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import json from json import JSONDecodeError import pandas as pd from requests import post import yaml # General class for necessary file imports class FileImport(): def read_app_key_file(self, filename: str = "keys.json") -> tuple: """Reads file with consumer key and consumer secret (JSON) Args: filename (str, optional): Defaults to "keys.json" Returns: Tuple with two strings: (1) being the twitter consumer token and (2) being the twitter consumer secret """ # TODO: change return to dictionary try: with open(filename, "r") as f: self.key_file = json.load(f) except FileNotFoundError: raise FileNotFoundError('"keys.json" could not be found') except JSONDecodeError as e: print("Bad JSON file. Please check that 'keys.json' is formatted\ correctly and that it is not empty") raise e if "consumer_token" not in self.key_file or "consumer_secret" not in self.key_file: raise KeyError('''"keys.json" does not contain the dictionary keys "consumer_token" and/or "consumer_secret"''') if type(self.key_file["consumer_secret"]) is not str or type( self.key_file["consumer_token"]) is not str: raise TypeError("Consumer secret is type" + str(type(self.key_file["consumer_secret"])) + "and consumer token is type " + str(type( self.key_file["consumer_token"])) + '''. Both must be of type str. ''') return (self.key_file["consumer_token"], self.key_file["consumer_secret"]) def read_seed_file(self, filename: str = "seeds.csv") -> pd.DataFrame: """Reads file with specified seeds to start from (csv) Args: filename (str, optional): Defaults to "seeds.csv" Returns: A single column pandas DataFrame with one Twitter ID (seed) each row. """ try: with open("seeds.csv", "r") as f: self.seeds = pd.read_csv(f, header=None) except FileNotFoundError: raise FileNotFoundError('"seeds.csv" could not be found') except pd.errors.EmptyDataError as e: print('"seeds.csv" is empty!') raise e return self.seeds def read_token_file(self, filename="tokens.csv"): """Reads file with authorized user tokens (csv). Args: filename (str, optional): Defaults to "tokens.csv" Returns: pandas.DataFrame: With columns `token` and `secret`, one line per user """ return pd.read_csv(filename) # Configuration class. Reads out all information from a given config.yml class Config(): """Class that handles the SQL and twitter user details configuration. Attributes: config_file (str): Path to configuration file config_dict (dict): Dictionary containing the config information (in case the dictionary shall be directly passed instead of read out of a configuration file). """ config_template = "config_template.py" # Initializes class using config.yml def __init__(self, config_file="config.yml", config_dict: dict = None): if config_dict is not None: self.config = config_dict else: self.config_path = config_file try: with open(self.config_path, 'r') as f: self.config = yaml.load(f) except FileNotFoundError: raise FileNotFoundError('Could not find "' + self.config_path + '''".\n Please run "python3 make_config.py" or provide a config.yml''') # Check if mailgun notifications should be used if "notifications" not in self.config: self.use_notifications = False else: self.notif_config = self.config["notifications"] notif_config_items = [value for (key, value) in self.notif_config.items()] single_items = list(set(notif_config_items)) if len(single_items) == 1 and single_items[0] is None: self.use_notifications = False elif None in single_items: missing = [key for (key, value) in self.notif_config.items() if value is None] raise ValueError(f"""You have not filled all required fields for the notifications configuration! Fields missing are {missing}""") else: self.use_notifications = True # Check for necessary database information. If no information is provided, # stop if "sql" not in self.config: print("Config file " + config_file + """ does not contain key 'sql'! Will use default sqlite configuration.""") self.config["sql"] = dict(dbtype="sqlite", dbname="new_database") self.sql_config = self.config["sql"] # No db type given in Config if self.sql_config["dbtype"] is None: print('''Parameter dbtype not set in the "config.yml". Will create an sqlite database.''') self.dbtype = "sqlite" else: self.dbtype = self.sql_config["dbtype"].strip() # DB type is msql - checking for all parameters if self.dbtype == "mysql": try: self.dbhost = str(self.sql_config["host"]) self.dbuser = str(self.sql_config["user"]) self.dbpwd = str(self.sql_config["passwd"]) if self.dbhost == '': raise ValueError("dbhost parameter is empty") if self.dbuser == '': raise ValueError("dbuser parameter is empty") if self.dbpwd == '': raise ValueError("passwd parameter is empty") except KeyError as e: raise e elif self.dbtype == "sqlite": self.dbhost = None self.dbuser = None self.dbpwd = None else: raise ValueError('''dbtype parameter is neither "sqlite" nor "mysql". Please adjust the "config.yml" ''') # Set db name if self.sql_config["dbname"] is not None: self.dbname = self.sql_config["dbname"] else: print('''Parameter "dbname" is missing. New database will have the name "new_database".''') self.dbname = "new_database" # Function to send mail if notifications are turned on in config.yml # TODO: finalize this function def send_mail(self, message_dict): '''Sends an email via Mailgun. Args: message_dict (dict): { "subject": "your_subject" "text": "message" } config (dict): { "mailgun_api_base_url": "link to mailgun_api_base_url" "mailgun_api_key": "your mailgun_api_key" "mailgun_default_smtp_login": "your mailgun_default_smtp_login" "email_to_notify": "the email_to_notify" } Returns: requests.post to Mailgun API. ''' api_base_url = self.notif_config["mailgun_api_base_url"] + '/messages' auth = ('api', self.notif_config["mailgun_api_key"]) data = { "from": f"SparseTwitter <{self.notif_config['mailgun_default_smtp_login']}>", "to": self.notif_config["email_to_notify"] } data.update(message_dict) return post(api_base_url, auth=auth, data=data) # TODO: Add mailgun config
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from .models import print_image_classifiers, image_classifier from .models import print_image_regression_models, image_regression_model from .data import show_image, show_random_images, preview_data_aug, get_data_aug from .data import images_from_folder, images_from_csv, images_from_array, images_from_fname, preprocess_csv from .predictor import ImagePredictor __all__ = [ 'image_classifier', 'image_regression_model', 'print_image_classifiers', 'print_image_regression_models', 'images_from_folder', 'images_from_csv', 'images_from_array', 'images_from_fname', 'get_data_aug', 'preprocess_csv', 'ImagePredictor', 'show_image', 'show_random_images', 'preview_data_aug' ]
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from .all_pass import all_pass def positive(x): return x > 0 def less_than_ten(x): return x < 10 def all_pass_nocurry_test(): assert all_pass([], "foo") assert all_pass([positive, less_than_ten], 5) assert not all_pass([positive, less_than_ten], 10) assert not all_pass([positive, less_than_ten], 0) def all_pass_curry_test(): between_zero_and_ten = all_pass([positive, less_than_ten]) assert between_zero_and_ten(5) assert not between_zero_and_ten(10) assert not between_zero_and_ten(0)
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from copy import deepcopy from typing import Any, Optional, Union import pandas as pd from pycaret.internal.logging import get_logger from pycaret.internal.Display import Display from sklearn.base import clone from sklearn.utils.validation import check_is_fitted from sklearn.pipeline import Pipeline def is_sklearn_pipeline(object): from sklearn.pipeline import Pipeline return isinstance(object, Pipeline) def is_sklearn_cv_generator(object): return not isinstance(object, str) and hasattr(object, "split") def is_fitted(estimator) -> bool: try: check_is_fitted(estimator) return True except: return False class fit_if_not_fitted(object): """ Context which fits an estimator if it's not fitted. """ def __init__( self, estimator, X_train: pd.DataFrame, y_train: pd.DataFrame, groups=None, **fit_kwargs, ): logger = get_logger() self.estimator = deepcopy(estimator) if not is_fitted(self.estimator): try: self.estimator._carry_over_final_estimator_fit_vars() except: pass if not is_fitted(self.estimator): logger.info(f"fit_if_not_fitted: {estimator} is not fitted, fitting") try: self.estimator.fit(X_train, y_train, groups=groups, **fit_kwargs) except: self.estimator.fit(X_train, y_train, **fit_kwargs) def __enter__(self): return self.estimator def __exit__(self, type, value, traceback): return def supports_partial_fit(estimator, params: dict = None) -> bool: # special case for MLP from sklearn.neural_network import MLPClassifier if isinstance(estimator, MLPClassifier): try: if ( params and "solver" in params and "lbfgs" in list(params["solver"]) ) or estimator.solver == "lbfgs": return False except: return False if isinstance(estimator, Pipeline): return hasattr(estimator.steps[-1][1], "partial_fit") return hasattr(estimator, "partial_fit")
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from requests import Session from bs4 import BeautifulSoup import re class tiktok: def __init__(self) -> None: self.request = Session() self.url = "https://ssstik.io" self.html = self.request.get(self.url).text self.key = BeautifulSoup(self.html, "html.parser").find_all("form",attrs={"data-hx-target":"#target"})[0].get("include-vals") self.post = BeautifulSoup(self.html, "html.parser").find_all("form",attrs={"data-hx-target":"#target"})[0].get("data-hx-post") self.tt = re.search("tt\:\'(.*?)\'",self.key)[1] self.ts = re.search("ts\:([0-9]{5,15})",self.key)[1] self.header = {"content-type": "application/x-www-form-urlencoded; charset=UTF-8","hx-active-element": "submit","hx-current-url": "https://ssstik.io/","hx-request": "true","hx-target": "target","origin": "https://ssstik.io","sec-fetch-dest": "","sec-fetch-mode": "cors","sec-fetch-site": "same-origin","user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36"} def download(self, url) -> dict: data = {"id": url,"locale": "en","tt": self.tt,"ts": int(self.ts)} post = self.request.post(f"{self.url}{self.post}", headers=self.header, data=data) respon = BeautifulSoup(post.text, "html.parser") hasil = {"video":[f'{self.url}{respon.find_all("a",class_="pure-button pure-button-primary is-center u-bl dl-button download_link without_watermark")[0].get("href")}',f'{self.url}{respon.find_all("a",class_="pure-button pure-button-primary is-center u-bl dl-button download_link without_watermark_direct")[0].get("href")}'],"music":f'{respon.find_all("a",class_="pure-button pure-button-primary is-center u-bl dl-button download_link music")[0].get("href")}'} return hasil class tiktok2: def __init__(self, url) -> None: self.request = Session() self.url =url self.header = {"accept": "*/*","accept-language": "en-US,en;q=0.9,id;q=0.8","origin": "https://snaptik.app","referer": "https://snaptik.app/ID","sec-fetch-dest": None,"sec-fetch-mode": "cors","sec-fetch-site": "same-origin","user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36",} def download(self): self.request.post("https://snaptik.app/check_token.php", headers=self.header) self.bs = BeautifulSoup(self.request.post("https://snaptik.app/action-2021.php", headers=self.header, data={"url":self.url}).text, "html.parser") return [self.request,{"title":self.bs('a', attrs={"title":""})[0].text,"date":self.bs("b", attrs={"class":"blur"})[0].text,"url":list(filter(lambda x:x, map(lambda x:x["href"] if "token" in x["href"] else None, self.bs("a", attrs={"class":"abutton is-success is-fullwidth"}))))}, self.header]
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def less_or_equal(value): if value : # Change this line return "25 or less" elif value : # Change this line return "75 or less" else: return "More than 75" # Change the value 1 below to experiment with different values print(less_or_equal(1))
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import os import json import argus from argus.callbacks import MonitorCheckpoint, EarlyStopping, LoggingToFile from torch.utils.data import DataLoader from src.dataset import SaltDataset, SaltTestDataset from src.transforms import SimpleDepthTransform, SaltTransform from src.lr_scheduler import ReduceLROnPlateau from src.argus_models import SaltMeanTeacherModel from src import config from src.nick_zoo.resnet_blocks import resnet152 EXPERIMENT_NAME = 'flex-fpn-mt-resnet152-001' TRAIN_BATCH_SIZE = 10 VAL_BATCH_SIZE = 10 UNLABELED_BATCH = 6 IMAGE_SIZE = (128, 128) OUTPUT_SIZE = (101, 101) TRAIN_FOLDS_PATH = '/workdir/data/train_folds_148.csv' TEST_DIR = '/workdir/data/test/images148' SAVE_DIR = f'/workdir/data/experiments/{EXPERIMENT_NAME}' FOLDS = list(range(config.N_FOLDS)) PARAMS = { 'nn_module': ('UNetFPNFlexProb', { 'num_classes': 1, 'num_channels': 3, 'blocks': resnet152, 'final': 'sigmoid', 'dropout_2d': 0.2, 'is_deconv': True, 'deflation': 4, 'use_first_pool': False, 'skip_dropout': True, 'pretrain': 'resnet152', 'pretrain_layers': [True for _ in range(5)], 'fpn_layers': [16, 32, 64, 128] }), 'loss': ('FbBceProbLoss', { 'fb_weight': 0.95, 'fb_beta': 2, 'bce_weight': 0.9, 'prob_weight': 0.85 }), 'prediction_transform': ('ProbOutputTransform', { 'segm_thresh': 0.5, 'prob_thresh': 0.5, }), 'mean_teacher': { 'alpha': 0.99, 'rampup_length': 10, 'unlabeled_batch': UNLABELED_BATCH, 'consistency_segm_weight': 0.3, 'consistency_prob_weight': 0.3 }, 'optimizer': ('Adam', {'lr': 0.0001}), 'device': 'cuda' } @argus.callbacks.on_epoch_start def update_model_epoch(state: argus.engine.State): state.model.epoch = state.epoch def train_fold(save_dir, train_folds, val_folds): depth_trns = SimpleDepthTransform() train_trns = SaltTransform(IMAGE_SIZE, True, 'crop') val_trns = SaltTransform(IMAGE_SIZE, False, 'crop') train_dataset = SaltDataset(TRAIN_FOLDS_PATH, train_folds, train_trns, depth_trns) val_dataset = SaltDataset(TRAIN_FOLDS_PATH, val_folds, val_trns, depth_trns) train_loader = DataLoader(train_dataset, batch_size=TRAIN_BATCH_SIZE, shuffle=True, drop_last=True, num_workers=4) val_loader = DataLoader(val_dataset, batch_size=VAL_BATCH_SIZE, shuffle=False, num_workers=4) test_dataset = SaltTestDataset(test_dir=TEST_DIR, transform=val_trns, depth_transform=depth_trns) model = SaltMeanTeacherModel(PARAMS) model.test_dataset = test_dataset callbacks = [ MonitorCheckpoint(save_dir, monitor='val_crop_iout', max_saves=3, copy_last=False), EarlyStopping(monitor='val_crop_iout', patience=100), ReduceLROnPlateau(monitor='val_crop_iout', patience=25, factor=0.72, min_lr=1e-8), LoggingToFile(os.path.join(save_dir, 'log.txt')), update_model_epoch ] model.fit(train_loader, val_loader=val_loader, max_epochs=700, callbacks=callbacks, metrics=['crop_iout']) if __name__ == "__main__": if not os.path.exists(SAVE_DIR): os.makedirs(SAVE_DIR) else: print(f"Folder {SAVE_DIR} already exists.") with open(os.path.join(SAVE_DIR, 'source.py'), 'w') as outfile: outfile.write(open(__file__).read()) with open(os.path.join(SAVE_DIR, 'params.json'), 'w') as outfile: json.dump(PARAMS, outfile) for i in range(len(FOLDS)): val_folds = [FOLDS[i]] train_folds = FOLDS[:i] + FOLDS[i + 1:] save_fold_dir = os.path.join(SAVE_DIR, f'fold_{FOLDS[i]}') print(f"Val folds: {val_folds}, Train folds: {train_folds}") print(f"Fold save dir {save_fold_dir}") train_fold(save_fold_dir, train_folds, val_folds)
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from measurement.measures import Energy class TestEnergy: def test_dietary_calories_kwarg(self): calories = Energy(Calorie=2000) kilojoules = Energy(kJ=8368) assert calories.si_value == kilojoules.si_value
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from typing import Tuple import numpy as np from PyGenetic.crossover import CrossoverDecidor from PyGenetic.mutation import MutationDecidor class FactoryPopulation(): def __init__(self): self.crossover_decidor = CrossoverDecidor(self.crossover_type, self.n_genes) self.mutation_decidor = MutationDecidor(self.mutation_type, self.n_genes, self.mutation_propability, self.low_boundery, self.high_boundery) def crossover(self, first_chromo: np.array, second_chromo: np.array) -> Tuple[np.array, np.array]: first_child, second_child = self.crossover_decidor.run( first_chromo, second_chromo) return (first_child, second_child) def mutation(self, chromosome: np.array) -> np.array: self.mutation_decidor.run(chromosome) def parent_selection(self, fitness: np.array) -> None: fit_idx = np.argsort(fitness)[::-1] self.parents = self.pool[fit_idx[:self.n_parents]] def breed_childern(self) -> None: for i in range(self.n_pool // 2): first_chromo = self.parents[np.random.choice(range( self.n_parents))] second_chromo = self.parents[np.random.choice(range( self.n_parents))] first_child, second_child = self.crossover(first_chromo, second_chromo) self.mutation(first_child) self.mutation(second_child) self.pool[i:i + 2] = [first_child, second_child] self.pool[-1] = self.parents[0]
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from django.conf.urls import url from drf_yasg.views import get_schema_view from drf_yasg import openapi schema_view = get_schema_view( openapi.Info( title="West Oakland Air Quality API", default_version="v1", description=( "West Oakland Air Quality (WOAQ) is a project of OpenOakland " "focused on building digital advocacy tools around air quality data " "collected by volunteers and citizen scientists. WOAQ works in partnership " "with West Oakland Environmental Indicators Project (WOEIP). This API is " "for storing and updating WOEIP air quality datasets." ), terms_of_service=None, # Optional URL to terms of service contact=openapi.Contact(email="<EMAIL>"), license=openapi.License( name="MIT", url="https://github.com/openoakland/woeip/blob/master/LICENSE" ), ), public=False, ) urlpatterns = [ url( r"^swagger(?P<format>\.json|\.yaml)$", schema_view.without_ui(cache_timeout=0), name="schema-json", ), url( r"^swagger/$", schema_view.with_ui("swagger", cache_timeout=0), name="schema-swagger-ui", ), url( r"^redoc/$", schema_view.with_ui("redoc", cache_timeout=0), name="schema-redoc", ), ]
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import os import datetime import torch def run(parser, dev): args = parser.parse_args() ## Set gpu ids str_ids = args.gpu_ids.split(',') args.gpu_ids = [] for str_id in str_ids: gpu_id = int(str_id) if gpu_id >= 0: args.gpu_ids.append(gpu_id) if len(args.gpu_ids) > 0: torch.cuda.set_device(args.gpu_ids[0]) ## Set device args.device = torch.device('cuda:{}'.format(args.gpu_ids[0])) if args.gpu_ids else torch.device('cpu') if args.isTrain: ## Set decay steps str_steps = args.decay_steps.split(',') args.decay_steps = [] for str_step in str_steps: str_step = int(str_step) args.decay_steps.append(str_step) ## Set names current_time = datetime.datetime.now().strftime("%Y%m%d-%H%M%S") args.name = '{}_{}_{}_{}_{}'.format(args.name, current_time, args.dataset, args.backbone, args.loss_type) ## Print Options message = '' message += '----------------- Options ---------------\n' for k, v in sorted(vars(args).items()): comment = '' default = parser.get_default(k) if v != default: comment = '\t[default: %s]' % str(default) message += '{:>25}: {:<30}{}\n'.format(str(k), str(v), comment) message += '----------------- End -------------------' print(message) if args.isTrain and not dev: ## Save Options expr_dir = os.path.join(args.checkpoints_dir, args.name) os.makedirs(expr_dir) file_name = os.path.join(expr_dir, 'arguments.txt') with open(file_name, 'wt') as opt_file: opt_file.write(message) opt_file.write('\n') return args
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from contextlib import closing import psycopg class PostgreSQLConnectionChecker: def __init__(self, **kwargs): self.host = kwargs.get('host') self.port = kwargs.get('port') self.user = kwargs.get('user') self.password = kwargs.get('password') self.database = kwargs.get('database', 'postgres') def _get_connection(self): conn = psycopg.connect(f'host={self.host} port={self.port} dbname={self.database} user={self.user} password={self.password}', connect_timeout=10) return conn def check_connection(self): try: con = self._get_connection() with closing(con) as con: cur = con.cursor() cur.execute('select 1;') connected = True except Exception as e: print('EXCEPTION!') print(e) connected = False return connected
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import tensorflow as tf import datetime import numpy as np import zutils.tf_math_funcs as tmf from zutils.py_utils import * from scipy.io import savemat class OneEpochRunner: def __init__( self, data_module, output_list=None, net_func=None, batch_axis=0, num_samples=None, disp_time_interval=2, output_fn=None, is_large=False): self.data_module = data_module self.num_samples = self.data_module.num_samples() self.batch_axis = batch_axis self.disp_time_interval = disp_time_interval self.output_fn = output_fn self.is_large = is_large if num_samples is not None: if self.num_samples < num_samples: print("specified number_samples is larger than one epoch") else: self.num_samples = num_samples self.use_net_func = output_list is None # otherwise use net_func if self.use_net_func: assert net_func is not None, \ "output_list and net_func should not be both specified" self.net_func = net_func # remark: net_func(sess) else: assert net_func is None, \ "one of output_list and net_func must be specified" self.output_list = output_list [self.flatten_output_list, self.output_wrap_func] = \ recursive_flatten_with_wrap_func( lambda x: tmf.is_tf_data(x), self.output_list) self.data_module.reset() self.cur_sample_end = 0 def run_single_batch(self, sess): if self.cur_sample_end >= self.num_samples: return None if self.use_net_func: output_val = self.net_func(sess) else: output_val = sess.run(self.flatten_output_list, {}) output_val = self.output_wrap_func(output_val) batch_size = first_element_apply( lambda x: isinstance(x, np.ndarray), lambda x: x.shape[self.batch_axis], output_val) self.batch_size = batch_size new_end = self.cur_sample_end + batch_size if new_end > self.num_samples: effective_batch_size = \ batch_size - (new_end-self.num_samples) slice_indexes = (slice(None),)*self.batch_axis + (slice(effective_batch_size),) output_val = recursive_apply( lambda x: isinstance(x, np.ndarray), lambda x: x[slice_indexes], output_val) self.cur_sample_end = new_end return output_val def run(self, sess): disp_countdown = IfTimeout(self.disp_time_interval) num_samples_total = self.num_samples output_val_single = self.run_single_batch(sess) output_val = [] while output_val_single is not None: output_val += [output_val_single] iter = self.data_module.iter() if self.data_module.epoch() == 0: num_samples_finished = self.data_module.num_samples_finished() else: num_samples_finished = self.num_samples if disp_countdown.is_timeout(): epoch_percentage = num_samples_finished / num_samples_total * 100 print("%s] Iter %d (%4.1f%% = %d / %d)" % (datetime.datetime.now().strftime('%Y-%m/%d-%H:%M:%S.%f'), iter, epoch_percentage, num_samples_finished, num_samples_total)) disp_countdown = IfTimeout(self.disp_time_interval) if self.is_large and (num_samples_finished % (100*self.batch_size) == 0 or num_samples_finished == self.num_samples): output_val = recursive_apply( lambda *args: isinstance(args[0], np.ndarray), lambda *args: np.concatenate(args, axis=self.batch_axis), *output_val) self.dir_path = os.path.dirname(self.output_fn+'_'+'%06d'%num_samples_finished) if not os.path.exists(self.dir_path): os.makedirs(self.dir_path) savemat(self.output_fn+'_'+'%06d'%num_samples_finished+'.mat',output_val) print('Saving part of output to '+ self.output_fn+'_'+'%06d'%num_samples_finished+'.mat') output_val = [] output_val_single = self.run_single_batch(sess) if not self.is_large: output_val = recursive_apply( lambda *args: isinstance(args[0], np.ndarray), lambda *args: np.concatenate(args, axis=self.batch_axis), *output_val) savemat(self.output_fn + ".mat", output_val) print('Saving output to ' + self.output_fn + ".mat")
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from simple_zpl2 import ZPLDocument def add_to_zdoc(upc): zdoc = ZPLDocument() zdoc.add_barcode(upc) return zdoc
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import unittest, sys, os, io, copy import numpy as np import cctk if __name__ == '__main__': unittest.main() class TestOrca(unittest.TestCase): def test_write(self): read_path = "test/static/test_peptide.xyz" path = "test/static/test_peptide.inp" new_path = "test/static/test_peptide_copy.inp" file = cctk.XYZFile.read_file(read_path) self.assertTrue(isinstance(file.get_molecule(), cctk.Molecule)) header = "! aug-cc-pVTZ aug-cc-pVTZ/C DLPNO-CCSD(T) TightSCF TightPNO MiniPrint" variables = {"maxcore": 4000} blocks = {"pal": ["nproc 4"], "mdci": ["density none"]} cctk.OrcaFile.write_molecule_to_file(new_path, file.get_molecule(), header, variables, blocks) with open(path) as old: with open(new_path) as new: self.assertListEqual( list(new), list(old) ) os.remove(new_path) ensemble = cctk.ConformationalEnsemble() ensemble.add_molecule(file.get_molecule()) orca_file = cctk.OrcaFile(job_types=[cctk.OrcaJobType.SP], ensemble=ensemble, header=header, blocks=blocks, variables=variables) orca_file.write_file(new_path) with open(path) as old: with open(new_path) as new: self.assertListEqual( list(new), list(old) ) os.remove(new_path) def test_read(self): path = "test/static/MsOH_ccsdt.out" file = cctk.OrcaFile.read_file(path) self.assertEqual(file.successful_terminations, 1) self.assertEqual(file.elapsed_time, 8575) self.assertEqual(file.header, "! aug-cc-pVQZ aug-cc-pVQZ/C DLPNO-CCSD(T) TightSCF TightPNO MiniPrint") self.assertEqual(file.variables["maxcore"], "50000") self.assertListEqual(file.blocks["mdci"], ["density none"]) mol = file.get_molecule() self.assertTrue(isinstance(mol, cctk.Molecule)) self.assertEqual(mol.num_atoms(), 9) self.assertEqual(file.ensemble[mol,"energy"], -663.663569902734) path = "test/static/AcOH_orca.out" file = cctk.OrcaFile.read_file(path) mol = file.get_molecule() self.assertTrue(isinstance(mol, cctk.Molecule)) self.assertEqual(mol.num_atoms(), 8) self.assertEqual(file.ensemble[mol,"energy"], -229.12132242363) self.assertEqual(file.ensemble[mol, "dipole_moment"], 1.76241) self.assertEqual(file.ensemble[mol, "mulliken_charges"][1], 0.333851) self.assertEqual(file.ensemble[mol, "lowdin_charges"][1], -0.515118) self.assertEqual(file.ensemble[mol, "temperature"], 298.15) self.assertEqual(file.ensemble[mol, "enthalpy"], -229.05330337) self.assertEqual(file.ensemble[mol, "gibbs_free_energy"], -229.08534132) def test_nmr(self): path = "test/static/ibuprofen_nmr_orca.out" file = cctk.OrcaFile.read_file(path) molecule = file.get_molecule() properties_dict = file.ensemble.get_properties_dict(molecule) energy = properties_dict["energy"] self.assertTrue(abs(energy + 656.306067336866) < 1e8) self.assertTrue(abs(file.ensemble[-1, "energy"] + 656.306067336866) < 1e8) shieldings = properties_dict["isotropic_shielding"] self.assertListEqual(list(shieldings[:6]), [55.307, 68.003, 63.738, 51.446, 65.325])
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import numpy as np def sigmoid(x): indp = np.where(x>=0) indn = np.where(x<0) tx = np.zeros(x.shape) tx[indp] = 1./(1.+np.exp(-x[indp])) tx[indn] = np.exp(x[indn])/(1.+np.exp(x[indn])) return tx def sigmoid_prime(x): return sigmoid(x) * (1 - sigmoid(x)) def KL_divergence(x, y): return x * (np.log(x+1E-20)-np.log(y+1E-20)) + (1 - x) * (np.log(1 - x+1E-20) - np.log(1 - y+1E-20)) def initialize(hidden_size, visible_size): r = np.sqrt(6) / np.sqrt(hidden_size + visible_size + 1) W1 = np.random.random((hidden_size, visible_size)) * 2 * r - r W2 = np.random.random((visible_size, hidden_size)) * 2 * r - r b1 = np.zeros(hidden_size, dtype=np.float64) b2 = np.zeros(visible_size, dtype=np.float64) theta = np.concatenate((W1.reshape(hidden_size * visible_size), W2.reshape(hidden_size * visible_size), b1.reshape(hidden_size), b2.reshape(visible_size))) return theta def sparse_autoencoder_cost(theta, visible_size, hidden_size, lambda_, sparsity_param, beta, data): W1 = theta[0:hidden_size * visible_size].reshape(hidden_size, visible_size) W2 = theta[hidden_size * visible_size:2 * hidden_size * visible_size].reshape(visible_size, hidden_size) b1 = theta[2 * hidden_size * visible_size:2 * hidden_size * visible_size + hidden_size] b2 = theta[2 * hidden_size * visible_size + hidden_size:] m = data.shape[1] z2 = W1.dot(data) + np.tile(b1, (m, 1)).transpose() a2 = sigmoid(z2) z3 = W2.dot(a2) + np.tile(b2, (m, 1)).transpose() h = sigmoid(z3) cost = np.sum((h - data) ** 2) / (2 * m) + \ (lambda_ / 2) * (np.sum(W1 ** 2) + np.sum(W2 ** 2))# + \ sparsity_delta = 0 delta3 = -(data - h) * sigmoid_prime(z3) delta2 = (W2.transpose().dot(delta3) + beta * sparsity_delta) * sigmoid_prime(z2) W1grad = delta2.dot(data.transpose()) / m + lambda_ * W1 W2grad = delta3.dot(a2.transpose()) / m + lambda_ * W2 b1grad = np.sum(delta2, axis=1) / m b2grad = np.sum(delta3, axis=1) / m grad = np.concatenate((W1grad.reshape(hidden_size * visible_size), W2grad.reshape(hidden_size * visible_size), b1grad.reshape(hidden_size), b2grad.reshape(visible_size))) return cost, grad def sparse_autoencoder(theta, hidden_size, visible_size, data): W1 = theta[0:hidden_size * visible_size].reshape(hidden_size, visible_size) b1 = theta[2 * hidden_size * visible_size:2 * hidden_size * visible_size + hidden_size] m = data.shape[1] z2 = W1.dot(data) + np.tile(b1, (m, 1)).transpose() a2 = sigmoid(z2) return a2 def sparse_autoencoder_linear_cost(theta, visible_size, hidden_size, lambda_, sparsity_param, beta, data): W1 = theta[0:hidden_size * visible_size].reshape(hidden_size, visible_size) W2 = theta[hidden_size * visible_size:2 * hidden_size * visible_size].reshape(visible_size, hidden_size) b1 = theta[2 * hidden_size * visible_size:2 * hidden_size * visible_size + hidden_size] b2 = theta[2 * hidden_size * visible_size + hidden_size:] m = data.shape[1] z2 = W1.dot(data) + np.tile(b1, (m, 1)).transpose() a2 = sigmoid(z2) z3 = W2.dot(a2) + np.tile(b2, (m, 1)).transpose() h = z3 cost = np.sum((h - data) ** 2) / (2 * m) + \ (lambda_ / 2) * (np.sum(W1 ** 2) + np.sum(W2 ** 2)) sparsity_delta = 0. delta3 = -(data - h) delta2 = (W2.transpose().dot(delta3) + beta * sparsity_delta) * sigmoid_prime(z2) W1grad = delta2.dot(data.transpose()) / m + lambda_ * W1 W2grad = delta3.dot(a2.transpose()) / m + lambda_ * W2 b1grad = np.sum(delta2, axis=1) / m b2grad = np.sum(delta3, axis=1) / m grad = np.concatenate((W1grad.reshape(hidden_size * visible_size), W2grad.reshape(hidden_size * visible_size), b1grad.reshape(hidden_size), b2grad.reshape(visible_size))) return cost, grad
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import json import traceback import uuid import datetime from isodate import duration_isoformat from motorway.utils import DateTimeAwareJsonEncoder import logging class Message(object): """ :param ramp_unique_id: the unique message ID delivered back upon completion to the ramp :param content: any json serializable content :param grouping_value: String that can be used for routing messages consistently to the same receiver :return: """ FAIL = -1 SUCCESS = 0 def __init__(self, ramp_unique_id, content=None, ack_value=None, controller_queue=None, grouping_value=None, error_message=None, process_name=None, producer_uuid=None, destination_endpoint=None, destination_uuid=None): self.ramp_unique_id = ramp_unique_id self.content = content if not ack_value: ack_value = uuid.uuid4().int self.ack_value = ack_value self.controller_queue = controller_queue self.grouping_value = grouping_value self.error_message = error_message self.process_name = process_name self.producer_uuid = producer_uuid self.destination_endpoint = destination_endpoint self.destination_uuid = destination_uuid self.init_time = datetime.datetime.now() @classmethod def new(cls, message, content, grouping_value=None, error_message=None): """ Creates a new message, based on an existing message. This has the consequence that it will be tracked together and the tap will not be notified until every message in the chain is properly ack'ed. :param message: Message instance, as received by the intersection :param content: Any value that can be serialized into json :param grouping_value: String that can be used for routing messages consistently to the same receiver """ return cls(ramp_unique_id=message.ramp_unique_id, content=content, grouping_value=grouping_value, error_message=error_message, producer_uuid=message.producer_uuid) @classmethod def from_message(cls, message, controller_queue, process_name=None): """ :param message: Message dict (converted from JSON) :param controller_queue: :param process_name: UUID of the process processing this message (as string) :return: """ # assert type(message) is dict, "message (%s) should be dict" % message if type(message) is not dict: logging.error("Expected type dict, got type %s - message: %s", type(message), message) message['process_name'] = process_name # assert 'producer_uuid' in message, "missing uuid %s" % message return cls(controller_queue=controller_queue, **message) def _message(self): return { 'content': self.content, 'ramp_unique_id': self.ramp_unique_id, 'ack_value': self.ack_value, 'grouping_value': self.grouping_value, 'producer_uuid': self.producer_uuid } def as_json(self): return json.dumps(self._message(), cls=DateTimeAwareJsonEncoder) def send(self, queue, producer_uuid=None): if producer_uuid and not self.producer_uuid: # Check if provided and we didn't get one already self.producer_uuid = producer_uuid elif not self.producer_uuid: assert self.producer_uuid queue.send_string( self.as_json() ) def send_control_message(self, controller_queue, time_consumed=None, process_name=None, destination_endpoint=None, destination_uuid=None, sender=None): """ Control messages are notifications that a new message have been created, so the controller can keep track of this particular message and let the ramp know once the entire tree of messages has been completed. This is called implicitly on yield Message(_id, 'message') :param process_name: UUID of the process processing this message (as string) """ content = { 'process_name': process_name, 'msg_type': 'new_msg', } if not self.producer_uuid: raise Exception("Cannot send control message without producer UUID") if time_consumed: # Ramps provide time consumed, since we don't know the "start time" like in a intersection # where it's clear when the message is received and later 'acked' as the last action content['duration'] = duration_isoformat(time_consumed) content['sender'] = sender controller_queue.send_json({ 'ramp_unique_id': self.ramp_unique_id, 'ack_value': self.ack_value, 'content': content, 'producer_uuid': self.producer_uuid, 'destination_endpoint': destination_endpoint, 'destination_uuid': destination_uuid }) def ack(self, time_consumed=None): """ Send a message to the controller that this message was properly processed """ self.controller_queue.send_json({ 'ramp_unique_id': self.ramp_unique_id, 'ack_value': self.ack_value, 'content': { 'process_name': self.process_name, 'msg_type': 'ack', 'duration': duration_isoformat(time_consumed or (datetime.datetime.now() - self.init_time)) }, 'producer_uuid': self.producer_uuid, 'destination_uuid': self.producer_uuid }) def fail(self, error_message="", capture_exception=True): """ Send a message to the controller that this message failed to process """ self.controller_queue.send_json({ 'ramp_unique_id': self.ramp_unique_id, 'ack_value': -1, 'content': { 'process_name': self.process_name, 'msg_type': 'fail', 'duration': duration_isoformat(datetime.datetime.now() - self.init_time), 'message_content': self.content }, 'producer_uuid': self.producer_uuid, 'destination_uuid': self.producer_uuid, 'error_message': error_message if not capture_exception else traceback.format_exc(), }) def __repr__(self): return "<Message: %s> %s" % (self.ramp_unique_id, self.content)
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from __future__ import absolute_import import sys from collections import Iterable, Mapping from kombu.five import string_t __all__ = ['lazy', 'maybe_evaluate', 'is_list', 'maybe_list'] class lazy(object): """Holds lazy evaluation. Evaluated when called or if the :meth:`evaluate` method is called. The function is re-evaluated on every call. Overloaded operations that will evaluate the promise: :meth:`__str__`, :meth:`__repr__`, :meth:`__cmp__`. """ def __init__(self, fun, *args, **kwargs): self._fun = fun self._args = args self._kwargs = kwargs def __call__(self): return self.evaluate() def evaluate(self): return self._fun(*self._args, **self._kwargs) def __str__(self): return str(self()) def __repr__(self): return repr(self()) def __eq__(self, rhs): return self() == rhs def __ne__(self, rhs): return self() != rhs def __deepcopy__(self, memo): memo[id(self)] = self return self def __reduce__(self): return (self.__class__, (self._fun, ), {'_args': self._args, '_kwargs': self._kwargs}) if sys.version_info[0] < 3: def __cmp__(self, rhs): if isinstance(rhs, self.__class__): return -cmp(rhs, self()) return cmp(self(), rhs) def maybe_evaluate(value): """Evaluates if the value is a :class:`lazy` instance.""" if isinstance(value, lazy): return value.evaluate() return value def is_list(l, scalars=(Mapping, string_t), iters=(Iterable, )): """Return true if the object is iterable (but not if object is a mapping or string).""" return isinstance(l, iters) and not isinstance(l, scalars or ()) def maybe_list(l, scalars=(Mapping, string_t)): """Return list of one element if ``l`` is a scalar.""" return l if l is None or is_list(l, scalars) else [l] # Compat names (before kombu 3.0) promise = lazy maybe_promise = maybe_evaluate
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from django.db import transaction class AtomicMixin(object): """ Ensures we rollback db transactions on exceptions. Idea from https://github.com/tomchristie/django-rest-framework/pull/1204 """ @transaction.atomic() def dispatch(self, *args, **kwargs): return super(AtomicMixin, self).dispatch(*args, **kwargs) def handle_exception(self, *args, **kwargs): response = super(AtomicMixin, self).handle_exception(*args, **kwargs) if getattr(response, 'exception'): # We've suppressed the exception but still need to rollback any transaction. transaction.set_rollback(True) return response
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from .windows import add_dock, window, run, persist_layout from mpldock.common import named from . import tweaks, backend __all__ = ['window', 'add_dock', 'tweaks', 'backend', 'run', 'persist_layout']
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import pytest @pytest.mark.parametrize(('f', 't'), [(sum, list), (len, int)]) def test_foo(f, t): assert isinstance(f([[1], [2]]), t) def test_bar(): # unparametrized pass
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from chainerui.models.argument import Argument # NOQA from chainerui.models.asset import Asset # NOQA from chainerui.models.bindata import Bindata # NOQA from chainerui.models.command import Command # NOQA from chainerui.models.log import Log # NOQA from chainerui.models.project import Project # NOQA from chainerui.models.result import Result # NOQA from chainerui.models.snapshot import Snapshot # NOQA
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BZX = Contract.from_abi("BZX", "0xc47812857a74425e2039b57891a3dfcf51602d5d", interface.IBZx.abi) TOKEN_REGISTRY = Contract.from_abi("TOKEN_REGISTRY", "0x2fA30fB75E08f5533f0CF8EBcbb1445277684E85", TokenRegistry.abi) list = TOKEN_REGISTRY.getTokens(0, 100) for l in list: iTokenTemp = Contract.from_abi("iTokenTemp", l[0], LoanTokenLogicStandard.abi) globals()[iTokenTemp.symbol()] = iTokenTemp underlyingTemp = Contract.from_abi("underlyingTemp", l[1], TestToken.abi) globals()[underlyingTemp.symbol()] = underlyingTemp CHI = Contract.from_abi("CHI", "0x0000000000004946c0e9F43F4Dee607b0eF1fA1c", TestToken.abi) CHEF = Contract.from_abi("CHEF", "0x1FDCA2422668B961E162A8849dc0C2feaDb58915", MasterChef_BSC.abi) HELPER = Contract.from_abi("HELPER", "0xE05999ACcb887D32c9bd186e8C9dfE0e1E7814dE", HelperImpl.abi) BGOV = Contract.from_abi("PGOV", "0xf8E026dC4C0860771f691EcFFBbdfe2fa51c77CF", GovToken.abi) CHEF = Contract.from_abi("CHEF", CHEF.address, interface.IMasterChef.abi) SWEEP_FEES = Contract.from_abi("STAKING", "0x5c9b515f05a0E2a9B14C171E2675dDc1655D9A1c", FeeExtractAndDistribute_BSC.abi)
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from sre_parse import Pattern, SubPattern, parse from sre_compile import compile as sre_compile from sre_constants import BRANCH, SUBPATTERN class _ScanMatch(object): def __init__(self, match, rule, start, end): self._match = match self._start = start self._end = end self._rule = rule def __getattr__(self, name): return getattr(self._match, name) def __group_proc(self, method, group): if group == 0: return method() if isinstance(group, basestring): return method(self._rule + '\x00' + group) real_group = self._start + group if real_group > self._end: raise IndexError('no such group') return method(real_group) def group(self, *groups): if len(groups) in (0, 1): return self.__group_proc(self._match.group, groups and groups[0] or 0) return tuple(self.__group_proc(self._match.group, group) for group in groups) def groupdict(self, default=None): prefix = self._rule + '\x00' rv = {} for key, value in self._match.groupdict(default).iteritems(): if key.startswith(prefix): rv[key[len(prefix):]] = value return rv def span(self, group=0): return self.__group_proc(self._match.span, group) def groups(self): return self._match.groups()[self._start:self._end] def start(self, group=0): return self.__group_proc(self._match.start, group) def end(self, group=0): return self.__group_proc(self._match.end, group) def expand(self, template): raise RuntimeError('Unsupported on scan matches') class ScanEnd(Exception): def __init__(self, pos): Exception.__init__(self, pos) self.pos = pos class Scanner(object): def __init__(self, rules, flags=0): pattern = Pattern() pattern.flags = flags pattern.groups = len(rules) + 1 _og = pattern.opengroup pattern.opengroup = lambda n: _og(n and '%s\x00%s' % (name, n) or n) self.rules = [] subpatterns = [] for group, (name, regex) in enumerate(rules, 1): last_group = pattern.groups - 1 subpatterns.append(SubPattern(pattern, [ (SUBPATTERN, (group, parse(regex, flags, pattern))), ])) self.rules.append((name, last_group, pattern.groups - 1)) self._scanner = sre_compile(SubPattern( pattern, [(BRANCH, (None, subpatterns))])).scanner def scan(self, string, skip=False): sc = self._scanner(string) match = None for match in iter(sc.search if skip else sc.match, None): rule, start, end = self.rules[match.lastindex - 1] yield rule, _ScanMatch(match, rule, start, end) if not skip: end = match and match.end() or 0 if end < len(string): raise ScanEnd(end) def scan_with_holes(self, string): pos = 0 for rule, match in self.scan(string, skip=True): hole = string[pos:match.start()] if hole: yield None, hole yield rule, match pos = match.end() hole = string[pos:] if hole: yield None, hole
176005
import pandas as pd import numpy as np from os.path import join, exists, split from os import mkdir, makedirs, listdir import gc import matplotlib.pyplot as plt import seaborn from copy import deepcopy from time import time import pickle import argparse parser = argparse.ArgumentParser() parser.add_argument('split_name') parser.add_argument('f') parser.add_argument('--t_reset',type=int, default=25) args = parser.parse_args() split_name = args.split_name f = args.f t_reset = args.t_reset # split_name = 'temporal_4' # f = 'batch_38.h5' # t_reset = 25 fixed_rec = 0.9 model_name = 'shap_top500_features' delta_t = 0 window_size = 480 data_version = 'v6b' result_version = '181108' t_postevent = np.timedelta64(2, 'h') wsize_upper_h = (window_size+delta_t) * np.timedelta64(1, 'm') wsize_lower_h = delta_t * np.timedelta64(1, 'm') bern_path = '/cluster/work/grlab/clinical/Inselspital/DataReleases/01-19-2017/InselSpital/' alarm_path = join(bern_path, 'circews_analysis', 'alarm_score_for_calibration_new', data_version, 'merged_0_reset_%d'%t_reset, model_name, split_name) ep_path = join(bern_path, '3a_endpoints', data_version,'reduced') res_dir = lambda s: 'WorseStateFromZero_0.0_8.0_%s_lightgbm_full'%s pred_path = join(bern_path, '8_predictions', result_version, 'reduced', split_name, res_dir(model_name)) with pd.HDFStore(join(pred_path, f), mode='r') as tmp: pids = [int(key[2:]) for key in tmp.keys()] gc.collect() df_store = pd.HDFStore(join(pred_path, f), mode='r') pids = [int(key[2:]) for key in df_store.keys()] df_store.close() gc.collect() stats = dict() lst_period_type = ['critical_window', 'maintenance_window', 'uncritical_window', 'patients_wo_events'] for period_type in lst_period_type: stats.update({period_type: dict(valid_los=[], cnt_alarm=[], los=[])}) stats.update(cnt_catched_event=0, cnt_missed_event=0) is_critical_win = lambda t, ts: np.logical_and(ts< t-wsize_lower_h, ts>=t-wsize_upper_h) is_maintenance_win = lambda t, ts: np.logical_and(ts>t, ts<=t+t_postevent) is_uncritical_win = lambda t, ts, mode: ts<t-wsize_upper_h if mode=='before' else ts>t+t_postevent t_start = time() for n, pid in enumerate(pids): df = pd.read_hdf(join(alarm_path, f), 'p%d'%pid).reset_index() # df = pd.read_hdf(join(alarm_path, 'rec_%g'%fixed_rec+f), 'p%d'%pid).reset_index() df.set_index('AbsDatetime', inplace=True) for col in ['InEvent', 'Stable']: df.loc[:,col] = df[col].astype(int) if df.InEvent.sum()==0: # assert('Yes' not in df.IsAlarmTrue.unique()) stats['patients_wo_events']['valid_los'].append( df.Stable.sum() / 12) stats['patients_wo_events']['cnt_alarm'].append( df.Alarm.sum() ) stats['patients_wo_events']['los'].append( len(df)/12 ) else: stable_sum = 0 beg_onset = df.index[np.where(np.array([0]+np.diff(df.InEvent.values).tolist())==1)[0]] end_onset = df.index[np.where(np.diff(df.InEvent.values)==-1)[0]] if df.iloc[0].InEvent==1: beg_onset = np.concatenate([[df.index[0]], beg_onset]) if df.iloc[-1].InEvent==1: end_onset = np.concatenate([end_onset, [df.index[-1]]]) assert(len(beg_onset)==len(end_onset)) ### Critical window for i, dt in enumerate(beg_onset): dt = np.datetime64(dt) win_pre_event = df[is_critical_win(dt, df.index.values)] if len(win_pre_event)==0: continue if len(win_pre_event)==0 or win_pre_event.Stable.sum()==0: continue if ~ df.loc[dt,'Onset']: pass elif win_pre_event.Alarm.sum()>0 and df.loc[dt,'Onset'] and df.loc[dt,'CatchedOnset']: stats['cnt_catched_event'] += 1 elif win_pre_event.Alarm.sum()==0 and df.loc[dt,'Onset'] and ~df.loc[dt,'CatchedOnset']: stats['cnt_missed_event'] += 1 else: print('Alarm number', win_pre_event.Alarm.sum(),'; Onset status', df.loc[dt, 'CatchedOnset']) print(dt) raise Exception('Problem!!!!') if i > 0: win_pre_event = win_pre_event[win_pre_event.index>end_onset[i-1]] stable_sum += win_pre_event.Stable.sum() / 12 stats['critical_window']['valid_los'].append( win_pre_event.Stable.sum() / 12 ) stats['critical_window']['los'].append( len(df)/12 ) stats['critical_window']['cnt_alarm'].append( win_pre_event.Alarm.sum() ) ### Uncritical window for i, dt in enumerate(beg_onset): dt = np.datetime64(dt) win_pre_event = df[is_uncritical_win(dt, df.index.values, 'before')] if len(win_pre_event)==0: continue if i > 0: win_pre_event = win_pre_event[win_pre_event.index>end_onset[i-1]+t_postevent] if len(win_pre_event)==0 or win_pre_event.Stable.sum()==0: continue stable_sum += win_pre_event.Stable.sum() / 12 stats['uncritical_window']['valid_los'].append(win_pre_event.Stable.sum() / 12) stats['uncritical_window']['los'].append( len(df)/12 ) stats['uncritical_window']['cnt_alarm'].append(win_pre_event.Alarm.sum()) win_post_last_event = df[is_uncritical_win(np.datetime64(end_onset[-1]),df.index.values,'after')] stable_sum += win_post_last_event.Stable.sum() / 12 stats['uncritical_window']['valid_los'].append(win_post_last_event.Stable.sum() / 12) stats['uncritical_window']['los'].append( len(df)/12 ) stats['uncritical_window']['cnt_alarm'].append(win_post_last_event.Alarm.sum()) ### Maintenance window for i, dt in enumerate(end_onset): dt = np.datetime64(dt) win_post_event = df[is_maintenance_win(dt, df.index.values)] if len(win_post_event)==0: continue if i < len(beg_onset) - 1: win_post_event = win_post_event[win_post_event.index<beg_onset[i+1]-wsize_upper_h] if len(win_post_event)==0 or win_post_event.Stable.sum()==0: continue stable_sum += win_post_event.Stable.sum() / 12 stats['maintenance_window']['valid_los'].append(win_post_event.Stable.sum() / 12) stats['maintenance_window']['los'].append( len(df)/12 ) stats['maintenance_window']['cnt_alarm'].append(win_post_event.Alarm.sum()) assert(np.abs(df.Stable.sum()/12-stable_sum)<1e-10) if (n+1)%10==0: print('Process %d patients, time: %4.4g sec'%(n+1, time()-t_start)) gc.collect() # with open(join(alarm_path, 'rec_%g'%fixed_rec+f.replace('.h5', '.pkl')), 'wb') as tmp: # pickle.dump(stats, tmp) with open(join(alarm_path, f.replace('.h5', '.pkl')), 'wb') as tmp: pickle.dump(stats, tmp)
176035
import numpy as np import pandas as pd from vimms.old_unused_experimental.PythonMzmine import get_base_scoring_df from vimms.Roi import make_roi QCB_MZML2CHEMS_DICT = {'min_ms1_intensity': 1.75E5, 'mz_tol': 2, 'mz_units': 'ppm', 'min_length': 1, 'min_intensity': 0, 'start_rt': 0, 'stop_rt': 1560} def get_rois(mzml, min_roi_length, mzml2chems_dict=QCB_MZML2CHEMS_DICT): good_roi, junk_roi = make_roi(mzml, mz_tol=mzml2chems_dict['mz_tol'], mz_units=mzml2chems_dict['mz_units'], min_length=min_roi_length, min_intensity=mzml2chems_dict['min_intensity'], start_rt=mzml2chems_dict['start_rt'], stop_rt=mzml2chems_dict['stop_rt']) return good_roi, junk_roi def mzml2classificationdata(mzmls, mzml_picked_peaks_files, min_roi_length=5, mzml2chems_dict=QCB_MZML2CHEMS_DICT, mz_slack=0.01, drift_window_lengths=[5], rt_peak_tol=2, include_status=True): rois = [] for i in range(len(mzmls)): good_roi, junk_roi = get_rois(mzmls[i], min_roi_length, mzml2chems_dict) rois.extend(good_roi) picked_peaks = get_base_scoring_df(mzml_picked_peaks_files[i]) df_new = rois2classificationdata2(good_roi, picked_peaks, mz_slack=mz_slack, drift_window_lengths=drift_window_lengths, rt_peak_tol=rt_peak_tol, include_status=include_status) if i == 0: df = df_new else: df = pd.concat([df, df_new]) return df, rois class get_prob_classifier(object): def __init__(self, mzmls, mzml_picked_peaks_files, min_roi_length=5, mzml2chems_dict=QCB_MZML2CHEMS_DICT, mz_slack=0.01, roi_change_n=5, rt_peak_tol=2): self.roi_change_n = roi_change_n df, rois = mzml2classificationdata(mzmls, mzml_picked_peaks_files, min_roi_length, mzml2chems_dict, mz_slack, [roi_change_n], rt_peak_tol, include_status=True) df = df.dropna(thresh=2) base_classes = ['Decrease', 'Increase', 'Noise', 'Top'] self.probabilities = [] for i in range(int(max(df.iloc[:, 0]) + 1)): i_classes = df['rt_status'].iloc[np.where(df.iloc[:, 0] == i)[0]] probs = np.array([sum(i_classes == base) for base in base_classes]) / len(i_classes) self.probabilities.append(probs) def predict(self, value): return self.probabilities[value] def calculate_window_change(intensities, drift_window_len): return sum((np.array(intensities)[-(drift_window_len - 1):] - np.array(intensities)[-drift_window_len:-1]) > 0) def find_possible_peaks(roi, picked_peaks, mz_slack): rt_check1 = (picked_peaks['rt min'] >= roi.rt_list[0]) & (roi.rt_list[-1] >= picked_peaks['rt min']) rt_check2 = (picked_peaks['rt max'] >= roi.rt_list[0]) & (roi.rt_list[-1] >= picked_peaks['rt max']) rt_check3 = (picked_peaks['rt min'] <= roi.rt_list[0]) & (picked_peaks['rt max'] >= roi.rt_list[-1]) rt_check = rt_check1 | rt_check2 | rt_check3 # logger.debug('rt len ' + len(rt_check)) # logger.debug('rt check ' + rt_check) # plus and minus one is just slack for the initial check initial_mz_check = (picked_peaks['m/z max'] + 1 >= roi.get_mean_mz()) & ( roi.get_mean_mz() >= picked_peaks['m/z min'] - 1) # logger.debug('mz len ' + len(initial_mz_check)) # logger.debug('mz check ' + initial_mz_check) possible_peaks = np.where(np.logical_and(rt_check, initial_mz_check))[0] updated_possible_peaks = [] for j in possible_peaks: peak = picked_peaks.iloc[j] check_peak = np.nonzero((peak['rt min'] < roi.rt_list) & (roi.rt_list < peak['rt max']))[0] mean_mz = np.mean(np.array(roi.mz_list)[check_peak]) if peak['m/z min'] - mz_slack < mean_mz < peak['m/z max'] + mz_slack: updated_possible_peaks.append(j) return updated_possible_peaks def rois2classificationdata2(rois, picked_peaks, mz_slack=0.01, drift_window_lengths=[5], rt_peak_tol=2, include_status=True): roi_change_list = [[] for i in range(len(drift_window_lengths))] rt_status_list = [] for roi in rois: # get drift data for window in range(len(drift_window_lengths)): roi_change_list[window].extend([None for i in range(drift_window_lengths[window] - 1)]) roi_change = [calculate_window_change(roi.intensity_list[:i], drift_window_lengths[window]) for i in range(drift_window_lengths[window], roi.n + 1)] roi_change_list[window].extend(roi_change) # get possible peaks if include_status: possible_peaks = find_possible_peaks(roi, picked_peaks, mz_slack) possible_peaks_list = picked_peaks.iloc[possible_peaks] # get data if not possible_peaks: rt_status_list.extend([0 for rt in roi.rt_list]) else: for rt in roi.rt_list: rt_status = 0 for j in range(len(possible_peaks_list.index)): if possible_peaks_list['rt centre'].iloc[j] - rt_peak_tol <= rt <= \ possible_peaks_list['rt centre'].iloc[j] + rt_peak_tol: rt_status = max(3, rt_status) elif possible_peaks_list['rt min'].iloc[j] <= rt <= possible_peaks_list['rt centre'].iloc[j]: rt_status = max(2, rt_status) elif possible_peaks_list['rt centre'].iloc[j] <= rt <= possible_peaks_list['rt max'].iloc[j]: rt_status = max(1, rt_status) else: rt_status = max(0, rt_status) rt_status_list.append(rt_status) # convert rt status to classes if include_status: rt_status_list = np.array(rt_status_list) rt_status_list_str = np.array(['Unknown' for i in range(len(rt_status_list))], dtype="<U10") rt_status_list_str[np.where(rt_status_list == 0)[0]] = 'Noise' rt_status_list_str[np.where(rt_status_list == 1)[0]] = 'Decrease' rt_status_list_str[np.where(rt_status_list == 2)[0]] = 'Increase' rt_status_list_str[np.where(rt_status_list == 3)[0]] = 'Top' # save as data frame df = pd.DataFrame() for window in range(len(drift_window_lengths)): df['roi_change_' + str(drift_window_lengths[window])] = roi_change_list[window] if include_status: df['rt_status'] = rt_status_list_str return df # def get_intensity_difference(roi_intensities, n, positive=True): # # add exception for short roi # difference = [] # for i in range(len(roi_intensities) - n): # difference.append(np.log(roi_intensities[i + n]) - np.log(roi_intensities[i])) # if positive: # return max(difference) # else: # return min(difference) # # # def get_max_increasing(roi_intensities, n_skip=0, increasing_TF=True): # # add exception for short roi # max_increasing = 0 # for i in range(len(roi_intensities)): # current_increasing = 0 # current_skip = 0 # if len(roi_intensities[i:]) <= max_increasing: # break # for j in range(1, len(roi_intensities[i:])): # if (roi_intensities[i:][j] > roi_intensities[i:][j - 1 - current_skip]) == increasing_TF: # current_increasing += 1 + current_skip # current_skip = 0 # else: # current_skip += 1 # if current_skip > n_skip: # max_increasing = max(max_increasing, current_increasing) # break # return max_increasing # # # def get_intensity_list(roi, max_length): # if max_length is None: # return roi.intensity_list # else: # return roi.intensity_list[0:max_length] # def rois2classificationdata(rois, picked_peaks, mz_slack=0.01): # base_roi = [] # base_status = [] # split_roi = [] # split_status = [] # for roi in rois: # rt_check1 = (picked_peaks['rt min'] >= roi.rt_list[0]) & (roi.rt_list[-1] >= picked_peaks['rt min']) # rt_check2 = (picked_peaks['rt max'] >= roi.rt_list[0]) & (roi.rt_list[-1] >= picked_peaks['rt max']) # rt_check3 = (picked_peaks['rt min'] <= roi.rt_list[0]) & (picked_peaks['rt max'] >= roi.rt_list[-1]) # rt_check = rt_check1 | rt_check2 | rt_check3 # # plus and minus one is just slack for the initial check # initial_mz_check = (picked_peaks['m/z max'] + 1 >= roi.get_mean_mz()) & ( # roi.get_mean_mz() >= picked_peaks['m/z min'] - 1) # possible_peaks = np.nonzero(rt_check & initial_mz_check)[0] # if len(possible_peaks) == 0: # base_roi.append(roi) # split_roi.append(roi) # base_status.append(0) # split_status.append(0) # else: # updated_possible_peaks = [] # for j in possible_peaks: # peak = picked_peaks.iloc[j] # check_peak = np.nonzero((peak['rt min'] < roi.rt_list) & (roi.rt_list < peak['rt max']))[0] # mean_mz = np.mean(np.array(roi.mz_list)[check_peak]) # if peak['m/z min'] - mz_slack < mean_mz < peak['m/z max'] + mz_slack: # updated_possible_peaks.append(j) # if len(updated_possible_peaks) == 0: # base_roi.append(roi) # split_roi.append(roi) # base_status.append(0) # split_status.append(0) # else: # if len(updated_possible_peaks) == 1: # base_roi.append(roi) # split_roi.append(roi) # base_status.append(1) # split_status.append(1) # if len(updated_possible_peaks) > 1: # base_roi.append(roi) # base_status.append(1) # df = picked_peaks.iloc[updated_possible_peaks] # df = df.sort_values(by=['rt min']) # splits = (np.array(df['rt min'][1:]) + np.array(df['rt max'][0:-1])) / 2 # splits = np.insert(np.insert(splits, 0, 0), len(splits) + 1, 2000) # for j in range(len(splits) - 1): # check_range1 = roi.rt_list > splits[j] # check_range2 = roi.rt_list < splits[j + 1] # mz = np.array(roi.mz_list)[np.nonzero(check_range1 & check_range2)[0]].tolist() # rt = np.array(roi.rt_list)[np.nonzero(check_range1 & check_range2)[0]].tolist() # intensity = np.array(roi.intensity_list)[np.nonzero(check_range1 & check_range2)].tolist() # split_roi.append(Roi(mz, rt, intensity)) # split_status.append(1) # return base_roi, base_status, split_roi, split_status # # # def get_roi_classification_params(rois, roi_param_dict): # df = pd.DataFrame() # if roi_param_dict['include_log_max_intensity']: # df['log_max_intensity'] = np.log([roi.get_max_intensity() for roi in rois]) # if roi_param_dict['include_log_intensity_difference']: # df['log_intensity_difference'] = np.log(df['log_max_intensity']) - np.log([roi.get_min_intensity() for roi in rois]) # if roi_param_dict['consecutively_change_max'] > 0: # for i in range(roi_param_dict['consecutively_change_max']): # df['n_increase_' + str(i)] = [get_max_increasing(roi.intensity_list, i, True) for roi in rois] # df['n_decrease_' + str(i)] = [get_max_increasing(roi.intensity_list, i, False) for roi in rois] # df['n_interaction_' + str(i)] = df['n_increase_' + str(i)] * df['n_decrease_' + str(i)] # if roi_param_dict['intensity_change_max'] > 0: # for i in range(roi_param_dict['intensity_change_max']): # df['intensity_increase_' + str(i)] = [get_intensity_difference(roi.intensity_list, i+1, True) for roi in rois] # df['intensity_decrease_' + str(i)] = [get_intensity_difference(roi.intensity_list, i+1, False) for roi in rois] # df['intensity_interaction_' + str(i)] = df['intensity_increase_' + str(i)] * df['intensity_decrease_' + str(i)] # if roi_param_dict['lag_max'] > 0: # for i in range(roi_param_dict['lag_max']): # df['autocorrelation_' + str(i+1)] = [roi.get_autocorrelation(i+1) for roi in rois] # return df
176057
from django.test import TestCase from django.test import Client class Exercise4TestCase(TestCase): def test_template_content(self): """Test that the index view returns the set names from the paramaters, or defaults to 'world'""" c = Client() response = c.get('/') self.assertEqual(response.status_code, 200) self.assertEqual(response.content, b'Hello, world!') response = c.get('/?name=Ben') self.assertEqual(response.status_code, 200) self.assertEqual(response.content, b'Hello, Ben!') response = c.get('/?name=Ben&name=John') self.assertEqual(response.status_code, 200) self.assertEqual(response.content, b'Hello, John!') response = c.get('/?name=') self.assertEqual(response.status_code, 200) self.assertEqual(response.content, b'Hello, world!')
176062
import connexion import six from tapi_server.models.inline_object1 import InlineObject1 # noqa: E501 from tapi_server.models.inline_object12 import InlineObject12 # noqa: E501 from tapi_server.models.inline_object13 import InlineObject13 # noqa: E501 from tapi_server.models.inline_object14 import InlineObject14 # noqa: E501 from tapi_server.models.inline_object27 import InlineObject27 # noqa: E501 from tapi_server.models.inline_object6 import InlineObject6 # noqa: E501 from tapi_server.models.tapi_common_bandwidth_profile import TapiCommonBandwidthProfile # noqa: E501 from tapi_server.models.tapi_common_capacity import TapiCommonCapacity # noqa: E501 from tapi_server.models.tapi_common_capacity_value import TapiCommonCapacityValue # noqa: E501 from tapi_server.models.tapi_common_name_and_value import TapiCommonNameAndValue # noqa: E501 from tapi_server.models.tapi_common_service_interface_point_ref import TapiCommonServiceInterfacePointRef # noqa: E501 from tapi_server.models.tapi_common_time_range import TapiCommonTimeRange # noqa: E501 from tapi_server.models.tapi_connectivity_ceplist_connection_end_point import TapiConnectivityCeplistConnectionEndPoint # noqa: E501 from tapi_server.models.tapi_connectivity_connection import TapiConnectivityConnection # noqa: E501 from tapi_server.models.tapi_connectivity_connection_end_point_ref import TapiConnectivityConnectionEndPointRef # noqa: E501 from tapi_server.models.tapi_connectivity_connection_ref import TapiConnectivityConnectionRef # noqa: E501 from tapi_server.models.tapi_connectivity_connectivity_context import TapiConnectivityConnectivityContext # noqa: E501 from tapi_server.models.tapi_connectivity_connectivity_service_ref import TapiConnectivityConnectivityServiceRef # noqa: E501 from tapi_server.models.tapi_connectivity_connectivitycontext_connectivity_service import TapiConnectivityConnectivitycontextConnectivityService # noqa: E501 from tapi_server.models.tapi_connectivity_connectivityservice_end_point import TapiConnectivityConnectivityserviceEndPoint # noqa: E501 from tapi_server.models.tapi_connectivity_context_topologycontext_topology_node_ownednodeedgepoint_cep_list import TapiConnectivityContextTopologycontextTopologyNodeOwnednodeedgepointCepList # noqa: E501 from tapi_server.models.tapi_connectivity_create_connectivity_service import TapiConnectivityCreateConnectivityService # noqa: E501 from tapi_server.models.tapi_connectivity_get_connection_details import TapiConnectivityGetConnectionDetails # noqa: E501 from tapi_server.models.tapi_connectivity_get_connection_end_point_details import TapiConnectivityGetConnectionEndPointDetails # noqa: E501 from tapi_server.models.tapi_connectivity_get_connectivity_service_details import TapiConnectivityGetConnectivityServiceDetails # noqa: E501 from tapi_server.models.tapi_connectivity_get_connectivity_service_list import TapiConnectivityGetConnectivityServiceList # noqa: E501 from tapi_server.models.tapi_connectivity_route import TapiConnectivityRoute # noqa: E501 from tapi_server.models.tapi_connectivity_route_ref import TapiConnectivityRouteRef # noqa: E501 from tapi_server.models.tapi_connectivity_switch import TapiConnectivitySwitch # noqa: E501 from tapi_server.models.tapi_connectivity_switch_control import TapiConnectivitySwitchControl # noqa: E501 from tapi_server.models.tapi_connectivity_switch_control_ref import TapiConnectivitySwitchControlRef # noqa: E501 from tapi_server.models.tapi_connectivity_update_connectivity_service import TapiConnectivityUpdateConnectivityService # noqa: E501 from tapi_server.models.tapi_path_computation_path_ref import TapiPathComputationPathRef # noqa: E501 from tapi_server.models.tapi_topology_cost_characteristic import TapiTopologyCostCharacteristic # noqa: E501 from tapi_server.models.tapi_topology_latency_characteristic import TapiTopologyLatencyCharacteristic # noqa: E501 from tapi_server.models.tapi_topology_link_ref import TapiTopologyLinkRef # noqa: E501 from tapi_server.models.tapi_topology_node_edge_point_ref import TapiTopologyNodeEdgePointRef # noqa: E501 from tapi_server.models.tapi_topology_node_ref import TapiTopologyNodeRef # noqa: E501 from tapi_server.models.tapi_topology_resilience_type import TapiTopologyResilienceType # noqa: E501 from tapi_server.models.tapi_topology_risk_characteristic import TapiTopologyRiskCharacteristic # noqa: E501 from tapi_server.models.tapi_topology_topology_ref import TapiTopologyTopologyRef # noqa: E501 from tapi_server.models.tapi_connectivity_getconnectivityservicelist_output import TapiConnectivityGetconnectivityservicelistOutput # noqa: F401,E501 from tapi_server.models.tapi_connectivity_getconnectivityservicedetails_output import TapiConnectivityGetconnectivityservicedetailsOutput # noqa: F401,E501 from tapi_server.models.tapi_connectivity_getconnectiondetails_output import TapiConnectivityGetconnectiondetailsOutput # noqa: F401,E501 from tapi_server.models.tapi_connectivity_getconnectionendpointdetails_output import TapiConnectivityGetconnectionendpointdetailsOutput # noqa: F401,E501 from tapi_server import util from tapi_server import database def data_context_connectivity_context_connectionuuid_connection_end_pointtopology_uuidnode_uuidnode_edge_point_uuidconnection_end_point_uuid_get(uuid, topology_uuid, node_uuid, node_edge_point_uuid, connection_end_point_uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_connection_end_pointtopology_uuidnode_uuidnode_edge_point_uuidconnection_end_point_uuid_get returns tapi.connectivity.ConnectionEndPointRef # noqa: E501 :param uuid: Id of connection :type uuid: str :param topology_uuid: Id of connection-end-point :type topology_uuid: str :param node_uuid: Id of connection-end-point :type node_uuid: str :param node_edge_point_uuid: Id of connection-end-point :type node_edge_point_uuid: str :param connection_end_point_uuid: Id of connection-end-point :type connection_end_point_uuid: str :rtype: TapiConnectivityConnectionEndPointRef """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_get(uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_get returns tapi.connectivity.Connection # noqa: E501 :param uuid: Id of connection :type uuid: str :rtype: TapiConnectivityConnection """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_lower_connectionconnection_uuid_get(uuid, connection_uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_lower_connectionconnection_uuid_get returns tapi.connectivity.ConnectionRef # noqa: E501 :param uuid: Id of connection :type uuid: str :param connection_uuid: Id of lower-connection :type connection_uuid: str :rtype: TapiConnectivityConnectionRef """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_namevalue_name_get(uuid, value_name): # noqa: E501 """data_context_connectivity_context_connectionuuid_namevalue_name_get returns tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connection :type uuid: str :param value_name: Id of name :type value_name: str :rtype: TapiCommonNameAndValue """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_routelocal_id_connection_end_pointtopology_uuidnode_uuidnode_edge_point_uuidconnection_end_point_uuid_get(uuid, local_id, topology_uuid, node_uuid, node_edge_point_uuid, connection_end_point_uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_routelocal_id_connection_end_pointtopology_uuidnode_uuidnode_edge_point_uuidconnection_end_point_uuid_get returns tapi.connectivity.ConnectionEndPointRef # noqa: E501 :param uuid: Id of connection :type uuid: str :param local_id: Id of route :type local_id: str :param topology_uuid: Id of connection-end-point :type topology_uuid: str :param node_uuid: Id of connection-end-point :type node_uuid: str :param node_edge_point_uuid: Id of connection-end-point :type node_edge_point_uuid: str :param connection_end_point_uuid: Id of connection-end-point :type connection_end_point_uuid: str :rtype: TapiConnectivityConnectionEndPointRef """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_routelocal_id_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectionuuid_routelocal_id_get returns tapi.connectivity.Route # noqa: E501 :param uuid: Id of connection :type uuid: str :param local_id: Id of route :type local_id: str :rtype: TapiConnectivityRoute """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_routelocal_id_namevalue_name_get(uuid, local_id, value_name): # noqa: E501 """data_context_connectivity_context_connectionuuid_routelocal_id_namevalue_name_get returns tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connection :type uuid: str :param local_id: Id of route :type local_id: str :param value_name: Id of name :type value_name: str :rtype: TapiCommonNameAndValue """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_supported_client_linktopology_uuidlink_uuid_get(uuid, topology_uuid, link_uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_supported_client_linktopology_uuidlink_uuid_get returns tapi.topology.LinkRef # noqa: E501 :param uuid: Id of connection :type uuid: str :param topology_uuid: Id of supported-client-link :type topology_uuid: str :param link_uuid: Id of supported-client-link :type link_uuid: str :rtype: TapiTopologyLinkRef """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_get(uuid, switch_control_uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_get returns tapi.connectivity.SwitchControl # noqa: E501 :param uuid: Id of connection :type uuid: str :param switch_control_uuid: Id of switch-control :type switch_control_uuid: str :rtype: TapiConnectivitySwitchControl """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_namevalue_name_get(uuid, switch_control_uuid, value_name): # noqa: E501 """data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_namevalue_name_get returns tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connection :type uuid: str :param switch_control_uuid: Id of switch-control :type switch_control_uuid: str :param value_name: Id of name :type value_name: str :rtype: TapiCommonNameAndValue """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_resilience_type_get(uuid, switch_control_uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_resilience_type_get returns tapi.topology.ResilienceType # noqa: E501 :param uuid: Id of connection :type uuid: str :param switch_control_uuid: Id of switch-control :type switch_control_uuid: str :rtype: TapiTopologyResilienceType """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_sub_switch_controlconnection_uuidsub_switch_control_switch_control_uuid_get(uuid, switch_control_uuid, connection_uuid, sub_switch_control_switch_control_uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_sub_switch_controlconnection_uuidsub_switch_control_switch_control_uuid_get returns tapi.connectivity.SwitchControlRef # noqa: E501 :param uuid: Id of connection :type uuid: str :param switch_control_uuid: Id of switch-control :type switch_control_uuid: str :param connection_uuid: Id of sub-switch-control :type connection_uuid: str :param sub_switch_control_switch_control_uuid: Id of sub-switch-control :type sub_switch_control_switch_control_uuid: str :rtype: TapiConnectivitySwitchControlRef """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_switchlocal_id_get(uuid, switch_control_uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_switchlocal_id_get returns tapi.connectivity.Switch # noqa: E501 :param uuid: Id of connection :type uuid: str :param switch_control_uuid: Id of switch-control :type switch_control_uuid: str :param local_id: Id of switch :type local_id: str :rtype: TapiConnectivitySwitch """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_switchlocal_id_namevalue_name_get(uuid, switch_control_uuid, local_id, value_name): # noqa: E501 """data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_switchlocal_id_namevalue_name_get returns tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connection :type uuid: str :param switch_control_uuid: Id of switch-control :type switch_control_uuid: str :param local_id: Id of switch :type local_id: str :param value_name: Id of name :type value_name: str :rtype: TapiCommonNameAndValue """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_switchlocal_id_selected_connection_end_pointtopology_uuidnode_uuidnode_edge_point_uuidconnection_end_point_uuid_get(uuid, switch_control_uuid, local_id, topology_uuid, node_uuid, node_edge_point_uuid, connection_end_point_uuid): # noqa: E501 """data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_switchlocal_id_selected_connection_end_pointtopology_uuidnode_uuidnode_edge_point_uuidconnection_end_point_uuid_get returns tapi.connectivity.ConnectionEndPointRef # noqa: E501 :param uuid: Id of connection :type uuid: str :param switch_control_uuid: Id of switch-control :type switch_control_uuid: str :param local_id: Id of switch :type local_id: str :param topology_uuid: Id of selected-connection-end-point :type topology_uuid: str :param node_uuid: Id of selected-connection-end-point :type node_uuid: str :param node_edge_point_uuid: Id of selected-connection-end-point :type node_edge_point_uuid: str :param connection_end_point_uuid: Id of selected-connection-end-point :type connection_end_point_uuid: str :rtype: TapiConnectivityConnectionEndPointRef """ return 'do some magic!' def data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_switchlocal_id_selected_routeconnection_uuidroute_local_id_get(uuid, switch_control_uuid, local_id, connection_uuid, route_local_id): # noqa: E501 """data_context_connectivity_context_connectionuuid_switch_controlswitch_control_uuid_switchlocal_id_selected_routeconnection_uuidroute_local_id_get returns tapi.connectivity.RouteRef # noqa: E501 :param uuid: Id of connection :type uuid: str :param switch_control_uuid: Id of switch-control :type switch_control_uuid: str :param local_id: Id of switch :type local_id: str :param connection_uuid: Id of selected-route :type connection_uuid: str :param route_local_id: Id of selected-route :type route_local_id: str :rtype: TapiConnectivityRouteRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_service_post(tapi_connectivity_connectivitycontext_connectivity_service=None): # noqa: E501 """data_context_connectivity_context_connectivity_service_post creates tapi.connectivity.connectivitycontext.ConnectivityService # noqa: E501 :param tapi_connectivity_connectivitycontext_connectivity_service: tapi.connectivity.connectivitycontext.ConnectivityService to be added to list :type tapi_connectivity_connectivitycontext_connectivity_service: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivitycontext_connectivity_service = TapiConnectivityConnectivitycontextConnectivityService.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_avoid_topologytopology_uuid_get(uuid, topology_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_avoid_topologytopology_uuid_get returns tapi.topology.TopologyRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param topology_uuid: Id of avoid-topology :type topology_uuid: str :rtype: TapiTopologyTopologyRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_connectionconnection_uuid_get(uuid, connection_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_connectionconnection_uuid_get returns tapi.connectivity.ConnectionRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param connection_uuid: Id of connection :type connection_uuid: str :rtype: TapiConnectivityConnectionRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_coroute_inclusion_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_coroute_inclusion_delete removes tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_coroute_inclusion_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_coroute_inclusion_get returns tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiConnectivityConnectivityServiceRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_coroute_inclusion_post(uuid, tapi_connectivity_connectivity_service_ref=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_coroute_inclusion_post creates tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_connectivity_connectivity_service_ref: tapi.connectivity.ConnectivityServiceRef to be added to list :type tapi_connectivity_connectivity_service_ref: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivity_service_ref = TapiConnectivityConnectivityServiceRef.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_coroute_inclusion_put(uuid, tapi_connectivity_connectivity_service_ref=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_coroute_inclusion_put creates or updates tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_connectivity_connectivity_service_ref: tapi.connectivity.ConnectivityServiceRef to be added or updated :type tapi_connectivity_connectivity_service_ref: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivity_service_ref = TapiConnectivityConnectivityServiceRef.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_cost_characteristic_post(uuid, tapi_topology_cost_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_cost_characteristic_post creates tapi.topology.CostCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_topology_cost_characteristic: tapi.topology.CostCharacteristic to be added to list :type tapi_topology_cost_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_cost_characteristic = TapiTopologyCostCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_cost_characteristiccost_name_delete(uuid, cost_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_cost_characteristiccost_name_delete removes tapi.topology.CostCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param cost_name: Id of cost-characteristic :type cost_name: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_cost_characteristiccost_name_get(uuid, cost_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_cost_characteristiccost_name_get returns tapi.topology.CostCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param cost_name: Id of cost-characteristic :type cost_name: str :rtype: TapiTopologyCostCharacteristic """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_cost_characteristiccost_name_post(uuid, cost_name, tapi_topology_cost_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_cost_characteristiccost_name_post creates tapi.topology.CostCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param cost_name: Id of cost-characteristic :type cost_name: str :param tapi_topology_cost_characteristic: tapi.topology.CostCharacteristic to be added to list :type tapi_topology_cost_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_cost_characteristic = TapiTopologyCostCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_cost_characteristiccost_name_put(uuid, cost_name, tapi_topology_cost_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_cost_characteristiccost_name_put creates or updates tapi.topology.CostCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param cost_name: Id of cost-characteristic :type cost_name: str :param tapi_topology_cost_characteristic: tapi.topology.CostCharacteristic to be added or updated :type tapi_topology_cost_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_cost_characteristic = TapiTopologyCostCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_delete removes tapi.connectivity.connectivitycontext.ConnectivityService # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusion_post(uuid, tapi_connectivity_connectivity_service_ref=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusion_post creates tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_connectivity_connectivity_service_ref: tapi.connectivity.ConnectivityServiceRef to be added to list :type tapi_connectivity_connectivity_service_ref: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivity_service_ref = TapiConnectivityConnectivityServiceRef.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusionconnectivity_service_uuid_delete(uuid, connectivity_service_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusionconnectivity_service_uuid_delete removes tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param connectivity_service_uuid: Id of diversity-exclusion :type connectivity_service_uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusionconnectivity_service_uuid_get(uuid, connectivity_service_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusionconnectivity_service_uuid_get returns tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param connectivity_service_uuid: Id of diversity-exclusion :type connectivity_service_uuid: str :rtype: TapiConnectivityConnectivityServiceRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusionconnectivity_service_uuid_post(uuid, connectivity_service_uuid, tapi_connectivity_connectivity_service_ref=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusionconnectivity_service_uuid_post creates tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param connectivity_service_uuid: Id of diversity-exclusion :type connectivity_service_uuid: str :param tapi_connectivity_connectivity_service_ref: tapi.connectivity.ConnectivityServiceRef to be added to list :type tapi_connectivity_connectivity_service_ref: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivity_service_ref = TapiConnectivityConnectivityServiceRef.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusionconnectivity_service_uuid_put(uuid, connectivity_service_uuid, tapi_connectivity_connectivity_service_ref=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_diversity_exclusionconnectivity_service_uuid_put creates or updates tapi.connectivity.ConnectivityServiceRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param connectivity_service_uuid: Id of diversity-exclusion :type connectivity_service_uuid: str :param tapi_connectivity_connectivity_service_ref: tapi.connectivity.ConnectivityServiceRef to be added or updated :type tapi_connectivity_connectivity_service_ref: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivity_service_ref = TapiConnectivityConnectivityServiceRef.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_point_post(uuid, tapi_connectivity_connectivityservice_end_point=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_point_post creates tapi.connectivity.connectivityservice.EndPoint # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_connectivity_connectivityservice_end_point: tapi.connectivity.connectivityservice.EndPoint to be added to list :type tapi_connectivity_connectivityservice_end_point: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivityservice_end_point = TapiConnectivityConnectivityserviceEndPoint.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_post(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_put(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_information_rate_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_information_rate_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_information_rate_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_information_rate_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_information_rate_post(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_information_rate_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_information_rate_put(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_information_rate_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_delete removes tapi.common.BandwidthProfile # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_get returns tapi.common.BandwidthProfile # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiCommonBandwidthProfile """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_post(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_put(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_information_rate_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_information_rate_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_information_rate_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_information_rate_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_information_rate_post(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_information_rate_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_information_rate_put(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_information_rate_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_post(uuid, local_id, tapi_common_bandwidth_profile=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_post creates tapi.common.BandwidthProfile # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_bandwidth_profile: tapi.common.BandwidthProfile to be added to list :type tapi_common_bandwidth_profile: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_bandwidth_profile = TapiCommonBandwidthProfile.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_put(uuid, local_id, tapi_common_bandwidth_profile=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_put creates or updates tapi.common.BandwidthProfile # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_bandwidth_profile: tapi.common.BandwidthProfile to be added or updated :type tapi_common_bandwidth_profile: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_bandwidth_profile = TapiCommonBandwidthProfile.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_delete removes tapi.common.Capacity # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_get returns tapi.common.Capacity # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiCommonCapacity """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_post(uuid, local_id, tapi_common_capacity=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_post creates tapi.common.Capacity # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity: tapi.common.Capacity to be added to list :type tapi_common_capacity: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity = TapiCommonCapacity.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_put(uuid, local_id, tapi_common_capacity=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_put creates or updates tapi.common.Capacity # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity: tapi.common.Capacity to be added or updated :type tapi_common_capacity: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity = TapiCommonCapacity.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_total_size_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_total_size_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_total_size_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_total_size_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_total_size_post(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_total_size_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_total_size_put(uuid, local_id, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_total_size_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_connection_end_pointtopology_uuidnode_uuidnode_edge_point_uuidconnection_end_point_uuid_get(uuid, local_id, topology_uuid, node_uuid, node_edge_point_uuid, connection_end_point_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_connection_end_pointtopology_uuidnode_uuidnode_edge_point_uuidconnection_end_point_uuid_get returns tapi.connectivity.ConnectionEndPointRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param topology_uuid: Id of connection-end-point :type topology_uuid: str :param node_uuid: Id of connection-end-point :type node_uuid: str :param node_edge_point_uuid: Id of connection-end-point :type node_edge_point_uuid: str :param connection_end_point_uuid: Id of connection-end-point :type connection_end_point_uuid: str :rtype: TapiConnectivityConnectionEndPointRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_delete removes tapi.connectivity.connectivityservice.EndPoint # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_get returns tapi.connectivity.connectivityservice.EndPoint # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiConnectivityConnectivityserviceEndPoint """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_name_post(uuid, local_id, tapi_common_name_and_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_name_post creates tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_name_and_value: tapi.common.NameAndValue to be added to list :type tapi_common_name_and_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_name_and_value = TapiCommonNameAndValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_namevalue_name_delete(uuid, local_id, value_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_namevalue_name_delete removes tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param value_name: Id of name :type value_name: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_namevalue_name_get(uuid, local_id, value_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_namevalue_name_get returns tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param value_name: Id of name :type value_name: str :rtype: TapiCommonNameAndValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_namevalue_name_post(uuid, local_id, value_name, tapi_common_name_and_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_namevalue_name_post creates tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param value_name: Id of name :type value_name: str :param tapi_common_name_and_value: tapi.common.NameAndValue to be added to list :type tapi_common_name_and_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_name_and_value = TapiCommonNameAndValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_namevalue_name_put(uuid, local_id, value_name, tapi_common_name_and_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_namevalue_name_put creates or updates tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param value_name: Id of name :type value_name: str :param tapi_common_name_and_value: tapi.common.NameAndValue to be added or updated :type tapi_common_name_and_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_name_and_value = TapiCommonNameAndValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_post(uuid, local_id, tapi_connectivity_connectivityservice_end_point=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_post creates tapi.connectivity.connectivityservice.EndPoint # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_connectivity_connectivityservice_end_point: tapi.connectivity.connectivityservice.EndPoint to be added to list :type tapi_connectivity_connectivityservice_end_point: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivityservice_end_point = TapiConnectivityConnectivityserviceEndPoint.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_put(uuid, local_id, tapi_connectivity_connectivityservice_end_point=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_put creates or updates tapi.connectivity.connectivityservice.EndPoint # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_connectivity_connectivityservice_end_point: tapi.connectivity.connectivityservice.EndPoint to be added or updated :type tapi_connectivity_connectivityservice_end_point: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivityservice_end_point = TapiConnectivityConnectivityserviceEndPoint.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_service_interface_point_delete(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_service_interface_point_delete removes tapi.common.ServiceInterfacePointRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_service_interface_point_get(uuid, local_id): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_service_interface_point_get returns tapi.common.ServiceInterfacePointRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :rtype: TapiCommonServiceInterfacePointRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_service_interface_point_post(uuid, local_id, tapi_common_service_interface_point_ref=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_service_interface_point_post creates tapi.common.ServiceInterfacePointRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_service_interface_point_ref: tapi.common.ServiceInterfacePointRef to be added to list :type tapi_common_service_interface_point_ref: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_service_interface_point_ref = TapiCommonServiceInterfacePointRef.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_service_interface_point_put(uuid, local_id, tapi_common_service_interface_point_ref=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_service_interface_point_put creates or updates tapi.common.ServiceInterfacePointRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param local_id: Id of end-point :type local_id: str :param tapi_common_service_interface_point_ref: tapi.common.ServiceInterfacePointRef to be added or updated :type tapi_common_service_interface_point_ref: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_service_interface_point_ref = TapiCommonServiceInterfacePointRef.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_exclude_linktopology_uuidlink_uuid_get(uuid, topology_uuid, link_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_exclude_linktopology_uuidlink_uuid_get returns tapi.topology.LinkRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param topology_uuid: Id of exclude-link :type topology_uuid: str :param link_uuid: Id of exclude-link :type link_uuid: str :rtype: TapiTopologyLinkRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_exclude_nodetopology_uuidnode_uuid_get(uuid, topology_uuid, node_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_exclude_nodetopology_uuidnode_uuid_get returns tapi.topology.NodeRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param topology_uuid: Id of exclude-node :type topology_uuid: str :param node_uuid: Id of exclude-node :type node_uuid: str :rtype: TapiTopologyNodeRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_exclude_pathpath_uuid_get(uuid, path_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_exclude_pathpath_uuid_get returns tapi.path.computation.PathRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param path_uuid: Id of exclude-path :type path_uuid: str :rtype: TapiPathComputationPathRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_get returns tapi.connectivity.connectivitycontext.ConnectivityService # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiConnectivityConnectivitycontextConnectivityService """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_include_linktopology_uuidlink_uuid_get(uuid, topology_uuid, link_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_include_linktopology_uuidlink_uuid_get returns tapi.topology.LinkRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param topology_uuid: Id of include-link :type topology_uuid: str :param link_uuid: Id of include-link :type link_uuid: str :rtype: TapiTopologyLinkRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_include_nodetopology_uuidnode_uuid_get(uuid, topology_uuid, node_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_include_nodetopology_uuidnode_uuid_get returns tapi.topology.NodeRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param topology_uuid: Id of include-node :type topology_uuid: str :param node_uuid: Id of include-node :type node_uuid: str :rtype: TapiTopologyNodeRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_include_pathpath_uuid_get(uuid, path_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_include_pathpath_uuid_get returns tapi.path.computation.PathRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param path_uuid: Id of include-path :type path_uuid: str :rtype: TapiPathComputationPathRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_include_topologytopology_uuid_get(uuid, topology_uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_include_topologytopology_uuid_get returns tapi.topology.TopologyRef # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param topology_uuid: Id of include-topology :type topology_uuid: str :rtype: TapiTopologyTopologyRef """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_latency_characteristic_post(uuid, tapi_topology_latency_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_latency_characteristic_post creates tapi.topology.LatencyCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_topology_latency_characteristic: tapi.topology.LatencyCharacteristic to be added to list :type tapi_topology_latency_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_latency_characteristic = TapiTopologyLatencyCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_latency_characteristictraffic_property_name_delete(uuid, traffic_property_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_latency_characteristictraffic_property_name_delete removes tapi.topology.LatencyCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param traffic_property_name: Id of latency-characteristic :type traffic_property_name: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_latency_characteristictraffic_property_name_get(uuid, traffic_property_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_latency_characteristictraffic_property_name_get returns tapi.topology.LatencyCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param traffic_property_name: Id of latency-characteristic :type traffic_property_name: str :rtype: TapiTopologyLatencyCharacteristic """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_latency_characteristictraffic_property_name_post(uuid, traffic_property_name, tapi_topology_latency_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_latency_characteristictraffic_property_name_post creates tapi.topology.LatencyCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param traffic_property_name: Id of latency-characteristic :type traffic_property_name: str :param tapi_topology_latency_characteristic: tapi.topology.LatencyCharacteristic to be added to list :type tapi_topology_latency_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_latency_characteristic = TapiTopologyLatencyCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_latency_characteristictraffic_property_name_put(uuid, traffic_property_name, tapi_topology_latency_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_latency_characteristictraffic_property_name_put creates or updates tapi.topology.LatencyCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param traffic_property_name: Id of latency-characteristic :type traffic_property_name: str :param tapi_topology_latency_characteristic: tapi.topology.LatencyCharacteristic to be added or updated :type tapi_topology_latency_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_latency_characteristic = TapiTopologyLatencyCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_name_post(uuid, tapi_common_name_and_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_name_post creates tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_name_and_value: tapi.common.NameAndValue to be added to list :type tapi_common_name_and_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_name_and_value = TapiCommonNameAndValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_namevalue_name_delete(uuid, value_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_namevalue_name_delete removes tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param value_name: Id of name :type value_name: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_namevalue_name_get(uuid, value_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_namevalue_name_get returns tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param value_name: Id of name :type value_name: str :rtype: TapiCommonNameAndValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_namevalue_name_post(uuid, value_name, tapi_common_name_and_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_namevalue_name_post creates tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param value_name: Id of name :type value_name: str :param tapi_common_name_and_value: tapi.common.NameAndValue to be added to list :type tapi_common_name_and_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_name_and_value = TapiCommonNameAndValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_namevalue_name_put(uuid, value_name, tapi_common_name_and_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_namevalue_name_put creates or updates tapi.common.NameAndValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param value_name: Id of name :type value_name: str :param tapi_common_name_and_value: tapi.common.NameAndValue to be added or updated :type tapi_common_name_and_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_name_and_value = TapiCommonNameAndValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_post(uuid, tapi_connectivity_connectivitycontext_connectivity_service=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_post creates tapi.connectivity.connectivitycontext.ConnectivityService # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_connectivity_connectivitycontext_connectivity_service: tapi.connectivity.connectivitycontext.ConnectivityService to be added to list :type tapi_connectivity_connectivitycontext_connectivity_service: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivitycontext_connectivity_service = TapiConnectivityConnectivitycontextConnectivityService.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_put(uuid, tapi_connectivity_connectivitycontext_connectivity_service=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_put creates or updates tapi.connectivity.connectivitycontext.ConnectivityService # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_connectivity_connectivitycontext_connectivity_service: tapi.connectivity.connectivitycontext.ConnectivityService to be added or updated :type tapi_connectivity_connectivitycontext_connectivity_service: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivitycontext_connectivity_service = TapiConnectivityConnectivitycontextConnectivityService.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_burst_size_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_burst_size_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_burst_size_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_burst_size_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_burst_size_post(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_burst_size_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_burst_size_put(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_burst_size_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_information_rate_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_information_rate_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_information_rate_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_information_rate_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_information_rate_post(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_information_rate_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_information_rate_put(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_committed_information_rate_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_delete removes tapi.common.BandwidthProfile # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_get returns tapi.common.BandwidthProfile # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiCommonBandwidthProfile """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_burst_size_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_burst_size_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_burst_size_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_burst_size_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_burst_size_post(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_burst_size_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_burst_size_put(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_burst_size_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_post(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_put(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_post(uuid, tapi_common_bandwidth_profile=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_post creates tapi.common.BandwidthProfile # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_bandwidth_profile: tapi.common.BandwidthProfile to be added to list :type tapi_common_bandwidth_profile: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_bandwidth_profile = TapiCommonBandwidthProfile.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_put(uuid, tapi_common_bandwidth_profile=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_put creates or updates tapi.common.BandwidthProfile # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_bandwidth_profile: tapi.common.BandwidthProfile to be added or updated :type tapi_common_bandwidth_profile: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_bandwidth_profile = TapiCommonBandwidthProfile.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_delete removes tapi.common.Capacity # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_get returns tapi.common.Capacity # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiCommonCapacity """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_post(uuid, tapi_common_capacity=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_post creates tapi.common.Capacity # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity: tapi.common.Capacity to be added to list :type tapi_common_capacity: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity = TapiCommonCapacity.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_put(uuid, tapi_common_capacity=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_put creates or updates tapi.common.Capacity # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity: tapi.common.Capacity to be added or updated :type tapi_common_capacity: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity = TapiCommonCapacity.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_total_size_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_total_size_delete removes tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_total_size_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_total_size_get returns tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiCommonCapacityValue """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_total_size_post(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_total_size_post creates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added to list :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_total_size_put(uuid, tapi_common_capacity_value=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_total_size_put creates or updates tapi.common.CapacityValue # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_capacity_value: tapi.common.CapacityValue to be added or updated :type tapi_common_capacity_value: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_capacity_value = TapiCommonCapacityValue.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_resilience_type_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_resilience_type_delete removes tapi.topology.ResilienceType # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_resilience_type_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_resilience_type_get returns tapi.topology.ResilienceType # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiTopologyResilienceType """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_resilience_type_post(uuid, tapi_topology_resilience_type=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_resilience_type_post creates tapi.topology.ResilienceType # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_topology_resilience_type: tapi.topology.ResilienceType to be added to list :type tapi_topology_resilience_type: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_resilience_type = TapiTopologyResilienceType.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_resilience_type_put(uuid, tapi_topology_resilience_type=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_resilience_type_put creates or updates tapi.topology.ResilienceType # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_topology_resilience_type: tapi.topology.ResilienceType to be added or updated :type tapi_topology_resilience_type: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_resilience_type = TapiTopologyResilienceType.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristic_post(uuid, tapi_topology_risk_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristic_post creates tapi.topology.RiskCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_topology_risk_characteristic: tapi.topology.RiskCharacteristic to be added to list :type tapi_topology_risk_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_risk_characteristic = TapiTopologyRiskCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristicrisk_characteristic_name_delete(uuid, risk_characteristic_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristicrisk_characteristic_name_delete removes tapi.topology.RiskCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param risk_characteristic_name: Id of risk-diversity-characteristic :type risk_characteristic_name: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristicrisk_characteristic_name_get(uuid, risk_characteristic_name): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristicrisk_characteristic_name_get returns tapi.topology.RiskCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param risk_characteristic_name: Id of risk-diversity-characteristic :type risk_characteristic_name: str :rtype: TapiTopologyRiskCharacteristic """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristicrisk_characteristic_name_post(uuid, risk_characteristic_name, tapi_topology_risk_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristicrisk_characteristic_name_post creates tapi.topology.RiskCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param risk_characteristic_name: Id of risk-diversity-characteristic :type risk_characteristic_name: str :param tapi_topology_risk_characteristic: tapi.topology.RiskCharacteristic to be added to list :type tapi_topology_risk_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_risk_characteristic = TapiTopologyRiskCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristicrisk_characteristic_name_put(uuid, risk_characteristic_name, tapi_topology_risk_characteristic=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_risk_diversity_characteristicrisk_characteristic_name_put creates or updates tapi.topology.RiskCharacteristic # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param risk_characteristic_name: Id of risk-diversity-characteristic :type risk_characteristic_name: str :param tapi_topology_risk_characteristic: tapi.topology.RiskCharacteristic to be added or updated :type tapi_topology_risk_characteristic: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_topology_risk_characteristic = TapiTopologyRiskCharacteristic.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_schedule_delete(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_schedule_delete removes tapi.common.TimeRange # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: None """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_schedule_get(uuid): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_schedule_get returns tapi.common.TimeRange # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :rtype: TapiCommonTimeRange """ return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_schedule_post(uuid, tapi_common_time_range=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_schedule_post creates tapi.common.TimeRange # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_time_range: tapi.common.TimeRange to be added to list :type tapi_common_time_range: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_time_range = TapiCommonTimeRange.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_connectivity_serviceuuid_schedule_put(uuid, tapi_common_time_range=None): # noqa: E501 """data_context_connectivity_context_connectivity_serviceuuid_schedule_put creates or updates tapi.common.TimeRange # noqa: E501 :param uuid: Id of connectivity-service :type uuid: str :param tapi_common_time_range: tapi.common.TimeRange to be added or updated :type tapi_common_time_range: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_common_time_range = TapiCommonTimeRange.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_delete(): # noqa: E501 """data_context_connectivity_context_delete removes tapi.connectivity.ConnectivityContext # noqa: E501 :rtype: None """ return 'do some magic!' def data_context_connectivity_context_get(): # noqa: E501 """data_context_connectivity_context_get returns tapi.connectivity.ConnectivityContext # noqa: E501 :rtype: TapiConnectivityConnectivityContext """ return 'do some magic!' def data_context_connectivity_context_post(tapi_connectivity_connectivity_context=None): # noqa: E501 """data_context_connectivity_context_post creates tapi.connectivity.ConnectivityContext # noqa: E501 :param tapi_connectivity_connectivity_context: tapi.connectivity.ConnectivityContext to be added to list :type tapi_connectivity_connectivity_context: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivity_context = TapiConnectivityConnectivityContext.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_connectivity_context_put(tapi_connectivity_connectivity_context=None): # noqa: E501 """data_context_connectivity_context_put creates or updates tapi.connectivity.ConnectivityContext # noqa: E501 :param tapi_connectivity_connectivity_context: tapi.connectivity.ConnectivityContext to be added or updated :type tapi_connectivity_connectivity_context: dict | bytes :rtype: None """ if connexion.request.is_json: tapi_connectivity_connectivity_context = TapiConnectivityConnectivityContext.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_aggregated_connection_end_pointtopology_uuidaggregated_connection_end_point_node_uuidnode_edge_point_uuidaggregated_connection_end_point_connection_end_point_uuid_get(uuid, node_uuid, owned_node_edge_point_uuid, connection_end_point_uuid, topology_uuid, aggregated_connection_end_point_node_uuid, node_edge_point_uuid, aggregated_connection_end_point_connection_end_point_uuid): # noqa: E501 """data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_aggregated_connection_end_pointtopology_uuidaggregated_connection_end_point_node_uuidnode_edge_point_uuidaggregated_connection_end_point_connection_end_point_uuid_get returns tapi.connectivity.ConnectionEndPointRef # noqa: E501 :param uuid: Id of topology :type uuid: str :param node_uuid: Id of node :type node_uuid: str :param owned_node_edge_point_uuid: Id of owned-node-edge-point :type owned_node_edge_point_uuid: str :param connection_end_point_uuid: Id of connection-end-point :type connection_end_point_uuid: str :param topology_uuid: Id of aggregated-connection-end-point :type topology_uuid: str :param aggregated_connection_end_point_node_uuid: Id of aggregated-connection-end-point :type aggregated_connection_end_point_node_uuid: str :param node_edge_point_uuid: Id of aggregated-connection-end-point :type node_edge_point_uuid: str :param aggregated_connection_end_point_connection_end_point_uuid: Id of aggregated-connection-end-point :type aggregated_connection_end_point_connection_end_point_uuid: str :rtype: TapiConnectivityConnectionEndPointRef """ return 'do some magic!' def data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_client_node_edge_pointtopology_uuidclient_node_edge_point_node_uuidnode_edge_point_uuid_get(uuid, node_uuid, owned_node_edge_point_uuid, connection_end_point_uuid, topology_uuid, client_node_edge_point_node_uuid, node_edge_point_uuid): # noqa: E501 """data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_client_node_edge_pointtopology_uuidclient_node_edge_point_node_uuidnode_edge_point_uuid_get returns tapi.topology.NodeEdgePointRef # noqa: E501 :param uuid: Id of topology :type uuid: str :param node_uuid: Id of node :type node_uuid: str :param owned_node_edge_point_uuid: Id of owned-node-edge-point :type owned_node_edge_point_uuid: str :param connection_end_point_uuid: Id of connection-end-point :type connection_end_point_uuid: str :param topology_uuid: Id of client-node-edge-point :type topology_uuid: str :param client_node_edge_point_node_uuid: Id of client-node-edge-point :type client_node_edge_point_node_uuid: str :param node_edge_point_uuid: Id of client-node-edge-point :type node_edge_point_uuid: str :rtype: TapiTopologyNodeEdgePointRef """ return 'do some magic!' def data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_get(uuid, node_uuid, owned_node_edge_point_uuid, connection_end_point_uuid): # noqa: E501 """data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_get returns tapi.connectivity.ceplist.ConnectionEndPoint # noqa: E501 :param uuid: Id of topology :type uuid: str :param node_uuid: Id of node :type node_uuid: str :param owned_node_edge_point_uuid: Id of owned-node-edge-point :type owned_node_edge_point_uuid: str :param connection_end_point_uuid: Id of connection-end-point :type connection_end_point_uuid: str :rtype: TapiConnectivityCeplistConnectionEndPoint """ return 'do some magic!' def data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_namevalue_name_get(uuid, node_uuid, owned_node_edge_point_uuid, connection_end_point_uuid, value_name): # noqa: E501 """data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_namevalue_name_get returns tapi.common.NameAndValue # noqa: E501 :param uuid: Id of topology :type uuid: str :param node_uuid: Id of node :type node_uuid: str :param owned_node_edge_point_uuid: Id of owned-node-edge-point :type owned_node_edge_point_uuid: str :param connection_end_point_uuid: Id of connection-end-point :type connection_end_point_uuid: str :param value_name: Id of name :type value_name: str :rtype: TapiCommonNameAndValue """ return 'do some magic!' def data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_parent_node_edge_point_get(uuid, node_uuid, owned_node_edge_point_uuid, connection_end_point_uuid): # noqa: E501 """data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_connection_end_pointconnection_end_point_uuid_parent_node_edge_point_get returns tapi.topology.NodeEdgePointRef # noqa: E501 :param uuid: Id of topology :type uuid: str :param node_uuid: Id of node :type node_uuid: str :param owned_node_edge_point_uuid: Id of owned-node-edge-point :type owned_node_edge_point_uuid: str :param connection_end_point_uuid: Id of connection-end-point :type connection_end_point_uuid: str :rtype: TapiTopologyNodeEdgePointRef """ return 'do some magic!' def data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_get(uuid, node_uuid, owned_node_edge_point_uuid): # noqa: E501 """data_context_topology_context_topologyuuid_nodenode_uuid_owned_node_edge_pointowned_node_edge_point_uuid_cep_list_get returns tapi.connectivity.context.topologycontext.topology.node.ownednodeedgepoint.CepList # noqa: E501 :param uuid: Id of topology :type uuid: str :param node_uuid: Id of node :type node_uuid: str :param owned_node_edge_point_uuid: Id of owned-node-edge-point :type owned_node_edge_point_uuid: str :rtype: TapiConnectivityContextTopologycontextTopologyNodeOwnednodeedgepointCepList """ return 'do some magic!' def operations_create_connectivity_service_post(inline_object1=None): # noqa: E501 """operations_create_connectivity_service_post # noqa: E501 :param inline_object1: :type inline_object1: dict | bytes :rtype: TapiConnectivityCreateConnectivityService """ if connexion.request.is_json: inline_object1 = InlineObject1.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def operations_delete_connectivity_service_post(inline_object6=None): # noqa: E501 """operations_delete_connectivity_service_post # noqa: E501 :param inline_object6: :type inline_object6: dict | bytes :rtype: None """ if connexion.request.is_json: inline_object6 = InlineObject6.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!' def operations_get_connection_details_post(inline_object12=None): # noqa: E501 """operations_get_connection_details_post # noqa: E501 :param inline_object12: :type inline_object12: dict | bytes :rtype: TapiConnectivityGetConnectionDetails """ if connexion.request.is_json: inline_object12 = InlineObject12.from_dict(connexion.request.get_json()) # noqa: E501 return TapiConnectivityGetConnectionDetails(TapiConnectivityGetconnectiondetailsOutput( database.connection(inline_object12.input.connection_id_or_name))) def operations_get_connection_end_point_details_post(inline_object13=None): # noqa: E501 """operations_get_connection_end_point_details_post # noqa: E501 :param inline_object13: :type inline_object13: dict | bytes :rtype: TapiConnectivityGetConnectionEndPointDetails """ if connexion.request.is_json: inline_object13 = InlineObject13.from_dict(connexion.request.get_json()) # noqa: E501 return TapiConnectivityGetConnectionEndPointDetails(TapiConnectivityGetconnectionendpointdetailsOutput( database.connection_end_point(inline_object13.input.topology_id_or_name, inline_object13.input.node_id_or_name, inline_object13.input.nep_id_or_name, inline_object13.input.cep_id_or_name))) def operations_get_connectivity_service_details_post(inline_object14=None): # noqa: E501 """operations_get_connectivity_service_details_post # noqa: E501 :param inline_object14: :type inline_object14: dict | bytes :rtype: TapiConnectivityGetConnectivityServiceDetails """ if connexion.request.is_json: inline_object14 = InlineObject14.from_dict(connexion.request.get_json()) # noqa: E501 return TapiConnectivityGetConnectivityServiceDetails(TapiConnectivityGetconnectivityservicedetailsOutput( database.connectivity_service(inline_object14.input.service_id_or_name))) def operations_get_connectivity_service_list_post(): # noqa: E501 """operations_get_connectivity_service_list_post # noqa: E501 :rtype: TapiConnectivityGetConnectivityServiceList """ return TapiConnectivityGetConnectivityServiceList(TapiConnectivityGetconnectivityservicelistOutput( database.connectivity_service_list())) def operations_update_connectivity_service_post(inline_object27=None): # noqa: E501 """operations_update_connectivity_service_post # noqa: E501 :param inline_object27: :type inline_object27: dict | bytes :rtype: TapiConnectivityUpdateConnectivityService """ if connexion.request.is_json: inline_object27 = InlineObject27.from_dict(connexion.request.get_json()) # noqa: E501 return 'do some magic!'
176082
from enum import IntEnum import struct from .parser import MsftBandParser from datetime import datetime from .filetimes import datetime_to_filetime class NotificationTypes(IntEnum): """Complete list of all Notification types""" SMS = 1 Email = 2 IncomingCall = 11 AnsweredCall = 12 MissedCall = 13 HangupCall = 14 Voicemail = 15 CalendarEventAdd = 16 CalendarClear = 17 Messaging = 18 GenericDialog = 100 GenericUpdate = 101 GenericClearTile = 102 GenericClearPage = 103 class Notification: guid = None notification_type = NotificationTypes.GenericDialog def serialize(self): return struct.pack("<H", self.notification_type) + self.guid.bytes_le class MessagingNotification(Notification): notification_type = NotificationTypes.Messaging datetime = None def __init__(self, guid, title='', text=''): self.guid = guid self.title = title[:20] self.text = text[:20] self.datetime = datetime.now() def serialize(self): packet = super().serialize() packet += struct.pack("H", len(self.title) * 2) packet += struct.pack("H", len(self.text) * 2) packet += struct.pack("<Qxx", datetime_to_filetime(self.datetime)) packet += MsftBandParser.serialize_text(self.title + self.text) return packet class GenericClearTileNotification(Notification): notification_type = NotificationTypes.GenericClearTile def __init__(self, guid): self.guid = guid
176089
class Solution: def rob(self, num): ls = [[0, 0]] for e in num: ls.append([max(ls[-1][0], ls[-1][1]), ls[-1][0] + e]) return max(ls[-1])
176099
import torch.nn as nn def conv_relu(in_channels, out_channels, kernel_size=3, stride=1, padding=1, bias=True): return [ nn.Conv2d(in_channels, out_channels, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias), nn.ReLU(inplace=True), ] def conv_bn_relu(in_channels, out_channels, kernel_size=3, stride=1, padding=1, bias=False): return [ nn.Conv2d(in_channels, out_channels, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias), nn.BatchNorm2d(out_channels), nn.ReLU(inplace=True), ] def linear_bn_relu_drop(in_channels, out_channels, dropout=0.5, bias=False): layers = [ nn.Linear(in_channels, out_channels, bias=bias), nn.BatchNorm1d(out_channels), nn.ReLU(inplace=True) ] if dropout > 0: layers.append(nn.Dropout(dropout)) return layers
176171
from pathlib import Path from typing import Tuple import re from itertools import groupby def find_suggestion_for_return(suggestions): for s in suggestions: if s.symbol_kind == "class-or-function": return s else: return None def annotate_line(line, suggestions): para_suggestions = sorted( (s for s in suggestions if s.symbol_kind == "parameter"), key=lambda x: x.file_location[1] ) annotated_line = annotate_parameters(line, para_suggestions) ret_suggestion = find_suggestion_for_return(suggestions) if ret_suggestion is not None: annotated_line = annotate_return(annotated_line, ret_suggestion) return annotated_line def insert_at(original, inserted, idx): return original[:idx] + inserted + original[idx:] def annotate_parameters(line, suggestions): """ Annotate the parameters of a function on a particular line """ annotated_line = " " + line length_increase = 0 for s in suggestions: assert line[s.file_location[1] :].startswith(s.name) insertion_position = s.file_location[1] + len(s.name) + 1 + length_increase annotated_line = insert_at(annotated_line, f": {s.suggestion}", insertion_position) length_increase += len(s.suggestion) + 2 return annotated_line def annotate_return(line, suggestion): """ Annotate the return of a function """ assert line.rstrip().endswith(":") return line.rstrip()[:-1] + f" -> {suggestion.suggestion}" + ":\n" def find_annotation_line(filepath, location, func_name): with open(filepath) as f: lines = f.readlines() assert func_name in lines[location[0] - 1] # Assume that the function's return is *not* already annotated. func_def_end = re.compile(r"\)\s*:$") annotation_lineno = location[0] while annotation_lineno <= len(lines): if func_def_end.search(lines[annotation_lineno - 1].rstrip()) is not None: break annotation_lineno += 1 else: raise Exception("Cannot find the closing brace for the parameter list.") return annotation_lineno def group_suggestions(suggestions): def key(s): return s.filepath + str(s.annotation_lineno) sorted_suggestions = sorted(suggestions, key=key) return [list(it) for k, it in groupby(sorted_suggestions, key)] ALIASES = {"typing.Text": "str"} def annotation_rewrite(annotation: str) -> str: for k, v in ALIASES.items(): annotation = annotation.replace(k, v) return annotation
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import torch import torchvision.transforms as T import numpy as np import cv2 from PIL import Image class DictBatch(object): def __init__(self, data): """ :param data: list of Dict of Tensors. """ self.keys = list(data[0].keys()) values = list(zip(*[list(d.values()) for d in data])) for idx, key in enumerate(self.keys): setattr(self, key, torch.cat(values[idx], dim=0)) def pin_memory(self): for key in self.keys: attr = getattr(self, key).pin_memory() setattr(self, key, attr) return self def cuda(self): for key in self.keys: attr = getattr(self, key).cuda() setattr(self, key, attr) return self def keys(self): return self.keys def __getitem__(self, key): """ :param key: str """ return getattr(self, key, None) def collate_dict_wrapper(batch): return DictBatch(batch) class ResizeNormalize(object): def __init__(self, size, use_cuda=False, normalize_rgb_values=False, toPIL=False, rgb_scaler=1.0): ''' Used to resize, normalize and convert raw pixel observations. :param x: Numpy array to be processed :param size: int or tuple, (height,width) size :param use_cuda: Boolean to determine whether to create Cuda Tensor :param normalize_rgb_values: Maps the 0-255 values of rgb colours to interval (0-1) ''' if isinstance(size, int): size = (size,size) ts = [] if toPIL: ts.append(T.ToPILImage()) ts.append(T.Resize(size=size)) ts.append(T.ToTensor()) self.scaling_operation = T.Compose(ts) self.normalize_rgb_values = normalize_rgb_values self.rgb_scaler = rgb_scaler self.use_cuda = use_cuda def __call__(self, x): x = self.scaling_operation(x) # WATCHOUT: it is necessary to cast the tensor into float before doing # the division, otherwise the result is yielded as a uint8 (full of zeros...) x = x.type(torch.FloatTensor) x = x / 255. if self.normalize_rgb_values else x x *= self.rgb_scaler if self.use_cuda: return x.cuda() return x def __repr__(self): return self.__class__.__name__ + '()' class AddEgocentricInvariance(object): def __init__(self, marker_demisize=2): ''' Add a central marker to enable egocentric invariance. :param marker_demisize: Int, half the size of the marker. ''' self.marker_demisize = marker_demisize def __call__(self, x): x = np.array(x) dim = x.shape[-2] xmax = x.max() marker_colour = 0 if x.mean() > 127 else xmax start = int(dim//2-self.marker_demisize) end = int(dim//2+self.marker_demisize) x[start:end, :, ...] = marker_colour x[:,start:end, ...] = marker_colour x = Image.fromarray(x.astype('uint8')) return x def __repr__(self): return self.__class__.__name__ + '()' class Rescale(object) : def __init__(self, output_size) : assert( isinstance(output_size, (int, tuple) ) ) self.output_size = output_size def __call__(self, sample) : image = sample h,w = image.shape[:2] new_h, new_w = self.output_size img = cv2.resize(image, (new_h, new_w) ) return img class RescaleNormalize(object): def __init__(self, size, use_cuda=False, normalize_rgb_values=False): ''' Used to resize, normalize and convert raw pixel observations. :param x: Numpy array to be processed :param size: int or tuple, (height,width) size :param use_cuda: Boolean to determine whether to create Cuda Tensor :param normalize_rgb_values: Maps the 0-255 values of rgb colours to interval (0-1) ''' if isinstance(size, int): size = (size,size) ts = [] ts.append(Rescale(output_size=size)) ts.append(T.ToTensor()) self.scaling_operation = T.Compose(ts) self.normalize_rgb_values = normalize_rgb_values self.use_cuda = use_cuda def __call__(self, x): x = self.scaling_operation(x) # WATCHOUT: it is necessary to cast the tensor into float before doing # the division, otherwise the result is yielded as a uint8 (full of zeros...) x = x.type(torch.FloatTensor) x = x / 255. if self.normalize_rgb_values else x if self.use_cuda: return x.cuda() return x def __repr__(self): return self.__class__.__name__ + '()'
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from netaddr import IPAddress def test_reverse_dns_v4(): assert IPAddress('172.24.0.13').reverse_dns == '192.168.3.11.in-addr.arpa.' def test_reverse_dns_v6(): assert IPAddress('fe80::feeb:daed').reverse_dns == ('d.e.a.d.b.e.e.f.0.0.0.0.0.0.0.0.' '0.0.0.0.0.0.0.0.0.0.0.0.0.8.e.f.' 'ip6.arpa.')
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def main(): # equilibrate then isolate cold finger info('Equilibrate then isolate coldfinger') close(name="C", description="Bone to Turbo") sleep(1) open(name="B", description="Bone to Diode Laser") sleep(20) close(name="B", description="Bone to Diode Laser")
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import vcs import sys import os # This test checks that png size is indeed controled by user import struct def get_image_info(fnm): data = open(fnm,"rb").read() w, h = struct.unpack('>LL', data[16:24]) width = int(w) height = int(h) return width, height x=vcs.init() x.drawlogooff() x.setantialiasing(0) x.plot([1,2,3,4,5,4,3,2,1],bg=1) fnm = "test_png_set_size.png" x.png(fnm,width=15) print get_image_info(fnm) assert(get_image_info(fnm) == (15,11)) x.png(fnm,height=16) print get_image_info(fnm) assert(get_image_info(fnm) == (20,16)) x.png(fnm,width=15,height=12) print get_image_info(fnm) assert(get_image_info(fnm) == (15,12)) os.remove(fnm)
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import nose.tools as nt import numpy as np import theano import theano.tensor as T import treeano import treeano.nodes as tn from treeano.sandbox.nodes import resnet fX = theano.config.floatX def test_zero_last_axis_partition_node(): network = tn.SequentialNode( "s", [tn.InputNode("i", shape=(None,)), resnet._ZeroLastAxisPartitionNode("z", zero_ratio=0.5, axis=0)] ).network() fn = network.function(["i"], ["s"]) x = np.arange(10).astype(fX) ans = x.copy() ans[5:] = 0 np.testing.assert_allclose(ans, fn(x)[0])
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import os from dataloaders.visual_genome import VG, vg_collate from lib.utils import define_model, load_ckpt, do_test from config import cfg from torch.utils.data import DataLoader test_data = VG(cfg.test_data_name, num_val_im=5000, filter_duplicate_rels=True, use_proposals=cfg.use_proposals, filter_non_overlap=cfg.mode == 'sgdet', num_im=cfg.num_im) test_loader = DataLoader( dataset=test_data, batch_size=cfg.num_gpus, shuffle=False, num_workers=cfg.num_workers, collate_fn=lambda x: vg_collate(x, mode='rel', num_gpus=cfg.num_gpus, is_train=True if cfg.test_data_name == 'train' else False), drop_last=True, pin_memory=True, ) if cfg.cache is not None and os.path.exists(cfg.cache): # No need to load model detector = None else: detector = define_model(cfg, test_data.ind_to_classes, test_data.ind_to_predicates) load_ckpt(detector, cfg.ckpt) detector.cuda() do_test(detector, test_data, test_loader)
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from abc import ABC from abc import abstractmethod class GAN(ABC): @property @abstractmethod def generators(self): raise NotImplementedError @property @abstractmethod def discriminators(self): raise NotImplementedError @abstractmethod def predict(self, inputs): raise NotImplementedError
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import numpy as np import pytest # noqa: F401 from pandas_datareader._utils import RemoteDataError from epymetheus.datasets import fetch_usstocks # -------------------------------------------------------------------------------- def test_toomanyasset(): """ Test if fetch_usstocks raises ValueError when n_asset is too many. """ with pytest.raises(ValueError): fetch_usstocks(n_assets=1000) def test_usstocks(): try: universe = fetch_usstocks(n_assets=2) assert not np.isnan(universe.values).any(axis=None) except RemoteDataError as e: print("Skip", e)
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from franka_interface_msgs.msg import SensorData, SensorDataGroup def sensor_proto2ros_msg(sensor_proto_msg, sensor_data_type, info=''): sensor_ros_msg = SensorData() sensor_ros_msg.type = sensor_data_type sensor_ros_msg.info = info sensor_data_bytes = sensor_proto_msg.SerializeToString() sensor_ros_msg.size = len(sensor_data_bytes) sensor_ros_msg.sensorData = sensor_data_bytes return sensor_ros_msg def make_sensor_group_msg(trajectory_generator_sensor_msg=None, feedback_controller_sensor_msg=None, termination_handler_sensor_msg=None): sensor_group_msg = SensorDataGroup() if trajectory_generator_sensor_msg is not None: sensor_group_msg.has_trajectory_generator_sensor_data = True sensor_group_msg.trajectoryGeneratorSensorData = trajectory_generator_sensor_msg if feedback_controller_sensor_msg is not None: sensor_group_msg.has_feedback_controller_sensor_data = True sensor_group_msg.feedbackControllerSensorData = feedback_controller_sensor_msg if termination_handler_sensor_msg is not None: sensor_group_msg.has_termination_handler_sensor_data = True sensor_group_msg.terminationHandlerSensorData = termination_handler_sensor_msg return sensor_group_msg
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import re def get_pars(text): pars = re.findall(r'\[[0-9]+\]\n*(.*)', text) pars = [p.strip() for p in pars] return pars def get_claims(text): claims = re.findall(r'.*claim.*', text, re.IGNORECASE) return claims def get_claim_body(text): match = re.search(r'^claim[s*]$', text, re.IGNORECASE | re.MULTILINE) try: claim = match.string[match.span()[0]:] claim = claim.replace('*', '') return claim except(AttributeError): return 'none' if __name__ == '__main__': import sys text = sys.stdin.read() for p in get_pars(text): print 'PARAGRAPH' print p for p in get_claims(text): print 'CLAIMS' print p print '---------' print get_claim_body(text)
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from petisco.base.domain.message.message import Message from petisco.base.domain.message.message_bus import MessageBus class NotImplementedMessageBus(MessageBus): def publish(self, message: Message): self._check_is_message(message) meta = self.get_configured_meta() _ = message.update_meta(meta) def retry_publish_only_on_store_queue(self, message: Message): self._check_is_message(message) meta = self.get_configured_meta() _ = message.update_meta(meta) def close(self): pass
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import asyncio import time from telegram import main import json from sql_util import get_phone, change_status from message_util import get_phone_test, cancel_all_recv from config import message_token from check_util import check_main from myLogger import log_main def run(phone, category): loop = asyncio.get_event_loop() loop.run_until_complete(main(phone, category)) loop.close() def loop_for_next_try(): n = 0 while True: n += 1 print('------็ฌฌ' + str(n) + 'ๆฌก------') log_main.logger.info('------็ฌฌ' + str(n) + 'ๆฌก------') time.sleep(5) # ๆ‰‹ๅŠจ่พ“ๅ…ฅๆ‰‹ๆœบๅท # phone = input("่ฏท่พ“ๅ…ฅๆ‰‹ๆœบๅท\n") # ไปŽๆ•ฐๆฎๅบ“ไธญ่Žทๅพ—ๆ‰‹ๆœบๅท category = 1 # phone, phone_id = get_phone(category) # ไปŽๆŽฅ็ ๅนณๅฐ่Žทๅ–ๆ‰‹ๆœบๅท print('ไปŽๆŽฅ็ ๅนณๅฐ่Žทๅ–ๆ‰‹ๆœบๅท...') try: cancel_all_recv(message_token) status, phone = get_phone_test(message_token) except Exception as e: print(e) continue if status != '1': print("ๆ‰‹ๆœบๅท่Žทๅ–ๅคฑ่ดฅ...") log_main.logger.error(str(phone) + "ๆ‰‹ๆœบๅท่Žทๅ–ๅคฑ่ดฅ...") continue try: # ๅ…ˆๅˆคๆ–ญ่ฏฅphoneๆ˜ฏๅฆๆณจๅ†Œ่ฟ‡ # if not check_main('8617121240943', phone): # print('่ฏฅๆ‰‹ๆœบๅทๆœชๆณจๅ†Œ') # change_status(phone_id, status=404) # else: run('86' + phone, category) # change_status(phone_id, status=1) except RuntimeError as e: print(e) log_main.logger.error(str(phone) + e.__str__()) # error = json.loads(e.__str__()) # error_code = error["error_code"] # msg = error["msg"] # print(msg) # ไฟฎๆ”นๆ•ฐๆฎๅบ“ไธญ็Šถๆ€ # change_status(phone_id, status=error_code) except Exception as e: print(e) log_main.logger.error(str(phone) + e.__str__()) if __name__ == '__main__': loop_for_next_try()
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import numpy as np import torch import torch.nn as nn from habitat_baselines.common.utils import Flatten from habitat_baselines.rl.models.simple_cnn import SimpleCNN class Contiguous(nn.Module): r"""Converts a tensor to be stored contiguously if it is not already so. """ def __init__(self): super(Contiguous, self).__init__() def forward(self, x): return x.contiguous() class SimpleAllCNN(SimpleCNN): r"""A Simple 3-Conv CNN followed by a fully connected layer. Takes in observations and produces an embedding of the rgb and/or depth components if they are present in the provided observations. Args: observation_space: The observation_space of the agent output_size: The size of the embedding vector """ def __init__(self, observation_space, output_size): nn.Module.__init__(self) if "rgb" in observation_space.spaces: self._n_input_rgb = observation_space.spaces["rgb"].shape[2] else: self._n_input_rgb = 0 if "depth" in observation_space.spaces: self._n_input_depth = observation_space.spaces["depth"].shape[2] else: self._n_input_depth = 0 cnn_dims = None if self._n_input_rgb > 0: cnn_dims = np.array( observation_space.spaces["rgb"].shape[:2], dtype=np.float32 ) elif self._n_input_depth > 0: cnn_dims = np.array( observation_space.spaces["depth"].shape[:2], dtype=np.float32 ) self._init_model(cnn_dims, output_size) def _init_model(self, cnn_dims, output_size): r"""cnn_dims: initial cnn dimensions. """ if self.is_blind: self.cnn = nn.Sequential() return # kernel size for different CNN layers self._cnn_layers_kernel_size = [(8, 8), (4, 4), (3, 3)] # strides for different CNN layers self._cnn_layers_stride = [(4, 4), (2, 2), (1, 1)] for kernel_size, stride in zip( self._cnn_layers_kernel_size, self._cnn_layers_stride ): cnn_dims = self._conv_output_dim( dimension=cnn_dims, padding=np.array([0, 0], dtype=np.float32), dilation=np.array([1, 1], dtype=np.float32), kernel_size=np.array(kernel_size, dtype=np.float32), stride=np.array(stride, dtype=np.float32), ) self.cnn = nn.Sequential( nn.Conv2d( in_channels=self._n_input_rgb + self._n_input_depth, out_channels=32, kernel_size=self._cnn_layers_kernel_size[0], stride=self._cnn_layers_stride[0], ), nn.ReLU(True), nn.Conv2d( in_channels=32, out_channels=64, kernel_size=self._cnn_layers_kernel_size[1], stride=self._cnn_layers_stride[1], ), nn.ReLU(True), nn.Conv2d( in_channels=64, out_channels=32, kernel_size=self._cnn_layers_kernel_size[2], stride=self._cnn_layers_stride[2], ), Contiguous(), Flatten(), nn.Linear(32 * cnn_dims[0] * cnn_dims[1], output_size), nn.ReLU(True), ) self.layer_init() class SimpleDepthCNN(SimpleAllCNN): r""" SimpleAllCNN where the only allowed input is a depth observation regardless of what other observation modalities are provided. """ def __init__(self, observation_space, output_size): nn.Module.__init__(self) assert ( "depth" in observation_space.spaces ), "Depth input required to use SimpleDepthCNN" self._n_input_depth = observation_space.spaces["depth"].shape[2] self._n_input_rgb = 0 cnn_dims = np.array( observation_space.spaces["depth"].shape[:2], dtype=np.float32 ) self._init_model(cnn_dims, output_size) def forward(self, observations): # permute tensor to dimension [BATCH x CHANNEL x HEIGHT X WIDTH] depth_observations = observations["depth"].permute(0, 3, 1, 2) return self.cnn(depth_observations) class SimpleRGBCNN(SimpleAllCNN): r""" SimpleAllCNN where the only allowed input is an RGB observation regardless of what other observation modalities are provided. """ def __init__(self, observation_space, output_size): nn.Module.__init__(self) assert ( "rgb" in observation_space.spaces ), "RGB input required to use SimpleRGBCNN" self._n_input_depth = 0 self._n_input_rgb = observation_space.spaces["rgb"].shape[2] cnn_dims = np.array(observation_space.spaces["rgb"].shape[:2], dtype=np.float32) self._init_model(cnn_dims, output_size) def forward(self, observations): # permute tensor to dimension [BATCH x CHANNEL x HEIGHT X WIDTH] rgb_observations = observations["rgb"].permute(0, 3, 1, 2) rgb_observations = rgb_observations / 255.0 # normalize RGB return self.cnn(rgb_observations)
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import time import cv2 import pyscreenshot as ImageGrab import numpy as np class Screenshot(object): def get_frame(self): img = np.array(ImageGrab.grab().convert('RGB'), dtype=np.uint8) img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR) ret2, jpeg = cv2.imencode('.jpg', img) return jpeg.tostring() def __del__(self): self.cam.release()
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import torch import numpy as np import torch.nn as nn import torch.nn.functional as F import GraphConv class DominantModel(nn.Module): def __init__(self, A_norm, dim_in, dim_out=16): super(DominantModel, self).__init__() self.gcn1 = GraphConv.GCN(A_norm, dim_in, 64) self.gcn2 = GraphConv.GCN(A_norm, 64, 32) self.gcn3 = GraphConv.GCN(A_norm, 32, dim_out) self.deconv = GraphConv.GCN(A_norm, dim_out, dim_in) def forward(self, X): X = self.gcn1(X) X = self.gcn2(X) Z = self.gcn3(X) return torch.sigmoid(Z.mm(Z.transpose(0, 1))), self.deconv(Z)
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from qgis.core import * from osgeo import gdal import math import numpy as np import os MARGIN = 0.01 def weightedFunction(x, y, x0, y0, weight): # the current weighted Function is a simple sqrt((x-x0)^1 + (y-y0)^2)/w return math.sqrt((x - x0) ** 2 + (y - y0) ** 2) / weight #Get the points vector layer pointsVector = QgsVectorLayer(sys.argv, 'points', 'ogr') #Add the vector layer to the map layer registry QgsProject.instance().addMapLayer(pointsVector) #get layer extents with a small margin to avoid ignoring points on bounding box's limit bounding_box = pointsVector.extent() extent_args = "-te " + str(bounding_box.xMinimum() - MARGIN) \ + " " + str(bounding_box.yMinimum() - MARGIN) \ + " " + str(bounding_box.xMaximum() + MARGIN) \ + " " + str(bounding_box.yMaximum() + MARGIN) os.system('gdal_rasterize -a z -ts 1000 1000 ' + extent_args + ' -l points "' + sys.argv + '" "./rasterPoints"') rasterPoints=QgsRasterLayer('./rasterPoints', 'rasterPoints') QgsProject.instance().addMapLayer(rasterPoints) dataset = gdal.Open('./rasterPoints') numpy_array = dataset.ReadAsArray() width, height = numpy_array.shape points = [] #get all the weighted points from the raster print("get the points with their weights from raster") for row in range(height): for col in range(width): if(numpy_array[row, col] != 0): print(str(numpy_array[row, col]) + " at point : " + str(row) + " , " + str(col)) points.append([row, col, numpy_array[row,col]]) print("compute the weighted distance grid for each point") distanceGrid = np.zeros(shape = (height, width)) for row in range(height): for col in range(width): index = 0 min_distance = weightedFunction(row, col, points[0][0], points[0][1], points[0][2]) for i in range(1, (len(points))): weightedDistance = weightedFunction(row, col, points[i][0], points[i][1], points[i][2]) if(weightedDistance < min_distance): min_distance = weightedDistance index = i distanceGrid[row, col] = index #save the distance grid as an output raster #output file name ( path to where to save the raster file ) print("save distance grid as raster GTiff") outFileName = './rasterVoronoi.tiff' #call the driver for the chosen format from GDAL driver = gdal.GetDriverByName('GTiff') #Create the file with dimensions of the input raster ( rasterized points ) output = driver.Create(outFileName, height, width, 1, gdal.GDT_Byte) #set the Raster transformation of the resulting raster output.SetGeoTransform(dataset.GetGeoTransform()) #set the projection of the resulting raster output.SetProjection(dataset.GetProjection()) #insert data to the resulting raster in band 1 from the weighted distance grid output.GetRasterBand(1).WriteArray(distanceGrid) #Call the raster output file rasterVoronoi = QgsRasterLayer('./rasterVoronoi.tiff', 'weighted Raster') #Add it to the map layer registry ( display it on the map) QgsProject.instance().addMapLayer(rasterVoronoi) #polygonize the result raster print("convert raster to shapefile") os.system('gdal_polygonize.bat ./rasterVoronoi.tiff ./WeightedVoronoi.shp -b 1 -f "ESRI Shapefile" weighted') weightedVoronoiVector = QgsVectorLayer('./WeightedVoronoi.shp', 'weighted voronoi', 'ogr') #load the vector weighted voronoi diagram QgsProject.instance().addMapLayer(weightedVoronoiVector) print("End of script")
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import warnings from math import ceil import numpy as np import openmdao.api as om from wisdem.landbosse.model.Manager import Manager from wisdem.landbosse.model.DefaultMasterInputDict import DefaultMasterInputDict from wisdem.landbosse.landbosse_omdao.OpenMDAODataframeCache import OpenMDAODataframeCache from wisdem.landbosse.landbosse_omdao.WeatherWindowCSVReader import read_weather_window with warnings.catch_warnings(): warnings.filterwarnings("ignore", message="numpy.ufunc size changed") import pandas as pd use_default_component_data = -1.0 class LandBOSSE(om.Group): def setup(self): # Add a tower section height variable. The default value of 30 m is for transportable tower sections. self.set_input_defaults("tower_section_length_m", 30.0, units="m") self.set_input_defaults("blade_drag_coefficient", use_default_component_data) # Unitless self.set_input_defaults("blade_lever_arm", use_default_component_data, units="m") self.set_input_defaults("blade_install_cycle_time", use_default_component_data, units="h") self.set_input_defaults("blade_offload_hook_height", use_default_component_data, units="m") self.set_input_defaults("blade_offload_cycle_time", use_default_component_data, units="h") self.set_input_defaults("blade_drag_multiplier", use_default_component_data) # Unitless self.set_input_defaults("turbine_spacing_rotor_diameters", 4) self.set_input_defaults("row_spacing_rotor_diameters", 10) self.set_input_defaults("commissioning_pct", 0.01) self.set_input_defaults("decommissioning_pct", 0.15) self.set_input_defaults("trench_len_to_substation_km", 50.0, units="km") self.set_input_defaults("interconnect_voltage_kV", 130.0, units="kV") self.set_input_defaults("foundation_height", 0.0, units="m") self.set_input_defaults("blade_mass", 8000.0, units="kg") self.set_input_defaults("hub_mass", 15.4e3, units="kg") self.set_input_defaults("nacelle_mass", 50e3, units="kg") self.set_input_defaults("tower_mass", 240e3, units="kg") self.set_input_defaults("turbine_rating_MW", 1500.0, units="kW") self.add_subsystem("landbosse", LandBOSSE_API(), promotes=["*"]) class LandBOSSE_API(om.ExplicitComponent): def setup(self): # Clear the cache OpenMDAODataframeCache._cache = {} self.setup_inputs() self.setup_outputs() self.setup_discrete_outputs() self.setup_discrete_inputs_that_are_not_dataframes() self.setup_discrete_inputs_that_are_dataframes() def setup_inputs(self): """ This method sets up the inputs. """ self.add_input("blade_drag_coefficient", use_default_component_data) # Unitless self.add_input("blade_lever_arm", use_default_component_data, units="m") self.add_input("blade_install_cycle_time", use_default_component_data, units="h") self.add_input("blade_offload_hook_height", use_default_component_data, units="m") self.add_input("blade_offload_cycle_time", use_default_component_data, units="h") self.add_input("blade_drag_multiplier", use_default_component_data) # Unitless # Even though LandBOSSE doesn't use foundation height, TowerSE does, # and foundation height can be used with hub height to calculate # tower height. self.add_input("foundation_height", 0.0, units="m") self.add_input("tower_section_length_m", 30.0, units="m") self.add_input("nacelle_mass", 0.0, units="kg") self.add_input("tower_mass", 0.0, units="kg") # A discrete input below, number_of_blades, gives the number of blades # on the rotor. # # The total mass of the rotor nacelle assembly (RNA) is the following # sum: # # (blade_mass * number_of_blades) + nac_mass + hub_mass self.add_input("blade_mass", use_default_component_data, units="kg", desc="The mass of one rotor blade.") self.add_input("hub_mass", use_default_component_data, units="kg", desc="Mass of the rotor hub") self.add_input( "crane_breakdown_fraction", val=0.0, desc="0 means the crane is never broken down. 1 means it is broken down every turbine.", ) self.add_input("construct_duration", val=9, desc="Total project construction time (months)") self.add_input("hub_height_meters", val=80, units="m", desc="Hub height m") self.add_input("rotor_diameter_m", val=77, units="m", desc="Rotor diameter m") self.add_input("wind_shear_exponent", val=0.2, desc="Wind shear exponent") self.add_input("turbine_rating_MW", val=1.5, units="MW", desc="Turbine rating MW") self.add_input("fuel_cost_usd_per_gal", val=1.5, desc="Fuel cost USD/gal") self.add_input( "breakpoint_between_base_and_topping_percent", val=0.8, desc="Breakpoint between base and topping (percent)" ) # Could not place units in turbine_spacing_rotor_diameters self.add_input("turbine_spacing_rotor_diameters", desc="Turbine spacing (times rotor diameter)", val=4) self.add_input("depth", units="m", desc="Foundation depth m", val=2.36) self.add_input("rated_thrust_N", units="N", desc="Rated Thrust (N)", val=5.89e5) # Can't set units self.add_input("bearing_pressure_n_m2", desc="Bearing Pressure (n/m2)", val=191521) self.add_input("gust_velocity_m_per_s", units="m/s", desc="50-year Gust Velocity (m/s)", val=59.5) self.add_input("road_length_adder_m", units="m", desc="Road length adder (m)", val=5000) # Can't set units self.add_input("fraction_new_roads", desc="Percent of roads that will be constructed (0.0 - 1.0)", val=0.33) self.add_input("road_quality", desc="Road Quality (0-1)", val=0.6) self.add_input("line_frequency_hz", units="Hz", desc="Line Frequency (Hz)", val=60) # Can't set units self.add_input("row_spacing_rotor_diameters", desc="Row spacing (times rotor diameter)", val=10) self.add_input( "trench_len_to_substation_km", units="km", desc="Combined Homerun Trench Length to Substation (km)", val=50 ) self.add_input("distance_to_interconnect_mi", units="mi", desc="Distance to interconnect (miles)", val=5) self.add_input("interconnect_voltage_kV", units="kV", desc="Interconnect Voltage (kV)", val=130) self.add_input( "critical_speed_non_erection_wind_delays_m_per_s", units="m/s", desc="Non-Erection Wind Delay Critical Speed (m/s)", val=15, ) self.add_input( "critical_height_non_erection_wind_delays_m", units="m", desc="Non-Erection Wind Delay Critical Height (m)", val=10, ) self.add_discrete_input("road_distributed_winnd", val=False) self.add_input("road_width_ft", units="ft", desc="Road width (ft)", val=20) self.add_input("road_thickness", desc="Road thickness (in)", val=8) self.add_input("crane_width", units="m", desc="Crane width (m)", val=12.2) self.add_input("overtime_multiplier", desc="Overtime multiplier", val=1.4) self.add_input("markup_contingency", desc="Markup contingency", val=0.03) self.add_input("markup_warranty_management", desc="Markup warranty management", val=0.0002) self.add_input("markup_sales_and_use_tax", desc="Markup sales and use tax", val=0) self.add_input("markup_overhead", desc="Markup overhead", val=0.05) self.add_input("markup_profit_margin", desc="Markup profit margin", val=0.05) self.add_input("Mass tonne", val=(1.0,), desc="", units="t") self.add_input( "development_labor_cost_usd", val=1e6, desc="The cost of labor in the development phase", units="USD" ) # Disabled due to Pandas conflict right now. self.add_input("labor_cost_multiplier", val=1.0, desc="Labor cost multiplier") self.add_input("commissioning_pct", 0.01) self.add_input("decommissioning_pct", 0.15) def setup_discrete_inputs_that_are_not_dataframes(self): """ This method sets up the discrete inputs that aren't dataframes. """ self.add_discrete_input("num_turbines", val=100, desc="Number of turbines in project") # Since 3 blades are so common on rotors, that is a reasonable default # value that will not need to be checked during component list # assembly. self.add_discrete_input("number_of_blades", val=3, desc="Number of blades on the rotor") self.add_discrete_input( "user_defined_home_run_trench", val=0, desc="Flag for user-defined home run trench length (0 = no; 1 = yes)" ) self.add_discrete_input( "allow_same_flag", val=False, desc="Allow same crane for base and topping (True or False)", ) self.add_discrete_input( "hour_day", desc="Dictionary of normal and long hours for construction in a day in the form of {'long': 24, 'normal': 10}", val={"long": 24, "normal": 10}, ) self.add_discrete_input( "time_construct", desc="One of the keys in the hour_day dictionary to specify how many hours per day construction happens.", val="normal", ) self.add_discrete_input( "user_defined_distance_to_grid_connection", desc="Flag for user-defined home run trench length (True or False)", val=False, ) # Could not place units in rate_of_deliveries self.add_discrete_input("rate_of_deliveries", val=10, desc="Rate of deliveries (turbines per week)") self.add_discrete_input("new_switchyard", desc="New Switchyard (True or False)", val=True) self.add_discrete_input("num_hwy_permits", desc="Number of highway permits", val=10) self.add_discrete_input("num_access_roads", desc="Number of access roads", val=2) def setup_discrete_inputs_that_are_dataframes(self): """ This sets up the default inputs that are dataframes. They are separate because they hold the project data and the way we need to hold their data is different. They have defaults loaded at the top of the file which can be overridden outside by setting the properties listed below. """ # Read in default sheets for project data default_project_data = OpenMDAODataframeCache.read_all_sheets_from_xlsx("ge15_public") self.add_discrete_input( "site_facility_building_area_df", val=default_project_data["site_facility_building_area"], desc="site_facility_building_area DataFrame", ) self.add_discrete_input( "components", val=default_project_data["components"], desc="Dataframe of components for tower, blade, nacelle", ) self.add_discrete_input( "crane_specs", val=default_project_data["crane_specs"], desc="Dataframe of specifications of cranes" ) self.add_discrete_input( "weather_window", val=read_weather_window(default_project_data["weather_window"]), desc="Dataframe of wind toolkit data", ) self.add_discrete_input("crew", val=default_project_data["crew"], desc="Dataframe of crew configurations") self.add_discrete_input( "crew_price", val=default_project_data["crew_price"], desc="Dataframe of costs per hour for each type of worker.", ) self.add_discrete_input( "equip", val=default_project_data["equip"], desc="Collections of equipment to perform erection operations." ) self.add_discrete_input( "equip_price", val=default_project_data["equip_price"], desc="Prices for various type of equipment." ) self.add_discrete_input("rsmeans", val=default_project_data["rsmeans"], desc="RSMeans price data") self.add_discrete_input( "cable_specs", val=default_project_data["cable_specs"], desc="cable specs for collection system" ) self.add_discrete_input( "material_price", val=default_project_data["material_price"], desc="Prices of materials for foundations and roads", ) self.add_discrete_input("project_data", val=default_project_data, desc="Dictionary of all dataframes of data") def setup_outputs(self): """ This method sets up the continuous outputs. This is where total costs and installation times go. To see how cost totals are calculated see, the compute_total_bos_costs method below. """ self.add_output( "bos_capex", 0.0, units="USD", desc="Total BOS CAPEX not including commissioning or decommissioning." ) self.add_output( "bos_capex_kW", 0.0, units="USD/kW", desc="Total BOS CAPEX per kW not including commissioning or decommissioning.", ) self.add_output( "total_capex", 0.0, units="USD", desc="Total BOS CAPEX including commissioning and decommissioning." ) self.add_output( "total_capex_kW", 0.0, units="USD/kW", desc="Total BOS CAPEX per kW including commissioning and decommissioning.", ) self.add_output("installation_capex", 0.0, units="USD", desc="Total foundation and erection installation cost.") self.add_output( "installation_capex_kW", 0.0, units="USD", desc="Total foundation and erection installation cost per kW." ) self.add_output("installation_time_months", 0.0, desc="Total balance of system installation time (months).") def setup_discrete_outputs(self): """ This method sets up discrete outputs. """ self.add_discrete_output( "landbosse_costs_by_module_type_operation", desc="The costs by module, type and operation", val=None ) self.add_discrete_output( "landbosse_details_by_module", desc="The details from the run of LandBOSSE. This includes some costs, but mostly other things", val=None, ) self.add_discrete_output("erection_crane_choice", desc="The crane choices for erection.", val=None) self.add_discrete_output( "erection_component_name_topvbase", desc="List of components and whether they are a topping or base operation", val=None, ) self.add_discrete_output( "erection_components", desc="List of components with their values modified from the defaults.", val=None ) def compute(self, inputs, outputs, discrete_inputs=None, discrete_outputs=None): """ This runs the ErectionCost module using the inputs and outputs into and out of this module. Note: inputs, discrete_inputs are not dictionaries. They do support [] notation. inputs is of class 'openmdao.vectors.default_vector.DefaultVector' discrete_inputs is of class openmdao.core.component._DictValues. Other than [] brackets, they do not behave like dictionaries. See the following documentation for details. http://openmdao.org/twodocs/versions/latest/_srcdocs/packages/vectors/default_vector.html https://mdolab.github.io/OpenAeroStruct/_modules/openmdao/core/component.html Parameters ---------- inputs : openmdao.vectors.default_vector.DefaultVector A dictionary-like object with NumPy arrays that hold float inputs. Note that since these are NumPy arrays, they need indexing to pull out simple float64 values. outputs : openmdao.vectors.default_vector.DefaultVector A dictionary-like object to store outputs. discrete_inputs : openmdao.core.component._DictValues A dictionary-like with the non-numeric inputs (like pandas.DataFrame) discrete_outputs : openmdao.core.component._DictValues A dictionary-like for non-numeric outputs (like pandas.DataFrame) """ # Put the inputs together and run all the modules master_output_dict = dict() master_input_dict = self.prepare_master_input_dictionary(inputs, discrete_inputs) manager = Manager(master_input_dict, master_output_dict) result = manager.execute_landbosse("WISDEM") # Check if everything executed correctly if result != 0: raise Exception("LandBOSSE didn't execute correctly") # Gather the cost and detail outputs costs_by_module_type_operation = self.gather_costs_from_master_output_dict(master_output_dict) discrete_outputs["landbosse_costs_by_module_type_operation"] = costs_by_module_type_operation details = self.gather_details_from_master_output_dict(master_output_dict) discrete_outputs["landbosse_details_by_module"] = details # This is where we have access to the modified components, so put those # in the outputs of the component discrete_outputs["erection_components"] = master_input_dict["components"] # Now get specific outputs. These have been refactored to methods that work # with each module so as to keep this method as compact as possible. self.gather_specific_erection_outputs(master_output_dict, outputs, discrete_outputs) # Compute the total BOS costs self.compute_total_bos_costs(costs_by_module_type_operation, master_output_dict, inputs, outputs) def prepare_master_input_dictionary(self, inputs, discrete_inputs): """ This prepares a master input dictionary by applying all the necessary modifications to the inputs. Parameters ---------- inputs : openmdao.vectors.default_vector.DefaultVector A dictionary-like object with NumPy arrays that hold float inputs. Note that since these are NumPy arrays, they need indexing to pull out simple float64 values. discrete_inputs : openmdao.core.component._DictValues A dictionary-like with the non-numeric inputs (like pandas.DataFrame) Returns ------- dict The prepared master input to go to the Manager. """ inputs_dict = {key: inputs[key][0] for key in inputs.keys()} discrete_inputs_dict = {key: value for key, value in discrete_inputs.items()} incomplete_input_dict = {**inputs_dict, **discrete_inputs_dict} # Modify the default component data if needed and copy it into the # appropriate values of the input dictionary. modified_components = self.modify_component_lists(inputs, discrete_inputs) incomplete_input_dict["project_data"]["components"] = modified_components incomplete_input_dict["components"] = modified_components # FoundationCost needs to have all the component data split into separate # NumPy arrays. incomplete_input_dict["component_data"] = modified_components for component in incomplete_input_dict["component_data"].keys(): incomplete_input_dict[component] = np.array(incomplete_input_dict["component_data"][component]) # These are aliases because parts of the code call the same thing by # difference names. incomplete_input_dict["crew_cost"] = discrete_inputs["crew_price"] incomplete_input_dict["cable_specs_pd"] = discrete_inputs["cable_specs"] # read in RSMeans per diem: crew_cost = discrete_inputs["crew_price"] crew_cost = crew_cost.set_index("Labor type ID", drop=False) incomplete_input_dict["rsmeans_per_diem"] = crew_cost.loc["RSMeans", "Per diem USD per day"] # Calculate project size in megawatts incomplete_input_dict["project_size_megawatts"] = float( discrete_inputs["num_turbines"] * inputs["turbine_rating_MW"] ) # Needed to avoid distributed wind keys incomplete_input_dict["road_distributed_wind"] = False defaults = DefaultMasterInputDict() master_input_dict = defaults.populate_input_dict(incomplete_input_dict) return master_input_dict def gather_costs_from_master_output_dict(self, master_output_dict): """ This method extract all the cost_by_module_type_operation lists for output in an Excel file. It finds values for the keys ending in '_module_type_operation'. It then concatenates them together so they can be easily written to a .csv or .xlsx On every row, it includes the: Rotor diameter m Turbine rating MW Number of turbines This enables easy mapping of new columns if need be. The columns have spaces in the names so that they can be easily written to a user-friendly output. Parameters ---------- runs_dict : dict Values are the names of the projects. Keys are the lists of dictionaries that are lines for the .csv Returns ------- list List of dicts to write to the .csv. """ line_items = [] # Gather the lists of costs cost_lists = [value for key, value in master_output_dict.items() if key.endswith("_module_type_operation")] # Flatten the list of lists that is the result of the gathering for cost_list in cost_lists: line_items.extend(cost_list) # Filter out the keys needed and rename them to meaningful values final_costs = [] for line_item in line_items: item = { "Module": line_item["module"], "Type of cost": line_item["type_of_cost"], "Cost / kW": line_item["usd_per_kw_per_project"], "Cost / project": line_item["cost_per_project"], "Cost / turbine": line_item["cost_per_turbine"], "Number of turbines": line_item["num_turbines"], "Rotor diameter (m)": line_item["rotor_diameter_m"], "Turbine rating (MW)": line_item["turbine_rating_MW"], "Project ID with serial": line_item["project_id_with_serial"], } final_costs.append(item) return final_costs def gather_details_from_master_output_dict(self, master_output_dict): """ This extracts the detail lists from all the modules to output the detailed non-cost data from the model run. Parameters ---------- master_output_dict : dict The master output dict with the finished module output in it. Returns ------- list List of dicts with detailed data. """ line_items = [] # Gather the lists of costs details_lists = [value for key, value in master_output_dict.items() if key.endswith("_csv")] # Flatten the list of lists for details_list in details_lists: line_items.extend(details_list) return line_items def gather_specific_erection_outputs(self, master_output_dict, outputs, discrete_outputs): """ This method gathers specific outputs from the ErectionCost module and places them on the outputs. The method does not return anything. Rather, it places the outputs directly on the continuous of discrete outputs. Parameters ---------- master_output_dict: dict The master output dictionary out of LandBOSSE outputs : openmdao.vectors.default_vector.DefaultVector A dictionary-like object to store outputs. discrete_outputs : openmdao.core.component._DictValues A dictionary-like for non-numeric outputs (like pandas.DataFrame) """ discrete_outputs["erection_crane_choice"] = master_output_dict["crane_choice"] discrete_outputs["erection_component_name_topvbase"] = master_output_dict["component_name_topvbase"] def compute_total_bos_costs(self, costs_by_module_type_operation, master_output_dict, inputs, outputs): """ This computes the total BOS costs from the master output dictionary and places them on the necessary outputs. Parameters ---------- costs_by_module_type_operation: List[Dict[str, Any]] The lists of costs by module, type and operation. master_output_dict: Dict[str, Any] The master output dictionary from the run. Used to obtain the construction time, outputs : openmdao.vectors.default_vector.DefaultVector The outputs in which to place the results of the computations """ bos_per_kw = 0.0 bos_per_project = 0.0 installation_per_project = 0.0 installation_per_kW = 0.0 for row in costs_by_module_type_operation: bos_per_kw += row["Cost / kW"] bos_per_project += row["Cost / project"] if row["Module"] in ["ErectionCost", "FoundationCost"]: installation_per_project += row["Cost / project"] installation_per_kW += row["Cost / kW"] commissioning_pct = inputs["commissioning_pct"] decommissioning_pct = inputs["decommissioning_pct"] commissioning_per_project = bos_per_project * commissioning_pct decomissioning_per_project = bos_per_project * decommissioning_pct commissioning_per_kW = bos_per_kw * commissioning_pct decomissioning_per_kW = bos_per_kw * decommissioning_pct outputs["total_capex_kW"] = np.round(bos_per_kw + commissioning_per_kW + decomissioning_per_kW, 0) outputs["total_capex"] = np.round(bos_per_project + commissioning_per_project + decomissioning_per_project, 0) outputs["bos_capex"] = round(bos_per_project, 0) outputs["bos_capex_kW"] = round(bos_per_kw, 0) outputs["installation_capex"] = round(installation_per_project, 0) outputs["installation_capex_kW"] = round(installation_per_kW, 0) actual_construction_months = master_output_dict["actual_construction_months"] outputs["installation_time_months"] = round(actual_construction_months, 0) def modify_component_lists(self, inputs, discrete_inputs): """ This method modifies the previously loaded default component lists with data about blades, tower sections, if they have been provided as input to the component. It only modifies the project component data if default data for the proper inputs have been overridden. The default blade data is assumed to be the first component that begins with the word "Blade" This should take mass from the tower in WISDEM. Ideally, this should have an input for transportable tower 4.3, large diameter steel tower LDST 6.2m, or unconstrained key stone tower. Or give warnings about the boundaries that we assume. Parameters ---------- inputs : openmdao.vectors.default_vector.DefaultVector A dictionary-like object with NumPy arrays that hold float inputs. Note that since these are NumPy arrays, they need indexing to pull out simple float64 values. discrete_inputs : openmdao.core.component._DictValues A dictionary-like with the non-numeric inputs (like pandas.DataFrame) Returns ------- pd.DataFrame The dataframe with the modified components. """ input_components = discrete_inputs["components"] # This list is a sequence of pd.Series instances that have the # specifications of each component. output_components_list = [] # Need to convert kg to tonnes kg_per_tonne = 1000 # Get the hub height hub_height_meters = inputs["hub_height_meters"][0] # Make the nacelle. This does not include the hub or blades. nacelle_mass_kg = inputs["nacelle_mass"][0] nacelle = input_components[input_components["Component"].str.startswith("Nacelle")].iloc[0].copy() if inputs["nacelle_mass"] != use_default_component_data: nacelle["Mass tonne"] = nacelle_mass_kg / kg_per_tonne nacelle["Component"] = "Nacelle" nacelle["Lift height m"] = hub_height_meters output_components_list.append(nacelle) # Make the hub hub_mass_kg = inputs["hub_mass"][0] hub = input_components[input_components["Component"].str.startswith("Hub")].iloc[0].copy() hub["Lift height m"] = hub_height_meters if hub_mass_kg != use_default_component_data: hub["Mass tonne"] = hub_mass_kg / kg_per_tonne output_components_list.append(hub) # Make blades blade = input_components[input_components["Component"].str.startswith("Blade")].iloc[0].copy() # There is always a hub height, so use that as the lift height blade["Lift height m"] = hub_height_meters if inputs["blade_drag_coefficient"][0] != use_default_component_data: blade["Coeff drag"] = inputs["blade_drag_coefficient"][0] if inputs["blade_lever_arm"][0] != use_default_component_data: blade["Lever arm m"] = inputs["blade_lever_arm"][0] if inputs["blade_install_cycle_time"][0] != use_default_component_data: blade["Cycle time installation hrs"] = inputs["blade_install_cycle_time"][0] if inputs["blade_offload_hook_height"][0] != use_default_component_data: blade["Offload hook height m"] = hub_height_meters if inputs["blade_offload_cycle_time"][0] != use_default_component_data: blade["Offload cycle time hrs"] = inputs["blade_offload_cycle_time"] if inputs["blade_drag_multiplier"][0] != use_default_component_data: blade["Multiplier drag rotor"] = inputs["blade_drag_multiplier"] if inputs["blade_mass"][0] != use_default_component_data: blade["Mass tonne"] = inputs["blade_mass"][0] / kg_per_tonne # Assume that number_of_blades always has a reasonable value. It's # default count when the discrete input is declared of 3 is always # reasonable unless overridden by another input. number_of_blades = discrete_inputs["number_of_blades"] for i in range(number_of_blades): component = f"Blade {i + 1}" blade_i = blade.copy() blade_i["Component"] = component output_components_list.append(blade_i) # Make tower sections tower_mass_tonnes = inputs["tower_mass"][0] / kg_per_tonne tower_height_m = hub_height_meters - inputs["foundation_height"][0] default_tower_section = input_components[input_components["Component"].str.startswith("Tower")].iloc[0] tower_sections = self.make_tower_sections(tower_mass_tonnes, tower_height_m, default_tower_section) output_components_list.extend(tower_sections) # Make the output component dataframe and return it. output_components = pd.DataFrame(output_components_list) return output_components @staticmethod def make_tower_sections(tower_mass_tonnes, tower_height_m, default_tower_section): """ This makes tower sections for a transportable tower. Approximations: - Weight is distributed uniformly among the sections - The number of sections is either the maximum allowed by mass or the maximum allowed by height, to maintain transportability. For each tower section, calculate: - lift height - lever arm - surface area The rest of values should remain at their defaults. Note: Tower sections are constrained in maximum diameter to 4.5 m. However, their surface area is calculated with a 1.3 m radius to agree more closely with empirical data. Also, tower sections are approximated as cylinders. Parameters ---------- tower_mass_tonnes: float The total tower mass in tonnes tower_height_m: float The total height of the tower in meters. default_tower_section: pd.Series There are a number of values that are kept constant in creating the tower sections. This series holds the values. Returns ------- List[pd.Series] A list of series to be appended onto an output component list. It is not a dataframe, because it is faster to append to a list and make a dataframe once. """ tower_radius = 1.3 number_of_sections = max(ceil(tower_height_m / 30), ceil(tower_mass_tonnes / 80)) tower_section_height_m = tower_height_m / number_of_sections tower_section_mass = tower_mass_tonnes / number_of_sections tower_section_surface_area_m2 = np.pi * tower_section_height_m * (tower_radius ** 2) sections = [] for i in range(number_of_sections): lift_height_m = (i * tower_section_height_m) + tower_section_height_m lever_arm = (i * tower_section_height_m) + (0.5 * tower_section_height_m) name = f"Tower {i + 1}" section = default_tower_section.copy() section["Component"] = name section["Mass tonne"] = tower_section_mass section["Lift height m"] = lift_height_m section["Surface area sq m"] = tower_section_surface_area_m2 section["Section height m"] = tower_section_height_m section["Lever arm m"] = lever_arm sections.append(section) return sections
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from collections import deque class PushSwapStacks: """ describe stacks for push-swap algorithm """ def __init__(self, initstate): """ initstate: Iterable[_T]=...""" self.stack_a = deque() self.stack_b = deque() self.new_data(initstate) self.cmd = { 'pa': self.pa, 'pb': self.pb, 'sa': self.sa, 'sb': self.sb, 'ss': self.ss, 'ra': self.ra, 'rb': self.rb, 'rr': self.rr, 'rra': self.rra, 'rrb': self.rrb, 'rrr': self.rrr } def new_data(self, initstate): self.stack_a.clear() self.stack_b.clear() tmp = sorted(initstate) self.stack_a.extend([tmp.index(x) + 1 for x in initstate]) def do_cmd(self, op): self.cmd[op]() return op def pa(self): if len(self.stack_b): self.stack_a.appendleft(self.stack_b.popleft()) def pb(self): if len(self.stack_a): self.stack_b.appendleft(self.stack_a.popleft()) def ra(self): if len(self.stack_a): self.stack_a.rotate(-1) def rb(self): if len(self.stack_b): self.stack_b.rotate(-1) def rr(self): self.ra() self.rb() def rra(self): if len(self.stack_a): self.stack_a.rotate(1) def rrb(self): if len(self.stack_b): self.stack_b.rotate(1) def rrr(self): self.rra() self.rrb() def sa(self): self.stack_a[0], self.stack_a[1] = self.stack_a[1], self.stack_a[0] def sb(self): self.stack_b[0], self.stack_b[1] = self.stack_b[1], self.stack_b[0] def ss(self): self.sa() self.sb()
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import logging from datetime import datetime import zmq from .handler import Handler LOGGER = logging.getLogger(__name__) class ZmqHandler(Handler): """Zmq handler. """ def __init__(self, connection, **kwargs): """Constructor. """ super().__init__(**kwargs) self._connection = connection self._context = zmq.Context() self._socket = None def load(self, queue): """Load. """ super().load(queue=queue) LOGGER.info('Binding connection %s as a publisher', self._connection) def create_table(self, table_name, fields, **kwargs): """Create table. """ assert self._socket, "Socket is not initialized" def insert(self, table_name, fields): """Insert. """ assert self._socket, "Socket is not initialized" native_fields = { k: self.serialize(v) for k, v in fields.items() if not v.is_auto_increment} data = { "table_name": table_name, "data": native_fields } self._socket.send_json(data) @staticmethod def serialize(value): """Serialize value. """ if isinstance(value.value, datetime): return str(value) return value.value def run(self): """Run. """ # The socket has to be initialized here due to pyzmq #1232 # https://github.com/zeromq/pyzmq/issues/1232 self._socket = self._context.socket(zmq.PUB) self._socket.bind(self._connection) super().run()
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import gpu import bgl from gpu_extras.batch import batch_for_shader class BL_UI_Widget: def __init__(self, x, y, width, height): self.x = x self.y = y self.x_screen = x self.y_screen = y self.width = width self.height = height self._bg_color = (0.8, 0.8, 0.8, 1.0) self._tag = None self.context = None self.__inrect = False self._mouse_down = False self.name = 'None' def set_location(self, x, y): self.x = x self.y = y self.x_screen = x self.y_screen = y self.update(x,y) @property def bg_color(self): return self._bg_color @bg_color.setter def bg_color(self, value): self._bg_color = value @property def tag(self): return self._tag @tag.setter def tag(self, value): self._tag = value def draw(self): self.shader.bind() self.shader.uniform_float("color", self._bg_color) bgl.glEnable(bgl.GL_BLEND) self.batch_panel.draw(self.shader) bgl.glDisable(bgl.GL_BLEND) def init(self, context): self.context = context self.update(self.x, self.y) def update(self, x, y): area_height = self.get_area_height() self.x_screen = x self.y_screen = y indices = ((0, 1, 2), (0, 2, 3)) y_screen_flip = area_height - self.y_screen # bottom left, top left, top right, bottom right vertices = ( (self.x_screen, y_screen_flip), (self.x_screen, y_screen_flip - self.height), (self.x_screen + self.width, y_screen_flip - self.height), (self.x_screen + self.width, y_screen_flip)) self.shader = gpu.shader.from_builtin('2D_UNIFORM_COLOR') self.batch_panel = batch_for_shader(self.shader, 'TRIS', {"pos" : vertices}, indices=indices) def handle_event(self, event): x = event.mouse_x y = event.mouse_y if(event.type == 'LEFTMOUSE'): if(event.value == 'PRESS'): self._mouse_down = True return self.mouse_down(x, y) else: self._mouse_down = False self.mouse_up(x, y) elif(event.type == 'MOUSEMOVE'): self.mouse_move(x, y) inrect = self.is_in_rect(x, y) # we enter the rect if not self.__inrect and inrect: self.__inrect = True self.mouse_enter(event, x, y) # we are leaving the rect elif self.__inrect and not inrect: self.__inrect = False self.mouse_exit(event, x, y) return False return False def get_area_height(self): return self.context.area.height def is_in_rect(self, x, y): area_height = self.get_area_height() widget_y = area_height - self.y_screen if ( (self.x_screen <= x <= (self.x_screen + self.width)) and (widget_y >= y >= (widget_y - self.height)) ): return True return False def mouse_down(self, x, y): return self.is_in_rect(x,y) def mouse_up(self, x, y): pass def mouse_enter(self, event, x, y): pass def mouse_exit(self, event, x, y): pass def mouse_move(self, x, y): pass
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import math import torch from torch import nn as nn class JSD(nn.Module): def __init__(self): super().__init__() def forward(self, x, eps=1e-8): logN = math.log(float(x.shape[0])) y = torch.mean(x, 0) y = y * (y + eps).log() / logN y = y.sum() x = x * (x + eps).log() / logN x = x.sum(1).mean() return 1.0 - x + y class InfoLoss(nn.Module): def __init__(self): super().__init__() def forward(self, x, eps=1e-8): x = torch.mean(x, 0) logN = math.log(float(x.shape[0])) x = x * (x + eps).log() / logN neg_entropy = x.sum() return 1.0 + neg_entropy class EntropyLoss(nn.Module): def __init__(self): super().__init__() def forward(self, x, eps=1e-8): logN = math.log(float(x.shape[0])) x = x * (x + eps).log() / logN neg_entropy = x.sum(1) return -neg_entropy.mean() infoLoss = InfoLoss() entropyLoss = EntropyLoss() jsd = JSD() def MSE(p, target): return (p - target) ** 2, 2 * (p - target)
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import os import sys sys.path.append(os.path.normpath(os.path.join(os.path.abspath(__file__), '..', '..', '..', "common"))) from env_indigo import * indigo = Indigo() # indigo::SmilesLoader::Error try: m = indigo.loadMolecule('CX') except IndigoException as e: print(getIndigoExceptionText(e)) # IndigoError try: r = indigo.loadReaction('C1=CC=CC=C1>>C1=CC=CC=C1') for atom in r.iterateAtoms(): print(atom) except IndigoException as e: print(getIndigoExceptionText(e))
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from numpy import genfromtxt import matplotlib # matplotlib.use('Agg') import matplotlib.pyplot as plt ''' ResNet-56 ''' train_error_52 = './epoch_error_train_52.csv' train_error_52 = genfromtxt(train_error_52, delimiter=',') valid_error_52 = './epoch_error_valid_52.csv' valid_error_52 = genfromtxt(valid_error_52, delimiter=',') train_error_53 = './epoch_error_train_53.csv' train_error_53 = genfromtxt(train_error_53, delimiter=',') valid_error_53 = './epoch_error_valid_53.csv' valid_error_53 = genfromtxt(valid_error_53, delimiter=',') # resnet56 (model 52) # Training time: 127m 41s, 281 epochs # # Best [Valid] | epoch: 221 - loss: 0.3129 - acc: 0.9396 # [Test] loss 0.3042 - acc: 0.9356 - acc_topk: 0.9795 # resnet56 alpha (model 53) # Training time: 134m 44s, 303 epochs # # Best [Valid] | epoch: 243 - loss: 0.2934 - acc: 0.9369 # [Test] loss 0.3062 - acc: 0.9345 - acc_topk: 0.9788 fig = plt.figure() plt.xlabel('epoch', fontsize=14) plt.ylabel('error (%)', fontsize=14) plt.title('ResNet-56', fontsize=16) plt.plot(train_error_53[1:,1], 100*train_error_53[1:,2], label='train (ReZero)', zorder=1)#, linewidth=1.5) plt.plot(valid_error_53[1:,1], 100*valid_error_53[1:,2], label='valid (ReZero)', zorder=2)#, linewidth=1.5) plt.plot(train_error_52[1:,1], 100*train_error_52[1:,2], 'c', label='train', zorder=3)#, linewidth=1.5) plt.plot(valid_error_52[1:,1], 100*valid_error_52[1:,2], 'm', label='valid', zorder=4)#, linewidth=1.5) plt.ticklabel_format(axis='y', style='sci') plt.grid(True) plt.legend(loc='upper right', fontsize='x-large') # upper right, lower right, lower left # plt.ylim(5, 80) # plt.xlim(1, 30) # plt.savefig('resnet56_error_0_30.png', box_inches='tight') plt.ylim(-2, 35) plt.xlim(0, 250) plt.savefig('resnet56_error.png', box_inches='tight') plt.show() train_loss_52 = './epoch_loss_train_52.csv' train_loss_52 = genfromtxt(train_loss_52, delimiter=',') valid_loss_52 = './epoch_loss_valid_52.csv' valid_loss_52 = genfromtxt(valid_loss_52, delimiter=',') train_loss_53 = './epoch_loss_train_53.csv' train_loss_53 = genfromtxt(train_loss_53, delimiter=',') valid_loss_53 = './epoch_loss_valid_53.csv' valid_loss_53 = genfromtxt(valid_loss_53, delimiter=',') fig = plt.figure() plt.xlabel('epoch', fontsize=14) plt.ylabel('loss', fontsize=14) plt.title('ResNet-56', fontsize=16) plt.plot(train_loss_53[1:,1], train_loss_53[1:,2], label='train (ReZero)', zorder=1)#, linewidth=1.5) plt.plot(valid_loss_53[1:,1], valid_loss_53[1:,2], label='valid (ReZero)', zorder=2)#, linewidth=1.5) plt.plot(train_loss_52[1:,1], train_loss_52[1:,2], 'c', label='train', zorder=3)#, linewidth=1.5) plt.plot(valid_loss_52[1:,1], valid_loss_52[1:,2], 'm', label='valid', zorder=4)#, linewidth=1.5) plt.ticklabel_format(axis='y', style='sci') plt.grid(True) plt.legend(loc='upper right', fontsize='x-large') # upper right, lower right, lower left plt.ylim(.2, 2.5) plt.xlim(1, 30) plt.savefig('resnet56_loss_0_30.png', box_inches='tight') # plt.ylim(-.1, 1.2) # plt.xlim(0, 250) # plt.savefig('resnet56_loss.png', box_inches='tight') plt.show() ''' ResNet-20 ''' train_error_54 = './epoch_error_train_54.csv' train_error_54 = genfromtxt(train_error_54, delimiter=',') valid_error_54 = './epoch_error_valid_54.csv' valid_error_54 = genfromtxt(valid_error_54, delimiter=',') train_error_55 = './epoch_error_train_55.csv' train_error_55 = genfromtxt(train_error_55, delimiter=',') valid_error_55 = './epoch_error_valid_55.csv' valid_error_55 = genfromtxt(valid_error_55, delimiter=',') # resnet-20 alpha (model 54) # Training time: 63m 9s, 327 # # Best [Valid] | epoch: 267 - loss: 0.3237 - acc: 0.9256 # [Test] loss 0.3491 - acc: 0.9206 - acc_topk: 0.9723 # resnet-20 (model 55) # Training time: 70m 3s, 398 # # Best [Valid] | epoch: 338 - loss: 0.3026 - acc: 0.9237 # [Test] loss 0.3055 - acc: 0.9202 - acc_topk: 0.9742 fig = plt.figure() plt.xlabel('epoch', fontsize=14) plt.ylabel('error (%)', fontsize=14) plt.title('ResNet-20', fontsize=16) plt.plot(train_error_54[1:,1], 100*train_error_54[1:,2], label='train (ReZero)', zorder=1)#, linewidth=1.5) plt.plot(valid_error_54[1:,1], 100*valid_error_54[1:,2], label='valid (ReZero)', zorder=2)#, linewidth=1.5) plt.plot(train_error_55[1:,1], 100*train_error_55[1:,2], 'c', label='train', zorder=3)#, linewidth=1.5) plt.plot(valid_error_55[1:,1], 100*valid_error_55[1:,2], 'm', label='valid', zorder=4)#, linewidth=1.5) plt.ticklabel_format(axis='y', style='sci') plt.grid(True) plt.legend(loc='upper right', fontsize='x-large') # upper right, lower right, lower left plt.ylim(5, 60) plt.xlim(1, 30) plt.savefig('resnet20_error_0_30.png', box_inches='tight') # plt.ylim(-2, 35) # plt.xlim(0, 300) # plt.savefig('resnet20_error.png', box_inches='tight') plt.show() train_loss_54 = './epoch_loss_train_54.csv' train_loss_54 = genfromtxt(train_loss_54, delimiter=',') valid_loss_54 = './epoch_loss_valid_54.csv' valid_loss_54 = genfromtxt(valid_loss_54, delimiter=',') train_loss_55 = './epoch_loss_train_55.csv' train_loss_55 = genfromtxt(train_loss_55, delimiter=',') valid_loss_55 = './epoch_loss_valid_55.csv' valid_loss_55 = genfromtxt(valid_loss_55, delimiter=',') fig = plt.figure() plt.xlabel('epoch', fontsize=14) plt.ylabel('loss', fontsize=14) plt.title('ResNet-20', fontsize=16) plt.plot(train_loss_54[1:,1], train_loss_54[1:,2], label='train (ReZero)', zorder=1)#, linewidth=1.5) plt.plot(valid_loss_54[1:,1], valid_loss_54[1:,2], label='valid (ReZero)', zorder=2)#, linewidth=1.5) plt.plot(train_loss_55[1:,1], train_loss_55[1:,2], 'c', label='train', zorder=3)#, linewidth=1.5) plt.plot(valid_loss_55[1:,1], valid_loss_55[1:,2], 'm', label='valid', zorder=4)#, linewidth=1.5) plt.ticklabel_format(axis='y', style='sci') plt.grid(True) plt.legend(loc='upper right', fontsize='x-large') # upper right, lower right, lower left plt.ylim(.2, 1.6) plt.xlim(1, 30) plt.savefig('resnet20_loss_0_30.png', box_inches='tight') # plt.ylim(-.1, 1.2) # plt.xlim(0, 300) # plt.savefig('resnet20_loss.png', box_inches='tight') plt.show() ''' ResNet-110 ''' train_error_58 = './epoch_error_train_58.csv' train_error_58 = genfromtxt(train_error_58, delimiter=',') valid_error_58 = './epoch_error_valid_58.csv' valid_error_58 = genfromtxt(valid_error_58, delimiter=',') train_error_59 = './epoch_error_train_59.csv' train_error_59 = genfromtxt(train_error_59, delimiter=',') valid_error_59 = './epoch_error_valid_59.csv' valid_error_59 = genfromtxt(valid_error_59, delimiter=',') # resnet-110 alpha (model 58) # Training time: 301m 19s, 410 epochs # # Best [Valid] | epoch: 350 - loss: 0.2925 - acc: 0.9416 # [Test] loss 0.2796 - acc: 0.9412 - acc_topk: 0.9816 # resnet-110 (model 59) # Training time: 240m 53s, 313 epochs # # Best [Valid] | epoch: 253 - loss: 0.3480 - acc: 0.9400 # [Test] loss 0.3392 - acc: 0.9361 - acc_topk: 0.9809 fig = plt.figure() plt.xlabel('epoch', fontsize=14) plt.ylabel('error (%)', fontsize=14) plt.title('ResNet-110', fontsize=16) plt.plot(train_error_58[1:,1], 100*train_error_58[1:,2], label='train (ReZero)', zorder=1)#, linewidth=1.5) plt.plot(valid_error_58[1:,1], 100*valid_error_58[1:,2], label='valid (ReZero)', zorder=2)#, linewidth=1.5) plt.plot(train_error_59[1:,1], 100*train_error_59[1:,2], 'c', label='train', zorder=3)#, linewidth=1.5) plt.plot(valid_error_59[1:,1], 100*valid_error_59[1:,2], 'm', label='valid', zorder=4)#, linewidth=1.5) plt.ticklabel_format(axis='y', style='sci') plt.grid(True) plt.legend(loc='upper right', fontsize='x-large') # upper right, lower right, lower left # plt.ylim(5, 70) # plt.xlim(1, 30) # plt.savefig('resnet110_error_0_30.png', box_inches='tight') plt.ylim(-2, 40) plt.xlim(0, 300) plt.savefig('resnet110_error.png', box_inches='tight') plt.show() train_loss_58 = './epoch_loss_train_58.csv' train_loss_58 = genfromtxt(train_loss_58, delimiter=',') valid_loss_58 = './epoch_loss_valid_58.csv' valid_loss_58 = genfromtxt(valid_loss_58, delimiter=',') train_loss_59 = './epoch_loss_train_59.csv' train_loss_59 = genfromtxt(train_loss_59, delimiter=',') valid_loss_59 = './epoch_loss_valid_59.csv' valid_loss_59 = genfromtxt(valid_loss_59, delimiter=',') fig = plt.figure() plt.xlabel('epoch', fontsize=14) plt.ylabel('loss', fontsize=14) plt.title('ResNet-110', fontsize=16) plt.plot(train_loss_58[1:,1], train_loss_58[1:,2], label='train (ReZero)', zorder=1)#, linewidth=1.5) plt.plot(valid_loss_58[1:,1], valid_loss_58[1:,2], label='valid (ReZero)', zorder=2)#, linewidth=1.5) plt.plot(train_loss_59[1:,1], train_loss_59[1:,2], 'c', label='train', zorder=3)#, linewidth=1.5) plt.plot(valid_loss_59[1:,1], valid_loss_59[1:,2], 'm', label='valid', zorder=4)#, linewidth=1.5) plt.ticklabel_format(axis='y', style='sci') plt.grid(True) plt.legend(loc='upper right', fontsize='x-large') # upper right, lower right, lower left # plt.ylim(.2, 1.8) # plt.xlim(1, 30) # plt.savefig('resnet110_loss_0_30.png', box_inches='tight') plt.ylim(-.1, 1.4) plt.xlim(0, 300) plt.savefig('resnet110_loss.png', box_inches='tight') plt.show()
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import subprocess from ctypes import * # I know, i know, this is probably the worst solution to a trivial challenge. Still, if it aint broke... class Ambient: def __init__(self): self.user32 = WinDLL("user32.dll") def change_color(self, r,g,b): rgb = r + (g<<8) + (b<<16) self.user32.SetSysColors(1, byref(c_int(1)), byref(c_int(rgb)))
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import sys from progress.bar import FillingSquaresBar from time import sleep from colored import fg, bg, attr, fore, style from colored import stylize from functools import wraps from colored import fg, bg, attr, fore, style def prefix(item): ''' This function decorates the other functions with bars ''' def decorator(fun): @wraps(fun) def wrapper(*args): print('\n') d = (stylize(item, fg("green_1"))) with FillingSquaresBar(d) as bar: for _ in range(100): sleep(0.01) bar.next() print('\n') return fun(*args) return wrapper return decorator def sub_prefix(item): ''' This function decorates the other functions with bars ''' def decorator(fun): @wraps(fun) def wrapper(*args): d = (stylize(item, fg("dodger_blue_1"))) with FillingSquaresBar(d) as bar: for _ in range(100): sleep(0.005) bar.next() return fun(*args) return wrapper return decorator def service_open(item,file_obj=None): ''' This function decorates the open functions with bars ''' print (fore.ORANGE_1 + ' [+] ' + f' {item}' + ' Endpoint Identified' + style.RESET) if file_obj: print(' [+] '+item + ' Endpoint Identified',file=file_obj) def resource_available(item,file_obj=None): ''' This function decorates the available resources with bars ''' print (fore.ORANGE_1 + ' [+] ' + f' {item}' + ' Identified in the cluster' + style.RESET) if file_obj: print(' [+] '+item + ' Identified in the cluster',file=file_obj) def scan_status(item): ''' This function decorates items being scanned with bars ''' d = (stylize(item, fg("dodger_blue_1"))) with FillingSquaresBar(d) as bar: for _ in range(100): sleep(0.005) bar.next() borderpadding = 2 def getLines(text): ''' cowsay stuff ''' lines = [] lines.append(text.strip()) return lines def getMaxLineLength(lines): ''' cowsay stuff ''' maxLength = 0 for line in lines: length = len(line) if length > maxLength: maxLength = length return maxLength def padLine(line, maxlinelength): ''' cowsay stuff ''' paddingLength = maxlinelength - len(line) - borderpadding padding = "" if paddingLength > 0: padding = " " * paddingLength return line + padding def drawTextBox(lines): ''' cowsay stuff ''' maxlinelength = getMaxLineLength(lines) + borderpadding horizontal_border = " " + ('-' * maxlinelength) print(horizontal_border) if len(lines) == 1: print("< " + padLine(lines[0], maxlinelength) + " >") else: print("/ " + (" " * (maxlinelength - borderpadding)) + " \\") for line in lines: print("| " + padLine(line, maxlinelength) + " |") print("\\ " + (" " * (maxlinelength - borderpadding)) + " /") print(horizontal_border) cow = [ fore.MAGENTA_1 + " \\ ^__^", " \\ (oo)\\________", " (__)\\ )\\/\\", " ||----W |", " || ||" + style.RESET] def drawAnimal(): """Draws a cow in the terminal with ascii art""" for line in cow: print(line) def cowsay(text): ''' cowsay stuff ''' lines = getLines(text) drawTextBox(lines) drawAnimal() def print_msg_box(msg, indent=1, width=None, title=None, file_obj=None): """Print message-box with optional title.""" lines = msg.split('\n') space = " " * indent if not width: width = max(map(len, lines)) box = f'โ•”{"โ•" * (width + indent * 2)}โ•—\n' # upper_border if title: box += f'โ•‘{space}{title:<{width}}{space}โ•‘\n' # title box += f'โ•‘{space}{"-" * len(title):<{width}}{space}โ•‘\n' # underscore box += ''.join([f'โ•‘{space}{line:<{width}}{space}โ•‘\n' for line in lines]) box += f'โ•š{"โ•" * (width + indent * 2)}โ•' # lower_border if file_obj: print(box, file=file_obj)
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import os import importlib path = __file__.replace("__init__.py", "") for file in os.listdir(path): if "__" not in file: globals()[file[:-3]] = getattr(importlib.import_module(__name__+"."+file[:-3]), file[:-3])
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import base64 import datetime import hashlib from io import BytesIO from logging import getLogger import OpenSSL.crypto import asn1crypto.ocsp import pytz from OpenSSL import crypto from OpenSSL.crypto import X509StoreContextError from asn1crypto import pem from bankid.experimental.helper import CompletionDataContainer, make_cert, NonceParse _LOG = getLogger(__name__) def verify_bankid_response(bank_id_response, ensure_certificates_still_valid=True, BANK_ID_ROOT_CERT=None): if not isinstance(bank_id_response, dict): raise TypeError("Response not a dictionary") if 'completionData' not in bank_id_response: raise AttributeError('Completion data missing in dictionary') try: cdc = CompletionDataContainer(bank_id_response['completionData']) # First step is to hash the data and verify the digest matches _LOG.info("1. Message Digest Verification\n") bid_signed_data_raw_bytes = cdc.signature_container.bid_signed_data_raw.encode() # TODO - Parse out of the XML which hashing algorithm should be sued bid_signed_data_hash = hashlib.sha256(bid_signed_data_raw_bytes).digest().hex() key_info_hash = hashlib.sha256(cdc.signature_container.key_info_raw.encode()).digest().hex() signed_data_hash_from_signature = base64.b64decode(cdc.signature_container.signed_data_digest.text).hex() key_info_hash_from_signature = base64.b64decode(cdc.signature_container.key_data_digest.text).hex() if bid_signed_data_hash != signed_data_hash_from_signature: raise AssertionError('Signed Data hash does not match!') if key_info_hash != key_info_hash_from_signature: raise AssertionError('Key Info hash does not match!') _LOG.info("\n2. Signature verification\n") # Helper function for the certificates user_certificate_string = make_cert(cdc.signature_container.certificates[0].text) # Making a certificate object out of it user_certificate = crypto.load_certificate(crypto.FILETYPE_PEM, BytesIO(user_certificate_string.encode()).read()) signature_bytes = base64.b64decode(cdc.signature_container.signature_value.text) signed_info = cdc.signature_container.signed_info.encode() try: _LOG.debug("Certificate:", user_certificate.get_subject()) _LOG.debug("Signature Bytes:", signature_bytes) _LOG.debug("Signature Data Raw:", signed_info) OpenSSL.crypto.verify(user_certificate, signature_bytes, signed_info, 'sha256') except OpenSSL.crypto.Error as e: raise AssertionError('The BankID signature is not valid!') _LOG.info("\n3. OCSP Response Verification\n") ocsp = base64.b64decode(bank_id_response['completionData']['ocspResponse']) ocsp_response = asn1crypto.ocsp.OCSPResponse.load(ocsp) basic_ocsp_response = ocsp_response['response_bytes']['response'].parsed # Some help by listing all the different parts of the OCSP response _LOG.debug("TBS Response Data", basic_ocsp_response['tbs_response_data']) _LOG.debug("SignatureAlgorithm", basic_ocsp_response['signature_algorithm'].signature_algo) _LOG.debug("SignatureAlgorithm Hash Function", basic_ocsp_response['signature_algorithm'].hash_algo) _LOG.debug("Signature", basic_ocsp_response['signature'].__bytes__()) _LOG.debug("Cert", basic_ocsp_response['certs']) # Response content _LOG.debug("version", basic_ocsp_response['tbs_response_data']['version']) _LOG.debug("responderID", basic_ocsp_response['tbs_response_data']['responder_id']) # has native _LOG.info("producedAt", basic_ocsp_response['tbs_response_data']['produced_at']) cest = pytz.timezone('Europe/Stockholm') ocsp_produced_at = basic_ocsp_response['tbs_response_data']['produced_at'].native if not isinstance(ocsp_produced_at, datetime.datetime): raise AssertionError('OCSP produced at is not a datetime!') ocsp_produced_at = ocsp_produced_at.astimezone(cest).strftime('%Y-%m-%d %H:%M:%S') _LOG.debug("responses", basic_ocsp_response['tbs_response_data']['responses']) _LOG.debug("response Extentions", basic_ocsp_response['tbs_response_data']['response_extensions']) _LOG.debug("Extentions") extention = basic_ocsp_response['tbs_response_data']['response_extensions'][0] _LOG.debug('extn_id', extention['extn_id']) _LOG.debug('critical', extention['critical']) # Cannot _LOG.debug the value without an exception being raised - need to parse that ourself later # print ('extn_value', extention['extn_value']) single_response = basic_ocsp_response['tbs_response_data']['responses'][0] _LOG.debug("CertID", single_response['cert_id']) _LOG.debug("certStatus", single_response['cert_status']) _LOG.debug("thisUpdate", single_response['this_update']) _LOG.debug("nextUpdate", single_response['next_update']) _LOG.debug("singleExtensions", single_response['single_extensions']) _LOG.info("3.1. OCSP Response - Verify success ") if ocsp_response['response_status'].native != 'successful': raise AssertionError('OCSP response status was not successful') _LOG.info("3.2. OCSP Response - Verify signature ") # Transform the asn1 certificate to an openssl certificate der_bytes = basic_ocsp_response['certs'][0].dump() pem_bytes = pem.armor('CERTIFICATE', der_bytes) ocsp_certificate = crypto.load_certificate(crypto.FILETYPE_PEM, pem_bytes) # Get the signature bytes signature = basic_ocsp_response['signature'].__bytes__() # Dump the TBS response data as DER bytes signature_data = basic_ocsp_response['tbs_response_data'].dump() # Define the hashing algorithm to be used digest_method = basic_ocsp_response['signature_algorithm'].hash_algo _LOG.debug("Certificate", ocsp_certificate.get_subject()) _LOG.debug("Signature", signature) _LOG.debug("Signature data", signature_data) _LOG.debug("Digest Method", digest_method) try: OpenSSL.crypto.verify(ocsp_certificate, signature, signature_data, digest_method) except OpenSSL.crypto.Error as e: raise AssertionError('The OCSP signature is not valid!') _LOG.info("3.2. OCSP Response - Compare nonce") nonce_computed = hashlib.sha1(bank_id_response['completionData']['signature'].encode('utf-8')).digest().hex() # A helper because the asn1 library seems to have a problem with the nonce parsing in some form or the other nonce_parser = NonceParse(extention.contents) # Verify that the computed nonce is part of the nonce value given in the oscp # Note that it only partially matches as we use sha-1 to compute the hash _LOG.debug("Nonce value computed ", nonce_computed) _LOG.debug("Nonce value presented", nonce_parser.value.hex()) if not nonce_parser.value.hex().startswith(nonce_computed): raise AssertionError('Computed nonce not matching the OCSP nonce') _LOG.info("\n4. Verify all the certificates by relying on the BankID root certificate as a trusted one \n") user_cert = crypto.load_certificate( crypto.FILETYPE_PEM, make_cert(cdc.signature_container.certificates[0].text).encode()) bank_user_cert = crypto.load_certificate( crypto.FILETYPE_PEM, make_cert(cdc.signature_container.certificates[1].text).encode()) bank_bank_id_cert = crypto.load_certificate( crypto.FILETYPE_PEM, make_cert(cdc.signature_container.certificates[2].text).encode()) bank_id_root_cert = crypto.load_certificate(crypto.FILETYPE_PEM, BANK_ID_ROOT_CERT.encode()) # 3. verify the certificate chain of the tbs certificate # Make sure we respect or do not respect certificate expiration times if not ensure_certificates_still_valid: tomorrow = datetime.datetime.now() + datetime.timedelta(days=1) bank_user_cert.set_notAfter(tomorrow.strftime('%Y%m%d%H%M%SZ').encode()) bank_bank_id_cert.set_notAfter(tomorrow.strftime('%Y%m%d%H%M%SZ').encode()) bank_id_root_cert.set_notAfter(tomorrow.strftime('%Y%m%d%H%M%SZ').encode()) ocsp_certificate.set_notAfter(tomorrow.strftime('%Y%m%d%H%M%SZ').encode()) user_cert.set_notAfter(tomorrow.strftime('%Y%m%d%H%M%SZ').encode()) store = crypto.X509Store() store.add_cert(bank_user_cert) store.add_cert(bank_bank_id_cert) store.add_cert(bank_id_root_cert) try: # Verify the user certificate up to the root certificate store_ctx = crypto.X509StoreContext(store, user_cert) store_ctx.verify_certificate() _LOG.debug('User Certificate issued by the respective bank... OK') except X509StoreContextError: raise AssertionError('BankID user certificate chain could not be verified.') try: # Verify the ocsp certificate up to the root certificate store_ctx = crypto.X509StoreContext(store, ocsp_certificate) store_ctx.verify_certificate() _LOG.debug('OCSP Certificate issued by the respective bank... OK') except X509StoreContextError: raise AssertionError('OCSP certificate chain could not be verified.') except Exception as e: raise e return ocsp_produced_at
176801
import rqalpha config = { "extra": { "log_level": "verbose", }, "mod": { "live_trade": { "lib": "./mod", "enabled": True, "priority": 100, } } } def run(baseConf): config["base"] = baseConf return rqalpha.run(config)
176818
print(open('teste_win1252.txt', errors='strict').read()) print(open('teste_win1252.txt', errors='replace').read()) print(open('teste_win1252.txt', errors='ignore').read()) print(open('teste_win1252.txt', errors='surrogateescape').read()) print(open('teste_win1252.txt', errors='backslashreplace').read())
176827
import pytest import grpc import uuid from threading import Event import yandex.cloud.compute.v1.zone_service_pb2_grpc as zone_service_pb2_grpc import yandex.cloud.compute.v1.zone_service_pb2 as zone_service_pb2 from yandexcloud import RetryInterceptor from yandexcloud import default_backoff, backoff_linear_with_jitter from tests.grpc_server_mock import DEFAULT_ZONE, grpc_server, default_channel class _FailFirstAttempts: def __init__(self, fail_attempts, code=grpc.StatusCode.UNAVAILABLE): self.__fail_attempts = fail_attempts self.code = code def handler(self, context): if self.__fail_attempts > 0: self.__fail_attempts -= 1 context.set_code(self.code) return DEFAULT_ZONE def reset(self, fail_attempts): self.__fail_attempts = fail_attempts def test_five_retries(): service = _FailFirstAttempts(5) server = grpc_server(service.handler) request = zone_service_pb2.GetZoneRequest(zone_id="id") with default_channel() as channel: for max_retry_count in range(4): interceptor = RetryInterceptor(max_retry_count=max_retry_count) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) with pytest.raises(grpc.RpcError) as e: client.Get(request) assert e.value.code() == grpc.StatusCode.UNAVAILABLE service.reset(5) interceptor = RetryInterceptor(max_retry_count=5) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) res = client.Get(request) assert res == DEFAULT_ZONE server.stop(0) def test_five_retries_internal(): service = _FailFirstAttempts(5, code=grpc.StatusCode.INTERNAL) server = grpc_server(service.handler) request = zone_service_pb2.GetZoneRequest(zone_id="id") retriable_codes = ( grpc.StatusCode.UNAVAILABLE, grpc.StatusCode.RESOURCE_EXHAUSTED, grpc.StatusCode.INTERNAL, ) with default_channel() as channel: for max_retry_count in range(4): interceptor = RetryInterceptor(max_retry_count=max_retry_count, retriable_codes=retriable_codes) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) with pytest.raises(grpc.RpcError) as e: client.Get(request) assert e.value.code() == grpc.StatusCode.INTERNAL service.reset(5) interceptor = RetryInterceptor(max_retry_count=5, retriable_codes=retriable_codes) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) res = client.Get(request) assert res == DEFAULT_ZONE server.stop(0) class _RetriableCodes: def __init__(self, retriable_codes): self.__retriable_codes = retriable_codes self.__get_count = 0 def handler(self, context): if self.__get_count < len(self.__retriable_codes): context.set_code(self.__retriable_codes[self.__get_count]) self.__get_count += 1 return DEFAULT_ZONE def reset_state(self): self.__get_count = 0 def test_retriable_codes(): retriable_codes = [grpc.StatusCode.RESOURCE_EXHAUSTED, grpc.StatusCode.UNAVAILABLE, grpc.StatusCode.DATA_LOSS] service = _RetriableCodes(retriable_codes) server = grpc_server(service.handler) with default_channel() as channel: for retry_qty in range(len(retriable_codes)): interceptor = RetryInterceptor(max_retry_count=retry_qty, retriable_codes=retriable_codes) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) with pytest.raises(grpc.RpcError) as e: client.Get(zone_service_pb2.GetZoneRequest(zone_id="id")) assert e.value.code() == retriable_codes[retry_qty] service.reset_state() interceptor = RetryInterceptor(max_retry_count=len(retriable_codes), retriable_codes=retriable_codes) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) assert client.Get(zone_service_pb2.GetZoneRequest(zone_id="id")) == DEFAULT_ZONE server.stop(0) class _AlwaysUnavailable: def __init__(self): self.__get_count = 0 self.__t_checker = None self.__error = False @property def error(self): return self.__error def handler(self, context): if self.__t_checker and not self.__t_checker(): self.__error = True self.__get_count += 1 if self.__get_count == 100: pass context.set_code(grpc.StatusCode.UNAVAILABLE) return DEFAULT_ZONE @pytest.mark.parametrize("backoff", [None, default_backoff(), backoff_linear_with_jitter(0.05, 0.1)]) def test_infinite_retries_deadline_and_backoff(backoff): service = _AlwaysUnavailable() server = grpc_server(service.handler) with default_channel() as channel: interceptor = RetryInterceptor(max_retry_count=-1, retriable_codes=[grpc.StatusCode.UNAVAILABLE], add_retry_count_to_header=True, back_off_func=backoff) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) with pytest.raises(grpc.RpcError) as e: client.Get(zone_service_pb2.GetZoneRequest(zone_id="id"), timeout=5) assert e.value.code() == grpc.StatusCode.DEADLINE_EXCEEDED server.stop(0) class _NeverReturnsInTime: def __init__(self, shutdown): self.__shutdown = shutdown def handler(self, context): time_remaining = context.time_remaining() # using hack here, since deadline is never None. 31557600 ~= one year in seconds if time_remaining < 31557600.: self.__shutdown.wait() context.set_code(grpc.StatusCode.UNAVAILABLE) return DEFAULT_ZONE def test_per_call_timeout(): shutdown = Event() service = _NeverReturnsInTime(shutdown) server = grpc_server(service.handler) with default_channel() as channel: interceptor = RetryInterceptor(max_retry_count=10, retriable_codes=[grpc.StatusCode.UNAVAILABLE], per_call_timeout=1, add_retry_count_to_header=True) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) with pytest.raises(grpc.RpcError) as e: client.Get(zone_service_pb2.GetZoneRequest(zone_id="id")) assert e.value.code() == grpc.StatusCode.DEADLINE_EXCEEDED shutdown.set() server.stop(1) class _HeaderTokenAndRetryCount: def __init__(self): self.__query_count = 0 self.__token = None self.__token_error = False self.__header_error = False @property def error(self): return self.__header_error or self.__token_error def handler(self, context): metadata = context.invocation_metadata() if metadata is not None: token = [v[1] for v in metadata if v[0] == "idempotency-key"] if len(token) != 1: self.__token_error = True else: # store token on first call, on consequent calls, check that token didn't change if self.__query_count == 0: self.__token = token[0] else: if self.__token != token[0]: self.__token_error = True if self.__query_count > 0: retry_meta = [v[1] for v in metadata if v[0] == "x-retry-attempt"] if len(retry_meta) != 1 or retry_meta[0] != str(self.__query_count): self.__header_error = True else: self.__token_error = True self.__header_error = True self.__query_count += 1 context.set_code(grpc.StatusCode.UNAVAILABLE) return DEFAULT_ZONE def test_header_token_and_retry_count(): service = _HeaderTokenAndRetryCount() server = grpc_server(service.handler) with default_channel() as channel: interceptor = RetryInterceptor(max_retry_count=100, retriable_codes=[grpc.StatusCode.UNAVAILABLE], add_retry_count_to_header=True) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) with pytest.raises(grpc.RpcError) as e: client.Get(zone_service_pb2.GetZoneRequest(zone_id="id")) assert e.value.code() == grpc.StatusCode.UNAVAILABLE assert not service.error server.stop(0) class _TokenUnchanged: def __init__(self, token): self.__token = token self.__token_changed = False @property def token_changed(self): return self.__token_changed def handler(self, context): metadata = context.invocation_metadata() if metadata is not None: token = [v[1] for v in metadata if v[0] == "idempotency-key"] if len(token) != 1 or token[0] != self.__token: self.__token_changed = True else: self.__token_changed = True context.set_code(grpc.StatusCode.UNAVAILABLE) return DEFAULT_ZONE def test_idempotency_token_not_changed(): token = str(uuid.uuid4()) service = _TokenUnchanged(token) server = grpc_server(service.handler) with default_channel() as channel: interceptor = RetryInterceptor(max_retry_count=100, retriable_codes=[grpc.StatusCode.UNAVAILABLE], add_retry_count_to_header=True) ch = grpc.intercept_channel(channel, interceptor) client = zone_service_pb2_grpc.ZoneServiceStub(ch) with pytest.raises(grpc.RpcError) as e: client.Get(zone_service_pb2.GetZoneRequest(zone_id="id"), metadata=[("idempotency-key", token)]) assert e.value.code() == grpc.StatusCode.UNAVAILABLE assert not service.token_changed server.stop(0)
176834
class FakeConfig(object): def __init__( self, src_dir=None, spec_dir=None, stylesheet_urls=None, script_urls=None, stop_spec_on_expectation_failure=False, stop_on_spec_failure=False, random=True ): self._src_dir = src_dir self._spec_dir = spec_dir self._stylesheet_urls = stylesheet_urls self._script_urls = script_urls self._stop_spec_on_expectation_failure = stop_spec_on_expectation_failure self._stop_on_spec_failure = stop_on_spec_failure self._random = random self.reload_call_count = 0 def src_dir(self): return self._src_dir def spec_dir(self): return self._spec_dir def stylesheet_urls(self): return self._stylesheet_urls def script_urls(self): return self._script_urls def stop_spec_on_expectation_failure(self): return self._stop_spec_on_expectation_failure def stop_on_spec_failure(self): return self._stop_on_spec_failure def random(self): return self._random def reload(self): self.reload_call_count += 1
176837
import os import shutil import time import glob import subprocess import web from libs import utils, form_utils from libs.logger import logger import settings subscription_versions = ['normal', 'nomail', 'digest'] def __get_ml_dir(mail): """Get absolute path of the root directory of mailing list account.""" if not utils.is_email(mail): return None mail = str(mail).lower() (_username, _domain) = mail.split('@', 1) return os.path.join(settings.MLMMJ_SPOOL_DIR, _domain, _username) def __get_ml_subscribers_dir(mail, subscription): """ Get absolute path of the directory used to store subscribers which subscribed to given subscription version. @mail -- mail address of mailing list account @subscription -- subscription version: normal, nomail, digest. """ if subscription == 'digest': return os.path.join(__get_ml_dir(mail=mail), 'digesters.d') elif subscription == 'nomail': return os.path.join(__get_ml_dir(mail=mail), 'nomailsubs.d') else: # subscription == 'normal' return os.path.join(__get_ml_dir(mail=mail), 'subscribers.d') def __remove_ml_sub_dir(mail, dirname): if not dirname: return (True, ) _ml_dir = __get_ml_dir(mail=mail) _sub_dir = os.path.join(_ml_dir, dirname) if os.path.exists(_sub_dir): try: shutil.rmtree(_sub_dir) logger.debug("[{0}] {1}, removed sub-directory: {2}".format(web.ctx.ip, mail, _sub_dir)) except Exception as e: logger.error("[{0}] {1}, error while removing sub-directory: {2}".format(web.ctx.ip, mail, _sub_dir)) return (False, repr(e)) return (True, ) def __set_file_permission(path): _uid = os.getuid() _gid = os.getgid() try: os.chown(path, _uid, _gid) return (True, ) except Exception as e: return (False, repr(e)) def __copy_dir_files(src, dest, create_dest=True): """Copy all regular files under source directory to dest directory.""" if create_dest: if not os.path.exists(dest): try: os.makedirs(dest, mode=settings.MLMMJ_FILE_PERMISSION) except Exception as e: return (False, repr(e)) for fn in os.listdir(src): _src_file = os.path.join(src, fn) if os.path.isfile(_src_file): shutil.copy(_src_file, dest) return (True, ) def __has_ml_dir(mail, path=None): if path: _ml_dir = path else: _ml_dir = __get_ml_dir(mail=mail) if os.path.exists(_ml_dir): return True else: return False def __has_param_file(f): if os.path.exists(f): return True else: return False def __get_param_file(mail, param): """Get path to the file used to control parameter setting. Sample value: /var/spool/mlmmj/<domain>/<username>/control/<param> """ if not utils.is_email(mail): return None (_username, _domain) = mail.split('@', 1) return os.path.join(settings.MLMMJ_SPOOL_DIR, _domain, _username, 'control', param) def __remove_file(path): if os.path.exists(path): try: os.remove(path) except Exception as e: logger.error("[{0}] error while removing parameter file: {1}, {2}".format(web.ctx.ip, path, e)) return (False, repr(e)) return (True, ) def __remove_param_file(mail, param): _path = __get_param_file(mail=mail, param=param) return __remove_file(_path) def __get_param_type(param): """Get parameter type. Possible param type must be one of: boolean, list, normal, text, or None (no such param). """ for (_type, _param_dict) in list(settings.MLMMJ_PARAM_TYPES.items()): if param in list(_param_dict.values()): return _type return None def __get_boolean_param_value(mail, param): _param_file = __get_param_file(mail=mail, param=param) if __has_param_file(_param_file): return 'yes' else: return 'no' def __get_list_param_value(mail, param, is_email=False, param_file=None): if not param_file: param_file = __get_param_file(mail=mail, param=param) _values = [] if __has_param_file(param_file): try: with open(param_file, "r", encoding="utf-8") as f: _lines = f.readlines() _lines = [_line.strip() for _line in _lines] # remove line breaks _values = [_line for _line in _lines if _line] # remove empty values if is_email: _values = [str(i).lower() for i in _values] except IOError: # No such file. pass except Exception as e: logger.error('Error while getting (list) parameter value: {0} -> {1}'.format(param, e)) _values.sort() return _values def __get_normal_param_value(mail, param, param_file=None): # Only first line is used by mlmmj. if not param_file: param_file = __get_param_file(mail=mail, param=param) try: with open(param_file, 'r', encoding='utf-8') as f: # Remove newline but keep spaces. value = f.readline().rstrip('\n') return value except IOError: # No such file. return '' except Exception as e: logger.error("[{0}] {1}, error while getting parameter value: {2}, {3}".format(web.ctx.ip, mail, param, e)) return '' def __get_text_param_value(mail, param, param_file=None): # Full content is used by mlmmj. if not param_file: param_file = __get_param_file(mail=mail, param=param) try: with open(param_file, 'r', encoding='utf-8') as f: value = f.read().rstrip('\n') return value except IOError: # No such file. return '' except Exception as e: logger.error("[{0}] {1}, error while getting parameter value: {2}, {3}".format(web.ctx.ip, mail, param, e)) return '' def __get_other_param_value(mail, param): if param in settings.MLMMJ_OTHER_PARAM_MAP: _v = settings.MLMMJ_OTHER_PARAM_MAP[param] _param_type = _v['type'] _mlmmj_param = _v['mlmmj_param'] _is_email = _v.get('is_email', False) if _param_type == 'boolean': return __get_boolean_param_value(mail=mail, param=_mlmmj_param) elif _param_type == 'list': return __get_list_param_value(mail, param=_mlmmj_param, is_email=_is_email) elif _param_type == 'normal': return __get_normal_param_value(mail, param=_mlmmj_param) elif _param_type == 'text': return __get_text_param_value(mail, param=_mlmmj_param) return 'INVALID_PARAM' def __get_param_value(mail, param): """Get value of given mailing list parameter. Possible returned values: - (False, <error_reason>) - (True, {'type': 'boolean', 'value': 'yes|no'}) - (True, {'type': 'list', 'value': [...]}) - (True, {'type': 'normal', 'value': '...'}) - (True, {'type': 'text', 'value': '...'}) """ if param in settings.MLMMJ_OTHER_WEB_PARAMS: _v = settings.MLMMJ_OTHER_PARAM_MAP[param] _param_type = _v['type'] _value = __get_other_param_value(mail=mail, param=param) return (True, {'type': _param_type, 'value': _value}) if param not in settings.MLMMJ_PARAM_NAMES: logger.error("[{0}] {1}, unknown parameter: {2}".format(web.ctx.ip, mail, param)) return (False, 'INVALID_PARAM') _param_file = __get_param_file(mail=mail, param=param) _param_type = __get_param_type(param=param) _ret = {'type': _param_type, 'value': None} # control file doesn't exist if not __has_param_file(_param_file): if _param_type == 'list': _ret['value'] = [] elif _param_type == 'boolean': _ret['value'] = 'no' else: _ret['value'] = '' return (True, _ret) if _param_type == 'boolean': _ret['value'] = 'yes' else: if _param_type == 'text': _func = __get_text_param_value elif _param_type == 'list': _func = __get_list_param_value else: # _param_type == 'normal': _func = __get_normal_param_value _ret['value'] = _func(mail=mail, param=param, param_file=_param_file) return (True, _ret) def __update_boolean_param(mail, param, value, param_file=None, touch_instead_of_create=False): """Create or remove parameter file for boolean type parameter. @touch_instead_of_create - touch parameter file instead of re-create it. """ if not param_file: param_file = __get_param_file(mail=mail, param=param) if value == 'yes': try: if touch_instead_of_create: open(param_file, 'a', encoding='utf-8').close() else: open(param_file, 'w', encoding='utf-8').close() # Avoid some conflicts if param == 'subonlypost': __remove_param_file(mail=mail, param='modonlypost') if param == 'modonlypost': __remove_param_file(mail=mail, param='subonlypost') # Create 'control/moderated' also _f = __get_param_file(mail=mail, param='moderated') open(_f, 'a', encoding='utf-8').close() except Exception as e: logger.error("[{0}] {1}, error while updating (boolean) parameter: {2} -> {3}, {4}".format( web.ctx.ip, mail, param, value, e)) return (False, repr(e)) else: qr = __remove_file(path=param_file) if not qr[0]: return qr logger.info("[{0}] {1}, updated (boolean) parameter: {2} -> {3}".format(web.ctx.ip, mail, param, value)) return (True, ) def __update_normal_param(mail, param, value, param_file=None, is_email=False): # Although we write all given value, but only first line is used by mlmmj. if not param_file: param_file = __get_param_file(mail=mail, param=param) if param == 'maxmailsize': try: value = int(value) except: value = 0 if not value: # Remove param file. qr = __remove_file(path=param_file) return qr if value: if is_email: value = str(value).lower() if not utils.is_email(value): return (False, 'INVALID_EMAIL') try: if isinstance(value, int): value = str(value) with open(param_file, 'w', encoding='utf-8') as f: f.write(value + '\n') except Exception as e: logger.error("[{0}] {1}, error while updating (normal) parameter: {2} -> {3}, {4}".format( web.ctx.ip, mail, param, value, e)) return (False, repr(e)) else: qr = __remove_file(path=param_file) if not qr[0]: return qr logger.info("[{0}] {1}, updated (normal) parameter: {2} -> {3}".format(web.ctx.ip, mail, param, value)) return (True, ) def __update_list_param(mail, param, value, param_file=None, is_email=False): if not param_file: param_file = __get_param_file(mail=mail, param=param) if isinstance(value, str): _values = __convert_web_param_value_to_list(value=value, is_email=is_email) else: _values = value if _values: try: param_file = __get_param_file(mail=mail, param=param) if param == 'listaddress': # Remove primary address(es) _values = [v for v in _values if v != mail] # Prepend primary address (must be first one) _values = [mail] + _values with open(param_file, 'w', encoding='utf-8') as f: f.write('\n'.join(_values) + '\n') logger.info("[{0}] {1}, updated: {2} -> {3}".format(web.ctx.ip, mail, param, ', '.join(_values))) except Exception as e: logger.error("[{0}] {1}, error while updating (list) parameter: {2} -> {3}, {4}".format( web.ctx.ip, mail, param, value, e)) return (False, repr(e)) else: qr = __remove_file(path=param_file) if not qr[0]: return qr logger.info("[{0}] {1}, updated (list) parameter: {2} -> {3}".format(web.ctx.ip, mail, param, value)) return (True, ) def __update_text_param(mail, param, value, param_file=None, create_if_empty=False): if not param_file: param_file = __get_param_file(mail=mail, param=param) if value: try: if isinstance(value, int): value = str(value) else: value = value.strip() # Footer text/html must ends with an empty line, otherwise # the characters will be a mess. with open(param_file, 'w', encoding='utf-8') as f: f.write(value + '\n') except Exception as e: logger.error("[{0}] {1}, error while updating (normal) parameter: {2} -> {3}, {4}".format( web.ctx.ip, mail, param, value, e)) return (False, repr(e)) else: if create_if_empty: # Footer text/html must ends with an empty line, otherwise # the characters will be a mess. with open(param_file, 'w', encoding='utf-8') as f: f.write('\n') else: qr = __remove_file(path=param_file) if not qr[0]: return qr logger.info("[{0}] {1}, updated (text) parameter: {2} -> {3}".format(web.ctx.ip, mail, param, value)) return (True, ) def __update_other_param(mail, param, value): """Update parameters which cannot be simply mapped to a mlmmj parameter.""" if param in settings.MLMMJ_OTHER_PARAM_MAP: _v = settings.MLMMJ_OTHER_PARAM_MAP[param] _param_type = _v['type'] _mlmmj_param = _v['mlmmj_param'] _is_email = _v.get('is_email', False) _param_file = __get_param_file(mail=mail, param=_mlmmj_param) if _param_type == 'boolean': return __update_boolean_param(mail=mail, param=_mlmmj_param, param_file=_param_file, value=value, touch_instead_of_create=True) elif _param_type == 'list': return __update_list_param(mail=mail, param=_mlmmj_param, param_file=_param_file, value=value, is_email=_is_email) elif _param_type == 'normal': return __update_normal_param(mail=mail, param=_mlmmj_param, param_file=_param_file, value=value, is_email=_is_email) elif _param_type == 'text': return __update_text_param(mail=mail, param=_mlmmj_param, param_file=_param_file, value=value) return (True, ) def __update_mlmmj_param(mail, param, value): """Update individual parameter of mailing list account.""" _param_type = __get_param_type(param) if _param_type == 'boolean': _update_func = __update_boolean_param elif _param_type == 'normal': _update_func = __update_normal_param elif _param_type == 'list': _update_func = __update_list_param elif _param_type == 'text': _update_func = __update_text_param elif _param_type == 'other': _update_func = __update_other_param else: logger.error("[{0}] {1}, unknown parameter: {2}".format(web.ctx.ip, mail, param)) return (False, 'INVALID_PARAM_TYPE') qr = _update_func(mail=mail, param=param, value=value) return qr def __update_mlmmj_params(mail, **kwargs): """Update multiple parameters of mailing list account. Abort if failed to update any parameter. Parameters must be used by mlmmj directly, not the ones used by web form. """ if kwargs: for (k, v) in list(kwargs.items()): qr = __update_mlmmj_param(mail=mail, param=k, value=v) if not qr[0]: return qr # If we have `footer_html`, make sure `footer_text` always exists, # otherwise AlterMIME may not work and email will be discarded. if kwargs.get('footer_html'): (_status, _d) = __get_param_value(mail, 'footer_text') if _status and (not _d.get('value')): __update_text_param(mail=mail, param='footer_text', value='', create_if_empty=True) return (True, ) def __convert_web_param_value_to_list(value, is_email=False): try: # Split by ',' and remove empty values v = [i for i in value.replace(' ', '').split(',') if i] except: v = [] if v and is_email: v = [str(i).lower() for i in v if utils.is_email(i)] return v def __convert_form_to_mlmmj_params(mail, form): """Convert variables in web form to (a dict of) mlmmj parameters.""" # Both 'moderate_subscription' and 'subscription_moderators' use same # mlmmj parameter name 'submod' if 'moderate_subscription' in form and 'subscription_moderators' in form: _mod = form.get('moderate_subscription') _moderators = form.get('subscription_moderators') if _mod == 'yes': if _moderators: # If there's some moderators, it will create 'submod' file # with emails of moderators. If file 'submod' presents, it # means moderation subscription is enabled. So we should remove # 'moderate_subscription' parameter here to avoid improper # file removal or re-creation (with empty content) form.pop('moderate_subscription') else: # If no subscription moderators, use an empty 'submod' file # and use mailing list owners as subscription moderators. form.pop('subscription_moderators') else: # remove 'subscription_moderators' and let mlmmjadmin remove # 'submod' directly. form.pop('subscription_moderators') # solve conflict of 'only_moderator_can_post' and 'only_subscriber_can_post' # 'only_moderator_can_post' should has higher priority if 'only_moderator_can_post' in form and 'only_subscriber_can_post' in form: if form.get('only_moderator_can_post') == 'yes': form['only_subscriber_can_post'] = 'no' # Store key:value of mlmmj parameters kvs = {} # Convert form variable names to mlmmj parameter names for param in form: kv = form_utils.get_dict_for_form_param(mail=mail, form=form, param=param) kvs.update(kv) return kvs def __archive_ml(mail): _dir = __get_ml_dir(mail=mail) if __has_ml_dir(mail=mail, path=_dir): _timestamp = time.strftime('-%Y%m%d%H%M%S', time.gmtime()) _new_dir = _dir + _timestamp if settings.MLMMJ_ARCHIVE_DIR: # Move to archive directory. __base_dir = _new_dir.replace(settings.MLMMJ_SPOOL_DIR, settings.MLMMJ_ARCHIVE_DIR) _new_dir = os.path.join(settings.MLMMJ_ARCHIVE_DIR, __base_dir) # Create parent directory if _new_dir.endswith('/'): _new_dir = os.path.dirname(_new_dir) # If new directory exists, append one more timestamp if os.path.exists(_new_dir): _new_dir = _new_dir + _timestamp # Create archive directory try: os.makedirs(_new_dir, mode=settings.MLMMJ_FILE_PERMISSION) except Exception as e: _msg = "error while creating directory under archive directory ({0}), {1}".format(_new_dir, repr(e)) logger.error("[{0}] {1}, {2}".format(web.ctx.ip, mail, _msg)) return (False, _msg) try: # Don't use `os.rename()` to handle this move, it raises error # if src and dest directories are not on same disk partition. shutil.move(_dir, _new_dir) logger.info("[{0}] {1}, archived: {2} -> {3}".format(web.ctx.ip, mail, _dir, _new_dir)) # Return new directory path return (True, _new_dir) except Exception as e: logger.error("[{0}] {1}, error while archiving: {2} ({3} -> {4})".format(web.ctx.ip, mail, repr(e), _dir, _new_dir)) return (False, repr(e)) return (True, ) def __remove_lines_in_file(path, lines): """ Remove line from given file. :param path: path to file :param lines: a list/dict/tuple of lines you want to remove """ if not lines: return (True, ) if not os.path.exists(path): return (True, ) try: with open(path, 'r', encoding='utf-8') as _f: _file_lines = _f.readlines() stripped_file_lines = [line.strip() for line in _file_lines] given_lines = [line.strip() for line in lines] filtered_lines = set(stripped_file_lines) - set(given_lines) if filtered_lines: with open(path, 'w', encoding='utf-8') as f: f.write('\n'.join(filtered_lines) + '\n') else: # Remove file qr = __remove_file(path=path) if not qr[0]: return qr return (True, ) except Exception as e: return (False, repr(e)) def __add_lines_in_file(f, lines): """ Add lines to given file. @f -- path to file @lines -- a list/dict/tuple of lines you want to remove @sort_before_saving -- A switch to sort lines before saving. """ if not lines: return (True, ) file_lines = [] try: if os.path.exists(f): with open(f, 'r', encoding='utf-8') as _f: file_lines = _f.readlines() lines = [i + '\n' for i in lines] file_lines += lines # Remove duplicate lines. file_lines = list(set(file_lines)) with open(f, 'w', encoding='utf-8') as nf: nf.write(''.join(file_lines)) return (True, ) except Exception as e: return (False, repr(e)) def __add_subscribers_with_confirm(mail, subscribers, subscription='normal'): """ Add subscribers with confirm. @mail -- mail address of mailing list @subscribers -- a list/tuple/set of subscribers' mail addresses @subscription -- subscription version (normal, digest, nomail) """ _dir = __get_ml_dir(mail) # Get absolute path of command `mlmmj-sub` _cmd_mlmmj_sub = settings.CMD_MLMMJ_SUB if not _cmd_mlmmj_sub: if os.path.exists('/usr/bin/mlmmj-sub'): _cmd_mlmmj_sub = '/usr/bin/mlmmj-sub' elif os.path.exists('/usr/local/bin/mlmmj-sub'): _cmd_mlmmj_sub = '/usr/local/bin/mlmmj-sub' else: return (False, 'SUB_COMMAND_NOT_FOUND') # mlmmj-sub arguments # # -L: Full path to list directory # -a: Email address to subscribe # -C: Request mail confirmation # -d: Subscribe to `digest` version of the list # -n: Subscribe to nomail version of the list _cmd = [_cmd_mlmmj_sub, '-L', _dir, '-C'] if subscription == 'digest': _cmd.append('-d') elif subscription == 'nomail': _cmd.append('-n') # Directory used to store subscription confirm notifications _subconf_dir = os.path.join(_dir, 'subconf') _error = {} for addr in subscribers: try: # Remove confirm file generated before this request _old_conf_files = glob.glob(os.path.join(_subconf_dir, '????????????????-' + addr.replace('@', '='))) for _f in _old_conf_files: qr = __remove_file(path=_f) if not qr[0]: return qr # Send new confirm _new_cmd = _cmd[:] + ['-a', addr] subprocess.Popen(_new_cmd, stdout=subprocess.PIPE) logger.debug("[{0}] {1}, queued confirm mail for {2}.".format(web.ctx.ip, mail, addr)) except Exception as e: logger.error("[{0}] {1}, error while subscribing {2}: {3}".format(web.ctx.ip, mail, addr, e)) _error[addr] = repr(e) if not _error: return (True, ) else: return (False, repr(_error)) def has_subscriber(mail, subscriber, subscription=None): """ Check whether mailing list `<mail>` has subscriber `<subscriber>`. Return `(True, <subscription>)` or `False`. """ mail = str(mail).lower() subscriber = str(subscriber).lower() if subscription: subscriptions = [subscription] else: subscriptions = subscription_versions for subscription in subscriptions: _sub_dir = __get_ml_subscribers_dir(mail=mail, subscription=subscription) _sub_file = os.path.join(_sub_dir, subscriber[0]) if os.path.exists(_sub_file): with open(_sub_file, 'r', encoding='utf-8') as f: for line in f: if line.strip() == subscriber: return (True, subscription) return False def is_maillist_exists(mail): if __has_ml_dir(mail): return True else: return False # This is the function we can get both web parameter and mlmmj parameter names. def get_web_param_value(mail, param): """Get mlmmj parameter value of given web parameter name.""" if param in settings.MLMMJ_WEB_PARAMS: _mlmmj_param = settings.MLMMJ_WEB_PARAMS[param] v = __get_param_value(mail=mail, param=_mlmmj_param) if param == 'extra_addresses': if mail in v[1]['value']: v[1]['value'].remove(mail) return v else: return (False, 'INVALID_PARAM') def add_maillist_from_web_form(mail, form): """Add a mailing list based on data submited from web form. @mail - mail address of mailing list account @form - a dict of web form input """ domain = mail.split('@', 1)[-1] # Store mlmmj parameters kvs = {} # Add empty values for 'remove_headers', 'custom_headers'. This will # trigger form process functions to add pre-defined default values. if 'remove_headers' not in form: form['remove_headers'] = '' if 'custom_headers' not in form: form['custom_headers'] = '' # Set 'owner' to 'postmaster@<domain>' if 'owner' not in form: form['owner'] = 'postmaster@' + domain # Set 'owner' to 'postmaster@<domain>' if 'moderators' not in form: form['moderators'] = 'postmaster@' + domain # If `footer_html` exists but `footer_text` doesn't if 'footer_html' in form and 'footer_text' not in form: form['footer_text'] = '' kvs.update(__convert_form_to_mlmmj_params(mail=mail, form=form)) # Add (missing) default settings _form = settings.MLMMJ_DEFAULT_PROFILE_SETTINGS for param in _form: # Avoid conflict parameters. if param == 'only_subscriber_can_post' and \ form.get('only_moderator_can_post') == 'yes': continue if param == 'only_moderator_can_post' and \ form.get('only_subscriber_can_post') == 'yes': continue if param not in form: kv = form_utils.get_dict_for_form_param(mail=mail, form=_form, param=param) kvs.update(kv) # Always set values _form = settings.MLMMJ_FORCED_PROFILE_SETTINGS for param in _form: kv = form_utils.get_dict_for_form_param(mail=mail, form=_form, param=param) kvs.update(kv) qr = create_ml(mail=mail, **kvs) return qr def create_ml(mail, **kwargs): """Create required directories/files for a new mailing list on file system. WARNING: it doesn't check whether account already exists in backend. @mail - full email address of new mailing list you're going to create @kwargs - dict of parameter/value pairs used to set account profile """ if not utils.is_email(mail): return (False, 'INVALID_EMAIL') mail = str(mail).lower() _ml_dir = __get_ml_dir(mail=mail) if not os.path.exists(_ml_dir): try: os.makedirs(_ml_dir, mode=settings.MLMMJ_FILE_PERMISSION) except Exception as e: _msg = "error while creating base directory ({0}), {1}".format(_ml_dir, repr(e)) logger.error("[{0}] {1}, {2}".format(web.ctx.ip, mail, _msg)) return (False, _msg) # Create required sub-directories for _dir in settings.MLMMJ_DEFAULT_SUB_DIRS: _sub_dir = os.path.join(_ml_dir, _dir) if not os.path.exists(_sub_dir): try: os.makedirs(_sub_dir, mode=settings.MLMMJ_FILE_PERMISSION) except Exception as e: _msg = "error while creating sub-directory ({0}), {1}".format(_sub_dir, repr(e)) logger.error("[{0}] {1}, {2}".format(web.ctx.ip, mail, _msg)) return (False, _msg) else: qr = __set_file_permission(_sub_dir) if not qr[0]: return qr # Create file `control/listaddress` with primary address _f = os.path.join(_ml_dir, 'control/listaddress') with open(_f, 'w', encoding='utf-8') as f: f.write('{0}\n'.format(mail)) # Create extra control file index_path = os.path.join(_ml_dir, 'index') open(index_path, 'w', encoding='utf-8').close() # Copy skel/language template files _sub_dir_text = os.path.join(_ml_dir, 'text') _language = kwargs.get('language', 'en') _src_dir = os.path.join(settings.MLMMJ_SKEL_DIR, _language) if not os.path.exists(_src_dir): logger.error("Skel directory does not exist: {0}".format(_src_dir)) return (False, 'SKEL_DIR_NOT_EXIST') qr = __copy_dir_files(_src_dir, _sub_dir_text) if not qr[0]: return qr qr = __update_mlmmj_params(mail=mail, **kwargs) if not qr[0]: return qr return (True, ) def delete_ml(mail, archive=True): """Delete a mailing list account. If archive is True or 'yes', account is 'removed' by renaming its data directory. """ _ml_dir = __get_ml_dir(mail=mail) if os.path.exists(_ml_dir): if archive in [True, 'yes']: qr = __archive_ml(mail=mail) return qr else: try: shutil.rmtree(_ml_dir) logger.info("[{0}] {1}, removed without archiving.".format(web.ctx.ip, mail)) except Exception as e: logger.error("[{0}] {1}, error while removing list from file system: {2}".format(web.ctx.ip, mail, repr(e))) return (False, repr(e)) else: logger.info("[{0}] {1}, removed (no data on file system).".format(web.ctx.ip, mail)) return (True, ) def update_web_form_params(mail, form): """Update mailing list profile with web form.""" kvs = {} kvs.update(__convert_form_to_mlmmj_params(mail=mail, form=form)) return __update_mlmmj_params(mail=mail, **kvs) def get_subscribers(mail, email_only=False): """Get subscribers of given subscription version. :param mail: mail address of mailing list account :param email_only: if True, return a list of subscribers' mail addresses. """ subscribers = [] for subscription in subscription_versions: _dir = __get_ml_subscribers_dir(mail=mail, subscription=subscription) try: fns = os.listdir(_dir) except: continue for fn in fns: _addresses = [str(i).lower().strip() for i in open(os.path.join(_dir, fn)).readlines()] if email_only: subscribers += _addresses else: subscribers += [{'mail': i, 'subscription': subscription} for i in _addresses] if email_only: subscribers.sort() return (True, subscribers) def remove_subscribers(mail, subscribers): """Remove multiple subscribers from given mailing list. :param mail: mail address of mailing list account :param subscribers: a list/tuple/set of subscribers' mail addresses. """ mail = mail.lower() subscribers = [str(i).lower() for i in subscribers if utils.is_email(i)] if not subscribers: return (True, ) grouped_subscribers = {} for i in subscribers: letter = i[0] if letter in grouped_subscribers: grouped_subscribers[letter].append(i) else: grouped_subscribers[letter] = [i] for subscription in ['normal', 'digest', 'nomail']: _dir = __get_ml_subscribers_dir(mail=mail, subscription=subscription) for letter in grouped_subscribers: # Get file stores the subscriber. path = os.path.join(_dir, letter) qr = __remove_lines_in_file(path=path, lines=grouped_subscribers[letter]) if not qr[0]: return qr return (True, ) def remove_all_subscribers(mail): """ Remove all subscribers. :param mail: mail address of mailing list account """ mail = mail.lower() _dirs = [__get_ml_subscribers_dir(mail=mail, subscription=i) for i in subscription_versions] try: for _dir in _dirs: for fn in os.listdir(_dir): _path = os.path.join(_dir, fn) qr = __remove_file(path=_path) if not qr[0]: return qr except Exception as e: return (False, repr(e)) return (True, ) def add_subscribers(mail, subscribers, subscription='normal', require_confirm=True): """Add subscribers to given subscription version of mailing list. :param mail: mail address of mailing list account :param subscribers: a list/tuple/set of subscribers' email addresses :param subscription: subscription version: normal, nomail, digest. :param require_confirm: subscription version: normal, nomail, digest. """ mail = mail.lower() subscribers = [str(i).lower() for i in subscribers if utils.is_email(i)] if not subscribers: return (True, ) if require_confirm: qr = __add_subscribers_with_confirm(mail=mail, subscribers=subscribers, subscription=subscription) if not qr[0]: logger.error("[{0}] {1} Failed to add subscribers (require " "confirm): error={2}".format(web.ctx.ip, mail, qr[1])) return qr else: grouped_subscribers = {} for i in subscribers: letter = i[0] if letter in grouped_subscribers: grouped_subscribers[letter].append(i) else: grouped_subscribers[letter] = [i] _dir = __get_ml_subscribers_dir(mail=mail, subscription=subscription) for letter in grouped_subscribers: # Get file stores the subscriber. path = os.path.join(_dir, letter) qr = __add_lines_in_file(f=path, lines=grouped_subscribers[letter]) if not qr[0]: logger.error('[{0}] {1} Failed to add subscribers to file: ' 'error={2}'.format(web.ctx.ip, mail, qr[1])) return qr logger.info('[{0}] {1}, added subscribers without confirming: {2}.'.format(web.ctx.ip, mail, ', '.join(subscribers))) return (True, ) def subscribe_to_lists(subscriber, lists, subscription='normal', require_confirm=True): """Add one subscriber to multiple mailing lists. @subscriber -- mail address of subscriber @lists -- a list/tuple/set of mailing lists @subscription -- subscription version: normal, nomail, digest. @require_confirm -- subscription version: normal, nomail, digest. """ subscriber = subscriber.lower() lists = [str(i).lower() for i in lists if utils.is_email(i)] if not lists: return (True, ) for ml in lists: qr = add_subscribers(mail=ml, subscribers=[subscriber], subscription=subscription, require_confirm=require_confirm) if not qr[0]: return qr return (True, )
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import numpy from amuse.test import amusetest from amuse.units import units, nbody_system from amuse.ic.brokenimf import * # Instead of random, use evenly distributed numbers, just for testing default_options = dict(random=False) class TestMultiplePartIMF(amusetest.TestCase): def test1(self): print("Test MultiplePartIMF with default mass_boundaries and alphas, i.e. Salpeter") instance = MultiplePartIMF(mass_max=100.0 | units.MSun) self.assertEqual(instance.mass_boundaries, [0.1, 100.0] | units.MSun) self.assertEqual(instance.alphas, [-2.35]) self.assertEqual(instance.number_of_bins, 1) self.assertEqual(instance.fraction_per_bin, [1.0]) self.assertEqual(instance.cumulative_fractions, [0.0, 1.0]) self.assertAlmostEqual(instance.mass([0.0]), 0.1 | units.MSun) self.assertAlmostEqual(instance.mass([1.0]), 100.0 | units.MSun) self.assertAlmostEqual(instance.mass_mean(), 0.351 | units.MSun, 3) def test2(self): print("Test MultiplePartIMF with mass_boundaries and alphas") instance = MultiplePartIMF(mass_boundaries = [1.0, 10.0, 100.0] | units.MSun, alphas = [1.3, -3.3], **default_options) self.assertEqual(instance.mass_boundaries, [1.0, 10.0, 100.0] | units.MSun) self.assertEqual(instance.alphas, [1.3, -3.3]) self.assertEqual(instance.number_of_bins, 2) self.assertAlmostEqual(instance.fraction_per_bin, numpy.array([0.5, 0.5])) self.assertEqual(instance.cumulative_fractions, [0.0, 0.5, 1.0]) self.assertAlmostEqual(instance.mass([0.0]), 1.0 | units.MSun) self.assertAlmostEqual(instance.mass([0.5]), 10.0 | units.MSun) self.assertAlmostEqual(instance.mass([1.0]), 100.0 | units.MSun) self.assertAlmostEqual(instance.mass_mean(), 11.9457684987 | units.MSun) self.assertAlmostEqual(instance.mass_mean(), instance.next_mass(10000).mean(), 2) def test3(self): print("Test new_broken_power_law_mass_distribution with default mass_boundaries and alphas, i.e. Salpeter") masses = new_broken_power_law_mass_distribution(10000, mass_max=100.0 | units.MSun, **default_options) self.assertTrue((masses >= 0.1 | units.MSun).all()) self.assertTrue((masses <= 100.0 | units.MSun).all()) self.assertAlmostEqual(min(masses), 0.1 | units.MSun) self.assertAlmostEqual(max(masses), 100.0 | units.MSun) mass_mean = MultiplePartIMF(mass_boundaries=[0.1, 100.0]|units.MSun, alphas=[-2.35]).mass_mean() self.assertAlmostEqual(mass_mean, 0.35136877959 | units.MSun) self.assertAlmostRelativeEqual(masses.mean(), 0.351 | units.MSun, 1) def test4(self): print("Test new_broken_power_law_mass_distribution with mass_boundaries and alphas") masses = new_broken_power_law_mass_distribution(10000, mass_boundaries = [1.0, 10.0, 100.0] | units.MSun, alphas = [1.3, -3.3], **default_options) self.assertTrue((masses >= 1.0 | units.MSun).all()) self.assertTrue((masses <= 100.0 | units.MSun).all()) self.assertAlmostEqual(min(masses), 1.0 | units.MSun) self.assertAlmostEqual(max(masses), 100.0 | units.MSun) mass_mean = MultiplePartIMF(mass_boundaries=[1.0, 10.0, 100.0]|units.MSun, alphas=[1.3, -3.3]).mass_mean() self.assertAlmostEqual(mass_mean, 11.9457684987 | units.MSun) self.assertAlmostRelativeEqual(masses.mean(), 11.9457684987 | units.MSun, 1) def test5(self): print("Test new_scalo_mass_distribution") masses = new_scalo_mass_distribution(10000, **default_options) self.assertTrue((masses >= 0.1 | units.MSun).all()) self.assertTrue((masses <= 125.0 | units.MSun).all()) self.assertAlmostEqual(min(masses), 0.1 | units.MSun) self.assertAlmostEqual(max(masses), 125.0 | units.MSun) mass_mean = MultiplePartIMF(mass_boundaries=[0.10, 0.18, 0.42, 0.62, 1.18, 3.5, 125.0]|units.MSun, alphas=[1.6, -1.01, -2.75, -2.08, -3.5, -2.63]).mass_mean() self.assertAlmostEqual(mass_mean, 0.487756751788 | units.MSun) self.assertAlmostRelativeEqual(masses.mean(), 0.487756751788 | units.MSun, 1) def test6(self): print("Test new_miller_scalo_mass_distribution") masses = new_miller_scalo_mass_distribution(10000, **default_options) self.assertTrue((masses >= 0.1 | units.MSun).all()) self.assertTrue((masses <= 125.0 | units.MSun).all()) self.assertAlmostEqual(min(masses), 0.1 | units.MSun) self.assertAlmostEqual(max(masses), 125.0 | units.MSun) mass_mean = MultiplePartIMF(mass_boundaries=[0.1, 1.0, 2.0, 10.0, 125.0]|units.MSun, alphas=[-1.25, -2.0, -2.3, -3.3]).mass_mean() self.assertAlmostEqual(mass_mean, 0.885783055149 | units.MSun) self.assertAlmostRelativeEqual(masses.mean(), 0.885783055149 | units.MSun, 1) def test7(self): print("Test new_kroupa_mass_distribution") masses = new_kroupa_mass_distribution(10000, **default_options) self.assertTrue((masses >= 0.01 | units.MSun).all()) roundoff = 1.0 + 1.0e-12 self.assertTrue((masses <= (100.0 * roundoff) | units.MSun).all()) self.assertAlmostEqual(min(masses), 0.01 | units.MSun) self.assertAlmostEqual(max(masses), 100.0 | units.MSun) mass_mean = MultiplePartIMF(mass_boundaries=[0.01, 0.08, 0.5, 100.0]|units.MSun, alphas=[-0.3, -1.3, -2.3]).mass_mean() self.assertAlmostEqual(mass_mean, 0.376175542639 | units.MSun) self.assertAlmostRelativeEqual(masses.mean(), 0.376175542639 | units.MSun, 1) def test8(self): print("Test with problematic alphas (new_salpeter_mass_distribution would give zero division errors)") masses = new_broken_power_law_mass_distribution(10000, mass_boundaries = [1.0, 10.0, 100.0] | units.MSun, alphas = [-1, -2], **default_options) self.assertTrue((masses >= 1.0 | units.MSun).all()) roundoff = 1.0 + 1.0e-12 self.assertTrue((masses <= (100.0 * roundoff) | units.MSun).all()) self.assertAlmostEqual(min(masses), 1.0 | units.MSun) self.assertAlmostEqual(max(masses), 100.0 | units.MSun) mass_mean = MultiplePartIMF(mass_boundaries=[1.0, 10.0, 100.0] | units.MSun, alphas=[-1, -2]).mass_mean() self.assertAlmostEqual(mass_mean, 10.0 | units.MSun) self.assertAlmostRelativeEqual(masses.mean(), 10.0 | units.MSun, 1) masses = new_broken_power_law_mass_distribution(101, mass_boundaries = [1.0, 100.0] | units.MSun, alphas = [-1], **default_options) self.assertAlmostEqual(masses.median(), 10.0 | units.MSun)
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import logging from sqlalchemy.orm import joinedload import smartdb from model import Machine, Schedule, MachineInterface logger = logging.getLogger(__file__) class ScheduleRepository: __name__ = "ScheduleRepository" def __init__(self, smart: smartdb.SmartDatabaseClient): self.smart = smart @staticmethod def _lint_schedule_data(schedule_data: dict): # { # "roles": ["kubernetes-control-plane", "etcd-member"], # "selector": { # "mac": mac # } # } try: _ = schedule_data["selector"]["mac"] _ = schedule_data["roles"] except KeyError as e: err_msg = "missing keys in schedule data: '%s'" % e logger.error(err_msg) raise TypeError(err_msg) return schedule_data def create_schedule(self, schedule_data: dict): caller = "%s.%s" % (self.__name__, self.create_schedule.__name__) schedule_data = self._lint_schedule_data(schedule_data) @smartdb.cockroach_transaction def callback(caller=caller): commit = False with self.smart.new_session() as session: machine = session.query(Machine) \ .join(MachineInterface) \ .options(joinedload("schedules")) \ .filter(MachineInterface.mac == schedule_data["selector"]["mac"]) \ .first() if not machine: logger.error("machine mac %s not in db", schedule_data["selector"]["mac"]) return commit else: machine_already_scheduled = [s.role for s in machine.schedules] for role in schedule_data["roles"]: if role in machine_already_scheduled: logger.info("machine mac %s already scheduled with role %s", schedule_data["selector"]["mac"], role) continue session.add(Schedule(machine_id=machine.id, role=role)) logger.info("scheduling machine mac %s as role %s", schedule_data["selector"]["mac"], role) commit = True session.commit() if commit else None return commit return callback(caller) def get_all_schedules(self): result = dict() with self.smart.new_session() as session: for machine in session.query(Machine) \ .options(joinedload("interfaces")) \ .options(joinedload("schedules")) \ .join(Schedule) \ .filter(MachineInterface.as_boot == True): if machine.schedules: result[machine.interfaces[0].mac] = [k.role for k in machine.schedules] return result def get_roles_by_mac_selector(self, mac: str): result = [] with self.smart.new_session() as session: for s in session.query(Schedule) \ .join(Machine) \ .join(MachineInterface) \ .filter(MachineInterface.mac == mac): result.append(s.role) return result def get_available_machines(self): available_machines = [] with self.smart.new_session() as session: for m in session.query(Machine) \ .join(MachineInterface) \ .options(joinedload("schedules")) \ .options(joinedload("interfaces")) \ .options(joinedload("disks")) \ .filter(MachineInterface.as_boot == True): # TODO find a way to support cockroach and SQLite without this if if not m.schedules: available_machines.append({ "mac": m.interfaces[0].mac, "ipv4": m.interfaces[0].ipv4, "cidrv4": m.interfaces[0].cidrv4, "as_boot": m.interfaces[0].as_boot, "name": m.interfaces[0].name, "fqdn": m.interfaces[0].fqdn, "netmask": m.interfaces[0].netmask, "created_date": m.created_date, "disks": [{"path": k.path, "size-bytes": k.size} for k in m.disks], }) return available_machines def _construct_machine_dict(self, machine: Machine, role): return { "mac": machine.interfaces[0].mac, "ipv4": machine.interfaces[0].ipv4, "cidrv4": machine.interfaces[0].cidrv4, "gateway": machine.interfaces[0].gateway, "as_boot": machine.interfaces[0].as_boot, "name": machine.interfaces[0].name, "netmask": machine.interfaces[0].netmask, "roles": role, "created_date": machine.created_date, "fqdn": machine.interfaces[0].fqdn, "disks": [{"path": k.path, "size-bytes": k.size} for k in machine.disks], } def get_machines_by_role(self, role: str): machines = [] with self.smart.new_session() as session: for machine in session.query(Machine) \ .options(joinedload("interfaces")) \ .options(joinedload("disks")) \ .join(Schedule) \ .filter(MachineInterface.as_boot == True) \ .filter(Schedule.role == role): machines.append(self._construct_machine_dict(machine, role)) return machines def get_machines_by_roles(self, *roles): if len(roles) == 1: return self.get_machines_by_role(roles[0]) machines = [] roles = list(roles) with self.smart.new_session() as session: for machine in session.query(Machine) \ .options(joinedload("interfaces")) \ .options(joinedload("disks")) \ .join(Schedule) \ .filter(MachineInterface.as_boot == True): # TODO Maybe do this with a sqlalchemy filter func if len(roles) == len(roles) and set(k.role for k in machine.schedules) == set(roles): machines.append(self._construct_machine_dict(machine, roles)) return machines def get_role_ip_list(self, role: str): ips = [] with self.smart.new_session() as session: for machine in session.query(Machine) \ .options(joinedload("interfaces")) \ .join(MachineInterface) \ .join(Schedule) \ .filter(Schedule.role == role, MachineInterface.as_boot == True): ips.append(machine.interfaces[0].ipv4) return ips
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from djangoevents.domain import BaseAggregate from djangoevents.domain import DomainEvent from djangoevents.utils_abstract import abstract from ..utils import camel_case_to_snake_case from ..utils import list_aggregate_events from ..utils import list_concrete_aggregates from ..utils import _list_subclasses from ..utils import _list_internal_classes from unittest import mock import pytest def test_list_subclasses(): class Parent: pass class Child(Parent): pass class GrandChild(Child): pass assert set(_list_subclasses(Parent)) == {Child, GrandChild} def test_list_subclasses_when_none(): class Parent: pass assert _list_subclasses(Parent) == [] def list_internal_classes(): class Parent: class Child1: pass class Child2: class GrandChild: pass # Please note that GrandChild is not on the list! assert set(_list_internal_classes(Parent)) == {Parent.Child1, Parent.Child2} def list_internal_classes_none(): class Parent: pass assert _list_internal_classes(Parent) == [] def test_list_aggregates_skip_abstract(): class Aggregate1(BaseAggregate): pass @abstract class Aggregate2(BaseAggregate): pass with mock.patch('djangoevents.utils._list_subclasses') as list_subclasses: list_subclasses.return_value = [Aggregate1, Aggregate2] aggregates = list_concrete_aggregates() assert aggregates == [Aggregate1] def test_list_aggregates_none_present(): with mock.patch('djangoevents.utils._list_subclasses') as list_subclasses: list_subclasses.return_value = [] aggregates = list_concrete_aggregates() assert aggregates == [] def test_list_events_sample_event_appart_from_abstract(): class Aggregate(BaseAggregate): class Evt1(DomainEvent): def mutate_event(self, *args, **kwargs): pass class Evt2(DomainEvent): def mutate_event(self, *args, **kwargs): pass class Evt3(DomainEvent): # No mutate_event present pass @abstract class Evt4(DomainEvent): def mutate_event(self, *args, **kwargs): pass events = list_aggregate_events(Aggregate) assert set(events) == {Aggregate.Evt1, Aggregate.Evt2} def test_list_events_not_an_aggregate(): events = list_aggregate_events(list) assert events == [] @pytest.mark.parametrize('name, expected_output', [ ('UserRegistered', 'user_registered'), ('UserRegisteredWithEmail', 'user_registered_with_email'), ('HttpResponse', 'http_response'), ('HTTPResponse', 'http_response'), ('already_snake', 'already_snake'), ]) def test_camel_case_to_snake_case(name, expected_output): assert expected_output == camel_case_to_snake_case(name)
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from pybluemonday import UGCPolicy, StrictPolicy, NewPolicy from collections import namedtuple Case = namedtuple("Case", ["input", "output"]) def test_StrictPolicy(): cases = [ Case(input="Hello, <b>World</b>!", output="Hello, World!"), Case(input="<blockquote>Hello, <b>World</b>!", output="Hello, World!"), Case( input="<quietly>email me - addy in profile</quiet>", output="email me - addy in profile", ), ] p = StrictPolicy() for case in cases: assert p.sanitize(case.input) == case.output def test_UGCPolicy(): cases = [ Case("Hello, World!", "Hello, World!"), Case("Hello, <b>World</b>!", "Hello, <b>World</b>!"), Case( "<p>Hello, <b onclick=alert(1337)>World</b>!</p>", "<p>Hello, <b>World</b>!</p>", ), Case( "<p onclick=alert(1337)>Hello, <b>World</b>!</p>", "<p>Hello, <b>World</b>!</p>", ), Case("""<a href="javascript:alert(1337)">foo</a>""", "foo"), Case( """<img src="http://example.org/foo.gif">""", """<img src="http://example.org/foo.gif">""", ), Case( """<img src="http://example.org/x.gif" alt="y" width=96 height=64 border=0>""", """<img src="http://example.org/x.gif" alt="y" width="96" height="64">""", ), Case( """<img src="http://example.org/x.png" alt="y" width="widgy" height=64 border=0>""", """<img src="http://example.org/x.png" alt="y" height="64">""", ), Case( """<a href="foo.html">Link text</a>""", """<a href="foo.html" rel="nofollow">Link text</a>""", ), Case( """<a href="foo.html" onclick="alert(1337)">Link text</a>""", """<a href="foo.html" rel="nofollow">Link text</a>""", ), Case( """<a href="http://example.org/x.html" onclick="alert(1337)">Link text</a>""", """<a href="http://example.org/x.html" rel="nofollow">Link text</a>""", ), Case( """<a href="https://example.org/x.html" onclick="alert(1337)">Link text</a>""", """<a href="https://example.org/x.html" rel="nofollow">Link text</a>""", ), Case( """<a href="//example.org/x.html" onclick="alert(1337)">Link text</a>""", """<a href="//example.org/x.html" rel="nofollow">Link text</a>""", ), Case( """<a href="javascript:alert(1337).html" onclick="alert(1337)">Link text</a>""", """Link text""", ), Case( """<a name="header" id="header">Header text</a>""", """<a id="header">Header text</a>""", ), Case( """<img src="planets.gif" width="145" height="126" alt="" usemap="#demomap"><map name="demomap"><area shape="rect" coords="0,0,82,126" href="demo.htm" alt="1"><area shape="circle" coords="90,58,3" href="demo.htm" alt="2"><area shape="circle" coords="124,58,8" href="demo.htm" alt="3"></map>""", """<img src="planets.gif" width="145" height="126" alt="" usemap="#demomap"><map name="demomap"><area shape="rect" coords="0,0,82,126" href="demo.htm" alt="1" rel="nofollow"><area shape="circle" coords="90,58,3" href="demo.htm" alt="2" rel="nofollow"><area shape="circle" coords="124,58,8" href="demo.htm" alt="3" rel="nofollow"></map>""", ), Case( """<table style="color: rgb(0, 0, 0);"><tbody><tr><th>Column One</th><th>Column Two</th></tr><tr><td align="center" style="background-color: rgb(255, 255, 254);"><font size="2">Size 2</font></td><td align="center" style="background-color: rgb(255, 255, 254);"><font size="7">Size 7</font></td></tr></tbody></table>""", """<table><tbody><tr><th>Column One</th><th>Column Two</th></tr><tr><td align="center">Size 2</td><td align="center">Size 7</td></tr></tbody></table>""", ), Case( """xss<a href="http://www.google.de" style="color:red;" onmouseover=alert(1) onmousemove="alert(2)" onclick=alert(3)>g<img src="http://example.org"/>oogle</a>""", """xss<a href="http://www.google.de" rel="nofollow">g<img src="http://example.org"/>oogle</a>""", ), Case( "<table>Hallo\r\n<script>SCRIPT</script>\nEnde\n\r", "<table>Hallo\n\nEnde\n\n", ), ] p = UGCPolicy() for case in cases: assert p.sanitize(case.input) == case.output
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from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals from builtins import * import numpy as np from .rnn_base import RNNBase from .utils import SymbolTable class TextRNN(RNNBase): """TextRNN for strings of text.""" def _preprocess_data(self, candidates, extend=False): """Convert candidate sentences to lookup sequences :param candidates: candidates to process :param extend: extend symbol table for tokens (train), or lookup (test)? """ if not hasattr(self, 'word_dict'): self.word_dict = SymbolTable() data, ends = [], [] for candidate in candidates: toks = candidate.get_contexts()[0].text.split() # Either extend word table or retrieve from it f = self.word_dict.get if extend else self.word_dict.lookup data.append(np.array(list(map(f, toks)))) ends.append(len(toks)) return data, ends
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import numpy as np import matplotlib # matplotlib.use("TkAgg") import matplotlib.pyplot as plt from typing import * import pandas as pd import seaborn as sns import math sns.set() class Accuracy(object): def at_radii(self, radii: np.ndarray): raise NotImplementedError() class ApproximateAccuracy(Accuracy): def __init__(self, data_file_path: str): self.data_file_path = data_file_path def at_radii(self, radii: np.ndarray) -> np.ndarray: df = pd.read_csv(self.data_file_path, delimiter="\t") return np.array([self.at_radius(df, radius) for radius in radii]) def at_radius(self, df: pd.DataFrame, radius: float): return (df["correct"] & (df["radius"] >= radius)).mean() class HighProbAccuracy(Accuracy): def __init__(self, data_file_path: str, alpha: float, rho: float): self.data_file_path = data_file_path self.alpha = alpha self.rho = rho def at_radii(self, radii: np.ndarray) -> np.ndarray: df = pd.read_csv(self.data_file_path, delimiter="\t") return np.array([self.at_radius(df, radius) for radius in radii]) def at_radius(self, df: pd.DataFrame, radius: float): mean = (df["correct"] & (df["radius"] >= radius)).mean() num_examples = len(df) return ( mean - self.alpha - math.sqrt( self.alpha * (1 - self.alpha) * math.log(1 / self.rho) / num_examples ) - math.log(1 / self.rho) / (3 * num_examples) ) class Line(object): def __init__( self, quantity: Accuracy, legend: str, plot_fmt: str = "", scale_x: float = 1 ): self.quantity = quantity self.legend = legend self.plot_fmt = plot_fmt self.scale_x = scale_x def plot_certified_accuracy( outfile: str, title: str, max_radius: float, lines: List[Line], radius_step: float = 0.01, ) -> None: radii = np.arange(0, max_radius + radius_step, radius_step) plt.figure() for line in lines: plt.plot(radii * line.scale_x, line.quantity.at_radii(radii), line.plot_fmt) plt.ylim((0, 1)) plt.xlim((0, max_radius)) plt.tick_params(labelsize=14) plt.xlabel("radius", fontsize=16) plt.ylabel("certified accuracy", fontsize=16) plt.legend([method.legend for method in lines], loc="upper right", fontsize=16) plt.savefig(outfile + ".pdf") plt.tight_layout() plt.title(title, fontsize=20) plt.tight_layout() plt.savefig(outfile + ".png", dpi=300) plt.close() def smallplot_certified_accuracy( outfile: str, title: str, max_radius: float, methods: List[Line], radius_step: float = 0.01, xticks=0.5, ) -> None: radii = np.arange(0, max_radius + radius_step, radius_step) plt.figure() for method in methods: plt.plot(radii, method.quantity.at_radii(radii), method.plot_fmt) plt.ylim((0, 1)) plt.xlim((0, max_radius)) plt.xlabel("radius", fontsize=22) plt.ylabel("certified accuracy", fontsize=22) plt.tick_params(labelsize=20) plt.gca().xaxis.set_major_locator(plt.MultipleLocator(xticks)) plt.legend([method.legend for method in methods], loc="upper right", fontsize=20) plt.tight_layout() plt.savefig(outfile + ".pdf") plt.close() def latex_table_certified_accuracy( outfile: str, radius_start: float, radius_stop: float, radius_step: float, methods: List[Line], ): radii = np.arange(radius_start, radius_stop + radius_step, radius_step) accuracies = np.zeros((len(methods), len(radii))) for i, method in enumerate(methods): accuracies[i, :] = method.quantity.at_radii(radii) f = open(outfile, "w") for radius in radii: f.write("& $r = {:.3}$".format(radius)) f.write("\\\\\n") f.write("\midrule\n") for i, method in enumerate(methods): f.write(method.legend) for j, radius in enumerate(radii): if i == accuracies[:, j].argmax(): txt = r" & \textbf{" + "{:.2f}".format(accuracies[i, j]) + "}" else: txt = " & {:.2f}".format(accuracies[i, j]) f.write(txt) f.write("\\\\\n") f.close() def markdown_table_certified_accuracy( outfile: str, radius_start: float, radius_stop: float, radius_step: float, methods: List[Line], ): radii = np.arange(radius_start, radius_stop + radius_step, radius_step) accuracies = np.zeros((len(methods), len(radii))) for i, method in enumerate(methods): accuracies[i, :] = method.quantity.at_radii(radii) f = open(outfile, "w") f.write("| | ") for radius in radii: f.write("r = {:.3} |".format(radius)) f.write("\n") f.write("| --- | ") for i in range(len(radii)): f.write(" --- |") f.write("\n") for i, method in enumerate(methods): f.write("<b> {} </b>| ".format(method.legend)) for j, radius in enumerate(radii): if i == accuracies[:, j].argmax(): txt = "{:.2f}<b>*</b> |".format(accuracies[i, j]) else: txt = "{:.2f} |".format(accuracies[i, j]) f.write(txt) f.write("\n") f.close() if __name__ == "__main__": latex_table_certified_accuracy( "analysis/latex/vary_noise_cifar10", 0.25, 1.5, 0.25, [ Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.12/test/sigma_0.12" ), "$\sigma = 0.12$", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.25/test/sigma_0.25" ), "$\sigma = 0.25$", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.50/test/sigma_0.50" ), "$\sigma = 0.50$", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_1.00/test/sigma_1.00" ), "$\sigma = 1.00$", ), ], ) markdown_table_certified_accuracy( "analysis/markdown/vary_noise_cifar10", 0.25, 1.5, 0.25, [ Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.12/test/sigma_0.12" ), "&sigma; = 0.12", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.25/test/sigma_0.25" ), "&sigma; = 0.25", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.50/test/sigma_0.50" ), "&sigma; = 0.50", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_1.00/test/sigma_1.00" ), "&sigma; = 1.00", ), ], ) latex_table_certified_accuracy( "analysis/latex/vary_noise_imagenet", 0.5, 3.0, 0.5, [ Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.25/test/sigma_0.25" ), "$\sigma = 0.25$", ), Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.50/test/sigma_0.50" ), "$\sigma = 0.50$", ), Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_1.00/test/sigma_1.00" ), "$\sigma = 1.00$", ), ], ) markdown_table_certified_accuracy( "analysis/markdown/vary_noise_imagenet", 0.5, 3.0, 0.5, [ Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.25/test/sigma_0.25" ), "&sigma; = 0.25", ), Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.50/test/sigma_0.50" ), "&sigma; = 0.50", ), Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_1.00/test/sigma_1.00" ), "&sigma; = 1.00", ), ], ) plot_certified_accuracy( "analysis/plots/vary_noise_cifar10", "CIFAR-10, vary $\sigma$", 1.5, [ Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.12/test/sigma_0.12" ), "$\sigma = 0.12$", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.25/test/sigma_0.25" ), "$\sigma = 0.25$", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.50/test/sigma_0.50" ), "$\sigma = 0.50$", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_1.00/test/sigma_1.00" ), "$\sigma = 1.00$", ), ], ) plot_certified_accuracy( "analysis/plots/vary_train_noise_cifar_050", "CIFAR-10, vary train noise, $\sigma=0.5$", 1.5, [ Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.25/test/sigma_0.50" ), "train $\sigma = 0.25$", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_0.50/test/sigma_0.50" ), "train $\sigma = 0.50$", ), Line( ApproximateAccuracy( "data/certify/cifar10/resnet110/noise_1.00/test/sigma_0.50" ), "train $\sigma = 1.00$", ), ], ) plot_certified_accuracy( "analysis/plots/vary_train_noise_imagenet_050", "ImageNet, vary train noise, $\sigma=0.5$", 1.5, [ Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.25/test/sigma_0.50" ), "train $\sigma = 0.25$", ), Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.50/test/sigma_0.50" ), "train $\sigma = 0.50$", ), Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_1.00/test/sigma_0.50" ), "train $\sigma = 1.00$", ), ], ) plot_certified_accuracy( "analysis/plots/vary_noise_imagenet", "ImageNet, vary $\sigma$", 4, [ Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.25/test/sigma_0.25" ), "$\sigma = 0.25$", ), Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.50/test/sigma_0.50" ), "$\sigma = 0.50$", ), Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_1.00/test/sigma_1.00" ), "$\sigma = 1.00$", ), ], ) plot_certified_accuracy( "analysis/plots/high_prob", "Approximate vs. High-Probability", 2.0, [ Line( ApproximateAccuracy( "data/certify/imagenet/resnet50/noise_0.50/test/sigma_0.50" ), "Approximate", ), Line( HighProbAccuracy( "data/certify/imagenet/resnet50/noise_0.50/test/sigma_0.50", 0.001, 0.001, ), "High-Prob", ), ], )
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from .trainer import Trainer, STOP_TIME from .my_checkpoint_management import MyCheckpointManager import signal class EvolutionTrainer(Trainer): def __init__( self, root_dir, evolutions, keep_checkpoint_steps, save_interval_minutes=30, signal_handler_signals=(signal.SIGINT, signal.SIGUSR1, signal.SIGTERM), ): """ Creates a new EvolutionTrainer object. This will create the root_dir for training and a directory for checkpoints and log files within this directory. In contrast to the default Trainer, EvolutionTrainer supports evolutions. Evolutions allow to implement trainings with multiple stages that need to run the training script multiple times. In addition EvolutionTrainer takes care of checkpoint management. root_dir : str path to the root of the training directory. evolutions : list of objects The evolution object must implement the attributes 'name' and 'stop_step'. 'name' is used in the filename of the checkpoint. 'stop_step' is the iteration number at which the evolution stops. keep_checkpoint_steps : list or set of integers A set of steps for which checkpoints are kept. save_interval_minutes : int The save interval in minutes. If the latest checkpoint is older than this interval then a new checkpoint will be created by save_if_needed() signal_handler_signals : list of signals This object will install a signal handler for these signals that will cause keep_training() to return False and create a checkpoint. """ if not evolutions: raise ValueError("List of evolutions must not be empty") if len([e.stop_step for e in evolutions]) != len( set([e.stop_step for e in evolutions])): raise ValueError("Duplicate 'stop_step' found in evolutions") if len([e.name for e in evolutions]) != len( set([e.name for e in evolutions])): raise ValueError("Duplicate 'name' found in evolutions") super().__init__(root_dir, signal_handler_signals) self._evolutions = sorted(evolutions, key=lambda x: x.stop_step) self._current_evolution = self._get_current_evolution() if keep_checkpoint_steps: self._keep_checkpoint_steps = set(keep_checkpoint_steps) else: self._keep_checkpoint_steps = set() # make sure that we keep checkpoints for the last step of each evolution for evo in self._evolutions: self._keep_checkpoint_steps.add(evo.stop_step) self._save_interval_minutes = save_interval_minutes self._checkpoint_manager = None def checkpoint_prefix_for_evo(self, evo): return 'ckpt_{}'.format(evo.name) def _get_current_evolution(self): current_evo = self._evolutions[-1] for evo in reversed(self._evolutions): checkpoint_prefix = self.checkpoint_prefix_for_evo(evo) ckpt_manager = MyCheckpointManager( None, self.checkpoint_dir, [], checkpoint_prefix=checkpoint_prefix) steps_checkpoints = ckpt_manager.get_steps_and_checkpoints() if steps_checkpoints: last_step = steps_checkpoints[-1][0] if last_step < evo.stop_step: # if there are checkpoints with a step smaller than the stop # step then this is the current evo and we can break out of # the loop current_evo = evo break else: # in this case evo is finished and the evo stored in # current_evo from the previous iteration is the current evo return current_evo else: # if there are no checkpoints we have to check if the previous # evo was finished. current_evo = evo return current_evo @property def current_evolution(self): return self._current_evolution @property def latest_checkpoint(self): """Returns the latest checkpoint across evolutions""" checkpoint = None for evo in reversed(self._evolutions): checkpoint_prefix = self.checkpoint_prefix_for_evo(evo) ckpt_manager = MyCheckpointManager( None, self.checkpoint_dir, [], checkpoint_prefix=checkpoint_prefix) if ckpt_manager.latest_checkpoint: checkpoint = ckpt_manager.latest_checkpoint break return checkpoint def _get_checkpoint_manager(self, checkpoint_fn): if self._checkpoint_manager is None: checkpoint_prefix = self.checkpoint_prefix_for_evo( self.current_evolution) self._checkpoint_manager = MyCheckpointManager( checkpoint_fn, self.checkpoint_dir, self._keep_checkpoint_steps, self._save_interval_minutes, checkpoint_prefix, ) return self._checkpoint_manager def keep_training( self, step_var, checkpoint_fn, stop_time=STOP_TIME, display_interval=10, display_str_list=None, runstats_interval_minutes=10, step_var_increment=1, ): """ This function increments the step_var, displays and logs runtime information and saves checkpoints. The function is intended to be used as the condition for the training loop, e.g. trainer = EvolutionTrainer(train_dir) step_var = torch.tensor(0) checkpoint_fn = lambda step: {'step': step_var', 'model': model.state_dict()} if trainer.latest_checkpoint: checkpoint = torch.load(trainer.latest_checkpoint) step_var = checkpoint['step'] model.load_state_dict(checkpoint['model']) while trainer.keep_training(step_var, checkpoint_fn): train() step_var : Scalar torch Tensor. The step variable that will be incremented each call. checkpoint_fn : A function returning the dictionary to be saved. stop_time : float or None stop_time in seconds since the epoch. The default will be read from the environment variable STOP_TIME. Set to None for no stop_time or do not set the env var STOP_TIME. display_interval : int The interval in iterations for displaying runtime information on the console. display_str_list : list A list of additional objects that will be displayed with print(). runstats_interval_minutes: int The interval for logging runtime statistics in minutes. step_var_increment : int The value to add to the step_var. If 0 the step_var will not be updated. For a single stop_step the return behavior is Returns True if step_var != stop_step Returns False if step_var == stop_step or the current time is larger than stop_time or if a signal has been received for which a signal handler was installed. """ status = super().keep_training( step_var=step_var, stop_step=self.current_evolution.stop_step, checkpoint_manager=self._get_checkpoint_manager(checkpoint_fn), stop_time=stop_time, display_interval=display_interval, display_str_list=display_str_list, runstats_interval_minutes=runstats_interval_minutes, step_var_increment=step_var_increment, ) return status
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from typing import List from deeppavlov.core.common.registry import register @register("sentseg_restore_sent") def SentSegRestoreSent(batch_words: List[List[str]], batch_tags: List[List[str]]) -> List[str]: ret = [] for words, tags in zip(batch_words, batch_tags): if len(tags) == 0: ret.append("") continue sent = words[0] punct = "" if tags[0] == "O" else tags[0][-1] for word, tag in zip(words[1:], tags[1:]): if tag != "O": sent += punct punct = tag[-1] sent += " " + word sent += punct ret.append(sent) return ret
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import os import numpy as np import pandas as pd import h5py from bmtk.utils.sonata.utils import add_hdf5_magic, add_hdf5_version def create_single_pop_h5(): h5_file_old = h5py.File('spike_files/spikes.old.h5', 'r') node_ids = h5_file_old['/spikes/gids'] timestamps = h5_file_old['/spikes/timestamps'] with h5py.File('spike_files/spikes.one_pop.h5', 'w') as h5: add_hdf5_magic(h5) add_hdf5_version(h5) core_grp = h5.create_group('/spikes/v1') core_grp.attrs['sorting'] = 'by_time' ts_ds = core_grp.create_dataset('timestamps', data=timestamps, dtype=np.float64) ts_ds.attrs['units'] = 'milliseconds' nids_ds = core_grp.create_dataset('node_ids', data=node_ids, dtype=np.uint64) def create_multipop_csv(dir_path='/local1/workspace/bmtk/docs/examples/NWB_files'): lgn_h5 = h5py.File(os.path.join(dir_path, 'lgn_spikes.nwb'), 'r') tw_h5 = h5py.File(os.path.join(dir_path, 'tw_spikes.nwb'), 'r') full_df = pd.DataFrame({ 'timestamps': pd.Series(dtype=np.float64), 'population': pd.Series(dtype=np.string_), 'node_ids': pd.Series(dtype=np.uint64) }) for pop_name, pop_h5, n_nodes in [('lgn', lgn_h5, 4000), ('tw', tw_h5, 2000)]: spike_train_grp = pop_h5['/processing/trial_0/spike_train'] for node_id in range(n_nodes): tmp_df = pd.DataFrame({ 'timestamps': spike_train_grp[str(node_id)]['data'][()], 'population': pop_name, 'node_ids': np.uint64(node_id) }) full_df = full_df.append(tmp_df) full_df = full_df[['timestamps', 'population', 'node_ids']] full_df.to_csv('spike_files/spikes.multipop.csv', sep=' ', index=False) def create_multipop_h5(): spikes_df = pd.read_csv('spike_files/spikes.multipop.csv', sep=' ') lgn_spikes_df = spikes_df[spikes_df['population'] == 'lgn'] tw_spikes_df = spikes_df[spikes_df['population'] == 'tw'] with h5py.File('spike_files/spikes.multipop.h5', 'w') as h5: add_hdf5_magic(h5) add_hdf5_version(h5) lgn_grp = h5.create_group('/spikes/lgn') lgn_grp.attrs['sorting'] = 'by_id' ts_ds = lgn_grp.create_dataset('timestamps', data=lgn_spikes_df['timestamps'], dtype=np.float64) ts_ds.attrs['units'] = 'milliseconds' lgn_grp.create_dataset('node_ids', data=lgn_spikes_df['node_ids'], dtype=np.uint64) tw_grp = h5.create_group('/spikes/tw') tw_grp.attrs['sorting'] = 'by_id' ts_ds = tw_grp.create_dataset('timestamps', data=tw_spikes_df['timestamps'], dtype=np.float64) ts_ds.attrs['units'] = 'milliseconds' tw_grp.create_dataset('node_ids', data=tw_spikes_df['node_ids'], dtype=np.uint64) def create_nwb(): spikes_df = pd.read_csv('spike_files/spikes.one_pop.csv', sep=' ') with h5py.File('spike_files/spikes.onepop.v1.0.nwb', 'w') as h5: spikes_grp = h5.create_group('/processing/trial_0/spike_train') for node_id in range(14): timestamps = spikes_df[spikes_df['node_ids'] == node_id]['timestamps'].values data_ds = spikes_grp.create_dataset('{}/data'.format(node_id), data=timestamps, dtype=np.float64) data_ds.attrs['dimension'] = 'time' data_ds.attrs['unit'] = 'millisecond' if __name__ == '__main__': # create_multipop_csv() # create_multipop_h5() create_nwb()
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from .imgurdownloader import ImgurDownloader # NOQA # defining __version__ variable is pointless __author__ = '<NAME> <<EMAIL>>' __all__ = []
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import hashlib import hmac import time class BitfinexAuth(): def __init__(self, api_key: str, secret_key: str): self.api_key = api_key self.secret_key = secret_key self.last_nonce = 0 def _sign_payload(self, payload) -> str: sig = hmac.new(self.secret_key.encode('utf8'), payload.encode('utf8'), hashlib.sha384).hexdigest() return sig def get_nonce(self) -> int: nonce = int(round(time.time() * 1_000_000)) if self.last_nonce == nonce: nonce = nonce + 1 elif self.last_nonce > nonce: nonce = self.last_nonce + 1 self.last_nonce = nonce return nonce def generate_auth_payload(self, payload, nonce = None): """ Sign payload """ nonce = nonce if nonce is not None else self.get_nonce() sig = self._sign_payload(payload) payload = { "apiKey": self.api_key, "authSig": sig, "authNonce": nonce, "authPayload": payload, "event": 'auth', } return payload def generate_api_headers(self, path, body): """ Generate headers for a signed payload """ nonce = str(self.get_nonce()) signature = "/api/" + path + nonce + body sig = self._sign_payload(signature) return { "bfx-nonce": nonce, "bfx-apikey": self.api_key, "bfx-signature": sig, "content-type": "application/json" }
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import functools import glob import os import shlex from typing import Callable, Iterable, List, Optional, Tuple from bs4 import BeautifulSoup, Comment, Doctype from mitmproxy import ctx, http import modules.arguments as A import modules.constants as C import modules.csp as csp import modules.inject as inject import modules.inline as inline import modules.metadata as metadata from modules.misc import sanitize from modules.requests import CONTENT_TYPE, containsQueryParam, inferEncoding import modules.text as T import modules.userscript as userscript from modules.userscript import Userscript, UserscriptError from modules.utilities import first, flag, fromOptional, itemList, second PATTERN_USERSCRIPT: str = "*.user.js" RELEVANT_CONTENT_TYPES: List[str] = ["text/html", "application/xhtml+xml"] CHARSET_DEFAULT: str = "utf-8" TAB: str = " " LIST_ITEM_PREFIX: str = TAB + "โ€ข " HTML_PARSER: str = "lxml" # lxml handles non-uppercase DOCTYPE correctly; html.parser does not: It emits # <!DOCTYPE doctype html> if the original source code contained <!doctype html>. HTML_INFO_COMMENT_PREFIX: str = f""" [{T.INFO_MESSAGE}] """ def logInfo(s: str) -> None: try: ctx.log.info(s) except Exception: print(s) def logWarning(s: str) -> None: try: ctx.log.warn(s) except Exception: print(s) def logError(s: str) -> None: try: ctx.log.error(s) except Exception: print(s) def indexOfDTD(soup: BeautifulSoup) -> Optional[int]: index: int = 0 for item in soup.contents: if isinstance(item, Doctype): return index index += 1 return None bulletList: Callable[[Iterable[str]], str] = functools.partial(itemList, LIST_ITEM_PREFIX) def unsafeSequencesMessage(script: Userscript) -> str: sequences = script.unsafeSequences return f"""{script.name} cannot be injected because it contains {"these unsafe sequences" if len(sequences) > 1 else "this unsafe sequence"}: {itemList(TAB, sequences)} <script> tags cannot contain any of these sequences (case-insensitive): {itemList(TAB, inline.DANGEROUS_SEQUENCES)} Possible solutions: """ + bulletList([ f"Make sure the userscript does not contain any of the sequences listed above.", f"Make the userscript available online and give it a {metadata.tag(userscript.directive_downloadURL)}", f"Remove the {flag(A.inline)} flag.", ]) # Because ctx.options is not subscriptable and we want to be able to use # expressions as keys: def option(key: str): return ctx.options.__getattr__(sanitize(key)) def loadUserscripts(directory: str) -> List[Userscript]: loadedUserscripts: List[Tuple[Userscript, str]] = [] workingDirectory = os.getcwd() logInfo(f"""Looking recursively for userscripts ({PATTERN_USERSCRIPT}) in directory `{directory}` ...""") os.chdir(directory) pattern = "**/" + PATTERN_USERSCRIPT # recursive=True only affects the meaning of "**". # https://docs.python.org/3/library/glob.html#glob.glob for unsafe_filename in glob.glob(pattern, recursive=True): filename = shlex.quote(unsafe_filename) logInfo("Loading " + filename + " ...") try: content = open(filename).read() except PermissionError: logError("Could not read file `"+filename+"`: Permission denied.") continue except Exception as e: logError("Could not read file `"+filename+"`: " + str(e)) continue try: script = userscript.create(content) if script.downloadURL is None: logWarning(f"""{script.name} will be injected inline because it does not have a {metadata.tag(userscript.directive_downloadURL)}.""") loadedUserscripts.append((script, filename)) if script.downloadURL is None and len(script.unsafeSequences) > 0: logError(unsafeSequencesMessage(script)) except metadata.MetadataError as err: logError("Metadata error:") logError(str(err)) continue except UserscriptError as err: logError("Userscript error:") logError(str(err)) continue os.chdir(workingDirectory) # so mitmproxy does not unload the script logInfo("") logInfo(str(len(loadedUserscripts)) + " userscript(s) loaded:") logInfo("") logInfo(bulletList(map( lambda s: f"{first(s).name} ({second(s)})", loadedUserscripts ))) logInfo("") return list(map(first, loadedUserscripts)) class UserscriptInjector: def __init__(self): self.userscripts: List[Userscript] = [] def load(self, loader): loader.add_option(sanitize(A.inline), bool, False, A.inline_help) loader.add_option(sanitize(A.no_default_userscripts), bool, False, A.no_default_userscripts_help) loader.add_option(sanitize(A.list_injected), bool, False, A.list_injected_help) loader.add_option(sanitize(A.bypass_csp), Optional[str], A.bypass_csp_default, A.bypass_csp_help) loader.add_option(sanitize(A.userscripts_dir), Optional[str], A.userscripts_dir_default, A.userscripts_dir_help) loader.add_option(sanitize(A.query_param_to_disable), str, A.query_param_to_disable_default, A.query_param_to_disable_help) def configure(self, updates): useDefaultUserscripts = True if sanitize(A.no_default_userscripts) in updates and option(A.no_default_userscripts): logInfo(f"""Built-in default userscripts will be skipped due to {flag(A.no_default_userscripts)} flag.""") useDefaultUserscripts = False if sanitize(A.inline) in updates and option(A.inline): logWarning(f"""Only inline injection will be used due to {flag(A.inline)} flag.""") if sanitize(A.query_param_to_disable) in updates: logInfo(f"""Userscripts will not be injected when the request URL contains a `{option(A.query_param_to_disable)}` query parameter.""") if sanitize(A.userscripts_dir) in updates: userscripts = loadUserscripts(C.DEFAULT_USERSCRIPTS_DIR) if useDefaultUserscripts else [] userscriptsDirectory = option(A.userscripts_dir) if userscriptsDirectory is None: logWarning(f"No custom userscripts will be loaded, because {flag(A.userscripts_dir)} was not provided.") else: userscripts.extend(loadUserscripts(userscriptsDirectory)) self.userscripts = userscripts def response(self, flow: http.HTTPFlow): response = flow.response if CONTENT_TYPE in response.headers: if any(map(lambda t: t in response.headers[CONTENT_TYPE], RELEVANT_CONTENT_TYPES)): # Response is a web page; proceed. injections: List[csp.Injection] = [] soup = BeautifulSoup( response.content, HTML_PARSER, from_encoding=inferEncoding(response) ) requestURL = flow.request.pretty_url # should work in transparent mode too, unless the Host header is spoofed if containsQueryParam(option(A.query_param_to_disable), flow.request): logInfo(f"""Not injecting any userscripts into {requestURL} because it contains a `{option(A.query_param_to_disable)}` query parameter.""") return isApplicable: Callable[[Userscript], bool] = userscript.applicableChecker(requestURL) for script in self.userscripts: if isApplicable(script): useInline = option(A.inline) or script.downloadURL is None if useInline and len(script.unsafeSequences) > 0: logError(unsafeSequencesMessage(script)) continue logInfo(f"""Injecting {script.name}{"" if script.version is None else " " + C.VERSION_PREFIX + script.version} into {requestURL} ({"inline" if useInline else "linked"}) ...""") shouldUseNonce = useInline and option(A.bypass_csp) == A.bypass_csp_script # If not inline, then URL is used for bypassing; if bypass for nothing or everything, then the nonce would have no effect anyway. nonce = csp.generateNonce() if shouldUseNonce else None result = inject.inject(script, soup, inject.Options( inline = option(A.inline), nonce = nonce )) if type(result) is BeautifulSoup: soup = result injections.append(csp.Injection( userscript = script, nonce = nonce, )) else: logError("Injection failed due to the following error:") logError(str(result)) handleContentSecurityPolicy(response, injections) index_DTD: Optional[int] = indexOfDTD(soup) # Insert information comment: if option(A.list_injected): namesOfInjectedScripts = [ i.userscript.name + ("" if i.userscript.version is None else " " + T.stringifyVersion(i.userscript.version)) for i in injections ] soup.insert(0 if index_DTD is None else 1+index_DTD, Comment( HTML_INFO_COMMENT_PREFIX + ( "No matching userscripts for this URL." if namesOfInjectedScripts == [] else "These scripts were inserted:\n" + bulletList(namesOfInjectedScripts) ) + "\n" )) # Serialize and encode: response.content = str(soup).encode( fromOptional(soup.original_encoding, CHARSET_DEFAULT), "replace" ) def handleContentSecurityPolicy(response: http.HTTPFlow.response, injections: List[csp.Injection]): # If there is a CSP header, we may need to modify it for the userscript(s) to work. ContentSecurityPolicy = "Content-Security-Policy" if ContentSecurityPolicy in response.headers: bypassCspValue = option(A.bypass_csp) if bypassCspValue == A.bypass_csp_script: logInfo(f"Bypassing host site's Content Security Policy for userscripts only (not any resources injected _by_ userscripts, such as stylesheets and images). Try `{flag(A.bypass_csp)} {A.bypass_csp_everything}` if something does not work properly.") response.headers[ContentSecurityPolicy] = csp.headerWithScriptsAllowed(response.headers[ContentSecurityPolicy], injections) elif bypassCspValue == A.bypass_csp_everything: logInfo(f"Bypassing host site's Content Security Policy altogether due to `{flag(A.bypass_csp)} {A.bypass_csp_everything}`.") del response.headers[ContentSecurityPolicy] else: logWarning(f"Host site has a Content Security Policy. Try the {flag(A.bypass_csp)} flag if userscripts don't work properly.") addons = [ UserscriptInjector() ]
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from marshmallow import INCLUDE, Schema, fields, post_load, pre_load class Urls: def __init__( self, digital_purchase_date=None, foc_date=None, onsale_date=None, unlimited_date=None, wiki=None, detail=None, **kwargs, ): self.digital_purchase_date = digital_purchase_date self.foc_date = foc_date self.onsale_date = onsale_date self.unlimited_date = unlimited_date self.wiki = wiki self.detail = detail self.unknown = kwargs class UrlsSchema(Schema): digitalPurchaseDate = fields.Url(attribute="digital_purchase_date") focDate = fields.Url(attribute="foc_date") onsaleDate = fields.Url(attribute="onsale_date") unlimitedDate = fields.Url(attribute="unlimited_date") # Should these go into a separate class like CharacterUrls? # For now let's put them here, but it may be something to consider to split them. wiki = fields.Url() detail = fields.Url() class Meta: unknown = INCLUDE @pre_load def process_input(self, data, **kwargs): return {d["type"]: d["url"] for d in data} @post_load def make(self, data, **kwargs): return Urls(**data)
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import os import shutil import readdy import tempfile import unittest import numpy as np class TestTopologyReactionCount(unittest.TestCase): @classmethod def setUpClass(cls) -> None: cls.dir = tempfile.mkdtemp("test-topology-reaction-count") @classmethod def tearDownClass(cls) -> None: shutil.rmtree(cls.dir, ignore_errors=True) def _test_kernel(self, kernel): system = readdy.ReactionDiffusionSystem(box_size=[20, 20, 20]) system.topologies.add_type("T1") system.topologies.add_type("T2") system.add_species("A") system.add_topology_species("B") system.topologies.configure_harmonic_bond("B", "B", 1., .1) system.add_topology_species("C") system.topologies.configure_harmonic_bond("C", "C", 1., .1) system.topologies.add_spatial_reaction("attach: T1(B) + (A) -> T1(B--B)", rate=1e-1, radius=.5) def flip1(topology): recipe = readdy.StructuralReactionRecipe(topology) for v in topology.graph.vertices: recipe.change_particle_type(v, "C") recipe.change_topology_type("T2") return recipe def flip2(topology): recipe = readdy.StructuralReactionRecipe(topology) for v in topology.graph.vertices: recipe.change_particle_type(v, "B") recipe.change_topology_type("T1") return recipe system.topologies.add_structural_reaction("flip_types_1", "T1", flip1, lambda x: 5e-2) system.topologies.add_structural_reaction("flip_types_2", "T2", flip2, lambda x: 5e-2) sim = system.simulation(kernel=kernel) sim.output_file = os.path.join(self.dir, "out_{}.h5".format(kernel)) collected_counts = [] def callback(results): nonlocal collected_counts collected_counts.append(results) sim.observe.reaction_counts(1, callback=callback) sim.observe.number_of_particles(1, types=["A", "B", "C"]) sim.add_particles("A", np.random.normal(scale=1, size=(1000, 3))) for _ in range(10): sim.add_topology("T1", "B", np.random.normal(size=(1, 3))) sim.run(1000, timestep=1, show_summary=False) traj = readdy.Trajectory(sim.output_file) times, n_particles = traj.read_observable_number_of_particles() times2, counts = traj.read_observable_reaction_counts() np.testing.assert_array_equal(times, times2) assert not counts["reactions"] spatials = counts["spatial_topology_reactions"] n_spatial = 0 cA_prev = None for t, (cA, cB, cC), cc in zip(times, n_particles, collected_counts): assert cA_prev is None or cA <= cA_prev np.testing.assert_equal(cA + cB + cC, 1010) cc_normal = cc[0] assert not cc_normal cc_spatial = cc[1] cc_structural = cc[2] n_spatial += spatials["attach"][t] assert cA == 1000 - n_spatial, f"Got {cA} A particles, expected {1000 - n_spatial}, at time t {t}" for sp in cc_spatial.keys(): recorded = spatials[sp][t] assert cc_spatial[sp] == recorded, f"Got {cc_spatial[sp]} != {recorded} (t={t})" for st in cc_structural.keys(): recorded = counts["structural_topology_reactions"][st][t] assert cc_structural[st] == recorded, f"Got {cc_structural[st]} != {recorded} (t={t})" cA_prev = cA def test_scpu(self): self._test_kernel("SingleCPU") def test_cpu(self): self._test_kernel("CPU") if __name__ == '__main__': unittest.main()
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Import("env") import os import tempfile def cprint(*args, **kwargs): print(f'pre_script_patch_debug.py:', *args, **kwargs) def get_winterrupts_path(): winterrupts_path = None for pio_package in env.PioPlatform().dump_used_packages(): pio_dir = env.PioPlatform().get_package_dir(pio_package['name']) # TODO: This should change for non-mega cores! possible_path = os.path.join(pio_dir, 'cores', 'MegaCore', 'WInterrupts.c') if os.path.exists(possible_path): cprint(f'Found WInterrupts.c: {possible_path}') winterrupts_path = possible_path return winterrupts_path def patch_function_factory(src_path, output_suffix, replacement_list): """ Creates a function that will return a filepath to a patched source file :param src_path: The actual source path on disk, this is different than node.get_abspath() :param output_suffix: The suffix for the output temporary file :param replacement_list: List of 'in'/'out' pairs that should be replaced :return: Build Middleware function """ def out_func(node): # patch_path_key needs to be kept in sync with post_script_remove_patched_files.py # so that after a successful build the patched file can be removed patch_path_key = '_patched_' with tempfile.NamedTemporaryFile(mode='w', suffix=f'{patch_path_key}{output_suffix}', delete=False) as tf: patched_filepath = tf.name cprint(f'Patching {src_path}') cprint(f'Replacement path: {patched_filepath}') cprint(f'Build path: {node.get_abspath()}') with open(src_path, 'r') as wint_f: for wint_line in wint_f.readlines(): # Default is to just path the line through un-replaced out_line = wint_line # Now we check if line is in the replacements list for replacement in replacement_list: if replacement['in'] in wint_line: out_line = replacement['out'] break # Write the (possibly replaced) line to the output temporary file tf.write(out_line) return env.File(patched_filepath) return out_func source_patch_dict = { '*WInterrupts.c': { 'actual_src_path': get_winterrupts_path(), 'patches': [ { 'in': 'IMPLEMENT_ISR(INT7_vect, EXTERNAL_INT_7)', 'out': '''\ #if defined(OAT_DEBUG_BUILD) #pragma message "OAT_DEBUG_BUILD is defined, ISR 7 disabled in WInterrupts.c" #else IMPLEMENT_ISR(INT7_vect, EXTERNAL_INT_7) #endif ''' }, ] } } for filepath_glob, file_patch_info in source_patch_dict.items(): file_src_path = file_patch_info['actual_src_path'] if not file_src_path: cprint(f'Could not find {filepath_glob} to patch! Skipping...') continue env.AddBuildMiddleware( patch_function_factory(src_path=file_src_path, replacement_list=file_patch_info['patches'], output_suffix='WInterrupts.c'), filepath_glob )
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import pytest from ymmsl import Reference, Settings from libmuscle.settings_manager import SettingsManager @pytest.fixture def settings_manager() -> SettingsManager: return SettingsManager() def test_create(settings_manager): assert len(settings_manager.base) == 0 assert len(settings_manager.overlay) == 0 def test_get_setting(settings_manager): ref = Reference settings_manager.base[ref('test')] = 13 assert settings_manager.get_setting(ref('instance'), ref('test')) == 13 settings_manager.overlay[ref('test2')] = 14 assert settings_manager.get_setting(ref('instance'), ref('test2')) == 14 settings_manager.base[ref('test2')] = 'test' assert settings_manager.get_setting(ref('instance'), ref('test2')) == 14 settings_manager.overlay = Settings() assert settings_manager.get_setting(ref('instance'), ref('test2')) == \ 'test' settings_manager.base[ref('test3')] = 'base_test3' settings_manager.base[ref('instance.test3')] = 'base_instance_test3' assert settings_manager.get_setting(ref('instance'), ref('test3')) == \ 'base_instance_test3' assert settings_manager.get_setting(ref('instance2'), ref('test3')) == \ 'base_test3' settings_manager.overlay[ref('test3')] = 'overlay_test3' settings_manager.overlay[ref('instance.test3')] = 'overlay_instance_test3' assert settings_manager.get_setting(ref('instance'), ref('test3')) == \ 'overlay_instance_test3' assert settings_manager.get_setting(ref('instance2'), ref('test3')) == \ 'overlay_test3' settings_manager.base[ref('instance.test4')] = 'base_test4' settings_manager.overlay[ref('test4')] = 'overlay_test4' assert settings_manager.get_setting(ref('instance'), ref('test4')) == \ 'base_test4' assert settings_manager.get_setting(ref('instance[10]'), ref('test4') ) == 'base_test4' settings_manager.base[ref('instance[10].test5')] = 'base_test5' settings_manager.overlay[ref('test5')] = 'overlay_test5' assert settings_manager.get_setting(ref('instance'), ref('test5')) == \ 'overlay_test5' assert settings_manager.get_setting(ref('instance[10]'), ref('test5') ) == 'base_test5' assert settings_manager.get_setting(ref('instance[11]'), ref('test5') ) == 'overlay_test5'
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import logging import codecs from scribeui_pyramid.modules.maps.models import Map from scribeui_pyramid.modules.workspaces.models import Workspace from BeautifulSoup import BeautifulStoneSoup from pyramid.view import view_config from pyramid.response import FileResponse from sqlalchemy.orm.exc import NoResultFound log = logging.getLogger(__name__) import pprint, os, fnmatch class APIMapcacheViewer(object): def __init__(self, request): self.request = request self.matchdict = request.matchdict @view_config( route_name='mapcache.getLayers', permission='view', renderer='json', request_method='GET' ) def getLayers(self): response = { 'status': 0, 'errors': [], 'layers': [], 'layernames': [] } try: mapID = self.request.GET.get('map') except KeyError as e: response['errors'].append('A map ID is required.') return response if mapID is None: response['errors'].append('A map ID is required.') return response try: map = Map.by_id(mapID) except NoResultFound, e: response['errors'].append('This map is unavailable or does not exist.') return response workspace = Workspace.by_id(map.workspace_id) if(workspace.name == self.request.userid): ##First, let's browse the folders to find some finished jobs. ## TODO: Add optional additional paths. paths = [] ## Add the default folder workspacesDirectory = self.request.registry.settings.get('workspaces.directory', '') + '/' mapDirectory = workspacesDirectory + self.request.userid + '/' + map.name + '/' mapcacheDirectory = self.request.registry.settings.get('mapcache.output.directory', '') if not mapcacheDirectory or mapcacheDirectory == '': mapcacheDirectory = mapDirectory+'mapcache/' else: mapcacheDirectory = mapcacheDirectory.rstrip('/') + '/' paths.append(mapcacheDirectory) level = 3 #maximum depth for recursive search for path in paths: some_dir = path.rstrip(os.path.sep) if os.path.isdir(some_dir): num_sep = some_dir.count(os.path.sep) for root, dirs, filenames in os.walk(some_dir): num_sep_this = root.count(os.path.sep) if num_sep + level <= num_sep_this: del dirs[:] for filename in fnmatch.filter(filenames, 'mapcacheConfig.xml'): response['layernames'].append(os.path.split(root)[1]) response['layers'].append(os.path.join(root, filename)) pprint.pprint(os.path.join(root, filename)) break else: response['errors'].append('Access denied.') return response @view_config( route_name='mapcache.tiles', permission='view', renderer='json', request_method='GET' ) def tiles(self): response = { 'status': 0, 'errors': [], } # Validation try: mapID = self.request.GET.get('map') except KeyError as e: response['errors'].append('A map ID is required.') if mapID is None: response['errors'].append('A map ID is required.') try: jobPath = self.request.GET.get('job') except KeyError as e: response['errors'].append('A job path is required.') if jobPath is None: response['errors'].append('A job path is required.') try: tilerequest = self.request.GET.get('request') except KeyError as e: response['errors'].append('A tile request is required.') if tilerequest is None: response['errors'].append('A tile request is required.') try: map = Map.by_id(mapID) except NoResultFound, e: response['errors'].append('This map is unavailable or does not exist.') return response workspace = Workspace.by_id(map.workspace_id) if len(response['errors']) is 0: if workspace.name == self.request.userid: if(os.path.isfile(jobPath)): # We now get the tileset and the grid from the config file # NOTE: We only support 1 tileset per config file for now, but several grids are supported. try: with codecs.open(jobPath, encoding='utf8') as f: content = f.read() f.close() except IOError: response['errors'].append("An error occured while opening '" + config_file + "' file.") return response content = BeautifulStoneSoup(content) tileset = content.mapcache.find('tileset') #Finding out the name of the tileset tilesetname = tileset['name'] #Getting the tileset's grid grid = tileset.find("grid").getText() #getting the cache's path cacheName = tileset.find("cache").getText() cache = content.find("cache", {"name":cacheName}) cachePath = cache.find("base").getText() tilesPath = os.path.join(cachePath,tilesetname) tilesPath = os.path.join(tilesPath,grid) if(os.path.isdir(tilesPath)): requestArgs = tilerequest.split("/") z = str(int(requestArgs[2])+1).zfill(2) x = requestArgs[3].zfill(9) y = requestArgs[4] y = y.replace(".png","") y = y.zfill(9) imagepath = os.path.join(tilesPath, z, x[:3], x[3:6], x[6:9], y[:3], y[3:6],y[6:9]+".png") if os.path.isfile(imagepath): return FileResponse( imagepath, content_type="image/png" ) else: response['errors'].append('Access denied.') return response
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from django.test import TestCase from rest_framework import serializers class EmptySerializerTestCase(TestCase): def test_empty_serializer(self): class FooBarSerializer(serializers.Serializer): foo = serializers.IntegerField() bar = serializers.SerializerMethodField('get_bar') def get_bar(self, obj): return 'bar' serializer = FooBarSerializer() self.assertEquals(serializer.data, {'foo': 0})
177414
from datetime import datetime import os from collections import defaultdict import os import yaml from .postgresql_manager import PostgreSQL_Manager ROOT_DIR = os.path.abspath(os.path.dirname(__file__)) class OpenDataWriter(object): def __init__(self, config): self._config = config allowed_fields_file_path = (config.field_data_file if config.field_data_file.startswith('/') else os.path.join(ROOT_DIR, '..', 'cfg_lists', config.field_data_file)) schema = self._get_schema(allowed_fields_file_path) db_data = {'host_address': config.postgres['host_address'], 'port_number': config.postgres['port'], 'database_name': config.postgres['database_name'], 'table_name': config.postgres['table_name'], 'user': config.postgres['user'], 'password': config.postgres['password'], 'table_schema': schema, 'readonly_users': config.postgres['readonly_users']} self._db_manager = PostgreSQL_Manager(**db_data) def write_records(self, records): self._db_manager.add_data(records) def _ensure_directory(self, path): if not os.path.exists(path): os.makedirs(path) def _get_schema(self, field_data_file_path): with open(field_data_file_path) as field_data_file: schema = [] for field_name, field_data in yaml.safe_load(field_data_file)['fields'].items(): if field_name not in ['id']: schema.append((field_name, field_data['type'])) schema.sort() return schema
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import json import logging import os import re import sys import urllib.parse from urllib.error import HTTPError, URLError from urllib.request import Request import praw import requests import yaml from shared.exceptions import AlreadyProcessed def load_configuration(): conf_file = os.path.join(os.path.dirname(__file__), os.environ['CONFIG']) with open(conf_file, encoding='utf8') as f: config = yaml.safe_load(f) # load dependent configuration config['FOOTER'] = "\n\n *** \n" + config['INFO_LINK'] + "&#32;|&#32;" + config[ 'CONTACT_LINK'] return config CONFIG = load_configuration() def authenticate(): """Authenticate via praw.ini file, look at praw documentation for more info""" authentication = praw.Reddit(site_name=CONFIG['BOT_NAME']) logging.info(f'Authenticated as {authentication.user.me()}') return authentication def log(service, stdout=False): if stdout: logging.basicConfig( stream=sys.stdout, level=logging.INFO, format=f'{service:<6}: %(asctime)s %(levelname)s: %(message)s', datefmt='%Y-%m-%d %H:%M:%S' ) else: logging.basicConfig( filename=f"shared/logs/bot.log", level=logging.INFO, format=f'{service:<6}: %(asctime)s %(levelname)s: %(message)s', datefmt='%Y-%m-%d %H:%M:%S' ) def get_reddit_item(reddit, request): if request['type'] == "message": return reddit.inbox.message(request['id']) else: return reddit.comment(request['id']) def contains_link(string): """Returns link or empty string""" match_link = re.search( r"https?://(www\.)?[-a-zA-Z0-9@:%._+~#=]{2,256}\.[a-z]{2,6}\b([-a-zA-Z0-9@:%_+.~#?&/=]*)", string) return match_link[0] if match_link else "" def contains_username(name, string): """Returns regex search""" return re.search(r"(?i)u/" + name, string) def get_lock(request_id): return f"{CONFIG['REDIS_REQUESTS_LOCKED']}:{request_id}" def open_lock(redis, request_id): # Remove redundant lock to free up space lock = get_lock(request_id) redis.delete(lock) def handle_failed_request(redis, request, current_set, exception): if request['retries'] > 10: open_lock(redis, request['id']) request.update( error=str(exception) ) next_set = CONFIG['REDIS_REQUESTS_FAILED'] logging.error(f"Reached retry limit. Pushing request {request['id']} : {request['link']} to failed requests.") else: request['retries'] += 1 next_set = current_set request_json = json.dumps(request) redis.sadd(next_set, request_json) def is_link_valid(link): # Check if download is valid without downloading if "reddit.tube" in link: if requests.head(link, timeout=10).ok: return True return False try: status_code = urllib.request.urlopen(link, timeout=2).getcode() return status_code == 200 except (HTTPError, URLError, ValueError): return False def already_processed_check(redis, request): if redis.sismember(CONFIG['REDIS_REQUESTS_SUCCESS'], request['id']): raise AlreadyProcessed(request['link'])
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from __future__ import division, print_function import tensorflow as tf import wave, os, sys import soundfile as sf import numpy as np import librosa from datetime import datetime def create_adam_optimizer(learning_rate, momentum): return tf.train.AdamOptimizer(learning_rate=learning_rate, epsilon=1e-6) def create_sgd_optimizer(learning_rate, momentum): return tf.train.MomentumOptimizer(learning_rate=learning_rate, momentum=momentum) def create_rmsprop_optimizer(learning_rate, momentum): return tf.train.RMSPropOptimizer(learning_rate=learning_rate, momentum=momentum, epsilon=1e-5) optimizer_factory = { 'adam': create_adam_optimizer, 'sgd': create_sgd_optimizer, 'rmsprop': create_rmsprop_optimizer } def save(saver, sess, logdir, step): model_name = 'model.ckpt' checkpoint_path = os.path.join(logdir, model_name) print('Storing checkpoint to {} ...'.format(logdir), end='') sys.stdout.flush() if not os.path.exists(logdir): os.makedirs(logdir) saver.save(sess, checkpoint_path, global_step=step) print('Done.') def load(saver, sess, logdir): print("Trying to restore saved checkpoints from {} ...".format(logdir), end='') ckpt = tf.train.get_checkpoint_state(logdir) if ckpt: print(" Checkpoint found: {}".format(ckpt.model_checkpoint_path)) global_step = int(ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1]) print(" Global step was: {}".format(global_step)) print(" Restoring...", end="") saver.restore(sess, ckpt.model_checkpoint_path) print(" Done.") return global_step else: print(" No checkpoint found.") return None def get_default_logdir(logdir_root, started_time): logdir = os.path.join(logdir_root, 'train', started_time) return logdir def validate_directories(args): # Arrangement logdir_root = args.logdir_root if logdir_root is None: logdir_root = './logdir' logdir = args.logdir if logdir is None: logdir = get_default_logdir(logdir_root, "{0:%Y-%m-%dT%H-%M-%S}".format(datetime.now())) print('Using default logdir: {}'.format(logdir)) restore_from = args.restore_from if restore_from is None: restore_from = logdir return { 'logdir': logdir, 'logdir_root': args.logdir_root, 'restore_from': restore_from } def learning_rate_decay(global_step, args, hparams): warm_up_step = int(hparams.warm_up_step) decay_step = int(hparams.decay_step) learning_rate = tf.cond( global_step < warm_up_step, lambda: tf.convert_to_tensor(args.learning_rate), lambda: tf.train.exponential_decay(args.learning_rate, global_step - warm_up_step + 1, decay_step, 0.5)) return tf.maximum(hparams.mini_lr, learning_rate) def create_optimizer(global_step, args, hparams): with tf.variable_scope('optimizer'): learning_rate_decayed = learning_rate_decay(global_step, args, hparams) optimizer = optimizer_factory[args.optimizer]( learning_rate=learning_rate_decayed, momentum=args.momentum) return learning_rate_decayed, optimizer def one_hot(samples, channels): with tf.name_scope('one_hot_encode'): encoded = tf.one_hot(samples, depth=channels, dtype=tf.float32) shape = [samples.get_shape().as_list()[0], -1, channels] encoded = tf.reshape(encoded, shape) return encoded
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from app.extensions import db class User(db.Document): """User model """ username = db.StringField() password = db.StringField() def to_json2(self): """Returns a json representantion of the user. :returns: a json object. """ return { 'id': str(self.id), 'username': self.username }
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class Marker(object): def __init__(self): self._body = None def make(self): raise NotImplementedError def update(self, marker): pass def show(self): if self._body is None: self._body = self.make() self.update(self._body) def hide(self): if self._body is not None: self._body.remove() self._body = None
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from bs4 import BeautifulSoup import urlparse import datetime from scraper import * class General(Scraper): def log_index_page(self): """Logs the index page, used for test purposes""" url = self.url_provider.get_page_url('overview') res = self.open_url(url) self.logger.info(res.read()) def get_game_datetime(self): url = self.url_provider.get_page_url('overview') res = self.open_url(url) soup = BeautifulSoup(res.read(), "lxml") datetime_data = soup.find("li", {"class": "OGameClock"}).text game_datetime = datetime.datetime.strptime(datetime_data, "%d.%m.%Y %H:%M:%S") return game_datetime def get_resources(self, planet): self.logger.info('Getting resources data for planet %s' % planet.name) url = self.url_provider.get_page_url('resources', planet) res = self.open_url(url) soup = BeautifulSoup(res.read(), "lxml") metal = int(soup.find(id='resources_metal').text.replace('.', '')) crystal = int(soup.find(id='resources_crystal').text.replace('.', '')) deuterium = int(soup.find(id='resources_deuterium').text.replace('.', '')) energy = int(soup.find(id='resources_energy').text.replace('.', '')) return Resources(metal, crystal, deuterium, energy) def get_planets(self): self.logger.info('Getting planets') url = self.url_provider.get_page_url('resources') res = self.open_url(url) soup = BeautifulSoup(res.read(), "lxml") links = soup(attrs={'class': "planetlink"}) planets = [Planet((str(link(attrs={'class': "planet-name"})[0].contents[0])), urlparse.parse_qs(link['href'])['cp'][0], parse_coordinates(str(link(attrs={'class': "planet-koords"})[0].contents[0]))) for link in links] return planets def parse_coordinates(coords): return coords.replace('[', '').replace(']', '')
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import torch import torch.optim as optim import torch.nn.functional as F import numpy as np import thinplate as tps from numpy.testing import assert_allclose def test_pytorch_grid(): c_dst = np.array([ [0., 0], [1., 0], [1, 1], [0, 1], ], dtype=np.float32) c_src = np.array([ [10., 10], [20., 10], [20, 20], [10, 20], ], dtype=np.float32) / 40. theta = tps.tps_theta_from_points(c_src, c_dst) theta_r = tps.tps_theta_from_points(c_src, c_dst, reduced=True) np_grid = tps.tps_grid(theta, c_dst, (20,20)) np_grid_r = tps.tps_grid(theta_r, c_dst, (20,20)) pth_theta = torch.tensor(theta).unsqueeze(0) pth_grid = tps.torch.tps_grid(pth_theta, torch.tensor(c_dst), (1, 1, 20, 20)).squeeze().numpy() pth_grid = (pth_grid + 1) / 2 # convert [-1,1] range to [0,1] pth_theta_r = torch.tensor(theta_r).unsqueeze(0) pth_grid_r = tps.torch.tps_grid(pth_theta_r, torch.tensor(c_dst), (1, 1, 20, 20)).squeeze().numpy() pth_grid_r = (pth_grid_r + 1) / 2 # convert [-1,1] range to [0,1] assert_allclose(np_grid, pth_grid) assert_allclose(np_grid_r, pth_grid_r) assert_allclose(np_grid_r, np_grid)
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import io import asyncio import threading import queue import logging from starlette import concurrency logger = logging.getLogger('vaex.file.async') class WriteStream(io.RawIOBase): '''File like object that has a sync write API, and a generator as consumer. This is useful for letting 1 thread write to this object, while another thread in consuming the byte chunks via an iterator, or async iterator. To let the writer thread stop, simply close the file. ''' def __init__(self, queue_size=3): self.writes = [] self.queue = queue.Queue(queue_size) self.closed = False self.pos = 0 self.exception = None def __iter__(self): yield from self.chunks() async def __aiter__(self): import starlette.concurrency async for item in starlette.concurrency.iterate_in_threadpool(self.chunks()): yield item def __enter__(self, *args): return self def __exit__(self, type, value, traceback): self.close() self.exception = value def read(self, *args): return b'' def seek(self, *args): if self.closed: return ValueError('stream closed') return 0 def readinto(self, *args): return b'' def tell(self): if self.closed: return ValueError('stream closed') return self.pos def flush(self): if self.closed: return ValueError('stream closed') pass def writable(self): return True def readable(self): return False def seekable(self): return False def write(self, b): if self.closed: return ValueError('stream closed') logger.debug('write: %r', len(b)) buffer = memoryview(b) # print("--", bytes(buffer)) self.pos += len(buffer) # we need to copy it seems (otherwise if we use a buffered writer, it will reuse the memory) self.queue.put(bytes(buffer)) # print(len(buffer)) return len(buffer) def close(self, force=False): '''Note that close can block due to the queue, using force=True the queue will be cleared''' logger.debug('closing stream, putting None element in queue to stop chunk yielding') # make sure nobody will add new items to the queue, at max 1 (the current write) self.closed = True if force: self._force_put(None) else: self.queue.put(None) def closed(self): return self.closed def chunks(self): logger.debug('yielding chunks') while True: logger.debug('waiting for chunk') item = self.queue.get() if item is None: logger.debug('stop yielding, file closed') break # if isinstance(item, BaseException): # logger.debug('stop yielding, exception occured') # raise item yield item if self.exception: raise self.exception def getvalue(self): return b''.join(bytes(k) for k in self.chunks()) # def stop(self, exception): # '''Empty the queue, and put the exception on the queue, and close the file. # If we don't empty the queue, this might block # ''' # self._force_put(exception) # self.closed = True def _force_put(self, item): # keep trying to put an exception on the queue # we dont want to do this blocking, since a producer # thread might fill this up. done = False while not done: logger.debug('clearing queue') while not self.queue.empty(): self.queue.get(block=False) try: logger.debug('put %r on queue', item) self.queue.put(item, block=False) done = True except queue.Full: logger.debug('retry putting exception on queue, because it was filled')
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import unittest from katas.kyu_7.sum_squares_of_numbers_in_list_that_may_contain_more_lists \ import SumSquares class SumSquaresTestCase(unittest.TestCase): def test_equal_1(self): self.assertEqual(SumSquares([1, 2, 3]), 14) def test_equal_2(self): self.assertEqual(SumSquares([[1, 2], 3]), 14) def test_equal_3(self): self.assertEqual(SumSquares([[[[[[[[[1]]]]]]]]]), 1) def test_equal_4(self): self.assertEqual(SumSquares([10, [[10], 10], [10]]), 400) def test_equal_5(self): self.assertEqual(SumSquares( [1, [[3], 10, 5, [2, [3], [4], [5, [6]]]], [10]] ), 325)
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import numpy as np import pybullet as p import pybullet_data as pd import pybullet_utils.bullet_client as bc from gym import spaces try: from .. import Environment from .robots import get_robot from .tasks import get_task except ImportError: from karolos.environments import Environment from karolos.environments.robot_task_environments.robots import get_robot from karolos.environments.robot_task_environments.tasks import get_task class RobotTaskEnvironment(Environment): def __init__(self, task_config, robot_config, render=False, bullet_client=None, **kwargs): self.render = render self.task_config = task_config self.robot_config = robot_config if bullet_client is None: connection_mode = p.GUI if render else p.DIRECT bullet_client = bc.BulletClient(connection_mode) bullet_client.setAdditionalSearchPath(pd.getDataPath()) time_step = 1. / 300. bullet_client.setTimeStep(time_step) bullet_client.setRealTimeSimulation(0) bullet_client.loadURDF("plane.urdf") self.bullet_client = bullet_client self.task = get_task(task_config, self.bullet_client) self.robot = get_robot(robot_config, self.bullet_client) self.action_space = self.robot.action_space self.observation_space = spaces.Dict({ 'robot': self.robot.observation_space, 'task': self.task.observation_space, }) self.reward_function = self.task.reward_function self.success_criterion = self.task.success_criterion def reset(self, desired_state=None): """ Reset the environment and return new state """ try: if desired_state is not None: observation_robot = self.robot.reset(desired_state["robot"]) observation_task, goal_info, _ = self.task.reset(self.robot, observation_robot, desired_state[ "task"]) else: observation_robot = self.robot.reset() observation_task, goal_info, _ = self.task.reset(self.robot, observation_robot) except AssertionError as e: return e state = { 'robot': observation_robot, 'task': observation_task } return state, goal_info def step(self, action): observation_robot = self.robot.step(action) observation_task, goal_info, done = self.task.step(observation_robot) state = { 'robot': observation_robot, 'task': observation_task } return state, goal_info, done if __name__ == "__main__": import time env_kwargs = { "render": True, "task_config": { "name": "pick_place", # "max_steps": 25 }, "robot_config": { "name": "panda", # "scale": .1, # "sim_time": .1 } } env = RobotTaskEnvironment(**env_kwargs) p.resetDebugVisualizerCamera(cameraDistance=1.5, cameraYaw=70, cameraPitch=-27, cameraTargetPosition=(0, 0, 0) ) time_step = p.getPhysicsEngineParameters()["fixedTimeStep"] while True: obs = env.reset() for _ in np.arange(1. / time_step): action = env.action_space.sample() time.sleep(time_step) observation, goal, done = env.step(action) reward = env.reward_function(False, goal)
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from typing import Any from graphscale.grapple.graphql_printer import print_graphql_defs from graphscale.grapple.parser import parse_grapple def assert_graphql_def(snapshot: Any, graphql: str) -> None: result = print_graphql_defs(parse_grapple(graphql)) snapshot.assert_match(result) def test_basic_type(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { name: String }""") def test_non_pythonic_name(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { longName: String }""") def test_nonnullable_type(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { name: String! }""") def test_list_type(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { names: [String] }""") def test_list_of_reqs(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { names: [String!] }""") def test_req_list(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { names: [String]! }""") def test_req_list_of_reqs(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { names: [String!]! }""") def test_double_list(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { matrix: [[String]] }""") def test_ref_to_self(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { other: Test }""") def test_args(snapshot: Any) -> None: assert_graphql_def(snapshot, """type Test { relatives(skip: Int, take: Int) : [Test] }""") def test_args_defaults(snapshot: Any) -> None: assert_graphql_def( snapshot, """type Test { many_args( defaultTen: Int = 10, defaultTwenty: Int = 20, defaultZero: Int = 0, strArg: String = "foo", defaultTrue: Boolean = true, defaultFalse: Boolean = false, ) : [Test] }""" ) def test_enum(snapshot: Any) -> None: assert_graphql_def( snapshot, """ type Hospital { status: HospitalStatus reqStatus: HospitalStatus! } enum HospitalStatus { AS_SUBMITTED } """ )
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def test_logout(ui): driver = ui.driver driver.find_element_by_css_selector(".user-dropdown").click() driver.find_element_by_css_selector(".logout-button").click() assert driver.find_element_by_css_selector('.login-form') def test_recorded_sessions_visible(ui_session): assert ui_session is not None
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user_input = 999 while user_input != "0": user_input = input("์‹ญ์ง„์ˆ˜ ์ˆซ์ž๋ฅผ ์ž…๋ ฅํ•ด์ฃผ์„ธ์š” : ") try: decimal_number = int(user_input) print(bin(decimal_number)) except ValueError as e: print(e) print("Error - 10์ง„์ˆ˜ ์ˆซ์ž๋งŒ ์ž…๋ ฅํ•ด์ฃผ์‹œ๊ธฐ ๋ฐ”๋ž๋‹ˆ๋‹ค.")
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import json import re import requests from rich.console import Console LOGIN_URL = "https://www.headspace.com/login" AUTH_URL = "https://auth.headspace.com/co/authenticate" BEARER_TOKEN_URL = "https://auth.headspace.com/authorize" session = requests.Session() console = Console() headers = { "User-Agent": "Mozilla/5.0 (X11; Linux x86_64; rv:88.0) Gecko/20100101 Firefox/88.0", "Accept": "*/*", "Accept-Language": "en-US,en;q=0.5", "Content-Type": "application/json", "Origin": "https://www.headspace.com", "Connection": "keep-alive", "TE": "Trailers", } session.headers.update(headers) def get_client_id(): response = session.get(LOGIN_URL) client_id = re.findall(r'"clientId":"(.+?)",', response.text)[0] return client_id def prompt(): email = console.input(f"[bold red]?[/] Email: ") password = console.input(f"[bold red]?[/] Password: ", password=True) return email, password def get_bearer_token(client_id, login_ticket): params = { "client_id": client_id, "response_type": "token", "response_mode": "web_message", "redirect_uri": "https://www.headspace.com/auth", "scope": "openid email", "audience": "https://api.prod.headspace.com", "realm": "User-Password-Headspace", "login_ticket": login_ticket, "prompt": "none", } response = session.get(BEARER_TOKEN_URL, params=params) html = response.text bearer_token = re.findall(r'"access_token":"(.+?)"', html)[0] return bearer_token def authenticate(email, password): data = { "client_id": get_client_id(), "username": email, "password": password, "realm": "User-Password-Headspace", "credential_type": "http://auth0.com/oauth/grant-type/password-realm", } response = session.post( AUTH_URL, headers=headers, data=json.dumps(data), ) resp_json: dict = response.json() try: login_ticket = resp_json["login_ticket"] except KeyError: if "error" in resp_json.keys(): console.print(resp_json["error"], style="red") if "error_description" in resp_json.keys(): console.print(resp_json["error_description"]) else: console.print(resp_json) return False bearer_token = get_bearer_token(data["client_id"], login_ticket) bearer_token = "bearer " + bearer_token return bearer_token
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import ctypes import numpy as np from devito.tools.utils import prod __all__ = ['numpy_to_ctypes', 'numpy_to_mpitypes', 'numpy_view_offsets'] def numpy_to_ctypes(dtype): """Map numpy types to ctypes types.""" return {np.int32: ctypes.c_int, np.float32: ctypes.c_float, np.int64: ctypes.c_int64, np.float64: ctypes.c_double}[dtype] def numpy_to_mpitypes(dtype): """Map numpy types to MPI datatypes.""" return {np.int32: 'MPI_INT', np.float32: 'MPI_FLOAT', np.int64: 'MPI_LONG', np.float64: 'MPI_DOUBLE'}[dtype] def numpy_view_offsets(array, base=None): """ Retrieve the offset of a view from its base array along each dimension and side. :param array: A :class:`numpy.ndarray`. :param base: The base of ``array``. Most of the times the ``base`` is available through ``array.base``. However, if this function is to be called within ``__array_finalize__``, where ``base`` hasn't been set yet, the ``base`` has to be provided explicitly """ if not isinstance(array, np.ndarray): raise TypeError("Expected a `numpy.ndarray`, got `%s`" % type(array)) if array.base is None: if base is None: raise ValueError("Cannot access ``array``'s base.") else: base = array.base start_byte_distance = np.byte_bounds(array)[0] - np.byte_bounds(base)[0] start_elem_distance = start_byte_distance // array.itemsize assert start_byte_distance % array.itemsize == 0 end_byte_distance = np.byte_bounds(array)[1] - np.byte_bounds(base)[0] end_elem_distance = (end_byte_distance // array.itemsize) - 1 assert end_byte_distance % array.itemsize == 0 offsets = [] for i, s in enumerate(base.shape): hyperplane_size = prod(base.shape[i+1:]) # Start lofs = start_elem_distance // hyperplane_size start_elem_distance -= lofs*hyperplane_size # End rofs = end_elem_distance // hyperplane_size end_elem_distance -= rofs*hyperplane_size offsets.append((lofs, s-rofs-1)) return tuple(offsets)
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import argparse import fnmatch import os import pathlib import sys import textwrap import yaml def write_header(output): header=''' ### # This file is automatically generated by {}. Do not edit! ### ''' output.write(textwrap.dedent(header.format(os.path.basename(__file__))).lstrip()) output.write('\n') def to_ipv4(proto, field, data): prop = { 'type': 'string', 'description': 'IPv4 {} address'.format(field), 'pattern': '^((25[0-5]|2[0-4][0-9]|[01]?[1-9]?[0-9])\.){3}(25[0-5]|2[0-4][0-9]|[01]?[1-9]?[0-9])$' } if 'default' in data: prop['default'] = data['default'] return prop def to_ipv6(proto, field, data): prop = { 'type': 'string', 'description': 'IPv6 {} address'.format(field), 'pattern': '^((::[0-9a-fA-F]{1,4})|([0-9a-fA-F]{1,4}::)|(([0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F])|(([0-9a-fA-F]{1,4}:){7}[0-9a-fA-F]{1,4}))$' } if 'default' in data: prop['default'] = data['default'] return prop def to_mac(proto, field, data): prop = { 'type': 'string', 'description': 'Ethernet MAC {} address'.format(field), 'pattern': '^([0-9a-fA-F]{1,2}(.|-|:)){5}[0-9a-fA-F]{1,2}$' } if 'default' in data: prop['default'] = data['default'] return prop def to_description(proto, field, data): if 'description' in data: return data['description'] else: return '{} {}'.format(proto, field).translate(str.maketrans('_', ' ')) def to_bool(proto, field, data): prop = { 'type': 'boolean', 'description': to_description(proto, field, data) } return prop def to_number(proto, field, data): length = int(data['length']) if length == 1: return to_bool(proto, field, data) max_value = int(pow(2, length)) - 1 if 'multipleOf' in data: max_value *= int(data['multipleOf']) prop = { 'type': 'integer', 'description': to_description(proto, field, data), 'format': 'int32' if data['length'] < 32 else 'int64', 'minimum': 0, 'maximum': max_value } if 'default' in data: prop['default'] = int(data['default']) if 'multipleOf' in data: prop['multipleOf'] = int(data['multipleOf']) return prop def to_enumeration_items(proto, field, data): return [next(iter(t)) for t in data['items']] def to_enumeration(proto, field, data): if 'uniqueItems' in data: prop = { 'type': 'string', 'description': to_description(proto, field, data), 'enum': to_enumeration_items(proto, field, data) } else: prop = { 'type': 'array', 'description': to_description(proto, field, data), 'items': { 'enum': to_enumeration_items(proto, field, data), 'type': 'string' } } if 'default' in data: prop['default'] = data['default'] return prop def dummy(field): return dict() def to_property(proto, field, data): format_dispatch = { 'ipv4': to_ipv4, 'ipv6': to_ipv6, 'mac': to_mac, 'number': to_number, 'enumeration': to_enumeration } prop = dict() if 'format' in data and data['format'] in format_dispatch: prop.update(format_dispatch[data['format']](proto, field, data)) else: prop.update(to_number(proto, field, data)) return prop def translate_fields(proto, blob): properties = dict() for field, props in blob.items(): properties[field] = to_property(proto, field, props) return properties def to_swagger_name(name): return 'PacketProtocol{}'.format(name.lower().capitalize()) """ Begin script proper """ def main(): parser = argparse.ArgumentParser( description="Generate swagger protocol specification from YAML definitions") parser.add_argument('--indir', nargs='?', type=pathlib.Path, default=os.getcwd(), help="input directory containing YAML definitions") parser.add_argument('--outfile', nargs='?', type=argparse.FileType('w'), default=sys.stdout, help="output swagger definition") args = parser.parse_args() if not os.path.isdir(args.indir): sys.stderr.write('Input directory, {}, does not exist\n'.format(args.indir)) sys.exit(1) if not os.access(args.indir, os.R_OK): sys.stderr.write('Input directory, {}, is not readable\n'.format(args.indir)) sys.exit(1) definitions = dict() for yaml_file in filter(lambda f: fnmatch.fnmatch(f, '*.yaml'), os.listdir(args.indir)): with open(os.path.join(args.indir, yaml_file), 'r') as f: for name, data in yaml.load(f, Loader=yaml.FullLoader).items(): definitions[name] = data swagger = dict() for name, data in definitions.items(): swagger_name = to_swagger_name(name) swagger[swagger_name] = { 'type': 'object', 'description': 'Describes {} {} header'.format( 'an' if name.lower()[0] in 'aeio' else 'a', name), } swagger[swagger_name]['properties'] = translate_fields(name, data['fields']) write_header(args.outfile) args.outfile.write(yaml.dump({'definitions': swagger})) if __name__ == "__main__": main()
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class CloudWatchEvent: def __init__(self, schedule_expression: str, is_active: bool, name: str =None): self.name = name self.schedule_expression = schedule_expression self.is_active = is_active
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from app import __metadata__ as meta from configparser import ConfigParser, ExtendedInterpolation from pathlib import Path from shutil import copy import os import io import logging log = logging.getLogger(__name__) APP = meta.APP_NAME ''' This component is responsible for configuration management. If this is the first time the app is run then it will create the config file, and set the system environment variables for the app The logic for checking the existence of the conf file and creating it if it's missing should be in init.py TODO: Add 2 more config sources 1) service - Get config from a service endpoint (JSON) 2) db - Get config from a database ''' class MetaConf(object): def __init__(self): conf = ConfigParser() conf.read_string(meta.__default_config__) self.config = conf self.resolveMacros() self.log_file, self.config_file = self.getConfPaths() def resolveMacros(self): for section in self.config.sections(): for k in self.config.options(section): v = self.config.get(section, k) if '{{app_root}}' in v: if 'SNAP_USER_COMMON' in Config.envGet2('SNAP_USER_COMMON'): v = v.replace('{{app_root}}', self.getSnapPath()) else: v = v.replace('{{app_root}}', self.getConfRoot()) self.config.set(section, k, v) def getConfRoot(self): module_dir = os.path.dirname(__file__) app_dir = os.path.dirname(module_dir) return os.path.dirname(app_dir) def getSnapPath(self): if not os.path.exists(str(Path.home()) + '/conf'): os.makedirs(str(Path.home()) + '/conf') os.makedirs(str(Path.home()) + '/logs') Path(str(Path.home()) + '/logs/lxdui.log').touch() copy(self.getConfRoot() + '/conf/auth.conf', str(Path.home()) + '/conf') copy(self.getConfRoot() + '/conf/log.conf', str(Path.home()) + '/conf') return str(Path.home()) def getConfPaths(self): f = io.StringIO() self.config.write(f) c = ConfigParser(interpolation=ExtendedInterpolation()) f.seek(0) c.read_file(f) log_file = c.get(APP, '{}.log.file'.format(APP.lower())) config_file = c.get(APP, '{}.conf.file'.format(APP.lower())) return log_file, config_file class Config(object): def __init__(self, **kwargs): """ Initialises the Config object and loads the configuration into memory. Order of operations: 1) if a config file has been provided then use that one 2) check to see if we have a local config file, and if so use that 3) no config file found so we'll create one with defaults :param kwargs: conf=</path/to/config/file> #External source """ m = MetaConf() self.config = None self.log_file = m.log_file self.config_file = m.config_file # conf file specified by the caller if kwargs: file = kwargs.get('conf') log.info('Loading external config file: {}'.format(file)) if file: self.config = self.load('external', file) self.envSet(log=self.log_file, conf=file) else: raise Exception('Unsupported parameter {}'.format(kwargs)) # no conf parameters specified so check local conf file elif Path(self.config_file).exists(): log.info('Using config file path = {}'.format(self.config_file)) self.config = self.load('ini', self.config_file) self.envSet() # load the default config from meta elif meta.AUTO_LOAD_CONFIG: log.info('Load default config (meta)') self.config = m.config self.envSet() self.save() else: raise Exception('Unable to load the configuration.') def load(self, conf_type, *file_path): """ Load the configuration into memory. The configuration is stored in the Config object. :param conf_type: :param file_path: :return: """ if conf_type == 'external': external_conf_file = Path(*file_path) config = self.getConfig(external_conf_file) return config elif conf_type == 'ini': conf = self.getConfig(self.config_file) return conf elif conf_type == 'service': raise Exception('Not implemented.') elif conf_type == 'db': raise Exception('Not implemented.') else: raise Exception('Unable to determine configuration type.') def get(self, section, key): """ Retrieve a configuration parameter. :param section: The section of the ini file to search :param key: The key to look up :return: Returns the value associated with the key """ return self.config.get(section, key) def set(self, section, key, value): """ Update a configuration parameter. :param section: The section of the ini config file to update :param key: The key that needs to be updated :param value: The new value associated with the key :return: """ self.config.set(section, key, value) def show(self): """ Prints out a listing of the config file to the console. :return: """ for section in self.config.sections(): for k in self.config.options(section): v = self.config.get(section, k) print('{} = {}'.format(k, v)) def save(self): """ Save the contents of the config object to the conf file. :return: """ with open(self.config_file, 'w') as f: self.config.write(f) @staticmethod def envGet(): """ Retrieve the environment variables containing the log and conf paths. :return: Returns a dictionary containing the file paths """ env = {} for k, v in os.environ.items(): if k in ['LXDUI_LOG', 'LXDUI_CONF']: env.update({k: os.environ.get(k)}) return env @staticmethod def envGet2(key): """ Retrieve the environment variables containing the log and conf paths. :return: Returns a dictionary containing the file paths """ env = {} for k, v in os.environ.items(): if key == k: env.update({k: os.environ.get(k)}) return env def envSet(self, **kwargs): """ Set the environment variables for the log and the conf file :param kwargs: Specify log=<log_path> and cong=<conf_path> :return: """ log_path = None conf_path = None if kwargs.get('log') and kwargs.get('conf'): log_path = kwargs.get('log') conf_path = kwargs.get('conf') log.debug('Setting environment variables') else: log_path = self.log_file conf_path = self.config_file os.environ['{}_LOG'.format(APP)] = log_path os.environ['{}_CONF'.format(APP)] = conf_path def envShow(self): if not self.envGet(): print('Environment variables for {} have not been set'.format(APP)) else: for k, v in self.envGet().items(): print('{} = {}'.format(k, v)) def getConfig(self, file): """ Checks to ensure that the file exists Retrieves the contents of the config file. :param file: A string representing the path to the conf file. :return: Returns a config object. """ # if the file exists then read the contents if Path(file).exists(): try: config = self.parseConfig(file) return config except IOError as e: log.info('Unable to open file.', e) else: raise FileNotFoundError @staticmethod def parseConfig(file): """ Parses the config file. The file must be of ini format. If the file exists but is empty and exception will be generated. :param file: The path of the file to parse :return: Return a config object """ # make sure the file is not empty size = Path(file).stat().st_size if size != 0: config = ConfigParser(interpolation=ExtendedInterpolation()) config.read(file.__str__()) return config else: raise Exception('File is empty.')