fumiyau/python_comments_free_500000 · Datasets at Hugging Face

1c2fb0f86f4a3e69043e5a1a430d789099947416

28,918

py

Python

src/train_model.py

aaronbuhendwa/twophasePINN

77bdcb2a07ab31dc9ab43623cf6b776a97c0b5c8

[ "MIT" ]

5

2021-06-09T07:03:40.000Z

2021-12-27T08:43:52.000Z

src/train_model.py

aaronbuhendwa/twophasePINN

77bdcb2a07ab31dc9ab43623cf6b776a97c0b5c8

[ "MIT" ]

null

src/train_model.py

aaronbuhendwa/twophasePINN

77bdcb2a07ab31dc9ab43623cf6b776a97c0b5c8

[ "MIT" ]

3

2021-02-04T15:21:32.000Z

2021-12-14T14:34:28.000Z

import sys sys.path.append("../utilities") import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID" GPU_ID = "0" os.environ["CUDA_VISIBLE_DEVICES"]= GPU_ID import tensorflow as tf tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR) from tensorflow.keras import backend as K import numpy as np import pandas as pd import scipy.io from generate_points import * from utilities import * import time import math import glob from datetime import datetime import shutil import logging np.random.seed(1234) tf.set_random_seed(1234) class TwoPhasePinn: ''' This class implements a physics-informed neural network. It approximates the incompressible two-phase Navier-Stokes equations in 2D using a Volume-of-Fluid approach. Thus, the neural network maps (x, y, t) -> (u, v, p, a) where a is the volume fraction field. The placeholders and losses have to be constructed for each case individually as they depend on the boundary conditions. The present implementation corresponds to the rising bubble case, see paper. Args: sess: tensorflow session dtype: data type hidden_layers: list containing number of nodes for each hidden layer activation_functions: dictionary assigning layers to activation function adaptive_activation_coeff: dictionary assigning layers to adaptive activation coeff adaptive_activation_init: dictionary assigning initial value to adaptive activation coeff adaptive_activation_n: list containing the scale factor of the adapative activation coeff for each layer - must have same length as hidden_layers use_ad_act: bool indicating whether to use adaptive activation coeff loss_weights_A: loss weight for volume fraction loss loss_weights_PDE: loss weights for PDEs checkpoint_interval: interval in epochs indicating when to save model epochs: list of epochs batch_sizes: list of batch sizes - should have same length as epochs learning_rates: list of learning rates - should have same length as epochs ''' def __init__(self, sess, dtype, hidden_layers, activation_functions, adaptive_activation_coeff, adaptive_activation_n, adaptive_activation_init, use_ad_act, loss_weights_A, loss_weights_PDE, mu, sigma, g, rho, u_ref, L_ref, checkpoint_interval, epochs, batch_sizes, learning_rates): # CREATE OUTPUT FOLDER AND GET LOGGER self.dirname, logpath = self.make_output_dir() self.logger = self.get_logger(logpath) # PHYSICAL PARAMETERS self.mu1 = mu[0] self.mu2 = mu[1] self.sigma = sigma self.g = g self.rho1 = rho[0] self.rho2 = rho[1] self.U_ref = u_ref self.L_ref = L_ref # MEMBERS FOR SAVING CHECKPOINTS AND TRACKING self.epoch_loss_checkpoints = 1e10 self.checkpoint_interval = checkpoint_interval self.mean_epoch_time = 0 # SGD OPT MEMBERS self.learning_rates = learning_rates self.epochs = epochs self.batch_sizes = batch_sizes # TENSORFLOW SESSION self.sess = sess K.set_session(self.sess) self.print("Building Computational Graph") # PLACEHOLDERS x_A = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_A") y_A = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_A") t_A = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_A") a_A = tf.placeholder(dtype=dtype, shape=[None, 1], name="a_A") x_N = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_N") y_N = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_N") t_N = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_N") p_N = tf.placeholder(dtype=dtype, shape=[None, 1], name="p_N") x_E = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_E") y_E = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_E") x_W = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_W") y_W = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_W") t_EW = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_EW") x_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_NSEW") y_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_NSEW") t_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_NSEW") u_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="u_NSEW") v_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="v_NSEW") x_PDE = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_PDE") y_PDE = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_PDE") t_PDE = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_PDE") f_PDE = tf.placeholder(dtype=dtype, shape=[None, 1], name="f_PDE") self.learning_rate_opt = tf.placeholder(dtype=dtype, shape=[], name="learning_rate") data_set_names = ["A", "PDE", "N", "EW", "NSEW"] self.placeholders = dict((name, []) for name in data_set_names) self.placeholders["A"].extend([x_A, y_A, t_A, a_A]) self.placeholders["PDE"].extend([x_PDE, y_PDE, t_PDE, f_PDE]) self.placeholders["N"].extend([x_N, y_N, t_N, p_N]) self.placeholders["EW"].extend([x_E, y_E, x_W, y_W, t_EW]) self.placeholders["NSEW"].extend([x_NSEW, y_NSEW, t_NSEW, u_NSEW, v_NSEW]) # VARIABLES ADAPTIVE ACTIVATION FOR HIDDEN LAYERS self.sanity_check_activation_functions(activation_functions, adaptive_activation_coeff, adaptive_activation_n, adaptive_activation_init, hidden_layers) self.ad_act_coeff = {} if use_ad_act: for key in adaptive_activation_coeff: initial_value = adaptive_activation_init[key] self.ad_act_coeff[key] = tf.Variable(initial_value, name=key) activation_functions_dict = self.get_activation_function_dict(activation_functions, adaptive_activation_coeff, adaptive_activation_n, hidden_layers, use_ad_act) # NETWORK ARCHITECTURE outputs = ["output_u", "output_v", "output_p", "output_a"] activations_output = [None, None, "exponential", "sigmoid"] output_layer = list(zip(outputs, activations_output)) nn = NNCreator(dtype) self.model = nn.get_model_dnn(3, hidden_layers, output_layer, activation_functions_dict, use_ad_act) # LOSSES ASSOCIATED WITH A output_tensors = self.model(tf.concat([x_A, y_A, t_A], 1)) loss_a_A = tf.reduce_mean(tf.square(a_A - output_tensors[3])) # LOSSES ASSOCIATED WITH FIXED VALUE NORTH SOUTH EAST WEST start = time.time() output_tensors = self.model(tf.concat([x_NSEW, y_NSEW, t_NSEW], 1)) loss_u_NSEW = tf.reduce_mean(tf.square(u_NSEW - output_tensors[0])) loss_v_NSEW = tf.reduce_mean(tf.square(v_NSEW - output_tensors[1])) loss_NSEW = tf.reduce_sum(tf.stack([loss_u_NSEW, loss_v_NSEW])) self.print(time.time()-start, "s") # LOSSES ASSOCIATED WITH FIXED PRESSURE NORTH start = time.time() output_tensors = self.model(tf.concat([x_N, y_N, t_N], 1)) loss_p_N = tf.reduce_mean(tf.square(p_N - output_tensors[2])) self.print(time.time()-start, "s") # LOSSES ASSOCIATED WITH PERIODIC BOUNDARY EAST WEST start = time.time() output_east = self.model(tf.concat([x_E, y_E, t_EW], 1)) output_west = self.model(tf.concat([x_W, y_W, t_EW], 1)) loss_u_EW = tf.reduce_mean(tf.square(output_east[0] - output_west[0])) loss_v_EW = tf.reduce_mean(tf.square(output_east[1] - output_west[1])) loss_p_EW = tf.reduce_mean(tf.square(output_east[2] - output_west[2])) loss_EW = tf.reduce_sum(tf.stack([loss_u_EW, loss_v_EW, loss_p_EW])) self.print(time.time()-start, "s") loss_NSEW = tf.reduce_sum(tf.stack([loss_p_N, loss_EW, loss_NSEW])) # LOSSES ASSOCIATED WITH PDEs -> PHYSICS INFORMED NEURAL NETS start = time.time() PDE_tensors = self.PDE_caller(x_PDE, y_PDE, t_PDE) loss_PDE_m = tf.losses.mean_squared_error(f_PDE, PDE_tensors[0]) loss_PDE_u = tf.losses.mean_squared_error(f_PDE, PDE_tensors[1]) loss_PDE_v = tf.losses.mean_squared_error(f_PDE, PDE_tensors[2]) loss_PDE_a = tf.losses.mean_squared_error(f_PDE, PDE_tensors[3]) self.print(time.time()-start, "s") loss_PDE = tf.tensordot(tf.stack([loss_PDE_m, loss_PDE_u, loss_PDE_v, loss_PDE_a]), np.array(loss_weights_PDE).astype("float32"), 1) # TOTAL LOSS loss_complete = loss_a_A + loss_NSEW + loss_PDE # OPTIMIZERS start = time.time() self.optimizer = tf.train.AdamOptimizer(self.learning_rate_opt) self.minimize_op = self.optimizer.minimize(loss_complete) self.print(time.time()-start, "s") # DEFINING LISTS AND DICTIONARIES FOR TRACKING LOSSES AND SPECIFIC TENSORS self.loss_tensor_list = [loss_complete, loss_a_A, loss_NSEW, loss_PDE_m, loss_PDE_u, loss_PDE_v, loss_PDE_a] self.loss_list = ["l", "a", "NSEW", "m", "u", "v", "PDE_a"] self.epoch_loss = dict.fromkeys(self.loss_list, 0) self.loss_history = dict((loss, []) for loss in self.loss_list) self.ad_act_coeff_history = dict((key, []) for key in self.ad_act_coeff) # INITIALIZING VARIABLES self.sess.run(tf.global_variables_initializer()) # SET WEIGHTS AND OPTIMIZER STATE IF AVAILABLE self.set_variables() # FINALIZING self.model.save_weights(os.path.join(self.dirname, "Weights_loss_%.4e.h5" % (self.epoch_loss_checkpoints))) self.sess.graph.finalize() def make_output_dir(self): if not os.path.exists("checkpoints"): os.mkdir("checkpoints") dirname = os.path.abspath(os.path.join("checkpoints", datetime.now().strftime("%b-%d-%Y_%H-%M-%S"))) os.mkdir(dirname) shutil.copyfile(__file__, os.path.join(dirname, __file__)) shutil.copyfile("generate_points.py", os.path.join(dirname, "generate_points.py")) logpath = os.path.join(dirname, "output.log") return dirname, logpath def get_logger(self, logpath): logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) sh = logging.StreamHandler() sh.setLevel(logging.DEBUG) sh.setFormatter(logging.Formatter('%(message)s')) fh = logging.FileHandler(logpath) logger.addHandler(sh) logger.addHandler(fh) return logger def sanity_check_activation_functions(self, activation_functions, adaptive_activations, adaptive_activation_n, adaptive_activation_init, hidden_layers): no_layers = len(hidden_layers) check = 0 for key, value in list(adaptive_activations.items()): check += sum(value) assert no_layers*(no_layers+1)/2 == check, "Not every layer has been assigned with an adaptive activation coefficient unambiguously" check = 0 for key, value in list(activation_functions.items()): check += sum(value) assert no_layers*(no_layers+1)/2 == check, "Not every layer has been assigned with an activation function unambiguously" assert no_layers == len(adaptive_activation_n), "Not every layer has an adaptive activation precoefficient" assert adaptive_activation_init.keys() == adaptive_activations.keys(), "Not every adaptive activation coefficient has been assigned an initial value" def get_activation_function_dict(self, activation_functions, adaptive_activation_coeff, adaptive_activation_n, hidden_layers, use_ad_act): activation_functions_dict = dict((key, [0, 0, 0]) for key in range(1, len(hidden_layers) + 1)) for layer_no in activation_functions_dict: activation_functions_dict[layer_no][2] = adaptive_activation_n[layer_no-1] for func_name, layers in activation_functions.items(): if layer_no in layers: activation_functions_dict[layer_no][0] = func_name if use_ad_act: # if use_ad_act is False, self.ad_act_coeff is empty! for coeff_name, layers in adaptive_activation_coeff.items(): if layer_no in layers: activation_functions_dict[layer_no][1] = self.ad_act_coeff[coeff_name] return activation_functions_dict def compute_gradients(self, x, y, t): u, v, p, a = self.model(tf.concat([x, y, t], 1)) u_x = tf.gradients(u, x)[0] u_y = tf.gradients(u, y)[0] u_t = tf.gradients(u, t)[0] u_xx = tf.gradients(u_x, x)[0] u_yy = tf.gradients(u_y, y)[0] v_x = tf.gradients(v, x)[0] v_y = tf.gradients(v, y)[0] v_t = tf.gradients(v, t)[0] v_xx = tf.gradients(v_x, x)[0] v_yy = tf.gradients(v_y, y)[0] p_x = tf.gradients(p, x)[0] p_y = tf.gradients(p, y)[0] a_x = tf.gradients(a, x)[0] a_y = tf.gradients(a, y)[0] a_t = tf.gradients(a, t)[0] a_xx = tf.gradients(a_x, x)[0] a_yy = tf.gradients(a_y, y)[0] a_xy = tf.gradients(a_x, y)[0] return [u, u_x, u_y, u_t, u_xx, u_yy], [v, v_x, v_y, v_t, v_xx, v_yy], [p, p_x, p_y], [a, a_x, a_y, a_t, a_xx, a_yy, a_xy] def PDE_caller(self, x, y, t): u_gradients, v_gradients, p_gradients, a_gradients = self.compute_gradients(x, y, t) u, u_x, u_y, u_t, u_xx, u_yy = u_gradients[:] v, v_x, v_y, v_t, v_xx, v_yy = v_gradients[:] p, p_x, p_y = p_gradients[:] a, a_x, a_y, a_t, a_xx, a_yy, a_xy = a_gradients[:] mu = self.mu2 + (self.mu1 - self.mu2) * a mu_x = (self.mu1 - self.mu2) * a_x mu_y = (self.mu1 - self.mu2) * a_y rho = self.rho2 + (self.rho1 - self.rho2) * a abs_interface_grad = tf.sqrt(tf.square(a_x) + tf.square(a_y) + np.finfo(float).eps) curvature = - ( (a_xx + a_yy)/abs_interface_grad - (a_x**2*a_xx + a_y**2*a_yy + 2*a_x*a_y*a_xy)/tf.pow(abs_interface_grad, 3) ) rho_ref = self.rho2 one_Re = mu/(rho_ref*self.U_ref*self.L_ref) one_Re_x = mu_x/(rho_ref*self.U_ref*self.L_ref) one_Re_y = mu_y/(rho_ref*self.U_ref*self.L_ref) one_We = self.sigma/(rho_ref*self.U_ref**2*self.L_ref) one_Fr = self.g*self.L_ref/self.U_ref**2 PDE_m = u_x + v_y PDE_a = a_t + u*a_x + v*a_y PDE_u = (u_t + u*u_x + v*u_y)*rho/rho_ref + p_x - one_We*curvature*a_x - one_Re*(u_xx + u_yy) - 2.0*one_Re_x*u_x - one_Re_y*(u_y + v_x) PDE_v = (v_t + u*v_x + v*v_y)*rho/rho_ref + p_y - one_We*curvature*a_y - one_Re*(v_xx + v_yy) - rho/rho_ref*one_Fr - 2.0*one_Re_y*v_y - one_Re_x*(u_y + v_x) return PDE_m, PDE_u, PDE_v, PDE_a def set_variables(self): ''' Implements functionality to continue training from checkpoint. Loads the weights and optimizer state from the .h5 file and the .mat file, respectively. This is only done if the necessary files are located in the same folder as this script ''' for file in glob.glob("*loss*"): if file.endswith("h5"): self.model.load_weights(file) self.print("Loading weights from file", file) if file.endswith("mat"): matfile = scipy.io.loadmat(file, squeeze_me=True) self.print("Setting optimizer variables according to file", file) optimizer_state = matfile["optimizer_state"] optimizer_variables = self.optimizer.variables() assert len(optimizer_variables) == len(optimizer_state), "Loading optimizer state failed: Not as many optimizer states saved as required, check architecture/aac compatibility!" for i in range(0, len(optimizer_variables)): if optimizer_variables[i].shape == (1,): # Shapes that require (1,) are loaded as floats from .mat file, thus have to be converted to np.array optimizer_state[i] = np.array([optimizer_state[i]]) if len(optimizer_variables[i].shape) == 2: if optimizer_variables[i].shape[1] == 1: # Shapes that require (?,1) are loaded as (?,) from .mat file, thus need reshaping optimizer_state[i] = optimizer_state[i].reshape(len(optimizer_state[i]),1) self.sess.run(optimizer_variables[i].assign(optimizer_state[i])) self.print("Setting adaptive activation coefficients according to file", file) ad_act_coeff = matfile["ad_act_coeff"] if len(self.ad_act_coeff) > 0: assert list(self.ad_act_coeff.keys()) == list(ad_act_coeff.dtype.names), "Loading adaptive activation coefficients failed: Restart coefficients %s do not match input %s" %(list(ad_act_coeff.dtype.names), list(self.ad_act_coeff.keys())) for key in self.ad_act_coeff: self.sess.run(self.ad_act_coeff[key].assign(float(ad_act_coeff[key]))) def train(self, data_sets): ''' Implements the training loop Args: data_sets: Dictionary assigning a pandas dataframe to each loss ''' self.check_matching_keys(data_sets) self.print_point_distribution(data_sets) self.print("\nEPOCHS: ", self.epochs, " BATCH SIZES: ", self.batch_sizes, " LEARNING RATES: ", self.learning_rates) start_total = time.time() for counter, epoch_value in enumerate(self.epochs): batch_sizes, number_of_batches = self.get_batch_sizes(counter, data_sets) for e in range(1, epoch_value + 1): start_epoch = time.time() data_sets = self.shuffle_data_and_reset_epoch_losses(data_sets) for b in range(number_of_batches): batches = self.get_batches(data_sets, b, batch_sizes) tf_dict = self.get_feed_dict(batches, counter) _, batch_losses = self.sess.run([self.minimize_op, self.loss_tensor_list], tf_dict) self.assign_batch_losses(batch_losses) self.append_loss_and_activation_coeff_history() self.save_model_checkpoint(self.epoch_loss[self.loss_list[0]], e, counter) self.print_info(e, self.epochs[counter], time.time() - start_epoch) self.print("\nTotal training time: %5.3fs" % (time.time() - start_total)) self.logger.handlers[1].close() def check_matching_keys(self, data_sets): for key1, key2 in zip(data_sets, self.placeholders): assert key1 == key2, "Data set key %s does not match placeholder key %s" % (key1, key2) def print_point_distribution(self, data_sets): no_points = 0 for key in data_sets: no_points += data_sets[key].shape[0] self.print("Training data %10s shape: %s" %(key, data_sets[key].shape)) self.print("Total number of points %d" % no_points) def shuffle_data_and_reset_epoch_losses(self, data_sets): for key in data_sets: length = len(data_sets[key]) shuffled_indices = np.random.choice(length, length, replace=False) data_sets[key] = pd.DataFrame(data=data_sets[key].to_numpy()[shuffled_indices,:], columns=data_sets[key].columns) for key in self.epoch_loss: self.epoch_loss[key] = 0 return data_sets def get_batches(self, data, b, batch_sizes): batches = dict.fromkeys(data.keys(), 0) for key in data: batches[key] = data[key][b*batch_sizes[key]:(b+1)*batch_sizes[key]] return batches def assign_batch_losses(self, batch_losses): for loss_values, key in zip(batch_losses, self.epoch_loss): self.epoch_loss[key] += loss_values def append_loss_and_activation_coeff_history(self): for key in self.loss_history: self.loss_history[key].append(self.epoch_loss[key]) for key, value in self.ad_act_coeff.items(): self.ad_act_coeff_history[key].append(self.sess.run(value)) def get_feed_dict(self, batches , counter): tf_dict = {self.learning_rate_opt: self.learning_rates[counter]} feed_dicts = [] for i, key in enumerate(self.placeholders): feed_dicts.append(dict.fromkeys(self.placeholders[key], 0)) for placeholder, column_name in zip(self.placeholders[key], batches[key].columns): assert placeholder.name[:-2] == column_name, "Placeholder %s does not match column %s in data %s!" % (placeholder.name[:-2], column_name, key) feed_dicts[i][placeholder] = np.transpose(np.atleast_2d(batches[key][column_name].to_numpy())) for dicts in feed_dicts: tf_dict.update(dicts) return tf_dict def save_model_checkpoint(self, loss, epoch, counter): ''' Saves the following files in self.dirname when a checkpoint epoch is reached: 1) architecture (.json) 2) weights (.h5) 3) optimizer state, loss history, adaptive activation coefficient history (.mat) These files may be used to restart a training run from checkpoint ''' if loss < self.epoch_loss_checkpoints and not (epoch)%self.checkpoint_interval: for file in glob.glob(os.path.join(self.dirname, "*")): if file.endswith("json") or file.endswith("h5") or file.endswith("mat"): os.remove(file) writeToJSONFile(self.dirname, "loss_%.4e_architecture" % (loss), self.model.to_json()) data = dict(loss_history=self.loss_history, ad_act_coeff_history=self.ad_act_coeff_history, optimizer_state=self.sess.run(self.optimizer.variables()), ad_act_coeff=self.sess.run(self.ad_act_coeff), epoch=epoch, learning_rate=self.learning_rates[counter]) scipy.io.savemat(os.path.join(self.dirname, "loss_%.4e_variables.mat") % (loss), data) self.model.save_weights(os.path.join(self.dirname, "loss_%.4e_weights.h5" % (loss))) self.epoch_loss_checkpoints = loss def print_info(self, current_epoch, epochs, time_for_epoch): if current_epoch == 1: # skipping first epoch, because it takes way longer self.mean_epoch_time = 0 else: self.mean_epoch_time = self.mean_epoch_time*(current_epoch-2)/(current_epoch-1) + time_for_epoch/(current_epoch-1) string = ["Epoch: %5d/%d - %7.2fms - avg: %7.2fms" % (current_epoch, epochs, time_for_epoch*1e3, self.mean_epoch_time*1e3)] for key, value in self.epoch_loss.items(): string.append(" - %s: %.4e" % (key, value)) for key, act_coeff in self.ad_act_coeff.items(): string.append(" - %s: %.4e" % (key, self.sess.run(act_coeff))) self.print(*string) def get_batch_sizes(self, counter, data_sets): number_of_samples = sum([len(data_sets[key]) for key in data_sets]) batch_sizes_datasets = dict.fromkeys(data_sets.keys(), 0) if self.batch_sizes[counter] >= number_of_samples: number_of_batches = 1 for key in data_sets: batch_sizes_datasets[key] = len(data_sets[key]) self.print("Batch size is larger equal the amount of training samples, thus going full batch mode") self.print("Total batch size: ", number_of_samples, " - ", "Batch sizes: ", batch_sizes_datasets, " - ", "learning rate: ", self.learning_rates[counter], "\n") else: number_of_batches = math.ceil(number_of_samples/self.batch_sizes[counter]) batch_percentages = dict.fromkeys(data_sets.keys(), 0) print_batches = dict.fromkeys(data_sets.keys(), "") for key in data_sets: batch_percentages[key] = len(data_sets[key])/number_of_samples batch_sizes_datasets[key] = math.ceil(self.batch_sizes[counter]*batch_percentages[key]) print_batches[key] = "%d/%d" % (batch_sizes_datasets[key], 0 if batch_sizes_datasets[key] == 0 else len(data_sets[key])%batch_sizes_datasets[key]) total_batch_size = sum([batch_sizes_datasets[key] for key in batch_sizes_datasets]) self.print("\nTotal batch size: ", total_batch_size, " - ", "number of batches: ", number_of_batches, " - ", "Batch sizes: ", print_batches, " - ", "learning rate: ", self.learning_rates[counter]) for key in data_sets: if len(data_sets[key]) == 0: continue assert (number_of_batches - 1) * batch_sizes_datasets[key] < len(data_sets[key]), "The specified batch size of %d will lead to empty batches with the present batch ratio, increase the batch size!" % (self.batch_sizes[counter]) return batch_sizes_datasets, number_of_batches def print(self, *args): for word in args: if len(args) == 1: self.logger.info(word) elif word != args[-1]: for handler in self.logger.handlers: handler.terminator = "" if type(word) == float or type(word) == np.float64 or type(word) == np.float32: self.logger.info("%.4e" % (word)) else: self.logger.info(word) else: for handler in self.logger.handlers: handler.terminator = "\n" if type(word) == float or type(word) == np.float64 or type(word) == np.float32: self.logger.info("%.4e" % (word)) else: self.logger.info(word) def compute_batch_size(training_data, number_of_batches): ''' Computes the batch size from number of batches and amount of training samples ''' number_of_samples = sum([len(training_data[key]) for key in training_data]) return math.ceil(number_of_samples/number_of_batches) def main(): ''' This scripts trains a PINN for the rising bubble case in <paper_cite_TBA>. The user may define the following: 1) Number of points for various losses (check function description) 2) The neural network architecture, i.e. number of hidden layers and the nodes in each hidden layer 3) The training hyperparameters, i.e. number of epochs, batch size and learning rates ''' # SETTING UP SESSION sess = tf.Session() # PARAMETRS FOR THE TRAINING DATA - NUMBER OF POINTS (NOP) FOR VARIOUS LOSSES NOP_a = (500, 400) NOP_PDE = (400, 2000, 3000) NOP_north = (20, 20) NOP_south = (20, 20) NOP_east = (20, 20) NOP_west = (20, 20) training_data = get_training_data(NOP_a, NOP_PDE, NOP_north, NOP_south, NOP_east, NOP_west) # NEURAL NETWORK ARCHITECTURE dtype = tf.float32 no_layers = 8 hidden_layers = [350]*no_layers activation_functions = dict(tanh = range(1,no_layers+1)) # dict assigning layer activation function to layer number # ADAPIVE ACTIVATION COEFFICIENTS SETUP adaptive_activation_coeff = {"aac_1": range(1,no_layers+1)} # list shows corresponding layer numbers adaptive_activation_init = {"aac_1": 0.1} adaptive_activation_n = [10]*no_layers # prefactor for activation function use_ad_act = False # PHYSICAL PARAMETERS mu = [1.0, 10.0] sigma = 24.5 g = -0.98 rho = [100, 1000] u_ref = 1.0 L_ref = 0.25 # HYPERPARAMETERS FOR TRAINING loss_weights_A = [1.0] loss_weights_PDE = [1.0, 10.0, 10.0, 1.0] epochs = [5000]*5 number_of_batches = 20 batch_sizes = [compute_batch_size(training_data, number_of_batches)]*5 learning_rates = [1e-4, 5e-5, 1e-5, 5e-6, 1e-6] checkpoint_interval = 100 # INSTANTIATE PINN PINN = TwoPhasePinn(sess, dtype, hidden_layers, activation_functions, adaptive_activation_coeff, adaptive_activation_n, adaptive_activation_init, use_ad_act, loss_weights_A, loss_weights_PDE, mu, sigma, g, rho, u_ref, L_ref, checkpoint_interval, epochs, batch_sizes, learning_rates) # TRAINING PINN.train(training_data) if __name__ == "__main__": main()

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import sys sys.path.append("../utilities") import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID" GPU_ID = "0" os.environ["CUDA_VISIBLE_DEVICES"]= GPU_ID import tensorflow as tf tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR) from tensorflow.keras import backend as K import numpy as np import pandas as pd import scipy.io from generate_points import * from utilities import * import time import math import glob from datetime import datetime import shutil import logging np.random.seed(1234) tf.set_random_seed(1234) class TwoPhasePinn: def __init__(self, sess, dtype, hidden_layers, activation_functions, adaptive_activation_coeff, adaptive_activation_n, adaptive_activation_init, use_ad_act, loss_weights_A, loss_weights_PDE, mu, sigma, g, rho, u_ref, L_ref, checkpoint_interval, epochs, batch_sizes, learning_rates): self.dirname, logpath = self.make_output_dir() self.logger = self.get_logger(logpath) self.mu1 = mu[0] self.mu2 = mu[1] self.sigma = sigma self.g = g self.rho1 = rho[0] self.rho2 = rho[1] self.U_ref = u_ref self.L_ref = L_ref self.epoch_loss_checkpoints = 1e10 self.checkpoint_interval = checkpoint_interval self.mean_epoch_time = 0 self.learning_rates = learning_rates self.epochs = epochs self.batch_sizes = batch_sizes self.sess = sess K.set_session(self.sess) self.print("Building Computational Graph") x_A = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_A") y_A = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_A") t_A = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_A") a_A = tf.placeholder(dtype=dtype, shape=[None, 1], name="a_A") x_N = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_N") y_N = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_N") t_N = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_N") p_N = tf.placeholder(dtype=dtype, shape=[None, 1], name="p_N") x_E = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_E") y_E = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_E") x_W = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_W") y_W = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_W") t_EW = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_EW") x_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_NSEW") y_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_NSEW") t_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_NSEW") u_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="u_NSEW") v_NSEW = tf.placeholder(dtype=dtype, shape=[None, 1], name="v_NSEW") x_PDE = tf.placeholder(dtype=dtype, shape=[None, 1], name="x_PDE") y_PDE = tf.placeholder(dtype=dtype, shape=[None, 1], name="y_PDE") t_PDE = tf.placeholder(dtype=dtype, shape=[None, 1], name="t_PDE") f_PDE = tf.placeholder(dtype=dtype, shape=[None, 1], name="f_PDE") self.learning_rate_opt = tf.placeholder(dtype=dtype, shape=[], name="learning_rate") data_set_names = ["A", "PDE", "N", "EW", "NSEW"] self.placeholders = dict((name, []) for name in data_set_names) self.placeholders["A"].extend([x_A, y_A, t_A, a_A]) self.placeholders["PDE"].extend([x_PDE, y_PDE, t_PDE, f_PDE]) self.placeholders["N"].extend([x_N, y_N, t_N, p_N]) self.placeholders["EW"].extend([x_E, y_E, x_W, y_W, t_EW]) self.placeholders["NSEW"].extend([x_NSEW, y_NSEW, t_NSEW, u_NSEW, v_NSEW]) self.sanity_check_activation_functions(activation_functions, adaptive_activation_coeff, adaptive_activation_n, adaptive_activation_init, hidden_layers) self.ad_act_coeff = {} if use_ad_act: for key in adaptive_activation_coeff: initial_value = adaptive_activation_init[key] self.ad_act_coeff[key] = tf.Variable(initial_value, name=key) activation_functions_dict = self.get_activation_function_dict(activation_functions, adaptive_activation_coeff, adaptive_activation_n, hidden_layers, use_ad_act) outputs = ["output_u", "output_v", "output_p", "output_a"] activations_output = [None, None, "exponential", "sigmoid"] output_layer = list(zip(outputs, activations_output)) nn = NNCreator(dtype) self.model = nn.get_model_dnn(3, hidden_layers, output_layer, activation_functions_dict, use_ad_act) output_tensors = self.model(tf.concat([x_A, y_A, t_A], 1)) loss_a_A = tf.reduce_mean(tf.square(a_A - output_tensors[3])) start = time.time() output_tensors = self.model(tf.concat([x_NSEW, y_NSEW, t_NSEW], 1)) loss_u_NSEW = tf.reduce_mean(tf.square(u_NSEW - output_tensors[0])) loss_v_NSEW = tf.reduce_mean(tf.square(v_NSEW - output_tensors[1])) loss_NSEW = tf.reduce_sum(tf.stack([loss_u_NSEW, loss_v_NSEW])) self.print(time.time()-start, "s") start = time.time() output_tensors = self.model(tf.concat([x_N, y_N, t_N], 1)) loss_p_N = tf.reduce_mean(tf.square(p_N - output_tensors[2])) self.print(time.time()-start, "s") start = time.time() output_east = self.model(tf.concat([x_E, y_E, t_EW], 1)) output_west = self.model(tf.concat([x_W, y_W, t_EW], 1)) loss_u_EW = tf.reduce_mean(tf.square(output_east[0] - output_west[0])) loss_v_EW = tf.reduce_mean(tf.square(output_east[1] - output_west[1])) loss_p_EW = tf.reduce_mean(tf.square(output_east[2] - output_west[2])) loss_EW = tf.reduce_sum(tf.stack([loss_u_EW, loss_v_EW, loss_p_EW])) self.print(time.time()-start, "s") loss_NSEW = tf.reduce_sum(tf.stack([loss_p_N, loss_EW, loss_NSEW])) start = time.time() PDE_tensors = self.PDE_caller(x_PDE, y_PDE, t_PDE) loss_PDE_m = tf.losses.mean_squared_error(f_PDE, PDE_tensors[0]) loss_PDE_u = tf.losses.mean_squared_error(f_PDE, PDE_tensors[1]) loss_PDE_v = tf.losses.mean_squared_error(f_PDE, PDE_tensors[2]) loss_PDE_a = tf.losses.mean_squared_error(f_PDE, PDE_tensors[3]) self.print(time.time()-start, "s") loss_PDE = tf.tensordot(tf.stack([loss_PDE_m, loss_PDE_u, loss_PDE_v, loss_PDE_a]), np.array(loss_weights_PDE).astype("float32"), 1) loss_complete = loss_a_A + loss_NSEW + loss_PDE start = time.time() self.optimizer = tf.train.AdamOptimizer(self.learning_rate_opt) self.minimize_op = self.optimizer.minimize(loss_complete) self.print(time.time()-start, "s") self.loss_tensor_list = [loss_complete, loss_a_A, loss_NSEW, loss_PDE_m, loss_PDE_u, loss_PDE_v, loss_PDE_a] self.loss_list = ["l", "a", "NSEW", "m", "u", "v", "PDE_a"] self.epoch_loss = dict.fromkeys(self.loss_list, 0) self.loss_history = dict((loss, []) for loss in self.loss_list) self.ad_act_coeff_history = dict((key, []) for key in self.ad_act_coeff) self.sess.run(tf.global_variables_initializer()) self.set_variables() self.model.save_weights(os.path.join(self.dirname, "Weights_loss_%.4e.h5" % (self.epoch_loss_checkpoints))) self.sess.graph.finalize() def make_output_dir(self): if not os.path.exists("checkpoints"): os.mkdir("checkpoints") dirname = os.path.abspath(os.path.join("checkpoints", datetime.now().strftime("%b-%d-%Y_%H-%M-%S"))) os.mkdir(dirname) shutil.copyfile(__file__, os.path.join(dirname, __file__)) shutil.copyfile("generate_points.py", os.path.join(dirname, "generate_points.py")) logpath = os.path.join(dirname, "output.log") return dirname, logpath def get_logger(self, logpath): logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) sh = logging.StreamHandler() sh.setLevel(logging.DEBUG) sh.setFormatter(logging.Formatter('%(message)s')) fh = logging.FileHandler(logpath) logger.addHandler(sh) logger.addHandler(fh) return logger def sanity_check_activation_functions(self, activation_functions, adaptive_activations, adaptive_activation_n, adaptive_activation_init, hidden_layers): no_layers = len(hidden_layers) check = 0 for key, value in list(adaptive_activations.items()): check += sum(value) assert no_layers*(no_layers+1)/2 == check, "Not every layer has been assigned with an adaptive activation coefficient unambiguously" check = 0 for key, value in list(activation_functions.items()): check += sum(value) assert no_layers*(no_layers+1)/2 == check, "Not every layer has been assigned with an activation function unambiguously" assert no_layers == len(adaptive_activation_n), "Not every layer has an adaptive activation precoefficient" assert adaptive_activation_init.keys() == adaptive_activations.keys(), "Not every adaptive activation coefficient has been assigned an initial value" def get_activation_function_dict(self, activation_functions, adaptive_activation_coeff, adaptive_activation_n, hidden_layers, use_ad_act): activation_functions_dict = dict((key, [0, 0, 0]) for key in range(1, len(hidden_layers) + 1)) for layer_no in activation_functions_dict: activation_functions_dict[layer_no][2] = adaptive_activation_n[layer_no-1] for func_name, layers in activation_functions.items(): if layer_no in layers: activation_functions_dict[layer_no][0] = func_name if use_ad_act: for coeff_name, layers in adaptive_activation_coeff.items(): if layer_no in layers: activation_functions_dict[layer_no][1] = self.ad_act_coeff[coeff_name] return activation_functions_dict def compute_gradients(self, x, y, t): u, v, p, a = self.model(tf.concat([x, y, t], 1)) u_x = tf.gradients(u, x)[0] u_y = tf.gradients(u, y)[0] u_t = tf.gradients(u, t)[0] u_xx = tf.gradients(u_x, x)[0] u_yy = tf.gradients(u_y, y)[0] v_x = tf.gradients(v, x)[0] v_y = tf.gradients(v, y)[0] v_t = tf.gradients(v, t)[0] v_xx = tf.gradients(v_x, x)[0] v_yy = tf.gradients(v_y, y)[0] p_x = tf.gradients(p, x)[0] p_y = tf.gradients(p, y)[0] a_x = tf.gradients(a, x)[0] a_y = tf.gradients(a, y)[0] a_t = tf.gradients(a, t)[0] a_xx = tf.gradients(a_x, x)[0] a_yy = tf.gradients(a_y, y)[0] a_xy = tf.gradients(a_x, y)[0] return [u, u_x, u_y, u_t, u_xx, u_yy], [v, v_x, v_y, v_t, v_xx, v_yy], [p, p_x, p_y], [a, a_x, a_y, a_t, a_xx, a_yy, a_xy] def PDE_caller(self, x, y, t): u_gradients, v_gradients, p_gradients, a_gradients = self.compute_gradients(x, y, t) u, u_x, u_y, u_t, u_xx, u_yy = u_gradients[:] v, v_x, v_y, v_t, v_xx, v_yy = v_gradients[:] p, p_x, p_y = p_gradients[:] a, a_x, a_y, a_t, a_xx, a_yy, a_xy = a_gradients[:] mu = self.mu2 + (self.mu1 - self.mu2) * a mu_x = (self.mu1 - self.mu2) * a_x mu_y = (self.mu1 - self.mu2) * a_y rho = self.rho2 + (self.rho1 - self.rho2) * a abs_interface_grad = tf.sqrt(tf.square(a_x) + tf.square(a_y) + np.finfo(float).eps) curvature = - ( (a_xx + a_yy)/abs_interface_grad - (a_x**2*a_xx + a_y**2*a_yy + 2*a_x*a_y*a_xy)/tf.pow(abs_interface_grad, 3) ) rho_ref = self.rho2 one_Re = mu/(rho_ref*self.U_ref*self.L_ref) one_Re_x = mu_x/(rho_ref*self.U_ref*self.L_ref) one_Re_y = mu_y/(rho_ref*self.U_ref*self.L_ref) one_We = self.sigma/(rho_ref*self.U_ref**2*self.L_ref) one_Fr = self.g*self.L_ref/self.U_ref**2 PDE_m = u_x + v_y PDE_a = a_t + u*a_x + v*a_y PDE_u = (u_t + u*u_x + v*u_y)*rho/rho_ref + p_x - one_We*curvature*a_x - one_Re*(u_xx + u_yy) - 2.0*one_Re_x*u_x - one_Re_y*(u_y + v_x) PDE_v = (v_t + u*v_x + v*v_y)*rho/rho_ref + p_y - one_We*curvature*a_y - one_Re*(v_xx + v_yy) - rho/rho_ref*one_Fr - 2.0*one_Re_y*v_y - one_Re_x*(u_y + v_x) return PDE_m, PDE_u, PDE_v, PDE_a def set_variables(self): for file in glob.glob("*loss*"): if file.endswith("h5"): self.model.load_weights(file) self.print("Loading weights from file", file) if file.endswith("mat"): matfile = scipy.io.loadmat(file, squeeze_me=True) self.print("Setting optimizer variables according to file", file) optimizer_state = matfile["optimizer_state"] optimizer_variables = self.optimizer.variables() assert len(optimizer_variables) == len(optimizer_state), "Loading optimizer state failed: Not as many optimizer states saved as required, check architecture/aac compatibility!" for i in range(0, len(optimizer_variables)): if optimizer_variables[i].shape == (1,): optimizer_state[i] = np.array([optimizer_state[i]]) if len(optimizer_variables[i].shape) == 2: if optimizer_variables[i].shape[1] == 1: optimizer_state[i] = optimizer_state[i].reshape(len(optimizer_state[i]),1) self.sess.run(optimizer_variables[i].assign(optimizer_state[i])) self.print("Setting adaptive activation coefficients according to file", file) ad_act_coeff = matfile["ad_act_coeff"] if len(self.ad_act_coeff) > 0: assert list(self.ad_act_coeff.keys()) == list(ad_act_coeff.dtype.names), "Loading adaptive activation coefficients failed: Restart coefficients %s do not match input %s" %(list(ad_act_coeff.dtype.names), list(self.ad_act_coeff.keys())) for key in self.ad_act_coeff: self.sess.run(self.ad_act_coeff[key].assign(float(ad_act_coeff[key]))) def train(self, data_sets): self.check_matching_keys(data_sets) self.print_point_distribution(data_sets) self.print("\nEPOCHS: ", self.epochs, " BATCH SIZES: ", self.batch_sizes, " LEARNING RATES: ", self.learning_rates) start_total = time.time() for counter, epoch_value in enumerate(self.epochs): batch_sizes, number_of_batches = self.get_batch_sizes(counter, data_sets) for e in range(1, epoch_value + 1): start_epoch = time.time() data_sets = self.shuffle_data_and_reset_epoch_losses(data_sets) for b in range(number_of_batches): batches = self.get_batches(data_sets, b, batch_sizes) tf_dict = self.get_feed_dict(batches, counter) _, batch_losses = self.sess.run([self.minimize_op, self.loss_tensor_list], tf_dict) self.assign_batch_losses(batch_losses) self.append_loss_and_activation_coeff_history() self.save_model_checkpoint(self.epoch_loss[self.loss_list[0]], e, counter) self.print_info(e, self.epochs[counter], time.time() - start_epoch) self.print("\nTotal training time: %5.3fs" % (time.time() - start_total)) self.logger.handlers[1].close() def check_matching_keys(self, data_sets): for key1, key2 in zip(data_sets, self.placeholders): assert key1 == key2, "Data set key %s does not match placeholder key %s" % (key1, key2) def print_point_distribution(self, data_sets): no_points = 0 for key in data_sets: no_points += data_sets[key].shape[0] self.print("Training data %10s shape: %s" %(key, data_sets[key].shape)) self.print("Total number of points %d" % no_points) def shuffle_data_and_reset_epoch_losses(self, data_sets): for key in data_sets: length = len(data_sets[key]) shuffled_indices = np.random.choice(length, length, replace=False) data_sets[key] = pd.DataFrame(data=data_sets[key].to_numpy()[shuffled_indices,:], columns=data_sets[key].columns) for key in self.epoch_loss: self.epoch_loss[key] = 0 return data_sets def get_batches(self, data, b, batch_sizes): batches = dict.fromkeys(data.keys(), 0) for key in data: batches[key] = data[key][b*batch_sizes[key]:(b+1)*batch_sizes[key]] return batches def assign_batch_losses(self, batch_losses): for loss_values, key in zip(batch_losses, self.epoch_loss): self.epoch_loss[key] += loss_values def append_loss_and_activation_coeff_history(self): for key in self.loss_history: self.loss_history[key].append(self.epoch_loss[key]) for key, value in self.ad_act_coeff.items(): self.ad_act_coeff_history[key].append(self.sess.run(value)) def get_feed_dict(self, batches , counter): tf_dict = {self.learning_rate_opt: self.learning_rates[counter]} feed_dicts = [] for i, key in enumerate(self.placeholders): feed_dicts.append(dict.fromkeys(self.placeholders[key], 0)) for placeholder, column_name in zip(self.placeholders[key], batches[key].columns): assert placeholder.name[:-2] == column_name, "Placeholder %s does not match column %s in data %s!" % (placeholder.name[:-2], column_name, key) feed_dicts[i][placeholder] = np.transpose(np.atleast_2d(batches[key][column_name].to_numpy())) for dicts in feed_dicts: tf_dict.update(dicts) return tf_dict def save_model_checkpoint(self, loss, epoch, counter): if loss < self.epoch_loss_checkpoints and not (epoch)%self.checkpoint_interval: for file in glob.glob(os.path.join(self.dirname, "*")): if file.endswith("json") or file.endswith("h5") or file.endswith("mat"): os.remove(file) writeToJSONFile(self.dirname, "loss_%.4e_architecture" % (loss), self.model.to_json()) data = dict(loss_history=self.loss_history, ad_act_coeff_history=self.ad_act_coeff_history, optimizer_state=self.sess.run(self.optimizer.variables()), ad_act_coeff=self.sess.run(self.ad_act_coeff), epoch=epoch, learning_rate=self.learning_rates[counter]) scipy.io.savemat(os.path.join(self.dirname, "loss_%.4e_variables.mat") % (loss), data) self.model.save_weights(os.path.join(self.dirname, "loss_%.4e_weights.h5" % (loss))) self.epoch_loss_checkpoints = loss def print_info(self, current_epoch, epochs, time_for_epoch): if current_epoch == 1: self.mean_epoch_time = 0 else: self.mean_epoch_time = self.mean_epoch_time*(current_epoch-2)/(current_epoch-1) + time_for_epoch/(current_epoch-1) string = ["Epoch: %5d/%d - %7.2fms - avg: %7.2fms" % (current_epoch, epochs, time_for_epoch*1e3, self.mean_epoch_time*1e3)] for key, value in self.epoch_loss.items(): string.append(" - %s: %.4e" % (key, value)) for key, act_coeff in self.ad_act_coeff.items(): string.append(" - %s: %.4e" % (key, self.sess.run(act_coeff))) self.print(*string) def get_batch_sizes(self, counter, data_sets): number_of_samples = sum([len(data_sets[key]) for key in data_sets]) batch_sizes_datasets = dict.fromkeys(data_sets.keys(), 0) if self.batch_sizes[counter] >= number_of_samples: number_of_batches = 1 for key in data_sets: batch_sizes_datasets[key] = len(data_sets[key]) self.print("Batch size is larger equal the amount of training samples, thus going full batch mode") self.print("Total batch size: ", number_of_samples, " - ", "Batch sizes: ", batch_sizes_datasets, " - ", "learning rate: ", self.learning_rates[counter], "\n") else: number_of_batches = math.ceil(number_of_samples/self.batch_sizes[counter]) batch_percentages = dict.fromkeys(data_sets.keys(), 0) print_batches = dict.fromkeys(data_sets.keys(), "") for key in data_sets: batch_percentages[key] = len(data_sets[key])/number_of_samples batch_sizes_datasets[key] = math.ceil(self.batch_sizes[counter]*batch_percentages[key]) print_batches[key] = "%d/%d" % (batch_sizes_datasets[key], 0 if batch_sizes_datasets[key] == 0 else len(data_sets[key])%batch_sizes_datasets[key]) total_batch_size = sum([batch_sizes_datasets[key] for key in batch_sizes_datasets]) self.print("\nTotal batch size: ", total_batch_size, " - ", "number of batches: ", number_of_batches, " - ", "Batch sizes: ", print_batches, " - ", "learning rate: ", self.learning_rates[counter]) for key in data_sets: if len(data_sets[key]) == 0: continue assert (number_of_batches - 1) * batch_sizes_datasets[key] < len(data_sets[key]), "The specified batch size of %d will lead to empty batches with the present batch ratio, increase the batch size!" % (self.batch_sizes[counter]) return batch_sizes_datasets, number_of_batches def print(self, *args): for word in args: if len(args) == 1: self.logger.info(word) elif word != args[-1]: for handler in self.logger.handlers: handler.terminator = "" if type(word) == float or type(word) == np.float64 or type(word) == np.float32: self.logger.info("%.4e" % (word)) else: self.logger.info(word) else: for handler in self.logger.handlers: handler.terminator = "\n" if type(word) == float or type(word) == np.float64 or type(word) == np.float32: self.logger.info("%.4e" % (word)) else: self.logger.info(word) def compute_batch_size(training_data, number_of_batches): number_of_samples = sum([len(training_data[key]) for key in training_data]) return math.ceil(number_of_samples/number_of_batches) def main(): sess = tf.Session() NOP_a = (500, 400) NOP_PDE = (400, 2000, 3000) NOP_north = (20, 20) NOP_south = (20, 20) NOP_east = (20, 20) NOP_west = (20, 20) training_data = get_training_data(NOP_a, NOP_PDE, NOP_north, NOP_south, NOP_east, NOP_west) dtype = tf.float32 no_layers = 8 hidden_layers = [350]*no_layers activation_functions = dict(tanh = range(1,no_layers+1)) adaptive_activation_coeff = {"aac_1": range(1,no_layers+1)} adaptive_activation_init = {"aac_1": 0.1} adaptive_activation_n = [10]*no_layers use_ad_act = False mu = [1.0, 10.0] sigma = 24.5 g = -0.98 rho = [100, 1000] u_ref = 1.0 L_ref = 0.25 loss_weights_A = [1.0] loss_weights_PDE = [1.0, 10.0, 10.0, 1.0] epochs = [5000]*5 number_of_batches = 20 batch_sizes = [compute_batch_size(training_data, number_of_batches)]*5 learning_rates = [1e-4, 5e-5, 1e-5, 5e-6, 1e-6] checkpoint_interval = 100 PINN = TwoPhasePinn(sess, dtype, hidden_layers, activation_functions, adaptive_activation_coeff, adaptive_activation_n, adaptive_activation_init, use_ad_act, loss_weights_A, loss_weights_PDE, mu, sigma, g, rho, u_ref, L_ref, checkpoint_interval, epochs, batch_sizes, learning_rates) PINN.train(training_data) if __name__ == "__main__": main()

true

1c2fb1a603f08b5ab90357ffe685fd73b30386e3

13,860

py

Python

tests/functional/test_sphinx_ext_autodoc.py

lipro/publishing-withsphinx

80d1f5d190e7123b73f1e1917f72ee80ad45221b

[ "MIT" ]

null

tests/functional/test_sphinx_ext_autodoc.py

lipro/publishing-withsphinx

80d1f5d190e7123b73f1e1917f72ee80ad45221b

[ "MIT" ]

28

2016-11-13T10:40:37.000Z

2019-02-28T17:24:15.000Z

tests/functional/test_sphinx_ext_autodoc.py

lipro/publishing-withsphinx

80d1f5d190e7123b73f1e1917f72ee80ad45221b

[ "MIT" ]

1

2016-11-15T19:34:56.000Z

# -*- coding: utf-8 -*- # # Copyright (c) 2016 Stephan Linz # # Permission is hereby granted, free of charge, to any person obtaining # a copy of this software and associated documentation files (the # "Software"), to deal in the Software without restriction, including # without limitation the rights to use, copy, modify, merge, publish, # distribute, sublicense, and/or sell copies of the Software, and to # permit persons to whom the Software is furnished to do so, subject to # the following conditions: # # The above copyright notice and this permission notice shall be # included in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, # EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF # MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. # IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY # CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, # TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # # How to write tests: http://docs.python-guide.org/en/latest/writing/tests/ # ''' test_sphinx_ext_autodoc ~~~~~~~~~~~~~~~~~~~~~~~ This module contains basic functional tests of the sphinx.ext.autodoc extension as part of the publishing.withsphinx package. :copyright: Copyright 2014-2016 by Li-Pro.Net, see AUTHORS. :license: MIT, see LICENSE for details. ''' from __future__ import absolute_import from tests.functional import fixtures import re class TestCaseSphinxExtAutoDoc(fixtures.TestCaseFunctionalPublishingSphinx): @fixtures.with_html_app( testroot='ext-autodoc', ) def test_build_html(self, app, status, warning): ''' FUNCTIONAL TEST: sphinx.ext.autodoc: can build html ''' app.builder.build_update() print(status.getvalue()) print(warning.getvalue()) p = fixtures.path(app.outdir / 'index.html') self.assertTrue(p.isfile(), 'missing file ' + p) c = p.read_text(encoding='utf-8') print(c) # check API auto-documentation r = re.compile( '(?ms)' + re.escape(r'<p>A pypi demonstration vehicle.</p>') + '.*' + re.escape(r'<p>This is something I want to say that is not in the docstring.</p>') + '.*' + re.escape(r'<em class="property">class </em>') + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_1.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'MyPublicClass') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r"<em>foo</em>, <em>bar='baz'</em>") + '.*' + re.escape(r'<p>We use this as a public class example class.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'get_foobar') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>foo</em>, <em>bar=True</em>') + '.*' + re.escape(r'<p>This gets the foobar</p>') + '.*' + re.escape(r'<p>This really should have a full function definition, but I am too lazy.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_1.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'public_fn_with_googley_docstring') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>name</em>, <em>state=None</em>') + '.*' + re.escape(r'<p>This function does something.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_1.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'public_fn_with_sphinxy_docstring') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>name</em>, <em>state=None</em>') + '.*' + re.escape(r'<p>This function does something.</p>') + '.*' + re.escape(r'<p>This is something I want to say that is not in the docstring.</p>') + '.*' + re.escape(r'<p>A very useful module indeed.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_2.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'public_fn_with_sphinxy_docstring') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>name</em>, <em>state=None</em>') + '.*' + re.escape(r'<p>This function does something.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_2.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'_private_fn_with_docstring') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r"<em>foo</em>, <em>bar='baz'</em>, <em>foobarbas=None</em>") + '.*' + re.escape(r'<p>I have a docstring, but ') + '.*' + re.escape(r'</p>') + '.*' + re.escape(r'<em class="property">class </em>') + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_2.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'MyPublicClass') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r"<em>foo</em>, <em>bar='baz'</em>") + '.*' + re.escape(r'<p>We use this as a public class example class.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'_get_baz') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>baz=None</em>') + '.*' + re.escape(r'<p>A private function to get baz.</p>') + '.*' + re.escape(r'<p>This really should have a full function definition, but I am too lazy.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'get_foobar') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>foo</em>, <em>bar=True</em>') + '.*' + re.escape(r'<p>This gets the foobar</p>') + '.*' + re.escape(r'<p>This really should have a full function definition, but I am too lazy.</p>') ) self.assertRegex(c, r) @fixtures.with_latex_app( testroot='ext-autodoc', ) def test_build_latex(self, app, status, warning): ''' FUNCTIONAL TEST: sphinx.ext.autodoc: can build latex ''' app.builder.build_update() print(status.getvalue()) print(warning.getvalue()) p = fixtures.path(app.outdir / 'index.tex') self.assertTrue(p.isfile(), 'missing file ' + p) c = p.read_text(encoding='utf-8') print(c) # check API auto-documentation r = re.compile( '(?ms)' + re.escape(r'A pypi demonstration vehicle.') + '.*' + re.escape(r'This is something I want to say that is not in the docstring.') + '.*' + re.escape(self.get_latex_code_strong() + r'{class }') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_1.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{MyPublicClass}') + '.*' + re.escape(r"{\emph{foo}, \emph{bar='baz'}}") + '.*' + re.escape(r'We use this as a public class example class.') + '.*' + re.escape(self.get_latex_bfcode() + r'{get\_foobar}') + '.*' + re.escape(r'{\emph{foo}, \emph{bar=True}}') + '.*' + re.escape(r'This gets the foobar') + '.*' + re.escape(r'This really should have a full function definition, but I am too lazy.') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_1.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{public\_fn\_with\_googley\_docstring}') + '.*' + re.escape(r'{\emph{name}, \emph{state=None}}') + '.*' + re.escape(r'This function does something.') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_1.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{public\_fn\_with\_sphinxy\_docstring}') + '.*' + re.escape(r'{\emph{name}, \emph{state=None}}') + '.*' + re.escape(r'This function does something.') + '.*' + re.escape(r'This is something I want to say that is not in the docstring.') + '.*' + re.escape(r'A very useful module indeed.') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_2.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{public\_fn\_with\_sphinxy\_docstring}') + '.*' + re.escape(r'{\emph{name}, \emph{state=None}}') + '.*' + re.escape(r'This function does something.') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_2.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{\_private\_fn\_with\_docstring}') + '.*' + re.escape(r"{\emph{foo}, \emph{bar='baz'}, \emph{foobarbas=None}}") + '.*' + re.escape(r'I have a docstring, but ') + '.*' + re.escape(self.get_latex_code_strong() + r'{class }') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_2.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{MyPublicClass}') + '.*' + re.escape(r"{\emph{foo}, \emph{bar='baz'}}") + '.*' + re.escape(r'We use this as a public class example class.') + '.*' + re.escape(self.get_latex_bfcode() + r'{\_get\_baz}') + '.*' + re.escape(r'{\emph{baz=None}}') + '.*' + re.escape(r'A private function to get baz.') + '.*' + re.escape(r'This really should have a full function definition, but I am too lazy.') + '.*' + re.escape(self.get_latex_bfcode() + r'{get\_foobar}') + '.*' + re.escape(r'{\emph{foo}, \emph{bar=True}}') + '.*' + re.escape(r'This gets the foobar') + '.*' + re.escape(r'This really should have a full function definition, but I am too lazy.') ) self.assertRegex(c, r) @fixtures.with_text_app( testroot='ext-autodoc', ) def test_build_text(self, app, status, warning): ''' FUNCTIONAL TEST: sphinx.ext.autodoc: can build text ''' app.builder.build_update() print(status.getvalue()) print(warning.getvalue()) p = fixtures.path(app.outdir / 'index.txt') self.assertTrue(p.isfile(), 'missing file ' + p) c = p.read_text(encoding='utf-8') print(c) # check API auto-documentation r = re.compile( '(?ms)' + re.escape(r'A pypi demonstration vehicle.') + '.*' + re.escape(r'This is something I want to say that is not in the docstring.') + '.*' + re.escape(r"class an_example_pypi_project.useful_1.MyPublicClass(foo, bar='baz')") + '.*' + re.escape(r' We use this as a public class example class.') + '.*' + re.escape(r' get_foobar(foo, bar=True)') + '.*' + re.escape(r' This gets the foobar') + '.*' + re.escape(r' This really should have a full function definition, but I am too') + '.*' + re.escape(r' lazy.') + '.*' + re.escape(r'an_example_pypi_project.useful_1.public_fn_with_googley_docstring(name, state=None)') + '.*' + re.escape(r' This function does something.') + '.*' + re.escape(r'an_example_pypi_project.useful_1.public_fn_with_sphinxy_docstring(name, state=None)') + '.*' + re.escape(r' This function does something.') + '.*' + re.escape(r'This is something I want to say that is not in the docstring.') + '.*' + re.escape(r'A very useful module indeed.') + '.*' + re.escape(r'an_example_pypi_project.useful_2.public_fn_with_sphinxy_docstring(name, state=None)') + '.*' + re.escape(r' This function does something.') + '.*' + re.escape(r'an_example_pypi_project.useful_2._private_fn_with_docstring') + re.escape(r"(foo, bar='baz', foobarbas=None)") + '.*' + re.escape(r' I have a docstring, but ') + '.*' + re.escape(r"class an_example_pypi_project.useful_2.MyPublicClass(foo, bar='baz')") + '.*' + re.escape(r' We use this as a public class example class.') + '.*' + re.escape(r' _get_baz(baz=None)') + '.*' + re.escape(r' A private function to get baz.') + '.*' + re.escape(r' This really should have a full function definition, but I am too') + '.*' + re.escape(r' lazy.') + '.*' + re.escape(r' get_foobar(foo, bar=True)') + '.*' + re.escape(r' This gets the foobar') + '.*' + re.escape(r' This really should have a full function definition, but I am too') + '.*' + re.escape(r' lazy.') ) self.assertRegex(c, r) if __name__ == "__main__": fixtures.main()

56.803279

118

0.581457

from __future__ import absolute_import from tests.functional import fixtures import re class TestCaseSphinxExtAutoDoc(fixtures.TestCaseFunctionalPublishingSphinx): @fixtures.with_html_app( testroot='ext-autodoc', ) def test_build_html(self, app, status, warning): app.builder.build_update() print(status.getvalue()) print(warning.getvalue()) p = fixtures.path(app.outdir / 'index.html') self.assertTrue(p.isfile(), 'missing file ' + p) c = p.read_text(encoding='utf-8') print(c) r = re.compile( '(?ms)' + re.escape(r'<p>A pypi demonstration vehicle.</p>') + '.*' + re.escape(r'<p>This is something I want to say that is not in the docstring.</p>') + '.*' + re.escape(r'<em class="property">class </em>') + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_1.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'MyPublicClass') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r"<em>foo</em>, <em>bar='baz'</em>") + '.*' + re.escape(r'<p>We use this as a public class example class.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'get_foobar') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>foo</em>, <em>bar=True</em>') + '.*' + re.escape(r'<p>This gets the foobar</p>') + '.*' + re.escape(r'<p>This really should have a full function definition, but I am too lazy.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_1.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'public_fn_with_googley_docstring') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>name</em>, <em>state=None</em>') + '.*' + re.escape(r'<p>This function does something.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_1.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'public_fn_with_sphinxy_docstring') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>name</em>, <em>state=None</em>') + '.*' + re.escape(r'<p>This function does something.</p>') + '.*' + re.escape(r'<p>This is something I want to say that is not in the docstring.</p>') + '.*' + re.escape(r'<p>A very useful module indeed.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_2.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'public_fn_with_sphinxy_docstring') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>name</em>, <em>state=None</em>') + '.*' + re.escape(r'<p>This function does something.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_2.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'_private_fn_with_docstring') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r"<em>foo</em>, <em>bar='baz'</em>, <em>foobarbas=None</em>") + '.*' + re.escape(r'<p>I have a docstring, but ') + '.*' + re.escape(r'</p>') + '.*' + re.escape(r'<em class="property">class </em>') + re.escape(self.get_html_code(args=' class="descclassname"')) + re.escape(r'an_example_pypi_project.useful_2.') + re.escape(self.get_html_code(close=True)) + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'MyPublicClass') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r"<em>foo</em>, <em>bar='baz'</em>") + '.*' + re.escape(r'<p>We use this as a public class example class.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'_get_baz') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>baz=None</em>') + '.*' + re.escape(r'<p>A private function to get baz.</p>') + '.*' + re.escape(r'<p>This really should have a full function definition, but I am too lazy.</p>') + '.*' + re.escape(self.get_html_code(args=' class="descname"')) + re.escape(r'get_foobar') + re.escape(self.get_html_code(close=True)) + '.*' + re.escape(r'<em>foo</em>, <em>bar=True</em>') + '.*' + re.escape(r'<p>This gets the foobar</p>') + '.*' + re.escape(r'<p>This really should have a full function definition, but I am too lazy.</p>') ) self.assertRegex(c, r) @fixtures.with_latex_app( testroot='ext-autodoc', ) def test_build_latex(self, app, status, warning): app.builder.build_update() print(status.getvalue()) print(warning.getvalue()) p = fixtures.path(app.outdir / 'index.tex') self.assertTrue(p.isfile(), 'missing file ' + p) c = p.read_text(encoding='utf-8') print(c) r = re.compile( '(?ms)' + re.escape(r'A pypi demonstration vehicle.') + '.*' + re.escape(r'This is something I want to say that is not in the docstring.') + '.*' + re.escape(self.get_latex_code_strong() + r'{class }') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_1.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{MyPublicClass}') + '.*' + re.escape(r"{\emph{foo}, \emph{bar='baz'}}") + '.*' + re.escape(r'We use this as a public class example class.') + '.*' + re.escape(self.get_latex_bfcode() + r'{get\_foobar}') + '.*' + re.escape(r'{\emph{foo}, \emph{bar=True}}') + '.*' + re.escape(r'This gets the foobar') + '.*' + re.escape(r'This really should have a full function definition, but I am too lazy.') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_1.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{public\_fn\_with\_googley\_docstring}') + '.*' + re.escape(r'{\emph{name}, \emph{state=None}}') + '.*' + re.escape(r'This function does something.') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_1.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{public\_fn\_with\_sphinxy\_docstring}') + '.*' + re.escape(r'{\emph{name}, \emph{state=None}}') + '.*' + re.escape(r'This function does something.') + '.*' + re.escape(r'This is something I want to say that is not in the docstring.') + '.*' + re.escape(r'A very useful module indeed.') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_2.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{public\_fn\_with\_sphinxy\_docstring}') + '.*' + re.escape(r'{\emph{name}, \emph{state=None}}') + '.*' + re.escape(r'This function does something.') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_2.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{\_private\_fn\_with\_docstring}') + '.*' + re.escape(r"{\emph{foo}, \emph{bar='baz'}, \emph{foobarbas=None}}") + '.*' + re.escape(r'I have a docstring, but ') + '.*' + re.escape(self.get_latex_code_strong() + r'{class }') + '.*' + re.escape(self.get_latex_code() + r'{an\_example\_pypi\_project.useful\_2.}') + '.*' + re.escape(self.get_latex_bfcode() + r'{MyPublicClass}') + '.*' + re.escape(r"{\emph{foo}, \emph{bar='baz'}}") + '.*' + re.escape(r'We use this as a public class example class.') + '.*' + re.escape(self.get_latex_bfcode() + r'{\_get\_baz}') + '.*' + re.escape(r'{\emph{baz=None}}') + '.*' + re.escape(r'A private function to get baz.') + '.*' + re.escape(r'This really should have a full function definition, but I am too lazy.') + '.*' + re.escape(self.get_latex_bfcode() + r'{get\_foobar}') + '.*' + re.escape(r'{\emph{foo}, \emph{bar=True}}') + '.*' + re.escape(r'This gets the foobar') + '.*' + re.escape(r'This really should have a full function definition, but I am too lazy.') ) self.assertRegex(c, r) @fixtures.with_text_app( testroot='ext-autodoc', ) def test_build_text(self, app, status, warning): app.builder.build_update() print(status.getvalue()) print(warning.getvalue()) p = fixtures.path(app.outdir / 'index.txt') self.assertTrue(p.isfile(), 'missing file ' + p) c = p.read_text(encoding='utf-8') print(c) r = re.compile( '(?ms)' + re.escape(r'A pypi demonstration vehicle.') + '.*' + re.escape(r'This is something I want to say that is not in the docstring.') + '.*' + re.escape(r"class an_example_pypi_project.useful_1.MyPublicClass(foo, bar='baz')") + '.*' + re.escape(r' We use this as a public class example class.') + '.*' + re.escape(r' get_foobar(foo, bar=True)') + '.*' + re.escape(r' This gets the foobar') + '.*' + re.escape(r' This really should have a full function definition, but I am too') + '.*' + re.escape(r' lazy.') + '.*' + re.escape(r'an_example_pypi_project.useful_1.public_fn_with_googley_docstring(name, state=None)') + '.*' + re.escape(r' This function does something.') + '.*' + re.escape(r'an_example_pypi_project.useful_1.public_fn_with_sphinxy_docstring(name, state=None)') + '.*' + re.escape(r' This function does something.') + '.*' + re.escape(r'This is something I want to say that is not in the docstring.') + '.*' + re.escape(r'A very useful module indeed.') + '.*' + re.escape(r'an_example_pypi_project.useful_2.public_fn_with_sphinxy_docstring(name, state=None)') + '.*' + re.escape(r' This function does something.') + '.*' + re.escape(r'an_example_pypi_project.useful_2._private_fn_with_docstring') + re.escape(r"(foo, bar='baz', foobarbas=None)") + '.*' + re.escape(r' I have a docstring, but ') + '.*' + re.escape(r"class an_example_pypi_project.useful_2.MyPublicClass(foo, bar='baz')") + '.*' + re.escape(r' We use this as a public class example class.') + '.*' + re.escape(r' _get_baz(baz=None)') + '.*' + re.escape(r' A private function to get baz.') + '.*' + re.escape(r' This really should have a full function definition, but I am too') + '.*' + re.escape(r' lazy.') + '.*' + re.escape(r' get_foobar(foo, bar=True)') + '.*' + re.escape(r' This gets the foobar') + '.*' + re.escape(r' This really should have a full function definition, but I am too') + '.*' + re.escape(r' lazy.') ) self.assertRegex(c, r) if __name__ == "__main__": fixtures.main()

true

1c2fb3146c4ad81957fc32a3a4da2d4c4935acf1

39,525

py

Python

astropy/io/fits/tests/test_hdulist.py

reidarkind/astropy

0d8e7dea86d39b9faad025708b852814c8d5d41a

[ "BSD-3-Clause" ]

445

2019-01-26T13:50:26.000Z

2022-03-18T05:17:38.000Z

Library/lib/python3.7/site-packages/astropy-4.0-py3.7-macosx-10.9-x86_64.egg/astropy/io/fits/tests/test_hdulist.py

gengyong/Carnets

8930a14f69360d4db115a85ff9e0f6efa80fa2e7

[ "BSD-3-Clause" ]

242

2019-01-29T15:48:27.000Z

2022-03-31T22:09:21.000Z

Library/lib/python3.7/site-packages/astropy-4.0-py3.7-macosx-10.9-x86_64.egg/astropy/io/fits/tests/test_hdulist.py

gengyong/Carnets

8930a14f69360d4db115a85ff9e0f6efa80fa2e7

[ "BSD-3-Clause" ]

31

2019-03-10T09:51:27.000Z

2022-02-14T23:11:12.000Z

# Licensed under a 3-clause BSD style license - see PYFITS.rst import glob import io import os import sys import copy import subprocess import pytest import numpy as np from astropy.io.fits.verify import VerifyError from astropy.io import fits from astropy.tests.helper import raises, catch_warnings, ignore_warnings from astropy.utils.exceptions import AstropyUserWarning, AstropyDeprecationWarning from . import FitsTestCase class TestHDUListFunctions(FitsTestCase): def test_update_name(self): with fits.open(self.data('o4sp040b0_raw.fits')) as hdul: hdul[4].name = 'Jim' hdul[4].ver = 9 assert hdul[('JIM', 9)].header['extname'] == 'JIM' def test_hdu_file_bytes(self): with fits.open(self.data('checksum.fits')) as hdul: res = hdul[0].filebytes() assert res == 11520 res = hdul[1].filebytes() assert res == 8640 def test_hdulist_file_info(self): def test_fileinfo(**kwargs): assert res['datSpan'] == kwargs.get('datSpan', 2880) assert res['resized'] == kwargs.get('resized', False) assert res['filename'] == self.data('checksum.fits') assert res['datLoc'] == kwargs.get('datLoc', 8640) assert res['hdrLoc'] == kwargs.get('hdrLoc', 0) assert res['filemode'] == 'readonly' with fits.open(self.data('checksum.fits')) as hdul: res = hdul.fileinfo(0) res = hdul.fileinfo(1) test_fileinfo(datLoc=17280, hdrLoc=11520) hdu = fits.ImageHDU(data=hdul[0].data) hdul.insert(1, hdu) res = hdul.fileinfo(0) test_fileinfo(resized=True) res = hdul.fileinfo(1) test_fileinfo(datSpan=None, resized=True, datLoc=None, hdrLoc=None) res = hdul.fileinfo(2) test_fileinfo(resized=1, datLoc=17280, hdrLoc=11520) def test_create_from_multiple_primary(self): """ Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/145 Ensure that a validation error occurs when saving an HDUList containing multiple PrimaryHDUs. """ hdul = fits.HDUList([fits.PrimaryHDU(), fits.PrimaryHDU()]) pytest.raises(VerifyError, hdul.writeto, self.temp('temp.fits'), output_verify='exception') def test_append_primary_to_empty_list(self): # Tests appending a Simple PrimaryHDU to an empty HDUList. hdul = fits.HDUList() hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.append(hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_extension_to_empty_list(self): """Tests appending a Simple ImageHDU to an empty HDUList.""" hdul = fits.HDUList() hdu = fits.ImageHDU(np.arange(100, dtype=np.int32)) hdul.append(hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_table_extension_to_empty_list(self): """Tests appending a Simple Table ExtensionHDU to a empty HDUList.""" hdul = fits.HDUList() with fits.open(self.data('tb.fits')) as hdul1: hdul.append(hdul1[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_groupshdu_to_empty_list(self): """Tests appending a Simple GroupsHDU to an empty HDUList.""" hdul = fits.HDUList() hdu = fits.GroupsHDU() hdul.append(hdu) info = [(0, 'PRIMARY', 1, 'GroupsHDU', 8, (), '', '1 Groups 0 Parameters')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_primary_to_non_empty_list(self): """Tests appending a Simple PrimaryHDU to a non-empty HDUList.""" with fits.open(self.data('arange.fits')) as hdul: hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.append(hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 7, (11, 10, 7), 'int32', ''), (1, '', 1, 'ImageHDU', 6, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_extension_to_non_empty_list(self): """Tests appending a Simple ExtensionHDU to a non-empty HDUList.""" with fits.open(self.data('tb.fits')) as hdul: hdul.append(hdul[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 11, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', ''), (2, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info @raises(ValueError) def test_append_groupshdu_to_non_empty_list(self): """Tests appending a Simple GroupsHDU to an empty HDUList.""" hdul = fits.HDUList() hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.append(hdu) hdu = fits.GroupsHDU() hdul.append(hdu) def test_insert_primary_to_empty_list(self): """Tests inserting a Simple PrimaryHDU to an empty HDUList.""" hdul = fits.HDUList() hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.insert(0, hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_extension_to_empty_list(self): """Tests inserting a Simple ImageHDU to an empty HDUList.""" hdul = fits.HDUList() hdu = fits.ImageHDU(np.arange(100, dtype=np.int32)) hdul.insert(0, hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_table_extension_to_empty_list(self): """Tests inserting a Simple Table ExtensionHDU to a empty HDUList.""" hdul = fits.HDUList() with fits.open(self.data('tb.fits')) as hdul1: hdul.insert(0, hdul1[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_groupshdu_to_empty_list(self): """Tests inserting a Simple GroupsHDU to an empty HDUList.""" hdul = fits.HDUList() hdu = fits.GroupsHDU() hdul.insert(0, hdu) info = [(0, 'PRIMARY', 1, 'GroupsHDU', 8, (), '', '1 Groups 0 Parameters')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_primary_to_non_empty_list(self): """Tests inserting a Simple PrimaryHDU to a non-empty HDUList.""" with fits.open(self.data('arange.fits')) as hdul: hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.insert(1, hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 7, (11, 10, 7), 'int32', ''), (1, '', 1, 'ImageHDU', 6, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_extension_to_non_empty_list(self): """Tests inserting a Simple ExtensionHDU to a non-empty HDUList.""" with fits.open(self.data('tb.fits')) as hdul: hdul.insert(1, hdul[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 11, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', ''), (2, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_groupshdu_to_non_empty_list(self): """Tests inserting a Simple GroupsHDU to an empty HDUList.""" hdul = fits.HDUList() hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.insert(0, hdu) hdu = fits.GroupsHDU() with pytest.raises(ValueError): hdul.insert(1, hdu) info = [(0, 'PRIMARY', 1, 'GroupsHDU', 8, (), '', '1 Groups 0 Parameters'), (1, '', 1, 'ImageHDU', 6, (100,), 'int32', '')] hdul.insert(0, hdu) assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info @raises(ValueError) def test_insert_groupshdu_to_begin_of_hdulist_with_groupshdu(self): """ Tests inserting a Simple GroupsHDU to the beginning of an HDUList that that already contains a GroupsHDU. """ hdul = fits.HDUList() hdu = fits.GroupsHDU() hdul.insert(0, hdu) hdul.insert(0, hdu) def test_insert_extension_to_primary_in_non_empty_list(self): # Tests inserting a Simple ExtensionHDU to a non-empty HDUList. with fits.open(self.data('tb.fits')) as hdul: hdul.insert(0, hdul[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', ''), (2, '', 1, 'ImageHDU', 12, (), '', ''), (3, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_image_extension_to_primary_in_non_empty_list(self): """ Tests inserting a Simple Image ExtensionHDU to a non-empty HDUList as the primary HDU. """ with fits.open(self.data('tb.fits')) as hdul: hdu = fits.ImageHDU(np.arange(100, dtype=np.int32)) hdul.insert(0, hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', ''), (1, '', 1, 'ImageHDU', 12, (), '', ''), (2, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_filename(self): """Tests the HDUList filename method.""" with fits.open(self.data('tb.fits')) as hdul: name = hdul.filename() assert name == self.data('tb.fits') def test_file_like(self): """ Tests the use of a file like object with no tell or seek methods in HDUList.writeto(), HDULIST.flush() or astropy.io.fits.writeto() """ hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul = fits.HDUList() hdul.append(hdu) tmpfile = open(self.temp('tmpfile.fits'), 'wb') hdul.writeto(tmpfile) tmpfile.close() info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert fits.info(self.temp('tmpfile.fits'), output=False) == info def test_file_like_2(self): hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) tmpfile = open(self.temp('tmpfile.fits'), 'wb') hdul = fits.open(tmpfile, mode='ostream') hdul.append(hdu) hdul.flush() tmpfile.close() hdul.close() info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert fits.info(self.temp('tmpfile.fits'), output=False) == info def test_file_like_3(self): tmpfile = open(self.temp('tmpfile.fits'), 'wb') fits.writeto(tmpfile, np.arange(100, dtype=np.int32)) tmpfile.close() info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert fits.info(self.temp('tmpfile.fits'), output=False) == info def test_shallow_copy(self): """ Tests that `HDUList.__copy__()` and `HDUList.copy()` return a shallow copy (regression test for #7211). """ n = np.arange(10.0) primary_hdu = fits.PrimaryHDU(n) hdu = fits.ImageHDU(n) hdul = fits.HDUList([primary_hdu, hdu]) for hdulcopy in (hdul.copy(), copy.copy(hdul)): assert isinstance(hdulcopy, fits.HDUList) assert hdulcopy is not hdul assert hdulcopy[0] is hdul[0] assert hdulcopy[1] is hdul[1] def test_deep_copy(self): """ Tests that `HDUList.__deepcopy__()` returns a deep copy. """ n = np.arange(10.0) primary_hdu = fits.PrimaryHDU(n) hdu = fits.ImageHDU(n) hdul = fits.HDUList([primary_hdu, hdu]) hdulcopy = copy.deepcopy(hdul) assert isinstance(hdulcopy, fits.HDUList) assert hdulcopy is not hdul for index in range(len(hdul)): assert hdulcopy[index] is not hdul[index] assert hdulcopy[index].header == hdul[index].header np.testing.assert_array_equal(hdulcopy[index].data, hdul[index].data) def test_new_hdu_extname(self): """ Tests that new extension HDUs that are added to an HDUList can be properly indexed by their EXTNAME/EXTVER (regression test for ticket:48). """ with fits.open(self.data('test0.fits')) as f: hdul = fits.HDUList() hdul.append(f[0].copy()) hdu = fits.ImageHDU(header=f[1].header) hdul.append(hdu) assert hdul[1].header['EXTNAME'] == 'SCI' assert hdul[1].header['EXTVER'] == 1 assert hdul.index_of(('SCI', 1)) == 1 assert hdul.index_of(hdu) == len(hdul) - 1 def test_update_filelike(self): """Test opening a file-like object in update mode and resizing the HDU. """ sf = io.BytesIO() arr = np.zeros((100, 100)) hdu = fits.PrimaryHDU(data=arr) hdu.writeto(sf) sf.seek(0) arr = np.zeros((200, 200)) hdul = fits.open(sf, mode='update') hdul[0].data = arr hdul.flush() sf.seek(0) hdul = fits.open(sf) assert len(hdul) == 1 assert (hdul[0].data == arr).all() def test_flush_readonly(self): """Test flushing changes to a file opened in a read only mode.""" oldmtime = os.stat(self.data('test0.fits')).st_mtime hdul = fits.open(self.data('test0.fits')) hdul[0].header['FOO'] = 'BAR' with catch_warnings(AstropyUserWarning) as w: hdul.flush() assert len(w) == 1 assert 'mode is not supported' in str(w[0].message) assert oldmtime == os.stat(self.data('test0.fits')).st_mtime def test_fix_extend_keyword(self): hdul = fits.HDUList() hdul.append(fits.PrimaryHDU()) hdul.append(fits.ImageHDU()) del hdul[0].header['EXTEND'] hdul.verify('silentfix') assert 'EXTEND' in hdul[0].header assert hdul[0].header['EXTEND'] is True def test_fix_malformed_naxisj(self): """ Tests that malformed NAXISj values are fixed sensibly. """ hdu = fits.open(self.data('arange.fits')) # Malform NAXISj header data hdu[0].header['NAXIS1'] = 11.0 hdu[0].header['NAXIS2'] = '10.0' hdu[0].header['NAXIS3'] = '7' # Axes cache needs to be malformed as well hdu[0]._axes = [11.0, '10.0', '7'] # Perform verification including the fix hdu.verify('silentfix') # Check that malformed data was converted assert hdu[0].header['NAXIS1'] == 11 assert hdu[0].header['NAXIS2'] == 10 assert hdu[0].header['NAXIS3'] == 7 hdu.close() def test_fix_wellformed_naxisj(self): """ Tests that wellformed NAXISj values are not modified. """ hdu = fits.open(self.data('arange.fits')) # Fake new NAXISj header data hdu[0].header['NAXIS1'] = 768 hdu[0].header['NAXIS2'] = 64 hdu[0].header['NAXIS3'] = 8 # Axes cache needs to be faked as well hdu[0]._axes = [768, 64, 8] # Perform verification including the fix hdu.verify('silentfix') # Check that malformed data was converted assert hdu[0].header['NAXIS1'] == 768 assert hdu[0].header['NAXIS2'] == 64 assert hdu[0].header['NAXIS3'] == 8 hdu.close() def test_new_hdulist_extend_keyword(self): """Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/114 Tests that adding a PrimaryHDU to a new HDUList object updates the EXTEND keyword on that HDU. """ h0 = fits.Header() hdu = fits.PrimaryHDU(header=h0) sci = fits.ImageHDU(data=np.array(10)) image = fits.HDUList([hdu, sci]) image.writeto(self.temp('temp.fits')) assert 'EXTEND' in hdu.header assert hdu.header['EXTEND'] is True def test_replace_memmaped_array(self): # Copy the original before we modify it with fits.open(self.data('test0.fits')) as hdul: hdul.writeto(self.temp('temp.fits')) hdul = fits.open(self.temp('temp.fits'), mode='update', memmap=True) old_data = hdul[1].data.copy() hdul[1].data = hdul[1].data + 1 hdul.close() with fits.open(self.temp('temp.fits'), memmap=True) as hdul: assert ((old_data + 1) == hdul[1].data).all() def test_open_file_with_end_padding(self): """Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/106 Open files with end padding bytes. """ with fits.open(self.data('test0.fits'), do_not_scale_image_data=True) as hdul: info = hdul.info(output=False) hdul.writeto(self.temp('temp.fits')) with open(self.temp('temp.fits'), 'ab') as f: f.seek(0, os.SEEK_END) f.write(b'\0' * 2880) with ignore_warnings(): assert info == fits.info(self.temp('temp.fits'), output=False, do_not_scale_image_data=True) def test_open_file_with_bad_header_padding(self): """ Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/136 Open files with nulls for header block padding instead of spaces. """ a = np.arange(100).reshape(10, 10) hdu = fits.PrimaryHDU(data=a) hdu.writeto(self.temp('temp.fits')) # Figure out where the header padding begins and fill it with nulls end_card_pos = str(hdu.header).index('END' + ' ' * 77) padding_start = end_card_pos + 80 padding_len = 2880 - padding_start with open(self.temp('temp.fits'), 'r+b') as f: f.seek(padding_start) f.write('\0'.encode('ascii') * padding_len) with catch_warnings(AstropyUserWarning) as w: with fits.open(self.temp('temp.fits')) as hdul: assert (hdul[0].data == a).all() assert ('contains null bytes instead of spaces' in str(w[0].message)) assert len(w) == 1 assert len(hdul) == 1 assert str(hdul[0].header) == str(hdu.header) def test_update_with_truncated_header(self): """ Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/148 Test that saving an update where the header is shorter than the original header doesn't leave a stump from the old header in the file. """ data = np.arange(100) hdu = fits.PrimaryHDU(data=data) idx = 1 while len(hdu.header) < 34: hdu.header[f'TEST{idx}'] = idx idx += 1 hdu.writeto(self.temp('temp.fits'), checksum=True) with fits.open(self.temp('temp.fits'), mode='update') as hdul: # Modify the header, forcing it to be rewritten hdul[0].header['TEST1'] = 2 with fits.open(self.temp('temp.fits')) as hdul: assert (hdul[0].data == data).all() # This test used to fail on Windows - if it fails again in future, see # https://github.com/astropy/astropy/issues/5797 # The warning appears on Windows but cannot be explicitly caught. @pytest.mark.filterwarnings("ignore:Assigning the 'data' attribute is an " "inherently unsafe operation") def test_update_resized_header(self): """ Test saving updates to a file where the header is one block smaller than before, and in the case where the heade ris one block larger than before. """ data = np.arange(100) hdu = fits.PrimaryHDU(data=data) idx = 1 while len(str(hdu.header)) <= 2880: hdu.header[f'TEST{idx}'] = idx idx += 1 orig_header = hdu.header.copy() hdu.writeto(self.temp('temp.fits')) with fits.open(self.temp('temp.fits'), mode='update') as hdul: while len(str(hdul[0].header)) > 2880: del hdul[0].header[-1] with fits.open(self.temp('temp.fits')) as hdul: assert hdul[0].header == orig_header[:-1] assert (hdul[0].data == data).all() with fits.open(self.temp('temp.fits'), mode='update') as hdul: idx = 101 while len(str(hdul[0].header)) <= 2880 * 2: hdul[0].header[f'TEST{idx}'] = idx idx += 1 # Touch something in the data too so that it has to be rewritten hdul[0].data[0] = 27 with fits.open(self.temp('temp.fits')) as hdul: assert hdul[0].header[:-37] == orig_header[:-1] assert hdul[0].data[0] == 27 assert (hdul[0].data[1:] == data[1:]).all() def test_update_resized_header2(self): """ Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/150 This is similar to test_update_resized_header, but specifically tests a case of multiple consecutive flush() calls on the same HDUList object, where each flush() requires a resize. """ data1 = np.arange(100) data2 = np.arange(100) + 100 phdu = fits.PrimaryHDU(data=data1) hdu = fits.ImageHDU(data=data2) phdu.writeto(self.temp('temp.fits')) with fits.open(self.temp('temp.fits'), mode='append') as hdul: hdul.append(hdu) with fits.open(self.temp('temp.fits'), mode='update') as hdul: idx = 1 while len(str(hdul[0].header)) <= 2880 * 2: hdul[0].header[f'TEST{idx}'] = idx idx += 1 hdul.flush() hdul.append(hdu) with fits.open(self.temp('temp.fits')) as hdul: assert (hdul[0].data == data1).all() assert hdul[1].header == hdu.header assert (hdul[1].data == data2).all() assert (hdul[2].data == data2).all() @ignore_warnings() def test_hdul_fromstring(self): """ Test creating the HDUList structure in memory from a string containing an entire FITS file. This is similar to test_hdu_fromstring but for an entire multi-extension FITS file at once. """ # Tests HDUList.fromstring for all of Astropy's built in test files def test_fromstring(filename): with fits.open(filename) as hdul: orig_info = hdul.info(output=False) with open(filename, 'rb') as f: dat = f.read() hdul2 = fits.HDUList.fromstring(dat) assert orig_info == hdul2.info(output=False) for idx in range(len(hdul)): assert hdul[idx].header == hdul2[idx].header if hdul[idx].data is None or hdul2[idx].data is None: assert hdul[idx].data == hdul2[idx].data elif (hdul[idx].data.dtype.fields and hdul2[idx].data.dtype.fields): # Compare tables for n in hdul[idx].data.names: c1 = hdul[idx].data[n] c2 = hdul2[idx].data[n] assert (c1 == c2).all() elif (any(dim == 0 for dim in hdul[idx].data.shape) or any(dim == 0 for dim in hdul2[idx].data.shape)): # For some reason some combinations of Python and Numpy # on Windows result in MemoryErrors when trying to work # on memmap arrays with more than one dimension but # some dimensions of size zero, so include a special # case for that return hdul[idx].data.shape == hdul2[idx].data.shape else: np.testing.assert_array_equal(hdul[idx].data, hdul2[idx].data) for filename in glob.glob(os.path.join(self.data_dir, '*.fits')): if sys.platform == 'win32' and filename == 'zerowidth.fits': # Running this test on this file causes a crash in some # versions of Numpy on Windows. See ticket: # https://aeon.stsci.edu/ssb/trac/pyfits/ticket/174 continue elif filename.endswith('variable_length_table.fits'): # Comparing variable length arrays is non-trivial and thus # skipped at this point. # TODO: That's probably possible, so one could make it work. continue test_fromstring(filename) # Test that creating an HDUList from something silly raises a TypeError pytest.raises(TypeError, fits.HDUList.fromstring, ['a', 'b', 'c']) def test_save_backup(self): """Test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/121 Save backup of file before flushing changes. """ self.copy_file('scale.fits') with ignore_warnings(): with fits.open(self.temp('scale.fits'), mode='update', save_backup=True) as hdul: # Make some changes to the original file to force its header # and data to be rewritten hdul[0].header['TEST'] = 'TEST' hdul[0].data[0] = 0 assert os.path.exists(self.temp('scale.fits.bak')) with fits.open(self.data('scale.fits'), do_not_scale_image_data=True) as hdul1: with fits.open(self.temp('scale.fits.bak'), do_not_scale_image_data=True) as hdul2: assert hdul1[0].header == hdul2[0].header assert (hdul1[0].data == hdul2[0].data).all() with ignore_warnings(): with fits.open(self.temp('scale.fits'), mode='update', save_backup=True) as hdul: # One more time to see if multiple backups are made hdul[0].header['TEST2'] = 'TEST' hdul[0].data[0] = 1 assert os.path.exists(self.temp('scale.fits.bak')) assert os.path.exists(self.temp('scale.fits.bak.1')) def test_replace_mmap_data(self): """Regression test for https://github.com/spacetelescope/PyFITS/issues/25 Replacing the mmap'd data of one file with mmap'd data from a different file should work. """ arr_a = np.arange(10) arr_b = arr_a * 2 def test(mmap_a, mmap_b): hdu_a = fits.PrimaryHDU(data=arr_a) hdu_a.writeto(self.temp('test_a.fits'), overwrite=True) hdu_b = fits.PrimaryHDU(data=arr_b) hdu_b.writeto(self.temp('test_b.fits'), overwrite=True) with fits.open(self.temp('test_a.fits'), mode='update', memmap=mmap_a) as hdul_a: with fits.open(self.temp('test_b.fits'), memmap=mmap_b) as hdul_b: hdul_a[0].data = hdul_b[0].data with fits.open(self.temp('test_a.fits')) as hdul_a: assert np.all(hdul_a[0].data == arr_b) with ignore_warnings(): test(True, True) # Repeat the same test but this time don't mmap A test(False, True) # Finally, without mmaping B test(True, False) def test_replace_mmap_data_2(self): """Regression test for https://github.com/spacetelescope/PyFITS/issues/25 Replacing the mmap'd data of one file with mmap'd data from a different file should work. Like test_replace_mmap_data but with table data instead of image data. """ arr_a = np.arange(10) arr_b = arr_a * 2 def test(mmap_a, mmap_b): col_a = fits.Column(name='a', format='J', array=arr_a) col_b = fits.Column(name='b', format='J', array=arr_b) hdu_a = fits.BinTableHDU.from_columns([col_a]) hdu_a.writeto(self.temp('test_a.fits'), overwrite=True) hdu_b = fits.BinTableHDU.from_columns([col_b]) hdu_b.writeto(self.temp('test_b.fits'), overwrite=True) with fits.open(self.temp('test_a.fits'), mode='update', memmap=mmap_a) as hdul_a: with fits.open(self.temp('test_b.fits'), memmap=mmap_b) as hdul_b: hdul_a[1].data = hdul_b[1].data with fits.open(self.temp('test_a.fits')) as hdul_a: assert 'b' in hdul_a[1].columns.names assert 'a' not in hdul_a[1].columns.names assert np.all(hdul_a[1].data['b'] == arr_b) with ignore_warnings(): test(True, True) # Repeat the same test but this time don't mmap A test(False, True) # Finally, without mmaping B test(True, False) def test_extname_in_hdulist(self): """ Tests to make sure that the 'in' operator works. Regression test for https://github.com/astropy/astropy/issues/3060 """ with fits.open(self.data('o4sp040b0_raw.fits')) as hdulist: hdulist.append(fits.ImageHDU(name='a')) assert 'a' in hdulist assert 'A' in hdulist assert ('a', 1) in hdulist assert ('A', 1) in hdulist assert 'b' not in hdulist assert ('a', 2) not in hdulist assert ('b', 1) not in hdulist assert ('b', 2) not in hdulist assert hdulist[0] in hdulist assert fits.ImageHDU() not in hdulist def test_overwrite_vs_clobber(self): hdulist = fits.HDUList([fits.PrimaryHDU()]) hdulist.writeto(self.temp('test_overwrite.fits')) hdulist.writeto(self.temp('test_overwrite.fits'), overwrite=True) with catch_warnings(AstropyDeprecationWarning) as warning_lines: hdulist.writeto(self.temp('test_overwrite.fits'), clobber=True) assert warning_lines[0].category == AstropyDeprecationWarning assert (str(warning_lines[0].message) == '"clobber" was ' 'deprecated in version 2.0 and will be removed in a ' 'future version. Use argument "overwrite" instead.') def test_invalid_hdu_key_in_contains(self): """ Make sure invalid keys in the 'in' operator return False. Regression test for https://github.com/astropy/astropy/issues/5583 """ hdulist = fits.HDUList(fits.PrimaryHDU()) hdulist.append(fits.ImageHDU()) hdulist.append(fits.ImageHDU()) # A more or less random assortment of things which are not valid keys. bad_keys = [None, 3.5, {}] for key in bad_keys: assert not (key in hdulist) def test_iteration_of_lazy_loaded_hdulist(self): """ Regression test for https://github.com/astropy/astropy/issues/5585 """ hdulist = fits.HDUList(fits.PrimaryHDU()) hdulist.append(fits.ImageHDU(name='SCI')) hdulist.append(fits.ImageHDU(name='SCI')) hdulist.append(fits.ImageHDU(name='nada')) hdulist.append(fits.ImageHDU(name='SCI')) filename = self.temp('many_extension.fits') hdulist.writeto(filename) f = fits.open(filename) # Check that all extensions are read if f is not sliced all_exts = [ext for ext in f] assert len(all_exts) == 5 # Reload the file to ensure we are still lazy loading f.close() f = fits.open(filename) # Try a simple slice with no conditional on the ext. This is essentially # the reported failure. all_exts_but_zero = [ext for ext in f[1:]] assert len(all_exts_but_zero) == 4 # Reload the file to ensure we are still lazy loading f.close() f = fits.open(filename) # Check whether behavior is proper if the upper end of the slice is not # omitted. read_exts = [ext for ext in f[1:4] if ext.header['EXTNAME'] == 'SCI'] assert len(read_exts) == 2 f.close() def test_proper_error_raised_on_non_fits_file_with_unicode(self): """ Regression test for https://github.com/astropy/astropy/issues/5594 The failure shows up when (in python 3+) you try to open a file with unicode content that is not actually a FITS file. See: https://github.com/astropy/astropy/issues/5594#issuecomment-266583218 """ import codecs filename = self.temp('not-fits-with-unicode.fits') with codecs.open(filename, mode='w', encoding='utf=8') as f: f.write('Ce\xe7i ne marche pas') # This should raise an OSError because there is no end card. with pytest.raises(OSError): with pytest.warns(AstropyUserWarning, match=r'non-ASCII characters ' r'are present in the FITS file header'): fits.open(filename) def test_no_resource_warning_raised_on_non_fits_file(self): """ Regression test for https://github.com/astropy/astropy/issues/6168 The ResourceWarning shows up when (in python 3+) you try to open a non-FITS file when using a filename. """ # To avoid creating the file multiple times the tests are # all included in one test file. See the discussion to the # PR at https://github.com/astropy/astropy/issues/6168 # filename = self.temp('not-fits.fits') with open(filename, mode='w') as f: f.write('# header line\n') f.write('0.1 0.2\n') # Opening the file should raise an OSError however the file # is opened (there are two distinct code paths, depending on # whether ignore_missing_end is True or False). # # Explicit tests are added to make sure the file handle is not # closed when passed in to fits.open. In this case the ResourceWarning # was not raised, but a check is still included. # with catch_warnings(ResourceWarning) as ws: # Make sure that files opened by the user are not closed with open(filename, mode='rb') as f: with pytest.raises(OSError): fits.open(f, ignore_missing_end=False) assert not f.closed with open(filename, mode='rb') as f: with pytest.raises(OSError): fits.open(f, ignore_missing_end=True) assert not f.closed with pytest.raises(OSError): fits.open(filename, ignore_missing_end=False) with pytest.raises(OSError): fits.open(filename, ignore_missing_end=True) assert len(ws) == 0 def test_pop_with_lazy_load(self): filename = self.data('checksum.fits') with fits.open(filename) as hdul: # Try popping the hdulist before doing anything else. This makes sure # that https://github.com/astropy/astropy/issues/7185 is fixed. hdu = hdul.pop() assert len(hdul) == 1 # Read the file again and try popping from the beginning with fits.open(filename) as hdul2: hdu2 = hdul2.pop(0) assert len(hdul2) == 1 # Just a sanity check with fits.open(filename) as hdul3: assert len(hdul3) == 2 assert hdul3[0].header == hdu2.header assert hdul3[1].header == hdu.header def test_pop_extname(self): with fits.open(self.data('o4sp040b0_raw.fits')) as hdul: assert len(hdul) == 7 hdu1 = hdul[1] hdu4 = hdul[4] hdu_popped = hdul.pop(('SCI', 2)) assert len(hdul) == 6 assert hdu_popped is hdu4 hdu_popped = hdul.pop('SCI') assert len(hdul) == 5 assert hdu_popped is hdu1 # Skip due to https://github.com/astropy/astropy/issues/8916 @pytest.mark.skipif('sys.platform.startswith("win32")') def test_write_hdulist_to_stream(self): """ Unit test for https://github.com/astropy/astropy/issues/7435 to ensure that an HDUList can be written to a stream. """ data = np.array([[1, 2, 3], [4, 5, 6]]) hdu = fits.PrimaryHDU(data) hdulist = fits.HDUList([hdu]) with open(self.temp('test.fits'), 'wb') as fout: with subprocess.Popen(["cat"], stdin=subprocess.PIPE, stdout=fout) as p: hdulist.writeto(p.stdin)

37.287736

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import glob import io import os import sys import copy import subprocess import pytest import numpy as np from astropy.io.fits.verify import VerifyError from astropy.io import fits from astropy.tests.helper import raises, catch_warnings, ignore_warnings from astropy.utils.exceptions import AstropyUserWarning, AstropyDeprecationWarning from . import FitsTestCase class TestHDUListFunctions(FitsTestCase): def test_update_name(self): with fits.open(self.data('o4sp040b0_raw.fits')) as hdul: hdul[4].name = 'Jim' hdul[4].ver = 9 assert hdul[('JIM', 9)].header['extname'] == 'JIM' def test_hdu_file_bytes(self): with fits.open(self.data('checksum.fits')) as hdul: res = hdul[0].filebytes() assert res == 11520 res = hdul[1].filebytes() assert res == 8640 def test_hdulist_file_info(self): def test_fileinfo(**kwargs): assert res['datSpan'] == kwargs.get('datSpan', 2880) assert res['resized'] == kwargs.get('resized', False) assert res['filename'] == self.data('checksum.fits') assert res['datLoc'] == kwargs.get('datLoc', 8640) assert res['hdrLoc'] == kwargs.get('hdrLoc', 0) assert res['filemode'] == 'readonly' with fits.open(self.data('checksum.fits')) as hdul: res = hdul.fileinfo(0) res = hdul.fileinfo(1) test_fileinfo(datLoc=17280, hdrLoc=11520) hdu = fits.ImageHDU(data=hdul[0].data) hdul.insert(1, hdu) res = hdul.fileinfo(0) test_fileinfo(resized=True) res = hdul.fileinfo(1) test_fileinfo(datSpan=None, resized=True, datLoc=None, hdrLoc=None) res = hdul.fileinfo(2) test_fileinfo(resized=1, datLoc=17280, hdrLoc=11520) def test_create_from_multiple_primary(self): hdul = fits.HDUList([fits.PrimaryHDU(), fits.PrimaryHDU()]) pytest.raises(VerifyError, hdul.writeto, self.temp('temp.fits'), output_verify='exception') def test_append_primary_to_empty_list(self): hdul = fits.HDUList() hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.append(hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_extension_to_empty_list(self): hdul = fits.HDUList() hdu = fits.ImageHDU(np.arange(100, dtype=np.int32)) hdul.append(hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_table_extension_to_empty_list(self): hdul = fits.HDUList() with fits.open(self.data('tb.fits')) as hdul1: hdul.append(hdul1[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_groupshdu_to_empty_list(self): hdul = fits.HDUList() hdu = fits.GroupsHDU() hdul.append(hdu) info = [(0, 'PRIMARY', 1, 'GroupsHDU', 8, (), '', '1 Groups 0 Parameters')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_primary_to_non_empty_list(self): with fits.open(self.data('arange.fits')) as hdul: hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.append(hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 7, (11, 10, 7), 'int32', ''), (1, '', 1, 'ImageHDU', 6, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info def test_append_extension_to_non_empty_list(self): with fits.open(self.data('tb.fits')) as hdul: hdul.append(hdul[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 11, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', ''), (2, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-append.fits')) assert fits.info(self.temp('test-append.fits'), output=False) == info @raises(ValueError) def test_append_groupshdu_to_non_empty_list(self): hdul = fits.HDUList() hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.append(hdu) hdu = fits.GroupsHDU() hdul.append(hdu) def test_insert_primary_to_empty_list(self): hdul = fits.HDUList() hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.insert(0, hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_extension_to_empty_list(self): hdul = fits.HDUList() hdu = fits.ImageHDU(np.arange(100, dtype=np.int32)) hdul.insert(0, hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_table_extension_to_empty_list(self): hdul = fits.HDUList() with fits.open(self.data('tb.fits')) as hdul1: hdul.insert(0, hdul1[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_groupshdu_to_empty_list(self): hdul = fits.HDUList() hdu = fits.GroupsHDU() hdul.insert(0, hdu) info = [(0, 'PRIMARY', 1, 'GroupsHDU', 8, (), '', '1 Groups 0 Parameters')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_primary_to_non_empty_list(self): with fits.open(self.data('arange.fits')) as hdul: hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.insert(1, hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 7, (11, 10, 7), 'int32', ''), (1, '', 1, 'ImageHDU', 6, (100,), 'int32', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_extension_to_non_empty_list(self): with fits.open(self.data('tb.fits')) as hdul: hdul.insert(1, hdul[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 11, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', ''), (2, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_groupshdu_to_non_empty_list(self): hdul = fits.HDUList() hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul.insert(0, hdu) hdu = fits.GroupsHDU() with pytest.raises(ValueError): hdul.insert(1, hdu) info = [(0, 'PRIMARY', 1, 'GroupsHDU', 8, (), '', '1 Groups 0 Parameters'), (1, '', 1, 'ImageHDU', 6, (100,), 'int32', '')] hdul.insert(0, hdu) assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info @raises(ValueError) def test_insert_groupshdu_to_begin_of_hdulist_with_groupshdu(self): hdul = fits.HDUList() hdu = fits.GroupsHDU() hdul.insert(0, hdu) hdul.insert(0, hdu) def test_insert_extension_to_primary_in_non_empty_list(self): with fits.open(self.data('tb.fits')) as hdul: hdul.insert(0, hdul[1]) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 4, (), '', ''), (1, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', ''), (2, '', 1, 'ImageHDU', 12, (), '', ''), (3, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_insert_image_extension_to_primary_in_non_empty_list(self): with fits.open(self.data('tb.fits')) as hdul: hdu = fits.ImageHDU(np.arange(100, dtype=np.int32)) hdul.insert(0, hdu) info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', ''), (1, '', 1, 'ImageHDU', 12, (), '', ''), (2, '', 1, 'BinTableHDU', 24, '2R x 4C', '[1J, 3A, 1E, 1L]', '')] assert hdul.info(output=False) == info hdul.writeto(self.temp('test-insert.fits')) assert fits.info(self.temp('test-insert.fits'), output=False) == info def test_filename(self): with fits.open(self.data('tb.fits')) as hdul: name = hdul.filename() assert name == self.data('tb.fits') def test_file_like(self): hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) hdul = fits.HDUList() hdul.append(hdu) tmpfile = open(self.temp('tmpfile.fits'), 'wb') hdul.writeto(tmpfile) tmpfile.close() info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert fits.info(self.temp('tmpfile.fits'), output=False) == info def test_file_like_2(self): hdu = fits.PrimaryHDU(np.arange(100, dtype=np.int32)) tmpfile = open(self.temp('tmpfile.fits'), 'wb') hdul = fits.open(tmpfile, mode='ostream') hdul.append(hdu) hdul.flush() tmpfile.close() hdul.close() info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert fits.info(self.temp('tmpfile.fits'), output=False) == info def test_file_like_3(self): tmpfile = open(self.temp('tmpfile.fits'), 'wb') fits.writeto(tmpfile, np.arange(100, dtype=np.int32)) tmpfile.close() info = [(0, 'PRIMARY', 1, 'PrimaryHDU', 5, (100,), 'int32', '')] assert fits.info(self.temp('tmpfile.fits'), output=False) == info def test_shallow_copy(self): n = np.arange(10.0) primary_hdu = fits.PrimaryHDU(n) hdu = fits.ImageHDU(n) hdul = fits.HDUList([primary_hdu, hdu]) for hdulcopy in (hdul.copy(), copy.copy(hdul)): assert isinstance(hdulcopy, fits.HDUList) assert hdulcopy is not hdul assert hdulcopy[0] is hdul[0] assert hdulcopy[1] is hdul[1] def test_deep_copy(self): n = np.arange(10.0) primary_hdu = fits.PrimaryHDU(n) hdu = fits.ImageHDU(n) hdul = fits.HDUList([primary_hdu, hdu]) hdulcopy = copy.deepcopy(hdul) assert isinstance(hdulcopy, fits.HDUList) assert hdulcopy is not hdul for index in range(len(hdul)): assert hdulcopy[index] is not hdul[index] assert hdulcopy[index].header == hdul[index].header np.testing.assert_array_equal(hdulcopy[index].data, hdul[index].data) def test_new_hdu_extname(self): with fits.open(self.data('test0.fits')) as f: hdul = fits.HDUList() hdul.append(f[0].copy()) hdu = fits.ImageHDU(header=f[1].header) hdul.append(hdu) assert hdul[1].header['EXTNAME'] == 'SCI' assert hdul[1].header['EXTVER'] == 1 assert hdul.index_of(('SCI', 1)) == 1 assert hdul.index_of(hdu) == len(hdul) - 1 def test_update_filelike(self): sf = io.BytesIO() arr = np.zeros((100, 100)) hdu = fits.PrimaryHDU(data=arr) hdu.writeto(sf) sf.seek(0) arr = np.zeros((200, 200)) hdul = fits.open(sf, mode='update') hdul[0].data = arr hdul.flush() sf.seek(0) hdul = fits.open(sf) assert len(hdul) == 1 assert (hdul[0].data == arr).all() def test_flush_readonly(self): oldmtime = os.stat(self.data('test0.fits')).st_mtime hdul = fits.open(self.data('test0.fits')) hdul[0].header['FOO'] = 'BAR' with catch_warnings(AstropyUserWarning) as w: hdul.flush() assert len(w) == 1 assert 'mode is not supported' in str(w[0].message) assert oldmtime == os.stat(self.data('test0.fits')).st_mtime def test_fix_extend_keyword(self): hdul = fits.HDUList() hdul.append(fits.PrimaryHDU()) hdul.append(fits.ImageHDU()) del hdul[0].header['EXTEND'] hdul.verify('silentfix') assert 'EXTEND' in hdul[0].header assert hdul[0].header['EXTEND'] is True def test_fix_malformed_naxisj(self): hdu = fits.open(self.data('arange.fits')) hdu[0].header['NAXIS1'] = 11.0 hdu[0].header['NAXIS2'] = '10.0' hdu[0].header['NAXIS3'] = '7' hdu[0]._axes = [11.0, '10.0', '7'] hdu.verify('silentfix') assert hdu[0].header['NAXIS1'] == 11 assert hdu[0].header['NAXIS2'] == 10 assert hdu[0].header['NAXIS3'] == 7 hdu.close() def test_fix_wellformed_naxisj(self): hdu = fits.open(self.data('arange.fits')) hdu[0].header['NAXIS1'] = 768 hdu[0].header['NAXIS2'] = 64 hdu[0].header['NAXIS3'] = 8 hdu[0]._axes = [768, 64, 8] hdu.verify('silentfix') assert hdu[0].header['NAXIS1'] == 768 assert hdu[0].header['NAXIS2'] == 64 assert hdu[0].header['NAXIS3'] == 8 hdu.close() def test_new_hdulist_extend_keyword(self): h0 = fits.Header() hdu = fits.PrimaryHDU(header=h0) sci = fits.ImageHDU(data=np.array(10)) image = fits.HDUList([hdu, sci]) image.writeto(self.temp('temp.fits')) assert 'EXTEND' in hdu.header assert hdu.header['EXTEND'] is True def test_replace_memmaped_array(self): with fits.open(self.data('test0.fits')) as hdul: hdul.writeto(self.temp('temp.fits')) hdul = fits.open(self.temp('temp.fits'), mode='update', memmap=True) old_data = hdul[1].data.copy() hdul[1].data = hdul[1].data + 1 hdul.close() with fits.open(self.temp('temp.fits'), memmap=True) as hdul: assert ((old_data + 1) == hdul[1].data).all() def test_open_file_with_end_padding(self): with fits.open(self.data('test0.fits'), do_not_scale_image_data=True) as hdul: info = hdul.info(output=False) hdul.writeto(self.temp('temp.fits')) with open(self.temp('temp.fits'), 'ab') as f: f.seek(0, os.SEEK_END) f.write(b'\0' * 2880) with ignore_warnings(): assert info == fits.info(self.temp('temp.fits'), output=False, do_not_scale_image_data=True) def test_open_file_with_bad_header_padding(self): a = np.arange(100).reshape(10, 10) hdu = fits.PrimaryHDU(data=a) hdu.writeto(self.temp('temp.fits')) end_card_pos = str(hdu.header).index('END' + ' ' * 77) padding_start = end_card_pos + 80 padding_len = 2880 - padding_start with open(self.temp('temp.fits'), 'r+b') as f: f.seek(padding_start) f.write('\0'.encode('ascii') * padding_len) with catch_warnings(AstropyUserWarning) as w: with fits.open(self.temp('temp.fits')) as hdul: assert (hdul[0].data == a).all() assert ('contains null bytes instead of spaces' in str(w[0].message)) assert len(w) == 1 assert len(hdul) == 1 assert str(hdul[0].header) == str(hdu.header) def test_update_with_truncated_header(self): data = np.arange(100) hdu = fits.PrimaryHDU(data=data) idx = 1 while len(hdu.header) < 34: hdu.header[f'TEST{idx}'] = idx idx += 1 hdu.writeto(self.temp('temp.fits'), checksum=True) with fits.open(self.temp('temp.fits'), mode='update') as hdul: hdul[0].header['TEST1'] = 2 with fits.open(self.temp('temp.fits')) as hdul: assert (hdul[0].data == data).all() @pytest.mark.filterwarnings("ignore:Assigning the 'data' attribute is an " "inherently unsafe operation") def test_update_resized_header(self): data = np.arange(100) hdu = fits.PrimaryHDU(data=data) idx = 1 while len(str(hdu.header)) <= 2880: hdu.header[f'TEST{idx}'] = idx idx += 1 orig_header = hdu.header.copy() hdu.writeto(self.temp('temp.fits')) with fits.open(self.temp('temp.fits'), mode='update') as hdul: while len(str(hdul[0].header)) > 2880: del hdul[0].header[-1] with fits.open(self.temp('temp.fits')) as hdul: assert hdul[0].header == orig_header[:-1] assert (hdul[0].data == data).all() with fits.open(self.temp('temp.fits'), mode='update') as hdul: idx = 101 while len(str(hdul[0].header)) <= 2880 * 2: hdul[0].header[f'TEST{idx}'] = idx idx += 1 hdul[0].data[0] = 27 with fits.open(self.temp('temp.fits')) as hdul: assert hdul[0].header[:-37] == orig_header[:-1] assert hdul[0].data[0] == 27 assert (hdul[0].data[1:] == data[1:]).all() def test_update_resized_header2(self): data1 = np.arange(100) data2 = np.arange(100) + 100 phdu = fits.PrimaryHDU(data=data1) hdu = fits.ImageHDU(data=data2) phdu.writeto(self.temp('temp.fits')) with fits.open(self.temp('temp.fits'), mode='append') as hdul: hdul.append(hdu) with fits.open(self.temp('temp.fits'), mode='update') as hdul: idx = 1 while len(str(hdul[0].header)) <= 2880 * 2: hdul[0].header[f'TEST{idx}'] = idx idx += 1 hdul.flush() hdul.append(hdu) with fits.open(self.temp('temp.fits')) as hdul: assert (hdul[0].data == data1).all() assert hdul[1].header == hdu.header assert (hdul[1].data == data2).all() assert (hdul[2].data == data2).all() @ignore_warnings() def test_hdul_fromstring(self): def test_fromstring(filename): with fits.open(filename) as hdul: orig_info = hdul.info(output=False) with open(filename, 'rb') as f: dat = f.read() hdul2 = fits.HDUList.fromstring(dat) assert orig_info == hdul2.info(output=False) for idx in range(len(hdul)): assert hdul[idx].header == hdul2[idx].header if hdul[idx].data is None or hdul2[idx].data is None: assert hdul[idx].data == hdul2[idx].data elif (hdul[idx].data.dtype.fields and hdul2[idx].data.dtype.fields): # Compare tables for n in hdul[idx].data.names: c1 = hdul[idx].data[n] c2 = hdul2[idx].data[n] assert (c1 == c2).all() elif (any(dim == 0 for dim in hdul[idx].data.shape) or any(dim == 0 for dim in hdul2[idx].data.shape)): # For some reason some combinations of Python and Numpy # on Windows result in MemoryErrors when trying to work # on memmap arrays with more than one dimension but # some dimensions of size zero, so include a special # case for that return hdul[idx].data.shape == hdul2[idx].data.shape else: np.testing.assert_array_equal(hdul[idx].data, hdul2[idx].data) for filename in glob.glob(os.path.join(self.data_dir, '*.fits')): if sys.platform == 'win32' and filename == 'zerowidth.fits': # Running this test on this file causes a crash in some # versions of Numpy on Windows. See ticket: # https://aeon.stsci.edu/ssb/trac/pyfits/ticket/174 continue elif filename.endswith('variable_length_table.fits'): # Comparing variable length arrays is non-trivial and thus # skipped at this point. # TODO: That's probably possible, so one could make it work. continue test_fromstring(filename) pytest.raises(TypeError, fits.HDUList.fromstring, ['a', 'b', 'c']) def test_save_backup(self): self.copy_file('scale.fits') with ignore_warnings(): with fits.open(self.temp('scale.fits'), mode='update', save_backup=True) as hdul: hdul[0].header['TEST'] = 'TEST' hdul[0].data[0] = 0 assert os.path.exists(self.temp('scale.fits.bak')) with fits.open(self.data('scale.fits'), do_not_scale_image_data=True) as hdul1: with fits.open(self.temp('scale.fits.bak'), do_not_scale_image_data=True) as hdul2: assert hdul1[0].header == hdul2[0].header assert (hdul1[0].data == hdul2[0].data).all() with ignore_warnings(): with fits.open(self.temp('scale.fits'), mode='update', save_backup=True) as hdul: hdul[0].header['TEST2'] = 'TEST' hdul[0].data[0] = 1 assert os.path.exists(self.temp('scale.fits.bak')) assert os.path.exists(self.temp('scale.fits.bak.1')) def test_replace_mmap_data(self): arr_a = np.arange(10) arr_b = arr_a * 2 def test(mmap_a, mmap_b): hdu_a = fits.PrimaryHDU(data=arr_a) hdu_a.writeto(self.temp('test_a.fits'), overwrite=True) hdu_b = fits.PrimaryHDU(data=arr_b) hdu_b.writeto(self.temp('test_b.fits'), overwrite=True) with fits.open(self.temp('test_a.fits'), mode='update', memmap=mmap_a) as hdul_a: with fits.open(self.temp('test_b.fits'), memmap=mmap_b) as hdul_b: hdul_a[0].data = hdul_b[0].data with fits.open(self.temp('test_a.fits')) as hdul_a: assert np.all(hdul_a[0].data == arr_b) with ignore_warnings(): test(True, True) test(False, True) # Finally, without mmaping B test(True, False) def test_replace_mmap_data_2(self): arr_a = np.arange(10) arr_b = arr_a * 2 def test(mmap_a, mmap_b): col_a = fits.Column(name='a', format='J', array=arr_a) col_b = fits.Column(name='b', format='J', array=arr_b) hdu_a = fits.BinTableHDU.from_columns([col_a]) hdu_a.writeto(self.temp('test_a.fits'), overwrite=True) hdu_b = fits.BinTableHDU.from_columns([col_b]) hdu_b.writeto(self.temp('test_b.fits'), overwrite=True) with fits.open(self.temp('test_a.fits'), mode='update', memmap=mmap_a) as hdul_a: with fits.open(self.temp('test_b.fits'), memmap=mmap_b) as hdul_b: hdul_a[1].data = hdul_b[1].data with fits.open(self.temp('test_a.fits')) as hdul_a: assert 'b' in hdul_a[1].columns.names assert 'a' not in hdul_a[1].columns.names assert np.all(hdul_a[1].data['b'] == arr_b) with ignore_warnings(): test(True, True) # Repeat the same test but this time don't mmap A test(False, True) test(True, False) def test_extname_in_hdulist(self): with fits.open(self.data('o4sp040b0_raw.fits')) as hdulist: hdulist.append(fits.ImageHDU(name='a')) assert 'a' in hdulist assert 'A' in hdulist assert ('a', 1) in hdulist assert ('A', 1) in hdulist assert 'b' not in hdulist assert ('a', 2) not in hdulist assert ('b', 1) not in hdulist assert ('b', 2) not in hdulist assert hdulist[0] in hdulist assert fits.ImageHDU() not in hdulist def test_overwrite_vs_clobber(self): hdulist = fits.HDUList([fits.PrimaryHDU()]) hdulist.writeto(self.temp('test_overwrite.fits')) hdulist.writeto(self.temp('test_overwrite.fits'), overwrite=True) with catch_warnings(AstropyDeprecationWarning) as warning_lines: hdulist.writeto(self.temp('test_overwrite.fits'), clobber=True) assert warning_lines[0].category == AstropyDeprecationWarning assert (str(warning_lines[0].message) == '"clobber" was ' 'deprecated in version 2.0 and will be removed in a ' 'future version. Use argument "overwrite" instead.') def test_invalid_hdu_key_in_contains(self): hdulist = fits.HDUList(fits.PrimaryHDU()) hdulist.append(fits.ImageHDU()) hdulist.append(fits.ImageHDU()) bad_keys = [None, 3.5, {}] for key in bad_keys: assert not (key in hdulist) def test_iteration_of_lazy_loaded_hdulist(self): hdulist = fits.HDUList(fits.PrimaryHDU()) hdulist.append(fits.ImageHDU(name='SCI')) hdulist.append(fits.ImageHDU(name='SCI')) hdulist.append(fits.ImageHDU(name='nada')) hdulist.append(fits.ImageHDU(name='SCI')) filename = self.temp('many_extension.fits') hdulist.writeto(filename) f = fits.open(filename) all_exts = [ext for ext in f] assert len(all_exts) == 5 f.close() f = fits.open(filename) all_exts_but_zero = [ext for ext in f[1:]] assert len(all_exts_but_zero) == 4 f.close() f = fits.open(filename) read_exts = [ext for ext in f[1:4] if ext.header['EXTNAME'] == 'SCI'] assert len(read_exts) == 2 f.close() def test_proper_error_raised_on_non_fits_file_with_unicode(self): import codecs filename = self.temp('not-fits-with-unicode.fits') with codecs.open(filename, mode='w', encoding='utf=8') as f: f.write('Ce\xe7i ne marche pas') with pytest.raises(OSError): with pytest.warns(AstropyUserWarning, match=r'non-ASCII characters ' r'are present in the FITS file header'): fits.open(filename) def test_no_resource_warning_raised_on_non_fits_file(self): filename = self.temp('not-fits.fits') with open(filename, mode='w') as f: f.write('# header line\n') f.write('0.1 0.2\n') with catch_warnings(ResourceWarning) as ws: with open(filename, mode='rb') as f: with pytest.raises(OSError): fits.open(f, ignore_missing_end=False) assert not f.closed with open(filename, mode='rb') as f: with pytest.raises(OSError): fits.open(f, ignore_missing_end=True) assert not f.closed with pytest.raises(OSError): fits.open(filename, ignore_missing_end=False) with pytest.raises(OSError): fits.open(filename, ignore_missing_end=True) assert len(ws) == 0 def test_pop_with_lazy_load(self): filename = self.data('checksum.fits') with fits.open(filename) as hdul: hdu = hdul.pop() assert len(hdul) == 1 with fits.open(filename) as hdul2: hdu2 = hdul2.pop(0) assert len(hdul2) == 1 with fits.open(filename) as hdul3: assert len(hdul3) == 2 assert hdul3[0].header == hdu2.header assert hdul3[1].header == hdu.header def test_pop_extname(self): with fits.open(self.data('o4sp040b0_raw.fits')) as hdul: assert len(hdul) == 7 hdu1 = hdul[1] hdu4 = hdul[4] hdu_popped = hdul.pop(('SCI', 2)) assert len(hdul) == 6 assert hdu_popped is hdu4 hdu_popped = hdul.pop('SCI') assert len(hdul) == 5 assert hdu_popped is hdu1 @pytest.mark.skipif('sys.platform.startswith("win32")') def test_write_hdulist_to_stream(self): data = np.array([[1, 2, 3], [4, 5, 6]]) hdu = fits.PrimaryHDU(data) hdulist = fits.HDUList([hdu]) with open(self.temp('test.fits'), 'wb') as fout: with subprocess.Popen(["cat"], stdin=subprocess.PIPE, stdout=fout) as p: hdulist.writeto(p.stdin)

true

1c2fb3bd371d853ef0b2d0d8fca7b77602f5083b

284

py

Python

metadata_service/entity/description.py

jacobhjkim/amundsenmetadatalibrary

19b5c7bf0ac496a357648b1a1b28f28f4d6a9ffb

[ "Apache-2.0" ]

null

metadata_service/entity/description.py

jacobhjkim/amundsenmetadatalibrary

19b5c7bf0ac496a357648b1a1b28f28f4d6a9ffb

[ "Apache-2.0" ]

1

2020-09-24T17:05:39.000Z

metadata_service/entity/description.py

jacobhjkim/amundsenmetadatalibrary

19b5c7bf0ac496a357648b1a1b28f28f4d6a9ffb

[ "Apache-2.0" ]

null

import attr from marshmallow_annotations.ext.attrs import AttrsSchema @attr.s(auto_attribs=True, kw_only=True) class Description: description: str = attr.ib() class DescriptionSchema(AttrsSchema): class Meta: target = Description register_as_scheme = True

20.285714

57

0.742958

import attr from marshmallow_annotations.ext.attrs import AttrsSchema @attr.s(auto_attribs=True, kw_only=True) class Description: description: str = attr.ib() class DescriptionSchema(AttrsSchema): class Meta: target = Description register_as_scheme = True

true

1c2fb3e1ff5c2206cf4863d4a3992cc8e52cf425

1,640

py

Python

setup.py

robertopreste/HmtNote

0f2c0f684a45c0087cabc3cb15f61803fac7daf1

[ "MIT" ]

11

2019-04-11T07:06:41.000Z

2021-03-22T09:13:40.000Z

setup.py

robertopreste/HmtNote

0f2c0f684a45c0087cabc3cb15f61803fac7daf1

[ "MIT" ]

64

2019-03-04T11:18:25.000Z

2022-03-31T23:03:01.000Z

setup.py

robertopreste/HmtNote

0f2c0f684a45c0087cabc3cb15f61803fac7daf1

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: UTF-8 -*- # Created by Roberto Preste from setuptools import setup, find_packages with open('README.rst') as readme_file: readme = readme_file.read() with open('HISTORY.rst') as history_file: history = history_file.read() requirements = ["Click==7.0", "requests==2.22.0", "numpy==1.16.4", "pandas==0.24.2", "aiohttp==3.5.4", "aiofiles==0.4.0", "vcfpy2==0.1.2", "scikit-allel==1.2.1"] setup_requirements = ['pytest-runner', ] test_requirements = ['pytest', ] setup( # pragma: no cover author="Roberto Preste", author_email='robertopreste@gmail.com', classifiers=[ 'Development Status :: 4 - Beta', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Natural Language :: English', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', ], description="Human mitochondrial variants annotation using HmtVar.", entry_points={ 'console_scripts': [ 'hmtnote=hmtnote.cli:main', ], }, install_requires=requirements, license="MIT license", long_description=readme + '\n\n' + history, long_description_content_type="text/x-rst", include_package_data=True, keywords='hmtnote', name='hmtnote', packages=find_packages(include=['hmtnote']), setup_requires=setup_requirements, test_suite='tests', tests_require=test_requirements, url='https://github.com/robertopreste/hmtnote', version='0.7.2', zip_safe=False, )

30.943396

72

0.632927

from setuptools import setup, find_packages with open('README.rst') as readme_file: readme = readme_file.read() with open('HISTORY.rst') as history_file: history = history_file.read() requirements = ["Click==7.0", "requests==2.22.0", "numpy==1.16.4", "pandas==0.24.2", "aiohttp==3.5.4", "aiofiles==0.4.0", "vcfpy2==0.1.2", "scikit-allel==1.2.1"] setup_requirements = ['pytest-runner', ] test_requirements = ['pytest', ] setup( author="Roberto Preste", author_email='robertopreste@gmail.com', classifiers=[ 'Development Status :: 4 - Beta', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Natural Language :: English', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', ], description="Human mitochondrial variants annotation using HmtVar.", entry_points={ 'console_scripts': [ 'hmtnote=hmtnote.cli:main', ], }, install_requires=requirements, license="MIT license", long_description=readme + '\n\n' + history, long_description_content_type="text/x-rst", include_package_data=True, keywords='hmtnote', name='hmtnote', packages=find_packages(include=['hmtnote']), setup_requires=setup_requirements, test_suite='tests', tests_require=test_requirements, url='https://github.com/robertopreste/hmtnote', version='0.7.2', zip_safe=False, )

true

1c2fb49649471ec4b964ba521bb4466ad02558f5

1,475

py

Python

ponyexpress/migrations/versions/334aefbc10df_.py

TelekomCloud/pony-express

a825b518687719be5dfe95692008c2129db115cd

[ "Apache-2.0" ]

null

ponyexpress/migrations/versions/334aefbc10df_.py

TelekomCloud/pony-express

a825b518687719be5dfe95692008c2129db115cd

[ "Apache-2.0" ]

null

ponyexpress/migrations/versions/334aefbc10df_.py

TelekomCloud/pony-express

a825b518687719be5dfe95692008c2129db115cd

[ "Apache-2.0" ]

null

"""empty message Revision ID: 334aefbc10df Revises: 36b5aaa11324 Create Date: 2014-04-01 16:37:00.017980 """ # revision identifiers, used by Alembic. revision = '334aefbc10df' down_revision = '36b5aaa11324' from alembic import op import sqlalchemy as sa def upgrade(): ### commands auto generated by Alembic - please adjust! ### op.create_table('repositories', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=255), nullable=True), sa.Column('uri', sa.String(length=255), nullable=True), sa.Column('label', sa.String(length=255), nullable=True), sa.Column('provider', sa.String(length=12), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_table('repohistory', sa.Column('id', sa.Integer(), nullable=False), sa.Column('repo_id', sa.Integer(), nullable=True), sa.Column('pkgsha', sa.String(length=255), nullable=True), sa.Column('pkgname', sa.String(length=255), nullable=True), sa.Column('pkgversion', sa.String(length=64), nullable=True), sa.Column('pkgsource', sa.Text(), nullable=True), sa.Column('released', sa.DATE(), nullable=True), sa.ForeignKeyConstraint(['repo_id'], ['repositories.id'], ), sa.PrimaryKeyConstraint('id') ) ### end Alembic commands ### def downgrade(): ### commands auto generated by Alembic - please adjust! ### op.drop_table('repohistory') op.drop_table('repositories') ### end Alembic commands ###

32.065217

65

0.677288

revision = '334aefbc10df' down_revision = '36b5aaa11324' from alembic import op import sqlalchemy as sa def upgrade(): ength=255), nullable=True), sa.Column('uri', sa.String(length=255), nullable=True), sa.Column('label', sa.String(length=255), nullable=True), sa.Column('provider', sa.String(length=12), nullable=True), sa.PrimaryKeyConstraint('id') ) op.create_table('repohistory', sa.Column('id', sa.Integer(), nullable=False), sa.Column('repo_id', sa.Integer(), nullable=True), sa.Column('pkgsha', sa.String(length=255), nullable=True), sa.Column('pkgname', sa.String(length=255), nullable=True), sa.Column('pkgversion', sa.String(length=64), nullable=True), sa.Column('pkgsource', sa.Text(), nullable=True), sa.Column('released', sa.DATE(), nullable=True), sa.ForeignKeyConstraint(['repo_id'], ['repositories.id'], ), sa.PrimaryKeyConstraint('id') )

true

1c2fb4d2c2ee899687cfffb6413569efa4eb69d4

2,264

py

Python

test/upbit_test.py

BbChip0103/kimchi_premium_notice

e812fda7bae7cd01c4ca82892e9466831ff96698

[ "Apache-2.0" ]

null

test/upbit_test.py

BbChip0103/kimchi_premium_notice

e812fda7bae7cd01c4ca82892e9466831ff96698

[ "Apache-2.0" ]

null

test/upbit_test.py

BbChip0103/kimchi_premium_notice

e812fda7bae7cd01c4ca82892e9466831ff96698

[ "Apache-2.0" ]

null

import asyncio import websockets import json import ccxt async def upbit_ws_client(coin_list, callback): uri = 'wss://api.upbit.com/websocket/v1' async with websockets.connect(uri) as websocket: subscribe_fmt = [ {'ticket': 'bbchip13'}, {'format': 'SIMPLE'} ] subscribe_fmt += [ { 'type': 'ticker', 'codes': ['KRW-{}'.format(coin_name)], 'isOnlyRealtime': True } for coin_name in coin_list ] subscribe_data = json.dumps(subscribe_fmt) await websocket.send(subscribe_data) while True: res = await websocket.recv() res = json.loads(res) print(res['cd'], res['tp']) def get_upbit_coin_list(): upbit_exchange_id = 'upbit' upbit_exchange_class = getattr(ccxt, upbit_exchange_id) upbit_exchange = upbit_exchange_class({ 'apiKey': 'YOUR_APP_KEY', 'secret': 'YOUR_SECRET', }) upbit_coin_dict = { k:v for k, v in upbit_exchange.load_markets().items() if '/KRW' in k } upbit_coin_list = [ name.replace('/KRW', '') for name in list(upbit_coin_dict.keys()) ] return upbit_coin_list def get_binance_coin_list(): binance_exchange_id = 'binance' binance_exchange_class = getattr(ccxt, binance_exchange_id) binance_exchange = binance_exchange_class({ 'apiKey': 'YOUR_APP_KEY', 'secret': 'YOUR_SECRET', }) binance_coin_dict = { k:v for k, v in binance_exchange.load_markets().items() if '/USDT' in k and v['active'] == True } binance_coin_list = [ name.replace('/USDT', '') for name in list(binance_coin_dict.keys()) ] return binance_coin_list def upbit_callback_func(): pass if __name__ == "__main__": upbit_coin_list = get_upbit_coin_list() binance_coin_list = get_binance_coin_list() overlapped_coin_list = list(set(upbit_coin_list)&set(binance_coin_list)) tasks = [ asyncio.ensure_future( upbit_ws_client(overlapped_coin_list, upbit_callback_func) ), ] event_loop = asyncio.get_event_loop() event_loop.run_until_complete(asyncio.wait(tasks))

27.277108

77

0.616166

import asyncio import websockets import json import ccxt async def upbit_ws_client(coin_list, callback): uri = 'wss://api.upbit.com/websocket/v1' async with websockets.connect(uri) as websocket: subscribe_fmt = [ {'ticket': 'bbchip13'}, {'format': 'SIMPLE'} ] subscribe_fmt += [ { 'type': 'ticker', 'codes': ['KRW-{}'.format(coin_name)], 'isOnlyRealtime': True } for coin_name in coin_list ] subscribe_data = json.dumps(subscribe_fmt) await websocket.send(subscribe_data) while True: res = await websocket.recv() res = json.loads(res) print(res['cd'], res['tp']) def get_upbit_coin_list(): upbit_exchange_id = 'upbit' upbit_exchange_class = getattr(ccxt, upbit_exchange_id) upbit_exchange = upbit_exchange_class({ 'apiKey': 'YOUR_APP_KEY', 'secret': 'YOUR_SECRET', }) upbit_coin_dict = { k:v for k, v in upbit_exchange.load_markets().items() if '/KRW' in k } upbit_coin_list = [ name.replace('/KRW', '') for name in list(upbit_coin_dict.keys()) ] return upbit_coin_list def get_binance_coin_list(): binance_exchange_id = 'binance' binance_exchange_class = getattr(ccxt, binance_exchange_id) binance_exchange = binance_exchange_class({ 'apiKey': 'YOUR_APP_KEY', 'secret': 'YOUR_SECRET', }) binance_coin_dict = { k:v for k, v in binance_exchange.load_markets().items() if '/USDT' in k and v['active'] == True } binance_coin_list = [ name.replace('/USDT', '') for name in list(binance_coin_dict.keys()) ] return binance_coin_list def upbit_callback_func(): pass if __name__ == "__main__": upbit_coin_list = get_upbit_coin_list() binance_coin_list = get_binance_coin_list() overlapped_coin_list = list(set(upbit_coin_list)&set(binance_coin_list)) tasks = [ asyncio.ensure_future( upbit_ws_client(overlapped_coin_list, upbit_callback_func) ), ] event_loop = asyncio.get_event_loop() event_loop.run_until_complete(asyncio.wait(tasks))

true

1c2fb4f74a9d9b8bbf553cbbcff20b7de2e4e7ec

30,576

py

Python

src/utils/imagenet_labels.py

u-shiori/DLtemplate2021

10d266b450a6505255c44a570c04cbc0d99a2568

[ "MIT" ]

null

src/utils/imagenet_labels.py

u-shiori/DLtemplate2021

10d266b450a6505255c44a570c04cbc0d99a2568

[ "MIT" ]

null

src/utils/imagenet_labels.py

u-shiori/DLtemplate2021

10d266b450a6505255c44a570c04cbc0d99a2568

[ "MIT" ]

null

idx2label = {0: 'tench, Tinca tinca', 1: 'goldfish, Carassius auratus', 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', 3: 'tiger shark, Galeocerdo cuvieri', 4: 'hammerhead, hammerhead shark', 5: 'electric ray, crampfish, numbfish, torpedo', 6: 'stingray', 7: 'cock', 8: 'hen', 9: 'ostrich, Struthio camelus', 10: 'brambling, Fringilla montifringilla', 11: 'goldfinch, Carduelis carduelis', 12: 'house finch, linnet, Carpodacus mexicanus', 13: 'junco, snowbird', 14: 'indigo bunting, indigo finch, indigo bird, Passerina cyanea', 15: 'robin, American robin, Turdus migratorius', 16: 'bulbul', 17: 'jay', 18: 'magpie', 19: 'chickadee', 20: 'water ouzel, dipper', 21: 'kite', 22: 'bald eagle, American eagle, Haliaeetus leucocephalus', 23: 'vulture', 24: 'great grey owl, great gray owl, Strix nebulosa', 25: 'European fire salamander, Salamandra salamandra', 26: 'common newt, Triturus vulgaris', 27: 'eft', 28: 'spotted salamander, Ambystoma maculatum', 29: 'axolotl, mud puppy, Ambystoma mexicanum', 30: 'bullfrog, Rana catesbeiana', 31: 'tree frog, tree-frog', 32: 'tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui', 33: 'loggerhead, loggerhead turtle, Caretta caretta', 34: 'leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea', 35: 'mud turtle', 36: 'terrapin', 37: 'box turtle, box tortoise', 38: 'banded gecko', 39: 'common iguana, iguana, Iguana iguana', 40: 'American chameleon, anole, Anolis carolinensis', 41: 'whiptail, whiptail lizard', 42: 'agama', 43: 'frilled lizard, Chlamydosaurus kingi', 44: 'alligator lizard', 45: 'Gila monster, Heloderma suspectum', 46: 'green lizard, Lacerta viridis', 47: 'African chameleon, Chamaeleo chamaeleon', 48: 'Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis', 49: 'African crocodile, Nile crocodile, Crocodylus niloticus', 50: 'American alligator, Alligator mississipiensis', 51: 'triceratops', 52: 'thunder snake, worm snake, Carphophis amoenus', 53: 'ringneck snake, ring-necked snake, ring snake', 54: 'hognose snake, puff adder, sand viper', 55: 'green snake, grass snake', 56: 'king snake, kingsnake', 57: 'garter snake, grass snake', 58: 'water snake', 59: 'vine snake', 60: 'night snake, Hypsiglena torquata', 61: 'boa constrictor, Constrictor constrictor', 62: 'rock python, rock snake, Python sebae', 63: 'Indian cobra, Naja naja', 64: 'green mamba', 65: 'sea snake', 66: 'horned viper, cerastes, sand viper, horned asp, Cerastes cornutus', 67: 'diamondback, diamondback rattlesnake, Crotalus adamanteus', 68: 'sidewinder, horned rattlesnake, Crotalus cerastes', 69: 'trilobite', 70: 'harvestman, daddy longlegs, Phalangium opilio', 71: 'scorpion', 72: 'black and gold garden spider, Argiope aurantia', 73: 'barn spider, Araneus cavaticus', 74: 'garden spider, Aranea diademata', 75: 'black widow, Latrodectus mactans', 76: 'tarantula', 77: 'wolf spider, hunting spider', 78: 'tick', 79: 'centipede', 80: 'black grouse', 81: 'ptarmigan', 82: 'ruffed grouse, partridge, Bonasa umbellus', 83: 'prairie chicken, prairie grouse, prairie fowl', 84: 'peacock', 85: 'quail', 86: 'partridge', 87: 'African grey, African gray, Psittacus erithacus', 88: 'macaw', 89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita', 90: 'lorikeet', 91: 'coucal', 92: 'bee eater', 93: 'hornbill', 94: 'hummingbird', 95: 'jacamar', 96: 'toucan', 97: 'drake', 98: 'red-breasted merganser, Mergus serrator', 99: 'goose', 100: 'black swan, Cygnus atratus', 101: 'tusker', 102: 'echidna, spiny anteater, anteater', 103: 'platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus', 104: 'wallaby, brush kangaroo', 105: 'koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus', 106: 'wombat', 107: 'jellyfish', 108: 'sea anemone, anemone', 109: 'brain coral', 110: 'flatworm, platyhelminth', 111: 'nematode, nematode worm, roundworm', 112: 'conch', 113: 'snail', 114: 'slug', 115: 'sea slug, nudibranch', 116: 'chiton, coat-of-mail shell, sea cradle, polyplacophore', 117: 'chambered nautilus, pearly nautilus, nautilus', 118: 'Dungeness crab, Cancer magister', 119: 'rock crab, Cancer irroratus', 120: 'fiddler crab', 121: 'king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica', 122: 'American lobster, Northern lobster, Maine lobster, Homarus americanus', 123: 'spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish', 124: 'crayfish, crawfish, crawdad, crawdaddy', 125: 'hermit crab', 126: 'isopod', 127: 'white stork, Ciconia ciconia', 128: 'black stork, Ciconia nigra', 129: 'spoonbill', 130: 'flamingo', 131: 'little blue heron, Egretta caerulea', 132: 'American egret, great white heron, Egretta albus', 133: 'bittern', 134: 'crane', 135: 'limpkin, Aramus pictus', 136: 'European gallinule, Porphyrio porphyrio', 137: 'American coot, marsh hen, mud hen, water hen, Fulica americana', 138: 'bustard', 139: 'ruddy turnstone, Arenaria interpres', 140: 'red-backed sandpiper, dunlin, Erolia alpina', 141: 'redshank, Tringa totanus', 142: 'dowitcher', 143: 'oystercatcher, oyster catcher', 144: 'pelican', 145: 'king penguin, Aptenodytes patagonica', 146: 'albatross, mollymawk', 147: 'grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus', 148: 'killer whale, killer, orca, grampus, sea wolf, Orcinus orca', 149: 'dugong, Dugong dugon', 150: 'sea lion', 151: 'Chihuahua', 152: 'Japanese spaniel', 153: 'Maltese dog, Maltese terrier, Maltese', 154: 'Pekinese, Pekingese, Peke', 155: 'Shih-Tzu', 156: 'Blenheim spaniel', 157: 'papillon', 158: 'toy terrier', 159: 'Rhodesian ridgeback', 160: 'Afghan hound, Afghan', 161: 'basset, basset hound', 162: 'beagle', 163: 'bloodhound, sleuthhound', 164: 'bluetick', 165: 'black-and-tan coonhound', 166: 'Walker hound, Walker foxhound', 167: 'English foxhound', 168: 'redbone', 169: 'borzoi, Russian wolfhound', 170: 'Irish wolfhound', 171: 'Italian greyhound', 172: 'whippet', 173: 'Ibizan hound, Ibizan Podenco', 174: 'Norwegian elkhound, elkhound', 175: 'otterhound, otter hound', 176: 'Saluki, gazelle hound', 177: 'Scottish deerhound, deerhound', 178: 'Weimaraner', 179: 'Staffordshire bullterrier, Staffordshire bull terrier', 180: 'American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier', 181: 'Bedlington terrier', 182: 'Border terrier', 183: 'Kerry blue terrier', 184: 'Irish terrier', 185: 'Norfolk terrier', 186: 'Norwich terrier', 187: 'Yorkshire terrier', 188: 'wire-haired fox terrier', 189: 'Lakeland terrier', 190: 'Sealyham terrier, Sealyham', 191: 'Airedale, Airedale terrier', 192: 'cairn, cairn terrier', 193: 'Australian terrier', 194: 'Dandie Dinmont, Dandie Dinmont terrier', 195: 'Boston bull, Boston terrier', 196: 'miniature schnauzer', 197: 'giant schnauzer', 198: 'standard schnauzer', 199: 'Scotch terrier, Scottish terrier, Scottie', 200: 'Tibetan terrier, chrysanthemum dog', 201: 'silky terrier, Sydney silky', 202: 'soft-coated wheaten terrier', 203: 'West Highland white terrier', 204: 'Lhasa, Lhasa apso', 205: 'flat-coated retriever', 206: 'curly-coated retriever', 207: 'golden retriever', 208: 'Labrador retriever', 209: 'Chesapeake Bay retriever', 210: 'German short-haired pointer', 211: 'vizsla, Hungarian pointer', 212: 'English setter', 213: 'Irish setter, red setter', 214: 'Gordon setter', 215: 'Brittany spaniel', 216: 'clumber, clumber spaniel', 217: 'English springer, English springer spaniel', 218: 'Welsh springer spaniel', 219: 'cocker spaniel, English cocker spaniel, cocker', 220: 'Sussex spaniel', 221: 'Irish water spaniel', 222: 'kuvasz', 223: 'schipperke', 224: 'groenendael', 225: 'malinois', 226: 'briard', 227: 'kelpie', 228: 'komondor', 229: 'Old English sheepdog, bobtail', 230: 'Shetland sheepdog, Shetland sheep dog, Shetland', 231: 'collie', 232: 'Border collie', 233: 'Bouvier des Flandres, Bouviers des Flandres', 234: 'Rottweiler', 235: 'German shepherd, German shepherd dog, German police dog, alsatian', 236: 'Doberman, Doberman pinscher', 237: 'miniature pinscher', 238: 'Greater Swiss Mountain dog', 239: 'Bernese mountain dog', 240: 'Appenzeller', 241: 'EntleBucher', 242: 'boxer', 243: 'bull mastiff', 244: 'Tibetan mastiff', 245: 'French bulldog', 246: 'Great Dane', 247: 'Saint Bernard, St Bernard', 248: 'Eskimo dog, husky', 249: 'malamute, malemute, Alaskan malamute', 250: 'Siberian husky', 251: 'dalmatian, coach dog, carriage dog', 252: 'affenpinscher, monkey pinscher, monkey dog', 253: 'basenji', 254: 'pug, pug-dog', 255: 'Leonberg', 256: 'Newfoundland, Newfoundland dog', 257: 'Great Pyrenees', 258: 'Samoyed, Samoyede', 259: 'Pomeranian', 260: 'chow, chow chow', 261: 'keeshond', 262: 'Brabancon griffon', 263: 'Pembroke, Pembroke Welsh corgi', 264: 'Cardigan, Cardigan Welsh corgi', 265: 'toy poodle', 266: 'miniature poodle', 267: 'standard poodle', 268: 'Mexican hairless', 269: 'timber wolf, grey wolf, gray wolf, Canis lupus', 270: 'white wolf, Arctic wolf, Canis lupus tundrarum', 271: 'red wolf, maned wolf, Canis rufus, Canis niger', 272: 'coyote, prairie wolf, brush wolf, Canis latrans', 273: 'dingo, warrigal, warragal, Canis dingo', 274: 'dhole, Cuon alpinus', 275: 'African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus', 276: 'hyena, hyaena', 277: 'red fox, Vulpes vulpes', 278: 'kit fox, Vulpes macrotis', 279: 'Arctic fox, white fox, Alopex lagopus', 280: 'grey fox, gray fox, Urocyon cinereoargenteus', 281: 'tabby, tabby cat', 282: 'tiger cat', 283: 'Persian cat', 284: 'Siamese cat, Siamese', 285: 'Egyptian cat', 286: 'cougar, puma, catamount, mountain lion, painter, panther, Felis concolor', 287: 'lynx, catamount', 288: 'leopard, Panthera pardus', 289: 'snow leopard, ounce, Panthera uncia', 290: 'jaguar, panther, Panthera onca, Felis onca', 291: 'lion, king of beasts, Panthera leo', 292: 'tiger, Panthera tigris', 293: 'cheetah, chetah, Acinonyx jubatus', 294: 'brown bear, bruin, Ursus arctos', 295: 'American black bear, black bear, Ursus americanus, Euarctos americanus', 296: 'ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus', 297: 'sloth bear, Melursus ursinus, Ursus ursinus', 298: 'mongoose', 299: 'meerkat, mierkat', 300: 'tiger beetle', 301: 'ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle', 302: 'ground beetle, carabid beetle', 303: 'long-horned beetle, longicorn, longicorn beetle', 304: 'leaf beetle, chrysomelid', 305: 'dung beetle', 306: 'rhinoceros beetle', 307: 'weevil', 308: 'fly', 309: 'bee', 310: 'ant, emmet, pismire', 311: 'grasshopper, hopper', 312: 'cricket', 313: 'walking stick, walkingstick, stick insect', 314: 'cockroach, roach', 315: 'mantis, mantid', 316: 'cicada, cicala', 317: 'leafhopper', 318: 'lacewing, lacewing fly', 319: "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk", 320: 'damselfly', 321: 'admiral', 322: 'ringlet, ringlet butterfly', 323: 'monarch, monarch butterfly, milkweed butterfly, Danaus plexippus', 324: 'cabbage butterfly', 325: 'sulphur butterfly, sulfur butterfly', 326: 'lycaenid, lycaenid butterfly', 327: 'starfish, sea star', 328: 'sea urchin', 329: 'sea cucumber, holothurian', 330: 'wood rabbit, cottontail, cottontail rabbit', 331: 'hare', 332: 'Angora, Angora rabbit', 333: 'hamster', 334: 'porcupine, hedgehog', 335: 'fox squirrel, eastern fox squirrel, Sciurus niger', 336: 'marmot', 337: 'beaver', 338: 'guinea pig, Cavia cobaya', 339: 'sorrel', 340: 'zebra', 341: 'hog, pig, grunter, squealer, Sus scrofa', 342: 'wild boar, boar, Sus scrofa', 343: 'warthog', 344: 'hippopotamus, hippo, river horse, Hippopotamus amphibius', 345: 'ox', 346: 'water buffalo, water ox, Asiatic buffalo, Bubalus bubalis', 347: 'bison', 348: 'ram, tup', 349: 'bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis', 350: 'ibex, Capra ibex', 351: 'hartebeest', 352: 'impala, Aepyceros melampus', 353: 'gazelle', 354: 'Arabian camel, dromedary, Camelus dromedarius', 355: 'llama', 356: 'weasel', 357: 'mink', 358: 'polecat, fitch, foulmart, foumart, Mustela putorius', 359: 'black-footed ferret, ferret, Mustela nigripes', 360: 'otter', 361: 'skunk, polecat, wood pussy', 362: 'badger', 363: 'armadillo', 364: 'three-toed sloth, ai, Bradypus tridactylus', 365: 'orangutan, orang, orangutang, Pongo pygmaeus', 366: 'gorilla, Gorilla gorilla', 367: 'chimpanzee, chimp, Pan troglodytes', 368: 'gibbon, Hylobates lar', 369: 'siamang, Hylobates syndactylus, Symphalangus syndactylus', 370: 'guenon, guenon monkey', 371: 'patas, hussar monkey, Erythrocebus patas', 372: 'baboon', 373: 'macaque', 374: 'langur', 375: 'colobus, colobus monkey', 376: 'proboscis monkey, Nasalis larvatus', 377: 'marmoset', 378: 'capuchin, ringtail, Cebus capucinus', 379: 'howler monkey, howler', 380: 'titi, titi monkey', 381: 'spider monkey, Ateles geoffroyi', 382: 'squirrel monkey, Saimiri sciureus', 383: 'Madagascar cat, ring-tailed lemur, Lemur catta', 384: 'indri, indris, Indri indri, Indri brevicaudatus', 385: 'Indian elephant, Elephas maximus', 386: 'African elephant, Loxodonta africana', 387: 'lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens', 388: 'giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca', 389: 'barracouta, snoek', 390: 'eel', 391: 'coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch', 392: 'rock beauty, Holocanthus tricolor', 393: 'anemone fish', 394: 'sturgeon', 395: 'gar, garfish, garpike, billfish, Lepisosteus osseus', 396: 'lionfish', 397: 'puffer, pufferfish, blowfish, globefish', 398: 'abacus', 399: 'abaya', 400: "academic gown, academic robe, judge's robe", 401: 'accordion, piano accordion, squeeze box', 402: 'acoustic guitar', 403: 'aircraft carrier, carrier, flattop, attack aircraft carrier', 404: 'airliner', 405: 'airship, dirigible', 406: 'altar', 407: 'ambulance', 408: 'amphibian, amphibious vehicle', 409: 'analog clock', 410: 'apiary, bee house', 411: 'apron', 412: 'ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin', 413: 'assault rifle, assault gun', 414: 'backpack, back pack, knapsack, packsack, rucksack, haversack', 415: 'bakery, bakeshop, bakehouse', 416: 'balance beam, beam', 417: 'balloon', 418: 'ballpoint, ballpoint pen, ballpen, Biro', 419: 'Band Aid', 420: 'banjo', 421: 'bannister, banister, balustrade, balusters, handrail', 422: 'barbell', 423: 'barber chair', 424: 'barbershop', 425: 'barn', 426: 'barometer', 427: 'barrel, cask', 428: 'barrow, garden cart, lawn cart, wheelbarrow', 429: 'baseball', 430: 'basketball', 431: 'bassinet', 432: 'bassoon', 433: 'bathing cap, swimming cap', 434: 'bath towel', 435: 'bathtub, bathing tub, bath, tub', 436: 'beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon', 437: 'beacon, lighthouse, beacon light, pharos', 438: 'beaker', 439: 'bearskin, busby, shako', 440: 'beer bottle', 441: 'beer glass', 442: 'bell cote, bell cot', 443: 'bib', 444: 'bicycle-built-for-two, tandem bicycle, tandem', 445: 'bikini, two-piece', 446: 'binder, ring-binder', 447: 'binoculars, field glasses, opera glasses', 448: 'birdhouse', 449: 'boathouse', 450: 'bobsled, bobsleigh, bob', 451: 'bolo tie, bolo, bola tie, bola', 452: 'bonnet, poke bonnet', 453: 'bookcase', 454: 'bookshop, bookstore, bookstall', 455: 'bottlecap', 456: 'bow', 457: 'bow tie, bow-tie, bowtie', 458: 'brass, memorial tablet, plaque', 459: 'brassiere, bra, bandeau', 460: 'breakwater, groin, groyne, mole, bulwark, seawall, jetty', 461: 'breastplate, aegis, egis', 462: 'broom', 463: 'bucket, pail', 464: 'buckle', 465: 'bulletproof vest', 466: 'bullet train, bullet', 467: 'butcher shop, meat market', 468: 'cab, hack, taxi, taxicab', 469: 'caldron, cauldron', 470: 'candle, taper, wax light', 471: 'cannon', 472: 'canoe', 473: 'can opener, tin opener', 474: 'cardigan', 475: 'car mirror', 476: 'carousel, carrousel, merry-go-round, roundabout, whirligig', 477: "carpenter's kit, tool kit", 478: 'carton', 479: 'car wheel', 480: 'cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM', 481: 'cassette', 482: 'cassette player', 483: 'castle', 484: 'catamaran', 485: 'CD player', 486: 'cello, violoncello', 487: 'cellular telephone, cellular phone, cellphone, cell, mobile phone', 488: 'chain', 489: 'chainlink fence', 490: 'chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour', 491: 'chain saw, chainsaw', 492: 'chest', 493: 'chiffonier, commode', 494: 'chime, bell, gong', 495: 'china cabinet, china closet', 496: 'Christmas stocking', 497: 'church, church building', 498: 'cinema, movie theater, movie theatre, movie house, picture palace', 499: 'cleaver, meat cleaver, chopper', 500: 'cliff dwelling', 501: 'cloak', 502: 'clog, geta, patten, sabot', 503: 'cocktail shaker', 504: 'coffee mug', 505: 'coffeepot', 506: 'coil, spiral, volute, whorl, helix', 507: 'combination lock', 508: 'computer keyboard, keypad', 509: 'confectionery, confectionary, candy store', 510: 'container ship, containership, container vessel', 511: 'convertible', 512: 'corkscrew, bottle screw', 513: 'cornet, horn, trumpet, trump', 514: 'cowboy boot', 515: 'cowboy hat, ten-gallon hat', 516: 'cradle', 517: 'crane', 518: 'crash helmet', 519: 'crate', 520: 'crib, cot', 521: 'Crock Pot', 522: 'croquet ball', 523: 'crutch', 524: 'cuirass', 525: 'dam, dike, dyke', 526: 'desk', 527: 'desktop computer', 528: 'dial telephone, dial phone', 529: 'diaper, nappy, napkin', 530: 'digital clock', 531: 'digital watch', 532: 'dining table, board', 533: 'dishrag, dishcloth', 534: 'dishwasher, dish washer, dishwashing machine', 535: 'disk brake, disc brake', 536: 'dock, dockage, docking facility', 537: 'dogsled, dog sled, dog sleigh', 538: 'dome', 539: 'doormat, welcome mat', 540: 'drilling platform, offshore rig', 541: 'drum, membranophone, tympan', 542: 'drumstick', 543: 'dumbbell', 544: 'Dutch oven', 545: 'electric fan, blower', 546: 'electric guitar', 547: 'electric locomotive', 548: 'entertainment center', 549: 'envelope', 550: 'espresso maker', 551: 'face powder', 552: 'feather boa, boa', 553: 'file, file cabinet, filing cabinet', 554: 'fireboat', 555: 'fire engine, fire truck', 556: 'fire screen, fireguard', 557: 'flagpole, flagstaff', 558: 'flute, transverse flute', 559: 'folding chair', 560: 'football helmet', 561: 'forklift', 562: 'fountain', 563: 'fountain pen', 564: 'four-poster', 565: 'freight car', 566: 'French horn, horn', 567: 'frying pan, frypan, skillet', 568: 'fur coat', 569: 'garbage truck, dustcart', 570: 'gasmask, respirator, gas helmet', 571: 'gas pump, gasoline pump, petrol pump, island dispenser', 572: 'goblet', 573: 'go-kart', 574: 'golf ball', 575: 'golfcart, golf cart', 576: 'gondola', 577: 'gong, tam-tam', 578: 'gown', 579: 'grand piano, grand', 580: 'greenhouse, nursery, glasshouse', 581: 'grille, radiator grille', 582: 'grocery store, grocery, food market, market', 583: 'guillotine', 584: 'hair slide', 585: 'hair spray', 586: 'half track', 587: 'hammer', 588: 'hamper', 589: 'hand blower, blow dryer, blow drier, hair dryer, hair drier', 590: 'hand-held computer, hand-held microcomputer', 591: 'handkerchief, hankie, hanky, hankey', 592: 'hard disc, hard disk, fixed disk', 593: 'harmonica, mouth organ, harp, mouth harp', 594: 'harp', 595: 'harvester, reaper', 596: 'hatchet', 597: 'holster', 598: 'home theater, home theatre', 599: 'honeycomb', 600: 'hook, claw', 601: 'hoopskirt, crinoline', 602: 'horizontal bar, high bar', 603: 'horse cart, horse-cart', 604: 'hourglass', 605: 'iPod', 606: 'iron, smoothing iron', 607: "jack-o'-lantern", 608: 'jean, blue jean, denim', 609: 'jeep, landrover', 610: 'jersey, T-shirt, tee shirt', 611: 'jigsaw puzzle', 612: 'jinrikisha, ricksha, rickshaw', 613: 'joystick', 614: 'kimono', 615: 'knee pad', 616: 'knot', 617: 'lab coat, laboratory coat', 618: 'ladle', 619: 'lampshade, lamp shade', 620: 'laptop, laptop computer', 621: 'lawn mower, mower', 622: 'lens cap, lens cover', 623: 'letter opener, paper knife, paperknife', 624: 'library', 625: 'lifeboat', 626: 'lighter, light, igniter, ignitor', 627: 'limousine, limo', 628: 'liner, ocean liner', 629: 'lipstick, lip rouge', 630: 'Loafer', 631: 'lotion', 632: 'loudspeaker, speaker, speaker unit, loudspeaker system, speaker system', 633: "loupe, jeweler's loupe", 634: 'lumbermill, sawmill', 635: 'magnetic compass', 636: 'mailbag, postbag', 637: 'mailbox, letter box', 638: 'maillot', 639: 'maillot, tank suit', 640: 'manhole cover', 641: 'maraca', 642: 'marimba, xylophone', 643: 'mask', 644: 'matchstick', 645: 'maypole', 646: 'maze, labyrinth', 647: 'measuring cup', 648: 'medicine chest, medicine cabinet', 649: 'megalith, megalithic structure', 650: 'microphone, mike', 651: 'microwave, microwave oven', 652: 'military uniform', 653: 'milk can', 654: 'minibus', 655: 'miniskirt, mini', 656: 'minivan', 657: 'missile', 658: 'mitten', 659: 'mixing bowl', 660: 'mobile home, manufactured home', 661: 'Model T', 662: 'modem', 663: 'monastery', 664: 'monitor', 665: 'moped', 666: 'mortar', 667: 'mortarboard', 668: 'mosque', 669: 'mosquito net', 670: 'motor scooter, scooter', 671: 'mountain bike, all-terrain bike, off-roader', 672: 'mountain tent', 673: 'mouse, computer mouse', 674: 'mousetrap', 675: 'moving van', 676: 'muzzle', 677: 'nail', 678: 'neck brace', 679: 'necklace', 680: 'nipple', 681: 'notebook, notebook computer', 682: 'obelisk', 683: 'oboe, hautboy, hautbois', 684: 'ocarina, sweet potato', 685: 'odometer, hodometer, mileometer, milometer', 686: 'oil filter', 687: 'organ, pipe organ', 688: 'oscilloscope, scope, cathode-ray oscilloscope, CRO', 689: 'overskirt', 690: 'oxcart', 691: 'oxygen mask', 692: 'packet', 693: 'paddle, boat paddle', 694: 'paddlewheel, paddle wheel', 695: 'padlock', 696: 'paintbrush', 697: "pajama, pyjama, pj's, jammies", 698: 'palace', 699: 'panpipe, pandean pipe, syrinx', 700: 'paper towel', 701: 'parachute, chute', 702: 'parallel bars, bars', 703: 'park bench', 704: 'parking meter', 705: 'passenger car, coach, carriage', 706: 'patio, terrace', 707: 'pay-phone, pay-station', 708: 'pedestal, plinth, footstall', 709: 'pencil box, pencil case', 710: 'pencil sharpener', 711: 'perfume, essence', 712: 'Petri dish', 713: 'photocopier', 714: 'pick, plectrum, plectron', 715: 'pickelhaube', 716: 'picket fence, paling', 717: 'pickup, pickup truck', 718: 'pier', 719: 'piggy bank, penny bank', 720: 'pill bottle', 721: 'pillow', 722: 'ping-pong ball', 723: 'pinwheel', 724: 'pirate, pirate ship', 725: 'pitcher, ewer', 726: "plane, carpenter's plane, woodworking plane", 727: 'planetarium', 728: 'plastic bag', 729: 'plate rack', 730: 'plow, plough', 731: "plunger, plumber's helper", 732: 'Polaroid camera, Polaroid Land camera', 733: 'pole', 734: 'police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria', 735: 'poncho', 736: 'pool table, billiard table, snooker table', 737: 'pop bottle, soda bottle', 738: 'pot, flowerpot', 739: "potter's wheel", 740: 'power drill', 741: 'prayer rug, prayer mat', 742: 'printer', 743: 'prison, prison house', 744: 'projectile, missile', 745: 'projector', 746: 'puck, hockey puck', 747: 'punching bag, punch bag, punching ball, punchball', 748: 'purse', 749: 'quill, quill pen', 750: 'quilt, comforter, comfort, puff', 751: 'racer, race car, racing car', 752: 'racket, racquet', 753: 'radiator', 754: 'radio, wireless', 755: 'radio telescope, radio reflector', 756: 'rain barrel', 757: 'recreational vehicle, RV, R.V.', 758: 'reel', 759: 'reflex camera', 760: 'refrigerator, icebox', 761: 'remote control, remote', 762: 'restaurant, eating house, eating place, eatery', 763: 'revolver, six-gun, six-shooter', 764: 'rifle', 765: 'rocking chair, rocker', 766: 'rotisserie', 767: 'rubber eraser, rubber, pencil eraser', 768: 'rugby ball', 769: 'rule, ruler', 770: 'running shoe', 771: 'safe', 772: 'safety pin', 773: 'saltshaker, salt shaker', 774: 'sandal', 775: 'sarong', 776: 'sax, saxophone', 777: 'scabbard', 778: 'scale, weighing machine', 779: 'school bus', 780: 'schooner', 781: 'scoreboard', 782: 'screen, CRT screen', 783: 'screw', 784: 'screwdriver', 785: 'seat belt, seatbelt', 786: 'sewing machine', 787: 'shield, buckler', 788: 'shoe shop, shoe-shop, shoe store', 789: 'shoji', 790: 'shopping basket', 791: 'shopping cart', 792: 'shovel', 793: 'shower cap', 794: 'shower curtain', 795: 'ski', 796: 'ski mask', 797: 'sleeping bag', 798: 'slide rule, slipstick', 799: 'sliding door', 800: 'slot, one-armed bandit', 801: 'snorkel', 802: 'snowmobile', 803: 'snowplow, snowplough', 804: 'soap dispenser', 805: 'soccer ball', 806: 'sock', 807: 'solar dish, solar collector, solar furnace', 808: 'sombrero', 809: 'soup bowl', 810: 'space bar', 811: 'space heater', 812: 'space shuttle', 813: 'spatula', 814: 'speedboat', 815: "spider web, spider's web", 816: 'spindle', 817: 'sports car, sport car', 818: 'spotlight, spot', 819: 'stage', 820: 'steam locomotive', 821: 'steel arch bridge', 822: 'steel drum', 823: 'stethoscope', 824: 'stole', 825: 'stone wall', 826: 'stopwatch, stop watch', 827: 'stove', 828: 'strainer', 829: 'streetcar, tram, tramcar, trolley, trolley car', 830: 'stretcher', 831: 'studio couch, day bed', 832: 'stupa, tope', 833: 'submarine, pigboat, sub, U-boat', 834: 'suit, suit of clothes', 835: 'sundial', 836: 'sunglass', 837: 'sunglasses, dark glasses, shades', 838: 'sunscreen, sunblock, sun blocker', 839: 'suspension bridge', 840: 'swab, swob, mop', 841: 'sweatshirt', 842: 'swimming trunks, bathing trunks', 843: 'swing', 844: 'switch, electric switch, electrical switch', 845: 'syringe', 846: 'table lamp', 847: 'tank, army tank, armored combat vehicle, armoured combat vehicle', 848: 'tape player', 849: 'teapot', 850: 'teddy, teddy bear', 851: 'television, television system', 852: 'tennis ball', 853: 'thatch, thatched roof', 854: 'theater curtain, theatre curtain', 855: 'thimble', 856: 'thresher, thrasher, threshing machine', 857: 'throne', 858: 'tile roof', 859: 'toaster', 860: 'tobacco shop, tobacconist shop, tobacconist', 861: 'toilet seat', 862: 'torch', 863: 'totem pole', 864: 'tow truck, tow car, wrecker', 865: 'toyshop', 866: 'tractor', 867: 'trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi', 868: 'tray', 869: 'trench coat', 870: 'tricycle, trike, velocipede', 871: 'trimaran', 872: 'tripod', 873: 'triumphal arch', 874: 'trolleybus, trolley coach, trackless trolley', 875: 'trombone', 876: 'tub, vat', 877: 'turnstile', 878: 'typewriter keyboard', 879: 'umbrella', 880: 'unicycle, monocycle', 881: 'upright, upright piano', 882: 'vacuum, vacuum cleaner', 883: 'vase', 884: 'vault', 885: 'velvet', 886: 'vending machine', 887: 'vestment', 888: 'viaduct', 889: 'violin, fiddle', 890: 'volleyball', 891: 'waffle iron', 892: 'wall clock', 893: 'wallet, billfold, notecase, pocketbook', 894: 'wardrobe, closet, press', 895: 'warplane, military plane', 896: 'washbasin, handbasin, washbowl, lavabo, wash-hand basin', 897: 'washer, automatic washer, washing machine', 898: 'water bottle', 899: 'water jug', 900: 'water tower', 901: 'whiskey jug', 902: 'whistle', 903: 'wig', 904: 'window screen', 905: 'window shade', 906: 'Windsor tie', 907: 'wine bottle', 908: 'wing', 909: 'wok', 910: 'wooden spoon', 911: 'wool, woolen, woollen', 912: 'worm fence, snake fence, snake-rail fence, Virginia fence', 913: 'wreck', 914: 'yawl', 915: 'yurt', 916: 'web site, website, internet site, site', 917: 'comic book', 918: 'crossword puzzle, crossword', 919: 'street sign', 920: 'traffic light, traffic signal, stoplight', 921: 'book jacket, dust cover, dust jacket, dust wrapper', 922: 'menu', 923: 'plate', 924: 'guacamole', 925: 'consomme', 926: 'hot pot, hotpot', 927: 'trifle', 928: 'ice cream, icecream', 929: 'ice lolly, lolly, lollipop, popsicle', 930: 'French loaf', 931: 'bagel, beigel', 932: 'pretzel', 933: 'cheeseburger', 934: 'hotdog, hot dog, red hot', 935: 'mashed potato', 936: 'head cabbage', 937: 'broccoli', 938: 'cauliflower', 939: 'zucchini, courgette', 940: 'spaghetti squash', 941: 'acorn squash', 942: 'butternut squash', 943: 'cucumber, cuke', 944: 'artichoke, globe artichoke', 945: 'bell pepper', 946: 'cardoon', 947: 'mushroom', 948: 'Granny Smith', 949: 'strawberry', 950: 'orange', 951: 'lemon', 952: 'fig', 953: 'pineapple, ananas', 954: 'banana', 955: 'jackfruit, jak, jack', 956: 'custard apple', 957: 'pomegranate', 958: 'hay', 959: 'carbonara', 960: 'chocolate sauce, chocolate syrup', 961: 'dough', 962: 'meat loaf, meatloaf', 963: 'pizza, pizza pie', 964: 'potpie', 965: 'burrito', 966: 'red wine', 967: 'espresso', 968: 'cup', 969: 'eggnog', 970: 'alp', 971: 'bubble', 972: 'cliff, drop, drop-off', 973: 'coral reef', 974: 'geyser', 975: 'lakeside, lakeshore', 976: 'promontory, headland, head, foreland', 977: 'sandbar, sand bar', 978: 'seashore, coast, seacoast, sea-coast', 979: 'valley, vale', 980: 'volcano', 981: 'ballplayer, baseball player', 982: 'groom, bridegroom', 983: 'scuba diver', 984: 'rapeseed', 985: 'daisy', 986: "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum", 987: 'corn', 988: 'acorn', 989: 'hip, rose hip, rosehip', 990: 'buckeye, horse chestnut, conker', 991: 'coral fungus', 992: 'agaric', 993: 'gyromitra', 994: 'stinkhorn, carrion fungus', 995: 'earthstar', 996: 'hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa', 997: 'bolete', 998: 'ear, spike, capitulum', 999: 'toilet tissue, toilet paper, bathroom tissue'}

30.576

130

0.680534

idx2label = {0: 'tench, Tinca tinca', 1: 'goldfish, Carassius auratus', 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', 3: 'tiger shark, Galeocerdo cuvieri', 4: 'hammerhead, hammerhead shark', 5: 'electric ray, crampfish, numbfish, torpedo', 6: 'stingray', 7: 'cock', 8: 'hen', 9: 'ostrich, Struthio camelus', 10: 'brambling, Fringilla montifringilla', 11: 'goldfinch, Carduelis carduelis', 12: 'house finch, linnet, Carpodacus mexicanus', 13: 'junco, snowbird', 14: 'indigo bunting, indigo finch, indigo bird, Passerina cyanea', 15: 'robin, American robin, Turdus migratorius', 16: 'bulbul', 17: 'jay', 18: 'magpie', 19: 'chickadee', 20: 'water ouzel, dipper', 21: 'kite', 22: 'bald eagle, American eagle, Haliaeetus leucocephalus', 23: 'vulture', 24: 'great grey owl, great gray owl, Strix nebulosa', 25: 'European fire salamander, Salamandra salamandra', 26: 'common newt, Triturus vulgaris', 27: 'eft', 28: 'spotted salamander, Ambystoma maculatum', 29: 'axolotl, mud puppy, Ambystoma mexicanum', 30: 'bullfrog, Rana catesbeiana', 31: 'tree frog, tree-frog', 32: 'tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui', 33: 'loggerhead, loggerhead turtle, Caretta caretta', 34: 'leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea', 35: 'mud turtle', 36: 'terrapin', 37: 'box turtle, box tortoise', 38: 'banded gecko', 39: 'common iguana, iguana, Iguana iguana', 40: 'American chameleon, anole, Anolis carolinensis', 41: 'whiptail, whiptail lizard', 42: 'agama', 43: 'frilled lizard, Chlamydosaurus kingi', 44: 'alligator lizard', 45: 'Gila monster, Heloderma suspectum', 46: 'green lizard, Lacerta viridis', 47: 'African chameleon, Chamaeleo chamaeleon', 48: 'Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis', 49: 'African crocodile, Nile crocodile, Crocodylus niloticus', 50: 'American alligator, Alligator mississipiensis', 51: 'triceratops', 52: 'thunder snake, worm snake, Carphophis amoenus', 53: 'ringneck snake, ring-necked snake, ring snake', 54: 'hognose snake, puff adder, sand viper', 55: 'green snake, grass snake', 56: 'king snake, kingsnake', 57: 'garter snake, grass snake', 58: 'water snake', 59: 'vine snake', 60: 'night snake, Hypsiglena torquata', 61: 'boa constrictor, Constrictor constrictor', 62: 'rock python, rock snake, Python sebae', 63: 'Indian cobra, Naja naja', 64: 'green mamba', 65: 'sea snake', 66: 'horned viper, cerastes, sand viper, horned asp, Cerastes cornutus', 67: 'diamondback, diamondback rattlesnake, Crotalus adamanteus', 68: 'sidewinder, horned rattlesnake, Crotalus cerastes', 69: 'trilobite', 70: 'harvestman, daddy longlegs, Phalangium opilio', 71: 'scorpion', 72: 'black and gold garden spider, Argiope aurantia', 73: 'barn spider, Araneus cavaticus', 74: 'garden spider, Aranea diademata', 75: 'black widow, Latrodectus mactans', 76: 'tarantula', 77: 'wolf spider, hunting spider', 78: 'tick', 79: 'centipede', 80: 'black grouse', 81: 'ptarmigan', 82: 'ruffed grouse, partridge, Bonasa umbellus', 83: 'prairie chicken, prairie grouse, prairie fowl', 84: 'peacock', 85: 'quail', 86: 'partridge', 87: 'African grey, African gray, Psittacus erithacus', 88: 'macaw', 89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita', 90: 'lorikeet', 91: 'coucal', 92: 'bee eater', 93: 'hornbill', 94: 'hummingbird', 95: 'jacamar', 96: 'toucan', 97: 'drake', 98: 'red-breasted merganser, Mergus serrator', 99: 'goose', 100: 'black swan, Cygnus atratus', 101: 'tusker', 102: 'echidna, spiny anteater, anteater', 103: 'platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus', 104: 'wallaby, brush kangaroo', 105: 'koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus', 106: 'wombat', 107: 'jellyfish', 108: 'sea anemone, anemone', 109: 'brain coral', 110: 'flatworm, platyhelminth', 111: 'nematode, nematode worm, roundworm', 112: 'conch', 113: 'snail', 114: 'slug', 115: 'sea slug, nudibranch', 116: 'chiton, coat-of-mail shell, sea cradle, polyplacophore', 117: 'chambered nautilus, pearly nautilus, nautilus', 118: 'Dungeness crab, Cancer magister', 119: 'rock crab, Cancer irroratus', 120: 'fiddler crab', 121: 'king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica', 122: 'American lobster, Northern lobster, Maine lobster, Homarus americanus', 123: 'spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish', 124: 'crayfish, crawfish, crawdad, crawdaddy', 125: 'hermit crab', 126: 'isopod', 127: 'white stork, Ciconia ciconia', 128: 'black stork, Ciconia nigra', 129: 'spoonbill', 130: 'flamingo', 131: 'little blue heron, Egretta caerulea', 132: 'American egret, great white heron, Egretta albus', 133: 'bittern', 134: 'crane', 135: 'limpkin, Aramus pictus', 136: 'European gallinule, Porphyrio porphyrio', 137: 'American coot, marsh hen, mud hen, water hen, Fulica americana', 138: 'bustard', 139: 'ruddy turnstone, Arenaria interpres', 140: 'red-backed sandpiper, dunlin, Erolia alpina', 141: 'redshank, Tringa totanus', 142: 'dowitcher', 143: 'oystercatcher, oyster catcher', 144: 'pelican', 145: 'king penguin, Aptenodytes patagonica', 146: 'albatross, mollymawk', 147: 'grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus', 148: 'killer whale, killer, orca, grampus, sea wolf, Orcinus orca', 149: 'dugong, Dugong dugon', 150: 'sea lion', 151: 'Chihuahua', 152: 'Japanese spaniel', 153: 'Maltese dog, Maltese terrier, Maltese', 154: 'Pekinese, Pekingese, Peke', 155: 'Shih-Tzu', 156: 'Blenheim spaniel', 157: 'papillon', 158: 'toy terrier', 159: 'Rhodesian ridgeback', 160: 'Afghan hound, Afghan', 161: 'basset, basset hound', 162: 'beagle', 163: 'bloodhound, sleuthhound', 164: 'bluetick', 165: 'black-and-tan coonhound', 166: 'Walker hound, Walker foxhound', 167: 'English foxhound', 168: 'redbone', 169: 'borzoi, Russian wolfhound', 170: 'Irish wolfhound', 171: 'Italian greyhound', 172: 'whippet', 173: 'Ibizan hound, Ibizan Podenco', 174: 'Norwegian elkhound, elkhound', 175: 'otterhound, otter hound', 176: 'Saluki, gazelle hound', 177: 'Scottish deerhound, deerhound', 178: 'Weimaraner', 179: 'Staffordshire bullterrier, Staffordshire bull terrier', 180: 'American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier', 181: 'Bedlington terrier', 182: 'Border terrier', 183: 'Kerry blue terrier', 184: 'Irish terrier', 185: 'Norfolk terrier', 186: 'Norwich terrier', 187: 'Yorkshire terrier', 188: 'wire-haired fox terrier', 189: 'Lakeland terrier', 190: 'Sealyham terrier, Sealyham', 191: 'Airedale, Airedale terrier', 192: 'cairn, cairn terrier', 193: 'Australian terrier', 194: 'Dandie Dinmont, Dandie Dinmont terrier', 195: 'Boston bull, Boston terrier', 196: 'miniature schnauzer', 197: 'giant schnauzer', 198: 'standard schnauzer', 199: 'Scotch terrier, Scottish terrier, Scottie', 200: 'Tibetan terrier, chrysanthemum dog', 201: 'silky terrier, Sydney silky', 202: 'soft-coated wheaten terrier', 203: 'West Highland white terrier', 204: 'Lhasa, Lhasa apso', 205: 'flat-coated retriever', 206: 'curly-coated retriever', 207: 'golden retriever', 208: 'Labrador retriever', 209: 'Chesapeake Bay retriever', 210: 'German short-haired pointer', 211: 'vizsla, Hungarian pointer', 212: 'English setter', 213: 'Irish setter, red setter', 214: 'Gordon setter', 215: 'Brittany spaniel', 216: 'clumber, clumber spaniel', 217: 'English springer, English springer spaniel', 218: 'Welsh springer spaniel', 219: 'cocker spaniel, English cocker spaniel, cocker', 220: 'Sussex spaniel', 221: 'Irish water spaniel', 222: 'kuvasz', 223: 'schipperke', 224: 'groenendael', 225: 'malinois', 226: 'briard', 227: 'kelpie', 228: 'komondor', 229: 'Old English sheepdog, bobtail', 230: 'Shetland sheepdog, Shetland sheep dog, Shetland', 231: 'collie', 232: 'Border collie', 233: 'Bouvier des Flandres, Bouviers des Flandres', 234: 'Rottweiler', 235: 'German shepherd, German shepherd dog, German police dog, alsatian', 236: 'Doberman, Doberman pinscher', 237: 'miniature pinscher', 238: 'Greater Swiss Mountain dog', 239: 'Bernese mountain dog', 240: 'Appenzeller', 241: 'EntleBucher', 242: 'boxer', 243: 'bull mastiff', 244: 'Tibetan mastiff', 245: 'French bulldog', 246: 'Great Dane', 247: 'Saint Bernard, St Bernard', 248: 'Eskimo dog, husky', 249: 'malamute, malemute, Alaskan malamute', 250: 'Siberian husky', 251: 'dalmatian, coach dog, carriage dog', 252: 'affenpinscher, monkey pinscher, monkey dog', 253: 'basenji', 254: 'pug, pug-dog', 255: 'Leonberg', 256: 'Newfoundland, Newfoundland dog', 257: 'Great Pyrenees', 258: 'Samoyed, Samoyede', 259: 'Pomeranian', 260: 'chow, chow chow', 261: 'keeshond', 262: 'Brabancon griffon', 263: 'Pembroke, Pembroke Welsh corgi', 264: 'Cardigan, Cardigan Welsh corgi', 265: 'toy poodle', 266: 'miniature poodle', 267: 'standard poodle', 268: 'Mexican hairless', 269: 'timber wolf, grey wolf, gray wolf, Canis lupus', 270: 'white wolf, Arctic wolf, Canis lupus tundrarum', 271: 'red wolf, maned wolf, Canis rufus, Canis niger', 272: 'coyote, prairie wolf, brush wolf, Canis latrans', 273: 'dingo, warrigal, warragal, Canis dingo', 274: 'dhole, Cuon alpinus', 275: 'African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus', 276: 'hyena, hyaena', 277: 'red fox, Vulpes vulpes', 278: 'kit fox, Vulpes macrotis', 279: 'Arctic fox, white fox, Alopex lagopus', 280: 'grey fox, gray fox, Urocyon cinereoargenteus', 281: 'tabby, tabby cat', 282: 'tiger cat', 283: 'Persian cat', 284: 'Siamese cat, Siamese', 285: 'Egyptian cat', 286: 'cougar, puma, catamount, mountain lion, painter, panther, Felis concolor', 287: 'lynx, catamount', 288: 'leopard, Panthera pardus', 289: 'snow leopard, ounce, Panthera uncia', 290: 'jaguar, panther, Panthera onca, Felis onca', 291: 'lion, king of beasts, Panthera leo', 292: 'tiger, Panthera tigris', 293: 'cheetah, chetah, Acinonyx jubatus', 294: 'brown bear, bruin, Ursus arctos', 295: 'American black bear, black bear, Ursus americanus, Euarctos americanus', 296: 'ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus', 297: 'sloth bear, Melursus ursinus, Ursus ursinus', 298: 'mongoose', 299: 'meerkat, mierkat', 300: 'tiger beetle', 301: 'ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle', 302: 'ground beetle, carabid beetle', 303: 'long-horned beetle, longicorn, longicorn beetle', 304: 'leaf beetle, chrysomelid', 305: 'dung beetle', 306: 'rhinoceros beetle', 307: 'weevil', 308: 'fly', 309: 'bee', 310: 'ant, emmet, pismire', 311: 'grasshopper, hopper', 312: 'cricket', 313: 'walking stick, walkingstick, stick insect', 314: 'cockroach, roach', 315: 'mantis, mantid', 316: 'cicada, cicala', 317: 'leafhopper', 318: 'lacewing, lacewing fly', 319: "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk", 320: 'damselfly', 321: 'admiral', 322: 'ringlet, ringlet butterfly', 323: 'monarch, monarch butterfly, milkweed butterfly, Danaus plexippus', 324: 'cabbage butterfly', 325: 'sulphur butterfly, sulfur butterfly', 326: 'lycaenid, lycaenid butterfly', 327: 'starfish, sea star', 328: 'sea urchin', 329: 'sea cucumber, holothurian', 330: 'wood rabbit, cottontail, cottontail rabbit', 331: 'hare', 332: 'Angora, Angora rabbit', 333: 'hamster', 334: 'porcupine, hedgehog', 335: 'fox squirrel, eastern fox squirrel, Sciurus niger', 336: 'marmot', 337: 'beaver', 338: 'guinea pig, Cavia cobaya', 339: 'sorrel', 340: 'zebra', 341: 'hog, pig, grunter, squealer, Sus scrofa', 342: 'wild boar, boar, Sus scrofa', 343: 'warthog', 344: 'hippopotamus, hippo, river horse, Hippopotamus amphibius', 345: 'ox', 346: 'water buffalo, water ox, Asiatic buffalo, Bubalus bubalis', 347: 'bison', 348: 'ram, tup', 349: 'bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis', 350: 'ibex, Capra ibex', 351: 'hartebeest', 352: 'impala, Aepyceros melampus', 353: 'gazelle', 354: 'Arabian camel, dromedary, Camelus dromedarius', 355: 'llama', 356: 'weasel', 357: 'mink', 358: 'polecat, fitch, foulmart, foumart, Mustela putorius', 359: 'black-footed ferret, ferret, Mustela nigripes', 360: 'otter', 361: 'skunk, polecat, wood pussy', 362: 'badger', 363: 'armadillo', 364: 'three-toed sloth, ai, Bradypus tridactylus', 365: 'orangutan, orang, orangutang, Pongo pygmaeus', 366: 'gorilla, Gorilla gorilla', 367: 'chimpanzee, chimp, Pan troglodytes', 368: 'gibbon, Hylobates lar', 369: 'siamang, Hylobates syndactylus, Symphalangus syndactylus', 370: 'guenon, guenon monkey', 371: 'patas, hussar monkey, Erythrocebus patas', 372: 'baboon', 373: 'macaque', 374: 'langur', 375: 'colobus, colobus monkey', 376: 'proboscis monkey, Nasalis larvatus', 377: 'marmoset', 378: 'capuchin, ringtail, Cebus capucinus', 379: 'howler monkey, howler', 380: 'titi, titi monkey', 381: 'spider monkey, Ateles geoffroyi', 382: 'squirrel monkey, Saimiri sciureus', 383: 'Madagascar cat, ring-tailed lemur, Lemur catta', 384: 'indri, indris, Indri indri, Indri brevicaudatus', 385: 'Indian elephant, Elephas maximus', 386: 'African elephant, Loxodonta africana', 387: 'lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens', 388: 'giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca', 389: 'barracouta, snoek', 390: 'eel', 391: 'coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch', 392: 'rock beauty, Holocanthus tricolor', 393: 'anemone fish', 394: 'sturgeon', 395: 'gar, garfish, garpike, billfish, Lepisosteus osseus', 396: 'lionfish', 397: 'puffer, pufferfish, blowfish, globefish', 398: 'abacus', 399: 'abaya', 400: "academic gown, academic robe, judge's robe", 401: 'accordion, piano accordion, squeeze box', 402: 'acoustic guitar', 403: 'aircraft carrier, carrier, flattop, attack aircraft carrier', 404: 'airliner', 405: 'airship, dirigible', 406: 'altar', 407: 'ambulance', 408: 'amphibian, amphibious vehicle', 409: 'analog clock', 410: 'apiary, bee house', 411: 'apron', 412: 'ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin', 413: 'assault rifle, assault gun', 414: 'backpack, back pack, knapsack, packsack, rucksack, haversack', 415: 'bakery, bakeshop, bakehouse', 416: 'balance beam, beam', 417: 'balloon', 418: 'ballpoint, ballpoint pen, ballpen, Biro', 419: 'Band Aid', 420: 'banjo', 421: 'bannister, banister, balustrade, balusters, handrail', 422: 'barbell', 423: 'barber chair', 424: 'barbershop', 425: 'barn', 426: 'barometer', 427: 'barrel, cask', 428: 'barrow, garden cart, lawn cart, wheelbarrow', 429: 'baseball', 430: 'basketball', 431: 'bassinet', 432: 'bassoon', 433: 'bathing cap, swimming cap', 434: 'bath towel', 435: 'bathtub, bathing tub, bath, tub', 436: 'beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon', 437: 'beacon, lighthouse, beacon light, pharos', 438: 'beaker', 439: 'bearskin, busby, shako', 440: 'beer bottle', 441: 'beer glass', 442: 'bell cote, bell cot', 443: 'bib', 444: 'bicycle-built-for-two, tandem bicycle, tandem', 445: 'bikini, two-piece', 446: 'binder, ring-binder', 447: 'binoculars, field glasses, opera glasses', 448: 'birdhouse', 449: 'boathouse', 450: 'bobsled, bobsleigh, bob', 451: 'bolo tie, bolo, bola tie, bola', 452: 'bonnet, poke bonnet', 453: 'bookcase', 454: 'bookshop, bookstore, bookstall', 455: 'bottlecap', 456: 'bow', 457: 'bow tie, bow-tie, bowtie', 458: 'brass, memorial tablet, plaque', 459: 'brassiere, bra, bandeau', 460: 'breakwater, groin, groyne, mole, bulwark, seawall, jetty', 461: 'breastplate, aegis, egis', 462: 'broom', 463: 'bucket, pail', 464: 'buckle', 465: 'bulletproof vest', 466: 'bullet train, bullet', 467: 'butcher shop, meat market', 468: 'cab, hack, taxi, taxicab', 469: 'caldron, cauldron', 470: 'candle, taper, wax light', 471: 'cannon', 472: 'canoe', 473: 'can opener, tin opener', 474: 'cardigan', 475: 'car mirror', 476: 'carousel, carrousel, merry-go-round, roundabout, whirligig', 477: "carpenter's kit, tool kit", 478: 'carton', 479: 'car wheel', 480: 'cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM', 481: 'cassette', 482: 'cassette player', 483: 'castle', 484: 'catamaran', 485: 'CD player', 486: 'cello, violoncello', 487: 'cellular telephone, cellular phone, cellphone, cell, mobile phone', 488: 'chain', 489: 'chainlink fence', 490: 'chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour', 491: 'chain saw, chainsaw', 492: 'chest', 493: 'chiffonier, commode', 494: 'chime, bell, gong', 495: 'china cabinet, china closet', 496: 'Christmas stocking', 497: 'church, church building', 498: 'cinema, movie theater, movie theatre, movie house, picture palace', 499: 'cleaver, meat cleaver, chopper', 500: 'cliff dwelling', 501: 'cloak', 502: 'clog, geta, patten, sabot', 503: 'cocktail shaker', 504: 'coffee mug', 505: 'coffeepot', 506: 'coil, spiral, volute, whorl, helix', 507: 'combination lock', 508: 'computer keyboard, keypad', 509: 'confectionery, confectionary, candy store', 510: 'container ship, containership, container vessel', 511: 'convertible', 512: 'corkscrew, bottle screw', 513: 'cornet, horn, trumpet, trump', 514: 'cowboy boot', 515: 'cowboy hat, ten-gallon hat', 516: 'cradle', 517: 'crane', 518: 'crash helmet', 519: 'crate', 520: 'crib, cot', 521: 'Crock Pot', 522: 'croquet ball', 523: 'crutch', 524: 'cuirass', 525: 'dam, dike, dyke', 526: 'desk', 527: 'desktop computer', 528: 'dial telephone, dial phone', 529: 'diaper, nappy, napkin', 530: 'digital clock', 531: 'digital watch', 532: 'dining table, board', 533: 'dishrag, dishcloth', 534: 'dishwasher, dish washer, dishwashing machine', 535: 'disk brake, disc brake', 536: 'dock, dockage, docking facility', 537: 'dogsled, dog sled, dog sleigh', 538: 'dome', 539: 'doormat, welcome mat', 540: 'drilling platform, offshore rig', 541: 'drum, membranophone, tympan', 542: 'drumstick', 543: 'dumbbell', 544: 'Dutch oven', 545: 'electric fan, blower', 546: 'electric guitar', 547: 'electric locomotive', 548: 'entertainment center', 549: 'envelope', 550: 'espresso maker', 551: 'face powder', 552: 'feather boa, boa', 553: 'file, file cabinet, filing cabinet', 554: 'fireboat', 555: 'fire engine, fire truck', 556: 'fire screen, fireguard', 557: 'flagpole, flagstaff', 558: 'flute, transverse flute', 559: 'folding chair', 560: 'football helmet', 561: 'forklift', 562: 'fountain', 563: 'fountain pen', 564: 'four-poster', 565: 'freight car', 566: 'French horn, horn', 567: 'frying pan, frypan, skillet', 568: 'fur coat', 569: 'garbage truck, dustcart', 570: 'gasmask, respirator, gas helmet', 571: 'gas pump, gasoline pump, petrol pump, island dispenser', 572: 'goblet', 573: 'go-kart', 574: 'golf ball', 575: 'golfcart, golf cart', 576: 'gondola', 577: 'gong, tam-tam', 578: 'gown', 579: 'grand piano, grand', 580: 'greenhouse, nursery, glasshouse', 581: 'grille, radiator grille', 582: 'grocery store, grocery, food market, market', 583: 'guillotine', 584: 'hair slide', 585: 'hair spray', 586: 'half track', 587: 'hammer', 588: 'hamper', 589: 'hand blower, blow dryer, blow drier, hair dryer, hair drier', 590: 'hand-held computer, hand-held microcomputer', 591: 'handkerchief, hankie, hanky, hankey', 592: 'hard disc, hard disk, fixed disk', 593: 'harmonica, mouth organ, harp, mouth harp', 594: 'harp', 595: 'harvester, reaper', 596: 'hatchet', 597: 'holster', 598: 'home theater, home theatre', 599: 'honeycomb', 600: 'hook, claw', 601: 'hoopskirt, crinoline', 602: 'horizontal bar, high bar', 603: 'horse cart, horse-cart', 604: 'hourglass', 605: 'iPod', 606: 'iron, smoothing iron', 607: "jack-o'-lantern", 608: 'jean, blue jean, denim', 609: 'jeep, landrover', 610: 'jersey, T-shirt, tee shirt', 611: 'jigsaw puzzle', 612: 'jinrikisha, ricksha, rickshaw', 613: 'joystick', 614: 'kimono', 615: 'knee pad', 616: 'knot', 617: 'lab coat, laboratory coat', 618: 'ladle', 619: 'lampshade, lamp shade', 620: 'laptop, laptop computer', 621: 'lawn mower, mower', 622: 'lens cap, lens cover', 623: 'letter opener, paper knife, paperknife', 624: 'library', 625: 'lifeboat', 626: 'lighter, light, igniter, ignitor', 627: 'limousine, limo', 628: 'liner, ocean liner', 629: 'lipstick, lip rouge', 630: 'Loafer', 631: 'lotion', 632: 'loudspeaker, speaker, speaker unit, loudspeaker system, speaker system', 633: "loupe, jeweler's loupe", 634: 'lumbermill, sawmill', 635: 'magnetic compass', 636: 'mailbag, postbag', 637: 'mailbox, letter box', 638: 'maillot', 639: 'maillot, tank suit', 640: 'manhole cover', 641: 'maraca', 642: 'marimba, xylophone', 643: 'mask', 644: 'matchstick', 645: 'maypole', 646: 'maze, labyrinth', 647: 'measuring cup', 648: 'medicine chest, medicine cabinet', 649: 'megalith, megalithic structure', 650: 'microphone, mike', 651: 'microwave, microwave oven', 652: 'military uniform', 653: 'milk can', 654: 'minibus', 655: 'miniskirt, mini', 656: 'minivan', 657: 'missile', 658: 'mitten', 659: 'mixing bowl', 660: 'mobile home, manufactured home', 661: 'Model T', 662: 'modem', 663: 'monastery', 664: 'monitor', 665: 'moped', 666: 'mortar', 667: 'mortarboard', 668: 'mosque', 669: 'mosquito net', 670: 'motor scooter, scooter', 671: 'mountain bike, all-terrain bike, off-roader', 672: 'mountain tent', 673: 'mouse, computer mouse', 674: 'mousetrap', 675: 'moving van', 676: 'muzzle', 677: 'nail', 678: 'neck brace', 679: 'necklace', 680: 'nipple', 681: 'notebook, notebook computer', 682: 'obelisk', 683: 'oboe, hautboy, hautbois', 684: 'ocarina, sweet potato', 685: 'odometer, hodometer, mileometer, milometer', 686: 'oil filter', 687: 'organ, pipe organ', 688: 'oscilloscope, scope, cathode-ray oscilloscope, CRO', 689: 'overskirt', 690: 'oxcart', 691: 'oxygen mask', 692: 'packet', 693: 'paddle, boat paddle', 694: 'paddlewheel, paddle wheel', 695: 'padlock', 696: 'paintbrush', 697: "pajama, pyjama, pj's, jammies", 698: 'palace', 699: 'panpipe, pandean pipe, syrinx', 700: 'paper towel', 701: 'parachute, chute', 702: 'parallel bars, bars', 703: 'park bench', 704: 'parking meter', 705: 'passenger car, coach, carriage', 706: 'patio, terrace', 707: 'pay-phone, pay-station', 708: 'pedestal, plinth, footstall', 709: 'pencil box, pencil case', 710: 'pencil sharpener', 711: 'perfume, essence', 712: 'Petri dish', 713: 'photocopier', 714: 'pick, plectrum, plectron', 715: 'pickelhaube', 716: 'picket fence, paling', 717: 'pickup, pickup truck', 718: 'pier', 719: 'piggy bank, penny bank', 720: 'pill bottle', 721: 'pillow', 722: 'ping-pong ball', 723: 'pinwheel', 724: 'pirate, pirate ship', 725: 'pitcher, ewer', 726: "plane, carpenter's plane, woodworking plane", 727: 'planetarium', 728: 'plastic bag', 729: 'plate rack', 730: 'plow, plough', 731: "plunger, plumber's helper", 732: 'Polaroid camera, Polaroid Land camera', 733: 'pole', 734: 'police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria', 735: 'poncho', 736: 'pool table, billiard table, snooker table', 737: 'pop bottle, soda bottle', 738: 'pot, flowerpot', 739: "potter's wheel", 740: 'power drill', 741: 'prayer rug, prayer mat', 742: 'printer', 743: 'prison, prison house', 744: 'projectile, missile', 745: 'projector', 746: 'puck, hockey puck', 747: 'punching bag, punch bag, punching ball, punchball', 748: 'purse', 749: 'quill, quill pen', 750: 'quilt, comforter, comfort, puff', 751: 'racer, race car, racing car', 752: 'racket, racquet', 753: 'radiator', 754: 'radio, wireless', 755: 'radio telescope, radio reflector', 756: 'rain barrel', 757: 'recreational vehicle, RV, R.V.', 758: 'reel', 759: 'reflex camera', 760: 'refrigerator, icebox', 761: 'remote control, remote', 762: 'restaurant, eating house, eating place, eatery', 763: 'revolver, six-gun, six-shooter', 764: 'rifle', 765: 'rocking chair, rocker', 766: 'rotisserie', 767: 'rubber eraser, rubber, pencil eraser', 768: 'rugby ball', 769: 'rule, ruler', 770: 'running shoe', 771: 'safe', 772: 'safety pin', 773: 'saltshaker, salt shaker', 774: 'sandal', 775: 'sarong', 776: 'sax, saxophone', 777: 'scabbard', 778: 'scale, weighing machine', 779: 'school bus', 780: 'schooner', 781: 'scoreboard', 782: 'screen, CRT screen', 783: 'screw', 784: 'screwdriver', 785: 'seat belt, seatbelt', 786: 'sewing machine', 787: 'shield, buckler', 788: 'shoe shop, shoe-shop, shoe store', 789: 'shoji', 790: 'shopping basket', 791: 'shopping cart', 792: 'shovel', 793: 'shower cap', 794: 'shower curtain', 795: 'ski', 796: 'ski mask', 797: 'sleeping bag', 798: 'slide rule, slipstick', 799: 'sliding door', 800: 'slot, one-armed bandit', 801: 'snorkel', 802: 'snowmobile', 803: 'snowplow, snowplough', 804: 'soap dispenser', 805: 'soccer ball', 806: 'sock', 807: 'solar dish, solar collector, solar furnace', 808: 'sombrero', 809: 'soup bowl', 810: 'space bar', 811: 'space heater', 812: 'space shuttle', 813: 'spatula', 814: 'speedboat', 815: "spider web, spider's web", 816: 'spindle', 817: 'sports car, sport car', 818: 'spotlight, spot', 819: 'stage', 820: 'steam locomotive', 821: 'steel arch bridge', 822: 'steel drum', 823: 'stethoscope', 824: 'stole', 825: 'stone wall', 826: 'stopwatch, stop watch', 827: 'stove', 828: 'strainer', 829: 'streetcar, tram, tramcar, trolley, trolley car', 830: 'stretcher', 831: 'studio couch, day bed', 832: 'stupa, tope', 833: 'submarine, pigboat, sub, U-boat', 834: 'suit, suit of clothes', 835: 'sundial', 836: 'sunglass', 837: 'sunglasses, dark glasses, shades', 838: 'sunscreen, sunblock, sun blocker', 839: 'suspension bridge', 840: 'swab, swob, mop', 841: 'sweatshirt', 842: 'swimming trunks, bathing trunks', 843: 'swing', 844: 'switch, electric switch, electrical switch', 845: 'syringe', 846: 'table lamp', 847: 'tank, army tank, armored combat vehicle, armoured combat vehicle', 848: 'tape player', 849: 'teapot', 850: 'teddy, teddy bear', 851: 'television, television system', 852: 'tennis ball', 853: 'thatch, thatched roof', 854: 'theater curtain, theatre curtain', 855: 'thimble', 856: 'thresher, thrasher, threshing machine', 857: 'throne', 858: 'tile roof', 859: 'toaster', 860: 'tobacco shop, tobacconist shop, tobacconist', 861: 'toilet seat', 862: 'torch', 863: 'totem pole', 864: 'tow truck, tow car, wrecker', 865: 'toyshop', 866: 'tractor', 867: 'trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi', 868: 'tray', 869: 'trench coat', 870: 'tricycle, trike, velocipede', 871: 'trimaran', 872: 'tripod', 873: 'triumphal arch', 874: 'trolleybus, trolley coach, trackless trolley', 875: 'trombone', 876: 'tub, vat', 877: 'turnstile', 878: 'typewriter keyboard', 879: 'umbrella', 880: 'unicycle, monocycle', 881: 'upright, upright piano', 882: 'vacuum, vacuum cleaner', 883: 'vase', 884: 'vault', 885: 'velvet', 886: 'vending machine', 887: 'vestment', 888: 'viaduct', 889: 'violin, fiddle', 890: 'volleyball', 891: 'waffle iron', 892: 'wall clock', 893: 'wallet, billfold, notecase, pocketbook', 894: 'wardrobe, closet, press', 895: 'warplane, military plane', 896: 'washbasin, handbasin, washbowl, lavabo, wash-hand basin', 897: 'washer, automatic washer, washing machine', 898: 'water bottle', 899: 'water jug', 900: 'water tower', 901: 'whiskey jug', 902: 'whistle', 903: 'wig', 904: 'window screen', 905: 'window shade', 906: 'Windsor tie', 907: 'wine bottle', 908: 'wing', 909: 'wok', 910: 'wooden spoon', 911: 'wool, woolen, woollen', 912: 'worm fence, snake fence, snake-rail fence, Virginia fence', 913: 'wreck', 914: 'yawl', 915: 'yurt', 916: 'web site, website, internet site, site', 917: 'comic book', 918: 'crossword puzzle, crossword', 919: 'street sign', 920: 'traffic light, traffic signal, stoplight', 921: 'book jacket, dust cover, dust jacket, dust wrapper', 922: 'menu', 923: 'plate', 924: 'guacamole', 925: 'consomme', 926: 'hot pot, hotpot', 927: 'trifle', 928: 'ice cream, icecream', 929: 'ice lolly, lolly, lollipop, popsicle', 930: 'French loaf', 931: 'bagel, beigel', 932: 'pretzel', 933: 'cheeseburger', 934: 'hotdog, hot dog, red hot', 935: 'mashed potato', 936: 'head cabbage', 937: 'broccoli', 938: 'cauliflower', 939: 'zucchini, courgette', 940: 'spaghetti squash', 941: 'acorn squash', 942: 'butternut squash', 943: 'cucumber, cuke', 944: 'artichoke, globe artichoke', 945: 'bell pepper', 946: 'cardoon', 947: 'mushroom', 948: 'Granny Smith', 949: 'strawberry', 950: 'orange', 951: 'lemon', 952: 'fig', 953: 'pineapple, ananas', 954: 'banana', 955: 'jackfruit, jak, jack', 956: 'custard apple', 957: 'pomegranate', 958: 'hay', 959: 'carbonara', 960: 'chocolate sauce, chocolate syrup', 961: 'dough', 962: 'meat loaf, meatloaf', 963: 'pizza, pizza pie', 964: 'potpie', 965: 'burrito', 966: 'red wine', 967: 'espresso', 968: 'cup', 969: 'eggnog', 970: 'alp', 971: 'bubble', 972: 'cliff, drop, drop-off', 973: 'coral reef', 974: 'geyser', 975: 'lakeside, lakeshore', 976: 'promontory, headland, head, foreland', 977: 'sandbar, sand bar', 978: 'seashore, coast, seacoast, sea-coast', 979: 'valley, vale', 980: 'volcano', 981: 'ballplayer, baseball player', 982: 'groom, bridegroom', 983: 'scuba diver', 984: 'rapeseed', 985: 'daisy', 986: "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum", 987: 'corn', 988: 'acorn', 989: 'hip, rose hip, rosehip', 990: 'buckeye, horse chestnut, conker', 991: 'coral fungus', 992: 'agaric', 993: 'gyromitra', 994: 'stinkhorn, carrion fungus', 995: 'earthstar', 996: 'hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa', 997: 'bolete', 998: 'ear, spike, capitulum', 999: 'toilet tissue, toilet paper, bathroom tissue'}

true

1c2fb54378459ed8b7825cffc34fee728bda2df1

378

py

Python

lib/datasets/_init_paths.py

liuqiang3/faster-rcnn

b665b46223d8623222f4d67299c232e39b242299

[ "MIT" ]

null

lib/datasets/_init_paths.py

liuqiang3/faster-rcnn

b665b46223d8623222f4d67299c232e39b242299

[ "MIT" ]

null

lib/datasets/_init_paths.py

liuqiang3/faster-rcnn

b665b46223d8623222f4d67299c232e39b242299

[ "MIT" ]

null

import os.path as osp import sys def add_path(path): if path not in sys.path: sys.path.insert(0, path) this_dir = osp.dirname(__file__) # Add lib to PYTHONPATH lib_path = osp.join(this_dir, '..', 'lib') add_path(lib_path) coco_path = osp.join(this_dir, '..', 'data', 'coco', 'PythonAPI') add_path(coco_path) lib_path = osp.join(this_dir, '..') add_path(lib_path)

22.235294

65

0.687831

import os.path as osp import sys def add_path(path): if path not in sys.path: sys.path.insert(0, path) this_dir = osp.dirname(__file__) lib_path = osp.join(this_dir, '..', 'lib') add_path(lib_path) coco_path = osp.join(this_dir, '..', 'data', 'coco', 'PythonAPI') add_path(coco_path) lib_path = osp.join(this_dir, '..') add_path(lib_path)

true

1c2fb5e395071cbfd684013207b19f4d5adecb86

18,724

py

Python

train.py

tsis-mobile-technology/deep-text-recognition-benchmark

d742dee8b13958437ec8565e70121732669fd704

[ "Apache-2.0" ]

null

train.py

tsis-mobile-technology/deep-text-recognition-benchmark

d742dee8b13958437ec8565e70121732669fd704

[ "Apache-2.0" ]

null

train.py

tsis-mobile-technology/deep-text-recognition-benchmark

d742dee8b13958437ec8565e70121732669fd704

[ "Apache-2.0" ]

null

#-*-coding:utf-8-*- import os import sys import time import random import string import argparse import torch import torch.backends.cudnn as cudnn import torch.nn.init as init import torch.optim as optim import torch.utils.data import numpy as np from utils import CTCLabelConverter, CTCLabelConverterForBaiduWarpctc, AttnLabelConverter, Averager from dataset import hierarchical_dataset, AlignCollate, Batch_Balanced_Dataset from model import Model from test import validation device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') ## 한글 학습을 위한 configuration (train.py) # python train.py --train_data /Users/gotaejong/ExternHard/97_Workspace/jupyter/Text_in_the_wild/data_lmdb/train --valid_data /Users/gotaejong/ExternHard/97_Workspace/jupyter/Text_in_the_wild/data_lmdb/validation --Transformation TPS --FeatureExtraction ResNet --SequenceModeling BiLSTM --Prediction CTC --data_filtering_off --workers 0 --imgH 64 --imgW 200 def train(opt): """ dataset preparation """ if not opt.data_filtering_off: print('Filtering the images containing characters which are not in opt.character') print('Filtering the images whose label is longer than opt.batch_max_length') # see https://github.com/clovaai/deep-text-recognition-benchmark/blob/6593928855fb7abb999a99f428b3e4477d4ae356/dataset.py#L130 opt.select_data = opt.select_data.split('-') opt.batch_ratio = opt.batch_ratio.split('-') train_dataset = Batch_Balanced_Dataset(opt) log = open(f'./saved_models/{opt.exp_name}/log_dataset.txt', 'a') AlignCollate_valid = AlignCollate(imgH=opt.imgH, imgW=opt.imgW, keep_ratio_with_pad=opt.PAD) valid_dataset, valid_dataset_log = hierarchical_dataset(root=opt.valid_data, opt=opt) valid_loader = torch.utils.data.DataLoader( valid_dataset, batch_size=opt.batch_size, shuffle=True, # 'True' to check training progress with validation function. num_workers=int(opt.workers), collate_fn=AlignCollate_valid, pin_memory=True) log.write(valid_dataset_log) print('-' * 80) log.write('-' * 80 + '\n') log.close() """ model configuration """ if 'CTC' in opt.Prediction: if opt.baiduCTC: converter = CTCLabelConverterForBaiduWarpctc(opt.character) else: converter = CTCLabelConverter(opt.character) else: converter = AttnLabelConverter(opt.character) opt.num_class = len(converter.character) if opt.rgb: opt.input_channel = 3 model = Model(opt) print('model input parameters', opt.imgH, opt.imgW, opt.num_fiducial, opt.input_channel, opt.output_channel, opt.hidden_size, opt.num_class, opt.batch_max_length, opt.Transformation, opt.FeatureExtraction, opt.SequenceModeling, opt.Prediction) # weight initialization for name, param in model.named_parameters(): if 'localization_fc2' in name: print(f'Skip {name} as it is already initialized') continue try: if 'bias' in name: init.constant_(param, 0.0) elif 'weight' in name: init.kaiming_normal_(param) except Exception as e: # for batchnorm. if 'weight' in name: param.data.fill_(1) continue # data parallel for multi-GPU model = torch.nn.DataParallel(model).to(device) model.train() if opt.saved_model != '': print(f'loading pretrained model from {opt.saved_model}') if opt.FT: # GPU # model.load_state_dict(torch.load(opt.saved_model), strict=False) # CPU model.load_state_dict(torch.load(opt.saved_model, map_location=torch.device('cpu')), strict=False) else: model.load_state_dict(torch.load(opt.saved_model)) print("Model:") print(model) """ setup loss """ if 'CTC' in opt.Prediction: if opt.baiduCTC: # need to install warpctc. see our guideline. # > 3/2 ERROR: warpctc_pytorch-0.2.1+torch16.cpu-cp38-cp38-manylinux1_x86_64.whl is not a supported wheel on this platform. # from warpctc_pytorch import CTCLoss # criterion = CTCLoss() criterion = torch.nn.CTCLoss(zero_infinity=True).to(device) else: criterion = torch.nn.CTCLoss(zero_infinity=True).to(device) else: criterion = torch.nn.CrossEntropyLoss(ignore_index=0).to(device) # ignore [GO] token = ignore index 0 # loss averager loss_avg = Averager() # filter that only require gradient decent filtered_parameters = [] params_num = [] for p in filter(lambda p: p.requires_grad, model.parameters()): filtered_parameters.append(p) params_num.append(np.prod(p.size())) print('Trainable params num : ', sum(params_num)) # [print(name, p.numel()) for name, p in filter(lambda p: p[1].requires_grad, model.named_parameters())] # setup optimizer if opt.adam: optimizer = optim.Adam(filtered_parameters, lr=opt.lr, betas=(opt.beta1, 0.999)) else: optimizer = optim.Adadelta(filtered_parameters, lr=opt.lr, rho=opt.rho, eps=opt.eps) print("Optimizer:") print(optimizer) """ final options """ # print(opt) with open(f'./saved_models/{opt.exp_name}/opt.txt', 'a') as opt_file: opt_log = '------------ Options -------------\n' args = vars(opt) for k, v in args.items(): opt_log += f'{str(k)}: {str(v)}\n' opt_log += '---------------------------------------\n' print(opt_log) opt_file.write(opt_log) """ start training """ start_iter = 0 if opt.saved_model != '': try: start_iter = int(opt.saved_model.split('_')[-1].split('.')[0]) print(f'continue to train, start_iter: {start_iter}') except: pass start_time = time.time() best_accuracy = -1 best_norm_ED = -1 iteration = start_iter while(True): # train part image_tensors, labels = train_dataset.get_batch() image = image_tensors.to(device) text, length = converter.encode(labels, batch_max_length=opt.batch_max_length) batch_size = image.size(0) if 'CTC' in opt.Prediction: preds = model(image, text) preds_size = torch.IntTensor([preds.size(1)] * batch_size) if opt.baiduCTC: preds = preds.permute(1, 0, 2) # to use CTCLoss format cost = criterion(preds, text, preds_size, length) / batch_size else: preds = preds.log_softmax(2).permute(1, 0, 2) cost = criterion(preds, text, preds_size, length) else: preds = model(image, text[:, :-1]) # align with Attention.forward target = text[:, 1:] # without [GO] Symbol cost = criterion(preds.view(-1, preds.shape[-1]), target.contiguous().view(-1)) model.zero_grad() cost.backward() torch.nn.utils.clip_grad_norm_(model.parameters(), opt.grad_clip) # gradient clipping with 5 (Default) optimizer.step() loss_avg.add(cost) # validation part if (iteration + 1) % opt.valInterval == 0 or iteration == 0: # To see training progress, we also conduct validation when 'iteration == 0' elapsed_time = time.time() - start_time # for log with open(f'./saved_models/{opt.exp_name}/log_train.txt', 'a') as log: model.eval() with torch.no_grad(): valid_loss, current_accuracy, current_norm_ED, preds, confidence_score, labels, infer_time, length_of_data = validation( model, criterion, valid_loader, converter, opt) model.train() # training loss and validation loss loss_log = f'[{iteration+1}/{opt.num_iter}] Train loss: {loss_avg.val():0.5f}, Valid loss: {valid_loss:0.5f}, Elapsed_time: {elapsed_time:0.5f}' loss_avg.reset() current_model_log = f'{"Current_accuracy":17s}: {current_accuracy:0.3f}, {"Current_norm_ED":17s}: {current_norm_ED:0.2f}' # keep best accuracy model (on valid dataset) if current_accuracy > best_accuracy: best_accuracy = current_accuracy torch.save(model.state_dict(), f'./saved_models/{opt.exp_name}/best_accuracy.pth') if current_norm_ED > best_norm_ED: best_norm_ED = current_norm_ED torch.save(model.state_dict(), f'./saved_models/{opt.exp_name}/best_norm_ED.pth') best_model_log = f'{"Best_accuracy":17s}: {best_accuracy:0.3f}, {"Best_norm_ED":17s}: {best_norm_ED:0.2f}' loss_model_log = f'{loss_log}\n{current_model_log}\n{best_model_log}' print(loss_model_log) log.write(loss_model_log + '\n') # show some predicted results dashed_line = '-' * 80 head = f'{"Ground Truth":25s} | {"Prediction":25s} | Confidence Score & T/F' predicted_result_log = f'{dashed_line}\n{head}\n{dashed_line}\n' for gt, pred, confidence in zip(labels[:5], preds[:5], confidence_score[:5]): if 'Attn' in opt.Prediction: gt = gt[:gt.find('[s]')] pred = pred[:pred.find('[s]')] predicted_result_log += f'{gt:25s} | {pred:25s} | {confidence:0.4f}\t{str(pred == gt)}\n' predicted_result_log += f'{dashed_line}' print(predicted_result_log) log.write(predicted_result_log + '\n') # save model per 1e+5 iter. if (iteration + 1) % 1e+5 == 0: torch.save( model.state_dict(), f'./saved_models/{opt.exp_name}/iter_{iteration+1}.pth') if (iteration + 1) == opt.num_iter: print('end the training') sys.exit() iteration += 1 if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--exp_name', help='Where to store logs and models') parser.add_argument('--train_data', required=True, help='path to training dataset') parser.add_argument('--valid_data', required=True, help='path to validation dataset') parser.add_argument('--manualSeed', type=int, default=1111, help='for random seed setting') parser.add_argument('--workers', type=int, help='number of data loading workers', default=4) parser.add_argument('--batch_size', type=int, default=192, help='input batch size') parser.add_argument('--num_iter', type=int, default=300000, help='number of iterations to train for') parser.add_argument('--valInterval', type=int, default=2000, help='Interval between each validation') parser.add_argument('--saved_model', default='', help="path to model to continue training") parser.add_argument('--FT', action='store_true', help='whether to do fine-tuning') parser.add_argument('--adam', action='store_true', help='Whether to use adam (default is Adadelta)') parser.add_argument('--lr', type=float, default=1, help='learning rate, default=1.0 for Adadelta') parser.add_argument('--beta1', type=float, default=0.9, help='beta1 for adam. default=0.9') parser.add_argument('--rho', type=float, default=0.95, help='decay rate rho for Adadelta. default=0.95') parser.add_argument('--eps', type=float, default=1e-8, help='eps for Adadelta. default=1e-8') parser.add_argument('--grad_clip', type=float, default=5, help='gradient clipping value. default=5') parser.add_argument('--baiduCTC', action='store_true', help='for data_filtering_off mode') """ Data processing """ ## default # parser.add_argument('--select_data', type=str, default='MJ-ST', # help='select training data (default is MJ-ST, which means MJ and ST used as training data)') # parser.add_argument('--batch_ratio', type=str, default='0.5-0.5', # help='assign ratio for each selected data in the batch') ## Text in the Wild case parser.add_argument('--select_data', type=str, default='/', help='select training data') parser.add_argument('--batch_ratio', type=str, default='1', help='assign ratio for each selected data in the batch') parser.add_argument('--total_data_usage_ratio', type=str, default='1.0', help='total data usage ratio, this ratio is multiplied to total number of data.') parser.add_argument('--batch_max_length', type=int, default=25, help='maximum-label-length') parser.add_argument('--imgH', type=int, default=32, help='the height of the input image') parser.add_argument('--imgW', type=int, default=100, help='the width of the input image') parser.add_argument('--rgb', action='store_true', help='use rgb input') ## default # parser.add_argument('--character', type=str, # default='0123456789abcdefghijklmnopqrstuvwxyz', help='character label') ## Text in the Wild case # character 추가 참고 : https://github.com/tsis-mobile-technology/EasyOCR/blob/master/easyocr/config.py parser.add_argument('--character', type=str, default='0123456789!#$%&\'"()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZㆍ가각간갇갈감갑값갓강갖같갚갛개객걀걔거걱건걷걸검겁것겉게겨격겪견결겹경곁계고곡곤곧골곰곱곳공과관광괜괴굉교구국군굳굴굵굶굽궁권귀귓규균귤그극근글긁금급긋긍기긴길김깅깊까깍깎깐깔깜깝깡깥깨꺼꺾껌껍껏껑께껴꼬꼭꼴꼼꼽꽂꽃꽉꽤꾸꾼꿀꿈뀌끄끈끊끌끓끔끗끝끼낌나낙낚난날낡남납낫낭낮낯낱낳내냄냇냉냐냥너넉넌널넓넘넣네넥넷녀녁년념녕노녹논놀놈농높놓놔뇌뇨누눈눕뉘뉴늄느늑는늘늙능늦늬니닐님다닥닦단닫달닭닮담답닷당닿대댁댐댓더덕던덜덟덤덥덧덩덮데델도독돈돌돕돗동돼되된두둑둘둠둡둥뒤뒷드득든듣들듬듭듯등디딩딪따딱딴딸땀땅때땜떠떡떤떨떻떼또똑뚜뚫뚱뛰뜨뜩뜯뜰뜻띄라락란람랍랑랗래랜램랫략량러럭런럴럼럽럿렁렇레렉렌려력련렬렵령례로록론롬롭롯료루룩룹룻뤄류륙률륭르른름릇릎리릭린림립릿링마막만많말맑맘맙맛망맞맡맣매맥맨맵맺머먹먼멀멈멋멍멎메멘멩며면멸명몇모목몬몰몸몹못몽묘무묵묶문묻물뭄뭇뭐뭘뭣므미민믿밀밉밌및밑바박밖반받발밝밟밤밥방밭배백뱀뱃뱉버번벌범법벗베벤벨벼벽변별볍병볕보복볶본볼봄봇봉뵈뵙부북분불붉붐붓붕붙뷰브븐블비빌빔빗빚빛빠빡빨빵빼뺏뺨뻐뻔뻗뼈뼉뽑뿌뿐쁘쁨사삭산살삶삼삿상새색샌생샤서석섞선설섬섭섯성세섹센셈셋셔션소속손솔솜솟송솥쇄쇠쇼수숙순숟술숨숫숭숲쉬쉰쉽슈스슨슬슴습슷승시식신싣실싫심십싯싱싶싸싹싼쌀쌍쌓써썩썰썹쎄쏘쏟쑤쓰쓴쓸씀씌씨씩씬씹씻아악안앉않알앓암압앗앙앞애액앨야약얀얄얇양얕얗얘어억언얹얻얼엄업없엇엉엊엌엎에엔엘여역연열엷염엽엿영옆예옛오옥온올옮옳옷옹와완왕왜왠외왼요욕용우욱운울움웃웅워원월웨웬위윗유육율으윽은을음응의이익인일읽잃임입잇있잊잎자작잔잖잘잠잡잣장잦재쟁쟤저적전절젊점접젓정젖제젠젯져조족존졸좀좁종좋좌죄주죽준줄줌줍중쥐즈즉즌즐즘증지직진질짐집짓징짙짚짜짝짧째쨌쩌쩍쩐쩔쩜쪽쫓쭈쭉찌찍찢차착찬찮찰참찻창찾채책챔챙처척천철첩첫청체쳐초촉촌촛총촬최추축춘출춤춥춧충취츠측츰층치칙친칠침칫칭카칸칼캄캐캠커컨컬컴컵컷케켓켜코콘콜콤콩쾌쿄쿠퀴크큰클큼키킬타탁탄탈탑탓탕태택탤터턱턴털텅테텍텔템토톤톨톱통퇴투툴툼퉁튀튜트특튼튿틀틈티틱팀팅파팎판팔팝패팩팬퍼퍽페펜펴편펼평폐포폭폰표푸푹풀품풍퓨프플픔피픽필핏핑하학한할함합항해핵핸햄햇행향허헌험헤헬혀현혈협형혜호혹혼홀홈홉홍화확환활황회획횟횡효후훈훌훔훨휘휴흉흐흑흔흘흙흡흥흩희흰히힘', help='character label') # 0123456789!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZㆍ가각간갇갈감갑값갓강갖같갚갛개객걀걔거걱건걷걸검겁것겉게겨격겪견결겹경곁계고곡곤곧골곰곱곳공과관광괜괴굉교구국군굳굴굵굶굽궁권귀귓규균귤그극근글긁금급긋긍기긴길김깅깊까깍깎깐깔깜깝깡깥깨꺼꺾껌껍껏껑께껴꼬꼭꼴꼼꼽꽂꽃꽉꽤꾸꾼꿀꿈뀌끄끈끊끌끓끔끗끝끼낌나낙낚난날낡남납낫낭낮낯낱낳내냄냇냉냐냥너넉넌널넓넘넣네넥넷녀녁년념녕노녹논놀놈농높놓놔뇌뇨누눈눕뉘뉴늄느늑는늘늙능늦늬니닐님다닥닦단닫달닭닮담답닷당닿대댁댐댓더덕던덜덟덤덥덧덩덮데델도독돈돌돕돗동돼되된두둑둘둠둡둥뒤뒷드득든듣들듬듭듯등디딩딪따딱딴딸땀땅때땜떠떡떤떨떻떼또똑뚜뚫뚱뛰뜨뜩뜯뜰뜻띄라락란람랍랑랗래랜램랫략량러럭런럴럼럽럿렁렇레렉렌려력련렬렵령례로록론롬롭롯료루룩룹룻뤄류륙률륭르른름릇릎리릭린림립릿링마막만많말맑맘맙맛망맞맡맣매맥맨맵맺머먹먼멀멈멋멍멎메멘멩며면멸명몇모목몬몰몸몹못몽묘무묵묶문묻물뭄뭇뭐뭘뭣므미민믿밀밉밌및밑바박밖반받발밝밟밤밥방밭배백뱀뱃뱉버번벌범법벗베벤벨벼벽변별볍병볕보복볶본볼봄봇봉뵈뵙부북분불붉붐붓붕붙뷰브븐블비빌빔빗빚빛빠빡빨빵빼뺏뺨뻐뻔뻗뼈뼉뽑뿌뿐쁘쁨사삭산살삶삼삿상새색샌생샤서석섞선설섬섭섯성세섹센셈셋셔션소속손솔솜솟송솥쇄쇠쇼수숙순숟술숨숫숭숲쉬쉰쉽슈스슨슬슴습슷승시식신싣실싫심십싯싱싶싸싹싼쌀쌍쌓써썩썰썹쎄쏘쏟쑤쓰쓴쓸씀씌씨씩씬씹씻아악안앉않알앓암압앗앙앞애액앨야약얀얄얇양얕얗얘어억언얹얻얼엄업없엇엉엊엌엎에엔엘여역연열엷염엽엿영옆예옛오옥온올옮옳옷옹와완왕왜왠외왼요욕용우욱운울움웃웅워원월웨웬위윗유육율으윽은을음응의이익인일읽잃임입잇있잊잎자작잔잖잘잠잡잣장잦재쟁쟤저적전절젊점접젓정젖제젠젯져조족존졸좀좁종좋좌죄주죽준줄줌줍중쥐즈즉즌즐즘증지직진질짐집짓징짙짚짜짝짧째쨌쩌쩍쩐쩔쩜쪽쫓쭈쭉찌찍찢차착찬찮찰참찻창찾채책챔챙처척천철첩첫청체쳐초촉촌촛총촬최추축춘출춤춥춧충취츠측츰층치칙친칠침칫칭카칸칼캄캐캠커컨컬컴컵컷케켓켜코콘콜콤콩쾌쿄쿠퀴크큰클큼키킬타탁탄탈탑탓탕태택탤터턱턴털텅테텍텔템토톤톨톱통퇴투툴툼퉁튀튜트특튼튿틀틈티틱팀팅파팎판팔팝패팩팬퍼퍽페펜펴편펼평폐포폭폰표푸푹풀품풍퓨프플픔피픽필핏핑하학한할함합항해핵핸햄햇행향허헌험헤헬혀현혈협형혜호혹혼홀홈홉홍화확환활황회획횟횡효후훈훌훔훨휘휴흉흐흑흔흘흙흡흥흩희흰히힘", parser.add_argument('--sensitive', action='store_true', help='for sensitive character mode') parser.add_argument('--PAD', action='store_true', help='whether to keep ratio then pad for image resize') parser.add_argument('--data_filtering_off', action='store_true', help='for data_filtering_off mode') """ Model Architecture """ parser.add_argument('--Transformation', type=str, required=True, help='Transformation stage. None|TPS') parser.add_argument('--FeatureExtraction', type=str, required=True, help='FeatureExtraction stage. VGG|RCNN|ResNet') parser.add_argument('--SequenceModeling', type=str, required=True, help='SequenceModeling stage. None|BiLSTM') parser.add_argument('--Prediction', type=str, required=True, help='Prediction stage. CTC|Attn') parser.add_argument('--num_fiducial', type=int, default=20, help='number of fiducial points of TPS-STN') parser.add_argument('--input_channel', type=int, default=1, help='the number of input channel of Feature extractor') parser.add_argument('--output_channel', type=int, default=512, help='the number of output channel of Feature extractor') parser.add_argument('--hidden_size', type=int, default=256, help='the size of the LSTM hidden state') opt = parser.parse_args() if not opt.exp_name: opt.exp_name = f'{opt.Transformation}-{opt.FeatureExtraction}-{opt.SequenceModeling}-{opt.Prediction}' opt.exp_name += f'-Seed{opt.manualSeed}' # print(opt.exp_name) os.makedirs(f'./saved_models/{opt.exp_name}', exist_ok=True) """ vocab / character number configuration """ if opt.sensitive: # opt.character += 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' opt.character = string.printable[:-6] # same with ASTER setting (use 94 char). """ Seed and GPU setting """ # print("Random Seed: ", opt.manualSeed) random.seed(opt.manualSeed) np.random.seed(opt.manualSeed) torch.manual_seed(opt.manualSeed) torch.cuda.manual_seed(opt.manualSeed) cudnn.benchmark = True cudnn.deterministic = True opt.num_gpu = torch.cuda.device_count() # print('device count', opt.num_gpu) if opt.num_gpu > 1: print('------ Use multi-GPU setting ------') print('if you stuck too long time with multi-GPU setting, try to set --workers 0') # check multi-GPU issue https://github.com/clovaai/deep-text-recognition-benchmark/issues/1 opt.workers = opt.workers * opt.num_gpu opt.batch_size = opt.batch_size * opt.num_gpu """ previous version print('To equlize batch stats to 1-GPU setting, the batch_size is multiplied with num_gpu and multiplied batch_size is ', opt.batch_size) opt.batch_size = opt.batch_size * opt.num_gpu print('To equalize the number of epochs to 1-GPU setting, num_iter is divided with num_gpu by default.') If you dont care about it, just commnet out these line.) opt.num_iter = int(opt.num_iter / opt.num_gpu) """ train(opt)

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import os import sys import time import random import string import argparse import torch import torch.backends.cudnn as cudnn import torch.nn.init as init import torch.optim as optim import torch.utils.data import numpy as np from utils import CTCLabelConverter, CTCLabelConverterForBaiduWarpctc, AttnLabelConverter, Averager from dataset import hierarchical_dataset, AlignCollate, Batch_Balanced_Dataset from model import Model from test import validation device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') ta_filtering_off: print('Filtering the images containing characters which are not in opt.character') print('Filtering the images whose label is longer than opt.batch_max_length') opt.select_data = opt.select_data.split('-') opt.batch_ratio = opt.batch_ratio.split('-') train_dataset = Batch_Balanced_Dataset(opt) log = open(f'./saved_models/{opt.exp_name}/log_dataset.txt', 'a') AlignCollate_valid = AlignCollate(imgH=opt.imgH, imgW=opt.imgW, keep_ratio_with_pad=opt.PAD) valid_dataset, valid_dataset_log = hierarchical_dataset(root=opt.valid_data, opt=opt) valid_loader = torch.utils.data.DataLoader( valid_dataset, batch_size=opt.batch_size, shuffle=True, num_workers=int(opt.workers), collate_fn=AlignCollate_valid, pin_memory=True) log.write(valid_dataset_log) print('-' * 80) log.write('-' * 80 + '\n') log.close() if 'CTC' in opt.Prediction: if opt.baiduCTC: converter = CTCLabelConverterForBaiduWarpctc(opt.character) else: converter = CTCLabelConverter(opt.character) else: converter = AttnLabelConverter(opt.character) opt.num_class = len(converter.character) if opt.rgb: opt.input_channel = 3 model = Model(opt) print('model input parameters', opt.imgH, opt.imgW, opt.num_fiducial, opt.input_channel, opt.output_channel, opt.hidden_size, opt.num_class, opt.batch_max_length, opt.Transformation, opt.FeatureExtraction, opt.SequenceModeling, opt.Prediction) for name, param in model.named_parameters(): if 'localization_fc2' in name: print(f'Skip {name} as it is already initialized') continue try: if 'bias' in name: init.constant_(param, 0.0) elif 'weight' in name: init.kaiming_normal_(param) except Exception as e: if 'weight' in name: param.data.fill_(1) continue model = torch.nn.DataParallel(model).to(device) model.train() if opt.saved_model != '': print(f'loading pretrained model from {opt.saved_model}') if opt.FT: model.load_state_dict(torch.load(opt.saved_model, map_location=torch.device('cpu')), strict=False) else: model.load_state_dict(torch.load(opt.saved_model)) print("Model:") print(model) if 'CTC' in opt.Prediction: if opt.baiduCTC: criterion = torch.nn.CTCLoss(zero_infinity=True).to(device) else: criterion = torch.nn.CTCLoss(zero_infinity=True).to(device) else: criterion = torch.nn.CrossEntropyLoss(ignore_index=0).to(device) loss_avg = Averager() filtered_parameters = [] params_num = [] for p in filter(lambda p: p.requires_grad, model.parameters()): filtered_parameters.append(p) params_num.append(np.prod(p.size())) print('Trainable params num : ', sum(params_num)) if opt.adam: optimizer = optim.Adam(filtered_parameters, lr=opt.lr, betas=(opt.beta1, 0.999)) else: optimizer = optim.Adadelta(filtered_parameters, lr=opt.lr, rho=opt.rho, eps=opt.eps) print("Optimizer:") print(optimizer) with open(f'./saved_models/{opt.exp_name}/opt.txt', 'a') as opt_file: opt_log = '------------ Options -------------\n' args = vars(opt) for k, v in args.items(): opt_log += f'{str(k)}: {str(v)}\n' opt_log += '---------------------------------------\n' print(opt_log) opt_file.write(opt_log) start_iter = 0 if opt.saved_model != '': try: start_iter = int(opt.saved_model.split('_')[-1].split('.')[0]) print(f'continue to train, start_iter: {start_iter}') except: pass start_time = time.time() best_accuracy = -1 best_norm_ED = -1 iteration = start_iter while(True): image_tensors, labels = train_dataset.get_batch() image = image_tensors.to(device) text, length = converter.encode(labels, batch_max_length=opt.batch_max_length) batch_size = image.size(0) if 'CTC' in opt.Prediction: preds = model(image, text) preds_size = torch.IntTensor([preds.size(1)] * batch_size) if opt.baiduCTC: preds = preds.permute(1, 0, 2) cost = criterion(preds, text, preds_size, length) / batch_size else: preds = preds.log_softmax(2).permute(1, 0, 2) cost = criterion(preds, text, preds_size, length) else: preds = model(image, text[:, :-1]) target = text[:, 1:] cost = criterion(preds.view(-1, preds.shape[-1]), target.contiguous().view(-1)) model.zero_grad() cost.backward() torch.nn.utils.clip_grad_norm_(model.parameters(), opt.grad_clip) optimizer.step() loss_avg.add(cost) if (iteration + 1) % opt.valInterval == 0 or iteration == 0: elapsed_time = time.time() - start_time with open(f'./saved_models/{opt.exp_name}/log_train.txt', 'a') as log: model.eval() with torch.no_grad(): valid_loss, current_accuracy, current_norm_ED, preds, confidence_score, labels, infer_time, length_of_data = validation( model, criterion, valid_loader, converter, opt) model.train() loss_log = f'[{iteration+1}/{opt.num_iter}] Train loss: {loss_avg.val():0.5f}, Valid loss: {valid_loss:0.5f}, Elapsed_time: {elapsed_time:0.5f}' loss_avg.reset() current_model_log = f'{"Current_accuracy":17s}: {current_accuracy:0.3f}, {"Current_norm_ED":17s}: {current_norm_ED:0.2f}' if current_accuracy > best_accuracy: best_accuracy = current_accuracy torch.save(model.state_dict(), f'./saved_models/{opt.exp_name}/best_accuracy.pth') if current_norm_ED > best_norm_ED: best_norm_ED = current_norm_ED torch.save(model.state_dict(), f'./saved_models/{opt.exp_name}/best_norm_ED.pth') best_model_log = f'{"Best_accuracy":17s}: {best_accuracy:0.3f}, {"Best_norm_ED":17s}: {best_norm_ED:0.2f}' loss_model_log = f'{loss_log}\n{current_model_log}\n{best_model_log}' print(loss_model_log) log.write(loss_model_log + '\n') dashed_line = '-' * 80 head = f'{"Ground Truth":25s} | {"Prediction":25s} | Confidence Score & T/F' predicted_result_log = f'{dashed_line}\n{head}\n{dashed_line}\n' for gt, pred, confidence in zip(labels[:5], preds[:5], confidence_score[:5]): if 'Attn' in opt.Prediction: gt = gt[:gt.find('[s]')] pred = pred[:pred.find('[s]')] predicted_result_log += f'{gt:25s} | {pred:25s} | {confidence:0.4f}\t{str(pred == gt)}\n' predicted_result_log += f'{dashed_line}' print(predicted_result_log) log.write(predicted_result_log + '\n') if (iteration + 1) % 1e+5 == 0: torch.save( model.state_dict(), f'./saved_models/{opt.exp_name}/iter_{iteration+1}.pth') if (iteration + 1) == opt.num_iter: print('end the training') sys.exit() iteration += 1 if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--exp_name', help='Where to store logs and models') parser.add_argument('--train_data', required=True, help='path to training dataset') parser.add_argument('--valid_data', required=True, help='path to validation dataset') parser.add_argument('--manualSeed', type=int, default=1111, help='for random seed setting') parser.add_argument('--workers', type=int, help='number of data loading workers', default=4) parser.add_argument('--batch_size', type=int, default=192, help='input batch size') parser.add_argument('--num_iter', type=int, default=300000, help='number of iterations to train for') parser.add_argument('--valInterval', type=int, default=2000, help='Interval between each validation') parser.add_argument('--saved_model', default='', help="path to model to continue training") parser.add_argument('--FT', action='store_true', help='whether to do fine-tuning') parser.add_argument('--adam', action='store_true', help='Whether to use adam (default is Adadelta)') parser.add_argument('--lr', type=float, default=1, help='learning rate, default=1.0 for Adadelta') parser.add_argument('--beta1', type=float, default=0.9, help='beta1 for adam. default=0.9') parser.add_argument('--rho', type=float, default=0.95, help='decay rate rho for Adadelta. default=0.95') parser.add_argument('--eps', type=float, default=1e-8, help='eps for Adadelta. default=1e-8') parser.add_argument('--grad_clip', type=float, default=5, help='gradient clipping value. default=5') parser.add_argument('--baiduCTC', action='store_true', help='for data_filtering_off mode') t('--select_data', type=str, default='/', help='select training data') parser.add_argument('--batch_ratio', type=str, default='1', help='assign ratio for each selected data in the batch') parser.add_argument('--total_data_usage_ratio', type=str, default='1.0', help='total data usage ratio, this ratio is multiplied to total number of data.') parser.add_argument('--batch_max_length', type=int, default=25, help='maximum-label-length') parser.add_argument('--imgH', type=int, default=32, help='the height of the input image') parser.add_argument('--imgW', type=int, default=100, help='the width of the input image') parser.add_argument('--rgb', action='store_true', help='use rgb input') gument('--character', type=str, default='0123456789!#$%&\'"()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZㆍ가각간갇갈감갑값갓강갖같갚갛개객걀걔거걱건걷걸검겁것겉게겨격겪견결겹경곁계고곡곤곧골곰곱곳공과관광괜괴굉교구국군굳굴굵굶굽궁권귀귓규균귤그극근글긁금급긋긍기긴길김깅깊까깍깎깐깔깜깝깡깥깨꺼꺾껌껍껏껑께껴꼬꼭꼴꼼꼽꽂꽃꽉꽤꾸꾼꿀꿈뀌끄끈끊끌끓끔끗끝끼낌나낙낚난날낡남납낫낭낮낯낱낳내냄냇냉냐냥너넉넌널넓넘넣네넥넷녀녁년념녕노녹논놀놈농높놓놔뇌뇨누눈눕뉘뉴늄느늑는늘늙능늦늬니닐님다닥닦단닫달닭닮담답닷당닿대댁댐댓더덕던덜덟덤덥덧덩덮데델도독돈돌돕돗동돼되된두둑둘둠둡둥뒤뒷드득든듣들듬듭듯등디딩딪따딱딴딸땀땅때땜떠떡떤떨떻떼또똑뚜뚫뚱뛰뜨뜩뜯뜰뜻띄라락란람랍랑랗래랜램랫략량러럭런럴럼럽럿렁렇레렉렌려력련렬렵령례로록론롬롭롯료루룩룹룻뤄류륙률륭르른름릇릎리릭린림립릿링마막만많말맑맘맙맛망맞맡맣매맥맨맵맺머먹먼멀멈멋멍멎메멘멩며면멸명몇모목몬몰몸몹못몽묘무묵묶문묻물뭄뭇뭐뭘뭣므미민믿밀밉밌및밑바박밖반받발밝밟밤밥방밭배백뱀뱃뱉버번벌범법벗베벤벨벼벽변별볍병볕보복볶본볼봄봇봉뵈뵙부북분불붉붐붓붕붙뷰브븐블비빌빔빗빚빛빠빡빨빵빼뺏뺨뻐뻔뻗뼈뼉뽑뿌뿐쁘쁨사삭산살삶삼삿상새색샌생샤서석섞선설섬섭섯성세섹센셈셋셔션소속손솔솜솟송솥쇄쇠쇼수숙순숟술숨숫숭숲쉬쉰쉽슈스슨슬슴습슷승시식신싣실싫심십싯싱싶싸싹싼쌀쌍쌓써썩썰썹쎄쏘쏟쑤쓰쓴쓸씀씌씨씩씬씹씻아악안앉않알앓암압앗앙앞애액앨야약얀얄얇양얕얗얘어억언얹얻얼엄업없엇엉엊엌엎에엔엘여역연열엷염엽엿영옆예옛오옥온올옮옳옷옹와완왕왜왠외왼요욕용우욱운울움웃웅워원월웨웬위윗유육율으윽은을음응의이익인일읽잃임입잇있잊잎자작잔잖잘잠잡잣장잦재쟁쟤저적전절젊점접젓정젖제젠젯져조족존졸좀좁종좋좌죄주죽준줄줌줍중쥐즈즉즌즐즘증지직진질짐집짓징짙짚짜짝짧째쨌쩌쩍쩐쩔쩜쪽쫓쭈쭉찌찍찢차착찬찮찰참찻창찾채책챔챙처척천철첩첫청체쳐초촉촌촛총촬최추축춘출춤춥춧충취츠측츰층치칙친칠침칫칭카칸칼캄캐캠커컨컬컴컵컷케켓켜코콘콜콤콩쾌쿄쿠퀴크큰클큼키킬타탁탄탈탑탓탕태택탤터턱턴털텅테텍텔템토톤톨톱통퇴투툴툼퉁튀튜트특튼튿틀틈티틱팀팅파팎판팔팝패팩팬퍼퍽페펜펴편펼평폐포폭폰표푸푹풀품풍퓨프플픔피픽필핏핑하학한할함합항해핵핸햄햇행향허헌험헤헬혀현혈협형혜호혹혼홀홈홉홍화확환활황회획횟횡효후훈훌훔훨휘휴흉흐흑흔흘흙흡흥흩희흰히힘', help='character label') # 0123456789!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZㆍ가각간갇갈감갑값갓강갖같갚갛개객걀걔거걱건걷걸검겁것겉게겨격겪견결겹경곁계고곡곤곧골곰곱곳공과관광괜괴굉교구국군굳굴굵굶굽궁권귀귓규균귤그극근글긁금급긋긍기긴길김깅깊까깍깎깐깔깜깝깡깥깨꺼꺾껌껍껏껑께껴꼬꼭꼴꼼꼽꽂꽃꽉꽤꾸꾼꿀꿈뀌끄끈끊끌끓끔끗끝끼낌나낙낚난날낡남납낫낭낮낯낱낳내냄냇냉냐냥너넉넌널넓넘넣네넥넷녀녁년념녕노녹논놀놈농높놓놔뇌뇨누눈눕뉘뉴늄느늑는늘늙능늦늬니닐님다닥닦단닫달닭닮담답닷당닿대댁댐댓더덕던덜덟덤덥덧덩덮데델도독돈돌돕돗동돼되된두둑둘둠둡둥뒤뒷드득든듣들듬듭듯등디딩딪따딱딴딸땀땅때땜떠떡떤떨떻떼또똑뚜뚫뚱뛰뜨뜩뜯뜰뜻띄라락란람랍랑랗래랜램랫략량러럭런럴럼럽럿렁렇레렉렌려력련렬렵령례로록론롬롭롯료루룩룹룻뤄류륙률륭르른름릇릎리릭린림립릿링마막만많말맑맘맙맛망맞맡맣매맥맨맵맺머먹먼멀멈멋멍멎메멘멩며면멸명몇모목몬몰몸몹못몽묘무묵묶문묻물뭄뭇뭐뭘뭣므미민믿밀밉밌및밑바박밖반받발밝밟밤밥방밭배백뱀뱃뱉버번벌범법벗베벤벨벼벽변별볍병볕보복볶본볼봄봇봉뵈뵙부북분불붉붐붓붕붙뷰브븐블비빌빔빗빚빛빠빡빨빵빼뺏뺨뻐뻔뻗뼈뼉뽑뿌뿐쁘쁨사삭산살삶삼삿상새색샌생샤서석섞선설섬섭섯성세섹센셈셋셔션소속손솔솜솟송솥쇄쇠쇼수숙순숟술숨숫숭숲쉬쉰쉽슈스슨슬슴습슷승시식신싣실싫심십싯싱싶싸싹싼쌀쌍쌓써썩썰썹쎄쏘쏟쑤쓰쓴쓸씀씌씨씩씬씹씻아악안앉않알앓암압앗앙앞애액앨야약얀얄얇양얕얗얘어억언얹얻얼엄업없엇엉엊엌엎에엔엘여역연열엷염엽엿영옆예옛오옥온올옮옳옷옹와완왕왜왠외왼요욕용우욱운울움웃웅워원월웨웬위윗유육율으윽은을음응의이익인일읽잃임입잇있잊잎자작잔잖잘잠잡잣장잦재쟁쟤저적전절젊점접젓정젖제젠젯져조족존졸좀좁종좋좌죄주죽준줄줌줍중쥐즈즉즌즐즘증지직진질짐집짓징짙짚짜짝짧째쨌쩌쩍쩐쩔쩜쪽쫓쭈쭉찌찍찢차착찬찮찰참찻창찾채책챔챙처척천철첩첫청체쳐초촉촌촛총촬최추축춘출춤춥춧충취츠측츰층치칙친칠침칫칭카칸칼캄캐캠커컨컬컴컵컷케켓켜코콘콜콤콩쾌쿄쿠퀴크큰클큼키킬타탁탄탈탑탓탕태택탤터턱턴털텅테텍텔템토톤톨톱통퇴투툴툼퉁튀튜트특튼튿틀틈티틱팀팅파팎판팔팝패팩팬퍼퍽페펜펴편펼평폐포폭폰표푸푹풀품풍퓨프플픔피픽필핏핑하학한할함합항해핵핸햄햇행향허헌험헤헬혀현혈협형혜호혹혼홀홈홉홍화확환활황회획횟횡효후훈훌훔훨휘휴흉흐흑흔흘흙흡흥흩희흰히힘", parser.add_argument('--sensitive', action='store_true', help='for sensitive character mode') parser.add_argument('--PAD', action='store_true', help='whether to keep ratio then pad for image resize') parser.add_argument('--data_filtering_off', action='store_true', help='for data_filtering_off mode') parser.add_argument('--Transformation', type=str, required=True, help='Transformation stage. None|TPS') parser.add_argument('--FeatureExtraction', type=str, required=True, help='FeatureExtraction stage. VGG|RCNN|ResNet') parser.add_argument('--SequenceModeling', type=str, required=True, help='SequenceModeling stage. None|BiLSTM') parser.add_argument('--Prediction', type=str, required=True, help='Prediction stage. CTC|Attn') parser.add_argument('--num_fiducial', type=int, default=20, help='number of fiducial points of TPS-STN') parser.add_argument('--input_channel', type=int, default=1, help='the number of input channel of Feature extractor') parser.add_argument('--output_channel', type=int, default=512, help='the number of output channel of Feature extractor') parser.add_argument('--hidden_size', type=int, default=256, help='the size of the LSTM hidden state') opt = parser.parse_args() if not opt.exp_name: opt.exp_name = f'{opt.Transformation}-{opt.FeatureExtraction}-{opt.SequenceModeling}-{opt.Prediction}' opt.exp_name += f'-Seed{opt.manualSeed}' # print(opt.exp_name) os.makedirs(f'./saved_models/{opt.exp_name}', exist_ok=True) if opt.sensitive: # opt.character += 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' opt.character = string.printable[:-6] # same with ASTER setting (use 94 char). # print("Random Seed: ", opt.manualSeed) random.seed(opt.manualSeed) np.random.seed(opt.manualSeed) torch.manual_seed(opt.manualSeed) torch.cuda.manual_seed(opt.manualSeed) cudnn.benchmark = True cudnn.deterministic = True opt.num_gpu = torch.cuda.device_count() # print('device count', opt.num_gpu) if opt.num_gpu > 1: print('------ Use multi-GPU setting ------') print('if you stuck too long time with multi-GPU setting, try to set --workers 0') # check multi-GPU issue https://github.com/clovaai/deep-text-recognition-benchmark/issues/1 opt.workers = opt.workers * opt.num_gpu opt.batch_size = opt.batch_size * opt.num_gpu train(opt)

true

1c2fb5fc10089bbacaa7a1f8c73535da8b2e736c

1,229

py

Python

Python3/0505-The-Maze-II/soln.py

wyaadarsh/LeetCode-Solutions

3719f5cb059eefd66b83eb8ae990652f4b7fd124

[ "MIT" ]

5

2020-07-24T17:48:59.000Z

2020-12-21T05:56:00.000Z

Python3/0505-The-Maze-II/soln.py

zhangyaqi1989/LeetCode-Solutions

2655a1ffc8678ad1de6c24295071308a18c5dc6e

[ "MIT" ]

null

Python3/0505-The-Maze-II/soln.py

zhangyaqi1989/LeetCode-Solutions

2655a1ffc8678ad1de6c24295071308a18c5dc6e

[ "MIT" ]

2

2020-07-24T17:49:01.000Z

2020-08-31T19:57:35.000Z

class Solution: def shortestDistance(self, maze, start, destination): """ :type maze: List[List[int]] :type start: List[int] :type destination: List[int] :rtype: int """ m, n = len(maze), len(maze[0]) start, dest = tuple(start), tuple(destination) heap = [] heapq.heappush(heap, [0, start]) visited = {start : 0} while heap: dis, (i, j), = heapq.heappop(heap) if (i, j) == dest: return dis for di, dj in ((-1, 0), (1, 0), (0, 1), (0, -1)): newi, newj = i + di, j + dj while 0 <= newi < m and 0 <= newj < n and maze[newi][newj] != 1: newi, newj = newi + di, newj + dj newi, newj = newi - di, newj - dj if newi != i or newj != j: distance = dis + ((newi - i) // di if newi != i else (newj - j) // dj) else: distance = dis if (newi, newj) not in visited or visited[newi, newj] > distance: visited[newi, newj] = distance heapq.heappush(heap, (distance, (newi, newj))) return -1

40.966667

90

0.441009

class Solution: def shortestDistance(self, maze, start, destination): m, n = len(maze), len(maze[0]) start, dest = tuple(start), tuple(destination) heap = [] heapq.heappush(heap, [0, start]) visited = {start : 0} while heap: dis, (i, j), = heapq.heappop(heap) if (i, j) == dest: return dis for di, dj in ((-1, 0), (1, 0), (0, 1), (0, -1)): newi, newj = i + di, j + dj while 0 <= newi < m and 0 <= newj < n and maze[newi][newj] != 1: newi, newj = newi + di, newj + dj newi, newj = newi - di, newj - dj if newi != i or newj != j: distance = dis + ((newi - i) // di if newi != i else (newj - j) // dj) else: distance = dis if (newi, newj) not in visited or visited[newi, newj] > distance: visited[newi, newj] = distance heapq.heappush(heap, (distance, (newi, newj))) return -1

true

1c2fb67571f8019d9cbbd8c5dfe8c8c59589de44

3,442

py

Python

network/wifiWidget.py

dailing/drcm

b692818ae5074611c27bff124dd41b34f0d7e64b

[ "MIT" ]

null

network/wifiWidget.py

dailing/drcm

b692818ae5074611c27bff124dd41b34f0d7e64b

[ "MIT" ]

null

network/wifiWidget.py

dailing/drcm

b692818ae5074611c27bff124dd41b34f0d7e64b

[ "MIT" ]

null

import sys import logging import subprocess from PyQt4 import QtGui, QtCore from wifiManager import wifiManager try: from sql.RunnableFunc import RunnableFunc from sql.PoolWrapper import PoolWrapper except Exception as e: pass from widget.LineEditDialog import LineEditDialog def showKeyBoard(): try: subprocess.Popen(["matchbox-keyboard"]) except FileNotFoundError: pass def hideKeyBoard(): pass subprocess.Popen(["killall","matchbox-keyboard"]) def visulizeSignal(wifiData): #convert to percentage representation quality = wifiData[0].split('/') quality = float(quality[0]) / float(quality[1]) quality = int(quality * 100) #'|' denote ten percent, '.' denote five percent rem = (quality % 10) > 5 strQuality = '|' * (quality / 10) + ('|' if rem else '.') res = ['' if e is None else e for e in wifiData] print (strQuality) res[0] = strQuality return res class WifiTableView(QtGui.QTableWidget): """wifi mananger table list view""" wifiQuerySignal = QtCore.pyqtSignal(list) def __init__(self): QtGui.QTableWidget.__init__(self) self.pw = PoolWrapper() self.initTable() self.setEditTriggers(QtGui.QAbstractItemView.CurrentChanged) def tabCellClicked(self, i, j): if j != 1: # return ssid = str(self.item(i, j).text()) if ssid == self.wifiManager.getCurrentWifi(): print ('is connected') return pwd = str(self.item(i, 2).text()) pwd, isOkay = LineEditDialog.newInstance('password',pwd) if not isOkay: return self.item(i, 2).setText(pwd) if pwd == '******': pwd = None pwd = self.pw.start( RunnableFunc( self.wifiManager.connectWifi, ssid, pwd ) ) print(str(self.item(i, 2).text())) def initTable(self): self.wifiManager = wifiManager() # table.itemClicked.connect(self.tabItemDoubleClicked) self.cellClicked.connect(self.tabCellClicked) # tableItem = QtGui.QTableWidgetItem() self.setWindowTitle("WIFI LIST") #quality, ssid, user, pwd self.setColumnCount(3) self.verticalHeader().hide() self.setHorizontalHeaderLabels(['quality', 'wifi', 'password']) self.setShowGrid(False) # table.setEditTriggers(QtGui.QAbstractItemView.NoEditTriggers) self.horizontalHeader().setResizeMode(QtGui.QHeaderView.Stretch) #[[quality, name, pwd]] # self.item(0, 2).setFlags(self.item(0, 2).flags() ^ QtCore.Qt.ItemIsEditable) self.pw.start( RunnableFunc( self.asynFillTable ) ) self.wifiQuerySignal.connect(self.asynFillTableCallBack) def asynFillTable(self): wifiList = self.wifiManager.getWifiList() print(wifiList) self.wifiQuerySignal.emit(wifiList) #pull data and emit signal def asynFillTableCallBack(self, wifiList): for w in wifiList: self.appendStrRow(visulizeSignal(w)) self.pw.start( RunnableFunc( wifiManager().connect_saved ) ) def appendStrRow(self, data): x = self.rowCount() self.insertRow(x) for i, v in enumerate(data) : item = QtGui.QTableWidgetItem(v) item.setTextAlignment(QtCore.Qt.AlignHCenter | QtCore.Qt.AlignVCenter) item.setFlags(item.flags() ^ QtCore.Qt.ItemIsEditable) self.setItem(x, i, item) if __name__ == '__main__': try: visulizeSignal(['59/70']) # app = QtGui.QApplication(sys.argv) # wrapper = QtGui.QMainWindow() # wrapper.setCentralWidget(WifiTableView()) # wrapper.setGeometry(400, 400, 800, 480) # wrapper.show() # sys.exit(app.exec_()) except Exception as e: print(e)

23.902778

80

0.705113

import sys import logging import subprocess from PyQt4 import QtGui, QtCore from wifiManager import wifiManager try: from sql.RunnableFunc import RunnableFunc from sql.PoolWrapper import PoolWrapper except Exception as e: pass from widget.LineEditDialog import LineEditDialog def showKeyBoard(): try: subprocess.Popen(["matchbox-keyboard"]) except FileNotFoundError: pass def hideKeyBoard(): pass subprocess.Popen(["killall","matchbox-keyboard"]) def visulizeSignal(wifiData): quality = wifiData[0].split('/') quality = float(quality[0]) / float(quality[1]) quality = int(quality * 100) rem = (quality % 10) > 5 strQuality = '|' * (quality / 10) + ('|' if rem else '.') res = ['' if e is None else e for e in wifiData] print (strQuality) res[0] = strQuality return res class WifiTableView(QtGui.QTableWidget): wifiQuerySignal = QtCore.pyqtSignal(list) def __init__(self): QtGui.QTableWidget.__init__(self) self.pw = PoolWrapper() self.initTable() self.setEditTriggers(QtGui.QAbstractItemView.CurrentChanged) def tabCellClicked(self, i, j): if j != 1: return ssid = str(self.item(i, j).text()) if ssid == self.wifiManager.getCurrentWifi(): print ('is connected') return pwd = str(self.item(i, 2).text()) pwd, isOkay = LineEditDialog.newInstance('password',pwd) if not isOkay: return self.item(i, 2).setText(pwd) if pwd == '******': pwd = None pwd = self.pw.start( RunnableFunc( self.wifiManager.connectWifi, ssid, pwd ) ) print(str(self.item(i, 2).text())) def initTable(self): self.wifiManager = wifiManager() self.cellClicked.connect(self.tabCellClicked) self.setWindowTitle("WIFI LIST") self.setColumnCount(3) self.verticalHeader().hide() self.setHorizontalHeaderLabels(['quality', 'wifi', 'password']) self.setShowGrid(False) self.horizontalHeader().setResizeMode(QtGui.QHeaderView.Stretch) self.pw.start( RunnableFunc( self.asynFillTable ) ) self.wifiQuerySignal.connect(self.asynFillTableCallBack) def asynFillTable(self): wifiList = self.wifiManager.getWifiList() print(wifiList) self.wifiQuerySignal.emit(wifiList) def asynFillTableCallBack(self, wifiList): for w in wifiList: self.appendStrRow(visulizeSignal(w)) self.pw.start( RunnableFunc( wifiManager().connect_saved ) ) def appendStrRow(self, data): x = self.rowCount() self.insertRow(x) for i, v in enumerate(data) : item = QtGui.QTableWidgetItem(v) item.setTextAlignment(QtCore.Qt.AlignHCenter | QtCore.Qt.AlignVCenter) item.setFlags(item.flags() ^ QtCore.Qt.ItemIsEditable) self.setItem(x, i, item) if __name__ == '__main__': try: visulizeSignal(['59/70']) except Exception as e: print(e)

true

1c2fb6a640426644549f001ce958942cb7912536

3,403

py

Python

src/models/utils.py

caixhstrive/Mini_Xception

0cf7ce88d9cbe56f0dc20b0ef2850a499c033ce3

[ "MIT" ]

3

2018-11-21T06:51:57.000Z

2018-11-21T08:20:53.000Z

src/models/utils.py

caixhstrive/Mini_Xception

0cf7ce88d9cbe56f0dc20b0ef2850a499c033ce3

[ "MIT" ]

null

src/models/utils.py

caixhstrive/Mini_Xception

0cf7ce88d9cbe56f0dc20b0ef2850a499c033ce3

[ "MIT" ]

null

#-*- coding:utf-8 -*- import os from keras import backend as K from keras.models import Model from keras.engine.topology import get_source_inputs from keras.layers import Activation, Add, Concatenate, Conv2D, GlobalMaxPooling2D from keras.layers import GlobalAveragePooling2D,Input, Dense from keras.layers import MaxPool2D,AveragePooling2D, BatchNormalization, Lambda, DepthwiseConv2D import numpy as np def channel_split(x, name=''): # equipartition in_channles = x.shape.as_list()[-1] ip = in_channles // 2 c_hat = Lambda(lambda z: z[:, :, :, 0:ip], name='%s/sp%d_slice' % (name, 0))(x) c = Lambda(lambda z: z[:, :, :, ip:], name='%s/sp%d_slice' % (name, 1))(x) return c_hat, c def channel_shuffle(x): height, width, channels = x.shape.as_list()[1:] channels_per_split = channels // 2 x = K.reshape(x, [-1, height, width, 2, channels_per_split]) x = K.permute_dimensions(x, (0,1,2,4,3)) x = K.reshape(x, [-1, height, width, channels]) return x def shuffle_unit(inputs, out_channels, bottleneck_ratio,strides=2,stage=1,block=1): if K.image_data_format() == 'channels_last': bn_axis = -1 else: raise ValueError('Only channels last supported') prefix = 'stage{}/block{}'.format(stage, block) bottleneck_channels = int(out_channels * bottleneck_ratio) if strides < 2: c_hat, c = channel_split(inputs, '{}/spl'.format(prefix)) inputs = c x = Conv2D(bottleneck_channels, kernel_size=(1,1), strides=1, padding='same', name='{}/1x1conv_1'.format(prefix))(inputs) x = BatchNormalization(axis=bn_axis, name='{}/bn_1x1conv_1'.format(prefix))(x) x = Activation('relu', name='{}/relu_1x1conv_1'.format(prefix))(x) x = DepthwiseConv2D(kernel_size=3, strides=strides, padding='same', name='{}/3x3dwconv'.format(prefix))(x) x = BatchNormalization(axis=bn_axis, name='{}/bn_3x3dwconv'.format(prefix))(x) x = Conv2D(bottleneck_channels, kernel_size=1,strides=1,padding='same', name='{}/1x1conv_2'.format(prefix))(x) x = BatchNormalization(axis=bn_axis, name='{}/bn_1x1conv_2'.format(prefix))(x) x = Activation('relu', name='{}/relu_1x1conv_2'.format(prefix))(x) if strides < 2: ret = Concatenate(axis=bn_axis, name='{}/concat_1'.format(prefix))([x, c_hat]) else: s2 = DepthwiseConv2D(kernel_size=3, strides=2, padding='same', name='{}/3x3dwconv_2'.format(prefix))(inputs) s2 = BatchNormalization(axis=bn_axis, name='{}/bn_3x3dwconv_2'.format(prefix))(s2) s2 = Conv2D(bottleneck_channels, kernel_size=1,strides=1,padding='same', name='{}/1x1_conv_3'.format(prefix))(s2) s2 = BatchNormalization(axis=bn_axis, name='{}/bn_1x1conv_3'.format(prefix))(s2) s2 = Activation('relu', name='{}/relu_1x1conv_3'.format(prefix))(s2) ret = Concatenate(axis=bn_axis, name='{}/concat_2'.format(prefix))([x, s2]) ret = Lambda(channel_shuffle, name='{}/channel_shuffle'.format(prefix))(ret) return ret def block(x, channel_map, bottleneck_ratio, repeat=1, stage=1): x = shuffle_unit(x, out_channels=channel_map[stage-1], strides=2,bottleneck_ratio=bottleneck_ratio,stage=stage,block=1) for i in range(1, repeat+1): x = shuffle_unit(x, out_channels=channel_map[stage-1],strides=1, bottleneck_ratio=bottleneck_ratio,stage=stage, block=(1+i)) return x

44.776316

125

0.675287

import os from keras import backend as K from keras.models import Model from keras.engine.topology import get_source_inputs from keras.layers import Activation, Add, Concatenate, Conv2D, GlobalMaxPooling2D from keras.layers import GlobalAveragePooling2D,Input, Dense from keras.layers import MaxPool2D,AveragePooling2D, BatchNormalization, Lambda, DepthwiseConv2D import numpy as np def channel_split(x, name=''): in_channles = x.shape.as_list()[-1] ip = in_channles // 2 c_hat = Lambda(lambda z: z[:, :, :, 0:ip], name='%s/sp%d_slice' % (name, 0))(x) c = Lambda(lambda z: z[:, :, :, ip:], name='%s/sp%d_slice' % (name, 1))(x) return c_hat, c def channel_shuffle(x): height, width, channels = x.shape.as_list()[1:] channels_per_split = channels // 2 x = K.reshape(x, [-1, height, width, 2, channels_per_split]) x = K.permute_dimensions(x, (0,1,2,4,3)) x = K.reshape(x, [-1, height, width, channels]) return x def shuffle_unit(inputs, out_channels, bottleneck_ratio,strides=2,stage=1,block=1): if K.image_data_format() == 'channels_last': bn_axis = -1 else: raise ValueError('Only channels last supported') prefix = 'stage{}/block{}'.format(stage, block) bottleneck_channels = int(out_channels * bottleneck_ratio) if strides < 2: c_hat, c = channel_split(inputs, '{}/spl'.format(prefix)) inputs = c x = Conv2D(bottleneck_channels, kernel_size=(1,1), strides=1, padding='same', name='{}/1x1conv_1'.format(prefix))(inputs) x = BatchNormalization(axis=bn_axis, name='{}/bn_1x1conv_1'.format(prefix))(x) x = Activation('relu', name='{}/relu_1x1conv_1'.format(prefix))(x) x = DepthwiseConv2D(kernel_size=3, strides=strides, padding='same', name='{}/3x3dwconv'.format(prefix))(x) x = BatchNormalization(axis=bn_axis, name='{}/bn_3x3dwconv'.format(prefix))(x) x = Conv2D(bottleneck_channels, kernel_size=1,strides=1,padding='same', name='{}/1x1conv_2'.format(prefix))(x) x = BatchNormalization(axis=bn_axis, name='{}/bn_1x1conv_2'.format(prefix))(x) x = Activation('relu', name='{}/relu_1x1conv_2'.format(prefix))(x) if strides < 2: ret = Concatenate(axis=bn_axis, name='{}/concat_1'.format(prefix))([x, c_hat]) else: s2 = DepthwiseConv2D(kernel_size=3, strides=2, padding='same', name='{}/3x3dwconv_2'.format(prefix))(inputs) s2 = BatchNormalization(axis=bn_axis, name='{}/bn_3x3dwconv_2'.format(prefix))(s2) s2 = Conv2D(bottleneck_channels, kernel_size=1,strides=1,padding='same', name='{}/1x1_conv_3'.format(prefix))(s2) s2 = BatchNormalization(axis=bn_axis, name='{}/bn_1x1conv_3'.format(prefix))(s2) s2 = Activation('relu', name='{}/relu_1x1conv_3'.format(prefix))(s2) ret = Concatenate(axis=bn_axis, name='{}/concat_2'.format(prefix))([x, s2]) ret = Lambda(channel_shuffle, name='{}/channel_shuffle'.format(prefix))(ret) return ret def block(x, channel_map, bottleneck_ratio, repeat=1, stage=1): x = shuffle_unit(x, out_channels=channel_map[stage-1], strides=2,bottleneck_ratio=bottleneck_ratio,stage=stage,block=1) for i in range(1, repeat+1): x = shuffle_unit(x, out_channels=channel_map[stage-1],strides=1, bottleneck_ratio=bottleneck_ratio,stage=stage, block=(1+i)) return x

true

1c2fb781ddcd4218fd8a81658d8b1820f7658753

425

py

Python

setup.py

dhruvdcoder/allennlp-wandb

160dceb1f4cec8e893b856d333bc302748afdd74

[ "MIT" ]

null

setup.py

dhruvdcoder/allennlp-wandb

160dceb1f4cec8e893b856d333bc302748afdd74

[ "MIT" ]

null

setup.py

dhruvdcoder/allennlp-wandb

160dceb1f4cec8e893b856d333bc302748afdd74

[ "MIT" ]

null

from setuptools import setup, find_packages install_requires = [ "allennlp>=0.9.0", "wandb==0.8.15", ] setup( name='allennlp_wandb', version='0.0.1', description='Utilities to use allennlp with wandb', packages=find_packages( exclude=["*.tests", "*.tests.*", "tests.*", "tests"]), package_data={'allennlp_wandb': ['py.typed']}, install_requires=install_requires, zip_safe=False)

25

62

0.647059

from setuptools import setup, find_packages install_requires = [ "allennlp>=0.9.0", "wandb==0.8.15", ] setup( name='allennlp_wandb', version='0.0.1', description='Utilities to use allennlp with wandb', packages=find_packages( exclude=["*.tests", "*.tests.*", "tests.*", "tests"]), package_data={'allennlp_wandb': ['py.typed']}, install_requires=install_requires, zip_safe=False)

true

1c2fb7ce59e423e59b7589b3cf8fd6d6bac8e56f

10,685

py

Python

gateware/butterstick-bitstream.py

butterstick-fpga/test-fixture-sw

6ab19faaeaaf3368fd9cd308fa94f913fe3e54be

[ "BSD-2-Clause" ]

null

gateware/butterstick-bitstream.py

butterstick-fpga/test-fixture-sw

6ab19faaeaaf3368fd9cd308fa94f913fe3e54be

[ "BSD-2-Clause" ]

null

gateware/butterstick-bitstream.py

butterstick-fpga/test-fixture-sw

6ab19faaeaaf3368fd9cd308fa94f913fe3e54be

[ "BSD-2-Clause" ]

null

#!/usr/bin/env python3 # This file is Copyright (c) Greg Davill <greg.davill@gmail.com> # License: BSD # This variable defines all the external programs that this module # relies on. lxbuildenv reads this variable in order to ensure # the build will finish without exiting due to missing third-party # programs. LX_DEPENDENCIES = ["riscv", "nextpnr-ecp5", "yosys"] # Import lxbuildenv to integrate the deps/ directory import lxbuildenv import os import shutil import argparse import subprocess from migen import * from migen.genlib.resetsync import AsyncResetSynchronizer from litex.build.lattice.trellis import trellis_args, trellis_argdict from litex.soc.integration.soc_core import * from litex.soc.integration.builder import * from litex.soc.interconnect.csr import * from litex.soc.cores.clock import * from litex.soc.cores.clock.common import period_ns from litex.soc.cores.gpio import GPIOOut, GPIOIn, GPIOTristate from litex.soc.cores.spi_flash import SpiFlashDualQuad from litedram.modules import MT41K256M16 from litedram.phy import ECP5DDRPHY from liteeth.phy.ecp5rgmii import LiteEthPHYRGMII from rtl.platform import butterstick_r1d0 from rtl.rgb import Leds from rtl.vccio import VccIo # CRG --------------------------------------------------------------------------------------------- class _CRG(Module): def __init__(self, platform, sys_clk_freq): self.rst = Signal() self.clock_domains.cd_init = ClockDomain() self.clock_domains.cd_por = ClockDomain(reset_less=True) self.clock_domains.cd_sys = ClockDomain() self.clock_domains.cd_sys2x = ClockDomain() self.clock_domains.cd_sys2x_i = ClockDomain(reset_less=True) # # # self.stop = Signal() self.reset = Signal() # Clk / Rst clk30 = platform.request("clk30") rst_n = platform.request("user_btn", 0) platform.add_period_constraint(clk30, period_ns(30e6)) platform.add_period_constraint(ClockSignal('jtag'), period_ns(20e6)) # Power on reset por_count = Signal(16, reset=2**16-1) por_done = Signal() self.comb += self.cd_por.clk.eq(clk30) self.comb += por_done.eq(por_count == 0) self.sync.por += If(~por_done, por_count.eq(por_count - 1)) # PLL self.submodules.pll = pll = ECP5PLL() self.comb += pll.reset.eq(~por_done | ~rst_n | self.rst) pll.register_clkin(clk30, 30e6) pll.create_clkout(self.cd_sys2x_i, 2*sys_clk_freq) pll.create_clkout(self.cd_init, 25e6) self.specials += [ Instance("ECLKSYNCB", i_ECLKI = self.cd_sys2x_i.clk, i_STOP = self.stop, o_ECLKO = self.cd_sys2x.clk), Instance("CLKDIVF", p_DIV = "2.0", i_ALIGNWD = 0, i_CLKI = self.cd_sys2x.clk, i_RST = self.reset, o_CDIVX = self.cd_sys.clk), AsyncResetSynchronizer(self.cd_sys, ~pll.locked | self.reset), AsyncResetSynchronizer(self.cd_sys2x, ~pll.locked | self.reset), ] # BaseSoC ------------------------------------------------------------------------------------------ class BaseSoC(SoCCore): mem_map = { "rom": 0x00000000, # (default shadow @0x80000000) "testrom": 0x08000000, # (default shadow @0x80000000) "sram": 0x10000000, # (default shadow @0xa0000000) "spiflash": 0x20000000, # (default shadow @0xa0000000) "main_ram": 0x40000000, # (default shadow @0xc0000000) "csr": 0xf0000000, # (default shadow @0xe0000000) "usb": 0xf0010000, } mem_map.update(SoCCore.mem_map) interrupt_map = { "timer0": 0, "uart": 1, } interrupt_map.update(SoCCore.interrupt_map) def __init__(self, sys_clk_freq=int(60e6), toolchain="trellis", **kwargs): # Board Revision --------------------------------------------------------------------------- revision = kwargs.get("revision", "0.2") device = kwargs.get("device", "25F") platform = butterstick_r1d0.ButterStickPlatform() # Serial ----------------------------------------------------------------------------------- # platform.add_extension(butterstick_r1d0._uart_debug) # SoCCore ---------------------------------------------------------------------------------- SoCCore.__init__(self, platform, clk_freq=sys_clk_freq, csr_data_width=32, integrated_rom_size=32*1024, integrated_sram_size=16*1024, uart_name='jtag_uart') # CRG -------------------------------------------------------------------------------------- self.submodules.crg = crg = _CRG(platform, sys_clk_freq) # VCCIO Control ---------------------------------------------------------------------------- self.submodules.vccio = VccIo(platform.request("vccio_ctrl")) # SPI Flash -------------------------------------------------------------------------------- from litespi.modules import W25Q128JV from litespi.opcodes import SpiNorFlashOpCodes as Codes self.add_spi_flash(mode="4x", module=W25Q128JV(Codes.READ_1_1_4), with_master=True) # Leds ------------------------------------------------------------------------------------- led = platform.request("led_rgb_multiplex") self.submodules.leds = Leds(led.a, led.c) self.add_csr("leds") # Test rom --------------------------------------------------------------------------------- self.add_rom("testrom", origin = self.mem_map['testrom'], size = 32*1024, contents = [], mode = 'r', ) self.add_constant("ROM_BOOT_ADDRESS", self.mem_map['testrom']) self.add_constant("UART_POLLING") self.submodules.gpioa = GPIOTristate(platform.request('gpio',0)) self.submodules.gpiob = GPIOTristate(platform.request('gpio',1)) self.submodules.gpioc = GPIOTristate(platform.request('gpio',2)) self.submodules.ddrphy = ECP5DDRPHY( platform.request("ddram"), sys_clk_freq=sys_clk_freq) self.comb += self.crg.stop.eq(self.ddrphy.init.stop) self.comb += self.crg.reset.eq(self.ddrphy.init.reset) self.add_sdram("sdram", phy = self.ddrphy, module = MT41K256M16(sys_clk_freq, "1:2"), l2_cache_size = kwargs.get("l2_size", 8192) ) # Ethernet / Etherbone --------------------------------------------------------------------- self.submodules.ethphy = LiteEthPHYRGMII( clock_pads = self.platform.request("eth_clocks"), pads = self.platform.request("eth")) self.add_ethernet(phy=self.ethphy) # Self Reset ------------------------------------------------------------------------------- rst = Signal() self.submodules.reset = GPIOOut(rst) self.comb += platform.request("rst_n").eq(~rst) # Buttons ---------------------------------------------------------------------------------- self.submodules.button = GPIOIn(platform.request("user_btn")) #Add GIT repo to the firmware git_rev_cmd = subprocess.Popen("git describe --tags --first-parent --always".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE) (git_stdout, _) = git_rev_cmd.communicate() self.add_constant('CONFIG_REPO_GIT_DESC',git_stdout.decode('ascii').strip('\n')) def PackageTestRom(self, builder): self.finalize() os.makedirs(builder.output_dir, exist_ok=True) # Remove un-needed sw packages builder.add_software_package("testrom", "{}/../firmware/testrom".format(os.getcwd())) builder._prepare_rom_software() builder._generate_includes() builder._generate_rom_software(compile_bios=False) # patch random file into BRAM rom_file = os.path.join(builder.software_dir, "testrom", "demo.bin") rom_data = soc_core.get_mem_data(rom_file, self.cpu.endianness) # Initialize SoC with with demo data. self.testrom.mem.init = rom_data def CreateFirmwareInit(init, output_file): content = "" for d in init: content += "{:08x}\n".format(d) with open(output_file, "w") as o: o.write(content) # Build -------------------------------------------------------------------------------------------- def main(): parser = argparse.ArgumentParser(description="Build ButterStick test gateware") parser.add_argument("--update-firmware", default=False, action='store_true', help="compile firmware and update existing gateware") args = parser.parse_args() soc = BaseSoC() builder = Builder(soc) rand_rom = os.path.join(builder.gateware_dir, "rand.data") input_config = os.path.join(builder.gateware_dir, f"{soc.platform.name}.config") output_config = os.path.join(builder.gateware_dir, f"{soc.platform.name}_patched.config") # Create rand fill for BRAM if (os.path.exists(rand_rom) == False) or (args.update_firmware == False): os.makedirs(os.path.join(builder.output_dir, 'software'), exist_ok=True) os.makedirs(os.path.join(builder.output_dir, 'gateware'), exist_ok=True) os.system(f"ecpbram --generate {rand_rom} --seed {0} --width {32} --depth {32*1024 // 4}") # patch random file into BRAM data = [] with open(rand_rom, 'r') as inp: for d in inp.readlines(): data += [int(d, 16)] soc.testrom.mem.init = data # Build gateware vns = builder.build() soc.do_exit(vns) soc.finalize() soc.PackageTestRom(builder) testrom_file = "{}/testrom/demo.bin".format(builder.software_dir) testrom_init = "{}/testrom/testrom.init".format(builder.software_dir) CreateFirmwareInit(get_mem_data(testrom_file, soc.cpu.endianness), testrom_init) # Insert Firmware into Gateware os.system(f"ecpbram --input {input_config} --output {output_config} --from {rand_rom} --to {testrom_init}") # create compressed config (ECP5 specific) output_bitstream = os.path.join(builder.gateware_dir, f"{soc.platform.name}.bit") os.system(f"ecppack --freq 38.8 --compress --input {output_config} --bit {output_bitstream}") if __name__ == "__main__": main()

37.756184

172

0.563594

LX_DEPENDENCIES = ["riscv", "nextpnr-ecp5", "yosys"] import lxbuildenv import os import shutil import argparse import subprocess from migen import * from migen.genlib.resetsync import AsyncResetSynchronizer from litex.build.lattice.trellis import trellis_args, trellis_argdict from litex.soc.integration.soc_core import * from litex.soc.integration.builder import * from litex.soc.interconnect.csr import * from litex.soc.cores.clock import * from litex.soc.cores.clock.common import period_ns from litex.soc.cores.gpio import GPIOOut, GPIOIn, GPIOTristate from litex.soc.cores.spi_flash import SpiFlashDualQuad from litedram.modules import MT41K256M16 from litedram.phy import ECP5DDRPHY from liteeth.phy.ecp5rgmii import LiteEthPHYRGMII from rtl.platform import butterstick_r1d0 from rtl.rgb import Leds from rtl.vccio import VccIo class _CRG(Module): def __init__(self, platform, sys_clk_freq): self.rst = Signal() self.clock_domains.cd_init = ClockDomain() self.clock_domains.cd_por = ClockDomain(reset_less=True) self.clock_domains.cd_sys = ClockDomain() self.clock_domains.cd_sys2x = ClockDomain() self.clock_domains.cd_sys2x_i = ClockDomain(reset_less=True) self.stop = Signal() self.reset = Signal() clk30 = platform.request("clk30") rst_n = platform.request("user_btn", 0) platform.add_period_constraint(clk30, period_ns(30e6)) platform.add_period_constraint(ClockSignal('jtag'), period_ns(20e6)) por_count = Signal(16, reset=2**16-1) por_done = Signal() self.comb += self.cd_por.clk.eq(clk30) self.comb += por_done.eq(por_count == 0) self.sync.por += If(~por_done, por_count.eq(por_count - 1)) self.submodules.pll = pll = ECP5PLL() self.comb += pll.reset.eq(~por_done | ~rst_n | self.rst) pll.register_clkin(clk30, 30e6) pll.create_clkout(self.cd_sys2x_i, 2*sys_clk_freq) pll.create_clkout(self.cd_init, 25e6) self.specials += [ Instance("ECLKSYNCB", i_ECLKI = self.cd_sys2x_i.clk, i_STOP = self.stop, o_ECLKO = self.cd_sys2x.clk), Instance("CLKDIVF", p_DIV = "2.0", i_ALIGNWD = 0, i_CLKI = self.cd_sys2x.clk, i_RST = self.reset, o_CDIVX = self.cd_sys.clk), AsyncResetSynchronizer(self.cd_sys, ~pll.locked | self.reset), AsyncResetSynchronizer(self.cd_sys2x, ~pll.locked | self.reset), ] class BaseSoC(SoCCore): mem_map = { "rom": 0x00000000, "testrom": 0x08000000, "sram": 0x10000000, "spiflash": 0x20000000, "main_ram": 0x40000000, "csr": 0xf0000000, "usb": 0xf0010000, } mem_map.update(SoCCore.mem_map) interrupt_map = { "timer0": 0, "uart": 1, } interrupt_map.update(SoCCore.interrupt_map) def __init__(self, sys_clk_freq=int(60e6), toolchain="trellis", **kwargs): revision = kwargs.get("revision", "0.2") device = kwargs.get("device", "25F") platform = butterstick_r1d0.ButterStickPlatform() SoCCore.__init__(self, platform, clk_freq=sys_clk_freq, csr_data_width=32, integrated_rom_size=32*1024, integrated_sram_size=16*1024, uart_name='jtag_uart') self.submodules.crg = crg = _CRG(platform, sys_clk_freq) self.submodules.vccio = VccIo(platform.request("vccio_ctrl")) from litespi.modules import W25Q128JV from litespi.opcodes import SpiNorFlashOpCodes as Codes self.add_spi_flash(mode="4x", module=W25Q128JV(Codes.READ_1_1_4), with_master=True) led = platform.request("led_rgb_multiplex") self.submodules.leds = Leds(led.a, led.c) self.add_csr("leds") self.add_rom("testrom", origin = self.mem_map['testrom'], size = 32*1024, contents = [], mode = 'r', ) self.add_constant("ROM_BOOT_ADDRESS", self.mem_map['testrom']) self.add_constant("UART_POLLING") self.submodules.gpioa = GPIOTristate(platform.request('gpio',0)) self.submodules.gpiob = GPIOTristate(platform.request('gpio',1)) self.submodules.gpioc = GPIOTristate(platform.request('gpio',2)) self.submodules.ddrphy = ECP5DDRPHY( platform.request("ddram"), sys_clk_freq=sys_clk_freq) self.comb += self.crg.stop.eq(self.ddrphy.init.stop) self.comb += self.crg.reset.eq(self.ddrphy.init.reset) self.add_sdram("sdram", phy = self.ddrphy, module = MT41K256M16(sys_clk_freq, "1:2"), l2_cache_size = kwargs.get("l2_size", 8192) ) self.submodules.ethphy = LiteEthPHYRGMII( clock_pads = self.platform.request("eth_clocks"), pads = self.platform.request("eth")) self.add_ethernet(phy=self.ethphy) rst = Signal() self.submodules.reset = GPIOOut(rst) self.comb += platform.request("rst_n").eq(~rst) self.submodules.button = GPIOIn(platform.request("user_btn")) git_rev_cmd = subprocess.Popen("git describe --tags --first-parent --always".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE) (git_stdout, _) = git_rev_cmd.communicate() self.add_constant('CONFIG_REPO_GIT_DESC',git_stdout.decode('ascii').strip('\n')) def PackageTestRom(self, builder): self.finalize() os.makedirs(builder.output_dir, exist_ok=True) builder.add_software_package("testrom", "{}/../firmware/testrom".format(os.getcwd())) builder._prepare_rom_software() builder._generate_includes() builder._generate_rom_software(compile_bios=False) rom_file = os.path.join(builder.software_dir, "testrom", "demo.bin") rom_data = soc_core.get_mem_data(rom_file, self.cpu.endianness) self.testrom.mem.init = rom_data def CreateFirmwareInit(init, output_file): content = "" for d in init: content += "{:08x}\n".format(d) with open(output_file, "w") as o: o.write(content) def main(): parser = argparse.ArgumentParser(description="Build ButterStick test gateware") parser.add_argument("--update-firmware", default=False, action='store_true', help="compile firmware and update existing gateware") args = parser.parse_args() soc = BaseSoC() builder = Builder(soc) rand_rom = os.path.join(builder.gateware_dir, "rand.data") input_config = os.path.join(builder.gateware_dir, f"{soc.platform.name}.config") output_config = os.path.join(builder.gateware_dir, f"{soc.platform.name}_patched.config") if (os.path.exists(rand_rom) == False) or (args.update_firmware == False): os.makedirs(os.path.join(builder.output_dir, 'software'), exist_ok=True) os.makedirs(os.path.join(builder.output_dir, 'gateware'), exist_ok=True) os.system(f"ecpbram --generate {rand_rom} --seed {0} --width {32} --depth {32*1024 // 4}") data = [] with open(rand_rom, 'r') as inp: for d in inp.readlines(): data += [int(d, 16)] soc.testrom.mem.init = data vns = builder.build() soc.do_exit(vns) soc.finalize() soc.PackageTestRom(builder) testrom_file = "{}/testrom/demo.bin".format(builder.software_dir) testrom_init = "{}/testrom/testrom.init".format(builder.software_dir) CreateFirmwareInit(get_mem_data(testrom_file, soc.cpu.endianness), testrom_init) os.system(f"ecpbram --input {input_config} --output {output_config} --from {rand_rom} --to {testrom_init}") output_bitstream = os.path.join(builder.gateware_dir, f"{soc.platform.name}.bit") os.system(f"ecppack --freq 38.8 --compress --input {output_config} --bit {output_bitstream}") if __name__ == "__main__": main()

true

1c2fb937fada7a62b8037f0529f48779b7d7d22b

6,028

py

Python

PyForge/ForgeUsers.py

sgthakare20/Pyforge

e3ce15586ccc07f39e0faf18885b472baa60ff5d

[ "MIT" ]

1

2020-04-13T13:02:43.000Z

PyForge/ForgeUsers.py

sgthakare20/Pyforge

e3ce15586ccc07f39e0faf18885b472baa60ff5d

[ "MIT" ]

null

PyForge/ForgeUsers.py

sgthakare20/Pyforge

e3ce15586ccc07f39e0faf18885b472baa60ff5d

[ "MIT" ]

2

2021-06-22T14:39:53.000Z

2021-06-22T15:28:21.000Z

# -*- coding: utf-8 -*- """Module containing classes related to users on the Autodesk Forge BIM360 platform.""" from PyForge.ForgeApi import ForgeApi class UsersApi(ForgeApi): """This class provides the base API calls for Autodesk BIM360 users.""" def __init__(self, token, base_url=r'https://developer.api.autodesk.com/bim360/admin/v1/', timeout=1): """ Initialize the UsersApi class and attach an authentication token for the Autodesk Forge API. Args: token (str): Authentication token for Autodesk Forge API. base_url (str, optional): Base URL for calls to the users API. Defaults to r'https://developer.api.autodesk.com/bim360/admin/v1/' timeout (float, optional): Default timeout for API calls. Defaults to 1. Returns: None. """ self.token = token def get_project_users(self, project_id=None, region='US', accept_language="de", filters={}, limit=100, offset=0, sort=[], fields=[], endpoint=r'projects/:projectId/users'): """ Send a GET projects/:projectId/users request to the BIM360 API, returns the users assigned to the project. Args: project_id (str, optional): The project id for the BIM360 project. Defaults to None. region (str, optional): The BIM360 server region to be adressed, can be US or EMEA. Defaults to US. accept_language (str, optional): The language in which the response is to be returned. Defaults to de. filters (dict, optional): A dict of filters in the form {filtertype : List(str filter entries)}. Defaults to {}. limit (int, optional): Size of the response array. Defaults to 100. offset (int, optional): Offset of the response array. Defaults to 0. sort (list, optional): List of string field names to sort in ascending order, Prepending a field with - sorts in descending order. Defaults to []. fields (list, optional): List of string field names to include in the response array. Defaults to []. endpoint (str, optional): endpoint for the GET projects/:projectId/users request. Defaults to r'projects/:projectId/users' Raises: ValueError: If self.token, project_id are of NoneType. ConnectionError: Different Connectionerrors based on retrieved ApiErrors from the Forge API. Returns: list(dict(JsonApiObject)): List of users JsonApi objects in the form of dicts. """ try: token = self.token except AttributeError: raise ValueError("Please initialise the UsersApi.") if project_id is None: raise ValueError("Please enter a project id.") if project_id.startswith("b."): project_id = project_id[2:] endpoint = endpoint.replace(':projectId', project_id) headers = {} headers.update({'Authorization' : "Bearer {}".format(token)}) headers.update({'Accept-Language' : accept_language}) headers.update({'Region' : region}) params = {} params.update({'limit' : limit}) params.update({'offset' : offset}) params.update(self.make_filters(filters)) if sort: sort = ",".join(sort) params.update({'sort' : sort}) if fields: fields = ",".join(fields) params.update({'field' : fields}) resp = self.http.get(endpoint, headers=headers, params=params) if resp.status_code == 200: cont = resp.json()['results'] if isinstance(cont, list): if len(cont) == limit: cont += self.get_account_projects(token=token, project_id=project_id, region=region, accept_language=accept_language, filters=filters, limit=limit, offset=offset+limit, sort=sort, fields=fields, url=url) return cont else: raise TypeError(f"Invalid response type for endpoint: {endpoint}\n" + f"with content: {resp.content}") if resp.status_code == 401: raise ConnectionError("Renew authorization token.") raise ConnectionError("Request failed with code {}".format(resp.status_code) + " and message : {}".format(resp.content) + " for endpoint: {}".format(endpoint)) def make_filters(self, filters): """ Create a filter query parameter of the given type with the given entries. Args: filters (dict, {str, filter_name : list(str, filter entires)}): The filters to be used. Raises: ValueError: Raised if the filter entries exceed 255 characters. TypeError: Raised if the filters parameter is not of type dict. Returns: dict: A filter dictionary to be used as a query parameter. """ if isinstance(filters, dict): if filters: for filt, entries in filters.items(): things = ",".join(entries) if len(things) > 255: raise ValueError("Max filterlength is 255 characters.") return {"filter[{}]".format(filt) : things} else: return {} raise TypeError("filters parameter has the wrong type: {}".format(type(filters)))

42.751773

158

0.547279

from PyForge.ForgeApi import ForgeApi class UsersApi(ForgeApi): def __init__(self, token, base_url=r'https://developer.api.autodesk.com/bim360/admin/v1/', timeout=1): self.token = token def get_project_users(self, project_id=None, region='US', accept_language="de", filters={}, limit=100, offset=0, sort=[], fields=[], endpoint=r'projects/:projectId/users'): try: token = self.token except AttributeError: raise ValueError("Please initialise the UsersApi.") if project_id is None: raise ValueError("Please enter a project id.") if project_id.startswith("b."): project_id = project_id[2:] endpoint = endpoint.replace(':projectId', project_id) headers = {} headers.update({'Authorization' : "Bearer {}".format(token)}) headers.update({'Accept-Language' : accept_language}) headers.update({'Region' : region}) params = {} params.update({'limit' : limit}) params.update({'offset' : offset}) params.update(self.make_filters(filters)) if sort: sort = ",".join(sort) params.update({'sort' : sort}) if fields: fields = ",".join(fields) params.update({'field' : fields}) resp = self.http.get(endpoint, headers=headers, params=params) if resp.status_code == 200: cont = resp.json()['results'] if isinstance(cont, list): if len(cont) == limit: cont += self.get_account_projects(token=token, project_id=project_id, region=region, accept_language=accept_language, filters=filters, limit=limit, offset=offset+limit, sort=sort, fields=fields, url=url) return cont else: raise TypeError(f"Invalid response type for endpoint: {endpoint}\n" + f"with content: {resp.content}") if resp.status_code == 401: raise ConnectionError("Renew authorization token.") raise ConnectionError("Request failed with code {}".format(resp.status_code) + " and message : {}".format(resp.content) + " for endpoint: {}".format(endpoint)) def make_filters(self, filters): if isinstance(filters, dict): if filters: for filt, entries in filters.items(): things = ",".join(entries) if len(things) > 255: raise ValueError("Max filterlength is 255 characters.") return {"filter[{}]".format(filt) : things} else: return {} raise TypeError("filters parameter has the wrong type: {}".format(type(filters)))

true

1c2fb9e585142cd6b3ce74512705e983aa22ee83

1,608

py

Python

amber/urls.py

Taywee/amberherbert.com

6bf384d7cdf18dc613252fe4dde38545150eabbc

[ "MIT" ]

null

amber/urls.py

Taywee/amberherbert.com

6bf384d7cdf18dc613252fe4dde38545150eabbc

[ "MIT" ]

2

2017-10-15T20:36:59.000Z

2017-10-17T05:27:49.000Z

amber/urls.py

Taywee/amberherbert.com

6bf384d7cdf18dc613252fe4dde38545150eabbc

[ "MIT" ]

null

from __future__ import absolute_import, unicode_literals from django.conf import settings from django.conf.urls import include, url from django.contrib import admin from wagtail.admin import urls as wagtailadmin_urls from wagtail.core import urls as wagtail_urls from wagtail.documents import urls as wagtaildocs_urls from search import views as search_views try: with open('/etc/amberherbert/django-admin.path', 'r') as file: djadmin = file.read().strip() except FileNotFoundError: djadmin = r'^django-admin/' try: with open('/etc/amberherbert/wagtail-admin.path', 'r') as file: wtadmin = file.read().strip() except FileNotFoundError: wtadmin = r'^admin/' urlpatterns = [ url(djadmin, admin.site.urls), url(wtadmin, include(wagtailadmin_urls)), url(r'^documents/', include(wagtaildocs_urls)), url(r'^search/$', search_views.search, name='search'), # For anything not caught by a more specific rule above, hand over to # Wagtail's page serving mechanism. This should be the last pattern in # the list: url(r'', include(wagtail_urls)), # Alternatively, if you want Wagtail pages to be served from a subpath # of your site, rather than the site root: # url(r'^pages/', include(wagtail_urls)), ] if settings.DEBUG: from django.conf.urls.static import static from django.contrib.staticfiles.urls import staticfiles_urlpatterns # Serve static and media files from development server urlpatterns += staticfiles_urlpatterns() urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

31.529412

80

0.731343

from __future__ import absolute_import, unicode_literals from django.conf import settings from django.conf.urls import include, url from django.contrib import admin from wagtail.admin import urls as wagtailadmin_urls from wagtail.core import urls as wagtail_urls from wagtail.documents import urls as wagtaildocs_urls from search import views as search_views try: with open('/etc/amberherbert/django-admin.path', 'r') as file: djadmin = file.read().strip() except FileNotFoundError: djadmin = r'^django-admin/' try: with open('/etc/amberherbert/wagtail-admin.path', 'r') as file: wtadmin = file.read().strip() except FileNotFoundError: wtadmin = r'^admin/' urlpatterns = [ url(djadmin, admin.site.urls), url(wtadmin, include(wagtailadmin_urls)), url(r'^documents/', include(wagtaildocs_urls)), url(r'^search/$', search_views.search, name='search'), # the list: url(r'', include(wagtail_urls)), # Alternatively, if you want Wagtail pages to be served from a subpath # of your site, rather than the site root: # url(r'^pages/', include(wagtail_urls)), ] if settings.DEBUG: from django.conf.urls.static import static from django.contrib.staticfiles.urls import staticfiles_urlpatterns # Serve static and media files from development server urlpatterns += staticfiles_urlpatterns() urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

true

1c2fb9fa00e7283d38dd9f6522c0eb79545438ef

2,145

py

Python

sympy/polys/tests/test_rationaltools.py

minrk/sympy

1cc6e3837b8ed20ba52ea97298f31aa08b43c508

[ "BSD-3-Clause" ]

2

2015-11-13T16:40:57.000Z

2017-09-15T15:37:19.000Z

openrave/sympy/polys/tests/test_rationaltools.py

jdsika/holy

a2ac55fa1751a3a8038cf61d29b95005f36d6264

[ "MIT" ]

1

2016-06-13T01:29:51.000Z

2016-06-14T00:38:27.000Z

openrave/sympy/polys/tests/test_rationaltools.py

jdsika/holy

a2ac55fa1751a3a8038cf61d29b95005f36d6264

[ "MIT" ]

null

"""Tests for tools for manipulation of rational expressions. """ from sympy.polys.rationaltools import together from sympy import S, symbols, Rational, sin, exp, Eq, Integral, Mul from sympy.abc import x, y, z A, B = symbols('A,B', commutative=False) def test_together(): assert together(0) == 0 assert together(1) == 1 assert together(x*y*z) == x*y*z assert together(x + y) == x + y assert together(1/x) == 1/x assert together(1/x + 1) == (x + 1)/x assert together(1/x + 3) == (3*x + 1)/x assert together(1/x + x) == (x**2 + 1)/x assert together(1/x + Rational(1, 2)) == (x + 2)/(2*x) assert together(Rational(1, 2) + x/2) == Mul(S.Half, x + 1, evaluate=False) assert together(1/x + 2/y) == (2*x + y)/(y*x) assert together(1/(1 + 1/x)) == x/(1 + x) assert together(x/(1 + 1/x)) == x**2/(1 + x) assert together(1/x + 1/y + 1/z) == (x*y + x*z + y*z)/(x*y*z) assert together(1/(1 + x + 1/y + 1/z)) == y*z/(y + z + y*z + x*y*z) assert together(1/(x*y) + 1/(x*y)**2) == y**(-2)*x**(-2)*(1 + x*y) assert together(1/(x*y) + 1/(x*y)**4) == y**(-4)*x**(-4)*(1 + x**3*y**3) assert together(1/(x**7*y) + 1/(x*y)**4) == y**(-4)*x**(-7)*(x**3 + y**3) assert together(5/(2 + 6/(3 + 7/(4 + 8/(5 + 9/x))))) == \ (S(5)/2)*((171 + 119*x)/(279 + 203*x)) assert together(1 + 1/(x + 1)**2) == (1 + (x + 1)**2)/(x + 1)**2 assert together(1 + 1/(x*(1 + x))) == (1 + x*(1 + x))/(x*(1 + x)) assert together(1/(x*(x + 1)) + 1/(x*(x + 2))) == (3 + 2*x)/(x*(1 + x)*(2 + x)) assert together(1 + 1/(2*x + 2)**2) == (4*(x + 1)**2 + 1)/(4*(x + 1)**2) assert together(sin(1/x + 1/y)) == sin(1/x + 1/y) assert together(sin(1/x + 1/y), deep=True) == sin((x + y)/(x*y)) assert together(1/exp(x) + 1/(x*exp(x))) == (1+x)/(x*exp(x)) assert together(1/exp(2*x) + 1/(x*exp(3*x))) == (1+exp(x)*x)/(x*exp(3*x)) assert together(Integral(1/x + 1/y, x)) == Integral((x + y)/(x*y), x) assert together(Eq(1/x + 1/y, 1 + 1/z)) == Eq((x + y)/(x*y), (z + 1)/z) assert together(1/(A*B) + 1/(B*A)) in [(A*B + B*A)/(B*A**2*B), (A*B + B*A)/(A*B**2*A)]

39

90

0.486247

from sympy.polys.rationaltools import together from sympy import S, symbols, Rational, sin, exp, Eq, Integral, Mul from sympy.abc import x, y, z A, B = symbols('A,B', commutative=False) def test_together(): assert together(0) == 0 assert together(1) == 1 assert together(x*y*z) == x*y*z assert together(x + y) == x + y assert together(1/x) == 1/x assert together(1/x + 1) == (x + 1)/x assert together(1/x + 3) == (3*x + 1)/x assert together(1/x + x) == (x**2 + 1)/x assert together(1/x + Rational(1, 2)) == (x + 2)/(2*x) assert together(Rational(1, 2) + x/2) == Mul(S.Half, x + 1, evaluate=False) assert together(1/x + 2/y) == (2*x + y)/(y*x) assert together(1/(1 + 1/x)) == x/(1 + x) assert together(x/(1 + 1/x)) == x**2/(1 + x) assert together(1/x + 1/y + 1/z) == (x*y + x*z + y*z)/(x*y*z) assert together(1/(1 + x + 1/y + 1/z)) == y*z/(y + z + y*z + x*y*z) assert together(1/(x*y) + 1/(x*y)**2) == y**(-2)*x**(-2)*(1 + x*y) assert together(1/(x*y) + 1/(x*y)**4) == y**(-4)*x**(-4)*(1 + x**3*y**3) assert together(1/(x**7*y) + 1/(x*y)**4) == y**(-4)*x**(-7)*(x**3 + y**3) assert together(5/(2 + 6/(3 + 7/(4 + 8/(5 + 9/x))))) == \ (S(5)/2)*((171 + 119*x)/(279 + 203*x)) assert together(1 + 1/(x + 1)**2) == (1 + (x + 1)**2)/(x + 1)**2 assert together(1 + 1/(x*(1 + x))) == (1 + x*(1 + x))/(x*(1 + x)) assert together(1/(x*(x + 1)) + 1/(x*(x + 2))) == (3 + 2*x)/(x*(1 + x)*(2 + x)) assert together(1 + 1/(2*x + 2)**2) == (4*(x + 1)**2 + 1)/(4*(x + 1)**2) assert together(sin(1/x + 1/y)) == sin(1/x + 1/y) assert together(sin(1/x + 1/y), deep=True) == sin((x + y)/(x*y)) assert together(1/exp(x) + 1/(x*exp(x))) == (1+x)/(x*exp(x)) assert together(1/exp(2*x) + 1/(x*exp(3*x))) == (1+exp(x)*x)/(x*exp(3*x)) assert together(Integral(1/x + 1/y, x)) == Integral((x + y)/(x*y), x) assert together(Eq(1/x + 1/y, 1 + 1/z)) == Eq((x + y)/(x*y), (z + 1)/z) assert together(1/(A*B) + 1/(B*A)) in [(A*B + B*A)/(B*A**2*B), (A*B + B*A)/(A*B**2*A)]

true

1c2fba2b5b481ced053f949679d016b98fc94c72

42,298

py

Python

tools/linter_lib/custom_check.py

dmryabov/zulip

fd2a63b049277f3cc7267a4a5bdbb485c4933719

[ "Apache-2.0" ]

null

tools/linter_lib/custom_check.py

dmryabov/zulip

fd2a63b049277f3cc7267a4a5bdbb485c4933719

[ "Apache-2.0" ]

null

tools/linter_lib/custom_check.py

dmryabov/zulip

fd2a63b049277f3cc7267a4a5bdbb485c4933719

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- from __future__ import print_function from __future__ import absolute_import from zulint.custom_rules import RuleList from typing import cast, Any, Dict, List, Tuple Rule = List[Dict[str, Any]] # Rule help: # By default, a rule applies to all files within the extension for which it is specified (e.g. all .py files) # There are three operators we can use to manually include or exclude files from linting for a rule: # 'exclude': 'set([<path>, ...])' - if <path> is a filename, excludes that file. # if <path> is a directory, excludes all files directly below the directory <path>. # 'exclude_line': 'set([(<path>, <line>), ...])' - excludes all lines matching <line> in the file <path> from linting. # 'include_only': 'set([<path>, ...])' - includes only those files where <path> is a substring of the filepath. LineTup = Tuple[int, str, str, str] PYDELIMS = r'''"'()\[\]{}#\\''' PYREG = r"[^{}]".format(PYDELIMS) PYSQ = r'"(?:[^"\\]|\\.)*"' PYDQ = r"'(?:[^'\\]|\\.)*'" PYLEFT = r"[(\[{]" PYRIGHT = r"[)\]}]" PYCODE = PYREG for depth in range(5): PYGROUP = r"""(?:{}|{}|{}{}*{})""".format(PYSQ, PYDQ, PYLEFT, PYCODE, PYRIGHT) PYCODE = r"""(?:{}|{})""".format(PYREG, PYGROUP) FILES_WITH_LEGACY_SUBJECT = { # This basically requires a big DB migration: 'zerver/lib/topic.py', # This is for backward compatibility. 'zerver/tests/test_legacy_subject.py', # Other migration-related changes require extreme care. 'zerver/lib/fix_unreads.py', 'zerver/tests/test_migrations.py', # These use subject in the email sense, and will # probably always be exempt: 'zerver/lib/email_mirror.py', 'zerver/lib/feedback.py', 'zerver/tests/test_new_users.py', 'zerver/tests/test_email_mirror.py', # These are tied more to our API than our DB model. 'zerver/openapi/python_examples.py', 'zerver/tests/test_openapi.py', # This has lots of query data embedded, so it's hard # to fix everything until we migrate the DB to "topic". 'zerver/tests/test_narrow.py', } shebang_rules = [ {'pattern': '^#!', 'description': "zerver library code shouldn't have a shebang line.", 'include_only': set(['zerver/'])}, # /bin/sh and /usr/bin/env are the only two binaries # that NixOS provides at a fixed path (outside a # buildFHSUserEnv sandbox). {'pattern': '^#!(?! *(?:/usr/bin/env|/bin/sh)(?: |$))', 'description': "Use `#!/usr/bin/env foo` instead of `#!/path/foo`" " for interpreters other than sh."}, {'pattern': '^#!/usr/bin/env python$', 'description': "Use `#!/usr/bin/env python3` instead of `#!/usr/bin/env python`."} ] # type: Rule trailing_whitespace_rule = { 'pattern': r'\s+$', 'strip': '\n', 'description': 'Fix trailing whitespace' } whitespace_rules = [ # This linter should be first since bash_rules depends on it. trailing_whitespace_rule, {'pattern': 'http://zulip.readthedocs.io', 'description': 'Use HTTPS when linking to ReadTheDocs', }, {'pattern': '\t', 'strip': '\n', 'exclude': set(['tools/ci/success-http-headers.txt']), 'description': 'Fix tab-based whitespace'}, ] # type: Rule comma_whitespace_rule = [ {'pattern': ', {2,}[^#/ ]', 'exclude': set(['zerver/tests', 'frontend_tests/node_tests', 'corporate/tests']), 'description': "Remove multiple whitespaces after ','", 'good_lines': ['foo(1, 2, 3)', 'foo = bar # some inline comment'], 'bad_lines': ['foo(1, 2, 3)', 'foo(1, 2, 3)']}, ] # type: Rule markdown_whitespace_rules = list([rule for rule in whitespace_rules if rule['pattern'] != r'\s+$']) + [ # Two spaces trailing a line with other content is okay--it's a markdown line break. # This rule finds one space trailing a non-space, three or more trailing spaces, and # spaces on an empty line. {'pattern': r'((?<!\s)\s$)|(\s\s\s+$)|(^\s+$)', 'strip': '\n', 'description': 'Fix trailing whitespace'}, {'pattern': '^#+[A-Za-z0-9]', 'strip': '\n', 'description': 'Missing space after # in heading', 'good_lines': ['### some heading', '# another heading'], 'bad_lines': ['###some heading', '#another heading']}, ] # type: Rule js_rules = RuleList( langs=['js'], rules=cast(Rule, [ {'pattern': 'subject|SUBJECT', 'exclude': set(['static/js/util.js', 'frontend_tests/']), 'exclude_pattern': 'emails', 'description': 'avoid subject in JS code', 'good_lines': ['topic_name'], 'bad_lines': ['subject="foo"', ' MAX_SUBJECT_LEN']}, {'pattern': r'[^_]function$', 'description': 'The keyword "function" should be followed by a space'}, {'pattern': r'.*blueslip.warning\(.*', 'description': 'The module blueslip has no function warning, try using blueslip.warn'}, {'pattern': '[)]{$', 'description': 'Missing space between ) and {'}, {'pattern': r'i18n\.t\([^)]+[^,\{$]$', 'description': 'i18n string should not be a multiline string'}, {'pattern': r'''i18n\.t$['"].+?['"]\s*\+''', 'description': 'Do not concatenate arguments within i18n.t()'}, {'pattern': r'i18n\.t\(.+$.*\+', 'description': 'Do not concatenate i18n strings'}, {'pattern': r'\+.*i18n\.t$.+$', 'description': 'Do not concatenate i18n strings'}, {'pattern': '[.]includes[(]', 'exclude': ['frontend_tests/'], 'description': '.includes() is incompatible with Internet Explorer. Use .indexOf() !== -1 instead.'}, {'pattern': '[.]html[(]', 'exclude_pattern': r'''[.]html[(]("|'|render_|html|message.content|sub.rendered_description|i18n.t|rendered_|$|[)]|error_text|widget_elem|[$]error|[$][(]"<p>"[)])''', 'exclude': ['static/js/portico', 'static/js/lightbox.js', 'static/js/ui_report.js', 'static/js/confirm_dialog.js', 'frontend_tests/'], 'description': 'Setting HTML content with jQuery .html() can lead to XSS security bugs. Consider .text() or using rendered_foo as a variable name if content comes from handlebars and thus is already sanitized.'}, {'pattern': '["\']json/', 'description': 'Relative URL for JSON route not supported by i18n'}, # This rule is constructed with + to avoid triggering on itself {'pattern': " =" + '[^ =>~"]', 'description': 'Missing whitespace after "="'}, {'pattern': '^[ ]*//[A-Za-z0-9]', 'description': 'Missing space after // in comment'}, {'pattern': 'if[(]', 'description': 'Missing space between if and ('}, {'pattern': 'else{$', 'description': 'Missing space between else and {'}, {'pattern': '^else {$', 'description': 'Write JS else statements on same line as }'}, {'pattern': '^else if', 'description': 'Write JS else statements on same line as }'}, {'pattern': 'console[.][a-z]', 'exclude': set(['static/js/blueslip.js', 'frontend_tests/zjsunit', 'frontend_tests/casper_lib/common.js', 'frontend_tests/node_tests', 'static/js/debug.js']), 'description': 'console.log and similar should not be used in webapp'}, {'pattern': r'''[.]text$["'][a-zA-Z]''', 'description': 'Strings passed to $().text should be wrapped in i18n.t() for internationalization', 'exclude': set(['frontend_tests/node_tests/'])}, {'pattern': r'''compose_error\(["']''', 'description': 'Argument to compose_error should be a literal string enclosed ' 'by i18n.t()'}, {'pattern': r'ui.report_success\(', 'description': 'Deprecated function, use ui_report.success.'}, {'pattern': r'''report.success\(["']''', 'description': 'Argument to report_success should be a literal string enclosed ' 'by i18n.t()'}, {'pattern': r'ui.report_error\(', 'description': 'Deprecated function, use ui_report.error.'}, {'pattern': r'''report.error\(["'][^'"]''', 'description': 'Argument to ui_report.error should be a literal string enclosed ' 'by i18n.t()', 'good_lines': ['ui_report.error("")', 'ui_report.error(_("text"))'], 'bad_lines': ['ui_report.error("test")']}, {'pattern': r'\$\(document$\.ready\(', 'description': "`Use $(f) rather than `$(document).ready(f)`", 'good_lines': ['$(function () {foo();}'], 'bad_lines': ['$(document).ready(function () {foo();}']}, {'pattern': '[$][.](get|post|patch|delete|ajax)[(]', 'description': "Use channel module for AJAX calls", 'exclude': set([ # Internal modules can do direct network calls 'static/js/blueslip.js', 'static/js/channel.js', # External modules that don't include channel.js 'static/js/stats/', 'static/js/portico/', 'static/js/billing/', ]), 'good_lines': ['channel.get(...)'], 'bad_lines': ['$.get()', '$.post()', '$.ajax()']}, {'pattern': 'style ?=', 'description': "Avoid using the `style=` attribute; we prefer styling in CSS files", 'exclude': set([ 'frontend_tests/node_tests/copy_and_paste.js', 'frontend_tests/node_tests/upload.js', 'frontend_tests/node_tests/templates.js', 'static/js/upload.js', 'static/js/stream_color.js', ]), 'good_lines': ['#my-style {color: blue;}'], 'bad_lines': ['<p style="color: blue;">Foo</p>', 'style = "color: blue;"']}, ]) + whitespace_rules + comma_whitespace_rule, ) python_rules = RuleList( langs=['py'], rules=cast(Rule, [ {'pattern': 'subject|SUBJECT', 'exclude_pattern': 'subject to the|email|outbox', 'description': 'avoid subject as a var', 'good_lines': ['topic_name'], 'bad_lines': ['subject="foo"', ' MAX_SUBJECT_LEN'], 'exclude': FILES_WITH_LEGACY_SUBJECT, 'include_only': set([ 'zerver/data_import/', 'zerver/lib/', 'zerver/tests/', 'zerver/views/'])}, {'pattern': '^(?!#)@login_required', 'description': '@login_required is unsupported; use @zulip_login_required', 'good_lines': ['@zulip_login_required', '# foo @login_required'], 'bad_lines': ['@login_required', ' @login_required']}, {'pattern': '^user_profile[.]save[(][)]', 'description': 'Always pass update_fields when saving user_profile objects', 'exclude_line': set([ ('zerver/lib/actions.py', "user_profile.save() # Can't use update_fields because of how the foreign key works."), ]), 'exclude': set(['zerver/tests', 'zerver/lib/create_user.py']), 'good_lines': ['user_profile.save(update_fields=["pointer"])'], 'bad_lines': ['user_profile.save()']}, {'pattern': r'^[^"]*"[^"]*"%\(', 'description': 'Missing space around "%"', 'good_lines': ['"%s" % ("foo")', '"%s" % (foo)'], 'bad_lines': ['"%s"%("foo")', '"%s"%(foo)']}, {'pattern': r"^[^']*'[^']*'%\(", 'description': 'Missing space around "%"', 'good_lines': ["'%s' % ('foo')", "'%s' % (foo)"], 'bad_lines': ["'%s'%('foo')", "'%s'%(foo)"]}, {'pattern': 'self: Any', 'description': 'you can omit Any annotation for self', 'good_lines': ['def foo (self):'], 'bad_lines': ['def foo(self: Any):']}, # This rule is constructed with + to avoid triggering on itself {'pattern': " =" + '[^ =>~"]', 'description': 'Missing whitespace after "="', 'good_lines': ['a = b', '5 == 6'], 'bad_lines': ['a =b', 'asdf =42']}, {'pattern': r'":\w[^"]*$', 'description': 'Missing whitespace after ":"', 'good_lines': ['"foo": bar', '"some:string:with:colons"'], 'bad_lines': ['"foo":bar', '"foo":1']}, {'pattern': r"':\w[^']*$", 'description': 'Missing whitespace after ":"', 'good_lines': ["'foo': bar", "'some:string:with:colons'"], 'bad_lines': ["'foo':bar", "'foo':1"]}, {'pattern': r"^\s+#\w", 'strip': '\n', 'exclude': set(['tools/droplets/create.py']), 'description': 'Missing whitespace after "#"', 'good_lines': ['a = b # some operation', '1+2 # 3 is the result'], 'bad_lines': [' #some operation', ' #not valid!!!']}, {'pattern': "assertEquals[(]", 'description': 'Use assertEqual, not assertEquals (which is deprecated).', 'good_lines': ['assertEqual(1, 2)'], 'bad_lines': ['assertEquals(1, 2)']}, {'pattern': "== None", 'description': 'Use `is None` to check whether something is None', 'good_lines': ['if foo is None'], 'bad_lines': ['foo == None']}, {'pattern': "type:[(]", 'description': 'Missing whitespace after ":" in type annotation', 'good_lines': ['# type: (Any, Any)', 'colon:separated:string:containing:type:as:keyword'], 'bad_lines': ['# type:(Any, Any)']}, {'pattern': "type: ignore$", 'exclude': set(['tools/tests', 'zerver/lib/test_runner.py', 'zerver/tests']), 'description': '"type: ignore" should always end with "# type: ignore # explanation for why"', 'good_lines': ['foo = bar # type: ignore # explanation'], 'bad_lines': ['foo = bar # type: ignore']}, {'pattern': "# type [(]", 'description': 'Missing : after type in type annotation', 'good_lines': ['foo = 42 # type: int', '# type: (str, int) -> None'], 'bad_lines': ['# type (str, int) -> None']}, {'pattern': "#type", 'description': 'Missing whitespace after "#" in type annotation', 'good_lines': ['foo = 42 # type: int'], 'bad_lines': ['foo = 42 #type: int']}, {'pattern': r'\b(if|else|while)[(]', 'description': 'Put a space between statements like if, else, etc. and (.', 'good_lines': ['if (1 == 2):', 'while (foo == bar):'], 'bad_lines': ['if(1 == 2):', 'while(foo == bar):']}, {'pattern': ", [)]", 'description': 'Unnecessary whitespace between "," and ")"', 'good_lines': ['foo = (1, 2, 3,)', 'foo(bar, 42)'], 'bad_lines': ['foo = (1, 2, 3, )']}, {'pattern': "% [(]", 'description': 'Unnecessary whitespace between "%" and "("', 'good_lines': ['"foo %s bar" % ("baz",)'], 'bad_lines': ['"foo %s bar" % ("baz",)']}, # This next check could have false positives, but it seems pretty # rare; if we find any, they can be added to the exclude list for # this rule. {'pattern': r"""^(?:[^'"#\\]|{}|{})*(?:{}|{})\s*%\s*(?![\s({{\\]|dict$|tuple\()(?:[^,{}]|{})+(?:$|[,#\\]|{})""".format( PYSQ, PYDQ, PYSQ, PYDQ, PYDELIMS, PYGROUP, PYRIGHT), 'description': 'Used % formatting without a tuple', 'good_lines': ['"foo %s bar" % ("baz",)'], 'bad_lines': ['"foo %s bar" % "baz"']}, {'pattern': r"""^(?:[^'"#\\]|{}|{})*(?:{}|{})\s*%\s*\((?:[^,{}]|{})*$""".format( PYSQ, PYDQ, PYSQ, PYDQ, PYDELIMS, PYGROUP), 'description': 'Used % formatting with parentheses that do not form a tuple', 'good_lines': ['"foo %s bar" % ("baz",)"'], 'bad_lines': ['"foo %s bar" % ("baz")']}, {'pattern': 'sudo', 'include_only': set(['scripts/']), 'exclude': set(['scripts/lib/setup_venv.py']), 'exclude_line': set([ ('scripts/lib/zulip_tools.py', 'sudo_args = kwargs.pop(\'sudo_args\', [])'), ('scripts/lib/zulip_tools.py', 'args = [\'sudo\'] + sudo_args + [\'--\'] + args'), ]), 'description': 'Most scripts are intended to run on systems without sudo.', 'good_lines': ['subprocess.check_call(["ls"])'], 'bad_lines': ['subprocess.check_call(["sudo", "ls"])']}, {'pattern': 'django.utils.translation', 'include_only': set(['test/', 'zerver/views/development/']), 'description': 'Test strings should not be tagged for translation', 'good_lines': [''], 'bad_lines': ['django.utils.translation']}, {'pattern': 'userid', 'description': 'We prefer user_id over userid.', 'good_lines': ['id = alice.user_id'], 'bad_lines': ['id = alice.userid']}, {'pattern': r'json_success${}$', 'description': 'Use json_success() to return nothing', 'good_lines': ['return json_success()'], 'bad_lines': ['return json_success({})']}, {'pattern': r'\Wjson_error$_\(?\w+$', 'exclude': set(['zerver/tests', 'zerver/views/development/']), 'description': 'Argument to json_error should be a literal string enclosed by _()', 'good_lines': ['return json_error(_("string"))'], 'bad_lines': ['return json_error(_variable)', 'return json_error(_(variable))']}, {'pattern': r'''\Wjson_error$['"].+[),]$''', 'exclude': set(['zerver/tests']), 'description': 'Argument to json_error should a literal string enclosed by _()'}, # To avoid JsonableError(_variable) and JsonableError(_(variable)) {'pattern': r'\WJsonableError\(_\(?\w.+$', 'exclude': set(['zerver/tests', 'zerver/views/development/']), 'description': 'Argument to JsonableError should be a literal string enclosed by _()'}, {'pattern': r'''\WJsonableError$["'].+$''', 'exclude': set(['zerver/tests', 'zerver/views/development/']), 'description': 'Argument to JsonableError should be a literal string enclosed by _()'}, {'pattern': r"""\b_\((?:\s|{}|{})*[^\s'")]""".format(PYSQ, PYDQ), 'description': 'Called _() on a computed string', 'exclude_line': set([ ('zerver/lib/i18n.py', 'result = _(string)'), ]), 'good_lines': ["return json_error(_('No presence data for %s') % (target.email,))"], 'bad_lines': ["return json_error(_('No presence data for %s' % (target.email,)))"]}, {'pattern': r'''([a-zA-Z0-9_]+)=REQ\(['"]\1['"]''', 'description': 'REQ\'s first argument already defaults to parameter name'}, {'pattern': r'self\.client\.(get|post|patch|put|delete)', 'description': \ '''Do not call self.client directly for put/patch/post/get. See WRAPPER_COMMENT in test_helpers.py for details. '''}, # Directly fetching Message objects in e.g. views code is often a security bug. {'pattern': '[^r]Message.objects.get', 'exclude': set(["zerver/tests", "zerver/lib/onboarding.py", "zilencer/management/commands/add_mock_conversation.py", "zerver/worker/queue_processors.py", "zerver/management/commands/export.py", "zerver/lib/export.py"]), 'description': 'Please use access_message() to fetch Message objects', }, {'pattern': 'Stream.objects.get', 'include_only': set(["zerver/views/"]), 'description': 'Please use access_stream_by_*() to fetch Stream objects', }, {'pattern': 'get_stream[(]', 'include_only': set(["zerver/views/", "zerver/lib/actions.py"]), 'exclude_line': set([ # This one in check_message is kinda terrible, since it's # how most instances are written, but better to exclude something than nothing ('zerver/lib/actions.py', 'stream = get_stream(stream_name, realm)'), ('zerver/lib/actions.py', 'get_stream(admin_realm_signup_notifications_stream, admin_realm)'), # Here we need get_stream to access streams you've since unsubscribed from. ('zerver/views/messages.py', 'stream = get_stream(operand, self.user_profile.realm)'), # Use stream_id to exclude mutes. ('zerver/views/messages.py', 'stream_id = get_stream(stream_name, user_profile.realm).id'), ]), 'description': 'Please use access_stream_by_*() to fetch Stream objects', }, {'pattern': 'Stream.objects.filter', 'include_only': set(["zerver/views/"]), 'description': 'Please use access_stream_by_*() to fetch Stream objects', }, {'pattern': '^from (zerver|analytics|confirmation)', 'include_only': set(["/migrations/"]), 'exclude': set([ 'zerver/migrations/0032_verify_all_medium_avatar_images.py', 'zerver/migrations/0060_move_avatars_to_be_uid_based.py', 'zerver/migrations/0104_fix_unreads.py', 'zerver/migrations/0206_stream_rendered_description.py', 'pgroonga/migrations/0002_html_escape_subject.py', ]), 'description': "Don't import models or other code in migrations; see docs/subsystems/schema-migrations.md", }, {'pattern': 'datetime[.](now|utcnow)', 'include_only': set(["zerver/", "analytics/"]), 'description': "Don't use datetime in backend code.\n" "See https://zulip.readthedocs.io/en/latest/contributing/code-style.html#naive-datetime-objects", }, {'pattern': r'render_to_response\(', 'description': "Use render() instead of render_to_response().", }, {'pattern': 'from os.path', 'description': "Don't use from when importing from the standard library", }, {'pattern': 'import os.path', 'description': "Use import os instead of import os.path", }, {'pattern': r'(logging|logger)\.warn\W', 'description': "Logger.warn is a deprecated alias for Logger.warning; Use 'warning' instead of 'warn'.", 'good_lines': ["logging.warning('I am a warning.')", "logger.warning('warning')"], 'bad_lines': ["logging.warn('I am a warning.')", "logger.warn('warning')"]}, {'pattern': r'\.pk', 'exclude_pattern': '[.]_meta[.]pk', 'description': "Use `id` instead of `pk`.", 'good_lines': ['if my_django_model.id == 42', 'self.user_profile._meta.pk'], 'bad_lines': ['if my_django_model.pk == 42']}, {'pattern': r'^[ ]*# type: $', 'exclude': set([ # These directories, especially scripts/ and puppet/, # have tools that need to run before a Zulip environment # is provisioned; in some of those, the `typing` module # might not be available yet, so care is required. 'scripts/', 'tools/', 'puppet/', # Zerver files that we should just clean. 'zerver/tests', 'zerver/openapi/python_examples.py', 'zerver/lib/request.py', 'zerver/views/streams.py', # thumbor is (currently) python2 only 'zthumbor/', ]), 'description': 'Comment-style function type annotation. Use Python3 style annotations instead.', }, {'pattern': r' = models[.].*null=True.*$ # type: (?!Optional)', 'include_only': {"zerver/models.py"}, 'description': 'Model variable with null=true not annotated as Optional.', 'good_lines': ['desc = models.TextField(null=True) # type: Optional[Text]', 'stream = models.ForeignKey(Stream, null=True, on_delete=CASCADE) # type: Optional[Stream]', 'desc = models.TextField() # type: Text', 'stream = models.ForeignKey(Stream, on_delete=CASCADE) # type: Stream'], 'bad_lines': ['desc = models.CharField(null=True) # type: Text', 'stream = models.ForeignKey(Stream, null=True, on_delete=CASCADE) # type: Stream'], }, {'pattern': r' = models[.](?!NullBoolean).*\) # type: Optional', # Optional tag, except NullBoolean(Field) 'exclude_pattern': 'null=True', 'include_only': {"zerver/models.py"}, 'description': 'Model variable annotated with Optional but variable does not have null=true.', 'good_lines': ['desc = models.TextField(null=True) # type: Optional[Text]', 'stream = models.ForeignKey(Stream, null=True, on_delete=CASCADE) # type: Optional[Stream]', 'desc = models.TextField() # type: Text', 'stream = models.ForeignKey(Stream, on_delete=CASCADE) # type: Stream'], 'bad_lines': ['desc = models.TextField() # type: Optional[Text]', 'stream = models.ForeignKey(Stream, on_delete=CASCADE) # type: Optional[Stream]'], }, {'pattern': r'[\s([]Text([^\s\w]|$)', 'exclude': set([ # We are likely to want to keep these dirs Python 2+3 compatible, # since the plan includes extracting them to a separate project eventually. 'tools/lib', # TODO: Update our migrations from Text->str. 'zerver/migrations/', # thumbor is (currently) python2 only 'zthumbor/', ]), 'description': "Now that we're a Python 3 only codebase, we don't need to use typing.Text. Please use str instead.", }, {'pattern': 'exit[(]1[)]', 'include_only': set(["/management/commands/"]), 'description': 'Raise CommandError to exit with failure in management commands', }, ]) + whitespace_rules + comma_whitespace_rule, max_length=110, shebang_rules=shebang_rules, ) bash_rules = RuleList( langs=['bash'], rules=cast(Rule, [ {'pattern': '#!.*sh [-xe]', 'description': 'Fix shebang line with proper call to /usr/bin/env for Bash path, change -x|-e switches' ' to set -x|set -e'}, {'pattern': 'sudo', 'description': 'Most scripts are intended to work on systems without sudo', 'include_only': set(['scripts/']), 'exclude': set([ 'scripts/lib/install', 'scripts/setup/configure-rabbitmq' ]), }, ]) + whitespace_rules[0:1], shebang_rules=shebang_rules, ) css_rules = RuleList( langs=['css', 'scss'], rules=cast(Rule, [ {'pattern': r'calc$[^+]+\+[^+]+$', 'description': "Avoid using calc with '+' operator. See #8403 : in CSS.", 'good_lines': ["width: calc(20% - -14px);"], 'bad_lines': ["width: calc(20% + 14px);"]}, {'pattern': r'^[^:]*:\S[^:]*;$', 'description': "Missing whitespace after : in CSS", 'good_lines': ["background-color: white;", "text-size: 16px;"], 'bad_lines': ["background-color:white;", "text-size:16px;"]}, {'pattern': '[a-z]{', 'description': "Missing whitespace before '{' in CSS.", 'good_lines': ["input {", "body {"], 'bad_lines': ["input{", "body{"]}, {'pattern': 'https://', 'description': "Zulip CSS should have no dependencies on external resources", 'good_lines': ['background: url(/static/images/landing-page/pycon.jpg);'], 'bad_lines': ['background: url(https://example.com/image.png);']}, {'pattern': '^[ ][ ][a-zA-Z0-9]', 'description': "Incorrect 2-space indentation in CSS", 'strip': '\n', 'good_lines': [" color: white;", "color: white;"], 'bad_lines': [" color: white;"]}, {'pattern': r'{\w', 'description': "Missing whitespace after '{' in CSS (should be newline).", 'good_lines': ["{\n"], 'bad_lines': ["{color: LightGoldenRodYellow;"]}, {'pattern': ' thin[ ;]', 'description': "thin CSS attribute is under-specified, please use 1px.", 'good_lines': ["border-width: 1px;"], 'bad_lines': ["border-width: thin;", "border-width: thin solid black;"]}, {'pattern': ' medium[ ;]', 'description': "medium CSS attribute is under-specified, please use pixels.", 'good_lines': ["border-width: 3px;"], 'bad_lines': ["border-width: medium;", "border: medium solid black;"]}, {'pattern': ' thick[ ;]', 'description': "thick CSS attribute is under-specified, please use pixels.", 'good_lines': ["border-width: 5px;"], 'bad_lines': ["border-width: thick;", "border: thick solid black;"]}, {'pattern': r'rgba?\(', 'description': 'Use of rgb(a) format is banned, Please use hsl(a) instead', 'good_lines': ['hsl(0, 0%, 0%)', 'hsla(0, 0%, 100%, 0.1)'], 'bad_lines': ['rgb(0, 0, 0)', 'rgba(255, 255, 255, 0.1)']}, ]) + whitespace_rules + comma_whitespace_rule ) prose_style_rules = cast(Rule, [ {'pattern': r'[^\/\#\-"]([jJ]avascript)', # exclude usage in hrefs/divs 'exclude': set(["docs/documentation/api.md"]), 'description': "javascript should be spelled JavaScript"}, {'pattern': r'''[^\/\-\."'\_\=\>]([gG]ithub)[^\.\-\_"\<]''', # exclude usage in hrefs/divs 'description': "github should be spelled GitHub"}, {'pattern': '[oO]rganisation', # exclude usage in hrefs/divs 'description': "Organization is spelled with a z", 'exclude_line': [('docs/translating/french.md', '* organization - **organisation**')]}, {'pattern': '!!! warning', 'description': "!!! warning is invalid; it's spelled '!!! warn'"}, {'pattern': 'Terms of service', 'description': "The S in Terms of Service is capitalized"}, {'pattern': '[^-_]botserver(?!rc)|bot server', 'description': "Use Botserver instead of botserver or bot server."}, ]) + comma_whitespace_rule html_rules = whitespace_rules + prose_style_rules + cast(Rule, [ {'pattern': 'subject|SUBJECT', 'exclude': set(['templates/zerver/email.html']), 'exclude_pattern': 'email subject', 'description': 'avoid subject in templates', 'good_lines': ['topic_name'], 'bad_lines': ['subject="foo"', ' MAX_SUBJECT_LEN']}, {'pattern': r'placeholder="[^{#](?:(?!\.com).)+$', 'description': "`placeholder` value should be translatable.", 'exclude_line': [('templates/zerver/register.html', 'placeholder="acme"'), ('templates/zerver/register.html', 'placeholder="Acme or Aκμή"')], 'exclude': set(["templates/analytics/support.html"]), 'good_lines': ['<input class="stream-list-filter" type="text" placeholder="{{ _(\'Search streams\') }}" />'], 'bad_lines': ['<input placeholder="foo">']}, {'pattern': "placeholder='[^{]", 'description': "`placeholder` value should be translatable.", 'good_lines': ['<input class="stream-list-filter" type="text" placeholder="{{ _(\'Search streams\') }}" />'], 'bad_lines': ["<input placeholder='foo'>"]}, {'pattern': "aria-label='[^{]", 'description': "`aria-label` value should be translatable.", 'good_lines': ['<button type="button" class="close close-alert-word-status" aria-label="{{t \'Close\' }}">'], 'bad_lines': ["<button aria-label='foo'></button>"]}, {'pattern': 'aria-label="[^{]', 'description': "`aria-label` value should be translatable.", 'good_lines': ['<button type="button" class="close close-alert-word-status" aria-label="{{t \'Close\' }}">'], 'bad_lines': ['<button aria-label="foo"></button>']}, {'pattern': 'script src="http', 'description': "Don't directly load dependencies from CDNs. See docs/subsystems/front-end-build-process.md", 'exclude': set(["templates/corporate/billing.html", "templates/zerver/hello.html", "templates/corporate/upgrade.html"]), 'good_lines': ["{{ render_bundle('landing-page') }}"], 'bad_lines': ['<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>']}, {'pattern': "title='[^{]", 'description': "`title` value should be translatable.", 'good_lines': ['<link rel="author" title="{{ _(\'About these documents\') }}" />'], 'bad_lines': ["<p title='foo'></p>"]}, {'pattern': r'title="[^{\:]', 'exclude_line': set([ ('templates/zerver/app/markdown_help.html', '<td class="rendered_markdown"><img alt=":heart:" class="emoji" src="/static/generated/emoji/images/emoji/heart.png" title=":heart:" /></td>') ]), 'exclude': set(["templates/zerver/emails", "templates/analytics/support.html"]), 'description': "`title` value should be translatable."}, {'pattern': r'''\Walt=["'][^{"']''', 'description': "alt argument should be enclosed by _() or it should be an empty string.", 'exclude': set(['static/templates/settings/display_settings.hbs', 'templates/zerver/app/keyboard_shortcuts.html', 'templates/zerver/app/markdown_help.html']), 'good_lines': ['<img src="{{source_url}}" alt="{{ _(name) }}" />', '<img alg="" />'], 'bad_lines': ['<img alt="Foo Image" />']}, {'pattern': r'''\Walt=["']{{ ?["']''', 'description': "alt argument should be enclosed by _().", 'good_lines': ['<img src="{{source_url}}" alt="{{ _(name) }}" />'], 'bad_lines': ['<img alt="{{ " />']}, {'pattern': r'\bon\w+ ?=', 'description': "Don't use inline event handlers (onclick=, etc. attributes) in HTML. Instead," "attach a jQuery event handler ($('#foo').on('click', function () {...})) when " "the DOM is ready (inside a $(function () {...}) block).", 'exclude': set(['templates/zerver/dev_login.html', 'templates/corporate/upgrade.html']), 'good_lines': ["($('#foo').on('click', function () {}"], 'bad_lines': ["<button id='foo' onclick='myFunction()'>Foo</button>", "<input onchange='myFunction()'>"]}, {'pattern': 'style ?=', 'description': "Avoid using the `style=` attribute; we prefer styling in CSS files", 'exclude_pattern': r'.*style ?=["' + "'" + '](display: ?none|background: {{|color: {{|background-color: {{).*', 'exclude': set([ # KaTeX output uses style attribute 'templates/zerver/app/markdown_help.html', # 5xx page doesn't have external CSS 'static/html/5xx.html', # Group PMs color is dynamically calculated 'static/templates/group_pms.hbs', # exclude_pattern above handles color, but have other issues: 'static/templates/draft.hbs', 'static/templates/subscription.hbs', 'static/templates/single_message.hbs', # Old-style email templates need to use inline style # attributes; it should be possible to clean these up # when we convert these templates to use premailer. 'templates/zerver/emails/email_base_messages.html', # Email log templates; should clean up. 'templates/zerver/email.html', 'templates/zerver/email_log.html', # Probably just needs to be changed to display: none so the exclude works 'templates/zerver/app/navbar.html', # Needs the width cleaned up; display: none is fine 'static/templates/settings/account_settings.hbs', # background image property is dynamically generated 'static/templates/user_profile_modal.hbs', 'static/templates/sidebar_private_message_list.hbs', # Inline styling for an svg; could be moved to CSS files? 'templates/zerver/landing_nav.html', 'templates/zerver/billing_nav.html', 'templates/zerver/app/home.html', 'templates/zerver/features.html', 'templates/zerver/portico-header.html', 'templates/corporate/billing.html', 'templates/corporate/upgrade.html', # Miscellaneous violations to be cleaned up 'static/templates/user_info_popover_title.hbs', 'static/templates/subscription_invites_warning_modal.hbs', 'templates/zerver/reset_confirm.html', 'templates/zerver/config_error.html', 'templates/zerver/dev_env_email_access_details.html', 'templates/zerver/confirm_continue_registration.html', 'templates/zerver/register.html', 'templates/zerver/accounts_send_confirm.html', 'templates/zerver/integrations/index.html', 'templates/zerver/documentation_main.html', 'templates/analytics/realm_summary_table.html', 'templates/corporate/zephyr.html', 'templates/corporate/zephyr-mirror.html', ]), 'good_lines': ['#my-style {color: blue;}', 'style="display: none"', "style='display: none"], 'bad_lines': ['<p style="color: blue;">Foo</p>', 'style = "color: blue;"']}, ]) handlebars_rules = RuleList( langs=['hbs'], rules=html_rules + cast(Rule, [ {'pattern': "[<]script", 'description': "Do not use inline <script> tags here; put JavaScript in static/js instead."}, {'pattern': '{{ t ("|\')', 'description': 'There should be no spaces before the "t" in a translation tag.'}, {'pattern': r"{{t '.*' }}[\.\?!]", 'description': "Period should be part of the translatable string."}, {'pattern': r'{{t ".*" }}[\.\?!]', 'description': "Period should be part of the translatable string."}, {'pattern': r"{{/tr}}[\.\?!]", 'description': "Period should be part of the translatable string."}, {'pattern': '{{t ("|\') ', 'description': 'Translatable strings should not have leading spaces.'}, {'pattern': "{{t '[^']+ ' }}", 'description': 'Translatable strings should not have trailing spaces.'}, {'pattern': '{{t "[^"]+ " }}', 'description': 'Translatable strings should not have trailing spaces.'}, ]), ) jinja2_rules = RuleList( langs=['html'], rules=html_rules + cast(Rule, [ {'pattern': r"{% endtrans %}[\.\?!]", 'description': "Period should be part of the translatable string."}, {'pattern': r"{{ _(.+) }}[\.\?!]", 'description': "Period should be part of the translatable string."}, ]), ) json_rules = RuleList( langs=['json'], rules=cast(Rule, [ # Here, we don't use `whitespace_rules`, because the tab-based # whitespace rule flags a lot of third-party JSON fixtures # under zerver/webhooks that we want preserved verbatim. So # we just include the trailing whitespace rule and a modified # version of the tab-based whitespace rule (we can't just use # exclude in whitespace_rules, since we only want to ignore # JSON files with tab-based whitespace, not webhook code). trailing_whitespace_rule, {'pattern': '\t', 'strip': '\n', 'exclude': set(['zerver/webhooks/']), 'description': 'Fix tab-based whitespace'}, {'pattern': r'":["\[\{]', 'exclude': set(['zerver/webhooks/', 'zerver/tests/fixtures/']), 'description': 'Require space after : in JSON'}, ]) ) markdown_docs_length_exclude = { # Has some example Vagrant output that's very long "docs/development/setup-vagrant.md", # Have wide output in code blocks "docs/subsystems/logging.md", "docs/subsystems/migration-renumbering.md", # Have curl commands with JSON that would be messy to wrap "zerver/webhooks/helloworld/doc.md", "zerver/webhooks/trello/doc.md", # Has a very long configuration line "templates/zerver/integrations/perforce.md", # Has some example code that could perhaps be wrapped "templates/zerver/api/incoming-webhooks-walkthrough.md", # This macro has a long indented URL "templates/zerver/help/include/git-webhook-url-with-branches-indented.md", # These two are the same file and have some too-long lines for GitHub badges "README.md", "docs/overview/readme.md", } markdown_rules = RuleList( langs=['md'], rules=markdown_whitespace_rules + prose_style_rules + cast(Rule, [ {'pattern': r'\[(?P<url>[^\]]+)\]$(?P=url)$', 'description': 'Linkified markdown URLs should use cleaner <http://example.com> syntax.'}, {'pattern': 'https://zulip.readthedocs.io/en/latest/[a-zA-Z0-9]', 'exclude': ['docs/overview/contributing.md', 'docs/overview/readme.md', 'docs/README.md'], 'include_only': set(['docs/']), 'description': "Use relative links (../foo/bar.html) to other documents in docs/", }, {'pattern': "su zulip -c [^']", 'include_only': set(['docs/']), 'description': "Always quote arguments using `su zulip -c '` to avoid confusion about how su works.", }, {'pattern': r'\][(][^#h]', 'include_only': set(['README.md', 'CONTRIBUTING.md']), 'description': "Use absolute links from docs served by GitHub", }, ]), max_length=120, length_exclude=markdown_docs_length_exclude, exclude_files_in='templates/zerver/help/' ) help_markdown_rules = RuleList( langs=['md'], rules=markdown_rules.rules + cast(Rule, [ {'pattern': '[a-z][.][A-Z]', 'description': "Likely missing space after end of sentence", 'include_only': set(['templates/zerver/help/']), }, {'pattern': r'\b[rR]ealm[s]?\b', 'include_only': set(['templates/zerver/help/']), 'good_lines': ['Organization', 'deactivate_realm', 'realm_filter'], 'bad_lines': ['Users are in a realm', 'Realm is the best model'], 'description': "Realms are referred to as Organizations in user-facing docs."}, ]), length_exclude=markdown_docs_length_exclude, ) txt_rules = RuleList( langs=['txt', 'text', 'yaml', 'rst'], rules=whitespace_rules, ) non_py_rules = [ handlebars_rules, jinja2_rules, css_rules, js_rules, json_rules, markdown_rules, help_markdown_rules, bash_rules, txt_rules, ]

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from __future__ import print_function from __future__ import absolute_import from zulint.custom_rules import RuleList from typing import cast, Any, Dict, List, Tuple Rule = List[Dict[str, Any]] LineTup = Tuple[int, str, str, str] PYDELIMS = r'''"'()\[\]{}#\\''' PYREG = r"[^{}]".format(PYDELIMS) PYSQ = r'"(?:[^"\\]|\\.)*"' PYDQ = r"'(?:[^'\\]|\\.)*'" PYLEFT = r"[(\[{]" PYRIGHT = r"[)\]}]" PYCODE = PYREG for depth in range(5): PYGROUP = r"""(?:{}|{}|{}{}*{})""".format(PYSQ, PYDQ, PYLEFT, PYCODE, PYRIGHT) PYCODE = r"""(?:{}|{})""".format(PYREG, PYGROUP) FILES_WITH_LEGACY_SUBJECT = { 'zerver/lib/topic.py', 'zerver/tests/test_legacy_subject.py', 'zerver/lib/fix_unreads.py', 'zerver/tests/test_migrations.py', 'zerver/lib/email_mirror.py', 'zerver/lib/feedback.py', 'zerver/tests/test_new_users.py', 'zerver/tests/test_email_mirror.py', 'zerver/openapi/python_examples.py', 'zerver/tests/test_openapi.py', # to fix everything until we migrate the DB to "topic". 'zerver/tests/test_narrow.py', } shebang_rules = [ {'pattern': '^ 'description': "zerver library code shouldn't have a shebang line.", 'include_only': set(['zerver/'])}, {'pattern': '^#!(?! *(?:/usr/bin/env|/bin/sh)(?: |$))', 'description': "Use `#!/usr/bin/env foo` instead of `#!/path/foo`" " for interpreters other than sh."}, {'pattern': '^#!/usr/bin/env python$', 'description': "Use `#!/usr/bin/env python3` instead of `#!/usr/bin/env python`."} ] trailing_whitespace_rule = { 'pattern': r'\s+$', 'strip': '\n', 'description': 'Fix trailing whitespace' } whitespace_rules = [ trailing_whitespace_rule, {'pattern': 'http://zulip.readthedocs.io', 'description': 'Use HTTPS when linking to ReadTheDocs', }, {'pattern': '\t', 'strip': '\n', 'exclude': set(['tools/ci/success-http-headers.txt']), 'description': 'Fix tab-based whitespace'}, ] comma_whitespace_rule = [ {'pattern': ', {2,}[^#/ ]', 'exclude': set(['zerver/tests', 'frontend_tests/node_tests', 'corporate/tests']), 'description': "Remove multiple whitespaces after ','", 'good_lines': ['foo(1, 2, 3)', 'foo = bar # some inline comment'], 'bad_lines': ['foo(1, 2, 3)', 'foo(1, 2, 3)']}, ] markdown_whitespace_rules = list([rule for rule in whitespace_rules if rule['pattern'] != r'\s+$']) + [ # This rule finds one space trailing a non-space, three or more trailing spaces, and # spaces on an empty line. {'pattern': r'((?<!\s)\s$)|(\s\s\s+$)|(^\s+$)', 'strip': '\n', 'description': 'Fix trailing whitespace'}, {'pattern': '^ 'strip': '\n', 'description': 'Missing space after 'good_lines': [' 'frontend_tests/']), 'exclude_pattern': 'emails', 'description': 'avoid subject in JS code', 'good_lines': ['topic_name'], 'bad_lines': ['subject="foo"', ' MAX_SUBJECT_LEN']}, {'pattern': r'[^_]function$', 'description': 'The keyword "function" should be followed by a space'}, {'pattern': r'.*blueslip.warning\(.*', 'description': 'The module blueslip has no function warning, try using blueslip.warn'}, {'pattern': '[)]{$', 'description': 'Missing space between ) and {'}, {'pattern': r'i18n\.t\([^)]+[^,\{$]$', 'description': 'i18n string should not be a multiline string'}, {'pattern': r'''i18n\.t$['"].+?['"]\s*\+''', 'description': 'Do not concatenate arguments within i18n.t()'}, {'pattern': r'i18n\.t\(.+$.*\+', 'description': 'Do not concatenate i18n strings'}, {'pattern': r'\+.*i18n\.t$.+$', 'description': 'Do not concatenate i18n strings'}, {'pattern': '[.]includes[(]', 'exclude': ['frontend_tests/'], 'description': '.includes() is incompatible with Internet Explorer. Use .indexOf() !== -1 instead.'}, {'pattern': '[.]html[(]', 'exclude_pattern': r'''[.]html[(]("|'|render_|html|message.content|sub.rendered_description|i18n.t|rendered_|$|[)]|error_text|widget_elem|[$]error|[$][(]"<p>"[)])''', 'exclude': ['static/js/portico', 'static/js/lightbox.js', 'static/js/ui_report.js', 'static/js/confirm_dialog.js', 'frontend_tests/'], 'description': 'Setting HTML content with jQuery .html() can lead to XSS security bugs. Consider .text() or using rendered_foo as a variable name if content comes from handlebars and thus is already sanitized.'}, {'pattern': '["\']json/', 'description': 'Relative URL for JSON route not supported by i18n'}, # This rule is constructed with + to avoid triggering on itself {'pattern': " =" + '[^ =>~"]', 'description': 'Missing whitespace after "="'}, {'pattern': '^[ ]*//[A-Za-z0-9]', 'description': 'Missing space after // in comment'}, {'pattern': 'if[(]', 'description': 'Missing space between if and ('}, {'pattern': 'else{$', 'description': 'Missing space between else and {'}, {'pattern': '^else {$', 'description': 'Write JS else statements on same line as }'}, {'pattern': '^else if', 'description': 'Write JS else statements on same line as }'}, {'pattern': 'console[.][a-z]', 'exclude': set(['static/js/blueslip.js', 'frontend_tests/zjsunit', 'frontend_tests/casper_lib/common.js', 'frontend_tests/node_tests', 'static/js/debug.js']), 'description': 'console.log and similar should not be used in webapp'}, {'pattern': r'''[.]text$["'][a-zA-Z]''', 'description': 'Strings passed to $().text should be wrapped in i18n.t() for internationalization', 'exclude': set(['frontend_tests/node_tests/'])}, {'pattern': r'''compose_error\(["']''', 'description': 'Argument to compose_error should be a literal string enclosed ' 'by i18n.t()'}, {'pattern': r'ui.report_success\(', 'description': 'Deprecated function, use ui_report.success.'}, {'pattern': r'''report.success\(["']''', 'description': 'Argument to report_success should be a literal string enclosed ' 'by i18n.t()'}, {'pattern': r'ui.report_error\(', 'description': 'Deprecated function, use ui_report.error.'}, {'pattern': r'''report.error\(["'][^'"]''', 'description': 'Argument to ui_report.error should be a literal string enclosed ' 'by i18n.t()', 'good_lines': ['ui_report.error("")', 'ui_report.error(_("text"))'], 'bad_lines': ['ui_report.error("test")']}, {'pattern': r'\$\(document$\.ready\(', 'description': "`Use $(f) rather than `$(document).ready(f)`", 'good_lines': ['$(function () {foo();}'], 'bad_lines': ['$(document).ready(function () {foo();}']}, {'pattern': '[$][.](get|post|patch|delete|ajax)[(]', 'description': "Use channel module for AJAX calls", 'exclude': set([ 'static/js/blueslip.js', 'static/js/channel.js', 'static/js/stats/', 'static/js/portico/', 'static/js/billing/', ]), 'good_lines': ['channel.get(...)'], 'bad_lines': ['$.get()', '$.post()', '$.ajax()']}, {'pattern': 'style ?=', 'description': "Avoid using the `style=` attribute; we prefer styling in CSS files", 'exclude': set([ 'frontend_tests/node_tests/copy_and_paste.js', 'frontend_tests/node_tests/upload.js', 'frontend_tests/node_tests/templates.js', 'static/js/upload.js', 'static/js/stream_color.js', ]), 'good_lines': [' 'bad_lines': ['<p style="color: blue;">Foo</p>', 'style = "color: blue;"']}, ]) + whitespace_rules + comma_whitespace_rule, ) python_rules = RuleList( langs=['py'], rules=cast(Rule, [ {'pattern': 'subject|SUBJECT', 'exclude_pattern': 'subject to the|email|outbox', 'description': 'avoid subject as a var', 'good_lines': ['topic_name'], 'bad_lines': ['subject="foo"', ' MAX_SUBJECT_LEN'], 'exclude': FILES_WITH_LEGACY_SUBJECT, 'include_only': set([ 'zerver/data_import/', 'zerver/lib/', 'zerver/tests/', 'zerver/views/'])}, {'pattern': '^(?! 'description': '@login_required is unsupported; use @zulip_login_required', 'good_lines': ['@zulip_login_required', ' 'bad_lines': ['@login_required', ' @login_required']}, {'pattern': '^user_profile[.]save[(][)]', 'description': 'Always pass update_fields when saving user_profile objects', 'exclude_line': set([ ('zerver/lib/actions.py', "user_profile.save() # Can't use update_fields because of how the foreign key works."), ]), 'exclude': set(['zerver/tests', 'zerver/lib/create_user.py']), 'good_lines': ['user_profile.save(update_fields=["pointer"])'], 'bad_lines': ['user_profile.save()']}, {'pattern': r'^[^"]*"[^"]*"%\(', 'description': 'Missing space around "%"', 'good_lines': ['"%s" % ("foo")', '"%s" % (foo)'], 'bad_lines': ['"%s"%("foo")', '"%s"%(foo)']}, {'pattern': r"^[^']*'[^']*'%\(", 'description': 'Missing space around "%"', 'good_lines': ["'%s' % ('foo')", "'%s' % (foo)"], 'bad_lines': ["'%s'%('foo')", "'%s'%(foo)"]}, {'pattern': 'self: Any', 'description': 'you can omit Any annotation for self', 'good_lines': ['def foo (self):'], 'bad_lines': ['def foo(self: Any):']}, {'pattern': " =" + '[^ =>~"]', 'description': 'Missing whitespace after "="', 'good_lines': ['a = b', '5 == 6'], 'bad_lines': ['a =b', 'asdf =42']}, {'pattern': r'":\w[^"]*$', 'description': 'Missing whitespace after ":"', 'good_lines': ['"foo": bar', '"some:string:with:colons"'], 'bad_lines': ['"foo":bar', '"foo":1']}, {'pattern': r"':\w[^']*$", 'description': 'Missing whitespace after ":"', 'good_lines': ["'foo': bar", "'some:string:with:colons'"], 'bad_lines': ["'foo':bar", "'foo':1"]}, {'pattern': r"^\s+ 'strip': '\n', 'exclude': set(['tools/droplets/create.py']), 'description': 'Missing whitespace after "#"', 'good_lines': ['a = b # some operation', '1+2 # 3 is the result'], 'bad_lines': [' #some operation', ' #not valid!!!']}, {'pattern': "assertEquals[(]", 'description': 'Use assertEqual, not assertEquals (which is deprecated).', 'good_lines': ['assertEqual(1, 2)'], 'bad_lines': ['assertEquals(1, 2)']}, {'pattern': "== None", 'description': 'Use `is None` to check whether something is None', 'good_lines': ['if foo is None'], 'bad_lines': ['foo == None']}, {'pattern': "type:[(]", 'description': 'Missing whitespace after ":" in type annotation', 'good_lines': ['# type: (Any, Any)', 'colon:separated:string:containing:type:as:keyword'], 'bad_lines': ['# type:(Any, Any)']}, {'pattern': "type: ignore$", 'exclude': set(['tools/tests', 'zerver/lib/test_runner.py', 'zerver/tests']), 'description': '"type: ignore" should always end with "# type: ignore # explanation for why"', 'good_lines': ['foo = bar # type: ignore # explanation'], 'bad_lines': ['foo = bar # type: ignore']}, {'pattern': " 'description': 'Missing : after type in type annotation', 'good_lines': ['foo = 42 # type: int', '# type: (str, int) -> None'], 'bad_lines': ['# type (str, int) -> None']}, {'pattern': " 'description': 'Missing whitespace after "#" in type annotation', 'good_lines': ['foo = 42 # type: int'], 'bad_lines': ['foo = 42 #type: int']}, {'pattern': r'\b(if|else|while)[(]', 'description': 'Put a space between statements like if, else, etc. and (.', 'good_lines': ['if (1 == 2):', 'while (foo == bar):'], 'bad_lines': ['if(1 == 2):', 'while(foo == bar):']}, {'pattern': ", [)]", 'description': 'Unnecessary whitespace between "," and ")"', 'good_lines': ['foo = (1, 2, 3,)', 'foo(bar, 42)'], 'bad_lines': ['foo = (1, 2, 3, )']}, {'pattern': "% [(]", 'description': 'Unnecessary whitespace between "%" and "("', 'good_lines': ['"foo %s bar" % ("baz",)'], 'bad_lines': ['"foo %s bar" % ("baz",)']}, # This next check could have false positives, but it seems pretty # rare; if we find any, they can be added to the exclude list for # this rule. {'pattern': r"""^(?:[^'"#\\]|{}|{})*(?:{}|{})\s*%\s*(?![\s({{\\]|dict$|tuple\()(?:[^,{}]|{})+(?:$|[,#\\]|{})""".format( PYSQ, PYDQ, PYSQ, PYDQ, PYDELIMS, PYGROUP, PYRIGHT), 'description': 'Used % formatting without a tuple', 'good_lines': ['"foo %s bar" % ("baz",)'], 'bad_lines': ['"foo %s bar" % "baz"']}, {'pattern': r"""^(?:[^'"#\\]|{}|{})*(?:{}|{})\s*%\s*\((?:[^,{}]|{})*$""".format( PYSQ, PYDQ, PYSQ, PYDQ, PYDELIMS, PYGROUP), 'description': 'Used % formatting with parentheses that do not form a tuple', 'good_lines': ['"foo %s bar" % ("baz",)"'], 'bad_lines': ['"foo %s bar" % ("baz")']}, {'pattern': 'sudo', 'include_only': set(['scripts/']), 'exclude': set(['scripts/lib/setup_venv.py']), 'exclude_line': set([ ('scripts/lib/zulip_tools.py', 'sudo_args = kwargs.pop(\'sudo_args\', [])'), ('scripts/lib/zulip_tools.py', 'args = [\'sudo\'] + sudo_args + [\'--\'] + args'), ]), 'description': 'Most scripts are intended to run on systems without sudo.', 'good_lines': ['subprocess.check_call(["ls"])'], 'bad_lines': ['subprocess.check_call(["sudo", "ls"])']}, {'pattern': 'django.utils.translation', 'include_only': set(['test/', 'zerver/views/development/']), 'description': 'Test strings should not be tagged for translation', 'good_lines': [''], 'bad_lines': ['django.utils.translation']}, {'pattern': 'userid', 'description': 'We prefer user_id over userid.', 'good_lines': ['id = alice.user_id'], 'bad_lines': ['id = alice.userid']}, {'pattern': r'json_success${}$', 'description': 'Use json_success() to return nothing', 'good_lines': ['return json_success()'], 'bad_lines': ['return json_success({})']}, {'pattern': r'\Wjson_error$_\(?\w+$', 'exclude': set(['zerver/tests', 'zerver/views/development/']), 'description': 'Argument to json_error should be a literal string enclosed by _()', 'good_lines': ['return json_error(_("string"))'], 'bad_lines': ['return json_error(_variable)', 'return json_error(_(variable))']}, {'pattern': r'''\Wjson_error$['"].+[),]$''', 'exclude': set(['zerver/tests']), 'description': 'Argument to json_error should a literal string enclosed by _()'}, # To avoid JsonableError(_variable) and JsonableError(_(variable)) {'pattern': r'\WJsonableError\(_\(?\w.+$', 'exclude': set(['zerver/tests', 'zerver/views/development/']), 'description': 'Argument to JsonableError should be a literal string enclosed by _()'}, {'pattern': r'''\WJsonableError$["'].+$''', 'exclude': set(['zerver/tests', 'zerver/views/development/']), 'description': 'Argument to JsonableError should be a literal string enclosed by _()'}, {'pattern': r"""\b_\((?:\s|{}|{})*[^\s'")]""".format(PYSQ, PYDQ), 'description': 'Called _() on a computed string', 'exclude_line': set([ ('zerver/lib/i18n.py', 'result = _(string)'), ]), 'good_lines': ["return json_error(_('No presence data for %s') % (target.email,))"], 'bad_lines': ["return json_error(_('No presence data for %s' % (target.email,)))"]}, {'pattern': r'''([a-zA-Z0-9_]+)=REQ\(['"]\1['"]''', 'description': 'REQ\'s first argument already defaults to parameter name'}, {'pattern': r'self\.client\.(get|post|patch|put|delete)', 'description': \ '''Do not call self.client directly for put/patch/post/get. See WRAPPER_COMMENT in test_helpers.py for details. '''}, # Directly fetching Message objects in e.g. views code is often a security bug. {'pattern': '[^r]Message.objects.get', 'exclude': set(["zerver/tests", "zerver/lib/onboarding.py", "zilencer/management/commands/add_mock_conversation.py", "zerver/worker/queue_processors.py", "zerver/management/commands/export.py", "zerver/lib/export.py"]), 'description': 'Please use access_message() to fetch Message objects', }, {'pattern': 'Stream.objects.get', 'include_only': set(["zerver/views/"]), 'description': 'Please use access_stream_by_*() to fetch Stream objects', }, {'pattern': 'get_stream[(]', 'include_only': set(["zerver/views/", "zerver/lib/actions.py"]), 'exclude_line': set([ # This one in check_message is kinda terrible, since it's # how most instances are written, but better to exclude something than nothing ('zerver/lib/actions.py', 'stream = get_stream(stream_name, realm)'), ('zerver/lib/actions.py', 'get_stream(admin_realm_signup_notifications_stream, admin_realm)'), # Here we need get_stream to access streams you've since unsubscribed from. ('zerver/views/messages.py', 'stream = get_stream(operand, self.user_profile.realm)'), # Use stream_id to exclude mutes. ('zerver/views/messages.py', 'stream_id = get_stream(stream_name, user_profile.realm).id'), ]), 'description': 'Please use access_stream_by_*() to fetch Stream objects', }, {'pattern': 'Stream.objects.filter', 'include_only': set(["zerver/views/"]), 'description': 'Please use access_stream_by_*() to fetch Stream objects', }, {'pattern': '^from (zerver|analytics|confirmation)', 'include_only': set(["/migrations/"]), 'exclude': set([ 'zerver/migrations/0032_verify_all_medium_avatar_images.py', 'zerver/migrations/0060_move_avatars_to_be_uid_based.py', 'zerver/migrations/0104_fix_unreads.py', 'zerver/migrations/0206_stream_rendered_description.py', 'pgroonga/migrations/0002_html_escape_subject.py', ]), 'description': "Don't import models or other code in migrations; see docs/subsystems/schema-migrations.md", }, {'pattern': 'datetime[.](now|utcnow)', 'include_only': set(["zerver/", "analytics/"]), 'description': "Don't use datetime in backend code.\n" "See https://zulip.readthedocs.io/en/latest/contributing/code-style.html }, {'pattern': r'render_to_response\(', 'description': "Use render() instead of render_to_response().", }, {'pattern': 'from os.path', 'description': "Don't use from when importing from the standard library", }, {'pattern': 'import os.path', 'description': "Use import os instead of import os.path", }, {'pattern': r'(logging|logger)\.warn\W', 'description': "Logger.warn is a deprecated alias for Logger.warning; Use 'warning' instead of 'warn'.", 'good_lines': ["logging.warning('I am a warning.')", "logger.warning('warning')"], 'bad_lines': ["logging.warn('I am a warning.')", "logger.warn('warning')"]}, {'pattern': r'\.pk', 'exclude_pattern': '[.]_meta[.]pk', 'description': "Use `id` instead of `pk`.", 'good_lines': ['if my_django_model.id == 42', 'self.user_profile._meta.pk'], 'bad_lines': ['if my_django_model.pk == 42']}, {'pattern': r'^[ ]*# type: $', 'exclude': set([ # These directories, especially scripts/ and puppet/, # have tools that need to run before a Zulip environment # is provisioned; in some of those, the `typing` module # might not be available yet, so care is required. 'scripts/', 'tools/', 'puppet/', # Zerver files that we should just clean. 'zerver/tests', 'zerver/openapi/python_examples.py', 'zerver/lib/request.py', 'zerver/views/streams.py', # thumbor is (currently) python2 only 'zthumbor/', ]), 'description': 'Comment-style function type annotation. Use Python3 style annotations instead.', }, {'pattern': r' = models[.].*null=True.*$ # type: (?!Optional)', 'include_only': {"zerver/models.py"}, 'description': 'Model variable with null=true not annotated as Optional.', 'good_lines': ['desc = models.TextField(null=True) # type: Optional[Text]', 'stream = models.ForeignKey(Stream, null=True, on_delete=CASCADE) # type: Optional[Stream]', 'desc = models.TextField() # type: Text', 'stream = models.ForeignKey(Stream, on_delete=CASCADE) # type: Stream'], 'bad_lines': ['desc = models.CharField(null=True) # type: Text', 'stream = models.ForeignKey(Stream, null=True, on_delete=CASCADE) # type: Stream'], }, {'pattern': r' = models[.](?!NullBoolean).*\) # type: Optional', # Optional tag, except NullBoolean(Field) 'exclude_pattern': 'null=True', 'include_only': {"zerver/models.py"}, 'description': 'Model variable annotated with Optional but variable does not have null=true.', 'good_lines': ['desc = models.TextField(null=True) # type: Optional[Text]', 'stream = models.ForeignKey(Stream, null=True, on_delete=CASCADE) # type: Optional[Stream]', 'desc = models.TextField() # type: Text', 'stream = models.ForeignKey(Stream, on_delete=CASCADE) # type: Stream'], 'bad_lines': ['desc = models.TextField() # type: Optional[Text]', 'stream = models.ForeignKey(Stream, on_delete=CASCADE) # type: Optional[Stream]'], }, {'pattern': r'[\s([]Text([^\s\w]|$)', 'exclude': set([ # We are likely to want to keep these dirs Python 2+3 compatible, # since the plan includes extracting them to a separate project eventually. 'tools/lib', # TODO: Update our migrations from Text->str. 'zerver/migrations/', # thumbor is (currently) python2 only 'zthumbor/', ]), 'description': "Now that we're a Python 3 only codebase, we don't need to use typing.Text. Please use str instead.", }, {'pattern': 'exit[(]1[)]', 'include_only': set(["/management/commands/"]), 'description': 'Raise CommandError to exit with failure in management commands', }, ]) + whitespace_rules + comma_whitespace_rule, max_length=110, shebang_rules=shebang_rules, ) bash_rules = RuleList( langs=['bash'], rules=cast(Rule, [ {'pattern': '#!.*sh [-xe]', 'description': 'Fix shebang line with proper call to /usr/bin/env for Bash path, change -x|-e switches' ' to set -x|set -e'}, {'pattern': 'sudo', 'description': 'Most scripts are intended to work on systems without sudo', 'include_only': set(['scripts/']), 'exclude': set([ 'scripts/lib/install', 'scripts/setup/configure-rabbitmq' ]), }, ]) + whitespace_rules[0:1], shebang_rules=shebang_rules, ) css_rules = RuleList( langs=['css', 'scss'], rules=cast(Rule, [ {'pattern': r'calc$[^+]+\+[^+]+$', 'description': "Avoid using calc with '+' operator. See #8403 : in CSS.", 'good_lines': ["width: calc(20% - -14px);"], 'bad_lines': ["width: calc(20% + 14px);"]}, {'pattern': r'^[^:]*:\S[^:]*;$', 'description': "Missing whitespace after : in CSS", 'good_lines': ["background-color: white;", "text-size: 16px;"], 'bad_lines': ["background-color:white;", "text-size:16px;"]}, {'pattern': '[a-z]{', 'description': "Missing whitespace before '{' in CSS.", 'good_lines': ["input {", "body {"], 'bad_lines': ["input{", "body{"]}, {'pattern': 'https://', 'description': "Zulip CSS should have no dependencies on external resources", 'good_lines': ['background: url(/static/images/landing-page/pycon.jpg);'], 'bad_lines': ['background: url(https://example.com/image.png);']}, {'pattern': '^[ ][ ][a-zA-Z0-9]', 'description': "Incorrect 2-space indentation in CSS", 'strip': '\n', 'good_lines': [" color: white;", "color: white;"], 'bad_lines': [" color: white;"]}, {'pattern': r'{\w', 'description': "Missing whitespace after '{' in CSS (should be newline).", 'good_lines': ["{\n"], 'bad_lines': ["{color: LightGoldenRodYellow;"]}, {'pattern': ' thin[ ;]', 'description': "thin CSS attribute is under-specified, please use 1px.", 'good_lines': ["border-width: 1px;"], 'bad_lines': ["border-width: thin;", "border-width: thin solid black;"]}, {'pattern': ' medium[ ;]', 'description': "medium CSS attribute is under-specified, please use pixels.", 'good_lines': ["border-width: 3px;"], 'bad_lines': ["border-width: medium;", "border: medium solid black;"]}, {'pattern': ' thick[ ;]', 'description': "thick CSS attribute is under-specified, please use pixels.", 'good_lines': ["border-width: 5px;"], 'bad_lines': ["border-width: thick;", "border: thick solid black;"]}, {'pattern': r'rgba?\(', 'description': 'Use of rgb(a) format is banned, Please use hsl(a) instead', 'good_lines': ['hsl(0, 0%, 0%)', 'hsla(0, 0%, 100%, 0.1)'], 'bad_lines': ['rgb(0, 0, 0)', 'rgba(255, 255, 255, 0.1)']}, ]) + whitespace_rules + comma_whitespace_rule ) prose_style_rules = cast(Rule, [ {'pattern': r'[^\/\#\-"]([jJ]avascript)', # exclude usage in hrefs/divs 'exclude': set(["docs/documentation/api.md"]), 'description': "javascript should be spelled JavaScript"}, {'pattern': r'''[^\/\-\."'\_\=\>]([gG]ithub)[^\.\-\_"\<]''', 'description': "github should be spelled GitHub"}, {'pattern': '[oO]rganisation', 'description': "Organization is spelled with a z", 'exclude_line': [('docs/translating/french.md', '* organization - **organisation**')]}, {'pattern': '!!! warning', 'description': "!!! warning is invalid; it's spelled '!!! warn'"}, {'pattern': 'Terms of service', 'description': "The S in Terms of Service is capitalized"}, {'pattern': '[^-_]botserver(?!rc)|bot server', 'description': "Use Botserver instead of botserver or bot server."}, ]) + comma_whitespace_rule html_rules = whitespace_rules + prose_style_rules + cast(Rule, [ {'pattern': 'subject|SUBJECT', 'exclude': set(['templates/zerver/email.html']), 'exclude_pattern': 'email subject', 'description': 'avoid subject in templates', 'good_lines': ['topic_name'], 'bad_lines': ['subject="foo"', ' MAX_SUBJECT_LEN']}, {'pattern': r'placeholder="[^{#](?:(?!\.com).)+$', 'description': "`placeholder` value should be translatable.", 'exclude_line': [('templates/zerver/register.html', 'placeholder="acme"'), ('templates/zerver/register.html', 'placeholder="Acme or Aκμή"')], 'exclude': set(["templates/analytics/support.html"]), 'good_lines': ['<input class="stream-list-filter" type="text" placeholder="{{ _(\'Search streams\') }}" />'], 'bad_lines': ['<input placeholder="foo">']}, {'pattern': "placeholder='[^{]", 'description': "`placeholder` value should be translatable.", 'good_lines': ['<input class="stream-list-filter" type="text" placeholder="{{ _(\'Search streams\') }}" />'], 'bad_lines': ["<input placeholder='foo'>"]}, {'pattern': "aria-label='[^{]", 'description': "`aria-label` value should be translatable.", 'good_lines': ['<button type="button" class="close close-alert-word-status" aria-label="{{t \'Close\' }}">'], 'bad_lines': ["<button aria-label='foo'></button>"]}, {'pattern': 'aria-label="[^{]', 'description': "`aria-label` value should be translatable.", 'good_lines': ['<button type="button" class="close close-alert-word-status" aria-label="{{t \'Close\' }}">'], 'bad_lines': ['<button aria-label="foo"></button>']}, {'pattern': 'script src="http', 'description': "Don't directly load dependencies from CDNs. See docs/subsystems/front-end-build-process.md", 'exclude': set(["templates/corporate/billing.html", "templates/zerver/hello.html", "templates/corporate/upgrade.html"]), 'good_lines': ["{{ render_bundle('landing-page') }}"], 'bad_lines': ['<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>']}, {'pattern': "title='[^{]", 'description': "`title` value should be translatable.", 'good_lines': ['<link rel="author" title="{{ _(\'About these documents\') }}" />'], 'bad_lines': ["<p title='foo'></p>"]}, {'pattern': r'title="[^{\:]', 'exclude_line': set([ ('templates/zerver/app/markdown_help.html', '<td class="rendered_markdown"><img alt=":heart:" class="emoji" src="/static/generated/emoji/images/emoji/heart.png" title=":heart:" /></td>') ]), 'exclude': set(["templates/zerver/emails", "templates/analytics/support.html"]), 'description': "`title` value should be translatable."}, {'pattern': r'''\Walt=["'][^{"']''', 'description': "alt argument should be enclosed by _() or it should be an empty string.", 'exclude': set(['static/templates/settings/display_settings.hbs', 'templates/zerver/app/keyboard_shortcuts.html', 'templates/zerver/app/markdown_help.html']), 'good_lines': ['<img src="{{source_url}}" alt="{{ _(name) }}" />', '<img alg="" />'], 'bad_lines': ['<img alt="Foo Image" />']}, {'pattern': r'''\Walt=["']{{ ?["']''', 'description': "alt argument should be enclosed by _().", 'good_lines': ['<img src="{{source_url}}" alt="{{ _(name) }}" />'], 'bad_lines': ['<img alt="{{ " />']}, {'pattern': r'\bon\w+ ?=', 'description': "Don't use inline event handlers (onclick=, etc. attributes) in HTML. Instead," "attach a jQuery event handler ($('#foo').on('click', function () {...})) when " "the DOM is ready (inside a $(function () {...}) block).", 'exclude': set(['templates/zerver/dev_login.html', 'templates/corporate/upgrade.html']), 'good_lines': ["($('#foo').on('click', function () {}"], 'bad_lines': ["<button id='foo' onclick='myFunction()'>Foo</button>", "<input onchange='myFunction()'>"]}, {'pattern': 'style ?=', 'description': "Avoid using the `style=` attribute; we prefer styling in CSS files", 'exclude_pattern': r'.*style ?=["' + "'" + '](display: ?none|background: {{|color: {{|background-color: {{).*', 'exclude': set([ # KaTeX output uses style attribute 'templates/zerver/app/markdown_help.html', # 5xx page doesn't have external CSS 'static/html/5xx.html', # Group PMs color is dynamically calculated 'static/templates/group_pms.hbs', # exclude_pattern above handles color, but have other issues: 'static/templates/draft.hbs', 'static/templates/subscription.hbs', 'static/templates/single_message.hbs', # Old-style email templates need to use inline style # attributes; it should be possible to clean these up # when we convert these templates to use premailer. 'templates/zerver/emails/email_base_messages.html', # Email log templates; should clean up. 'templates/zerver/email.html', 'templates/zerver/email_log.html', # Probably just needs to be changed to display: none so the exclude works 'templates/zerver/app/navbar.html', # Needs the width cleaned up; display: none is fine 'static/templates/settings/account_settings.hbs', # background image property is dynamically generated 'static/templates/user_profile_modal.hbs', 'static/templates/sidebar_private_message_list.hbs', # Inline styling for an svg; could be moved to CSS files? 'templates/zerver/landing_nav.html', 'templates/zerver/billing_nav.html', 'templates/zerver/app/home.html', 'templates/zerver/features.html', 'templates/zerver/portico-header.html', 'templates/corporate/billing.html', 'templates/corporate/upgrade.html', # Miscellaneous violations to be cleaned up 'static/templates/user_info_popover_title.hbs', 'static/templates/subscription_invites_warning_modal.hbs', 'templates/zerver/reset_confirm.html', 'templates/zerver/config_error.html', 'templates/zerver/dev_env_email_access_details.html', 'templates/zerver/confirm_continue_registration.html', 'templates/zerver/register.html', 'templates/zerver/accounts_send_confirm.html', 'templates/zerver/integrations/index.html', 'templates/zerver/documentation_main.html', 'templates/analytics/realm_summary_table.html', 'templates/corporate/zephyr.html', 'templates/corporate/zephyr-mirror.html', ]), 'good_lines': ['#my-style {color: blue;}', 'style="display: none"', "style='display: none"], 'bad_lines': ['<p style="color: blue;">Foo</p>', 'style = "color: blue;"']}, ]) handlebars_rules = RuleList( langs=['hbs'], rules=html_rules + cast(Rule, [ {'pattern': "[<]script", 'description': "Do not use inline <script> tags here; put JavaScript in static/js instead."}, {'pattern': '{{ t ("|\')', 'description': 'There should be no spaces before the "t" in a translation tag.'}, {'pattern': r"{{t '.*' }}[\.\?!]", 'description': "Period should be part of the translatable string."}, {'pattern': r'{{t ".*" }}[\.\?!]', 'description': "Period should be part of the translatable string."}, {'pattern': r"{{/tr}}[\.\?!]", 'description': "Period should be part of the translatable string."}, {'pattern': '{{t ("|\') ', 'description': 'Translatable strings should not have leading spaces.'}, {'pattern': "{{t '[^']+ ' }}", 'description': 'Translatable strings should not have trailing spaces.'}, {'pattern': '{{t "[^"]+ " }}', 'description': 'Translatable strings should not have trailing spaces.'}, ]), ) jinja2_rules = RuleList( langs=['html'], rules=html_rules + cast(Rule, [ {'pattern': r"{% endtrans %}[\.\?!]", 'description': "Period should be part of the translatable string."}, {'pattern': r"{{ _(.+) }}[\.\?!]", 'description': "Period should be part of the translatable string."}, ]), ) json_rules = RuleList( langs=['json'], rules=cast(Rule, [ # whitespace rule flags a lot of third-party JSON fixtures # under zerver/webhooks that we want preserved verbatim. So # we just include the trailing whitespace rule and a modified # version of the tab-based whitespace rule (we can't just use trailing_whitespace_rule, {'pattern': '\t', 'strip': '\n', 'exclude': set(['zerver/webhooks/']), 'description': 'Fix tab-based whitespace'}, {'pattern': r'":["\[\{]', 'exclude': set(['zerver/webhooks/', 'zerver/tests/fixtures/']), 'description': 'Require space after : in JSON'}, ]) ) markdown_docs_length_exclude = { "docs/development/setup-vagrant.md", # Have wide output in code blocks "docs/subsystems/logging.md", "docs/subsystems/migration-renumbering.md", # Have curl commands with JSON that would be messy to wrap "zerver/webhooks/helloworld/doc.md", "zerver/webhooks/trello/doc.md", # Has a very long configuration line "templates/zerver/integrations/perforce.md", # Has some example code that could perhaps be wrapped "templates/zerver/api/incoming-webhooks-walkthrough.md", # This macro has a long indented URL "templates/zerver/help/include/git-webhook-url-with-branches-indented.md", # These two are the same file and have some too-long lines for GitHub badges "README.md", "docs/overview/readme.md", } markdown_rules = RuleList( langs=['md'], rules=markdown_whitespace_rules + prose_style_rules + cast(Rule, [ {'pattern': r'\[(?P<url>[^\]]+)\]$(?P=url)$', 'description': 'Linkified markdown URLs should use cleaner <http://example.com> syntax.'}, {'pattern': 'https://zulip.readthedocs.io/en/latest/[a-zA-Z0-9]', 'exclude': ['docs/overview/contributing.md', 'docs/overview/readme.md', 'docs/README.md'], 'include_only': set(['docs/']), 'description': "Use relative links (../foo/bar.html) to other documents in docs/", }, {'pattern': "su zulip -c [^']", 'include_only': set(['docs/']), 'description': "Always quote arguments using `su zulip -c '` to avoid confusion about how su works.", }, {'pattern': r'\][(][^ 'include_only': set(['README.md', 'CONTRIBUTING.md']), 'description': "Use absolute links from docs served by GitHub", }, ]), max_length=120, length_exclude=markdown_docs_length_exclude, exclude_files_in='templates/zerver/help/' ) help_markdown_rules = RuleList( langs=['md'], rules=markdown_rules.rules + cast(Rule, [ {'pattern': '[a-z][.][A-Z]', 'description': "Likely missing space after end of sentence", 'include_only': set(['templates/zerver/help/']), }, {'pattern': r'\b[rR]ealm[s]?\b', 'include_only': set(['templates/zerver/help/']), 'good_lines': ['Organization', 'deactivate_realm', 'realm_filter'], 'bad_lines': ['Users are in a realm', 'Realm is the best model'], 'description': "Realms are referred to as Organizations in user-facing docs."}, ]), length_exclude=markdown_docs_length_exclude, ) txt_rules = RuleList( langs=['txt', 'text', 'yaml', 'rst'], rules=whitespace_rules, ) non_py_rules = [ handlebars_rules, jinja2_rules, css_rules, js_rules, json_rules, markdown_rules, help_markdown_rules, bash_rules, txt_rules, ]

true

1c2fba5a7b75cab145ff9a67266c2c28d6b40e9d

5,333

py

Python

nlpaug/model/lang_models/language_models.py

So-AI-love/nlpaug

3aff5754609cb6bf092709d9af2089ccd55ffc93

[ "MIT" ]

null

nlpaug/model/lang_models/language_models.py

So-AI-love/nlpaug

3aff5754609cb6bf092709d9af2089ccd55ffc93

[ "MIT" ]

null

nlpaug/model/lang_models/language_models.py

So-AI-love/nlpaug

3aff5754609cb6bf092709d9af2089ccd55ffc93

[ "MIT" ]

null

try: import torch import torch.nn.functional as F except ImportError: # No installation required if not using this function pass import numpy as np import string import nlpaug.util.selection.filtering as filtering class LanguageModels: OPTIMIZE_ATTRIBUTES = ['external_memory', 'return_proba'] def __init__(self, device='cpu', temperature=1.0, top_k=100, top_p=0.01, optimize=None, silence=True): try: import torch except ModuleNotFoundError: raise ModuleNotFoundError('Missed torch library. Install torch by following https://pytorch.org/get-started/locally/`') # self.device = 'cuda' if device is None and torch.cuda.is_available() else 'cpu' self.device = device if device else 'cpu' self.temperature = temperature self.top_k = top_k self.top_p = top_p self.optimize = self.init_optimize(optimize) self.silence = silence @classmethod def get_default_optimize_config(cls): return { 'external_memory': 1024, # GPT2 needs either zero or non-zero. XLNet needs number of extra memory tokens. 'return_proba': False } def init_optimize(self, optimize): _optimize = self.get_default_optimize_config() if optimize is None: return _optimize for attr in self.OPTIMIZE_ATTRIBUTES: if attr in optimize: _optimize[attr] = optimize[attr] return _optimize def clean(self, text): return text.strip() def predict(self, text, target_word=None, n=1): raise NotImplementedError @classmethod def control_randomness(cls, logits, seed): temperature = seed['temperature'] if temperature is not None: return logits / temperature return logits def filtering(self, logits, seed): top_k = seed['top_k'] top_p = seed['top_p'] check_top_k = False check_top_p = False if top_k is not None and 0 < top_k < len(logits): logits, idxes = filtering.filter_top_k(logits, top_k, replace=-float('Inf')) check_top_k = True if top_p is not None and 0 < top_p < 1: logits, idxes = filtering.nucleus_sampling(logits, top_p) check_top_p = True # If top_p is not None, value will be sorted, so no need to select it again if not check_top_p: if check_top_k: logits = logits.index_select(0, idxes) # TODO: Externalize to util for checking if 'cuda' in self.device: idxes = idxes.cpu() idxes = idxes.detach().numpy().tolist() else: idxes = np.arange(len(logits)).tolist() else: logits = logits[:len(idxes)] # TODO: Externalize to util for checking if 'cuda' in self.device: idxes = idxes.cpu() idxes = idxes.detach().numpy().tolist() return logits, idxes def pick(self, logits, idxes, target_word, n=1, include_punctuation=False): candidate_ids, candidate_probas = self.prob_multinomial(logits, n=n*10) candidate_ids = [idxes[candidate_id] for candidate_id in candidate_ids] results = self.get_candidiates(candidate_ids, candidate_probas, target_word, n, include_punctuation) return results def id2token(self, _id): raise NotImplementedError() def prob_multinomial(self, logits, n): # Convert to probability probas = F.softmax(logits, dim=-1) # Draw candidates num_sample = min(n, torch.nonzero(probas, as_tuple=False).size(0)) # Number of potential candidate is small when top_k/ top_p are used. filtered_top_n_ids = torch.multinomial(probas, num_samples=num_sample, replacement=False).tolist() if self.optimize['return_proba']: top_n_probas = [probas[_id] for _id in filtered_top_n_ids] return filtered_top_n_ids, top_n_probas return filtered_top_n_ids, None def is_skip_candidate(self, candidate): return False def get_candidiates(self, candidate_ids, candidate_probas, target_word=None, n=1, include_punctuation=False): # To have random behavior, NO sorting for candidate_probas. results = [] if candidate_probas is None: candidate_probas = [0] * len(candidate_ids) for candidate_id, candidate_proba in zip(candidate_ids, candidate_probas): candidate_word = self.id2token(candidate_id) # unable to predict word if candidate_word in ['', self.UNKNOWN_TOKEN, self.SUBWORD_PREFIX] or 'unused' in candidate_word: continue # predicted same word if target_word is not None and candidate_word.lower() == target_word.lower(): continue # stop word if self.is_skip_candidate(candidate_word): continue # punctuation if not include_punctuation and candidate_word in string.punctuation: continue results.append((candidate_word, candidate_proba)) if len(results) >= n: break return results

35.317881

144

0.624602

try: import torch import torch.nn.functional as F except ImportError: pass import numpy as np import string import nlpaug.util.selection.filtering as filtering class LanguageModels: OPTIMIZE_ATTRIBUTES = ['external_memory', 'return_proba'] def __init__(self, device='cpu', temperature=1.0, top_k=100, top_p=0.01, optimize=None, silence=True): try: import torch except ModuleNotFoundError: raise ModuleNotFoundError('Missed torch library. Install torch by following https://pytorch.org/get-started/locally/`') self.device = device if device else 'cpu' self.temperature = temperature self.top_k = top_k self.top_p = top_p self.optimize = self.init_optimize(optimize) self.silence = silence @classmethod def get_default_optimize_config(cls): return { 'external_memory': 1024, 'return_proba': False } def init_optimize(self, optimize): _optimize = self.get_default_optimize_config() if optimize is None: return _optimize for attr in self.OPTIMIZE_ATTRIBUTES: if attr in optimize: _optimize[attr] = optimize[attr] return _optimize def clean(self, text): return text.strip() def predict(self, text, target_word=None, n=1): raise NotImplementedError @classmethod def control_randomness(cls, logits, seed): temperature = seed['temperature'] if temperature is not None: return logits / temperature return logits def filtering(self, logits, seed): top_k = seed['top_k'] top_p = seed['top_p'] check_top_k = False check_top_p = False if top_k is not None and 0 < top_k < len(logits): logits, idxes = filtering.filter_top_k(logits, top_k, replace=-float('Inf')) check_top_k = True if top_p is not None and 0 < top_p < 1: logits, idxes = filtering.nucleus_sampling(logits, top_p) check_top_p = True if not check_top_p: if check_top_k: logits = logits.index_select(0, idxes) if 'cuda' in self.device: idxes = idxes.cpu() idxes = idxes.detach().numpy().tolist() else: idxes = np.arange(len(logits)).tolist() else: logits = logits[:len(idxes)] if 'cuda' in self.device: idxes = idxes.cpu() idxes = idxes.detach().numpy().tolist() return logits, idxes def pick(self, logits, idxes, target_word, n=1, include_punctuation=False): candidate_ids, candidate_probas = self.prob_multinomial(logits, n=n*10) candidate_ids = [idxes[candidate_id] for candidate_id in candidate_ids] results = self.get_candidiates(candidate_ids, candidate_probas, target_word, n, include_punctuation) return results def id2token(self, _id): raise NotImplementedError() def prob_multinomial(self, logits, n): probas = F.softmax(logits, dim=-1) num_sample = min(n, torch.nonzero(probas, as_tuple=False).size(0)) filtered_top_n_ids = torch.multinomial(probas, num_samples=num_sample, replacement=False).tolist() if self.optimize['return_proba']: top_n_probas = [probas[_id] for _id in filtered_top_n_ids] return filtered_top_n_ids, top_n_probas return filtered_top_n_ids, None def is_skip_candidate(self, candidate): return False def get_candidiates(self, candidate_ids, candidate_probas, target_word=None, n=1, include_punctuation=False): results = [] if candidate_probas is None: candidate_probas = [0] * len(candidate_ids) for candidate_id, candidate_proba in zip(candidate_ids, candidate_probas): candidate_word = self.id2token(candidate_id) if candidate_word in ['', self.UNKNOWN_TOKEN, self.SUBWORD_PREFIX] or 'unused' in candidate_word: continue if target_word is not None and candidate_word.lower() == target_word.lower(): continue if self.is_skip_candidate(candidate_word): continue if not include_punctuation and candidate_word in string.punctuation: continue results.append((candidate_word, candidate_proba)) if len(results) >= n: break return results

true

1c2fbae5ecfebac86fe0e32e8e1486af950d1fe0

2,988

py

Python

models/others/lsa.py

dahyun-kang/renet

43a4e5af96b56c99a0cd63e35bd272db72f7f3a4

[ "MIT" ]

50

2021-08-18T23:41:16.000Z

2022-03-09T03:08:40.000Z

models/others/lsa.py

ChiaraDom18/renet

b58ebc092fcdb40e7f534f6407512df4f109cacd

[ "MIT" ]

6

2021-08-31T11:55:36.000Z

2022-02-10T02:16:27.000Z

models/others/lsa.py

ChiaraDom18/renet

b58ebc092fcdb40e7f534f6407512df4f109cacd

[ "MIT" ]

11

2021-08-30T08:36:36.000Z

2022-03-22T07:21:45.000Z

""" code references: https://github.com/leaderj1001/Stand-Alone-Self-Attention """ import torch import torch.nn as nn import torch.nn.functional as F import torch.nn.init as init class LocalSelfAttention(nn.Module): def __init__(self, in_channels, out_channels, kernel_size, stride=1, padding=0, groups=1, bias=False): super(LocalSelfAttention, self).__init__() self.out_channels = out_channels self.kernel_size = kernel_size self.stride = stride self.padding = padding self.groups = groups assert self.out_channels % self.groups == 0, "out_channels should be divided by groups. (example: out_channels: 40, groups: 4)" self.rel_h = nn.Parameter(torch.randn(out_channels // 2, 1, 1, kernel_size, 1), requires_grad=True) self.rel_w = nn.Parameter(torch.randn(out_channels // 2, 1, 1, 1, kernel_size), requires_grad=True) self.key_conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, bias=bias) self.query_conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, bias=bias) self.value_conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, bias=bias) self.agg = nn.Sequential( nn.BatchNorm2d(out_channels), nn.ReLU(inplace=True), nn.Conv2d(out_channels, out_channels, kernel_size=1, bias=False), nn.BatchNorm2d(out_channels)) self.reset_parameters() def forward(self, x): batch, channels, height, width = x.size() padded_x = F.pad(x, [self.padding, self.padding, self.padding, self.padding]) q_out = self.query_conv(x) k_out = self.key_conv(padded_x) v_out = self.value_conv(padded_x) k_out = k_out.unfold(2, self.kernel_size, self.stride).unfold(3, self.kernel_size, self.stride) v_out = v_out.unfold(2, self.kernel_size, self.stride).unfold(3, self.kernel_size, self.stride) k_out_h, k_out_w = k_out.split(self.out_channels // 2, dim=1) k_out = torch.cat((k_out_h + self.rel_h, k_out_w + self.rel_w), dim=1) k_out = k_out.contiguous().view(batch, self.groups, self.out_channels // self.groups, height, width, -1) v_out = v_out.contiguous().view(batch, self.groups, self.out_channels // self.groups, height, width, -1) q_out = q_out.view(batch, self.groups, self.out_channels // self.groups, height, width, 1) out = q_out * k_out out = F.softmax(out, dim=-1) out = torch.einsum('bnchwk,bnchwk -> bnchw', out, v_out).view(batch, -1, height, width) out = self.agg(out) return out def reset_parameters(self): init.kaiming_normal_(self.key_conv.weight, mode='fan_out', nonlinearity='relu') init.kaiming_normal_(self.value_conv.weight, mode='fan_out', nonlinearity='relu') init.kaiming_normal_(self.query_conv.weight, mode='fan_out', nonlinearity='relu') init.normal_(self.rel_h, 0, 1) init.normal_(self.rel_w, 0, 1)

43.941176

135

0.66834

import torch import torch.nn as nn import torch.nn.functional as F import torch.nn.init as init class LocalSelfAttention(nn.Module): def __init__(self, in_channels, out_channels, kernel_size, stride=1, padding=0, groups=1, bias=False): super(LocalSelfAttention, self).__init__() self.out_channels = out_channels self.kernel_size = kernel_size self.stride = stride self.padding = padding self.groups = groups assert self.out_channels % self.groups == 0, "out_channels should be divided by groups. (example: out_channels: 40, groups: 4)" self.rel_h = nn.Parameter(torch.randn(out_channels // 2, 1, 1, kernel_size, 1), requires_grad=True) self.rel_w = nn.Parameter(torch.randn(out_channels // 2, 1, 1, 1, kernel_size), requires_grad=True) self.key_conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, bias=bias) self.query_conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, bias=bias) self.value_conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, bias=bias) self.agg = nn.Sequential( nn.BatchNorm2d(out_channels), nn.ReLU(inplace=True), nn.Conv2d(out_channels, out_channels, kernel_size=1, bias=False), nn.BatchNorm2d(out_channels)) self.reset_parameters() def forward(self, x): batch, channels, height, width = x.size() padded_x = F.pad(x, [self.padding, self.padding, self.padding, self.padding]) q_out = self.query_conv(x) k_out = self.key_conv(padded_x) v_out = self.value_conv(padded_x) k_out = k_out.unfold(2, self.kernel_size, self.stride).unfold(3, self.kernel_size, self.stride) v_out = v_out.unfold(2, self.kernel_size, self.stride).unfold(3, self.kernel_size, self.stride) k_out_h, k_out_w = k_out.split(self.out_channels // 2, dim=1) k_out = torch.cat((k_out_h + self.rel_h, k_out_w + self.rel_w), dim=1) k_out = k_out.contiguous().view(batch, self.groups, self.out_channels // self.groups, height, width, -1) v_out = v_out.contiguous().view(batch, self.groups, self.out_channels // self.groups, height, width, -1) q_out = q_out.view(batch, self.groups, self.out_channels // self.groups, height, width, 1) out = q_out * k_out out = F.softmax(out, dim=-1) out = torch.einsum('bnchwk,bnchwk -> bnchw', out, v_out).view(batch, -1, height, width) out = self.agg(out) return out def reset_parameters(self): init.kaiming_normal_(self.key_conv.weight, mode='fan_out', nonlinearity='relu') init.kaiming_normal_(self.value_conv.weight, mode='fan_out', nonlinearity='relu') init.kaiming_normal_(self.query_conv.weight, mode='fan_out', nonlinearity='relu') init.normal_(self.rel_h, 0, 1) init.normal_(self.rel_w, 0, 1)

true

1c2fbb148908d1bc8211429d7a1d2e851c65fc4a

2,081

py

Python

autosuspend_mcstatus/activity.py

nikp123/autosuspend-mcstatus

0fec99e9ee6fa961bfafdd677684290495fcdcbf

[ "MIT" ]

null

autosuspend_mcstatus/activity.py

nikp123/autosuspend-mcstatus

0fec99e9ee6fa961bfafdd677684290495fcdcbf

[ "MIT" ]

null

autosuspend_mcstatus/activity.py

nikp123/autosuspend-mcstatus

0fec99e9ee6fa961bfafdd677684290495fcdcbf

[ "MIT" ]

null

from typing import * import configparser import socket from mcstatus import MinecraftServer from autosuspend.checks import Activity, ConfigurationError from .util import MCStatusMixin class ServerOnline(Activity, MCStatusMixin): @classmethod def create(cls, name: str, config: configparser.SectionProxy) -> "ServerOnline": return cls(name, **cls.collect_init_args(config)) def __init__(self, name: str, **kwargs) -> None: MCStatusMixin.__init__(self, **kwargs) Activity.__init__(self, name) def check(self) -> Optional[str]: self.logger.debug("Sending SLP to {}".format(self._address)) try: self._server.ping(tries=self._retries) return "Server is online" except socket.timeout as error: pass except ConnectionError as error: pass class PlayersOnline(Activity, MCStatusMixin): @classmethod def create(cls, name: str, config: configparser.SectionProxy) -> "PlayersOnline": try: treshold = config.getint("treshold", fallback=0) except ValueError as error: raise ConfigurationError("Treshold must be integer") from error return cls(name, treshold, **cls.collect_init_args(config)) def __init__(self, name: str, treshold: int, **kwargs) -> None: MCStatusMixin.__init__(self, **kwargs) Activity.__init__(self, name) self._treshold = treshold def check(self) -> Optional[str]: self.logger.debug("Sending SLP to {}".format(self._address)) try: status = self._server.status(tries=self._retries) if status.players.online > self._treshold: return "{} players online on {}".format( status.players.online, self._address ) except socket.timeout as error: self.logger.warning("SLP timed out, server is probably down") except ConnectionError as error: self.logger.warning("Connection error: {}".format(error))

35.87931

85

0.635272

from typing import * import configparser import socket from mcstatus import MinecraftServer from autosuspend.checks import Activity, ConfigurationError from .util import MCStatusMixin class ServerOnline(Activity, MCStatusMixin): @classmethod def create(cls, name: str, config: configparser.SectionProxy) -> "ServerOnline": return cls(name, **cls.collect_init_args(config)) def __init__(self, name: str, **kwargs) -> None: MCStatusMixin.__init__(self, **kwargs) Activity.__init__(self, name) def check(self) -> Optional[str]: self.logger.debug("Sending SLP to {}".format(self._address)) try: self._server.ping(tries=self._retries) return "Server is online" except socket.timeout as error: pass except ConnectionError as error: pass class PlayersOnline(Activity, MCStatusMixin): @classmethod def create(cls, name: str, config: configparser.SectionProxy) -> "PlayersOnline": try: treshold = config.getint("treshold", fallback=0) except ValueError as error: raise ConfigurationError("Treshold must be integer") from error return cls(name, treshold, **cls.collect_init_args(config)) def __init__(self, name: str, treshold: int, **kwargs) -> None: MCStatusMixin.__init__(self, **kwargs) Activity.__init__(self, name) self._treshold = treshold def check(self) -> Optional[str]: self.logger.debug("Sending SLP to {}".format(self._address)) try: status = self._server.status(tries=self._retries) if status.players.online > self._treshold: return "{} players online on {}".format( status.players.online, self._address ) except socket.timeout as error: self.logger.warning("SLP timed out, server is probably down") except ConnectionError as error: self.logger.warning("Connection error: {}".format(error))

true

1c2fbb6630d7d1f4de8a8b6f7db503ab9258f7c7

1,544

py

Python

models/layers/linears.py

MachineWei/ChineseNer

fae4dfb0498c2f1f7dfafee70fa47c935266bfaf

[ "MIT" ]

1

2021-08-28T11:45:18.000Z

models/layers/linears.py

MachineWei/bert-crf-for-ner

fae4dfb0498c2f1f7dfafee70fa47c935266bfaf

[ "MIT" ]

null

models/layers/linears.py

MachineWei/bert-crf-for-ner

fae4dfb0498c2f1f7dfafee70fa47c935266bfaf

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F # from torch.modeling_utils import PoolerStartLogits, PoolerEndLogits class FeedForwardNetwork(nn.Module): def __init__(self, input_size, hidden_size, output_size, dropout_rate=0): super(FeedForwardNetwork, self).__init__() self.dropout_rate = dropout_rate self.linear1 = nn.Linear(input_size, hidden_size) self.linear2 = nn.Linear(hidden_size, output_size) def forward(self, x): x_proj = F.dropout(F.relu(self.linear1(x)), p=self.dropout_rate, training=self.training) x_proj = self.linear2(x_proj) return x_proj class PoolerStartLogits(nn.Module): def __init__(self, hidden_size, num_classes): super(PoolerStartLogits, self).__init__() self.dense = nn.Linear(hidden_size, num_classes) def forward(self, hidden_states, p_mask=None): x = self.dense(hidden_states) return x class PoolerEndLogits(nn.Module): def __init__(self, hidden_size, num_classes): super(PoolerEndLogits, self).__init__() self.dense_0 = nn.Linear(hidden_size, hidden_size) self.activation = nn.Tanh() self.LayerNorm = nn.LayerNorm(hidden_size) self.dense_1 = nn.Linear(hidden_size, num_classes) def forward(self, hidden_states, start_positions=None, p_mask=None): x = self.dense_0(torch.cat([hidden_states, start_positions], dim=-1)) x = self.activation(x) x = self.LayerNorm(x) x = self.dense_1(x) return x

36.761905

96

0.69171

import torch import torch.nn as nn import torch.nn.functional as F class FeedForwardNetwork(nn.Module): def __init__(self, input_size, hidden_size, output_size, dropout_rate=0): super(FeedForwardNetwork, self).__init__() self.dropout_rate = dropout_rate self.linear1 = nn.Linear(input_size, hidden_size) self.linear2 = nn.Linear(hidden_size, output_size) def forward(self, x): x_proj = F.dropout(F.relu(self.linear1(x)), p=self.dropout_rate, training=self.training) x_proj = self.linear2(x_proj) return x_proj class PoolerStartLogits(nn.Module): def __init__(self, hidden_size, num_classes): super(PoolerStartLogits, self).__init__() self.dense = nn.Linear(hidden_size, num_classes) def forward(self, hidden_states, p_mask=None): x = self.dense(hidden_states) return x class PoolerEndLogits(nn.Module): def __init__(self, hidden_size, num_classes): super(PoolerEndLogits, self).__init__() self.dense_0 = nn.Linear(hidden_size, hidden_size) self.activation = nn.Tanh() self.LayerNorm = nn.LayerNorm(hidden_size) self.dense_1 = nn.Linear(hidden_size, num_classes) def forward(self, hidden_states, start_positions=None, p_mask=None): x = self.dense_0(torch.cat([hidden_states, start_positions], dim=-1)) x = self.activation(x) x = self.LayerNorm(x) x = self.dense_1(x) return x

true

1c2fbc32946418c6d20fc9cc650f8583cf072fe2

536

py

Python

src/thenewboston/transactions/validation.py

achalpatel/thenewboston-python

4044ce07cb5e0d1f92b4332bbd8c6ac8f33bcdb9

[ "MIT" ]

122

2020-07-12T23:08:49.000Z

2021-12-18T16:14:10.000Z

src/thenewboston/transactions/validation.py

achalpatel/thenewboston-python

4044ce07cb5e0d1f92b4332bbd8c6ac8f33bcdb9

[ "MIT" ]

47

2020-07-15T02:18:09.000Z

2021-09-22T19:51:59.000Z

src/thenewboston/transactions/validation.py

achalpatel/thenewboston-python

4044ce07cb5e0d1f92b4332bbd8c6ac8f33bcdb9

[ "MIT" ]

52

2020-07-13T10:49:52.000Z

2021-10-30T03:34:55.000Z

def validate_transaction_exists(*, amount, fee, error, recipient, txs): """Check for the existence of a Tx""" tx = next( ( tx for tx in txs if tx.get('amount') >= amount and tx.get('fee') == fee and tx.get('recipient') == recipient ), None ) if not tx: raise error({ 'error_message': 'Tx not found', 'expected_amount': amount, 'expected_fee': fee, 'expected_recipient': recipient })

26.8

71

0.494403

def validate_transaction_exists(*, amount, fee, error, recipient, txs): tx = next( ( tx for tx in txs if tx.get('amount') >= amount and tx.get('fee') == fee and tx.get('recipient') == recipient ), None ) if not tx: raise error({ 'error_message': 'Tx not found', 'expected_amount': amount, 'expected_fee': fee, 'expected_recipient': recipient })

true

1c2fbd6abc51e920a13f546a06ef5107166764c0

21,025

py

Python

PC/utils/scheduler.py

StanLei52/GEBD

5f7e722e0384f9877c75d116e1db72400d2bc58f

[ "MIT" ]

44

2021-03-24T07:10:57.000Z

2022-03-12T11:49:14.000Z

PC/utils/scheduler.py

StanLei52/GEBD

5f7e722e0384f9877c75d116e1db72400d2bc58f

[ "MIT" ]

2

2021-05-26T09:31:55.000Z

2021-08-11T11:47:38.000Z

PC/utils/scheduler.py

StanLei52/GEBD

5f7e722e0384f9877c75d116e1db72400d2bc58f

[ "MIT" ]

6

2021-04-07T00:51:51.000Z

2022-01-12T01:54:41.000Z

from typing import Dict, Any import torch import math import logging import numpy as np _logger = logging.getLogger(__name__) class Scheduler: """ Parameter Scheduler Base Class A scheduler base class that can be used to schedule any optimizer parameter groups. Unlike the builtin PyTorch schedulers, this is intended to be consistently called * At the END of each epoch, before incrementing the epoch count, to calculate next epoch's value * At the END of each optimizer update, after incrementing the update count, to calculate next update's value The schedulers built on this should try to remain as stateless as possible (for simplicity). This family of schedulers is attempting to avoid the confusion of the meaning of 'last_epoch' and -1 values for special behaviour. All epoch and update counts must be tracked in the training code and explicitly passed in to the schedulers on the corresponding step or step_update call. Based on ideas from: * https://github.com/pytorch/fairseq/tree/master/fairseq/optim/lr_scheduler * https://github.com/allenai/allennlp/tree/master/allennlp/training/learning_rate_schedulers """ def __init__(self, optimizer: torch.optim.Optimizer, param_group_field: str, noise_range_t=None, noise_type='normal', noise_pct=0.67, noise_std=1.0, noise_seed=None, initialize: bool = True) -> None: self.optimizer = optimizer self.param_group_field = param_group_field self._initial_param_group_field = f"initial_{param_group_field}" if initialize: for i, group in enumerate(self.optimizer.param_groups): if param_group_field not in group: raise KeyError(f"{param_group_field} missing from param_groups[{i}]") group.setdefault(self._initial_param_group_field, group[param_group_field]) else: for i, group in enumerate(self.optimizer.param_groups): if self._initial_param_group_field not in group: raise KeyError(f"{self._initial_param_group_field} missing from param_groups[{i}]") self.base_values = [group[self._initial_param_group_field] for group in self.optimizer.param_groups] self.metric = None # any point to having this for all? self.noise_range_t = noise_range_t self.noise_pct = noise_pct self.noise_type = noise_type self.noise_std = noise_std self.noise_seed = noise_seed if noise_seed is not None else 42 self.update_groups(self.base_values) def state_dict(self) -> Dict[str, Any]: return {key: value for key, value in self.__dict__.items() if key != 'optimizer'} def load_state_dict(self, state_dict: Dict[str, Any]) -> None: self.__dict__.update(state_dict) def get_epoch_values(self, epoch: int): return None def get_update_values(self, num_updates: int): return None def step(self, epoch: int, metric: float = None) -> None: self.metric = metric values = self.get_epoch_values(epoch) if values is not None: values = self._add_noise(values, epoch) self.update_groups(values) def step_update(self, num_updates: int, metric: float = None): self.metric = metric values = self.get_update_values(num_updates) if values is not None: values = self._add_noise(values, num_updates) self.update_groups(values) def update_groups(self, values): if not isinstance(values, (list, tuple)): values = [values] * len(self.optimizer.param_groups) for param_group, value in zip(self.optimizer.param_groups, values): param_group[self.param_group_field] = value def _add_noise(self, lrs, t): if self.noise_range_t is not None: if isinstance(self.noise_range_t, (list, tuple)): apply_noise = self.noise_range_t[0] <= t < self.noise_range_t[1] else: apply_noise = t >= self.noise_range_t if apply_noise: g = torch.Generator() g.manual_seed(self.noise_seed + t) if self.noise_type == 'normal': while True: # resample if noise out of percent limit, brute force but shouldn't spin much noise = torch.randn(1, generator=g).item() if abs(noise) < self.noise_pct: break else: noise = 2 * (torch.rand(1, generator=g).item() - 0.5) * self.noise_pct lrs = [v + v * noise for v in lrs] return lrs class CosineLRScheduler(Scheduler): """ Cosine decay with restarts. This is described in the paper https://arxiv.org/abs/1608.03983. Inspiration from https://github.com/allenai/allennlp/blob/master/allennlp/training/learning_rate_schedulers/cosine.py """ def __init__(self, optimizer: torch.optim.Optimizer, t_initial: int, t_mul: float = 1., lr_min: float = 0., decay_rate: float = 1., warmup_t=0, warmup_lr_init=0, warmup_prefix=False, cycle_limit=0, t_in_epochs=True, noise_range_t=None, noise_pct=0.67, noise_std=1.0, noise_seed=42, initialize=True) -> None: super().__init__( optimizer, param_group_field="lr", noise_range_t=noise_range_t, noise_pct=noise_pct, noise_std=noise_std, noise_seed=noise_seed, initialize=initialize) assert t_initial > 0 assert lr_min >= 0 if t_initial == 1 and t_mul == 1 and decay_rate == 1: _logger.warning("Cosine annealing scheduler will have no effect on the learning " "rate since t_initial = t_mul = eta_mul = 1.") self.t_initial = t_initial self.t_mul = t_mul self.lr_min = lr_min self.decay_rate = decay_rate self.cycle_limit = cycle_limit self.warmup_t = warmup_t self.warmup_lr_init = warmup_lr_init self.warmup_prefix = warmup_prefix self.t_in_epochs = t_in_epochs if self.warmup_t: self.warmup_steps = [(v - warmup_lr_init) / self.warmup_t for v in self.base_values] super().update_groups(self.warmup_lr_init) else: self.warmup_steps = [1 for _ in self.base_values] def _get_lr(self, t): if t < self.warmup_t: lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps] else: if self.warmup_prefix: t = t - self.warmup_t if self.t_mul != 1: i = math.floor(math.log(1 - t / self.t_initial * (1 - self.t_mul), self.t_mul)) t_i = self.t_mul ** i * self.t_initial t_curr = t - (1 - self.t_mul ** i) / (1 - self.t_mul) * self.t_initial else: i = t // self.t_initial t_i = self.t_initial t_curr = t - (self.t_initial * i) gamma = self.decay_rate ** i lr_min = self.lr_min * gamma lr_max_values = [v * gamma for v in self.base_values] if self.cycle_limit == 0 or (self.cycle_limit > 0 and i < self.cycle_limit): lrs = [ lr_min + 0.5 * (lr_max - lr_min) * (1 + math.cos(math.pi * t_curr / t_i)) for lr_max in lr_max_values ] else: lrs = [self.lr_min for _ in self.base_values] return lrs def get_epoch_values(self, epoch: int): if self.t_in_epochs: return self._get_lr(epoch) else: return None def get_update_values(self, num_updates: int): if not self.t_in_epochs: return self._get_lr(num_updates) else: return None def get_cycle_length(self, cycles=0): if not cycles: cycles = self.cycle_limit cycles = max(1, cycles) if self.t_mul == 1.0: return self.t_initial * cycles else: return int(math.floor(-self.t_initial * (self.t_mul ** cycles - 1) / (1 - self.t_mul))) class TanhLRScheduler(Scheduler): """ Hyberbolic-Tangent decay with restarts. This is described in the paper https://arxiv.org/abs/1806.01593 """ def __init__(self, optimizer: torch.optim.Optimizer, t_initial: int, lb: float = -6., ub: float = 4., t_mul: float = 1., lr_min: float = 0., decay_rate: float = 1., warmup_t=0, warmup_lr_init=0, warmup_prefix=False, cycle_limit=0, t_in_epochs=True, noise_range_t=None, noise_pct=0.67, noise_std=1.0, noise_seed=42, initialize=True) -> None: super().__init__( optimizer, param_group_field="lr", noise_range_t=noise_range_t, noise_pct=noise_pct, noise_std=noise_std, noise_seed=noise_seed, initialize=initialize) assert t_initial > 0 assert lr_min >= 0 assert lb < ub assert cycle_limit >= 0 assert warmup_t >= 0 assert warmup_lr_init >= 0 self.lb = lb self.ub = ub self.t_initial = t_initial self.t_mul = t_mul self.lr_min = lr_min self.decay_rate = decay_rate self.cycle_limit = cycle_limit self.warmup_t = warmup_t self.warmup_lr_init = warmup_lr_init self.warmup_prefix = warmup_prefix self.t_in_epochs = t_in_epochs if self.warmup_t: t_v = self.base_values if self.warmup_prefix else self._get_lr(self.warmup_t) self.warmup_steps = [(v - warmup_lr_init) / self.warmup_t for v in t_v] super().update_groups(self.warmup_lr_init) else: self.warmup_steps = [1 for _ in self.base_values] def _get_lr(self, t): if t < self.warmup_t: lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps] else: if self.warmup_prefix: t = t - self.warmup_t if self.t_mul != 1: i = math.floor(math.log(1 - t / self.t_initial * (1 - self.t_mul), self.t_mul)) t_i = self.t_mul ** i * self.t_initial t_curr = t - (1 - self.t_mul ** i) / (1 - self.t_mul) * self.t_initial else: i = t // self.t_initial t_i = self.t_initial t_curr = t - (self.t_initial * i) if self.cycle_limit == 0 or (self.cycle_limit > 0 and i < self.cycle_limit): gamma = self.decay_rate ** i lr_min = self.lr_min * gamma lr_max_values = [v * gamma for v in self.base_values] tr = t_curr / t_i lrs = [ lr_min + 0.5 * (lr_max - lr_min) * (1 - math.tanh(self.lb * (1. - tr) + self.ub * tr)) for lr_max in lr_max_values ] else: lrs = [self.lr_min * (self.decay_rate ** self.cycle_limit) for _ in self.base_values] return lrs def get_epoch_values(self, epoch: int): if self.t_in_epochs: return self._get_lr(epoch) else: return None def get_update_values(self, num_updates: int): if not self.t_in_epochs: return self._get_lr(num_updates) else: return None def get_cycle_length(self, cycles=0): if not cycles: cycles = self.cycle_limit cycles = max(1, cycles) if self.t_mul == 1.0: return self.t_initial * cycles else: return int(math.floor(-self.t_initial * (self.t_mul ** cycles - 1) / (1 - self.t_mul))) class StepLRScheduler(Scheduler): """ """ def __init__(self, optimizer: torch.optim.Optimizer, decay_t: float, decay_rate: float = 1., warmup_t=0, warmup_lr_init=0, t_in_epochs=True, noise_range_t=None, noise_pct=0.67, noise_std=1.0, noise_seed=42, initialize=True, ) -> None: super().__init__( optimizer, param_group_field="lr", noise_range_t=noise_range_t, noise_pct=noise_pct, noise_std=noise_std, noise_seed=noise_seed, initialize=initialize) self.decay_t = decay_t self.decay_rate = decay_rate self.warmup_t = warmup_t self.warmup_lr_init = warmup_lr_init self.t_in_epochs = t_in_epochs if self.warmup_t: self.warmup_steps = [(v - warmup_lr_init) / self.warmup_t for v in self.base_values] super().update_groups(self.warmup_lr_init) else: self.warmup_steps = [1 for _ in self.base_values] def _get_lr(self, t): if t < self.warmup_t: lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps] else: lrs = [v * (self.decay_rate ** (t // self.decay_t)) for v in self.base_values] return lrs def get_epoch_values(self, epoch: int): if self.t_in_epochs: return self._get_lr(epoch) else: return None def get_update_values(self, num_updates: int): if not self.t_in_epochs: return self._get_lr(num_updates) else: return None class PlateauLRScheduler(Scheduler): """Decay the LR by a factor every time the validation loss plateaus.""" def __init__(self, optimizer, decay_rate=0.1, patience_t=10, verbose=True, threshold=1e-4, cooldown_t=0, warmup_t=0, warmup_lr_init=0, lr_min=0, mode='max', noise_range_t=None, noise_type='normal', noise_pct=0.67, noise_std=1.0, noise_seed=None, initialize=True, ): super().__init__(optimizer, 'lr', initialize=initialize) self.lr_scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau( self.optimizer, patience=patience_t, factor=decay_rate, verbose=verbose, threshold=threshold, cooldown=cooldown_t, mode=mode, min_lr=lr_min ) self.noise_range = noise_range_t self.noise_pct = noise_pct self.noise_type = noise_type self.noise_std = noise_std self.noise_seed = noise_seed if noise_seed is not None else 42 self.warmup_t = warmup_t self.warmup_lr_init = warmup_lr_init if self.warmup_t: self.warmup_steps = [(v - warmup_lr_init) / self.warmup_t for v in self.base_values] super().update_groups(self.warmup_lr_init) else: self.warmup_steps = [1 for _ in self.base_values] self.restore_lr = None def state_dict(self): return { 'best': self.lr_scheduler.best, 'last_epoch': self.lr_scheduler.last_epoch, } def load_state_dict(self, state_dict): self.lr_scheduler.best = state_dict['best'] if 'last_epoch' in state_dict: self.lr_scheduler.last_epoch = state_dict['last_epoch'] # override the base class step fn completely def step(self, epoch, metric=None): if epoch <= self.warmup_t: lrs = [self.warmup_lr_init + epoch * s for s in self.warmup_steps] super().update_groups(lrs) else: if self.restore_lr is not None: # restore actual LR from before our last noise perturbation before stepping base for i, param_group in enumerate(self.optimizer.param_groups): param_group['lr'] = self.restore_lr[i] self.restore_lr = None self.lr_scheduler.step(metric, epoch) # step the base scheduler if self.noise_range is not None: if isinstance(self.noise_range, (list, tuple)): apply_noise = self.noise_range[0] <= epoch < self.noise_range[1] else: apply_noise = epoch >= self.noise_range if apply_noise: self._apply_noise(epoch) def _apply_noise(self, epoch): g = torch.Generator() g.manual_seed(self.noise_seed + epoch) if self.noise_type == 'normal': while True: # resample if noise out of percent limit, brute force but shouldn't spin much noise = torch.randn(1, generator=g).item() if abs(noise) < self.noise_pct: break else: noise = 2 * (torch.rand(1, generator=g).item() - 0.5) * self.noise_pct # apply the noise on top of previous LR, cache the old value so we can restore for normal # stepping of base scheduler restore_lr = [] for i, param_group in enumerate(self.optimizer.param_groups): old_lr = float(param_group['lr']) restore_lr.append(old_lr) new_lr = old_lr + old_lr * noise param_group['lr'] = new_lr self.restore_lr = restore_lr def create_scheduler(args, optimizer): num_epochs = args.epochs if getattr(args, 'lr_noise', None) is not None: lr_noise = getattr(args, 'lr_noise') if isinstance(lr_noise, (list, tuple)): noise_range = [n * num_epochs for n in lr_noise] if len(noise_range) == 1: noise_range = noise_range[0] else: noise_range = lr_noise * num_epochs else: noise_range = None lr_scheduler = None if args.sched == 'cosine': lr_scheduler = CosineLRScheduler( optimizer, t_initial=num_epochs, t_mul=getattr(args, 'lr_cycle_mul', 1.), lr_min=args.min_lr, decay_rate=args.decay_rate, warmup_lr_init=args.warmup_lr, warmup_t=args.warmup_epochs, cycle_limit=getattr(args, 'lr_cycle_limit', 1), t_in_epochs=True, noise_range_t=noise_range, noise_pct=getattr(args, 'lr_noise_pct', 0.67), noise_std=getattr(args, 'lr_noise_std', 1.), noise_seed=getattr(args, 'seed', 42), ) num_epochs = lr_scheduler.get_cycle_length() + args.cooldown_epochs elif args.sched == 'tanh': lr_scheduler = TanhLRScheduler( optimizer, t_initial=num_epochs, t_mul=getattr(args, 'lr_cycle_mul', 1.), lr_min=args.min_lr, warmup_lr_init=args.warmup_lr, warmup_t=args.warmup_epochs, cycle_limit=getattr(args, 'lr_cycle_limit', 1), t_in_epochs=True, noise_range_t=noise_range, noise_pct=getattr(args, 'lr_noise_pct', 0.67), noise_std=getattr(args, 'lr_noise_std', 1.), noise_seed=getattr(args, 'seed', 42), ) num_epochs = lr_scheduler.get_cycle_length() + args.cooldown_epochs elif args.sched == 'step': lr_scheduler = StepLRScheduler( optimizer, decay_t=args.decay_epochs, decay_rate=args.decay_rate, warmup_lr_init=args.warmup_lr, warmup_t=args.warmup_epochs, noise_range_t=noise_range, noise_pct=getattr(args, 'lr_noise_pct', 0.67), noise_std=getattr(args, 'lr_noise_std', 1.), noise_seed=getattr(args, 'seed', 42), ) elif args.sched == 'plateau': mode = 'min' if 'loss' in getattr(args, 'eval_metric', '') else 'max' lr_scheduler = PlateauLRScheduler( optimizer, decay_rate=args.decay_rate, patience_t=args.patience_epochs, lr_min=args.min_lr, mode=mode, warmup_lr_init=args.warmup_lr, warmup_t=args.warmup_epochs, cooldown_t=0, noise_range_t=noise_range, noise_pct=getattr(args, 'lr_noise_pct', 0.67), noise_std=getattr(args, 'lr_noise_std', 1.), noise_seed=getattr(args, 'seed', 42), ) return lr_scheduler, num_epochs

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from typing import Dict, Any import torch import math import logging import numpy as np _logger = logging.getLogger(__name__) class Scheduler: def __init__(self, optimizer: torch.optim.Optimizer, param_group_field: str, noise_range_t=None, noise_type='normal', noise_pct=0.67, noise_std=1.0, noise_seed=None, initialize: bool = True) -> None: self.optimizer = optimizer self.param_group_field = param_group_field self._initial_param_group_field = f"initial_{param_group_field}" if initialize: for i, group in enumerate(self.optimizer.param_groups): if param_group_field not in group: raise KeyError(f"{param_group_field} missing from param_groups[{i}]") group.setdefault(self._initial_param_group_field, group[param_group_field]) else: for i, group in enumerate(self.optimizer.param_groups): if self._initial_param_group_field not in group: raise KeyError(f"{self._initial_param_group_field} missing from param_groups[{i}]") self.base_values = [group[self._initial_param_group_field] for group in self.optimizer.param_groups] self.metric = None self.noise_range_t = noise_range_t self.noise_pct = noise_pct self.noise_type = noise_type self.noise_std = noise_std self.noise_seed = noise_seed if noise_seed is not None else 42 self.update_groups(self.base_values) def state_dict(self) -> Dict[str, Any]: return {key: value for key, value in self.__dict__.items() if key != 'optimizer'} def load_state_dict(self, state_dict: Dict[str, Any]) -> None: self.__dict__.update(state_dict) def get_epoch_values(self, epoch: int): return None def get_update_values(self, num_updates: int): return None def step(self, epoch: int, metric: float = None) -> None: self.metric = metric values = self.get_epoch_values(epoch) if values is not None: values = self._add_noise(values, epoch) self.update_groups(values) def step_update(self, num_updates: int, metric: float = None): self.metric = metric values = self.get_update_values(num_updates) if values is not None: values = self._add_noise(values, num_updates) self.update_groups(values) def update_groups(self, values): if not isinstance(values, (list, tuple)): values = [values] * len(self.optimizer.param_groups) for param_group, value in zip(self.optimizer.param_groups, values): param_group[self.param_group_field] = value def _add_noise(self, lrs, t): if self.noise_range_t is not None: if isinstance(self.noise_range_t, (list, tuple)): apply_noise = self.noise_range_t[0] <= t < self.noise_range_t[1] else: apply_noise = t >= self.noise_range_t if apply_noise: g = torch.Generator() g.manual_seed(self.noise_seed + t) if self.noise_type == 'normal': while True: noise = torch.randn(1, generator=g).item() if abs(noise) < self.noise_pct: break else: noise = 2 * (torch.rand(1, generator=g).item() - 0.5) * self.noise_pct lrs = [v + v * noise for v in lrs] return lrs class CosineLRScheduler(Scheduler): def __init__(self, optimizer: torch.optim.Optimizer, t_initial: int, t_mul: float = 1., lr_min: float = 0., decay_rate: float = 1., warmup_t=0, warmup_lr_init=0, warmup_prefix=False, cycle_limit=0, t_in_epochs=True, noise_range_t=None, noise_pct=0.67, noise_std=1.0, noise_seed=42, initialize=True) -> None: super().__init__( optimizer, param_group_field="lr", noise_range_t=noise_range_t, noise_pct=noise_pct, noise_std=noise_std, noise_seed=noise_seed, initialize=initialize) assert t_initial > 0 assert lr_min >= 0 if t_initial == 1 and t_mul == 1 and decay_rate == 1: _logger.warning("Cosine annealing scheduler will have no effect on the learning " "rate since t_initial = t_mul = eta_mul = 1.") self.t_initial = t_initial self.t_mul = t_mul self.lr_min = lr_min self.decay_rate = decay_rate self.cycle_limit = cycle_limit self.warmup_t = warmup_t self.warmup_lr_init = warmup_lr_init self.warmup_prefix = warmup_prefix self.t_in_epochs = t_in_epochs if self.warmup_t: self.warmup_steps = [(v - warmup_lr_init) / self.warmup_t for v in self.base_values] super().update_groups(self.warmup_lr_init) else: self.warmup_steps = [1 for _ in self.base_values] def _get_lr(self, t): if t < self.warmup_t: lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps] else: if self.warmup_prefix: t = t - self.warmup_t if self.t_mul != 1: i = math.floor(math.log(1 - t / self.t_initial * (1 - self.t_mul), self.t_mul)) t_i = self.t_mul ** i * self.t_initial t_curr = t - (1 - self.t_mul ** i) / (1 - self.t_mul) * self.t_initial else: i = t // self.t_initial t_i = self.t_initial t_curr = t - (self.t_initial * i) gamma = self.decay_rate ** i lr_min = self.lr_min * gamma lr_max_values = [v * gamma for v in self.base_values] if self.cycle_limit == 0 or (self.cycle_limit > 0 and i < self.cycle_limit): lrs = [ lr_min + 0.5 * (lr_max - lr_min) * (1 + math.cos(math.pi * t_curr / t_i)) for lr_max in lr_max_values ] else: lrs = [self.lr_min for _ in self.base_values] return lrs def get_epoch_values(self, epoch: int): if self.t_in_epochs: return self._get_lr(epoch) else: return None def get_update_values(self, num_updates: int): if not self.t_in_epochs: return self._get_lr(num_updates) else: return None def get_cycle_length(self, cycles=0): if not cycles: cycles = self.cycle_limit cycles = max(1, cycles) if self.t_mul == 1.0: return self.t_initial * cycles else: return int(math.floor(-self.t_initial * (self.t_mul ** cycles - 1) / (1 - self.t_mul))) class TanhLRScheduler(Scheduler): def __init__(self, optimizer: torch.optim.Optimizer, t_initial: int, lb: float = -6., ub: float = 4., t_mul: float = 1., lr_min: float = 0., decay_rate: float = 1., warmup_t=0, warmup_lr_init=0, warmup_prefix=False, cycle_limit=0, t_in_epochs=True, noise_range_t=None, noise_pct=0.67, noise_std=1.0, noise_seed=42, initialize=True) -> None: super().__init__( optimizer, param_group_field="lr", noise_range_t=noise_range_t, noise_pct=noise_pct, noise_std=noise_std, noise_seed=noise_seed, initialize=initialize) assert t_initial > 0 assert lr_min >= 0 assert lb < ub assert cycle_limit >= 0 assert warmup_t >= 0 assert warmup_lr_init >= 0 self.lb = lb self.ub = ub self.t_initial = t_initial self.t_mul = t_mul self.lr_min = lr_min self.decay_rate = decay_rate self.cycle_limit = cycle_limit self.warmup_t = warmup_t self.warmup_lr_init = warmup_lr_init self.warmup_prefix = warmup_prefix self.t_in_epochs = t_in_epochs if self.warmup_t: t_v = self.base_values if self.warmup_prefix else self._get_lr(self.warmup_t) self.warmup_steps = [(v - warmup_lr_init) / self.warmup_t for v in t_v] super().update_groups(self.warmup_lr_init) else: self.warmup_steps = [1 for _ in self.base_values] def _get_lr(self, t): if t < self.warmup_t: lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps] else: if self.warmup_prefix: t = t - self.warmup_t if self.t_mul != 1: i = math.floor(math.log(1 - t / self.t_initial * (1 - self.t_mul), self.t_mul)) t_i = self.t_mul ** i * self.t_initial t_curr = t - (1 - self.t_mul ** i) / (1 - self.t_mul) * self.t_initial else: i = t // self.t_initial t_i = self.t_initial t_curr = t - (self.t_initial * i) if self.cycle_limit == 0 or (self.cycle_limit > 0 and i < self.cycle_limit): gamma = self.decay_rate ** i lr_min = self.lr_min * gamma lr_max_values = [v * gamma for v in self.base_values] tr = t_curr / t_i lrs = [ lr_min + 0.5 * (lr_max - lr_min) * (1 - math.tanh(self.lb * (1. - tr) + self.ub * tr)) for lr_max in lr_max_values ] else: lrs = [self.lr_min * (self.decay_rate ** self.cycle_limit) for _ in self.base_values] return lrs def get_epoch_values(self, epoch: int): if self.t_in_epochs: return self._get_lr(epoch) else: return None def get_update_values(self, num_updates: int): if not self.t_in_epochs: return self._get_lr(num_updates) else: return None def get_cycle_length(self, cycles=0): if not cycles: cycles = self.cycle_limit cycles = max(1, cycles) if self.t_mul == 1.0: return self.t_initial * cycles else: return int(math.floor(-self.t_initial * (self.t_mul ** cycles - 1) / (1 - self.t_mul))) class StepLRScheduler(Scheduler): def __init__(self, optimizer: torch.optim.Optimizer, decay_t: float, decay_rate: float = 1., warmup_t=0, warmup_lr_init=0, t_in_epochs=True, noise_range_t=None, noise_pct=0.67, noise_std=1.0, noise_seed=42, initialize=True, ) -> None: super().__init__( optimizer, param_group_field="lr", noise_range_t=noise_range_t, noise_pct=noise_pct, noise_std=noise_std, noise_seed=noise_seed, initialize=initialize) self.decay_t = decay_t self.decay_rate = decay_rate self.warmup_t = warmup_t self.warmup_lr_init = warmup_lr_init self.t_in_epochs = t_in_epochs if self.warmup_t: self.warmup_steps = [(v - warmup_lr_init) / self.warmup_t for v in self.base_values] super().update_groups(self.warmup_lr_init) else: self.warmup_steps = [1 for _ in self.base_values] def _get_lr(self, t): if t < self.warmup_t: lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps] else: lrs = [v * (self.decay_rate ** (t // self.decay_t)) for v in self.base_values] return lrs def get_epoch_values(self, epoch: int): if self.t_in_epochs: return self._get_lr(epoch) else: return None def get_update_values(self, num_updates: int): if not self.t_in_epochs: return self._get_lr(num_updates) else: return None class PlateauLRScheduler(Scheduler): def __init__(self, optimizer, decay_rate=0.1, patience_t=10, verbose=True, threshold=1e-4, cooldown_t=0, warmup_t=0, warmup_lr_init=0, lr_min=0, mode='max', noise_range_t=None, noise_type='normal', noise_pct=0.67, noise_std=1.0, noise_seed=None, initialize=True, ): super().__init__(optimizer, 'lr', initialize=initialize) self.lr_scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau( self.optimizer, patience=patience_t, factor=decay_rate, verbose=verbose, threshold=threshold, cooldown=cooldown_t, mode=mode, min_lr=lr_min ) self.noise_range = noise_range_t self.noise_pct = noise_pct self.noise_type = noise_type self.noise_std = noise_std self.noise_seed = noise_seed if noise_seed is not None else 42 self.warmup_t = warmup_t self.warmup_lr_init = warmup_lr_init if self.warmup_t: self.warmup_steps = [(v - warmup_lr_init) / self.warmup_t for v in self.base_values] super().update_groups(self.warmup_lr_init) else: self.warmup_steps = [1 for _ in self.base_values] self.restore_lr = None def state_dict(self): return { 'best': self.lr_scheduler.best, 'last_epoch': self.lr_scheduler.last_epoch, } def load_state_dict(self, state_dict): self.lr_scheduler.best = state_dict['best'] if 'last_epoch' in state_dict: self.lr_scheduler.last_epoch = state_dict['last_epoch'] # override the base class step fn completely def step(self, epoch, metric=None): if epoch <= self.warmup_t: lrs = [self.warmup_lr_init + epoch * s for s in self.warmup_steps] super().update_groups(lrs) else: if self.restore_lr is not None: # restore actual LR from before our last noise perturbation before stepping base for i, param_group in enumerate(self.optimizer.param_groups): param_group['lr'] = self.restore_lr[i] self.restore_lr = None self.lr_scheduler.step(metric, epoch) # step the base scheduler if self.noise_range is not None: if isinstance(self.noise_range, (list, tuple)): apply_noise = self.noise_range[0] <= epoch < self.noise_range[1] else: apply_noise = epoch >= self.noise_range if apply_noise: self._apply_noise(epoch) def _apply_noise(self, epoch): g = torch.Generator() g.manual_seed(self.noise_seed + epoch) if self.noise_type == 'normal': while True: # resample if noise out of percent limit, brute force but shouldn't spin much noise = torch.randn(1, generator=g).item() if abs(noise) < self.noise_pct: break else: noise = 2 * (torch.rand(1, generator=g).item() - 0.5) * self.noise_pct restore_lr = [] for i, param_group in enumerate(self.optimizer.param_groups): old_lr = float(param_group['lr']) restore_lr.append(old_lr) new_lr = old_lr + old_lr * noise param_group['lr'] = new_lr self.restore_lr = restore_lr def create_scheduler(args, optimizer): num_epochs = args.epochs if getattr(args, 'lr_noise', None) is not None: lr_noise = getattr(args, 'lr_noise') if isinstance(lr_noise, (list, tuple)): noise_range = [n * num_epochs for n in lr_noise] if len(noise_range) == 1: noise_range = noise_range[0] else: noise_range = lr_noise * num_epochs else: noise_range = None lr_scheduler = None if args.sched == 'cosine': lr_scheduler = CosineLRScheduler( optimizer, t_initial=num_epochs, t_mul=getattr(args, 'lr_cycle_mul', 1.), lr_min=args.min_lr, decay_rate=args.decay_rate, warmup_lr_init=args.warmup_lr, warmup_t=args.warmup_epochs, cycle_limit=getattr(args, 'lr_cycle_limit', 1), t_in_epochs=True, noise_range_t=noise_range, noise_pct=getattr(args, 'lr_noise_pct', 0.67), noise_std=getattr(args, 'lr_noise_std', 1.), noise_seed=getattr(args, 'seed', 42), ) num_epochs = lr_scheduler.get_cycle_length() + args.cooldown_epochs elif args.sched == 'tanh': lr_scheduler = TanhLRScheduler( optimizer, t_initial=num_epochs, t_mul=getattr(args, 'lr_cycle_mul', 1.), lr_min=args.min_lr, warmup_lr_init=args.warmup_lr, warmup_t=args.warmup_epochs, cycle_limit=getattr(args, 'lr_cycle_limit', 1), t_in_epochs=True, noise_range_t=noise_range, noise_pct=getattr(args, 'lr_noise_pct', 0.67), noise_std=getattr(args, 'lr_noise_std', 1.), noise_seed=getattr(args, 'seed', 42), ) num_epochs = lr_scheduler.get_cycle_length() + args.cooldown_epochs elif args.sched == 'step': lr_scheduler = StepLRScheduler( optimizer, decay_t=args.decay_epochs, decay_rate=args.decay_rate, warmup_lr_init=args.warmup_lr, warmup_t=args.warmup_epochs, noise_range_t=noise_range, noise_pct=getattr(args, 'lr_noise_pct', 0.67), noise_std=getattr(args, 'lr_noise_std', 1.), noise_seed=getattr(args, 'seed', 42), ) elif args.sched == 'plateau': mode = 'min' if 'loss' in getattr(args, 'eval_metric', '') else 'max' lr_scheduler = PlateauLRScheduler( optimizer, decay_rate=args.decay_rate, patience_t=args.patience_epochs, lr_min=args.min_lr, mode=mode, warmup_lr_init=args.warmup_lr, warmup_t=args.warmup_epochs, cooldown_t=0, noise_range_t=noise_range, noise_pct=getattr(args, 'lr_noise_pct', 0.67), noise_std=getattr(args, 'lr_noise_std', 1.), noise_seed=getattr(args, 'seed', 42), ) return lr_scheduler, num_epochs

true

1c2fbd7e9cc84b577c89dfb84de3fe84522eb5fe

2,636

py

Python

Missions_to_Mars/.history/scrape_mars_20200809061221.py

ermiasgelaye/web-scraping-challenge

f99c3436dfb0169595c46dae7733d90e21385cc6

[ "ADSL" ]

null

Missions_to_Mars/.history/scrape_mars_20200809061221.py

ermiasgelaye/web-scraping-challenge

f99c3436dfb0169595c46dae7733d90e21385cc6

[ "ADSL" ]

null

Missions_to_Mars/.history/scrape_mars_20200809061221.py

ermiasgelaye/web-scraping-challenge

f99c3436dfb0169595c46dae7733d90e21385cc6

[ "ADSL" ]

2

2020-11-02T08:12:16.000Z

2021-05-17T21:45:42.000Z

# Dependencies import numpy as np import pandas as pd from bs4 import BeautifulSoup as bs import requests from splinter import Browser import re import time # Initialize browser def init_browser(): executable_path = {"executable_path": "/usr/local/bin/chromedriver"} #executable_path = {'executable_path': 'chromedriver.exe'} return Browser("chrome", **executable_path, headless=False) def scrape(): browser = init_browser() url = 'https://mars.nasa.gov/news/' browser.visit(url) html = browser.html soup = bs(html, 'html.parser') news_title = soup.find('div', class_='content_title').text news_p = soup.find('div', class_='article_teaser_body').text url = 'https://www.jpl.nasa.gov/spaceimages/' browser.visit(url) html = browser.html soup = bs(html, 'html.parser') base_url = 'https://www.jpl.nasa.gov' image_url = soup.find("a", class_="button fancybox")["data-fancybox-href"] featured_image_url = base_url + image_url url = 'https://twitter.com/marswxreport?lang=en' browser.visit(url) html = browser.html soup = bs(html, "html.parser") mars_weather = soup.find(text=re.compile("InSight sol")) url = 'https://space-facts.com/mars/' browser.visit(url) tables = pd.read_html(url) facts_df = tables[0] facts_df.columns = ['Fact', 'Value'] facts_df['Fact'] = facts_df['Fact'].str.replace(':', '') facts_df.reset_index(drop=True, inplace=True) facts_html = facts_df.to_html() hemisphere_img_urls = [] url = 'https://astrogeology.usgs.gov/search/results?q=hemisphere+enhanced&k1=target&v1=Mars' browser.visit(url) html = browser.html soup = bs(html, 'html.parser') results = soup.find_all('div', class_="description") base_url = 'https://astrogeology.usgs.gov/' sites = [] for result in results: link = result.find('a', class_="itemLink product-item") link_text = link['href'] hemispheres_url = base_url + link_text sites.append(hemispheres_url) hemispheres = [] for site in sites: browser.visit(site) html = browser.html soup = bs(html, 'html.parser') title = soup.find('h2', class_="title").text.strip() url = soup.find_all('a', target="_blank", href=True)[0]['href'] hemispheres.append({"title": title, "img_url": url}) output = { "news_title": news_title, "news_p": news_p, "featured_image_url": featured_image_url, "mars_weather": mars_weather, "facts_html": facts_html, "hemispheres": hemispheres } return output

31.759036

96

0.649469

import numpy as np import pandas as pd from bs4 import BeautifulSoup as bs import requests from splinter import Browser import re import time def init_browser(): executable_path = {"executable_path": "/usr/local/bin/chromedriver"} return Browser("chrome", **executable_path, headless=False) def scrape(): browser = init_browser() url = 'https://mars.nasa.gov/news/' browser.visit(url) html = browser.html soup = bs(html, 'html.parser') news_title = soup.find('div', class_='content_title').text news_p = soup.find('div', class_='article_teaser_body').text url = 'https://www.jpl.nasa.gov/spaceimages/' browser.visit(url) html = browser.html soup = bs(html, 'html.parser') base_url = 'https://www.jpl.nasa.gov' image_url = soup.find("a", class_="button fancybox")["data-fancybox-href"] featured_image_url = base_url + image_url url = 'https://twitter.com/marswxreport?lang=en' browser.visit(url) html = browser.html soup = bs(html, "html.parser") mars_weather = soup.find(text=re.compile("InSight sol")) url = 'https://space-facts.com/mars/' browser.visit(url) tables = pd.read_html(url) facts_df = tables[0] facts_df.columns = ['Fact', 'Value'] facts_df['Fact'] = facts_df['Fact'].str.replace(':', '') facts_df.reset_index(drop=True, inplace=True) facts_html = facts_df.to_html() hemisphere_img_urls = [] url = 'https://astrogeology.usgs.gov/search/results?q=hemisphere+enhanced&k1=target&v1=Mars' browser.visit(url) html = browser.html soup = bs(html, 'html.parser') results = soup.find_all('div', class_="description") base_url = 'https://astrogeology.usgs.gov/' sites = [] for result in results: link = result.find('a', class_="itemLink product-item") link_text = link['href'] hemispheres_url = base_url + link_text sites.append(hemispheres_url) hemispheres = [] for site in sites: browser.visit(site) html = browser.html soup = bs(html, 'html.parser') title = soup.find('h2', class_="title").text.strip() url = soup.find_all('a', target="_blank", href=True)[0]['href'] hemispheres.append({"title": title, "img_url": url}) output = { "news_title": news_title, "news_p": news_p, "featured_image_url": featured_image_url, "mars_weather": mars_weather, "facts_html": facts_html, "hemispheres": hemispheres } return output

true

1c2fbd99e8a358645cbd1a49f7f62034df8161ae

5,189

py

Python

condoor/actions.py

kstaniek/condoor-ng

adbe6d37b5978e17237e41051525ab59c589adbc

[ "Apache-2.0" ]

null

condoor/actions.py

kstaniek/condoor-ng

adbe6d37b5978e17237e41051525ab59c589adbc

[ "Apache-2.0" ]

6

2016-12-07T05:55:13.000Z

2017-01-07T02:52:55.000Z

condoor/actions.py

kstaniek/condoor-ng

adbe6d37b5978e17237e41051525ab59c589adbc

[ "Apache-2.0" ]

null

"""Provides predefined actions for Finite State Machines.""" import logging from condoor.fsm import action from condoor.exceptions import ConnectionAuthenticationError, ConnectionError, ConnectionTimeoutError @action def a_send_line(text, ctx): """Send text line to the controller followed by `os.linesep`.""" ctx.ctrl.sendline(text) return True @action def a_send(text, ctx): """Send text line to the controller.""" ctx.ctrl.send(text) return True @action def a_send_username(username, ctx): """Sent the username text.""" if username: ctx.ctrl.sendline(username) return True else: ctx.ctrl.disconnect() raise ConnectionAuthenticationError("Username not provided", ctx.ctrl.hostname) @action def a_send_password(password, ctx): """Send the password text. Before sending the password local echo is disabled. If password not provided it disconnects from the device and raises ConnectionAuthenticationError exception. """ if password: # ctx.ctrl.setecho(False) ctx.ctrl.sendline(password) # ctx.ctrl.setecho(True) return True else: ctx.ctrl.disconnect() raise ConnectionAuthenticationError("Password not provided", ctx.ctrl.hostname) @action def a_authentication_error(ctx): """Raise ConnectionAuthenticationError exception and disconnect.""" ctx.ctrl.disconnect() raise ConnectionAuthenticationError("Authentication failed", ctx.ctrl.hostname) @action def a_unable_to_connect(ctx): """Provide detailed information about the session (before, after) when unable to connect. The state machine finishes without exception """ message = "{}{}".format(ctx.ctrl.before, ctx.ctrl.after) ctx.msg = message.strip().splitlines()[-1] ctx.device.last_error_msg = ctx.msg # ctx.msg = "{}{}".format(ctx.ctrl.before, ctx.ctrl.after) return False @action def a_standby_console(ctx): """Raise ConnectionError exception when connected to standby console.""" ctx.device.is_console = True raise ConnectionError("Standby console", ctx.ctrl.hostname) @action def a_disconnect(ctx): """Disconnect from the device when device is reloading.""" ctx.msg = "Device is reloading" ctx.ctrl.disconnect() return True @action def a_reload_na(ctx): """Provide the message when the reload is not possible.""" ctx.msg = "Reload to the ROM monitor disallowed from a telnet line. " \ "Set the configuration register boot bits to be non-zero." ctx.failed = True return False @action def a_connection_closed(ctx): """Provide message when connection is closed by remote host.""" ctx.msg = "Device disconnected" ctx.device.connected = False # do not stop FSM to detect the jumphost prompt return True @action def a_stays_connected(ctx): """Stay connected.""" ctx.ctrl.connected = True ctx.device.connected = False return True @action def a_unexpected_prompt(ctx): """Provide message when received humphost prompt.""" prompt = ctx.ctrl.after ctx.msg = "Received the jump host prompt: '{}'".format(prompt) ctx.device.connected = False ctx.finished = True raise ConnectionError("Unable to connect to the device.", ctx.ctrl.hostname) @action def a_connection_timeout(ctx): """Checks the prompt and update the drivers.""" prompt = ctx.ctrl.after ctx.msg = "Received the jump host prompt: '{}'".format(prompt) print(ctx.msg) ctx.device.connected = False ctx.finished = True raise ConnectionTimeoutError("Unable to connect to the device.", ctx.ctrl.hostname) @action def a_expected_prompt(ctx): """Update driver, config mode and hostname when received an expected prompt.""" prompt = ctx.ctrl.after ctx.device.update_driver(prompt) ctx.device.update_config_mode() ctx.device.update_hostname() ctx.finished = True return True @action def a_save_last_pattern(obj, ctx): """Save last pattern in the context.""" obj.last_pattern = ctx.pattern return True @action def a_send_boot(rommon_boot_command, ctx): """Send boot command.""" ctx.ctrl.sendline(rommon_boot_command) return True @action def a_reconnect(ctx): """Reconnect.""" ctx.device.connect(ctx.ctrl) return True @action def a_return_and_reconnect(ctx): """Send new line and reconnect.""" ctx.ctrl.send("\r") ctx.ctrl.connect(ctx.device) return True @action def a_store_cmd_result(ctx): """Store the command result for complex state machines. It is useful when exact command output is embedded in another commands, i.e. admin show inventory in eXR. """ result = ctx.ctrl.before # check if multi line index = result.find('\n') if index > 0: # remove first line result = result[index + 1:] ctx.device.last_command_result = result.replace('\r', '') return True @action def a_message_callback(ctx): """Message the captured pattern.""" message = ctx.ctrl.after.strip().splitlines()[-1] ctx.device.chain.connection.emit_message(message, log_level=logging.INFO) return True

26.747423

111

0.695895

import logging from condoor.fsm import action from condoor.exceptions import ConnectionAuthenticationError, ConnectionError, ConnectionTimeoutError @action def a_send_line(text, ctx): ctx.ctrl.sendline(text) return True @action def a_send(text, ctx): ctx.ctrl.send(text) return True @action def a_send_username(username, ctx): if username: ctx.ctrl.sendline(username) return True else: ctx.ctrl.disconnect() raise ConnectionAuthenticationError("Username not provided", ctx.ctrl.hostname) @action def a_send_password(password, ctx): if password: ctx.ctrl.sendline(password) return True else: ctx.ctrl.disconnect() raise ConnectionAuthenticationError("Password not provided", ctx.ctrl.hostname) @action def a_authentication_error(ctx): ctx.ctrl.disconnect() raise ConnectionAuthenticationError("Authentication failed", ctx.ctrl.hostname) @action def a_unable_to_connect(ctx): message = "{}{}".format(ctx.ctrl.before, ctx.ctrl.after) ctx.msg = message.strip().splitlines()[-1] ctx.device.last_error_msg = ctx.msg return False @action def a_standby_console(ctx): ctx.device.is_console = True raise ConnectionError("Standby console", ctx.ctrl.hostname) @action def a_disconnect(ctx): ctx.msg = "Device is reloading" ctx.ctrl.disconnect() return True @action def a_reload_na(ctx): ctx.msg = "Reload to the ROM monitor disallowed from a telnet line. " \ "Set the configuration register boot bits to be non-zero." ctx.failed = True return False @action def a_connection_closed(ctx): ctx.msg = "Device disconnected" ctx.device.connected = False return True @action def a_stays_connected(ctx): ctx.ctrl.connected = True ctx.device.connected = False return True @action def a_unexpected_prompt(ctx): prompt = ctx.ctrl.after ctx.msg = "Received the jump host prompt: '{}'".format(prompt) ctx.device.connected = False ctx.finished = True raise ConnectionError("Unable to connect to the device.", ctx.ctrl.hostname) @action def a_connection_timeout(ctx): prompt = ctx.ctrl.after ctx.msg = "Received the jump host prompt: '{}'".format(prompt) print(ctx.msg) ctx.device.connected = False ctx.finished = True raise ConnectionTimeoutError("Unable to connect to the device.", ctx.ctrl.hostname) @action def a_expected_prompt(ctx): prompt = ctx.ctrl.after ctx.device.update_driver(prompt) ctx.device.update_config_mode() ctx.device.update_hostname() ctx.finished = True return True @action def a_save_last_pattern(obj, ctx): obj.last_pattern = ctx.pattern return True @action def a_send_boot(rommon_boot_command, ctx): ctx.ctrl.sendline(rommon_boot_command) return True @action def a_reconnect(ctx): ctx.device.connect(ctx.ctrl) return True @action def a_return_and_reconnect(ctx): ctx.ctrl.send("\r") ctx.ctrl.connect(ctx.device) return True @action def a_store_cmd_result(ctx): result = ctx.ctrl.before index = result.find('\n') if index > 0: result = result[index + 1:] ctx.device.last_command_result = result.replace('\r', '') return True @action def a_message_callback(ctx): message = ctx.ctrl.after.strip().splitlines()[-1] ctx.device.chain.connection.emit_message(message, log_level=logging.INFO) return True

true

1c2fbe6b562df5257fec1a80f3d6038e91915a3f

3,740

py

Python

staves/runtimes/docker.py

digitalernachschub/staves

8b96e018ebd79e18b446e931eb8a04dc5e3a8a87

[ "Apache-2.0" ]

11

2020-05-14T16:25:34.000Z

2022-01-06T07:25:37.000Z

staves/runtimes/docker.py

digitalernachschub/staves

8b96e018ebd79e18b446e931eb8a04dc5e3a8a87

[ "Apache-2.0" ]

null

staves/runtimes/docker.py

digitalernachschub/staves

8b96e018ebd79e18b446e931eb8a04dc5e3a8a87

[ "Apache-2.0" ]

null

import io import json import logging import os import socket import struct import tarfile from dataclasses import asdict from pathlib import Path from typing import Mapping import docker from docker.types import Mount import staves.builders.gentoo as gentoo_builder from staves.builders.gentoo import ImageSpec logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) def run( builder: str, portage: str, build_cache: str, image_spec: ImageSpec, image_path: Path, stdlib: bool = False, ssh: bool = False, netrc: bool = False, env: Mapping[str, str] = None, ): docker_client = docker.from_env() mounts = [ Mount( type="volume", source=build_cache, target="/var/cache/binpkgs", ) ] if ssh: ssh_dir = str(Path.home().joinpath(".ssh")) mounts += [ Mount(type="bind", source=ssh_dir, target="/root/.ssh", read_only=True), Mount( type="bind", source=ssh_dir, target="/var/tmp/portage/.ssh", read_only=True, ), ] if netrc: netrc_path = str(Path.home().joinpath(".ssh")) mounts += [ Mount( type="bind", source=netrc_path, target="/root/.netrc", read_only=True ), Mount( type="bind", source=netrc_path, target="/var/tmp/portage/.netrc", read_only=True, ), ] logger.debug("Starting docker container with the following mounts:") for mount in mounts: logger.debug(str(mount)) for log_output in docker_client.api.pull(portage, stream=True, decode=True): print(log_output) portage_container = docker_client.containers.create( portage, auto_remove=True, ) args = [] if stdlib: args += ["--stdlib"] container = docker_client.containers.create( builder, entrypoint=["/usr/bin/python", "/staves.py"], command=args, mounts=mounts, detach=True, environment=env, stdin_open=True, volumes_from=[portage_container.id + ":ro"], ) bundle_file = io.BytesIO() with tarfile.TarFile(fileobj=bundle_file, mode="x") as archive: builder_runtime_path = os.path.abspath(gentoo_builder.__file__) archive.add(builder_runtime_path, arcname="staves.py") bundle_file.seek(0) bundle_content = bundle_file.read() container.put_archive("/", bundle_content) container.start() container_input = container.attach_socket(params={"stdin": 1, "stream": 1}) serialized_image_spec = json.dumps( dict( locale=asdict(image_spec.locale), global_env=image_spec.global_env, package_envs=image_spec.package_envs, repositories=[asdict(repository) for repository in image_spec.repositories], package_configs=image_spec.package_configs, packages_to_be_installed=image_spec.packages_to_be_installed, ) ).encode() content_length = struct.pack(">Q", len(serialized_image_spec)) content = content_length + serialized_image_spec container_input._sock.send(content) container_input._sock.shutdown(socket.SHUT_RDWR) container_input.close() for line in container.logs(stream=True): print(line.decode(), end="") container.stop() container.wait() image_chunks, _ = container.get_archive("/tmp/rootfs") with image_path.open(mode="wb") as image_archive: for chunk in image_chunks: image_archive.write(chunk) container.remove() portage_container.remove()

30.655738

88

0.622727

import io import json import logging import os import socket import struct import tarfile from dataclasses import asdict from pathlib import Path from typing import Mapping import docker from docker.types import Mount import staves.builders.gentoo as gentoo_builder from staves.builders.gentoo import ImageSpec logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) def run( builder: str, portage: str, build_cache: str, image_spec: ImageSpec, image_path: Path, stdlib: bool = False, ssh: bool = False, netrc: bool = False, env: Mapping[str, str] = None, ): docker_client = docker.from_env() mounts = [ Mount( type="volume", source=build_cache, target="/var/cache/binpkgs", ) ] if ssh: ssh_dir = str(Path.home().joinpath(".ssh")) mounts += [ Mount(type="bind", source=ssh_dir, target="/root/.ssh", read_only=True), Mount( type="bind", source=ssh_dir, target="/var/tmp/portage/.ssh", read_only=True, ), ] if netrc: netrc_path = str(Path.home().joinpath(".ssh")) mounts += [ Mount( type="bind", source=netrc_path, target="/root/.netrc", read_only=True ), Mount( type="bind", source=netrc_path, target="/var/tmp/portage/.netrc", read_only=True, ), ] logger.debug("Starting docker container with the following mounts:") for mount in mounts: logger.debug(str(mount)) for log_output in docker_client.api.pull(portage, stream=True, decode=True): print(log_output) portage_container = docker_client.containers.create( portage, auto_remove=True, ) args = [] if stdlib: args += ["--stdlib"] container = docker_client.containers.create( builder, entrypoint=["/usr/bin/python", "/staves.py"], command=args, mounts=mounts, detach=True, environment=env, stdin_open=True, volumes_from=[portage_container.id + ":ro"], ) bundle_file = io.BytesIO() with tarfile.TarFile(fileobj=bundle_file, mode="x") as archive: builder_runtime_path = os.path.abspath(gentoo_builder.__file__) archive.add(builder_runtime_path, arcname="staves.py") bundle_file.seek(0) bundle_content = bundle_file.read() container.put_archive("/", bundle_content) container.start() container_input = container.attach_socket(params={"stdin": 1, "stream": 1}) serialized_image_spec = json.dumps( dict( locale=asdict(image_spec.locale), global_env=image_spec.global_env, package_envs=image_spec.package_envs, repositories=[asdict(repository) for repository in image_spec.repositories], package_configs=image_spec.package_configs, packages_to_be_installed=image_spec.packages_to_be_installed, ) ).encode() content_length = struct.pack(">Q", len(serialized_image_spec)) content = content_length + serialized_image_spec container_input._sock.send(content) container_input._sock.shutdown(socket.SHUT_RDWR) container_input.close() for line in container.logs(stream=True): print(line.decode(), end="") container.stop() container.wait() image_chunks, _ = container.get_archive("/tmp/rootfs") with image_path.open(mode="wb") as image_archive: for chunk in image_chunks: image_archive.write(chunk) container.remove() portage_container.remove()

true

1c2fbea4b7cf369327216abf4b9b0f4d2b266cd6

3,661

py

Python

build/PureCloudPlatformClientV2/models/week_shift_trade_list_response.py

cjohnson-ctl/platform-client-sdk-python

38ce53bb8012b66e8a43cc8bd6ff00cf6cc99100

[ "MIT" ]

10

2019-02-22T00:27:08.000Z

2021-09-12T23:23:44.000Z

libs/PureCloudPlatformClientV2/models/week_shift_trade_list_response.py

rocketbot-cl/genesysCloud

dd9d9b5ebb90a82bab98c0d88b9585c22c91f333

[ "MIT" ]

5

2018-06-07T08:32:00.000Z

2021-07-28T17:37:26.000Z

libs/PureCloudPlatformClientV2/models/week_shift_trade_list_response.py

rocketbot-cl/genesysCloud

dd9d9b5ebb90a82bab98c0d88b9585c22c91f333

[ "MIT" ]

6

2020-04-09T17:43:07.000Z

2022-02-17T08:48:05.000Z

# coding: utf-8 """ Copyright 2016 SmartBear Software 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. Ref: https://github.com/swagger-api/swagger-codegen """ from pprint import pformat from six import iteritems import re import json from ..utils import sanitize_for_serialization class WeekShiftTradeListResponse(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ def __init__(self): """ WeekShiftTradeListResponse - a model defined in Swagger :param dict swaggerTypes: The key is attribute name and the value is attribute type. :param dict attributeMap: The key is attribute name and the value is json key in definition. """ self.swagger_types = { 'entities': 'list[WeekShiftTradeResponse]' } self.attribute_map = { 'entities': 'entities' } self._entities = None @property def entities(self): """ Gets the entities of this WeekShiftTradeListResponse. :return: The entities of this WeekShiftTradeListResponse. :rtype: list[WeekShiftTradeResponse] """ return self._entities @entities.setter def entities(self, entities): """ Sets the entities of this WeekShiftTradeListResponse. :param entities: The entities of this WeekShiftTradeListResponse. :type: list[WeekShiftTradeResponse] """ self._entities = entities def to_dict(self): """ Returns the model properties as a dict """ result = {} for attr, _ in iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_json(self): """ Returns the model as raw JSON """ return json.dumps(sanitize_for_serialization(self.to_dict())) def to_str(self): """ Returns the string representation of the model """ return pformat(self.to_dict()) def __repr__(self): """ For `print` and `pprint` """ return self.to_str() def __eq__(self, other): """ Returns true if both objects are equal """ return self.__dict__ == other.__dict__ def __ne__(self, other): """ Returns true if both objects are not equal """ return not self == other

27.946565

77

0.580716

from pprint import pformat from six import iteritems import re import json from ..utils import sanitize_for_serialization class WeekShiftTradeListResponse(object): def __init__(self): self.swagger_types = { 'entities': 'list[WeekShiftTradeResponse]' } self.attribute_map = { 'entities': 'entities' } self._entities = None @property def entities(self): return self._entities @entities.setter def entities(self, entities): self._entities = entities def to_dict(self): result = {} for attr, _ in iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_json(self): return json.dumps(sanitize_for_serialization(self.to_dict())) def to_str(self): return pformat(self.to_dict()) def __repr__(self): return self.to_str() def __eq__(self, other): return self.__dict__ == other.__dict__ def __ne__(self, other): return not self == other

true

1c2fbf246556300f28b607ea53fca3967c6adc28

7,777

py

Python

build/python-env/lib/python2.7/site-packages/docker/models/networks.py

imiMoisesEducation/beatcookie-discbot

59c8be23346d8d2fc1777a2b08856df88e2ae5c2

[ "Apache-2.0" ]

20

2018-05-08T20:41:48.000Z

2019-08-15T02:15:58.000Z

build/python-env/lib/python2.7/site-packages/docker/models/networks.py

imiMoisesEducation/beatcookie-discbot

59c8be23346d8d2fc1777a2b08856df88e2ae5c2

[ "Apache-2.0" ]

2

2021-02-02T22:48:24.000Z

2021-06-02T02:04:53.000Z

build/python-env/lib/python2.7/site-packages/docker/models/networks.py

imiMoisesEducation/beatcookie-discbot

59c8be23346d8d2fc1777a2b08856df88e2ae5c2

[ "Apache-2.0" ]

5

2018-07-03T03:15:01.000Z

2020-09-10T06:30:27.000Z

from ..api import APIClient from ..utils import version_gte from .containers import Container from .resource import Model, Collection class Network(Model): """ A Docker network. """ @property def name(self): """ The name of the network. """ return self.attrs.get('Name') @property def containers(self): """ The containers that are connected to the network, as a list of :py:class:`~docker.models.containers.Container` objects. """ return [ self.client.containers.get(cid) for cid in (self.attrs.get('Containers') or {}).keys() ] def connect(self, container, *args, **kwargs): """ Connect a container to this network. Args: container (str): Container to connect to this network, as either an ID, name, or :py:class:`~docker.models.containers.Container` object. aliases (:py:class:`list`): A list of aliases for this endpoint. Names in that list can be used within the network to reach the container. Defaults to ``None``. links (:py:class:`list`): A list of links for this endpoint. Containers declared in this list will be linkedto this container. Defaults to ``None``. ipv4_address (str): The IP address of this container on the network, using the IPv4 protocol. Defaults to ``None``. ipv6_address (str): The IP address of this container on the network, using the IPv6 protocol. Defaults to ``None``. link_local_ips (:py:class:`list`): A list of link-local (IPv4/IPv6) addresses. Raises: :py:class:`docker.errors.APIError` If the server returns an error. """ if isinstance(container, Container): container = container.id return self.client.api.connect_container_to_network( container, self.id, *args, **kwargs ) def disconnect(self, container, *args, **kwargs): """ Disconnect a container from this network. Args: container (str): Container to disconnect from this network, as either an ID, name, or :py:class:`~docker.models.containers.Container` object. force (bool): Force the container to disconnect from a network. Default: ``False`` Raises: :py:class:`docker.errors.APIError` If the server returns an error. """ if isinstance(container, Container): container = container.id return self.client.api.disconnect_container_from_network( container, self.id, *args, **kwargs ) def remove(self): """ Remove this network. Raises: :py:class:`docker.errors.APIError` If the server returns an error. """ return self.client.api.remove_network(self.id) class NetworkCollection(Collection): """ Networks on the Docker server. """ model = Network def create(self, name, *args, **kwargs): """ Create a network. Similar to the ``docker network create``. Args: name (str): Name of the network driver (str): Name of the driver used to create the network options (dict): Driver options as a key-value dictionary ipam (IPAMConfig): Optional custom IP scheme for the network. check_duplicate (bool): Request daemon to check for networks with same name. Default: ``None``. internal (bool): Restrict external access to the network. Default ``False``. labels (dict): Map of labels to set on the network. Default ``None``. enable_ipv6 (bool): Enable IPv6 on the network. Default ``False``. attachable (bool): If enabled, and the network is in the global scope, non-service containers on worker nodes will be able to connect to the network. scope (str): Specify the network's scope (``local``, ``global`` or ``swarm``) ingress (bool): If set, create an ingress network which provides the routing-mesh in swarm mode. Returns: (:py:class:`Network`): The network that was created. Raises: :py:class:`docker.errors.APIError` If the server returns an error. Example: A network using the bridge driver: >>> client.networks.create("network1", driver="bridge") You can also create more advanced networks with custom IPAM configurations. For example, setting the subnet to ``192.168.52.0/24`` and gateway address to ``192.168.52.254``. .. code-block:: python >>> ipam_pool = docker.types.IPAMPool( subnet='192.168.52.0/24', gateway='192.168.52.254' ) >>> ipam_config = docker.types.IPAMConfig( pool_configs=[ipam_pool] ) >>> client.networks.create( "network1", driver="bridge", ipam=ipam_config ) """ resp = self.client.api.create_network(name, *args, **kwargs) return self.get(resp['Id']) def get(self, network_id, *args, **kwargs): """ Get a network by its ID. Args: network_id (str): The ID of the network. verbose (bool): Retrieve the service details across the cluster in swarm mode. scope (str): Filter the network by scope (``swarm``, ``global`` or ``local``). Returns: (:py:class:`Network`) The network. Raises: :py:class:`docker.errors.NotFound` If the network does not exist. :py:class:`docker.errors.APIError` If the server returns an error. """ return self.prepare_model( self.client.api.inspect_network(network_id, *args, **kwargs) ) def list(self, *args, **kwargs): """ List networks. Similar to the ``docker networks ls`` command. Args: names (:py:class:`list`): List of names to filter by. ids (:py:class:`list`): List of ids to filter by. filters (dict): Filters to be processed on the network list. Available filters: - ``driver=[<driver-name>]`` Matches a network's driver. - ``label=[<key>]`` or ``label=[<key>=<value>]``. - ``type=["custom"|"builtin"]`` Filters networks by type. greedy (bool): Fetch more details for each network individually. You might want this to get the containers attached to them. Returns: (list of :py:class:`Network`) The networks on the server. Raises: :py:class:`docker.errors.APIError` If the server returns an error. """ greedy = kwargs.pop('greedy', False) resp = self.client.api.networks(*args, **kwargs) networks = [self.prepare_model(item) for item in resp] if greedy and version_gte(self.client.api._version, '1.28'): for net in networks: net.reload() return networks def prune(self, filters=None): self.client.api.prune_networks(filters=filters) prune.__doc__ = APIClient.prune_networks.__doc__

36.00463

79

0.555098

from ..api import APIClient from ..utils import version_gte from .containers import Container from .resource import Model, Collection class Network(Model): @property def name(self): return self.attrs.get('Name') @property def containers(self): return [ self.client.containers.get(cid) for cid in (self.attrs.get('Containers') or {}).keys() ] def connect(self, container, *args, **kwargs): if isinstance(container, Container): container = container.id return self.client.api.connect_container_to_network( container, self.id, *args, **kwargs ) def disconnect(self, container, *args, **kwargs): if isinstance(container, Container): container = container.id return self.client.api.disconnect_container_from_network( container, self.id, *args, **kwargs ) def remove(self): return self.client.api.remove_network(self.id) class NetworkCollection(Collection): model = Network def create(self, name, *args, **kwargs): resp = self.client.api.create_network(name, *args, **kwargs) return self.get(resp['Id']) def get(self, network_id, *args, **kwargs): return self.prepare_model( self.client.api.inspect_network(network_id, *args, **kwargs) ) def list(self, *args, **kwargs): greedy = kwargs.pop('greedy', False) resp = self.client.api.networks(*args, **kwargs) networks = [self.prepare_model(item) for item in resp] if greedy and version_gte(self.client.api._version, '1.28'): for net in networks: net.reload() return networks def prune(self, filters=None): self.client.api.prune_networks(filters=filters) prune.__doc__ = APIClient.prune_networks.__doc__

true

1c2fbffd53700052b6c2bf61434722bcee5798b7

1,336

py

Python

setup.py

albmarin/pcuf

90fe58a5373d4afb46d95486ced91976e13e2f90

[ "BSD-3-Clause" ]

null

setup.py

albmarin/pcuf

90fe58a5373d4afb46d95486ced91976e13e2f90

[ "BSD-3-Clause" ]

247

2020-02-19T05:55:58.000Z

2022-03-28T13:43:12.000Z

setup.py

albmarin/pcuf

90fe58a5373d4afb46d95486ced91976e13e2f90

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """The setup script.""" from setuptools import setup, find_packages with open("README.rst") as readme_file: readme = readme_file.read() with open("HISTORY.rst") as history_file: history = history_file.read() requirements = [ "xlrd>=1.2.0", "pandas>=0.24.1", "requests>=2.21.0", "click>=7.0", "openpyxl>=2.5.12", ] setup_requirements = ["pytest-runner"] test_requirements = ["pytest"] setup( author="Alberto J. Marin", author_email="alberto@ajmar.in", classifiers=[ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Natural Language :: English", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", ], description="A personal collection of useful and frequently used Python functions.", install_requires=requirements, license="BSD license", long_description=readme + "\n\n" + history, include_package_data=True, keywords="pcuf", name="pcuf", packages=find_packages(), setup_requires=setup_requirements, test_suite="tests", tests_require=test_requirements, url="https://github.com/git-albertomarin/pcuf", version="0.1.9", zip_safe=False, )

25.692308

88

0.643713

from setuptools import setup, find_packages with open("README.rst") as readme_file: readme = readme_file.read() with open("HISTORY.rst") as history_file: history = history_file.read() requirements = [ "xlrd>=1.2.0", "pandas>=0.24.1", "requests>=2.21.0", "click>=7.0", "openpyxl>=2.5.12", ] setup_requirements = ["pytest-runner"] test_requirements = ["pytest"] setup( author="Alberto J. Marin", author_email="alberto@ajmar.in", classifiers=[ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Natural Language :: English", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", ], description="A personal collection of useful and frequently used Python functions.", install_requires=requirements, license="BSD license", long_description=readme + "\n\n" + history, include_package_data=True, keywords="pcuf", name="pcuf", packages=find_packages(), setup_requires=setup_requirements, test_suite="tests", tests_require=test_requirements, url="https://github.com/git-albertomarin/pcuf", version="0.1.9", zip_safe=False, )

true

1c2fc0173c6d37b75e054681031b636b7288fb33

8,657

py

Python

2015/day_03/day_03_part_2.py

Sancti0n/advent-of-code

360c20f63c2308439e2e191c60b7164be86c4d4a

[ "MIT" ]

null

2015/day_03/day_03_part_2.py

Sancti0n/advent-of-code

360c20f63c2308439e2e191c60b7164be86c4d4a

[ "MIT" ]

null

2015/day_03/day_03_part_2.py

Sancti0n/advent-of-code

360c20f63c2308439e2e191c60b7164be86c4d4a

[ "MIT" ]

null

path = 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t = [] x1, y1, x2, y2 = 0, 0, 0, 0 for i in range(len(path)): if i%2 == 0: if path[i] == '^': x2+=1 if path[i] == 'v': x2-=1 if path[i] == '>': y2+=1 if path[i] == '<': y2-=1 t.append(str(x2)+'/'+str(y2)) if i%2 == 1: if path[i] == '^': x1+=1 if path[i] == 'v': x1-=1 if path[i] == '>': y1+=1 if path[i] == '<': y1-=1 t.append(str(x1)+'/'+str(y1)) print(len(set(t)))

480.944444

8,201

0.258866

path = '^^<<v<<v><v^^<><>^^<v<v^>>^^^><^>v^>v><><><<vv^^<^>^^<v^>v>v^v>>>^<>v<^<v^><^>>>>><<v>>^>>^>v^>><<^>v>v<>^v^v^vvv><>^^>v><v<><>^><^^<vv^v<v>^v>>^v^>v><>v^<vv>^><<v^>vv^<<>v>>><<<>>^<vv<^<>^^vv>>>^><<<<vv^v^>>><><^>v<>^>v<v^v<^vv><^v^><<<<>^<>v>^v>v<v<v<<>v<^<<<v>>>>>^^v>vv^^<>^<>^^^^<^^^v<v^^>v<^^v^^>v>^v^^^^>><<v<>v<>^v^<v<>><>^^><<^^<^^>vv<>v^<^v<vv<<<>^>^^>^<>v^^vv<>>v><<<>vvv<>v<>><^<^v<>^vv>^^v<v<v><^<>>vv<^>>^>>vv^v<vv^vv<^<<>>^v^<>^>>>>vv>^^>v>vv>v><^vv^<<v>^<<^^<v<v>vv<v^^<>^^v>^>>v><^<<vv<<v^vv^^^v>>v<<v^><vv^><vv<^vv<<vv^v<<^v<^^v>><<v^>>^^<>v>><<v<>>^^<v>>^^>>vvv^><<<<<^<^vv<^<><v<<>^^^<<<^>^^^<v<<vv>vv<>^<>v<^v>^<<<v<v<v>>^v<>>v<<^<<v<<>^<<<><><>^>>>>^>v^v<<v<v<<>>vv<^vvv^^^^<vv>vv>^v^^v^<v^v><^vv<^vv>v<^>vv<>>^>^><vv<><^>v>^v>vvv<>^>^v<><>vv>><^v^<><><v>>v^v^><^<^>vv>v<^>vvv>v<<<<<^<v<<vv<^^^<<>>^v<vv<^<>v>^<v<>><><>^<<v>v^>^<vv>><><>>^>^>><^<v>^^>^^>^^v^^<^v^^>v^^>>><<><v<v<<v^vv<><><>^<v>^<<^^v^>v>><>^^^><^vvv<^^^^^v><<><v<^^v><><>>^>vv<vvvv<<>>><v<^^^^v<<^><v>^vv<v^^v^vv<^^>^^<v>><<v^>v<^^>^<^<v<^^v>^<<v>^>>>^v<>v<^^^>vvv^v<<^><>>><vvv^<^^^<^>>v>>><v>^^vvv^vvv<^^^^v^v^<vv^<v>^<<^>v^v^<<><>><^v><v<><<>><<<>^v>v<>^<v^v>^vv>>^<>v^^<<v><^v>>v<>>^v^^>><^>v^<^v^^>><>v^>^v^v<<<v^<v^^v<^>v<><>vv>>>>^>v<>v<<<>^^>vv^v<><v^<>^<<<<>>^^>^v<v^v<<><>^v<>>^v^<<^<^>>>^vv<><v<^^<>v^>>v<^^v<v>>>^>><<><<<>><vv<v>>^v>><^<v><vv>^vv<v<>>><>v^><>vv<^^v^^^v<>><^vvv<<^<>v>>>v>><v><>>><>><v^><v^v<v>^v>v<v>>^^<^>^>v><>vv>^v><<>>>>>>>^<<^vv^^vvvv<^^><<<v<<>vvv<>^><<v<v^v^<<v>v<>>^<vv^<v<v>^<<^^vv>v>^<vv<<>v<v^<>v>>^v^^vvvv>^^>>v^v^^><<^>v>>^^>^<^^<>v<v>vv^vv>v<v>>^v<><^vv^<vv<v^^^v<^v^>>^v>>>^^<^<^>^v^>^>>>^v>^>^^^>>^<>v^^<>^v<<^^>^^<vv<>v<^v^>><^v^>^<>>^vv^vv^>v^<vvvvvv^>><^^<^v<^<v^<<^^<<v^<^>><>v><^v^v^^^v>v^<>^<<v<^^vvv<v>^^>^v^^<><vv^v^>v^<<>>vv<>>>>v>v<>^>>>v<>^^><v<v^^^<>^<^><>^><<v>><>^<<>>><<^<vvv<^><v>>^vv^v>><v<>vv^<<^^<<><v><<^<v<vv<<^v^vv>v^>>>v<<<<v<<>v>^vv<^v><v<v>v<^>^^vv>v><v>><<v<<v^v>>><>^<>><><<^<<^v^v<<v>v>v<v<^^>vv<^v^^^<v^<<<v<>v^><^v>^<^<v>>^<<<v>>v^<><>>^v<>vvv<vvvvv<^^><^>><^^>^>^v^vv<^><<^v>><^^v>^v<>^>vvvv><^>^<<v^^vv<v^^<><>v>^>>^<^<<<^v^^^>^>>^>><><<^>v^^<v>>v<<<<vvv<vvvv^<^<v^^<>^>vvv^<vv^v^v>^<<><v><^v^v^^^>^^>^vv<>v>>v^>vv^vv>v<^v^^>>^v^v<>>^^><<v<<>><>>>^>^<>^^v^^><^<>><<^<vv^^^^^>>vv^<v^<^>>>>v<<><<^>vv>vvv>^<><>>>>vv><<v^v<^^^<<^^^vv^<v<><><<<<>><<v^<>v>v^><>v^v^^><>v>v>^^v<^v<>>^^^^^<v>><v^>^^<v>><v^^>v<^<^>>>^><^^>><<>>^><>^^^>v^^^>^^v^<>^^><^>>><><^>>v<v^>v<^><v<v^<>v<^v>v^<^vv^^><<<><><^v^<v<^^>v>v^>>^^vv^<v>^v>^<^v<>^>^><^<v>^v><^<^<>v^^>^><>>><<v><<><>v<<^v^^<^><>^<><><v>v<^^<v<v>>^^<<>>^<v>><^><^<^>^^v<>v>>><><<>^>v><><<<<v^^^^v<>>^^^v>><<^v>^>>><vv^>>^vv<^<>>^<^^<^v>v<v<<<<<>^<<^<<<<<^<^>>^><<>><>v^v>^<^>v^<><vvv^>^v^v^v><^<v<>vv<<^<>^^^<>^v>^<v^^<v^v>v<>>^>v<<>v<>v^v>v<<<>>v>vv>>v<<>v<>v<^>^>^<v>>v>^>^^^<vv>v<<>>><v>^vvv^^>^^<^vv^^^^>v>^v^>v^^v^>>^v>^vv>^^v^<<<<>^<><^<^<<^^>v^^^v<>>vvv<v>>vv><v<v>^<^v>>^v<vv^<<v<vv><^^v^v>v<>^v<<<^^v^^^<^v>v^v^v>><vvv<<>v<>^v>vv^v>vv<<^v<v>^v>v>><^v<v<>v>>>><<<><vv><>^v^<^vvv>v<>><^v>^>><v>vv<><><>v><>>><^>vv>>^<>v^>>^><<<^><<>^v^>>><><>vv>^<>^>^v^^><^>>><<>v^<^vv>^<^vv>><v<>vv<v><><<^><>v<^^<^>vv^^^^vv<<v><>vv<><v>v<>>>>^><v><>^<><>v<>><<>^^vvv>^^^<><>>vvv^v>><>vv<vv>^^^v^<<>^^v<><<^^v<>^^>^<^^v>>v^v^^>>v>>>^<<^<>^>^^v>>>><vv<<>^v<<vv><<^^vv><^>vv<>>v<v>v^>v>>v^<vv<<<v><v^>vvv^^>vv^<<v>v^>>v^<>>><><<^^<^v>^>>>v>v>^v<>vv><vv<vvv<<v>v>^v<<<>><<><><>v^>>>v^>v^>>vv^^<v>^<>>><^>v^<>^^><v>v<><<<><v^v<<<v<v^>v^v>^>v<^<>v>v^^>>v>vv^v<>>^^^^<>v^>>>>>>>><v<^<<vvv<^v^>^v<^<<>>><<<^<<^>^>v^<>^<<<>v>><^vv^>^>^>>>^<vv><v^^^<v^<v<><v^vvv<>v<vvv^vv<<<v^<^<^vvvv^<<vv<^v><<>^>^<v^v^<^>v^><>>v^>v^>^>>v<>vv^v<<>^^>>vv<>vv>>^v<^vv>^v>v<v^vvv^<<^><>v^<><vv><>v^^><<<><>^>^v^<>><vv<^>v^v>v<>><v<<^>^<vv<^v>^<<v><^<^^vv^<>><v^>^vv^<>>^^^^v>v><^^^v^<<<>^<^<<>><>>v<<^v^>><><v^>>^vv^v>vv>>>>>>^^<<>v^>v^v>^^>>><vv^^^v>^v>>^^^<>><>v^<<<v<vv^^<v^<<<>v>v^^^<vv<>>^v>^v<^<<><>vv>^^^<^^vv<v<<vv>^^>vv>v<<^>^vv><^><v>^^^^v<<vv>v^<<^^>>^^vvvv^v^>vv>>v^<v>vvv<>>^><>>v^^>>^<>>vvvv^>><v^v<^^<^vv>>v<<^<<^><v^^><v^>v^>><<<v>v>v^>^v<v^vv<^^^v<^<vvvvv<<vvv>><>v<v<v<<^v<><<>vv>><v>><^>>^^v>^>><>vv^><<>>vv<<<^<^^>^<<^>>>><v<^v<<<>>v>vv<^>^v><>>v<v^v<>v^vvvv>v^>>v><<^<v>^^v>>vv^^>v>^v>^v^^>^<^vv<v<<^>vv<<^>>^<<^^>>^<^>v^><^vv>^^v><v^>>><>v^v>^v<^><<<>vv><v>v<><>>v^<>^^>^<>^<<^>>vv^><^<v<^^vvv>>v^>>v^>v>vv><>>v<^>><<<v<<vv><v<v<v>v<v>vv^vvv^vv^>^>v><vv<v^^<>>>>vv^>^<>v<^>^<^v>vv<^<<>>^<^<vv><^^<>^<<v^v^>v<<><v>v>><^v<<^vvv>v>v<<^^<^^>v<vv<v<v^v>^^^>^>vv<v<<^^v^<v<^>^^^vv>v<>>>vv>><><^><><<<vvv<<^^v^<v^<<^>>vv>vv^v^>>><v><<v^v>>v>>vv>^^vvv^>^^>^>^>^v<<^vv^>vvv^^vv><^>^v^>^><>v<^^vv<v><v^<><^<>><v>^^v^v>v^vv<>><^v>^<^v>^<>^v>>>><<vv^^^vv^>>><vv^v>>v><^v^vv><<^v<<>^^<v><^v>vvv<><^^><<^v><>^<^v<^^<^vvvv^^>>>>vv>v>>>v<v^><<<<v>>v^><v>>vv^v<vv<>vv<>vvv>>>><>>><>^v<v^v><vvv<<v^^v^v<>>><>>^vv<<v<><<vv<v^>^^vv><^v^v<v^vvv^v>v^^^vv>^><^vvv<<>^vvv^<v<v^v>>>>^<<<><<<<<^v<^^>>>>^>^<v^^^v<vvv<vv^<>v<<<^<^>>v^<v><<><<^^vvv^>v<>>^^>v>^v>>v<v><v>>>>^<^<^>v^v<vv<>^>><>^<<^vvv^^<>^<vvv<>v^>^^<<^>^vv><vvv>>v^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t = [] x1, y1, x2, y2 = 0, 0, 0, 0 for i in range(len(path)): if i%2 == 0: if path[i] == '^': x2+=1 if path[i] == 'v': x2-=1 if path[i] == '>': y2+=1 if path[i] == '<': y2-=1 t.append(str(x2)+'/'+str(y2)) if i%2 == 1: if path[i] == '^': x1+=1 if path[i] == 'v': x1-=1 if path[i] == '>': y1+=1 if path[i] == '<': y1-=1 t.append(str(x1)+'/'+str(y1)) print(len(set(t)))

true

1c2fc07b459c8bfbe90b2101897c68347d65049c

2,950

py

Python

pyreaclib/amemass/ame_nuclide.py

jennranta/pyreaclib

bd9210153b0c01c7ce230b43b88f0a5a1e198c0f

[ "BSD-3-Clause" ]

null

pyreaclib/amemass/ame_nuclide.py

jennranta/pyreaclib

bd9210153b0c01c7ce230b43b88f0a5a1e198c0f

[ "BSD-3-Clause" ]

null

pyreaclib/amemass/ame_nuclide.py

jennranta/pyreaclib

bd9210153b0c01c7ce230b43b88f0a5a1e198c0f

[ "BSD-3-Clause" ]

null

# Common Imports from __future__ import print_function class AMENuclide(object): def __init__(self, n=None, z=None, a=None, element=None, origin=None, mexcess=None, d_mexcess=None, nucbind=None, d_nucbind=None, decay_type=None, ebeta=None, d_ebeta=None, mass=None, d_mass=None): self.n=None self.z=None self.a=None self.element=None self.origin=None self.mexcess=None self.d_mexcess=None self.nucbind=None self.d_nucbind=None self.decay_type=None self.ebeta=None self.d_ebeta=None self.mass=None self.d_mass=None if n: self.n = int(n) if z: self.z = int(z) if a: self.a = int(a) self.element = element self.origin = origin if mexcess: self.mexcess = float(mexcess) if d_mexcess: self.d_mexcess = float(d_mexcess) if nucbind: self.nucbind = float(nucbind) if d_nucbind: self.d_nucbind = float(d_nucbind) self.decay_type = decay_type if ebeta: self.ebeta = float(ebeta) if d_ebeta: self.d_ebeta = float(d_ebeta) if mass: self.mass = float(mass) if d_mass: self.d_mass = float(d_mass) self.convert_MeV() self.convert_amu() def print_contents(self): """ Print Contents """ print('n = {}'.format(self.n)) print('z = {}'.format(self.z)) print('a = {}'.format(self.a)) print('element = {}'.format(self.element)) print('origin = {}'.format(self.origin)) print('mexcess = {}'.format(self.mexcess)) print('d_mexcess = {}'.format(self.d_mexcess)) print('nucbind = {}'.format(self.nucbind)) print('d_nucbind = {}'.format(self.d_nucbind)) print('decay_type = {}'.format(self.decay_type)) print('ebeta = {}'.format(self.ebeta)) print('d_ebeta = {}'.format(self.d_ebeta)) print('mass = {}'.format(self.mass)) print('d_mass = {}'.format(self.d_mass)) def convert_MeV(self): """ Convert keV to MeV """ if self.mexcess: self.mexcess = self.mexcess/1.0e3 if self.d_mexcess: self.d_mexcess = self.d_mexcess/1.0e3 if self.nucbind: self.nucbind = self.nucbind/1.0e3 if self.d_nucbind: self.d_nucbind = self.d_nucbind/1.0e3 if self.ebeta: self.ebeta = self.ebeta/1.0e3 if self.d_ebeta: self.d_ebeta = self.d_ebeta/1.0e3 def convert_amu(self): """ Convert micro-amu to amu """ if self.mass: self.mass = self.mass/1.0e6 if self.d_mass: self.d_mass = self.d_mass/1.0e6

29.79798

73

0.530847

from __future__ import print_function class AMENuclide(object): def __init__(self, n=None, z=None, a=None, element=None, origin=None, mexcess=None, d_mexcess=None, nucbind=None, d_nucbind=None, decay_type=None, ebeta=None, d_ebeta=None, mass=None, d_mass=None): self.n=None self.z=None self.a=None self.element=None self.origin=None self.mexcess=None self.d_mexcess=None self.nucbind=None self.d_nucbind=None self.decay_type=None self.ebeta=None self.d_ebeta=None self.mass=None self.d_mass=None if n: self.n = int(n) if z: self.z = int(z) if a: self.a = int(a) self.element = element self.origin = origin if mexcess: self.mexcess = float(mexcess) if d_mexcess: self.d_mexcess = float(d_mexcess) if nucbind: self.nucbind = float(nucbind) if d_nucbind: self.d_nucbind = float(d_nucbind) self.decay_type = decay_type if ebeta: self.ebeta = float(ebeta) if d_ebeta: self.d_ebeta = float(d_ebeta) if mass: self.mass = float(mass) if d_mass: self.d_mass = float(d_mass) self.convert_MeV() self.convert_amu() def print_contents(self): print('n = {}'.format(self.n)) print('z = {}'.format(self.z)) print('a = {}'.format(self.a)) print('element = {}'.format(self.element)) print('origin = {}'.format(self.origin)) print('mexcess = {}'.format(self.mexcess)) print('d_mexcess = {}'.format(self.d_mexcess)) print('nucbind = {}'.format(self.nucbind)) print('d_nucbind = {}'.format(self.d_nucbind)) print('decay_type = {}'.format(self.decay_type)) print('ebeta = {}'.format(self.ebeta)) print('d_ebeta = {}'.format(self.d_ebeta)) print('mass = {}'.format(self.mass)) print('d_mass = {}'.format(self.d_mass)) def convert_MeV(self): if self.mexcess: self.mexcess = self.mexcess/1.0e3 if self.d_mexcess: self.d_mexcess = self.d_mexcess/1.0e3 if self.nucbind: self.nucbind = self.nucbind/1.0e3 if self.d_nucbind: self.d_nucbind = self.d_nucbind/1.0e3 if self.ebeta: self.ebeta = self.ebeta/1.0e3 if self.d_ebeta: self.d_ebeta = self.d_ebeta/1.0e3 def convert_amu(self): if self.mass: self.mass = self.mass/1.0e6 if self.d_mass: self.d_mass = self.d_mass/1.0e6

true

1c2fc0eaac66c2170fc9e708497eb4ba1c41f83a

2,412

py

Python

astropy/constants/utils.py

MatiasRepetto/astropy

689f9d3b063145150149e592a879ee40af1fac06

[ "BSD-3-Clause" ]

1

2019-03-11T12:26:49.000Z

astropy/constants/utils.py

MatiasRepetto/astropy

689f9d3b063145150149e592a879ee40af1fac06

[ "BSD-3-Clause" ]

1

2019-10-09T18:54:27.000Z

astropy/constants/utils.py

MatiasRepetto/astropy

689f9d3b063145150149e592a879ee40af1fac06

[ "BSD-3-Clause" ]

1

2020-02-18T04:10:00.000Z

# Licensed under a 3-clause BSD style license - see LICENSE.rst """Utility functions for ``constants`` sub-package.""" import itertools __all__ = [] def _get_c(codata, iaudata, module, not_in_module_only=True): """ Generator to return a Constant object. Parameters ---------- codata, iaudata : obj Modules containing CODATA and IAU constants of interest. module : obj Namespace module of interest. not_in_module_only : bool If ``True``, ignore constants that are already in the namespace of ``module``. Returns ------- _c : Constant Constant object to process. """ from .constant import Constant for _nm, _c in itertools.chain(sorted(vars(codata).items()), sorted(vars(iaudata).items())): if not isinstance(_c, Constant): continue elif (not not_in_module_only) or (_c.abbrev not in module.__dict__): yield _c def _set_c(codata, iaudata, module, not_in_module_only=True, doclines=None, set_class=False): """ Set constants in a given module namespace. Parameters ---------- codata, iaudata : obj Modules containing CODATA and IAU constants of interest. module : obj Namespace module to modify with the given ``codata`` and ``iaudata``. not_in_module_only : bool If ``True``, constants that are already in the namespace of ``module`` will not be modified. doclines : list or None If a list is given, this list will be modified in-place to include documentation of modified constants. This can be used to update docstring of ``module``. set_class : bool Namespace of ``module`` is populated with ``_c.__class__`` instead of just ``_c`` from :func:`_get_c`. """ for _c in _get_c(codata, iaudata, module, not_in_module_only=not_in_module_only): if set_class: value = _c.__class__(_c.abbrev, _c.name, _c.value, _c._unit_string, _c.uncertainty, _c.reference) else: value = _c setattr(module, _c.abbrev, value) if doclines is not None: doclines.append('{:^10} {:^14.9g} {:^16} {}'.format( _c.abbrev, _c.value, _c._unit_string, _c.name))

29.777778

77

0.596186

import itertools __all__ = [] def _get_c(codata, iaudata, module, not_in_module_only=True): from .constant import Constant for _nm, _c in itertools.chain(sorted(vars(codata).items()), sorted(vars(iaudata).items())): if not isinstance(_c, Constant): continue elif (not not_in_module_only) or (_c.abbrev not in module.__dict__): yield _c def _set_c(codata, iaudata, module, not_in_module_only=True, doclines=None, set_class=False): for _c in _get_c(codata, iaudata, module, not_in_module_only=not_in_module_only): if set_class: value = _c.__class__(_c.abbrev, _c.name, _c.value, _c._unit_string, _c.uncertainty, _c.reference) else: value = _c setattr(module, _c.abbrev, value) if doclines is not None: doclines.append('{:^10} {:^14.9g} {:^16} {}'.format( _c.abbrev, _c.value, _c._unit_string, _c.name))

true

1c2fc1bdd77a98dff2241412a763ab542480c417

7,213

py

Python

Lib/site-packages/openpyxl/workbook/defined_name.py

percevalm/aumyproject

b24b38005188ce9dd41ed663cf54dad5464afef3

[ "bzip2-1.0.6" ]

1

2017-10-31T02:37:37.000Z

Lib/site-packages/openpyxl/workbook/defined_name.py

percevalm/aumyproject

b24b38005188ce9dd41ed663cf54dad5464afef3

[ "bzip2-1.0.6" ]

16

2020-03-24T17:30:37.000Z

2022-03-11T23:57:41.000Z

Lib/site-packages/openpyxl/workbook/defined_name.py

percevalm/aumyproject

b24b38005188ce9dd41ed663cf54dad5464afef3

[ "bzip2-1.0.6" ]

null

from __future__ import absolute_import # Copyright (c) 2010-2017 openpyxl import re from openpyxl.descriptors.serialisable import Serialisable from openpyxl.descriptors import ( Alias, Typed, String, Float, Integer, Bool, NoneSet, Set, Sequence, Descriptor, ) from openpyxl.compat import safe_string from openpyxl.formula import Tokenizer from openpyxl.utils.cell import ( SHEETRANGE_RE, SHEET_TITLE, ) RESERVED = frozenset(["Print_Area", "Print_Titles", "Criteria", "_FilterDatabase", "Extract", "Consolidate_Area", "Sheet_Title"]) _names = "|".join(RESERVED) RESERVED_REGEX = re.compile(r"^_xlnm\.(?P<name>{0})".format(_names)) COL_RANGE = r"""(?P<cols>[$]?[a-zA-Z]{1,3}:[$]?[a-zA-Z]{1,3})""" COL_RANGE_RE = re.compile(COL_RANGE) ROW_RANGE = r"""(?P<rows>[$]?\d+:[$]?\d+)""" ROW_RANGE_RE = re.compile(ROW_RANGE) TITLES_REGEX = re.compile("""{0}{1}?,?{2}?""".format(SHEET_TITLE, ROW_RANGE, COL_RANGE), re.VERBOSE) ### utilities def _unpack_print_titles(defn): """ Extract rows and or columns from print titles so that they can be assigned to a worksheet """ scanner = TITLES_REGEX.finditer(defn.value) kw = dict((k, v) for match in scanner for k, v in match.groupdict().items() if v) return kw.get('rows'), kw.get('cols') def _unpack_print_area(defn): """ Extract print area """ new = [] for m in SHEETRANGE_RE.finditer(defn.value): # can be multiple coord = m.group("cells") if coord: new.append(coord) return new class DefinedName(Serialisable): tagname = "definedName" name = String() # unique per workbook/worksheet comment = String(allow_none=True) customMenu = String(allow_none=True) description = String(allow_none=True) help = String(allow_none=True) statusBar = String(allow_none=True) localSheetId = Integer(allow_none=True) hidden = Bool(allow_none=True) function = Bool(allow_none=True) vbProcedure = Bool(allow_none=True) xlm = Bool(allow_none=True) functionGroupId = Integer(allow_none=True) shortcutKey = String(allow_none=True) publishToServer = Bool(allow_none=True) workbookParameter = Bool(allow_none=True) attr_text = Descriptor() value = Alias("attr_text") def __init__(self, name=None, comment=None, customMenu=None, description=None, help=None, statusBar=None, localSheetId=None, hidden=None, function=None, vbProcedure=None, xlm=None, functionGroupId=None, shortcutKey=None, publishToServer=None, workbookParameter=None, attr_text=None ): self.name = name self.comment = comment self.customMenu = customMenu self.description = description self.help = help self.statusBar = statusBar self.localSheetId = localSheetId self.hidden = hidden self.function = function self.vbProcedure = vbProcedure self.xlm = xlm self.functionGroupId = functionGroupId self.shortcutKey = shortcutKey self.publishToServer = publishToServer self.workbookParameter = workbookParameter self.attr_text = attr_text @property def type(self): tok = Tokenizer("=" + self.value) parsed = tok.items[0] if parsed.type == "OPERAND": return parsed.subtype return parsed.type @property def destinations(self): if self.type == "RANGE": tok = Tokenizer("=" + self.value) for part in tok.items: if part.subtype == "RANGE": m = SHEETRANGE_RE.match(part.value) sheetname = m.group('notquoted') or m.group('quoted') yield sheetname, m.group('cells') @property def is_reserved(self): m = RESERVED_REGEX.match(self.name) if m: return m.group("name") @property def is_external(self): return re.compile(r"^\[\d+\].*").match(self.value) is not None def __iter__(self): for key in self.__attrs__: if key == "attr_text": continue v = getattr(self, key) if v is not None: if v in RESERVED: v = "_xlnm." + v yield key, safe_string(v) class DefinedNameList(Serialisable): tagname = "definedNames" definedName = Sequence(expected_type=DefinedName) def __init__(self, definedName=()): self.definedName = definedName def _cleanup(self): """ Strip broken or unknown definitions """ self.delete("_xlnm.Print_Titles") self.delete("_xlnm.Print_Area") def _duplicate(self, defn): """ Check for whether DefinedName with the same name and scope already exists """ for d in self.definedName: if d.name == defn.name and d.localSheetId == defn.localSheetId: return True def append(self, defn): if not isinstance(defn, DefinedName): raise TypeError("""You can only append DefinedNames""") if self._duplicate(defn): raise ValueError("""DefinedName with the same name and scope already exists""") names = self.definedName[:] names.append(defn) self.definedName = names def __len__(self): return len(self.definedName) def __contains__(self, name): """ See if a globaly defined name exists """ for defn in self.definedName: if defn.name == name and defn.localSheetId is None: return True def __getitem__(self, name): """ Get globally defined name """ defn = self.get(name) if not defn: raise KeyError("No definition called {0}".format(name)) return defn def get(self, name, scope=None): """ Get the name assigned to a specicic sheet or global """ for defn in self.definedName: if defn.name == name and defn.localSheetId == scope: return defn def __delitem__(self, name): """ Delete a globally defined name """ if not self.delete(name): raise KeyError("No globally defined name {0}".format(name)) def delete(self, name, scope=None): """ Delete a name assigned to a specific or global """ for idx, defn in enumerate(self.definedName): if defn.name == name and defn.localSheetId == scope: del self.definedName[idx] return True def localnames(self, scope): """ Provide a list of all names for a particular worksheet """ return [defn.name for defn in self.definedName if defn.localSheetId == scope]

27.530534

91

0.579093

from __future__ import absolute_import import re from openpyxl.descriptors.serialisable import Serialisable from openpyxl.descriptors import ( Alias, Typed, String, Float, Integer, Bool, NoneSet, Set, Sequence, Descriptor, ) from openpyxl.compat import safe_string from openpyxl.formula import Tokenizer from openpyxl.utils.cell import ( SHEETRANGE_RE, SHEET_TITLE, ) RESERVED = frozenset(["Print_Area", "Print_Titles", "Criteria", "_FilterDatabase", "Extract", "Consolidate_Area", "Sheet_Title"]) _names = "|".join(RESERVED) RESERVED_REGEX = re.compile(r"^_xlnm\.(?P<name>{0})".format(_names)) COL_RANGE = r"""(?P<cols>[$]?[a-zA-Z]{1,3}:[$]?[a-zA-Z]{1,3})""" COL_RANGE_RE = re.compile(COL_RANGE) ROW_RANGE = r"""(?P<rows>[$]?\d+:[$]?\d+)""" ROW_RANGE_RE = re.compile(ROW_RANGE) TITLES_REGEX = re.compile("""{0}{1}?,?{2}?""".format(SHEET_TITLE, ROW_RANGE, COL_RANGE), re.VERBOSE) les(defn): scanner = TITLES_REGEX.finditer(defn.value) kw = dict((k, v) for match in scanner for k, v in match.groupdict().items() if v) return kw.get('rows'), kw.get('cols') def _unpack_print_area(defn): new = [] for m in SHEETRANGE_RE.finditer(defn.value): coord = m.group("cells") if coord: new.append(coord) return new class DefinedName(Serialisable): tagname = "definedName" name = String() comment = String(allow_none=True) customMenu = String(allow_none=True) description = String(allow_none=True) help = String(allow_none=True) statusBar = String(allow_none=True) localSheetId = Integer(allow_none=True) hidden = Bool(allow_none=True) function = Bool(allow_none=True) vbProcedure = Bool(allow_none=True) xlm = Bool(allow_none=True) functionGroupId = Integer(allow_none=True) shortcutKey = String(allow_none=True) publishToServer = Bool(allow_none=True) workbookParameter = Bool(allow_none=True) attr_text = Descriptor() value = Alias("attr_text") def __init__(self, name=None, comment=None, customMenu=None, description=None, help=None, statusBar=None, localSheetId=None, hidden=None, function=None, vbProcedure=None, xlm=None, functionGroupId=None, shortcutKey=None, publishToServer=None, workbookParameter=None, attr_text=None ): self.name = name self.comment = comment self.customMenu = customMenu self.description = description self.help = help self.statusBar = statusBar self.localSheetId = localSheetId self.hidden = hidden self.function = function self.vbProcedure = vbProcedure self.xlm = xlm self.functionGroupId = functionGroupId self.shortcutKey = shortcutKey self.publishToServer = publishToServer self.workbookParameter = workbookParameter self.attr_text = attr_text @property def type(self): tok = Tokenizer("=" + self.value) parsed = tok.items[0] if parsed.type == "OPERAND": return parsed.subtype return parsed.type @property def destinations(self): if self.type == "RANGE": tok = Tokenizer("=" + self.value) for part in tok.items: if part.subtype == "RANGE": m = SHEETRANGE_RE.match(part.value) sheetname = m.group('notquoted') or m.group('quoted') yield sheetname, m.group('cells') @property def is_reserved(self): m = RESERVED_REGEX.match(self.name) if m: return m.group("name") @property def is_external(self): return re.compile(r"^\[\d+\].*").match(self.value) is not None def __iter__(self): for key in self.__attrs__: if key == "attr_text": continue v = getattr(self, key) if v is not None: if v in RESERVED: v = "_xlnm." + v yield key, safe_string(v) class DefinedNameList(Serialisable): tagname = "definedNames" definedName = Sequence(expected_type=DefinedName) def __init__(self, definedName=()): self.definedName = definedName def _cleanup(self): self.delete("_xlnm.Print_Titles") self.delete("_xlnm.Print_Area") def _duplicate(self, defn): for d in self.definedName: if d.name == defn.name and d.localSheetId == defn.localSheetId: return True def append(self, defn): if not isinstance(defn, DefinedName): raise TypeError("""You can only append DefinedNames""") if self._duplicate(defn): raise ValueError("""DefinedName with the same name and scope already exists""") names = self.definedName[:] names.append(defn) self.definedName = names def __len__(self): return len(self.definedName) def __contains__(self, name): for defn in self.definedName: if defn.name == name and defn.localSheetId is None: return True def __getitem__(self, name): defn = self.get(name) if not defn: raise KeyError("No definition called {0}".format(name)) return defn def get(self, name, scope=None): for defn in self.definedName: if defn.name == name and defn.localSheetId == scope: return defn def __delitem__(self, name): if not self.delete(name): raise KeyError("No globally defined name {0}".format(name)) def delete(self, name, scope=None): for idx, defn in enumerate(self.definedName): if defn.name == name and defn.localSheetId == scope: del self.definedName[idx] return True def localnames(self, scope): return [defn.name for defn in self.definedName if defn.localSheetId == scope]

true

1c2fc1e3ad518f905ac5ccdd97c9c53482b06b2c

8,778

py

Python

danceschool/financial/handlers.py

django-danceschool/django-danceschool

65ae09ffdcb0821e82df0e1f634fe13c0384a525

[ "BSD-3-Clause" ]

32

2017-09-12T04:25:25.000Z

2022-03-21T10:48:07.000Z

danceschool/financial/handlers.py

django-danceschool/django-danceschool

65ae09ffdcb0821e82df0e1f634fe13c0384a525

[ "BSD-3-Clause" ]

97

2017-09-01T02:43:08.000Z

2022-01-03T18:20:34.000Z

danceschool/financial/handlers.py

django-danceschool/django-danceschool

65ae09ffdcb0821e82df0e1f634fe13c0384a525

[ "BSD-3-Clause" ]

19

2017-09-26T13:34:46.000Z

2022-03-21T10:48:10.000Z

from django.dispatch import receiver from django.db.models import Q, Value, CharField, F from django.db.models.query import QuerySet from django.db.models.signals import post_save, m2m_changed from django.utils.translation import gettext_lazy as _ from django.contrib.auth.models import User import sys import logging from danceschool.core.models import ( EventStaffMember, EventOccurrence, InvoiceItem, Invoice, StaffMember, Location, EventRegistration ) from danceschool.core.constants import getConstant from danceschool.core.signals import get_eventregistration_data from .models import ExpenseItem, RevenueItem, RepeatedExpenseRule # Define logger for this file logger = logging.getLogger(__name__) @receiver(m2m_changed, sender=EventStaffMember.occurrences.through) def modifyExistingExpenseItemsForEventStaff(sender, instance, **kwargs): if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return if kwargs.get('action', None) != 'post_add': return logger.debug('ExpenseItem signal fired for EventStaffMember %s.' % instance.pk) staff_expenses = ExpenseItem.objects.filter( event=instance.event, expenseRule__in=instance.staffMember.expenserules.all(), expenseRule__applyRateRule=RepeatedExpenseRule.RateRuleChoices.hourly, ) if staff_expenses: logger.debug('Updating existing expense items for event staff member.') # Fill in the updated hours and the updated total. Set the expense item # to unapproved. for expense in staff_expenses: logger.debug('Updating expense item %s.' % expense.id) expense.hours = instance.netHours expense.total = expense.hours * expense.wageRate expense.approved = None expense.save() if hasattr(instance.replacedStaffMember, 'staffMember'): logger.debug('Adjusting totals for replaced event staff member.') replaced_expenses = ExpenseItem.objects.filter( event=instance.event, expenseRule__staffmemberwageinfo__staffMember=instance.replacedStaffMember.staffMember, expenseRule__applyRateRule=RepeatedExpenseRule.RateRuleChoices.hourly, ) # Fill in the updated hours and the updated total. Set the expense item # to unapproved. for expense in replaced_expenses: logger.debug('Updating expense item %s' % expense.id) expense.hours = instance.replacedStaffMember.netHours expense.total = expense.hours * expense.wageRate expense.approved = None expense.save() @receiver(post_save, sender=EventOccurrence) def modifyExistingExpenseItemsForSeriesClass(sender, instance, **kwargs): if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return logger.debug('ExpenseItem signal fired for EventOccurrence %s.' % instance.id) staff_expenses = ExpenseItem.objects.filter( event=instance.event, expenseRule__staffmemberwageinfo__isnull=False, expenseRule__applyRateRule=RepeatedExpenseRule.RateRuleChoices.hourly, ) # Fill in the updated hours and the updated total. Set the expense item # to unapproved. for expense in staff_expenses: esm_filters = Q(event=expense.event) & Q(staffMember=expense.expenseRule.staffMember) if expense.expenseRule.category: esm_filters = esm_filters & Q(category=expense.expenseRule.category) # In instances where the expense rule does not specify a category, there could # be more than one EventStaffMember object for a given staffMember at the # same Event. There is no easy way to identify which expense is which in this instance, # so when EventOccurrences are modified, these expenses will not update. eventstaffmembers = EventStaffMember.objects.filter(esm_filters) if eventstaffmembers.count() == 1: esm = eventstaffmembers.first() expense.hours = esm.netHours expense.total = expense.hours * expense.wageRate expense.approved = None expense.save() @receiver(post_save, sender=InvoiceItem) def createRevenueItemForInvoiceItem(sender, instance, **kwargs): if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return logger.debug('RevenueItem signal fired for InvoiceItem %s.' % instance.id) if instance.invoice.status == Invoice.PaymentStatus.preliminary: logger.debug('Preliminary invoice. No revenue item will be created.') return received_status = (not instance.invoice.unpaid) related_item = getattr(instance, 'revenueitem', None) if not related_item: related_item = RevenueItem.objects.create( invoiceItem=instance, invoiceNumber=instance.id, grossTotal=instance.grossTotal, total=instance.total, adjustments=instance.adjustments, fees=instance.fees, taxes=instance.taxes, buyerPaysSalesTax=instance.invoice.buyerPaysSalesTax, category=getConstant('financial__registrationsRevenueCat'), submissionUser=instance.invoice.submissionUser, currentlyHeldBy=instance.invoice.collectedByUser, received=received_status, paymentMethod=instance.invoice.get_payment_method(), description=_('Registration invoice %s' % instance.id) ) logger.debug('RevenueItem created.') else: # Check that the existing revenueItem is still correct saveFlag = False for field in ['grossTotal', 'total', 'adjustments', 'fees', 'taxes']: if getattr(related_item, field) != getattr(instance, field): setattr(related_item, field, getattr(instance, field)) saveFlag = True for field in ['buyerPaysSalesTax', ]: if getattr(related_item, field) != getattr(instance.invoice, field): setattr(related_item, field, getattr(instance.invoice, field)) saveFlag = True if related_item.received != received_status: related_item.received = received_status related_item.paymentMethod = instance.invoice.get_payment_method() saveFlag = True if saveFlag: related_item.save() logger.info('RevenueItem associated with InvoiceItem %s updated.' % instance.id) @receiver(post_save, sender=Invoice) def createRevenueItemsFromInvoice(sender, instance, **kwargs): ''' This signal handler exists because an invoice can be changed from preliminary to non-preliminary without editing the invoice items, in which case revenue items will need to be created. ''' if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return logger.debug('RevenueItem signal fired for Invoice %s.' % instance.id) if instance.status == Invoice.PaymentStatus.preliminary: logger.debug('Preliminary invoice. No revenue items will be created.') return for item in instance.invoiceitem_set.all(): createRevenueItemForInvoiceItem(sender, item, **kwargs) @receiver(post_save, sender=User) @receiver(post_save, sender=StaffMember) @receiver(post_save, sender=Location) def updateTransactionParty(sender, instance, **kwargs): ''' If a User, StaffMember, or Location is updated, and there exists an associated TransactionParty, then the name and other attributes of that party should be updated to reflect the new information. ''' if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return logger.debug('TransactionParty signal fired for %s %s.' % (instance.__class__.__name__, instance.id)) party = getattr(instance, 'transactionparty', None) if party: party.save(updateBy=instance) @receiver(get_eventregistration_data) def reportRevenue(sender, **kwargs): logger.debug('Signal fired to return revenue items associated with registrations') regs = kwargs.pop('eventregistrations', None) if not regs or not isinstance(regs, QuerySet) or not (regs.model == EventRegistration): logger.warning('No/invalid EventRegistration queryset passed, so revenue items not found.') return extras = {} regs = regs.filter(invoiceItem__revenueitem__isnull=False).select_related( 'invoiceItem__revenueitem' ) for reg in regs: extras[reg.id] = [{ 'id': reg.invoiceItem.revenueitem.id, 'name': reg.invoiceItem.revenueitem.description, 'type': 'revenueitem', 'amount': reg.invoiceItem.revenueitem.total, }, ] return extras

39.719457

105

0.692755

from django.dispatch import receiver from django.db.models import Q, Value, CharField, F from django.db.models.query import QuerySet from django.db.models.signals import post_save, m2m_changed from django.utils.translation import gettext_lazy as _ from django.contrib.auth.models import User import sys import logging from danceschool.core.models import ( EventStaffMember, EventOccurrence, InvoiceItem, Invoice, StaffMember, Location, EventRegistration ) from danceschool.core.constants import getConstant from danceschool.core.signals import get_eventregistration_data from .models import ExpenseItem, RevenueItem, RepeatedExpenseRule logger = logging.getLogger(__name__) @receiver(m2m_changed, sender=EventStaffMember.occurrences.through) def modifyExistingExpenseItemsForEventStaff(sender, instance, **kwargs): if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return if kwargs.get('action', None) != 'post_add': return logger.debug('ExpenseItem signal fired for EventStaffMember %s.' % instance.pk) staff_expenses = ExpenseItem.objects.filter( event=instance.event, expenseRule__in=instance.staffMember.expenserules.all(), expenseRule__applyRateRule=RepeatedExpenseRule.RateRuleChoices.hourly, ) if staff_expenses: logger.debug('Updating existing expense items for event staff member.') for expense in staff_expenses: logger.debug('Updating expense item %s.' % expense.id) expense.hours = instance.netHours expense.total = expense.hours * expense.wageRate expense.approved = None expense.save() if hasattr(instance.replacedStaffMember, 'staffMember'): logger.debug('Adjusting totals for replaced event staff member.') replaced_expenses = ExpenseItem.objects.filter( event=instance.event, expenseRule__staffmemberwageinfo__staffMember=instance.replacedStaffMember.staffMember, expenseRule__applyRateRule=RepeatedExpenseRule.RateRuleChoices.hourly, ) for expense in replaced_expenses: logger.debug('Updating expense item %s' % expense.id) expense.hours = instance.replacedStaffMember.netHours expense.total = expense.hours * expense.wageRate expense.approved = None expense.save() @receiver(post_save, sender=EventOccurrence) def modifyExistingExpenseItemsForSeriesClass(sender, instance, **kwargs): if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return logger.debug('ExpenseItem signal fired for EventOccurrence %s.' % instance.id) staff_expenses = ExpenseItem.objects.filter( event=instance.event, expenseRule__staffmemberwageinfo__isnull=False, expenseRule__applyRateRule=RepeatedExpenseRule.RateRuleChoices.hourly, ) for expense in staff_expenses: esm_filters = Q(event=expense.event) & Q(staffMember=expense.expenseRule.staffMember) if expense.expenseRule.category: esm_filters = esm_filters & Q(category=expense.expenseRule.category) eventstaffmembers = EventStaffMember.objects.filter(esm_filters) if eventstaffmembers.count() == 1: esm = eventstaffmembers.first() expense.hours = esm.netHours expense.total = expense.hours * expense.wageRate expense.approved = None expense.save() @receiver(post_save, sender=InvoiceItem) def createRevenueItemForInvoiceItem(sender, instance, **kwargs): if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return logger.debug('RevenueItem signal fired for InvoiceItem %s.' % instance.id) if instance.invoice.status == Invoice.PaymentStatus.preliminary: logger.debug('Preliminary invoice. No revenue item will be created.') return received_status = (not instance.invoice.unpaid) related_item = getattr(instance, 'revenueitem', None) if not related_item: related_item = RevenueItem.objects.create( invoiceItem=instance, invoiceNumber=instance.id, grossTotal=instance.grossTotal, total=instance.total, adjustments=instance.adjustments, fees=instance.fees, taxes=instance.taxes, buyerPaysSalesTax=instance.invoice.buyerPaysSalesTax, category=getConstant('financial__registrationsRevenueCat'), submissionUser=instance.invoice.submissionUser, currentlyHeldBy=instance.invoice.collectedByUser, received=received_status, paymentMethod=instance.invoice.get_payment_method(), description=_('Registration invoice %s' % instance.id) ) logger.debug('RevenueItem created.') else: saveFlag = False for field in ['grossTotal', 'total', 'adjustments', 'fees', 'taxes']: if getattr(related_item, field) != getattr(instance, field): setattr(related_item, field, getattr(instance, field)) saveFlag = True for field in ['buyerPaysSalesTax', ]: if getattr(related_item, field) != getattr(instance.invoice, field): setattr(related_item, field, getattr(instance.invoice, field)) saveFlag = True if related_item.received != received_status: related_item.received = received_status related_item.paymentMethod = instance.invoice.get_payment_method() saveFlag = True if saveFlag: related_item.save() logger.info('RevenueItem associated with InvoiceItem %s updated.' % instance.id) @receiver(post_save, sender=Invoice) def createRevenueItemsFromInvoice(sender, instance, **kwargs): if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return logger.debug('RevenueItem signal fired for Invoice %s.' % instance.id) if instance.status == Invoice.PaymentStatus.preliminary: logger.debug('Preliminary invoice. No revenue items will be created.') return for item in instance.invoiceitem_set.all(): createRevenueItemForInvoiceItem(sender, item, **kwargs) @receiver(post_save, sender=User) @receiver(post_save, sender=StaffMember) @receiver(post_save, sender=Location) def updateTransactionParty(sender, instance, **kwargs): if 'loaddata' in sys.argv or ('raw' in kwargs and kwargs['raw']): return logger.debug('TransactionParty signal fired for %s %s.' % (instance.__class__.__name__, instance.id)) party = getattr(instance, 'transactionparty', None) if party: party.save(updateBy=instance) @receiver(get_eventregistration_data) def reportRevenue(sender, **kwargs): logger.debug('Signal fired to return revenue items associated with registrations') regs = kwargs.pop('eventregistrations', None) if not regs or not isinstance(regs, QuerySet) or not (regs.model == EventRegistration): logger.warning('No/invalid EventRegistration queryset passed, so revenue items not found.') return extras = {} regs = regs.filter(invoiceItem__revenueitem__isnull=False).select_related( 'invoiceItem__revenueitem' ) for reg in regs: extras[reg.id] = [{ 'id': reg.invoiceItem.revenueitem.id, 'name': reg.invoiceItem.revenueitem.description, 'type': 'revenueitem', 'amount': reg.invoiceItem.revenueitem.total, }, ] return extras

true

1c2fc3209f2199d9779888529609d26bf3a2c41a

3,245

py

Python

twittertennis/handler_utils.py

ferencberes/twittertennis

d9a21655c3e5c3599fe4149904c967ed67139569

[ "CC0-1.0" ]

null

twittertennis/handler_utils.py

ferencberes/twittertennis

d9a21655c3e5c3599fe4149904c967ed67139569

[ "CC0-1.0" ]

null

twittertennis/handler_utils.py

ferencberes/twittertennis

d9a21655c3e5c3599fe4149904c967ed67139569

[ "CC0-1.0" ]

null

import pandas as pd import networkx as nx from collections import Counter ### EDGES ### def groupby_count(df, group_cols, count_col): parts = [df[col] for col in group_cols] tuples = list(zip(*parts)) cnt = Counter(tuples) keys, counts = zip(*list(cnt.items())) res = pd.DataFrame(keys, columns=group_cols) res[count_col] = counts return res def group_edges(df, key_col="date"): edges_grouped = {} keys = sorted(list(df[key_col].unique())) for key in keys: edges_grouped[key] = df[df[key_col]==key].copy() return edges_grouped def get_weighted_edges(df, group_cols): weighted_edges = groupby_count(df, group_cols, "weight") return weighted_edges def prepare_edges(mentions, snapshot_col="date"): group_cols = ["src","trg",snapshot_col] weighted_edges = get_weighted_edges(mentions, group_cols) weighted_edges_grouped = group_edges(weighted_edges, snapshot_col) edges_grouped = group_edges(mentions[group_cols], snapshot_col) return weighted_edges, weighted_edges_grouped, edges_grouped ### NODE REINDEXING ### def reindex_labels(label_dict, id2account, account2index): tuples = [] for key, label in label_dict.items(): account = id2account[key] if account in account2index: new_id = account2index[account] tuples.append((new_id, label)) new_dict = dict(tuples) ordered_dict = dict(sorted(new_dict.items())) return ordered_dict def reindex_edges(df, id_to_account, account_to_index=None, src_col="src_screen_str", trg_col="trg_screen_str"): if account_to_index != None: accounts = list(account_to_index.keys()) tmp = df.copy() # old solution would also be good with isnull() tmp[src_col] = tmp["src"].apply(lambda x: id_to_account.get(x)) tmp[trg_col] = tmp["trg"].apply(lambda x: id_to_account.get(x)) tmp = tmp[tmp[src_col].isin(accounts) & tmp[trg_col].isin(accounts)] src = tmp[src_col].apply(lambda x: account_to_index.get(x)) trg = tmp[trg_col].apply(lambda x: account_to_index.get(x)) else: src = df["src"] trg = df["trg"] return src, trg ### LABELS ### def regression_labels(df, snapshot_col): label_records = groupby_count(df, [snapshot_col,"trg"], "count") snapshots = sorted(list(label_records[snapshot_col].unique())) labels = {} for snapshot_id in snapshots: rec_tmp = label_records[label_records[snapshot_col]==snapshot_id] dict_tmp = dict(zip(rec_tmp["trg"],rec_tmp["count"])) labels[snapshot_id] = dict_tmp return labels ### FEATURES ### def calculate_node_features(G, total_nodes=None, degree=True, transitivity=True): """Calculate degree and node transitivty as node features. The graph nodes must have integer identifiers from 0 to N-1 where N is the number of nodes in G.""" if total_nodes == None: total_nodes = G.number_of_nodes() scores = [] if degree: degs = dict(nx.degree(G)) scores.append([degs.get(i,0) for i in range(total_nodes)]) if transitivity: trans = dict(nx.clustering(G)) scores.append([trans.get(i,0) for i in range(total_nodes)]) return list(zip(*scores))

37.298851

162

0.678274

import pandas as pd import networkx as nx from collections import Counter _cols, count_col): parts = [df[col] for col in group_cols] tuples = list(zip(*parts)) cnt = Counter(tuples) keys, counts = zip(*list(cnt.items())) res = pd.DataFrame(keys, columns=group_cols) res[count_col] = counts return res def group_edges(df, key_col="date"): edges_grouped = {} keys = sorted(list(df[key_col].unique())) for key in keys: edges_grouped[key] = df[df[key_col]==key].copy() return edges_grouped def get_weighted_edges(df, group_cols): weighted_edges = groupby_count(df, group_cols, "weight") return weighted_edges def prepare_edges(mentions, snapshot_col="date"): group_cols = ["src","trg",snapshot_col] weighted_edges = get_weighted_edges(mentions, group_cols) weighted_edges_grouped = group_edges(weighted_edges, snapshot_col) edges_grouped = group_edges(mentions[group_cols], snapshot_col) return weighted_edges, weighted_edges_grouped, edges_grouped unt2index): tuples = [] for key, label in label_dict.items(): account = id2account[key] if account in account2index: new_id = account2index[account] tuples.append((new_id, label)) new_dict = dict(tuples) ordered_dict = dict(sorted(new_dict.items())) return ordered_dict def reindex_edges(df, id_to_account, account_to_index=None, src_col="src_screen_str", trg_col="trg_screen_str"): if account_to_index != None: accounts = list(account_to_index.keys()) tmp = df.copy() tmp[src_col] = tmp["src"].apply(lambda x: id_to_account.get(x)) tmp[trg_col] = tmp["trg"].apply(lambda x: id_to_account.get(x)) tmp = tmp[tmp[src_col].isin(accounts) & tmp[trg_col].isin(accounts)] src = tmp[src_col].apply(lambda x: account_to_index.get(x)) trg = tmp[trg_col].apply(lambda x: account_to_index.get(x)) else: src = df["src"] trg = df["trg"] return src, trg pshot_col): label_records = groupby_count(df, [snapshot_col,"trg"], "count") snapshots = sorted(list(label_records[snapshot_col].unique())) labels = {} for snapshot_id in snapshots: rec_tmp = label_records[label_records[snapshot_col]==snapshot_id] dict_tmp = dict(zip(rec_tmp["trg"],rec_tmp["count"])) labels[snapshot_id] = dict_tmp return labels tal_nodes=None, degree=True, transitivity=True): if total_nodes == None: total_nodes = G.number_of_nodes() scores = [] if degree: degs = dict(nx.degree(G)) scores.append([degs.get(i,0) for i in range(total_nodes)]) if transitivity: trans = dict(nx.clustering(G)) scores.append([trans.get(i,0) for i in range(total_nodes)]) return list(zip(*scores))

true

1c2fc51f8b3649c1bd241cd9d62b5618aa991773

700

py

Python

pybind/slxos/v16r_1_00b/no/fcsp/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/slxos/v16r_1_00b/no/fcsp/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/slxos/v16r_1_00b/no/fcsp/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

1

2021-11-05T22:15:42.000Z

from operator import attrgetter import pyangbind.lib.xpathhelper as xpathhelper from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType from pyangbind.lib.base import PybindBase from decimal import Decimal from bitarray import bitarray import __builtin__ class fcsp(PybindBase): """ This class was auto-generated by the PythonClass plugin for PYANG from YANG module brocade-common-def - based on the path /no/fcsp. Each member element of the container is represented as a class variable - with a specific YANG type. """ _pyangbind_elements = {}

33.333333

102

0.808571

from operator import attrgetter import pyangbind.lib.xpathhelper as xpathhelper from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType from pyangbind.lib.base import PybindBase from decimal import Decimal from bitarray import bitarray import __builtin__ class fcsp(PybindBase): _pyangbind_elements = {}

true

1c2fc5e3838e7f3766ffd4648fa5a200e09d866f

2,394

py

Python

145-Binary-Tree-Postorder-Traversal/solution.py

Tanych/CodeTracking

86f1cb98de801f58c39d9a48ce9de12df7303d20

[ "MIT" ]

null

145-Binary-Tree-Postorder-Traversal/solution.py

Tanych/CodeTracking

86f1cb98de801f58c39d9a48ce9de12df7303d20

[ "MIT" ]

null

145-Binary-Tree-Postorder-Traversal/solution.py

Tanych/CodeTracking

86f1cb98de801f58c39d9a48ce9de12df7303d20

[ "MIT" ]

null

# Definition for a binary tree node. # class TreeNode(object): # def __init__(self, x): # self.val = x # self.left = None # self.right = None class Solution(object): def reverse(self,from_node,to_node): if from_node==to_node: return a,b,c=from_node,from_node.right,None while True: c=b.right b.right=a a=b b=c if a==to_node:break def reverseadd(self,from_node,to_node,res): self.reverse(from_node,to_node) p=to_node while True: res.append(p.val) if p==from_node: break p=p.right # get back self.reverse(to_node,from_node) def postorderTraversal(self,root): dump=TreeNode(-1) dump.left=root cur,pre=dump,None res=[] while cur: if not cur.left: cur=cur.right else: pre=cur.left while pre.right and pre.right!=cur: pre=pre.right if not pre.right: pre.right=cur cur=cur.left else: self.reverseadd(cur.left,pre,res) pre.right=None cur=cur.right return res def postorderTraversal_on(self, root): """ :type root: TreeNode :rtype: List[int] """ # using stack ways stck=[] # current node cur=root peak=last=None res=[] while cur or stck: if cur: stck.append(cur) cur=cur.left elif stck: # get the peak peak=stck[-1] # if has right branch, we need get right first # mark the peak and add the right subtree to stack # if subtree has all print out, add the peak val # last!=peak.right, aviod revisited if peak.right and last!=peak.right: cur=peak.right # no right branch, directly add to res else: res.append(peak.val) last=peak stck.pop() return res

28.164706

66

0.447786

class Solution(object): def reverse(self,from_node,to_node): if from_node==to_node: return a,b,c=from_node,from_node.right,None while True: c=b.right b.right=a a=b b=c if a==to_node:break def reverseadd(self,from_node,to_node,res): self.reverse(from_node,to_node) p=to_node while True: res.append(p.val) if p==from_node: break p=p.right self.reverse(to_node,from_node) def postorderTraversal(self,root): dump=TreeNode(-1) dump.left=root cur,pre=dump,None res=[] while cur: if not cur.left: cur=cur.right else: pre=cur.left while pre.right and pre.right!=cur: pre=pre.right if not pre.right: pre.right=cur cur=cur.left else: self.reverseadd(cur.left,pre,res) pre.right=None cur=cur.right return res def postorderTraversal_on(self, root): stck=[] cur=root peak=last=None res=[] while cur or stck: if cur: stck.append(cur) cur=cur.left elif stck: peak=stck[-1] if peak.right and last!=peak.right: cur=peak.right else: res.append(peak.val) last=peak stck.pop() return res

true

1c2fc5e42bff60eaaacc0ac9a42e4f4b9325450c

9,723

py

Python

scripts/external_libs/jsonpickle-2.0.0/tests/pandas_test.py

GabrielGanne/trex-core

688a0fe0adb890964691473723d70ffa98e00dd3

[ "Apache-2.0" ]

956

2015-06-24T15:04:55.000Z

2022-03-30T06:25:04.000Z

scripts/external_libs/jsonpickle-2.0.0/tests/pandas_test.py

hjat2005/trex-core

400f03c86c844a0096dff3f6b13e58a808aaefff

[ "Apache-2.0" ]

782

2015-09-20T15:19:00.000Z

2022-03-31T23:52:05.000Z

scripts/external_libs/jsonpickle-2.0.0/tests/pandas_test.py

hjat2005/trex-core

400f03c86c844a0096dff3f6b13e58a808aaefff

[ "Apache-2.0" ]

429

2015-06-27T19:34:21.000Z

2022-03-23T11:02:51.000Z

from __future__ import absolute_import, division, unicode_literals import datetime import pytest try: import pandas as pd import numpy as np from pandas.testing import assert_series_equal from pandas.testing import assert_frame_equal from pandas.testing import assert_index_equal except ImportError: pytest.skip('numpy is not available', allow_module_level=True) import jsonpickle import jsonpickle.ext.pandas @pytest.fixture(scope='module', autouse=True) def pandas_extension(): """Initialize the numpy extension for this test module""" jsonpickle.ext.pandas.register_handlers() yield # control to the test function. jsonpickle.ext.pandas.unregister_handlers() def roundtrip(obj): return jsonpickle.decode(jsonpickle.encode(obj)) def test_series_roundtrip(): ser = pd.Series( { 'an_int': np.int_(1), 'a_float': np.float_(2.5), 'a_nan': np.nan, 'a_minus_inf': -np.inf, 'an_inf': np.inf, 'a_str': np.str_('foo'), 'a_unicode': np.unicode_('bar'), 'date': np.datetime64('2014-01-01'), 'complex': np.complex_(1 - 2j), # TODO: the following dtypes are not currently supported. # 'object': np.object_({'a': 'b'}), } ) decoded_ser = roundtrip(ser) assert_series_equal(decoded_ser, ser) def test_dataframe_roundtrip(): df = pd.DataFrame( { 'an_int': np.int_([1, 2, 3]), 'a_float': np.float_([2.5, 3.5, 4.5]), 'a_nan': np.array([np.nan] * 3), 'a_minus_inf': np.array([-np.inf] * 3), 'an_inf': np.array([np.inf] * 3), 'a_str': np.str_('foo'), 'a_unicode': np.unicode_('bar'), 'date': np.array([np.datetime64('2014-01-01')] * 3), 'complex': np.complex_([1 - 2j, 2 - 1.2j, 3 - 1.3j]), # TODO: the following dtypes are not currently supported. # 'object': np.object_([{'a': 'b'}]*3), } ) decoded_df = roundtrip(df) assert_frame_equal(decoded_df, df) def test_multindex_dataframe_roundtrip(): df = pd.DataFrame( { 'idx_lvl0': ['a', 'b', 'c'], 'idx_lvl1': np.int_([1, 1, 2]), 'an_int': np.int_([1, 2, 3]), 'a_float': np.float_([2.5, 3.5, 4.5]), 'a_nan': np.array([np.nan] * 3), 'a_minus_inf': np.array([-np.inf] * 3), 'an_inf': np.array([np.inf] * 3), 'a_str': np.str_('foo'), 'a_unicode': np.unicode_('bar'), } ) df = df.set_index(['idx_lvl0', 'idx_lvl1']) decoded_df = roundtrip(df) assert_frame_equal(decoded_df, df) def test_dataframe_with_interval_index_roundtrip(): df = pd.DataFrame( {'a': [1, 2], 'b': [3, 4]}, index=pd.IntervalIndex.from_breaks([1, 2, 4]) ) decoded_df = roundtrip(df) assert_frame_equal(decoded_df, df) def test_index_roundtrip(): idx = pd.Index(range(5, 10)) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_datetime_index_roundtrip(): idx = pd.date_range(start='2019-01-01', end='2019-02-01', freq='D') decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_ragged_datetime_index_roundtrip(): idx = pd.DatetimeIndex(['2019-01-01', '2019-01-02', '2019-01-05']) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_timedelta_index_roundtrip(): idx = pd.timedelta_range(start='1 day', periods=4, closed='right') decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_period_index_roundtrip(): idx = pd.period_range(start='2017-01-01', end='2018-01-01', freq='M') decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_int64_index_roundtrip(): idx = pd.Int64Index([-1, 0, 3, 4]) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_uint64_index_roundtrip(): idx = pd.UInt64Index([0, 3, 4]) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_float64_index_roundtrip(): idx = pd.Float64Index([0.1, 3.7, 4.2]) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_interval_index_roundtrip(): idx = pd.IntervalIndex.from_breaks(range(5)) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_datetime_interval_index_roundtrip(): idx = pd.IntervalIndex.from_breaks(pd.date_range('2019-01-01', '2019-01-10')) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_multi_index_roundtrip(): idx = pd.MultiIndex.from_product(((1, 2, 3), ('a', 'b'))) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_timestamp_roundtrip(): obj = pd.Timestamp('2019-01-01') decoded_obj = roundtrip(obj) assert decoded_obj == obj def test_period_roundtrip(): obj = pd.Timestamp('2019-01-01') decoded_obj = roundtrip(obj) assert decoded_obj == obj def test_interval_roundtrip(): obj = pd.Interval(2, 4, closed=str('left')) decoded_obj = roundtrip(obj) assert decoded_obj == obj def test_b64(): """Test the binary encoding""" # array of substantial size is stored as b64 a = np.random.rand(20, 10) index = ['Row' + str(i) for i in range(1, a.shape[0] + 1)] columns = ['Col' + str(i) for i in range(1, a.shape[1] + 1)] df = pd.DataFrame(a, index=index, columns=columns) decoded_df = roundtrip(df) assert_frame_equal(decoded_df, df) def test_series_list_index(): """Test pandas using series with a list index""" expect = pd.Series(0, index=[1, 2, 3]) actual = roundtrip(expect) assert expect.values[0] == actual.values[0] assert 0 == actual.values[0] assert expect.index[0] == actual.index[0] assert expect.index[1] == actual.index[1] assert expect.index[2] == actual.index[2] def test_series_multi_index(): """Test pandas using series with a multi-index""" expect = pd.Series(0, index=[[1], [2], [3]]) actual = roundtrip(expect) assert expect.values[0] == actual.values[0] assert 0 == actual.values[0] assert expect.index[0] == actual.index[0] assert expect.index[0][0] == actual.index[0][0] assert expect.index[0][1] == actual.index[0][1] assert expect.index[0][2] == actual.index[0][2] def test_series_multi_index_strings(): """Test multi-index with strings""" lets = ['A', 'B', 'C'] nums = ['1', '2', '3'] midx = pd.MultiIndex.from_product([lets, nums]) expect = pd.Series(0, index=midx) actual = roundtrip(expect) assert expect.values[0] == actual.values[0] assert 0 == actual.values[0] assert expect.index[0] == actual.index[0] assert expect.index[1] == actual.index[1] assert expect.index[2] == actual.index[2] assert expect.index[3] == actual.index[3] assert expect.index[4] == actual.index[4] assert expect.index[5] == actual.index[5] assert expect.index[6] == actual.index[6] assert expect.index[7] == actual.index[7] assert expect.index[8] == actual.index[8] assert ('A', '1') == actual.index[0] assert ('A', '2') == actual.index[1] assert ('A', '3') == actual.index[2] assert ('B', '1') == actual.index[3] assert ('B', '2') == actual.index[4] assert ('B', '3') == actual.index[5] assert ('C', '1') == actual.index[6] assert ('C', '2') == actual.index[7] assert ('C', '3') == actual.index[8] def test_dataframe_with_timedelta64_dtype(): data_frame = pd.DataFrame( { 'Start': [ '2020/12/14 00:00:01', '2020/12/14 00:00:04', '2020/12/14 00:00:06', ], 'End': [ '2020/12/14 00:00:04', '2020/12/14 00:00:06', '2020/12/14 00:00:09', ], } ) data_frame['Start'] = pd.to_datetime(data_frame['Start']) data_frame['End'] = pd.to_datetime(data_frame['End']) data_frame['Duration'] = data_frame['End'] - data_frame['Start'] encoded = jsonpickle.encode(data_frame) actual = jsonpickle.decode(encoded) assert isinstance(actual, pd.DataFrame) assert data_frame['Start'][0] == actual['Start'][0] assert data_frame['Start'][1] == actual['Start'][1] assert data_frame['Start'][2] == actual['Start'][2] assert data_frame['End'][0] == actual['End'][0] assert data_frame['End'][1] == actual['End'][1] assert data_frame['End'][2] == actual['End'][2] assert isinstance(actual['Duration'][0], datetime.timedelta) assert isinstance(actual['Duration'][1], datetime.timedelta) assert isinstance(actual['Duration'][2], datetime.timedelta) assert data_frame['Duration'][0] == actual['Duration'][0] assert data_frame['Duration'][1] == actual['Duration'][1] assert data_frame['Duration'][2] == actual['Duration'][2] def test_multilevel_columns(): iterables = [['inj', 'prod'], ['hourly', 'cumulative']] names = ['first', 'second'] # transform it to tuples columns = pd.MultiIndex.from_product(iterables, names=names) # build a multi-index from it data_frame = pd.DataFrame( np.random.randn(3, 4), index=['A', 'B', 'C'], columns=columns ) encoded = jsonpickle.encode(data_frame) cloned_data_frame = jsonpickle.decode(encoded) assert isinstance(cloned_data_frame, pd.DataFrame) assert data_frame.columns.names == cloned_data_frame.columns.names assert_frame_equal(data_frame, cloned_data_frame) if __name__ == '__main__': pytest.main([__file__])

31.364516

81

0.622236

from __future__ import absolute_import, division, unicode_literals import datetime import pytest try: import pandas as pd import numpy as np from pandas.testing import assert_series_equal from pandas.testing import assert_frame_equal from pandas.testing import assert_index_equal except ImportError: pytest.skip('numpy is not available', allow_module_level=True) import jsonpickle import jsonpickle.ext.pandas @pytest.fixture(scope='module', autouse=True) def pandas_extension(): jsonpickle.ext.pandas.register_handlers() yield jsonpickle.ext.pandas.unregister_handlers() def roundtrip(obj): return jsonpickle.decode(jsonpickle.encode(obj)) def test_series_roundtrip(): ser = pd.Series( { 'an_int': np.int_(1), 'a_float': np.float_(2.5), 'a_nan': np.nan, 'a_minus_inf': -np.inf, 'an_inf': np.inf, 'a_str': np.str_('foo'), 'a_unicode': np.unicode_('bar'), 'date': np.datetime64('2014-01-01'), 'complex': np.complex_(1 - 2j), } ) decoded_ser = roundtrip(ser) assert_series_equal(decoded_ser, ser) def test_dataframe_roundtrip(): df = pd.DataFrame( { 'an_int': np.int_([1, 2, 3]), 'a_float': np.float_([2.5, 3.5, 4.5]), 'a_nan': np.array([np.nan] * 3), 'a_minus_inf': np.array([-np.inf] * 3), 'an_inf': np.array([np.inf] * 3), 'a_str': np.str_('foo'), 'a_unicode': np.unicode_('bar'), 'date': np.array([np.datetime64('2014-01-01')] * 3), 'complex': np.complex_([1 - 2j, 2 - 1.2j, 3 - 1.3j]), } ) decoded_df = roundtrip(df) assert_frame_equal(decoded_df, df) def test_multindex_dataframe_roundtrip(): df = pd.DataFrame( { 'idx_lvl0': ['a', 'b', 'c'], 'idx_lvl1': np.int_([1, 1, 2]), 'an_int': np.int_([1, 2, 3]), 'a_float': np.float_([2.5, 3.5, 4.5]), 'a_nan': np.array([np.nan] * 3), 'a_minus_inf': np.array([-np.inf] * 3), 'an_inf': np.array([np.inf] * 3), 'a_str': np.str_('foo'), 'a_unicode': np.unicode_('bar'), } ) df = df.set_index(['idx_lvl0', 'idx_lvl1']) decoded_df = roundtrip(df) assert_frame_equal(decoded_df, df) def test_dataframe_with_interval_index_roundtrip(): df = pd.DataFrame( {'a': [1, 2], 'b': [3, 4]}, index=pd.IntervalIndex.from_breaks([1, 2, 4]) ) decoded_df = roundtrip(df) assert_frame_equal(decoded_df, df) def test_index_roundtrip(): idx = pd.Index(range(5, 10)) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_datetime_index_roundtrip(): idx = pd.date_range(start='2019-01-01', end='2019-02-01', freq='D') decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_ragged_datetime_index_roundtrip(): idx = pd.DatetimeIndex(['2019-01-01', '2019-01-02', '2019-01-05']) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_timedelta_index_roundtrip(): idx = pd.timedelta_range(start='1 day', periods=4, closed='right') decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_period_index_roundtrip(): idx = pd.period_range(start='2017-01-01', end='2018-01-01', freq='M') decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_int64_index_roundtrip(): idx = pd.Int64Index([-1, 0, 3, 4]) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_uint64_index_roundtrip(): idx = pd.UInt64Index([0, 3, 4]) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_float64_index_roundtrip(): idx = pd.Float64Index([0.1, 3.7, 4.2]) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_interval_index_roundtrip(): idx = pd.IntervalIndex.from_breaks(range(5)) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_datetime_interval_index_roundtrip(): idx = pd.IntervalIndex.from_breaks(pd.date_range('2019-01-01', '2019-01-10')) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_multi_index_roundtrip(): idx = pd.MultiIndex.from_product(((1, 2, 3), ('a', 'b'))) decoded_idx = roundtrip(idx) assert_index_equal(decoded_idx, idx) def test_timestamp_roundtrip(): obj = pd.Timestamp('2019-01-01') decoded_obj = roundtrip(obj) assert decoded_obj == obj def test_period_roundtrip(): obj = pd.Timestamp('2019-01-01') decoded_obj = roundtrip(obj) assert decoded_obj == obj def test_interval_roundtrip(): obj = pd.Interval(2, 4, closed=str('left')) decoded_obj = roundtrip(obj) assert decoded_obj == obj def test_b64(): a = np.random.rand(20, 10) index = ['Row' + str(i) for i in range(1, a.shape[0] + 1)] columns = ['Col' + str(i) for i in range(1, a.shape[1] + 1)] df = pd.DataFrame(a, index=index, columns=columns) decoded_df = roundtrip(df) assert_frame_equal(decoded_df, df) def test_series_list_index(): expect = pd.Series(0, index=[1, 2, 3]) actual = roundtrip(expect) assert expect.values[0] == actual.values[0] assert 0 == actual.values[0] assert expect.index[0] == actual.index[0] assert expect.index[1] == actual.index[1] assert expect.index[2] == actual.index[2] def test_series_multi_index(): expect = pd.Series(0, index=[[1], [2], [3]]) actual = roundtrip(expect) assert expect.values[0] == actual.values[0] assert 0 == actual.values[0] assert expect.index[0] == actual.index[0] assert expect.index[0][0] == actual.index[0][0] assert expect.index[0][1] == actual.index[0][1] assert expect.index[0][2] == actual.index[0][2] def test_series_multi_index_strings(): lets = ['A', 'B', 'C'] nums = ['1', '2', '3'] midx = pd.MultiIndex.from_product([lets, nums]) expect = pd.Series(0, index=midx) actual = roundtrip(expect) assert expect.values[0] == actual.values[0] assert 0 == actual.values[0] assert expect.index[0] == actual.index[0] assert expect.index[1] == actual.index[1] assert expect.index[2] == actual.index[2] assert expect.index[3] == actual.index[3] assert expect.index[4] == actual.index[4] assert expect.index[5] == actual.index[5] assert expect.index[6] == actual.index[6] assert expect.index[7] == actual.index[7] assert expect.index[8] == actual.index[8] assert ('A', '1') == actual.index[0] assert ('A', '2') == actual.index[1] assert ('A', '3') == actual.index[2] assert ('B', '1') == actual.index[3] assert ('B', '2') == actual.index[4] assert ('B', '3') == actual.index[5] assert ('C', '1') == actual.index[6] assert ('C', '2') == actual.index[7] assert ('C', '3') == actual.index[8] def test_dataframe_with_timedelta64_dtype(): data_frame = pd.DataFrame( { 'Start': [ '2020/12/14 00:00:01', '2020/12/14 00:00:04', '2020/12/14 00:00:06', ], 'End': [ '2020/12/14 00:00:04', '2020/12/14 00:00:06', '2020/12/14 00:00:09', ], } ) data_frame['Start'] = pd.to_datetime(data_frame['Start']) data_frame['End'] = pd.to_datetime(data_frame['End']) data_frame['Duration'] = data_frame['End'] - data_frame['Start'] encoded = jsonpickle.encode(data_frame) actual = jsonpickle.decode(encoded) assert isinstance(actual, pd.DataFrame) assert data_frame['Start'][0] == actual['Start'][0] assert data_frame['Start'][1] == actual['Start'][1] assert data_frame['Start'][2] == actual['Start'][2] assert data_frame['End'][0] == actual['End'][0] assert data_frame['End'][1] == actual['End'][1] assert data_frame['End'][2] == actual['End'][2] assert isinstance(actual['Duration'][0], datetime.timedelta) assert isinstance(actual['Duration'][1], datetime.timedelta) assert isinstance(actual['Duration'][2], datetime.timedelta) assert data_frame['Duration'][0] == actual['Duration'][0] assert data_frame['Duration'][1] == actual['Duration'][1] assert data_frame['Duration'][2] == actual['Duration'][2] def test_multilevel_columns(): iterables = [['inj', 'prod'], ['hourly', 'cumulative']] names = ['first', 'second'] columns = pd.MultiIndex.from_product(iterables, names=names) data_frame = pd.DataFrame( np.random.randn(3, 4), index=['A', 'B', 'C'], columns=columns ) encoded = jsonpickle.encode(data_frame) cloned_data_frame = jsonpickle.decode(encoded) assert isinstance(cloned_data_frame, pd.DataFrame) assert data_frame.columns.names == cloned_data_frame.columns.names assert_frame_equal(data_frame, cloned_data_frame) if __name__ == '__main__': pytest.main([__file__])

true

1c2fc604ac3d747626eaa5c5d0cc9a69eace435f

1,293

py

Python

worker/tasks/db_writer.py

ZTJiu/WebsiteIpParser

173703a03e329cb9488a9637e84b421a1ed20a19

[ "Apache-2.0" ]

null

worker/tasks/db_writer.py

ZTJiu/WebsiteIpParser

173703a03e329cb9488a9637e84b421a1ed20a19

[ "Apache-2.0" ]

null

worker/tasks/db_writer.py

ZTJiu/WebsiteIpParser

173703a03e329cb9488a9637e84b421a1ed20a19

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding=utf-8 -*- ########################################### # File : db_writer.py # Date : 2017-09-17 # Author: Zhang Tianjiu # Email : zhangtianjiu@vip.qq.com ########################################### from sqlalchemy import Table, MetaData, Column, String, create_engine from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.declarative import declarative_base from conf import get_db_info # 创建对象的基类: Base = declarative_base() # 初始化数据库连接: engine = create_engine('mysql+mysqlconnector://{}'.format(get_db_info)) metadata = MetaData() DbSession = sessionmaker(bind=engine) def init_table(): ip_list_table = Table('ip_list', metadata, Column('ip', String(20), primary_key=True), Column('website', String(60))) ip_list_table.create(engine) init_table() # 定义User对象: class Ip(Base): # 表的名字: __tablename__ = 'ip_list' # 表的结构: ip = Column(String(20), primary_key=True) url = Column(String(40)) def insert_data(ip, website): # 创建session对象: session = DbSession() # 创建新User对象: new_ip = Ip(ip = ip, url = website) # 添加到session: session.add(new_ip) # 提交即保存到数据库: session.commit() # 关闭session: session.close() __all__ = ['insert_data']

23.509091

71

0.615623

true

1c2fc67455b0e53a2eb879e29cb998a2ac40df9f

3,463

py

Python

app/tests/testDownload.py

lhorne-gavant/OpenPubArchive-Content-Server-1

2b7c02417a8bb37f5a627343fab7fa05dc532bf7

[ "Apache-2.0" ]

null

app/tests/testDownload.py

lhorne-gavant/OpenPubArchive-Content-Server-1

2b7c02417a8bb37f5a627343fab7fa05dc532bf7

[ "Apache-2.0" ]

null

app/tests/testDownload.py

lhorne-gavant/OpenPubArchive-Content-Server-1

2b7c02417a8bb37f5a627343fab7fa05dc532bf7

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- # Third-party imports... #from nose.tools import assert_true # This test module is in development... import sys import os.path folder = os.path.basename(os.path.dirname(os.path.abspath(__file__))) if folder == "tests": # testing from within WingIDE, default folder is tests sys.path.append('../libs') sys.path.append('../config') sys.path.append('../../app') else: # python running from should be within folder app sys.path.append('./libs') sys.path.append('./config') from starlette.testclient import TestClient import unittest from localsecrets import TESTUSER, TESTPW, SECRET_KEY, ALGORITHM import jwt from datetime import datetime from unitTestConfig import base_api, base_plus_endpoint_encoded from main import app client = TestClient(app) class TestDownload(unittest.TestCase): """ Tests for basic login and Download Note: tests are performed in alphabetical order, hence the function naming with forced order in the names. """ def test_0_login(self): full_URL = base_plus_endpoint_encoded(f'/v2/Session/Login/?grant_type=password&username={TESTUSER}&password={TESTPW}') response = client.get(full_URL) # Confirm that the request-response cycle completed successfully. assert(response.ok == True) r = response.json() access_token = r["access_token"] session_id = r["session_id"] decoded_access_token = jwt.decode(access_token, key=SECRET_KEY, algorithms=ALGORITHM ) expires_time = datetime.fromtimestamp(decoded_access_token['exp']) orig_session_id = decoded_access_token['orig_session_id'] assert(r["authenticated"] == True) assert(session_id == orig_session_id) print (decoded_access_token ) def test_1_Download(self): full_URL = base_plus_endpoint_encoded(f'/v2/Session/Login/?grant_type=password&username={TESTUSER}&password={TESTPW}') response = client.get(full_URL) # Confirm that the request-response cycle completed successfully. full_URL = base_plus_endpoint_encoded(f'/v2/Documents/Downloads/PDFORIG/IJP.077.0217A/') # local, this works...but fails in the response.py code trying to convert self.status to int. response = client.get(full_URL) # Confirm that the request-response cycle completed successfully. assert(response.ok == True) def test_2_Download(self): full_URL = base_plus_endpoint_encoded(f'/v2/Documents/Downloads/PDF/IFP.017.0240A/') response = client.get(full_URL) # Confirm that the request-response cycle completed successfully. assert(response.ok == True) def test_3_Download(self): full_URL = base_plus_endpoint_encoded(f'/v2/Documents/Downloads/EPUB/IJPSP.009.0324A/') response = client.get(full_URL) # Confirm that the request-response cycle completed successfully. assert(response.ok == True) def test_4_Download(self): full_URL = base_plus_endpoint_encoded(f'/v2/Documents/Downloads/HTML/IJPSP.009.0324A/') response = client.get(full_URL) # Confirm that the request-response cycle completed successfully. assert(response.ok == True) if __name__ == '__main__': unittest.main()

38.477778

126

0.674848

import sys import os.path folder = os.path.basename(os.path.dirname(os.path.abspath(__file__))) if folder == "tests": sys.path.append('../libs') sys.path.append('../config') sys.path.append('../../app') else: sys.path.append('./libs') sys.path.append('./config') from starlette.testclient import TestClient import unittest from localsecrets import TESTUSER, TESTPW, SECRET_KEY, ALGORITHM import jwt from datetime import datetime from unitTestConfig import base_api, base_plus_endpoint_encoded from main import app client = TestClient(app) class TestDownload(unittest.TestCase): def test_0_login(self): full_URL = base_plus_endpoint_encoded(f'/v2/Session/Login/?grant_type=password&username={TESTUSER}&password={TESTPW}') response = client.get(full_URL) assert(response.ok == True) r = response.json() access_token = r["access_token"] session_id = r["session_id"] decoded_access_token = jwt.decode(access_token, key=SECRET_KEY, algorithms=ALGORITHM ) expires_time = datetime.fromtimestamp(decoded_access_token['exp']) orig_session_id = decoded_access_token['orig_session_id'] assert(r["authenticated"] == True) assert(session_id == orig_session_id) print (decoded_access_token ) def test_1_Download(self): full_URL = base_plus_endpoint_encoded(f'/v2/Session/Login/?grant_type=password&username={TESTUSER}&password={TESTPW}') response = client.get(full_URL) full_URL = base_plus_endpoint_encoded(f'/v2/Documents/Downloads/PDFORIG/IJP.077.0217A/') response = client.get(full_URL) assert(response.ok == True) def test_2_Download(self): full_URL = base_plus_endpoint_encoded(f'/v2/Documents/Downloads/PDF/IFP.017.0240A/') response = client.get(full_URL) assert(response.ok == True) def test_3_Download(self): full_URL = base_plus_endpoint_encoded(f'/v2/Documents/Downloads/EPUB/IJPSP.009.0324A/') response = client.get(full_URL) assert(response.ok == True) def test_4_Download(self): full_URL = base_plus_endpoint_encoded(f'/v2/Documents/Downloads/HTML/IJPSP.009.0324A/') response = client.get(full_URL) assert(response.ok == True) if __name__ == '__main__': unittest.main()

true

1c2fc75c25ffb9aca3dbac7b67593a66e503ab2c

2,021

py

Python

accounts/forms.py

Nor-Mal/django-ecommerce

e57d316cb78fbe4315fb0a4b07a79779143981dd

[ "Apache-2.0" ]

2

2021-09-05T20:45:59.000Z

2021-11-03T11:55:20.000Z

accounts/forms.py

Nor-Mal/django-ecommerce

e57d316cb78fbe4315fb0a4b07a79779143981dd

[ "Apache-2.0" ]

null

accounts/forms.py

Nor-Mal/django-ecommerce

e57d316cb78fbe4315fb0a4b07a79779143981dd

[ "Apache-2.0" ]

null

from django import forms from django.contrib.auth.forms import UserCreationForm from django.contrib.auth import get_user_model from .models import Customer, Address class UserCreateForm(UserCreationForm): class Meta: fields = ('username', 'first_name', 'last_name', 'email', 'password1', 'password2') model = get_user_model() def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields['username'].label = 'Username' self.fields['first_name'].label = 'First name' self.fields['first_name'].blank = False self.fields['last_name'].label = 'Last name' self.fields['last_name'].blank = False self.fields['email'].label = 'Email address' self.fields['email'].blank = False class UserUpdateForm(forms.ModelForm): class Meta: fields = ('username', 'first_name', 'last_name', 'email', 'date_joined', 'last_login') model = get_user_model() def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields['username'].label = 'Username' self.fields['first_name'].label = 'First name' self.fields['last_name'].label = 'Last name' self.fields['email'].label = 'Email address' self.fields['date_joined'].label = 'Created on' self.fields['last_login'].label = 'Last login' self.fields['date_joined'].disabled = True self.fields['last_login'].disabled = True class CustomerUpdateForm(forms.ModelForm): class Meta: model = Customer fields = ['customer_id'] class AddressUpdateForm(forms.ModelForm): class Meta: model = Address exclude = ['customer'] def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields['address_name'].disabled = True class AddressCreateForm(forms.ModelForm): class Meta: model = Address exclude = ['customer']

33.131148

95

0.620485

from django import forms from django.contrib.auth.forms import UserCreationForm from django.contrib.auth import get_user_model from .models import Customer, Address class UserCreateForm(UserCreationForm): class Meta: fields = ('username', 'first_name', 'last_name', 'email', 'password1', 'password2') model = get_user_model() def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields['username'].label = 'Username' self.fields['first_name'].label = 'First name' self.fields['first_name'].blank = False self.fields['last_name'].label = 'Last name' self.fields['last_name'].blank = False self.fields['email'].label = 'Email address' self.fields['email'].blank = False class UserUpdateForm(forms.ModelForm): class Meta: fields = ('username', 'first_name', 'last_name', 'email', 'date_joined', 'last_login') model = get_user_model() def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields['username'].label = 'Username' self.fields['first_name'].label = 'First name' self.fields['last_name'].label = 'Last name' self.fields['email'].label = 'Email address' self.fields['date_joined'].label = 'Created on' self.fields['last_login'].label = 'Last login' self.fields['date_joined'].disabled = True self.fields['last_login'].disabled = True class CustomerUpdateForm(forms.ModelForm): class Meta: model = Customer fields = ['customer_id'] class AddressUpdateForm(forms.ModelForm): class Meta: model = Address exclude = ['customer'] def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields['address_name'].disabled = True class AddressCreateForm(forms.ModelForm): class Meta: model = Address exclude = ['customer']

true

1c2fc7a04f19443bfe8f1d68c70f77000c87265a

482

py

Python

api/models/images.py

syth0le/async_cookeat

0cecdd44c064be6fe19c0d0ae8342d7baf5a9bb8

[ "CC0-1.0" ]

null

api/models/images.py

syth0le/async_cookeat

0cecdd44c064be6fe19c0d0ae8342d7baf5a9bb8

[ "CC0-1.0" ]

null

api/models/images.py

syth0le/async_cookeat

0cecdd44c064be6fe19c0d0ae8342d7baf5a9bb8

[ "CC0-1.0" ]

null

from sqlalchemy import Column, String, Integer, ForeignKey from sqlalchemy.orm import relationship from api.utils.db_init import Base class Images(Base): __tablename__ = 'images' id = Column(Integer, primary_key=True, unique=True) image = Column(String(50), nullable=False) recipe_id = Column(Integer, ForeignKey("recipe.id")) recipe_image = relationship("Recipe", back_populates="images") def __repr__(self): return '<Images %r>' % self.image

26.777778

66

0.717842

from sqlalchemy import Column, String, Integer, ForeignKey from sqlalchemy.orm import relationship from api.utils.db_init import Base class Images(Base): __tablename__ = 'images' id = Column(Integer, primary_key=True, unique=True) image = Column(String(50), nullable=False) recipe_id = Column(Integer, ForeignKey("recipe.id")) recipe_image = relationship("Recipe", back_populates="images") def __repr__(self): return '<Images %r>' % self.image

true

1c2fc82b12fbba10922a54228785c5d486281380

66

py

Python

streamfig/__init__.py

TiphaineV/streamfig

4acd92625c34bde0089b7963ec076d902d8ebba1

[ "MIT" ]

5

2019-09-19T07:11:13.000Z

2021-12-13T11:18:41.000Z

streamfig/__init__.py

TiphaineV/streamfig

4acd92625c34bde0089b7963ec076d902d8ebba1

[ "MIT" ]

3

2020-04-23T17:37:23.000Z

2021-12-13T09:40:31.000Z

streamfig/__init__.py

TiphaineV/streamfig

4acd92625c34bde0089b7963ec076d902d8ebba1

[ "MIT" ]

5

2018-12-14T13:53:33.000Z

2020-05-18T17:22:52.000Z

from .streamfig import StreamFig from .printers import FigPrinter

22

32

0.848485

from .streamfig import StreamFig from .printers import FigPrinter

true

1c2fc89fac73d58e54ab12a3e1de3df8b88365e0

26,158

py

Python

kiali_qe/tests/test_istio_config_validation.py

Hawkular-QE/kiali-qe-python

24e058def1efd0a509a2b599901f4179dbf37583

[ "Apache-2.0" ]

null

kiali_qe/tests/test_istio_config_validation.py

Hawkular-QE/kiali-qe-python

24e058def1efd0a509a2b599901f4179dbf37583

[ "Apache-2.0" ]

3

2018-03-28T17:11:13.000Z

2018-03-28T17:55:08.000Z

kiali_qe/tests/test_istio_config_validation.py

Hawkular-QE/kiali-qe-python

24e058def1efd0a509a2b599901f4179dbf37583

[ "Apache-2.0" ]

2

2018-02-13T10:56:03.000Z

2018-03-20T14:07:51.000Z

import pytest from selenium.common.exceptions import NoSuchElementException from kiali_qe.tests import ValidationsTest, ConfigValidationObject, ServiceValidationObject from kiali_qe.utils.path import istio_objects_validation_path from kiali_qe.components.error_codes import ( KIA0205, KIA0401, KIA0301, KIA0302, KIA0201, KIA0202, KIA0203, KIA0209, KIA1102, KIA0701, KIA0601, KIA1104, KIA0204, KIA0001, KIA0004, KIA0002, KIA0003, KIA1103, KIA1004, KIA1006, KIA0105, KIA1106, KIA1107, KIA1101 ) ''' Tests are divided into groups using different services and namespaces. This way the group of tests can be run in parallel. ''' BOOKINFO = 'bookinfo' BOOKINFO2 = 'bookinfo2' ISTIO_SYSTEM = 'istio-system' SCENARIO_1 = "two_gateways_same_host.yaml" SCENARIO_2 = "no_matching_workload_gateway.yaml" SCENARIO_3 = "more_destination_rules.yaml" SCENARIO_4 = "no_matching_entry_registry.yaml" SCENARIO_5 = "subset_label_not_found.yaml" SCENARIO_6 = "missing_mesh_policy.yaml" SCENARIO_7 = "mtls_settings_overridden.yaml" SCENARIO_8 = "mesh_policy_permissive.yaml" SCENARIO_9 = "mesh_policy_mtls_enable.yaml" SCENARIO_10 = "non_existing_gateway.yaml" SCENARIO_11 = "not_defined_protocol.yaml" SCENARIO_12 = "destination_rule_fqdn.yaml" SCENARIO_13 = "destination_rule_wrong_fqdn.yaml" SCENARIO_14 = "ratings_java_svc.yaml" SCENARIO_15 = "port_name_suffix_missing.yaml" SCENARIO_16 = "virtual-service-less-than-100-weight.yaml" SCENARIO_17 = "wrong-host-label-sidecar.yaml" SCENARIO_18 = "duplicate-no-workload-sidecar.yaml" SCENARIO_19 = "duplicate-workload-sidecar.yaml" SCENARIO_20 = "default-sidecar-with-workload.yaml" SCENARIO_21 = "mesh_policy_disable.yaml" SCENARIO_22 = "auth-policy-mtls.yaml" SCENARIO_23 = "vs_subset_service_entry.yaml" SCENARIO_24 = "vs_wrong_subset_no_dr.yaml" SCENARIO_25 = "duplicate-vs-gateway.yaml" SCENARIO_26 = "vs_destination_host_not_found.yaml" SCENARIO_27 = "request_auth_no_workload.yaml" SCENARIO_28 = "two_gateways_different_selectors.yaml" SCENARIO_29 = "subset_not_have_label.yaml" @pytest.mark.p_group_last def test_two_gateways_same_host(kiali_client, openshift_client): """ More than one Gateway for the same host port combination """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_1, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='Gateway', object_name='bookinfo-gateway-auto-host', namespace=BOOKINFO, error_messages=[KIA0301]), ConfigValidationObject( object_type='Gateway', object_name='bookinfo-gateway-auto-host-copy', namespace=BOOKINFO2, error_messages=[KIA0301]) ], ignore_common_errors=False) @pytest.mark.p_group_last def test_two_gateways_different_selectors(kiali_client, openshift_client): """ More than one Gateway for the same host port combination referring to different selectors """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_28, namespace=ISTIO_SYSTEM, config_validation_objects=[ ConfigValidationObject( object_type='Gateway', object_name='istio-gateway-prv', namespace=ISTIO_SYSTEM, error_messages=[KIA0302]), ConfigValidationObject( object_type='Gateway', object_name='istio-gateway-pub', namespace=ISTIO_SYSTEM, error_messages=[KIA0302]) ], ignore_common_errors=False) @pytest.mark.p_group_last def test_gateway_no_matching_workload(kiali_client, openshift_client): """ No matching workload found for gateway selector in this namespace """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_2, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='Gateway', object_name='bookinfo-gateway-auto-not-match', namespace=BOOKINFO, error_messages=[KIA0302]) ]) @pytest.mark.p_group_last def test_more_drs_same_host_port(kiali_client, openshift_client): """ More than one DestinationRules for the same host subset combination """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_3, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-dr1-auto', namespace=BOOKINFO, error_messages=[KIA0201]), ConfigValidationObject( object_type='DestinationRule', object_name='reviews-dr2-auto', namespace=BOOKINFO, error_messages=[KIA0201]) ], ignore_common_errors=False) @pytest.mark.p_group_last def test_no_matching_entry_dr(kiali_client, openshift_client): """ This host has no matching entry in the service registry (service, workload or service entries) """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_4, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-no-match-entry-auto', namespace=BOOKINFO, error_messages=[KIA0202]) ]) @pytest.mark.p_group_last def test_subset_label_not_found(kiali_client, openshift_client): """ This subset’s labels are not found in any matching host """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_5, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-no-subset-label-auto', namespace=BOOKINFO, error_messages=[KIA0203, KIA0203]) ]) @pytest.mark.p_group_last def test_mesh_policy_not_found(kiali_client, openshift_client): """ PeerAuthentication enabling mTLS is missing """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_6, namespace=ISTIO_SYSTEM, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='default', namespace=ISTIO_SYSTEM, error_messages=[KIA0205]) ]) @pytest.mark.p_group_last def test_mtls_settings_overridden(kiali_client, openshift_client): """ mTLS settings of a non-local Destination Rule are overridden """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_7, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='default', namespace=ISTIO_SYSTEM, error_messages=[KIA0205]), ConfigValidationObject( object_type='DestinationRule', object_name='reviews-overridden-auto', namespace=BOOKINFO, error_messages=[KIA0204]) ]) @pytest.mark.p_group_last def test_meshpolicy_permissive_ok(kiali_client, openshift_client): """ PeerAuthentication enabling mTLS found, permissive policy is needed: PeerAuthentication to enable PERMISSIVE mode to all the workloads in the mesh """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_8, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='default', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='PeerAuthentication', object_name='default', namespace=ISTIO_SYSTEM, error_messages=[]) ]) @pytest.mark.p_group_last def test_meshpolicy_mtls_enable_ok(kiali_client, openshift_client): """ PeerAuthentication enabling mTLS found, permissive policy is needed: DestinatonRule to enable mTLS instead of disabling it (change the mode to ISTIO_MUTUAL) """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_9, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='default', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='PeerAuthentication', object_name='default', namespace=ISTIO_SYSTEM, error_messages=[KIA0401]) ]) @pytest.mark.p_group_last def test_vs_to_non_existing_gateway(kiali_client, openshift_client): """ VirtualService is pointing to a non-existent gateway """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_10, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='details-vs-non-existing-gateway-auto', namespace=BOOKINFO, error_messages=[KIA1102]) ]) @pytest.mark.p_group_last def test_vs_not_defined_protocol(kiali_client, openshift_client): """ VirtualService doesn’t define any route protocol """ try: tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_11, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='details-not-defined-protocol', namespace=BOOKINFO, error_messages=[KIA1103]) ]) except NoSuchElementException: # because vs should have protocol defined pass @pytest.mark.p_group_last def test_dr_fqdn_ok(kiali_client, openshift_client): """ Host in DR is given in FQDN """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_12, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-dr-fqdn-auto', namespace=BOOKINFO, error_messages=[]) ]) @pytest.mark.p_group_last def test_dr_fqdn_not_exist(kiali_client, openshift_client): """ Host in DR is given in FQDN which does not exist """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_13, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-dr-wrong-fqdn-auto', namespace=BOOKINFO, error_messages=[KIA0202]) ]) @pytest.mark.p_group_last def __test_deployment_port_not_found(kiali_client, openshift_client): """ Deployment exposing same port as Service not found """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_service_validation( scenario=SCENARIO_14, service_name='ratings-java', namespace='bookinfo', service_validation_objects=[ ServiceValidationObject( error_message=KIA0701)]) @pytest.mark.p_group_last def __test_port_name_suffix(kiali_client, openshift_client): """ Port name must follow <protocol>[-suffix] form """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_service_validation( scenario=SCENARIO_15, service_name='ratings-java-svc-suffix', namespace='bookinfo', service_validation_objects=[ ServiceValidationObject( error_message=KIA0601)]) @pytest.mark.p_group_last def test_vs_less_than_100_weight(kiali_client, openshift_client): """ VirtualService has only weight < 100 """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_16, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='virtual-service-less-100-weight-auto', namespace=BOOKINFO, error_messages=[KIA1104]) ]) @pytest.mark.p_group_last def test_sidecar_errors(kiali_client, openshift_client): """ Multiple errors """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_17, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='Sidecar', object_name='wrong-host-sidecar-auto', namespace=BOOKINFO, error_messages=[KIA0004, KIA1004, KIA1004, KIA1004, KIA1004]) ]) @pytest.mark.p_group_last def test_duplicate_sidecar_errors(kiali_client, openshift_client): """ More than one selector-less Sidecar in the same namespace """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_18, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='Sidecar', object_name='dupliacate-sidecar1-auto', namespace=BOOKINFO, error_messages=[KIA0002, KIA1004, KIA1004]), ConfigValidationObject( object_type='Sidecar', object_name='dupliacate-sidecar2-auto', namespace=BOOKINFO, error_messages=[KIA0002, KIA1004, KIA1004]) ]) @pytest.mark.p_group_last def test_duplicate_workload_sidecar_errors(kiali_client, openshift_client): """ More than one selector-less Sidecar in the same namespace """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_19, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='Sidecar', object_name='dupliacate-workload-sidecar1-auto', namespace=BOOKINFO, error_messages=[KIA1004, KIA1004, KIA0003]), ConfigValidationObject( object_type='Sidecar', object_name='dupliacate-workload-sidecar2-auto', namespace=BOOKINFO, error_messages=[KIA1004, KIA1004, KIA0003]) ]) @pytest.mark.p_group_last def test_default_workload_sidecar(kiali_client, openshift_client): """ Global default sidecar should not have workloadSelector """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_20, namespace=ISTIO_SYSTEM, config_validation_objects=[ ConfigValidationObject( object_type='Sidecar', object_name='default-sidecar-workload-auto', namespace=ISTIO_SYSTEM, error_messages=[KIA1006, KIA0004]) ]) @pytest.mark.p_group_last def test_meshpolicy_disabled_ok(kiali_client, openshift_client): """ PeerAuthentication disabling mtls for the whole namespace (mode = DISABLE) Destination Rule disabling mTLS for a whole namespace (mode = DISABLE) """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_21, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='disable-mtls', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='PeerAuthentication', object_name='default', namespace=BOOKINFO, error_messages=[]) ]) @pytest.mark.p_group_last def test_authpolicy_validations_mtls(kiali_client, openshift_client): """ KIA0105 This field requires mTLS to be enabled from.source.{namespaces | notNamespaces | principals | notPrincipals} when.key = {source.principal | source.namespace | connection.sni } """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_22, namespace=BOOKINFO2, config_validation_objects=[ ConfigValidationObject( object_type='AuthorizationPolicy', object_name='authpolicymtls', namespace=BOOKINFO2, error_messages=([KIA0105, KIA0105, KIA0105, KIA0105, KIA0105, KIA0105, KIA0105] if not openshift_client.is_auto_mtls() else [])) ]) @pytest.mark.p_group_last def test_vs_subset_validations_service_entry(kiali_client, openshift_client): """ KIA1107 Subset found as ServiceEntry exists """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_23, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='orahub-vs', namespace=BOOKINFO, error_messages=[KIA1104, KIA1104]) ]) @pytest.mark.p_group_last def test_vs_subset_validations_no_service_entry(kiali_client, openshift_client): """ KIA1107 Subset not found as ServiceEntry missing """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_24, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='orahub-vs-no-dr', namespace=BOOKINFO, error_messages=[KIA1104, KIA1104, KIA1107, KIA1107]) ]) @pytest.mark.p_group_last def test_vs_duplicate_gateway(kiali_client, openshift_client): """ KIA1106 More than one Virtual Service for same host """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_25, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='admin-vs-2', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='VirtualService', object_name='admin-vs', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='VirtualService', object_name='user-vs-2', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='VirtualService', object_name='user-vs', namespace=BOOKINFO, error_messages=[]) ]) @pytest.mark.p_group_last def test_vs_destination_host_not_found(kiali_client, openshift_client): """ KIA1101 DestinationWeight on route doesn't have a valid service (host not found) """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_26, namespace=ISTIO_SYSTEM, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='foo-dev', namespace=ISTIO_SYSTEM, error_messages=[KIA1101]) ]) @pytest.mark.p_group_last def test_request_auth_workload_not_found(kiali_client, openshift_client): """ KIA0003, KIA0004, KIA0002 """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_27, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-dup-1', namespace=BOOKINFO, error_messages=[KIA0003]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-dup-2', namespace=BOOKINFO, error_messages=[KIA0003]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-matching', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-no-matching', namespace=BOOKINFO, error_messages=[KIA0004]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-ns-wise', namespace=BOOKINFO, error_messages=[KIA0002]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-ns-wise-1', namespace=BOOKINFO, error_messages=[KIA0002]) ]) @pytest.mark.p_group_last def test_subset_no_label(kiali_client, openshift_client): """ This subset have not label """ tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_29, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-subset-not-label-auto', namespace=BOOKINFO, error_messages=[KIA0209]) ])

36.08

98

0.652038

import pytest from selenium.common.exceptions import NoSuchElementException from kiali_qe.tests import ValidationsTest, ConfigValidationObject, ServiceValidationObject from kiali_qe.utils.path import istio_objects_validation_path from kiali_qe.components.error_codes import ( KIA0205, KIA0401, KIA0301, KIA0302, KIA0201, KIA0202, KIA0203, KIA0209, KIA1102, KIA0701, KIA0601, KIA1104, KIA0204, KIA0001, KIA0004, KIA0002, KIA0003, KIA1103, KIA1004, KIA1006, KIA0105, KIA1106, KIA1107, KIA1101 ) BOOKINFO = 'bookinfo' BOOKINFO2 = 'bookinfo2' ISTIO_SYSTEM = 'istio-system' SCENARIO_1 = "two_gateways_same_host.yaml" SCENARIO_2 = "no_matching_workload_gateway.yaml" SCENARIO_3 = "more_destination_rules.yaml" SCENARIO_4 = "no_matching_entry_registry.yaml" SCENARIO_5 = "subset_label_not_found.yaml" SCENARIO_6 = "missing_mesh_policy.yaml" SCENARIO_7 = "mtls_settings_overridden.yaml" SCENARIO_8 = "mesh_policy_permissive.yaml" SCENARIO_9 = "mesh_policy_mtls_enable.yaml" SCENARIO_10 = "non_existing_gateway.yaml" SCENARIO_11 = "not_defined_protocol.yaml" SCENARIO_12 = "destination_rule_fqdn.yaml" SCENARIO_13 = "destination_rule_wrong_fqdn.yaml" SCENARIO_14 = "ratings_java_svc.yaml" SCENARIO_15 = "port_name_suffix_missing.yaml" SCENARIO_16 = "virtual-service-less-than-100-weight.yaml" SCENARIO_17 = "wrong-host-label-sidecar.yaml" SCENARIO_18 = "duplicate-no-workload-sidecar.yaml" SCENARIO_19 = "duplicate-workload-sidecar.yaml" SCENARIO_20 = "default-sidecar-with-workload.yaml" SCENARIO_21 = "mesh_policy_disable.yaml" SCENARIO_22 = "auth-policy-mtls.yaml" SCENARIO_23 = "vs_subset_service_entry.yaml" SCENARIO_24 = "vs_wrong_subset_no_dr.yaml" SCENARIO_25 = "duplicate-vs-gateway.yaml" SCENARIO_26 = "vs_destination_host_not_found.yaml" SCENARIO_27 = "request_auth_no_workload.yaml" SCENARIO_28 = "two_gateways_different_selectors.yaml" SCENARIO_29 = "subset_not_have_label.yaml" @pytest.mark.p_group_last def test_two_gateways_same_host(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_1, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='Gateway', object_name='bookinfo-gateway-auto-host', namespace=BOOKINFO, error_messages=[KIA0301]), ConfigValidationObject( object_type='Gateway', object_name='bookinfo-gateway-auto-host-copy', namespace=BOOKINFO2, error_messages=[KIA0301]) ], ignore_common_errors=False) @pytest.mark.p_group_last def test_two_gateways_different_selectors(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_28, namespace=ISTIO_SYSTEM, config_validation_objects=[ ConfigValidationObject( object_type='Gateway', object_name='istio-gateway-prv', namespace=ISTIO_SYSTEM, error_messages=[KIA0302]), ConfigValidationObject( object_type='Gateway', object_name='istio-gateway-pub', namespace=ISTIO_SYSTEM, error_messages=[KIA0302]) ], ignore_common_errors=False) @pytest.mark.p_group_last def test_gateway_no_matching_workload(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_2, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='Gateway', object_name='bookinfo-gateway-auto-not-match', namespace=BOOKINFO, error_messages=[KIA0302]) ]) @pytest.mark.p_group_last def test_more_drs_same_host_port(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_3, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-dr1-auto', namespace=BOOKINFO, error_messages=[KIA0201]), ConfigValidationObject( object_type='DestinationRule', object_name='reviews-dr2-auto', namespace=BOOKINFO, error_messages=[KIA0201]) ], ignore_common_errors=False) @pytest.mark.p_group_last def test_no_matching_entry_dr(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_4, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-no-match-entry-auto', namespace=BOOKINFO, error_messages=[KIA0202]) ]) @pytest.mark.p_group_last def test_subset_label_not_found(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_5, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-no-subset-label-auto', namespace=BOOKINFO, error_messages=[KIA0203, KIA0203]) ]) @pytest.mark.p_group_last def test_mesh_policy_not_found(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_6, namespace=ISTIO_SYSTEM, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='default', namespace=ISTIO_SYSTEM, error_messages=[KIA0205]) ]) @pytest.mark.p_group_last def test_mtls_settings_overridden(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_7, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='default', namespace=ISTIO_SYSTEM, error_messages=[KIA0205]), ConfigValidationObject( object_type='DestinationRule', object_name='reviews-overridden-auto', namespace=BOOKINFO, error_messages=[KIA0204]) ]) @pytest.mark.p_group_last def test_meshpolicy_permissive_ok(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_8, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='default', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='PeerAuthentication', object_name='default', namespace=ISTIO_SYSTEM, error_messages=[]) ]) @pytest.mark.p_group_last def test_meshpolicy_mtls_enable_ok(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_9, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='default', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='PeerAuthentication', object_name='default', namespace=ISTIO_SYSTEM, error_messages=[KIA0401]) ]) @pytest.mark.p_group_last def test_vs_to_non_existing_gateway(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_10, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='details-vs-non-existing-gateway-auto', namespace=BOOKINFO, error_messages=[KIA1102]) ]) @pytest.mark.p_group_last def test_vs_not_defined_protocol(kiali_client, openshift_client): try: tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_11, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='details-not-defined-protocol', namespace=BOOKINFO, error_messages=[KIA1103]) ]) except NoSuchElementException: pass @pytest.mark.p_group_last def test_dr_fqdn_ok(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_12, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-dr-fqdn-auto', namespace=BOOKINFO, error_messages=[]) ]) @pytest.mark.p_group_last def test_dr_fqdn_not_exist(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_13, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-dr-wrong-fqdn-auto', namespace=BOOKINFO, error_messages=[KIA0202]) ]) @pytest.mark.p_group_last def __test_deployment_port_not_found(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_service_validation( scenario=SCENARIO_14, service_name='ratings-java', namespace='bookinfo', service_validation_objects=[ ServiceValidationObject( error_message=KIA0701)]) @pytest.mark.p_group_last def __test_port_name_suffix(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_service_validation( scenario=SCENARIO_15, service_name='ratings-java-svc-suffix', namespace='bookinfo', service_validation_objects=[ ServiceValidationObject( error_message=KIA0601)]) @pytest.mark.p_group_last def test_vs_less_than_100_weight(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_16, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='virtual-service-less-100-weight-auto', namespace=BOOKINFO, error_messages=[KIA1104]) ]) @pytest.mark.p_group_last def test_sidecar_errors(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_17, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='Sidecar', object_name='wrong-host-sidecar-auto', namespace=BOOKINFO, error_messages=[KIA0004, KIA1004, KIA1004, KIA1004, KIA1004]) ]) @pytest.mark.p_group_last def test_duplicate_sidecar_errors(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_18, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='Sidecar', object_name='dupliacate-sidecar1-auto', namespace=BOOKINFO, error_messages=[KIA0002, KIA1004, KIA1004]), ConfigValidationObject( object_type='Sidecar', object_name='dupliacate-sidecar2-auto', namespace=BOOKINFO, error_messages=[KIA0002, KIA1004, KIA1004]) ]) @pytest.mark.p_group_last def test_duplicate_workload_sidecar_errors(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_19, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='Sidecar', object_name='dupliacate-workload-sidecar1-auto', namespace=BOOKINFO, error_messages=[KIA1004, KIA1004, KIA0003]), ConfigValidationObject( object_type='Sidecar', object_name='dupliacate-workload-sidecar2-auto', namespace=BOOKINFO, error_messages=[KIA1004, KIA1004, KIA0003]) ]) @pytest.mark.p_group_last def test_default_workload_sidecar(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_20, namespace=ISTIO_SYSTEM, config_validation_objects=[ ConfigValidationObject( object_type='Sidecar', object_name='default-sidecar-workload-auto', namespace=ISTIO_SYSTEM, error_messages=[KIA1006, KIA0004]) ]) @pytest.mark.p_group_last def test_meshpolicy_disabled_ok(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_21, namespace=None, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='disable-mtls', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='PeerAuthentication', object_name='default', namespace=BOOKINFO, error_messages=[]) ]) @pytest.mark.p_group_last def test_authpolicy_validations_mtls(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_22, namespace=BOOKINFO2, config_validation_objects=[ ConfigValidationObject( object_type='AuthorizationPolicy', object_name='authpolicymtls', namespace=BOOKINFO2, error_messages=([KIA0105, KIA0105, KIA0105, KIA0105, KIA0105, KIA0105, KIA0105] if not openshift_client.is_auto_mtls() else [])) ]) @pytest.mark.p_group_last def test_vs_subset_validations_service_entry(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_23, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='orahub-vs', namespace=BOOKINFO, error_messages=[KIA1104, KIA1104]) ]) @pytest.mark.p_group_last def test_vs_subset_validations_no_service_entry(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_24, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='orahub-vs-no-dr', namespace=BOOKINFO, error_messages=[KIA1104, KIA1104, KIA1107, KIA1107]) ]) @pytest.mark.p_group_last def test_vs_duplicate_gateway(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_25, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='admin-vs-2', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='VirtualService', object_name='admin-vs', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='VirtualService', object_name='user-vs-2', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='VirtualService', object_name='user-vs', namespace=BOOKINFO, error_messages=[]) ]) @pytest.mark.p_group_last def test_vs_destination_host_not_found(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_26, namespace=ISTIO_SYSTEM, config_validation_objects=[ ConfigValidationObject( object_type='VirtualService', object_name='foo-dev', namespace=ISTIO_SYSTEM, error_messages=[KIA1101]) ]) @pytest.mark.p_group_last def test_request_auth_workload_not_found(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_27, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-dup-1', namespace=BOOKINFO, error_messages=[KIA0003]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-dup-2', namespace=BOOKINFO, error_messages=[KIA0003]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-matching', namespace=BOOKINFO, error_messages=[]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-no-matching', namespace=BOOKINFO, error_messages=[KIA0004]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-ns-wise', namespace=BOOKINFO, error_messages=[KIA0002]), ConfigValidationObject( object_type='RequestAuthentication', object_name='httpbin-ns-wise-1', namespace=BOOKINFO, error_messages=[KIA0002]) ]) @pytest.mark.p_group_last def test_subset_no_label(kiali_client, openshift_client): tests = ValidationsTest( kiali_client=kiali_client, openshift_client=openshift_client, objects_path=istio_objects_validation_path.strpath) tests.test_istio_objects( scenario=SCENARIO_29, namespace=BOOKINFO, config_validation_objects=[ ConfigValidationObject( object_type='DestinationRule', object_name='reviews-subset-not-label-auto', namespace=BOOKINFO, error_messages=[KIA0209]) ])

true

1c2fc8f9475fca07fd19d084ffbe32021b3ce474

7,459

py

Python

probatus/utils/shap_helpers.py

PaulZhutovsky/probatus

d8f85dc0eac65a7fec64b76f265693c845afcbe2

[ "MIT" ]

null

probatus/utils/shap_helpers.py

PaulZhutovsky/probatus

d8f85dc0eac65a7fec64b76f265693c845afcbe2

[ "MIT" ]

null

probatus/utils/shap_helpers.py

PaulZhutovsky/probatus

d8f85dc0eac65a7fec64b76f265693c845afcbe2

[ "MIT" ]

null

# Copyright (c) 2020 ING Bank N.V. # # Permission is hereby granted, free of charge, to any person obtaining a copy of # this software and associated documentation files (the "Software"), to deal in # the Software without restriction, including without limitation the rights to # use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of # the Software, and to permit persons to whom the Software is furnished to do so, # subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS # FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR # COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER # IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN # CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. import warnings import numpy as np import pandas as pd from shap import Explainer from shap.explainers._tree import Tree from shap.utils import sample from sklearn.pipeline import Pipeline def shap_calc( model, X, return_explainer=False, verbose=0, sample_size=100, approximate=False, check_additivity=True, **shap_kwargs, ): """ Helper function to calculate the shapley values for a given model. Args: model (binary model): Trained model. X (pd.DataFrame or np.ndarray): features set. return_explainer (boolean): if True, returns a a tuple (shap_values, explainer). verbose (int, optional): Controls verbosity of the output: - 0 - nether prints nor warnings are shown - 1 - 50 - only most important warnings - 51 - 100 - shows other warnings and prints - above 100 - presents all prints and all warnings (including SHAP warnings). approximate (boolean): if True uses shap approximations - less accurate, but very fast. It applies to tree-based explainers only. check_additivity (boolean): if False SHAP will disable the additivity check for tree-based models. **shap_kwargs: kwargs of the shap.Explainer Returns: (np.ndarray or tuple(np.ndarray, shap.Explainer)): shapley_values for the model, optionally also returns the explainer. """ if isinstance(model, Pipeline): raise ( TypeError( "The provided model is a Pipeline. Unfortunately, the features based on SHAP do not support " "pipelines, because they cannot be used in combination with shap.Explainer. Please apply any " "data transformations before running the probatus module." ) ) # Suppress warnings regarding XGboost and Lightgbm models. with warnings.catch_warnings(): if verbose <= 100: warnings.simplefilter("ignore") # For tree explainers, do not pass masker when feature_perturbation is # tree_path_dependent, or when X contains categorical features # related to issue: # https://github.com/slundberg/shap/issues/480 if shap_kwargs.get("feature_perturbation") == "tree_path_dependent" or X.select_dtypes("category").shape[1] > 0: # Calculate Shap values. explainer = Explainer(model, **shap_kwargs) else: # Create the background data,required for non tree based models. # A single datapoint can passed as mask # (https://github.com/slundberg/shap/issues/955#issuecomment-569837201) if X.shape[0] < sample_size: sample_size = int(np.ceil(X.shape[0] * 0.2)) else: pass mask = sample(X, sample_size) explainer = Explainer(model, masker=mask, **shap_kwargs) # For tree-explainers allow for using check_additivity and approximate arguments if isinstance(explainer, Tree): # Calculate Shap values shap_values = explainer.shap_values(X, check_additivity=check_additivity, approximate=approximate) else: # Calculate Shap values shap_values = explainer.shap_values(X) if isinstance(shap_values, list) and len(shap_values) == 2: warnings.warn( "Shap values are related to the output probabilities of class 1 for this model, instead of " "log odds." ) shap_values = shap_values[1] if return_explainer: return shap_values, explainer return shap_values def shap_to_df(model, X, precalc_shap=None, **kwargs): """ Calculates the shap values and return the pandas DataFrame with the columns and the index of the original. Args: model (binary model): Pretrained model (Random Forest of XGBoost at the moment). X (pd.DataFrame or np.ndarray): Dataset on which the SHAP importance is calculated. precalc_shap (np.array): Precalculated SHAP values. If None, they are computed. **kwargs: for the function shap_calc Returns: (pd.DataFrame): Dataframe with SHAP feature importance per features on X dataset. """ if precalc_shap is not None: shap_values = precalc_shap else: shap_values = shap_calc(model, X, **kwargs) if isinstance(X, pd.DataFrame): return pd.DataFrame(shap_values, columns=X.columns, index=X.index) elif isinstance(X, np.ndarray) and len(X.shape) == 2: return pd.DataFrame(shap_values, columns=[f"col_{ix}" for ix in range(X.shape[1])]) else: raise NotImplementedError("X must be a dataframe or a 2d array") def calculate_shap_importance(shap_values, columns, output_columns_suffix=""): """ Returns the average shapley value for each column of the dataframe, as well as the average absolute shap value. Args: shap_values (np.array): Shap values. columns (list of str): Feature names. output_columns_suffix (str, optional): Suffix to be added at the end of column names in the output. Returns: (pd.DataFrame): Mean absolute shap values and Mean shap values of features. """ # Find average shap importance for neg and pos class shap_abs_mean = np.mean(np.abs(shap_values), axis=0) shap_mean = np.mean(shap_values, axis=0) # Prepare importance values in a handy df importance_df = pd.DataFrame( { f"mean_abs_shap_value{output_columns_suffix}": shap_abs_mean.tolist(), f"mean_shap_value{output_columns_suffix}": shap_mean.tolist(), }, index=columns, ) # Set the correct column types importance_df[f"mean_abs_shap_value{output_columns_suffix}"] = importance_df[ f"mean_abs_shap_value{output_columns_suffix}" ].astype(float) importance_df[f"mean_shap_value{output_columns_suffix}"] = importance_df[ f"mean_shap_value{output_columns_suffix}" ].astype(float) importance_df = importance_df.sort_values(f"mean_abs_shap_value{output_columns_suffix}", ascending=False) return importance_df

36.925743

120

0.667114

import warnings import numpy as np import pandas as pd from shap import Explainer from shap.explainers._tree import Tree from shap.utils import sample from sklearn.pipeline import Pipeline def shap_calc( model, X, return_explainer=False, verbose=0, sample_size=100, approximate=False, check_additivity=True, **shap_kwargs, ): if isinstance(model, Pipeline): raise ( TypeError( "The provided model is a Pipeline. Unfortunately, the features based on SHAP do not support " "pipelines, because they cannot be used in combination with shap.Explainer. Please apply any " "data transformations before running the probatus module." ) ) with warnings.catch_warnings(): if verbose <= 100: warnings.simplefilter("ignore") if shap_kwargs.get("feature_perturbation") == "tree_path_dependent" or X.select_dtypes("category").shape[1] > 0: explainer = Explainer(model, **shap_kwargs) else: 0] < sample_size: sample_size = int(np.ceil(X.shape[0] * 0.2)) else: pass mask = sample(X, sample_size) explainer = Explainer(model, masker=mask, **shap_kwargs) if isinstance(explainer, Tree): shap_values = explainer.shap_values(X, check_additivity=check_additivity, approximate=approximate) else: shap_values = explainer.shap_values(X) if isinstance(shap_values, list) and len(shap_values) == 2: warnings.warn( "Shap values are related to the output probabilities of class 1 for this model, instead of " "log odds." ) shap_values = shap_values[1] if return_explainer: return shap_values, explainer return shap_values def shap_to_df(model, X, precalc_shap=None, **kwargs): if precalc_shap is not None: shap_values = precalc_shap else: shap_values = shap_calc(model, X, **kwargs) if isinstance(X, pd.DataFrame): return pd.DataFrame(shap_values, columns=X.columns, index=X.index) elif isinstance(X, np.ndarray) and len(X.shape) == 2: return pd.DataFrame(shap_values, columns=[f"col_{ix}" for ix in range(X.shape[1])]) else: raise NotImplementedError("X must be a dataframe or a 2d array") def calculate_shap_importance(shap_values, columns, output_columns_suffix=""): shap_abs_mean = np.mean(np.abs(shap_values), axis=0) shap_mean = np.mean(shap_values, axis=0) importance_df = pd.DataFrame( { f"mean_abs_shap_value{output_columns_suffix}": shap_abs_mean.tolist(), f"mean_shap_value{output_columns_suffix}": shap_mean.tolist(), }, index=columns, ) importance_df[f"mean_abs_shap_value{output_columns_suffix}"] = importance_df[ f"mean_abs_shap_value{output_columns_suffix}" ].astype(float) importance_df[f"mean_shap_value{output_columns_suffix}"] = importance_df[ f"mean_shap_value{output_columns_suffix}" ].astype(float) importance_df = importance_df.sort_values(f"mean_abs_shap_value{output_columns_suffix}", ascending=False) return importance_df

true

1c2fc8fb4a8080d320c1086f19b7f02983c690e3

12,910

py

Python

panel/io/server.py

nritsche/panel

15aa31b1c78988d107b3ace765d3c0fec36188c8

[ "BSD-3-Clause" ]

null

panel/io/server.py

nritsche/panel

15aa31b1c78988d107b3ace765d3c0fec36188c8

[ "BSD-3-Clause" ]

null

panel/io/server.py

nritsche/panel

15aa31b1c78988d107b3ace765d3c0fec36188c8

[ "BSD-3-Clause" ]

null

""" Utilities for creating bokeh Server instances. """ from __future__ import absolute_import, division, unicode_literals import os import signal import sys import threading import uuid from contextlib import contextmanager from functools import partial from types import FunctionType from bokeh.document.events import ModelChangedEvent from bokeh.server.server import Server from tornado.websocket import WebSocketHandler from tornado.web import RequestHandler, StaticFileHandler from tornado.wsgi import WSGIContainer from .state import state #--------------------------------------------------------------------- # Private API #--------------------------------------------------------------------- INDEX_HTML = os.path.join(os.path.dirname(__file__), '..', '_templates', "index.html") def _origin_url(url): if url.startswith("http"): url = url.split("//")[1] return url def _server_url(url, port): if url.startswith("http"): return '%s:%d%s' % (url.rsplit(':', 1)[0], port, "/") else: return 'http://%s:%d%s' % (url.split(':')[0], port, "/") @contextmanager def set_curdoc(doc): state.curdoc = doc yield state.curdoc = None def _eval_panel(panel, server_id, title, location, doc): from ..template import BaseTemplate from ..pane import panel as as_panel with set_curdoc(doc): if isinstance(panel, FunctionType): panel = panel() if isinstance(panel, BaseTemplate): doc = panel._modify_doc(server_id, title, doc, location) else: doc = as_panel(panel)._modify_doc(server_id, title, doc, location) return doc #--------------------------------------------------------------------- # Public API #--------------------------------------------------------------------- @contextmanager def unlocked(): """ Context manager which unlocks a Document and dispatches ModelChangedEvents triggered in the context body to all sockets on current sessions. """ curdoc = state.curdoc if curdoc is None or curdoc.session_context is None: yield return connections = curdoc.session_context.session._subscribed_connections hold = curdoc._hold if hold: old_events = list(curdoc._held_events) else: old_events = [] curdoc.hold() try: yield events = [] for conn in connections: socket = conn._socket if hasattr(socket, 'write_lock') and socket.write_lock._block._value == 0: state._locks.add(socket) locked = socket in state._locks for event in curdoc._held_events: if (isinstance(event, ModelChangedEvent) and event not in old_events and hasattr(socket, 'write_message') and not locked): msg = conn.protocol.create('PATCH-DOC', [event]) WebSocketHandler.write_message(socket, msg.header_json) WebSocketHandler.write_message(socket, msg.metadata_json) WebSocketHandler.write_message(socket, msg.content_json) for header, payload in msg._buffers: WebSocketHandler.write_message(socket, header) WebSocketHandler.write_message(socket, payload, binary=True) elif event not in events: events.append(event) curdoc._held_events = events finally: if not hold: curdoc.unhold() def serve(panels, port=0, address=None, websocket_origin=None, loop=None, show=True, start=True, title=None, verbose=True, location=True, **kwargs): """ Allows serving one or more panel objects on a single server. The panels argument should be either a Panel object or a function returning a Panel object or a dictionary of these two. If a dictionary is supplied the keys represent the slugs at which each app is served, e.g. `serve({'app': panel1, 'app2': panel2})` will serve apps at /app and /app2 on the server. Arguments --------- panel: Viewable, function or {str: Viewable or function} A Panel object, a function returning a Panel object or a dictionary mapping from the URL slug to either. port: int (optional, default=0) Allows specifying a specific port address : str The address the server should listen on for HTTP requests. websocket_origin: str or list(str) (optional) A list of hosts that can connect to the websocket. This is typically required when embedding a server app in an external web site. If None, "localhost" is used. loop : tornado.ioloop.IOLoop (optional, default=IOLoop.current()) The tornado IOLoop to run the Server on show : boolean (optional, default=False) Whether to open the server in a new browser tab on start start : boolean(optional, default=False) Whether to start the Server title: str or {str: str} (optional, default=None) An HTML title for the application or a dictionary mapping from the URL slug to a customized title verbose: boolean (optional, default=True) Whether to print the address and port location : boolean or panel.io.location.Location Whether to create a Location component to observe and set the URL location. kwargs: dict Additional keyword arguments to pass to Server instance """ return get_server(panels, port, address, websocket_origin, loop, show, start, title, verbose, location, **kwargs) class ProxyFallbackHandler(RequestHandler): """A `RequestHandler` that wraps another HTTP server callback and proxies the subpath. """ def initialize(self, fallback, proxy=None): self.fallback = fallback self.proxy = proxy def prepare(self): if self.proxy: self.request.path = self.request.path.replace(self.proxy, '') self.fallback(self.request) self._finished = True self.on_finish() def get_static_routes(static_dirs): """ Returns a list of tornado routes of StaticFileHandlers given a dictionary of slugs and file paths to serve. """ patterns = [] for slug, path in static_dirs.items(): if not slug.startswith('/'): slug = '/' + slug if slug == '/static': raise ValueError("Static file route may not use /static " "this is reserved for internal use.") path = os.path.abspath(path) if not os.path.isdir(path): raise ValueError("Cannot serve non-existent path %s" % path) patterns.append( (r"%s/(.*)" % slug, StaticFileHandler, {"path": path}) ) return patterns def get_server(panel, port=0, address=None, websocket_origin=None, loop=None, show=False, start=False, title=None, verbose=False, location=True, static_dirs={}, **kwargs): """ Returns a Server instance with this panel attached as the root app. Arguments --------- panel: Viewable, function or {str: Viewable} A Panel object, a function returning a Panel object or a dictionary mapping from the URL slug to either. port: int (optional, default=0) Allows specifying a specific port address : str The address the server should listen on for HTTP requests. websocket_origin: str or list(str) (optional) A list of hosts that can connect to the websocket. This is typically required when embedding a server app in an external web site. If None, "localhost" is used. loop : tornado.ioloop.IOLoop (optional, default=IOLoop.current()) The tornado IOLoop to run the Server on. show : boolean (optional, default=False) Whether to open the server in a new browser tab on start. start : boolean(optional, default=False) Whether to start the Server. title : str or {str: str} (optional, default=None) An HTML title for the application or a dictionary mapping from the URL slug to a customized title. verbose: boolean (optional, default=False) Whether to report the address and port. location : boolean or panel.io.location.Location Whether to create a Location component to observe and set the URL location. static_dirs: dict (optional, default={}) A dictionary of routes and local paths to serve as static file directories on those routes. kwargs: dict Additional keyword arguments to pass to Server instance. Returns ------- server : bokeh.server.server.Server Bokeh Server instance running this panel """ from tornado.ioloop import IOLoop server_id = kwargs.pop('server_id', uuid.uuid4().hex) kwargs['extra_patterns'] = extra_patterns = kwargs.get('extra_patterns', []) if isinstance(panel, dict): apps = {} for slug, app in panel.items(): if isinstance(title, dict): try: title_ = title[slug] except KeyError: raise KeyError( "Keys of the title dictionnary and of the apps " f"dictionary must match. No {slug} key found in the " "title dictionnary.") else: title_ = title slug = slug if slug.startswith('/') else '/'+slug if 'flask' in sys.modules: from flask import Flask if isinstance(app, Flask): wsgi = WSGIContainer(app) if slug == '/': raise ValueError('Flask apps must be served on a subpath.') if not slug.endswith('/'): slug += '/' extra_patterns.append(('^'+slug+'.*', ProxyFallbackHandler, dict(fallback=wsgi, proxy=slug))) continue apps[slug] = partial(_eval_panel, app, server_id, title_, location) else: apps = {'/': partial(_eval_panel, panel, server_id, title, location)} extra_patterns += get_static_routes(static_dirs) opts = dict(kwargs) if loop: loop.make_current() opts['io_loop'] = loop elif opts.get('num_procs', 1) == 1: opts['io_loop'] = IOLoop.current() if 'index' not in opts: opts['index'] = INDEX_HTML if address is not None: opts['address'] = address if websocket_origin: if not isinstance(websocket_origin, list): websocket_origin = [websocket_origin] opts['allow_websocket_origin'] = websocket_origin server = Server(apps, port=port, **opts) if verbose: address = server.address or 'localhost' print("Launching server at http://%s:%s" % (address, server.port)) state._servers[server_id] = (server, panel, []) if show: def show_callback(): server.show('/') server.io_loop.add_callback(show_callback) def sig_exit(*args, **kwargs): server.io_loop.add_callback_from_signal(do_stop) def do_stop(*args, **kwargs): server.io_loop.stop() try: signal.signal(signal.SIGINT, sig_exit) except ValueError: pass # Can't use signal on a thread if start: server.start() try: server.io_loop.start() except RuntimeError: pass return server class StoppableThread(threading.Thread): """Thread class with a stop() method.""" def __init__(self, io_loop=None, timeout=1000, **kwargs): from tornado import ioloop super(StoppableThread, self).__init__(**kwargs) self._stop_event = threading.Event() self.io_loop = io_loop self._cb = ioloop.PeriodicCallback(self._check_stopped, timeout) self._cb.start() def _check_stopped(self): if self.stopped: self._cb.stop() self.io_loop.stop() def run(self): if hasattr(self, '_target'): target, args, kwargs = self._target, self._args, self._kwargs else: target, args, kwargs = self._Thread__target, self._Thread__args, self._Thread__kwargs if not target: return bokeh_server = None try: bokeh_server = target(*args, **kwargs) finally: if isinstance(bokeh_server, Server): bokeh_server.stop() if hasattr(self, '_target'): del self._target, self._args, self._kwargs else: del self._Thread__target, self._Thread__args, self._Thread__kwargs def stop(self): self._stop_event.set() @property def stopped(self): return self._stop_event.is_set()

34.518717

97

0.609992

from __future__ import absolute_import, division, unicode_literals import os import signal import sys import threading import uuid from contextlib import contextmanager from functools import partial from types import FunctionType from bokeh.document.events import ModelChangedEvent from bokeh.server.server import Server from tornado.websocket import WebSocketHandler from tornado.web import RequestHandler, StaticFileHandler from tornado.wsgi import WSGIContainer from .state import state INDEX_HTML = os.path.join(os.path.dirname(__file__), '..', '_templates', "index.html") def _origin_url(url): if url.startswith("http"): url = url.split("//")[1] return url def _server_url(url, port): if url.startswith("http"): return '%s:%d%s' % (url.rsplit(':', 1)[0], port, "/") else: return 'http://%s:%d%s' % (url.split(':')[0], port, "/") @contextmanager def set_curdoc(doc): state.curdoc = doc yield state.curdoc = None def _eval_panel(panel, server_id, title, location, doc): from ..template import BaseTemplate from ..pane import panel as as_panel with set_curdoc(doc): if isinstance(panel, FunctionType): panel = panel() if isinstance(panel, BaseTemplate): doc = panel._modify_doc(server_id, title, doc, location) else: doc = as_panel(panel)._modify_doc(server_id, title, doc, location) return doc @contextmanager def unlocked(): curdoc = state.curdoc if curdoc is None or curdoc.session_context is None: yield return connections = curdoc.session_context.session._subscribed_connections hold = curdoc._hold if hold: old_events = list(curdoc._held_events) else: old_events = [] curdoc.hold() try: yield events = [] for conn in connections: socket = conn._socket if hasattr(socket, 'write_lock') and socket.write_lock._block._value == 0: state._locks.add(socket) locked = socket in state._locks for event in curdoc._held_events: if (isinstance(event, ModelChangedEvent) and event not in old_events and hasattr(socket, 'write_message') and not locked): msg = conn.protocol.create('PATCH-DOC', [event]) WebSocketHandler.write_message(socket, msg.header_json) WebSocketHandler.write_message(socket, msg.metadata_json) WebSocketHandler.write_message(socket, msg.content_json) for header, payload in msg._buffers: WebSocketHandler.write_message(socket, header) WebSocketHandler.write_message(socket, payload, binary=True) elif event not in events: events.append(event) curdoc._held_events = events finally: if not hold: curdoc.unhold() def serve(panels, port=0, address=None, websocket_origin=None, loop=None, show=True, start=True, title=None, verbose=True, location=True, **kwargs): return get_server(panels, port, address, websocket_origin, loop, show, start, title, verbose, location, **kwargs) class ProxyFallbackHandler(RequestHandler): def initialize(self, fallback, proxy=None): self.fallback = fallback self.proxy = proxy def prepare(self): if self.proxy: self.request.path = self.request.path.replace(self.proxy, '') self.fallback(self.request) self._finished = True self.on_finish() def get_static_routes(static_dirs): patterns = [] for slug, path in static_dirs.items(): if not slug.startswith('/'): slug = '/' + slug if slug == '/static': raise ValueError("Static file route may not use /static " "this is reserved for internal use.") path = os.path.abspath(path) if not os.path.isdir(path): raise ValueError("Cannot serve non-existent path %s" % path) patterns.append( (r"%s/(.*)" % slug, StaticFileHandler, {"path": path}) ) return patterns def get_server(panel, port=0, address=None, websocket_origin=None, loop=None, show=False, start=False, title=None, verbose=False, location=True, static_dirs={}, **kwargs): from tornado.ioloop import IOLoop server_id = kwargs.pop('server_id', uuid.uuid4().hex) kwargs['extra_patterns'] = extra_patterns = kwargs.get('extra_patterns', []) if isinstance(panel, dict): apps = {} for slug, app in panel.items(): if isinstance(title, dict): try: title_ = title[slug] except KeyError: raise KeyError( "Keys of the title dictionnary and of the apps " f"dictionary must match. No {slug} key found in the " "title dictionnary.") else: title_ = title slug = slug if slug.startswith('/') else '/'+slug if 'flask' in sys.modules: from flask import Flask if isinstance(app, Flask): wsgi = WSGIContainer(app) if slug == '/': raise ValueError('Flask apps must be served on a subpath.') if not slug.endswith('/'): slug += '/' extra_patterns.append(('^'+slug+'.*', ProxyFallbackHandler, dict(fallback=wsgi, proxy=slug))) continue apps[slug] = partial(_eval_panel, app, server_id, title_, location) else: apps = {'/': partial(_eval_panel, panel, server_id, title, location)} extra_patterns += get_static_routes(static_dirs) opts = dict(kwargs) if loop: loop.make_current() opts['io_loop'] = loop elif opts.get('num_procs', 1) == 1: opts['io_loop'] = IOLoop.current() if 'index' not in opts: opts['index'] = INDEX_HTML if address is not None: opts['address'] = address if websocket_origin: if not isinstance(websocket_origin, list): websocket_origin = [websocket_origin] opts['allow_websocket_origin'] = websocket_origin server = Server(apps, port=port, **opts) if verbose: address = server.address or 'localhost' print("Launching server at http://%s:%s" % (address, server.port)) state._servers[server_id] = (server, panel, []) if show: def show_callback(): server.show('/') server.io_loop.add_callback(show_callback) def sig_exit(*args, **kwargs): server.io_loop.add_callback_from_signal(do_stop) def do_stop(*args, **kwargs): server.io_loop.stop() try: signal.signal(signal.SIGINT, sig_exit) except ValueError: pass if start: server.start() try: server.io_loop.start() except RuntimeError: pass return server class StoppableThread(threading.Thread): def __init__(self, io_loop=None, timeout=1000, **kwargs): from tornado import ioloop super(StoppableThread, self).__init__(**kwargs) self._stop_event = threading.Event() self.io_loop = io_loop self._cb = ioloop.PeriodicCallback(self._check_stopped, timeout) self._cb.start() def _check_stopped(self): if self.stopped: self._cb.stop() self.io_loop.stop() def run(self): if hasattr(self, '_target'): target, args, kwargs = self._target, self._args, self._kwargs else: target, args, kwargs = self._Thread__target, self._Thread__args, self._Thread__kwargs if not target: return bokeh_server = None try: bokeh_server = target(*args, **kwargs) finally: if isinstance(bokeh_server, Server): bokeh_server.stop() if hasattr(self, '_target'): del self._target, self._args, self._kwargs else: del self._Thread__target, self._Thread__args, self._Thread__kwargs def stop(self): self._stop_event.set() @property def stopped(self): return self._stop_event.is_set()

true

1c2fc92aa9611edafd68b1d93acc7f621dcebf02

3,955

py

Python

mpa/cls/exporter.py

openvinotoolkit/model_preparation_algorithm

8d36bf5944837b7a3d22fc2c3a4cb93423619fc2

[ "Apache-2.0" ]

null

mpa/cls/exporter.py

openvinotoolkit/model_preparation_algorithm

8d36bf5944837b7a3d22fc2c3a4cb93423619fc2

[ "Apache-2.0" ]

null

mpa/cls/exporter.py

openvinotoolkit/model_preparation_algorithm

8d36bf5944837b7a3d22fc2c3a4cb93423619fc2

[ "Apache-2.0" ]

null

# Copyright (C) 2022 Intel Corporation # SPDX-License-Identifier: Apache-2.0 # import os import torch.onnx from functools import partial from mmcv.runner import load_checkpoint, wrap_fp16_model from mmcls.models import build_classifier from mpa.registry import STAGES from .stage import ClsStage from mpa.utils import mo_wrapper from mpa.utils.logger import get_logger import numpy as np import torch from mmcls.datasets.pipelines import Compose logger = get_logger() @STAGES.register_module() class ClsExporter(ClsStage): def __init__(self, **kwargs): super().__init__(**kwargs) def get_fake_input(self, cfg, orig_img_shape=(128, 128, 3)): pipeline = cfg.data.test.pipeline pipeline = Compose(pipeline) data = dict(img=np.zeros(orig_img_shape, dtype=np.uint8)) data = pipeline(data) return data def get_norm_values(self, cfg): pipeline = cfg.data.test.pipeline mean_values = [0, 0, 0] scale_values = [1, 1, 1] for pipeline_step in pipeline: if pipeline_step.type == 'Normalize': mean_values = pipeline_step.mean scale_values = pipeline_step.std break return mean_values, scale_values def run(self, model_cfg, model_ckpt, data_cfg, **kwargs): """Run exporter stage """ self._init_logger() mode = kwargs.get('mode', 'train') if mode not in self.mode: logger.warning(f'mode for this stage {mode}') return {} cfg = self.configure(model_cfg, model_ckpt, data_cfg, training=False, **kwargs) output_path = os.path.join(cfg.work_dir, 'export') onnx_path = output_path+'/model.onnx' os.makedirs(output_path, exist_ok=True) # build the model and load checkpoint model = build_classifier(cfg.model) fp16_cfg = cfg.get('fp16', None) if fp16_cfg is not None: wrap_fp16_model(model) logger.info('load checkpoint from ' + cfg.load_from) _ = load_checkpoint(model, cfg.load_from, map_location='cpu') if hasattr(model, 'is_export'): model.is_export = True model.eval() model.forward = partial(model.forward, img_metas={}, return_loss=False) data = self.get_fake_input(cfg) fake_img = data['img'].unsqueeze(0) try: torch.onnx.export(model, fake_img, onnx_path, verbose=False, export_params=True, input_names=['data'], output_names=['logits', 'features', 'vector'], dynamic_axes={}, opset_version=11, operator_export_type=torch.onnx.OperatorExportTypes.ONNX ) mean_values, scale_values = self.get_norm_values(cfg) mo_args = { 'input_model': onnx_path, 'mean_values': mean_values, 'scale_values': scale_values, 'data_type': 'FP32', 'model_name': 'model', 'reverse_input_channels': None, } ret, msg = mo_wrapper.generate_ir(output_path, output_path, silent=True, **mo_args) os.remove(onnx_path) except Exception as ex: return {'outputs': None, 'msg': f'exception {type(ex)}'} bin_file = [f for f in os.listdir(output_path) if f.endswith('.bin')][0] xml_file = [f for f in os.listdir(output_path) if f.endswith('.xml')][0] logger.info('Exporting completed') return { 'outputs': { 'bin': os.path.join(output_path, bin_file), 'xml': os.path.join(output_path, xml_file) }, 'msg': '' }

34.391304

95

0.570923

import os import torch.onnx from functools import partial from mmcv.runner import load_checkpoint, wrap_fp16_model from mmcls.models import build_classifier from mpa.registry import STAGES from .stage import ClsStage from mpa.utils import mo_wrapper from mpa.utils.logger import get_logger import numpy as np import torch from mmcls.datasets.pipelines import Compose logger = get_logger() @STAGES.register_module() class ClsExporter(ClsStage): def __init__(self, **kwargs): super().__init__(**kwargs) def get_fake_input(self, cfg, orig_img_shape=(128, 128, 3)): pipeline = cfg.data.test.pipeline pipeline = Compose(pipeline) data = dict(img=np.zeros(orig_img_shape, dtype=np.uint8)) data = pipeline(data) return data def get_norm_values(self, cfg): pipeline = cfg.data.test.pipeline mean_values = [0, 0, 0] scale_values = [1, 1, 1] for pipeline_step in pipeline: if pipeline_step.type == 'Normalize': mean_values = pipeline_step.mean scale_values = pipeline_step.std break return mean_values, scale_values def run(self, model_cfg, model_ckpt, data_cfg, **kwargs): self._init_logger() mode = kwargs.get('mode', 'train') if mode not in self.mode: logger.warning(f'mode for this stage {mode}') return {} cfg = self.configure(model_cfg, model_ckpt, data_cfg, training=False, **kwargs) output_path = os.path.join(cfg.work_dir, 'export') onnx_path = output_path+'/model.onnx' os.makedirs(output_path, exist_ok=True) model = build_classifier(cfg.model) fp16_cfg = cfg.get('fp16', None) if fp16_cfg is not None: wrap_fp16_model(model) logger.info('load checkpoint from ' + cfg.load_from) _ = load_checkpoint(model, cfg.load_from, map_location='cpu') if hasattr(model, 'is_export'): model.is_export = True model.eval() model.forward = partial(model.forward, img_metas={}, return_loss=False) data = self.get_fake_input(cfg) fake_img = data['img'].unsqueeze(0) try: torch.onnx.export(model, fake_img, onnx_path, verbose=False, export_params=True, input_names=['data'], output_names=['logits', 'features', 'vector'], dynamic_axes={}, opset_version=11, operator_export_type=torch.onnx.OperatorExportTypes.ONNX ) mean_values, scale_values = self.get_norm_values(cfg) mo_args = { 'input_model': onnx_path, 'mean_values': mean_values, 'scale_values': scale_values, 'data_type': 'FP32', 'model_name': 'model', 'reverse_input_channels': None, } ret, msg = mo_wrapper.generate_ir(output_path, output_path, silent=True, **mo_args) os.remove(onnx_path) except Exception as ex: return {'outputs': None, 'msg': f'exception {type(ex)}'} bin_file = [f for f in os.listdir(output_path) if f.endswith('.bin')][0] xml_file = [f for f in os.listdir(output_path) if f.endswith('.xml')][0] logger.info('Exporting completed') return { 'outputs': { 'bin': os.path.join(output_path, bin_file), 'xml': os.path.join(output_path, xml_file) }, 'msg': '' }

true

1c2fca169471f7b3ec70ce30effce80a1c395acd

747

py

Python

micropsi_core/tests/test_statuslogger.py

Doik/micropsi2

35ef3b48d9da255939e8e7af0e00bbcc98597602

[ "MIT" ]

null

micropsi_core/tests/test_statuslogger.py

Doik/micropsi2

35ef3b48d9da255939e8e7af0e00bbcc98597602

[ "MIT" ]

null

micropsi_core/tests/test_statuslogger.py

Doik/micropsi2

35ef3b48d9da255939e8e7af0e00bbcc98597602

[ "MIT" ]

1

2019-01-07T21:33:18.000Z

def test_statuslogger_does_not_overwrite_children(runtime, test_nodenet): net = runtime.get_nodenet(test_nodenet) sl = net.netapi.statuslogger sl.info("Learning.Foo", sl.ACTIVE, progress=(5, 23)) sl.info("Learning", sl.SUCCESS, "Learning complete") res, tree = runtime.get_status_tree(test_nodenet) assert tree['Learning']['level'] == "info" assert tree['Learning']['state'] == "success" assert tree['Learning']['msg'] == "Learning complete" assert tree['Learning']['children']['Foo']['level'] == "info" assert tree['Learning']['children']['Foo']['state'] == "active" sl.remove("Learning.Foo") res, tree = runtime.get_status_tree(test_nodenet) assert 'Foo' not in tree['Learning']['children']

43.941176

73

0.676037

def test_statuslogger_does_not_overwrite_children(runtime, test_nodenet): net = runtime.get_nodenet(test_nodenet) sl = net.netapi.statuslogger sl.info("Learning.Foo", sl.ACTIVE, progress=(5, 23)) sl.info("Learning", sl.SUCCESS, "Learning complete") res, tree = runtime.get_status_tree(test_nodenet) assert tree['Learning']['level'] == "info" assert tree['Learning']['state'] == "success" assert tree['Learning']['msg'] == "Learning complete" assert tree['Learning']['children']['Foo']['level'] == "info" assert tree['Learning']['children']['Foo']['state'] == "active" sl.remove("Learning.Foo") res, tree = runtime.get_status_tree(test_nodenet) assert 'Foo' not in tree['Learning']['children']

true

1c2fca5f62fd0ebc9291106c3ba7ee9313876a22

21,639

py

Python

manim/scene/scene_file_writer.py

EpicEricEE/manim

66d26380e526b44d10a405b474356acbbf1f6434

[ "MIT" ]

1

2021-04-19T18:01:55.000Z

manim/scene/scene_file_writer.py

EpicEricEE/manim

66d26380e526b44d10a405b474356acbbf1f6434

[ "MIT" ]

null

manim/scene/scene_file_writer.py

EpicEricEE/manim

66d26380e526b44d10a405b474356acbbf1f6434

[ "MIT" ]

1

2021-03-31T20:46:51.000Z

"""The interface between scenes and ffmpeg.""" __all__ = ["SceneFileWriter"] import datetime import os import shutil import subprocess from pathlib import Path from time import sleep import numpy as np from PIL import Image from pydub import AudioSegment from manim import __version__ from .. import config, logger from ..constants import FFMPEG_BIN, GIF_FILE_EXTENSION from ..utils.file_ops import ( add_extension_if_not_present, add_version_before_extension, guarantee_existence, is_gif_format, is_png_format, is_webm_format, modify_atime, write_to_movie, ) from ..utils.sounds import get_full_sound_file_path class SceneFileWriter: """ SceneFileWriter is the object that actually writes the animations played, into video files, using FFMPEG. This is mostly for Manim's internal use. You will rarely, if ever, have to use the methods for this class, unless tinkering with the very fabric of Manim's reality. Some useful attributes are: "write_to_movie" (bool=False) Whether or not to write the animations into a video file. "movie_file_extension" (str=".mp4") The file-type extension of the outputted video. "partial_movie_files" List of all the partial-movie files. """ def __init__(self, renderer, scene_name, **kwargs): self.renderer = renderer self.stream_lock = False self.init_output_directories(scene_name) self.init_audio() self.frame_count = 0 self.partial_movie_files = [] def init_output_directories(self, scene_name): """Initialise output directories. Notes ----- The directories are read from ``config``, for example ``config['media_dir']``. If the target directories don't already exist, they will be created. """ if config["dry_run"]: # in dry-run mode there is no output return if config["input_file"]: module_name = config.get_dir("input_file").stem else: module_name = "" if config["output_file"] and not config["write_all"]: default_name = config.get_dir("output_file") else: default_name = Path(scene_name) if config["media_dir"]: image_dir = guarantee_existence( config.get_dir("images_dir", module_name=module_name) ) self.image_file_path = os.path.join( image_dir, add_extension_if_not_present(default_name, ".png") ) if write_to_movie(): movie_dir = guarantee_existence( config.get_dir("video_dir", module_name=module_name) ) self.movie_file_path = os.path.join( movie_dir, add_extension_if_not_present( default_name, config["movie_file_extension"] ), ) if is_gif_format(): self.gif_file_path = os.path.join( movie_dir, add_extension_if_not_present(default_name, GIF_FILE_EXTENSION), ) self.partial_movie_directory = guarantee_existence( config.get_dir( "partial_movie_dir", scene_name=scene_name, module_name=module_name, ) ) def add_partial_movie_file(self, hash_animation): """Adds a new partial movie file path to scene.partial_movie_files from an hash. This method will compute the path from the hash. Parameters ---------- hash_animation : str Hash of the animation. """ if not hasattr(self, "partial_movie_directory") or not write_to_movie(): return # None has to be added to partial_movie_files to keep the right index with scene.num_plays. # i.e if an animation is skipped, scene.num_plays is still incremented and we add an element to partial_movie_file be even with num_plays. if hash_animation is None: self.partial_movie_files.append(None) return new_partial_movie_file = os.path.join( self.partial_movie_directory, f"{hash_animation}{config['movie_file_extension']}", ) self.partial_movie_files.append(new_partial_movie_file) def get_resolution_directory(self): """Get the name of the resolution directory directly containing the video file. This method gets the name of the directory that immediately contains the video file. This name is ``<height_in_pixels_of_video>p<frame_rate>``. For example, if you are rendering an 854x480 px animation at 15fps, the name of the directory that immediately contains the video, file will be ``480p15``. The file structure should look something like:: MEDIA_DIR |--Tex |--texts |--videos |--<name_of_file_containing_scene> |--<height_in_pixels_of_video>p<frame_rate> |--<scene_name>.mp4 Returns ------- :class:`str` The name of the directory. """ pixel_height = config["pixel_height"] frame_rate = config["frame_rate"] return f"{pixel_height}p{frame_rate}" # Sound def init_audio(self): """ Preps the writer for adding audio to the movie. """ self.includes_sound = False def create_audio_segment(self): """ Creates an empty, silent, Audio Segment. """ self.audio_segment = AudioSegment.silent() def add_audio_segment(self, new_segment, time=None, gain_to_background=None): """ This method adds an audio segment from an AudioSegment type object and suitable parameters. Parameters ---------- new_segment : AudioSegment The audio segment to add time : int, float, optional the timestamp at which the sound should be added. gain_to_background : optional The gain of the segment from the background. """ if not self.includes_sound: self.includes_sound = True self.create_audio_segment() segment = self.audio_segment curr_end = segment.duration_seconds if time is None: time = curr_end if time < 0: raise ValueError("Adding sound at timestamp < 0") new_end = time + new_segment.duration_seconds diff = new_end - curr_end if diff > 0: segment = segment.append( AudioSegment.silent(int(np.ceil(diff * 1000))), crossfade=0, ) self.audio_segment = segment.overlay( new_segment, position=int(1000 * time), gain_during_overlay=gain_to_background, ) def add_sound(self, sound_file, time=None, gain=None, **kwargs): """ This method adds an audio segment from a sound file. Parameters ---------- sound_file : str The path to the sound file. time : float or int, optional The timestamp at which the audio should be added. gain : optional The gain of the given audio segment. **kwargs This method uses add_audio_segment, so any keyword arguments used there can be referenced here. """ file_path = get_full_sound_file_path(sound_file) new_segment = AudioSegment.from_file(file_path) if gain: new_segment = new_segment.apply_gain(gain) self.add_audio_segment(new_segment, time, **kwargs) # Writers def begin_animation(self, allow_write=False, file_path=None): """ Used internally by manim to stream the animation to FFMPEG for displaying or writing to a file. Parameters ---------- allow_write : bool, optional Whether or not to write to a video file. """ if write_to_movie() and allow_write: self.open_movie_pipe(file_path=file_path) def end_animation(self, allow_write=False): """ Internally used by Manim to stop streaming to FFMPEG gracefully. Parameters ---------- allow_write : bool, optional Whether or not to write to a video file. """ if write_to_movie() and allow_write: self.close_movie_pipe() def write_frame(self, frame_or_renderer): """ Used internally by Manim to write a frame to the FFMPEG input buffer. Parameters ---------- frame : np.array Pixel array of the frame. """ if config.renderer == "opengl": renderer = frame_or_renderer self.writing_process.stdin.write( renderer.get_raw_frame_buffer_object_data() ) else: frame = frame_or_renderer if write_to_movie(): self.writing_process.stdin.write(frame.tobytes()) if is_png_format() and not config["dry_run"]: target_dir, extension = os.path.splitext(self.image_file_path) if config["zero_pad"]: Image.fromarray(frame).save( f"{target_dir}{str(self.frame_count).zfill(config['zero_pad'])}{extension}" ) else: Image.fromarray(frame).save( f"{target_dir}{self.frame_count}{extension}" ) self.frame_count += 1 def save_final_image(self, image): """ The name is a misnomer. This method saves the image passed to it as an in the default image directory. Parameters ---------- image : np.array The pixel array of the image to save. """ if config["dry_run"]: return if not config["output_file"]: self.image_file_path = add_version_before_extension(self.image_file_path) image.save(self.image_file_path) self.print_file_ready_message(self.image_file_path) def idle_stream(self): """ Doesn't write anything to the FFMPEG frame buffer. """ while self.stream_lock: a = datetime.datetime.now() # self.update_frame() self.renderer.update_frame() n_frames = 1 # frame = self.get_frame() frame = self.renderer.get_frame() # self.add_frame(*[frame] * n_frames) self.renderer.add_frame(*[frame] * n_frames) b = datetime.datetime.now() time_diff = (b - a).total_seconds() frame_duration = 1 / config["frame_rate"] if time_diff < frame_duration: sleep(frame_duration - time_diff) def finish(self, partial_movie_files=None): """ Finishes writing to the FFMPEG buffer or writing images to output directory. Combines the partial movie files into the whole scene. If save_last_frame is True, saves the last frame in the default image directory. """ if write_to_movie(): if hasattr(self, "writing_process"): self.writing_process.terminate() self.combine_movie_files(partial_movie_files=partial_movie_files) if config["flush_cache"]: self.flush_cache_directory() else: self.clean_cache() elif is_png_format() and not config["dry_run"]: target_dir, _ = os.path.splitext(self.image_file_path) logger.info("\n%i images ready at %s\n", self.frame_count, target_dir) def open_movie_pipe(self, file_path=None): """ Used internally by Manim to initialise FFMPEG and begin writing to FFMPEG's input buffer. """ if file_path is None: file_path = self.partial_movie_files[self.renderer.num_plays] self.partial_movie_file_path = file_path fps = config["frame_rate"] if fps == int(fps): # fps is integer fps = int(fps) if config.renderer == "opengl": width, height = self.renderer.get_pixel_shape() else: height = config["pixel_height"] width = config["pixel_width"] command = [ FFMPEG_BIN, "-y", # overwrite output file if it exists "-f", "rawvideo", "-s", "%dx%d" % (width, height), # size of one frame "-pix_fmt", "rgba", "-r", str(fps), # frames per second "-i", "-", # The input comes from a pipe "-an", # Tells FFMPEG not to expect any audio "-loglevel", config["ffmpeg_loglevel"].lower(), "-metadata", f"comment=Rendered with Manim Community v{__version__}", ] if config.renderer == "opengl": command += ["-vf", "vflip"] if is_webm_format(): command += ["-vcodec", "libvpx-vp9", "-auto-alt-ref", "0"] # .mov format elif config["transparent"]: command += ["-vcodec", "qtrle"] else: command += ["-vcodec", "libx264", "-pix_fmt", "yuv420p"] command += [file_path] self.writing_process = subprocess.Popen(command, stdin=subprocess.PIPE) def close_movie_pipe(self): """ Used internally by Manim to gracefully stop writing to FFMPEG's input buffer """ self.writing_process.stdin.close() self.writing_process.wait() logger.info( f"Animation {self.renderer.num_plays} : Partial movie file written in %(path)s", {"path": f"'{self.partial_movie_file_path}'"}, ) def is_already_cached(self, hash_invocation): """Will check if a file named with `hash_invocation` exists. Parameters ---------- hash_invocation : :class:`str` The hash corresponding to an invocation to either `scene.play` or `scene.wait`. Returns ------- :class:`bool` Whether the file exists. """ if not hasattr(self, "partial_movie_directory") or not write_to_movie(): return False path = os.path.join( self.partial_movie_directory, f"{hash_invocation}{config['movie_file_extension']}", ) return os.path.exists(path) def combine_movie_files(self, partial_movie_files=None): """ Used internally by Manim to combine the separate partial movie files that make up a Scene into a single video file for that Scene. """ # Manim renders the scene as many smaller movie files which are then # concatenated to a larger one. The reason for this is that sometimes # video-editing is made easier when one works with the broken up scene, # which effectively has cuts at all the places you might want. But for # viewing the scene as a whole, one of course wants to see it as a # single piece. partial_movie_files = [el for el in self.partial_movie_files if el is not None] # NOTE : Here we should do a check and raise an exception if partial # movie file is empty. We can't, as a lot of stuff (in particular, in # tests) use scene initialization, and this error would be raised as # it's just an empty scene initialized. # Write a file partial_file_list.txt containing all partial movie # files. This is used by FFMPEG. file_list = os.path.join( self.partial_movie_directory, "partial_movie_file_list.txt" ) logger.debug( f"Partial movie files to combine ({len(partial_movie_files)} files): %(p)s", {"p": partial_movie_files[:5]}, ) with open(file_list, "w") as fp: fp.write("# This file is used internally by FFMPEG.\n") for pf_path in partial_movie_files: if os.name == "nt": pf_path = pf_path.replace("\\", "/") fp.write(f"file 'file:{pf_path}'\n") movie_file_path = self.movie_file_path commands = [ FFMPEG_BIN, "-y", # overwrite output file if it exists "-f", "concat", "-safe", "0", "-i", file_list, "-loglevel", config["ffmpeg_loglevel"].lower(), "-metadata", f"comment=Rendered with Manim Community v{__version__}", "-nostdin", ] if write_to_movie() and not is_gif_format(): commands += ["-c", "copy", movie_file_path] if is_gif_format(): if not config["output_file"]: self.gif_file_path = str( add_version_before_extension(self.gif_file_path) ) commands += [ "-vf", f"fps={np.clip(config['frame_rate'], 1, 50)},split[s0][s1];[s0]palettegen=stats_mode=diff[p];[s1][p]paletteuse=dither=bayer:bayer_scale=5:diff_mode=rectangle", self.gif_file_path, ] if not self.includes_sound: commands.insert(-1, "-an") combine_process = subprocess.Popen(commands) combine_process.wait() if self.includes_sound: extension = config["movie_file_extension"] sound_file_path = movie_file_path.replace(extension, ".wav") # Makes sure sound file length will match video file self.add_audio_segment(AudioSegment.silent(0)) self.audio_segment.export( sound_file_path, bitrate="312k", ) temp_file_path = movie_file_path.replace(extension, f"_temp{extension}") commands = [ FFMPEG_BIN, "-i", movie_file_path, "-i", sound_file_path, "-y", # overwrite output file if it exists "-c:v", "copy", "-c:a", "aac", "-b:a", "320k", # select video stream from first file "-map", "0:v:0", # select audio stream from second file "-map", "1:a:0", "-loglevel", config["ffmpeg_loglevel"].lower(), "-metadata", f"comment=Rendered with Manim Community v{__version__}", # "-shortest", temp_file_path, ] subprocess.call(commands) shutil.move(temp_file_path, movie_file_path) os.remove(sound_file_path) self.print_file_ready_message( self.gif_file_path if is_gif_format() else movie_file_path ) if write_to_movie(): for file_path in partial_movie_files: # We have to modify the accessed time so if we have to clean the cache we remove the one used the longest. modify_atime(file_path) def clean_cache(self): """Will clean the cache by removing the partial_movie_files used by manim the longest ago.""" cached_partial_movies = [ os.path.join(self.partial_movie_directory, file_name) for file_name in os.listdir(self.partial_movie_directory) if file_name != "partial_movie_file_list.txt" ] if len(cached_partial_movies) > config["max_files_cached"]: number_files_to_delete = ( len(cached_partial_movies) - config["max_files_cached"] ) oldest_files_to_delete = sorted( cached_partial_movies, key=os.path.getatime, )[:number_files_to_delete] # oldest_file_path = min(cached_partial_movies, key=os.path.getatime) for file_to_delete in oldest_files_to_delete: os.remove(file_to_delete) logger.info( f"The partial movie directory is full (> {config['max_files_cached']} files). Therefore, manim has removed {number_files_to_delete} file(s) used by it the longest ago." + "You can change this behaviour by changing max_files_cached in config." ) def flush_cache_directory(self): """Delete all the cached partial movie files""" cached_partial_movies = [ os.path.join(self.partial_movie_directory, file_name) for file_name in os.listdir(self.partial_movie_directory) if file_name != "partial_movie_file_list.txt" ] for f in cached_partial_movies: os.remove(f) logger.info( f"Cache flushed. {len(cached_partial_movies)} file(s) deleted in %(par_dir)s.", {"par_dir": self.partial_movie_directory}, ) def print_file_ready_message(self, file_path): """Prints the "File Ready" message to STDOUT.""" config["output_file"] = file_path logger.info("\nFile ready at %(file_path)s\n", {"file_path": f"'{file_path}'"})

35.885572

184

0.575674

__all__ = ["SceneFileWriter"] import datetime import os import shutil import subprocess from pathlib import Path from time import sleep import numpy as np from PIL import Image from pydub import AudioSegment from manim import __version__ from .. import config, logger from ..constants import FFMPEG_BIN, GIF_FILE_EXTENSION from ..utils.file_ops import ( add_extension_if_not_present, add_version_before_extension, guarantee_existence, is_gif_format, is_png_format, is_webm_format, modify_atime, write_to_movie, ) from ..utils.sounds import get_full_sound_file_path class SceneFileWriter: def __init__(self, renderer, scene_name, **kwargs): self.renderer = renderer self.stream_lock = False self.init_output_directories(scene_name) self.init_audio() self.frame_count = 0 self.partial_movie_files = [] def init_output_directories(self, scene_name): if config["dry_run"]: return if config["input_file"]: module_name = config.get_dir("input_file").stem else: module_name = "" if config["output_file"] and not config["write_all"]: default_name = config.get_dir("output_file") else: default_name = Path(scene_name) if config["media_dir"]: image_dir = guarantee_existence( config.get_dir("images_dir", module_name=module_name) ) self.image_file_path = os.path.join( image_dir, add_extension_if_not_present(default_name, ".png") ) if write_to_movie(): movie_dir = guarantee_existence( config.get_dir("video_dir", module_name=module_name) ) self.movie_file_path = os.path.join( movie_dir, add_extension_if_not_present( default_name, config["movie_file_extension"] ), ) if is_gif_format(): self.gif_file_path = os.path.join( movie_dir, add_extension_if_not_present(default_name, GIF_FILE_EXTENSION), ) self.partial_movie_directory = guarantee_existence( config.get_dir( "partial_movie_dir", scene_name=scene_name, module_name=module_name, ) ) def add_partial_movie_file(self, hash_animation): if not hasattr(self, "partial_movie_directory") or not write_to_movie(): return if hash_animation is None: self.partial_movie_files.append(None) return new_partial_movie_file = os.path.join( self.partial_movie_directory, f"{hash_animation}{config['movie_file_extension']}", ) self.partial_movie_files.append(new_partial_movie_file) def get_resolution_directory(self): pixel_height = config["pixel_height"] frame_rate = config["frame_rate"] return f"{pixel_height}p{frame_rate}" def init_audio(self): self.includes_sound = False def create_audio_segment(self): self.audio_segment = AudioSegment.silent() def add_audio_segment(self, new_segment, time=None, gain_to_background=None): if not self.includes_sound: self.includes_sound = True self.create_audio_segment() segment = self.audio_segment curr_end = segment.duration_seconds if time is None: time = curr_end if time < 0: raise ValueError("Adding sound at timestamp < 0") new_end = time + new_segment.duration_seconds diff = new_end - curr_end if diff > 0: segment = segment.append( AudioSegment.silent(int(np.ceil(diff * 1000))), crossfade=0, ) self.audio_segment = segment.overlay( new_segment, position=int(1000 * time), gain_during_overlay=gain_to_background, ) def add_sound(self, sound_file, time=None, gain=None, **kwargs): file_path = get_full_sound_file_path(sound_file) new_segment = AudioSegment.from_file(file_path) if gain: new_segment = new_segment.apply_gain(gain) self.add_audio_segment(new_segment, time, **kwargs) def begin_animation(self, allow_write=False, file_path=None): if write_to_movie() and allow_write: self.open_movie_pipe(file_path=file_path) def end_animation(self, allow_write=False): if write_to_movie() and allow_write: self.close_movie_pipe() def write_frame(self, frame_or_renderer): if config.renderer == "opengl": renderer = frame_or_renderer self.writing_process.stdin.write( renderer.get_raw_frame_buffer_object_data() ) else: frame = frame_or_renderer if write_to_movie(): self.writing_process.stdin.write(frame.tobytes()) if is_png_format() and not config["dry_run"]: target_dir, extension = os.path.splitext(self.image_file_path) if config["zero_pad"]: Image.fromarray(frame).save( f"{target_dir}{str(self.frame_count).zfill(config['zero_pad'])}{extension}" ) else: Image.fromarray(frame).save( f"{target_dir}{self.frame_count}{extension}" ) self.frame_count += 1 def save_final_image(self, image): if config["dry_run"]: return if not config["output_file"]: self.image_file_path = add_version_before_extension(self.image_file_path) image.save(self.image_file_path) self.print_file_ready_message(self.image_file_path) def idle_stream(self): while self.stream_lock: a = datetime.datetime.now() self.renderer.update_frame() n_frames = 1 frame = self.renderer.get_frame() self.renderer.add_frame(*[frame] * n_frames) b = datetime.datetime.now() time_diff = (b - a).total_seconds() frame_duration = 1 / config["frame_rate"] if time_diff < frame_duration: sleep(frame_duration - time_diff) def finish(self, partial_movie_files=None): if write_to_movie(): if hasattr(self, "writing_process"): self.writing_process.terminate() self.combine_movie_files(partial_movie_files=partial_movie_files) if config["flush_cache"]: self.flush_cache_directory() else: self.clean_cache() elif is_png_format() and not config["dry_run"]: target_dir, _ = os.path.splitext(self.image_file_path) logger.info("\n%i images ready at %s\n", self.frame_count, target_dir) def open_movie_pipe(self, file_path=None): if file_path is None: file_path = self.partial_movie_files[self.renderer.num_plays] self.partial_movie_file_path = file_path fps = config["frame_rate"] if fps == int(fps): fps = int(fps) if config.renderer == "opengl": width, height = self.renderer.get_pixel_shape() else: height = config["pixel_height"] width = config["pixel_width"] command = [ FFMPEG_BIN, "-y", "-f", "rawvideo", "-s", "%dx%d" % (width, height), "-pix_fmt", "rgba", "-r", str(fps), "-i", "-", "-an", "-loglevel", config["ffmpeg_loglevel"].lower(), "-metadata", f"comment=Rendered with Manim Community v{__version__}", ] if config.renderer == "opengl": command += ["-vf", "vflip"] if is_webm_format(): command += ["-vcodec", "libvpx-vp9", "-auto-alt-ref", "0"] elif config["transparent"]: command += ["-vcodec", "qtrle"] else: command += ["-vcodec", "libx264", "-pix_fmt", "yuv420p"] command += [file_path] self.writing_process = subprocess.Popen(command, stdin=subprocess.PIPE) def close_movie_pipe(self): self.writing_process.stdin.close() self.writing_process.wait() logger.info( f"Animation {self.renderer.num_plays} : Partial movie file written in %(path)s", {"path": f"'{self.partial_movie_file_path}'"}, ) def is_already_cached(self, hash_invocation): if not hasattr(self, "partial_movie_directory") or not write_to_movie(): return False path = os.path.join( self.partial_movie_directory, f"{hash_invocation}{config['movie_file_extension']}", ) return os.path.exists(path) def combine_movie_files(self, partial_movie_files=None): partial_movie_files = [el for el in self.partial_movie_files if el is not None] # tests) use scene initialization, and this error would be raised as # it's just an empty scene initialized. file_list = os.path.join( self.partial_movie_directory, "partial_movie_file_list.txt" ) logger.debug( f"Partial movie files to combine ({len(partial_movie_files)} files): %(p)s", {"p": partial_movie_files[:5]}, ) with open(file_list, "w") as fp: fp.write("# This file is used internally by FFMPEG.\n") for pf_path in partial_movie_files: if os.name == "nt": pf_path = pf_path.replace("\\", "/") fp.write(f"file 'file:{pf_path}'\n") movie_file_path = self.movie_file_path commands = [ FFMPEG_BIN, "-y", "-f", "concat", "-safe", "0", "-i", file_list, "-loglevel", config["ffmpeg_loglevel"].lower(), "-metadata", f"comment=Rendered with Manim Community v{__version__}", "-nostdin", ] if write_to_movie() and not is_gif_format(): commands += ["-c", "copy", movie_file_path] if is_gif_format(): if not config["output_file"]: self.gif_file_path = str( add_version_before_extension(self.gif_file_path) ) commands += [ "-vf", f"fps={np.clip(config['frame_rate'], 1, 50)},split[s0][s1];[s0]palettegen=stats_mode=diff[p];[s1][p]paletteuse=dither=bayer:bayer_scale=5:diff_mode=rectangle", self.gif_file_path, ] if not self.includes_sound: commands.insert(-1, "-an") combine_process = subprocess.Popen(commands) combine_process.wait() if self.includes_sound: extension = config["movie_file_extension"] sound_file_path = movie_file_path.replace(extension, ".wav") self.add_audio_segment(AudioSegment.silent(0)) self.audio_segment.export( sound_file_path, bitrate="312k", ) temp_file_path = movie_file_path.replace(extension, f"_temp{extension}") commands = [ FFMPEG_BIN, "-i", movie_file_path, "-i", sound_file_path, "-y", "-c:v", "copy", "-c:a", "aac", "-b:a", "320k", "-map", "0:v:0", "-map", "1:a:0", "-loglevel", config["ffmpeg_loglevel"].lower(), "-metadata", f"comment=Rendered with Manim Community v{__version__}", temp_file_path, ] subprocess.call(commands) shutil.move(temp_file_path, movie_file_path) os.remove(sound_file_path) self.print_file_ready_message( self.gif_file_path if is_gif_format() else movie_file_path ) if write_to_movie(): for file_path in partial_movie_files: modify_atime(file_path) def clean_cache(self): cached_partial_movies = [ os.path.join(self.partial_movie_directory, file_name) for file_name in os.listdir(self.partial_movie_directory) if file_name != "partial_movie_file_list.txt" ] if len(cached_partial_movies) > config["max_files_cached"]: number_files_to_delete = ( len(cached_partial_movies) - config["max_files_cached"] ) oldest_files_to_delete = sorted( cached_partial_movies, key=os.path.getatime, )[:number_files_to_delete] for file_to_delete in oldest_files_to_delete: os.remove(file_to_delete) logger.info( f"The partial movie directory is full (> {config['max_files_cached']} files). Therefore, manim has removed {number_files_to_delete} file(s) used by it the longest ago." + "You can change this behaviour by changing max_files_cached in config." ) def flush_cache_directory(self): cached_partial_movies = [ os.path.join(self.partial_movie_directory, file_name) for file_name in os.listdir(self.partial_movie_directory) if file_name != "partial_movie_file_list.txt" ] for f in cached_partial_movies: os.remove(f) logger.info( f"Cache flushed. {len(cached_partial_movies)} file(s) deleted in %(par_dir)s.", {"par_dir": self.partial_movie_directory}, ) def print_file_ready_message(self, file_path): config["output_file"] = file_path logger.info("\nFile ready at %(file_path)s\n", {"file_path": f"'{file_path}'"})

true

1c2fcab9e0c5719bddabf9a517978dbf7b670dfb

5,708

py

Python

openGaussBase/testcase/SQL/DML/copy/Opengauss_Function_DML_Copy_Case0113.py

opengauss-mirror/Yat

aef107a8304b94e5d99b4f1f36eb46755eb8919e

[ "MulanPSL-1.0" ]

null

openGaussBase/testcase/SQL/DML/copy/Opengauss_Function_DML_Copy_Case0113.py

opengauss-mirror/Yat

aef107a8304b94e5d99b4f1f36eb46755eb8919e

[ "MulanPSL-1.0" ]

null

openGaussBase/testcase/SQL/DML/copy/Opengauss_Function_DML_Copy_Case0113.py

opengauss-mirror/Yat

aef107a8304b94e5d99b4f1f36eb46755eb8919e

[ "MulanPSL-1.0" ]

null

""" Copyright (c) 2022 Huawei Technologies Co.,Ltd. openGauss is licensed under Mulan PSL v2. You can use this software according to the terms and conditions of the Mulan PSL v2. You may obtain a copy of Mulan PSL v2 at: http://license.coscl.org.cn/MulanPSL2 THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE. See the Mulan PSL v2 for more details. """ """ Case Type : 拷贝数据 Case Name : copy from模式下指定smalldatetime_format参数,不带时区 Description : 1.创建测试表并插入数据 2.构造数据文件 3.copy from模式下指定smalldatetime_format不合法的smalldatetime格式 4.copy from模式,binary格式下指定smalldatetime_format 5.copy from模式下指定smalldatetime_format合法的smalldatetime格式 6.清理环境 Expect : 1.创建测试表并插入数据成功 2.构造数据文件成功 3.copy失败 4.copy失败 5.copy成功 6.清理环境成功 History : """ import unittest import os from yat.test import Node from yat.test import macro from testcase.utils.Common import Common from testcase.utils.CommonSH import CommonSH from testcase.utils.Logger import Logger from testcase.utils.Constant import Constant class CopyFile(unittest.TestCase): def setUp(self): self.log = Logger() self.log.info(f'-----{os.path.basename(__file__)} start-----') self.pri_sh = CommonSH('PrimaryDbUser') self.pri_user = Node(node='PrimaryDbUser') self.common = Common() self.Constant = Constant() self.tb_name = 't_copy_113' self.file_name = 'testcopy113.dat' self.copy_dir_path = os.path.join(macro.DB_INSTANCE_PATH, 'pg_copydir') def test_copy_file(self): text = '-----step1:创建测试表并对测试表插入数据' \ 'Expect:创建测试表并插入数据成功-----' self.log.info(text) sql_cmd = f"drop table if exists {self.tb_name};" \ f"create table {self.tb_name} (sk integer,id varchar(16)," \ f"name varchar(20),create_smalldatetime smalldatetime);" \ f"insert into {self.tb_name} values " \ f"(001,'sk1','tt1','2021-11-01 01:02:30');" \ f"insert into {self.tb_name} values " \ f"(002,'sk2','tt2','2022-01-23 02:02:30');" \ f"insert into {self.tb_name} values" \ f" (003,'sk3','tt3','2000-12-23 03:02:30');" self.log.info(sql_cmd) sql_res = self.pri_sh.execut_db_sql(sql_cmd) self.log.info(sql_res) self.assertIn(self.Constant.CREATE_TABLE_SUCCESS, sql_res, '执行失败:' + text) self.assertIn(self.Constant.INSERT_SUCCESS_MSG, sql_res, '执行失败:' + text) self.assertNotIn(self.Constant.SQL_WRONG_MSG[1], sql_res, '执行失败:' + text) text = '-----step2:构造数据文件 Expect:构造数据文件成功-----' self.log.info(text) excute_cmd = f'''mkdir {self.copy_dir_path}; touch {os.path.join(self.copy_dir_path, self.file_name)};''' self.log.info(excute_cmd) msg = self.common.get_sh_result(self.pri_user, excute_cmd) self.log.info(msg) self.assertEqual(len(msg), 0, '执行失败:' + text) sql_cmd = self.pri_sh.execut_db_sql( f"copy {self.tb_name} to '" f"{os.path.join(self.copy_dir_path, self.file_name)}';") self.assertIn('COPY 3', sql_cmd, '执行失败:' + text) text = '-----step3:copy from模式下指定smalldatetime_format不合法的' \ 'smalldatetime格式 Expect:copy失败-----' self.log.info(text) sql_cmd = f"copy {self.tb_name} from '" \ f"{os.path.join(self.copy_dir_path, self.file_name)}' " \ f"with(format 'text',smalldatetime_format 'YYYY-M-D HH:MI:SS');" self.log.info(sql_cmd) sql_res = self.pri_sh.execut_db_sql(sql_cmd) self.log.info(sql_res) self.assertIn('invalid data for match in format string', sql_res, '执行失败:' + text) text = '-----step4:copy from模式,binary格式下指定smalldatetime_format' \ 'Expect:copy失败-----' self.log.info(text) sql_cmd = f"copy {self.tb_name} from '" \ f"{os.path.join(self.copy_dir_path, self.file_name)}'" \ f"with(format 'binary',smalldatetime_format " \ f"'YYYY-MM-DD HH:MI:SS');" self.log.info(sql_cmd) sql_res = self.pri_sh.execut_db_sql(sql_cmd) self.log.info(sql_res) self.assertIn('compatibility options in BINARY mode', sql_res, '执行失败:' + text) text = '-----step5:copy from模式下指定smalldatetime_format合法的' \ 'smalldatetime格式 Expect:copy成功-----' self.log.info(text) sql_cmd = f"copy {self.tb_name} from '" \ f"{os.path.join(self.copy_dir_path, self.file_name)}'" \ f"with(format 'text',smalldatetime_format 'YYYY-MM-DD HH:MI:SS');" self.log.info(sql_cmd) sql_res = self.pri_sh.execut_db_sql(sql_cmd) self.log.info(sql_res) self.assertIn('COPY 3', sql_res, '执行失败:' + text) def tearDown(self): text = '-----step6:清理环境 Expect:清理环境成功-----' self.log.info(text) sql_cmd = self.pri_sh.execut_db_sql( f"drop table if exists {self.tb_name};") self.log.info(sql_cmd) excute_cmd = f'''rm -rf {self.copy_dir_path}''' self.log.info(excute_cmd) msg = self.common.get_sh_result(self.pri_user, excute_cmd) self.log.info(msg) self.assertEqual(len(msg), 0, '执行失败:' + text) self.assertIn(self.Constant.TABLE_DROP_SUCCESS, sql_cmd) self.log.info(f'-----{os.path.basename(__file__)} end-----')

39.638889

84

0.61405

import unittest import os from yat.test import Node from yat.test import macro from testcase.utils.Common import Common from testcase.utils.CommonSH import CommonSH from testcase.utils.Logger import Logger from testcase.utils.Constant import Constant class CopyFile(unittest.TestCase): def setUp(self): self.log = Logger() self.log.info(f'-----{os.path.basename(__file__)} start-----') self.pri_sh = CommonSH('PrimaryDbUser') self.pri_user = Node(node='PrimaryDbUser') self.common = Common() self.Constant = Constant() self.tb_name = 't_copy_113' self.file_name = 'testcopy113.dat' self.copy_dir_path = os.path.join(macro.DB_INSTANCE_PATH, 'pg_copydir') def test_copy_file(self): text = '-----step1:创建测试表并对测试表插入数据' \ 'Expect:创建测试表并插入数据成功-----' self.log.info(text) sql_cmd = f"drop table if exists {self.tb_name};" \ f"create table {self.tb_name} (sk integer,id varchar(16)," \ f"name varchar(20),create_smalldatetime smalldatetime);" \ f"insert into {self.tb_name} values " \ f"(001,'sk1','tt1','2021-11-01 01:02:30');" \ f"insert into {self.tb_name} values " \ f"(002,'sk2','tt2','2022-01-23 02:02:30');" \ f"insert into {self.tb_name} values" \ f" (003,'sk3','tt3','2000-12-23 03:02:30');" self.log.info(sql_cmd) sql_res = self.pri_sh.execut_db_sql(sql_cmd) self.log.info(sql_res) self.assertIn(self.Constant.CREATE_TABLE_SUCCESS, sql_res, '执行失败:' + text) self.assertIn(self.Constant.INSERT_SUCCESS_MSG, sql_res, '执行失败:' + text) self.assertNotIn(self.Constant.SQL_WRONG_MSG[1], sql_res, '执行失败:' + text) text = '-----step2:构造数据文件 Expect:构造数据文件成功-----' self.log.info(text) excute_cmd = f'''mkdir {self.copy_dir_path}; touch {os.path.join(self.copy_dir_path, self.file_name)};''' self.log.info(excute_cmd) msg = self.common.get_sh_result(self.pri_user, excute_cmd) self.log.info(msg) self.assertEqual(len(msg), 0, '执行失败:' + text) sql_cmd = self.pri_sh.execut_db_sql( f"copy {self.tb_name} to '" f"{os.path.join(self.copy_dir_path, self.file_name)}';") self.assertIn('COPY 3', sql_cmd, '执行失败:' + text) text = '-----step3:copy from模式下指定smalldatetime_format不合法的' \ 'smalldatetime格式 Expect:copy失败-----' self.log.info(text) sql_cmd = f"copy {self.tb_name} from '" \ f"{os.path.join(self.copy_dir_path, self.file_name)}' " \ f"with(format 'text',smalldatetime_format 'YYYY-M-D HH:MI:SS');" self.log.info(sql_cmd) sql_res = self.pri_sh.execut_db_sql(sql_cmd) self.log.info(sql_res) self.assertIn('invalid data for match in format string', sql_res, '执行失败:' + text) text = '-----step4:copy from模式,binary格式下指定smalldatetime_format' \ 'Expect:copy失败-----' self.log.info(text) sql_cmd = f"copy {self.tb_name} from '" \ f"{os.path.join(self.copy_dir_path, self.file_name)}'" \ f"with(format 'binary',smalldatetime_format " \ f"'YYYY-MM-DD HH:MI:SS');" self.log.info(sql_cmd) sql_res = self.pri_sh.execut_db_sql(sql_cmd) self.log.info(sql_res) self.assertIn('compatibility options in BINARY mode', sql_res, '执行失败:' + text) text = '-----step5:copy from模式下指定smalldatetime_format合法的' \ 'smalldatetime格式 Expect:copy成功-----' self.log.info(text) sql_cmd = f"copy {self.tb_name} from '" \ f"{os.path.join(self.copy_dir_path, self.file_name)}'" \ f"with(format 'text',smalldatetime_format 'YYYY-MM-DD HH:MI:SS');" self.log.info(sql_cmd) sql_res = self.pri_sh.execut_db_sql(sql_cmd) self.log.info(sql_res) self.assertIn('COPY 3', sql_res, '执行失败:' + text) def tearDown(self): text = '-----step6:清理环境 Expect:清理环境成功-----' self.log.info(text) sql_cmd = self.pri_sh.execut_db_sql( f"drop table if exists {self.tb_name};") self.log.info(sql_cmd) excute_cmd = f'''rm -rf {self.copy_dir_path}''' self.log.info(excute_cmd) msg = self.common.get_sh_result(self.pri_user, excute_cmd) self.log.info(msg) self.assertEqual(len(msg), 0, '执行失败:' + text) self.assertIn(self.Constant.TABLE_DROP_SUCCESS, sql_cmd) self.log.info(f'-----{os.path.basename(__file__)} end-----')

true

1c2fcaee24f6b4fdf6f998f4d35d716b58107bbf

356

py

Python

src/admin_utils/brief.py

ionelmc/django-admin-utils

d1c1d64a6d97f3589746c06352b21500d234209d

[ "BSD-2-Clause" ]

14

2015-02-05T04:18:37.000Z

2022-01-29T08:35:23.000Z

src/admin_utils/brief.py

mattcaldwell/django-admin-utils

a1bf8638111fa90dada9d39e515972668630f7be

[ "BSD-2-Clause" ]

null

src/admin_utils/brief.py

mattcaldwell/django-admin-utils

a1bf8638111fa90dada9d39e515972668630f7be

[ "BSD-2-Clause" ]

3

2015-03-30T18:44:26.000Z

2021-01-05T18:49:03.000Z

from django.contrib import admin def register(model, site=admin.site): def decorator(klass): site.register(model, klass) return klass return decorator def inline(model, klass=admin.TabularInline, **options): return type( "%sInlineAdmin" % model.__name__, (klass,), dict(model=model, **options) )

20.941176

56

0.63764

from django.contrib import admin def register(model, site=admin.site): def decorator(klass): site.register(model, klass) return klass return decorator def inline(model, klass=admin.TabularInline, **options): return type( "%sInlineAdmin" % model.__name__, (klass,), dict(model=model, **options) )

true

1c2fcb490335c2e2fc92adb3893eecaaa49d33f2

1,436

py

Python

pytext/loss/tests/ctc_loss_test.py

dmitryvinn/pytext

43373462d1b9bada3ba02072aed78338d3bb3a12

[ "BSD-3-Clause" ]

6,199

2018-12-13T15:34:51.000Z

2022-03-26T04:08:58.000Z

pytext/loss/tests/ctc_loss_test.py

dmitryvinn/pytext

43373462d1b9bada3ba02072aed78338d3bb3a12

[ "BSD-3-Clause" ]

1,356

2018-12-13T15:50:33.000Z

2022-03-03T20:45:58.000Z

pytext/loss/tests/ctc_loss_test.py

dmitryvinn/pytext

43373462d1b9bada3ba02072aed78338d3bb3a12

[ "BSD-3-Clause" ]

842

2018-12-13T15:35:13.000Z

2022-03-23T13:27:00.000Z

#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved import unittest import torch import torch.nn.functional as F from pytext.loss.loss import CTCLoss class CTCLossTest(unittest.TestCase): def test_ctc_loss(self): torch.manual_seed(0) N = 16 # Batch size T = 50 # Input sequence length C = 20 # Number of classes (including blank) S = 30 # Target sequence length of longest target in batch (padding length) S_min = 10 # Minimum target length (only for testing) logits = torch.randn(N, T, C) targets = torch.randint(1, C, (N, S), dtype=torch.long) input_lengths = torch.full((N,), T, dtype=torch.long) target_lengths = torch.randint(S_min, S, (N,), dtype=torch.long) config = CTCLoss.Config() config.blank = 0 # Needs to be set to 0 for CuDNN support. ctc_loss_fn = CTCLoss(config=config) ctc_loss_val = ctc_loss_fn( logits, targets, input_lengths, target_lengths, ) # PyTorch CTC loss log_probs = logits.permute(1, 0, 2).log_softmax( 2 ) # permute to conform to CTC loss input tensor (T,N,C) in PyTorch. lib_ctc_loss_val = F.ctc_loss(log_probs, targets, input_lengths, target_lengths) self.assertAlmostEqual(ctc_loss_val.item(), lib_ctc_loss_val.item())

32.636364

88

0.629526

import unittest import torch import torch.nn.functional as F from pytext.loss.loss import CTCLoss class CTCLossTest(unittest.TestCase): def test_ctc_loss(self): torch.manual_seed(0) N = 16 T = 50 C = 20 S = 30 S_min = 10 logits = torch.randn(N, T, C) targets = torch.randint(1, C, (N, S), dtype=torch.long) input_lengths = torch.full((N,), T, dtype=torch.long) target_lengths = torch.randint(S_min, S, (N,), dtype=torch.long) config = CTCLoss.Config() config.blank = 0 ctc_loss_fn = CTCLoss(config=config) ctc_loss_val = ctc_loss_fn( logits, targets, input_lengths, target_lengths, ) log_probs = logits.permute(1, 0, 2).log_softmax( 2 ) lib_ctc_loss_val = F.ctc_loss(log_probs, targets, input_lengths, target_lengths) self.assertAlmostEqual(ctc_loss_val.item(), lib_ctc_loss_val.item())

true

1c2fcf462232fd130a11832b921637407dc6a8a4

14,515

py

Python

core/common.py

tangb/cleep-desktop

7e333b0ce8445fad86216c4b51b1ade8c21695fd

[ "MIT" ]

2

2020-07-31T13:24:05.000Z

2022-03-10T08:44:06.000Z

core/common.py

tangb/cleep-desktop

7e333b0ce8445fad86216c4b51b1ade8c21695fd

[ "MIT" ]

6

2020-04-09T16:44:28.000Z

2022-02-22T11:26:24.000Z

core/common.py

tangb/cleep-desktop

7e333b0ce8445fad86216c4b51b1ade8c21695fd

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ This file shares some constants and classes """ from core.exception import InvalidMessage import copy __all__ = ['CORE_MODULES', 'CATEGORIES', 'PeerInfos', 'ExecutionStep', 'MessageResponse', 'MessageRequest'] """ CONSTANTS """ CORE_MODULES = [ 'system', 'update', 'audio', 'network', 'cleepbus', 'parameters' ] class CATEGORIES(object): """ Cleep application categories """ #generic application APPLICATION = 'APPLICATION' #mobile application for car, bike, hiking... MOBILE = 'MOBILE' #application to configure and use hardware (soundcard, display...) DRIVER = 'DRIVER' #home automation application (shutter, light...) HOMEAUTOMATION = 'HOMEAUTOMATION' #media application (music player, video player...) MEDIA = 'MEDIA' #application based on online service (sms broker, weather provider...) SERVICE = 'SERVICE' ALL = ['APPLICATION', 'MOBILE', 'DRIVER', 'HOMEAUTOMATION', 'MEDIA', 'SERVICE'] class ExecutionStep(object): """ Cleep execution steps """ #boot step (init logger, brokers...) BOOT = 0 #init modules (constructor) INIT = 1 #configure modules (_configure) CONFIG = 2 #application and all modules are running RUN = 3 #stopping cleep STOP = 4 def __init__(self): self.step = self.BOOT class PeerInfos(): """ Stores peer informations """ def __init__(self, uuid=None, ident=None, hostname=None, ip=None, port=80, ssl=False, macs=None, cleepdesktop=False, extra={}, ): """ Constructor Args: uuid (string): peer uuid provided by cleep ident (string): peer identifier provided by external bus hostname (string): peer hostname ip (string): peer ip port (int): peer access port ssl (bool): peer has ssl enabled macs (list): list of macs addresses cleepdesktop (bool): is cleepdesktop peer extra (dict): extra peer informations (about hardware...) Note: Uuid is mandatory because device can change identifier after each connection. Id is the identifier provided by your external bus implementation. Hostname is mandatory because it is used to display user friendly peer name Mac addresses are mandatory because they are used to identify a peer that has been reinstalled (and has lost its previous uuid) """ self.uuid = uuid self.ident = ident self.hostname = hostname self.ip = ip self.port = port self.ssl = ssl self.macs = macs self.cleepdesktop = cleepdesktop self.online = False self.extra = extra def to_dict(self, with_extra=False): """ Return peer infos as dict Args: with_extra (bool): add extra data Returns: dict: peer infos """ out = { 'uuid': self.uuid, 'ident': self.ident, 'hostname': self.hostname, 'ip': self.ip, 'port': self.port, 'ssl': self.ssl, 'macs': self.macs, 'cleepdesktop': self.cleepdesktop, 'online': self.online, 'extra': self.extra, } with_extra and out.update({'extra': self.extra}) return out def __str__(self): """ To string method Returns: string: peer infos as string """ return 'PeerInfos(uuid:%s, ident:%s, hostname:%s, ip:%s port:%s, ssl:%s, macs:%s, cleepdesktop:%s, online:%s, extra:%s)' % ( self.uuid, self.ident, self.hostname, self.ip, self.port, self.ssl, self.macs, self.cleepdesktop, self.online, self.extra, ) def fill_from_dict(self, peer_infos): """ Fill infos from dict Args: peer_infos (dict): peer informations """ if not isinstance(peer_infos, dict): raise Exception('Parameter "peer_infos" must be a dict') self.uuid = peer_infos.get('uuid', None) self.ident = peer_infos.get('ident', None) self.hostname = peer_infos.get('hostname', None) self.ip = peer_infos.get('ip', None) self.port = peer_infos.get('port', None) self.ssl = peer_infos.get('ssl', False) self.macs = peer_infos.get('macs', None) self.cleepdesktop = peer_infos.get('cleepdesktop', False) self.extra = copy.deepcopy(peer_infos.get('extra', {})) class MessageResponse(object): """ Object that holds message response A response is composed of: * an error flag: True if error, False otherwise * a message: a message about request * some data: data returned by the request """ def __init__(self, error=False, message='', data=None, broadcast=False): """ Constructor Args: error (bool): error flag (default False) message (string): response message (default empty string) data (any): response data (default None) broadcast (bool): response comes from broadcast (default False) """ self.error = error self.message = message self.data = data self.broadcast = broadcast def __str__(self): """ Stringify """ return 'MessageResponse(error:%r, message:"%s", data:%s, broadcast:%r)' % ( self.error, self.message, str(self.data), self.broadcast ) def to_dict(self): """ Return message response """ return {'error':self.error, 'message':self.message, 'data':self.data} def fill_from_response(self, response): """ Fill from other response Args: response (MessageResponse): message response instance """ if not isinstance(response, MessageResponse): raise Exception('Parameter "response" must be a MessageResponse instance') self.error = response.error self.message = response.message self.data = copy.deepcopy(response.data) self.broadcast = response.broadcast def fill_from_dict(self, response): """ Fill from dict Args: response (dict): response as dict """ if not isinstance(response, dict): raise Exception('Parameter "response" must be a dict') self.error = response.get('error', False) self.broadcast = response.get('broadcast', False) self.message = response.get('message', '') self.data = response.get('data', None) class MessageRequest(object): """ Object that holds message request A message request is composed of: * in case of a command: * a command name * command parameters * the command sender * in case of an event: * an event name * event parameters * propagate flag to say if event can be propagated out of the device * a device id * a startup flag that indicates this event was sent during cleep startup Attribute peer_infos is filled when message comes from oustide. This field must also be filled when message is intented to be sent to outside. Members: command (string): command name event (string): event name propagate (bool): True if event can be propagated out of the device [event only] params (dict): list of event or command parameters to (string): message module recipient sender (string): message sender [command only] device_id (string): internal virtual device identifier [event only] peer_infos (PeerInfos): peer informations. Must be filled if message comes from outside the device Note: A message cannot be a command and an event, priority to command if both are specified. """ def __init__(self, command=None, event=None, params={}, to=None): """ Constructor Args: command (string): request command event (string): request event params (dict): message parameter if any to (string): message recipient if any """ self.command = command self.event = event self.params = params self.to = to self.propagate = False self.sender = None self.device_id = None self.peer_infos = None self.command_uuid = None self.timeout = None def __str__(self): """ Stringify function """ if self.command: return 'MessageRequest(command:%s, params:%s, to:%s, sender:%s, device_id:%s, peer_infos:%s, command_uuid:%s, timeout:%s)' % ( self.command, str(self.params), self.to, self.sender, self.device_id, self.peer_infos.to_dict() if self.peer_infos else None, self.command_uuid, self.timeout, ) elif self.event: return 'MessageRequest(event:%s, propagate:%s, params:%s, to:%s, device_id:%s, peer_infos:%s, command_uuid:%s)' % ( self.event, self.propagate, str(self.params), self.to, self.device_id, self.peer_infos.to_dict() if self.peer_infos else None, self.command_uuid, ) return 'MessageRequest(Invalid message)' def is_broadcast(self): """ Return broadcast status Returns: bool: True if the request is broadcast """ return True if self.to is None else False def is_command(self): """ Return true if message is a command. If not it is an event Returns: bool: True if message is a command, otherwise it is an event """ return True if self.command else False def is_external_event(self): """ Return True if event comes from external device Returns: bool: True if event comes from external device """ return True if self.peer_infos is not None else False def to_dict(self, startup=False, external_sender=None): """ Convert message request to dict object Params: startup (bool): True if the message is startup message external_sender (string): specify module name that handles message from external bus Raise: InvalidMessage if message is not valid """ if self.command and not self.peer_infos: # internal command return { 'command': self.command, 'params': self.params, 'to': self.to, 'sender': self.sender, 'broadcast': self.is_broadcast(), } elif self.event and not self.peer_infos: # internal event return { 'event': self.event, 'to': self.to, 'params': self.params, 'startup': startup, 'device_id': self.device_id, 'sender': self.sender, } elif self.command and self.peer_infos: # external command return { 'command': self.command, 'params': self.params, 'to': self.to, 'sender': external_sender or self.sender, 'broadcast': self.is_broadcast(), 'peer_infos': self.peer_infos.to_dict(), 'command_uuid': self.command_uuid, 'timeout': self.timeout, } elif self.event and self.peer_infos: # external event return { 'event': self.event, 'params': self.params, 'startup': False, 'device_id': None, 'sender': external_sender or self.sender, 'peer_infos': self.peer_infos.to_dict(), 'command_uuid': self.command_uuid, } else: raise InvalidMessage() def fill_from_request(self, request): """ Fill instance from other request Args: request (MessageRequest): message request instance """ if not isinstance(request, MessageRequest): raise Exception('Parameter "request" must be a MessageRequest instance') self.command = request.command self.event = request.event self.propagate = request.propagate self.params = copy.deepcopy(request.params) self.to = request.to self.sender = request.sender self.device_id = request.device_id self.peer_infos = None self.command_uuid = request.command_uuid if request.peer_infos: self.peer_infos = PeerInfos() self.peer_infos.fill_from_dict(request.peer_infos.to_dict(True)) def fill_from_dict(self, request): """ Fill instance from other request Args: request (dict): message request infos """ if not isinstance(request, dict): raise Exception('Parameter "request" must be a dict') self.command = request.get('command', None) self.event = request.get('event', None) self.propagate = request.get('propagate', False) self.params = copy.deepcopy(request.get('params', {})) self.to = request.get('to', None) self.sender = request.get('sender', None) self.device_id = request.get('device_id', None) self.command_uuid = request.get('command_uuid', None) self.timeout = request.get('timeout', 5.0) self.peer_infos = None if request.get('peer_infos', None): self.peer_infos = PeerInfos() self.peer_infos.fill_from_dict(request.get('peer_infos'))

29.989669

138

0.559283

from core.exception import InvalidMessage import copy __all__ = ['CORE_MODULES', 'CATEGORIES', 'PeerInfos', 'ExecutionStep', 'MessageResponse', 'MessageRequest'] CORE_MODULES = [ 'system', 'update', 'audio', 'network', 'cleepbus', 'parameters' ] class CATEGORIES(object): APPLICATION = 'APPLICATION' MOBILE = 'MOBILE' DRIVER = 'DRIVER' HOMEAUTOMATION = 'HOMEAUTOMATION' MEDIA = 'MEDIA' SERVICE = 'SERVICE' ALL = ['APPLICATION', 'MOBILE', 'DRIVER', 'HOMEAUTOMATION', 'MEDIA', 'SERVICE'] class ExecutionStep(object): BOOT = 0 INIT = 1 CONFIG = 2 RUN = 3 STOP = 4 def __init__(self): self.step = self.BOOT class PeerInfos(): def __init__(self, uuid=None, ident=None, hostname=None, ip=None, port=80, ssl=False, macs=None, cleepdesktop=False, extra={}, ): self.uuid = uuid self.ident = ident self.hostname = hostname self.ip = ip self.port = port self.ssl = ssl self.macs = macs self.cleepdesktop = cleepdesktop self.online = False self.extra = extra def to_dict(self, with_extra=False): out = { 'uuid': self.uuid, 'ident': self.ident, 'hostname': self.hostname, 'ip': self.ip, 'port': self.port, 'ssl': self.ssl, 'macs': self.macs, 'cleepdesktop': self.cleepdesktop, 'online': self.online, 'extra': self.extra, } with_extra and out.update({'extra': self.extra}) return out def __str__(self): return 'PeerInfos(uuid:%s, ident:%s, hostname:%s, ip:%s port:%s, ssl:%s, macs:%s, cleepdesktop:%s, online:%s, extra:%s)' % ( self.uuid, self.ident, self.hostname, self.ip, self.port, self.ssl, self.macs, self.cleepdesktop, self.online, self.extra, ) def fill_from_dict(self, peer_infos): if not isinstance(peer_infos, dict): raise Exception('Parameter "peer_infos" must be a dict') self.uuid = peer_infos.get('uuid', None) self.ident = peer_infos.get('ident', None) self.hostname = peer_infos.get('hostname', None) self.ip = peer_infos.get('ip', None) self.port = peer_infos.get('port', None) self.ssl = peer_infos.get('ssl', False) self.macs = peer_infos.get('macs', None) self.cleepdesktop = peer_infos.get('cleepdesktop', False) self.extra = copy.deepcopy(peer_infos.get('extra', {})) class MessageResponse(object): def __init__(self, error=False, message='', data=None, broadcast=False): self.error = error self.message = message self.data = data self.broadcast = broadcast def __str__(self): return 'MessageResponse(error:%r, message:"%s", data:%s, broadcast:%r)' % ( self.error, self.message, str(self.data), self.broadcast ) def to_dict(self): return {'error':self.error, 'message':self.message, 'data':self.data} def fill_from_response(self, response): if not isinstance(response, MessageResponse): raise Exception('Parameter "response" must be a MessageResponse instance') self.error = response.error self.message = response.message self.data = copy.deepcopy(response.data) self.broadcast = response.broadcast def fill_from_dict(self, response): if not isinstance(response, dict): raise Exception('Parameter "response" must be a dict') self.error = response.get('error', False) self.broadcast = response.get('broadcast', False) self.message = response.get('message', '') self.data = response.get('data', None) class MessageRequest(object): def __init__(self, command=None, event=None, params={}, to=None): self.command = command self.event = event self.params = params self.to = to self.propagate = False self.sender = None self.device_id = None self.peer_infos = None self.command_uuid = None self.timeout = None def __str__(self): if self.command: return 'MessageRequest(command:%s, params:%s, to:%s, sender:%s, device_id:%s, peer_infos:%s, command_uuid:%s, timeout:%s)' % ( self.command, str(self.params), self.to, self.sender, self.device_id, self.peer_infos.to_dict() if self.peer_infos else None, self.command_uuid, self.timeout, ) elif self.event: return 'MessageRequest(event:%s, propagate:%s, params:%s, to:%s, device_id:%s, peer_infos:%s, command_uuid:%s)' % ( self.event, self.propagate, str(self.params), self.to, self.device_id, self.peer_infos.to_dict() if self.peer_infos else None, self.command_uuid, ) return 'MessageRequest(Invalid message)' def is_broadcast(self): return True if self.to is None else False def is_command(self): return True if self.command else False def is_external_event(self): return True if self.peer_infos is not None else False def to_dict(self, startup=False, external_sender=None): if self.command and not self.peer_infos: return { 'command': self.command, 'params': self.params, 'to': self.to, 'sender': self.sender, 'broadcast': self.is_broadcast(), } elif self.event and not self.peer_infos: return { 'event': self.event, 'to': self.to, 'params': self.params, 'startup': startup, 'device_id': self.device_id, 'sender': self.sender, } elif self.command and self.peer_infos: return { 'command': self.command, 'params': self.params, 'to': self.to, 'sender': external_sender or self.sender, 'broadcast': self.is_broadcast(), 'peer_infos': self.peer_infos.to_dict(), 'command_uuid': self.command_uuid, 'timeout': self.timeout, } elif self.event and self.peer_infos: return { 'event': self.event, 'params': self.params, 'startup': False, 'device_id': None, 'sender': external_sender or self.sender, 'peer_infos': self.peer_infos.to_dict(), 'command_uuid': self.command_uuid, } else: raise InvalidMessage() def fill_from_request(self, request): if not isinstance(request, MessageRequest): raise Exception('Parameter "request" must be a MessageRequest instance') self.command = request.command self.event = request.event self.propagate = request.propagate self.params = copy.deepcopy(request.params) self.to = request.to self.sender = request.sender self.device_id = request.device_id self.peer_infos = None self.command_uuid = request.command_uuid if request.peer_infos: self.peer_infos = PeerInfos() self.peer_infos.fill_from_dict(request.peer_infos.to_dict(True)) def fill_from_dict(self, request): if not isinstance(request, dict): raise Exception('Parameter "request" must be a dict') self.command = request.get('command', None) self.event = request.get('event', None) self.propagate = request.get('propagate', False) self.params = copy.deepcopy(request.get('params', {})) self.to = request.get('to', None) self.sender = request.get('sender', None) self.device_id = request.get('device_id', None) self.command_uuid = request.get('command_uuid', None) self.timeout = request.get('timeout', 5.0) self.peer_infos = None if request.get('peer_infos', None): self.peer_infos = PeerInfos() self.peer_infos.fill_from_dict(request.get('peer_infos'))

true

1c2fd346542e78afce69ecd41b77a94c70950c89

244

py

Python

catalog/bindings/csw/exception.py

NIVANorge/s-enda-playground

56ae0a8978f0ba8a5546330786c882c31e17757a

[ "Apache-2.0" ]

null

catalog/bindings/csw/exception.py

NIVANorge/s-enda-playground

56ae0a8978f0ba8a5546330786c882c31e17757a

[ "Apache-2.0" ]

null

catalog/bindings/csw/exception.py

NIVANorge/s-enda-playground

56ae0a8978f0ba8a5546330786c882c31e17757a

[ "Apache-2.0" ]

null

from dataclasses import dataclass from bindings.csw.exception_type import ExceptionType __NAMESPACE__ = "http://www.opengis.net/ows" @dataclass class Exception(ExceptionType): class Meta: namespace = "http://www.opengis.net/ows"

22.181818

53

0.758197

from dataclasses import dataclass from bindings.csw.exception_type import ExceptionType __NAMESPACE__ = "http://www.opengis.net/ows" @dataclass class Exception(ExceptionType): class Meta: namespace = "http://www.opengis.net/ows"

true

1c2fd3a10430ee151538db6ca511a9c5c6a5b7f2

36,429

py

Python

test.py

Miraclelwk/learn-notes

65ee8713a9477b6fe13ca93f787438f206fe6fd7

[ "MIT" ]

null

test.py

Miraclelwk/learn-notes

65ee8713a9477b6fe13ca93f787438f206fe6fd7

[ "MIT" ]

null

test.py

Miraclelwk/learn-notes

65ee8713a9477b6fe13ca93f787438f206fe6fd7

[ "MIT" ]

null

""" # 多行注释第一个注释第二个注释第三个注释 """ """ print("Hello,Python!!!") # 缩进不同导致代码报错 if True: print("1") print("true") else: print("0") print("false") # 数字过长使用分隔符 print(100_100_100) # 二进制表示 a = 0b10 print(a) # 浮点型不能直接计算，会得到一个不精确的结果 b = 0.1 + 0.2 print(b) # 引号指定字符串 s = 'Hello' print(s) # 不同引号之间才能嵌套 s = '子曰："学而时习之，不亦说乎"' print(s) # 三引号指定多行字符串 s = '''锄禾日当午，汗滴禾下土。谁知盘中餐，粒粒皆辛苦。''' print(s) # 转义符 s = '子曰:"学而时习之，\n不亦说乎"' print(s) # 格式化字符串 a = 123 print('a=',a) # 指定单个占位符 b = 'hello %s'%'孙悟空' print(b) # 指定多个占位符 c = 'hello %s 你好 %s'%('tom','孙悟空') print(c) # 指定占位符最小字符位数 d = 'hello %3s'%'abcde' print(d) # 占位不够最小字符数时空格补位 e = 'hello %5s'%'abc' print(e) # 占位字符数区间 f = 'hello %3.5s'%'abcdefg' print(f) # 指定占位符最大字符位数 g = 'hello %.3s'%'abcde' print(g) # %f指定小数的位数 h = 'hello %.3f'%123.45678 print(h) # 整数占位符 i = 'hello %d'%123.123 print(i) # 字符串嵌入变量 a = '123' b = '六儿' c = f'hello {a} {b}' print(f'c= {c}') print(f'a= {a}') # 练习：创建变量保存名字，使用四种方式输出，欢迎xxx光临 name = '李4' #拼串 print('欢迎'+name+'光临!') #多个参数 print('欢迎',name,'光临！') #占位符 print('欢迎%s光临!'%name) #格式化字符串 print(f'欢迎{name}光临!') #复制字符串 k = 'abc' k = k*20 print(k) #布尔值 a = True print('a = ',a) #布尔值属于整型 print(1+False) #空值 c = None print(c) #类型检查 a = 123 b = '123' #方式一 type(123) c = type(123) print(c) #方式二 d = type(a) print(d) #方式三 print(type(b)) # 直接查看值的type print(type(1)) print(type(1.5)) print(type(True)) print(type('hello')) print(type(None)) # 查找值的id id(123) # 变量与对象 a = 123 id(a) b = a id(b) #变量相互独立 a = 10 b = a print(b) a = 20 print(a,b) # 定义一个变量a的类型 a = True print('a = ',a) print('a的类型为',type(a)) # 重新赋值a a = 'True' # int(a) 若执行结果a仍为bool，不会产生影响 a = int(a) # 重新赋值a print('a = ',a) print('a的类型为',type(a)) # 需要字符串和其他类型拼串时 b = 123 print('hello',str(b)) # 加法运算符 a = 10 + 5 print('a =',a) # 计算 b = 'hello' + 'world' # 拼串 print('b =',b) # 除法运算符 a = 10 / 3 print('a = ',a) b =10 // 3 # 整除 print('b = ',b) #幂运算和开方 a = 2**3 print('a = ',a) b = 16**0.5 # 求开方 print('b = ',b) #取模 a = 10 % 5 print('a = ',a) b = 10 % 4 print('b = ',b) c = 10 % 3 print('c = ',c) d = 10 % 2 print('d = ',d) # 关系运算符 10 > 20 print(int('2') > int('11')) result = 'qqq' is not 'aaa' print('result = ',result) #非运算 a = True a = not a #对a进行非运算 b = 1 b = not b c = '' c = not c print('a = ',a) print('b = ',b) print('c = ',c) # 练习 # 布尔值逻辑运算 a = True a = not a b = None b = not b print('a = ',a) print('b = ',b) result = True and False print('result = ',result) result1 = True or False print('result1 = ',result1) #非布尔值逻辑运算 c = 10 c = not c print('c = ',c) d = 10 and 20 print('d = ',d) e = 'hello' and 'world' print('e = ',e) f = True or 'world' print('f = ',f) g = 'hello' or 123 print('g = ',g) # 非布尔值的逻辑运算 # True and True result1 = 1 and 2 # 2 # True and False result2 = 1 and 0 # 0 # False and True result3 = 0 and 1 # 0 # False and False result4 = 0 and None # 0 print('result1 = ',result1) print('result2 = ',result2) print('result3 = ',result3) print('result4 = ',result4) # True or True result5 = 1 or 2 # 1 # True or False result6 = 1 or 0 # 1 # False or True result7 = 0 or 1 # 1 # False or False result8 = 0 or None # None print('result5 = ',result5) print('result6 = ',result6) print('result7 = ',result7) print('result8 = ',result8) # 比较两个值的大小 a = 10 b = 20 print('a大') if a > b else print('b大') c = 66 d = 38 max = c if c > d else d print('max = ',max) # 练习 # 三个值的最大值 a = 100 b = 200 c = 300 mid = a if a > b else b max = mid if mid > c else c print('三者中最大值是',max) # 运算符可以用括号控制优先级 a = 1 or 2 and 3 b = (1 or 2) and 3 print(a,b) # 条件判断语句 num = 20 if num > 10 : print('num比10大') # if 后面跟代码块 if True : print('123456') print('789') print('abc') print('hello') # 练习：在命令行让用户输入一个用户名，获取用户输入，并进行判断：如果用户输入的用户名是admin，则显示欢迎管理员光临；如果用户输入的是其他用户名，则什么也不做。 str_input = input('\n\n请输入用户名:') if str_input == 'admin': print('欢迎管理员光临') # input（）函数 a = input() print('用户输入的内容是：',a) input('请输入用户名：') # 练习：用户输入一个年龄，如果年龄大于18岁，则显示你已经成年了。 # age = input('请输入用户的年龄：') # age = int(age) # age是字符串不能直接和数字比较,也可以用下面语句： age = int(input('请输入用户的年龄：')) if age >= 18: print('你已经成年了~~~') # if-else username = input('输入用户名：') if username == 'admin': print('欢迎管理员光临！') else : print('欢迎用户光临！') # if-elif-else age = int(input('输入年龄：')) if age <= 20: print('青年') elif age <= 30: print('青年') elif age <= 60: print('老年') else: print('小孩') # if语句练习 1.获取用户输入的整数，判断数字的奇偶性 num = int(input('输入一个整数:')) if num % 2 == 1: print('这个数是奇数') else: print('这个数是偶数') # 2.编写一个程序判断年份是否为闰年。如果年份可以不能被100整除或者可以被400整除，那么年份为闰年 year = int(input('输入年份判断是否为闰年：')) if year % 100 != 0 or year % 400 == 0: print('闰年') else: print('平年') # 3.狗的前两年每一年相当于人的10.5岁，之后每增加一年就增加4岁。编写一个程序，获取用户输入的狗的年龄，显示其相当于人类的年龄。 dog_age = int(input('输入狗的年龄：')) if dog_age < 0: if dog_age <= 2: print('狗的年龄相当于人的：', dog_age * 10.5,'岁') else: print('狗的年龄相当于人的：', (dog_age - 2) * 4 + 21, '岁') else: print(请输入合法的数字：) 4.从键盘输入小明的期末成绩：当成绩为10时，’奖励一辆BMW‘；当成绩为[80-99]时，’奖励一台iphone‘；当成绩为[60-79]时，’奖励一本参考书‘；其他时什么奖励都没有 def customFun(): acheviementReport = int(input('请输入你的成绩:\n')) if acheviementReport==10: print('奖励一辆BMW') elif 80 <= acheviementReport <= 90: print('奖励一台iphone') elif 60 <= acheviementReport < 80: print('奖励一本参考书') else: print("什么都没有") customFun() customFun() # 5.女方家长嫁女儿的条件：高：180cm以上；富：1000以上；帅：500以上； # 如果三个条件同时满足，则'我一定要嫁给他'； # 如果三个条件有为真的情况，则'嫁吧，比上不足比下有余' # 如果三个条件都不满足，则'不嫁' high = int(input('身高：\n')) price = int(input('请输入家产:\n')) handsome = int(input('请输入颜值:\n')) if high >= 180 and price >= 1000 and handsome >= 500: print('我一定要嫁给他！') elif high >= 180 or price >= 1000 or handsome >= 500: print('嫁吧，比上不足比下有余') else: print('不嫁') # while循环语句 i = 0 # 初始化表达式 while i < 10: # 初始化表达式 i += 1 # 更新表达式 print('hello') # while语句练习 # 1.求100以内所有的奇数之和 # 获取100内所有的数 i = 0 # 创建一个变量保存结果 result = 0 while i < 100: i += 1 if i % 2 == 1: result += i print('100内所有奇数之和为：', result) # 获取100以内所有的奇数 i = 1 while i < 100: print(i) i += 1 # 2.求100以内所有7的倍数之和以及个数 i = 0 num = 0 result = 0 while i < 100: i += 1 if i % 7 == 0: num += 1 result += i print('100以内所有7的倍数之和为：\n', result) print('100以内所有7的倍数的个数：\n', num) # 3.水仙花数是指一个n位数（n>=3），它的每个位上的数字的n次幂之和等于它本身 # （例如1**3 + 5**3 + 3**3 = 153）求1000以内所有的水仙花数 i = 100 while i < 1000: # 设a为i的百位数 a = i // 100 # 设b为i的十位数 b = i // 10 % 10 # b = i - a * 100 // 10 # 设c为i的个位数 c = i % 10 if a ** 3 + b ** 3 + c ** 3 == i: print(i) i += 1 # 4.获取用户输入的任意数，判断其是否为质数 i = 2 num = int(input('输入任意整数：')) flag = True while i < num: if num % i == 0: flag = False i += 1 if flag: print(num, '是质数') else: print(num, '不是质数') # 步骤： # 获取用户输入的任意数 num = int(input('输入任意整数：')) # 举例有可能成为9的因数的数- 2、3、4、5、6、7、8 # 获取所有可能整除num的整数 # i = 2 # 不包含1 # flag = True # 传递判断结果 # while i < num: # 不包含自身 # # 判断num能否被i整除 # # if num % i != 0: i还没递增，num不能被一个i整除，不能判断为质数 # # 逆向思维num能被i整除，num不是质数 # if num % i == 0: # flag = False # num不是质数则结果输出为False # i += 1 # 循环嵌套练习 # 1.打印99乘法表 i = 0 while i < 9: j = 0 while j < i + 1: a = i + 1 b = j + 1 c = a * b print(a, '*', b, '=', c, '', end='') j += 1 print('') i += 1 i = 0 while i < 9: j = 0 while j < i + 1: print('*', end='') j += 1 print('') i += 1 # 2.求100以内所有质数 i = 2 # j = 2 # j没有放进循环不会重置，j应从2开始 # result = True #result没有放进循环不会重置，result应该默认为True开始 while i <= 100: j = 2 result = True while j < i: if i % j == 0: result = False j += 1 if result: print(i) i += 1 #创建循环求1-100 i = 2 while i <= 100: # print(i) # 创建一个变量，记录i的状态，默认i是质数 flag = True # 判断i是否质数 # 获取所有可能是i的因数 j = 2 while j < i: # 判断i能否被j整除 if i % j == 0: flag = False j += 1 # 验证结果并输出 if flag: print(i) i += 1 # 3.倒三角形 i = 0 while i < 9: j = 9 while j > i: print('*', end='') j -= 1 i += 1 print('') # break i = 0 while i < 5: if i == 3: break print(i) i += 1 else: print('hello') # continue i = 0 while i < 5: i += 1 if i == 3: continue print(i) else: print('hello') # 质数练习优化 from time import * begin = time() i = 2 while i <= 10000: j = 2 result = True # while j < i: while j <= i ** 0.5: if i % j == 0: result = False break j += 1 if result: # print(i) pass i += 1 end = time() print('程序执行花费了：', end - begin, '秒') # 综合练习 # 小游戏《唐僧大战白骨精》 # 1. 身份选择 # - 显示提示信息：欢迎来到《xxx》 # - 请选择你的身份：1. xxx 2. xxx # - 根据用户选择来分配身份（显示不同提示信息）：你已经选择唐僧，恭喜你将以唐僧的身份进行游戏！ # - 你居然选择白骨精，太不要脸了。系统已为你自动分配角色为唐僧 # - 选项错误，系统已自动为你分配角色为唐僧。 # # 2. 游戏进行 # - 显示玩家基本信息（攻击力、生命值） # - 显示玩家可以进行的操作（练级打boss 逃跑） # - 练级：提升玩家攻击力和生命值 # - 打boss：玩家攻击boss，boss反击，计算boss是否被玩家消灭，计算玩家是否已经被boss消灭。 # 身份选择 # 欢迎语 print('='*15, '欢迎来到20年前的小游戏', '='*15) # 游戏身份选择 identity = int(input('请选择你的身份：\n 1.唐僧\n 2.白骨精\n')) # 打印分割线 print('-'*50) if identity == 1: print('你已经选择->唐僧<-，恭喜你将以->唐僧<-的身份进行游戏！') elif identity == 2: print('你居然选择白骨精，太不要脸了。系统已为你自动分配角色为->唐僧<-') else: print(' 选项错误，系统已自动为你分配角色为唐僧。') # 进入游戏 # 显示玩家信息 # print('******当前角色是：唐僧\t 生命值：100\t 攻击力：20******') # 创建变量保存信息 # operation = int(input('请选择下一步操作:\n 1.练级\n 2.打boss\n 3.睡大觉')) play_life = 100 # 生命值 play_attack = 20 # 攻击力 play_grade = 1 # 等级 boss_life = 1000 boss_attack = 200 print('*' * 10, f'当前角色是：唐僧\t 生命值：{play_life}\t', f'攻击力：{play_attack}\t', f'等级： {play_grade}\t', '*' * 10) # 游戏选项需要反复出现，写到死循环中 while True: operation = int(input('请选择下一步操作:\n 1.练级\n 2.打boss\n 3.逃跑\n')) # 增加玩家生命值和攻击力 if operation == 1: play_life += 50 play_attack += 100 play_grade += 1 print('*'*20, '练级成功！当前等级为：', play_grade, '当前生命值为：', play_life, '当前攻击力为：', play_attack, '*'*20) # 玩家攻击boss，boss减去的生命值等于玩家攻击力 elif operation == 2: # 玩家攻击boss，boss减去的生命值等于玩家攻击力 boss_life -= play_attack print('->唐僧<- 攻击了 ->白骨精<-') # 检查玩家是否赢了,赢则游戏结束，没赢则受到反击 if boss_life <= 0: print(f'->白骨精<-受到了{play_attack}点伤害，打败boss，->唐僧<-赢得对局') break else: # boss反击，唐僧受到boss攻击力等额伤害 play_life -= boss_attack print(' ->白骨精<-攻击了->唐僧<- ') if play_life <= 0: print(f'->唐僧<-受到了{ boss_attack } 点伤害，挑战失败') break # 逃跑，退出游戏 elif operation == 3: print('->唐僧<-扭头撒腿就跑！game over') break else: break print('选项错误，退出游戏') # 字符串截取 a = 'hello world' print(a[0:6]) # 截取第一个到第六个字符：hello （空格也算） print(a[2:-2]) # 截取第三个到倒数第三个字符：hello wor print(a[0]) # 截取第一个字符：h print(a[1:]) # 截取第二个后的全部字符：ello world # 列表创建 list1 = ['如果可以作弊', '我会想你念你', 1, 2, 3] print(list1) list2 = ['我', '曾将', '青春', '翻涌', '成', '她'] print(list2[1]) # 曾将 print(list2[-1]) # 成 # 列表截取(切片) nums = [10, 20, 30, 40, 50, 60, 70, 80] print(nums[2:7]) # 30,40,50,60,70 print(nums[1:-2]) # 20,30,40,50,60 # 列表长度 nums = [10, 20, 30, 40, 50, 60, 70, 80] print('列表长度为： ', len(nums)) # 练习：在列表中保存5个名字，通过索引获取每个名字。 names = ['小a', '小b', '小c', '小d', '小e'] print(names[0]) print(names[1]) print(names[2]) print(names[-2]) print(names[-1]) # 列表单个元素修改 list3 = ['如果可以作弊', '我会想你念你', 1, 2, 3] list3[2] = '到最后的荼蘼' print(list3) # 列表切片修改 list3 = ['如果可以作弊', '我会想你念你', 1, 2, 3] list3[2:] = ['到最后的荼蘼','如果回忆容易', '我会想你念你'] print(list3) # 设置步长修改列表 list3 = [1, '如果可以作弊', 2, '我会想你念你', 3] list3[::2] = ['到最后的荼蘼', '如果回忆容易', '我会想你念你'] print(list3) # 列表添加和删除 list3 = ['如果可以作弊', '我会想你念你', 1, 2, 3] list3.append('到最后的荼蘼') del list3[3] print(list3) # 通过切片删除列表元素 casual_list = [1, 123, 213, 12321, 3242213, 223, 123, 423, 324, 32133] del casual_list[0:2] print(casual_list) del casual_list[::2] print(casual_list) # 列表拼接和重复 squares = [1, 2, 3] squares += [7, 8, 9] print(squares) print(squares * 3) # 列表函数&方法 # 函数 # in & not in casual_list = [1, 123, 213, 12321, 3242213] print(123 in casual_list) print('hello' not in casual_list) # len() & min() & max() casual_list = [1, 123, 213, 12321, 3242213] print(len(casual_list)) print(min(casual_list)) print(max(casual_list)) # 方法 # index（） casual_list = [1, 123, 213, 123, 3242213] print(casual_list.index(213)) print(casual_list.index(213, 1)) # 第二个参数表示查找的起始位置 print(casual_list.index(213, 1, 3)) # 第三个参数表示查找的终点位置 # count() casual_list = [1, 123, 213, 123, 3242213] print(casual_list.count(123)) print(casual_list.count(213)) print(casual_list.count(111)) # 列表的方法 # insert stus = ['孙悟空', '猪八戒', '牛魔王', '白骨精'] print('原列表：', stus) stus.insert(2, '唐僧') print('新列表：', stus) # extend stus = ['孙悟空', '猪八戒', '牛魔王', '白骨精'] print('原列表：', stus) stus.extend(['dddd', '唐僧']) print('新列表：', stus) # clear stus = ['孙悟空', '猪八戒', '牛魔王', '白骨精'] stus.clear() print(stus) # pop stus = ['孙悟空', '猪八戒', '牛魔王', '白骨精'] result = stus.pop(2) print('返回值：', result) # remove stus = ['孙悟空', '猪八戒', '牛魔王', '白骨精', '猪八戒'] stus.remove('猪八戒') print(stus) # reverse casual_list = [1, 123, 213, 12321, 3242213] casual_list.reverse() print(casual_list) # sort casual_list = [1, 123, 213, 12321, 3242213] casual_list.sort() print(casual_list) casual_list.sort(reverse=True) print(casual_list) # 遍历列表 # while循环 stus = ['孙悟空', '猪八戒', '牛魔王', '白骨精', '猪八戒'] i = 0 while i < 4: print(stus[i]) i += 1 # for循环 stus = ['孙悟空', '猪八戒', '牛魔王', '白骨精', '猪八戒'] for s in stus: print(s) # 嵌套列表 a = ['a', 'b', 'c'] n = [1, 2, 3] list = [a, n] print(list) # 索引子表 print(list[0]) # ['a', 'b', 'c'] # 索引子表的元素 print(list[0][1]) # b # 列表练习 # EMS（Employee Manager System 员工管理系统） # 显示系统欢迎信息 print('-'*20, '欢迎进入员工管理系统', '-'*20) # 创建列表,保存员工信息，字符串形式 emps = ['\t孙悟空\t16', '\t猪八戒\t15'] # 创建死循环 while True: # 显示用户选项 print('-' * 60) print('请选择你要进行的操作：') print('\t1.查询员工\t') print('\t2.添加员工\t') print('\t3.删除员工\t') print('\t4.退出\t') user_code = input('请选择1-4：\n') print('-'*60) if user_code == '1': # 查询员工 # 创建变量 print('\t序号\t\t姓名\t\t年龄') # 创建变量表示序号 n = 1 for emp in emps: print(f'\t{n}\t{emp}') n += 1 elif user_code == '2': # 添加员工 # 获取员工信息 emp_name = input('请输入员工姓名:') emp_age = input('请输入员工年龄:') emp = f'\t{emp_name}\t\t{emp_age}' print('-' * 60) # 提示 print('员工：', emp, '将被添加到系统中') user_confirm = input('是否继续添加[Y/N]：') print('-' * 60) if user_confirm == 'Y': emps.append(emp) print('插入成功') elif user_confirm == 'N': print('取消成功') pass # 删除员工 elif user_code == '3': del_num = int(input('请输入删除员工序号：')) if 0 < del_num <= len(emps): del_index = del_num - 1 else: print('输入有误') print('员工：', emps[del_index], '将被删除') print('\t序号\t姓名\t\t年龄') print(f'\t{del_num}\t{emps[del_index]}') user_confirm = input('是否继续删除[Y/N]：') if user_confirm == 'Y': del emps[del_index] print('删除成功') elif user_confirm == 'N': print('操作取消') pass elif user_code == '4': input('欢迎使用，点击回车键退出') break else: print('您的输入有误请重新输入') # range # 创建元组 tuple = ('Google', 'Runoob', 1997, 2000) tup1 = (1, 2, 3, 4, 5) tup2 = 3, 5, 6 # 不用小括号也可以 tup3 = () print(type(tuple)) print(type(tup1)) print(type(tup2)) print(tup1) print(tup2) print(tup3) # 元组只有单个元素，加逗号 tup1 = (50) tup2 = (50,) print(type(tup1)) print(type(tup2)) # 元组解包 # 利用解包交换变量的值 tup1 = (10, 20, 30, 40) a, b, c, d = tup1 print(a, b, c, d) a, b = b, a print(a, b) # 利用解包分配元素给相对位置的变量 tup1 = (10, 20, 30, 40, 50) a, b, *c = tup1 print(a, b, c) a, *b, c = tup1 print(a, b, c) *a, b, c = tup1 print(a, b, c) # 元组索引 tup1 = (10, 20, 30, 40, 50, 60) print(tup1[0]) # 10 print(tup1[1:5]) # (20, 30, 40 ,50) print(tup1[2:-1]) # ( 30, 40, 50) # 元组拼接 tup1 = ('a', 'b', 'c') tup2 = (1, 2, 3) tup3 = tup1 + tup2 print(tup3) # 元组的删除 tup1 = (1, 2, 3) del tup1 print(tup1) # 元组不可变 tup1 = (1, 2, 3) print(id(tup1)) tup1 = ('a', 'b', 'c') print(id(tup1)) # 创建字典 tinydict = {'a': 1, 'b': 2, 'c': 3} emptydict = {} print(tinydict) print(emptydict) print('length=', len(tinydict)) print('length=', len(emptydict)) print(type(tinydict)) # 访问字典 tinydict = {'Name': '大傻春', 'Age': 2, 'Class': '你要干什么'} print(tinydict['Name']) print(tinydict['Class']) # 字典新增、修改 tinydict = {'Name': '大傻春', 'Age': 2, 'Class': '你要干什么'} tinydict['Age'] = '你个大傻子' tinydict['Word'] = '滚就滚' print(tinydict['Word']) print(tinydict) # 删除字典元素 tinydict = {'Name': '大傻春', 'Age': 2, 'Class': '你要干什么', 'Word': '滚就滚'} del(tinydict['Age'], tinydict['Word']) print(tinydict) tinydict.clear() print(tinydict) # 删除一个字典 tinydict = {'a': 1, 'b': 2, 'c': 3} del tinydict print(tinydict) # 字典键不允许被赋值两次 tinydict = {'a': 1, 'b': 2, 'c': 3} tinydict['b'] = 30 print(tinydict) # 字典键不允许用可变的数据类型 tinydict = {[a]: 1, 'b': 2, 'c': 3} print(tinydict) # rang r = range(5) # 生成一个序列【0，1，2，3，4】 s = range(3, 10, 2) print(list(r)) print(list(s)) # 通过range可以创建一个指定次数的for循环 # for循环除了创建方式以外，其余和while一样，包括break、continue都可以在for循环中使用。 for i in range(30): print(i) # 可变对象 a = [1, 2, 3] print('修改前：', a, id(a)) # 通过索引改变对象[1,2,3]的值,不会改变变量所指向的对象 a[0] = 10 print('修改后：', a, id(a)) # 修改对象的值时，如果有其他变量也指向该对象，则修改也会在其他的变量中体现 a = [1, 2, 3] print('修改前：', a, id(a)) b = a a[0] = 10 print('修改后：', a, id(a)) print('修改后：', b, id(b)) # 为变量重新赋值，改变变量所指向的对象 a = [1, 2, 3] print('修改前：', a, id(a)) a = [4, 5, 6] print('修改后：', a, id(a)) # dict函数创建字典 d = dict(name='孙悟空', age='8') print(d, type(d)) # 双值子序列转换为字典 e = dict([('name', '孙悟饭'), ('age', 18)]) print(e, type(e)) # 获取字典的长度 d = dict(name='孙悟空', age='8') print(len(d)) # in & not in d = {'name': '孙悟空', 'age': 18} print('name' in d) # get(key,[default])获取指定键的值 e = dict([('name', '孙悟饭'), ('age', 18)]) print(d.get('name')) print(d.get('abc')) print(d.get('hello', '返回默认值')) print(d) # setdefault(key,[, default])添加字典的值 d = {'name': '孙悟空', 'age': 18} result = d.setdefault('name') result1 = d.setdefault('abc') result2 = d.setdefault('address', '花果山') print(result, result1, result2) print(d) # update() d = {'a': 1, 'b': 2, 'c': 3} d2 = {'d': 4, 'e': 5, 'f': 6, 'a': 8} d.update(d2) print(d) # popitem删除字典的键值对 d = {'a': 1, 'b': 2, 'c': 3} result = d.popitem() print(result) print(d) e = {} print(e.popitem()) # pop删除字典的键值对 d = {'a': 1, 'b': 2, 'c': 3} result1 = d.pop('c') result2 = d.pop('e', '返回默认值') print('result1=', result1) print('result2= ', result2) print(d) # copy()字典浅复制 d = {'a': 1, 'b': 2, 'c': 3, 'e': {'name': '孙悟空', 'age': 18}} d2 = d.copy() print(d, id(d)) print(d2, id(d2)) d2['e']['name'] = '猪八戒' # 修改可变对象时，原对象也会改变 print(d, id(d)) print(d2, id(d2)) # 字典遍历 # keys（） d = {'name': '孙悟空', 'age': 18, 'address': '花果山'} for k in d.keys(): print(k) # values() d = {'name': '孙悟空', 'age': 18, 'address': '花果山'} for v in d.values(): print(v) # items() d = {'name': '孙悟空', 'age': 18, 'address': '花果山'} for k, v in d.items(): print(k, '=', v) # 创建集合 s = {1, 2, 3, 4, 5, 6, 7, 8} print(s) p = {1, 1, 1, 1, 1, 2, 2, 2, 10, 20, 30} print(p) q = set('hello') # 字符串转换为集合 t = set({'a': 1, 'b': 2, 'c': 3}) # 字典转换为集合 print(q) print(t) # in & not in s = {1, 2, 3, 4, 5, 6, 7, 8} print(1 in s) print('hello' not in s) # len() s = {1, 2, 3, 4, 5, 6, 7, 8} print(len(s)) # 集合添加元素 # add（） s = {1, 2, 3, 4, 5, 6, 7, 8} s.add(10) print(s) # update（） s = {1, 2, 3, 4, 5, 6, 7, 8} s2 = set('hello') print(s) s.update((10, 20, 30)) print(s) s.update({'a': 1, 'b': 2, 'c': 3}) # update字典类型只会插入键 print(s) # 删除集合元素 # pop（） s = {1, 2, 3, 4, 5, 6, 7, 8} result = s.pop() print(result, s) # remove() s = {1, 2, 3, 4, 5, 6, 7, 8} s.remove(7) print(s) # clear() s = {1, 2, 3, 4, 5, 6, 7, 8} s.clear() print(s) # copy() s = {1, 2, 3, 4, 5, 6, 7, 8} s2 = s.copy() print(s, id(s)) print(s2, id(s2)) # 集合的运算 s1 = {1, 2, 3, 4, 5} s2 = {3, 4, 5, 6, 7, 8, 9} # & 交集运算 result1 = s1 & s2 print(result1) # | 并集运算 s1 = {1, 2, 3, 4, 5} s2 = {3, 4, 5, 6, 7, 8, 9} result2 = s1 | s2 print(result2) # - 差集运算 s1 = {1, 2, 3, 4, 5} s2 = {3, 4, 5, 6, 7, 8, 9} result3 = s1 - s2 print(result3) # ^ 异或集运算 s1 = {1, 2, 3, 4, 5} s2 = {3, 4, 5, 6, 7, 8, 9} result4 = s1 ^ s2 print(result4) # <= 检查一个集合是否为另一个的子集 s1 = {1, 2, 3} s2 = {1, 2, 3, 4, 5, 6} result = s1 <= s2 print(result) # < 检查一个集合是否为另一个的真子集 s1 = {1, 2, 3} s2 = {1, 2, 3, 4, 5, 6} result = s1 <= s2 print(result) # >= 检查一个集合是否为另一个的超集 s1 = {1, 2, 3} s2 = {1, 2, 3} s3 = {123, 213} result1 = s1 >= s2 result2 = s1 >= s3 print('result1=', result1) print('result2=', result2) # > 检查一个集合是否为另一个的真超集 s1 = {1, 2, 3} s2 = {1, 2, 3} s3 = {1, 2} result1 = s1 > s2 result2 = s1 > s3 print('result1=', result1) print('result2=', result2) # 函数 # 定义函数 def fun(): print('这是我的第一个函数') print('hello') print('world') fun() print(type(fun)) print(id(fun)) # 函数的参数 def add_sum(a, b): # 形参相当于在函数内写上：a = None b = None print(a, '+', b, '=', a+b) add_sum(10, 20) add_sum(123, 233) add_sum(12, 21) # 定义函数练习1：定义一个函数，可以用来求任意三个数的乘积 def product(a, b, c): print(a, '*', b, '*', c, '=', a*b*c) product(10, 20, 30) product(123, 345, 789) # 定义函数练习2：定义一个函数，可以根据不同的用户名显示不同的欢迎信息 def welcome(a): print('欢迎', a, '光临') welcome('孙悟空') # 实参的类型 def fn(): print('这是我的第一个函数') print('hello') print('world') def fn2(a): print('a = ', a) b = 123 c = True d = 'hello' e = [1, 2, 3] fn2(b) fn2(c) fn2(d) fn2(e) fn2(fn) # 形参重新赋值对其他变量不产生影响 def fn3(a): a = 20 print('a = ', a) c = 10 fn3(c) print('c = ', c) # 修改形参指向的对象会对其他变量产生影响 def fn4(a): a[0] = 10 print('a = ', a, id(a)) c = [1, 2, 3] fn4(c) print('c = ', c, id(c)) # 不定长参数 def fn(*a): print('a= ', a, type(a)) fn(123, 213, 323) # 定义一个函数可以令任意数字相加 def fun(*nums): result = 0 for n in nums: result += n print('sum=', result) fun(123456, 123, 123123, 123123, 12) # 可变参数的使用 def fn(a, b, *c): print('a= ', a) print('b= ', b) print('c= ', c) fn(1, 2, 3, 4, 5) # 可变参数后的参数必须关键字传参 def fn2(a, *b, c): print('a= ', a) print('b= ', b) print('c= ', c) fn2(1, 2, 3, 4, 5, c=6) # 全部参数以关键字传参 def fn2(*, a, b, c): print('a= ', a) print('b= ', b) print('c= ', c) fn2(a=1, b=2, c=3) # **形参 def fn2(b, c, **a): print('a= ', a, type(a)) print('b= ', b) print('c= ', c) fn2(b=2, c=3, d=1, e=5, f=6) # 参数解包 # 对序列解包 def fn2(a, b, c): print('a= ', a) print('b= ', b) print('c= ', c) # 创建一个元组或者列表 t = (1, 2, 3) # 传统方式传参： fn2(t[0], t[1], t[2]) fn2(*t) # 对字典解包 def fn2(a, b, c): print('a= ', a) print('b= ', b) print('c= ', c) # 创建一个字典 t = {'a': 1, 'b': 2, 'c': 3} # 传统方式传参： fn2(t[0], t[1], t[2]) fn2(**t) # 返回值 def fn(): def fn2(): print('hello world') return fn2() # return 100 # return 'hello' # return [1,2,3] fn() print(fn()) def fun(*nums): result = 0 for n in nums: result += n return result r = fun(123, 123) print(r) # 函数后加不加（）的区别 def fn5(): return 10 print(fn5) print(fn5()) # 文档字符串 # help()函数 help(print) # 文档字符串 def fn(): ''' 这是一个文档字符串的示例函数的作用:..... 函数的参数： a:作用，类型，默认值...... b:作用，类型，默认值...... c:作用，类型，默认值...... ''' return 10 # 说明参数和返回值类型 def fn(a: int, b: bool, c: str = 10) -> int: # 此处说明参数a为int，b为bool，c为str，返回值为int return 10 # 作用域 # 全局作用域 b = 20 def fn(): a = 10 print('函数内a：', a) print('函数外b:', b) fn() # 函数作用域 a = 20 def fn(): a = 10 print('函数内a：', a) fn() print('函数外a：', a) # 变量的查找 a = 10 def fn(): global a a = 20 print('修改后的a:', a) fn() print('全局变量的a：', a) # 命名空间 scope = locals() # 获得当前命名空间 print(scope, type(scope)) # 返回一个字典 scope['c'] = 10 # 向字典中添加一个key-value相当于创建一个全局变量（一般不建议这么做） print('c=', c) def fn(): a = 10 scope = locals() # 获得当前函数命名空间 print(scope, type(scope)) # 返回一个字典 scope['b'] = 20 # 通过操作函数的命名空间（一般不建议这么做） print('b = ', b) fn() # globals（）查看全局命名空间 b = 10 def fn(): global_scope = globals() # 获得全局命名空间 print(global_scope) # 查看全局命名空间 global_scope['b'] = 20 # 修改全局变量 print('b = ', b) fn() print('函数外b：', b) # 递归 # 创建一个函数求10！ def factorial(): n = 10 for i in range(1, 10): n = n * i print(n) factorial() # 创建一个函数求任意数的阶乘 def factorial2(n): ''' 这是一个求任意数阶乘的函数参数 n：求阶乘的数字 ''' # 创建一个变量保存结果 result = n for i in range(1, n): result = result * i return result print(n, '的阶乘为：', result) factorial2(5) # 递归例子：求任意数的阶乘 # 10! = 10 *9! # 9! = 9 * 8! # 8! = 8 *7! ... # 1!= 1 def factorial2(n): ''' 这是一个求任意数阶乘的函数参数 n：求阶乘的数字 ''' # 基线条件：判断n是否为1，如果为1则不再继续 if n == 1: # 1的阶乘就是1，直接返回1 return 1 # 递归条件 return n*(n-1) return n * factorial2(n-1) print(factorial2(10)) # 递归练习 # 练习1：创建一个函数power来求任意数字做幂运算 n ** i def power(n, i): ''' 这是一个power函数，为任意函数做幂运算参数 n：幂运算数字 i:幂运算次数 ''' # 基线条件：1次幂 if i == 1: return n # 递归条件 return n * power(n, i-1) # print(n, '的', i, '次幂为：', power(10, 3)) print(power(10, 3)) # 练习2:创建一个函数，用来检查一个任意字符串是否是回文字符串，如果是返回True，否则返回False def pal(pal_str): ''' 该函数用来检查字符串是否为回文字符串，是返回True，否返回False ''' # abcdedcba # 先判断第一个和最后一个字符是否相等，如果相等判断bcdedcb是否回文 # 判断bcdedcb是否回文 # 判断cdedc是否回文 # 判断ded是否回文 # 判断e是否回文 # 基线条件：字符串的长度小于2是回文字符串 # 字符串第一个不等于最后一个不是回文字符串 if len(pal_str) < 2: return True elif pal_str[0] != pal_str[-1]: return False # 递归条件 return pal(pal_str[1:-1]) print(pal('abcdedcba')) # 高阶函数 l1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] l2 = [] def fn2(i): if i % 2 == 0: return True return False def fn(func, lst): ''' 该函数用于将指定的元素输出到新的列表中参数 lst：用来保存新表 ''' for n in lst: if func(n): l2.append(n) return l2 print(fn(fn2, l1)) # 匿名函数 # filter l1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] l2 = [] def fn2(i): if i % 2 == 0: return True return False def fn(func, lst): ''' 该函数用于将指定的元素输出到新的列表中参数 lst：用来保存新表 ''' for n in lst: if func(n): l2.append(n) return l2 r = filter(fn2, l1) print(list(r)) # def fn(a, b): # return a+b # 等价于: lambda a, b: a + b print(lambda a, b: a + b) print((lambda a, b: a + b)(10, 20)) l1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] l2 = [] # 匿名函数 def fn(func, lst): ''' 该函数用于将指定的元素输出到新的列表中参数 lst：用来保存新表 ''' for n in lst: if func(n): l2.append(n) return l2 r = filter(lambda i: i % 2 == 0, l1) print(list(r)) # map（） l1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] r = map(lambda i: i + 1, l1) print(r) print(list(r)) # sort()方法 l3 = ['kkk', 'cc', 'aa', 'hhh'] l3.sort() print(l3) l3 = ['kkk', 'c', 'aa', 'hhhhh'] l3.sort(key=len) print(l3) l3 = [5, '1', 3, 8, 6] l3.sort(key=int) print(l3) # 闭包 a = 20 def fn(): # 在函数内部定义一个变量 a = 10 # 在函数fn（）内部定义一个函数fn2（） def fn2(): print('我是fn2', a) # 将函数fn2（）作为返回值返回 return fn2() # r是调用fn（）后返回的函数，在函数内部定义，并不是全局函数 # 因此外部无法访问到函数fn（）内部的变量，r能访问到内部变量 r = fn() r print(a) # 求平均值 nums = [] # 创建一个函数来计算平均值 def averager(n): # 将n添加到列表中 nums.append(n) # 计算平均值 return sum(nums)/len(nums) print(averager(10)) print(averager(20)) print(averager(30)) # 平均数优化 def make_averager(): nums = [] # 创建一个函数来计算平均值 def averager(n): # 将n添加到列表中 nums.append(n) # 计算平均值 return sum(nums)/len(nums) return averager averager = make_averager() print(averager(10)) print(averager(20)) print(averager(20)) print(averager(20)) # 装饰器引入 # 新需求：在函数执行前后增加提示 # 直接修改原函数较为麻烦且违反ocp原则 def add(a, b): ''' 求两个数的和 ''' r = a + b return r def mul(a , b): ''' 求两个数的乘积 ''' r = a * b return r # 可根据现有函数创建一个新的函数 def new_add(a, b): print('加法开始计算~~~') c = add(a, b) print('加法计算完成~~~') return c r = new_add(10, 20) print(r) # 装饰器使用 def begin_end(old): ''' 用来对其他函数进行扩展参数： old 要扩展的函数对象 ''' # 创建一个新的函数，扩展被调用的函数 # 参数采用不定长参数，可以根据被调用函数的参数数量自动接收 def new_function(*args, **kwargs): print('程序开始执行') # 调用被扩展的函数 result = old(*args, **kwargs) print('程序执行完毕') # 返回函数的执行结果 return result # 返回新函数 return new_function f1 = begin_end(add) f2 = begin_end(mul) r = f1(2, 3) p = f2(5, 6) print(r) print(p) def fn3(old): ''' 用来对其他函数进行扩展参数： old 要扩展的函数对象 ''' # 创建一个新的函数，扩展被调用的函数 # 参数采用不定长参数，可以根据被调用函数的参数数量自动接收 def new_function(*args, **kwargs): print('这里是fn3装饰器~~~') # 调用被扩展的函数 result = old(*args, **kwargs) print('这里是fn3装饰器~~~') # 返回函数的执行结果 return result # 返回新函数 return new_function @begin_end @fn3 def say_helllo(): print('hello') say_helllo() # 类与对象 # 类 class MyClass: pass print(MyClass) # 使用类来创建对象，就像调用一个函数 mc1 = MyClass() # mc就是通过MyClass创建的对象，也是MyClass的实例 mc2 = MyClass() mc3 = MyClass() print(mc1, type(mc1)) # 对象创建流程 class MyClass: pass mc = MyClass() mc.name = '孙悟空' # 对象属性赋值为“孙悟空” print(mc.name) # 输出对象属性与变量类似 # 类的定义 class Person: # 在类的代码块中，可以定义变量和函数 # 在类中所定义的变量，将会成为所有实例的公共属性，所有实例都可以访问这些变量 name = '孙悟空' # 公共属性，所有实例都可以访问 # 在类中定义的函数称为方法，这些方法可以通过该类所有实例来访问 def say_hello(a): print('你好') # 创建Person类的实例 p1 = Person() p2 = Person() print(p1.name) print(p2.name) # 方法和函数调用的区别： # 如果是函数调用，则调用时传几个参数，就会由几个实参； # 但如果是方法调用，默认传递一个参数，所以方法中至少要定义一个形参。 p1.say_hello() p2.say_hello() # 属性和方法 class Person: name = '孙悟空' def say_hello(a): print('你好') p1 = Person() p2 = Person() print(p1.name) # 孙悟空 # 修改p1的name属性 p1.name = '猪八戒' # 实例化对象p1中原来没有name属性，查找到类person中的name属性 # 修改p1name属性后，在对象p1的内存中添加name属性 print(p1.name) # 猪八戒 print(p2.name) # 孙悟空 # self class Person: name = '孙悟空' def say_hello(self): # say_hello()方法实现如下格式：你好，我是xxx # 在方法中不能直接调用类中的属性如：print('你好，我是%s'% name) # 第一个参数就是调用方法的对象本身 # 如果是p1调用，则第一个参数就是p1对象 # 如果是p2调用，则第一个参数就是p2对象 # 一般将这个参数命名为self。 print('你好,我是%s' % self.name) p1 = Person() p2 = Person() p1.name = '孙悟空' p2.name = '猪八戒' p1.say_hello() # 你好,我是孙悟空 p2.say_hello() # 你好,我是猪八戒 # 对象初始化 class Person: def say_hello(self): print('你好,我是%s' % self.name) # 目前来讲，对于Person类来说name属性是必须的，而且每个对象的name属性都是不同的 # 而现在是定义对象之后，手动将name属性添加到对象中，这种方式容易被忽略或出现错误 # 我们希望在创建对象时，必须设置name属性，如果不设置对象将无法创建 # 属性的创建应该是自动完成的，而不是创建对象后手动添加 def __init__(self, name): # 通过self向新建的对象中初始化属性 # 每调用一次init方法就会复制实例化对象一个name属性 self.name = name # 调用一个Person相当于调用init，传参到init中 p1 = Person('孙悟空') p2 = Person('猪八戒') p1.say_hello() p2.say_hello() # 练习：自定义一个表示狗的类（Dog） # 属性：name,age,gender,height # 方法：call(),bite(),run() class Dog: def __init__(self, name, age, gender, height): self.name = name self.age = age self.gender = gender self.height = height def call(self): print('狗在叫') def bite(self): print('狗在咬') def run(self): print('狗在跑') d1 = Dog('小5', 23, '男', 167) d1.call() d1.bite() d1.run() # 封装 class Dog: def __init__(self, name): # 没有一种方法可以完全隐藏属性，封装仅仅是将属性名设置为不常用的，防君子不防小人。 self.hidden_name = name def say_hello(self): print('hello, 这里是狗%s' % self.hidden_name) def get_name(self): ''' 函数用来获取属性 ''' # 获取属性的同时进行其他操作 print('用户属性已经被获取') return self.hidden_name def set_name(self, name): ''' 函数用来修改属性 ''' print('用户属性已经被修改') self.hidden_name = name d1 = Dog('小5') d1.say_hello() # getter和setter方法 class Person: def __init__(self, name): self._name = name # getter方法装饰器 @property def name(self): print('getter方法执行了') return self._name # setter方法装饰器: @属性名(???).setter # 属性名还是getter的方法名 @name.setter def set_name(self, name): print('setter方法执行了') self._name = name # 此处可将方法像属性一样调用：实例化对象.方法 p1 = Person('孙悟空') p1.set_name = '猪八戒' print(p1.name) # 继承 # 定义一个类Animal，这个类需要两个方法:run() sleep()、 class Animal: def run(self): print('动物会跑~~~') def sleep(self): print('动物会睡觉~~~') # 定义一个类Dog，这个类需要三个方法:run() sleep() bark() # 有一个类能实现大部分功能，但是不能实现全部功能 # 如何让这个类实现全部功能？ # 1.直接修改这个类，在这个类中添加需要的功能 --修改麻烦并且违反OCP原则 # 2.直接创建一个新的类 --创建比较麻烦，需要复制粘贴，会出现大量的重复性代码 # 3.直接从Animal类中继承属性和方法 class Dog(Animal): def bark(self): print('狗会嚎叫~~~') d = Dog() d.run() d.sleep() d.bark() # isinstance检查一个对象是否一个类的实例，如果这个类是这个对象的父类，也会返回True print(isinstance(d, Dog)) print(isinstance(d, Animal)) # 所有的对象都是object的实例 print(isinstance(d, object)) # 检查一个类是否为一个类的子类 print(issubclass(Dog, Animal)) print(issubclass(Dog, object)) print(issubclass(Animal, object)) print(issubclass(print, object)) # 方法的重写 class A(object): def AA(self): print('AAA') class B(A): def AA(self): print('bbb') class C(B): def AA(self): print('ccc') c = C() c.AA() # super() class Animal: def __init__(self, name): self._name = name @property def name(self): return self._name @name.setter def name(self, name): self._name = name def run(self): print('动物会跑~~~') def sleep(self): print('动物会睡觉~~~') # 父类中的所有方法都会被子类继承，包括特殊方法，也可以重写特殊方法。 class Dog(Animal): def __init__(self, name, age): # 希望可以直接调用父类的__init__来初始化父类中定义的属性 super().__init__(name) self._age = age @property def age(self): return self._age @age.setter def age(self, age): self._age = age d = Dog('小5', 23) print(d.name) print(d.age) # 多重继承 class A(object): def test(self): print('AAA') class B(object): def test2(self): print('BBB') class C(A, B): pass c = C() c.test() c.test2() print(A.__bases__) print(B.__bases__) print(C.__bases__) class A(object): def test(self): print('AAA') class B(object): def test2(self): print('BBB') class C(A, B): pass c = C() c.test() # 多重继承的复杂性 class A(object): def test(self): print('这是A的test方法') class B(object): def test(self): print('这是B的test方法') class C(A, B): pass c = C() c.test() # 多态 class A: def __init__(self, name): self._name = name @property def name(self): return self._name @name.setter def name(self, name): self._name = name class B: def __init__(self, name): self._name = name @property def name(self): return self._name @name.setter def name(self, name): self._name = name class C: pass a = A('孙悟空') b = B('猪八戒') # 对于函数say_hello（）来说，只要对象中含有name属性，就可以作为参数传递 # 这个函数不会考虑对象的类型，只要有name属性即可 def say_hello(obj): print('hello,我是%s' % obj.name) say_hello(a) say_hello(b) # 在say_hello2（）中做了一个类型检查，也就是只有obj是A类型的对象时，才可以正常使用 # 其他类型的对象都无法使用该函数，这个函数就违反了多态 # 违反了多态的函数，只适用于一种类型的对象，无法处理其他类型对象，这样导致函数的适应性非常差 def say_hello2(obj): # 类型检查 # 注意：像isinstance（）这种函数在开发中一般不会使用，因为这意味着函数可能违反了多态 if isinstance(obj, A): print('hello,我是%s' % obj.name) else: print('此类型对象无法使用该函数') say_hello2(a) say_hello2(b) # 类和方法总结 # 定义一个类 class A: # 类属性，直接在类中定义的属性是类属性 # 类属性可以通过类或类的实例化对象访问 # 但类属性只能通过类对象修改，无法通过实例化对象修改 count = 0 a = A() print(a.count) print(A.count) a.count = 100 A.count = 10 print(a.count) print(A.count) class B: # 实例属性，通过实例化对象添加的属性属于实例属性 # 实例属性只能通过实例对象来访问和修改，类对象无法访问修改 def __init__(self): self.name = '孙悟空' b = B() # print('B,', B.name) # 报错 print('b:', b.name) class C: # 实例方法：在类中定义，以第一个参数的方法都是实例方法 # 实例方法在调用时，Python会将调用对象作为self传入 # 实例方法可以通过实例和类调用。当通过实例调用时，会自动将当前对象作为self传入 # 当通过类调用时，不会自动传递self，此时需要手动传递self def test(self): print('这是test方法~~~') c = C() c.test() # 类调用方法时,需要手动传入实例化对象 C.test(c) # 等价于c.test() # 类方法 class D: @classmethod def test(cls): print('这是一个类方法~~~') print('类方法', cls) d = D() D.test() d.test() # 静态方法 class E: @staticmethod def test(): print('这是一个静态方法~~~') e = E() E.test() e.test() """

15.229515

105

0.556342

true

1c2fd423183c48e273f5b744cb621c5dd8b65e84

1,751

py

Python

NasAssesment/manage.py

siddshadab/Django_Assesment

a06ebf73bccd4e83b78391a1f70792cb5979ba8e

[ "MIT" ]

null

NasAssesment/manage.py

siddshadab/Django_Assesment

a06ebf73bccd4e83b78391a1f70792cb5979ba8e

[ "MIT" ]

null

NasAssesment/manage.py

siddshadab/Django_Assesment

a06ebf73bccd4e83b78391a1f70792cb5979ba8e

[ "MIT" ]

null

#!/usr/bin/env python """Django's command-line utility for administrative tasks.""" import os import sys import sqlite3 from sqlite3 import Error import environ from NasAssesment.settings import BASE_DIR def create_connection(db_file): conn = None try: conn = sqlite3.connect(db_file) except Error as e: print(e) return conn def update_task(conn,id): #insert if record not exist sql = 'INSERT INTO restApi_slotMaster (id) SELECT ' +str(id) + ' WHERE NOT EXISTS (SELECT * FROM restApi_slotMaster WHERE id ='+str(id)+');' print(id) print(sql) cur = conn.cursor() cur.execute(sql) conn.commit() def main(): """Run administrative tasks.""" database = BASE_DIR / 'db.sqlite3' print(database) os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'NasAssesment.settings') conn = create_connection(database) # Handle for first run env = environ.Env() env.read_env(env.str('BASE_DIR', '.env')) SLOT_NUMBER = env('SLOT_NUMBER') try: with conn: for x in range(int(SLOT_NUMBER)): #Take range from property file later update_task(conn,x + 1) except: print("An exception occurred On first Time Server Run") try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv) if __name__ == '__main__': main()

28.241935

144

0.632781

import os import sys import sqlite3 from sqlite3 import Error import environ from NasAssesment.settings import BASE_DIR def create_connection(db_file): conn = None try: conn = sqlite3.connect(db_file) except Error as e: print(e) return conn def update_task(conn,id): sql = 'INSERT INTO restApi_slotMaster (id) SELECT ' +str(id) + ' WHERE NOT EXISTS (SELECT * FROM restApi_slotMaster WHERE id ='+str(id)+');' print(id) print(sql) cur = conn.cursor() cur.execute(sql) conn.commit() def main(): database = BASE_DIR / 'db.sqlite3' print(database) os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'NasAssesment.settings') conn = create_connection(database) env = environ.Env() env.read_env(env.str('BASE_DIR', '.env')) SLOT_NUMBER = env('SLOT_NUMBER') try: with conn: for x in range(int(SLOT_NUMBER)): update_task(conn,x + 1) except: print("An exception occurred On first Time Server Run") try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv) if __name__ == '__main__': main()

true

1c2fd450d2aa0c4510a90e6e5a7df1a0957949f4

1,575

py

Python

tests/create_images.py

neurodata/ndex

c4d84e3be16de1ff53028d3bb1efd770790759af

[ "Apache-2.0" ]

4

2018-12-03T14:08:35.000Z

2020-07-24T06:19:10.000Z

tests/create_images.py

neurodata/ndex

c4d84e3be16de1ff53028d3bb1efd770790759af

[ "Apache-2.0" ]

null

tests/create_images.py

neurodata/ndex

c4d84e3be16de1ff53028d3bb1efd770790759af

[ "Apache-2.0" ]

null

import math import os import numpy as np import png import tifffile as tiff def create_img_file(x_size, y_size, dtype, file_format, img_fname, intensity_range=None): if intensity_range is None: bit_width = int(''.join(filter(str.isdigit, dtype))) else: bit_width = round(math.log(intensity_range, 2)) ar = np.random.randint( 1, 2**bit_width, size=(y_size, x_size), dtype=dtype) directory = os.path.dirname(img_fname) if not os.path.isdir(directory): os.makedirs(directory) if file_format == 'tif': tiff.imsave(img_fname, ar) elif file_format == 'png': with open(img_fname, 'wb') as f: writer = png.Writer(width=x_size, height=y_size, bitdepth=bit_width, greyscale=True) writer.write(f, ar.tolist()) def gen_images(ingest_job, intensity_range=None): for z in range(ingest_job.z_range[0], ingest_job.z_range[1], ingest_job.z_step): img_fname = ingest_job.get_img_fname(z) img_size = ingest_job.img_size if img_size is None: img_size = [ingest_job.x_extent[1], ingest_job.y_extent[1], ingest_job.z_extent[1]] create_img_file(img_size[0], img_size[1], ingest_job.datatype, ingest_job.extension, img_fname, intensity_range) def del_test_images(ingest_job): for z in range(ingest_job.z_range[0], ingest_job.z_range[1], ingest_job.z_step): img_fname = ingest_job.get_img_fname(z) os.remove(img_fname)

34.23913

89

0.641905

import math import os import numpy as np import png import tifffile as tiff def create_img_file(x_size, y_size, dtype, file_format, img_fname, intensity_range=None): if intensity_range is None: bit_width = int(''.join(filter(str.isdigit, dtype))) else: bit_width = round(math.log(intensity_range, 2)) ar = np.random.randint( 1, 2**bit_width, size=(y_size, x_size), dtype=dtype) directory = os.path.dirname(img_fname) if not os.path.isdir(directory): os.makedirs(directory) if file_format == 'tif': tiff.imsave(img_fname, ar) elif file_format == 'png': with open(img_fname, 'wb') as f: writer = png.Writer(width=x_size, height=y_size, bitdepth=bit_width, greyscale=True) writer.write(f, ar.tolist()) def gen_images(ingest_job, intensity_range=None): for z in range(ingest_job.z_range[0], ingest_job.z_range[1], ingest_job.z_step): img_fname = ingest_job.get_img_fname(z) img_size = ingest_job.img_size if img_size is None: img_size = [ingest_job.x_extent[1], ingest_job.y_extent[1], ingest_job.z_extent[1]] create_img_file(img_size[0], img_size[1], ingest_job.datatype, ingest_job.extension, img_fname, intensity_range) def del_test_images(ingest_job): for z in range(ingest_job.z_range[0], ingest_job.z_range[1], ingest_job.z_step): img_fname = ingest_job.get_img_fname(z) os.remove(img_fname)

true

1c2fd45f0ec11984bef0ea3fcbfb99c970afdb9e

11,684

py

Python

client/modules/Calendar.py

archeltaneka/jasper-finalproject

88151554f0ced1e7e8c592584ccfe1b79493b71f

[ "MIT" ]

3

2019-05-29T15:21:53.000Z

2022-01-19T12:48:47.000Z

client/modules/Calendar.py

archeltaneka/jasper-finalproject

88151554f0ced1e7e8c592584ccfe1b79493b71f

[ "MIT" ]

null

client/modules/Calendar.py

archeltaneka/jasper-finalproject

88151554f0ced1e7e8c592584ccfe1b79493b71f

[ "MIT" ]

2

2018-09-24T12:54:38.000Z

2018-10-02T15:04:39.000Z

import httplib2 import sys import datetime import re import gflags import calendar import jasperpath import logging import requests from client.app_utils import getTimezone from dateutil import tz from dateutil import parser from dateutil.relativedelta import relativedelta from apiclient.discovery import build from oauth2client.file import Storage from oauth2client.client import AccessTokenRefreshError from oauth2client.client import OAuth2WebServerFlow from oauth2client.tools import * logging.getLogger('googleapiclient.discovery_cache').setLevel(logging.ERROR) # Written by Marc Poul Joseph Laventure FLAGS = gflags.FLAGS WORDS = [ "Calendar", "Events", "Check", "My" ] # The scope URL for read/write access to a user's calendar data scope = 'https://www.googleapis.com/auth/calendar' if bool(re.search('--noauth_local_webserver', str(sys.argv), re.IGNORECASE)): argv = FLAGS(sys.argv[1]) def convertDateToGoogleStr(timezone, d): dateStr = timezone.normalize(timezone.localize(d)).astimezone(tz.tzutc()).isoformat('T') return dateStr def getStartOfDay( dayOfInterest ): return datetime.datetime(dayOfInterest.year, dayOfInterest.month, dayOfInterest.day ) def getEndOfDay(dayOfInterest): return getStartOfDay(dayOfInterest) + datetime.timedelta(days=1, minutes=-1 ) def convertGoogleDateStr( dateStr, tz ): date = parser.parse(dateStr) return date.astimezone( tz ) def addEvent(profile, mic, service): while True: try: mic.say("What would you like to add?") eventData = mic.activeListen() createdEvent = service.events().quickAdd(calendarId='primary', text=eventData).execute() mic.say("Added event " + createdEvent['summary'] + " on " + getReadableDateFromEvent(createdEvent, getTimezone(profile)) + " " + getReadableTimeFromEvent(createdEvent, getTimezone(profile))) # Create a variable for POST ev = createdEvent['summary'] dt = getReadableDateFromEvent(createdEvent, getTimezone(profile)) tm = getReadableTimeFromEvent(createdEvent, getTimezone(profile)) mic.say("Is this what you wanted?") if bool(re.search(r'\bYes\b', mic.activeListen(), re.IGNORECASE)): mic.say("Okay, it's on your calendar") # POST request for req here payload = {'user_id':3, 'event':ev, 'date':dt, 'time':tm} r = requests.post("http://178.128.62.29/api/schedule/createNew", params=payload) else: mic.say("My mistake, english is my second language.") service.events().delete(calendarId='primary', eventId=createdEvent['id']).execute() return except KeyError: mic.say("Could not add event to your calender; check if internet issue.") mic.say("Would you like to attempt again?") responseRedo = mic.activeListen() if bool(re.search(r'\bNo\b', responseRedo, re.IGNORECASE)): return #gets all events today def getEventsToday(profile, mic, service): tz = getTimezone(profile) d = datetime.datetime.now(tz=tz) getEventsOn(d, tz, mic, "today", service) #gets all events tomorrow def getEventsTomorrow(profile, mic, service): tz = getTimezone(profile) d = datetime.datetime.now(tz=tz) + datetime.timedelta(days=1) getEventsOn(d, tz, mic, "tomorrow", service) #gets all events on the provided next day of week (Monday, Tuesday, etc..) def getEventsOnNextDayOfWeek(profile, mic, dayOfWeekStr, service ): tz = getTimezone(profile) d = datetime.datetime.now(tz=tz) dayOfWeek = list(calendar.day_name).index(dayOfWeekStr) if ( dayOfWeek == d.weekday() ): timediff = datetime.timedelta(days=7) elif ( dayOfWeek <= d.weekday() ): timediff = datetime.timedelta(days=(7-dayOfWeek)) else: timediff = datetime.timedelta(days=(dayOfWeek-d.weekday())) getEventsOn(d+timediff, tz, mic, "next " + dayOfWeekStr, service) #gets all events on the provided day def getEventsOn( day, tz, mic, keyword, service ): events = queryEvents(convertDateToGoogleStr(tz, getStartOfDay(day)), convertDateToGoogleStr(tz, getEndOfDay(day)), service) if(len(events) == 0): mic.say( "You have no events scheduled for " + keyword ) return sep="" for event in events: eventTitle = getSummaryFromEvent(event) mic.say( sep + eventTitle + getReadableTimeFromEvent(event,tz) ) sep = "and " #gets all events in the next month that contain keywords def getEventsBySummary( profile, mic, keyWords, service ): tz = getTimezone(profile) today = getStartOfDay(datetime.datetime.now(tz=tz)) oneMonthFromToday = today + relativedelta(months=1) events = queryEvents(convertDateToGoogleStr(tz, today), convertDateToGoogleStr(tz, oneMonthFromToday), service, keyWords) if len(events) == 0: mic.say("You don't have any events like that") return sep="" for event in events: eventTitle = getSummaryFromEvent(event) mic.say( sep + " on " + getReadableDateFromEvent(event, tz) + " " + eventTitle + getReadableTimeFromEvent(event, tz) ) sep="and" #returns a readable title from Google event def getSummaryFromEvent(event): if 'summary' in event: return str(event['summary']) return "An Event" #returns a readable date phrase from Google event def getReadableDateFromEvent(event, tz): eventRawStartTime = event['start'] if "dateTime" in eventRawStartTime: date = convertGoogleDateStr(eventRawStartTime['dateTime'], tz) else: date = eventRawStartTime['date'].split("-") date = datetime.datetime(year=int(date[0]), month=int(date[1]), day=int(date[2]), tzinfo=tz) #if it's with 7 days, say the name of day if (date - datetime.datetime.now(tz=tz)).days <= 7: return " next " + calendar.day_name[date.weekday()] #else return Month, Day Number return calendar.month_name[date.month] + " " + str(date.day) #returns a readable time phrase from Google event def getReadableTimeFromEvent(event, tz): eventRawStartTime = event['start'] if "dateTime" in eventRawStartTime: date = convertGoogleDateStr(eventRawStartTime['dateTime'], tz) startMinute = ":" + str(date.minute) startHour = date.hour appendingTime = "am" if ((date.hour - 12) > 0 ): startHour = date.hour - 12 appendingTime = "pm" if date.minute == 0: startMinute = "" elif (date.minute < 10): startMinute = " OH " + str(date.minute) return " at " + str(startHour) + startMinute + " " + appendingTime return " all day" #querys google events, expecting start and end to be already converted to google format def queryEvents(start, end, service, keyWords=None, ): page_token = None myEvents = [] while True: # Gets events from primary calender from each page in present day boundaries if not keyWords: events = service.events().list(calendarId='primary', pageToken=page_token, timeMin=start, timeMax=end, singleEvents=True, orderBy="startTime").execute() else: events = service.events().list(calendarId='primary', pageToken=page_token, timeMin=start, timeMax=end, q=keyWords, singleEvents=True, orderBy="startTime").execute() myEvents.extend(events['items']) page_token = events.get('nextPageToken') if not page_token: break return myEvents def handle(text, mic, profile, recursive=False): print ("****") if not text and recursive: mic.say("Okay nevermind then") if bool(re.search(r'\b(Add|Create|Set)\b', text, re.IGNORECASE)): addEvent(profile,mic, getService(profile)) elif bool(re.search(r'\bToday\b', text, re.IGNORECASE)): getEventsToday(profile,mic, getService(profile)) elif bool(re.search(r'\bTomorrow\b', text, re.IGNORECASE)): getEventsTomorrow(profile,mic, getService(profile)) elif bool(re.search(r'\b(Monday|Tuesday|Wednesday|Thursday|Friday|Saturday|Sunday)\b', text, re.IGNORECASE)): for day in list(calendar.day_name): if ( re.search(r'\b%s\b' % day, text, re.IGNORECASE) ): getEventsOnNextDayOfWeek(profile, mic, day, getService(profile)) break; elif bool(re.search(r'\b(Search)\b', text, re.IGNORECASE)): if bool(re.search(r'\b(calendar for)\b', text, re.IGNORECASE)): text = str(text).lower().replace("search calendar for","") if len(str.strip(text)) > 0: mic.say("I am searching for " + text) getEventsBySummary( profile, mic, text, getService(profile) ) return mic.say("What events would you like to search for?") getEventsBySummary( profile, mic, mic.activeListen(), getService(profile) ) elif not recursive: mic.say("Did you want to do something with your calendar?") handle( mic.activeListen(), mic, profile, True ) else: mic.say("Okay nevermind then") def getService(profile): print ("TESTTEST") client_id = profile["google_calendar"]["id"] client_secret = profile["google_calendar"]["secret"] print ("TEST") # Create a flow object. This object holds the client_id, client_secret, and # scope. It assists with OAuth 2.0 steps to get user authorization and # credentials. flow = OAuth2WebServerFlow(client_id, client_secret, scope) # Create a Storage object. This object holds the credentials that your # application needs to authorize access to the user's data. The name of the # credentials file is provided. If the file does not exist, it is # created. This object can only hold credentials for a single user, so # as-written, this script can only handle a single user. print( jasperpath.config('calendar/credentials.dat') ) storage = Storage(jasperpath.config('calendar/credentials.dat')) # storage = Storage('credentials.dat') # The get() function returns the credentials for the Storage object. If no # credentials were found, None is returned. credentials = storage.get() # If no credentials are found or the credentials are invalid due to # expiration, new credentials need to be obtained from the authorization # server. The oauth2client.tools.run_flow() function attempts to open an # authorization server page in your default web browser. The server # asks the user to grant your application access to the user's data. # If the user grants access, the run_flow() function returns new credentials. # The new credentials are also stored in the supplied Storage object, # which updates the credentials.dat file. if credentials is None or credentials.invalid: credentials = run_flow(flow, storage) # Create an httplib2.Http object to handle our HTTP requests, and authorize it # using the credentials.authorize() function. http = httplib2.Http() http = credentials.authorize(http) # The apiclient.discovery.build() function returns an instance of an API service # object can be used to make API calls. The object is constructed with # methods specific to the calendar API. The arguments provided are: # name of the API ('calendar') # version of the API you are using ('v3') # authorized httplib2.Http() object that can be used for API calls return build('calendar', 'v3', http=http) def isValid(text): return bool(re.search(r'\bCalendar\b', text, re.IGNORECASE))

43.114391

176

0.676566

import httplib2 import sys import datetime import re import gflags import calendar import jasperpath import logging import requests from client.app_utils import getTimezone from dateutil import tz from dateutil import parser from dateutil.relativedelta import relativedelta from apiclient.discovery import build from oauth2client.file import Storage from oauth2client.client import AccessTokenRefreshError from oauth2client.client import OAuth2WebServerFlow from oauth2client.tools import * logging.getLogger('googleapiclient.discovery_cache').setLevel(logging.ERROR) FLAGS = gflags.FLAGS WORDS = [ "Calendar", "Events", "Check", "My" ] scope = 'https://www.googleapis.com/auth/calendar' if bool(re.search('--noauth_local_webserver', str(sys.argv), re.IGNORECASE)): argv = FLAGS(sys.argv[1]) def convertDateToGoogleStr(timezone, d): dateStr = timezone.normalize(timezone.localize(d)).astimezone(tz.tzutc()).isoformat('T') return dateStr def getStartOfDay( dayOfInterest ): return datetime.datetime(dayOfInterest.year, dayOfInterest.month, dayOfInterest.day ) def getEndOfDay(dayOfInterest): return getStartOfDay(dayOfInterest) + datetime.timedelta(days=1, minutes=-1 ) def convertGoogleDateStr( dateStr, tz ): date = parser.parse(dateStr) return date.astimezone( tz ) def addEvent(profile, mic, service): while True: try: mic.say("What would you like to add?") eventData = mic.activeListen() createdEvent = service.events().quickAdd(calendarId='primary', text=eventData).execute() mic.say("Added event " + createdEvent['summary'] + " on " + getReadableDateFromEvent(createdEvent, getTimezone(profile)) + " " + getReadableTimeFromEvent(createdEvent, getTimezone(profile))) # Create a variable for POST ev = createdEvent['summary'] dt = getReadableDateFromEvent(createdEvent, getTimezone(profile)) tm = getReadableTimeFromEvent(createdEvent, getTimezone(profile)) mic.say("Is this what you wanted?") if bool(re.search(r'\bYes\b', mic.activeListen(), re.IGNORECASE)): mic.say("Okay, it's on your calendar") payload = {'user_id':3, 'event':ev, 'date':dt, 'time':tm} r = requests.post("http://178.128.62.29/api/schedule/createNew", params=payload) else: mic.say("My mistake, english is my second language.") service.events().delete(calendarId='primary', eventId=createdEvent['id']).execute() return except KeyError: mic.say("Could not add event to your calender; check if internet issue.") mic.say("Would you like to attempt again?") responseRedo = mic.activeListen() if bool(re.search(r'\bNo\b', responseRedo, re.IGNORECASE)): return def getEventsToday(profile, mic, service): tz = getTimezone(profile) d = datetime.datetime.now(tz=tz) getEventsOn(d, tz, mic, "today", service) def getEventsTomorrow(profile, mic, service): tz = getTimezone(profile) d = datetime.datetime.now(tz=tz) + datetime.timedelta(days=1) getEventsOn(d, tz, mic, "tomorrow", service) def getEventsOnNextDayOfWeek(profile, mic, dayOfWeekStr, service ): tz = getTimezone(profile) d = datetime.datetime.now(tz=tz) dayOfWeek = list(calendar.day_name).index(dayOfWeekStr) if ( dayOfWeek == d.weekday() ): timediff = datetime.timedelta(days=7) elif ( dayOfWeek <= d.weekday() ): timediff = datetime.timedelta(days=(7-dayOfWeek)) else: timediff = datetime.timedelta(days=(dayOfWeek-d.weekday())) getEventsOn(d+timediff, tz, mic, "next " + dayOfWeekStr, service) def getEventsOn( day, tz, mic, keyword, service ): events = queryEvents(convertDateToGoogleStr(tz, getStartOfDay(day)), convertDateToGoogleStr(tz, getEndOfDay(day)), service) if(len(events) == 0): mic.say( "You have no events scheduled for " + keyword ) return sep="" for event in events: eventTitle = getSummaryFromEvent(event) mic.say( sep + eventTitle + getReadableTimeFromEvent(event,tz) ) sep = "and " def getEventsBySummary( profile, mic, keyWords, service ): tz = getTimezone(profile) today = getStartOfDay(datetime.datetime.now(tz=tz)) oneMonthFromToday = today + relativedelta(months=1) events = queryEvents(convertDateToGoogleStr(tz, today), convertDateToGoogleStr(tz, oneMonthFromToday), service, keyWords) if len(events) == 0: mic.say("You don't have any events like that") return sep="" for event in events: eventTitle = getSummaryFromEvent(event) mic.say( sep + " on " + getReadableDateFromEvent(event, tz) + " " + eventTitle + getReadableTimeFromEvent(event, tz) ) sep="and" #returns a readable title from Google event def getSummaryFromEvent(event): if 'summary' in event: return str(event['summary']) return "An Event" #returns a readable date phrase from Google event def getReadableDateFromEvent(event, tz): eventRawStartTime = event['start'] if "dateTime" in eventRawStartTime: date = convertGoogleDateStr(eventRawStartTime['dateTime'], tz) else: date = eventRawStartTime['date'].split("-") date = datetime.datetime(year=int(date[0]), month=int(date[1]), day=int(date[2]), tzinfo=tz) #if it's with 7 days, say the name of day if (date - datetime.datetime.now(tz=tz)).days <= 7: return " next " + calendar.day_name[date.weekday()] return calendar.month_name[date.month] + " " + str(date.day) def getReadableTimeFromEvent(event, tz): eventRawStartTime = event['start'] if "dateTime" in eventRawStartTime: date = convertGoogleDateStr(eventRawStartTime['dateTime'], tz) startMinute = ":" + str(date.minute) startHour = date.hour appendingTime = "am" if ((date.hour - 12) > 0 ): startHour = date.hour - 12 appendingTime = "pm" if date.minute == 0: startMinute = "" elif (date.minute < 10): startMinute = " OH " + str(date.minute) return " at " + str(startHour) + startMinute + " " + appendingTime return " all day" def queryEvents(start, end, service, keyWords=None, ): page_token = None myEvents = [] while True: if not keyWords: events = service.events().list(calendarId='primary', pageToken=page_token, timeMin=start, timeMax=end, singleEvents=True, orderBy="startTime").execute() else: events = service.events().list(calendarId='primary', pageToken=page_token, timeMin=start, timeMax=end, q=keyWords, singleEvents=True, orderBy="startTime").execute() myEvents.extend(events['items']) page_token = events.get('nextPageToken') if not page_token: break return myEvents def handle(text, mic, profile, recursive=False): print ("****") if not text and recursive: mic.say("Okay nevermind then") if bool(re.search(r'\b(Add|Create|Set)\b', text, re.IGNORECASE)): addEvent(profile,mic, getService(profile)) elif bool(re.search(r'\bToday\b', text, re.IGNORECASE)): getEventsToday(profile,mic, getService(profile)) elif bool(re.search(r'\bTomorrow\b', text, re.IGNORECASE)): getEventsTomorrow(profile,mic, getService(profile)) elif bool(re.search(r'\b(Monday|Tuesday|Wednesday|Thursday|Friday|Saturday|Sunday)\b', text, re.IGNORECASE)): for day in list(calendar.day_name): if ( re.search(r'\b%s\b' % day, text, re.IGNORECASE) ): getEventsOnNextDayOfWeek(profile, mic, day, getService(profile)) break; elif bool(re.search(r'\b(Search)\b', text, re.IGNORECASE)): if bool(re.search(r'\b(calendar for)\b', text, re.IGNORECASE)): text = str(text).lower().replace("search calendar for","") if len(str.strip(text)) > 0: mic.say("I am searching for " + text) getEventsBySummary( profile, mic, text, getService(profile) ) return mic.say("What events would you like to search for?") getEventsBySummary( profile, mic, mic.activeListen(), getService(profile) ) elif not recursive: mic.say("Did you want to do something with your calendar?") handle( mic.activeListen(), mic, profile, True ) else: mic.say("Okay nevermind then") def getService(profile): print ("TESTTEST") client_id = profile["google_calendar"]["id"] client_secret = profile["google_calendar"]["secret"] print ("TEST") flow = OAuth2WebServerFlow(client_id, client_secret, scope) # credentials file is provided. If the file does not exist, it is # created. This object can only hold credentials for a single user, so # as-written, this script can only handle a single user. print( jasperpath.config('calendar/credentials.dat') ) storage = Storage(jasperpath.config('calendar/credentials.dat')) # storage = Storage('credentials.dat') # The get() function returns the credentials for the Storage object. If no # credentials were found, None is returned. credentials = storage.get() # If no credentials are found or the credentials are invalid due to # expiration, new credentials need to be obtained from the authorization # server. The oauth2client.tools.run_flow() function attempts to open an # authorization server page in your default web browser. The server # asks the user to grant your application access to the user's data. if credentials is None or credentials.invalid: credentials = run_flow(flow, storage) http = httplib2.Http() http = credentials.authorize(http) return build('calendar', 'v3', http=http) def isValid(text): return bool(re.search(r'\bCalendar\b', text, re.IGNORECASE))

true

1c2fd5f5966cf7d51a1860d24e47594d7de8d44f

6,104

py

Python

tests/unit/modules/test_drbd.py

ifraixedes/saltstack-salt

b54becb8b43cc9b7c00b2c0bc637ac534dc62896

[ "Apache-2.0" ]

9,425

2015-01-01T05:59:24.000Z

2022-03-31T20:44:05.000Z

tests/unit/modules/test_drbd.py

ifraixedes/saltstack-salt

b54becb8b43cc9b7c00b2c0bc637ac534dc62896

[ "Apache-2.0" ]

33,507

2015-01-01T00:19:56.000Z

2022-03-31T23:48:20.000Z

tests/unit/modules/test_drbd.py

ifraixedes/saltstack-salt

b54becb8b43cc9b7c00b2c0bc637ac534dc62896

[ "Apache-2.0" ]

5,810

2015-01-01T19:11:45.000Z

2022-03-31T02:37:20.000Z

""" :codeauthor: Jayesh Kariya <jayeshk@saltstack.com> """ import salt.modules.drbd as drbd from tests.support.mixins import LoaderModuleMockMixin from tests.support.mock import MagicMock, patch from tests.support.unit import TestCase class DrbdTestCase(TestCase, LoaderModuleMockMixin): """ Test cases for salt.modules.drbd """ def setup_loader_modules(self): return {drbd: {}} # 'overview' function tests: 1 def test_overview(self): """ Test if it shows status of the DRBD devices """ ret = { "connection state": "True", "device": "Stack", "fs": "None", "local disk state": "UpToDate", "local role": "master", "minor number": "Salt", "mountpoint": "True", "partner disk state": "UpToDate", "partner role": "minion", "percent": "888", "remains": "666", "total size": "50", "used": "50", } mock = MagicMock( return_value=( "Salt:Stack True master/minion UpToDate/UpToDate True None 50 50 666 888" ) ) with patch.dict(drbd.__salt__, {"cmd.run": mock}): self.assertDictEqual(drbd.overview(), ret) ret = { "connection state": "True", "device": "Stack", "local disk state": "UpToDate", "local role": "master", "minor number": "Salt", "partner disk state": "partner", "partner role": "minion", "synched": "5050", "synchronisation: ": "syncbar", } mock = MagicMock( return_value=( "Salt:Stack True master/minion UpToDate/partner syncbar None 50 50" ) ) with patch.dict(drbd.__salt__, {"cmd.run": mock}): self.assertDictEqual(drbd.overview(), ret) def test_status(self): """ Test if it shows status of the DRBD resources via drbdadm """ ret = [ { "local role": "Primary", "local volumes": [{"disk": "UpToDate"}], "peer nodes": [ { "peer volumes": [ { "done": "96.47", "peer-disk": "Inconsistent", "replication": "SyncSource", } ], "peernode name": "opensuse-node2", "role": "Secondary", } ], "resource name": "single", } ] mock = MagicMock( return_value=""" single role:Primary disk:UpToDate opensuse-node2 role:Secondary replication:SyncSource peer-disk:Inconsistent done:96.47 """ ) with patch.dict(drbd.__salt__, {"cmd.run": mock}): try: # python2 self.assertItemsEqual(drbd.status(), ret) except AttributeError: # python3 self.assertCountEqual(drbd.status(), ret) ret = [ { "local role": "Primary", "local volumes": [ {"disk": "UpToDate", "volume": "0"}, {"disk": "UpToDate", "volume": "1"}, ], "peer nodes": [ { "peer volumes": [ {"peer-disk": "UpToDate", "volume": "0"}, {"peer-disk": "UpToDate", "volume": "1"}, ], "peernode name": "node2", "role": "Secondary", }, { "peer volumes": [ {"peer-disk": "UpToDate", "volume": "0"}, {"peer-disk": "UpToDate", "volume": "1"}, ], "peernode name": "node3", "role": "Secondary", }, ], "resource name": "test", }, { "local role": "Primary", "local volumes": [ {"disk": "UpToDate", "volume": "0"}, {"disk": "UpToDate", "volume": "1"}, ], "peer nodes": [ { "peer volumes": [ {"peer-disk": "UpToDate", "volume": "0"}, {"peer-disk": "UpToDate", "volume": "1"}, ], "peernode name": "node2", "role": "Secondary", }, { "peer volumes": [ {"peer-disk": "UpToDate", "volume": "0"}, {"peer-disk": "UpToDate", "volume": "1"}, ], "peernode name": "node3", "role": "Secondary", }, ], "resource name": "res", }, ] mock = MagicMock( return_value=""" res role:Primary volume:0 disk:UpToDate volume:1 disk:UpToDate node2 role:Secondary volume:0 peer-disk:UpToDate volume:1 peer-disk:UpToDate node3 role:Secondary volume:0 peer-disk:UpToDate volume:1 peer-disk:UpToDate test role:Primary volume:0 disk:UpToDate volume:1 disk:UpToDate node2 role:Secondary volume:0 peer-disk:UpToDate volume:1 peer-disk:UpToDate node3 role:Secondary volume:0 peer-disk:UpToDate volume:1 peer-disk:UpToDate """ ) with patch.dict(drbd.__salt__, {"cmd.run": mock}): try: # python2 self.assertItemsEqual(drbd.status(), ret) except AttributeError: # python3 self.assertCountEqual(drbd.status(), ret)

31.791667

89

0.422182

import salt.modules.drbd as drbd from tests.support.mixins import LoaderModuleMockMixin from tests.support.mock import MagicMock, patch from tests.support.unit import TestCase class DrbdTestCase(TestCase, LoaderModuleMockMixin): def setup_loader_modules(self): return {drbd: {}} def test_overview(self): ret = { "connection state": "True", "device": "Stack", "fs": "None", "local disk state": "UpToDate", "local role": "master", "minor number": "Salt", "mountpoint": "True", "partner disk state": "UpToDate", "partner role": "minion", "percent": "888", "remains": "666", "total size": "50", "used": "50", } mock = MagicMock( return_value=( "Salt:Stack True master/minion UpToDate/UpToDate True None 50 50 666 888" ) ) with patch.dict(drbd.__salt__, {"cmd.run": mock}): self.assertDictEqual(drbd.overview(), ret) ret = { "connection state": "True", "device": "Stack", "local disk state": "UpToDate", "local role": "master", "minor number": "Salt", "partner disk state": "partner", "partner role": "minion", "synched": "5050", "synchronisation: ": "syncbar", } mock = MagicMock( return_value=( "Salt:Stack True master/minion UpToDate/partner syncbar None 50 50" ) ) with patch.dict(drbd.__salt__, {"cmd.run": mock}): self.assertDictEqual(drbd.overview(), ret) def test_status(self): ret = [ { "local role": "Primary", "local volumes": [{"disk": "UpToDate"}], "peer nodes": [ { "peer volumes": [ { "done": "96.47", "peer-disk": "Inconsistent", "replication": "SyncSource", } ], "peernode name": "opensuse-node2", "role": "Secondary", } ], "resource name": "single", } ] mock = MagicMock( return_value=""" single role:Primary disk:UpToDate opensuse-node2 role:Secondary replication:SyncSource peer-disk:Inconsistent done:96.47 """ ) with patch.dict(drbd.__salt__, {"cmd.run": mock}): try: self.assertItemsEqual(drbd.status(), ret) except AttributeError: self.assertCountEqual(drbd.status(), ret) ret = [ { "local role": "Primary", "local volumes": [ {"disk": "UpToDate", "volume": "0"}, {"disk": "UpToDate", "volume": "1"}, ], "peer nodes": [ { "peer volumes": [ {"peer-disk": "UpToDate", "volume": "0"}, {"peer-disk": "UpToDate", "volume": "1"}, ], "peernode name": "node2", "role": "Secondary", }, { "peer volumes": [ {"peer-disk": "UpToDate", "volume": "0"}, {"peer-disk": "UpToDate", "volume": "1"}, ], "peernode name": "node3", "role": "Secondary", }, ], "resource name": "test", }, { "local role": "Primary", "local volumes": [ {"disk": "UpToDate", "volume": "0"}, {"disk": "UpToDate", "volume": "1"}, ], "peer nodes": [ { "peer volumes": [ {"peer-disk": "UpToDate", "volume": "0"}, {"peer-disk": "UpToDate", "volume": "1"}, ], "peernode name": "node2", "role": "Secondary", }, { "peer volumes": [ {"peer-disk": "UpToDate", "volume": "0"}, {"peer-disk": "UpToDate", "volume": "1"}, ], "peernode name": "node3", "role": "Secondary", }, ], "resource name": "res", }, ] mock = MagicMock( return_value=""" res role:Primary volume:0 disk:UpToDate volume:1 disk:UpToDate node2 role:Secondary volume:0 peer-disk:UpToDate volume:1 peer-disk:UpToDate node3 role:Secondary volume:0 peer-disk:UpToDate volume:1 peer-disk:UpToDate test role:Primary volume:0 disk:UpToDate volume:1 disk:UpToDate node2 role:Secondary volume:0 peer-disk:UpToDate volume:1 peer-disk:UpToDate node3 role:Secondary volume:0 peer-disk:UpToDate volume:1 peer-disk:UpToDate """ ) with patch.dict(drbd.__salt__, {"cmd.run": mock}): try: self.assertItemsEqual(drbd.status(), ret) except AttributeError: self.assertCountEqual(drbd.status(), ret)

true

1c2fd66b33bfdead4ee11a93556cf890ac8cb385

214

py

Python

peruintercorp/peruintercorp/doctype/proyectos/test_proyectos.py

aaguirrek/pii-peruintercorp

027d4c5f1fb79a1b16937bcf0938c4739f26b52a

[ "MIT" ]

null

peruintercorp/peruintercorp/doctype/proyectos/test_proyectos.py

aaguirrek/pii-peruintercorp

027d4c5f1fb79a1b16937bcf0938c4739f26b52a

[ "MIT" ]

null

peruintercorp/peruintercorp/doctype/proyectos/test_proyectos.py

aaguirrek/pii-peruintercorp

027d4c5f1fb79a1b16937bcf0938c4739f26b52a

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Copyright (c) 2020, Peru Intercorp and Contributors # See license.txt from __future__ import unicode_literals import frappe import unittest class TestProyectos(unittest.TestCase): pass

19.454545

53

0.771028

from __future__ import unicode_literals import frappe import unittest class TestProyectos(unittest.TestCase): pass

true

1c2fd86a3f1225beeae650437858e61c423f2ef8

1,143

py

Python

test/pyaz/postgres/flexible_server/deploy/__init__.py

bigdatamoore/py-az-cli

54383a4ee7cc77556f6183e74e992eec95b28e01

[ "MIT" ]

null

test/pyaz/postgres/flexible_server/deploy/__init__.py

bigdatamoore/py-az-cli

54383a4ee7cc77556f6183e74e992eec95b28e01

[ "MIT" ]

9

2021-09-24T16:37:24.000Z

2021-12-24T00:39:19.000Z

test/pyaz/postgres/flexible_server/deploy/__init__.py

bigdatamoore/py-az-cli

54383a4ee7cc77556f6183e74e992eec95b28e01

[ "MIT" ]

null

import json, subprocess from .... pyaz_utils import get_cli_name, get_params def setup(resource_group, server_name, database_name, admin_user, admin_password, sql_file, repo, action_name=None, branch=None, allow_push=None): params = get_params(locals()) command = "az postgres flexible-server deploy setup " + params print(command) output = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) stdout = output.stdout.decode("utf-8") stderr = output.stderr.decode("utf-8") if stdout: return json.loads(stdout) print(stdout) else: raise Exception(stderr) print(stderr) def run(action_name, branch): params = get_params(locals()) command = "az postgres flexible-server deploy run " + params print(command) output = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) stdout = output.stdout.decode("utf-8") stderr = output.stderr.decode("utf-8") if stdout: return json.loads(stdout) print(stdout) else: raise Exception(stderr) print(stderr)

35.71875

146

0.682415

import json, subprocess from .... pyaz_utils import get_cli_name, get_params def setup(resource_group, server_name, database_name, admin_user, admin_password, sql_file, repo, action_name=None, branch=None, allow_push=None): params = get_params(locals()) command = "az postgres flexible-server deploy setup " + params print(command) output = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) stdout = output.stdout.decode("utf-8") stderr = output.stderr.decode("utf-8") if stdout: return json.loads(stdout) print(stdout) else: raise Exception(stderr) print(stderr) def run(action_name, branch): params = get_params(locals()) command = "az postgres flexible-server deploy run " + params print(command) output = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) stdout = output.stdout.decode("utf-8") stderr = output.stderr.decode("utf-8") if stdout: return json.loads(stdout) print(stdout) else: raise Exception(stderr) print(stderr)

true

1c2fd86c5a584ac6d9a5926e64b58842e9791db0

977

py

Python

general_itests/steps/shared_steps.py

sobolevn/paasta

8b87e0b13816c09b3d063b6d3271e6c7627fd264

[ "Apache-2.0" ]

1,711

2015-11-10T18:04:56.000Z

2022-03-23T08:53:16.000Z

general_itests/steps/shared_steps.py

sobolevn/paasta

8b87e0b13816c09b3d063b6d3271e6c7627fd264

[ "Apache-2.0" ]

1,689

2015-11-10T17:59:04.000Z

2022-03-31T20:46:46.000Z

general_itests/steps/shared_steps.py

sobolevn/paasta

8b87e0b13816c09b3d063b6d3271e6c7627fd264

[ "Apache-2.0" ]

267

2015-11-10T19:17:16.000Z

2022-02-08T20:59:52.000Z

# Copyright 2015-2016 Yelp 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 behave import then @then('it should have a return code of "{code:d}"') def see_expected_return_code(context, code): print(context.output) print(context.return_code) print() assert context.return_code == code @then('the output should contain "{output_string}"') def output_contains(context, output_string): print(output_string) assert output_string in context.output

33.689655

74

0.752303

from behave import then @then('it should have a return code of "{code:d}"') def see_expected_return_code(context, code): print(context.output) print(context.return_code) print() assert context.return_code == code @then('the output should contain "{output_string}"') def output_contains(context, output_string): print(output_string) assert output_string in context.output

true

1c2fd9a22e506269dd9c789c4afcef4614f97997

328

py

Python

test/filter_lol_test.py

zhenggc1/guietta

2eb78b7d0a30d145a248c6eac27cab2bb907d64c

[ "MIT" ]

1

2020-07-22T17:30:10.000Z

test/filter_lol_test.py

zhenggc1/guietta

2eb78b7d0a30d145a248c6eac27cab2bb907d64c

[ "MIT" ]

null

test/filter_lol_test.py

zhenggc1/guietta

2eb78b7d0a30d145a248c6eac27cab2bb907d64c

[ "MIT" ]

null

# -*- coding: utf-8 -*- import unittest from guietta.guietta import _filter_lol class FilterLolTest(unittest.TestCase): def test_filter_lol(self): lol = [[1, 3, 10], [3.14, 0, -2]] def func(x): return x * 2 _filter_lol(lol, func) assert lol == [[2, 6, 20], [6.28, 0, -4]]

17.263158

49

0.545732

import unittest from guietta.guietta import _filter_lol class FilterLolTest(unittest.TestCase): def test_filter_lol(self): lol = [[1, 3, 10], [3.14, 0, -2]] def func(x): return x * 2 _filter_lol(lol, func) assert lol == [[2, 6, 20], [6.28, 0, -4]]

true

1c2fda6177765b7906214bb4b8231a55632b2a0e

22,030

py

Python

tests/test_s3boto3.py

danielholmes/django-storages

45d8235ebd62da29bcca6b1e012a143009b2fb0c

[ "BSD-3-Clause" ]

null

tests/test_s3boto3.py

danielholmes/django-storages

45d8235ebd62da29bcca6b1e012a143009b2fb0c

[ "BSD-3-Clause" ]

null

tests/test_s3boto3.py

danielholmes/django-storages

45d8235ebd62da29bcca6b1e012a143009b2fb0c

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals import gzip import pickle import threading import warnings from datetime import datetime from unittest import skipIf from botocore.exceptions import ClientError from django.conf import settings from django.core.exceptions import ImproperlyConfigured from django.core.files.base import ContentFile from django.test import TestCase, override_settings from django.utils.six.moves.urllib import parse as urlparse from django.utils.timezone import is_aware, utc from storages.backends import s3boto3 try: from unittest import mock except ImportError: # Python 3.2 and below import mock class S3Boto3TestCase(TestCase): def setUp(self): self.storage = s3boto3.S3Boto3Storage() self.storage._connections.connection = mock.MagicMock() class S3Boto3StorageTests(S3Boto3TestCase): def test_clean_name(self): """ Test the base case of _clean_name """ path = self.storage._clean_name("path/to/somewhere") self.assertEqual(path, "path/to/somewhere") def test_clean_name_normalize(self): """ Test the normalization of _clean_name """ path = self.storage._clean_name("path/to/../somewhere") self.assertEqual(path, "path/somewhere") def test_clean_name_trailing_slash(self): """ Test the _clean_name when the path has a trailing slash """ path = self.storage._clean_name("path/to/somewhere/") self.assertEqual(path, "path/to/somewhere/") def test_clean_name_windows(self): """ Test the _clean_name when the path has a trailing slash """ path = self.storage._clean_name("path\\to\\somewhere") self.assertEqual(path, "path/to/somewhere") def test_pickle_with_bucket(self): """ Test that the storage can be pickled with a bucket attached """ # Ensure the bucket has been used self.storage.bucket self.assertIsNotNone(self.storage._bucket) # Can't pickle MagicMock, but you can't pickle a real Bucket object either p = pickle.dumps(self.storage) new_storage = pickle.loads(p) self.assertIsInstance(new_storage._connections, threading.local) # Put the mock connection back in new_storage._connections.connection = mock.MagicMock() self.assertIsNone(new_storage._bucket) new_storage.bucket self.assertIsNotNone(new_storage._bucket) def test_pickle_without_bucket(self): """ Test that the storage can be pickled, without a bucket instance """ # Can't pickle a threadlocal p = pickle.dumps(self.storage) new_storage = pickle.loads(p) self.assertIsInstance(new_storage._connections, threading.local) def test_storage_url_slashes(self): """ Test URL generation. """ self.storage.custom_domain = 'example.com' # We expect no leading slashes in the path, # and trailing slashes should be preserved. self.assertEqual(self.storage.url(''), 'https://example.com/') self.assertEqual(self.storage.url('path'), 'https://example.com/path') self.assertEqual(self.storage.url('path/'), 'https://example.com/path/') self.assertEqual(self.storage.url('path/1'), 'https://example.com/path/1') self.assertEqual(self.storage.url('path/1/'), 'https://example.com/path/1/') def test_storage_save(self): """ Test saving a file """ name = 'test_storage_save.txt' content = ContentFile('new content') self.storage.save(name, content) self.storage.bucket.Object.assert_called_once_with(name) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( content.file, ExtraArgs={ 'ContentType': 'text/plain', 'ACL': self.storage.default_acl, } ) def test_storage_save_with_acl(self): """ Test saving a file with user defined ACL. """ name = 'test_storage_save.txt' content = ContentFile('new content') self.storage.default_acl = 'private' self.storage.save(name, content) self.storage.bucket.Object.assert_called_once_with(name) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( content.file, ExtraArgs={ 'ContentType': 'text/plain', 'ACL': 'private', } ) def test_content_type(self): """ Test saving a file with a None content type. """ name = 'test_image.jpg' content = ContentFile('data') content.content_type = None self.storage.save(name, content) self.storage.bucket.Object.assert_called_once_with(name) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( content.file, ExtraArgs={ 'ContentType': 'image/jpeg', 'ACL': self.storage.default_acl, } ) def test_storage_save_gzipped(self): """ Test saving a gzipped file """ name = 'test_storage_save.gz' content = ContentFile("I am gzip'd") self.storage.save(name, content) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( content.file, ExtraArgs={ 'ContentType': 'application/octet-stream', 'ContentEncoding': 'gzip', 'ACL': self.storage.default_acl, } ) def test_storage_save_gzip(self): """ Test saving a file with gzip enabled. """ self.storage.gzip = True name = 'test_storage_save.css' content = ContentFile("I should be gzip'd") self.storage.save(name, content) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( mock.ANY, ExtraArgs={ 'ContentType': 'text/css', 'ContentEncoding': 'gzip', 'ACL': self.storage.default_acl, } ) args, kwargs = obj.upload_fileobj.call_args content = args[0] zfile = gzip.GzipFile(mode='rb', fileobj=content) self.assertEqual(zfile.read(), b"I should be gzip'd") def test_storage_save_gzip_twice(self): """ Test saving the same file content twice with gzip enabled. """ # Given self.storage.gzip = True name = 'test_storage_save.css' content = ContentFile("I should be gzip'd") # When self.storage.save(name, content) self.storage.save('test_storage_save_2.css', content) # Then obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( mock.ANY, ExtraArgs={ 'ContentType': 'text/css', 'ContentEncoding': 'gzip', 'ACL': self.storage.default_acl, } ) args, kwargs = obj.upload_fileobj.call_args content = args[0] zfile = gzip.GzipFile(mode='rb', fileobj=content) self.assertEqual(zfile.read(), b"I should be gzip'd") def test_compress_content_len(self): """ Test that file returned by _compress_content() is readable. """ self.storage.gzip = True content = ContentFile("I should be gzip'd") content = self.storage._compress_content(content) self.assertTrue(len(content.read()) > 0) def test_storage_open_write(self): """ Test opening a file in write mode """ name = 'test_open_for_writïng.txt' content = 'new content' # Set the encryption flag used for multipart uploads self.storage.encryption = True self.storage.reduced_redundancy = True self.storage.default_acl = 'public-read' file = self.storage.open(name, 'w') self.storage.bucket.Object.assert_called_with(name) obj = self.storage.bucket.Object.return_value # Set the name of the mock object obj.key = name file.write(content) obj.initiate_multipart_upload.assert_called_with( ACL='public-read', ContentType='text/plain', ServerSideEncryption='AES256', StorageClass='REDUCED_REDUNDANCY' ) # Save the internal file before closing multipart = obj.initiate_multipart_upload.return_value multipart.parts.all.return_value = [mock.MagicMock(e_tag='123', part_number=1)] file.close() multipart.Part.assert_called_with(1) part = multipart.Part.return_value part.upload.assert_called_with(Body=content.encode('utf-8')) multipart.complete.assert_called_once_with( MultipartUpload={'Parts': [{'ETag': '123', 'PartNumber': 1}]}) def test_storage_write_beyond_buffer_size(self): """ Test writing content that exceeds the buffer size """ name = 'test_open_for_writïng_beyond_buffer_size.txt' # Set the encryption flag used for multipart uploads self.storage.encryption = True self.storage.reduced_redundancy = True self.storage.default_acl = 'public-read' file = self.storage.open(name, 'w') self.storage.bucket.Object.assert_called_with(name) obj = self.storage.bucket.Object.return_value # Set the name of the mock object obj.key = name # Initiate the multipart upload file.write('') obj.initiate_multipart_upload.assert_called_with( ACL='public-read', ContentType='text/plain', ServerSideEncryption='AES256', StorageClass='REDUCED_REDUNDANCY' ) multipart = obj.initiate_multipart_upload.return_value # Write content at least twice as long as the buffer size written_content = '' counter = 1 while len(written_content) < 2 * file.buffer_size: content = 'hello, aws {counter}\n'.format(counter=counter) # Write more than just a few bytes in each iteration to keep the # test reasonably fast content += '*' * int(file.buffer_size / 10) file.write(content) written_content += content counter += 1 # Save the internal file before closing multipart.parts.all.return_value = [ mock.MagicMock(e_tag='123', part_number=1), mock.MagicMock(e_tag='456', part_number=2) ] file.close() self.assertListEqual( multipart.Part.call_args_list, [mock.call(1), mock.call(2)] ) part = multipart.Part.return_value uploaded_content = ''.join( (args_list[1]['Body'].decode('utf-8') for args_list in part.upload.call_args_list) ) self.assertEqual(uploaded_content, written_content) multipart.complete.assert_called_once_with( MultipartUpload={'Parts': [ {'ETag': '123', 'PartNumber': 1}, {'ETag': '456', 'PartNumber': 2}, ]} ) def test_auto_creating_bucket(self): self.storage.auto_create_bucket = True Bucket = mock.MagicMock() self.storage._connections.connection.Bucket.return_value = Bucket self.storage._connections.connection.meta.client.meta.region_name = 'sa-east-1' Bucket.meta.client.head_bucket.side_effect = ClientError({'Error': {}, 'ResponseMetadata': {'HTTPStatusCode': 404}}, 'head_bucket') self.storage._get_or_create_bucket('testbucketname') Bucket.create.assert_called_once_with( ACL='public-read', CreateBucketConfiguration={ 'LocationConstraint': 'sa-east-1', } ) def test_auto_creating_bucket_with_acl(self): self.storage.auto_create_bucket = True self.storage.bucket_acl = 'public-read' Bucket = mock.MagicMock() self.storage._connections.connection.Bucket.return_value = Bucket self.storage._connections.connection.meta.client.meta.region_name = 'sa-east-1' Bucket.meta.client.head_bucket.side_effect = ClientError({'Error': {}, 'ResponseMetadata': {'HTTPStatusCode': 404}}, 'head_bucket') self.storage._get_or_create_bucket('testbucketname') Bucket.create.assert_called_once_with( ACL='public-read', CreateBucketConfiguration={ 'LocationConstraint': 'sa-east-1', } ) def test_storage_exists(self): self.assertTrue(self.storage.exists("file.txt")) self.storage.connection.meta.client.head_object.assert_called_with( Bucket=self.storage.bucket_name, Key="file.txt", ) def test_storage_exists_false(self): self.storage.connection.meta.client.head_object.side_effect = ClientError( {'Error': {'Code': '404', 'Message': 'Not Found'}}, 'HeadObject', ) self.assertFalse(self.storage.exists("file.txt")) self.storage.connection.meta.client.head_object.assert_called_with( Bucket=self.storage.bucket_name, Key='file.txt', ) def test_storage_exists_doesnt_create_bucket(self): with mock.patch.object(self.storage, '_get_or_create_bucket') as method: self.storage.exists('file.txt') self.assertFalse(method.called) def test_storage_delete(self): self.storage.delete("path/to/file.txt") self.storage.bucket.Object.assert_called_with('path/to/file.txt') self.storage.bucket.Object.return_value.delete.assert_called_with() def test_storage_listdir_base(self): # Files: # some/path/1.txt # 2.txt # other/path/3.txt # 4.txt pages = [ { 'CommonPrefixes': [ {'Prefix': 'some'}, {'Prefix': 'other'}, ], 'Contents': [ {'Key': '2.txt'}, {'Key': '4.txt'}, ], }, ] paginator = mock.MagicMock() paginator.paginate.return_value = pages self.storage._connections.connection.meta.client.get_paginator.return_value = paginator dirs, files = self.storage.listdir('') paginator.paginate.assert_called_with(Bucket=None, Delimiter='/', Prefix='') self.assertEqual(dirs, ['some', 'other']) self.assertEqual(files, ['2.txt', '4.txt']) def test_storage_listdir_subdir(self): # Files: # some/path/1.txt # some/2.txt pages = [ { 'CommonPrefixes': [ {'Prefix': 'some/path'}, ], 'Contents': [ {'Key': 'some/2.txt'}, ], }, ] paginator = mock.MagicMock() paginator.paginate.return_value = pages self.storage._connections.connection.meta.client.get_paginator.return_value = paginator dirs, files = self.storage.listdir('some/') paginator.paginate.assert_called_with(Bucket=None, Delimiter='/', Prefix='some/') self.assertEqual(dirs, ['path']) self.assertEqual(files, ['2.txt']) def test_storage_size(self): obj = self.storage.bucket.Object.return_value obj.content_length = 4098 name = 'file.txt' self.assertEqual(self.storage.size(name), obj.content_length) def test_storage_mtime(self): # Test both USE_TZ cases for use_tz in (True, False): with self.settings(USE_TZ=use_tz): self._test_storage_mtime(use_tz) def _test_storage_mtime(self, use_tz): obj = self.storage.bucket.Object.return_value obj.last_modified = datetime.now(utc) name = 'file.txt' self.assertFalse( is_aware(self.storage.modified_time(name)), 'Naive datetime object expected from modified_time()' ) self.assertIs( settings.USE_TZ, is_aware(self.storage.get_modified_time(name)), '%s datetime object expected from get_modified_time() when USE_TZ=%s' % ( ('Naive', 'Aware')[settings.USE_TZ], settings.USE_TZ ) ) def test_storage_url(self): name = 'test_storage_size.txt' url = 'http://aws.amazon.com/%s' % name self.storage.bucket.meta.client.generate_presigned_url.return_value = url self.storage.bucket.name = 'bucket' self.assertEqual(self.storage.url(name), url) self.storage.bucket.meta.client.generate_presigned_url.assert_called_with( 'get_object', Params={'Bucket': self.storage.bucket.name, 'Key': name}, ExpiresIn=self.storage.querystring_expire ) custom_expire = 123 self.assertEqual(self.storage.url(name, expire=custom_expire), url) self.storage.bucket.meta.client.generate_presigned_url.assert_called_with( 'get_object', Params={'Bucket': self.storage.bucket.name, 'Key': name}, ExpiresIn=custom_expire ) def test_generated_url_is_encoded(self): self.storage.custom_domain = "mock.cloudfront.net" filename = "whacky & filename'.mp4" url = self.storage.url(filename) parsed_url = urlparse.urlparse(url) self.assertEqual(parsed_url.path, "/whacky%20%26%20filename%27.mp4") self.assertFalse(self.storage.bucket.meta.client.generate_presigned_url.called) def test_special_characters(self): self.storage.custom_domain = "mock.cloudfront.net" name = "ãlöhâ.jpg" content = ContentFile('new content') self.storage.save(name, content) self.storage.bucket.Object.assert_called_once_with(name) url = self.storage.url(name) parsed_url = urlparse.urlparse(url) self.assertEqual(parsed_url.path, "/%C3%A3l%C3%B6h%C3%A2.jpg") def test_strip_signing_parameters(self): expected = 'http://bucket.s3-aws-region.amazonaws.com/foo/bar' self.assertEqual(self.storage._strip_signing_parameters( '%s?X-Amz-Date=12345678&X-Amz-Signature=Signature' % expected), expected) self.assertEqual(self.storage._strip_signing_parameters( '%s?expires=12345678&signature=Signature' % expected), expected) @skipIf(threading is None, 'Test requires threading') def test_connection_threading(self): connections = [] def thread_storage_connection(): connections.append(self.storage.connection) for x in range(2): t = threading.Thread(target=thread_storage_connection) t.start() t.join() # Connection for each thread needs to be unique self.assertIsNot(connections[0], connections[1]) def test_location_leading_slash(self): msg = ( "S3Boto3Storage.location cannot begin with a leading slash. " "Found '/'. Use '' instead." ) with self.assertRaises(ImproperlyConfigured, msg=msg): s3boto3.S3Boto3Storage(location='/') def test_deprecated_acl(self): with override_settings(AWS_DEFAULT_ACL=None), warnings.catch_warnings(record=True) as w: s3boto3.S3Boto3Storage(acl='private') assert len(w) == 1 assert issubclass(w[-1].category, DeprecationWarning) message = ( "The acl argument of S3Boto3Storage is deprecated. Use argument " "default_acl or setting AWS_DEFAULT_ACL instead. The acl argument " "will be removed in version 2.0." ) assert str(w[-1].message) == message def test_deprecated_bucket(self): with override_settings(AWS_DEFAULT_ACL=None), warnings.catch_warnings(record=True) as w: s3boto3.S3Boto3Storage(bucket='django') assert len(w) == 1 assert issubclass(w[-1].category, DeprecationWarning) message = ( "The bucket argument of S3Boto3Storage is deprecated. Use argument " "bucket_name or setting AWS_STORAGE_BUCKET_NAME instead. The bucket " "argument will be removed in version 2.0." ) assert str(w[-1].message) == message def test_deprecated_default_acl(self): with warnings.catch_warnings(record=True) as w: s3boto3.S3Boto3Storage() assert len(w) == 1 message = ( "The default behavior of S3Boto3Storage is insecure and will change " "in django-storages 2.0. By default files and new buckets are saved " "with an ACL of 'public-read' (globally publicly readable). Version 2.0 will " "default to using the bucket's ACL. To opt into the new behavior set " "AWS_DEFAULT_ACL = None, otherwise to silence this warning explicitly " "set AWS_DEFAULT_ACL." ) assert str(w[-1].message) == message def test_deprecated_default_acl_override_class_variable(self): class MyStorage(s3boto3.S3Boto3Storage): default_acl = "private" with warnings.catch_warnings(record=True) as w: MyStorage() assert len(w) == 0

36.47351

111

0.607354

from __future__ import unicode_literals import gzip import pickle import threading import warnings from datetime import datetime from unittest import skipIf from botocore.exceptions import ClientError from django.conf import settings from django.core.exceptions import ImproperlyConfigured from django.core.files.base import ContentFile from django.test import TestCase, override_settings from django.utils.six.moves.urllib import parse as urlparse from django.utils.timezone import is_aware, utc from storages.backends import s3boto3 try: from unittest import mock except ImportError: import mock class S3Boto3TestCase(TestCase): def setUp(self): self.storage = s3boto3.S3Boto3Storage() self.storage._connections.connection = mock.MagicMock() class S3Boto3StorageTests(S3Boto3TestCase): def test_clean_name(self): path = self.storage._clean_name("path/to/somewhere") self.assertEqual(path, "path/to/somewhere") def test_clean_name_normalize(self): path = self.storage._clean_name("path/to/../somewhere") self.assertEqual(path, "path/somewhere") def test_clean_name_trailing_slash(self): path = self.storage._clean_name("path/to/somewhere/") self.assertEqual(path, "path/to/somewhere/") def test_clean_name_windows(self): path = self.storage._clean_name("path\\to\\somewhere") self.assertEqual(path, "path/to/somewhere") def test_pickle_with_bucket(self): self.storage.bucket self.assertIsNotNone(self.storage._bucket) p = pickle.dumps(self.storage) new_storage = pickle.loads(p) self.assertIsInstance(new_storage._connections, threading.local) new_storage._connections.connection = mock.MagicMock() self.assertIsNone(new_storage._bucket) new_storage.bucket self.assertIsNotNone(new_storage._bucket) def test_pickle_without_bucket(self): p = pickle.dumps(self.storage) new_storage = pickle.loads(p) self.assertIsInstance(new_storage._connections, threading.local) def test_storage_url_slashes(self): self.storage.custom_domain = 'example.com' # We expect no leading slashes in the path, # and trailing slashes should be preserved. self.assertEqual(self.storage.url(''), 'https://example.com/') self.assertEqual(self.storage.url('path'), 'https://example.com/path') self.assertEqual(self.storage.url('path/'), 'https://example.com/path/') self.assertEqual(self.storage.url('path/1'), 'https://example.com/path/1') self.assertEqual(self.storage.url('path/1/'), 'https://example.com/path/1/') def test_storage_save(self): name = 'test_storage_save.txt' content = ContentFile('new content') self.storage.save(name, content) self.storage.bucket.Object.assert_called_once_with(name) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( content.file, ExtraArgs={ 'ContentType': 'text/plain', 'ACL': self.storage.default_acl, } ) def test_storage_save_with_acl(self): name = 'test_storage_save.txt' content = ContentFile('new content') self.storage.default_acl = 'private' self.storage.save(name, content) self.storage.bucket.Object.assert_called_once_with(name) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( content.file, ExtraArgs={ 'ContentType': 'text/plain', 'ACL': 'private', } ) def test_content_type(self): name = 'test_image.jpg' content = ContentFile('data') content.content_type = None self.storage.save(name, content) self.storage.bucket.Object.assert_called_once_with(name) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( content.file, ExtraArgs={ 'ContentType': 'image/jpeg', 'ACL': self.storage.default_acl, } ) def test_storage_save_gzipped(self): name = 'test_storage_save.gz' content = ContentFile("I am gzip'd") self.storage.save(name, content) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( content.file, ExtraArgs={ 'ContentType': 'application/octet-stream', 'ContentEncoding': 'gzip', 'ACL': self.storage.default_acl, } ) def test_storage_save_gzip(self): self.storage.gzip = True name = 'test_storage_save.css' content = ContentFile("I should be gzip'd") self.storage.save(name, content) obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( mock.ANY, ExtraArgs={ 'ContentType': 'text/css', 'ContentEncoding': 'gzip', 'ACL': self.storage.default_acl, } ) args, kwargs = obj.upload_fileobj.call_args content = args[0] zfile = gzip.GzipFile(mode='rb', fileobj=content) self.assertEqual(zfile.read(), b"I should be gzip'd") def test_storage_save_gzip_twice(self): self.storage.gzip = True name = 'test_storage_save.css' content = ContentFile("I should be gzip'd") # When self.storage.save(name, content) self.storage.save('test_storage_save_2.css', content) # Then obj = self.storage.bucket.Object.return_value obj.upload_fileobj.assert_called_with( mock.ANY, ExtraArgs={ 'ContentType': 'text/css', 'ContentEncoding': 'gzip', 'ACL': self.storage.default_acl, } ) args, kwargs = obj.upload_fileobj.call_args content = args[0] zfile = gzip.GzipFile(mode='rb', fileobj=content) self.assertEqual(zfile.read(), b"I should be gzip'd") def test_compress_content_len(self): self.storage.gzip = True content = ContentFile("I should be gzip'd") content = self.storage._compress_content(content) self.assertTrue(len(content.read()) > 0) def test_storage_open_write(self): name = 'test_open_for_writïng.txt' content = 'new content' # Set the encryption flag used for multipart uploads self.storage.encryption = True self.storage.reduced_redundancy = True self.storage.default_acl = 'public-read' file = self.storage.open(name, 'w') self.storage.bucket.Object.assert_called_with(name) obj = self.storage.bucket.Object.return_value # Set the name of the mock object obj.key = name file.write(content) obj.initiate_multipart_upload.assert_called_with( ACL='public-read', ContentType='text/plain', ServerSideEncryption='AES256', StorageClass='REDUCED_REDUNDANCY' ) # Save the internal file before closing multipart = obj.initiate_multipart_upload.return_value multipart.parts.all.return_value = [mock.MagicMock(e_tag='123', part_number=1)] file.close() multipart.Part.assert_called_with(1) part = multipart.Part.return_value part.upload.assert_called_with(Body=content.encode('utf-8')) multipart.complete.assert_called_once_with( MultipartUpload={'Parts': [{'ETag': '123', 'PartNumber': 1}]}) def test_storage_write_beyond_buffer_size(self): name = 'test_open_for_writïng_beyond_buffer_size.txt' # Set the encryption flag used for multipart uploads self.storage.encryption = True self.storage.reduced_redundancy = True self.storage.default_acl = 'public-read' file = self.storage.open(name, 'w') self.storage.bucket.Object.assert_called_with(name) obj = self.storage.bucket.Object.return_value # Set the name of the mock object obj.key = name # Initiate the multipart upload file.write('') obj.initiate_multipart_upload.assert_called_with( ACL='public-read', ContentType='text/plain', ServerSideEncryption='AES256', StorageClass='REDUCED_REDUNDANCY' ) multipart = obj.initiate_multipart_upload.return_value # Write content at least twice as long as the buffer size written_content = '' counter = 1 while len(written_content) < 2 * file.buffer_size: content = 'hello, aws {counter}\n'.format(counter=counter) # Write more than just a few bytes in each iteration to keep the # test reasonably fast content += '*' * int(file.buffer_size / 10) file.write(content) written_content += content counter += 1 # Save the internal file before closing multipart.parts.all.return_value = [ mock.MagicMock(e_tag='123', part_number=1), mock.MagicMock(e_tag='456', part_number=2) ] file.close() self.assertListEqual( multipart.Part.call_args_list, [mock.call(1), mock.call(2)] ) part = multipart.Part.return_value uploaded_content = ''.join( (args_list[1]['Body'].decode('utf-8') for args_list in part.upload.call_args_list) ) self.assertEqual(uploaded_content, written_content) multipart.complete.assert_called_once_with( MultipartUpload={'Parts': [ {'ETag': '123', 'PartNumber': 1}, {'ETag': '456', 'PartNumber': 2}, ]} ) def test_auto_creating_bucket(self): self.storage.auto_create_bucket = True Bucket = mock.MagicMock() self.storage._connections.connection.Bucket.return_value = Bucket self.storage._connections.connection.meta.client.meta.region_name = 'sa-east-1' Bucket.meta.client.head_bucket.side_effect = ClientError({'Error': {}, 'ResponseMetadata': {'HTTPStatusCode': 404}}, 'head_bucket') self.storage._get_or_create_bucket('testbucketname') Bucket.create.assert_called_once_with( ACL='public-read', CreateBucketConfiguration={ 'LocationConstraint': 'sa-east-1', } ) def test_auto_creating_bucket_with_acl(self): self.storage.auto_create_bucket = True self.storage.bucket_acl = 'public-read' Bucket = mock.MagicMock() self.storage._connections.connection.Bucket.return_value = Bucket self.storage._connections.connection.meta.client.meta.region_name = 'sa-east-1' Bucket.meta.client.head_bucket.side_effect = ClientError({'Error': {}, 'ResponseMetadata': {'HTTPStatusCode': 404}}, 'head_bucket') self.storage._get_or_create_bucket('testbucketname') Bucket.create.assert_called_once_with( ACL='public-read', CreateBucketConfiguration={ 'LocationConstraint': 'sa-east-1', } ) def test_storage_exists(self): self.assertTrue(self.storage.exists("file.txt")) self.storage.connection.meta.client.head_object.assert_called_with( Bucket=self.storage.bucket_name, Key="file.txt", ) def test_storage_exists_false(self): self.storage.connection.meta.client.head_object.side_effect = ClientError( {'Error': {'Code': '404', 'Message': 'Not Found'}}, 'HeadObject', ) self.assertFalse(self.storage.exists("file.txt")) self.storage.connection.meta.client.head_object.assert_called_with( Bucket=self.storage.bucket_name, Key='file.txt', ) def test_storage_exists_doesnt_create_bucket(self): with mock.patch.object(self.storage, '_get_or_create_bucket') as method: self.storage.exists('file.txt') self.assertFalse(method.called) def test_storage_delete(self): self.storage.delete("path/to/file.txt") self.storage.bucket.Object.assert_called_with('path/to/file.txt') self.storage.bucket.Object.return_value.delete.assert_called_with() def test_storage_listdir_base(self): # Files: # some/path/1.txt # 2.txt # other/path/3.txt # 4.txt pages = [ { 'CommonPrefixes': [ {'Prefix': 'some'}, {'Prefix': 'other'}, ], 'Contents': [ {'Key': '2.txt'}, {'Key': '4.txt'}, ], }, ] paginator = mock.MagicMock() paginator.paginate.return_value = pages self.storage._connections.connection.meta.client.get_paginator.return_value = paginator dirs, files = self.storage.listdir('') paginator.paginate.assert_called_with(Bucket=None, Delimiter='/', Prefix='') self.assertEqual(dirs, ['some', 'other']) self.assertEqual(files, ['2.txt', '4.txt']) def test_storage_listdir_subdir(self): # Files: # some/path/1.txt # some/2.txt pages = [ { 'CommonPrefixes': [ {'Prefix': 'some/path'}, ], 'Contents': [ {'Key': 'some/2.txt'}, ], }, ] paginator = mock.MagicMock() paginator.paginate.return_value = pages self.storage._connections.connection.meta.client.get_paginator.return_value = paginator dirs, files = self.storage.listdir('some/') paginator.paginate.assert_called_with(Bucket=None, Delimiter='/', Prefix='some/') self.assertEqual(dirs, ['path']) self.assertEqual(files, ['2.txt']) def test_storage_size(self): obj = self.storage.bucket.Object.return_value obj.content_length = 4098 name = 'file.txt' self.assertEqual(self.storage.size(name), obj.content_length) def test_storage_mtime(self): # Test both USE_TZ cases for use_tz in (True, False): with self.settings(USE_TZ=use_tz): self._test_storage_mtime(use_tz) def _test_storage_mtime(self, use_tz): obj = self.storage.bucket.Object.return_value obj.last_modified = datetime.now(utc) name = 'file.txt' self.assertFalse( is_aware(self.storage.modified_time(name)), 'Naive datetime object expected from modified_time()' ) self.assertIs( settings.USE_TZ, is_aware(self.storage.get_modified_time(name)), '%s datetime object expected from get_modified_time() when USE_TZ=%s' % ( ('Naive', 'Aware')[settings.USE_TZ], settings.USE_TZ ) ) def test_storage_url(self): name = 'test_storage_size.txt' url = 'http://aws.amazon.com/%s' % name self.storage.bucket.meta.client.generate_presigned_url.return_value = url self.storage.bucket.name = 'bucket' self.assertEqual(self.storage.url(name), url) self.storage.bucket.meta.client.generate_presigned_url.assert_called_with( 'get_object', Params={'Bucket': self.storage.bucket.name, 'Key': name}, ExpiresIn=self.storage.querystring_expire ) custom_expire = 123 self.assertEqual(self.storage.url(name, expire=custom_expire), url) self.storage.bucket.meta.client.generate_presigned_url.assert_called_with( 'get_object', Params={'Bucket': self.storage.bucket.name, 'Key': name}, ExpiresIn=custom_expire ) def test_generated_url_is_encoded(self): self.storage.custom_domain = "mock.cloudfront.net" filename = "whacky & filename'.mp4" url = self.storage.url(filename) parsed_url = urlparse.urlparse(url) self.assertEqual(parsed_url.path, "/whacky%20%26%20filename%27.mp4") self.assertFalse(self.storage.bucket.meta.client.generate_presigned_url.called) def test_special_characters(self): self.storage.custom_domain = "mock.cloudfront.net" name = "ãlöhâ.jpg" content = ContentFile('new content') self.storage.save(name, content) self.storage.bucket.Object.assert_called_once_with(name) url = self.storage.url(name) parsed_url = urlparse.urlparse(url) self.assertEqual(parsed_url.path, "/%C3%A3l%C3%B6h%C3%A2.jpg") def test_strip_signing_parameters(self): expected = 'http://bucket.s3-aws-region.amazonaws.com/foo/bar' self.assertEqual(self.storage._strip_signing_parameters( '%s?X-Amz-Date=12345678&X-Amz-Signature=Signature' % expected), expected) self.assertEqual(self.storage._strip_signing_parameters( '%s?expires=12345678&signature=Signature' % expected), expected) @skipIf(threading is None, 'Test requires threading') def test_connection_threading(self): connections = [] def thread_storage_connection(): connections.append(self.storage.connection) for x in range(2): t = threading.Thread(target=thread_storage_connection) t.start() t.join() self.assertIsNot(connections[0], connections[1]) def test_location_leading_slash(self): msg = ( "S3Boto3Storage.location cannot begin with a leading slash. " "Found '/'. Use '' instead." ) with self.assertRaises(ImproperlyConfigured, msg=msg): s3boto3.S3Boto3Storage(location='/') def test_deprecated_acl(self): with override_settings(AWS_DEFAULT_ACL=None), warnings.catch_warnings(record=True) as w: s3boto3.S3Boto3Storage(acl='private') assert len(w) == 1 assert issubclass(w[-1].category, DeprecationWarning) message = ( "The acl argument of S3Boto3Storage is deprecated. Use argument " "default_acl or setting AWS_DEFAULT_ACL instead. The acl argument " "will be removed in version 2.0." ) assert str(w[-1].message) == message def test_deprecated_bucket(self): with override_settings(AWS_DEFAULT_ACL=None), warnings.catch_warnings(record=True) as w: s3boto3.S3Boto3Storage(bucket='django') assert len(w) == 1 assert issubclass(w[-1].category, DeprecationWarning) message = ( "The bucket argument of S3Boto3Storage is deprecated. Use argument " "bucket_name or setting AWS_STORAGE_BUCKET_NAME instead. The bucket " "argument will be removed in version 2.0." ) assert str(w[-1].message) == message def test_deprecated_default_acl(self): with warnings.catch_warnings(record=True) as w: s3boto3.S3Boto3Storage() assert len(w) == 1 message = ( "The default behavior of S3Boto3Storage is insecure and will change " "in django-storages 2.0. By default files and new buckets are saved " "with an ACL of 'public-read' (globally publicly readable). Version 2.0 will " "default to using the bucket's ACL. To opt into the new behavior set " "AWS_DEFAULT_ACL = None, otherwise to silence this warning explicitly " "set AWS_DEFAULT_ACL." ) assert str(w[-1].message) == message def test_deprecated_default_acl_override_class_variable(self): class MyStorage(s3boto3.S3Boto3Storage): default_acl = "private" with warnings.catch_warnings(record=True) as w: MyStorage() assert len(w) == 0

true

1c2fda91b51d903a1fb662774f2ddb659efb16c0

3,680

py

Python

selfdrive/controls/lib/lane_planner.py

azure93/openpilot_079_neokii

7ac7c327527e8ab7a1b9dc42463ce02be81c444d

[ "MIT" ]

null

selfdrive/controls/lib/lane_planner.py

azure93/openpilot_079_neokii

7ac7c327527e8ab7a1b9dc42463ce02be81c444d

[ "MIT" ]

null

selfdrive/controls/lib/lane_planner.py

azure93/openpilot_079_neokii

7ac7c327527e8ab7a1b9dc42463ce02be81c444d

[ "MIT" ]

2

2021-05-19T12:34:17.000Z

2021-06-12T11:32:55.000Z

from common.numpy_fast import interp import numpy as np from cereal import log from selfdrive.ntune import ntune_get CAMERA_OFFSET = 0.06 # m from center car to camera def compute_path_pinv(l=50): deg = 3 x = np.arange(l*1.0) X = np.vstack(tuple(x**n for n in range(deg, -1, -1))).T pinv = np.linalg.pinv(X) return pinv def model_polyfit(points, path_pinv): return np.dot(path_pinv, [float(x) for x in points]) def eval_poly(poly, x): return poly[3] + poly[2]*x + poly[1]*x**2 + poly[0]*x**3 def calc_d_poly(l_poly, r_poly, p_poly, l_prob, r_prob, lane_width, v_ego): # This will improve behaviour when lanes suddenly widen # these numbers were tested on 2000segments and found to work well lane_width = min(4.0, lane_width) width_poly = l_poly - r_poly prob_mods = [] for t_check in [0.0, 1.5, 3.0]: width_at_t = eval_poly(width_poly, t_check * (v_ego + 7)) prob_mods.append(interp(width_at_t, [4.0, 5.0], [1.0, 0.0])) mod = min(prob_mods) l_prob = mod * l_prob r_prob = mod * r_prob path_from_left_lane = l_poly.copy() path_from_left_lane[3] -= lane_width / 2.0 path_from_right_lane = r_poly.copy() path_from_right_lane[3] += lane_width / 2.0 lr_prob = l_prob + r_prob - l_prob * r_prob # neokii if lr_prob > 0.65: lr_prob = min(lr_prob * 1.35, 1.0) d_poly_lane = (l_prob * path_from_left_lane + r_prob * path_from_right_lane) / (l_prob + r_prob + 0.0001) return lr_prob * d_poly_lane + (1.0 - lr_prob) * p_poly class LanePlanner(): def __init__(self): self.l_poly = [0., 0., 0., 0.] self.r_poly = [0., 0., 0., 0.] self.p_poly = [0., 0., 0., 0.] self.d_poly = [0., 0., 0., 0.] self.lane_width_estimate = 3.7 self.lane_width_certainty = 1.0 self.lane_width = 3.7 self.l_prob = 0. self.r_prob = 0. self.l_lane_change_prob = 0. self.r_lane_change_prob = 0. self._path_pinv = compute_path_pinv() self.x_points = np.arange(50) def parse_model(self, md): if len(md.leftLane.poly): self.l_poly = np.array(md.leftLane.poly) self.r_poly = np.array(md.rightLane.poly) self.p_poly = np.array(md.path.poly) else: self.l_poly = model_polyfit(md.leftLane.points, self._path_pinv) # left line self.r_poly = model_polyfit(md.rightLane.points, self._path_pinv) # right line self.p_poly = model_polyfit(md.path.points, self._path_pinv) # predicted path self.l_prob = md.leftLane.prob # left line prob self.r_prob = md.rightLane.prob # right line prob if len(md.meta.desireState): self.l_lane_change_prob = md.meta.desireState[log.PathPlan.Desire.laneChangeLeft - 1] self.r_lane_change_prob = md.meta.desireState[log.PathPlan.Desire.laneChangeRight - 1] def update_d_poly(self, v_ego): # only offset left and right lane lines; offsetting p_poly does not make sense cameraOffset = ntune_get("cameraOffset") self.l_poly[3] += cameraOffset self.r_poly[3] += cameraOffset # Find current lanewidth self.lane_width_certainty += 0.05 * (self.l_prob * self.r_prob - self.lane_width_certainty) current_lane_width = abs(self.l_poly[3] - self.r_poly[3]) self.lane_width_estimate += 0.005 * (current_lane_width - self.lane_width_estimate) speed_lane_width = interp(v_ego, [0., 31.], [2.8, 3.5]) self.lane_width = self.lane_width_certainty * self.lane_width_estimate + \ (1 - self.lane_width_certainty) * speed_lane_width self.d_poly = calc_d_poly(self.l_poly, self.r_poly, self.p_poly, self.l_prob, self.r_prob, self.lane_width, v_ego) def update(self, v_ego, md): self.parse_model(md) self.update_d_poly(v_ego)

33.454545

118

0.682609

from common.numpy_fast import interp import numpy as np from cereal import log from selfdrive.ntune import ntune_get CAMERA_OFFSET = 0.06 def compute_path_pinv(l=50): deg = 3 x = np.arange(l*1.0) X = np.vstack(tuple(x**n for n in range(deg, -1, -1))).T pinv = np.linalg.pinv(X) return pinv def model_polyfit(points, path_pinv): return np.dot(path_pinv, [float(x) for x in points]) def eval_poly(poly, x): return poly[3] + poly[2]*x + poly[1]*x**2 + poly[0]*x**3 def calc_d_poly(l_poly, r_poly, p_poly, l_prob, r_prob, lane_width, v_ego): lane_width = min(4.0, lane_width) width_poly = l_poly - r_poly prob_mods = [] for t_check in [0.0, 1.5, 3.0]: width_at_t = eval_poly(width_poly, t_check * (v_ego + 7)) prob_mods.append(interp(width_at_t, [4.0, 5.0], [1.0, 0.0])) mod = min(prob_mods) l_prob = mod * l_prob r_prob = mod * r_prob path_from_left_lane = l_poly.copy() path_from_left_lane[3] -= lane_width / 2.0 path_from_right_lane = r_poly.copy() path_from_right_lane[3] += lane_width / 2.0 lr_prob = l_prob + r_prob - l_prob * r_prob if lr_prob > 0.65: lr_prob = min(lr_prob * 1.35, 1.0) d_poly_lane = (l_prob * path_from_left_lane + r_prob * path_from_right_lane) / (l_prob + r_prob + 0.0001) return lr_prob * d_poly_lane + (1.0 - lr_prob) * p_poly class LanePlanner(): def __init__(self): self.l_poly = [0., 0., 0., 0.] self.r_poly = [0., 0., 0., 0.] self.p_poly = [0., 0., 0., 0.] self.d_poly = [0., 0., 0., 0.] self.lane_width_estimate = 3.7 self.lane_width_certainty = 1.0 self.lane_width = 3.7 self.l_prob = 0. self.r_prob = 0. self.l_lane_change_prob = 0. self.r_lane_change_prob = 0. self._path_pinv = compute_path_pinv() self.x_points = np.arange(50) def parse_model(self, md): if len(md.leftLane.poly): self.l_poly = np.array(md.leftLane.poly) self.r_poly = np.array(md.rightLane.poly) self.p_poly = np.array(md.path.poly) else: self.l_poly = model_polyfit(md.leftLane.points, self._path_pinv) self.r_poly = model_polyfit(md.rightLane.points, self._path_pinv) self.p_poly = model_polyfit(md.path.points, self._path_pinv) self.l_prob = md.leftLane.prob self.r_prob = md.rightLane.prob if len(md.meta.desireState): self.l_lane_change_prob = md.meta.desireState[log.PathPlan.Desire.laneChangeLeft - 1] self.r_lane_change_prob = md.meta.desireState[log.PathPlan.Desire.laneChangeRight - 1] def update_d_poly(self, v_ego): cameraOffset = ntune_get("cameraOffset") self.l_poly[3] += cameraOffset self.r_poly[3] += cameraOffset self.lane_width_certainty += 0.05 * (self.l_prob * self.r_prob - self.lane_width_certainty) current_lane_width = abs(self.l_poly[3] - self.r_poly[3]) self.lane_width_estimate += 0.005 * (current_lane_width - self.lane_width_estimate) speed_lane_width = interp(v_ego, [0., 31.], [2.8, 3.5]) self.lane_width = self.lane_width_certainty * self.lane_width_estimate + \ (1 - self.lane_width_certainty) * speed_lane_width self.d_poly = calc_d_poly(self.l_poly, self.r_poly, self.p_poly, self.l_prob, self.r_prob, self.lane_width, v_ego) def update(self, v_ego, md): self.parse_model(md) self.update_d_poly(v_ego)

true

1c2fdac8dcd7093d69110e668617a1a1d89c8df3

1,144

py

Python

vsphere/objects_queue.py

SumoLogic/sumologic-vmware

6c19d48b208cec7a69e726dfad0a5e7aa16ad220

[ "Apache-2.0" ]

1

2022-02-12T02:01:09.000Z

vsphere/objects_queue.py

SumoLogic/sumologic-vmware

6c19d48b208cec7a69e726dfad0a5e7aa16ad220

[ "Apache-2.0" ]

null

vsphere/objects_queue.py

SumoLogic/sumologic-vmware

6c19d48b208cec7a69e726dfad0a5e7aa16ad220

[ "Apache-2.0" ]

null

import threading class ObjectsQueue: """ Implements a queue to store Mor objects of any type for each instance. """ def __init__(self): self._objects_queue = {} self._objects_queue_lock = threading.RLock() def fill(self, key, mor_dict): """ Set a dict mapping (resouce_type --> objects[]) for a given key """ with self._objects_queue_lock: self._objects_queue[key] = mor_dict def contains(self, key): with self._objects_queue_lock: return key in self._objects_queue def size(self, key, resource_type): """ Return the size of the queue for a given key and resource type. """ with self._objects_queue_lock: return len(self._objects_queue[key].get(resource_type, [])) def pop(self, key, resource_type): """ Extract an object from the list. If the list is empty, method will return None """ with self._objects_queue_lock: objects = self._objects_queue[key].get(resource_type, []) return objects.pop() if objects else None

30.105263

74

0.611014

import threading class ObjectsQueue: def __init__(self): self._objects_queue = {} self._objects_queue_lock = threading.RLock() def fill(self, key, mor_dict): with self._objects_queue_lock: self._objects_queue[key] = mor_dict def contains(self, key): with self._objects_queue_lock: return key in self._objects_queue def size(self, key, resource_type): with self._objects_queue_lock: return len(self._objects_queue[key].get(resource_type, [])) def pop(self, key, resource_type): with self._objects_queue_lock: objects = self._objects_queue[key].get(resource_type, []) return objects.pop() if objects else None

true

1c2fdade7e9808dec5d8d44a9e50dd624d2cefb4

1,958

py

Python

covsirphy/regression/param_decision_tree.py

ardhanii/covid19-sir

87881963c49a2fc5b6235c8b21269d216acaa941

[ "Apache-2.0" ]

97

2020-05-15T15:20:15.000Z

2022-03-18T02:55:54.000Z

covsirphy/regression/param_decision_tree.py

ardhanii/covid19-sir

87881963c49a2fc5b6235c8b21269d216acaa941

[ "Apache-2.0" ]

970

2020-06-01T13:48:34.000Z

2022-03-29T08:20:49.000Z

covsirphy/regression/param_decision_tree.py

ardhani31/Covid19-SIRV-v3

59d95156b375c41259c46ce4e656b86903f92ec2

[ "Apache-2.0" ]

36

2020-05-15T15:36:43.000Z

2022-02-25T17:59:08.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- from sklearn.decomposition import PCA from sklearn.model_selection import GridSearchCV, TimeSeriesSplit from sklearn.pipeline import Pipeline from sklearn.preprocessing import MinMaxScaler from sklearn.tree import DecisionTreeRegressor from covsirphy.regression.regbase import _RegressorBase from covsirphy.regression.reg_rate_converter import _RateConverter class _ParamDecisionTreeRegressor(_RegressorBase): """ Predict parameter values of ODE models with decision tree regressor. Args: - X_train (pandas.DataFrame): X for training with time index - X_test (pandas.DataFrame): X for test with time index - Y_train (pandas.DataFrame): Y for training with time index - Y_test (pandas.DataFrame): Y for test with time index - X_target (pandas.DataFrame): X for prediction with time index """ # Description of regressor DESC = "Indicators -> Parameters with Decision Tree Regressor" def _fit(self): """ Fit regression model with training dataset, update self._pipeline and self._param. """ # Paramters of the steps param_grid = { "converter__to_convert": [True, False], "pca__n_components": [0.3, 0.5, 0.7, 0.9], "regressor__max_depth": list(range(1, 10)), } # Fit with pipeline steps = [ ("converter", _RateConverter()), ("scaler", MinMaxScaler()), ("pca", PCA(random_state=0)), ("regressor", DecisionTreeRegressor(random_state=0)), ] tscv = TimeSeriesSplit(n_splits=5).split(self._X_train) pipeline = GridSearchCV(Pipeline(steps=steps), param_grid, n_jobs=-1, cv=tscv) pipeline.fit(self._X_train, self._Y_train) # Update regressor self._pipeline = pipeline # Update param self._param.update(**{k: type(v) for (k, v) in steps})

38.392157

90

0.660368

from sklearn.decomposition import PCA from sklearn.model_selection import GridSearchCV, TimeSeriesSplit from sklearn.pipeline import Pipeline from sklearn.preprocessing import MinMaxScaler from sklearn.tree import DecisionTreeRegressor from covsirphy.regression.regbase import _RegressorBase from covsirphy.regression.reg_rate_converter import _RateConverter class _ParamDecisionTreeRegressor(_RegressorBase): DESC = "Indicators -> Parameters with Decision Tree Regressor" def _fit(self): param_grid = { "converter__to_convert": [True, False], "pca__n_components": [0.3, 0.5, 0.7, 0.9], "regressor__max_depth": list(range(1, 10)), } steps = [ ("converter", _RateConverter()), ("scaler", MinMaxScaler()), ("pca", PCA(random_state=0)), ("regressor", DecisionTreeRegressor(random_state=0)), ] tscv = TimeSeriesSplit(n_splits=5).split(self._X_train) pipeline = GridSearchCV(Pipeline(steps=steps), param_grid, n_jobs=-1, cv=tscv) pipeline.fit(self._X_train, self._Y_train) self._pipeline = pipeline self._param.update(**{k: type(v) for (k, v) in steps})

true

1c2fdaeab3d1bc770885a1c1c6fb65b25d46fa6d

29,037

py

Python

lightbus/transports/redis/event.py

apollo13/lightbus

ad9bb5e376e7aabb400d01307345e00fd07e4677

[ "Apache-2.0" ]

null

lightbus/transports/redis/event.py

apollo13/lightbus

ad9bb5e376e7aabb400d01307345e00fd07e4677

[ "Apache-2.0" ]

null

lightbus/transports/redis/event.py

apollo13/lightbus

ad9bb5e376e7aabb400d01307345e00fd07e4677

[ "Apache-2.0" ]

null

import asyncio import logging import time from collections import OrderedDict from datetime import datetime from enum import Enum from typing import ( Mapping, Optional, List, Tuple, Union, Sequence, AsyncGenerator, Iterable, TYPE_CHECKING, ) from aioredis import ConnectionClosedError, ReplyError from aioredis.util import decode from lightbus.transports.base import EventTransport, EventMessage from lightbus.log import LBullets, L, Bold from lightbus.serializers import ByFieldMessageSerializer, ByFieldMessageDeserializer from lightbus.transports.redis.utilities import ( RedisEventMessage, RedisTransportMixin, normalise_since_value, datetime_to_redis_steam_id, redis_stream_id_add_one, redis_stream_id_subtract_one, ) from lightbus.utilities.async_tools import make_exception_checker, cancel from lightbus.utilities.frozendict import frozendict from lightbus.utilities.human import human_time from lightbus.utilities.importing import import_from_string if TYPE_CHECKING: # pylint: disable=unused-import,cyclic-import from lightbus.config import Config from lightbus.client import BusClient logger = logging.getLogger("lightbus.transports.redis") Since = Union[str, datetime, None] class StreamUse(Enum): PER_API = "per_api" PER_EVENT = "per_event" def __eq__(self, other): # pylint: disable=comparison-with-callable if isinstance(other, str): return self.value == other else: return super().__eq__(other) class RedisEventTransport(RedisTransportMixin, EventTransport): """Redis Event Transport For a description of the protocol see https://lightbus.org/reference/protocols/event/ """ def __init__( self, redis_pool=None, *, service_name: str, consumer_name: str, url=None, serializer=ByFieldMessageSerializer(), deserializer=ByFieldMessageDeserializer(RedisEventMessage), connection_parameters: Mapping = frozendict(maxsize=100), batch_size=10, reclaim_batch_size: int = None, acknowledgement_timeout: float = 60, max_stream_length: Optional[int] = 100_000, stream_use: StreamUse = StreamUse.PER_API, consumption_restart_delay: int = 5, consumer_ttl: int = 2_592_000, ): self.set_redis_pool(redis_pool, url, connection_parameters) self.batch_size = batch_size self.reclaim_batch_size = reclaim_batch_size if reclaim_batch_size else batch_size * 10 self.service_name = service_name self.consumer_name = consumer_name self.acknowledgement_timeout = acknowledgement_timeout self.max_stream_length = max_stream_length self.stream_use = stream_use self.consumption_restart_delay = consumption_restart_delay self.consumer_ttl = consumer_ttl super().__init__(serializer=serializer, deserializer=deserializer) @classmethod def from_config( cls, config: "Config", service_name: str = None, consumer_name: str = None, url: str = "redis://127.0.0.1:6379/0", connection_parameters: Mapping = frozendict(maxsize=100), batch_size: int = 10, reclaim_batch_size: int = None, serializer: str = "lightbus.serializers.ByFieldMessageSerializer", deserializer: str = "lightbus.serializers.ByFieldMessageDeserializer", acknowledgement_timeout: float = 60, max_stream_length: Optional[int] = 100_000, stream_use: StreamUse = StreamUse.PER_API, consumption_restart_delay: int = 5, consumer_ttl: int = 2_592_000, ): serializer = import_from_string(serializer)() deserializer = import_from_string(deserializer)(RedisEventMessage) service_name = service_name or config.service_name consumer_name = consumer_name or config.process_name if isinstance(stream_use, str): stream_use = StreamUse[stream_use.upper()] return cls( redis_pool=None, service_name=service_name, consumer_name=consumer_name, url=url, connection_parameters=connection_parameters, batch_size=batch_size, reclaim_batch_size=reclaim_batch_size, serializer=serializer, deserializer=deserializer, acknowledgement_timeout=acknowledgement_timeout, max_stream_length=max_stream_length or None, stream_use=stream_use, consumption_restart_delay=consumption_restart_delay, consumer_ttl=consumer_ttl, ) async def send_event(self, event_message: EventMessage, options: dict, bus_client: "BusClient"): """Publish an event""" stream = self._get_stream_names( listen_for=[(event_message.api_name, event_message.event_name)] )[0] logger.debug( LBullets( L( "Enqueuing event message {} in Redis stream {}", Bold(event_message), Bold(stream), ), items=dict(**event_message.get_metadata(), kwargs=event_message.get_kwargs()), ) ) # Performance: I suspect getting a connection from the connection manager each time is causing # performance issues. Need to confirm. with await self.connection_manager() as redis: start_time = time.time() await redis.xadd( stream=stream, fields=self.serializer(event_message), max_len=self.max_stream_length or None, exact_len=False, ) logger.debug( L( "Enqueued event message {} in Redis in {} stream {}", Bold(event_message.canonical_name), human_time(time.time() - start_time), Bold(stream), ) ) async def consume( self, listen_for: List[Tuple[str, str]], listener_name: str, bus_client: "BusClient", since: Union[Since, Sequence[Since]] = "$", forever=True, ) -> AsyncGenerator[List[RedisEventMessage], None]: """Consume events for the given APIs""" self._sanity_check_listen_for(listen_for) consumer_group = f"{self.service_name}-{listener_name}" if not isinstance(since, (list, tuple)): # Since has been specified as a single value. Normalise it into # the value-per-listener format. since = [since] * len(listen_for) since = map(normalise_since_value, since) stream_names = self._get_stream_names(listen_for) # Keys are stream names, values as the latest ID consumed from that stream streams = OrderedDict(zip(stream_names, since)) expected_events = {event_name for _, event_name in listen_for} logger.debug( LBullets( L( "Consuming events as consumer {} in group {} on streams", Bold(self.consumer_name), Bold(consumer_group), ), items={"{} ({})".format(*v) for v in streams.items()}, ) ) # Cleanup any old groups & consumers await self._cleanup(stream_names) # Here we use a queue to combine messages coming from both the # fetch messages loop and the reclaim messages loop. queue = asyncio.Queue(maxsize=1) async def consume_loop(): """Regular event consuming. See _fetch_new_messages()""" while True: try: async for messages in self._fetch_new_messages( streams, consumer_group, expected_events, forever ): await queue.put(messages) # Wait for the queue to empty before getting trying to get another message await queue.join() except (ConnectionClosedError, ConnectionResetError): # ConnectionClosedError is from aioredis. However, sometimes the connection # can die outside of aioredis, in which case we get a builtin ConnectionResetError. logger.warning( f"Redis connection lost while consuming events, reconnecting " f"in {self.consumption_restart_delay} seconds..." ) await asyncio.sleep(self.consumption_restart_delay) async def reclaim_loop(): """ Reclaim messages which other consumers have failed to processes in reasonable time. See _reclaim_lost_messages() """ await asyncio.sleep(self.acknowledgement_timeout) async for messages in self._reclaim_lost_messages( stream_names, consumer_group, expected_events ): await queue.put(messages) # Wait for the queue to empty before getting trying to get another message await queue.join() consume_task = None reclaim_task = None try: # Run the two above coroutines in their own tasks consume_task = asyncio.ensure_future(consume_loop()) reclaim_task = asyncio.ensure_future(reclaim_loop()) # Make sure we surface any exceptions that occur in either task consume_task.add_done_callback(make_exception_checker(bus_client)) reclaim_task.add_done_callback(make_exception_checker(bus_client)) while True: try: messages = await queue.get() yield messages queue.task_done() except GeneratorExit: return finally: # Make sure we cleanup the tasks we created await cancel(consume_task, reclaim_task) async def _fetch_new_messages( self, streams, consumer_group, expected_events, forever ) -> AsyncGenerator[List[EventMessage], None]: """Coroutine to consume new messages The consumption has two stages: 1. Fetch and yield any messages this consumer is responsible for processing but has yet to successfully process. This can happen in cases where a message was previously consumed but not acknowledged (i.e. due to an error). This is a one-off startup stage. 2. Wait for new messages to arrive. Yield these messages when they arrive, then resume waiting for messages See Also: _reclaim_lost_messages() - Another coroutine which reclaims messages which timed out while being processed by other consumers in this group """ with await self.connection_manager() as redis: # Firstly create the consumer group if we need to await self._create_consumer_groups(streams, redis, consumer_group) # Get any messages that this consumer has yet to process. # This can happen in the case where the processes died before acknowledging. pending_messages = await redis.xread_group( group_name=consumer_group, consumer_name=self.consumer_name, streams=list(streams.keys()), # Using ID '0' indicates we want unacked pending messages latest_ids=["0"] * len(streams), timeout=None, # Don't block, return immediately ) event_messages = [] for stream, message_id, fields in pending_messages: message_id = decode(message_id, "utf8") stream = decode(stream, "utf8") event_message = self._fields_to_message( fields, expected_events, stream=stream, native_id=message_id, consumer_group=consumer_group, ) if not event_message: # noop message, or message an event we don't care about continue logger.debug( LBullets( L( "⬅ Receiving pending event {} on stream {}", Bold(message_id), Bold(stream), ), items=dict( **event_message.get_metadata(), kwargs=event_message.get_kwargs() ), ) ) event_messages.append(event_message) if event_messages: yield event_messages # We've now cleaned up any old messages that were hanging around. # Now we get on to the main loop which blocks and waits for new messages while True: # Fetch some messages. # This will block until there are some messages available stream_messages = await redis.xread_group( group_name=consumer_group, consumer_name=self.consumer_name, streams=list(streams.keys()), # Using ID '>' indicates we only want new messages which have not # been passed to other consumers in this group latest_ids=[">"] * len(streams), count=self.batch_size, ) # Handle the messages we have received event_messages = [] for stream, message_id, fields in stream_messages: message_id = decode(message_id, "utf8") stream = decode(stream, "utf8") event_message = self._fields_to_message( fields, expected_events, stream=stream, native_id=message_id, consumer_group=consumer_group, ) if not event_message: # noop message, or message an event we don't care about continue logger.debug( LBullets( L( "⬅ Received new event {} on stream {}", Bold(message_id), Bold(stream), ), items=dict( **event_message.get_metadata(), kwargs=event_message.get_kwargs() ), ) ) # NOTE: YIELD ALL MESSAGES, NOT JUST ONE event_messages.append(event_message) if event_messages: yield event_messages if not forever: return async def _reclaim_lost_messages( self, stream_names: List[str], consumer_group: str, expected_events: set ) -> AsyncGenerator[List[EventMessage], None]: """Reclaim batches of messages that other consumers in the group failed to acknowledge within a timeout. The timeout period is specified by the `acknowledgement_timeout` option. """ with await self.connection_manager() as redis: for stream in stream_names: old_messages = True reclaim_from = None # Keep pulling reclaimable messages from Redis until there are none left while old_messages: # reclaim_from keeps track of where we are up to in our fetching # of messages if not reclaim_from: # This is our first iteration, so fetch from the start of time reclaim_from = "-" else: # This is a subsequent iteration. XPENDING's 'start' parameter is inclusive, # so we need to add one to the reclaim_from value to ensure we don't get a message # we've already seen reclaim_from = redis_stream_id_add_one(reclaim_from) # Fetch the next batch of messages old_messages = await redis.xpending( stream, consumer_group, reclaim_from, "+", count=self.reclaim_batch_size ) timeout = self.acknowledgement_timeout * 1000 event_messages = [] # Try to claim each messages for ( message_id, consumer_name, ms_since_last_delivery, num_deliveries, ) in old_messages: message_id = decode(message_id, "utf8") consumer_name = decode(consumer_name, "utf8") reclaim_from = message_id # This 'if' is not strictly required as the subsequent call to xclaim # will honor the timeout parameter. However, using this if here allows # for more sane logging from the point of view of the user. Without it # we would report that we were trying to claim messages which were # clearly not timed out yet. if ms_since_last_delivery > timeout: logger.info( L( "Found timed out event {} in stream {}. Abandoned by {}. Attempting to reclaim...", Bold(message_id), Bold(stream), Bold(consumer_name), ) ) # *Try* to claim the messages... result = await redis.xclaim( stream, consumer_group, self.consumer_name, int(timeout), message_id ) # Parse each message we managed to claim for claimed_message_id, fields in result: claimed_message_id = decode(claimed_message_id, "utf8") event_message = self._fields_to_message( fields, expected_events, stream=stream, native_id=claimed_message_id, consumer_group=consumer_group, ) if not event_message: # noop message, or message an event we don't care about continue logger.debug( LBullets( L( "⬅ Reclaimed timed out event {} on stream {}. Abandoned by {}.", Bold(message_id), Bold(stream), Bold(consumer_name), ), items=dict( **event_message.get_metadata(), kwargs=event_message.get_kwargs(), ), ) ) event_messages.append(event_message) # And yield our batch of messages if event_messages: yield event_messages async def acknowledge(self, *event_messages: RedisEventMessage, bus_client: "BusClient"): """Acknowledge that a message has been successfully processed """ with await self.connection_manager() as redis: p = redis.pipeline() for event_message in event_messages: p.xack(event_message.stream, event_message.consumer_group, event_message.native_id) logging.debug( f"Preparing to acknowledge message {event_message.id} (Native ID: {event_message.native_id})" ) logger.debug( f"Batch acknowledging successful processing of {len(event_messages)} message." ) await p.execute() async def history( self, api_name, event_name, start: datetime = None, stop: datetime = None, start_inclusive: bool = True, batch_size: int = 100, ) -> AsyncGenerator[EventMessage, None]: """Retrieve historical events for the given API Will not have any impact on existing consumer groups. """ redis_start = datetime_to_redis_steam_id(start) if start else "-" redis_stop = datetime_to_redis_steam_id(stop) if stop else "+" if start and not start_inclusive: redis_start = redis_stream_id_add_one(redis_start) stream_name = self._get_stream_names([(api_name, event_name)])[0] logger.debug( f"Getting history for stream {stream_name} from {redis_start} ({start}) " f"to {redis_stop} ({stop}) in batches of {batch_size}" ) with await self.connection_manager() as redis: messages = True while messages: messages = await redis.xrevrange( stream_name, redis_stop, redis_start, count=batch_size ) if not messages: return for message_id, fields in messages: message_id = decode(message_id, "utf8") redis_stop = redis_stream_id_subtract_one(message_id) event_message = self._fields_to_message( fields, expected_event_names={event_name}, stream=stream_name, native_id=message_id, consumer_group=None, ) if event_message: yield event_message async def _create_consumer_groups(self, streams, redis, consumer_group): """Ensure the consumer groups exist This is means we have to ensure the streams exist too """ for stream, since in streams.items(): if not await redis.exists(stream): # Add a noop to ensure the stream exists # TODO: We can now use MKSTREAM, change this logic # Documented here: https://redis.io/topics/streams-intro await redis.xadd(stream, fields={"": ""}) try: # Create the group (it may already exist) await redis.xgroup_create(stream, consumer_group, latest_id=since) except ReplyError as e: if "BUSYGROUP" in str(e): # Already exists pass else: raise async def _cleanup(self, stream_names: List[str]): """Cleanup old consumers and groups A group will be deleted if it contains no consumers. A consumer will be deleted if it has been idle for more than consumer_ttl. """ if not self.consumer_ttl: # Don't do the cleanup if no TTL is given, consider this to mean # cleanup is disabled return with await self.connection_manager() as redis: # For every stream key... for stream_name in stream_names: consumers: List[Tuple[str, str]] = [] # Get all the groups for that key... try: groups = await redis.xinfo_groups(stream_name) except ReplyError as e: if "ERR no such key" in str(e): # Steam doesn't exist yet groups = [] else: raise for group in groups: active_consumers = 0 group_name = group[b"name"] # Get all the consumers for that group for consumer in await redis.xinfo_consumers(stream_name, group_name): consumer_name = consumer[b"name"] idle_seconds = consumer[b"idle"] / 1000 # And delete the consumer if they have not re-started # listening for self.consumer_ttl seconds if idle_seconds >= self.consumer_ttl: logger.debug( f"Cleaning up consumer {consumer_name} in group {group_name} on stream {stream_name}. " f"The consumer has been idle for {idle_seconds} seconds, which is more than the " f"consumer TTL of {self.consumer_ttl}" ) await redis.xgroup_delconsumer(stream_name, group_name, consumer_name) else: active_consumers += 1 # If no active consumers were found for this group, then delete the entire group # on the grounds that it is no longer used and can be cleaned up. if not active_consumers: # We do this atomically using a lua script. This avoids race conditions # whereby a new consumer comes into existence the moment before we delete the group try: await redis.eval( ATOMIC_DESTROY_CONSUMER_GROUP, [stream_name], [group_name] ) except ReplyError as e: if "NOGROUP" in str(e): # Already deleted pass def _fields_to_message( self, fields: dict, expected_event_names: Iterable[str], stream: str, native_id: str, consumer_group: Optional[str], ) -> Optional[RedisEventMessage]: """Convert a dict of Redis message fields into a RedisEventMessage""" if tuple(fields.items()) == ((b"", b""),): # Is a noop message, ignore return None message = self.deserializer( fields, stream=stream, native_id=native_id, consumer_group=consumer_group ) want_message = ("*" in expected_event_names) or (message.event_name in expected_event_names) if self.stream_use == StreamUse.PER_API and not want_message: # Only care about events we are listening for. If we have one stream # per API then we're probably going to receive some events we don't care about. logger.debug( f"Ignoring message for unneeded event: {message}. " f"Only listening for {', '.join(expected_event_names)}" ) return None return message def _get_stream_names(self, listen_for): """Convert a list of api names & event names into stream names The format of these names will vary based on the stream_use setting. """ stream_names = [] for api_name, event_name in listen_for: if self.stream_use == StreamUse.PER_EVENT: stream_name = f"{api_name}.{event_name}:stream" elif self.stream_use == StreamUse.PER_API: stream_name = f"{api_name}.*:stream" else: raise ValueError( "Invalid value for stream_use config option. This should have been caught " "during config validation." ) if stream_name not in stream_names: stream_names.append(stream_name) return stream_names # See RedisEventTransport._cleanup() ATOMIC_DESTROY_CONSUMER_GROUP = """ local stream_name = KEYS[1] local group_name = ARGV[1] local consumers = redis.call('xinfo', 'consumers', stream_name, group_name) if table.getn(consumers) == 0 then redis.call('xgroup', 'destroy', stream_name, group_name) end """

41.719828

119

0.5431

import asyncio import logging import time from collections import OrderedDict from datetime import datetime from enum import Enum from typing import ( Mapping, Optional, List, Tuple, Union, Sequence, AsyncGenerator, Iterable, TYPE_CHECKING, ) from aioredis import ConnectionClosedError, ReplyError from aioredis.util import decode from lightbus.transports.base import EventTransport, EventMessage from lightbus.log import LBullets, L, Bold from lightbus.serializers import ByFieldMessageSerializer, ByFieldMessageDeserializer from lightbus.transports.redis.utilities import ( RedisEventMessage, RedisTransportMixin, normalise_since_value, datetime_to_redis_steam_id, redis_stream_id_add_one, redis_stream_id_subtract_one, ) from lightbus.utilities.async_tools import make_exception_checker, cancel from lightbus.utilities.frozendict import frozendict from lightbus.utilities.human import human_time from lightbus.utilities.importing import import_from_string if TYPE_CHECKING: from lightbus.config import Config from lightbus.client import BusClient logger = logging.getLogger("lightbus.transports.redis") Since = Union[str, datetime, None] class StreamUse(Enum): PER_API = "per_api" PER_EVENT = "per_event" def __eq__(self, other): if isinstance(other, str): return self.value == other else: return super().__eq__(other) class RedisEventTransport(RedisTransportMixin, EventTransport): def __init__( self, redis_pool=None, *, service_name: str, consumer_name: str, url=None, serializer=ByFieldMessageSerializer(), deserializer=ByFieldMessageDeserializer(RedisEventMessage), connection_parameters: Mapping = frozendict(maxsize=100), batch_size=10, reclaim_batch_size: int = None, acknowledgement_timeout: float = 60, max_stream_length: Optional[int] = 100_000, stream_use: StreamUse = StreamUse.PER_API, consumption_restart_delay: int = 5, consumer_ttl: int = 2_592_000, ): self.set_redis_pool(redis_pool, url, connection_parameters) self.batch_size = batch_size self.reclaim_batch_size = reclaim_batch_size if reclaim_batch_size else batch_size * 10 self.service_name = service_name self.consumer_name = consumer_name self.acknowledgement_timeout = acknowledgement_timeout self.max_stream_length = max_stream_length self.stream_use = stream_use self.consumption_restart_delay = consumption_restart_delay self.consumer_ttl = consumer_ttl super().__init__(serializer=serializer, deserializer=deserializer) @classmethod def from_config( cls, config: "Config", service_name: str = None, consumer_name: str = None, url: str = "redis://127.0.0.1:6379/0", connection_parameters: Mapping = frozendict(maxsize=100), batch_size: int = 10, reclaim_batch_size: int = None, serializer: str = "lightbus.serializers.ByFieldMessageSerializer", deserializer: str = "lightbus.serializers.ByFieldMessageDeserializer", acknowledgement_timeout: float = 60, max_stream_length: Optional[int] = 100_000, stream_use: StreamUse = StreamUse.PER_API, consumption_restart_delay: int = 5, consumer_ttl: int = 2_592_000, ): serializer = import_from_string(serializer)() deserializer = import_from_string(deserializer)(RedisEventMessage) service_name = service_name or config.service_name consumer_name = consumer_name or config.process_name if isinstance(stream_use, str): stream_use = StreamUse[stream_use.upper()] return cls( redis_pool=None, service_name=service_name, consumer_name=consumer_name, url=url, connection_parameters=connection_parameters, batch_size=batch_size, reclaim_batch_size=reclaim_batch_size, serializer=serializer, deserializer=deserializer, acknowledgement_timeout=acknowledgement_timeout, max_stream_length=max_stream_length or None, stream_use=stream_use, consumption_restart_delay=consumption_restart_delay, consumer_ttl=consumer_ttl, ) async def send_event(self, event_message: EventMessage, options: dict, bus_client: "BusClient"): stream = self._get_stream_names( listen_for=[(event_message.api_name, event_message.event_name)] )[0] logger.debug( LBullets( L( "Enqueuing event message {} in Redis stream {}", Bold(event_message), Bold(stream), ), items=dict(**event_message.get_metadata(), kwargs=event_message.get_kwargs()), ) ) with await self.connection_manager() as redis: start_time = time.time() await redis.xadd( stream=stream, fields=self.serializer(event_message), max_len=self.max_stream_length or None, exact_len=False, ) logger.debug( L( "Enqueued event message {} in Redis in {} stream {}", Bold(event_message.canonical_name), human_time(time.time() - start_time), Bold(stream), ) ) async def consume( self, listen_for: List[Tuple[str, str]], listener_name: str, bus_client: "BusClient", since: Union[Since, Sequence[Since]] = "$", forever=True, ) -> AsyncGenerator[List[RedisEventMessage], None]: self._sanity_check_listen_for(listen_for) consumer_group = f"{self.service_name}-{listener_name}" if not isinstance(since, (list, tuple)): since = [since] * len(listen_for) since = map(normalise_since_value, since) stream_names = self._get_stream_names(listen_for) streams = OrderedDict(zip(stream_names, since)) expected_events = {event_name for _, event_name in listen_for} logger.debug( LBullets( L( "Consuming events as consumer {} in group {} on streams", Bold(self.consumer_name), Bold(consumer_group), ), items={"{} ({})".format(*v) for v in streams.items()}, ) ) await self._cleanup(stream_names) queue = asyncio.Queue(maxsize=1) async def consume_loop(): while True: try: async for messages in self._fetch_new_messages( streams, consumer_group, expected_events, forever ): await queue.put(messages) await queue.join() except (ConnectionClosedError, ConnectionResetError): logger.warning( f"Redis connection lost while consuming events, reconnecting " f"in {self.consumption_restart_delay} seconds..." ) await asyncio.sleep(self.consumption_restart_delay) async def reclaim_loop(): await asyncio.sleep(self.acknowledgement_timeout) async for messages in self._reclaim_lost_messages( stream_names, consumer_group, expected_events ): await queue.put(messages) await queue.join() consume_task = None reclaim_task = None try: consume_task = asyncio.ensure_future(consume_loop()) reclaim_task = asyncio.ensure_future(reclaim_loop()) consume_task.add_done_callback(make_exception_checker(bus_client)) reclaim_task.add_done_callback(make_exception_checker(bus_client)) while True: try: messages = await queue.get() yield messages queue.task_done() except GeneratorExit: return finally: await cancel(consume_task, reclaim_task) async def _fetch_new_messages( self, streams, consumer_group, expected_events, forever ) -> AsyncGenerator[List[EventMessage], None]: with await self.connection_manager() as redis: await self._create_consumer_groups(streams, redis, consumer_group) pending_messages = await redis.xread_group( group_name=consumer_group, consumer_name=self.consumer_name, streams=list(streams.keys()), latest_ids=["0"] * len(streams), timeout=None, ) event_messages = [] for stream, message_id, fields in pending_messages: message_id = decode(message_id, "utf8") stream = decode(stream, "utf8") event_message = self._fields_to_message( fields, expected_events, stream=stream, native_id=message_id, consumer_group=consumer_group, ) if not event_message: # noop message, or message an event we don't care about continue logger.debug( LBullets( L( "⬅ Receiving pending event {} on stream {}", Bold(message_id), Bold(stream), ), items=dict( **event_message.get_metadata(), kwargs=event_message.get_kwargs() ), ) ) event_messages.append(event_message) if event_messages: yield event_messages # Now we get on to the main loop which blocks and waits for new messages while True: # Fetch some messages. # This will block until there are some messages available stream_messages = await redis.xread_group( group_name=consumer_group, consumer_name=self.consumer_name, streams=list(streams.keys()), # Using ID '>' indicates we only want new messages which have not # been passed to other consumers in this group latest_ids=[">"] * len(streams), count=self.batch_size, ) # Handle the messages we have received event_messages = [] for stream, message_id, fields in stream_messages: message_id = decode(message_id, "utf8") stream = decode(stream, "utf8") event_message = self._fields_to_message( fields, expected_events, stream=stream, native_id=message_id, consumer_group=consumer_group, ) if not event_message: # noop message, or message an event we don't care about continue logger.debug( LBullets( L( "⬅ Received new event {} on stream {}", Bold(message_id), Bold(stream), ), items=dict( **event_message.get_metadata(), kwargs=event_message.get_kwargs() ), ) ) event_messages.append(event_message) if event_messages: yield event_messages if not forever: return async def _reclaim_lost_messages( self, stream_names: List[str], consumer_group: str, expected_events: set ) -> AsyncGenerator[List[EventMessage], None]: with await self.connection_manager() as redis: for stream in stream_names: old_messages = True reclaim_from = None while old_messages: if not reclaim_from: reclaim_from = "-" else: # so we need to add one to the reclaim_from value to ensure we don't get a message reclaim_from = redis_stream_id_add_one(reclaim_from) # Fetch the next batch of messages old_messages = await redis.xpending( stream, consumer_group, reclaim_from, "+", count=self.reclaim_batch_size ) timeout = self.acknowledgement_timeout * 1000 event_messages = [] # Try to claim each messages for ( message_id, consumer_name, ms_since_last_delivery, num_deliveries, ) in old_messages: message_id = decode(message_id, "utf8") consumer_name = decode(consumer_name, "utf8") reclaim_from = message_id # This 'if' is not strictly required as the subsequent call to xclaim # will honor the timeout parameter. However, using this if here allows # for more sane logging from the point of view of the user. Without it # we would report that we were trying to claim messages which were # clearly not timed out yet. if ms_since_last_delivery > timeout: logger.info( L( "Found timed out event {} in stream {}. Abandoned by {}. Attempting to reclaim...", Bold(message_id), Bold(stream), Bold(consumer_name), ) ) # *Try* to claim the messages... result = await redis.xclaim( stream, consumer_group, self.consumer_name, int(timeout), message_id ) # Parse each message we managed to claim for claimed_message_id, fields in result: claimed_message_id = decode(claimed_message_id, "utf8") event_message = self._fields_to_message( fields, expected_events, stream=stream, native_id=claimed_message_id, consumer_group=consumer_group, ) if not event_message: # noop message, or message an event we don't care about continue logger.debug( LBullets( L( "⬅ Reclaimed timed out event {} on stream {}. Abandoned by {}.", Bold(message_id), Bold(stream), Bold(consumer_name), ), items=dict( **event_message.get_metadata(), kwargs=event_message.get_kwargs(), ), ) ) event_messages.append(event_message) if event_messages: yield event_messages async def acknowledge(self, *event_messages: RedisEventMessage, bus_client: "BusClient"): with await self.connection_manager() as redis: p = redis.pipeline() for event_message in event_messages: p.xack(event_message.stream, event_message.consumer_group, event_message.native_id) logging.debug( f"Preparing to acknowledge message {event_message.id} (Native ID: {event_message.native_id})" ) logger.debug( f"Batch acknowledging successful processing of {len(event_messages)} message." ) await p.execute() async def history( self, api_name, event_name, start: datetime = None, stop: datetime = None, start_inclusive: bool = True, batch_size: int = 100, ) -> AsyncGenerator[EventMessage, None]: redis_start = datetime_to_redis_steam_id(start) if start else "-" redis_stop = datetime_to_redis_steam_id(stop) if stop else "+" if start and not start_inclusive: redis_start = redis_stream_id_add_one(redis_start) stream_name = self._get_stream_names([(api_name, event_name)])[0] logger.debug( f"Getting history for stream {stream_name} from {redis_start} ({start}) " f"to {redis_stop} ({stop}) in batches of {batch_size}" ) with await self.connection_manager() as redis: messages = True while messages: messages = await redis.xrevrange( stream_name, redis_stop, redis_start, count=batch_size ) if not messages: return for message_id, fields in messages: message_id = decode(message_id, "utf8") redis_stop = redis_stream_id_subtract_one(message_id) event_message = self._fields_to_message( fields, expected_event_names={event_name}, stream=stream_name, native_id=message_id, consumer_group=None, ) if event_message: yield event_message async def _create_consumer_groups(self, streams, redis, consumer_group): for stream, since in streams.items(): if not await redis.exists(stream): await redis.xadd(stream, fields={"": ""}) try: await redis.xgroup_create(stream, consumer_group, latest_id=since) except ReplyError as e: if "BUSYGROUP" in str(e): pass else: raise async def _cleanup(self, stream_names: List[str]): if not self.consumer_ttl: # cleanup is disabled return with await self.connection_manager() as redis: # For every stream key... for stream_name in stream_names: consumers: List[Tuple[str, str]] = [] # Get all the groups for that key... try: groups = await redis.xinfo_groups(stream_name) except ReplyError as e: if "ERR no such key" in str(e): # Steam doesn't exist yet groups = [] else: raise for group in groups: active_consumers = 0 group_name = group[b"name"] for consumer in await redis.xinfo_consumers(stream_name, group_name): consumer_name = consumer[b"name"] idle_seconds = consumer[b"idle"] / 1000 if idle_seconds >= self.consumer_ttl: logger.debug( f"Cleaning up consumer {consumer_name} in group {group_name} on stream {stream_name}. " f"The consumer has been idle for {idle_seconds} seconds, which is more than the " f"consumer TTL of {self.consumer_ttl}" ) await redis.xgroup_delconsumer(stream_name, group_name, consumer_name) else: active_consumers += 1 if not active_consumers: try: await redis.eval( ATOMIC_DESTROY_CONSUMER_GROUP, [stream_name], [group_name] ) except ReplyError as e: if "NOGROUP" in str(e): pass def _fields_to_message( self, fields: dict, expected_event_names: Iterable[str], stream: str, native_id: str, consumer_group: Optional[str], ) -> Optional[RedisEventMessage]: if tuple(fields.items()) == ((b"", b""),): return None message = self.deserializer( fields, stream=stream, native_id=native_id, consumer_group=consumer_group ) want_message = ("*" in expected_event_names) or (message.event_name in expected_event_names) if self.stream_use == StreamUse.PER_API and not want_message: logger.debug( f"Ignoring message for unneeded event: {message}. " f"Only listening for {', '.join(expected_event_names)}" ) return None return message def _get_stream_names(self, listen_for): stream_names = [] for api_name, event_name in listen_for: if self.stream_use == StreamUse.PER_EVENT: stream_name = f"{api_name}.{event_name}:stream" elif self.stream_use == StreamUse.PER_API: stream_name = f"{api_name}.*:stream" else: raise ValueError( "Invalid value for stream_use config option. This should have been caught " "during config validation." ) if stream_name not in stream_names: stream_names.append(stream_name) return stream_names ATOMIC_DESTROY_CONSUMER_GROUP = """ local stream_name = KEYS[1] local group_name = ARGV[1] local consumers = redis.call('xinfo', 'consumers', stream_name, group_name) if table.getn(consumers) == 0 then redis.call('xgroup', 'destroy', stream_name, group_name) end """

true

1c2fdb0210a8225d09724a1dc46d1be23dc02305

1,206

py

Python

twkit/__init__.py

evaperon/twAwler

8e9f2064cad846177ed6547b9f56f053226a2d5e

[ "Apache-2.0" ]

5

2018-12-06T16:14:14.000Z

2020-05-22T07:36:45.000Z

twkit/__init__.py

evaperon/twAwler

8e9f2064cad846177ed6547b9f56f053226a2d5e

[ "Apache-2.0" ]

null

twkit/__init__.py

evaperon/twAwler

8e9f2064cad846177ed6547b9f56f053226a2d5e

[ "Apache-2.0" ]

3

2020-04-20T07:20:18.000Z

2021-08-19T17:31:38.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- ########################################### # (c) 2016-2020 Polyvios Pratikakis # polyvios@ics.forth.gr ########################################### """A library for crawling twitter and analyzing crawled tweets and relations. By Polyvios Pratikakis <polyvios@ics.forth.gr>. For support, use the github repository contact methods (https://www.github.com/polyvios/twAwler). Currently extracts 6 kinds of relations: * follow: unweighted, directed graph * favorite: weighted, directed graph * reply: weighted, directed graph * retweet: weighted, directed graph * quote: weighted, directed graph * listsim: weighted, undirected graph * avatar: undirected graph Currently extracts around 2000 features per user. """ __author__ = 'Polyvios Pratikakis' __email__ = 'polyvios@ics.forth.gr' __copyright__ = ''' Copyright (c) 2016-present Polyvios Pratikakis, FORTH. All rights reserved.''' __license__ = 'Apache License 2.0' __version__ = '0.0.3' __url__ = 'https://github.com/polyvios/twAwler' __description__ = 'A Twitter API crawler and feature extraction library' from twkit.utils import init_state, verbose

32.594595

78

0.677446

true

1c2fdbc47064bff8c963b841458330ffba157b64

273

py

Python

topCoder/srms/200s/srm209/div2/moving_averages.py

gauravsingh58/algo

397859a53429e7a585e5f6964ad24146c6261326

[ "WTFPL" ]

1

2020-09-30T19:53:08.000Z

topCoder/srms/200s/srm209/div2/moving_averages.py

gauravsingh58/algo

397859a53429e7a585e5f6964ad24146c6261326

[ "WTFPL" ]

null

topCoder/srms/200s/srm209/div2/moving_averages.py

gauravsingh58/algo

397859a53429e7a585e5f6964ad24146c6261326

[ "WTFPL" ]

1

2020-10-15T09:10:57.000Z

class MovingAverages: def calculate(self, times, n): def as_second(s): h, m, s = map(int, s.split(':')) return h * 3600 + m * 60 + s s = map(as_second, times) return map(lambda i: sum(s[i:i+n])/n, xrange(len(times)-n+1))

34.125

69

0.520147

class MovingAverages: def calculate(self, times, n): def as_second(s): h, m, s = map(int, s.split(':')) return h * 3600 + m * 60 + s s = map(as_second, times) return map(lambda i: sum(s[i:i+n])/n, xrange(len(times)-n+1))

true

1c2fdd77a2b8772f3f77fe224a8336b4a07e1707

7,571

py

Python

tests_unit/test__init__.py

daltonmatos/BarterDude

9f7eb049711d688d61061036e886c33d855e563a

[ "Apache-2.0" ]

12

2020-02-14T20:30:38.000Z

2022-03-08T17:53:55.000Z

tests_unit/test__init__.py

daltonmatos/BarterDude

9f7eb049711d688d61061036e886c33d855e563a

[ "Apache-2.0" ]

11

2020-02-29T15:06:25.000Z

2021-05-03T15:23:12.000Z

tests_unit/test__init__.py

daltonmatos/BarterDude

9f7eb049711d688d61061036e886c33d855e563a

[ "Apache-2.0" ]

3

2020-02-28T20:43:11.000Z

2022-02-07T21:56:34.000Z

from asynctest import Mock, TestCase, CoroutineMock, patch, call from asyncworker import Options, RouteTypes from barterdude import BarterDude from barterdude.message import Message from tests_unit.helpers import load_fixture class TestBarterDude(TestCase): @patch("barterdude.App") @patch("barterdude.AMQPConnection") def setUp(self, AMQPConnection, App): self.monitor = Mock() self.monitor.dispatch_before_consume = CoroutineMock() self.monitor.dispatch_on_success = CoroutineMock() self.monitor.dispatch_on_fail = CoroutineMock() self.callback = CoroutineMock() self.messages = [Mock(value=i) for i in range(10)] self.calls = [call(message) for message in self.messages] self.AMQPConnection = AMQPConnection self.connection = self.AMQPConnection.return_value self.App = App self.app = self.App.return_value self.app.startup = CoroutineMock() self.app.shutdown = CoroutineMock() self.decorator = self.app.route.return_value self.schema = load_fixture("schema.json") self.barterdude = BarterDude() def test_should_create_connection(self): self.AMQPConnection.assert_called_once_with( # nosec hostname="127.0.0.1", username="guest", password="guest", prefetch=10, name="default", ) self.App.assert_called_once_with(connections=[self.connection]) def test_should_call_route_when_created(self): monitor = Mock() self.barterdude.consume_amqp( ["queue"], monitor=monitor )(CoroutineMock()) self.app.route.assert_called_once_with( ["queue"], type=RouteTypes.AMQP_RABBITMQ, options={ Options.BULK_SIZE: 10, Options.BULK_FLUSH_INTERVAL: 60, Options.CONNECTION_FAIL_CALLBACK: monitor.dispatch_on_connection_fail, } ) def test_should_call_route_when_adding_endpoint(self): hook = Mock() self.barterdude.add_endpoint(['/my_route'], ['GET'], hook) self.app.route.assert_called_once_with( routes=['/my_route'], methods=['GET'], type=RouteTypes.HTTP ) self.decorator.assert_called_once_with(hook) async def test_should_call_callback_for_each_message(self): self.barterdude.consume_amqp(["queue"], self.monitor)(self.callback) self.decorator.assert_called_once() wrapper = self.decorator.call_args[0][0] await wrapper(self.messages) messages = [] for message in self.callback.mock_calls: self.assertEqual(Message, type(message[1][0])) messages.append(message[1][0]._message) self.assertListEqual( sorted(messages, key=lambda x: x.value), sorted(self.messages, key=lambda x: x.value)) async def test_should_call_reject_when_callback_fail(self): self.callback.side_effect = Exception('Boom!') self.barterdude.consume_amqp(["queue"], self.monitor)(self.callback) wrapper = self.decorator.call_args[0][0] await wrapper(self.messages) for message in self.messages: message.reject.assert_called_once() async def test_should_call_monitor_for_each_success_message(self): self.barterdude.consume_amqp(["queue"], self.monitor)(self.callback) wrapper = self.decorator.call_args[0][0] await wrapper(self.messages) self.monitor.dispatch_before_consume.assert_has_calls( self.calls, any_order=True) self.monitor.dispatch_on_success.assert_has_calls( self.calls, any_order=True) self.monitor.dispatch_on_fail.assert_not_called() async def test_should_call_callback_for_valid_message(self): self.barterdude.consume_amqp( ["queue"], self.monitor, validation_schema=self.schema )(self.callback) self.decorator.assert_called_once() wrapper = self.decorator.call_args[0][0] message = Mock(Message) message.body = {"key": 'ok'} await wrapper([message]) self.callback.assert_called_once() self.assertEqual( self.callback.await_args[0][0].body["key"], message.body["key"] ) async def test_should_not_call_callback_for_valid_message(self): self.barterdude.consume_amqp( ["queue"], self.monitor, validation_schema=self.schema )(self.callback) self.decorator.assert_called_once() wrapper = self.decorator.call_args[0][0] message = Mock(Message) message.body = {"wrong": 'ok'} await wrapper([message]) self.callback.assert_not_called() async def test_should_call_monitor_for_each_fail_message(self): error = Exception('Boom!') self.callback.side_effect = error self.barterdude.consume_amqp(["queue"], self.monitor)(self.callback) wrapper = self.decorator.call_args[0][0] await wrapper(self.messages) self.monitor.dispatch_before_consume.assert_has_calls( self.calls, any_order=True) error_calls = [call(message, error) for message in self.messages] self.monitor.dispatch_on_fail.assert_has_calls( error_calls, any_order=True) self.monitor.dispatch_on_success.assert_not_called() async def test_should_call_put_when_publish(self): data = Mock() self.connection.put = CoroutineMock() await self.barterdude.publish_amqp( 'exchange', data, vhost="vhost", routing_key="routing_key" ) self.connection.put.assert_called_once_with( exchange='exchange', data=data, vhost="vhost", routing_key="routing_key", properties=None ) async def test_should_call_startup_and_shutdown(self): await self.barterdude.startup() self.app.startup.assert_called_once_with() await self.barterdude.shutdown() self.app.shutdown.assert_called_once_with() def test_should_call_run(self): self.barterdude.run() self.app.run.assert_called_once_with() class TestAppSharedProperties(TestCase): def setUp(self): self.barterdude = BarterDude() def test_setitem_changes_state(self): self.barterdude["foo"] = foo = Mock() self.assertEqual(foo, self.barterdude["foo"]) async def test_getitem_returns_internal_state_value(self): self.barterdude["foo"] = "bar" self.assertEqual("bar", self.barterdude["foo"]) def test_delitem_changes_state(self): self.barterdude["foo"] = foo = Mock() self.assertEqual(foo, self.barterdude["foo"]) del self.barterdude["foo"] with self.assertRaises(KeyError): self.assertIsNone(self.barterdude["foo"]) def test_len_returns_state_len(self): test_data = {"foo": 1, "bar": 2} for k, v in test_data.items(): self.barterdude[k] = v self.assertEqual( len(self.barterdude), len(dict(self.barterdude._BarterDude__app)) ) async def test_iter_iters_through_internal_state_value(self): test_data = {"foo": 1, "bar": 2} for k, v in test_data.items(): self.barterdude[k] = v state = dict(**self.barterdude) self.assertDictContainsSubset(test_data, state)

37.666667

76

0.645093

from asynctest import Mock, TestCase, CoroutineMock, patch, call from asyncworker import Options, RouteTypes from barterdude import BarterDude from barterdude.message import Message from tests_unit.helpers import load_fixture class TestBarterDude(TestCase): @patch("barterdude.App") @patch("barterdude.AMQPConnection") def setUp(self, AMQPConnection, App): self.monitor = Mock() self.monitor.dispatch_before_consume = CoroutineMock() self.monitor.dispatch_on_success = CoroutineMock() self.monitor.dispatch_on_fail = CoroutineMock() self.callback = CoroutineMock() self.messages = [Mock(value=i) for i in range(10)] self.calls = [call(message) for message in self.messages] self.AMQPConnection = AMQPConnection self.connection = self.AMQPConnection.return_value self.App = App self.app = self.App.return_value self.app.startup = CoroutineMock() self.app.shutdown = CoroutineMock() self.decorator = self.app.route.return_value self.schema = load_fixture("schema.json") self.barterdude = BarterDude() def test_should_create_connection(self): self.AMQPConnection.assert_called_once_with( hostname="127.0.0.1", username="guest", password="guest", prefetch=10, name="default", ) self.App.assert_called_once_with(connections=[self.connection]) def test_should_call_route_when_created(self): monitor = Mock() self.barterdude.consume_amqp( ["queue"], monitor=monitor )(CoroutineMock()) self.app.route.assert_called_once_with( ["queue"], type=RouteTypes.AMQP_RABBITMQ, options={ Options.BULK_SIZE: 10, Options.BULK_FLUSH_INTERVAL: 60, Options.CONNECTION_FAIL_CALLBACK: monitor.dispatch_on_connection_fail, } ) def test_should_call_route_when_adding_endpoint(self): hook = Mock() self.barterdude.add_endpoint(['/my_route'], ['GET'], hook) self.app.route.assert_called_once_with( routes=['/my_route'], methods=['GET'], type=RouteTypes.HTTP ) self.decorator.assert_called_once_with(hook) async def test_should_call_callback_for_each_message(self): self.barterdude.consume_amqp(["queue"], self.monitor)(self.callback) self.decorator.assert_called_once() wrapper = self.decorator.call_args[0][0] await wrapper(self.messages) messages = [] for message in self.callback.mock_calls: self.assertEqual(Message, type(message[1][0])) messages.append(message[1][0]._message) self.assertListEqual( sorted(messages, key=lambda x: x.value), sorted(self.messages, key=lambda x: x.value)) async def test_should_call_reject_when_callback_fail(self): self.callback.side_effect = Exception('Boom!') self.barterdude.consume_amqp(["queue"], self.monitor)(self.callback) wrapper = self.decorator.call_args[0][0] await wrapper(self.messages) for message in self.messages: message.reject.assert_called_once() async def test_should_call_monitor_for_each_success_message(self): self.barterdude.consume_amqp(["queue"], self.monitor)(self.callback) wrapper = self.decorator.call_args[0][0] await wrapper(self.messages) self.monitor.dispatch_before_consume.assert_has_calls( self.calls, any_order=True) self.monitor.dispatch_on_success.assert_has_calls( self.calls, any_order=True) self.monitor.dispatch_on_fail.assert_not_called() async def test_should_call_callback_for_valid_message(self): self.barterdude.consume_amqp( ["queue"], self.monitor, validation_schema=self.schema )(self.callback) self.decorator.assert_called_once() wrapper = self.decorator.call_args[0][0] message = Mock(Message) message.body = {"key": 'ok'} await wrapper([message]) self.callback.assert_called_once() self.assertEqual( self.callback.await_args[0][0].body["key"], message.body["key"] ) async def test_should_not_call_callback_for_valid_message(self): self.barterdude.consume_amqp( ["queue"], self.monitor, validation_schema=self.schema )(self.callback) self.decorator.assert_called_once() wrapper = self.decorator.call_args[0][0] message = Mock(Message) message.body = {"wrong": 'ok'} await wrapper([message]) self.callback.assert_not_called() async def test_should_call_monitor_for_each_fail_message(self): error = Exception('Boom!') self.callback.side_effect = error self.barterdude.consume_amqp(["queue"], self.monitor)(self.callback) wrapper = self.decorator.call_args[0][0] await wrapper(self.messages) self.monitor.dispatch_before_consume.assert_has_calls( self.calls, any_order=True) error_calls = [call(message, error) for message in self.messages] self.monitor.dispatch_on_fail.assert_has_calls( error_calls, any_order=True) self.monitor.dispatch_on_success.assert_not_called() async def test_should_call_put_when_publish(self): data = Mock() self.connection.put = CoroutineMock() await self.barterdude.publish_amqp( 'exchange', data, vhost="vhost", routing_key="routing_key" ) self.connection.put.assert_called_once_with( exchange='exchange', data=data, vhost="vhost", routing_key="routing_key", properties=None ) async def test_should_call_startup_and_shutdown(self): await self.barterdude.startup() self.app.startup.assert_called_once_with() await self.barterdude.shutdown() self.app.shutdown.assert_called_once_with() def test_should_call_run(self): self.barterdude.run() self.app.run.assert_called_once_with() class TestAppSharedProperties(TestCase): def setUp(self): self.barterdude = BarterDude() def test_setitem_changes_state(self): self.barterdude["foo"] = foo = Mock() self.assertEqual(foo, self.barterdude["foo"]) async def test_getitem_returns_internal_state_value(self): self.barterdude["foo"] = "bar" self.assertEqual("bar", self.barterdude["foo"]) def test_delitem_changes_state(self): self.barterdude["foo"] = foo = Mock() self.assertEqual(foo, self.barterdude["foo"]) del self.barterdude["foo"] with self.assertRaises(KeyError): self.assertIsNone(self.barterdude["foo"]) def test_len_returns_state_len(self): test_data = {"foo": 1, "bar": 2} for k, v in test_data.items(): self.barterdude[k] = v self.assertEqual( len(self.barterdude), len(dict(self.barterdude._BarterDude__app)) ) async def test_iter_iters_through_internal_state_value(self): test_data = {"foo": 1, "bar": 2} for k, v in test_data.items(): self.barterdude[k] = v state = dict(**self.barterdude) self.assertDictContainsSubset(test_data, state)

true

1c2fddcbe5eda8f0b8a7640f59c56bbb9a809a56

5,745

py

Python

RTO_comp/RTO_Bayes_runs.py

OptiMaL-PSE-Lab/Expensive-Black-Box-Optim-ChemEng

19c34dcff8c983926df501b93152fa3b3b0305d6

[ "MIT" ]

null

RTO_comp/RTO_Bayes_runs.py

OptiMaL-PSE-Lab/Expensive-Black-Box-Optim-ChemEng

19c34dcff8c983926df501b93152fa3b3b0305d6

[ "MIT" ]

null

RTO_comp/RTO_Bayes_runs.py

OptiMaL-PSE-Lab/Expensive-Black-Box-Optim-ChemEng

19c34dcff8c983926df501b93152fa3b3b0305d6

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Fri Apr 2 15:49:18 2021 @author: dv516 """ from algorithms.Bayesian_opt_Pyro.utilities_full import BayesOpt from case_studies.RTO.systems import * import numpy as np import pickle import pyro pyro.enable_validation(True) # can help with debugging def RTO(x): # x = extract_FT(x) plant = WO_system() f = plant.WO_obj_sys_ca_noise_less g1 = plant.WO_con1_sys_ca_noise_less g2 = plant.WO_con2_sys_ca_noise_less return f(x), [g1(x), g2(x)] def RTO_rand(x): # x = extract_FT(x) plant = WO_system() f = plant.WO_obj_sys_ca g1 = plant.WO_con1_sys_ca g2 = plant.WO_con2_sys_ca return f(x), [g1(x), g2(x)] def RTO_SAA(x): # x = extract_FT(x) N_SAA = 5 plant = WO_system() f = plant.WO_obj_sys_ca g1 = plant.WO_con1_sys_ca g2 = plant.WO_con2_sys_ca f_SAA = 0 g1_SAA, g2_SAA = - np.inf, - np.inf for i in range(N_SAA): f_SAA += f(x)/N_SAA g1_SAA = max(g1_SAA, g1(x)) g2_SAA = max(g2_SAA, g2(x)) return f_SAA, [g1_SAA, g2_SAA] def RTO_Noise(x, noise, N_SAA): plant = WO_system() f = plant.WO_obj_sys_ca_noise_less g1 = plant.WO_con1_sys_ca_noise_less g2 = plant.WO_con2_sys_ca_noise_less f_SAA = 0 g1_SAA, g2_SAA = - np.inf, - np.inf for i in range(N_SAA): f_SAA += (f(x) + 5e-1 * np.random.normal(0., noise))/N_SAA g1_SAA = max(g1_SAA, g1(x) + 5e-4 * np.random.normal(0., noise)) g2_SAA = max(g2_SAA, g2(x) + 5e-4 * np.random.normal(0., noise)) return f_SAA, [g1_SAA, g2_SAA] x0 = [6.9, 83] bounds = np.array([[4., 7.], [70., 100.]]) # max_f_eval = 100 # max_it = 50 nbr_feval = 30 N = 10 RTO_Bayes_list = [] for i in range(N): Bayes = BayesOpt() pyro.set_rng_seed(i) RTO_Bayes = Bayes.solve(RTO, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict RTO_Bayes_list.append(RTO_Bayes) print('10 BayesOpt deterministic iterations completed') with open('BayesRTO_list.pickle', 'wb') as handle: pickle.dump(RTO_Bayes_list, handle, protocol=pickle.HIGHEST_PROTOCOL) N = 10 RTORand_Bayes_list = [] for i in range(N): Bayes = BayesOpt() pyro.set_rng_seed(i) RTORand_Bayes = Bayes.solve(RTO_rand, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict RTORand_Bayes_list.append(RTORand_Bayes) print('10 BayesOpt random iterations completed') with open('BayesRTO_listRand.pickle', 'wb') as handle: pickle.dump(RTORand_Bayes_list, handle, protocol=pickle.HIGHEST_PROTOCOL) N = 10 RTOSAA_Bayes_list = [] for i in range(N): Bayes = BayesOpt() pyro.set_rng_seed(i) RTOSAA_Bayes = Bayes.solve(RTO_SAA, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict RTOSAA_Bayes_list.append(RTOSAA_Bayes) print('10 BayesOpt SAA iterations completed') with open('BayesRTO_listRandSAA.pickle', 'wb') as handle: pickle.dump(RTOSAA_Bayes_list, handle, protocol=pickle.HIGHEST_PROTOCOL) n_noise = 6 noise_mat = np.zeros(n_noise) for i in range(n_noise): noise_mat[i] = 1/3*i x0 = [6.9, 83] bounds = np.array([[4., 7.], [70., 100.]]) max_f_eval = 50 ; N_SAA = 1 N_SAA = 1 N_samples = 20 RTOnoise_list_Bayes = [] RTOconstraint_list_Bayes = [] for i in range(n_noise): print('Outer Iteration ', i+1, ' out of ', n_noise,' of BayesOpt') best = [] best_constr = [] Bayes = BayesOpt() f = lambda x: RTO_Noise(x, noise_mat[i], N_SAA) for j in range(N_samples): sol = Bayes.solve(f, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict best.append(sol['f_best_so_far'][-1]) _, g = RTO_Noise(sol['x_best_so_far'][-1], 0, N_SAA) best_constr.append(np.sum(np.maximum(g, 0))) RTOnoise_list_Bayes.append(best) RTOconstraint_list_Bayes.append(best_constr) with open('BayesRTO_listNoiseConv.pickle', 'wb') as handle: pickle.dump(RTOnoise_list_Bayes, handle, protocol=pickle.HIGHEST_PROTOCOL) with open('BayesRTO_listNoiseConstr.pickle', 'wb') as handle: pickle.dump(RTOconstraint_list_Bayes, handle, protocol=pickle.HIGHEST_PROTOCOL) nbr_feval = 25 N_SAA = 2 N_samples = 20 RTOnoiseSAA_list_Bayes = [] RTOconstraintSAA_list_Bayes = [] for i in range(n_noise): print('Outer Iteration ', i+1, ' out of ', n_noise,' of BayesOpt') best = [] best_constr = [] for j in range(N_samples): f = lambda x: RTO_Noise(x, noise_mat[i], N_SAA) sol = Bayes.solve(f, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict best.append(sol['f_best_so_far'][-1]) _, g = RTO_Noise(sol['x_best_so_far'][-1], 0, N_SAA) best_constr.append(np.sum(np.maximum(g, 0))) RTOnoiseSAA_list_Bayes.append(best) RTOconstraintSAA_list_Bayes.append(best_constr) with open('BayesRTO_listNoiseConvSAA.pickle', 'wb') as handle: pickle.dump(RTOnoiseSAA_list_Bayes, handle, protocol=pickle.HIGHEST_PROTOCOL) with open('BayesRTO_listNoiseConstrSAA.pickle', 'wb') as handle: pickle.dump(RTOconstraintSAA_list_Bayes, handle, protocol=pickle.HIGHEST_PROTOCOL)

29.921875

86

0.641775

from algorithms.Bayesian_opt_Pyro.utilities_full import BayesOpt from case_studies.RTO.systems import * import numpy as np import pickle import pyro pyro.enable_validation(True) def RTO(x): plant = WO_system() f = plant.WO_obj_sys_ca_noise_less g1 = plant.WO_con1_sys_ca_noise_less g2 = plant.WO_con2_sys_ca_noise_less return f(x), [g1(x), g2(x)] def RTO_rand(x): plant = WO_system() f = plant.WO_obj_sys_ca g1 = plant.WO_con1_sys_ca g2 = plant.WO_con2_sys_ca return f(x), [g1(x), g2(x)] def RTO_SAA(x): N_SAA = 5 plant = WO_system() f = plant.WO_obj_sys_ca g1 = plant.WO_con1_sys_ca g2 = plant.WO_con2_sys_ca f_SAA = 0 g1_SAA, g2_SAA = - np.inf, - np.inf for i in range(N_SAA): f_SAA += f(x)/N_SAA g1_SAA = max(g1_SAA, g1(x)) g2_SAA = max(g2_SAA, g2(x)) return f_SAA, [g1_SAA, g2_SAA] def RTO_Noise(x, noise, N_SAA): plant = WO_system() f = plant.WO_obj_sys_ca_noise_less g1 = plant.WO_con1_sys_ca_noise_less g2 = plant.WO_con2_sys_ca_noise_less f_SAA = 0 g1_SAA, g2_SAA = - np.inf, - np.inf for i in range(N_SAA): f_SAA += (f(x) + 5e-1 * np.random.normal(0., noise))/N_SAA g1_SAA = max(g1_SAA, g1(x) + 5e-4 * np.random.normal(0., noise)) g2_SAA = max(g2_SAA, g2(x) + 5e-4 * np.random.normal(0., noise)) return f_SAA, [g1_SAA, g2_SAA] x0 = [6.9, 83] bounds = np.array([[4., 7.], [70., 100.]]) nbr_feval = 30 N = 10 RTO_Bayes_list = [] for i in range(N): Bayes = BayesOpt() pyro.set_rng_seed(i) RTO_Bayes = Bayes.solve(RTO, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict RTO_Bayes_list.append(RTO_Bayes) print('10 BayesOpt deterministic iterations completed') with open('BayesRTO_list.pickle', 'wb') as handle: pickle.dump(RTO_Bayes_list, handle, protocol=pickle.HIGHEST_PROTOCOL) N = 10 RTORand_Bayes_list = [] for i in range(N): Bayes = BayesOpt() pyro.set_rng_seed(i) RTORand_Bayes = Bayes.solve(RTO_rand, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict RTORand_Bayes_list.append(RTORand_Bayes) print('10 BayesOpt random iterations completed') with open('BayesRTO_listRand.pickle', 'wb') as handle: pickle.dump(RTORand_Bayes_list, handle, protocol=pickle.HIGHEST_PROTOCOL) N = 10 RTOSAA_Bayes_list = [] for i in range(N): Bayes = BayesOpt() pyro.set_rng_seed(i) RTOSAA_Bayes = Bayes.solve(RTO_SAA, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict RTOSAA_Bayes_list.append(RTOSAA_Bayes) print('10 BayesOpt SAA iterations completed') with open('BayesRTO_listRandSAA.pickle', 'wb') as handle: pickle.dump(RTOSAA_Bayes_list, handle, protocol=pickle.HIGHEST_PROTOCOL) n_noise = 6 noise_mat = np.zeros(n_noise) for i in range(n_noise): noise_mat[i] = 1/3*i x0 = [6.9, 83] bounds = np.array([[4., 7.], [70., 100.]]) max_f_eval = 50 ; N_SAA = 1 N_SAA = 1 N_samples = 20 RTOnoise_list_Bayes = [] RTOconstraint_list_Bayes = [] for i in range(n_noise): print('Outer Iteration ', i+1, ' out of ', n_noise,' of BayesOpt') best = [] best_constr = [] Bayes = BayesOpt() f = lambda x: RTO_Noise(x, noise_mat[i], N_SAA) for j in range(N_samples): sol = Bayes.solve(f, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict best.append(sol['f_best_so_far'][-1]) _, g = RTO_Noise(sol['x_best_so_far'][-1], 0, N_SAA) best_constr.append(np.sum(np.maximum(g, 0))) RTOnoise_list_Bayes.append(best) RTOconstraint_list_Bayes.append(best_constr) with open('BayesRTO_listNoiseConv.pickle', 'wb') as handle: pickle.dump(RTOnoise_list_Bayes, handle, protocol=pickle.HIGHEST_PROTOCOL) with open('BayesRTO_listNoiseConstr.pickle', 'wb') as handle: pickle.dump(RTOconstraint_list_Bayes, handle, protocol=pickle.HIGHEST_PROTOCOL) nbr_feval = 25 N_SAA = 2 N_samples = 20 RTOnoiseSAA_list_Bayes = [] RTOconstraintSAA_list_Bayes = [] for i in range(n_noise): print('Outer Iteration ', i+1, ' out of ', n_noise,' of BayesOpt') best = [] best_constr = [] for j in range(N_samples): f = lambda x: RTO_Noise(x, noise_mat[i], N_SAA) sol = Bayes.solve(f, x0, acquisition='EI',bounds=bounds.T, \ print_iteration = True, constraints=2, casadi=True, \ maxfun = nbr_feval, ).output_dict best.append(sol['f_best_so_far'][-1]) _, g = RTO_Noise(sol['x_best_so_far'][-1], 0, N_SAA) best_constr.append(np.sum(np.maximum(g, 0))) RTOnoiseSAA_list_Bayes.append(best) RTOconstraintSAA_list_Bayes.append(best_constr) with open('BayesRTO_listNoiseConvSAA.pickle', 'wb') as handle: pickle.dump(RTOnoiseSAA_list_Bayes, handle, protocol=pickle.HIGHEST_PROTOCOL) with open('BayesRTO_listNoiseConstrSAA.pickle', 'wb') as handle: pickle.dump(RTOconstraintSAA_list_Bayes, handle, protocol=pickle.HIGHEST_PROTOCOL)

true

1c2fdebdb580e69cba2adc7acdd3c5b2ac28b500

12,914

py

Python

polus-image-assembler-plugin/src/main.py

blowekamp/polus-plugins

87f9c36647b4cf95cf107cfede3a5a1d749415a5

[ "MIT" ]

null

polus-image-assembler-plugin/src/main.py

blowekamp/polus-plugins

87f9c36647b4cf95cf107cfede3a5a1d749415a5

[ "MIT" ]

null

polus-image-assembler-plugin/src/main.py

blowekamp/polus-plugins

87f9c36647b4cf95cf107cfede3a5a1d749415a5

[ "MIT" ]

null

import argparse, logging, multiprocessing, re from bfio import BioReader,BioWriter import numpy as np from concurrent.futures import ThreadPoolExecutor from pathlib import Path STITCH_VARS = ['file','correlation','posX','posY','gridX','gridY'] # image stitching values STITCH_LINE = "file: {}; corr: {}; position: ({}, {}); grid: ({}, {});\n" def buffer_image(image_path,supertile_buffer,Xi,Yi,Xt,Yt): """buffer_image Load and image and store in buffer This method loads an image and stores it in the appropriate position based on the stitching vector coordinates within a large tile of the output image. It is intended to be used as a thread to increase the reading component to assembling the image. Args: image_path ([str]): Path to image to load supertile_buffer ([np.ndarray]): A supertile storing multiple images Xi ([list]): Xmin and Xmax of pixels to load from the image Yi ([list]): Ymin and Ymax of pixels to load from the image Xt ([list]): X position within the buffer to store the image Yt ([list]): Y position within the buffer to store the image """ # Load the image br = BioReader(image_path,max_workers=2) image = br.read_image(X=Xi,Y=Yi) # only get the first z,c,t layer # Put the image in the buffer supertile_buffer[Yt[0]:Yt[1],Xt[0]:Xt[1],...] = image def make_tile(x_min,x_max,y_min,y_max,stitchPath): """make_tile Create a supertile This method identifies images that have stitching vector positions within the bounds of the supertile defined by the x and y input arguments. It then spawns threads to load images and store in the supertile buffer. Finally it returns the assembled supertile to allow the main thread to generate the write thread. Args: x_min ([int]): Minimum x bound of the tile x_max ([int]): Maximum x bound of the tile y_min ([int]): Minimum y bound of the tile y_max ([int]): Maximum y bound of the tile stitchPath ([str]): Path to the stitching vector Returns: [type]: [description] """ # Parse the stitching vector outvals = _parse_stitch(stitchPath,imgPath,True) # Get the data type br = BioReader(str(Path(imgPath).joinpath(outvals['filePos'][0]['file']))) dtype = br._pix['type'] # initialize the supertile template = np.zeros((y_max-y_min,x_max-x_min,1,1,1),dtype=dtype) # get images in bounds of current super tile with ThreadPoolExecutor(max([multiprocessing.cpu_count(),2])) as executor: for f in outvals['filePos']: if (f['posX'] >= x_min and f['posX'] <= x_max) or (f['posX']+f['width'] >= x_min and f['posX']+f['width'] <= x_max): if (f['posY'] >= y_min and f['posY'] <= y_max) or (f['posY']+f['height'] >= y_min and f['posY']+f['height'] <= y_max): # get bounds of image within the tile Xt = [max(0,f['posX']-x_min)] Xt.append(min(x_max-x_min,f['posX']+f['width']-x_min)) Yt = [max(0,f['posY']-y_min)] Yt.append(min(y_max-y_min,f['posY']+f['height']-y_min)) # get bounds of image within the image Xi = [max(0,x_min - f['posX'])] Xi.append(min(f['width'],x_max - f['posX'])) Yi = [max(0,y_min - f['posY'])] Yi.append(min(f['height'],y_max - f['posY'])) executor.submit(buffer_image,str(Path(imgPath).joinpath(f['file'])),template,Xi,Yi,Xt,Yt) return template def get_number(s): """ Check that s is number In this plugin, heatmaps are created only for columns that contain numbers. This function checks to make sure an input value is able to be converted into a number. Inputs: s - An input string or number Outputs: value - Either float(s) or False if s cannot be cast to float """ try: return int(s) except ValueError: return s def _parse_stitch(stitchPath,imagePath,timepointName=False): """ Load and parse image stitching vectors This function creates a list of file dictionaries that include the filename and pixel position and dimensions within a stitched image. It also determines the size of the final stitched image and the suggested name of the output image based on differences in file names in the stitching vector. Inputs: stitchPath - A path to stitching vectors imagePath - A path to tiled tiff images timepointName - Use the vector timeslice as the image name Outputs: out_dict - Dictionary with keys (width, height, name, filePos) """ # Initialize the output out_dict = { 'width': int(0), 'height': int(0), 'name': '', 'filePos': []} # Set the regular expression used to parse each line of the stitching vector line_regex = r"file: (.*); corr: (.*); position: $(.*), (.*)$; grid: $(.*), (.*)$;" # Get a list of all images in imagePath images = [p.name for p in Path(imagePath).iterdir()] # Open each stitching vector fpath = str(Path(stitchPath).absolute()) name_pos = {} with open(fpath,'r') as fr: # Read the first line to get the filename for comparison to all other filenames line = fr.readline() stitch_groups = re.match(line_regex,line) stitch_groups = {key:val for key,val in zip(STITCH_VARS,stitch_groups.groups())} name = stitch_groups['file'] name_ind = [i for i in range(len(name))] fr.seek(0) # reset to the first line # Read each line in the stitching vector for line in fr: # Read and parse values from the current line stitch_groups = re.match(line_regex,line) stitch_groups = {key:get_number(val) for key,val in zip(STITCH_VARS,stitch_groups.groups())} # If an image in the vector doesn't match an image in the collection, then skip it if stitch_groups['file'] not in images: continue # Get the image size stitch_groups['width'], stitch_groups['height'] = BioReader.image_size(str(Path(imagePath).joinpath(stitch_groups['file']).absolute())) if out_dict['width'] < stitch_groups['width']+stitch_groups['posX']: out_dict['width'] = stitch_groups['width']+stitch_groups['posX'] if out_dict['height'] < stitch_groups['height']+stitch_groups['posY']: out_dict['height'] = stitch_groups['height']+stitch_groups['posY'] # Set the stitching vector values in the file dictionary out_dict['filePos'].append(stitch_groups) # Determine the difference between first name and current name if not timepointName: for i in name_ind: if name[i] != stitch_groups['file'][i]: if i not in name_pos.keys(): name_pos[i] = set() name_pos[i].update([get_number(stitch_groups['file'][i])]) name_pos[i].update([get_number(name[i])]) else: name_pos[i].update([get_number(stitch_groups['file'][i])]) # Generate the output file name # NOTE: This should be rewritten later to determine numeric values rather than position values. # Output file names should be indices = sorted(name_pos.keys()) if timepointName: global_regex = ".*global-positions-([0-9]+).txt" name = re.match(global_regex,Path(stitchPath).name).groups()[0] name += '.ome.tif' out_dict['name'] = name elif len(indices) > 0: out_dict['name'] = name[0:indices[0]] minvals = [] maxvals = [] for v,i in enumerate(indices): if len(minvals)==0: out_dict['name'] += '<' minvals.append(min(name_pos[i])) maxvals.append(max(name_pos[i])) if i == indices[-1] or indices[v+1] - i > 1: out_dict['name'] += ''.join([str(ind) for ind in minvals]) out_dict['name'] += '-' out_dict['name'] += ''.join([str(ind) for ind in maxvals]) out_dict['name'] += '>' if i == indices[-1]: out_dict['name'] += name[indices[-1]+1:] else: out_dict['name'] += name[indices[v]+1:indices[v+1]] minvals = [] maxvals = [] else: out_dict['name'] = name return out_dict if __name__=="__main__": # Initialize the logger logging.basicConfig(format='%(asctime)s - %(name)-8s - %(levelname)-8s - %(message)s', datefmt='%d-%b-%y %H:%M:%S') logger = logging.getLogger("main") logger.setLevel(logging.INFO) # Setup the argument parsing parser = argparse.ArgumentParser(prog='main', description='Assemble images from a single stitching vector.') parser.add_argument('--stitchPath', dest='stitchPath', type=str, help='Complete path to a stitching vector', required=True) parser.add_argument('--imgPath', dest='imgPath', type=str, help='Input image collection to be processed by this plugin', required=True) parser.add_argument('--outDir', dest='outDir', type=str, help='Output collection', required=True) parser.add_argument('--timesliceNaming', dest='timesliceNaming', type=str, help='Use timeslice number as image name', required=False) # Parse the arguments args = parser.parse_args() imgPath = args.imgPath if Path(imgPath).joinpath('images').is_dir(): imgPath = str(Path(imgPath).joinpath('images').absolute()) outDir = args.outDir logger.info('outDir: {}'.format(outDir)) timesliceNaming = args.timesliceNaming == 'true' logger.info('timesliceNaming: {}'.format(timesliceNaming)) stitchPath = args.stitchPath # Get a list of stitching vectors vectors = [str(p.absolute()) for p in Path(stitchPath).iterdir() if p.is_file() and "".join(p.suffixes)=='.txt'] logger.info('imgPath: {}'.format(imgPath)) logger.info('stitchPath: {}'.format(stitchPath)) vectors.sort() # Variables for image building processes img_processes = [] img_paths = [] for v in vectors: # Check to see if the file is a stitching vector if 'img-global-positions' not in Path(v).name: continue # Parse the stitching vector logger.info('Analyzing vector: {}'.format(Path(v).name)) outvals = _parse_stitch(v,imgPath,timesliceNaming) logger.info('Building image: {}'.format(outvals['name'])) logger.info('Output image size (width, height): {},{}'.format(outvals['width'],outvals['height'])) # Variables for tile building processes pnum = 0 ptotal = np.ceil(outvals['width']/10240) * np.ceil(outvals['height']/10240) ptotal = 1/ptotal * 100 # Initialize the output image logger.info('Initializing output file: {}'.format(outvals['name'])) refImg = str(Path(imgPath).joinpath(outvals['filePos'][0]['file']).absolute()) outFile = str(Path(outDir).joinpath(outvals['name']).absolute()) br = BioReader(str(Path(refImg).absolute())) bw = BioWriter(str(Path(outFile).absolute()),metadata=br.read_metadata(),max_workers=max([multiprocessing.cpu_count(),2])) bw.num_x(outvals['width']) bw.num_y(outvals['height']) del br # Assemble the images logger.info('Generating tiles...') threads = [] with ThreadPoolExecutor(max([multiprocessing.cpu_count()//2,2])) as executor: for x in range(0, outvals['width'], 10240): X_range = min(x+10240,outvals['width']) # max x-pixel index in the assembled image for y in range(0, outvals['height'], 10240): Y_range = min(y+10240,outvals['height']) # max y-pixel index in the assembled image image_buffer = make_tile(x,X_range,y,Y_range,v) threads.append(executor.submit(bw.write_image,image_buffer,X=[x],Y=[y])) # bw.write_image(image_buffer,X=[x],Y=[y]) logger.info('{:.2f} finished...'.format(0)) for ind,thread in enumerate(threads): thread.result() logger.info('{:.2f}% finished...'.format(100*(ind+1)/len(threads))) logger.info('Closing image...') bw.close_image()

43.92517

147

0.594471

import argparse, logging, multiprocessing, re from bfio import BioReader,BioWriter import numpy as np from concurrent.futures import ThreadPoolExecutor from pathlib import Path STITCH_VARS = ['file','correlation','posX','posY','gridX','gridY'] STITCH_LINE = "file: {}; corr: {}; position: ({}, {}); grid: ({}, {});\n" def buffer_image(image_path,supertile_buffer,Xi,Yi,Xt,Yt): br = BioReader(image_path,max_workers=2) image = br.read_image(X=Xi,Y=Yi) supertile_buffer[Yt[0]:Yt[1],Xt[0]:Xt[1],...] = image def make_tile(x_min,x_max,y_min,y_max,stitchPath): outvals = _parse_stitch(stitchPath,imgPath,True) br = BioReader(str(Path(imgPath).joinpath(outvals['filePos'][0]['file']))) dtype = br._pix['type'] template = np.zeros((y_max-y_min,x_max-x_min,1,1,1),dtype=dtype) with ThreadPoolExecutor(max([multiprocessing.cpu_count(),2])) as executor: for f in outvals['filePos']: if (f['posX'] >= x_min and f['posX'] <= x_max) or (f['posX']+f['width'] >= x_min and f['posX']+f['width'] <= x_max): if (f['posY'] >= y_min and f['posY'] <= y_max) or (f['posY']+f['height'] >= y_min and f['posY']+f['height'] <= y_max): Xt = [max(0,f['posX']-x_min)] Xt.append(min(x_max-x_min,f['posX']+f['width']-x_min)) Yt = [max(0,f['posY']-y_min)] Yt.append(min(y_max-y_min,f['posY']+f['height']-y_min)) Xi = [max(0,x_min - f['posX'])] Xi.append(min(f['width'],x_max - f['posX'])) Yi = [max(0,y_min - f['posY'])] Yi.append(min(f['height'],y_max - f['posY'])) executor.submit(buffer_image,str(Path(imgPath).joinpath(f['file'])),template,Xi,Yi,Xt,Yt) return template def get_number(s): try: return int(s) except ValueError: return s def _parse_stitch(stitchPath,imagePath,timepointName=False): out_dict = { 'width': int(0), 'height': int(0), 'name': '', 'filePos': []} line_regex = r"file: (.*); corr: (.*); position: $(.*), (.*)$; grid: $(.*), (.*)$;" images = [p.name for p in Path(imagePath).iterdir()] fpath = str(Path(stitchPath).absolute()) name_pos = {} with open(fpath,'r') as fr: line = fr.readline() stitch_groups = re.match(line_regex,line) stitch_groups = {key:val for key,val in zip(STITCH_VARS,stitch_groups.groups())} name = stitch_groups['file'] name_ind = [i for i in range(len(name))] fr.seek(0) for line in fr: stitch_groups = re.match(line_regex,line) stitch_groups = {key:get_number(val) for key,val in zip(STITCH_VARS,stitch_groups.groups())} if stitch_groups['file'] not in images: continue # Get the image size stitch_groups['width'], stitch_groups['height'] = BioReader.image_size(str(Path(imagePath).joinpath(stitch_groups['file']).absolute())) if out_dict['width'] < stitch_groups['width']+stitch_groups['posX']: out_dict['width'] = stitch_groups['width']+stitch_groups['posX'] if out_dict['height'] < stitch_groups['height']+stitch_groups['posY']: out_dict['height'] = stitch_groups['height']+stitch_groups['posY'] # Set the stitching vector values in the file dictionary out_dict['filePos'].append(stitch_groups) # Determine the difference between first name and current name if not timepointName: for i in name_ind: if name[i] != stitch_groups['file'][i]: if i not in name_pos.keys(): name_pos[i] = set() name_pos[i].update([get_number(stitch_groups['file'][i])]) name_pos[i].update([get_number(name[i])]) else: name_pos[i].update([get_number(stitch_groups['file'][i])]) # Generate the output file name # NOTE: This should be rewritten later to determine numeric values rather than position values. # Output file names should be indices = sorted(name_pos.keys()) if timepointName: global_regex = ".*global-positions-([0-9]+).txt" name = re.match(global_regex,Path(stitchPath).name).groups()[0] name += '.ome.tif' out_dict['name'] = name elif len(indices) > 0: out_dict['name'] = name[0:indices[0]] minvals = [] maxvals = [] for v,i in enumerate(indices): if len(minvals)==0: out_dict['name'] += '<' minvals.append(min(name_pos[i])) maxvals.append(max(name_pos[i])) if i == indices[-1] or indices[v+1] - i > 1: out_dict['name'] += ''.join([str(ind) for ind in minvals]) out_dict['name'] += '-' out_dict['name'] += ''.join([str(ind) for ind in maxvals]) out_dict['name'] += '>' if i == indices[-1]: out_dict['name'] += name[indices[-1]+1:] else: out_dict['name'] += name[indices[v]+1:indices[v+1]] minvals = [] maxvals = [] else: out_dict['name'] = name return out_dict if __name__=="__main__": # Initialize the logger logging.basicConfig(format='%(asctime)s - %(name)-8s - %(levelname)-8s - %(message)s', datefmt='%d-%b-%y %H:%M:%S') logger = logging.getLogger("main") logger.setLevel(logging.INFO) # Setup the argument parsing parser = argparse.ArgumentParser(prog='main', description='Assemble images from a single stitching vector.') parser.add_argument('--stitchPath', dest='stitchPath', type=str, help='Complete path to a stitching vector', required=True) parser.add_argument('--imgPath', dest='imgPath', type=str, help='Input image collection to be processed by this plugin', required=True) parser.add_argument('--outDir', dest='outDir', type=str, help='Output collection', required=True) parser.add_argument('--timesliceNaming', dest='timesliceNaming', type=str, help='Use timeslice number as image name', required=False) # Parse the arguments args = parser.parse_args() imgPath = args.imgPath if Path(imgPath).joinpath('images').is_dir(): imgPath = str(Path(imgPath).joinpath('images').absolute()) outDir = args.outDir logger.info('outDir: {}'.format(outDir)) timesliceNaming = args.timesliceNaming == 'true' logger.info('timesliceNaming: {}'.format(timesliceNaming)) stitchPath = args.stitchPath # Get a list of stitching vectors vectors = [str(p.absolute()) for p in Path(stitchPath).iterdir() if p.is_file() and "".join(p.suffixes)=='.txt'] logger.info('imgPath: {}'.format(imgPath)) logger.info('stitchPath: {}'.format(stitchPath)) vectors.sort() # Variables for image building processes img_processes = [] img_paths = [] for v in vectors: # Check to see if the file is a stitching vector if 'img-global-positions' not in Path(v).name: continue # Parse the stitching vector logger.info('Analyzing vector: {}'.format(Path(v).name)) outvals = _parse_stitch(v,imgPath,timesliceNaming) logger.info('Building image: {}'.format(outvals['name'])) logger.info('Output image size (width, height): {},{}'.format(outvals['width'],outvals['height'])) # Variables for tile building processes pnum = 0 ptotal = np.ceil(outvals['width']/10240) * np.ceil(outvals['height']/10240) ptotal = 1/ptotal * 100 # Initialize the output image logger.info('Initializing output file: {}'.format(outvals['name'])) refImg = str(Path(imgPath).joinpath(outvals['filePos'][0]['file']).absolute()) outFile = str(Path(outDir).joinpath(outvals['name']).absolute()) br = BioReader(str(Path(refImg).absolute())) bw = BioWriter(str(Path(outFile).absolute()),metadata=br.read_metadata(),max_workers=max([multiprocessing.cpu_count(),2])) bw.num_x(outvals['width']) bw.num_y(outvals['height']) del br # Assemble the images logger.info('Generating tiles...') threads = [] with ThreadPoolExecutor(max([multiprocessing.cpu_count()//2,2])) as executor: for x in range(0, outvals['width'], 10240): X_range = min(x+10240,outvals['width']) # max x-pixel index in the assembled image for y in range(0, outvals['height'], 10240): Y_range = min(y+10240,outvals['height']) # max y-pixel index in the assembled image image_buffer = make_tile(x,X_range,y,Y_range,v) threads.append(executor.submit(bw.write_image,image_buffer,X=[x],Y=[y])) # bw.write_image(image_buffer,X=[x],Y=[y]) logger.info('{:.2f} finished...'.format(0)) for ind,thread in enumerate(threads): thread.result() logger.info('{:.2f}% finished...'.format(100*(ind+1)/len(threads))) logger.info('Closing image...') bw.close_image()

true

1c2fdece658ee45e7c59df804f24c5c925f8d7d9

17,589

py

Python

gaia.py

0x7c2/cpme2

09ee443ca7193d1566ae300fc0f9707aa5d042e0

[ "Apache-2.0" ]

null

gaia.py

0x7c2/cpme2

09ee443ca7193d1566ae300fc0f9707aa5d042e0

[ "Apache-2.0" ]

null

gaia.py

0x7c2/cpme2

09ee443ca7193d1566ae300fc0f9707aa5d042e0

[ "Apache-2.0" ]

2

2020-12-17T08:11:45.000Z

2021-02-25T17:25:43.000Z

# # Copyright 2020 by 0x7c2, Simon Brecht. # All rights reserved. # This file is part of the Report/Analytic Tool - CPme, # and is released under the "Apache License 2.0". Please see the LICENSE # file that should have been included as part of this package. # from templates import check import func class check_gaia_hwinfo(check): page = "GAiA.0verview" category = "Appliance" title = "" isFirewall = True isManagement = True minVersion = 8020 command = "cpstat -f hw_info os" isCommand = True def run_check(self): for line in self.commandOut: if ":" in line: data = line.split(':') a_field = data[0].strip() if len(data) > 1: a_val = data[1].strip() else: a_val = "" self.add_result(a_field, "INFO", a_val) class check_gaia_scheduled_backup(check): page = "GAiA.0verview" category = "GAiA Settings" title = "Scheduled Backup Config" isFirewall = True isManagement = True minVersion = 8020 command = "func.gaia_get_value('backup-scheduled')" isCommand = False def run_check(self): if self.commandOut: self.add_result(self.title, 'PASS', '') else: self.add_result(self.title, 'WARN', 'not configured') class check_gaia_check_snapshots(check): page = "GAiA.0verview" category = "Environment" title = "Existing GAiA Snapshots" isFirewall = True isManagement = True minVersion = 8020 command = "lvs | grep -v 'wi-ao' | tail -n +2" isCommand = True def run_check(self): found = False for o in self.commandOut: temp = ' '.join(o.split()) cols = temp.split(' ') if len(cols)>1: found = True name = cols[0].strip(' ').strip('\n') vg = cols[1].strip(' ').strip('\n') attr = cols[2].strip(' ').strip('\n') size = cols[3].strip(' ').strip('\n') detail = vg + " / " + name + " (" + size + ")" if "hwdiag" in name or "fcd_GAIA" in name: self.add_result(self.title, 'INFO', detail) else: self.add_result(self.title, 'WARN', detail) if not found: self.add_result(self.title, 'INFO', '') class check_gaia_check_cpuse_agent_version(check): page = "GAiA.CPUSE" category = "Agent" title = "Deployment Agent Version" isFirewall = True isManagement = True minVersion = 8020 command = "$DADIR/bin/da_cli da_status" isCommand = True def run_check(self): found = False for o in self.commandOut: if 'up to date' in o: found = True self.add_result(self.title, 'PASS', '') if not found: self.add_result(self.title, 'WARN', 'new version available') class check_gaia_check_cpuse_agent_pending_reboot(check): page = "GAiA.CPUSE" category = "Agent" title = "Deployment Agent Pending Reboot" isFirewall = True isManagement = True minVersion = 8020 command = "$DADIR/bin/da_cli is_pending_reboot" isCommand = True def run_check(self): found = False for o in self.commandOut: if 'no reboot' in o: found = True self.add_result(self.title, 'PASS', '') if not found: self.add_result(self.title, 'WARN', 'Reboot pending!') class check_gaia_check_cpuse_agent_packages(check): page = "GAiA.CPUSE" category = "Packages" title = "Packages available for install" isFirewall = True isManagement = True minVersion = 8020 command = "$DADIR/bin/da_cli packages_info status=available" isCommand = True def run_check(self): found = False for o in self.commandOut: if 'filename' in o: tmp = o.split(':')[1].replace('"','').replace(',','') self.add_result(self.title, 'WARN', tmp) found = True if not found: self.add_result(self.title, 'PASS', '') class check_gaia_check_proxy_settings(check): page = "GAiA.0verview" category = "GAiA Settings" title = "Proxy Configuration" isFirewall = True isManagement = True minVersion = 8020 command = "func.gaia_get_value('proxy:ip-address')" isCommand = False def run_check(self): if self.commandOut: proxy_port = func.gaia_get_value('proxy:port') self.add_result(self.title, 'INFO', self.commandOut + ':' + proxy_port) else: self.add_result(self.title, 'INFO', 'direct') class check_gaia_ntp(check): page = "GAiA.0verview" category = "GAiA Settings" title = "NTP - Time and Date" isFirewall = True isManagement = True minVersion = 8020 command = "ntpstat" isCommand = True def run_check(self): found = False for o in self.commandOut: if 'synchronised to' in o: self.add_result(self.title, "PASS", "") found = True if not found: self.add_result(self.title, "FAIL", "") class check_gaia_dns_external_checkpoint(check): page = "GAiA.Connectivity" category = "DNS Resolver" title = "DNS Lookup [checkpoint.com]" isFirewall = True isManagement = True minVersion = 8020 command = "nslookup checkpoint.com | awk 'NR>3 { print $0 }'" isCommand = True def run_check(self): passme = False detail = "" for line in self.commandOut: if 'Address:' in line: if '209' in line: passme = True detail = line.strip() if passme: self.add_result(self.title, 'PASS', detail) else: self.add_result(self.title, 'FAIL', detail) class check_gaia_dns_external_heise(check): page = "GAiA.Connectivity" category = "DNS Resolver" title = "DNS Lookup [heise.de]" isFirewall = True isManagement = True minVersion = 8020 command = "nslookup heise.de | awk 'NR>3 { print $0 }'" isCommand = True def run_check(self): passme = False detail = "" for line in self.commandOut: if 'Address:' in line: if '193' in line: passme = True detail = line.strip() if passme: self.add_result(self.title, 'PASS', detail) else: self.add_result(self.title, 'FAIL', detail) class check_gaia_z_check_connectivity(check): page = "GAiA.Connectivity" category = "Check Point Services" title = "Connection" isFirewall = True isManagement = True minVersion = 8020 command = "ls" isCommand = True runOnStartup = False def run_check(self): proxy = "" urls = [] urls.append(['http://cws.checkpoint.com/APPI/SystemStatus/type/short','Social Media Widget Detection']) urls.append(['http://cws.checkpoint.com/URLF/SystemStatus/type/short','URL Filtering Cloud Categorization']) urls.append(['http://cws.checkpoint.com/AntiVirus/SystemStatus/type/short','Virus Detection']) urls.append(['http://cws.checkpoint.com/Malware/SystemStatus/type/short','Bot Detection']) urls.append(['https://updates.checkpoint.com/','IPS Updates']) urls.append(['http://dl3.checkpoint.com','Download Service Updates ']) urls.append(['https://usercenter.checkpoint.com/usercenter/services/ProductCoverageService','Contract Entitlement ']) urls.append(['https://usercenter.checkpoint.com/usercenter/services/BladesManagerService','Software Blades Manager Service']) urls.append(['http://resolver1.chkp.ctmail.com','Suspicious Mail Outbreaks']) urls.append(['http://download.ctmail.com','Anti-Spam']) urls.append(['http://te.checkpoint.com','Threat Emulatin']) urls.append(['http://teadv.checkpoint.com','Threat Emulation Advanced']) urls.append(['http://kav8.zonealarm.com/version.txt','Deep inspection']) urls.append(['http://kav8.checkpoint.com','Traditional Anti-Virus']) urls.append(['http://avupdates.checkpoint.com/UrlList.txt','Traditional Anti-Virus, Legacy URL Filtering']) urls.append(['http://sigcheck.checkpoint.com/Siglist2.txt','Download of signature updates']) urls.append(['http://secureupdates.checkpoint.com','Manage Security Gateways']) urls.append(['https://productcoverage.checkpoint.com/ProductCoverageService','Makes sure the machines contracts are up-to-date']) urls.append(['https://sc1.checkpoint.com/sc/images/checkmark.gif','Download of icons and screenshots from Check Point media storage servers']) urls.append(['https://sc1.checkpoint.com/za/images/facetime/large_png/60342479_lrg.png','Download of icons and screenshots from Check Point media storage servers']) urls.append(['https://sc1.checkpoint.com/za/images/facetime/large_png/60096017_lrg.png','Download of icons and screenshots from Check Point media storage servers']) urls.append(['https://push.checkpoint.com','Push Notifications ']) urls.append(['http://downloads.checkpoint.com','Download of Endpoint Compliance Updates']) for url in urls: if self.runOnStartup: out, err = func.execute_command('curl_cli -Lisk ' + proxy + url[0] + ' | head -n1') data = out.read().strip('\n').strip(' ') if "OK" in data or "Found" in data or "Moved" in data or "Connection established" in data: state = "PASS" detail = "" else: state = "FAIL" detail = data self.add_result(self.title + " [" + url[1] + "]", state, detail) else: self.add_result(self.title + " [" + url[1] + "]", 'WAIT', '') def set_command(self): self.runOnStartup = True class check_gaia_interface_bonds(check): page = "GAiA.Networking" category = "Bonding" title = "Bond" isFirewall = True isManagement = True minVersion = 8020 command = "ifconfig | grep -c bond" isCommand = True def run_check(self): if int(self.commandOut[0]) > 0: cmd = "cphaprob show_bond" b_out, b_err = func.execute_command(cmd) for data in b_out: if "|" in data and "bond" in data: cols = data.split("|") b_name = cols[0].strip() b_mode = cols[1].strip() b_stat = cols[2].strip() b_cfg = cols[3].strip() b_up = cols[4].strip() b_req = cols[5].strip() state = "PASS" if b_stat != "UP": state = "WARN" self.add_result(self.title + " [" + b_name + ", " + b_mode + "]", state, b_up + "/" + b_cfg + " , Required: " + b_req) else: self.add_result("No bonding found", "PASS", "") class check_gaia_interface_buffers(check): page = "GAiA.Networking" category = "Ring Buffer" title = "Buffer Size" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "ifconfig | grep HWaddr" isCommand = True def run_check(self): for line in self.commandOut: b_rx = "" b_tx = "" state = "PASS" nic = line.split()[0].strip() b_out, b_err = func.execute_command('ethtool -g ' + nic) for data in b_out: if "RX:" in data: b_rx = data.split()[1].strip() if "TX:" in data: b_tx = data.split()[1].strip() if b_rx != "256": state = "WARN" if b_tx != "1024": state = "WARN" detail = "RX: " + b_rx + ", TX: " + b_tx if not "." in nic: self.add_result(self.title + " [" + nic + "]", state, detail) class check_gaia_interface_stats(check): page = "GAiA.Networking" category = "Statistics" title = "Interface statistics" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "ls" isCommand = True def run_check(self): values_rx = ["rx_dropped", "rx_crc_errors", "rx_errors", "rx_fifo_errors", "rx_frame_errors", "rx_length_errors", "rx_missed_errors", "rx_over_errors"] values_tx = ["tx_aborted_errors", "tx_carrier_errors", "tx_dropped", "tx_errors", "tx_fifo_errors", "tx_heartbeat_errors", "tx_window_errors"] out, err = func.execute_command('ls -1 /sys/class/net | grep -vE "(lo|bond|vpn|sit|\.)"') for line in out: interface = line.strip('\n') i = 0 error = False while i<len(values_rx): read, err = func.execute_command('cat /sys/class/net/'+interface+'/statistics/'+values_rx[i]) val = read.read().strip('\n') state = "PASS" detail = "" if val != "0": state = "FAIL" detail = val error = True self.add_result(self.title + " (" + interface + " - " + values_rx[i] + ")", state, detail) i = i + 1 if not error: for t in values_rx: self.results.pop() self.add_result(self.title + " (" + interface + " - rx/all" + ")", "PASS", "") i = 0 error = False while i<len(values_tx): read, err = func.execute_command('cat /sys/class/net/'+interface+'/statistics/'+values_tx[i]) val = read.read().strip('\n') state = "PASS" detail = "" if val != "0": state = "FAIL" detail = val error = True self.add_result(self.title + " (" + interface + " - " + values_rx[i] + ")", state, detail) i = i + 1 if not error: for t in values_tx: self.results.pop() self.add_result(self.title + " (" + interface + " - tx/all" + ")", "PASS", "") class check_gaia_disk_space(check): page = "GAiA.0verview" category = "Harddisk" title = "Disk Space" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "df -h | sed s/\ \ */\;/g | cut -d ';' -f 6,4 | awk 'NR>1 {print $1}'" isCommand = True def run_check(self): for line in self.commandOut: state = "FAIL" data = str(line).strip('\n').split(";") if len(data) < 2: continue if "M" in data[0]: state = "WARN" if "G" in data[0]: state = "PASS" if data[1] == "/boot" or data[1] == "/dev/shm": state = "PASS" self.add_result(self.title + " (" + data[1] + ")", state, data[0]) class check_gaia_cpu_smt(check): page = "GAiA.0verview" category = "CPU" title = "Hyperthreading/SMT" isFirewall = True isManagement = False minVersion = 8020 command = 'if [ ! -f "/proc/smt_status" ] ; then echo "Not available" ; else cat /proc/smt_status ; fi' isCommand = True def run_check(self): data = self.commandOut[0].strip() if "Unsupported" in data: self.add_result(self.title, "INFO", "Disabled") else: self.add_result(self.title, "INFO", data) class check_gaia_cpu_usage(check): page = "GAiA.0verview" category = "CPU" title = "CPU Usage" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "ls" isCommand = True def run_check(self): if func.isFirewall(): out, err = func.execute_command("fw ctl affinity -l") affinity = out.read() else: affinity = "" dbcur = func.execute_sqlite_query("select name_of_cpu,max(cpu_usage) from UM_STAT_UM_CPU_UM_CPU_ORDERED_TABLE group by name_of_cpu;") for row in dbcur: worker = "" nic = "" daemon = "" cpu = row[0] for line in affinity.split('\n'): if "CPU "+str(cpu)+'#' in line +'#': if "Kernel" in line: if worker != "": worker = worker + ", " worker = worker + line.split(":")[0].replace("Kernel ", "") elif "Daemon" in line: daemon = "Daemon(s), " else: if nic != "": nic = nic + ", " nic = nic + line.split(":")[0] load = str(row[1]).split(".")[0] state = "PASS" if int(load) > 85 and nic != "": state = "FAIL" elif int(load) > 85 and nic == "": state = "WARN" if nic != "": nic = nic + ", " self.add_result(self.title + " (peak - CPU " + str(cpu) + "): " + daemon + nic + worker, state, load + "%") dbcur = func.execute_sqlite_query("select name_of_cpu,avg(cpu_usage) from UM_STAT_UM_CPU_UM_CPU_ORDERED_TABLE group by name_of_cpu;") for row in dbcur: worker = "" nic = "" daemon = "" cpu = row[0] for line in affinity.split('\n'): if "CPU "+str(cpu)+'#' in line+'#': if "Kernel" in line: if worker != "": worker = worker + ", " worker = worker + line.split(":")[0].replace("Kernel ", "") elif "Daemon" in line: daemon = "Daemon(s), " else: if nic != "": nic = nic + ", " nic = nic + line.split(":")[0] load = str(row[1]).split(".")[0] state = "PASS" if int(load) > 50: state = "WARN" if int(load) > 50 and nic != "": state = "FAIL" if int(load) > 85 and worker != "": state = "FAIL" if nic != "": nic = nic + ", " self.add_result(self.title + " (avg - CPU " + str(cpu) + "): " + daemon + nic + worker, state, load + "%") dbcur.close() class check_gaia_memory_usage(check): page = "GAiA.0verview" category = "Memory" title = "Memory Usage" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "ls" isCommand = True def run_check(self): mem_total = 0 mem_avg = 0 mem_peak = 0 dbcur = func.execute_sqlite_query("select max(real_total) from UM_STAT_UM_MEMORY;") for row in dbcur: mem_total = row[0] dbcur = func.execute_sqlite_query("select avg(real_used) from UM_STAT_UM_MEMORY;") for row in dbcur: mem_avg = row[0] dbcur = func.execute_sqlite_query("select max(real_used) from UM_STAT_UM_MEMORY;") for row in dbcur: mem_peak = row[0] dbcur.close() mem_avg_used = int(str(mem_avg/mem_total*100).split(".")[0]) mem_peak_used = int(str(mem_peak/mem_total*100).split(".")[0]) state = "PASS" if mem_avg_used > 70: state = "WARN" if mem_avg_used > 90: state = "FAIL" self.add_result(self.title + " (average)", state, str(mem_avg_used)+"%") state = "PASS" if mem_peak_used > 80: state = "WARN" self.add_result(self.title + " (peak)", state, str(mem_peak_used)+"%") out, err = func.execute_command("free -g | grep -i swap | awk '{print $3,$4}'") data = out.read().strip('\n').split(" ") used = data[0] avail = data[1] percent = str(int(used) / int(avail) * 100).split(".")[0] state = "WARN" if percent == "0": state = "PASS" self.add_result(self.title + " (swap)", state, percent + "%")

30.642857

166

0.627722

from templates import check import func class check_gaia_hwinfo(check): page = "GAiA.0verview" category = "Appliance" title = "" isFirewall = True isManagement = True minVersion = 8020 command = "cpstat -f hw_info os" isCommand = True def run_check(self): for line in self.commandOut: if ":" in line: data = line.split(':') a_field = data[0].strip() if len(data) > 1: a_val = data[1].strip() else: a_val = "" self.add_result(a_field, "INFO", a_val) class check_gaia_scheduled_backup(check): page = "GAiA.0verview" category = "GAiA Settings" title = "Scheduled Backup Config" isFirewall = True isManagement = True minVersion = 8020 command = "func.gaia_get_value('backup-scheduled')" isCommand = False def run_check(self): if self.commandOut: self.add_result(self.title, 'PASS', '') else: self.add_result(self.title, 'WARN', 'not configured') class check_gaia_check_snapshots(check): page = "GAiA.0verview" category = "Environment" title = "Existing GAiA Snapshots" isFirewall = True isManagement = True minVersion = 8020 command = "lvs | grep -v 'wi-ao' | tail -n +2" isCommand = True def run_check(self): found = False for o in self.commandOut: temp = ' '.join(o.split()) cols = temp.split(' ') if len(cols)>1: found = True name = cols[0].strip(' ').strip('\n') vg = cols[1].strip(' ').strip('\n') attr = cols[2].strip(' ').strip('\n') size = cols[3].strip(' ').strip('\n') detail = vg + " / " + name + " (" + size + ")" if "hwdiag" in name or "fcd_GAIA" in name: self.add_result(self.title, 'INFO', detail) else: self.add_result(self.title, 'WARN', detail) if not found: self.add_result(self.title, 'INFO', '') class check_gaia_check_cpuse_agent_version(check): page = "GAiA.CPUSE" category = "Agent" title = "Deployment Agent Version" isFirewall = True isManagement = True minVersion = 8020 command = "$DADIR/bin/da_cli da_status" isCommand = True def run_check(self): found = False for o in self.commandOut: if 'up to date' in o: found = True self.add_result(self.title, 'PASS', '') if not found: self.add_result(self.title, 'WARN', 'new version available') class check_gaia_check_cpuse_agent_pending_reboot(check): page = "GAiA.CPUSE" category = "Agent" title = "Deployment Agent Pending Reboot" isFirewall = True isManagement = True minVersion = 8020 command = "$DADIR/bin/da_cli is_pending_reboot" isCommand = True def run_check(self): found = False for o in self.commandOut: if 'no reboot' in o: found = True self.add_result(self.title, 'PASS', '') if not found: self.add_result(self.title, 'WARN', 'Reboot pending!') class check_gaia_check_cpuse_agent_packages(check): page = "GAiA.CPUSE" category = "Packages" title = "Packages available for install" isFirewall = True isManagement = True minVersion = 8020 command = "$DADIR/bin/da_cli packages_info status=available" isCommand = True def run_check(self): found = False for o in self.commandOut: if 'filename' in o: tmp = o.split(':')[1].replace('"','').replace(',','') self.add_result(self.title, 'WARN', tmp) found = True if not found: self.add_result(self.title, 'PASS', '') class check_gaia_check_proxy_settings(check): page = "GAiA.0verview" category = "GAiA Settings" title = "Proxy Configuration" isFirewall = True isManagement = True minVersion = 8020 command = "func.gaia_get_value('proxy:ip-address')" isCommand = False def run_check(self): if self.commandOut: proxy_port = func.gaia_get_value('proxy:port') self.add_result(self.title, 'INFO', self.commandOut + ':' + proxy_port) else: self.add_result(self.title, 'INFO', 'direct') class check_gaia_ntp(check): page = "GAiA.0verview" category = "GAiA Settings" title = "NTP - Time and Date" isFirewall = True isManagement = True minVersion = 8020 command = "ntpstat" isCommand = True def run_check(self): found = False for o in self.commandOut: if 'synchronised to' in o: self.add_result(self.title, "PASS", "") found = True if not found: self.add_result(self.title, "FAIL", "") class check_gaia_dns_external_checkpoint(check): page = "GAiA.Connectivity" category = "DNS Resolver" title = "DNS Lookup [checkpoint.com]" isFirewall = True isManagement = True minVersion = 8020 command = "nslookup checkpoint.com | awk 'NR>3 { print $0 }'" isCommand = True def run_check(self): passme = False detail = "" for line in self.commandOut: if 'Address:' in line: if '209' in line: passme = True detail = line.strip() if passme: self.add_result(self.title, 'PASS', detail) else: self.add_result(self.title, 'FAIL', detail) class check_gaia_dns_external_heise(check): page = "GAiA.Connectivity" category = "DNS Resolver" title = "DNS Lookup [heise.de]" isFirewall = True isManagement = True minVersion = 8020 command = "nslookup heise.de | awk 'NR>3 { print $0 }'" isCommand = True def run_check(self): passme = False detail = "" for line in self.commandOut: if 'Address:' in line: if '193' in line: passme = True detail = line.strip() if passme: self.add_result(self.title, 'PASS', detail) else: self.add_result(self.title, 'FAIL', detail) class check_gaia_z_check_connectivity(check): page = "GAiA.Connectivity" category = "Check Point Services" title = "Connection" isFirewall = True isManagement = True minVersion = 8020 command = "ls" isCommand = True runOnStartup = False def run_check(self): proxy = "" urls = [] urls.append(['http://cws.checkpoint.com/APPI/SystemStatus/type/short','Social Media Widget Detection']) urls.append(['http://cws.checkpoint.com/URLF/SystemStatus/type/short','URL Filtering Cloud Categorization']) urls.append(['http://cws.checkpoint.com/AntiVirus/SystemStatus/type/short','Virus Detection']) urls.append(['http://cws.checkpoint.com/Malware/SystemStatus/type/short','Bot Detection']) urls.append(['https://updates.checkpoint.com/','IPS Updates']) urls.append(['http://dl3.checkpoint.com','Download Service Updates ']) urls.append(['https://usercenter.checkpoint.com/usercenter/services/ProductCoverageService','Contract Entitlement ']) urls.append(['https://usercenter.checkpoint.com/usercenter/services/BladesManagerService','Software Blades Manager Service']) urls.append(['http://resolver1.chkp.ctmail.com','Suspicious Mail Outbreaks']) urls.append(['http://download.ctmail.com','Anti-Spam']) urls.append(['http://te.checkpoint.com','Threat Emulatin']) urls.append(['http://teadv.checkpoint.com','Threat Emulation Advanced']) urls.append(['http://kav8.zonealarm.com/version.txt','Deep inspection']) urls.append(['http://kav8.checkpoint.com','Traditional Anti-Virus']) urls.append(['http://avupdates.checkpoint.com/UrlList.txt','Traditional Anti-Virus, Legacy URL Filtering']) urls.append(['http://sigcheck.checkpoint.com/Siglist2.txt','Download of signature updates']) urls.append(['http://secureupdates.checkpoint.com','Manage Security Gateways']) urls.append(['https://productcoverage.checkpoint.com/ProductCoverageService','Makes sure the machines contracts are up-to-date']) urls.append(['https://sc1.checkpoint.com/sc/images/checkmark.gif','Download of icons and screenshots from Check Point media storage servers']) urls.append(['https://sc1.checkpoint.com/za/images/facetime/large_png/60342479_lrg.png','Download of icons and screenshots from Check Point media storage servers']) urls.append(['https://sc1.checkpoint.com/za/images/facetime/large_png/60096017_lrg.png','Download of icons and screenshots from Check Point media storage servers']) urls.append(['https://push.checkpoint.com','Push Notifications ']) urls.append(['http://downloads.checkpoint.com','Download of Endpoint Compliance Updates']) for url in urls: if self.runOnStartup: out, err = func.execute_command('curl_cli -Lisk ' + proxy + url[0] + ' | head -n1') data = out.read().strip('\n').strip(' ') if "OK" in data or "Found" in data or "Moved" in data or "Connection established" in data: state = "PASS" detail = "" else: state = "FAIL" detail = data self.add_result(self.title + " [" + url[1] + "]", state, detail) else: self.add_result(self.title + " [" + url[1] + "]", 'WAIT', '') def set_command(self): self.runOnStartup = True class check_gaia_interface_bonds(check): page = "GAiA.Networking" category = "Bonding" title = "Bond" isFirewall = True isManagement = True minVersion = 8020 command = "ifconfig | grep -c bond" isCommand = True def run_check(self): if int(self.commandOut[0]) > 0: cmd = "cphaprob show_bond" b_out, b_err = func.execute_command(cmd) for data in b_out: if "|" in data and "bond" in data: cols = data.split("|") b_name = cols[0].strip() b_mode = cols[1].strip() b_stat = cols[2].strip() b_cfg = cols[3].strip() b_up = cols[4].strip() b_req = cols[5].strip() state = "PASS" if b_stat != "UP": state = "WARN" self.add_result(self.title + " [" + b_name + ", " + b_mode + "]", state, b_up + "/" + b_cfg + " , Required: " + b_req) else: self.add_result("No bonding found", "PASS", "") class check_gaia_interface_buffers(check): page = "GAiA.Networking" category = "Ring Buffer" title = "Buffer Size" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "ifconfig | grep HWaddr" isCommand = True def run_check(self): for line in self.commandOut: b_rx = "" b_tx = "" state = "PASS" nic = line.split()[0].strip() b_out, b_err = func.execute_command('ethtool -g ' + nic) for data in b_out: if "RX:" in data: b_rx = data.split()[1].strip() if "TX:" in data: b_tx = data.split()[1].strip() if b_rx != "256": state = "WARN" if b_tx != "1024": state = "WARN" detail = "RX: " + b_rx + ", TX: " + b_tx if not "." in nic: self.add_result(self.title + " [" + nic + "]", state, detail) class check_gaia_interface_stats(check): page = "GAiA.Networking" category = "Statistics" title = "Interface statistics" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "ls" isCommand = True def run_check(self): values_rx = ["rx_dropped", "rx_crc_errors", "rx_errors", "rx_fifo_errors", "rx_frame_errors", "rx_length_errors", "rx_missed_errors", "rx_over_errors"] values_tx = ["tx_aborted_errors", "tx_carrier_errors", "tx_dropped", "tx_errors", "tx_fifo_errors", "tx_heartbeat_errors", "tx_window_errors"] out, err = func.execute_command('ls -1 /sys/class/net | grep -vE "(lo|bond|vpn|sit|\.)"') for line in out: interface = line.strip('\n') i = 0 error = False while i<len(values_rx): read, err = func.execute_command('cat /sys/class/net/'+interface+'/statistics/'+values_rx[i]) val = read.read().strip('\n') state = "PASS" detail = "" if val != "0": state = "FAIL" detail = val error = True self.add_result(self.title + " (" + interface + " - " + values_rx[i] + ")", state, detail) i = i + 1 if not error: for t in values_rx: self.results.pop() self.add_result(self.title + " (" + interface + " - rx/all" + ")", "PASS", "") i = 0 error = False while i<len(values_tx): read, err = func.execute_command('cat /sys/class/net/'+interface+'/statistics/'+values_tx[i]) val = read.read().strip('\n') state = "PASS" detail = "" if val != "0": state = "FAIL" detail = val error = True self.add_result(self.title + " (" + interface + " - " + values_rx[i] + ")", state, detail) i = i + 1 if not error: for t in values_tx: self.results.pop() self.add_result(self.title + " (" + interface + " - tx/all" + ")", "PASS", "") class check_gaia_disk_space(check): page = "GAiA.0verview" category = "Harddisk" title = "Disk Space" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "df -h | sed s/\ \ */\;/g | cut -d ';' -f 6,4 | awk 'NR>1 {print $1}'" isCommand = True def run_check(self): for line in self.commandOut: state = "FAIL" data = str(line).strip('\n').split(";") if len(data) < 2: continue if "M" in data[0]: state = "WARN" if "G" in data[0]: state = "PASS" if data[1] == "/boot" or data[1] == "/dev/shm": state = "PASS" self.add_result(self.title + " (" + data[1] + ")", state, data[0]) class check_gaia_cpu_smt(check): page = "GAiA.0verview" category = "CPU" title = "Hyperthreading/SMT" isFirewall = True isManagement = False minVersion = 8020 command = 'if [ ! -f "/proc/smt_status" ] ; then echo "Not available" ; else cat /proc/smt_status ; fi' isCommand = True def run_check(self): data = self.commandOut[0].strip() if "Unsupported" in data: self.add_result(self.title, "INFO", "Disabled") else: self.add_result(self.title, "INFO", data) class check_gaia_cpu_usage(check): page = "GAiA.0verview" category = "CPU" title = "CPU Usage" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "ls" isCommand = True def run_check(self): if func.isFirewall(): out, err = func.execute_command("fw ctl affinity -l") affinity = out.read() else: affinity = "" dbcur = func.execute_sqlite_query("select name_of_cpu,max(cpu_usage) from UM_STAT_UM_CPU_UM_CPU_ORDERED_TABLE group by name_of_cpu;") for row in dbcur: worker = "" nic = "" daemon = "" cpu = row[0] for line in affinity.split('\n'): if "CPU "+str(cpu)+'#' in line +'#': if "Kernel" in line: if worker != "": worker = worker + ", " worker = worker + line.split(":")[0].replace("Kernel ", "") elif "Daemon" in line: daemon = "Daemon(s), " else: if nic != "": nic = nic + ", " nic = nic + line.split(":")[0] load = str(row[1]).split(".")[0] state = "PASS" if int(load) > 85 and nic != "": state = "FAIL" elif int(load) > 85 and nic == "": state = "WARN" if nic != "": nic = nic + ", " self.add_result(self.title + " (peak - CPU " + str(cpu) + "): " + daemon + nic + worker, state, load + "%") dbcur = func.execute_sqlite_query("select name_of_cpu,avg(cpu_usage) from UM_STAT_UM_CPU_UM_CPU_ORDERED_TABLE group by name_of_cpu;") for row in dbcur: worker = "" nic = "" daemon = "" cpu = row[0] for line in affinity.split('\n'): if "CPU "+str(cpu)+'#' in line+'#': if "Kernel" in line: if worker != "": worker = worker + ", " worker = worker + line.split(":")[0].replace("Kernel ", "") elif "Daemon" in line: daemon = "Daemon(s), " else: if nic != "": nic = nic + ", " nic = nic + line.split(":")[0] load = str(row[1]).split(".")[0] state = "PASS" if int(load) > 50: state = "WARN" if int(load) > 50 and nic != "": state = "FAIL" if int(load) > 85 and worker != "": state = "FAIL" if nic != "": nic = nic + ", " self.add_result(self.title + " (avg - CPU " + str(cpu) + "): " + daemon + nic + worker, state, load + "%") dbcur.close() class check_gaia_memory_usage(check): page = "GAiA.0verview" category = "Memory" title = "Memory Usage" isFirewall = True isManagement = True isClusterXL = False minVersion = 8020 command = "ls" isCommand = True def run_check(self): mem_total = 0 mem_avg = 0 mem_peak = 0 dbcur = func.execute_sqlite_query("select max(real_total) from UM_STAT_UM_MEMORY;") for row in dbcur: mem_total = row[0] dbcur = func.execute_sqlite_query("select avg(real_used) from UM_STAT_UM_MEMORY;") for row in dbcur: mem_avg = row[0] dbcur = func.execute_sqlite_query("select max(real_used) from UM_STAT_UM_MEMORY;") for row in dbcur: mem_peak = row[0] dbcur.close() mem_avg_used = int(str(mem_avg/mem_total*100).split(".")[0]) mem_peak_used = int(str(mem_peak/mem_total*100).split(".")[0]) state = "PASS" if mem_avg_used > 70: state = "WARN" if mem_avg_used > 90: state = "FAIL" self.add_result(self.title + " (average)", state, str(mem_avg_used)+"%") state = "PASS" if mem_peak_used > 80: state = "WARN" self.add_result(self.title + " (peak)", state, str(mem_peak_used)+"%") out, err = func.execute_command("free -g | grep -i swap | awk '{print $3,$4}'") data = out.read().strip('\n').split(" ") used = data[0] avail = data[1] percent = str(int(used) / int(avail) * 100).split(".")[0] state = "WARN" if percent == "0": state = "PASS" self.add_result(self.title + " (swap)", state, percent + "%")

true

1c2fdfdfa6ead222afd8b8eb59e9c9e529e8da83

3,000

py

Python

parton/cli.py

peterstangl/parton

a7adefee7e8372e9b046a51b263d6a06165ff098

[ "MIT" ]

5

2018-12-25T20:56:32.000Z

2022-03-22T00:16:38.000Z

parton/cli.py

peterstangl/parton

a7adefee7e8372e9b046a51b263d6a06165ff098

[ "MIT" ]

1

2022-01-18T07:13:04.000Z

2022-01-28T05:42:29.000Z

parton/cli.py

peterstangl/parton

a7adefee7e8372e9b046a51b263d6a06165ff098

[ "MIT" ]

3

2019-09-20T14:52:16.000Z

2022-03-28T15:27:09.000Z

"""Command line interface.""" import argparse from fnmatch import fnmatch from . import io import tarfile import logging logging.basicConfig(level=logging.INFO) def main(argv=None): parser = argparse.ArgumentParser(prog='parton', description="Command line interface to download parton distribution functions.") subparsers = parser.add_subparsers(title='subcommands') defaultdir = io.data_dir() parser.add_argument("--listdir", default=defaultdir, help="Directory where the index of PDF sets is stored (default: {}).".format(defaultdir)) parser.add_argument("--pdfdir", default=defaultdir, help="Directory where the PDF sets are stored (default: {}).".format(defaultdir)) parser_update = subparsers.add_parser('update', description="Command line script to update the list of PDF sets.", help="Update the list of parton distribution functions.") parser_update.set_defaults(func=update) parser_list = subparsers.add_parser('list', description="Command line script to listthe PDF sets.", help="Show list of parton distribution functions.") parser_list.add_argument('--installed', action='store_true') parser_list.set_defaults(func=listpdf) parser_install = subparsers.add_parser('install', description="Command line script to install a PDF set.", help="Install a PDF set.") parser_install.add_argument('name') parser_install.add_argument('-y', action='store_true') parser_install.set_defaults(func=install) args = parser.parse_args(argv) try: args.func(args) except AttributeError: parser.print_help() def update(args): io.download_index(args.listdir) def install(args): pdfs_av = io.list_available(args.listdir) to_install = [pdf for pdf in pdfs_av if fnmatch(pdf, args.name)] if not to_install: print("No PDF sets matching the pattern {} found.".format(args.name)) return pdfs_in = set(io.list_installed(args.pdfdir, args.listdir)) to_install = [pdf for pdf in to_install if pdf not in pdfs_in] if not to_install: return print("The following PDF sets will be installed:") print('\n'.join(to_install)) yes = args.y or input("Proceed? (y/n): ").lower() if yes: for pdf in to_install: try: io.download_pdfset(pdf, args.pdfdir) except tarfile.TarError: logging.error("Unable to extract archive for PDF set {}".format(pdf)) def listpdf(args): if args.installed: pdfs = io.list_installed(args.pdfdir, args.listdir) else: pdfs = io.list_available(args.listdir) for pdf in pdfs: print(pdf)

37.5

120

0.618

import argparse from fnmatch import fnmatch from . import io import tarfile import logging logging.basicConfig(level=logging.INFO) def main(argv=None): parser = argparse.ArgumentParser(prog='parton', description="Command line interface to download parton distribution functions.") subparsers = parser.add_subparsers(title='subcommands') defaultdir = io.data_dir() parser.add_argument("--listdir", default=defaultdir, help="Directory where the index of PDF sets is stored (default: {}).".format(defaultdir)) parser.add_argument("--pdfdir", default=defaultdir, help="Directory where the PDF sets are stored (default: {}).".format(defaultdir)) parser_update = subparsers.add_parser('update', description="Command line script to update the list of PDF sets.", help="Update the list of parton distribution functions.") parser_update.set_defaults(func=update) parser_list = subparsers.add_parser('list', description="Command line script to listthe PDF sets.", help="Show list of parton distribution functions.") parser_list.add_argument('--installed', action='store_true') parser_list.set_defaults(func=listpdf) parser_install = subparsers.add_parser('install', description="Command line script to install a PDF set.", help="Install a PDF set.") parser_install.add_argument('name') parser_install.add_argument('-y', action='store_true') parser_install.set_defaults(func=install) args = parser.parse_args(argv) try: args.func(args) except AttributeError: parser.print_help() def update(args): io.download_index(args.listdir) def install(args): pdfs_av = io.list_available(args.listdir) to_install = [pdf for pdf in pdfs_av if fnmatch(pdf, args.name)] if not to_install: print("No PDF sets matching the pattern {} found.".format(args.name)) return pdfs_in = set(io.list_installed(args.pdfdir, args.listdir)) to_install = [pdf for pdf in to_install if pdf not in pdfs_in] if not to_install: return print("The following PDF sets will be installed:") print('\n'.join(to_install)) yes = args.y or input("Proceed? (y/n): ").lower() if yes: for pdf in to_install: try: io.download_pdfset(pdf, args.pdfdir) except tarfile.TarError: logging.error("Unable to extract archive for PDF set {}".format(pdf)) def listpdf(args): if args.installed: pdfs = io.list_installed(args.pdfdir, args.listdir) else: pdfs = io.list_available(args.listdir) for pdf in pdfs: print(pdf)

true

1c2fe051fc50416987d34e6e97aa237660a84ae8

5,535

py

Python

kornia/geometry/epipolar/projection.py

FGeri/kornia

92fa259601679031dc59c82ffe6862a1b5c8878a

[ "ECL-2.0", "Apache-2.0" ]

1

2020-06-17T16:57:14.000Z

kornia/geometry/epipolar/projection.py

FGeri/kornia

92fa259601679031dc59c82ffe6862a1b5c8878a

[ "ECL-2.0", "Apache-2.0" ]

null

kornia/geometry/epipolar/projection.py

FGeri/kornia

92fa259601679031dc59c82ffe6862a1b5c8878a

[ "ECL-2.0", "Apache-2.0" ]

1

2022-01-26T13:39:34.000Z

"""Module for image projections.""" from typing import Union import torch from kornia.geometry.epipolar import numeric def intrinsics_like(focal: float, input: torch.Tensor) -> torch.Tensor: r"""Returns a 3x3 instrinsics matrix, with same size as the input. The center of projection will be based in the input image size. Args: focal (float): the focal length for tha camera matrix. input (torch.Tensor): image tensor that will determine the batch size and image height and width. It is assumed to be a tensor in the shape of :math:`(B, C, H, W)`. Returns: torch.Tensor: The camera matrix with the shape of :math:`(B, 3, 3)`. """ assert len(input.shape) == 4, input.shape assert focal > 0, focal B, _, H, W = input.shape intrinsics = numeric.eye_like(3, input) intrinsics[..., 0, 0] *= focal intrinsics[..., 1, 1] *= focal intrinsics[..., 0, 2] += 1. * W / 2 intrinsics[..., 1, 2] += 1. * H / 2 return intrinsics def random_intrinsics(low: Union[float, torch.Tensor], high: Union[float, torch.Tensor]) -> torch.Tensor: r"""Generates a random camera matrix based on a given uniform distribution. Args: low (Union[float, torch.Tensor]): lower range (inclusive). high (Union[float, torch.Tensor]): upper range (exclusive). Returns: torch.Tensor: The random camera matrix with the shape of :math:`(1, 3, 3)`. """ sampler = torch.distributions.Uniform(low, high) fx, fy, cx, cy = [sampler.sample((1,)) for _ in range(4)] zeros, ones = torch.zeros_like(fx), torch.ones_like(fx) camera_matrix: torch.Tensor = torch.cat([ fx, zeros, cx, zeros, fy, cy, zeros, zeros, ones, ]) return camera_matrix.view(1, 3, 3) def scale_intrinsics( camera_matrix: torch.Tensor, scale_factor: Union[float, torch.Tensor]) -> torch.Tensor: r"""Scale a camera matrix containing the intrinsics. Applies the scaling factor to the focal length and center of projection. Args: camera_matrix (torch.Tensor): the camera calibration matrix containing the intrinsic parameters. The expected shape for the tensor is :math:`(B, 3, 3)`. scale_factor (Union[float, torch.Tensor]): the scaling factor to be applied. Returns: torch.Tensor: The scaled camera matrix with shame shape as input :math:`(B, 3, 3)`. """ K_scale = camera_matrix.clone() K_scale[..., 0, 0] *= scale_factor K_scale[..., 1, 1] *= scale_factor K_scale[..., 0, 2] *= scale_factor K_scale[..., 1, 2] *= scale_factor return K_scale def projection_from_KRt(K: torch.Tensor, R: torch.Tensor, t: torch.Tensor) -> torch.Tensor: r"""Get the projection matrix P from K, R and t. This function estimate the projection matrix by solving the following equation: :math:`P = K * [R|t]`. Args: K (torch.Tensor): the camera matrix with the instrinsics with shape :math:`(B, 3, 3)`. R (torch.Tensor): The rotation matrix with shape :math:`(B, 3, 3)`. t (torch.Tensor): The translation vector with shape :math:`(B, 3, 1)`. Returns: torch.Tensor: The projection matrix P with shape :math:`(B, 4, 4)`. """ assert K.shape[-2:] == (3, 3), K.shape assert R.shape[-2:] == (3, 3), R.shape assert t.shape[-2:] == (3, 1), t.shape assert len(K.shape) == len(R.shape) == len(t.shape) Rt: torch.Tensor = torch.cat([R, t], dim=-1) # 3x4 Rt_h = torch.nn.functional.pad(Rt, [0, 0, 0, 1], "constant", 0.) # 4x4 Rt_h[..., -1, -1] += 1. K_h: torch.Tensor = torch.nn.functional.pad(K, [0, 1, 0, 1], "constant", 0.) # 4x4 K_h[..., -1, -1] += 1. return K @ Rt def depth(R: torch.Tensor, t: torch.Tensor, X: torch.Tensor) -> torch.Tensor: r"""Returns the depth of a point transformed by a rigid transform. Args: R (torch.Tensor): The rotation matrix with shape :math:`(*, 3, 3)`. t (torch.Tensor): The translation vector with shape :math:`(*, 3, 1)`. X (torch.Tensor): The 3d points with shape :math:`(*, 3)`. Returns: torch.Tensor: The depth value per point with shape :math:`(*, 1)`. """ X_tmp = R @ X.transpose(-2, -1) X_out = X_tmp[..., 2, :] + t[..., 2, :] return X_out # adapted from: # https://github.com/opencv/opencv_contrib/blob/master/modules/sfm/src/fundamental.cpp#L61 # https://github.com/mapillary/OpenSfM/blob/master/opensfm/multiview.py#L14 def _nullspace(A): '''Compute the null space of A. Return the smallest singular value and the corresponding vector. ''' u, s, vh = torch.svd(A) return s[..., -1], vh[..., -1] def projections_from_fundamental(F_mat: torch.Tensor) -> torch.Tensor: r"""Get the projection matrices from the Fundamenal Matrix. Args: F_mat (torch.Tensor): the fundamenal matrix with the shape :math:`(*, 3, 3)`. Returns: torch.Tensor: The projection matrices with shape :math:`(*, 4, 4, 2)`. """ assert len(F_mat.shape) >= 2, F_mat.shape assert F_mat.shape[-2:] == (3, 3), F_mat.shape R1 = numeric.eye_like(3, F_mat) # Bx3x3 t1 = numeric.vec_like(3, F_mat) # Bx3 Ft_mat = F_mat.transpose(-2, -1) _, e2 = _nullspace(Ft_mat) R2 = numeric.cross_product_matrix(e2) @ F_mat # Bx3x3 t2 = e2[..., :, None] # Bx3x1 P1 = torch.cat([R1, t1], dim=-1) # Bx3x4 P2 = torch.cat([R2, t2], dim=-1) # Bx3x4 return torch.stack([P1, P2], dim=-1)

32.946429

106

0.61897

from typing import Union import torch from kornia.geometry.epipolar import numeric def intrinsics_like(focal: float, input: torch.Tensor) -> torch.Tensor: assert len(input.shape) == 4, input.shape assert focal > 0, focal B, _, H, W = input.shape intrinsics = numeric.eye_like(3, input) intrinsics[..., 0, 0] *= focal intrinsics[..., 1, 1] *= focal intrinsics[..., 0, 2] += 1. * W / 2 intrinsics[..., 1, 2] += 1. * H / 2 return intrinsics def random_intrinsics(low: Union[float, torch.Tensor], high: Union[float, torch.Tensor]) -> torch.Tensor: sampler = torch.distributions.Uniform(low, high) fx, fy, cx, cy = [sampler.sample((1,)) for _ in range(4)] zeros, ones = torch.zeros_like(fx), torch.ones_like(fx) camera_matrix: torch.Tensor = torch.cat([ fx, zeros, cx, zeros, fy, cy, zeros, zeros, ones, ]) return camera_matrix.view(1, 3, 3) def scale_intrinsics( camera_matrix: torch.Tensor, scale_factor: Union[float, torch.Tensor]) -> torch.Tensor: K_scale = camera_matrix.clone() K_scale[..., 0, 0] *= scale_factor K_scale[..., 1, 1] *= scale_factor K_scale[..., 0, 2] *= scale_factor K_scale[..., 1, 2] *= scale_factor return K_scale def projection_from_KRt(K: torch.Tensor, R: torch.Tensor, t: torch.Tensor) -> torch.Tensor: assert K.shape[-2:] == (3, 3), K.shape assert R.shape[-2:] == (3, 3), R.shape assert t.shape[-2:] == (3, 1), t.shape assert len(K.shape) == len(R.shape) == len(t.shape) Rt: torch.Tensor = torch.cat([R, t], dim=-1) Rt_h = torch.nn.functional.pad(Rt, [0, 0, 0, 1], "constant", 0.) Rt_h[..., -1, -1] += 1. K_h: torch.Tensor = torch.nn.functional.pad(K, [0, 1, 0, 1], "constant", 0.) K_h[..., -1, -1] += 1. return K @ Rt def depth(R: torch.Tensor, t: torch.Tensor, X: torch.Tensor) -> torch.Tensor: X_tmp = R @ X.transpose(-2, -1) X_out = X_tmp[..., 2, :] + t[..., 2, :] return X_out _nullspace(A): u, s, vh = torch.svd(A) return s[..., -1], vh[..., -1] def projections_from_fundamental(F_mat: torch.Tensor) -> torch.Tensor: assert len(F_mat.shape) >= 2, F_mat.shape assert F_mat.shape[-2:] == (3, 3), F_mat.shape R1 = numeric.eye_like(3, F_mat) t1 = numeric.vec_like(3, F_mat) Ft_mat = F_mat.transpose(-2, -1) _, e2 = _nullspace(Ft_mat) R2 = numeric.cross_product_matrix(e2) @ F_mat t2 = e2[..., :, None] P1 = torch.cat([R1, t1], dim=-1) P2 = torch.cat([R2, t2], dim=-1) return torch.stack([P1, P2], dim=-1)

true

1c2fe086337950aa673e79642215c2f1a374b0ea

30,570

py

Python

app/grandchallenge/evaluation/migrations/0001_initial.py

kaczmarj/grand-challenge.org

8dc8a2170e51072354f7e94f2a22578805a67b94

[ "Apache-2.0" ]

7

2016-11-05T07:16:30.000Z

2017-11-23T03:38:03.000Z

app/grandchallenge/evaluation/migrations/0001_initial.py

kaczmarj/grand-challenge.org

8dc8a2170e51072354f7e94f2a22578805a67b94

[ "Apache-2.0" ]

113

2015-05-26T09:27:59.000Z

2018-03-21T10:45:56.000Z

app/grandchallenge/evaluation/migrations/0001_initial.py

kaczmarj/grand-challenge.org

8dc8a2170e51072354f7e94f2a22578805a67b94

[ "Apache-2.0" ]

7

2015-07-16T20:11:22.000Z

2017-06-06T02:41:24.000Z

# Generated by Django 3.1.1 on 2020-12-02 13:26 import uuid from decimal import Decimal import django.core.validators import django.db.models.deletion import django_extensions.db.fields from django.conf import settings from django.db import migrations, models import grandchallenge.components.models import grandchallenge.core.storage import grandchallenge.core.validators import grandchallenge.evaluation.models class Migration(migrations.Migration): initial = True dependencies = [ ("algorithms", "0001_initial"), migrations.swappable_dependency(settings.AUTH_USER_MODEL), ("challenges", "0001_initial"), ("components", "0001_initial"), ("archives", "0001_initial"), ] operations = [ migrations.CreateModel( name="Phase", fields=[ ( "id", models.UUIDField( default=uuid.uuid4, editable=False, primary_key=True, serialize=False, ), ), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "title", models.CharField( default="Challenge", help_text="The title of this phase.", max_length=64, ), ), ( "slug", django_extensions.db.fields.AutoSlugField( blank=True, editable=False, max_length=64, populate_from="title", ), ), ( "score_title", models.CharField( default="Score", help_text="The name that will be displayed for the scores column, for instance: Score (log-loss)", max_length=32, ), ), ( "score_jsonpath", models.CharField( blank=True, help_text="The jsonpath of the field in metrics.json that will be used for the overall scores on the results page. See http://goessner.net/articles/JsonPath/ for syntax. For example: dice.mean", max_length=255, ), ), ( "score_error_jsonpath", models.CharField( blank=True, help_text="The jsonpath for the field in metrics.json that contains the error of the score, eg: dice.std", max_length=255, ), ), ( "score_default_sort", models.CharField( choices=[("asc", "Ascending"), ("desc", "Descending")], default="desc", help_text="The default sorting to use for the scores on the results page.", max_length=4, ), ), ( "score_decimal_places", models.PositiveSmallIntegerField( default=4, help_text="The number of decimal places to display for the score", ), ), ( "extra_results_columns", models.JSONField( blank=True, default=list, help_text="A JSON object that contains the extra columns from metrics.json that will be displayed on the results page. ", validators=[ grandchallenge.core.validators.JSONValidator( schema={ "$schema": "http://json-schema.org/draft-06/schema#", "definitions": {}, "items": { "$id": "#/items", "additionalProperties": False, "properties": { "error_path": { "$id": "#/items/properties/error_path", "default": "", "examples": [ "aggregates.dice.std" ], "pattern": "^(.*)$", "title": "The Error Path Schema", "type": "string", }, "order": { "$id": "#/items/properties/order", "default": "", "enum": ["asc", "desc"], "examples": ["asc"], "pattern": "^(asc|desc)$", "title": "The Order Schema", "type": "string", }, "path": { "$id": "#/items/properties/path", "default": "", "examples": [ "aggregates.dice.mean" ], "pattern": "^(.*)$", "title": "The Path Schema", "type": "string", }, "title": { "$id": "#/items/properties/title", "default": "", "examples": ["Mean Dice"], "pattern": "^(.*)$", "title": "The Title Schema", "type": "string", }, }, "required": ["title", "path", "order"], "title": "The Items Schema", "type": "object", }, "title": "The Extra Results Columns Schema", "type": "array", } ) ], ), ), ( "scoring_method_choice", models.CharField( choices=[ ( "abs", "Use the absolute value of the score column", ), ( "avg", "Use the mean of the relative ranks of the score and extra result columns", ), ( "med", "Use the median of the relative ranks of the score and extra result columns", ), ], default="abs", help_text="How should the rank of each result be calculated?", max_length=3, ), ), ( "result_display_choice", models.CharField( choices=[ ("all", "Display all results"), ( "rec", "Only display each users most recent result", ), ("bst", "Only display each users best result"), ], default="all", help_text="Which results should be displayed on the leaderboard?", max_length=3, ), ), ( "submission_kind", models.PositiveSmallIntegerField( choices=[(1, "CSV"), (2, "ZIP"), (3, "Algorithm")], default=1, help_text="Should participants submit a .csv/.zip file of predictions, or an algorithm?", ), ), ( "allow_submission_comments", models.BooleanField( default=False, help_text="Allow users to submit comments as part of their submission.", ), ), ( "display_submission_comments", models.BooleanField( default=False, help_text="If true, submission comments are shown on the results page.", ), ), ( "supplementary_file_choice", models.CharField( choices=[ ("off", "Off"), ("opt", "Optional"), ("req", "Required"), ], default="off", help_text="Show a supplementary file field on the submissions page so that users can upload an additional file along with their predictions file as part of their submission (eg, include a pdf description of their method). Off turns this feature off, Optional means that including the file is optional for the user, Required means that the user must upload a supplementary file.", max_length=3, ), ), ( "supplementary_file_label", models.CharField( blank=True, default="Supplementary File", help_text="The label that will be used on the submission and results page for the supplementary file. For example: Algorithm Description.", max_length=32, ), ), ( "supplementary_file_help_text", models.CharField( blank=True, default="", help_text='The help text to include on the submissions page to describe the submissions file. Eg: "A PDF description of the method.".', max_length=128, ), ), ( "show_supplementary_file_link", models.BooleanField( default=False, help_text="Show a link to download the supplementary file on the results page.", ), ), ( "publication_url_choice", models.CharField( choices=[ ("off", "Off"), ("opt", "Optional"), ("req", "Required"), ], default="off", help_text="Show a supplementary url field on the submission page so that users can submit a link to a publication that corresponds to their submission. Off turns this feature off, Optional means that including the url is optional for the user, Required means that the user must provide an url.", max_length=3, ), ), ( "show_publication_url", models.BooleanField( default=False, help_text="Show a link to the supplementary url on the results page", ), ), ( "daily_submission_limit", models.PositiveIntegerField( default=10, help_text="The limit on the number of times that a user can make a submission over the submission limit period. Set this to 0 to close submissions for this phase.", ), ), ( "submissions_open", models.DateTimeField( blank=True, help_text="If set, participants will not be able to make submissions to this phase before this time.", null=True, ), ), ( "submissions_close", models.DateTimeField( blank=True, help_text="If set, participants will not be able to make submissions to this phase after this time.", null=True, ), ), ( "submission_page_html", models.TextField( blank=True, help_text="HTML to include on the submission page for this challenge.", ), ), ( "auto_publish_new_results", models.BooleanField( default=True, help_text="If true, new results are automatically made public. If false, the challenge administrator must manually publish each new result.", ), ), ( "display_all_metrics", models.BooleanField( default=True, help_text="Should all of the metrics be displayed on the Result detail page?", ), ), ( "evaluation_detail_observable_url", models.URLField( blank=True, help_text="The URL of the embeddable observable notebook for viewing individual results. Must be of the form https://observablehq.com/embed/@user/notebook?cell=...", max_length=2000, validators=[ django.core.validators.RegexValidator( "^https\\:\\/\\/observablehq\\.com\\/embed\\/\\@[^\\/]+\\/[^\\?\\.]+\\?cell\\=.*$", "URL must be of the form https://observablehq.com/embed/@user/notebook?cell=*", ) ], ), ), ( "evaluation_comparison_observable_url", models.URLField( blank=True, help_text="The URL of the embeddable observable notebook for comparingresults. Must be of the form https://observablehq.com/embed/@user/notebook?cell=...", max_length=2000, validators=[ django.core.validators.RegexValidator( "^https\\:\\/\\/observablehq\\.com\\/embed\\/\\@[^\\/]+\\/[^\\?\\.]+\\?cell\\=.*$", "URL must be of the form https://observablehq.com/embed/@user/notebook?cell=*", ) ], ), ), ( "archive", models.ForeignKey( blank=True, help_text="Which archive should be used as the source dataset for this phase?", null=True, on_delete=django.db.models.deletion.SET_NULL, to="archives.archive", ), ), ( "challenge", models.ForeignKey( editable=False, on_delete=django.db.models.deletion.CASCADE, to="challenges.challenge", ), ), ( "inputs", models.ManyToManyField( related_name="evaluation_inputs", to="components.ComponentInterface", ), ), ( "outputs", models.ManyToManyField( related_name="evaluation_outputs", to="components.ComponentInterface", ), ), ], options={ "ordering": ("challenge", "submissions_open", "created"), "permissions": ( ("create_phase_submission", "Create Phase Submission"), ), "unique_together": { ("challenge", "slug"), ("challenge", "title"), }, }, ), migrations.CreateModel( name="Submission", fields=[ ( "id", models.UUIDField( default=uuid.uuid4, editable=False, primary_key=True, serialize=False, ), ), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "creators_ip", models.GenericIPAddressField( default=None, editable=False, null=True ), ), ( "creators_user_agent", models.TextField(blank=True, default="", editable=False), ), ( "predictions_file", models.FileField( blank=True, storage=grandchallenge.core.storage.ProtectedS3Storage(), upload_to=grandchallenge.evaluation.models.submission_file_path, validators=[ grandchallenge.core.validators.MimeTypeValidator( allowed_types=("application/zip", "text/plain") ), grandchallenge.core.validators.ExtensionValidator( allowed_extensions=(".zip", ".csv") ), ], ), ), ( "supplementary_file", models.FileField( blank=True, storage=grandchallenge.core.storage.PublicS3Storage(), upload_to=grandchallenge.evaluation.models.submission_supplementary_file_path, validators=[ grandchallenge.core.validators.MimeTypeValidator( allowed_types=("text/plain", "application/pdf") ) ], ), ), ( "comment", models.CharField( blank=True, default="", help_text="You can add a comment here to help you keep track of your submissions.", max_length=128, ), ), ( "publication_url", models.URLField( blank=True, help_text="A URL associated with this submission.", ), ), ( "algorithm_image", models.ForeignKey( null=True, on_delete=django.db.models.deletion.SET_NULL, to="algorithms.algorithmimage", ), ), ( "creator", models.ForeignKey( null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL, ), ), ( "phase", models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, to="evaluation.phase", ), ), ], options={ "unique_together": { ("phase", "predictions_file", "algorithm_image") } }, ), migrations.CreateModel( name="Method", fields=[ ( "id", models.UUIDField( default=uuid.uuid4, editable=False, primary_key=True, serialize=False, ), ), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "staged_image_uuid", models.UUIDField(blank=True, editable=False, null=True), ), ( "image", models.FileField( blank=True, help_text=".tar.xz archive of the container image produced from the command 'docker save IMAGE | xz -c > IMAGE.tar.xz'. See https://docs.docker.com/engine/reference/commandline/save/", storage=grandchallenge.core.storage.PrivateS3Storage(), upload_to=grandchallenge.components.models.docker_image_path, validators=[ grandchallenge.core.validators.ExtensionValidator( allowed_extensions=( ".tar", ".tar.gz", ".tar.xz", ) ) ], ), ), ( "image_sha256", models.CharField(editable=False, max_length=71), ), ( "ready", models.BooleanField( default=False, editable=False, help_text="Is this image ready to be used?", ), ), ("status", models.TextField(editable=False)), ("requires_gpu", models.BooleanField(default=False)), ( "requires_gpu_memory_gb", models.PositiveIntegerField(default=4), ), ("requires_memory_gb", models.PositiveIntegerField(default=4)), ( "requires_cpu_cores", models.DecimalField( decimal_places=2, default=Decimal("1.0"), max_digits=4 ), ), ( "creator", models.ForeignKey( null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL, ), ), ( "phase", models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, to="evaluation.phase", ), ), ], options={"abstract": False}, ), migrations.CreateModel( name="Evaluation", fields=[ ( "id", models.UUIDField( default=uuid.uuid4, editable=False, primary_key=True, serialize=False, ), ), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "status", models.PositiveSmallIntegerField( choices=[ (0, "Queued"), (1, "Started"), (2, "Re-Queued"), (3, "Failed"), (4, "Succeeded"), (5, "Cancelled"), ], default=0, ), ), ("stdout", models.TextField()), ("stderr", models.TextField(default="")), ( "error_message", models.CharField(default="", max_length=1024), ), ("started_at", models.DateTimeField(null=True)), ("completed_at", models.DateTimeField(null=True)), ("published", models.BooleanField(default=True)), ( "rank", models.PositiveIntegerField( default=0, help_text="The position of this result on the leaderboard. If the value is zero, then the result is unranked.", ), ), ("rank_score", models.FloatField(default=0.0)), ("rank_per_metric", models.JSONField(default=dict)), ( "inputs", models.ManyToManyField( related_name="evaluation_evaluations_as_input", to="components.ComponentInterfaceValue", ), ), ( "method", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="evaluation.method", ), ), ( "outputs", models.ManyToManyField( related_name="evaluation_evaluations_as_output", to="components.ComponentInterfaceValue", ), ), ( "submission", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="evaluation.submission", ), ), ], options={"abstract": False}, ), migrations.CreateModel( name="AlgorithmEvaluation", fields=[ ( "status", models.PositiveSmallIntegerField( choices=[ (0, "Queued"), (1, "Started"), (2, "Re-Queued"), (3, "Failed"), (4, "Succeeded"), (5, "Cancelled"), ], default=0, ), ), ("stdout", models.TextField()), ("stderr", models.TextField(default="")), ( "error_message", models.CharField(default="", max_length=1024), ), ("started_at", models.DateTimeField(null=True)), ("completed_at", models.DateTimeField(null=True)), ("id", models.BigAutoField(primary_key=True, serialize=False)), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "inputs", models.ManyToManyField( related_name="evaluation_algorithmevaluations_as_input", to="components.ComponentInterfaceValue", ), ), ( "outputs", models.ManyToManyField( related_name="evaluation_algorithmevaluations_as_output", to="components.ComponentInterfaceValue", ), ), ( "submission", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="evaluation.submission", ), ), ], options={"abstract": False}, ), ]

43.056338

403

0.367648

import uuid from decimal import Decimal import django.core.validators import django.db.models.deletion import django_extensions.db.fields from django.conf import settings from django.db import migrations, models import grandchallenge.components.models import grandchallenge.core.storage import grandchallenge.core.validators import grandchallenge.evaluation.models class Migration(migrations.Migration): initial = True dependencies = [ ("algorithms", "0001_initial"), migrations.swappable_dependency(settings.AUTH_USER_MODEL), ("challenges", "0001_initial"), ("components", "0001_initial"), ("archives", "0001_initial"), ] operations = [ migrations.CreateModel( name="Phase", fields=[ ( "id", models.UUIDField( default=uuid.uuid4, editable=False, primary_key=True, serialize=False, ), ), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "title", models.CharField( default="Challenge", help_text="The title of this phase.", max_length=64, ), ), ( "slug", django_extensions.db.fields.AutoSlugField( blank=True, editable=False, max_length=64, populate_from="title", ), ), ( "score_title", models.CharField( default="Score", help_text="The name that will be displayed for the scores column, for instance: Score (log-loss)", max_length=32, ), ), ( "score_jsonpath", models.CharField( blank=True, help_text="The jsonpath of the field in metrics.json that will be used for the overall scores on the results page. See http://goessner.net/articles/JsonPath/ for syntax. For example: dice.mean", max_length=255, ), ), ( "score_error_jsonpath", models.CharField( blank=True, help_text="The jsonpath for the field in metrics.json that contains the error of the score, eg: dice.std", max_length=255, ), ), ( "score_default_sort", models.CharField( choices=[("asc", "Ascending"), ("desc", "Descending")], default="desc", help_text="The default sorting to use for the scores on the results page.", max_length=4, ), ), ( "score_decimal_places", models.PositiveSmallIntegerField( default=4, help_text="The number of decimal places to display for the score", ), ), ( "extra_results_columns", models.JSONField( blank=True, default=list, help_text="A JSON object that contains the extra columns from metrics.json that will be displayed on the results page. ", validators=[ grandchallenge.core.validators.JSONValidator( schema={ "$schema": "http://json-schema.org/draft-06/schema#", "definitions": {}, "items": { "$id": "#/items", "additionalProperties": False, "properties": { "error_path": { "$id": "#/items/properties/error_path", "default": "", "examples": [ "aggregates.dice.std" ], "pattern": "^(.*)$", "title": "The Error Path Schema", "type": "string", }, "order": { "$id": "#/items/properties/order", "default": "", "enum": ["asc", "desc"], "examples": ["asc"], "pattern": "^(asc|desc)$", "title": "The Order Schema", "type": "string", }, "path": { "$id": "#/items/properties/path", "default": "", "examples": [ "aggregates.dice.mean" ], "pattern": "^(.*)$", "title": "The Path Schema", "type": "string", }, "title": { "$id": "#/items/properties/title", "default": "", "examples": ["Mean Dice"], "pattern": "^(.*)$", "title": "The Title Schema", "type": "string", }, }, "required": ["title", "path", "order"], "title": "The Items Schema", "type": "object", }, "title": "The Extra Results Columns Schema", "type": "array", } ) ], ), ), ( "scoring_method_choice", models.CharField( choices=[ ( "abs", "Use the absolute value of the score column", ), ( "avg", "Use the mean of the relative ranks of the score and extra result columns", ), ( "med", "Use the median of the relative ranks of the score and extra result columns", ), ], default="abs", help_text="How should the rank of each result be calculated?", max_length=3, ), ), ( "result_display_choice", models.CharField( choices=[ ("all", "Display all results"), ( "rec", "Only display each users most recent result", ), ("bst", "Only display each users best result"), ], default="all", help_text="Which results should be displayed on the leaderboard?", max_length=3, ), ), ( "submission_kind", models.PositiveSmallIntegerField( choices=[(1, "CSV"), (2, "ZIP"), (3, "Algorithm")], default=1, help_text="Should participants submit a .csv/.zip file of predictions, or an algorithm?", ), ), ( "allow_submission_comments", models.BooleanField( default=False, help_text="Allow users to submit comments as part of their submission.", ), ), ( "display_submission_comments", models.BooleanField( default=False, help_text="If true, submission comments are shown on the results page.", ), ), ( "supplementary_file_choice", models.CharField( choices=[ ("off", "Off"), ("opt", "Optional"), ("req", "Required"), ], default="off", help_text="Show a supplementary file field on the submissions page so that users can upload an additional file along with their predictions file as part of their submission (eg, include a pdf description of their method). Off turns this feature off, Optional means that including the file is optional for the user, Required means that the user must upload a supplementary file.", max_length=3, ), ), ( "supplementary_file_label", models.CharField( blank=True, default="Supplementary File", help_text="The label that will be used on the submission and results page for the supplementary file. For example: Algorithm Description.", max_length=32, ), ), ( "supplementary_file_help_text", models.CharField( blank=True, default="", help_text='The help text to include on the submissions page to describe the submissions file. Eg: "A PDF description of the method.".', max_length=128, ), ), ( "show_supplementary_file_link", models.BooleanField( default=False, help_text="Show a link to download the supplementary file on the results page.", ), ), ( "publication_url_choice", models.CharField( choices=[ ("off", "Off"), ("opt", "Optional"), ("req", "Required"), ], default="off", help_text="Show a supplementary url field on the submission page so that users can submit a link to a publication that corresponds to their submission. Off turns this feature off, Optional means that including the url is optional for the user, Required means that the user must provide an url.", max_length=3, ), ), ( "show_publication_url", models.BooleanField( default=False, help_text="Show a link to the supplementary url on the results page", ), ), ( "daily_submission_limit", models.PositiveIntegerField( default=10, help_text="The limit on the number of times that a user can make a submission over the submission limit period. Set this to 0 to close submissions for this phase.", ), ), ( "submissions_open", models.DateTimeField( blank=True, help_text="If set, participants will not be able to make submissions to this phase before this time.", null=True, ), ), ( "submissions_close", models.DateTimeField( blank=True, help_text="If set, participants will not be able to make submissions to this phase after this time.", null=True, ), ), ( "submission_page_html", models.TextField( blank=True, help_text="HTML to include on the submission page for this challenge.", ), ), ( "auto_publish_new_results", models.BooleanField( default=True, help_text="If true, new results are automatically made public. If false, the challenge administrator must manually publish each new result.", ), ), ( "display_all_metrics", models.BooleanField( default=True, help_text="Should all of the metrics be displayed on the Result detail page?", ), ), ( "evaluation_detail_observable_url", models.URLField( blank=True, help_text="The URL of the embeddable observable notebook for viewing individual results. Must be of the form https://observablehq.com/embed/@user/notebook?cell=...", max_length=2000, validators=[ django.core.validators.RegexValidator( "^https\\:\\/\\/observablehq\\.com\\/embed\\/\\@[^\\/]+\\/[^\\?\\.]+\\?cell\\=.*$", "URL must be of the form https://observablehq.com/embed/@user/notebook?cell=*", ) ], ), ), ( "evaluation_comparison_observable_url", models.URLField( blank=True, help_text="The URL of the embeddable observable notebook for comparingresults. Must be of the form https://observablehq.com/embed/@user/notebook?cell=...", max_length=2000, validators=[ django.core.validators.RegexValidator( "^https\\:\\/\\/observablehq\\.com\\/embed\\/\\@[^\\/]+\\/[^\\?\\.]+\\?cell\\=.*$", "URL must be of the form https://observablehq.com/embed/@user/notebook?cell=*", ) ], ), ), ( "archive", models.ForeignKey( blank=True, help_text="Which archive should be used as the source dataset for this phase?", null=True, on_delete=django.db.models.deletion.SET_NULL, to="archives.archive", ), ), ( "challenge", models.ForeignKey( editable=False, on_delete=django.db.models.deletion.CASCADE, to="challenges.challenge", ), ), ( "inputs", models.ManyToManyField( related_name="evaluation_inputs", to="components.ComponentInterface", ), ), ( "outputs", models.ManyToManyField( related_name="evaluation_outputs", to="components.ComponentInterface", ), ), ], options={ "ordering": ("challenge", "submissions_open", "created"), "permissions": ( ("create_phase_submission", "Create Phase Submission"), ), "unique_together": { ("challenge", "slug"), ("challenge", "title"), }, }, ), migrations.CreateModel( name="Submission", fields=[ ( "id", models.UUIDField( default=uuid.uuid4, editable=False, primary_key=True, serialize=False, ), ), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "creators_ip", models.GenericIPAddressField( default=None, editable=False, null=True ), ), ( "creators_user_agent", models.TextField(blank=True, default="", editable=False), ), ( "predictions_file", models.FileField( blank=True, storage=grandchallenge.core.storage.ProtectedS3Storage(), upload_to=grandchallenge.evaluation.models.submission_file_path, validators=[ grandchallenge.core.validators.MimeTypeValidator( allowed_types=("application/zip", "text/plain") ), grandchallenge.core.validators.ExtensionValidator( allowed_extensions=(".zip", ".csv") ), ], ), ), ( "supplementary_file", models.FileField( blank=True, storage=grandchallenge.core.storage.PublicS3Storage(), upload_to=grandchallenge.evaluation.models.submission_supplementary_file_path, validators=[ grandchallenge.core.validators.MimeTypeValidator( allowed_types=("text/plain", "application/pdf") ) ], ), ), ( "comment", models.CharField( blank=True, default="", help_text="You can add a comment here to help you keep track of your submissions.", max_length=128, ), ), ( "publication_url", models.URLField( blank=True, help_text="A URL associated with this submission.", ), ), ( "algorithm_image", models.ForeignKey( null=True, on_delete=django.db.models.deletion.SET_NULL, to="algorithms.algorithmimage", ), ), ( "creator", models.ForeignKey( null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL, ), ), ( "phase", models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, to="evaluation.phase", ), ), ], options={ "unique_together": { ("phase", "predictions_file", "algorithm_image") } }, ), migrations.CreateModel( name="Method", fields=[ ( "id", models.UUIDField( default=uuid.uuid4, editable=False, primary_key=True, serialize=False, ), ), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "staged_image_uuid", models.UUIDField(blank=True, editable=False, null=True), ), ( "image", models.FileField( blank=True, help_text=".tar.xz archive of the container image produced from the command 'docker save IMAGE | xz -c > IMAGE.tar.xz'. See https://docs.docker.com/engine/reference/commandline/save/", storage=grandchallenge.core.storage.PrivateS3Storage(), upload_to=grandchallenge.components.models.docker_image_path, validators=[ grandchallenge.core.validators.ExtensionValidator( allowed_extensions=( ".tar", ".tar.gz", ".tar.xz", ) ) ], ), ), ( "image_sha256", models.CharField(editable=False, max_length=71), ), ( "ready", models.BooleanField( default=False, editable=False, help_text="Is this image ready to be used?", ), ), ("status", models.TextField(editable=False)), ("requires_gpu", models.BooleanField(default=False)), ( "requires_gpu_memory_gb", models.PositiveIntegerField(default=4), ), ("requires_memory_gb", models.PositiveIntegerField(default=4)), ( "requires_cpu_cores", models.DecimalField( decimal_places=2, default=Decimal("1.0"), max_digits=4 ), ), ( "creator", models.ForeignKey( null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL, ), ), ( "phase", models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, to="evaluation.phase", ), ), ], options={"abstract": False}, ), migrations.CreateModel( name="Evaluation", fields=[ ( "id", models.UUIDField( default=uuid.uuid4, editable=False, primary_key=True, serialize=False, ), ), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "status", models.PositiveSmallIntegerField( choices=[ (0, "Queued"), (1, "Started"), (2, "Re-Queued"), (3, "Failed"), (4, "Succeeded"), (5, "Cancelled"), ], default=0, ), ), ("stdout", models.TextField()), ("stderr", models.TextField(default="")), ( "error_message", models.CharField(default="", max_length=1024), ), ("started_at", models.DateTimeField(null=True)), ("completed_at", models.DateTimeField(null=True)), ("published", models.BooleanField(default=True)), ( "rank", models.PositiveIntegerField( default=0, help_text="The position of this result on the leaderboard. If the value is zero, then the result is unranked.", ), ), ("rank_score", models.FloatField(default=0.0)), ("rank_per_metric", models.JSONField(default=dict)), ( "inputs", models.ManyToManyField( related_name="evaluation_evaluations_as_input", to="components.ComponentInterfaceValue", ), ), ( "method", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="evaluation.method", ), ), ( "outputs", models.ManyToManyField( related_name="evaluation_evaluations_as_output", to="components.ComponentInterfaceValue", ), ), ( "submission", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="evaluation.submission", ), ), ], options={"abstract": False}, ), migrations.CreateModel( name="AlgorithmEvaluation", fields=[ ( "status", models.PositiveSmallIntegerField( choices=[ (0, "Queued"), (1, "Started"), (2, "Re-Queued"), (3, "Failed"), (4, "Succeeded"), (5, "Cancelled"), ], default=0, ), ), ("stdout", models.TextField()), ("stderr", models.TextField(default="")), ( "error_message", models.CharField(default="", max_length=1024), ), ("started_at", models.DateTimeField(null=True)), ("completed_at", models.DateTimeField(null=True)), ("id", models.BigAutoField(primary_key=True, serialize=False)), ("created", models.DateTimeField(auto_now_add=True)), ("modified", models.DateTimeField(auto_now=True)), ( "inputs", models.ManyToManyField( related_name="evaluation_algorithmevaluations_as_input", to="components.ComponentInterfaceValue", ), ), ( "outputs", models.ManyToManyField( related_name="evaluation_algorithmevaluations_as_output", to="components.ComponentInterfaceValue", ), ), ( "submission", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="evaluation.submission", ), ), ], options={"abstract": False}, ), ]

true

1c2fe087748a1234df572bee756c776a9b182f2d

363

py

Python

my_classes/Tuples/.history/name_tuples_20210721190506.py

minefarmer/deep-Dive-1

b0675b853180c5b5781888266ea63a3793b8d855

[ "Unlicense" ]

null

my_classes/Tuples/.history/name_tuples_20210721190506.py

minefarmer/deep-Dive-1

b0675b853180c5b5781888266ea63a3793b8d855

[ "Unlicense" ]

null

my_classes/Tuples/.history/name_tuples_20210721190506.py

minefarmer/deep-Dive-1

b0675b853180c5b5781888266ea63a3793b8d855

[ "Unlicense" ]

null

""" Tuple as Data Structure We have see how we interpreted tuples as data structures The position of the object contained in the tuple gives it meaning For example, we can represent a 2D coordinate as: (10, 20) x y If pt is a position tuple, we can retrieve the x and y coordinates using: """

30.25

73

0.61708

true

1c2fe11c6ac3fa508db890bc4ec79ab09cf86292

4,779

py

Python

Programs/sent_processing/processing_dwe_17.py

mikepackard415/Scientific-Environmental-Discourse

f8d08734f7c2ce98e088479ac7b58c7b348c0401

[ "MIT" ]

null

Programs/sent_processing/processing_dwe_17.py

mikepackard415/Scientific-Environmental-Discourse

f8d08734f7c2ce98e088479ac7b58c7b348c0401

[ "MIT" ]

null

Programs/sent_processing/processing_dwe_17.py

mikepackard415/Scientific-Environmental-Discourse

f8d08734f7c2ce98e088479ac7b58c7b348c0401

[ "MIT" ]

null

import pandas as pd import ast import dask.dataframe as dd from gensim.utils import effective_n_jobs import spacy try: nlp = spacy.load("en") except OSError: nlp = spacy.load("en_core_web_sm") path = 'Environmental-Discourse' env = pd.read_pickle('../../Data/'+path+'/env_0.pkl') env = env[env.year == 2017] def word_tokenize(word_list, model=nlp, MAX_LEN=1500000): tokenized = [] if type(word_list) == list and len(word_list) == 1: word_list = word_list[0] if type(word_list) == list: word_list = ' '.join([str(elem) for elem in word_list]) # since we're only tokenizing, I remove RAM intensive operations and increase max text size model.max_length = MAX_LEN doc = model(word_list, disable=["parser", "tagger", "ner", "lemmatizer"]) for token in doc: if not token.is_punct and len(token.text.strip()) > 0: tokenized.append(token.text) return tokenized def normalizeTokens(word_list, extra_stop=[], model=nlp, lemma=True, MAX_LEN=1500000): #We can use a generator here as we just need to iterate over it normalized = [] if type(word_list) == list and len(word_list) == 1: word_list = word_list[0] if type(word_list) == list: word_list = ' '.join([str(elem) for elem in word_list]) # since we're only normalizing, I remove RAM intensive operations and increase max text size model.max_length = MAX_LEN doc = model(word_list.lower(), disable=["parser", "ner"]) if len(extra_stop) > 0: for stopword in extra_stop: lexeme = nlp.vocab[stopword] lexeme.is_stop = True # we check if we want lemmas or not earlier to avoid checking every time we loop if lemma: for w in doc: # if it's not a stop word or punctuation mark, add it to our article if w.text != '\n' and not w.is_stop and not w.is_punct and not w.like_num and len(w.text.strip()) > 0: # we add the lematized version of the word normalized.append(str(w.lemma_)) else: for w in doc: # if it's not a stop word or punctuation mark, add it to our article if w.text != '\n' and not w.is_stop and not w.is_punct and not w.like_num and len(w.text.strip()) > 0: # we add the lematized version of the word normalized.append(str(w.text.strip())) return normalized def ngram_tagger(tokens): n = len(tokens) i = 0 tokens_q = [] tokens_qt = [] tokens_qtb = [] # quadgrams while i < n: words = '_'.join(tokens[i:i+4]) if words in quadgrams: tokens_q.append(words) i += 4 else: tokens_q.append(tokens[i]) i += 1 # trigrams n = len(tokens_q) i = 0 while i < n: words = '_'.join(tokens_q[i:i+3]) if words in trigrams: tokens_qt.append(words) i += 3 else: tokens_qt.append(tokens_q[i]) i += 1 # bigrams n = len(tokens_qt) i = 0 while i < n: words = '_'.join(tokens_qt[i:i+2]) if words in bigrams: tokens_qtb.append(words) i += 2 else: tokens_qtb.append(tokens_qt[i]) i += 1 return tokens_qtb def sent_tokenize(word_list, model=nlp): doc = model(word_list) sentences = [sent.text.strip() for sent in doc.sents] return sentences quadgrams = [('intergovernmental', 'panel', 'climate', 'change'), ('natural', 'resources', 'defense', 'council'), ('coal', 'fired', 'power', 'plants'), ('national', 'oceanic', 'atmospheric', 'administration')] tr = pd.read_csv('../../Data/' + path + '/trigrams.csv', converters={'Unnamed: 0': ast.literal_eval}) tr.columns = ['trigram', 'freq', 'tag'] trigrams = [t for t in tr[tr.tag == 1].trigram] b = pd.read_csv('../../Data/' + path + '/bigrams.csv', converters={'Unnamed: 0': ast.literal_eval}) b.columns = ['bigram', 'freq', 'tag'] bigrams = [t for t in b[b.tag == 1].bigram] quadgrams = ['_'.join(t) for t in quadgrams] trigrams = ['_'.join(t) for t in trigrams] bigrams = ['_'.join(t) for t in bigrams] d_env = dd.from_pandas(env, npartitions=effective_n_jobs(-1)) d_env['sents'] = d_env.text.map(lambda x: [ngram_tagger( normalizeTokens( word_tokenize(s), lemma=False)) for s in sent_tokenize(x)]) d_env['sents'] = d_env.sents.map(lambda x: [s for s in x if len(s)>0]) env = d_env.compute() env.to_pickle('../../Data/'+path+'/sent_processing/env_processed_sent_17.pkl') env.to_csv('../../Data/'+path+'/sent_processing/env_processed_sent_17.csv')

33.41958

114

0.594267

import pandas as pd import ast import dask.dataframe as dd from gensim.utils import effective_n_jobs import spacy try: nlp = spacy.load("en") except OSError: nlp = spacy.load("en_core_web_sm") path = 'Environmental-Discourse' env = pd.read_pickle('../../Data/'+path+'/env_0.pkl') env = env[env.year == 2017] def word_tokenize(word_list, model=nlp, MAX_LEN=1500000): tokenized = [] if type(word_list) == list and len(word_list) == 1: word_list = word_list[0] if type(word_list) == list: word_list = ' '.join([str(elem) for elem in word_list]) model.max_length = MAX_LEN doc = model(word_list, disable=["parser", "tagger", "ner", "lemmatizer"]) for token in doc: if not token.is_punct and len(token.text.strip()) > 0: tokenized.append(token.text) return tokenized def normalizeTokens(word_list, extra_stop=[], model=nlp, lemma=True, MAX_LEN=1500000): #We can use a generator here as we just need to iterate over it normalized = [] if type(word_list) == list and len(word_list) == 1: word_list = word_list[0] if type(word_list) == list: word_list = ' '.join([str(elem) for elem in word_list]) # since we're only normalizing, I remove RAM intensive operations and increase max text size model.max_length = MAX_LEN doc = model(word_list.lower(), disable=["parser", "ner"]) if len(extra_stop) > 0: for stopword in extra_stop: lexeme = nlp.vocab[stopword] lexeme.is_stop = True if lemma: for w in doc: if w.text != '\n' and not w.is_stop and not w.is_punct and not w.like_num and len(w.text.strip()) > 0: # we add the lematized version of the word normalized.append(str(w.lemma_)) else: for w in doc: # if it's not a stop word or punctuation mark, add it to our article if w.text != '\n' and not w.is_stop and not w.is_punct and not w.like_num and len(w.text.strip()) > 0: normalized.append(str(w.text.strip())) return normalized def ngram_tagger(tokens): n = len(tokens) i = 0 tokens_q = [] tokens_qt = [] tokens_qtb = [] while i < n: words = '_'.join(tokens[i:i+4]) if words in quadgrams: tokens_q.append(words) i += 4 else: tokens_q.append(tokens[i]) i += 1 n = len(tokens_q) i = 0 while i < n: words = '_'.join(tokens_q[i:i+3]) if words in trigrams: tokens_qt.append(words) i += 3 else: tokens_qt.append(tokens_q[i]) i += 1 n = len(tokens_qt) i = 0 while i < n: words = '_'.join(tokens_qt[i:i+2]) if words in bigrams: tokens_qtb.append(words) i += 2 else: tokens_qtb.append(tokens_qt[i]) i += 1 return tokens_qtb def sent_tokenize(word_list, model=nlp): doc = model(word_list) sentences = [sent.text.strip() for sent in doc.sents] return sentences quadgrams = [('intergovernmental', 'panel', 'climate', 'change'), ('natural', 'resources', 'defense', 'council'), ('coal', 'fired', 'power', 'plants'), ('national', 'oceanic', 'atmospheric', 'administration')] tr = pd.read_csv('../../Data/' + path + '/trigrams.csv', converters={'Unnamed: 0': ast.literal_eval}) tr.columns = ['trigram', 'freq', 'tag'] trigrams = [t for t in tr[tr.tag == 1].trigram] b = pd.read_csv('../../Data/' + path + '/bigrams.csv', converters={'Unnamed: 0': ast.literal_eval}) b.columns = ['bigram', 'freq', 'tag'] bigrams = [t for t in b[b.tag == 1].bigram] quadgrams = ['_'.join(t) for t in quadgrams] trigrams = ['_'.join(t) for t in trigrams] bigrams = ['_'.join(t) for t in bigrams] d_env = dd.from_pandas(env, npartitions=effective_n_jobs(-1)) d_env['sents'] = d_env.text.map(lambda x: [ngram_tagger( normalizeTokens( word_tokenize(s), lemma=False)) for s in sent_tokenize(x)]) d_env['sents'] = d_env.sents.map(lambda x: [s for s in x if len(s)>0]) env = d_env.compute() env.to_pickle('../../Data/'+path+'/sent_processing/env_processed_sent_17.pkl') env.to_csv('../../Data/'+path+'/sent_processing/env_processed_sent_17.csv')

true

1c2fe2e453be6b526576ae046a9baaf0afe5582d

2,990

py

Python

linter.py

yubchen/SublimeLinter-for-QJS

c386b5ad5de89d7570c9fb29ea2992e95d2f0666

[ "MIT" ]

null

linter.py

yubchen/SublimeLinter-for-QJS

c386b5ad5de89d7570c9fb29ea2992e95d2f0666

[ "MIT" ]

null

linter.py

yubchen/SublimeLinter-for-QJS

c386b5ad5de89d7570c9fb29ea2992e95d2f0666

[ "MIT" ]

null

# # linter.py # Linter for SublimeLinter3, a code checking framework for Sublime Text 3 # # Written by roadhump # Copyright (c) 2014 roadhump # # License: MIT # """This module exports the ESLint plugin class.""" import sublime import os import re import sys from .lint import NodeLinter class ESLint(NodeLinter): """Provides an interface to the eslint executable.""" cwd = os.path.split(os.path.realpath(__file__))[0] syntax = ('javascript', 'html', 'javascriptnext', 'javascript (babel)', 'javascript (jsx)', 'jsx-real') npm_name = 'eslint' cmd = ('node', cwd+'/eslint/bin/eslint.js', '--format', 'compact', '--stdin', '--stdin-filename', '__RELATIVE_TO_FOLDER__') version_args = '--version' version_re = r'v(?P<version>\d+\.\d+\.\d+)' version_requirement = '>= 0.20.0' regex = ( r'^.+?: line (?P<line>\d+), col (?P<col>\d+), ' r'(?:(?P<error>Error)|(?P<warning>Warning)) - ' r'(?P<message>.+)' ) config_fail_regex = re.compile(r'^Cannot read config file: .*\r?\n') crash_regex = re.compile( r'^(.*?)\r?\n\w*Error: \1', re.MULTILINE ) line_col_base = (1, 0) selectors = { 'html': 'source.js.embedded.html' } def find_errors(self, output): """ Parses errors from linter's output We override this method to handle parsing eslint crashes """ match = self.config_fail_regex.match(output) if match: return [(match, 0, None, "Error", "", match.group(0), None)] match = self.crash_regex.match(output) if match: msg = "ESLint crashed: %s" % match.group(1) return [(match, 0, None, "Error", "", msg, None)] return super().find_errors(output) def split_match(self, match): """ Extract and return values from match. We override this method to silent warning by .eslintignore settings. """ match, line, col, error, warning, message, near = super().split_match(match) if message and message == 'File ignored because of your .eslintignore file. Use --no-ignore to override.': return match, None, None, None, None, '', None return match, line, col, error, warning, message, near def communicate(self, cmd, code=None): """Run an external executable using stdin to pass code and return its output.""" if '__RELATIVE_TO_FOLDER__' in cmd: relfilename = self.filename if int(sublime.version()) >= 3080: window = self.view.window() vars = window.extract_variables() if 'folder' in vars: relfilename = os.path.relpath(self.filename, vars['folder']) cmd[cmd.index('__RELATIVE_TO_FOLDER__')] = relfilename elif not code: cmd.append(self.filename) sys.stderr.write(super().communicate(cmd, code)); return super().communicate(cmd, code)

30.824742

127

0.59398

import sublime import os import re import sys from .lint import NodeLinter class ESLint(NodeLinter): cwd = os.path.split(os.path.realpath(__file__))[0] syntax = ('javascript', 'html', 'javascriptnext', 'javascript (babel)', 'javascript (jsx)', 'jsx-real') npm_name = 'eslint' cmd = ('node', cwd+'/eslint/bin/eslint.js', '--format', 'compact', '--stdin', '--stdin-filename', '__RELATIVE_TO_FOLDER__') version_args = '--version' version_re = r'v(?P<version>\d+\.\d+\.\d+)' version_requirement = '>= 0.20.0' regex = ( r'^.+?: line (?P<line>\d+), col (?P<col>\d+), ' r'(?:(?P<error>Error)|(?P<warning>Warning)) - ' r'(?P<message>.+)' ) config_fail_regex = re.compile(r'^Cannot read config file: .*\r?\n') crash_regex = re.compile( r'^(.*?)\r?\n\w*Error: \1', re.MULTILINE ) line_col_base = (1, 0) selectors = { 'html': 'source.js.embedded.html' } def find_errors(self, output): match = self.config_fail_regex.match(output) if match: return [(match, 0, None, "Error", "", match.group(0), None)] match = self.crash_regex.match(output) if match: msg = "ESLint crashed: %s" % match.group(1) return [(match, 0, None, "Error", "", msg, None)] return super().find_errors(output) def split_match(self, match): match, line, col, error, warning, message, near = super().split_match(match) if message and message == 'File ignored because of your .eslintignore file. Use --no-ignore to override.': return match, None, None, None, None, '', None return match, line, col, error, warning, message, near def communicate(self, cmd, code=None): if '__RELATIVE_TO_FOLDER__' in cmd: relfilename = self.filename if int(sublime.version()) >= 3080: window = self.view.window() vars = window.extract_variables() if 'folder' in vars: relfilename = os.path.relpath(self.filename, vars['folder']) cmd[cmd.index('__RELATIVE_TO_FOLDER__')] = relfilename elif not code: cmd.append(self.filename) sys.stderr.write(super().communicate(cmd, code)); return super().communicate(cmd, code)

true

1c2fe3e3373768dfde7d9a8b16225d720e95fca2

597

py

Python

var/spack/repos/builtin/packages/pslib/package.py

kkauder/spack

6ae8d5c380c1f42094b05d38be26b03650aafb39

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

2,360

2017-11-06T08:47:01.000Z

2022-03-31T14:45:33.000Z

var/spack/repos/builtin/packages/pslib/package.py

kkauder/spack

6ae8d5c380c1f42094b05d38be26b03650aafb39

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

13,838

2017-11-04T07:49:45.000Z

2022-03-31T23:38:39.000Z

var/spack/repos/builtin/packages/pslib/package.py

kkauder/spack

6ae8d5c380c1f42094b05d38be26b03650aafb39

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

1,793

2017-11-04T07:45:50.000Z

2022-03-30T14:31:53.000Z

# Copyright 2013-2021 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) from spack import * class Pslib(AutotoolsPackage): """C-library to create PostScript files on the fly.""" homepage = "http://pslib.sourceforge.net/" url = "https://sourceforge.net/projects/pslib/files/pslib/0.4.5/pslib-0.4.5.tar.gz" version('0.4.5', sha256='7a33928982b281660206bb3749a4a563e3ac987eea64f41696f212df345212be') depends_on('jpeg') depends_on('libpng')

31.421053

95

0.730318

from spack import * class Pslib(AutotoolsPackage): homepage = "http://pslib.sourceforge.net/" url = "https://sourceforge.net/projects/pslib/files/pslib/0.4.5/pslib-0.4.5.tar.gz" version('0.4.5', sha256='7a33928982b281660206bb3749a4a563e3ac987eea64f41696f212df345212be') depends_on('jpeg') depends_on('libpng')

true

1c2fe3faf32bb6c742fd8ded31cfd83c6c15abcb

20,258

py

Python

lib/rucio/tests/test_api_external_representation.py

fno2010/rucio

47e93cfbe5887071c70de4ba815c1bbdddfac2ce

[ "Apache-2.0" ]

null

lib/rucio/tests/test_api_external_representation.py

fno2010/rucio

47e93cfbe5887071c70de4ba815c1bbdddfac2ce

[ "Apache-2.0" ]

null

lib/rucio/tests/test_api_external_representation.py

fno2010/rucio

47e93cfbe5887071c70de4ba815c1bbdddfac2ce

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Copyright CERN since 2020 # # 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 random import string import unittest from datetime import datetime from json import loads import pytest import rucio.api.account_limit as api_acc_lim import rucio.api.rse as api_rse import rucio.core.account_counter as account_counter from rucio.api.account import add_account, get_account_info, list_accounts from rucio.api.did import add_did, add_did_to_followed, attach_dids_to_dids, get_users_following_did, scope_list from rucio.api.exporter import export_data from rucio.api.identity import add_account_identity, list_accounts_for_identity from rucio.api.replica import add_replicas, get_did_from_pfns, list_replicas from rucio.api.request import get_request_by_did, list_requests, queue_requests from rucio.api.rule import add_replication_rule from rucio.api.scope import add_scope, list_scopes, get_scopes from rucio.api.subscription import add_subscription, list_subscriptions, list_subscription_rule_states, \ get_subscription_by_id from rucio.common.config import config_get_bool from rucio.common.types import InternalAccount, InternalScope from rucio.common.utils import api_update_return_dict, generate_uuid from rucio.core.rse import get_rse_id from rucio.core.vo import add_vo, vo_exists from rucio.daemons.abacus import rse as abacus_rse from rucio.daemons.judge import cleaner from rucio.daemons.reaper import reaper from rucio.db.sqla import constants from rucio.tests.common import rse_name_generator from rucio.tests.common_server import get_vo @pytest.mark.noparallel(reason='uses pre-defined RSE, fails when run in parallel') class TestApiExternalRepresentation(unittest.TestCase): @classmethod def setUpClass(cls): if config_get_bool('common', 'multi_vo', raise_exception=False, default=False): cls.vo = {'vo': get_vo()} cls.new_vo = {'vo': 'new'} cls.multi_vo = True if not vo_exists(**cls.new_vo): add_vo(description='Test', email='rucio@email.com', **cls.new_vo) else: cls.vo = {} cls.new_vo = {} cls.multi_vo = False # Add test account cls.account_name = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) add_account(account=cls.account_name, type_='user', email='rucio@email.com', issuer='root', **cls.vo) cls.account = InternalAccount(cls.account_name, **cls.vo) # Add test scope cls.scope_name = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) add_scope(scope=cls.scope_name, account=cls.account_name, issuer='root', **cls.vo) cls.scope = InternalScope(cls.scope_name, **cls.vo) # Get test RSEs cls.rse_name = 'MOCK' cls.rse_id = get_rse_id(rse=cls.rse_name, **cls.vo) cls.rse2_name = 'MOCK2' cls.rse2_id = get_rse_id(rse=cls.rse2_name, **cls.vo) cls.rse3_name = rse_name_generator() cls.rse3_id = api_rse.add_rse(cls.rse3_name, 'root', **cls.new_vo) cls.rse4_name = rse_name_generator() cls.rse4_id = api_rse.add_rse(cls.rse4_name, 'root', **cls.new_vo) api_rse.add_distance(cls.rse3_name, cls.rse4_name, issuer='root', distance=3, **cls.new_vo) def test_api_update_return_dict(self): """ API: Test the conversion of dictionaries to external representation """ test_dict = {'account': self.account, 'scope': self.scope, 'rse_expression': 'MOCK|MOCK2', 'rse_id': self.rse_id, 'src_rse_id': self.rse_id, 'source_rse_id': self.rse_id, 'dest_rse_id': self.rse_id, 'destination_rse_id': self.rse_id} value = api_update_return_dict(test_dict) expected = {'account': self.account_name, 'scope': self.scope_name, 'rse_expression': 'MOCK|MOCK2', 'rse_id': self.rse_id, 'rse': self.rse_name, 'src_rse_id': self.rse_id, 'src_rse': self.rse_name, 'source_rse_id': self.rse_id, 'source_rse': self.rse_name, 'dest_rse_id': self.rse_id, 'dest_rse': self.rse_name, 'destination_rse_id': self.rse_id, 'destination_rse': self.rse_name} assert value == expected def test_api_account(self): """ ACCOUNT (API): Test external representation of account information """ out = get_account_info(self.account_name, **self.vo) assert self.account_name == out['account'] out = [acc['account'] for acc in list_accounts(**self.vo)] assert self.account_name in out if self.multi_vo: assert self.account.internal not in out assert '@' not in ' '.join(out) def test_api_account_limit(self): """ ACCOUNT_LIMIT (API): Test external representation of account limits """ # Add mock account limits rse_expr = '{}|{}'.format(self.rse_name, self.rse2_name) api_acc_lim.set_local_account_limit(self.account_name, self.rse_name, 10000, issuer='root', **self.vo) api_acc_lim.set_global_account_limit(self.account_name, rse_expr, 20000, issuer='root', **self.vo) out = api_acc_lim.get_local_account_limits(self.account_name, **self.vo) assert self.rse_name in out assert self.rse_id not in out out = api_acc_lim.get_local_account_limit(self.account_name, self.rse_name, **self.vo) assert self.rse_name in out assert self.rse_id not in out out = api_acc_lim.get_global_account_limits(self.account_name, **self.vo) assert rse_expr in out if self.multi_vo: assert 'vo={}&({})'.format(self.vo['vo'], rse_expr) not in out out = api_acc_lim.get_global_account_limit(self.account_name, rse_expr, **self.vo) assert rse_expr in out if self.multi_vo: assert 'vo={}&({})'.format(self.vo['vo'], rse_expr) not in out out = api_acc_lim.get_local_account_usage(self.account_name, self.rse_name, issuer='root', **self.vo) out = list(out) assert 0 != len(out) assert self.rse_id in [usage['rse_id'] for usage in out if 'rse_id' in usage] for usage in out: if 'rse_id' in usage: assert 'rse' in usage if usage['rse_id'] == self.rse_id: assert self.rse_name == usage["rse"] out = api_acc_lim.get_global_account_usage(self.account_name, rse_expr, issuer='root', **self.vo) out = list(out) assert 0 != len(out) assert rse_expr in [usage['rse_expression'] for usage in out if 'rse_expression' in usage] def test_api_did(self): """ DID (API): Test external representation of DIDs """ # add some dids add_did(self.scope_name, 'ext_parent', 'container', issuer='root', account=self.account_name, **self.vo) add_did(self.scope_name, 'ext_child', 'dataset', issuer='root', account=self.account_name, **self.vo) attachment = {'scope': self.scope_name, 'name': 'ext_parent', 'dids': [{'scope': self.scope_name, 'name': 'ext_child', 'type': 'DATASET'}]} attach_dids_to_dids([attachment], issuer='root', **self.vo) # test scope_list out = scope_list(self.scope_name, recursive=True, **self.vo) out = list(out) assert 0 != len(out) parent_found = False for did in out: assert did['scope'] == self.scope_name if did['parent'] is not None: parent_found = True assert did['parent']['scope'] == self.scope_name assert parent_found # test get_did add_did_to_followed(self.scope_name, 'ext_parent', self.account_name, **self.vo) out = get_users_following_did('ext_parent', self.scope_name, **self.vo) out = list(out) assert 0 != len(out) for user in out: assert user['user'] == self.account_name def test_api_exporter(self): """ EXPORTER (API): Test external representation of exported data """ out = export_data('root', **self.new_vo) rses = out['rses'] assert self.rse3_name in rses assert self.rse3_id not in rses distances = out['distances'] assert self.rse3_name in distances assert self.rse3_id not in distances assert self.rse4_name in distances[self.rse3_name] assert self.rse4_id not in distances[self.rse3_name] # check for interference from other VOs if self.multi_vo: assert self.rse_name not in rses assert self.rse_id not in rses assert self.rse2_name not in rses assert self.rse2_id not in rses assert self.rse_name not in distances assert self.rse_id not in distances assert self.rse2_name not in distances assert self.rse2_id not in distances def test_api_identity(self): """ IDENTITY (API): Test external representation of identity accounts """ id_key = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) add_account_identity(id_key, 'userpass', self.account_name, 'rucio_test@test.com', 'root', default=True, password='ext_pass', **self.vo) out = list_accounts_for_identity(id_key, 'userpass') assert self.account_name in out if self.multi_vo: assert self.account.internal not in out def test_api_replica(self): """ REPLICA (API): Test external representation of replicas """ did = 'ext_' + str(generate_uuid()) pfn = 'srm://mock2.com:8443/srm/managerv2?SFN=/rucio/tmpdisk/rucio_tests/%s/%s' % (self.scope_name, generate_uuid()) add_replicas(self.rse2_name, files=[{'scope': self.scope_name, 'name': did, 'bytes': 100, 'pfn': pfn}], issuer='root', **self.vo) add_did(self.scope_name, 'ext_parent_2', 'dataset', issuer='root', account=self.account_name, **self.vo) attachment = {'scope': self.scope_name, 'name': 'ext_parent_2', 'dids': [{'scope': self.scope_name, 'name': did}]} attach_dids_to_dids([attachment], issuer='root', **self.vo) out = get_did_from_pfns([pfn], self.rse2_name, **self.vo) out = list(out) assert 0 != len(out) did_found = False for p in out: for key in p: if p[key]['name'] == did: did_found = True assert self.scope_name == p[key]['scope'] assert did_found out = list_replicas(dids=[{'scope': self.scope_name, 'name': did}], resolve_parents=True, **self.vo) out = list(out) assert 0 != len(out) parents_found = False for rep in out: assert rep['scope'] == self.scope_name if 'parents' in rep: parents_found = True for parent in rep['parents']: assert self.scope_name in parent if self.multi_vo: assert self.scope.internal not in parent assert parents_found def test_api_request(self): """ REQUEST (API): Test external representation of requests """ did = generate_uuid() add_did(self.scope_name, did, 'dataset', issuer='root', account=self.account_name, rse=self.rse_name, **self.vo) requests = [{ 'dest_rse_id': self.rse2_id, 'source_rse_id': self.rse_id, 'request_type': constants.RequestType.TRANSFER, 'request_id': generate_uuid(), 'name': did, 'scope': self.scope_name, 'account': self.account_name, 'rule_id': generate_uuid(), 'retry_count': 1, 'requested_at': datetime.now(), 'attributes': { 'activity': 'User Subscription', 'bytes': 10, 'md5': '', 'adler32': '' } }] reqs = queue_requests(requests, issuer='root', **self.vo) # this does not pass in the source rse reqs = list(reqs) assert 0 != len(reqs) for r in reqs: assert r['scope'] == self.scope_name assert r['account'] == self.account_name assert r['source_rse'] == self.rse_name assert r['dest_rse'] == self.rse2_name out = get_request_by_did(self.scope_name, did, self.rse2_name, issuer='root', **self.vo) assert out['scope'] == self.scope_name assert out['account'] == self.account_name assert out['dest_rse'] == self.rse2_name assert out['source_rse'] == self.rse_name out = list_requests([self.rse_name], [self.rse2_name], [constants.RequestState.QUEUED], issuer='root', **self.vo) out = list(out) assert 0 != len(out) assert self.scope_name in [req['scope'] for req in out] for req in out: if req['scope'] == self.scope_name: assert req['scope'] == self.scope_name assert req['account'] == self.account_name assert req['dest_rse'] == self.rse2_name assert req['source_rse'] == self.rse_name @pytest.mark.noparallel(reason='runs the reaper on a pre-defined rse, might interfere with other tests') def test_api_rse(self): """ RSE (API): Test external representation of RSEs """ out = api_rse.get_rse(self.rse_name, **self.vo) assert out['rse'] == self.rse_name assert out['id'] == self.rse_id out = api_rse.list_rses(**self.new_vo) out = list(out) assert 0 != len(out) rse_ids = [rse['id'] for rse in out] assert self.rse3_id in rse_ids assert self.rse4_id in rse_ids for rse in out: assert 'rse' in rse if rse['id'] == self.rse3_id: assert rse['rse'] == self.rse3_name elif rse['id'] == self.rse4_id: assert rse['rse'] == self.rse4_name key = "KEY_" + generate_uuid() api_rse.add_rse_attribute(self.rse_name, key, 1, issuer='root', **self.vo) out = api_rse.get_rses_with_attribute(key) out = list(out) assert 0 != len(out) for rse in out: assert rse['rse'] == self.rse_name out = api_rse.get_rse_protocols(self.rse_name, issuer='root', **self.vo) assert out['rse'] == self.rse_name # add some account and RSE counters rse_mock = 'MOCK4' rse_mock_id = get_rse_id(rse_mock, **self.vo) account_counter.del_counter(rse_id=rse_mock_id, account=self.account) account_counter.add_counter(rse_id=rse_mock_id, account=self.account) account_counter.increase(rse_id=rse_mock_id, account=self.account, files=1, bytes_=10) account_counter.update_account_counter(self.account, rse_mock_id) did = 'file_' + generate_uuid() add_did(self.scope_name, did, 'DATASET', 'root', account=self.account_name, rse=rse_mock, **self.vo) abacus_rse.run(once=True) out = api_rse.get_rse_usage(rse_mock, per_account=True, issuer='root', **self.vo) assert rse_mock_id in [o['rse_id'] for o in out] for usage in out: if usage['rse_id'] == rse_mock_id: assert usage['rse'] == rse_mock accounts = [u['account'] for u in usage['account_usages']] assert self.account_name in accounts if self.multi_vo: assert self.account.internal not in accounts # clean up files cleaner.run(once=True) if self.multi_vo: reaper.run(once=True, include_rses='vo=%s&(%s)' % (self.vo['vo'], rse_mock), greedy=True) else: reaper.run(once=True, include_rses=rse_mock, greedy=True) abacus_rse.run(once=True) out = api_rse.parse_rse_expression('%s|%s' % (self.rse_name, self.rse2_name), **self.vo) assert self.rse_name in out assert self.rse2_name in out assert self.rse_id not in out assert self.rse2_id not in out def test_api_scope(self): """ SCOPE (API): Test external representation of scopes """ out = list_scopes() assert self.scope_name in out if self.multi_vo: assert self.scope.internal not in out out = get_scopes(self.account_name, **self.vo) assert self.scope_name in out if self.multi_vo: assert self.scope.internal not in out def test_api_subscription(self): """ SUBSCRIPTION (API): Test external representation of subscriptions """ sub = 'ext_' + generate_uuid() did = 'ext_' + generate_uuid() new_acc_name = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) new_scope_name = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) add_account(new_acc_name, 'USER', 'test@test.com', 'root', **self.new_vo) add_scope(new_scope_name, new_acc_name, 'root', **self.new_vo) api_acc_lim.set_local_account_limit(new_acc_name, self.rse3_name, 10, 'root', **self.new_vo) api_acc_lim.set_local_account_limit(new_acc_name, self.rse4_name, 10, 'root', **self.new_vo) add_did(new_scope_name, did, 'DATASET', 'root', account=new_acc_name, rse=self.rse3_name, **self.new_vo) sub_id = add_subscription(sub, new_acc_name, {'account': [new_acc_name], 'scope': [new_scope_name]}, [{'copies': 1, 'rse_expression': self.rse3_name, 'weight': 0, 'activity': 'User Subscriptions', 'source_replica_expression': self.rse4_name}], '', False, 0, 0, 3, 'root', **self.new_vo) add_replication_rule(dids=[{'scope': new_scope_name, 'name': did}], copies=1, rse_expression=self.rse3_name, weight=None, lifetime=180, grouping='DATASET', account=new_acc_name, locked=False, subscription_id=sub_id, source_replica_expression=self.rse4_name, activity='User Subscriptions', notify=None, purge_replicas=False, ignore_availability=False, comment='', ask_approval=False, asynchronous=False, delay_injection=None, priority=0, split_container=False, meta='', issuer='root', **self.new_vo) out = list_subscriptions(sub, **self.new_vo) out = list(out) assert 0 != len(out) assert sub_id in [o['id'] for o in out] for o in out: if o['id'] == sub_id: assert o['account'] == new_acc_name rules = loads(o['replication_rules'])[0] assert rules['rse_expression'] == self.rse3_name assert rules['source_replica_expression'] == self.rse4_name fil = loads(o['filter']) assert fil['account'] == [new_acc_name] assert fil['scope'] == [new_scope_name] out = list_subscription_rule_states(sub, **self.new_vo) out = list(out) assert 0 != len(out) for o in out: assert o.account == new_acc_name out = get_subscription_by_id(sub_id, **self.new_vo) assert out['account'] == new_acc_name rules = loads(out['replication_rules'])[0] assert rules['rse_expression'] == self.rse3_name assert rules['source_replica_expression'] == self.rse4_name fil = loads(out['filter']) assert fil['account'] == [new_acc_name] assert fil['scope'] == [new_scope_name]

45.626126

144

0.623655

import random import string import unittest from datetime import datetime from json import loads import pytest import rucio.api.account_limit as api_acc_lim import rucio.api.rse as api_rse import rucio.core.account_counter as account_counter from rucio.api.account import add_account, get_account_info, list_accounts from rucio.api.did import add_did, add_did_to_followed, attach_dids_to_dids, get_users_following_did, scope_list from rucio.api.exporter import export_data from rucio.api.identity import add_account_identity, list_accounts_for_identity from rucio.api.replica import add_replicas, get_did_from_pfns, list_replicas from rucio.api.request import get_request_by_did, list_requests, queue_requests from rucio.api.rule import add_replication_rule from rucio.api.scope import add_scope, list_scopes, get_scopes from rucio.api.subscription import add_subscription, list_subscriptions, list_subscription_rule_states, \ get_subscription_by_id from rucio.common.config import config_get_bool from rucio.common.types import InternalAccount, InternalScope from rucio.common.utils import api_update_return_dict, generate_uuid from rucio.core.rse import get_rse_id from rucio.core.vo import add_vo, vo_exists from rucio.daemons.abacus import rse as abacus_rse from rucio.daemons.judge import cleaner from rucio.daemons.reaper import reaper from rucio.db.sqla import constants from rucio.tests.common import rse_name_generator from rucio.tests.common_server import get_vo @pytest.mark.noparallel(reason='uses pre-defined RSE, fails when run in parallel') class TestApiExternalRepresentation(unittest.TestCase): @classmethod def setUpClass(cls): if config_get_bool('common', 'multi_vo', raise_exception=False, default=False): cls.vo = {'vo': get_vo()} cls.new_vo = {'vo': 'new'} cls.multi_vo = True if not vo_exists(**cls.new_vo): add_vo(description='Test', email='rucio@email.com', **cls.new_vo) else: cls.vo = {} cls.new_vo = {} cls.multi_vo = False cls.account_name = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) add_account(account=cls.account_name, type_='user', email='rucio@email.com', issuer='root', **cls.vo) cls.account = InternalAccount(cls.account_name, **cls.vo) cls.scope_name = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) add_scope(scope=cls.scope_name, account=cls.account_name, issuer='root', **cls.vo) cls.scope = InternalScope(cls.scope_name, **cls.vo) cls.rse_name = 'MOCK' cls.rse_id = get_rse_id(rse=cls.rse_name, **cls.vo) cls.rse2_name = 'MOCK2' cls.rse2_id = get_rse_id(rse=cls.rse2_name, **cls.vo) cls.rse3_name = rse_name_generator() cls.rse3_id = api_rse.add_rse(cls.rse3_name, 'root', **cls.new_vo) cls.rse4_name = rse_name_generator() cls.rse4_id = api_rse.add_rse(cls.rse4_name, 'root', **cls.new_vo) api_rse.add_distance(cls.rse3_name, cls.rse4_name, issuer='root', distance=3, **cls.new_vo) def test_api_update_return_dict(self): test_dict = {'account': self.account, 'scope': self.scope, 'rse_expression': 'MOCK|MOCK2', 'rse_id': self.rse_id, 'src_rse_id': self.rse_id, 'source_rse_id': self.rse_id, 'dest_rse_id': self.rse_id, 'destination_rse_id': self.rse_id} value = api_update_return_dict(test_dict) expected = {'account': self.account_name, 'scope': self.scope_name, 'rse_expression': 'MOCK|MOCK2', 'rse_id': self.rse_id, 'rse': self.rse_name, 'src_rse_id': self.rse_id, 'src_rse': self.rse_name, 'source_rse_id': self.rse_id, 'source_rse': self.rse_name, 'dest_rse_id': self.rse_id, 'dest_rse': self.rse_name, 'destination_rse_id': self.rse_id, 'destination_rse': self.rse_name} assert value == expected def test_api_account(self): out = get_account_info(self.account_name, **self.vo) assert self.account_name == out['account'] out = [acc['account'] for acc in list_accounts(**self.vo)] assert self.account_name in out if self.multi_vo: assert self.account.internal not in out assert '@' not in ' '.join(out) def test_api_account_limit(self): rse_expr = '{}|{}'.format(self.rse_name, self.rse2_name) api_acc_lim.set_local_account_limit(self.account_name, self.rse_name, 10000, issuer='root', **self.vo) api_acc_lim.set_global_account_limit(self.account_name, rse_expr, 20000, issuer='root', **self.vo) out = api_acc_lim.get_local_account_limits(self.account_name, **self.vo) assert self.rse_name in out assert self.rse_id not in out out = api_acc_lim.get_local_account_limit(self.account_name, self.rse_name, **self.vo) assert self.rse_name in out assert self.rse_id not in out out = api_acc_lim.get_global_account_limits(self.account_name, **self.vo) assert rse_expr in out if self.multi_vo: assert 'vo={}&({})'.format(self.vo['vo'], rse_expr) not in out out = api_acc_lim.get_global_account_limit(self.account_name, rse_expr, **self.vo) assert rse_expr in out if self.multi_vo: assert 'vo={}&({})'.format(self.vo['vo'], rse_expr) not in out out = api_acc_lim.get_local_account_usage(self.account_name, self.rse_name, issuer='root', **self.vo) out = list(out) assert 0 != len(out) assert self.rse_id in [usage['rse_id'] for usage in out if 'rse_id' in usage] for usage in out: if 'rse_id' in usage: assert 'rse' in usage if usage['rse_id'] == self.rse_id: assert self.rse_name == usage["rse"] out = api_acc_lim.get_global_account_usage(self.account_name, rse_expr, issuer='root', **self.vo) out = list(out) assert 0 != len(out) assert rse_expr in [usage['rse_expression'] for usage in out if 'rse_expression' in usage] def test_api_did(self): add_did(self.scope_name, 'ext_parent', 'container', issuer='root', account=self.account_name, **self.vo) add_did(self.scope_name, 'ext_child', 'dataset', issuer='root', account=self.account_name, **self.vo) attachment = {'scope': self.scope_name, 'name': 'ext_parent', 'dids': [{'scope': self.scope_name, 'name': 'ext_child', 'type': 'DATASET'}]} attach_dids_to_dids([attachment], issuer='root', **self.vo) out = scope_list(self.scope_name, recursive=True, **self.vo) out = list(out) assert 0 != len(out) parent_found = False for did in out: assert did['scope'] == self.scope_name if did['parent'] is not None: parent_found = True assert did['parent']['scope'] == self.scope_name assert parent_found add_did_to_followed(self.scope_name, 'ext_parent', self.account_name, **self.vo) out = get_users_following_did('ext_parent', self.scope_name, **self.vo) out = list(out) assert 0 != len(out) for user in out: assert user['user'] == self.account_name def test_api_exporter(self): out = export_data('root', **self.new_vo) rses = out['rses'] assert self.rse3_name in rses assert self.rse3_id not in rses distances = out['distances'] assert self.rse3_name in distances assert self.rse3_id not in distances assert self.rse4_name in distances[self.rse3_name] assert self.rse4_id not in distances[self.rse3_name] if self.multi_vo: assert self.rse_name not in rses assert self.rse_id not in rses assert self.rse2_name not in rses assert self.rse2_id not in rses assert self.rse_name not in distances assert self.rse_id not in distances assert self.rse2_name not in distances assert self.rse2_id not in distances def test_api_identity(self): id_key = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) add_account_identity(id_key, 'userpass', self.account_name, 'rucio_test@test.com', 'root', default=True, password='ext_pass', **self.vo) out = list_accounts_for_identity(id_key, 'userpass') assert self.account_name in out if self.multi_vo: assert self.account.internal not in out def test_api_replica(self): did = 'ext_' + str(generate_uuid()) pfn = 'srm://mock2.com:8443/srm/managerv2?SFN=/rucio/tmpdisk/rucio_tests/%s/%s' % (self.scope_name, generate_uuid()) add_replicas(self.rse2_name, files=[{'scope': self.scope_name, 'name': did, 'bytes': 100, 'pfn': pfn}], issuer='root', **self.vo) add_did(self.scope_name, 'ext_parent_2', 'dataset', issuer='root', account=self.account_name, **self.vo) attachment = {'scope': self.scope_name, 'name': 'ext_parent_2', 'dids': [{'scope': self.scope_name, 'name': did}]} attach_dids_to_dids([attachment], issuer='root', **self.vo) out = get_did_from_pfns([pfn], self.rse2_name, **self.vo) out = list(out) assert 0 != len(out) did_found = False for p in out: for key in p: if p[key]['name'] == did: did_found = True assert self.scope_name == p[key]['scope'] assert did_found out = list_replicas(dids=[{'scope': self.scope_name, 'name': did}], resolve_parents=True, **self.vo) out = list(out) assert 0 != len(out) parents_found = False for rep in out: assert rep['scope'] == self.scope_name if 'parents' in rep: parents_found = True for parent in rep['parents']: assert self.scope_name in parent if self.multi_vo: assert self.scope.internal not in parent assert parents_found def test_api_request(self): did = generate_uuid() add_did(self.scope_name, did, 'dataset', issuer='root', account=self.account_name, rse=self.rse_name, **self.vo) requests = [{ 'dest_rse_id': self.rse2_id, 'source_rse_id': self.rse_id, 'request_type': constants.RequestType.TRANSFER, 'request_id': generate_uuid(), 'name': did, 'scope': self.scope_name, 'account': self.account_name, 'rule_id': generate_uuid(), 'retry_count': 1, 'requested_at': datetime.now(), 'attributes': { 'activity': 'User Subscription', 'bytes': 10, 'md5': '', 'adler32': '' } }] reqs = queue_requests(requests, issuer='root', **self.vo) reqs = list(reqs) assert 0 != len(reqs) for r in reqs: assert r['scope'] == self.scope_name assert r['account'] == self.account_name assert r['source_rse'] == self.rse_name assert r['dest_rse'] == self.rse2_name out = get_request_by_did(self.scope_name, did, self.rse2_name, issuer='root', **self.vo) assert out['scope'] == self.scope_name assert out['account'] == self.account_name assert out['dest_rse'] == self.rse2_name assert out['source_rse'] == self.rse_name out = list_requests([self.rse_name], [self.rse2_name], [constants.RequestState.QUEUED], issuer='root', **self.vo) out = list(out) assert 0 != len(out) assert self.scope_name in [req['scope'] for req in out] for req in out: if req['scope'] == self.scope_name: assert req['scope'] == self.scope_name assert req['account'] == self.account_name assert req['dest_rse'] == self.rse2_name assert req['source_rse'] == self.rse_name @pytest.mark.noparallel(reason='runs the reaper on a pre-defined rse, might interfere with other tests') def test_api_rse(self): out = api_rse.get_rse(self.rse_name, **self.vo) assert out['rse'] == self.rse_name assert out['id'] == self.rse_id out = api_rse.list_rses(**self.new_vo) out = list(out) assert 0 != len(out) rse_ids = [rse['id'] for rse in out] assert self.rse3_id in rse_ids assert self.rse4_id in rse_ids for rse in out: assert 'rse' in rse if rse['id'] == self.rse3_id: assert rse['rse'] == self.rse3_name elif rse['id'] == self.rse4_id: assert rse['rse'] == self.rse4_name key = "KEY_" + generate_uuid() api_rse.add_rse_attribute(self.rse_name, key, 1, issuer='root', **self.vo) out = api_rse.get_rses_with_attribute(key) out = list(out) assert 0 != len(out) for rse in out: assert rse['rse'] == self.rse_name out = api_rse.get_rse_protocols(self.rse_name, issuer='root', **self.vo) assert out['rse'] == self.rse_name rse_mock = 'MOCK4' rse_mock_id = get_rse_id(rse_mock, **self.vo) account_counter.del_counter(rse_id=rse_mock_id, account=self.account) account_counter.add_counter(rse_id=rse_mock_id, account=self.account) account_counter.increase(rse_id=rse_mock_id, account=self.account, files=1, bytes_=10) account_counter.update_account_counter(self.account, rse_mock_id) did = 'file_' + generate_uuid() add_did(self.scope_name, did, 'DATASET', 'root', account=self.account_name, rse=rse_mock, **self.vo) abacus_rse.run(once=True) out = api_rse.get_rse_usage(rse_mock, per_account=True, issuer='root', **self.vo) assert rse_mock_id in [o['rse_id'] for o in out] for usage in out: if usage['rse_id'] == rse_mock_id: assert usage['rse'] == rse_mock accounts = [u['account'] for u in usage['account_usages']] assert self.account_name in accounts if self.multi_vo: assert self.account.internal not in accounts cleaner.run(once=True) if self.multi_vo: reaper.run(once=True, include_rses='vo=%s&(%s)' % (self.vo['vo'], rse_mock), greedy=True) else: reaper.run(once=True, include_rses=rse_mock, greedy=True) abacus_rse.run(once=True) out = api_rse.parse_rse_expression('%s|%s' % (self.rse_name, self.rse2_name), **self.vo) assert self.rse_name in out assert self.rse2_name in out assert self.rse_id not in out assert self.rse2_id not in out def test_api_scope(self): out = list_scopes() assert self.scope_name in out if self.multi_vo: assert self.scope.internal not in out out = get_scopes(self.account_name, **self.vo) assert self.scope_name in out if self.multi_vo: assert self.scope.internal not in out def test_api_subscription(self): sub = 'ext_' + generate_uuid() did = 'ext_' + generate_uuid() new_acc_name = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) new_scope_name = ''.join(random.choice(string.ascii_lowercase) for x in range(10)) add_account(new_acc_name, 'USER', 'test@test.com', 'root', **self.new_vo) add_scope(new_scope_name, new_acc_name, 'root', **self.new_vo) api_acc_lim.set_local_account_limit(new_acc_name, self.rse3_name, 10, 'root', **self.new_vo) api_acc_lim.set_local_account_limit(new_acc_name, self.rse4_name, 10, 'root', **self.new_vo) add_did(new_scope_name, did, 'DATASET', 'root', account=new_acc_name, rse=self.rse3_name, **self.new_vo) sub_id = add_subscription(sub, new_acc_name, {'account': [new_acc_name], 'scope': [new_scope_name]}, [{'copies': 1, 'rse_expression': self.rse3_name, 'weight': 0, 'activity': 'User Subscriptions', 'source_replica_expression': self.rse4_name}], '', False, 0, 0, 3, 'root', **self.new_vo) add_replication_rule(dids=[{'scope': new_scope_name, 'name': did}], copies=1, rse_expression=self.rse3_name, weight=None, lifetime=180, grouping='DATASET', account=new_acc_name, locked=False, subscription_id=sub_id, source_replica_expression=self.rse4_name, activity='User Subscriptions', notify=None, purge_replicas=False, ignore_availability=False, comment='', ask_approval=False, asynchronous=False, delay_injection=None, priority=0, split_container=False, meta='', issuer='root', **self.new_vo) out = list_subscriptions(sub, **self.new_vo) out = list(out) assert 0 != len(out) assert sub_id in [o['id'] for o in out] for o in out: if o['id'] == sub_id: assert o['account'] == new_acc_name rules = loads(o['replication_rules'])[0] assert rules['rse_expression'] == self.rse3_name assert rules['source_replica_expression'] == self.rse4_name fil = loads(o['filter']) assert fil['account'] == [new_acc_name] assert fil['scope'] == [new_scope_name] out = list_subscription_rule_states(sub, **self.new_vo) out = list(out) assert 0 != len(out) for o in out: assert o.account == new_acc_name out = get_subscription_by_id(sub_id, **self.new_vo) assert out['account'] == new_acc_name rules = loads(out['replication_rules'])[0] assert rules['rse_expression'] == self.rse3_name assert rules['source_replica_expression'] == self.rse4_name fil = loads(out['filter']) assert fil['account'] == [new_acc_name] assert fil['scope'] == [new_scope_name]

true

1c2fe45d995e3b53e075541991a3ec3d5009d8ad

439

py

Python

users_manage_api/urls.py

OscarMCV/prueba_backend

893d68c0f3d9bb2dc7bea701e50eed44df4df87f

[ "MIT" ]

null

users_manage_api/urls.py

OscarMCV/prueba_backend

893d68c0f3d9bb2dc7bea701e50eed44df4df87f

[ "MIT" ]

null

users_manage_api/urls.py

OscarMCV/prueba_backend

893d68c0f3d9bb2dc7bea701e50eed44df4df87f

[ "MIT" ]

null

#Django from django.urls import path #Django rest framework from rest_framework.urlpatterns import format_suffix_patterns #Views from users_manage_api import views as user_views """In order to handle urls management better, the "views" name has been changed""" urlpatterns = [ path('login/', user_views.UserAPIView.as_view()), path('logon/', user_views.CreateUser.as_view()), ] urlpatterns = format_suffix_patterns(urlpatterns)

27.4375

82

0.781321

from django.urls import path from rest_framework.urlpatterns import format_suffix_patterns from users_manage_api import views as user_views urlpatterns = [ path('login/', user_views.UserAPIView.as_view()), path('logon/', user_views.CreateUser.as_view()), ] urlpatterns = format_suffix_patterns(urlpatterns)

true

1c2fe5cf35fa1b453b2fe317770a5af30692455d

486

py

Python

app/backend/registries/migrations/0013_auto_20180712_2107.py

stephenhillier/gwells

235d35f1f40dd845f8fecd0d7c3371c4564567c6

[ "Apache-2.0" ]

null

app/backend/registries/migrations/0013_auto_20180712_2107.py

stephenhillier/gwells

235d35f1f40dd845f8fecd0d7c3371c4564567c6

[ "Apache-2.0" ]

null

app/backend/registries/migrations/0013_auto_20180712_2107.py

stephenhillier/gwells

235d35f1f40dd845f8fecd0d7c3371c4564567c6

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.11.14 on 2018-07-12 21:07 from __future__ import unicode_literals from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('registries', '0012_auto_20180704_2105'), ] operations = [ migrations.AlterModelOptions( name='registriesapplication', options={'ordering': ['primary_certificate_no'], 'verbose_name_plural': 'Applications'}, ), ]

24.3

100

0.654321

from __future__ import unicode_literals from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('registries', '0012_auto_20180704_2105'), ] operations = [ migrations.AlterModelOptions( name='registriesapplication', options={'ordering': ['primary_certificate_no'], 'verbose_name_plural': 'Applications'}, ), ]

true

1c2fe5f15190b2d43bdd5dc69c9fd74b7a7bebe8

6,082

py

Python

owlbot.py

HoangDinhTho/nodejs-firestore

58ed6d6acff6ebefbd0609257ccf5a78c9dec46c

[ "Apache-2.0" ]

1

2019-10-18T22:44:00.000Z

owlbot.py

renovate-bot/nodejs-firestore

1dda1bdb53818299fcaefe606d82777ce74dafd2

[ "Apache-2.0" ]

null

owlbot.py

renovate-bot/nodejs-firestore

1dda1bdb53818299fcaefe606d82777ce74dafd2

[ "Apache-2.0" ]

null

import synthtool as s import synthtool.gcp as gcp import synthtool.languages.node as node import logging import os import subprocess from pathlib import Path from synthtool import _tracked_paths import shutil logging.basicConfig(level=logging.DEBUG) staging = Path("owl-bot-staging") if staging.is_dir(): try: v1_admin_library = staging / "admin/v1" v1beta1_library = staging / "v1beta1" v1_library = staging / "v1" _tracked_paths.add(v1_admin_library) _tracked_paths.add(v1beta1_library) _tracked_paths.add(v1_library) # skip index, protos, package.json, and README.md s.copy(v1_admin_library, "dev", excludes=["package.json", "README.md", "src/index.ts", "src/v1/index.ts", "tsconfig.json", "linkinator.config.json", "webpack.config.js"]) s.copy(v1beta1_library, "dev", excludes=["package.json", "README.md", "src/index.ts", "src/v1beta1/index.ts", "tsconfig.json", "linkinator.config.json", "webpack.config.js"]) s.copy(v1_library, "dev", excludes=["package.json", "README.md", "src/index.ts", "src/v1/index.ts", "tsconfig.json", "linkinator.config.json", "webpack.config.js"]) # Fix dropping of google-cloud-resource-header # See: https://github.com/googleapis/nodejs-firestore/pull/375 s.replace( "dev/src/v1beta1/firestore_client.ts", "return this\.innerApiCalls\.listen$options$;", "return this.innerApiCalls.listen({}, options);", ) s.replace( "dev/src/v1/firestore_client.ts", "return this\.innerApiCalls\.listen$options$;", "return this.innerApiCalls.listen({}, options);", ) s.replace( "dev/test/gapic_firestore_v1beta1.ts", "calledWithExactly$undefined$", "calledWithExactly({}, undefined)", ) s.replace( "dev/src/v1beta1/firestore_client.ts", "return this\.innerApiCalls\.write$options$;", "return this.innerApiCalls.write({}, options);", ) s.replace( "dev/src/v1/firestore_client.ts", "return this\.innerApiCalls\.write$options$;", "return this.innerApiCalls.write({}, options);", ) s.replace( "dev/test/gapic_firestore_v1.ts", "calledWithExactly$undefined$", "calledWithExactly({}, undefined)", ) # use the existing proto .js / .d.ts files s.replace( "dev/src/v1/firestore_client.ts", "/protos/protos'", "/protos/firestore_v1_proto_api'" ) s.replace( "dev/test/gapic_firestore_v1.ts", "/protos/protos'", "/protos/firestore_v1_proto_api'" ) s.replace( "dev/test/gapic_firestore_v1.ts", "import \* as firestoreModule from '\.\./src';", "import * as firestoreModule from '../src/v1';" ) s.replace( "dev/test/gapic_firestore_v1.ts", "firestoreModule\.v1", "firestoreModule" ) s.replace( "dev/src/v1/firestore_admin_client.ts", "/protos/protos'", "/protos/firestore_admin_v1_proto_api'" ) s.replace( "dev/test/gapic_firestore_admin_v1.ts", "/protos/protos'", "/protos/firestore_admin_v1_proto_api'" ) s.replace( "dev/test/gapic_firestore_admin_v1.ts", "import \* as firestoreadminModule from '\.\./src';", "import * as firestoreadminModule from '../src/v1';" ) s.replace( "dev/test/gapic_firestore_admin_v1.ts", "firestoreadminModule\.v1", "firestoreadminModule" ) s.replace( "dev/src/v1beta1/firestore_client.ts", "/protos/protos'", "/protos/firestore_v1beta1_proto_api'" ) s.replace( "dev/test/gapic_firestore_v1beta1.ts", "/protos/protos'", "/protos/firestore_v1beta1_proto_api'" ) s.replace( "dev/test/gapic_firestore_v1beta1.ts", "import \* as firestoreModule from \'../src\';", "import * as firestoreModule from '../src/v1beta1';" ) s.replace( "dev/test/gapic_firestore_v1beta1.ts", "firestoreModule\.v1beta1", "firestoreModule" ) # Mark v1beta1 as deprecated s.replace( "dev/src/v1beta1/firestore_client.ts", "@class", "@class\n * @deprecated Use v1/firestore_client instead." ) s.replace( "dev/src/v1beta1/firestore_client.ts", "const version", "// tslint:disable deprecation\n\nconst version", 1 ) os.rename("dev/.gitignore", ".gitignore") os.rename("dev/.eslintignore", ".eslintignore") os.rename("dev/.mocharc.js", ".mocharc.js") os.rename("dev/.jsdoc.js", ".jsdoc.js") os.rename("dev/.prettierrc.js", ".prettierrc.js") os.unlink("dev/.eslintrc.json") s.replace(".jsdoc.js", "protos", "build/protos", 1) # Remove auto-generated packaging tests os.system('rm -rf dev/system-test/fixtures dev/system-test/install.ts') os.chdir("dev") node.compile_protos_hermetic() os.chdir("protos") os.unlink('protos.js') os.unlink('protos.d.ts') subprocess.run('./update.sh', shell=True) os.chdir("../../") # Copy types into types/ # These files were generated by node.compile_protos_hermetic() above. os.system("cp build/src/v1/firestore*.d.ts types/v1") os.system("cp build/src/v1beta1/firestore_client.d.ts types/v1beta1") os.system("cp build/protos/firestore*.d.ts types/protos") s.replace( "types/v1/firestore_client.d.ts", "../../protos", "../protos" ) s.replace( "types/v1/firestore_admin_client.d.ts", "../../protos", "../protos" ) s.replace( "types/v1beta1/firestore_client.d.ts", "../../protos", "../protos" ) finally: # The staging directory should never be merged into the main branch. shutil.rmtree(staging) # Copy template files common_templates = gcp.CommonTemplates() templates = common_templates.node_library( source_location="build/src", test_project="node-gcloud-ci" ) s.copy(templates, excludes=[".eslintrc.json", ".kokoro/**/*", ".github/CODEOWNERS"]) node.fix_hermetic() # fix formatting

31.350515

113

0.634988

import synthtool as s import synthtool.gcp as gcp import synthtool.languages.node as node import logging import os import subprocess from pathlib import Path from synthtool import _tracked_paths import shutil logging.basicConfig(level=logging.DEBUG) staging = Path("owl-bot-staging") if staging.is_dir(): try: v1_admin_library = staging / "admin/v1" v1beta1_library = staging / "v1beta1" v1_library = staging / "v1" _tracked_paths.add(v1_admin_library) _tracked_paths.add(v1beta1_library) _tracked_paths.add(v1_library) s.copy(v1_admin_library, "dev", excludes=["package.json", "README.md", "src/index.ts", "src/v1/index.ts", "tsconfig.json", "linkinator.config.json", "webpack.config.js"]) s.copy(v1beta1_library, "dev", excludes=["package.json", "README.md", "src/index.ts", "src/v1beta1/index.ts", "tsconfig.json", "linkinator.config.json", "webpack.config.js"]) s.copy(v1_library, "dev", excludes=["package.json", "README.md", "src/index.ts", "src/v1/index.ts", "tsconfig.json", "linkinator.config.json", "webpack.config.js"]) s.replace( "dev/src/v1beta1/firestore_client.ts", "return this\.innerApiCalls\.listen$options$;", "return this.innerApiCalls.listen({}, options);", ) s.replace( "dev/src/v1/firestore_client.ts", "return this\.innerApiCalls\.listen$options$;", "return this.innerApiCalls.listen({}, options);", ) s.replace( "dev/test/gapic_firestore_v1beta1.ts", "calledWithExactly$undefined$", "calledWithExactly({}, undefined)", ) s.replace( "dev/src/v1beta1/firestore_client.ts", "return this\.innerApiCalls\.write$options$;", "return this.innerApiCalls.write({}, options);", ) s.replace( "dev/src/v1/firestore_client.ts", "return this\.innerApiCalls\.write$options$;", "return this.innerApiCalls.write({}, options);", ) s.replace( "dev/test/gapic_firestore_v1.ts", "calledWithExactly$undefined$", "calledWithExactly({}, undefined)", ) s.replace( "dev/src/v1/firestore_client.ts", "/protos/protos'", "/protos/firestore_v1_proto_api'" ) s.replace( "dev/test/gapic_firestore_v1.ts", "/protos/protos'", "/protos/firestore_v1_proto_api'" ) s.replace( "dev/test/gapic_firestore_v1.ts", "import \* as firestoreModule from '\.\./src';", "import * as firestoreModule from '../src/v1';" ) s.replace( "dev/test/gapic_firestore_v1.ts", "firestoreModule\.v1", "firestoreModule" ) s.replace( "dev/src/v1/firestore_admin_client.ts", "/protos/protos'", "/protos/firestore_admin_v1_proto_api'" ) s.replace( "dev/test/gapic_firestore_admin_v1.ts", "/protos/protos'", "/protos/firestore_admin_v1_proto_api'" ) s.replace( "dev/test/gapic_firestore_admin_v1.ts", "import \* as firestoreadminModule from '\.\./src';", "import * as firestoreadminModule from '../src/v1';" ) s.replace( "dev/test/gapic_firestore_admin_v1.ts", "firestoreadminModule\.v1", "firestoreadminModule" ) s.replace( "dev/src/v1beta1/firestore_client.ts", "/protos/protos'", "/protos/firestore_v1beta1_proto_api'" ) s.replace( "dev/test/gapic_firestore_v1beta1.ts", "/protos/protos'", "/protos/firestore_v1beta1_proto_api'" ) s.replace( "dev/test/gapic_firestore_v1beta1.ts", "import \* as firestoreModule from \'../src\';", "import * as firestoreModule from '../src/v1beta1';" ) s.replace( "dev/test/gapic_firestore_v1beta1.ts", "firestoreModule\.v1beta1", "firestoreModule" ) s.replace( "dev/src/v1beta1/firestore_client.ts", "@class", "@class\n * @deprecated Use v1/firestore_client instead." ) s.replace( "dev/src/v1beta1/firestore_client.ts", "const version", "// tslint:disable deprecation\n\nconst version", 1 ) os.rename("dev/.gitignore", ".gitignore") os.rename("dev/.eslintignore", ".eslintignore") os.rename("dev/.mocharc.js", ".mocharc.js") os.rename("dev/.jsdoc.js", ".jsdoc.js") os.rename("dev/.prettierrc.js", ".prettierrc.js") os.unlink("dev/.eslintrc.json") s.replace(".jsdoc.js", "protos", "build/protos", 1) os.system('rm -rf dev/system-test/fixtures dev/system-test/install.ts') os.chdir("dev") node.compile_protos_hermetic() os.chdir("protos") os.unlink('protos.js') os.unlink('protos.d.ts') subprocess.run('./update.sh', shell=True) os.chdir("../../") os.system("cp build/src/v1/firestore*.d.ts types/v1") os.system("cp build/src/v1beta1/firestore_client.d.ts types/v1beta1") os.system("cp build/protos/firestore*.d.ts types/protos") s.replace( "types/v1/firestore_client.d.ts", "../../protos", "../protos" ) s.replace( "types/v1/firestore_admin_client.d.ts", "../../protos", "../protos" ) s.replace( "types/v1beta1/firestore_client.d.ts", "../../protos", "../protos" ) finally: shutil.rmtree(staging) common_templates = gcp.CommonTemplates() templates = common_templates.node_library( source_location="build/src", test_project="node-gcloud-ci" ) s.copy(templates, excludes=[".eslintrc.json", ".kokoro/**/*", ".github/CODEOWNERS"]) node.fix_hermetic()

true

1c2fe7bccf9324aea7bb17a9739be1ad6a210a33

2,658

py

Python

servicios_profesionales/photologue_custom/tests.py

acs-um/ServiciosProfesionales

b29d67cda42f3d975a8abaf58203d92c9d1a3f57

[ "MIT" ]

1

2018-05-24T23:33:02.000Z

servicios_profesionales/photologue_custom/tests.py

acs-um/ServiciosProfesionales

b29d67cda42f3d975a8abaf58203d92c9d1a3f57

[ "MIT" ]

22

2018-05-07T20:46:27.000Z

2018-06-10T23:59:49.000Z

servicios_profesionales/photologue_custom/tests.py

acs-um/ServiciosProfesionales

b29d67cda42f3d975a8abaf58203d92c9d1a3f57

[ "MIT" ]

null

from django.test import TestCase, RequestFactory from django.urls import reverse from django.apps import apps from .apps import PhotologueCustomConfig from .form import GalleryExtendedForm from Categorias.models import Categoria from .models import GalleryExtended from usuarios.models import MyUser from servicios.models import Service from photologue.models import Photo class GalleryViewTests(TestCase): def setUp(self): self.factory = RequestFactory() self.user = MyUser.objects.create_user( email=" test@g.com ", date_of_birth="1995-01-02", password=" 123123b ", first_name="Test", last_name="Apellido" ) self.categoria = Categoria.objects.create( name='Construcción', description='Trabajos de construcción' ) self.service = Service.objects.create( name='Albañil', description='Servicios generales', category=self.categoria ) self.service2 = Service.objects.create( name='Yesero', description='Yesería en general', category=self.categoria ) def test_apps(self): self.assertEqual(PhotologueCustomConfig.name, 'photologue_custom') self.assertEqual(apps.get_app_config('photologue_custom').name, 'photologue_custom') def test_gallery(self): custom_g = GalleryExtended.nuevo(self.service, self.user) string = self.user.first_name + '-' + self.service.name self.assertEquals(custom_g.gallery.title, string) form = GalleryExtendedForm(data={ 'title': custom_g.gallery.title, 'slug': custom_g.gallery.slug, 'description': custom_g.gallery.description, }) self.assertFalse(form.is_valid()) def test_update_gallery(self): galeria = GalleryExtended.nuevo(self.service2, self.user) pc = galeria.gallery.photo_count() p1 = Photo.objects.create(title='test photo 1') galeria.gallery.photos.add(p1) str = galeria.gallery.photo_count() response = self.client.post( reverse('updateGallery', kwargs={'pk': galeria.gallery.id}), {'photos': p1}) self.assertEqual(response.status_code, 302) galeria.refresh_from_db() self.assertEqual(pc + 1, galeria.gallery.photo_count()) description = "The Catcher in the Rye" response = self.client.post( reverse('updateGallery', kwargs={'pk': galeria.gallery.id}), {'description': description, 'photos': p1}) self.assertEqual(response.status_code, 302)

37.43662

92

0.647856

from django.test import TestCase, RequestFactory from django.urls import reverse from django.apps import apps from .apps import PhotologueCustomConfig from .form import GalleryExtendedForm from Categorias.models import Categoria from .models import GalleryExtended from usuarios.models import MyUser from servicios.models import Service from photologue.models import Photo class GalleryViewTests(TestCase): def setUp(self): self.factory = RequestFactory() self.user = MyUser.objects.create_user( email=" test@g.com ", date_of_birth="1995-01-02", password=" 123123b ", first_name="Test", last_name="Apellido" ) self.categoria = Categoria.objects.create( name='Construcción', description='Trabajos de construcción' ) self.service = Service.objects.create( name='Albañil', description='Servicios generales', category=self.categoria ) self.service2 = Service.objects.create( name='Yesero', description='Yesería en general', category=self.categoria ) def test_apps(self): self.assertEqual(PhotologueCustomConfig.name, 'photologue_custom') self.assertEqual(apps.get_app_config('photologue_custom').name, 'photologue_custom') def test_gallery(self): custom_g = GalleryExtended.nuevo(self.service, self.user) string = self.user.first_name + '-' + self.service.name self.assertEquals(custom_g.gallery.title, string) form = GalleryExtendedForm(data={ 'title': custom_g.gallery.title, 'slug': custom_g.gallery.slug, 'description': custom_g.gallery.description, }) self.assertFalse(form.is_valid()) def test_update_gallery(self): galeria = GalleryExtended.nuevo(self.service2, self.user) pc = galeria.gallery.photo_count() p1 = Photo.objects.create(title='test photo 1') galeria.gallery.photos.add(p1) str = galeria.gallery.photo_count() response = self.client.post( reverse('updateGallery', kwargs={'pk': galeria.gallery.id}), {'photos': p1}) self.assertEqual(response.status_code, 302) galeria.refresh_from_db() self.assertEqual(pc + 1, galeria.gallery.photo_count()) description = "The Catcher in the Rye" response = self.client.post( reverse('updateGallery', kwargs={'pk': galeria.gallery.id}), {'description': description, 'photos': p1}) self.assertEqual(response.status_code, 302)

true

1c2fe86730e711e6fb182397ce9e735878b5b04b

1,670

py

Python

alipay/aop/api/domain/CloudbusCommonResult.py

antopen/alipay-sdk-python-all

8e51c54409b9452f8d46c7bb10eea7c8f7e8d30c

[ "Apache-2.0" ]

213

2018-08-27T16:49:32.000Z

2021-12-29T04:34:12.000Z

alipay/aop/api/domain/CloudbusCommonResult.py

antopen/alipay-sdk-python-all

8e51c54409b9452f8d46c7bb10eea7c8f7e8d30c

[ "Apache-2.0" ]

29

2018-09-29T06:43:00.000Z

2021-09-02T03:27:32.000Z

alipay/aop/api/domain/CloudbusCommonResult.py

antopen/alipay-sdk-python-all

8e51c54409b9452f8d46c7bb10eea7c8f7e8d30c

[ "Apache-2.0" ]

59

2018-08-27T16:59:26.000Z

2022-03-25T10:08:15.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- import json from alipay.aop.api.constant.ParamConstants import * class CloudbusCommonResult(object): def __init__(self): self._code = None self._data = None self._message = None @property def code(self): return self._code @code.setter def code(self, value): self._code = value @property def data(self): return self._data @data.setter def data(self, value): self._data = value @property def message(self): return self._message @message.setter def message(self, value): self._message = value def to_alipay_dict(self): params = dict() if self.code: if hasattr(self.code, 'to_alipay_dict'): params['code'] = self.code.to_alipay_dict() else: params['code'] = self.code if self.data: if hasattr(self.data, 'to_alipay_dict'): params['data'] = self.data.to_alipay_dict() else: params['data'] = self.data if self.message: if hasattr(self.message, 'to_alipay_dict'): params['message'] = self.message.to_alipay_dict() else: params['message'] = self.message return params @staticmethod def from_alipay_dict(d): if not d: return None o = CloudbusCommonResult() if 'code' in d: o.code = d['code'] if 'data' in d: o.data = d['data'] if 'message' in d: o.message = d['message'] return o

23.521127

65

0.534132

import json from alipay.aop.api.constant.ParamConstants import * class CloudbusCommonResult(object): def __init__(self): self._code = None self._data = None self._message = None @property def code(self): return self._code @code.setter def code(self, value): self._code = value @property def data(self): return self._data @data.setter def data(self, value): self._data = value @property def message(self): return self._message @message.setter def message(self, value): self._message = value def to_alipay_dict(self): params = dict() if self.code: if hasattr(self.code, 'to_alipay_dict'): params['code'] = self.code.to_alipay_dict() else: params['code'] = self.code if self.data: if hasattr(self.data, 'to_alipay_dict'): params['data'] = self.data.to_alipay_dict() else: params['data'] = self.data if self.message: if hasattr(self.message, 'to_alipay_dict'): params['message'] = self.message.to_alipay_dict() else: params['message'] = self.message return params @staticmethod def from_alipay_dict(d): if not d: return None o = CloudbusCommonResult() if 'code' in d: o.code = d['code'] if 'data' in d: o.data = d['data'] if 'message' in d: o.message = d['message'] return o

true

1c2fe965d8089210f836636560e36b0573e31f72

6,563

py

Python

Script/clf_pre_ln_tf.py

ywu94/Tencent-Ads-Algo-Comp-2020

8f008fc1cc21c832e6bdb76056d12ad357da5475

[ "MIT" ]

27

2020-06-09T18:33:45.000Z

2021-11-15T11:49:54.000Z

Script/clf_pre_ln_tf.py

Wannaman/Tencent-Ads-Algo-Comp-2020

8f008fc1cc21c832e6bdb76056d12ad357da5475

[ "MIT" ]

2

2020-06-21T01:58:56.000Z

2020-11-12T18:12:40.000Z

Script/clf_pre_ln_tf.py

Wannaman/Tencent-Ads-Algo-Comp-2020

8f008fc1cc21c832e6bdb76056d12ad357da5475

[ "MIT" ]

15

2020-06-07T14:19:57.000Z

2020-07-16T08:27:42.000Z

import numpy as np import torch from torch import nn import torch.nn.functional as F from torch.nn.init import xavier_uniform_, kaiming_normal_ class Pre_LN_Transformer_Encoder_Layer(nn.Module): """ Encoder layer for Pre-LN Transformer """ def __init__(self, d_model, n_head, intermediate_size=2048, device=None, dropout=0.1, **kwargs): super(Pre_LN_Transformer_Encoder_Layer, self).__init__(**kwargs) self.d_model = d_model self.n_head = n_head self.intermediate_size = intermediate_size self.device = device if device else torch.device('cpu') self.dropout = dropout self.ln_layer_1 = nn.LayerNorm(d_model) self.mha_layer = nn.MultiheadAttention(d_model, n_head, dropout=dropout) self.attn_dropout = nn.Dropout(p=dropout) self.ln_layer_2 = nn.LayerNorm(d_model) self.ffn_layer_1 = nn.Linear(d_model, intermediate_size) self.dropout_1 = nn.Dropout(p=dropout) self.ffn_layer_2 = nn.Linear(intermediate_size, d_model) self.dropout_2 = nn.Dropout(p=dropout) def _get_padding_mask(self, batch_size, seq_len, inp_len): padding_mask = np.ones((batch_size, seq_len)) for index, l in enumerate(inp_len): padding_mask[index,:l] = 0 return torch.from_numpy(padding_mask).bool().to(self.device) def forward(self, inp, inp_len): batch_size, seq_len, _ = inp.shape padding_mask = self._get_padding_mask(batch_size, seq_len, inp_len) # (batch_size, seq_len) inp1 = self.ln_layer_1(inp).permute(1,0,2) # (seq_len, batch_size, d_model) inp2 = self.mha_layer(inp1, inp1, inp1, key_padding_mask=padding_mask)[0].permute(1,0,2) # (batch_size, seq_len, d_model) inp = inp + self.attn_dropout(inp2) inp1 = self.ln_layer_2(inp) inp2 = self.ffn_layer_2(self.dropout_1(F.relu(self.ffn_layer_1(inp1)))) inp = inp + self.dropout_2(inp2) return inp class Pre_LN_Transformer_Encoder(nn.Module): """ Stacked Pre-LN Transformer Encoder layers """ def __init__(self, n_layer, d_model, n_head, intermediate_size=2048, device=None, dropout=0.1, **kwargs): super(Pre_LN_Transformer_Encoder, self).__init__(**kwargs) self.n_layer = n_layer self.d_model = d_model self.n_head = n_head self.intermediate_size = intermediate_size self.device = device if device else torch.device('cpu') self.dropout = dropout for index in range(n_layer): setattr(self, 'pre_ln_tf_encoder_{}'.format(index), Pre_LN_Transformer_Encoder_Layer(d_model, n_head, intermediate_size=intermediate_size, device=self.device, dropout=0.1)) def forward(self, inp, inp_len): for index in range(self.n_layer): inp = getattr(self, 'pre_ln_tf_encoder_{}'.format(index))(inp, inp_len) return inp class MLP_Classification_Layer(nn.Module): """ Multilayer Perception Classification Layer - Layer 1: Linear + Batchnorm + ReLU + Dropout - Layer 2: Linear + Batchnorm + ReLU + Dropout - Layer 3: Linear """ def __init__(self, inp_size, out_size, dropout=0.5, **kwargs): super(MLP_Classification_Layer, self).__init__(**kwargs) self.inp_size = inp_size self.out_size = out_size self.dropout = dropout self.mlp_1 = nn.Linear(inp_size, 4096) self.batchnorm_1 = nn.BatchNorm1d(4096) self.mlp_dropout_1 = nn.Dropout(p=dropout) self.mlp_2 = nn.Linear(4096, 2048) self.batchnorm_2 = nn.BatchNorm1d(2048) self.mlp_dropout_2 = nn.Dropout(p=dropout) self.mlp_3 = nn.Linear(2048, out_size) def forward(self, inp): mlp_out = self.mlp_1(inp) # (batch_size, 4096) mlp_out = self.mlp_dropout_1(F.relu(self.batchnorm_1(mlp_out))) # (batch_size, 4096) mlp_out = self.mlp_2(mlp_out) # (batch_size, 2048) mlp_out = self.mlp_dropout_2(F.relu(self.batchnorm_2(mlp_out))) # (batch_size, 2048) mlp_out = self.mlp_3(mlp_out) # (batch_size, out_size) return mlp_out class Multi_Seq_Pre_LN_Transformer_Encoder_Classifier(nn.Module): def __init__(self, embed_size, hidden_size, n_layer, n_head, out_size, intermediate_size=2048, max_seq_len=100, device=None, tf_dropout=0.1, rnn_dropout=0.2, dnn_dropout=0.5, **kwargs): super(Multi_Seq_Pre_LN_Transformer_Encoder_Classifier, self).__init__(**kwargs) self.embed_size = embed_size self.hidden_size = hidden_size self.n_layer = n_layer self.n_head = n_head self.out_size = out_size self.intermediate_size = intermediate_size self.max_seq_len = max_seq_len self.device = device if device else torch.device('cpu') self.tf_dropout = tf_dropout self.rnn_dropout = rnn_dropout self.dnn_dropout = dnn_dropout self.n_extraction = len(embed_size) self.mlp_inp_size = sum(map(lambda x:4*x, hidden_size)) for index, e_size in enumerate(embed_size): setattr(self, 'pre_ln_tf_encoder_{}'.format(index), Pre_LN_Transformer_Encoder(n_layer, e_size, n_head, intermediate_size=intermediate_size, device=self.device, dropout=tf_dropout)) setattr(self, 'ln_{}'.format(index), nn.LayerNorm(e_size)) for index, (e_size, h_size) in enumerate(zip(embed_size, hidden_size)): setattr(self, 'lstm_{}'.format(index), nn.LSTM(input_size=e_size, hidden_size=h_size, bias=True, bidirectional=True)) self.max_pooling = nn.MaxPool1d(max_seq_len) self.inp_bn = nn.BatchNorm1d(self.mlp_inp_size) self.inp_dropout = nn.Dropout(p=dnn_dropout) self.mlp_layer = MLP_Classification_Layer(self.mlp_inp_size, out_size, dropout=dnn_dropout) def forward(self, *args): assert len(args)==self.n_extraction+1 buf, inp_len = [], args[-1] for index, inp in enumerate(args[:-1]): inp = getattr(self, 'pre_ln_tf_encoder_{}'.format(index))(inp, inp_len) # (batch_size, seq_len, embed_size) inp = getattr(self, 'ln_{}'.format(index))(inp) # (batch_size, seq_len, embed_size) inp = getattr(self, 'lstm_{}'.format(index))(inp.permute(1,0,2))[0].permute(1,0,2) # (batch_size, seq_len, 2*hidden_size) buf.append(inp[np.arange(len(inp_len)), inp_len-1, :]) # (batch_size, 2*hidden_size) buf.append(self.max_pooling(inp.permute(0,2,1)).squeeze(2)) # (batch_size, 2*hidden_size) out = self.inp_bn(torch.cat(buf, dim=1)) # (batch_size, Σ4*hidden_size) out = self.mlp_layer(self.inp_dropout(F.relu(out))) # (batch_size, out_size) return out

45.576389

186

0.689928

import numpy as np import torch from torch import nn import torch.nn.functional as F from torch.nn.init import xavier_uniform_, kaiming_normal_ class Pre_LN_Transformer_Encoder_Layer(nn.Module): def __init__(self, d_model, n_head, intermediate_size=2048, device=None, dropout=0.1, **kwargs): super(Pre_LN_Transformer_Encoder_Layer, self).__init__(**kwargs) self.d_model = d_model self.n_head = n_head self.intermediate_size = intermediate_size self.device = device if device else torch.device('cpu') self.dropout = dropout self.ln_layer_1 = nn.LayerNorm(d_model) self.mha_layer = nn.MultiheadAttention(d_model, n_head, dropout=dropout) self.attn_dropout = nn.Dropout(p=dropout) self.ln_layer_2 = nn.LayerNorm(d_model) self.ffn_layer_1 = nn.Linear(d_model, intermediate_size) self.dropout_1 = nn.Dropout(p=dropout) self.ffn_layer_2 = nn.Linear(intermediate_size, d_model) self.dropout_2 = nn.Dropout(p=dropout) def _get_padding_mask(self, batch_size, seq_len, inp_len): padding_mask = np.ones((batch_size, seq_len)) for index, l in enumerate(inp_len): padding_mask[index,:l] = 0 return torch.from_numpy(padding_mask).bool().to(self.device) def forward(self, inp, inp_len): batch_size, seq_len, _ = inp.shape padding_mask = self._get_padding_mask(batch_size, seq_len, inp_len) inp1 = self.ln_layer_1(inp).permute(1,0,2) inp2 = self.mha_layer(inp1, inp1, inp1, key_padding_mask=padding_mask)[0].permute(1,0,2) inp = inp + self.attn_dropout(inp2) inp1 = self.ln_layer_2(inp) inp2 = self.ffn_layer_2(self.dropout_1(F.relu(self.ffn_layer_1(inp1)))) inp = inp + self.dropout_2(inp2) return inp class Pre_LN_Transformer_Encoder(nn.Module): def __init__(self, n_layer, d_model, n_head, intermediate_size=2048, device=None, dropout=0.1, **kwargs): super(Pre_LN_Transformer_Encoder, self).__init__(**kwargs) self.n_layer = n_layer self.d_model = d_model self.n_head = n_head self.intermediate_size = intermediate_size self.device = device if device else torch.device('cpu') self.dropout = dropout for index in range(n_layer): setattr(self, 'pre_ln_tf_encoder_{}'.format(index), Pre_LN_Transformer_Encoder_Layer(d_model, n_head, intermediate_size=intermediate_size, device=self.device, dropout=0.1)) def forward(self, inp, inp_len): for index in range(self.n_layer): inp = getattr(self, 'pre_ln_tf_encoder_{}'.format(index))(inp, inp_len) return inp class MLP_Classification_Layer(nn.Module): def __init__(self, inp_size, out_size, dropout=0.5, **kwargs): super(MLP_Classification_Layer, self).__init__(**kwargs) self.inp_size = inp_size self.out_size = out_size self.dropout = dropout self.mlp_1 = nn.Linear(inp_size, 4096) self.batchnorm_1 = nn.BatchNorm1d(4096) self.mlp_dropout_1 = nn.Dropout(p=dropout) self.mlp_2 = nn.Linear(4096, 2048) self.batchnorm_2 = nn.BatchNorm1d(2048) self.mlp_dropout_2 = nn.Dropout(p=dropout) self.mlp_3 = nn.Linear(2048, out_size) def forward(self, inp): mlp_out = self.mlp_1(inp) mlp_out = self.mlp_dropout_1(F.relu(self.batchnorm_1(mlp_out))) mlp_out = self.mlp_2(mlp_out) mlp_out = self.mlp_dropout_2(F.relu(self.batchnorm_2(mlp_out))) mlp_out = self.mlp_3(mlp_out) return mlp_out class Multi_Seq_Pre_LN_Transformer_Encoder_Classifier(nn.Module): def __init__(self, embed_size, hidden_size, n_layer, n_head, out_size, intermediate_size=2048, max_seq_len=100, device=None, tf_dropout=0.1, rnn_dropout=0.2, dnn_dropout=0.5, **kwargs): super(Multi_Seq_Pre_LN_Transformer_Encoder_Classifier, self).__init__(**kwargs) self.embed_size = embed_size self.hidden_size = hidden_size self.n_layer = n_layer self.n_head = n_head self.out_size = out_size self.intermediate_size = intermediate_size self.max_seq_len = max_seq_len self.device = device if device else torch.device('cpu') self.tf_dropout = tf_dropout self.rnn_dropout = rnn_dropout self.dnn_dropout = dnn_dropout self.n_extraction = len(embed_size) self.mlp_inp_size = sum(map(lambda x:4*x, hidden_size)) for index, e_size in enumerate(embed_size): setattr(self, 'pre_ln_tf_encoder_{}'.format(index), Pre_LN_Transformer_Encoder(n_layer, e_size, n_head, intermediate_size=intermediate_size, device=self.device, dropout=tf_dropout)) setattr(self, 'ln_{}'.format(index), nn.LayerNorm(e_size)) for index, (e_size, h_size) in enumerate(zip(embed_size, hidden_size)): setattr(self, 'lstm_{}'.format(index), nn.LSTM(input_size=e_size, hidden_size=h_size, bias=True, bidirectional=True)) self.max_pooling = nn.MaxPool1d(max_seq_len) self.inp_bn = nn.BatchNorm1d(self.mlp_inp_size) self.inp_dropout = nn.Dropout(p=dnn_dropout) self.mlp_layer = MLP_Classification_Layer(self.mlp_inp_size, out_size, dropout=dnn_dropout) def forward(self, *args): assert len(args)==self.n_extraction+1 buf, inp_len = [], args[-1] for index, inp in enumerate(args[:-1]): inp = getattr(self, 'pre_ln_tf_encoder_{}'.format(index))(inp, inp_len) inp = getattr(self, 'ln_{}'.format(index))(inp) inp = getattr(self, 'lstm_{}'.format(index))(inp.permute(1,0,2))[0].permute(1,0,2) buf.append(inp[np.arange(len(inp_len)), inp_len-1, :]) buf.append(self.max_pooling(inp.permute(0,2,1)).squeeze(2)) out = self.inp_bn(torch.cat(buf, dim=1)) out = self.mlp_layer(self.inp_dropout(F.relu(out))) return out

true

1c2fe96ba751a5bd946a6277f0b8f492d52c2402

2,126

py

Python

src/openvino_dnn_detector.py

FenixFly/UNN_HPC_SCHOOL_2019_OPENVINO

5e5ce1fa14d56549c7809d1a24bc03353ffadcbb

[ "Apache-2.0" ]

null

src/openvino_dnn_detector.py

FenixFly/UNN_HPC_SCHOOL_2019_OPENVINO

5e5ce1fa14d56549c7809d1a24bc03353ffadcbb

[ "Apache-2.0" ]

2

2019-11-12T09:03:18.000Z

2019-11-18T18:19:56.000Z

src/openvino_dnn_detector.py

FenixFly/UNN_HPC_SCHOOL_2019_OPENVINO

5e5ce1fa14d56549c7809d1a24bc03353ffadcbb

[ "Apache-2.0" ]

null

import cv2 import numpy from openvino.inference_engine import IENetwork, IECore class OpenvinoDnnDetector: def __init__(self, weightsPath=None, configPath=None, task_type=None, cpu_extension = None): self.weights = weightsPath self.config = configPath self.task_type = task_type # Create net #self.net = cv2.dnn.readNet(self.weights, self.config) self.ie = IECore() self.net = IENetwork(model=configPath, weights=weightsPath) if cpu_extension: self.ie.add_extension(cpu_extension, 'CPU') self.exec_net = self.ie.load_network(network=self.net, device_name='CPU') def _output_detection(self, output, img): (h, w) = img.shape[:2] for i in range(0, output.shape[2]): confidence = output[0, 0, i, 2] if confidence > 0.5: print(i, confidence) box = output[0, 0, i, 3:7] * numpy.array([w, h, w, h]) print(box) (startX, startY, endX, endY) = box.astype("int") text = "{:.2f}%".format(confidence * 100) y = startY - 10 if startY - 10 > 10 else startY + 10 cv2.rectangle(img, (startX, startY), (endX, endY), (0, 255, 0), 2) cv2.putText(img, text, (startX, y), cv2.FONT_HERSHEY_COMPLEX, 0.45, (0, 0, 255), 1) return img def prepare_image(self, image, h, w): if image.shape[:-1] != (h, w): image = cv2.resize(image, (w, h)) image = image.transpose((2, 0, 1)) # Change data layout from HWC to CHW return image def detect(self, image): input_blob = next(iter(self.net.inputs)) out_blob = next(iter(self.net.outputs)) n, c, h, w = self.net.inputs[input_blob].shape blob = self.prepare_image(image, h, w) output = self.exec_net.infer(inputs={input_blob: blob}) output = output[out_blob] print(output.shape, output) return self._output_detection(output, image)

40.113208

81

0.557855

import cv2 import numpy from openvino.inference_engine import IENetwork, IECore class OpenvinoDnnDetector: def __init__(self, weightsPath=None, configPath=None, task_type=None, cpu_extension = None): self.weights = weightsPath self.config = configPath self.task_type = task_type self.ie = IECore() self.net = IENetwork(model=configPath, weights=weightsPath) if cpu_extension: self.ie.add_extension(cpu_extension, 'CPU') self.exec_net = self.ie.load_network(network=self.net, device_name='CPU') def _output_detection(self, output, img): (h, w) = img.shape[:2] for i in range(0, output.shape[2]): confidence = output[0, 0, i, 2] if confidence > 0.5: print(i, confidence) box = output[0, 0, i, 3:7] * numpy.array([w, h, w, h]) print(box) (startX, startY, endX, endY) = box.astype("int") text = "{:.2f}%".format(confidence * 100) y = startY - 10 if startY - 10 > 10 else startY + 10 cv2.rectangle(img, (startX, startY), (endX, endY), (0, 255, 0), 2) cv2.putText(img, text, (startX, y), cv2.FONT_HERSHEY_COMPLEX, 0.45, (0, 0, 255), 1) return img def prepare_image(self, image, h, w): if image.shape[:-1] != (h, w): image = cv2.resize(image, (w, h)) image = image.transpose((2, 0, 1)) return image def detect(self, image): input_blob = next(iter(self.net.inputs)) out_blob = next(iter(self.net.outputs)) n, c, h, w = self.net.inputs[input_blob].shape blob = self.prepare_image(image, h, w) output = self.exec_net.infer(inputs={input_blob: blob}) output = output[out_blob] print(output.shape, output) return self._output_detection(output, image)

true

1c2fe973c5f524536ba18e5ee4f9dbd3bd74c8da

800

py

Python

pong/RandomUtils.py

FireFlyForLife/Python-Pong

bb0c7e2173f87a379fc5426c2ab24df859238ace

[ "MIT" ]

null

pong/RandomUtils.py

FireFlyForLife/Python-Pong

bb0c7e2173f87a379fc5426c2ab24df859238ace

[ "MIT" ]

null

pong/RandomUtils.py

FireFlyForLife/Python-Pong

bb0c7e2173f87a379fc5426c2ab24df859238ace

[ "MIT" ]

null

def randomRanges(ranges): index = int( random(len(ranges)) ) val = random(float(ranges[index][0]), float(ranges[index][1])) return val lastTime = 0 def deltaTime(): global lastTime delta = millis() - lastTime lastTime = millis() return delta #http://stackoverflow.com/questions/401847/circle-rectangle-collision-detection-intersection def intersects(ball, platform): closestX = constrain(ball.pos.x, platform.pos.x, platform.pos.x + platform.w); closestY = constrain(ball.pos.y, platform.pos.y, platform.pos.y + platform.h); distanceX = ball.pos.x - closestX; distanceY = ball.pos.y - closestY; radius = ball.r / 2 distanceSquared = (distanceX * distanceX) + (distanceY * distanceY); return distanceSquared < (radius * radius);

33.333333

92

0.6775

def randomRanges(ranges): index = int( random(len(ranges)) ) val = random(float(ranges[index][0]), float(ranges[index][1])) return val lastTime = 0 def deltaTime(): global lastTime delta = millis() - lastTime lastTime = millis() return delta def intersects(ball, platform): closestX = constrain(ball.pos.x, platform.pos.x, platform.pos.x + platform.w); closestY = constrain(ball.pos.y, platform.pos.y, platform.pos.y + platform.h); distanceX = ball.pos.x - closestX; distanceY = ball.pos.y - closestY; radius = ball.r / 2 distanceSquared = (distanceX * distanceX) + (distanceY * distanceY); return distanceSquared < (radius * radius);

true

1c2fe9c8f31aa841529840a16b5969ee18f61dd2

1,522

py

Python

CreateNetworks.py

yukimasano/nw_SEIR

af9d1298861eba8aadd1517a92e176f76a7218a2

[ "MIT" ]

7

2019-02-13T18:04:34.000Z

2021-01-17T15:49:40.000Z

CreateNetworks.py

yukimasano/nw_SEIR

af9d1298861eba8aadd1517a92e176f76a7218a2

[ "MIT" ]

2

2017-11-15T21:52:33.000Z

2020-02-10T08:33:25.000Z

CreateNetworks.py

yukimasano/nw_SEIR

af9d1298861eba8aadd1517a92e176f76a7218a2

[ "MIT" ]

5

2019-05-05T01:38:48.000Z

2020-04-03T08:32:48.000Z

# -*- coding: utf-8 -*- """ CreateNetworks.py This algorithm aggregates the temporally resolved network data default= 20min aggregation, by setting mins=1/3 we get 20sec resolution. Output: Tensor A20 for day 1, tensor B20 for day 2 along with the the times as vectors. @author: Yuki M. Asano """ import numpy as np def createnw(data,metadata,mins): tt=-1 maxtime=np.ceil((data[-1,0] - data[0,0] )/(20*3*mins)) # 20min numIndividuals=len(metadata[:, 0]) startid=int(metadata[0][0]) A= np.zeros((numchildren+1,numIndividuals+1, maxtime+1),dtype=np.int) told=0 for row in range(len(data[:,0])): t=data[row,0] id1=int(np.argwhere(str(data[row,1])== metadata[:,0])) id2=int(np.argwhere(str(data[row,2])== metadata[:,0])) if (t>= (told+(20*3*mins))) and t!=told: #start new timeslot tt+=1 told=t if id1>id2: #fill lower triangular A[id1][id2][tt]+=1 else: A[id2][id1][tt]+=1 return A, range(tt) data=np.loadtxt('primaryschool_wo_class.csv', delimiter=',', dtype=np.int) firstday=data[0:60623,:] secondday=data[60623:,:] metadata=np.loadtxt('metadata_primaryschool.txt', delimiter='\t', dtype='S16') # create 20min aggregated data [A20,time] =createnw(firstday,metadata,20) [B20,time2] =createnw(secondday,metadata,20) # save data as numpy objects np.save('day1.npy', A) np.save('day2.npy', B) np.save('numbers.npy',no) np.save('times1.npy',time) np.save('times2.npy',time2)

29.843137

87

0.639947

import numpy as np def createnw(data,metadata,mins): tt=-1 maxtime=np.ceil((data[-1,0] - data[0,0] )/(20*3*mins)) numIndividuals=len(metadata[:, 0]) startid=int(metadata[0][0]) A= np.zeros((numchildren+1,numIndividuals+1, maxtime+1),dtype=np.int) told=0 for row in range(len(data[:,0])): t=data[row,0] id1=int(np.argwhere(str(data[row,1])== metadata[:,0])) id2=int(np.argwhere(str(data[row,2])== metadata[:,0])) if (t>= (told+(20*3*mins))) and t!=told: tt+=1 told=t if id1>id2: A[id1][id2][tt]+=1 else: A[id2][id1][tt]+=1 return A, range(tt) data=np.loadtxt('primaryschool_wo_class.csv', delimiter=',', dtype=np.int) firstday=data[0:60623,:] secondday=data[60623:,:] metadata=np.loadtxt('metadata_primaryschool.txt', delimiter='\t', dtype='S16') [A20,time] =createnw(firstday,metadata,20) [B20,time2] =createnw(secondday,metadata,20) np.save('day1.npy', A) np.save('day2.npy', B) np.save('numbers.npy',no) np.save('times1.npy',time) np.save('times2.npy',time2)

true

1c2fea21b8f9ccc7b4e55871b2cc9d33d28e9fd9

1,619

py

Python

t.py

lucascbarbosa/real-pokedex

1c0dc26fa6a923db5d7f525c303d85644f632ccd

[ "MIT" ]

null

t.py

lucascbarbosa/real-pokedex

1c0dc26fa6a923db5d7f525c303d85644f632ccd

[ "MIT" ]

null

t.py

lucascbarbosa/real-pokedex

1c0dc26fa6a923db5d7f525c303d85644f632ccd

[ "MIT" ]

null

a = ['Abra', 'Aerodactyl', 'Alakazam', 'Arbok', 'Arcanine', 'Articuno', 'Beedrill', 'Bellsprout', 'Blastoise', 'bulbasaur', 'Butterfree', 'Caterpie', 'Chansey', 'Charizard', 'Charmander', 'Charmeleon', 'Clefable', 'Clefairy', 'Cloyster', 'Cubone', 'desktop.ini', 'Dewgong', 'Diglett', 'Ditto', 'Dodrio', 'Doduo', 'Dragonair', 'Dragonite', 'Dratini', 'Drowzee', 'Dugtrio', 'Eevee', 'Ekans', 'Electabuzz', 'Electrode', 'Exeggcute', 'Exeggutor', 'Farfetchd', 'Fearow', 'Flareon', 'Gastly', 'Gengar', 'Geodude', 'Gloom', 'Golbat', 'Goldeen', 'Golduck', 'Golem', 'Graveler', 'Grimer', 'Growlithe', 'Gyarados', 'Haunter', 'Hitmonchan', 'Hitmonlee', 'Horsea', 'Hypno', 'Ivysaur', 'Jigglypuff', 'Jolteon', 'Jynx', 'Kabuto', 'Kabutops', 'Kadabra', 'Kakuna', 'Kangaskhan', 'Kingler', 'Koffing', 'Krabby', 'Lapras', 'Lickitung', 'Machamp', 'Machoke', 'Machop', 'Magikarp', 'Magmar', 'Magnemite', 'Magneton', 'Mankey', 'Marowak', 'Meowth', 'Metapod', 'Mew', 'Mewtwo', 'Moltres', 'MrMime', 'Muk', 'Nidoking', 'Nidoqueen', 'Nidoran Female', 'Nidoran Male', 'Nidorina', 'Nidorino', 'Ninetales', 'Oddish', 'Omanyte', 'Omastar', 'Onix', 'Paras', 'Parasect', 'Persian', 'Pidgeot', 'Pidgeotto', 'Pidgey', 'Pikachu', 'Pinsir', 'Poliwag', 'Poliwhirl', 'Poliwrath', 'Ponyta', 'Porygon', 'Primeape', 'Psyduck', 'Raichu', 'Rapidash', 'Raticate', 'Rattata', 'Rhydon', 'Rhyhorn', 'Sandshrew', 'Sandslash', 'Scyther', 'Seadra', 'Seaking', 'Seel', 'Shellder', 'Slowbro', 'Slowpoke', 'Snorlax', 'Spearow', 'Squirtle', 'Starmie', 'Staryu', 'Tangela', 'Tauros', 'Tentacool', 'Tentacruel', 'Vaporeon', 'Venomoth', 'Venonat', 'Venusaur'] print(len(a))

539.666667

928

0.644225

a = ['Abra', 'Aerodactyl', 'Alakazam', 'Arbok', 'Arcanine', 'Articuno', 'Beedrill', 'Bellsprout', 'Blastoise', 'bulbasaur', 'Butterfree', 'Caterpie', 'Chansey', 'Charizard', 'Charmander', 'Charmeleon', 'Clefable', 'Clefairy', 'Cloyster', 'Cubone', 'desktop.ini', 'Dewgong', 'Diglett', 'Ditto', 'Dodrio', 'Doduo', 'Dragonair', 'Dragonite', 'Dratini', 'Drowzee', 'Dugtrio', 'Eevee', 'Ekans', 'Electabuzz', 'Electrode', 'Exeggcute', 'Exeggutor', 'Farfetchd', 'Fearow', 'Flareon', 'Gastly', 'Gengar', 'Geodude', 'Gloom', 'Golbat', 'Goldeen', 'Golduck', 'Golem', 'Graveler', 'Grimer', 'Growlithe', 'Gyarados', 'Haunter', 'Hitmonchan', 'Hitmonlee', 'Horsea', 'Hypno', 'Ivysaur', 'Jigglypuff', 'Jolteon', 'Jynx', 'Kabuto', 'Kabutops', 'Kadabra', 'Kakuna', 'Kangaskhan', 'Kingler', 'Koffing', 'Krabby', 'Lapras', 'Lickitung', 'Machamp', 'Machoke', 'Machop', 'Magikarp', 'Magmar', 'Magnemite', 'Magneton', 'Mankey', 'Marowak', 'Meowth', 'Metapod', 'Mew', 'Mewtwo', 'Moltres', 'MrMime', 'Muk', 'Nidoking', 'Nidoqueen', 'Nidoran Female', 'Nidoran Male', 'Nidorina', 'Nidorino', 'Ninetales', 'Oddish', 'Omanyte', 'Omastar', 'Onix', 'Paras', 'Parasect', 'Persian', 'Pidgeot', 'Pidgeotto', 'Pidgey', 'Pikachu', 'Pinsir', 'Poliwag', 'Poliwhirl', 'Poliwrath', 'Ponyta', 'Porygon', 'Primeape', 'Psyduck', 'Raichu', 'Rapidash', 'Raticate', 'Rattata', 'Rhydon', 'Rhyhorn', 'Sandshrew', 'Sandslash', 'Scyther', 'Seadra', 'Seaking', 'Seel', 'Shellder', 'Slowbro', 'Slowpoke', 'Snorlax', 'Spearow', 'Squirtle', 'Starmie', 'Staryu', 'Tangela', 'Tauros', 'Tentacool', 'Tentacruel', 'Vaporeon', 'Venomoth', 'Venonat', 'Venusaur'] print(len(a))

true

1c2fec35942e7d1eb8b16707c437ec0877f05d70

17,276

py

Python

py-polars/tests/test_datelike.py

tamasfe/polars

709b8d57e32f61c57191cb8ab435a200e3ae6df7

[ "MIT" ]

3

2022-03-06T12:45:47.000Z

2022-03-26T08:43:31.000Z

py-polars/tests/test_datelike.py

webclinic017/polars

5d342a6474754e47baa4f10d64201a4ae015e6c7

[ "MIT" ]

null

py-polars/tests/test_datelike.py

webclinic017/polars

5d342a6474754e47baa4f10d64201a4ae015e6c7

[ "MIT" ]

null

import io from datetime import date, datetime, timedelta import numpy as np import pandas as pd import pyarrow as pa import pytest from test_series import verify_series_and_expr_api import polars as pl def test_fill_null() -> None: dt = datetime.strptime("2021-01-01", "%Y-%m-%d") s = pl.Series("A", [dt, None]) for fill_val in (dt, pl.lit(dt)): out = s.fill_null(fill_val) # type: ignore assert out.null_count() == 0 assert out.dt[0] == dt assert out.dt[1] == dt dt1 = date(2001, 1, 1) dt2 = date(2001, 1, 2) dt3 = date(2001, 1, 3) s = pl.Series("a", [dt1, dt2, dt3, None]) dt_2 = date(2001, 1, 4) for fill_val in (dt_2, pl.lit(dt_2)): out = s.fill_null(fill_val) # type: ignore assert out.null_count() == 0 assert out.dt[0] == dt1 assert out.dt[1] == dt2 assert out.dt[-1] == dt_2 def test_filter_date() -> None: dataset = pl.DataFrame( {"date": ["2020-01-02", "2020-01-03", "2020-01-04"], "index": [1, 2, 3]} ) df = dataset.with_column(pl.col("date").str.strptime(pl.Date, "%Y-%m-%d")) assert df.filter(pl.col("date") <= pl.lit(datetime(2019, 1, 3))).is_empty() assert df.filter(pl.col("date") < pl.lit(datetime(2020, 1, 4))).shape[0] == 2 assert df.filter(pl.col("date") < pl.lit(datetime(2020, 1, 5))).shape[0] == 3 assert df.filter(pl.col("date") <= pl.lit(datetime(2019, 1, 3))).is_empty() assert df.filter(pl.col("date") < pl.lit(datetime(2020, 1, 4))).shape[0] == 2 assert df.filter(pl.col("date") < pl.lit(datetime(2020, 1, 5))).shape[0] == 3 def test_series_add_timedelta() -> None: dates = pl.Series( [datetime(2000, 1, 1), datetime(2027, 5, 19), datetime(2054, 10, 4)] ) out = pl.Series( [datetime(2027, 5, 19), datetime(2054, 10, 4), datetime(2082, 2, 19)] ) assert (dates + timedelta(days=10_000)).series_equal(out) def test_series_add_datetime() -> None: deltas = pl.Series([timedelta(10_000), timedelta(20_000), timedelta(30_000)]) out = pl.Series( [datetime(2027, 5, 19), datetime(2054, 10, 4), datetime(2082, 2, 19)] ) assert (deltas + pl.Series([datetime(2000, 1, 1)])) == out def test_diff_datetime() -> None: df = pl.DataFrame( { "timestamp": ["2021-02-01", "2021-03-1", "2850-04-1"], "guild": [1, 2, 3], "char": ["a", "a", "b"], } ) out = ( df.with_columns( [ pl.col("timestamp").str.strptime(pl.Date, fmt="%Y-%m-%d"), ] ).with_columns([pl.col("timestamp").diff().list().over("char")]) )["timestamp"] assert out[0] == out[1] def test_timestamp() -> None: a = pl.Series("a", [a * 1000_000 for a in [10000, 20000, 30000]], dtype=pl.Datetime) assert a.dt.timestamp("ms") == [10000, 20000, 30000] out = a.dt.to_python_datetime() assert isinstance(out[0], datetime) assert a.dt.min() == out[0] assert a.dt.max() == out[2] df = pl.DataFrame([out]) # test if rows returns objects assert isinstance(df.row(0)[0], datetime) def test_from_pydatetime() -> None: dates = [ datetime(2021, 1, 1), datetime(2021, 1, 2), datetime(2021, 1, 3), datetime(2021, 1, 4, 12, 12), None, ] s = pl.Series("name", dates) assert s.dtype == pl.Datetime assert s.name == "name" assert s.null_count() == 1 assert s.dt[0] == dates[0] dates = [date(2021, 1, 1), date(2021, 1, 2), date(2021, 1, 3), None] # type: ignore s = pl.Series("name", dates) assert s.dtype == pl.Date assert s.name == "name" assert s.null_count() == 1 assert s.dt[0] == dates[0] def test_to_python_datetime() -> None: df = pl.DataFrame({"a": [1, 2, 3]}) assert ( df.select(pl.col("a").cast(pl.Datetime).dt.to_python_datetime())["a"].dtype == pl.Object ) assert ( df.select(pl.col("a").cast(pl.Datetime).dt.timestamp())["a"].dtype == pl.Int64 ) def test_from_numpy() -> None: # numpy support is limited; will be stored as object x = np.asarray(range(100_000, 200_000, 10_000), dtype="datetime64[s]") s = pl.Series(x) assert s[0] == x[0] assert len(s) == 10 def test_datetime_consistency() -> None: # dt = datetime(2021, 1, 1, 10, 30, 45, 123456) dt = datetime(2021, 1, 1, 10, 30, 45, 123000) df = pl.DataFrame({"date": [dt]}) assert df["date"].dt[0] == dt assert df.select(pl.lit(dt))["literal"].dt[0] == dt def test_timezone() -> None: ts = pa.timestamp("s") data = pa.array([1000, 2000], type=ts) s: pl.Series = pl.from_arrow(data) # type: ignore # with timezone; we do expect a warning here tz_ts = pa.timestamp("s", tz="America/New_York") tz_data = pa.array([1000, 2000], type=tz_ts) with pytest.warns(Warning): tz_s: pl.Series = pl.from_arrow(tz_data) # type: ignore # timezones have no effect, i.e. `s` equals `tz_s` assert s.series_equal(tz_s) def test_to_list() -> None: s = pl.Series("date", [123543, 283478, 1243]).cast(pl.Date) out = s.to_list() assert out[0] == date(2308, 4, 2) s = pl.Series("datetime", [a * 1_000_000 for a in [123543, 283478, 1243]]).cast( pl.Datetime ) out = s.to_list() assert out[0] == datetime(1970, 1, 2, 10, 19, 3) def test_rows() -> None: s0 = pl.Series("date", [123543, 283478, 1243]).cast(pl.Date) s1 = ( pl.Series("datetime", [a * 1_000_000 for a in [123543, 283478, 1243]]) .cast(pl.Datetime) .dt.and_time_unit("ns") ) df = pl.DataFrame([s0, s1]) rows = df.rows() assert rows[0][0] == date(2308, 4, 2) assert rows[0][1] == datetime(1970, 1, 1, 0, 2, 3, 543000) def test_to_numpy() -> None: s0 = pl.Series("date", [123543, 283478, 1243]).cast(pl.Date) s1 = pl.Series( "datetime", [datetime(2021, 1, 2, 3, 4, 5), datetime(2021, 2, 3, 4, 5, 6)] ) s2 = pl.date_range( datetime(2021, 1, 1, 0), datetime(2021, 1, 1, 1), interval="1h", time_unit="ms" ) assert str(s0.to_numpy()) == "['2308-04-02' '2746-02-20' '1973-05-28']" assert ( str(s1.to_numpy()[:2]) == "['2021-01-02T03:04:05.000000' '2021-02-03T04:05:06.000000']" ) assert ( str(s2.to_numpy()[:2]) == "['2021-01-01T00:00:00.000' '2021-01-01T01:00:00.000']" ) s3 = pl.Series([timedelta(hours=1), timedelta(hours=-2)]) out = np.array([3_600_000_000_000, -7_200_000_000_000], dtype="timedelta64[ns]") assert (s3.to_numpy() == out).all() def test_truncate() -> None: start = datetime(2001, 1, 1) stop = datetime(2001, 1, 2) s1 = pl.date_range(start, stop, timedelta(minutes=30), name="dates", time_unit="ms") s2 = pl.date_range(start, stop, timedelta(minutes=30), name="dates", time_unit="ns") # we can pass strings and timedeltas for out in [s1.dt.truncate("1h"), s2.dt.truncate(timedelta(hours=1))]: assert out.dt[0] == start assert out.dt[1] == start assert out.dt[2] == start + timedelta(hours=1) assert out.dt[3] == start + timedelta(hours=1) # ... assert out.dt[-3] == stop - timedelta(hours=1) assert out.dt[-2] == stop - timedelta(hours=1) assert out.dt[-1] == stop def test_date_range() -> None: result = pl.date_range( datetime(1985, 1, 1), datetime(2015, 7, 1), timedelta(days=1, hours=12) ) assert len(result) == 7426 assert result.dt[0] == datetime(1985, 1, 1) assert result.dt[1] == datetime(1985, 1, 2, 12, 0) assert result.dt[2] == datetime(1985, 1, 4, 0, 0) assert result.dt[-1] == datetime(2015, 6, 30, 12, 0) for tu in ["ns", "ms"]: rng = pl.date_range( datetime(2020, 1, 1), datetime(2020, 1, 2), "2h", time_unit=tu ) assert rng.time_unit == tu assert rng.shape == (13,) assert rng.dt[0] == datetime(2020, 1, 1) assert rng.dt[-1] == datetime(2020, 1, 2) def test_date_comp() -> None: one = datetime(2001, 1, 1) two = datetime(2001, 1, 2) a = pl.Series("a", [one, two]) assert (a == one).to_list() == [True, False] assert (a != one).to_list() == [False, True] assert (a > one).to_list() == [False, True] assert (a >= one).to_list() == [True, True] assert (a < one).to_list() == [False, False] assert (a <= one).to_list() == [True, False] one = date(2001, 1, 1) # type: ignore two = date(2001, 1, 2) # type: ignore a = pl.Series("a", [one, two]) assert (a == one).to_list() == [True, False] assert (a != one).to_list() == [False, True] assert (a > one).to_list() == [False, True] assert (a >= one).to_list() == [True, True] assert (a < one).to_list() == [False, False] assert (a <= one).to_list() == [True, False] # also test if the conversion stays correct with wide date ranges one = date(201, 1, 1) # type: ignore two = date(201, 1, 2) # type: ignore a = pl.Series("a", [one, two]) assert (a == one).to_list() == [True, False] assert (a == two).to_list() == [False, True] one = date(5001, 1, 1) # type: ignore two = date(5001, 1, 2) # type: ignore a = pl.Series("a", [one, two]) assert (a == one).to_list() == [True, False] assert (a == two).to_list() == [False, True] def test_truncate_negative_offset() -> None: df = pl.DataFrame( { "event_date": [ datetime(2021, 4, 11), datetime(2021, 4, 29), datetime(2021, 5, 29), ], "adm1_code": [1, 2, 1], } ) out = df.groupby_dynamic( index_column="event_date", every="1mo", period="2mo", offset="-1mo", include_boundaries=True, ).agg( [ pl.col("adm1_code"), ] ) assert out["event_date"].to_list() == [ datetime(2021, 4, 1), datetime(2021, 4, 1), datetime(2021, 5, 1), ] df = pl.DataFrame( { "event_date": [ datetime(2021, 4, 11), datetime(2021, 4, 29), datetime(2021, 5, 29), ], "adm1_code": [1, 2, 1], "five_type": ["a", "b", "a"], "actor": ["a", "a", "a"], "admin": ["a", "a", "a"], "fatalities": [10, 20, 30], } ) out = df.groupby_dynamic( index_column="event_date", every="1mo", by=["admin", "five_type", "actor"], ).agg([pl.col("adm1_code").unique(), (pl.col("fatalities") > 0).sum()]) assert out["event_date"].to_list() == [ datetime(2021, 4, 1), datetime(2021, 5, 1), datetime(2021, 4, 1), ] for dt in [pl.Int32, pl.Int64]: df = pl.DataFrame( { "idx": np.arange(6), "A": ["A", "A", "B", "B", "B", "C"], } ).with_columns(pl.col("idx").cast(dt)) out = df.groupby_dynamic( "idx", every="2i", period="3i", include_boundaries=True ).agg(pl.col("A").list()) assert out.shape == (3, 4) def test_to_arrow() -> None: date_series = pl.Series("dates", ["2022-01-16", "2022-01-17"]).str.strptime( pl.Date, "%Y-%m-%d" ) arr = date_series.to_arrow() assert arr.type == pa.date32() def test_non_exact_strptime() -> None: a = pl.Series("a", ["2022-01-16", "2022-01-17", "foo2022-01-18", "b2022-01-19ar"]) fmt = "%Y-%m-%d" expected = pl.Series("a", [date(2022, 1, 16), date(2022, 1, 17), None, None]) verify_series_and_expr_api( a, expected, "str.strptime", pl.Date, fmt, strict=False, exact=True ) expected = pl.Series( "a", [date(2022, 1, 16), date(2022, 1, 17), date(2022, 1, 18), date(2022, 1, 19)], ) verify_series_and_expr_api( a, expected, "str.strptime", pl.Date, fmt, strict=False, exact=False ) with pytest.raises(Exception): a.str.strptime(pl.Date, fmt, strict=True, exact=True) def test_explode_date() -> None: datetimes = [ datetime(2021, 12, 1, 0, 0), datetime(2021, 12, 1, 0, 0), datetime(2021, 12, 1, 0, 0), datetime(2021, 12, 1, 0, 0), ] dates = [ date(2021, 12, 1), date(2021, 12, 1), date(2021, 12, 1), date(2021, 12, 1), ] for d in [dates, datetimes]: df = pl.DataFrame( { "a": d, "b": ["a", "b", "a", "b"], "c": [1.0, 2.0, 1.1, 2.2], } ) out = ( df.groupby("b") .agg([pl.col("a"), pl.col("c").pct_change()]) .explode(["a", "c"]) ) assert out.shape == (4, 3) def test_rolling() -> None: dates = [ "2020-01-01 13:45:48", "2020-01-01 16:42:13", "2020-01-01 16:45:09", "2020-01-02 18:12:48", "2020-01-03 19:45:32", "2020-01-08 23:16:43", ] df = pl.DataFrame({"dt": dates, "a": [3, 7, 5, 9, 2, 1]}).with_column( pl.col("dt").str.strptime(pl.Datetime) ) out = df.groupby_rolling(index_column="dt", period="2d").agg( [ pl.sum("a").alias("sum_a"), pl.min("a").alias("min_a"), pl.max("a").alias("max_a"), ] ) assert out["sum_a"].to_list() == [3, 10, 15, 24, 11, 1] assert out["max_a"].to_list() == [3, 7, 7, 9, 9, 1] assert out["min_a"].to_list() == [3, 3, 3, 3, 2, 1] def test_upsample() -> None: df = pl.DataFrame( { "time": [ datetime(2021, 2, 1), datetime(2021, 4, 1), datetime(2021, 5, 1), datetime(2021, 6, 1), ], "admin": ["Åland", "Netherlands", "Åland", "Netherlands"], "test2": [0, 1, 2, 3], } ) up = df.upsample( time_column="time", every="1mo", by="admin", maintain_order=True ).select(pl.all().forward_fill()) expected = pl.DataFrame( { "time": [ datetime(2021, 2, 1, 0, 0), datetime(2021, 3, 1, 0, 0), datetime(2021, 4, 1, 0, 0), datetime(2021, 5, 1, 0, 0), datetime(2021, 4, 1, 0, 0), datetime(2021, 5, 1, 0, 0), datetime(2021, 6, 1, 0, 0), ], "admin": [ "Åland", "Åland", "Åland", "Åland", "Netherlands", "Netherlands", "Netherlands", ], "test2": [0, 0, 0, 2, 1, 1, 3], } ) assert up.frame_equal(expected) def test_microseconds_accuracy() -> None: timestamps = [ datetime(2600, 1, 1, 0, 0, 0, 123456), datetime(2800, 1, 1, 0, 0, 0, 456789), ] a = pa.Table.from_arrays( arrays=[timestamps, [128, 256]], schema=pa.schema( [ ("timestamp", pa.timestamp("us")), ("value", pa.int16()), ] ), ) assert pl.from_arrow(a)["timestamp"].to_list() == timestamps # type: ignore def test_cast_time_units() -> None: dates = pl.Series("dates", [datetime(2001, 1, 1), datetime(2001, 2, 1, 10, 8, 9)]) dates_in_ns = np.array([978307200000000000, 981022089000000000]) assert dates.dt.cast_time_unit("ns").cast(int).to_list() == list(dates_in_ns) assert dates.dt.cast_time_unit("us").cast(int).to_list() == list( dates_in_ns // 1_000 ) assert dates.dt.cast_time_unit("ms").cast(int).to_list() == list( dates_in_ns // 1_000_000 ) def test_read_utc_times_parquet() -> None: df = pd.DataFrame( data={ "Timestamp": pd.date_range( "2022-01-01T00:00+00:00", "2022-01-01T10:00+00:00", freq="H" ) } ) f = io.BytesIO() df.to_parquet(f) f.seek(0) df_in = pl.read_parquet(f) assert df_in["Timestamp"][0] == datetime(2022, 1, 1, 0, 0) def test_epoch() -> None: dates = pl.Series("dates", [datetime(2001, 1, 1), datetime(2001, 2, 1, 10, 8, 9)]) for unit in ["ns", "us", "ms"]: assert dates.dt.epoch(unit).series_equal(dates.dt.timestamp(unit)) assert dates.dt.epoch("s").series_equal(dates.dt.timestamp("ms") // 1000) assert dates.dt.epoch("d").series_equal( (dates.dt.timestamp("ms") // (1000 * 3600 * 24)).cast(pl.Int32) ) def test_default_negative_every_offset_dynamic_groupby() -> None: # 2791 dts = [ datetime(2020, 1, 1), datetime(2020, 1, 2), datetime(2020, 2, 1), datetime(2020, 3, 1), ] df = pl.DataFrame({"dt": dts, "idx": range(len(dts))}) out = df.groupby_dynamic(index_column="dt", every="1mo", closed="right").agg( pl.col("idx") ) expected = pl.DataFrame( { "dt": [ datetime(2020, 1, 1, 0, 0), datetime(2020, 1, 1, 0, 0), datetime(2020, 3, 1, 0, 0), ], "idx": [[0], [1, 2], [3]], } ) assert out.frame_equal(expected)

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import io from datetime import date, datetime, timedelta import numpy as np import pandas as pd import pyarrow as pa import pytest from test_series import verify_series_and_expr_api import polars as pl def test_fill_null() -> None: dt = datetime.strptime("2021-01-01", "%Y-%m-%d") s = pl.Series("A", [dt, None]) for fill_val in (dt, pl.lit(dt)): out = s.fill_null(fill_val) assert out.null_count() == 0 assert out.dt[0] == dt assert out.dt[1] == dt dt1 = date(2001, 1, 1) dt2 = date(2001, 1, 2) dt3 = date(2001, 1, 3) s = pl.Series("a", [dt1, dt2, dt3, None]) dt_2 = date(2001, 1, 4) for fill_val in (dt_2, pl.lit(dt_2)): out = s.fill_null(fill_val) assert out.null_count() == 0 assert out.dt[0] == dt1 assert out.dt[1] == dt2 assert out.dt[-1] == dt_2 def test_filter_date() -> None: dataset = pl.DataFrame( {"date": ["2020-01-02", "2020-01-03", "2020-01-04"], "index": [1, 2, 3]} ) df = dataset.with_column(pl.col("date").str.strptime(pl.Date, "%Y-%m-%d")) assert df.filter(pl.col("date") <= pl.lit(datetime(2019, 1, 3))).is_empty() assert df.filter(pl.col("date") < pl.lit(datetime(2020, 1, 4))).shape[0] == 2 assert df.filter(pl.col("date") < pl.lit(datetime(2020, 1, 5))).shape[0] == 3 assert df.filter(pl.col("date") <= pl.lit(datetime(2019, 1, 3))).is_empty() assert df.filter(pl.col("date") < pl.lit(datetime(2020, 1, 4))).shape[0] == 2 assert df.filter(pl.col("date") < pl.lit(datetime(2020, 1, 5))).shape[0] == 3 def test_series_add_timedelta() -> None: dates = pl.Series( [datetime(2000, 1, 1), datetime(2027, 5, 19), datetime(2054, 10, 4)] ) out = pl.Series( [datetime(2027, 5, 19), datetime(2054, 10, 4), datetime(2082, 2, 19)] ) assert (dates + timedelta(days=10_000)).series_equal(out) def test_series_add_datetime() -> None: deltas = pl.Series([timedelta(10_000), timedelta(20_000), timedelta(30_000)]) out = pl.Series( [datetime(2027, 5, 19), datetime(2054, 10, 4), datetime(2082, 2, 19)] ) assert (deltas + pl.Series([datetime(2000, 1, 1)])) == out def test_diff_datetime() -> None: df = pl.DataFrame( { "timestamp": ["2021-02-01", "2021-03-1", "2850-04-1"], "guild": [1, 2, 3], "char": ["a", "a", "b"], } ) out = ( df.with_columns( [ pl.col("timestamp").str.strptime(pl.Date, fmt="%Y-%m-%d"), ] ).with_columns([pl.col("timestamp").diff().list().over("char")]) )["timestamp"] assert out[0] == out[1] def test_timestamp() -> None: a = pl.Series("a", [a * 1000_000 for a in [10000, 20000, 30000]], dtype=pl.Datetime) assert a.dt.timestamp("ms") == [10000, 20000, 30000] out = a.dt.to_python_datetime() assert isinstance(out[0], datetime) assert a.dt.min() == out[0] assert a.dt.max() == out[2] df = pl.DataFrame([out]) assert isinstance(df.row(0)[0], datetime) def test_from_pydatetime() -> None: dates = [ datetime(2021, 1, 1), datetime(2021, 1, 2), datetime(2021, 1, 3), datetime(2021, 1, 4, 12, 12), None, ] s = pl.Series("name", dates) assert s.dtype == pl.Datetime assert s.name == "name" assert s.null_count() == 1 assert s.dt[0] == dates[0] dates = [date(2021, 1, 1), date(2021, 1, 2), date(2021, 1, 3), None] s = pl.Series("name", dates) assert s.dtype == pl.Date assert s.name == "name" assert s.null_count() == 1 assert s.dt[0] == dates[0] def test_to_python_datetime() -> None: df = pl.DataFrame({"a": [1, 2, 3]}) assert ( df.select(pl.col("a").cast(pl.Datetime).dt.to_python_datetime())["a"].dtype == pl.Object ) assert ( df.select(pl.col("a").cast(pl.Datetime).dt.timestamp())["a"].dtype == pl.Int64 ) def test_from_numpy() -> None: x = np.asarray(range(100_000, 200_000, 10_000), dtype="datetime64[s]") s = pl.Series(x) assert s[0] == x[0] assert len(s) == 10 def test_datetime_consistency() -> None: dt = datetime(2021, 1, 1, 10, 30, 45, 123000) df = pl.DataFrame({"date": [dt]}) assert df["date"].dt[0] == dt assert df.select(pl.lit(dt))["literal"].dt[0] == dt def test_timezone() -> None: ts = pa.timestamp("s") data = pa.array([1000, 2000], type=ts) s: pl.Series = pl.from_arrow(data) tz_ts = pa.timestamp("s", tz="America/New_York") tz_data = pa.array([1000, 2000], type=tz_ts) with pytest.warns(Warning): tz_s: pl.Series = pl.from_arrow(tz_data) assert s.series_equal(tz_s) def test_to_list() -> None: s = pl.Series("date", [123543, 283478, 1243]).cast(pl.Date) out = s.to_list() assert out[0] == date(2308, 4, 2) s = pl.Series("datetime", [a * 1_000_000 for a in [123543, 283478, 1243]]).cast( pl.Datetime ) out = s.to_list() assert out[0] == datetime(1970, 1, 2, 10, 19, 3) def test_rows() -> None: s0 = pl.Series("date", [123543, 283478, 1243]).cast(pl.Date) s1 = ( pl.Series("datetime", [a * 1_000_000 for a in [123543, 283478, 1243]]) .cast(pl.Datetime) .dt.and_time_unit("ns") ) df = pl.DataFrame([s0, s1]) rows = df.rows() assert rows[0][0] == date(2308, 4, 2) assert rows[0][1] == datetime(1970, 1, 1, 0, 2, 3, 543000) def test_to_numpy() -> None: s0 = pl.Series("date", [123543, 283478, 1243]).cast(pl.Date) s1 = pl.Series( "datetime", [datetime(2021, 1, 2, 3, 4, 5), datetime(2021, 2, 3, 4, 5, 6)] ) s2 = pl.date_range( datetime(2021, 1, 1, 0), datetime(2021, 1, 1, 1), interval="1h", time_unit="ms" ) assert str(s0.to_numpy()) == "['2308-04-02' '2746-02-20' '1973-05-28']" assert ( str(s1.to_numpy()[:2]) == "['2021-01-02T03:04:05.000000' '2021-02-03T04:05:06.000000']" ) assert ( str(s2.to_numpy()[:2]) == "['2021-01-01T00:00:00.000' '2021-01-01T01:00:00.000']" ) s3 = pl.Series([timedelta(hours=1), timedelta(hours=-2)]) out = np.array([3_600_000_000_000, -7_200_000_000_000], dtype="timedelta64[ns]") assert (s3.to_numpy() == out).all() def test_truncate() -> None: start = datetime(2001, 1, 1) stop = datetime(2001, 1, 2) s1 = pl.date_range(start, stop, timedelta(minutes=30), name="dates", time_unit="ms") s2 = pl.date_range(start, stop, timedelta(minutes=30), name="dates", time_unit="ns") for out in [s1.dt.truncate("1h"), s2.dt.truncate(timedelta(hours=1))]: assert out.dt[0] == start assert out.dt[1] == start assert out.dt[2] == start + timedelta(hours=1) assert out.dt[3] == start + timedelta(hours=1) assert out.dt[-3] == stop - timedelta(hours=1) assert out.dt[-2] == stop - timedelta(hours=1) assert out.dt[-1] == stop def test_date_range() -> None: result = pl.date_range( datetime(1985, 1, 1), datetime(2015, 7, 1), timedelta(days=1, hours=12) ) assert len(result) == 7426 assert result.dt[0] == datetime(1985, 1, 1) assert result.dt[1] == datetime(1985, 1, 2, 12, 0) assert result.dt[2] == datetime(1985, 1, 4, 0, 0) assert result.dt[-1] == datetime(2015, 6, 30, 12, 0) for tu in ["ns", "ms"]: rng = pl.date_range( datetime(2020, 1, 1), datetime(2020, 1, 2), "2h", time_unit=tu ) assert rng.time_unit == tu assert rng.shape == (13,) assert rng.dt[0] == datetime(2020, 1, 1) assert rng.dt[-1] == datetime(2020, 1, 2) def test_date_comp() -> None: one = datetime(2001, 1, 1) two = datetime(2001, 1, 2) a = pl.Series("a", [one, two]) assert (a == one).to_list() == [True, False] assert (a != one).to_list() == [False, True] assert (a > one).to_list() == [False, True] assert (a >= one).to_list() == [True, True] assert (a < one).to_list() == [False, False] assert (a <= one).to_list() == [True, False] one = date(2001, 1, 1) two = date(2001, 1, 2) a = pl.Series("a", [one, two]) assert (a == one).to_list() == [True, False] assert (a != one).to_list() == [False, True] assert (a > one).to_list() == [False, True] assert (a >= one).to_list() == [True, True] assert (a < one).to_list() == [False, False] assert (a <= one).to_list() == [True, False] one = date(201, 1, 1) two = date(201, 1, 2) a = pl.Series("a", [one, two]) assert (a == one).to_list() == [True, False] assert (a == two).to_list() == [False, True] one = date(5001, 1, 1) two = date(5001, 1, 2) a = pl.Series("a", [one, two]) assert (a == one).to_list() == [True, False] assert (a == two).to_list() == [False, True] def test_truncate_negative_offset() -> None: df = pl.DataFrame( { "event_date": [ datetime(2021, 4, 11), datetime(2021, 4, 29), datetime(2021, 5, 29), ], "adm1_code": [1, 2, 1], } ) out = df.groupby_dynamic( index_column="event_date", every="1mo", period="2mo", offset="-1mo", include_boundaries=True, ).agg( [ pl.col("adm1_code"), ] ) assert out["event_date"].to_list() == [ datetime(2021, 4, 1), datetime(2021, 4, 1), datetime(2021, 5, 1), ] df = pl.DataFrame( { "event_date": [ datetime(2021, 4, 11), datetime(2021, 4, 29), datetime(2021, 5, 29), ], "adm1_code": [1, 2, 1], "five_type": ["a", "b", "a"], "actor": ["a", "a", "a"], "admin": ["a", "a", "a"], "fatalities": [10, 20, 30], } ) out = df.groupby_dynamic( index_column="event_date", every="1mo", by=["admin", "five_type", "actor"], ).agg([pl.col("adm1_code").unique(), (pl.col("fatalities") > 0).sum()]) assert out["event_date"].to_list() == [ datetime(2021, 4, 1), datetime(2021, 5, 1), datetime(2021, 4, 1), ] for dt in [pl.Int32, pl.Int64]: df = pl.DataFrame( { "idx": np.arange(6), "A": ["A", "A", "B", "B", "B", "C"], } ).with_columns(pl.col("idx").cast(dt)) out = df.groupby_dynamic( "idx", every="2i", period="3i", include_boundaries=True ).agg(pl.col("A").list()) assert out.shape == (3, 4) def test_to_arrow() -> None: date_series = pl.Series("dates", ["2022-01-16", "2022-01-17"]).str.strptime( pl.Date, "%Y-%m-%d" ) arr = date_series.to_arrow() assert arr.type == pa.date32() def test_non_exact_strptime() -> None: a = pl.Series("a", ["2022-01-16", "2022-01-17", "foo2022-01-18", "b2022-01-19ar"]) fmt = "%Y-%m-%d" expected = pl.Series("a", [date(2022, 1, 16), date(2022, 1, 17), None, None]) verify_series_and_expr_api( a, expected, "str.strptime", pl.Date, fmt, strict=False, exact=True ) expected = pl.Series( "a", [date(2022, 1, 16), date(2022, 1, 17), date(2022, 1, 18), date(2022, 1, 19)], ) verify_series_and_expr_api( a, expected, "str.strptime", pl.Date, fmt, strict=False, exact=False ) with pytest.raises(Exception): a.str.strptime(pl.Date, fmt, strict=True, exact=True) def test_explode_date() -> None: datetimes = [ datetime(2021, 12, 1, 0, 0), datetime(2021, 12, 1, 0, 0), datetime(2021, 12, 1, 0, 0), datetime(2021, 12, 1, 0, 0), ] dates = [ date(2021, 12, 1), date(2021, 12, 1), date(2021, 12, 1), date(2021, 12, 1), ] for d in [dates, datetimes]: df = pl.DataFrame( { "a": d, "b": ["a", "b", "a", "b"], "c": [1.0, 2.0, 1.1, 2.2], } ) out = ( df.groupby("b") .agg([pl.col("a"), pl.col("c").pct_change()]) .explode(["a", "c"]) ) assert out.shape == (4, 3) def test_rolling() -> None: dates = [ "2020-01-01 13:45:48", "2020-01-01 16:42:13", "2020-01-01 16:45:09", "2020-01-02 18:12:48", "2020-01-03 19:45:32", "2020-01-08 23:16:43", ] df = pl.DataFrame({"dt": dates, "a": [3, 7, 5, 9, 2, 1]}).with_column( pl.col("dt").str.strptime(pl.Datetime) ) out = df.groupby_rolling(index_column="dt", period="2d").agg( [ pl.sum("a").alias("sum_a"), pl.min("a").alias("min_a"), pl.max("a").alias("max_a"), ] ) assert out["sum_a"].to_list() == [3, 10, 15, 24, 11, 1] assert out["max_a"].to_list() == [3, 7, 7, 9, 9, 1] assert out["min_a"].to_list() == [3, 3, 3, 3, 2, 1] def test_upsample() -> None: df = pl.DataFrame( { "time": [ datetime(2021, 2, 1), datetime(2021, 4, 1), datetime(2021, 5, 1), datetime(2021, 6, 1), ], "admin": ["Åland", "Netherlands", "Åland", "Netherlands"], "test2": [0, 1, 2, 3], } ) up = df.upsample( time_column="time", every="1mo", by="admin", maintain_order=True ).select(pl.all().forward_fill()) expected = pl.DataFrame( { "time": [ datetime(2021, 2, 1, 0, 0), datetime(2021, 3, 1, 0, 0), datetime(2021, 4, 1, 0, 0), datetime(2021, 5, 1, 0, 0), datetime(2021, 4, 1, 0, 0), datetime(2021, 5, 1, 0, 0), datetime(2021, 6, 1, 0, 0), ], "admin": [ "Åland", "Åland", "Åland", "Åland", "Netherlands", "Netherlands", "Netherlands", ], "test2": [0, 0, 0, 2, 1, 1, 3], } ) assert up.frame_equal(expected) def test_microseconds_accuracy() -> None: timestamps = [ datetime(2600, 1, 1, 0, 0, 0, 123456), datetime(2800, 1, 1, 0, 0, 0, 456789), ] a = pa.Table.from_arrays( arrays=[timestamps, [128, 256]], schema=pa.schema( [ ("timestamp", pa.timestamp("us")), ("value", pa.int16()), ] ), ) assert pl.from_arrow(a)["timestamp"].to_list() == timestamps def test_cast_time_units() -> None: dates = pl.Series("dates", [datetime(2001, 1, 1), datetime(2001, 2, 1, 10, 8, 9)]) dates_in_ns = np.array([978307200000000000, 981022089000000000]) assert dates.dt.cast_time_unit("ns").cast(int).to_list() == list(dates_in_ns) assert dates.dt.cast_time_unit("us").cast(int).to_list() == list( dates_in_ns // 1_000 ) assert dates.dt.cast_time_unit("ms").cast(int).to_list() == list( dates_in_ns // 1_000_000 ) def test_read_utc_times_parquet() -> None: df = pd.DataFrame( data={ "Timestamp": pd.date_range( "2022-01-01T00:00+00:00", "2022-01-01T10:00+00:00", freq="H" ) } ) f = io.BytesIO() df.to_parquet(f) f.seek(0) df_in = pl.read_parquet(f) assert df_in["Timestamp"][0] == datetime(2022, 1, 1, 0, 0) def test_epoch() -> None: dates = pl.Series("dates", [datetime(2001, 1, 1), datetime(2001, 2, 1, 10, 8, 9)]) for unit in ["ns", "us", "ms"]: assert dates.dt.epoch(unit).series_equal(dates.dt.timestamp(unit)) assert dates.dt.epoch("s").series_equal(dates.dt.timestamp("ms") // 1000) assert dates.dt.epoch("d").series_equal( (dates.dt.timestamp("ms") // (1000 * 3600 * 24)).cast(pl.Int32) ) def test_default_negative_every_offset_dynamic_groupby() -> None: dts = [ datetime(2020, 1, 1), datetime(2020, 1, 2), datetime(2020, 2, 1), datetime(2020, 3, 1), ] df = pl.DataFrame({"dt": dts, "idx": range(len(dts))}) out = df.groupby_dynamic(index_column="dt", every="1mo", closed="right").agg( pl.col("idx") ) expected = pl.DataFrame( { "dt": [ datetime(2020, 1, 1, 0, 0), datetime(2020, 1, 1, 0, 0), datetime(2020, 3, 1, 0, 0), ], "idx": [[0], [1, 2], [3]], } ) assert out.frame_equal(expected)

true

1c2fecc3e4fcae7bb5d8e4e51a3b7a4a48038d87

9,247

py

Python

networkx/algorithms/tests/test_clique.py

AaronOpfer/networkx

f04ca835c3503f04f9b3e933270575980e44205b

[ "BSD-3-Clause" ]

1

2020-05-13T01:08:42.000Z

networkx/algorithms/tests/test_clique.py

AaronOpfer/networkx

f04ca835c3503f04f9b3e933270575980e44205b

[ "BSD-3-Clause" ]

1

2019-11-28T21:08:50.000Z

networkx/algorithms/tests/test_clique.py

AaronOpfer/networkx

f04ca835c3503f04f9b3e933270575980e44205b

[ "BSD-3-Clause" ]

1

2021-01-27T12:09:05.000Z

#!/usr/bin/env python from nose.tools import * import networkx as nx from networkx import convert_node_labels_to_integers as cnlti class TestCliques: def setUp(self): z = [3, 4, 3, 4, 2, 4, 2, 1, 1, 1, 1] self.G = cnlti(nx.generators.havel_hakimi_graph(z), first_label=1) self.cl = list(nx.find_cliques(self.G)) H = nx.complete_graph(6) H = nx.relabel_nodes(H, dict([(i, i + 1) for i in range(6)])) H.remove_edges_from([(2, 6), (2, 5), (2, 4), (1, 3), (5, 3)]) self.H = H def test_find_cliques1(self): cl = list(nx.find_cliques(self.G)) rcl = nx.find_cliques_recursive(self.G) expected = [[2, 6, 1, 3], [2, 6, 4], [5, 4, 7], [8, 9], [10, 11]] assert_equal(sorted(map(sorted, cl)), sorted(map(sorted, rcl))) assert_equal(sorted(map(sorted, cl)), sorted(map(sorted, expected))) def test_selfloops(self): self.G.add_edge(1, 1) cl = list(nx.find_cliques(self.G)) rcl = list(nx.find_cliques_recursive(self.G)) assert_equal(set(map(frozenset, cl)), set(map(frozenset, rcl))) answer = [{2, 6, 1, 3}, {2, 6, 4}, {5, 4, 7}, {8, 9}, {10, 11}] assert_equal(len(answer), len(cl)) assert_true(all(set(c) in answer for c in cl)) def test_find_cliques2(self): hcl = list(nx.find_cliques(self.H)) assert_equal(sorted(map(sorted, hcl)), [[1, 2], [1, 4, 5, 6], [2, 3], [3, 4, 6]]) def test_clique_number(self): G = self.G assert_equal(nx.graph_clique_number(G), 4) assert_equal(nx.graph_clique_number(G, cliques=self.cl), 4) def test_clique_number2(self): G = nx.Graph() G.add_nodes_from([1, 2, 3]) assert_equal(nx.graph_clique_number(G), 1) def test_clique_number3(self): G = nx.Graph() assert_equal(nx.graph_clique_number(G), 0) def test_number_of_cliques(self): G = self.G assert_equal(nx.graph_number_of_cliques(G), 5) assert_equal(nx.graph_number_of_cliques(G, cliques=self.cl), 5) assert_equal(nx.number_of_cliques(G, 1), 1) assert_equal(list(nx.number_of_cliques(G, [1]).values()), [1]) assert_equal(list(nx.number_of_cliques(G, [1, 2]).values()), [1, 2]) assert_equal(nx.number_of_cliques(G, [1, 2]), {1: 1, 2: 2}) assert_equal(nx.number_of_cliques(G, 2), 2) assert_equal(nx.number_of_cliques(G), {1: 1, 2: 2, 3: 1, 4: 2, 5: 1, 6: 2, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1}) assert_equal(nx.number_of_cliques(G, nodes=list(G)), {1: 1, 2: 2, 3: 1, 4: 2, 5: 1, 6: 2, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1}) assert_equal(nx.number_of_cliques(G, nodes=[2, 3, 4]), {2: 2, 3: 1, 4: 2}) assert_equal(nx.number_of_cliques(G, cliques=self.cl), {1: 1, 2: 2, 3: 1, 4: 2, 5: 1, 6: 2, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1}) assert_equal(nx.number_of_cliques(G, list(G), cliques=self.cl), {1: 1, 2: 2, 3: 1, 4: 2, 5: 1, 6: 2, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1}) def test_node_clique_number(self): G = self.G assert_equal(nx.node_clique_number(G, 1), 4) assert_equal(list(nx.node_clique_number(G, [1]).values()), [4]) assert_equal(list(nx.node_clique_number(G, [1, 2]).values()), [4, 4]) assert_equal(nx.node_clique_number(G, [1, 2]), {1: 4, 2: 4}) assert_equal(nx.node_clique_number(G, 1), 4) assert_equal(nx.node_clique_number(G), {1: 4, 2: 4, 3: 4, 4: 3, 5: 3, 6: 4, 7: 3, 8: 2, 9: 2, 10: 2, 11: 2}) assert_equal(nx.node_clique_number(G, cliques=self.cl), {1: 4, 2: 4, 3: 4, 4: 3, 5: 3, 6: 4, 7: 3, 8: 2, 9: 2, 10: 2, 11: 2}) def test_cliques_containing_node(self): G = self.G assert_equal(nx.cliques_containing_node(G, 1), [[2, 6, 1, 3]]) assert_equal(list(nx.cliques_containing_node(G, [1]).values()), [[[2, 6, 1, 3]]]) assert_equal([sorted(c) for c in list(nx.cliques_containing_node(G, [1, 2]).values())], [[[2, 6, 1, 3]], [[2, 6, 1, 3], [2, 6, 4]]]) result = nx.cliques_containing_node(G, [1, 2]) for k, v in result.items(): result[k] = sorted(v) assert_equal(result, {1: [[2, 6, 1, 3]], 2: [[2, 6, 1, 3], [2, 6, 4]]}) assert_equal(nx.cliques_containing_node(G, 1), [[2, 6, 1, 3]]) expected = [{2, 6, 1, 3}, {2, 6, 4}] answer = [set(c) for c in nx.cliques_containing_node(G, 2)] assert_in(answer, (expected, list(reversed(expected)))) answer = [set(c) for c in nx.cliques_containing_node(G, 2, cliques=self.cl)] assert_in(answer, (expected, list(reversed(expected)))) assert_equal(len(nx.cliques_containing_node(G)), 11) def test_make_clique_bipartite(self): G = self.G B = nx.make_clique_bipartite(G) assert_equal(sorted(B), [-5, -4, -3, -2, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) # Project onto the nodes of the original graph. H = nx.project(B, range(1, 12)) assert_equal(H.adj, G.adj) # Project onto the nodes representing the cliques. H1 = nx.project(B, range(-5, 0)) # Relabel the negative numbers as positive ones. H1 = nx.relabel_nodes(H1, {-v: v for v in range(1, 6)}) assert_equal(sorted(H1), [1, 2, 3, 4, 5]) def test_make_max_clique_graph(self): """Tests that the maximal clique graph is the same as the bipartite clique graph after being projected onto the nodes representing the cliques. """ G = self.G B = nx.make_clique_bipartite(G) # Project onto the nodes representing the cliques. H1 = nx.project(B, range(-5, 0)) # Relabel the negative numbers as nonnegative ones, starting at # 0. H1 = nx.relabel_nodes(H1, {-v: v - 1 for v in range(1, 6)}) H2 = nx.make_max_clique_graph(G) assert_equal(H1.adj, H2.adj) @raises(nx.NetworkXNotImplemented) def test_directed(self): cliques = nx.find_cliques(nx.DiGraph()) class TestEnumerateAllCliques: def test_paper_figure_4(self): # Same graph as given in Fig. 4 of paper enumerate_all_cliques is # based on. # http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1559964&isnumber=33129 G = nx.Graph() edges_fig_4 = [('a', 'b'), ('a', 'c'), ('a', 'd'), ('a', 'e'), ('b', 'c'), ('b', 'd'), ('b', 'e'), ('c', 'd'), ('c', 'e'), ('d', 'e'), ('f', 'b'), ('f', 'c'), ('f', 'g'), ('g', 'f'), ('g', 'c'), ('g', 'd'), ('g', 'e')] G.add_edges_from(edges_fig_4) cliques = list(nx.enumerate_all_cliques(G)) clique_sizes = list(map(len, cliques)) assert_equal(sorted(clique_sizes), clique_sizes) expected_cliques = [['a'], ['b'], ['c'], ['d'], ['e'], ['f'], ['g'], ['a', 'b'], ['a', 'b', 'd'], ['a', 'b', 'd', 'e'], ['a', 'b', 'e'], ['a', 'c'], ['a', 'c', 'd'], ['a', 'c', 'd', 'e'], ['a', 'c', 'e'], ['a', 'd'], ['a', 'd', 'e'], ['a', 'e'], ['b', 'c'], ['b', 'c', 'd'], ['b', 'c', 'd', 'e'], ['b', 'c', 'e'], ['b', 'c', 'f'], ['b', 'd'], ['b', 'd', 'e'], ['b', 'e'], ['b', 'f'], ['c', 'd'], ['c', 'd', 'e'], ['c', 'd', 'e', 'g'], ['c', 'd', 'g'], ['c', 'e'], ['c', 'e', 'g'], ['c', 'f'], ['c', 'f', 'g'], ['c', 'g'], ['d', 'e'], ['d', 'e', 'g'], ['d', 'g'], ['e', 'g'], ['f', 'g'], ['a', 'b', 'c'], ['a', 'b', 'c', 'd'], ['a', 'b', 'c', 'd', 'e'], ['a', 'b', 'c', 'e']] assert_equal(sorted(map(sorted, cliques)), sorted(map(sorted, expected_cliques)))

42.810185

95

0.43798

from nose.tools import * import networkx as nx from networkx import convert_node_labels_to_integers as cnlti class TestCliques: def setUp(self): z = [3, 4, 3, 4, 2, 4, 2, 1, 1, 1, 1] self.G = cnlti(nx.generators.havel_hakimi_graph(z), first_label=1) self.cl = list(nx.find_cliques(self.G)) H = nx.complete_graph(6) H = nx.relabel_nodes(H, dict([(i, i + 1) for i in range(6)])) H.remove_edges_from([(2, 6), (2, 5), (2, 4), (1, 3), (5, 3)]) self.H = H def test_find_cliques1(self): cl = list(nx.find_cliques(self.G)) rcl = nx.find_cliques_recursive(self.G) expected = [[2, 6, 1, 3], [2, 6, 4], [5, 4, 7], [8, 9], [10, 11]] assert_equal(sorted(map(sorted, cl)), sorted(map(sorted, rcl))) assert_equal(sorted(map(sorted, cl)), sorted(map(sorted, expected))) def test_selfloops(self): self.G.add_edge(1, 1) cl = list(nx.find_cliques(self.G)) rcl = list(nx.find_cliques_recursive(self.G)) assert_equal(set(map(frozenset, cl)), set(map(frozenset, rcl))) answer = [{2, 6, 1, 3}, {2, 6, 4}, {5, 4, 7}, {8, 9}, {10, 11}] assert_equal(len(answer), len(cl)) assert_true(all(set(c) in answer for c in cl)) def test_find_cliques2(self): hcl = list(nx.find_cliques(self.H)) assert_equal(sorted(map(sorted, hcl)), [[1, 2], [1, 4, 5, 6], [2, 3], [3, 4, 6]]) def test_clique_number(self): G = self.G assert_equal(nx.graph_clique_number(G), 4) assert_equal(nx.graph_clique_number(G, cliques=self.cl), 4) def test_clique_number2(self): G = nx.Graph() G.add_nodes_from([1, 2, 3]) assert_equal(nx.graph_clique_number(G), 1) def test_clique_number3(self): G = nx.Graph() assert_equal(nx.graph_clique_number(G), 0) def test_number_of_cliques(self): G = self.G assert_equal(nx.graph_number_of_cliques(G), 5) assert_equal(nx.graph_number_of_cliques(G, cliques=self.cl), 5) assert_equal(nx.number_of_cliques(G, 1), 1) assert_equal(list(nx.number_of_cliques(G, [1]).values()), [1]) assert_equal(list(nx.number_of_cliques(G, [1, 2]).values()), [1, 2]) assert_equal(nx.number_of_cliques(G, [1, 2]), {1: 1, 2: 2}) assert_equal(nx.number_of_cliques(G, 2), 2) assert_equal(nx.number_of_cliques(G), {1: 1, 2: 2, 3: 1, 4: 2, 5: 1, 6: 2, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1}) assert_equal(nx.number_of_cliques(G, nodes=list(G)), {1: 1, 2: 2, 3: 1, 4: 2, 5: 1, 6: 2, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1}) assert_equal(nx.number_of_cliques(G, nodes=[2, 3, 4]), {2: 2, 3: 1, 4: 2}) assert_equal(nx.number_of_cliques(G, cliques=self.cl), {1: 1, 2: 2, 3: 1, 4: 2, 5: 1, 6: 2, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1}) assert_equal(nx.number_of_cliques(G, list(G), cliques=self.cl), {1: 1, 2: 2, 3: 1, 4: 2, 5: 1, 6: 2, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1}) def test_node_clique_number(self): G = self.G assert_equal(nx.node_clique_number(G, 1), 4) assert_equal(list(nx.node_clique_number(G, [1]).values()), [4]) assert_equal(list(nx.node_clique_number(G, [1, 2]).values()), [4, 4]) assert_equal(nx.node_clique_number(G, [1, 2]), {1: 4, 2: 4}) assert_equal(nx.node_clique_number(G, 1), 4) assert_equal(nx.node_clique_number(G), {1: 4, 2: 4, 3: 4, 4: 3, 5: 3, 6: 4, 7: 3, 8: 2, 9: 2, 10: 2, 11: 2}) assert_equal(nx.node_clique_number(G, cliques=self.cl), {1: 4, 2: 4, 3: 4, 4: 3, 5: 3, 6: 4, 7: 3, 8: 2, 9: 2, 10: 2, 11: 2}) def test_cliques_containing_node(self): G = self.G assert_equal(nx.cliques_containing_node(G, 1), [[2, 6, 1, 3]]) assert_equal(list(nx.cliques_containing_node(G, [1]).values()), [[[2, 6, 1, 3]]]) assert_equal([sorted(c) for c in list(nx.cliques_containing_node(G, [1, 2]).values())], [[[2, 6, 1, 3]], [[2, 6, 1, 3], [2, 6, 4]]]) result = nx.cliques_containing_node(G, [1, 2]) for k, v in result.items(): result[k] = sorted(v) assert_equal(result, {1: [[2, 6, 1, 3]], 2: [[2, 6, 1, 3], [2, 6, 4]]}) assert_equal(nx.cliques_containing_node(G, 1), [[2, 6, 1, 3]]) expected = [{2, 6, 1, 3}, {2, 6, 4}] answer = [set(c) for c in nx.cliques_containing_node(G, 2)] assert_in(answer, (expected, list(reversed(expected)))) answer = [set(c) for c in nx.cliques_containing_node(G, 2, cliques=self.cl)] assert_in(answer, (expected, list(reversed(expected)))) assert_equal(len(nx.cliques_containing_node(G)), 11) def test_make_clique_bipartite(self): G = self.G B = nx.make_clique_bipartite(G) assert_equal(sorted(B), [-5, -4, -3, -2, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) H = nx.project(B, range(1, 12)) assert_equal(H.adj, G.adj) H1 = nx.project(B, range(-5, 0)) H1 = nx.relabel_nodes(H1, {-v: v for v in range(1, 6)}) assert_equal(sorted(H1), [1, 2, 3, 4, 5]) def test_make_max_clique_graph(self): G = self.G B = nx.make_clique_bipartite(G) H1 = nx.project(B, range(-5, 0)) H1 = nx.relabel_nodes(H1, {-v: v - 1 for v in range(1, 6)}) H2 = nx.make_max_clique_graph(G) assert_equal(H1.adj, H2.adj) @raises(nx.NetworkXNotImplemented) def test_directed(self): cliques = nx.find_cliques(nx.DiGraph()) class TestEnumerateAllCliques: def test_paper_figure_4(self): G = nx.Graph() edges_fig_4 = [('a', 'b'), ('a', 'c'), ('a', 'd'), ('a', 'e'), ('b', 'c'), ('b', 'd'), ('b', 'e'), ('c', 'd'), ('c', 'e'), ('d', 'e'), ('f', 'b'), ('f', 'c'), ('f', 'g'), ('g', 'f'), ('g', 'c'), ('g', 'd'), ('g', 'e')] G.add_edges_from(edges_fig_4) cliques = list(nx.enumerate_all_cliques(G)) clique_sizes = list(map(len, cliques)) assert_equal(sorted(clique_sizes), clique_sizes) expected_cliques = [['a'], ['b'], ['c'], ['d'], ['e'], ['f'], ['g'], ['a', 'b'], ['a', 'b', 'd'], ['a', 'b', 'd', 'e'], ['a', 'b', 'e'], ['a', 'c'], ['a', 'c', 'd'], ['a', 'c', 'd', 'e'], ['a', 'c', 'e'], ['a', 'd'], ['a', 'd', 'e'], ['a', 'e'], ['b', 'c'], ['b', 'c', 'd'], ['b', 'c', 'd', 'e'], ['b', 'c', 'e'], ['b', 'c', 'f'], ['b', 'd'], ['b', 'd', 'e'], ['b', 'e'], ['b', 'f'], ['c', 'd'], ['c', 'd', 'e'], ['c', 'd', 'e', 'g'], ['c', 'd', 'g'], ['c', 'e'], ['c', 'e', 'g'], ['c', 'f'], ['c', 'f', 'g'], ['c', 'g'], ['d', 'e'], ['d', 'e', 'g'], ['d', 'g'], ['e', 'g'], ['f', 'g'], ['a', 'b', 'c'], ['a', 'b', 'c', 'd'], ['a', 'b', 'c', 'd', 'e'], ['a', 'b', 'c', 'e']] assert_equal(sorted(map(sorted, cliques)), sorted(map(sorted, expected_cliques)))

true

1c2feccef9baf99c4cf758dcacd8533f5c4d54ca

747

py

Python

gsextract/gsextract.py

ssloxford/gsextract

f892161767f994f291ffd13a45417dfe7184d409

[ "Unlicense" ]

35

2020-09-30T11:18:13.000Z

2022-03-20T13:05:24.000Z

gsextract/gsextract.py

ssloxford/gsextract

f892161767f994f291ffd13a45417dfe7184d409

[ "Unlicense" ]

2

2020-11-30T22:06:58.000Z

2021-01-01T15:19:43.000Z

gsextract/gsextract.py

ssloxford/gsextract

f892161767f994f291ffd13a45417dfe7184d409

[ "Unlicense" ]

4

2020-11-19T22:20:25.000Z

2021-10-09T01:34:58.000Z

import click import gsextract.gse_parser as gse_parser @click.command() @click.argument('input_file', type=click.Path(exists=True)) @click.argument('output_file', type=click.Path()) @click.option('--stream/--no-stream', default=False, help='Stream continuously from the file. Use the --stream flag to dump to a pcap from a real time GSE recording.') @click.option('--reliable/--no-reliable', default=True, help='Add the --no-reliable flag to attempt to brute force IP headers in certain situations. Increases recovery but also can result in fake packets.') def gsextract(input_file, output_file, stream, reliable): gse_parser.gse_parse(file=input_file, outfile=output_file, stream=stream, reliable=reliable) def cli_runner(): gsextract()

57.461538

206

0.768407

import click import gsextract.gse_parser as gse_parser @click.command() @click.argument('input_file', type=click.Path(exists=True)) @click.argument('output_file', type=click.Path()) @click.option('--stream/--no-stream', default=False, help='Stream continuously from the file. Use the --stream flag to dump to a pcap from a real time GSE recording.') @click.option('--reliable/--no-reliable', default=True, help='Add the --no-reliable flag to attempt to brute force IP headers in certain situations. Increases recovery but also can result in fake packets.') def gsextract(input_file, output_file, stream, reliable): gse_parser.gse_parse(file=input_file, outfile=output_file, stream=stream, reliable=reliable) def cli_runner(): gsextract()

true

1c2fed3ccbdce6442d7a0f5d1ce30c9fad72def6

728

py

Python

fcuser/admin.py

hwanseok-dev/the-fast

089952047f7228385e655153c094d0fce9c5e1da

[ "MIT" ]

null

fcuser/admin.py

hwanseok-dev/the-fast

089952047f7228385e655153c094d0fce9c5e1da

[ "MIT" ]

null

fcuser/admin.py

hwanseok-dev/the-fast

089952047f7228385e655153c094d0fce9c5e1da

[ "MIT" ]

null

from django.contrib import admin from .models import Fcuser class FcuserAdmin(admin.ModelAdmin): list_display = ('email', 'password') def changelist_view(self, request, extra_context=None): extra_context = {'title': '사용자 목록'} return super().changelist_view(request, extra_context) def changeform_view(self, request, object_id=None, form_url='', extra_context=None): fcuser = Fcuser.objects.get(pk=object_id) extra_context = {'title': f'{fcuser.name} 수정'} return super().changeform_view(request, object_id, form_url, extra_context) admin.site.register(Fcuser, FcuserAdmin) admin.site.site_header = "HwanSeok's BackOffice" admin.site.index_title = "HwanSeok's BackOffice"

34.666667

88

0.723901

from django.contrib import admin from .models import Fcuser class FcuserAdmin(admin.ModelAdmin): list_display = ('email', 'password') def changelist_view(self, request, extra_context=None): extra_context = {'title': '사용자 목록'} return super().changelist_view(request, extra_context) def changeform_view(self, request, object_id=None, form_url='', extra_context=None): fcuser = Fcuser.objects.get(pk=object_id) extra_context = {'title': f'{fcuser.name} 수정'} return super().changeform_view(request, object_id, form_url, extra_context) admin.site.register(Fcuser, FcuserAdmin) admin.site.site_header = "HwanSeok's BackOffice" admin.site.index_title = "HwanSeok's BackOffice"

true

1c2fed7afd2f122fb62bb2d4f069b59c2f3a2420

4,225

py

Python

yatube/yatube/settings.py

Andrey11995/yatube_project

5f053803e6deb42f1e75e69ecb3d2b94cbb255e5

[ "MIT" ]

null

yatube/yatube/settings.py

Andrey11995/yatube_project

5f053803e6deb42f1e75e69ecb3d2b94cbb255e5

[ "MIT" ]

null

yatube/yatube/settings.py

Andrey11995/yatube_project

5f053803e6deb42f1e75e69ecb3d2b94cbb255e5

[ "MIT" ]

null

""" Django settings for yatube project. Generated by 'django-admin startproject' using Django 2.2.19. For more information on this file, see https://docs.djangoproject.com/en/2.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.2/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'c+utti0k^6xo3=@hpoehw_%jteq#492km*@k-h6q6qci+()c96' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [ 'localhost', '127.0.0.1', '[::1]', 'testserver', 'www.andrey11995.pythonanywhere.com', 'andrey11995.pythonanywhere.com', ] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'posts.apps.PostsConfig', 'users.apps.UsersConfig', 'core.apps.CoreConfig', 'about.apps.AboutConfig', 'sorl.thumbnail', 'debug_toolbar', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', 'debug_toolbar.middleware.DebugToolbarMiddleware', ] if DEBUG: MIDDLEWARE += [ 'debug_toolbar.middleware.DebugToolbarMiddleware', ] ROOT_URLCONF = 'yatube.urls' TEMPLATES_DIR = os.path.join(BASE_DIR, 'templates') TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [TEMPLATES_DIR], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', 'core.context_processors.year.year' ], }, }, ] STATICFILES_DIRS = [os.path.join(BASE_DIR, 'static')] WSGI_APPLICATION = 'yatube.wsgi.application' # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'ru-ru' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = '/static/' LOGIN_URL = 'users:login' LOGIN_REDIRECT_URL = 'posts:index' # LOGOUT_REDIRECT_URL = 'posts:index' EMAIL_BACKEND = 'django.core.mail.backends.filebased.EmailBackend' EMAIL_FILE_PATH = os.path.join(BASE_DIR, 'sent_emails') CSRF_FAILURE_VIEW = 'core.views.csrf_failure' MEDIA_URL = '/media/' MEDIA_ROOT = os.path.join(BASE_DIR, 'media') CACHES = { 'default': { 'BACKEND': 'django.core.cache.backends.locmem.LocMemCache', } } INTERNAL_IPS = [ '127.0.0.1', ]

25.299401

91

0.692308

import os BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) SECRET_KEY = 'c+utti0k^6xo3=@hpoehw_%jteq#492km*@k-h6q6qci+()c96' DEBUG = True ALLOWED_HOSTS = [ 'localhost', '127.0.0.1', '[::1]', 'testserver', 'www.andrey11995.pythonanywhere.com', 'andrey11995.pythonanywhere.com', ] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'posts.apps.PostsConfig', 'users.apps.UsersConfig', 'core.apps.CoreConfig', 'about.apps.AboutConfig', 'sorl.thumbnail', 'debug_toolbar', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', 'debug_toolbar.middleware.DebugToolbarMiddleware', ] if DEBUG: MIDDLEWARE += [ 'debug_toolbar.middleware.DebugToolbarMiddleware', ] ROOT_URLCONF = 'yatube.urls' TEMPLATES_DIR = os.path.join(BASE_DIR, 'templates') TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [TEMPLATES_DIR], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', 'core.context_processors.year.year' ], }, }, ] STATICFILES_DIRS = [os.path.join(BASE_DIR, 'static')] WSGI_APPLICATION = 'yatube.wsgi.application' # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'ru-ru' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = '/static/' LOGIN_URL = 'users:login' LOGIN_REDIRECT_URL = 'posts:index' # LOGOUT_REDIRECT_URL = 'posts:index' EMAIL_BACKEND = 'django.core.mail.backends.filebased.EmailBackend' EMAIL_FILE_PATH = os.path.join(BASE_DIR, 'sent_emails') CSRF_FAILURE_VIEW = 'core.views.csrf_failure' MEDIA_URL = '/media/' MEDIA_ROOT = os.path.join(BASE_DIR, 'media') CACHES = { 'default': { 'BACKEND': 'django.core.cache.backends.locmem.LocMemCache', } } INTERNAL_IPS = [ '127.0.0.1', ]

true

1c2fee1ff86668a2fd7b4d181ef083791a47ddcd

6,726

py

Python

modulo_ht_validate_transform/ht_validate_transform/src/datasets_collections_files/metadata.py

regulondbunam/3RegulonDB-Santana

7a9076ea3b4a26dc5445f4ac181bc26993d9ec1c

[ "MIT" ]

null

modulo_ht_validate_transform/ht_validate_transform/src/datasets_collections_files/metadata.py

regulondbunam/3RegulonDB-Santana

7a9076ea3b4a26dc5445f4ac181bc26993d9ec1c

[ "MIT" ]

null

modulo_ht_validate_transform/ht_validate_transform/src/datasets_collections_files/metadata.py

regulondbunam/3RegulonDB-Santana

7a9076ea3b4a26dc5445f4ac181bc26993d9ec1c

[ "MIT" ]

null

import pandas as pd import json '''# # name: Metadata.py Version [1.0] Clase que se encargara de recibir un dataframe con datos del metadata y se encargara de manipularlos y poder crear un dataframe con los datos del metadadata estructurados como se requieren. ```python program_name [options list] arguments ``` ## examples ```python put here your code example ``` ## description Manipulacion de datos atraves de dataframes para poder crear el metadata ## arguments No necesita de argumentos para la ejecuion de dicha clase ## requirements Sin requerimientos ## softwareRequirements Se necesita la libreria de python llamadas pandas - Es un paquete de Python que proporciona estructuras de datos similares a los dataframes de R. Pandas depende de Numpy, la librería que añade un potente tipo matricial a Python. json - Es un formato de intercambio de datos ligero inspirado en la sintaxis literal de objetos de JavaScript ## memoryRequirements Se recomienda al menos tener 8gb de ram para que el proceso se ejecute a una velocidad estandar a la hora de correrlo. #''' class Metadata(): DATASET_TITLE = "#DATASET TITLE" PMID = "#PMID:" CORRESPONDING_AUTHOR = "#CORRESPONDING AUTHOR (EMAIL):" STRAIN = "#STRAIN:" REFERENCE_GENOME = "#REFERENCE GENOME:" DATASET_ACCESION_NUMBER = "#DATASET ACCESION NUMBER[DATABASE]:" EXPERIMENTAL_DETAILS = "#EXPERIMENTAL DETAILS" METHOD = "#METHOD:" METHOD_DETAILS = "#METHOD DETAILS:" INSTRUMENT = "#INSTRUMENT:" EVIDENCE = "#EVIDENCE:" STATISTICAL_MODEL = "#STATISTICAL MODEL" VALUE_COLUMN = 'Value' def __init__(self, dataframe): self.dataframe = dataframe self.title = dataframe self.pmid = dataframe self.corresponding_author = dataframe self.strain = dataframe self.reference_genome = dataframe self.dataset_accesion_number = dataframe self.experiment_details = dataframe self.method = dataframe self.method_details = dataframe self.instrument = dataframe self.evidence =dataframe self.statistical_model = dataframe @property def title(self): return self._title @title.setter def title(self, dataframe): try: self._title = dataframe.at[Metadata.DATASET_TITLE, Metadata.VALUE_COLUMN] except KeyError: self._title = None @property def pmid(self): return self._pmid @pmid.setter def pmid(self, dataframe): try: self._pmid = dataframe.at[Metadata.PMID, Metadata.VALUE_COLUMN] except KeyError: self._pmid = None @property def corresponding_author(self): return self._corresponding_author @corresponding_author.setter def corresponding_author(self, dataframe): try: self._corresponding_author = dataframe.at[Metadata.CORRESPONDING_AUTHOR, Metadata.VALUE_COLUMN] except KeyError: self._corresponding_author = None @property def strain(self): return self._strain @strain.setter def strain(self, dataframe): try: self._strain = dataframe.at[Metadata.STRAIN, Metadata.VALUE_COLUMN] except KeyError: self._strain = None @property def reference_genome(self): return self._reference_genome @reference_genome.setter def reference_genome(self, dataframe): try: self._reference_genome = dataframe.at[Metadata.REFERENCE_GENOME, Metadata.VALUE_COLUMN] except KeyError: self._reference_genome = None @property def dataset_accesion_number(self): return self._dataset_accesion_number @dataset_accesion_number.setter def dataset_accesion_number(self, dataframe): try: self._dataset_accesion_number = dataframe.at[Metadata.DATASET_ACCESION_NUMBER, Metadata.VALUE_COLUMN] except KeyError: self._dataset_accesion_number = None @property def experiment_details(self): return self._experiment_details @experiment_details.setter def experiment_details(self, dataframe): try: self._experiment_details = dataframe.at[Metadata.EXPERIMENTAL_DETAILS, Metadata.VALUE_COLUMN] except KeyError: self._experiment_details = None @property def method(self): return self._method @method.setter def method(self, dataframe): try: self._method = dataframe.at[Metadata.METHOD, Metadata.VALUE_COLUMN] except KeyError: self._method = None @property def method_details(self): return self._method_details @method_details.setter def method_details(self, dataframe): try: self._method_details = dataframe.at[Metadata.METHOD_DETAILS, Metadata.VALUE_COLUMN] except KeyError: self._method_details = None @property def instrument(self): return self._instrument @instrument.setter def instrument(self, dataframe): try: self._instrument = dataframe.at[Metadata.INSTRUMENT, Metadata.VALUE_COLUMN] except KeyError: self._instrument = None @property def evidence(self): return self._evidence @evidence.setter def evidence(self, dataframe): try: self._evidence = dataframe.at[Metadata.EVIDENCE, Metadata.VALUE_COLUMN] except KeyError: self._evidence = None @property def statistical_model(self): return self._statistical_model @statistical_model.setter def statistical_model(self, dataframe): try: self._statistical_model = dataframe.at[Metadata.STATISTICAL_MODEL, Metadata.VALUE_COLUMN] except KeyError: self._statistical_model = None def __call__(self): metadata_frame = { 'title': self.title, 'pmid': self.pmid, 'author': self.corresponding_author, 'strain': self.strain, 'reference genome': self.reference_genome, 'dataset accesion number': self.dataset_accesion_number, 'experiment details': self.experiment_details, 'method': self.method, 'method details': self.method_details, 'instrument': self.instrument, 'evidence': self.evidence, 'statistical model': self.statistical_model } return metadata_frame '''# dateCreated: [2020-12-22] - author: [Santana Estrada Hernandez] dateModified [2021-01-07] - contributor: [Se realizo una optimizacion de codigo] #'''

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import pandas as pd import json class Metadata(): DATASET_TITLE = "#DATASET TITLE" PMID = "#PMID:" CORRESPONDING_AUTHOR = "#CORRESPONDING AUTHOR (EMAIL):" STRAIN = "#STRAIN:" REFERENCE_GENOME = "#REFERENCE GENOME:" DATASET_ACCESION_NUMBER = "#DATASET ACCESION NUMBER[DATABASE]:" EXPERIMENTAL_DETAILS = "#EXPERIMENTAL DETAILS" METHOD = "#METHOD:" METHOD_DETAILS = "#METHOD DETAILS:" INSTRUMENT = "#INSTRUMENT:" EVIDENCE = "#EVIDENCE:" STATISTICAL_MODEL = "#STATISTICAL MODEL" VALUE_COLUMN = 'Value' def __init__(self, dataframe): self.dataframe = dataframe self.title = dataframe self.pmid = dataframe self.corresponding_author = dataframe self.strain = dataframe self.reference_genome = dataframe self.dataset_accesion_number = dataframe self.experiment_details = dataframe self.method = dataframe self.method_details = dataframe self.instrument = dataframe self.evidence =dataframe self.statistical_model = dataframe @property def title(self): return self._title @title.setter def title(self, dataframe): try: self._title = dataframe.at[Metadata.DATASET_TITLE, Metadata.VALUE_COLUMN] except KeyError: self._title = None @property def pmid(self): return self._pmid @pmid.setter def pmid(self, dataframe): try: self._pmid = dataframe.at[Metadata.PMID, Metadata.VALUE_COLUMN] except KeyError: self._pmid = None @property def corresponding_author(self): return self._corresponding_author @corresponding_author.setter def corresponding_author(self, dataframe): try: self._corresponding_author = dataframe.at[Metadata.CORRESPONDING_AUTHOR, Metadata.VALUE_COLUMN] except KeyError: self._corresponding_author = None @property def strain(self): return self._strain @strain.setter def strain(self, dataframe): try: self._strain = dataframe.at[Metadata.STRAIN, Metadata.VALUE_COLUMN] except KeyError: self._strain = None @property def reference_genome(self): return self._reference_genome @reference_genome.setter def reference_genome(self, dataframe): try: self._reference_genome = dataframe.at[Metadata.REFERENCE_GENOME, Metadata.VALUE_COLUMN] except KeyError: self._reference_genome = None @property def dataset_accesion_number(self): return self._dataset_accesion_number @dataset_accesion_number.setter def dataset_accesion_number(self, dataframe): try: self._dataset_accesion_number = dataframe.at[Metadata.DATASET_ACCESION_NUMBER, Metadata.VALUE_COLUMN] except KeyError: self._dataset_accesion_number = None @property def experiment_details(self): return self._experiment_details @experiment_details.setter def experiment_details(self, dataframe): try: self._experiment_details = dataframe.at[Metadata.EXPERIMENTAL_DETAILS, Metadata.VALUE_COLUMN] except KeyError: self._experiment_details = None @property def method(self): return self._method @method.setter def method(self, dataframe): try: self._method = dataframe.at[Metadata.METHOD, Metadata.VALUE_COLUMN] except KeyError: self._method = None @property def method_details(self): return self._method_details @method_details.setter def method_details(self, dataframe): try: self._method_details = dataframe.at[Metadata.METHOD_DETAILS, Metadata.VALUE_COLUMN] except KeyError: self._method_details = None @property def instrument(self): return self._instrument @instrument.setter def instrument(self, dataframe): try: self._instrument = dataframe.at[Metadata.INSTRUMENT, Metadata.VALUE_COLUMN] except KeyError: self._instrument = None @property def evidence(self): return self._evidence @evidence.setter def evidence(self, dataframe): try: self._evidence = dataframe.at[Metadata.EVIDENCE, Metadata.VALUE_COLUMN] except KeyError: self._evidence = None @property def statistical_model(self): return self._statistical_model @statistical_model.setter def statistical_model(self, dataframe): try: self._statistical_model = dataframe.at[Metadata.STATISTICAL_MODEL, Metadata.VALUE_COLUMN] except KeyError: self._statistical_model = None def __call__(self): metadata_frame = { 'title': self.title, 'pmid': self.pmid, 'author': self.corresponding_author, 'strain': self.strain, 'reference genome': self.reference_genome, 'dataset accesion number': self.dataset_accesion_number, 'experiment details': self.experiment_details, 'method': self.method, 'method details': self.method_details, 'instrument': self.instrument, 'evidence': self.evidence, 'statistical model': self.statistical_model } return metadata_frame

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