic, "ClassicExpiredDays": classic_expired_days, "VpcId": vpc_id} return self._handle_request(api_request).result def describe_zones( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, accept_language=None, owner_id=None): api_request = APIRequest('DescribeZones', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "AcceptLanguage": accept_language, "OwnerId": owner_id} return self._handle_request(api_request).result def delete_snapshot( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DeleteSnapshot', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def create_temp_instance( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('CreateTempInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def create_snapshot( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('CreateSnapshot', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def delete_temp_instance( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DeleteTempInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def delete_snapshot_settings( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DeleteSnapshotSettings', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def get_snapshot_settings( self, resource_owner_id=None, instance_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('GetSnapshotSettings', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_temp_instance( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeTempInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_snapshots( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, end_time=None, begin_time=None, owner_id=None): api_request = APIRequest('DescribeSnapshots', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "BeginTime": begin_time, "OwnerId": owner_id} return self._handle_request(api_request).result def restore_snapshot( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('RestoreSnapshot', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def query_task( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('QueryTask', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def switch_temp_instance( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('SwitchTempInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def set_snapshot_settings( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('SetSnapshotSettings', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def renew_multi_instance( self, resource_owner_id=None, period=None, auto_pay=None, from_app=None, resource_owner_account=None, owner_account=None, coupon_no=None, owner_id=None, security_token=None, instance_ids=None, business_info=None): api_request = APIRequest('RenewMultiInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "Period": period, "AutoPay": auto_pay, "FromApp": from_app, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "CouponNo": coupon_no, "OwnerId": owner_id, "SecurityToken": security_token, "InstanceIds": instance_ids, "BusinessInfo": business_info} return self._handle_request(api_request).result def transform_to_pre_paid( self, resource_owner_id=None, period=None, instance_id=None, auto_pay=None, from_app=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('TransformToPrePaid', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "Period": period, "InstanceId": instance_id, "AutoPay": auto_pay, "FromApp": from_app, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def renew_instance( self, resource_owner_id=None, period=None, auto_pay=None, from_app=None, resource_owner_account=None, owner_account=None, coupon_no=None, owner_id=None, instance_class=None, capacity=None, instance_id=None, security_token=None, force_upgrade=None, business_info=None): api_request = APIRequest('RenewInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "Period": period, "AutoPay": auto_pay, "FromApp": from_app, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "CouponNo": coupon_no, "OwnerId": owner_id, "InstanceClass": instance_class, "Capacity": capacity, "InstanceId": instance_id, "SecurityToken": security_token, "ForceUpgrade": force_upgrade, "BusinessInfo": business_info} return self._handle_request(api_request).result def verify_password( self, resource_owner_id=None, password=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('VerifyPassword', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "Password": password, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def modify_instance_config( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, config=None): api_request = APIRequest('ModifyInstanceConfig', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "Config": config} return self._handle_request(api_request).result def modify_instance_attribute( self, resource_owner_id=None, instance_id=None, instance_name=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None, new_password=None): api_request = APIRequest('ModifyInstanceAttribute', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "InstanceName": instance_name, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id, "NewPassword": new_password} return self._handle_request(api_request).result def flush_instance( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('FlushInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_regions( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, accept_language=None, owner_id=None): api_request = APIRequest('DescribeRegions', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "AcceptLanguage": accept_language, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_monitor_items( self, resource_owner_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeMonitorItems', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_instances( self, resource_owner_id=None, instance_status=None, resource_owner_account=None, owner_account=None, search_key=None, network_type=None, engine_version=None, owner_id=None, instance_class=None, page_number=None, vswitch_id=None, expired=None, security_token=None, instance_ids=None, architecture_type=None, vpc_id=None, page_size=None, instance_type=None, zone_id=None, charge_type=None, list_of_tag=None): api_request = APIRequest('DescribeInstances', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceStatus": instance_status, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "SearchKey": search_key, "NetworkType": network_type, "EngineVersion": engine_version, "OwnerId": owner_id, "InstanceClass": instance_class, "PageNumber": page_number, "VSwitchId": vswitch_id, "Expired": expired, "SecurityToken": security_token, "InstanceIds": instance_ids, "ArchitectureType": architecture_type, "VpcId": vpc_id, "PageSize": page_size, "InstanceType": instance_type, "ZoneId": zone_id, "ChargeType": charge_type, "Tag": list_of_tag} repeat_info = {"Tag": ('Tag', 'list', 'dict', [('Value', 'str', None, None), ('Key', 'str', None, None), ]), } verify_params(api_request._params, repeat_info) return self._handle_request(api_request).result def describe_instance_config( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DescribeInstanceConfig', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def describe_history_monitor_values( self, resource_owner_id=None, resource_owner_account=None, owner_account=None, end_time=None, start_time=None, owner_id=None, instance_id=None, security_token=None, interval_for_history=None, node_id=None, monitor_keys=None): api_request = APIRequest('DescribeHistoryMonitorValues', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "EndTime": end_time, "StartTime": start_time, "OwnerId": owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "IntervalForHistory": interval_for_history, "NodeId": node_id, "MonitorKeys": monitor_keys} return self._handle_request(api_request).result def delete_instance( self, resource_owner_id=None, instance_id=None, security_token=None, resource_owner_account=None, owner_account=None, owner_id=None): api_request = APIRequest('DeleteInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "InstanceId": instance_id, "SecurityToken": security_token, "ResourceOwnerAccount": resource_owner_account, "OwnerAccount": owner_account, "OwnerId": owner_id} return self._handle_request(api_request).result def create_instance( self, resource_owner_id=None, node_type=None, coupon_no=None, network_type=None, engine_version=None, auto_use_coupon=None, instance_class=None, capacity=None, password=None, security_token=None, instance_type=None, business_info=None, auto_renew_period=None, period=None, resource_owner_account=None, src_db_instance_id=None, owner_account=None, backup_id=None, owner_id=None, token=None, vswitch_id=None, private_ip_address=None, instance_name=None, auto_renew=None, vpc_id=None, zone_id=None, charge_type=None, config=None): api_request = APIRequest('CreateInstance', 'GET', 'http', 'RPC', 'query') api_request._params = { "ResourceOwnerId": resource_owner_id, "NodeType": node_type, "CouponNo": coupon_no, "NetworkType": network_type, "EngineVersion": engine_version, "AutoUseCoupon": auto_use_coupon, "InstanceClass": instance_class, "Capacity": capacity, "Password": password, "SecurityToken": security_token, "InstanceType": instance_type, "BusinessInfo": business_info, "AutoRenewPeriod": auto_renew_period, "Period": period, "ResourceOwnerAccount": resource_owner_account, "SrcDBInstanceId": src_db_instance_id, "OwnerAccount": owner_account, "BackupId": backup_id, "OwnerId": owner_id, "Token": token, "VSwitchId": vswitch_id, "PrivateIpAddress": private_ip_address, "InstanceName": instance_name, "AutoRenew": auto_renew, "VpcId": vpc_id, "ZoneId": zone_id, "ChargeType": charge_type, "Config": config} return self._handle_request(api_request).result

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100

0.584732

9,062

100,487

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0.0597

0.108007

0.062311

0.060307

0.852367

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0.814276

0.778027

0.762006

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0

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100,487

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101

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null

0

1

0

1

0

null

0

7

4f94a23ca7e19b56160d9eccd3849d5a44bc3779

520

py

Python

train_mosmed_timm-regnetx_002_clahe.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

train_mosmed_timm-regnetx_002_clahe.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

train_mosmed_timm-regnetx_002_clahe.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

import os ls=["python main.py --configs configs/train_mosmed_unetplusplus_timm-regnetx_002_fold0_clahe.yml", "python main.py --configs configs/train_mosmed_unetplusplus_timm-regnetx_002_fold1_clahe.yml", "python main.py --configs configs/train_mosmed_unetplusplus_timm-regnetx_002_fold2_clahe.yml", "python main.py --configs configs/train_mosmed_unetplusplus_timm-regnetx_002_fold3_clahe.yml", "python main.py --configs configs/train_mosmed_unetplusplus_timm-regnetx_002_fold4_clahe.yml", ] for l in ls: os.system(l)

47.272727

98

0.840385

80

520

5.0875

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0.12285

0.14742

0.233415

0.85258

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520

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null

0

1

0

1

null

0

9

8c0ab765bec36840bd3c85e0d62097a308db48fe

14,657

py

Python

det3d/datasets/pipelines/formating.py

Charrrrrlie/CenterPoint

51d699e306fea3b0237648088ee33a1760ab00ec

[ "MIT" ]

null

det3d/datasets/pipelines/formating.py

Charrrrrlie/CenterPoint

51d699e306fea3b0237648088ee33a1760ab00ec

[ "MIT" ]

null

det3d/datasets/pipelines/formating.py

Charrrrrlie/CenterPoint

51d699e306fea3b0237648088ee33a1760ab00ec

[ "MIT" ]

null

from det3d import torchie import numpy as np import torch from ..registry import PIPELINES class DataBundle(object): def __init__(self, data): self.data = data @PIPELINES.register_module class Reformat(object): def __init__(self, **kwargs): double_flip = kwargs.get('double_flip', False) self.double_flip = double_flip def __call__(self, res, info): meta = res["metadata"] points = res["lidar"]["points"] data_bundle = dict( metadata=meta ) if points is not None: data_bundle.update(points=points) if 'voxels' in res["lidar"]: voxels = res["lidar"]["voxels"] data_bundle.update( voxels=voxels["voxels"], shape=voxels["shape"], num_points=voxels["num_points"], num_voxels=voxels["num_voxels"], coordinates=voxels["coordinates"], ) if res["mode"] == "train": data_bundle.update(res["lidar"]["targets"]) elif res["mode"] == "val": data_bundle.update(dict(metadata=meta, )) if self.double_flip: # y axis yflip_points = res["lidar"]["yflip_points"] yflip_voxels = res["lidar"]["yflip_voxels"] yflip_data_bundle = dict( metadata=meta, points=yflip_points, voxels=yflip_voxels["voxels"], shape=yflip_voxels["shape"], num_points=yflip_voxels["num_points"], num_voxels=yflip_voxels["num_voxels"], coordinates=yflip_voxels["coordinates"], ) # x axis xflip_points = res["lidar"]["xflip_points"] xflip_voxels = res["lidar"]["xflip_voxels"] xflip_data_bundle = dict( metadata=meta, points=xflip_points, voxels=xflip_voxels["voxels"], shape=xflip_voxels["shape"], num_points=xflip_voxels["num_points"], num_voxels=xflip_voxels["num_voxels"], coordinates=xflip_voxels["coordinates"], ) # double axis flip double_flip_points = res["lidar"]["double_flip_points"] double_flip_voxels = res["lidar"]["double_flip_voxels"] double_flip_data_bundle = dict( metadata=meta, points=double_flip_points, voxels=double_flip_voxels["voxels"], shape=double_flip_voxels["shape"], num_points=double_flip_voxels["num_points"], num_voxels=double_flip_voxels["num_voxels"], coordinates=double_flip_voxels["coordinates"], ) return [data_bundle, yflip_data_bundle, xflip_data_bundle, double_flip_data_bundle], info return data_bundle, info @PIPELINES.register_module class DynamicReformat(object): def __init__(self, **kwargs): double_flip = kwargs.get('double_flip', False) self.double_flip = double_flip def __call__(self, res, info): meta = res["metadata"] points = res["lidar"]["points"] data_bundle = dict( metadata=meta ) if points is not None: data_bundle.update(points=points) if 'voxels' in res["lidar"]: voxels = res["lidar"]["voxels"] data_bundle.update( voxels=voxels["voxels"], shape=voxels["shape"], num_points=voxels["num_points"], num_voxels=voxels["num_voxels"], coordinates=voxels["coordinates"], ) if res["mode"] == "train": data_bundle.update(res["lidar"]["targets"]) elif res["mode"] == "val": data_bundle.update(dict(metadata=meta, )) if self.double_flip and 'voxels' in res["lidar"]: # y axis yflip_points = res["lidar"]["yflip_points"] yflip_voxels = res["lidar"]["yflip_voxels"] yflip_data_bundle = dict( metadata=meta, points=yflip_points, voxels=yflip_voxels["voxels"], shape=yflip_voxels["shape"], num_points=yflip_voxels["num_points"], num_voxels=yflip_voxels["num_voxels"], coordinates=yflip_voxels["coordinates"], ) # x axis xflip_points = res["lidar"]["xflip_points"] xflip_voxels = res["lidar"]["xflip_voxels"] xflip_data_bundle = dict( metadata=meta, points=xflip_points, voxels=xflip_voxels["voxels"], shape=xflip_voxels["shape"], num_points=xflip_voxels["num_points"], num_voxels=xflip_voxels["num_voxels"], coordinates=xflip_voxels["coordinates"], ) # double axis flip double_flip_points = res["lidar"]["double_flip_points"] double_flip_voxels = res["lidar"]["double_flip_voxels"] double_flip_data_bundle = dict( metadata=meta, points=double_flip_points, voxels=double_flip_voxels["voxels"], shape=double_flip_voxels["shape"], num_points=double_flip_voxels["num_points"], num_voxels=double_flip_voxels["num_voxels"], coordinates=double_flip_voxels["coordinates"], ) elif self.double_flip: # print('#'*100) yflip_points = res["lidar"]["yflip_points"] yflip_data_bundle = dict( metadata=meta, points=yflip_points, ) xflip_points = res["lidar"]["xflip_points"] xflip_data_bundle = dict( metadata=meta, points=xflip_points, ) double_flip_points = res["lidar"]["double_flip_points"] double_flip_data_bundle = dict( metadata=meta, points=double_flip_points, ) # points_rotate0_points = res["lidar"]["points_rotate0"] # points_rotate0_bundle = dict( # metadata=meta, # points=points_rotate0_points, # ) # points_rotate1_points = res["lidar"]["points_rotate1"] # points_rotate1_bundle = dict( # metadata=meta, # points=points_rotate1_points, # ) # points_rotate2_points = res["lidar"]["points_rotate2"] # points_rotate2_bundle = dict( # metadata=meta, # points=points_rotate2_points, # ) # points_rotate3_points = res["lidar"]["points_rotate3"] # points_rotate3_bundle = dict( # metadata=meta, # points=points_rotate3_points, # ) # points_rotate4_points = res["lidar"]["points_rotate4"] # points_rotate4_bundle = dict( # metadata=meta, # points=points_rotate4_points, # ) # points_rotate5_points = res["lidar"]["points_rotate5"] # points_rotate5_bundle = dict( # metadata=meta, # points=points_rotate5_points, # ) return [data_bundle, yflip_data_bundle, xflip_data_bundle, double_flip_data_bundle], info # return [data_bundle, yflip_data_bundle, xflip_data_bundle, double_flip_data_bundle, points_rotate0_bundle,points_rotate1_bundle,points_rotate2_bundle,points_rotate3_bundle,points_rotate4_bundle,points_rotate5_bundle], info return data_bundle, info @PIPELINES.register_module class DynamicScaleReformat(object): def __init__(self, **kwargs): double_flip = kwargs.get('double_flip', False) self.double_flip = double_flip def __call__(self, res, info): meta = res["metadata"] points = res["lidar"]["points"] data_bundle = dict( metadata=meta ) if points is not None: data_bundle.update(points=points) if 'voxels' in res["lidar"]: voxels = res["lidar"]["voxels"] data_bundle.update( voxels=voxels["voxels"], shape=voxels["shape"], num_points=voxels["num_points"], num_voxels=voxels["num_voxels"], coordinates=voxels["coordinates"], ) if res["mode"] == "train": data_bundle.update(res["lidar"]["targets"]) elif res["mode"] == "val": data_bundle.update(dict(metadata=meta, )) if self.double_flip and 'voxels' in res["lidar"]: # y axis yflip_points = res["lidar"]["yflip_points"] yflip_voxels = res["lidar"]["yflip_voxels"] yflip_data_bundle = dict( metadata=meta, points=yflip_points, voxels=yflip_voxels["voxels"], shape=yflip_voxels["shape"], num_points=yflip_voxels["num_points"], num_voxels=yflip_voxels["num_voxels"], coordinates=yflip_voxels["coordinates"], ) # x axis xflip_points = res["lidar"]["xflip_points"] xflip_voxels = res["lidar"]["xflip_voxels"] xflip_data_bundle = dict( metadata=meta, points=xflip_points, voxels=xflip_voxels["voxels"], shape=xflip_voxels["shape"], num_points=xflip_voxels["num_points"], num_voxels=xflip_voxels["num_voxels"], coordinates=xflip_voxels["coordinates"], ) # double axis flip double_flip_points = res["lidar"]["double_flip_points"] double_flip_voxels = res["lidar"]["double_flip_voxels"] double_flip_data_bundle = dict( metadata=meta, points=double_flip_points, voxels=double_flip_voxels["voxels"], shape=double_flip_voxels["shape"], num_points=double_flip_voxels["num_points"], num_voxels=double_flip_voxels["num_voxels"], coordinates=double_flip_voxels["coordinates"], ) elif self.double_flip: # print('#'*100) orgflip_points = res["lidar"]["org_points_scale0"] orgflip_data_bundle0 = dict( metadata=meta, points=orgflip_points, ) orgflip_points = res["lidar"]["org_points_scale1"] orgflip_data_bundle1 = dict( metadata=meta, points=orgflip_points, ) orgflip_points = res["lidar"]["org_points_scale2"] orgflip_data_bundle2 = dict( metadata=meta, points=orgflip_points, ) yflip_points = res["lidar"]["yflip_points_scale0"] yflip_data_bundle0 = dict( metadata=meta, points=yflip_points, ) yflip_points = res["lidar"]["yflip_points_scale1"] yflip_data_bundle1 = dict( metadata=meta, points=yflip_points, ) yflip_points = res["lidar"]["yflip_points_scale2"] yflip_data_bundle2 = dict( metadata=meta, points=yflip_points, ) xflip_points = res["lidar"]["xflip_points_scale0"] xflip_data_bundle0 = dict( metadata=meta, points=xflip_points, ) xflip_points = res["lidar"]["xflip_points_scale1"] xflip_data_bundle1 = dict( metadata=meta, points=xflip_points, ) xflip_points = res["lidar"]["xflip_points_scale2"] xflip_data_bundle2 = dict( metadata=meta, points=xflip_points, ) # doubleflip_points = res["lidar"]["double_flip_points_scale0"] # doubleflip_data_bundle0 = dict( # metadata=meta, # points=doubleflip_points, # ) # doubleflip_points = res["lidar"]["double_flip_points_scale0"] # doubleflip_data_bundle1 = dict( # metadata=meta, # points=doubleflip_points, # ) # doubleflip_points = res["lidar"]["double_flip_points_scale0"] # doubleflip_data_bundle2 = dict( # metadata=meta, # points=doubleflip_points, # ) return [orgflip_data_bundle0, yflip_data_bundle0, xflip_data_bundle0], info # return [orgflip_data_bundle0, yflip_data_bundle0, xflip_data_bundle0, # orgflip_data_bundle1, yflip_data_bundle1, xflip_data_bundle1, # orgflip_data_bundle2, yflip_data_bundle2, xflip_data_bundle2], info # return [orgflip_data_bundle0, yflip_data_bundle0, xflip_data_bundle0, doubleflip_data_bundle0, # orgflip_data_bundle1, yflip_data_bundle1, xflip_data_bundle1, doubleflip_data_bundle1, # orgflip_data_bundle2, yflip_data_bundle2, xflip_data_bundle2, doubleflip_data_bundle2], info return data_bundle, info

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8c350ac5d18c987d8fccb0ddda8be00c54286dc3

93

py

Python

simple_learning/__init__.py

JA-Bar/simple-learning

c59ce4231a4ca6d4c0359eeff85ca43c85e0348f

[ "MIT" ]

null

simple_learning/__init__.py

JA-Bar/simple-learning

c59ce4231a4ca6d4c0359eeff85ca43c85e0348f

[ "MIT" ]

null

simple_learning/__init__.py

JA-Bar/simple-learning

c59ce4231a4ca6d4c0359eeff85ca43c85e0348f

[ "MIT" ]

null

from simple_learning.tensor import Tensor from simple_learning.grad.function import no_grad

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338

py

Python

menpo/image/test/image_gaussian_test.py

jacksoncsy/menpo

3cac491fe30454935ed12fcaa89f453c5f6ec878

[ "BSD-3-Clause" ]

1

2021-04-20T00:36:57.000Z

menpo/image/test/image_gaussian_test.py

dykestra/menpo

3a4690f991003a8706028ddb898493ac5b53418e

[ "BSD-3-Clause" ]

null

menpo/image/test/image_gaussian_test.py

dykestra/menpo

3a4690f991003a8706028ddb898493ac5b53418e

[ "BSD-3-Clause" ]

null

import menpo def test_image_gaussian_pyramid_n_levels(): lenna = menpo.io.import_builtin_asset.lenna_png() assert len(list(lenna.gaussian_pyramid(n_levels=4))) == 4 def test_image_gaussian_pyramid_one_level(): lenna = menpo.io.import_builtin_asset.lenna_png() assert len(list(lenna.gaussian_pyramid(n_levels=1))) == 1

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4fb8f8e0297bfbb75e0c8e30c12db5fb56e9f31d

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py

Python

swagger_client/api/authorization_api.py

chbndrhnns/finapi-client

259beda8b05e912c49d2dc4c3ed71205134e5d8a

[ "MIT" ]

2

2019-04-15T05:58:21.000Z

2021-11-15T18:26:37.000Z

swagger_client/api/authorization_api.py

chbndrhnns/finapi-client

259beda8b05e912c49d2dc4c3ed71205134e5d8a

[ "MIT" ]

1

2021-06-18T09:46:25.000Z

2021-06-18T20:12:41.000Z

swagger_client/api/authorization_api.py

chbndrhnns/finapi-client

259beda8b05e912c49d2dc4c3ed71205134e5d8a

[ "MIT" ]

2

2019-07-08T13:41:09.000Z

2020-12-07T12:10:04.000Z

# coding: utf-8 """ finAPI RESTful Services finAPI RESTful Services # noqa: E501 OpenAPI spec version: v1.42.1 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from swagger_client.api_client import ApiClient class AuthorizationApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def get_token(self, grant_type, client_id, client_secret, **kwargs): # noqa: E501 """Get tokens # noqa: E501 finAPI implements the OAuth 2.0 Standard for authorizing applications and users within applications. OAuth uses the terminology of clients and users. A client represents an application that calls finAPI services. A service call might be in the context of a user of the client (e.g.: getting a user's bank connections), or outside any user context (e.g.: editing your client's configuration, or creating a new user for your client). In any case, every service call must be authorized by an access_token. This service can be used to get such an access_token, for either one of the client's users, or for the client itself. Also, this service can be used to refresh the access_token of a user that has previously requested an access_token.<br/><br/>To get a token, you must always pass a valid client identifier and client secret (=client credentials). You can get free client credentials for the sandbox <a href='http://www.finapi.io/jetzt-testen/'>here</a>. Alternatively, you can also contact us at <a href='mailto:support@finapi.io'>support@finapi.io</a>.<br/><br/>The authorization process is similar for both a user within a client, and for the client itself: <br/>• To authorize a client (i.e. application), use <code>grant_type=client_credentials</code><br/>• To authorize a user, use <code>grant_type=password</code><br/><br/>If the given parameters are valid, the service will respond with the authorization data. <br/>Here is an example of a response when authorizing a user: <br/><pre>{ \"access_token\": \"yvMbx_TgwdYE0hgOVb8N4ZOvxOukqfjzYOGRZcJiCjQuRGkVIBfjjV3YG4zKTGiY2aPn2cQTGaQOT8uo5uo7_QOXts1s5UBSVuRHc6a8X30RrGBTyqV9h26SUHcZPNbZ\", \"token_type\": \"bearer\", \"refresh_token\": \"0b9KjiBVlZLz7a4HshSAIcFuscStiXT1VzT5mgNYwCQ_dWctTDsaIjedAhD1LpsOFJ7x6K8Emf8M3VOQkwNFR9FHijALYSQw2UeRwAC2MvrOKwfF1dHmOq5VEVYEaGf6\", \"expires_in\": 3600, \"scope\": \"all\" }</pre><br/><p>Use the returned access_token for other service calls by sending it in a 'Authorization' header, with the word 'Bearer' in front of the token. Like this:</p><pre>Authorization: Bearer yvMbx_TgwdYE0hgOVb8N4ZOvxOukqfjzYOGRZcJiCjQuRGkVIBfjjV3YG4zKTGiY2aPn2cQTGaQOT8uo5uo7_QOXts1s5UBSVuRHc6a8X30RrGBTyqV9h26SUHcZPNbZ</pre><p><b>WARNING</b>: Sending the access_token as a request parameter is deprecated and will probably be no longer supported in the next release of finAPI. Please always send the access_token in the request header, as shown above.</p><p>By default, the access tokens have an expiration time of one hour (however, you can change this via the service PATCH /clientConfiguration). If a token has expired, then using the token for a service call will result in a HTTP code 401. To restore access you can simply get a new token (as it is described above) or use <code>grant_type=refresh_token</code> (which works for user-related tokens only). In the latter case you just have to pass the previously received <code>refresh_token</code> for the user.</p><p>If the user that you want to authorize is not yet verified by the client (please see the 'isUserAutoVerificationEnabled' flag in the Client Configuration), then the service will respond with HTTP code 403. If the user is locked (see 'maxUserLoginAttempts' in the Client Configuration), the service will respond with HTTP code 423.</p><p>If the current role has no privileges to call a certain service (e.g. if a user tries to create a new user, or if a client tries to access user data outside of any user context), then the request will fail with the HTTP code 403.</p><p><b>IMPORTANT NOTES:</b><br/>• Even though finAPI is not logging query parameters, it is still recommended to pass the parameters in the POST body instead of in the URL. Also, please set the Content-Type of your request to 'application/x-www-form-urlencoded' when calling this service.<br/>• You should use this service only when you actually need a new token. As long as a token exists and has not expired, the service will always return the same token for the same credentials. Calling this service repeatedly with the same credentials contradicts the idea behind the tokens in OAuth, and will have a negative impact on the performance of your application. So instead of retrieving the same tokens over and over with this service, you should cache the tokens and re-use them as long as they have not expired - or at least as long as you're using the same tokens repeatedly, e.g. for the time of an active user session in your application.</p> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.get_token(grant_type, client_id, client_secret, async=True) >>> result = thread.get() :param async bool :param str grant_type: Determines the required type of authorization:password - authorize a user; client_credentials - authorize a client;refresh_token - refresh a user's access_token. (required) :param str client_id: Client identifier (required) :param str client_secret: Client secret (required) :param str refresh_token: Refresh token. Required for grant_type=refresh_token only. :param str username: User identifier. Required for grant_type=password only. :param str password: User password. Required for grant_type=password only. :return: AccessToken If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.get_token_with_http_info(grant_type, client_id, client_secret, **kwargs) # noqa: E501 else: (data) = self.get_token_with_http_info(grant_type, client_id, client_secret, **kwargs) # noqa: E501 return data def get_token_with_http_info(self, grant_type, client_id, client_secret, **kwargs): # noqa: E501 """Get tokens # noqa: E501 finAPI implements the OAuth 2.0 Standard for authorizing applications and users within applications. OAuth uses the terminology of clients and users. A client represents an application that calls finAPI services. A service call might be in the context of a user of the client (e.g.: getting a user's bank connections), or outside any user context (e.g.: editing your client's configuration, or creating a new user for your client). In any case, every service call must be authorized by an access_token. This service can be used to get such an access_token, for either one of the client's users, or for the client itself. Also, this service can be used to refresh the access_token of a user that has previously requested an access_token.<br/><br/>To get a token, you must always pass a valid client identifier and client secret (=client credentials). You can get free client credentials for the sandbox <a href='http://www.finapi.io/jetzt-testen/'>here</a>. Alternatively, you can also contact us at <a href='mailto:support@finapi.io'>support@finapi.io</a>.<br/><br/>The authorization process is similar for both a user within a client, and for the client itself: <br/>• To authorize a client (i.e. application), use <code>grant_type=client_credentials</code><br/>• To authorize a user, use <code>grant_type=password</code><br/><br/>If the given parameters are valid, the service will respond with the authorization data. <br/>Here is an example of a response when authorizing a user: <br/><pre>{ \"access_token\": \"yvMbx_TgwdYE0hgOVb8N4ZOvxOukqfjzYOGRZcJiCjQuRGkVIBfjjV3YG4zKTGiY2aPn2cQTGaQOT8uo5uo7_QOXts1s5UBSVuRHc6a8X30RrGBTyqV9h26SUHcZPNbZ\", \"token_type\": \"bearer\", \"refresh_token\": \"0b9KjiBVlZLz7a4HshSAIcFuscStiXT1VzT5mgNYwCQ_dWctTDsaIjedAhD1LpsOFJ7x6K8Emf8M3VOQkwNFR9FHijALYSQw2UeRwAC2MvrOKwfF1dHmOq5VEVYEaGf6\", \"expires_in\": 3600, \"scope\": \"all\" }</pre><br/><p>Use the returned access_token for other service calls by sending it in a 'Authorization' header, with the word 'Bearer' in front of the token. Like this:</p><pre>Authorization: Bearer yvMbx_TgwdYE0hgOVb8N4ZOvxOukqfjzYOGRZcJiCjQuRGkVIBfjjV3YG4zKTGiY2aPn2cQTGaQOT8uo5uo7_QOXts1s5UBSVuRHc6a8X30RrGBTyqV9h26SUHcZPNbZ</pre><p><b>WARNING</b>: Sending the access_token as a request parameter is deprecated and will probably be no longer supported in the next release of finAPI. Please always send the access_token in the request header, as shown above.</p><p>By default, the access tokens have an expiration time of one hour (however, you can change this via the service PATCH /clientConfiguration). If a token has expired, then using the token for a service call will result in a HTTP code 401. To restore access you can simply get a new token (as it is described above) or use <code>grant_type=refresh_token</code> (which works for user-related tokens only). In the latter case you just have to pass the previously received <code>refresh_token</code> for the user.</p><p>If the user that you want to authorize is not yet verified by the client (please see the 'isUserAutoVerificationEnabled' flag in the Client Configuration), then the service will respond with HTTP code 403. If the user is locked (see 'maxUserLoginAttempts' in the Client Configuration), the service will respond with HTTP code 423.</p><p>If the current role has no privileges to call a certain service (e.g. if a user tries to create a new user, or if a client tries to access user data outside of any user context), then the request will fail with the HTTP code 403.</p><p><b>IMPORTANT NOTES:</b><br/>• Even though finAPI is not logging query parameters, it is still recommended to pass the parameters in the POST body instead of in the URL. Also, please set the Content-Type of your request to 'application/x-www-form-urlencoded' when calling this service.<br/>• You should use this service only when you actually need a new token. As long as a token exists and has not expired, the service will always return the same token for the same credentials. Calling this service repeatedly with the same credentials contradicts the idea behind the tokens in OAuth, and will have a negative impact on the performance of your application. So instead of retrieving the same tokens over and over with this service, you should cache the tokens and re-use them as long as they have not expired - or at least as long as you're using the same tokens repeatedly, e.g. for the time of an active user session in your application.</p> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.get_token_with_http_info(grant_type, client_id, client_secret, async=True) >>> result = thread.get() :param async bool :param str grant_type: Determines the required type of authorization:password - authorize a user; client_credentials - authorize a client;refresh_token - refresh a user's access_token. (required) :param str client_id: Client identifier (required) :param str client_secret: Client secret (required) :param str refresh_token: Refresh token. Required for grant_type=refresh_token only. :param str username: User identifier. Required for grant_type=password only. :param str password: User password. Required for grant_type=password only. :return: AccessToken If the method is called asynchronously, returns the request thread. """ all_params = ['grant_type', 'client_id', 'client_secret', 'refresh_token', 'username', 'password'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_token" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'grant_type' is set if ('grant_type' not in params or params['grant_type'] is None): raise ValueError("Missing the required parameter `grant_type` when calling `get_token`") # noqa: E501 # verify the required parameter 'client_id' is set if ('client_id' not in params or params['client_id'] is None): raise ValueError("Missing the required parameter `client_id` when calling `get_token`") # noqa: E501 # verify the required parameter 'client_secret' is set if ('client_secret' not in params or params['client_secret'] is None): raise ValueError("Missing the required parameter `client_secret` when calling `get_token`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'grant_type' in params: query_params.append(('grant_type', params['grant_type'])) # noqa: E501 if 'client_id' in params: query_params.append(('client_id', params['client_id'])) # noqa: E501 if 'client_secret' in params: query_params.append(('client_secret', params['client_secret'])) # noqa: E501 if 'refresh_token' in params: query_params.append(('refresh_token', params['refresh_token'])) # noqa: E501 if 'username' in params: query_params.append(('username', params['username'])) # noqa: E501 if 'password' in params: query_params.append(('password', params['password'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/oauth/token', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='AccessToken', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def revoke_token(self, token, **kwargs): # noqa: E501 """Revoke a token # noqa: E501 An additional endpoint for the OAuth 2.0 Standard, which allows clients to notify finAPI that a previously obtained refresh_token or access_token is no longer required. A successful request will invalidate the given token. The revocation of a particular token may also cause the revocation of related tokens and the underlying authorization grant. For token_type_hint=access_token finAPI will invalidate only the given access_token. For token_type_hint=refresh_token, finAPI will invalidate the refresh token and all access tokens based on the same authorization grant. If the token_type_hint is not defined, finAPI will revoke all access and refresh tokens (if applicable) that are based on the same authorization grant.<br/><br/>Note that the service responds with HTTP status code 200 both if the token has been revoked successfully, and if the client submitted an invalid token.<br/><br/>Note also that the client's access_token is required to authenticate the revocation.<br/><br/>Here is an example of how to revoke a user's refresh_token (and therefore also his access tokens):<pre>Authorization: Bearer {client_access_token} POST /oauth/revoke?token={refresh_token}&token_type_hint=refresh_token</pre> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.revoke_token(token, async=True) >>> result = thread.get() :param async bool :param str token: The token that the client wants to get revoked (required) :param str token_type_hint: A hint about the type of the token submitted for revocation :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.revoke_token_with_http_info(token, **kwargs) # noqa: E501 else: (data) = self.revoke_token_with_http_info(token, **kwargs) # noqa: E501 return data def revoke_token_with_http_info(self, token, **kwargs): # noqa: E501 """Revoke a token # noqa: E501 An additional endpoint for the OAuth 2.0 Standard, which allows clients to notify finAPI that a previously obtained refresh_token or access_token is no longer required. A successful request will invalidate the given token. The revocation of a particular token may also cause the revocation of related tokens and the underlying authorization grant. For token_type_hint=access_token finAPI will invalidate only the given access_token. For token_type_hint=refresh_token, finAPI will invalidate the refresh token and all access tokens based on the same authorization grant. If the token_type_hint is not defined, finAPI will revoke all access and refresh tokens (if applicable) that are based on the same authorization grant.<br/><br/>Note that the service responds with HTTP status code 200 both if the token has been revoked successfully, and if the client submitted an invalid token.<br/><br/>Note also that the client's access_token is required to authenticate the revocation.<br/><br/>Here is an example of how to revoke a user's refresh_token (and therefore also his access tokens):<pre>Authorization: Bearer {client_access_token} POST /oauth/revoke?token={refresh_token}&token_type_hint=refresh_token</pre> # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.revoke_token_with_http_info(token, async=True) >>> result = thread.get() :param async bool :param str token: The token that the client wants to get revoked (required) :param str token_type_hint: A hint about the type of the token submitted for revocation :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['token', 'token_type_hint'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method revoke_token" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'token' is set if ('token' not in params or params['token'] is None): raise ValueError("Missing the required parameter `token` when calling `revoke_token`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'token' in params: query_params.append(('token', params['token'])) # noqa: E501 if 'token_type_hint' in params: query_params.append(('token_type_hint', params['token_type_hint'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['finapi_auth'] # noqa: E501 return self.api_client.call_api( '/oauth/revoke', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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1

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1

0

null

0

1

0

9

8b224ed86f8128faac71eec5b6283fd3f87475c5

1,015

py

Python

pyQPanda/pyqpanda/Algorithm/test/test_utils.py

QianJianhua1/QPanda-2

a13c7b733031b1d0007dceaf1dae6ad447bb969c

[ "Apache-2.0" ]

631

2019-01-21T01:33:38.000Z

2022-03-31T07:33:04.000Z

pyQPanda/pyqpanda/Algorithm/test/test_utils.py

yinxx/QPanda-2

c70c4117a90978916b871424e204c5159f645642

[ "Apache-2.0" ]

24

2019-02-01T10:12:45.000Z

2021-12-02T01:49:57.000Z

pyQPanda/pyqpanda/Algorithm/test/test_utils.py

yinxx/QPanda-2

c70c4117a90978916b871424e204c5159f645642

[ "Apache-2.0" ]

80

2019-01-21T03:04:20.000Z

2022-03-29T15:38:45.000Z

''' Test Utils\n Copyright (C) Origin Quantum 2017-2018\n Licensed Under Apache Licence 2.0 ''' def test_begin_str(test_name,max_len=40): """ Use with test_end_str(test_name) to make string like this:\n ******** Test Begin ********\n ******** Test End ********** """ if (len(test_name)%2==1): star_len=(max_len-len(test_name))//2+1 return '*'*star_len+" "+test_name+" Begin "+'*'*(star_len-1) else: star_len=(max_len-len(test_name))//2 return '*'*star_len+" "+test_name+" Begin "+'*'*star_len def test_end_str(test_name,max_len=40): """ Use with test_begin_str(test_name) to make string like this:\n ******** Test Begin ********\n ******** Test End ********** """ if (len(test_name)%2==1): star_len=(max_len-len(test_name))//2+1 return '*'*star_len+" "+test_name+" End **"+'*'*(star_len-1) else: star_len=(max_len-len(test_name))//2 return '*'*star_len+" "+test_name+" End **"+'*'*star_len

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null

0

8

8ca4476924324ced011a73ec864e899b8a5387de

10,261

py

Python

mayan/apps/user_management/tests/test_api.py

eshbeata/open-paperless

6b9ed1f21908116ad2795b3785b2dbd66713d66e

[ "Apache-2.0" ]

2,743

2017-12-18T07:12:30.000Z

2022-03-27T17:21:25.000Z

mayan/apps/user_management/tests/test_api.py

eshbeata/open-paperless

6b9ed1f21908116ad2795b3785b2dbd66713d66e

[ "Apache-2.0" ]

15

2017-12-18T14:58:07.000Z

2021-03-01T20:05:05.000Z

mayan/apps/user_management/tests/test_api.py

eshbeata/open-paperless

6b9ed1f21908116ad2795b3785b2dbd66713d66e

[ "Apache-2.0" ]

257

2017-12-18T03:12:58.000Z

2022-03-25T08:59:10.000Z

from __future__ import unicode_literals from django.contrib.auth import get_user_model from django.contrib.auth.models import Group from django.urls import reverse from rest_api.tests import BaseAPITestCase from ..tests.literals import ( TEST_ADMIN_EMAIL, TEST_ADMIN_PASSWORD, TEST_ADMIN_USERNAME ) from .literals import ( TEST_GROUP_NAME, TEST_GROUP_NAME_EDITED, TEST_USER_EMAIL, TEST_USER_PASSWORD, TEST_USER_USERNAME, TEST_USER_USERNAME_EDITED ) class UserManagementUserAPITestCase(BaseAPITestCase): def setUp(self): super(UserManagementUserAPITestCase, self).setUp() self.admin_user = get_user_model().objects.create_superuser( username=TEST_ADMIN_USERNAME, email=TEST_ADMIN_EMAIL, password=TEST_ADMIN_PASSWORD ) self.client.login( username=TEST_ADMIN_USERNAME, password=TEST_ADMIN_PASSWORD ) def tearDown(self): get_user_model().objects.all().delete() super(UserManagementUserAPITestCase, self).tearDown() def test_user_create(self): response = self.client.post( reverse('rest_api:user-list'), data={ 'email': TEST_USER_EMAIL, 'password': TEST_USER_PASSWORD, 'username': TEST_USER_USERNAME, } ) self.assertEqual(response.status_code, 201) user = get_user_model().objects.get(pk=response.data['id']) self.assertEqual(user.username, TEST_USER_USERNAME) def test_user_create_with_group(self): group_1 = Group.objects.create(name='test group 1') response = self.client.post( reverse('rest_api:user-list'), data={ 'email': TEST_USER_EMAIL, 'password': TEST_USER_PASSWORD, 'username': TEST_USER_USERNAME, 'groups_pk_list': '{}'.format(group_1.pk) } ) self.assertEqual(response.status_code, 201) user = get_user_model().objects.get(pk=response.data['id']) self.assertEqual(user.username, TEST_USER_USERNAME) self.assertQuerysetEqual(user.groups.all(), (repr(group_1),)) def test_user_create_with_groups(self): group_1 = Group.objects.create(name='test group 1') group_2 = Group.objects.create(name='test group 2') response = self.client.post( reverse('rest_api:user-list'), data={ 'email': TEST_USER_EMAIL, 'password': TEST_USER_PASSWORD, 'username': TEST_USER_USERNAME, 'groups_pk_list': '{},{}'.format(group_1.pk, group_2.pk) } ) self.assertEqual(response.status_code, 201) user = get_user_model().objects.get(pk=response.data['id']) self.assertEqual(user.username, TEST_USER_USERNAME) self.assertQuerysetEqual( user.groups.all().order_by('name'), (repr(group_1), repr(group_2)) ) def test_user_create_login(self): response = self.client.post( reverse('rest_api:user-list'), data={ 'email': TEST_USER_EMAIL, 'password': TEST_USER_PASSWORD, 'username': TEST_USER_USERNAME, } ) self.assertEqual(response.status_code, 201) self.assertTrue( self.client.login( username=TEST_USER_USERNAME, password=TEST_USER_PASSWORD ) ) def test_user_create_login_password_change(self): response = self.client.post( reverse('rest_api:user-list'), data={ 'email': TEST_USER_EMAIL, 'password': 'bad_password', 'username': TEST_USER_USERNAME, } ) self.assertEqual(response.status_code, 201) self.assertFalse( self.client.login( username=TEST_USER_USERNAME, password=TEST_USER_PASSWORD ) ) user = get_user_model().objects.get(pk=response.data['id']) response = self.client.patch( reverse('rest_api:user-detail', args=(user.pk,)), data={ 'password': TEST_USER_PASSWORD, } ) self.assertTrue( self.client.login( username=TEST_USER_USERNAME, password=TEST_USER_PASSWORD ) ) def test_user_edit_via_put(self): user = get_user_model().objects.create_user( email=TEST_USER_EMAIL, password=TEST_USER_PASSWORD, username=TEST_USER_USERNAME ) response = self.client.put( reverse('rest_api:user-detail', args=(user.pk,)), data={'username': TEST_USER_USERNAME_EDITED} ) self.assertEqual(response.status_code, 200) user.refresh_from_db() self.assertEqual(user.username, TEST_USER_USERNAME_EDITED) def test_user_edit_via_patch(self): user = get_user_model().objects.create_user( email=TEST_USER_EMAIL, password=TEST_USER_PASSWORD, username=TEST_USER_USERNAME ) response = self.client.patch( reverse('rest_api:user-detail', args=(user.pk,)), data={'username': TEST_USER_USERNAME_EDITED} ) self.assertEqual(response.status_code, 200) user.refresh_from_db() self.assertEqual(user.username, TEST_USER_USERNAME_EDITED) def test_user_edit_remove_groups_via_patch(self): user = get_user_model().objects.create_user( email=TEST_USER_EMAIL, password=TEST_USER_PASSWORD, username=TEST_USER_USERNAME ) group_1 = Group.objects.create(name='test group 1') user.groups.add(group_1) response = self.client.patch( reverse('rest_api:user-detail', args=(user.pk,)), ) self.assertEqual(response.status_code, 200) user.refresh_from_db() self.assertQuerysetEqual( user.groups.all().order_by('name'), (repr(group_1),) ) def test_user_edit_add_groups_via_patch(self): user = get_user_model().objects.create_user( email=TEST_USER_EMAIL, password=TEST_USER_PASSWORD, username=TEST_USER_USERNAME ) group_1 = Group.objects.create(name='test group 1') response = self.client.patch( reverse('rest_api:user-detail', args=(user.pk,)), data={'groups_pk_list': '{}'.format(group_1.pk)} ) self.assertEqual(response.status_code, 200) user.refresh_from_db() self.assertQuerysetEqual( user.groups.all().order_by('name'), (repr(group_1),) ) def test_user_delete(self): user = get_user_model().objects.create_user( email=TEST_USER_EMAIL, password=TEST_USER_PASSWORD, username=TEST_USER_USERNAME ) response = self.client.delete( reverse('rest_api:user-detail', args=(user.pk,)) ) self.assertEqual(response.status_code, 204) with self.assertRaises(get_user_model().DoesNotExist): get_user_model().objects.get(pk=user.pk) def test_user_group_list(self): group = Group.objects.create(name=TEST_GROUP_NAME) user = get_user_model().objects.create_user( email=TEST_USER_EMAIL, password=TEST_USER_PASSWORD, username=TEST_USER_USERNAME ) user.groups.add(group) response = self.client.get( reverse('rest_api:users-group-list', args=(user.pk,)) ) self.assertEqual(response.status_code, 200) self.assertEqual(response.json()['results'][0]['name'], TEST_GROUP_NAME) def test_user_group_add(self): group = Group.objects.create(name=TEST_GROUP_NAME) user = get_user_model().objects.create_user( email=TEST_USER_EMAIL, password=TEST_USER_PASSWORD, username=TEST_USER_USERNAME ) response = self.client.post( reverse( 'rest_api:users-group-list', args=(user.pk,) ), data={ 'group_pk_list': '{}'.format(group.pk) } ) self.assertEqual(response.status_code, 201) self.assertEqual(group.user_set.first(), user) class UserManagementGroupAPITestCase(BaseAPITestCase): def setUp(self): super(UserManagementGroupAPITestCase, self).setUp() self.admin_user = get_user_model().objects.create_superuser( username=TEST_ADMIN_USERNAME, email=TEST_ADMIN_EMAIL, password=TEST_ADMIN_PASSWORD ) self.client.login( username=TEST_ADMIN_USERNAME, password=TEST_ADMIN_PASSWORD ) def tearDown(self): get_user_model().objects.all().delete() super(UserManagementGroupAPITestCase, self).tearDown() def test_group_create(self): response = self.client.post( reverse('rest_api:group-list'), data={'name': TEST_GROUP_NAME} ) self.assertEqual(response.status_code, 201) group = Group.objects.get(pk=response.data['id']) self.assertEqual(group.name, TEST_GROUP_NAME) def test_group_edit_via_put(self): group = Group.objects.create(name=TEST_GROUP_NAME) response = self.client.put( reverse('rest_api:group-detail', args=(group.pk,)), data={ 'name': TEST_GROUP_NAME_EDITED } ) self.assertEqual(response.status_code, 200) group.refresh_from_db() self.assertEqual(group.name, TEST_GROUP_NAME_EDITED) def test_group_edit_via_patch(self): group = Group.objects.create(name=TEST_GROUP_NAME) response = self.client.patch( reverse('rest_api:group-detail', args=(group.pk,)), data={ 'name': TEST_GROUP_NAME_EDITED } ) self.assertEqual(response.status_code, 200) group.refresh_from_db() self.assertEqual(group.name, TEST_GROUP_NAME_EDITED) def test_group_delete(self): group = Group.objects.create(name=TEST_GROUP_NAME) response = self.client.delete( reverse('rest_api:group-detail', args=(group.pk,)) ) self.assertEqual(response.status_code, 204) self.assertEqual(Group.objects.count(), 0)

32.993569

80

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0.072218

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0.063002

0.090566

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0.763249

0.750615

0.723708

0

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0.262548

10,261

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33.1

0.79622

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0.083333

false

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null

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null

0

1

0

7

8cc23d6e16dec99454b8cb44433eaca01fc806b7

11,100

py

Python

backend/microservices/auth/__test__/controller_test/register.py

MuhamedAbdalla/Automatic-Audio-Book-Based-On-Emotion-Detection

72130ad037b900461af5be6d80b27ab29c81de5e

[ "MIT" ]

3

2021-04-26T00:17:14.000Z

2021-07-04T15:30:09.000Z

backend/microservices/auth/__test__/controller_test/register.py

MuhamedAbdalla/Automatic-Audio-Book-Based-On-Emotion-Detection

72130ad037b900461af5be6d80b27ab29c81de5e

[ "MIT" ]

null

backend/microservices/auth/__test__/controller_test/register.py

MuhamedAbdalla/Automatic-Audio-Book-Based-On-Emotion-Detection

72130ad037b900461af5be6d80b27ab29c81de5e

[ "MIT" ]

null

import unittest import json from controller import app from __test__.core_test.util import * class RegisterTestCase(unittest.TestCase): def setUp(self): app.testing = True self.app = app.test_client() def test_register_with_valid_data(self): first_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH ) last_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) email = generate_lowercase_string_of_length(USER_EMAIL_MAX_LENGTH - len("@gmail.com")) + "@gmail.com" phone = "+201234567890" password = generate_lowercase_string_of_length(USER_PASSWORD_MAX_LENGTH) gender = "m" birthday = datetime(1999, 7, 24) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert res is not None assert "201" in res.status res = self.app.post(LOGIN_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password}) assert res is not None assert "200" in res.status res = json.loads(res.data) assert RES_ACCESS_TOKEN_KEY_NAME in res assert RES_REFRESH_TOKEN_KEY_NAME in res def test_register_user_with_invalid_email(self): first_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) last_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) email = generate_lowercase_string_of_length(USER_EMAIL_MAX_LENGTH - len("@gmail.com")) + "l@gmail.com" phone = "+201234567890" password = generate_lowercase_string_of_length(USER_PASSWORD_MAX_LENGTH) gender = "m" birthday = datetime(1999, 7, 24) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status email = generate_lowercase_string_of_length(USER_EMAIL_MAX_LENGTH - len("@gmail.com")) + "gmail.com" res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status email = generate_lowercase_string_of_length(USER_EMAIL_MAX_LENGTH - len("@gmail.com")) + "@gmailcom" res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status def test_register_user_with_invalid_first_name(self): first_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH + 1) last_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) email = generate_lowercase_string_of_length(USER_EMAIL_MAX_LENGTH - len("@gmail.com")) + "@gmail.com" phone = "+201234567890" password = generate_lowercase_string_of_length(USER_PASSWORD_MAX_LENGTH) gender = "m" birthday = datetime(1999, 7, 24) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status first_name = generate_lowercase_string_of_length(USER_NAME_MIN_LENGTH - 1) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status def test_register_user_with_invalid_last_name(self): first_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) last_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH + 1) email = generate_lowercase_string_of_length(USER_EMAIL_MAX_LENGTH - len("@gmail.com")) + "@gmail.com" phone = "+201234567890" password = generate_lowercase_string_of_length(USER_PASSWORD_MAX_LENGTH) gender = "m" birthday = datetime(1999, 7, 24) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status last_name = generate_lowercase_string_of_length(USER_NAME_MIN_LENGTH - 1) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status def test_register_user_with_invalid_phone(self): first_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) last_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) email = generate_lowercase_string_of_length(USER_EMAIL_MAX_LENGTH - len("@gmail.com")) + "@gmail.com" phone = "01234567890" password = generate_lowercase_string_of_length(USER_PASSWORD_MAX_LENGTH) gender = "m" birthday = datetime(1999, 7, 24) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status def test_register_user_with_invalid_password_length(self): first_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) last_name = generate_lowercase_string_of_length(USER_NAME_MAX_LENGTH) email = generate_lowercase_string_of_length(USER_EMAIL_MAX_LENGTH - len("@gmail.com")) + "@gmail.com" phone = "+201234567890" password = generate_lowercase_string_of_length(USER_PASSWORD_MAX_LENGTH + 1) gender = "m" birthday = datetime(1999, 7, 24) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status password = generate_lowercase_string_of_length(USER_PASSWORD_MIN_LENGTH - 1) res = self.app.post(REGISTER_ABS_ENDPOINT_NAME, data={REQ_USER_EMAIL_KEY_NAME: email, REQ_USER_PASSWORD_KEY_NAME: password, REQ_USER_FIRST_NAME_KEY_NAME: first_name, REQ_USER_LAST_NAME_KEY_NAME: last_name, REQ_USER_BIRTHDAY_KEY_NAME: birthday.strftime(REQ_USER_BIRTHDAY_FORMAT), REQ_USER_PHONE_KEY_NAME: phone, REQ_USER_GENDER_KEY_NAME: gender}) assert "400" in res.status

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60.326087

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1

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1

0

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8cd13df92238111ccfe66601635f4df99728d4f8

21,077

py

Python

muri/muda.py

dtsukiyama/muri

a9c935edf010bcf0f63988668a166b57d7d7dad8

[ "MIT" ]

1

2019-08-13T02:42:17.000Z

muri/muda.py

dtsukiyama/muri

a9c935edf010bcf0f63988668a166b57d7d7dad8

[ "MIT" ]

5

2021-03-19T01:41:07.000Z

2022-03-11T23:51:26.000Z

muri/muda.py

dtsukiyama/muri

a9c935edf010bcf0f63988668a166b57d7d7dad8

[ "MIT" ]

null

from __future__ import division import argparse import os import time import chainer import numpy as np from PIL import Image import six from muri.lib import iproc from muri.lib import reconstruct from muri.lib import srcnn from muri.lib import utils class Namespace: def __init__(self, **kwargs): self.__dict__.update(kwargs) class Validate(object): @classmethod def model(cls, model): models = ['vgg7','upresnet10','upconv7','resnet10'] if model.lower() not in models: raise ValueError('Model does not exist. Only the following models are acceptable: {}, {}, {}, {}'.format(models[0], models[1], models[2], models[3])) @classmethod def ns_model(cls, model): models = ['upresnet10','upconv7','resnet10'] if model.lower() not in models: raise ValueError('Model does not exist. Only the following models are acceptable: {}, {}, {}'.format(models[0], models[1], models[2])) @classmethod def color(cls, color): colors = ['rgb', 'y'] if color not in colors: raise ValueError('Only two color models available: {} and {}'.format(colors[0], colors[1])) @classmethod def noise(cls, noise_level): levels = [0,1,2,3] if noise_level not in levels: raise ValueError('Please set your noise level accordingly, between 0 and 3') # scale models class Scale(object): def __init__(self, model='VGG7', color='rgb', tta_level=8, tta=False, batch_size=16, block_size=128, scale_ratio=2.0, width=0, height=0, shorter_side=0, longer_side=0, quality=None, extension='png'): Validate.model(model) Validate.color(color) self.model_directory = 'muri/models/{}'.format(model.lower()) self.models = {} self.channel = 3 if color == 'rgb' else 1 self.color = color self.model = model self.tta_level = tta_level self.tta = tta self.batch_size = batch_size self.block_size = block_size self.scale_ratio = scale_ratio self.width = width self.height = height self.shorter_side = shorter_side self.longer_side = longer_side self.quality = quality self.extension = extension def config(self): settings = Namespace() settings.model_dir = self.model_directory settings.color = self.color settings.model = self.model settings.ch = self.channel settings.tta_level = self.tta_level settings.batch_size = self.batch_size settings.block_size = self.block_size settings.scale_ratio = self.scale_ratio settings.height = self.height settings.width = self.width settings.shorter_side = self.shorter_side settings.longer_side = self.longer_side settings.tta = self.tta settings.quality = self.quality settings.extension = self.extension return settings def cpu(self): model_name = 'anime_style_scale_{}.npz'.format(self.color) model_path = os.path.join(self.model_directory, model_name) self.models['scale'] = srcnn.archs[self.model](self.channel) chainer.serializers.load_npz(model_path, self.models['scale']) return self.models def gpu(self, n_gpu): model_name = 'anime_style_scale_{}.npz'.format(self.color) model_path = os.path.join(self.model_directory, model_name) self.models['scale'] = srcnn.archs[self.model](self.channel) chainer.serializers.load_npz(model_path, self.models['scale']) chainer.backends.cuda.check_cuda_available() chainer.backends.cuda.get_device(n_gpu).use() for _, model in self.models.items(): model.to_gpu() return self.models class Noise(object): def __init__(self, model='VGG7', noise_level = 1, color='rgb', tta_level=8, tta=False, batch_size=16, block_size=128, scale_ratio=2.0, width=0, height=0, shorter_side=0, longer_side=0, quality=None, extension='png'): Validate.model(model) Validate.color(color) Validate.noise(noise_level) self.model_directory = 'muri/models/{}'.format(model.lower()) self.models = {} self.channel = 3 if color == 'rgb' else 1 self.color = color self.noise_level = noise_level self.model = model self.tta_level = tta_level self.tta = tta self.batch_size = batch_size self.block_size = block_size self.scale_ratio = scale_ratio self.width = width self.height = height self.shorter_side = shorter_side self.longer_side = longer_side self.quality = quality self.extension = extension def config(self): settings = Namespace() settings.model_dir = self.model_directory settings.color = self.color settings.noise_level = self.noise_level settings.model = self.model settings.ch = self.channel settings.tta_level = self.tta_level settings.batch_size = self.batch_size settings.block_size = self.block_size settings.scale_ratio = self.scale_ratio settings.height = self.height settings.width = self.width settings.shorter_side = self.shorter_side settings.longer_side = self.longer_side settings.tta = self.tta settings.quality = self.quality settings.extension = self.extension return settings def cpu(self): model_name = 'anime_style_noise{}_{}.npz'.format(self.noise_level, self.color) model_path = os.path.join(self.model_directory, model_name) if not os.path.exists(model_path): model_name = 'anime_style_noise{}_scale_{}.npz'.format(self.noise_level, self.color) model_path = os.path.join(self.model_directory, model_name) self.models['noise'] = srcnn.archs[self.model](self.channel) chainer.serializers.load_npz(model_path, self.models['noise']) return self.models def gpu(self, n_gpu): model_name = 'anime_style_noise{}_{}.npz'.format(self.noise_level, self.color) model_path = os.path.join(self.model_directory, model_name) if not os.path.exists(model_path): model_name = 'anime_style_noise{}_scale_{}.npz'.format(self.noise_level, self.color) model_path = os.path.join(self.model_directory, model_name) self.models['noise'] = srcnn.archs[self.model](self.channel) chainer.serializers.load_npz(model_path, self.models['noise']) chainer.backends.cuda.check_cuda_available() chainer.backends.cuda.get_device(n_gpu).use() for _, model in self.models.items(): model.to_gpu() return self.models class NoiseScale(object): def __init__(self, model='UpConv7', noise_level=1, color='rgb', tta_level=8, tta=False, batch_size=16, block_size=128, scale_ratio=2.0, width=0, height=0, shorter_side=0, longer_side=0, quality=None, extension='png'): Validate.ns_model(model) Validate.color(color) Validate.noise(noise_level) self.model_directory = 'muri/models/{}'.format(model.lower()) self.models = {} self.channel = 3 if color == 'rgb' else 1 self.color = color self.noise_level = noise_level self.model = model self.tta_level = tta_level self.tta = tta self.batch_size = batch_size self.block_size = block_size self.scale_ratio = scale_ratio self.width = width self.height = height self.shorter_side = shorter_side self.longer_side = longer_side self.quality = quality self.extension = extension def config(self): settings = Namespace() settings.model_dir = self.model_directory settings.color = self.color settings.noise_level = self.noise_level settings.model = self.model settings.ch = self.channel settings.tta_level = self.tta_level settings.batch_size = self.batch_size settings.block_size = self.block_size settings.scale_ratio = self.scale_ratio settings.height = self.height settings.width = self.width settings.shorter_side = self.shorter_side settings.longer_side = self.longer_side settings.tta = self.tta settings.quality = self.quality settings.extension = self.extension return settings def cpu(self): model_name = 'anime_style_noise{}_scale_{}.npz'.format(self.noise_level, self.color) model_path = os.path.join(self.model_directory, model_name) if os.path.exists(model_path): self.models['noise_scale'] = srcnn.archs[self.model](self.channel) chainer.serializers.load_npz(model_path, self.models['noise_scale']) alpha_model_name = 'anime_style_scale_{}.npz'.format(self.color) alpha_model_path = os.path.join(self.model_directory, alpha_model_name) self.models['alpha'] = srcnn.archs[self.model](self.channel) chainer.serializers.load_npz(alpha_model_path, self.models['alpha']) return self.models def gpu(self, n_gpu): model_name = 'anime_style_noise{}_{}.npz'.format(self.noise_level, self.color) model_path = os.path.join(self.model_directory, model_name) if os.path.exists(model_path): self.models['noise_scale'] = srcnn.archs[self.model](self.channel) chainer.serializers.load_npz(model_path, self.models['noise_scale']) alpha_model_name = 'anime_style_scale_{}.npz'.format(self.color) alpha_model_path = os.path.join(self.model_directory, alpha_model_name) self.models['alpha'] = srcnn.archs[self.model](self.channel) chainer.serializers.load_npz(alpha_model_path, self.models['alpha']) chainer.serializers.load_npz(model_path, models['noise']) chainer.backends.cuda.check_cuda_available() chainer.backends.cuda.get_device(n_gpu).use() for _, model in self.models.items(): model.to_gpu() return self.models class Transform(object): def __init__(self, models, settings, extension='png'): self.models = models self.input_exts = ['.png', '.jpg', '.jpeg', '.bmp', '.tif', '.tiff', '.webp'] self.output_exts = ['.png', '.webp'] self.settings = settings def denoise_image(self, src, model): dst, alpha = self.split_alpha(src, model) six.print_('Level {} denoising...'.format(self.settings.noise_level), end=' ', flush=True) if self.settings.tta: dst = reconstruct.image_tta( dst, model, self.settings.tta_level, self.settings.block_size, self.settings.batch_size) else: dst = reconstruct.image(dst, model, self.settings.block_size, self.settings.batch_size) if model.inner_scale != 1: dst = dst.resize((src.size[0], src.size[1]), Image.LANCZOS) six.print_('OK') if alpha is not None: dst.putalpha(alpha) return dst def split_alpha(self, src, model): alpha = None if src.mode in ('L', 'RGB', 'P'): if isinstance(src.info.get('transparency'), bytes): src = src.convert('RGBA') rgb = src.convert('RGB') if src.mode in ('LA', 'RGBA'): six.print_('Splitting alpha channel...', end=' ', flush=True) alpha = src.split()[-1] rgb = iproc.alpha_make_border(rgb, alpha, model) six.print_('OK') return rgb, alpha def upscale_image(self, src, scale_model, alpha_model=None): dst, alpha = self.split_alpha(src, scale_model) for i in range(int(np.ceil(np.log2(self.settings.scale_ratio)))): six.print_('2.0x upscaling...', end=' ', flush=True) model = scale_model if i == 0 or alpha_model is None else alpha_model if model.inner_scale == 1: dst = iproc.nn_scaling(dst, 2) # Nearest neighbor 2x scaling alpha = iproc.nn_scaling(alpha, 2) # Nearest neighbor 2x scaling if self.settings.tta: dst = reconstruct.image_tta( dst, model, self.settings.tta_level, self.settings.block_size, self.settings.batch_size) else: dst = reconstruct.image(dst, model, self.settings.block_size, self.settings.batch_size) if alpha_model is None: alpha = reconstruct.image( alpha, scale_model, self.settings.block_size, self.settings.batch_size) else: alpha = reconstruct.image( alpha, alpha_model, self.settings.block_size, self.settings.batch_size) six.print_('OK') dst_w = int(np.round(src.size[0] * self.settings.scale_ratio)) dst_h = int(np.round(src.size[1] * self.settings.scale_ratio)) if dst_w != dst.size[0] or dst_h != dst.size[1]: six.print_('Resizing...', end=' ', flush=True) dst = dst.resize((dst_w, dst_h), Image.LANCZOS) six.print_('OK') if alpha is not None: if alpha.size[0] != dst_w or alpha.size[1] != dst_h: alpha = alpha.resize((dst_w, dst_h), Image.LANCZOS) dst.putalpha(alpha) return dst def build_filelist(self, input, output): outname = None outdir = output outext = '.' + self.settings.extension if os.path.isdir(input): filelist = utils.load_filelist(input) else: tmpname, tmpext = os.path.splitext(os.path.basename(output)) if tmpext in self.output_exts: outext = tmpext outname = tmpname outdir = os.path.dirname(output) outdir = './' if outdir == '' else outdir elif not tmpext == '': raise ValueError('Format {} is not supported'.format(tmpext)) filelist = [input] # create outpur directory if not os.path.exists(outdir): os.makedirs(outdir) return outext, outname, outdir, filelist def process_image(self, outext, outname, outdir, filelist): for path in filelist: if outname is None or len(filelist) > 1: outname, outext = os.path.splitext(os.path.basename(path)) outpath = os.path.join(outdir, '{}{}'.format(outname, outext)) if outext.lower() in self.input_exts: src = Image.open(path) w, h = src.size[:2] if self.settings.width != 0: self.settings.scale_ratio = self.settings.width / w elif self.settings.height != 0: self.settings.scale_ratio = self.settings.height / h elif self.settings.shorter_side != 0: if w < h: self.settings.scale_ratio = self.settings.shorter_side / w else: self.settings.scale_ratio = self.settings.shorter_side / h elif self.settings.longer_side != 0: if w > h: self.settings.scale_ratio = self.settings.longer_side / w else: self.settings.scale_ratio = self.settings.longer_side / h dst = src.copy() outname += '_(tta{})'.format(self.settings.tta_level) if self.settings.tta else '_' return outdir, outpath, outname, dst, src def process_collection(self, outext, outname, outdir, filelist): collection = [] for path in filelist: if outname is None or len(filelist) > 1: outname, outext = os.path.splitext(os.path.basename(path)) outpath = os.path.join(outdir, '{}{}'.format(outname, outext)) if outext.lower() in self.input_exts: src = Image.open(path) w, h = src.size[:2] if self.settings.width != 0: self.settings.scale_ratio = self.settings.width / w elif self.settings.height != 0: self.settings.scale_ratio = self.settings.height / h elif self.settings.shorter_side != 0: if w < h: self.settings.scale_ratio = self.settings.shorter_side / w else: self.settings.scale_ratio = self.settings.shorter_side / h elif self.settings.longer_side != 0: if w > h: self.settings.scale_ratio = self.settings.longer_side / w else: self.settings.scale_ratio = self.settings.longer_side / h dst = src.copy() outname += '_(tta{})'.format(self.settings.tta_level) if self.settings.tta else '_' collection.append((outdir, outpath, outname, dst, src)) return collection def scale(self, input, output): outext, outname, outdir, filelist = self.build_filelist(input, output) collection = self.process_collection(outext, outname, outdir, filelist) for features in collection: outdir = features[0] outpath = features[1] outname = features[2] dst = features[3] src = features[4] outname += '(scale{:.1f}x)'.format(self.settings.scale_ratio) dst = self.upscale_image(dst, self.models['scale']) outname += '({}_{}){}'.format(self.settings.model, self.settings.color, outext) if os.path.exists(outpath): outpath = os.path.join(outdir, outname) lossless = self.settings.quality is None quality = 100 if lossless else self.settings.quality icc_profile = src.info.get('icc_profile') icc_profile = "" if icc_profile is None else icc_profile dst.convert(src.mode).save(outpath, quality=quality, lossless=lossless, icc_profile=icc_profile) six.print_('Saved as \'{}\''.format(outpath)) def noise(self, input, output): outext, outname, outdir, filelist = self.build_filelist(input, output) collection = self.process_collection(outext, outname, outdir, filelist) for features in collection: outdir = features[0] outpath = features[1] outname = features[2] dst = features[3] src = features[4] outname += '(noise{})'.format(self.settings.noise_level) dst = self.denoise_image(dst, self.models['noise']) outname += '({}_{}){}'.format(self.settings.model, self.settings.color, outext) if os.path.exists(outpath): outpath = os.path.join(outdir, outname) lossless = self.settings.quality is None quality = 100 if lossless else self.settings.quality icc_profile = src.info.get('icc_profile') icc_profile = "" if icc_profile is None else icc_profile dst.convert(src.mode).save(outpath, quality=quality, lossless=lossless, icc_profile=icc_profile) six.print_('Saved as \'{}\''.format(outpath)) def noise_scale(self, input, output): outext, outname, outdir, filelist = self.build_filelist(input, output) collection = self.process_collection(outext, outname, outdir, filelist) for features in collection: outdir = features[0] outpath = features[1] outname = features[2] dst = features[3] src = features[4] outname += '(noise{}_scale{:.1f}x)'.format(self.settings.noise_level, self.settings.scale_ratio) dst = self.upscale_image(dst, self.models['noise_scale'], self.models['alpha']) outname += '({}_{}){}'.format(self.settings.model, self.settings.color, outext) if os.path.exists(outpath): outpath = os.path.join(outdir, outname) lossless = self.settings.quality is None quality = 100 if lossless else self.settings.quality icc_profile = src.info.get('icc_profile') icc_profile = "" if icc_profile is None else icc_profile dst.convert(src.mode).save(outpath, quality=quality, lossless=lossless, icc_profile=icc_profile) six.print_('Saved as \'{}\''.format(outpath))

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0.827198

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8cee9632a8eccfe71c578d581c03644a24ff23fd

30,781

py

Python

errorcam/models/attention_refine/atten_refine_network.py

frkl/SOBERT-XVQA-demo

c99d2f36d9ed275dfd3ba25c200019bbde197d4f

[ "Apache-2.0" ]

2

2021-07-25T12:44:29.000Z

2021-07-27T08:55:48.000Z

errorcam/models/attention_refine/atten_refine_network.py

frkl/SOBERT-XVQA-demo

c99d2f36d9ed275dfd3ba25c200019bbde197d4f

[ "Apache-2.0" ]

null

errorcam/models/attention_refine/atten_refine_network.py

frkl/SOBERT-XVQA-demo

c99d2f36d9ed275dfd3ba25c200019bbde197d4f

[ "Apache-2.0" ]

1

2021-07-25T12:44:30.000Z

import torch from torch import nn from torch.nn import functional as F from math import sqrt import pdb # a custom loss, not used def softXEnt (input, target): logprobs = torch.nn.functional.log_softmax (input, dim = 1) return -(target * logprobs).sum() / input.shape[0] class attention_refine_net(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=128, q_feat_dim=300, im_feat_dim=36*2048, out_atten_dim=14*14): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Sequential( nn.Linear(im_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.linear_block_attention_out = nn.Sequential( nn.Linear(hidden_feat_size*3, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size,14*14), nn.Softmax() ) def forward(self, attention, im_feat, q_feat): att_feats = self.atten_input(attention) im_feats = self.im_feat_in(im_feat) q_feats = self.question_feat_in(q_feat) concat_feat = torch.cat((att_feats, im_feats, q_feats), dim=1) att_out = self.linear_block_attention_out(concat_feat) return {'refined_attn':att_out} class attention_refine_net_ansconf(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=64, q_feat_dim=300, im_feat_dim=36*2048, ans_dim=3000, out_atten_dim=14*14): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Sequential( nn.Linear(im_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.linear_block_attention_out = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size,14*14), nn.Softmax() ) def forward(self, attention, im_feat, q_feat, ans_scores): att_feats = self.atten_input(attention) im_feats = self.im_feat_in(im_feat) q_feats = self.question_feat_in(q_feat) ans_score_feat = self.answer_score_in(ans_scores) concat_feat = torch.cat((att_feats, im_feats, q_feats, ans_score_feat), dim=1) att_out = self.linear_block_attention_out(concat_feat) return {'refined_attn':att_out} class attention_refine_net_corrpred(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=64, q_feat_dim=300, im_feat_dim=36*2048, ans_dim=3000, out_atten_dim=14*14, att_out_nonlin="Softmax"): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size*2), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Sequential( nn.Linear(im_feat_dim, hidden_feat_size*2), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size*2), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size*2), nn.LeakyReLU(0.1) ) self.concat2feat = nn.Sequential( nn.Linear(hidden_feat_size*8, hidden_feat_size*4), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size*4, hidden_feat_size*3), nn.LeakyReLU(0.1), ) self.linear_block_attention_out = nn.Sequential( nn.Linear(hidden_feat_size*3, hidden_feat_size*3), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size*3,14*14), getattr(nn, att_out_nonlin)() ) self.linear_block_corr_pred = nn.Sequential( nn.Linear(hidden_feat_size*3, 1), nn.Sigmoid() ) def forward(self, attention, im_feat, q_feat, ans_scores): att_feats = self.atten_input(attention) im_feats = self.im_feat_in(im_feat) q_feats = self.question_feat_in(q_feat) ans_score_feat = self.answer_score_in(ans_scores) concat_feat = torch.cat((att_feats, im_feats, q_feats, ans_score_feat), dim=1) feats = self.concat2feat(concat_feat) refined_attention = self.linear_block_attention_out(feats) corr_pred = self.linear_block_corr_pred(feats) return {'refined_attn':refined_attention, 'corr_pred':corr_pred} class attention_refine_net_anspred(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=64, q_feat_dim=300, im_feat_dim=36*2048, ans_dim=3000, out_atten_dim=14*14, att_out_nonlin="Softmax"): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size*2), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Sequential( nn.Linear(im_feat_dim, hidden_feat_size*2), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size*2), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size*2), nn.LeakyReLU(0.1) ) self.concat2feat = nn.Sequential( nn.Linear(hidden_feat_size*8, hidden_feat_size*4), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size*4, hidden_feat_size*3), nn.LeakyReLU(0.1), ) self.linear_block_attention_out = nn.Sequential( nn.Linear(hidden_feat_size*3, hidden_feat_size*3), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size*3,14*14), getattr(nn, att_out_nonlin)() ) self.linear_block_ans_pred = nn.Linear(hidden_feat_size*3, ans_dim) self.att_out_nonlin = att_out_nonlin def forward(self, attention, im_feat, q_feat, ans_scores): att_feats = self.atten_input(attention) im_feats = self.im_feat_in(im_feat) q_feats = self.question_feat_in(q_feat) ans_score_feat = self.answer_score_in(ans_scores) concat_feat = torch.cat((att_feats, im_feats, q_feats, ans_score_feat), dim=1) feats = self.concat2feat(concat_feat) refined_attention = self.linear_block_attention_out(feats) ans_pred = self.linear_block_ans_pred(feats) return {'refined_attn':refined_attention, 'ans_pred':ans_pred} class uncertain_attention_net_cam(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048), ans_dim=3129, num_class=1): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU() ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) if num_class==1: self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*4, num_class), nn.Sigmoid() ) else: self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size), nn.Linear(hidden_feat_size, hidden_feat_size), nn.Linear(hidden_feat_size, hidden_feat_size//2), nn.Linear(hidden_feat_size//2, num_class) ) self.gradients = [] def save_gradients(self, grad): self.gradients = [grad] def forward(self, attention, im_feat, q_feat, ans_scores): att_feats = self.atten_input(attention) im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) q_feats = self.question_feat_in(q_feat) ans_feat = self.answer_score_in(ans_scores) concat_feats = torch.cat((att_feats, im_feats, q_feats, ans_feat), dim=1) corr_pred = self.corr_pred_layer(concat_feats) return {'wrong_pred':corr_pred, 'im_feature':[im_feats_feature]} class uncertainatt_refinedatt_net_cam(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048), ans_dim=3129, ques_cam=False): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU() ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size), nn.LeakyReLU(), nn.Linear(hidden_feat_size, 1), nn.Sigmoid() ) self.linear_block_attention_out = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size*3), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size*3,hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size,7*7), nn.Sigmoid() ) self.gradients = [] self.gradients_qfeat = [] self.ques_cam = ques_cam def save_gradients(self, grad): self.gradients = [grad] def save_gradients_qfeat(self, grad): self.gradients_qfeat = [grad] def forward(self, attention, im_feat, q_feat, ans_scores): att_feats = self.atten_input(attention) im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) if self.ques_cam: q_feat.register_hook(self.save_gradients_qfeat) q_feats = self.question_feat_in(q_feat) ans_feat = self.answer_score_in(ans_scores) concat_feats = torch.cat((att_feats, im_feats, q_feats, ans_feat), dim=1) corr_pred = self.corr_pred_layer(concat_feats) refined_attn = self.linear_block_attention_out(concat_feats) return {'wrong_pred':corr_pred, 'im_feature':im_feats_feature, 'refined_attn': refined_attn, 'q_feats':q_feat} class uncertainatt_refinedatt_net_cam_bigger(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048), ans_dim=3129, ques_cam=False): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size//2), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size//2, 1), nn.Sigmoid() ) self.linear_block_attention_out = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size*3), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size*3,hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size,7*7), nn.Sigmoid() ) self.gradients = [] self.gradients_qfeat = [] self.ques_cam = ques_cam def save_gradients(self, grad): self.gradients = [grad] def save_gradients_qfeat(self, grad): self.gradients_qfeat = [grad] def forward(self, attention, im_feat, q_feat, ans_scores): att_feats = self.atten_input(attention) im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) if self.ques_cam: q_feat.register_hook(self.save_gradients_qfeat) q_feats = self.question_feat_in(q_feat) ans_feat = self.answer_score_in(ans_scores) concat_feats = torch.cat((att_feats, im_feats, q_feats, ans_feat), dim=1) corr_pred = self.corr_pred_layer(concat_feats) refined_attn = self.linear_block_attention_out(concat_feats) return {'wrong_pred':corr_pred, 'im_feature':im_feats_feature, 'refined_attn': refined_attn, 'q_feats':q_feat} class uncertainatt_net_cam_bigger(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048), ans_dim=3129, ques_cam=False): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size//2), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size//2, 1), nn.Sigmoid() ) self.gradients = [] self.gradients_qfeat = [] self.ques_cam = ques_cam def save_gradients(self, grad): self.gradients = [grad] def save_gradients_qfeat(self, grad): self.gradients_qfeat = [grad] def forward(self, attention, im_feat, q_feat, ans_scores): att_feats = self.atten_input(attention) im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) if self.ques_cam: q_feat.register_hook(self.save_gradients_qfeat) q_feats = self.question_feat_in(q_feat) ans_feat = self.answer_score_in(ans_scores) concat_feats = torch.cat((att_feats, im_feats, q_feats, ans_feat), dim=1) corr_pred = self.corr_pred_layer(concat_feats) return {'wrong_pred':corr_pred, 'im_feature':im_feats_feature, 'q_feats':q_feat} class uncertainatt_refinedatt_agnosticnet_cam_bigger(nn.Module): def __init__(self, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048), ans_dim=3129, ques_cam=False): super().__init__() self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*3, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size//2), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size//2, 1), nn.Sigmoid() ) self.gradients = [] self.gradients_qfeat = [] self.ques_cam = ques_cam def save_gradients(self, grad): self.gradients = [grad] def save_gradients_qfeat(self, grad): self.gradients_qfeat = [grad] def forward(self, attention, im_feat, q_feat, ans_scores): im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) if self.ques_cam: q_feat.register_hook(self.save_gradients_qfeat) q_feats = self.question_feat_in(q_feat) ans_feat = self.answer_score_in(ans_scores) concat_feats = torch.cat((im_feats, q_feats, ans_feat), dim=1) corr_pred = self.corr_pred_layer(concat_feats) return {'wrong_pred':corr_pred, 'im_feature':im_feats_feature, 'q_feats':q_feat} class uncertainatt_refinedatt_net_cam_bigger_errorcondatt(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048), ans_dim=3129, ques_cam=False): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_linear2 = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size//2), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size//2, 1), nn.Sigmoid() ) self.linear_block_attention_out = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size*3), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size*3,hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size,7*7), nn.Sigmoid() ) self.gradients = [] self.gradients_qfeat = [] self.gradients_bert = [] self.ques_cam = ques_cam def save_gradients(self, grad): self.gradients = [grad] def save_gradients_qfeat(self, grad): self.gradients_qfeat = [grad] def save_gradients_bert(self, grad): self.gradients_bert = [grad] def forward(self, attention, im_feat, q_feat, ans_scores): #if self.ques_cam: # attention.register_hook(self.save_gradients_bert) att_feats = self.atten_input(attention) im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) if self.ques_cam: q_feat.register_hook(self.save_gradients_qfeat) q_feats = self.question_feat_in(q_feat) ans_feat = self.answer_score_in(ans_scores) concat_feats = torch.cat((att_feats, im_feats, q_feats, ans_feat), dim=1) refined_attn = self.linear_block_attention_out(concat_feats) ref_att_format = refined_attn.view(-1, 7,7).unsqueeze(1).repeat(1,1024,1,1) im_feats_feature_weighted = im_feats_feature*ref_att_format im_feats_weighted = im_feats_feature_weighted.view(im_feats_feature_weighted.size(0), -1) im_feats_weighted = self.im_feat_linear2(im_feats_weighted) concat_feats_weighted = torch.cat((att_feats, im_feats_weighted, q_feats, ans_feat), dim=1) corr_pred = self.corr_pred_layer(concat_feats_weighted) return {'wrong_pred':corr_pred, 'im_feature':im_feats_feature, 'refined_attn': refined_attn, 'q_feats':q_feat} class uncertainatt_net_cam_bigger(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048), ans_dim=3129, ques_cam=False): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*4, hidden_feat_size), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size, hidden_feat_size//2), nn.LeakyReLU(0.1), nn.Linear(hidden_feat_size//2, 1), nn.Sigmoid() ) self.gradients = [] self.gradients_qfeat = [] self.ques_cam = ques_cam def save_gradients(self, grad): self.gradients = [grad] def save_gradients_qfeat(self, grad): self.gradients_qfeat = [grad] def forward(self, attention, im_feat, q_feat, ans_scores): att_feats = self.atten_input(attention) im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) if self.ques_cam: q_feat.register_hook(self.save_gradients_qfeat) q_feats = self.question_feat_in(q_feat) ans_feat = self.answer_score_in(ans_scores) concat_feats = torch.cat((att_feats, im_feats, q_feats, ans_feat), dim=1) corr_pred = self.corr_pred_layer(concat_feats) return {'wrong_pred':corr_pred, 'im_feature':im_feats_feature, 'q_feats':q_feat} class uncertain_attention_net_noans_cam(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048)): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU() ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*3, 1), nn.Sigmoid() ) self.gradients = [] def save_gradients(self, grad): self.gradients = [grad] def forward(self, attention, im_feat, q_feat): att_feats = self.atten_input(attention) im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) q_feats = self.question_feat_in(q_feat) concat_feats = torch.cat((att_feats, im_feats, q_feats), dim=1) corr_pred = self.corr_pred_layer(concat_feats) return {'wrong_pred':corr_pred, 'im_feature':[im_feats_feature]} class uncertain_attention_net(nn.Module): def __init__(self, hidden_feat_size=64, q_feat_dim=300, im_feat_dim=36*2048): super().__init__() self.im_feat_in = nn.Sequential( nn.Linear(im_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.attention_layer = nn.Linear(hidden_feat_size*2, 7*7*2048) self.weighted_im_layer = nn.Sequential( nn.Linear(im_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*2, 1), nn.Sigmoid() ) def forward(self, im_feat, q_feat): im_feats = self.im_feat_in(im_feat) q_feats = self.question_feat_in(q_feat) concat_feats = torch.cat((im_feats, q_feats), dim=1) attention = self.attention_layer(concat_feats) attention = attention.view(-1, 7*7,2048) attention = F.softmax(attention, dim=1) attention = attention.view(-1, 7*7*2048) weighted_im = attention*im_feat weighted_im_feats = self.weighted_im_layer(weighted_im) concat_weighted_feats = torch.cat((weighted_im_feats, q_feats), dim=1) corr_pred = self.corr_pred_layer(concat_weighted_feats) return {'wrong_pred':corr_pred, 'wrong_att':attention} class quescaptionmatch_failurepred(nn.Module): def __init__(self, atten_dim = 4*12*115*115, hidden_feat_size=96, q_feat_dim=300, im_feat_dim=(7,7,2048), ans_dim=3129): super().__init__() self.atten_input = nn.Sequential( nn.Linear(atten_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.im_feat_in = nn.Conv2d(im_feat_dim[-1], 1024, 1) self.im_feat_linear = nn.Sequential( nn.Linear(im_feat_dim[0]*im_feat_dim[1]*1024, hidden_feat_size), nn.LeakyReLU() ) self.question_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.quescap_feat_in = nn.Sequential( nn.Linear(q_feat_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.answer_score_in = nn.Sequential( nn.Linear(ans_dim, hidden_feat_size), nn.LeakyReLU(0.1) ) self.corr_pred_layer = nn.Sequential( nn.Linear(hidden_feat_size*5, 1), nn.Sigmoid() ) self.gradients = [] def save_gradients(self, grad): self.gradients = [grad] def forward(self, attention, im_feat, q_feat, q_cap_feat, ans_scores): att_feats = self.atten_input(attention) im_feats_feature = self.im_feat_in(im_feat) im_feats_feature.register_hook(self.save_gradients) im_feats = im_feats_feature.view(im_feats_feature.size(0), -1) im_feats = self.im_feat_linear(im_feats) q_feats = self.question_feat_in(q_feat) q_cap_feats = self.quescap_feat_in(q_cap_feat) ans_feat = self.answer_score_in(ans_scores) concat_feats = torch.cat((att_feats, im_feats, q_feats, q_cap_feats, ans_feat), dim=1) corr_pred = self.corr_pred_layer(concat_feats) return {'wrong_pred':corr_pred, 'im_feature':[im_feats_feature]}

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0.907023

0.902121

0

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0.270232

30,781

947

169

32.503696

0.745537

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null

0

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1

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null

0

7

50780ea051fda0aaf1679955b3b1de3b0788789a

192

py

Python

main.py

abdurrahmanabzd/path_planning_demo_live

75891ccf83dcb219edeb654f55da2618c6b60a2d

[ "MIT" ]

68

2016-12-14T19:53:01.000Z

2022-03-05T08:34:24.000Z

main.py

abdurrahmanabzd/path_planning_demo_live

75891ccf83dcb219edeb654f55da2618c6b60a2d

[ "MIT" ]

null

main.py

abdurrahmanabzd/path_planning_demo_live

75891ccf83dcb219edeb654f55da2618c6b60a2d

[ "MIT" ]

45

2016-12-15T01:51:49.000Z

2022-03-05T08:34:17.000Z

import process_image occupied_grids, planned_path = process_image.main("test_images/test_image3.jpg") print "Occupied Grids : " print occupied_grids print "Planned Path :" print planned_path

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0f9f58eec1f0f08d8029bb8e8925ee2009c0b40e

6,106

py

Python

tests/Unit/Evolution/Systems/RadiationTransport/M1Grey/BoundaryConditions/DirichletAnalytic.py

nilsvu/spectre

1455b9a8d7e92db8ad600c66f54795c29c3052ee

[ "MIT" ]

117

2017-04-08T22:52:48.000Z

2022-03-25T07:23:36.000Z

tests/Unit/Evolution/Systems/RadiationTransport/M1Grey/BoundaryConditions/DirichletAnalytic.py

GitHimanshuc/spectre

4de4033ba36547113293fe4dbdd77591485a4aee

[ "MIT" ]

3,177

2017-04-07T21:10:18.000Z

2022-03-31T23:55:59.000Z

tests/Unit/Evolution/Systems/RadiationTransport/M1Grey/BoundaryConditions/DirichletAnalytic.py

geoffrey4444/spectre

9350d61830b360e2d5b273fdd176dcc841dbefb0

[ "MIT" ]

85

2017-04-07T19:36:13.000Z

2022-03-01T10:21:00.000Z

# Distributed under the MIT License. # See LICENSE.txt for details. import numpy as np import PointwiseFunctions.AnalyticSolutions.RadiationTransport.M1Grey.\ TestFunctions as soln import Evolution.Systems.RadiationTransport.M1Grey.Fluxes as fluxes def soln_error(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): return None _soln_mean_velocity = np.array([0.1, 0.2, 0.3]) _soln_comoving_energy_density = 0.4 # There is no Python implementation of the M1Closure, so for now we hardcode # the pressure tensor with values obtained by running the C++ code run with # the same input parameters. This is hacky, because it couples the C++ and # Python implementations and makes the test less robust. _tilde_p_values_from_cxx = np.array( [[0.13953488372093026, 0.012403100775193798, 0.018604651162790694], [0.012403100775193798, 0.15813953488372096, 0.037209302325581388], [0.018604651162790694, 0.037209302325581388, 0.18914728682170545]]) def soln_tilde_e_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): return soln.constant_m1_tildeE(coords, time, _soln_mean_velocity, _soln_comoving_energy_density) def soln_tilde_e_bar_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): return soln.constant_m1_tildeE(coords, time, _soln_mean_velocity, _soln_comoving_energy_density) def soln_tilde_s_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): return soln.constant_m1_tildeS(coords, time, _soln_mean_velocity, _soln_comoving_energy_density) def soln_tilde_s_bar_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): return soln.constant_m1_tildeS(coords, time, _soln_mean_velocity, _soln_comoving_energy_density) def soln_flux_tilde_e_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): tilde_e = soln_tilde_e_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim) tilde_s = soln_tilde_s_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim) tilde_p = _tilde_p_values_from_cxx lapse = 1.0 shift = np.array([0.0, 0.0, 0.0]) spatial_metric = np.identity(3) inv_spatial_metric = np.identity(3) return fluxes.tilde_e_flux(tilde_e, tilde_s, tilde_p, lapse, shift, spatial_metric, inv_spatial_metric) def soln_flux_tilde_e_bar_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): tilde_e = soln_tilde_e_bar_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim) tilde_s = soln_tilde_s_bar_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim) tilde_p = _tilde_p_values_from_cxx lapse = 1.0 shift = np.array([0.0, 0.0, 0.0]) spatial_metric = np.identity(3) inv_spatial_metric = np.identity(3) return fluxes.tilde_e_flux(tilde_e, tilde_s, tilde_p, lapse, shift, spatial_metric, inv_spatial_metric) def soln_flux_tilde_s_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): tilde_e = soln_tilde_e_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim) tilde_s = soln_tilde_s_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim) tilde_p = _tilde_p_values_from_cxx lapse = 1.0 shift = np.array([0.0, 0.0, 0.0]) spatial_metric = np.identity(3) inv_spatial_metric = np.identity(3) return fluxes.tilde_s_flux(tilde_e, tilde_s, tilde_p, lapse, shift, spatial_metric, inv_spatial_metric) def soln_flux_tilde_s_bar_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim): tilde_e = soln_tilde_e_bar_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim) tilde_s = soln_tilde_s_bar_nue(face_mesh_velocity, outward_directed_normal_covector, outward_directed_normal_vector, coords, time, dim) tilde_p = _tilde_p_values_from_cxx lapse = 1.0 shift = np.array([0.0, 0.0, 0.0]) spatial_metric = np.identity(3) inv_spatial_metric = np.identity(3) return fluxes.tilde_s_flux(tilde_e, tilde_s, tilde_p, lapse, shift, spatial_metric, inv_spatial_metric)

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1

0

1

0

null

0

8

0fec41cfa83dff5ce0e007994c8f2f7333d7bc57

986

py

Python

samsungctl/remote_encrypted/keys.py

p3g4asus/samsungctl

90756acc7ac210e37bbfa23dccf1ca3113e55154

[ "MIT" ]

135

2018-11-23T10:49:42.000Z

2022-03-20T05:42:40.000Z

samsungctl/remote_encrypted/keys.py

p3g4asus/samsungctl

90756acc7ac210e37bbfa23dccf1ca3113e55154

[ "MIT" ]

114

2018-11-25T00:18:31.000Z

2022-02-24T02:33:59.000Z

samsungctl/remote_encrypted/keys.py

p3g4asus/samsungctl

90756acc7ac210e37bbfa23dccf1ca3113e55154

[ "MIT" ]

42

2018-12-01T19:58:13.000Z

2021-11-13T16:35:46.000Z

publicKey = ( '2cb12bb2cbf7cec713c0fff7b59ae68a96784ae517f41d259a45d20556177c0ffe951ca60' 'ec03a990c9412619d1bee30adc7773088c5721664cffcedacf6d251cb4b76e2fd7aef09b3' 'ae9f9496ac8d94ed2b262eee37291c8b237e880cc7c021fb1be0881f3d0bffa4234d3b8e6' 'a61530c00473ce169c025f47fcc001d9b8051' ) privateKey = ( '2fd6334713816fae018cdee4656c5033a8d6b00e8eaea07b3624999242e96247112dcd019' 'c4191f4643c3ce1605002b2e506e7f1d1ef8d9b8044e46d37c0d5263216a87cd783aa1854' '90436c4a0cb2c524e15bc1bfeae703bcbc4b74a0540202e8d79cadaae85c6f9c218bc1107' 'd1f5b4b9bd87160e782f4e436eeb17485ab4d' ) wbKey = 'abbb120c09e7114243d1fa0102163b27' transKey = '6c9474469ddf7578f3e5ad8a4c703d99' prime = ( 'b361eb0ab01c3439f2c16ffda7b05e3e320701ebee3e249123c3586765fd5bf6c1dfa88bb' '6bb5da3fde74737cd88b6a26c5ca31d81d18e3515533d08df619317063224cf0943a2f29a' '5fe60c1c31ddf28334ed76a6478a1122fb24c4a94c8711617ddfe90cf02e643cd82d4748d' '6d4a7ca2f47d88563aa2baf6482e124acd7dd' )

46.952381

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45.736842

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0.566079

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986

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49.3

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0.843813

0

1

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false

0

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null

0

1

0

1

0

1

null

1

0

7

e8d473ea332acc8539ffe71651629e6a0d006f25

12,003

py

Python

dynamo/vectorfield/cell_vectors.py

davisidarta/dynamo-release

0dbd769f52ea07f3cdaa8fb31022ceb89938c382

[ "BSD-3-Clause" ]

null

dynamo/vectorfield/cell_vectors.py

davisidarta/dynamo-release

0dbd769f52ea07f3cdaa8fb31022ceb89938c382

[ "BSD-3-Clause" ]

null

dynamo/vectorfield/cell_vectors.py

davisidarta/dynamo-release

0dbd769f52ea07f3cdaa8fb31022ceb89938c382

[ "BSD-3-Clause" ]

null

from ..tools.cell_velocities import cell_velocities from .topography import VectorField from .vector_calculus import acceleration, curvature def cell_accelerations(adata, vf_basis='pca', basis='umap', enforce=True, preserve_len=True, other_kernels_dict={}, **kwargs): """Compute RNA acceleration field via reconstructed vector field and project it to low dimensional embeddings. In classical physics, including fluidics and aerodynamics, velocity and acceleration vector fields are used as fundamental tools to describe motion or external force of objects, respectively. In analogy, RNA velocity or accelerations estimated from single cells can be regarded as samples in the velocity (La Manno et al. 2018) or acceleration vector field (Gorin, Svensson, and Pachter 2019). In general, a vector field can be defined as a vector-valued function f that maps any points (or cells’ expression state) x in a domain Ω with D dimension (or the gene expression system with D transcripts / proteins) to a vector y (for example, the velocity or acceleration for different genes or proteins), that is f(x) = y. In two or three dimensions, a vector field is often visualised as a quiver plot where a collection of arrows with a given magnitude and direction is drawn. For example, the velocity estimates of unspliced transcriptome of sampled cells projected into two dimensions is drawn to show the prediction of the future cell states in RNA velocity (La Manno et al. 2018). During the differentiation process, external signal factors perturb cells and thus change the vector field. Since we perform genome-wide profiling of cell states and the experiments performed are often done in a short time scale, we assume a constant vector field without loss of generality (See also Discussion). Assuming an asymptotic deterministic system, the trajectory of the cells travelling in the gene expression space follows the vector field and can be calculated using numerical integration methods, for example Runge-Kutta algorithm. In two or three dimensions, a streamline plot can be used to visualize the paths of cells will follow if released in different regions of the gene expression state space under a steady flow field. Another more intuitive way to visualize the structure of vector field is the so called line integral convolution method or LIC (Cabral and Leedom 1993), which works by adding random black-and-white paint sources on the vector field and letting the flowing particle on the vector field picking up some texture to ensure the same streamline having similar intensity. Although we have not provides such functionalities in dynamo, with vector field that changes over time, similar methods, for example, streakline, pathline, timeline, etc. can be used to visualize the evolution of single cell or cell populations. Arguments --------- adata: :class:`~anndata.AnnData` an Annodata object. vf_basis: 'int' (optional, default `pca`) The dictionary key that corresponds to the low dimensional embedding where the vector field function reconstructed. basis: 'int' (optional, default `umap`) The dictionary key that corresponds to the reduced dimension in `.obsm` attribute. enforce: `bool` (default: `False`) Whether to enforce 1) redefining use_for_transition column in obs attribute; 2) recalculation of transition matrix. preserve_len: `bool` (default: `True`) Whether to preserve the length of high dimension vector length. When set to be True, the length of low dimension projected vector will be proportionally scaled to that of the high dimensional vector. Note that when preserve_len is set to be True, the acceleration field may seem to be messy (although the magnitude will be reflected) while the trend of acceleration when `preserve_len` is `True` is more clearer but will lose information of acceleration magnitude. This is because the acceleration is not directly related to the distance of cells in the low embedding space; thus the acceleration direction can be better preserved than the magnitude. On the other hand, velocity is more relevant to the distance in low embedding space, so preserving magnitude and direction of velocity vector in low dimension can be more easily achieved. other_kernels_dict: `dict` (default: `{}`) A dictionary of paramters that will be passed to the cosine/correlation kernel. Returns ------- Adata: :class:`~anndata.AnnData` Returns an updated `~anndata.AnnData` with transition_matrix and projected embedding of high dimension acceleration vectors in the existing embeddings of current cell state, calculated using either the Itô kernel method (default) or the diffusion approximation or the method from (La Manno et al. 2018). """ if 'velocity_' + vf_basis not in adata.obsm.keys(): cell_velocities(adata, basis=vf_basis) if 'VecFld_' + vf_basis not in adata.uns_keys(): VectorField(adata, basis=vf_basis) if 'acceleration_' + vf_basis not in adata.obsm.keys(): acceleration(adata, basis=vf_basis) X = adata.obsm['X_' + vf_basis] V = adata.obsm['acceleration_' + vf_basis] X_embedding = adata.obsm['X_' + basis] if basis != vf_basis and vf_basis.lower() not in ['umap', 'tsne', 'trimap', 'ddtree', 'diffusion_map']: cell_velocities( adata, X=X, V=V, X_embedding=X_embedding, basis=basis, enforce=enforce, key='acceleration', preserve_len=preserve_len, other_kernels_dict=other_kernels_dict, **kwargs ) def cell_curvatures(adata, vf_basis='pca', basis='umap', enforce=True, preserve_len=True, other_kernels_dict={}, **kwargs): """Compute RNA curvature field via reconstructed vector field and project it to low dimensional embeddings. In classical physics, including fluidics and aerodynamics, velocity and acceleration vector fields are used as fundamental tools to describe motion or external force of objects, respectively. In analogy, RNA velocity or accelerations estimated from single cells can be regarded as samples in the velocity (La Manno et al. 2018) or acceleration vector field (Gorin, Svensson, and Pachter 2019). In general, a vector field can be defined as a vector-valued function f that maps any points (or cells’ expression state) x in a domain Ω with D dimension (or the gene expression system with D transcripts / proteins) to a vector y (for example, the velocity or acceleration for different genes or proteins), that is f(x) = y. In two or three dimensions, a vector field is often visualised as a quiver plot where a collection of arrows with a given magnitude and direction is drawn. For example, the velocity estimates of unspliced transcriptome of sampled cells projected into two dimensions is drawn to show the prediction of the future cell states in RNA velocity (La Manno et al. 2018). During the differentiation process, external signal factors perturb cells and thus change the vector field. Since we perform genome-wide profiling of cell states and the experiments performed are often done in a short time scale, we assume a constant vector field without loss of generality (See also Discussion). Assuming an asymptotic deterministic system, the trajectory of the cells travelling in the gene expression space follows the vector field and can be calculated using numerical integration methods, for example Runge-Kutta algorithm. In two or three dimensions, a streamline plot can be used to visualize the paths of cells will follow if released in different regions of the gene expression state space under a steady flow field. Another more intuitive way to visualize the structure of vector field is the so called line integral convolution method or LIC (Cabral and Leedom 1993), which works by adding random black-and-white paint sources on the vector field and letting the flowing particle on the vector field picking up some texture to ensure the same streamline having similar intensity. Although we have not provides such functionalities in dynamo, with vector field that changes over time, similar methods, for example, streakline, pathline, timeline, etc. can be used to visualize the evolution of single cell or cell populations. Arguments --------- adata: :class:`~anndata.AnnData` an Annodata object. vf_basis: 'int' (optional, default `pca`) The dictionary key that corresponds to the low dimensional embedding where the vector field function reconstructed. basis: 'int' (optional, default `umap`) The dictionary key that corresponds to the reduced dimension in `.obsm` attribute. enforce: `bool` (default: `False`) Whether to enforce 1) redefining use_for_transition column in obs attribute; 2) recalculation of transition matrix. preserve_len: `bool` (default: `True`) Whether to preserve the length of high dimension vector length. When set to be True, the length of low dimension projected vector will be proportionally scaled to that of the high dimensional vector. Note that when preserve_len is set to be True, the acceleration field may seem to be messy (although the magnitude will be reflected) while the trend of acceleration when `preserve_len` is `True` is more clearer but will lose information of acceleration magnitude. This is because the acceleration is not directly related to the distance of cells in the low embedding space; thus the acceleration direction can be better preserved than the magnitude. On the other hand, velocity is more relevant to the distance in low embedding space, so preserving magnitude and direction of velocity vector in low dimension can be more easily achieved. other_kernels_dict: `dict` (default: `{}`) A dictionary of paramters that will be passed to the cosine/correlation kernel. Returns ------- Adata: :class:`~anndata.AnnData` Returns an updated `~anndata.AnnData` with transition_matrix and projected embedding of high dimension curvature vectors in the existing embeddings of current cell state, calculated using either the Itô kernel method (default) or the diffusion approximation or the method from (La Manno et al. 2018). """ if 'velocity_' + vf_basis not in adata.obsm.keys(): cell_velocities(adata, basis=vf_basis) if 'VecFld_' + vf_basis not in adata.uns_keys(): VectorField(adata, basis=vf_basis) if 'curvature_' + vf_basis not in adata.obsm.keys(): curvature(adata, basis=vf_basis) X = adata.obsm['X_' + vf_basis] V = adata.obsm['curvature_' + vf_basis] X_embedding = adata.obsm['X_' + basis] if basis != vf_basis and vf_basis.lower() not in ['umap', 'tsne', 'trimap', 'ddtree', 'diffusion_map']: cell_velocities( adata, X=X, V=V, X_embedding=X_embedding, basis=basis, enforce=enforce, key='curvature', preserve_len=preserve_len, other_kernels_dict=other_kernels_dict, **kwargs )

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1

0

null

0

7

2ce00720e4e77c15f7cbc5a1e8cea2b1bc2c1434

717

py

Python

tests/test_render.py

lejmr/ecsctl

688c5d5e10536ee74ded9de187309134a4b7effc

[ "MIT" ]

null

tests/test_render.py

lejmr/ecsctl

688c5d5e10536ee74ded9de187309134a4b7effc

[ "MIT" ]

1

2021-02-14T19:53:08.000Z

tests/test_render.py

lejmr/ecsctl

688c5d5e10536ee74ded9de187309134a4b7effc

[ "MIT" ]

null

from ecs.render import render def test_simple_render(): # task definition td = { "version": "latest", "task_name": "name_{{ var1 }}" } # Variable definition vars = { "var1": "value1" } # The render r = render(td, vars) # Asserts assert r == {"version": "latest", "task_name": "name_value1"} def test_nested_case1(): # task definition td = { "version": "latest", "task_name": "name_{{ var1 }}" } # Variable definition vars = { "var1": "{{ var2 }}", "var2": "value1" } # The render r = render(td, vars) # Asserts assert r == {"version": "latest", "task_name": "name_value1"}

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717

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0.189944

0.234637

0.804469

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0.32357

717

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0.715464

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0.136364

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0

1

0

null

0

8

2cf64cde0b37fc71b141d614c266e011a676c9f0

174

py

Python

workflow_miniscope/paths.py

davidgodinez/workflow-miniscope

8b464aec1293d234bb1dada33b2409a1840d4ef4

[ "MIT" ]

null

workflow_miniscope/paths.py

davidgodinez/workflow-miniscope

8b464aec1293d234bb1dada33b2409a1840d4ef4

[ "MIT" ]

1

2022-03-23T20:05:14.000Z

workflow_miniscope/paths.py

davidgodinez/workflow-miniscope

8b464aec1293d234bb1dada33b2409a1840d4ef4

[ "MIT" ]

null

import datajoint as dj def get_miniscope_root_data_dir(): root_data_dirs = dj.config.get('custom', {}).get('miniscope_root_data_dir', None) return root_data_dirs

19.333333

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0.747126

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174

4.407407

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0.268908

0.336134

0.386555

0

0.143678

174

8

86

21.75

0.798658

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1

0

null

0

1

0

1

0

7

d74a82e74637b14b3e67e5e0e9e1a72dc3748f00

280

py

Python

badkeys/__init__.py

hoheinzollern/badkeys

62417cbf4304a20a5af40b5b102438406068f998

[ "MIT" ]

null

badkeys/__init__.py

hoheinzollern/badkeys

62417cbf4304a20a5af40b5b102438406068f998

[ "MIT" ]

null

badkeys/__init__.py

hoheinzollern/badkeys

62417cbf4304a20a5af40b5b102438406068f998

[ "MIT" ]

null

__all__ = ["allchecks", "checkrsa", "checkpubkey", "checkprivkey", "checkcrt", "checkcsr", "checksshpubkey", "detectandcheck"] from .checks import (allchecks, checkrsa, checkpubkey, checkprivkey, checkcrt, checkcsr, checksshpubkey, detectandcheck)

56

78

0.682143

20

280

9.35

0.6

0.181818

0.299465

0.427807

0.898396

0

0.189286

280

4

79

70

0.823789

0

0.3

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false

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0.25

0

0.25

0

1

0

null

0

1

0

1

0

null

0

8

d75048ea9c48f22312bd338742d0500d12220036

186

py

Python

conftest.py

vis7/django_pytest_fixture_tutorial

e4662aaca6ffebdc6d467e06115c249dc5106665

[ "MIT" ]

null

conftest.py

vis7/django_pytest_fixture_tutorial

e4662aaca6ffebdc6d467e06115c249dc5106665

[ "MIT" ]

null

conftest.py

vis7/django_pytest_fixture_tutorial

e4662aaca6ffebdc6d467e06115c249dc5106665

[ "MIT" ]

null

import pytest from school.models import Student @pytest.fixture def student(): return { "vis": Student.objects.get(pk=1), "dhruvin": Student.objects.get(pk=2) }

18.6

44

0.645161

24

186

5

0.666667

0.233333

0.283333

0.316667

0

0.013793

0.22043

186

9

45

20.666667

0.813793

0

0.053763

0

1

0.125

true

0

0.25

0.125

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

ad515e129f08e0ba4fb5044846855696728ec596

80

py

Python

packages/mccomponents/python/mccomponents/detector/elements/units.py

mcvine/mcvine

42232534b0c6af729628009bed165cd7d833789d

[ "BSD-3-Clause" ]

5

2017-01-16T03:59:47.000Z

2020-06-23T02:54:19.000Z

packages/mccomponents/python/mccomponents/detector/units.py

mcvine/mcvine

42232534b0c6af729628009bed165cd7d833789d

[ "BSD-3-Clause" ]

293

2015-10-29T17:45:52.000Z

2022-01-07T16:31:09.000Z

packages/mccomponents/python/mccomponents/detector/units.py

mcvine/mcvine

42232534b0c6af729628009bed165cd7d833789d

[ "BSD-3-Clause" ]

1

2019-05-25T00:53:31.000Z

from pyre.units import length, time, pressure, energy from pyre.units import *

20

53

0.775

12

80

5.166667

0.666667

0.258065

0.419355

0.612903

0

0.15

80

3

54

26.666667

0.911765

0

1

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true

0

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null

0

1

0

1

0

1

0

8

ad552933648aaf42eaae64b7276f804a0832a408

903

py

Python

src/nets/inception.py

xiaocn/ImageClassifer

3075150aa7ef547333729dcff5876147682c6694

[ "Apache-2.0" ]

2

2018-11-09T10:01:23.000Z

2018-12-18T04:30:57.000Z

src/nets/inception.py

xiaocn/ImageClassifer

3075150aa7ef547333729dcff5876147682c6694

[ "Apache-2.0" ]

null

src/nets/inception.py

xiaocn/ImageClassifer

3075150aa7ef547333729dcff5876147682c6694

[ "Apache-2.0" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function # pylint: disable=unused-import from nets.inception_resnet_v2 import inception_resnet_v2 from nets.inception_resnet_v2 import inception_resnet_v2_arg_scope from nets.inception_resnet_v2 import inception_resnet_v2_base from nets.inception_v1 import inception_v1 from nets.inception_v1 import inception_v1_arg_scope from nets.inception_v1 import inception_v1_base from nets.inception_v2 import inception_v2 from nets.inception_v2 import inception_v2_arg_scope from nets.inception_v2 import inception_v2_base from nets.inception_v3 import inception_v3 from nets.inception_v3 import inception_v3_arg_scope from nets.inception_v3 import inception_v3_base from nets.inception_v4 import inception_v4 from nets.inception_v4 import inception_v4_arg_scope from nets.inception_v4 import inception_v4_base

45.15

66

0.895903

144

903

5.166667

0.138889

0.16129

0.342742

0.107527

0.83871

0.795699

0.774194

0.193548

0

0.036232

0.083056

903

20

67

45.15

0.862319

0.032115

0

1

0

true

0

1

0

1

0.055556

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

7

ad739290227bd708d70ed07eb1a73a08038e0df3

3,925

py

Python

demography/management/commands/bake/aggregate/_state.py

The-Politico/politico-civic-demography

080bb964b64b06db7fd04386530e893ceed1cf98

[ "MIT" ]

null

demography/management/commands/bake/aggregate/_state.py

The-Politico/politico-civic-demography

080bb964b64b06db7fd04386530e893ceed1cf98

[ "MIT" ]

null

demography/management/commands/bake/aggregate/_state.py

The-Politico/politico-civic-demography

080bb964b64b06db7fd04386530e893ceed1cf98

[ "MIT" ]

null

from tqdm import tqdm from geography.models import Division class AggregateState(object): def aggregate_state_estimates_by_county(self, parent): """ Aggregates county-level estimates for each table within a given state. Creates data structure designed for an export in this format: ...{series}/{year}/{table}/{state_fips}/counties.json """ data = {} for division in tqdm( Division.objects.filter(level=self.COUNTY_LEVEL, parent=parent) ): fips = division.code id = division.id aggregated_labels = [] # Keep track of already agg'ed variables for estimate in division.census_estimates.all(): series = estimate.variable.table.series year = estimate.variable.table.year table = estimate.variable.table.code label = None if estimate.variable.label: label = estimate.variable.label.label table_label = "{}{}".format(table, label) code = estimate.variable.code if series not in data: data[series] = {} if year not in data[series]: data[series][year] = {} if table not in data[series][year]: data[series][year][table] = {} if fips not in data[series][year][table]: data[series][year][table][fips] = {} if label is not None: if table_label not in aggregated_labels: aggregated_labels.append(table_label) data[series][year][table][fips][ label ] = self.aggregate_variable(estimate, id) else: data[series][year][table][division.code][ code ] = estimate.estimate return data def aggregate_state_estimates_by_district(self, state): """ Aggregates district-level estimates for each table within a given state. Creates data structure designed for an export in this format: ...{series}/{year}/{table}/{state_fips}/districts.json """ data = {} for division in tqdm( Division.objects.filter(level=self.DISTRICT_LEVEL, parent=state) ): fips = division.code id = division.id aggregated_labels = [] # Keep track of already agg'ed variables for estimate in division.census_estimates.all(): series = estimate.variable.table.series year = estimate.variable.table.year table = estimate.variable.table.code label = None if estimate.variable.label: label = estimate.variable.label.label table_label = "{}{}".format(table, label) code = estimate.variable.code if series not in data: data[series] = {} if year not in data[series]: data[series][year] = {} if table not in data[series][year]: data[series][year][table] = {} if fips not in data[series][year][table]: data[series][year][table][fips] = {} if label is not None: if table_label not in aggregated_labels: aggregated_labels.append(table_label) data[series][year][table][fips][ label ] = self.aggregate_variable(estimate, id) else: data[series][year][table][division.code][ code ] = estimate.estimate return data

40.463918

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0.09904

0.096008

0.895402

0.867105

0

0.39949

3,925

96

79

40.885417

0.839627

0.116433

0

0.906667

0

0.002367

0

1

0.026667

false

0

0.026667

0

0.093333

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null

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1

0

1

0

null

0

7

ad8968f9ae5c9c7463e3fe40e8336f13b82d87eb

104,352

py

Python

tests/test_scenarios_synthetic.py

KellyGriffin/kalc

9b78c4177ed9ffccbf1ecfbf9a7946286cd7c583

[ "Apache-2.0" ]

null

tests/test_scenarios_synthetic.py

KellyGriffin/kalc

9b78c4177ed9ffccbf1ecfbf9a7946286cd7c583

[ "Apache-2.0" ]

null

tests/test_scenarios_synthetic.py

KellyGriffin/kalc

9b78c4177ed9ffccbf1ecfbf9a7946286cd7c583

[ "Apache-2.0" ]

null

try: from tests.test_util import print_objects except: from test_util import print_objects try: from tests.libs_for_tests import prepare_yamllist_for_diff except: from libs_for_tests import prepare_yamllist_for_diff from kalc.model.search import Check_services, Check_deployments, Check_daemonsets, OptimisticRun, CheckNodeOutage, Check_node_outage_and_service_restart from kalc.model.system.Scheduler import Scheduler from kalc.model.system.globals import GlobalVar from kalc.model.kinds.Service import Service from kalc.model.kinds.Node import Node from kalc.model.kinds.Pod import Pod from kalc.model.kinds.Deployment import Deployment from kalc.model.kinds.DaemonSet import DaemonSet from kalc.model.kinds.PriorityClass import PriorityClass from kalc.model.kubernetes import KubernetesCluster from kalc.misc.const import * import pytest from kalc.model.search import K8ServiceInterruptSearch from kalc.misc.object_factory import labelFactory from click.testing import CliRunner from kalc.model.scenario import Scenario from poodle import planned try: from tests.libs_for_tests import convert_space_to_yaml,print_objects_from_yaml,print_plan,load_yaml, print_objects_compare, checks_assert_conditions, reload_cluster_from_yaml, checks_assert_conditions_in_one_mode except: from libs_for_tests import convert_space_to_yaml,print_objects_from_yaml,print_plan,load_yaml, print_objects_compare, checks_assert_conditions, reload_cluster_from_yaml, checks_assert_conditions_in_one_mode DEBUG_MODE = 0 # 0 - no debug, 1- debug with yaml load , 2 - debug without yaml load def build_running_pod(podName, cpuRequest, memRequest, atNode): pod_running_1 = Pod() pod_running_1.metadata_name = "pod"+str(podName) pod_running_1.cpuRequest = cpuRequest pod_running_1.memRequest = memRequest pod_running_1.atNode = atNode pod_running_1.status = STATUS_POD["Running"] pod_running_1.hasDeployment = False pod_running_1.hasService = False pod_running_1.hasDaemonset = False return pod_running_1 def build_running_pod_with_d(podName, cpuRequest, memRequest, atNode, d, ds): pod_running_1 = Pod() pod_running_1.metadata_name = "pod"+str(podName) pod_running_1.cpuRequest = cpuRequest pod_running_1.memRequest = memRequest pod_running_1.atNode = atNode pod_running_1.status = STATUS_POD["Running"] pod_running_1.hasDeployment = False pod_running_1.hasService = False pod_running_1.hasDaemonset = False if d is not None: d.podList.add(pod_running_1) d.amountOfActivePods += 1 pod_running_1.hasDeployment = True if ds is not None: ds.podList.add(pod_running_1) ds.amountOfActivePods += 1 pod_running_1.hasDaemonset = True atNode.currentFormalCpuConsumption += cpuRequest atNode.currentFormalMemConsumption += memRequest return pod_running_1 def build_pending_pod(podName, cpuRequest, memRequest, toNode): p = build_running_pod(podName, cpuRequest, memRequest, Node.NODE_NULL) p.status = STATUS_POD["Pending"] p.toNode = toNode p.hasDeployment = False p.hasService = False p.hasDaemonset = False return p def build_pending_pod_with_d(podName, cpuRequest, memRequest, toNode, d, ds): p = Pod() p.metadata_name = "pod"+str(podName) p.cpuRequest = cpuRequest p.memRequest = memRequest p.status = STATUS_POD["Pending"] p.hasDeployment = False p.hasService = False p.hasDaemonset = False if d is not None: d.podList.add(p) p.hasDeployment = True if ds is not None: ds.podList.add(p) p.hasDaemonset = True p.toNode = toNode return p def prepare_test_0_run_pods_no_eviction(): # print("0") # TODO: extract final status for loader unit tests from here # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.currentFormalCpuConsumption = 0 n.currentFormalMemConsumption = 0 # priority - as needed pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Pedning pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] # Create a "holding" controller - optional ds = DaemonSet() ds.podList.add(pod_pending_1) ds.amountOfActivePods = 0 pod_pending_1.hasDaemonset = True k.state_objects.extend([n, pc, ds]) create_objects = [pod_pending_1] k2 = reload_cluster_from_yaml(k,create_objects) k.state_objects.extend(create_objects) k._build_state() return k, k2 @pytest.mark.debug(reason="this test is for debug perspective") def test_0_run_pods_no_eviction(): k, k2 = prepare_test_0_run_pods_no_eviction() pod_pending_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class Task_Check_services(Check_services): goal = lambda self: pod_pending_1.status == STATUS_POD["Running"] class Task_Check_deployments(Check_deployments): goal = lambda self: pod_pending_1.status == STATUS_POD["Running"] p = Task_Check_services(k.state_objects) p.run(timeout=200) assert "StartPod" in "\n".join([repr(x) for x in p.plan]) p = Task_Check_deployments(k.state_objects) p.run(timeout=200) assert "StartPod" in "\n".join([repr(x) for x in p.plan]) def test_0_run_pods_no_eviction_invload(): k, k2 = prepare_test_0_run_pods_no_eviction() pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) class NewGoal_k1(Check_services): goal = lambda self: pod_pending_1_1.status == STATUS_POD["Running"] p = NewGoal_k1(k.state_objects) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) class NewGoal_k2(Check_services): goal = lambda self: pod_pending_1_2.status == STATUS_POD["Running"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["StartPod"] not_assert_conditions = ["Evict"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def construct_scpace_for_test_1_run_pods_with_eviction(): # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, pod_pending_1]) k._build_state() create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) return k, k2 def test_1_run_pods_with_eviction_invload(): k, k2 = construct_scpace_for_test_1_run_pods_with_eviction() pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) class NewGoal_k1(Check_services): goal = lambda self: pod_pending_1_1.status == STATUS_POD["Running"] p = NewGoal_k1(k.state_objects) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) class NewGoal_k2(Check_services): goal = lambda self: pod_pending_1_2.status == STATUS_POD["Running"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["StartPod","Evict"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def construct_scpace_for_test_2_synthetic_service_outage(): # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False n.searchable = False # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) n.amountOfActivePods = 2 ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 1 s.status = STATUS_SERV["Started"] # our service has only one pod so it can detect outage # (we can't evict all pods here with one) s.podList.add(pod_running_1) pod_running_1.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, pod_pending_1,s]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() return k, k2 @pytest.mark.debug(reason="if debug needed - uncomment me") def test_2_synthetic_service_outage_step1(): # print("2-1") k, k2 =construct_scpace_for_test_2_synthetic_service_outage() pod_running_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) pod_pending_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class NewGoal(OptimisticRun): # pass # goal = lambda self: pod_pending_1.status == STATUS_POD["Running"] goal = lambda self: pod_running_1.status == STATUS_POD["Killing"] p = NewGoal(k.state_objects) p.run(timeout=200) # for a in p.plan: # print(a) # print_objects(k.state_objects) assert "Evict" in "\n".join([repr(x) for x in p.plan]) assert not "NodeOutageFinished" in "\n".join([repr(x) for x in p.plan]) @pytest.mark.debug(reason="if debug needed - uncomment me") def test_2_synthetic_service_outage_step2(): # print("2-2") k, k2 =construct_scpace_for_test_2_synthetic_service_outage() pod_running_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) pod_pending_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) # print_objects(k.state_objects) class NewGoal(OptimisticRun): # pass # goal = lambda self: pod_pending_1.status == STATUS_POD["Running"] goal = lambda self: pod_running_1.status == STATUS_POD["Pending"] p = NewGoal(k.state_objects) p.run(timeout=200) # for a in p.plan: # print(a) # print_objects(k.state_objects) assert "Evict" in "\n".join([repr(x) for x in p.plan]) assert "KillPod" in "\n".join([repr(x) for x in p.plan]) assert not "NodeOutageFinished" in "\n".join([repr(x) for x in p.plan]) @pytest.mark.debug(reason="if debug needed - uncomment me") def test_2_synthetic_service_outage_step3(): # print("2-3") k, k2 =construct_scpace_for_test_2_synthetic_service_outage() pod_running_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) pod_pending_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) # print_objects(k.state_objects) class NewGoal(OptimisticRun): # pass goal = lambda self: pod_pending_1.status == STATUS_POD["Running"] and\ pod_running_1.status == STATUS_POD["Pending"] p = NewGoal(k.state_objects) p.run(timeout=200) # for a in p.plan: # print(a) # print_objects(k.state_objects) assert "StartPod" in "\n".join([repr(x) for x in p.plan]) assert "Evict" in "\n".join([repr(x) for x in p.plan]) assert not "NodeOutageFinished" in "\n".join([repr(x) for x in p.plan]) @pytest.mark.debug(reason="if debug needed - uncomment me") def test_2_synthetic_service_outage_step4(): # print("2-4") k, k2 =construct_scpace_for_test_2_synthetic_service_outage() pod_running_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) pod_pending_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # print_objects(k.state_objects) class NewGoal(OptimisticRun): goal = lambda self: pod_pending_1.status == STATUS_POD["Running"] and\ pod_running_1.status == STATUS_POD["Pending"] and\ scheduler.queueLength == 1 p = NewGoal(k.state_objects) p.run(timeout=400) # for a in p.plan: # print(a) # print_objects(k.state_objects) assert "StartPod" in "\n".join([repr(x) for x in p.plan]) assert "Evict" in "\n".join([repr(x) for x in p.plan]) assert not "NodeOutageFinished" in "\n".join([repr(x) for x in p.plan]) @pytest.mark.debug(reason="if debug needed - uncomment me") def test_2_synthetic_service_outage_step5(): # print("2-5") k, k2 =construct_scpace_for_test_2_synthetic_service_outage() pod_running_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) pod_pending_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # print_objects(k.state_objects) class NewGoal(OptimisticRun): goal = lambda self: pod_pending_1.status == STATUS_POD["Running"] and\ pod_running_1.status == STATUS_POD["Pending"] and\ scheduler.status == STATUS_SCHED["Clean"] p = NewGoal(k.state_objects) p.run(timeout=400) # for a in p.plan: # print(a) # print_objects(k.state_objects) assert "StartPod" in "\n".join([repr(x) for x in p.plan]) assert "Evict" in "\n".join([repr(x) for x in p.plan]) assert not "NodeOutageFinished" in "\n".join([repr(x) for x in p.plan]) # assert "MarkServiceOutageEvent" in "\n".join([repr(x) for x in p.plan]) #TODO PASS wioth Scheduler_cant_place_pod cost=30000 @pytest.mark.debug(reason="if debug needed - uncomment me") def test_2_synthetic_service_outage_step6_noNodeSelected(): # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False n.searchable = False # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) n.amountOfActivePods = 2 ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 1 s.status = STATUS_SERV["Started"] # our service has only one pod so it can detect outage # (we can't evict all pods here with one) s.podList.add(pod_running_1) pod_running_1.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,Node.NODE_NULL) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, pod_pending_1,s]) "this test was needed when debugging invloads" # print("2-6") globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # print_objects(k.state_objects) class test_2_synthetic_service_outage_step6_noNodeSelected_Task_Check_services(Check_services): goal = lambda self: globalVar.is_service_disrupted == True p = test_2_synthetic_service_outage_step6_noNodeSelected_Task_Check_services(k.state_objects) p.run(timeout=200) # print_plan(p) assert "SelectNode" in "\n".join([repr(x) for x in p.plan]) # StartPod not necessarily happens assert "StartPod" in "\n".join([repr(x) for x in p.plan]) # StartPod not necessarily happens assert "Evict" in "\n".join([repr(x) for x in p.plan]) assert "MarkServiceOutageEvent" in "\n".join([repr(x) for x in p.plan]) assert not "NodeOutageFinished" in "\n".join([repr(x) for x in p.plan]) @pytest.mark.debug(reason="if debug needed - uncomment me") def test_2_synthetic_service_outage_step6(): # print("2-6") k, k2 =construct_scpace_for_test_2_synthetic_service_outage() pod_running_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) pod_pending_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # print_objects(k.state_objects) class Task_Check_services(Check_services): goal = lambda self: globalVar.is_service_disrupted == True class Task_Check_daemonsets(Check_daemonsets): goal = lambda self: globalVar.is_daemonset_disrupted == True p = Task_Check_services(k.state_objects) p.run(timeout=200) # print_plan(p) # assert "StartPod" in "\n".join([repr(x) for x in p.plan]) # StartPod not necessarily happens assert "Evict" in "\n".join([repr(x) for x in p.plan]) assert "MarkServiceOutageEvent" in "\n".join([repr(x) for x in p.plan]) assert not "NodeOutageFinished" in "\n".join([repr(x) for x in p.plan]) def test_2_synthetic_service_outage_invload(): # print("2-6") k, k2 =construct_scpace_for_test_2_synthetic_service_outage() pod_running_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) pod_running_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k2.state_objects)) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) node_1 = next(filter(lambda x: isinstance(x, Node), k.state_objects)) node_1.searchable = False node_2 = next(filter(lambda x: isinstance(x, Node), k2.state_objects)) node_2.searchable = False globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) class NewGoal_k1(Check_services): goal = lambda self: globalVar_k1.is_service_disrupted == True p = NewGoal_k1(k.state_objects) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) class NewGoal_k2(Check_services): goal = lambda self: globalVar_k2.is_service_disrupted == True p2 = NewGoal_k2(k2.state_objects) assert_conditions = [ # "StartPod", "Evict","MarkServiceOutageEvent"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def construct_multi_pods_eviction_problem(): # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 n.amountOfActivePods = 2 n.searchable = False # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] # our service has only one pod so it can detect outage # (we can't evict all pods here with one) # TODO: no outage detected if res is not 4 s.podList.add(pod_running_1) s.podList.add(pod_running_2) pod_running_1.hasService = True pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,4,4,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, pod_pending_1,s]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) # print_objects(k.state_objects) k._build_state() return k, k2, pod_pending_1 def test_3_synthetic_service_outage_multi_invload(): # print("3") "Multiple pods are evicted from one service to cause outage" k, k2, pod_pending_1 = construct_multi_pods_eviction_problem() globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) node_k1 = next(filter(lambda x: isinstance(x, Node), k.state_objects)) node_k2 = next(filter(lambda x: isinstance(x, Node), k2.state_objects)) node_k1.searchable = False node_k2.searchable = False globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) class NewGoal_k1(Check_services): goal = lambda self: globalVar_k1.is_service_disrupted == True p = NewGoal_k1(k.state_objects) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) class NewGoal_k2(Check_services): goal = lambda self: globalVar_k2.is_service_disrupted == True p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["MarkServiceOutageEvent"] not_assert_conditions = [] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def prepare_test_4_synthetic_service_NO_outage_multi(): # print("4") "No outage is caused by evicting only one pod of a multi-pod service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] # our service has only one pod so it can detect outage # (we can't evict all pods here with one) # TODO: no outage detected if res is not 4 s.podList.add(pod_running_1) s.podList.add(pod_running_2) pod_running_1.hasService = True pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, pod_pending_1,s]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() return k,k2 def test_4_synthetic_service_NO_outage_multi(): k, k2 = prepare_test_4_synthetic_service_NO_outage_multi() globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) class NewGoal_k1(Check_services): goal = lambda self: globalVar_k1.goal_achieved == True p = NewGoal_k1(k.state_objects) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) class NewGoal_k2(Check_services): goal = lambda self: globalVar_k2.goal_achieved == True p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["SchedulerQueueClean"] not_assert_conditions = [] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) @pytest.mark.debug() def test_synthetic_service_NO_outage_deployment_IS_outage_step_1(): "Deployment (partial) outage must be registered in case where Deployment exists" # Initialize scheduler, globalvar # kalc.misc.util.CPU_DIVISOR=40 # kalc.misc.util.MEM_DIVISOR=125 k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] # our service has only one pod so it can detect outage # (we can't evict all pods here with one) # TODO: no outage detected if res is not 4 pod_running_1.targetService = s pod_running_2.targetService = s pod_running_1.hasService = True pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] d = Deployment() d.spec_replicas = 2 d.amountOfActivePods = 2 pod_running_1.hasDeployment = True pod_running_2.hasDeployment = True d.podList.add(pod_running_1) d.podList.add(pod_running_2) k.state_objects.extend([n, pc, pod_running_1, pod_running_2, pod_pending_1,s,d]) # kalc.misc.util.CPU_DIVISOR=40 # kalc.misc.util.MEM_DIVISOR=125 yamlState = convert_space_to_yaml(k.state_objects, wrap_items=True) k2 = KubernetesCluster() load_yaml(yamlState,k2) k._build_state() globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) class test_synthetic_service_NO_outage_deployment_IS_outage_k1(Check_deployments): goal = lambda self: pod_running_1.status == STATUS_POD["Pending"] p = test_synthetic_service_NO_outage_deployment_IS_outage_k1(k.state_objects) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) pods = filter(lambda x: isinstance(x, Pod), k2.state_objects) pod_k2 = next(filter(lambda x: x.metadata_name._get_value() == "pod1", pods)) class test_synthetic_service_NO_outage_deployment_IS_outage_k2(Check_deployments): goal = lambda self: pod_k2.status == STATUS_POD["Pending"] p2 = test_synthetic_service_NO_outage_deployment_IS_outage_k2(k2.state_objects) assert_conditions = ["Evict_and_replace_less_prioritized_pod_when_target_node_is_defined"] not_assert_conditions = [] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_synthetic_service_NO_outage_deployment_IS_outage(): "Deployment (partial) outage must be registered in case where Deployment exists" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] # our service has only one pod so it can detect outage # (we can't evict all pods here with one) # TODO: no outage detected if res is not 4 s.podList.add(pod_running_1) s.podList.add(pod_running_2) pod_running_1.hasService = True pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] d = Deployment() d.spec_replicas = 2 d.amountOfActivePods = 2 pod_running_1.hasDeployment = True pod_running_2.hasDeployment = True d.podList.add(pod_running_1) d.podList.add(pod_running_2) k.state_objects.extend([n, pc, pod_running_1, pod_running_2, pod_pending_1,s,d]) yamlState = convert_space_to_yaml(k.state_objects, wrap_items=True) k2 = KubernetesCluster() load_yaml(yamlState,k2) k._build_state() globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) class NewGoal_k1(Check_deployments): goal = lambda self: globalVar_k1.is_deployment_disrupted == True p = NewGoal_k1(k.state_objects) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) class NewGoal_k2(Check_deployments): goal = lambda self: globalVar_k2.is_deployment_disrupted == True p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["MarkDeploymentOutageEvent"] not_assert_conditions = [] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_5_evict_and_killpod_deployment_without_service(): # print("5") "Test that killPod works for deployment" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False # create Deploymnent that we're going to detect failure of... d = Deployment() d.spec_replicas = 2 # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,d,None) pod_running_2 = build_running_pod_with_d(2,2,2,n,d,None) n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, s, pod_pending_1, d]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_running_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_running_1_1.status == STATUS_POD["Pending"] p = NewGoal_k1(k.state_objects) pod_running_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_running_1_2.status == STATUS_POD["Pending"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["Evict_and_replace_less_prioritized_pod_when_target_node_is_defined",\ "KillPod_IF_Deployment_isNotNUll_Service_isNull_Daemonset_isNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_6_evict_and_killpod_without_deployment_without_service(): # print("6") "Test that killPod works without either deployment or service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 # create Deploymnent that we're going to detect failure of... # d = Deployment() # d.spec_replicas = 2 # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,None,None) pod_running_2 = build_running_pod_with_d(2,2,2,n,None,None) # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, s, pod_pending_1]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_running_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_running_1_1.status == STATUS_POD["Pending"] p = NewGoal_k1(k.state_objects) pod_running_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_running_1_2.status == STATUS_POD["Pending"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["Evict_and_replace_less_prioritized_pod_when_target_node_is_defined",\ "KillPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) # @pytest.mark.skip(reason="FIXME") def test_7_evict_and_killpod_with_deployment_and_service(): # print("7") "Test that killPod works for deployment with service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 # create Deploymnent that we're going to detect failure of... d = Deployment() d.spec_replicas = 2 # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,d,None) pod_running_2 = build_running_pod_with_d(2,2,2,n,d,None) n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] # our service has multiple pods but we are detecting pods pending issue # remove service as we are detecting service outage by a bug above s.podList.add(pod_running_1) pod_running_1.hasService = True s.podList.add(pod_running_2) pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, s, pod_pending_1, d]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_running_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_running_1_1.status == STATUS_POD["Pending"] p = NewGoal_k1(k.state_objects) pod_running_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_running_1_2.status == STATUS_POD["Pending"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["Evict_and_replace_less_prioritized_pod_when_target_node_is_defined",\ "KillPod_IF_Deployment_isNotNUll_Service_isNotNull_Daemonset_isNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_8_evict_and_killpod_with_daemonset_without_service(): # print("8") "Test that killPod works with daemonset" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 # create Deploymnent that we're going to detect failure of... ds = DaemonSet() # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,None,ds) pod_running_2 = build_running_pod_with_d(2,2,2,n,None,ds) n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" # s.amountOfActivePods = 2 # s.status = STATUS_SERV["Started"] # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, s, pod_pending_1,ds]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_running_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_running_1_1.status == STATUS_POD["Pending"] p = NewGoal_k1(k.state_objects) pod_running_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_running_1_2.status == STATUS_POD["Pending"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["Evict_and_replace_less_prioritized_pod_when_target_node_is_defined",\ "KillPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_9_evict_and_killpod_with_daemonset_with_service(): # print("9") "Test that killPod works with daemonset and service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 # create Deploymnent that we're going to detect failure of... ds = DaemonSet() # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,None,ds) pod_running_2 = build_running_pod_with_d(2,2,2,n,None,ds) n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] # our service has multiple pods but we are detecting pods pending issue # remove service as we are detecting service outage by a bug above s.podList.add(pod_running_1) pod_running_1.hasService = True s.podList.add(pod_running_2) pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, s, pod_pending_1,ds]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_running_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_running_1_1.status == STATUS_POD["Pending"] p = NewGoal_k1(k.state_objects) pod_running_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_running_1_2.status == STATUS_POD["Pending"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["Evict_and_replace_less_prioritized_pod_when_target_node_is_defined",\ "KillPod_IF_Deployment_isNUll_Service_isNotNull_Daemonset_isNotNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_10_startpod_without_deployment_without_service(): # print("10") "Test that StartPod works without daemonset/deployment and service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 ds = DaemonSet() # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,None,ds) n.amountOfActivePods = 1 # Service s = Service() s.podList.add(pod_running_1) pod_running_1.hasService = True # Pending pod pod_pending_1 = build_pending_pod_with_d(3,2,2,n,None,None) ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pod_running_1, s, pod_pending_1,ds]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_pending_1_1.status == STATUS_POD["Running"] p = NewGoal_k1(k.state_objects) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_pending_1_2.status == STATUS_POD["Running"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["SelectNode",\ "StartPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_11_startpod_without_deployment_with_service(): # print("11") "Test that StartPod works without daemonset/deployment but with service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 ds = DaemonSet() # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,None,ds) n.amountOfActivePods = 1 # Pending pod pod_pending_1 = build_pending_pod_with_d(3,2,2,n,None,None) # Service s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 0 s.status = STATUS_SERV["Pending"] s.podList.add(pod_pending_1) pod_pending_1.hasService = True ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pod_running_1, s, pod_pending_1,ds]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_pending_1_1.status == STATUS_POD["Running"] p = NewGoal_k1(k.state_objects) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_pending_1_2.status == STATUS_POD["Running"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["SelectNode",\ "StartPod_IF_Deployment_isNUll_Service_isNotNull_Daemonset_isNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_12_startpod_with_deployment_with_service(): # print("12") "Test that StartPod works with deployment and service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 d = Deployment() d.spec_replicas = 2 # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,d,None) n.amountOfActivePods = 1 # Pending pod pod_pending_1 = build_pending_pod_with_d(3,2,2,n,d,None) # Service s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 0 s.status = STATUS_SERV["Pending"] s.podList.add(pod_running_1) pod_running_1.hasService = True s.podList.add(pod_pending_1) pod_pending_1.hasService = True ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pod_running_1, s, pod_pending_1,d]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_pending_1_1.status == STATUS_POD["Running"] p = NewGoal_k1(k.state_objects) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_pending_1_2.status == STATUS_POD["Running"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["SelectNode",\ "StartPod_IF_Deployment_isNotNUll_Service_isNotNull_Daemonset_isNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_13_startpod_with_daemonset_without_service(): # print("13") "Test that StartPod works with daemonset and without service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 d = DaemonSet() # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,None,d) n.amountOfActivePods = 1 # Pending pod pod_pending_1 = build_pending_pod_with_d(3,2,2,n,None,d) ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pod_running_1, pod_pending_1,d]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_pending_1_1.status == STATUS_POD["Running"] p = NewGoal_k1(k.state_objects) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_pending_1_2.status == STATUS_POD["Running"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["StartPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_14_startpod_with_daemonset_with_service(): # print("14") "Test that StartPod works with daemonset and service" # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 d = DaemonSet() # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,None,d) n.amountOfActivePods = 1 # Pending pod pod_pending_1 = build_pending_pod_with_d(3,2,2,n,None,d) # Service s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 0 s.status = STATUS_SERV["Pending"] s.podList.add(pod_pending_1) pod_running_1.hasService = True s.podList.add(pod_pending_1) pod_pending_1.hasService = True ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pod_running_1, s, pod_pending_1,d]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_pending_1_1.status == STATUS_POD["Running"] p = NewGoal_k1(k.state_objects) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_pending_1_2.status == STATUS_POD["Running"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["StartPod_IF_Deployment_isNUll_Service_isNotNull_Daemonset_isNotNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) # @pytest.mark.skip(reason="FIXME") def test_15_has_deployment_creates_daemonset__pods_evicted_pods_pending_synthetic(): # print("15") # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 # create Deploymnent that we're going to detect failure of... d = Deployment() d.spec_replicas = 2 # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,d,None) pod_running_2 = build_running_pod_with_d(2,2,2,n,d,None) n.amountOfActivePods = 2 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] # Create Daemonset for prioritized pod ds = DaemonSet() # Pending pod pod_pending_1 = build_pending_pod_with_d(3,2,2,n,None,ds) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, pod_pending_1, d,s,ds]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() print_objects(k.state_objects) print_objects_from_yaml(k) print("----") print_objects(k2.state_objects) print_objects_from_yaml(k2) globalVar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) # class NewGoal_step1_k1(Check_deployments): # goal = lambda self: globalVar_k1.goal_achieved == True and\ # pod_pending_1_1.status == STATUS_POD["Running"] class NewGoal_k1(Check_deployments): pass p = NewGoal_k1(k.state_objects) globalVar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) class NewGoal_k2(Check_deployments): pass # class NewGoal_step1_k2(Check_deployments): # goal = lambda self: globalVar_k2.goal_achieved == True and\ # pod_pending_1_2.status == STATUS_POD["Running"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["Evict", "MarkDeploymentOutageEvent"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_16_creates_deployment_but_insufficient_resource__pods_pending_synthetic(): # print("16") # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) n.amountOfActivePods = 2 ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] # create Deploymnent that we're going to detect failure of... d = Deployment() d.podList.add(pod_running_1) d.podList.add(pod_running_2) d.amountOfActivePods = 2 d.spec_replicas = 2 dnew = Deployment() dnew.podList.add(pod_pending_1) dnew.amountOfActivePods = 0 dnew.spec_replicas = 1 k.state_objects.extend([n, pod_running_1, pod_running_2, d]) create_objects = [dnew] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() # pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class NewGoal_k1(Check_deployments): pass p = NewGoal_k1(k.state_objects) class NewGoal_k2(Check_deployments): pass p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["MarkDeploymentOutageEvent"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_17_creates_service_and_deployment_insufficient_resource__service_outage(): # print("17") # Initialize scheduler, globalVar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.searchable = False # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) n.amountOfActivePods = 2 ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 # priority for pod-to-evict # pc = PriorityClass() # pc.priority = 10 # pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] s.searchable = True # our service has multiple pods but we are detecting pods pending issue # remove service as we are detecting service outage by a bug above s.podList.add(pod_running_1) s.podList.add(pod_running_1) pod_running_1.hasService = True pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) # pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] # create Deploymnent that we're going to detect failure of... d = Deployment() d.podList.add(pod_running_1) d.podList.add(pod_running_2) d.amountOfActivePods = 2 d.spec_replicas = 2 pod_running_1.hasDeployment = True pod_running_2.hasDeployment = True dnew = Deployment() dnew.podList.add(pod_pending_1) dnew.amountOfActivePods = 0 dnew.spec_replicas = 1 pod_pending_1.hasDeployment = True snew = Service() snew.metadata_name = "test-service-new" snew.amountOfActivePods = 0 snew.status = STATUS_SERV["Pending"] snew.podList.add(pod_pending_1) pod_pending_1.hasService = True snew.searchable = True k.state_objects.extend([n, s, pod_running_1, pod_running_2, d]) create_objects = [snew,dnew] k2 = reload_cluster_from_yaml(k,create_objects) k.state_objects.extend(create_objects) k.state_objects.extend([pod_pending_1]) k._build_state() k2._build_state() n_k2 = next(filter(lambda x: isinstance(x, Node), k2.state_objects)) n_k2.searchable = False k._build_state() class NewGoal_k1(Check_services): pass p = NewGoal_k1(k.state_objects) class NewGoal_k2(Check_services): pass p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["MarkServiceOutageEvent"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_17_creates_service_and_deployment_insufficient_resource__service_outage_invtest(): # print("17") # Initialize scheduler, globalVar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) n.amountOfActivePods = 2 ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 # priority for pod-to-evict # pc = PriorityClass() # pc.priority = 10 # pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] s.searchable = True # our service has multiple pods but we are detecting pods pending issue # remove service as we are detecting service outage by a bug above s.podList.add(pod_running_1) s.podList.add(pod_running_2) pod_running_1.hasService = True pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) # pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] # create Deploymnent that we're going to detect failure of... d = Deployment() d.podList.add(pod_running_1) d.podList.add(pod_running_2) d.amountOfActivePods = 2 d.spec_replicas = 2 pod_running_1.hasDeployment = True pod_running_2.hasDeployment = True dnew = Deployment() dnew.metadata_name = "new-deploymt" dnew.podList.add(pod_pending_1) dnew.amountOfActivePods = 0 dnew.spec_replicas = 1 pod_pending_1.hasDeployment = True snew = Service() snew.metadata_name = "test-service-new" snew.amountOfActivePods = 0 snew.status = STATUS_SERV["Pending"] snew.podList.add(pod_pending_1) pod_pending_1.hasService = True snew.searchable = True k.state_objects.extend([n, s, pod_running_1, pod_running_2, d]) yamlState = convert_space_to_yaml(k.state_objects, wrap_items=True) create_objects = [snew, dnew] yamlCreate = convert_space_to_yaml(create_objects, wrap_items=False, load_logic_support=False) k2 = KubernetesCluster() for y in yamlState: # print(y) k2.load(y) for y in yamlCreate: k2.load(y, mode=KubernetesCluster.CREATE_MODE) k2._build_state() k._build_state() globalVar = k2.state_objects[1] scheduler = k2.state_objects[0] # print_objects(k.state_objects) class NewGoal(Check_services): # pass goal = lambda self: globalVar.is_service_disrupted == True and \ scheduler.status == STATUS_SCHED["Clean"] p = NewGoal(k2.state_objects) p.run(timeout=200) for a in p.plan: print(a) assert "MarkServiceOutageEvent" in "\n".join([repr(x) for x in p.plan]) assert not "NodeOutageFinished" in "\n".join([repr(x) for x in p.plan]) def test_17_2_creates_service_and_deployment_insufficient_resource__two_service_outage(): # print("17") # Initialize scheduler, globalVar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalVar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 # Create running pods pod_running_1 = build_running_pod(1,2,2,n) pod_running_2 = build_running_pod(2,2,2,n) n.amountOfActivePods = 2 ## Set consumptoin as expected n.currentFormalCpuConsumption = 4 n.currentFormalMemConsumption = 4 # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] s.searchable = True # our service has multiple pods but we are detecting pods pending issue # remove service as we are detecting service outage by a bug above s.podList.add(pod_running_1) s.podList.add(pod_running_2) pod_running_1.hasService = True pod_running_2.hasService = True # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_2 = build_pending_pod(4,2,2,n) # pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.podQueue.add(pod_pending_2) scheduler.queueLength += 2 scheduler.status = STATUS_SCHED["Changed"] # create Deploymnent that we're going to detect failure of... d = Deployment() d.podList.add(pod_running_1) d.podList.add(pod_running_2) d.amountOfActivePods = 2 d.spec_replicas = 2 pod_running_1.hasDeployment = True pod_running_2.hasDeployment = True dnew = Deployment() dnew.podList.add(pod_pending_1) dnew.amountOfActivePods = 0 dnew.spec_replicas = 1 pod_pending_1.hasDeployment = True snew = Service() snew.metadata_name = "test-service-new" snew.amountOfActivePods = 0 snew.status = STATUS_SERV["Pending"] snew.podList.add(pod_pending_1) pod_pending_1.hasService = True snew.searchable = True snew2 = Service() snew2.metadata_name = "test-service-new" snew2.amountOfActivePods = 0 snew2.status = STATUS_SERV["Pending"] snew2.podList.add(pod_pending_2) pod_pending_2.hasService = True snew2.searchable = True k.state_objects.extend([n, s, snew, snew2, pod_running_1, pod_running_2, pod_pending_1, pod_pending_2, d, dnew]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_pending_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k.state_objects)) class NewGoal_k1(Check_services): pass p = NewGoal_k1(k.state_objects) pod_pending_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Pending"], k2.state_objects)) class NewGoal_k2(Check_services): pass p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["MarkDeploymentOutageEvent"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_19_has_deployment_creates_deployment__pods_evicted_pods_pending_test_snackable_branch(): # print("19") k = KubernetesCluster() prios = {} pch = PriorityClass() k.state_objects.append(pch) pch.priority = 10 pch.metadata_name = "high-prio-test" prios["high"] = pch pcl = PriorityClass() k.state_objects.append(pcl) pcl.priority = 1 pcl.metadata_name = "low-prio-test" prios["low"] = pcl pods = [] node = Node() k.state_objects.append(node) node.memCapacity = 3 node.cpuCapacity = 3 d_was = Deployment() k.state_objects.append(d_was) d_was.metadata_name = "d_was" d_was.priorityClass = prios["low"] d_was.spec_template_spec_priorityClassName = prios["low"].metadata_name d_was.amountOfActivePods = 2 d_was.spec_replicas = 2 for i in range(2): pod = Pod() k.state_objects.append(pod) pod.metadata_name = "pod_number_" + str(i) pod.memRequest = 1 pod.cpuRequest = 1 pod.status = STATUS_POD["Running"] pod.priorityClass = prios["low"] pod.spec_priorityClassName = prios["low"].metadata_name pod.hasDeployment = True pods.append(pod) node.amountOfActivePods += 1 node.currentFormalMemConsumption += pod.memRequest node.currentFormalCpuConsumption += pod.cpuRequest d_was.podList.add(pod) d_new = Deployment() d_new.metadata_name = "d_new" d_new.spec_replicas = 2 d_new.priorityClass = prios["high"] d_new.spec_template_spec_priorityClassName = prios["high"].metadata_name d_new.memRequest = 1 d_new.cpuRequest = 1 d_new.hook_after_create(k.state_objects) k.state_objects.append(d_new) pod_pending_count = 0 pPod = [] for pod in filter(lambda x: isinstance(x, Pod), k.state_objects): if "pod_number_" in pod.metadata_name._get_value(): assert pod.status._get_value() == "Running", "pod_number_X pods should be Running before planning but have {0} status".format(pod.status._get_value()) if pod.status._get_value() == "Pending": pod_pending_count += 1 pPod.append(pod) assert pod_pending_count == 2, "should be 2 pod in pending have only {0}".format(pod_pending_count) class TestRun(K8ServiceInterruptSearch): goal = lambda self: self.scheduler.status == STATUS_SCHED["Clean"] and pPod[0].status == STATUS_POD["Running"]and pPod[1].status == STATUS_POD["Running"] p = TestRun(k.state_objects) # print_objects(k.state_objects) # p.run() # print("scenario \n{0}".format(p.plan)) p.xrun() # print("---after calculation ----") # print_objects(k.state_objects) assert d_new.amountOfActivePods == 2 assert d_was.amountOfActivePods == 1 assert node.amountOfActivePods == 3 for pod in filter(lambda x: isinstance(x, Pod), k.state_objects): if "d_new" in pod.metadata_name._get_value(): assert pod.status._get_value() == "Running", "{1} pods should be Running after planning but have {0} status".format(pod.status._get_value(),pod.metadata_name._get_value() ) @pytest.mark.skip(reason="This test case is broken see #109") def test_20_scheduller_counter_bug(): # print("20") k = KubernetesCluster() prios = {} pch = PriorityClass() k.state_objects.append(pch) pch.priority = 10 pch.metadata_name = "high-prio-test" prios["high"] = pch pcl = PriorityClass() k.state_objects.append(pcl) pcl.priority = 1 pcl.metadata_name = "low-prio-test" prios["low"] = pcl pods = [] node = Node() k.state_objects.append(node) node.memCapacity = 3 node.cpuCapacity = 3 d_was = Deployment() k.state_objects.append(d_was) d_was.metadata_name = "d_was" d_was.priorityClass = prios["low"] d_was.spec_template_spec_priorityClassName = prios["low"].metadata_name d_was.amountOfActivePods = 2 d_was.spec_replicas = 2 for i in range(2): pod = Pod() k.state_objects.append(pod) pod.metadata_name = "pod_number_" + str(i) pod.memRequest = 1 pod.cpuRequest = 1 pod.status = STATUS_POD["Running"] pod.priorityClass = prios["low"] pod.spec_priorityClassName = prios["low"].metadata_name pod.hasDeployment = True pods.append(pod) node.amountOfActivePods += 1 node.currentFormalMemConsumption += pod.memRequest node.currentFormalCpuConsumption += pod.cpuRequest d_was.podList.add(pod) d_new = Deployment() d_new.metadata_name = "d_new" d_new.spec_replicas = 2 d_new.priorityClass = prios["high"] d_new.spec_template_spec_priorityClassName = prios["high"].metadata_name d_new.memRequest = 1 d_new.cpuRequest = 1 d_new.hook_after_create(k.state_objects) k.state_objects.append(d_new) scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) pPod = [] for pod in filter(lambda x: isinstance(x, Pod), k.state_objects): if pod.status._get_value() == "Pending": pPod.append(pod) class TestRun(K8ServiceInterruptSearch): goal = lambda self: self.scheduler.status == STATUS_SCHED["Clean"] and pPod[0].status == STATUS_POD["Running"]and pPod[1].status == STATUS_POD["Running"] p = TestRun(k.state_objects) p.xrun() assert scheduler.queueLength._get_value() == 0 assert len(scheduler.podQueue._get_value()) == 0 def test_21_has_daemonset_creates_deployment__pods_evicted_daemonset_outage_synthetic(): # print("21") # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalvar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n1 = Node("node 1") n1.cpuCapacity = 3 n1.memCapacity = 3 n2 = Node("node 2") n2.cpuCapacity = 3 n2.memCapacity = 3 #Create Daemonset ds = DaemonSet() ds.searchable = True # Create running pods as Daemonset pod_running_1 = build_running_pod_with_d(1,2,2,n1,None,ds) pod_running_2 = build_running_pod_with_d(2,2,2,n2,None,ds) n1.amountOfActivePods = 1 n2.amountOfActivePods = 1 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # # Service to detecte eviction s = Service() s.metadata_name = "test-service" # Pending pod with deployment d = Deployment() d.spec_replicas = 1 d.priorityClass = pc pod_pending_1 = build_pending_pod_with_d(3,2,2,n1,d,None) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n1, n2, pc, pod_running_1, pod_running_2, pod_pending_1, d,ds]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() class NewGoal_k1(Check_daemonsets): pass p = NewGoal_k1(k.state_objects) class NewGoal_k2(Check_daemonsets): pass p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["MarkDaemonsetOutageEvent"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def prepare_test_22_has_daemonset_with_service_creates_deployment__pods_evicted_daemonset_outage_synthetic(): k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalvar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n1 = Node() n1.metadata_name = "node 1" n1.cpuCapacity = 3 n1.memCapacity = 3 n1.isNull == False n2 = Node("node 2") n2.metadata_name = "node 2" n2.cpuCapacity = 3 n2.memCapacity = 3 n2.isNull == False #Create Daemonset ds = DaemonSet() ds.searchable = True # Create running pods as Daemonset pod_running_1 = build_running_pod_with_d(1,2,2,n1,None,ds) pod_running_2 = build_running_pod_with_d(2,2,2,n2,None,ds) n1.amountOfActivePods = 1 n2.amountOfActivePods = 1 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 2 s.status = STATUS_SERV["Started"] s.podList.add(pod_running_1) s.podList.add(pod_running_2) # Pending pod with deployment d = Deployment() d.spec_replicas = 1 d.priorityClass = pc pod_pending_1 = build_pending_pod_with_d(3,2,2,n1,None,None) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n1, pc, pod_running_1, pod_running_2, pod_pending_1, d, ds]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() return k, k2 # @pytest.mark.debug(reason="if debug needed - uncomment me") # def test_22_has_daemonset_with_service_creates_deployment__pods_evicted_daemonset_outage_synthetic_step1(): # # print("22") # # Initialize scheduler, globalvar # k, k2 =prepare_test_22_has_daemonset_with_service_creates_deployment__pods_evicted_daemonset_outage_synthetic() # class NewGoal(OptimisticRun): # # pass # # goal = lambda self: globalvar.is_daemonset_disrupted == True # goal = lambda self: pod_running_1.status == STATUS_POD["Killing"] # p = NewGoal(k.state_objects) # p.run(timeout=200) # # for a in p.plan: # # print(a) # assert "Evict_and_replace_less_prioritized_pod_when_target_node_is_not_defined" in "\n".join([repr(x) for x in p.plan]) # # assert "MarkDeploymentOutageEvent" in "\n".join([repr(x) for x in p.plan]) # @pytest.mark.debug(reason="if debug needed - uncomment me") # def test_23_has_daemonset_with_service_creates_deployment__pods_evicted_daemonset_outage_synthetic_step2(): # # print("23") # # Initialize scheduler, globalvar # k, k2 = prepare_test_22_has_daemonset_with_service_creates_deployment__pods_evicted_daemonset_outage_synthetic() # # print_objects(k.state_objects) # class NewGoal(OptimisticRun): # # pass # # goal = lambda self: globalvar.is_daemonset_disrupted == True # goal = lambda self: pod_running_1.status == STATUS_POD["Pending"] # p = NewGoal(k.state_objects) # p.run(timeout=200) # # print("---after calculation ----") # # print_objects(k.state_objects) # # for a in p.plan: # # print(a) # assert "Evict_and_replace_less_prioritized_pod_when_target_node_is_not_defined" in "\n".join([repr(x) for x in p.plan]) # assert "KillPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull" in "\n".join([repr(x) for x in p.plan]) def test_24_has_daemonset_with_service_creates_deployment__pods_evicted_daemonset_outage_synthetic_step3(): # print("24") # Initialize scheduler, globalvar k, k2 = prepare_test_22_has_daemonset_with_service_creates_deployment__pods_evicted_daemonset_outage_synthetic() globalvar_k1 = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) globalvar_k2 = next(filter(lambda x: isinstance(x, GlobalVar), k2.state_objects)) class NewGoal_k1(Check_daemonsets): goal = lambda self: globalvar_k1.is_daemonset_disrupted == True p = NewGoal_k1(k.state_objects) class NewGoal_k2(Check_daemonsets): goal = lambda self: globalvar_k1.is_daemonset_disrupted == True p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["MarkDaemonsetOutageEvent"] not_assert_conditions = [] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def prepare_test_has_service_only_on_node_that_gets_disrupted(): k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) globalvar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # initial node state n1 = Node() n1.metadata_name = "node 1" n1.cpuCapacity = 6 n1.memCapacity = 6 n1.isNull == False n2 = Node("node 2") n2.metadata_name = "node 2" n2.cpuCapacity = 6 n2.memCapacity = 6 n2.isNull == False # Create running pods as Daemonset pod_running_1 = build_running_pod_with_d(1,2,2,n1,None,None) pod_running_2 = build_running_pod_with_d(2,2,2,n1,None,None) pod_running_3 = build_running_pod_with_d(3,2,2,n1,None,None) pod_running_4 = build_running_pod_with_d(4,2,2,n2,None,None) pod_running_5 = build_running_pod_with_d(5,2,2,n2,None,None) pod_running_6 = build_running_pod_with_d(6,2,2,n2,None,None) n1.amountOfActivePods = 3 n2.amountOfActivePods = 3 # # Service to detecte eviction s1 = Service() s1.metadata_name = "test-service1" s1.amountOfActivePods = 2 s1.status = STATUS_SERV["Started"] s2 = Service() s2.metadata_name = "test-service2" s2.amountOfActivePods = 4 s2.status = STATUS_SERV["Started"] s1.podList.add(pod_running_1) s1.podList.add(pod_running_2) s2.podList.add(pod_running_3) s2.podList.add(pod_running_4) s2.podList.add(pod_running_5) s2.podList.add(pod_running_6) # s2.podList.add(pod_running_7) pod_running_1.hasService = True pod_running_2.hasService = True pod_running_3.hasService = True pod_running_4.hasService = True pod_running_5.hasService = True pod_running_6.hasService = True ## We have clean scheduler queue scheduler.status = STATUS_SCHED["Clean"] k.state_objects.extend([n1, n2, s1, s2, pod_running_1, pod_running_2, pod_running_3, pod_running_4, pod_running_5, pod_running_6]) return k,n1,pod_running_1 # @pytest.mark.skip(reason="if debug needed - uncomment me") # def test_25_node_outage_with_service_eviction_step0(): # # print("25") # # Initialize scheduler, globalvar # k,n1,pod_running_1=construct_space_1322_has_service_only_on_node_that_gets_disrupted() # globalvar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # class test_25_node_outage_with_service_eviction_step1(Check_services): # goal = lambda self: self.pod_running_1.status == STATUS_POD["Killing"] # p = test_25_node_outage_with_service_eviction_step1(k.state_objects) # p.run(timeout=200) # # print_objects(k.state_objects) # # for a in p.plan: # # print(a) # assert "Initiate_node_outage" in "\n".join([repr(x) for x in p.plan]) # # assert "Evict_and_replace_less_prioritized_pod_when_target_node_is_not_defined" in "\n".join([repr(x) for x in p.plan]) # # assert "KillPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull" in "\n".join([repr(x) for x in p.plan]) # # assert "MarkDaemonsetOutageEvent" in "\n".join([repr(x) for x in p.plan]) # # @pytest.mark.skip(reason="if debug needed - uncomment me") # def test_25_node_outage_with_service_eviction_step1(): # # print("25") # # Initialize scheduler, globalvar # k,n1=construct_space_1322_has_service_only_on_node_that_gets_disrupted() # globalvar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # class test_25_node_outage_with_service_eviction_step1(Check_services): # goal = lambda self: n1.status == STATUS_NODE["Inactive"] # p = test_25_node_outage_with_service_eviction_step1(k.state_objects) # p.run(timeout=200) # # print_objects(k.state_objects) # # for a in p.plan: # # print(a) # assert "Initiate_node_outage" in "\n".join([repr(x) for x in p.plan]) # # assert "Evict_and_replace_less_prioritized_pod_when_target_node_is_not_defined" in "\n".join([repr(x) for x in p.plan]) # # assert "KillPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull" in "\n".join([repr(x) for x in p.plan]) # # assert "MarkDaemonsetOutageEvent" in "\n".join([repr(x) for x in p.plan]) # @pytest.mark.skip(reason="if debug needed - uncomment me") # def test_26_node_outage_with_service_eviction_step2(): # # print("26") # # Initialize scheduler, globalvar # k,n1=construct_space_1322_has_service_only_on_node_that_gets_disrupted() # globalvar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # class Check_services(Check_services): # goal = lambda self: globalvar.is_node_disrupted == True # p = Check_services(k.state_objects) # p.run(timeout=200) # # print_objects(k.state_objects) # # for a in p.plan: # # print(a) # # assert "StartPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull" in "\n".join([repr(x) for x in p.plan]) # # assert "Evict_and_replace_less_prioritized_pod_when_target_node_is_not_defined" in "\n".join([repr(x) for x in p.plan]) # # assert "KillPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull" in "\n".join([repr(x) for x in p.plan]) # # assert "MarkDaemonsetOutageEvent" in "\n".join([repr(x) for x in p.plan]) # @pytest.mark.debug(reason="if debug needed - uncomment me") # def test_27_node_outage_with_service_eviction_step3(): # # print("27") # # Initialize scheduler, globalvar # k,n1=construct_space_1322_has_service_only_on_node_that_gets_disrupted() # globalvar = next(filter(lambda x: isinstance(x, GlobalVar), k.state_objects)) # class Check_services_with_node_eviction(Check_services): # goal = lambda self: globalvar.is_node_disrupted == True and globalvar.is_service_disrupted == True # p = Check_services_with_node_eviction(k.state_objects) # p.run(timeout=200) # # print_objects(k.state_objects) # # for a in p.plan: # # print(a) # # assert "StartPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull" in "\n".join([repr(x) for x in p.plan]) # # assert "Evict_and_replace_less_prioritized_pod_when_target_node_is_not_defined" in "\n".join([repr(x) for x in p.plan]) # # assert "KillPod_IF_Deployment_isNUll_Service_isNull_Daemonset_isNotNull" in "\n".join([repr(x) for x in p.plan]) # # assert "MarkDaemonsetOutageEvent" in "\n".join([repr(x) for x in p.plan]) def test_28_from_test_5_evict_and_killpod_deployment_without_service_with_null_mem_request(): # print("28") # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state n = Node() n.cpuCapacity = 5 n.memCapacity = 5 n.isNull = False # create Deploymnent that we're going to detect failure of... d = Deployment() d.spec_replicas = 2 # Create running pods pod_running_1 = build_running_pod_with_d(1,2,2,n,d,None) pod_running_2 = build_running_pod_with_d(2,2,2,n,d,None) n.amountOfActivePods = 2 pod_running_1.memRequest = 0 pod_running_2.memRequest = 0 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" # Service to detecte eviction s = Service() s.metadata_name = "test-service" # Pending pod pod_pending_1 = build_pending_pod(3,2,2,n) pod_pending_1.priorityClass = pc # high prio will evict! ## Add pod to scheduler queue scheduler.podQueue.add(pod_pending_1) scheduler.queueLength += 1 scheduler.status = STATUS_SCHED["Changed"] k.state_objects.extend([n, pc, pod_running_1, pod_running_2, s, pod_pending_1, d]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() pod_running_1_1 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k.state_objects)) class NewGoal_k1(OptimisticRun): goal = lambda self: pod_running_1_1.status == STATUS_POD["Pending"] p = NewGoal_k1(k.state_objects) pod_running_1_2 = next(filter(lambda x: isinstance(x, Pod) and x.status._property_value == STATUS_POD["Running"], k2.state_objects)) class NewGoal_k2(OptimisticRun): goal = lambda self: pod_running_1_2.status == STATUS_POD["Pending"] p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["Evict_and_replace_less_prioritized_pod_when_target_node_is_defined",\ "KillPod_IF_Deployment_isNotNUll_Service_isNull_Daemonset_isNull"] not_assert_conditions = ["NodeOutageFinished"] checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) def prepare_test_29_many_pods_not_enough_capacity_for_service(nodes_amount,node_capacity,pod2_amount,pod0_amount,pod2_2_amount,pod3_amount): # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state i = 0 j = 0 nodes = [] pods = [] # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 0 s2 = Service() s2.metadata_name = "test-service2" s2.amountOfActivePods = 0 # create Deploymnent that we're going to detect failure of... d = Deployment() d.spec_replicas = 2 pod_id = 1 for i in range(nodes_amount): node_item = Node("node"+str(i)) node_item.cpuCapacity = node_capacity node_item.memCapacity = node_capacity node_item.isNull = False node_item.status = STATUS_NODE["Active"] nodes.append(node_item) for j in range(pod2_amount): pod_running_2 = build_running_pod_with_d(pod_id,2,2,node_item,None,None) pod_id += 1 pod_running_2.hasService = True pods.append(pod_running_2) node_item.amountOfActivePods += 1 s.podList.add(pod_running_2) s.amountOfActivePods +=1 for j in range(pod0_amount): pod_running_0 = build_running_pod_with_d(pod_id,0,0,node_item,None,None) pod_id += 1 pods.append(pod_running_0) node_item.amountOfActivePods += 1 for j in range(pod2_2_amount): pod_running_2 = build_running_pod_with_d(pod_id,2,2,node_item,None,None) pod_id += 1 pod_running_2.hasService = True pods.append(pod_running_2) node_item.amountOfActivePods += 1 s.podList.add(pod_running_2) s.amountOfActivePods +=1 for j in range(pod3_amount): pod_running_2 = build_running_pod_with_d(pod_id,2,2,nodes[0],None,None) pod_id += 1 pod_running_2.hasService = True pods.append(pod_running_2) node_item.amountOfActivePods += 1 s2.podList.add(pod_running_2) s2.amountOfActivePods +=1 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" k.state_objects.extend(nodes) k.state_objects.extend(pods) k.state_objects.extend([pc, s, s2 ]) create_objects = [] k2 = reload_cluster_from_yaml(k,create_objects) k._build_state() class NewGoal_k1(CheckNodeOutage): pass p = NewGoal_k1(k.state_objects) class NewGoal_k2(CheckNodeOutage): pass p2 = NewGoal_k2(k2.state_objects) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] return k, k2, p , p2 def prepare_test_29_many_pods_not_enough_capacity_for_service_without_yaml_loading(nodes_amount,node_capacity,pod2_amount,pod0_amount,pod2_2_amount,pod3_amount): # Initialize scheduler, globalvar k = KubernetesCluster() scheduler = next(filter(lambda x: isinstance(x, Scheduler), k.state_objects)) # initial node state i = 0 j = 0 nodes = [] pods = [] # Service to detecte eviction s = Service() s.metadata_name = "test-service" s.amountOfActivePods = 0 s2 = Service() s2.metadata_name = "test-service2" s2.amountOfActivePods = 0 # create Deploymnent that we're going to detect failure of... d = Deployment() d.spec_replicas = 2 pod_id = 1 for i in range(nodes_amount): node_item = Node("node"+str(i)) node_item.cpuCapacity = node_capacity node_item.memCapacity = node_capacity node_item.isNull = False node_item.status = STATUS_NODE["Active"] nodes.append(node_item) for j in range(pod2_amount): pod_running_2 = build_running_pod_with_d(pod_id,2,2,node_item,None,None) pod_id += 1 pod_running_2.hasService = True pods.append(pod_running_2) node_item.amountOfActivePods += 1 s.podList.add(pod_running_2) s.amountOfActivePods +=1 for j in range(pod0_amount): pod_running_0 = build_running_pod_with_d(pod_id,0,0,node_item,None,None) pod_id += 1 pods.append(pod_running_0) node_item.amountOfActivePods += 1 for j in range(pod2_2_amount): pod_running_2 = build_running_pod_with_d(pod_id,2,2,node_item,None,None) pod_id += 1 pod_running_2.hasService = True pods.append(pod_running_2) node_item.amountOfActivePods += 1 s.podList.add(pod_running_2) s.amountOfActivePods +=1 for j in range(pod3_amount): pod_running_2 = build_running_pod_with_d(pod_id,2,2,nodes[1],None,None) pod_id += 1 pod_running_2.hasService = True pods.append(pod_running_2) node_item.amountOfActivePods += 1 s2.podList.add(pod_running_2) s2.amountOfActivePods +=1 # priority for pod-to-evict pc = PriorityClass() pc.priority = 10 pc.metadata_name = "high-prio-test" k.state_objects.extend(nodes) k.state_objects.extend(pods) k.state_objects.extend([pc, s, s2 ]) create_objects = [] k._build_state() class NewGoal_k1(CheckNodeOutage): pass p = NewGoal_k1(k.state_objects) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] return k, p def test_29(): k, k2, p, p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,15,1,1,1,1) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_30(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,19,2,2,1,1) assert_conditions = ["SchedulerQueueCleanHighCost",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_31(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,23,3,3,1,1) assert_conditions = ["SchedulerQueueCleanHighCost",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_32(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,26,3,3,2,2) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_33(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,32,4,4,4,4) assert_conditions = ["SchedulerQueueCleanHighCost",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_34(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,40,5,5,5,5) assert_conditions = ["SchedulerQueueCleanHighCost",\ "Mark_node_outage_event"] not_assert_conditions = [] checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_36(): k, k2, p, p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,8,1,1,1,1) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_37(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,8,2,2,1,1) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_38(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,8,3,3,1,1) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_39(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,4,4,4,4) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_40(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,25,5,5,5,5) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,DEBUG_MODE) def test_41(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,11,4,4,4,4) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_42(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,5,5,4,4) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_43(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,5,5,5,4) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_44(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,5,5,5,5) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_45(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,4,4,4,4) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_46(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,16,5,4,4,4) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_47(): k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,20,5,5,4,4) assert_conditions = ["MarkServiceOutageEvent",\ "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions_in_one_mode(k,p,assert_conditions,not_assert_conditions,"functional test", DEBUG_MODE) def test_48(): node = 24 for cap in range(10,20): print("test node ", node, " cap " ,cap) k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(1,node,cap,0,0,1) assert_conditions = ["MarkServiceOutageEvent", "Mark_node_outage_event"] not_assert_conditions = [] assert_brake = checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) # def test_49(): # k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,25,5,5,5,5) # assert_conditions = ["MarkServiceOutageEvent",\ # "Mark_node_outage_event"] # not_assert_conditions = [] # assert_brake = checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) # def test_50(): # k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,4,4,4,4) # assert_conditions = ["MarkServiceOutageEvent",\ # "Mark_node_outage_event"] # not_assert_conditions = [] # assert_brake = checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) # def test_51(): # k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,4,4,4,4) # assert_conditions = ["MarkServiceOutageEvent",\ # "Mark_node_outage_event"] # not_assert_conditions = [] # assert_brake = checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) # def test_52(): # k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,4,4,4,4) # assert_conditions = ["MarkServiceOutageEvent",\ # "Mark_node_outage_event"] # not_assert_conditions = [] # assert_brake = checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE) # def test_53(): # k, k2,p ,p2 = prepare_test_29_many_pods_not_enough_capacity_for_service(2,12,4,4,4,4) # assert_conditions = ["MarkServiceOutageEvent",\ # "Mark_node_outage_event"] # not_assert_conditions = [] # assert_brake = checks_assert_conditions(k,k2,p,p2,assert_conditions,not_assert_conditions,DEBUG_MODE)

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null

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1

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null

0

7

d1104812377106b10e65deca4522853d8d89e36f

11,815

py

Python

src/genie/libs/parser/iosxe/tests/ShowIpBgpDetail/cli/equal/golden_output8_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

204

2018-06-27T00:55:27.000Z

2022-03-06T21:12:18.000Z

src/genie/libs/parser/iosxe/tests/ShowIpBgpDetail/cli/equal/golden_output8_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

468

2018-06-19T00:33:18.000Z

2022-03-31T23:23:35.000Z

src/genie/libs/parser/iosxe/tests/ShowIpBgpDetail/cli/equal/golden_output8_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

309

2019-01-16T20:21:07.000Z

2022-03-30T12:56:41.000Z

expected_output = { "instance": { "default": { "vrf": { "vrf_1": { "address_family": { "vpnv4": { "default_vrf": "vrf_1", "prefixes": { "10.64.4.0/22": { "available_path": "1", "best_path": "", "index": { 1: { "community": "65100:106 65100:500 65100:601 65361:3", "ext_community": "RT:65000:31838", "gateway": "10.9.3.4", "localpref": 100, "next_hop": "10.9.3.4", "next_hop_via": "vrf vrf_1", "origin_codes": "i", "originator": "10.9.3.4", "recipient_pathid": "0", "refresh_epoch": 1, "route_info": "65000 65201 4400004007 4400004507 4400004001 4400004505 4400004005 4400004504 1234 5678", "route_status": "received-only", "status_codes": "* ", "transfer_pathid": "0", } }, "paths": "1 available, no best path", "table_version": "0", }, "10.64.4.0/24": { "available_path": "4", "best_path": "3", "index": { 1: { "community": "9:9 65100:106 65100:508 65100:704 65371:2", "ext_community": "RT:65000:31838", "gateway": "10.9.3.4", "localpref": 100, "next_hop": "10.9.3.4", "next_hop_via": "vrf vrf_1", "origin_codes": "i", "originator": "10.9.3.4", "recipient_pathid": "0", "refresh_epoch": 1, "route_info": "65000 65211 4400002007 4400002507 4400002001 4400002505 4400002005 4400002504 3456 5678 2345", "route_status": "received-only", "status_codes": "* ", "transfer_pathid": "0", "update_group": [2, 3, 47], }, 2: { "community": "9:9 65100:106 65100:508 65100:700 65100:704 65371:2", "gateway": "10.105.3.84", "localpref": 100, "next_hop": "10.105.3.84", "next_hop_via": "vrf vrf_1", "origin_codes": "i", "originator": "10.105.2.27", "recipient_pathid": "0", "refresh_epoch": 1, "route_info": "4400005007 4400005507 4400005001 4400065100 4400002001 4400002505 4400002005 4400002504 3456 5678 2345", "route_status": "received & used", "status_codes": "* ", "transfer_pathid": "0", "update_group": [2, 3, 47], }, 3: { "community": "9:9 65100:106 65100:508 65100:700 65100:704 65371:2", "gateway": "10.105.3.80", "localpref": 100, "next_hop": "10.105.3.80", "next_hop_via": "vrf vrf_1", "origin_codes": "i", "originator": "10.105.2.26", "recipient_pathid": "0", "refresh_epoch": 1, "route_info": "4400005007 4400005507 4400005001 4400065100 4400002001 4400002505 4400002005 4400002504 3456 5678 2345", "route_status": "received & used", "status_codes": "*>", "transfer_pathid": "0x0", "update_group": [2, 3, 47], }, 4: { "community": "9:9 65100:106 65100:508 65100:700 65100:704 65371:2", "gateway": "10.105.2.1", "localpref": 100, "metric": 0, "next_hop": "10.105.2.1", "next_hop_igp_metric": "2", "next_hop_via": "vrf vrf_1", "origin_codes": "i", "originator": "10.105.2.1", "recipient_pathid": "0", "refresh_epoch": 2, "route_info": "4400005007 4400005507 4400005001 4400065100 4400002001 4400002505 4400002005 4400002504 3456 5678 2345", "route_status": "received & used", "status_codes": "* i", "transfer_pathid": "0", "update_group": [2, 3, 47], }, }, "paths": "4 available, best #3, table vrf_1", "table_version": "1863365", }, }, "route_distinguisher": "101:101", } } }, "vrf_2": { "address_family": { "vpnv4": { "default_vrf": "vrf_2", "prefixes": { "0.0.0.0/0": { "available_path": "3", "best_path": "2", "index": { 1: { "community": "65100:106 65100:500 65100:601 65351:1", "gateway": "10.105.6.84", "localpref": 100, "next_hop": "10.105.6.84", "next_hop_via": "vrf vrf_2", "origin_codes": "i", "originator": "10.105.5.17", "recipient_pathid": "0", "refresh_epoch": 1, "route_info": "4400005002 4400005502 4400005001 4400005505 4400005005 4400005504 6789 5678", "route_status": "received & used", "status_codes": "* ", "transfer_pathid": "0", "update_group": [1, 29, 54], }, 2: { "community": "65100:106 65100:500 65100:601 65351:1", "gateway": "10.105.6.80", "localpref": 100, "next_hop": "10.105.6.80", "next_hop_via": "vrf vrf_2", "origin_codes": "i", "originator": "10.105.5.16", "recipient_pathid": "0", "refresh_epoch": 1, "route_info": "4400005002 4400005502 4400005001 4400005505 4400005005 4400005504 6789 5678", "route_status": "received & used", "status_codes": "*>", "transfer_pathid": "0x0", "update_group": [1, 29, 54], }, 3: { "community": "65100:106 65100:500 65100:601 65351:1", "gateway": "10.105.5.1", "localpref": 100, "metric": 0, "next_hop": "10.105.5.1", "next_hop_igp_metric": "2", "next_hop_via": "vrf vrf_2", "origin_codes": "i", "originator": "10.105.5.1", "recipient_pathid": "0", "refresh_epoch": 3, "route_info": "4400005002 4400005502 4400005001 4400005505 4400005005 4400005504 6789 5678", "route_status": "received & used", "status_codes": "* i", "transfer_pathid": "0", "update_group": [1, 29, 54], }, }, "paths": "3 available, best #2, table vrf_2", "table_version": "1814679", } }, "route_distinguisher": "102:102", } } }, } } } }

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9

d128d1b109e903d6f3a6da3739207addf75d8a9a

3,382

py

Python

secuencias.py

CCG-Magno/Tutoriales_Python

7f6291675cabccc35ddad71070271cbc58e7e283

[ "MIT" ]

1

2020-09-20T22:37:20.000Z

secuencias.py

CCG-Magno/Tutoriales_Python

7f6291675cabccc35ddad71070271cbc58e7e283

[ "MIT" ]

null

secuencias.py

CCG-Magno/Tutoriales_Python

7f6291675cabccc35ddad71070271cbc58e7e283

[ "MIT" ]

null

class Node: def __init__(self,val): self.val = val self.nxt = None return class DoubleNode(Node): def __init__(self, val): return def listas(): # Las listas son secuencias de objetos/valores separados por comas # que quedan encasillados por brackets '[' ']' # Ej: asistencia = ["Juan" , "Jesus" , "Antonio" , "Luis"] print(f"Tomemos asistencia para la clase:\n{asistencia}\n") # Los objetos no necesariamente tienen que ser del mismo tipo. # Ej: valores_aleatorios = ["a", 10 , 0.75, False] print(f"Escupamos basura:\n{valores_aleatorios}\n") print() print(f"El tipo de 'asistencia' es {type(asistencia)} y el tipo de 'valores_aleatorios' es {type(valores_aleatorios)}'\n") #las listas pueden crecer o disminuir en tamano dinamicamente mientras se ejecuta el programa print(f"Tamano de asistencia: {len(asistencia)}\n") #ahora vamos anadir alguien que llego tarde tarde = "Andres" print(f"{tarde} llego tarde!") asistencia.append(tarde) # Tomemos asistencia otra vez print(f"Tomemos asistencia para la clase(gracias {tarde}!):\n{asistencia}\n") # verifiquemos de nuevo el tamano print(f"Tamano de asistencia: {len(asistencia)}\n") #Alguien se fue del salon #Para eliminar alguien de la lista usamos o eliminamos en base al indice que ocupan en la lista. # Nota: Los indices van en el rango: [0, len(lista)-1] # Es decir, si el tamano de la lista es 5 el rango seria: [0,4] asistencia.remove('Jesus') print(f"Tomemos asistencia para la clase(adios Jesus!):\n{asistencia}\n") print(f"Tamano de asistencia: {len(asistencia)}\n") return def sets(): return def tuples(): # Las listas son secuencias de objetos/valores separados por comas # que quedan encasillados por parentesis '(' ')' # Ej: asistencia = ("Juan" , "Jesus" , "Antonio" , "Luis") print(f"Tomemos asistencia para la clase:\n{asistencia}\n") # Los objetos no necesariamente tienen que ser del mismo tipo. # Ej: valores_aleatorios = ("a", 10 , 0.75, False) print(f"Escupamos basura:\n{valores_aleatorios}\n") print() print(f"El tipo de 'asistencia' es {type(asistencia)} y el tipo de 'valores_aleatorios' es {type(valores_aleatorios)}'\n") #las listas pueden crecer o disminuir en tamano dinamicamente mientras se ejecuta el programa print(f"Tamano de asistencia: {len(asistencia)}\n") #ahora vamos anadir alguien que llego tarde tarde = "Andres" print(f"{tarde} llego tarde!") asistencia.append(tarde) # Tomemos asistencia otra vez print(f"Tomemos asistencia para la clase(gracias {tarde}!):\n{asistencia}\n") # verifiquemos de nuevo el tamano print(f"Tamano de asistencia: {len(asistencia)}\n") #Alguien se fue del salon #Para eliminar alguien de la lista usamos o eliminamos en base al indice que ocupan en la lista. # Nota: Los indices van en el rango: [0, len(lista)-1] # Es decir, si el tamano de la lista es 5 el rango seria: [0,4] asistencia.remove('Jesus') print(f"Tomemos asistencia para la clase(adios Jesus!):\n{asistencia}\n") print(f"Tamano de asistencia: {len(asistencia)}\n") return def main(): listas() return if __name__ == "__main__": main()

31.314815

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0.662034

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108

127

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null

0

1

0

null

0

1

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7

d155f8b61a43304988d0511d2e2c6841d7b25d71

5,204

py

Python

linguistic_style_transfer_model/config/human_annotation_config.py

spencerbraun/linguistic-style-transfer

76774bc805c56e823f958f98e6ae8d5973518757

[ "Apache-2.0" ]

136

2018-08-17T21:31:01.000Z

2022-01-03T15:01:41.000Z

linguistic_style_transfer_model/config/human_annotation_config.py

spencerbraun/linguistic-style-transfer

76774bc805c56e823f958f98e6ae8d5973518757

[ "Apache-2.0" ]

18

2018-06-29T21:41:28.000Z

2020-07-09T08:53:37.000Z

linguistic_style_transfer_model/config/human_annotation_config.py

spencerbraun/linguistic-style-transfer

76774bc805c56e823f958f98e6ae8d5973518757

[ "Apache-2.0" ]

29

2018-09-27T04:51:10.000Z

2022-03-01T21:24:04.000Z

output_folder = "/home/v2john/documents/style-transfer-models/annotations/" annotation_config = { "nips-yelp-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/nips/yelp/data/sentiment.test.1", "generated": "/home/v2john/documents/style-transfer-models/nips/yelp/sentiment.test.1.tsf", "count": 20 }, "nips-yelp-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/nips/yelp/data/sentiment.test.0", "generated": "/home/v2john/documents/style-transfer-models/nips/yelp/sentiment.test.0.tsf", "count": 20 }, "aaai-yelp-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/nips/yelp/data/sentiment.test.1", "generated": "/home/v2john/documents/style-transfer-models/aaai/yelp-test/fixed/style0.txt", "count": 20 }, "aaai-yelp-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/nips/yelp/data/sentiment.test.0", "generated": "/home/v2john/documents/style-transfer-models/aaai/yelp-test/fixed/style1.txt", "count": 20 }, "iclr-yelp-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/iclr/stytra-yelp/26_output_decoder_1_from.txt", "generated": "/home/v2john/documents/style-transfer-models/iclr/stytra-yelp/26_output_decoder_1_tran.txt", "count": 20 }, "iclr-yelp-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/iclr/stytra-yelp/26_output_decoder_2_from.txt", "generated": "/home/v2john/documents/style-transfer-models/iclr/stytra-yelp/26_output_decoder_2_tran.txt", "count": 20 }, "dae-yelp-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/output/20180629130342-inference/actual_sentences_0.txt", "generated": "/home/v2john/documents/style-transfer-models/output/20180629130342-inference/generated_sentences_0.txt", "count": 20 }, "dae-yelp-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/output/20180629130342-inference/actual_sentences_1.txt", "generated": "/home/v2john/documents/style-transfer-models/output/20180629130342-inference/generated_sentences_1.txt", "count": 20 }, "vae-yelp-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/output/20180702122511-inference/actual_sentences_0.txt", "generated": "/home/v2john/documents/style-transfer-models/output/20180702122511-inference/generated_sentences_0.txt", "count": 20 }, "vae-yelp-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/output/20180702122511-inference/actual_sentences_1.txt", "generated": "/home/v2john/documents/style-transfer-models/output/20180702122511-inference/generated_sentences_1.txt", "count": 20 }, "nips-amazon-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/nips/amazon/data/sentiment.test.1", "generated": "/home/v2john/documents/style-transfer-models/nips/amazon/sentiment.test.1.tsf", "count": 0 }, "nips-amazon-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/nips/amazon/data/sentiment.test.0", "generated": "/home/v2john/documents/style-transfer-models/nips/amazon/sentiment.test.0.tsf", "count": 0 }, "aaai-amazon-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/nips/amazon/data/sentiment.test.1", "generated": "/home/v2john/documents/style-transfer-models/aaai/amazon-test/fixed/style0.txt", "count": 0 }, "aaai-amazon-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/nips/amazon/data/sentiment.test.0", "generated": "/home/v2john/documents/style-transfer-models/aaai/amazon-test/fixed/style1.txt", "count": 0 }, "dae-amazon-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/output/20180707010403-inference/actual_sentences_0.txt", "generated": "/home/v2john/documents/style-transfer-models/output/20180707010403-inference/generated_sentences_0.txt", "count": 0 }, "dae-amazon-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/output/20180707010403-inference/actual_sentences_1.txt", "generated": "/home/v2john/documents/style-transfer-models/output/20180707010403-inference/generated_sentences_1.txt", "count": 0 }, "vae-amazon-pos-to-neg": { "original": "/home/v2john/documents/style-transfer-models/output/20180707142655-inference/actual_sentences_0.txt", "generated": "/home/v2john/documents/style-transfer-models/output/20180707142655-inference/generated_sentences_0.txt", "count": 0 }, "vae-amazon-neg-to-pos": { "original": "/home/v2john/documents/style-transfer-models/output/20180707142655-inference/actual_sentences_1.txt", "generated": "/home/v2john/documents/style-transfer-models/output/20180707142655-inference/generated_sentences_1.txt", "count": 0 } }

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66f588f30e37b7a0b2379b655e8c19406302cded

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py

Python

tests/test_formatter.py

kevinzg/beanbot

4558804f539720895f9fea2bb46bcdbfe886b034

[ "MIT" ]

4

2019-09-30T10:04:45.000Z

2021-09-18T05:39:08.000Z

tests/test_formatter.py

kevinzg/beanbot

4558804f539720895f9fea2bb46bcdbfe886b034

[ "MIT" ]

2

2021-07-30T02:13:56.000Z

2021-07-30T02:14:02.000Z

tests/test_formatter.py

kevinzg/beanbot

4558804f539720895f9fea2bb46bcdbfe886b034

[ "MIT" ]

1

2021-03-23T10:40:37.000Z

import textwrap from decimal import Decimal from beanbot.formatter import format_transaction from beanbot.models import Posting, Transaction class TestFormatTransaction: def test_format_simple_transaction(self): tx = Transaction( id=1, date=None, info='Test', postings=[ Posting( id=1, debit_account='Food', credit_account='Cash', amount=Decimal(10), currency='USD', ) ], ) assert ( format_transaction(tx) == textwrap.dedent( """ Test ` 10.00 USD `_Food_ `=======` `- 10.00 USD `Cash """ ).strip() ) def test_format_simple_transaction_with_empty_info(self): tx = Transaction( id=1, date=None, info='', postings=[ Posting( id=1, debit_account='Food', credit_account='Cash', amount=Decimal(10), currency='USD', ) ], ) assert ( format_transaction(tx) == textwrap.dedent( """ ` 10.00 USD `_Food_ `=======` `- 10.00 USD `Cash """ ).strip() ) def test_format_transaction_two_postings(self): tx = Transaction( id=1, date=None, info='Test', postings=[ Posting( id=1, debit_account='Food', credit_account='Cash', amount=Decimal(10), currency='USD', ), Posting( id=2, debit_account='Candy', credit_account='Cash', amount=Decimal(2), currency='USD', ), ], ) assert ( format_transaction(tx) == textwrap.dedent( """ Test ` 10.00 USD `_Food_ ` 2.00 USD `_Candy_ `=======` `- 12.00 USD `Cash """ ).strip() ) def test_format_transaction_different_credit_account(self): tx = Transaction( id=1, date=None, info='Test', postings=[ Posting( id=1, debit_account='Food', credit_account='Cash', amount=Decimal(10), currency='USD', ), Posting( id=2, debit_account='Candy', credit_account='CC', amount=Decimal(2), currency='USD', ), ], ) assert ( format_transaction(tx) == textwrap.dedent( """ Test ` 10.00 USD `_Food_ ` 2.00 USD `_Candy_ `=======` `- 10.00 USD `Cash `- 2.00 USD `CC """ ).strip() ) def test_format_transaction_default_currency(self): tx = Transaction( id=1, date=None, info='Test', postings=[ Posting( id=1, debit_account='Food', credit_account='Cash', amount=Decimal(10), currency='USD', ), Posting( id=2, debit_account='Candy', credit_account='CC', amount=Decimal(2), currency='USD', ), ], ) assert ( format_transaction(tx, default_currency='USD') == textwrap.dedent( """ Test ` 10.00 `_Food_ ` 2.00 `_Candy_ `=======` `- 10.00 `Cash `- 2.00 `CC """ ).strip() ) def test_format_transaction_different_credit_accounts_and_currency(self): tx = Transaction( id=1, date=None, info='Test', postings=[ Posting( id=1, debit_account='Food', credit_account='Cash', amount=Decimal(10), currency='USD', ), Posting( id=2, debit_account='Candy', credit_account='CC', amount=Decimal(2), currency='EUR', ), ], ) assert ( format_transaction(tx) == textwrap.dedent( """ Test ` 10.00 USD `_Food_ ` 2.00 EUR `_Candy_ `=======` `- 10.00 USD `Cash `- 2.00 EUR `CC """ ).strip() ) def test_format_transaction_postings_different_currency(self): tx = Transaction( id=1, date=None, info='Test', postings=[ Posting( id=1, debit_account='Food', credit_account='Cash', amount=Decimal(10), currency='USD', ), Posting( id=2, debit_account='Candy', credit_account='Cash', amount=Decimal(2), currency='EUR', ), ], ) formatted = textwrap.dedent( """ Test ` 10.00 USD `_Food_ ` 2.00 EUR `_Candy_ `=======` `- 10.00 USD `Cash `- 2.00 EUR ` """ ).strip() assert format_transaction(tx) == formatted assert format_transaction(tx, default_currency='USD') == formatted def test_format_transaction_postings_credit_accounts_with_different_currency(self): tx = Transaction( id=1, date=None, info='Test', postings=[ Posting( id=1, debit_account='Food', credit_account='Cash', amount=Decimal(10), currency='USD', ), Posting( id=2, debit_account='Candy', credit_account='Cash', amount=Decimal(2), currency='EUR', ), Posting( id=3, debit_account='Books', credit_account='Bank', amount=Decimal(10), currency='USD', ), Posting( id=4, debit_account='Cookies', credit_account='Bank', amount=Decimal(2), currency='EUR', ), ], ) formatted = textwrap.dedent( """ Test ` 10.00 USD `_Food_ ` 2.00 EUR `_Candy_ ` 10.00 USD `_Books_ ` 2.00 EUR `_Cookies_ `=======` `- 10.00 USD `Cash `- 2.00 EUR ` `- 10.00 USD `Bank `- 2.00 EUR ` """ ).strip() assert format_transaction(tx) == formatted assert format_transaction(tx, default_currency='USD') == formatted def test_escape_markdown(self): tx = Transaction( id=1, date=None, info='Test . _ * `', postings=[ Posting( id=1, debit_account='Food.', credit_account='Cash', amount=Decimal(10), currency='USD', ) ], ) assert ( format_transaction(tx) == textwrap.dedent( """ Test \\. \\_ \\* \\` ` 10.00 USD `_Food\\._ `=======` `- 10.00 USD `Cash """ ).strip() )

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8

66fb1b41a10989c63e0b6d781b0db1d4a3997406

3,669

py

Python

openstates/openstates-master/scripts/affected_code/fl-test.py

Jgorsick/Advocacy_Angular

8906af3ba729b2303880f319d52bce0d6595764c

[ "CC-BY-4.0" ]

null

openstates/openstates-master/scripts/affected_code/fl-test.py

Jgorsick/Advocacy_Angular

8906af3ba729b2303880f319d52bce0d6595764c

[ "CC-BY-4.0" ]

null

openstates/openstates-master/scripts/affected_code/fl-test.py

Jgorsick/Advocacy_Angular

8906af3ba729b2303880f319d52bce0d6595764c

[ "CC-BY-4.0" ]

null

s = ''' Subsections (1), (2), (3), (4), and (6) and paragraph (c) of subsection (7) of section 1002.69, Florida Statutes, are amended to read: Section 1003.46, Florida Statutes, is amended to read: Paragraph (d) of subsection (3) of section 1002.20, Florida Statutes, is amended to read: Subsection (10) of section 447.203, Florida Statutes, is amended to read: Paragraph (a) of subsection (4) of section 1001.20, Florida Statutes, is amended to read: Paragraphs (b) and (e) of subsection (1) and subsections (2) and (4) of section 1006.33, Florida Statutes, are amended to read: Subsection (1), paragraph (a) of subsection (2), and paragraphs (b) and (e) of subsection (3) of section 1006.28, Florida Statutes, are amended to read: Subsections (1), (2), (3), and (7) of section 1006.34, Florida Statutes, are amended to read: Subsection (2), paragraph (a) of subsection (3), and subsection (4) of section 1006.40, Florida Statutes, are amended to read: Paragraph (p) of subsection (1) and paragraph (b) of subsection (6) of section 1011.62, Florida Statutes, are amended to read: Paragraph (b) of subsection (3) and subsection (4) of section 1008.33, Florida Statutes, are amended to read: Subsection (23) of section 1001.42, Florida Statutes, is amended to read: Paragraph (b) of subsection (5) of section 1002.33, Florida Statutes, is amended to read: Paragraph (a) of subsection (1) of section 1002.37, Florida Statutes, is amended to read: Paragraph (f) is added to subsection (3) of section 1002.38, Florida Statutes, to read: Paragraph (b) of subsection (2) of section 1002.45, Florida Statutes, is amended to read: Subsection (1) and paragraph (c) of subsection (3) of section 1002.67, Florida Statutes, are amended to read: Subsection (2) of section 1002.73, Florida Statutes, is amended to read: Paragraph (c) of subsection (4) of section 1003.03, Florida Statutes, is amended to read: Subsection (1) of section 1003.4156, Florida Statutes, is amended to read: Section 1003.4203, Florida Statutes, is created to read: Subsection (2) of section 1003.428, Florida Statutes, is amended to read: Subsection (1) of section 1003.492, Florida Statutes, is amended to read: Section 1003.493, Florida Statutes, is amended to read: Section 1003.575, Florida Statutes, is amended to read: Subsection (2) of section 1003.621, Florida Statutes, is amended to read: Section 1006.29, Florida Statutes, is amended to read: Section 1006.30, Florida Statutes, is amended to read: Section 1006.31, Florida Statutes, is amended to read: Section 1006.32, Florida Statutes, is amended to read: Subsection (2) of section 1006.35, Florida Statutes, is amended to read: Section 1006.36, Florida Statutes, is amended to read: Section 1006.37, Florida Statutes, is repealed. Subsection (5) of section 1006.39, Florida Statutes, is amended to read: Section 1006.43, Florida Statutes, is amended to read: Effective upon this act becoming a law, subsection (2) and paragraph (c) of subsection (3) of section 1008.22, Florida Statutes, are amended to read: Subsection (3) of section 1008.34, Florida Statutes, is amended to read: Paragraph (a) of subsection (3) of section 1011.01, Florida Statutes, is amended to read: Subsection (4) of section 1011.03, Florida Statutes, is amended to read: Subsection (1) of section 1011.61, Florida Statutes, is amended to read: Subsection (1) of section 1012.39, Florida Statutes, is amended to read:''' def main(): from core.utils import parse from core.fl import Lexer, Parser for section in filter(None, s.splitlines()): tokens = parse(Lexer, Parser, None, section) print section if __name__ == '__main__': main()

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66fc3367cda58f58ef8a5b1539d76a81537678b0

160

py

Python

queued_mailer/utils.py

jar3b/django-queued-mailer

51554bf80cc0e36869d2dc61b92175f5f7402b3f

[ "MIT" ]

1

2018-12-05T13:35:17.000Z

queued_mailer/utils.py

jar3b/django-queued-mailer

51554bf80cc0e36869d2dc61b92175f5f7402b3f

[ "MIT" ]

null

queued_mailer/utils.py

jar3b/django-queued-mailer

51554bf80cc0e36869d2dc61b92175f5f7402b3f

[ "MIT" ]

null

from django.core.mail import get_connection from .settings import EMAIL_BACKEND def get_email_connection(): return get_connection(backend=EMAIL_BACKEND)

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0f443cefc172960cc543bd2710642cedd560c527

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py

Python

tests/test_basic.py

deeplook/mcinstall

52e6926316f5db329a194cfd1dfcca638cb40d67

[ "MIT" ]

6

2019-09-30T12:10:53.000Z

2020-03-13T09:34:32.000Z

tests/test_basic.py

sackh/mcinstall

2bda5942096c23a52057ecef7d9d2bba9e3045b8

[ "MIT" ]

14

2020-02-19T07:59:37.000Z

2020-05-15T06:18:00.000Z

tests/test_basic.py

sackh/mcinstall

2bda5942096c23a52057ecef7d9d2bba9e3045b8

[ "MIT" ]

3

2020-02-16T14:45:55.000Z

2020-03-13T09:34:58.000Z

""" Test creating Miniconda installation and provisioning. """ import json import os import re import subprocess import sys import pytest import platform import tempfile import shutil from mcinstall import MinicondaInstaller, config def test_show_config(): print(json.dumps(config, indent=4)) @pytest.mark.skipif(platform.system() == "Windows", reason="uname command will not run on Windows.") def test_uname_m(): out = subprocess.check_output(["uname", "-m"]) print(out.decode("utf-8")) def test_install_dependencies(): try: with tempfile.TemporaryDirectory() as tempdir: mci = MinicondaInstaller(tempdir, verbose=True) mci.download() mci.install_miniconda() mci.update_miniconda_base() mci.install_pip(dependencies=["geopy"]) mci.install_conda(channel="conda-forge", dependencies=["pyyaml"]) if platform.system() == "Windows": py_exe = "%s\\python" % tempdir else: py_exe = "%s/bin/python" % tempdir # Run Miniconda's Python and import the installed dependencies. for pkg_name in ["geopy", "pyyaml"]: if pkg_name == "pyyaml": pkg_name = "yaml" if platform.system() == "Windows": cmd = [ "%s\\condabin\\activate"%(tempdir), "&&", py_exe, "-c", '''import %s; print("%s %%s ok" %% %s.__version__)''' % \ (pkg_name, pkg_name, pkg_name) ] else: cmd = [ py_exe, "-c", '''import %s; print("%s %%s ok" %% %s.__version__)''' % \ (pkg_name, pkg_name, pkg_name) ] if platform.system() == "Windows": out = subprocess.check_output(cmd, shell=True).decode("utf-8").strip() else: out = subprocess.check_output(cmd).decode("utf-8").strip() print(out) if platform.system() == "Windows": assert re.search("%s .+ ok" % pkg_name, out) else: assert re.match("%s .+ ok" % pkg_name, out) except NotADirectoryError as err: print(err) shutil.rmtree(tempdir) print() assert not os.path.exists(tempdir) def test_install_dependencies_index_url(): try: with tempfile.TemporaryDirectory() as tempdir: mci = MinicondaInstaller(tempdir, verbose=True) mci.download() mci.install_miniconda() mci.update_miniconda_base() mci.install_pip(dependencies=["pypi_pkg_test"], index_url="https://test.pypi.org/simple/") if platform.system() == "Windows": py_exe = "%s\\python" % tempdir else: py_exe = "%s/bin/python" % tempdir # Run Miniconda's Python and import the installed dependencies. for pkg_name in ["pypi_pkg_test"]: cmd = [ py_exe, "-c", '''import %s; print("%s %%s ok" %% %s)''' % \ (pkg_name, pkg_name, pkg_name) ] if platform.system() == "Windows": out = subprocess.check_output(cmd, shell=True).decode("utf-8").strip() else: out = subprocess.check_output(cmd).decode("utf-8").strip() print(out) assert re.match("%s .+ ok" % pkg_name, out) except NotADirectoryError: shutil.rmtree(tempdir) print() assert not os.path.exists(tempdir) def test_install_dependencies_extra_index_url(): try: with tempfile.TemporaryDirectory() as tempdir: mci = MinicondaInstaller(tempdir, verbose=True) mci.download() mci.install_miniconda() mci.update_miniconda_base() mci.install_pip(dependencies=["pypi_pkg_test"], index_url="https://test.pypi.org/simpletest/", extra_index_url="https://test.pypi.org/simple/") if platform.system() == "Windows": py_exe = "%s\\python" % tempdir else: py_exe = "%s/bin/python" % tempdir # Run Miniconda's Python and import the installed dependencies. for pkg_name in ["pypi_pkg_test"]: cmd = [ py_exe, "-c", '''import %s; print("%s %%s ok" %% %s)''' % \ (pkg_name, pkg_name, pkg_name) ] if platform.system() == "Windows": out = subprocess.check_output(cmd, shell=True).decode("utf-8").strip() else: out = subprocess.check_output(cmd).decode("utf-8").strip() print(out) assert re.match("%s .+ ok" % pkg_name, out) except NotADirectoryError: shutil.rmtree(tempdir) print() assert not os.path.exists(tempdir) def test_install_dependencies_extra_index_urls(): try: with tempfile.TemporaryDirectory() as tempdir: mci = MinicondaInstaller(tempdir, verbose=True) mci.download() mci.install_miniconda() mci.update_miniconda_base() mci.install_pip(dependencies=["pypi_pkg_test"], index_url="https://test.pypi.org/simpletest/", extra_index_url="https://test.pypi.org/simpletest1/, https://test.pypi.org/simple/") if platform.system() == "Windows": py_exe = "%s\\python" % tempdir else: py_exe = "%s/bin/python" % tempdir # Run Miniconda's Python and import the installed dependencies. for pkg_name in ["pypi_pkg_test"]: cmd = [ py_exe, "-c", '''import %s; print("%s %%s ok" %% %s)''' % \ (pkg_name, pkg_name, pkg_name) ] if platform.system() == "Windows": out = subprocess.check_output(cmd, shell=True).decode("utf-8").strip() else: out = subprocess.check_output(cmd).decode("utf-8").strip() print(out) assert re.match("%s .+ ok" % pkg_name, out) except NotADirectoryError: shutil.rmtree(tempdir) print() assert not os.path.exists(tempdir)

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py

Python

Pyto Mac/PyObjC/VideoToolbox/_metadata.py

cclauss/Pyto

1c4ccc47e3a91e996bf6ec38c527d244de2cf7ed

[ "MIT" ]

4

2019-03-11T18:05:49.000Z

2021-05-22T21:09:09.000Z

Pyto Mac/PyObjC/VideoToolbox/_metadata.py

cclauss/Pyto

1c4ccc47e3a91e996bf6ec38c527d244de2cf7ed

[ "MIT" ]

null

Pyto Mac/PyObjC/VideoToolbox/_metadata.py

cclauss/Pyto

1c4ccc47e3a91e996bf6ec38c527d244de2cf7ed

[ "MIT" ]

1

2019-03-18T18:53:36.000Z

# This file is generated by objective.metadata # # Last update: Sun Sep 9 19:02:46 2018 import objc, sys if sys.maxsize > 2 ** 32: def sel32or64(a, b): return b else: def sel32or64(a, b): return a if sys.byteorder == 'little': def littleOrBig(a, b): return a else: def littleOrBig(a, b): return b misc = { } misc.update({'VTInt32Point': objc.createStructType('VTInt32Point', b'{VTInt32Point=ii}', ['x', 'y']), 'VTInt32Size': objc.createStructType('VTInt32Size', b'{VTInt32Size=ii}', ['width', 'height'])}) constants = '''$kVTCompressionPropertyKey_AllowFrameReordering@^{__CFString=}$kVTCompressionPropertyKey_AllowOpenGOP@^{__CFString=}$kVTCompressionPropertyKey_AllowTemporalCompression@^{__CFString=}$kVTCompressionPropertyKey_AspectRatio16x9@^{__CFString=}$kVTCompressionPropertyKey_AverageBitRate@^{__CFString=}$kVTCompressionPropertyKey_BaseLayerFrameRate@^{__CFString=}$kVTCompressionPropertyKey_CleanAperture@^{__CFString=}$kVTCompressionPropertyKey_ColorPrimaries@^{__CFString=}$kVTCompressionPropertyKey_ContentLightLevelInfo@^{__CFString=}$kVTCompressionPropertyKey_DataRateLimits@^{__CFString=}$kVTCompressionPropertyKey_Depth@^{__CFString=}$kVTCompressionPropertyKey_EncoderID@^{__CFString=}$kVTCompressionPropertyKey_ExpectedDuration@^{__CFString=}$kVTCompressionPropertyKey_ExpectedFrameRate@^{__CFString=}$kVTCompressionPropertyKey_FieldCount@^{__CFString=}$kVTCompressionPropertyKey_FieldDetail@^{__CFString=}$kVTCompressionPropertyKey_H264EntropyMode@^{__CFString=}$kVTCompressionPropertyKey_ICCProfile@^{__CFString=}$kVTCompressionPropertyKey_MasteringDisplayColorVolume@^{__CFString=}$kVTCompressionPropertyKey_MaxFrameDelayCount@^{__CFString=}$kVTCompressionPropertyKey_MaxH264SliceBytes@^{__CFString=}$kVTCompressionPropertyKey_MaxKeyFrameInterval@^{__CFString=}$kVTCompressionPropertyKey_MaxKeyFrameIntervalDuration@^{__CFString=}$kVTCompressionPropertyKey_MaximizePowerEfficiency@^{__CFString=}$kVTCompressionPropertyKey_MoreFramesAfterEnd@^{__CFString=}$kVTCompressionPropertyKey_MoreFramesBeforeStart@^{__CFString=}$kVTCompressionPropertyKey_MultiPassStorage@^{__CFString=}$kVTCompressionPropertyKey_NumberOfPendingFrames@^{__CFString=}$kVTCompressionPropertyKey_PixelAspectRatio@^{__CFString=}$kVTCompressionPropertyKey_PixelBufferPoolIsShared@^{__CFString=}$kVTCompressionPropertyKey_PixelTransferProperties@^{__CFString=}$kVTCompressionPropertyKey_ProfileLevel@^{__CFString=}$kVTCompressionPropertyKey_ProgressiveScan@^{__CFString=}$kVTCompressionPropertyKey_Quality@^{__CFString=}$kVTCompressionPropertyKey_RealTime@^{__CFString=}$kVTCompressionPropertyKey_SourceFrameCount@^{__CFString=}$kVTCompressionPropertyKey_TransferFunction@^{__CFString=}$kVTCompressionPropertyKey_UsingHardwareAcceleratedVideoEncoder@^{__CFString=}$kVTCompressionPropertyKey_VideoEncoderPixelBufferAttributes@^{__CFString=}$kVTCompressionPropertyKey_YCbCrMatrix@^{__CFString=}$kVTDecompressionPropertyKey_ContentHasInterframeDependencies@^{__CFString=}$kVTDecompressionPropertyKey_DeinterlaceMode@^{__CFString=}$kVTDecompressionPropertyKey_FieldMode@^{__CFString=}$kVTDecompressionPropertyKey_MaxOutputPresentationTimeStampOfFramesBeingDecoded@^{__CFString=}$kVTDecompressionPropertyKey_MaximizePowerEfficiency@^{__CFString=}$kVTDecompressionPropertyKey_MinOutputPresentationTimeStampOfFramesBeingDecoded@^{__CFString=}$kVTDecompressionPropertyKey_NumberOfFramesBeingDecoded@^{__CFString=}$kVTDecompressionPropertyKey_OnlyTheseFrames@^{__CFString=}$kVTDecompressionPropertyKey_OutputPoolRequestedMinimumBufferCount@^{__CFString=}$kVTDecompressionPropertyKey_PixelBufferPool@^{__CFString=}$kVTDecompressionPropertyKey_PixelBufferPoolIsShared@^{__CFString=}$kVTDecompressionPropertyKey_PixelFormatsWithReducedResolutionSupport@^{__CFString=}$kVTDecompressionPropertyKey_PixelTransferProperties@^{__CFString=}$kVTDecompressionPropertyKey_RealTime@^{__CFString=}$kVTDecompressionPropertyKey_ReducedCoefficientDecode@^{__CFString=}$kVTDecompressionPropertyKey_ReducedFrameDelivery@^{__CFString=}$kVTDecompressionPropertyKey_ReducedResolutionDecode@^{__CFString=}$kVTDecompressionPropertyKey_SuggestedQualityOfServiceTiers@^{__CFString=}$kVTDecompressionPropertyKey_SupportedPixelFormatsOrderedByPerformance@^{__CFString=}$kVTDecompressionPropertyKey_SupportedPixelFormatsOrderedByQuality@^{__CFString=}$kVTDecompressionPropertyKey_ThreadCount@^{__CFString=}$kVTDecompressionPropertyKey_UsingHardwareAcceleratedVideoDecoder@^{__CFString=}$kVTDecompressionProperty_DeinterlaceMode_Temporal@^{__CFString=}$kVTDecompressionProperty_DeinterlaceMode_VerticalFilter@^{__CFString=}$kVTDecompressionProperty_FieldMode_BothFields@^{__CFString=}$kVTDecompressionProperty_FieldMode_BottomFieldOnly@^{__CFString=}$kVTDecompressionProperty_FieldMode_DeinterlaceFields@^{__CFString=}$kVTDecompressionProperty_FieldMode_SingleField@^{__CFString=}$kVTDecompressionProperty_FieldMode_TopFieldOnly@^{__CFString=}$kVTDecompressionProperty_OnlyTheseFrames_AllFrames@^{__CFString=}$kVTDecompressionProperty_OnlyTheseFrames_IFrames@^{__CFString=}$kVTDecompressionProperty_OnlyTheseFrames_KeyFrames@^{__CFString=}$kVTDecompressionProperty_OnlyTheseFrames_NonDroppableFrames@^{__CFString=}$kVTDecompressionProperty_TemporalLevelLimit@^{__CFString=}$kVTDecompressionResolutionKey_Height@^{__CFString=}$kVTDecompressionResolutionKey_Width@^{__CFString=}$kVTDownsamplingMode_Average@^{__CFString=}$kVTDownsamplingMode_Decimate@^{__CFString=}$kVTEncodeFrameOptionKey_ForceKeyFrame@^{__CFString=}$kVTH264EntropyMode_CABAC@^{__CFString=}$kVTH264EntropyMode_CAVLC@^{__CFString=}$kVTMultiPassStorageCreationOption_DoNotDelete@^{__CFString=}$kVTPixelTransferPropertyKey_DestinationCleanAperture@^{__CFString=}$kVTPixelTransferPropertyKey_DestinationColorPrimaries@^{__CFString=}$kVTPixelTransferPropertyKey_DestinationICCProfile@^{__CFString=}$kVTPixelTransferPropertyKey_DestinationPixelAspectRatio@^{__CFString=}$kVTPixelTransferPropertyKey_DestinationTransferFunction@^{__CFString=}$kVTPixelTransferPropertyKey_DestinationYCbCrMatrix@^{__CFString=}$kVTPixelTransferPropertyKey_DownsamplingMode@^{__CFString=}$kVTPixelTransferPropertyKey_ScalingMode@^{__CFString=}$kVTProfileLevel_H263_Profile0_Level10@^{__CFString=}$kVTProfileLevel_H263_Profile0_Level45@^{__CFString=}$kVTProfileLevel_H263_Profile3_Level45@^{__CFString=}$kVTProfileLevel_H264_Baseline_1_3@^{__CFString=}$kVTProfileLevel_H264_Baseline_3_0@^{__CFString=}$kVTProfileLevel_H264_Baseline_3_1@^{__CFString=}$kVTProfileLevel_H264_Baseline_3_2@^{__CFString=}$kVTProfileLevel_H264_Baseline_4_0@^{__CFString=}$kVTProfileLevel_H264_Baseline_4_1@^{__CFString=}$kVTProfileLevel_H264_Baseline_4_2@^{__CFString=}$kVTProfileLevel_H264_Baseline_5_0@^{__CFString=}$kVTProfileLevel_H264_Baseline_5_1@^{__CFString=}$kVTProfileLevel_H264_Baseline_5_2@^{__CFString=}$kVTProfileLevel_H264_Baseline_AutoLevel@^{__CFString=}$kVTProfileLevel_H264_Extended_5_0@^{__CFString=}$kVTProfileLevel_H264_Extended_AutoLevel@^{__CFString=}$kVTProfileLevel_H264_High_3_0@^{__CFString=}$kVTProfileLevel_H264_High_3_1@^{__CFString=}$kVTProfileLevel_H264_High_3_2@^{__CFString=}$kVTProfileLevel_H264_High_4_0@^{__CFString=}$kVTProfileLevel_H264_High_4_1@^{__CFString=}$kVTProfileLevel_H264_High_4_2@^{__CFString=}$kVTProfileLevel_H264_High_5_0@^{__CFString=}$kVTProfileLevel_H264_High_5_1@^{__CFString=}$kVTProfileLevel_H264_High_5_2@^{__CFString=}$kVTProfileLevel_H264_High_AutoLevel@^{__CFString=}$kVTProfileLevel_H264_Main_3_0@^{__CFString=}$kVTProfileLevel_H264_Main_3_1@^{__CFString=}$kVTProfileLevel_H264_Main_3_2@^{__CFString=}$kVTProfileLevel_H264_Main_4_0@^{__CFString=}$kVTProfileLevel_H264_Main_4_1@^{__CFString=}$kVTProfileLevel_H264_Main_4_2@^{__CFString=}$kVTProfileLevel_H264_Main_5_0@^{__CFString=}$kVTProfileLevel_H264_Main_5_1@^{__CFString=}$kVTProfileLevel_H264_Main_5_2@^{__CFString=}$kVTProfileLevel_H264_Main_AutoLevel@^{__CFString=}$kVTProfileLevel_HEVC_Main10_AutoLevel@^{__CFString=}$kVTProfileLevel_HEVC_Main_AutoLevel@^{__CFString=}$kVTProfileLevel_MP4V_AdvancedSimple_L0@^{__CFString=}$kVTProfileLevel_MP4V_AdvancedSimple_L1@^{__CFString=}$kVTProfileLevel_MP4V_AdvancedSimple_L2@^{__CFString=}$kVTProfileLevel_MP4V_AdvancedSimple_L3@^{__CFString=}$kVTProfileLevel_MP4V_AdvancedSimple_L4@^{__CFString=}$kVTProfileLevel_MP4V_Main_L2@^{__CFString=}$kVTProfileLevel_MP4V_Main_L3@^{__CFString=}$kVTProfileLevel_MP4V_Main_L4@^{__CFString=}$kVTProfileLevel_MP4V_Simple_L0@^{__CFString=}$kVTProfileLevel_MP4V_Simple_L1@^{__CFString=}$kVTProfileLevel_MP4V_Simple_L2@^{__CFString=}$kVTProfileLevel_MP4V_Simple_L3@^{__CFString=}$kVTPropertyDocumentationKey@^{__CFString=}$kVTPropertyReadWriteStatusKey@^{__CFString=}$kVTPropertyReadWriteStatus_ReadOnly@^{__CFString=}$kVTPropertyReadWriteStatus_ReadWrite@^{__CFString=}$kVTPropertyShouldBeSerializedKey@^{__CFString=}$kVTPropertySupportedValueListKey@^{__CFString=}$kVTPropertySupportedValueMaximumKey@^{__CFString=}$kVTPropertySupportedValueMinimumKey@^{__CFString=}$kVTPropertyTypeKey@^{__CFString=}$kVTPropertyType_Boolean@^{__CFString=}$kVTPropertyType_Enumeration@^{__CFString=}$kVTPropertyType_Number@^{__CFString=}$kVTScalingMode_CropSourceToCleanAperture@^{__CFString=}$kVTScalingMode_Letterbox@^{__CFString=}$kVTScalingMode_Normal@^{__CFString=}$kVTScalingMode_Trim@^{__CFString=}$kVTVideoDecoderSpecification_EnableHardwareAcceleratedVideoDecoder@^{__CFString=}$kVTVideoDecoderSpecification_PreferredDecoderGPURegistryID@^{__CFString=}$kVTVideoDecoderSpecification_RequireHardwareAcceleratedVideoDecoder@^{__CFString=}$kVTVideoDecoderSpecification_RequiredDecoderGPURegistryID@^{__CFString=}$kVTVideoEncoderList_CodecName@^{__CFString=}$kVTVideoEncoderList_CodecType@^{__CFString=}$kVTVideoEncoderList_DisplayName@^{__CFString=}$kVTVideoEncoderList_EncoderID@^{__CFString=}$kVTVideoEncoderList_EncoderName@^{__CFString=}$kVTVideoEncoderSpecification_EnableHardwareAcceleratedVideoEncoder@^{__CFString=}$kVTVideoEncoderSpecification_EncoderID@^{__CFString=}$kVTVideoEncoderSpecification_RequireHardwareAcceleratedVideoEncoder@^{__CFString=}$''' enums = '''$kVTAllocationFailedErr@-12904$kVTColorCorrectionImageRotationFailedErr@-12219$kVTColorCorrectionPixelTransferFailedErr@-12212$kVTColorSyncTransformConvertFailedErr@-12919$kVTCompressionSessionBeginFinalPass@1$kVTCouldNotCreateColorCorrectionDataErr@-12918$kVTCouldNotCreateInstanceErr@-12907$kVTCouldNotFindTemporalFilterErr@-12217$kVTCouldNotFindVideoDecoderErr@-12906$kVTCouldNotFindVideoEncoderErr@-12908$kVTDecodeFrame_1xRealTimePlayback@4$kVTDecodeFrame_DoNotOutputFrame@2$kVTDecodeFrame_EnableAsynchronousDecompression@1$kVTDecodeFrame_EnableTemporalProcessing@8$kVTDecodeInfo_Asynchronous@1$kVTDecodeInfo_FrameDropped@2$kVTDecodeInfo_ImageBufferModifiable@4$kVTEncodeInfo_Asynchronous@1$kVTEncodeInfo_FrameDropped@2$kVTFormatDescriptionChangeNotSupportedErr@-12916$kVTFrameSiloInvalidTimeRangeErr@-12216$kVTFrameSiloInvalidTimeStampErr@-12215$kVTImageRotationNotSupportedErr@-12914$kVTInsufficientSourceColorDataErr@-12917$kVTInvalidSessionErr@-12903$kVTMultiPassStorageIdentifierMismatchErr@-12213$kVTMultiPassStorageInvalidErr@-12214$kVTParameterErr@-12902$kVTPixelTransferNotPermittedErr@-12218$kVTPixelTransferNotSupportedErr@-12905$kVTPropertyNotSupportedErr@-12900$kVTPropertyReadOnlyErr@-12901$kVTUnlimitedFrameDelayCount@-1$kVTVideoDecoderAuthorizationErr@-12210$kVTVideoDecoderBadDataErr@-12909$kVTVideoDecoderMalfunctionErr@-12911$kVTVideoDecoderNotAvailableNowErr@-12913$kVTVideoDecoderRemovedErr@-17690$kVTVideoDecoderUnsupportedDataFormatErr@-12910$kVTVideoEncoderAuthorizationErr@-12211$kVTVideoEncoderMalfunctionErr@-12912$kVTVideoEncoderNotAvailableNowErr@-12915$''' misc.update({}) functions={'VTPixelTransferSessionCreate': (sel32or64(b'l^{__CFAllocator=}^^{OpaqueVTPixelTransferSession=}', b'i^{__CFAllocator=}^^{OpaqueVTPixelTransferSession=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {1: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTCreateCGImageFromCVPixelBuffer': (sel32or64(b'l^{__CVBuffer=}^{__CFDictionary=}^^{CGImage=}', b'i^{__CVBuffer=}^{__CFDictionary=}^^{CGImage=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {2: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTMultiPassStorageGetTypeID': (sel32or64(b'L', b'Q'),), 'VTDecompressionSessionFinishDelayedFrames': (sel32or64(b'l^{OpaqueVTDecompressionSession=}', b'i^{OpaqueVTDecompressionSession=}'),), 'VTSessionCopySupportedPropertyDictionary': (sel32or64(b'l@^^{__CFDictionary=}', b'i@^^{__CFDictionary=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {1: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTSessionSetProperty': (sel32or64(b'l@^{__CFString=}@', b'i@^{__CFString=}@'),), 'VTPixelTransferSessionTransferImage': (sel32or64(b'l^{OpaqueVTPixelTransferSession=}^{__CVBuffer=}^{__CVBuffer=}', b'i^{OpaqueVTPixelTransferSession=}^{__CVBuffer=}^{__CVBuffer=}'),), 'VTFrameSiloGetProgressOfCurrentPass': (sel32or64(b'l^{OpaqueVTFrameSilo=}^f', b'i^{OpaqueVTFrameSilo=}^f'), '', {'arguments': {1: {'type_modifier': 'o'}}}), 'VTMultiPassStorageClose': (sel32or64(b'l^{OpaqueVTMultiPassStorage=}', b'i^{OpaqueVTMultiPassStorage=}'),), 'VTIsHardwareDecodeSupported': (sel32or64(b'ZL', b'ZI'),), 'VTCompressionSessionPrepareToEncodeFrames': (sel32or64(b'l^{OpaqueVTCompressionSession=}', b'i^{OpaqueVTCompressionSession=}'),), 'VTCompressionSessionInvalidate': (b'v^{OpaqueVTCompressionSession=}',), 'VTCompressionSessionCompleteFrames': (sel32or64(b'l^{OpaqueVTCompressionSession=}{_CMTime=qiIq}', b'i^{OpaqueVTCompressionSession=}{_CMTime=qiIq}'),), 'VTFrameSiloCallBlockForEachSampleBuffer': (sel32or64(b'l^{OpaqueVTFrameSilo=}{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}@?', b'i^{OpaqueVTFrameSilo=}{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}@?'), '', {'arguments': {2: {'callable': {'retval': {'type': b'i'}, 'arguments': {0: {'type': '^v'}, 1: {'type': '^{opaqueCMSampleBuffer=}'}}}, 'block': {'retval': {'type': b'i'}, 'arguments': {0: {'type': b'^{opaqueCMSampleBuffer=}'}}}}}}), 'VTSessionCopyProperty': (sel32or64(b'l@^{__CFString=}^{__CFAllocator=}^@', b'i@^{__CFString=}^{__CFAllocator=}^@'), '', {'retval': {'already_cfretained': True}, 'arguments': {3: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTFrameSiloAddSampleBuffer': (sel32or64(b'l^{OpaqueVTFrameSilo=}^{opaqueCMSampleBuffer=}', b'i^{OpaqueVTFrameSilo=}^{opaqueCMSampleBuffer=}'),), 'VTDecompressionSessionDecodeFrame': (sel32or64(b'l^{OpaqueVTDecompressionSession=}^{opaqueCMSampleBuffer=}I^v^L', b'i^{OpaqueVTDecompressionSession=}^{opaqueCMSampleBuffer=}I^v^I'), '', {'arguments': {4: {'type_modifier': 'o'}}}), 'VTRegisterProfessionalVideoWorkflowVideoEncoders': (b'v',), 'VTCompressionSessionEncodeFrameWithOutputHandler': (sel32or64(b'l^{OpaqueVTCompressionSession=}^{__CVBuffer=}{_CMTime=qiIq}{_CMTime=qiIq}^{__CFDictionary=}^L@?', b'i^{OpaqueVTCompressionSession=}^{__CVBuffer=}{_CMTime=qiIq}{_CMTime=qiIq}^{__CFDictionary=}^I@?'), '', {'arguments': {5: {'type_modifier': 'o'}, 6: {'callable': {'retval': {'type': b'v'}, 'arguments': {0: {'type': '^v'}, 1: {'type': 'i'}, 2: {'type': [u'I', u'Q']}, 3: {'type': '^{opaqueCMSampleBuffer=}'}}}}}}), 'VTPixelTransferSessionGetTypeID': (sel32or64(b'L', b'Q'),), 'VTCompressionSessionGetTypeID': (sel32or64(b'L', b'Q'),), 'VTCompressionSessionGetPixelBufferPool': (b'^{__CVPixelBufferPool=}^{OpaqueVTCompressionSession=}',), 'VTFrameSiloCallFunctionForEachSampleBuffer': (sel32or64(b'l^{OpaqueVTFrameSilo=}{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}^v^?', b'i^{OpaqueVTFrameSilo=}{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}^v^?'), '', {'arguments': {3: {'callable': {'retval': {'type': b'i'}, 'arguments': {0: {'type': b'^v'}, 1: {'type': b'^{opaqueCMSampleBuffer=}'}}}, 'callable_retained': False}}}), 'VTDecompressionSessionCopyBlackPixelBuffer': (sel32or64(b'l^{OpaqueVTDecompressionSession=}^^{__CVBuffer=}', b'i^{OpaqueVTDecompressionSession=}^^{__CVBuffer=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {1: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTDecompressionSessionCanAcceptFormatDescription': (b'Z^{OpaqueVTDecompressionSession=}^{opaqueCMFormatDescription=}',), 'VTCopyVideoEncoderList': (sel32or64(b'l^{__CFDictionary=}^^{__CFArray=}', b'i^{__CFDictionary=}^^{__CFArray=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {1: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTMultiPassStorageCreate': (sel32or64(b'l^{__CFAllocator=}^{__CFURL=}{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}^{__CFDictionary=}^^{OpaqueVTMultiPassStorage=}', b'i^{__CFAllocator=}^{__CFURL=}{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}^{__CFDictionary=}^^{OpaqueVTMultiPassStorage=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {4: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTDecompressionSessionGetTypeID': (sel32or64(b'L', b'Q'),), 'VTCompressionSessionBeginPass': (sel32or64(b'l^{OpaqueVTCompressionSession=}I^I', b'i^{OpaqueVTCompressionSession=}I^I'),), 'VTSessionSetProperties': (sel32or64(b'l@^{__CFDictionary=}', b'i@^{__CFDictionary=}'),), 'VTDecompressionSessionWaitForAsynchronousFrames': (sel32or64(b'l^{OpaqueVTDecompressionSession=}', b'i^{OpaqueVTDecompressionSession=}'),), 'VTFrameSiloSetTimeRangesForNextPass': (sel32or64(b'l^{OpaqueVTFrameSilo=}l^{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}', b'i^{OpaqueVTFrameSilo=}q^{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}'), '', {'arguments': {2: {'c_array_length_in_arg': 1, 'type_modifier': 'n'}}}), 'VTRegisterProfessionalVideoWorkflowVideoDecoders': (b'v',), 'VTPixelTransferSessionInvalidate': (b'v^{OpaqueVTPixelTransferSession=}',), 'VTDecompressionSessionDecodeFrameWithOutputHandler': (sel32or64(b'l^{OpaqueVTDecompressionSession=}^{opaqueCMSampleBuffer=}I^L@?', b'i^{OpaqueVTDecompressionSession=}^{opaqueCMSampleBuffer=}I^I@?'), '', {'arguments': {3: {'type_modifier': 'o'}, 4: {'callable': {'retval': {'type': b'v'}, 'arguments': {0: {'type': '^v'}, 1: {'type': 'i'}, 2: {'type': 'I'}, 3: {'type': '^{__CVBuffer=}'}, 4: {'type': '{_CMTime=qiIq}'}, 5: {'type': '{_CMTime=qiIq}'}}}}}}), 'VTCompressionSessionEndPass': (sel32or64(b'l^{OpaqueVTCompressionSession=}^Z^I', b'i^{OpaqueVTCompressionSession=}^Z^I'), '', {'arguments': {1: {'type_modifier': 'o'}}}), 'VTCompressionSessionEncodeFrame': (sel32or64(b'l^{OpaqueVTCompressionSession=}^{__CVBuffer=}{_CMTime=qiIq}{_CMTime=qiIq}^{__CFDictionary=}^v^L', b'i^{OpaqueVTCompressionSession=}^{__CVBuffer=}{_CMTime=qiIq}{_CMTime=qiIq}^{__CFDictionary=}^v^I'), '', {'arguments': {6: {'type_modifier': 'o'}}}), 'VTFrameSiloCreate': (sel32or64(b'l^{__CFAllocator=}^{__CFURL=}{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}^{__CFDictionary=}^^{OpaqueVTFrameSilo=}', b'i^{__CFAllocator=}^{__CFURL=}{_CMTimeRange={_CMTime=qiIq}{_CMTime=qiIq}}^{__CFDictionary=}^^{OpaqueVTFrameSilo=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {4: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTCompressionSessionCreate': (sel32or64(b'l^{__CFAllocator=}iiL^{__CFDictionary=}^{__CFDictionary=}^{__CFAllocator=}^?^v^^{OpaqueVTCompressionSession=}', b'i^{__CFAllocator=}iiI^{__CFDictionary=}^{__CFDictionary=}^{__CFAllocator=}^?^v^^{OpaqueVTCompressionSession=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {9: {'already_cfretained': True, 'type_modifier': 'o'}, 7: {'callable': {'retval': {'type': b'v'}, 'arguments': {0: {'type': b'^v'}, 1: {'type': b'^v'}, 2: {'type': b'i'}, 3: {'type': b'I'}, 4: {'type': b'^{opaqueCMSampleBuffer=}'}}}}}}), 'VTCopySupportedPropertyDictionaryForEncoder': (sel32or64(b'liiL^{__CFDictionary=}^^{__CFString=}^^{__CFDictionary=}', b'iiiI^{__CFDictionary=}^^{__CFString=}^^{__CFDictionary=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {4: {'already_cfretained': True, 'type_modifier': 'o'}, 5: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTFrameSiloGetTypeID': (sel32or64(b'L', b'Q'),), 'VTSessionCopySerializableProperties': (sel32or64(b'l@^{__CFAllocator=}^^{__CFDictionary=}', b'i@^{__CFAllocator=}^^{__CFDictionary=}'), '', {'retval': {'already_cfretained': True}, 'arguments': {2: {'already_cfretained': True, 'type_modifier': 'o'}}}), 'VTDecompressionSessionInvalidate': (b'v^{OpaqueVTDecompressionSession=}',)} aliases = {'VT_SUPPORT_COLORSYNC_PIXEL_TRANSFER': 'COREMEDIA_TRUE'} cftypes=[('VTPixelTransferSessionRef', b'^{OpaqueVTPixelTransferSession=}', ':VTPixelTransferSessionGetTypeID', None), ('VTDecompressionSessionRef', b'^{OpaqueVTDecompressionSession=}', ':VTDecompressionSessionGetTypeID', None), ('VTFrameSiloRef', b'^{OpaqueVTFrameSilo=}', ':VTFrameSiloGetTypeID', None), ('VTSessionRef', b'^{OpaqueVTSession=}', ':VTSessionGetTypeID', None), ('VTMultiPassStorageRef', b'^{OpaqueVTMultiPassStorage=}', ':VTMultiPassStorageGetTypeID', None)] expressions = {} # END OF FILE

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7e289d8467590acbc33df40d1c22d18b21da79ab

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py

Python

segnlp/pretrained_features/__init__.py

AxlAlm/SegNLP

89b8d077952397dfcea089376b373b117bcf6a65

[ "Apache-2.0" ]

1

2021-01-21T17:16:55.000Z

segnlp/pretrained_features/__init__.py

AxlAlm/SegNLP

89b8d077952397dfcea089376b373b117bcf6a65

[ "Apache-2.0" ]

2

2021-01-24T20:07:54.000Z

2021-01-26T16:59:28.000Z

segnlp/pretrained_features/__init__.py

AxlAlm/SegNLP

89b8d077952397dfcea089376b373b117bcf6a65

[ "Apache-2.0" ]

1

2021-01-21T17:16:57.000Z

from .bow import BOW from .flair_embeddings import FlairEmbeddings from .flair_embeddings import GloveEmbeddings from .flair_embeddings import BertEmbeddings from .dummy import DummyFeature from .elmo import ELMoEmbeddings

28

45

0.861607

27

224

7.037037

0.444444

0.142105

0.3

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0

0.111607

224

8

46

28

0.954774

0

1

0

true

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1

0

7

7e783ab793dc8a36abf3c0f01449b07ebe2c101f

7,137

py

Python

models.py

MILE-IISc/CRNN

88e7350f53a972b1cabc65aeb8c8b151cfd92f0e

[ "MIT" ]

null

models.py

MILE-IISc/CRNN

88e7350f53a972b1cabc65aeb8c8b151cfd92f0e

[ "MIT" ]

null

models.py

MILE-IISc/CRNN

88e7350f53a972b1cabc65aeb8c8b151cfd92f0e

[ "MIT" ]

null

import numpy as np from tensorflow.keras.layers import Input, Conv2D, BatchNormalization, MaxPooling2D, Reshape, Dense, LSTM, add, concatenate, Dropout, Lambda, Flatten from tensorflow.keras.models import Model import tensorflow.keras.backend as K from STN.spatial_transformer import SpatialTransformer def loc_net(input_shape): b = np.zeros((2, 3), dtype='float32') b[0, 0] = 1 b[1, 1] = 1 w = np.zeros((64, 6), dtype='float32') weights = [w, b.flatten()] loc_input = Input(input_shape) loc_conv_1 = Conv2D(16, (5, 5), padding='same', activation='relu')(loc_input) loc_conv_2 = Conv2D(32, (5, 5), padding='same', activation='relu')(loc_conv_1) loc_fla = Flatten()(loc_conv_2) loc_fc_1 = Dense(64, activation='relu')(loc_fla) loc_fc_2 = Dense(6, weights=weights)(loc_fc_1) output = Model(inputs=loc_input, outputs=loc_fc_2) return output def ctc_lambda_func(args): iy_pred, ilabels, iinput_length, ilabel_length = args # the 2 is critical here since the first couple outputs of the RNN # tend to be garbage: iy_pred = iy_pred[:, 2:, :] # no such influence return K.ctc_batch_cost(ilabels, iy_pred, iinput_length, ilabel_length) def CRNN_STN(cfg): inputs = Input((cfg.width, cfg.height, cfg.nb_channels)) c_1 = Conv2D(cfg.conv_filter_size[0], (3, 3), activation='relu', padding='same', name='conv_1')(inputs) c_2 = Conv2D(cfg.conv_filter_size[1], (3, 3), activation='relu', padding='same', name='conv_2')(c_1) c_3 = Conv2D(cfg.conv_filter_size[2], (3, 3), activation='relu', padding='same', name='conv_3')(c_2) bn_3 = BatchNormalization(name='bn_3')(c_3) p_3 = MaxPooling2D(pool_size=(2, 2), name='maxpool_3')(bn_3) c_4 = Conv2D(cfg.conv_filter_size[3], (3, 3), activation='relu', padding='same', name='conv_4')(p_3) c_5 = Conv2D(cfg.conv_filter_size[4], (3, 3), activation='relu', padding='same', name='conv_5')(c_4) bn_5 = BatchNormalization(name='bn_5')(c_5) p_5 = MaxPooling2D(pool_size=(2, 2), name='maxpool_5')(bn_5) c_6 = Conv2D(cfg.conv_filter_size[5], (3, 3), activation='relu', padding='same', name='conv_6')(p_5) c_7 = Conv2D(cfg.conv_filter_size[6], (3, 3), activation='relu', padding='same', name='conv_7')(c_6) bn_7 = BatchNormalization(name='bn_7')(c_7) bn_7_shape = bn_7.get_shape() loc_input_shape = (bn_7_shape[1].value, bn_7_shape[2].value, bn_7_shape[3].value) stn = SpatialTransformer(localization_net=loc_net(loc_input_shape), output_size=(loc_input_shape[0], loc_input_shape[1]))(bn_7) reshape = Reshape(target_shape=(int(bn_7_shape[1]), int(bn_7_shape[2] * bn_7_shape[3])), name='reshape')(stn) fc_9 = Dense(cfg.lstm_nb_units[0], activation='relu', name='fc_9')(reshape) lstm_10 = LSTM(cfg.lstm_nb_units[0], kernel_initializer="he_normal", return_sequences=True, name='lstm_10')(fc_9) lstm_10_back = LSTM(cfg.lstm_nb_units[0], kernel_initializer="he_normal", go_backwards=True, return_sequences=True, name='lstm_10_back')(fc_9) lstm_10_add = add([lstm_10, lstm_10_back]) lstm_11 = LSTM(cfg.lstm_nb_units[1], kernel_initializer="he_normal", return_sequences=True, name='lstm_11')(lstm_10_add) lstm_11_back = LSTM(cfg.lstm_nb_units[1], kernel_initializer="he_normal", go_backwards=True, return_sequences=True, name='lstm_11_back')(lstm_10_add) lstm_11_concat = concatenate([lstm_11, lstm_11_back]) do_11 = Dropout(cfg.dropout_rate, name='dropout')(lstm_11_concat) cfg.characters = list(); for line in open(cfg.characters_file): line = line.rstrip('\n'); cfg.characters.append(line); fc_12 = Dense(len(cfg.characters), kernel_initializer='he_normal', activation='softmax', name='fc_12')(do_11) prediction_model = Model(inputs=inputs, outputs=fc_12) labels = Input(name='labels', shape=[cfg.label_len], dtype='float32') input_length = Input(name='input_length', shape=[1], dtype='int64') label_length = Input(name='label_length', shape=[1], dtype='int64') ctc_loss = Lambda(ctc_lambda_func, output_shape=(1,), name='ctc')([fc_12, labels, input_length, label_length]) training_model = Model(inputs=[inputs, labels, input_length, label_length], outputs=[ctc_loss]) return training_model, prediction_model def CRNN(cfg): inputs = Input((cfg.width, cfg.height, cfg.nb_channels)) c_1 = Conv2D(cfg.conv_filter_size[0], (3, 3), activation='relu', padding='same', name='conv_1')(inputs) c_2 = Conv2D(cfg.conv_filter_size[1], (3, 3), activation='relu', padding='same', name='conv_2')(c_1) c_3 = Conv2D(cfg.conv_filter_size[2], (3, 3), activation='relu', padding='same', name='conv_3')(c_2) bn_3 = BatchNormalization(name='bn_3')(c_3) p_3 = MaxPooling2D(pool_size=(2, 2), name='maxpool_3')(bn_3) c_4 = Conv2D(cfg.conv_filter_size[3], (3, 3), activation='relu', padding='same', name='conv_4')(p_3) c_5 = Conv2D(cfg.conv_filter_size[4], (3, 3), activation='relu', padding='same', name='conv_5')(c_4) bn_5 = BatchNormalization(name='bn_5')(c_5) p_5 = MaxPooling2D(pool_size=(2, 2), name='maxpool_5')(bn_5) c_6 = Conv2D(cfg.conv_filter_size[5], (3, 3), activation='relu', padding='same', name='conv_6')(p_5) c_7 = Conv2D(cfg.conv_filter_size[6], (3, 3), activation='relu', padding='same', name='conv_7')(c_6) bn_7 = BatchNormalization(name='bn_7')(c_7) bn_7_shape = bn_7.get_shape() reshape = Reshape(target_shape=(int(bn_7_shape[1]), int(bn_7_shape[2] * bn_7_shape[3])), name='reshape')(bn_7) fc_9 = Dense(cfg.lstm_nb_units[0], activation='relu', name='fc_9')(reshape) lstm_10 = LSTM(cfg.lstm_nb_units[0], kernel_initializer="he_normal", return_sequences=True, name='lstm_10')(fc_9) lstm_10_back = LSTM(cfg.lstm_nb_units[0], kernel_initializer="he_normal", go_backwards=True, return_sequences=True, name='lstm_10_back')(fc_9) lstm_10_add = add([lstm_10, lstm_10_back]) lstm_11 = LSTM(cfg.lstm_nb_units[1], kernel_initializer="he_normal", return_sequences=True, name='lstm_11')(lstm_10_add) lstm_11_back = LSTM(cfg.lstm_nb_units[1], kernel_initializer="he_normal", go_backwards=True, return_sequences=True, name='lstm_11_back')(lstm_10_add) lstm_11_concat = concatenate([lstm_11, lstm_11_back]) do_11 = Dropout(cfg.dropout_rate, name='dropout')(lstm_11_concat) cfg.characters = list(); for line in open(cfg.characters_file): line = line.rstrip('\n'); cfg.characters.append(line); fc_12 = Dense(len(cfg.characters), kernel_initializer='he_normal', activation='softmax', name='fc_12')(do_11) prediction_model = Model(inputs=inputs, outputs=fc_12) labels = Input(name='labels', shape=[cfg.label_len], dtype='float32') input_length = Input(name='input_length', shape=[1], dtype='int64') label_length = Input(name='label_length', shape=[1], dtype='int64') ctc_loss = Lambda(ctc_lambda_func, output_shape=(1,), name='ctc')([fc_12, labels, input_length, label_length]) training_model = Model(inputs=[inputs, labels, input_length, label_length], outputs=[ctc_loss]) return training_model, prediction_model

49.909091

153

0.702396

1,157

7,137

4.029386

0.121867

0.057057

0.039039

0.057057

0.800944

0.788074

0

0.053678

0.133389

7,137

142

154

50.260563

0.700081

0.014292

0

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false

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0.051546

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0

null

0

1

0

1

0

null

0

7

0e1a7daa3346d7ebf50def2f78637c7e9f3ca2de

145

py

Python

satchmo/upsell/__init__.py

sankroh/satchmo

e48df0c2a4be4ce14785d0a5d6dd1e516c57a838

[ "BSD-3-Clause" ]

1

2016-05-09T12:21:04.000Z

satchmo/upsell/__init__.py

sankroh/satchmo

e48df0c2a4be4ce14785d0a5d6dd1e516c57a838

[ "BSD-3-Clause" ]

null

satchmo/upsell/__init__.py

sankroh/satchmo

e48df0c2a4be4ce14785d0a5d6dd1e516c57a838

[ "BSD-3-Clause" ]

null

from satchmo.shop.signals import satchmo_cart_add_complete import views satchmo_cart_add_complete.connect(views.cart_add_listener, sender=None)

29

71

0.882759

22

145

5.454545

0.590909

0.175

0.233333

0.366667

0

0.062069

145

4

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36.25

0.882353

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true

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null

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1

0

1

0

7

0e26d71432e605cd7c3151ffb8e0db8d90cb19f7

219

py

Python

portfolio/mainapp/admin.py

PlagueEvgeny/Portfolio

aa7199fe23a10d3a8ad1e3307dbdbd50f9e150c3

[ "MIT" ]

null

portfolio/mainapp/admin.py

PlagueEvgeny/Portfolio

aa7199fe23a10d3a8ad1e3307dbdbd50f9e150c3

[ "MIT" ]

null

portfolio/mainapp/admin.py

PlagueEvgeny/Portfolio

aa7199fe23a10d3a8ad1e3307dbdbd50f9e150c3

[ "MIT" ]

null

from django.contrib import admin from mainapp.models import Hello, About, Portfolio, Image, Certificate, Facts, Tools, UseTools admin.site.register([Hello, About, Portfolio, Image, Certificate, Facts, Tools, UseTools])

54.75

94

0.794521

28

219

6.214286

0.607143

0.114943

0.218391

0.275862

0.609195

0

0.105023

219

4

95

54.75

0.887755

0

1

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true

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0.666667

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null

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null

0

1

0

1

0

1

0

7

0e468d21267a052e0c0f3fea765b8ae71dcbce0e

239

py

Python

omnipath/_core/requests/__init__.py

TheAustinator/omnipath

c0d61216e3a7d95cdb098ac025f08a9b09e0f8fe

[ "MIT" ]

13

2020-12-02T15:47:54.000Z

2022-03-08T02:39:55.000Z

omnipath/_core/requests/__init__.py

TheAustinator/omnipath

c0d61216e3a7d95cdb098ac025f08a9b09e0f8fe

[ "MIT" ]

15

2020-11-10T13:03:09.000Z

2022-03-29T08:51:38.000Z

omnipath/_core/requests/__init__.py

michalk8/omnipath

014ddf046d07ad16ce722e2280b39796598ca9a8

[ "MIT" ]

2

2020-11-06T23:08:19.000Z

2022-03-28T21:46:33.000Z

from omnipath._core.requests._request import Enzsub, SignedPTMs from omnipath._core.requests._complexes import Complexes from omnipath._core.requests._intercell import Intercell from omnipath._core.requests._annotations import Annotations

47.8

63

0.874477

29

239

6.931034

0.37931

0.238806

0.318408

0.477612

0

0.07113

239

4

64

59.75

0.905405

0

1

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true

0

1

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1

0

1

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null

1

0

1

0

null

0

1

0

1

0

1

0

8

7ebf5c80a509dceef9b257b6bf7c064e4b28ec75

148

py

Python

utils/__init__.py

gaoliyao/Replica_Exchange_Stochastic_Gradient_MCMC

609f803ca334b21820dc020c16ad8113363a03e2

[ "MIT" ]

21

2020-06-30T01:14:45.000Z

2022-03-31T08:03:17.000Z

utils/__init__.py

gaoliyao/Replica_Exchange_Stochastic_Gradient_MCMC

609f803ca334b21820dc020c16ad8113363a03e2

[ "MIT" ]

null

utils/__init__.py

gaoliyao/Replica_Exchange_Stochastic_Gradient_MCMC

609f803ca334b21820dc020c16ad8113363a03e2

[ "MIT" ]

2

2020-11-02T22:06:10.000Z

2021-07-17T23:35:21.000Z

#from .misc import Plot from .data_manipulation import * from .data_operation import * from .chains_operation import * from .pytorch_label import *

24.666667

32

0.797297

20

148

5.7

0.5

0.263158

0.333333

0

0.135135

148

5

33

29.6

0.890625

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0

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true

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null

0

1

0

1

0

1

0

7

7d13fa7bef82bef71e888e9436d314c7b7b87927

76,258

py

Python

recommenders/RM_start_of_studies.py

virtUOS/siddata_backend

e2e09fbb51e650ede2e743ad0a1169c71c064494

[ "MIT" ]

null

recommenders/RM_start_of_studies.py

virtUOS/siddata_backend

e2e09fbb51e650ede2e743ad0a1169c71c064494

[ "MIT" ]

4

2022-03-28T08:10:46.000Z

2022-03-28T09:29:04.000Z

recommenders/RM_start_of_studies.py

virtUOS/siddata_backend

e2e09fbb51e650ede2e743ad0a1169c71c064494

[ "MIT" ]

null

from backend import models from recommenders.RM_BASE import RM_BASE import pandas as pd import os class RM_start_of_studies(RM_BASE): """ Recommender that contains - initial activites (guided tour) - teaser activities that introduce all recommenders - salient or emergent activities In Addition the frontend adds a tile view of all recommenders available. """ def __init__(self): # this magic line of code lets our recommender inherit all attributes and methods from the baseclass. super().__init__() # This name should be unique and appears in the Stud.IP GUI. self.NAME = "Orientierung zum Studienstart" # The description text summarizes the functionality. It is shown in teaser activity and tile view, self.DESCRIPTION = "Hilfe in der Studieneingangsphase." # This text is displayed in Teaser Activities self.TEASER_TEXT = "Unter Orientierung zum Studienstart kannst du dich über verschiedene Themen rund um " \ "den Studienstart informieren. Außerdem werden dir auf Basis deiner Themenwünsche " \ "konkrete Workshops und Trainings für den Studieneinstieg empfohlen." # If set to False, the recommender will not appear in the GUI or the DB self.ACTIVE = True # Image is shown in teaser activity self.IMAGE = "professions.png" # determines arrangement in Frontend self.ORDER = 1 # This string tells the user which data is required for this recommender self.DATA_INFO = "Diese Funktion speichert diejenigen Daten, die du aktiv eingibst und nutze Daten zu deiner Uni um passgenaue Empfehlungen zu geben." # Reference to the database object, can be used as value vor recommender attribute in goals. self.recommender = models.Recommender.objects.get_or_create( name=self.get_name(), description=self.DESCRIPTION, classname=self.__class__.__name__, image=self.IMAGE, order=self.ORDER, data_info=self.DATA_INFO, )[0] self.dirname = os.path.dirname(__file__) self.filename = os.path.join(self.dirname, 'recommender_data/start_of_studies_data.csv') self.course_df = pd.read_csv(self.filename, delimiter=',') def initialize_templates(self): """ Creates and updates all templates of this recommender Is executed at server startup """ super().initialize_templates() order = 1 # create template for general information question general_information_question = models.Question.objects.create( question_text="Der Studienstart ist mit verschiedenen Herausforderungen und Chancen verbunden. Hier " "findest du passende Informationen und Unterstützungsangebote:", answer_type="checkbox", selection_answers=["Studienverlauf, Prüfungen, Rückmeldung", "Literatur ausleihen", "Raum für Gruppenarbeiten", "Raum zum ruhigen Arbeiten", "Studium und Familie", "Sport treiben", "Eine weitere Sprache lernen", "Auslandssemester", "Probleme im Studium", "Technische Fragen und Probleme", "Finanzierung meines Studiums", "Wohnen", "Was gibt es heute zum Mittag?", ] ) models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("general_information_question"), defaults={ "title": "Generelle Infos zum Studium", "description": "Orientierung zum Studienstart", "type": "question", "status": "template", "question": general_information_question, "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 # create template for general recommendations question general_recommendation_question = models.Question.objects.create( question_text="Wusstest du schon: deine Universität bietet neben den Vorlesungen deines Studiengangs auch Veranstaltungen an, die dich in deinem Studium " "unterstützen sollen. Welche Themen interessieren dich? Wenn du deine Auswahl getroffen " "hast, bekommst du konkrete Veranstaltungen vorgeschlagen.", answer_type="checkbox", selection_answers=["Wissenschaftliches Arbeiten", "Lernen & Gedächtnis", "Prüfungsvorbereitung", "Präsentation & Kommunikation", "Projektmanagement", "Selbst- und Zeitmanagement", "Gesund studieren", "Sport & Bewegung", "Literaturverwaltung", "Schreibtraining", ] ) models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("general_recommendation_question"), defaults={ "title": "Persönliche Weiterentwicklung", "description": "Orientierung zum Studienstart", "type": "question", "status": "template", "question": general_recommendation_question, "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 # create course recommendation templates for index in self.course_df.index: models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("course_recommendation_{}".format(index)), defaults={ "title": "Veranstaltung zum Thema '{}'".format(self.course_df["Categories"].iloc[index]), "description": "<p><strong>Volltreffer! Wir haben eine Kursempfehlung für dich:</strong></p>" "<ul>" "<li>Veranstaltung: {}</li> " "<li>Beschreibung: {}</li> " "<li>Zeit: {}</li> " "<li>Ort: {}</li> " "<li>Link: <a href='{}' target='_blank'>Hier geht es zum Kurs.</a></li>" "</ul>".format(self.course_df["Course"].iloc[index], self.course_df["Description"].iloc[index], self.course_df["Date"].iloc[index], self.course_df["Location"].iloc[index], self.course_df["Registration"].iloc[index]), "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, # changed all order attributes to unique values in DataFrame "order": self.course_df["Order"].iloc[index], } ) # order count up not necessary anymore in for-loop # order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("library_OS"), defaults={ "title": "Universitätsbibliothek", "description": "Wenn du dir Literatur ausleihen möchtest, kann dir die Bibliothek deiner Universität" "helfen. <a href='https://www.ub.uni-osnabrueck.de/startseite.html' target='_blank'>Hier geht es zur " "Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("library_UB"), defaults={ "title": "Universitätsbibliothek", "description": "Wenn du dir Literatur ausleihen möchtest, kann dir die Bibliothek deiner Universität" "helfen. <a href='https://www.suub.uni-bremen.de/' target='_blank'>Hier geht es zur " "Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("library_LUH"), defaults={ "title": "Universitätsbibliothek", "description": "Wenn du dir Literatur ausleihen möchtest, kann dir die Bibliothek deiner Universität" "helfen. <a href='https://www.tib.eu/de/' target='_blank'>Hier geht es zur " "Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("rooms_OS"), defaults={ "title": "Lern- und Gruppenarbeitsräume", "description": "Wenn du einen ruhigen Platz zum Arbeiten suchst oder einen Ort für Gruppenarbeiten" " benötigst, kannst du dir hier einen Raum buchen. " "<a href='https://www.ub.uni-osnabrueck.de/startseite.html'" "target='_blank'>Hier geht es zur " "Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("rooms_UB"), defaults={ "title": "Lern- und Gruppenarbeitsräume", "description": "Wenn du einen ruhigen Platz zum Arbeiten suchst oder einen Ort für Gruppenarbeiten" " benötigst,kannst du dir hier einen Raum buchen. " "<a href='https://www.uni-bremen.de/universitaet/campus/lernraeume'" "target='_blank'>Hier geht es zur " "Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("rooms_LUH"), defaults={ "title": "Lern- und Gruppenarbeitsräume", "description": "Wenn du einen ruhigen Platz zum Arbeiten suchst oder einen Ort für Gruppenarbeiten" " benötigst,kannst du dir hier einen Raum buchen. " "<a href='https://www.zqs.uni-hannover.de/de/qs/lernraum/'" "target='_blank'>Hier geht es zur " "Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("problems_OS"), defaults={ "title": "Wenn es mal nicht so läuft...", "description": "Schwierige Phasen erlebt jeder einmal, im Studium und im Privaten." " Nicht immer lassen sich diese Hindernisse schnell und aus eigener Kraft überwinden." " Wenn du in einer solchen Phase bist, scheue dich nicht Hilfe anzunehmen. " "<a href='https://www.studentenwerk-osnabrueck.de/de/beratung/" "psychologische-beratung.html' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("problems_UB"), defaults={ "title": "Wenn es mal nicht so läuft...", "description": "Schwierige Phasen erlebt jeder einmal, im Studium und im Privaten." " Nicht immer lassen sich diese Hindernisse schnell und aus eigener Kraft überwinden." " Wenn du in einer solchen Phase bist, scheue dich nicht Hilfe anzunehmen. " "<a href='https://www.stw-bremen.de/de/beratung/psychologische-beratung'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("problems_LUH"), defaults={ "title": "Wenn es mal nicht so läuft...", "description": "Schwierige Phasen erlebt jeder einmal, im Studium und im Privaten." " Nicht immer lassen sich diese Hindernisse schnell und aus eigener Kraft überwinden." " Wenn du in einer solchen Phase bist, scheue dich nicht Hilfe anzunehmen. " "<a href='https://www.ptb.uni-hannover.de/'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("language_OS"), defaults={ "title": "Sprachen lernen", "description": "Möchtest du eine neue Fremdsprache lernen oder deine Kenntnisse auffrischen?" " Das Fremdsprachenangebot an Grund-, Aufbau- und Vertiefungskursen findest du hier: " "<a href='https://www.uni-osnabrueck.de/universitaet/organisation/" "zentrale-einrichtungen/sprachenzentrum/'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("language_UB"), defaults={ "title": "Sprachen lernen", "description": "Möchtest du eine neue Fremdsprache lernen oder deine Kenntnisse auffrischen?" " Das Fremdsprachenangebot an Grund-, Aufbau- und Vertiefungskursen findest du hier: " "<a href='https://www.fremdsprachenzentrum-bremen.de/'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("language_LUH"), defaults={ "title": "Sprachen lernen", "description": "Möchtest du eine neue Fremdsprache lernen oder deine Kenntnisse auffrischen?" " Das Fremdsprachenangebot an Grund-, Aufbau- und Vertiefungskursen findest du hier: " "<a href='https://www.llc.uni-hannover.de/'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("sports_OS"), defaults={ "title": "Sportangebote", "description": "Jedes Semester stehen dir zahlreiche Sportangebote im Rahmen des Hochschulsports zur " "Verfügung. <a href='https://www.zfh.uni-osnabrueck.de/startseite.html'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("sports_UB"), defaults={ "title": "Sportangebote", "description": "Jedes Semester stehen dir zahlreiche Sportangebote im Rahmen des Hochschulsports zur " "Verfügung. <a href='https://www.uni-bremen.de/hospo'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("sports_LUH"), defaults={ "title": "Sportangebote", "description": "Jedes Semester stehen dir zahlreiche Sportangebote im Rahmen des Hochschulsports zur " "Verfügung. <a href='https://www.hochschulsport-hannover.de/'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("international_office_OS"), defaults={ "title": "International Office", "description": "Wenn du dich für einen Studienaufenthalt im Ausland interessiert, erhältst du hier " "Informationen und Unterstützung bei der Planung. " "<a href='https://www.uni-osnabrueck.de/universitaet/organisation/studentisches/" "international-office/' target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("international_office_UB"), defaults={ "title": "International Office", "description": "Wenn du dich für einen Studienaufenthalt im Ausland interessiert, erhältst du hier " "Informationen und Unterstützung bei der Planung. " "<a href='https://www.uni-bremen.de/universitaet/profil/international/" "international-office' target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("international_office_LUH"), defaults={ "title": "International Office", "description": "Wenn du dich für einen Studienaufenthalt im Ausland interessiert, erhältst du hier " "Informationen und Unterstützung bei der Planung. " "<a href='https://www.uni-hannover.de/de/universitaet/internationales/'" "_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("rechenzentrum_OS"), defaults={ "title": "Rechenzentrum", "description": "Bei technischen Fragen (z.B. zu deinem Uni-Account, zum WLAN) findest du hier " "Informationen und Hilfestellungen." "<ul> <li><a href='https://www.rz.uni-osnabrueck.de/' target='_blank'>" "Hier geht es zur Website des Rechenzentrums.</a></li>" "<li><a href='https://www.rz.uni-osnabrueck.de/dienste/leitfaden/" "leitfaden_studierende.html' target='_blank'>Hier geht es zu einem Leitfaden für " "Erstsemester</a></li></ul>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("rechenzentrum_UB"), defaults={ "title": "Rechenzentrum", "description": "Bei technischen Fragen (z.B. zu deinem Uni-Account, zum WLAN) findest du hier " "Informationen und Hilfestellungen. " "<a href='https://www.uni-bremen.de/zfn' target='_blank'>" "Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("rechenzentrum_LUH"), defaults={ "title": "Rechenzentrum", "description": "Bei technischen Fragen (z.B. zu deinem Uni-Account, zum WLAN) findest du hier " "Informationen und Hilfestellungen. " "<a href='https://www.luis.uni-hannover.de/' target='_blank'>" "Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("sekretariat_OS"), defaults={ "title": "Studierendensekretariat", "description": "Das Studierendensekretariat ist zuständig für die den Studierendenstatus betreffenden " "administrativen Vorgänge während der gesamten Studienzeit z.B. der Rückmeldung, der " "Campuscard oder der Beurlaubung." "<ul> <li><a href='https://www.uni-osnabrueck.de/universitaet/organisation/" "studentisches/studierenden-information-osnabrueck-studios/'" " target='_blank'>Hier geht es zur Website der Studierenden Information Osnabrück." "</a></li>" "<li><a href='https://www.uni-osnabrueck.de/universitaet/organisation/" "zentrale-verwaltung/studentische-angelegenheiten/studierendenservice/'" " target='_blank'>Hier geht es zur Website vom Studierendenservice.</a></li></ul>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("sekretariat_UB"), defaults={ "title": "Studierendensekretariat", "description": "Das Studierendensekretariat ist zuständig für die den Studierendenstatus betreffenden " "administrativen Vorgänge während der gesamten Studienzeit z.B. der Rückmeldung, der " "Campuscard oder der Beurlaubung. " "<a href='https://www.uni-bremen.de/sfs' target='_blank'> Hier geht es zur Website.", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("sekretariat_LUH"), defaults={ "title": "Studierendensekretariat", "description": "Das Studierendensekretariat ist zuständig für die den Studierendenstatus betreffenden " "administrativen Vorgänge während der gesamten Studienzeit z.B. der Rückmeldung, der " "Campuscard oder der Beurlaubung. " "<a href='https://www.uni-hannover.de/de/studium/beratung-und-hilfe/servicecenter/'" " target='_blank'> Hier geht es zur Website.", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("studienberatung_OS"), defaults={ "title": "Studienberatung", "description": "Die Studienberatung ist Anlaufstelle bei Fragen und Anliegen," " die im Zusammenhang mit der Wahl oder Durchführung eines Studiums auftreten. " "<a href='https://www.zsb-os.de/' target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("studienberatung_UB"), defaults={ "title": "Studienberatung", "description": "Die Studienberatung ist Anlaufstelle bei Fragen und Anliegen," " die im Zusammenhang mit der Wahl oder Durchführung eines Studiums auftreten. " "<a href='https://www.uni-bremen.de/zsb' target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("studienberatung_LUH"), defaults={ "title": "Studienberatung", "description": "Die Studienberatung ist Anlaufstelle bei Fragen und Anliegen," " die im Zusammenhang mit der Wahl oder Durchführung eines Studiums auftreten. " "<a href='https://www.uni-hannover.de/de/universitaet/organisation/" "dezernate/dezernat-6/sg-63-zentrale-studienberatung/'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("funding_OS"), defaults={ "title": "Finanzierung und Förderung", "description": "Hier findest du Informationen rund um die Finanzierung deines Studiums z.B. " "zum BAföG oder zu Stipendienprogrammen:" "<ul><li><a href='https://www.studentenwerk-osnabrueck.de/de/finanzen/bafoeg.html' " "target='_blank'>BAföG-Abteilung des Studentenwerks</a></li>" "<li><a href='https://www.uni-osnabrueck.de/studieninteressierte/" "stipendien-und-foerderung/'target='_blank'>Stipendien & Förderung</a></li></ul>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("funding_UB"), defaults={ "title": "Finanzierung und Förderung", "description": "Hier findest du Informationen rund um die Finanzierung deines Studiums z.B. " "zum BAföG oder zu Stipendienprogrammen:" "<a href='https://www.uni-bremen.de/studium/rund-ums-studium" "studienfinanzierung-und-jobben' target='_blank'>Studienfinanzierung und Jobben</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("funding_LUH"), defaults={ "title": "Finanzierung und Förderung", "description": "Hier findest du Informationen rund um die Finanzierung deines Studiums z.B. " "zum BAföG oder zu Stipendienprogrammen: " "<a href='https://www.uni-hannover.de/de/studium/finanzierung-foerderung/'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("digitization_OS"), defaults={ "title": "Digitalisierung von Studium und Lehre", "description": "Bei Fragen rund um das Thema digitale Medien in Studium und Lehre (z.B. zu Stud.IP) " "findest du hier Informationen und Hilfestellungen: " "<a href='https://www.virtuos.uni-osnabrueck.de/zentrum_fuer_digitale_lehre_campus_" "management_und_hochschuldidaktik.html' target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("digitization_UB"), defaults={ "title": "Digitalisierung von Studium und Lehre", "description": "Bei Fragen rund um das Thema digitale Medien in Studium und Lehre (z.B. zu Stud.IP) " "findest du hier Informationen und Hilfestellungen: " "<a href='https://www.uni-bremen.de/zmml' target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("digitization_LUH"), defaults={ "title": "Digitalisierung von Studium und Lehre", "description": "Bei Fragen rund um das Thema digitale Medien in Studium und Lehre (z.B. zu Stud.IP) " "findest du hier Informationen und Hilfestellungen: " "<a href='https://www.zqs.uni-hannover.de/de/elsa/'" " target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("family_OS"), defaults={ "title": "Studieren mit Familie", "description": "Alle Informationen rund um das Thema Studieren mit Familie (z.B. Kinderbetreuung, " "Pflege von Angehörigen) findest du hier: " "<a href='https://www.uni-osnabrueck.de/universitaet/organisation/familien-service/'" " target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("family_UB"), defaults={ "title": "Studieren mit Familie", "description": "Alle Informationen rund um das Thema Studieren mit Familie (z.B. Kinderbetreuung, " "Pflege von Angehörigen) findest du hier: " "<a href='https://www.uni-bremen.de/familie/studierende'" " target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("family_LUH"), defaults={ "title": "Studieren mit Familie", "description": "Alle Informationen rund um das Thema Studieren mit Familie (z.B. Kinderbetreuung, " "Pflege von Angehörigen) findest du hier: " "<a href='https://www.chancenvielfalt.uni-hannover.de/" "de/angebote/angebote-fuer-familien/'" " target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("asta_OS"), defaults={ "title": "Allgemeiner Studierendenausschuss (AStA)", "description": "Allgemeiner Studierendenausschuss (AStA)" " ist die universitätsweite Interessenvertretung der Studierenden und informiert euch" " über Themen wie Bafög, Semesterticket etc. " "<a href='https://www.asta.uni-osnabrueck.de/' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("asta_UB"), defaults={ "title": "Allgemeiner Studierendenausschuss (AStA)", "description": "Allgemeiner Studierendenausschuss (AStA)" " ist die universitätsweite Interessenvertretung der Studierenden und informiert euch" " über Themen wie Bafög, Semesterticket etc. " "<a href='https://www.asta.uni-bremen.de/' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("asta_LUH"), defaults={ "title": "Allgemeiner Studierendenausschuss (AStA)", "description": "Allgemeiner Studierendenausschuss (AStA)" " ist die universitätsweite Interessenvertretung der Studierenden und informiert euch" " über Themen wie Bafög, Semesterticket etc. " "<a href='https://www.asta-hannover.de/' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("cantine_OS"), defaults={ "title": "Mensa", "description": "Das Studentenwerk bietet dir in seinen Mensen ein vielfältiges Essensangebot. " "<a href='https://www.studentenwerk-osnabrueck.de/de/essen/speiseplaene.html' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("cantine_UB"), defaults={ "title": "Mensa", "description": "Das Studentenwerk bietet dir in seinen Mensen ein vielfältiges Essensangebot. " "<a href='https://www.stw-bremen.de/de/mensa/uni-mensa' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("cantine_LUH"), defaults={ "title": "Mensa", "description": "Das Studentenwerk bietet dir in seinen Mensen ein vielfältiges Essensangebot. " "<a href='https://www.studentenwerk-hannover.de/essen/speiseplaene/alle-mensen-heute/' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("dorms_OS"), defaults={ "title": "Wohnungsangebote", "description": "Guten und preiswerten Wohnraum zu finden ist nicht immer leicht. Hier findest du " "Informationen und Hilfestellungen: " "<a href='https://www.studentenwerk-osnabrueck.de/de/wohnen.html' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("dorms_UB"), defaults={ "title": "Wohnungsangebote", "description": "Guten und preiswerten Wohnraum zu finden ist nicht immer leicht. Hier findest du " "Informationen und Hilfestellungen: " "<a href='https://www.uni-bremen.de/universitaet/campus/wohnen' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("dorms_LUH"), defaults={ "title": "Wohnungsangebote", "description": "Guten und preiswerten Wohnraum zu finden ist nicht immer leicht. Hier findest du " "Informationen und Hilfestellungen: " "<a href='https://www.uni-hannover.de/de/universitaet/campus-und-stadt/wohnen/' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("prüfungsamt_LUH"), defaults={ "title": "Zentrales Prüfungsamt", "description": "Das zentrale Prüfungsamt ist zuständig bei Fragen und Problemen rund um " "Prüfungsangelegenheiten. " "<a href='https://www.uni-hannover.de/de/universitaet/" "organisation/dezernate/dezernat-6/pruefungsamt/'" "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) order += 1 models.ActivityTemplate.objects.update_or_create( template_id=self.get_template_id("prüfungsamt_OS"), defaults={ "title": "Mehr-Fächer-Prüfungsamt PATMOS", "description": "Das Mehrfächer-Prüfungsamt ist zuständig für die Prüfungsadministration des " "fachübergreifenden Bereichs (Kerncurriculum Lehrerbildung" ", allgemeine Schlüsselkompetenzen) " "und für die Erstellung von übergreifenden Bescheinigungen, Leistungsübersichten sowie " "Abschlusszeugnissen in den Mehrfächer-Studiengängen. " "<a href='https://www.uni-osnabrueck.de/universitaet/organisation/zentrale-verwaltung/" "studentische-angelegenheiten/mehrfaecher-pruefungsamt-patmos/' " "target='_blank'>Hier geht es zur Website.</a>", "type": "todo", "status": "template", "feedback_size": 0, "image": self.IMAGE, "order": order, } ) return True def initialize(self, user): """ When a user logs in for the first time, initial activities are generated. :param user: SiddataUser object :return: True if successful """ goal = self.activate_recommender_for_user_and_create_first_goal(user) models.Activity.create_activity_from_template( template_id=self.get_template_id("general_information_question"), goal=goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("general_recommendation_question"), goal=goal, ) return True def process_activity(self, activity): """ :param activity: models.Activity instance modified by Stud.IP plugin :return: True if successful """ # get user api endpoint from incoming activity user_api_endpoint = activity.goal.userrecommender.user.origin.api_endpoint # check if answer value is None if activity.answers is None: activity.answers = [] if "Studienverlauf, Prüfungen, Rückmeldung" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("international_office_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("sekretariat_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("studienberatung_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("prüfungsamt_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("international_office_UB"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("sekretariat_UB"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("studienberatung_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("international_office_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("sekretariat_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("studienberatung_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("prüfungsamt_LUH"), goal=activity.goal, ) if "Literatur ausleihen" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("library_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("library_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("library_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("rooms_LUH"), goal=activity.goal, ) if "Raum für Gruppenarbeiten" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("library_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("rooms_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("library_UB"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("rooms_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("rooms_LUH"), goal=activity.goal, ) if "Raum zum ruhigen Arbeiten" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("library_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("library_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("rooms_LUH"), goal=activity.goal, ) if "Studium und Familie" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("family_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("family_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("family_LUH"), goal=activity.goal, ) if "Sport treiben" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("sports_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("sports_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("sports_LUH"), goal=activity.goal, ) if "eine weitere Sprache lernen" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("language_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("language_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("language_LUH"), goal=activity.goal, ) if "Auslandssemester" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("language_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("international_office_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("language_UB"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("international_office_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("language_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("international_office_LUH"), goal=activity.goal, ) if "Probleme im Studium" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("sekretariat_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("studienberatung_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("problems_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("sekretariat_UB"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("studienberatung_UB"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("problems_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("sekretariat_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("studienberatung_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("problems_LUH"), goal=activity.goal, ) if "Technische Fragen und Probleme" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("rechenzentrum_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("digitization_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("rechenzentrum_UB"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("digitization_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("rechenzentrum_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("digitization_LUH"), goal=activity.goal, ) if "Finanzierung meines Studiums" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("funding_OS"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("asta_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("funding_UB"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("asta_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("funding_LUH"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("asta_LUH"), goal=activity.goal, ) if "Wohnen" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("dorms_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("dorms_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("dorms_LUH"), goal=activity.goal, ) if "Was gibt es heute zu Mittag?" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("cantine_OS"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("cantine_UB"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("cantine_LUH"), goal=activity.goal, ) ### ORANGE TREE ### if "Wissenschaftliches Arbeiten" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_0"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_1"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_2"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_3"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_4"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_22"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_23"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_27"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_0"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_1"), goal=activity.goal, ) if "Lernen & Gedächtnis" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_3"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_4"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_6"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): ... if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_13"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_16"), goal=activity.goal, ) if "Prüfungsvorbereitung" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_6"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_24"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_25"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_26"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): ... if "Präsentation & Kommunikation" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_8"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): ... if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_15"), goal=activity.goal, ) if "Projektmanagement" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): ... if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): ... if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): ... if "Selbst- und Zeitmanagement" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_5"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_6"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_7"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_9"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_10"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_11"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_18"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_19"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_20"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_21"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_12"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_14"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_17"), goal=activity.goal, ) if "Gesund studieren" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_5"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_6"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): ... if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): ... if "Sport & Bewegung" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): ... if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): ... if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): ... if "Literaturverwaltung" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_1"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_2"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): ... if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): ... if "Schreibtraining" in activity.answers: if any(endpoint in user_api_endpoint for endpoint in ["osnabrueck", "localhost"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_0"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["bremen"]): models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_22"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_23"), goal=activity.goal, ) models.Activity.create_activity_from_template( template_id=self.get_template_id("course_recommendation_27"), goal=activity.goal, ) if any(endpoint in user_api_endpoint for endpoint in ["hannover"]): ... return True

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7d31788eaafbf1dd78b1f37d51c85feee1230bbe

13,580

py

Python

lib/python/treadmill/tests/ad/gmsa_test.py

vrautela/treadmill

05e47fa8acdf8bad7af78e737efb26ea6488de82

[ "Apache-2.0" ]

133

2016-09-15T13:36:12.000Z

2021-01-18T06:29:13.000Z

lib/python/treadmill/tests/ad/gmsa_test.py

vrautela/treadmill

05e47fa8acdf8bad7af78e737efb26ea6488de82

[ "Apache-2.0" ]

108

2016-12-28T23:41:27.000Z

2020-03-05T21:20:37.000Z

lib/python/treadmill/tests/ad/gmsa_test.py

evreng/treadmill

05e47fa8acdf8bad7af78e737efb26ea6488de82

[ "Apache-2.0" ]

69

2016-09-23T20:38:58.000Z

2020-11-11T02:31:21.000Z

"""Unit test for treadmill.ad.gmsa. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import io import os import shutil import tempfile import unittest import ldap3 import mock import yaml # Disable W0611: Unused import import treadmill.tests.treadmill_test_skip_windows # pylint: disable=W0611 from treadmill import utils from treadmill.ad import gmsa from treadmill.ad import _servers as servers class HostGroupWatchTest(unittest.TestCase): """Mock test for treadmill.ad.gmsa.HostGroupWatch. """ def setUp(self): self.root = tempfile.mkdtemp() self.placement_dir = os.path.join(self.root, 'placement') self.servers_dir = os.path.join(self.root, 'servers') os.mkdir(self.placement_dir) os.mkdir(self.servers_dir) def tearDown(self): if self.root and os.path.isdir(self.root): shutil.rmtree(self.root) @mock.patch('ldap3.Connection') @mock.patch('treadmill.ad.gmsa._check_ldap3_operation', mock.Mock()) def test_sync(self, connection): """Test gmsa.HostGroupWatch.sync.""" # Access protected module # pylint: disable=W0212 server1_path = os.path.join(self.placement_dir, 'server1.ad.com') os.mkdir(server1_path) utils.touch(os.path.join(server1_path, 'proid1.app#0000000000001')) server2_path = os.path.join(self.placement_dir, 'server2.ad.com') os.mkdir(server2_path) utils.touch(os.path.join(server2_path, 'proid4.app#0000000000004')) server3_path = os.path.join(self.placement_dir, 'server3.ad.com') os.mkdir(server3_path) server4_path = os.path.join(self.placement_dir, 'server4.ad.com') os.mkdir(server4_path) utils.touch(os.path.join(server4_path, 'proid3.app#0000000000003')) server5_path = os.path.join(self.placement_dir, 'server5.ad.com') os.mkdir(server5_path) utils.touch(os.path.join(server5_path, 'proid5.app#0000000000005')) utils.touch(os.path.join(server5_path, 'proid5.app#0000000000006')) with io.open(os.path.join(self.servers_dir, 'server1.ad.com'), 'w') as f: yaml.dump({ servers.DC_KEY: 'dc.ad.com', servers.DN_KEY: 'CN=server1,DC=AD,DC=COM', 'partition': 'partition1' }, f) with io.open(os.path.join(self.servers_dir, 'server2.ad.com'), 'w') as f: yaml.dump({ servers.DC_KEY: 'dc.ad.com', servers.DN_KEY: 'CN=server2,DC=AD,DC=COM', 'partition': 'partition1' }, f) with io.open(os.path.join(self.servers_dir, 'server3.ad.com'), 'w') as f: yaml.dump({ servers.DC_KEY: 'dc.ad.com', servers.DN_KEY: 'CN=server3,DC=AD,DC=COM', 'partition': 'partition1' }, f) with io.open(os.path.join(self.servers_dir, 'server5.ad.com'), 'w') as f: yaml.dump({ servers.DC_KEY: 'dc.ad.com', servers.DN_KEY: 'CN=server5,DC=AD,DC=COM', 'partition': 'partition1' }, f) mock_connection = mock.MagicMock() connection.return_value = mock_connection type(mock_connection).result = mock.PropertyMock(side_effect={ 'result': 0 }) type(mock_connection).response = mock.PropertyMock(return_value=[ {'attributes': { 'samAccountName': 'proid1-gmsa-hosts', 'member': ['CN=server1,DC=AD,DC=COM'] }}, {'attributes': { 'samAccountName': 'proid2-gmsa-hosts', 'member': ['CN=server3,DC=AD,DC=COM'] }}, {'attributes': { 'samAccountName': 'proid3-gmsa-hosts', 'member': [] }}, {'attributes': { 'samAccountName': 'proid4-gmsa-hosts', 'member': [] }}, {'attributes': { 'samAccountName': 'proid5-gmsa-hosts', 'member': [] }} ]) watch = gmsa.HostGroupWatch(self.root, 'partition1', 'OU=test,DC=ad,DC=com', '{}-gmsa-hosts') watch._sync() self.assertEqual(watch._proids, { 'proid1': {'CN=server1,DC=AD,DC=COM': 1}, 'proid2': {}, 'proid3': {}, 'proid4': {'CN=server2,DC=AD,DC=COM': 1}, 'proid5': {'CN=server5,DC=AD,DC=COM': 2}, }) mock_connection.modify.assert_has_calls( [ mock.call('CN=proid2-gmsa-hosts,OU=test,DC=ad,DC=com', {'member': [(ldap3.MODIFY_DELETE, ['CN=server3,DC=AD,DC=COM'])]}), mock.call('CN=proid4-gmsa-hosts,OU=test,DC=ad,DC=com', {'member': [(ldap3.MODIFY_ADD, ['CN=server2,DC=AD,DC=COM'])]}), mock.call('CN=proid5-gmsa-hosts,OU=test,DC=ad,DC=com', {'member': [(ldap3.MODIFY_ADD, ['CN=server5,DC=AD,DC=COM'])]}), ], any_order=True ) @mock.patch('ldap3.Connection') @mock.patch('treadmill.ad.gmsa._check_ldap3_operation', mock.Mock()) def test_on_created_placement(self, connection): """Test gmsa.HostGroupWatch._on_created_placement.""" # Access protected module # pylint: disable=W0212 server1_path = os.path.join(self.placement_dir, 'server1.ad.com') os.mkdir(server1_path) with io.open(os.path.join(self.servers_dir, 'server1.ad.com'), 'w') as f: yaml.dump({ servers.DC_KEY: 'dc.ad.com', servers.DN_KEY: 'CN=server1,DC=AD,DC=COM', 'partition': 'partition1' }, f) mock_connection = mock.MagicMock() connection.return_value = mock_connection type(mock_connection).result = mock.PropertyMock(side_effect={ 'result': 0 }) type(mock_connection).response = mock.PropertyMock(return_value=[ {'attributes': { 'samAccountName': 'proid1-gmsa-hosts', 'member': [] }} ]) watch = gmsa.HostGroupWatch(self.root, 'partition1', 'OU=test,DC=ad,DC=com', '{}-gmsa-hosts') watch._sync() self.assertEqual(watch._proids, { 'proid1': {}, }) placement_path = os.path.join(server1_path, 'proid1.app#0000000000001') utils.touch(placement_path) watch._on_created_placement(placement_path) self.assertEqual(watch._proids, { 'proid1': {'CN=server1,DC=AD,DC=COM': 1}, }) mock_connection.modify.assert_has_calls([ mock.call('CN=proid1-gmsa-hosts,OU=test,DC=ad,DC=com', {'member': [(ldap3.MODIFY_ADD, ['CN=server1,DC=AD,DC=COM'])]}), ]) @mock.patch('ldap3.Connection') @mock.patch('treadmill.ad.gmsa._check_ldap3_operation', mock.Mock()) def test_on_created_same_host(self, connection): """Test gmsa.HostGroupWatch._on_created_placement.""" # Access protected module # pylint: disable=W0212 server1_path = os.path.join(self.placement_dir, 'server1.ad.com') os.mkdir(server1_path) with io.open(os.path.join(self.servers_dir, 'server1.ad.com'), 'w') as f: yaml.dump({ servers.DC_KEY: 'dc.ad.com', servers.DN_KEY: 'CN=server1,DC=AD,DC=COM', 'partition': 'partition1' }, f) mock_connection = mock.MagicMock() connection.return_value = mock_connection type(mock_connection).result = mock.PropertyMock(side_effect={ 'result': 0 }) type(mock_connection).response = mock.PropertyMock(return_value=[ {'attributes': { 'samAccountName': 'proid1-gmsa-hosts', 'member': [] }} ]) watch = gmsa.HostGroupWatch(self.root, 'partition1', 'OU=test,DC=ad,DC=com', '{}-gmsa-hosts') watch._sync() self.assertEqual(watch._proids, { 'proid1': {}, }) placement_path1 = os.path.join(server1_path, 'proid1.app#0000000000001') utils.touch(placement_path1) watch._on_created_placement(placement_path1) self.assertEqual(watch._proids, { 'proid1': {'CN=server1,DC=AD,DC=COM': 1}, }) placement_path2 = os.path.join(server1_path, 'proid1.app#0000000000001') utils.touch(placement_path2) watch._on_created_placement(placement_path2) self.assertEqual(watch._proids, { 'proid1': {'CN=server1,DC=AD,DC=COM': 2}, }) mock_connection.modify.assert_has_calls([ mock.call('CN=proid1-gmsa-hosts,OU=test,DC=ad,DC=com', {'member': [(ldap3.MODIFY_ADD, ['CN=server1,DC=AD,DC=COM'])]}), ]) self.assertEqual(mock_connection.modify.call_count, 1) @mock.patch('ldap3.Connection') @mock.patch('treadmill.ad.gmsa._check_ldap3_operation', mock.Mock()) def test_on_deleted_placement(self, connection): """Test gmsa.HostGroupWatch._on_deleted_placement.""" # Access protected module # pylint: disable=W0212 server1_path = os.path.join(self.placement_dir, 'server1.ad.com') os.mkdir(server1_path) placement_path = os.path.join(server1_path, 'proid1.app#0000000000001') utils.touch(placement_path) with io.open(os.path.join(self.servers_dir, 'server1.ad.com'), 'w') as f: yaml.dump({ servers.DC_KEY: 'dc.ad.com', servers.DN_KEY: 'CN=server1,DC=AD,DC=COM', 'partition': 'partition1' }, f) mock_connection = mock.MagicMock() connection.return_value = mock_connection type(mock_connection).result = mock.PropertyMock(side_effect={ 'result': 0 }) type(mock_connection).response = mock.PropertyMock(return_value=[ {'attributes': { 'samAccountName': 'proid1-gmsa-hosts', 'member': ['CN=server1,DC=AD,DC=COM'] }} ]) watch = gmsa.HostGroupWatch(self.root, 'partition1', 'OU=test,DC=ad,DC=com', '{}-gmsa-hosts') watch._sync() self.assertEqual(watch._proids, { 'proid1': {'CN=server1,DC=AD,DC=COM': 1}, }) os.remove(placement_path) watch._on_deleted_placement(placement_path) self.assertEqual(watch._proids, { 'proid1': {'CN=server1,DC=AD,DC=COM': 0}, }) mock_connection.modify.assert_has_calls([ mock.call('CN=proid1-gmsa-hosts,OU=test,DC=ad,DC=com', {'member': [(ldap3.MODIFY_DELETE, ['CN=server1,DC=AD,DC=COM'])]}), ]) @mock.patch('ldap3.Connection') @mock.patch('treadmill.ad.gmsa._check_ldap3_operation', mock.Mock()) def test_on_deleted_same_host(self, connection): """Test gmsa.HostGroupWatch._on_deleted_placement.""" # Access protected module # pylint: disable=W0212 server1_path = os.path.join(self.placement_dir, 'server1.ad.com') os.mkdir(server1_path) placement_path1 = os.path.join(server1_path, 'proid1.app#0000000000001') utils.touch(placement_path1) placement_path2 = os.path.join(server1_path, 'proid1.app#0000000000002') utils.touch(placement_path2) with io.open(os.path.join(self.servers_dir, 'server1.ad.com'), 'w') as f: yaml.dump({ servers.DC_KEY: 'dc.ad.com', servers.DN_KEY: 'CN=server1,DC=AD,DC=COM', 'partition': 'partition1' }, f) mock_connection = mock.MagicMock() connection.return_value = mock_connection type(mock_connection).result = mock.PropertyMock(side_effect={ 'result': 0 }) type(mock_connection).response = mock.PropertyMock(return_value=[ {'attributes': { 'samAccountName': 'proid1-gmsa-hosts', 'member': ['CN=server1,DC=AD,DC=COM'] }} ]) watch = gmsa.HostGroupWatch(self.root, 'partition1', 'OU=test,DC=ad,DC=com', '{}-gmsa-hosts') watch._sync() self.assertEqual(watch._proids, { 'proid1': {'CN=server1,DC=AD,DC=COM': 2}, }) os.remove(placement_path2) watch._on_deleted_placement(placement_path2) self.assertEqual(watch._proids, { 'proid1': {'CN=server1,DC=AD,DC=COM': 1}, }) mock_connection.modify.assert_not_called() if __name__ == '__main__': unittest.main()

36.31016

79

0.548233

1,478

13,580

4.870095

0.090663

0.026118

0.032509

0.048764

0.842039

0.807724

0.77327

0.748819

0.740622

0.72145

0

0.036732

0.312371

13,580

373

80

36.407507

0.734097

0.043446

0

0.719595

0

0.209859

0.104621

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0.054054

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0.023649

false

0

0.054054

0

0.081081

0.003378

0

null

0

1

0

1

0

null

0

7

adb07688bdf832f451debba4caa77fba9a4d1315

2,431

py

Python

Chi-Square-Test.py

munafsaiyed/Data-Science-crime-analysis-of-india

d0481b0c6c7796f2424dc627b40a49bed7083068

[ "MIT" ]

null

Chi-Square-Test.py

munafsaiyed/Data-Science-crime-analysis-of-india

d0481b0c6c7796f2424dc627b40a49bed7083068

[ "MIT" ]

null

Chi-Square-Test.py

munafsaiyed/Data-Science-crime-analysis-of-india

d0481b0c6c7796f2424dc627b40a49bed7083068

[ "MIT" ]

null

import pandas as pd from scipy import stats import array data=pd.read_csv('project_file.csv') rowhead=['rape','robbery','murder','total'] rowguj=[data["rape"][data["state_ut"] == "GUJARAT"].sum(),data["robbery"][data["state_ut"] == "GUJARAT"].sum(),data["murder"][data["state_ut"] == "GUJARAT"].sum()] rowraj=[data["rape"][data["state_ut"] == "RAJASTHAN"].sum(),data["robbery"][data["state_ut"] == "RAJASTHAN"].sum(),data["murder"][data["state_ut"] == "RAJASTHAN"].sum()] rowbihar=[data["rape"][data["state_ut"] == "BIHAR"].sum(),data["robbery"][data["state_ut"] == "BIHAR"].sum(),data["murder"][data["state_ut"] == "BIHAR"].sum()] rowup=[data["rape"][data["state_ut"] == "UTTAR PRADESH"].sum(),data["robbery"][data["state_ut"] == "UTTAR PRADESH"].sum(),data["murder"][data["state_ut"] == "UTTAR PRADESH"].sum()] rowt=data["rape"][data["state_ut"] == "GUJARAT"].sum()+data["rape"][data["state_ut"] == "RAJASTHAN"].sum()+data["rape"][data["state_ut"] == "BIHAR"].sum()+data["rape"][data["state_ut"] == "UTTAR PRADESH"].sum()+data["robbery"][data["state_ut"] == "GUJARAT"].sum()+data["robbery"][data["state_ut"] == "RAJASTHAN"].sum()+data["robbery"][data["state_ut"] == "BIHAR"].sum()+data["robbery"][data["state_ut"] == "UTTAR PRADESH"].sum()+data["murder"][data["state_ut"] == "GUJARAT"].sum()+data["murder"][data["state_ut"] == "RAJASTHAN"].sum()+data["murder"][data["state_ut"] == "BIHAR"].sum()+data["murder"][data["state_ut"] == "UTTAR PRADESH"].sum() rowtot=["TOTAL",data["rape"][data["state_ut"] == "GUJARAT"].sum()+data["rape"][data["state_ut"] == "RAJASTHAN"].sum()+data["rape"][data["state_ut"] == "BIHAR"].sum()+data["rape"][data["state_ut"] == "UTTAR PRADESH"].sum(),data["robbery"][data["state_ut"] == "GUJARAT"].sum()+data["robbery"][data["state_ut"] == "RAJASTHAN"].sum()+data["robbery"][data["state_ut"] == "BIHAR"].sum()+data["robbery"][data["state_ut"] == "UTTAR PRADESH"].sum(),data["murder"][data["state_ut"] == "GUJARAT"].sum()+data["murder"][data["state_ut"] == "RAJASTHAN"].sum()+data["murder"][data["state_ut"] == "BIHAR"].sum()+data["murder"][data["state_ut"] == "UTTAR PRADESH"].sum(),rowt] table=[rowguj,rowraj,rowbihar,rowup] print(table) chi2_stat, p_val, dof, ex = stats.chi2_contingency(table) print("===Chi2 Stat===") print(chi2_stat) print("\n") print("===Degrees of Freedom===") print(dof) print("\n") print("===P-Value===") print(p_val) print("\n") print("===Contingency Table===") print(ex)

83.827586

659

0.634307

337

2,431

4.448071

0.136499

0.216144

0.264176

0.136091

0.771848

0.735824

0

0.001736

0.052242

2,431

28

660

86.821429

0.648872

0

0.12

0

0.379424

0

1

0

false

0

0.12

0

0.12

0.48

0

null

1

0

1

0

null

0

1

0

8

add51fa293b8043119ef92446e0617a91e47e638

748

py

Python

r2con2020/tasks/defuse/scripts/solve2.py

BlackVS/CTFs

ca7d5c9a3dbf1bcfe7607bbfd454eca470634dde

[ "MIT" ]

10

2020-09-06T12:08:32.000Z

2021-07-19T15:12:30.000Z

r2con2020/tasks/defuse/scripts/solve2.py

BlackVS/CTFs

ca7d5c9a3dbf1bcfe7607bbfd454eca470634dde

[ "MIT" ]

null

r2con2020/tasks/defuse/scripts/solve2.py

BlackVS/CTFs

ca7d5c9a3dbf1bcfe7607bbfd454eca470634dde

[ "MIT" ]

1

2021-11-22T05:14:56.000Z

#!/usr/bin/env python3 import os,sys from itertools import * #for p in product( 'prxz', 'su', 'ln', 'ce', 'prxz', 'aio', 'ln', 'ce', 'km', 'aio', 'prxz', 'ce', 'tv', 'aio', 'km', 'ce' ): #for p in product( 'prxz', 'su', 'ln', 'ce', 'prxz', 'aio' ): #for p in product( ['rule'], 'prxz', 'aio', 'ln', 'ce', 'km', 'aio', 'prxz', 'ce', 'tv', 'aio', 'km', 'ce' ): #for p in product( 'prxz', 'ce', 'tv', 'aio', 'km', 'ce' ): #for p in product( ['rule'], 'prxz', 'aio', 'ln', 'ce', 'km', 'aio', 'prxz', 'ce', ['take','time','tome']): #for p in product( ['rule'], 'prxz', 'aio', 'ln', 'ce', 'km', 'aio', 'prxz', 'ce', ['time']): for p in product( ['rule'], 'prxz', 'aio', 'ln', 'ce', ['more'], ['time']): print("esil"+"".join(p)) esilrulezonemoretime

53.428571

125

0.494652

113

748

3.274336

0.256637

0.075676

0.113514

0.245946

0.718919

0.643243

0

0.00158

0.153743

748

14

126

53.428571

0.582938

0.760695

0

0.156069

0

1

0

false

0

0.4

0

0.4

0.2

0

null

0

1

0

1

0

null

0

1

0

7

bc22e61aa14f9b54edc3219b2abfe2f3cd9285b3

13,324

py

Python

tests/flytekit/unit/common_tests/types/impl/test_blobs.py

flytehub/flytekit

f8f53567594069b29fcd3f99abd1da71a5ef0e22

[ "Apache-2.0" ]

1

2019-10-22T05:22:16.000Z

tests/flytekit/unit/common_tests/types/impl/test_blobs.py

chixcode/flytekit

f901aee721847c6264d44079d4fa31a75b8876e1

[ "Apache-2.0" ]

null

tests/flytekit/unit/common_tests/types/impl/test_blobs.py

chixcode/flytekit

f901aee721847c6264d44079d4fa31a75b8876e1

[ "Apache-2.0" ]

1

2019-08-28T22:27:07.000Z

from __future__ import absolute_import from flytekit.common.exceptions import user as _user_exceptions from flytekit.common.types.impl import blobs from flytekit.common.utils import AutoDeletingTempDir from flytekit.models.core import types as _core_types from flytekit.sdk import test_utils import pytest import os def test_blob(): b = blobs.Blob("/tmp/fake") assert b.remote_location == "/tmp/fake" assert b.local_path is None assert b.mode == "rb" assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.SINGLE def test_blob_from_python_std(): with test_utils.LocalTestFileSystem() as t: with AutoDeletingTempDir('test') as wd: tmp_name = wd.get_named_tempfile("from_python_std") with open(tmp_name, 'wb') as w: w.write("hello hello".encode('utf-8')) b = blobs.Blob.from_python_std(tmp_name) assert b.mode == "wb" assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.SINGLE assert b.remote_location.startswith(t.name) assert b.local_path == tmp_name with open(b.remote_location, 'rb') as r: assert r.read() == "hello hello".encode('utf-8') b = blobs.Blob("/tmp/fake") b2 = blobs.Blob.from_python_std(b) assert b == b2 with pytest.raises(_user_exceptions.FlyteTypeException): blobs.Blob.from_python_std(3) def test_blob_create_at(): with test_utils.LocalTestFileSystem() as t: with AutoDeletingTempDir('test') as wd: tmp_name = wd.get_named_tempfile('tmp') b = blobs.Blob.create_at_known_location(tmp_name) assert b.local_path is None assert b.remote_location == tmp_name assert b.mode == 'wb' assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.SINGLE with b as w: w.write("hello hello".encode('utf-8')) assert b.local_path.startswith(t.name) with open(tmp_name, 'rb') as r: assert r.read() == "hello hello".encode('utf-8') def test_blob_fetch_managed(): with AutoDeletingTempDir('test') as wd: with test_utils.LocalTestFileSystem() as t: tmp_name = wd.get_named_tempfile('tmp') with open(tmp_name, 'wb') as w: w.write("hello".encode('utf-8')) b = blobs.Blob.fetch(tmp_name) assert b.local_path.startswith(t.name) assert b.remote_location == tmp_name assert b.mode == 'rb' assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.SINGLE with b as r: assert r.read() == "hello".encode('utf-8') with pytest.raises(_user_exceptions.FlyteAssertion): blobs.Blob.fetch(tmp_name, local_path=b.local_path) with open(tmp_name, 'wb') as w: w.write("bye".encode('utf-8')) b2 = blobs.Blob.fetch(tmp_name, local_path=b.local_path, overwrite=True) with b2 as r: assert r.read() == "bye".encode('utf-8') with pytest.raises(_user_exceptions.FlyteAssertion): blobs.Blob.fetch(tmp_name) def test_blob_fetch_unmanaged(): with AutoDeletingTempDir('test') as wd: with AutoDeletingTempDir('test2') as t: tmp_name = wd.get_named_tempfile('source') tmp_sink = t.get_named_tempfile('sink') with open(tmp_name, 'wb') as w: w.write("hello".encode('utf-8')) b = blobs.Blob.fetch(tmp_name, local_path=tmp_sink) assert b.local_path == tmp_sink assert b.remote_location == tmp_name assert b.mode == 'rb' assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.SINGLE with b as r: assert r.read() == "hello".encode('utf-8') with pytest.raises(_user_exceptions.FlyteAssertion): blobs.Blob.fetch(tmp_name, local_path=tmp_sink) with open(tmp_name, 'wb') as w: w.write("bye".encode('utf-8')) b2 = blobs.Blob.fetch(tmp_name, local_path=tmp_sink, overwrite=True) with b2 as r: assert r.read() == "bye".encode('utf-8') def test_blob_double_enter(): with test_utils.LocalTestFileSystem(): with AutoDeletingTempDir('test') as wd: b = blobs.Blob(wd.get_named_tempfile("sink"), mode='wb') with b: with pytest.raises(_user_exceptions.FlyteAssertion): with b: pass def test_blob_download_managed(): with AutoDeletingTempDir('test') as wd: with test_utils.LocalTestFileSystem() as t: tmp_name = wd.get_named_tempfile('tmp') with open(tmp_name, 'wb') as w: w.write("hello".encode('utf-8')) b = blobs.Blob(tmp_name) b.download() assert b.local_path.startswith(t.name) assert b.remote_location == tmp_name assert b.mode == 'rb' assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.SINGLE with b as r: assert r.read() == "hello".encode('utf-8') b2 = blobs.Blob(tmp_name) with pytest.raises(_user_exceptions.FlyteAssertion): b2.download(b.local_path) with open(tmp_name, 'wb') as w: w.write("bye".encode('utf-8')) b2 = blobs.Blob(tmp_name) b2.download(local_path=b.local_path, overwrite=True) with b2 as r: assert r.read() == "bye".encode('utf-8') b = blobs.Blob(tmp_name) with pytest.raises(_user_exceptions.FlyteAssertion): b.download() def test_blob_download_unmanaged(): with AutoDeletingTempDir('test') as wd: with AutoDeletingTempDir('test2') as t: tmp_name = wd.get_named_tempfile('source') tmp_sink = t.get_named_tempfile('sink') with open(tmp_name, 'wb') as w: w.write("hello".encode('utf-8')) b = blobs.Blob(tmp_name) b.download(tmp_sink) assert b.local_path == tmp_sink assert b.remote_location == tmp_name assert b.mode == 'rb' assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.SINGLE with b as r: assert r.read() == "hello".encode('utf-8') b = blobs.Blob(tmp_name) with pytest.raises(_user_exceptions.FlyteAssertion): b.download(tmp_sink) with open(tmp_name, 'wb') as w: w.write("bye".encode('utf-8')) b2 = blobs.Blob(tmp_name) b2.download(tmp_sink, overwrite=True) with b2 as r: assert r.read() == "bye".encode('utf-8') def test_multipart_blob(): b = blobs.MultiPartBlob("/tmp/fake", mode='w', format='csv') assert b.remote_location == "/tmp/fake/" assert b.local_path is None assert b.mode == "w" assert b.metadata.type.format == "csv" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.MULTIPART def _generate_multipart_blob_data(tmp_dir): n = tmp_dir.get_named_tempfile("0") with open(n, 'wb') as w: w.write("part0".encode('utf-8')) n = tmp_dir.get_named_tempfile("1") with open(n, 'wb') as w: w.write("part1".encode('utf-8')) n = tmp_dir.get_named_tempfile("2") with open(n, 'wb') as w: w.write("part2".encode('utf-8')) def test_multipart_blob_from_python_std(): with test_utils.LocalTestFileSystem() as t: with AutoDeletingTempDir('test') as wd: _generate_multipart_blob_data(wd) b = blobs.MultiPartBlob.from_python_std(wd.name) assert b.mode == "wb" assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.MULTIPART assert b.remote_location.startswith(t.name) assert b.local_path == wd.name with open(os.path.join(b.remote_location, '0'), 'rb') as r: assert r.read() == "part0".encode('utf-8') with open(os.path.join(b.remote_location, '1'), 'rb') as r: assert r.read() == "part1".encode('utf-8') with open(os.path.join(b.remote_location, '2'), 'rb') as r: assert r.read() == "part2".encode('utf-8') b = blobs.MultiPartBlob("/tmp/fake/") b2 = blobs.MultiPartBlob.from_python_std(b) assert b == b2 with pytest.raises(_user_exceptions.FlyteTypeException): blobs.MultiPartBlob.from_python_std(3) def test_multipart_blob_create_at(): with test_utils.LocalTestFileSystem(): with AutoDeletingTempDir('test') as wd: b = blobs.MultiPartBlob.create_at_known_location(wd.name) assert b.local_path is None assert b.remote_location == wd.name + "/" assert b.mode == 'wb' assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.MULTIPART with b.create_part('0') as w: w.write("part0".encode('utf-8')) with b.create_part('1') as w: w.write("part1".encode('utf-8')) with b.create_part('2') as w: w.write("part2".encode('utf-8')) with open(os.path.join(wd.name, '0'), 'rb') as r: assert r.read() == "part0".encode('utf-8') with open(os.path.join(wd.name, '1'), 'rb') as r: assert r.read() == "part1".encode('utf-8') with open(os.path.join(wd.name, '2'), 'rb') as r: assert r.read() == "part2".encode('utf-8') def test_multipart_blob_fetch_managed(): with AutoDeletingTempDir('test') as wd: with test_utils.LocalTestFileSystem() as t: _generate_multipart_blob_data(wd) b = blobs.MultiPartBlob.fetch(wd.name) assert b.local_path.startswith(t.name) assert b.remote_location == wd.name + "/" assert b.mode == 'rb' assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.MULTIPART with b as r: assert r[0].read() == "part0".encode('utf-8') assert r[1].read() == "part1".encode('utf-8') assert r[2].read() == "part2".encode('utf-8') with pytest.raises(_user_exceptions.FlyteAssertion): blobs.MultiPartBlob.fetch(wd.name, local_path=b.local_path) with open(os.path.join(wd.name, "0"), 'wb') as w: w.write("bye".encode('utf-8')) b2 = blobs.MultiPartBlob.fetch(wd.name, local_path=b.local_path, overwrite=True) with b2 as r: assert r[0].read() == "bye".encode('utf-8') assert r[1].read() == "part1".encode('utf-8') assert r[2].read() == "part2".encode('utf-8') with pytest.raises(_user_exceptions.FlyteAssertion): blobs.Blob.fetch(wd.name) def test_multipart_blob_fetch_unmanaged(): with AutoDeletingTempDir('test') as wd: with AutoDeletingTempDir('test2') as t: _generate_multipart_blob_data(wd) tmp_sink = t.get_named_tempfile('sink') b = blobs.MultiPartBlob.fetch(wd.name, local_path=tmp_sink) assert b.local_path == tmp_sink assert b.remote_location == wd.name + "/" assert b.mode == 'rb' assert b.metadata.type.format == "" assert b.metadata.type.dimensionality == _core_types.BlobType.BlobDimensionality.MULTIPART with b as r: assert r[0].read() == "part0".encode('utf-8') assert r[1].read() == "part1".encode('utf-8') assert r[2].read() == "part2".encode('utf-8') with pytest.raises(_user_exceptions.FlyteAssertion): blobs.MultiPartBlob.fetch(wd.name, local_path=tmp_sink) with open(os.path.join(wd.name, "0"), 'wb') as w: w.write("bye".encode('utf-8')) b2 = blobs.MultiPartBlob.fetch(wd.name, local_path=tmp_sink, overwrite=True) with b2 as r: assert r[0].read() == "bye".encode('utf-8') assert r[1].read() == "part1".encode('utf-8') assert r[2].read() == "part2".encode('utf-8') def test_multipart_blob_no_enter_on_write(): with test_utils.LocalTestFileSystem(): b = blobs.MultiPartBlob.create_at_any_location() with pytest.raises(_user_exceptions.FlyteAssertion): with b: pass

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bc2ee864ebb0fa0013ff728ac206f3c64231998e

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Python

python/Expression.py

Greakz/mdh-cmake-cubevis

6c64ec0e14dcdd07e69fa1f018aa7954eeeaf173

[ "MIT" ]

null

python/Expression.py

Greakz/mdh-cmake-cubevis

6c64ec0e14dcdd07e69fa1f018aa7954eeeaf173

[ "MIT" ]

5

2021-08-24T11:09:54.000Z

2021-08-24T21:14:15.000Z

python/Expression.py

Greakz/mdh-cmake-cubevis

6c64ec0e14dcdd07e69fa1f018aa7954eeeaf173

[ "MIT" ]

null

class Expression: @staticmethod def process_string_without_clocks(data, raw_txt): result = raw_txt for constant in data.constants: result = result.replace(constant["name"], "this->" + constant["cname"]) return result @staticmethod def process_string(data, raw_txt): result = raw_txt for constant in data.constants: result = result.replace(constant["name"], "this->v->" + constant["cname"]) for clock in data.clocks_par: result = result.replace(clock["name"], "this->v->clock->" + clock["cname"]) for clock in data.clocks_seq: result = result.replace(clock["name"], "this->v->clock->" + clock["cname"]) return result @staticmethod def process_str_exp_but_set_clock_to_min(data, raw_txt): result = raw_txt for constant in data.constants: result = result.replace(constant["name"], "this->v->" + constant["cname"]) for clock in data.clocks_par: result = result.replace(clock["name"], "this->v->" + clock["cname_start_f"] + "()") for clock in data.clocks_seq: result = result.replace(clock["name"], "this->v->" + clock["cname_start_f"] + "()") return result @staticmethod def process_str_exp_but_set_clock_to_min_except_for(data, raw_txt, exceptional_clocks, add_custom_value): x = raw_txt for constant in data.constants: x = x.replace(constant["name"], "this->v->" + constant["cname"]) for clock in data.clocks_par: if is_in(exceptional_clocks, clock["name"]): x = x.replace(clock["name"], "(this->v->" + clock["cname_start_f"] + "() + " + str(add_custom_value) + ")") else: x = x.replace(clock["name"], "this->v->" + clock["cname_start_f"] + "()") for clock in data.clocks_seq: if is_in(exceptional_clocks, clock["name"]): x = x.replace(clock["name"], "(this->v->" + clock["cname_start_f"] + "() + " + str(add_custom_value) + ")") else: x = x.replace(clock["name"], "this->v->" + clock["cname_start_f"] + "()") return x def is_in(search_list, key): for item in search_list: if key == item: return True return False

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cb2d2e512b3faec3b836f6d9eb8806788663cec6

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py

Python

tests/test_provider_onelogin_onelogin.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

507

2017-07-26T02:58:38.000Z

2022-01-21T12:35:13.000Z

tests/test_provider_onelogin_onelogin.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

135

2017-07-20T12:01:59.000Z

2021-10-04T22:25:40.000Z

tests/test_provider_onelogin_onelogin.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

81

2018-02-20T17:55:28.000Z

2022-01-31T07:08:40.000Z

# tests/test_provider_onelogin_onelogin.py # Automatically generated by tools/makecode.py (24-Sep-2021 15:23:37 UTC) def test_provider_import(): import terrascript.provider.onelogin.onelogin def test_resource_import(): from terrascript.resource.onelogin.onelogin import onelogin_app_role_attachments from terrascript.resource.onelogin.onelogin import onelogin_app_rules from terrascript.resource.onelogin.onelogin import onelogin_apps from terrascript.resource.onelogin.onelogin import onelogin_auth_servers from terrascript.resource.onelogin.onelogin import onelogin_oidc_apps from terrascript.resource.onelogin.onelogin import onelogin_privileges from terrascript.resource.onelogin.onelogin import onelogin_roles from terrascript.resource.onelogin.onelogin import onelogin_saml_apps from terrascript.resource.onelogin.onelogin import ( onelogin_smarthook_environment_variables, ) from terrascript.resource.onelogin.onelogin import onelogin_smarthooks from terrascript.resource.onelogin.onelogin import onelogin_user_mappings from terrascript.resource.onelogin.onelogin import onelogin_users def test_datasource_import(): from terrascript.data.onelogin.onelogin import onelogin_user from terrascript.data.onelogin.onelogin import onelogin_users # TODO: Shortcut imports without namespace for official and supported providers. # TODO: This has to be moved into a required_providers block. # def test_version_source(): # # import terrascript.provider.onelogin.onelogin # # t = terrascript.provider.onelogin.onelogin.onelogin() # s = str(t) # # assert 'https://github.com/onelogin/terraform-provider-onelogin' in s # assert '0.1.23' in s

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